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["Johansson A.C.; Zhu Z.","Johansson, Anders C. (36871011000); Zhu, Zhen (56643462200)","36871011000; 56643462200","Reputational assets and social media marketing activeness: Empirical insights from China",2023.0,"Electronic Commerce Research and Applications",61.0,null,101305.0,null,null,null,0.0,"10.1016/j.elerap.2023.101305","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85170096531&doi=10.1016%2fj.elerap.2023.101305&partnerID=40&md5=f0afa4ad349491c91c40e9d38aa98a23","Stockholm School of Economics, Sweden; University of Kent, United Kingdom","Johansson A.C., Stockholm School of Economics, Sweden; Zhu Z., University of Kent, United Kingdom","We explore the linkages between social media marketing activeness and reputational assets on digital platforms with a unique sample of over 8,000 customer-to-customer (C2C) sellers registered on both Taobao, China's largest C2C online shopping platform, and Sina Weibo, China's largest microblogging platform. A unique collaborative effort between the two platforms enables us to examine whether C2C sellers are motivated to engage in marketing activities on a separate social media platform. Applying machine learning methods, we first classify whether C2C sellers conduct social media marketing on their microblogs or not, which allows the measurement of social media marketing activeness. We then use logistic regression models and find that earned reputational assets such as the rating scores and the number of followers are significantly associated with social media marketing activeness on both platforms. However, we identify a conflict of owned reputational assets such as the shop age and the paid membership between the two platforms, which provides a potential explanation for the limited success of the cross-platform collaboration. © 2023 The Author(s)","China; Electronic commerce; Reputational assets; Social media marketing","Learning systems; Marketing; Social networking (online); China; Digital platforms; Machine learning methods; Marketing activities; Micro-blogging platforms; Online shopping; Reputational asset; Sina-weibo; Social media marketings; Social media platforms; Electronic commerce",{"$nulls":6},"Abed S.S., Social commerce adoption using TOE framework: An empirical investigation of Saudi Arabian SMEs, Int. J. Inf. Manage., 53, (2020); Ali Abbasi G., bdul Rahim N.F., Wu H., Iranmanesh M., Keong B.N.C., (2022); Appel G., Grewal L., Hadi R., Stephen A.T., The future of social media marketing, J. Acad. Market. 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Sci., 32, 3, pp. 368-392, (2013); Vock M., Dolen W.V., Ruyter K.D., Understanding willingness to pay for social network sites, J. Serv. Res., 16, 3, pp. 311-325, (2013); Wang X., Baesens B., Zhu Z., On the optimal marketing aggressiveness level of C2C sellers in social media: Evidence from China, Omega, 85, pp. 83-93, (2019); Wang Z., Li H., Ye Q., Law R., Saliency effects of online reviews embedded in the description on sales: Moderating role of reputation, Decis. Support Syst., 87, pp. 50-58, (2016); (2019); Yang J., Hu X., Zhang H., Effects of a reputation feedback system on an online consumer-to-consumer auction market, Decis. Support Syst., 44, 1, pp. 93-105, (2007); Ye Q., Li Y., Kiang M., Wu W., The Impact of Seller Reputation on the Performance of online sales: evidence from TaoBao buy-it-now (BIN) data, ACM SIGMIS Database: the DATABASE for Advances in Information Systems, 40, 1, pp. 12-19, (2009); Yoon H.S., Occena L.G., Influencing factors of trust in consumer-to-consumer electronic commerce with gender and age, Int. J. Inf. Manage., 35, 3, pp. 352-363, (2015); Yu H., Cui L., China's E-Commerce: Empowering Rural Women?, China Q., 238, pp. 1-20, (2019); Zolkepli I.A., Kamarulzaman Y., Social media adoption: The role of media needs and innovation characteristics, Comput. Hum. Behav., 43, pp. 189-209, (2015)","Z. Zhu; University of Kent, United Kingdom; email: z.zhu@kent.ac.uk",null,"Elsevier B.V.",{"$nulls":5},1.5674223E7,null,null,null,"English","Elect. Commer. Res. Appl.","Article","Final","All Open Access; Green Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85170096531"]
["Moslem S.; Pilla F.","Moslem, Sarbast (57203017976); Pilla, Francesco (54411156200)","57203017976; 54411156200","A hybrid decision making support method for parcel lockers location selection",2023.0,"Research in Transportation Economics",100.0,null,101320.0,null,null,null,8.0,"10.1016/j.retrec.2023.101320","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85163380647&doi=10.1016%2fj.retrec.2023.101320&partnerID=40&md5=72b0b1973d97312ee29c0d5eabf078d9","School of Architecture Planning and Environmental Policy, University College Dublin, Belfield, Dublin, D04 V1W8, Ireland","Moslem S., School of Architecture Planning and Environmental Policy, University College Dublin, Belfield, Dublin, D04 V1W8, Ireland; Pilla F., School of Architecture Planning and Environmental Policy, University College Dublin, Belfield, Dublin, D04 V1W8, Ireland","Due to the rise of e-commerce, there has been a significant increase in commercial transactions, playing a crucial role in driving economic growth. However, the delivery systems need help locating addresses and dealing with issues such as missed deliveries and exacerbating problems in last-mile logistics, such as traffic congestion and environmental impact. Parcel lockers offer an efficient solution to address these critical issues, but selecting an appropriate location is vital to ensure optimal service and improve overall logistic performance. For this motive, our work aims to define the best location for parcel lockers in Ireland, Dublin, using the Spherical Fuzzy Analytic Hierarchy Process (SFAHP). Spherical Fuzzy Sets (SFS) involve decision-makers hesitating in evaluating location selection. The integrated model is a suitable approach to avoid AHP deterministic disadvantages. Moreover, it is the first application of SFAHP to select parcel locker locations. The obtained results will benefit policymakers in making their strategic decisions on selecting parcel locker locations. © 2023","Analytic hierarchy process; Location problem; Multi-criteria decision making; Parcel locker's location; Parcel lockers; Urban logistics",{"$nulls":5},"European Commission, EC, (H2020MG-2018-2020); Royal Irish Academy, RIA, (861,540)","This article was partially funded by the European Commission through the SENATOR project (H2020MG-2018-2020, RIA , project n. 861,540). ","Apostolou B., Hassell J.M., An empirical examination of the sensitivity of the analytic hierarchy process to departures from recommended consistency ratios, Mathematical and Computer Modelling, 17, 4-5, pp. 163-170, (1993); Bengtsson C., Vikingson A., Exploring and evaluating the parcel locker–A Swedish consumer perspective, (2015); Browne M., Allen J., Nemoto T., Patier D., Visser J., Reducing social and environmental impacts of urban freight transport: A review of some major cities, Procedia Soc. Behav. Sci., 39, pp. 19-33, (2012); Celikbilek Y., Moslem S., A grey multi-criteria decision-making application for analysing the essential reasons for a recurrent lane change, (2023); Dos Santos P.H., Neves S.M., Sant'Anna D.O., de Oliveira C.H., Carvalho H.D., The analytic hierarchy process supporting decision making for sustainable development: An overview of applications, Journal of Cleaner Production, 212, pp. 119-138, (2019); Emec U., Catay B., Bozkaya B., An adaptive large neighborhood search for an E-grocery delivery routing problem, Computers & Operations Research, 69, pp. 109-125, (2016); Ghaderi H., Zhang L., Tsai P.W., Woo J., Crowdsourced last-mile delivery with parcel lockers, International Journal of Production Economics, 251, (2022); Guler D., Yomralioglu T., Suitable location selection for the electric vehicle fast charging station with AHP and fuzzy AHP methods using GIS, Annals of GIS, 26, 2, pp. 169-189, (2020); Iwan S., Kijewska K., Lemke J., Analysis of parcel lockers' efficiency as the last mile delivery solution–the results of the research in Poland, Transportation Research Procedia, 12, pp. 644-655, (2016); Keeling K.L., Schaefer J.S., Figliozzi M.A., Accessibility and equity analysis of transit facility sites for common carrier parcel lockers, Transportation Research Record, 2675, 12, pp. 1075-1087, (2021); Kilibarda M., Andrejic M., Popovic V., Research in logistics service quality: A systematic literature review, Transport, 35, 2, pp. 224-235, (2020); Kutlu Gundogdu F., Kahraman C., Spherical fuzzy sets and spherical fuzzy TOPSIS method, Journal of Intelligent and Fuzzy Systems, 36, 1, pp. 337-352, (2019); Lachapelle U., Burke M., Brotherton A., Leung A., Parcel locker systems in a car dominant city: Location, characterisation and potential impacts on city planning and consumer travel access, Journal of Transport Geography, 71, pp. 1-14, (2018); Lagorio A., Pinto R., The parcel locker location issues: An overview of factors affecting their location, pp. 414-421, (2020); Lee H., Chen M., Pham H.T., Choo S., Development of a decision-making system for installing unmanned parcel lockers: Focusing on residential complexes in Korea, KSCE Journal of Civil Engineering, 23, 6, pp. 2713-2722, (2019); Lemke J., Iwan S., Korczak J., Usability of the parcel lockers from the customer perspective–the research in Polish Cities, Transportation Research Procedia, 16, pp. 272-287, (2016); Morganti E., Seidel S., Blanquart C., Dablanc L., Lenz B., The impact of e-commerce on final deliveries: Alternative parcel delivery services in France and Germany, Transportation Research Procedia, 4, pp. 178-190, (2014); Moslem S., A novel parsimonious best worst method for evaluating travel mode choice, IEEE Access, 11, pp. 16768-16773, (2023); Moslem S., Farooq D., Jamal A., Almarhabi Y., Almoshaogeh M., Butt F.M., Tufail R.F., An integrated fuzzy analytic hierarchy process (AHP) model for studying significant factors associated with frequent lane changing, Entropy, 24, 3, (2022); Moslem S., Saraji M.K., Mardani A., Alkharabsheh A., Duleba S., Esztergar-Kiss D., A systematic review of analytic hierarchy process applications to solve transportation problems: From 2003 to 2019, IEEE Access, 11, pp. 11973-11990, (2023); Moslem S., Stevic Z., Tanackov I., Pilla F., Sustainable development solutions of public transportation: An integrated IMF SWARA and Fuzzy Bonferroni operator, Sustainable Cities and Society, 93, (2023); Nassi C.D., da Costa F.C.D.C., Use of the analytic hierarchy process to evaluate the transit fare system, Research in Transportation Economics, 36, 1, pp. 50-62, (2012); Oliveira L.K.D., Oliveira R.L.M.D., Sousa L.T.M.D., Caliari I.D.P., Nascimento C.D.O.L., Analysis of accessibility from collection and delivery points: Towards the sustainability of the e-commerce delivery, urbe. Revista Brasileira de Gestão Urbana, 11, (2019); Pan S., Zhang L., Thompson R.G., Ghaderi H., A parcel network flow approach for joint delivery networks using parcel lockers, International Journal of Production Research, 59, 7, pp. 2090-2115, (2021); Rajak M., Shaw K., Evaluation and selection of mobile health (mHealth) applications using AHP and fuzzy TOPSIS, Technology in Society, 59, (2019); Saaty T.L., A scaling method for priorities in hierarchical structures, Journal of Mathematical Psychology, 15, 3, pp. 234-281, (1977); Schaefer J.S., Figliozzi M.A., Spatial accessibility and equity analysis of Amazon parcel lockers facilities, Journal of Transport Geography, 97, (2021); Tang Y.M., Chau K.Y., Xu D., Liu X., Consumer perceptions to support IoT-based smart parcel locker logistics in China, Journal of Retailing and Consumer Services, 62, (2021); Van Asch T., Dewulf W., Kupfer F., Cardenas I., Van de Voorde E., Cross-border e-commerce logistics–Strategic success factors for airports, Research in Transportation Economics, 79, (2020); Vargas L.G., An overview of the analytic hierarchy process and its applications, European Journal of Operational Research, 48, 1, pp. 2-8, (1990); Yang G., Huang Y., Fu Y., Huang B., Sheng S., Mao L., Yin Q., Parcel locker location based on a bilevel programming model, Mathematical Problems in Engineering, 2020, (2020)","S. Moslem; School of Architecture Planning and Environmental Policy, University College Dublin, Dublin, Belfield, D04 V1W8, Ireland; email: sarbast.moslem@ucd.ie",null,"Emerald Publishing",{"$nulls":5},7398859.0,null,null,null,"English","Res. Transp. Econ.","Article","Final",null,"Scopus","2-s2.0-85163380647"]
["Munshi A.; Alhindi A.; Qadah T.M.; Alqurashi A.","Munshi, Amr (56428688000); Alhindi, Ahmad (55632703100); Qadah, Thamir M. (57034058200); Alqurashi, Amjad (58648675000)","56428688000; 55632703100; 57034058200; 58648675000","An Electronic Commerce Big Data Analytics Architecture and Platform",2023.0,"Applied Sciences (Switzerland)",13.0,19.0,10962.0,null,null,null,0.0,"10.3390/app131910962","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174211670&doi=10.3390%2fapp131910962&partnerID=40&md5=6f531952add75a17f35bde1eabe1013f","College of Computer and Information Systems, Umm Al-Qura University, Makkah, 21955, Saudi Arabia; Salla Research and Innovation, Makkah, 24225, Saudi Arabia","Munshi A., College of Computer and Information Systems, Umm Al-Qura University, Makkah, 21955, Saudi Arabia; Alhindi A., College of Computer and Information Systems, Umm Al-Qura University, Makkah, 21955, Saudi Arabia; Qadah T.M., College of Computer and Information Systems, Umm Al-Qura University, Makkah, 21955, Saudi Arabia; Alqurashi A., Salla Research and Innovation, Makkah, 24225, Saudi Arabia","The COVID-19 pandemic significantly increased e-commerce growth, adding more than 218 billion US dollars to the United States e-commerce sales. With this significant growth, various operational challenges have appeared, including logistic difficulties and customer satisfaction. Businesses that strive to take advantage of increased e-commerce growth must understand data and rely on e-commerce analytics. The large scale of e-commerce data requires sophisticated information technology techniques and cyber-infrastructure to leverage and analyze. This study presents a big e-commerce data platform to address several challenges in e-commerce. The presented platform’s design is based on a distributed system architecture that supports e-commerce analytics applications using historical and real-time data and features a continuous feedback loop to observe the decision-making and evaluation processes to achieve the desired objectives. The platform was validated using two analytical applications. The first application was to identify the periods in which customers prefer to place orders, while the second was used to verify the big e-commerce data platform. The resulting insights and findings promote informed e-commerce decisions. Furthermore, viewing and acting on insight results and findings promote informed decisions that potentially benefit the e-commerce industry. The proposed platform can perform numerous e-commerce applications that potentially benefit the e-commerce industry. © 2023 by the authors.","big data; data lake; data warehouse; e-commerce",{"$nulls":5},"Salla Research & Innovation Centre, (SRI222)","This research was funded by Salla Research & Innovation Centre, Makkah, grant number [SRI222].","Duffin A., The State of the Digital Commerce, (2021); von Abrams K., Global Ecommerce Forecast 2021: Digital Leads the Way, Building on 2020’s Growth, (2021); Akter S., Fosso Wamba S., Big data analytics in e-commerce: A systematic review and agenda for future research, Electron. Mark, 26, pp. 173-194, (2016); Arya K., Kumar T., Jain M.K., Big data analytics of global e-commerce organisations: A study, survey and analysis, Int. J. Sci. Eng. Res, 7, pp. 82-84, (2016); Pavithra B., Niranjanmurthy M., Shaker J.K., Mani M.S., The study of big data analytics in e-commerce, Int. J. Adv. Res. Comput. Commun. Eng, 5, pp. 126-131, (2016); Vinodhini M., Appukuttan M., A survey on big data analytics in e-commerce, IJEST ISSN, 1, pp. 61-64, (2016); Hadwan M., Social commerce in saudi arabia: Literature review, Int. J. Eng. Res. Technol, 12, pp. 3018-3026, (2019); Mikalef P., Pappas I., Krogstie J., Giannakos M., Big data analytics capabilities: A systematic literature review and research agenda, Inf. Syst. Bus. Manag, 16, pp. 547-578, (2018); Alrumiah S., Hadwan M., Implementing big data analytics in e-commerce: Vendor and customer view, IEEE Access, 9, pp. 37281-37286, (2021); Zhuang W., The influence of big data analytics on e-commerce: Case study of the U.S. and China, Wirel. Commun. Mob. Comput, 2021, (2021); Weiqing Z., Wang M.C., Nakamoto I., Jiang M., Big Data Analytics in E-commerce for the U.S. and China Through Literature Reviewing, J. Syst. Sci. Inf, 9, pp. 16-44, (2021); Panwar M., Wadhwa A., Pippal S., An overview: Exploratory data analytics on e-commerce dataset, Proceedings of the 2021 3rd International Conference on Advances in Computing, Communication Control and Networking (ICAC3N), pp. 91-93; Mohamed M., El-Henawy I., Salah A., Price prediction of seasonal items using machine learning and statistical methods, Comput. Mater. Contin, 70, pp. 3473-3489, (2022); Vapiwala F., Pandita D., Analyzing the Application of Artificial Intelligence for E-Commerce Customer Engagement, Proceedings of the 2022 International Conference on Data Analytics for Business and Industry (ICDABI), pp. 423-427; Yu J., Wen Y., Yang L., Zhao Z., Guo Y., Guo X., Monitoring on Triboelectric Nanogenerator and Deep Learning Method, Nano Energy, 92, (2022); Salamai A., Ageeli A., El-kenawy E.-S., Forecasting e-commerce adoption based on bidirectional recurrent neural networks, Comput. Mater. Contin, 70, pp. 5091-5106, (2022); Luo Y., Xu S., Xie C., E-commerce big data classification and mining algorithm based on artificial intelligence, Proceedings of the 2022 IEEE 2nd International Conference on Electronic Technology, Communication and Information (ICETCI), pp. 1153-1155; Yu R., Wu C., Yan B., Yu B., Zhou X., Yu Y., Chen N., Analysis of the impact of big data on e-commerce in cloud computing environment, Complexity, 2021, (2021); Desai P., Ganatra K., Artificial Intelligence In Strengthening The Operations Of Ecommerce Based Business, Proceedings of the 2022 Interdisciplinary Research in Technology and Management (IRTM), pp. 1-7; Marz N., Warren J., Big Data: Principles and Best Practices of Scalable Real-Time Data Systems, Manning, (2015); Munshi A., Mohamed Y., Data lake lambda architecture for smart grids big data analytics, IEEE Access, 6, pp. 40463-40471, (2018); Armbrust M., Reynold S.X., Cheng L., Yin H., Davies L., Bradley J.K., Meng X., Spark sql: Relational data processing in spark, Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 1383-1394; Apache Flume and Apache Sqoop Data Ingestion to Apache Hadoop Clusters on VMware vSphere, (2013); Cloudera, Palo Alto, CA, USA, (2016); Tall Arrays; Meng X., Bradley J., Yavuz B., Sparks E., Venkataraman S., Liu D., Freeman J., Tsai D.B., Amde M., Owen S., Et al., MLlib: Machine learning in apache spark, J. Mach. Learn. Res, 17, pp. 1235-1241, (2016); Tableau; Vavilapalli V.K., Murthy A.C., Douglas C., Agarwal S., Konar M., Evans R., Graves T., Lowe J., Shah H., Seth S., Apache hadoop YARN: Yet another resource negotiator, Proceedings of the 4th Annual Symposium on Cloud Computing, SoCC; Cheng Y., Liu F., Jing S., Xu W., Chau D., Building Big Data Processing and Visualization Pipeline through Apache Zeppelin, Proceedings of the Practice and Experience on Advanced Research Computing, pp. 1-7; Taylor S., Letham B., Forecasting at scale, PeerJ, 9, pp. 2167-9843, (2017)","T.M. Qadah; College of Computer and Information Systems, Umm Al-Qura University, Makkah, 21955, Saudi Arabia; email: tmqadah@uqu.edu.sa",null,"Multidisciplinary Digital Publishing Institute (MDPI)",{"$nulls":5},2.0763417E7,null,null,null,"English","Appl. Sci.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85174211670"]
["Zhuang X.; Gao Z.; Zhang Y.; Zhang Q.; Wu S.","Zhuang, Xiaotian (57722824700); Gao, Zhenyu (58409588800); Zhang, Yuli (7601314406); Zhang, Qian (58606886500); Wu, Shengnan (57211021028)","57722824700; 58409588800; 7601314406; 58606886500; 57211021028","Stochastic Joint Replenishment Optimization under Joint Inbound Operational Cost",2023.0,"Journal of Systems Science and Systems Engineering",32.0,5.0,null,531.0,552.0,21.0,0.0,"10.1007/s11518-023-5567-7","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85163645139&doi=10.1007%2fs11518-023-5567-7&partnerID=40&md5=b2689ef1b354ca744fe3fd92422f6f19","Department of Intelligent Supply Chain, JD Logistics, Beijing, 100076, China; School of Management and Economics, Beijing Institute of Technology, Beijing, 100081, China; Yangtze Delta Region Academy of Beijing Institute of Technology, Zhejiang, Jiaxing, 314019, China","Zhuang X., Department of Intelligent Supply Chain, JD Logistics, Beijing, 100076, China; Gao Z., Department of Intelligent Supply Chain, JD Logistics, Beijing, 100076, China; Zhang Y., School of Management and Economics, Beijing Institute of Technology, Beijing, 100081, China, Yangtze Delta Region Academy of Beijing Institute of Technology, Zhejiang, Jiaxing, 314019, China; Zhang Q., School of Management and Economics, Beijing Institute of Technology, Beijing, 100081, China; Wu S., Department of Intelligent Supply Chain, JD Logistics, Beijing, 100076, China","With e-commerce concentrating retailers and customers onto one platform, logistics companies (e.g., JD Logistics) have launched integrated supply chain solutions for corporate customers (e.g., online retailers) with warehousing, transportation, last-mile delivery, and other value-added services. The platform’s concentration of business flows leads to the consolidation of logistics resources, which allows us to coordinate supply chain operations across different corporate customers. This paper studies the stochastic joint replenishment problem of coordinating multiple suppliers and multiple products to gain the economies of scale of the replenishment setup cost and the warehouse inbound operational cost. To this end, we develop stochastic joint replenishment models based on the general-integer policy (SJRM-GIP) for the multi-supplier and multi-product problems and further reformulate the resulted nonlinear optimization models into equivalent mixed integer second-order conic programs (MISOCPs) when the inbound operational cost takes the square-root form. Then, we propose generalized Benders decomposition (GBD) algorithms to solve the MISOCPs by exploiting the Lagrangian duality, convexity, and submodularity of the sub-problems. To reduce the computational burden of the SJRM-GIP, we further propose an SJRM based on the power-of-two policy and extend the proposed GBD algorithms. Extensive numerical experiments based on practical datasets show that the stochastic joint replenishment across multiple suppliers and multiple products would deliver 13∼20% cost savings compared to the independent replenishment benchmark, and on average the proposed GBD algorithm based on the enhanced gradient cut can achieve more than 90% computational time reduction for large-size problem instances compared to the Gurobi solver. The power-of-two policy is capable of providing high-quality solutions with high computational efficiency. © 2023, Systems Engineering Society of China and Springer-Verlag GmbH Germany.","benders decomposition; inbound warehouse cost; power-of-two policy; stochastic demand; Stochastic joint replenishment","Computational efficiency; Integer programming; Nonlinear programming; Sales; Stochastic models; Stochastic programming; Stochastic systems; Supply chains; Warehouses; Benders decomposition algorithm; Benders' decompositions; Generalized benders decompositions; Inbound warehouse cost; Joint replenishment; Power-of-two policies; Stochastic joint replenishment; Stochastic-demand; Stochastics; Warehouse costs; Costs",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (2022ZD0115403, 71871023, 72061127001, 72201121, 72271029)","This work has been supported by the National Natural Science Foundation of China under Grant numbers 72271029, 71871023, 72061127001, and 72201121, and National Science and Technology Innovation 2030 Major program under Grant 2022ZD0115403. The referees are greatly appreciated for their help to improve the quality of the extended paper. 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Bastos L.S.L., Mendes M.L., Nunes D.R.L., Melo A.C.S., Carneiro M.P., A systematic literature review on the joint replenishment problem solutions: 2006–2015, Production, (2017); Bayindir Z.P., Birbil S., Frenk J., The joint replenishment problem with variable production costs, European Journal of Operational Research, 175, 1, pp. 622-640, (2006); Braglia M., Castellano D., Gallo M., An extension of the stochastic joint replenishment problem under the class of cyclic policies, Operations Research Letters, 44, 2, pp. 278-284, (2016); Cai L., Chen J., Yan H., Single-period two-product inventory model with substitution: Solution and properties, Journal of Systems Science and Systems Engineering, 13, 1, pp. 112-123, (2004); Cheung M., Elmachtoub A., Levi R., Shmoys D., The submodular joint replenishment problem, Mathematical Programming, 158, 1, pp. 207-233, (2016); Creemers S., Boute R., The joint replenishment problem: Optimal policy and exact evaluation method, European Journal of Operational Research, 302, 3, pp. 1175-1188, (2022); 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Goyal S., Determination of optimum packaging frequency of items jointly replenished, Management Science, 21, 4, pp. 436-443, (1974); Goyal S., Belton A.S., Note on a simple method of determining order quantities in joint replenishments under deterministic demand, Management Science, 25, 6, pp. 604-605, (1979); Goyal S., Deshmukh S., Discussion a note on ‘the economic ordering quantity for jointly replenishing items’, International Journal of Production Research, 31, 12, pp. 2959-2961, (1993); Hariga M., Two new heuristic procedures for the joint replenishment problem, Journal of the Operational Research Society, 45, 4, pp. 463-471, (1994); Jackson P., Maxwell W., Muckstadt J., The joint replenishment problem with a powers-of-two restriction, IIE Transactions, 17, 1, pp. 25-32, (1985); Kaspi M., Rosenblatt M., An improvement of Silver’s algorithm for the joint replenishment problem, AIIE Transactions, 15, 3, pp. 264-267, (1983); Kaspi M., Rosenblatt M., On the economic ordering quantity for jointly replenished items, The International Journal of Production Research, 29, 1, pp. 107-114, (1991); 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Roundy R., 98%-effective integer-ratio lot-sizing for one-warehouse multi-retailer systems, Management Science, 31, 11, pp. 1416-1430, (1985); Shu F., Economic ordering frequency for two items jointly replenished, Management Science, 17, 6, pp. 406-407, (1971); Silver E.A., Some characteristics of a special joint-order inventory model, Operations Research, 13, 2, pp. 319-322, (1965); Silver E.A., Three ways of obtaining the average cost expression in a problem related to joint replenishment inventory control, Naval Research Logistics Quarterly, 20, 2, pp. 241-254, (1973); Silver E.A., A control system for coordinated inventory replenishment, International Journal of Production Research, 12, 6, pp. 647-671, (1974); Silver E.A., A simple method of determining order quantities in joint replenishments under deterministic demand, Management Science, 22, 12, pp. 1351-1361, (1976); Silver E.A., Establishing reorder points in the (s, c, s) coordinated control system under compound poisson demand, International Journal of Production Research, 19, 6, pp. 743-750, (1981); Singh R., Mishra V.K., Sustainable integrated inventory model for substitutable deteriorating items considering both transport and industry carbon emissions, Journal of Systems Science and Systems Engineering, 31, 3, pp. 267-287, (2022); Snyder L.V., Shen Z.J.M., Fundamentals of Supply Chain Theory, (2019); van Eijs M., Heuts R.M.J., Kleijnen J.P.C., Analysis and comparison of two strategies for multi-item inventory systems with joint replenishment costs, European Journal of Operational Research, 59, 3, pp. 405-412, (1992); Viswanathan S., A new optimal algorithm for the joint replenishment problem, Journal of the Operational Research Society, 47, 7, pp. 936-944, (1996); Viswanathan S., Note. Periodic review (s, S) policies for joint replenishment inventory systems, Management Science, 43, 10, pp. 1447-1454, (1997); Wang L., Dun C.X., Bi W.J., Zeng Y.R., An effective and efficient differential evolution algorithm for the integrated stochastic joint replenishment and delivery model, Knowledge Based Systems, 36, pp. 104-114, (2012); Youssef M.A., Mahmoud M.M., An iterative procedure for solving the uncapacitated production-distribution problem under concave cost function, International Journal of Operations & Production Management, 16, 3, pp. 18-27, (1996); Zheng Y.S., Federgruen A., Finding optimal (s, S) policies is about as simple as evaluating a single policy, Operations Research, 39, 4, pp. 654-665, (1991); Zhong J., Chu F., Chu C., Yang S., Polynomial dynamic programming algorithms for lot sizing models with bounded inventory and stockout and/or backlogging, Journal of Systems Science and Systems Engineering, 25, 3, pp. 370-397, (2016)","Y. Zhang; School of Management and Economics, Beijing Institute of Technology, Beijing, 100081, China; email: zhangyuli@bit.edu.cn",null,"Systems Engineering Society of China",{"$nulls":5},1.0043756E7,null,null,null,"English","J. Syst. Sci. Syst. Eng.","Article","Final",null,"Scopus","2-s2.0-85163645139"]
["Pelet J.-E.; Taieb B.; Alkhudary R.","Pelet, Jean-Eric (25927450000); Taieb, Basma (57191995186); Alkhudary, Rami (57217734054)","25927450000; 57191995186; 57217734054","Measuring consumer perceptions of home-delivery convenience – the case of cargo bikes",2023.0,"International Journal of Retail and Distribution Management",51.0,"2024-10-09",null,1371.0,1387.0,16.0,0.0,"10.1108/IJRDM-11-2022-0483","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85159345463&doi=10.1108%2fIJRDM-11-2022-0483&partnerID=40&md5=1c97ee1b510ffe5849bb80c322af9211","Department of Marketing, Université Paris Panthéon-Assas, Paris, France; Department of Digital Marketing, Pole Universitaire Leonard de Vinci, Paris, France; LARGEPA, Université Paris-Panthéon-Assas, Paris, France","Pelet J.-E., Department of Marketing, Université Paris Panthéon-Assas, Paris, France; Taieb B., Department of Digital Marketing, Pole Universitaire Leonard de Vinci, Paris, France; Alkhudary R., LARGEPA, Université Paris-Panthéon-Assas, Paris, France","Purpose: Despite the increasing use of home delivery (HD) in e-commerce, no studies have explicitly examined consumer perceptions of the convenience of the last-mile delivery of goods by cargo bike (CB). Therefore, this study aims to identify the dimensions of HD convenience and to develop a reliable and valid measurement tool, namely the Home-Delivery Convenience via Cargo Bike (HDCCB) scale. Design/methodology/approach: The methodology of this scale development study is premised on a review of the existing literature, which identifies differences in consumer perceptions of the convenience of services. The authors conducted semi-structured interviews with 10 online consumers and validated the content with 3 experts on marketing in the retail and services sectors in order to develop the items for the scale. Thereafter, the authors identified the main dimensions through an exploratory factor analysis that the authors applied to an online survey with 116 respondents. Finally, the scale was validated through a confirmatory factor analysis of an online survey with 300 respondents. Findings: Following the original work of Brown (1990), the authors define consumer perceptions of HD convenience as a multidimensional construct and measure each facet of its four dimensions, which are time, use, execution and acquisition. E-retailers and last-mile logistics providers could use the authors' proposed measurement tool to assess consumer perceptions of the convenience of HD. That assessment could generate a competitive advantage. Originality/value: This study is original as the study deepens the existing understanding of consumer perceptions of the convenience of HD by CB in last-mile logistics. This study also develops a multidimensional measure that is based on an empirical study. © 2023, Emerald Publishing Limited.","Cargo bike; Consumer perceptions; e-commerce; HDCCB; Home delivery; Home-delivery convenience; Last-mile logistics; Service convenience",{"$nulls":7},{"$cut":{"chars":17230,"head":"Ageron B., Marty J., Connecting the customer to the supply chain : proposition of a conceptual framework, European Journal of International Management, 1, 1, (2022); Amasiatu C.V., Shah M.H., The management of first party fraud in e-tailing: a qualitative study, International Journal of Retail and Distribution Management, 47, 4, pp. 433-452, (2019); Anosike A., Loomes H., Udokporo C.K., Garza-Reyes J.A., Exploring the challenges of electric vehicle adoption in final mile parcel delivery, International Journal of Logistics Research and Applications, 1-25, (2021); Asiah Omar N., Musa R., Measuring service quality in retail loyalty programmes (LPSQual): implications for retailers' retention strategies, International Journal of Retail and Distribution Management, 39, 10, pp. 759-784, (2011); Bagdare S., Jain R., Measuring retail customer experience, International Journal of Retail and Distribution Management, 41, 10, pp. 790-804, (2013); Bagozzi R.P., Yi Y., On the evaluation of structural equation models, Journal of the Academy of Marketing Science, 16, 1, pp. 74-94, (1988); Beauchamp M.B., Ponder N., Perceptions of retail convenience for in-store and online shoppers, Marketing Management Journal, 20, 1, pp. 49-65, (2010); Bergadaa M.M., The role of time in the action of the consumer, Journal of Consumer Research, 17, 3, (1990); Berry L.L., Seiders K., Grewal D., Understanding service convenience, Journal of Marketing, 66, 3, pp. 1-17, (2002); Bhatt G., Sarkar A., Sarkar J.G., Attractive and facilitating store atmospheric stimuli : validating the scales, International Journal of Retail and Distribution Management, 48, 4, pp. 363-379, (2020); Bhuyan A., Tripathy A., Padhy R.K., Gautam A., Evaluating the lithium-ion battery recycling industry in an emerging economy : a multi-stakeholder and multi-criteria decision-making approach, Journal of Cleaner Production, 331, (2022); Brown L.G., The strategic and tactical implications of convenience in consumer product marketing, Journal of Consumer Marketing, 6, 3, pp. 13-19, (1989); Brown L.G., Convenience in services marketing, Journal of Services Marketing, 4, 1, pp. 53-59, (1990); Browne M., Allen J., Leonardi J., Evaluating the use of an urban consolidation centre and electric vehicles in central London, IATSS Research, 35, 1, pp. 1-6, (2011); Buldeo Rai H., Verlinde S., Macharis C., The ‘next day, free delivery’ myth unravelled : possibilities for sustainable last mile transport in an omnichannel environment, International Journal of Retail and Distribution Management, 47, 1, pp. 39-54, (2019); Charmaz K., Constructing Grounded Theory : A Practical Guide through Qualitative Analysis, (2006); Chekembayeva G., Garaus M., Schmidt O., The role of time convenience and (anticipated) emotions in AR mobile retailing application adoption, Journal of Retailing and Consumer Services, 72, (2023); Childs M., Blanchflower T., Hur S., Matthews D., Non-traditional marketplaces in the retail apocalypse: investigating consumers' buying behaviours, International Journal of Retail and Distribution Management, 48, 3, pp. 262-286, (2020); Churchill G.A., A paradigm for developing better measures of marketing constructs, Journal of Marketing Research, 16, 1, pp. 64-73, (1979); Clulow V., Reimers V., How do consumers define retail centre convenience?, Australasian Marketing Journal, 17, 3, pp. 125-132, (2009); Colwell S.R., Aung M., Kanetkar V., Holden A.L., Toward a measure of service convenience : multiple‐item scale development and empirical test, Journal of Services Marketing, 22, 2, pp. 160-169, (2008); Copeland M., Relation of consumers: buying habits to marketing methods, Harvard Business Review, pp. 282-289, (1923); Dai H., Salam A.F., Does service convenience matter? An empirical assessment of service quality, service convenience and exchange relationship in electronic mediated environment, Electronic Markets, 24, 4, pp. 269-284, (2014); Dalla Chiara G., Donnelly G., Gunes S., Goodchild A., How cargo cycle drivers use the urban transport infrastructure, Transportation Research Part A: Policy a"}},"J.-E. Pelet; Department of Marketing, Université Paris Panthéon-Assas, Paris, France; email: jean-eric.pelet@u-paris2.fr",null,"Emerald Publishing",{"$nulls":5},9590552.0,null,null,null,"English","Int. J. Retail Disrtib. Manage.","Article","Final",null,"Scopus","2-s2.0-85159345463"]
["Zhang L.; Tang L.","Zhang, Li (58634739400); Tang, Liang (57198909725)","58634739400; 57198909725","How Much Can TFA Boost Sustainable International Trade? -Evidence from RCEP and China",2023.0,"International Journal of Sustainable Development and Planning",18.0,8.0,null,2331.0,2337.0,6.0,0.0,"10.18280/IJSDP.180803","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85173475696&doi=10.18280%2fIJSDP.180803&partnerID=40&md5=3e765f2e1b2a2c845c13da2c4e4bc242","International College, Krirk University, Maha Nakhon, 10220, Thailand","Zhang L., International College, Krirk University, Maha Nakhon, 10220, Thailand; Tang L., International College, Krirk University, Maha Nakhon, 10220, Thailand","In February 2017, as the first multilateral agreement on trade since the establishment of the WTO, the Trade Facilitation Agreement (TFA) came into effect. Hitherto, however, there is still very little evidence on the factual effect of trade facilitation on promoting international trade. Based on panel data from 2017-2021, using a trade gravity model and the least squares regression analysis, this paper explores the impact of the implementation of the TFA on the import and export values between China and five RCEP countries (Indonesia, Malaysia, Singapore, Thailand, and Vietnam). The results demonstrate that China's trade facilitation level is significantly and positively related to the trade flow of goods. In addition, the population size of RCEP countries is also positively correlated with the trade flows between the two sides. 1 per cent of Trade Facilitation Index (TFI) can increase trade flows by US$10,352.9 million. It is recommended to actively promote the development of trade facilitation, including the formation of RCEP logistics industry alliance, the establishment of one-stop digital customs, the acceleration of Cross-border E-commerce, as well as the reasonable use of blockchain. © 2023 WITPress. All rights reserved.","blockchain; Cross-border E-commerce; RCEP; TFA; trade facilitation; trade gravity model","China; Indonesia; Malaysia; Singapore; Thailand; Viet Nam; electronic commerce; facilitation; free trade; international trade; policy implementation; regional trade; trade policy; trade reform",{"$nulls":6},"Wang J., Wang Q., A study on the trade potential and trade efficiency between China and RCEP partner countries: With measurement based on SFA model, Journal of Soochow University (Philosophy & Social Science Edition), 42, 3, pp. 111-123, (2021); Hillberry R., Zurita-Castro C., Commitment behaviour in the World Trade Organization trade facilitation agreement, The World Economy, 45, 1, pp. 36-75, (2022); Wilson J.S., Mann C.L., Otsuki T., Trade facilitation and economic development: A new approach to quantifying the impact, The World Bank Economic Review, 17, 3, pp. 367-389, (2003); Beberelli C., Ticku R., Reducing tariff evasion: The role of trade facilitation, Journal of Comparative Economics, 50, 2, pp. 534-554, (2022); Laboni I.J., Khatun M.F., Chowdhury N.I., Anto N.J., Rouf O., Driving economic growth: How bangladesh can leverage the WTO trade facilitation agreement, (2023); Research on the development status and problems of China-ASEAN trade facilitation in the context of RCEP, Jiangsu Commercial Forum, 2023, 3, pp. 55-58, (2023); Qi W., Peng X.Y., Xiong H.Y., Impact of trade facilitation level of countries along the \"the Belt and Road\" on import and export trade, Statistics and Decision, 2021, 32, pp. 144-148, (2021); Moise E., Sorescu S., Trade facilitation indicators: The potential impact of trade facilitation on developing countries’ trade, OECD Trade Policy Paper, 2013, pp. 1-7, (2013); Olubandwa B.N., WTO trade facilitation adoption challenges in East African trade region during COVID-19 crisis, Open Access Library Journal, 9, pp. 1-23, (2022); Nga L., Huy D., Hang N., Lan L., Thach N., Reforming specialized inspection procedures to improve business environment in Vietnam for trade facilitation implementation, Management, 25, 1, pp. 234-258, (2019); Mao Y.H., Qiu X.Q., Wang L., Trade facilitation of the belt and road and countries’ participation in global value chain, International Trade, 2023, 1, pp. 11-20, (2023); Yu Y.M., Chen T.W., Zhao K., The development and countermeasures of Cross border E-commerce between China & RCEP: a study based on trade facilitation and single window of international trade, Inquiry into Economic Issues, 2018, 4, pp. 128-136, (2018); Cui X.S., Guo L.F., Li F., Would trade tacilitation promote China's inter-provincial trade by trade creation?-Evidence from the survey on the Chinese trade facilitation, Economics of Finance and Trade, 40, 4, pp. 100-115, (2019); Zhi H., Research on the impact of trade facilitation in countries along “Belt and Road” on China’s exports, Economic Review, 2020, pp. 115-128, (2020); Zhan J.L., The impact of RCEP on reducing the time of Cross-border cargo release, Journal of Beijing Institute of Technology (Social Sciences Edition), 25, 3, pp. 160-171, (2023); Meng Q.L., Wang Y.H., Impact of trade facilitation on complexity of export technology in “the Belt and Road” countries, Journal of South-Central University for Nationalities (Humanities and Social Sciences), 42, 12, pp. 123-133, (2022); Yang J.J., Liu Y.F., Li H.L., Trade facilitation, import of intermediate goods and enterprise export value added, Finance & Trade Economics, 2020, 4, pp. 115-129, (2020); Shi Y.R., Yu J.P., Bi C.H., Trade facilitation and enterprise technology upgrading, International Economics and Trade Research, 38, 7, pp. 72-85, (2022); Ma M.Y., Min S., Zhang X.H., The impact of trade facilitation on export quality of processed agricultural products-an empirical evidence of China and countries (regions) along “the Belt and Road” route, World Agriculture, 525, pp. 30-43, (2023); Yuan K., Impact of trade facilitation on operation performance of Cross-border E-commerce in background of double-cycle -an empirical analysis based on provincial panel data, Journal of Commercial Economics, 2021, 22, pp. 89-92, (2022); Sorescu S., Bollig C., Trade facilitation reforms worldwide: State of play in 2022, (2022); Ismail N.W., Digital trade facilitation and bilateral trade in selected Asian countries, Studies in Economics and Finance, 38, 2, pp. 257-271, (2021); Liu X., Impact of trade facilitation on the development of commerce and distribution enterprises in the context of the double cycle-Intermediation effects of investment in innovation, Journal of Commercial Economics, 2023, 7, pp. 133-136, (2023); Duan W.Q., Jing G.Z., Qi J.H., Trade facilitation and enterprise supply chain security—a perspective of diversification and localization, Journal of International Trade, 2023, 4, pp. 90-106, (2023); Xiao Y., Zhi Y.P., Xie T., The impact of trade facilitation on the export technological complexity of Chinese manufacturing enterprises in countries along the \"Belt and Road\" route, Macroeconomics, 2020, 9, pp. 164-175, (2020); Xie. Q., Liu W.G., Zhang. P.Y., Embedded technology of import intermediate goods and enterprise productivity, Management World, 37, 2, pp. 66-80, (2021); Tinbergen J., Shaping the World Economy; Suggestions for an International Economic Policy, (1962); Li C.P., Research on China's foreign trade efficiency under background of \"Belt and Road\"-based on empirical data from the 19 countries of the new Eurasian Land Bridge, Journal of Technical Economics & Management, 2021, 2, pp. 112-117, (2021); Yang J., Qi C.J., An empirical analysis on the trade potential of export to China from countries along the silk road economic belt-based on TPI and an expanded framework of stochastic frontier gravity model, Journal of International Trade, 2020, 6, pp. 127-142, (2020)","L. Zhang; International College, Krirk University, Maha Nakhon, 10220, Thailand; email: krirkuniversity218@hotmail.com",null,"International Information and Engineering Technology Association",{"$nulls":5},1.7437601E7,null,null,null,"English","Int. J. Sustainable Dev. Plann.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85173475696"]
["Mao H.","Mao, Hehua (58648298200)",5.86482982E10,"Supply and distribution of fresh produce based on the O2O marketing mode",2023.0,"International Journal of COMADEM",26.0,4.0,null,9.0,13.0,4.0,0.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174204981&partnerID=40&md5=8db1a091ee3f44d9554e41ea18781524","Shazhou Professional Institute of Technology, Jiangsu, Zhangjiagang, 215600, China","Mao H., Shazhou Professional Institute of Technology, Jiangsu, Zhangjiagang, 215600, China","Fresh produce has stricter requirements for supply and distribution due to their short preservation period. Investigating the optimal supply and distribution route of fresh produce in the online to offline (O2O) mode can help the advancement of the fresh industry in the e-commerce sector. This paper established a model of the optimal supply and distribution path for fresh produce in the O2O mode and used a genetic algorithm for solution. By contrasting the distribution distance, time, total cost, and satisfaction before and after optimization, the distribution cost-minimizing path solution was obtained. It was found through simulation experiments that the minimum total distribution cost was 357.57 yuan after the computation by the genetic algorithm: the optimized path reduced the total distribution distance by 47.4 kilometers, the time by 0.95 hours, and the cost by 133.75 yuan, and raised the average consumer satisfaction by 0.12. The results further confirm the correctness of the model constructed in the study and the selected algorithm. © 2023 COMADEM International. All rights reserved.","fresh agricultural product; genetic algorithm; logistics distribution; O2O mode; path optimization","Agricultural products; Distribution costs; Distribution route; E- commerces; Fresh agricultural products; Fresh produce; Logistic distributions; O2O mode; Offline; Path optimizations; Preservation period; Genetic algorithms",{"$nulls":6},"Pal A., Kant K., Internet of Perishable Logistics: Building Smart Fresh Food Supply Chain Networks, IEEE Access, 7, pp. 17675-17695, (2019); Zhang H., Xu C., Gong Y., Ai X., Wang X., Sang H., The Research and Analysis on Users’ Evaluation System of Fresh Community Joint Distribution Service, IOP Conference Series: Earth and Environmental Science, 526, 1, pp. 1-6, (2020); Prajapati D., Harish A. R., Daultani Y., Singh H., Pratap S., A Clustering Based Routing Heuristic for Last-Mile Logistics in Fresh Food E-Commerce, Global Business Review, 24, 1, pp. 7-20, (2023); Fan H., Yang X., Li D., Li Y., Liu P., Wu J., Half open multi-depot vehicle routing problem based on joint distribution mode of fresh food, Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS, 25, 1, pp. 256-266, (2019); Li D., Cao Q., Zuo M., Xu F., Optimization of Green Fresh Food Logistics with Heterogeneous Fleet Vehicle Route Problem by Improved Genetic Algorithm, Sustainability, 12, 5, pp. 1-17, (2020); Wang X., He H., Zhang Z., Zhao M., Bi-level Optimization Model of 020 Fresh Product Experience Store Location Considering Service Quality - Science Direct, Procedia Computer Science, 159, pp. 1767-1776, (2019); Wang O., Somogyi S., Charlebois S., Food choice in the e-commerce era: A comparison between Business-To- Consumer (B2C), Online-To-Offline (020) and New Retail, British Food Journal, 122, 4, pp. 1215-1237, (2020); Wang X., Cao W., Research on optimization of distribution route for cold chain logistics cooperative distribution of fresh e-commerce based on price discount, Journal of Physics: Conference Series, 1732, 1, pp. 1-9, (2021); Liu R., Jiang Z., A hybrid large-neighborhood search algorithm for the cumulative capacitated vehicle routing problem with time-window constraints, Applied Soft Computing, 80, 2, pp. 18-30, (2019); Kaswengi J., Lambey-Checchin C., How logistics service quality and product quality matter in the retailer-customer relationship of food drive-throughs: The role of perceived convenience, International Journal of Physical Distribution & Logistics Management, 50, 5, pp. 535-555, (2020); Pan Y., Li S., Chen Q., Zhang N., Cheng T., Li Z., Guo B., Han Q., Zhu T., Efficient Schedule of Energy- Constrained UAV Using Crowdsourced Buses in Last-Mile Parcel Delivery, Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies, 5, 1, pp. 1-23, (2021); Yan B., Liu G., Wu X., Wu J., Decision-Making on the Supply Chain of Fresh Agricultural Products with Two-Period Price and Option Contract, Asia Pacific Journal of Operational Research, 38, 1, pp. 1-22, (2020); Wang M., Wang Y., Liu W., Ma Y., Xiang L., Yang Y., Li X., How to achieve a win-win scenario between cost and customer satisfaction for cold chain logistics?, Physica A: Statistical Mechanics and its Applications, 566, pp. 1-11, (2021); Wang Y., Qiu W., Optimization of the delivery route for community group-purchasing fresh products considering customer satisfaction, IOP Conference Series: Earth and Environmental Science, 619, 1, pp. 1-6, (2020); Zhao Z., Li X., Zhou X., Distribution Route Optimization for Electric Vehicles in Urban Cold Chain Logistics for Fresh Products under Time-Varying Traffic Conditions, Mathematical Problems in Engineering, 2020, pp. 1-17, (2020); Yuan M., Kan X., Chi C., Cao L., Shu H., Fan Y., An adaptive simulated annealing and artificial fish swarm algorithm for the optimization of multi-depot express delivery vehicle routing, Intelligent Data Analysis, 26, 1, pp. 239-256, (2022); Li S., Liu Z., Fang H., Liu L., Vehicle Routing Problem of Fresh Agricultural Products Considering Decaying Factors, IOP Conference Series: Materials Science and Engineering, 688, 4, pp. 1-6, (2019)","H. Mao; Shazhou Professional Institute of Technology, Zhangjiagang, Jiangsu, 215600, China; email: hm4070@163.com",null,"COMADEM International",{"$nulls":5},1.3637681E7,null,null,null,"English","Int. J. COMADEM","Article","Final",null,"Scopus","2-s2.0-85174204981"]
["Li Y.; Mu D.; Li J.","Li, Yufeng (58609637500); Mu, Dan (58609121200); Li, Jingbo (58158226700)","58609637500; 58609121200; 58158226700","RFID-based logistics big data asset evaluation and data mining research",2023.0,"Applied Mathematics and Nonlinear Sciences",8.0,2.0,null,665.0,676.0,11.0,0.0,"10.2478/amns.2021.2.00236","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85171748071&doi=10.2478%2famns.2021.2.00236&partnerID=40&md5=9af53196833db61345d3223cc570693b","College of Finance and Taxation, Jilin Business and Technology College, Jilin, Changchun, 130507, China; Process Quality Department, Jilin GKN Norinco Drive Shaft Co., Ltd, Jilin, Jilin, 132021, China; School of Accounting, College of Humanities Information, Changchun University of Technology, Jilin, Changchun, 130000, China","Li Y., College of Finance and Taxation, Jilin Business and Technology College, Jilin, Changchun, 130507, China; Mu D., Process Quality Department, Jilin GKN Norinco Drive Shaft Co., Ltd, Jilin, Jilin, 132021, China; Li J., School of Accounting, College of Humanities Information, Changchun University of Technology, Jilin, Changchun, 130000, China","With the rapid rise of e-commerce platforms, in view of the sharp increase in the amount of data in the logistics system, the timely update and processing of relevant logistics information data have assumed a particular relevance. In this paper, we fully draw on the excellent performance of radio frequency identification (RFID) technology and data mining technology, begin by using RFID technology to authenticate logistics commodities, move on to extracting relevant feature information and finally carry out a detailed comparison between k-nearest neighbour algorithm, support vector machine (SVM) algorithm, logistic regression (LR) algorithm and improved LR algorithm. The algorithm provides a solution method for asset information collection channel and data mining classification algorithm. It meets the needs of different customers, and provides a variety of working modes, which helps to improve the time and operation efficiency of data processing algorithms. The results show that the SVM algorithm only achieves 93.8% accuracy when iterating 50 times for the classification results of the classification samples containing the objective functions of x1 and x2. The improved LR algorithm stochastic gradient descent algorithm has a classification accuracy of 94.6% after 50 iterations. The RFID-based logistics big data asset evaluation and data mining research identification algorithm has obvious advantages, and the accuracy rate reaches 97.3%. © 2022 Li et al., published by Sciendo.","algorithm; data mining; logistics big data; RFID","Big data; Classification (of information); Data handling; Gradient methods; Nearest neighbor search; Radio frequency identification (RFID); Stochastic systems; Support vector machines; Asset datum; Asset evaluations; Commerce platforms; Data assets; E- commerces; Logistic big data; Logistic regression algorithms; Radio frequency identification technology; Radio-frequency-identification; Support vector machines algorithms; Data mining",{"$nulls":6},"Vavilova V., Construction of a simulation model of management of internal commodity flows of pharmacy networks, Innovative Economy, 2020, 5-6, pp. 89-96; Tarakanov M., Lozova T., Uzun I., Integrated approach to the use of logistics and marketing in the system of commodity markets, Economics Ecology Socium, 4, 3, pp. 12-23, (2020); Buana I., Et al., The logistics system planning for red onion: case study of Sulawesi and Maluku Islands, IOP Conference Series Earth and Environmental Science, 649, 1, (2021); Chen P., A Traceable and Verifiable Tobacco Products Logistics System with GPS and RFID Technologies, Applied Sciences, 2021; Kuteyi D., Winkler H., Logistics Challenges in Sub-Saharan Africa and Opportunities for Digitalization, Sustainability, 2022; Evseev O., Et al., Strategic Forecasting of Multimodal Container Traffic Basing on Transport and Economic Balance of the Russian Federation, Journal of Physics Conference Series, 2021, 1, (1828); Xu Z., Complex event detection for commodity distribution Internet of Things model incorporating radio frequency identification and Wireless Sensor Network, Future Generation Computer Systems, 2021, 7; Subsomboon P., The development of database system for commodity flows and logistics system from Thailand to North Asia (China, Japan, South Korea)/Pattaraporn Subsomboon, Pediatrics International, (2015); Lim H., Et al., Towards timeout-less transport in commodity datacenter networks, EuroSys ‘21: Sixteenth European Conference on Computer Systems; Sun W., Destructive and Constructive Full Duplex Relaying for Commodity RFID System, IEEE Journal of Radio Frequency Identification, 2021, 99; Rejeb A., The Potentialities of RFID – Based Traceability System in the Olives Post – Harvest Stage, (2019); Hua G.Z., The Reorganization of Yiwu Commodity Logistics System under E-commerce, Journal of Jinhua College of Vocation and Technology, (2010); Fang C., Et al., Mapping Relation of Leakage Currents of Polluted Insulators and Discharge Arc Area, Frontiers in Energy Research, 2021; Suresh S., Chakaravarthi G., RFID technology and its diverse applications: A brief exposition with a proposed Machine Learning approach, Measurement, 2022, 195; Ovezmyradov B., Kurata H., Omnichannel fulfillment and item-level RFID tracking in fashion retailing, Computers & Industrial Engineering, 2022, 168; Baghdad A., An improved RFID anti-collision protocol (IMRAP) with low energy consumption and high throughput, Scientific African, 2022, 16; Khorasgani A.A., Sajadieh M., Yazdani M.R., Novel lightweight RFID authentication protocols for inexpensive tags, Journal of Information Security and Applications, 2022, 67; Che H., Wang J., A Two-Timescale Duplex Neurodynamic Approach to Biconvex Optimization, IEEE Transactions on Neural Networks and Learning Systems, 30, 8, pp. 2503-2514, (2019); Leung K.H., Lee C.K.M., Choy K.L., An integrated online pick-to-sort order batching approach for managing frequent arrivals of B2B e-commerce orders under both fixed and variable time-window batching, Advanced Engineering Informatics, 2020, 45; Cen L., Et al., Application of density-based clustering algorithm and capsule network to performance monitoring of antimony flotation process, Minerals Engineering, (2022); Govender P., Sivakumar V., Application of k-means and hierarchical clustering techniques for analysis of air pollution: A review (1980–2019), Atmospheric pollution research, 11, 1, pp. 40-56, (2020); Boysen N., Et al., Automated sortation conveyors: A survey from an operational research perspective, European Journal of Operational Research, 276, 3, pp. 796-815, (2019); Mitroshin P., Et al., Big Data and Data Mining Technologies Application at Road Transport Logistics, Transportation Research Procedia, 2022, 61, pp. 462-466; Ting S.L., Et al., Mining logistics data to assure the quality in a sustainable food supply chain: A case in the red wine industry, International Journal of Production Economics, 152, pp. 200-209, (2014); Does service quality influence operational and financial performance of third party logistics service providers? A mixed multi criteria decision making -text mining-based investigation, Transportation Research Part E: Logistics and Transportation Review, 2022, 157; Hsiao Y., Chen M., Liao W., Logistics service design for cross-border E-commerce using Kansei engineering with text-mining-based online content analysis, Telematics and Informatics, 34, 4, pp. 284-302, (2017); Holzapfel A., Kuhn H., Sternbeck M.G., Product allocation to different types of distribution center in retail logistics networks, European Journal of Operational Research, 264, 3, pp. 948-966, (2018)","Y. Li; College of Finance and Taxation, Jilin Business and Technology College, Changchun, Jilin, 130507, China; email: spw_china@126.com",null,"Sciendo",{"$nulls":5},2.4448656E7,null,null,null,"English","Appl. Math. Nonlinear Sci.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85171748071"]
["Revanna J.K.C.; Al-Nakash N.Y.B.","Revanna, Jai Keerthy Chowlur (58265303700); Al-Nakash, Nushwan Yousif B. (57221473133)","58265303700; 57221473133","Metaheuristic link prediction (MLP) using AI based ACO-GA optimization model for solving vehicle routing problem",2023.0,"International Journal of Information Technology (Singapore)",15.0,7.0,null,3425.0,3439.0,14.0,3.0,"10.1007/s41870-023-01378-5","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85166647164&doi=10.1007%2fs41870-023-01378-5&partnerID=40&md5=e7e019f043e471e6969a4ae78af7caac","Information systems Engineering and management, Harrisburg University of Science and Technology, 325 Market street, Harrisburg, 17101, PA, United States","Revanna J.K.C., Information systems Engineering and management, Harrisburg University of Science and Technology, 325 Market street, Harrisburg, 17101, PA, United States; Al-Nakash N.Y.B., Information systems Engineering and management, Harrisburg University of Science and Technology, 325 Market street, Harrisburg, 17101, PA, United States","Delivering goods is crucial to the supply chain industry because it directly affects package delivery, a crucial aspect of real-time vehicle movement on which most e-commerce businesses rely. By improving the vehicle routing process, package delivery speed could be increased, and especially for medical emergency-related items, this will drastically impact the nature of delivery, cost, and time spent on it. This is being done to prepare an efficient routing model for the vehicle route, which will ultimately result in an improved path. As they have a variety of restrictions, the goal of this article is to identify the various parameters that, when used with a multi-objective optimization-based routing model, will satisfy the limit. The routing route may be made more efficient using ant colony optimization (ACO) in conjunction with an upgraded recurrent model of the genetic algorithm (GA). To achieve this, the ACO-GA optimization method known as metaheuristic link prediction (MLP) was used for parameter prediction. This method offers an evaluation of the relationship between the emission of CO2 (carbon dioxide), the trip region, and the other associated parameters. The authors of this study compare the findings of their prior work, which combined ACO and K-means clustering to get better results. Once the results are established, they will become the primary objective function of the optimization algorithm, which will be responsible for choosing the path that is connected to the parameter values. The complete procedure of the suggested method was simulated and evaluated using the publicly accessible data set of Solomon’s benchmark data set with the property pairs, and then it was compared with the ACO-K-means method. In addition to this, the current algorithm is compared with other vehicle routing algorithms to improve the process. © 2023, The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of Computer Applications and Management.","Ant colony optimization (ACO); Artificial intelligence; Genetic algorithm (GA); Metaheuristic link prediction (MLP); Multi-objective optimization; Vehicle routing problem; Vehicle routing problem (VRP)",{"$nulls":7},"Ostermeier M., Hubner A.H., Vehicle selection for a multi-compartment vehicle routing problem, Eur J Oper Res, 269, pp. 682-694, (2018); Poonthalir G., Nadarajan R., A fuel efficient green vehicle routing problem with varying speed constraint (f-gvrp), Exp Syst Appl, 100, pp. 131-144, (2018); Schermer D., Moeini M., Wendt O., Algorithms for Solving the Vehicle Routing Problem with Drones, pp. 352-361, (2018); Wei L., Zhang Z., Zhang D.-F., Leung S.C.H., A simulated annealing algorithm for the capacitated vehicle routing problem with two-dimensional loading constraints, Eur J Oper Res, 265, pp. 843-859, (2018); Macrina G., Guerriero F., The green vehicle routing problem with occasional drivers, New trends in emerging complex real life problems, pp. 357-366, (2018); Zou X., Liu L., Li K., Li W., A coordinated algorithm for integrated production scheduling and vehicle routing problem, Int J Product Res, 56, 15, pp. 5005-5024, (2018); Stavropoulou F., Repoussis P.P., Tarantilis C.D., The vehicle routing problem with profits and consistency constraints, Eur J Operat Res, 274, 1, pp. 340-356, (2019); Gayialis S.P., Konstantakopoulos G.D., Tatsiopoulos I.P., Vehicle routing problem for urban freight transportation: A review of the recent literature, Operational Research in the Digital era–ICT Challenges, pp. 89-104, (2019); Long J., Sun Z., Pardalos P.M., Hong Y., Zhang S., Li C., A hybrid multi-objective genetic local search algorithm for the prize-collecting vehicle routing problem, Inf Sci, 478, pp. 40-61, (2019); Xiao Y., Zuo X., Kaku I., Zhou S., Pan X., Development of energy consumption optimization model for the electric vehicle routing problem with time windows, J Clean Product, 225, pp. 647-663, (2019); Chen L., Liu Y., Langevin A., A multi-compartment vehicle routing problem in cold-chain distribution, Comp Operat Res, 111, pp. 58-66, (2019); Xu Z., Elomri A., Pokharel S., Mutlu F., A model for capacitated green vehicle routing problem with the time-varying vehicle speed and soft time windows, Comp Ind Eng, 137, (2019); Gurumoorthi E., Ayyasamy A., Performance analysis of geocast based location aided routing using cache agent in vanet, International Journal of Information Technology, pp. 1-10, (2019); Wang R., Zhou J., Yi X., Pantelous A.A., Solving the green-fuzzy vehicle routing problem using a revised hybrid intelligent algorithm, J Amb Intell Human Comput, 10, 1, pp. 321-332, (2019); Zhang W., Chen Z., Zhang S., Wang W., Yang S., Cai Y., Composite multi-objective optimization on a new collaborative vehicle routing problem with shared carriers and depots, J Clean Product, 274, (2020); Tyagi P., Dembla D., A secured routing algorithm against black hole attack for better intelligent transportation system in vehicular ad hoc network, Int J Inf Tech, 11, pp. 743-749, (2019); Feng L., Huang Y., Zhou L., Zhong J., Gupta A., Tang K., Tan K.C., Explicit evolutionary multitasking for combinatorial optimization: A case study on capacitated vehicle routing problem, IEEE Transact Cybern, 51, 6, pp. 3143-3156, (2020); Konstantakopoulos G.D., Gayialis S.P., Kechagias E.P., Vehicle routing problem and related algorithms for logistics distribution: A literature review and classification, Operat Res, 22, 3, pp. 2033-2062, (2022); Pasha J., Dulebenets M.A., Kavoosi M., Abioye O.F., Wang H., Guo W., An optimization model and solution algorithms for the vehicle routing problem with a “factory-in-a-box, IEEE Access, 8, pp. 134743-134763, (2020); Sumathi M., Vijayaraj N., Raja S.P., Rajkamal M., Hho-aco hybridized load balancing technique in cloud computing, Int J Inf Tech, 15, 3, pp. 1357-1365, (2023); Pachuau J.L., Kashyap P., Kumar A., Paul R., Id P., Chandrakiran B., Debnath S., Saha A.K., Segmentation of composite signal into harmonic fourier expansion using genetic algorithm, Int J Inf Tech, 14, 7, pp. 3507-3515, (2022); Kitjacharoenchai P., Min B.-C., Lee S., Two echelon vehicle routing problem with drones in last mile delivery, Int J Product Econ, 225, (2020); Archetti C., Guerriero F., Macrina G., The online vehicle routing problem with occasional drivers, Comp Operat Res, 127, (2021); Abdullahi H., Reyes-Rubiano L., Ouelhadj D., Faulin J., Juan A.A., Modelling and multi-criteria analysis of the sustainability dimensions for the green vehicle routing problem, Eur J Operat Res, 292, 1, pp. 143-154, (2021); Ali I.M.S., Hariprasad D., Hyper-heuristic salp swarm optimization of multi-kernel support vector machines for big data classification, International Journal of Information Technology, pp. 1-13, (2023); Rajagopal B.G., Intelligent traffic analysis system for indian road conditions, International Journal of Information Technology, pp. 1-13, (2020); Vincent F.Y., Jodiawan P., Gunawan A., An adaptive large neighborhood search for the green mixed fleet vehicle routing problem with realistic energy consumption and partial recharges, Appl Soft Comp, 105, (2021); Aggarwal D., Kumar V., Performance evaluation of distance metrics on firefly algorithm for vrp with time windows, Int J Inf Tech, 13, pp. 2355-2362, (2021); Olgun B., Koc C., Altiparmak F., A hyper heuristic for the green vehicle routing problem with simultaneous pickup and delivery, Comp Ind Eng, 153, (2021); Shamsi Gamchi N., Torabi S.A., Jolai F., A novel vehicle routing problem for vaccine distribution using sir epidemic model, OR Spectrum, 43, 1, pp. 155-188, (2021); Akbarpour N., Salehi-Amiri A., Hajiaghaei-Keshteli M., Oliva D., An innovative waste management system in a smart city under stochastic optimization using vehicle routing problem, Soft Comp, 25, 8, pp. 6707-6727, (2021); Park H., Son D., Koo B., Jeong B., Waiting strategy for the vehicle routing problem with simultaneous pickup and delivery using genetic algorithm, Expert Syst Appl, 165, (2021); Sarkar A., Sharma H.S., Singh M.M., A supervised machine learning-based solution for efficient network intrusion detection using ensemble learning based on hyperparameter optimization, Int J Inf Tech, 15, 1, pp. 423-434, (2023); Tamke F., Buscher U., A branch-and-cut algorithm for the vehicle routing problem with drones, Transp Res Part B: Methodological, 144, pp. 174-203, (2021); Zhang Q., Wang Z., Huang M., Yu Y., Fang S.-C., Heterogeneous multi-depot collaborative vehicle routing problem, Transp Res Part B: Methodol, 160, pp. 1-20, (2022); Guo J., Long J., Xu X., Yu M., Yuan K., The vehicle routing problem of intercity ride-sharing between two cities, Transp Res Part B: Methodol, 158, pp. 113-139, (2022); Shahnejat-Bushehri S., Tavakkoli-Moghaddam R., Boronoos M., Ghasemkhani A., A robust home health care routing-scheduling problem with temporal dependencies under uncertainty, Expert Syst Appl, 182, (2021); Revanna J.K.C., Al-Nakash N.Y.B., Vehicle routing problem with time window constrain using kmeans clustering to obtain the closest customer, Global J Comp Sci Technol, 22, D1, pp. 25-37, (2022); Veerabhadrappa R., Ul Hassan M., Zhang J., Bhatti A., Compatibility evaluation of clustering algorithms for contemporary extracellular neural spike sorting, Front Syst Neurosci, 14, (2020); Revanna J.K.C., Al-Nakash N.Y.B., Ant colony optimization with simulated annealing algorithm for google maps, 2023 9Th International Conference on Advanced Computing and Communication Systems (ICACCS), 1, pp. 320-326, (2023); Dorigo M., Blum C., Ant colony optimization theory: a survey, Theoret Comp Sci, 344, 2-3, pp. 243-278, (2005); Ramya R., Padmapriya K., Hybrid optimized using grey wolf-flower pollination for wireless sensor network routing, International Journal of Information Technology, pp. 1-9, (2023); Gunawan A., Kendall G., McCollum B., Seow H.-V., Lee L.S., Vehicle routing: Review of benchmark datasets, J Operat Res Soc, 72, 8, pp. 1794-1807, (2021)","J.K.C. Revanna; Information systems Engineering and management, Harrisburg University of Science and Technology, Harrisburg, 325 Market street, 17101, United States; email: jchowlur@my.harrisburgu.edu",null,"Springer Science and Business Media B.V.",{"$nulls":5},2.5112104E7,null,null,null,"English","Int. J. Inf. Technol.","Article","Final",null,"Scopus","2-s2.0-85166647164"]
["Wang G.; Hou Y.; Shin C.","Wang, Gaofeng (58033623800); Hou, Yanning (58512180600); Shin, Changhoon (7202571530)","58033623800; 58512180600; 7202571530","Exploring Sustainable Development Pathways for Agri-Food Supply Chains Empowered by Cross-Border E-Commerce Platforms: A Hybrid Grounded Theory and DEMATEL-ISM-MICMAC Approach",2023.0,"Foods",12.0,21.0,3916.0,null,null,null,1.0,"10.3390/foods12213916","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85176381165&doi=10.3390%2ffoods12213916&partnerID=40&md5=8011f2f7d93329f4c8400eb46b875554","School of Management, Henan University of Technology, Zhengzhou, 450001, China; School of Management, Zhengzhou University, Zhengzhou, 450001, China; College of Ocean Science and Engineering, Korea Maritime & Ocean University, Busan, 49112, South Korea","Wang G., School of Management, Henan University of Technology, Zhengzhou, 450001, China; Hou Y., School of Management, Zhengzhou University, Zhengzhou, 450001, China; Shin C., College of Ocean Science and Engineering, Korea Maritime & Ocean University, Busan, 49112, South Korea","As cross-border e-commerce platforms become increasingly integrated into the agricultural supply chain, the establishment of a sustainable supply chain ecosystem is of paramount importance. This study, grounded in the platform theory and the supply chain ecosystem theory, combines the grounded theory and the DEMATEL–ISM–MICMAC model to thoroughly analyze the complex mechanisms driving sustainable development. Utilizing the grounded theory, we construct a system of driving factors comprising five primary indicators and eighteen secondary indicators. The hybrid model reveals the interrelationships, significance, system hierarchy, and dependence-driving relationships among these factors. Notably, the driving factor system is categorized into a six-level hierarchical structure, encompassing profound elements, such as policy optimization and digital empowerment, as well as surface-level factors, such as simplification of customs procedures and consumer demand forecasting. Based on the analysis results, this research proposes a set of pathways to achieve the sustainability of the supply chain. These strategies involve improving cross-border agricultural e-commerce policy frameworks, enhancing digital-driven supply–demand coordination, strengthening logistics infrastructure and transparency, and cultivating brand influence. The study’s findings not only enrich the relevant theories but also provide practical guidance for the coordinated advancement of economic, social, environmental, and resilient development. Furthermore, they are conducive to advancing the United Nations Sustainable Development Goals. © 2023 by the authors.","agri-food product supply chain; cross-border e-commerce platforms; driving mechanisms; implementation pathway; sustainable development",{"$nulls":5},"Henan University of Technology High-level Talents Scientific Research Start-up fund Project, (31401371); Henan University of Technology Young Key Teacher Training Program, (21420174); Logistics Research Center of the Key Research Base of Humanities and Social Sciences of Henan Province fund Project, (2022-JD-01); National Office for Philosophy and Social Sciences, NPOPSS, (20CGL017)","This research was funded by the National Social Science Foundation of China (grant number: 20CGL017), the Logistics Research Center of the Key Research Base of Humanities and Social Sciences of Henan Province fund Project (grant number: 2022-JD-01), the Henan University of Technology High-level Talents Scientific Research Start-up fund Project (grant number: 31401371), and the Henan University of Technology Young Key Teacher Training Program (grant number: 21420174).",{"$cut":{"chars":16909,"head":"Guo H.D., Steps to the digital Silk Road, Nature, 554, pp. 25-27, (2018); Wang G., Li S., Zhang Z., Hou Y., Shin C., A Visual Knowledge Map Analysis of Cross-Border Agri-Food Supply Chain Research Based on CiteSpace, Sustainability, 15, (2023); Development Report on Cross-Border E-Commerce of Agri-Food Products in China, (2023); Climate Change 2022: Impacts, Adaptation and Vulnerability, (2022); The State of Food Security and Nutrition in the World 2022: Repurposing Food and Agri-Food Policies to Make Healthy Diets More Affordable, (2022); Trollman H., Jagtap S., Trollman F., Crowdsourcing food security: Introducing food choice derivatives for sustainability, Food Secur, 15, pp. 953-965, (2023); Ren S., Towards a sustainable cross-border e-commerce development, China Commun, 18, pp. 1-15, (2021); Zhu Q., Sarkis J., Lai K.H., Institutional pressures, dynamic capabilities and environmental management systems: Investigating the ISO 9000-Environmental management system implementation linkage, J. Environ. Manag, 209, pp. 103-115, (2018); Hu Y.Q., Lin H., The Mechanism and Effect of ‘Internet+’ Empowering Small Farmers to Connect with the Big Market, Mod. Econ. Res, pp. 110-117, (2020); The Paris Agreement, (2015); Our Common Future, (1987); Wang G., Zhang Z., Li S., Shin C., Research on the Influencing Factors of Sustainable Supply Chain Development of Agri-Food Products Based on Cross-Border Live-Streaming E-Commerce in China, Foods, 12, (2023); Kahar A., Performance Evaluation and Improvement Path of Agri-Food Trade Supply Chain between China and Central Asian Countries, (2022); Su H.M., Research on Risk Identification of Cross-Border Agri-Food Product Supply Chain Based on Immune Theory, (2019); Sui B.W., Zhuang L.J., Cross border agri-food products supply chain: The cornerstone of the development of China ASEAN agri-food products circulation industry, China Circ. Econ, 30, pp. 67-74, (2016); Saeed M.A., Kersten W., Drivers of sustainable supply chain management: Identification and classification, Sustainability, 11, (2019); Guimaraes Y.M., Eustachio J.H.P.P., Leal Filho W., Martinez L.F., do Valle M.R., Caldana A.C.F., Drivers and barriers in sustainable supply chains: The case of the Brazilian coffee industry, Sustain. Prod. Consum, 34, pp. 42-54, (2022); Ghadge A., Kara E.M., Mogale G.D., Choudhary S., Dani S., Sustainability implementation challenges in food supply chains: A case of UK artisan cheese producers, Prod. Plan. Control, 32, pp. 1191-1206, (2022); Bottani E., Casella G., Nobili M., Tebaldi L., Assessment of the economic and environmental sustainability of a food cold supply chain, IFAC Pap. OnLine, 52, pp. 367-372, (2019); Ali S.M., Moktadir M.A., Kabir G., Chakma J., Rumi M.J.U., Islam M.T., Framework for evaluating risks in food supply chain: Implications in food wastage reduction, J. Clean. Prod, 228, pp. 786-800, (2019); Allaoui H., Guo Y., Sarkis J., Decision support for collaboration planning in sustainable supply chains, J. Clean. Prod, 229, pp. 761-774, (2019); Sharma R., Kamble S.S., Gunasekaran A., Big GIS analytics framework for agriculture supply chains: A literature review identifying the current trends and future perspectives, Comput. Electron. Agric, 155, pp. 103-120, (2018); Dania W.A.P., Xing K., Amer Y., Collaboration behavioural factors for sustainable agri-food supply chains: A systematic review, J. Clean. Prod, 186, pp. 851-864, (2018); Agyemang M., Zhu Q., Adzanyo M., Antarciuc E., Zhao S., Evaluating barriers to green supply chain redesign and implementation of related practices in the West Africa cashew industry, Resour. Conserv. Recycl, 136, pp. 209-222, (2018); Chkanikova O., Mont O., Corporate Supply Chain Responsibility: Drivers and Barriers for Sustainable Food Retailing, Corp. Soc. Responsib. Environ. Manag, 22, pp. 65-82, (2015); Salim K.H., Padfield R., Lee T.C., Syayuti K., Papargyropoulou E., Tham M.H., An investigation of the drivers, barriers, and incentives for environmental management systems in the Malaysian food and beverage industry, Clean Technol. Environ. Policy, 20"}},"C. Shin; College of Ocean Science and Engineering, Korea Maritime & Ocean University, Busan, 49112, South Korea; email: chshin@kmou.ac.kr",null,"Multidisciplinary Digital Publishing Institute (MDPI)",{"$nulls":5},2.3048158E7,null,null,null,"English","Foods","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85176381165"]
["Lal A.; Renaldy T.; Breuning L.; Hamacher T.; You F.","Lal, Apoorv (57915153200); Renaldy, Thomas (58419862400); Breuning, Larissa (57221201170); Hamacher, Thomas (8065564500); You, Fengqi (56750277000)","57915153200; 58419862400; 57221201170; 8065564500; 56750277000","Electrifying light commercial vehicles for last-mile deliveries: Environmental and economic perspectives",2023.0,"Journal of Cleaner Production",416.0,null,137933.0,null,null,null,3.0,"10.1016/j.jclepro.2023.137933","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85163795091&doi=10.1016%2fj.jclepro.2023.137933&partnerID=40&md5=03195f2f171c61324df81a898afcec19","Robert Frederick Smith School of Chemical and Biomolecular Engineering, Cornell University, Ithaca, 14853, NY, United States; Energy & Process Engineering, Technical University of Munich, Arcisstraße, Munich, 80333, Germany","Lal A., Robert Frederick Smith School of Chemical and Biomolecular Engineering, Cornell University, Ithaca, 14853, NY, United States; Renaldy T., Robert Frederick Smith School of Chemical and Biomolecular Engineering, Cornell University, Ithaca, 14853, NY, United States, Energy & Process Engineering, Technical University of Munich, Arcisstraße, Munich, 80333, Germany; Breuning L., Energy & Process Engineering, Technical University of Munich, Arcisstraße, Munich, 80333, Germany; Hamacher T., Energy & Process Engineering, Technical University of Munich, Arcisstraße, Munich, 80333, Germany; You F., Robert Frederick Smith School of Chemical and Biomolecular Engineering, Cornell University, Ithaca, 14853, NY, United States","The COVID-19 pandemic has led to a surge in online shopping and home deliveries, driving the demand for delivery vehicles. Last-mile delivery vehicles are one of the rampant carbon dioxide emitters, with zero-direct emission alternatives as the glaringly obvious solution to this problem. To address this issue, we present a comprehensive evaluation of the total cost of ownership (TCO) and life cycle environmental impacts of three types of light commercial vehicles (LCVs): internal combustion engine, battery electric (BE), and hydrogen fuel cell (FC) electric LCVs in Germany and California. In this study, we present the first analysis of the life cycle impacts of an FC-LCV with a lower fuel cell system power but a larger traction battery capacity referred to as a “Mid-FC” vehicle configuration. In addition, the research establishes various scenarios to examine the effect of a greener electricity grid and hydrogen produced from water electrolysis on the overall LCV life cycle impacts. Results suggest that BE LCVs are already cost-competitive in both the studied regions. Replacing a diesel LCV with a BE alternative can reduce greenhouse gas emissions by 15%–48% over the LCV's lifetime and up to 69% in a low-carbon grid scenario. The study also found that a Mid-FC LCV has lower environmental impacts than an FC counterpart if the hydrogen is produced via water electrolysis powered by low-carbon electricity. These findings provide critical insights for fleet operators seeking to balance cost-effectiveness and environmental sustainability in their LCV selection. © 2023 Elsevier Ltd","Last-mile delivery; Life cycle assessment; Light commercial vehicles; Total cost of ownership","Carbon dioxide; Commercial vehicles; Cost effectiveness; Electrolysis; Environmental impact; Fuel cells; Gas emissions; Greenhouse gases; Hydrogen production; Secondary batteries; Sustainable development; Delivery vehicle; Economic perspective; Last mile; Last-mile delivery; Life cycle assessment; Life cycle impacts; Light commercial vehicles; Online shopping; Total cost of ownership; Water electrolysis; Life cycle",{"$nulls":4},"National Science Foundation, NSF, (1643244)","This material is based upon work supported by the National Science Foundation (NSF) under Grant No. 1643244 .","Alonso-Villar A., Davidsdottir B., Stefansson H., Asgeirsson E.I., Kristjansson R., Technical, economic, and environmental feasibility of alternative fuel heavy-duty vehicles in Iceland, J. 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Commun., 11, 1, (2020); Goncalves F.D.O., Lopes E.S., Savioli Lopes M., Maciel Filho R., Thorough evaluation of the available light-duty engine technologies to reduce greenhouse gases emissions in Brazil, J. Clean. 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Life Cycle Assess., 21, 9, pp. 1218-1230, (2016); Wong Y.C., Al-Obaidi K.M., Mahyuddin N., Recycling of end-of-life vehicles (ELVs) for building products: concept of processing framework from automotive to construction industries in Malaysia, J. Clean. Prod., 190, pp. 285-302, (2018); Wu W., Pai C.-T., Viswanathan K., Chang J.-S., Comparative life cycle assessment and economic analysis of methanol/hydrogen production processes for fuel cell vehicles, J. Clean. Prod., 300, (2021); Wulf C., Kaltschmitt M., Hydrogen supply chains for mobility—environmental and economic assessment, Sustainability, 10, 6, (2018); Yang L., Yu B., Yang B., Chen H., Malima G., Wei Y.-M., Life cycle environmental assessment of electric and internal combustion engine vehicles in China, J. Clean. Prod., 285, (2021); Ziegler D., Abdelkafi N., Business models for electric vehicles: literature review and key insights, J. Clean. Prod., 330, (2022)","F. You; Robert Frederick Smith School of Chemical and Biomolecular Engineering, Cornell University, Ithaca, 14853, United States; email: fengqi.you@cornell.edu",null,"Elsevier Ltd",{"$nulls":5},9596526.0,null,"JCROE",null,"English","J. Clean. Prod.","Article","Final",null,"Scopus","2-s2.0-85163795091"]
["Henaway M.","Henaway, Mostafa (55658425900)",5.56584259E10,"Amazon's distribution space: Constructing a 'labour fix' through digital Taylorism and corporate Keynesianism",2023.0,"ZFW - Advances in Economic Geography",67.0,4.0,null,202.0,216.0,14.0,2.0,"10.1515/zfw-2022-0017","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85173228984&doi=10.1515%2fzfw-2022-0017&partnerID=40&md5=d7b89a48e82bbed79cefee87db6f77fd","Concordia University, Geography Planning and Environment, 1455 De Maisonneuve Blvd. W., 12th Floor, Montreal, Canada","Henaway M., Concordia University, Geography Planning and Environment, 1455 De Maisonneuve Blvd. W., 12th Floor, Montreal, Canada","Amazon is one of the largest e-commerce corporations in the world and has built a reputation for fast, low-cost service. To rapidly and efficiently move goods from production to consumption, however, Amazon relies on a logistics network that entails significant investments in infrastructure (physical and human) and these investments present a challenge for capital accumulation. In this paper, I examine the labour practices that Amazon employs within its distribution work spaces to address this challenge. The analysis is based on a case study of Amazon's distribution facilities (fulfilment centres and delivery stations) in Montreal, Quebec. It draws on ethnographic research as a community organizer and semi-structured interviews with workers (present and former), trade union representatives and public policy experts to identify Amazon's key strategies. Building on past studies on the platform economy, I illustrate how Amazon relies on 'digital Taylorism' (Staab & Nachtwey, 2016), involving the use of digital technologies to structure and control the labour process and surveil workers, as a key strategy. However, I further illustrate how Amazon seeks to balance the harmful effects of digital Taylorism with what I term 'corporate keynesianism' (i.e., social welfare benefits) to attain a 'labour fix', i.e., the steady supply of precarious, compliant labour needed to sustain the logistics machine.  © 2023 bei den Autorinnen und Autoren, publiziert von De Gruyter.","Amazon; digital Taylorism; e-commerce; labour process; logistics; Montreal","Canada; Montreal; Quebec [Canada]; cost analysis; electronic commerce; investment; Keynesian theory; labor market; network analysis",{"$nulls":6},"Alimahomed-Wilson J., Reese E., The Cost of Free Shipping: Amazon in the Global Economy, (2020); Alimahomed-Wilson J., Unfree shipping: The racialisation of logistics labour, Work Organisation, Labour & Globalisation, 13(1), pp. 96-113, (2019); Alimahomed-Wilson J., Ness I., Choke Points, (2018); Altenried M., The digital factory, In the Digital Factory, (2022); Altenried M., On the last mile: Logistical urbanism and the transformation of labour, Work Organisation, Labour & Globalisation, 13(1), pp. 114-129, (2019); Amazon 2021 Annual Report, (2022); Amazon Employee Benefits., About Amazon., (2022); Amazon Removes $25 Minimum Purchase Requirement on Millions of Items Eligible for Prime Free One-Day Delivery in Canada, Press Release, (2022); Amazon's First Fulfillment Centre in Quebec Celebrates Its Day One with New Employees, (2020); How Amazon workers are organizing for the long haul, Labor Notes.https://www.labornotes.org/2020/05/how-amazon-workers-are-organizing-long-haul[Accessed June 20, 2022}, (2020); Bensman D., Globalization and the labor markets of the logistics industry, In 2008 Industry Studies Conference Paper, (2008); Benvegnu C., Cuppini N., Struggles and grassroots organizing in an extended European choke point, In: Alimahomed-Wilson, J., & Ness, I.(eds) Choke Points: Logistics Workers Disrupting the Global Supply Chain., pp. 230-242, (2018); Burawoy M., Blum J.A., George S., Gille Z., Thayer M., Global Ethnography: Forces, Connections, and Imaginations in A Postmodern World, (2000); Braverman H., Labor and Monopoly Capital: The Degradation of Work in the Twentieth Century, (1974); Briken K., Taylor P., Fulfilling the 'British way': Beyond constrained choice - Amazon workers' lived experiences of workfare, Industrial Relations Journal, 49(5-6), pp. 438-458, (2018); Work-related Musculoskeletal Disorders (WMSDs) - Risk Factors, (2022); Cattero B., D'Onofrio M., Organizing and collective bargaining in the digitized \"tertiary factories\" of Amazon: A comparison between Germany and Italy, In: Ales E, Curzi Y, Fabbri T, et Al. 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Henaway; Concordia University, Geography, Planning and Environment, Montreal, 1455 De Maisonneuve Blvd. W., 12th Floor, Canada; email: mhenaway@gmail.com",null,"Walter de Gruyter GmbH",{"$nulls":5},2.7481956E7,null,null,null,"English","ZFW. Adv. Eco. Geo","Article","Final","All Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85173228984"]
["Yu S.; Wang X.; Liu J.; Wei F.","Yu, Siming (57218649231); Wang, Xun (58581049500); Liu, Jiaming (58582816700); Wei, Fang (57205585902)","57218649231; 58581049500; 58582816700; 57205585902","Role of mining waste trade on green development in China: Policy implications for circular economy",2023.0,"Resources Policy",86.0,null,104147.0,null,null,null,6.0,"10.1016/j.resourpol.2023.104147","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85171347488&doi=10.1016%2fj.resourpol.2023.104147&partnerID=40&md5=c23cd17914b023330a9364f56b61ca06","School of Economics & Management, China Three Gorges University, No. 8 University Road, Xiling District, Yichang, 443002, China; Local Government Development Institute/Law School, Shantou University, Shantou, 515063, China","Yu S., School of Economics & Management, China Three Gorges University, No. 8 University Road, Xiling District, Yichang, 443002, China; Wang X., School of Economics & Management, China Three Gorges University, No. 8 University Road, Xiling District, Yichang, 443002, China; Liu J., Local Government Development Institute/Law School, Shantou University, Shantou, 515063, China; Wei F., School of Economics & Management, China Three Gorges University, No. 8 University Road, Xiling District, Yichang, 443002, China","The primary objective of this paper is to assess the impact of mining waste trade on China's green development between 1980 and 2021, utilizing the Autoregressive Distributed Lag (ARDL) technique. The key findings reveal that the coefficients associated with mining waste trade amount to 0.15% and 0.07% for the long-term and short-term perspectives, respectively, indicating a positive influence of mining waste trade on green growth in China. Furthermore, enhancements in the circular economy index are demonstrated to effectively promote green economic growth in China. Conversely, the ecological footprint poses a threat to China's green prosperity. The adverse effects of the ecological footprint on green growth underscore that sustainable and environmentally-friendly economic growth potential diminishes as the ecological footprint expands. This paper puts forward practical policy recommendations which include reforming regulations concerning mining waste trade, fostering innovative technologies for efficient and eco-friendly processing and treatment of mining waste, actively creating or connecting to an e-commerce trading platform for mining waste, and implementing eco-friendly logistics and transportation practices in mineral waste trade. © 2023","China; Circular economy; Green development; Mining waste trade; Trading platform","China; Ecology; Economic and social effects; Environmental protection; Mining; Public policy; Waste treatment; China; Circular economy; Eco-friendly; Ecological footprint; Economic growths; Green development; Green growths; Mining waste; Mining waste trade; Trading platform; economic growth; mine waste; numerical model; policy approach; recycling; regulatory framework; sustainable development; Commerce",{"$nulls":6},"Clemente Lopez J., Montanes A., Reyes M., Testing for a unit root in variables with a double change in the mean, Econ. 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Pol., 83, (2023); Lin B., Zhou Y., Measuring the green economic growth in China: influencing factors and policy perspectives, Energy, 241, (2022); Liu S., Towards a sustainable agriculture: achievements and challenges of sustainable development goal indicator 2.4.1, Global Food Secur., 37, (2023); Liu X., Lei T., Bore A., Lou Z., Abdouraman B., Ma W., Evolution of global plastic waste trade flows from 2000 to 2020 and its predicted trade sinks in 2030, J. Clean. Prod., 376, (2022); Lottermoser B.G., Mine Wastes: Characterization, Treatment and Environmental Impacts, (2010); Mcown R., Sam C., Goh S., Bootstrapping the autoregressive distributed lag test for coitegration, Appl. Econ., 50, pp. 1509-1521, (2019); Mensah D., Ng K., Hasan M., Jeenat R., Hurlbert M., Assessing non-hazardous solid waste business characteristics of Western Canadian provinces, Ecol. Inf., 75, (2023); Nandy S., Fortunato E., Martins R., Green economy and waste management: an inevitable plan for materials science, Prog. Nat. Sci.: Mater. Int., 32, 1, pp. 1-9, (2022); Ren X., An Y., Jin C., The asymmetric effect of geopolitical risk on China's crude oil prices: new evidence from a QARDL approach, Finance Res. Lett., 53, (2023); Stevis D., Vasavada A., Green growth and climate change governance: comparative analysis and recommendations for reform, J. Environ. Pol. Plann., 23, 2, pp. 157-172, (2021); Global green new deal: policy brief, (2020); Inside the global effort to save the world's forests, (2021); Vines V., Pasquali M., Ganguli S., Meyer D., Understanding the trade-offs of national municipal solid waste estimation methods for circular economy policy, J. Clean. Prod., 412, (2023); Wan Q., Qian J., Baghirli A., Aghayev A., Green finance and carbon reduction: implications for green recovery, Econ. Anal. Pol., 76, pp. 901-913, (2022); Wang Z., Yang L., Yin J., Zhang B., Assessment and prediction of environmental sustainability in China based on a modified ecological footprint model, Resour. Conserv. Recycl., 132, pp. 301-311, (2018); Zachariadis T., Giannakis E., Taliotis C., Karmellos M., Fylaktos N., Howells M., Blyth W., Hallegatte S., Science policy frameworks for a post-pandemic green economic recovery, Energy Strategy Rev., 45, (2023); Zhang F., Lu J., Chen L., When green recovery fails to consider coal pushback: exploring global coal rebounds, production, and policy retrenchment post Covid-19, Energy Res. Social Sci., 101, (2023); Zhao L., Rasoulinezhad E., Role of natural resources utilization efficiency in achieving green economic recovery: evidence from BRICS countries, Resour. Pol., 80, (2023); Zhao X., Guo Y., Feng T., Towards green recovery: natural resources utilization efficiency under the impact of environmental information disclosure, Resour. Pol., 83, (2023); Zivot E., Andrews D., Further evidence on the great crash, the oil-price shock, and the unit-root hypothesis, J. Bus. Econ. Stat., 20, 1, pp. 25-44, (2002)","J. Liu; Local Government Development Institute/Law School, Shantou University, Shantou, 515063, China; email: 15216138510@163.com",null,"Elsevier Ltd",{"$nulls":5},3014207.0,null,null,null,"English","Resour. Policy","Article","Final",null,"Scopus","2-s2.0-85171347488"]
["Antón-Maraña P.; Puche-Regaliza J.C.; Arranz-Val P.; Aparicio-Castillo S.","Antón-Maraña, Paula (57682445800); Puche-Regaliza, Julio César (45561439400); Arranz-Val, Pablo (55480264600); Aparicio-Castillo, Santiago (57200660778)","57682445800; 45561439400; 55480264600; 57200660778","Examining the relationship between online distribution channels and tourist satisfaction and loyalty; [Examinando la relación entre los canales de distribución en línea y la satisfacción y lealtad de los turistas]",2023.0,"Tourism and Management Studies",19.0,4.0,null,"7'",20.0,null,0.0,"10.18089/tms.2023.190401","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85186922947&doi=10.18089%2ftms.2023.190401&partnerID=40&md5=d9c294bed46cfca302ac826f0665490c","Department of Applied Economics, Faculty of Economics, University of Burgos, Spain","Antón-Maraña P., Department of Applied Economics, Faculty of Economics, University of Burgos, Spain; Puche-Regaliza J.C., Department of Applied Economics, Faculty of Economics, University of Burgos, Spain; Arranz-Val P., Department of Applied Economics, Faculty of Economics, University of Burgos, Spain; Aparicio-Castillo S., Department of Applied Economics, Faculty of Economics, University of Burgos, Spain","Although the Internet and e-commerce have contributed positively to the tourism sector, there is not much empirical research on the transformation of distribution channels or that considers the use of the Internet in travel planning as an antecedent of tourist satisfaction and loyalty. This paper aims to test the influence of online distribution channels in trip planning by tourists on their general satisfaction level and their loyalty towards the destination and to differentiate the profile of digital and traditional tourists. Quantitative research techniques are used to analyse the dataset of 1,387 surveys of tourists visiting the province of Burgos, Spain. Among those surveyed, 65% search for information online and 54% book or pay for services online. According to ordinal regression analysis, the use of online channels does not significantly influence the level of satisfaction, but according to binary logistic regression, it does significantly influence loyalty. The findings provide valuable information for developing marketing strategies in tourism organisations and support decision-makers in creating competitive tourism destinations that are resilient to the demographic challenge of depopulation. © 2023 University of Algarve. All rights reserved.","Information and Communication Technologies; Online Channel; Tourism Distribution System; Tourist Destination Loyalty; Trip Satisfaction",{"$nulls":5},"Ministry of Science and Innovation of the Government of Spain; Society for the Development; State Research Agency; Universidad de Burgos, UBU, (PEBUR 15-20); Federación Española de Enfermedades Raras, FEDER, (PID2022-139543OB-C44)","This work was financially supported by the Society for the Development of the Province of Burgos, thanks to the collaboration agreement signed between the University of Burgos and this institution for the development of actions included in the Rural Strategic Plan of Burgos (PEBUR 15-20) in the fields of tourism, environmental economics and human capital and by the State Research Agency (Ministry of Science and Innovation of the Government of Spain) and FEDER Funds (Knowledge Generation Projects) through the project \"Methodologies for solving problems with economic, social and environmental criteria. Application to healthcare resource management\" (ECOSOEN-HEALTH, grant ref. PID2022-139543OB-C44). The authors deeply appreciate the financial support received.",{"$cut":{"chars":18808,"head":"Abbasi A. Z., Rather R. A., Hooi Ting D., Nisar S., Hussain K., Khwaja M. G., Shamim A., Exploring tourism-generated social media communication, brand equity, satisfaction, and loyalty: A PLS-SEM-based multi-sequential approach, Journal of Vacation Marketing, (2022); Agresti A., Categorical data analysis, (2002); Albayrak T., Caber M., Tourists' satisfaction and its interaction with loyalty towards a destination, Estableciendo puentes en una economía global, (2008); Amaro S., Duarte P., Online travel purchasing: A literature review, Journal of Travel & Tourism Marketing, 30, 8, pp. 755-785, (2013); Anton Marana P., Aparicio Castillo S., Puche Regaliza J. C., Arranz Val P., A comparative study for understanding the impact and evolution of the tourism role in Burgos province, Revista Turismo & Desenvolvimento, 36, 1, pp. 221-231, (2021); Aparicio-Castillo S., Arranz-Val P., Alvear-Gonzalez A., Anton-Marana P., Puche-Regaliza J. C., Target points as survey locations: Touristic potentiality index, Revista de Métodos Cuantitativos para la Economía y la Empresa, 36, (2023); Azis N., Amin M., Chan S., Aprilia C., How smart tourism technologies affect tourist destination loyalty, Journal of Hospitality and Tourism Technology, 11, 4, pp. 603-625, (2020); Bandres E., Azon V., La despoblación de la España Interior, (2021); Baptista Alves H. M., Pires Manso J. R., da Silva Serrasqueiro Teixeira Z. M., Santos Estevao C. M., Pinto Nave A. C., Tourism-based regional development: boosting and inhibiting factors, Anatolia: An International Journal of Tourism and Hospitality Research, 33, 1, pp. 128-142, (2022); Beldona S., Nusair K., Demicco F., Online travel purchase behavior of generational cohorts: A longitudinal study, Journal of Hospitality Marketing & Management, 18, 4, pp. 406-420, (2009); Benitez-Marquez M. D., Bermudez-Gonzalez G., Sanchez-Teba E. M., Cruz-Ruiz E., Exploring the antecedents of cruisers’ destination loyalty: cognitive destination image and cruisers’ satisfaction, Mathematics, 9, 11, (2021); Berne-Manero C., Garcia-Gonzalez M., Garcia-Uceda M. E., Mugica-Grijalba J. M., The effect of ICT on relationship enhancement and performance in tourism channels, Tourism Management, 48, pp. 188-198, (2015); Bernini C., Cagnone S., Analysing tourist satisfaction at a mature and multi-product destination, Current Issues in Tourism, 17, 1, pp. 1-20, (2014); Buhalis D., Relationships in the distribution channel of tourism, International Journal of Hospitality and Tourism Administration, 1, 1, pp. 113-139, (2000); Buhalis D., Laws E., Tourism distribution channels: practices, issues and transformations, (2001); Buhalis D., Law R., Progress in information technology and tourism management: 20 years on and 10 years after the Internet—The state of eTourism research, Tourism Management, 29, 4, pp. 609-623, (2008); Canalis X., Esta es la foto que Google ha hecho de los turistas digitales, Innovación. Hosteltur, (2018); Castaneda J. A., Frias D. M., Rodriguez M. A., The influence of the Internet on destination satisfaction, Internet Research, 17, 4, pp. 402-420, (2007); Campon-Cerro A. M., Hernandez-Mogollon J. M., Alves H., Sustainable improvement of competitiveness in rural tourism destinations: The quest for tourist loyalty in Spain, Journal of Destination Marketing & Management, 6, 3, pp. 252-266, (2017); Chen C. C., Huang W. J., Petrick J. F., Holiday recovery experiences, tourism satisfaction and life satisfaction – Is there a relationship?, Tourism Management, 53, pp. 140-147, (2016); Chen C. F., Tsai D., How destination image and evaluative factors affect behavioural intentions?, Tourism Management, 28, 4, pp. 1115-1122, (2007); Chen R., Zhou Z., Zhan G., Zhou N., The impact of destination brand authenticity and destination brand self-congruence on tourist loyalty: The mediating role of destination brand engagement, Journal of Destination Marketing & Management, 15, (2020); Cheung C. M., Lee M. K., Understanding consumer trust in Internet shopping: A multidisciplinary approach, Journal of the American society for Information Sci"}},null,null,"University of Algarve",{"$nulls":5},2.1828458E7,null,null,null,"English","Tour. Manag. Stud","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85186922947"]
["Yahyaoui H.; Jaegler A.; Randrianarisoa L.","Yahyaoui, Hiba (58823766900); Jaegler, Anicia (36630589900); Randrianarisoa, Laingo (56600640800)","58823766900; 36630589900; 56600640800","A cost calculation model for urban delivery of parcels by river",2023.0,"Research in Transportation Business and Management",51.0,null,101059.0,null,null,null,0.0,"10.1016/j.rtbm.2023.101059","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85175023861&doi=10.1016%2fj.rtbm.2023.101059&partnerID=40&md5=322f1d1d1d74791243dc857706365358","Kedge Business School, 40 Avenue des Terroirs de France, Paris, 75012, France","Yahyaoui H., Kedge Business School, 40 Avenue des Terroirs de France, Paris, 75012, France; Jaegler A., Kedge Business School, 40 Avenue des Terroirs de France, Paris, 75012, France; Randrianarisoa L., Kedge Business School, 40 Avenue des Terroirs de France, Paris, 75012, France","Public and private actors in cities have embarked on a race to achieve net-zero carbon emissions. However, parcel delivery in urban areas is booming, especially due to e-commerce. This context necessitates the study of sustainable transportation use. Among the various city-center parcel delivery modes, delivery by river is largely understudied. This study proposes a cost calculation model for delivery by inland waterways. This model considers fixed and variable costs for pre-carriage, transshipment, and last-mile delivery using a two-echelon last-mile delivery network framework. The model is tested using a real-life French case study and worldwide academic investigation. The results show that load optimization is key for profitability and that the most important costs are personnel and investment costs. © 2023 Elsevier Ltd","Cost model; Inland waterway; Last mile delivery; Parcels; River logistics",{"$nulls":7},"Aiello G.A.C., Quaranta S., Inguanta R., Optimization of urban delivery systems based on electric assisted cargo bikes with modular battery size, taking into account the service requirements and the specific operational context, Energies, 14, (2021); Al Enezy O., van Hassel E., Sys C., Vanelslander T., Developing a cost calculation, Research in Transportation Business & Management, 23, pp. 64-74, (2017); Bannaga S., Revitalization of greater Khartoum urban transportation system, Future Cities and Environment, 4, (2018); Beelen M., Structuring and modelling decision making in the inland navigation sector, (2011); Buwana E., Hayati S.H., Abdini C., Alternatives selection for sustainable transportation system in Kasongan City, Procedia - Social and Behavioral Sciences, 227, pp. 11-18, (2016); Campbell I., Calhoun K., Hao Y., Li T., Lu S., Mandel J., Wang M., Near-zero carbon zones in China. Policy Roadmaps and Case Study; Christodoulou A., Christidis P., Bisselink B., Forecasting the impacts of climate change on inland waterways, Transportation Research Part D: Transport and Environment, 82, (2020); David A., Mako P., Galierikova A., Stupalo V., Transshipment activities in the Rhine ports, Transportation Research Procedia, 53, pp. 188-195, (2021); de Barros, de Carvalho, Junior A.C.P.B., Inland waterway transport and the 2030 agenda: Taxonomy of sustainability issues, Cleaner Engineering and Technology, 8, (2022); Divieso E., Junior O.F.L., De Oliveira H.C., The use of waterways for urban logistics: The case of Brazil, Theoretical and Empirical Researches in Urban Management, 16, 1, pp. 62-85, (2021); Diziain D., Taniguchi E., Dablanc L., Urban logistics by rail and waterways in France and Japan, Procedia - Social and Behavioral Sciences, 125, pp. 159-170, (2014); Durajczyk P., Drop N., Possibilities of using inland navigation to improve efficiency of urban and interurban freight transport with the use of the river information services (RIS) system – Case study, Energies, 14, 21, (2021); European Commission, An integrated European action Programme for inland waterway transport, (2006); Fuhrmann M., Spatial, social and economical dynamic of contemporary Warsaw–City profile, Cities, 94, pp. 286-295, (2019); Hunt J.D., Pokhrel Y., Chaudhari S., Mesquita A.L.A., Nascimento A., Leal Filho W., Lopes M.A., Challenges and opportunities for a South America waterway system, Cleaner Engineering and Technology, 11, (2022); Jaegler A., Burlat P., Carbon friendly supply chains: A simulation study of different scenarios, Production Planning and Control, 23, 4, pp. 269-278, (2012); Janjevic M., Ndiaye A.B., Inland waterways transport for city logistics: a review of experiences and the role of local public authorities, Urban Transport XX, 138, pp. 279-290, (2014); Kim N.S., Van Wee B., The relative importance of factors that influence the break-even distance of intermodal freight transport systems, Journal of Transport Geography, 19, 4, pp. 859-875, (2011); Lu C., Yan X., The break-even distance of road and inland waterway freight transportation systems, Maritime Economics & Logistics, 17, pp. 246-263, (2017); Melo I.C., Junior P.N.A., Perico A.E., Guzman M.G.S., Rebelatto D.A.D.N., Benchmarking freight transportation corridors and routes with data envelopment analysis (DEA), Benchmarking: An International Journal, 25, 2, pp. 713-742, (2018); Notteboom T., Challenges for container river services on the Yangtze River: A case study for Chongqing, Research in Transportation Economics, 35, 1, pp. 41-49, (2012); PLANCO Consulting GmbH, Bundesanstalt für Gewässerkunde, Economical and Ecological Comparison of Transport Modes: Road, Railways, Inland Waterways – Summary of Findings, (2007); PPMC, A global macro roadmap outlining an actionable vision towards decarbonized, resilient transport, Paris Process Mobil. Clim, (2017); Ramirez-Villamil A., Jaegler A., Montoya-Torres J.R., Sustainable local pickup and delivery: The case of Paris, Research in Transportation Business and Management, (2021); Ramirez-Villamil A., Montoya-Torres J.R., Jaegler A., Urban logistics through river: A two-echelon distribution model, Applied Sciences, 13, 12, (2023); Rijkswaterstaat, Ministerie van infrastructuur en milieu, (2011); Schmidt J., Tilk C., Irnich S., Using public transport in a 2-echelon last-mile delivery network, European Journal of Operational Research, (2022); Sheth M., Butrina P., McCormack E., Measuring delivery route cost trade-offs between electric-assist cargo bicycles and delivery trucks in dense urban areas, European Transport Research Review, 11, (2019); Tipagornwong C., Figliozzi M., Analysis of competitiveness of freight tricycle delivery services in urban areas, Transportation Research Record: Journal of the Transportation Research Board, 2410, pp. 76-84, (2014); Tolliver D., Lu P., Benson D., Comparing rail fuel efficiency with truck and waterway, Transportation Research Part D: Transport and Environment, 24, pp. 69-75, (2013); United Nations Environment Programme, Emissions gap report 2022: The closing window - climate crisis calls for rapid transformation of societies, (2022); Van Duin J.H.R., Kortmann R., Van den Boogaard S.L., City logistics through the canals? A simulation study on freight waterborne transport in the inner-city of Amsterdam, International Journal of Urban Sciences, 18, 2, pp. 186-200, (2014); Wiegmans B., Konings R., Intermodal inland waterway transport: Modelling conditions influencing its cost competitiveness, The Asian Journal of Shipping and Logistics, 31, 2, pp. 273-294, (2015); Winkenbach M., Janjevic M., Classification of last‐mile delivery models for e‐commerce distribution: A global perspective. City Logistics 1: New Opportunities and Challenges, pp. 209-229, (2018)","A. Jaegler; Kedge Business School, Paris, 40 Avenue des Terroirs de France, 75012, France; email: anicia.jaegler@kedgebs.com",null,"Elsevier Ltd",{"$nulls":5},2.2105395E7,null,null,null,"English","Res. Transport. Bus. Manage.","Article","Final",null,"Scopus","2-s2.0-85175023861"]
["Li Z.; Gu W.; Meng Q.","Li, Zhen (57191699978); Gu, Wen (58236524300); Meng, Qingfeng (36704082100)","57191699978; 58236524300; 36704082100","The impact of COVID-19 on logistics and coping strategies: A literature review",2023.0,"Regional Science Policy and Practice",15.0,8.0,null,1768.0,1794.0,26.0,0.0,"10.1111/rsp3.12665","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85158144200&doi=10.1111%2frsp3.12665&partnerID=40&md5=765839a812003159529bc67ad42288ef","School of Management, Jiangsu University, 301 Xuefu Road Zhenjiang, 212013, China","Li Z., School of Management, Jiangsu University, 301 Xuefu Road Zhenjiang, 212013, China; Gu W., School of Management, Jiangsu University, 301 Xuefu Road Zhenjiang, 212013, China; Meng Q., School of Management, Jiangsu University, 301 Xuefu Road Zhenjiang, 212013, China","The COVID-19 pandemic has posed many challenges to the continuous development of logistics and has received increasing attention from all sectors of society. This paper systematically reviews 85 related papers; sets the framework of literature analysis on the basis of five fields of logistics: life, e-commerce, healthcare, air transportation, and emergency; systematically composes and analyzes the scope and content of the impact of the COVID-19 pandemic on logistics in different fields; and comprehensively shows the current status of research on the impact of COVID-19 on the continuous development of logistics. On this basis, we combed out the diverse measures of government, enterprises, and related institutions for the logistics problems that have emerged, and put forward some prospects for future research in this field in terms of multi-period strategies, multi-factor evaluation, degree of impacts, and quantification of effects. The work in this paper has some reference value and significance for mitigating or eliminating the negative impact of COVID-19 on the continuous development process of logistics in multiple fields, rationalizing the epidemic response measures and expanding and deepening the research on this topic. © 2023 The Authors. Regional Science Policy & Practice © 2023 Regional Science Association International.","COVID-19; impacts; logistics management; response strategies; transportation",{"$nulls":5},"National Natural Science Foundation of China, NSFC, (71671078, 71971100, 72071096)","The authors would like to acknowledge the professionals who collaborated on this study. The authors would also like to thank all the reviewers who provided suggestions to improve this paper. This work was supported by the National Natural Science Foundation of China (Nos. 72071096, 71971100, 71671078). ",{"$cut":{"chars":18052,"head":"Abudureheman A., Nilupaer A., Optimization model design of cross-border e-commerce transportation path under the background of prevention and control of COVID-19 pneumonia, Soft Computing, 25, pp. 1-9, (2021); Aday S., Aday M.S., Impact of COVID-19 on the food supply chain, Food Quality and Safety, 4, 4, pp. 167-180, (2020); Amicarelli V., Bux C., Food waste in Italian households during the Covid-19 pandemic: a self-reporting approach, Food Security, 13, 1, pp. 25-37, (2021); Amling A., Daugherty P.J., Logistics and distribution innovation in China, International Journal of Physical Distribution and Logistics Management, 50, 3, pp. 323-332, (2020); Anser M.K., Yousaf S.U., Hyder S., Nassani A.A., Zaman K., Abro M.M.Q., Socio-economic and corporate factors and COVID-19 pandemic: a wake-up call, Environmental Science and Pollution Research International, 28, pp. 63215-63226, (2021); Arvidsson N., Pazirandeh A., An ex ante evaluation of mobile depots in cities: a sustainability perspective, International Journal of Sustainable Transportation, 11, 8, pp. 623-632, (2017); Barker J.M., Brau R.I., Shipping surcharges and LSQ: pricing the last mile, International Journal of Physical Distribution and Logistics Management, 50, 6, pp. 667-691, (2020); Bartle J.R., Lutte R.K., Leuenberger D.Z., Sustainability and air freight transportation: lessons from the global pandemic, Sustainability, 13, (2021); Benedict S., Shared mobility intelligence using permissioned Blockchains for smart cities, New Generation Computing, 40, pp. 1-19, (2022); Betcheva L., Erhun F., Jiang H., OM Forum—supply chain thinking in healthcare: lessons and outlooks, Manufacturing & Service Operations Management, 23, 6, pp. 1333-1353, (2021); Borsellino V., Kaliji S., Schimmenti E., COVID-19 drives consumer behaviour and agro-food markets towards healthier and more sustainable patterns. (special issue: Agri-food markets towards sustainable patterns: trends, drivers and challenges.), Sustainability, 12, (2020); Butt A.S., Strategies to mitigate the impact of COVID-19 on supply chain disruptions: a multiple case analysis of buyers and distributors, International Journal of Logistics Management, (2021); Cai M., Luo J., Influence of COVID-19 on manufacturing industry and corresponding countermeasures from supply chain perspective, J Shanghai Jiaotong Univ Sci, 25, 4, pp. 409-416, (2020); Chen X., Guo Y., Yang C., Ding F., Yuan Q., Exploring essential travel during COVID-19 quarantine: evidence from China, Transport Policy, 111, pp. 90-97, (2021); Chen Y., Zheng W., Li W., Huang Y., The robustness and sustainability of port logistics Systems for Emergency Supplies from overseas, Journal of Advanced Transportation, 2020, pp. 1-10, (2020); Choi T.M., Risk analysis in logistics systems: a research agenda during and after the COVID-19 pandemic [article], Transportation Research Part E-Logistics and Transportation Review, 145, (2021); Cui R., Li M., Li Q., Value of high-quality logistics: evidence from a clash between SF express and Alibaba, Management Science, 66, 9, pp. 3879-3902, (2020); De A., Singh S.P., A resilient pricing and service quality level decision for fresh Agri-product supply chain in post-COVID-19 era, International Journal of Logistics Management, (2021); de Campos E.A.R., ten Caten C.S., de Paula I.C., End-of-use and end-of-life medicines-insights from pharmaceutical care process into waste medicines management, Environmental Science and Pollution Research, 28, pp. 58170-58188, (2021); Ding Q., Zhao H.M., Study on e-commerce logistics cost control methods in the context of COVID-19 prevention and control [article; early access], Soft Computing, 9, pp. 11955-11963, (2021); Dorofeev A., Kurganov V., Fillipova N., Pashkova T., Ensuring the integrity of transportation and logistics during the COVID-19 pandemic, Transportation Research Procedia, 50, pp. 96-105, (2020); Duan W., Ma H., Xu D., Analysis of the impact of COVID-19 on the coupling of the material flow and capital flow in a closed-loop supply chain, Advances in Production Engineering & Management, "}},"W. Gu; School of Management, Jiangsu University, Zhenjiang, 301 Xuefu Road, 212013, China; email: 2222010038@stmail.ujs.edu.cn",null,"John Wiley and Sons Inc",{"$nulls":5},1.7577802E7,null,null,null,"English","Reg. Sci. Policy Pract.","Article","Final",null,"Scopus","2-s2.0-85158144200"]
["Lemardelé C.; Pinheiro Melo S.; Cerdas F.; Herrmann C.; Estrada M.","Lemardelé, Clément (57222744565); Pinheiro Melo, Sofia (58035419200); Cerdas, Felipe (56790067900); Herrmann, Christoph (35764295500); Estrada, Miquel (7102245693)","57222744565; 58035419200; 56790067900; 35764295500; 7102245693","Life-cycle analysis of last-mile parcel delivery using autonomous delivery robots",2023.0,"Transportation Research Part D: Transport and Environment",121.0,null,103842.0,null,null,null,1.0,"10.1016/j.trd.2023.103842","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85167965426&doi=10.1016%2fj.trd.2023.103842&partnerID=40&md5=bf6070a116222207b61128fa462b5599","CARNET – Future Mobility Research Hub. C. Jordi Girona 29, Building Nexus II, Office 0A, Barcelona, 08034, Spain; Chair of Sustainable Manufacturing & Life Cycle Engineering, Institute of Machine Tools and Production Technology (IWF), Technische Universität Braunschweig, Langer Kamp 19b, Braunschweig, 38106, Germany; Civil Engineering School of Barcelona, Department of Civil and Environmental Engineering, Universitat Politècnica de Catalunya – Barcelona TECH, C. Jordi Girona 1-3, Building B1, North Campus, Barcelona, 08034, Spain","Lemardelé C., CARNET – Future Mobility Research Hub. C. Jordi Girona 29, Building Nexus II, Office 0A, Barcelona, 08034, Spain, Civil Engineering School of Barcelona, Department of Civil and Environmental Engineering, Universitat Politècnica de Catalunya – Barcelona TECH, C. Jordi Girona 1-3, Building B1, North Campus, Barcelona, 08034, Spain; Pinheiro Melo S., Chair of Sustainable Manufacturing & Life Cycle Engineering, Institute of Machine Tools and Production Technology (IWF), Technische Universität Braunschweig, Langer Kamp 19b, Braunschweig, 38106, Germany; Cerdas F., Chair of Sustainable Manufacturing & Life Cycle Engineering, Institute of Machine Tools and Production Technology (IWF), Technische Universität Braunschweig, Langer Kamp 19b, Braunschweig, 38106, Germany; Herrmann C., Chair of Sustainable Manufacturing & Life Cycle Engineering, Institute of Machine Tools and Production Technology (IWF), Technische Universität Braunschweig, Langer Kamp 19b, Braunschweig, 38106, Germany; Estrada M., Civil Engineering School of Barcelona, Department of Civil and Environmental Engineering, Universitat Politècnica de Catalunya – Barcelona TECH, C. Jordi Girona 1-3, Building B1, North Campus, Barcelona, 08034, Spain","The acceleration of global e-commerce brings an increasing environmental burden to urban last-mile logistics. Autonomous delivery robots (ADRs) have often been considered as an attractive solution to this challenge but, to date, their environmental impact had not been fully assessed. To fill this gap, a life-cycle analysis of two-echelon and business-as-usual distribution strategies is proposed in this paper. To model ADR production, primary data from an actual prototype is used. The mathematical formulation of the use stage is done using the continuous approximation methodology. Finally, some managerial insights are obtained. Two-echelon operations would generate between 60 and 130 gCO2-eq per parcel delivery depending on the considered operation scenario. The ADR fleet production and renewal are the biggest contributors to this total global warming potential (GWP). As a consequence, the three main leverages to decrease the GWP of an ADR-based two-echelon delivery scheme are an improvement of the ADR production processes, the maximization of the robot lifespan (both for mechanical parts and battery), and the optimization of delivery operations to minimize the robot fleet size. © 2023 The Authors","Autonomous delivery robot; Continuous approximation; E-commerce; Last-mile logistics; Life cycle analysis","Environmental impact; Global warming; Life cycle; Robots; Attractive solutions; Autonomous delivery robot; Continous approximation; Environmental burdens; Global e commerces; Global warming potential; Last mile; Last-mile logistic; Life cycle analysis; Parcel delivery; electronic commerce; global warming; life cycle analysis; logistics; optimization; robotics; Electronic commerce",{"$nulls":4},"CARNET; Deutsche Forschungsgemeinschaft, DFG, (PID2020-118641RB-I00); Ministerio de Ciencia e Innovación, MICINN, (MCIN/AEI/10.13039/501100011033)","Funding text 1: The first author would like to personally acknowledge CARNET for the funding of this research article, developed in the framework of his PhD thesis. The second author also thanks the funding by the DFG, German Research Foundation , under Germany's Excellence Strategy - EXC 2163/1 – SE 2 A. ; Funding text 2: The participation of the last author of this paper was made under the project PID2020-118641RB-I00, funded by the Spanish Ministry of Science and Innovation, MCIN/AEI/10.13039/501100011033. ","Allen J., Piecyk M., Piotrowska M., McLeod F., Cherrett T., Ghali K., Austwick M., Understanding the impact of e-commerce on last-mile light goods vehicle activity in urban areas: The case of London, Transp. Res. Part D: Transp. Environ., 61, pp. 325-338, (2018); Alyassi R., Khonji M., Karapetyan A., Chau S.C.K., Elbassioni K., Tseng C.M., Autonomous recharging and flight mission planning for battery-operated autonomous drones, IEEE Trans. Autom. Sci. Eng., 20, 2, pp. 1034-1046, (2022); Baldacci R., Mingozzi A., Roberti R., Recent exact algorithms for solving the vehicle routing problem under capacity and time window constraints, Eur. J. Oper. Res., 218, 1, pp. 1-6, (2012); Bruni M.E., Khodaparasti S., Perboli G., Energy Efficient UAV-Based Last-Mile Delivery: A Tactical-Operational Model With Shared Depots and Non-Linear Energy Consumption, IEEE Access, 11, pp. 18560-18570, (2023); Bunderverband Paket & Express Logistik, Innovationen auf der letzen meile, (2017); Cerdas F., Integrated Computational Life Cycle Engineering for Traction Batteries, (2022); Cerdas F., Juraschek M., Thiede S., Herrmann C., Life cycle assessment of 3D printed products in a distributed manufacturing system, J. Ind. Ecol., 21, S1, pp. S80-S93, (2017); Cerdas F., Titscher P., Bognar N., Schmuch R., Winter M., Kwade A., Herrmann C., Exploring the effect of increased energy density on the environmental impacts of traction batteries: A comparison of energy optimized lithium-ion and lithium-sulfur batteries for mobility applications, Energies, 11, 1, (2018); Cobert A., Environmental comparison of Michelin Tweel and pneumatic tire using life cycle analysis, (2009); (2020); Cox B., Mutel C.L., Bauer C., Mendoza Beltran A., van Vuuren D.P., Uncertain environmental footprint of current and future battery electric vehicles, Environ. Sci. Tech., 52, 8, pp. 4989-4995, (2018); Cucinotta F., Guglielmino E., Sfravara F., Life cycle assessment in yacht industry: A case study of comparison between hand lay-up and vacuum infusion, J. Clean. Prod., 142, pp. 3822-3833, (2017); Daganzo C.F., The length of tours in zones of different shapes, Transp. Res. 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Environ., 85, (2020); Gawron J.H., Keoleian G.A., De Kleine R.D., Wallington T.J., Kim H.C., Life cycle assessment of connected and automated vehicles: sensing and computing subsystem and vehicle level effects, Environ. Sci. Tech., 52, 5, pp. 3249-3256, (2018); Goedkoop M., Heijungs R., Huijbregts M., Schryver A., Struijs J., Zelm R., ReCiPE 2008: A life cycle impact assessment method which comprises harmonised category indicators at the midpoint and the endpoint level, (2013); Hauschild M.Z., Rosenbaum R.K., Olsen S.I., Life Cycle Assessment, (2018); Hawkins T.R., Singh B., Majeau-Bettez G., Stromman A.H., Comparative environmental life cycle assessment of conventional and electric vehicles, J. Ind. Ecol., 17, 1, pp. 53-64, (2013); Hollingsworth J., Copeland B., Johnson J.X., Are e-scooters polluters? The environmental impacts of shared dockless electric scooters, Environ. Res. 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B Methodol., 24, 4, pp. 263-286, (1990); Soysal M., Bloemhof-Ruwaard J.M., Bektas T., The time-dependent two-echelon capacitated vehicle routing problem with environmental considerations, Int. J. Prod. Econ., 164, pp. 366-378, (2015); Stolaroff J.K., Samaras C., O'Neill E.R., Lubers A., Mitchell A.S., Ceperley D., Energy use and life cycle greenhouse gas emissions of drones for commercial package delivery, Nat. Commun., 9, 1, (2018); (2021); Torabbeigi M., Lim G.J., Kim S.J., Drone delivery scheduling optimization considering payload-induced battery consumption rates, J. Intell. Rob. Syst., 97, pp. 471-487, (2020); Whitehead B., Andrews D., Shah A., The life cycle assessment of a UK data centre, Int. J. Life Cycle Assess., 20, 3, pp. 332-349, (2015); Williams L., Sovacool B.K., Foxon T.J., The energy use implications of 5G: Reviewing whole network operational energy, embodied energy, and indirect effects, Renew. Sustain. Energy Rev., 157, (2022); Yowtak K., Imiola J., Andrews M., Cardillo K., Skerlos S., Comparative life cycle assessment of unmanned aerial vehicles, internal combustion engine vehicles and battery electric vehicles for grocery delivery, Procedia CIRP, 90, pp. 244-250, (2020); Zhang Y., Carballo A., Yang H., Takeda K., (2021)","C. Lemardelé; CARNET – Future Mobility Research Hub. C. Jordi Girona 29, Barcelona, Building Nexus II, Office 0A, 08034, Spain; email: clement.lemardele@upc.edu",null,"Elsevier Ltd",{"$nulls":5},1.3619209E7,null,"TRDTF",null,"English","Transp. Res. Part D Transp. Environ.","Article","Final","All Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85167965426"]
["Mishra D.; Obaidat M.S.; Kasi A.; Rewal P.; Mishra A.","Mishra, Dheerendra (57211415687); Obaidat, Mohammad S. (7005628795); Kasi, Abhijit (57456837100); Rewal, Purva (57456837200); Mishra, Ankita (57222464538)","57211415687; 7005628795; 57456837100; 57456837200; 57222464538","Construction of a secure and efficient content key distribution framework for DRM systems",2023.0,"International Journal of Communication Systems",36.0,17.0,"e5605",null,null,null,0.0,"10.1002/dac.5605","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85168578904&doi=10.1002%2fdac.5605&partnerID=40&md5=ff015cfc7fccf30c0dbac4a16e10abf6","Department of Mathematics, Bioinformatics and Computer Applications, Maulana Azad National Institute of Technology, Bhopal, India; Chair & of Computer Science Department and Director of Cybersecurity Center, University of Texas-Permian Basin, Odessa, TX, United States; King Abdullah II School of Information Technology, University of Jordan, Amman, Jordan; School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, China; Department of Mathematics, Govt Motilal Vigyan Mahavidyalaya, Bhopal, India","Mishra D., Department of Mathematics, Bioinformatics and Computer Applications, Maulana Azad National Institute of Technology, Bhopal, India; Obaidat M.S., Chair & of Computer Science Department and Director of Cybersecurity Center, University of Texas-Permian Basin, Odessa, TX, United States, King Abdullah II School of Information Technology, University of Jordan, Amman, Jordan, School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, China; Kasi A., Department of Mathematics, Bioinformatics and Computer Applications, Maulana Azad National Institute of Technology, Bhopal, India; Rewal P., Department of Mathematics, Bioinformatics and Computer Applications, Maulana Azad National Institute of Technology, Bhopal, India; Mishra A., Department of Mathematics, Govt Motilal Vigyan Mahavidyalaya, Bhopal, India","Recent advances in networks and digital technology have provided many user-friendly environments such as telemedicine, e-banking, e-content, and e-commerce. It has revolutionized the multimedia industry and made it accessible anytime and anywhere. However, its limitation also appeared in digital content piracy, which is more prevalent nowadays. Digital rights management (DRM) systems were developed to control the illegal spreading of digital content. Protocols are being developed to enable effective and secure communication in DRM systems. As security and efficiency are essential parameters, the approach should be two birds with one stone; i.e., the protocol should achieve efficiency and security together. Our investigation identified that secure mechanisms either have increased computation/communication overhead or fail to meet specified security criteria when discussing efficient content key delivery mechanisms. So, an efficient protocol design with the right security attributes is required. We have worked on designing a content delivery mechanism keeping in mind the desirable attribute of security and without decreasing overhead. The suggested solution targets “two birds with one stone.” We proved the security of the scheme in the random oracle model. We verify the security against active attacks using the formal simulation tool AVISPA. Detailed analysis is performed for the evaluation of computational and communication overhead. The comparative study is also presented to understand the gains in efficiency and security. © 2023 John Wiley & Sons Ltd.","authentication; computational efficiency; digital rights management; multimedia systems; security","Birds; Copyrights; Electronic commerce; Multimedia systems; Network security; Communication overheads; Delivery mechanism; Digital Rights Management; Digital rights management system; Digital technologies; In networks; Key distribution; Network technologies; Security; User friendly; Computational efficiency",{"$nulls":6},"Mishra D., Rana S., A provably secure content distribution framework for portable DRM systems, J Inform Secur Appl, 61, (2021); Rana S., Mishra D., An authenticated access control framework for digital right management system, Multimed Tools Appl, 80, pp. 25255-25270, (2021); Rana S., Obaidat M.S., Mishra D., Mukhopadhyay S., Sadoun B., Computational efficient authenticated digital content distribution frameworks for DRM systems: Review and outlook, IEEE Syst J, 15, 2, pp. 1586-1593, (2020); Chang C.-C., Yang J.-H., Wang D.-W., An efficient and reliable E-DRM scheme for mobile environments, Expert Syst Appl, 37, 9, pp. 6176-6181, (2010); Chang C.-C., Chang S.-C., Yang J.-H., A practical secure and efficient enterprise digital rights management mechanism suitable for mobile environment, Secur Commun Netw, 6, 8, pp. 972-984, (2013); Mishra D., Das A.K., Mukhopadhyay S., An anonymous and secure biometric-based enterprise digital rights management system for mobile environment, Secur Commun Netw, 9, 16, (2016); Zhang Y.-C., Yang L., Xu P., Zhan Y.-S., A DRM authentication scheme based on smart-card, 2, pp. 202-207, (2009); Yang H.-W., Yang C.-C., Lin W., Enhanced digital rights management authentication scheme based on smart card, IET Inform Secur, 7, 3, pp. 189-194, (2013); Mishra D., Mukhopadhyay S., Cryptanalysis of Yang et al.'s digital rights management authentication scheme based on smart card, pp. 288-297, (2014); Lee C.-C., Li C.-T., Chen Z.-W., Lai Y.-M., Shieh J.-C., An improved E-DRM scheme for mobile environments, J Inform Secur Appl, 39, pp. 19-30, (2018); Lee C.-C., Li C.-T., Chen Z.-W., Lai Y.-M., A biometric-based authentication and anonymity scheme for digital rights management system, Inform Technol Control, 47, 2, pp. 262-274, (2018); Yu S., Park K., Park Y., Kim H., Park Y., A lightweight three-factor authentication protocol for digital rights management system, Peer-to-peer Netw Appl, 13, 5, pp. 1340-1356, (2020); Amin R., Islam S.K.H., Biswas G.P., Giri D., Khan M.K., Kumar N., A more secure and privacy-aware anonymous user authentication scheme for distributed mobile cloud computing environments, Secur Commun Netw, 9, 17, pp. 4650-4666, (2016); Lee C.-C., Li C.-T., Chen Z.-W., Chen S.-D., Lai Y.-M., A novel authentication scheme for anonymity and digital rights management based on elliptic curve cryptography, Int J Electron Secur Digit Forensic, 11, 1, pp. 96-117, (2019); Moon J., Lee D., Jung J., Won D., Improvement of efficient and secure smart card based password authentication scheme, Int J Netw Secur, 19, 6, pp. 1053-1061, (2017); Pan H.-T., Yang H.-W., Hwang M.-S., An enhanced secure smart card-based password authentication scheme, Int J Netw Secur, 22, 2, pp. 358-363, (2020); Khan M.A., Ghani A., Obaidat M.S., Vijayakumar P., Mansoor K., Chaudhry S.A., A robust anonymous authentication scheme using biometrics for digital rights management system, pp. 1-5, (2021); Rewal P., Kasi A., Obaidat M.S., Mishra D., Mishra A., Hsiao K.-F., On the security of content key distribution framework for DRM systems, pp. 1-7, (2022); Fan Q., Chen J., Wen Y., Luo M., Eland: an efficient lightweight anonymous authentication protocol applied to digital rights management system, J Int Technol, 23, 2, pp. 267-278, (2022); Hussain S., Zikria Y.B., Mallah G.A., Et al., An improved authentication scheme for digital rights management system, Wirel Commun Mobile Comput, 2022, pp. 1-11, (2022); Garba A., Dwivedi A.D., Kamal M., Et al., A digital rights management system based on a scalable blockchain, Peer-to-Peer Netw Appl, 14, 5, pp. 2665-2680, (2021); Li T., Wang H., He D., Yu J., Blockchain-based privacy-preserving and rewarding private data sharing for IoT, IEEE Int Things J, 9, 16, pp. 15138-15149, (2022); Shyla S., Sujatha S.S., Efficient secure data retrieval on cloud using multi-stage authentication and optimized blowfish algorithm, J Ambient Intell Humanized Comput, 13, 1, pp. 151-163, (2022); Dolev D., Yao A., On the security of public key protocols, IEEE Trans Inform Theory, 29, 2, pp. 198-208, (1983); Messerges T.S., Dabbish E.A., Sloan R.H., Examining smart-card security under the threat of power analysis attacks, IEEE Trans Comput, 51, 5, pp. 541-552, (2002); Canetti R., Krawczyk H., Universally composable notions of key exchange and secure channels, pp. 337-351, (2002); Chen H.-B., Lee W.-B., Chen T.-H., A novel DRM scheme for accommodating expectations of personal use, Multimed Tools Appl, 77, pp. 23099-23114, (2018); Mishra D., Kasi A., Obaidat M.S., Rewal P., Mishra A., Construction of lightweight content key distribution framework for DRM systems, pp. 863-868, (2021)","D. Mishra; Department of Mathematics, Bioinformatics and Computer Applications, Maulana Azad National Institute of Technology, Bhopal, 462003, India; email: dheerendra@manit.ac.in",null,"John Wiley and Sons Ltd",{"$nulls":5},1.0745351E7,null,"IJCYE",null,"English","Int J Commun Syst","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85168578904"]
["Zhou C.; Li B.","Zhou, Cai (57771146100); Li, Bowen (57349350200)","57771146100; 57349350200","How does e-commerce demonstration city improve urban innovation? Evidence from China",2023.0,"Economics of Transition and Institutional Change",31.0,4.0,null,915.0,940.0,25.0,2.0,"10.1111/ecot.12361","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85148608003&doi=10.1111%2fecot.12361&partnerID=40&md5=e9c83c6be9216adebcc37730c03e0aa9","School of Public Economics and Administration, Shanghai University of Finance and Economics, Shanghai, China; School of Economics, Lanzhou University, Lanzhou, China","Zhou C., School of Public Economics and Administration, Shanghai University of Finance and Economics, Shanghai, China; Li B., School of Economics, Lanzhou University, Lanzhou, China","This paper provides a feasible way to realize urban innovation through the e-commerce pilot. Based on the data of 289 cities in China from 2002 to 2019, we examine the impact of the National E-commerce Demonstration City pilot on urban innovation with a staggered difference-in-differences method. The results show that after becoming a pilot city of National E-commerce Demonstration Cities (NEDC), the quantity and quality of urban innovation have improved. Further, NEDC policy plays a greater role in promoting innovation in economically agglomerated areas, first-and third-tier cities and areas with a higher degree of marketization. Finally, NEDC policy can affect the level of urban innovation by optimizing the allocation of innovation factors, improving the efficiency of credit resource allocation and forming the logistics scale effect. © 2023 European Bank for Reconstruction and Development.","difference-in-differences method; e-commerce city pilot; NEDC policy; urban innovation","China; agglomeration; electronic commerce; innovation; resource allocation; urban economy",{"$nulls":4},"Shanghai University of Finance and Economics, SUFE","We thank Tian Lin (associate editor), one reviewer, Sisi Zhang at Jinan University, Yiping Wu at Shanghai University of Finance and Economics and Changcheng Yao at Southwestern University of Finance and Economics for helpful comments. All errors are our own. The authors did not receive support from any organization for the submitted work. The authors have no financial or proprietary interests in any material discussed in this article.","Abadie A., Imbens G.W., Matching on the estimated propensity score, Econometrica, 84, 2, pp. 781-807, (2016); Akcigit U., Baslandze S., Stantcheva S., Taxation and the international mobility of inventors, The American Economic Review, 106, 10, pp. 2930-2981, (2016); Baron R.M., Kenny D.A., The moderator-mediator variable distinction in social psychological research: Concept strategic and statistical considerations, Journal of Personality and Social Psychology, 51, 6, pp. 1173-1182, (1986); Bernstein F., Song J.S., Zheng X., “Bricks-and-mortar” vs. “clicks-and-mortar”: An equilibrium analysis, European Journal of Operational Research, 187, 3, pp. 671-690, (2008); Bjorkegren D., Grissen D., The potential of digital credit to bank the poor, AEA Papers and Proceedings, 108, pp. 68-71, (2018); Bosetti V., Cattaneo C., Verdolini E., Migration of skilled workers and innovation: A European perspective, Journal of International Economics, 96, 2, pp. 311-322, (2015); Brulhart M., Sbergami F., Agglomeration and growth: Cross-country evidence, Journal of Urban Economics, 65, 1, pp. 48-63, (2009); Caragliu A., Del Bo C.F., Smart innovative cities: The impact of Smart City policies on urban innovation, Technological Forecasting and Social Change, 142, pp. 373-383, (2019); Caragliu A., Del Bo C.F., Kourtit K., Nijkamp P., The winner takes it all: Forward-looking cities and urban innovation, The Annals of Regional Science, 56, 3, pp. 617-645, (2016); Chang K.C., Jackson J., Grover V., E-commerce and corporate strategy: An executive perspective, Information & Management, 40, 7, pp. 663-675, (2003); Chang S.H., Chang H.Y., Study on national innovation capacity and international connection, Innovation, 15, 4, pp. 452-462, (2013); Chatain O., Value creation, competition, and performance in buyer-supplier relationships, Strategic Management Journal, 32, 1, pp. 76-102, (2011); Che Y., Zhang L., Human capital, technology adoption and firm performance: Impacts of China's higher education expansion in the late 1990s, The Economic Journal, 128, 614, pp. 2282-2320, (2018); Cho C., Halford J.T., Hsu S., Ng L., Do managers matter for corporate innovation?, Journal of Corporate Finance, 36, pp. 206-229, (2016); Couture V., Faber B., Gu Y., Liu L., Connecting the countryside via e-commerce: Evidence from China, The American Economic Review: Insights, 3, 1, pp. 35-50, (2021); Dutta N., Sobel R.S., Entrepreneurship and human capital: The role of financial development, International Review of Economics & Finance, 57, pp. 319-332, (2018); Faber B., Trade integration, market size, and industrialization: Evidence from China’s National Trunk Highway System, The Review of Economic Studies, 81, 3, pp. 1046-1070, (2014); Fan F., Dai S., Zhang K., Ke H., Innovation agglomeration and urban hierarchy: Evidence from Chinese cities, Applied Economics, 53, 54, pp. 6300-6318, (2021); Fan G., Xiaolu W., Guangrong M., The contribution of marketization to China’s economic growth, China Economist, 7, 2, (2012); Fassio C., Montobbio F., Venturini A., Skilled migration and innovation in European industries, Research Policy, 48, 3, pp. 706-718, (2019); Figueiredo R., Bahli B., Service business growth: “A spinner innovation model approach, Technological innovation and international competitiveness for business growth, pp. 191-214, (2021); Fu X., Foreign direct investment, absorptive capacity and regional innovation capabilities: Evidence from China, Oxford Development Studies, 36, 1, pp. 89-110, (2008); Graham S., Vishnubhakat S., Of smart phone wars and software patents, The Journal of Economic Perspectives, 27, 1, pp. 67-86, (2013); Gruenhagen J.H., Parker R., Factors driving or impeding the diffusion and adoption of innovation in mining: A systematic review of the literature, Resources Policy, 65, (2020); Guo F., Wang J., Wang F., Kong T., Zhang X., Cheng Z., Measuring the development of digital inclusive finance in China: Indexing and spatial characteristics, China Economics Quarterly, 19, pp. 1401-1418, (2020); Haeussler C., Harhoff D., Mueller E., How patenting informs VC investors–The case of biotechnology, Research Policy, 43, 8, pp. 1286-1298, (2014); Hambleton R., Gross J.S., Governing cities in a global era: Urban innovation, competition, and democratic reform, pp. 15-16, (2007); Hoenig D., Henkel J., Quality signals? The role of patents, alliances, and team experience in venture capital financing, Research Policy, 44, 5, pp. 1049-1064, (2015); Jensen R., The digital provide: Information (technology), market performance, and welfare in the South Indian fisheries sector, Quarterly Journal of Economics, 122, 3, pp. 879-924, (2007); Ji X.Y., Gu N.H., Does the establishment of intellectual property model cities affect innovation quality?, Journal of Finance and Economics, 47, 5, pp. 49-63, (2021); Joss S., Sustainable cities: Governing for urban innovation, (2017); Keller W., Yeaple S.R., Multinational enterprises, international trade, and productivity growth: Firm-level evidence from the United States, The Review of Economics and Statistics, 91, 4, pp. 821-831, (2009); Kou Z., Liu X., FIND report on city and industrial innovation in China, (2017); La Ferrara E., Chong A., Duryea S., Soap operas and fertility: Evidence from Brazil, American Economic Journal: Applied Economics, 4, 4, pp. 1-31, (2012); Li D., Wei Y.D., Wang T., Spatial and temporal evolution of urban innovation network in China, Habitat International, 49, pp. 484-496, (2015); Martin R., Sunley P., Path dependence and regional economic evolution, Journal of Economic Geography, 6, 4, pp. 395-437, (2006); Ning L., Wang F., Li J., Urban innovation, regional externalities of foreign direct investment and industrial agglomeration: Evidence from Chinese cities, Research Policy, 45, 4, pp. 830-843, (2016); Nunn N., Wantchekon L., The slave trade and the origins of mistrust in Africa, The American Economic Review, 101, 7, pp. 3221-3252, (2011); Peri G., Determinants of knowledge flows and their effect on innovation, The Review of Economics and Statistics, 87, 2, pp. 308-322, (2005); Shamim F., The ICT environment, financial sector and economic growth: A cross-country analysis, Journal of Economics Studies, 34, 4, pp. 352-370, (2007); Shang Q., Poon J.P., Yue Q., The role of regional knowledge spillovers on China’s innovation, China Economic Review, 23, 4, pp. 1164-1175, (2012); Shimamoto D., Yamada H., Gummert M., Mobile phones and market information: Evidence from rural Cambodia, Food Policy, 57, pp. 135-141, (2015); Silva C.N., Fiscal austerity and innovation in local governance in Europe, (2016); Tajeddini K., Martin E., Altinay L., The importance of human-related factors on service innovation and performance, International Journal of Hospitality Management, 85, (2020); Tam C., Loureiro A., Oliveira T., The individual performance outcome behind e-commerce: Integrating information systems success and overall trust, Internet Research, 30, 2, pp. 439-462, (2019); Tang C., Guan M., Dou J., Understanding the impact of high speed railway on urban innovation performance from the perspective of agglomeration externalities and network externalities, Technology in Society, 67, (2021); Vakulenko Y., Shams P., Hellstrom D., Hjort K., Service innovation in e-commerce last mile delivery: Mapping the e-customer journey, Journal of Business Research, 101, pp. 461-468, (2019); Wang J., Cai S., The construction of high-speed railway and urban innovation capacity: Based on the perspective of knowledge Spillover, China Economic Review, 63, (2020); Yang Q., Feng B., Song P., Research on agricultural e-commerce public trade platform system, International conference on computer and computing technologies in agriculture, pp. 933-942, (2007); Zhang Y., Long H., Ma L., Tu S., Li Y., Ge D., Analysis of rural economic restructuring driven by e-commerce based on the space of flows: The case of Xiaying village in central China, Journal of Rural Studies, 93, 12, pp. 1-13, (2018); Zhou Y., Li S., Can the innovative-city-pilot policy promote urban innovation? An empirical analysis from China, Journal of Urban Affairs, pp. 1-19, (2021)","B. Li; School of Economics, Lanzhou University, Lanzhou, 730000, China; email: bowenli@126.com",null,"John Wiley and Sons Inc",{"$nulls":5},2.5776975E7,null,null,null,"English","Econ. Trans.  Inst. Change","Article","Final",null,"Scopus","2-s2.0-85148608003"]
["Ouyang Z.; Leung E.K.H.; Cai Y.; Huang G.Q.","Ouyang, Zhiyuan (57329730900); Leung, Eric K.H. (57328966600); Cai, Yiji (57190510708); Huang, George Q. (7403425048)","57329730900; 57328966600; 57190510708; 7403425048","Dynamic community partitioning for e-commerce last mile delivery with time window constraints",2023.0,"Computers and Operations Research",160.0,null,106394.0,null,null,null,0.0,"10.1016/j.cor.2023.106394","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85169292345&doi=10.1016%2fj.cor.2023.106394&partnerID=40&md5=c6f5866737ba11b0871dc838ca0c8205","Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong; Management School, University of Liverpool, Liverpool, United Kingdom; College of Business, Southern University of Science and Technology, Shenzhen, Guangdong, China","Ouyang Z., Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong; Leung E.K.H., Management School, University of Liverpool, Liverpool, United Kingdom; Cai Y., College of Business, Southern University of Science and Technology, Shenzhen, Guangdong, China; Huang G.Q., Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong","Community logistics (CL) is a recently proposed delivery strategy designed to deal with e-commerce last-mile delivery scheduling by dynamically assigning vehicles to designated delivery regions partitioned into “communities”. Since optimizing vehicle routes is not mandatory in the CL spectrum, the delivery solution format and optimization process can be greatly simplified. Nevertheless, abandoning vehicle routes means vehicle arrival time at each customer specified delivery destination is unknown, resulting in the inability of handling time window constraints of e-commerce orders. To expand the application scope of CL, this study introduces community time window, an aggregation of identical or adjacent order time windows. Once the community time window for a delivery community is satisfied, all orders in this community can be received within designated time windows without determining vehicle routes. With this new concept, the application range of the CL is extended to e-commerce last mile delivery contexts where order time window constraints are considered. A dynamic community partitioning problem with the time window is presented based on the Markov decision process (MDP). An efficient heuristic solution framework based on policy function approximation is proposed to solve the MDP model. Numerical results show that the CL is very effective in dealing with the time window constraints of e-commerce orders. © 2023 Elsevier Ltd","Business to customer e-commerce; Dynamic community partitioning problem; Last mile delivery; Logistics; Time window constraints","Electronic commerce; Optimization; Vehicles; Business to customer e commerces; Delivery scheduling; Dynamic communities; Dynamic community partitioning problem; E- commerces; Last mile; Last mile delivery; Partitioning problem; Time window constraint; Time windows; Markov processes",{"$nulls":4},"Guangdong Special Support Talent Program – Innovation and Entrepreneurship Leading Team, (201909010006, 2019BT02S593); HKSAR RGC, (17203518)","The authors would like to acknowledge partial financial supports from funding sources, including the 2019 Guangdong Special Support Talent Program – Innovation and Entrepreneurship Leading Team (China) (2019BT02S593), 2018 Guangzhou Leading Innovation Team Program (201909010006), HKSAR RGC GRF Project (17203518). 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Sci., 53, 1, pp. 167-184, (2019); Wang H., Routing and scheduling for a last-mile transportation system, Transp. Sci., 53, 1, pp. 131-147, (2019); Wang Y., Zhang S., Guan X., Peng S., Wang H., Liu Y., Xu M., Collaborative multi-depot logistics network design with time window assignment, Expert Syst. Appl., 140, (2020); Winkenbach M., Kleindorfer P.R., Spinler S., Enabling urban logistics services at la poste through multi-echelon location-routing, Transp. Sci., 50, 2, pp. 520-540, (2016); Yucenur G.N., Demirel N.C., A new geometric shape-based genetic clustering algorithm for the multi-depot vehicle routing problem, Expert Syst. Appl., 38, 9, pp. 11859-11865, (2011); Zhang W., Yang D., Zhang G., Gen M., Hybrid multiobjective evolutionary algorithm with fast sampling strategy-based global search and route sequence difference-based local search for VRPTW, Expert Syst. Appl., 145, (2020); Zunic E., Donko D., Supic H., Delalic S., (2020)","G.Q. Huang; Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong; email: gq.huang@polyu.edu.hk",null,"Elsevier Ltd",{"$nulls":5},3050548.0,null,"CMORA",null,"English","Comp. Oper. Res.","Article","Final",null,"Scopus","2-s2.0-85169292345"]
["Villa R.; Serrano M.; García T.; González G.","Villa, Rafael (57223124517); Serrano, Marta (58555288100); García, Tomás (58554878000); González, Gema (58554878100)","57223124517; 58555288100; 58554878000; 58554878100","To Green or Not to Green: The E-Commerce-Delivery Question",2023.0,"Sustainability (Switzerland)",15.0,16.0,12161.0,null,null,null,0.0,"10.3390/su151612161","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85169124101&doi=10.3390%2fsu151612161&partnerID=40&md5=73de871b95591767e2d2a7a0915263bd","School of Technology and Science, Camilo José Cela University, Madrid, 28692, Spain","Villa R., School of Technology and Science, Camilo José Cela University, Madrid, 28692, Spain; Serrano M., School of Technology and Science, Camilo José Cela University, Madrid, 28692, Spain; García T., School of Technology and Science, Camilo José Cela University, Madrid, 28692, Spain; González G., School of Technology and Science, Camilo José Cela University, Madrid, 28692, Spain","In an era in which e-commerce has become an integral facet of our lives, the delivery process has evolved into a vital part of online shopping. As the sole tangible interaction in an otherwise digital undertaking, it forms a decisive aspect of consumers’ e-commerce experience. In the face of the ever-growing prevalence of e-commerce, the ecological footprint left by delivery practices has emerged as a pressing concern. This focus is attributed not only to the environmental externalities resulting from e-commerce delivery but also due to the system’s inherent inefficiencies. As the primary beneficiaries of e-commerce, consumers form a pivotal force in driving sustainable delivery initiatives. This study embarks on an exploration of consumers’ attitudes toward environmentally friendly e-commerce-delivery practices. We aim to investigate whether consumers are willing to bear additional costs for assured green deliveries and identify which sustainable practices they perceive as most effective. A survey was conducted among e-commerce users to show their readiness to incur higher costs for green delivery and accept delayed deliveries if they supported sustainability. However, our findings reveal a conflicting scenario. While consumers display a readiness to opt for green deliveries, the price and speed of delivery emerged as more critical considerations. This study also uncovers significant discrepancies in attitudes towards green delivery based on demographic factors, such as gender and generation. Utilizing multivariate logistic regression, the study outlines the main factors that predict a willingness to pay for guaranteed green delivery. This study’s findings stress the need to balance the drive for speed and cost-effectiveness in e-commerce delivery with the urgency to adopt sustainable practices. It underscores the necessity for e-commerce platforms and logistics partners to take the lead in crafting and implementing innovative green delivery solutions while educating and incentivizing consumers to choose sustainable delivery options. © 2023 by the authors.","E-commerce consumers; E-commerce delivery; green logistics; sustainable delivery; sustainable e-commerce","ecological footprint; electronic commerce; exploration; gender; logistics; willingness to pay",{"$nulls":6},"E-Commerce Statistics for Individuals3, (2021); Comercio Electrónico en El Mundo, (2022); Dionysiou G., Fouskas K., Karamitros D., The impact of COVID-19 in e-commerce Effects on consumer purchase behavior, Strategic Innovative Marketing and Tourism in the COVID-19 Era, pp. 199-210, (2021); The Future of Retail: Omnichannel Shopping in 2030, (2021); Munoz-Villamizar A., Velazquez-Martinez J.C., Haro P., Ferrer A., Marino R., The environmental impact of fast shipping ecommerce in inbound logistics operations: A case study in Mexico, J. Clean. Prod, 283, (2021); Nogueira G.P.M., de Assis Rangel J.J., Shimoda E., Sustainable last-mile distribution in B2C e-commerce: Do consumers really care?, Clean. Responsible Consum, 3, (2021); Vakulenko Y., Shams P., Hellstrom D., Hjort K., Service innovation in e-commerce last mile delivery: Mapping the e-customer journey, J. Bus. Res, 101, pp. 461-468, (2019); Heskett J.L., Jones T.O., Loveman G.W., Sasser W.E., Schlesinger L.A., Putting the service-profit chain to work, Harv. Bus. Rev, 72, pp. 164-174, (2008); Pham T.S.H., Ahammad M.F., Antecedents and consequences of online customer satisfaction: A holistic process perspective, Technol. Forecast. Soc. Chang, 124, pp. 332-342, (2017); Mangiaracina R., Marchet G., Perotti S., Tumino A., A review of the environmental implications of B2C E-commerce: A logistics perspective, Int. J. Phys. Distrib. Logist. 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Prod, 258, (2020); Li Y., Feng C., Liu H., Package-free returns: A trend in green ecommerce, Advances in Digital Marketing and Ecommerce, pp. 330-334, (2021); Xie G., Huang L., Apostolidis C., Huang Z., Cai W., Li G., Assessing Consumer Preference for Overpackaging Solutions in E-Commerce, Int. J. Environ. Res. Public Health, 18, (2021); The Cost of E-Commerce Returns for Retailers, (2022); Frei R., Jack L., Krzyzaniak S.-A., Mapping product returns processes in multichannel retailing: Challenges and opportunities, Sustainability, 14, (2022); Zhang Y., Voorhees C.M., Lin C., Chiang J., Hult G.T.M., Calantone R.J., Information search and product returns across mobile and traditional online channels, J. Retail, 98, pp. 260-276, (2022); Frei R., Jack L., Brown S., Product returns: A growing problem for business, society and environment, Int. J. Oper. Prod. Manag, 40, pp. 1613-1621, (2020); Manerba D., Mansini R., Zanotti R., Attended Home Delivery: Reducing last-mile environmental impact by changing customer habits, IFAC-PapersOnLine, 51, pp. 55-60, (2018); Guo X., Lujan Jaramillo Y.J., Bloemhof-Ruwaard J., Claassen G.D.H., On integrating crowdsourced delivery in last-mile logistics: A simulation study to quantify its feasibility, J. Clean. Prod, 241, (2019); Ding Y., Jin M., Service and pricing strategies in online retailing under car-bon emission regulation, J. Clean. Prod, 217, pp. 85-94, (2019); Green & Social Delivery Report. The Future of Ecommerce Lies in Its Sustainability and Sociality, (2018); Buldeo Rai H., Broekaert C., Verlinde S., Macharis C., Sharing is caring: How non-financial incentives drive sustainable e-commerce delivery, Transp. Res. Part D Transp. Environ, 93, (2021); Accenture Chemicals Global Consumer Sustainability Survey 2019, (2019); Rausch T.M., Baier D., Wening S., Does sustainability really matter to consumers? Assessing the importance of online shop and apparel product attributes, J. Retail. Consum. Serv, 63, (2021); E-Commerce in Europe, (2022); Nguyen D.H., de Leeuw S., Dullaert W., Foubert B.P.J., What is the right delivery option for you? Consumer preferences for delivery attributes in online retailing, J. Bus. Logist, 40, pp. 299-321, (2019); Falke A., Schroder N., Hofmann C., The influence of values in sustainable consumption among millennials, J. Bus. Econ, 92, pp. 899-928, (2021); Brand B.M., Rausch T.M., Brandel J., The importance of sustainability aspects when purchasing online: Comparing generation x and generation z, Sustainability, 14, (2022); Charter R.A., Statistical approaches to achieving sufficiently high test score re-liabilities for research purposes, J. Gen. Psychol, 135, pp. 241-251, (2008); Freedman D., Pisani R., Purves R., Statistics (International Student Edition), (2007); Hilbe J.M., Logistic Regression Models, (2009); Pepe M.S., An interpretation for the roc curve and inference using glm procedures, Biometrics, 56, pp. 352-359, (2000); A ‘Natural’ Rise in Sustainability around the World. NielsenIQ, (2019); Randall D.M., Fernandes M.F., The social desirability response bias in ethics research, J. Bus. Ethics, 10, pp. 805-817, (1991); Dabija D.C., Bejan B.M., Dinu V., How sustainability oriented is Generation Z in retail? A literature review, Transform. Bus. Econ, 18, pp. 140-155, (2019)","R. Villa; School of Technology and Science, Camilo José Cela University, Madrid, 28692, Spain; email: rvilla@ucjc.edu",null,"Multidisciplinary Digital Publishing Institute (MDPI)",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85169124101"]
["Cordeau J.-F.; Iori M.; Vezzali D.","Cordeau, Jean-François (57562809600); Iori, Manuel (24502681400); Vezzali, Dario (57216965371)","57562809600; 24502681400; 57216965371","A survey of attended home delivery and service problems with a focus on applications",2023.0,"4OR",21.0,4.0,null,547.0,583.0,36.0,0.0,"10.1007/s10288-023-00556-2","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85177730541&doi=10.1007%2fs10288-023-00556-2&partnerID=40&md5=3fe709d283c7a7a11d3998ed04897c1b","Department of Logistics and Operations Management, HEC Montréal, 3000 Chemin de la Côte-Sainte-Catherine, Montréal, H3T 2A7, Canada; Department of Sciences and Methods for Engineering, University of Modena and Reggio Emilia, Via Amendola 2, Reggio Emilia, 42122, Italy; “Marco Biagi” Foundation, University of Modena and Reggio Emilia, Largo Marco Biagi 10, Modena, 41121, Italy","Cordeau J.-F., Department of Logistics and Operations Management, HEC Montréal, 3000 Chemin de la Côte-Sainte-Catherine, Montréal, H3T 2A7, Canada; Iori M., Department of Sciences and Methods for Engineering, University of Modena and Reggio Emilia, Via Amendola 2, Reggio Emilia, 42122, Italy; Vezzali D., Department of Sciences and Methods for Engineering, University of Modena and Reggio Emilia, Via Amendola 2, Reggio Emilia, 42122, Italy, “Marco Biagi” Foundation, University of Modena and Reggio Emilia, Largo Marco Biagi 10, Modena, 41121, Italy","The research field of attended home delivery (AHD) and attended home service (AHS) problems has experienced fast growing interest in the last two decades, with the rapid growth of online platforms and e-commerce transactions. The COVID-19 pandemic has reinforced that interest, raising further challenges and opportunities that have to be tackled by innovative methodologies and policies. The aim of this work is to provide an extensive literature review on the state of the art for AHD and AHS problems, with a particular focus on real-world applications. A discussion of promising future research directions is also provided. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.","Attended home delivery; Attended home service; Demand management; Integrated demand management and routing; Routing","Attended home delivery; Attended home service; Demand management; Home delivery; Home services; Integrated demand management and routing; Rapid growth; Research fields; Routings; COVID-19",{"$nulls":4},"National Recovery and Resilience Plan, (0001052, 23/06/2022)","The authors gratefully acknowledge financial support under the National Recovery and Resilience Plan (NRRP), Mission 04 Component 2 Investment 1.5–NextGenerationEU, Call for tender n. 3277 dated 30/12/2021, Award Number: 0001052 dated 23/06/2022. ",{"$cut":{"chars":22334,"head":"Abdollahi M., Yang X., Nasri M.I., Fairbank M., Demand management in time-slotted last-mile delivery via dynamic routing with forecast orders, Eur J Oper Res, 309, 2, pp. 704-718, (2023); Agatz N., Campbell A.M., Fleischmann M., Savelsbergh M., Challenges and opportunities in attended home delivery, The Vehicle Routing Problem: Latest Advances and New Challenges, pp. 379-396, (2008); Agatz N., Fleischmann M., van Nunen J., E-fulfillment and multi-channel distribution—a review, Eur J Oper Res, 187, 2, pp. 339-356, (2008); Agatz N., Campbell A.M., Fleischmann M., Savelsbergh M., Time slot management in attended home delivery, Transp Sci, 45, 3, pp. 435-449, (2011); Agatz N., Campbell A.M., Fleischmann M., van Nunen J., Savelsbergh M., Revenue management opportunities for internet retailers, J Revenue Pricing Manag, 12, 2, pp. 128-138, (2013); Agatz N., Fan Y., Stam D., The impact of green labels on time slot choice and operational sustainability, Prod Oper Manag, 30, 7, pp. 2285-2303, (2021); Ali O., Cote J.F., Coelho L.C., Models and algorithms for the delivery and installation routing problem, Eur J Oper Res, 291, 1, pp. 162-177, (2021); Archetti C., Bertazzi L., Recent challenges in routing and inventory routing: E-commerce and last-mile delivery, Netw Int J, 77, 2, pp. 255-268, (2021); Asdemir K., Jacob V.S., Krishnan R., Dynamic pricing of multiple home delivery options, Eur J Oper Res, 196, 1, pp. 246-257, (2009); Azi N., Gendreau M., Potvin J.Y., An exact algorithm for a single-vehicle routing problem with time windows and multiple routes, Eur J Oper Res, 178, 3, pp. 755-766, (2007); Azi N., Gendreau M., Potvin J.Y., An exact algorithm for a vehicle routing problem with time windows and multiple use of vehicles, Eur J Oper Res, 202, 3, pp. 756-763, (2010); Azi N., Gendreau M., Potvin J.Y., A dynamic vehicle routing problem with multiple delivery routes, Ann Oper Res, 199, 1, pp. 103-112, (2012); Azi N., Gendreau M., Potvin J.Y., An adaptive large neighborhood search for a vehicle routing problem with multiple routes, Comput Oper Res, 41, pp. 167-173, (2014); Baldacci R., Hadjiconstantinou E., Mingozzi A., An exact algorithm for the capacitated vehicle routing problem based on a two-commodity network flow formulation, Oper Res, 52, 5, pp. 723-738, (2004); Baldacci R., Mingozzi A., Roberti R., New route relaxation and pricing strategies for the vehicle routing problem, Oper Res, 59, 5, pp. 1269-1283, (2011); Baldacci R., Mingozzi A., Roberti R., Recent exact algorithms for solving the vehicle routing problem under capacity and time window constraints, Eur J Oper Res, 218, 1, pp. 1-6, (2012); Bent R.W., Van Hentenryck P., Scenario-based planning for partially dynamic vehicle routing with stochastic customers, Oper Res, 52, 6, pp. 977-987, (2004); Bertsimas D., Sim M., The price of robustness, Oper Res, 52, 1, pp. 35-53, (2004); The dark side of 15-minute grocery delivery., (2021); Boschetti M.A., Maniezzo V., Matheuristics: using mathematics for heuristic design, 4OR, 20, 2, pp. 173-208, (2022); Boysen N., Fedtke S., Schwerdfeger S., Last-mile delivery concepts: a survey from an operational research perspective, OR Spectr, 43, 1, pp. 1-58, (2021); Braysy O., Gendreau M., Vehicle routing problem with time windows, Transp Sci, 39, 1, pp. 104-118, (2005); Braysy O., Gendreau M., Vehicle routing problem with time windows, Transp Sci, 39, 1, pp. 119-139, (2005); Bredstrom D., Ronnqvist M., Combined vehicle routing and scheduling with temporal precedence and synchronization constraints, Eur J Oper Res, 191, 1, pp. 19-31, (2008); Bruck B.P., Cordeau J.F., Iori M., A practical time slot management and routing problem for attended home services, Omega, 81, pp. 208-219, (2018); Bruck B.P., Castegini F., Cordeau J.F., Iori M., Poncemi T., Vezzali D., A decision support system for attended home services, INFORMS J Appl Anal, 50, 2, pp. 137-152, (2020); Buhler D., Klein R., Neugebauer M., Model-based delivery cost approximation in attended home services, Comput Ind Eng, 98, pp. 78-90, (2016); Campbell A.M., Savelsbergh M., Decision"}},"D. Vezzali; “Marco Biagi” Foundation, University of Modena and Reggio Emilia, Modena, Largo Marco Biagi 10, 41121, Italy; email: dario.vezzali@unimore.it",null,"Institute for Ionics",{"$nulls":5},1.61945E7,null,null,null,"English","4OR","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85177730541"]
["Agnimo V.; Ouhimmou M.; Paquet M.; Montecinos J.","Agnimo, Viviane (58059552300); Ouhimmou, Mustapha (23978646100); Paquet, Marc (36909241400); Montecinos, Julio (57045868200)","58059552300; 23978646100; 36909241400; 57045868200","Integrated strategic and tactical design of multi-echelon city distribution systems with vehicles synchronization: A case of the Greater Montréal area",2023.0,"Computers and Industrial Engineering",183.0,null,109458.0,null,null,null,0.0,"10.1016/j.cie.2023.109458","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85166475969&doi=10.1016%2fj.cie.2023.109458&partnerID=40&md5=06399b77864d1f803032229578b1d1b1","Systems Engineering Department, École de technologie supérieure, 1100 Rue Notre-Dame Ouest, Montréal, H3C 1K3, Québec, Canada","Agnimo V., Systems Engineering Department, École de technologie supérieure, 1100 Rue Notre-Dame Ouest, Montréal, H3C 1K3, Québec, Canada; Ouhimmou M., Systems Engineering Department, École de technologie supérieure, 1100 Rue Notre-Dame Ouest, Montréal, H3C 1K3, Québec, Canada; Paquet M., Systems Engineering Department, École de technologie supérieure, 1100 Rue Notre-Dame Ouest, Montréal, H3C 1K3, Québec, Canada; Montecinos J., Systems Engineering Department, École de technologie supérieure, 1100 Rue Notre-Dame Ouest, Montréal, H3C 1K3, Québec, Canada","The sharp increase in e-commerce volume drives the explosive demand growth for urban parcel delivery. Consequently, more and more logistics service providers (LSP) are moving toward establishing more distribution centres in customers' vicinity within metropolitan areas to ensure fast deliveries to online shoppers and reduce costs. Such LSP seeks to optimize the design of their multi-echelon distribution systems by finding the best satellite locations and vehicle routing solutions. However, since satellites have limited parking and no storage spaces, synchronizing the vehicles' arrival times at these facilities and minimizing their waiting times to be loaded/unloaded are essential in designing multi-echelon distribution systems. This study proposes a new Two Echelons Location Routing problem (2E-LRP) model that incorporates vehicles' temporal synchronization at satellites through minimization and setting of a maximum duration to the second echelon vehicle's waiting times, which had not until now been dealt with in 2E-LRP literature. The 2E-LRP new extension is called Two-Echelon Capacitated Location Routing Problem with Vehicles Synchronization (2E-CLRPVS), and the Binary Variable Fixing (BVF) method is proposed to solve it. To assess the validity and applicability of the 2E-CLRPVS model and the efficiency and robustness of the proposed solving method, we conducted computational experiments for a network with up to 99 customers and 5 five satellites based on data from the Great Montreal area in Canada. We also conducted an extensive sensitivity analysis of some critical parameters of the problem to provide some interesting managerial insights regarding multi-echelon urban distribution network design decision-making. © 2023 Elsevier Ltd","City Logistics; Exact method with binary variable fixing; Satellites location; Synchronization; Transportation plan design; Two-echelon distribution systems","Decision making; Digital storage; Electric power distribution; Geographical distribution; Satellites; Sensitivity analysis; Synchronization; Urban growth; Urban transportation; Binary variables; City logistics; Distribution systems; Exact method with binary variable fixing; Exact methods; Satellite location; Transportation plan design; Transportation plans; Two-echela distribution system; Variable fixing; Location",{"$nulls":4},"Natural Sciences and Engineering Research Council of Canada, NSERC","This research has been supported by the Natural Sciences and Engineering Research Council of Canada (NSERC) . 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Ouhimmou; Systems Engineering Department, École de technologie supérieure, Montréal, 1100 Rue Notre-Dame Ouest, H3C 1K3, Canada; email: mustapha.ouhimmou@etsmtl.ca",null,"Elsevier Ltd",{"$nulls":5},3608352.0,null,"CINDD",null,"English","Comput Ind Eng","Article","Final",null,"Scopus","2-s2.0-85166475969"]
["Li C.; Jiang W.; Yang Y.; Pan S.; Huang G.; Guo L.","Li, Chaojie (57202605973); Jiang, Wensen (57450802000); Yang, Yin (35148742800); Pan, Shirui (55522732400); Huang, Gang (57550751700); Guo, Lijie (57450260000)","57202605973; 57450802000; 35148742800; 55522732400; 57550751700; 57450260000","Predicting Best-Selling New Products in a Major Promotion Campaign Through Graph Convolutional Networks",2023.0,"IEEE Transactions on Neural Networks and Learning Systems",34.0,11.0,null,9102.0,9115.0,13.0,2.0,"10.1109/TNNLS.2022.3155690","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85127046244&doi=10.1109%2fTNNLS.2022.3155690&partnerID=40&md5=26f3e775512f924fc722e13e311021db","University of New South Wales, Department of Electrical Engineering and Telecommunications, Sydney, 2052, NSW, Australia; Alibaba Group, Hangzhou, Zhejiang, 310023, China; Hamad Bin Khalifa University, College of Science and Engineering, Education City, Doha, Qatar; Monash University, Department of Data Science and Artificial Intelligence, Clayton, 3800, VIC, Australia","Li C., University of New South Wales, Department of Electrical Engineering and Telecommunications, Sydney, 2052, NSW, Australia; Jiang W., Alibaba Group, Hangzhou, Zhejiang, 310023, China; Yang Y., Hamad Bin Khalifa University, College of Science and Engineering, Education City, Doha, Qatar; Pan S., Monash University, Department of Data Science and Artificial Intelligence, Clayton, 3800, VIC, Australia; Huang G., Alibaba Group, Hangzhou, Zhejiang, 310023, China; Guo L., Alibaba Group, Hangzhou, Zhejiang, 310023, China","Many e-commerce platforms, such as AliExpress, run major promotion campaigns regularly. Before such a promotion, it is important to predict potential best sellers and their respective sales volumes so that the platform can arrange their supply chains and logistics accordingly. For items with a sufficiently long sales history, accurate sales forecast can be achieved through the traditional statistical forecasting techniques. Accurately predicting the sales volume of a new item, however, is rather challenging with existing methods; time series models tend to overfit due to the very limited historical sales records of the new item, whereas models that do not utilize historical information often fail to make accurate predictions, due to the lack of strong indicators of sales volume among the item's basic attributes. This article presents the solution deployed at Alibaba in 2019, which had been used in production to prepare for its annual 'Double 11' promotion event whose total sales amount exceeded U.S. $\\$ $ 38 billion in a single day. The main idea of the proposed solution is to predict the sales volume of each new item through its connections with older products with sufficiently long sales history. In other words, our solution considers the cross-selling effects between different products, which has been largely neglected in previous methods. Specifically, the proposed solution first constructs an item graph, in which each new item is connected to relevant older items. Then, a novel multitask graph convolutional neural network (GCN) is trained by a multiobjective optimization-based gradient surgery technique to predict the expected sales volumes of new items. The designs of both the item graph and the GCN exploit the fact that we only need to perform accurate sales forecasts for potential best-selling items in a major promotion, which helps reduce computational overhead. Extensive experiments on both proprietary AliExpress data and a public dataset demonstrate that the proposed solution achieves consistent performance gains compared to existing methods for sales forecast.  © 2012 IEEE.","Cross-selling effect; graph convolutional network; multiobjective optimization; multitask learning (MTL); sales forecast","Convolution; Deep learning; Directed graphs; Job analysis; Multiobjective optimization; Neural networks; Sales; Supply chains; Time series analysis; Convolutional networks; Cross-selling; Cross-selling effect; Deep learning; Graph convolutional network; Multi-objectives optimization; Multitask learning; Predictive models; Sale forecast.; Sales forecasts; Task analysis; Time-series analysis; article; convolutional neural network; electronic commerce; forecasting; human; multiobjective optimization; prediction; time series analysis; Forecasting",{"$nulls":4},"Hunan Provincial Science and Technology Research Foundation of China, (2019RS1003); Australian Research Council, ARC, (DE210100274, DP200101197); Digital Grid Futures Institute, University of New South Wales Canberra, DGFI","This work was supported in part by the ARC Discovery Project under Grant DP200101197 and Grant DE210100274, in part by the UNSW Digital Grid Futures Institute, and in part by Hunan Provincial Science and Technology Research Foundation of China under Grant 2019RS1003.","Seeger M.W., Salinas D., Flunkert V., Bayesian intermittent demand forecasting for large inventories, Proc. 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Berlin, Germany: Springer-Verlag, pp. 377-384, (2011); Bandara K., Shi P., Bergmeir C., Hewamalage H., Tran Q., Seaman B., Sales demand forecast in e-commerce using a long shortterm memory neural network methodology, Neural Information Processing, pp. 462-474, (2019); Christ M., Braun N., Neuffer J., Kempa-Liehr A.W., Time series FeatuRe extraction on basis of scalable hypothesis tests (tsfresh- A Python package), Neurocomputing, 307, pp. 72-77, (2018); He X., Chua T.-S., Neural factorization machines for sparse predictive analytics, Proc. 40th Int. ACM SIGIR Conf. Res. Develop. Inf. Retr., pp. 355-364, (2017); Hochreiter S., Schmidhuber J., Long short-term memory, Neural Comput, 9, 8, pp. 1735-1780, (1997); Li Q., Han Z., Wu X.-M., Deeper insights into graph convolutional networks for semi-supervised learning, Proc. 32nd AAAI Conf. Artif. Intell, pp. 1-8, (2018); Van Der Maaten L., Hinton G., Visualizing data using t-SNE, J. Mach. Learn. Res, 9, pp. 2579-2605, (2008)","W. Jiang; Alibaba Group, Zhejiang, Hangzhou, 310023, China; email: wensen.jws@alibaba-inc.com",null,"Institute of Electrical and Electronics Engineers Inc.",{"$nulls":5},"2162237X",null,null,3.5320107E7,"English","IEEE Trans. Neural Networks Learn. Sys.","Article","Final",null,"Scopus","2-s2.0-85127046244"]
["Buldeo Rai H.; Marcher P.","Buldeo Rai, Heleen (57195135422); Marcher, Paul (58522267800)","57195135422; 58522267800","Mobility and the mall: Three solution pathways for efficient and sustainable omnichannel goods transportation for a mall in paris",2023.0,"Research in Transportation Economics",100.0,null,101331.0,null,null,null,0.0,"10.1016/j.retrec.2023.101331","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85166649050&doi=10.1016%2fj.retrec.2023.101331&partnerID=40&md5=a749fa5867ce0254e6457e08dd42636b","Logistics City Chair, University Gustave Eiffel, Paris, France","Buldeo Rai H., Logistics City Chair, University Gustave Eiffel, Paris, France; Marcher P., Logistics City Chair, University Gustave Eiffel, Paris, France","Urban shopping malls do not only depend on consumer mobility to operate and thrive, but goods mobility as well. With the emergence of omnichannel retail, stores are now multifunctional hubs accommodating collection, delivery, and return of online purchases. As a consequence, goods transportation requirements for stores have intensified. This impacts the malls in which they are localized as well. The scientific literature that covers goods mobility and malls is fairly limited. It has not yet explored the efficiency and sustainability of goods transportation to and from malls in the omnichannel era. To perform a state of practice and suggest improvements, we combine case study and exploratory research for the Beaugrenelle mall in Paris. The research demonstrates three operational issues. First, chaotic supply operations resulting in alternative practices that expose delivery workers to financial, security, and ergonomic risks. Second, patchy delivery practices that are not aligned with the regular supplies. Third, a lack of storage. In response, we explore three solution pathways: i.e., introducing dedicated staff, engaging third parties, and implementing intelligent technology. In doing so, we intend to provide elements for discussion for the mall operator, the retail tenants, their logistics service providers and the city moving forward. © 2023 Elsevier Ltd","City logistics; e-commerce; Omnichannel retail; Shopping centers; Shopping malls; Urban freight transport; Urban goods movements",{"$nulls":7},"Alho A., Oh S., Seshadri R., Dalla Chiara G., Chong W.H., Sakai T., Cheah L., Ben-Akiva M., An agent-based simulation assessment of freight parking demand management strategies for large urban freight generators, (2022); Allen J., Browne M., Woodburn A., Leonardi J., The role of urban consolidation centres in sustainable freight transport, Transport Reviews, 32, 4, pp. 473-490, (2012); Apur, Le e-commerce dans la métropole du grand Paris. 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Towards a carbon neutral city, 100% renewable energies, resilient, fair and inclusive, (2018); Le CNCC présente les résultats d'une étude réalisée par EY : Évaluation comparée de l'impact environnemental et social des centres commerciaux, Communiqué de presse, (2021); Dalla Chiara G., Cheah L., Data stories from urban loading bays, European Transport Research Review, 9, 50, (2017); Dalla Chiara G., Cheah L., Azevedo C.L., Ben-Akiva M.E., A policy-sensitive model of parking choice for commercial vehicles in urban areas, Transportation Science, 54, 3, pp. 606-630, (2020); Eidhammer O., Johansen B.G., Andersen J., Comparing deliveries to on-street consignees and consignees located at shopping centers, Transportation Research Procedia, 14, pp. 1221-1229, (2016); Erkip F., Ozuduru B.H., Retail development in Turkey: An account after two decades of shopping malls in the urban scene, Progress in Planning, 102, pp. 1-33, (2015); Goss J., The “magic of the mall”: An analysis of form, function, and meaning in the contemporary retail built environment, Annals of the Association of American Geographers, 83, 1, pp. 18-47, (1993); Hagberg J., Jonsson A., Egels-Zanden N., Retail digitalization: Implications for physical stores, Journal of Retailing and Consumer Services, 39, pp. 264-269, (2017); Holguin-Veras J., Aros-Vera F., Browne M., Agent interactions and the response of supply chains to pricing and incentives, Economics of Transportation, 4, 3, pp. 147-155, (2015); Jaller M., Wang X.C., Holguin-Veras J., Large urban freight traffic generators: Opportunities for city logistics initiatives, Journal of Transport and Land Use, 8, 1, pp. 51-67, (2015); Kang J., Kong H., Lin Z., Dang A., Mapping the dynamics of electric vehicle charging demand within Beijing's spatial structure, Sustainable Cities and Society, 76, (2022); Kim H., Goodchild A., Boyle L.N., Empirical analysis of commercial vehicle dwell times around freight-attracting urban buildings in downtown Seattle, Transportation Research Part A: Policy and Practice, 147, pp. 320-338, (2021); Nesterova N., Rooijen T.V., Talen S., Verlinde S., Kin B., Dablanc L., Liu Z., Marcucci E., Gatta V., McLeod F., Eidhammer O., Orving T., Leonardi J., CITYLAB Deliverable D 5.4 Sustainability analysis of the CITYLAB solutions, (2017); Orving T., Fossheim K., Eidhammer O., Andersen J., Leonardi J., van Rooijen T., Nesterova N., Talen S., Kin B., Verlinde S., Cherrett T., McLeod F., Marcucci E., Gatta V., Romagnoli G.C., Dablanc L., Liu Z., Lazarevic N., Rouhier J., CITYLAB deliverable 5.3 (2018), Impact and process assessment of the seven CITYLAB implementations, (2018); Paddeu D., Fadda P., Fancello G., Parkhurst G., Ricci M., Reduced urban traffic and emissions within urban consolidation centre schemes: The case of bristol, Transportation Research Procedia, 3, pp. 508-517, (2014); Rodriguez-Torrico P., San Jose Cabezudo R., San-Martin S., Tell me what they are like and I will tell you where they buy. An analysis of omnichannel consumer behavior, Computers in Human Behavior, 68, pp. 465-471, (2017); Rosenzweig C., Solecki W., Hammer S.A., Mehrotra S., Cities lead the way in climate–change action, Nature, 467, 7318, pp. 909-911, (2010); Sardi D.L., Bona K., Developing a mesoscopic simulation model for examination of freight traffic of shopping malls in Budapest, 2017 smart cities symposium prague, SCSP 2017 - IEEE proceedings, (2017); Sardi D.L., Bona K., A geometrical structure-based new approach for city logistics system planning with cargo bikes and its application for the shopping malls of budapest, Applied Sciences, 11, 8, (2021); Song R., Lau C., Luo X., Zhao L., Lau H.C., Coordinated delivery to shopping malls with limited docking capacity, Transportation Science, 56, 2, pp. 501-527, (2022); Triantafyllou M.K., Cherrett T.J., Browne M., Urban freight consolidation centers: Case study in the UK retail sector, Transportation Research Record: Journal of the Transportation Research Board, 2411, pp. 34-44, (2014)","H. Buldeo Rai; Logistics City Chair, University Gustave Eiffel, Paris, France; email: heleen.buldeo.rai@vub.be",null,"Emerald Publishing",{"$nulls":5},7398859.0,null,null,null,"English","Res. Transp. Econ.","Article","Final",null,"Scopus","2-s2.0-85166649050"]
["Ut-Tha V.","Ut-Tha, Veenarat (57316292000)",5.7316292E10,"Pioneering Eco-Cart: Carbon Reduction Solutions for Thai Online Shoppers",2023.0,"Management and Marketing",18.0,4.0,null,515.0,536.0,21.0,0.0,"10.2478/mmcks-2023-0028","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85182669138&doi=10.2478%2fmmcks-2023-0028&partnerID=40&md5=5b3c4993c1777b8098d9d76105f72a53","Faculty of Environment and Resource Studies, Mahidol University, Nakorn Pathom, Thailand","Ut-Tha V., Faculty of Environment and Resource Studies, Mahidol University, Nakorn Pathom, Thailand","This research aims to identify effective strategies for reducing carbon emissions in online shopping by examining the perspectives of Thai consumers and utilizing sociodemographic data to anticipate their choices for carbon mitigation. The study encompasses eco-logistics, last-mile innovations, and responsible consumer behavior. Data collected from a questionnaire gathered responses from 800 participants across diverse regions, resulting in a 96.50% response rate. Using a multinomial logit model in Stata 15, the analysis reveals factors influencing consumer decisions. Eco-logistics is the preferred choice for 35.74% of individuals aiming to reduce carbon emissions from online shopping. Regular purchases of clothing and shoes correlate with a 46% higher likelihood of selecting eco-logistics, while responsible purchasing shows a 33.03% adoption rate. Last-mile innovations, chosen by 31.23%, appeal to higher-income individuals, while women, older age groups (46+), and those with higher education lean toward eco-logistics. Higher education enhances responsible purchasing, influenced by critical thinking, income, and professional networks. Additionally, suburban consumers prefer eco-logistics due to longer distances, while urban residents opt for last-mile innovations. Addressing these challenges facilitates environmentally conscious practices in the e-commerce supply chain, providing insights for policymakers and businesses to formulate sustainable and equitable strategies. © 2023 Veenarat Ut-Tha, published by Sciendo.","carbon emissions; carbon reduction; eco-logistics; last-mile innovations; online shopping; responsible consumer",{"$nulls":7},"Abukhader S.M., Jonson G., E-commerce and the environment: A gateway to the renewal of greening supply chains, International Journal of Technology Management, 28, 2, pp. 274-288, (2004); Ageron B., Gunasekaran A., Spalanzani A., Sustainable supply management: An empirical study, International Journal of Production Economics, 140, 1, pp. 168-182, (2012); Auclair O., Burgos S.A., Carbon footprint of Canadian self-selected diets: Comparing intake of foods, nutrients, and diet quality between low- and high-greenhouse gas emission diets, Journal of Cleaner Production, 316, (2021); Awwad M., Shekhar A., Iyer A., Sustainable Last-Mile logistics operation in the Era of E-commerce, Proceedings of the International Conference on Industrial Engineering and Operations Management, (2018); Bak I., Szczecinska B., Cheba K., The impact of transport on the quality of the environment in cities of Poland-a statistical analysis, Transportation Research Procedia, 39, pp. 24-33, (2019); Birney C.I., Franklin K.F., Davidson F.T., Webber M.E., An assessment of individual foodprints attributed to diets and food waste in the United States, Environmental Research Letters, 12, 10, (2017); Bozzi C., Neves M., Mont'Alvao C., Fashion E-Tail and the Impact of Returns: Mapping Processes and the Consumer Journey towards More Sustainable Practices, Sustainability, 14, 9, (2022); Brown J.R., Guiffrida A.L., Carbon emissions comparison of last mile delivery versus customer pickup, International Journal of Logistics Research and Applications, 17, 6, pp. 503-521, (2014); Caspersen E., Navrud S., The sharing economy and consumer preferences for environmentally sustainable last mile deliveries, Transportation Research Part D: Transport and Environment, 95, (2021); Caspersen E., Navrud S., Bengtsson J., Act locally? 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Consumer preferences for delivery attributes in online retailing, Journal of Business Logistics, 40, 4, pp. 299-321, (2019); Greenhouse Gas Emissions in the Road Transport Sector, (2023); Oliveira L.K.D., Morganti E., Dablanc L., Oliveira R.L.M.D., Analysis of the potential demand of automated delivery stations for e-commerce deliveries in Belo Horizonte, Brazil, Research in Transportation Economics, 65, pp. 34-43, (2017); Patella S.M., Grazieschi G., Gatta V., Marcucci E., Carrese S., The adoption of green vehicles in last mile logistics: A systematic review, Sustainability, 13, 1, (2020); Poon W.C., Tung S.E.H., The rise of online food delivery culture during the COVID-19 pandemic: An analysis of intention and its associated risk, European Journal of Management and Business Economics, (2022); Ranieri L., Digiesi S., Silvestri B., Roccotelli M., A review of last mile logistics innovations in an externalities cost reduction vision, Sustainability, 10, 3, (2018); Shaw N., Eschenbrenner B., Baier D., Online shopping continuance after COVID-19: A comparison of Canada, Germany and the United States, Journal of Retailing and Consumer Services, 69, (2022); Soler J.R.L., Christidis P., Vassallo J.M., Teleworking and online shopping: Socio-economic factors affecting their impact on transport demand, Sustainability, 13, 13, (2021); E-commerce Share of Retail Sales in Thailand 2015-2025, (2023); Thogersen J., Consumer behavior and climate change: Consumers need considerable assistance, Current Opinion in Behavioral Sciences, 42, pp. 9-14, (2021); Consumer Online Shopping Behavior, (2021); Ensure Sustainable Consumption and Production Patterns, (2023); SDG Investor Map Thailand 2022, (2022); Van Loon P., Deketele L., Dewaele J., McKinnon A., Rutherford C., A comparative analysis of carbon emissions from online retailing of fast moving consumer goods, Journal of Cleaner Production, 106, pp. 478-486, (2015); Van Rensburg M.L., Nkomo S.P.L., Mkhize N.M., Life cycle and End-of-Life management options in the footwear industry: A review, Waste Management & Research, 38, 6, pp. 599-613, (2020); Vasan A., Sood B., Pecht M., Carbon footprinting of electronic products, Applied Energy, 136, pp. 636-648, (2014); Wakeland W., Cholette S., Venkat K., Food transportation issues and reducing carbon footprint, Green Technologies in Food Production and Processing, pp. 211-236, (2012); Wassmuth K., Kohler C., Agatz N., Fleischmann M., Demand management for attended home delivery-a literature review, European Journal of Operational Research, (2023); Weltevreden J., B2C e-commerce logistics: The rise of collection-and-delivery points in the Netherlands, International Journal of Retail & Distribution Management, 36, 8, pp. 638-660, (2008); Wilson C., Pettifor H., Cassar E., Kerr L., Wilson M., The potential contribution of disruptive low-carbon innovations to 1.5 C climate mitigation, Energy Efficiency, 12, pp. 423-440, (2019); Thailand Economic Monitor-building Back Greener: The Circular Economy (English), (2022); Xiao Z., Wang J.J., Liu Q., The impacts of final delivery solutions on e-shopping usage behaviour: The case of Shenzhen, China, International Journal of Retail & Distribution Management, 46, 1, pp. 2-20, (2018)","V. Ut-Tha; Faculty of Environment and Resource Studies, Mahidol University, Nakorn Pathom, Thailand; email: veenarat.utt@mahidol.ac.th",null,"Sciendo",{"$nulls":5},1.8420206E7,null,null,null,"English","Manage. Mark.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85182669138"]
["Beckers J.; Cardenas I.; Le Pira M.; Zhang J.","Beckers, Joris (57191037901); Cardenas, Ivan (57191038157); Le Pira, Michela (56780165600); Zhang, Jia (58414999200)","57191037901; 57191038157; 56780165600; 58414999200","Exploring Logistics-as-a-Service to integrate the consumer into urban freight",2023.0,"Research in Transportation Economics",101.0,null,101354.0,null,null,null,0.0,"10.1016/j.retrec.2023.101354","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85172882662&doi=10.1016%2fj.retrec.2023.101354&partnerID=40&md5=ecccc2e73ad1d1d8fdb653a2243ecab2","Department of Transport and Regional Economics, University of Antwerp, Prinsstraat 13, Antwerpen, 2000, Belgium; Division of Service Management and Logistics, Chalmers University of Technology, Chalmersplatsen 4, Gothenburg, 41296, Sweden; Department of Civil Engineering and Architecture, University of Catania, Via Santa Sofia 64, Catania, 95123, Italy","Beckers J., Department of Transport and Regional Economics, University of Antwerp, Prinsstraat 13, Antwerpen, 2000, Belgium; Cardenas I., Division of Service Management and Logistics, Chalmers University of Technology, Chalmersplatsen 4, Gothenburg, 41296, Sweden; Le Pira M., Department of Civil Engineering and Architecture, University of Catania, Via Santa Sofia 64, Catania, 95123, Italy; Zhang J., Department of Transport and Regional Economics, University of Antwerp, Prinsstraat 13, Antwerpen, 2000, Belgium","E-commerce established the consumer as a freight actor. This new reality in the e-commerce supply chain holds economic, social, and environmental opportunities. First, logistics service providers can capitalize on the willingness to pay of consumers with tailored logistics services. Second, consumers can be confronted with the correct costs of delivery options, raising awareness and influencing their choices' sustainability. Third, policymakers can steer the consumer directly, nudging their behaviour to reach urban freight policy objectives. Until now, the lack of interaction between the logistics service provider and the consumer prevented exploiting these opportunities. In this paper, we look at passenger transport, specifically the concept of Mobility-as-a-Service (MaaS), for inspiration on how to integrate the consumer into the logistics market. We propose conceptualizations for a Logistics-as-a-Service (LaaS) platform with different levels of integration and discuss the role of various stakeholders. We conclude with a suite of research questions that deserve attention to develop further the LaaS idea and its proof of concept for consumer logistics. © 2023","Consumer logistics; LaaS; Last mile; MaaS; Urban freight",{"$nulls":5},"European Union's Horizon Europe research and innovation programme, (101069892); United Kingdom Research and Innovation; UK Research and Innovation, UKRI, (10063223, 10065303, 10068295, 10069608); European Climate, Infrastructure and Environment Executive Agency, CINEA","Funding text 1: “This work has been supported by the GREEN-LOG project that has received funding from the European Union's Horizon Europe research and innovation programme under Grant Agreement No 101069892 and from the United Kingdom Research and Innovation ( UKRI ) agency [Grant Reference Numbers: 10063223 , 10068295 , 10069608 and 10065303 ]. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union, the European Climate, Infrastructure and Environment Executive Agency (CINEA) or the UKRI. Neither the European Union nor the granting authorities can be held responsible for them.”; Funding text 2: “This work has been supported by the GREEN-LOG project that has received funding from the European Union's Horizon Europe research and innovation programme under Grant Agreement No 101069892 and from the United Kingdom Research and Innovation (UKRI) agency [Grant Reference Numbers: 10063223, 10068295, 10069608 and 10065303]. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union, the European Climate, Infrastructure and Environment Executive Agency (CINEA) or the UKRI. Neither the European Union nor the granting authorities can be held responsible for them.”","Agatz N., Fan Y., Stam D., Going green: The effect of green labels on delivery time slot choices, (2020); Allen J., Piecyk M., Piotrowska M., McLeod F., Cherrett T., Ghali K., Nguyen T., Bektas T., Bates O., Friday A., Wise S., Austwick M., Understanding the impact of e-commerce on last-mile light goods vehicle activity in urban areas: The case of London, Transportation Research Part D: Transport and Environment, (2017); Allen J., Piecyk M., Piotrowska M., McLeod F., Cherrett T., Ghali K., Nguyen T., Bektas T., Bates O., Friday A., Wise S., Austwick M., Understanding the impact of e-commerce on last-mile light goods vehicle activity in urban areas: The case of London, Transportation Research Part D: Transport and Environment, 61, pp. 325-338, (2018); Alyavina E., Nikitas A., Njoya E.T., Mobility as a service (MaaS): A thematic map of challenges and opportunities, Research in Transportation Business and Management, 43, February, (2022); Ambrosino G., Nelson J.D., Boero M., Pettinelli I., Enabling intermodal urban transport through complementary services: From flexible mobility services to the shared use mobility agency: Workshop 4. 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An exploration of pandemic-driven behavioural changes in self-collection users, International Journal of Environmental Research and Public Health, 18, 16, (2021); Whittle C., Whitmarsh L., Hagger P., Morgan P., Parkhurst G., User decision-making in transitions to electrified, autonomous, shared or reduced mobility, Transportation Research Part D: Transport and Environment, 71, pp. 302-319, (2019); Winkenbach M., Janjevic M., Classification of last-mile delivery models for e-commerce distribution - a global perspective, The 10th International Conference on City Logistics, pp. 162-176, (2017)","J. Beckers; Department of Transport and Regional Economics, University of Antwerp, Antwerpen, Prinsstraat 13, 2000, Belgium; email: joris.beckers@uantwerpen.be",null,"Emerald Publishing",{"$nulls":5},7398859.0,null,null,null,"English","Res. Transp. Econ.","Article","Final","All Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85172882662"]
["Ahsini Y.; Díaz-Masa P.; Inglés B.; Rubio A.; Martínez A.; Magraner A.; Conejero J.A.","Ahsini, Yusef (58553399100); Díaz-Masa, Pablo (58618040000); Inglés, Belén (58616404000); Rubio, Ana (58617761700); Martínez, Alba (58711350700); Magraner, Aina (58618040100); Conejero, J. Alberto (57219968950)","58553399100; 58618040000; 58616404000; 58617761700; 58711350700; 58618040100; 57219968950","The Electric Vehicle Traveling Salesman Problem on Digital Elevation Models for Traffic-Aware Urban Logistics",2023.0,"Algorithms",16.0,9.0,402.0,null,null,null,0.0,"10.3390/a16090402","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85172269854&doi=10.3390%2fa16090402&partnerID=40&md5=72fbfe4fe7db05790da779b43c44d0dd","Escuela Técnica Superior de Ingeniería Informática, Universitat Politècnica de València, Valencia, 46022, Spain; Instituto Universitario Matemática Pura y Aplicada, Universitat Politècnica de València, Valencia, 46022, Spain","Ahsini Y., Escuela Técnica Superior de Ingeniería Informática, Universitat Politècnica de València, Valencia, 46022, Spain; Díaz-Masa P., Escuela Técnica Superior de Ingeniería Informática, Universitat Politècnica de València, Valencia, 46022, Spain; Inglés B., Escuela Técnica Superior de Ingeniería Informática, Universitat Politècnica de València, Valencia, 46022, Spain; Rubio A., Escuela Técnica Superior de Ingeniería Informática, Universitat Politècnica de València, Valencia, 46022, Spain; Martínez A., Escuela Técnica Superior de Ingeniería Informática, Universitat Politècnica de València, Valencia, 46022, Spain; Magraner A., Escuela Técnica Superior de Ingeniería Informática, Universitat Politècnica de València, Valencia, 46022, Spain; Conejero J.A., Instituto Universitario Matemática Pura y Aplicada, Universitat Politècnica de València, Valencia, 46022, Spain","With the increasing demand for online shopping and home delivery services, optimizing the routing of electric delivery vehicles in urban areas is crucial to reduce environmental pollution and improve operational efficiency. To address this opportunity, we optimize the Steiner Traveling Salesman Problem (STSP) for electric vehicles (EVs) in urban areas by combining city graphs with topographic and traffic information. The STSP is a variant of the traditional Traveling Salesman Problem (TSP) where it is not mandatory to visit all the nodes present in the graph. We train an artificial neural network (ANN) model to estimate electric consumption between nodes in the route using synthetic data generated with historical traffic simulation and topographical data. This allows us to generate smaller-weighted graphs that transform the problem from an STSP to a normal TSP where the 2-opt optimization algorithm is used to solve it with a Nearest Neighbor (NN) initialization. Compared to the approach of optimizing routes based on distance, our proposed algorithm offers a fast solution to the STSP for EVs (EV-STSP) with routes that consume 17.34% less energy for the test instances generated. © 2023 by the authors.","artificial neural networks; digital elevation model; electric vehicle routing; node filtering; Steiner Traveling Salesman Problem","Digital instruments; Electric vehicles; Geomorphology; Graph theory; Neural networks; Routing algorithms; Surveying; Traveling salesman problem; Digital elevation model; Electric vehicle routing; Home delivery services; Node filtering; Online shopping; Steiner; Steiner traveling salesman problem; Traffic aware; Urban areas; Urban logistics; Vehicle routing",{"$nulls":4},"Ministerio de Ciencia e Innovación, MICINN; European Regional Development Fund, ERDF; Agencia Estatal de Investigación, AEI, (0011033)","J.A.C is supported by grant PID2022-138860NB-I00 funded by MCIN/AEI/ 10.13039/50110 0011033 and, as appropriate, by “ERDF A way of making Europe”, by the “European Union” or by the “European Union NextGenerationEU/PRTR”.","Basso R., Kulcsar B., Egardt B., Lindroth P., Sanchez-Diaz I., Energy consumption estimation integrated into the electric vehicle routing problem, Transp. Res. D-Transp. Environ, 69, pp. 141-167, (2019); Pelletier S., Jabali O., Laporte G., The electric vehicle routing problem with energy consumption uncertainty, Trasnp. Res. B-Meth, 126, pp. 225-255, (2019); Conejero J., Jordan C., Sanabria-Codesal E., An iterative algorithm for the management of an electric car-rental service, J. Appl. Math, 2014, (2014); Conejero J., Jordan C., Sanabria-Codesal E., An algorithm for self-organization of driverless vehicles of a car-rental service, Nonlinear Dyn, 84, pp. 107-114, (2016); Yang S., Li M., Lin Y., Tang T., Electric vehicle’s electricity consumption on a road with different slope, Phys. A, 402, pp. 41-48, (2014); Graser A., Asamer J., Dragaschnig M., How to reduce range anxiety? The impact of digital elevation model quality on energy estimates for electric vehicles, GI Forum 2014. Geospatial Innovation for Society, pp. 165-174, (2014); Graser A., Asamer J., Ponweiser W., The elevation factor: Digital elevation model quality and sampling impacts on electric vehicle energy estimation errors, Proceedings of the 2015 International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS), pp. 81-86; Evtimov I., Ivanov R., Sapundjiev M., Energy consumption of auxiliary systems of electric cars, MATEC Web Conf, 133, (2017); Muren, Wu J., Zhou L., Du Z., Lv Y., Mixed steepest descent algorithm for the traveling salesman problem and application in air logistics, Transp. Res. E-Log, 126, pp. 87-102, (2019); Baniasadi P., Foumani M., Smith-Miles K., Ejov V., A transformation technique for the clustered generalized traveling salesman problem with applications to logistics, Eur. J. Oper. Res, 285, pp. 444-457, (2020); Bay M., Limbourg S., TSP model for electric vehicle deliveries, considering speed, loading and road grades, Proceedings of the Sixth International Workshop on Freight Transportation and Logistics (ODYSSEUS 2015); Applegate D., Bixby R., Chvatal V., Cook W., The Traveling Salesman Problem: A Computational Study, (2006); Roberti R., Wen M., The electric traveling salesman problem with time windows, Transp. Res. E-Log, 89, pp. 32-52, (2016); Doppstadt C., Koberstein A., Vigo D., The hybrid electric vehicle–traveling salesman problem, Eur. J. Oper. Res, 253, pp. 825-842, (2016); Murakami K., Formulation and algorithms for route planning problem of plug-in hybrid electric vehicles, Oper. Res, 18, pp. 497-519, (2018); Unal V., Soysal M., Cimen M., Koc C., Dynamic routing optimization with electric vehicles under stochastic battery depletion, Transp. Lett, (2022); Baum M., Dibbelt J., Pajor T., Sauer J., Wagner D., Zundorf T., Energy-optimal routes for battery electric vehicles, Algorithmica, 82, pp. 1490-1546, (2020); Rokbani N., Kumar R., Abraham A., Alimi A.M., Long H.V., Priyadarshini I., Son L., Bi-heuristic ant colony optimization-based approaches for traveling salesman problem, Soft Comput, 25, pp. 3775-3794, (2021); Qi X., Wu G., Boriboonsomsin K., Barth M., Data-driven decomposition analysis and estimation of link-level electric vehicle energy consumption under real-world traffic conditions, Transp. Res. D-Transp. Environ, 64, pp. 36-52, (2018); Bellman R., On a routing problem, Q. Appl. 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Res, 6, pp. 791-812, (1958); Nuraiman D., Ilahi F., Dewi Y., Hamidi E.A., A new hybrid method based on nearest neighbor algorithm and 2-OPT algorithm for traveling salesman problem, Proceedings of the 2018 4th International Conference on Wireless and Telematics (ICWT), pp. 1-4; Agarap A., Deep learning using rectified linear units (relu), arXiv, (2018); Kingma D., Ba J., Adam: A method for stochastic optimization, arXiv, (2014); Yao Y., Rosasco L., Caponnetto A., On early stopping in gradient descent learning, Constr. Approx, 26, pp. 289-315, (2007); Wang Y., Han Z., Ant colony optimization for traveling salesman problem based on parameters optimization, Appl. Soft Comput, 107, (2021); Kizilates G., Nuriyeva F., On the nearest neighbor algorithms for the traveling salesman problem, Advances in Computational Science, Engineering and Information Technology, Proceedings of the Third International Conference on Computational Science, Engineering and Information Technology (CCSEIT-2013), Konya, Turkey, 7–9 June 2013, pp. 111-118, (2013); Mohammed M., Abd Ghani M., Hamed R., Mostafa S., Ibrahim D., Jameel H., Alallah A., Solving vehicle routing problem by using improved K-nearest neighbor algorithm for best solution, J. Comput. Sci, 21, pp. 232-240, (2017)","J.A. Conejero; Instituto Universitario Matemática Pura y Aplicada, Universitat Politècnica de València, Valencia, 46022, Spain; email: aconejero@upv.es",null,"Multidisciplinary Digital Publishing Institute (MDPI)",{"$nulls":5},1.9994893E7,null,null,null,"English","Algorithms","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85172269854"]
["Tebaldi L.; Reverberi D.; Romagnoli G.; Bottani E.; Rizzi A.","Tebaldi, Letizia (57204497688); Reverberi, Davide (57218701342); Romagnoli, Giovanni (39762851400); Bottani, Eleonora (14035135900); Rizzi, Antonio (14036285200)","57204497688; 57218701342; 39762851400; 14035135900; 14036285200","RFID technology in Retail 4.0: state-of-the-art in the Fast-Moving Consumer Goods field",2023.0,"International Journal of RF Technologies: Research and Applications",13.0,2.0,null,105.0,133.0,28.0,0.0,"10.3233/RFT-221505","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85180006799&doi=10.3233%2fRFT-221505&partnerID=40&md5=df277bc0531a06a040b48dbb21e17cbb","Department of Engineering and Architecture, University of Parma, Parma, Italy","Tebaldi L., Department of Engineering and Architecture, University of Parma, Parma, Italy; Reverberi D., Department of Engineering and Architecture, University of Parma, Parma, Italy; Romagnoli G., Department of Engineering and Architecture, University of Parma, Parma, Italy; Bottani E., Department of Engineering and Architecture, University of Parma, Parma, Italy; Rizzi A., Department of Engineering and Architecture, University of Parma, Parma, Italy","The well-known Radio Frequency Identification (RFID) technology is now evolving its applications: indeed, at the industrial level, it was firstly conceived at the pallet/case level for enhancing productivity and accuracy of logistics processes, while at present the focus is shifting towards item-level tagging applications for also managing in-store processes, including the selling experience. Due to a more technological customer, to the spread of e-commerce and the need of omnichannel sales availability, also Fast-Moving Consumer Goods (FMCG) are subject to an evolution of the way of selling, enabled by an item-level RFID tagging. Since these technologies are connected to the fourth industrial revolution, this novelty is referred to as Retail 4.0, which is still an uncommon term among the scientific community. For this reason, this paper makes an attempt to define the state-of-the-art of research and industrial projects on this topic, and it represents the first study investigating the Retail 4.0 from a practical side, closing the scientific gap regarding this issue. Eleven documents and fourteen projects focusing on item-level RFID tagging of FMCGs are examined and categorized according to a pre-existing use cases framework, and the enabled scenarios under a Retail 4.0 perspective are identified and defined. Inventory and Life-Cycle Management related use cases turned out to be the most investigated (7 scientific documents and 12 projects), while the User Experience was only considered at the industrial level (12 projects). From both sides, the Product Integrity was not perceived as relevant (2 articles and 6 projects); similarly, scarce attention was paid to the sustainability functionality of packaging with a total of 1 scientific paper and 5 projects.  © 2023 - IOS Press. All rights reserved.","Fast-Moving Consumer Goods; Internet of Things; IoT; Item-level RFID; Logistics; Retail 4.0; Smart Packaging","Costs; Industrial research; Life cycle; Radio frequency identification (RFID); Sales; Fast moving consumer goods; IoT; Item-level; Item-level radio frequency identification; ITS applications; Radio frequency identification technology; Radio-frequency-identification; Retail 4.0; Smart Packaging; State of the art; Internet of things",{"$nulls":6},"Azevedo S., Carvalho H., Cruz-Machado V., A cross-case analysis of rfid deployment in fast fashion supply chain, Advances in Intelligent Systems and Computing, 280, pp. 605-617, (2014); Barge P., Gay P., Merlino V., Tortia C., Item-level Radio-Frequency IDentification for the traceability of food products: Application on a dairy product, Journal of Food Engineering, 125, pp. 119-130, (2014); Bertolini M., Ferretti G., Montanari R., Rizzi A., Vignali G., A quantitative evaluation of the impact of the RFID technology on shelf availability, International Journal of RF Technologies: Research and Applications, 3, 3, pp. 159-180, (2012); Bertolini M., Maggiali L., Rizzi A., Romagnoli G., Volpi A., Introducing new RFID-enabled indicators to evaluate the performance of fashion retailers, Proceedings of the Summer School Francesco Turco 2017-September, pp. 54-60, (2017); Bordeleau F.-E., Mosconi E., De Santa-Eulalia L., Business intelligence in industry 4.0: State of the art and research opportunities, Proceedings of the 51st Hawaii International Conference on System Sciences, pp. 3944-3953, (2018); Bottani E., Ferretti G., Montanari R., Rizzi A., The impact of RFID technology on logistics processes of the fashion industry supply chain, International Journal of RF Technologies: Research and Applications, 1, 4, pp. 225-252, (2009); Casella G., Bigliardi B., Bottani E., The evolution of RFID technology in the logistics field: A review, Procedia Computer Science, 200, pp. 1582-1592, (2022); Cilloni G., Leporati R., Rizzi A., Romagnoli G., State of the art of item-level RFID deployments in fashion and apparel retail, International Journal of RF Technologies, 10, 3-4, pp. 65-88, (2019); Conti M., Orcioni S., Cloud-based sustainable management of electrical and electronic equipment from production to end-of-life, International Journal of Quality & Reliability Management, 36, 1, pp. 98-119, (2019); Cui L., Deng J., Liu F., Zhang Y., Xu M., Investigation of RFID investment in a single retailer two-supplier supply chain with random demand to decrease inventory inaccuracy, Journal of Cleaner Production, 142, pp. 2028-2044, (2017); Cui L., Zhang Z., Gao N., Meng Z., Li Z., Radio frequency identification and sensing techniques and their applications-A review and the state-of-art, Sensors, 19, (2019); Capturing value from the smart packaging revolution., (2018); Domdouzis K., Kumar B., Anumba C., Radio-frequency identification (rfid) applications: A brief introduction, Advanced Engineering Informatics, 21, pp. 350-355, (2007); Duroc Y., From identification to sensing: RFID is one of the key technologies in the IoT field, Sensors, 22, 19, (2022); Esposito E., Romagnoli G., Sandri S., Villani L., Deploying RFID in the fashion and apparel sector: An \"in the field\" analysis to understand where the technology is going to, Proceedings of the Summer School Francesco Turco, pp. 7-15, (2015); 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Xu C., Zhao D., Optimal decisions for adoption of item-level RFID in a retail supply chain with inventory shrinkage under CVaR criterion, Discrete Dynamics in Nature and Society, 2016, pp. 1-17, (2016); Zhou W., Piramuthu S., Remanufacturing with RFID item-level information: Optimization, waste reduction and quality improvement, International Journal of Production Economics, 145, 2, pp. 647-657, (2013)","L. Tebaldi; Department of Engineering and Architecture, University of Parma, Parma, Italy; email: letizia.tebaldi@unipr.it",null,"IOS Press BV",{"$nulls":5},1.754573E7,null,null,null,"English","Int. J. RF Technol. Res. Appl.","Article","Final",null,"Scopus","2-s2.0-85180006799"]
["Ding H.-C.; Wang G.; Zhong Z.; Xu Q.; Wu Q.; Zhong Y.; Zhan Y.; Li M.","Ding, Hong-Chao (57204060384); Wang, Gang (57216853380); Zhong, Zuchang (57194723459); Xu, Qunmin (57216856221); Wu, Qianru (57216868316); Zhong, Yuanyuan (57216858764); Zhan, Yanting (57216866193); Li, Miaoting (57216862317)","57204060384; 57216853380; 57194723459; 57216856221; 57216868316; 57216858764; 57216866193; 57216862317","Regression analysis on correlation of China’s export via cross-border e-commerce",2023.0,"International Journal of Electrical Engineering and Education",60.0,"2_suppl",null,120.0,129.0,9.0,5.0,"10.1177/0020720920923663","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85085006030&doi=10.1177%2f0020720920923663&partnerID=40&md5=dc9200fd74a8d00756576552e0ebb9d6","School of Further Education, Guangzhou Panyu Polytechnic, Guangzhou, China; School of Business, Guangdong University of Foreign Studies, Guangzhou, China","Ding H.-C., School of Further Education, Guangzhou Panyu Polytechnic, Guangzhou, China; Wang G., School of Business, Guangdong University of Foreign Studies, Guangzhou, China; Zhong Z., School of Business, Guangdong University of Foreign Studies, Guangzhou, China; Xu Q., School of Business, Guangdong University of Foreign Studies, Guangzhou, China; Wu Q., School of Business, Guangdong University of Foreign Studies, Guangzhou, China; Zhong Y., School of Business, Guangdong University of Foreign Studies, Guangzhou, China; Zhan Y., School of Business, Guangdong University of Foreign Studies, Guangzhou, China; Li M., School of Business, Guangdong University of Foreign Studies, Guangzhou, China","In the Chinese national strategic context of “Internet Plus”, innovation of internet technologies and business models play crucial roles in driving economic growth. The research shows that gross domestic product (GDP), logistics infrastructure and internet penetration of the target countries rank the top 3 of factors that influence export scale via cross-border e-commerce, while the distance to China and tariff constitute negative roles. It is on this assumption that logistics information database of cross-border e-commerce export and foreign infrastructure construction is proposed to expedite trade between China and countries along the Belt and Road. © The Author(s) 2020.","Belt and Road initiative; cross-border e-commerce; export; influencing factors","Electronic commerce; Roads and streets; Belt and road initiative; Business models; Cross-border; Cross-border e-commerce; E- commerces; Economic growths; Export; Gross domestic products; Influencing factor; Internet technology; Regression analysis",{"$nulls":4},"12th Five-Year Plan Program of Philosophy and Social Science in Guangdong Province; Guangdong Educational Science; Guangdong-Hong Kong-Macao Greater Bay Area)     Innovation team project; Humanities and Social Sciences Planning Project of the Ministry of Education; Humanities and Social Sciences) of universities in Guangdong, (2017WCXTD003); Ministry of Education, (15YJA630067); National Natural Science Foundation of Guangdong; Science and Technology Program of Guangdong Province, (2015A070704055); Soft Science Project of the Science and Technology Program of Guangdong Province; National Natural Science Foundation of China, NSFC, (71673064, 71673064 71974039, 71974039); Natural Science Foundation of Guangdong Province, (2019A1515011475); Guangdong University of Foreign Studies, GDUFS; Guangdong Planning Office of Philosophy and Social Science, (GD14CGL11)","Funding text 1: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The research is supported by the Specialized Study of Philosophy and Social Science 2019 Under Provincial 13th Five-Year Plan of Guangdong Educational Science (Approaches to Multi-talent Cultivation of Cross-border E-commerce in Guangdong-Hong Kong-Macao Greater Bay Area), the Humanities and Social Sciences Planning Project of the Ministry of Education (15YJA630067), Soft Science Project of the Science and Technology Program of Guangdong Province (2015A070704055) and the 12th Five-Year Plan Program of Philosophy and Social Science in Guangdong Province (GD14CGL11), the National Natural Science Foundation of China (Grant: 71673064; 71974039), the National Natural Science Foundation of Guangdong (2019A1515011475), Innovation Team Project (Humanities and Social Sciences) of universities in Guangdong (Grant: 2017WCXTD003), regional and national projects of Guangdong University of Foreign Studies in 2018 (Grant: 6).; Funding text 2:  In the Chinese national strategic context of “Internet Plus”, innovation of internet technologies and business models play crucial roles in driving economic growth. The research shows that gross domestic product (GDP), logistics infrastructure and internet penetration of the target countries rank the top 3 of factors that influence export scale via cross-border e-commerce, while the distance to China and tariff constitute negative roles. It is on this assumption that logistics information database of cross-border e-commerce export and foreign infrastructure construction is proposed to expedite trade between China and countries along the Belt and Road.   Belt and Road initiative influencing factors export cross-border e-commerce    the National Natural Science Foundation of China  71673064 71974039    Regional and national projects of Guangdong University of Foreign Studies in 2018  6    the 12thFive-year Plan Program of Philosophy and Social Science in Guangdong Province  GD14CGL11    the Specialized Study of Philosophy and Social Science 2019 Under Provincial 13-Five-Year Plan of Guangdong Educational Science(Approaches to Multi-talent Cultivation of Cross-border E-commerce in Guangdong-Hong Kong-Macao Greater Bay Area)     Innovation team project (HUMANITIES AND SOCIAL SCIENCES) of universities in Guangdong  2017WCXTD003    Soft Science Project of the Science and Technology Program of Guangdong Province  2015A070704055    the National Natural Science Foundation of Guangdong  2019A1515011475    the Humanities and Social Sciences Planning Project of the Ministry of Education  15YJA630067    edited-state corrected-proof   typesetter ts2","McCallum J., National borders matter: Canada-U.S. regional trade patterns, Am Econ Rev, 85, pp. 615-623, (1995); Blum B.S., Goldfarb A., Does the internet defy the law of gravity?, J Int Econ, 70, pp. 384-405, (2006); Yeqing H., Zhang Y., An empirical analysis of new trends of China’s foreign trade based on trade gravity model, Int Econ Trade Res, pp. 23-28, (2008); Youwei L., Kaiqian W., Cross-border electronic commerce’s development characteristics, obstacle factors and the next step in China, Reform, 5, pp. 68-74, (2014); Xiaheng Z., Tianshan M., Difficulties and countermeasures about China’s cross-border e-commerce logistics, Contemp Econ Manage, pp. 51-54, (2015); Ying K., Research of logistics mode selection in B2C cross-border e-commerce in China, China Bus Market, pp. 63-69, (2015); Linlin Y., Worries solutions of China Tea Export via cross-border e-commerce from perspective of the big data and the Belt and Road, Stat Manage, pp. 61-65, (2016); Yuhua L.V., Influencing factors of China import and export trade flows – empirical study on trade gravity model by panel data, Econ Probl, pp. 29-31, (2009); Yunhe D., Opportunities of cross-border e-commerce under China’s Belt and Road strategic background, Contemp Econ, pp. 38-40, (2016); Bao J., Chen W., Jian L., Empirical analysis of trade gravity on China’s cross-border e-commerce, J Commer Econ, pp. 32-34, (2017); Zhe J., Status quo of China’s cross-border e-commerce and its strategies under the Belt and Road initiative, World Shipping, pp. 6-10, (2017)","G. Wang; School of Business, Guangdong University of Foreign Studies, Guangzhou, China; email: 13570105916@163.com",null,"SAGE Publications Inc.",{"$nulls":5},207209.0,null,"IJEEA",null,"English","Int J Electr Eng Educ","Article","Final",null,"Scopus","2-s2.0-85085006030"]
["Chaubey G.; Gavhane P.R.; Bisen D.; Arjaria S.K.","Chaubey, Gyanendra (57216925562); Gavhane, Prathamesh Rajendra (57579557200); Bisen, Dhananjay (57194975182); Arjaria, Siddhartha Kumar (57213586256)","57216925562; 57579557200; 57194975182; 57213586256","Customer purchasing behavior prediction using machine learning classification techniques",2023.0,"Journal of Ambient Intelligence and Humanized Computing",14.0,12.0,null,16133.0,16157.0,24.0,6.0,"10.1007/s12652-022-03837-6","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85128436896&doi=10.1007%2fs12652-022-03837-6&partnerID=40&md5=585835a366bb44e8afd364dca4e1d78f","Department of Information Technology, Rajkiya Engineering College, Atarra, UP, Banda, 210201, India; Dr. D Y Patil School of Engineering and Technology, Charoli (BK), via Lohegaon, Maharastra, Pune, 412105, India; Department of Information Technology, Madhav Institute of Technology and Science, MP, Gwalior, 474005, India","Chaubey G., Department of Information Technology, Rajkiya Engineering College, Atarra, UP, Banda, 210201, India; Gavhane P.R., Dr. D Y Patil School of Engineering and Technology, Charoli (BK), via Lohegaon, Maharastra, Pune, 412105, India; Bisen D., Department of Information Technology, Madhav Institute of Technology and Science, MP, Gwalior, 474005, India; Arjaria S.K., Department of Information Technology, Rajkiya Engineering College, Atarra, UP, Banda, 210201, India","Many sales and service-providing companies need to talk up related customers while launching the new products, services, and updated versions of existing products. While doing so, they need to target their existing customers. The behavior of these customers gives companies information about how to sell products. This paper presents a comparative study of different machine learning techniques that have been applied to the problem of customer purchasing behavior prediction. Experiments are done using supervised classification machine learning techniques like logistic regression, decision tree, k-nearest neighbors (KNN), Naïve Bayes, SVM, random forest, stochastic gradient descent (SGD), ANN, AdaBoost, XgBoost, and dummy classifier, as well as some hybrid algorithms that use stacking like SvmAda, RfAda, and KnnSgd. Models are evaluated using the cross-validation technique. Furthermore, the confusion matrix and ROC curve are used to calculate the accuracy of each model. Finally, the best classifier is a hybrid classifier using the ensemble stacking technique (KnnSgd), with an accuracy of 92.42%. KnnSgd gives the highest accuracy with maximum features because the error of the KNN and SGD are minimized by the KNN at the end. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.","Customer purchasing behavior prediction; E-commerce; Machine learning; Supervised classification algorithms","Adaptive boosting; Forecasting; Gradient methods; Nearest neighbor search; Sales; Stochastic systems; Support vector machines; Behavior prediction; Classification algorithm; Customer purchasing behavior prediction; Machine learning techniques; Machine-learning; Purchasing behaviors; Stackings; Stochastic gradient descent; Supervised classification; Supervised classification algorithm; Decision trees",{"$nulls":6},"Adebola Orogun B.O., Predicting consumer behaviour in digital market: a machine learning approach, Int J Innov Res Sci Eng Technol, 8, 8, pp. 8391-8402, (2019); Adeniyi D., Wei Z., Yongquan Y., Automated web usage data mining and recommendation system using k-nearest neighbor (KNN) classification method, Appl Comput Inform, 12, 1, pp. 90-108, (2016); Agatonovic-Kustrin S., Beresford R., Basic concepts of artificial neural network (ANN) modeling and its application in pharmaceutical research, J Pharm Biomed Anal, 22, 5, pp. 717-727, (2000); Ali J., Khan R., Ahmad N., Maqsood I., Random forests and decision trees, Int J Comp Sci, 9, 5, (2012); Alloghani M., Al-Jumeily D., Baker T., Hussain A., Mustafina J., Aljaaf A.J., Applications of machine learning techniques for software engineering learning and early prediction of students’ performance, . in Communications in Computer and Information Science, pp. 246-258, (2018); Amin A., Shah B., Khattak A.M., Baker T., Ur Rahman Durani H., Anwar S., Just-in-time customer churn prediction: Eith and without data transformation, 2018 IEEE Congress on Evolutionary Computation (CEC). IEEE, (2018); Bala R., Kumar D., Classification using ANN: a review, Int J Comput Intell Res, 13, 7, pp. 1811-1820, (2017); Bottou L., Large-scale machine learning with stochastic gradient descent, Proceedings of COMPSTAT’2010, pp. 177-186, (2010); Breiman L., Random forests, Mach Learn, 45, 1, pp. 5-32, (2001); Uci Machine Learning Repository, (2014); Cardoso M.G.M.S., Logical discriminant models, Quantitative Modelling in Marketing and Management, (2012); Charanasomboon T., Viyanon W., A comparative study of repeat buyer prediction, Proceedings of the 2019 2Nd International Conference on Information Science and Systems, (2019); Chaubey G., Bisen D., Arjaria S., Yadav V., Thyroid disease prediction using machine learning approaches, Natl Acad Sci Lett, 44, 3, pp. 233-238, (2020); Chen T., Guestrin C., XGBoost, Proceedings of the 22Nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM, (2016); Das T.K., A customer classification prediction model based on machine learning techniques, 2015 International Conference on Applied and Theoretical Computing and Communication Technology (Icatcct), (2015); Dawood E.A.E., Elfakhrany E., Maghraby F.A., Improve profiling bank customer’s behavior using machine learning, IEEE Access, 7, pp. 109320-109327, (2019); Do Q.H., Trang T.V., An approach based on machine learning techniques for forecasting vietnamese consumers’ purchase behaviour, Decis Sci Lett, pp. 313-322, (2020); Dreiseitl S., Ohno-Machado L., Logistic regression and artificial neural network classification models: a methodology review, J Biomed Inform, 35, 5-6, pp. 352-359, (2002); Dzeroski S., Zenko B., Is combining classifiers with stacking better than selecting the best one?, Mach Learn, 54, 3, pp. 255-273, (2004); Freund Y., Schapire R.E., A short introduction to boosting, Jpn Japan Soc Artif Intell, 14, 5, pp. 771-780, (1999); Gupta G., Aggarwal H., Improving customer relationship management using data mining, Int J Mach Learn Comput, pp. 874-877, (2012); Hehn T.M., Kooij J.F.P., Hamprecht F.A., End-to-end learning of decision trees and forests, Int J Comput Vision, 128, 4, pp. 997-1011, (2019); Kachamas P., Akkaradamrongrat S., Sinthupinyo S., Chandrachai A., Application of artificial intelligent in the prediction of consumer behavior from facebook posts analysis, Int J Mach Learn Comput, 9, 1, pp. 91-97, (2019); Kaviani P., Dhotre M.S., Short Survey on Naive Bayes Algorithm-Ijaerd, (2017); Kohavi R., Mason L., Parekh R., Zheng Z., Lessons and challenges from mining retail e-commerce data, Mach Learn, 57, 1-2, pp. 83-113, (2004); Lavrac N., Cestnik B., Gamberger D., Flach P., Decision support through subgroup discovery: three case studies and the lessons learned, Mach Learn, 57, 1-2, pp. 115-143, (2004); Liu W., Wang J., Sangaiah A.K., Yin J., Dynamic metric embedding model for point-of-interest prediction, Futur Gener Comput Syst, 83, pp. 183-192, (2018); Momin S., Bohra T., Raut P., Prediction of customer churn using machine learning, EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing, pp. 203-212, (2019); Nalepa J., Kawulok M., Selecting training sets for support vector machines: a review, Artif Intell Rev, 52, 2, pp. 857-900, (2018); Raghuwanshi B.S., Shukla S., Class-specific extreme learning machine for handling binary class imbalance problem, Neural Netw, 105, pp. 206-217, (2018); Rokach L., Maimon O., Decision trees, Data mining and knowledge discovery handbook, (2005); Sanchez-Franco M.J., Navarro-Garcia A., Rondan-Cataluna F.J., A Naive Bayes strategy for classifying customer satisfaction: a study based on online reviews of hospitality services, J Bus Res, 101, pp. 499-506, (2019); Sangaiah A.K., Medhane D.V., Han T., Hossain M.S., Muhammad G., Enforcing position-based confidentiality with machine learning paradigm through mobile edge computing in real-time industrial informatics, IEEE Trans Industr Inf, 15, 7, pp. 4189-4196, (2019); Santharam A., Krishnan S.B., Survey on customer churn prediction techniques, Int Res J Eng Tech, 5, 11, pp. 131-137, (2018); Schapire R.E., Explaining AdaBoost, Empirical inference, pp. 37-52, (2013); Sweilam N.H., Tharwat A., Moniem N.A., Support vector machine for diagnosis cancer disease: a comparative study, Egypt Inform J, 11, 2, pp. 81-92, (2010); Ullah I., Raza B., Malik A.K., Imran M., Islam S.U., Kim S.W., A churn prediction model using random forest: analysis of machine learning techniques for churn prediction and factor identification in telecom sector, IEEE Access, 7, pp. 60134-60149, (2019); Vafeiadis T., Diamantaras K., Sarigiannidis G., Chatzisavvas K., A comparison of machine learning techniques for customer churn prediction, Simul Model Pract Theory, 55, pp. 1-9, (2015); Zhang Z., Introduction to machine learning: k-nearest neighbors, Ann Transl Med, 4, 11, (2016); Zhao B., Takasu A., Yahyapour R.X., Loyal consumers or one-time deal hunters: Repeat buyer prediction for e-commerce, In 2019 International Conference on Data Mining Workshops (ICDMW, (2019)","G. Chaubey; Department of Information Technology, Rajkiya Engineering College, Atarra, Banda, UP, 210201, India; email: gyanendrachaubey68@gmail.com",null,"Springer Science and Business Media Deutschland GmbH",{"$nulls":5},1.8685137E7,null,null,null,"English","J. Ambient Intell. Humanized Comput.","Article","Final",null,"Scopus","2-s2.0-85128436896"]
["Wang C.; Zhou T.; Ren M.","Wang, Chenxi (58117728500); Zhou, Tao (36887782800); Ren, Maohui (58117221000)","58117728500; 36887782800; 58117221000","Driving spatial network connections in rural settlements: The role of e-commerce",2023.0,"Applied Geography",159.0,null,103067.0,null,null,null,2.0,"10.1016/j.apgeog.2023.103067","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85168326568&doi=10.1016%2fj.apgeog.2023.103067&partnerID=40&md5=131096a715857cad1eca036d78d92498","School of Management Science and Real Estate, Chongqing University, Chongqing, 400044, China; Research Center for Construction Economy and Management, Chongqing University, Chongqing, 400044, China","Wang C., School of Management Science and Real Estate, Chongqing University, Chongqing, 400044, China; Zhou T., School of Management Science and Real Estate, Chongqing University, Chongqing, 400044, China, Research Center for Construction Economy and Management, Chongqing University, Chongqing, 400044, China; Ren M., School of Management Science and Real Estate, Chongqing University, Chongqing, 400044, China","In certain developing countries, the e-commerce industries of rural areas are subjected to clustering, which provides an entry point through which the following can be observed: the influence of information and communications technology and the digital economy on spatial connections in rural settlements. Hence, Zhejiang Province, China's leading rural e-commerce province, is selected as the study site. The spatial correlation between e-commerce and the spatial landscape pattern of rural settlements and their network connections is analysed. Moreover, with regard to the spatial network of rural settlements, the driving factors of e-commerce are explored. The research findings demonstrate that: (1) e-commerce cluster areas are primarily distributed where the in-degree is higher than the out-degree, and the betweenness centrality is also significant. (2) E-commerce fosters the expansion and integration of land use in rural settlements and enhances the spatial network connections between rural settlements. (3) In regional economies, e-commerce enhances the connectivity and resource circulation efficiency of spatial networks in rural settlements through scale effects, traffic and informatisation levels, and the logistics development environment. The aforementioned findings contribute to the enrichment of the policy toolbox for rural planning and spatial governance, and the exploration of the market potential of e-commerce development in rural areas. © 2023 Elsevier Ltd","E-commerce; Geographic spaces; Rural settlements; Spatial network","China; Zhejiang; developing world; electronic commerce; governance approach; information and communication technology; rural area; rural planning; spatial analysis",{"$nulls":4},"National Office for Philosophy and Social Sciences, NPOPSS, (23AZD019)","The authors thank the support from the National Social Science Fund of China (Grant No. 23AZD019 ).","Alphan H., Karamanli E., Derse M.A., Uslu C., Analyzing pattern features of urban/rural residential land use change: The case of the southern coast of Turkey, Land Use Policy, 122, (2022); Banski J., Wesolowska M., Transformations in housing construction in rural areas of Poland's Lublin region-Influence on the spatial settlement structure and landscape aesthetics, Landscape and Urban Planning, 94, pp. 116-126, (2010); 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Zhou; School of Management Science and Real Estate, Chongqing University, Chongqing, 400044, China; email: taozhou@cqu.edu.cn",null,"Elsevier Ltd",{"$nulls":5},1436228.0,null,null,null,"English","Appl. Geogr.","Article","Final",null,"Scopus","2-s2.0-85168326568"]
["Cieśla M.","Cieśla, Maria (55973444400)",5.59734444E10,"Perceived Importance and Quality Attributes of Automated Parcel Locker Services in Urban Areas",2023.0,"Smart Cities",6.0,5.0,null,2661.0,2679.0,18.0,0.0,"10.3390/smartcities6050120","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85175234222&doi=10.3390%2fsmartcities6050120&partnerID=40&md5=de5389f709b4927f7e0974a9ca0dfa1c","Department of Transport Systems, Traffic Engineering and Logistics, Faculty of Transport and Aviation Engineering, Silesian University of Technology, 8 Krasińskiego St, Katowice, 40-019, Poland","Cieśla M., Department of Transport Systems, Traffic Engineering and Logistics, Faculty of Transport and Aviation Engineering, Silesian University of Technology, 8 Krasińskiego St, Katowice, 40-019, Poland","Recent global trends related to the increasing use of e-commerce are becoming a challenge for courier transport, especially in the last-mile process of delivering products to the final retail recipient. One delivery method is the personal collection of the parcel in an automated post box, available 24/7 for the customer. Our research method was based on a preliminary selection of the most important features of parcel lockers’ service quality, which were extracted based on the analysis of the scientific literature and previous research. This analysis was carried out by conducting a survey of Polish parcel locker users that provided data coded according to the dimensions of the Kano model. Based on the total satisfaction index, the results allowed us to conclude that a dedicated application (−0.96), proper placement of the parcel in the box (−0.82), adjusting the size of the parcel to the size of the box (−0.79), the location of parcel stations (−0.74), and ensuring improvements for the disabled (−0.62) are the most important features in the process of the automatic delivery of parcels to recipients in urban areas. This paper enriches the literature on the customer service quality of self-service technologies for last-mile delivery with the use of automated parcel lockers. © 2023 by the author.","automated deliveries; city parcel lockers; courier transport; customer service quality; Kano model; parcel lockers; quality features",{"$nulls":7},"Chevalier S., Global Retail e-Commerce Sales Worldwide from 2014 to 2026. Statista 2022, eMarketer, (2022); Allen J., Piecyk M., Piotrowska M., McLeod F., Cherrett T., Ghali K., Nguyen T., Bektas T., Bates O., Friday A., Et al., Understanding the impact of e-commerce on last-mile light goods vehicle activity in urban areas: The case of London, Transp. Res. Part D Transp. Environ, 61, pp. 325-338, (2018); Dey B.K., Sarkar M., Chaudhuri K., Sarkar B., Do you think that the home delivery is good for retailing?, J. Retail. Consum. 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Geogr, 71, pp. 1-14, (2018); Wang Y., Bi M., Lai J., Chen Y., Locating movable parcel lockers under stochastic demands, Symmetry, 12, (2020); Schwerdfeger S., Boysen N., Who moves the locker? A benchmark study of alternative mobile parcel locker concepts, Transp. Res. Part C Emerg. Technol, 142, (2022); Lazarevic D., Dobrodolac M., Markovic D., Implementation of Mobile Parcel Lockers in Delivery Systems–Analysis by the AHP Approach, Int. J. Traffic Transp. Eng, 13, pp. 40-49, (2023)","M. Cieśla; Department of Transport Systems, Traffic Engineering and Logistics, Faculty of Transport and Aviation Engineering, Silesian University of Technology, Katowice, 8 Krasińskiego St, 40-019, Poland; email: maria.ciesla@polsl.pl",null,"Multidisciplinary Digital Publishing Institute (MDPI)",{"$nulls":5},2.6246511E7,null,null,null,"English","Smart. Cities.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85175234222"]
["Kötschau R.; Soeffker N.; Ehmke J.F.","Kötschau, Rico (58516998600); Soeffker, Ninja (57189641955); Ehmke, Jan Fabian (37017183900)","58516998600; 57189641955; 37017183900","Mobile parcel lockers with individual customer service",2023.0,"Networks",82.0,4.0,null,506.0,526.0,20.0,0.0,"10.1002/net.22173","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85166421433&doi=10.1002%2fnet.22173&partnerID=40&md5=73673093bb2d8559e6a518877aa8bd46","Business Analytics Group, University of Vienna, Vienna, Austria","Kötschau R., Business Analytics Group, University of Vienna, Vienna, Austria; Soeffker N., Business Analytics Group, University of Vienna, Vienna, Austria; Ehmke J.F., Business Analytics Group, University of Vienna, Vienna, Austria","The ongoing growth of e-commerce deliveries has led to a significant increase in last-mile delivery volumes. New technologies are being investigated to provide these deliveries efficiently and in a customer-friendly manner. A common practice is to use fixed parcel lockers (FPLs) to make deliveries independent from the presence of the customer as is the case in attended home deliveries (AHDs). FPLs are usually installed at key locations in cities, and customers can collect their package at any time once it has been delivered to this particular location. Mobile parcel lockers (MPLs) represent a new idea: they can be parked for temporary collection of items at different locations, keeping the pickup distance to the customer short and avoiding high infrastructure costs. However, customers need to collect their parcels within a restricted time window. This service is supposed to become especially efficient through autonomously operating vehicles that can move MPLs at low costs. In this article, we introduce the heterogeneous locker location problem to study the effects of fleets combining two of the services—FPLs, MPLs, AHDs—within one framework. In our comparison, we consider that customers may have different expectations regarding their maximum pickup distance as well as their temporal flexibility in accepting deliveries. A fixed fleet is applied to maximize the number of customers served, respecting individual customer preferences in terms of pickup distances and time windows. We evaluate the different delivery services regarding managerial insights on service quality and efficiency. In the experiments, we analyze the impact of structural demand differences and different fleet sizes, as well as the operational fleet utilization and the individual customer experience. Results show the potential to increase the number of customers served by about 14%–19% through the use of MPLs while considering individual customer preferences. © 2023 The Authors. Networks published by Wiley Periodicals LLC.","attended home delivery; customer preferences; heterogeneous locker location problem; individual customer service; last-mile delivery; mixed-integer program; mobile parcel locker; parcel locker","Costs; Integer programming; Locks (fasteners); Pickups; Sales; Attended home delivery; Customer preferences; Customer-service; Heterogeneous locker location problem; Home delivery; Individual customer service; Individual customers; Last mile; Last-mile delivery; Location problems; Mixed-integer programs; Mobile parcel locker; Parcel locker; Location",{"$nulls":6},"Campbell A.M., Savelsbergh M., Incentive schemes for attended home delivery services, Transp. Sci., 40, 3, pp. 327-341, (2006); Deutsch Y., Golany B., A parcel locker network as a solution to the logistics last mile problem, Int. J. Prod. Res., 56, 1-2, pp. 251-261, (2018); Dixit A., Mishra A., Shukla A., Vehicle routing problem with time windows using meta-heuristic algorithms: A survey, Harmony search and nature inspired optimization algorithms, pp. 539-546, (2019); Dumez D., Lehuede F., Peton O., A large neighborhood search approach to the vehicle routing problem with delivery options, Transp. Res. B Methodol., 144, pp. 103-132, (2021); Eliyan A., Elomri A., Kerbache L., The last-mile delivery challenge: Evaluating the efficiency of smart parcel stations, Supply Chain Forum Int. J., 22, pp. 360-369, (2021); Enthoven D.L., Jargalsaikhan B., Roodbergen K.J., uit het Broek M.A., Schrotenboer A.H., The two-echelon vehicle routing problem with covering options: City logistics with cargo bikes and parcel lockers, Comput. Oper. Res., 118, (2020); Faugere L., Montreuil B., Smart locker bank design optimization for urban omnichannel logistics: Assessing monolithic vs. modular configurations, Comput. Ind. Eng., 139, (2020); Gehring H., Homberger J., A parallel hybrid evolutionary metaheuristic for the vehicle routing problem with time windows, Proceedings of EUROGEN99, pp. 57-64, (1999); Grabenschweiger J., Doerner K.F., Hartl R.F., Savelsbergh M.W., The vehicle routing problem with heterogeneous locker boxes, Cent. Eur. J. Oper. Res., 29, 1, pp. 113-142, (2021); Hubner A.H., Kuhn H., Wollenburg J., Last mile fulfilment and distribution in omni-channel grocery retailing: A strategic planning framework, Int. J. Retail Distrib. Manag, 44, pp. 228-247, (2016); What is a mobile parcel locker?; Joerss M., Schroder J., Neuhaus F., Klink C., Mann F., Parcel delivery: The future of last mile, pp. 1-32, (2016); Krisch J., Vesper will auf der letzten meile mobile paketstationen nutzen; Kumar S.N., Panneerselvam R., A survey on the vehicle routing problem and its variants, Intell. Inf. Manag., 4, 3, pp. 66-74, (2012); Kohler C., Haferkamp J., Evaluation of delivery cost approximation for attended home deliveries, Transp. Res. Procedia, 37, pp. 67-74, (2019); Mancini S., Gansterer M., Vehicle routing with private and shared delivery locations, Comput. Oper. Res., 133, (2021); Orenstein I., Raviv T., Sadan E., Flexible parcel delivery to automated parcel lockers: Models, solution methods and analysis, EURO J. Transp. Logist., 8, 5, pp. 683-711, (2019); Schwerdfeger S., Boysen N., Optimizing the changing locations of mobile parcel lockers in last-mile distribution, Eur. J. Oper. Res., 285, 3, pp. 1077-1094, (2020); Schwerdfeger S., Boysen N., Who moves the locker? A benchmark study of alternative mobile parcel locker concepts, Transp. Res. Part C Emerg. Technol., 142, (2022); Seghezzi A., Siragusa C., Mangiaracina R., Parcel lockers vs. home delivery: A model to compare last-mile delivery cost in urban and rural areas, Int. J. Phys. Distribut. Logist. Manage., 52, pp. 213-237, (2022); Solomon M.M., Algorithms for the vehicle routing and scheduling problems with time window constraints, Oper. Res., 35, 2, pp. 254-265, (1987); Tilk C., Olkis K., Irnich S., The last-mile vehicle routing problem with delivery options, OR Spectr., 43, pp. 877-904, (2021); Veenstra M., Roodbergen K.J., Coelho L.C., Zhu S.X., A simultaneous facility location and vehicle routing problem arising in health care logistics in the Netherlands, Eur. J. Oper. Res., 268, 2, pp. 703-715, (2018); Wang Y., Bi M., Chen Y., A scheduling strategy of mobile parcel lockers for the last mile delivery problem, Promet, 32, 6, pp. 875-885, (2020); Wang Y., Bi M., Lai J., Chen Y., Locating movable parcel lockers under stochastic demands, Symmetry, 12, 12, (2020); Zurel O., Van Hoyweghen L., Braes S., Seghers A., Parcel lockers, an answer to the pressure on the last mile delivery?, New business and regulatory strategies in the postal sector, pp. 299-312, (2018)","R. Kötschau; Business Analytics Group, University of Vienna, Vienna, Kolingasse 14-16, 1090, Austria; email: rico.koetschau@univie.ac.at",null,"John Wiley and Sons Inc",{"$nulls":5},283045.0,null,null,null,"English","Networks","Article","Final","All Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85166421433"]
["Yao K.-C.; Yang J.-J.; Lo H.-W.; Lin S.-W.; Li G.-H.","Yao, Kai-Chao (23399061700); Yang, Jen-Jen (57203725180); Lo, Huai-Wei (57201915019); Lin, Sheng-Wei (57204533059); Li, Guan-Hong (58298558600)","23399061700; 57203725180; 57201915019; 57204533059; 58298558600","Using a BBWM-PROMETHEE model for evaluating mobile commerce service quality: A case study of food delivery platform",2023.0,"Research in Transportation Business and Management",49.0,null,100988.0,null,null,null,0.0,"10.1016/j.rtbm.2023.100988","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85160841754&doi=10.1016%2fj.rtbm.2023.100988&partnerID=40&md5=70c5c0f02cca9a9d754816244f1b9f78","Department of Industrial Education and Technology, National Changhua University of Education, Changhua, Taiwan; Department of Business Administration, Chaoyang University of Technology, Taichung, Taiwan; Department of Industrial Engineering and Management, National Yunlin University of Science and Technology, Taiwan; Department of Financial Management, Nation Defense University, Taiwan","Yao K.-C., Department of Industrial Education and Technology, National Changhua University of Education, Changhua, Taiwan; Yang J.-J., Department of Industrial Education and Technology, National Changhua University of Education, Changhua, Taiwan, Department of Business Administration, Chaoyang University of Technology, Taichung, Taiwan; Lo H.-W., Department of Industrial Engineering and Management, National Yunlin University of Science and Technology, Taiwan; Lin S.-W., Department of Financial Management, Nation Defense University, Taiwan; Li G.-H., Department of Business Administration, Chaoyang University of Technology, Taichung, Taiwan","In the age of COVID-19, many governments imposed social distancing, work-from-home, and crowd control measures, which continue to affect economic development and forces service providers to be increasingly reliant on e-commerce and m-commerce platform technology. Moreover, due to the availability of 5G network speeds, cell phone applications and the Internet services have become indispensable for future smart lifestyles, prompting brick-and-mortar businesses to shift their sales models to mobile network operators (MNOs). To popularize the use of m-commerce, it is critical to ensure that service platforms operate well and give the customer what they want. It is thus essential to create a comprehensive and complete performance framework for the evaluation of m-commerce services. In this paper, a hybrid model is developed to explore this issue and the effectiveness and robustness of the model is illustrated by an application to two major food delivery platforms in Taiwan. The Bayesian Best Worst Method (BBWM) is applied to identify the criteria weights and ranks. The judgments of 14 experts are integrated to obtain the optimal group criteria weights. The performance data were obtained from a survey of 210 experienced users of these delivery platforms. The difference between the actual performance of each delivery platform and the aspiration level (AL) was calculated using the modified Preference Ranking Organization Method for Enrichment Evaluations (modified PROMETHEE) to determine an overall score for each delivery platform. A sensitivity analysis was also conducted and comparison made with other Multiple Criteria Decision-Making (MCDM) methods. The results show that information security and privacy, integrity, and mobile transaction service are the most important criteria, with Food Panda performing better than the other mobile food delivery service provider. The proposed evaluation framework is useful for performance evaluation of mobile commerce service quality, and providing effective suggestions to assist decision-makers in creating development strategies. © 2023 Elsevier Ltd","Bayesian BWM; E-commerce; Modified PROMETHEE; Service performance",{"$nulls":7},"Ak M.F., Yucesan M., Gul M., Occupational health, safety and environmental risk assessment in textile production industry through a Bayesian BWM-VIKOR approach, Stochastic Environmental Research and Risk Assessment, 36, 2, pp. 629-642, (2022); Ashraf A.R., Tek N.T., Anwar A., Lapa L., Venkatesh V., Perceived values and motivations influencing m-commerce use: A nine-country comparative study, International Journal of Information Management, 59, (2021); Balapour A., Nikkhah H.R., Sabherwal R., Mobile application security: Role of perceived privacy as the predictor of security perceptions, International Journal of Information Management, 52, (2020); Belanche D., Flavian M., Perez-Rueda A., Mobile apps use and WOM in the food delivery sector: The role of planned behavior, perceived security and customer lifestyle compatibility, Sustainability, 12, 10, (2020); Bongo M.F., Alimpangog K.M.S., Loar J.F., Montefalcon J.A., Ocampo L.A., An application of DEMATEL-ANP and PROMETHEE II approach for air traffic controllers’ workload stress problem: A case of Mactan civil Aviation Authority of the Philippines, Journal of Air Transport Management, 68, pp. 198-213, (2018); Brans J.-P., Vincke P., Note—A preference ranking organisation method: (the PROMETHEE method for multiple criteria decision-making), Management Science, 31, 6, pp. 647-656, (1985); Choi J.-C., User familiarity and satisfaction with food delivery mobile apps, SAGE Open, 10, 4, (2020); Goodell J.W., COVID-19 and finance: Agendas for future research, Finance Research Letters, 35, (2020); Gu J., Xu Y.C., Xu H., Zhang C., Ling H., Privacy concerns for mobile app download: An elaboration likelihood model perspective, Decision Support Systems, 94, pp. 19-28, (2017); Gul M., Yucesan M., Performance evaluation of Turkish universities by an integrated Bayesian BWM-TOPSIS model, Socio-Economic Planning Sciences, 80, (2022); Guo H., Liu Y., Shi X., Chen K.Z., The role of e-commerce in the urban food system under COVID-19: Lessons from China, China Agric. Econ. Rev., 13, 2, pp. 436-455, (2020); Hu S.-K., Lu M.-T., Tzeng G.-H., Improving mobile commerce adoption using a new hybrid fuzzy MADM model, International Journal of Fuzzy Systems, 17, 3, pp. 399-413, (2015); Jou R.-C., Day Y.-J., Application of revised importance–performance analysis to investigate critical service quality of hotel online booking, Sustainability, 13, 4, (2021); Kang X., Pang H., City selection for fresh produce e-commerce's market entry strategy: Based on the perspective of urban logistics competitiveness, Transportation Research Interdisciplinary Perspectives, 13, (2022); Kim E.-A., Social distancing and public health guidelines at workplaces in Korea: Responses to coronavirus disease-19, Safety and Health at Work, 11, 3, pp. 275-283, (2020); Kim S., Baek T.H., Examining the antecedents and consequences of mobile app engagement, Telematics and Informatics, 35, 1, pp. 148-158, (2018); Li Y., Li G., Tayi G.K., Cheng T., Omni-channel retailing: Do offline retailers benefit from online reviews?, International Journal of Production Economics, 218, pp. 43-61, (2019); Liebana-Cabanillas F., Japutra A., Molinillo S., Singh N., Sinha N., Assessment of mobile technology use in the emerging market: Analyzing intention to use m-payment services in India, Telecommunications Policy, 44, 9, (2020); Lo H.-W., Liou J.J., An integrated Bayesian BWM and classifiable TOPSIS model for risk assessment, Multi-criteria decision analysis for risk assessment and management, pp. 21-51, (2021); Mohammadi M., Rezaei J., Bayesian best-worst method: A probabilistic group decision making model, Omega, 96, (2020); Moslehpour M., Pham V.K., Wong W.-K., Bilgicli I., E-purchase intention of Taiwanese consumers: Sustainable mediation of perceived usefulness and perceived ease of use, Sustainability, 10, 1, (2018); Muangmee C., Kot S., Meekaewkunchorn N., Kassakorn N., Khalid B., Factors determining the behavioral intention of using food delivery apps during COVID-19 pandemics, Journal of Theoretical and Applied Electronic Commerce Research, 16, 5, pp. 1297-1310, (2021); Mulyono R.A., Pasaribu L.H., The impact of mobile service quality and brand image on customer loyalty. Enrichment, Journal of Management, 12, 1, pp. 1-7, (2021); Nilashi M., Ibrahim O., Mirabi V.R., Ebrahimi L., Zare M., The role of security, design and content factors on customer trust in mobile commerce, Journal of Retailing and Consumer Services, 26, pp. 57-69, (2015); Omar S., Mohsen K., Tsimonis G., Oozeerally A., Hsu J.-H., M-commerce: The nexus between mobile shopping service quality and loyalty, Journal of Retailing and Consumer Services, 60, (2021); Orji I.J., Ojadi F., Okwara U.K., The nexus between e-commerce adoption in a health pandemic and firm performance: The role of pandemic response strategies, Journal of Business Research, 145, pp. 616-635, (2022); Rezaei J., Best-worst multi-criteria decision-making method, Omega, 53, pp. 49-57, (2015); Sarkar S., Chauhan S., Khare A., A meta-analysis of antecedents and consequences of trust in mobile commerce, International Journal of Information Management, 50, pp. 286-301, (2020); Shaw N., Sergueeva K., The non-monetary benefits of mobile commerce: Extending UTAUT2 with perceived value, International Journal of Information Management, 45, pp. 44-55, (2019); Su D.N., Nguyen N.A.N., Nguyen L.N.T., Luu T.T., Nguyen-Phuoc D.Q., Modeling consumers’ trust in mobile food delivery apps: Perspectives of technology acceptance model, mobile service quality and personalization-privacy theory, Journal of Hospitality Marketing & Management, pp. 1-35, (2022); Verplanken B., Orbell S., Attitudes, habits, and behavior change, Annual Review of Psychology, 73, pp. 327-352, (2022); Vinerean S., Budac C., Baltador L.A., Dabija D.-C., Assessing the effects of the COVID-19 pandemic on M-commerce adoption: An adapted UTAUT2 approach, Electronics, 11, 8, (2022); Yang C.-C., Shen C.-C., Mao T.-Y., Lo H.-W., Pai C.-J., A hybrid model for assessing the performance of medical tourism: Integration of Bayesian BWM and Grey PROMETHEE-AL, Journal of Function Spaces, 2022, (2022); Yuwen H., Guanxing S., Qiongwei Y., Consumers’ perceived trust evaluation of cross-border E-commerce platforms in the context of socialization, Procedia Computer Science, 199, pp. 548-555, (2022); Zheng B., Wang H., Golmohammadi A.-M., Goli A., Impacts of logistics service quality and energy service of business to consumer (B2C) online retailing on customer loyalty in a circular economy, Sustainable Energy Technologies and Assessments, 52, (2022); Zhou M., Huang J., Wu K., Huang X., Kong N., Campy K.S., Characterizing Chinese consumers’ intention to use live e-commerce shopping, Technology in Society, 67, (2021)","S.-W. Lin; Department of Financial Management, Nation Defense University, Taiwan; email: shengwei.lin1985@gmail.com",null,"Elsevier Ltd",{"$nulls":5},2.2105395E7,null,null,null,"English","Res. Transport. Bus. Manage.","Article","Final",null,"Scopus","2-s2.0-85160841754"]
["Bi H.; Zhu X.; Lu F.; Huang M.","Bi, Hualing (55273175200); Zhu, Xiaoxue (58772870700); Lu, Fuqiang (22734918400); Huang, Min (57996768400)","55273175200; 58772870700; 22734918400; 57996768400","The Meal Delivery Routing Problem in E-commerce Platforms under the Shared Logistics Mode",2023.0,"Journal of Theoretical and Applied Electronic Commerce Research",18.0,4.0,null,1799.0,1819.0,20.0,2.0,"10.3390/jtaer18040091","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85179308567&doi=10.3390%2fjtaer18040091&partnerID=40&md5=9febdf9800d945992c6f7f9f88084abc","School of Economics and Management, Yanshan University, Qinhuangdao, 066004, China; College of Information Science and Engineering, Northeastern University, Shenyang, 110819, China","Bi H., School of Economics and Management, Yanshan University, Qinhuangdao, 066004, China; Zhu X., College of Information Science and Engineering, Northeastern University, Shenyang, 110819, China; Lu F., School of Economics and Management, Yanshan University, Qinhuangdao, 066004, China; Huang M., College of Information Science and Engineering, Northeastern University, Shenyang, 110819, China","The meal delivery routing problem faced by the e-commerce platform is challenging. In order to reduce the logistics cost and meet the needs of customers, a multi-objective meal delivery routing problem is studied under the shared logistics services mode (SLSM). In the meal delivery problem, the third-party logistics providers need to arrange vehicles in the multi-depot to pick up meals from multiple food providers and deliver them to customers, so as to realize the sharing of logistics services between food providers and compare them with the traditional logistics service mode (TLSM). While realizing sharing, it is also necessary to meet customer time requirements as much as possible. In this case, a multi-objective mathematical model to minimize customer dissatisfaction and delivery cost is established, and the linear weighting method is employed to transform the model. An improved Ant Lion Optimizer (IALO) is proposed to solve the problem, and compared with other algorithms. The experiments verified the effectiveness of the proposed algorithm and show that SLSM can save logistics costs and meet customer needs more than TLSM, and provide certain reference opinions for the e-commerce platform. © 2023 by the authors.","ant lion optimizer; e-commerce; meal delivery; multi-objective; shared logistics service mode",{"$nulls":5},"Regional Economic Development Research Center of Yanshan University, (JJ2208); National Key Research and Development Program of China, NKRDPC, (2020YFB1712802)","Please add: This research was funded by the National Key R&D Program of China grant number 2020YFB1712802, and the Research Program of the Regional Economic Development Research Center of Yanshan University grant number JJ2208 and The APC was funded by the National Key R&D Program of China.","Li C.W., Optimization analysis of logistics distribution process route—Take meal delivery as an example, Econ. Trade Pract, 10, (2015); Yi C.Y., Integrated Production and Delivery Scheduling Model and Algorithm under Online Meal Ordering, Master’s Thesis, (2016); Dantzig G.B., Ramser J.H., The truck dispatching problem, Manag. Sci, 6, pp. 80-91, (1959); Yang Q.J., Tang Y.L., Teng X.B., Luo C.J., Zhang Z.B., Bi Q.L., Wei A., Hybrid mosquito tracking algorithm for MDVRP problem, J. Dongguan Univ. Technol, 26, (2019); Jose B., A memory-based iterated local search algorithm for the multi-depot open vehicle routing problem, Eur. J. Oper. 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Rev, 157, (2022); Guan Y., Wang Y., Yan X., Guo H., Zhao Y., The One E-Ticket Customized Bus Service Mode for Passengers with Multiple Trips and the Routing Problem, Sustainability, 14, (2022); Nickkar A., Lee Y.J., Meskar M., Developing an optimal algorithm for demand responsive feeder transit service accommodating temporary stops, J. Public Transp, 24, (2022); Hua S., Zeng W., Liu X., Qi M., Optimality-guaranteed algorithms on the dynamic shared-taxi problem, Transp. Res. Part E Logist. Transp. Rev, 164, (2022); Fu Z., Chow J.Y.J., Dial-a-ride problem with modular platooning and en-route transfers, Transp. Res. Part C Emerg. Technol, 152, (2023); Matusiewicz M., Ksiazkiewicz D., Shared Logistics—Literature Review, Appl. Sci, 13, (2023); Li J., Li T., Yu Y., Zhang Z., Pardalos P.M., Zhang Y., Ma Y., Discrete firefly algorithm with compound neighborhoods for asymmetric multi-depot vehicle routing problem in the maintenance of farm machinery, Appl. 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Technol, 40, pp. 1532-1538, (2018); Wen H., Wang S.X., Lu F.Q., Feng M., Wang L.Z., Xiong J.K., Si M.C., Colony search optimization algorithm using global optimization, J. Supercomput, 78, pp. 6567-6611, (2022); Zhai J.S., Thai Y.H., Delivery Routing Optimization Based on Time Window Constraint, Logist. Sci-Tech, 41, pp. 15-18, (2018); Ye Y., Zhang H.Z., Wolf pack algorithm for multi-depot routing problem, Appl. Res. Comput, 34, pp. 2590-2593, (2017); Yin Z., Ye C.M., Study on the hierarchical model for multi-depot logistic vehicle scheduling problem, J. Syst. Manag, 23, pp. 602-606, (2014); Wu Q.J., Study on Delivery Vehicle Routing Problem with Hard Time Window, Master’s Thesis, (2020); Zhang L.Y., Zhang J., Xiao B., Multi-objective O2O Take-Out Instant Delivery Routing Optimization Considering Customer Priority, Ind. Eng. Manag, 26, pp. 196-204, (2021); Zhao Q., Lu F., Wang L., Wang S., Research on Drones and Riders Joint Take-Out Delivery Routing Problem, Comput. Eng. Appl, 58, pp. 57-67, (2022)","F. Lu; School of Economics and Management, Yanshan University, Qinhuangdao, 066004, China; email: fqlu@ysu.edu.cn",null,"Multidisciplinary Digital Publishing Institute (MDPI)",{"$nulls":5},7181876.0,null,null,null,"English","J. Theor. Appl. Electron. Commer. Res.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85179308567"]
["Wang C.-N.; Chung Y.-C.; Wibowo F.D.; Dang T.-T.; Nguyen N.-A.-T.","Wang, Chia-Nan (57757351100); Chung, Yu-Chi (8970747500); Wibowo, Fajar Dwi (58295935500); Dang, Thanh-Tuan (57218565464); Nguyen, Ngoc-Ai-Thy (57218570813)","57757351100; 8970747500; 58295935500; 57218565464; 57218570813","Sustainable Last-Mile Delivery Solution Evaluation in the Context of a Developing Country: A Novel OPA–Fuzzy MARCOS Approach",2023.0,"Sustainability (Switzerland)",15.0,17.0,12866.0,null,null,null,0.0,"10.3390/su151712866","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85170396976&doi=10.3390%2fsu151712866&partnerID=40&md5=367ca46b24bc1f9686e8c0c497dcc041","Department of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung, 80778, Taiwan; Department of Logistics and Supply Chain Management, Hong Bang International University, Ho Chi Minh City, 72320, Viet Nam; Faculty of Business, FPT University, Ho Chi Minh City, 70000, Viet Nam","Wang C.-N., Department of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung, 80778, Taiwan; Chung Y.-C., Department of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung, 80778, Taiwan; Wibowo F.D., Department of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung, 80778, Taiwan; Dang T.-T., Department of Logistics and Supply Chain Management, Hong Bang International University, Ho Chi Minh City, 72320, Viet Nam; Nguyen N.-A.-T., Faculty of Business, FPT University, Ho Chi Minh City, 70000, Viet Nam","With the surge in e-commerce volumes during COVID-19, improving last-mile logistics is extremely challenging, specifically for developing economies, due to poor infrastructures, lack of stakeholders’ cooperation, and untapped resources. In the context of Vietnam, there are certain solutions that can bring more efficient and sustainable last-mile logistics. In this paper, to evaluate and rank these potentially sustainable last-mile solutions (LMSs), we propose a novel hybrid multiple attribute decision-making (MADM) model that combines the Ordinal Priority Approach (OPA) and fuzzy Measurement of Alternatives and Ranking according to the COmpromise Solution (fuzzy MARCOS). Twelve sustainability factors of technical, economic, social, and environmental aspects were determined through a literature review and experts’ opinions to employ the MADM approach. A case study evaluating five LMSs in Vietnam concerning their sustainable implementation is solved to exhibit the proposed framework’s applicability. From the OPA findings, “efficiency”, “costs of implementation and control”, “voice of customer”, “reliability”, and “flexibility” are the topmost criteria when considering a new LMS implementation in the context of Vietnam. Moreover, sensitivity analysis and comparative analysis were performed to test the robustness of the approach. The results illustrate that the applied methods reach consistent solution rankings, where LMS-03 (convenience store pickup), LMS-02 (parcel lockers), and LMS-01 (green vehicles) are the best solutions in Vietnam. The study holds novelty in evaluating last-mile initiatives for Vietnam by utilizing a unique approach in the form of two novel MADM techniques, thus providing significant insights for research and applications. © 2023 by the authors.","conflicting criteria; fuzzy MARCOS; last-mile delivery; MADM; OPA; sustainability; urban logistics","Viet Nam; COVID-19; electronic commerce; logistics; sensitivity analysis; sustainability",{"$nulls":4},"Hong Bang International University; FPT University; National Kaohsiung University of Science and Technology, NKUST","The authors appreciate the support from the National Kaohsiung University of Science and Technology, Taiwan; Hong Bang International University, Vietnam; and FPT University, Vietnam. ","Mangiaracina R., Perego A., Seghezzi A., Tumino A., Innovative Solutions to Increase Last-Mile Delivery Efficiency in B2C e-Commerce: A Literature Review, Int. J. Phys. Distrib. Logist. 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Appl, 37, pp. 7745-7754, (2010); Agarwal S., Kant R., Shankar R., Evaluating Solutions to Overcome Humanitarian Supply Chain Management Barriers: A Hybrid Fuzzy SWARA—Fuzzy WASPAS Approach, Int. J. Disaster Risk Reduct, 51, (2020); Ecer F., Pamucar D., Sustainable Supplier Selection: A Novel Integrated Fuzzy Best Worst Method (F-BWM) and Fuzzy CoCoSo with Bonferroni (CoCoSo’B) Multi-Criteria Model, J. Clean. Prod, 266, (2020); Roszkowska E., Kacprzak D., The Fuzzy Saw and Fuzzy TOPSIS Procedures Based on Ordered Fuzzy Numbers, Inf. Sci, 369, pp. 564-584, (2016); Bozanic D., Tesic D., Kocic J., Multi-Criteria FUCOM—Fuzzy MABAC Model for the Selection of Location for Construction of Single-Span Bailey Bridge, Decis. Mak. Appl. Manag. Eng, 2, pp. 132-146, (2019); Yazdani M., Alidoosti A., Zavadskas E.K., Risk Analysis of Critical Infrastructures Using Fuzzy Copras, Econ. Res.-Ekon. Istraživanja, 24, pp. 27-40, (2011); Toslak M., Ulutas A., Urea S., Stevic Z., Selection of Peanut Butter Machine by the Integrated PSI-SV-MARCOS Method, Int. J. Knowl.-Based Intell. Eng. Syst, 27, pp. 73-86, (2023); Shekhovtsov A., Kolodziejczyk J., Salabun W., Fuzzy Model Identification Using Monolithic and Structured Approaches in Decision Problems with Partially Incomplete Data, Symmetry, 12, (2020); Shekhovtsov A., Wieckowski J., Kizielewicz B., Salabun W., Towards Reliable Decision-Making in The Green Urban Transport Domain, Facta Univ. Ser. Mech. Eng, 20, (2022)","F.D. Wibowo; Department of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung, 80778, Taiwan; email: i110143105@nkust.edu.tw",null,"Multidisciplinary Digital Publishing Institute (MDPI)",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85170396976"]
["Yunlin C.","Yunlin, Chen (58690634800)",5.86906348E10,"Awareness of green logistics technology, certification, and standards by logistics practitioners at Chinese e-commerce company, Jing Dong",2023.0,"Asian Journal of Shipping and Logistics",39.0,4.0,null,37.0,46.0,9.0,0.0,"10.1016/j.ajsl.2023.10.004","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85176473619&doi=10.1016%2fj.ajsl.2023.10.004&partnerID=40&md5=14511f5edc78b8e3960406f1c1b852df","The School of Management, Univerisiti Sains Malaysia, Pulau Pinang, Gelugor, 11800, Malaysia","Yunlin C., The School of Management, Univerisiti Sains Malaysia, Pulau Pinang, Gelugor, 11800, Malaysia","This study examined the awareness of the environmental and sustainability impacts of green logistics technologies, standards, and certifications by logistics practitioners at the Chinese e-commerce company, Jing Dong. 309 surveys based on questionnaires were gathered using stratified snowball sampling. They were then encoded and examined through descriptive statistics, chi-square tests, and regression techniques. The outcomes indicated that roughly 33 % of the organization's logistics professionals understand the beneficial effects of logistics operations on the environment, and an equivalent proportion comprehended the significance of sustainable development. Additionally, the classifications of logistics operations and years of industry expertise significantly have influenced various aspects of green logistics technology, standards, and certification. The research also has indicated that the acceptance of green logistics technology is contingent on the backgrounds and classifications of the company's logistics experts. This suggests that Jing Dong should strengthen the implementation of relevant logistics policies and raise awareness among logistics practitioners regarding green logistics technology, standards, and certification. © 2023 The Authors","Environment; Green logistics certification and standards; Green logistics technology; Logistics; Sustainability",{"$nulls":7},"Adelson J.L., McCoach D.B., Measuring the mathematical attitudes of elementary students: The effects of a 4-point or 5-point Likert-type scale, Educational and Psychological Measurement, 70, 5, pp. 796-807, (2010); Akhtar S., Shah S.W.A., Rafiq M., Khan A., Research design and statistical methods in Pakistan Journal of Medical Sciences (PJMS), Pakistan Journal of Medical Sciences, 32, 1, (2016); Almeida L., Ecolabels and organic certification for textile products. Roadmap to Sustainable Textiles and Clothing, Regulatory Aspects and Sustainability Standards of Textiles and the Clothing Supply Chain, pp. 175-196, (2015); Anser M.K., Yousaf Z., Zaman K., Green technology acceptance model and green logistics operations: “to see which way the wind is blowing, Frontiers in Sustainability, 1, (2020); Cao J., (2020); Champion A., (2022); Correia J.B., Steering G.F.E., (2013); Delubac A., (2023); (2022); Fernando J., (2022); Finstad K., Response interpolation and scale sensitivity: Evidence against 5-point scales, Journal of Usability Studies, 5, 3, pp. 104-110, (2010); Haoxiang R., (2022); Henriques I., Sadorsky P., The determinants of an environmentally responsive firm: An empirical approach, Journal of Environmental Economics and Management, 30, 3, pp. 381-395, (1996); (2016); (2020); Kenlon T., (2021); (2008); Kidron E., (2021); Lin C.Y., Factors affecting innovation in logistics technologies for logistics service providers in China, Journal of Technology Management in China, 2, 1, pp. 22-37, (2007); Liu C., Ma T., Green logistics management and supply chain system construction based on internet of things technology, Sustainable Computing: Informatics and Systems, 35, (2022); Liu S., Zhang Y., Liu Y., Wang L., Wang X.V., An ‘Internet of Things’ enabled dynamic optimization method for smart vehicles and logistics tasks, Journal of Cleaner Production, 215, pp. 806-820, (2019); Lu X., White H., Robustness checks and robustness tests in applied economics, Journal of Econometrics, 178, pp. 194-206, (2014); Lukewille A., Aviation and shipping emissions in focus, (2021); Maji I.K., Saudi N.S.M., Yusuf M., An assessment of green logistics and environmental sustainability: Evidence from Bauchi, Cleaner Logistics and Supply Chain, 6, (2023); Meegeren P.V., Blue bags or refuse tourism: Social acceptance of closed policymaking, Society & Natural Resources, 14, 1, pp. 77-86, (2001); Menti F., Romero D., Jacobsen P., A technology assessment and implementation model for evaluating socio-cultural and technical factors for the successful deployment of logistics 4.0 technologies, Technological Forecasting and Social Change, 190, (2023); Montgomery D.C., Runger G.C., Hubele N.F., Engineering statistics, (2009); Olivo F., Junqueira M.C., Furlan M.B., Justi P.A., de Morais Lima P., Monetary losses caused by the absence of packaging reverse logistics: environmental and economic impacts, Journal of Material Cycles and Waste Management, 22, 6, pp. 1801-1817, (2020); Pandis N., The chi-square test, American Journal of Orthodontics and Dentofacial Orthopedics, 150, 5, pp. 898-899, (2016); Pattberg P., What role for private rule-making in global environmental governance? Analysing the Forest Stewardship Council (FSC), International Environmental Agreements: Politics, Law and Economics, 5, pp. 175-189, (2005); Perez-Vicente S., Ruiz M.E., Descriptive statistics, Allergologia et Immunopathologia, 37, 6, pp. 314-320, (2009); Pinto L.F.G., Gardner T., McDermott C.L., Ayub K.O.L., Group certification supports an increase in the diversity of sustainable agriculture network–rainforest alliance certified coffee producers in Brazil, Ecological Economics, 107, pp. 59-64, (2014); Rao P., Holt D., Do green supply chains lead to competitiveness and economic performance?, International Journal of Operations & Production Management, 25, 9, pp. 898-916, (2005); Ritchie H., (2020); Sanderford A.R., McCoy A.P., Keefe M.J., Adoption of energy star certifications: Theory and evidence compared, Building Research & Information, 46, 2, pp. 207-219, (2018); Sonnad S.S., Describing data: Statistical and graphical methods, Radiology, 225, 3, pp. 622-628, (2002); Sotvaldieva A.S., (2023); Sun H., Li J., Behavioural choice of governments, enterprises and consumers on recyclable green logistics packaging, Sustainable Production and Consumption, 28, pp. 459-471, (2021); Tian G., Lu W., Zhang X., Zhan M., Dulebenets M.A., Aleksandrov A., Fathollahi-Fard A.M., Ivanov M., A survey of multi-criteria decision-making techniques for green logistics and low-carbon transportation systems, Environmental Science and Pollution Research, 30, 20, pp. 57279-57301, (2023); Villena V.H., Gioia D.A., (2020); Wang F., Hu Y., Research on certification standards of LSQ, American Journal of Industrial and Business Management, 6, 8, pp. 895-899, (2016); Wyatt R.C., Meyers L.S., Psychometric properties of four 5-point Likert-type response scales, Educational and psychological Measurement, 47, 1, pp. 27-35, (1987); Wynne R.D., The emperor's new eco-logos? A critical review of the Scientific Certification Systems environmental report card and the Green Seal certification mark programs, Virginia Environmental Law Journal, pp. 51-149, (1994); Xiang N., Xu F., Sha J., Simulation analysis of China's energy and industrial structure adjustment potential to achieve a low-carbon economy by 2020, Sustainability, 5, 12, pp. 5081-5099, (2013); Zhang G., Zhao Z., Green packaging management of logistics enterprises, Physics Procedia, 24, pp. 900-905, (2012); Zhang L., Xu M., Chen H., Li Y., Chen S., (2022); Zhu Y., Research on sustainable development of green logistics in China, World Maritime University Dissertations, (2012); Zujewski B., (2023)",null,null,"Korean Association of Shipping and Logistics, Inc.",{"$nulls":5},2.0925212E7,null,null,null,"English","Asian J. Shipp. Logist.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85176473619"]
["Saker A.; Eltawil A.; Ali I.","Saker, Amira (58634152300); Eltawil, Amr (35242211900); Ali, Islam (55872915700)","58634152300; 35242211900; 55872915700","Adaptive Large Neighborhood Search Metaheuristic for the Capacitated Vehicle Routing Problem with Parcel Lockers",2023.0,"Logistics",7.0,4.0,72.0,null,null,null,0.0,"10.3390/logistics7040072","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85180677126&doi=10.3390%2flogistics7040072&partnerID=40&md5=aac21013af20a9f22f0f22ea8f41d64e","Department of Industrial and Manufacturing Engineering, Egypt-Japan University of Science and Technology (EJUST, Alexandria, 21934, Egypt; Production & Mechanical, Design Engineering Department, Faculty of Engineering, Mansoura University, Mansoura, 35516, Egypt; Production Engineering Department, Faculty of Engineering, Alexandria University, Alexandria, 21544, Egypt","Saker A., Department of Industrial and Manufacturing Engineering, Egypt-Japan University of Science and Technology (EJUST, Alexandria, 21934, Egypt, Production & Mechanical, Design Engineering Department, Faculty of Engineering, Mansoura University, Mansoura, 35516, Egypt; Eltawil A., Department of Industrial and Manufacturing Engineering, Egypt-Japan University of Science and Technology (EJUST, Alexandria, 21934, Egypt, Production Engineering Department, Faculty of Engineering, Alexandria University, Alexandria, 21544, Egypt; Ali I., Department of Industrial and Manufacturing Engineering, Egypt-Japan University of Science and Technology (EJUST, Alexandria, 21934, Egypt, Production Engineering Department, Faculty of Engineering, Alexandria University, Alexandria, 21544, Egypt","Background: The growth of e-commerce necessitates efficient logistics management to address rising last-mile delivery challenges. To overcome some of the last-mile delivery costs, parcel lockers as a delivery option, can be an alternative solution. This study presents the Capacitated Vehicle Routing Problem with Delivery Options (CVRPDO), which includes locker delivery. Methods: this problem is solved with An Adaptive Large Neighborhood Search (ALNS). The solution suggests some specific destroy and repair operators and integrates them with various selection schemes. The proposed method results are compared with the exact solution of the MIP model of the problem for validation. Results: Objective function values improved by 25%, 30%, 7%, 5%, and 6% for 1000, 800, 600, 400, and 200 customers, respectively, when using a 120-s ALNS runtime compared to the MIP model with a 3-h runtime. Conclusions: the CVRPDO problem involves creating a set of routes for ve-hicles that visit each customer at their delivery location or deliver their parcels to one of the lockers. These routes should respect the capacity of each vehicle and locker while minimizing the total routing costs and the number of utilized vehicles. The problem is resolved by ALNS algorithm, which outperformed the MIP model. © 2023 by the authors.","ALNS; delivery options; parcel lockers; shared delivery locations",{"$nulls":5},"Egypt-Japan University of Science and Technology, E-JUST; Ministry of Higher Education, MOHE; Japan International Cooperation Agency, JICA","This work was supported by the Egyptian Ministry of Higher Education Grant and the Japanese International Cooperation Agency (JICA) in the scope of Egypt-Japan University of Science and Technology. ","Janjevic M., Winkenbach M., Characterizing urban last-mile distribution strategies in mature and emerging e-commerce markets, Transp. Res. Part A Policy Pract, 133, pp. 164-196, (2020); Mancini S., Gansterer M., Vehicle routing with private and shared delivery locations, Comput. Oper. Res, 133, (2021); Saker A., Iijima J., Ali I., Eltawil A., Capacitated Vehicle Routing Problem with Delivery Options: Private or Shared Location, Proceedings of the ICIEA 2023, the 10th International Conference on Industrial Engineering and Applications; Reyes D., Savelsbergh M., Toriello A., Vehicle routing with roaming delivery locations, Transp. Res. Part C Emerg. Technol, 80, pp. 71-91, (2017); Zhou L., Wang X., Ni L., Lin Y., Location-routing problem with simultaneous home delivery and customer’s pickup for city distribution of online shopping purchases, Sustainability, 8, (2016); Deutsch Y., Golany B., A parcel locker network as a solution to the logistics last mile problem, Int. J. Prod. Res, 56, pp. 251-261, (2018); Vakulenko Y., Hellstrom D., Hjort K., What’s in the parcel locker? Exploring customer value in e-commerce last mile delivery, J. Bus. Res, 88, pp. 421-427, (2018); Parcu P.L., Brennan T., Glass V., The Changing Postal Environment, (2020); Zhou L., Baldacci R., Vigo D., Wang X., A multi-depot two-echelon vehicle routing problem with delivery options arising in the last mile distribution, Eur. J. Oper. Res, 265, pp. 765-778, (2018); Dumez D., Lehuede F., Peton O., A large neighborhood search approach to the vehicle routing problem with delivery options, Transp. Res. Part B Methodol, 144, pp. 103-132, (2021); Friedrich C., Elbert R., Adaptive Large Neighborhood Search for Vehicle Routing Problems with Transshipment Facilities Arising in City Logistics, Comput. Oper. Res, 137, (2021); de Jong C., Kant G., Van Vlient A., On Finding Minimal Route Duration in the Vehicle Routing Problem with Multiple Time Windows. 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Res, 273, pp. 257-277, (2019); Rodrigue J.-P., The Geography of Transport Systems, (2020); Freitag M., Kotzab H., Pannek J., Lecture Notes in Logistics Dynamics in Logistics; Ropke S., Pisinger D., An adaptive large neighborhood search heuristic for the pickup and delivery problem with time windows, Transp. Sci, 40, pp. 455-472, (2006); Shaw P., Using constraint programming and local search methods to solve vehicle routing problems, Principles and Practice of Constraint Programming—CP98: 4th International Conference, CP98 Pisa, Italy, October 26–30, 1998 Proceedings 4, pp. 417-431, (1998); Wouda N.A., Lan L., ALNS: A Python implementation of the adaptive large neighbourhood search metaheuristic, J. Open Source Softw, 8, (2023); Gutin G., Yeo A., Zverovich A., Traveling salesman should not be greedy: Domination analysis of greedy-type heuristics for the TSP, Discret. Appl. Math, 117, pp. 81-86, (2002); Christiaens J., Berghe G.V., Slack induction by string removals for vehicle routing problems, Transp. Sci, 54, pp. 417-433, (2020); Santini A., Ropke S., Hvattum L.M., A comparison of acceptance criteria for the adaptive large neighbourhood search metaheuristic, J. Heuristics, 24, pp. 783-815, (2018); Solomon M.M., Algorithms for the Vehicle Routing and Scheduling Problems with Time Window Constraints, Oper. Res, 35, pp. 254-265, (1987)","A. Saker; Department of Industrial and Manufacturing Engineering, Egypt-Japan University of Science and Technology (EJUST, Alexandria, 21934, Egypt; email: amira.saker@ejust.edu.eg",null,"Multidisciplinary Digital Publishing Institute (MDPI)",{"$nulls":5},2.305629E7,null,null,null,"English","Logist.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85180677126"]
["Jaller M.; Xiao R.I.; Dennis-Bauer S.; Rivera-Royero D.; Pahwa A.","Jaller, Miguel (36158256500); Xiao, Runhua (Ivan) (58623928200); Dennis-Bauer, Sarah (58537380600); Rivera-Royero, Daniel (57190385230); Pahwa, Anmol (57214588705)","36158256500; 58623928200; 58537380600; 57190385230; 57214588705","Estimating last-mile deliveries and shopping travel emissions by 2050",2023.0,"Transportation Research Part D: Transport and Environment",123.0,null,103913.0,null,null,null,0.0,"10.1016/j.trd.2023.103913","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85172723373&doi=10.1016%2fj.trd.2023.103913&partnerID=40&md5=7db89b5c7747b1e6ebc7b173eeb67195","Department of Civil and Environmental Engineering, University of California, Davis, One Shields Ave Ghausi Hall 3143, Davis, 95616, CA, United States; Sustainable Freight Research Program, Institute of Transportation Studies, Davis, United States","Jaller M., Sustainable Freight Research Program, Institute of Transportation Studies, Davis, United States; Xiao R.I., Department of Civil and Environmental Engineering, University of California, Davis, One Shields Ave Ghausi Hall 3143, Davis, 95616, CA, United States; Dennis-Bauer S., Department of Civil and Environmental Engineering, University of California, Davis, One Shields Ave Ghausi Hall 3143, Davis, 95616, CA, United States; Rivera-Royero D., Department of Civil and Environmental Engineering, University of California, Davis, One Shields Ave Ghausi Hall 3143, Davis, 95616, CA, United States; Pahwa A., Department of Civil and Environmental Engineering, University of California, Davis, One Shields Ave Ghausi Hall 3143, Davis, 95616, CA, United States","This study investigates the potential ramifications of e-commerce on shopping behaviors, travel, and residential deliveries by the year 2050. A comprehensive modeling framework has been devised to predict alterations in shopping behavior, generate future synthesized populations for major metropolitan statistical areas (MSAs), and estimate parameters associated with shopping travel and last-mile delivery alternatives. This framework relies on an integrated simulation that produces shopping and delivery travel, incorporating techniques such as Weighted Multinomial Logit and Monte Carlo simulation. The findings reveal that population growth and socio-demographic factors will differentially impact shopping behaviors across various MSAs. Furthermore, shopping travel and delivery patterns are subject to the influence of the spatial distribution of trips and transportation mode selection. The study underscores the significance of contemplating the implementation of clean energy fleets and effective transportation strategies to mitigate the negative externalities related to shopping activities. © 2023 The Author(s)","E-commerce; Externalities; Monte Carlo simulation; Shopping behavior","Intelligent systems; Monte Carlo methods; Population statistics; Comprehensive modeling; E- commerces; Externality; Integrated simulations; Last mile; Modelling framework; Monte Carlo's simulation; Shopping behaviour; Synthesised; Travel emissions; computer simulation; electronic commerce; estimation method; Monte Carlo analysis; shopping activity; spatial distribution; traffic emission; transportation mode; Electronic commerce",{"$nulls":4},"Network for the Digital Economy and the Environment; University of California Institute of Transportation Studies, UC ITS; Internet Society Foundation; National Center for Sustainable Transportation Technology, NCSTT","Funding text 1: This research would like to acknowledge the National Center for Sustainable Transportation (NCST) support at the Institute of Transportation Studies, University of California, Davis. Additional support for this work was provided by the Network for the Digital Economy and the Environment through funding from the Internet Society Foundation.; Funding text 2: This research would like to acknowledge the National Center for Sustainable Transportation (NCST) support at the Institute of Transportation Studies, University of California, Davis. Additional support for this work was provided by the Network for the Digital Economy and the Environment through funding from the Internet Society Foundation. ","Bridges E., Fowler K., Grocery Shopping before, during and after the Pandemic: A Qualitative Study, Fam. Consum. Sci. Res. J., 51, 1, pp. 35-50, (2022); Brown J.R., Guiffrida A.L., Carbon emissions comparison of last mile delivery versus customer pickup, Int. J Log. Res. Appl., 17, 6, pp. 503-521, (2014); Cao X.J., Xu Z., Douma F., The interactions between e-shopping and traditional in-store shopping: an application of structural equations model, Transportation, 39, 5, pp. 957-974, (2012); Chen Q., Conway A., (2016); Comi A., Nuzzolo A., Exploring the Relationships Between e-shopping Attitudes and Urban Freight Transport, Transp. Res. Procedia, 12, pp. 399-412, (2016); Cullinane S., Et al., pp. 185-196, (2017); Dias F.F., Lavieri P.S., Sharda S., Khoeini S., Bhat C.R., Pendyala R.M., Pinjari A.R., Ramadurai G., Srinivasan K.K., A comparison of online and in-person activity engagement: The case of shopping and eating meals, Transport. Rese. Part C: Emerging Technol., 114, pp. 643-656, (2020); (2022); Durand B., Gonzalez-Feliu J., Urban Logistics and E-Grocery: Have Proximity Delivery Services a Positive Impact on Shopping Trips?, Procedia. Soc. Behav. Sci., 39, pp. 510-520, (2012); Ecola L., Lu H., Rohr C., (2020); Farag S., Schwanen T., Dijst M., Faber J., Shopping online and/or in-store? A structural equation model of the relationships between e-shopping and in-store shopping, Transp. Res. A Policy Pract., 41, 2, pp. 125-141, (2007); Fuhs C., Obenberger J., Development of High-Occupancy Vehicle Facilities: Review of National Trends, Transp. Res. Rec., 1781, 1, pp. 1-9, (2002); Garver M.S., Et al., pp. 128-151, (2012); (2020); Gramling K., Orschell J., Chernoff J., (2021); Hauer M.E., Population projections for U.S. counties by age, sex, and race controlled to shared socioeconomic pathway, Sci. Data, 6, 1, (2019); Holguin-Veras J., Jaller M., Destro L., Ban X., Lawson C., Levinson H.S., Freight Generation, Freight Trip Generation, and Perils of Using Constant Trip Rates, Transp. Res. Rec., 2224, 1, pp. 68-81, (2011); Holguin-Veras J., Xu N., Jaller M., Mitchell J., A dynamic spatial price equilibrium model of integrated urban production-transportation operations considering freight delivery tours, Transp. Sci., 50, 2, pp. 489-519, (2016); Holguin-Veras J., (2016); Jaller M., Sanchez S., Green J., Fandino M., Quantifying the Impacts of Sustainable City Logistics Measures in the Mexico City Metropolitan Area, Transp. Res. Procedia, 12, pp. 613-626, (2016); Jaller M., Otero-Palencia C., Pahwa A., Automation, electrification, and shared mobility in urban freight: opportunities and challenges, Transp. Res. Procedia, 46, pp. 13-20, (2020); Jaller M., Otero-Palencia C., Yie-Pinedo R., ‘nventory and fleet purchase decisions under a sustainable regulatory environment, Supply Chain Forum: An Int. J., 21, 1, pp. 53-65, (2020); Jaller M., Pahwa A., Evaluating the environmental impacts of online shopping: A behavioral and transportation approach, Transp. Res. Part D: Transp. Environ., 80, (2020); Jaller M., Pineda L., Ambrose H., Kendall A., Empirical analysis of the role of incentives in zero-emission last-mile deliveries in California, J. Clean. Prod., 317, (2021); Jensen K.L., Yenerall J., Chen X., Yu T.E., US Consumers’ Online Shopping Behaviors and Intentions During and After the COVID-19 Pandemic, J. Agric. Appl. Econ., 53, 3, pp. 416-434, (2021); Keeling K.L., Schaefer J.S., Figliozzi M.A., Accessibility and Equity Analysis of Transit Facility Sites for Common Carrier Parcel Lockers, Transp. Res. Rec., 2675, 12, pp. 1075-1087, (2021); Le H.T.K., Carrel A.L., Shah H., Impacts of online shopping on travel demand: a systematic review, Transp. Rev., 42, 3, pp. 273-295, (2022); Lee R.J., Sener I.N., Mokhtarian P.L., Handy S.L., Relationships between the online and in-store shopping frequency of Davis, California residents, Transp. Res. A Policy Pract., 100, pp. 40-52, (2017); Pahwa A., Jaller M., A cost-based comparative analysis of different last-mile strategies for e-commerce delivery, Transport. Res. Part E: Logistics Transport. Rev., 164, (2022); Poraj-Kuczewski K.; Pourrahmani E., Jaller M., Crowdshipping in last mile deliveries: Operational challenges and research opportunities, Socioecon. Plann. Sci., 78, (2021); Punakivi M., Yrjola H., Holmstrom J., pp. 427-439, (2001); Rivera-Royero D., Jaller M., Kim C.-M., Spatio-Temporal Analysis of Freight Flows in Southern California, Transp. Res. Rec., 2675, 9, pp. 740-755, (2021); Shen S., Benedetti M.H., Zhao S., Wei L., Zhu M., Comparing distance and time as driving exposure measures to evaluate fatal crash risk ratios, Accid. Anal. Prev., 142, (2020); Siikavirta H., Et al., pp. 83-97, (2002); (2022); (2020); Srinivasan S., Bhat C.R., Modeling household interactions in daily in-home and out-of-home maintenance activity participation, Transportation, 32, 5, pp. 523-544, (2005); Stinson M., Auld J., Mohammadian A., A large-scale, agent-based simulation of metropolitan freight movements with passenger and freight market interactions, Procedia Comput. Sci., 170, pp. 771-778, (2020); Stinson M., Et al., pp. 1-7, (2019); (2021); Tozzi M., Corazza M.V., Musso A., Recurring Patterns of Commercial Vehicles Movements in Urban Areas: The Parma Case Study, Procedia. Soc. Behav. Sci., 87, pp. 306-320, (2013); (2020); Vallamsundar S., Lin J., (2011); Wang X., pp. 46-55, (2015); Wang S., Et al., (2022); Weltevreden J.W., Rietbergen T.V., E-Shopping Versus City Centre Shopping: the Role of Perceived City Centre Attractiveness, Tijdchr. Econ. Soc. Geogr., 98, 1, pp. 68-85, (2007); Wiese A., Toporowski W., Zielke S., Transport-related CO2 effects of online and brick-and-mortar shopping: A comparison and sensitivity analysis of clothing retailing, Transp. Res. Part D: Transp. Environ., 17, 6, pp. 473-477, (2012); Wygonik E., Goodchild A.V., Urban form and last-mile goods movement: Factors affecting vehicle miles travelled and emissions, Transp. Res. Part D: Transp. Environ., 61, pp. 217-229, (2018); Zhou Y., Wang X., Explore the relationship between online shopping and shopping trips: An analysis with the 2009 NHTS data, Transp. Res. A Policy Pract., 70, pp. 1-9, (2014)","R.I. Xiao; Department of Civil and Environmental Engineering, University of California, Davis, Davis, One Shields Ave Ghausi Hall 3143, 95616, United States; email: rhxiao@ucdavis.edu",null,"Elsevier Ltd",{"$nulls":5},1.3619209E7,null,"TRDTF",null,"English","Transp. Res. Part D Transp. Environ.","Article","Final","All Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85172723373"]
["Teodorescu D.; Aivaz K.-A.; Vancea D.P.C.; Condrea E.; Dragan C.; Olteanu A.C.","Teodorescu, Daniel (7003317773); Aivaz, Kamer-Ainur (35338759600); Vancea, Diane Paula Corine (35070500200); Condrea, Elena (26767647400); Dragan, Cristian (58245880700); Olteanu, Ana Cornelia (58536077500)","7003317773; 35338759600; 35070500200; 26767647400; 58245880700; 58536077500","Consumer Trust in AI Algorithms Used in E-Commerce: A Case Study of College Students at a Romanian Public University",2023.0,"Sustainability (Switzerland)",15.0,15.0,11925.0,null,null,null,1.0,"10.3390/su151511925","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85167904167&doi=10.3390%2fsu151511925&partnerID=40&md5=0e6183204fde98cac2da139acaf744c8","School of Education, Clark Atlanta University, Atlanta, 30314, GA, United States; Faculty of Economic Sciences, Ovidius University of Constanta, Constanta, 900573, Romania; Faculty of Navigation and Naval Transport, Constanta Maritime University, Constanta, 900663, Romania","Teodorescu D., School of Education, Clark Atlanta University, Atlanta, 30314, GA, United States; Aivaz K.-A., Faculty of Economic Sciences, Ovidius University of Constanta, Constanta, 900573, Romania; Vancea D.P.C., Faculty of Economic Sciences, Ovidius University of Constanta, Constanta, 900573, Romania; Condrea E., Faculty of Economic Sciences, Ovidius University of Constanta, Constanta, 900573, Romania; Dragan C., Faculty of Navigation and Naval Transport, Constanta Maritime University, Constanta, 900663, Romania; Olteanu A.C., Faculty of Navigation and Naval Transport, Constanta Maritime University, Constanta, 900663, Romania","The aim of this cross-sectional study was to investigate the factors associated with trust in AI algorithms used in the e-commerce industry in Romania. The motivation for conducting this analysis arose from the observation of a research gap in the Romanian context regarding this specific topic. The researchers utilized a non-probability convenience sample of 486 college students enrolled at a public university in Romania, who participated in a web-based survey focusing on their attitudes towards AI in e-commerce. The findings obtained from an ordinal logistic model indicated that trust in AI is significantly influenced by factors such as transparency, familiarity with other AI technologies, perceived usefulness of AI recommenders, and the students’ field of study. To ensure widespread acceptance and adoption by consumers, it is crucial for e-commerce companies to prioritize building trust in these new technologies. This study makes significant contributions to our understanding of how young consumers in Romania perceive and evaluate AI algorithms utilized in the e-commerce sector. The findings provide valuable guidance for e-commerce practitioners in Romania seeking to effectively leverage AI technologies while building trust among their target audience. © 2023 by the authors.","AI algorithms; ecommerce; familiarity with AI; perceived usefulness of AI; Romania; transparency; trust in AI","Romania; algorithm; electronic commerce; familiarity; perception; public attitude; questionnaire survey; university sector",{"$nulls":6},"Kumar T., Trakru O., The Collossal Impact of Artificial Intelligence in E-Commerce: Statistics and Facts, Int. Res. J. Eng. Technol. (IRJET), 6, pp. 570-572, (2019); Soni V.D., Emerging Roles of Artificial Intelligence in ecommerce, Int. J. Trend Sci. Res. Dev, 4, pp. 223-225, (2020); Chi O.H., Denton G., Gursoy D., Artificially intelligent device use in service delivery: A systematic review, synthesis, and research agenda, J. Hosp. Mark. Manag, 29, pp. 757-786, (2020); Gursoy D., Ch O.H., Lu L., Nunkoo R., Consumers acceptance of artificially intelligent (AI) device use in service delivery, Int. J. Inf. Manag, 49, pp. 157-169, (2019); Ba S., Pavlou P., Evidence of Trust Building Technology in Electronic Markets: Price Premiums and Buyer Behavior, MIS Q, 26, pp. 243-268, (2002); Gefen D., Karahanna E., Straub D., Trust and TAM in Online Shopping: An Integrated Model, MIS Q, 27, pp. 51-90, (2003); Cabrera-Sanchez J.-P., Ramos-de-Luna I., Carvajal-Trujillo E., Villarejo-Ramos A.F., Online Recommendation Systems: Factors Influencing Use in E-Commerce, Sustainability, 12, (2020); Siemon D., Ahmad R., Harms H., de Vreede T., Requirements and Solution Approaches to Personality-Adaptive Conversational Agents in Mental Health Care, Sustainability, 14, (2022); McKnight D.H., Cummings L., Chervany N.L., Initial Trust Formation in New Organizational Relationships, Acad. Manag. Rev, 23, pp. 473-490, (1998); Fang Y., Liu S., Wei K.K., Zhang P., Trust, satisfaction, and online repurchase intention: The moderating role of perceived effectiveness of e-Commerce institutional mechanisms, MIS Q, 38, pp. 407-428, (2014); Qureshi I., Fang Y., Ramsey E., Understanding online customer repurchasing intention and the mediating role of trust: An empirical investigation in two developed countries, Eur. J. Inf. Syst, 18, pp. 205-222, (2009); Gurses S., Troncoso C., Diaz C., Engineering Privacy by Design, Proceedings of the Computers, Privacy & Data Protection Conference; Acquisti A., Brandimarte L., Loewenstein G., Privacy and human behavior in the age of information, Science, 347, pp. 509-514, (2015); Mohd Rahim N.I., Iahad N.A., Yusof A.F., Al-Sharafi M.A., AI-Based Chatbots Adoption Model for Higher-Education Institutions: A Hybrid PLS-SEM-Neural Network Modelling Approach, Sustainability, 14, (2022); Guo X., Yu W., Guo Q., Trust building mechanisms in AI-powered service systems: The roles of explainability and transparency, Inf. Syst. Front, 22, pp. 477-494, (2020); Shin D., Kee K.F., Shin E.Y., Algorithm awareness: Why user awareness is critical for personal privacy in the adoption of algorithmic platforms?, Int. J. Inf. Manag, 65, (2022); Belanche D., Casalo L.V., Flavian C., Artificial Intelligence in FinTech: Understanding robo-advisors adoption among customers, Ind. Manag. Data Syst, 119, pp. 1411-1430, (2019); Horowitz M.C., Kahn L., Macdonald J., Schneider J., Adopting AI: How familiarity breeds both trust and contempt, AI Soc, 38, pp. 1-15, (2023); Smith A.M., Rainie L., Shneiderman B., Himelboim I., Algorithmic transparency in the era of artificial intelligence: The case of news recommender systems, J. Comput.-Mediat. Commun, 23, pp. 163-181, (2018); Nguyen C.H., Nguyen T.H., Factors affecting consumers’ perceptions and behaviors toward personal data collection, J. Consum. Behav, 18, pp. 69-83, (2019); Dutta-Bergman M.J., Complementarity in consumption of news types across traditional and new media, J. Broadcast. Electron. Media, 48, pp. 41-60, (2004); Li C., Pan R., Xin H., Deng Z., Research on Artificial Intelligence Customer Service on Consumer Attitude and Its Impact during Online Shopping, J. Phys. Conf. Ser, 1575, (2020); Wu Z., Liu J., Li D., The effects of AI recommendation algorithms on consumers’ purchase intentions in social commerce: The mediation of trust, Inf. Technol. People, 33, pp. 1082-1105, (2020); Kian T.P., Boon G.H., Fong S.W., Ai Y.J., Factors That Influence the Consumer Purchase Intention in Social Media Websites, Int. J. Supply Chain Manag, 6, pp. 209-214, (2017); Noreen U., Shafique A., Ahmed Z., Ashfaq M., Banking 4.0: Artificial Intelligence (AI) in Banking Industry & Consumer’s Perspective, Sustainability, 15, (2023); Li Y., Liang X., Zhang H., Huang X., User experience of chatbots in mobile shopping applications: An investigation using mobile eye-tracking, Inf. Manag, 56, pp. 103-157, (2019); Chen R., Wang Q., Xu W., Mining user requirements to facilitate mobile app quality upgrades with big data, Electron. Commer. Res, 38, (2019); Huang C.Y., Liao H.L., Huang Y.T., Consumers’ perceived value, attitude, and repurchase intention toward personalizedrecommendations: The moderating role of algorithm transparency, Internet Res, 31, pp. 654-677, (2021); Riaz M., Hashmi M.R., Linear Diophantine fuzzy set and its applications towards multi-attribute decision-making problems, J. Intell. Fuzzy Syst, 37, pp. 5417-5439, (2019); Almagrabi A.O., Abdullah S., Shams M., Al-Otaibi Y.D., Ashraf S., A new approach to q-linear Diophantine fuzzy emergency decision support system for COVID19, J. Ambient. Intell. Hum. Comput, 13, pp. 1687-1713, (2022); Riaz M., Hashmi M.R., Pamucar D., Chu Y.M., Spherical linear Diophantine fuzzy sets with modeling uncertainties in MCDM, Comput. Model. Eng. Sci, 126, pp. 1125-1164, (2021); Parimala M., Jafari S., Riaz M., Aslam M., Applying the Dijkstra Algorithm to Solve a Linear Diophantine Fuzzy Environment, Symmetry, 13, (2021); Li X., Li J., Zhang L., Liang X., Exploring the impact of artificial intelligence on fashion consumer purchase behavior, J. Retail. Consum. Serv, 44, pp. 226-233, (2018); Gupta A., Dogru T., Gao T., Role of artificial intelligence in customer experience management, J. Serv. Manag, 30, pp. 485-506, (2019); Zhao R., Benbasat I., Cavusoglu H., Do users always want to know more? Investigating the relationship between system transparency and users’ trust in advice-giving systems, Proceedings of the 27th European Conference on Information Systems (ECIS)","D. Teodorescu; School of Education, Clark Atlanta University, Atlanta, 30314, United States; email: dteodorescu@cau.edu",null,"Multidisciplinary Digital Publishing Institute (MDPI)",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85167904167"]
["Greening L.M.; Dahan M.; Erera A.L.","Greening, Lacy M. (58399727100); Dahan, Mathieu (57189358452); Erera, Alan L. (7801316807)","58399727100; 57189358452; 7801316807","Lead-Time-Constrained Middle-Mile Consolidation Network Design with Fixed Origins and Destinations",2023.0,"Transportation Research Part B: Methodological",174.0,null,102782.0,null,null,null,0.0,"10.1016/j.trb.2023.102782","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85163562288&doi=10.1016%2fj.trb.2023.102782&partnerID=40&md5=b900a4eb76e24f30f7ed9318838f0b60","H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA, United States","Greening L.M., H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA, United States; Dahan M., H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA, United States; Erera A.L., H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA, United States","Many large e-commerce retailers move sufficient freight volumes to operate private middle-mile consolidation networks for order fulfillment, transporting customer shipments from stocking locations to last-mile delivery partners in consolidated loads to reduce freight costs. We study a middle-mile network design optimization problem with fixed origins and destinations to build load consolidation plans that minimize cost and satisfy customer shipment lead-time constraints. We propose models that extend traditional flat network service network design problems to capture waiting delays between load dispatches and ensure that shipment lead-time requirements are satisfied with a desired probability. We approximate these chance constraints using hyperparameterized linear constraints, resulting in new mixed-integer programs (MIPs) for service network design. To find high-quality solutions to the proposed MIPs, we develop an effective integer-programming-based local search (IPBLS) heuristic that iteratively improves a solution by optimizing over a smartly selected subset of commodities. For the largest problem instances, we propose a two-phase IPBLS heuristic that first utilizes a simplified, restricted MIP that constrains leg waiting delays individually. Computational experiments using data from a large U.S.-based e-commerce partner demonstrate the significant impact of tight lead-time constraints on the structure of the consolidation network designs and their concomitant operating costs. Notably, tighter constraints lead to solutions with increased shipment consolidation and higher dispatch frequencies on selected key transportation lanes. Such solutions trade off higher shipment transit times with significantly reduced shipment waiting times to meet lead-time constraints at lower cost. © 2023 Elsevier Ltd","E-commerce logistics; Local search; Middle mile; Service network design","United States; Cost reduction; Customer satisfaction; Economic and social effects; Electric load dispatching; Electronic commerce; Local search (optimization); Normal distribution; Operating costs; Sales; Ships; E- commerces; E-commerce logistic; Leadtime; Local search; Middle mile; Mixed-integer programs; Network design; Origin and destinations; Service network designs; Time constraints; electronic commerce; freight transport; logistics; network design; operations technology; retailing; shipping; Integer programming",{"$nulls":6},"Andersen J., Crainic T., Christiansen M., Service network design with management and coordination of multiple fleets, European J. Oper. Res., 193, 2, pp. 377-389, (2009); Bai R., Wallace S., Li J., Chong A., Stochastic service network design with rerouting, Transp. Res. B, 60, pp. 50-65, (2014); Bakir I., Erera A., Savelsbergh M., Motor carrier service network design, Network Design with Applications To Transportation and Logistics, pp. 427-467, (2021); Boland N., Hewitt M., Marshall L., Savelsbergh M., The continuous-time service network design problem, Oper. Res., 65, 5, pp. 1303-1321, (2017); Boland N., Hewitt M., Marshall L., Savelsbergh M., The price of discretizing time: a study in service network design, EURO J. Transp. Logist., 8, 2, pp. 195-216, (2019); Bouzaiene-Ayari B., Gendreau M., Sang N., Modeling bus stops in transit networks : A survey and new formulations: Mass public transit, Transp. Sci., 35, 3, pp. 304-321, (2001); Cancela H., Mauttone A., Urquhart M., Mathematical programming formulations for transit network design, Transp. Res. B: Methodol., 77, pp. 17-37, (2015); Crainic T., Service network design in freight transportation, European J. Oper. Res., 122, 2, pp. 272-288, (2000); Crainic T., Ferland J., Rousseau J., A tactical planning model for rail freight transportation, Transp. Sci., 18, 2, pp. 165-184, (1984); Crainic T., Hewitt M., Toulouse M., Vu D., Service network design with resource constraints, Transp. Sci., 50, 4, pp. 1380-1393, (2016); Crainic T., Rousseau J., Multicommodity, multimode freight transportation: A general modeling and algorithmic framework for the service network design problem, Transp. Res. B, 20, 3, pp. 225-242, (1986); Crainic T., Roy J., OR tools for tactical freight transportation planning, European J. Oper. Res., 33, 3, pp. 290-297, (1988); Daganzo C., Fundamentals of Transportation and Traffic Operations, (1997); Demir E., Burgholzer W., Hrusovsky M., Arikan E., Jammernegg W., Van Woensel T., A green intermodal service network design problem with travel time uncertainty, Transp. Res. B, 93, pp. 789-807, (2016); Erera A., Hewitt M., Savelsbergh M., Zhang Y., Improved load plan design through integer programming based local search, Transp. Sci., 47, 3, pp. 412-427, (2013); Franceschi R.D., Fischetti M., Toth P., A new ILP-based refinement heuristic for vehicle routing problems, Math. Program., 105, 2, pp. 471-499, (2006); Hewitt M., Enhanced dynamic discretization discovery for the continuous time load plan design problem, Transp. Sci., 53, 6, pp. 1731-1750, (2019); Hewitt M., The flexible scheduled service network design problem, Transp. Sci., 56, 4, pp. 1000-1021, (2022); Hewitt M., Nemhauser G., Savelsbergh M., Combining exact and heuristic approaches for the capacitated fixed-charge network flow problem, INFORMS J. Comput., 22, 2, pp. 314-325, (2010); Hwang J., Park S., Kong I., An integer programming-based local search for large-scale multidimensional knapsack problems, Int. J. Comput. Sci. Eng., 3, 6, pp. 2257-2264, (2011); Jarrah A., Johnson E., Neubert L., Large-scale, less-than-truckload service network design, Oper. Res., 57, 3, pp. 609-625, (2009); Kang J., Kim S., Kim Y., Jang Y., Generalized convolution of uniform distributions, J. Appl. Math. Inform., 28, (2010); Leonard M., Amazon insources logistics with a growing network of delivery stations, (2021); Lin C., The freight routing problem of time-definite freight delivery common carriers, Transp. Res. B, 35, 6, pp. 525-547, (2001); Lindsey K., Erera A., Savelsbergh M., Improved integer programming-based neighborhood search for less-than-truckload load plan design, Transp. Sci., 50, 4, pp. 1360-1379, (2016); Lium A., Crainic T., Wallace S., A study of demand stochasticity in service network design, Transp. Sci., 43, 2, pp. 144-157, (2009); Marshall L., Boland N., Savelsbergh M., Hewitt M., Interval-based dynamic discretization discovery for solving the continuous-time service network design problem, Transp. Sci., 55, 1, pp. 29-51, (2021); Mauttone A., Cancela H., Urquhar M., Public transportation, Network Design with Applications to Transportation and Logistics, pp. 539-565, (2021); Pedersen M., Crainic T., Madsen O., Models and tabu search metaheuristics for service network design with asset-balance requirements, Transp. Sci., 43, 2, pp. 158-177, (2009); Powell W., A local improvement heuristic for the design of less-than-truckload motor carrier networks, Transp. Sci., 20, 4, pp. 246-257, (1986); Powell W., Koskosidis I., Shipment routing algorithms with tree constraints, Transp. Sci., 26, 3, pp. 230-245, (1992); Powell W., Sheffi Y., The load planning problem of motor carriers: Problem description and a proposed solution approach, Transp. Res. A: Gen., 17, 6, pp. 471-480, (1983); Savelsbergh M., Song J., An optimization algorithm for the inventory routing problem with continuous moves, Comput. Oper. Res., 35, 7, pp. 2266-2282, (2008); Scherr Y., Hewitt M., Neumann-Saavedra B., Mattfeld D., Dynamic discretization discovery for the service network design problem with mixed autonomous fleets, Transp. Res. B, 141, pp. 164-195, (2020); Scherr Y., Saavedra B.N., Hewitt M., Mattfeld D., Service network design with mixed autonomous fleets, Transp. Res. E, 124, pp. 40-55, (2019); Spiess H., Florian M., Optimal strategies: A new assignment model for transit networks, Transp. Res. B: Methodol., 23, 2, pp. 83-102, (1989); The Home Depot H., Home Depot strong - annual report 2020, (2021); Wang Z., Qi M., Robust service network design under demand uncertainty, Transp. Sci., 54, 3, pp. 676-689, (2020); Wayfair Z., Investor presentation - Q2 2021, (2021); Wieberneit N., Service network design for freight transportation: a review, OR Spectrum, 30, 1, pp. 77-112, (2008); Zhu E., Crainic T., Gendreau M., Scheduled service network design for freight rail transportation, Oper. Res., 62, 2, pp. 383-400, (2014)","L.M. Greening; H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, United States; email: lacy.greening@gatech.edu",null,"Elsevier Ltd",{"$nulls":5},1912615.0,null,null,null,"English","Transp. Res. Part B Methodol.","Article","Final",null,"Scopus","2-s2.0-85163562288"]
["Agrawal D.K.","Agrawal, Durgesh Kumar (55185438000)",5.5185438E10,"Increasing digital dissemination and online apparel shopping behaviour of Generation Y",2023.0,"Journal of Fashion Marketing and Management",28.0,1.0,null,28.0,44.0,16.0,0.0,"10.1108/JFMM-03-2022-0072","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85152047572&doi=10.1108%2fJFMM-03-2022-0072&partnerID=40&md5=ba53b2bfe769b64f111370786bc85e38","Independent Researcher & Vising Professor, National Capital Region, Delhi, Ghaziabad, India","Agrawal D.K., Independent Researcher & Vising Professor, National Capital Region, Delhi, Ghaziabad, India","Purpose: This paper aims to examine the online apparel shopping behaviour of Generation Y (Gen Y) in an unprecedented digital dissemination era. Design/methodology/approach: For this purpose, a “mixed-method approach” was used with an explanatory sequential research design. Logistic regression was conducted to identify the role of various contemporary elements of shopping motives. Fifteen semi-structured interviews were conducted to explain quantitative outputs. Findings: It finds that Gen Y consumers demonstrate “fashion-hunting”, “variety-seeking”, “status/recognition-seeking” and “deal-hunting” behaviours in online apparel shopping. “Haptic impressions” gained via hands and other “socio-psychological benefits” trigger their apparel shopping behaviour. They make better and more informed purchase decisions based on prior online research and user-generated content shared by friends/relatives on social media portraying the true characteristics of “digital natives”. They do not trust online retailers for premium apparel shopping due to associated “product risk” and lack of transparency in their “exchange/return/refund policy”. Finally, they are increasingly inspired to have an “integrated online and offline shopping experience”. Practical implications: Online retailers can use the findings of this study to develop more effective marketing strategies to serve Gen Y consumers. Originality/value: The study measured actual behaviours on a holistic gamut of shopping motives consisting of utilitarian, hedonic, physical product-specific (apparel) and emerging elements of shopping motives in the technology-enabled era of shopping exclusively. Therefore, the results of the study offer significant, realistic and useful theoretical contributions to the existing literature on the subject matter along with valuable inputs to practitioners alike. © 2023, Emerald Publishing Limited.","Apparel; Digital technology; Generation Y; Mixed-method approach; Online shopping behaviour",{"$nulls":7},"Agrawal D.K., Determining behavioural differences of Y and Z generational cohorts in online shopping, International Journal of Retail & Distribution Management, 50, 7, pp. 880-895, (2022); Agrawal D.K., Agrawal D.P., Singh D., The internet-based distribution systems: a framework for adoption, Information Systems: Debates, Applications and Impacts, pp. 109-140, (2019); Agrawal D.K., Gupta S., A new theoretical framework of shopping motives and channel preference behaviour in the digital era, International Journal of Consumer Studies, 47, 1, pp. 400-418, (2023); Ariffin S.K., Influence of consumers' perceived risk on consumers' online purchase intention, Journal of Research in Interactive Marketing, 12, 3, pp. 309-327, (2018); Bailey R., Sale or no sale, online shoppers always get great deals in India, (2019); Ten things you should know about e-commerce in India, (2022); Briedis H., Harris T., Pacchia M., Ungerman K., Ready to where: getting sharp on apparel omnichannel excellence, (2019); Dorie A., Loranger D., The multi-generation generational differences in channel activity, International Journal of Retail & Distribution Management, 48, 4, pp. 395-416, (2020); Faul F., Erdfelder E., Buchner A., Lang A.-G., Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses, Behaviour Research Methods, 41, pp. 1149-1160, (2009); New research shows the growing impact of online research on in-store purchases, (2018); Harrison R.L., Reilly T.M., Mixed methods designs in marketing research, Qualitative Market Research: An International Journal, 14, 1, pp. 7-26, (2011); Hirschman E.C., Holbrook M.B., Hedonic consumption: emerging concepts, methods and propositions, Journal of Marketing, 46, 2, pp. 92-101, (1982); James G., Witten D., Hastie T., Tibshirani R., An Introduction to Statistical Learning, (2013); Johnson R.B., Onwuegbuzie A.J., Turner L.A., Toward a definition of mixed methods research, Journal of Mixed Methods Research, 1, 2, pp. 112-133, (2007); Ladhari R., Gonthier J., Lajante M., Generation Y and online fashion shopping: orientations and profiles, Journal of Retailing and Consumer Services, 43, pp. 113-121, (2019); Lee S.M., Lee D., Untact: a new customer service strategy in the digital age, Service Business, 14, pp. 1-22, (2019); Li K., Chen Y., Zhang L., Exploring the influence of online reviews and motivating factors on sales: a meta-analytic study and the moderating role of product category, Journal of Retailing and Consumer Services, 55, pp. 102-107, (2020); Lissitsa S., Kol O., Generation X vs. Generation Y – a decade of online shopping, Journal of Retailing and Consumer Services, 31, pp. 304-312, (2016); Loupiac P., Goudey A., How website browsing impacts expectations of store features, International Journal of Retail & Distribution Management, 48, 1, pp. 92-108, (2020); State of fashion technology report 2022, (2022); MacKenzie S.B., Podsakoff P.M., Common method bias in marketing: causes, mechanisms, and procedural remedies, Journal of Retailing, 88, pp. 542-555, (2012); Malhotra N.K., Dash S., Marketing Research: An Applied Orientation, (2011); Nash J., Exploring how social media platforms influence fashion consumer decisions in the UK retail sector, Journal of Fashion Marketing and Management, 23, 1, pp. 82-103, (2019); Nisel R., Analysis of consumer characteristics which influence the determinants of buying decisions by the logistic regression model, Logistics Information Management, 14, 3, pp. 223-228, (2001); Parker C.J., Wenyu L., What influences Chinese fashion retail? Shopping motivations, demographics and spending, Journal of Fashion Marketing and Management, 23, 2, pp. 158-175, (2019); Parment A., Generation Y vs. baby boomers: shopping behaviour, buyer involvement and implications for retailing, Journal of Retailing and Consumer Services, 20, pp. 189-199, (2013); Pentecost R., Donoghue S., Thaichon P., Emerging from my youth-intra-cohort segmentation, International Journal of Retail & Distribution Management, 47, 5, pp. 571-588, (2019); Rahulan M., Troynikov O., Watson C., Janta M., Senner V., Consumer behaviour of generational cohorts for compression sportswear, Journal of Fashion Marketing Management, 19, 1, pp. 87-104, (2015); Ringler C., Nancy J., Sirianni N.J., Anders Gustafsson A., Peck J., Look but don't touch! The impact of active interpersonal haptic blocking on compensatory touch and purchase behaviour, Journal of Retailing, 95, 4, pp. 186-203, (2019); Roggeveen A.L., Grewal D., Schweiger E.B., The DAST framework for retail atmospherics: the impact of in- and out-of-store retail journey touchpoints on the customer experience, Journal of Retailing, 96, 1, pp. 128-137, (2020); Sheth J.N., An integrative theory of patronage preference and behaviour, Patronage Behavior and Retail Management, pp. 9-28, (1983); Singh R., Why do online grocery shoppers switch or stay? An exploratory analysis of consumers' response to online grocery shopping experience, International Journal of Retail & Distribution Management, 47, 12, pp. 1300-1317, (2019); Tauber E.M., Why people do shop?, Journal of Marketing, 36, 4, pp. 46-49, (1972); Tongco M.D.C., Purposive sampling as a tool for informant selection, Ethnobotany Research and Applications, 5, pp. 147-158, (2007); Valaei N., Nikhashemi S.R., Generation Y consumers' buying behaviour in fashion apparel industry: a moderation analysis, Journal of Fashion Marketing and Management, 21, 4, pp. 523-543, (2017); Wooldridge J.M., Introductory Econometrics: A Modern Approach, (2013); Future of consumption in fast-growth consumer markets: India, (2019); Zhu B., Kowatthanakul S., Satanasavapak P., Generation Y consumer online repurchase intention in Bangkok based on stimulus-organism-response (SOR) model, International Journal of Retail & Distribution Management, 48, 1, pp. 53-69, (2020); Leung L., Generational differences in content generation in social media: the roles of gratifications sought and of narcissism, Computers in Human Behaviour, 29, 3, pp. 997-1006, (2013)","D.K. Agrawal; Independent Researcher & Vising Professor, National Capital Region, Ghaziabad, Delhi, India; email: agrawal_dk2001@yahoo.com",null,"Emerald Publishing",{"$nulls":5},1.3612026E7,null,null,null,"English","J. Fash. Mark. Manage.","Article","Final",null,"Scopus","2-s2.0-85152047572"]
["Kaur M.; Rani S.","Kaur, Manpreet (57220556152); Rani, Shalli (56024601000)","57220556152; 56024601000","Recommender System: Towards Identification of Shilling Attacks in Rating System Using Machine Learning Algorithms",2023.0,"International Journal of Performability Engineering",19.0,7.0,null,443.0,451.0,8.0,0.0,"10.23940/ijpe.23.07.p3.443451","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85173231911&doi=10.23940%2fijpe.23.07.p3.443451&partnerID=40&md5=71b2df8f9ae8f58dff2c127d2d407b98","Baba Farid College of Engineering and Technology, Punjab, India; Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India","Kaur M., Baba Farid College of Engineering and Technology, Punjab, India; Rani S., Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India","Recommender System is a software tool that considers multiple parameters like the interest of a user, historical user data, browsing behavior, etc. to provide suitable recommendations. From e-commerce to social websites and from online research articles to entertainment, recommender systems have successfully rooted themselves in almost every application domain. Due to the popularity gain and people reliance on the recommendations generated in almost every domain, recommender systems have become vulnerable to online attacks known as shilling attacks or false rating attacks. An insight of recommender systems along with an analysis of shilling attacks is performed in this paper. These attacks are very common in social media to make the content popular among users by false ratings. Therefore, to find out the effect of false ratings, analysis of average, bandwagon attack, hybrid, and segment attacks are done on the basis of specificity, sensitivity, recall, precision and F-measure on Netflix and Movie lens dataset. These attacks should not affect food product items because most people purchase online items on the basis of ratings only. A good recommender system can overcome these attacks. Therefore, to deal with the above challenge of false ratings' attack, an ensemble learning model has been proposed to classify the individuals which are most similar to the target user so that relevant recommendations are made to each user as well. The proposed approach is validated for dataset of the German online reviews/rating of organic coffee, to determine the customer demand for a particular brand of coffee using Machine learning algorithms. The comparative results show that proposed approach is better than Locally Deep Support Vector Machine,Neural Network, Logistic Regression, Bayes Point, and Decision Forest algorithms with an accuracy of 98 percent.  © 2023 Totem Publisher, Inc.","attacks; machine learning; rating system; recommender system",{"$nulls":7},"Ricci F., Rokach L., Shapira B., Introduction to recommender systems handbook, Recommender systems handbook, pp. 1-35, (2010); Vinayak S., Sharma R., Singh R., MOVBOK: A personalized social network based cross domain recommender system, Indian Journal of Science and Technology, 9, 31, pp. 1-10, (2016); Sharma R., Singh R., Evolution of recommender systems from ancient times to modern era: a survey, Indian Journal of Science and Technology, 9, 20, pp. 1-12, (2016); Jannach D., Zanker M., Felfernig A., Friedrich G., Recommender systems: an introduction, (2010); Guo L., Liang J., Zhu Y., Luo Y., Sun L., Zheng X., Collaborative filtering recommendation based on trust and emotion, Journal of Intelligent Information Systems, 53, pp. 113-135, (2019); Friedrich G., Jannach D., Tutorial: Recommender Systems, Proceeding of the International Joint Conference on Artificial Intelligence, (2011); Azadjalal M.M., Moradi P., Abdollahpouri A., Jalili M., A trust-aware recommendation method based on Pareto dominance and confidence concepts, Knowledge-Based Systems, 116, pp. 130-143, (2017); Cao J., Wu Z., Mao B., Zhang Y., Shilling attack detection utilizing semi-supervised learning method for collaborative recommender system, World Wide Web, 16, pp. 729-748, (2013); Mane M.B., Panage B.M., Content analysis of university library portal: A detail study of Jayakar Library Portal, Savitribai Phule University of Pune, International Journal of Library and Information Science, 7, 5, pp. 109-116, (2015); Taylor W., Zhu X.H., Dekkers J., Marshall B., Socio-economic factors affecting home internet usage patterns in Central Queensland, (2003); Uppal M., Gupta D., Goyal N., Imoize A.L., Kumar A., Ojo S., Pani S.K., Kim Y., Choi J., A Real-Time Data Monitoring Framework for Predictive Maintenance Based on the Internet of Things, Complexity, (2023); Sharma R., Vinayak S., Singh R., Guide Me: A Research Work Area Recommender System, International Journal of Intelligent Systems and Applications, 8, 9, pp. 30-37, (2016); Lu J., Wu D., Mao M., Wang W., Zhang G, Recommender system application developments: a survey, Decision support systems, 74, pp. 12-32, (2015); Wang X., Zhao H., Wang Y., Tao H., Cao J., Supervised Prototypical Variational Autoencoder for Shilling Attack Detection in Recommender Systems, International Conference on Data Mining and Big Data, pp. 231-245, (2022); Moradi R., Hamidi H., A New Mechanism for Detecting Shilling Attacks in Recommender Systems Based on Social Network Analysis and Gaussian Rough Neural Network with Emotional Learning, International Journal of Engineering, 36, 2, pp. 321-334, (2023); Patel S.R., Bhoi P.R., Sharma A.M., Field-testing of SPRERI's open core gasifier for thermal application, Biomass and Bioenergy, 30, 6, pp. 580-583, (2006); Freeman C., Technology policy and economic performance, (1989); Zarrinkalam F., Kahani M., A multi-criteria hybrid citation recommendation system based on linked data, 2012 2nd International eConference on Computer and Knowledge Engineering (ICCKE), pp. 283-288, (2012); Ghauth K.I., Abdullah N.A., Learning materials recommendation using good learners' ratings and content-based filtering, Educational technology research and development, 58, pp. 711-727, (2010); Azizi M., Do H., A collaborative filtering recommender system for test case prioritization in web applications, Proceedings of the 33rd annual ACM symposium on applied computing, pp. 1560-1567, (2018); Nagarnaik P., Thomas A., Survey on recommendation system methods, 2015 2nd international conference on electronics and communication systems (ICECS), pp. 1603-1608, (2015); Raghuwanshi S.K., Pateriya R.K., Recommendation systems: Techniques, challenges, application, and evaluation, Soft Computing for Problem Solving: SocProS 2017, 2, pp. 151-164, (2019); Adomavicius G., Tuzhilin A., Context-aware recommender systems, Recommender systems handbook, pp. 217-253, (2010); Wu Z., Wu J., Cao J., Tao D., HySAD: A semi-supervised hybrid shilling attack detector for trustworthy product recommendation, Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining, pp. 985-993, (2012); Horsburgh B., Craw S., Massie S., Learning pseudo-tags to augment sparse tagging in hybrid music recommender systems, Artificial Intelligence, 219, pp. 25-39, (2015); Sharma S., Gupta K., Gupta D., Recommender System: A bibliometric analysis, IOP Conference Series: Materials Science and Engineering, 1022, 1, (2021); Gupta D., A comprehensive study of recommender systems for the internet of things, Journal of Physics: Conference Series, 1969, 1; Uppal M., Gupta D., Juneja S., Dhiman G., Kautish S., Cloud-based fault prediction using IoT in office automation for improvisation of health of employees, Journal of Healthcare Engineering, (2021)","S. Rani; Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India; email: shalli.rani@chitkara.edu.in",null,"Totem Publishers Ltd",{"$nulls":5},9731318.0,null,null,null,"English","Int. J. Perform. Eng.","Article","Final",null,"Scopus","2-s2.0-85173231911"]
["Zheng K.; Huo X.; Jasimuddin S.; Zhang J.Z.; Battaïa O.","Zheng, Kangning (36132654700); Huo, Xiaoxin (57459541600); Jasimuddin, Sajjad (57202559872); Zhang, Justin Zuopeng (58262864500); Battaïa, Olga (54881280800)","36132654700; 57459541600; 57202559872; 58262864500; 54881280800","Logistics distribution optimization: Fuzzy clustering analysis of e-commerce customers’ demands",2023.0,"Computers in Industry",151.0,null,103960.0,null,null,null,2.0,"10.1016/j.compind.2023.103960","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85162130603&doi=10.1016%2fj.compind.2023.103960&partnerID=40&md5=bc2524f66c44cacb5dee854a9be98ea0","School of Logistics and E-Commerce, Zhejiang Wanli University, Ningbo, China; Kedge Business School, France; Coggin College of Business, University of North Florida, Jacksonville, FL, United States","Zheng K., School of Logistics and E-Commerce, Zhejiang Wanli University, Ningbo, China; Huo X., School of Logistics and E-Commerce, Zhejiang Wanli University, Ningbo, China; Jasimuddin S., Kedge Business School, France; Zhang J.Z., Coggin College of Business, University of North Florida, Jacksonville, FL, United States; Battaïa O., Kedge Business School, France","E-commerce customers’ demands for delivery services have become more personalized, diversified, and complex. In this paper, we conduct cluster analysis on the customer demand attributes resulting in a list of attributes including quantitative and qualitative expectations that can be relevant for creating efficient distribution routes taking into account the delivery time and customer satisfaction. A fuzzy clustering optimization method is elaborated for the treatment of above-mentioned customer attributes for distribution management in order to generate efficient delivery strategies. A case study from Shun-Feng (SF) International Express is used to demonstrate the effectiveness and practicability of the proposed method. The obtained results show that both customer satisfaction and the net profit of the enterprise have considerably increased due to an efficient distribution management. © 2023 Elsevier B.V.","Classification of e-commerce customers; E-commerce; Fuzzy clustering; Logistics","Cluster analysis; Customer satisfaction; Fuzzy clustering; Sales; Classification of e-commerce customer; Customer demands; Customers' satisfaction; Delivery service; Distribution management; Distribution optimization; Distribution route; E- commerces; Fuzzy clustering analysis; Logistic distributions; Electronic commerce",{"$nulls":6},"Ballestar M.T., Grau-Carles P., Sainz J., Customer segmentation in ecommerce: applications to the cashback business model, J. Bus. 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["Kostecka Z.; Kopczewska K.","Kostecka, Zuzanna (58630325000); Kopczewska, Katarzyna (55757120600)","58630325000; 55757120600","Spatial CRM and location strategy: E-commerce solutions in the furniture industry. Case of IKEA pick-up points in Poland",2023.0,"Electronic Commerce Research and Applications",62.0,null,101308.0,null,null,null,0.0,"10.1016/j.elerap.2023.101308","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85173112495&doi=10.1016%2fj.elerap.2023.101308&partnerID=40&md5=7b19ff0ccc52bbf0da643d66b1782903","Faculty of Economic Sciences, University of Warsaw, Poland","Kostecka Z., Faculty of Economic Sciences, University of Warsaw, Poland; Kopczewska K., Faculty of Economic Sciences, University of Warsaw, Poland","E-commerce in the furniture industry is specific as delivery of heavy and oversized parcels with traditional channels is not feasible. Alternative solutions, aside from stationary shops, include pick-up points which combine e-commerce purchasing with stationary collection. Convenient pick-up locations that support environmental sustainability and offer cost savings is a domain of Spatial Customer Relationship Management (CRM), which is not enough discussed in the literature. In this paper we develop Spatial CRM for the location strategy of pick-up points in the furniture industry, using IKEA Poland as a case study. We provide the methodology for analysing the spatial range of population potential for collection points and stationary shops based on radial catchment areas of 20 km and precise population data from a grid 1 km × 1 km. We compare this market coverage with customers' attraction to IKEA shops expressed through Google Trends searches to evaluate location strategies for furniture retailers. Our regional approach is responsive to local needs, improves CRM, and remains cost-effective for businesses. Given the similarity of European furniture markets in terms of consumer perspective and e-commerce development, our analysis methodology can be adapted for use in other countries and markets. © 2023 The Author(s)","E-commerce; Furniture industry; Location strategy; Market coverage; Population potential; Spatial CRM","Catchments; Electronic commerce; Location; Pickups; Population statistics; Public relations; Sales; Sustainable development; Alternative solutions; Customer relationship management; E- commerces; Furniture industry; Location strategies; Management strategies; Market coverage; Pick up points; Population potential; Spatial customer relationship management; Cost effectiveness",{"$nulls":4},"Ministry of Education “School of Eagles; Ministry of Education, MOE; European Social Fund, ESF; Uniwersytet Warszawski, UW, (MNISW/2020/142/DIR/KH)","The article was prepared within the framework of a non-competitive project of the Ministry of Education “School of Eagles” based on the agreement between the Ministry of Education and the University of Warsaw, contract no. MNISW/2020/142/DIR/KH, signed on 26 May 2020. Project co-financed from the European Social Fund under the Operational Programme Knowledge Education Development 2014-2020. The APC was funded by University of Warsaw. ","Accenture, The Sustainable Last Mile, (2021); Alfaro M., Assessing gains of trade in monopolistic competition under the presence of industry leaders, Appl. Econ., 54, 41, pp. 4711-4724, (2022); Allen J., Piecyk M., Piotrowska M., McLeod F., Cherrett T., Ghali K., Nguyen T., Bektas T., Bates O., Friday A., Wise S., Austwick M., Understanding the impact of e-commerce on last-mile light goods vehicle activity in urban areas: The case of London, Transp. Res. Part D: Transp. Environ., 61, pp. 325-338, (2018); Alvarado C., Liu Y., E-commerce and the Environment: Finding the Optimal Location for In-store Pick-Up, (2019); Bilgihan A., Kandampully J., Zhang T.C., Towards a unified customer experience in online shopping environments, Int. J. Qual. Serv. 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["Baisholan N.; Turdalyuly M.; Gnatyuk S.; Baisholanova K.; Kubayev K.","Baisholan, Nazerke (57871534400); Turdalyuly, Mussa (57202317230); Gnatyuk, Sergiy (36184129600); Baisholanova, Karlygash (57195631252); Kubayev, Kazila (58509962300)","57871534400; 57202317230; 36184129600; 57195631252; 58509962300","IMPLEMENTATION OF MACHINE LEARNING TECHNIQUES TO DETECT FRAUDULENT CREDIT CARD TRANSACTIONS ON A DESIGNED DATASET",2023.0,"Journal of Theoretical and Applied Information Technology",101.0,13.0,null,5279.0,5287.0,8.0,0.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85166026687&partnerID=40&md5=6f5adfdd5da98f16f5faecc40418ac49","Al-Farabi Kazakh National University, Almaty, Kazakhstan; Satbayev University, Almaty, Kazakhstan; National Aviation University, Kyiv, Ukraine","Baisholan N., Al-Farabi Kazakh National University, Almaty, Kazakhstan; Turdalyuly M., Satbayev University, Almaty, Kazakhstan; Gnatyuk S., National Aviation University, Kyiv, Ukraine; Baisholanova K., Al-Farabi Kazakh National University, Almaty, Kazakhstan; Kubayev K., Al-Farabi Kazakh National University, Almaty, Kazakhstan","The rise in technology, particularly the increase in online shopping, has made it easier for cybercriminals to obtain and exploit stolen payment card information. Traditional fraud detection systems are finding it increasingly challenging to keep up with the rapid pace of technological advancement, leading to a surge in payment card fraud. Hence, it is essential for companies to continually update their fraud detection methods to keep up with the latest tactics employed by fraudsters. Machine learning algorithms have the ability to analyze large datasets and quickly identify anomalies or deviations from normal behaviour, making them a highly effective tool for payment card fraud detection. By detecting fraud early, organizations can minimize their financial losses and prevent further damage. In this study, we generated a credit card fraud dataset that comprises three types of fraud cases. The dataset is imbalanced, with a ratio of fraudulent transactions at 0.004, making it close to real-world data. To handle the imbalance in the dataset related to credit card fraud detection, we employed popular machine learning models such as Random Forest, Decision Tree, Logistic Regression, and XGBoost. The results showed that XGBoost and Random Forest outperformed the other models on both the training and test sets. However, the Decision Tree algorithm with unlimited depth had the highest average accuracy on the training set and the lowest average accuracy on the test set, indicating that this algorithm should be avoided due to overfitting. In conclusion, our study highlights the significance of using machine learning algorithms for payment card fraud detection. The results demonstrate that XGBoost and Random Forest are the most effective models for detecting credit card fraud in imbalanced datasets. By employing these models, organizations can improve their fraud detection capabilities and minimize the financial impact of payment card fraud. © 2023 Little Lion Scientific.","Anomaly Detection; Decision Tree; Fraud Detection; Imbalanced Dataset; Logistic Regression; Random Forest; Transaction Fraud Dataset",{"$nulls":7},"A triple threat across the Americas: KPMG 2022 Fraud Outlook, (2022); The Nilson Report 2021, Issue 1209, (2021); Abdou A.E., Wael K., Ismail R., Abdel-Badeeh S., Machine Learning Techniques for Credit Card Fraud Detection, Future Computing and Informatics Journal, 4, 2, (2019); Rundo F., Trenta F., di Stallo A.L., Battiato S., Machine learning for quantitative finance applications: A survey, Applied Sciences, 9, 24, (2019); Abakarim Y., Lahby M., Attioui A., An efficient real time model for credit card fraud detection based on deep learning, Proc. 12th Int. Conf. Intell. 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Eng, 7, pp. 402-403, (2019); Shirodkar N., Mandrekar P., Mandrekar R.S., Sakhalkar R., Kumar K.C., Aswale S., Credit card fraud detection techniques–A survey, Proceedings of the 2020 International Conference on Emerging Trends in Information Technology and Engineering (ic-ETITE), pp. 1-7, (2020); Seeja K., Zareapoor M., Fraudminer: A novel credit card fraud detection model based on frequent itemset mining, Scientific World Journal, pp. 1-10, (2014); Xu M., Watanachaturaporn P., Varshney P.K., Arora M.K., Decision tree regression for soft classification of remote sensing data, Remote Sensing of Environment, 97, 3, pp. 322-336, (2005); Dhieb N., Ghazzai H., Besbes H., Massoud Y., A secure AI-driven architecture for automated insurance systems: Fraud detection and risk measurement, IEEE Access, 8, pp. 58546-58558, (2020); Priscilla C.V., Prabha D.P., Influence of optimizing xgboost to handle class imbalance in credit card fraud detection, Proceedings of the 3rd International Conference on Smart Systems and Inventive Technology, ICSSIT, pp. 1309-1315, (2020); Gnatyuk S., Berdibayev R., Azarov I., Baisholan N., Lozova I., Modern Types of Databases for SIEM System Development, CEUR Workshop Proceedings, 3187, pp. 127-138, (2021); Kaggle",null,null,"Little Lion Scientific",{"$nulls":5},1.9928645E7,null,null,null,"English","J. Theor. Appl. Inf. Technol.","Article","Final",null,"Scopus","2-s2.0-85166026687"]
["Lara C.L.; Wassick J.","Lara, Cristiana L. (57191855570); Wassick, John (7801493949)","57191855570; 7801493949","The future of supply chain - a perspective from the process and online retail industries",2023.0,"Computers and Chemical Engineering",179.0,null,108401.0,null,null,null,1.0,"10.1016/j.compchemeng.2023.108401","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85171759601&doi=10.1016%2fj.compchemeng.2023.108401&partnerID=40&md5=f140e13519bc67f2d4cc016bec6afd24","Modeling and Optimization, Amazon.com, United States; Department of Chemical Engineering, Carnegie Mellon University, United States","Lara C.L., Modeling and Optimization, Amazon.com, United States; Wassick J., Department of Chemical Engineering, Carnegie Mellon University, United States","This paper discusses the broad challenges shared by online retail and the process industries operating global supply chains. Specifically, we discuss how process industry and online retailing differ in many aspects but have similar challenges ahead of them in order to remain competitive, keep up with the always increasing requirements of the customers and stakeholders, and gain efficiency. While both industries have been early adopters of decision support tools based on machine intelligence, both share unresolved challenges related to scalability, integration of decision-making over different time horizons (e.g., strategic, tactical and execution-level decisions) and across internal business units, and orchestration of human and computer-based decision-makers. We discuss future trends and research opportunities in the area of supply chain, and suggest that the methods of multi-agent systems supported by rigorous treatment of human decision-making in combination with machine intelligence is a great contender to address these critical challenges. © 2023 Elsevier Ltd","Artificial intelligence; e-commerce; Logistics; Process industry; Supply chain","Decision making; Decision support systems; Intelligent agents; Multi agent systems; Sales; Decision supports; E- commerces; Gain efficiency; Global supply chain; Machine intelligence; Online retailing; Online retails; Process industries; Retail industry; Support tool; Supply chains",{"$nulls":6},"Amazon, The evolution of Amazon's inventory planning system, (2021); Amazon, How Amazon's Middle Mile team helps packages make the journey to your doorstep, (2021); Amazon, Amazon is ready to deliver for customers and sellers this Prime Day, (2022); AspenTech, Aspen GDOT, (2022); Bassett M., Optimizing the design of new and existing supply chains at dow AgroSciences, Comput. Chem. Eng., 114, pp. 191-200, (2018); Bixby R.E., A brief history of linear and mixed-integer programming computation, Documenta Mathematica, pp. 107-121, (2012); Brunaud B., Models and Algorithms for Multilevel Supply Chain Optimization, (2019); Chen A.I.-A., Large-scale Optimization in Online-retail Inventory Management, (2017); Clemons E.K., Nunes P.F., Carrying your long tail: Delighting your consumers and managing your operations, Decis. Support Syst., 51, 4, pp. 884-893, (2011); Delipinar G.E., Kocaoglu B., Using SCOR model to gain competitive advantage: A literature review, Proc. - Soc. Behav. Sci., 229, pp. 398-406, (2016); Delling D., Goldberg A.V., Pajor T., Werneck R.F., Customizable route planning in road networks, Transp. Sci., 51, 2, pp. 566-591, (2017); DeValve L., Wei Y., Wu D., Yuan R., Understanding the value of fulfillment flexibility in an online retailing environment, Manuf. Serv. Oper. Manage., 25, 2, pp. 391-408, (2023); dos Santos D.S., Bazzan A.L.C., Distributed clustering for group formation and task allocation in multiagent systems: A swarm intelligence approach, Appl. Soft Comput., 12, 8, pp. 2123-2131, (2012); Eppen G.D., Effects of centralization on expected costs in a multi-location newsboy problem, Manage. Sci., 25, 5, pp. 498-501, (1979); Faugere L., Klibi W., White C., Montreuil B., Dynamic pooled capacity deployment for urban parcel logistics, European J. Oper. Res., 303, 2, pp. 650-667, (2022); FourKites, Transform your supply chain with a real-time visibility platform, (2022); Gil M., Albert M., Fons J., Pelechano V., Engineering human-in-the-loop interactions in cyber-physical systems, Inf. Softw. Technol., 126, (2020); Govindarajan A., Sinha A., Uichanco J., Joint inventory and fulfillment decisions for omnichannel retail networks, Nav. Res. Logist., 68, 6, pp. 779-794, (2021); Gupta R., Zhang Q., Decomposition and adaptive sampling for data-driven inverse linear optimization, INFORMS J. Comput., 34, 5, pp. 2720-2735, (2022); Gupta R., Zhang Q., Efficient learning of decision-making models: A penalty block coordinate descent algorithm for data-driven inverse optimization, Comput. Chem. Eng., 170, (2023); Hao K., The computing power needed to train AI is now rising seven times faster than ever before, (2019); Housni O.E., Goyal V., Humair S., Mouchtaki O., Sadighian A., Wu J., Joint assortment and inventory planning for heavy tailed demand, MSOM 2021, (2021); Jarrahi M.H., Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making, Bus. Horiz., 61, 4, pp. 577-586, (2018); Jones A.T., Romero D., Wuest T., Modeling agents as joint cognitive systems in smart manufacturing systems, Manuf. Lett., 17, pp. 6-8, (2018); Karlinsky N., How artificial intelligence helps Amazon deliver, (2019); Lara C.L., Koenemann J., Nie Y., de Souza C.C., Scalable timing-aware network design via lagrangian decomposition, European J. Oper. Res., 309, 1, pp. 152-169, (2023); Liu Y., Han T., Ma S., Zhang J., Yang Y., Tian J., He H., Li A., He M., Liu Z., Wu Z., Zhu D., Li X., Qiang N., Shen D., Liu T., Ge B., Summary of ChatGPT/GPT-4 research and perspective towards the future of large language models, (2023); Maggiar A., Song I., Muharremoglu A., Multi-echelon inventory management for a non-stationary capacitated distribution network, Optim. Online, (2022); Maravelias C.T., Integration of production planning and scheduling, 10th International Symposium on Process Systems Engineering: Part A, Computer Aided Chemical Engineering, 27, pp. 117-118, (2009); Ni D., Xiao Z., Lim M.K., A systematic review of the research trends of machine learning in supply chain management, Int. J. Mach. Learn. Cybern., 11, pp. 1463-1482, (2020); Perez H.D., Wassick J.M., Grossmann I.E., Scheduling of material and information flows in the manufacturing of chemicals for the order-to-cash process of a digital supply chain, 14th International Symposium on Process Systems Engineering, Computer Aided Chemical Engineering, 49, pp. 523-528, (2022); RoboCup Federation, RoboCup rescue simulation league, (2023); Stanford University, Gathering Strength, Gathering Storms: The One Hundred Year Study on Artificial Intelligence (AI100) 2021 Study Panel Report: Technical Report, (2021); Sull D., Closing the gap between strategy and execution, MIT Sloan Manage. Rev., 48, 4, pp. 30-38, (2007); SupplyChainWorld, The dow chemical company, (2015); Tarasov K., Amazon is making its own containers and bypassing supply chain chaos with chartered ships and long-haul planes, (2021); Walmart, Our retail divisions, (2005); Wang L., Wang S., Gong Y., Peng L., Optimizing a multi-echelon location-inventory problem with joint replenishment: A Lipschitz ϵ-optimal approach using Lagrangian relaxation, Comput. Oper. Res., 151, (2023); Wassick J.M., Enterprise-wide optimization in an integrated chemical complex, Comput. Chem. Eng., 33, 12, pp. 1950-1963, (2009); Wenzel H., Smit D., Sardesai S., A literature review on machine learning in supply chain management, Artificial Intelligence and Digital Transformation in Supply Chain Management: Innovative Approaches for Supply Chains. Proceedings of the Hamburg Int, Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), 27, pp. 413-441, (2019); Xu P.J., Order Fulfillment in Online Retailing: What Goes Where, (2005); Ye D., Zhang M., Vasilakos A.V., A survey of self-organization mechanisms in multiagent systems, IEEE Trans. Syst. Man Cybern.: Syst., 47, 3, pp. 441-461, (2017); You F., Grossmann I.E., Stochastic inventory management for tactical process planning under uncertainties: MINLP models and algorithms, AIChE J., 57, 5, pp. 1250-1277, (2011); Yuan R., Cezik T., Graves S.C., Velocity-based storage assignment in semi-automated storage systems, MSOM 2016, (2016)","C.L. Lara; Modeling and Optimization, Amazon.com, United States; email: larcrist@amazon.com",null,"Elsevier Ltd",{"$nulls":5},981354.0,null,"CCEND",null,"English","Comput. Chem. Eng.","Article","Final",null,"Scopus","2-s2.0-85171759601"]
["Yao Y.; Zhang H.; Lin L.; Lin G.; Shibasaki R.; Song X.; Yu K.","Yao, Yuhao (57223744471); Zhang, Haoran (57208173635); Lin, Lifeng (57491688700); Lin, Guixu (57223765572); Shibasaki, Ryosuke (7003648498); Song, Xuan (7402269519); Yu, Keping (56316023300)","57223744471; 57208173635; 57491688700; 57223765572; 7003648498; 7402269519; 56316023300","Internet of Things Positioning Technology Based Intelligent Delivery System",2023.0,"IEEE Transactions on Intelligent Transportation Systems",24.0,11.0,null,12862.0,12876.0,14.0,3.0,"10.1109/TITS.2022.3155638","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85126559894&doi=10.1109%2fTITS.2022.3155638&partnerID=40&md5=5e6bf3d1dd079f4e0e677fdb2ba1609c","The University of Tokyo, Center for Spatial Information Science, Tokyo, 113-8654, Japan; LocationMind Inc., Kashiwa, 277-0882, Japan; Southern University of Science and Technology, University of Tokyo Joint Research Center for Super Smart Cities, Department of Computer and Engineering, Southern University of Science and Technology, Shenzhen, 518055, China; Waseda University, Global Information and Telecommunication Institute, Tokyo, 169-8050, Japan","Yao Y., The University of Tokyo, Center for Spatial Information Science, Tokyo, 113-8654, Japan, LocationMind Inc., Kashiwa, 277-0882, Japan; Zhang H., The University of Tokyo, Center for Spatial Information Science, Tokyo, 113-8654, Japan, LocationMind Inc., Kashiwa, 277-0882, Japan; Lin L., The University of Tokyo, Center for Spatial Information Science, Tokyo, 113-8654, Japan; Lin G., The University of Tokyo, Center for Spatial Information Science, Tokyo, 113-8654, Japan; Shibasaki R., The University of Tokyo, Center for Spatial Information Science, Tokyo, 113-8654, Japan, LocationMind Inc., Kashiwa, 277-0882, Japan; Song X., Southern University of Science and Technology, University of Tokyo Joint Research Center for Super Smart Cities, Department of Computer and Engineering, Southern University of Science and Technology, Shenzhen, 518055, China; Yu K., Waseda University, Global Information and Telecommunication Institute, Tokyo, 169-8050, Japan","The fast growing of e-commerce makes the express delivery an important component of transportation system. Absent delivery as one of the main reasons of failed delivery, brings serious waste of resources every year. Although with the development of Internet of Things technology, positioning system of recipients' mobile devices can provide location information to help delivery routing optimization solving absent delivery, the lack of security makes it not practical. This paper proposes an IoT positioning technology based intelligent delivery system by introducing blockchain system and location information encryption, which overcomes three fatal problems of traditional IoT positioning technology based system: different party shares all information, location information interaction is too exposed and the system is unattractive to recipients. A set of analysis with real case experiment about efficiency improvement, incentive effect and security are conducted to validate the robustness of the system. Compared with previous research, the proposed system not only has high accuracy by utilizing real-time location information instead of unreliable prediction results, but also possesses high security.  © 2000-2011 IEEE.","blockchain; Delivery system; Internet of Things; positioning technology","Cryptography; Internet of things; Location; Block-chain; Blockchain.; Delivery systems; Location information; Optimisations; Positioning technologies; Prototype; Road; Routings; Technology-based; Blockchain",{"$nulls":6},"Liu C., Bendtsen C., Johnson M., Orozco O., Peart M., Worldwide Retail Ecommerce Sales: The eMarketer Forecast for 2016, (2016); Gevaers R., De Van V.E., Vanelslander T., Characteristics of innovations in last-mile logistics-using best practices, case studies and making the link with green and sustainable logistics, Assoc. Eur. Transp. Contributors, 1, (2009); Arnold F., Cardenas I., Sorensen K., Dewulf W., Simulation of B2C e-commerce distribution in Antwerp using cargo bikes and delivery points, Eur. Transp. Res. Rev., 10, 1, pp. 1-13, (2018); Social Loss Caused From Parcel Redelivery, (2015); Chen C., Liu L., Qiu T., Yang K., Gong F., Song H., ASGR: An artificial spider-web-based geographic routing in heterogeneous vehicular networks, IEEE Trans. Intell. Transp. Syst., 20, 5, pp. 1604-1620, (2019); Chen C., Liu L., Qiu T., Jiang J., Pei Q., Song H., Routing with traffic awareness and link preference in internet of vehicles, IEEE Trans. Intell. Transp. Syst., 23, 1, pp. 200-214, (2022); Liu Y., Wang J., Li J., Niu S., Song H., Class-incremental learning for wireless device identification in IoT, IEEE Internet Things J., 8, 23, pp. 17227-17235, (2021); Song H., Srinivasan R., Sookoor T., Jeschke S., Smart Cities: Foundations, Principles, and Applications, (2017); Sun Y., Song H., Jara A.J., Bie R., Internet of Things and big data analytics for smart and connected communities, IEEE Access, 4, pp. 766-773, (2016); Ohsugi S., Tanaka K., Koshizuka N., Privacy enhancement for delivery route optimization through occupancy prediction, Proc. 8th Int. Conf. Softw. Comput. Appl., pp. 385-391, (2019); Li W., Et al., Effective metagraph-based life pattern clustering with big human mobility data, (2021); Praet S., Martens D., Efficient parcel delivery by predicting customers' locations, Decis. Sci., 51, 5, pp. 1202-1231, (2020); Toth P., Vigo D., Models, relaxations and exact approaches for the capacitated vehicle routing problem, Discrete Appl. Math., 123, 1-3, pp. 487-512, (2002); Kedia R.K., Naick B.K., Review of vehicle route optimisation, Proc. 2nd IEEE Int. Conf. Intell. Transp. Eng. (ICITE), pp. 57-61, (2017); Oliveira L.K.D., Oliveira R.L.M.D., Sousa L.T.M.D., Caliari I.D.P., Nascimento C.D.O.L., Analysis of accessibility from collection and delivery points: Towards the sustainability of the ecommerce delivery, Urbe. Revista Brasileira de Gestão Urbana, 11, (2019); Lachapelle U., Burke M., Brotherton A., Leung A., Parcel locker systems in a car dominant city: Location, characterisation and potential impacts on city planning and consumer travel access, J. Transp. Geography, 71, pp. 1-14, (2018); Zurel O., Van Hoyweghen L., Braes S., Seghers A., Parcel lockers, an answer to the pressure on the last mile delivery, New Business and Regulatory Strategies in the Postal Sector., pp. 299-312, (2018); Vikingson A., Bengtsson C., Exploring and Evaluating the Parcel Locker: A Swedish Consumer Perspective, (2015); Agatz N., Campbell A.M., Fleischmann M., Savels M., Challenges and opportunities in attended home delivery, The Vehicle Routing Problem: Latest Advances and New Challenges., pp. 379-396, (2008); Hvattum L.M., Lokketangen A., Laporte G., Solving a dynamic and stochastic vehicle routing problem with a sample scenario hedging heuristic, Transp. Sci., 40, 4, pp. 421-438, (2006); Van Duin J.H.R., De Goffau W., Wiegmans B., Tavasszy L.A., Saes M., Improving home delivery efficiency by using principles of address intelligence for B2C deliveries, Transp. Res. Proc., 12, pp. 14-25, (2016); Pan S., Han Y., Qiao B., Grover-Silva E., Giannikas V., Mining customer-related data to enhance home delivery in E-commerce: An experimental study, Proc. 6th Int. Conf. Inf. Syst., Logistics Supply Chain (ILS), pp. 1-8, (2016); Kleiminger W., Beckel C., Staake T., Santini S., Occupancy detection from electricity consumption data, Proc. 5th ACM Workshop Embedded Syst. Energy-Efficient Buildings, pp. 1-8, (2013); Pan S., Giannikas V., Han Y., Grover-Silva E., Qiao B., Using customer-related data to enhance e-grocery home delivery, Ind. Manage. Data Syst., 117, 9, pp. 1917-1933, (2017); Mangiaracina R., Perego A., Seghezzi A., Tumino A., Smart home devices and B2C e-commerce: A way to reduce failed deliveries, Proc. Symp. Logistics, (2019); Ohsugi S., Koshizuka N., Delivery route optimization through occupancy prediction from electricity usage, Proc. IEEE 42nd Annu. Comput. Softw. Appl. Conf. (COMPSAC), pp. 842-849, (2018); Yu K., Et al., A blockchain-based Shamir's threshold cryptography scheme for data protection in industrial Internet of Things settings, IEEE Internet Things J., (2021); Feng C., Liu B., Guo Z., Yu K., Qin Z., Choo K.-K.-R., Blockchain-based cross-domain authentication for intelligent 5Genabled Internet of Drones, IEEE Internet Things J., (2021); Cao B., Wang X., Zhang W., Song H., Lv Z., A many-objective optimization model of industrial Internet of Things based on private blockchain, IEEE Network, 34, 5, pp. 78-83, (2020)","H. Zhang; The University of Tokyo, Center for Spatial Information Science, Tokyo, 113-8654, Japan; email: zhang_ronan@csis.u-tokyo.ac.jp; K. Yu; Waseda University, Global Information and Telecommunication Institute, Tokyo, 169-8050, Japan; email: keping.yu@aoni.waseda.jp",null,"Institute of Electrical and Electronics Engineers Inc.",{"$nulls":5},1.524905E7,null,null,null,"English","IEEE Trans. Intell. Transp. Syst.","Article","Final",null,"Scopus","2-s2.0-85126559894"]
["Jiang W.","Jiang, Wenjuan (58812776700)",5.88127767E10,"Enhancing Operational Efficiency in E-Commerce Through Artificial Intelligence and Information Management Integration",2023.0,"Revue d'Intelligence Artificielle",37.0,6.0,null,1545.0,1555.0,10.0,1.0,"10.18280/RIA.370619","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85182361395&doi=10.18280%2fRIA.370619&partnerID=40&md5=c3813bd29acf7d5e72a27043420b8995","Division of Business Administration, Seoul School of Integrated Sciences and Technologies, Seoul, 03767, South Korea","Jiang W., Division of Business Administration, Seoul School of Integrated Sciences and Technologies, Seoul, 03767, South Korea","In the rapidly evolving domain of global e-commerce, operational organizations are increasingly grappling with unprecedented competitive pressures and challenges in operational efficiency. This study investigates the integration of artificial intelligence (AI) and information management as a transformative approach to augment operational efficiency in e-commerce organizations. The research delves into the optimization of organizational structures, leveraging the predictive capabilities of key information facilitated by AI. A novel decision-making model, integrating AI techniques, is developed to address the limitations inherent in existing decision-making technologies. The model's efficacy is demonstrated through a detailed case study of an e-commerce platform, where objectives and constraints for optimizing e-commerce operational organizations are meticulously constructed. The research identifies critical optimization points, including resource allocation, inventory management, logistics distribution, and customer relationship management. A distinctive organizational operation decision-making model, synergizing with the established Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), is proposed. This model focuses on optimizing variables pivotal to operational efficiency, with the dual goals of elevating efficiency and enhancing customer satisfaction. The findings underscore the significant role of AI technology in amplifying decision quality and boosting operational efficiency in e-commerce operational organizations, while also presenting potential applicability to a broader spectrum of organizational types. Copyright: © 2023 IIETA. This article is published by IIETA and is licensed under the CC BY 4.0 license (http://creativecommons.org/licenses/by/4.0/).","artificial intelligence; decision model; e-commerce operational organization; information management integration; operational efficiency; Technique for Order Preference by Similarity to an Ideal Solution",{"$nulls":7},"Tuktarova L.R., Economic aspects of enterprises' sustainable development, International Conference Engineering Innovations and Sustainable Development, pp. 434-441, (2023); Richnak P., Fidlerova H., Impact and potential of sustainable development goals in dimension of the technological revolution industry 4.0 within the analysis of industrial enterprises, Energies, 15, 10, (2022); Zhao J., Dual innovation: The road to sustainable development of enterprises, International Journal of Innovation Science, 13, 4, pp. 423-436, (2021); Cheng J., Li W., Zhao J., Wang Y., Chang Y., Wu L., Meng W., Research on the evaluation index system of organizational effectiveness based on multiintegrated and highly elastic energy Internet enterprises, 2022 2nd International Conference on Computer Science, Electronic Information Engineering and Intelligent Control Technology (CEI), pp. 468-472, (2022); Kareem H.M., Aziz K.A., Maelah R., Yunus Y.M., Alsheikh A., Alsheikh W., The influence of accounting information systems, knowledge management capabilities, and innovation on organizational performance in Iraqi SMEs, International Journal of Knowledge Management (IJKM), 17, 2, pp. 72-103, (2021); Iswari N.M.S., Budiardjo E.K., Santoso H.B., Hasibuan Z.A., E-business application recommendation for SMEs based on organization profile using random forest classification, 2019 International Seminar on Research of Information Technology and Intelligent Systems (ISRITI), pp. 522-527, (2019); Melnik A., Ermolaev K., Kuzmin M., Requirements for companies' energy saving programs under the conditions of digitalization of Russian economy, IOP Conference Series: Materials Science and Engineering, 497, 1, (2019); Choi M.J., Kim S., Park H., Empirical study on the factors influencing process innovation when adopting intelligent robots at small-and medium-sized enterprises-the role of organizational supports, Information, 9, 12, (2018); Hiran D., Kothari H., Singh S., Impact of Artificial Intelligence on Human Resource Management practices in private organizations of India, International Conference on ICT for Sustainable Development, pp. 149-164, (2023); Li Y.P., Yang S.C., Mao W.B., Gao G.Z., Lu Y.N., Huang Z.H., Active power balance scheduling architecture and strategy of distributed flexible resource based on collective intelligence, Dianli Zidonghua Shebei/Electric Power Automation Equipment, 42, 7, pp. 174-182, (2022); Gong F., Application of artificial intelligence computer intelligent heuristic search algorithm, Advances in Multimedia, 2022, (2022); Grabowski M., Martelli P.F., Roberts K.H., Reliability-Seeking virtual organizations at the margins of systems, resources and capacity, Safety Science, 168, (2023); Bandyopadhyay S., Mukherjee R., Sarkar S., A report on the first workshop on software engineering for artificial intelligence (SE4AI 2020), Proceedings of the 13th Innovations in Software Engineering Conference on Formerly known as India Software Engineering Conference, pp. 1-2, (2020); Uttarwar S., Gambani S., Thakkar T., Mulla N., Artificial intelligence based system for preliminary rounds of recruitment process, Computational Vision and Bio-Inspired Computing: ICCVBIC 2019, pp. 909-920, (2020); Xia W., Research on data resource classification for intelligent highway scenarios, 2023 7th International Conference on Transportation Information and Safety (ICTIS), pp. 1457-1461, (2023); Al Yami M., Ajmal M.M., Balasubramanian S., Does size matter? The effects of public sector organizational size'on knowledge management processes and operational efficiency, VINE Journal of Information and Knowledge Management Systems, 52, 5, pp. 670-700, (2022); Leite L., Kon F., Pinto G., Meirelles P., Platform teams: An organizational structure for continuous delivery, Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops, pp. 505-511, (2020); Wyganowska M., Establishing the optimal number of priority communication levels in an organizational structure based on mining companies, 18th International Multidisciplinary Scientific GeoConferences SGEM 2018, pp. 389-396, (2018); Li Y., Wang X., Gong T., Wang H., Breaking out of the pandemic: How can firms match internal competence with external resources to shape operational resilience?, Journal of Operations Management, 69, 3, pp. 384-403, (2023); Xiao L., Study on the organizational structure of rural land stock cooperative system based on game theory and network data, International Journal of Security and Its Applications, 10, 3, pp. 333-344, (2016); Mayo G., Shoghli O., Morgan T., Investigating efficiency utilizing data envelopment analysis: Case study of shipyards, Journal of Infrastructure Systems, 26, 2, (2020); Wang Y., Liu J., Zuo J., Rameezdeen R., Ways to improve the project management efficiency in a centralized public procurement system: A structural equation modeling approach, Engineering, Construction and Architectural Management, 27, 1, pp. 168-185, (2019)","W. Jiang; Division of Business Administration, Seoul School of Integrated Sciences and Technologies, Seoul, 03767, South Korea; email: elechiang@stud.assist.ac.kr",null,"International Information and Engineering Technology Association",{"$nulls":5},"0992499X",null,null,null,"English","Rev. Intell. Artif.","Article","Final","All Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85182361395"]
["Ju C.; Liu H.; Xu A.; Zhang J.","Ju, Chunhua (25421802900); Liu, Huajin (57686388200); Xu, Aidi (57217089154); Zhang, Jie (58077659000)","25421802900; 57686388200; 57217089154; 58077659000","Green logistics of fossil fuels and E-commerce: Implications for sustainable economic development",2023.0,"Resources Policy",85.0,null,103991.0,null,null,null,3.0,"10.1016/j.resourpol.2023.103991","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85166271888&doi=10.1016%2fj.resourpol.2023.103991&partnerID=40&md5=84898b03c75d42fe2f93e713c7ad3df9","Zhejiang Gongshang University, School of Business Administration, China; Zhejiang Yuexiu University, School of Digital Commerce, China; Zhejiang University of Science and Technology, School of Economics and Management, China","Ju C., Zhejiang Gongshang University, School of Business Administration, China; Liu H., Zhejiang Gongshang University, School of Business Administration, China; Xu A., Zhejiang Yuexiu University, School of Digital Commerce, China; Zhang J., Zhejiang University of Science and Technology, School of Economics and Management, China","This research task to analyze the impacts of e-commerce and green logistics on the sustainable development of 21 emerging and developing countries in Asia from 2000 to 2021. The estimated coefficients from the Fully Modified OLS (FMOLS) analysis confirm that e-commerce, green logistics, green electricity generation, good governance, and ICT diffusion have a favorable effect on advancing the sustainable development goals. Conversely, the consumption of fossil fuels presents a serious obstacle to achieving sustainable development. Furthermore, the inflow of foreign direct investment has shown no significant effect on the sustainable development index. Countries should prepare the platform for the adoption of electronic commerce by spreading ICT and culturalizing the digital economy in society, thereby increasing digital literacy. Simultaneously, governments can attract green foreign direct investment to promote environmentally friendly projects and foster sustainable practices. © 2023 Elsevier Ltd","e-commerce; FMOLS panel technique; Green growth; Green logistics; Sustainable development","Asia; Developing countries; Electronic commerce; Fossil fuels; E- commerces; Electricity-generation; Foreign direct investments; Fully modified OLS panel technique; Good governances; Green electricity; Green growths; Green logistics; ICT diffusions; Sustainable economic development; developing world; economic development; electricity generation; electronic commerce; environmental economics; foreign direct investment; fossil fuel; governance approach; information and communication technology; logistics; sustainable development; Sustainable Development Goal; Sustainable development",{"$nulls":6},"Abu-Shanab E., Harb Y., E-government research insights: text mining analysis, Electronic Commerce Research ad Applications, 38, (2019); Alwan S., Al Abahi A., Al Harazi Y., Al Harazi A., Sustainable and resilient e-commerce under COVID-19 pandemic: a hybrid grey decision-making approach, Environ. Sci. Pollut. Control Ser., 30, (2023); The Environmental Impact of Logistics and How to Reduce it, (2023); Embracing the E-commerce revolution in Asia and the pacific, (2018); Biglari S., Beiglary S., Arthanari T., Achieving sustainable development goals: fact or Fiction?, J. Clean. Prod., 332, (2022); Cheba K., Kiba- Janiak M., Baraniecka A., Kolakowski T., Impact of external factors on e-commerce market in cities and its implications on environment, Sustain. Cities Soc., 72, (2021); Chmielarz W., Zborowski M., Xuetao J., Atasever M., Szpakowska J., Covid-19 pandemic as sustainability determinant of e-commerce in the creation of information society, Procedia Comput. Sci., 207, pp. 4378-4389, (2022); De Souza E., Krber J., Bouzon M., Rodriguez C., Performance evaluation of green logistics: paving the way towards circular economy, Cleaner Logistics and Supply Chain, 3, (2022); Dumitrescu E.I., Hurlin C., Testing for granger noncausality in heterogeneous panels, Econ. 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Manag., 23, 01n02, (2021); Yousafzai S., Pallister J., Foxall G., A proposed model of e-trust for electronic banking, Technovation, 23, 11, pp. 847-860, (2023); Zhang J., Wang S., Pradhan P., Zhao W., Fu B., Untangling the interactions among the sustainable development goals in China, Sci. Bull., 67, 9, pp. 977-984, (2022); Zhao L., Rasoulinezhad E., Role of natural resources utilization efficiency in achieving green economic recovery: evidence from BRICS countries, Resour. Pol., 80, (2023); Zhao Y., Wu G., Gong Y., Yang M., Ni H., Environmental benefits of electronic commerce over the conventional retail trade? A case study in Shenzhen, China, Sci. Total Environ., 679, pp. 378-386, (2019)","J. Zhang; Zhejiang University of Science and Technology, School of Economics and Management, China; email: 17855835837@163.com",null,"Elsevier Ltd",{"$nulls":5},3014207.0,null,null,null,"English","Resour. Policy","Article","Final",null,"Scopus","2-s2.0-85166271888"]
["Peng X.; Zhang L.; Thompson R.G.; Wang K.","Peng, Xiaoshuai (57201497707); Zhang, Lele (37562307200); Thompson, Russell G. (56754264400); Wang, Kangzhou (55501582900)","57201497707; 37562307200; 56754264400; 55501582900","A three-phase heuristic for last-mile delivery with spatial-temporal consolidation and delivery options",2023.0,"International Journal of Production Economics",266.0,null,109044.0,null,null,null,0.0,"10.1016/j.ijpe.2023.109044","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85172983946&doi=10.1016%2fj.ijpe.2023.109044&partnerID=40&md5=154259247db705a42305104dd2a6b343","School of Management, Lanzhou University, Lanzhou, 730000, China; School of Mathematics and Statistics, The University of Melbourne, Parkville, Victoria, 3010, Australia; Department of Infrastructure Engineering, The University of Melbourne, Parkville, Victoria, 3010, Australia","Peng X., School of Management, Lanzhou University, Lanzhou, 730000, China; Zhang L., School of Mathematics and Statistics, The University of Melbourne, Parkville, Victoria, 3010, Australia; Thompson R.G., Department of Infrastructure Engineering, The University of Melbourne, Parkville, Victoria, 3010, Australia; Wang K., School of Management, Lanzhou University, Lanzhou, 730000, China","The parcel demand in last-mile delivery increases sharply with the growth of e-commerce, which has been accelerated by the COVID-19 pandemic. The current delivery scheme follows a first-in-first-out (FIFO) rule, i.e., parcels arriving at different periods for the same customer are likely to become separate deliveries, which incurs a high transportation cost. To address this, an innovative spatial-temporal based consolidation (STC) strategy is proposed to consolidate parcels based on their delivery due dates and spatial distributions to reduce redundant delivery trips and lower the total cost. In addition to reducing the operational cost, improving customer satisfaction by offering diversified delivery preferences is key for enterprises to maintain competitiveness. This paper investigates a new variant of last-mile delivery that integrates parcel consolidation and flexible delivery options, including serving through home delivery and parcel lockers. A bi-objective model is formulated to balance the total cost and the service satisfaction. Then a three-phase heuristic is developed to solve the model. In the three-phase heuristic, the first phase determines the parcel distribution schedule, delivery option and node visiting schedule, while the second one optimizes vehicle routing by solving a series of traveling salesman problems. The third phase improves the solution by applying a general improvement routing procedure. The performance of the three-phase heuristic is demonstrated through extensive computational experiments based on a realistic parcel distribution network in the city of Melbourne, Australia. Experimental results reveal that the STC strategy has significant advantages over the FIFO scheme. Moreover, the advantage increases with the unit transportation cost, vehicle capacity and consumer distribution dispersion. © 2023 Elsevier B.V.","Delivery option; Last-mile delivery; Shipment consolidation; Three-phase heuristic","Competition; Cost reduction; Customer satisfaction; Traveling salesman problem; Delivery option; E- commerces; Last mile; Last-mile delivery; Shipment consolidation; Spatial temporals; Three phase; Three phasis; Three-phase heuristic; Transportation cost; Vehicle routing",{"$nulls":4},"Humanity and Social Science Youth Foundation; Melbourne Research Cloud; Soft Science Special Project of Gansu Basic Research Plan, (23JRZA376); Youth Doctor Fund Project for Universities of Gansu Province, (2021A-006); National Natural Science Foundation of China, NSFC, (72171105, 72201116); Ministry of Education of the People's Republic of China, MOE, (21YJC630133); Fundamental Research Funds for the Central Universities, (21lzujbkyjh008, 22lzujbkydx020)","This work was supported by the National Natural Science Foundation of China [Grant Numbers: 72201116 , 72171105 ]; Humanity and Social Science Youth Foundation of the Ministry of Education of China, China [Grant Number: 21YJC630133 ]; Soft Science Special Project of Gansu Basic Research Plan (Grant Number: 23JRZA376 ); Fundamental Research Funds for the Central Universities [Grant Numbers: 22lzujbkydx020 , 21lzujbkyjh008 ]; Youth Doctor Fund Project for Universities of Gansu Province [Grant Number: 2021A-006 ]. We acknowledge the support of the Melbourne Research Cloud (MRC). ","Absi N., Archetti C., Dauzere-Peres S., Feillet D., A two-phase iterative heuristic approach for the production routing problem, Transport. Sci., 49, 4, pp. 784-795, (2014); Adobe, Adobe Digital Economy Index, (2020); Anderluh A., Nolz P.C., Hemmelmayr V.C., Crainic T.G., Multi-objective optimization of a two-echelon vehicle routing problem with vehicle synchronization and ‘grey zone’ customers arising in urban logistics, Eur. J. Oper. Res., 289, 3, pp. 940-958, (2021); Archetti C., Jabali O., Speranza M.G., Multi-period vehicle routing problem with due dates, Comput. Oper. Res., 61, pp. 122-134, (2015); Bababeik M., Khademi N., Chen A., Increasing the resilience level of a vulnerable rail network: the strategy of location and allocation of emergency relief trains, Transport. Res. E Logist. Transport. 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Rev., 141, (2020); Zhang Y., Sun L., Hu X., Zhao C., Order consolidation for the last-mile split delivery in online retailing, Transport. Res. E Logist. Transport. Rev., 122, pp. 309-327, (2019); Zhou H., Qin H., Cheng C., Rousseau L.-M., An exact algorithm for the two-echelon vehicle routing problem with drones, Transp. Res. Part B Methodol., 168, pp. 124-150, (2023); Zhou L., Baldacci R., Vigo D., Wang X., A multi-depot two-echelon vehicle routing problem with delivery options arising in the last mile distribution, Eur. J. Oper. Res., 265, 2, pp. 765-778, (2018)","K. Wang; School of Management, Lanzhou University, Lanzhou, 222 South Tianshui Road, Gansu, China; email: kzhwang@lzu.edu.cn",null,"Elsevier B.V.",{"$nulls":5},9255273.0,null,"IJPCE",null,"English","Int J Prod Econ","Article","Final",null,"Scopus","2-s2.0-85172983946"]
["Wang X.; Wong Y.D.; Yuen K.F.","Wang, Xueqin (57196484178); Wong, Yiik Diew (57218910096); Yuen, Kum Fai (56581269200)","57196484178; 57218910096; 56581269200","Going solo and feeling smart? An exploratory study on shoppers' time valuation and cultural perception",2023.0,"Internet Research",33.0,4.0,null,1276.0,1301.0,25.0,0.0,"10.1108/INTR-10-2021-0748","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85146999135&doi=10.1108%2fINTR-10-2021-0748&partnerID=40&md5=cde347e6592c1ad8d04df9fbd24a1348","Department of International Logistics, Chung-Ang University, Seoul, South Korea; School of Civil and Environmental Engineering, Nanyang Technological University, Singapore, Singapore","Wang X., Department of International Logistics, Chung-Ang University, Seoul, South Korea; Wong Y.D., School of Civil and Environmental Engineering, Nanyang Technological University, Singapore, Singapore; Yuen K.F., School of Civil and Environmental Engineering, Nanyang Technological University, Singapore, Singapore","Purpose: The advent of digitalization and the trend of social distancing coincide with the individualized lifestyle that is emerging among contemporary shoppers. This study explores the unique market of “smart solo shoppers”. Two empirical studies are conducted, which aim to identify the major dimensions of multi-channel shopping activities that are engaged by the shoppers (Study 1, n = 64) and to differentiate the shoppers' valuation of time invested in the distinct dimensions under different cultural influences (Study 2, n = 519). Design/methodology/approach: A survey questionnaire is used for data collection, and data are analyzed using structural equation modeling. Findings: Results reveal that the shopping activities converge into four principal dimensions: offline shopping, online shopping, post-shopping delivery and product return activities. Shoppers who perceive offline shopping activities as a time burden and online shopping and delivery activities as venues of value creation are more strongly self-identified as smart solo shoppers. Furthermore, smart solo shoppers who are under a strong influence of individualistic culture are found to spend time on multi-channel shopping to make the right purchase the first time, whereas shoppers perceiving being in a weak individualistic culture prefer to engage online channels while being prepared to return the unwanted purchases. Originality/value: This study highlights an emerging research field in the nexus of solo consumption and smart shopping. Emphasizing the utility-driven and ego-expressive nature of smart solo shoppers, the authors provide an initial profile of these shoppers based on their time-valuation patterns and the contextual impacts of individualistic culture. © 2023, Emerald Publishing Limited.","Digital shopping; Multi-channel shopping; Smart-shopper feeling; Solo shopping; Time valuation; Value co-creation",{"$nulls":7},"Alzayat A., Lee S.H., Virtual products as an extension of my body: exploring hedonic and utilitarian shopping value in a virtual reality retail environment, Journal of Business Research, 130, 1, pp. 348-363, (2021); Ameen N., Tarhini A., Reppel A., Anand A., Customer experiences in the age of artificial intelligence, Computers in Human Behavior, 114, 1, (2021); Atkins K.G., Runyan R.C., Kim Y.K., Smart shopping: conceptualization and measurement, International Journal of Retail and Distribution Management, 40, 5, pp. 360-375, (2012); Atkins K.G., Kumar A., Kim Y.-K., Smart grocery shopper segments, Journal of International Consumer Marketing, 28, 1, pp. 42-53, (2016); Bahn K.D., Granzin K.L., Tokman M., End-user contribution to logistics value co-creation: a series of exploratory studies, Journal of Marketing Channels, 22, 1, pp. 3-26, (2015); Bianchi C., Solo holiday travellers: motivators and drivers of satisfaction and dissatisfaction, International Journal of Tourism Research, 18, 2, pp. 197-208, (2016); Blut M., Chowdhry N., Mittal V., Brock C., E-Service quality: a meta-analytic review, Journal of Retailing, 91, 4, pp. 679-700, (2015); Brailovskaia J., Margraf J., The relationship between burden caused by coronavirus (Covid-19), addictive social media use, sense of control and anxiety, Computers in Human Behavior, 119, (2021); Brown L., Buhalis D., Beer S., Dining alone: improving the experience of solo restaurant goers, International Journal of Contemporary Hospitality Management, 32, 3, pp. 1347-1365, (2020); Chang Y.Y.-C., Lonely or alone? 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Yuen; School of Civil and Environmental Engineering, Nanyang Technological University, Singapore, Singapore; email: kumfai.yuen@ntu.edu.sg",null,"Emerald Publishing",{"$nulls":5},1.0662243E7,null,null,null,"English","Internet Res.","Article","Final",null,"Scopus","2-s2.0-85146999135"]
["Zhu X.; Cai L.; Lai P.-L.; Wang X.; Ma F.","Zhu, Xiaonan (57273283700); Cai, Lanhui (57219317060); Lai, Po-Lin (55340966100); Wang, Xueqin (57196484178); Ma, Fei (57198553001)","57273283700; 57219317060; 55340966100; 57196484178; 57198553001","Evolution, Challenges, and Opportunities of Transportation Methods in the Last-Mile Delivery Process",2023.0,"Systems",11.0,10.0,509.0,null,null,null,0.0,"10.3390/systems11100509","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85175046099&doi=10.3390%2fsystems11100509&partnerID=40&md5=cdf27a96a0b6c57b4bc7a96b9431b39f","Department of International Trade and Logistics, Graduate School, Chung-Ang University, Seoul, 06974, South Korea; Department of International Logistics, College of Business and Economic, Chung-Ang University, Seoul, 06974, South Korea; School of Economics and Management, Chang’an University, Xi’an, 710064, China","Zhu X., Department of International Trade and Logistics, Graduate School, Chung-Ang University, Seoul, 06974, South Korea; Cai L., Department of International Trade and Logistics, Graduate School, Chung-Ang University, Seoul, 06974, South Korea; Lai P.-L., Department of International Logistics, College of Business and Economic, Chung-Ang University, Seoul, 06974, South Korea; Wang X., Department of International Logistics, College of Business and Economic, Chung-Ang University, Seoul, 06974, South Korea; Ma F., School of Economics and Management, Chang’an University, Xi’an, 710064, China","The rapid development of modern logistics and e-commerce highlights the importance of exploring various modes of transportation in the last-mile delivery (LMD) process. However, no comprehensive studies exist in the literature exploring all modes of LMD transportation, the changes in these transportation modes, and the commonalities between them. In this study, we address this gap by conducting a systematic review of 150 academic journal articles utilizing a combination of the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) content analysis and text mining analysis. Nine primary transportation methods (parcel lockers, autonomous drones, trucks, bicycles, crowd logistics, electric vehicles, tricycles, autonomous robots, and autonomous vehicles) are identified in this research. Additionally, we provide an analysis of the historical changes in these transportation modes in LMD. Using a bottom-up induction method, we identify the three major clusters of scholarly focus in the LMD literature: emphasis on value co-creation between consumers and logistics providers, practical delivery performance (path optimization or algorithms), and environmental friendliness. Further, we analyze the main themes under each cluster, leading to the identification of opportunities, challenges, and future research agendas. Our findings have implications for scholars, policymakers, and other stakeholders involved in LMD transportation modes. © 2023 by the authors.","challenges and opportunities; last-mile delivery; mode of transport; PRISMA; text mining analysis",{"$nulls":5},"Ministry of Oceans and Fisheries, MOF","This research was supported by the 4th Educational Training Program for the Shipping, Port and Logistics from the Ministry of Oceans and Fisheries.",{"$cut":{"chars":25598,"head":"Thao T.T., Binh D.T.T., Impacts of Last Mile Delivery on Environment in Urban Areas: Hanoi Case Study, Proceedings of the CIGOS 2021, Emerging Technologies and Applications for Green Infrastructure: Proceedings of the 6th International Conference on Geotechnics, Civil Engineering and Structures, pp. 1653-1661; Fessler A., Cash P., Thorhauge M., Haustein S., A public transport based crowdshipping concept: Results of a field test in Denmark, Transp. Policy, 134, pp. 106-118, (2023); Hubner A.H., Kuhn H., Wollenburg J., Last mile fulfilment and distribution in omni-channel grocery retailing: A strategic planning framework, Int. J. Retail Distrib. Manag, 44, (2016); Joerss M., Schroder J., Neuhaus F., Klink C., Mann F., Parcel Delivery: The Future of the Last Mile, (2016); Pourrahmani E., Jaller M., Crowdshipping in last mile deliveries: Operational challenges and research opportunities, Socio-Econ. Plan. Sci, 78, (2021); Aurambout J.-P., Gkoumas K., Ciuffo B., Last mile delivery by drones: An estimation of viable market potential and access to citizens across European cities, Eur. Transp. Res. Rev, 11, (2019); Figliozzi M.A., Carbon emissions reductions in last mile and grocery deliveries utilizing air and ground autonomous vehicles, Transp. Res. Part D Transp. Environ, 85, (2020); Jiang Y., Lai P.-L., Yang C.-C., Wang X., Exploring the factors that drive consumers to use contactless delivery services in the context of the continued COVID-19 pandemic, J. Retail. Consum. Serv, 72, (2023); Merkert R., Bliemer M.C., Fayyaz M., Consumer preferences for innovative and traditional last-mile parcel delivery, Int. J. Phys. Distrib. Logist. Manag, 52, pp. 261-284, (2022); Olsson J., Hellstrom D., Vakulenko Y., Customer experience dimensions in last-mile delivery: An empirical study on unattended home delivery, Int. J. Phys. Distrib. Logist. Manag, 53, pp. 184-205, (2023); Vakulenko Y., Shams P., Hellstrom D., Hjort K., Online retail experience and customer satisfaction: The mediating role of last mile delivery, Int. Rev. Retail Distrib. Consum. Res, 29, pp. 306-320, (2019); Glaser S., Jahnke H., Strassheim N., Opportunities and challenges of crowd logistics on the last mile for courier, express and parcel service providers–a literature review, Int. J. Logist. Res. Appl, 26, pp. 1006-1034, (2023); Li X., Zhou Y., Yuen K.F., A systematic review on seafarer health: Conditions, antecedents and interventions, Transp. Policy, 122, pp. 11-25, (2022); Page M.J., McKenzie J.E., Bossuyt P.M., Boutron I., Hoffmann T.C., Mulrow C.D., Shamseer L., Tetzlaff J.M., Akl E.A., Brennan S.E., The PRISMA 2020 statement: An updated guideline for reporting systematic reviews, Int. J. Surg, 88, (2021); Galvagno M., Dalli D., Theory of value co-creation: A systematic literature review, Manag. Serv. Qual, 24, pp. 643-683, (2014); Van Eck N., Waltman L., Software survey: VOSviewer, a computer program for bibliometric mapping, Scientometrics, 84, pp. 523-538, (2010); Perianes-Rodriguez A., Waltman L., Van Eck N.J., Constructing bibliometric networks: A comparison between full and fractional counting, J. Informetr, 10, pp. 1178-1195, (2016); He Y., Pricing of the Bus-Truck Co-Delivery Mode of Last Mile Delivery Considering Social Welfare Maximization, Sustainability, 15, (2023); Chen C., Pan S., Using the crowd of taxis to last mile delivery in e-commerce: A methodological research, Proceedings of the Studies in Computational Intelligence, pp. 61-70; Chen C., Pan S., Wang Z., Zhong R.Y., Using taxis to collect citywide E-commerce reverse flows: A crowdsourcing solution, Int. J. Prod. Res, 55, pp. 1833-1844, (2017); Kervola H., Kallionpaa E., Liimatainen H., Delivering Goods Using a Baby Pram: The Sustainability of Last-Mile Logistics Business Models, Sustainability, 14, (2022); Cai L., Yuen K.F., Fang M., Wang X., A literature review on the impact of the COVID-19 pandemic on consumer behaviour: Implications for consumer-centric logistics, Asia Pac. J. Mark. Logist, (2023); Prahalad C.K., Ramaswamy V., Co-creation experiences: The next practice in value creation"}},"P.-L. Lai; Department of International Logistics, College of Business and Economic, Chung-Ang University, Seoul, 06974, South Korea; email: polin@cau.ac.kr",null,"Multidisciplinary Digital Publishing Institute (MDPI)",{"$nulls":5},2.0798954E7,null,null,null,"English","Systems","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85175046099"]
["Bahaghighat M.; Ghasemi M.; Ozen F.","Bahaghighat, Mahdi (36518105300); Ghasemi, Majid (58549806800); Ozen, Figen (6507062410)","36518105300; 58549806800; 6507062410","A high-accuracy phishing website detection method based on machine learning",2023.0,"Journal of Information Security and Applications",77.0,null,103553.0,null,null,null,1.0,"10.1016/j.jisa.2023.103553","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85168805753&doi=10.1016%2fj.jisa.2023.103553&partnerID=40&md5=58c2b58c46683689f0475cccd43006a3","Islamic Republic of Iran, Qazvin, Iran; Imam Khomeini International University, Iran; Halic University, Turkey","Bahaghighat M., Islamic Republic of Iran, Qazvin, Iran; Ghasemi M., Imam Khomeini International University, Iran; Ozen F., Halic University, Turkey","The rapid development of e-commerce, e-banking, and social networks has made phishing attack detection one of the most critical technologies in all cyber security systems. To improve the efficiency of anti-phishing techniques, we present an improved predictive model based on machine learning. The proposed method uses six different algorithms; Logistic Regression, K-Nearest Neighbors, Naive Bayes, Random Forest, Support Vector Machine, and Extreme Gradient Boosting (XGBoost). The experiments are based on a public dataset of 58,000 legitimate websites and 30,647 phishing ones, including 112 attributes for each sample. Our evaluations in the feature selection process show that after balancing the dataset and dropping constant features, a noticeable improvement can be achieved. We conducted our evaluation found on eight major unique scenarios. The experimental results of our phishing websites detection (PWD) method indicate remarkable performances in which each algorithm reached an accuracy of more than 93%, and the XGBoost classifier outperforms others with 99.2% overall accuracy, 99.1% precision, 99.4% recall, and 99.1% specificity. In addition, the study achieved optimal run-time of about 1500 ms for the XGBoost algorithm without dimension reduction while using Principal Component Analysis (PCA) reduces it down to just 869 ms. As a result, the proposed approach would be practical in both offline and real-time applications. © 2023","Classification; Cyber security; Machine learning; Phishing website detection; XGBoost","Adaptive boosting; Balancing; Computer crime; Cybersecurity; Electronic commerce; Principal component analysis; Support vector machines; Websites; Cyber security; Detection methods; E- commerces; E-banking; High-accuracy; Machine-learning; On-machines; Phishing website detection; Phishing websites; Xgboost; Nearest neighbor search",{"$nulls":6},"Badotra S., Sundas A., A systematic review on the security of E-commerce systems, Int J Appl Sci Eng, 18, 2, pp. 1-9, (2021); Ansari M.F., Sharma P.K., Dash B., Prevention of phishing attacks using AI-based cybersecurity awareness training, Prevention, (2022); Li J., Sun L., Yan Q., Li Z., Srisa-An W., Ye H., Significant permission identification for machine-learning-based android malware detection, IEEE Trans Ind Inf, 14, 7, pp. 3216-3225, (2018); Bhuiyan M.Z., Wu J., Wang G., Cao J., Sensing and decision making in cyber-physical systems: the case of structural event monitoring, IEEE Trans Ind Inf, 12, 6, pp. 2103-2114, (2016); 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Bahaghighat; Islamic Republic of Iran, Qazvin, Iran; email: M.Bahaghighat@aut.ac.ir",null,"Elsevier Ltd",{"$nulls":5},2.2142134E7,null,null,null,"English","J. Inf. Secur. Appl.","Article","Final",null,"Scopus","2-s2.0-85168805753"]
["Tiwari K.V.; Sharma S.K.","Tiwari, Krishna Veer (57614824400); Sharma, Satyendra Kumar (57876067200)","57614824400; 57876067200","An optimization model for vehicle routing problem in last-mile delivery",2023.0,"Expert Systems with Applications",222.0,null,119789.0,null,null,null,2.0,"10.1016/j.eswa.2023.119789","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85150030849&doi=10.1016%2fj.eswa.2023.119789&partnerID=40&md5=124ca6513ca5373acf9820af0a38daf9","Birla Institute of Technology & Science, Rajasthan, Pilani, India","Tiwari K.V., Birla Institute of Technology & Science, Rajasthan, Pilani, India; Sharma S.K., Birla Institute of Technology & Science, Rajasthan, Pilani, India","Due to rapid urbanization, timely delivery using vehicle routing is the most pressing issue for E-commerce logistics and distribution. In this study, we articulate multiple vehicle routing problems with a maximum capacity constraint and no time constraint. A brief literature review is conducted to identify the widely used optimization models for perishable goods delivery in the last mile. We have implemented and compared optimization algorithms such as Intra-Route Local Search, Inter-Route Local Search, and Tabu Search that provide a suboptimal solution to the greedy solution of this NP-hard problem. We compared the solution provided by these algorithms with the optimal solution that can be obtained in exponential time using processing time and precision. The results demonstrate that Tabu search outperforms other techniques for larger instance sizes, but for smaller instance sizes, Local search can produce results that are comparable to TABU search in a significantly shorter amount of time. In addition, the impact of instance size on the performance of the aforementioned algorithms is evaluated. The real-life evaluation is done to understand the use cases of this problem for an e-commerce company that will repeatedly face this challenge during warehouse storage management, last-mile delivery planning, and execution. A comprehensive performance comparison of various algorithms is presented to optimize last-mile delivery for future cases in order to reduce the overall carbon footprint and achieve profitability through the use of sustainable modes of distribution. © 2023 Elsevier Ltd","E-commerce; Last-mile delivery; Local search; Vehicle routing problem (VRP); Warehouse management","Carbon footprint; Computational complexity; Electronic commerce; Storage management; Vehicle routing; Vehicles; Warehouses; Capacity constraints; Last mile; Last-mile delivery; Local search; Optimization models; Pressung; Rapid urbanizations; Vehicle routing problem; Vehicle Routing Problems; Warehouse management; Tabu search",{"$nulls":6},"Afifi S., Dang D.C., Moukrim A., A simulated annealing algorithm for the vehicle routing problem with time windows and synchronization constraints, Lecture Notes in Computer Science, 259-265, (2013); Ahmadianfar I., Heidari A.A., Gandomi A.H., Chu X., Chen H., RUN beyond the metaphor: An efficient optimization algorithm based on Runge Kutta method, Expert Systems with Applications, 181, (2021); 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Tiwari; Department of Management, New Academic Block, BITS Pilani, Vidya Vihar Road, Pilani, Jhunjhunu, Rajasthan, Zip-code: 333031, India; email: p20200038@pilani.bits-pilani.ac.in",null,"Elsevier Ltd",{"$nulls":5},9574174.0,null,"ESAPE",null,"English","Expert Sys Appl","Article","Final",null,"Scopus","2-s2.0-85150030849"]
["Samanta T.; Aithal R.","Samanta, Tamal (57223183337); Aithal, Rajesh (55069419500)","57223183337; 55069419500","Resilience of small retailers in facing the Covid-19 pandemic – a qualitative study",2023.0,"Qualitative Market Research",26.0,5.0,null,555.0,578.0,23.0,2.0,"10.1108/QMR-03-2022-0050","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174918351&doi=10.1108%2fQMR-03-2022-0050&partnerID=40&md5=4dcbde12d7df63b87e37f8ef48952cd2","Department of Marketing, Indian Institute of Management Lucknow, Lucknow, India","Samanta T., Department of Marketing, Indian Institute of Management Lucknow, Lucknow, India; Aithal R., Department of Marketing, Indian Institute of Management Lucknow, Lucknow, India","Purpose: This study aims to understand the impact of the Covid-19 pandemic on small retailers, and their response to it, using the crisis management model. The research documents the impact and responses and attempts to identify the factors contributing to and hindering retailers’ attempts to achieve resilience. Design/methodology/approach: Semi-structured interviews were used to collect qualitative data from small retailers. The interview transcripts were analysed using MAXQDA 2020 Analytics Pro data analysis software. The heterogeneity in responses to the challenges posed by the pandemic is explained using self-determination theory and diffusion of innovation theory. Findings: One of the most significant impacts of the crisis was the disruption in the regular supply chain network on which the studied retailers relied for their traditional buying. The retailers increased customer services such as free home delivery and enhanced the use of technology in their shops. However, and worryingly, although the retailers faced two waves of the pandemic, the urge to plan and prepare was missing. The overall crisis can, therefore, be seen as an opportunity for small retailers to improve their responses when facing similar situations. Social implications: Small retailers are part of the social fabric in many emerging economies and function as a source of employment. They have been facing challenges from organised retail and e-commerce. The Covid-19 crisis pushed them to respond, and the authors hope that they will take some cues from this disruption and become more efficient and competitive in the future. Originality/value: To the best of the authors’ knowledge, this is among the first studies to map the impact of the crisis on small retailers and their response to it, drawing implications for retailers and companies and analysing the efforts made by small retailers to achieve resilience. © 2023, Emerald Publishing Limited.","Crisis management; Emerging economies; Innovation; Resilience; Small retail",{"$nulls":7},"Adhikary A., Diatha K.S., Borah S.B., Sharma A., How does the adoption of digital payment technologies influence Unorganized retailers' performance? 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An innovation diffusion theory account of small retail businesses’ social media use, Journal of Retailing and Consumer Services, 62, (2021); Lenartowicz T., Balasubramanian S., Practices and performance of small retail stores in developing economies, Journal of International Marketing, 17, 1, pp. 58-90, (2009); Leung L.S.K., Matanda M.J., The impact of basic human needs on the use of retailing self-service technologies: a study of self-determination theory, Journal of Retailing and Consumer Services, 20, 6, pp. 549-559, (2013); Li L.H., Cheung K.S., Tse W.S., Understanding the shoppers’ perception in retail shopping malls: a self-determination theory perspective, Journal of Strategic Marketing, 31, 1, pp. 1-16, (2021); McClatchey J., Cattell K., Michell K., The impact of online retail grocery shopping on retail space: a cape town case study, Facilities, 25, 3-4, pp. 115-126, (2007); Mahajan S., Van Ryzin G., Stocking retail assortments under dynamic consumer substitution, Operations Research, 49, 3, pp. 334-351, (2001); Manjeshwar S., Sternquist B., Good L.K., Decision making of retail buyers: perspectives from China and India, Qualitative Market Research: An International Journal, 16, 1, pp. 38-52, (2013); Miles M.B., Huberman A.M., Qualitative Data Analysis: An Expanded Sourcebook, (1994); Mitroff I.I., Pearson C.M., Harrington L.K., The Essential Guide to Managing Corporate Crisis: A Step-by-Step Handbook for Surviving Major Catastrophes, (1996); Naeem M., Do social media platforms develop consumer panic buying during the fear of Covid-19 pandemic, Journal of Retailing and Consumer Services, 58, pp. 1-12, (2021); Naeem M., The role of social media to generate social proof as engaged society for stockpiling behaviour of customers during Covid-19 pandemic, Qualitative Market Research: An International Journal, 24, 3, pp. 281-301, (2021); Onyemah V., Akpa S.O., Open air markets: uniquenesses about African marketing channels, International Marketing Review, 33, 1, pp. 112-136, (2016); Pantano E., Vannucci V., Who is innovating? 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Samanta; Department of Marketing, Indian Institute of Management Lucknow, Lucknow, India; email: fpm20005@iiml.ac.in",null,"Emerald Publishing",{"$nulls":5},1.3522752E7,null,null,null,"English","Qual. Mark. Res.","Article","Final",null,"Scopus","2-s2.0-85174918351"]
["Tavakoli M.; Tajally A.; Ghanavati-Nejad M.; Jolai F.","Tavakoli, Mahdieh (57222296761); Tajally, Amirreza (57226397290); Ghanavati-Nejad, Mohssen (57455197300); Jolai, Fariborz (56218703500)","57222296761; 57226397290; 57455197300; 56218703500","A Markovian-based fuzzy decision-making approach for the customer-based sustainable-resilient supplier selection problem",2023.0,"Soft Computing",27.0,20.0,null,15153.0,15184.0,31.0,1.0,"10.1007/s00500-023-08380-w","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85159683040&doi=10.1007%2fs00500-023-08380-w&partnerID=40&md5=e671883c3eb51327fe0702869fe85205","School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran","Tavakoli M., School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran; Tajally A., School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran; Ghanavati-Nejad M., School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran; Jolai F., School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran","The supplier selection problem is one of the most important issues in supply chain management. So, many papers have investigated the mentioned problem. However, the related literature shows that researchers had less attention to the sustainability and resilience aspects based on the customer preferences in supplier selection problem. To cover this gap, this research tries to investigate the customer-based sustainable-resilient supplier selection problem. In this way, a Markovian-based fuzzy decision-making method is proposed. At the outset, the customer preferences are evaluated using a combination of the quality function deployment and the Markov transition matrix. Then, by combining the transition matrix and the fuzzy best–worst method, the weights of the indicators are calculated. Finally, the decision matrix is formed and the performance of suppliers is measured based on the multiplication of the decision matrix and vector of sub-criteria weights. Regarding the recent pandemic disruption (COVID-19), the importance of online marketplaces is highlighted more than the past. Hence, this study considers an online marketplace as a case study. Results show that in a pandemic situation, the preferences of customers when they cannot go shopping normally will change after a while. Based on the Markov steady state, these changes are from the priority of price, availability, and performance in initial time to serviceability, reliability, and availability in the future. Finally, based on the FBWM results, from the customer point of view, the top five sub-criteria for sustainable-resilient supplier selection include cost, quality, delivery, responsiveness, and service. So, based on these priorities, the case study potential suppliers are prioritized, respectively. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.","Customer preferences; FBWM; Markovian-based decision-making; Resilience; Supplier selection; Sustainability","COVID-19; Electronic commerce; Markov processes; Sales; Supply chain management; Sustainable development; Customer preferences; Decision matrix; Decisions makings; FBWM; Fuzzy Decision making; Markovian; Markovian-based decision-making; Resilience; Selection problems; Supplier selection; Decision making",{"$nulls":6},{"$cut":{"chars":16501,"head":"Abdel-Basset M., Manogaran G., Mohamed M., Chilamkurti N., Three-way decisions based on neutrosophic sets and AHP-QFD framework for supplier selection problem, Futur Gener Comput Syst, 89, pp. 19-30, (2018); Afrasiabi A., Tavana M., Di Caprio D., An extended hybrid fuzzy multi-criteria decision model for sustainable and resilient supplier selection, Environ Sci Poll Res, 29, 25, pp. 37291-37314, (2022); Alikhani R., Torabi S.A., Altay N., Strategic supplier selection under sustainability and risk criteria, Int J Prod Econ, 208, pp. 69-82, (2019); Amindoust A., A resilient-sustainable based supplier selection model using a hybrid intelligent method, Comput Ind Eng, 126, pp. 122-135, (2018); Aria S., Torabi S.A., Nayeri S., A hybrid fuzzy decision-making approach to select the best online-taxis business, Adv Ind Eng, 54, pp. 99-120, (2020); Asadabadi M.R., A customer based supplier selection process that combines quality function deployment, the analytic network process and a Markov chain, Eur J Oper Res, 263, pp. 1049-1062, (2017); Azadnia A.H., Saman M.Z.M., Wong K.Y., Sustainable supplier selection and order lot-sizing: an integrated multi-objective decision-making process, Int J Prod Res, 53, pp. 383-408, (2015); Bhattacharya K., De S.K., A robust two layer green supply chain modelling under performance based fuzzy game theoretic approach, Comput Ind Eng, 152, (2021); Buyukozkan G., Cifci G., A novel fuzzy multi-criteria decision framework for sustainable supplier selection with incomplete information, Comput Ind, 62, pp. 164-174, (2011); Chai N., Zhou W., Jiang Z., Sustainable supplier selection using an intuitionistic and interval-valued fuzzy MCDM approach based on cumulative prospect theory, Inf Sci, 626, pp. 710-737, (2023); Chang K.-H., A novel enhanced supplier selection method used for handling hesitant fuzzy linguistic information, Math Probl Eng, (2022); Chen S.H., Wang P.W., Chen C.M., Lee H.T., An analytic hierarchy process approach with linguistic variables for selection of an R&D strategic alliance partner, Comput Ind Eng, 58, pp. 278-287, (2010); Chen Z., Ming X., Zhou T., Chang Y., Sustainable supplier selection for smart supply chain considering internal and external uncertainty: an integrated rough-fuzzy approach, Appl Soft Comput, 87, (2020); Cheraghalipour A., Farsad S., A bi-objective sustainable supplier selection and order allocation considering quantity discounts under disruption risks: a case study in plastic industry, Comput Ind Eng, 118, pp. 237-250, (2018); Chia-Nan W., Chao-Fen P., Nguyen V.T., Syed Tam H., Sustainable supplier selection model in supply chains during the COVID-19 pandemic, Comput Mater Contin, 70, 2, pp. 3005-3019, (2022); Coskun S.S., Kumru M., Kan N.M., An integrated framework for sustainable supplier development through supplier evaluation based on sustainability indicators, J Clean Prod, (2022); Davoudabadi R., Mousavi S.M., Mohagheghi V., Vahdani B., Resilient supplier selection through introducing a new interval-valued intuitionistic fuzzy evaluation and decision-making framework, Arab J Sci Eng, 44, pp. 7351-7360, (2019); Davoudabadi R., Mousavi S.M., Sharifi E., An integrated weighting and ranking model based on entropy, DEA and PCA considering two aggregation approaches for resilient supplier selection problem, J Comput Sci, 40, (2020); De S.K., Mahata G.C., A production inventory supply chain model with partial backordering and disruption under triangular linguistic dense fuzzy lock set approach, Soft Comput, 24, pp. 5053-5069, (2020); De S.K., Mahata G.C., Solution of an imperfect-quality EOQ model with backorder under fuzzy lock leadership game approach, Int J Intell Syst, 36, pp. 421-446, (2021); Dogan E., Inglesi-Lotz R., Analyzing the effects of real income and biomass energy consumption on carbon dioxide (CO<sub>2</sub>) emissions: empirical evidence from the panel of biomass-consuming countries, Energy, 138, pp. 721-727, (2017); Dogan E., Seker F., Determinants of CO<sub>2</sub> emissions in the European Union: the role of renewable and non-renewable energy"}},"F. Jolai; School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran; email: fjolai@ut.ac.ir",null,"Springer Science and Business Media Deutschland GmbH",{"$nulls":5},1.4327643E7,null,null,null,"English","Soft Comput.","Article","Final","All Open Access; Bronze Open Access; Green Open Access","Scopus","2-s2.0-85159683040"]
["Straubinger A.; de Groot H.L.F.; Verhoef E.T.","Straubinger, Anna (57209339174); de Groot, Henri L.F. (7102115441); Verhoef, Erik T. (7003293765)","57209339174; 7102115441; 7003293765","E-commerce, delivery drones and their impact on cities",2023.0,"Transportation Research Part A: Policy and Practice",178.0,null,103841.0,null,null,null,0.0,"10.1016/j.tra.2023.103841","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174050823&doi=10.1016%2fj.tra.2023.103841&partnerID=40&md5=65864bd3705da85cb2f390a0256c0a2f","ZEW - Leibniz Centre for European Economic Research, L7, 1, Mannheim, 68161, Germany; Department of Spatial Economics, School of Business and Economics, Vrije Universiteit Amsterdam, De Boelelaan 1105, HV Amsterdam, 1081, Netherlands; Tinbergen Institute, Gustav Mahlerplein 17, MS Amsterdam, 1082, Netherlands","Straubinger A., ZEW - Leibniz Centre for European Economic Research, L7, 1, Mannheim, 68161, Germany; de Groot H.L.F., Department of Spatial Economics, School of Business and Economics, Vrije Universiteit Amsterdam, De Boelelaan 1105, HV Amsterdam, 1081, Netherlands, Tinbergen Institute, Gustav Mahlerplein 17, MS Amsterdam, 1082, Netherlands; Verhoef E.T., Department of Spatial Economics, School of Business and Economics, Vrije Universiteit Amsterdam, De Boelelaan 1105, HV Amsterdam, 1081, Netherlands, Tinbergen Institute, Gustav Mahlerplein 17, MS Amsterdam, 1082, Netherlands","E-commerce has gained importance over the last years and the COVID-19 pandemic has further strengthened this development. With the increasing opportunities that novel transport technologies such as cargo drones offer, e-commerce is likely to even become more attractive in upcoming years. This paper therefore analyses the long-run effects of increasing importance of e-commerce and, more specifically, the impact of a shift towards package delivery via drones. Using a polycentric urban spatial general equilibrium model that incorporates the different retail channels, we model the consumer's choice between local and online shopping. In the case of online shopping, delivery takes place either via drone or via truck. Due to the equilibrium mechanisms, changes in shopping behavior potentially result in different home and work location choices or labor supply choices. The model thus allows assessing the long-run effects of e-commerce and drone delivery, also on related markets such as the markets for land, labor and goods. A numerical simulation of the model shows that each additional retail channel adds welfare and that changes in the shopping channels result in changes in location choices of households and companies. © 2023 Elsevier Ltd","Agglomeration effects; Cargo drones; E-commerce; Spatial equilibrium; Welfare effects","Drones; Employment; Agglomeration effects; Cargo drone; E- commerces; Location choice; Longest run; Online shopping; Retail channel; Spatial equilibrium; Transport technology; Welfare effects; agglomeration; COVID-19; electronic commerce; epidemic; market system; spatial analysis; transportation development; transportation planning; Electronic commerce",{"$nulls":6},"Al-Kaisy A., Jung Y., Rakha H., Developing Passenger Car Equivalency Factors for Heavy Vehicles during Congestion, J. Transp. Eng., 131, 7, pp. 514-523, (2005); (2017); Anas A., Hiramatsu T., The economics of cordon tolling: General equilibrium and welfare analysis, Econ. 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How the Internet changes city centre shopping, J. Retail. Consum. Serv., 14, 3, pp. 192-207, (2007); Zhang J., Campbell J.F., Sweeney I.I., Donald C., Hupman A.C., Energy consumption models for delivery drones: A comparison and assessment, Transp. Res. Part D: Transp. Environ., 90, (2021)","A. Straubinger; ZEW - Leibniz Centre for European Economic Research, Mannheim, L7, 1, 68161, Germany; email: anna.straubinger@zew.de",null,"Elsevier Ltd",{"$nulls":5},9658564.0,null,null,null,"English","Transp. Res. Part A Policy Pract.","Article","Final",null,"Scopus","2-s2.0-85174050823"]
["Wang J.","Wang, Jing (58777892800)",5.87778928E10,"Cost control problems and countermeasures of e-commerce enterprises under the background of big data and Internet of Things",2023.0,"Journal of Computational Methods in Sciences and Engineering",23.0,6.0,null,3135.0,3145.0,10.0,0.0,"10.3233/JCM-226931","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85180532141&doi=10.3233%2fJCM-226931&partnerID=40&md5=89c74973addb1b25cfcc7885378f6c03","School of Economics and Management, Jiaozuo University, Henan, Jiaozuo, 454000, China","Wang J., School of Economics and Management, Jiaozuo University, Henan, Jiaozuo, 454000, China","The scale of e-commerce in China continues to expand, and it has a relatively good development prospect. However, there are many problems in cost control in the development of e-commerce in our country. E-commerce companies have many problems in terms of promotion costs, warehousing costs, and operating costs. Although predecessors have made great achievements in this field and helped e-commerce companies solve problems related to cost control, there are still many problems in e-commerce companies. Question. This article starts with big data and Internet of Things technology, and focuses on storage costs and transportation costs to solve the problems of cost control in e-commerce companies. The problems existing in the development of e-commerce enterprises are: (1) The cost control system is not mature enough, the business scope is not clear, the cost control lacks innovative awareness, the logistics cost remains high, and the logistics management model is unreasonable. In order to solve these problems, we built a transportation cost optimization model and an operation cost optimization model based on big data and Internet of Things technology. Transportation cost and operation cost are two important components of the cost of e-commerce enterprises in my country. The model has been verified to effectively reduce transportation costs and operating costs, which is of great significance to reducing the cost of e-commerce enterprises in my country, can solve the problems of e-commerce enterprise development, and promote the development of e-commerce in my country. Finally, according to the model constructed by the questionnaire survey and the article, we put forward corresponding suggestions (1) optimize customer relationship, improve the enterprise model (2) promote enterprise innovation, and promote the transformation of marketing costs (3) improve the degree of informatization of e-commerce enterprises.  © 2023 - IOS Press. All rights reserved.","Big data; cost control; countermeasures; e-commerce; Internet of Things","Big data; Cost effectiveness; Digital storage; Electronic commerce; Informatization; Internet of things; Optimization; Public relations; Control problems; Cost controls; Costs Optimization; Countermeasure; E- commerces; E-commerce enterprise; Internet of things technologies; Operations cost; Optimization models; Transportation cost; Operating costs",{"$nulls":6},"Cumming D., Johan S., Khan Z., Meyer M., E-commerce policy and international business, Manag Int Rev., 63, 1, pp. 3-25, (2023); Yin X., He J., Construction of tourism e-commerce platform based on artificial intelligence algorithm, Comput Intell Neurosci., 2022, (2022); Ding Q., Zhao H., Study on e-commerce logistics cost control methods in the context of COVID-19 prevention and control, Soft Comput., 25, 18, pp. 11955-11963, (2021); Chen W.H., Lin Y.C., Bag A., Chen C.L., Influence factors of small and medium-sized enterprises and micro-enterprises in the cross-border e-commerce platforms, J Theor Appl El Comm., 18, 1, pp. 416-440, (2023); Jiang J., Chen J., Framework of blockchain-supported e-commerce platform for small and medium enterprises, Sustainability., 13, 15, (2021); Chen Q., Analysis and prediction of cross-border e-commerce scale of china based on the machine learning model, Comput Intell Neurosci., 2022, (2022); Li L.Z., Zhang J., Research and analysis of an enterprise e-commerce marketing system under the big data environment, J Organ End User Com., 33, 6, pp. 1-19, (2021); Cao X., Deng M., Li H., How does e-commerce city pilot improve green total factor productivity? 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Wang; School of Economics and Management, Jiaozuo University, Jiaozuo, Henan, 454000, China; email: wang_jing188@outlook.com",null,"IOS Press BV",{"$nulls":5},1.4727978E7,null,null,null,"English","J. Comput. Methods Sci. Eng.","Article","Final",null,"Scopus","2-s2.0-85180532141"]
["Zhang W.; Fan Y.; Yuan Y.","Zhang, Wei (56413415700); Fan, Yangming (58627857800); Yuan, Ye (57217330438)","56413415700; 58627857800; 57217330438","Research on the Symbiotic Model of Supply Chains Based on the Logistic Expansion Model for E-Commerce Platforms",2023.0,"Sustainability (Switzerland)",15.0,18.0,13826.0,null,null,null,0.0,"10.3390/su151813826","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85172890192&doi=10.3390%2fsu151813826&partnerID=40&md5=58087faf49abc5903795f00f1744ce60","School of Economics and Management, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China; School of Modern Post, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China","Zhang W., School of Economics and Management, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China; Fan Y., School of Modern Post, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China; Yuan Y., School of Economics and Management, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China","With the development of globalization and technology, e-commerce platforms provide a more convenient shopping experience while also increasing the complexity and difficulty of the supply chain. Managers of e-commerce platform operations need to think about and investigate how to optimize the supply chains of e-commerce platforms, reduce costs and improve efficiency. In this paper, we use the logistic population expansion model to explore the symbiotic relationship among the core populations, key populations and supporting populations within the supply chain ecosystem of e-commerce platforms and the conditions that affect the evolution direction of the symbiotic model. The results show the following: (1) The size of the symbiosis between the three types of populations determines the equilibrium state of the symbiotic evolution of the e-commerce platform supply chain ecosystem. (2) The value of the sum of the symbiotic interaction coefficients between subjects in the supply chain ecosystem of an e-commerce platform determines the result of the symbiotic evolution of the system. (3) The reciprocal symbiosis model can maximize the synergy of the three types of subjects and is the best goal direction for ecosystem evolution. This study can provide a theoretical basis and practical support for the development of e-commerce platform-related enterprises. © 2023 by the authors.","e-commerce platform supply chain; ecosystem; logistic expansion model; symbiotic model","electronic commerce; globalization; logistics; supply chain management; symbiosis",{"$nulls":4},"Humanities and Social Sciences Ministry of Education in China, (18YJC790224); Science and Technology research project of the Chongqing Education Commission, (KJQN202100636); Chongqing Municipal Education Commission, CQMEC, (23SKJD064)","The authors gratefully thank the project of the Humanities and Social Sciences Ministry of Education in China (18YJC790224), the project of the Humanities and Social Sciences Research Base of Chongqing Education Commission in 2023 (23SKJD064) and the Science and Technology research project of the Chongqing Education Commission (KJQN202100636).","Ehrlich P., Raven P., Butterflies and plants: A study in co-evolution, Evolution, 18, pp. 586-608, (1964); Chertow M., Ehrenfeld J., Organizing self-organizing systems: Toward a theory of industrial symbiosis, J. 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Mark, 32, pp. 1813-1842, (2022); Gibbons R.S., Game Theory for Applied Economists, (1992); Xia M., He X., Zhou Y., Symbiosis evolution of science communication ecosystem based on social media: A Lotka–Volterra model-based simulation, Complexity, 2021, (2021); Zhang C., Liang C., Zhang C., Ma Y., Symbiosis evolution model and behavior of multiple resource agents in the smart elderly care service ecosystem, Symmetry, 13, (2021)","Y. Fan; School of Modern Post, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China; email: s210731004@stu.cqupt.edu.cn",null,"Multidisciplinary Digital Publishing Institute (MDPI)",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85172890192"]
["Schaumann S.K.; Bergmann F.M.; Wagner S.M.; Winkenbach M.","Schaumann, Sarah K. (57224512918); Bergmann, Felix M. (57211960607); Wagner, Stephan M. (55728980600); Winkenbach, Matthias (57189308132)","57224512918; 57211960607; 55728980600; 57189308132","Route efficiency implications of time windows and vehicle capacities in first- and last-mile logistics",2023.0,"European Journal of Operational Research",311.0,1.0,null,88.0,111.0,23.0,1.0,"10.1016/j.ejor.2023.04.018","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85158066250&doi=10.1016%2fj.ejor.2023.04.018&partnerID=40&md5=775923168ab11a213ced6c9be50ea628","ETH Zurich, Chair of Logistics Management, Weinbergstrasse 56/58, Zurich, 8092, Switzerland; Massachusetts Institute of Technology, Center for Transportation and Logistics, 77 Massachusetts Avenue, Cambridge, 02139, MA, United States","Schaumann S.K., ETH Zurich, Chair of Logistics Management, Weinbergstrasse 56/58, Zurich, 8092, Switzerland; Bergmann F.M., ETH Zurich, Chair of Logistics Management, Weinbergstrasse 56/58, Zurich, 8092, Switzerland; Wagner S.M., ETH Zurich, Chair of Logistics Management, Weinbergstrasse 56/58, Zurich, 8092, Switzerland; Winkenbach M., Massachusetts Institute of Technology, Center for Transportation and Logistics, 77 Massachusetts Avenue, Cambridge, 02139, MA, United States","In this paper, we analyze the route efficiency effects that emerge from combining realistically constrained first-mile pickup and last-mile delivery operations into joint vehicle routes. Specifically, we examine (i) the individual effect of discrete, non-overlapping time window constraints; (ii) the individual effect of vehicle capacity constraints; and (iii) the joint impact of both constraint types on local route efficiency gains due to the integration of pickup and delivery operations. Extending the existent literature on continuum approximation of route distances, we propose closed-form adjustment factors which accurately capture these non-trivial route efficiency effects. To derive the adjustment factors, we conduct extensive numerical experiments and apply a novel hybrid data analysis approach which combines exploratory data analysis with symbolic regression. Our analysis suggests that these real-world constraints affect the optimal stop sequence and diminish or even eliminate the expected efficiency gains from integrating first- and last-mile operations. The proposed adjustment factors are particularly relevant for the optimal strategic design and operational planning of modern, industrial-scale distribution networks in light of growing and increasingly fragmented e-commerce volumes and a high cost pressure on the logistics industry. They help researchers and practitioners to efficiently quantify the expected benefits from integrating pickup and delivery operations, and to assess under which circumstances such an integration is (not) desirable. © 2023 The Authors","Continuum approximation; Pickup and delivery problems; Routing; Symbolic regression; Time windows","Data handling; Information analysis; Pickups; Vehicles; Adjustment factors; Continuum approximation; Efficiency gain; First mile; Last mile; Pickup and delivery; Pickup and delivery problems; Routings; Symbolic regression; Time windows; Efficiency",{"$nulls":6},"Acimovic J., Graves S.C., Making better fulfillment decisions on the fly in an online retail environment, Manufacturing and Service Operations Management, 17, 1, pp. 34-51, (2015); Ansari S., Basdere M., Li X., Ouyang Y., Smilowitz K., Advancements in continuous approximation models for logistics and transportation systems: 1996–2016, Transportation Research Part B: Methodological, 107, pp. 229-252, (2018); 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A modern approach, (2015); World Economic Forum, Net-zero challenge: The supply chain opportunity, Technical report, (2021)","S.K. Schaumann; ETH Zurich, Chair of Logistics Management, Zurich, Weinbergstrasse 56/58, 8092, Switzerland; email: sschaumann@ethz.ch",null,"Elsevier B.V.",{"$nulls":5},3772217.0,null,"EJORD",null,"English","Eur J Oper Res","Article","Final","All Open Access; Green Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85158066250"]
["Su E.; Qin H.; Li J.; Pan K.","Su, E. (57431785100); Qin, Hu (25925253100); Li, Jiliu (57211495066); Pan, Kai (54883210000)","57431785100; 25925253100; 57211495066; 54883210000","An exact algorithm for the pickup and delivery problem with crowdsourced bids and transshipment",2023.0,"Transportation Research Part B: Methodological",177.0,null,102831.0,null,null,null,0.0,"10.1016/j.trb.2023.102831","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85171626521&doi=10.1016%2fj.trb.2023.102831&partnerID=40&md5=4df52e2a84f3b713259c58565949d7cc","School of Management, Northwestern Polytechnical University, Xi'an, 710072, China; School of Management, Huazhong University of Science and Technology, Wuhan, 430074, China; Department of Logistics and Maritime Studies, Faculty of Business, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong","Su E., School of Management, Huazhong University of Science and Technology, Wuhan, 430074, China; Qin H., School of Management, Huazhong University of Science and Technology, Wuhan, 430074, China; Li J., School of Management, Northwestern Polytechnical University, Xi'an, 710072, China; Pan K., Department of Logistics and Maritime Studies, Faculty of Business, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong","This paper addresses a pickup and delivery problem with crowdsourced bids and transshipment (PDPCBT) in last-mile delivery, where all requests can be satisfied by either using the own vehicle fleet or outsourcing with a small compensation to crowdshippers through transshipment facilities. The crowdshippers show their willingness to deliver by submitting bids to the e-commerce company. To minimize both the travel cost of vehicles and the compensation of crowdshippers, the routes of vehicles and the selection of bids need to be optimized simultaneously. We formulate the PDPCBT into an arc-based formulation and a route-based formulation, where the latter is strengthened by the subset row inequalities. Based on the route-based formulation, we present a branch-and-price-and-cut algorithm to solve it exactly. To deal with two possible ways of serving requests, we first decompose the corresponding pricing problem into a shortest path problem and a knapsack problem, and then tackle them in the same bi-directional labeling algorithm framework. We also discuss acceleration techniques and implementation details to speed up the performance of the overall procedure. Computational experiments are conducted on a set of classic request instances, together with a set of randomly generated bid instances. With a time limit of two hours, numerical results validate the efficiency and effectiveness of the proposed algorithm. Finally, sensitivity analysis and managerial findings are also provided on the PDPCBT. © 2023 Elsevier Ltd","Branch-and-price-and-cut; Crowdsourced delivery; Pickup and delivery; Transshipment facilities; Vehicle routing","Combinatorial optimization; Crowdsourcing; Fleet operations; Graph theory; Integer programming; Pickups; Routing algorithms; Sensitivity analysis; Vehicles; Branch-and-price-and-cut; Crowdsourced delivery; E- commerces; Exact algorithms; Last mile; Pickup and delivery; Pickup and delivery problems; Transshipment facility; Travel costs; Vehicle fleets; algorithm; crowdsourcing; price dynamics; sensitivity analysis; shipping; travel behavior; Vehicle routing",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (71821001, 72301213); Research Grants Council, University Grants Committee, 研究資助局, (15501319)","The authors wish to sincerely thank the associate editor and two anonymous reviewers for their valuable suggestions and insightful comments to improve the manuscript. The work described in this paper was supported by two National Natural Science Foundations of China (No. 72301213 and 71821001 ), and was also partially supported by the Research Grants Council of Hong Kong [Grant 15501319 ]. ","Aized T., Srai J.S., Hierarchical modelling of last mile logistic distribution system, Int. J. Adv. Manuf. Technol., 70, pp. 1053-1061, (2014); Alcaraz J.J., Caballero-Arnaldos L., Vales-Alonso J., Rich vehicle routing problem with last-mile outsourcing decisions, Transp. Res. E, pp. 263-286, (2019); Alnaggar A., Gzara F., Bookbinder J., Crowdsourced delivery: A review of platforms and academic literature, Omega-Int. J. Manag. Sci., 98, (2019); Archetti C., Savelsbergh M., Speranza M., The vehicle routing problem with occasional drivers, European J. Oper. Res., 254, pp. 472-480, (2016); Arslan A.M., Agatz N.A.H., Kroon L.G., Zuidwijk R.A., Crowdsourced delivery - a dynamic pickup and delivery problem with ad hoc drivers, Transp. 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Rev., 4, pp. 13-22, (2017); Zhou L., Baldacci R., Vigo D., Wang X., A multi-depot two-echelon vehicle routing problem with delivery options arising in the last mile distribution, European J. Oper. Res., 265, pp. 765-778, (2018); Zou B., Kafle N., Designing mechanisms for crowdsourced urban parcel delivery, Transp. Lett., (2022)","J. Li; School of Management, Northwestern Polytechnical University, Xi'an, 710072, China; email: jiliuli@nwpu.edu.cn",null,"Elsevier Ltd",{"$nulls":5},1912615.0,null,null,null,"English","Transp. Res. Part B Methodol.","Article","Final",null,"Scopus","2-s2.0-85171626521"]
["Snoeck A.; Winkenbach M.; Fransoo J.C.","Snoeck, André (57201382701); Winkenbach, Matthias (57189308132); Fransoo, Jan C. (6602253532)","57201382701; 57189308132; 6602253532","On-demand last-mile distribution network design with omnichannel inventory",2023.0,"Transportation Research Part E: Logistics and Transportation Review",180.0,null,103324.0,null,null,null,0.0,"10.1016/j.tre.2023.103324","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85175070927&doi=10.1016%2fj.tre.2023.103324&partnerID=40&md5=80743b3e35d54b96c45eb43ff050b847","Massachusetts Institute of Technology, Center for Transportation and Logistics, 77 Massachusetts Avenue, Cambridge, 02139, MA, United States; Tilburg University, Tilburg School of Economics and Management, Warandelaan 2, LE Tilburg, NL-5000, Netherlands","Snoeck A., Massachusetts Institute of Technology, Center for Transportation and Logistics, 77 Massachusetts Avenue, Cambridge, 02139, MA, United States; Winkenbach M., Massachusetts Institute of Technology, Center for Transportation and Logistics, 77 Massachusetts Avenue, Cambridge, 02139, MA, United States; Fransoo J.C., Tilburg University, Tilburg School of Economics and Management, Warandelaan 2, LE Tilburg, NL-5000, Netherlands","E-commerce delivery deadlines are getting increasingly tight, driven by a growing ‘I-want-it-now’ instant gratification mindset of consumers and the desire of online and omnichannel retailers to capitalize on the growth of on-demand e-commerce. On-demand deliveries with delivery deadlines as tight as one or two hours force companies to rethink their last-mile distribution network, since tight delivery deadlines require decentralization of order picking and inventory holding to ensure close proximity to consumers. This fundamentally changes the strategic design process of last-mile distribution networks. We study the impact of incorporating inventory order-up-to level decisions into the strategic design process of last-mile distribution networks with tight delivery deadlines. We develop an approximate inventory model by including an estimate of the cost of late delivery and additional transportation due to local stock-outs in a newsvendor formulation. Such local stock-outs require an order to be delivered from a more distant facility, which may lead to late delivery and additional transportation cost. We integrate our approximate inventory model and a location–allocation mixed-integer program that determines optimal facility locations, associated order-up-to inventory levels, and fleet composition, into a metamodel simulation-based optimization approach. Our numerical analyses demonstrate that pooling the additional online inventory with brick-and-mortar (B&M) inventories leads to cannibalization by the B&M network and higher B&M service levels. However, the pooling benefits to the online network outweigh the cost of inventory cannibalization. Furthermore, we show under which circumstances omnichannel retailers may have an incentive to consolidate online inventory in specific B&M facilities. © 2023 Elsevier Ltd","Last-mile logistics; Newsvendor model; Omnichannel; Simulation-based optimization; Strategic network design","Design; Electronic commerce; Fleet operations; Integer programming; Inventory control; Delivery deadlines; Last mile; Last-mile logistic; Network design; Newsvendor models; Omnichannel; On demands; Simulation-based optimizations; Strategic design; Strategic network design; cost analysis; distribution system; electronic commerce; inventory; location-allocation model; network design; optimization; travel demand; Cost benefit analysis",{"$nulls":6},"Acimovic J., Graves S.C., Making better fulfillment decisions on the fly in an online retail environment, Manuf. Serv. Oper. Manag., 17, 1, pp. 34-51, (2015); Acimovic J., Graves S.C., Mitigating spillover in online retailing via replenishment, Manuf. Serv. Oper. 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["Min H.","Min, Hokey (7102292247)",7.102292247E9,"Leveraging Drone Technology for Last-Mile Deliveries in the e-Tailing Ecosystem",2023.0,"Sustainability (Switzerland)",15.0,15.0,11588.0,null,null,null,2.0,"10.3390/su151511588","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85167786136&doi=10.3390%2fsu151511588&partnerID=40&md5=85b8c5cc2d7bab9f85ab5bf7a3a99000","Allen and Carol Schmidthorst College of Business, Bowling Green State University, Bowling Green, 43403, OH, United States","Min H., Allen and Carol Schmidthorst College of Business, Bowling Green State University, Bowling Green, 43403, OH, United States","The extended lockdown and limited in-person interactions resulting from the COVID-19 pandemic have radically changed many consumers’ shopping behavior. These changes include a rapid rise in online shopping, leading to the fast growth of e-logistics. As the popularity of e-logistics has spread worldwide, many retailers’ success hinges on their ability to deliver products to their consumers’ doorsteps. This ability cannot be nurtured without handling last-mile delivery services in a cost-efficient and sustainable way. However, last-mile delivery services pose unique and complex challenges since they require individual, door-to-door services that limit the opportunity to consolidate small shipments into large ones and thus increase cost burdens for retailers selling products online. These challenges call for new, innovative ways of managing last-mile delivery services. Such practices include utilizing emerging drone technology that allows retailers to deliver products from point to point ubiquitously without a pilot, driver, or vehicle consuming too much fossil fuel. This paper is one of the first studies to develop viable strategic plans for commercializing drone technology in the e-tailing ecosystem using visual decision-aid tools and performance management systems. © 2023 by the author.","drone technology; e-commerce; last-mile delivery; supply chain ecosystem; sustainability","COVID-19; fossil fuel; logistics; supply chain management; sustainability; tailings",{"$nulls":6},"This Year Next Year: E-Commerce forecast. Group Business Intelligence; Kim Y., Kang J., Chun H., Is online shopping packaging waste a threat to the environment?, Econ. Lett, 214, (2022); Chua J.M., Online shopping has boomed in the pandemic. But what about all the packaging?, Vox, (2021); Min H., The Essentials of Supply Chain Management: New Business Concepts and Applications, (2015); Nonami K., Drone technology, cutting-edge drone business, and prospects, J. Robot. Mechatron, 28, pp. 262-272, (2016); Boyle M.J., The Drone Age: How Drone Technology Will Change War and Peace, (2020); Public Perception of Drone Delivery in the United States, (2016); Drone logistics and transportation market size to reach USD 31.84 billion in 2028, PR Newswire, (2022); Caon V., How will drone corridors change the logistics sector?, Investment Monitor, (2023); Moshref-Javadi M., Winkenbach M., Applications and Research avenues for drone-based models in logistics: A classification and review, Expert Syst. Appl, 177, (2021); Rejeb A., Rejeb K., Simske S.J., Treiblmaier H., Drones for supply chain management and logistics: A review and research agenda, Int. J. Logist. Res. Appl, 26, pp. 708-731, (2021); Benarbia T., Kyamakya K., A literature review of drone-based package delivery logistics systems and their implementation feasibility, Sustainability, 14, (2022); Muricho M.W., Mogaka C.O., Drone technology and performance of retail logistics, J. Sustain. Dev. Transp. 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J. Op. Prod. Manag, 16, pp. 27-37, (1996); Broadbent J., Laughlin R., Performance management systems: A conceptual model, Manag. Account. Res, 20, pp. 283-295, (2009)","H. Min; Allen and Carol Schmidthorst College of Business, Bowling Green State University, Bowling Green, 43403, United States; email: hmin@bgsu.edu",null,"Multidisciplinary Digital Publishing Institute (MDPI)",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85167786136"]
["Zeng S.; Fu Q.; Haleem F.; Han Y.; Zhou L.","Zeng, Shaolong (57216081690); Fu, Qinyi (58101172100); Haleem, Fazli (57194018368); Han, Yiyang (57992816600); Zhou, Ling (58185218800)","57216081690; 58101172100; 57194018368; 57992816600; 58185218800","Logistics density, E-commerce and high-quality economic development: An empirical analysis based on provincial panel data in China",2023.0,"Journal of Cleaner Production",426.0,null,138871.0,null,null,null,0.0,"10.1016/j.jclepro.2023.138871","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85173020119&doi=10.1016%2fj.jclepro.2023.138871&partnerID=40&md5=742ba775e4ac1a27f039d54db37cd134","School of Economics, Hangzhou Normal University, Zhejiang, Hangzhou, 311121, China; Department of Management Sciences, Shaheed Benazir Bhutto University, Sheringal, 18200, Pakistan; Stanford University, Stanford Institute of Economic Policy Research, 366 Galvez St, Stanford, CA, United States; School of Marxism, Hangzhou Normal University, Zhejiang, Hangzhou, 311121, China","Zeng S., School of Economics, Hangzhou Normal University, Zhejiang, Hangzhou, 311121, China; Fu Q., School of Economics, Hangzhou Normal University, Zhejiang, Hangzhou, 311121, China; Haleem F., Department of Management Sciences, Shaheed Benazir Bhutto University, Sheringal, 18200, Pakistan; Han Y., Stanford University, Stanford Institute of Economic Policy Research, 366 Galvez St, Stanford, CA, United States; Zhou L., School of Marxism, Hangzhou Normal University, Zhejiang, Hangzhou, 311121, China","Under the background of high-quality development, the e-commerce industry needs to seek more comprehensive development, and the logistics industry should not only maintain higher efficiency, but also meet the requirements of green and low-carbon transportation. This study aims to investigate the link between the logistic density and the proportion of e-commerce transaction scale. There are few studies on how logistics density affects the development of e-commerce quantitatively. In order to solve this gap, this study establishes an impact model of high-quality growth of e-commerce, and based on Solow production model, constructs a calculation method of logistics density, and analyzes the impact mechanism of logistics density on the scale ratio of e-commerce transactions. Using the bidirectional fixed effect model, this paper makes an empirical analysis of the panel data of 31 provinces consisting of 248 observations and autonomous regions in China from 2014 to 2020. The results show that logistic density has a positive and significant impact on the growth of e-commerce, thus promoting the optimization of economic structure. The acceleration of logistics density decreases the expansion of the ecommerce. Finally, there are obvious regional differences between the development of e-commerce and logistics infrastructure in China. Finally, based on the empirical result, this paper puts forward recommendations for government and companies. © 2023 The Authors","China; E-commerce scale; High-quality development; Influence; Logistics density","Acceleration; Quality control; Structural optimization; China; E- commerces; E-commerce scale; E-commerce transactions; Empirical analysis; High quality; High-quality development; Influence; Logistic density; Panel data; Electronic commerce",{"$nulls":4},"Teaching Reform Project for Undergraduate Universities in Zhejiang Province of China, (jg20220488); Hangzhou Normal University, HNU, (2022HSDYJSKY082)","The work was supported by the “14th Five-Year Plan” Teaching Reform Project for Undergraduate Universities in Zhejiang Province of China [Grant No. jg20220488 ]; 2022 Hangzhou Normal University Graduate Research Innovation Promotion Project [Grant No. 2022HSDYJSKY082 ]. 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Technol., 35, 4-6, pp. 357-367, (2016); Zhu L., Thatcher S., National information ecology: a new institutional economics perspective on global E-commerce adoption, J. Electron. Commer. Res., 11, 1, pp. 53-72, (2010); Zhu F.C., Shi Q.L., Balezentis T., Zhang C.H., The impact of e-commerce and R&D on firm-level production in China: evidence from manufacturing sector, Struct. Change Econ. Dynam., 65, pp. 101-110, (2023)","L. Zhou; School of Marxism, Hangzhou Normal University, Hangzhou, Zhejiang, 311121, China; email: lingzhou@hznu.edu.cn",null,"Elsevier Ltd",{"$nulls":5},9596526.0,null,"JCROE",null,"English","J. Clean. Prod.","Article","Final","All Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85173020119"]
["Long Y.; Chen G.; Wang Y.","Long, Ying (58513960300); Chen, Guangwu (56898280400); Wang, Yafei (56010795100)","58513960300; 56898280400; 56010795100","Carbon footprint of residents' online consumption in China",2023.0,"Environmental Impact Assessment Review",103.0,null,107228.0,null,null,null,4.0,"10.1016/j.eiar.2023.107228","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85166321071&doi=10.1016%2fj.eiar.2023.107228&partnerID=40&md5=fa15e0ac1138bd62fe0d140714073cde","School of Statistics, Beijing Normal University, Beijing, 100875, China; School of Business, University of Queensland, St Lucia, 4072, QLD, Australia","Long Y., School of Statistics, Beijing Normal University, Beijing, 100875, China; Chen G., School of Business, University of Queensland, St Lucia, 4072, QLD, Australia; Wang Y., School of Statistics, Beijing Normal University, Beijing, 100875, China","Although China boasts the largest online consumption market, there has been no prior case study addressing the carbon footprint of online consumption. The rapid expansion of online consumption has posed a challenge to China's carbon neutrality pledge. This paper aims to fill this crucial gap by conducting a pioneering study based on survey data collected from 6000 households. To achieve this goal, this study has combined provincial Multi-Regional Input-Output (MRIO) tables with residents' online consumption calculated by the Non-Linear Optimization model, and applied the Environmental Input-Output Life Cycle Assessment (EIO-LCA) model to calculate the carbon footprint of residents' online consumption. Result indicated that the average carbon footprint of residents' online consumption was 0.46 tCO2e in 2016, accounting for 12.30% of the total consumption carbon footprint. Notably, high-emission regions include Beijing-Tianjin, Jiangsu-Zhejiang-Shanghai, and Hubei. Moreover, the dominant sources of the online consumption carbon footprint were electricity, food, clothing, and beauty products. Furthermore, we found that the carbon footprint of online consumption tends to increase with income, with differential income elasticities observed for various products and income groups. We also quantified the average expenditure-based life-cycle carbon coefficient for parcel delivery (0.22 kgCO2e/yuan) and conducted two scenario analyses to assess its impact. From a policy perspective, our research on measuring the carbon footprint of residents' online consumption can provide valuable insights for designing future policies and decisions related to e-commerce and key sectors along the supply chains. Additionally, it will further encourage Chinese residents to adopt low-carbon lifestyles. © 2023","Environmental input-output life cycle assessment model; Household survey; Income elasticity; Non-linear optimization; Online consumption","Beijing [China]; China; Hubei; Jiangsu; Shanghai; Tianjin; Zhejiang; Elasticity; Emission control; Life cycle; Nonlinear programming; Supply chains; Carbon neutralities; Case-studies; Environmental input-output life cycle assessment model; Household surveys; Income elasticities; Input-output; Life cycle assessment model; Non-linear optimization; Online consumption; Rapid expansion; carbon footprint; consumption behavior; electronic commerce; environmental economics; household income; life cycle analysis; optimization; Carbon footprint",{"$nulls":4},"National Philosophy and Social Science Foundation of China, (21CTJ017, 22VRC165)","This work was supported by the National Philosophy and Social Science Foundation of China [Grant NO. 22VRC165 ] and Youth Program of National Philosophy and Social Science Foundation of China [Grant NO. 21CTJ017 ]. 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["Tao Y.; Zhuo H.; Lai X.","Tao, Yi (36476868000); Zhuo, Haibing (58498635700); Lai, Xiaofan (37100077900)","36476868000; 58498635700; 37100077900","The pickup and delivery problem with multiple depots and dynamic occasional drivers in crowdshipping delivery",2023.0,"Computers and Industrial Engineering",182.0,null,109440.0,null,null,null,1.0,"10.1016/j.cie.2023.109440","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85165320155&doi=10.1016%2fj.cie.2023.109440&partnerID=40&md5=fa56cb98d69288b438f99e4e92fbf2e1","School of Management, Guangdong University of Technology, Guangzhou, China; Institute of Big Data Intelligent Management and Decision, College of Management, Shenzhen University, Shenzhen, China","Tao Y., School of Management, Guangdong University of Technology, Guangzhou, China; Zhuo H., School of Management, Guangdong University of Technology, Guangzhou, China; Lai X., Institute of Big Data Intelligent Management and Decision, College of Management, Shenzhen University, Shenzhen, China","In recent years, crowdshipping has gained much popularity because it not only has economic and environmental advantages, but also is regarded as an effective way to increase the resilience of supply chains and logistics. In this work, we focus on a last-mile delivery system that supports its O2O e-commerce partner for processing and fulfilling online orders in an urban area. Besides the full-time regular drivers, the system also relies on occasional drivers from society who dynamically announce their availability over the time horizon. We model the studied problem as a multi-depot pickup and delivery problem with dynamic occasional drivers. An event-based rolling horizon solution approach is proposed to solve the problem through iteratively calling for a re-optimization procedure to update the delivery plan at each decision epoch. Besides, we investigate the scenarios of disruptions to the delivery system. Extensive numerical experiments have proven the effectiveness of our proposed approach and have also demonstrated the studied crowdshipping system can help achieve the supply chain and logistics resilience. Moreover, sensitivity analysis on several important parameters have been carried out and managerial insights are drawn. © 2023 Elsevier Ltd","Crowdshipping; Disruption; Dynamic occasional drivers; Rolling horizon approach; Supply chain resilience","Pickups; Sensitivity analysis; Crowdshipping; Delivery systems; Disruption; Dynamic occasional driver; Last mile; Multiple depot; Pickup and delivery problems; Rolling horizon; Rolling horizon approach; Supply chain resiliences; Supply chains",{"$nulls":4},"SZU-LU, (202202003); Shenzhen Education Science, (jypj22002); Social Sciences and Planning Fund of Shenzhen, (SZ2022C009); National Natural Science Foundation of China, NSFC, (72071050); Ministry of Education of the People's Republic of China, MOE, (21YJC630052); Basic and Applied Basic Research Foundation of Guangdong Province, (2022A1515010541, 2023A1515030260)","This work is partially supported by National Natural Science Foundation of China (NSFC) ( 72071050 ), Guangdong Basic and Applied Basic Research Foundation ( 2022A1515010541 , 2023A1515030260 ), Humanities and Social Science Fund of Ministry of Education of China ( 21YJC630052 ), Social Sciences and Planning Fund of Shenzhen ( SZ2022C009 ), The 14th Five-Year Plan Fund of Shenzhen Education Science (jypj22002) and SZU-LU Joint Research Programme ( 202202003 ). 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Springer Proceedings in Mathematics & Statistics, 217, pp. 577-587, (2017); Macrina G., Pugliese L.D.P., Guerriero F., Laporte G., Crowd-shipping with time windows and transshipment nodes, Computers & Operations Research, 113, (2020); Mancini S., Gansterer M., Bundle generation for last-mile delivery with occasional drivers, Omega, 108, (2022); (2020); Mladenovic N., Hansen P., Variable neighborhood search, Computers & Operations Research, 24, 11, pp. 1097-1100, (1997); Mousavi K., Bodur M., Roorda M.J., Stochastic Last-Mile Delivery with Crowd-Shipping and Mobile Depots, Transportation Science, 56, 3, pp. 612-630, (2021); Nagy G., Wassan N.A., Speranza M.G., Archetti C., The Vehicle Routing Problem with Divisible Deliveries and Pickups, Transportation Science, 49, 2, pp. 271-294, (2013); Oyola J., Arntzen H., Woodruff D.L., The stochastic vehicle routing problem, a literature review, part II: Solution methods, EURO Journal on Transportation and Logistics, 6, pp. 349-388, (2016); Pani P., (2021); Phonin S., Likasiri C., 3-Phase heuristics for capacitated multiple-depot vehicle routing problem with separate backhaul and linehaul with a case study on corn residue management system, Computers & Industrial Engineering, 158, (2021); Polat O., A parallel variable neighborhood search for the vehicle routing problem with divisible deliveries and pickups, Computers & Operations Research, 85, pp. 71-86, (2017); Psaraftis H.N., Wen M., Kontovas C.A., Dynamic vehicle routing problems: Three decades and counting, Networks, 67, pp. 3-31, (2016); Pugliese L.D.P., Ferone D., Macrina G., Festa P., Guerriero F., The crowd-shipping with penalty cost function and uncertain travel times, Omega, 115, (2023); Punel A., Ermagun A., Stathopoulos A., Studying determinants of crowd-shipping use, Travel Behaviour and Society, 12, pp. 30-40, (2018); Sethanan K., Jamrus T., Hybrid differential evolution algorithm and genetic operator for multi-trip vehicle routing problem with backhauls and heterogeneous fleet in the beverage logistics industry, Computers & Industrial Engineering, 146, (2020); Singh S., Kumar R., Panchal R., Tiwari M.K., Impact of COVID-19 on logistics systems and disruptions in food supply chain, International Journal of Production Research, 59, 7, pp. 1993-2008, (2021); Solomon M.M., Algorithms for the vehicle routing and scheduling problems with time window constraints, Operations Research, 35, 2, pp. 254-265, (1987); Tao Y., Lai X., Zhou S., Information sharing in a transparent supply chain with transportation disruptions and supplier competition, Annals of Operations Research, pp. 1-23, (2020); Tao Y., Lin C., Wei L., Metaheuristics for a Large-Scale Vehicle Routing Problem of Same-Day Delivery in E-Commerce Logistics System, Journal of Advanced Transportation, Article, (2022); Torres F., Gendreau M., Rei W., Vehicle Routing with Stochastic Supply of Crowd Vehicles and Time Windows, Transportation Science, 56, 3, pp. 631-653, (2021); Torres F., Gendreau M., Rei W., Crowdshipping: An open VRP variant with stochastic destinations, Transportation Research Part C: Emerging Technologies, 140, (2022); Wang Y., Lei L., Zhang D., Lee L.H., Towards delivery-as-a-service: Effective neighborhood search strategies for integrated delivery optimization of E-commerce and static O2O parcels, Transportation Research Part B: Methodological, 139, pp. 38-63, (2020); Wang Y., Zhang D.X., Liu Q., Shen F.M., Lee L.H., Towards enhancing the last-mile delivery: An effective crowd-tasking model with scalable solutions, Transportation Research Part E: Logistics and Transportation Review, 93, pp. 279-293, (2016); Wei L., Zhang Z., Lim A., An adaptive variable neighborhood search for a heterogeneous fleet vehicle routing problem with three-dimensional loading constraints, IEEE Computational Intelligence Magazine, 9, 4, pp. 18-30, (2014); Wolfinger D., Salazar-Gonzalez J.J., The pickup and delivery problem with split loads and transshipments: A branch-and-cut solution approach, European Journal of Operational Research, 289, 2, pp. 470-484, (2021); Yu V.F., Jodiawan P., Hou M.-L., Gunawan A., Design of a two-echelon freight distribution system in last-mile logistics considering covering locations and occasional drivers, Transportation Research Part E: Logistics and Transportation Review, 154, (2021); Yu V.F., Jodiawan P., Redi A.A.N.P., Crowd-shipping problem with time windows, transshipment nodes, and delivery options, Transportation Research Part E: Logistics and Transportation Review, 157, (2022)","X. Lai; Institute of Big Data Intelligent Management and Decision, College of Management, Shenzhen University, Shenzhen, China; email: xiaofanlai@gmail.com",null,"Elsevier Ltd",{"$nulls":5},3608352.0,null,"CINDD",null,"English","Comput Ind Eng","Article","Final",null,"Scopus","2-s2.0-85165320155"]
["Li K.","Li, Kuigang (58630789200)",5.86307892E10,"Optimizing warehouse logistics scheduling strategy using soft computing and advanced machine learning techniques",2023.0,"Soft Computing",27.0,23.0,null,18077.0,18092.0,15.0,0.0,"10.1007/s00500-023-09269-4","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85173116831&doi=10.1007%2fs00500-023-09269-4&partnerID=40&md5=7e47cf5fcdf29a9e66b909b1042e1bbd","School of Economics, Anyang Normal University, Henan, Anyang, 455000, China","Li K., School of Economics, Anyang Normal University, Henan, Anyang, 455000, China","In recent years, with the improvement of people’s living standards, online shopping has become an indispensable part of people’s lives. The rapid development of e-commerce has brought unprecedented opportunities to the express delivery industry. Therefore, modern manufacturing enterprises must shorten the cycle from order to delivery to be successful. The study of machine learning (ML), which integrates computer science, statistics, pattern recognition, data mining, and predictive analytics, has become one of the most significant areas of research in the last few decades. It has also established itself as a cornerstone in terms of applications, making significant progress in modern information technology and practice. This paper used the capabilities of one of the powerful paradigms of ML called reinforcement learning (RL) and soft computing to improve the warehouse automation process while taking market demands into account. Since stackers and Automatic Guided Vehicles (AGV) are the main participants in this automation process, we focused on these two in our research to enhance the warehouse logistic scheduling process as a whole. To accomplish this, we collected historical data related to warehouse operation from the warehouse environment, such as AGV and stacker moments, inventory level, job execution time, and other pertinent factors. We first created an RF-based model using the Q-learning technique, one of the RF approaches, before using these data for the model training. The model designing is accomplished by first formulating the logistic scheduling problem as a Markov Decision Process (MDP), where the warehouse system changes between states and takes actions to maximize a cumulative reward over time. After that, we performed a number of operations, including state representation, action space definition, and reward design, to transform the problem into a format that the Q-learning approach can handle. In four experiments, the design model is trained using the data that has been collected up to 100 episodes. The proposed model is further improved with soft computing approaches such as fuzzy control methods. We utilized MATLAB and Plant simulation software to conduct the experiments. The results of the proposed model are thoroughly evaluated and compared with already existing approaches. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.","Machine learning algorithm; Reinforcement learning; Scheduling strategy; System simulation; Warehousing logistics","Automatic guided vehicles; Data mining; Electronic commerce; Fuzzy control; Learning algorithms; Learning systems; Markov processes; MATLAB; Pattern recognition; Scheduling algorithms; Soft computing; Automation process; Logistics scheduling; Machine learning algorithms; Machine learning techniques; Machine-learning; Reinforcement learnings; Scheduling strategies; Soft-Computing; System simulations; Warehousing logistic; Reinforcement learning",{"$nulls":4},"Education Department of Henan Province, (2020-ZDJH-013)","This study was funded by the General Project of Humanities and Social Sciences Research of Henan Provincial Department of Education: Research on Quality and Safety Monitoring Mechanism for Cold Chain Logistics of Agricultural Products in Henan Province, under Project Approval No. 2020-ZDJH-013. ","Aider M., Baatout F.Z., Hifi M., A look-ahead strategy-based method for scheduling multiprocessor tasks on two dedicated processors, Comput Ind Eng, 158, (2021); Cao F., An-Zhao J.I., A generalized classification scheme for crane scheduling with interference[J], Eur J Oper Res, 258, 1, pp. 343-357, (2017); Chen Z., Observer-based dissipative output feedback control for network T-S fuzzy systems under time delays with mismatch premise, Nonlinear Dyn, 95, pp. 2923-2941, (2019); Chen Z., Lu Y., Qin J., Cheng Z., An optimal seed scheduling strategy algorithm applied to cyberspace mimic defense, IEEE Access, 9, pp. 129032-129050, (2021); Chen J., Wang Q., Cheng H.H., Peng W., Xu W., A review of vision-based traffic semantic understanding in ITSs, IEEE Trans Intell Transp Syst, 23, 11, pp. 19954-19979, (2022); Cheng B., Wang M., Zhao S., Zhai Z., Zhu D., Et al., Situation-Aware Dynamic Service Coordination in an IoT Environment, IEEE/ACM Trans Networking, 25, 4, pp. 2082-2095, (2017); Dai X., Hou J., Li Q., Ullah R., Ni Z., Liu Y., Reliable control design for composite-driven scheme based on delay networked T-S fuzzy system, Int J Robust Nonlinear Control, 30, 4, pp. 1622-1642, (2020); Duan L.M., Path planning for batch picking of warehousing and logistics robots based on modified A* algorithm, Int J Online Eng, 14, 11, (2018); Hazrat B., Yin B., Kumar A., Ali M., Zhang J., Yao J., Jerk-bounded trajectory planning for rotary flexible joint manipulator: an experimental approach, Soft Comput, 27, 7, pp. 4029-4039, (2023); Jawad K., Wang L., Zhang J., Kumar A., Real-time lane detection and tracking for advanced driver assistance systems, In: 2019 Chinese Control Conference (CCC), pp. 6772-6777, (2019); Li C., Zhang Y., Hao Z., Luo Y., An effective scheduling strategy based on hypergraph partition in geographically distributed datacenters, Comput Netw, 170, (2020); Liu J., Lin G., Huang S., Zhou Y., Li Y., Rehtanz C., Optimal EV charging scheduling by considering the limited number of chargers, IEEE Trans Transport Electrific, 7, 3, pp. 1112-1122, (2020); Lu S., Ding Y., Liu M., Yin Z., Yin L., Et al., Multiscale feature extraction and fusion of image and text in VQA, Int J Comput Intell Syst, 16, 1, (2023); Lutz E., Coradi P.C., Applications of new technologies for monitoring and predicting grains quality stored: Sensors, internet of things, and artificial intelligence, Measurement, 188, (2022); Ma K., Et al., Reliability-constrained throughput optimization of industrial wireless sensor networks with energy harvesting relay, IEEE Internet Things J, 8, 17, pp. 13343-13354, (2021); Matsuo Y., LeCun Y., Sahani M., Precup D., Silver D., Sugiyama M., Uchibe E., Morimoto J., Deep learning, reinforcement learning, and world models, Neural Netw, 152, pp. 267-275, (2022); Muhammad A., Yin B., Kumar A., Sheikh A.M., Et al., Reduction of multiplications in convolutional neural networks, In: 2020 39Th Chinese Control Conference (CCC), pp. 7406-7411, (2020); Qaisar I., Majid A., Shamrooz S., Adaptive event-triggered robust H∞ control for Takagi-Sugeno fuzzy networked Markov jump systems with time-varying delay, Asian J Control, 25, 1, pp. 213-228, (2023); Shaikh A.M., Li Y., Et al., Pruning filters with L1-norm and capped L1-norm for CNN compression, Appl Intell, 51, pp. 1152-1160, (2021); Shamrooz M., Li Q., Hou J., Fault detection for asynchronous T-S fuzzy networked Markov jump systems with new event-triggered scheme, IET Control Theory Appl, 15, 11, pp. 1461-1473, (2021); Sun Z., Cao Y., Et al., A data-driven approach for intrusion and anomaly detection using automated machine learning for the Internet of Things, Soft Comput, (2023); Tang X., Reliability-aware cost-efficient scientific workflows scheduling strategy on multi-cloud systems, IEEE Trans Cloud Comput, 10, 4, pp. 2909-2919, (2021); Ullah R., Dai X., Sheng A., Event-triggered scheme for fault detection and isolation of non-linear system with time-varying delay, IET Control Theory Appl, 14, 16, pp. 2429-2438, (2020); Wu Z., Cao J., Wang Y., Wang Y., Zhang L., Et al., hPSD: A hybrid PU-learning-based spammer detection model for product reviews, IEEE Trans Cybern, 50, 4, pp. 1595-1606, (2020); Yan W., Xu Z., Zhou X., Su Q., Li S., Wu H., Fast object pose estimation using adaptive threshold for bin-picking, IEEE Access, 8, pp. 63055-63064, (2020); Yin B., Aslam M.S., Et al., A practical study of active disturbance rejection control for rotary flexible joint robot manipulator, Soft Comput, 27, pp. 4987-5001, (2023); Yu X., Liao X., Li W., Liu X., Tao Z., Logistics automation control based on machine learning algorithm, Clust Comput, 22, pp. 14003-14011, (2019); Yu G., Wu Y., Guo J., Experimental validation of fuzzy PID control of flexible joint system in presence of uncertainties, In: 2017 36Th Chinese Control Conference (CCC), pp. 4192-4197, (2017); Zhai Q., Yin B., Et al., Second-order convolutional network for crowd counting, In: Proc. SPIE 11198, Fourth International Workshop on Pattern Recognition, (2019); Zhang Y., Fu J., Energy-efficient computation offloading strategy with tasks scheduling in edge computing, Wirel Netw, 27, pp. 609-620, (2021); Zhang Y., Wang J., Liu S., Qian C., Game theory based real-time shop floor scheduling strategy and method for cloud manufacturing, Int J Intell Syst, 32, 4, pp. 437-463, (2017); Zhang H., Mi Y., Liu X., Zhang Y., Wang J., Et al., A differential game approach for real-time security defense decision in scale-free networks, Comput Netw, 224, (2023); Zheng Y., Shang Y., Shao Z., Jian L., A novel real-time scheduling strategy with near-linear complexity for integrating large-scale electric vehicles into smart grid, Appl Energy, 217, pp. 1-13, (2018); Zhou W., Piramuthu S., Chu F., Chu C., RFID-enabled flexible warehousing, Decis Support Syst, 98, pp. 99-112, (2017); Zhu D., IOT and big data based cooperative logistical delivery scheduling method and cloud robot system, Futur Gener Comput Syst, 86, pp. 709-715, (2018)","K. Li; School of Economics, Anyang Normal University, Anyang, Henan, 455000, China; email: z9583169@163.com",null,"Springer Science and Business Media Deutschland GmbH",{"$nulls":5},1.4327643E7,null,null,null,"English","Soft Comput.","Article","Final",null,"Scopus","2-s2.0-85173116831"]
["Hidayati N.N.","Hidayati, Nuraisa Novia (57221594540)",5.722159454E10,"Improving Aspect-Based Sentiment Analysis for Hotel Reviews with Latent Dirichlet Allocation and Machine Learning Algorithms",2023.0,"Register: Jurnal Ilmiah Teknologi Sistem Informasi",9.0,2.0,null,144.0,157.0,13.0,0.0,"10.26594/register.v9i2.3441","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85180874496&doi=10.26594%2fregister.v9i2.3441&partnerID=40&md5=3887fce38bb5af4d352ea85a470f9807","National Research and Innovation Agency, B.J. Building Habibie, Jl. M.H. Thamrin No.8, Central Jakarta, 10340, Indonesia","Hidayati N.N., National Research and Innovation Agency, B.J. Building Habibie, Jl. M.H. Thamrin No.8, Central Jakarta, 10340, Indonesia","The rapid expansion of online platforms has resulted in a deluge of user-generated content, emphasizing the need for sentiment analysis to gauge public opinion. Aspect-based sentiment analysis is now essential for uncovering intricate opinions within product reviews, social media posts, and online texts. Despite their potential, the complexity of human emotions and diverse language nuances pose significant challenges. Our study focuses on the importance and trends of sentiment and aspect-based sentiment analysis in automated review analysis, with a primary focus on Indonesian-language hotel reviews. Our research underscores the need for nuanced tools to unravel multifaceted sentiments. We propose an automation framework that utilizes Latent Dirichlet Allocation (LDA) for feature extraction. We evaluate LDA's performance, enhance it through filtration, and enrich it by integrating it with Word2Vec and Doc2Vec. Our methodology encompasses various machine learning algorithms, including Logistic Regression (LR), Stochastic Gradient Descent (SGD), Support Vector Machine (SVM), Random Forest (RF), and Light Gradient Boosting Machine (LGBM). Empirical results reveal that the optimal combination involves LDA bigram and Word2Vec, alongside the LGBM classifier, yielding an average F1 score of 86.6 across ten aspects. This contribution advances automated aspect-based sentiment analysis, offering concrete implications for e-commerce, marketing, and customer service. Our insights inform precise marketing strategies and enhance customer experiences, underscoring the research's relevance in the digital landscape. © 2023, the author(s).","aspect-based sentiment analysis; automated review analysis; customer service industries; latent dirichlet Allocation; machine learning algorithms",{"$nulls":7},"Drus Z., Khalid H., Sentiment analysis in social media and its application: Systematic literature review, Procedia Comput. Sci, 161, pp. 707-714, (2019); Jabalameli S., Xu Y., Shetty S., Spatial and sentiment analysis of public opinion toward COVID-19 pandemic using twitter data: At the early stage of vaccination, Int. J. Disaster Risk Reduct, 80, (2022); Felipe R., Et al., ScienceDirect Data Science in Social Politics with Particular Emphasis Data Politics with on Sentiment Data Science Science in in Social Social Politics Analysis with Particular Particular Emphasis Emphasis on Sentiment Analysis Sentiment Analysis, Procedia Comput. Sci, 214, pp. 420-427, (2022); Basak G. K., Kumar P., Marjit S., Mukherjee D., North American Journal of Economics and Finance The British Stock Market, currencies, brexit, and media sentiments: A big data analysis, North Am. J. Econ. Financ, 64, (2022); Li H., Yu B. X. B., Li G., Gao H., Restaurant survival prediction using customer-generated content: An aspect-based sentiment analysis of online reviews, Tour. Manag, 96, (2023); Huang Y., Wang R., Huang B., Wei B., Zheng S. L., Chen M., Sentiment Classification of Crowdsourcing Participants' Reviews Text Based on LDA Topic Model, IEEE Access, 9, pp. 108131-108143, (2021); Abelard A. R., Sibaroni Y., Multi-aspect sentiment analysis on netflix application using latent dirichlet allocation and support vector machine methods, J. Infotel, 13, 3, pp. 128-133, (2021); Wardhana Janu Akrama, Sibaroni Yuliant, Aspect Level Sentiment Analysis on Zoom Cloud Meetings App Review Using LDA, J. RESTI (Rekayasa Sist. dan Teknol. Informasi), 5, 4, pp. 631-638, (2021); Sudiro R. V. O. I., Prasetiyowati S. S., Sibaroni Y., Aspect Based Sentiment Analysis with Combination Feature Extraction LDA and Word2vec, 2021 9th Int. Conf. Inf. Commun. Technol. ICoICT, 2021, pp. 611-615, (2021); Anoop V. S., Asharaf S., Aspect-oriented sentiment analysis: A topic modeling-powered approach, J. Intell. Syst, 29, 1, pp. 1166-1178, (2020); Wahyudi E., Kusumaningrum R., Aspect Based Sentiment Analysis in E-Commerce User Reviews Using Latent Dirichlet Allocation (LDA) and Sentiment Lexicon, ICICOS 2019-3rd Int. Conf. Informatics Comput. Sci. Accel. Informatics Comput. Res. Smarter Soc. Era Ind. 4.0, Proc, pp. 1-6, (2019); Cahyawijaya S., Et al., IndoNLG: Benchmark and Resources for Evaluating Indonesian Natural Language Generation, EMNLP 2021-2021 Conf. Empir. Methods Nat. Lang. Process. Proc, pp. 8875-8898, (2021); Pebiana S., Et al., Experimentation of Various Pre-processing Pipelines for Sentiment Analysis on Twitter Data about New Indonesia's Capital City Using SVM and CNN, 2022 25th Conf. Orient. COCOSDA Int. Comm. Co-ord. Stand. Speech Databases Assess. Tech. O-COCOSDA 2022-Proc, (2022); Prihatini P. M., Suryawan I. K., Mandia I. N., Feature extraction for document text using Latent Dirichlet Allocation, J. Phys. Conf. Ser, 953, 1, (2018); Hidayati N. N., Parlina A., Performance Comparison of Topic Modeling Algorithms on Indonesian Short Texts, ACM International Conference Proceeding Series, pp. 117-120, (2022); Martincic-Ipsic S., Milicic T., Todorovski L., The influence of feature representation of text on the performance of document classification, Appl. Sci, 9, 4, (2019); Reddy P. S., Sri D. R., Reddy C. S., Shaik S., Sentimental Analysis using Logistic Regression, 11, pp. 36-40, (2021); Qiu N., Shen Z., Hu X., Wang P., A novel sentiment classification model based on online learning, J. Algorithm. Comput. Technol, 13, 7186, (2019); Sabrila T. S., Azhar Y., Aditya C. S. K., Analisis Sentimen Tweet Tentang UU Cipta Kerja Menggunakan Algoritma SVM Berbasis PSO, JISKA (Jurnal Inform. Sunan Kalijaga), 7, 1, pp. 10-19, (2022); Bahrawi N., Sentiment Analysis Using Random Forest Algorithm-Online Social Media Based, J. Inf. Technol. Its Util, 2, 2, (2019); Alzamzami F., Hoda M., El Saddik A., Light Gradient Boosting Machine for General Sentiment Classification on Short Texts: A Comparative Evaluation, IEEE Access, 8, pp. 101840-101858, (2020); Prakash R., (PDF) Class Weight technique for Handling Class Imbalance, (2022); Abd Elrahman S. M., Abraham A., A Review of Class Imbalance Problem, J. Netw. Innov. Comput, 1, pp. 332-340, (2013); Johnson J. M., Khoshgoftaar T. M., Survey on deep learning with class imbalance, J. Big Data, 6, 1, (2019); Jeni L. A., Cohn J. F., De La Torre F., Facing imbalanced data-Recommendations for the use of performance metrics, Proc.-2013 Hum. Assoc. Conf. Affect. Comput. Intell. Interact. ACII 2013, pp. 245-251, (2013)","N.N. Hidayati; National Research and Innovation Agency, Central Jakarta, B.J. Building Habibie, Jl. M.H. Thamrin No.8, 10340, Indonesia; email: nunohida@gmail.com",null,"Universitas Pesantren Tinggi Darul Ulum",{"$nulls":5},2.5030477E7,null,null,null,"English","regist. j. ilm. teknol. sist. inf.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85180874496"]
["Vivaldini M.","Vivaldini, Mauro (26027693600)",2.60276936E10,"Logistical outsourcing in a virtual digital world: the dilemma for logistics service providers",2023.0,"International Journal of Logistics Systems and Management",46.0,3.0,null,312.0,332.0,20.0,0.0,"10.1504/IJLSM.2023.134799","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85178314202&doi=10.1504%2fIJLSM.2023.134799&partnerID=40&md5=e1fdd7c95298e97749ba6966d95bd803","PPGA, Paulista University – Unip, Rua Dr. Barcelar,, Vila Clementino, São Paulo, 1212, Brazil","Vivaldini M., PPGA, Paulista University – Unip, Rua Dr. Barcelar,, Vila Clementino, São Paulo, 1212, Brazil","This paper contextualises the impact of the transformations, arising from an increasingly virtual digital world, on logistics service providers (LSPs). The influence of changes driving logistical services to ever-increasing immediacy is also examined. As this paper addresses a still recent topic in the literature, with a restricted and limited research focus (logistical immediacy), this paper adopts a systematic literature review as the research method. A proposition concerning the dilemma faced by LSPs is constructed by highlighting aspects related to opportunities and implications, questioning the current model of logistical services adopted by companies. In addition to this contribution, the study presents several insights capable of leading to new ideas and new research avenues. © 2023 Inderscience Enterprises Ltd.. All rights reserved.","digital technology; e-commerce; logistic platforms; logistic service; logistical immediacy; logistics service providers; LSPs",{"$nulls":7},{"$cut":{"chars":20292,"head":"XPLore the New Frontier, (2020); Agrawal S., Singh R.K., Outsourcing and reverse supply chain performance: a triple bottom line approach, Benchmarking: An International Journal, 28, 4, (2020); Ali I., Golgeci I., Where is supply chain resilience research heading? A systematic and co-occurrence analysis, International Journal of Physical Distribution & Logistics Management, 49, 8, pp. 793-815, (2019); Alkhatib S.F., Strategic logistics outsourcing: upstream-downstream supply chain comparison, Journal of Global Operations and Strategic Sourcing, 10, 3, pp. 309-333, (2017); Amling A., Daugherty P.J., Logistics and distribution innovation in China, International Journal of Physical Distribution & Logistics Management, 50, 3, pp. 323-332, (2018); Ansari A., Modarress B., Challenges of outsourcing logistics to third-party providers, Int. J. Logistics Systems and Management, 7, 2, pp. 198-218, (2010); Asian S., Pool J.K., Nazarpour A., Tabaeeian R.A., On the importance of service performance and customer satisfaction in third-party logistics selection: an application of Kano model, Benchmarking: An International Journal, 26, 5, pp. 1550-1564, (2019); Azanha A., Vivaldini M., Pires S.R.I., Camargo Junior J.B.D., Voice picking: analysis of critical factors through a case study in Brazil and the United States, International Journal of Productivity and Performance Management, 65, 5, pp. 723-739, (2016); Bag S., Gupta S., Luo Z., Examining the role of logistics 4.0 enabled dynamic capabilities on firm performance, The International Journal of Logistics Management, 31, 3, pp. 607-628, (2020); Bartol T., Budimir G., Dekleva-Smrekar D., Et al., Assessment of research fields in Scopus and Web of Science in the view of national research evaluation in Slovenia, Scientometrics, 98, 2, pp. 1491-1504, (2014); Busse C.A., Procedure for secondary data analysis: innovation by logistics service providers, Journal of Supply Chain Management, 46, 4, pp. 44-58, (2010); Carbone V., Stone M.A., Growth and relational strategies used by the European logistics service providers: rationale and outcomes, Transportation Research Part E, 41, 6, pp. 495-510, (2005); Centobelli P., Cerchione R., Esposito E., Pursuing supply chain sustainable development goals through the adoption of green practices and enabling technologies: a cross-country analysis of LSPs, Technological Forecasting and Social Change, 153, (2020); Chapman K., Ellinger A.E., An evaluation of Web of Science, Scopus and Google Scholar citations in operations management, The International Journal of Logistics Management, 30, 4, pp. 1039-1053, (2019); Chen X., Cai G., Song J-S., The cash flow advantages of 3PLS as supply chain orchestrators, Manufacturing and Service Operations Management, 21, 2, pp. 435-451, (2019); Chopra A., Conceptual framework of IoT for transport logistics an approach to connecting material flow and IT in self-directing collaborating logistics progressions, International Journal of System Assurance Engineering and Management, 11, 2, pp. 258-266, (2020); Chu Z., Wang L., Lai F., Customer pressure and green innovations at third party logistics providers in China: the moderation effect of organizational culture, The International Journal of Logistics Management, 30, 1, pp. 57-75, (2018); Cichosz M., Wallenburg C.M., Knemeyer A.M., Digital transformation at logistics service providers: barriers, success factors and leading practices, The International Journal of Logistics Management, 31, 2, pp. 209-238, (2020); Cimini C., Lagorio A., Pirola F., Pinto R., How human factors affect operators’ task evolution in Logistics 4.0, Human Factors Management, 31, 1, pp. 98-117, (2021); Damanpour F., Magelssen C., Walker R.M., Outsourcing and insourcing of organizational activities: the role of outsourcing process mechanisms, Public Management Review, 22, 6, pp. 767-790, (2020); Dayarian I., Savelsbergh M., Crowdshipping and same‐day delivery: employing in‐store customers to deliver online orders, Production and Operation Management, 29, 9, pp. 2153-2174, (2020); Deepen B.M., Goldsby T.J., "}},"M. Vivaldini; PPGA, Paulista University – Unip, São Paulo, Rua Dr. Barcelar,, Vila Clementino, 1212, Brazil; email: mavivald@gmail.com",null,"Inderscience Publishers",{"$nulls":5},1.7427967E7,null,null,null,"English","Int. J. Logist. Syst. Manage.","Article","Final",null,"Scopus","2-s2.0-85178314202"]
["Zhan Y.; Sun Y.; Xu J.","Zhan, Ying (57206724106); Sun, Yue (57546592000); Xu, Junfei (57135519200)","57206724106; 57546592000; 57135519200","A Study on the Recycling Classification Behavior of Express Packaging Based on UTAUT under “Dual Carbon” Targets",2023.0,"Sustainability (Switzerland)",15.0,15.0,11622.0,null,null,null,1.0,"10.3390/su151511622","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85167807152&doi=10.3390%2fsu151511622&partnerID=40&md5=5219d037d86bddebfb5705c3bd1eb4f1","Department of Business Administration, Wuhan Business University, Wuhan, 430056, China; College of Weaponry Engineering, Naval University of Engineering, Wuhan, 430033, China","Zhan Y., Department of Business Administration, Wuhan Business University, Wuhan, 430056, China; Sun Y., Department of Business Administration, Wuhan Business University, Wuhan, 430056, China; Xu J., College of Weaponry Engineering, Naval University of Engineering, Wuhan, 430033, China","The rapid development of e-commerce has brought about a sharp increase in the demand for express packaging materials, which in turn has led to problems such as resource waste and environmental pollution. Under the target of “dual carbon”, the urgency and importance of effective classification and recycling of express packaging waste cannot be ignored. Based on the unified theory of technology acceptance and use (UTAUT) model and the characteristics of express packaging, this study selected performance expectancy, effort expectancy, social influence and perceived value as core variables, and gender, age and frequency as moderating variables, and established a structural equation through survey and analysis to study the factors influencing consumers’ willingness to recycle express packaging. The results of the study showed that performance expectancy, effort expectancy, social influence and perceived value had a significant positive effect on consumers’ willingness to classify. Classification willingness had a significant positive effect on consumers’ classification behavior. In addition to directly influencing classification intention, performance expectancy, effort expectancy and social influence also have mediating effects. In addition, gender played a moderating role in the effects of performance expectancy and social influence on classification intention. Based on the findings, this study proposes targeted measures to promote the green and healthy development of the express delivery industry. © 2023 by the authors.","carbon peaking and carbon neutrality; classification willingness; express packaging recycling; UTAUT model","classification; electronic commerce; environmental impact assessment; environmental planning; packaging waste; performance assessment; recycling; sustainable development",{"$nulls":4},"Hubei Provincial Department of Education, (B2021271)","This research was funded by [2021 Hubei Provincial Department of Education Research Program Project].grant number [B2021271].","Bi K.X., Yang M.K., Zhou X.G., Zahid L., Zhu Y.F., Sun Z.Y., Reducing Carbon Emissions from Collaborative Distribution: A Case Study of Urban Express in China, Environ. Sci. Pollut. 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Recycl, 168, (2021); Duan H.B., Song G.H., Qu S., Dong X.B., Xu M., Post-Consumer Packaging Waste from Express Delivery in China, Resour. Conserv. Recycl, 144, pp. 137-143, (2019); Su Y.H., Duan H.B., Wang Z.N., Song G.H., Kang P., Chen D.J., Characterizing the Environmental Impact of Packaging Materials for Express Delivery via Life Cycle Assessment, J. Clean. Prod, 274, (2020); Zheng Y., Li Z.M., Chai J.L., Progress and Prospects of International Carbon Peaking and Carbon Neutral Research—Based on Bibliometric Analysis (1991–2022), Front. Energy Res, 11, (2023); Liu W., Ouyang H.J., Liu Q., Cai S.H., Wang C., Xie J.J., Hu W., Image Recognition for Garbage Classification Based on Transfer Learning and Model Fusion, Math. Probl. Eng, 2022, (2022); Li Y.F., Liu W., Deep Learning-Based Garbage Image Recognition Algorithm, Appl. Nanosci, 13, pp. 1415-1424, (2023); Wu Z.Z., Li H.Y., Wang X.F., Wu Z.J., Zou L., Xu L.X., Tan M., New Benchmark for Household Garbage Image Recognition, Tsinghua Sci. Technol, 27, pp. 793-803, (2022); Huang J., Tian C.Y., Ren J.W., Bian Z.F., Study on Impact Acoustic-Visual Sensor-Based Sorting of ELV Plastic Materials, Sensors, 17, (2017); Woidasky J., Moesslein J., Wendler P., Kirchenbauer D., Wacker D., Gao G.J., Lang-Koetz C., Identification and Sorting of Polymers in a Circular Economy Using Fluorescent Tracer Materials, Chem. Ing. 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Prot, 169, pp. 685-696, (2023); El-Hefnawy M.E., Ismail A.I., Alhayyani S., Al-Goul S.T., Zayed M.M., Taleb M.A., Immobilization of Strontium Aluminate into Recycled Polycarbonate Plastics towards an Afterglow and Photochromic Smart Window, Polymers, 15, (2023); Alvarenga L.M., Xavier T.P., Barrozo M.A.S., Bacelos M.S., Lira T.S., Determination of Activation Energy of Pyrolysis of Carton Packaging Wastes and Its Pure Components Using Thermogravimetry, Waste Manag, 53, pp. 68-75, (2016); Xiao L., Fan R.R., Wang C.J., Wang J., Policy Analyses on Promoting the Recycling of Express Packages, Sustainability, 12, (2020); Hu N.J., Zhang Q., Li C.L., Sun H.W., Policy Intervention Effect Research on Pesticide Packaging Waste Recycling: Evidence from Jiangsu, China, Front. Environ. Sci, 10, (2022); Xu Q.Y., Shao Z., He Y., Optimal Delivery Strategies for Packing Box Recycling in Online Platforms, J. Clean. Prod, 276, (2020); Mao J., Cheng J.Y., Li X.Y., Zhao H.G., Lin C.Y., Optimal Design of Reverse Logistics Recycling Network for Express Packaging Considering Carbon Emissions, Mathematics, 11, (2023); Reijonen H., Bellman S., Murphy J., Kokkonen H., Factors Related to Recycling Plastic Packaging in Finland’s New Waste Management Scheme, Waste Manag, 131, pp. 88-97, (2021); Sajid M.J., Gonzalez E.D.R.S., Zhan J., Song X.H., Sun Y.B., Xie J., A Methodologically Sound Survey of Chinese Consumers’ Willingness to Participate in Courier, Express, and Parcel Companies’ Green Logistics, PLoS ONE, 16, (2021); Bai R., Lin B.Q., Are Residents Willing to Pay for Garbage Recycling: Evidence from a Survey in Chinese First-Tier Cities, Environ. Impact Assess. Rev, 95, (2022); Cao Y., Heng X., Zhang X., Qu M., Influence of Social Capital on Rural Household Garbage Sorting and Recycling Behavior: The Moderating Effect of Class Identity, Waste Manag, 158, pp. 84-92, (2023); He Y.Z., Pricing of the Bus-Truck Co-Delivery Mode of Last Mile Delivery Considering Social Welfare Maximization, Sustainability, 15, (2023); Wu C.X., Wu J.J., Wu Y., Wu Q.H., Lin X., Xiong N.N., Design and Analysis of the Task Distribution Scheme of Express Center at the End of Modern Logistics, Electronics, 8, (2019); Wu S.H., Yang Q., Yang Z.Z., Integrating Express Package Delivery Service with Offline Mobile Sales: A New Potential Solution to Sustainable Last-Mile Logistics in Rural China, Int. J. Logist.-Res. Appl, (2022); Lyu R., Zhang C.H., Li Z.T., Optimal Strategies of Green Express Packaging Recycling and Sales Mode in an Online Platform, J. Clean. 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Psychol, 13, (2022); Venkatesh V., Morris M.G., Davis D.F.D., User Acceptance of Information Technology: Toward a Unified View, MIS Q, 27, pp. 425-478, (2003); Laughrea M., Tam J., Ribosomal Protein S1 and Initiation Factor IF3 Do Not Promote the Ribosomal Binding of Approximately 19-Nucleotide-Long mDNA and mRNA Models, Biochem. Cell Biol. Biochim. Biol. Cell, 67, pp. 812-817, (1989); Vallerand J.R., Blssonnette R., Intrinsic, Extrinsic, and Amotivational Styles as Predictors of Behavior: A Prospective Study, J. Personal, 60, pp. 599-620, (1992); Thompson R.L., Higgins C.A., Howell J.M., Personal Computing: Toward A Conceptual Model of Utilization, MIS Q, 15, pp. 125-143, (1991); Rogers E.M., Diffusion of Innovation, (1995); Bandura A., The Explanatory and Predictive Scope of Self-Efficacy Theory, J. Soc. Clin. Psychol, 4, pp. 359-373, (1986); Hill R.J., Fishbein M., Ajzen I., Belief, Attitude, Intention and Behavior: An Introduction to Theory and Research, Contemp. Sociol, 6, pp. 244-245, (1977); Zeithaml V.A., Consumer Perceptions of Price, Quality, and Value: A Means-End Model and Synthesis of Evidence, J. Mark, 52, pp. 2-22, (1988); Dodds W.B., Monroe K.B., Grewal D., Effects of Price, Brand, and Store Information on Buyers’ Product Evaluations, J. Mark. Res, 28, pp. 307-319, (1991); Hsu C.L., Lin C.C., Effect of Perceived Value and Social Influences on Mobile App Stickiness and In-App Purchase Intention, Technol. Forecast. Soc. Chang, 108, pp. 42-53, (2016); Ming J.R., Zhang J., Yang Y.N., Chen K.L., User Behavior Model and Empirical Study of Mobile Library Based on UTAUT, Libr. Forum, 37, pp. 70-77, (2017); Guo J., Wang J.W., A Study on the Factors Influencing Mass Participation Behavior in Crowdsourcing Logistics Based on UTAUT Perspective, Oper. Res. Manag, 26, pp. 1-6, (2017); Mu X.Z., Xue L., A Study on the Classification Behavior of University Students in the Recycling Process of Take-Away Packaging, Environ. Eng, 40, pp. 199-205, (2022); Fang A.H., Lu M.M., Liu K.F., An Empirical Study on Users’ Willingness to Pay for Knowledge in Virtual Communities, Libr. Intell. Work, 62, pp. 105-115, (2018); He W.Q., Nie H., Pei L., An Exploratory Analysis of Factors Influencing Online Music Users’ Willingness to Pay, Mod. Intell, 41, pp. 118-128, (2021); Song T., Research on the Influencing Factors of Shopping App User’s Usage Behavior Based on UTAUT Model, Master’s Thesis, (2017)","Y. Zhan; Department of Business Administration, Wuhan Business University, Wuhan, 430056, China; email: 20150381@wbu.edu.cn",null,"Multidisciplinary Digital Publishing Institute (MDPI)",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85167807152"]
["Hai X.; Liao T.; Zhao C.","Hai, Xiaowei (55270111200); Liao, Tian (58618769300); Zhao, Chanchan (25423276100)","55270111200; 58618769300; 25423276100","Fresh Produce E-Commerce Supply Chain Coordination Considering Promotional and Freshness-Keeping Efforts",2023.0,"Journal of Information Processing Systems",19.0,4.0,null,513.0,526.0,13.0,0.0,"10.3745/JIPS.04.0283","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85172323311&doi=10.3745%2fJIPS.04.0283&partnerID=40&md5=9b68be4ee95bcfbc3a71afb78e1e5e1f","School of Economics and Management, Inner Mongolia University of Technology, Hohhot, China; College of Information Engineering, Inner Mongolia University of Technology, Hohhot, China","Hai X., School of Economics and Management, Inner Mongolia University of Technology, Hohhot, China; Liao T., School of Economics and Management, Inner Mongolia University of Technology, Hohhot, China; Zhao C., College of Information Engineering, Inner Mongolia University of Technology, Hohhot, China","Supply chain coordination plays a critical role in improving the enterprise performance and the competitive advantage of fresh e-commerce. This study explores the coordination problem of a two-echelon fresh produce e-commerce supply chain comprising a fresh e-commerce enterprise and a fresh supplier in a novel framework. In this framework, the fresh e-commerce sells fresh produce and provides promotion effort; meanwhile, the fresh supplier deliveries fresh produce and provides freshness-keeping effort. Specifically, the optimal decisions under centralized and decentralized decision-making are compared, and it is found that centralized decisionmaking is more profitable. Based on this work, we created a cost-sharing and revenue-sharing combination contract. This study demonstrates that this contract effectively coordinates the supply chain and makes both parties achieve Pareto optimization when the parameters meet certain conditions. Finally, the feasibility and validity of the contract are presented through a numerical example. © 2023 KIPS","Fresh Produce E-commerce; Freshness-Keeping Effort; Promotional Effort; Supply Chain Coordination","Competition; Cost effectiveness; Decision making; Electronic commerce; Multiobjective optimization; Pareto principle; Centralised; Competitive advantage; E- commerces; Enterprise performance; Fresh produce; Fresh produce E-commerce; Freshness-keeping; Freshness-keeping effort; Promotional efforts; Supply chain coordination; Supply chains",{"$nulls":4},"Inner Mongolia Modern Logistics and Supply Chain Management Research Center; National Natural Science Foundation of China, NSFC, (71963025); Inner Mongolia University of Technology, IMUT, (BS201936); Research Program of Science and Technology at Universities of Inner Mongolia Autonomous Region, (NJZY22382)","This work is supported by the Research Program of Science and Technology at Universities of Inner Mongolia Autonomous Region (No. NJZY22382), the National Natural Science Foundation of China (No. 71963025), the Science Research Project of Inner Mongolia University of Technology (No. BS201936), and the Inner Mongolia Modern Logistics and Supply Chain Management Research Center.","Zan M. Y., Chen G., Wang Z. B., Development of e-commerce of fresh agricultural products in China: progress, difficulties and strategies, On Economic Problems, 2020, 12, pp. 68-74, (2020); Zhao A., Analysis of the development status, opportunities and trends of China's fresh food e-commerce industry in 2020, (2020); Howard Finch J., Becherer R. C., Casavant R., An option-based approach for pricing perishable services assets, Journal of Services Marketing, 12, 6, pp. 473-483, (1998); Grewal D., Ailawadi K. L., Gauri D., Hall K., Kopalle P., Robertson J. R., Innovations in retail pricing and promotions, Journal of Retailing, 87, pp. S43-S52, (2011); Lan C., Yu X., Revenue sharing-commission coordination contract for community group buying supply chain considering promotion effort, Alexandria Engineering Journal, 61, 4, pp. 2739-2748, (2022); Heydari J., Asl-Najafi J., A revised sales rebate contract with effort-dependent demand: a channel coordination approach, International Transactions in Operational Research, 28, 1, pp. 438-469, (2021); Krishnan H., Kapuscinski R., Butz D. A., Coordinating contracts for decentralized supply chains with retailer promotional effort, Management Science, 50, 1, pp. 48-63, (2004); Edelman B., Jaffe S., Kominers S. D., To groupon or not to groupon: the profitability of deep discounts, Marketing Letters, 27, pp. 39-53, (2016); Huo H., Wang Z. T., A study on coordination of agricultural products supply chain considering retailers' promotion efforts, Statistics & Decision, 36, 11, pp. 184-188, (2020); Dye C. Y., Yang C. T., Optimal dynamic pricing and preservation technology investment for deteriorating products with reference price effects, Omega, 62, pp. 52-67, (2016); McLaughlin K., Priceline’s ex-CEO puts eggs in basket of an online grocer, Wall Street Journal, (2005); Cai X., Chen J., Xiao Y., Xu X., Yu G., Fresh-product supply chain management with logistics outsourcing, Omega, 41, 4, pp. 752-765, (2013); Piao H., Hu X., The coordination of three-level fresh agricultural product supply chain oriented to green and fresh consumption, Industrial Engineering Journal, 23, 4, pp. 1-10, (2020); Zheng Q., Ieromonachou P., Fan T., Zhou L., Supply chain contracting coordination for fresh products with fresh-keeping effort, Industrial Management & Data Systems, 117, 3, pp. 538-559, (2017); Cao Y., Li Y. M., Wan G. Y., Study on the fresh degree incentive mechanism of fresh agricultural product supply chain based on consumer utility, Chinese Journal of Management Science, 26, 2, pp. 160-174, (2018); Gu B., Fu Y., Li Y., Fresh-keeping effort and channel performance in a fresh product supply chain with loss-averse consumers’ returns, Mathematical Problems in Engineering, 2018, (2018); Liu M. L., Dan B., Ma S. X., Optimal strategies and coordination of fresh e-commerce supply chain considering freshness-keeping effort and value-added service, Chinese Journal of Management Science, 28, 8, pp. 76-88, (2020); Yang Y., Fan T. J., Zhang L., Coordination of fresh agricultural supply chain with asymmetric freshness information, Chinese Journal of Management Science, 24, 9, pp. 147-155, (2016); Zheng Q., Fan T., Zhang L., The revenue sharing contract of fresh agricultural products under the mode of \"agricultural supermarket docking, Journal of Systems & Management, 28, 4, pp. 742-751, (2019); Huang Y., Liu L., Qi E., The dynamic decision in risk-averse complementary product manufacturers with corporate social responsibility, Kybernetes, 45, 2, pp. 244-265, (2016); Cai X., Chen J., Xiao Y., Xu X., Optimization and coordination of fresh product supply chains with freshness-keeping effort, Production and Operations Management, 19, 3, pp. 261-278, (2010); Ha A. Y., Tong S., Zhang H., Sharing demand information in competing supply chains with production diseconomies, Management Science, 57, 3, pp. 566-581, (2011); Wang G., Ding P., Chen H., Mu J., Green fresh product cost sharing contracts considering freshness-keeping effort, Soft Computing, 24, pp. 2671-2691, (2020)","C. Zhao; College of Information Engineering, Inner Mongolia University of Technology, Hohhot, China; email: cczhao@imut.edu.cn",null,"Korea Information Processing Society",{"$nulls":5},"1976913X",null,null,null,"English","J. Inf. Process. Syst.","Article","Final",null,"Scopus","2-s2.0-85172323311"]
["Olaghere J.A.; Inegbedion H.E.; Osiobe F.O.","Olaghere, John Ayo (58569252100); Inegbedion, Henry Egbezien (57192189691); Osiobe, Faith Ogheneriode (58569035200)","58569252100; 57192189691; 58569035200","The Implications of Digitalization in Retail Service Delivery on Circular Economy in Nigeria: An Exploratory Case Study",2023.0,"Sustainability (Switzerland)",15.0,17.0,13192.0,null,null,null,0.0,"10.3390/su151713192","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85170361814&doi=10.3390%2fsu151713192&partnerID=40&md5=78cfcc46c85c95965829c60119ecff27","School of Economics and Management, Hunan Institute of Science and Technology, Yueyang, 414006, China; Department of Business Administration, College of Management and Social Sciences, Bowen University, Iwo, 232102, Nigeria; Pinkkees Global Services Ltd, Nana St, Ughelli, 3331, Nigeria","Olaghere J.A., School of Economics and Management, Hunan Institute of Science and Technology, Yueyang, 414006, China; Inegbedion H.E., Department of Business Administration, College of Management and Social Sciences, Bowen University, Iwo, 232102, Nigeria; Osiobe F.O., Pinkkees Global Services Ltd, Nana St, Ughelli, 3331, Nigeria","The circular economy (CE) model has gained greater recognition and acceptance in recent years for its potential to enhance sustainability. Within this context, many practices in the retail sector are being overhauled through technological innovation, thereby changing the business landscape. Digitalization facilitates this transformation to mitigate the impacts of climate change without sacrificing productivity. This article explored the implications of digitalization in retail processes for CE in Nigeria and advanced practices that improve efficiency. Research efforts on circularity and digitalization have concentrated on advanced economies; consequently, little is known about the situation in lower-income countries. Due to the exploratory nature of this research, a qualitative approach that combined multiple data sources was adopted. Specifically, a case study of four major grocery retailers was carried out through documentary evidence supplemented by integrating thematic categories from semi-structured interviews with seasoned retail professionals. The findings revealed that (i) the circularity paradigm is a relatively vague concept among retailers in Nigeria; (ii) digital technologies are adopted primarily for the business value they create rather than to regenerate the ecosystem; (iii) the retailers have adopted technological processes such as e-commerce channel, automation, real-time tracking, social media marketing, and digital payment; and (iv) retailers familiar with circularity favor shortening supply chains by investing in rural hubs, food waste reduction, and closed-loops and reducing the use of non-biodegradable packaging. Retail managers could gain insights from these results to move towards CE, foster efficient business processes, and enhance customer satisfaction. © 2023 by the authors.","circular economy; digital transformation; digitalization; retail; sustainable development","Nigeria; automation; digitization; economic impact; electronic commerce; marketing; retailing; social media; sustainable development",{"$nulls":6},"The Role of Business in the Circular Economy: Markets, Processes and Enabling Policies, (2018); Ezeudu O., Ezeudu T., Ugochukwu U., Agunwamba J., Oraelosi T., Enablers and barriers to implementation of circular economy in solid waste valorization: The case of urban markets in Anambra, Southeast Nigeria, Environ. Sustain. Indic, 12, (2021); Murray A., Skene K., Haynes K., The circular economy: An interdisciplinary exploration of the concept and application in a global context, J. Bus. Ethics, 140, pp. 369-380, (2017); Tanveer M., Khan S., Umar M., Zhang Y., Sajid M., Haq I., Waste management and green technology: Future trends in circular economy leading towards environmental sustainability, Environ. Sci. Pollut. Res, 29, pp. 80161-80178, (2022); Dura C., Iordache A., Ionescu A., Isac C., Breaz T., Analyzing Performance in Wholesale Trade Romanian SMEs: Framing Circular Economy Business Scenarios, Sustainability, 14, (2022); Antikainen M., Uusitalo T., Kivikyto-Reponen P., Digitalization as an enabler of circular economy, Procedia CIRP, 73, pp. 45-49, (2018); Manzoor R., Sahay B., Singh S., Blockchain technology in supply chainmanagement: An organizational theoretic overview and research agenda, Ann. Oper. Res, (2022); Reis J., Amorim M., Melao N., Cohen Y., Rodrigues M., Digitalization: A literature review and research agenda, Proceedings of the 25th International Joint Conference on Industrial Engineering and Operations Management—IJCIEOM, pp. 443-456, (2020); Tsolakis NSchumacher R., Dora M., Kumar M., Artificial intelligence and blockchain implementation in supply chains: A pathway to sustainability and data monetisation?, Ann. Oper. Res, 327, pp. 157-210, (2023); Belhadi A., Mani V., Kamble S., Khan S., Verma S., Artificial intelligence-driven innovation for enhancing supply chain resilience and performance under the effect of supply chain dynamism: An empirical investigation, Ann. Oper. 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Prod, 138, pp. 8-18, (2016); Borrello M., Caracciolo F., Lombardi A., Pascucci S., Cembalo L., Consumers’ perspective on circular economy strategy for reducing food waste, Sustainability, 9, (2017); Kalogirou E., Waste-to-Energy Technologies and Global Applications, (2017); World Population Prospects 2022: Summary of Results, Department of Economic and Social Affairs, (2022); Heyes G., Sharmina M., Mendoza J., Developing and implementing circular economy business models in service-oriented technology companies, J. Clean. Prod, 177, pp. 621-632, (2018); Bag S., Wood L., Mangla S., Luthra S., Procurement 4.0 and its implications on business process performance in a circular economy, Resour. Conserv. Recycl, 152, (2020); Retail: From the Report, Nigeria 2022; Okere J., Ofodum C., Azorji J., Nwosu O., Waste-to-energy: A circular economy tool towards climate change mitigation in Imo State, South-Eastern, Nigeria, Asian J. Adv. Res. Rep, 7, pp. 1-17, (2019); Oyelola O., Ajiboshin I., Okewole J., Effective waste management in the circular economy: The case study of Lagos State, Nigeria, Procedia Environ. Sci. Eng. Manag, 4, pp. 143-148, (2017); Wollenburg J., Holzapfel A., Hubner A., Omni-channel customer management processes in retail: An exploratory study on fulfillment-related options, Logist. Res, 12, (2019); Ledford J., Barton E., Severini K., Zimmerman K., A primer on single-case research designs: Contemporary use and analysis, Am. J. Intellect. Dev. Disabil, 124, pp. 35-56, (2019); Mishra J., Hopkinson P., Tidridge G., Value creation from circular economy-led closed loop supply chains: A case study of fast-moving consumer goods, Prod. Plan. Control, 29, pp. 509-521, (2018); Saxena R., Muddling through the passage of qualitative research: Experiences of a novice researcher, Vision, 21, pp. 314-322, (2017); Olaghere J.A., Impacts of tourism on residents: An analysis of the integrated threat theory, Int. J. Tour. Hosp. Res, 34, pp. 89-103, (2022); Barratt M., Choi T., Li M., Qualitative case studies in operations management: Trends, research outcomes, and future research implications, J. Oper. Manag, 29, pp. 329-342, (2011); Reynolds T., Gutman J., Laddering theory, method, analysis, and interpretation, J. Advert. Res, 28, pp. 11-31, (1988); Spradley J., Participant Observation, (1980); Attride-Stirling J., Thematic networks: An analytic tool for qualitative research, Qual. Res, 1, pp. 385-405, (2001); Braun V., Clarke V., Using thematic analysis in psychology, Qual. Res. Psychol, 3, pp. 77-101, (2006); Nwokoro I., Onukwube H., Understanding green and sustainable construction in Lagos, Nigeria: Principles, attributes and framework, Ethiop. J. Environ. Stud. Manag, 8, pp. 57-68, (2015)","J.A. Olaghere; School of Economics and Management, Hunan Institute of Science and Technology, Yueyang, 414006, China; email: john.olaghere@hnist.edu.cn",null,"Multidisciplinary Digital Publishing Institute (MDPI)",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85170361814"]
["Sun X.","Sun, Xiujing (58759723600)",5.87597236E10,"Framework for service quality evaluation of international logistics enterprises from the perspective of cross-border e-commerce supply chain under spherical fuzzy sets",2023.0,"Journal of Intelligent and Fuzzy Systems",45.0,6.0,null,11835.0,11851.0,16.0,0.0,"10.3233/JIFS-233384","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85179586010&doi=10.3233%2fJIFS-233384&partnerID=40&md5=499fbc97d925652a132678cb0c226581","International Business School, Jilin International Studies University, Jilin, Changchun, China","Sun X., International Business School, Jilin International Studies University, Jilin, Changchun, China","With the rapid development and application of internet technology, cross-border e-commerce (CBEC) has begun to popularize globally and play an important role in China's foreign trade. The Chinese government has successively introduced multiple policies and regulations to strongly support its rapid development. Compared to the booming trend of CBEC, the development of its supply chain is slightly lacking in momentum, which has formed a certain obstacle to the overall development of CBEC. The supply chain is the foundation of successful CBEC transactions, and the foundation of the supply chain is logistics. The primary task to improve the backwardness of supply chain development is to solve logistics problems. Therefore, while enjoying the dividends brought by the rapid development of CBEC, international logistics enterprises should continuously improve their logistics service capabilities, effectively evaluate their service quality, and then identify problems based on the evaluation results, analyze and improve them. The service quality evaluation of international logistics enterprises from the perspective of CBEC supply chain is a classical multiple attribute group decision making (MAGDM). The Spherical fuzzy sets (SFSs) provide more free space for DMs to portray uncertain information during the service quality evaluation of international logistics enterprises from the perspective of CBEC supply chain. Therefore, this paper expands the partitioned Maclaurin symmetric mean (PPMSM) operator and IOWA operator to SFSs based on the power average (PA) technique and construct induced spherical fuzzy weighted power partitioned MSM (I-SFWPPMSM) technique. Subsequently, a novel MAGDM method is constructed based on I-SFWPPMSM technique and SFNWG technique under SFSs. Finally, a numerical example for service quality evaluation of international logistics enterprises from the perspective of CBEC supply chain is employed to verify the constructed method, and comparative analysis with some existing techniques to testy the validity and superiority of the I-SFWPPMSM technique.  © 2023 - IOS Press. All rights reserved.","I-SFWPPMSM operator; MAGDM; Service quality evaluation; Spherical fuzzy sets (SFSs)","Decision making; Electronic commerce; International trade; Numerical methods; Quality control; Spheres; Supply chains; Cross-border; Development and applications; E- commerces; Induced spherical fuzzy weighted power partitioned MSM operator; Internet technology; Logistics enterprise; Multiple-attribute group decision makings; Service quality evaluation; Spherical fuzzy set; Weighted power; Fuzzy sets",{"$nulls":4},"JiLin Association for Higher Education, (JGJX2022D329)","This work was supported by JiLin Association for Higher Education, research on Study on Blended Teaching Model in the Digital Era - An Example of Cross-border E-Commerce Course(Project No. JGJX2022D329).",{"$cut":{"chars":17630,"head":"Li S., Assessment of service quality of logistics center in chain stores based on fuzzy logic and TOPSIS, 4th International Conference on Electronic Business (ICEB 2004), pp. 34-37, (2004); He S.G., Chen L.W., Qi E.S., A study on the evaluation and controlling of service quality for 3(rd) party logistics, 4th Wuhan International Conference on E-Business - Global Business Interface, pp. 1117-1122, (2005); Zheng B., Dong D.H., A study of the Effect of Logistics Service Quality on Customer Satisfaction, 12th International Conference on Industrial Engineering and Engineering Management, pp. 383-386, (2005); Dovbischuk I., Sustainability in Logistics Service Quality: Evidence from Agri-Food Supply Chain in Ukraine, Sustainability, 15, 2023; Liu C., Lv J.Y., Hou P., Lu D.R., Disclosing products’ freshness level as a non-contractible quality: Optimal logistics service contracts in the fresh products supply chain, European Journal of Operational Research, 307, 2023, pp. 1085-1102; Ta H., Esper T.L., Hofer A.R.R., Sodero A., Crowd-sourced delivery and customer assessments of e-Logistics Service Quality: An appraisal theory perspective, Journal of Business Logistics, 44, 3, pp. 345-368, (2023); Dabees A., Barakat M., Elbarky S.S., Lisec A., A Framework for Adopting a Sustainable Reverse Logistics Service Quality for Reverse Logistics Service Providers: A Systematic Literature Review, Sustainability, 15, 2023; Do Q.H., Kim T.Y., Wang X., Effects of logistics service quality and price fairness on customer repurchase intention: The moderating role of cross-border e-commerce experiences, Journal of Retailing and Consumer Services, 70, 2023; Yang S.F., Construction of Rural E-Commerce Logistics Service Quality Evaluation System and IoT Applications under the Background of New Retail, Wireless Communications & Mobile Computing, 2022, 2022; Zhang Y., Chen X., Gao L., Dong Y., Pedryczc W., Consensus reaching with trust evolution in social network group decision making, Expert Systems with Applications, 188, (2022); Zheng B., Wang H., Golmohammadi A.M., Goli A., Impacts of logistics service quality and energy service of Business to Consumer (B2C) online retailing on customer loyalty in a circular economy, Sustainable Energy Technologies and Assessments, 52, 2022; Oh K.Y., Kang S.Y., Oh Y.G., The Moderating Effects of Eco-Friendliness between Logistics Service Quality and Customer Satisfaction in Cross-Border e-Commerce: Evidence from Overseas Direct Purchasers in Korea, Sustainability, 14, 2022; Singh S.P., Adhikari A., Majumdar A., Bisi A., Does service quality influence operational and financial performance of third party logistics service providers? A mixed multi criteria decision making -text mining-based investigation, Transportation Research Part E-Logistics and Transportation Review, 157, 2022; Wu P.J., Lin L.T., Huang C.C., Diagnosing the service quality of perishable-food logistics: temperature-sensitive milk delivery, Asia Pacific Journal of Marketing and Logistics, 34, 2022, pp. 1943-1955; Hu K.C., Chia K.C., Lu M.Y., Liang Y.L., Using importance-performance analysis, goal difficulty and the Kano model to prioritize improvements in the quality of home delivery logistics services, International Journal of Logistics Management, 33, 2022, pp. 477-498; Ma M., Shen L., Sun X.Q., Optimization of e-commerce logistics service quality considering multiple consumption psychologies, Frontiers in Psychology, 13, 2022; Michalski M., Montes-Botella J.L., Logistics service quality in an emergent market in Latin America, International Journal of Logistics Management, 33, 2022, pp. 79-101; Jain N.K., Gajjar H., Shah B.J., Electronic logistics service quality and repurchase intention in e-tailing: Catalytic role of shopping satisfaction, payment options, gender and returning experience, Journal of Retailing and Consumer Services, 59, 2021; Ju Y.J., Hou H.P., Yang J.L., Integration quality, value co-creation and resilience in logistics service supply chains: moderating role of digital technology, Industrial Management & Data Systems, 121, 2021, pp"}},"X. Sun; International Business School, Jilin International Studies University, Changchun, Jilin, 130117, China; email: sunlaoshi1981@163.com",null,"IOS Press BV",{"$nulls":5},1.0641246E7,null,null,null,"English","J. Intelligent Fuzzy Syst.","Article","Final",null,"Scopus","2-s2.0-85179586010"]
["Špicas R.; Neifaltas A.; Kanapickienė R.; Keliuotytė-Staniulėnienė G.; Vasiliauskaitė D.","Špicas, Renatas (57201875658); Neifaltas, Airidas (57941353600); Kanapickienė, Rasa (23389476000); Keliuotytė-Staniulėnienė, Greta (56447045900); Vasiliauskaitė, Deimantė (58198890400)","57201875658; 57941353600; 23389476000; 56447045900; 58198890400","Estimating the Acceptance Probabilities of Consumer Loan Offers in an Online Loan Comparison and Brokerage Platform",2023.0,"Risks",11.0,7.0,138.0,null,null,null,0.0,"10.3390/risks11070138","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85166426922&doi=10.3390%2frisks11070138&partnerID=40&md5=9f97dfb63bf5f6eb05fad2866e86b460","Department of Finance, Faculty of Economics and Business Administration, Vilnius University, Vilnius, 10222, Lithuania","Špicas R., Department of Finance, Faculty of Economics and Business Administration, Vilnius University, Vilnius, 10222, Lithuania; Neifaltas A., Department of Finance, Faculty of Economics and Business Administration, Vilnius University, Vilnius, 10222, Lithuania; Kanapickienė R., Department of Finance, Faculty of Economics and Business Administration, Vilnius University, Vilnius, 10222, Lithuania; Keliuotytė-Staniulėnienė G., Department of Finance, Faculty of Economics and Business Administration, Vilnius University, Vilnius, 10222, Lithuania; Vasiliauskaitė D., Department of Finance, Faculty of Economics and Business Administration, Vilnius University, Vilnius, 10222, Lithuania","It is widely recognised that the ability of e-commerce businesses to predict conversion probability, i.e., acceptance probability, is critically important in today’s business environment. While the issue of conversion prediction based on browsing data in various e-commerce websites is broadly analysed in scientific literature, there is a lack of studies covering this topic in the context of online loan comparison and brokerage (OLCB) platforms. It can be argued that due to the inseparable relationship between the operation of these platforms and credit risk, the behaviour of consumers in making loan decisions differs from typical consumer behaviour in choosing non-risk-related products. In this paper, we aim to develop and propose statistical acceptance prediction models of loan offers in OLCB platforms. For modelling, we use diverse data obtained from an operating OLCB platform, including on customer (i.e., borrower) behaviour and demographics, financial variables, and characteristics of the loan offers presented to the borrowers/customers. To build the models, we experiment with various classifiers including logistic regression, random forest, XGboost, artificial neural networks, and support vector machines. Computational experiments show that our models can predict conversion with good performance in terms of area under the curve (AUC) score. The models presented are suitable for use in a loan comparison and brokerage platform for real-time process optimisation purposes. © 2023 by the authors.","binary models; conversion prediction; digital loan brokerage; machine learning",{"$nulls":5},"LMTLT; Lietuvos Mokslo Taryba; European Regional Development Fund, ERDF, (13.1.1-LMT-K-718-05-0010)","This research has received funding from the European Regional Development Fund (project No 13.1.1-LMT-K-718-05-0010) under grant agreement with the Research Council of Lithuania (LMTLT). The project was funded as the European Union’s measure in response to the COVID-19 pandemic.",{"$cut":{"chars":20399,"head":"Agarwal S., Bos M., Rationality in the consumer credit market, Handbook of US Consumer Economics, pp. 121-139, (2019); Agarwal S., Chomsisengphet S., Liu C., Souleles N.S., Do consumers choose the right credit contracts?, The Review of Corporate Finance Studies, 4, pp. 239-257, (2015); Akimoto T., Takeda F., Price movements in the Japanese online home electronics market, Electronic Commerce Research and Applications, 8, pp. 28-36, (2009); Alam A., Anjum A.A., Tasin F.S., Reyad M.R., Sinthee S.A., Hossain N., Upoma: A Dynamic Online Price Comparison Tool for Bangladeshi E-commerce Websites, Paper presented at the 2020 IEEE Region 10 Symposium (TENSYMP), pp. 194-197, (2020); Alfawzan M., Alturki R., Personal Loans Comparison Websites in Saudi Arabia: Challenges and Proposed Solution, Paper presented at the 2018 21st Saudi Computer Society National Computer Conference (NCC), pp. 1-8, (2018); Ambre A., Gaikwad P., Pawar K., Patil V., Web and Android Application for Comparison of E-Commerce Products, International Journal of Advanced Engineering, Management and Science (IJAEMS), 5, pp. 266-268, (2017); Antal M., A “parasite market”: A competitive market of energy price comparison websites reduces consumer welfare, Energy Policy, 138, (2020); Banerjee S., Gollapudi S., Kollias K., Munagala K., Segmenting two-sided markets, Paper presented at the 26th International Conference on World Wide Web, pp. 63-72, (2017); Baye M.R., Morgan J., Scholten P., Price dispersion in the small and in the large: Evidence from an internet price comparison site, The Journal of Industrial Economics, 52, pp. 463-496, (2004); Bigon L., Cassani G., Greco C., Lacasa L., Pavoni M., Polonioli A., Tagliabue J., Prediction is very hard, especially about conversion. Predicting user purchases from clickstream data in fashion e-commerce, arXiv, (2019); Bishop C.M., Neural Networks for Pattern Recognition, (1995); Bodur H.O., Klein N.M., Arora N., Online price search: Impact of price comparison sites on offline price evaluations, Journal of Retailing, 91, pp. 125-139, (2015); Boheim R., Hackl F., Holzl-Leitner M., The impact of price adjustment costs on price dispersion in e-commerce, International Journal of Industrial Organization, 77, (2021); Breiman L., Random forests, Machine Learning, 45, pp. 5-32, (2001); Broeckelmann P., Groeppel-Klein A., Usage of mobile price comparison sites at the point of sale and its influence on consumers’ shopping behaviour, The International Review of Retail, Distribution and Consumer Research, 18, pp. 149-166, (2008); Broniarczyk S.M., Griffin J.G., Decision difficulty in the age of consumer empowerment, Journal of Consumer Psychology, 24, pp. 608-625, (2014); Brown J.R., Goolsbee A., Does the Internet make markets more competitive? Evidence from the life insurance industry, Journal of Political Economy, 110, pp. 481-507, (2002); Cai Z., Zhen Y., He M., Chen L., Sun L., Zhou T., Du Y., Browsing Behavioral Intent Prediction on Product Recommendation Pages of E-commerce Platform, Paper presented at the Artificial Intelligence: Second CAAI International Conference, CICAI 2022, pp. 33-45, (2023); Chatterjee P., Wang Y., Online comparison shopping behavior of travel consumers, Journal of Quality Assurance in Hospitality & Tourism, 13, pp. 1-23, (2012); Chawla N.V., Bower K.W., Hall L.O., Kegelmeyer W.P., SMOTE: Synthetic Minority Over-sampling Technique, Journal of Artificial Intelligence Research, 16, pp. 321-357, (2002); Chen T., Guestrin C., Xgboost: A scalable tree boosting system, Paper presented at the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 785-794, (2016); Chevalier J., Goolsbee A., Measuring prices and price competition online: Amazon. com and BarnesandNoble. com, Quantitative marketing and Economics, 1, pp. 203-222, (2003); Choe L., How many ‘clicks’ does it take?: Finding price information on New Zealand lawyers’ websites, Victoria University of Wellington Law Review, 52, pp. 487-505, (2021); Chung S., The role of online informediaries for consumers: A dual perspective about "}},"R. Špicas; Department of Finance, Faculty of Economics and Business Administration, Vilnius University, Vilnius, 10222, Lithuania; email: renatas.spicas@evaf.vu.lt",null,"Multidisciplinary Digital Publishing Institute (MDPI)",{"$nulls":5},2.2279091E7,null,null,null,"English","Risks","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85166426922"]
["Yin Y.; Li D.; Wang D.; Ignatius J.; Cheng T.C.E.; Wang S.","Yin, Yunqiang (18439000200); Li, Dongwei (58141738300); Wang, Dujuan (56103089300); Ignatius, Joshua (8346805200); Cheng, T.C.E. (13302593800); Wang, Sutong (57212384593)","18439000200; 58141738300; 56103089300; 8346805200; 13302593800; 57212384593","A branch-and-price-and-cut algorithm for the truck-based drone delivery routing problem with time windows",2023.0,"European Journal of Operational Research",309.0,3.0,null,1125.0,1144.0,19.0,10.0,"10.1016/j.ejor.2023.02.030","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85150026446&doi=10.1016%2fj.ejor.2023.02.030&partnerID=40&md5=b9309d023153002c0a3180b9393a36c3","School of Management and Economics, University of Electronic Science and Technology of China, Chengdu, 611731, China; Business School, Sichuan University, Chengdu, 610064, China; Aston Business School, Aston University, Birmingham, B47ET, United Kingdom; Department of Logistics and Maritime Studies, The Hong Kong Polytechnic University, Kowloon, Hong Kong; School of Management Science and Engineering, Dalian University of Technology, Dalian, 116000, China","Yin Y., School of Management and Economics, University of Electronic Science and Technology of China, Chengdu, 611731, China; Li D., School of Management and Economics, University of Electronic Science and Technology of China, Chengdu, 611731, China; Wang D., Business School, Sichuan University, Chengdu, 610064, China; Ignatius J., Aston Business School, Aston University, Birmingham, B47ET, United Kingdom; Cheng T.C.E., Department of Logistics and Maritime Studies, The Hong Kong Polytechnic University, Kowloon, Hong Kong; Wang S., School of Management Science and Engineering, Dalian University of Technology, Dalian, 116000, China","Increasing e-commerce activities poses a tough challenge for logistics distribution. With the development of new technology, firms attempt to leverage drones for parcel delivery to improve delivery efficiency and reduce overall costs. We consider the truck-based drone delivery routing problem with time windows. In our setting, a set of trucks and drones (each truck is associated with a drone) collaborate to serve customers, where a drone can take off from its associated truck at a node, independently serve one or more customers within the time windows, and return to the truck at another node along the truck route. To solve the problem, we develop an enhanced branch-and-price-and-cut algorithm incorporating a bounded bidirectional labelling algorithm to solve the challenging pricing problem. To improve the algorithm, we use the subset-row inequalities to tighten the lower bound and apply enhancement strategies, which solve the pricing problem efficiency. We perform extensive numerical studies to evaluate the performance of the developed algorithm, assess the gain of the truck-based drone delivery over the truck-only delivery, and provide some managerial insights. © 2023 Elsevier B.V.","Column generation; Delivery; Logistics; Valid inequalities; Vehicle routing","Automobiles; Costs; Drones; Integer programming; Linear programming; Routing algorithms; Trucks; Vehicle routing; Branch-and-price-and-cut; Column generation; Delivery; E- commerces; Logistic distributions; Parcel delivery; Pricing problems; Routing problems; Time windows; Valid inequality; Efficiency",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (71871148, 71971041, 72171161); Sichuan University, SCU, (SKSYL2021-08); National Office for Philosophy and Social Sciences, NPOPSS, (ZD084); Shanxi Provincial Key Research and Development Project; Chengdu Office of Philosophy and Social Science, (2022C19); Key Research and Development Program of Sichuan Province, (2023YFS0397); special key project of Chengdu Philosophy and social science planning, (2022E04)","Funding text 1: This paper was supported in part by the National Natural Science Foundation of China under grant numbers 71971041, 72171161, and 71871148; by the Major Program of National Social Science Foundation of China under Grant 20&ZD084; by the special key project of Chengdu Philosophy and social science planning “Young Eagle Plan” for “Study and Interpret the Party's Twenty Great Spirits” (2022E04); by the Key Research and Development Project of Sichuan Province (No. 2023YFS0397); by the Chengdu Philosophy and Social Science Planning Project (No. 2022C19); and by the Sichuan University to Building a World-class University (No. SKSYL2021-08).; Funding text 2: This paper was supported in part by the National Natural Science Foundation of China under grant numbers 71971041 , 72171161 , and 71871148 ; by the Major Program of National Social Science Foundation of China under Grant 20&ZD084; by the special key project of Chengdu Philosophy and social science planning “Young Eagle Plan” for “Study and Interpret the Party's Twenty Great Spirits” (2022E04); by the Key Research and Development Project of Sichuan Province (No. 2023YFS0397); by the Chengdu Philosophy and Social Science Planning Project (No. 2022C19); and by the Sichuan University to Building a World-class University (No. SKSYL2021-08).","Agatz N., Bouman P., Schmidt M., Optimization approaches for the traveling salesman problem with drone, Transportation Science, 52, 4, pp. 965-981, (2018); Baldacci R., Mingozzi A., Roberti R., New route relaxation and pricing strategies for the vehicle routing problem, Operations Research, 59, 5, pp. 1269-1283, (2011); Bishop T., (2015); Boysen N., Briskorn D., Fedtke S., Schwerdfeger S., Drone delivery from trucks: Drone scheduling for given truck routes, Networks, 72, 4, pp. 506-527, (2018); Dayarian I., Crainic T.G., Gendreau M., Rei W., A branch-and-price approach for a multi-period vehicle routing problem, Computers and Operations Research, 55, pp. 167-184, (2015); Dayarian I., Savelsbergh M., Clarke J.P., Same-day delivery with drone resupply, Transportation Science, 54, 1, pp. 229-249, (2020); 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Kloster K., Moeini M., Vigo D., Wendt O., The multiple traveling salesman problem in presence of drone-and robot-supported packet stations, European Journal of Operational Research, 305, 2, pp. 630-643, (2023); Kuo R.J., Lu S.H., Lai P.Y., Mara S.T.W., Vehicle routing problem with drones considering time windows, Expert Systems with Applications, 191, (2022); Landi H., (2022); Luo Z., Poon M., Zhang Z., Liu Z., Lim A., The multi-visit traveling salesman problem with multi-drones, Transportation Research Part C: Emerging Technologies, 128, (2021); Macrina G., Pugliese L.D.P., Guerriero F., Laporte G., Drone-aided routing: A literature review, Transportation Research Part C: Emerging Technologies, 120, (2020); (2021); Minemyer P.C., (2019); Murray C.C., Chu A.G., The flying sidekick traveling salesman problem: Optimization of drone-assisted parcel delivery, Transportation Research Part C: Emerging Technologies, 54, pp. 86-109, (2015); Pierce D., (2013); Righini G., Salani M., Symmetry helps: Bounded bi-directional dynamic programming for the elementary shortest path problem with resource constraints, Discrete Optimization, 3, 3, pp. 255-273, (2006); Roberti R., Mingozzi A., Dynamic ng-path relaxation for the delivery man problem, Transportation Science, 48, 3, pp. 413-424, (2014); Roberti R., Ruthmair M., Exact methods for the traveling salesman problem with drone, Transportation Science, 55, 2, pp. 315-335, (2021); Sacramento D., Pisinger D., Ropke S., An adaptive large neighborhood search metaheuristic for the vehicle routing problem with drones, Transportation Research Part C: Emerging Technologies, 102, pp. 289-315, (2019); Sanchez A., (2017); Solomon M.M., Algorithms for the vehicle routing and scheduling problems with time window constraints, Operations Research, 35, 2, pp. 254-265, (1987); Tamke F., Buscher U., A branch-and-cut algorithm for the vehicle routing problem with drones, Transportation Research Part B: Methodological, 144, pp. 174-203, (2021); Thiago T., (2019); Wang K., Yuan B., Zhao M., Lu Y., Cooperative route planning for the drone and truck in delivery services: A bi-objective optimisation approach, Journal of the Operational Research Society, 71, 10, pp. 1657-1674, (2020); Wang Z., Sheu J.B., Vehicle routing problem with drones, Transportation Research Part B: Methodological, 122, pp. 350-364, (2019); Wohlsen M., (2014); Yurek E.E., Ozmutlu H.C., A decomposition-based iterative optimization algorithm for traveling salesman problem with drone, Transportation Research Part C: Emerging Technologies, 91, pp. 249-262, (2018)","D. Wang; Business School, Sichuan University, Chengdu, 610064, China; email: djwang@scu.edu.cn",null,"Elsevier B.V.",{"$nulls":5},3772217.0,null,"EJORD",null,"English","Eur J Oper Res","Article","Final",null,"Scopus","2-s2.0-85150026446"]
["Yusoff F.A.M.; Mohamad F.; Tamyez P.F.M.; Panatik S.A.","Yusoff, Fara Adura Mohd (57202996304); Mohamad, Fazeeda (57210422892); Tamyez, Puteri Fadzline Muhamad (23989758600); Panatik, Siti Aisyah (56100479800)","57202996304; 57210422892; 23989758600; 56100479800","Do I need to use it? Factors influencing the intention to adopt automated parcel lockers as last-mile delivery services",2023.0,"Acta Logistica",10.0,4.0,null,567.0,575.0,8.0,0.0,"10.22306/al.v10i4.435","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85180851384&doi=10.22306%2fal.v10i4.435&partnerID=40&md5=59ef790ef6339c8734a9fa2665530969","Faculty of Industrial Management, Universiti Malaysia Pahang Al-Sultan Abdullah, Lebuh Persiaran Tun Khalil Yaakob, Pahang, Kuantan, 26300, Malaysia; Commerce Department, Politeknik Sultan Haji Ahmad Shah, Pahang, Kuantan, 25350, Malaysia; Faculty of Social Science and Humanities, Universiti Teknologi Malaysia, Johor, Skudai, 81310, Malaysia","Yusoff F.A.M., Faculty of Industrial Management, Universiti Malaysia Pahang Al-Sultan Abdullah, Lebuh Persiaran Tun Khalil Yaakob, Pahang, Kuantan, 26300, Malaysia, Commerce Department, Politeknik Sultan Haji Ahmad Shah, Pahang, Kuantan, 25350, Malaysia; Mohamad F., Faculty of Industrial Management, Universiti Malaysia Pahang Al-Sultan Abdullah, Lebuh Persiaran Tun Khalil Yaakob, Pahang, Kuantan, 26300, Malaysia; Tamyez P.F.M., Faculty of Industrial Management, Universiti Malaysia Pahang Al-Sultan Abdullah, Lebuh Persiaran Tun Khalil Yaakob, Pahang, Kuantan, 26300, Malaysia; Panatik S.A., Faculty of Social Science and Humanities, Universiti Teknologi Malaysia, Johor, Skudai, 81310, Malaysia","Researchers have been intrigued by parcel lockers for last-mile delivery services, prompting them to investigate the matter more. This study examines factors affecting consumers’ intention to use parcel lockers through the Unified Theory of Acceptance and the Use of Technology (UTAUT). This study proposed the mediating role of performance expectancy in the relationship between social influence and effort expectancy with the intention of adopting parcel locker services. An online structured questionnaire was employed and managed to collect data from 444 respondents. The non-probability purposive sampling technique was chosen as the sampling technique, while the SmartPLS version 4.0 analysed research data. The data found that performance expectancy and compatibility over consumers' intention strongly exerted the intention to use parcel lockers. For the mediator factor, the analysis uncovered evidence that performance expectancy can effectively mediate the relationship between social influence, effort expectancy, and intention to adopt parcel lockers. The research demonstrated the significance of the UTAUT model in pinpointing the reason for the parcel locker's adoption intention in Malaysia. The research findings could provide meaningful information to logistics businesses, courier companies, and relevant government bodies to design and implement strategies to enhance the acceptance and usage of parcel lockers as the last delivery option compared to home delivery. © Acta Logistica.","e-commerce; intention; last-mile delivery; parcel locker; UTAUT",{"$nulls":5},"Universiti Malaysia Pahang Al-Sultan Abdullah, (RDU220389)","The authors would like to thank Universiti Malaysia Pahang Al-Sultan Abdullah for the financial support under Internal Research Grant RDU220389.","CHEVALIER S., Global retail e-commerce sales 2014-2025, (2022); IANNACCONE G., MARCUCCI E., GATTA V., What Young E-Consumers Want? Forecasting Parcel Lockers Choice in Rome, Logistics, 5, 3, pp. 1-16, (2021); YUEN K.F., WANG X., MA F., WONG Y.D., The determinants of customers’ intention to use smart lockers for last-mile deliveries, Journal of Retailing and Consumer Services, 49, pp. 316-326, (2019); PARCELMONITOR: The State of E-Commerce In Malaysia, (2020); LEE H.J., LYU J., Personal values as determinants of intentions to use self-service technology in retailing, Computers in Human Behavior, 60, pp. 322-332, (2016); WANG X., YUEN K.F., WONG Y.D., TEO C.C., It is green, but is it fair? Investigating consumers’ fairness perception of green service offerings, Journal of Cleaner Production, 181, pp. 235-248, (2018); VAKULENKO Y., SHAMS P., HELLSTROM D., HJORT K., Service innovation in e-commerce last mile delivery: Mapping the e-customer journey, Journal of Business Research, 101, pp. 461-468, (2019); MOHAMAD F.H., NGAH A.H., The role of openness to change in automated parcel locker usage among online buyers in Malaysia, International Scientific Journal about Logistics, 9, pp. 1001-1012, (2022); KHAN R.A., QUDRAT-ULLAH H., Adoption of LMS in Higher Educational Institutions of the Middle East, (2021); ALSHAHER A., IT capabilities as a fundamental of electronic government system success in developing countries from users perspectives, Transforming Government: People, Process and Policy, 15, 1, pp. 129-149, (2021); RAHI S., GHANI M., Investigating the role of UTAUT and e-service quality in internet banking adoption setting, TQM Journal, 31, 3, pp. 491-506, (2019); KAPSER S., ABDELRAHMAN M., BERNECKER T., Autonomous delivery vehicles to fight the spread of Covid-19 – How do men and women differ in their acceptance?, Transportation Research Part A: Policy and Practice, 148, pp. 183-198, (2021); ZHOU M., ZHAO L., KONG N., CAMPY K.S., XU G., ZHU G., CAO X., WANG S., Understanding consumers’ behavior to adopt self-service parcel services for last-mile delivery, Journal of Retailing and Consumer Services, 52, pp. 1-12, (2020); WUT E., NG P., LEUNG K.S.W., LEE D., Do gamified elements affect young people’s use behaviour on consumption-related mobile applications?, Young Consumers, 22, 3, pp. 368-386, (2021); ELPRAMA S.A., VANNIEUWENHUYZE J.T.A., DE BOCK S., VANDERBORGHT B., DE PAUW K., MEEUSEN R., JACOBS A., Processes: What Determines Industrial Workers’ Intention to Use Exoskeletons?, Human Factors, 62, 3, pp. 337-350, (2020); SABBIR M.M., ISLAM M., DAS S., Understanding the determinants of online pharmacy adoption: a two-staged SEM-neural network analysis approach, Journal of Science and Technology Policy Management, 12, 4, pp. 666-687; KAPSER S., ABDELRAHMAN M., Acceptance of autonomous delivery vehicles for last-mile delivery in Germany – Extending UTAUT2 with risk perceptions, Transportation Research Part C, 111, pp. 210-225, (2020); ZHONG S., LOMAS C., WORTH T., Understanding customers’ adoption of express delivery service for last-mile delivery in the UK, International Journal of Logistics Research and Applications, 25, 12, pp. 1-18, (2021); BOUTERAA M., RAJA HISHAM R.R.I., ZAINOL Z., Challenges affecting bank consumers’ intention to adopt green banking technology in the UAE: A UTAUT-based mixed-methods approach, Journal of Islamic Marketing, (2022); ERJAVEC J., MANFREDA A., Online shopping adoption during COVID-19 and social isolation: Extending the UTAUT model with herd behavior, Journal of Retailing and Consumer Services, 65, pp. 1-12, (2022); YANG M., AL MAMUN A., MOHIUDDIN M., NAWI N.C., ZAINOL N.R, Cashless transactions: A study on intention and adoption of e-wallets, Sustainability, 13, 2, pp. 1-18, (2021); CHAWLA D., JOSHI H., Consumer attitude and intention to adopt mobile wallet in India – An empirical study, International Journal of Bank Marketing, 37, 7, pp. 1590-1618, (2019); DUAN S.X., DENG H., Hybrid analysis for understanding contact tracing apps adoption, Industrial Management and Data Systems, 121, 7, pp. 1599-1616, (2021); RAHI S., OTHMAN MANSOUR M.M., ALGHIZZAWI M., ALNASER F.M., Integration of UTAUT model in internet banking adoption context: The mediating role of performance expectancy and effort expectancy, Journal of Research in Interactive Marketing, 13, 3, pp. 411-435, (2019); RAMIREZ-CORREA P.E., GRANDON E.E., ARENAS-GAITAN J., RONDAN-CATALUNA F.J., ARAVENA A., Explaining Performance Expectancy of IoT in Chilean SMEs, Lecture Notes in Business Information Processing, 353, pp. 475-486, (2019); HAIR J.F., HULT G.T.M., RINGLE C.M., SARSTEDT M., A primer on partial least squares structural equation modelling (PLS-SEM), (2017); ROSCOE J.T., Fundamental research statistics for the behavioral sciences, (1975); VENKATESH V., MORRIS M.G., DAVIS G.B., DAVIS F.D., Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology, Management Information Systems Research Center, 27, 3, pp. 425-478, (2003); WANG X., YUEN K.F., WONG Y.D., TEO C.C., Consumer participation in last-mile logistics service: an investigation on cognitions and affects, International Journal of Physical Distribution and Logistics Management, 49, 2, pp. 217-238, (2019); VENKATESH V.LJ.Y., XU X., Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology, Management Information Systems Research Center, 36, 1, pp. 157-178, (2012); ANDERSON J.C., GERBING D.W., Structural equation modeling in practice: a review and recommended two-step approach, Phychological Bulletin, 103, 3, pp. 411-423, (1988); KOCK N., LYNN G.S., Lateral collinearity and misleading results in variance-based SEM: An illustration and recommendations, Journal of the Association for Information Systems, 13, 7, pp. 546-580, (2012); HAIR J.F., BLACK W.C., BLACK B., BABIN B.J., ANDERSON R.E., Multivariate data analysis, (2010); FRANKE G., SARSTEDT M., Heuristics versus statistics in discriminant validity testing: a comparison of four procedures, Internet Research, 29, 3, pp. 430-447, (2019); HAIR J., HOLLINGSWORTH C.L., RANDOLPH A.B., CHONG A.Y.L., An updated and expanded assessment of PLS-SEM in information systems research, Industrial Management & Data Systems, 117, 3, pp. 442-458, (2017); PREACHER K.J., HAYES A.F., Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models, Behavior Research Methods, 40, 3, pp. 879-891, (2008); SHMUELI G., SARSTEDT M., HAIR J.F., CHEAH J.H., TING H., VAITHILINGAM S., RINGLE C.M., Predictive model assessment in PLS-SEM: guidelines for using PLSpredict, European Journal of Marketing, 53, 11, pp. 2322-2347, (2019); MAKANYEZA C., Determinants of consumers’ intention to adopt mobile banking services in Zimbabwe, International Journal of Bank Marketing, 12, 7, pp. 1-32, (2017); SHARMA S., SINGH G., PRATT S., NARAYAN J., Exploring consumer behavior to purchase travel online in Fiji and Solomon Islands? An extension of the UTAUT framework, International Journal of Culture, Tourism, and Hospitality Research, 15, 2, pp. 227-247, (2021); ACHARJYA B., DAS S., Adoption of E-learning during the covid-19 pandemic: The moderating role of age and gender, International Journal of Web-Based Learning and Teaching Technologies, 17, 2, pp. 1-14, (2022); NIKOLOPOULOU K., GIALAMAS V., LAVIDAS K., Acceptance of mobile phone by university students for their studies: an investigation applying UTAUT2 model, Education and Information Technologies, 25, pp. 4139-4155, (2020); POPOVA Y., ZAGULOVA D., UTAUT Model for Smart City Concept Implementation: Use of Web Applications by Residents for Everyday Operation, Informatics, 9, 1, pp. 1-19","F. Mohamad; Faculty of Industrial Management, Universiti Malaysia Pahang Al-Sultan Abdullah, Kuantan, Lebuh Persiaran Tun Khalil Yaakob, Pahang, 26300, Malaysia; email: fazeedamohamad@umpsa.edu.my",null,"4S go, s.r.o",{"$nulls":5},1.3395629E7,null,null,null,"English","Acta Logistica","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85180851384"]
["Kaur B.; Rani S.","Kaur, Babaljeet (57212491447); Rani, Shalli (56024601000)","57212491447; 56024601000","Are the Customers Receiving Exact Recommendations from the E-Commerce Companies? Towards the Identification of Gray Sheep Users Using Personality Parameters",2023.0,"International Journal of Performability Engineering",19.0,7.0,null,425.0,433.0,8.0,0.0,"10.23940/ijpe.23.07.p1.425433","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174350387&doi=10.23940%2fijpe.23.07.p1.425433&partnerID=40&md5=7c9c6a94f99f0082596a695ee5489116","Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India","Kaur B., Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India; Rani S., Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India","In the real-world, use of digital media is increasing day by day. Consumers are always in a dilemma when they have a lot of choices and they always get confused among them. The E-commerce companies want to increase their profit, so they introduced recommender systems. The recommender system is like the newspaper which gives us recommendations when we do not have any information about the particular products of the market. Users’ mind diverts the fetching of data from users’ favorite headlines just like the recommender system which fetches the items according to the users’ taste and preferences. However, to date Recommender systems have constraints of cold start problems, gray sheep user problems and shilling attacks. Variety in the tastes of the users gives rise to the gray sheep problem where it is difficult to match the products as per the choice of one person’s taste to the other person. This affects the performance of recommender systems. In this paper, the chocolate bars flavors_of_Cacao dataset (124KB) with 1796 entries tuples and 9 attributes dataset based on the personality parameters (modeling with Big Five model), is analyzed with boosted decision trees, two neural networks, logistic regression and decision forest. The accuracy of the decision forest is validated over other machine learning algorithms for a recommendation of the chocolate bars. © 2023 Totem Publisher, Inc. All rights reserved.","Chocolate Bars popularity; Gray Sheep users; machine learning; personality models; recommender system",{"$nulls":7},"Konstan J.A., Introduction to Recommender Systems, Proceedings of the 2008 ACM SIGMOD international conference on Management of data, pp. 1373-1374, (2008); Ricci F., Rokach L., Shapira B., Recommender Systems: Introduction and Challenges, Recommender systems handbook, pp. 1-34, (2015); Resnick P., Varian H.R., Recommender Systems, Communications of the ACM, 40, 3, pp. 56-58, (1997); Drachsler H., Hummel H., Koper R., Recommendations for Learners Are Different: Applying Memory-Based Recommender System Techniques to Lifelong Learning, (2007); Lu J., Wu D., Mao M., Wang W., Zhang G., Recommender System Application Developments: A Survey, Decision support systems, 74, pp. 12-32, (2015); Khusro S., Ali Z., Ullah I., Recommender Systems: Issues, Challenges, and Research Opportunities, Information science and applications (ICISA), pp. 1179-1189, (2016); Lakshmi S.S., Lakshmi T.A., Recommendation Systems: Issues and Challenges, International Journal of Computer Science and Information Technologies, 5, 4, pp. 5771-5772, (2014); Van Meteren R., Van Someren M., using Content-Based Filtering for Recommendation, Proceedings of the machine learning in the new information age: MLnet/ECML2000 workshop, 30, pp. 47-56, (2000); Claypool M., Gokhale A., Miranda T., Murnikov P., Netes D., Sartin M., Combing Content-Based and Collaborative Filters in an Online Newspaper, Proc. of Workshop on Recommender Systems-Implementation and Evaluation, (1999); Su X., Khoshgoftaar T.M., A Survey of Collaborative Filtering Techniques, Advances in artificial intelligence, (2009); Nunes M.A.S., Hu R., Personality-Based Recommender Systems: An Overview, Proceedings of the sixth ACM conference on Recommender systems, pp. 5-6, (2012); Hu R., Pu P., Acceptance Issues of Personality-Based Recommender Systems, Proceedings of the third ACM conference on Recommender systems, pp. 221-224, (2009); Bidjerano T., Dai D.Y., The Relationship between the Big-Five Model of Personality and Self-Regulated Learning Strategies, Learning and individual differences, 17, 1, pp. 69-81, (2007); Bernard L.C., Hutchison S., Lavin A., Pennington P., Ego-Strength, Hardiness, Self-Esteem, Self-Efficacy, Optimism, and Maladjustment: Health-Related Personality Constructs and the “Big Five” Model of Personality, Assessment, 3, 2, pp. 115-131, (1996); Pohling R., Bzdok D., Eigenstetter M., Stumpf S., Strobel A., What Is Ethical Competence? The Role of Empathy, Personal Values, and the Five-Factor Model of Personality in Ethical Decision-Making, Journal of Business Ethics, 137, pp. 449-474, (2016); Srivastava A., Bala P.K., Kumar B., New Perspectives on Gray Sheep Behavior in E-Commerce Recommendations, Journal of Retailing and Consumer Services, 53, (2020); Kanagawa H., Kobayashi H., Shimizu N., Tagami Y., Suzuki T., Cross-Domain Recommendation via Deep Domain Adaptation, European Conference on Information Retrieval, pp. 20-29, (2019); Cremonesi P., Tripodi A., Turrin R., Cross-Domain Recommender Systems, 2011 IEEE 11th International Conference on Data Mining Workshops, pp. 496-503, (2011); Ghazanfar M., Prugel-Bennett A., Fulfilling the Needs of Gray-Sheep Users in Recommender Systems, A Clustering Solution, (2011); Srivastava A., Gray Sheep, Influential Users, User Modeling and Recommender System Adoption by Startups, Proceedings of the 10th ACM conference on recommender systems, pp. 443-446, (2016); Sharma S., Gupta K., Gupta D., Recommender System: A Bibliometric Analysis, IOP Conference Series: Materials Science and Engineering, 1022, 1, (2021); Gupta D., A Comprehensive Study of Recommender Systems for the Internet of Things, Journal of Physics: Conference Series, 1969, 1, (2021); Ramakrishnan G., Saicharan V., Chandrasekaran K., Rathnamma M.V., Ramana V.V., Collaborative Filtering for Book Recommendation System, Soft Computing for Problem Solving: SocProS 2018, 2, pp. 325-338, (2020)","S. Rani; Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India; email: shalli.rani@chitkara.edu.in",null,"Totem Publishers Ltd",{"$nulls":5},9731318.0,null,null,null,"English","Int. J. Perform. Eng.","Article","Final",null,"Scopus","2-s2.0-85174350387"]
["Kim M.; Shin W.; Kim S.; Kim H.-W.","Kim, Minsu (58366847000); Shin, Woosik (57818042800); Kim, SeongBeom (58547055000); Kim, Hee-Woong (7410131022)","58366847000; 57818042800; 58547055000; 7410131022","Predicting Session Conversion on E-commerce: A Deep Learning-based Multimodal Fusion Approach",2023.0,"Asia Pacific Journal of Information Systems",33.0,3.0,null,737.0,767.0,30.0,0.0,"10.14329/apjis.2023.33.3.737","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85177421626&doi=10.14329%2fapjis.2023.33.3.737&partnerID=40&md5=a6ee1488f4bc41dd930fc6c67d8a616d","Data Scientist, LG UPlus Corporation, South Korea; Graduate School of Information, Yonsei University, South Korea; Graduate School of Information, Yonsei University, South Korea","Kim M., Data Scientist, LG UPlus Corporation, South Korea; Shin W., Graduate School of Information, Yonsei University, South Korea; Kim S., Graduate School of Information, Yonsei University, South Korea; Kim H.-W., Graduate School of Information, Yonsei University, South Korea","With the availability of big customer data and advances in machine learning techniques, the prediction of customer behavior at the session-level has attracted considerable attention from marketing practitioners and scholars. This study aims to predict customer purchase conversion at the session-level by employing customer profile, transaction, and clickstream data. For this purpose, we develop a multimodal deep learning fusion model with dynamic and static features (i.e., DS-fusion). Specifically, we base page views within focal visist and recency, frequency, monetary value, and clumpiness (RFMC) for dynamic and static features, respectively, to comprehensively capture customer characteristics for buying behaviors. Our model with deep learning architectures combines these features for conversion prediction. We validate the proposed model using real-world e-commerce data. The experimental results reveal that our model outperforms unimodal classifiers with each feature and the classical machine learning models with dynamic and static features, including random forest and logistic regression. In this regard, this study sheds light on the promise of the machine learning approach with the complementary method for different modalities in predicting customer behaviors. © (2023). All Rights Reserved.","Clickstream Data; Deep Learning; Multimodal Fusion; Purchase Conversion; Rfmc",{"$nulls":5},"Ministry of Science, ICT and Future Planning, MSIP, (2022R1F1A1073133); National Research Foundation of Korea, NRF","This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea Government (MSIT) (No. 2022R1F1A1073133).","Baumann A., Haupt J., Gebert F., Lessmann S., Changing perspectives: Using graph metrics to predict purchase probabilities, Expert Systems with Applications, 94, pp. 137-148, (2018); Baumann A., Haupt J., Gebert F., Lessmann S., The price of privacy, Business & Information Systems Engineering, 61, 4, pp. 413-431, (2019); Bigon L., Cassani G., Greco C., Lacasa L., Pavoni M., Polonioli A., Tagliabue J., Prediction is very hard, especially about conversion, Predicting user purchases from clickstream data in fashion e-commerce, (2019); Bogina V., Kuflik T., Incorporating dwell time in session-based recommendations with recurrent neural networks, CEUR Workshop Proceedings, 1922, pp. 57-59, (2017); Bradley A. 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["Guarino Neto L.; Geraldo Vidal Vieira J.","Guarino Neto, Luigi (58306808100); Geraldo Vidal Vieira, José (26023896600)","58306808100; 26023896600","An investigation of consumer intention to use pick-up point services for last-mile distribution in a developing country",2023.0,"Journal of Retailing and Consumer Services",74.0,null,103425.0,null,null,null,2.0,"10.1016/j.jretconser.2023.103425","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85161356494&doi=10.1016%2fj.jretconser.2023.103425&partnerID=40&md5=f097cd38125b2b92034b4472c6e0ef0e","Department of Production Engineering, USP - University of São Paulo, São Paulo, CEP 05508-010, Brazil; Department of Production Engineering UFSCAR - University of Sao Carlos, Sorocaba, CEP 13565-905, Brazil","Guarino Neto L., Department of Production Engineering, USP - University of São Paulo, São Paulo, CEP 05508-010, Brazil; Geraldo Vidal Vieira J., Department of Production Engineering UFSCAR - University of Sao Carlos, Sorocaba, CEP 13565-905, Brazil","Pick-up point services are one response to last-mile distribution challenges in the e-commerce growth scenario. However, in large cities in developing countries where the low-income and high-income groups are clearly divided, differences in consumer behavior between income groups may affect service distribution. The literature shows that most consumers may use pick-up points when available. However, the service implementation is facing huge inertia. A survey was carried out with 396 consumers in São Paulo, and a conceptual framework was proposed to expand the Diffusion of Innovation Theory to reveal these behaviors. Data were accessed using advanced structural equation modeling techniques (Multigroup and IPMA) to conduct a case study. The findings suggest that ‘Trialability’, ‘Compatibility’, and ‘Relative advantage’ constructs most affect consumer behavior. Location security and accessibility are matters of great concern. The higher preference to use the pick-up point system comes from low-income consumers (social classes D and E); almost 96% of them reported being affected by delivery issues. They also prefer personal attendance and supermarkets as safe and accessible locations. Higher social classes (A and B) still prefer home delivery. This research will help retailers to understand how to operate in a given market to provide an effective, fair, and sustainable service, promoting its diffusion. © 2023 Elsevier Ltd","Diffusion of innovation theory; E-commerce; Last-mile; Low-income consumers; Pick-up point; Structural Equation Modeling (SEM)","Brazil; Sao Paulo [Brazil]; consumption behavior; developing world; electronic commerce; innovation; low income population; numerical model; retailing; technology diffusion",{"$nulls":4},"Conselho Nacional de Desenvolvimento Científico e Tecnológico, CNPq, (3107202022-2)","The authors acknowledge the support of the Brazilian National Council for Scientific and Technological Development (CNPq, Portuguese: Conselho Nacional de Desenvolvimento Científico e Tecnológico) . Grant number 3107202022-2 . 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["Fitriani N.; Setiawan D.; Aryani Y.A.; Arifin T.","Fitriani, Novi (58704806800); Setiawan, Doddy (56028197800); Aryani, Y. Anni (57191042768); Arifin, Taufiq (56310015200)","58704806800; 56028197800; 57191042768; 56310015200","Does social media affect performance in e-commerce business? The role of customer management",2023.0,"Journal of Open Innovation: Technology, Market, and Complexity",9.0,4.0,100171.0,null,null,null,0.0,"10.1016/j.joitmc.2023.100171","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85177495258&doi=10.1016%2fj.joitmc.2023.100171&partnerID=40&md5=7a97b074df2df9121fc546300774b0d1","Faculty of Economics and Business, Universitas Sebelas Maret, Jl. Ir. Sutami 36A, Surakarta, Indonesia; Statistics Indonesia - Special Region of Yogyakarta, Jl. Brawijaya, Tamantirto, Bantul, Kasihan, Indonesia","Fitriani N., Faculty of Economics and Business, Universitas Sebelas Maret, Jl. Ir. Sutami 36A, Surakarta, Indonesia, Statistics Indonesia - Special Region of Yogyakarta, Jl. Brawijaya, Tamantirto, Bantul, Kasihan, Indonesia; Setiawan D., Faculty of Economics and Business, Universitas Sebelas Maret, Jl. Ir. Sutami 36A, Surakarta, Indonesia; Aryani Y.A., Faculty of Economics and Business, Universitas Sebelas Maret, Jl. Ir. Sutami 36A, Surakarta, Indonesia; Arifin T., Faculty of Economics and Business, Universitas Sebelas Maret, Jl. Ir. Sutami 36A, Surakarta, Indonesia","Technological innovation can help a business gain maximum profits. Previous studies have proven that social media is vital for improving performance, but research gaps remain. This research aims to examine the influence of social media on enhancing performance and analyze the moderating role of customer management. The unit of analysis in this research is micro-scale e-commerce businesses in Indonesia. This business is exciting to study because most households in Indonesia depend on this business for their livelihood. This business has also saved the Indonesian economy from recession. The data used in this research is secondary data totalling 11,077 units and was processed using the STATA 17 application. Because the dependent variable in this research is dichotomous, this research uses binary logistic regression analysis. The research results show that social media has a positive effect on performance. However, customer management was unable to moderate the relationship. These findings support the Resource-Based View theory by highlighting the importance of technological innovation in the form of social media, which can be built in such a way as to achieve sustainable competitive advantage and ultimately increase performance. Practically, this research can be a reference for entrepreneurs to optimize the use of social media and improve customer management so that maximum profits can be realized. © 2023 The Authors","Binary logistic regression; Customer management; Micro-scale e-commerce businesses; Performance; Social media",{"$nulls":5},"Universitas Sebelas Maret, UNS, (228/UN27.22/PT.01.03/2023)","The authors acknowledge financial support from Universitas Sebelas Maret , Mandatory Research Grant nu, 228/UN27.22/PT.01.03/2023 . ","Ahmad R.A., (2023); Barney J., Firm resources and sustained competitive advantage, J. Manag., 17, 1, pp. 99-120, (1991); Baron R.A., Markman G.D., Beyond social capital: the role of entrepreneurs’ social competence in their financial success, J. Bus. Ventur., 18, 1, pp. 41-60, (2003); (2021); Caballero-Morales S.O., Innovation as recovery strategy for SMEs in emerging economies during the COVID-19 pandemic, Res. Int. Bus. 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["Garg V.; Niranjan S.; Prybutok V.; Pohlen T.; Gligor D.","Garg, Vipul (57320986100); Niranjan, Suman (58395464700); Prybutok, Victor (7004907736); Pohlen, Terrance (6505913722); Gligor, David (55226503300)","57320986100; 58395464700; 7004907736; 6505913722; 55226503300","Drones in last-mile delivery: A systematic review on Efficiency, Accessibility, and Sustainability",2023.0,"Transportation Research Part D: Transport and Environment",123.0,null,103831.0,null,null,null,2.0,"10.1016/j.trd.2023.103831","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85171879685&doi=10.1016%2fj.trd.2023.103831&partnerID=40&md5=3c5162a2c33d68a24eb3b0da4492af4c","Doctoral Candidate of Logistics, Department of Logistics and Operations Management, G. Brint Ryan College of Business, University of North Texas, Denton, 76201, TX, United States; Assistant Professor of Logistics, Department of Logistics and Operations Management, G. Brint Ryan College of Business, University of North Texas, Denton, 76201, TX, United States; Dean of the Toulouse Graduate School, Vice Provost of Graduate Education, & Regents Professor of Decision Sciences, G. Brint Ryan College of Business, University of North Texas, Denton, 76201, TX, United States; Senior Associate Dean & Director of Jim McNatt Institute of Logistics Research, Department of Logistics and Operations Management, G. Brint Ryan College of Business, University of North Texas, Denton, 76201, TX, United States; Endowed Chair & Professor of Logistics, Department of Logistics and Operations Management, G. Brint Ryan College of Business, University of North Texas, Denton, 76201, TX, United States","Garg V., Doctoral Candidate of Logistics, Department of Logistics and Operations Management, G. Brint Ryan College of Business, University of North Texas, Denton, 76201, TX, United States; Niranjan S., Assistant Professor of Logistics, Department of Logistics and Operations Management, G. Brint Ryan College of Business, University of North Texas, Denton, 76201, TX, United States; Prybutok V., Dean of the Toulouse Graduate School, Vice Provost of Graduate Education, & Regents Professor of Decision Sciences, G. Brint Ryan College of Business, University of North Texas, Denton, 76201, TX, United States; Pohlen T., Senior Associate Dean & Director of Jim McNatt Institute of Logistics Research, Department of Logistics and Operations Management, G. Brint Ryan College of Business, University of North Texas, Denton, 76201, TX, United States; Gligor D., Endowed Chair & Professor of Logistics, Department of Logistics and Operations Management, G. Brint Ryan College of Business, University of North Texas, Denton, 76201, TX, United States","With the rise of e-commerce, there has been a surge in demand for efficient and accessible last-mile delivery options, leading to the examination of promising new technologies such as drones. However, the current research on drone applications in last-mile delivery is limited, often needing more comprehensive analysis and frameworks. This systematic literature review comprehensively analyzes 55 interdisciplinary studies to address this gap, focusing on critical aspects such as consumer accessibility, potential cost savings, and environmental sustainability. The review identifies significant gaps in current research, including the failure to explain how drone-delivered packages will increase consumer accessibility and frequently excluded key assumptions such as weather, flight duration, and battery capacity. Additionally, current research primarily focuses on drone deliveries in the United States, neglecting other regions such as Africa and Asia. This review provides valuable insights for academics, government agencies, and practitioners seeking to understand and develop sustainable drone delivery solutions. © 2023 Elsevier Ltd","Drone applications; Drone delivery methods; Humanitarian logistics; Last-mile delivery","Africa; Asia; United States; Sustainable development; 'current; Comprehensive analysis; Delivery methods; Drone application; Drone delivery method; E- commerces; Humanitarian logistics; Last mile; Last-mile delivery; Systematic Review; accessibility; freight transport; literature review; logistics; sustainability; technological development; Drones",{"$nulls":4},"National Aeronautics and Space Administration, NASA; University of North Texas, UNT","The authors appreciate the support of the National Aeronautics and Space Administration (NASA) and the Jim McNatt Institute for Logistics Research at the University of North Texas. Special thanks to Dr. Timothy G. 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["Kwilinski A.","Kwilinski, Aleksy (57204068618)",5.7204068618E10,"E-Commerce and Sustainable Development in the European Union: A Comprehensive Analysis of SDG2, SDG12, and SDG13",2023.0,"Forum Scientiae Oeconomia",11.0,3.0,null,87.0,107.0,20.0,20.0,"10.23762/FSO_VOL11_NO3_5","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174228890&doi=10.23762%2fFSO_VOL11_NO3_5&partnerID=40&md5=e2a5b2549876378eb05b49ccac3e7274","The London Academy of Science and Business, UK WSB University, London, Dabrowa Gornicza, Poland","Kwilinski A., The London Academy of Science and Business, UK WSB University, London, Dabrowa Gornicza, Poland","The rapid expansion of e-commerce has revolutionised global trade and connectivity, bringing forth both opportunities and challenges for sustainable growth in European Union (EU) countries. This study aims to investigate the impact of e-commerce on key sustainable development goals (SDGs) in the EU, specifically focusing on SDG2 (Zero Hunger), SDG12 (Responsible Consumption and Production), and SDG13 (Climate Action). To analyse the influence of e-commerce on the selected SDGs, this study adopts two distinct approaches: the panel-corrected standard error (static estimation) approach and the system generalised method of moments (dynamic estimation) approach. The investigation yields significant insights into the role of e-commerce in shaping the achievement of the aforementioned SDGs. The findings indicate that e-commerce has the potential to enhance food distribution networks, thus improving access to nutritious food in certain regions. However, concerns are raised regarding increased food waste and its impact on food availability for vulnerable populations. Additionally, the study highlights the environmental implications of e-commerce, particularly in terms of excessive packaging waste and carbon emissions from logistics. Based on empirical findings, policymakers, businesses, and stakeholders should develop targeted strategies to capitalise on the positive impacts of e-commerce while addressing the challenges thereof in the context of sustainable development. Recommended measures include optimising delivery routes, promoting sustainable packaging practices, and integrating green technology into e-commerce operations to effectively align e-commerce with the SDGs. © 2023, WSB University. All rights reserved.","climate action; digitalisation; no hunger; online shopping; responsible consumption; responsible production",{"$nulls":7},{"$cut":{"chars":20638,"head":"Agan B., Balcilar M., Unraveling the Green Growth Matrix: Exploring the Impact of Green Technology, Climate Change Adaptation, and Macroeconomic Factors on Sustainable Development, Sustainability, 15, (2023); Ahi A.A., Sinkovics N., Sinkovics R.R., E-commerce policy and the global economy: A path to more inclusive development?, Management International Review, 63, 1, pp. 27-56, (2023); Akimov O., Karpa M., Parkhomenko-Kutsevil O., Kupriichuk V., Omarov A., Entrepreneur ship education of the formation of the e-commerce managers professional qualities, International Journal of Entrepreneurship, 25, 7, pp. 1-8, (2021); Altarturi H.H., Nor A.R. 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Monte Carlo evidence and an application to employment equations, Review of Economic Studies, 58, pp. 277-297, (1991); Baltagi B.H., Pesaran M., Heterogeneity and cross-section dependence in panel data models: theory and applications introduction, Journal of Applied Econometrics, 22, 2, pp. 229-232, (2007); Baptista C., Matias F., do Valle P.O., The moderating role of strategy and environment on the relationship between corporate liquidity and investment: evidence from panel data, Tourism & Management Studies, 9, 1, pp. 85-91, (2013); Bashir M.F., Benjiang M.A., Hussain H.I., Shahbaz M., Koca K., Shahzadi I., Evaluating environmental commitments to COP21 and the role of economic complexity, renewable energy, financial development, urbanization, and energy innovation: empirical evidence from the RCEP countries, Renewable Energy, 184, pp. 541-550, (2022); Ben Youssef A., Dahmani M., Examining the Drivers of E-Commerce Adoption by Moroccan Firms: A Multi-Model Analysis, Information, 14, 7, (2023); Carpio C.E., Isengildina-Massa O., Lamie R.D., Zapata S.D., Does e-commerce help agricultural markets? The case of MarketMaker, Choices, 28, 4, pp. 1-7, (2013); Chen Y., Kwilinski A., Chygryn O., Lyulyov O., Pimonenko T., The Green Competitiveness of Enterprises: Justifying the Quality Criteria of Digital Marketing Communication Channels, Sustainability, 13, (2021); Chen Y., Lyulyov O., Pimonenko T., Kwilinski A., Green development of the country: Role of macroeconomic stability, Energy & Environment, (2023); Chen Z., Cao H., Xu F., Cheng M., Wang T., Li Y., Understanding the role of intermediaries in online social e-commerce: an exploratory study of beidian, Proceedings of the ACM on Human-Computer Interaction, 4, pp. 1-24, (2020); Chiu A.S., Aviso K.B., Baquillas J., Tan R.R., Can disruptive events trigger transitions toward sustainable consumption?, Cleaner and Responsible Consumption, 1, (2020); Cordes D.L., Marinova D., Systematic literature review of the role of e-commerce in providing pathways to sustainability for poverty alleviation in Sub-Saharan Africa, Discover Sustainability, 4, 1, (2023); Criveanu M.M., Investigating Digital Intensity and E-Commerce as Drivers for Sustainability and Economic Growth in the EU Countries, Electronics, 12, 10, (2023); Curto J.D., Pinto J.C., The corrected vif (cvif), Journal of Applied Statistics, 38, 7, pp. 1499-1507, (2011); Dau L., Moore E., Doh J., Soto M., Does global integration stimulate corporate citizenship? The effect of international trade agreements and regulatory quality on state and private firm adoption of CSR standards, Journal of International Business Policy, 5, 3, pp. 328-352, (2021); Delina L. L., Perez O"}},"A. Kwilinski; The London Academy of Science and Business, UK WSB University, London, Dabrowa Gornicza, Poland; email: a.kwilinski@london-asb.co.uk",null,"WSB University",{"$nulls":5},2.3005947E7,null,null,null,"English","Forum Scientiae Oeconomia","Article","Final",null,"Scopus","2-s2.0-85174228890"]
["Kafile M.; Mbhele T.P.","Kafile, Masithembe (58785802100); Mbhele, Thokozani Patmond (6505480363)","58785802100; 6505480363","Improving last mile distribution systems through the Internet of Things: a South African case",2023.0,"Acta Logistica",10.0,4.0,null,597.0,603.0,6.0,0.0,"10.22306/al.v10i4.438","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85180854490&doi=10.22306%2fal.v10i4.438&partnerID=40&md5=9a600da9e2a31a3df9376137d95f03ae","University of KwaZulu Natal, 228 High Bury Park Kuils-River, Western Cape, Cape Town, South Africa; University of KwaZulu Natal University, Road Westville, KwaZulu Natal, Durban, 4000, South Africa","Kafile M., University of KwaZulu Natal, 228 High Bury Park Kuils-River, Western Cape, Cape Town, South Africa; Mbhele T.P., University of KwaZulu Natal University, Road Westville, KwaZulu Natal, Durban, 4000, South Africa","The study investigates the impact of the IoT on the cost and quality of last-mile logistics, the critical and often challenging final phase of the supply chain. With the relentless growth of e-commerce and the increasing demands for efficient and reliable delivery services, understanding how IoT affects last-mile logistics is increasingly becoming important. Through the integration of IoT technologies such as GPS tracking, RFID systems, and real-time data analytics, the study aimed to assess the extent to which the application of the IoT affects the cost and quality of last-mile distribution in South Africa. As a result, the study provides valuable insights into the potential cost savings or increases associated with IoT adoption, quality challenges and areas of improvement, customer satisfaction and the overall performance of last-mile distribution systems. The methodology involves the collection of primary data from selected distribution companies in South Africa. Statistical software was used to analyse the data to shed light on the tangible benefits and challenges associated with IoT adoption in last-mile logistics as they relate to cost and quality. The research findings indicate that implementing IoT in last-mile distribution systems in South Africa can significantly improve efficiency and effectiveness. The IoT integration with existing infrastructure enables seamless communication, proactive decision-making, and reduced delivery delays. Overall, by leveraging IoT technologies and real-time data analysis, organisations can optimise their distribution processes, reduce costs, improve quality, and enhance overall customer experience. © Acta Logistica, www.actalogistica.eu.","distribution; IoT; last-mile; logistics",{"$nulls":5},"National Research Foundation, NRF; Inyuvesi Yakwazulu-Natali, UKZN","This research was funded by the South African National Research Foundation (SANRF) and the University of KwaZulu Natal, college of law and management studies research grant.","RIED L., ECKERD S., KAUFMANN L., CARTER C., Spillover effects of information leakages in buyer– supplier–supplier triads, Journal of Operations Management, 67, 3, pp. 280-306, (2021); GUPTA H., YADAV A.K., KUSI-SARPONG S., KHAN S.A., SHARMA S.C., Strategies to overcome barriers to innovative digitalisation technologies for supply chain logistics resilience during pandemic, Technology in Society, 69, pp. 1-19, (2022); WINKELHAUS S., GROSSE E.H., Logistics 4.0: a systematic review towards a new logistics system, International Journal of Production Research, 58, 1, pp. 18-43, (2020); YANG C., LAN S., ZHAO Z., ZHANG M., WU W., HUANG G.Q., Edge-cloud blockchain and IoE enabled quality management platform for perishable supply chain logistics, IEEE Internet of Things Journal, 10, 4, pp. 3264-3275, (2023); AJAYI M.O., LASEINDE O.T., A review of supply chain 4IR management strategy for appraising the manufacturing industry's potentials and shortfalls in the 21<sup>st</sup> century, Procedia Computer Science, 217, pp. 513-525, (2023); DEVARI A., NIKOLAEV A.G., HE Q., Crowdsourcing the last mile delivery of online orders by exploiting the social networks of retail store customers, Transportation Research Part E: Logistics and Transportation Review, 105, pp. 105-122, (2017); GIELENS K., GIJSBRECHTS E., GEYSKENS I., Navigating the last mile: The demand effects of click-and-collect order fulfillment, Journal of Marketing, 85, 4, pp. 158-178, (2021); KAYIKCI Y., Sustainability impact of digitisation in logistics, Procedia manufacturing, 21, pp. 782-789, (2018); BUYUKOZKAN G., GOCER F., Digital Supply Chain: Literature review and a proposed framework for future research, Computers in Industry, 97, pp. 157-177, (2018); BALAJI M.S., ROY S.K., Value co-creation with Internet of things technology in the retail industry, Journal of Marketing Management, 33, 1-2, pp. 7-31, (2017); DE VASS T., SHEE H., MIAH S.J., IoT in supply chain management: a narrative on retail sector sustainability, International Journal of Logistics Research and Applications, 24, 6, pp. 605-624, (2021); BIRKEL H.S., HARTMANN E., Impact of IoT challenges and risks for SCM, Supply Chain Management, 24, 1, pp. 39-61, (2019); TU M., An exploratory study of internet of things (IoT) adoption intention in logistics and supply chain management: a mixed research approach, International Journal of Logistics Management, 29, 1, pp. 131-151, (2018); MANAVALAN E., JAYAKRISHNA K., A review of Internet of Things (IoT) embedded sustainable supply chain for Industry 4.0 requirements, Computers and Industrial Engineering, 127, pp. 925-953, (2019); ELSOKKARY N., OTROK H., SINGH S., MIZOUNI R., BARADA H., OMAR M., Crowdsourced last mile delivery: Collaborative workforce assignment, Internet of Things, 22, pp. 1-12, (2023); PHASE A., MHETRE N., Using IoT in supply chain management, International Journal of Engineering and Techniques, 4, 2, pp. 973-979, (2018); TAJFAR A.H., GHEYSARI M., Analysis the effects of internet of things technology in managing supply chain, International Journal of Information & Communication Technology Research, 8, 3, pp. 15-25, (2016); BAG S., GUPTA S., LUO Z., Examining the role of logistics 4.0 enabled dynamic capabilities on company performance, International Journal of Logistics Management, 31, 3, pp. 607-628, (2020); CHOUDHURY A., BEHL A., SHEOREY P.A., PAL A., Digital supply chain to unlock new agility: a TISM approach, Benchmarking, 28, 6, pp. 2075-2109; BEN-DAYA M., HASSINI E., BAHROUN Z., Internet of things and supply chain management: a literature review, International Journal of Production Research, 57, 15-16, pp. 4719-4742, (2019); KAYA S.K., Industrial Internet of Things: How Industrial Internet of Things Impacts the Supply Chain, Internet of Things (IoT) Applications for Enterprise Productivity, IGI Global, pp. 134-155, (2020); HOPKINS J., HAWKING P., Big Data Analytics and IoT in logistics: a case study, The International Journal of Logistics Management, 29, 2, pp. 575-591, (2018); VILLENA V.H., WILHELM M., XIAO C.Y., Untangling drivers for supplier environmental and social responsibility: An investigation in Philips Lighting’s Chinese supply chain, Journal of Operations Management, 67, 4, pp. 476-510, (2021); GHADGE A., ER KARA M., MORADLOU H., GOSWAMI M., The impact of Industry 4.0 implementation on supply chains, Journal of Manufacturing Technology Management, 31, 4, pp. 669-686, (2020); SOMAPA S., COOLS M., DULLAERT W., Characterizing supply chain visibility – A literature review, International Journal of Logistics Management, 29, 1, pp. 308-339, (2018); CALATAYUD A., MANGAN J., CHRISTOPHER M., The self-thinking supply chain, Supply Chain Management: An International Journal, 24, 1, pp. 22-38, (2019); TOYMENTSEVA I.A., KARPOVA N.P., EVTODIEVA T.E., Strategic purchasing control of the industrial enterprise: Digitalization and logistics approach, Digital Age: Chances, Challenges and Future, 7, pp. 398-407, (2020); SAUNDERS M., LEWIS P., THORNHILL A., Understanding research philosophies and approaches, Research Methods for Business Students, (2018); SEKARAN U., BOUGIE R., Research methods for business: A skill-building approach, 20, (2016); DALLA CHIARA G., GOODCHILD A., Do commercial vehicles cruise for parking? Empirical evidence from Seattle, Transport Policy, 97, pp. 26-36, (2020); ALABI S., WHITE M., BELOFF N., Contactless Palm Vein Authentication Security Technique for Better Adoption of e-Commerce in Developing Countries, Advances in Intelligent Systems and Computing, 1230, pp. 380-390, (2020); NGUYEN T., PETERSEN T.E., Technology adoption in Norway: organizational assimilation of big data, (2017); RODRIGUES J., RUIVO P., OLIVEIRA T., Mediation role of business value and strategy in company performance of organisations using software-as-a-service enterprise applications, Information and Management, 58, 1, pp. 1-14, (2021); TURRINI L., BESIOU M., PAPIES D., MEISSNER J., The role of operational expenditures and misalignments in fundraising for international humanitarian aid, Journal of Operations Management, 66, 4, pp. 379-417, (2020); ARMENIA S., CASALINO N., GNAN L., FLAMINI G., A systems approach to the digital transformation of public administration, Prospettive in organizzazione, 14, pp. 1-20, (2021)","M. Kafile; University of KwaZulu Natal, Cape Town, 228 High Bury Park Kuils-River, Western Cape, South Africa; email: masithembekafile@gmail.com",null,"4S go, s.r.o",{"$nulls":5},1.3395629E7,null,null,null,"English","Acta Logistica","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85180854490"]
["İbroşka B.; Özpeynirci S.; Özpeynirci Ö.","İbroşka, Baybars (58562746900); Özpeynirci, Selin (25228157500); Özpeynirci, Özgür (16402801100)","58562746900; 25228157500; 16402801100","Multiple traveling salesperson problem with drones: General variable neighborhood search approach",2023.0,"Computers and Operations Research",160.0,null,106390.0,null,null,null,0.0,"10.1016/j.cor.2023.106390","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85169826652&doi=10.1016%2fj.cor.2023.106390&partnerID=40&md5=d90e74268e3730f070e5db1596200224","Trendyol Express, İstanbul, Turkey; Department of Industrial Engineering, İzmir University of Economics, İzmir, Turkey; Department of Logistics Management, İzmir University of Economics, İzmir, Turkey","İbroşka B., Trendyol Express, İstanbul, Turkey; Özpeynirci S., Department of Industrial Engineering, İzmir University of Economics, İzmir, Turkey; Özpeynirci Ö., Department of Logistics Management, İzmir University of Economics, İzmir, Turkey","A key factor to consider in the development of new technologies in a number of fields is the use of unmanned aerial vehicles. This rapidly developing technology is used in military, communication, health, mapping, agriculture and transportation fields. The importance of cargo transportation has grown due to the growth of e-commerce. Currently, with advancing technology, and the effect of the pandemic, purchases are increasingly made over the internet. For cargo transporters, this situation leads to an increase in the number of destination points, in distances traveled, and in the delivery frequency, and a decrease in the package sizes. As a result, the planning of transportation has become increasingly complex. One solution is to make greater use of unmanned aerial vehicles in this sector, and to reduce reliance on trucks through appropriate planning. This involves two aspects: the unmanned aerial vehicle delivering to a point, while the cargo truck delivers to a separate point. In this study, we consider a multiple traveling salesperson problem simultaneously using multiple trucks and unmanned aerial vehicles for package delivery. We develop a general variable neighborhood search algorithm, and compare the results with the existing studies in the literature. Computational experiments show that our approach is able to find highly satisfactory solutions in reasonable time, and outperforms the existing methods in terms of best solution, average solution and solution time in majority of the instances. © 2023 Elsevier Ltd","Drone delivery; Routing; Transportation; Unmanned aerial vehicles; Variable neighborhood search","Antennas; Traveling salesman problem; Trucks; Advancing technology; Aerial vehicle; Cargo transportation; Drone delivery; E- commerces; Key factors; Multiple traveling salesperson problem; Routings; Unmanned aerial vehicle; Variable neighborhood search; Drones",{"$nulls":6},"Agatz N., Bouman P., Schmidt M., Optimization approaches for the traveling salesman problem with drone, Transp. 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C, 86, pp. 597-621, (2018); Hansen P., Mladenovic N., Variable neighborhood search: Principles and applications, European J. Oper. Res., 130, 3, pp. 449-467, (2001); Hansen P., Mladenovic N., Variable neighborhood search, Handbook of Heuristics, (R. Martí, P. Pardalos, M. Resende, eds.), Springer, Cham, pp. 759-787, (2018); Hansen P., Mladenovic N., Moreno-Perez J.A., Variable neighbourhood search: Methods and applications, 4OR, 6, pp. 319-360, (2008); Hansen P., Mladenovic N., Moreno-Perez J.A., Variable neighbourhood search: Methods and applications, Ann. Oper. Res., 175, 1, pp. 367-407, (2010); Hansen P., Mladenovic N., Todosijevic R., Hanafi S., Variable neighborhood search: basics and variants, EURO J. Comput. Optim., 5, pp. 423-454, (2017); Ibroska B., Simultaneous operation of trucks and unmanned aerial vehicles at package delivery, (2021); Jarboui B., Derbel H., Hanafi S., Mladenovic N., Variable neighborhood search for location routing, Comput. Oper. Res., 40, pp. 47-57, (2013); Kitjacharoenchai P., Min B.-C., Lee S., Two echelon vehicle routing problem with drones in last mile delivery, Int. J. Prod. Econ., 225, (2020); Kitjacharoenchai P., Ventresca M., Moshref-Javadi M., Lee S., Tanchoco J.M., Brunese P.A., Multiple traveling salesman problem with drones: Mathematical model and heuristic approach, Comput. Ind. Eng., 129, pp. 14-30, (2019); Kocaturk F., Ozpeynirci O., Variable neighborhood search for the pharmacy duty scheduling problem, Comput. Oper. Res., 51, pp. 218-226, (2014); Lin C., A vehicle routing problem with pickup and delivery time windows, and coordination of transportable resources, Comput. Oper. Res., 38, 11, pp. 1596-1609, (2011); Lin S.-W., Yu V.F., Chou S.-Y., Solving the truck and trailer routing problem based on a simulated annealing heuristic, Comput. Oper. Res., 36, 5, pp. 1683-1692, (2009); Lu Z., Hao J.-K., Glover F., Neighborhood analysis: a case study on curriculum-based course timetabling, J. Heuristics, 17, 2, pp. 97-118, (2011); Macrina G., Di Puglia Pugliese L., Guerriero F., Laporte G., Drone-aided routing: A literature review, Transp. Res. C, 120, (2020); Mjirda A., Todosijevic R., Hanafi S., Hansen P., Mladenovic N., Sequential variable neighborhood descent variants: An empirical study on the traveling salesman problem, Int. Trans. Oper. Res., 24, 3, pp. 615-633, (2017); Mladenovic N., Hansen P., Variable neighborhood search, Comput. Oper. Res., 24, 11, pp. 1097-1100, (1997); Murray C., Chu A., The flying sidekick traveling salesman problem: Optimization of drone-assisted parcel delivery, Transp. Res. C, 54, pp. 86-109, (2015); Murray C.C., Raj R., The multiple flying sidekicks traveling salesman problem: Parcel delivery with multiple drones, Transp. Res. C, 110, pp. 368-398, (2020); Otto A., Agatz N., Campbell J., Golden B., Pesch E., Optimization approaches for civil applications of unmanned aerial vehicles UAVs or aerial drones: A survey, Networks, 72, pp. 411-458, (2018); Parreno F., Alvarez-Valdes R., Oliveira J., Tamarit J., Neighborhood structures for the container loading problem: a VNS implementation, J. Heuristics, 16, pp. 1-22, (2010); Poikonen S., Wang X., Golden B., The vehicle routing problem with drones: Extended models and connections, Networks, 70, 1, pp. 34-43, (2017); Ponza A., Optimization of drone-assisted parcel delivery, (2016); Rojas Viloria D., Solano-Charris E.L., Munoz-Villamizar A., Montoya-Torres J.R., Unmanned aerial vehicles/drones in vehicle routing problems: a literature review, Int. Trans. Oper. Res., 28, 4, pp. 1626-1657, (2021); Soylu B., A general variable neighborhood search heuristic for multiple traveling salesmen problem, Comput. Ind. Eng., 90, pp. 390-401, (2015); Toumi S., Cheikh M., Jarboui B., 0-1 quadratic knapsack problem solved with VNS algorithm, Electron. Notes Discrete Math., 47, pp. 269-276, (2015); UPS S., UPS operates first ever U.S. drone COVID-19 vaccine delivery, (2021); Wang K., Pesch E., Kress D., Fridman I., Boysen N., The piggyback transportation problem: Transporting drones launched from a flying warehouse, European J. Oper. Res., 296, pp. 504-519, (2022); Wang X., Poikonen S., Golden B., The vehicle routing problem with drones: Several worst-case results, Optim. Lett., 11, pp. 679-697, (2017)","S. Özpeynirci; Department of Industrial Engineering, İzmir University of Economics, İzmir, Turkey; email: selin.ozpeynirci@ieu.edu.tr",null,"Elsevier Ltd",{"$nulls":5},3050548.0,null,"CMORA",null,"English","Comp. Oper. Res.","Article","Final",null,"Scopus","2-s2.0-85169826652"]
["Song Y.; Fang X.","Song, Yu (57441223700); Fang, Xi (37013171200)","57441223700; 37013171200","An Improved Strength Pareto Evolutionary Algorithm 2 with Adaptive Crossover Operator for Bi-Objective Distributed Unmanned Aerial Vehicle Delivery",2023.0,"Mathematics",11.0,15.0,3327.0,null,null,null,1.0,"10.3390/math11153327","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85167595332&doi=10.3390%2fmath11153327&partnerID=40&md5=1d82260e673c54e37d9ac574baa4e2f4","School of Science, Wuhan University of Technology, Wuhan, 430070, China","Song Y., School of Science, Wuhan University of Technology, Wuhan, 430070, China; Fang X., School of Science, Wuhan University of Technology, Wuhan, 430070, China","With the development of the e-commerce industry, using UAVs (unmanned aerial vehicles) to deliver goods has become more popular in transportation systems. This delivery method can reduce labor costs and improve the distribution efficiency, and UAVs can reach places that are difficult for humans to reach. Because some goods are perishable, the quality of the delivery will have an impact on the customer satisfaction. At the same time, the delivery time should also meet the needs of customers as much as possible. Therefore, this paper takes the distribution distance and customer satisfaction as the objective functions, establishes a bi-objective dynamic programming model, and proposes an improved SPEA2 (strength Pareto evolutionary algorithm 2). The improved algorithm introduces the local search strategy, on the basis of the original algorithm. It conducts a local search for the better non-dominated solutions obtained in each iteration. The new dominated solutions and non-dominated solutions are determined, and the crossover operator is improved, so that the local search ability is improved, on the basis of ensuring its global search ability. The numerical experiment results show that the improved algorithm achieves an excellent performance in three aspects: the Pareto front, generation distance, and spacing, and would have a high application value in UAV cargo delivery and other MOPs (multi-objective optimization problems). The average spacing value of the improved algorithm is more than 20% smaller than SPEA2 + SDE (strength Pareto evolution algorithm 2–shift-based density estimation), which is the second-best algorithm. In the comparison of the average generation distance value, this number reaches 30%. © 2023 by the authors.","bi-objective; local search; multi-objective optimization; strength Pareto; UAV delivery",{"$nulls":5},"Equipment Pre-Research Ministry of Education, (6141A02033703)","This work was supported by the Equipment Pre-Research Ministry of Education Joint Fund [grant number 6141A02033703].","Zhang Z., Zhang Z., Chen X., Research on Location Selection of UAV Distribution Center Based on Improved Gravity Method, J. Phys. Conf. Ser, 1624, (2020); Chopra O., Ghose D., Distributed Control for Multiple UAV Transport of Slung Loads, Proceedings of the AIAA Science and Technology Forum and Exposition; Choi T.-M., Innovative “Bring-Service-Near-Your-Home” operations under Corona-Virus (COVID-19/SARS-CoV-2) outbreak: Can logistics become the Messiah?, Transp. Res. Part E Logist. Transp. 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["Aksenov K.E.","Aksenov, K.E. (6508006036)",6.508006036E9,"Impact of Digital Transformation on the Spatial Organization of Nonfood Retail in a Russian City",2023.0,"Regional Research of Russia",13.0,3.0,null,524.0,533.0,9.0,0.0,"10.1134/S2079970523700910","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85173744487&doi=10.1134%2fS2079970523700910&partnerID=40&md5=c853c73122f35632bf624e78588565f8","St. Petersburg State University, St. Petersburg, 199034, Russian Federation","Aksenov K.E., St. Petersburg State University, St. Petersburg, 199034, Russian Federation","Abstract—: The objective of this study is to reveal what has changed under the influence of digital transformation in the “physical” spatial structure of the retail/purchase process in connection with the emergence of a choice between online and offline “spaces,” or environments, as well as how e-commerce has changed the “physical” spatial principles of organizing nonfood retail in a Russian city with a case study of St. Petersburg. The principles of placement of new e-commerce facilities were analyzed by comparing various shopping models and spatiotemporal systems formed by them, including specific objects (warehouses-stores, warehouses-distributors, order pickup points and parcel terminals), features of interaction between retail actors and transport and logistics flows in the city. Two opposing trends in the placement of new types of retail facilities are described: towards the transfer of the trading function to non-trading premises and the transfer of the non-trading retail function to retail premises. They create spatial competition with traditional retail as well as a new hierarchical competition with office and warehouse business types. The trend towards retail infrastructure for durable goods to be within walking distance means the rollout of a new type of competition for locations: with FMCG sellers. The fact that in delivery the logistics of the “last mile” passes from consumer to seller/logistician means a fundamental shift in the economic geography of goods flows. Instead of private spontaneous pedestrian flows, it forms new regulated small-tonnage types of “last mile” commercial cargo transportation using both alternative transport modes (personal transporter) and transport routes (sidewalks, pedestrian walkways, etc.). All these require the development of a new urban regulation policy. © 2023, The Author(s).","digital transformation; logistics; nonfood retail; spatial competition; spatial organization; types of shopping; urban space","Russian Federation; retailing; spatiotemporal analysis; urban area; urban development; urban economy; urbanization",{"$nulls":6},"Adams P.C., Warp B., Introduction: Cyberspace and geographical space, Geogr. Rev., 87, pp. 139-145, (1997); Aksenov K., Brade I., Bondarchuk E., Transformatsionnoe I Postransformatsionnoe Gorodskoe Prostranstvo. 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Nauki, 172, pp. 57-61, (2019); Mikhailyuk M.V., Internet trade logistics market in 2017–2018: Self-pickup development and spatial expansion of delivery geography, Nauka V Sovremennom Obshchestve: Zakonomernostii I Tendentsii (Science in Modern Society: Laws and Trends), pp. 96-102, (2019); Nagy E., Tourism and Geopolitics: Issues and Concepts form Eastern and Central Europe, (2017); Ratchford B., Soysal G., Zentner A., Gauri D.K., Online and offline retailing: What we know and directions for future research, J. Retailing, 98, pp. 152-177, (2022); Ren F., Kwan M.-P., The impact of geographic context on e-shopping behavior, Environ. Plann., B, 36, pp. 262-278, (2009); Schwab K., The Fourth Industrial Revolution, (2017); Setiawan R., Et al., References for shopping online versus in stores what do customers prefer and how do offline retailers cope with it?, Prod. Manage., 1, pp. 874-898, (2020); Shi M., Zhou J., Jiang Z., Consumer heterogeneity and online vs. offline retail spatial competition, Front. Bus. Res. China, 13, pp. 1-19, (2019); Sikos T.T., Kozak T., Kovacs A., New retail models in online and offline space, Deturope—Central Eur, J. Reg. Dev. Tourism, 11, pp. 9-28, (2019); Tsifrovaya ekonomika: Global’nye trendy i praktika rossiiskogo biznesa, Analiticheskii doklad, (2017); Warf B., Global Geographies of the Internet, (2013); Winters A., Swoboda B., Pathways of offline-online and online-offline channel integration in omni-channel retailing, Proc. Eur. Marketing Acad., 48, (2019); Wrigley N., Lowe M., Reading Retail: A Geographical Perspective on Retailing and Consumption Spaces, (2014)","K.E. Aksenov; St. Petersburg State University, St. Petersburg, 199034, Russian Federation; email: axenov@peterlink.ru",null,"Pleiades Publishing",{"$nulls":5},2.0799705E7,null,null,null,"English","Reg. Res. Russ.","Article","Final","All Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85173744487"]
["Rachana Harish A.; Liu X.L.; Li M.; Zhong R.Y.; Huang G.Q.","Rachana Harish, Arjun (57220854460); Liu, X.L. (57204569405); Li, Ming (57196402801); Zhong, Ray Y. (55353690000); Huang, George Q. (7403425048)","57220854460; 57204569405; 57196402801; 55353690000; 7403425048","Blockchain-enabled digital assets tokenization for cyber-physical traceability in E-commerce logistics financing",2023.0,"Computers in Industry",150.0,null,103956.0,null,null,null,5.0,"10.1016/j.compind.2023.103956","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85159564772&doi=10.1016%2fj.compind.2023.103956&partnerID=40&md5=66c21409c656942488c006292b5ee0f2","Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong; Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong","Rachana Harish A., Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong; Liu X.L., Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong; Li M., Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong; Zhong R.Y., Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong; Huang G.Q., Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong","E-commerce logistics financing drives growth in small and medium-sized logistics companies. Despite the popularity, its adoption faces vexing challenges in supply chains, such as (i) asymmetry arising from information silos, (ii) hidden centrality in existing information technology solutions, and (iii) opaqueness in information ownership. Blockchain technology, with its native constructs, such as shared ledger, smart contracts, and tokens, is deemed promising to alleviate these concerns. Hence, this study introduces a blockchain-enabled cyber-physical traceability system for logistics financing based on digital asset tokenization. The tokenization of digital assets brings visibility and traceability into the supply chain's cyber (information flow) and physical (logistics flow) transactions. Subsequently, we (i) introduce the design and implementation of the proposed traceability system and (ii) demonstrate the application of the proposed system in logistics financing. Some of the resulting implications include: (i) The information sharing through blockchain technology brings resolution into the operations in the supply chain for logistics financing. (ii) The system minimizes the required upfront expenditure and provides flexible access to computing resources to promote the system's adoption by the stakeholders. © 2023 Elsevier B.V.","Blockchain; Cyber-physical traceability; Digital asset; E-commerce logistics financing; Tokenization","Cyber Physical System; Distributed ledger; Electronic commerce; Finance; Supply chains; Block-chain; Cybe-physical traceability; Cyber physicals; Digital assets; E-commerce logistic financing; Information technology solutions; Logistics company; Logistics financings; Tokenization; Traceability systems; Blockchain",{"$nulls":4},"RGC, (R7036-22F, T32-707-22-N)","The authors are grateful for partial supports from the RGC TRS grant (Project No.: T32-707-22-N ) and RGC RIF grant ( R7036-22F ). ","Abeyratne S.A., Monfared R.P., Blockchain ready manufacturing supply chain using distributed ledger, IJRET Int. J. Res. Eng. Technol., 5, (2016); Ambler P., (2017); Asharaf S., Adarsh S., Decentralized computing using blockchain technologies and smart contracts: Emerging research and opportunities, Decentralized Computing Using Blockchain Technologies and Smart Contracts: Emerging Research and Opportunities, (2017); Bals C., Toward a supply chain finance (SCF) ecosystem – Proposing a framework and agenda for future research, J. Purch. Supply Manag., 25, pp. 105-117, (2019); Chakuu S., Masi D., Godsell J., Exploring the relationship between mechanisms, actors and instruments in supply chain finance: a systematic literature review, Int. J. Prod. Econ., 216, pp. 35-53, (2019); Choi T.M., Feng L., Li R., Information disclosure structure in supply chains with rental service platforms in the blockchain technology era, Int. J. Prod. Econ., 221, (2020); (2018); (2020); Fu Y., Zhu J., Operation mechanisms for intelligent logistics system: a blockchain perspective, IEEE Access, 7, pp. 144202-144213, (2019); Gengzhong F., Xiao S., Analysis of Logistics Financing Business Innovation in China, Inst. Electr. Electron. Eng. (IEEE), pp. 127-131, (2007); George S., (2019); Guller M., Koc E., Hegmanns T., Henke M., Noche B., A simulation-based decision support framework for real-time supply chain risk management, Int. J. Adv. Logist., 4, pp. 17-26, (2015); Harish A.R., Liu X.L., Zhong R.Y., Huang G.Q., Log-flock: a blockchain-enabled platform for digital asset valuation and risk assessment in E-commerce logistics financing, Comput. Ind. 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Financ., 57, pp. 43-69, (2018); Toyoda K., Machi K., Ohtake Y., Zhang A.N., Function-level bottleneck analysis of private proof-of-authority ethereum blockchain, IEEE Access, 8, pp. 141611-141621, (2020); Tsang Y.P., Choy K.L., Wu C.H., Ho G.T.S., Lam H.Y., Blockchain-Driven IoT for food traceability with an integrated consensus mechanism, IEEE Access, 7, pp. 129000-129017, (2019); Wang J., Li L., He Q., Yu X., Liu Z., Research on the application of block chain in supply chain finance, DEStech Trans. Comput. Sci. Eng., pp. 326-334, (2018); Wang Y., Singgih M., Wang J., Rit M., Making sense of blockchain technology: How will it transform supply chains?, Int. J. Prod. Econ., 211, pp. 221-236, (2019); Wu W., Shen L., Zhao Z., Harish A.R., Zhong R.Y., Huang G.Q., Internet of everything and digital twin enabled service platform for cold chain logistics, J. Ind. Inf. Integr., 33, (2023); Yu Y., Huang G., Guo X., Financing strategy analysis for a multi-sided platform with blockchain technology, Int. J. Prod. Res., (2020); Zacharia Z.G., Sanders N.R., Nix N.W., The Emerging Role of the Third-Party Logistics Provider (3PL) as an Orchestrator, J. Bus. Logist., 32, pp. 40-54, (2011); Zhang C., Dhaliwal J., An investigation of resource-based and institutional theoretic factors in technology adoption for operations and supply chain management, Int. J. Prod. Econ., 120, pp. 252-269, (2009)","G.Q. Huang; Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong; email: gq.huang@polyu.edu.hk",null,"Elsevier B.V.",{"$nulls":5},1663615.0,null,"CINUD",null,"English","Comput Ind","Article","Final",null,"Scopus","2-s2.0-85159564772"]
["Berke A.; Ding G.; Chin C.; Gopalakrishnan K.; Larson K.; Balakrishnan H.; Li M.Z.","Berke, Alex (57212166580); Ding, Geoffrey (57544122500); Chin, Christopher (57614530700); Gopalakrishnan, Karthik (57190494639); Larson, Kent (7102155300); Balakrishnan, Hamsa (57202677518); Li, Max Z. (57193712088)","57212166580; 57544122500; 57614530700; 57190494639; 7102155300; 57202677518; 57193712088","Drone delivery and the value of customer privacy: A discrete choice experiment with U.S. consumers",2023.0,"Transportation Research Part C: Emerging Technologies",157.0,null,104391.0,null,null,null,0.0,"10.1016/j.trc.2023.104391","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174163934&doi=10.1016%2fj.trc.2023.104391&partnerID=40&md5=03dec997c2cc04f5026dd6dc4d15ffc3","MIT Media Lab, Massachusetts Institute of Technology, Cambridge, MA, United States; Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, MA, United States; Department of Aeronautics and Astronautic, Stanford University, Stanford, CA, United States; Department of Aerospace Engineering, Department of Industrial and Operations Engineering, University of Michigan, Ann Arbor, MI, United States","Berke A., MIT Media Lab, Massachusetts Institute of Technology, Cambridge, MA, United States; Ding G., Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, MA, United States; Chin C., Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, MA, United States; Gopalakrishnan K., Department of Aeronautics and Astronautic, Stanford University, Stanford, CA, United States; Larson K., MIT Media Lab, Massachusetts Institute of Technology, Cambridge, MA, United States; Balakrishnan H., Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, MA, United States; Li M.Z., Department of Aerospace Engineering, Department of Industrial and Operations Engineering, University of Michigan, Ann Arbor, MI, United States","Drone delivery services are becoming increasingly available, but they introduce new consumer privacy risks. As a result of safety regulations that require drones to broadcast their locations, third-party observers may link customers to their purchases by following a delivery from vendor to customer. These privacy risks can be reduced with routing strategies that aggregate customer orders, at the potential cost of additional delivery wait times or fees. This study measures the importance of these privacy risks to delivery service customers, their willingness to pay for privacy, and how this differs across consumer groups and product types. We developed a discrete choice experiment and mode choice logit models using data from over 3700 U.S. consumers who chose between ground vehicle versus drone delivery across a range of privacy, delivery fee, and wait time options. Preferences were tested for various product types: take-out food, liquor store items, groceries, and prescription medications. Results show offering privacy enhancements significantly increased consumers’ likelihood of choosing drone delivery. Without privacy enhancements, when fees and wait times were the same, consumers chose ground vehicle 4 times more often than drone. Offering privacy for the drone option closed this gap. Yet preferences differ by demographic group. Males and frequent e-commerce users were more likely to prefer drone regardless of privacy, while privacy improvements had a significantly larger impact on females and younger consumers. We measured consumers’ value of privacy in both money and time. The value of privacy for medications delivery was about twice that for other product types. The value of privacy was then highest for liquor store items, then groceries, then take-out food. Our results can inform delivery service planning as well as contribute to a broader understanding of how consumers value privacy and methods to measure that valuation. © 2023 The Author(s)","Discrete choice experiment; Drone delivery; Mode choice; Panel mixed logit; Privacy; Willingness to pay","United States; Ground vehicles; Risk assessment; Sales; Delivery service; Discrete choice experiments; Drone delivery; Mixed logit; Mode choice; Panel mixed logit; Privacy; Privacy risks; Wait time; Willingness to pay; consumption behavior; discrete choice analysis; experimental study; preference behavior; service quality; technology adoption; transportation system; transportation technology; unmanned vehicle; willingness to pay; Drones",{"$nulls":4},"National Science Foundation, NSF, (2137195); National Aeronautics and Space Administration, NASA, (80NSSC20M0163, 80NSSC21M0071)","Funding text 1: The NASA University Leadership Initiative, United States (grants #80NSSC21M0071 and #80NSSC20M0163 ) provided funds to assist the authors with their research, but this article solely reflects the opinions and conclusions of its authors and not any NASA entity. GD was additionally supported by a National Science Foundation (NSF), United States Graduate Research Fellowship. MZL was partially supported by an NSF IUCRC Phase I: Center for Autonomous Air Mobility and Sensing (CAAMS) Award, United States No. 2137195 . ; Funding text 2: The NASA University Leadership Initiative, United States (grants #80NSSC21M0071 and #80NSSC20M0163) provided funds to assist the authors with their research, but this article solely reflects the opinions and conclusions of its authors and not any NASA entity. GD was additionally supported by a National Science Foundation (NSF), United States Graduate Research Fellowship. MZL was partially supported by an NSF IUCRC Phase I: Center for Autonomous Air Mobility and Sensing (CAAMS) Award, United States No. 2137195.","Arthur R., BrewDog starts using drones for beer deliveries, (2020); Bain & Company R., Spatial economics: The declining cost of distance, (2016); Bellan R., Zipline's drones to deliver medicine in Salt Lake City area, (2022); Ben-Akiva M.E., Lerman S.R., Lerman S.R., Et al., Discrete Choice Analysis: Theory and Application to Travel Demand, Vol. 9, (1985); Bierlaire M., A short introduction to PandasBiogeme. Technical report TRANSP-OR 200605. Transport and Mobility Laboratory, ENAC, EPFL, (2020); CBS News M., Amazon CEO unveils drone delivery concept, (2013); Cho S.-H., Kim M., Assessment of the environmental impact and policy responses for urban air mobility: A case study of seoul metropolitan area, J. Clean. 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Manag., 58, 2, (2021); Guggina D., We're Bringing the Convenience of Drone Delivery to 4 Million U.S. Households in Partnership with DroneUp, (2022); Haan J., Garrow L.A., Marzuoli A., Roy S., Bierlaire M., Are commuter air taxis coming to your city? A ranking of 40 cities in the United States, Transp. Res. C, 132, (2021); Hann I.-H., Hui K.-L., Lee S.-Y.T., Png I.P., Overcoming online information privacy concerns: An information-processing theory approach, J. Manag. Inf. Syst., 24, 2, pp. 13-42, (2007); Hawkins A.J., UPS and CVS will use drones to deliver prescriptions in Florida, (2020); Kelly H., Beer-delivery drone grounded by FAA | CNN Business, (2014); Lee D., Hess D.J., Heldeweg M.A., Safety and privacy regulations for unmanned aerial vehicles: A multiple comparative analysis, Technol. Soc., 71, (2022); Leon S., Chen C., Ratcliffe A., Consumers’ perceptions of last mile drone delivery, Int. J. Logist. Res. Appl., pp. 1-20, (2021); Levin A., Drone Deliveries From Drugstore Now a Reality in Virginia Town, (2019); Luppicini R., So A., A technoethical review of commercial drone use in the context of governance, ethics, and privacy, Technol. Soc., 46, pp. 109-119, (2016); McFadden D., Quantitative Methods for Analyzing Travel Behaviour of Individuals: Some Recent Developments: Technical Repor, (1977); Merkert R., Bliemer M.C., Fayyaz M., Consumer preferences for innovative and traditional last-mile parcel delivery, Int. J. Phys. Distrib. Logist. Manage., (2022); Nguyen D.H., De Leeuw S., Dullaert W., Foubert B.P., What is the right delivery option for you? Consumer preferences for delivery attributes in online retailing, J. Bus. Logist., 40, 4, pp. 299-321, (2019); Norberg P.A., Horne D.R., Horne D.A., The privacy paradox: Personal information disclosure intentions versus behaviors, J. Consumer Affairs, 41, 1, pp. 100-126, (2007); O'Brien M., Spatial economics: The declining cost of distance, (2021); Palinski M., Paying with your data. Privacy tradeoffs in ride-hailing services, Appl. Econ. Lett., 29, 18, pp. 1719-1725, (2022); Pew Research Center M., Demographic and economic trends in urban, suburban and rural communities, (2018); Pitney Bowes M., Pitney bowes parcel shipping index, (2021); Potoglou D., Palacios J.-F., Feijoo C., An integrated latent variable and choice model to explore the role of privacy concern on stated behavioural intentions in e-commerce, J. Choice Modell., 17, pp. 10-27, (2015); Rifan R., Adikariwattage V., Barros A.D., Identification of urban air logistics distribution network concepts, Transp. Res. Rec., (2022); Rose J.M., Bliemer M.C., Constructing efficient stated choice experimental designs, Transp. 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Syst. Res., 22, 2, pp. 254-268, (2011); U.S. Census Bureau J.Y., Quick facts, (2021); U.S. Census Bureau J.Y., Annual estimates of the resident population for selected age groups by sex for the United States: April 1, 2020 to july 1, 2021 (NC-EST2021-AGESEX), (2022); U.S. Census Bureau J.Y., Annual estimates of the resident population for the United States, regions, states, district of columbia, and puerto rico: April 1, 2020 to july 1, 2022 (NST-est2022-POP), (2022); U.S. Postal Service Office of Inspector General J.Y., Public perception of drone delivery in the United States (RARC-WP-17-001), (2016); Walker J.L., Ben-Akiva M., Bolduc D., Identification of parameters in normal error component logit-mixture (NECLM) models, J. Appl. Econometrics, 22, 6, pp. 1095-1125, (2007); Walker J.L., Wang Y., Thorhauge M., Ben-Akiva M., D-efficient or deficient? A robustness analysis of stated choice experimental designs, Theory and Decision, 84, pp. 215-238, (2018); Weber S., A step-by-step procedure to implement discrete choice experiments in qualtrics, Soc. Sci. Comput. Rev., 39, 5, pp. 903-921, (2021)","A. Berke; MIT Media Lab, Massachusetts Institute of Technology, Cambridge, United States; email: aberke@mit.edu",null,"Elsevier Ltd",{"$nulls":5},"0968090X",null,null,null,"English","Transp. Res. Part C Emerg. Technol.","Article","Final","All Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85174163934"]
["Christanto H.J.; Sutresno S.A.; Simi V.S.; Dewi C.; Dai G.","Christanto, Henoch Juli (58027737000); Sutresno, Stephen Aprius (58640008300); Simi, Valdi Septian (58770951000); Dewi, Christine (57210169726); Dai, Guowei (57795065000)","58027737000; 58640008300; 58770951000; 57210169726; 57795065000","ANALYSIS OF GAME THEORY IN MARKETING STRATEGIES OF TIKTOK AND INSTAGRAM",2023.0,"Journal of Theoretical and Applied Information Technology",101.0,22.0,null,7100.0,7109.0,9.0,1.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85180106953&partnerID=40&md5=dce6db35bd3c96b607f7aed1c1fa299f","Atma Jaya Catholic University of Indonesia, Information System Department, Faculty of Engineering, Jakarta, Indonesia; Satya Wacana Christian University, Faculty of Information and Technology, Salatiga, Indonesia; Agricultural Information Institute of CAAS, National Agriculture Science Data Center, Beijing, 100081, China","Christanto H.J., Atma Jaya Catholic University of Indonesia, Information System Department, Faculty of Engineering, Jakarta, Indonesia; Sutresno S.A., Atma Jaya Catholic University of Indonesia, Information System Department, Faculty of Engineering, Jakarta, Indonesia; Simi V.S., Atma Jaya Catholic University of Indonesia, Information System Department, Faculty of Engineering, Jakarta, Indonesia; Dewi C., Satya Wacana Christian University, Faculty of Information and Technology, Salatiga, Indonesia; Dai G., Agricultural Information Institute of CAAS, National Agriculture Science Data Center, Beijing, 100081, China","The rise of social media platforms like Instagram and Tiktok has had a profound impact on the business landscape, leading to a significant increase in e-commerce activities. This study focuses on examining the marketing strategies of Instagram and Tiktok using the 7P framework, which includes Product, Price, Promotion, Place, People, Physical evidence, and Process. Understanding these strategies is crucial for businesses aiming to enhance their online presence and drive sales.The study employed purposive sampling and collected data through questionnaires from individuals who frequently used Instagram and Tiktok for shopping. Validity was assessed using Karl Pearson's product-moment correlation, while reliability was evaluated using Cronbach's alpha. The data was then analyzed using Game Theory to identify optimal strategies.The findings highlight the significance of the \"Place\" element in the marketing strategies of Instagram and Tiktok. Both platforms prioritize user-friendly interfaces, secure and timely deliveries, and convenient product selection. The Game Theory analysis revealed a saddle point value of 2, indicating that the implemented strategies are effective in maximizing profits and minimizing losses. This research provides valuable insights into the marketing strategies of Instagram and Tiktok, demonstrating the relevance of the 7P framework and Game Theory in driving successful online businesses. By implementing these strategies, businesses can improve their competitiveness, attract a broader customer base, and thrive in the dynamic digital market. Understanding the effective marketing approaches employed by Instagram and Tiktok serves as a practical guide for aspiring entrepreneurs and existing businesses to navigate the realm of e-commerce and achieve sustainable growth. © 2023 Little Lion Scientific.","7P Framework; Game Theory; Marketing Strategies; Social Media",{"$nulls":7},"Dewi C., Christanto H. J., Combination of Deep Cross-Stage Partial Network and Spatial Pyramid Pooling for Automatic Hand Detection, Big Data and Cognitive Computing, 6, 3, (2022); Khan I., Do brands’ social media marketing activities matter? A moderation analysis, Journal of Retailing and Consumer Services, 64, (2022); Jacobson J., Gruzd A., Hernandez-Garcia A., Social media marketing: Who is watching the watchers?, Journal of Retailing and Consumer Services, 53, (2020); Chan I. C. C., Chen Z., Leung D., The more the better? Strategizing visual elements in social media marketing, Journal of Hospitality and Tourism Management, 54, pp. 268-289, (2023); Kurniawan Y., Cornelia V., Langitiska C., Young W., Anwar N., Johan, Analysis of The Effectiveness Of Social Media Instagram (A Case Study at Pom-Pom Café), 2021 International Conference on Information Management and Technology (ICIMTech), pp. 393-397, (2021); Shareef M. A., Mukerji B., Dwivedi Y. K., Rana N. P., Islam R., Social media marketing: Comparative effect of advertisement sources, Journal of Retailing and Consumer Services, 46, pp. 58-69, (2019); Image B., TikTok, TikTok, the time is now: Future directions in social media and body image, Body Image, 44, (2023); Dwivedi Y. K., Ismagilova E., Hughes D. L., Carlson J., Filieri R., Jacobson J., Jain V., Karjaluoto H., Kefi H., Krishen A. S., Kumar V., Rahman M. M., Raman R., Rauschnabel P. A., Rowley J., Salo J., Tran G. A., Wang Y., Setting the future of digital and social media marketing research: Perspectives and research propositions, International Journal of Information Management, 59, (2021); Kushwaha G. S., Agrawal S. R., An Indian Customer Surrounding 7P's of Service Marketing, Journal of Retailing and Consumer Services, 22, pp. 85-95, (2015); Kusumawati R. D., Oswari T., Utomo R. B., Kumar V., The Influence of 7P's of Marketing Mix on Buying Intention of Music Product in Indonesia, Procedia Engineering, 97, pp. 1765-1771, (2014); Astuti R., Silalahi R. L. R., Wijaya G. D. P., Marketing Strategy Based on Marketing Mix Influence on Purchasing Decisions of Malang Apples Consumers at Giant Olympic Garden Mall (MOG), Malang City, East Java Province, Indonesia, Agriculture and Agricultural Science Procedia, 3, pp. 67-71, (2015); Lin S.-M., Marketing Mix (7P) and Performance Assessment of Western Fast Food Industry in Taiwan: An Application by Associating DEMATEL and ANP, African Journal of Business Management, 5, 26, pp. 10634-10644, (2011); Othman B., He W., Huang Z., Xi J., Ramsey T., The effects on service value and customer retention by integrating after sale service into the traditional marketing mix model of clothing store brands in China, Environmental Technology & Innovation, 23, (2021); Oreagba O. T., Ogunnaike O. O., Kehinde O. 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C., Salleh K. M., Measuring the Validity and Reliability of Research Instruments, Procedia - Social and Behavioral Sciences, 204, pp. 164-171, (2015); Peeters M. J., Harpe S. E., Updating conceptions of validity and reliability, Research in Social and Administrative Pharmacy, 16, 8, pp. 1127-1130, (2020); Christmann A., Aelst S. V., Robust estimation of Cronbach's alpha, Journal of Multivariate Analysis, 97, 7, pp. 1660-1674, (2006); Taber K., The Use of Cronbach’s Alpha When Developing and Reporting Research Instruments in Science Education, pp. 1273-1296, (2018); Bolton G. E., Game theory’s role in role-playing, International Journal of Forecasting, 18, 3, pp. 353-358, (2002); Christanto H. J., Game Theory Analysis on Marketing Strategy Determination of KAI Access and Traveloka based on Usability of HCI (Human-Computer Interaction), Journal of Information Systems and Informatics, 4, 3, pp. 665-672, (2022); Chatterjee K., Lilien G. L., Game theory in marketing science uses and limitations, International Journal of Research in Marketing, 3, 2, pp. 79-93, (1986)",null,null,"Little Lion Scientific",{"$nulls":5},1.9928645E7,null,null,null,"English","J. Theor. Appl. Inf. Technol.","Article","Final",null,"Scopus","2-s2.0-85180106953"]
["Buldeo Rai H.; Mariquivoi J.; Schorung M.; Dablanc L.","Buldeo Rai, Heleen (57195135422); Mariquivoi, Joséphine (58492654000); Schorung, Matthieu (57190191307); Dablanc, Laetitia (15118955600)","57195135422; 58492654000; 57190191307; 15118955600","Dark stores in the City of Light: Geographical and transportation impacts of ‘quick commerce’ in Paris",2023.0,"Research in Transportation Economics",100.0,null,101333.0,null,null,null,3.0,"10.1016/j.retrec.2023.101333","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85165040959&doi=10.1016%2fj.retrec.2023.101333&partnerID=40&md5=aa601bfa085da3938b9eb522d1ad85f7","Logistics City Chair, University Gustave Eiffel, Paris, France","Buldeo Rai H., Logistics City Chair, University Gustave Eiffel, Paris, France; Mariquivoi J., Logistics City Chair, University Gustave Eiffel, Paris, France; Schorung M., Logistics City Chair, University Gustave Eiffel, Paris, France; Dablanc L., Logistics City Chair, University Gustave Eiffel, Paris, France","Food e-commerce has long remained a limited phenomenon, which only changed noticeably during the COVID-19 pandemic. Not only did more consumers take advantage of the options offered online, it also prompted the launch of many food delivery start-ups around the world. Quick commerce in particular, offering grocery deliveries within twenty minutes or less, attracted significant sums of venture capital, alongside criticism from urban administrations and communities for the nuisances caused. Indeed, to offer instant grocery deliveries, quick commerce companies rely on a tightknit network of small, store-like warehouses, called ‘dark stores’, and a readily available vehicle fleet and staff. While plenty of ink has flowed about the urban implications of quick commerce in the press, a thorough scientific analysis lacks. To objectify and quantify the nuisances generated by quick commerce, we study geographical dimensions and transportation activities in Paris. By means of a press review, expert interviews, field observations and a cartography, we detail a supply chain consisting of various facility types; demonstrate the transportation-intensity of dark stores consisting mainly of electric two-wheelers; problematize the public space consumed by the vehicles in particular; and contrast the ultimately limited network of dark stores relative to traditional food retail. © 2023 Elsevier Ltd","Dark stores; E-commerce; E-groceries; Instant deliveries; Omnichannel retail; Proximity logistics; Urban logistics; Urban planning",{"$nulls":7},"Allen J., Piecyk M., Cherrett T., Juhari M.N., McLeod F., Piotrowska M., Bates O., Bektas T., Cheliotis K., Friday A., Wise S., Understanding the transport and CO2 impacts of on-demand meal deliveries: A London case study, Cities, 108, (2021); Apur, Drive piéton, dark kitchens, dark stores - les nouvelles formes de la distribution alimentaire à Paris; Aziz S., Maltese I., Marcucci E., Gatta V., Benmoussa R., Irhirane E.H., Energy consumption and environmental impact of E-grocery: A systematic literature review, Energies, 15, 7289, (2022); Bjorgen A., Bjerkan K.Y., Hjelkrem O.A., E-groceries: Sustainable last mile distribution in city planning, Research in Transportation Economics, 87, (2021); Buldeo Rai H., Dark stores as post-pandemic omnichannel strategy: Implications for urban logistics, Routledge handbook of urban logistics, (2023); Buldeo Rai H., Verlinde S., Macharis C., Schoutteet P., Vanhaverbeke L., Logistics outsourcing in omnichannel retail: State of practice and service recommendations, International Journal of Physical Distribution & Logistics Management, 49, 3, pp. 267-286, (2019); Butler K., The truth about meal-kit freezer packs, Mother Jones, (2017); Chiffoleau Y., Boure M., Akermann G., Les circuits courts alimentaires à l'heure du numérique: Quels enjeux ? Une exploration, Innovations Agronomiques, 67, pp. 37-47, (2018); Dablanc L., Land use planning for a more sustainable urban freight, Handbook on city logistics and urban freight, (2023); Dablanc L., Aguilera A., Krier C., Cognez A., Chretien J., Louvet N., Étude sur les livreurs des plateformes de livraison instantanée à Paris et en petite couronne, (2022); Dablanc L., Morganti E., Arvidsson N., Woxenius J., Browne M., Saidi N., The rise of on-demand ‘ Instant Deliveries ’ in European cities, Supply Chain Forum: International Journal, (2017); Dannenberg P., Fuchs M., Riedler T., Wiedemann C., Digital transition by COVID-19 pandemic? The German food online retail, Tijdschrift voor Economische en Sociale Geografie, 111, 3, pp. 543-560, (2020); Davalos J., Levingston I., 15-Minute grocery delivery services hit reality, (2022); Delberghe C., Herbert R., Laizet F., Laubli D., Nyssens J.-A., Rastrollo B., Vallof R., Wachinger T., Navigating the market headwinds – the state of grocery retail 2022: Europe, (2022); Delvallee J., La livraison à domicile alimentaire pèse désormais plus que le drive ! LSA, (2021); El Hassani J., Quick commerce : Un marché à 122 millions d'euros en France. LSA; Fischer J., Appetite for rapid grocery delivery is growing around Europe, (2022); Gee I.M., Davidson F.T., Speetles B.L., Webber M.E., Deliver Me from food waste: Model framework for comparing the energy use of meal-kit delivery and groceries, Journal of Cleaner Production, 236, (2019); Gee I.M., Heard B.R., Webber M.E., Miller S.A., The future of food: Environmental lessons from E-commerce, Environmental Science & Technology, 54, pp. 14776-14784, (2020); Heard B.R., Bandekar M., Vassar B., Miller S.A., Comparison of life cycle environmental impacts from meal kits and grocery store meals, Resources, Conservation and Recycling, 147, pp. 189-200, (2019); Hu W., 15-Minute grocery delivery has come to N.Y.C. 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Étude de cas dans les Hauts-de-France, Géocarrefour, 93, (2019); Schaefer M., Ghost kitchens: Food delivery amid lockdown, (2020); Schorung M., Buldeo Rai H., Dablanc L., Flink, Getir, Cajoo Les « dark stores » et le « quick commerce » remodèlent les grandes villes, The Conversation, (2022); Seidel S., One goal, one approach? A comparative analysis of online grocery strategies in France and Germany, Case Studies on Transport Policy, 9, 4, pp. 1922-1932, (2021); Seidel S., Blanquart C., Ehrler V., Same-same but different? A comparison of food retail and distribution structures in France and Germany, Case Studies on Transport Policy, 4, 1, pp. 29-37, (2016); Srinivas S., Nishi B., Bradas T., Comparing the intensity of use of E-commerce facilities, (2019); Online food delivery practices in Paris, London and Geneva, (2022); Toilier F., Gardrat M., Routhier J.L., Bonnafous A., Freight transport modelling in urban areas: The French case of the FRETURB model, Case Studies on Transport Policy, 6, pp. 753-764, (2018); COVID-19 and E-commerce: A global review, (2021); Wagner L., Pinto C., Amorim P., On the value of subscription models for online grocery retail, European Journal of Operational Research, 294, 3, pp. 874-894, (2021); Wolf M., The case for 15-minute grocery delivery is questionable. So why did it raise so much capital?, The Spoon, (2022); Wollenburg J., Hubner A., Kuhn H., Trautrims A., From bricks-and-mortar to bricks-and-clicks: Logistics networks in omni-channel grocery retailing, International Journal of Physical Distribution & Logistics Management, 48, 4, pp. 415-438, (2018); Zaugg J., Les livreurs, le nouveau prolétariat chinois, Les Echos, (2021)","H. Buldeo Rai; Logistics City Chair, University Gustave Eiffel, Paris, France; email: heleen.buldeo.rai@vub.be",null,"Emerald Publishing",{"$nulls":5},7398859.0,null,null,null,"English","Res. Transp. Econ.","Article","Final",null,"Scopus","2-s2.0-85165040959"]
["Chou Y.-C.; Shao B.B.M.","Chou, Yen-Chun (36006181600); Shao, Benjamin B. M. (7103207904)","36006181600; 7103207904","An Empirical Study of Information Technology Capabilities to Enable Value Chain Activities and Interfaces",2023.0,"Information Systems Frontiers",25.0,4.0,null,1533.0,1547.0,14.0,2.0,"10.1007/s10796-022-10301-5","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85132173239&doi=10.1007%2fs10796-022-10301-5&partnerID=40&md5=604544a21c0b8d84c998497683e4e412","Department of Management Information Systems, College of Commerce, National Chengchi University, Taipei, 11605, Taiwan; Department of Information Systems, W. P. Carey School of Business, Arizona State University, Tempe, 85287, AZ, United States","Chou Y.-C., Department of Management Information Systems, College of Commerce, National Chengchi University, Taipei, 11605, Taiwan; Shao B.B.M., Department of Information Systems, W. P. Carey School of Business, Arizona State University, Tempe, 85287, AZ, United States","Information technology (IT) is a critical resource and asset for a firm’s internal operations and external interactions with outside stakeholders. This paper explores IT capabilities that enable a retailer’s value chain activities and interfaces with suppliers and customers. IT capabilities that enable the value chain activities of logistics and operations as well as those of marketing and sales are identified to examine how they influence a retailer’s implementation of value chain interfaces. Through the lens of organizational information processing theory (OIPT), we find that both IT capabilities and IT infrastructure play a pivotal role in implementing value chain interfaces but in distinctive ways. On the supplier-facing side, a retailer’s IT infrastructure and IT capabilities enabling logistics and operations are essential to its vendor-managed inventory (VMI) system. On the customer-facing side, a retailer’s e-commerce website requires IT infrastructure and IT capabilities that enable marketing and sales. Moreover, synergies are found downstream for e-commerce website that benefits from the integration of IT infrastructure and IT capabilities enabling logistics and operations while such synergies are not found upstream for VMI. This partial complementary effect is explicated by the sequential asymmetric information dependency of value chain activities. Finally, we discuss the implications of our findings for the research and practice of IT enablement and integration. © 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.","e-commerce website; IT capabilities; IT infrastructure; Organizational information processing theory; Value chain activities and interfaces; Vendor-managed inventory","Electronic commerce; Facings; Websites; E-commerce websites; Empirical studies; Information processing theories; Information technology capability; Information technology infrastructure; Organizational information processing; Organizational information processing theory; Value chain activity and interface; Value chains; Vendor managed Inventory; Sales",{"$nulls":6},"Albert T.C., Goes P.B., Gupta A., GIST: A model for design and management of content and interactivity of customer-centric web sites, MIS Quarterly, 28, 2, pp. 161-182, (2004); AlMarzouq M., Grover V., Thatcher J.B., Taxing the development structure of open source communities: An information processing view, Decision Support Systems, 80, 1, pp. 27-41, (2015); Babich V., Independence of capacity ordering and financial subsidies to risky suppliers, Manufacturing & Service Operations Management, 12, 4, pp. 583-607, (2010); Bharadwaj S., Bharadwaj A., Bendoly E., The performance effects of complementarities between information systems, marketing, manufacturing, and supply chain processes, Information Systems Research, 18, 4, pp. 437-453, (2007); Byers R.E., So K.C., A mathematical model for evaluating cross-sales policies in telephone service centers, Manufacturing & Service Operations Management, 9, 1, pp. 1-8, (2007); Byrd T.A., Pitts J.P., Adrian A.M., Davidson N.W., Examination of a path model relating information technology infrastructure with firm performance, Journal of Business Logistics, 29, 2, pp. 161-187, (2008); Cachon G.P., Fisher M., Supply chain inventory management and the value of shared information, Management Science, 46, 8, pp. 1032-1049, (2000); Cameron A.C., Miller D.L., A practitioner’s guide to cluster-robust inference, Journal of Human Resources, 50, 2, pp. 317-372, (2015); Cameron A.C., Trivedi P.K., Microeconometrics using STATA (2nd ed.), (2010); Cazier J., Shao B.B.M., Louis R., Value congruence, trust, and their effects on purchase intention and reservation price, ACM Transactions on Management Information Systems, 8, 4, pp. 1-28, (2017); Cetinkaya S., Lee C.Y., Stock replenishment and shipment scheduling for vendor-managed inventory systems, Management Science, 46, 2, pp. 217-232, (2000); Cheung K.L., Lee H.L., The inventory benefit of shipment coordination and stock rebalancing in a supply chain, Management Science, 48, 2, pp. 300-306, (2002); Corbett J., Using information systems to improve energy efficiency: Do smart meters make a difference?, Information Systems Frontiers, 15, 5, pp. 747-760, (2013); Dedrick J., Xu S.X., Zhu K.X., How does information technology shape supply chain relationships? 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A study of alliance performance in software outsourcing, Strategic Management Journal, 29, 7, pp. 769-780, (2008); Tsai J.Y., Raghu T.S., Shao B.B.M., Information systems and technology sourcing strategies of e-retailers for value chain enablement, Journal of Operations Management, 31, 6, pp. 345-362, (2013); Williams B.D., Roh J., Tokar T., Swink M., Leveraging supply chain visibility for responsiveness: The moderating role of internal integration, Journal of Operations Management, 31, 7-8, pp. 543-554, (2013); Wong C.Y., Boon-itt S., Wong C.W.Y., The contingency effects of environmental uncertainty on the relationship between supply chain integration and operational performance, Journal of Operations Management, 29, 6, pp. 604-615, (2011); Yao Y., Dong Y., Dresner M., Supply chain learning and spillovers in vendor managed inventory, Decision Sciences, 43, 6, pp. 979-1001, (2012); Zhang F.Q., Competition, cooperation, and information sharing in a two-echelon assembly system, Manufacturing & Service Operations Management, 8, 3, pp. 273-291, (2006); Zhu K., Kraemer K.L., E-commerce metrics for net-enhanced organizations: Assessing the value of e-commerce to firm performance in the manufacturing sector, Information Systems Research, 13, 3, pp. 275-295, (2002); Zhu K., Kraemer K.L., Post-adoption variations in usage and value of e-Business by organizations: Cross-country evidence from the retail industry, Information Systems Research, 16, 1, pp. 61-84, (2005)","B.B.M. Shao; Department of Information Systems, W. P. Carey School of Business, Arizona State University, Tempe, 85287, United States; email: ben.shao@asu.edu",null,"Springer",{"$nulls":5},1.3873326E7,null,null,null,"English","Inf. Syst. Front.","Article","Final",null,"Scopus","2-s2.0-85132173239"]
["Wirdiyanti R.; Yusgiantoro I.; Sugiarto A.; Harjanti A.D.; Mambea I.Y.; Soekarno S.; Damayanti S.M.","Wirdiyanti, Rosnita (57563847400); Yusgiantoro, Inka (57209510434); Sugiarto, Agus (58754785200); Harjanti, Aprillia Dwi (57564859600); Mambea, Indra Yudha (57219595403); Soekarno, Subiakto (55991048900); Damayanti, Sylviana Maya (56962728100)","57563847400; 57209510434; 58754785200; 57564859600; 57219595403; 55991048900; 56962728100","How does e-commerce adoption impact micro, small, and medium enterprises’ performance and financial inclusion? Evidence from Indonesia",2023.0,"Electronic Commerce Research",23.0,4.0,null,2485.0,2515.0,30.0,5.0,"10.1007/s10660-022-09547-7","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85127680876&doi=10.1007%2fs10660-022-09547-7&partnerID=40&md5=1d00acf78d9fc33ca262a43afb616244","Otoritas Jasa Keuangan, Jakarta, Indonesia; Institut Teknologi Bandung, School of Business and Management, Bandung, Indonesia","Wirdiyanti R., Otoritas Jasa Keuangan, Jakarta, Indonesia; Yusgiantoro I., Otoritas Jasa Keuangan, Jakarta, Indonesia; Sugiarto A., Otoritas Jasa Keuangan, Jakarta, Indonesia; Harjanti A.D., Otoritas Jasa Keuangan, Jakarta, Indonesia; Mambea I.Y., Institut Teknologi Bandung, School of Business and Management, Bandung, Indonesia; Soekarno S., Institut Teknologi Bandung, School of Business and Management, Bandung, Indonesia; Damayanti S.M., Institut Teknologi Bandung, School of Business and Management, Bandung, Indonesia","We study the adoption of technology by micro, small, and medium enterprises (MSMEs) in Indonesia to enhance their businesses and inclusivity in financial products and services. Using a survey of 338 MSMEs that adopt e-commerce across ten provinces in the country, we use two-stage least squares regression to empirically analyze the impact of e-commerce adoption on business performance and its effect on financial inclusion. We further investigate the effects of e-commerce on marketing by performing ordered logistic regression using indicators in ordinal scale. The results show that brand recognition and customer awareness improve performance significantly. Our findings also reveal that the performance improvements caused by e-commerce adoption will encourage better inclusion of MSMEs in the financial system through access and use of more diverse financial products and services. Furthermore, collaborations between financial institutions and e-commerce platforms will accelerate MSMEs’ financial inclusion in Indonesia. © 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.","Adoption; E-commerce; Financial inclusion (FI); Indonesia; MSMEs; Ordered logistic regression; Two-stage least squares","Finance; Adoption; E-commerce adoption; Financial inclusion; Financial inclusions; Indonesia; Logistics regressions; Micro-enterprises; Ordered logistic regression; Small-and-medium enterprise; Two stage least squares; Electronic commerce",{"$nulls":4},"School of Business and Management Institut Teknologi Bandung","We thank Oktofa Yudha Sudrajad, Patricia Marla Setiawati and Faqih Ahmad Muzakky from School of Business and Management Institut Teknologi Bandung (SBM-ITB) for their useful suggestion.",{"$cut":{"chars":17602,"head":"Afshar Jahanshahi A., Zhang S.X., Brem A., E-commerce for SMEs: Empirical insights from three countries, Journal of Small Business and Enterprise Development, 20, 4, pp. 849-865, (2013); Aghaunor L., Fotoh X., Factors affecting e-commerce adoption in Nigerian Banks, IT and Business Renewal, pp. 1-40, (2006); Agyekum F.K., Reddy K., Wallace D., Wellalage N.H., Does technological inclusion promote financial inclusion among SMEs? Evidence from South-East Asian (SEA) countries, Global Finance Journal, (2021); Al-Bakri A.A., Katsioloudes M.I., The factors affecting e-commerce adoption by Jordanian SMEs, Management Research Review, 38, 7, pp. 726-749, (2015); Aldrich H., Auster E.R., Even dwarfs started small: Liabilities of age and size and their strategic implications, Research in Organizational Behaviour, 8, pp. 165-198, (1986); Allen F., Demirguc-Kunt A., Klapper L., Martinez Peria M., The foundations of financial inclusion: Understanding ownership and use of formal accounts, Journal of Financial Intermediation, 27, pp. 1-30, (2016); Babbitt L.G., Brown D., Mazaheri N., Gender, entrepreneurship, and the formal–informal dilemma: Evidence from Indonesia, World Development, 72, pp. 163-174, (2015); Bakar H.O., Sulong Z., The role of financial sector on economic growth: Theoretical and empirical literature reviews analysis, Journal of Global Economics, 6, (2018); Balasubramanian S., Mail versus mall: A strategic analysis of competition between direct marketers and conventional retailers, Marketing Science, 17, 3, pp. 181-195, (1998); Barney J.B., Gaining and Sustaining Competitive Advantage, (2002); Barney J., Firm resources and sustained competitive advantage, Journal of Management, 17, pp. 99-120, (1991); Barua A., Konana P., Whinston A.B., Yin F., An empirical investigation of net-enabled business value, MIS Quarterly: Management Information Systems, 28, 4, pp. 585-620, (2004); Beck T., Demirguc-Kunt A., Small and medium-size enterprises: Access to finance as a growth constraint, Journal of Banking and Finance, 30, 11, pp. 2931-2943, (2006); Benjamin R., Wigand R., Electronic markets and virtual value chains on the information superhighway, Sloan Management Review, 36, 2, pp. 62-73, (1995); Bongomin G.O.C., Munene J.C., Ntayi J.M., Malinga C.A., Nexus between financial literacy and financial inclusion, International Journal of Bank Marketing, 36, 7, pp. 1190-1212, (2018); Borges M., Hoppen N., Luce F.B., Information technology impact on market orientation in e-business, Journal of Business Research, 62, 9, pp. 883-890, (2009); Carvalho M., Mamede H.S., The impact of e-commerce on the success of microenterprise retail sector of the Pinhal Interior Norte sub-region of Portugal, Procedia Computer Science, 138, pp. 571-579, (2018); Chatterjee S., Dutta Gupta S., Upadhyay P., Technology adoption and entrepreneurial orientation for rural women: Evidence from India, Technological Forecasting and Social Change, (2020); Chau T., Deng H., (2018). Critical Determinants for Mobile Commerce Adoption in Vietnamese Smes: A Preliminary Study. In, (2018); Choshin M., Ghaffari A., An investigation of the impact of effective factors on the success of e-commerce in small- and medium-sized companies, Computers in Human Behavior, 66, pp. 67-74, (2017); Ciborra C.U., Teams, markets and systems: Business innovation and information technology, (1993); Clayton T., Waldron K., E-commerce adoption and business impact: A progress report, Economic Trends, 591, 2, pp. 33-40, (2003); Coleman S., Cotei C., Farhat J., A resource-based view of new firm survival: New perspectives on the role of industry and exit route, Journal of Developmental Entrepreneurship, (2013); Dai Y., Gregory V., Eusin J., Gary B., Risk assessment in e-commerce: How sellers’ photos, reputation scores, and the stake of a transaction influence buyers’ purchase behavior and information processing, Computers in Human Behavior, 84, pp. 342-351, (2018); Daniel E.M., Grimshaw D.J., An exploratory comparison of electronic commerce adoption in large and small enterprises, Journal of Informati"}},"R. Wirdiyanti; Otoritas Jasa Keuangan, Jakarta, Indonesia; email: rosnita_w@ojk.go.id",null,"Springer",{"$nulls":5},1.3895753E7,null,null,null,"English","Electron. Commer. Res.","Article","Final",null,"Scopus","2-s2.0-85127680876"]
["Liu H.; Xu T.; Jing S.; Liu Z.; Wang S.","Liu, He (57204158665); Xu, Tianting (58155180100); Jing, Shuai (42262145600); Liu, Zhidong (55714737900); Wang, Shouyang (57918955100)","57204158665; 58155180100; 42262145600; 55714737900; 57918955100","The interplay between logistics strategy and platform's channel structure design in B2C platform market",2023.0,"European Journal of Operational Research",310.0,2.0,null,812.0,833.0,21.0,9.0,"10.1016/j.ejor.2023.02.043","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85150830477&doi=10.1016%2fj.ejor.2023.02.043&partnerID=40&md5=0b3e614da320624cd67905b77715c609","School of Management Science and Engineering, Central University of Finance and Economics, Beijing, Changping District, 102206, China; Academy of Mathematics and Systems Science, Chinese Academy of Sciences, 55 Zhongguancun East Road, Beijing, Haidian District, 100090, China; School of Economics and Management, University of Chinese Academy of Sciences, 80 Zhongguancun East Road, Beijing, Haidian District, 100090, China; School of Entrepreneurship and Management, ShanghaiTech University, 393 Middle Huaxia Road, Shanghai, Pudong, 201210, China","Liu H., School of Management Science and Engineering, Central University of Finance and Economics, Beijing, Changping District, 102206, China; Xu T., School of Management Science and Engineering, Central University of Finance and Economics, Beijing, Changping District, 102206, China, School of Economics and Management, University of Chinese Academy of Sciences, 80 Zhongguancun East Road, Beijing, Haidian District, 100090, China; Jing S., School of Management Science and Engineering, Central University of Finance and Economics, Beijing, Changping District, 102206, China; Liu Z., School of Management Science and Engineering, Central University of Finance and Economics, Beijing, Changping District, 102206, China; Wang S., Academy of Mathematics and Systems Science, Chinese Academy of Sciences, 55 Zhongguancun East Road, Beijing, Haidian District, 100090, China, School of Economics and Management, University of Chinese Academy of Sciences, 80 Zhongguancun East Road, Beijing, Haidian District, 100090, China, School of Entrepreneurship and Management, ShanghaiTech University, 393 Middle Huaxia Road, Shanghai, Pudong, 201210, China","B2C platforms choose different channel choices and logistics strategies and many platforms changed their channel structures after building platforms’ self-supporting logistics. With the platform's logistics, some manufacturers adopt the platform's logistics while others do not. In this paper, we develop a game-theoretic model consisting of a platform, a manufacturer, and consumers to investigate the interplay between the logistics strategy and the platform's channel choice. In the first stage, the platform decides whether to build its self-supporting logistics and its optimal logistics level. In the second stage, the platform chooses among the marketplace channel, the reselling channel and the hybrid channel. In the third stage, the manufacturer chooses whether to adopt the platform's logistics if its store exists in the market (under the marketplace or hybrid channel). In the fourth and fifth stages, the manufacturer and the platform make pricing strategies. The results indicate the interplay between the two types of strategies. First, when the platform logistics level is much higher than the third-party logistics, the platform's optimal channel choice is to operate the hybrid channel. Second, the platform's channel choice affects the manufacturer's logistics provider. When the platform logistics level is slightly higher than the third-party logistics level, the manufacturer chooses to adopt the platform's logistics under the marketplace channel and not adopt it under the hybrid channel. We also find that the platform chooses to build its self-supporting logistics when the third-party logistics level is in the low or medium ranges. © 2023 Elsevier B.V.","Channel structure; E-commerce; Game theory; Horizontal competition; Logistics strategy","Commerce; Outsourcing; Building platforms; Channel structures; Game-theoretic model; Horizontal competition; Hybrid channels; Logistics platforms; Logistics strategy; Pricing strategy; Structure design; Third-party logistics; Game theory",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (71988101, 72101281); Central University of Finance and Economics, CUFE, (21XXJC010)","We thank the Editor and the three anonymous reviewers very much for their constructive comments and suggestions, which help us to significantly improve the paper. This work was supported by the National Natural Science Foundation of China [grants number 72101281 , 71988101 ]; and the Emerging Interdisciplinary Project of CUFE [grant number 21XXJC010]. ","Abhishek V., Jerath K., Zhang Z.J., Agency selling or reselling? 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Examining platform owners’ entry into complementors spaces, Journal of Economics and Management Strategy, 28, pp. 23-28, (2019); Zhu F., Liu Q., Competing with complementors: An empirical look at amazon. com, Strategic Management Journal, 39, pp. 2618-2642, (2018)","S. Jing; School of Management Science and Engineering, Central University of Finance and Economics, Changping District, Beijing, 102206, China; email: jing@cufe.edu.cn",null,"Elsevier B.V.",{"$nulls":5},3772217.0,null,"EJORD",null,"English","Eur J Oper Res","Article","Final",null,"Scopus","2-s2.0-85150830477"]
["Anshari M.; Hamdan M.","Anshari, Muhammad (24536991300); Hamdan, Mahani (56573594700)","24536991300; 56573594700","Enhancing e-government with a digital twin for innovation management",2023.0,"Journal of Science and Technology Policy Management",14.0,6.0,null,1055.0,1065.0,10.0,4.0,"10.1108/JSTPM-11-2021-0176","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135693586&doi=10.1108%2fJSTPM-11-2021-0176&partnerID=40&md5=c22bc2297c357777b09fe1e20c9625f9","Institute of Policy Studies, Universiti Brunei Darussalam and School of Business and Economics, Universiti Brunei Darussalam, Bandar Seri Begawan, Brunei Darussalam","Anshari M., Institute of Policy Studies, Universiti Brunei Darussalam and School of Business and Economics, Universiti Brunei Darussalam, Bandar Seri Begawan, Brunei Darussalam; Hamdan M., Institute of Policy Studies, Universiti Brunei Darussalam and School of Business and Economics, Universiti Brunei Darussalam, Bandar Seri Begawan, Brunei Darussalam","Purpose: The implementation of digital twin in e-government services will become the future of public service delivery. It has a great promise for significantly optimizing e-government service delivery in public services because digital twin can be leveraged to achieve value co-creation, which can be turned for innovation and new knowledge creation. The purpose of this study is to fill a knowledge gap in the domain of e-government with digital twin enabled. Design/methodology/approach: This study examined the concept of digital twins in the context of e-government for innovation management. This research applied exploratory research discussing a dynamic and interpretive model that examines the main factors to consider when developing digital twins for the Fourth Industrial Revolution’s integration of e-government services. This study begins with a thorough assessment and then evaluates the results to propose a model that would be used as a benchmark for future research. Secondary data was gathered from a variety of previously published primary research sources, including peer-reviewed journals, case studies, periodicals, newspapers and books. Findings: E-government with digital twin platform will become increasingly integral to business or public value creation and can be managed individually as people and organizations expect much greater value for their well-being that is linked to a number of better outcomes. E-government with digital twin will no longer to be seen as a static web service but the next enabling platform to offer a comprehensive digital advisory for each and every user. The digital twin’s goal is to extract all of a user’s digital activity processes and thoroughly analyze them across all of e-services. When there are crucial issues or problems that need to be alerted to the (physical) user, the digital twin will present options, solutions and recommendations based on the entire gathered data continuum. Research limitations/implications: This study is conducted to provide a better understanding of the digital twin’s impact on public service delivery in the future. When it comes to e-government, a digital twin is a digital representation of an individual with the ability to integrate e-government services (such as e-citizenship, e-employment, e-participation, e-business, e-commerce, e-health, e-learning, e-regulation, e-entertainment and so on) with nearly real-time data and advanced analytics. Individuals will be able to improve, discover, foresee and make better and faster decisions as a result of the digital twin. The proposed model shows a future scenario for e-government services, in which the key principle of Industrial Revolution 4.0, Cyber Physical Systems, is accommodated by digital twins. Originality/value: This study provides academics, policymakers and practitioners in the fields of technology, public and/or private service delivery and public policy, with the opportunity to define priorities, processes and outcomes of e-government services and thereby benefit more directly from the findings of the study. This study presents some novel insights into e-government services the use of digital twins to optimize public service delivery. © 2022, Emerald Publishing Limited.","Digital twin; E-government; Internet of Thing (IoT); Public service delivery; Robo advisory",{"$nulls":7},"Ahad A.D., Anshari M., Razzaq A., Domestication of smartphones among adolescents in Brunei Darussalam, International Journal of Cyber Behavior, Psychology and Learning (IJCBPL), 7, 4, pp. 26-39, (2017); Ahmad M., Hasibuan Z.A., Government services integration based on cloud technology, Proceedings of the 14th International Conference on Information Integration and Web-based Applications and Services, pp. 303-306, (2012); Almunawar M.N., Low K.C.P., Habibur-Rahman M., Mohiddin F., From e-government to e-governance: winning people’s trust, E-Governance and Civic Engagement: Factors and Determinants of E-Democracy, pp. 613-635, (2012); Anshari M., Almunawar M.N., Adopting open innovation for SMEs and industrial revolution 4.0, Journal of Science and Technology Policy Management, 13, 2, (2021); Anshari M., Lim S.A., E-government with big data enabled through smartphone for public services: possibilities and challenges, International Journal of Public Administration, 40, 13, pp. 1143-1158, (2017); Anshari M., Almunawar M.N., Masri M., Digital twin: financial technology’s next frontier of robo-advisor, Journal of Risk and Financial Management, 15, 4, (2022); Aujoulat I., d' Hoore W., Deccache A., Patient empowerment in theory and practice: polysemy or cacophony?, Patient Education and Counseling, 66, 1, pp. 13-20, (2007); de Pablos P.O., Edvinsson L., Intellectual Capital in the Digital Economy, (2020); de Pablos P.O., Preface: intellectual capital, efficiency and organisational performance: some lessons, Int. J. Learning and Intellectual Capital, 18, 3, (2021); de Pablos P.O., Knowledge management and intellectual capital in the digital economy, Int. J. Learning and Intellectual Capital, 19, 1, (2022); Industry 4.0 and the digital twin manufacturing meets its match, (2017); Deng T., Zhang K., Shen Z.J.M., A systematic review of a digital twin city: a new pattern of urban governance toward smart cities, Journal of Management Science and Engineering, 6, 2, pp. 125-134, (2021); Erol T., Mendi A.F., Dogan D., Digital transformation revolution with digital twin technology, 2020 4th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT)IEEE, pp. 1-7, (2020); Fawcett S.B., White G.W., Balcazar F., Suarez-Balcazar Y., Mathews R., Paine A., Seekins T., Smith J., A contextual-behavioral model of empowerment: case studies involving people with disabilities, American Journal of Community Psychology, 22, 4, pp. 471-496, (1994); Garfinkel J., Gartner identifies the top 10 strategic technology trends, for 2019, (2019); Gibson C.H., A concept analysis of empowerment, Journal of Advanced Nursing, 16, 3, pp. 354-361, (1991); Grieves M., Digital twin: manufacturing excellence through virtual factory replication, White Paper, 1, pp. 1-7, (2014); Hasmawati F., Samiha Y.T., Razzaq A., Anshari M., Understanding nomophobia among digital natives: characteristics and challenges, Journal of Critical Reviews, 7, 13, pp. 122-131, (2020); Hertzum M., Breakdowns in collaborative information seeking: a study of the medication process, Information Processing and Management, 46, 6, (2010); Kritzinger W., Karner M., Traar G., Henjes J., Sihn W., Digital twin in manufacturing: a categorical literature review and classification, IFAC-PapersOnLine, 51, 11, pp. 1016-1022, (2018); McWilliam C.L., Stewart M., Brown J.B., McNair S., Desai K., Patterson M.L., Del Maestro N., Pittman B.J., Creating empowering meaning: an interactive process of promoting health with chronically ill older Canadians, HealthPromotInt, 12, pp. 111-123, (1997); Digital Twin Market by Technology, Type (Product, Process, and System), Application (Predictive Maintenance, and Others), Industry (Aerospace and Defense, Automotive and Transportation, Healthcare, and others), and Geography-Global Forecast to 2026, (2020); Mulyani M.A., Razzaq A., Sumardi W.H., Anshari M., Smartphone adoption in mobile learning scenario, 2019 International Conference on Information Management and Technology (ICIMTech), 1, pp. 208-211, (2019); O'Malley A.S., Grossman J.M., Cohen G.R., Kemper N.M., Pham H.H., Are electronic medical records helpful for care coordination? Experiences of physician practices, Journal of General Internal Medicine, 25, 3, (2010); Obi T., Iwasaki N., Smart government using digital twin in Japan, 2021 International Conference on ICT for Smart Society (ICISS), pp. 1-4, (2021); Perkins D.D., Zimmerman M.A., Empowerment theory, research, and application, American Journal of Community Psychology, 23, 5, pp. 569-579, (1995); Razzaq A., Samiha Y.T., Anshari M., Smartphone habits and behaviors in supporting students self-efficacy, International Journal of Emerging Technologies in Learning, 13, 2, (2018); Richard L.S., Ronald M.E., Lessons from theory and research on Cl inician-patient communication, Health Behavior and Health Education; Theory, Research, and Practice, 11, pp. 236-269, (2008); Schrotter G., Hurzeler C., The digital twin of the city of Zurich for urban planning, PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science, 88, 1, pp. 99-112, (2020); Singh M., Fuenmayor E., Hinchy E.P., Qiao Y., Murray N., Devine D., Digital twin: origin to future, Applied System Innovation, 4, 2, (2021); Digital twin use cases and application, (2021); Tao F., Zhang M., Nee A.Y.C., Applications of digital twin, Digital Twin Driven Smart Manufacturing, pp. 29-62, (2019); United Nations E-Government Survey 2014, (2014); Wan L., Nochta T., Schooling J.M., Developing a city-level digital twin-propositions and a case study, International Conference on Smart Infrastructure and Construction 2019 (ICSIC) Driving Data-Informed Decision-Making, pp. 187-194, (2019)","M. Anshari; Institute of Policy Studies, Universiti Brunei Darussalam and School of Business and Economics, Universiti Brunei Darussalam, Bandar Seri Begawan, Brunei Darussalam; email: anshari.ali@ubd.edu.bn",null,"Emerald Publishing",{"$nulls":5},2.053462E7,null,null,null,"English","J. Sci. Technol. Policy Manage.","Article","Final",null,"Scopus","2-s2.0-85135693586"]
["Teck S.; Vansteenwegen P.; Dewil R.","Teck, Sander (57204391534); Vansteenwegen, Pieter (24067941800); Dewil, Reginald (37097079500)","57204391534; 24067941800; 37097079500","An efficient multi-agent approach to order picking and robot scheduling in a robotic mobile fulfillment system",2023.0,"Simulation Modelling Practice and Theory",127.0,null,102789.0,null,null,null,1.0,"10.1016/j.simpat.2023.102789","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85162140603&doi=10.1016%2fj.simpat.2023.102789&partnerID=40&md5=848fc8f3f7609f20bb573229ec594dfd","Department of Mechanical Engineering, Centre for Industrial Management, KU Leuven, Celestijnenlaan 300, Leuven, 3001, Belgium; KU Leuven Institute for Mobility – CIB, KU Leuven, Belgium","Teck S., Department of Mechanical Engineering, Centre for Industrial Management, KU Leuven, Celestijnenlaan 300, Leuven, 3001, Belgium, KU Leuven Institute for Mobility – CIB, KU Leuven, Belgium; Vansteenwegen P., Department of Mechanical Engineering, Centre for Industrial Management, KU Leuven, Celestijnenlaan 300, Leuven, 3001, Belgium, KU Leuven Institute for Mobility – CIB, KU Leuven, Belgium; Dewil R., Department of Mechanical Engineering, Centre for Industrial Management, KU Leuven, Celestijnenlaan 300, Leuven, 3001, Belgium","This paper presents a Multi-Agent System (MAS) for optimizing the scheduling and routing of mobile robots and human pickers in a Robotic Mobile Fulfillment System (RMFS). The RMFS is a system designed for e-commerce warehousing where autonomous mobile robots are used to fetch inventory pods, also referred to as racks, from the storage area and transport them to the appropriate picking station where human pickers pick the required number of goods. The system requires the solution of several hard decision problems like: the order-to-picking station assignment and sequencing, the pod selection, and the multi-robot task allocation. The proposed solution approach employs decentralized scheduling mechanisms, i.e. auctions and dispatching rules, to communicate and distribute picking and retrieval tasks among the agents. Various dispatching rules are identified and analyzed over a wide set of problem instances of the RMFS with varying numbers of mobile robots, picking stations, and order sizes. The proposed MAS framework shows promising results and requires only a fraction of the computation time compared to a centralized scheduling algorithm. The MAS also includes both unidirectional and bidirectional lanes. Although additional complexity in collision avoidance is introduced when using bidirectional lanes, it allows for better system performance. © 2023 Elsevier B.V.","Distributed control; Logistics; Multi-agent system; Robotic mobile fulfillment system; Scheduling and routing","Distributed parameter control systems; Mobile agents; Mobile commerce; Mobile robots; Scheduling algorithms; Autonomous Mobile Robot; Dispatching rules; Distributed-control; E- commerces; Hard decisions; Multi-agent approach; Order-picking; Robotic mobile fulfillment system; Scheduling and routing; Storage area; Multi agent systems",{"$nulls":4},"Fonds Wetenschappelijk Onderzoek, FWO, (1S97322)","This work was supported by the Research Foundation – Flanders ( FWO ) under Grant 1S97322 .","Gruchmann T., Mies A., Neukirchen T., Gold S., Tensions in Sustainable Warehousing: including the Blue-Collar Perspective on Automation and Ergonomic workplace design, J. Bus. Econ., 91, 2, pp. 151-178, (2020); Truxillo D., Cadiz D., Hammer L., Supporting the aging workforce: a review and recommendations for workplace intervention research, Ann. Rev. Org. Psych. Org. Beh., 2, 1, pp. 351-381, (2015); Le-anh T., de Koster M.B.M., A review of design and control of automated guided vehicle systems, Eur. J. Oper. Res., 171, pp. 1-23, (2016); Luo L., Zhao N., (2022); Merschformann M., Lamballais T., de Koster M.B.M., Suhl L., Decision rules for robotic mobile fulfillment systems, Oper. Res. Persp., 6, (2019); Van Lon R., Holvoet T., When do agents outperform centralized algorithms?: A systematic empirical evaluation in logistics, Aut. Agents Multi-Agent Sys., 31, 6, pp. 1578-1609, (2017); Erol R., Sahin C., Baykasoglu A., Kaplanoglu V., A multi-agent based approach to dynamic scheduling of machines and automated guided vehicles in manufacturing systems, Appl. S. Comp., 12, 6, pp. 1720-1732, (2012); Chen K., Chen C., Applying multi-agent technique in multi-section flexible manufacturing system, Exp. Sys. Appl., 37, 11, pp. 7310-7318, (2012); Macron E., Chaabane S., Sallez Y., Bonte T., A multi-agent system based on reactive decision rules for solving the caregiver routing problem in home health care, Sim. Model. Pract. Theory, 74, pp. 134-151, (2017); Bozer Y., Aldarondo F., A simulation-based comparison of two goods-to-person order picking systems in an online retail setting, Int. J. Prod. Res., 56, 11, pp. 3838-3858, (2018); Sahin C., Demirtas M., Erol R., Baykasoglu A., Kaplanoglu V., A multi-agent based approach to dynamic scheduling with flexible processing capabilities, J. Int. Manuf., 28, pp. 1827-1845, (2017); Giordani S., Lujak M., Martinelli F., A distributed multi-agent production planning and scheduling framework for mobile robots, Comp. Ind. Eng., 64, pp. 19-30, (2013); De Ryck M., Pissoort D., Holvoet T., Demeester E., Decentral task allocation for industrial AGV-systems with resource constraints, J. Manuf. Sys., 59, pp. 310-319, (2021); Boysen N., Briskorn D., Emde S., Parts-to-picker based order processing in a rack-moving mobile robots environment, Eur. J. Oper. Res., 262, 2, pp. 550-562, (2017); Li X., Yang X., Zhang C., Qi M., A simulation study on the robotic mobile fulfillment system in high-density storage warehouses, Sim. Model. Practice and Theory, 122, (2021); Zhuang Y., Zhou Y., Yuan Y., Hu X., Hassini E., Order Picking Optimization With Rack-Moving Mobile Robots and Multiple Workstations, Eur. J. Oper. Res., 300, pp. 527-544, (2022); Yang X., Hua G., Hu L., Cheng T., Huang A., Joint optimization of order sequencing and rack scheduling in the robotic mobile fulfilment system, Comp. Oper. Res., 135, (2021); Valle A., Beasley J., Order allocation, rack allocation and rack sequencing for pickers in a mobile rack environment, Comp. Oper. Res., 125, (2021); Teck S., Dewil R., A Bi-level memetic algorithm for the integrated order and vehicle scheduling in a RMFS, Appl. S. Comp., 121, (2022); Teck S., Dewil R., Optimization models for scheduling operations in robotic mobile fulfillment systems, Appl. Math. Model., 111, pp. 270-287, (2022); Xie L., Thieme N., Krenzler R., Li H., Introducing split orders and optimizing operational policies in robotic mobile fulfillment systems, Eur. J. Oper. Res., 288, pp. 80-97, (2021); Khamis A., Hussein A., Elmogy A., A Multi-robot Task Allocation: a Review of the State-of-the-art, Coop. Rob. Sens. Netw., 8, pp. 30-51, (2015); De Ryck M., Versteyhe M., Debrouwere F., Automated guided vehicle systems, state-of-the-art control algorithms and techniques, J. Manuf. 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Res., 256, 3, pp. 976-990, (2017); Enright J., Wurman P.R., Optimization and coordinated autonomy in mobile fulfillment systems, Proceedings of the AAAI workshop on automated action planning for autonomous mobile robots, pp. 33-38, (2011); Meyer R., pp. 3-16, (2014); Jin B., Zhu W., Lim A., Solving the container relocation problem by an improved greedy look-ahead heuristic, Eur. J. Oper. Res., 240, 3, pp. 837-847, (2014); Potvin J., Rousseau J., A parallel route building algorithm for the vehicle routing and scheduling problem with time windows, Eur. J. Oper. Res., 66, 3, pp. 331-340, (1993); Chen Z., Alonso-Mora J., Bai X., Harabor D., Stuckey P., Integrated task assignment and path planning for capacitated multi-agent pickup and delivery, IEEE Robot. Autom. Lett., 6, 3, pp. 5816-5823, (2021); Hemmelmayr V., Cordeau J., Crainic T., An adaptive large neighborhood search heuristic for two-echelon vehicle routing problems arising in city logistics, Comp. Oper. Res., 39, 12, pp. 3215-3228, (2012); Helsgaun K., An extension of the Lin-Kernighan-Helsgaun TSP solver for constrained traveling salesman and vehicle routing problems, Techn. Rep., (2017); Lin S., Kernighan W., An effective heuristic algorithm for the travelling-salesman problem, Oper. Res., 21, pp. 498-516, (1973); Zhang Z., Guo Q., Chen J., Yuan P., Collision-free route planning for multiple AGVs in an automated warehouse based on collision classification, IEEE Access, 6, pp. 26022-26035, (2018); Zhong M., Yang Y., Dessouky Y., Postolache O., Multi-AGV scheduling for conflict-free path planning in automated container terminals, Comp. Ind. Eng., 142, (2020); Qin H., Xiao J., Ge D., Xin L., Gao J., He S., Hu H., JD.com: operations research algorithms drive intelligent warehouse robots to work, INFORMS J. Appl. Anal., 52, 1, pp. 42-55, (2022)","S. Teck; Department of Mechanical Engineering, Centre for Industrial Management, Leuven, KU Leuven, Celestijnenlaan 300, 3001, Belgium; email: sander.teck@kuleuven.be",null,"Elsevier B.V.",{"$nulls":5},"1569190X",null,null,null,"English","Simul. Model. Pract. Theory","Article","Final",null,"Scopus","2-s2.0-85162140603"]
["Peng J.","Peng, Juanjuan (58616087400)",5.86160874E10,"Effectiveness of Mixed Fuzzy Time Window Multi-objective Allocation in E-Commerce Logistics Distribution Path",2023.0,"International Journal of Computational Intelligence Systems",16.0,1.0,156.0,null,null,null,0.0,"10.1007/s44196-023-00338-y","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85172141557&doi=10.1007%2fs44196-023-00338-y&partnerID=40&md5=fe1f8c13d20ac17649d9ff85410c71c6","School of Economics and Management, Jiangsu Vocational College of Finance and Economics, Huai’an, 223003, China","Peng J., School of Economics and Management, Jiangsu Vocational College of Finance and Economics, Huai’an, 223003, China","The study of logistics distribution network under e-commerce environment is conducive to the establishment of efficient logistics distribution system, but also to promote the further development of e-commerce and improve social benefits of great significance. This study considers multiple fuzzy factors and introduces a customer fuzzy time window with variable coefficients, establishes a multi-objective set allocation integrated multi-level location path planning model, and proposes an archive type multi-objective simulated annealing improvement algorithm based on master–slave parallel framework embedded taboo search to solve the model. Tabu search and large-scale neighborhood algorithm are used to solve the initial solutions of the first level network and the second level network respectively, and archival reception criterion is introduced to deal with the multi-objective problem. The results of the proposed algorithm for the two-level site-routing problem are less than 6% different from the internationally known optimal solution. The master–slave parallel computing framework improves the efficiency of the algorithm by about 6.38%. The experimental results prove the effectiveness and necessity of the improved optimization. In addition, this study simulates the site-routing problem model constructed by the study by extending the data of standard examples. The experimental results prove the correctness and reference significance of the multilevel site-routing problem model with multiple fuzzy factors. © 2023, Springer Nature B.V.","Aggregation integration; Large-scale neighborhood search; Master–slave parallel computing framework; Mixed fuzzy time window; Site-path problem","Electric power distribution; Electronic commerce; Motion planning; Simulated annealing; Aggregation integration; Computing frameworks; Large-scale neighborhood search; Large-scales; Master slave; Master–slave parallel computing framework; Mixed fuzzy time window; Neighborhood search; Parallel com- puting; Path problems; Site-path problem; Time windows; Tabu search",{"$nulls":4},"Philosophy and Social Science research project of Jiangsu Universities, (2021SJYB1985)","The research is supported by Philosophy and Social Science research project of Jiangsu Universities in 2022, “Research on Effectiveness, deficiency and optimization path of digitalized development of new agricultural management subjects” (No. 2021SJYB1985). ","Xin C., Wang J., Wang Z., Wu C.H., Nawaz M., Tsai S.B., Reverse logistics research of municipal hazardous waste: a literature review, Environ. Dev. Sustain., 24, 2, pp. 1495-1531, (2022); Deineko E., Thaller C., Liedtke G., Assessing long-term impacts of automation on freight transport and logistics networks: large-scale LRP integrated in microscopic transport simulation, Transp. Res. Procedia., 62, pp. 624-631, (2022); Tian T., Wang Y., Research on emergency logistics location-routing problem for public health emergencies, Acad. J. Manag. Soc. Sci., 2, 1, pp. 116-118, (2023); Zhang C., Zhao Y., Leng L., A hyper-heuristic algorithm for time-dependent green location routing problem with time windows, IEEE Access, 8, pp. 83092-83104, (2020); Sholichah A.N., Yuniaristanto Y., Suletra I.W., Location routing problem with consideration of CO2 emissions cost: a case study, J. Teknik Industri., 21, 2, pp. 225-234, (2020); Sutrisno H., Yang C.L., A two-echelon location routing problem with mobile satellites for last-mile delivery: mathematical formulation and clustering-based heuristic method, Ann. Oper. Res., 323, 1-2, pp. 203-228, (2023); Yan T., Lu F., Wang S., Wang L., Bi H., A hybrid metaheuristic algorithm for the multi-objective location-routing problem in the early post-disaster stage, J. Ind. Manag. Optim., 19, 6, pp. 4663-4691, (2023); Lee M., Hong J., Cheong T., Lee H., Flexible delivery routing for elastic logistics: a model and an algorithm, IEEE Trans. Intell. Transp. Syst., 23, 7, pp. 6864-6882, (2022); Nataraj S., Ferone D., Quintero-Araujo C., Juan A.A., Festa P., Consolidation centers in city logistics: a cooperative approach based on the location routing problem, Int. J. Ind. Eng. Comput., 10, 3, pp. 393-404, (2019); Schneider M., Loffler M., Large composite neighborhoods for the capacitated location-routing problem, Transp. Sci., 53, 1, pp. 301-318, (2019); Macrina G., Laporte G., Guerriero F., Pugliese L.D.P., An energy-efficient green-vehicle routing problem with mixed vehicle fleet, partial battery recharging and time windows, Eur. J. Oper. Res., 276, 3, pp. 971-982, (2019); Cortes-Murcia D.L., Prodhon C., Afsar H.M., The electric vehicle routing problem with time windows, partial recharges and satellite customers, Trans. Res. Part E Logist. Transp. Rev., 130, pp. 184-206, (2019); Capelle T., Cortes C.E., Gendreau M., Rey P.A., Rousseau L.M., A column generation approach for location-routing problems with pickup and delivery, Eur. J. Oper. Res., 272, 1, pp. 121-131, (2019); do Martins C.L., Hirsch P., Juan A.A., Agile optimization of a two-echelon vehicle routing problem with pickup and delivery, Int. Trans. Oper. Res., 28, 1, pp. 201-221, (2021); Wolfinger D., Salazar-Gonzalez J.J., The pickup and delivery problem with split loads and transshipments: a branch-and-cut solution approach, Eur. J. Oper. Res., 289, 2, pp. 470-484, (2021); Chen C., Demir E., Huang Y., An adaptive large neighborhood search heuristic for the vehicle routing problem with time windows and delivery robots, Eur. J. Oper. Res., 294, 3, pp. 1164-1180, (2021); Harbaoui Dridi I., Ben Alaia E., Borne P., Bouchriha H., Optimisation of the multi-depots pick-up and delivery problems with time windows and multi-vehicles using PSO algorithm, Int. J. Prod. Res., 58, 14, pp. 4201-4214, (2020); Gruler A., Panadero J., de Armas J., Perez J.A.M., A variable neighborhood search simheuristic for the multiperiod inventory routing problem with stochastic demands, Int. Trans. Oper. Res., 27, 1, pp. 314-335, (2020); Pan B., Zhang Z., Lim A., Multi-trip time-dependent vehicle routing problem with time windows, Eur. J. Oper. Res., 291, 1, pp. 218-231, (2021); Anderluh A., Nolz P.C., Hemmelmayr V.C., Crainic T.G., Multi-objective optimization of a two-echelon vehicle routing problem with vehicle synchronization and ‘grey zone’customers arising in urban logistics, Eur. J. Oper. Res., 289, 3, pp. 940-958, (2021); Perez-Canedo B., Verdegay J.L., On the application of a lexicographic method to fuzzy linear programming problems, J. Comput. Cognit. Eng., 2, 1, pp. 47-56, (2023); Yazbek H.A., Surriya F., Khan S.U., Jan N., Marinkovic D., A Novel approach to model the economic characteristics of an organization by interval-valued complex pythagorean fuzzy information, J. Comput. Cognit. Eng., 2, 1, pp. 75-87, (2023)","J. Peng; School of Economics and Management, Jiangsu Vocational College of Finance and Economics, Huai’an, 223003, China; email: jscjxypjj@163.com",null,"Springer Science and Business Media B.V.",{"$nulls":5},1.8756891E7,null,null,null,"English","Int. J. Comput. Intell. Syst.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85172141557"]
["Pathak V.K.; Garg D.; Agarwal A.","Pathak, Vivek Kumar (57225451618); Garg, Dixit (7102459365); Agarwal, Ashish (56377639100)","57225451618; 7102459365; 56377639100","Analysis of Last Mile Delivery Performance Barriers by the DEMATEL Approach",2023.0,"Evergreen",10.0,3.0,null,1495.0,1507.0,12.0,0.0,"10.5109/7151698","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174527454&doi=10.5109%2f7151698&partnerID=40&md5=2e9f15907bb0b0e287fd04bdc61198a0","Department of Mechanical Engineering, NIT Kurukshetra, Haryana, India; Department of Mechanical Engineering, KIET group of institutions, Delhi NCR, U.P., Ghaziabad, India; School of Engineering and Technology, IGNOU, New Delhi, India","Pathak V.K., Department of Mechanical Engineering, NIT Kurukshetra, Haryana, India, Department of Mechanical Engineering, KIET group of institutions, Delhi NCR, U.P., Ghaziabad, India; Garg D., Department of Mechanical Engineering, NIT Kurukshetra, Haryana, India; Agarwal A., School of Engineering and Technology, IGNOU, New Delhi, India","E-commerce industry depends upon the last mile delivery performance. There are some variables acting as enablers help to improve the last mile delivery performance whereas variables acting as barriers restrict the growth in last mile delivery performance. After studying several literatures of supply chain, some variables are identified on which last mile delivery performance depends. Among these variables, barriers have been identified. This paper analyses the impact of barriers on last mile delivery performance. on the basis of literature review, expert talk and brainstorming, twenty variables as barriers to last mile delivery are identified. An integrated decision-making trail and evaluation laboratory (DEMATEL) approach is used to inter-relate barriers and cause/effect relationship among the barriers. Eleven barriers are selected to be considered in cause group and further are in Effect group. Routing simulation, Alternative vehicles, Unawareness about upgraded technology are most important barriers according to study. A framework for barriers to last mile delivery is proposed which provides valuable insights to managers for better last mile delivery performance and improves customer satisfaction. © 2023 Novel Carbon Resource Sciences. 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["Ötken Ç.N.; Yıldız B.; Arslan O.; Laporte G.","Ötken, Çelen Naz (57210593738); Yıldız, Barış (56421693300); Arslan, Okan (55849033100); Laporte, Gilbert (7101734278)","57210593738; 56421693300; 55849033100; 7101734278","Making opportunity sales in attended home delivery",2023.0,"Computers and Operations Research",160.0,null,106362.0,null,null,null,1.0,"10.1016/j.cor.2023.106362","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85167835895&doi=10.1016%2fj.cor.2023.106362&partnerID=40&md5=f4adbe7ce24d70d0405bc44e929527c8","Department of Industrial Engineering, Koc University, Istanbul, Turkey; CIRRELT, GERAD and Department of Decision Sciences, HEC Montréal, Canada; University of Bath, Bath, United Kingdom","Ötken Ç.N., Department of Industrial Engineering, Koc University, Istanbul, Turkey; Yıldız B., Department of Industrial Engineering, Koc University, Istanbul, Turkey; Arslan O., CIRRELT, GERAD and Department of Decision Sciences, HEC Montréal, Canada; Laporte G., CIRRELT, GERAD and Department of Decision Sciences, HEC Montréal, Canada, University of Bath, Bath, United Kingdom","Research on time window management in attended home delivery mainly focuses on influencing customers’ delivery time choices to reduce monetary and environmental costs. In this study, we adopt a different perspective and propose exploiting otherwise idle time and vehicle capacities to generate extra profits through opportunity sales for e-groceries. We consider nudging potential target customers (residing in locations that are ”easy” to insert into the delivery tours) with push notifications to generate new sales. These customers are incentivized for purchases by dropping the terms imposed on standard e-grocery sales such as service fees or minimum purchase quantities. Managing the delivery operations for this innovative business model requires concurrently choosing the target customers and planning the vehicle routes under the offer acceptance and response time uncertainties. To solve this challenging problem, we propose an integer linear programming model that enables a decomposition of the problem into a routing problem and several customer selection problems. For the solution to the customer selection problems, we propose mathematical models with varying risk-taking levels. We also investigate the benefits of dynamic policies to take advantage of the information revealed during the delivery operations in order to adjust customer selection and vehicle routing decisions. Our extensive numerical experiments show that these models, equipped with dynamic decision making, can compete with the risk-ignorant models for the total profit while generating more sales per offer, as well as ensuring timely execution of the delivery operations. © 2023 Elsevier Ltd","Attended home delivery; Dynamic vehicle routing; E-grocery; Online shopping; Opportunity sales","Decision making; Integer programming; Profitability; Risk management; Vehicle routing; Vehicles; Attended home delivery; Customer selections; Dynamic Vehicle Routing; E-grocery; Home delivery; Online shopping; Opportunity sale; Selection problems; Time windows; Window management; Sales",{"$nulls":4},"Natural Sciences and Engineering Research Council of Canada, NSERC, (2015-06189, 2022-04979); Türkiye Bilimsel ve Teknolojik Araştırma Kurumu, TÜBİTAK","The first author thankfully acknowledges the funding provided by TÜBİTAK (The Scientific and Technological Research Council of Turkey) 2210-A National MSc/MA Scholarship Program. The third and fourth authors gratefully acknowledge funding provided by the Natural Sciences and Engineering Research Council of Canada under grants 2022-04979 and 2015-06189 , respectively. Thanks are due to reviewers for their valuable comments. ","Agatz N., Campbell A.M., Fleischmann M., Savelsbergh M.W.P., Time slot management in attended home delivery, Transp. Sci., 45, 3, pp. 435-449, (2011); Amorim P., DeHoratius N., Online shoppers don't always care about faster delivery, MIT Sloan Manag. Rev., (2021); Archetti C., Carrabs F., Cerulli R., The set orienteering problem, European J. Oper. Res., 267, 1, pp. 264-272, (2018); Archetti C., Hertz A., Speranza M.G., Metaheuristics for the team orienteering problem, J. 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Yıldız; Department of Industrial Engineering, Koc University, Istanbul, Turkey; email: byildiz@ku.edu.tr",null,"Elsevier Ltd",{"$nulls":5},3050548.0,null,"CMORA",null,"English","Comp. Oper. Res.","Article","Final",null,"Scopus","2-s2.0-85167835895"]
["Mukherjee S.; Narang D.","Mukherjee, Sramana (57442245500); Narang, Dushyant (57442371500)","57442245500; 57442371500","Digital Economy and Work-from-Home: The Rise of Home Offices Amidst the COVID-19 Outbreak in India",2023.0,"Journal of the Knowledge Economy",14.0,2.0,null,924.0,945.0,21.0,9.0,"10.1007/s13132-022-00896-0","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124120773&doi=10.1007%2fs13132-022-00896-0&partnerID=40&md5=7289728de5af7d72a5c896eaa3279f19","Department of Humanities and Social Sciences, National Institute of Technology, Odisha, Rourkela, 769008, India; Embibe Individual Pvt. Ltd., Diamond District, Old Airport Road, Kodihalli, Bangalore, 560008, India","Mukherjee S., Department of Humanities and Social Sciences, National Institute of Technology, Odisha, Rourkela, 769008, India; Narang D., Embibe Individual Pvt. Ltd., Diamond District, Old Airport Road, Kodihalli, Bangalore, 560008, India","The coronavirus pandemic that marked its presence with the need for social distancing, mandatory self-isolations, quarantines and administrative regulatory lockdowns, has, in turn, ushered in a major transition into an all-consuming digital realm, from the physical, material world. The significance of the virtual interactions on digital platforms have increased manifold with tele-mediated interrelationships occurring at work (within the work-from-home mode), education (with stay-at-home schooling), in consumption patterns (online shopping and delivery of products) and political undertakings (such as mailed in polling). As a direct outcome, the idea of space — both physical and social — are undergoing transformations in the way they are being perceived today, more so, within the economic sectors and labour processes. Remote working in India skyrocketed under the influence of COVID-19 and set newer trends in motion making it intriguing to understand how work patterns have changed under this modus operandi. Adopting a primary survey method, conducted online, among IT sector employees of India, results have been generated across various socio-demographic categories to answer questions of efficiency and productivity, availability of infrastructure and work environment, major challenges and benefits encountered and the desired continuity of work-from-home. 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Mukherjee; Department of Humanities and Social Sciences, National Institute of Technology, Rourkela, Odisha, 769008, India; email: sramana.m@rediffmail.com",null,"Springer",{"$nulls":5},1.8687865E7,null,null,null,"English","J. Knowl. Econ.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85124120773"]
["Laynes-Fiascunari V.; Gutierrez-Franco E.; Rabelo L.; Sarmiento A.T.; Lee G.","Laynes-Fiascunari, Valeria (57982820800); Gutierrez-Franco, Edgar (58244273500); Rabelo, Luis (7004646073); Sarmiento, Alfonso T. (23012990900); Lee, Gene (56226329100)","57982820800; 58244273500; 7004646073; 23012990900; 56226329100","A Framework for Urban Last-Mile Delivery Traffic Forecasting: An In-Depth Review of Social Media Analytics and Deep Learning Techniques",2023.0,"Applied Sciences (Switzerland)",13.0,10.0,5888.0,null,null,null,2.0,"10.3390/app13105888","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85160672647&doi=10.3390%2fapp13105888&partnerID=40&md5=9fe888c8ccd455685edef02b930613c9","Department of Industrial Engineering and Management Systems, University of Central Florida, Orlando, 32826, FL, United States; Massachusetts Institute of Technology, Center for Transportation and Logistics, Cambridge, 02142, MA, United States; Grupo de Investigación en Sistemas Logísticos, Facultad de Ingeniería, Universidad de La Sabana, Campus del Puente del Común, Km. 7, Autopista Norte, Chía, 250001, Colombia","Laynes-Fiascunari V., Department of Industrial Engineering and Management Systems, University of Central Florida, Orlando, 32826, FL, United States; Gutierrez-Franco E., Massachusetts Institute of Technology, Center for Transportation and Logistics, Cambridge, 02142, MA, United States; Rabelo L., Department of Industrial Engineering and Management Systems, University of Central Florida, Orlando, 32826, FL, United States; Sarmiento A.T., Grupo de Investigación en Sistemas Logísticos, Facultad de Ingeniería, Universidad de La Sabana, Campus del Puente del Común, Km. 7, Autopista Norte, Chía, 250001, Colombia; Lee G., Department of Industrial Engineering and Management Systems, University of Central Florida, Orlando, 32826, FL, United States","The proliferation of e-commerce in recent years has been driven in part by the increasing ease of making purchases online and having them delivered directly to the consumer. However, these last-mile delivery logistics have become complex due to external factors (traffic, weather, etc.) affecting the delivery routes’ optimization. Intelligent Transportation Systems (ITS) also have a challenge that contributes to the need of delivery companies for traffic sensors in urban areas. The main purpose of this paper is to propose a framework that closes the gap on accurate traffic prediction tailored for last-mile delivery logistics, leveraging social media analysis along with traditional methods. This work can be divided into two stages: (1) traffic prediction, which utilizes advanced deep learning techniques such as Graph Convolutional and Long-Short Term Memory Neural Networks, as well as data from sources such as social media check-ins and Collaborative Innovation Networks (COINs); and (2) experimentation in both short- and long-term settings, examining the interactions of traffic, social media, weather, and other factors within the model. The proposed framework allows for the integration of additional analytical techniques to further enhance vehicle routing, including the use of simulation tools such as agent-based simulation, discrete-event simulation, and system dynamics. © 2023 by the authors.","intelligent transportation system; last-mile delivery; social media analytics; traffic prediction",{"$nulls":7},"Schomer A., The E-Commerce in Digital Media Report: How Digital Media Businesses Are Successfully Integrating E-Commerce as a New Revenue Stream and How Brands Can Benefit. 2018 DEC 3; Ulmer M.W., Approximate Dynamic Programming for Dynamic Vehicle Routing, 61, (2017); Sharma G., Lijuan W., The effects of online service quality of e-commerce Websites on user satisfaction, Electron. Libr, 33, pp. 468-485, (2015); Izogo E.E., Jayawardhena C., Online shopping experience in an emerging e-retailing market, J. Res. Interact. 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Opt, 45, pp. 154-160, (2021); Gloor P., Sociometrics and Human Relationships: Analyzing Social Networks to Manage Brands, Predict Trends, and Improve Organizational Performance, (2017); Gloor P., Swarm Leadership and the Collective Mind: Using Collaborative Innovation Networks to Build a Better Business, (2017); Yu B., Yin H., Zhu Z., Spatio-temporal graph convolutional networks: A deep learning framework for traffic forecasting, arXiv, (2018)","L. Rabelo; Department of Industrial Engineering and Management Systems, University of Central Florida, Orlando, 32826, United States; email: luis.rabelo@ucf.edu",null,"MDPI",{"$nulls":5},2.0763417E7,null,null,null,"English","Appl. Sci.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85160672647"]
["Wagner S.; Mönch L.","Wagner, Stefan (57761408900); Mönch, Lars (6602003174)","57761408900; 6602003174","A variable neighborhood search approach to solve the order batching problem with heterogeneous pick devices",2023.0,"European Journal of Operational Research",304.0,2.0,null,461.0,475.0,14.0,7.0,"10.1016/j.ejor.2022.03.056","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85132677558&doi=10.1016%2fj.ejor.2022.03.056&partnerID=40&md5=0437a132959c52841cc9722f8f1f2f03","Department of Mathematics and Computer Science, University of Hagen, Hagen, 58097, Germany","Wagner S., Department of Mathematics and Computer Science, University of Hagen, Hagen, 58097, Germany; Mönch L., Department of Mathematics and Computer Science, University of Hagen, Hagen, 58097, Germany","In this paper, we discuss the order batching problem in manual order picking systems. In such systems, order pickers move through a warehouse to collect items that are requested by customers. Customer orders have to be grouped into picking orders of limited size to ensure that the total length of the picker tours to collect all items is minimized. Motivated by real-world restrictions, we assume that the pick devices are heterogeneous, i.e., it is not necessarily possible to transport each customer order with each device. Since the order batching problem is NP-hard, we propose both serial and parallel versions of a variable neighborhood search (VNS) scheme to tackle large-sized problem instances in a reasonable amount of time. Moreover, the VNS scheme is hybridized with a set partitioning problem formulation. Based on computational experiments, we show that the proposed VNS scheme is a very fast approach that is able to provide solutions for benchmark instances with homogeneous pick devices that are of comparable quality or even partly superior to the best performing approaches from the literature. New benchmark instances for heterogeneous pick devices are proposed. High-quality solutions are obtained for these instances. We also consider large-scale problem instances from a real-world e-commerce warehouse. The VNS scheme outperforms the heuristic applied for order batching in this warehouse. Moreover, we demonstrate that a warehouse setup with heterogeneous pick devices is highly beneficial with respect to operating cost savings. © 2022 Elsevier B.V.","Dedicated heterogeneous pick devices; Logistics; Order batching; Real-world problem; Variable neighborhood search","Benchmarking; Optimization; Sales; Batching problem; Customer orders; Dedicated heterogeneous pick device; Order batching; Order-picking systems; Problem instances; Real-world; Real-world problem; Search scheme; Variable neighborhood search; Warehouses",{"$nulls":6},"Albareda-Sambola M., Alonso-Ayuso A., Molina E., Simon de Blas C., Variable neighborhood search for order batching in a warehouse, Asia-Pacific Journal of Operational Research, 26, 5, pp. 655-683, (2009); Boysen N., de Koster R., Weidinger F., Warehousing in the e-commerce era: A survey, European Journal of Operational Research, 277, pp. 396-411, (2019); Brandao J.C.S., Mercer A., The multi-trip vehicle routing problem, Journal of the Operational Research Society, 49, pp. 799-805, (1998); Bue M., Cattaruzza D., Ogier M., (2019); Cergibozan C., Tasan A.S., Order batching operations: An overview of classification, solution techniques, and future research, Journal of Intelligent Manufacturing, pp. 1-15, (2016); Chen T.-L., Cheng C.-Y., Chen Y.-Y., Chan L.-K., An efficient hybrid algorithm for integrated order batching, sequencing and routing problem, International Journal of Production Economics, 159, pp. 158-167, (2015); Chu P.C., Beasley J.E., Constraint handling in genetic algorithms: The set partitioning problem, Journal of Heuristics, 11, pp. 323-357, (1998); Clarke G., Wright J.W., Scheduling of vehicles from a central depot to a number of delivery points, Operations Research, 12, 4, pp. 568-581, (1964); Crawford B., Castro C., Integrating lookahead and post processing procedures with ACO for solving set partitioning and covering problems, Proceedings ICAISC 2006, LNAI, 4029, pp. 1082-1090, (2006); de Koster M.B.M., van der Poort E.S., Wolters M., Efficient orderbatching methods in warehouses, International Journal of Production Research, 37, 7, pp. 1479-1504, (1999); de Koster R., Le-Duc T., Roodbergen K.J., Design and control of warehouse order picking: A literature review, European Journal of Operational Research, 182, 2, pp. 481-501, (2007); (2020); Dosa G., Li R., Han X., Tuza Z., Tight absolute bound for first fit decreasing bin-packing, Theoretical Computer Science, 510, pp. 13-61, (2013); Elsayed E.A., Algorithms for optimal material handling in automatic warehousing systems, International Journal of Production Research, 19, 5, pp. 525-535, (1981); Elsayed E.A., Unal O.I., Order batching algorithms and travel-time estimation for automated storage/retrieval systems, International Journal of Production Research, 27, 7, pp. 1097-1114, (1989); Fleischmann B., The vehicle routing problem with multiple use of vehicles. working paper, fachbereich wirtschaftswissenschaften, (1990); Gademann N., van den Berg J.P., van der Hoff H.H., An order batching algorithm for wave picking in a parallel-aisle warehouse, IIE Transactions, 33, 5, pp. 385-398, (2001); Gademann N., van de Velde S., Order batching to minimize total travel time in a parallel-aisle warehouse, IIE Transactions, 37, 1, pp. 63-75, (2005); Gibson D.R., Sharp G.P., Order batching procedures, European Journal of Operational Research, 58, 1, pp. 57-67, (1992); Gil-Borras S., Pardo E.G., Alonso-Ayuso A., Duarte A., New VNS variants for the online order batching problem, Proceedings ICVNS 2018, LNCS, 11328, pp. 89-100, (2019); Grosse E.H., Glock C.H., Jaber M.Y., Neumann W.P., Incorporating human factors in order picking planning models. Framework and research opportunities, International Journal of Production Research, 53, 3, pp. 695-717, (2014); Hansen P., Mladenovic N., Variable neighborhood search: Principles and applications, European Journal of Operational Research, 130, pp. 449-467, (2001); Hansen P., Mladenovic N., Variable neighborhood search, Handbook heuristics, pp. 759-787, (2018); Henn S., Koch S., Doerner K.F., Strauss C., Wascher G., Metaheuristics for the order batching problem in manual order picking systems, Business Research, 3, 1, pp. 82-105, (2010); Henn S., Schmidt V., Metaheuristics for order batching and sequencing in manual order picking systems, Computers & Industrial Engineering, 66, pp. 338-351, (2013); Henn S., Wascher G., Tabu search heuristics for the order batching problem in manual order picking systems, European Journal of Operational Research, 222, pp. 484-494, (2012); Koch S., Wascher G., A grouping genetic algorithm for the order batching problem in distribution warehouses, Journal of Business Economics, 86, 1-2, pp. 131-153, (2016); Martello S., Toth P., Martello S., Toth P., Bin-packing problem, Knapsack problems. algorithms and computer implementations, pp. 221-245, (1990); Matusiak M., de Koster R., Kroon L., Saarinen J., A fast simulated annealing method for batching precedence-constrained customer orders in a warehouse, European Journal of Operational Research, 236, 3, pp. 968-977, (2014); Matusiak M., de Koster R., Saarinen J., Utilizing individual picker skills to improve order batching in a warehouse, European Journal of Operational Research, 263, 3, pp. 888-899, (2017); Menendez B., Bustillo M., Pardo E.G., Duarte A., General variable neighborhood search for the order batching and sequencing problem, European Journal of Operational Research, 263, 1, pp. 82-93, (2017); Menendez B., Pardo E.G., Alonso-Ayuso A., Molina E., Duarte A., Variable neighborhood search strategies for the order batching problem, Computers & Operations Research, 78, pp. 500-512, (2017); Menendez B., Pardo E.G., Duarte A., Alonso-Ayuso A., Molina E., General variable neighborhood search applied to the picking process in a warehouse, Electronic Notes in Discrete Mathematics, 47, pp. 77-84, (2015); Menendez B., Pardo E.G., Sanchez-Oro J., Duarte A., Parallel variable neighborhood search for the min-max order batching problem, International Transactions on Operational Research, 24, 3, pp. 635-662, (2017); Muter I., Oncan T., An exact solution approach for the order batching problem, IIE Transactions, 47, 7, pp. 728-738, (2015); (2021); Oncan T., MILP formulations and an iterated local search algorithm with tabu thresholding for the order batching problem, European Journal of Operational Research, 243, 1, pp. 142-155, (2015); Penna P.H.V., Subramanian A., Ochi L.S., Vidal T., Prins C., A hybrid heuristic for a broad class of vehicle routing problems with heterogeneous fleet, Annals of Operations Research, 273, 1, pp. 5-74, (2019); Pferschy U., Schauer J., Order batching and routing in a non-standard warehouse, Electronic Notes in Discrete Mathematics, 69, pp. 125-132, (2018); Pisinger D., Ropke S., Large neighborhood search, Handbook of metaheuristics, pp. 399-420, (2010); Rosenwein M.B., A comparison of heuristics for the problem of batching orders for warehouse selection, International Journal of Production Research, 34, 3, pp. 657-664, (1996); Ruben R.A., Jacobs F.R., Batch construction heuristics and storage assignment strategies for walk/ride and pick systems, Management Science, 45, 4, pp. 575-596, (1999); Scholz A., Schubert D., Wascher G., Order picking with multiple pickers and due dates – simultaneous solution of order batching, batch assignment and sequencing, and picker routing problems, European Journal of Operational Research, 263, 2, pp. 461-478, (2017); Subramanian A., Penna P.H.V., Uchoa E., Ochi L.S., A hybrid algorithm for the heterogeneous fleet vehicle routing problem, European Journal of Operational Research, 221, 2, pp. 285-295, (2012); Taillard E., Laporte G., Gendreau M., Vehicle routeing with multiple use of vehicles, Journal of the Operational Research Society, 47, pp. 1065-1070, (1996); Tompkins J.A., White J.A., Bozer Y.A., Tanchoco J.M.A., Facilities planning, (2010); Tsai C.-Y., Liou J.J.H., Huang T.-M., Using a multiple-GA method to solve the batch picking problem: Considering travel distance and order due time, International Journal of Production Research, 46, 22, pp. 6533-6555, (2008); Valle C.A., Beasley J.E., da Cunha A.S., Optimally solving the joint order batching and picker routing problem, European Journal of Operational Research, 262, 3, pp. 817-834, (2017); van Gils T., Ramaekers K., Caris A., de Koster R.B.M., Designing efficient order picking systems by combining planning problems. State-of-the-art classification and review, European Journal of Operational Research, 267, 1, pp. 1-15, (2018); Wagner S., Monch L., Using variable neighborhood search to solve the order batching problem in manual order picking systems, Proceedings of the XI metaheuristic international conference (MIC), (2015); Wascher G., Order picking. A survey of planning problems and methods, Supply chain management and reverse logistics, pp. 323-347, (2004); Zulj I., Kramer S., Schneider M., A hybrid of adaptive large neighborhood search and tabu search for the order-batching problem, European Journal of Operational Research, 264, 2, pp. 653-664, (2018)","L. Mönch; Department of Mathematics and Computer Science, University of Hagen, Hagen, 58097, Germany; email: Lars.Moench@fernuni-hagen.de",null,"Elsevier B.V.",{"$nulls":5},3772217.0,null,"EJORD",null,"English","Eur J Oper Res","Article","Final",null,"Scopus","2-s2.0-85132677558"]
["Gu R.; Liu Y.; Poon M.","Gu, Ruixue (57693793800); Liu, Yang (56421736600); Poon, Mark (57693700900)","57693793800; 56421736600; 57693700900","Dynamic truck–drone routing problem for scheduled deliveries and on-demand pickups with time-related constraints",2023.0,"Transportation Research Part C: Emerging Technologies",151.0,null,104139.0,null,null,null,2.0,"10.1016/j.trc.2023.104139","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85152488713&doi=10.1016%2fj.trc.2023.104139&partnerID=40&md5=8f8f5eadb646e767f86819bd46f18975","Department of Industrial Systems Engineering and Management, National University of Singapore, Singapore, 117576, Singapore; Department of Civil and Environmental Engineering, National University of Singapore, Singapore, 117576, Singapore; Amazon, Seattle, 98109, WA, United States","Gu R., Department of Industrial Systems Engineering and Management, National University of Singapore, Singapore, 117576, Singapore; Liu Y., Department of Industrial Systems Engineering and Management, National University of Singapore, Singapore, 117576, Singapore, Department of Civil and Environmental Engineering, National University of Singapore, Singapore, 117576, Singapore; Poon M., Amazon, Seattle, 98109, WA, United States","The on-demand logistics services have risen continuously with the expansion of e-commerce. Logistics companies face challenges to meet customers’ expectations with high efficiency and reliability at a low cost. Hence, this paper investigates the dynamic truck–drone routing problem with scheduled deliveries and on-demand pickups (D-TDRP-SDOP) for an on-demand logistics system. Trucks and drones are deployed to serve a batch of deterministic deliveries and an uncertain set of pickup requests with deadlines subject to maximum working hour constraints. The drones can serve multiple requests per trip subject to load constraints and endurance capacity restrictions. The service provider aims to maximize the total profits by dynamic reassignment and recourse of the vehicles. We formulate the D-TDRP-SDOP problem as a Markov decision process (MDP) and propose a heuristic solution approach framework, consisting of an offline enhanced construction algorithm (OECA) and a segment-based heuristic, to solve the MDP. The comprehensive numerical experiments demonstrate the effectiveness of the proposed solution approach and the benefits of the model. Our model improves the total profits by 15% by considering on-demand requests, and the drone operations contribute to a 50% improvement in the acceptance rate of dynamic customer requests. Improved drone technology, such as a higher drone speed and a higher battery capacity, can enable the system to serve more on-demand requests and increase the final profits. However, the benefit diminishes when the drone capability reaches a certain threshold. © 2023 Elsevier Ltd","Drone delivery; Dynamic routing; Multi-visits; On-demand delivery; Vehicle routing problems","Automobiles; Costs; Drones; Markov processes; Pickups; Profitability; Vehicle routing; Delivery demands; Drone delivery; Dynamic routing; Markov Decision Processes; Multi-visit; On demands; On-demand delivery; Routing problems; Total profits; Vehicle Routing Problems; electronic commerce; heuristics; logistics; routing; threshold; trucking; Trucks",{"$nulls":4},"Ministry of Education - Singapore, MOE, (MOE2019-T2-2-165)","The work was supported by Singapore Ministry of Education Academic Research Fund Tier 2 ( MOE2019-T2-2-165 ). 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["Shapiro A.","Shapiro, Aaron (57191545018)",5.7191545018E10,"Platform urbanism in a pandemic: Dark stores, ghost kitchens, and the logistical-urban frontier",2023.0,"Journal of Consumer Culture",23.0,1.0,null,168.0,187.0,19.0,16.0,"10.1177/14695405211069983","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124214256&doi=10.1177%2f14695405211069983&partnerID=40&md5=9640ee3f948bd0d3d07a862cbeffea91","Department of Communication, University of North Carolina–Chapel Hill, Chapel Hill, NC, United States","Shapiro A., Department of Communication, University of North Carolina–Chapel Hill, Chapel Hill, NC, United States","As demand for e-commerce surged during the COVID-19 pandemic, investors began pouring billions into start-ups promising to accelerate digitization and automation in small-margin, winner-take-all sectors, such as retail, grocery, and dining. I examine two business models that feature prominently in this swell of financial optimism: dark stores and ghost kitchens. Both sacrifice consumer-facing real estate to create logistical spaces for online order fulfillment, and both are predicted to become permanent fixtures of the post-pandemic economic landscape. However, few have commented on the consequences of this future-in-the-making or who is likely to suffer them. The essay therefore anticipates how “going dark” may impact consumers, workers, and urban geographies. I argue that going dark represents a new threshold in the spatial materialities and financial imaginary of platform urbanism, what I call the logistical-urban frontier. I theorize how this frontier threatens historically disenfranchised urban communities, and I conclude the essay with a reflection on the conflicted temporalities of logistical speculation. © The Author(s) 2022.","Dark stores; e-commerce; ghost kitchens; logistics; platform urbanism; political economy of technology; supply chain capitalism",{"$nulls":7},"Adam B.E., Futures in the making: sociological practice and challenge, Handbook of Public Sociology, pp. 429-474, (2009); Alimohamed-Wilson J., The Amazonification of logistics: e-commerce, labor, and exploitation in the last mile, The Cost of Free Shipping: Amazon in the Global Economy, pp. 69-84, (2020); Alimohamed-Wilson J., Allison J., Reese E., Introduction: Amazon capitalism, The Cost of Free Shipping: Amazon in the Global Economy, pp. 1-20, (2020); Altenried M., On the last mile: logistical urbanism and the transformation of labour. work organisation, labour & globalisation, Pluto Journals, 13, 1, pp. 114-129, (2019); Ang C., Visualized: A Breakdown of Amazon’s Revenue Model, (2020); Anonymous, Dark Stores—Thread Regarding Macy’s Inc. 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Now what?, (2020); Sundaram A., Yelp Data Shows 60% of Business Closures Due to the Coronavirus Pandemic are Now Permanent, (2020); Major Retailers Using Tecsys-Enabled Micro-Fulfillment and Dark Stores to Account for Surge in Digital Commerce Retailing, (2020); Thorne J., Us Vc Fundraising Hits Record $69b in 2020 After A16z Closes Two Mega-Funds, (2020); Tsing A., Supply chains and the human condition, Rethinking Marxism, 21, 2, pp. 148-176, (2009); van Doorn N., Platform labor: on the gendered and racialized exploitation of low-income service work in the ‘on-demand’ economy, Information, Communication & Society, 20, 6, pp. 898-914, (2017); Ventura L., World’s Largest Companies 2020, (2021); West E., Amazon: Surveillance-as-a-Service, Surveillance & Society, 17, 1-2, pp. 27-33, (2019); Wiener A., Our Ghost-Kitchen Future, (2020)","A. Shapiro; Department of Communication, University of North Carolina–Chapel Hill, Chapel Hill, United States; email: amshap@unc.edu",null,"SAGE Publications Ltd",{"$nulls":5},1.4695405E7,null,null,null,"English","J. Consum. Cult.","Article","Final",null,"Scopus","2-s2.0-85124214256"]
["Gunasekar S.; Ray S.; Dixit S.K.; PA M.R.","Gunasekar, Sangeetha (57188860591); Ray, Sougata (57195572544); Dixit, Saurabh Kumar (57195132858); PA, Manoj Raj (57665881100)","57188860591; 57195572544; 57195132858; 57665881100","AI-enables product purchase on Amazon: what are the consumers saying?",2023.0,"Foresight",25.0,2.0,null,185.0,193.0,8.0,0.0,"10.1108/FS-10-2021-0212","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85129374983&doi=10.1108%2fFS-10-2021-0212&partnerID=40&md5=64f2f9174af810f880a6866b4c547f80","Amrita School of Business, Amrita Vishwa Vidyapeetham, Coimbatore, India; Department of Finance and Economics, International Management Institute, Bhubaneswar, India; Department of Tourism and Hotel Management, North-Eastern Hill University, Shillong, India","Gunasekar S., Amrita School of Business, Amrita Vishwa Vidyapeetham, Coimbatore, India; Ray S., Department of Finance and Economics, International Management Institute, Bhubaneswar, India; Dixit S.K., Department of Tourism and Hotel Management, North-Eastern Hill University, Shillong, India; PA M.R., Amrita School of Business, Amrita Vishwa Vidyapeetham, Coimbatore, India","Purpose: This study aims to identify the product attributes that influence customer satisfaction related to AI-enabled products with a strong forecast of growth. This study is very timely as the market for AI-based smart home products is still at a nascent stage in emerging economies (Vaishali Dar, 2021). Adding evidence to literature on the experience of customers, identifying the attributes that lead to customer satisfaction and those that lead to dissatisfaction are essential for products that were launched recently during the pandemic. This study makes valuable addition to the existing literature. Design/methodology/approach: Online reviews (12,326 reviews) for EchoDot products launched by Amazon India during the pandemic were collected for the study. The attributes were identified based on the most frequently discussed attributes in the text reviews. Further review valence was determined to group the reviews under positive reviews indicating customer satisfaction and negative reviews indicating customer dissatisfaction. Logistic regression was used to identify the attributes that significantly impact customer satisfaction/dissatisfaction. Findings: The results of the study indicate that while EchoDot is seen to add value to the smart home environment (home variable), video (video variable) and speaker (speaker variable) quality also contribute to customer satisfaction. Further, consumers found the product truly worth their money (value for money variable). Other attributes like a complaint about Bluetooth features are seen to increase the probability of customer dissatisfaction. Originality/value: This study identifies the most important attributes that influence customer satisfaction in AI-enabled product sales on e-commerce platforms in pandemic times for India. Such studies are scarce in the emerging markets where the AI-based home appliance market is still in its nascent stage, and the customers are trying out their experiences with these products. What the customers expect and are these products fulfill these expectations is an important question that needs to be addressed by research. This study addresses this gap and adds to this literature. © 2022, Emerald Publishing Limited.","Customer satisfaction; E-commerce Smarthome product; Logistic regression; Online review; Text analytics",{"$nulls":7},"Anderson E.W., Customer satisfaction and word of mouth, Journal of Service Research, 1, 1, pp. 5-17, (1998); Anderson E.W., Sullivan M.W., The antecedents and consequences of customer satisfaction for firms, Marketing Science, 12, 2, pp. 125-143, (1993); Awalegaonkar K., Berkey R., Douglass G., Reilly A., AI: built to scale, (2019); Bhattacharyya S., Bose I., S-commerce: influence of facebook likes on purchases and recommendations on a linked e-commerce site, Decision Support Systems, 138, (2020); Bitner M.J., Evaluating service encounters: the effects of physical surroundings and employee responses, Journal of Marketing, 54, 2, pp. 69-82, (1990); Brynjolfsson E., McAfee A., The second machine age: Work, Progress, and Prosperity in a Time of Brilliant Technologies, (2014); Canziani B., MacSween S., Consumer acceptance of voice-activated smart home devices for product information seeking and online ordering, Computers in Human Behavior, 119, (2021); Chevalier J.A., Mayzlin D., The effect of word of mouth on sales: online book reviews (no. w10148), (2003); Churchill G.A., Surprenant C., An investigation into the determinants of customer satisfaction, Journal of Marketing Research, 19, 4, pp. 491-504, (1982); Davis A., Khazanchi D., An empirical study of online word of mouth as a predictor for multi-product category e-commerce sales, Electronic Markets, 18, 2, pp. 130-141, (2008); Duan Y., Liu T., Mao Z., How online reviews and coupons affect sales and pricing: an empirical study based on e-commerce platform, Journal of Retailing and Consumer Services, 65, (2022); Eachempati P., Srivastava P.R., Kumar A., Prat J.M.D., Delen D., Can customer sentiment impact firm value? 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Investigating the effects of adjusted expectations and customer loyalty, Psychology and Marketing, 21, 5, pp. 351-373, (2004); Zhang C., Tian Y.-X., Fan Z.-P., Forecasting sales using online review and search engine data: a method based on PCA–DSFOA–BPNN, International Journal of Forecasting, (2021); Dar V., Home smart home: variety of products to offer, (2021); Lankes R.D., Silverstein J., Nicholson S., Participatory networks: the library as conversation, Information Technology and Libraries, 26, 4, pp. 17-33, (2007); SciutoSainiForlizzi A., Hong J.I., Hey Alexa, what's up?” a Mixed-Methods studies of in-Home conversational agent usage","S. Gunasekar; Amrita School of Business, Coimbatore, Amrita Vishwa Vidyapeetham, India; email: sangeetha1000@gmail.com",null,"Emerald Publishing",{"$nulls":5},1.4636689E7,null,null,null,"English","Foresight","Article","Final",null,"Scopus","2-s2.0-85129374983"]
["Kang S.","Kang, Sanggyun (57200163048)",5.7200163048E10,"Reexamination of the association between development patterns and truck crashes: A case study in Dallas-Fort Worth, TX",2023.0,"Accident Analysis and Prevention",186.0,null,107052.0,null,null,null,0.0,"10.1016/j.aap.2023.107052","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85152243757&doi=10.1016%2fj.aap.2023.107052&partnerID=40&md5=d2dd7b19fe0e2e33a9f0289db6b89686","Department of International Logistics, College of Business and Economics, Chung Ang University, Seoul, South Korea","Kang S., Department of International Logistics, College of Business and Economics, Chung Ang University, Seoul, South Korea","Over the last decade, urban logistics operations have changed significantly due to globalized production and distribution systems and expanding online shopping sales. On the one hand, goods are distributed on a greater scale through large-scale transportation infrastructure. On the other, exploding online shopping shipment has added another layer of complexity to urban logistics operations. Nowadays, instant home delivery has become prevalent. Provided that the geography, extent, and frequency of freight trip generation have completely changed, it can be assumed that the relationship between the development pattern characteristics and road safety outcomes has also changed, accordingly. Then, it is imperative that the spatial distribution of truck crashes, in conjunction with development pattern characteristics, is reexamined. As a Dallas-Fort Worth, TX metro area case study, this research examines whether the spatial distribution of truck crashes on city streets is different from that of other vehicle crashes and tests whether truck crashes have a unique association with development patterns. Results show that truck and passenger car crashes are distinguished in terms of how they are associated with urban density and employment sector compositions. The explanatory variables with significant and expected signs of relationship are VMT per network mile (exposure), intersection density, household income, % non-white, and % no high school diploma. Results indicate that the spatial heterogeneity in goods shipment intensity has strong implications for the variation in truck crash patterns. Results also call for a comprehensive reexamination of trucking activity in dense urban areas. © 2023 Elsevier Ltd","Development patterns; Logistics restructuring; Road safety; Truck crash; Urban logistics","Accidents, Traffic; Commerce; Humans; Motor Vehicles; Accidents; Electric power distribution; Electronic commerce; Motor transportation; Online systems; Ships; Spatial distribution; Trucks; Case-studies; Development patterns; Logistic operations; Logistic restructuring; Online shopping; Pattern characteristic; Production system; Road safety; Truck crash; Urban logistics; commercial phenomena; human; motor vehicle; traffic accident; Roads and streets",{"$nulls":4},"University of Texas at Arlington, UTA; Chung-Ang University, CAU","This research was supported by Chung-Ang University and the Center for Transportation, Equity, Decisions, and Dollars (CTEDD) at the University of Texas at Arlington. The funding sponsor had no involvement in the study design or any aspect of the research and analysis. The views expressed are those of the author, and all errors are the responsibility of the author.","Abdel-Aty M., Lee J., Siddiqui C., Choi K., Geographical Unit Based Analysis in the Context of Transportation Safety Planning, Transp. Res. A Policy Pract., 49, March, pp. 62-75, (2013); Bedard M., Guyatt G.H., Stones M.J., Hirdes J.P., The Independent Contribution of Driver, Crash, and Vehicle Characteristics to Driver Fatalities, Accid. Anal. Prev., 34, 6, pp. 717-727, (2002); Belzer M.H., Rodriguez D., Sedo S.A., Paying for Safety: An Economic Analysis of the Effect of Pay on Truck Driver Safety, (2002); Blower D., Campbell K.L., Green P.E., Accident Rates for Heavy Truck-Tractors in Michigan, Accid. Anal. 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["Li Y.; Zhou C.; Yuan P.; Ngo T.T.A.","Li, Yifu (57551078100); Zhou, Chenhao (56809928400); Yuan, Peixue (57551469400); Ngo, Thi Tu Anh (57549142200)","57551078100; 56809928400; 57551469400; 57549142200","Experience-based territory planning and driver assignment with predicted demand and driver present condition",2023.0,"Transportation Research Part E: Logistics and Transportation Review",171.0,null,103036.0,null,null,null,0.0,"10.1016/j.tre.2023.103036","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85147590268&doi=10.1016%2fj.tre.2023.103036&partnerID=40&md5=f3575b94c4ed4458212b998f2cdc94ff","International Institute of Finance, School of Management, University of Science and Technology of China, Hefei, 230026, China; School of Management, Northwestern Polytechnical University, Xi'an, 710072, China; Department of Industrial Systems Engineering and Management, National University of Singapore, Singapore","Li Y., International Institute of Finance, School of Management, University of Science and Technology of China, Hefei, 230026, China; Zhou C., School of Management, Northwestern Polytechnical University, Xi'an, 710072, China; Yuan P., School of Management, Northwestern Polytechnical University, Xi'an, 710072, China; Ngo T.T.A., Department of Industrial Systems Engineering and Management, National University of Singapore, Singapore","The parcel delivery industry has enjoyed rapid growth with the rise of the e-commerce business. To survive the highly competitive market, service providers have introduced various methods to improve the customer experience, for example, providing faster response or wider delivery coverage. One way is to adopt the territory-based delivery system, in which each courier serves a fixed group of customers. In this study, we propose a novel territory design method allowing the territory plan to be adjusted while guaranteeing service consistency. The territory planning problem (TPP) can be formulated as a Markov decision process (MDP), and we develop a two-stage Rolling Horizon (TSRH) method to compute the optimal territory plan. In the first stage, the algorithm assigns certain cells to the drivers based on the predicted demands. In the second stage, the remaining cells are assigned to the drivers with the actual demands while taking driver experience into consideration. The computational studies reveal that the proposed TSRH method is able to resolve the TPP efficiently, and it is robust under different situations. The TSRH method outperforms the classical method with fixed core areas. We also find that the learning potential and learning efficiency can largely impact the optimal territory plan, which eventually leads to significant improvement on driver's performance. © 2023 Elsevier Ltd","Driver assignment; Learning effect; Markov decision process; Rolling horizon method; Territory planning","Behavioral research; Learning systems; Condition; Driver assignment; Learning effects; Markov Decision Processes; Parcel delivery; Planning problem; Rapid growth; Rolling horizon; Rolling horizon method; Territory planning; algorithm; competitiveness; growth; learning; Markov chain; territorial management; territorial planning; Markov processes",{"$nulls":4},"Shaanxi Provincial Key R&D Program, China, (2022KW-02); Youth Innovation Team of Shaanxi Universities; National Natural Science Foundation of China, NSFC, (72101203, 72201210)","This research is supported by the National Natural Science Foundation of China [ 72201210 , 72101203 ], Shaanxi Provincial Key R&D Program, China [ 2022KW-02 ], and The Youth Innovation Team of Shaanxi Universities, China . 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Zhou; School of Management, Northwestern Polytechnical University, Xi'an, 710072, China; email: zhouchenhao@nwpu.edu.cn",null,"Elsevier Ltd",{"$nulls":5},1.3665545E7,null,null,null,"English","Transp. Res. Part E Logist. Transp. Rev.","Article","Final",null,"Scopus","2-s2.0-85147590268"]
["Sharma D.R.; Singh B.; Jaiswal K.","Sharma, Devika Rani (57222489312); Singh, Balgopal (57202959822); Jaiswal, Kamal (55378099100)","57222489312; 57202959822; 55378099100","Understanding the Influence of Mobile In-App Price Promotions in Food Delivery Apps on Customer Engagement and Advocacy",2023.0,"Indian Journal of Marketing",53.0,7.0,null,8.0,29.0,21.0,0.0,"10.17010/ijom/2023/v53/i7/170023","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85165869953&doi=10.17010%2fijom%2f2023%2fv53%2fi7%2f170023&partnerID=40&md5=11752bb9e571c021443d7774e39ff43e","School of Business, GITAM (Deemed to Be University), Telangana, Hyderabad, India; FMS, Banasthali Vidyapith, Rajasthan, 304 022, India; Higher Colleges of Technology, Abu Dhabi, United Arab Emirates","Sharma D.R., School of Business, GITAM (Deemed to Be University), Telangana, Hyderabad, India; Singh B., FMS, Banasthali Vidyapith, Rajasthan, 304 022, India; Jaiswal K., Higher Colleges of Technology, Abu Dhabi, United Arab Emirates","Purpose: With the emergence of e-commerce, food ordering through mobile-app also witnessed significant growth akin to other products. However, the consumers’ switching rates for online food service provider was found to be high. Traditional marketing wisdom suggested various forms of promotion to counter this. The form of promotion mainly suggested was price promotion. The objective of the present study was to understand the role of in-app price promotion between consumer engagement and advocacy relationships in the context of food delivery applications. Methodology: The descriptive research design was adopted to further the study. A research model depicting the proposed hypotheses was developed based on social exchange and incentive theories. Data were collected through an online questionnaire from 293 users of food delivery applications from the Delhi-NCR region. PLS-SEM was used to test the hypothesized relationships between the constructs. Findings: The study established that in-app price promotion was positively associated with consumer advocacy and fully mediated the relationship between consumer engagement and advocacy. Practical Implications: This study strongly recommended that food delivery app managers should frequently offer in-app price discount coupons to their existing customers. Availing of promotional benefits would help spread positive word-of-mouth about food and service quality. Positive advocacy would be beneficial to attract new customers. This study would also be helpful to future researchers in the conceptualizing study in another e-commerce context. Originality: This study was the first to determine the role of in-app price promotion between consumer engagement and advocacy relationships in the online food-delivery app context. © 2023, Associated Management Consultants Pvt. Ltd.. All rights reserved.","consumer advocacy; customer engagement; food delivery apps; in-app price promotion",{"$nulls":7},{"$cut":{"chars":20710,"head":"Ahn J., Impact of cognitive aspects of food mobile application on customers’ behaviour, Current Issues in Tourism, 25, 4, pp. 516-523, (2022); Ailawadi K. L., Neslin S. A., Gedenk K., Pursuing the value-conscious consumer: Store brands versus national brand promotions, Journal of Marketing, 65, 1, pp. 71-89, (2001); Alguacil M., Nunez-Pomar J. M., Valantine I., Crespo-Hervas J., Perez-Campos C., Staskeviciute-Butiene I., The importance of the services brand in predicting loyalty and word of mouth, Engineering Economics, 29, 4, pp. 446-454, (2018); Andrews M., Goehring J., Hui S., Pancras J., Thornswood L., Mobile promotions: A framework and research priorities, Journal of Interactive Marketing, 34, 1, pp. 15-24, (2016); Andrews R. L., Currim I. 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P., Consumers’ usage of food delivery app: A theory of consumption values, Journal of Hospitality Marketing & Management, 31, 5, pp. 601-619, (2022); Chandon P., Wansink B., Laurent G., A benefit congruency framework of sales promotion effectiveness, Journal of Marketing, 64, 4, pp. 65-81, (2000); Chandra Y. U., Cassandra C., Stimulus factors of order online food delivery, 2019 International Conference on Information Management and Technology (ICIMTech), pp. 330-333, (2019); Chelminski P., Coulter R. A., An examination of consumer advocacy and complaining behavior in the c o n t e x t o f s e r v i c e f a i l u r e, J o u r n a l o f S e r v i c e s M a r k e t i n g, 2 5, pp. 361-370, (2011); Chintagunta P. K., Chu J., Cebollada J., Quantifying transaction costs in online/offline grocery channel choice, Marketing Science, 31, 1, pp. 96-114, (2012); Cho M., Bonn M. A., Li J., Differences in perceptions about food delivery apps between single-person and multi-person households, International Journal of Hospitality Management, 77, pp. 108-116, (2019); Chu J., Arce-Urriza M., Cebollada-Calvo J.-J., Chintagunta P. K., An empirical analysis of shopping behavior across online and offline channels for grocery products: The moderating effects of household and product characteristics, Journal of Interactive Marketing, 24, 4, pp. 251-268, (2010); Chung C. M., Darke P. R., The consumer as advocate: Self-relevance,"}},"B. Singh; FMS, Banasthali Vidyapith, Rajasthan, 304 022, India; email: balgopalsingh@banasthali.in",null,"Associated Management Consultants Pvt. Ltd.",{"$nulls":5},9738703.0,null,null,null,"English","Ind. J. Mark.","Article","Final",null,"Scopus","2-s2.0-85165869953"]
["Qi Y.; Wang X.; Zhang M.; Wang Q.","Qi, Yinan (55446928000); Wang, Xiaorui (57985483000); Zhang, Min (55801329700); Wang, Qiang (55627548700)","55446928000; 57985483000; 55801329700; 55627548700","Developing supply chain resilience through integration: An empirical study on an e-commerce platform",2023.0,"Journal of Operations Management",69.0,3.0,null,477.0,496.0,19.0,11.0,"10.1002/joom.1226","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85142877189&doi=10.1002%2fjoom.1226&partnerID=40&md5=d4a49dc697ab643153c743753b7acec1","Business School, University of International Business & Economics, Beijing, China; School of International Trade and Economics, University of International Business & Economics, Beijing, China; Queen's Management School, Queen's University Belfast, Belfast, United Kingdom","Qi Y., Business School, University of International Business & Economics, Beijing, China; Wang X., School of International Trade and Economics, University of International Business & Economics, Beijing, China; Zhang M., Queen's Management School, Queen's University Belfast, Belfast, United Kingdom; Wang Q., School of International Trade and Economics, University of International Business & Economics, Beijing, China","The outbreak of the COVID-19 pandemic has disrupted supply chains and increased the uncertainties faced by firms. While firms are struggling to survive and recover from the pandemic, Chinese e-commerce platforms have demonstrated resilient supply chains. We develop a framework that investigates the impacts of integration between an e-commerce platform and suppliers on supply chain resilience and the moderating effect of the suppliers' product flexibility. An analysis of data from a Chinese e-commerce platform using operational indicators finds that integration between the e-commerce platform and suppliers in terms of information sharing, joint planning and logistics cooperation has positive impacts on supply chain resilience, while procurement automation has the opposite effect. Furthermore, product flexibility positively moderates the impacts of information sharing, joint planning and logistics cooperation. The results enhance current understandings of the factors that contribute to the development of supply chain resilience and reveal that the relationship between integration and resilience should be examined within a contingency framework. The findings also provide guidelines for managers taking measures to mitigate the negative influences of supply chain disruptions. © 2022 Association for Supply Chain Management, Inc.","COVID-19; e-commerce platform; product flexibility; supply chain integration; supply chain resilience","Electronic commerce; Information analysis; Information dissemination; Integration; Supply chain management; Commerce platforms; E- commerces; E-commerce platform; Empirical studies; Information sharing; Joint planning; Logistics cooperations; Product flexibility; Supply chain resiliences; Supply-chain integration; COVID-19",{"$nulls":4},"University of International Business and Economics, UIBE; National Natural Science Foundation of China, NSFC, (71733002); Fundamental Research Funds for the Central Universities; National Office for Philosophy and Social Sciences, NPOPSS, (20VMG020, 72042003)","Funding text 1: National Natural Science Foundation of China, Grant/Award Number: 71733002; Fundamental Research Funds for the Central Universities, UIBE, Grant/Award Number: ZD3‐11 Funding information ; Funding text 2: This study is supported by National Social Science Fund of China (No. 20VMG020, No. 72042003) and National Natural Science Foundation of China (No. 71733002).","Ambulkar S., Blackhurst J., Grawe S., Firm's resilience to supply chain disruptions: Scale development and empirical examination, Journal of Operations Management, 33-34, pp. 111-122, (2015); Ataseven C., Nair A., Assessment of supply chain integration and performance relationships: A meta-analytic investigation of the literature, International Journal of Production Economics, 185, pp. 252-265, (2017); Azadegan A., Parast M., Lucianetti L., Nishicant R., Blackhurst J., Supply chain disruptions and business continuity: An empirical assessment, Decision Sciences, 51, pp. 38-73, (2020); Behzadi G., O'Sullivan M.J., Olsen T.L., On metrics for supply chain resilience, European Journal of Operational Research, 287, pp. 145-158, (2020); Belhadi A., Kamble S., Jabbour C.J.C., Gunasekaran A., Ndubisi M.O., Venkatesh M., Manufacturing and service supply chain resilience to the COVID-19 outbreak: Lessons learned from the automobile and airline industries, Technological Forecasting and Social Change, 163, pp. 1-19, (2021); Ben-Jebara M., Modi S.B., Product personalization and firm performance: An empirical analysis of the pharmaceutical industry, Journal of Operations Management, 67, pp. 82-104, (2021); Bode C., Wagner S.M., Petersen K.J., Ellram L.M., Understanding responses to supply chain disruptions: Insights from information processing and resource dependence perspectives, Academy of Management Journal, 54, pp. 833-856, (2011); Brandon-Jones E., Squire B., Autry C.W., Petersen K.J., A contingent resource-based perspective of supply chain resilience and robustness, Journal of Supply Chain Management, 50, pp. 55-73, (2014); Brusset X., Teller C., Supply chain capabilities, risks, and resilience, International Journal of Production Economics, 184, pp. 59-68, (2017); Cao M., Zhang Q., Supply chain collaboration: Impact on collaborative advantage and firm performance, Journal of Operations Management, 29, pp. 163-180, (2011); Chang W., Ellinger A., Kim K., Franke G., Supply chain integration and firm financial performance: A meta-analysis of positional advantage mediation and moderating factors, European Management Journal, 34, pp. 282-295, (2016); Choi T.Y., Rogers D., Vakil B., Coronavirus is a wake-up call for supply chain management, (2020); Cohen J.E., Statistical power analysis for the behavioral sciences, (1988); Craighead C.W., Blackhurst J., Rungtusanatham M.J., Handfield R.B., The severity of supply chain disruptions: Design characteristics and mitigation capabilities, Decision Sciences, 38, pp. 131-155, (2007); Duong L., Chong J., Supply chain collaboration in the presence of disruptions: A literature review, International Journal of Production Research, 58, pp. 3488-3507, (2020); Fan Y., Stevenson M., Li F., Supplier initiating risk management behaviour and supply-side resilience: The effects of interpersonal relationships and dependence asymmetry in buyer-supplier relationships, International Journal of Operations and Production Management, 40, pp. 971-995, (2020); Flynn B.B., Huo B., Zhao X., The impact of supply chain integration on performance: A contingency and configuration approach, Journal of Operations Management, 28, pp. 58-71, (2010); Gao S., Simchi-Levi D., Teo C., Yan Z., Disruption risk mitigation in supply chains: The risk exposure index revisited, Operations Research, 67, pp. 831-852, (2019); Hale T., Anania J., Angrist N., Boby T., Cameron-Blake E., Di Folco M., Ellen L., Goldszmidt R., Hallas L., Kira B., Luciano M., Majumdar S., Nagesh R., Petherick A., Phillips T., Tatlow H., Webster S., Wood A., Zhang Y., Variation in government responses to COVID-19 version 12.0. Blavatnik School of Government, Working Paper, (2021); Han J., Kamber M., Pei J., Data mining: Concepts and techniques, (2012); Hosseini S., Ivanov D., Dolgui A., Review of quantitative methods for supply chain resilience analysis, Transportation Research Part E, 125, pp. 285-307, (2019); Ivanov D., Predicting the impacts of epidemic outbreaks on global supply chains: A simulation-based analysis on the coronavirus outbreak (COVID-19/SARS-CoV-2) case, Transportation Research Part E, 136, (2020); Jacobides M.G., Cennamo C., Gawer A., Towards a theory of ecosystems, Strategic Management Journal, 39, 8, pp. 2255-2276, (2018); Jain A., Jain P.K., Chan F., Singh S., A review on manufacturing flexibility, International Journal of Production Research, 51, pp. 5949-5970, (2013); Juttner U., Maklan S., Supply chain resilience in the global financial crisis: An empirical study, Supply Chain Management: An International Journal, 16, pp. 246-259, (2011); Kamalahmadi M., Parast M., A review of the literature on the principles of enterprise and supply chain resilience: Major findings and directions for future research, International Journal of Production Economics, 171, pp. 116-133, (2016); 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McIntyre D.P., Srinivasan A., Networks, platforms, and strategy: Emerging views and next steps, Strategic Management Journal, 38, 1, pp. 141-160, (2017); Mishra S., Modi S., Animesh A., The relationship between information technology capability, inventory efficiency and shareholder wealth: A firm-level empirical analysis, Journal of Operations Management, 31, pp. 298-312, (2013); Narasimhan R., Talluri S., Das A., Exploring flexibility and execution competencies of manufacturing firms, Journal of Operations Management, 22, pp. 91-106, (2004); Purchasing managers index for October 2020, (2020); Pettit T.J., Croxton K.L., Fiksel J., The evolution of resilience in supply chain management: A retrospective on ensuring supply chain resilience, Journal of Business Logistics, 40, pp. 56-65, (2019); Reeves M., Faste L., Chen C., Carlsson-Szlezak P., Whitaker K., How Chinese companies have responded to coronavirus, (2020); Sarkar S., Kumar S., A behavioral experiment on inventory management with supply chain disruption, International Journal of Production Economics, 169, pp. 169-178, (2015); 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Upton D.M., The management of manufacturing flexibility, California Management Review, 36, 2, pp. 72-89, (1994); Vokurka R.J., O'leary-Kelly S.W., A review of empirical research on manufacturing flexibility, Journal of Operations Management, 18, pp. 485-501, (2000); Wan X., Sanders R., The negative impact of product variety: Forecast bias, inventory levels, and the role of vertical integration, International Journal of Production Economics, 186, pp. 123-131, (2017); Wong C.Y., Boon-Itt S., Wong C.W.Y., The contingency effects of environmental uncertainty on the relationship between supply chain integration and operational performance, Journal of Operations Management, 29, pp. 604-615, (2011); Zhang Q., Vonderembse M.A., Lim J.S., Manufacturing flexibility: Defining and analyzing relationships among competence, capability, and customer satisfaction, Journal of Operations Management, 21, pp. 173-191, (2003); Zhang Y., Hale T., Wood A., Phillips T., Petherick A., Di Folco M., Meng K., Ge T., Chinese provincial government responses to COVID-19 version 1.0, (2021); Zhou Y., Wan X., Product variety and vertical integration, Strategic Management Journal, 38, pp. 1134-1150, (2017)","Q. Wang; School of International Trade and Economics, University of International Business & Economics, Beijing, China; email: qwang@uibe.edu.cn",null,"John Wiley and Sons Inc",{"$nulls":5},2726963.0,null,"JOTME",null,"English","J Oper Manage","Article","Final",null,"Scopus","2-s2.0-85142877189"]
["Samudio Lezcano M.; Harper C.D.; Nock D.; Lowry G.V.; Michalek J.J.","Samudio Lezcano, Mateo (58172528800); Harper, Corey D. (57190285243); Nock, Destenie (56203946100); Lowry, Gregory V. (7003945037); Michalek, Jeremy J. (7006027951)","58172528800; 57190285243; 56203946100; 7003945037; 7006027951","Online grocery delivery: Sustainable practice, or congestion generator and environmental burden?",2023.0,"Transportation Research Part D: Transport and Environment",119.0,null,103722.0,null,null,null,3.0,"10.1016/j.trd.2023.103722","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85151810410&doi=10.1016%2fj.trd.2023.103722&partnerID=40&md5=bdbb7ea82feb4ffd81e8406dc683b6c4","Department of Civil and Environmental Engineering, Carnegie Mellon University, Porter Hall, 4815 Frew Street, Pittsburgh, 15213, PA, United States; Heinz School of Information Systems and Public Policy, Carnegie Mellon University, Hamburg Hall, 4800 Forbes Avenue, Pittsburgh, 15213, PA, United States; Department of Engineering and Public Policy, Carnegie Mellon University, Wean Hall, 5000 Forbes Avenue, Pittsburgh, 15213, PA, United States; Department of Mechanical Engineering, Carnegie Mellon University Wean Hall, 5000 Forbes Avenue, Pittsburgh, 15213, PA, United States","Samudio Lezcano M., Department of Civil and Environmental Engineering, Carnegie Mellon University, Porter Hall, 4815 Frew Street, Pittsburgh, 15213, PA, United States; Harper C.D., Department of Civil and Environmental Engineering, Carnegie Mellon University, Porter Hall, 4815 Frew Street, Pittsburgh, 15213, PA, United States, Heinz School of Information Systems and Public Policy, Carnegie Mellon University, Hamburg Hall, 4800 Forbes Avenue, Pittsburgh, 15213, PA, United States; Nock D., Department of Civil and Environmental Engineering, Carnegie Mellon University, Porter Hall, 4815 Frew Street, Pittsburgh, 15213, PA, United States, Department of Engineering and Public Policy, Carnegie Mellon University, Wean Hall, 5000 Forbes Avenue, Pittsburgh, 15213, PA, United States; Lowry G.V., Department of Civil and Environmental Engineering, Carnegie Mellon University, Porter Hall, 4815 Frew Street, Pittsburgh, 15213, PA, United States; Michalek J.J., Department of Engineering and Public Policy, Carnegie Mellon University, Wean Hall, 5000 Forbes Avenue, Pittsburgh, 15213, PA, United States, Department of Mechanical Engineering, Carnegie Mellon University Wean Hall, 5000 Forbes Avenue, Pittsburgh, 15213, PA, United States","Grocery delivery services have seen rapid growth in recent years. We develop a method to estimate changes in travel patterns caused by grocery delivery adoption and apply it to a case study in Seattle, WA. Results suggest that delivery can increase or decrease peak hour emissions (−0.9% to + 4.9%) and vehicle hours traveled (−4.2% to + 6.3%), depending most critically on (1) delivery center location, (2) whether deliveries displace dedicated or non-dedicated shopping trips, (3) the degree to which delivery replaces shopping trips or increases demand, (4) the number of deliveries that can be coordinated in a single route, and (5) delivery timing relative to peak travel periods. No scenarios tested where deliveries originate from the store where customers shop achieve emissions or energy use reductions; however, congestion reductions of 3.4% are still possible if the delivery trips are shifted to off-peak hours. © 2023 The Author(s)","E-commerce; Emissions; Energy; Grocery delivery; Traffic congestion; Traffic simulation","Seattle; United States; Washington [United States]; Electronic commerce; Sustainable development; Delivery service; Emission; Energy; Environmental burdens; Grocery delivery; Rapid growth; Shopping trip; Sustainable practices; Traffic simulations; Travel patterns; electronic commerce; emission; energy use; shopping activity; traffic congestion; Traffic congestion",{"$nulls":4},"Carnegie Institute of Technology; Puget Sound Regional Council; U.S. Department of Transportation, DOT, (69A3551747111); Carnegie Mellon University, CMU","Funding text 1: These projects benefited from funding by the Carnegie Institute of Technology, the Dr. Elio D’Appolonia Graduate Fellowship program, the Metro21 Smart Cities Institute at Carnegie Mellon University, and the ATLAS Group at Carnegie Mellon University. This research was also supported by the US DOT [Grant Number 69A3551747111] through Mobility21, a University Transportation Center, with the goal of improving mobility of goods and services. This project benefitted from the collabotation with Zhufeng Fan from the Civil and Environmental Engineering Department of Carnegie Mellon University, as he provided the calibrated baseline demand matrix of Seattle. The data used for the case study was provided by the Puget Sound Regional Council. ; Funding text 2: These projects benefited from funding by the Carnegie Institute of Technology, the Dr. Elio D'Appolonia Graduate Fellowship program, the Metro21 Smart Cities Institute at Carnegie Mellon University, and the ATLAS Group at Carnegie Mellon University. This research was also supported by the US DOT [Grant Number 69A3551747111] through Mobility21, a University Transportation Center, with the goal of improving mobility of goods and services. This project benefitted from the collabotation with Zhufeng Fan from the Civil and Environmental Engineering Department of Carnegie Mellon University, as he provided the calibrated baseline demand matrix of Seattle. The data used for the case study was provided by the Puget Sound Regional Council.","(2021); Astashkina E., Belavina E., Marinesi S., The environmental impact of the advent of online grocery retailing, SSRN Electron. J., (2019); Auf der Landwehr M., Trott M., von Viebahn C., Simulation-based Assessment of Grocery Shopping in Urban Areas, SNE Simulation Notes Europe, 30, 4, pp. 145-158, (2020); Aziz S., Maltese I., Marcucci E., Gatta V., Benmoussa R., Irhirane E.H., Energy consumption and environmental impact of E-Grocery: a systematic literature review, Energies, 15, 19, (2022); Balk G., (2019); (2021); Fan Z., Harper C.D., Congestion and environmental impacts of short car trip replacement with micromobility modes, Transp. Res. Part D: Transport Environ., 103, (2022); Gatta V., Marcucci E., Maltese I., Iannaccone G., Fan J., E-Groceries: a channel choice analysis in Shanghai, Sustainability, 13, 7, (2021); Google L.L.C., Google Earth Pro [Computer software], (2022); Hanig L., Harper C.D., Nock D., COVID-19 public transit precautions: Trade-offs between risk reduction and costs, Transp. Res. Interdiscip. Perspect., 18, (2023); Hardi L., Wagner U., Grocery delivery or customer pickup—Influences on energy consumption and CO<sub>2</sub> emissions in Munich, Sustainability, 11, 3, (2019); Harper C.D., Hendrickson C.T., Samaras C., Exploring the economic, environmental, and travel implications of changes in parking choices due to driverless vehicles: an agent-based simulation approach, J. Urban Planning Dev., 144, 4, (2018); Heldt B., Matteis T., von Schmidt A., Heinrichs M., Cool but dirty food? – Estimating the impact of grocery home delivery on transport and CO<sub>2</sub> emissions including cooling, Res. Transp. Econ., 87, (2021); (2021); Jaller M., Pahwa A., Evaluating the environmental impacts of online shopping: a behavioral and transportation approach, Transp. Res. Part D: Transport Environ., 80, (2020); (2022); Maltese I., Le Pira M., Marcucci E., Gatta V., Evangelinos C., Grocery or @grocery: a stated preference investigation in Rome and Milan, Res. Transp. Econ., 87, (2021); Marcucci E., Gatta V., Le Pira M., Chao T., Li S., Bricks or clicks? Consumer channel choice and its transport and environmental implications for the grocery market in Norway, Cities, 110, (2021); (2022); Morgan B., (2020); (2014); PTV A.G., (2021); (2021); Siikavirta H., Punakivi M., Karkkainen M., Linnanen L., Effects of E-Commerce on greenhouse gas emissions: a case study of grocery home delivery in Finland, J. Ind. Ecol., 6, 2, pp. 83-97, (2008); Tehrani S., Karbassi A., Ghoddosi J., Monavvari S., Mirbagheri S., Prediction of energy consumption and urban air pollution reduction in e-shopping adoption, J. Food Agric. Environ., 7, 3-4, pp. 898-903, (2009); van Loon P., Deketele L., Dewaele J., McKinnon A., Rutherford C., A comparative analysis of carbon emissions from online retailing of fast moving consumer goods, J. Cleaner Product., 106, pp. 478-486, (2015); Wygonik E., Goodchild A., Evaluating the efficacy of shared-use vehicles for reducing greenhouse gas emissions: A U.S. case study of grocery delivery, J. Transp. Res. Forum, 51, 2, (2012)","M. Samudio Lezcano; Department of Civil and Environmental Engineering, Carnegie Mellon University, Pittsburgh, Porter Hall, 4815 Frew Street, 15213, United States; email: csamudio@andrew.cmu.edu",null,"Elsevier Ltd",{"$nulls":5},1.3619209E7,null,"TRDTF",null,"English","Transp. Res. Part D Transp. Environ.","Article","Final","All Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85151810410"]
["Wang K.; Chen Z.; Cheng L.; Zhu P.; Shi J.; Bian Z.","Wang, Kailai (57202419560); Chen, Zhenhua (55578621900); Cheng, Long (56678178600); Zhu, Pengyu (36624731400); Shi, Jian (55491835900); Bian, Zheyong (56844654800)","57202419560; 55578621900; 56678178600; 36624731400; 55491835900; 56844654800","Integrating spatial statistics and machine learning to identify relationships between e-commerce and distribution facilities in Texas, US",2023.0,"Transportation Research Part A: Policy and Practice",173.0,null,103696.0,null,null,null,1.0,"10.1016/j.tra.2023.103696","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85159629214&doi=10.1016%2fj.tra.2023.103696&partnerID=40&md5=ace2038616443b31d6798d39da043cab","Department of Construction Management, University of Houston, United States; City and Regional Planning, Knowlton School of Architecture, The Ohio State University, United States; Jiangsu Key Laboratory of Urban ITS, Southeast University, China; Department of Geography, Ghent University, Belgium; Division of Public Policy, Hong Kong University of Science and Technology, Hong Kong; Department of Engineering Technology, University of Houston, United States","Wang K., Department of Construction Management, University of Houston, United States; Chen Z., City and Regional Planning, Knowlton School of Architecture, The Ohio State University, United States; Cheng L., Jiangsu Key Laboratory of Urban ITS, Southeast University, China, Department of Geography, Ghent University, Belgium; Zhu P., Division of Public Policy, Hong Kong University of Science and Technology, Hong Kong; Shi J., Department of Engineering Technology, University of Houston, United States; Bian Z., Department of Construction Management, University of Houston, United States","This paper proposes a novel analytical framework that integrates spatial statistics and machine learning techniques to identify relationships between e-commerce and distribution facilities. The framework includes centrographic analysis, global and local spatial association measurements, and a recently popularized interpretable machine learning approach – gradient boosting decision trees (GBDT) – to analyze warehousing location choices. We apply this framework to ZIP Codes Business Patterns data from 2003 to 2016 in three large metropolitan areas in Texas, US (i.e., Dallas-Fort Worth, Austin, and Houston). The thematic maps reveal the spatial clustering of areas with higher e-commerce activity but lower logistics facility coverage. It is worth noting that we do not observe logistics sprawl in the study region. The GBDT results show that industrial activities and transportation network accessibility are key factors influencing warehousing location choices. We also find that the relationship between warehouses and e-commerce establishments is weaker in Houston, a major maritime gateway for goods entering and leaving, as compared to Dallas-Fort Worth and Austin. Implications for local freight transportation planners and decision-makers are discussed. © 2023 Elsevier Ltd","E-Commerce; Gradient Boosting Decision Trees (GBDT); Logistics sprawl; Spatial analysis; Warehouses and Distribution Centers (W&DCs)","Texas; United States; Electronic commerce; Freight transportation; Machine learning; Maps; Spatial distribution; Spatial variables measurement; Warehouses; Distribution centres; Distribution facilities; E- commerces; Gradient boosting; Gradient boosting decision tree; Logistic sprawl; Spatial analysis; Spatial statistics; Statistics learning; Warehouse and distribution center; accessibility; electronic commerce; identification method; information and communication technology; integrated approach; logistics; machine learning; metropolitan area; spatial analysis; Decision trees",{"$nulls":4},"NRUF, (R0507403); University of Houston-National Research University Fund","This study was partially supported by the University of Houston-National Research University Fund (NRUF) (Project Number: R0507403). 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Technol., 58, pp. 308-324, (2015)","L. Cheng; Jiangsu Key Laboratory of Urban ITS, Southeast University, China; email: long.cheng@ugent.be",null,"Elsevier Ltd",{"$nulls":5},9658564.0,null,null,null,"English","Transp. Res. Part A Policy Pract.","Article","Final",null,"Scopus","2-s2.0-85159629214"]
["Varghese A.M.; Jacob R.T.; Narayanamurthy G.","Varghese, Ann Mary (58688087500); Jacob, Remya Tressa (57749104300); Narayanamurthy, Gopalakrishnan (36638192700)","58688087500; 57749104300; 36638192700","Shoppre’s dilemma with marketplace launch – Do it sooner, delay for later or dismiss forever?",2023.0,"Emerald Emerging Markets Case Studies",14.0,1.0,null,1.0,36.0,35.0,0.0,"10.1108/EEMCS-05-2023-0158","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85181471743&doi=10.1108%2fEEMCS-05-2023-0158&partnerID=40&md5=b9ff708c48e2c116d4e233e29f1a676e","Vinod Gupta School of Management, Indian Institute of Technology, Kharagpur, India; Manipal Academy of Higher Education, T A Pai Management Institute, Manipal, India; Department of Operations and Supply Chain Management, University of Liverpool Management School, Liverpool, United Kingdom","Varghese A.M., Vinod Gupta School of Management, Indian Institute of Technology, Kharagpur, India; Jacob R.T., Manipal Academy of Higher Education, T A Pai Management Institute, Manipal, India; Narayanamurthy G., Department of Operations and Supply Chain Management, University of Liverpool Management School, Liverpool, United Kingdom","Learning outcomes: After completing the case study, the students will be able to explore, create and capture the dilemmas of a platform strategy; compare, contrast and configure strategies for successful platform adoption; develop fitting configurations for marketplace design; and use temple framework to evaluate the dilemma of the element of time (do it sooner, delay for later or dismiss forever) in launching a new marketplace. Case overview/synopsis: Shoppre was a parcel-forwarding firm established in 2017. In a short period, Shoppre turned out to be one of the best parcel forwarding and cross-border commerce companies in India, thanks to the first-mover advantage it enjoyed. Shoppre had offerings of shopping and shipping of cross-border e-commerce. As a new firm looking forward to increasing its market power, Shoppre faced the dilemma of whether to launch the marketplace, and if yes, whether to do it soon or delay it for the future. There was also confusion in the marketplace’s design and implementation. Nikkitha Shankar’s (she/her) worry was that if Shoppre did not decide quickly on this, there would be possible crises in managing the partners and their financial performance. Shankar was brainstorming the issues with the founding partner and was gauging the dimensions. This case study presented new marketplaces’ dilemmas along with managing sellers, customers, markets, finance, logistics and digital transformation. Complexity academic level: The case study is suitable for undergraduate- and graduate-level students pursuing courses in business programmes and senior management professionals participating in executive education programmes. The case study will also fit well for courses such as the “Platform strategy: building and thriving in a vibrant ecosystem” course [1], digital business models [2] and digital business strategy [3]. Supplementary materials: Teaching notes are available for educators only. Subject code: CSS 11: Strategy. © 2023, Emerald Publishing Limited.","Business development; Business model innovation; E-commerce; Marketplace launch; Parcel forwarding; Platform economy; Strategic management; Temple framework",{"$nulls":8},"A.M. Varghese; Vinod Gupta School of Management, Indian Institute of Technology, Kharagpur, India; email: annmaryvar008@gmail.com",null,"Emerald Publishing",{"$nulls":5},2.0450621E7,null,null,null,"English","Emerald Emerg. Mark. Case Stud.","Article","Final",null,"Scopus","2-s2.0-85181471743"]
["Wang J.; Fu M.-J.","Wang, Jun (56211585400); Fu, Man-Jun (58249516300)","56211585400; 58249516300","Study on the Distribution of Fresh Food Support System—An Example of Shanghai during the Epidemic Closure of 2022",2023.0,"Sustainability (Switzerland)",15.0,9.0,7107.0,null,null,null,2.0,"10.3390/su15097107","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85159295435&doi=10.3390%2fsu15097107&partnerID=40&md5=728ecbc5ce3e7942e3f255f97d47357c","School of Art Design and Media, East China University of Science and Technology, No.130, Meilong Rd., Shanghai, 200237, China","Wang J., School of Art Design and Media, East China University of Science and Technology, No.130, Meilong Rd., Shanghai, 200237, China; Fu M.-J., School of Art Design and Media, East China University of Science and Technology, No.130, Meilong Rd., Shanghai, 200237, China","One of the key indicators to measure the sustainability and resilience of a city during a public health crisis is how well it can meet the daily needs of its residents. During the COVID-19 lockdown in Shanghai in 2022, e-commerce shopping and delivery became the most important method for ensuring the city’s material supplies. This article uses the distribution data of a fresh e-commerce platform’s pre-warehouse and static population distribution data to establish a basic material supply system evaluation model for the city and explore its resilience potential. Focusing on the central urban area of Shanghai, this study uses a population heat map with geographic coordinates to reflect the static distribution of residents and obtains the distribution data of the e-commerce pre-warehouses. Using kernel density analysis, the relationship between the pre-warehouses and the residents’ needs is established. Through analysis, it was found that the supply capacity of fresh food in different areas of Shanghai during the lockdown could be categorized as insufficient, adequate, or excessive. Based on these three categories, improvement strategies were proposed. Finally, this article suggests establishing a scientific supply security system to promote urban sustainability and prepare for future challenges. © 2023 by the authors.","basic material supply system; epidemic closure; sustainability; urban resilience","China; Shanghai; COVID-19; decision support system; distribution system; electronic commerce; epidemic; population distribution; public health; resilience; strategic approach; supply chain management; sustainability; urban area",{"$nulls":4},"National Social Science Fund of China, NSSFC, (19BJY063)","This research was funded by China National Social Science Fund (No. 19BJY063).","Holling C.S., Resilience and Stability of Ecological Systems, Annu. Rev. Ecol. 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Geogr, 40, pp. 607-619, (2021); Guida C., Gargiulo C., Caglioni M., Carpentieri G., Urban Accessibility to Healthcare Facilities for the Elderly: Evolution of the Time-Based 2SFCA Methodology for the Nice Case Study (France), Proceedings of the 21st International Conference on Computational Science and Its Applications, ICCSA 2021, (2021); Niembro A., Guevara T., Cavanagh E., Urban segregation and infrastructure in Latin America: A neighborhood typology for Bariloche, Argentina, Habitat Int, 10, (2020); Fan X.J., Study on Supply Decision System for Public Cultural Servicing Facilities Based on Satisfaction Degree, Ph.D. Thesis, (2016); Yang Q.Y., Xu J.G., An Analysis Model of Public Service Facilities Based on Attraction Accessibility, Planners, 31, pp. 96-101, (2015); Zhang H.L., Extracting Active Population Data Based on Baidu Heat Maps for Transportation Planning Applications, Urban Transp. China, 19, pp. 103-111, (2021); Tan X., Huang D.Q., Zhao X.S., Ying Y.U., Leng B., Feng L., Jobs housing balance based on Baidu thermodynamic diagram, J. Beijing Norm. Univ. (Nat. Sci.), 52, pp. 622-627, (2016); Wang F.H., Quantitative Methods Applications in GIS, (2011); Cheng L., Wang F.H., Xiu C.L., Trade Area of Supermarket in Changchun Centeral Urban Area Based on GIS, Econ. Geogr, 34, pp. 54-83, (2014)","J. Wang; School of Art Design and Media, East China University of Science and Technology, Shanghai, No.130, Meilong Rd., 200237, China; email: wangjun81@ecust.edu.cn",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85159295435"]
["Lim S.F.W.T.; Wang Q.; Webster S.","Lim, Stanley Frederick W.T. (57192250816); Wang, Qingchen (58043996300); Webster, Scott (7101874279)","57192250816; 58043996300; 7101874279","Do it right the first time: Vehicle routing with home delivery attempt predictors",2023.0,"Production and Operations Management",32.0,4.0,null,1262.0,1284.0,22.0,0.0,"10.1111/poms.13926","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85145729811&doi=10.1111%2fpoms.13926&partnerID=40&md5=e960936c7e71e5007dc73fb1d5651e24","Eli Broad College of Business, Michigan State University, East Lansing, MI, United States; Institute for Infocomm Research, A*STAR, Singapore; Ophelos Limited, London, United Kingdom; W.P. Carey School of Business, Arizona State University, Tempe, AZ, United States","Lim S.F.W.T., Eli Broad College of Business, Michigan State University, East Lansing, MI, United States, Institute for Infocomm Research, A*STAR, Singapore; Wang Q., Ophelos Limited, London, United Kingdom; Webster S., W.P. Carey School of Business, Arizona State University, Tempe, AZ, United States","Up to 20% of all business-to-consumer deliveries fail on the first attempt. Failed deliveries not only carry cost implications but also incur damage to retailers’ brand reputation. Despite its economic significance, research has paid little attention to delivery attempt as an operational outcome or seldom accounted for its effects in routing models. This is partly due to the many factors that can influence delivery outcomes. We address this knowledge gap by first demonstrating that failed delivery attempts can be reasonably predicted using common routing, demand, environmental, and market attributes at both the individual package and route levels. For model-building, we use transaction data from an e-commerce retailer in South America. We then explore the value of accounting for failed delivery attempts in routing models. We propose a two-stage greedy algorithm for solving large problem instances. Our analysis indicates that not accounting for the probability of failed attempts in routing models may create a significant downward bias in the total cost of delivery. The analysis also suggests that manipulating the sequence in which packages in a route are delivered can be a cost-efficient lever that firms can employ at almost zero cost to profoundly affect delivery outcomes. We replicate the prediction model to a new sample from a delivery company in Singapore and calibrate it for a randomized field experiment to validate our algorithm's performance. Packages and drivers are randomly assigned to either our algorithm or the focal company's existing algorithm. Results suggest that our algorithm, on average, reduces the share of failed delivery attempts by 10% and the total cost of delivery by $13 per route. We further propose drivers’ discretionary work effort and the goal-gradient hypothesis as a mechanism for the efficacy of our algorithm. Controlling for time of day and other fixed effects, we empirically find that packages assigned to slots later in the route tend to have a lower failure rate because drivers display a higher degree of discretionary work effort toward the end of a route. Our approach can be applied to other firms’ last-mile delivery operations to improve their delivery execution. © 2022 Production and Operations Management Society.","discretionary work effort; field experiment; goal-gradient hypothesis; home delivery attempt; online retailing; vehicle routing",{"$nulls":5},"University of Pennsylvania; Harvard Business School, HBS; National University of Singapore, NUS","The authors thank Jinjia Huang at National University of Singapore, Sheng Liu at University of Toronto, Antonio Moreno at Harvard Business School, Mark Poon at Amazon, and Xuanming Su at University of Pennsylvania, as well as seminar participants at The University of Hong Kong for helpful comments on an earlier version of this manuscript. The authors also thank the department editor Sunil Mithas, the anonymous associate editor, and the two reviewers for constructive reviews.","Anderson S.W., Baggett L.S., Widener S.K., The impact of service operations failures on customer satisfaction: Evidence on how failures and their source affect what matters to customers, Manufacturing & Service Operations Management, 11, 1, pp. 52-69, (2009); Baldacci R., Hadjiconstantinou E., Mingozzi A., An exact algorithm for the capacitated vehicle routing problem based on a two-commodity network flow formulation, Operations Research, 52, 5, pp. 723-738, (2004); Boyer K.K., Prud'homme A.M., Chung W., The last mile challenge: Evaluating the effects of customer density and delivery window patterns, Journal of Business Logistics, 30, 1, pp. 185-201, (2009); Boyer K.K., Hult G.T.M., Customer behavioral intentions for online purchases: An examination of fulfillment method and customer experience level, Journal of Operations Management, 24, 2, pp. 124-147, (2006); Bray R., Operational transparency: Showing when work gets done, Manufacturing & Service Operations Management, (2020); Chen T., Guestrin C., Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 785-794, (2016); Cui R., Li M., Li Q., Value of high-quality logistics: Evidence from a clash between SF Express and Alibaba, Management Science, 66, 9, pp. 3879-3902, (2020); Cui R., Sun T., Lu Z., Golden J., Sooner or later? 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Linking online order fulfillment glitches with future purchase behavior, Journal of Operations Management, 29, 7-8, pp. 692-703, (2011); Rao S., Rabinovich E., Raju D., The role of physical distribution services as determinants of product returns in Internet retailing, Journal of Operations Management, 32, 6, pp. 295-312, (2014); Shang W., Liu L., Promised delivery time and capacity games in time-based competition, Management Science, 57, 3, pp. 599-610, (2011); Shmueli G., To explain or to predict?, Statistical Science, 25, 3, pp. 289-310, (2010); E-commerce as percentage of total retail sales worldwide from 2015 to 2020, with forecasts from 2021 to 2025, (2022); Number of parcels distributed worldwide from 2015 to 2020, by sector, (2022); Sun J., Zhang D., Hu H., Van Mieghem J.A., Predicting human discretion to adjust algorithmic prescription: A large-scale field experiment in warehouse operations, Management Science, 68, 2, pp. 846-865, (2022); Tashman L.J., Out-of-sample tests of forecasting accuracy: An analysis and review, International Journal of Forecasting, 16, 4, pp. 437-450, (2000); Tokar T., Williams B.D., Fugate B.S., I heart logistics—Just don't ask me to pay for it: Online shopper behavior in response to a delivery carrier upgrade and subsequent shipping charge increase, Journal of Business Logistics, 41, 3, pp. 182-205, (2020); Wang H., Routing and scheduling for a last-mile transportation system, Transportation Science, 53, 1, pp. 131-147, (2019); White H., A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity, Econometrica, 48, 4, pp. 817-838, (1980)","S.F.W.T. Lim; Eli Broad College of Business, Michigan State University, East Lansing, 632 Bogue St, 48825, United States; email: slim@msu.edu",null,"John Wiley and Sons Inc",{"$nulls":5},1.0591478E7,null,null,null,"English","Prod. Oper. Manage.","Article","Final",null,"Scopus","2-s2.0-85145729811"]
["Ding M.; Ullah N.; Grigoryan S.; Hu Y.; Song Y.","Ding, Mengyue (57565986000); Ullah, Nadeem (57353044800); Grigoryan, Sara (57565397100); Hu, Yike (57208507528); Song, Yan (35224016100)","57565986000; 57353044800; 57565397100; 57208507528; 35224016100","Variations in the Spatial Distribution of Smart Parcel Lockers in the Central Metropolitan Region of Tianjin, China: A Comparative Analysis before and after COVID-19",2023.0,"ISPRS International Journal of Geo-Information",12.0,5.0,203.0,null,null,null,1.0,"10.3390/ijgi12050203","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85160294352&doi=10.3390%2fijgi12050203&partnerID=40&md5=a3a34b1cddff3289633ce4f1ddd8559e","School of Architecture, Tianjin University, Tianjin, 300072, China; Department of City and Regional Planning, University of North Carolina at Chapel Hill, Chapel Hill, 27599, NC, United States","Ding M., School of Architecture, Tianjin University, Tianjin, 300072, China, Department of City and Regional Planning, University of North Carolina at Chapel Hill, Chapel Hill, 27599, NC, United States; Ullah N., School of Architecture, Tianjin University, Tianjin, 300072, China; Grigoryan S., School of Architecture, Tianjin University, Tianjin, 300072, China; Hu Y., School of Architecture, Tianjin University, Tianjin, 300072, China; Song Y., Department of City and Regional Planning, University of North Carolina at Chapel Hill, Chapel Hill, 27599, NC, United States","The COVID-19 pandemic has led to a significant increase in e-commerce, which has prompted residents to shift their purchasing habits from offline to online. As a result, Smart Parcel Lockers (SPLs) have emerged as an accessible end-to-end delivery service that fits into the pandemic strategy of maintaining social distance and no-contact protocols. Although numerous studies have examined SPLs from various perspectives, few have analyzed their spatial distribution from an urban planning perspective, which could enhance the development of other disciplines in this field. To address this gap, we investigate the distribution of SPLs in Tianjin’s central urban area before and after the pandemic (i.e., 2019 and 2022) using kernel density estimation, average nearest neighbor analysis, standard deviation elliptic, and geographical detector. Our results show that, in three years, the number of SPLs has increased from 51 to 479, and a majority were installed in residential communities (i.e., 92.2% in 2019, and 97.7% in 2022). We find that SPLs were distributed randomly before the pandemic, but after the pandemic, SPLs agglomerated and followed Tianjin’s development pattern. We identify eight influential factors on the spatial distribution of SPLs and discuss their individual and compound effects. Our discussion highlights potential spatial distribution analysis, such as dynamic layout planning, to improve the allocation of SPLs in city planning and city logistics. © 2023 by the authors.","average nearest neighbor; COVID-19; geographical detector; kernel density estimation; last-delivery logistics; self-service facilities; self-service technology; smart parcel lockers; standard deviational ellipse; Tianjin",{"$nulls":5},"Science and Technology R&D Platform Construction Special Project of Hebei Province, China, (21567631H); National Natural Science Foundation of China, NSFC, (52038007)","This research was funded by Reconstructing the Architecture System based on the Coherence Mechanism of “Architecture-human-environment” in the Chinese Context, Key Project of National Natural Science Foundation of China, grant number 52038007, and “Science and Technology R&D Platform Construction Special Project of Hebei Province, China (21567631H)”.","Bhatti A., Akram H., Basit H.M., Khan A.U., Raza S.M., Naqvi M.B., E-commerce trends during COVID-19 Pandemic, Int. 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Infect, 148, (2020); Lemke J., Iwan S., Korczak J., Usability of the Parcel Lockers from the Customer Perspective—The Research in Polish Cities, Transp. Res. Rec, 16, pp. 272-287, (2016); Schaefer J.S., Figliozzi M.A., Spatial accessibility and equity analysis of Amazon parcel lockers facilities, J. Transp. Geogr, 97, (2021); Ranjbari A., Diehl C., Dalla Chiara G., Goodchild A., What is the Right Size for a Residential Building Parcel Locker?, Transp. Res. Rec, 2677, pp. 1397-1407, (2022); Lagorio A., Pinto R., The parcel locker location issues: An overview of factors affecting their location, Interconnected Supply Chains in an Era of Innovation, Proceedings of the 8th International Conference on Information Systems, Logistics and Supply Chain, ILS, Austin, TX, USA, 22–24 April 2020, pp. 414-421, (2020); Schwerdfeger S., Boysen N., Optimizing the changing locations of mobile parcel lockers in last-mile distribution, Eur. J. Oper. Res, 285, pp. 1077-1094, (2020); Ssa B., Nb A., Who moves the locker? A benchmark study of alternative mobile parcel locker concepts, Transp. Res. Part C Emerg. Technol, 142, (2022); Che Z.H., Chiang T.A., Luo Y.J., Multiobjective Optimization for Planning the Service Areas of Smart Parcel Locker Facilities in Logistics Last Mile Delivery, Mathematics, 10, (2022); Aurambout J.P., Gkoumas K., Ciuffo B., Last mile delivery by drones: An estimation of viable market potential and access to citizens across European cities, Eur. Transp. Res. Rev, 11, (2019); Lemardele C., Estrada M., Pages L., Bachofner M., Potentialities of drones and ground autonomous delivery devices for last-mile logistics, Transp. Res. E Logist. Transp. Rev, 149, (2021); Wang Y., Bi M., Chen Y., A scheduling strategy of mobile parcel lockers for the last mile delivery problem, Promet-Zagreb, 32, pp. 875-885, (2020); Boysen N., Fedtke S., Schwerdfeger S., Last-mile delivery concepts: A survey from an operational research perspective, Or Spectr, 43, pp. 1-58, (2021)","Y. Hu; School of Architecture, Tianjin University, Tianjin, 300072, China; email: huyike11@tju.edu.cn",null,"MDPI",{"$nulls":5},2.2209964E7,null,null,null,"English","ISPRS Int. J. Geo-Inf.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85160294352"]
["Wang X.; Liu Z.; Li X.","Wang, Xudong (58091624400); Liu, Zeyu (57215544718); Li, Xueping (55718185700)","58091624400; 57215544718; 55718185700","Optimal delivery route planning for a fleet of heterogeneous drones: A rescheduling-based genetic algorithm approach",2023.0,"Computers and Industrial Engineering",179.0,null,109179.0,null,null,null,5.0,"10.1016/j.cie.2023.109179","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85151023637&doi=10.1016%2fj.cie.2023.109179&partnerID=40&md5=bb8b8cdf20067adcc9a9c76a87588cc5","Department of Industrial and Systems Engineering, The University of Tennessee, Knoxville, 37996, TN, United States; Department of Industrial and Management Systems Engineering, West Virginia University, Morgantown, 26506, WV, United States","Wang X., Department of Industrial and Systems Engineering, The University of Tennessee, Knoxville, 37996, TN, United States; Liu Z., Department of Industrial and Management Systems Engineering, West Virginia University, Morgantown, 26506, WV, United States; Li X., Department of Industrial and Systems Engineering, The University of Tennessee, Knoxville, 37996, TN, United States","The past decade has witnessed the rapid growth of pilot studies and the adoption of drone-assisted delivery by many e-commerce companies. In practice, delivery companies usually assemble fleets of drones consisting of heterogeneous configurations to satisfy various customer package demands, and this calls for in-depth research on how to deliver packages via drones efficiently. In this study, we extend the classic vehicle routing problem (VRP) by optimally scheduling the operations in a package depot center with a fleet of drones with different capacities, speeds, and maximum flight ranges. The drones travel multiple sorties to serve customers nearby. We formulate this problem as a mixed integer programming (MIP) model that minimizes the total delivery time for a set of packages. Due to the NP-hardness of the problem, we first develop a FIFO-based genetic algorithm (FBGA) to solve the problem. In anticipation of multiple trips, we further propose a modified, rescheduling-based genetic algorithm (RBGA) that incorporates a small-scale routing-planning optimization model that “reschedules” drone operations at the end of drone sorties, with the objective of minimizing the completion time. The RBGA features the combination of the knapsack problem, the shortest path problem, and a scheduling problem, from which near-optimal delivery plans are obtained for the fleet of drones. We conduct extensive numerical experiments with different numbers of customers and drones to evaluate the performance of the algorithms. The results suggest that compared with MIP, the proposed algorithms solve the problem efficiently for the testing instances, particularly for large instances that MIP fails to solve in time, indicating the practicality of the proposed methods for real-world implementations. © 2023 Elsevier Ltd","Drone delivery; Genetic algorithm; Mixed integer linear programming; Vehicle routing problem","Combinatorial optimization; Customer satisfaction; Drones; Fleet operations; Graph theory; Integer programming; Routing algorithms; Sales; Vehicle routing; Delivery routes; Drone delivery; Genetic algorithm approach; Integer Linear Programming; Mixed integer linear; Mixed integer linear programming; Mixed-Integer Programming; Rapid growth; Route planning; Vehicle Routing Problems; Genetic algorithms",{"$nulls":4},"Oak Ridge National Laboratory, ORNL; University of Tennessee, UT","The research was supported in part by the Graduate Advancement, Training and Education (GATE) Program between the Oak Ridge National Laboratory and the University of Tennessee, Knoxville .","Amazon, Amazon prime air, (2019); 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Hassanalian M., Abdelkefi A., Classifications, applications, and design challenges of drones: A review, Progress in Aerospace Sciences, 91, pp. 99-131, (2017); Holland J.H., Et al., Adaptation in natural and artificial systems: an introductory analysis with applications to biology, control, and artificial intelligence, (1992); Kim S.J., Lim G.J., Cho J., Cote M.J., Drone-aided healthcare services for patients with chronic diseases in rural areas, Journal of Intelligent and Robotic Systems, 88, pp. 163-180, (2017); Kirschstein T., Comparison of energy demands of drone-based and ground-based parcel delivery services, Transportation Research Part D: Transport and Environment, 78, (2020); Kitjacharoenchai P., Ventresca M., Moshref-Javadi M., Lee S., Tanchoco J.M., Brunese P.A., Multiple traveling salesman problem with drones: Mathematical model and heuristic approach, Computers & Industrial Engineering, 129, pp. 14-30, (2019); Liu C., Chen H., Li X., Liu Z., A scheduling decision support model for minimizing the number of drones with dynamic package arrivals and personalized deadlines, Expert Systems with Applications, 167, (2021); 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Torabbeigi M., Lim G.J., Kim S.J., Drone delivery scheduling optimization considering payload-induced battery consumption rates, Journal of Intelligent and Robotic Systems, 97, pp. 471-487, (2020); Toth P., Vigo D., Models, relaxations and exact approaches for the capacitated vehicle routing problem, Discrete Applied Mathematics, 123, pp. 487-512, (2002); Walmart, Walmart now piloting on-demand drone delivery with flytrex, (2020); Wang X., Poikonen S., Golden B., The vehicle routing problem with drones: several worst-case results, Optimization Letters, 11, pp. 679-697, (2017)","X. Li; Department of Industrial and Systems Engineering, The University of Tennessee, Knoxville, 37996, United States; email: xueping.li@utk.edu",null,"Elsevier Ltd",{"$nulls":5},3608352.0,null,"CINDD",null,"English","Comput Ind Eng","Article","Final",null,"Scopus","2-s2.0-85151023637"]
["G R.; Asokan-Ajitha A.","G, Rejikumar (55513688700); Asokan-Ajitha, Aswathy (57488230300)","55513688700; 57488230300","Business customer experience in B2B2C service settings: a scale development",2023.0,"Journal of Business and Industrial Marketing",38.0,4.0,null,886.0,904.0,18.0,4.0,"10.1108/JBIM-07-2021-0342","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85132800438&doi=10.1108%2fJBIM-07-2021-0342&partnerID=40&md5=a7a4fcf7560775ffe0e006d98dba25e7","Department of Management, Amrita Vishwa Vidyapeetham, Kochi Campus, India; Indian Institute of Management Amritsar, Amritsar, India","G R., Department of Management, Amrita Vishwa Vidyapeetham, Kochi Campus, India; Asokan-Ajitha A., Indian Institute of Management Amritsar, Amritsar, India","Purpose: Business-to-business (B2B) relations will become more prevalent in many areas such as delivery services, based on current trends supporting e-commerce proliferation. In addition, hyperlocal e-commerce, which focuses on customers in a small geographic region, relies heavily on another business to handle the supply chain. Emerging trends in business to business to customer (B2B2C) experiences provide retailers with opportunities to develop strategies for better customer service. Therefore, the purpose of this study was to develop a scale for measuring business customer experience in the B2B2C aggregator business model. Design/methodology/approach: Using the psychometric scale development procedure, the researchers devised a 29-item, six-dimensional scale measuring business customer experience with the help of two cross-sectional studies. Restaurant managers who rely on delivery partners to serve their customers were surveyed twice. The authors validated a scale for assessing business customer experience using exploratory factor analysis, confirmatory factor analysis and structural equation modelling. Findings: Based on fit criteria, a higher-order formative structure was best suited to the scale. The dimensions identified were shared vision, interaction experience, end-customer focus, relationship experience, service experience and outcome focus. According to the study, business customer experience is more objective and utilitarian than existing paradigms on customer experience. Research limitations/implications: Theoretically, this research helps to understand the underpinnings behind the formation of business customer experience and attempt to bring transformative service research focus in the B2B2C trilogy as better experiences predict the well-being of members of the business centre in the B2B. Practical implications: Practically, this research helps businesses to revisit their strategies for a better relationship with business partners for jointly offering an improved experience to the end customers. Originality/value: This study explains a pioneer attempt to develop a scale for business customer experience in the context of B2B2C aggregator business models. © 2022, Emerald Publishing Limited.","Aggregator business models; B2B2C; Business customer experience; End-customer focus; Scale development",{"$nulls":7},{"$cut":{"chars":30056,"head":"Ali F., Hussain K., Ragavan N.A., Memorable customer experience: examining the effects of customers experience on memories and loyalty in Malaysian resort hotels, Procedia – Social and Behavioral Sciences, 144, pp. 273-279, (2014); Almomani H.Q., Relationship quality as predictor of B2B customer loyalty in the pharmaceutical sector: evidence from Jordan, Journal of Relationship Marketing, 18, 2, pp. 108-123, (2019); Anderson E.W., Fornell C., Lehmann D.R., Customer satisfaction, market share, and profitability: findings from Sweden, Journal of Marketing, 58, 3, pp. 53-66, (1994); Anderson J.C., Narus J.A., A model of distributor firm and manufacturer firm working partnerships, Journal of Marketing, 54, 1, pp. 42-58, (1990); Arli D., Bauer C., Palmatier R.W., Relational selling: past, present and future, Industrial Marketing Management, 69, pp. 169-184, (2018); Arnold C., Kiel D., Voigt K.I., How the industrial internet of things changes business models in different manufacturing industries, Digital Disruptive Innovation, pp. 139-168, (2020); Ashforth B.E., Humphrey R.H., Labeling processes in the organization, Research in Organizational Behavior, 17, pp. 413-461, (1995); Babin B.J., Darden W.R., Griffin M., Work and/or fun: measuring hedonic and utilitarian shopping value, Journal of Consumer Research, 20, 4, pp. 644-656, (1994); Bagozzi R.P., The role of social and self‐conscious emotions in the regulation of business‐to‐business relationships in salesperson‐customer interactions, Journal of Business & Industrial Marketing, 21, 7, pp. 453-457, (2006); Baker W.E., Sinkula J.M., The synergistic effect of market orientation and learning orientation on organizational performance, Journal of the Academy of Marketing Science, 27, 4, pp. 411-427, (1999); Barrera R.B., Garcia A.N., Moreno M.R., Evaluation of the e-service quality in service encounters with incidents: differences according to the socio-demographic profile of the online consumer, Revista Europea de Dirección y Economía de la Empresa, 23, 4, pp. 184-193, (2014); Battisti S., Brem A., Digital entrepreneurs in technology-based spinoffs: an analysis of hybrid value creation in retail public–private partnerships to tackle showrooming, Journal of Business & Industrial Marketing, 36, 10, pp. 1780-1792, (2021); Becker L., Jaakkola E., Halinen A., Toward a goal-oriented view of customer journeys, Journal of Service Management, 31, 4, pp. 767-790, (2020); Bentler P.M., Chou C.P., Practical issues in structural modeling, Sociological Methods & Research, 16, 1, pp. 78-117, (1987); Berry L.L., Carbone L.P., Build loyalty through experience management, Quality Progress, 40, 9, pp. 26-32, (2007); Bhattacharjee A., Mogilner C., Happiness from ordinary and extraordinary experiences, Journal of Consumer Research, 41, 1, pp. 1-17, (2014); Biedenbach G., Marell A., The impact of customer experience on brand equity in a business-to-business services setting, Journal of Brand Management, 17, 6, pp. 446-458, (2010); Biggemann S., Williams M., Kro G., Building in sustainability, social responsibility and value co-creation, Journal of Business & Industrial Marketing, 29, 4, pp. 304-312, (2014); Bitner M.J., Services-capes: the impact of physical surroundings on customers and employees, Journal of Marketing, 56, 2, pp. 57-71, (1992); Bollen K., Lennox R., Conventional wisdom on measurement: a structural equation perspective, Psychological Bulletin, 110, 2, pp. 305-314, (1991); Brakus J.J., Schmitt B.H., Zarantonello L., Brand experience: what is it? How is it measured? Does it affect loyalty?, Journal of Marketing, 73, 3, pp. 52-68, (2009); Brotspies H., Weinstein A., Rethinking business segmentation: a conceptual model and strategic insights, Journal of Strategic Marketing, 27, 2, pp. 164-176, (2019); Byrne B.M., Structural Equation Modeling with AMOS: basic Concepts, Applications, and Programming (Multivariate Applications Series, 396, (2010); Byrne B.M., Stewart S.M., Kennard B.D., Lee P.W., The beck depression Inventory-II: testing for measurement equivalence and factor mean differenc"}},"R. G; Department of Management, Amrita Vishwa Vidyapeetham, Kochi Campus, India; email: drrejikumarg@gmail.com",null,"Emerald Publishing",{"$nulls":5},8858624.0,null,null,null,"English","J. Bus. Ind. Mark.","Article","Final",null,"Scopus","2-s2.0-85132800438"]
["De A.; Singh S.P.","De, Arkajyoti (57204477924); Singh, Surya Prakash (57199578228)","57204477924; 57199578228","A resilient pricing and service quality level decision for fresh agri-product supply chain in post-COVID-19 era",2023.0,"International Journal of Logistics Management",34.0,4.0,null,1101.0,1140.0,39.0,17.0,"10.1108/IJLM-02-2021-0117","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85114484002&doi=10.1108%2fIJLM-02-2021-0117&partnerID=40&md5=c9006135792baa62d472305dda53cb95","Department of Management Studies, Indian Institute of Technology Delhi, New Delhi, India","De A., Department of Management Studies, Indian Institute of Technology Delhi, New Delhi, India; Singh S.P., Department of Management Studies, Indian Institute of Technology Delhi, New Delhi, India","Purpose: This paper investigates how the channel leadership strategies develop a post-coronavirus disease (COVID-19) resilient agri-supply chain, which reduces supplier and retailer's price loss and enhances the logistics service quality level considering logistics outsourcing of agri-product especially for the rapidly changing market condition. Design/methodology/approach: Based on the classical leadership theory, two channel leadership strategies, i.e. LPL and SL, are considered. The proposed framework first derives the equilibrium price and service quality level decision among the supplier, the logistics provider and the retailer. Then it compares both leadership strategies in terms of the equilibrium prices and service quality theoretically. This article also presents a case study of Arabian dates pricing and supply chain to test the theoretically derived propositions. Findings: Selection of suitable leadership strategy is a critical factor for profit maximization of the supply chain drivers and proper optimization of equilibrium price and service quality. Here, the product's quality and the market's socio-economic condition play an important role in selecting a suitable leadership strategy. A random transformation of the physical market to an e-commerce portal creates a wide variation of the market's socio-economic parameters, affecting the equilibrium pricing and the logistics provider's service quality. Research limitations/implications: This study proposes a post-COVID-19 resilient agri-supply chain framework considering price and quality-dependent stochastic market demand, incorporating a wide range of socio-economic factors in the model to counteract the effect of rapid behavior change of agri-market due to COVID-19 norms. This research examines the effect of different channel leadership strategies to facilitate suitable decisions on prices and service quality and retrieve the profit of the supplier, retailer and logistics provider. The future models can incorporate competitiveness in logistics outsourcing, fourth-party logistics (4PL) and contract farming in the agri-supply chain. Each of the extensions can open avenues in different directions. Practical implications: As the post-COVID-19 market and the customer behavior is randomly changing, and the traditional market is rapidly converting into supermarkets and e-commerce portals, this paper examines the model with a wide variety of e-commerce portals with multi-variation of product. It is conclusive that the product's quality and the market's socio-economic behavior significantly impact the equilibrium decision. The drivers of the supply chain must take them into account before choosing a particular channel leadership strategy. Originality/value: This study considers a multi-product and multi-market (e-commerce) model by integrating a wide variety of products and the market's socio-economic parameters. The model is tested in a price and quality-dependent stochastic market condition, contributing to the literature by reconciling two different channel leadership strategies into the global logistics of fresh agri-product. © 2021, Emerald Publishing Limited.","Agri-pricing and supply chain; Arabian dates pricing and supply chain; Channel leadership; Logistics outsourcing; Post-COVID-19 resilient supply chain; Price equilibrium; Stackelberg game modeling",{"$nulls":7},"Aldaco R., Hoehn D., Laso J., Margallo M., Ruiz-Salmon J., Cristobal J., Kahhat R., Villanueva-Rey P., Bala A., Batlle-Bayer L., Fullana-i-Palmer P., Irabien A., Vazquez-Rowe I., Food waste management during the COVID-19 outbreak: a holistic climate, economic and nutritional approach, Science of the Total Environment, 742, (2020); Aldrighetti R., Battini D., Ivanov D., Zennaro I., Costs of resilience and disruptions in supply chain network design models: a review and future research directions, International Journal of Production Economics, 235, (2021); Alvesson M., Sandberg J., Generating research questions through problematization, Academy of Management Review, 36, 2, pp. 247-271, (2011); Azadegan A., Dooley K., A typology of supply network resilience strategies: complex collaborations in a complex world, Journal of Supply Chain Management, 57, 1, pp. 17-26, (2021); Bakalis S., Valdramidis V., Argyropoulos D., Ahrne L., Chen J., Cullen P.J., Cummins E., Datta A.K., Emmanouilidis C., Foster T., Fryer P.J., Gouseti O., Hospido A., Knoerzer K., LeBail A., Marangoni A.G., Rao P., Schluter O.K., Taoukis P., Xanthakis E., Van Impe J., Perspective from CO+RE: how COVID-19 changed our food systems and food security paradigms, Food Science, 3, pp. 166-172, (2020); Bialas W.F., Cooperative n-person Stackelberg games, Proceedings of the 28th IEEE Conference on Decision and Control, pp. 2439-2444, (1989); Bialas W.F., Chew M.H., A Linear Model of Coalition Formation in Hierarchical Organizations, (1981); Blackmon L., Chan R., Carbral O., Chintapally G., Dhara S., Felix P., Jagdish A., Konakalla S., Labana J., McIlvain J., Stone J., Tang S., Torres C., Wu W.J., Rapid development of a decision support system to alleviate food insecurity at the Los Angeles regional food bank amid the COVID‐19 pandemic, Production and Operations Management, (2021); Butt A.S., Strategies to mitigate the impact of COVID-19 on supply chain disruptions: a multiple case analysis of buyers and distributors, The International Journal of Logistics Management, (2021); Cai X., Chen J., Xiao Y., Xu X., Optimization and coordination of fresh product supply chains with freshness‐keeping effort, Production and Operations Management, 19, 3, pp. 261-278, (2010); Chen L.G., Ding D., Ou J., Power structure and profitability in assembly supply chains, Production and Operations Management, 23, 9, pp. 1599-1616, (2014); Choi S.C., Price competition in a channel structure with a common retailer, Marketing Science, 10, 4, pp. 271-296, (1991); Choi T.M., Li Y., Xu L., Channel leadership, performance and coordination in closed loop supply chains, International Journal of Production Economics, 146, 1, pp. 371-380, (2013); Chu Z., Wang L., Lai F., Customer pressure and green innovations at third party logistics providers in China: the moderation effect of organizational culture, The International Journal of Logistics Management, 30, 1, pp. 57-75, (2019); Coluccia B., Agnusdei G.P., Miglietta P.P., De Leo F., Effects of COVID-19 on the Italian agri-food supply and value chains, Food Control, 123, (2021); Daghar A., Alinaghian L., Turner N., The role of collaborative interorganizational relationships in supply chain risks: a systematic review using a social capital perspective, Supply Chain Management: An International Journal, 26, 2, pp. 279-296, (2021); Dai J., Che W., Lim J.J., Shou Y., Service innovation of cold chain logistics service providers: a multiple-case study in China, Industrial Marketing Management, 89, pp. 143-156, (2020); El Baz J., Ruel S., Can supply chain risk management practices mitigate the disruption impacts on supply chains' resilience and robustness? 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Singh; Department of Management Studies, Indian Institute of Technology Delhi, New Delhi, India; email: surya.singh@gmail.com",null,"Emerald Publishing",{"$nulls":5},9574093.0,null,null,null,"English","Int. J. Logist. Manage.","Article","Final",null,"Scopus","2-s2.0-85114484002"]
["Li Y.; Wu Q.; Zhang Y.; Huang G.; Zhang H.","Li, Yuanjun (57671657700); Wu, Qitao (7404602641); Zhang, Yuling (55988989800); Huang, Guangqing (57207029126); Zhang, Hongou (15077596100)","57671657700; 7404602641; 55988989800; 57207029126; 15077596100","Spatial Structure of China’s E-commerce Express Logistics Network Based on Space of Flows",2023.0,"Chinese Geographical Science",33.0,1.0,null,36.0,50.0,14.0,1.0,"10.1007/s11769-022-1322-0","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85141447107&doi=10.1007%2fs11769-022-1322-0&partnerID=40&md5=843fed0fccc2d860379b24238900b1e2","Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou, 510070, China","Li Y., Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou, 510070, China; Wu Q., Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou, 510070, China; Zhang Y., Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou, 510070, China; Huang G., Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou, 510070, China; Zhang H., Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou, 510070, China","The intermediate link compression characteristics of e-commerce express logistics networks influence the traditional mode of circulation of goods and economic organization, and alter the city spatial pattern. Based on the theory of space of flows, this study adopts China Smart Logistics Network relational data to build China’s e-commerce express logistics network and explore its spatial structure characteristics through social network analysis (SNA), the PageRank technique, and geospatial methods. The results are as follows: the network density is 0.9270, which is close to 1; hence, indicating that e-commerce express logistics lines between Chinese cities are nearly complete and they form a typical network structure, thereby eliminating fragmented spaces. Moreover, the average minimum number of edges is 1.1375, which indicates that the network has a small world effect and thus has a high flow efficiency of logistics elements. A significant hierarchical diffusion effect was observed in dominant flows with the highest edge weights. A diamond-structured network was formed with Shanghai, Guangzhou, Chongqing, and Beijing as the four core nodes. Other node cities with a large logistics scale and importance in the network are mainly located in the 19 city agglomerations of China, revealing the fact that the development of city agglomerations is essential for promoting the separation of experience space and changing the urban spatial pattern. This study enriches the theory of urban networks, reveals the flow laws of modern logistics elements, and encourages coordinated development of urban logistics. © 2023, Science Press, Northeast Institute of Geography and Agroecology, CAS and Springer-Verlag GmbH Germany, part of Springer Nature.","e-commerce express logistics; logistics big data; space of flows; urban logistics network","Beijing [China]; China; Chongqing; Guangdong; Guangzhou; Shanghai; economic development; economic impact; electronic commerce; Internet; logistics; urban economy",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (2021GDASYL-20210103004, 2023GDASZH-2023010101, 41801144, 42071165)","Under the auspices of National Natural Science Foundation of China (No. 42071165, 41801144), GDAS’ Project of Science and Technology Development (No. 2023GDASZH-2023010101, 2021GDASYL-20210103004)","Akhavan M., Ghiara H., Mariotti I., Et al., Logistics global network connectivity and its determinants. 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An analysis based on bibliometric indicators, Urban Studies, 47, 9, pp. 1879-1897, (2010); O'Kelly M.E., Bryan D.L., Hub location with flow economies of scale, Transportation Research Part B:Methodological, 32, 8, pp. 605-616, (1998); O'Kelly M.E., A geographer’s analysis of hub-and-spoke networks, Journal of Transport Geography, 6, 3, pp. 171-186, (1998); Reilly W.J., Methods for the Study of Retail Relationships, (1929); Rogerson C.M., Visser G., International tourist flows and urban tourism in South Africa, Urban Forum, 17, 2, pp. 199-213, (2006); Rotem-Mindali O., Weltevreden J.W.J., Transport effects of e-commerce: what can be learned after years of research, Transportation, 40, 5, pp. 867-885, (2013); Russo F., Comi A., A modelling system to simulate goods movements at an urban scale, Transportation, 37, 6, pp. 987-1009, (2010); Seghezzi A., Mangiaracina R., Investigating multi-parcel crowdsourcing logistics for B2C e-commerce last-mile deliveries, International Journal of Logistics Research and Applications, 25, 3, pp. 260-277, (2022); Shen L., Xi G., Qin X., Et al., The research on the characteristics of the regional space of flows based on measurement of the express logistic of flows: a case study of Jiangsu province, Human Geography, 33, 1, pp. 102-108, (2018); Sobolevsky S., Szell M., Campari R., Et al., Delineating geographical regions with networks of human interactions in an extensive set of countries, PLoS One, 8, 12, (2013); Tang C., Ma X., Spatial pattern and structure of networked logistics connection of cities in China based on express logistics branch data, Progress in Geography, 39, 11, pp. 1809-1821, (2020); Wang L., Liu H., Liu Q., China’s city network based on Tencent’s migration big data, Acta Geographica Sinica, 76, 4, pp. 853-869, (2021); Wang N.N., Mi Y.Y., Gao H., Et al., Logistics network model based on matter element node, Procedia Computer Science, 91, pp. 351-356, (2016); Wu J.P., Research on air transportation network with information technology for express logistics enterprise, Advanced Materials Research, 1014, pp. 467-470, (2014); Xiu C., Sun P., Wang Q., Residence-employment structure analysis on spaces of geography and flows in Shenyang City, Acta Geographica Sinica, 68, 8, pp. 1110-1118, (2013); Yan J., Research on Manuel Castells’s thought of ‘Space of Flows’, (2019); Yang X., Gu C., Wang Q., Urban tourism flow network structure construction in Nanjing, Acta Geographica Sinica, 62, 6, pp. 609-620, (2007); Ye L., Duan X., City network structure of the Yangtze River Delta region based on logistics enterprise network, Progress in Geography, 35, 5, pp. 622-631, (2016); Zeng B.D., Pattern of Chinese tourist flows in Japan: a social network analysis perspective, Tourism Geographies, 20, 5, pp. 810-832, (2018); Zhang H., Michael S., Fu X., Et al., Dynamical behaviour of an epidemic on complex networks with population mobility, Chinese Physics B, 18, 9, pp. 3639-3646, (2009); Zhou J., Liu C., Xu W., Et al., Logistics network structure of express delivery companies and their self-organization effect under the background of e-commerce: taking ZTO express as an example, Economic Geography, 41, 2, pp. 103-112, (2021); Zong H., Zhou S., Yan X., Research on the spatial network of local comprehensive third-party logistics company under globalization: taking Tengbang logistics company as a case, Geographical Research, 34, 5, pp. 944-952, (2015)","Q. Wu; Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou, 510070, China; email: wuqitao@gdas.ac.cn",null,"Science Press",{"$nulls":5},1.0020063E7,null,null,null,"English","Chin. Geogr. Sci.","Article","Final","All Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85141447107"]
["Wang X.; Wong Y.D.; Kim T.Y.; Yuen K.F.","Wang, Xueqin (57196484178); Wong, Yiik Diew (57218910096); Kim, Thai Young (57192254230); Yuen, Kum Fai (56581269200)","57196484178; 57218910096; 57192254230; 56581269200","Does consumers’ involvement in e-commerce last-mile delivery change after COVID-19? An investigation on behavioural change, maintenance and habit formation",2023.0,"Electronic Commerce Research and Applications",60.0,null,101273.0,null,null,null,1.0,"10.1016/j.elerap.2023.101273","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85162135718&doi=10.1016%2fj.elerap.2023.101273&partnerID=40&md5=4318b394ec9ae4f69ec70759ac75b43d","Department of International Logistics, Chung-Ang University, Seoul, South Korea; School of Civil and Environmental Engineering, Nanyang Technological University, Singapore","Wang X., Department of International Logistics, Chung-Ang University, Seoul, South Korea; Wong Y.D., School of Civil and Environmental Engineering, Nanyang Technological University, Singapore; Kim T.Y., Department of International Logistics, Chung-Ang University, Seoul, South Korea; Yuen K.F., School of Civil and Environmental Engineering, Nanyang Technological University, Singapore","The COVID-19 pandemic accelerates e-commerce adoption, which naturally induces an expedited acceptance of innovative last-mile deliveries. Focusing on self-collection via parcel lockers, this study investigates consumers’ behavioural change, maintenance and habit formation related to e-commerce deliveries in response to the pandemic. We use a survey instrument for data collection (n = 500) and structural equation modelling for data analysis. Anchored on the risk–attitude–norm–ability–self-regulation (RANAS) framework, this study found that risk, attitude, norm, ability and self-regulation factors related to using the contactless shopping-delivery channel lead to the formation of self-collection habits, and that the formation process is fully mediated by consumers’ maintenance motivation to use the channel. Furthermore, consumers’ online shopping habit partially mediates the relationship between the maintenance motivation and self-collection habit formation. Additionally, model comparisons are conducted,revealing the differentiated habit formation processes. The findings contribute to a theoretical understanding of the formation of delivery habit as driven by the pandemic. Practical implications are also created which guide logistics and e-commerce operators’ interactions with consumers in the post-pandemic period. © 2023 Elsevier B.V.","Contactless shopping and delivery; COVID-19 pandemic; Habit formation; RANAS; Self-collection; Smart parcel locker","Deregulation; Electronic commerce; Locks (fasteners); Maintenance; Motivation; Contact less; Contactless shopping and delivery; COVID-19 pandemic; E- commerces; Habit formation; Risk attitude; Risk–attitude–norm–ability–self-regulation; Self regulation; Self-collection; Smart parcel locker; COVID-19",{"$nulls":6},"Ajzen I., The theory of planned behaviour: Reactions and reflections, Psychol. 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Rev., 114, pp. 843-863, (2007); Yaprak U., Kilic F., Okumus A., Is the covid-19 pandemic strong enough to change the online order delivery methods? Changes in the relationship between attitude and behavior towards order delivery by drone, Technol. Forecast. Soc. Chang., 169, (2021); Yuen K.F., Wang X., Ng L.T.W., Wong Y.D., An investigation of customers’ intention to use self-collection services for last-mile delivery, Transp. Policy, 66, pp. 1-8, (2018); Yuen K.F., Wang X., Ma F., Wong Y.D., The determinants of customers’ intention to use smart lockers for last-mile deliveries, J. Retail. Consum. Serv., 49, pp. 316-326, (2019)","K.F. Yuen; School of Civil and Environmental Engineering, Nanyang Technological University, Singapore; email: kumfai.yuen@ntu.edu.sg",null,"Elsevier B.V.",{"$nulls":5},1.5674223E7,null,null,null,"English","Elect. Commer. Res. Appl.","Article","Final",null,"Scopus","2-s2.0-85162135718"]
["Edirisinghe G.S.; Almutairi T.","Edirisinghe, Gihan S. (57664758800); Almutairi, Thamer (58286866000)","57664758800; 58286866000","Multi-Echelon Inventory Optimization for Practitioners: a Predictive Global Sensitivity Analysis Approach",2023.0,"Operations Research Forum",4.0,2.0,45.0,null,null,null,0.0,"10.1007/s43069-023-00222-7","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85160028326&doi=10.1007%2fs43069-023-00222-7&partnerID=40&md5=f848a04d7b87a42c6ad802522e3ca91d","Department of Management, Gordon Ford College of Business, Western Kentucky University, 1906 College Heights Blvd #11058, Bowling Green, 42101-1058, KY, United States; Department of Finance and Management Science, Carson College of Business, Washington State University, PO Box 644746, Pullman, 99164-4746, WA, United States","Edirisinghe G.S., Department of Management, Gordon Ford College of Business, Western Kentucky University, 1906 College Heights Blvd #11058, Bowling Green, 42101-1058, KY, United States; Almutairi T., Department of Finance and Management Science, Carson College of Business, Washington State University, PO Box 644746, Pullman, 99164-4746, WA, United States","Intense competition in e-commerce has forced firms to provide highly precise delivery time guarantees such as ‘same-day’ and ‘2-day’ shipping. To meet these stringent standards, it is imperative that companies avoid stock-outs across multi-echelon supply chain networks. Due to their demanding computational requirements, current approaches for optimizing network-wide safety stock levels are challenging tools to use for day-to-day managerial decision-making. We propose a methodology that creates structural equations using regression techniques based on known optimal results. To achieve this, we employ predictive global sensitivity analysis (PGSA), which allows us to create structural equations based on known optimal results using regression techniques. However, these equations do not necessarily require the conventional inputs of models like the guaranteed-service model. Instead, we regress more intelligible independent variables for near-optimal solutions, which suffices in many initial decision-making situations faced by practitioners, such as evaluating different options, what-if-analysis, and scenario planning. © 2023, The Author(s), under exclusive licence to Springer Nature Switzerland AG.","Guaranteed-service model (GSM); Multi-echelon supply chains; Predictive global sensitivity analysis (PGSA); Safety stock; Supply chain management",{"$nulls":7},"Lebeau M., (2022); Eruguz A.S., Sahin E., Jemai Z., Dallery Y., A comprehensive survey of guaranteed-service models for multi-echelon inventory optimization, Int J Prod Econ, 172, pp. 110-125, (2016); Farasyn I., Et al., Inventory optimization at Procter & Gamble: achieving real benefits through user adoption of inventory tools, Interfaces (Providence), 41, 1, pp. 66-78, (2011); Sinha P., Kumar S., Prakash S., Measuring and mitigating the effects of cost disturbance propagation in multi-echelon apparel supply chains, Eur J Oper Res, 282, 1, pp. 148-160, (2020); Silver E.A., Pyke D.F., Peterson R., Inventory management and production planning and scheduling, 3, (1998); Graves S.C., Willems S.P., Optimizing strategic safety stock placement in supply chains, Manuf Serv Oper Manag, 2, 1, pp. 68-83, (2000); Billington C., Et al., Accelerating the profitability of Hewlett-Packard’s supply chains, Interfaces (Providence), 34, 1, pp. 59-72, (2004); Wieland B., Mastrantonio P., Willems S.P., Kempf K.G., Optimizing inventory levels within Intel’s channel supply demand operations, Interfaces (Providence), 42, 6, pp. 517-527, (2012); Maynard H.B., (2001); Wagner H.M., Global sensitivity analysis, Oper Res, 43, 6, pp. 948-969, (1995); Magnanti T.L., Shen Z.J.M., Shu J., Simchi-Levi D., Teo C.P., Inventory placement in acyclic supply chain networks, Oper Res Lett, 34, 2, pp. 228-238, (2006); Kimball G.E., General principles of inventory control, J Manuf Oper Manag, 1, 1, pp. 119-130, (1988); Simpson K., In-process inventories, Oper Res, 6, 6, pp. 863-874, (1958); Diks E.B., De Kok A.G., Lagodimos A.G., Multi-echelon systems: a service measure perspective, Eur J Oper Res, 95, 2, pp. 241-263, (1996); Pianosi F., Wagener T., A simple and efficient method for global sensitivity analysis based on cumulative distribution functions, Environ Model Softw, 67, pp. 1-11, (2015); Graves S.C., Willems S.P., Supply chain design: Safety stock placement and supply chain configuration, Handbooks Oper Res Manag Sci, 11, C:, pp. 95-132, (2003); Inderfurth K., Safety stock optimization in multi-stage inventory systems, Int J Prod Econ, 24, 1-2, pp. 103-113, (1991); Inderfurth K., Minner S., Safety stocks in multi-stage inventory systems under different service measures, Eur J Oper Res, 106, 1, pp. 57-73, (1998); Graves S.C., Lesnaia E., Optimizing safety stock placement in general network supply chains, In Proceedings of Singapore-Mit Alliance Annual Symposium Conference, pp. 7-13, (2004); Minner S., Strategic safety stocks in reverse logistics supply chains, Int J Prod Econ, 71, 1-3, pp. 417-428, (2001); Minner S., Strategic safety stocks in supply chains, (2000); Grahl J., Minner S., Dittmar D., Meta-heuristics for placing strategic safety stock in multi-echelon inventory with differentiated service times, Ann Oper Res, 242, 2, pp. 489-504, (2014); Li H., Jiang D., New model and heuristics for safety stock placement in general acyclic supply chain networks, Comput Oper Res, 39, 7, pp. 1333-1344, (2012); Shu J., Karimi I.A., Efficient heuristics for inventory placement in acyclic networks, Comput Oper Res, 36, 11, pp. 2899-2904, (2009); Ghadimi F., Aouam T., Vanhoucke M., Optimizing production capacity and safety stocks in general acyclic supply chains, Comput Oper Res, 120, (2020); Aouam T., Ghadimi F., Vanhoucke M., Finite inventory budgets in production capacity and safety stock placement under the guaranteed service approach, Comput Oper Res, 131, (2021); Neale J.J., Willems S.P., Managing inventory in supply chains with nonstationary demand, Interfaces (Providence), 39, 5, (2009); Saltelli A., Ratto M., Tarantola S., Campolongo F., Sensitivity analysis practice: a guide to scientific models, Reliab Eng Syst Saf, 91, 10-11, pp. 1109-1125, (2006); Borgonovo E., Peccati L., Global sensitivity analysis in inventory management, Int J Prod Econ, 108, 1-2, pp. 302-313, (2007); Hall N.G., Posner M.E., Sensitivity analysis for stochastic scheduling problems, J Sched, 7, pp. 49-83, (2004); Kouvelis P., Munson C.L., Yang S., Robust structural equations for designing and monitoring strategic international facility networks, Prod Oper Manag, 22, 3, pp. 535-554, (2013); Lee C., Munson C.L., A predictive global sensitivity analysis approach to monitoring and modifying operational hedging positions, Int J Integr Supply Manag, 9, 3, pp. 178-203, (2015)","G.S. Edirisinghe; Department of Management, Gordon Ford College of Business, Western Kentucky University, Bowling Green, 1906 College Heights Blvd #11058, 42101-1058, United States; email: gihan.edirisinghe@wku.edu",null,"Springer International Publishing",{"$nulls":5},2.6622556E7,null,null,null,"English","SN Oper. Res. Forum","Article","Final",null,"Scopus","2-s2.0-85160028326"]
["Naruetharadhol P.; Wongsaichia S.; Pienwisetkaew T.; Schrank J.; Chaiwongjarat K.; Thippawong P.; Khotsombat T.; Ketkaew C.","Naruetharadhol, Phaninee (57191518785); Wongsaichia, Sasichakorn (57222050743); Pienwisetkaew, Teerapong (57930335500); Schrank, Johannes (57788864100); Chaiwongjarat, Kullanan (58172156900); Thippawong, Peeranut (58170972400); Khotsombat, Thanaphat (58172157000); Ketkaew, Chavis (57988391900)","57191518785; 57222050743; 57930335500; 57788864100; 58172156900; 58170972400; 58172157000; 57988391900","Consumer Intention to Utilize an E-Commerce Platform for Imperfect Vegetables Based on Health-Consciousness",2023.0,"Foods",12.0,6.0,1166.0,null,null,null,1.0,"10.3390/foods12061166","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85151753962&doi=10.3390%2ffoods12061166&partnerID=40&md5=9bef5e19737a69a23c429fd46950d97a","International College, Khon Kaen University, Khon Kaen, 40002, Thailand; Center for Sustainable Innovation and Society, Khon Kaen University, Khon Kaen, 40002, Thailand","Naruetharadhol P., International College, Khon Kaen University, Khon Kaen, 40002, Thailand, Center for Sustainable Innovation and Society, Khon Kaen University, Khon Kaen, 40002, Thailand; Wongsaichia S., International College, Khon Kaen University, Khon Kaen, 40002, Thailand, Center for Sustainable Innovation and Society, Khon Kaen University, Khon Kaen, 40002, Thailand; Pienwisetkaew T., International College, Khon Kaen University, Khon Kaen, 40002, Thailand, Center for Sustainable Innovation and Society, Khon Kaen University, Khon Kaen, 40002, Thailand; Schrank J., International College, Khon Kaen University, Khon Kaen, 40002, Thailand, Center for Sustainable Innovation and Society, Khon Kaen University, Khon Kaen, 40002, Thailand; Chaiwongjarat K., International College, Khon Kaen University, Khon Kaen, 40002, Thailand; Thippawong P., International College, Khon Kaen University, Khon Kaen, 40002, Thailand; Khotsombat T., International College, Khon Kaen University, Khon Kaen, 40002, Thailand; Ketkaew C., International College, Khon Kaen University, Khon Kaen, 40002, Thailand, Center for Sustainable Innovation and Society, Khon Kaen University, Khon Kaen, 40002, Thailand","Thailand has a problem with fruit and vegetable waste because consumers have a negative attitude towards fruit and vegetables with imperfect shapes; however, those imperfections have no impact on nutritional quality. Young adults are most aware of the problem of food waste. Here, we study factors influencing consumer’ intention to adopt an e-commerce platform that commercializes imperfect vegetables (ugly veggies). In all, 390 respondents from four provinces of Thailand were enrolled in the study. Cluster analysis, structural equation modeling, and multigroup moderation analysis approaches were used. The main conceptual framework was adapted from the unified theory of acceptance and the use of technology. Respondents were classified into low, moderate, and high health-conscious segments. We found that performance expectancy positively influences the behavioral intention of highly health-conscious consumers. For consumers in the moderate health-consciousness segment, effort expectancy and social influence positively affect behavioral intention. None of the hypothesized factors influence the low health-consciousness segment’s behavioral intention. This paper expands the understanding of consumer’ attitudes toward accepting an imperfect vegetable e-commerce platform. Additionally, the research can guide platform development and marketing efforts. © 2023 by the authors.","food delivery platform; health-consciousness; imperfect fruit and vegetables; organic food; young adult",{"$nulls":5},"National Research Council of Thailand, NRCT, (N25A65-152)","Funding text 1: This research is funded by the National Research Council of Thailand (NRCT). We are grateful for the research facilities provided by the International College, Khon Kaen University, Thailand. ; Funding text 2: This research is funded by the National Research Council of Thailand (NRCT), contract number N25A65-152.","FAO Publications Catalogue 2021, (2021); Cattaneo A., Sanchez M.V., Torero M., Vos R., Reducing food loss and waste: Five challenges for policy and research, Food Policy, 98, (2021); Porter S.D., Reay D.S., Bomberg E., Higgins P., Avoidable food losses and associated production-phase greenhouse gas emissions arising from application of cosmetic standards to fresh fruit and vegetables in Europe and the UK, J. Clean. 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["Du X.; Wang X.; Hatzenbuehler P.","Du, Xiaoxue (56895454700); Wang, Xuejian (57755769800); Hatzenbuehler, Patrick (55241830700)","56895454700; 57755769800; 55241830700","Digital technology in agriculture: a review of issues, applications and methodologies",2023.0,"China Agricultural Economic Review",15.0,1.0,null,95.0,108.0,13.0,7.0,"10.1108/CAER-01-2022-0009","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85132370978&doi=10.1108%2fCAER-01-2022-0009&partnerID=40&md5=15e35dd7f9d8b355ee09070f66f47f8b","Department of Agricultural Economics and Rural Sociology, University of Idaho, Moscow, ID, United States","Du X., Department of Agricultural Economics and Rural Sociology, University of Idaho, Moscow, ID, United States; Wang X., Department of Agricultural Economics and Rural Sociology, University of Idaho, Moscow, ID, United States; Hatzenbuehler P., Department of Agricultural Economics and Rural Sociology, University of Idaho, Moscow, ID, United States","Purpose: The purpose of this paper is to show the impact of digital agriculture on food supply chain, research trend, emphasis and implications for future research. Design/methodology/approach: The paper analyzes how the digital technology reshapes the production, assembly, transaction, retail and logistics. Impact from each main technological progress is discussed. Findings: First, digital agriculture develops quickly and changes all parts of the food supply chain. Second, while many technological progresses show their impacts in agriculture and food sector, e-commerce and progress of artificial intelligence show its comprehensive impact on the argi-food sector. Originality/value: The paper shows the technological trend and progress in food and agriculture sector. Researchers focusing on agricultural economics and agribusiness should pay attention to recent developments in the real world, know the recent developments from other disciplines, get more data for empirical research and show the impact of digital agriculture on consumer's preference and social welfare. © 2022, Emerald Publishing Limited.","Automation; Farm; Food delivery; Internet of Things; Marketing; O2O; Remote sensing; Robotics",{"$nulls":5},"New Hampshire Agricultural Experiment Station, NHAES","The authors thank the editor and reviewer for excellent comments and guidance. 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Discussion on new retail marketing mode based on 4Cs theory, Proceedings of the 2018 International Conference on E-Business and Applications - ICEBA 2018, (2018); Zhao J., Wang S., Huang W.V., A study of B2B e-market in China: E-commerce process perspective, Information and Management, 45, 4, pp. 242-248, (2008); Zheng Y.-Y., Kong J.-L., Jin X.-B., Wang X.-Y., Su T.-L., Zuo M., CropDeep: the crop vision dataset for deep-learning-based classification and detection in precision agriculture, Sensors 2019, 19, 5, (2019); Zhu Q., Jiang C., Development mode of the E-commerce of eco-agriculture products in China, Ecological Economy, 3, (2017); Zou Z., Chen Q., Uysal I., Zheng L., Radio frequency identification enabled wireless sensing for intelligent food logistics, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 372, 2017, (2014)","X. Du; Department of Agricultural Economics and Rural Sociology, University of Idaho, Moscow, United States; email: xiaoxuedu@uidaho.edu",null,"Emerald Publishing",{"$nulls":5},"1756137X",null,null,null,"English","China Agric. Econ. Rev.","Article","Final",null,"Scopus","2-s2.0-85132370978"]
["Ouyang Z.; Leung E.K.H.; Huang G.Q.","Ouyang, Zhiyuan (57329730900); Leung, Eric K.H. (57328966600); Huang, George Q. (7403425048)","57329730900; 57328966600; 7403425048","Community logistics and dynamic community partitioning: A new approach for solving e-commerce last mile delivery",2023.0,"European Journal of Operational Research",307.0,1.0,null,140.0,156.0,16.0,6.0,"10.1016/j.ejor.2022.08.029","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85138831386&doi=10.1016%2fj.ejor.2022.08.029&partnerID=40&md5=142753d06f3ab25cd6d2266797f21c5f","Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Pokfulam, Hong Kong; Management School, University of Liverpool, Liverpool, United Kingdom","Ouyang Z., Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Pokfulam, Hong Kong; Leung E.K.H., Management School, University of Liverpool, Liverpool, United Kingdom; Huang G.Q., Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Pokfulam, Hong Kong","Last mile delivery shows an increasingly tough challenge for logistics service providers due to the rapidly expanding e-commerce sales around the globe. To ease the implementation of last mile delivery, an effective delivery strategy is to predetermine the service regions of vehicles before optimizing their delivery routes. On this ground, this paper proposes a new delivery strategy named Community Logistics (CL) to generate vehicle service region and departure time dynamically. Through adopting this new delivery strategy, we transform the original last mile delivery to a new type of research problem, namely dynamic community partitioning problem (DCPP), with an aim to strike a balance between vehicle service region range, order delay time and vehicle capacity usage based on the real-time order arrivals and vehicle availability status. We present a Markov decision process (MDP) model for the DCPP and develop a heuristic solution approach to solve this MDP model. Numerical results demonstrate significant benefits of the proposed solution framework and delivery strategy. © 2022 Elsevier B.V.","Business to customer e-commerce; Community logistics; Dynamic community partitioning problem; Last mile delivery; Logistics","Electronic commerce; Markov processes; Business to customer e commerces; Community logistic; Dynamic communities; Dynamic community partitioning problem; E- commerces; Last mile; Last mile delivery; Markov decision process models; Partitioning problem; Vehicle service; Vehicles",{"$nulls":4},"Guangdong Special Support Talent Program – Innovation and Entrepreneurship Leading Team, (201909010006, 2019BT02S593); HKSAR RGC, (17203518)","The authors would like to acknowledge partial financial supports from funding sources, including the 2019 Guangdong Special Support Talent Program – Innovation and Entrepreneurship Leading Team (China) ( 2019BT02S593 ), 2018 Guangzhou Leading Innovation Team Program ( 201909010006 ), HKSAR RGC GRF Project ( 17203518 ). This work is among research works that motivate the theme-based research project (T32-707-22-N). 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Huang; Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Pokfulam, Hong Kong; email: gqhuang@hku.hk",null,"Elsevier B.V.",{"$nulls":5},3772217.0,null,"EJORD",null,"English","Eur J Oper Res","Article","Final",null,"Scopus","2-s2.0-85138831386"]
["Ma W.; Hoen F.S.; Tørset T.","Ma, Winnie (58038293000); Hoen, Fredrik S. (58037799900); Tørset, Trude (56027661300)","58038293000; 58037799900; 56027661300","No way back? A survey on changes in travel demand post-pandemic in Norway",2023.0,"Case Studies on Transport Policy",11.0,null,100942.0,null,null,null,2.0,"10.1016/j.cstp.2022.100942","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85145293993&doi=10.1016%2fj.cstp.2022.100942&partnerID=40&md5=ea3d22ee9098fbfd5ff497ee773b7046","Norwegian University of Science and Technology (NTNU), Høgskoleringen 7a, Trondheim, 7034, Norway","Ma W., Norwegian University of Science and Technology (NTNU), Høgskoleringen 7a, Trondheim, 7034, Norway; Hoen F.S., Norwegian University of Science and Technology (NTNU), Høgskoleringen 7a, Trondheim, 7034, Norway; Tørset T., Norwegian University of Science and Technology (NTNU), Høgskoleringen 7a, Trondheim, 7034, Norway","Research shows a significant reduction in travel demand during the pandemic. Vaccines are currently distributed, allowing us to go back to pre-COVID-19 life, if that is the case. This study provides insight into changes in activities and travel demand during the pandemic and expected changes after the pandemic. Our paper presents the findings from a Likert scale survey (n = 360) conducted in Norway June–July 2021. We investigate how relocated activities impacted travel behaviour during the pandemic, and prospects of lasting impacts of the pandemic. The results show that the prevalence of home office and digital meetings, the new normal for many people during the pandemic, will continue to some degree after the pandemic. There is an increased willingness to commute by active modes, while no pronounced increase in car commutes is reported. However, car use is expected to increase for leisure trips; a significant correlation with the demand of more domestic outdoor travel. One out of five states that they will use public transport less often in the future. We may expect more online shopping, although home-deliveries for groceries is not as popular as for non-edible goods—not during the pandemic nor after. Earlier disruptive events have shown that people tend to adjust back to normal after a while, even if they have stated otherwise. There are certain mid-pandemic habits that go along with political goals and/or employers’ interests, implying these might be prolonged into the future. © 2022 World Conference on Transport Research Society","Activity-transport pattern; COVID-19; Likert scale; Post-pandemic","Norway; car use; COVID-19; public transport; travel behavior; travel demand",{"$nulls":6},"Abdullah M., Dias C., Muley D., Shahin M., Exploring the impacts of COVID-19 on travel behavior and mode preferences, Transp. Res. Interdiscip. Perspect., (2020); Abu-Rayash A., Dincer I., Analysis of mobility trends during the COVID-19 coronavirus pandemic: exploring the impacts on global aviation and travel in selected cities, Energy Res. Social Sci., 68, (2020); Barbieri D.M., Et al., Impact of COVID-19 pandemic on mobility in ten countries and associated perceived risk for all transport modes, PLoS One, (2021); Beck M.J., Hensher D.A., Insights into the impact of COVID-19 on household travel and activities in Australia – the early days of easing restrictions, Transp. Policy, 99, pp. 95-119, (2020); Bucsky P., Modal share changes due to COVID-19: the case of Budapest, Transp. Res. Interdiscip. Perspect., 8, (2020); Forsyth P., Guiomard C., Niemeierc H.-M., Covid-19, the collapse in passenger demand and airport charges, J. Air Transp. Manage., 89, (2020); Haas M.D., Faber R., Hamersma M., How COVID-19 and the Dutch ‘intelligent lockdown’ change activities, work and travel behaviour: evidence from longitudinal data in the Netherlands, Transp. Res. Interdiscip. Perspect., 6, (2020); Hjorthol R., Engebretsen O., Uteng T.P., 2013/14, National Travel Survey – Key Results, (2014); Jenelius E., Cebecauer M., Impacts of COVID-19 on public transport ridership in Sweden: analysis of ticket validations, sales and passenger counts, Transp. Res. Interdiscip. Perspect., 8, (2020); Kontou E., Murray-Tuite P., Wernstedt K., Duration of commute travel changes in the aftermath of Hurricane Sandy using accelerated failure time modeling, Transp. Res. A: Policy Pract., pp. 170-181, (2017); Kwasnicka D., Dombrowski S.U., White M., Sniehotta F., pp. 277-296, (2016); Lattaruloa P., Masucci V., Pazienza M.G., Resistance to change: car use and routines, Transp. Policy, 74, pp. 63-72, (2019); (2020); Parkes S., Jopson A., Marsden G., Understanding travel behaviour change during mega-events: lessons from the London 2012 games, Transp. Res. A: Policy Pract., 92, pp. 104-119, (2016); Prager F.G.R.B.A., Lee B., Winterfeldt D.V., Exploring reductions in London underground passenger journeys following the July 2005 bombings, Risk Anal., 31, 5, pp. 773-786, (2011); Rothe J., (2021); Shamshiripour A., Rahimi E., Shabanpour R., Mohammadian A., How is COVID-19 reshaping activity-travel behavior? Evidence from a comprehensive survey in Chicago, Transp. Res. Interdiscip. Perspect., 7, 3, (2020); Sheth J., Impact of COVID-19 on consumer behavior: will the old habits return or die?, J. Bus. Res., 117, pp. 280-283, (2020); Siemens R.A., Henning M., Poeske A., Trier M., Covid-19 and its effect on trip mode and destination decisions of transit riders: experience from Ohio, Transp. Res. Interdiscip. Perspect., 11, 2, (2021); Sivertsen B., (2021); Timmermans H., Ettema D., Activity-based Approaches to Travel Analysis, (1997); Tuv N., Fredriksen K., Rydjord M., (2021); Ugur N.G., Akbiyik A., Impacts of COVID-19 on global tourism industry: a cross-regional comparison, Tour. Manage. Perspect., 36, (2020)","W. Ma; Institute for Civil and Environmental Engineering at NTNU, Trondheim, 7491, Norway; email: winnie.g.h.ma@ntnu.no",null,"Elsevier Ltd",{"$nulls":5},"2213624X",null,null,null,"English","Case Stud. Transp. Policy","Article","Final","All Open Access; Green Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85145293993"]
["Wang L.; Xu M.; Qin H.","Wang, Li (57871697000); Xu, Min (57189711796); Qin, Hu (25925253100)","57871697000; 57189711796; 25925253100","Joint optimization of parcel allocation and crowd routing for crowdsourced last-mile delivery",2023.0,"Transportation Research Part B: Methodological",171.0,null,null,111.0,135.0,24.0,5.0,"10.1016/j.trb.2023.03.007","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85151048408&doi=10.1016%2fj.trb.2023.03.007&partnerID=40&md5=ec3e2b4c546f0972e9329e10a61b4c52","School of Management, Huazhong University of Science and Technology, Wuhan, China; Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong","Wang L., School of Management, Huazhong University of Science and Technology, Wuhan, China, Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong; Xu M., Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong; Qin H., School of Management, Huazhong University of Science and Technology, Wuhan, China","Urban last-mile delivery providers are facing more and more challenges with the explosive development of e-commerce. The advancement of smart mobile and communication technology in recent years has stimulated the development of a new business model of city logistics, referred to as crowdsourced delivery or crowd-shipping. In this paper, we investigate a form of crowdsourced last-mile delivery that utilizes the journeys of commuters/travelers (crowd-couriers) to deliver parcels from intermediate stations to customers. We consider a logistics service provider that jointly optimizes parcel allocation to intermediate stations and the delivery routing of the crowd-couriers. The joint optimization model gives rise to a new variant of the last-mile delivery problem. We propose a data-driven column generation algorithm to solve the problem based on a set-partitioning formulation. Additionally, a rolling-horizon approach is proposed to address large-scale instances. Extensive numerical experiments are conducted to verify the efficiency of our model and solution approach, as well as the significance of the joint optimization of parcel allocation and the delivery route of the crowdsourced last-mile delivery. The results show that our data-driven column generation algorithm can obtain (near-)optimal solutions for up to 200 parcels in significantly less time than the exact algorithm. For larger instances, the combination of the data-driven column generation algorithm and the rolling-horizon approach can obtain good-quality solutions for up to 1000 parcels in 15 min. Moreover, compared with crowd-courier route optimization only, the joint optimization of parcel allocation and crowd-routing reduces the total cost by 32%. © 2023 Elsevier Ltd","Crowdsourced delivery; Data-driven column generation; Last-mile delivery; Parcel allocation and crowd routing","Crowdsourcing; Mobile commerce; Column generation; Crowdsourced delivery; Data driven; Data-driven column generation; Generation algorithm; Joint optimization; Last mile; Last-mile delivery; Parcel allocation and crowd routing; Routings; algorithm; business development; crowdsourcing; electronic commerce; logistics; optimization; resource allocation; service provision; telecommunication; urban development; Linear programming",{"$nulls":4},"UAKQ, (71821001, 71971090, 7210010522); National Natural Science Foundation of China, NSFC, (71901189); Research Grants Council, University Grants Committee, 研究資助局, (PolyU 15221821); Hong Kong Polytechnic University, PolyU","The authors gratefully thank Dr. Kianoush Mousavi, Prof. Merve Bodur, and Prof. Matthew J. Roorda for providing us the problem instances generated based on the data of transportation tomorrow survey (TTS) from the data management group (DMG) in the City of Toronto. The work described in this paper was supported by National Natural Science Foundation of China (No. 71901189 ) and the Research Grants Council of the Hong Kong Special Administrative Region, China (Project No. PolyU 15221821), and the Research Committee of The Hong Kong Polytechnic University (UAKQ). This research was also supported by National Natural Science Foundation of China (Grant nos. 71971090 , 71821001 , 7210010522 ). ","Ahamed T., Zou B., Farazi N.P., Tulabandhula T., Deep reinforcement learning for crowdsourced urban delivery, Transp. Res. 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Manag., 24, 2, pp. 791-809, (2022); Gdowska K., Viana A., Pedroso J.P., Stochastic last-mile delivery with crowdshipping, Transp. Res. Procedia, 30, pp. 90-100, (2018); Insider K., Worldwide ecommerce continues double-digit growth following pandemic push to online, (2021); Janinhoff L., Klein R., Scholz D., Multitrip vehicle routing with delivery options: A data-driven application to the parcel industry, (2022); Kafle N., Zou B., Lin J., Design and modeling of a crowdsource-enabled system for urban parcel relay and delivery, Transp. Res. B, 99, pp. 62-82, (2017); Kwon O., Golden B., Wasil E., Estimating the length of the optimal TSP tour: An empirical study using regression and neural networks, Comput. Oper. Res., 22, 10, pp. 1039-1046, (1995); Le T.V., Stathopoulos A., Van Woensel T., Ukkusuri S.V., Supply, demand, operations, and management of crowd-shipping services: A review and empirical evidence, Transp. Res. 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Res., 179, 2, pp. 372-389, (2007); Shen Y., Sun Y., Li X., Eberhard A., Ernst A., Enhancing column generation by a machine-learning-based pricing heuristic for graph coloring, Proceedings of the AAAI Conference on Artificial Intelligence, vol. 36(9), pp. 9926-9934, (2022); Tahir A., Quesnel F., Desaulniers G., El Hallaoui I., Yaakoubi Y., An improved integral column generation algorithm using machine learning for aircrew pairing, Transp. Sci., 55, 6, pp. 1411-1429, (2021); Vincent F.Y., Jodiawan P., Redi A.P., Crowd-shipping problem with time windows, transshipment nodes, and delivery options, Transp. Res. E, 157, (2022); Voigt S., Kuhn H., Crowdsourced logistics: The pickup and delivery problem with transshipments and occasional drivers, Networks, (2021); Wang Y., Zhang D., Liu Q., Shen F., Lee L.H., Towards enhancing the last-mile delivery: An effective crowd-tasking model with scalable solutions, Transp. Res. E, 93, pp. 279-293, (2016); Wu Z., Wang L., Huang F., Et al., pp. 4195-4203, (2022); Yildiz B., Express package routing problem with occasional couriers, Transp. Res. C, 123, (2021); Yildiz B., Savelsbergh M., Service and capacity planning in crowd-sourced delivery, Transp. Res. C, 100, pp. 177-199, (2019)","M. Xu; Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong; email: min.m.xu@polyu.edu.hk",null,"Elsevier Ltd",{"$nulls":5},1912615.0,null,null,null,"English","Transp. Res. Part B Methodol.","Article","Final",null,"Scopus","2-s2.0-85151048408"]
["Yuan X.; Sheng W.; Wang M.; Zhang D.","Yuan, Xigang (56784790500); Sheng, Wenwen (58118923100); Wang, Min (57201778268); Zhang, Dalin (57202792363)","56784790500; 58118923100; 57201778268; 57202792363","Logistics Service Selection Strategy of Green Manufacturers in Green Low-Carbon Supply Chain",2023.0,"International Journal of Environmental Research and Public Health",20.0,4.0,3356.0,null,null,null,0.0,"10.3390/ijerph20043356","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85148963501&doi=10.3390%2fijerph20043356&partnerID=40&md5=e34a4e861328fdc459e4731f267b1a49","Business School, Jiangsu Normal University, Xuzhou, 221116, China; School of Business, Linyi University, Linyi, 276000, China; Department of Computer Science, Aalborg University, Aalborgost, 9220, Denmark","Yuan X., Business School, Jiangsu Normal University, Xuzhou, 221116, China; Sheng W., Business School, Jiangsu Normal University, Xuzhou, 221116, China; Wang M., School of Business, Linyi University, Linyi, 276000, China; Zhang D., Department of Computer Science, Aalborg University, Aalborgost, 9220, Denmark","In order to analyze the logistics service mode and sales mode selection strategy, a green low-carbon supply chain consisting of a single manufacturer and a single e-commerce platform is considered. First, in the green low-carbon supply chain which consists of a direct selling channel and reselling channel, the selection strategy of the manufacturer’s logistics service mode is analyzed. Second, in the green low-carbon supply chain which consists of a direct selling channel and an agency channel, the selection strategy of the manufacturer’s logistics service mode is analyzed. Last, the manufacturer’s sales mode is analyzed. We use the backward induction method to solve the theoretical model. This study contributes to the literature by considering the optimal decision of a green low-carbon supply chain. This study brings together the literature from streams on the selling channel selection strategy in green supply chains and the logistics service strategy in green supply chains. The impacts of the logistics service cost, the selling cost, and the green input cost coefficient on the optimal decision and the firms’ profit are discussed. The result shows that in the direct selling channel and reselling channel, when the basic market demand and the logistics service level of the third-party logistics service provider are low, manufacturers will choose the e-commerce platform logistics service; in the opposite case, manufacturers will choose the third-party logistics service. In the direct selling channel and agency channels, when the logistics service level of the third-party logistics service provider is greater than or equal to a certain critical value and less than or equal to the logistics service level of the e-commerce platform, manufacturers will choose the e-commerce platform logistics service; in the opposite case, manufacturers will choose the third-party logistics service. No matter whether the manufacturer chooses the logistics service provided by the third-party logistics service provider or the logistics service provided by the e-commerce platform, the manufacturer should choose the direct selling channel and the agency channel. © 2023 by the authors.","e-commerce platform; green low-carbon supply chain; logistics service mode; selling mode","Carbon; Commerce; Consumer Behavior; Decision Making; Models, Theoretical; carbon; carbon emission; electronic commerce; logistics; manufacturing; optimization; Article; comparative study; controlled study; cost benefit analysis; decision making; electronic commerce; environmental impact; environmental management; financial management; green chemistry; price; product market; profit; quantitative study; theoretical model; commercial phenomena; consumer attitude; decision making",null,"carbon, 7440-44-0; Carbon, ",null,null,"2022 General Project of Innovation and Entrepreneurship for College Students in Jiangsu Province, (202201); Natural Science Foundation of University in Jiangsu Province, (22KJB630005); Major Project of Philosophy and Social Science Research in Colleges and Universities of Jiangsu Province, (2022SJYB1167); Social Science Foundation of Jiangsu Province, (22GLC011)","This work was supported by the 2022 General Project of Innovation and Entrepreneurship for College Students in Jiangsu Province (No. 202201), the Natural Science Foundation of University in Jiangsu Province (No. 22KJB630005), the Social Science Foundation in Jiangsu Province (No. 22GLC011), and the Philosophy and Social Science Research Project of University in Jiangsu Province (No. 2022SJYB1167).","Swami S., Shah J., Channel coordination in green supply chain management, J. Oper. Res. Soc, 64, pp. 336-351, (2013); Chen C., Design for the Environment: A Quality-Based Model for Green Product Development, Manag. Sci, 47, pp. 250-263, (2001); He P., Wen J., Ye S., Li Z., Logistics service sharing and competition in a dual-channel e-commerce supply chain, Comput. Ind. Eng, 149, pp. 106-123, (2020); Guo L., Wu X., Capacity Sharing Between Competitors, Manag. Sci, 64, pp. 3554-3573, (2018); Tian L., Vakharia A.J., Tan Y., Xu Y., Marketplace, reseller, or hybrid: Strategic analysis of an emerging e- commerce model, Product. Operat. Manag, 27, pp. 1595-1610, (2018); Leng M., Parlar M., Lead-time reduction in a two-level supply chain: Non-cooperative equilibria vs. coordination with a profit-sharing contract, Int. J. Prod. Econ, 118, pp. 521-544, (2009); Yu Y., Wang X., Zhong R.Y., Huang G.Q., E-commerce Logistics in Supply Chain Management: Practice Perspective, Procedia CIRP, 52, pp. 179-185, (2016); Boyaci Y., Ray S., Product differentiation and capacity cost interaction in time and price sensitive markets, Manu. Service Oper. Manage, 5, pp. 18-36, (2003); Pekgun P., Griffin P.M., Keskinocak P., Centralized versus Decentralized Competition for Price and Lead-Time Sensitive Demand, Decis. Sci, 48, pp. 1198-1227, (2016); He P., Zhang S.S., He C., Impacts of logistics resource sharing on B2C e-commerce firms and customers, Elec. Com. Res. Applicat, 34, pp. 100-124, (2019); Jiang B., Jerath K., Srinivasan K., Firm strategies in the “Mid Tail” of platform-based retailing, Market. Sci, 30, pp. 757-775, (2011); Liu W., Yan X., Li X., Wei W., The impacts of market size and data-driven marketing on the sales mode selection in an Internet platform based supply chain, Transp. Res. Part E Logist. Transp. Rev, 136, pp. 101-124, (2020); Dan B., Xu G.Y., Liu C., Pricing policies in a dual-channel supply chain with retail services, Int. J. Prod. Econ, 139, pp. 312-320, (2012); Tan C.Q., Yi W.T., Dual channel supply chain pricing and online direct delivery strategy, J. Sys. Eng, 34, pp. 683-699, (2019); Choi T.-M., Wallace S.W., Wang Y., Risk management and coordination in service supply chains: Information, logistics and outsourcing, J. Oper. Res. Soc, 67, pp. 159-164, (2016); Tsai M.-C., Lai K.-H., Lloyd A.E., Lin H.-J., The dark side of logistics outsourcing—Unraveling the potential risks leading to failed relationships, Transp. Res. Part E Logist. Transp. Rev, 48, pp. 178-189, (2012); Lou Y., Feng L., He S., He Z., Zhao X., Logistics service outsourcing choices in a retailer-led supply chain, Transp. Res. Part E Logist. Transp. Rev, 141, pp. 115-141, (2020); He P., Wei J., Lu J., Zhao J., Interactions of competing manufacturer’s leader-follower relationship and sales format on online platforms, Eur. J. Operat. Res, 280, pp. 508-522, (2020); Qin X., Liu Z., Tian L., The strategic analysis of logistics service sharing in an e-commerce platform, Omega, 92, pp. 102-133, (2020); Li X., Li Y., Cai X., Shan J., Service channel choice for supply chain: Who is better off by undertaking the service?, Prod. Oper. Mana, 25, pp. 516-534, (2016); Li P., Wei H., Distribution, platform or Mix—Research on the choice of retailer business model, J. Manage. Sci, 21, pp. 50-75, (2018); Sun Z.L., Wang X.P., Ruan J.H., Manufacturer’s sales model selection considering direct selling cost and platform transaction fee, J. Manag, 15, pp. 111-117, (2018); Sun H.X., Li X.F., Zhou Z., Pricing strategies of dual channel retailers and traditional retailers, J. Chin. Manag. Sci, 28, pp. 104-111, (2020); Tian C., Lu J.H., Wei J., Research on logistics service and sales mode selection of complementary product based on e-commerce platform, J. Industr. Eng. Manag, 26, pp. 188-195, (2021); Wu G.Q., Xu J., Research on the equilibrium model of C2M service manufacturing logistics system based on logistics equilibrium theory, J. Industr. Eng. Manag, 25, pp. 125-142, (2020); Dai P.Q., Yao G.X., Xu J., Incentive mechanism design of logistics service provider under urban-rural two-way logistics model, J. Industr. Eng. Manag, 24, pp. 31-39, (2019); Gurnani H., Erkoc M., Luo Y., Impact of product pricing and timing of investment decisions on supply chain co-opetition, Eur. J. Oper. Res, 180, pp. 228-248, (2007); Anupindi R., Bassok Y., Zemel E., A General Framework for the Study of Decentralized Distribution Systems, Manuf. Serv. Oper. Manag, 3, pp. 349-368, (2001); Brandenburger A., Stuart H., Biform games, Manag. Sci, 53, pp. 537-549, (2007); Hu X., Caldentey R., Vulcano G., Revenue Sharing in Airline Alliances, Manag. Sci, 59, pp. 1177-1195, (2013); Abhishek V., Jerath K., Zhang Z.J., Agency Selling or Reselling? Channel Structures in Electronic Retailing, Manag. Sci, 62, pp. 2259-2280, (2016); Yan Y., Zhao R., Liu Z., Strategic introduction of the marketplace channel under spillovers from online to offline sales, Eur. J. Oper. Res, 267, pp. 65-77, (2018); Bernstein F., Federgruen A., A General Equilibrium Model for Industries with Price and Service Competition, Oper. Res, 52, pp. 868-886, (2004); Zhang Z., Xu H., Ke G.Y., Chen K., Selecting online distribution modes for differentiated products in a platform supply chain, Int. J. Prod. Econ, 244, pp. 108-125, (2022); Ha A.Y., Luo H., Shang W., Supplier Encroachment, Information Sharing, and Channel Structure in Online Retail Platforms, Prod. Oper. Manag, 31, pp. 1235-1251, (2021); Ren X., Herty M., Zhao L., Optimal price and service decisions for sharing platform and coordination between manufacturer and platform with recycling, Comput. Ind. Eng, 147, pp. 586-610, (2020); Lai G.M., Liu H.H., Xiao W.Q., Zhao X.Y., Fulfilled by Amazon”: A strategic perspective of competition at the e-commerce platform. Manu, Serv. Operat. Manag, 24, pp. 1261-1304, (2022)","M. Wang; School of Business, Linyi University, Linyi, 276000, China; email: wmly0180@163.com; D. Zhang; Department of Computer Science, Aalborg University, Aalborgost, 9220, Denmark; email: zhangdalin90@gmail.com",null,"MDPI",{"$nulls":5},1.6617827E7,null,null,3.6834049E7,"English","Int. J. Environ. Res. Public Health","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85148963501"]
["Gu J.","Gu, Jiafeng (37561156000)",3.7561156E10,"What drives SMEs to adopt e-commerce? The joint role of testosterone and absorptive capacity",2023.0,"Asia Pacific Journal of Marketing and Logistics",35.0,1.0,null,90.0,107.0,17.0,2.0,"10.1108/APJML-07-2021-0487","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85122814855&doi=10.1108%2fAPJML-07-2021-0487&partnerID=40&md5=68080e768130b787fab0c0c37c5ed09e","Peking University, Beijing, China","Gu J., Peking University, Beijing, China","Purpose: The study aims to investigate the relationship between chief executive officers' (CEOs') prenatal testosterone exposure, absorptive capacity and e-commerce adoption by small and medium-sized enterprises (SMEs). Design/methodology/approach: Based on a study of 1,519 SMEs led by a male CEO in China, the impact of entrepreneur's digital ratio on e-commerce adoption is empirically analyzed through a multivariate logistic model. Findings: The results show that the second-to-fourth digit ratio (2D:4D), a reverse measurement of prenatal testosterone exposure, is negatively correlated with the adoption of e-commerce by SMEs. This evidence suggests that CEOs with high prenatal testosterone exposure have a higher probability of adopting e-commerce. In addition, this research indicates a positive correlation between absorptive capacity, which is defined by market innovation, process innovation and marketing innovation, and the adoption of e-commerce by SMEs. Originality/value: This research can contribute to the discussion by providing new insights into the antecedents of the adoption of e-commerce in SMEs. © 2022, Emerald Publishing Limited.","Absorptive capacity; China; Digit ratio; E-commerce adoption; Small and medium-sized enterprises",{"$nulls":5},"National Social Science Foundation Project; National Office for Philosophy and Social Sciences, NPOPSS, (17BSH122)","Funding text 1: Funding: This study received funding from National Social Science Foundation of China (Award Number: 17BSH122).; Funding text 2: The authors gratefully acknowledge that the paper is the stage achievement of National Social Science Foundation Project (17BSH122) and thank for the support of National Social Science Foundation of China. The authors would like to express thanks to the editor and two anonymous reviewers for insightful comments and suggestions. ",{"$cut":{"chars":17798,"head":"Abebe M., Electronic commerce adoption, entrepreneurial orientation and small- and medium-sized enterprise (SME) performance, Journal of Small Business and Enterprise Development, 21, 1, pp. 100-116(117), (2014); Aboelmaged M., Hashem G., Absorptive capacity and green innovation adoption in SMEs: the mediating effects of sustainable organisational capabilities, Journal of Cleaner Production, 220, pp. 853-863, (2019); Adams E., Celebrating the world's MSMEs, International Trade Forum, 2, (2017); Albort-Morant G., Leal-Rodriguez A.L., Marchi V.D., Absorptive capacity and relationship learning mechanisms as complementary drivers of green innovation performance, Journal of Knowledge Management, 2, 2, pp. 432-452, (2018); Al-Bakri A.A., Katsioloudes M.I., The factors affecting e-commerce adoption by Jordanian SMEs, Management Research Review, 38, 7, pp. 726-749, (2015); Al-Qirim N.A.Y., The impact of the entrepreneurial characteristics of the CEO on eCommerce adoption in SMEs in New Zealand, The 2005 Information Resources Management Association International Conference, (2005); Apicella C.L., Dreber A., Campbell B., Gray P.B., Hoffman M., Little A.C., Testosterone and financial risk preferences, Evolution and Human Behavior, 29, 6, pp. 384-390, (2008); Ar I.M., Baki B., Antecedents and performance impacts of product versus process innovation: empirical evidence from SMEs located in Turkish science and technology parks, European Journal of Innovation Management, 14, 2, pp. 172-206, (1998); Arvey R.D., Li W.-D., Wang N., Genetics and organizational behavior, Annual Review of Organizational Psychology and Organizational Behavior, 3, pp. 167-190, (2016); Ayob A.H., E-commerce adoption in ASEAN: who and where?, Future Business Journal, 7, (2021); Baldwin J.R., Jarmin R.S., Tang J., The trend to smaller producers in manufacturing in Canada and the U.S, Social Science Electronic Publishing, 421, 2002003e, pp. 91-98, (2002); Baskerville R., Pries-Heje J., A multiple-theory analysis of a diffusion of information technology case, Information Systems Journal, 11, 3, pp. 181-212, (2001); Beaton A.A., Magowan S.V., Rudling N.G., Does handedness or digit ratio (2D:4D) predict lateralised cognitive ability?, Personality and Individual Differences, 52, 5, pp. 627-631, (2012); Beck R., Wigand R.T., Koenig W., Integration of E-commerce by SMEs in the manufacturing sector: a data envelopment analysis approach, Journal of Global Information Management, 13, 3, pp. 20-32, (2005); Beck T., Demirguc-Kunt A., Levine R., SMEs, growth, and poverty: cross-country evidence, Journal of Economic Growth, 10, 3, pp. 199-229, (2005); Boissy A., Bouissou M.F., Effects of androgen treatment on behavioral and physiological responses of heifers to fear-eliciting situations, Hormones and Behavior, 28, 1, pp. 66-83, (1994); Bonte W., Procher V.D., Urbig D., Biology and selection into entrepreneurship—the relevance of prenatal testosterone exposure, Entrepreneurship Theory and Practice, 40, 5, pp. 1121-1148, (2016); Bosch-Domenech A., Branas-Garza P., Espinc M.A., Can exposure to prenatal sex hormones (2D:4D) predict cognitive reflection?, Psychoneuroendocrinology, 43, 6, pp. 1-10, (2014); Branas-Garza P., Rustichini A., Organizing effects of testosterone and economic behavior: not just risk taking, PLoS One, 6, 12, (2011); Carre J., Olmstead N.A., Social neuroendocrinology of human aggression: examining the role of competition-induced testosterone dynamics, Neuroscience, 286, pp. 171-186, (2015); Chicaiza-Becerra L.A., Garcia-Molina M., Prenatal testosterone predicts financial risk taking: evidence from Latin America, Personality and Individual Differences, 116, pp. 32-37, (2017); Chiware E., Dick A.L., Information needs and information seeking patterns of small, medium and micro enterprises in Namibia, Information Development, 24, 1, pp. 24-36, (2008); Chu K.F., An organizational culture and the empowerment for change in SMEs in the Hong Kong manufacturing industry, Journal of Materials Processing Technology, 139, 1-3, pp. 505-509, (2003); Cohen W.M., Levinthal D."}},"J. Gu; Peking University, Beijing, China; email: isssgujf@pku.edu.cn",null,"Emerald Publishing",{"$nulls":5},1.3555855E7,null,null,null,"English","Asia Pac. J. Mark. Logist.","Article","Final",null,"Scopus","2-s2.0-85122814855"]
["Hu X.; Chuang Y.-F.","Hu, Xiulian (57427408700); Chuang, Yi-Fei (36774280200)","57427408700; 36774280200","E-commerce warehouse layout optimization: systematic layout planning using a genetic algorithm",2023.0,"Electronic Commerce Research",23.0,1.0,null,97.0,114.0,17.0,5.0,"10.1007/s10660-021-09521-9","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85123487380&doi=10.1007%2fs10660-021-09521-9&partnerID=40&md5=40154c98ce2fe40d557aabfec63dafd2","School of Economics and Management, Fuzhou University of International Studies and Trade, Fujian, 350202, China; Department of Business Administration, Ming Chuan University, Taipei, 11103, Taiwan; Social Science Research Base of Fujian Province, Logistics Research Center of Fuzhou University, Fujian, 350202, China","Hu X., School of Economics and Management, Fuzhou University of International Studies and Trade, Fujian, 350202, China, Department of Business Administration, Ming Chuan University, Taipei, 11103, Taiwan, Social Science Research Base of Fujian Province, Logistics Research Center of Fuzhou University, Fujian, 350202, China; Chuang Y.-F., Department of Business Administration, Ming Chuan University, Taipei, 11103, Taiwan","China has witnessed a rapid growth in e-commerce in recent years, particularly after the introduction of mobile Internet. The growth of logistics applications has led to the need for effective logistics operations. To facilitate this, the sorting efficiency of goods in a warehouse has to be high. As an important node connecting the central warehouse and the distribution website in the e-commerce supply chain, the warehouse belonging to an e-commerce business is crucial as the sorting efficiency of goods depends on the layout of the warehouse. The purpose of this article is to optimize the layout of e-commerce warehouses and improve sorting efficiency. First, the comprehensive interrelationship of functional areas is obtained employing a systematic layout planning method. Then, a nonlinear programming model is established. The objective function is constructed with the minimum total handling cost and the maximum comprehensive relationship. Finally, a genetic algorithm is used to solve the nonlinear programming model to obtain a scientific and reasonable e-commerce warehouse layout plan. The genetic algorithm is shown to have better convergence than particle swarm optimization and simulated annealing. After re-layout, the handling cost can be considerably reduced after optimization and the fitness function optimization rate is 39.25%. Our findings shed light on the facility layout decision of e-commerce warehouse, and reduce the material handling cost of the company and improve the picking efficiency. © 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.","E-commerce warehouse layout; Genetic algorithm; Intelligent optimization; Layout design; Layout optimization; Systematic layout planning",{"$nulls":5},"Fujian province social science planning, (FJ2020JDZ020); Fujian Provincial Federation of Social Sciences","Funding text 1: Research was sponsored by the Major project funding for social science research base in Fujian province social science planning, \"Research on the Impact of the Belt and Road Initiative on the performance of China's logistics industry --based on the perspective of International Trade\", Agreement number FJ2020JDZ020.; Funding text 2: Research was sponsored by the Major project funding for social science research base in Fujian province social science planning, \"Research on the Impact of the Belt and Road Initiative on the performance of China's logistics industry --based on the perspective of International Trade\", Agreement number FJ2020JDZ020. ","Ahmadi A., Pishvaee M.S., Jokar M.R.A., A survey on multi-floor facility layout problems, Computers & Industrial Engineering, 107, pp. 158-170, (2017); Al-Zubaidi S.Q.D., Fantoni G., Failli F., Analysis of drivers for solving facility layout problems: A Literature review, Journal of Industrial Information Integration, 21, (2021); Arnaout J.P., ElKhoury C., Karayaz G., Solving the multiple level warehouse layout problem using ant colony optimization, Operational Research, 20, 1, pp. 473-490, (2020); Besbes M., Zolghadri M., Affonso R.C., Masmoudi F., Haddar M., A methodology for solving facility layout problem considering barriers: Genetic algorithm coupled with A* search, Journal of Intelligent Manufacturing, 31, 3, pp. 615-640, (2020); Boysen N., de Koster R., Weidinger F., Warehousing in the e-commerce era: A survey, European Journal of Operational Research, 277, 2, pp. 396-411, (2019); Boysen N., Stephan K., Weidinger F., Manual order consolidation with put walls: The batched order bin sequencing problem, Euro Journal on Transportation and Logistics, 8, 2, pp. 169-193, (2019); Che A., Zhang Y.P., Feng J.G., Bi-objective optimization for multi-floor facility layout problem with fixed inner configuration and room adjacency constraints, Computers & Industrial Engineering, 105, pp. 265-276, (2017); Ejeh J.O., Liu S.S., Chalchooghi M.M., Papageorgiou L.G., Optimization-based approach for process plant layout, Industrial & Engineering Chemistry Research, 57, 31, pp. 10482-10490, (2018); Erik A., Kuvvetli Y., Integration of material handling devices assignment and facility layout problems, Journal of Manufacturing Systems, 58, pp. 59-74, (2021); Feng F.L., Jing L., Yang L.W., Layout method for the functional area of railway logistics center based on the improved systematic layout planning, China Railway Science, 33, 2, pp. 121-128, (2012); Guo Y., Wang Q., Liang F., Facility layout design based on particle swarm optimization, Computer Integrated Manufacturing Systems, 18, 11, pp. 2476-2484, (2012); Ha J.K., Lee E.S., Development of an optimal multifloor layout model for the generic liquefied natural gas liquefaction process, Korean Journal of Chemical Engineering, 33, 3, pp. 755-763, (2016); Horta M., Coelho F., Relvas S., Layout design modelling for a real world just-in-time warehouse, Computers & Industrial Engineering, 101, pp. 1-9, (2016); Hou S.W., Wen H.J., Feng S.X., Wang H., Li Z.B., Application of layered coding genetic algorithm in optimization of unequal area production facilities layout, Computational Intelligence and Neuroscience, 2019, pp. 1-17, (2019); E-commerce industry data analysis: China'sclothing industry B2B e-commerce accounted for 27% in 2019., (2020); Li J.H., Guo H., Zhang S.C., Wu X.Y., Shi L.L., Optimum design of ship cabin equipment layout based on SLP method and genetic algorithm, Mathematical Problems in Engineering, 2019, pp. 1-14, (2019); Nabavi S.R., Taghipour A.H., Gorji A.M., Optimization of facility layout of tank farms using genetic algorithm and fireball scenario, Chemical Product and Process Modeling, 11, 2, pp. 149-157, (2016); Sadrzadeh A., A genetic algorithm with the heuristic procedure to solve the multi-line layout problem, Computers & Industrial Engineering, 62, 4, pp. 1055-1064, (2012); Sinha R., Rabinovich E., Logistics: The key to e-Retail success, Supply Chain Management Review, 8, 6, pp. 36-56, (2006); Solimanpur M., Jafari A., Optimal solution for the two-dimensional facility layout problem using a branch-and-bound algorithm, Computers & Industrial Engineering, 55, 3, pp. 606-619, (2008); (2020); Su S.J., Zheng Y.S., Xu J.N., Wang T.L., Cabin placement layout optimisation based on systematic layout planning and genetic algorithm, Polish Maritime Research, 27, 1, pp. 162-172, (2020); Uribe N.R., Herran A., Colmenar J.M., Duarte A., An improved GRASP method for the multiple row equal facility layout problem, Expert Systems with Applications, 182, (2021); Yang P., Zhao Z.J., Guo H.J., Order batch picking optimization under different storage scenarios for e-commerce warehouses, Transportation Research Part E-Logistics and Transportation Review, 136, pp. 1-18, (2020); Zuniga E.R., Garcia E.F., Moris M.U., Fathi M., Syberfeldt A., (2021)","X. Hu; School of Economics and Management, Fuzhou University of International Studies and Trade, Fujian, 350202, China; email: huxiulian2007@gmail.com; Y.-F. Chuang; Department of Business Administration, Ming Chuan University, Taipei, 11103, Taiwan; email: yfchuang@mail.mcu.edu.tw",null,"Springer",{"$nulls":5},1.3895753E7,null,null,null,"English","Electron. Commer. Res.","Article","Final",null,"Scopus","2-s2.0-85123487380"]
["Wang B.; Yang X.; Qi M.","Wang, Bingqian (57417541700); Yang, Xiuqing (56095605600); Qi, Mingyao (23111610800)","57417541700; 56095605600; 23111610800","Order and rack sequencing in a robotic mobile fulfillment system with multiple picking stations",2023.0,"Flexible Services and Manufacturing Journal",35.0,2.0,null,509.0,547.0,38.0,4.0,"10.1007/s10696-021-09433-8","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85123097639&doi=10.1007%2fs10696-021-09433-8&partnerID=40&md5=4faf3fc38f5cc8a7e877f5be815ee687","Research Center on Modern Logistics, Shenzhen International Graduate School, Tsinghua University, Shenzhen, 518055, China; The Civil Aviation Logistics Technology Co., Ltd., The Second Research Institute of Civil Aviation Administration of China, Chengdu, 610041, China","Wang B., Research Center on Modern Logistics, Shenzhen International Graduate School, Tsinghua University, Shenzhen, 518055, China; Yang X., The Civil Aviation Logistics Technology Co., Ltd., The Second Research Institute of Civil Aviation Administration of China, Chengdu, 610041, China; Qi M., Research Center on Modern Logistics, Shenzhen International Graduate School, Tsinghua University, Shenzhen, 518055, China","The robotic mobile fulfillment system, where mobile robots carry racks to stationary stations for human pickers, is widely used in e-commerce warehouses. The operational efficiency of the system is largely affected by the organization of the order picking process. In this paper, we investigate an order picking tactic in a robotic mobile fulfillment system that allows racks moving between multiple picking stations in order to feed more orders during one visit and therefore save the overall throughput time. To evaluate this operational tactic’s effectiveness, we propose a mathematical model to jointly optimize the order assignment, order sequencing, rack selection, and rack sequencing. A two-stage hybrid heuristic algorithm framework is then presented, including order assignment in the first stage and order and rack sequencing in the second stage. We conduct numerical experiments to validate the proposed algorithms’ performance under different strategies and find out that the inter-station operation can significantly save order throughput time on the testing cases. We also investigate the effects of several factors, including the number of picking stations, their capacities, the stock keeping unit diversity, and queue length. Furthermore, a solid simulation is carried out to show the rationale of using rack moves as the objective rather than the completion time. © 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.","Heuristics; Logistics; Material handling; Order picking; Robotic; Simulation","Heuristic algorithms; Mobile robots; E- commerces; Heuristic; Hybrid heuristic algorithms; Material handling; Operational efficiencies; Operational tactics; Order assignment; Order-picking; Simulation; Throughput time; Materials handling",{"$nulls":4},"Sichuan Province Science and Technology Support Program, (2021JDRC0009); National Natural Science Foundation of China, NSFC, NNSF, NNSFC, (71772100); Key Technologies Research and Development Program; National Key Research and Development Program of China, NKRDPC, (2018AAA0101705); Science and Technology Planning Project of Shenzhen Municipality, (JCYJ20170412171044606)","This work is supported by the National Key R&D Program of China under grant No. 2018AAA0101705, the National Natural Science Foundation of China under Grant No. 71772100, and Shenzhen Science and Technology Project under Grant No. JCYJ20170412171044606, and Sichuan Science and Technology Program under grant No. 2021JDRC0009. ","Azadeh K., De Koster R., Roy D., Robotized and automated warehouse systems: review and recent developments, Transp Sci, 53, 4, pp. 917-945, (2019); Bartholdi I.I.I.J.J., Hackman S.T., (2008); Boysen N., Briskorn D., Emde S., Parts-to-picker based order processing in a rack-moving mobile robots environment, Eur J Opera Res, 262, 2, pp. 550-562, (2017); Boysen N., Briskorn D., Emde S., Sequencing of picking orders in mobile rack warehouses, Eur J Opera Res, 259, 1, pp. 293-307, (2017); Boysen N., Fedtke S., Weidinger F., Optimizing automated sorting in warehouses: the minimum order spread sequencing problem, Eur J Opera Res, 270, 1, pp. 386-400, (2018); Boysen N., de Koster R., Weidinger F., Warehousing in the e-commerce era: a survey, Eur J Opera Res, 277, 2, pp. 396-411, (2019); Bozer Y.A., Aldarondo F.J., A simulation-based comparison of two goods-to-person order picking systems in an online retail setting, Int J Prod Res, 56, 11, pp. 3838-3858, (2018); De Koster R., Le-Duc T., Roodbergen K.J., Design and control of warehouse order picking: a literature review, Eur J Opera Res, 182, 2, pp. 481-501, (2007); Duan G., Zhang C., Gonzalez P., Qi M., Performance evaluation for robotic mobile fulfillment systems with time-varying arrivals, Comp Ind Eng, 158, (2021); Fussler D., Boysen N., High-performance order processing in picking workstations, EURO J Transp Logist, 8, 1, pp. 65-90, (2019); Grosse E.H., Glock C.H., Jaber M.Y., Neumann W.P., Incorporating human factors in order picking planning models: framework and research opportunities, Int J Prod Res, 53, 3, pp. 695-717, (2015); Gu J., Goetschalckx M., McGinnis L.F., Research on warehouse operation: a comprehensive review, Eur J Opera Res, 177, 1, pp. 1-21, (2007); Huang G.Q., Chen M.Z., Pan J., Robotics in ecommerce logistics. HKIE, Transactions, 22, 2, pp. 68-77, (2015); Jaghbeer Y., Hanson R., Johansson M.I., Automated order picking systems and the links between design and performance: a systematic literature review, Int J Prod Res, 58, 15, pp. 4489-4505, (2020); Lamballais T., Roy D., de Koster M.B.M., Inventory allocation in robotic mobile fulfillment systems, IISE Transactions, pp. 1-17, (2019); Li Z., Li W., Mathematical model and algorithm for the task allocation problem of robots in the smart warehouse, Am J Opera Res, 5, 6, (2015); Li Z.P., Zhang J.L., Zhang H.J., Hua G.W., Optimal selection of movable shelves under cargo-to-person picking mode, Int J Simul Modell, 16, 1, pp. 145-156, (2017); Menendez B., Pardo E.G., Alonso-Ayuso A., Molina E., Duarte A., Variable neighborhood search strategies for the order batching problem, Comp Opera Res, 78, pp. 500-512, (2016); Merschformann M., Lamballais T., Koster M.B.M.D., Suhl L., Decision rules for robotic mobile fulfillment systems, Opera Res Perspect, 6, (2019); Mladenovic N., Hansen P., Variable neighborhood search, Comp Opera Res, 24, 11, pp. 1097-1100, (1997); Oncan T., Milp formulations and an iterated local search algorithm with tabu thresholding for the order batching problem, Euro J Opera Res, 243, 1, pp. 142-155, (2015); Quicktron, (2020); Roy D., Nigam S., de Koster R., Adan I., Resing J., Robot-storage zone assignment strategies in mobile fulfillment systems, Transp Res Part E: Logist Transp Rev, 122, pp. 119-142, (2019); Scholz A., Schubert D., Wascher G., Order picking with multiple pickers and due dates-simultaneous solution of order batching, batch assignment and sequencing, and picker routing problems, Euro J Opera Res, 263, 2, pp. 461-478, (2017); Tanimoto T.T., Ibm internal report, (1957); Valle C.A., Beasley J.E., Order allocation, rack allocation and rack sequencing for pickers in a mobile rack environment, Computers & Operations Research, 125, (2021); Weidinger F., Boysen N., Briskorn D., Storage assignment with rack-moving mobile robots in kiva warehouses, Transp Sci, 52, 6, pp. 1479-1495, (2018); Wurman P.R., D'Andrea R., Mountz M., Coordinating hundreds of cooperative, autonomous vehicles in warehouses, AI Magaz, 29, 1, (2008); Xi X., Liu C., Miao L., Storage assignment and order batching problem in kiva mobile fulfilment system, Eng Optim, 50, 11, pp. 1941-1962, (2018); Yuan R., Graves S.C., Cezik T., Velocity-based storage assignment in semi-automated storage systems, Prod Opera Manag, 28, 2, pp. 354-373, (2019); Zhang J., Yang F., Weng X., A building-block-based genetic algorithm for solving the robots allocation problem in a robotic mobile fulfilment system, Mathematical Problems in Engineering, (2019); Zou B., Gong Y.Y., Xu X., Yuan Z., Assignment rules in robotic mobile fulfilment systems for online retailers, Int J Prod Res, 55, 20, pp. 6175-6192, (2017)","M. Qi; Research Center on Modern Logistics, Shenzhen International Graduate School, Tsinghua University, Shenzhen, 518055, China; email: qimy@sz.tsinghua.edu.cn",null,"Springer",{"$nulls":5},1.9366582E7,null,null,null,"English","Flexible Serv Manuf J","Article","Final",null,"Scopus","2-s2.0-85123097639"]
["Xu X.; Guo S.; Cheng T.C.E.; Du P.","Xu, Xiaoping (57212081104); Guo, Shunan (58160208500); Cheng, T.C.E. (13302593800); Du, Pengcheng (57221800062)","57212081104; 58160208500; 13302593800; 57221800062","The choice between the agency and reselling modes considering green technology with the cap-and-trade scheme",2023.0,"International Journal of Production Economics",260.0,null,108839.0,null,null,null,4.0,"10.1016/j.ijpe.2023.108839","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85151023827&doi=10.1016%2fj.ijpe.2023.108839&partnerID=40&md5=fd6409ef6312ef77bddbf22959eb3f89","School of Business, Anhui University, Hefei, China; Department of Logistics and Maritime Studies, Faculty of Business, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong","Xu X., School of Business, Anhui University, Hefei, China; Guo S., School of Business, Anhui University, Hefei, China; Cheng T.C.E., Department of Logistics and Maritime Studies, Faculty of Business, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong; Du P., School of Business, Anhui University, Hefei, China","Given an online platform and a manufacturer, we research the platform mode choice where the two firms' cooperative mode is either the reselling or agency mode. With the cap-and-trade scheme, green technology is used to comply with this scheme and cater to consumers' environmental consciousness. We consider agency inefficiency and platform-enabled power, the platform's inherent characteristics in e-commerce, in our models. In addition, given the power structure, we consider three cases, namely the agency, manufacturer-led reselling, and platform-led reselling modes. Analyzing the optimal operational decisions, platform mode choice, and coordination problems in the three cases, we derive new and interesting findings. First, we uncover that increasing the cap weakens the optimal green level. However, increasing the cap first weakens and then enhances the optimal production quantity. Second, we uncover that the platform-led reselling mode is always more conducive to the production quantity and green level but the manufacturer-led reselling mode is more conducive to the manufacturer's profit. In addition, increasing agency inefficiency gradually enhances the market share, green level, and manufacturer's profit in the agency mode. Lastly, the manufacturer-led reselling mode can coordinate the two firms. Extending our models to consider the delivery time, we uncover that the agency and manufacturer-led reselling modes can coordinate the two firms. © 2023","Cap-and-trade scheme; Green technology; Platform; Power structure","Commerce; Competition; Profitability; Cap and trade; Cap-and-trade scheme; E- commerces; Green technology; Inherent characteristics; Mode choice; Online platforms; Platform; Power; Power structures; Environmental technology",{"$nulls":4},"Excellent Youth Research Project of Universities in Anhui Province, (2022AH030005); Project of Leading Talent of Anhui Province, (S020218015); National Natural Science Foundation of China, NSFC, (71801211, 71872001, 72171001, 72272001); Anhui Provincial Department of Education, (SK 2020A0041)","This work was supported in part by grants from the National Natural Science Foundation of China [Nos. 72171001, 71801211, 72272001 and 71872001]; Excellent Youth Research Project of Universities in Anhui Province [2022AH030005]; the Project of Leading Talent of Anhui Province [No. S020218015], the Key Project of the Education Department of Anhui Province [No. SK 2020A0041].","Cao K.Y., Guo Q., Xu Y.Q., Information sharing and carbon reduction strategies with extreme weather in the platform economy, Int. 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Rev., 97, pp. 268-281, (2017); Chen X., Wang X.J., Gong K., The effect of bidimensional power structure on supply chain decisions and performance, IEEE Transactions on Systems Man Cybernetics-Systems, 50, pp. 1095-1110, (2020); Chen X., Wang X.J., Zhang D., Yang M.F., Selling models for platforms under service-sensitive demand, Omega, 115, (2023); Chen X., Wang X.J., Zhou M.M., Firms' green R&D cooperation behaviour in a supply chain: technological spillover, power and coordination, Int. J. Prod. Econ., 218, pp. 118-134, (2019); Cheng F., Chen T., Shen Y.T., Jing X.D., Impact of green technology improvement and store brand introduction on the sales mode selection, Int. J. Prod. Econ., 253, (2022); Ding Y., Gao X., Huang C., Shu J., Yang D.H., Service competition in an online duopoly market, Omega, 77, pp. 58-72, (2018); Fan X.S., Chen K.L., Chen Y.J., Is price commitment a better solution to control carbon emissions and promote technology investment?, Manag. 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The role of platform entry strategy in an online marketplace, Transport. Res. E Logist. Transport. Rev., 170, (2023); Liu J.J., Ke H., Firms' pricing strategies under different decision sequences in dual-format online retailing, Soft Comput., 24, pp. 7811-7826, (2020); Liu J.J., Ke H., Firms' preferences for retailing formats considering one manufacturer's emission reduction investment, Int. J. Prod. Res., 59, pp. 3062-3083, (2021); Niu W., Shen H., Zhang L., Impact of power structure on decarbonizing investment with uncertain innovation: a triple bottom line perspective, Transport. Res. E Logist. Transport. Rev., 160, (2022); Pu X.J., Zhang S.M., Ji B.W., Han G.H., Online channel strategies under different offline channel power structures, J. Retailing Consum. Serv., 60, (2021); Shen Y.L., Willems S.P., Dai Y., Channel selection and contracting in the presence of a retail platform, Prod. Oper. 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Econ., 247, (2022); Xu X.P., He P., Fan Y.M., The pricing and carbon abatement decisions of a manufacturer selling with marketplace or reselling mode, Int. Trans. Oper. Res., 29, pp. 1220-1245, (2022); Xu X.P., He P., Xu H., Zhang Q.P., Supply chain coordination with green technology under cap-and-trade regulation, Int. J. Prod. Econ., 183, pp. 433-442, (2017); Xu X.P., He P., Zhang S.S., Channel addition from marketplace or reselling under regional carbon cap-and-trade regulation, Int. J. Prod. Econ., 236, (2021); Xu X.P., Zhang M.Y., Dou G.W., Yu Y.G., Coordination of a supply chain with an online platform considering green technology in the blockchain era, Int. J. Prod. Res., (2021); Xue M.S., Zhang J.X., Impacts of heterogeneous environment awareness and power structure on green supply chain, Oper. Res., 52, pp. 143-157, (2018); Yan Y.C., Zhao R.Q., Liu Z.B., Strategic introduction of the marketplace channel under spillovers from online to offline sales, Eur. J. Oper. Res., 267, pp. 65-77, (2018); Yan Y.C., Zhao R.Q., Xing T.T., Strategic introduction of the marketplace channel under dual upstream disadvantages in sales efficiency and demand information, Eur. J. Oper. Res., 273, pp. 968-982, (2019); Yang L., Zhang Q., Ji J.N., Pricing and carbon emission reduction decisions in supply chains with vertical and horizontal cooperation, Int. J. Prod. Econ., 191, pp. 286-297, (2017); Yu Y.G., Li X., Xu X.P., Reselling or marketplace mode for an online platform: the choice between cap-and-trade and carbon tax regulation, Ann. Oper. Res., 310, pp. 293-329, (2021); Zennyo Y., Strategic contracting and hybrid use of agency and wholesale contracts in e-commerce platforms, Eur. J. Oper. Res., 281, pp. 231-239, (2020); Zha Y., Li Q., Huang T.L., Yu Y.G., Strategic information sharing of online platforms as resellers or marketplaces, Market. Sci., (2023); Zhang Z., Xu H., Ke G.Y., Chen K., Selecting online distribution modes for differentiated products in a platform supply chain, Int. J. Prod. Econ., 244, (2022); Zhang Z.C., Xu H.Y., Chen K.B., Zhao Y.X., Liu Z., Channel mode selection for an e-platform supply chain in the presence of a secondary marketplace, Eur. J. Oper. Res., 305, pp. 1215-1235, (2023); Zhao X., Shang Y.P., Ma X.W., Xia P.F., Shahzad U., Does carbon trading lead to green technology innovation: recent evidence from Chinese companies in resource-based industries, IEEE Trans. Eng. Manag., (2022)","P. Du; School of Business, Anhui University, Hefei, China; email: dupengch@126.com",null,"Elsevier B.V.",{"$nulls":5},9255273.0,null,"IJPCE",null,"English","Int J Prod Econ","Article","Final",null,"Scopus","2-s2.0-85151023827"]
["Vrhovac V.; Vasić S.; Milisavljević S.; Dudić B.; Štarchoň P.; Žižakov M.","Vrhovac, Vijoleta (57698036700); Vasić, Stana (57213593529); Milisavljević, Stevan (55572466600); Dudić, Branislav (57199506472); Štarchoň, Peter (56582350100); Žižakov, Marina (57213595542)","57698036700; 57213593529; 55572466600; 57199506472; 56582350100; 57213595542","Measuring E-Commerce User Experience in the Last-Mile Delivery",2023.0,"Mathematics",11.0,6.0,1482.0,null,null,null,1.0,"10.3390/math11061482","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85151373148&doi=10.3390%2fmath11061482&partnerID=40&md5=3fe9722c9e5e6fe8148e448124f270de","Faculty of Technical Sciences, University of Novi Sad, Novi Sad, 21000, Serbia; Faculty of Management, Comenius University Bratislava, Bratislava, 82005, Slovakia; Faculty of Economics and Engineering Management, University Business Academy, Novi Sad, 21000, Serbia","Vrhovac V., Faculty of Technical Sciences, University of Novi Sad, Novi Sad, 21000, Serbia; Vasić S., Faculty of Technical Sciences, University of Novi Sad, Novi Sad, 21000, Serbia; Milisavljević S., Faculty of Technical Sciences, University of Novi Sad, Novi Sad, 21000, Serbia; Dudić B., Faculty of Management, Comenius University Bratislava, Bratislava, 82005, Slovakia, Faculty of Economics and Engineering Management, University Business Academy, Novi Sad, 21000, Serbia; Štarchoň P., Faculty of Management, Comenius University Bratislava, Bratislava, 82005, Slovakia; Žižakov M., Faculty of Technical Sciences, University of Novi Sad, Novi Sad, 21000, Serbia","This research aims to develop and to examine a measurement of customers’ experiences in the last-mile delivery process, which is a critical step towards their satisfaction and future intention to order products from the same retailer again. The CMX-LMD scale is proposed as a self-report tool whose psychometric properties where then examined. The total sample of N = 907 participants (63.4% females) was randomly split into two subsamples, then EFA and CFA were conducted, followed by item and correlation analysis. Six factors were revealed (Delivery efficiency, Parcel tracking, Smooth delivery, Visual appeal, Joyful anticipation, and Convenience), explaining about 60% of the total variance. The structure was supported by CFA (χ2(237) = 584.71, p < 0.001, CFI = 0.941, TLI = 0.932, RMSEA = 0.057, SRMR = 0.058). The relations of the derived scales and other variables, such as trust in courier services, were also examined. The CDX-LMD offers acceptable properties and provides a useful measurement for researchers and practitioners in the cross-section between e-commerce and logistics. © 2023 by the authors.","customer experience; customer satisfaction; delivery; e-commerce; last-mile delivery; logistics",{"$nulls":7},"Aljohani K., Thompson R.G., A Stakeholder-Based Evaluation of the Most Suitable and Sustainable Delivery Fleet for Freight Consolidation Policies in the Inner-City Area, Sustainability, 11, (2019); Buldeo Rai H., Verlinde S., Macharis C., The “next Day, Free Delivery” Myth Unravelled: Possibilities for Sustainable Last Mile Transport in an Omnichannel Environment, Int. J. Retail Distrib. 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Res, 277, pp. 396-411, (2019); Schwerdfeger S., Boysen N., Optimizing the Changing Locations of Mobile Parcel Lockers in Last-Mile Distribution, Eur. J. Oper. Res, 285, pp. 1077-1094, (2020); Vakulenko Y., Shams P., Hellstrom D., Hjort K., Online Retail Experience and Customer Satisfaction: The Mediating Role of Last Mile Delivery, Int. Rev. Retail. Distrib. Consum. Res, 29, pp. 306-320, (2019); Buldeo Rai H., Broekaert C., Verlinde S., Macharis C., Sharing Is Caring: How Non-Financial Incentives Drive Sustainable e-Commerce Delivery, Transp. Res. Part D Transp. Environ, 93, (2021); Srivatsa Srinivas S., Marathe R.R., Moving towards “Mobile Warehouse”: Last-Mile Logistics during COVID-19 and Beyond, Transp. Res. Interdiscip. Perspect, 10, pp. 6-11, (2021); Mangiaracina R., Perego A., Seghezzi A., Tumino A., Innovative Solutions to Increase Last-Mile Delivery Efficiency in B2C e-Commerce: A Literature Review, Int. J. Phys. Distrib. Logist. 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J, 10, pp. 1293-1304, (2022); Celikkol S., Uludag C.C., The relationship of lipstick effect with sustainable management processes of businesses: A qualitative research on cosmetics industry executives, Dogus Univ. J, 23, pp. 105-127, (2022)","S. Vasić; Faculty of Technical Sciences, University of Novi Sad, Novi Sad, 21000, Serbia; email: vasic.stana@uns.ac.rs; B. Dudić; Faculty of Management, Comenius University Bratislava, Bratislava, 82005, Slovakia; email: branislav.dudic@fm.uniba.sk",null,"MDPI",{"$nulls":5},2.227739E7,null,null,null,"English","Mathematics","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85151373148"]
["Sıcakyüz Ç.","Sıcakyüz, Çiğdem (58099476800)",5.80994768E10,"Analyzing Healthcare and Wellness Products’ Quality Embedded in Online Customer Reviews: Assessment with a Hybrid Fuzzy LMAW and Fermatean Fuzzy WASPAS Method",2023.0,"Sustainability (Switzerland)",15.0,4.0,3428.0,null,null,null,6.0,"10.3390/su15043428","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85149299222&doi=10.3390%2fsu15043428&partnerID=40&md5=ac383fdfc81a88f8f6675931d311948f","Industrial Engineering Department, Faculty of Engineering and Architecture, Ankara Science University, Ankara, 06200, Turkey","Sıcakyüz Ç., Industrial Engineering Department, Faculty of Engineering and Architecture, Ankara Science University, Ankara, 06200, Turkey","With the high impetus in global digitization, online shopping (OS) is anticipated to increase further in the near future. Contrary to this anticipation, however, recent studies have emphasized a certain amount of drop in a considerable number of online purchasing transactions in 2022. One of the reasons might be customer dissatisfaction. To analyze online customer reviews, manual sentiment analysis was conducted to detect which quality criteria cause the dissatisfaction of online shoppers. The quality parameters are categorized into product, delivery service, and aftersales service quality (SQ). These main quality criteria are then divided into sub-factors. Eight health category products, including personal care products, wellness products, and household cleaners, were ranked to the importance of the sub-quality parameters using the multi-criteria decision-making (MCDM) method. In this study, a new hybrid MCDM method was also proposed, which combines the triangular fuzzy logarithm methodology of additive weights (F-LMAW) and the Fermatean fuzzy weighted aggregated sum product assessment method (FF-WASPAS). The study reveals that the most important criteria were products’ performance, as well as their side effects, pay-back, and change possibility, while the products’ reasonable price was the least important criterion. Aftersales service was more significant than delivery service. Furthermore, moisturizing creams and medical pillows were the most popular products bought in OS compared with hair conditioners and washing liquids. The study’s multifold contributions and managerial implications were elaborately discussed. © 2023 by the author.","customer satisfaction; e-commerce; F-LMAW; FF-WASPAS; MCDM; online shopping; service quality; sustainable competitive advantage; word of mouth","assessment method; electronic commerce; fuzzy mathematics; service quality; spatiotemporal analysis; sustainability; World Wide Web",{"$nulls":6},{"$cut":{"chars":24472,"head":"Chevalier S., Retail E-Commerce Sales Worldwide from 2014 to 2026; Bernhardt G., Global Ecommerce Sales Growth Report for 2021–2026; Roberts R., Health and Wellness Marketing: An Ecommerce Report on the Health and Wellness Industry, Consumer Trends & Strategies for Growth; Inflation Edges up to 10.7% in October, (2022); Pasquali M., Shopping Cart Abandonment Rate Worldwide 2022, by Industry; Rita P., Oliveira T., Farisa A., The Impact of E-Service Quality and Customer Satisfaction on Customer Behavior in Online Shopping, Heliyon, 5, (2019); The Global Governance of Online Consumer Protection and E-Commerce Building Trust, (2019); Sabou S., Avram-Pop B., Zima L.A., The Impact of the Problems Faced by Online Customers on Ecommerce, Stud. Univ. Babes-Bolyai Oeconomica, 62, pp. 77-88, (2017); Fedorko R., Kral S., Online Shopping Problems in the Context of B2C E-Commerce in the Visegrad Four Countries, Springer Proceedings in Business and Economics, pp. 83-94, (2021); Brandtner P., Darbanian F., Falatouri T., Udokwu C., Impact of COVID-19 on the Customer End of Retail Supply Chains: A Big Data Analysis of Consumer Satisfaction, Sustainability, 13, (2021); Fihartini Y., Helmi A., Hassan M., Oesman Y.M., Perceived Health Risk, Online Retail Ethics, and Consumer Behavior within Online Shopping during the Covid-19 Pandemic, Innov. Mark, 17, pp. 17-29, (2021); Coppola D., ACSI—U.S. Customer Satisfaction with Amazon.Com as of 2021; Charm T., Dhar R., Haas S., Liu J., Novemsky N., Teichner W., Understanding and Shaping Consumer Behavior in the next Normal; Ma H., Competitive Advantage and Firm Performance, Compet. Rev, 10, pp. 15-32, (2000); Huang K.F., Dyerson R., Wu L.Y., Harindranath G., From Temporary Competitive Advantage to Sustainable Competitive Advantage, Br. J. Manag, 26, pp. 617-636, (2015); Uzir M.U.H., al Halbusi H., Thurasamy R., Thiam Hock R.L., Aljaberi M.A., Hasan N., Hamid M., The Effects of Service Quality, Perceived Value and Trust in Home Delivery Service Personnel on Customer Satisfaction: Evidence from a Developing Country, J. Retail. Consum. Serv, 63, (2021); Sundaram V., Ramkumar D., Shankar P., Impact of E-Service Quality on Customer Satisfaction and Loyalty Empirical Study in India Online Business, KINERJA, 21, pp. 48-69, (2017); Senecal S., Nantel J., The Influence of Online Product Recommendations on Consumers’ Online Choices, J. Retail, 80, pp. 159-169, (2004); Robson K., Farshid M., Bredican J., Humphrey S., Making Sense of Online Consumer Reviews: A Methodology, Int. J. Mark. Res, 55, (2013); Cui G., Lui H.K., Guo X., The Effect of Online Consumer Reviews on New Product Sales, Int. J. Electron. Commer, 17, pp. 39-58, (2012); Singh J., Crisafulli B., Managing Online Service Recovery: Procedures, Justice and Customer Satisfaction, J. Serv. Theory Pract, 26, pp. 764-787, (2016); Wang W., Li F., Yi Z., Scores vs. Stars: A Regression Discontinuity Study of Online Consumer Reviews, Inf. Manag, 56, pp. 418-428, (2019); Truong D., Truong M.D., How Do Customers Change Their Purchasing Behaviors during the COVID-19 Pandemic?, J. Retail. Consum. Serv, 67, (2022); Cao Y., Ajjan H., Hong P., Post-Purchase Shipping and Customer Service Experiences in Online Shopping and Their Impact on Customer Satisfaction: An Empirical Study with Comparison, Asia Pac. J. Mark. Logist, 30, pp. 400-416, (2018); Chatterjee S., Goyal D., Prakash A., Sharma J., Exploring Healthcare/Health-Product Ecommerce Satisfaction: A Text Mining and Machine Learning Application, J. Bus. Res, 131, pp. 815-825, (2021); Lackermair G., Kailer D., Kanmaz K., Importance of Online Product Reviews from a Consumer’s Perspective, Adv. Econ. Bus, 1, pp. 1-5, (2013); Medhat W., Hassan A., Korashy H., Sentiment Analysis Algorithms and Applications: A Survey, Ain. Shams Eng. J, 5, pp. 1093-1113, (2014); Ganu G., Am A., Marian A., Beyond the Stars: Improving Rating Predictions Using Review Text Content, Proceedings of the Twelfth International Workshop on the Web and Databases (WebDB 2009), pp. 1-6; Hussein D.M.E.D.M., A Survey on Sentiment Analysis Challenges,"}},"Ç. Sıcakyüz; Industrial Engineering Department, Faculty of Engineering and Architecture, Ankara Science University, Ankara, 06200, Turkey; email: cigdem.sicakyuz@ankarabilim.edu.tr",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85149299222"]
["Chen J.C.; Chen T.-L.; Lee Y.-H.","Chen, James C. (7501886993); Chen, Tzu-Li (58250383600); Lee, Yu-Hsin (57209136208)","7501886993; 58250383600; 57209136208","Simulation optimization for parcel hub scheduling problem in closed-loop sortation system with shortcuts",2023.0,"Simulation Modelling Practice and Theory",124.0,null,102728.0,null,null,null,0.0,"10.1016/j.simpat.2023.102728","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85147546495&doi=10.1016%2fj.simpat.2023.102728&partnerID=40&md5=e4aa1dc78289ac0d54439d5b3369f8bb","Department of Industrial Engineering and Engineering Management, National Tsing Hua University, Hsinchu, 30013, Taiwan; Graduate Institute of Intelligent Manufacturing Technology, National Taiwan University of Science and Technology, Taipei, 106335, Taiwan","Chen J.C., Department of Industrial Engineering and Engineering Management, National Tsing Hua University, Hsinchu, 30013, Taiwan; Chen T.-L., Graduate Institute of Intelligent Manufacturing Technology, National Taiwan University of Science and Technology, Taipei, 106335, Taiwan; Lee Y.-H., Department of Industrial Engineering and Engineering Management, National Tsing Hua University, Hsinchu, 30013, Taiwan","With the growth of e-commerce, the quantity of delivery orders and parcels is steadily increasing. Reliable and fast parcel delivery services are of utmost importance to customers. To achieve this target, the central parcel consolidation terminals (CPCT) known as parcel sorting hubs are dedicated to improving the operational efficiency especially in the optimal scheduling of inbound trucks. This study aims to determine the optimal schedule and assignment of inbound trucks to the inbound docks, known as the parcel hub scheduling problem with shortcuts (PHSPwS), for minimizing the expected makespan and expected waiting time of inbound trucks in the closed-loop automated sorting conveyor (ASC) system with shortcuts of the parcel sorting hubs. We first construct a mathematical formulation to present the PHSPwS problem based on the traffic control model. However, due to the congestion behavior on the conveyors and stochastic and dynamic nature of the ASC system, the expected objective functions are not analytically available from the mathematical model. Then, a simulation optimization (SO) approach combined with an adaptive genetic-based discrete particle swarm optimization (AGDPSO) algorithm is proposed to tackle the PHSPwS problem in a stochastic and dynamic ASC environment. The closed-loop ASC simulation model is first established to describe the detail operation of the closed-loop ASC sortation system with shortcut. Based on performance evaluation of this simulation model, a novelty algorithm AGDPSO, which hybridized genetic algorithm and particle swarm optimization algorithm with self-tuning parameters is developed to search and find the optimal inbound truck schedule in the large-scale solution space. In particular, the time-varying acceleration coefficients embedded in the AGDPSO are adopted to amplify the effectiveness of the global and local best solutions to obtain a better balance between exploration and exploitation of the searching space. The experimental results reveal that AGDPSO outperforms other algorithms and provides a better and more stable solution. Moreover, the impact of the strategic and operational factors of the closed-loop ASC system for the expected makespan and truck queueing time are also investigated, while the automatic truck unloading mode is confirmed to significantly improve the system efficiency. © 2023 Elsevier B.V.","Adaptive genetic-based discrete particle swarm optimization; Intersection of parcels; Parcel hub scheduling problem; Simulation optimization; Time-varying acceleration coefficients","Acceleration; Automobiles; Conveyors; Efficiency; Genetic algorithms; Particle swarm optimization (PSO); Stochastic systems; Traffic control; Unloading; Adaptive genetic-based discrete particle swarm optimization; Automated sorting; Closed-loop; Discrete particle swarm optimization; Hub scheduling; Intersection of parcel; Parcel hub scheduling problem; Scheduling problem; Simulation optimization; Time-varying acceleration coefficients; Trucks",{"$nulls":6},"Yu Y., Wang X., Zhong R.Y., Huang G.Q., E-commerce logistics in supply chain management Implementations and future perspective in furniture industry, Industr. Manag. Data Syst., 117, 10, pp. 2263-2286, (2017); Boysen N., Fliedner M., Cross dock scheduling: classification, literature review and research agenda, Omega (Westport), 38, 6, pp. 413-422, (2010); Apte U.M., Viswanathan S., Effective cross docking for improving distribution efficiencies, Int. J. Logist. Res. Applic., 3, 3, pp. 291-302, (2000); Boysen N., Briskorn D., Fedtke S., Schmickerath M., Automated sortation conveyors: a survey from an operational research perspective, Eur. J. Oper. Res., 276, 3, pp. 796-815, (2019); Hosseini-Nasab H., Fereidouni S., Fatemi Ghomi S.M.T., Fakhrzad M.B., Classification of facility layout problems: a review study, Int. J. Adv. Manuf. Technol., 94, 1, pp. 957-977, (2017); Mcwilliams D.L., A genetic based scheduling algorithm for the PHSP with unequal batch size inbound trailers, J. Industr. Syst. Eng., 4, 3, pp. 167-182, (2010); Chen J.C., Huang C.F., Chen T.L., Lee Y.H., Solving a sortation conveyor layout design problem with simulation-optimization approach, 2019 IEEE 6th International Conference on Industrial Engineering and Applications, ICIEA 2019, pp. 551-555, (2019); Chen J.C., Chen T.L., Ou T.C., Lee Y.H., Adaptive genetic algorithm for parcel hub scheduling problem with shortcuts in closed-loop sortation system, Comput. Industr. Eng., 138, (2019); McWilliams D.L., Stanfield P.M., Geiger C.D., The parcel hub scheduling problem: a simulation-based solution approach, Comput. Industr. Eng., 49, 3, pp. 393-412, (2005); McWilliams D.L., Stanfield P.M., Geiger C.D., Minimizing the completion time of the transfer operations in a central parcel consolidation terminal with unequal-batch-size inbound trailers, Comput. Industr. Eng., 54, 4, pp. 709-720, (2008); McWilliams D.L., Genetic-based scheduling to solve the parcel hub scheduling problem, Comput. Ind. Eng., 56, 4, pp. 1607-1616, (2009); Chen F., Lee C.Y., Minimizing the makespan in a two-machine cross-docking flow shop problem, Eur. J. Oper. Res., 193, 1, pp. 59-72, (2009); Chen F., Song K., Minimizing makespan in two-stage hybrid cross docking scheduling problem, Comput. Operat. Res., 36, 6, pp. 2066-2073, (2009); Boysen N., Fliedner M., Scholl A., Scheduling inbound and outbound trucks at cross docking terminals, OR Spectrum, 32, 1, pp. 135-161, (2008); Boysen N., Truck scheduling at zero-inventory cross docking terminals, Comput. Operat. Res., 37, 1, pp. 32-41, (2010); Briskorn D., Emde S., Boysen N., Scheduling shipments in closed-loop sortation conveyors, J. Sched., 20, 1, pp. 25-42, (2017); McWilliams D.L., McBride M.E., A beam search heuristics to solve the parcel hub scheduling problem, Comput. Industr. Eng., 62, 4, pp. 1080-1092, (2012); Boysen N., Fedtke S., Weidinger F., Truck scheduling in the postal service industry, Transp. Sci., 51, 2, pp. 723-736, (2017); Yu W., Egbelu P.J., Scheduling of inbound and outbound trucks in cross docking systems with temporary storage, Eur. J. Oper. Res., 184, 1, pp. 377-396, (2008); Larbi R., Alpan G., Baptiste P., Penz B., Scheduling cross docking operations under full, partial and no information on inbound arrivals, Comput. Oper. Res., 38, 6, pp. 889-900, (2011); Bodnar P., de Koster R., Azadeh K., Scheduling trucks in a cross-dock with mixed service mode dock doors, Transp. Sci., 51, 1, pp. 112-131, (2017); Heidari F., Zegordi S.H., Tavakkoli-Moghaddam R., Modeling truck scheduling problem at a cross-dock facility through a bi-objective bi-level optimization approach, J. Intell. 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Extr., 1, 1, pp. 157-191, (2018); Lopes H.S., Coelho L.S., Particle swarm optimization with fast local search for the blind travelling salesman problem, Proceedings - HIS 2005: Fifth International Conference on Hybrid Intelligent Systems, 2005, pp. 245-250, (2005); Bo Y., Yunping C., Zunlian Z., A hybrid evolutionary algorithm by combination of PSO and GA for unconstrained and constrained optimization problems, 2007 IEEE International Conference on Control and Automation, ICCA, pp. 166-170, (2007); Anjana V., Sridharan R., Ram Kumar P.N., Metaheuristics for solving a multi-objective flow shop scheduling problem with sequence-dependent setup times, J. Sched., 23, 1, pp. 49-69, (2020); Ratnaweera A., Halgamuge S.K., Watson H.C., Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients, IEEE Trans. Evol. Comput., 8, 3, pp. 240-255, (2004); Cai Q., Gong M., Ma L., Ruan S., Yuan F., Jiao L., Greedy discrete particle swarm optimization for large-scale social network clustering, Inf. Sci., 316, pp. 503-516, (2015)","T.-L. Chen; Graduate Institute of Intelligent Manufacturing Technology, National Taiwan University of Science and Technology, Taipei, 106335, Taiwan; email: chentzuli@gmail.com",null,"Elsevier B.V.",{"$nulls":5},"1569190X",null,null,null,"English","Simul. Model. Pract. Theory","Article","Final",null,"Scopus","2-s2.0-85147546495"]
["Li M.; Feng J.; Xu S.X.","Li, Ming (57196402801); Feng, Jianghong (57218395456); Xu, Su Xiu (35773963700)","57196402801; 57218395456; 35773963700","Toward resilient cloud warehousing via a blockchain-enabled auction approach",2023.0,"Frontiers of Engineering Management",10.0,1.0,null,20.0,38.0,18.0,2.0,"10.1007/s42524-022-0224-2","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85152593699&doi=10.1007%2fs42524-022-0224-2&partnerID=40&md5=b07072140f0334b5eb253c80a2e33730","Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong; School of Management, Jinan University, Guangzhou, 510632, China; School of Management and Economics, Beijing Institute of Technology, Beijing, 100081, China","Li M., Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong; Feng J., School of Management, Jinan University, Guangzhou, 510632, China; Xu S.X., School of Management and Economics, Beijing Institute of Technology, Beijing, 100081, China","Cloud warehousing service (CWS) has emerged as a promising third-party logistics service paradigm driven by the widespread use of e-commerce. The current CWS billing method is typically based on a fixed rate in a coarse-grained manner. This method cannot reflect the true service value under the fluctuating e-commerce logistics demand and is not conducive to CWS resilience management. Accordingly, a floating mechanism can be considered to introduce more flexible billing. A CWS provider lacks sufficient credibility to implement floating mechanisms because it has vested interests in terms of fictitious demand. To address this concern, this report proposes a blockchain-enabled floating billing management system as an overall solution for CWS providers to enhance the security, credibility, and transparency of CWS. A one-sided Vickrey–Clarke–Groves (O-VCG) auction mechanism model is designed as the underlying floating billing mechanism to reflect the real-time market value of fine-grained CWS resources. A blockchain-based floating billing prototype system is built as an experimental environment. Our results show that the O-VCG mechanism can effectively reflect the real-time market value of CWSs and increase the revenue of CWS providers. When the supply of CWS providers remains unchanged, allocation efficiency increases when demand increases. By analyzing the performance of the O-VCG auction and comparing it with that of the fixed-rate billing model, the proposed mechanism has more advantages. Moreover, our work provides novel managerial insights for CWS market stakeholders in terms of practical applications. © 2023, Higher Education Press.","auction mechanism; blockchain technology; floating billing management system; resilient cloud warehousing; third-party logistics",{"$nulls":5},"RGC, (T32-707-22-N); National Natural Science Foundation of China, NSFC, (52005218, 72071093); Natural Science Foundation of Guangdong Province, (2019A1515110296); Basic and Applied Basic Research Foundation of Guangdong Province","This work is supported by the National Natural Science Foundation of China (Grant Nos. 52005218 and 72071093), RGC TRS Project (Grant No. T32-707-22-N), and the Guangdong Basic and Applied Basic Research Foundation (Guangdong Natural Science Fund, Grant No. 2019A1515110296).","Alexandridis A., Al-Sumaidaee G., Alkhudary R., Zilic Z., Making case for using RAFT in healthcare through hyperledger fabric, IEEE International Conference on Big Data, pp. 2185-2191, (2021); Barker J.M., Gibson A.R., Hofer A.R., Hofer C., Moussaoui I., Scott M.A., A competitive dynamics perspective on the diversification of third-party logistics providers’ service portfolios, Transportation Research Part E: Logistics and Transportation Review, 146, (2021); Baruffaldi G., Accorsi R., Manzini R., Warehouse management system customization and information availability in 3PL companies: A decision-support tool, Industrial Management & Data Systems, 119, 2, pp. 251-273, (2019); Basar G., Cetin M., Auction-based tolling systems in a connected and automated vehicles environment: Public opinion and implications for toll revenue and capacity utilization, Transportation Research Part C: Emerging Technologies, 81, pp. 268-285, (2017); Borgstrom B., Hertz S., Jensen L.M., Strategic development of third-party logistics providers (TPLs): “Going under the floor” or “raising the roof”?, Industrial Marketing Management, 97, pp. 183-192, (2021); Chen X., Feldman J., Jung S.H., Kouvelis P., Approximation schemes for the joint inventory selection and online resource allocation problem, Production and Operations Management, 31, 8, pp. 3143-3159, (2022); Cheng M., Ning Y., Xu S.X., Wang Z., Novel double auctions for spatially distributed parking slot assignment with externalities, IISE Transactions, 55, 3, pp. 288-300, (2023); Choi T.M., Risk analysis in logistics systems: A research agenda during and after the COVID-19 pandemic, Transportation Research Part E: Logistics and Transportation Review, 145, (2021); Choi T.M., Shi X., Reducing supply risks by supply guarantee deposit payments in the fashion industry in the “New Normal after COVID-19, Omega, 109, (2022); Chu X., Xu S.X., Cai F., Chen J., Qin Q., An efficient auction mechanism for regional logistics synchronization, Journal of Intelligent Manufacturing, 30, 7, pp. 2715-2731, (2019); Dibaj S.R., Miri A., Mostafavi S., A cloud dynamic online double auction mechanism (DODAM) for sustainable pricing, Telecommunication Systems, 75, 4, pp. 461-480, (2020); Dimitris P., Pricing of 3PL services, Outsourcing Management for Supply Chain Operations and Logistics Service, pp. 376-387, (2013); Dolgui A., Ivanov D., Ripple effect and supply chain disruption management: New trends and research directions, International Journal of Production Research, 59, 1, pp. 102-109, (2021); Du M., Chen Q., Chen J., Ma X., An optimized consortium blockchain for medical information sharing, IEEE Transactions on Engineering Management, 68, 6, pp. 1677-1689, (2021); Dutta P., Choi T.M., Somani S., Butala R., Blockchain technology in supply chain operations: Applications, challenges and research opportunities, Transportation Research Part E: Logistics and Transportation Review, 142, (2020); El Baz J., Ruel S., Can supply chain risk management practices mitigate the disruption impacts on supply chains’ resilience and robustness? 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Xu; School of Management and Economics, Beijing Institute of Technology, Beijing, 100081, China; email: xusuxiu@bit.edu.cn",null,"Higher Education Press Limited Company",{"$nulls":5},2.0957513E7,null,null,null,"English","Front. Eng. Manag.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85152593699"]
["Chen W.-H.; Lin Y.-C.; Bag A.; Chen C.-L.","Chen, Wei-Hung (57202006662); Lin, Yao-Chin (35076073500); Bag, Anima (58158875000); Chen, Chun-Liang (55268789000)","57202006662; 35076073500; 58158875000; 55268789000","Influence Factors of Small and Medium-Sized Enterprises and Micro-Enterprises in the Cross-Border E-Commerce Platforms",2023.0,"Journal of Theoretical and Applied Electronic Commerce Research",18.0,1.0,null,416.0,440.0,24.0,5.0,"10.3390/jtaer18010022","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85150980277&doi=10.3390%2fjtaer18010022&partnerID=40&md5=a495e9d435923128a586bb7aee3ede23","Department of Information Management, Chihlee University of Technology, New Taipei City, 220305, Taiwan; Department of Information Management, Yuan Ze University, Taoyuan City, 32003, Taiwan; Graduate School of Creative Industry Design, National Taiwan University of Arts, New Taipei City, 22058, Taiwan","Chen W.-H., Department of Information Management, Chihlee University of Technology, New Taipei City, 220305, Taiwan; Lin Y.-C., Department of Information Management, Yuan Ze University, Taoyuan City, 32003, Taiwan; Bag A., Department of Information Management, Yuan Ze University, Taoyuan City, 32003, Taiwan; Chen C.-L., Graduate School of Creative Industry Design, National Taiwan University of Arts, New Taipei City, 22058, Taiwan","Small and medium-sized businesses (SMEs) are frequently exposed to a variety of difficulties during global epidemic crises like coronavirus (COVID-19), which may even threaten their lives. The purpose of this study explores the influencing factors of Taiwan’s companies between small and medium-sized enterprises and micro-enterprises on the choice of the cross-border e-commerce platform. The findings are defined as taking into account small and medium-sized businesses and microenterprises when choosing cross-border e-commerce through a literature review and an examination of secondary data among the 10 participating businesses through interviews in various regions and business sectors in Taiwan. In this case we used study-based research, which included five small, medium-sized, and micro-enterprises, as well as five cross-border e-commerce projects and the company’s management senior officers. According to the study’s emphasis on the economic, social, technological, and legal aspects of various firms, these factors lead to a variety of decisions regarding the best cross-border e-commerce platform. The case study approach was utilized in this investigation to confirm the consideration of micro-and small-sized businesses that took part in cross-border e-commerce project counseling. This study summarizes five types of enterprises with different capabilities: product enhancement, marketing enhancement, cross-border potential, knowledge-based enhancement, and cross-border start-up. According to the results, it was found that different enterprise capabilities will affect the choice of cross-border e-commerce platforms. These five capabilities also have different types of consideration factors; among them, SMEs pay attention to marketing, pricing, market analysis, culture, customer service, payment, logistics, certification, taxation, etc. In addition to theoretical implications, this research also gives small and medium enterprises and micro-enterprises practice when choosing cross-border e-commerce platform, as well as suggestions for future research. © 2023 by the authors.","COVID-19; cross-border e-commerce platform; e-commerce; micro-enterprises; small and medium enterprises",{"$nulls":7},"Rather R.A., Demystifying the effects of perceived risk and fear on customer engagement, co-creation and revisit intention during COVID-19: A protection motivation theory approach, J. Destin. Mark. Manag, 20, (2021); Liu Z., Li Z., A blockchain-based framework of cross-border e-commerce supply chain, Int. J. Inf. 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Res, 3, pp. 39-45, (2014); Duan C., Kotey B., Sandhu K., The effects of cross-border E-commerce platforms on transnational digital entrepreneurship: Case studies in the Chinese immigrant community, J. Glob. Inf. Manag, 30, pp. 1-19, (2021)","A. Bag; Department of Information Management, Yuan Ze University, Taoyuan City, 32003, Taiwan; email: anima86.bag@gmail.com",null,"MDPI",{"$nulls":5},7181876.0,null,null,null,"English","J. Theor. Appl. Electron. Commer. Res.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85150980277"]
["Du W.; Dzamankulov B.","Du, WenYang (58871720300); Dzamankulov, Bolot (58872332900)","58871720300; 58872332900","THE VALUE, ROLE, AND ANALYSIS OF CROSS-BORDER E-COMMERCE DEVELOPMENT IN CHINA'S IMPORT AND EXPORT ECONOMY",2023.0,"International Journal of eBusiness and eGovernment Studies",15.0,1.0,null,366.0,393.0,27.0,null,"10.34109/ijebeg.2023150117","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85184494002&doi=10.34109%2fijebeg.2023150117&partnerID=40&md5=fcba53eea86a5fe7e7dea7ec834cee1f","Jusup Balasagyn Kyrgyz National University, Department of Economics, Bishkek, 720033, Kyrgyzstan; Department of Theoretical Problems of the Developing Economy, Institute of Economics of the National Academy of Sciences of the Kyrgyz Republic, 265a, Chui prospect, Bishkek, 720010, Kyrgyzstan","Du W., Jusup Balasagyn Kyrgyz National University, Department of Economics, Bishkek, 720033, Kyrgyzstan; Dzamankulov B., Department of Theoretical Problems of the Developing Economy, Institute of Economics of the National Academy of Sciences of the Kyrgyz Republic, 265a, Chui prospect, Bishkek, 720010, Kyrgyzstan","The proliferation of technology, advancements in logistics, and widespread availability of internet connectivity in recent times have significantly contributed to the heightened allure and expansion of cross-border electronic commerce. The utilisation of global connectivity enables companies to reach a diverse range of consumers worldwide, thereby expanding their customer base beyond their domestic market. In addition to domestic suppliers, customers can procure a broader assortment of goods and services from international vendors, often at reduced prices. The objective of this study is to analyse the significance and function of global e-commerce in facilitating China's import and export operations. This study examines the impact of market share on the expansion of cross-border e-commerce, considering the influence of the legislative framework and competitive advantage. Additionally, this study investigates the mediating and regulating roles of consumer behaviour and economic effects in the relationship. This study employs a rigorous methodology, including a comprehensive literature review and the utilisation of quantitative research methods. The data analysed in this study is derived from a sample of 300 employees working in cross-border trade companies in China. The data is analysed using structural equation modelling (SEM). This study is grounded in the utilisation of convenience sampling, which is a non-probability sampling technique. The research findings contribute to the existing scholarly literature by providing a comprehensive understanding of the significance, operational mechanisms, and dynamics of cross-border e-commerce within China's import and export sectors. The findings of this study offer valuable insights on various strategies that can be employed to enhance market share, effectively navigate regulatory frameworks, capitalise on competitive advantages, and effectively utilise consumer behaviour and economic impact in the context of cross-border e-commerce. These findings hold practical implications for businesses, policymakers, and practitioners involved in the field of international trade. © (2023), (Social Sciences Research Society). All Rights Reserved.","Competitive advantage; Consumer behaviour; Cross border e-commerce sales; Economic impact; Market share; Regulatory environment",{"$nulls":7},"Ab Hamid M., Sami W., Sidek M. M., Discriminant validity assessment: Use of Fornell & Larcker criterion versus HTMT criterion, Journal of Physics: Conference Series, (2017); Algarni M. A., Ali M., Leal-Rodriguez A. L., Albort-Morant G., The differential effects of potential and realized absorptive capacity on imitation and innovation strategies, and its impact on sustained competitive advantage, Journal of Business Research, 158, (2023); Anderson E. W., Fornell C., Lehmann D. 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["Pu W.; Jin J.; Yan X.","Pu, Wei (57190976835); Jin, Jiahua (56103848600); Yan, Xiangbin (7403596630)","57190976835; 56103848600; 7403596630","A Data-Driven Bilevel Optimization Problem Considering Product Popularity for the E-Commerce Presale Mode",2023.0,"International Journal of Fuzzy Systems",25.0,5.0,null,1952.0,1974.0,22.0,0.0,"10.1007/s40815-023-01483-4","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85148594653&doi=10.1007%2fs40815-023-01483-4&partnerID=40&md5=5e4996c73032a5df8c0b55af5d3f19bd","School of Economics and Management, University of Science and Technology Beijing, Beijing, 100083, China","Pu W., School of Economics and Management, University of Science and Technology Beijing, Beijing, 100083, China; Jin J., School of Economics and Management, University of Science and Technology Beijing, Beijing, 100083, China; Yan X., School of Economics and Management, University of Science and Technology Beijing, Beijing, 100083, China","To obtain a competitive advantage in the e-commerce presale mode, an e-tailer needs to design new products favored by consumers and consider the demand matching and supply chain services to achieve better operational results. This paper develops a data-driven optimization model based on consumer analytics and bilevel multiobjective programming to provide practical solutions for the e-commerce presale mode. At the upper level, the e-tailer, as the leader, identifies consumer preferences by quantifying product popularity through consumer analytics. Then, the e-tailer optimizes the product popularity to select the products suitable for presale and formulates the production plan. At the lower level, the logistics enterprise, as the follower, formulates the distribution plan based on the leader’s decision. Because consumer analytics are utilized and the model has a bilevel structure, a data-driven optimization method is proposed to conduct simulations for the proposed model. The model uses the multiple objectives binary particle swarm optimization with multiple social structures (MOBGLNPSO) and bilevel multiobjective particle swarm optimization with multiple social structures (Bi-MOGLNPSO). The results analysis and sensitivity analysis verify that the proposed model and method can improve the demand matching and operational efficiency of the e-commerce supply chain and uncover managerial implications for both the e-tailers and logistic enterprises. © 2023, The Author(s) under exclusive licence to Taiwan Fuzzy Systems Association.","Bilevel multiobjective programming; Consumer analytics; E-commerce supply chain; Multiobjective particle swarm optimization algorithm with multiple social structures; Product popularity","Competition; Computer programming; Electronic commerce; Particle swarm optimization (PSO); Product design; Production control; Sensitivity analysis; Shape optimization; Supply chains; Bilevel; Bilevel multiobjective programming; Consumer analytic; E-commerce supply chain; E-tailers; Multi-objective particle swarm optimization algorithms; Multiobjective particle swarm optimization algorithm with multiple social structure; Multiobjective programming; Product popularity; Social structure; Multiobjective optimization",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (71729001, 72025101)","The work was supported by the National Natural Science Foundation of China under Grant Nos. 72025101 and 71729001.","Wu M., Teunter R.H., Zhu S.X., Online marketing: When to offer a refund for advanced sales, Int. 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Intell., 26, 8, pp. 1832-1840, (2013); Pongchairerks P., Kachitvichyanukul V., A non-homogenous particle swarm optimization with multiple social structures, Proceedings of the International Conference on Simulation and Modeling, pp. 137-144, (2005); Lee C., Ho G., Choy K., Pang G., A rfid-based recursive process mining system for quality assurance in the garment industry, Int. J. Prod. Res., 52, 14, pp. 4216-4238, (2014); Viet N.Q., Behdani B., Bloemhof J., Data-driven process redesign: anticipatory shipping in agro-food supply chains, Int. J. Prod. Res., 58, 5, pp. 1302-1318, (2020); Qi Y., Ma X., Liu F., Jiao L., Sun J., Wu J., Moea/d with adaptive weight adjustment, Evol. Comput., 22, 2, pp. 231-264, (2014); Deb K., Jain H., An evolutionary many-objective optimization algorithm using reference-point-based nondominated sorting approach, part i: solving problems with box constraints, IEEE Trans. Evol. Comput., 18, 4, pp. 577-601, (2013)","J. Jin; School of Economics and Management, University of Science and Technology Beijing, Beijing, 100083, China; email: jinjiahua@ustb.edu.cn",null,"Springer Science and Business Media Deutschland GmbH",{"$nulls":5},1.5622479E7,null,null,null,"English","Int. J. Fuzzy Syst.","Article","Final",null,"Scopus","2-s2.0-85148594653"]
["Chen Y.; Zhao Q.; Wang W.; Zhang S.","Chen, Yunkai (57942569600); Zhao, Quanwu (25958587800); Wang, Wei (56948575600); Zhang, Shu (57194408160)","57942569600; 25958587800; 56948575600; 57194408160","Mixed multi-echelon location routing problem with differentiated intermediate depots",2023.0,"Computers and Industrial Engineering",177.0,null,109026.0,null,null,null,0.0,"10.1016/j.cie.2023.109026","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85147254047&doi=10.1016%2fj.cie.2023.109026&partnerID=40&md5=f5e114b47be48d67a1e9684fd64c8f3b","School of Economics and Business Administration, Chongqing University, 400030, China; College of Mechanical Engineering, Chongqing University, 400030, China; Department of Logistics and Maritime Studies, The Hong Kong Polytechnic University, 999077, Hong Kong; Chongqing Key Laboratory of Logistics, Chongqing University, Chongqing, China","Chen Y., School of Economics and Business Administration, Chongqing University, 400030, China, College of Mechanical Engineering, Chongqing University, 400030, China, Chongqing Key Laboratory of Logistics, Chongqing University, Chongqing, China; Zhao Q., School of Economics and Business Administration, Chongqing University, 400030, China, Chongqing Key Laboratory of Logistics, Chongqing University, Chongqing, China; Wang W., Department of Logistics and Maritime Studies, The Hong Kong Polytechnic University, 999077, Hong Kong, Chongqing Key Laboratory of Logistics, Chongqing University, Chongqing, China; Zhang S., School of Economics and Business Administration, Chongqing University, 400030, China, Chongqing Key Laboratory of Logistics, Chongqing University, Chongqing, China","With the increasing of E-commerce parcels in China in recent years, the logistics networks of many express companies are more and more unreasonable. Considering the distribution of parcels is regionally related, we describe a mixed multi-echelon (MME) urban logistics network to handle the regionally distributed parcels. The MME network contains limited urban distribution centers (UDCs), many differentiated intermediate depots (IDs), and a large number of terminals. This research constructs a mixed integer linear programming (MILP) to solve the mixed multi-echelon location routing problem (MME-LRP) where the location and the type of IDs are determined. A hybrid heuristic algorithm based on iterated local search and intensified by path relinking (HH-ILS-PR) is proposed to tackle the problem. The quality of our algorithm and the practicability of the MME network are verified by three sets of instances: two of them are adapted from benchmark instances of 2E-LRP and one is developed from real-world data. In the real-world instance, MME urban logistics network reduces the cost by 11.08% compared with two-echelon urban logistics network. We also present several managerial implications to express companies. © 2023 Elsevier Ltd","Differentiated intermediate depots; Iterated local search; Location routing problem; Mixed multi-echelon; Path relinking","Benchmarking; Heuristic algorithms; Integer programming; Local search (optimization); Network security; Differentiated intermediate depot; Iterated local search; Location routing problem; Logistics network; Mixed multi-echela; Multiechelon; Path relinking; Real-world; Urban distribution centers; Urban logistics; Location",{"$nulls":4},"Humanities and Social Sciences Foundation; Technological Innovation and Application Program of Chongqing, (cstc2019jscx-mbdxX0008); Ministry of Education of the People's Republic of China, MOE, (19YJA630122); Fundamental Research Funds for Central Universities of the Central South University, (2019 CDJSK 02 XK 12, 2019CDCGJG331)","This research was supported by the Humanities and Social Sciences Foundation Program of the Ministry of Education (Project No. 19YJA630122 ) , the Fundamental Research Funds for the Central Universities of Chongqing University (Project No. 2019 CDJSK 02 XK 12, 2019CDCGJG331) , and the Technological Innovation and Application Program of Chongqing (Project No. cstc2019jscx-mbdxX0008) .","Baldacci R., Mingozzi A., Calvo R.W., An exact method for the capacitated location-routing problem, Operations Research, 59, 5, pp. 1284-1296, (2011); Beasley J., Route first—Cluster second methods for vehicle routing, Omega, 11, 4, pp. 403-408, (1983); Boccia M., Crainic T.G., Sforza A., Sterle C., (2010); Clarke G., Wright J.W., Scheduling of vehicles from a central depot to a number of delivery points, Operations Research, 12, 4, pp. 568-581, (1964); Contardo C., Cordeau J.F., Gendron B., A computational comparison of flow formulations for the capacitated location-routing problem, Discrete Optimization, 10, 4, pp. 263-295, (2013); Contardo C., Cordeau J.F., Gendron B., A GRASP + ILP-based metaheuristic for the capacitated location-routing problem. In, Journal of Heuristics, 20, 1, (2014); Contardo C., Hemmelmayr V., Crainic T.G., Lower and upper bounds for the two-echelon capacitated location-routing problem, Computers and Operations Research, 39, 12, pp. 3185-3199, (2012); Dai Z., Aqlan F., Gao K., Zhou Y., A two-phase method for multi-echelon location-routing problems in supply chains, Expert Systems with Applications, 115, pp. 618-634, (2019); Dalfard V.M., Kaveh M., Nosratian N.E., Two meta-heuristic algorithms for two-echelon location-routing problem with vehicle fleet capacity and maximum route length constraints, Neural Computing and Applications, 23, 7-8, pp. 2341-2349, (2013); Darvish M., Archetti C., Coelho L.C., Speranza M.G., Flexible two-echelon location routing problem, European Journal of Operational Research, 277, 3, pp. 1124-1136, (2019); Escobar J.W., Linfati R., Baldoquin M.G., Toth P., A granular variable tabu neighborhood search for the capacitated location-routing problem, Transportation Research Part B: Methodological, 67, pp. 344-356, (2014); Fan H., Wu J., Li X., Jiang X., (2020); Jacobsen S.K., Madsen O.B.G., A comparative study of heuristics for a two-level routing-location problem, European Journal of Operational Research, 5, 6, pp. 378-387, (1980); Jin L., Zhu Y., Shen H., Ku T., Research on two-layer location-routing problem and optimization algorithm, International Journal of Advancements in Computing Technology, 2, 2, pp. 102-108, (2010); Koc C., Bektas T., Jabali O., Laporte G., The fleet size and mix location-routing problem with time windows: Formulations and a heuristic algorithm, European Journal of Operational Research, 248, 1, pp. 33-51, (2016); Li H., Li S., Two-echelon location routing problem with multi-fuzzy and pick-delivery model and algorithm, Advances in Intelligent Systems and Computing, 928, (2020); Lopes R.B., Ferreira C., Santos B.S., A simple and effective evolutionary algorithm for the capacitated location-routing problem, Computers and Operations Research, 70, pp. 155-162, (2016); Madsen O.B.G., Methods for solving combined two level location-routing problems of realistic dimensions, European Journal of Operational Research, 12, 3, pp. 295-301, (1983); Mirhedayatian S.M., Crainic T.G., Guajardo M., Wallace S.W., A two-echelon location-routing problem with synchronisation, Journal of the Operational Research Society, 72, 1, pp. 145-160, (2021); Nguyen V.P., Prins C., Prodhon C., A multi-start iterated local search with tabu list and path relinking for the two-echelon location-routing problem, Engineering Applications of Artificial Intelligence, 25, 1, pp. 56-71, (2012); Nguyen V.P., Prins C., Prodhon C., Solving the two-echelon location routing problem by a GRASP reinforced by a learning process and path relinking, European Journal of Operational Research, 216, 1, pp. 113-126, (2012); Pichka K., Bajgiran A.H., Petering M.E.H., Jang J., Yue X., The two echelon open location routing problem: Mathematical model and hybrid heuristic, Computers and Industrial Engineering, 121, May, pp. 97-112, (2018); Pirkwieser S., Raidl G.R., (2010); Prins C., A simple and effective evolutionary algorithm for the vehicle routing problem, Computers and Operations Research, 31, 12, pp. 1985-2002, (2004); Prins C., Prodhon C., Calvo R.W.; Prins C., Prodhon C., Calvo R.W., Solving the capacitated location-routing problem by a GRASP complemented by a learning process and a path relinking, 4or, 4, 3, pp. 47-64, (2006); Prins C., Prodhon C., Ruiz A., Soriano P., Calvo R.W., Solving the capacitated location-routing problem by a cooperative Lagrangean relaxation-granular tabu search heuristic, Transportation Science, 41, 4, pp. 470-483, (2007); Rahmani Y., Ramdane Cherif-Khettaf W., Oulamara A., The two-echelon multi-products location-routing problem with pickup and delivery: Formulation and heuristic approaches, International Journal of Production Research, 54, 4, pp. 999-1019, (2016); Savelsbergh M., Van Woensel T., City logistics: Challenges and opportunities, Transportation Science, 50, 2, pp. 579-590, (2016); Schwengerer M., Pirkwieser S., Raidl G.R., (2012); von Boventer E., The relationship between transportation costs and location rent in transportation problems, Journal of Regional Science, 3, 2, pp. 27-40, (1961); Wang Y., Assogba K., Liu Y., Ma X., Xu M., Wang Y., Two-echelon location-routing optimization with time windows based on customer clustering, Expert Systems with Applications, 104, pp. 244-260, (2018); Winkenbach M., Kleindorfer P.R., Spinler S., Enabling urban logistics services at la poste through multi-echelon location-routing, Transportation Science, 50, 2, pp. 520-540, (2016); Yu V.F., Lin S.W., Multi-start simulated annealing heuristic for the location routing problem with simultaneous pickup and delivery, Applied Soft Computing Journal, 24, pp. 284-290, (2014); Zhao Q., Wang W., De Souza R., A heterogeneous fleet two-echelon capacitated location-routing model for joint delivery arising in city logistics, International Journal of Production Research, 56, 15, pp. 5062-5080, (2018)","Q. Zhao; School of Economics and Business Administration, Chongqing University, 400030, China; email: zhaoquanwumx@cqu.edu.cn",null,"Elsevier Ltd",{"$nulls":5},3608352.0,null,"CINDD",null,"English","Comput Ind Eng","Article","Final",null,"Scopus","2-s2.0-85147254047"]
["Abualola H.; Mizouni R.; Otrok H.; Singh S.; Barada H.","Abualola, Huda (57189460442); Mizouni, Rabeb (8572417600); Otrok, Hadi (20436645500); Singh, Shakti (57191471628); Barada, Hassan (6603345338)","57189460442; 8572417600; 20436645500; 57191471628; 6603345338","A matching game-based crowdsourcing framework for last-mile delivery: Ground-vehicles and Unmanned-Aerial Vehicles",2023.0,"Journal of Network and Computer Applications",213.0,null,103601.0,null,null,null,5.0,"10.1016/j.jnca.2023.103601","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85148324336&doi=10.1016%2fj.jnca.2023.103601&partnerID=40&md5=db91271789ac5161740b8a8bda19eefa","Electrical Engineering and Computer Science Department, Khalifa University, Abu Dhabi, United Arab Emirates","Abualola H., Electrical Engineering and Computer Science Department, Khalifa University, Abu Dhabi, United Arab Emirates; Mizouni R., Electrical Engineering and Computer Science Department, Khalifa University, Abu Dhabi, United Arab Emirates; Otrok H., Electrical Engineering and Computer Science Department, Khalifa University, Abu Dhabi, United Arab Emirates; Singh S., Electrical Engineering and Computer Science Department, Khalifa University, Abu Dhabi, United Arab Emirates; Barada H., Electrical Engineering and Computer Science Department, Khalifa University, Abu Dhabi, United Arab Emirates","This paper tackles the problem of allocating time-constrained last-mile delivery tasks to crowdsourced vehicles and Unmanned Aerial Vehicles (UAVs). With the increasing development of E-commerce, the demand for home deliveries is rapidly increasing. However, last-mile delivery remains the costliest part endured by shipping companies, particularly for time-critical deliveries. To mitigate this high cost, recently, several researchers and companies, such as Amazon and Mercedes-Benz, have adopted (1) crowdsourced and (2) UAVs-based delivery solutions. Nevertheless, crowdsourcing delivery tasks, where workers with vehicles are being recruited to deliver parcels, suffers from long delivery time and delays for time-critical tasks during peak traffic hours. Although UAVs are perceived currently as a trending solution for fast and timely delivery of time-critical delivery tasks, yet they are constrained by the flying time and the package weight. These limitations have a direct impact on the cost of delivery and the task accomplishment rate. In this paper, a hybrid framework that crowd-sources vehicles’ drivers and UAVs for delivery tasks is proposed. It aims at improving the delivery time and the allocation percentage mainly at peak hours, by the proposed, (1) task filtering, (2) worker quality estimation, and (3) task allocation and scheduling. The filtering of possible tasks, that each type of worker can accomplish is done based on the availability of the workers and their ability to reach the destination. The worker quality, with regard to the delivery task, is estimated using the Bayesian belief function that is utilized in the allocation. The allocation of tasks and workers is performed using the Gale–Shapley matching game to consider the preferences of both workers and tasks. The simulation results show that the hybrid framework outperforms the non-hybrid crowdsourcing model in terms of task allocation percentage, delivery time, and payoff. © 2023 Elsevier Ltd","Bayesian belief; Crowdsourcing; E-commerce; Gale–Shapley matching; Hybrid; Last-mile delivery; Supply chain; Unmanned Aerial Vehicles","Antennas; Crowdsourcing; Electronic commerce; Ground vehicles; Uncertainty analysis; Unmanned aerial vehicles (UAV); Aerial vehicle; Bayesian; Bayesian belief; Gale–shapley matching; Hybrid; Last mile; Last-mile delivery; Matchings; Shapley; Unmanned aerial vehicle; Supply chains",{"$nulls":4},"Khalifa University of Science, (CIRA-2020-028)","This work was supported by the Khalifa University of Science and Technology-Competitive Internal Research Award, United Arab Emirates ( CIRA-2020-028 ), United Arab Emirates. ","Abououf M., Singh S., Otrok H., Mizouni R., Damiani E., Machine learning in mobile crowd sourcing: A behavior-based recruitment model, ACM Trans. Internet Technol., 22, 1, (2021); Abououf M., Singh S., Otrok H., Mizouni R., Ouali A., Gale-shapley matching game selection: A framework for user satisfaction, IEEE Access, 7, pp. 3694-3703, (2019); (2019); Anon, Amazon Flex, (2021); Anon, Amazon Prime Air, (2021); Anon, eCommerce, (2021); Anon, Vans & Drones in Zurich, (2021); Anon, The official US. Government for fuel economy information, (2022); Anon, Phantom 4 Pro, (2022); Aurambout J.-P., Gkoumas K., Ciuffo B., Last mile delivery by drones: An estimation of viable market potential and access to citizens across European cities, Eur. Transp. Res. Rev., 11, 1, (2019); Basik F., Gedik B., Ferhatosmanoglu H., Wu K.-L., Fair task allocation in crowdsourced delivery, IEEE Trans. Serv. Comput., 14, 4, pp. 1040-1053, (2021); Chang Y.S., Lee H.J., Optimal delivery routing with wider drone-delivery areas along a shorter truck-route, Expert Syst. Appl., 104, pp. 307-317, (2018); Chen P., Chankov S.M., Crowdsourced delivery for last-mile distribution: An agent-based modelling and simulation approach, 2017 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM, pp. 1271-1275, (2017); Chen C., Wang Z., Zhang D., Sending more with less: Crowdsourcing integrated transportation as a new form of citywide passenger–package delivery system, IT Prof., 22, 1, pp. 56-62, (2020); Doole M., Ellerbroek J., Hoekstra J., Estimation of traffic density from drone-based delivery in very low level urban airspace, J. Air Transp. Manag., 88, (2020); Dorling K., Heinrichs J., Messier G.G., Magierowski S., Vehicle routing problems for drone delivery, IEEE Trans. Syst. 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Appl., 191, (2021); Kafle N., Zou B., Lin J., Design and modeling of a crowdsource-enabled system for urban parcel relay and delivery, Transp. Res. B, 99, pp. 62-82, (2017); Martin J., Jurgen S., Florian N., Christoph K., Florian M., Parcel delivery the future of last mile, Travel Transport, and Logistics, (2016); Shushman C., Kiril S., Mykel K., Marco J.P., Efficient large-scale multi-drone delivery using transit networks, J. Artificial Intelligence Res., 70, pp. 757-788, (2021); Torabbeigi M., Lim G., Kim S., Drone delivery scheduling optimization considering payload-induced battery consumption rates, J. Intell. Robot. Syst., 97, pp. 471-487, (2020); Tri Windras Mara S., Pratama Rifai A., Maya Sopha B., An adaptive large neighborhood search heuristic for the flying sidekick traveling salesman problem with multiple drops, Expert Syst. Appl., (2022); Wang F., Wang F., Ma X., Liu J., Demystifying the crowd intelligence in last mile parcel delivery for smart cities, IEEE Netw., 33, 2, pp. 23-29, (2019); Wang F., Zhu Y., Wang F., Liu J., Ma X., Fan X., Car4pac: Last mile parcel delivery through intelligent car trip sharing, IEEE Trans. Intell. Transp. Syst., 21, 10, pp. 4410-4424, (2020)","H. Otrok; Electrical Engineering and Computer Science Department, Khalifa University, Abu Dhabi, United Arab Emirates; email: hadi.otrok@ku.ac.ae",null,"Academic Press",{"$nulls":5},1.0848045E7,null,null,null,"English","J Network Comput Appl","Article","Final",null,"Scopus","2-s2.0-85148324336"]
["Deshpande V.; Pendem P.K.","Deshpande, Vinayak (7103112805); Pendem, Pradeep K. (57226091454)","7103112805; 57226091454","Logistics Performance, Ratings, and Its Impact on Customer Purchasing Behavior and Sales in E-Commerce Platforms",2023.0,"Manufacturing and Service Operations Management",25.0,3.0,null,827.0,845.0,18.0,12.0,"10.1287/msom.2021.1045","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85161622981&doi=10.1287%2fmsom.2021.1045&partnerID=40&md5=c47f06deee8560f7cc66ed5c33ee4c63","Kenan-Flagler Business School, University of North Carolina, Chapel Hill, 27599, NC, United States; Charles H. Lundquist College of Business, University of Oregon, Eugene, 97403, OR, United States","Deshpande V., Kenan-Flagler Business School, University of North Carolina, Chapel Hill, 27599, NC, United States; Pendem P.K., Charles H. Lundquist College of Business, University of Oregon, Eugene, 97403, OR, United States","Problem definition: We examine the impact of logistics performance metrics such as delivery time and customer’s requested delivery speed on logistics service ratings and third-party sellers’ sales on an e-commerce platform. Academic/practical relevance: Although e-commerce retailers like Amazon have recently invested heavily in their logistics networks to provide faster delivery to customers, there is scant academic literature that tests and quantifies the premise that convenient and fast delivery will drive sales. In this paper, we provide empirical evidence on whether this relationship holds in practice by analyzing a mechanism that connects delivery performance to sales through logistics ratings. Prior academic work on online ratings in e-commerce platforms has mostly analyzed customers’ response to product functional performance and biases that exist within. Our study contributes to this stream of literature by examining customer experience from a service quality perspective by analyzing logistics service performance, logistics ratings, and its impact on customer purchase probability and sales. Methodology: Using an extensive data set of more than 15 million customer orders on the Tmall platform and Cainiao network (logistics arm of Alibaba), we use the Heckman ordered regression model to explain the variation in customers’ rating of logistics performance and the likelihood of customers posting a logistics rating. Next, we develop a generic customer choice model that links the customer’s likelihood of making a purchase to the logistics ratings provided by prior customers. We implement a two-step estimation of the choice model to quantify the impact of logistics ratings on customer purchase probability and third-party seller sales. Results: We surprisingly find that even customers with no promise on delivery speed are likely to post lower logistics ratings for delivery times longer than two days. Although these customers are not promised an explicit delivery deadline, they seem to have a mental threshold of two days and expect deliveries to be made within that time. Similarly, we find that priority customers (those with two-day and one-day promise speed) provide lower logistics ratings for delivery times longer than their anticipated delivery date. We estimate that reducing the delivery time of all three-day delivered orders on this platform (which makeup ≈ 35% of the total orders) to two days would improve the average daily third-party seller sales by 13.3% on this platform. The impact of delivery time performance on sales is more significant for sellers with a higher percentage of three-day delivered orders and a higher spend per order. Managerial implications: Our study emphasizes that delivery performance and logistics ratings, which measure service quality, are essential drivers of the customer purchase decision on e-commerce platforms. Furthermore, by quantifying the impact of delivery time performance on sales, our study also provides a framework for online retailers to assess if the increase in sales because of improved logistics performance can offset the increase in additional infrastructure costs required for faster deliveries. Our study’s insights are relevant to third-party sellers and e-commerce platform managers who aim to improve long-term online customer traffic and sales. © 2022 INFORMS.","big data analytics; e-commerce; integrated warehousing and logistics; logistics ratings","Big data; Data Analytics; Digital storage; Electronic commerce; Regression analysis; Big data analytic; Commerce platforms; Data analytics; Delivery speed; Delivery time; E- commerces; Integrated warehousing and logistic; Logistic performance; Logistic rating; Third parties; Sales",{"$nulls":6},"Allon G, Federgruen A, Pierson M, How much is a reduction of your customers’ wait worth? An empirical study of the fast-food drive-thru industry based on structural estimation methods, Manufacturing Service Oper. 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["Qi B.; Shen Y.; Xu T.","Qi, Bitian (58168595500); Shen, Yanbo (58167307100); Xu, Tieyu (58167523700)","58168595500; 58167307100; 58167523700","An artificial-intelligence-enabled sustainable supply chain model for B2C E-commerce business in the international trade",2023.0,"Technological Forecasting and Social Change",191.0,null,122491.0,null,null,null,6.0,"10.1016/j.techfore.2023.122491","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85151405558&doi=10.1016%2fj.techfore.2023.122491&partnerID=40&md5=7e2de8ea839ce3d83bbe901438d23707","School of Economics and Management, Yichun University, Jiangxi, Yichun, 336000, China; School of business college, Suzhou University, Anhui, 215000, China","Qi B., School of Economics and Management, Yichun University, Jiangxi, Yichun, 336000, China; Shen Y., School of business college, Suzhou University, Anhui, 215000, China; Xu T., School of business college, Suzhou University, Anhui, 215000, China","This work aims to improve the efficiency of logistics distribution in the international trade environment by optimizing the distribution path of the e-commerce supply chain model (SCM). First, this work analyzes the international trade and e-commerce backgrounds and unveils the existing problems in the sustainable supply chain model (SCM). Then, an experiment is designed to study sustainable SCM under the Business to Consumer (B2C) E-commerce business model and compare it to the Consumer to Consumer (C2C) business model. This research has important reference value for improving resource efficiency in the logistics field. The optimal experimental results of the model show that given an order quantity of 2000, the vehicle competition ratio (VCR) is only 1.1 when the vehicle capacity (VC) is 12. In contrast, when the VC is 72, the VCR is 1.45. Therefore, the greater that the load of a single vehicle in the logistics management system is, the higher the logistics distribution efficiency of the supply chain. The research content has practical application value for improving the efficiency of logistics distribution under the current e-commerce environment and promoting the digital and electronic development of international trade logistics. © 2023 Elsevier Inc.","Artificial intelligence; Business to consumer (B2C); Electronic commerce (E-commerce); International trade; Sustainable supply chain","Efficiency; Electronic commerce; International trade; Supply chains; Vehicles; B2C electronic commerce; Business models; Business to Consumer; Business to consumer (B2C); E- commerces; Electronic commerce; Logistic distributions; Supply chain modeling; Sustainable supply chains; Vehicle's capacity; artificial intelligence; electronic commerce; international trade; logistics; Artificial intelligence",{"$nulls":6},"Aladwan A.S., Alrousan M., Al-Soud A., Al-Yaseen H., Revealing the black box of shifting from electronic commerce to mobile commerce: the case of Jordan, J. Theor. Appl. Electron. Commer. 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["Grida M.; Mostafa N.A.","Grida, Mohamed (57194068292); Mostafa, Noha A. (56684734000)","57194068292; 56684734000","Are smart contracts too smart for Supply Chain 4.0? A blockchain framework to mitigate challenges",2023.0,"Journal of Manufacturing Technology Management",34.0,4.0,null,644.0,665.0,21.0,7.0,"10.1108/JMTM-09-2021-0359","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85122918899&doi=10.1108%2fJMTM-09-2021-0359&partnerID=40&md5=20618ec63887cc0b089aeeffee976eac","Industrial Engineering Department, Zagazig University, Zagazig, Egypt; Mechanical Engineering Department, The British University in Egypt, Cairo, Egypt","Grida M., Industrial Engineering Department, Zagazig University, Zagazig, Egypt; Mostafa N.A., Industrial Engineering Department, Zagazig University, Zagazig, Egypt, Mechanical Engineering Department, The British University in Egypt, Cairo, Egypt","Purpose: Smart contracts are self-executing computer programmes that have the potential to be used in several applications instead of traditional written contracts. With the recent rise of smart systems (e.g. Internet of things) and digital platforms (e.g. blockchain), smart contracts are gaining high interest in both business and academia. In this work, a framework for smart contracts was proposed with using reputation as the system currency, and conducts currency mining through fulfilling the physical commitments that are agreed upon. Design/methodology/approach: A game theory model is developed to represent the proposed system, and then a system dynamics simulator is used to check the response of the blockchain with different sizes. Findings: The numerical results showed that the proposed system could identify the takeover attacks and protect the blockchain from being controlled by an outsider. Another important finding is that careful setting of the maximum currency amount can improve the scalability of the blockchain and prevent the currency inflation. Research limitations/implications: This work is proposed as a conceptual framework for supply chain 4.0. Future work will be dedicated to implement and experiment the proposed framework for other characteristics that may be encountered in the context of supply chain 4.0, such as different suppliers' tiers, different customer typologies and smart logistics applications, which may reveal other challenges and provide additional interesting insights. Practical implications: By using the proposed framework, smart contracts and blockchains can be implemented to handle many issues in the context of operations and supply chain 4.0, especially in times of turbulence such as the COVID-19 global pandemic crisis. Originality/value: This work emphasizes that smart contracts are not too smart to be applied in the context of supply chain 4.0. The proposed framework of smart contracts is expected to serve supply chain 4.0 by automating the knowledge work and enabling scenario planning through the game theory model. It will also improve online transparency and order processing in real-time through secured multitier connectivity. This can be applied in global supply chain functions backed with digitization, notably during the time of the pandemic, in which e-commerce and online shopping have changed the rules of the game. © 2021, Emerald Publishing Limited.","Digitization; Industry 4.0; Information exchange; Modelling; Smart contracts; Supply chains","Blockchain; Game theory; Industry 4.0; Supply chains; Block-chain; Design/methodology/approach; Digital platforms; Digitisation; Dynamics simulator; Game theory models; Information exchanges; Modeling; Smart System; System Dynamics; Smart contract",{"$nulls":6},"Abd-alrazaq A.A., Alajlani M., Alhuwail D., Erbad A., Giannicchi A., Shah Z., Hamdi M., Househ M., Blockchain technologies to mitigate COVID-19 challenges: a scoping review, Computer Methods and Programs in Biomedicine Update, 1, (2021); Abeyratne S.A., Monfared R.P., Blockchain ready manufacturing supply chain using distributed ledger, International Journal of Research in Engineering and Technology, 5, 9, pp. 1-10, (2016); 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Xu L.D., Xu E.L., Li L., Industry 4.0: state of the art and future trends, International Journal of Production Research, 56, 8, pp. 2941-2962, (2018); Yao M.-J., Lin J.-Y., Lee C., Wang P.-H., Optimal replenishment and inventory financing strategy in a three-echelon supply chain under the variable demand and default risk, Journal of the Operational Research Society, 72, 10, pp. 2196-2210, (2020)","N.A. Mostafa; Industrial Engineering Department, Zagazig University, Zagazig, Egypt; email: noha.mostafa@bue.edu.eg",null,"Emerald Publishing",{"$nulls":5},"1741038X",null,null,null,"English","J. Manuf. Technol. Manage.","Article","Final",null,"Scopus","2-s2.0-85122918899"]
["Pourmohammadreza N.; Jokar M.R.A.","Pourmohammadreza, Nima (58300109700); Jokar, Mohammad Reza Akbari (14420910300)","58300109700; 14420910300","A Novel Two-Phase Approach for Optimization of the Last-Mile Delivery Problem with Service Options",2023.0,"Sustainability (Switzerland)",15.0,10.0,8098.0,null,null,null,1.0,"10.3390/su15108098","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85160942006&doi=10.3390%2fsu15108098&partnerID=40&md5=dfaa93a243ccb800e413e7ce6db8a238","Department of Industrial Engineering, Sharif University of Technology, Tehran, 1458889694, Iran","Pourmohammadreza N., Department of Industrial Engineering, Sharif University of Technology, Tehran, 1458889694, Iran; Jokar M.R.A., Department of Industrial Engineering, Sharif University of Technology, Tehran, 1458889694, Iran","As the growth of e-commerce continues to accelerate, there is a need for new and innovative strategies in last-mile delivery to meet the changing demands of customers. The main objective of this study is to address this need by optimizing the last-mile delivery problem with service options (LMDPSOs) through a novel two-phase approach that considers various delivery options such as home delivery, self-pickup, and delivery at different prices. This original approach enables simultaneous optimization of the selection of the most appropriate pickup and delivery points and determination of the most efficient vehicle routing. The LMDPSOs reduces overall costs, minimizes environmental impact, and considers customer satisfaction levels by determining the most appropriate trips according to the available service options. This research employs a two-phase methodology for decision making. The first phase determines the value of the proposed locations through a novel multi-criteria decision-making (MCDM) approach that incorporates sustainability criteria. In the second phase, a tailored mathematical model is proposed for vehicle routing with service options. The model is coded in the CPLEXsoftware version 12.6 in various dimensions. We evaluate the potential and advantages of diverse delivery choices, illustrating that aggregating orders at pickup and delivery points can reduce delivery costs and minimize environmental impact. Additionally, this paper directs managers in selecting the most appropriate delivery method for last-mile delivery, considering environmental, social, and economic factors. © 2023 by the authors.","multi-criteria decision making; pickup and delivery points; service options; sustainability; sustainable last-mile delivery problem; two-phase methodology; vehicle routing problem","decision making; electronic commerce; optimization; planning method; service sector; sustainability; transport process; two phase flow",{"$nulls":6},"Gross W.F., Hayden C., Butz C., About the impact of rising oil price on logistics networks and transportation greenhouse gas emission, Logist. 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Shipp. Logist, 38, pp. 25-30, (2022); Liu S., Liu Y., Zhang R., Cao Y., Li M., Zikirya B., Zhou C., Heterogeneity of Spatial Distribution and Factors Influencing Unattended Locker Points in Guangzhou, China: The Case of Hive Box, ISPRS Int. J. Geoinf, 10, (2021); Rabe M., Gonzalez-Feliu J., Chicaiza-Vaca J., Tordecilla R.D., Simulation-optimization approach for multi-period facility location problems with forecasted and random demands in a last-mile logistics application, Algorithms, 14, (2021); Ducret R., Parcel deliveries and urban logistics: Changes and challenges in the courier express and parcel sector in Europe—The French case, Res. Transp. Bus. Manag, 11, pp. 15-22, (2014); Wang Y., Ong T., Lee L.H., Chew E.P., Capacitated competitive facility location problem of self-collection lockers by using public big data, Proceedings of the 2017 13th IEEE Conference on Automation Science and Engineering (CASE); Lee H., Chen M., Pham H.T., Choo S., Development of a decision making system for installing unmanned parcel lockers: Focusing on residential complexes in Korea, KSCE J. Civ. Eng, 23, pp. 2713-2722, (2019); Buzzega G., Novellani S., Last mile deliveries with lockers: Formulations and algorithms, Soft Comput, pp. 1-19, (2022); Dumez D., Lehuede F., Peton O., A large neighborhood search approach to the vehicle routing problem with delivery options, Transp. Res. Part B Methodol, 144, pp. 103-132, (2021); Enthoven D.L.J.U., Jargalsaikhan B., Roodbergen K.J., Uit het Broek M.A.J., Schrotenboer A.H., The two-echelon vehicle routing problem with covering options: City logistics with cargo bikes and parcel lockers, Comput. Oper. Res, 118, (2020); Friedrich C., Elbert R., Adaptive large neighborhood search for vehicle routing problems with transshipment facilities arising in city logistics, Comput. Oper. Res, 137, (2022); He Y., Wang X., Zhou F., Lin Y., Dynamic vehicle routing problem considering simultaneous dual services in the last mile delivery, Kybernetes, 49, pp. 1267-1284, (2019); Janinhoff L., Klein R., Scholz D., Multitrip Vehicle Routing with Delivery Options: A Data-Driven Application to the Parcel Industry, OR Spectr, pp. 1-54, (2023); Los J., Spaan M.T.J., Negenborn R.R., Fleet management for pickup and delivery problems with multiple locations and preferences, International Conference on Dynamics in Logistics, pp. 86-94, (2018); Sampaio A., Kinable J., Veelenturf L.P., Van Woensel T., A scenario-based approach for the vehicle routing problem with roaming delivery locations under stochastic travel times, Optim. Online, pp. 1-29, (2019); Tilk C., Olkis K., Irnich S., The last-mile vehicle routing problem with delivery options, OR Spectr, 43, pp. 877-904, (2021); Zhou L., Wang X., Ni L., Lin Y., Location-routing problem with simultaneous home delivery and customer’s pickup for city distribution of online shopping purchases, Sustainability, 8, (2016); Zhou L., Baldacci R., Vigo D., Wang X., A multi-depot two-echelon vehicle routing problem with delivery options arising in the last mile distribution, Eur. J. Oper. Res, 265, pp. 765-778, (2018); Selmic M., Nikolic M., Cupic A., Postboxes quantitative optimization model, Sustainability, 12, (2020); Mostarac K., Mostarac P., Kavran Z., Sarac D., Determining Optimal Locations of Postal Access Points Based on Simulated Annealing, Sustainability, 14, (2022); Zenezini G., Lagorio A., Pinto R., De Marco A., Golini R., The collection-and-delivery points implementation process from the courier, express and parcel operator’s perspective, IFAC-Pap, 51, pp. 594-599, (2018); Lemke J., Iwan S., Korczak J., Usability of the parcel lockers from the customer perspective–the research in Polish Cities, Transp. Res. Procedia, 16, pp. 272-287, (2016); Tang Y.M., Chau K.Y., Xu D., Liu X., Consumer perceptions to support IoT based smart parcel locker logistics in China, J. Retail. Consum. Serv, 62, (2021); Stasys R., Svaze D., Klimas E., The main reasons for customer satisfaction with parcel locker services: The case of Lithuania, Reg. Form. Dev. Stud. J. Soc. Sci, 37, pp. 175-187, (2022); Tedjo A.T., Tee P.K., Ahmad R., A Study on the Factors Boosting Customer Experience in the Adoption of Smart Locker in Klang Valley, Int. J. Acad. Res. Bus. Soc. Sci, 12, pp. 430-443, (2022); Yu B., Du G., Research on fuzzy evaluation of online shopping express service quality based on SERVQUAL model, Ind. Eng, 2, pp. 127-133, (2013); Iwan S., Kijewska K., Lemke J., Analysis of parcel lockers’ efficiency as the last mile delivery solution–the results of the research in Poland, Transp. Res. Procedia, 12, pp. 644-655, (2016); Faugere L., Montreuil B., Hyperconnected pickup & delivery locker networks, Proceedings of the 4th International Physical Internet Conference, pp. 1-14; Lin Y., Chen A., Zhong S., Giannikas V., Lomas C., Worth T., Service supply chain resilience: A social-ecological perspective on last-mile delivery operations, Int. J. Oper. Prod. Manag, 43, pp. 140-165, (2023); Pahwa A., Jaller M., Assessing last-mile distribution resilience under demand disruptions, Transp. Res. E Logist. Transp. Rev, 172, (2023); Giret A., Carrascosa C., Julian V., Rebollo M., Botti V., A crowdsourcing approach for sustainable last mile delivery, Sustainability, 10, (2018); Le D.N., Nguyen H.T., Truong P.H., Port logistics service quality and customer satisfaction: Empirical evidence from Vietnam, Asian J. Shipp. Logist, 36, pp. 89-103, (2020); Lagorio A., Pinto R., The parcel locker location issues: An overview of factors affecting their location, Proceedings of the 8th International Conference on Information Systems, Logistics and Supply Chain: Interconnected Supply Chains in an Era of Innovation, ILS, pp. 414-421; Zolfani S.H., Bahrami M., Investment prioritizing in high tech industries based on SWARA-COPRAS approach, Technol. Econ. Dev. Econ, 20, pp. 534-553, (2014); Salehi F., Mirzapour Al-e-hashem S.M.J., Husseini S.M.M., A 2-phase interdependent methodology for sustainable project portfolio planning in the pharmaceutical industry, Comput. Ind. Eng, 174, (2022); Majeed R.A., Breesam H.K., Application of SWARA technique to find criteria weights for selecting landfill site in Baghdad governorate, IOP Conference Series: Materials Science and Engineering, (2021); Yazdani M., Zarate P., Kazimieras Zavadskas E., Turskis Z., A combined compromise solution (CoCoSo) method for multi-criteria decision-making problems, Manag. Decis, 57, pp. 2501-2519, (2019); Hasanpour Jesri Z.S., Eshghi K., Rafiee M., Van Woensel T., The Multi-Depot Traveling Purchaser Problem with Shared Resources, Sustainability, 14, (2022); Reinhelt G., {TSPLIB}: A Library of Sample Instances for the TSP (and Related Problems) from Various Sources and of Various Types, (2014); Ataei Y., Mahmoudi A., Feylizadeh M.R., Li D.-F., Ordinal priority approach (OPA) in multiple attribute decision-making, Appl. Soft Comput, 86, (2020); Keshavarz Ghorabaee M., Zavadskas E.K., Olfat L., Turskis Z., Multi-criteria inventory classification using a new method of evaluation based on distance from average solution (EDAS), Informatica, 26, pp. 435-451, (2015)","M.R.A. Jokar; Department of Industrial Engineering, Sharif University of Technology, Tehran, 1458889694, Iran; email: reza.akbari@sharif.edu",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85160942006"]
["Tampubolon J.","Tampubolon, Jongkers (16067416900)",1.60674169E10,"FOOD AND AGRICULTURAL SECTOR IN INDONESIA’S ECONOMIC GROWTH DURING COVID-19 PANDEMIC: AN ARDL APPROACH",2023.0,"Agricultural and Resource Economics",9.0,2.0,null,223.0,244.0,21.0,0.0,"10.51599/are.2023.09.02.10","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85165626990&doi=10.51599%2fare.2023.09.02.10&partnerID=40&md5=83bf838d52e478541bbb9e43500df2d7","University of HKBP Nommensen, Indonesia","Tampubolon J., University of HKBP Nommensen, Indonesia","Purpose. Global-scale financial crises, either in the financial sector itself or in other fields such as zoonotic disasters, in the form of the spread of viruses resulting in deaths and significant economic contraction, are becoming more frequent and are expected to occur in the future. This study aims to assess the crisis’s impacts, in this case, COVID-19 pandemic, on the food and agriculture sector’s role in Indonesia’s economic growth. Methodology / approach. This study used ARDL bound test to cointegration approach to analyze whether COVID-19 pandemic had a negative impact on Indonesia’s economic growth with regard to the food and agricultural sector. The relation pattern of particular interests includes (i) the relation between agriculture and economic growth, (ii) the relation between food and beverage industry and economic growth, and (iii) the causal relation between agriculture, food and beverage industry, and economic growth. Results. In the long run, economic growth, agricultural output, and food and beverage industry’s output have a dynamic causal relation (bi-directional causality). Partially, COVID-19 pandemic influences economic growth negatively but insignificantly. However, the effect is simultaneously significant, but the regression coefficient is very small, and not strong enough to disrupt the positive effect of agricultural output and food and beverage industry’s output. COVID-19 does not negatively influence agricultural production and food and beverage industry as the regression coefficients are positive, insignificant, and very small. Originality / scientific novelty. This research is the first (particularly in Indonesia) to analyze COVID-19’s impacts on economic growth with regard to food and agriculture sector using an econometric operation with time series statistical data, covering data during the pandemic. Therefore, the parameter test results have higher predictability. Practical value / implication. This study presents evidence that COVID-19 pandemic influences economic growth not through disruption of production in the agriculture and food and beverage sectors, but induction by demand. Therefore, the most appropriate policy to deal with the crisis is to simultaneously handle health aspect as the source of crisis and maintain demand for agricultural and food products directly through fiscal stimulus in the form of social safety net for poor and near-poor households and indirectly through supporting micro, small and medium enterprises (MSMEs) from bankruptcy in the prevention of mass unemployment. In the future, however, there will be a need to further study agricultural resilience by subsector and investigate food and beverage industry’s role in an open economic model. In addition, it is quite advisable to further study the impacts of the government’s safety net program in the form of basic food assistance and delivery cost subsidy for online shopping to stimulate demand-driven growth that can support farmers in production and service demand through contactless marketing. © 2023, Institute of Eastern European Research and Consulting. All rights reserved.","COVID-19 pandemic and agriculture; economic growth; financial crisis; food and agricultural sector; Indonesia’s economy",{"$nulls":7},"Baldwin R., Globalization: the great unbundling(s), Economic Council of Finland, (2006); Baldwin R., Lopez-Gonzalez J., Supply-chain trade: a portrait of global patterns and several testable hypotheses, The World Economy, 38, 11, pp. 1682-1721, (2015); ASEAN 4.0. What does the Fourth Industrial Revolution mean for regional economic integration?, (2017); Busega I., The impact of the financial crisis under the effect of increasing global economic interdependence. The case of Eastern and Central Europe Economies, The Romanian Economic Journal, 18, 51, pp. 97-116, (2015); Marin A. J. T., Learning lessons from the economic crisis in self-employment, Contemporary Economic, 14, 1, pp. 3-21, (2019); ASEAN+3 regional economic outlook 2021: global value chains in the post-pandemic “New Normal”, (2021); Jiang D., Wang X., Zhao R., Analysis on the economic recovery in the post-Covid-19 era: evidence from China, Frontier Public Health, 9, (2022); Detrix J., The next financial crisis is probably around the corner – we just don’t know from where, (2017); Bloom E., de Wit V., Jose M. J. C-S., Potential Economic Impact of an Avian Flu Pandemic on Asia, (2005); Barro R. J., Ursula J. F., Weng J., Macroeconomics of the great influenza pandemic, 1918–1920, Research in Economics, 76, 1, pp. 21-29, (2022); Osterhaus A., Emerging virus infections in a changing world: combating nature, the most dangerous bio-terrorist in UN/ISDR, Know Risk, pp. 150-151, (2005); Nayak J., Mishra M., Naik B., Swapnarekha H., Cengiz K., Shanmuganathan V., An impact study of COVID-19 on six different industries: automobile, energy and power, agriculture, education, travel and tourism and consumer electronics, Expert Systems, 39, 3, (2020); Coccia M., Factors determining the diffusion of covid-19 and suggested strategy to prevent future accelerated viral infectivity similar to COVID, Science of the Total Environment, 729, (2020); Baudron F., Liegeois F., Fixing our global agricultural system to prevent the next COVID-19, Outlook on Agriculture, 49, 2, pp. 111-118, (2020); Hamid S., Mir M. Y., Global Asia-food sector: challenges and opportunity in Covid-19 pandemic, Frontier Sociology, 6, (2021); Maren I. E., Wijk H., McNeal K., Wang S., Zu S., Cao R., Furst K., Marsh R., Diversified farming systems: impact and adaptive responses to the covid-19 pandemic in the United States, Norway and China, Frontier Sustainable Food System, 6, (2022); COVID-19 pandemic implications on agriculture and food consumption, production and trade in the ASEAN Member States, (2021); Global Economic Prospects, (2020); Fan S., Teng P., Chew P., Smith G., Copeland L., Food system resilience and COVID-19 – lesson from the Asian Experience, Global Food Security, 28, (2021); Heo K., Hong S. H., Han J-S., Long G. T., Gonzales M. M. D., Tabe T., Yeah K. 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M., Gupta N., Plage J., Awasthi A., Veluguri D., Rastogi S., Dall'Agnese E., Jain A., Correction: impact of the COVID-19 pandemic on agriculture in India: cross-sectional results from a nationally representative survey, PLOS Sustain Transform, 1, 10, (2022); Durant J. L., Asprooth L., Galt R. E., Schmulevich S. P., Manser G. M., Pinzon N., Farm resilience during the COVID-19 pandemic: the case of California Direct Market Farmers, Agricultural Systems, 204, (2023); Boyaci-Gunduz C. P., Ibrahim S. A., Wei O. C., Galanakis C. M., Transformation of the food sector: security and resilience during the COVID-19 Pandemic, Food, 10, 3, (2021); Okolie C. C., Ogundeji A., Effect of COVID-19 on agricultural production and food security: a scientometric analysis, Humanities and Social Science Communications, 9, (2022); Agriculture and Food Sectors and the Economy, (2023); Bashir A., Suhel Azwardi, Adiyatma D. 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["Maji S.; Maity S.; Giri D.; Castillo O.; Maiti M.","Maji, Somnath (58020395900); Maity, Samir (56564875000); Giri, Debasis (23396481600); Castillo, Oscar (7007101709); Maiti, Manoranjan (7005401629)","58020395900; 56564875000; 23396481600; 7007101709; 7005401629","A multi-path delivery system with random refusal against online booking using Type-2 fuzzy logic-based fireworks algorithm",2023.0,"Decision Analytics Journal",6.0,null,100151.0,null,null,null,3.0,"10.1016/j.dajour.2022.100151","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85144294327&doi=10.1016%2fj.dajour.2022.100151&partnerID=40&md5=f30f909de48be02d55cad7df2d7e1054","Department of Computer Science and Engineering, Maulana Abul Kalam Azad University of Technology, NH-12, Haringhata, West Bengal, Nadia, 741249, India; Department of Information Science, Maulana Abul Kalam Azad University of Technology, NH-12, Haringhata, West Bengal, Nadia, 741249, India; Department of Information Technology, Maulana Abul Kalam Azad University of Technology, NH-12, Haringhata, West Bengal, Nadia, 741249, India; Department of Computer Science, Tijuana Institute of Technology, Av Castillo de Chapultepec 562, Tomas Aquino, B.C., Tijuana, 22414, Mexico; Department of Applied Mathematics, Vidyasagar University, Medinipur, 721102, India","Maji S., Department of Computer Science and Engineering, Maulana Abul Kalam Azad University of Technology, NH-12, Haringhata, West Bengal, Nadia, 741249, India; Maity S., Department of Information Science, Maulana Abul Kalam Azad University of Technology, NH-12, Haringhata, West Bengal, Nadia, 741249, India; Giri D., Department of Information Technology, Maulana Abul Kalam Azad University of Technology, NH-12, Haringhata, West Bengal, Nadia, 741249, India; Castillo O., Department of Computer Science, Tijuana Institute of Technology, Av Castillo de Chapultepec 562, Tomas Aquino, B.C., Tijuana, 22414, Mexico; Maiti M., Department of Applied Mathematics, Vidyasagar University, Medinipur, 721102, India","With the development of the internet and the availability of smart phones, online shopping and the number of digital buyers have increased enormously under the present social context (COVID-19). The major pitfall of this marketing system is the random non-availability of/refusal by customers. Nowadays, with the development of infrastructure, there are several route connections among the different locations worldwide. Considering these, we formulate some multi-path routing for goods delivery with refusal problems (MPRfGDwRPs) against online booking having different route connections between nodes (customers) and solved by a novel Type-2 fuzzy logic based fireworks algorithm (T2FLFWA) developed for discrete problems with probability-based selection and generation based prime mutation. In T2FLFWA, inferences are drawn to obtain the amplitude coefficient against the assumed spark number and iteration ratio. Some instances from TSPLIB are solved and supremacy of T2FLFWA is established through ANOVA test. In MPRfGDwRP, a delivery man starts with goods from a warehouse against customers’ online demands under cash-on-delivery or cash-on bookings systems and delivers the appropriate goods to the respective customers located at different locations. The random refusal or non-availability of customers is considered. The optimum travel plan and appropriate routes between the nodes are selected for minimum total cost. The models are illustrated numerically through a real-life problem. Some managerial conclusions are drawn. The novelty of the investigation is that for the first time, T2FLFWA for discrete problems is developed, delivery man's routing plan with multiple paths between nodes with refusals is formulated and its solution using T2FLFWA is presented. © 2022 The Author(s)","Fireworks algorithm; Goods delivery problem; Multi-path routing; Probabilistic refusal; Type-2 fuzzy logic",{"$nulls":7},"Yang L., Zheng Y.-Y., Wu C.-H., Dong S.-Z., Shao X.-F., Liu W., Deciding online and offline sales strategies when service industry customers express fairness concerns, Enterpr. Inf. Syst., 16, 3, pp. 427-444, (2022); Bubanja I., Vidas-Bubanja M., Managing trade transactions in the covid era: The rise of e-commerce, J. Eng. Manage. Compet. (JEMC), 12, 1, pp. 20-34, (2022); Gupta P., Sharma A., E-commerce in India-a new perspective, Integr. J. Res. 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["Cebeci M.S.; Tapia R.J.; Kroesen M.; de Bok M.; Tavasszy L.","Cebeci, Merve Seher (58120901900); Tapia, Rodrigo Javier (56494372900); Kroesen, Maarten (24344046200); de Bok, Michiel (9336248700); Tavasszy, Lóránt (41762713200)","58120901900; 56494372900; 24344046200; 9336248700; 41762713200","The effect of trust on the choice for crowdshipping services",2023.0,"Transportation Research Part A: Policy and Practice",170.0,null,103622.0,null,null,null,5.0,"10.1016/j.tra.2023.103622","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85149057167&doi=10.1016%2fj.tra.2023.103622&partnerID=40&md5=21449514ffb58f3a7cb7b7122398294f","Department of Transport and Planning, Faculty of Civil Engineering and Geosciences, Delft University of Technology, Stevinweg 1, CN Delft, 2628, Netherlands; Transport Policy Group, Faculty of Technology, Policy and Management, Delft University of Technology, P.O. Box 5015, GA Delft, 2600, Netherlands; Significance BV, Grote Marktstraat 47, BH The Hague, 2511, Netherlands","Cebeci M.S., Department of Transport and Planning, Faculty of Civil Engineering and Geosciences, Delft University of Technology, Stevinweg 1, CN Delft, 2628, Netherlands; Tapia R.J., Department of Transport and Planning, Faculty of Civil Engineering and Geosciences, Delft University of Technology, Stevinweg 1, CN Delft, 2628, Netherlands, Significance BV, Grote Marktstraat 47, BH The Hague, 2511, Netherlands; Kroesen M., Transport Policy Group, Faculty of Technology, Policy and Management, Delft University of Technology, P.O. Box 5015, GA Delft, 2600, Netherlands; de Bok M., Department of Transport and Planning, Faculty of Civil Engineering and Geosciences, Delft University of Technology, Stevinweg 1, CN Delft, 2628, Netherlands, Significance BV, Grote Marktstraat 47, BH The Hague, 2511, Netherlands; Tavasszy L., Department of Transport and Planning, Faculty of Civil Engineering and Geosciences, Delft University of Technology, Stevinweg 1, CN Delft, 2628, Netherlands, Transport Policy Group, Faculty of Technology, Policy and Management, Delft University of Technology, P.O. Box 5015, GA Delft, 2600, Netherlands","The fast growth of e-commerce in urban areas has led to a surge in last-mile transportation demand and an associated increase of external effects: congestion, noise and visual pollution. This paper analyses a new urban freight transport service that has a potential to reduce this footprint: crowdshipping. Crowdshipping is a service where a package is delivered via a traveller who is already making a personal trip for other purposes. The decision of whether or not to use crowdshipping is known to be subject to various service, time and price conditions, including trust in a correct delivery. The effect of trust has not been investigated explicitly, however. We conduct a stated choice experiment and estimate a hybrid choice model with trust as a situation-specific latent variable. The research design allows us to explore how the relevant attributes influence service adoption via trust. We find a significant influence of established choice attributes on service adoption, except for the delivery company's reputation and the possibility of damage. In addition, all attributes except delivery time have a significant influence on trust. We conclude that trust has a partially mediating effect on the adoption of the service except delivery time, and a fully mediating effect on adoption via reputation and damage. © 2023 The Author(s)","Crowdshipping; Hybrid Choice Model; Stated Preference; Trust","Freight transportation; Urban growth; Choice model; Crowdshipping; Delivery time; E- commerces; Fast growths; Hybrid choice model; Mediating effect; Stated preferences; Trust; Urban areas; demand analysis; freight transport; shipping; transportation planning; transportation policy; urban transport; Urban transportation",{"$nulls":4},"Turkish Ministry of National Education; Horizon 2020 Framework Programme, H2020; Horizon 2020, (861598)","Funding text 1: The financial support of the Turkish Ministry of National Education is gratefully acknowledged. Moreover, this project has received funding from the European Union's Horizon 2020 research and innovation program under grant agreement No 861598. Lastly, we thank the reviewers for their comments and suggestions that led to improvements in the manuscript. Author statement. The authors confirm contribution to the paper as follows: study conception and design: Cebeci, Tapia, Kroesen, Tavasszy; data collection: Cebeci; analysis and interpretation of results: Cebeci, Tapia, Kroesen, de Bok, Tavasszy; draft manuscript preparation: Cebeci, Tapia, Kroesen, de Bok, Tavasszy. All authors reviewed the results and approved the final version of the manuscript.; Funding text 2: The financial support of the Turkish Ministry of National Education is gratefully acknowledged. Moreover, this project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No 861598. Lastly, we thank the reviewers for their comments and suggestions that led to improvements in the manuscript. 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(2018); Nguyen-Phuoc D.Q., Oviedo-Trespalacios O., Vo N.S., Le P.T., Van Nguyen T., How does perceived risk affect passenger satisfaction and loyalty towards ride-sourcing services?, Transportation Research Part D: Transport and Environment, 97, (2021); Punel A., Stathopoulos A., Modeling the acceptability of crowdsourced goods deliveries: Role of context and experience effects, Transportation Research Part E: Logistics and Transportation, Review105), pp. 18-38, (2017); Punel A., Ermagun A., Stathopoulos A., Studying determinants of crowd-shipping use, Travel Behaviour and Society, 12, pp. 30-40, (2018); Punel A., Ermagun A., Stathopoulos A., pp. 18-05587; Ranieri L., Digiesi S., Silvestri B., Roccotelli M., A review of last mile logistics innovations in an externalities cost reduction vision, Sustainability, 10, 3, (2018); Roh T., Yang Y.S., Xiao S., Park B.I., What makes consumers trust and adopt fintech? 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A Multiple Discrete Extreme Value Model Application for Grain Consolidators in Argentina, Networks and Spatial Economics, 21, 3, pp. 581-608, (2021); Tapia R.J., Kourounioti I., Thoen S., de Bok M., Tavasszy L., A disaggregate model of passenger-freight matching in crowdshipping services, Transportation Research Part A: Policy and Practice, 169, (2023); Upadhyay C.K., Tewari V., Tiwari V., Assessing the impact of sharing economy through adoption of ICT based crowdshipping platform for last-mile delivery in urban and semi-urban India, Information Technology for Development, 27, 4, pp. 670-696, (2021); Walker J., Ben-Akiva M., Generalized random utility model, Mathematical Social Sciences, 43, 3, pp. 303-343, (2002); Wicaksono S., Lin X., Tavasszy L.A., Market potential of bicycle crowdshipping: A two-sided acceptance analysis, Research in Transportation Business & Management, (2021); Yrjola M., Rintamaki T., Saarijarvi H., Joensuu J., Consumer-to-consumer e-commerce: outcomes and implications, The International Review of Retail, Distribution and Consumer Research, 27, 3, pp. 300-315, (2017)","M.S. Cebeci; Department of Transport and Planning, Faculty of Civil Engineering and Geosciences, Delft University of Technology, CN Delft, Stevinweg 1, 2628, Netherlands; email: M.S.Cebeci@tudelft.nl",null,"Elsevier Ltd",{"$nulls":5},9658564.0,null,null,null,"English","Transp. Res. Part A Policy Pract.","Article","Final","All Open Access; Green Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85149057167"]
["Das J.N.; Tiwari M.K.; Sinha A.K.; Khanzode V.","Das, Jyotirmoy Nirupam (57874785000); Tiwari, Manoj Kumar (35427952100); Sinha, Ashesh Kumar (55982238100); Khanzode, Vivek (20433501800)","57874785000; 35427952100; 55982238100; 20433501800","Integrated warehouse assignment and carton configuration optimization using deep clustering-based evolutionary algorithms",2023.0,"Expert Systems with Applications",212.0,null,118680.0,null,null,null,7.0,"10.1016/j.eswa.2022.118680","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137274647&doi=10.1016%2fj.eswa.2022.118680&partnerID=40&md5=680cf9a10a9cda062b10473b2698f64b","National Institute of Industrial Engineering (NITIE), Vihar Lake Marg, Powai, Maharashtra, Mumbai, India; Department of Industrial Engineering and Management, Indian Institute of Technology, Kharagpur, India; Kansas State University, United States","Das J.N., National Institute of Industrial Engineering (NITIE), Vihar Lake Marg, Powai, Maharashtra, Mumbai, India; Tiwari M.K., National Institute of Industrial Engineering (NITIE), Vihar Lake Marg, Powai, Maharashtra, Mumbai, India, Department of Industrial Engineering and Management, Indian Institute of Technology, Kharagpur, India; Sinha A.K., Kansas State University, United States; Khanzode V., National Institute of Industrial Engineering (NITIE), Vihar Lake Marg, Powai, Maharashtra, Mumbai, India","A rapid rise in e-commerce has forced logistic companies to invest in efficiency and reduce last-mile delivery costs. A significant part of last-mile delivery operations is the cartonization of orders and economically delivering them. An optimal carton configuration leads to a better cartonization and reduces the carton manufacturing costs and carbon footprint, whereas the optimal warehouse allocation directly reduces the transportation costs. Therefore, a multiobjective formulation has been proposed in this study to address the warehouse assignment and carton configuration optimization problem. A novel Interdependent Pareto Ant Colony Optimization (IPACO) has been integrated with a Deep Embedded Clustering algorithm (DEC) to form a DEC-based IPACO (DECIPACO) model to solve the proposed formulation. The integrated model was tested on 54 different datasets and compared against other clustering-based evolutionary algorithm models. The DECIPACO model provided an optimal or a non-dominated solution in all cases against the k-means clustering-based evolutionary algorithm models. Hence, the proposed DECIPACO model was able to explore an optimal trade-off between fuel costs and total carton volume while fulfilling the customer demand from inventory-constrained warehouses. © 2022 Elsevier Ltd","Deep Clustering; Last-mile; Multi-objective; Warehouse Operations","Carbon footprint; Cost reduction; Economic and social effects; Evolutionary algorithms; K-means clustering; Manufacture; Multiobjective optimization; Warehouses; Algorithm model; Clusterings; Configuration optimization; Deep clustering; E- commerces; Integrated warehouse; Last mile; Logistics company; Multi objective; Warehouse operation; Ant colony optimization",{"$nulls":6},"Acimovic J., Graves S.C., Making better fulfillment decisions on the fly in an online retail environment, Manufacturing and Service Operations Management, 17, 1, pp. 34-51, (2014); Ardjmand E., Sanei Bajgiran O., Rahman S., Weckman G.R., Young W.A., A multi-objective model for order cartonization and fulfillment center assignment in the e-tail/retail industry, Transportation Research Part E: Logistics and Transportation Review, 115, May, pp. 16-34, (2018); 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Espino-Rodriguez T.F., Rodriguez-Diaz M., Determining the core activities in the order fulfillment process: An empirical application, Business Process Management Journal, 20, 1, pp. 2-24, (2014); Fadda E., Gobbato L., Perboli G., Rosano M., Tadei R., Waste collection in urban areas: A case study, Interfaces, 48, 4, pp. 307-322, (2018); Fadda E., Perboli G., Rosano M., Mascolo J.E., Masera D., A Decision Support System for Supporting Strategic Production Allocation in the Automotive Industry, Sustainability (Switzerland), 14, 4, pp. 1-21, (2022); Fan J., Wang G., Thurer M., Approximation Algorithms for a New Truck Loading Problem in Urban Freight Transportation, Transportation Science, 54, 3, pp. 690-702, (2020); Fekete S.P., Schepers J., Van Der Veen J.C., An exact algorithm for higher-dimensional orthogonal packing, Operations Research, 55, 3, pp. 569-587, (2007); Gilmore P.C., Gomory R.E., Multistage Cutting Stock Problems of Two and More Dimensions, Operations Research, 13, 1, pp. 94-120, (1965); 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Li T.H.S., Liu C.Y., Kuo P.H., Fang N.C., Li C.H., Cheng C.W., Chen C.Y., A three-dimensional adaptive PSO-based packing algorithm for an IoT-based automated e-fulfillment packaging system, IEEE Access, 5, pp. 9188-9205, (2017); Liu Y., Wang Z., Cheng G.Q., Optimization design for size of footwear outer packaging boxes, Advanced Materials Research, 694, 697, pp. 3516-3521, (2013); Mao T., Mihaita A.-S., Chen F., Vu H.L.; Martello S., Pisinger D., Vigo D., The three-dimensional bin packing problem, Operations Research, 48, 2, pp. 256-267, (2000); Min E., Guo X., Liu Q., Zhang G., Cui J., Long J., A survey of clustering with deep learning: from the perspective of network architecture, IEEE Access, 6, pp. 39501-39514, (2018); Ming M., Wang R., Ishibuchi H., Zhang T., A novel dual-stage dual-population evolutionary algorithm for constrained multi-objective optimization, IEEE Transactions on Evolutionary Computation, c, 1-15, (2021); Munien C., Mahabeer S., Dzitiro E., Singh S., Zungu S., Ezugwu A.E., Metaheuristic approaches for one-dimensional bin packing problem: A comparative performance study, IEEE Access, 8, (2020); Ahire S.L., Malhotra M.K., INFORMS Journal on Applied Analytics Editor's Statement, INFORMS Journal on Applied Analytics, 50, 1, pp. 1-2, (2020); Singh M., Ardjmand E., Carton set optimization in e-commerce warehouses: A case study, Journal of Business Logistics, 41, 3, pp. 222-235, (2020); Tang J., Yang Y., Hao W., Liu F., Wang Y., A data-driven timetable optimization of urban bus line based on multi-objective genetic algorithm, IEEE Transactions on Intelligent Transportation Systems, 22, 4, pp. 2417-2429, (2021); Thirumalai S., Sinha K.K., Customer satisfaction with order fulfillment in retail supply chains: Implications of product type in electronic B2C transactions, Journal of Operations Management, 23, 3-4, pp. 291-303, (2005); Torabi S.A., Hassini E., Jeihoonian M., Fulfillment source allocation, inventory transshipment, and customer order transfer in e-tailing, Transportation Research Part E: Logistics and Transportation Review, 79, pp. 128-144, (2015); (2021); van Heeswijk W.J.A., Mes M.R.K., Schutten J.M.J., The delivery dispatching problem with time windows for urban consolidation centers, Transportation Science, 53, 1, pp. 203-221, (2019); Wei L., Lai M., Lim A., Hu Q., Discrete Optimization A branch-and-price algorithm for the two-dimensional vector packing problem, European Journal of Operational Research, 281, 1, pp. 25-35, (2020); Xie J., Girshick R., Farhadi A., (2016); Yuan C., (2019); (2009); Zhang G., Shang X., Alawneh F., Yang Y., Nishi T., Integrated production planning and warehouse storage assignment problem: An IoT assisted case, International Journal of Production Economics, 234, (2021); Zhao X., Bennell J.A., Bektas T., Dowsland K., A comparative review of 3D container loading algorithms, International Transactions in Operational Research, 23, 1-2, pp. 287-320, (2016); Zhu S., Hu X., Huang K., Yuan Y., Optimization of product category allocation in multiple warehouses to minimize splitting of online supermarket customer orders, European Journal of Operational Research, 290, 2, pp. 556-571, (2021)","A.K. Sinha; Kansas State University, United States; email: sinhaa@ksu.edu",null,"Elsevier Ltd",{"$nulls":5},9574174.0,null,"ESAPE",null,"English","Expert Sys Appl","Article","Final",null,"Scopus","2-s2.0-85137274647"]
["Teimoury E.; Rashid R.","Teimoury, Ebrahim (25652394500); Rashid, Reza (57192644781)","25652394500; 57192644781","A hybrid large-neighborhood search for a truck and drone delivery system with stochastic customer existence and time windows",2023.0,"Journal of Intelligent and Fuzzy Systems",44.0,6.0,null,10197.0,10211.0,14.0,0.0,"10.3233/JIFS-224307","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85166396573&doi=10.3233%2fJIFS-224307&partnerID=40&md5=7f023e49d664b338942bd1e4552c591a","Department of Industrial Engineering, Iran University of Science and Technology, Narmak, Tehran, Iran","Teimoury E., Department of Industrial Engineering, Iran University of Science and Technology, Narmak, Tehran, Iran; Rashid R., Department of Industrial Engineering, Iran University of Science and Technology, Narmak, Tehran, Iran","In recent years, e-commerce has become increasingly popular, and consumers expect quick and affordable delivery, placing additional pressure on city logistics activities. An innovative approach is proposed to coordinate ground vehicles and drones for delivery services, which has gained tremendous attention from academia and logistic service providers. This paper introduces a variant of this problem: the two-echelon truck and drone routing problem, characterized by stochastic demand existence and soft time windows. A Markov chain is used to model the problem, and a linear mathematical model is presented. This work employs a hybrid large-neighborhood search approach. Numerous computational experiments are conducted to evaluate the performance of the proposed solution method, and the results demonstrate its efficacy. © 2023 - IOS Press. All rights reserved.","large-neighborhood search; Last-mile delivery; Markov chain; stochastic optimization; truck and drone routing","Markov processes; Optimization; Trucks; Delivery systems; E- commerces; Large neighbourhood searches; Last mile; Last-mile delivery; Routings; Stochastic optimizations; Stochastics; Time windows; Truck and drone routing; Drones",{"$nulls":6},"Enthoven D.L.J.U., Jargalsaikhan B., Roodbergen K.J., Broek M.A.J., Schrotenboer A.H., The two-echelon vehicle routing problem with covering options: City logistics with cargo bikes and parcel lockers, Computers and Operations Research, (2020); Asadi A., Pinkley S.N., Mes M., A Markov decision process approach for managing medical drone deliveries, Expert Systems with Applications, 204, (2022); Moshref-Javadi M., Winkenbach M., Applications and Research avenues for drone-based models in logistics: A classification and review, Expert Systems with Applications, 177, (2021); Luo Z., Poon M., Zhang Z., Liu Z., Lim A., The multi-visit traveling salesman problem with multi-drones, Transportation Research Part C: Emerging Technologies, 128, (2021); Wang D., Hu P., Du V., Zhou P., Deng T., Hu M., Routing and scheduling for hybrid truck-drone collaborative parcel delivery with independent and truck-carried drones, IEEE Internet of Things Journal, 6, 6, pp. 10483-10495, (2019); Freitas J.C., Penna P.H.V., A variable neighborhood search for flying sidekick traveling salesman problem, International Transactions in Operational Research, pp. 1-24, (2019); Chen C., Demir E., Huang Y., An adaptive largeneighborhood search heuristic for the vehicle routing problem with time windows and delivery robots, European Journal of Operational Research, 294, pp. 1164-1180, (2021); Murray C.C., Chu A.G., The flying sidekick traveling salesman problem: Optimization of drone-assisted parcel delivery, Transportation Research Part C: Emerging Technologies, 54, pp. 86-109, (2015); Jeong H.Y., Song B.D., Lee S., Truck-drone hybrid delivery routing: Payload-energy dependency and No-Fly zones, International Journal of Production Economics, 214, pp. 220-233, (2019); Murray C.C., Raj R., The multiple flying sidekicks traveling salesman problem: Parcel delivery with multiple drones, Transportation Research Part C: Emerging Technologies, 110, pp. 368-398, (2020); Raj R., Murray C., The multiple flying sidekicks traveling salesman problem with variable drone speeds, Transportation Research Part C: Emerging Technologies, 120, (2020); Bouman P., Agatz N., Schmidt M., Dynamic programming approaches for the traveling salesman problem with drone, Networks, 72, pp. 528-542, (2018); Poikonen S., Golden B., The mothership and drone routing problem, INFORMSJournal on Computing, 32, 2, pp. 249-262, (2019); Tu P.A., Dat N.T., Dung P.Q., Traveling salesman problem with multiple drones, SoICT, pp. 6-7, (2018); Moshref-Javadi M., Lee S., Winkenbach M., Design and evaluation of a multi-trip delivery model with truck and drones Transportation Research Part E: Logis-Transportation Research Part E: Logis, Transportation Research Part E: Logistics and Transportation Review, 136, (2020); Moshref-Javadi M., Hemmati A., Winkenbach M., A truck and drones model for last-mile delivery: a mathematical model and heuristic approach, Applied Mathematical Modelling, 2019; Schermer D., Moeini M., Wendt O., A matheuristic for the vehicle routing problem with drones and its variants, Transportation Research Part C: Emerging Technologies, 106, pp. 166-204, (2019); Poikonen S., Golden B., Wasil E., A branch-and-bound approach to the traveling salesman problem with a drone, INFORMS Journal on Computing, 31, 2, pp. 335-346, (2019); Lee S.Y., Han S.R., Song B.D., Simultaneous cooperation of Refrigerated Ground Vehicle (RGV) and Unmanned Aerial Vehicle (UAV) for rapid delivery with perishable food, Applied Mathematical Modelling, 106, pp. 844-866, (2022); Luo Z., Lio Z., Shi J., A two-echelon cooperated routing problem for a ground vehicle and its carried unmanned aerial vehicle, Sensors, 17, (2017); Karak A., Abdelghany K., The hybrid vehicle-drone routing problem for pick-up and delivery services, Transportation Research Part C: Emerging Technologies, 102, pp. 427-449, (2019); Oyola J., Arntzen H., Woodruff D.L., The stochastic vehicle routing problem, a literature review, part I: models, EUROJournal on Transportation and Logistics, 7, 3, pp. 193-221, (2018); Liu Z., Li X., Khojandi A., The flying sidekick traveling salesman problem with stochastic travel time: A reinforcement learning approach, Transportation Research Part E: Logistics and Transportation Review, 164, (2022); Ghelichi Z., Gentili M., Mirchandani P.B., Drone logistics for uncertain demand of disaster-impacted populations, Transportation Research Part C: Emerging Technologies, 141, (2022); Sawadsitang S., Niyato D., Tan P., Wang P., Joint ground and aerial package delivery services: a stochastic optimization approach, IEEE Transactions on Intelligent Transportation Systems, 20, 6, pp. 2241-2254, (2019); Mathew N., Smith S.L., Waslander S.L., Planning paths for package delivery in heterogeneous multirobot teams, IEEE Transactions on Automation Science and Engineering, 12, 4, pp. 1298-1308, (2015); Carlsson J.G., Song S., Coordinated logistics with a truck and a drone, Management Science, 64, 9, pp. 4052-4069, (2017); Chang Y.S., Lee H.J., Optimal delivery routing with wider drone-delivery areas along a shorter truck-route, Expert Systems with Applications, 2018; Kitjacharoenchai P., Min B., Lee S., Two echelon vehicle routing problem with drones in last mile delivery, International Journal of Production Economics, 225, (2020); Sacramento D., Pisinger D., Ropke S., An adaptive large-neighborhood search metaheuristic for the vehicle routing problem with drones, Transportation Research Part C: Emerging Technologies, 102, pp. 289-315, (2019); Li H., Wang H., Chen J., Bai M., Two-echelon vehicle routing problem with time windows and mobile satellites, Transportation Research Part B: Methodological, 138, pp. 179-201, (2020); Pina-Pardo J.C., Silva D.F., Smith A.E., The traveling salesman problem with release dates and drone resupply, Computers & Operations Research, 129, (2021); Leon-Blanco J.M., Gonzalez-R P.L., Andrade-Pineda J.L., Canca D., Calle M., A multi-agent approach to the truck multi-drone routing problem, Expert Systems with Applications, 195, (2022); Kyriakakis N.A., Stamadianos T., Marinaki M., Marinakis Y., The electric vehicle routing problem with drones: An energy minimization approach for aerial deliveries, Cleaner Logistics and Supply Chain, 4, (2022)","E. Teimoury; Department of Industrial Engineering, Iran University of Science and Technology, Tehran, Narmak, Iran; email: Teimoury@iust.ac.ir",null,"IOS Press BV",{"$nulls":5},1.0641246E7,null,null,null,"English","J. Intelligent Fuzzy Syst.","Article","Final",null,"Scopus","2-s2.0-85166396573"]
["Golinska-Dawson P.; Werner-Lewandowska K.; Kolinska K.; Kolinski A.","Golinska-Dawson, Paulina (23034141000); Werner-Lewandowska, Karolina (56741522400); Kolinska, Karolina (55779888500); Kolinski, Adam (57196346630)","23034141000; 56741522400; 55779888500; 57196346630","Impact of Market Drivers on the Digital Maturity of Logistics Processes in a Supply Chain",2023.0,"Sustainability (Switzerland)",15.0,4.0,3120.0,null,null,null,4.0,"10.3390/su15043120","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85149205436&doi=10.3390%2fsu15043120&partnerID=40&md5=34ce81332b50af356bcd62e5a35795ad","Institute of Logistics, Faculty of Engineering Management, Poznan University of Technology, Poznan, 60-965, Poland; Poznan School of Logistics, Poznan, 61-755, Poland; Lukasiewicz Research Network—Poznan Institute of Technology, Poznan, 61-755, Poland","Golinska-Dawson P., Institute of Logistics, Faculty of Engineering Management, Poznan University of Technology, Poznan, 60-965, Poland; Werner-Lewandowska K., Institute of Logistics, Faculty of Engineering Management, Poznan University of Technology, Poznan, 60-965, Poland; Kolinska K., Poznan School of Logistics, Poznan, 61-755, Poland; Kolinski A., Lukasiewicz Research Network—Poznan Institute of Technology, Poznan, 61-755, Poland","Logistics processes allow for the movement of goods along the supply chain to the customers. Companies are using digital solutions more widely to support their logistics processes. Current studies focus mainly on the intrinsic perspective of the digital maturity of logistics processes. Rarely do previous studies consider the impact of external factors (e.g., market trends, as external drivers at the strategic level) on the digital maturity of logistics processes. In this paper, our aim is to propose a novel generic approach to measuring the level of adoption of digital technologies in logistics processes. We applied the maturity model theory to provide a generic framework for the assessment of different partners in supply chains (suppliers, manufacturers, retailers, e-tailers, logistics service providers) in a homogeneous way. We propose the five levels (Avoiding, Discovering, Adopting, Improving, Excelling) to measure the frequency of the application of the digital technologies with high intelligence in the domain of logistics processes. Furthermore, we investigate the relationship between the selected market trends, which are external drivers at the strategic level, and the digital maturity of logics processes. We conducted the survey among a group of 38 companies to classify their maturity level and then to test which market trends motivate them to digitalize their processes. We applied Bayesian statistics to test the level of the relationship between the digitalization of logistics processes and four market trends, namely, the sustainability, e-commerce, sharing economy, and speed-orientation of customers. The results show that all the trends tested moderately and positively influence the digital maturity of logistics processes. © 2023 by the authors.","Bayesian statistics; digitalization; E-commerce; Logistics 4.0; maturity; sharing economy; sustainability","Bayesian analysis; digitization; electronic commerce; logistics; supply chain management; sustainability; urban economy",{"$nulls":4},"Politechnika Poznańska, PUT, (0812/SBAD/4202)","The APC was funded by the internal research grant of the Poznan University of Technology no. 0812/SBAD/4202.",{"$cut":{"chars":16577,"head":"Chowdhury P., Paul S.K., Kaisar S., Moktadir M.A., COVID-19 Pandemic Related Supply Chain Studies: A Systematic Review, Transp. Res. Part E Logist. Transp. Rev, 148, (2021); Winkelhaus S., Grosse E.H., Logistics 4.0: A Systematic Review towards a New Logistics System, Int. J. Prod. Res, 58, pp. 18-43, (2020); Brzezinski L., Hadas L., Cyplik P., The Transformation of the Business Model of SMEs Due to COVID-19 Pandemic, Eur. Res. Stud. J, 24, pp. 915-924, (2021); Bjorgen A., Bjerkan K.Y., Hjelkrem O.A., E-Groceries: Sustainable Last Mile Distribution in City Planning, Res. Transp. Econ, 87, (2021); Kawa A., Pieranski B., Green logistics in e-commerce, LogForum, 17, pp. 183-192, (2021); Daugherty P.J., Bolumole Y., Grawe S.J., The New Age of Customer Impatience: An Agenda for Reawakening Logistics Customer Service Research, Int. J. Phys. Distrib. Logist. Manag, 49, pp. 4-32, (2019); Werner-Lewandowsk K., Lubinski P., Sloniec J., The Effect of Covid-19 on Consumer Behavior in Poland—Preliminary Research Results, Eur. Res. Stud, XXIV, pp. 405-416, (2021); Tudor C., Integrated Framework to Assess the Extent of the Pandemic Impact on the Size and Structure of the E-Commerce Retail Sales Sector and Forecast Retail Trade E-Commerce, Electronics, 11, (2022); Hirt M., Willmott P., Strategic Principles for Competing in the Digital Age, (2014); Gunasekaran A., Subramanian N., Papadopoulos T., Information Technology for Competitive Advantage within Logistics and Supply Chains: A Review, Transp. Res. Part E Logist. Transp. Rev, 99, pp. 14-33, (2017); Mathauer M., Hofmann E., Technology Adoption by Logistics Service Providers, Int. J. Phys. Distrib. Logist. Manag, 49, pp. 416-434, (2019); Bharadwaj A., El Sawy O.A., Pavlou P.A., Venkatraman N., Digital Business Strategy: Toward a Next Generation of Insights, MIS Q, 37, pp. 471-482, (2013); Cichosz M., Wallenburg C.M., Knemeyer A.M., Digital Transformation at Logistics Service Providers: Barriers, Success Factors and Leading Practices, Int. J. Logist. Manag, 31, pp. 209-238, (2020); Cichosz M., Digitalization and Competitiveness in the Logistics Service Industry, E Mentor, 77, pp. 73-82, (2018); Golinska P., Hajdul M., Multi-Agent Coordination Mechanism of Virtual Supply Chain, pp. 620-629, (2011); Pawlewski P., Golinska P., Fertsch M., Trujillo J.A., Pasek Z.J., Multiagent Approach for Supply Chain Integration by Distributed Production Planning, Scheduling and Control System, Proceedings of the International Symposium on Distributed Computing and Artificial Intelligence 2008 (DCAI 2008), pp. 29-37, (2009); Arunachalam D., Kumar N., Kawalek J.P., Understanding Big Data Analytics Capabilities in Supply Chain Management: Unravelling the Issues, Challenges and Implications for Practice, Transp. Res. Part E Logist. Transp. Rev, 114, pp. 416-436, (2018); Hofmann E., Rusch M., Industry 4.0 and the Current Status as Well as Future Prospects on Logistics, Comput. Ind, 89, pp. 23-34, (2017); Yang M., Fu M., Zhang Z., The Adoption of Digital Technologies in Supply Chains: Drivers, Process and Impact, Technol. Forecast. Soc. Chang, 169, (2021); Nguyen T., Zhou L., Spiegler V., Ieromonachou P., Lin Y., Big Data Analytics in Supply Chain Management: A State-of-the-Art Literature Review, Comput. Oper. Res, 98, pp. 254-264, (2018); Ivanov D., Dolgui A., A Digital Supply Chain Twin for Managing the Disruption Risks and Resilience in the Era of Industry 4.0, Prod. Plan. Control, 32, pp. 775-788, (2021); Lu Y., Industry 4.0: A Survey on Technologies, Applications and Open Research Issues, J. Ind. Inf. Integr, 6, pp. 1-10, (2017); Pawlewski P., Kosacka-Olejnik M., Werner-Lewandowska K., Digital Twin Lean Intralogistics: Research Implications, Appl. Sci, 11, (2021); Ben-Daya M., Hassini E., Bahroun Z., Internet of Things and Supply Chain Management: A Literature Review, Int. J. Prod. Res, 57, pp. 4719-4742, (2019); Jiang W., An Intelligent Supply Chain Information Collaboration Model Based on Internet of Things and Big Data, IEEE Access, 7, pp. 58324-58335, (2019); Schoenherr T., Speier-Pero C., Data Scienc"}},"P. Golinska-Dawson; Institute of Logistics, Faculty of Engineering Management, Poznan University of Technology, Poznan, 60-965, Poland; email: paulina.golinska@put.poznan.pl",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85149205436"]
["Ge X.; Jin Y.","Ge, Xianlong (55647754300); Jin, Yuanzhi (57219283180)","55647754300; 57219283180","Sustainability Oriented Vehicle Route Planning Based on Time-Dependent Arc Travel Durations",2023.0,"Sustainability (Switzerland)",15.0,4.0,3208.0,null,null,null,1.0,"10.3390/su15043208","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85149271803&doi=10.3390%2fsu15043208&partnerID=40&md5=538a0371e3c28739e191c295e3958ee1","School of Economics and Management, Chongqing Jiaotong University, Chongqing, 400074, China; Department of Computer Technology and Information Engineering, Sanmenxia Polytechnic, Sanmenxia, 472000, China","Ge X., School of Economics and Management, Chongqing Jiaotong University, Chongqing, 400074, China; Jin Y., School of Economics and Management, Chongqing Jiaotong University, Chongqing, 400074, China, Department of Computer Technology and Information Engineering, Sanmenxia Polytechnic, Sanmenxia, 472000, China","Traffic congestion has become a growing concern in cities, with both economic and environmental impacts on both individuals and the logistics industry. Therefore, a model of freight distribution in urban areas considering economic and environmental objectives needs to be established to alleviate the consequences. In this paper, a multi-stage heuristic algorithm is designed for solving the route planning based on time-dependent arc travel durations. The algorithm includes a savings method, a modified tabu search heuristic and a cycle transforming optimization (CTO) algorithm. Benchmark instances and the case of Jingdong, one of the largest e-commerce platforms in China, have been adopted to verify the accuracy and feasibility of the model and algorithm. Results of the performance test reveal that the designed algorithm is suitable for addressing large-scale instances. Based on the single objective models, two objectives referring to economical-related and environmental-related factors are considered in the proposed sustainability oriented bi-objective model, and a modified solution framework using a multi-objective decision making method with a relaxation coefficient which is designed for addressing the bi-objective model. Finally, the time-dependent arc travel durations based on real-time traffic information have been incorporated into the optimization algorithms, simulation of distribution process and dynamic route updating strategy, which can reduce costs and route-associated emissions of logistics companies. © 2023 by the authors.","bi-objective optimization; sustainability; time-dependent arc travel durations; vehicle routing problem","China; decision making; electronic commerce; logistics; optimization; savings; sustainability; traffic congestion; transport vehicle; travel behavior",{"$nulls":4},"Key scientific and technological innovation project of “Construction of Chengdu-Chongqing Economic Circle; Natural Science Foundation of Chongqing, (cstc2020jcyj-msxmX0108); Chongqing Municipal Education Commission, CQMEC, (KJCXZD2020031)","This research was funded by the General Project of Chongqing Natural Science Foundation, grant number cstc2020jcyj-msxmX0108 and the Key scientific and technological innovation project of “Construction of Chengdu-Chongqing Economic Circle” of Chongqing Municipal Education Commission, grant number KJCXZD2020031.","Hannan M.A., Begum R., Al-Shetwi A.Q., Ker P., Al Mamun M., Hussain A., Basri H., Mahlia T., Waste collection route optimisation model for linking cost saving and emission reduction to achieve sustainable development goals, Sustain. 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Integr, 26, (2021); Bondy J.A., Murty U.S.R., Graph Theory, (2007); Augerat P., Naddef D., Belenguer J.M., Benavent E., Corberan A., Rinaldi G., The VRP Web, (2022); The Global Optimization Challenge, (2018); Nichat M.K., Chopde R.N., Nichat M., Landmark Based Shortest Path Detection By Using A* Algorithm and Haversine Formula, Int. J. Innov. Res. Comput. Commun. Eng, 1, (2013); Ge X., Jin Y., Zhang L., Genetic-based algorithms for cash-in-transit multi depot vehicle routing problems: Economic and environmental optimization, Environ. Dev. Sustain, 25, pp. 557-586, (2022)","Y. Jin; School of Economics and Management, Chongqing Jiaotong University, Chongqing, 400074, China; email: jinyuanzhi@haust.edu.cn",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85149271803"]
["Naseem M.H.; Yang J.; Zhang T.; Alam W.","Naseem, Muhammad Hamza (57226579229); Yang, Jiaqi (16026171300); Zhang, Tongxia (58296548800); Alam, Waseem (58297866700)","57226579229; 16026171300; 58296548800; 58297866700","Utilizing Fuzzy AHP in the Evaluation of Barriers to Blockchain Implementation in Reverse Logistics",2023.0,"Sustainability (Switzerland)",15.0,10.0,7961.0,null,null,null,5.0,"10.3390/su15107961","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85160775907&doi=10.3390%2fsu15107961&partnerID=40&md5=a2e9ea7482d9b3af31b3b306936d0032","School of Transportation and Logistics Engineering, Wuhan University of Technology, Wuhan, 430063, China","Naseem M.H., School of Transportation and Logistics Engineering, Wuhan University of Technology, Wuhan, 430063, China; Yang J., School of Transportation and Logistics Engineering, Wuhan University of Technology, Wuhan, 430063, China; Zhang T., School of Transportation and Logistics Engineering, Wuhan University of Technology, Wuhan, 430063, China; Alam W., School of Transportation and Logistics Engineering, Wuhan University of Technology, Wuhan, 430063, China","Digital technologies like blockchain, the Internet of Things, and smart warehouses have been developed due to the fourth industrial revolution, or “Industry 4.0.” Any business’ supply chain includes several stakeholders, including manufacturers, distributors, suppliers, and final consumers. The demand for firms to utilize these technologies to gain competitive advantages has intensified in the modern world due to rising worldwide rivalry. Additionally, the adoption of blockchain technology, in particular, can have a huge impact on a company’s reverse logistics, accelerating processes by decentralizing, tracking, and overseeing the delivery of items to final consumers. The goal of this study is to pinpoint those significant obstacles because several must be overcome for blockchain technology to be successfully implemented in reverse logistics. This study identified 16 impediments to the adoption of blockchain technology after a thorough analysis of the literature and expert opinion. The fuzzy AHP approach was used in this study to rank those barriers as this approach helps to address the complexity and uncertainty associated with decision-making in supply chain management and provides a more robust and reliable ranking of the barriers to blockchain adoption. A case study of Pakistan’s e-commerce industry was carried out. The results show that the high installation cost, stakeholders’ resistance to the blockchain, and the lack of top-management support are the critical success factors in blockchain adoption. From an industrial perspective, the study highlights the need for businesses to carefully evaluate the potential benefits and costs of adopting blockchain technology. It also underscores the importance of addressing the barriers to adoption to ensure successful implementation. By doing so, businesses can enhance their supply chain management and improve their overall competitiveness. © 2023 by the authors.","blockchain barriers; fuzzy AHP; reverse logistics; supply chain sustainability","Pakistan; decision making; electronic commerce; fuzzy mathematics; policy implementation; supply chain management; sustainability; technology adoption",{"$nulls":6},"Di Vaio A., Varriale L., Blockchain technology in supply chain management for sustainable performance: Evidence from the airport industry, Int. J. Inf. 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Eng, 136, pp. 225-241, (2019); Kaur J., Kumar S., Narkhede B.E., Dabic M., Rathore A.P.S., Joshi R., Barriers to blockchain adoption for supply chain finance: The case of Indian SMEs, Electron. Commer. Res, pp. 1-38, (2022); Caldarelli G., Zardini A., Rossignoli C., Blockchain adoption in the fashion sustainable supply chain: Pragmatically addressing barriers, J. Organ. Chang. Manag, 6, (2021); Nazam M., Hashim M., Nuta F.M., Yao L., Zia M.A., Malik M.Y., Usman M., Dimen L., Devising a Mechanism for Analyzing the Barriers of Blockchain Adoption in the Textile Supply Chain: A Sustainable Business Perspective, Sustainability, 14, (2022); Farooque M., Jain V., Zhang A., Li Z., Fuzzy DEMATEL analysis of barriers to Blockchain-based life cycle assessment in China, Comput. Ind. Eng, 147, (2020); Subramanian N., Chaudhuri A., Kayikci Y., Blockchain applications in reverse logistics, Blockchain Supply Chain Logistics: Evolutionary Case Studies, pp. 67-81, (2020); Panghal A., Manoram S., Mor R.S., Vern P., Adoption challenges of blockchain technology for reverse logistics in the food processing industry, Supply Chain. Forum Int. J, 24, pp. 7-16, (2023); Zkik K., Belhadi A., Khan S.A.R., Kamble S.S., Oudani M., Touriki F.E., Exploration of barriers and enablers of blockchain adoption for sustainable performance: Implications for e-enabled agriculture supply chains, Int. J. Logist. Res. Appl, pp. 1-38, (2022); Yadav N., Luthra S., Garg D., Blockchain technology and its relationships to sustainable supply chain management, Int. J. Prod. Res, 57, pp. 2117-2135, (2019); Kaur J., Sidhu R., Awasthi A., Chauhan S., Goyal S., A DEMATEL based approach for investigating barriers in green supply chain management in Canadian manufacturing firms, Int. J. Prod. 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Res, 95, pp. 649-655, (1996); Ar I.M., Erol I., Peker I., Ozdemir A.I., Evaluating the feasibility of blockchain in logistics operations: A decision framework, Expert Syst. Appl, 158, (2020); Lyu H.M., Sun W.J., Shen S.L., Zhou A.N., Risk assessment using a new consulting process in fuzzy AHP, J. Constr. Eng. Manag, 146, (2020); Prakash C., Barua M.K., Integration of AHP-TOPSIS method for prioritizing the solutions of reverse logistics adoption to overcome its barriers under fuzzy environment, J. Manuf. Syst, 37, pp. 599-615, (2015); Naseem M.H., Yang J., Xiang Z., Prioritizing the solutions to reverse logistics barriers for the e-commerce industry in pakistan based on a fuzzy ahp-topsis approach, Sustainability, 13, (2021)","M.H. Naseem; School of Transportation and Logistics Engineering, Wuhan University of Technology, Wuhan, 430063, China; email: muhammadhamza@whut.edu.cn",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85160775907"]
["Li Y.; Tan C.; Ip W.H.; Wu C.H.","Li, Yuting (57394306400); Tan, Chunqiao (19640693300); Ip, W.H. (55498852200); Wu, C.H. (55506191100)","57394306400; 19640693300; 55498852200; 55506191100","Dynamic blockchain adoption for freshness-keeping in the fresh agricultural product supply chain",2023.0,"Expert Systems with Applications",217.0,null,119494.0,null,null,null,22.0,"10.1016/j.eswa.2022.119494","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85146099528&doi=10.1016%2fj.eswa.2022.119494&partnerID=40&md5=a49cb7dc138b0845d0e5b4c73ff3d9bb","School of Business, Central South University, Changsha, China; School of Business, Nanjing Audit University, Nanjing, China; Department of Mechanical Engineering, University of Saskatchewan, Saskatoon, Canada; Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong; Department of Supply Chain and Information Management, The Hang Seng University of Hong Kong, Hong Kong","Li Y., School of Business, Central South University, Changsha, China; Tan C., School of Business, Nanjing Audit University, Nanjing, China; Ip W.H., Department of Mechanical Engineering, University of Saskatchewan, Saskatoon, Canada, Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong; Wu C.H., Department of Supply Chain and Information Management, The Hang Seng University of Hong Kong, Hong Kong","During COVID-19, the explosive growth of demand for fresh agricultural products on E-commerce platform has increased the difficulty of maintaining the greenness and freshness in delivery. The traditional cold chain delivery is effective in keeping greenness, but its information asymmetry makes the freshness-keeping activities unable to be regulated, which may lead to the supply chain members giving up their freshness-keeping efforts. Can the blockchain technology effectively solve these problems? We consider a fresh agricultural product supply chain consisting of a supplier and an E-commerce platform (retailer). The retailer is responsible for the wholesale and sales of fresh agricultural products, and determines the blockchain adoption degree and advertising effort. The supplier is responsible for delivering fresh agricultural products to consumers, and determines the greenness investment and freshness-keeping effort. Based on the traditional and blockchain-based fresh agricultural product supply chain, we discuss the dynamic optimization of freshness-keeping effort, advertising effort, and blockchain adoption degree. Results show that the supplier will give up the freshness-keeping effort after receiving the wholesale funds in the traditional fresh agricultural product supply chain, which will naturally worsen the fresh agricultural products. When adopting blockchain technology, the supplier continues to make the freshness-keeping effort in delivery. And five specific settings are proved that blockchain is effective in maintaining freshness. But two other specific settings are determined that it is not suited for adopting blockchain. In addition, compared with the traditional fresh agricultural product supply chain, blockchain adoption can effectively reduce the freshness-keeping effort, advertising investment and goodwill for achieving the same profit margin level, and will not affect the greenness investment decision of the supplier. Our research can provide some insights into the cold chain logistics management of fresh blockchain. © 2022","Blockchain technology; Fresh agricultural product supply chain; Freshness-keeping; Greenness investment","Agricultural products; Blockchain; Electronic commerce; Sales; Supply chains; Advertizing; Block-chain; Blockchain technology; Commerce platforms; Explosive growth; Fresh agricultural product supply chain; Fresh agricultural products; Freshness-keeping; Greenness investment; Product supply chains; Investments",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (71671188, 71971218)","This research was supported by the National Natural Science Foundation of China (Nos. 71971218 and 71671188). ","Bamakan S.M.H., Moghaddam S.G., Manshadi S.D., Blockchain-enabled pharmaceutical cold chain: Applications, key challenges, and future trends, Journal of Cleaner Production, 302, (2021); Bigliardi B., Galanakis C., Innovation management and sustainability in the food industry: Concepts and models, The interaction of food industry and environment, pp. 315-340, (2020); Blackburn J., Scudder G., Supply chain strategies for perishable products: The case of fresh produce, Production and Operations Management, 18, 2, pp. 129-137, (2009); Cai X., Chen J., Xiao Y., Xu X., Optimization and coordination of fresh product supply chains with freshness-keeping effort, Production and Operations Management, 19, 3, pp. 261-278, (2010); Cao Y., Tao L., Wu K., Wan G., Coordinating joint greening efforts in an agri-food supply chain with environmentally sensitive demand, Journal of Cleaner Production, 277, (2020); (2022); Chang H.H., Meyerhoefer C.D., COVID-19 and the demand for online food shopping services: Empirical Evidence from Taiwan, American Journal of Agricultural Economics, 103, 2, pp. 448-465, (2021); 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Zennyo Y., Strategic contracting and hybrid use of agency and wholesale contracts in e-commerce platforms, European Journal of Operational Research, 281, 1, pp. 231-239, (2020); Zhang X., Sun Y., Sun Y., (2022)","C. Tan; School of Business, Nanjing Audit University, Nanjing, China; email: chunqiaot@sina.com",null,"Elsevier Ltd",{"$nulls":5},9574174.0,null,"ESAPE",null,"English","Expert Sys Appl","Article","Final",null,"Scopus","2-s2.0-85146099528"]
["Tan S.; Fang K.; Lester T.W.","Tan, Simon (58149085300); Fang, Kevin (57218542763); Lester, T. William (31967661000)","58149085300; 57218542763; 31967661000","Post-pandemic travel patterns of remote tech workers",2023.0,"Transportation Research Interdisciplinary Perspectives",19.0,null,100804.0,null,null,null,2.0,"10.1016/j.trip.2023.100804","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85150455611&doi=10.1016%2fj.trip.2023.100804&partnerID=40&md5=1f577fcffcab46ce962ed21905b78147","San José State University, One Washington Square, San José, 95192, CA, United States; Sonoma State University, 1801 East Cotati Ave, Rohnert Park, 94928, CA, United States","Tan S., San José State University, One Washington Square, San José, 95192, CA, United States; Fang K., Sonoma State University, 1801 East Cotati Ave, Rohnert Park, 94928, CA, United States; Lester T.W., San José State University, One Washington Square, San José, 95192, CA, United States","Almost half of all jobs in the San Francisco Bay Area are “remote-eligible” – more than any other metropolitan area in the United States, due to the high concentration of employees in the technology sector who were early to embrace teleworking at the start of the COVID-19 pandemic in early 2020. Any significant share of these tech workers staying remote may have profound long-term impacts on aggregate travel patterns in the region. This research seeks to predict the magnitude of these impacts and derive insights about the newly learned behaviors of tech workers, as indicative of remote-eligible workers in general. A survey of over 660 tech workers ran from November 2021 to March 2022, asking about participants’ employers and remote work policies, commute details and mode preferences, non-work trips, and interest in relocation. Respondents expected employer-driven hybrid arrangements of 2–3 days per week in the office after the pandemic, which in turn dictated the number of predicted future commuting trips and suppressed interest in relocation. Though almost half of respondents expressed interest in moving, they only planned to move a median of 20.93 miles – staying within the region but shifting away from their offices and towards less dense and more automobile-oriented suburban neighborhoods. Additionally, those moving more than ten miles from their office are likely to switch to less sustainable travel modes. On the other hand, robust observed retention of online shopping habits for groceries and food delivery may mitigate the added vehicle trips caused by rebound effects. © 2023 The Author(s)","ICT; Relocation; Remote work; Tech industry; Telecommuting; Telework",{"$nulls":5},"San Francisco Municipal Transportation Agency","The authors want to thank Professor Nikhil Menon of Penn State Harrisburg for references on prior work and guidance regarding survey questions, Alexandra Hallowell from the San Francisco Municipal Transportation Agency (SFMTA) for professional review and assistance with data, and all our colleagues from the software industry who shared and participated in the survey.","Akan D., Remote working and relocation after COVID-19, (2022); Balbontin C., Hensher D.A., Beck M.J., Giesen R., Basnak P., Vallejo-Borda J.A., Venter C., Impact of COVID-19 on the number of days working from home and commuting travel: A cross-cultural comparison between Australia, South America and South Africa, J. Transp. Geogr., 96, (2021); Balbontin C., Hensher D.A., Beck M.J., Advanced modelling of commuter choice model and work from home during COVID-19 restrictions in Australia, Transp. Res. Part E: Logist. Transp. Rev., 162, (2022); Barbour N., Menon N., Mannering F., A statistical assessment of work-from-home participation during different stages of the COVID-19 pandemic, Transp. Res. Interdisc. Perspect., 11, (2021); Barrero J.M., Bloom N., Davis S.J., (2021); Batty M., The Morphology of the Post Pandemic City. University College London, Centre for Advanced Spatial Analysis, (2021); (2021); (2021); Beck M.J., Hensher D.A., Wei E., Slowly coming out of COVID-19 restrictions in Australia: Implications for working from home and commuting trips by car and public transport, J. Transp. Geogr., 88, (2020); Beria P., Lunkar V., Presence and mobility of the population during the first wave of Covid-19 outbreak and lockdown in Italy, Sustain. 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Home-based telecommuting and intra-household interactions in work and non-work travel: A seemingly unrelated censored regression approach, Transp. Res. A Policy Pract., 80, pp. 197-214, (2015); Korolevich S., (2022); Lachapelle U., Tanguay G.A., Neumark-Gaudet L., Telecommuting and sustainable travel: Reduction of overall travel time, increases in non-motorised travel and congestion relief?, Urban Stud., 55, 10, pp. 2226-2244, (2018); Lei L., Liu X., June 26). The COVID-19 pandemic and residential mobility intentions in the United States: Evidence from Google Trends data, Popul. Space Place, 28, (2022); Levy A., (2021); Liu S., Su Y.; Long C.; Lyons G., An assessment of teleworking as a practice for travel demand management, Proc. Inst. Civ. Eng. Transp., 129, 4, pp. 195-200, (1998); Menon N., Keita Y., Bertini R.L., Impact of COVID-19 on Travel Behavior and Shared Mobility Systems, (2020); (2021); Mokhtarian P.L., A synthetic approach to estimating the impacts of telecommuting on travel, Urban Stud., 35, 2, pp. 215-241, (1998); Molla R., (2021); Muller P.O., Transportation and Urban Form, The Geography of Urban Transportation, pp. 57-85, (2017); Neilson S., Sumida N., (2022); Oldham E., (2021); Ory D.T., Mokhtarian P.L., Which Came First, the Telecommuting or the Residential Relocation? An Empirical Analysis of Causality, (2007); (2021); Ramani A., Bloom N., (2021); Rivera M., Mullen S., Yi C., (2021); (2021); (2022); Shelburne P., Coleman J., (2022); Truong K., (2022); (2014); Varghese R., (2022)","S. Tan; San José State University, San José, One Washington Square, 95192, United States; email: simon.tan@sjsu.edu",null,"Elsevier Ltd",{"$nulls":5},2.5901982E7,null,null,null,"English","Transp.  Res.  Interdiscip.  Perspect.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85150455611"]
["Campisi T.; Russo A.; Bouhouras E.; Tesoriere G.; Basbas S.","Campisi, Tiziana (56866098200); Russo, Antonio (57271512800); Bouhouras, Efstathios (25627110400); Tesoriere, Giovanni (57201041875); Basbas, Socrates (6602806643)","56866098200; 57271512800; 25627110400; 57201041875; 6602806643","The Increase in E-commerce Purchases and the Impact on the Newest European City Logistics Development",2023.0,"Open Transportation Journal",17.0,null,"e26671212279047",null,null,null,0.0,"10.2174/0126671212279047231128105715","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85181936740&doi=10.2174%2f0126671212279047231128105715&partnerID=40&md5=d5fd982da2429e7795a3ace025d0e8b0","University of Enna Kore, Faculty of Engineering and Architecture, Cittadella Universitaria, Enna, 94100, Italy; Aristotle University of Thessaloniki, Faculty of Engineering, School of Rural and Surveying Engineering, Thessaloniki, GR54124, Greece","Campisi T., University of Enna Kore, Faculty of Engineering and Architecture, Cittadella Universitaria, Enna, 94100, Italy; Russo A., University of Enna Kore, Faculty of Engineering and Architecture, Cittadella Universitaria, Enna, 94100, Italy; Bouhouras E., Aristotle University of Thessaloniki, Faculty of Engineering, School of Rural and Surveying Engineering, Thessaloniki, GR54124, Greece; Tesoriere G., University of Enna Kore, Faculty of Engineering and Architecture, Cittadella Universitaria, Enna, 94100, Italy; Basbas S., Aristotle University of Thessaloniki, Faculty of Engineering, School of Rural and Surveying Engineering, Thessaloniki, GR54124, Greece","Background: In recent times, the advancement of urban logistics has encountered a series of pivotal challenges pertaining to the efficient distribution of goods and associated concerns such as congestion and pollution. In response, efforts have been directed towards identifying enhanced solutions. Notably, the growing development of electronic commerce of electronic commerce has underscored the necessity of devising viable approaches, both functionally and economically, to bolster the evolution of city logistics. The document focuses on a comparative analysis of e-commerce purchase demand data in Europe, focusing on two product macro-categories, namely clothing and e-grocery. It points out that the pandemic, but the health crisis has accelerated this practice. Objective: The acquired findings unequivocally validate the necessity for a fundamental reassessment of delivery transport methods, taking into account the perishability of materials, sustainable urban accessibility, and the incorporation of cutting-edge technologies. Methods: The comparison in the different European contexts and the different trends recorded with the variation of the macro product categories was defined by QGIS maps and they underline how some of the states have restored their context of demand for mobility while others have preferred online commerce by reducing physical movements. Results: Analysis of the available data revealed that between 2020 and 2022 e-commerce concerning clothing, online food purchase and home delivery these are the findings; for the clothing category,, the distribution remained very similar; for the online food purchase category, the situation is quite similar and for home delivery category of ready-to-eat restaurant and fast-food food, many countries exceeded percentages of 20%. Conclusion: This could lead to an improvement in urban mobility planning, prompting an integration of these issues within the Sustainable Urban Mobility Plans (SUMPs) and at the same time it would allow logistics service managers to be able to introduce more sustainable and efficient modal forms. © 2023 The Author(s).","City logistics; European e-commerce trend; First and last mile logistics; Healthy emergency; Pandemic; Sustainable mobility",{"$nulls":7},"Coccia M., COVID-19 pandemic over 2020 (with lockdowns) and 2021 (with vaccinations): Similar effects for seasonality and environmental factors, Environ. Res, 208, (2022); You G., The disturbance of urban mobility in the context of COVID-19 pandemic, Cities, 128, (2022); Lei L., Liu X., The COVID☐19 pandemic and residential mobility intentions in the United States: Evidence from Google Trends data, Popul. Space Place, 28, 6, (2022); von Homeyer I., Oberthur S., Dupont C., Implementing the European Green Deal during the evolving energy crisis, J. Common Mark. Stud, 60, S1, pp. 125-136, (2022); Charradi I., Campisi T., Tesoriere G., Abdallah K.B., A Holistic Approach to SUMP Strategies and Actions in the Post-pandemic and Energy Crisis Era, Computational Science and Its Applications, pp. 345-359, (2022); Na L., Yang L., Psychological and behavioral responses during the COVID-19 pandemic among individuals with mobility and/or self-care disabilities, Disabil. Health J, 15, 1, (2022); Campisi T., Basbas S., Trouva M., Papas T., Akgun-Tanbay N., Stamatiadis N., Tesoriere G., Anxiety, fear and stress feelings of road users during daily walking in COVID-19 pandemic: Sicilian cities, Transp. Res. Procedia, 62, pp. 107-114, (2022); Campisi T., Tesoriere G., Trouva M., Papas T., Basbas S., Impact of teleworking on travel behaviour during the COVID-19 era: the case of Sicily, Italy, Transp. Res. Procedia, 60, pp. 251-258, (2022); Marzano G., Zajac A., Emergency remote education and smart working at three European higher education institutions, Int. J. Web-Based Learn. Teach. Technol, 17, 6, pp. 1-22, (2021); Campisi T., Basbas S., Tanbay N.A., Georgiadis G., Some considerations on the key factors determining the reduction of public transport demand in Sicily during COVID-19 pandemic, Int. J. Transp. Dev. Integration, 6, 1, pp. 81-94, (2021); Campisi T., Russo A., Basbas S., Bouhouras E., Tesoriere G., A literature review of the main factors influencing the e-commerce and last-mile delivery projects during COVID-19 pandemic, Transp. Res. Procedia, 69, pp. 552-559, (2023); Bosehans G., Kavta K., Bell M.C., Dissanayake D., Exploring the potential of shared electric vehicles from e☐mobility hubs as an alternative for commute and food shopping trips, IET Intell. Transp. Syst, (2023); Pahwa A., Jaller M., Assessing last-mile distribution resilience under demand disruptions, Transp. Res., Part E Logist. Trans. Rev, 172, (2023); Garola G., Siragusa C., Seghezzi A., Mangiaracina R., Managing COVID-19 disruption: The response of express couriers and lessons learned to improve resilience, Int. J. Logist. Manag, 34, 7, pp. 121-141, (2023); Zhang Y., Kamargianni M., A review on the factors influencing the adoption of new mobility technologies and services: Autonomous vehicle, drone, micromobility and mobility as a service, Transp. Rev, 43, 3, pp. 407-429, (2023); Russo F., Sustainable Mobility as a Service: Dynamic models for agenda 2030 policies, Information, 13, 8, (2022); Campisi T., Garau C., Acampa G., Maltinti F., Canale A., Coni M., Developing flexible mobility on-demand in the era of mobility as a service: An overview of the italian context before and after pandemic, Computational Science and Its Applications, pp. 323-338, (2021); Campisi T., Garau C., Ignaccolo M., Coni M., Canale A., Inturri G., Torrisi V., A new vision on smart and resilient urban mobility in the aftermath of the pandemic: Key factors on european transport policies, Computational science and its applications, pp. 603-618, (2021); Vitkauskaite E., Vaiciukynaite E., Comparative study of business models of European micro-mobility online services, Proceedings of The 20th International Conference on Electronic Business, pp. 55-62; Campisi T., Russo A., Basbas S., Politis I., Bouhouras E., Tesoriere G., Assessing the evolution of urban planning and last mile delivery in the era of E-commerce, Conference on Sustainable Urban Mobility, pp. 1253-1265; Kiba-Janiak M., Cheba K., Witkowski J., Jagoda A., Skowronska A., Kolakowski T., Mucowska M., Sustainable city logistics of last-mile delivery and returns on the e-commerce market”, Various Groups of Stakeholders’ Perspectives–Aims and Scope of the Project, ACC Journal, (2022); Russo F., Comi A., The role of city logistics in pursuing the goals of agenda 2030, International Conference on Computational Science and Its Applications, pp. 335-348; Rosales R., Haarstad H., Governance challenges for urban logistics: Lessons from three N orwegian cities, Environ. Policy Gov, 33, 3, pp. 221-231, (2023); Niranjanamurthy M., Kavyashree N., Jagannath S., Chahar D., Analysis of e-commerce and m-commerce: Advantages, limitations and security issues, Int. J. Adv. Res. Comput. Commun. Eng, 2, 6, pp. 2360-2370, (2013); Correia D., Vagos C., Marques J. L., Teixeira L., Fulfilment of last-mile urban logistics for sustainable and inclusive smart cities: A case study conducted in Portugal, Int. J. Logist. Res, pp. 1-28, (2023); Vinerean S., Budac C., Baltador L.A., Dabija D.C., Assessing the effects of the COVID-19 pandemic on M-commerce adoption: An adapted UTAUT2 approach, Electronics, 11, 8, (2022); Kourouthanasassis P., Giaglis G., Introduction to the special issue mobile commerce; The past, present, and future of mobile commerce research, Int. J. Electron. Commer, 16, 4, pp. 5-18, (2012); Du S., Li H., The knowledge mapping of mobile commerce research: A visual analysis based on I-Model, Sustainability, 11, 6, (2019); Ashraf A.R., Thongpapanl N.T., Menguc B., Northey G., The role of M-commerce readiness in emerging and developed markets, J. Int. Mark, 25, 2, pp. 25-51, (2017); The impact of e-coomerce on trasnport in Europe and possible actions to be taken to meet increased demand; Soava G., Mehedintu A., Sterpu M., Analysis and forecast of the use of E-commerce in enterprises of the European Union States, Sustainability, 14, 14, (2022); Hung B.Q., Nham N.T.H., Ha L.T., The importance of digitalization in powering environmental innovation performance of European countries, Journal of Innovation & Knowledge, 8, 1, (2023); Ha L.T., Are digital business and digital public services a driver for better energy security? Evidence from a European sample, Environ. Sci. Pollut. Res. Int, 29, 18, pp. 27232-27256, (2022); Kwilinski A., Lyulyov O., Pimonenko T., Environmental sustainability within attaining sustainable development goals: The role of digitalization and the transport sector, Sustainability, 15, 14, (2023); Schoder D., Ding F., Campos J.K., The impact of e-commerce development on urban logistics sustainability, Open Journal of Social Sciences, 4, 3, pp. 1-6, (2016); Bachofner M., Lemardele C., Estrada M., Pages L., City logistics: Challenges and opportunities for technology providers, Journal of Urban Mobility, 2, (2022); Argiles-Bosch J.M., Garcia-Blandon J., Ravenda D., Cost behavior in e-commerce firms, Electron. Commerce Res, pp. 1-34, (2022); Lone S., Weltevreden J.W.J., 2022 European E-commerce Report, (2022); E-commerce continues to grow in the EU; Eskandaripour H., Boldsaikhan E., Last-mile drone delivery: Past, present, and future, Drones, 7, 2, (2023); Yanpirat N., Silva D.F., Smith A.E., Sustainable last mile parcel delivery and return service using drones, Eng. Appl. Artif. Intell, 124, (2023); Nikolic M., Netjasov F., Crnogorac D., Milenkovic M., Glavic D., Urban air mobility: Multi-objective mixed integer programming model for solving the drone scheduling problem, International Conference on Computational Science and Its Applications, pp. 349-362; EUROSTAT, Internet purchases – goods of services; Keszka J., The Only 2 Reasons Why People Buy; QGIS Geographic Information System, (2023); Layer openstreet map (OpenStreetMap contributors","A. Russo; University of Enna Kore, Faculty of Engineering and Architecture, Cittadella Universitaria, Enna, 94100, Italy; email: tiziana.campisi@unikore.it",null,"Bentham Science Publishers",{"$nulls":5},1.8744478E7,null,null,null,"English","Open Transp. J.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85181936740"]
["Fontaine P.; Minner S.; Schiffer M.","Fontaine, Pirmin (56377230600); Minner, Stefan (6602630441); Schiffer, Maximilian (57193122624)","56377230600; 6602630441; 57193122624","Smart and sustainable city logistics: Design, consolidation, and regulation",2023.0,"European Journal of Operational Research",307.0,3.0,null,1071.0,1084.0,13.0,15.0,"10.1016/j.ejor.2022.09.022","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85139724358&doi=10.1016%2fj.ejor.2022.09.022&partnerID=40&md5=ca8cc12564f9d6debfcddf3f86985558","Catholic University of Eichstätt-Ingolstadt, Ingolstadt School of Management, Auf der Schanz 49, Ingolstadt, 85049, Germany; TUM School of Management & Munich Data Science Institute, Technical University of Munich, Munich, 80333, Germany","Fontaine P., Catholic University of Eichstätt-Ingolstadt, Ingolstadt School of Management, Auf der Schanz 49, Ingolstadt, 85049, Germany; Minner S., TUM School of Management & Munich Data Science Institute, Technical University of Munich, Munich, 80333, Germany; Schiffer M., TUM School of Management & Munich Data Science Institute, Technical University of Munich, Munich, 80333, Germany","Growing e-commerce delivery increases traffic congestion and demands for smart last-mile city distribution systems. In this context, municipalities and logistics service providers aim towards sustainable and profitable city logistics, which are often conflicting goals. Whether to use single-echelon or two-echelon systems with micro-depots and city freighters as well as quantifying the benefits of shipment consolidation between independent providers under different system designs are unanswered questions in academia and practice. We provide a general methodological framework based on continuous approximation theory to study the design of city logistics networks with multiple logistics service providers that choose transportation strategies, each defined by a network structure and specific transportation modes. We provide analytical results on the comparison of different transportation strategies. By providing thresholds on the benefit of consolidated systems, we analytically quantify shipment consolidation effects in city centers. We then embed this continuous approximation into a mixed-integer non-linear program and study parameter sensitivities for a real-world case study. Our results show that higher customer density and longer distances between depots and distribution areas promote 2-tier transportation strategies. Consolidation between logistics service providers allows for emission reductions independent of the transportation strategy and correlate with cost reductions up to 50% on the lower echelon. Outsourcing promotes 2-tier last-mile deliveries with city freighters and in a city with heterogeneous districts, it is beneficial to use a hybrid network that includes both single- and two-echelon strategies using multiple transportation modes for different demand classes. © 2022 Elsevier B.V.","City logistics; Consolidation; Continuous approximation; Logistics","Approximation theory; Cost reduction; Emission control; Integer programming; Internet service providers; Linear programming; Ships; Traffic congestion; City distribution; City logistics; Continous approximation; Distribution systems; E- commerces; Last mile; Logistics service provider; Sustainable cities; Transportation mode; Transportation strategies; Nonlinear programming",{"$nulls":4},"German Federal Ministry for Digital and Transport; NRVP","The authors thank the reviewers for their constructive comments, which helped to improve this paper. The paper was partially funded by the German Federal Ministry for Digital and Transport within the National Cycling Plan 2020 (NRVP). ","Alptekinoglu A., Banerjee A., Paul A., Jain N., Inventory pooling to deliver differentiated service, Manufacturing & Service Operations Management, 15, 1, pp. 33-44, (2013); Beardwood J., Halton J., Hammersley J., The shortest path through many points, Mathematical Proceedings of the Cambridge Philosophical Society, 55, 4, pp. 299-327, (1959); Benjelloun A., Crainic T., Bigras Y., Towards a taxonomy of city logistics projects, Procedia - Social and Behavioral Sciences, 2, 3, pp. 6217-6228, (2010); Brotcorne L., Perboli G., Rosano M., Wei Q., A managerial analysis of urban parcel delivery: A lean business approach, Sustainability, 11, 12, (2019); Carlsson J., Jia F., Continuous facility location with backbone network costs, Transportation Science, 49, 3, pp. 433-451, (2015); Crainic T.G., Ricciardi N., Storchi G., Models for evaluating and planning city logistics systems, Transportation Science, 43, 4, pp. 432-454, (2009); Daganzo C., The length of tours in zones of different shapes, Transportation Research Part B: Methodological, 18, 2, pp. 135-145, (1984); Daganzo C., Logistics systems analysis, (2005); Daganzo C.F., The distance traveled to visit n points with a maximum of c stops per vehicle: An analytic model and an application, Transportation Science, 18, 4, pp. 331-350, (1984); Davis B.A., Figliozzi M.A., A methodology to evaluate the competitiveness of electric delivery trucks, Transportation Research Part E: Logistics and Transportation Review, 49, 1, pp. 8-23, (2013); (2019); (2011); Figliozzi M., Planning approximations to the average length of vehicle routing problems with varying customer demands and routing constraints, Transportation Research Record, 2089, 1, pp. 1-8, (2008); Figliozzi M.A., Planning approximations to the average length of vehicle routing problems with time window constraints, Transportation Research Part B: Methodological, 43, 4, pp. 438-447, (2009); Franceschetti A., Jabali O., Laporte L., Continuous approximation models in freight distribution management, TOP, 25, 3, pp. 413-433, (2017); Francis P., Smilowitz K., Modeling techniques for periodic vehicle routing problems, Transportation Research Part B: Methodological, 40, 10, pp. 872-884, (2006); Ghaffarinasab N., Van Woensel T., Minner S., A continuous approximation approach to the planar hub location-routing problem: Modeling and solution algorithms, Computers & Operations Research, 100, pp. 140-154, (2018); Hasija S., Shen Z.-J.M., Teo C.-P., Smart city operations: Modeling challenges and opportunities, Manufacturing & Service Operations Management, 22, 1, pp. 203-213, (2020); He L., Mak H.-Y., Rong Y., Shen Z.-J.M., Service region design for urban electric vehicle sharing systems, Manufacturing & Service Operations Management, 19, 2, pp. 309-327, (2017); Jabali O., Gendreau M., Laporte G., A continuous approximation model for the fleet composition problem, Transportation Research Part B: Methodological, 46, 10, pp. 1591-1606, (2012); Janjevic M., Merchan D., Winkenbach M., Designing multi-tier, multi-service-level, and multi-modal last-mile distribution networks for omni-channel operations, European Journal of Operational Research, 294, 3, pp. 1059-1077, (2021); Kurte K.E.-C.O.N.S.U.L.T., (2018); (2020); Li B., Krushinsky D., Reijers H., Van Woensel T., The share-a-ride problem: People and parcels sharing taxis, European Journal of Operational Research, 238, 1, pp. 31-40, (2014); Mak H.-Y., Enabling smarter cities with operations management, Manufacturing & Service Operations Management, (2020); Merchan D., Winkenbach M., An empirical validation and data-driven extension of continuum approximation approaches for urban route distances, Networks, 73, 4, pp. 418-433, (2019); Mourad A., Puchinger J., Chu C., A survey of models and algorithms for optimizing shared mobility, Transportation Research Part B: Methodological, 123, pp. 323-346, (2019); Perboli G., Rosano M., Parcel delivery in urban areas: Opportunities and threats for the mix of traditional and green business models, Transportation Research Part C: Emerging Technologies, 99, pp. 19-36, (2019); (2018); Qi W., Li L., Liu S., Shen Z.-J.M., Shared mobility for last mile delivery: Design, operational prescriptions and environmental impact, Manufacturing & Service Operations Management, 20, 4, pp. 737-751, (2018); Savelsbergh M., Van Woensel T., City logistics: Challenges and opportunities, Transportation Science, 50, 2, pp. 579-590, (2016); Sheth M., Butrina P., Goodchild A., McCormack E., Measuring delivery route cost trade-offs between electric-assist cargo bicycles and delivery trucks in dense urban areas, European Transport Research Review, 11, 1, (2019); (2017); (2020); (2018); Winkenbach M., Kleindorfer P.R., Spinler S., Enabling urban logistics services at la poste through multi-echelon location-routing, Transportation Science, 50, 2, pp. 520-540, (2016); Xie W., Ouyang Y., Optimal layout of transshipment facility locations on an infinite homogeneous plane, Transportation Research Part B: Methodological, 75, pp. 74-88, (2015)","P. Fontaine; Catholic University of Eichstätt-Ingolstadt, Ingolstadt School of Management, Ingolstadt, Auf der Schanz 49, 85049, Germany; email: pirmin.fontaine@ku.de",null,"Elsevier B.V.",{"$nulls":5},3772217.0,null,"EJORD",null,"English","Eur J Oper Res","Article","Final",null,"Scopus","2-s2.0-85139724358"]
["Bigdellou S.; Aslani S.; Modarres M.","Bigdellou, Saeide (57312017700); Aslani, Shirin (36805590200); Modarres, Mohammad (58851261700)","57312017700; 36805590200; 58851261700","Sustainable Trade Promotions in Case of Negative Demand Disruption in E-Commerce",2023.0,"Sustainability (Switzerland)",15.0,3.0,2320.0,null,null,null,0.0,"10.3390/su15032320","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85148020090&doi=10.3390%2fsu15032320&partnerID=40&md5=63a9e82bb277d0fba4edd7dd955ed92d","Department of Industrial Engineering, Sharif University of Technology, Tehran, 11365/8639, Iran; Graduate School of Management and Economics, Sharif University of Technology, Tehran, 11365/8639, Iran","Bigdellou S., Department of Industrial Engineering, Sharif University of Technology, Tehran, 11365/8639, Iran; Aslani S., Graduate School of Management and Economics, Sharif University of Technology, Tehran, 11365/8639, Iran; Modarres M., Department of Industrial Engineering, Sharif University of Technology, Tehran, 11365/8639, Iran","In this research, we examine the impact of a negative demand disruption on trade promotions strategy, where suppliers offer discounted prices to online supply chain retailers. To analyze the various factors that affect trade promotion strategies, we develop a Stackelberg game model to determine the optimal pricing for both manufacturers and retailers, as well as the optimal order quantity of the retailers. Our findings indicate that through an appropriate sustainable trade promotion policy, the profit of the supply chain’s members can be increased in different scenarios, including various product disposal costs and the time of product delivery. In addition to the trade promotion policies, we consider a new strategy where the manufacturer assists the retailer by paying some part of the delivery cost. Then, we compare these strategies to determine which approach leads to the highest profit for the manufacturer, retailer, and integrated supply chain under the different intensities of negative demand disruption. © 2023 by the authors.","demand disruption; lead time-dependent demand; sustainability; trade promotion","electronic commerce; policy approach; profitability; strategic approach; sustainability; trade policy",{"$nulls":6},"Mu Z., Zheng Y., Sun H., Cooperative Green Technology Innovation of an E-Commerce Sales Channel in a Two-Stage Supply Chain, Sustainability, 13, (2021); Jaller M., Pahwa A., Evaluating the Environmental Impacts of Online Shopping: A Behavioral and Transportation Approach, Transp. Res. Part D Transp. Environ, 80, (2020); Wygonik E., Goodchild A.V., Urban Form and Last-Mile Goods Movement: Factors Affecting Vehicle Miles Travelled and Emissions, Transp. Res. Part D Transp. Environ, 61, pp. 217-229, (2018); Dan B., Xu G., Liu C., Pricing Policies in a Dual-Channel Supply Chain with Retail Services, Int. J. Prod. Econ, 139, pp. 312-320, (2012); Su Y., Geunes J., Multi-Period Price Promotions in a Single-Supplier, Multi-Retailer Supply Chain under Asymmetric Demand Information, Ann. Oper. Res, 211, pp. 447-472, (2013); Wu J., Chen Z., Ji X., Sustainable Trade Promotion Decisions under Demand Disruption in Manufacturer-Retailer Supply Chains, Ann. Oper. Res, 290, pp. 115-143, (2020); Cui T.H., Raju J.S., Zhang Z.J., A Price Discrimination Model of Trade Promotions, Mark. Sci, 27, pp. 779-795, (2008); Chen J., Bell P.C., The Impact of Customer Returns on Supply Chain Decisions under Various Channel Interactions, Ann. Oper. Res, 206, pp. 59-74, (2013); Chen X., Wang A., Trade Credit Contract with Limited Liability in the Supply Chain with Budget Constraints, Ann. Oper. Res, 196, pp. 153-165, (2012); Varadarajan P., Horizontal Cooperative Sales Promotion: A Framework for Classification and Additional Perspectives, J. Mark, 50, pp. 61-73, (1986); Wakefield K.L., Barnes J.H., Retailing Hedonic Consumption: A Model of Sales Promotion of a Leisure Service, J. Retail, 72, pp. 409-427, (1996); Wu S., Liu Q., Zhang R.Q., The Reference Effects on a Retailer’s Dynamic Pricing and Inventory Strategies with Strategic Consumers, Oper. Res, 63, pp. 1320-1335, (2015); Yuan H., Gomez M.I., Rao V.R., Trade Promotion Decisions under Demand Uncertainty: A Market Experiment Approach, Manage. Sci, 59, pp. 1709-1724, (2013); Iordache Platis M., Olteanu C., Hotoi A.L., Evolution of the Online Sales of Sustainable Products in the COVID-19 Pandemic, Sustainability, 14, (2022); Kurata H., Yue X., Trade Promotion Mode Choice and Information Sharing in Fashion Retail Supply Chains, Int. J. Prod. Econ, 114, pp. 507-519, (2008); Tantiwattanakul P., Dumrongsiri A., Multi-Period Supply Chain Coordination Using Trade Promotion: Complementary Slackness Approach, Int. J. Ind. Eng, 26, (2019); Bambal A., Kumar S., Abraham J., Design of Trade Promotion to Maximize Overall Supply Chain Profitability Using Mathematical Optimization, Proceedings of the 2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO), pp. 1-6; Li Y., Khouja M.J., Pan J., Zhou J., Buy-One-Get-One Promotions in a Two-Echelon Supply Chain, Manage. Sci, (2022); Yang L., Wang G., Ke C., Remanufacturing and Promotion in Dual-Channel Supply Chains under Cap-and-Trade Regulation, J. Clean. Prod, 204, pp. 939-957, (2018); Cai G.G., Zhang Z.G., Zhang M., Game Theoretical Perspectives on Dual-Channel Supply Chain Competition with Price Discounts and Pricing Schemes, Int. J. Prod. Econ, 117, pp. 80-96, (2009); Tsao Y.-C., Sheen G.-J., Effects of Promotion Cost Sharing Policy with the Sales Learning Curve on Supply Chain Coordination, Comput. Oper. Res, 39, pp. 1872-1878, (2012); Modak N.M., Panda S., Sana S.S., Three-Echelon Supply Chain Coordination Considering Duopolistic Retailers with Perfect Quality Products, Int. J. Prod. Econ, 182, pp. 564-578, (2016); Tsao Y.-C., Lu J.-C., Trade Promotion Policies in Manufacturer-Retailer Supply Chains, Transp. Res. Part E Logist. Transp. Rev, 96, pp. 20-39, (2016); Yao D.-Q., Yue X., Wang X., Liu J.J., The Impact of Information Sharing on a Returns Policy with the Addition of a Direct Channel, Int. J. Prod. Econ, 97, pp. 196-209, (2005); Yang J.Q., Zhang X.M., Fu H.Y., Liu C., Inventory Competition in a Dual-Channel Supply Chain with Delivery Lead Time Consideration, Appl. Math. Model, 42, pp. 675-692, (2017); Jabbour C.J.C., Janeiro R.C., de Sousa Jabbour A.B.L., Junior J.A.G., Salgado M.H., Jugend D., Social Aspects of Sustainable Supply Chains: Unveiling Potential Relationships in the Brazilian Context, Ann. Oper. Res, 290, pp. 327-341, (2020); Johansson L., Olsson F., Quantifying Sustainable Control of Inventory Systems with Non-Linear Backorder Costs, Ann. Oper. Res, 259, pp. 217-239, (2017); Ji X., Wu J., Liang L., Zhu Q., The Impacts of Public Sustainability Concerns on Length of Product Line, Eur. J. Oper. Res, 269, pp. 16-23, (2018); Li Y., Zhou J., Sustainable Supplier’s Equilibrium Discount Strategy under Random Demand, Sustainability, 14, (2022); Modak N.M., Kelle P., Managing a Dual-Channel Supply Chain under Price and Delivery-Time Dependent Stochastic Demand, Eur. J. Oper. Res, 272, pp. 147-161, (2019); Cachon G.P., Netessine S., Game Theory in Supply Chain Analysis, Model. Methods Appl. Innov. Decis. Mak, 23, pp. 200-233, (2006); Desiraju R., Moorthy S., Managing a Distribution Channel under Asymmetric Information with Performance Requirements, Manage. Sci, 43, pp. 1628-1644, (1997); Savaskan R.C., Van Wassenhove L.N., Reverse Channel Design: The Case of Competing Retailers, Manage. Sci, 52, pp. 1-14, (2006); Pellegrino R., Costantino N., Tauro D., Advance Purchase Discounts for Supply Chain Finance System Coordination, Sustainability, 12, (2020); Nair G., Pleasance D., Mitigating Channel Conflict, McKinsey Q, 3, pp. 16-17, (2005)","S. Aslani; Graduate School of Management and Economics, Sharif University of Technology, Tehran, 11365/8639, Iran; email: sh.aslani@sharif.edu",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85148020090"]
["Kumar S.; Sheu J.-B.; Kundu T.","Kumar, Suryakant (58141523900); Sheu, Jiuh-Biing (7201928686); Kundu, Tanmoy (57193643395)","58141523900; 7201928686; 57193643395","Planning a parts-to-picker order picking system with consideration of the impact of perceived workload",2023.0,"Transportation Research Part E: Logistics and Transportation Review",173.0,null,103088.0,null,null,null,1.0,"10.1016/j.tre.2023.103088","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85150028490&doi=10.1016%2fj.tre.2023.103088&partnerID=40&md5=932b71f4ce74c7759a70332495cc5582","Department of Business Administration, National Taiwan University, Taipei, Taiwan; School of Management and Entrepreneurship, Indian Institute of Technology Jodhpur, India","Kumar S., Department of Business Administration, National Taiwan University, Taipei, Taiwan; Sheu J.-B., Department of Business Administration, National Taiwan University, Taipei, Taiwan; Kundu T., School of Management and Entrepreneurship, Indian Institute of Technology Jodhpur, India","In the digital age, coordinating robots and humans is critical in e-commerce warehousing. Motivated by observed industrial practices, this study presents a queueing theory based analytical model to investigate the planning issue of robot-human coordination in a parts-to-picker warehousing system. The critical planning decisions involve finding the optimal number of robots in the warehouse, the expected number of robots at essential locations of the warehouse, and performance analysis of the order picking system. A distinctive feature of this study is the conceptualization of a human factor called perceived workload (which depends on the number of robots) in the order picking planning model for efficient order fulfillment. Our analyses interestingly suggest that deploying more robots in warehouses with a parts-to-picker system does not necessarily increase the warehousing system's performance; instead, a trade-off exists. Additionally, the workload-dependent service rate significantly influences the robots queueing in front of the order picking station (internal queue) and the synchronization station (external queue) in the warehouse. More importantly, this work contributes to the design of a human-centric work environment for parts-to-picker order fulfillment system. © 2023 Elsevier Ltd","E-commerce; Order picking system; Parts-to-picker; Queueing theory; Robot-human coordination; Smart warehouses","Economic and social effects; Electronic commerce; Robot programming; Warehouses; Digital age; E- commerces; Industrial practices; Order fulfillment; Order-picking; Order-picking systems; Part-to-picker; Robot-human coordination; Smart warehouse; Warehousing systems; analytical framework; electronic commerce; logistics; numerical model; planning system; robotics; theoretical study; Queueing theory",{"$nulls":4},"Ministry of Science and Technology, Taiwan, MOST, (109-2410-H-002-076-MY3)","This research is supported by grant MOST 109-2410-H-002-076-MY3 from Ministry of Science and Technology of Taiwan, R.O.C. The authors also wish to thank the editors and referees for their helpful comments and suggestions. Any errors or omissions remain the sole responsibility of the authors. ","(2018); (2019); (2022); Azadeh K., de Koster R., Roy D., Robotized and automated warehouse systems: review and recent developments, Transp. Sci., 53, pp. 917-945, (2019); Azadeh K., Roy D., de Koster R., Design, modeling, and analysis of vertical robotic storage and retrieval systems, Transp. Sci., 53, pp. 1213-1234, (2019); Azadeh K., Roy D., de Koster M.B.M.R., Dynamic policies for resource reallocation in a robotic mobile fulfillment system with time-varying demand, Eur. J. Oper. Res., (2020); Battini D., Calzavara M., Persona A., Sgarbossa F., Additional effort estimation due to ergonomic conditions in order picking systems, Int. J. Prod. Res., 55, pp. 2764-2774, (2017); Battini D., Glock C.H., Grosse E.H., Persona A., Sgarbossa F., Human energy expenditure in order picking storage assignment: A bi-objective method, Comput. Ind. 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Manag., 64, pp. 83-93, (2017)","J.-B. Sheu; Department of Business Administration, National Taiwan University, Taipei, Taiwan; email: jbsheu@ntu.edu.tw",null,"Elsevier Ltd",{"$nulls":5},1.3665545E7,null,null,null,"English","Transp. Res. Part E Logist. Transp. Rev.","Article","Final",null,"Scopus","2-s2.0-85150028490"]
["Wu W.; Shen L.; Zhao Z.; Harish A.R.; Zhong R.Y.; Huang G.Q.","Wu, Wei (57211855654); Shen, Leidi (57202985842); Zhao, Zhiheng (57192180873); Harish, Arjun Rachana (57215021978); Zhong, Ray Y. (55353690000); Huang, George Q. (7403425048)","57211855654; 57202985842; 57192180873; 57215021978; 55353690000; 7403425048","Internet of Everything and Digital Twin enabled Service Platform for Cold Chain Logistics",2023.0,"Journal of Industrial Information Integration",33.0,null,100443.0,null,null,null,14.0,"10.1016/j.jii.2023.100443","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85149318292&doi=10.1016%2fj.jii.2023.100443&partnerID=40&md5=619e0a86bd963e8a8dbc5efde36fb65c","College of Mechanical and Vehicle Engineering, Chongqing University, P.R, Chongqing, China; Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong, Hong Kong; Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong, Hong Kong","Wu W., College of Mechanical and Vehicle Engineering, Chongqing University, P.R, Chongqing, China; Shen L., Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong, Hong Kong; Zhao Z., Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong, Hong Kong; Harish A.R., Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong, Hong Kong; Zhong R.Y., Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong, Hong Kong; Huang G.Q., Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong, Hong Kong","The proliferation of the e-commerce market has posed challenges to staff safety, product quality, and operational efficiency, especially for cold chain logistics (CCL). Recently, the logistics of vaccine supply under the worldwide COVID-19 pandemic rearouses public attention and calls for innovative solutions to tackle the challenges remaining in CCL. Accordingly, this study proposes a cyber-physical platform framework applying the Internet of Everything (IoE) and Digital Twin (DT) technologies to promote information integration and provide smart services for different stakeholders in the CCL. In the platform, reams of data are generated, gathered, and leveraged to interconnect and digitalize physical things, people, and processes in cyberspace, paving the way for digital servitization. Deep learning techniques are used for accident identification and indoor localization based on Bluetooth Low Energy (BLE) to actualize real-time staff safety supervision in the cold warehouse. Both algorithms are designed to take advantage of the IoE infrastructure to achieve online self-adapting in response to surrounding evolutions. Besides, with the help of mobile and desktop applications, paperless operation for shipment, remote temperature and humidity (T&H) monitoring, anomaly detection and warning, and customer interaction are enabled. Thus, information traceability and visibility are highly fortified in this way. Finally, a real-life case study is conducted in a pharmaceutical distribution center to demonstrate the feasibility and practicality of the proposed platform and methods. The dedicated hardware and software are developed and deployed on site. As a result, the effectiveness of staff safety management, operational informatization, product quality assurance, and stakeholder loyalty maintenance shows a noticeable improvement. The insights and lessons harvested in this study may spark new ideas for researchers and inspire practitioners to meet similar needs in the industry. © 2023 Elsevier Inc.","Abnormal stationary detection; Cold chain logistics; Digital twin; Indoor positioning; Internet of everything; Service platform","Anomaly detection; Human resource management; Indoor positioning systems; Internet of Everything; Learning systems; Quality assurance; Web services; Abnormal stationary detection; Cold chain logistics; E- commerces; Indoor positioning; Innovative solutions; Operational efficiencies; Products quality; Safety products; Service platforms; Vaccine supplies; Deep learning",{"$nulls":4},"RGC, (T32-707-22-N)","This work is partially supported by grants from RGC HK TRS (Project No.: T32-707-22-N ).","Dai J., Che W., Lim J.J., Shou Y., Service innovation of cold chain logistics service providers: a multiple-case study in China, Ind. Mark. 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Comput., (2019)","G.Q. Huang; Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong, Hong Kong; email: gq.huang@polyu.edu.hk",null,"Elsevier B.V.",{"$nulls":5},"2452414X",null,null,null,"English","J.  Ind. Infor. Integr.","Article","Final","All Open Access; Bronze Open Access; Green Open Access","Scopus","2-s2.0-85149318292"]
["Di Gangi M.; Polimeni A.; Belcore O.M.","Di Gangi, Massimo (57200152615); Polimeni, Antonio (23486747400); Belcore, Orlando Marco (57217013834)","57200152615; 23486747400; 57217013834","Freight Distribution in Small Islands: Integration between Naval Services and Parcel Lockers",2023.0,"Sustainability (Switzerland)",15.0,9.0,7535.0,null,null,null,2.0,"10.3390/su15097535","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85159347563&doi=10.3390%2fsu15097535&partnerID=40&md5=8f9138ec6de4c9aee71cd1de4be1296e","Department of Engineering, University of Messina, Contr. di Dio—Villaggio S. Agata, Messina, 98166, Italy","Di Gangi M., Department of Engineering, University of Messina, Contr. di Dio—Villaggio S. Agata, Messina, 98166, Italy; Polimeni A., Department of Engineering, University of Messina, Contr. di Dio—Villaggio S. Agata, Messina, 98166, Italy; Belcore O.M., Department of Engineering, University of Messina, Contr. di Dio—Villaggio S. Agata, Messina, 98166, Italy","Freight transportation in urban areas represents an essential activity from the standpoint of economic development; in recent years, the spread of e-commerce (also accelerated by COVID-19) has contributed to increasing the demand for freight distribution over short distances. In most cities, the approaches and measures are often based on new technologies. Nevertheless, today there are contexts wherein delivery operations represent critical tasks to be solved. Furthermore, low accessibility areas, such as small islands, present further problems due to their exclusive dependence on maritime links (and often low-reliability services). This paper tackles this topic, formulating and solving a distribution problem by linking shipping services with last-mile distribution operated by means of an automatic delivery service (parcel lockers). A test application is proposed by considering the small island of Lipari in the archipelago of the Aeolian islands (Sicily, Southern Italy). The results show that such a type of service could reduce the user’s waiting time when compared to traditional home deliveries. © 2023 by the authors.","city logistics; e-commerce; freight distribution; freight transport; last mile distribution; naval services; parcel lockers",{"$nulls":7},"E-Commerce Statistics for Individuals; Taniguchi E., Thompson R.G., Qureshi A.G., Recent Developments and Prospects for Modeling City Logistics, City Logistics 1, pp. 1-27, (2018); Russo F., Comi A., A Classification of City Logistics Measures and Connected Impacts, Procedia-Soc. Behav. Sci, 2, pp. 6355-6365, (2010); Russo F., Comi A., Investigating the Effects of City Logistics Measures on the Economy of the City, Sustainability, 12, (2020); Taniguchi E., Concepts of City Logistics for Sustainable and Liveable Cities, Procedia-Soc. Behav. Sci, 151, pp. 310-317, (2014); Buldeo Rai H., Verlinde S., Macharis C., City Logistics in an Omnichannel Environment. The Case of Brussels, Case Stud. Transp. Policy, 7, pp. 310-317, (2019); Russo F., Comi A., A Model System for the Ex-Ante Assessment of City Logistics Measures, Res. Transp. Econ, 31, pp. 81-87, (2011); Akgun E.Z., Monios J., Fonzone A., Supporting Urban Consolidation Centres with Urban Freight Transport Policies: A Comparative Study of Scotland and Sweden, Int. J. Logist. Res. Appl, 23, pp. 291-310, (2020); Musolino G., Rindone C., Polimeni A., Vitetta A., Planning Urban Distribution Center Location with Variable Restocking Demand Scenarios: General Methodology and Testing in a Medium-Size Town, Transp. Policy, 80, pp. 157-166, (2019); Coppola P., Silvestri F., Assessing the Impacts of E-Commerce on Future Urban Logistics Scenarios: Case Study of the City of Rome, Int. J. Transp. Econ, 48, pp. 339-358, (2021); Teo J.S.E., Taniguchi E., Qureshi A.G., Evaluation of Urban Distribution Centers Using Multiagent Modeling with Geographic Information Systems, Transp. Res. Rec, 2478, pp. 35-47, (2015); Juvvala R., Sarmah S.P., Evaluation of Policy Options Supporting Electric Vehicles in City Logistics: A Case Study, Sustain. Cities Soc, 74, (2021); Napoli G., Micari S., Dispenza G., Andaloro L., Antonucci V., Polimeni A., Freight Distribution with Electric Vehicles: A Case Study in Sicily. RES, Infrastructures and Vehicle Routing, Transp. Eng, 3, (2021); Polimeni A., Vitetta A., Urban Transport Planning and Energy Resources: Electric Vehicle Routing with Reliable Link Travel Times, WIT Trans. Ecol. Environ, 238, pp. 653-661, (2019); de Oliveira L.K., Macedo A.D.R., Sampaio J.C.L., de Oliveira T.D.P.M., de Oliveira R.L.M., Vieira J.G.V., Challenges to Urban Freight Transport in Historical Cities: A Case Study for Sabará (Brazil), Transp. Res. 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Res. Procedia, 47, pp. 425-432, (2020); Belcore O.M., Discrete Choice Model Assessing Attitudes Effects on Decisions: An Exploratory Modelling Approach, Based on Empirical Choice Observation to Analyse Households, Ph.D. Thesis, (2020); Schaefer J.S., Figliozzi M.A., Spatial Accessibility and Equity Analysis of Amazon Parcel Lockers Facilities, J. Transp. Geogr, 97, (2021)","M. Di Gangi; Department of Engineering, University of Messina, Messina, Contr. di Dio—Villaggio S. Agata, 98166, Italy; email: massimo.digangi@unime.it",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85159347563"]
["Dong C.; Huang Q.; Pan Y.; Ng C.T.; Liu R.","Dong, Ciwei (56612672900); Huang, Qianzhi (58062423400); Pan, Yuqing (57458824800); Ng, Chi To (58605566600); Liu, Renjun (57201550128)","56612672900; 58062423400; 57458824800; 58605566600; 57201550128","Logistics outsourcing: Effects of greenwashing and blockchain technology",2023.0,"Transportation Research Part E: Logistics and Transportation Review",170.0,null,103015.0,null,null,null,10.0,"10.1016/j.tre.2023.103015","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85146167689&doi=10.1016%2fj.tre.2023.103015&partnerID=40&md5=851abb6eaa104abdd69852e4e59a8ab1","School of Business Administration, Zhongnan University of Economic and Law, Wuhan, 430073, China; Logistics Research Centre, Department of Logistics and Maritime Studies, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong","Dong C., School of Business Administration, Zhongnan University of Economic and Law, Wuhan, 430073, China; Huang Q., School of Business Administration, Zhongnan University of Economic and Law, Wuhan, 430073, China; Pan Y., Logistics Research Centre, Department of Logistics and Maritime Studies, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong; Ng C.T., Logistics Research Centre, Department of Logistics and Maritime Studies, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong; Liu R., School of Business Administration, Zhongnan University of Economic and Law, Wuhan, 430073, China","In this paper, we study the logistics outsourcing strategy of a manufacturer with regard to green logistics, greenwashing, and blockchain. The manufacturer sells its products through an e-commerce platform, which has self-built logistics service. To transport the products to the customers, the manufacturer can choose to outsource this logistics service to the e-commerce platform or a third-party logistics (3PL) firm. The e-commerce platform and 3PL firm are called logistics firms in this paper. Both logistics firms consider investing in green logistics activities and may involve in greenwashing behavior. We show that outsourcing to the e-commerce platform is more beneficial for the manufacturer, no matter whether the logistics firms pursue greenwashing. Moreover, whether the logistics firms pursue greenwashing depends on both the probability that the greenwashing behavior is exposed and the corresponding penalty for greenwashing. Although adopting blockchain has the potential to prevent greenwashing, the logistics firms may still take risks to pursue greenwashing when the cost of blockchain adoption is too large. Interestingly, we find that the logistics firms will set the same green levels in logistics activities, independent of the outsourcing strategy of the manufacturer, and greenwashing decisions and blockchain adoption decisions of the logistics firms. © 2023 Elsevier Ltd","Blockchain; Green logistics; Greenwashing; Outsourcing; Supply chain","Blockchain; Electronic commerce; Supply chains; Block-chain; Commerce platforms; E- commerces; Green logistics; Greenwashing; Logistic firms; Logistics outsourcing; Logistics services; Outsourcing strategy; Self-build; electronic commerce; logistics; outsourcing; probability; supply chain management; Outsourcing",{"$nulls":4},"Zhongnan University of Economics and Law, ZUEL, (2722022AK002, YRTD202212); National Natural Science Foundation of China, NSFC, (71971215); Fundamental Research Funds for the Central Universities; National Office for Philosophy and Social Sciences, NPOPSS, (20BJY188)","We sincerely thank the editor and three anonymous reviewers for helpful and constructive comments. This paper is partially supported by the National Natural Science Foundation of China (grant number: 71971215), the National Social Science Fund of China (grant number: 20BJY188), “the Fundamental Research Funds for the Central Universities” in Zhongnan University of Economics and Law (2722022AK002), and the Special Funds for Postgraduate Teaching Reform Project in Zhongnan University of Economics and Law (YRTD202212).","Banker R.D., Khosla I., Sinha K.K., D Quality and competition, Management Science, 44, 9, pp. 1179-1192, (1998); Berrone P., Fosfuri A., Gelabert L., Does greenwashing pay of? Understanding the relationship between environmental actions and environmental legitimacy, J. Bus. 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Manag., 31, 1, pp. 9-31, (2022); Choi T.M., Luo S., Data quality challenges for sustainable fashion supply chain operations in emerging markets: Roles of blockchain, government sponsors and environment taxes, Transportation Research Part E: Logistics and Transportation Review., 131, pp. 139-152, (2019); Choi T.M., (2020); Dong C., Shen B., Chow P.S., Yang L., Ng C.T., Sustainability investment under cap-and-trade regulation, Annals of Operations Research, 240, pp. 509-531, (2016); Dong C., Liu Q., Shen B., To be or not to be green? Strategic investment for green product development in a supply chain, Transportation Research Part E: Logistics and Transportation Review., 131, pp. 193-227, (2019); Dong C., Chen C., Shi X., Ng C.T., Operations strategy for supply chain finance with asset-backed securitization: Centralization and blockchain adoption, Int. J. Prod. Econ., 241, (2021); Du X., How the market values greenwashing? Evidence from China, J. Bus. Ethics, 128, 3, pp. 547-574, (2014); Dutta P., Choi T.M., Somani S., Butala R., Blockchain technology in supply chain operations: Applications, challenges and research opportunities, Transportation Research Part E: Logistics and Transportation Review., 142, (2020); Esmaeilian B., Sarkis J., Lewis K., Behdad S., Blockchain for the future of sustainable supply chain management in Industry 4.0, Resour. Conserv. Recycl., 163, (2020); Ghosh D., Shah J., Supply chain analysis under green sensitive consumer demand and cost sharing contract, Int. J. Prod. Econ., 164, pp. 319-329, (2015); Giri B.C., Sarker B.R., Improving performance by coordinating a supply chain with third party logistics outsourcing under production disruption, Comput. Ind. Eng., 103, pp. 168-177, (2017); Guo R., Tao L., Li C.B., Wang T., A path analysis of greenwashing in a trust crisis among Chinese energy companies: The role of brand legitimacy and brand loyalty, J. Bus. Ethics, 140, pp. 523-536, (2017); Guo R., Zhang W., Wang T., Li C.B., Tao L., Timely or considered? Brand trust repair strategies and mechanism after greenwashing in China—from a legitimacy perspective, Ind. Mark. Manag., 72, pp. 127-137, (2018); Hartmann J., Moeller S., Chain liability in multitier supply chain? Responsibility attributions for unsustainable supplier behavior, J. Oper. Manag., 32, pp. 281-294, (2014); Huang M., Tu J., Chao X., Jin D., Quality risk in logistics outsourcing: A fourth party logistics perspective, Eur. J. Oper. Res., 276, 3, pp. 855-879, (2019); Li Q., Ma M., Shi T., Zhu C., Green investment in a sustainable supply chain: The role of blockchain and fairness, Transportation Research Part E: Logistics and Transportation Review., 167, (2022); Liu C., Huo B., Liu S., Zhao X., Effect of information sharing and process coordination on logistics outsourcing, Ind. Manag. Data Syst., 115, 1, pp. 41-63, (2015); Lou Y., Feng L., He S., He Z., Zhao X., Logistics service outsourcing choices in a retailer-led supply chain, Transportation Research Part E: Logistics and Transportation Review., 141, (2020); Lyon T.P., Maxwell J.W., Greenwash: Corporate environmental disclosure under threat of audit, J. Econ. Manag. Strateg., 20, 1, pp. 3-41, (2011); Maiden T., (2020); Marquis C., Toffel M.W., Zhou Y., Scrutiny, norms, and selective disclosure: A global study of greenwashing, Organ. Sci., 27, 2, pp. 483-504, (2016); Niu B., Mu Z., Sustainable efforts, procurement outsourcing, and channel co-opetition in emerging markets, Transportation Research Part E: Logistics and Transportation Review., 138, (2020); (2020); Saberi S., Kouhizadeh M., Sarkis J., Shen L., Blockchain technology and its relationships to sustainable supply chain management, Int. J. Prod. Res., 57, 7, pp. 2117-2135, (2019); Shen B., Dong C., Minner S., Combating Copycats in the Supply Chain with Permissioned Blockchain Technology, Prod. Oper. Manag. Available at:, (2021); Shi X., Chan H.L., Dong C., Value of bargaining contract in a supply chain system with sustainability investment: An incentive analysis, IEEE Transactions on Systems, Man, and Cybernetics: Systems., 50, 4, pp. 1622-1634, (2020); Shi X., Chan H.L., Dong C., Impacts of competition between buying firms on corporate social responsibility efforts: Does competition do more harm than good?, Transportation Research Part E: Logistics and Transportation Review., 140, (2020); Shi X., Yao S., Luo S., Innovative platform operations with the use of technologies in the blockchain era, Int. J. Prod. Res. Available at:, (2021); Shi X., Yao S., Ma Y., When and how should cross-border platforms manage blockchain technology in the presence of purchasing agents?, Asia-Pacific J. Oper. Res. Available at:, (2021); (2021); (2022); Walker K., Wan F., The harm of symbolic actions and green-washing: Corporate actions and communications on environmental performance and their financial implications, J. Bus. Ethics, 109, pp. 227-242, (2012); Wu Y., Zhang K., Xie J., Bad greenwashing, good greenwashing: Corporate social responsibility and information transparency, Manag. Sci., 66, 7, pp. 3095-3112, (2020); Yang L., Ni D., Ng C.T., Blockchain enabled traceability and producer's incentive to outsource delivery, Int. J. Prod. Res. Available at:, (2022); Yu E.-P.-Y., Van Luu B., Chen C.H., Greenwashing in environmental, social and governance disclosures, Res. Int. Bus. Financ., 52, (2020)","R. Liu; School of Business Administration, Zhongnan University of Economic and Law, Wuhan, 430073, China; email: mrlrj@zuel.edu.cn",null,"Elsevier Ltd",{"$nulls":5},1.3665545E7,null,null,null,"English","Transp. Res. Part E Logist. Transp. Rev.","Article","Final",null,"Scopus","2-s2.0-85146167689"]
["Wang L.; Wang S.; Gong Y.; Peng L.","Wang, Lin (57193123129); Wang, Sirui (57206896643); Gong, Yeming (24767308200); Peng, Lu (57191972898)","57193123129; 57206896643; 24767308200; 57191972898","Optimizing a multi-echelon location-inventory problem with joint replenishment: A Lipschitz ϵ-optimal approach using Lagrangian relaxation",2023.0,"Computers and Operations Research",151.0,null,106128.0,null,null,null,3.0,"10.1016/j.cor.2022.106128","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85145239967&doi=10.1016%2fj.cor.2022.106128&partnerID=40&md5=5385aa401ffe58c2981b7a94f4ac6c05","School of Management, Huazhong University of Science and Technology, Wuhan, 430074, China; EMLYON Business School, 23 Avenue Guy de Collongue, France; School of Management, Wuhan University of Technology, Wuhan, 430070, China","Wang L., School of Management, Huazhong University of Science and Technology, Wuhan, 430074, China; Wang S., School of Management, Huazhong University of Science and Technology, Wuhan, 430074, China; Gong Y., EMLYON Business School, 23 Avenue Guy de Collongue, France; Peng L., School of Management, Wuhan University of Technology, Wuhan, 430070, China","This paper investigates a supply network design problem for cross-border e-commerce. The supply chain consists of suppliers, regional distribution centers, and distribution centers. Our goal is to determine simultaneously location decisions of regional distribution centers, and the inventory decisions for coordinated replenishment and delivery. We formulate this problem as a mixed-integer non-linear program, and develop a Lipschitz optimization algorithm and an iterative heuristic to solve it. Moreover, we propose a tight lower bound via constructing a dual problem. Computational results show that both the Lipschitz optimization method and the heuristic can produce a near-optimal solution with a gap below 1%. Finally, we analyze the influence of integrated decision making and capacity constraints. An interesting finding is that the capacity of regional distribution centers has a critical influence, while the capacity of distribution centers is trivial. Integrated decision making can achieve remarkable cost savings only if the capacity constraints of regional distribution centers are loose. Nevertheless, capacity constraints of distribution centers make almost no impact. This result can be a good guide for a company's investment plan: one should give top priority to regional distribution centers, and give only low priority to distribution centers. © 2022 Elsevier Ltd","Heuristic algorithm; Joint replenishment; Lagrangian relaxation; Lipschitz optimization; Location-inventory; Mixed integer nonlinear program","Decision making; Heuristic algorithms; Heuristic methods; Integer programming; Investments; Iterative methods; Lagrange multipliers; Location; Nonlinear programming; Distribution centres; Heuristics algorithm; Joint replenishment; Lagrangian relaxations; Lipschitz; Lipschitz optimization; Location-inventory; Mixed integer nonlinear program; Optimisations; Regional distribution centers; Supply chains",{"$nulls":4},"National Office for Philosophy and Social Sciences, NPOPSS, (ZD126)","This research is partially supported by National Social Science Foundation of China (Grant number: 20&ZD126 ). 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["Pu S.; Xia C.","Pu, Song (56702010200); Xia, Chang (26634434000)","56702010200; 26634434000","Exact Approach for Integrated Delivery Optimization of E-Commerce and Online-to-Offline Parcels",2023.0,"Asia-Pacific Journal of Operational Research",40.0,3.0,2250026.0,null,null,null,1.0,"10.1142/S0217595922500269","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85143702606&doi=10.1142%2fS0217595922500269&partnerID=40&md5=210b34a540d6bb816c0651576600e352","School of Economics and Management, Chengdu Technological University, Chengdu, 611730, China","Pu S., School of Economics and Management, Chengdu Technological University, Chengdu, 611730, China; Xia C., School of Economics and Management, Chengdu Technological University, Chengdu, 611730, China","This paper studies a novel form of last-mile delivery that combines delivery optimization of E-commerce and Online-to-Offline (O2O) parcels. While O2O parcels must first be picked up from O2O shops before being delivered to the appropriate customers, E-commerce parcels are delivered to customers from a predetermined number of depots. The goal is to use the same fleet of vehicles to provide integrated delivery services for various merchant types. We propose a branch-and-price algorithm based on the set partitioning formulation, where the pricing problem is solved by a label-setting algorithm. Several acceleration techniques including elementary path relaxation, ng-path relaxation and decremental space search are designed to speed up the price problem. Both the conventional dataset used in the literature and a real-world database with up to 75 clients are utilized to test the performance of the suggested method, demonstrating its efficacy.  © 2023 World Scientific Publishing Co.","branch-and-price; label-setting algorithm; pickup and delivery problem; Vehicle routing","Electronic commerce; Fleet operations; Integer programming; Routing algorithms; Statistical tests; Branch and price; Branch-and-price algorithms; Delivery service; Exact approach; Fleet of vehicles; Label-setting algorithm; Last mile; Offline; Optimisations; Pickup and delivery problems; Vehicle routing",{"$nulls":4},"Key Foundation on Philosophical Social Sciences in Sichuan Province-Resource City Development Research Center, (ZYZX-ZD-2102); Sichuan Mineral Resources Research Center, (SCKCZY2022-ZC004)","The author gratefully would like to thank the support of the Key Foundation on Philosophical Social Sciences in Sichuan Province-Resource City Development Research Center (Project Nos. ZYZX-ZD-2102) and Sichuan Mineral Resources Research Center(SCKCZY2022-ZC004).","Aziez I, Cote JF, Coelho LC, Exact algorithms for the multi-pickup and delivery problem with time windows, European Journal of Operational Research, 284, 3, pp. 906-919, (2020); Baldacci R, Bartolini E, Mingozzi A, An exact algorithm for the pickup and delivery problem with time windows, Operations Research, 59, 2, pp. 414-426, (2011); Baldacci R, Mingozzi A, Roberti R, New route relaxation and pricing strategies for the vehicle routing problem, Operations Research, 59, 5, pp. 1269-1283, (2011); Bettinelli A, Cacchiani V, Crainic TG, Vigo D, A branch-and-cut-and-price algorithm for the multi-trip separate pickup and delivery problem with time windows at customers and facilities, European Journal of Operational Research, 279, 3, pp. 824-839, (2019); Boland N, Dethridge J, Dumitrescu I, Accelerated label setting algorithms for the elementary resource constrained shortest path problem, Operations Research Letters, 34, 1, pp. 58-68, (2006); Capelle T, Cortes CE, Gendreau M, Rey PA, Rousseau LM, A column generation approach for location-routing problems with pickup and delivery, European Journal of Operational Research, 272, 1, pp. 121-131, (2019); Castro MP, Cire AA, Beck JC, An MDD-based lagrangian approach to the multicommodity pickup-and-delivery TSP, INFORMS Journal on Computing, 32, 2, pp. 263-278, (2020); Cordeau JF, Laporte G, The dial-a-ride problem: Models and algorithms, Annals of Operations Research, 153, 1, pp. 29-46, (2007); Cortes CE, Matamala M, Contardo C, The pickup and delivery problem with transfers: Formulation and a branch-and-cut solution method, European Journal of Operational Research, 200, 3, pp. 711-724, (2010); Costa L, Contardo C, Desaulniers G, Exact branch-price-and-cut algorithms for vehicle routing, Transportation Science, 53, 4, pp. 946-985, (2019); DellAmico M, Righini G, Salani M, A branch-and-price approach to the vehicle routing problem with simultaneous distribution and collection, Transportation Science, 40, 2, pp. 235-247, (2006); Dumas Y, Desrosiers J, Soumis F, The pickup and delivery problem with time windows, European Journal of Operational Research, 54, 1, pp. 7-22, (1991); Feillet D, Gendreau M, Rousseau LM, New refinements for the solution of vehicle routing problems with branch and price, INFOR: Information Systems and Operational Research, 45, 4, pp. 239-256, (2007); Ghilas V, Cordeau JF, Demir E, Woensel TV, Branch-and-price for the pickup and delivery problem with time windows and scheduled lines, Transportation Science, 52, 5, pp. 1191-1210, (2018); Gschwind T, A comparison of column-generation approaches to the synchronized pickup and delivery problem, European Journal of Operational Research, 247, 1, pp. 60-71, (2015); Gutierrez-Jarpa G, Desaulniers G, Laporte G, Marianov V, A branch-and-price algorithm for the vehicle routing problem with deliveries, selective pickups and time windows, European Journal of Operational Research, 206, 2, pp. 341-349, (2010); Li C, Gong L, Luo Z, Lim A, A branch-and-price-and-cut algorithm for a pickup and delivery problem in retailing, Omega, 89, pp. 71-91, (2019); 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Righini G, Salani M, Dynamic programming algorithms for the elementary shortest path problem with resource constraints, Electronic Notes in Discrete Mathematics, 17, pp. 247-249, (2004); Ropke S, Cordeau JF, Branch and cut and price for the pickup and delivery problem with time windows, Transportation Science, 43, 3, pp. 267-286, (2009); Wang Y, Lei L, Zhang D, Lee LH, Towards delivery-as-a-service: Effective neighborhood search strategies for integrated delivery optimization of e-commerce and static o2o parcels, Transportation Research Part B: Methodological, 139, pp. 38-63, (2020); Xue L, Luo Z, Lim A, Exact approaches for the pickup and delivery problem with loading cost, Omega, 59, pp. 131-145, (2016); Yu B, Yang Z, Xie J, A parallel improved ant colony optimization for multidepot vehicle routing problem, Journal of the Operational Research Society, 62, 1, pp. 183-188, (2011); Zhen L, Tan Z, Wang S, Yi W, Lyu J, Shared mobility oriented open vehicle routing with order radius decision, Transportation Research Part A: Policy and Practice, 144, pp. 19-33, (2021)","C. Xia; School of Economics and Management, Chengdu Technological University, Chengdu, 611730, China; email: 028xiachang@163.com",null,"World Scientific",{"$nulls":5},2175959.0,null,"APJRE",null,"English","Asia Pac J Oper Res","Article","Final",null,"Scopus","2-s2.0-85143702606"]
["Prajapati D.; Harish A.R.; Daultani Y.; Singh H.; Pratap S.","Prajapati, Dhirendra (57215023349); Harish, Arjun R (57215021978); Daultani, Yash (56677743400); Singh, Harpreet (56290146300); Pratap, Saurabh (56667217800)","57215023349; 57215021978; 56677743400; 56290146300; 56667217800","A Clustering Based Routing Heuristic for Last-Mile Logistics in Fresh Food E-Commerce",2023.0,"Global Business Review",24.0,1.0,null,7.0,20.0,13.0,28.0,"10.1177/0972150919889797","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85079712064&doi=10.1177%2f0972150919889797&partnerID=40&md5=56297849bb3af1cfa3f6e985f741257b","Department of Mechanical Engineering, Indian Institute of Information Technology, Design & Manufacturing, Jabalpur, India; Operations Management Group, Indian Institute of Management, Lucknow, India","Prajapati D., Department of Mechanical Engineering, Indian Institute of Information Technology, Design & Manufacturing, Jabalpur, India; Harish A.R., Department of Mechanical Engineering, Indian Institute of Information Technology, Design & Manufacturing, Jabalpur, India; Daultani Y., Operations Management Group, Indian Institute of Management, Lucknow, India; Singh H., Department of Mechanical Engineering, Indian Institute of Information Technology, Design & Manufacturing, Jabalpur, India; Pratap S., Department of Mechanical Engineering, Indian Institute of Information Technology, Design & Manufacturing, Jabalpur, India","This study considers the fresh food city logistics that involves the last-mile distribution of commodities to the customer locations from the local distribution centres (LDCs) established by the e-commerce firms. In this scenario, the last-mile logistics is crucial for its speed of response and the effectiveness in distribution of packages to the target destinations. We propose a clustering-based routing heuristic (CRH) to manage the vehicle routing for the last-mile logistic operations of fresh food in e-commerce. CRH is a clustering algorithm that performs repetitive clustering of demand nodes until the nodes within each cluster become serviceable by a single vehicle. The computational complexity of the algorithm is reduced due to the downsizing of the network through clustering and, hence, produces an optimum feasible solution in less computational time. The algorithm performance was analysed using various operating scenarios and satisfactory results were obtained. © 2022 IMI.","cluster-based heuristic; clustering; Fresh food e-commerce; last-mile operation; logistics",{"$nulls":7},"Arvidsson N., The milk run revisited: A load factor paradox with economic and environmental implications for urban freight transport, Transportation Research Part A: Policy and Practice, 51, pp. 56-62, (2013); Balaji N., Balaji A.N., Solving the multi-period fixed cost transportation problem using LINGO solver, International Journal of Pure and Applied Mathematics, 119, 12, pp. 2151-2157, (2018); Barsing P., Daultani Y., Vaidya O.S., Kumar S., Cross-docking centre location in a supply chain network: A social network analysis approach, Global Business Review, 19, 3_suppl, pp. S218-S234, (2018); Dablanc L., Goods transport in large European cities: Difficult to organize, difficult to modernize, Transportation Research Part A: Policy and Practice, 41, 3, pp. 280-285, (2007); Daultani Y., Goswami M., Vaidya O.S., Kumar S., Inclusive risk modeling for manufacturing firms: A Bayesian network approach, Journal of Intelligent Manufacturing, 30, 8, pp. 2789-2803, (2019); Duka E., Traveling sales problem solved by branch and bound algorithm in LINDO programming, SSRN Electronic Journal, (2018); Fernie J., Sparks L., McKinnon A.C., Retail logistics in the UK: Past, present and future, International Journal of Retail and Distribution Management, 38, pp. 894-914, (2010); Geismar J.H.N., Laporte G., Lei L., Sriskandarajah C., The integrated production and transportation scheduling problem for a product with a short lifespan, INFORMS Journal on Computing, 20, 1, pp. 21-33, (2008); Ho G.T.S., Lau H.C.W., Chung S.H., Fung R.Y.K., Chan T.M., Lee C.K.M., Fuzzy rule sets for enhancing performance in a supply chain network, Industrial Management and Data Systems, 108, 7, pp. 947-972, (2008); Holguin-Veras J., Thorson E., Zorrilla J.C., Commercial vehicle empty trip models with variable zero order empty trip probabilities, Networks and Spatial Economics, 10, 2, pp. 241-259, (2010); Hui Y.Y.Y., Choy K.L., Ho G.T.S., Leung K.H., Lam H.Y., A cloud-based location assignment system for packaged food allocation in e-fulfillment warehouse, 8, pp. 1-15, (2016); Katiyar R., Barua M.K., Meena P.L., Analysing the interactions among the barriers of supply chain performance measurement: An ISM with fuzzy MICMAC approach, Global Business Review, 19, 1, pp. 48-68, (2018); Kin B., Verlinde S., Macharis C., Sustainable urban freight transport in megacities in emerging markets, Sustainable Cities and Society, 32, pp. 31-41, (2017); Lam C.H.Y., Choy K.L., Chung S.H., A decision support system to facilitate warehouse order fulfillment in cross-border supply chain, Journal of Manufacturing Technology Management, 22, 8, pp. 972-983, (2011); McFarlane D., Giannikas V., Lu W., Intelligent logistics: Involving the customer, Computers in Industry, 81, pp. 105-115, (2016); Ozdamar L., Demir O., A hierarchical clustering and routing procedure for large scale disaster relief logistics planning, Transportation Research Part E: Logistics and Transportation Review, 48, 3, pp. 591-602, (2012); Panigrahi S.K., Kar F.W., Fen T.A., Hoe L.K., Wong M., A strategic initiative for successful reverse logistics management in retail industry, Global Business Review, 19, 3_suppl, pp. S151-S175, (2018); Quak H., Sustainability of urban freight transport, (2008); Roy S.K., Sutapa I.N., Case studies of use of design of experiments in material research, Jurnal Teknik Industri, 5, 1, pp. 32-40, (2003); Sabir L.B., Farooquie J.A., Effect of different dimensions of inventory management of fruits and vegetables on profitability of retail stores: An empirical study, Global Business Review, 19, 1, pp. 99-110, (2018); Zegordi S.H., Abadi I.N.K., Nia M.A.B., A novel genetic algorithm for solving production and transportation scheduling in a two-stage supply chain, Computers and Industrial Engineering, 58, 3, pp. 373-381, (2010); Zhang M., Fu Y., Zhao Z., Pratap S., Huang G.Q., Game theoretic analysis of horizontal carrier coordination with revenue sharing in e-commerce logistics, International Journal of Production Research, 57, 5, pp. 1524-1551, (2019); Zhang M., Pratap S., Huang G.Q., Zhao Z., Optimal collaborative transportation service trading in B2B e-commerce logistics, International Journal of Production Research, 7543, May, pp. 1-17, (2017)","D. Prajapati; Department of Mechanical Engineering, Indian Institute of Information Technology, Design & Manufacturing, Jabalpur, India; email: pdhirendra15@gmail.com",null,"Sage Publications India Pvt. Ltd",{"$nulls":5},9721509.0,null,null,null,"English","Global Bus. Rev.","Article","Final",null,"Scopus","2-s2.0-85079712064"]
["Mishra S.; Sharma I.; Pani A.","Mishra, Sabyasachee (55090748200); Sharma, Ishant (57217163468); Pani, Agnivesh (57192668189)","55090748200; 57217163468; 57192668189","Analyzing autonomous delivery acceptance in food deserts based on shopping travel patterns",2023.0,"Transportation Research Part A: Policy and Practice",169.0,null,103589.0,null,null,null,1.0,"10.1016/j.tra.2023.103589","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85147856160&doi=10.1016%2fj.tra.2023.103589&partnerID=40&md5=6e3a99292ff4acbca74a300b36e5a172","Department of Civil Engineering, University of Memphis, Memphis, 38152, TN, United States; Department of Civil Engineering, Birla Institute of Technology and Science (BITS) Pilani, Telangana, Hyderabad, 500078, India; Department of Civil Engineering, Indian Institute of Technology (BHU) Varanasi, Uttar Pradesh, 221005, India","Mishra S., Department of Civil Engineering, University of Memphis, Memphis, 38152, TN, United States; Sharma I., Department of Civil Engineering, Birla Institute of Technology and Science (BITS) Pilani, Telangana, Hyderabad, 500078, India; Pani A., Department of Civil Engineering, Indian Institute of Technology (BHU) Varanasi, Uttar Pradesh, 221005, India","Food desert communities in the US have a widely recognized gap between the demand for healthy foods and the minimum order size that makes it worthwhile for food purveyors to deliver to such neighborhoods, thereby creating delivery deficiencies. A diverse set of mobility constraints and activity-travel patterns exist for disadvantaged segments in these communities, especially the elderly, unemployed, and socially excluded. Appreciating this complexity, an effective solution would be to improve the food access of such communities by providing faster, inexpensive, and flexible online deliveries of healthy foods. However, little is currently known about the shopping travel pattern in food desert communities and the associated mobility inequalities. This paper fulfills this critical research gap and quantifies the differences in shopping travel behavior observed among consumers residing in food deserts and food oases using data collected from Portland and Nashville Metropolitan areas. The paper subsequently captures the perceived acceptance of autonomous delivery robots (ADRs) among these consumers to overcome their mobility inequalities. The results indicate that food desert residents aged between 18 and 25 years, African Americans and those earning more than $75,000 are more likely to engage in internet shopping than food oasis residents. Despite the perceived potential of ADRs to reduce the mobility inequalities in food deserts, acceptance levels for this emerging technology are found to be significantly less among food desert residents, especially among older generational cohorts and less qualified. This study will provide key takeaways to e-commerce companies to expand their delivery service through ADRs in underserved areas. © 2023 Elsevier Ltd","Delivery robots; Food access; Shopping travel; Transportation-disadvantaged; Travel substitution","United States; Arid regions; Consumer behavior; Delivery robot; Food access; Healthy foods; Minimum order; Neighbourhood; Order size; Shopping travel; Transportation-disadvantaged; Travel patterns; Travel substitution; complexity; food consumption; neighborhood; shopping activity; travel behavior; travel demand; Landforms",{"$nulls":6},{"$cut":{"chars":22472,"head":"Abrar M.M., Islam R., Shanto M.A.H., An Autonomous Delivery Robot to Prevent the Spread of Coronavirus in Product Delivery System, pp. 0461-0466, (2020); Adam A., Jensen J.D., What is the effectiveness of obesity related interventions at retail grocery stores and supermarkets? - a systematic review, BMC Public Health, 16, pp. 1-18, (2016); Aitchison J., Ho C.H., The Multivariate Poisson-Log Normal Distribution, Biometrika, 76, (1989); Allcott H., Diamond R., Dube J.-P., Handbury J., Rahkovsky I., Schnell M., (2017); Apparicio P., Cloutier M.S., Shearmur R., The case of Montréal's missing food deserts: Evaluation of accessibility to food supermarkets, Int. 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(Baltim), 58, pp. 33-39, (2014); Boysen N., Schwerdfeger S., Weidinger F., Scheduling last-mile deliveries with truck-based autonomous robots, Eur. J. Oper. Res., 271, pp. 1085-1099, (2018); Brandt E.J., Silvestri D.M., Mande J.R., Holland M.L., Ross J.S., Availability of Grocery Delivery to Food Deserts in States Participating in the Online Purchase Pilot, JAMA Netw. Open, 2, (2019); Bridle-Fitzpatrick S., Food deserts or food swamps?: A mixed-methods study of local food environments in a Mexican city, Soc. Sci. 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["Zhaoji Y.U.; Manling Z.H.U.; Chuang W.E.I.","Zhaoji, Y.U. (57222031192); Manling, Z.H.U. (58852186200); Chuang, W.E.I. (58851873200)","57222031192; 58852186200; 58851873200","Effect of online preventive service recovery strategies on consumer forgiveness from the perspective of psychological contract",2023.0,"Journal of Industrial Engineering and Engineering Management",37.0,6.0,null,201.0,211.0,10.0,0.0,"10.13587/j.cnki.jieem.2023.06.017","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85183542213&doi=10.13587%2fj.cnki.jieem.2023.06.017&partnerID=40&md5=854fa9f2835e6c2376cb09ea51d33f2f","Management School, Shenyang University of Technology, Shenyang, 110870, China; Business School, Nanjing Normal University, Nanjing, 210023, China; Business School, Central University of Finance and Economics, Beijing, 100081, China","Zhaoji Y.U., Management School, Shenyang University of Technology, Shenyang, 110870, China; Manling Z.H.U., Business School, Nanjing Normal University, Nanjing, 210023, China; Chuang W.E.I., Business School, Central University of Finance and Economics, Beijing, 100081, China","Even the most successful giant companies are inevitably making mistakes in marketing activities, it is important to recover consumers from service failure. Due to the prevalence of online service failures, effective service recovery strategies are crucial for service providers to achieve consumer satisfaction. Though mountainous research has shown that post-failure recovery can achieve consumer satisfaction, preventive service recovery strategies provide new insights for solving the puzzle of “ customer silence”. Customer salience is referred to consumers who would like not to reach out to the company when service or product failure happens. How to mitigate the negative influence of service failures and obtain consumer forgiveness is important for companies to recover consumers and enhance consumer loyalty. Since it is critical for companies to sustain long-term relationships with their consumers, the current research focuses on understanding which form of preventive service recovery strategy is more effective for obtaining consumer forgiveness. Besides, forgiveness is a powerful human emotion and consumer forgiveness is crucial for companies to attenuate consumer negative attitudes and is a foundation for companies to restore relationships with consumers in the long term. Building on the theories of service recovery and psychological prevention, the current work examines the effect of preventive service recovery strategies on consumer forgiveness. When and why preventive service recovery strategy would be more efficient to recover consumers and obtain consumer? Are there any potential boundary conditions would moderate the effect of preventive service recovery strategy on consumer forgiveness? The current work proposed that the underlying mechanism of the effect of preventive service recovery on consumer forgiveness, is sequentially mediated by psychological contract and consumer empathy, respectively. Also, results suggested that the effect of preventive service recovery on consumer forgiveness is moderated by brand story (top dog brand vs. underdog brand), which is widely adopted in advertising communication by conveying brand history or brand identity. To examine the effects we proposed, the mix method was used (i. e. field experiment and behavioral experiment) to test the hypotheses we proposed, including several consumer consumption situations in real-world marketing activities, such as delivery delay and inconsistence between actual product and displayed consumer forgiveness and the sequential mediating roles of psychological contract and empathy toward the company. Three experiments were conducted to test these hypotheses. Using an online shopping field experiment, Experiment 1 shows that preventive service recovery has a positive effect on consumer forgiveness and consumer satisfaction. Specifically, preventive economic recovery can elicit higher consumer forgiveness and satisfaction as compared to preventive emotional recovery. Experiment 2 demonstrates that preventive economic recovery strategy is more effective as compared to immediate recovery strategy, and preventive economic recovery leads to more consumer forgiveness and satisfaction as compared to preventive emotional recovery. Experiment 3 suggests that psychological contract and consumer empathy are the sequential mediators in the effect of preventive service recovery on consumer forgiveness. Besides, brand story plays an importantly moderating role in the effect of preventive service recovery on consumer forgiveness. Specifically, when consumers confront underdog brand story, the effect of preventive tangible remedies on consumer forgiveness was attenuated. When consumers confront top dog brand story, the effect of preventive service recovery strategies on consumer forgiveness remained. To sum, results across three experiments illustrate the effect of preventive service recovery on consumer forgiveness, the serial mediation of psychological contract and consumer empathy, and the boundary condition of brand story. At the same time, an in-depth discussion of mechanism was carried out to make up for the deficiencies of the existing literature. The current research makes several contributions to research and practically. Theoretically, our work contributes to the extant literature on preventive service recovery, psychological contract, consumer forgiveness, and brand story. In practice, the current work provides important practical implications for online retailers to recover service failures, improve company reputation, and enhance consumer satisfaction and consumer loyalty. Meanwhile, the current work demonstrates the limitation of our study and potential research questions for future research. © (2023) Zhejiang University.","Brand story; Consumer empathy; Consumer forgiveness; Preventive service recovery; Psychological contract",{"$nulls":5},"National Natural Science Foundation of China, NSFC, (72072098)","Received Date: 2021-07-28 　 　 　 Funded Project: Supported by the National Natural Science Foundation of China (72072098). ∗Corresponding author","(2021); The 47th “statistical report on the development of china′s internet” [R], (2021); Umashankar N, Ward M K, Dahl D W., The benefit of becoming friends: complaining after service failures leads customers with strong ties to increase loyalty[J], Journal of Marketing, 81, 6, pp. 79-98, (2017); Ostrom A L, Iacobucci D., The effect of guarantees on consumers′ evaluation of services[J], Journal of Services Marketing, 12, 5, pp. 362-378, (2016); 31, 10, pp. 153-163, (2019); Yang Q, Meng L, Dong Z., Service is not good,try to be vaccinated against complaints - study on preventive service recovery based on complainant heterogeneity, Business Review, 31, 10, pp. 153-163, (2019); 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Industrial Eng. Eng. Management","Article","Final",null,"Scopus","2-s2.0-85183542213"]
["Liu Y.; Yue Z.; Wang Y.; Wang H.","Liu, Yong (57201749293); Yue, Zhicheng (58126753700); Wang, Yong (56018368000); Wang, Haizhong (55964470100)","57201749293; 58126753700; 56018368000; 55964470100","Logistics Distribution Vehicle Routing Problem with Time Window under Pallet 3D Loading Constraint",2023.0,"Sustainability (Switzerland)",15.0,4.0,3594.0,null,null,null,4.0,"10.3390/su15043594","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85149297831&doi=10.3390%2fsu15043594&partnerID=40&md5=86377c3b16395ffd7aa1391628ac1805","School of Economics and Management, Chongqing Jiaotong University, Chongqing, 400074, China; School of Civil and Construction Engineering, Oregon State University, Corvallis, 97330, OR, United States","Liu Y., School of Economics and Management, Chongqing Jiaotong University, Chongqing, 400074, China; Yue Z., School of Economics and Management, Chongqing Jiaotong University, Chongqing, 400074, China; Wang Y., School of Economics and Management, Chongqing Jiaotong University, Chongqing, 400074, China; Wang H., School of Civil and Construction Engineering, Oregon State University, Corvallis, 97330, OR, United States","As an important support of the e-commerce industry, the express delivery industry is particularly important in national development. Low loading rates caused by numerous types of containers and cost increases caused by low loading and unloading efficiency are still remaining issues in the process of goods delivery and packing. This study introduced the pallet with telescopic support height as the middle to address these issues and proposed a distribution scheme based on the constraints of three-dimensional pallet loading with a time window. First, combining the path optimization of the time window and cargo loading, a solution model was established to solve the existing express delivery problem with the lowest total delivery cost and the highest average vehicle loading rate. In addition, the multi-objective problem was transformed through the multi-objective linear weighting method. Second, we cluster the customer nodes. In order to solve the large number of gaps generated by the hierarchy theory, we adopt the descending order of cargo volume as the initial sequence and design the coding and decoding for path optimization and pallet loading, solving the problem through the simulated anneal-genetic algorithm. Finally, the effectiveness of the algorithm is obtained through the comparison with other algorithms and the simple three-dimensional loading and distribution scheme by using examples. It is proved that the optimization of three-dimensional packing for express delivery using pallets as carriers can not only meet the high loading rate but also improve the loading and unloading speed, reduce the time penalty cost, and improve the operability of loading. This paper provides decision reference and method support for path optimization under three-dimensional loading constraints. © 2023 by the authors.","hybrid simulated annealing-genetic algorithm; pallet 3D reprint constraint; vehicle loading rate; vehicle routing problem","genetic algorithm; instrumentation; optimization; simulated annealing; three-dimensional modeling",{"$nulls":4},"Human Social Science Base of Chongqing Municipal Education Commission, (22SKJD093, CSTB2022BSXM-JCX0116); Social Science Foundation of Chongqing of China, (2020BS62); Chongqing Municipal Education Commission, CQMEC, (KJQN202100702); Chongqing Jiaotong University, CQJTU, (21JDKJC-A021)","This work was supported by the Social Science Foundation of Chongqing of China (grant No. 2020BS62), the Science and Technology Research Program of Chongqing Municipal Education Commission (grant No. KJQN202100702), the Key Project of the Human Social Science Base of Chongqing Municipal Education Commission (22SKJD093), the Ph.D. Direct Train Research Program of Chongqing (grant No. CSTB2022BSXM-JCX0116), and the Research Start-up Funding of Chongqing Jiaotong University (No. 21JDKJC-A021). The authors sincerely appreciate the editor and anonymous referees for their comments and suggestions.","Erbayrak S., Ozkir V., Yildirim U.M., Multi-objective 3D bin packing problem with load balance and product family concerns, Comput. Ind. Eng, 159, (2021); Eilon S., Christofides N., The loading problem, Manag. Sci, 17, pp. 259-268, (1971); Iori M., Martello S., Routing problems with loading constraints, Top, 18, pp. 4-27, (2010); Pisinger D., Heuristics for the container loading problem, Eur. J. Oper. Res, 141, pp. 382-392, (2002); Georce J.A., Robinson D.F., A heuristic for packing boxes into a container, Comput. Oper. Res, 7, pp. 147-156, (1980); Bortfeldt A., Gehring H., A hybrid genetic algorithm for the container loading problem, Eur. J. Oper. Res, 131, pp. 143-161, (2001); Gehring H., Bortfeldt A., A genetic algorithm for solving the container loading problem, Int. Trans. Oper. 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Optim, 54, pp. 2123-2139, (2022); Li J., Qin H., Baldacci R., Zhu W., Branch-and-price-and-cut for the synchronized vehicle routing problem with split delivery, proportional service time and multiple time windows, Transp. Res. Part E Logist. Transp. Rev, 140, (2020); Jalilvand M., Bashiri M., Nikzad E., An effective Progressive Hedging algorithm for the two-layers time window assignment vehicle routing problem in a stochastic environment, Expert Syst. Appl, 165, (2021); Gunantara N., A review of multi-objective optimization: Methods and its applications, Cogent Eng, 5, (2018); Williams J., Alizadeh R., Allen J.K., Mistree F., Using network partitioning to design a green supply chain, Proceedings of the International Design Engineering Technical Conferences and Computers and Information in Engineering Conference","Y. Wang; School of Economics and Management, Chongqing Jiaotong University, Chongqing, 400074, China; email: yongwx@cqjtu.edu.cn",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85149297831"]
["Beliaev M.; Mehr N.; Pedarsani R.","Beliaev, Mark (57222148294); Mehr, Negar (57191618459); Pedarsani, Ramtin (36574033500)","57222148294; 57191618459; 36574033500","Congestion-Aware Bi-Modal Delivery Systems Utilizing Drones",2023.0,"Future Transportation",3.0,1.0,null,329.0,348.0,19.0,0.0,"10.3390/futuretransp3010020","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85176581799&doi=10.3390%2ffuturetransp3010020&partnerID=40&md5=2ce8e2bbda3fb5b2d5fc71aa9b240040","Electrical & Computer Engineering, University of California Santa Barbara, Santa Barbara, 93106, CA, United States; Aerospace Engineering, University of Illinois at Urbana-Champaign, Champaign, 61820, IL, United States","Beliaev M., Electrical & Computer Engineering, University of California Santa Barbara, Santa Barbara, 93106, CA, United States; Mehr N., Aerospace Engineering, University of Illinois at Urbana-Champaign, Champaign, 61820, IL, United States; Pedarsani R., Electrical & Computer Engineering, University of California Santa Barbara, Santa Barbara, 93106, CA, United States","With e-commerce demand rising, logistic operators are investing in alternative delivery methods such as drones. Because of their aerial reach, drones can provide much needed utility in the last mile by taking the load off of vehicles delivering parcels to customers on the road. Our goal is to assess the potential drones have in mitigating traffic congestion. To do so, we develop a mathematical model for a bi-modal delivery system composed of parcels carrying trucks and drones, combining it with an optimization problem that can be solved for the socially optimal routing and allocation policy efficiently. Within this formulation, we include multiple stakeholder perspectives by modeling the objective function in terms of both traffic congestion and parcel latency. This allows our model to quantify the impact of drones on reducing traffic congestion, and simultaneously finds the path routing that minimizes the given objective. To account for the effects of stopping trucks on road latency, we simulate roads shared between trucks and cars by utilizing SUMO. We then use quadratic optimization techniques to test our proposed framework on a variety of real-world transportation networks. Our findings highlight the trade-off between reducing traffic congestion and increasing parcel latency—while routing trucks along less time-efficient paths may alleviate traffic congestion, this disproportionately increases the parcel latency. This suggests the need for a balanced approach that considers both factors when solving for the routing policy. © 2023 by the authors.","air transportation; computational modeling; logistics; optimization; traffic congestion",{"$nulls":5},"National Science Foundation, NSF, (1952920, ECCS–2145134)","This research was funded by NSF ECCS–1952920 and NSF ECCS–2145134 grants.","Joerss M., Schroder J., Neuhaus F., Klink C., Mann F., Parcel Delivery: The Future of Last Mile, pp. 1-32, (2016); Ali F., US Ecommerce Grows 44.0 in 2020, (2021); Adobe Digital Economy Index, Q1 2021, (2021); Joerss M., Neuhaus F., Schroder J., How Customer Demands Are Reshaping Last-Mile Delivery, pp. 1-32, (2016); Weiss C., Onnen-Weber U., The challenge of sustainable last mile distribution of CEP services in small towns, Transp. Res. Procedia, 39, pp. 597-604, (2019); Holguin-Veras J., Amaya J., Sanchez-Diaz I., Browne M., Wojtowicz J., State of the art and practice of urban freight management Part II: Financial approaches, logistics, and demand management, Transp. Res. Part Policy Pract, 137, pp. 383-410, (2020); Bosona T., Urban freight last mile logistics—challenges and opportunities to improve sustainability: A literature review, Sustainability, 12, (2020); Ranieri L., Digiesi S., Silvestri B., Roccotelli M., A review of last mile logistics innovations in an externalities cost reduction vision, Sustainability, 10, (2018); Cardenas I., Borbon-Galvez Y., Verlinden T., Van de Voorde E., Vanelslander T., Dewulf W., City logistics, urban goods distribution and last mile delivery and collection, Compet. Regul. Netw. 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Technol, 120, (2020); Frachtenberg E., Practical drone delivery, Computer, 52, pp. 53-57, (2019); Smart ATM U-Space, (2021); National Environmental Policy Act and Drones, (2022); Amazon Prime Air; DHL drone delivery and Parcelcopter Technology: Discover DHL, (2021); Viu-Roig M., Alvarez-Palau E.J., The impact of E-Commerce-related last-mile logistics on cities: A systematic literature review, Sustainability, 12, (2020); Cleophas C., Cottrill C., Ehmke J.F., Tierney K., Collaborative urban transportation: Recent advances in theory and practice, Eur. J. Oper. Res, 273, pp. 801-816, (2019); Holguin-Veras J., Leal J.A., Sanchez-Diaz I., Browne M., Wojtowicz J., State of the art and practice of urban freight management: Part I: Infrastructure, vehicle-related, and traffic operations, Transp. Res. Part A Policy Pract, 137, pp. 360-382, (2020); Kiba-Janiak M., Marcinkowski J., Jagoda A., Skowronska A., Sustainable last mile delivery on e-commerce market in cities from the perspective of various stakeholders. Literature review, Sustain. Cities Soc, 71, (2021); Beliaev M., Mehr N., Pedarsani R., Congestion-aware Bi-modal Delivery Systems Utilizing Drones, Proceedings of the European Control Conference; Lopez P.A., Behrisch M., Bieker-Walz L., Erdmann J., Flotterod Y.P., Hilbrich R., Lucken L., Rummel J., Wagner P., Wiessner E., Microscopic Traffic Simulation using SUMO, Proceedings of the 21st IEEE International Conference on Intelligent Transportation Systems; Merkert R., Bushell J., Managing the drone revolution: A systematic literature review into the current use of airborne drones and future strategic directions for their effective control, J. Air Transp. Manag, 89, (2020); Murray C.C., Chu A.G., The flying sidekick traveling salesman problem: Optimization of drone-assisted parcel delivery, Transp. Res. Part Emerg. Technol, 54, pp. 86-109, (2015); Wang X., Poikonen S., Golden B., The vehicle routing problem with drones: Several worst-case results, Optim. Lett, 11, pp. 679-697, (2017); Lindholm M., Urban Freight Transport from a Local Authority Perspective—A Literature Review, (2013); Hu X., Liu T., Hao X., Su Z., Yang Z., Research on the influence of bus bay on traffic flow in adjacent lane: Simulations in the framework of Kerner’s three-phase traffic theory, Phys. Stat. Mech. Its Appl, 563, (2021); Raj P., Asaithambi G., Ravi Shankar A., Effect of curbside bus stops on passenger car units and capacity in disordered traffic using simulation model, Transp. Lett, 14, pp. 104-113, (2022); Trott M., Baur N.F., der Landwehr M.A., Rieck J., von Viebahn C., Evaluating the role of commercial parking bays for urban stakeholders on last-mile deliveries—A consideration of various sustainability aspects, J. Clean. Prod, 312, (2021); Hu X., Hao X., Wang H., Su Z., Zhang F., Research on on-street temporary parking effects based on cellular automaton model under the framework of Kerner’s three-phase traffic theory, Phys. A Stat. Mech. Its Appl, 545, (2020); Chen J., Li Z., Jiang H., Zhu S., Wang W., Simulating the impacts of on-street vehicle parking on traffic operations on urban streets using cellular automation, Phys. A Stat. Mech. Its Appl, 468, pp. 880-891, (2017); Kong D., Guo X., Yang B., Wu D., Analyzing the Impact of Trucks on Traffic Flow Based on an Improved Cellular Automaton Model, Discret. Dyn. Nat. Soc, 2016, (2016); Al Eisaeia M., Moridpourb S., Tay R., Heavy Vehicle Management: Restriction Strategies, Transp. Res. Procedia, 21, pp. 18-28, (2017); Thompson R.G., Vehicle Orientated Initiatives for Improving the Environmental Performance of Urban Freight Systems, Green Logistics and Transportation: A Sustainable Supply Chain Perspective, pp. 119-129, (2015); Dablanc L., Rodrigue J.P., The geography of urban freight, The Geography of Urban Transportation, (2014); LLC Gurobi Optimizer Reference Manual Gurobi Optimization, (2022); Stabler B., Transportation Networks for Research Core Team; Ukkusuri S.V., Yushimito W.F., A methodology to assess the criticality of highway transportation networks, J. Transp. Secur, 2, pp. 29-46, (2009); Kim M., Matson E.T., A Cost-Optimization Model in Multi-agent System Routing for Drone Delivery, Proceedings of the Highlights of Practical Applications of Cyber-Physical Multi-Agent Systems, pp. 40-51, (2017); Cui Y., Chang T.H., Hong M., Pang J.S., A Study of Piecewise Linear-Quadratic Programs, J. Optim. Theory Appl, 186, pp. 523-553, (2020); Sharpe B., Rodriguez F., Market analysis of heavy-duty commercial trailers in Europe, (2018); Bokare P., Maurya A., Acceleration-Deceleration Behaviour of Various Vehicle Types, Transp. Res. Procedia, 25, pp. 4733-4749, (2017)","M. Beliaev; Electrical & Computer Engineering, University of California Santa Barbara, Santa Barbara, 93106, United States; email: mbeliaev@ucsb.edu",null,"Multidisciplinary Digital Publishing Institute (MDPI)",{"$nulls":5},2.673759E7,null,null,null,"English","Future. Transp.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85176581799"]
["Xie L.; Li H.; Luttmann L.","Xie, Lin (55339497400); Li, Hanyi (57210961357); Luttmann, Laurin (57222131417)","55339497400; 57210961357; 57222131417","Formulating and solving integrated order batching and routing in multi-depot AGV-assisted mixed-shelves warehouses",2023.0,"European Journal of Operational Research",307.0,2.0,null,713.0,730.0,17.0,6.0,"10.1016/j.ejor.2022.08.047","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85138771527&doi=10.1016%2fj.ejor.2022.08.047&partnerID=40&md5=eed354a44475083cf18b13bffbe791d8","Leuphana University of Lüneburg, Universitätallee 1, Lüneburg, 21335, Germany; Beijing Hanning Tech Co., Ltd, China","Xie L., Leuphana University of Lüneburg, Universitätallee 1, Lüneburg, 21335, Germany; Li H., Beijing Hanning Tech Co., Ltd, China; Luttmann L., Leuphana University of Lüneburg, Universitätallee 1, Lüneburg, 21335, Germany","Different retail and e-commerce companies are facing the challenge of assembling large numbers of time-critical picking orders that include both small-line and multi-line orders. To reduce unproductive picker working time as in traditional picker-to-parts warehousing systems, different solutions are proposed in the literature and in practice. For example, in a mixed-shelves storage policy, items of the same stock keeping unit are spread over several shelves in a warehouse; or automated guided vehicles (AGVs) are used to transport the picked items from the storage area to packing stations instead of human pickers. This is the first paper to combine both solutions, creating what we call AGV-assisted mixed-shelves picking systems. We model the new integrated order batching and routing problem in such systems as an extended multi-depot vehicle routing problem with both three-index and two-commodity network flow formulations. Due to the complexity of the integrated problem, we develop a novel variable neighborhood search algorithm to solve the integrated problem more efficiently. We test our methods with different sizes of instances, and conclude that the mixed-shelves storage policy is more suitable than the usual storage policy in AGV-assisted mixed-shelves systems for orders with different sizes of order lines (saving up to 62% on driving distances for AGVs). Our variable neighborhood search algorithm provides optimal solutions within an acceptable computational time. © 2022 The Author(s)","AGV-assisted picking; Logistics; Mixed-shelves storage; Order batching; Routing","Automatic guided vehicles; Learning algorithms; Optimization; Vehicle routing; Automated guided vehicle-assisted picking; Automated guided vehicles; Different sizes; Mixed-shelf storage; Neighborhood search algorithms; Order batching; Routings; Shelf storage; Storage policies; Variable neighborhood search; Warehouses",{"$nulls":6},"Alvim A., Glover F.S., Ribeiro C.C., Aloise D.J., Local search for the bin packing problem, Extended abstracts of the 3rd metaheuristics international conference, pp. 7-12, (1999); Archetti C., Bertazzi L., Speranza M.G., Reoptimizing the traveling salesman problem, Networks: An International Journal, 42, 3, pp. 154-159, (2003); Azadeh K., De Koster R., Roy D., Robotized and automated warehouse systems: Review and recent developments, Transportation Science, 53, 4, pp. 917-945, (2019); Baldacci R., Hadjiconstantinou E., Mingozzi A., An exact algorithm for the capacitated vehicle routing problem based on a two-commodity network flow formulation, Operations Research, 52, 5, pp. 723-738, (2004); Baldacci R., Toth P., Vigo D., Recent advances in vehicle routing exact algorithms, 4OR, 5, 4, pp. 269-298, (2007); Boysen N., Briskorn D., Emde S., Parts-to-picker based order processing in a rack-moving mobile robots environment, European Journal of Operational Research, 262, 2, pp. 550-562, (2017); Boysen N., de Koster R., Weidinger F., Warehousing in the e-commerce era: A survey, European Journal of Operational Research, 277, 2, pp. 396-411, (2019); Briant O., Cambazard H., Cattaruzza D., Catusse N., Ladier A.-L., Ogier M., An efficient and general approach for the joint order batching and picker routing problem, European Journal of Operational Research, 285, 2, pp. 497-512, (2020); Chen T.-L., Cheng C.-Y., Chen Y.-Y., Chan L.-K., An efficient hybrid algorithm for integrated order batching, sequencing and routing problem, International Journal of Production Economics, 159, pp. 158-167, (2015); Cheng C.-Y., Chen Y.-Y., Chen T.-L., Yoo J.J.-W., Using a hybrid approach based on the particle swarm optimization and ant colony optimization to solve a joint order batching and picker routing problem, International Journal of Production Economics, 170, pp. 805-814, (2015); Daniels R.L., Rummel J.L., Schantz R., A model for warehouse order picking, European Journal of Operational Research, 105, 1, pp. 1-17, (1998); De Koster R., Le-Duc T., Roodbergen K.J., Design and control of warehouse order picking: A literature review, European Journal of Operational Research, 182, 2, pp. 481-501, (2007); De Koster R.B., Le-Duc T., Zaerpour N., Determining the number of zones in a pick-and-sort order picking system, International Journal of Production Research, 50, 3, pp. 757-771, (2012); Dosa G., Sgall J., First fit bin packing: A tight analysis, 30th International symposium on theoretical aspects of computer science (STACS 2013), (2013); Ene S., Ozturk N., Storage location assignment and order picking optimization in the automotive industry, The International Journal of Advanced Manufacturing Technology, 60, 5-8, pp. 787-797, (2012); (2020); Finke G., A two-commodity network flow approach to the traveling salesman problem, Congressus Numerantium, 41, pp. 167-178, (1984); Garey M.R., Johnson D.S., Computers and intractability: A guide to the theory of NP-completeness, 174, (1979); Gendreau M., Potvin J.-Y.E., Handbook of metaheuristics, 3, (2010); Giosa I., Tansini I., Viera I., New assignment algorithms for the multi-depot vehicle routing problem, Journal of the Operational Research Society, 53, 9, pp. 977-984, (2002); Hagberg A.A., Schult D.A., Swart P.J., Exploring network structure, dynamics, and function using NetworkX, Proceedings of the 7th python in science conference, pp. 11-15, (2008); Karmarkar N., Karp R.M., The differencing method of set partitioning, Computer Science Division (EECS), (1982); Kulak O., Sahin Y., Taner M.E., Joint order batching and picker routing in single and multiple-cross-aisle warehouses using cluster-based tabu search algorithms, Flexible Services and Manufacturing Journal, 24, 1, pp. 52-80, (2012); Kytojoki J., Nuortio T., Braysy O., Gendreau M., An efficient variable neighborhood search heuristic for very large scale vehicle routing problems, Computers & Operations Research, 34, 9, pp. 2743-2757, (2007); Lee H.-Y., Murray C.C., Robotics in order picking: Evaluating warehouse layouts for pick, place, and transport vehicle routing systems, International Journal of Production Research, 57, 18, pp. 5821-5841, (2019); Li J., Huang R., Dai J.B., Joint optimisation of order batching and picker routing in the online retailers warehouse in China, International Journal of Production Research, 55, 2, pp. 447-461, (2017); Lin C.-C., Kang J.-R., Hou C.-C., Cheng C.-Y., Joint order batching and picker Manhattan routing problem, Computers & Industrial Engineering, 95, pp. 164-174, (2016); Matusiak M., de Koster R., Kroon L., Saarinen J., A fast simulated annealing method for batching precedence-constrained customer orders in a warehouse, European Journal of Operational Research, 236, 3, pp. 968-977, (2014); Mladenovic N., Hansen P., Variable neighborhood search, Computers & Operations Research, 24, 11, pp. 1097-1100, (1997); Montoya-Torres J.R., Franco J.L., Isaza S.N., Jimenez H.F., Herazo-Padilla N., A literature review on the vehicle routing problem with multiple depots, Computers & Industrial Engineering, 79, pp. 115-129, (2015); Ramos T.R.P., Gomes M.I., Povoa A.P.B., Multi-depot vehicle routing problem: A comparative study of alternative formulations, International Journal of Logistics Research and Applications, 23, 2, pp. 103-120, (2020); Scholz A., Schubert D., Wascher G., Order picking with multiple pickers and due dates: Simultaneous solution of order batching, batch assignment and sequencing, and picker routing problems, European Journal of Operational Research, 263, 2, pp. 461-478, (2017); Tompkins J.A., Facilities planning, (2010); Tsai C.-Y., Liou J.J., Huang T.-M., Using a multiple-GA method to solve the batch picking problem: Considering travel distance and order due time, International Journal of Production Research, 46, 22, pp. 6533-6555, (2008); Valle C.A., Beasley J.E., da Cunha A.S., Optimally solving the joint order batching and picker routing problem, European Journal of Operational Research, 262, 3, pp. 817-834, (2017); Van Gils T., Caris A., Ramaekers K., Braekers K., Formulating and solving the integrated batching, routing, and picker scheduling problem in a real-life spare parts warehouse, European Journal of Operational Research, 277, 3, pp. 814-830, (2019); Van Gils T., Ramaekers K., Caris A., De Koster R.B., Designing efficient order picking systems by combining planning problems: State-of-the-art classification and review, European Journal of Operational Research, 267, 1, pp. 1-15, (2018); Weidinger F., Picker routing in rectangular mixed shelves warehouses, Computers & Operations Research, 95, pp. 139-150, (2018); Weidinger F., Boysen N., Schneider M., Picker routing in the mixed-shelves warehouses of e-commerce retailers, European Journal of Operational Research, 274, 2, pp. 501-515, (2019); Won J., Olafsson S., Joint order batching and order picking in warehouse operations, International Journal of Production Research, 43, 7, pp. 1427-1442, (2005); Wulfraat M., (2016); Xie L., Thieme N., Krenzler R., Li H., Introducing split orders and optimizing operational policies in robotic mobile fulfillment systems, European Journal of Operational Research, (2020)","L. Xie; Leuphana University of Lüneburg, Universitätallee 1, Lüneburg, 21335, Germany; email: xie@leuphana.de",null,"Elsevier B.V.",{"$nulls":5},3772217.0,null,"EJORD",null,"English","Eur J Oper Res","Article","Final","All Open Access; Green Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85138771527"]
["Chang S.; Li A.; Wang X.; Zhang J.","Chang, Shuhua (55713455600); Li, Anqi (57556947900); Wang, Xinyu (57221484278); Zhang, Jiayue (57218903679)","55713455600; 57556947900; 57221484278; 57218903679","Optimal combination of platform channel contract and guarantee financing strategy in e-commerce market",2023.0,"Transportation Research Part E: Logistics and Transportation Review",172.0,null,103094.0,null,null,null,2.0,"10.1016/j.tre.2023.103094","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85150012329&doi=10.1016%2fj.tre.2023.103094&partnerID=40&md5=52039c961c97ba871b072f9ea9124884","Coordinated Innovation Center for Computable Modeling in Management Science, Tianjin University of Finance and Economics, Tianjin, 300222, China; Coordinated Innovation Center for Computable Modeling in Management Science, Yango University, Fujian, 350015, China; International Business School, Tianjin Foreign Studies University, Tianjin, 300204, China","Chang S., Coordinated Innovation Center for Computable Modeling in Management Science, Tianjin University of Finance and Economics, Tianjin, 300222, China, Coordinated Innovation Center for Computable Modeling in Management Science, Yango University, Fujian, 350015, China; Li A., Coordinated Innovation Center for Computable Modeling in Management Science, Tianjin University of Finance and Economics, Tianjin, 300222, China; Wang X., Coordinated Innovation Center for Computable Modeling in Management Science, Tianjin University of Finance and Economics, Tianjin, 300222, China; Zhang J., International Business School, Tianjin Foreign Studies University, Tianjin, 300204, China","With the development of economy and technology, e-commerce platforms can connect consumers and online channel suppliers providing transportation services through third-party logistics (3PL). To help these suppliers, especially small- and medium-sized enterprises (SMEs) with financing dilemmas, this paper proposes evidence on the members of the e-commerce supply chain providing procurement and financial assistance. Many partner enterprises offer various innovative financing schemes, such as guarantee financing. To examine the advantage in practice, we study the guarantee financing in the online channel of e-commerce market, which includes capital constrained SME suppliers, e-commerce platforms, 3PLs and banks. We analyze the equilibrium of the optimal combination strategy with channel sales mode and guarantee financing scheme, and explore the conditions under which this innovative financing scheme will benefit all members. It is more feasible for the SME supplier to seek the e-commerce platform (or the 3PL) guarantee financing with high (low) platform service construction cost compared with bank loans without guarantee. This preference comes from the trade-off between the potential market demand risk in sales season and the financing risk of the debtor. We further determine how the release on the sales mode of platform is affected by the guarantee financing scheme. No matter who guarantees, the platform tends to provide the reselling (marketplace) mode when the market demand risk is flat (high). With the increasing of investment in platform's service construction, the platform is more (less) willing to switch the role from the non-guarantor to the guarantor in the reselling (marketplace) mode. The reason is that the e-commerce platform and the 3PL prefer to act as non-guarantor to obtain free-riding benefits, especially in the marketplace mode. Results of this paper provide theoretical support for the innovative financial practice of the e-commerce industry. The insights are relevant to the e-commerce platform and the 3PL managers who aim to promote the applicability of financing scheme to debtors under two channel modes and increase the revenue through construction investment and business expansion. © 2023 Elsevier Ltd","Channel structure; E-commerce; Guarantee financing; Newsvendor; Supply chain financing","electronic commerce; finance; market conditions; small and medium-sized enterprise; supply chain management",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (12101447, 12271395); Ministry of Education of the People's Republic of China, MOE, (19YJCZH174, 22YJAZH156); Graduate Scientific Research and Innovation Foundation of Chongqing, (2021YJSB350, 2021YJSB351)","The authors gratefully acknowledge the constructive suggestions offered by the three referees and editors. This project was supported by the National Natural Science Foundation of China ( 12271395 , 12101447 ), the Humanities and Social Science Research Program of the Ministry of Education of China ( 19YJCZH174 , 22YJAZH156 ) and the Graduate Scientific Research and Innovation Foundation of Tianjin, China ( 2021YJSB350 , 2021YJSB351 ). ","Abhishek V., Jerath K., Zhang Z.J., Agency selling or reselling? Channel structures in electronic retailing, Manage. Sci., 62, 8, pp. 2259-2280, (2016); Babich V., Kouvelis P., Introduction to the special issue on research at the interface of finance, operations, and risk management (iFORM): Recent contributions and future directions, Manuf. Serv. Oper. Manag., 20, 1, pp. 1-18, (2018); Belhadj N., Laussel D., Resende J., Marketplace or reselling? A signalling model, Inf. Econ. Policy, 50, (2020); Biery M.E., These industries generate the highest profit margins, (2015); Birge J., Candogan O., Chen H., Saban D., Optimal commissions and subscriptions in networked markets, Manuf. Serv. Oper. Manag., 23, 3, pp. 569-588, (2020); Cao Y., Wang Q., The informational role of guarantee contracts, European J. Oper. Res., 301, 1, pp. 191-202, (2022); Chakraborty S., Swinney R., Signaling to the crowd: Private quality information and rewards-based crowdfunding, Manuf. Serv. Oper. Manag., 23, 1, pp. 155-169, (2020); Chang S., Li A., Wang X., Wang X., Joint optimization of e-commerce supply chain financing strategy and channel contract, European J. Oper. Res., 303, 2, pp. 908-927, (2022); Chen X., Cai A., Song J., The cash flow advantages of 3PLs as supply chain orchestrators, Manuf. Serv. Oper. 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Zhang; International Business School, Tianjin Foreign Studies University, Tianjin, 300204, China; email: lwsj2020@126.com",null,"Elsevier Ltd",{"$nulls":5},1.3665545E7,null,null,null,"English","Transp. Res. Part E Logist. Transp. Rev.","Article","Final",null,"Scopus","2-s2.0-85150012329"]
["Buldeo Rai H.","Buldeo Rai, Heleen (57195135422)",5.7195135422E10,"Urban warehouses as good neighbors: Findings from a New York City case study",2023.0,"Transportation Research Interdisciplinary Perspectives",19.0,null,100823.0,null,null,null,1.0,"10.1016/j.trip.2023.100823","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85159578481&doi=10.1016%2fj.trip.2023.100823&partnerID=40&md5=a632206b64747828e794fa214098242d","Université Gustave Eiffel – Logistics City Chair, 16 Bd Newton, Champs-sur-Marne, 77420, France","Buldeo Rai H., Université Gustave Eiffel – Logistics City Chair, 16 Bd Newton, Champs-sur-Marne, 77420, France","The surge in online shopping has contributed in no small part to the return of warehouses in cities. Urban warehouses allow retail and delivery companies to serve consumer populations faster. They are also a necessary condition for the transition to an urban logistics system that is efficient and sustainable. However, integrating urban warehouses into dense, mixed-use urban areas presents considerable challenges, particularly in coexistence with surrounding communities. This study explores how urban warehouses can become good neighbors, through a case study of New York City. The city has a high e-commerce demand and high population density. In addition, zoning regulation and administration in particular have enabled the development of several warehouses in recent years. The study introduces seven types of practices that can promote the proper integration of warehouses in cities. Scaled from the system (i.e., the city) to the site (i.e., the warehouse), best practices include the following: zoning for innovation as well as nuisance monitoring and mitigation, environmental policy for movement and place, supply chain awareness for citizens/consumers, blocks and buffers for neighborhood design, community conversation, sustainable transportation transition for goods as well as people, and context-sensitive building design. © 2023 The Author","E-commerce; Good neighbors; Proximity logistics; Urban freight transport; Urban warehousing",{"$nulls":5},"Fondation Palladio","This article was produced at the Logistics City chair, as part of a project funded by the Fondation Palladio. Thank you to all the experts interviewed for this study, for generously sharing their time and expertise. ","(2022); Bell M.G., (2021); Brettmo A., Sanchez-Diaz I., Property owners as possible game changers for sustainable urban freight, Research in Transportation Business & Management, (2021); Buldeo Rai H., Kang S., Sakai T., Tejada C., Yuan Q., Conway A., Et al., ‘Proximity logistics’: Characterizing the development of logistics facilities in dense, mixed-use urban areas around the world, Transportation Research Part A: Policy and Practice, 166, pp. 41-61, (2022); Burton S.O., Cardoso D., Freer R.M., Hovaguimian G., Kim J., Lessin R., Et al., (2011); CityLand, Ikea Development Approved; Sent to Council, (2004); Cuba J., Environmental Justice Advocates Seek to Regulate ‘ Last- Mile ’ Trucking Facilities, (2022); Dablanc L., Palacios-Arguello L., De Oliveira L., Locational patterns of warehouses in 74 cities around the world, a comparative meta-analysis, (2020); Fhwa, Freight as a Good Neighbor – Land Use, Transportation System, and Environmental Considerations, in: FHWA Freight and Land Use Handbook, (2012); Fuller G., How green is your delivery? 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Bklyner, (2022); Yin R.K., Case Study Reserach - Design and Methods, (1984)",null,null,"Elsevier Ltd",{"$nulls":5},2.5901982E7,null,null,null,"English","Transp.  Res.  Interdiscip.  Perspect.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85159578481"]
["Silva A.T.; Duarte S.P.; Melo S.; Witkowska-Konieczny A.; Giannuzzi M.; Lobo A.","Silva, André Teixeira (58454936400); Duarte, Sérgio Pedro (57220519706); Melo, Sandra (56652456800); Witkowska-Konieczny, Adriana (57796770300); Giannuzzi, Michele (57711070600); Lobo, António (18335651100)","58454936400; 57220519706; 56652456800; 57796770300; 57711070600; 18335651100","Attitudes towards Urban Air Mobility for E-Commerce Deliveries: An Exploratory Survey Comparing European Regions",2023.0,"Aerospace",10.0,6.0,536.0,null,null,null,3.0,"10.3390/aerospace10060536","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85163707863&doi=10.3390%2faerospace10060536&partnerID=40&md5=c76b82a1ddc3d8697a48bfdb5ab7ff64","CEiiA—Centro de Engenharia e Desenvolvimento, Porto, 4450-017, Portugal; Departamento de Engenharia e Gestão Industrial, Faculdade de Engenharia da Universidade do Porto, Porto, 4405-614, Portugal; CITTA—Centro de Investigação do Território, Transportes e Ambiente, Faculdade de Engenharia da Universidade do Porto, Porto, 4405-614, Portugal; Gornosląsko-Zagłębiowska Metropolia, Katowice, 40-053, Poland; Distretto Tecnologico Aerospaziale S.C. a r.l, Brindisi, 72100, Italy; Department of Innovation Engineering, Università del Salento, Campus Ecotekne, Monteroni di Lecce, 73047, Italy","Silva A.T., CEiiA—Centro de Engenharia e Desenvolvimento, Porto, 4450-017, Portugal, Departamento de Engenharia e Gestão Industrial, Faculdade de Engenharia da Universidade do Porto, Porto, 4405-614, Portugal; Duarte S.P., CITTA—Centro de Investigação do Território, Transportes e Ambiente, Faculdade de Engenharia da Universidade do Porto, Porto, 4405-614, Portugal; Melo S., CEiiA—Centro de Engenharia e Desenvolvimento, Porto, 4450-017, Portugal; Witkowska-Konieczny A., Gornosląsko-Zagłębiowska Metropolia, Katowice, 40-053, Poland; Giannuzzi M., Distretto Tecnologico Aerospaziale S.C. a r.l, Brindisi, 72100, Italy, Department of Innovation Engineering, Università del Salento, Campus Ecotekne, Monteroni di Lecce, 73047, Italy; Lobo A., CITTA—Centro de Investigação do Território, Transportes e Ambiente, Faculdade de Engenharia da Universidade do Porto, Porto, 4405-614, Portugal","This study explores attitudes towards urban air mobility (UAM) for e-commerce deliveries. UAM, which utilizes drones, has the potential to revolutionize transport services and logistics, leading to economic benefits and reductions in congestion and pollution. However, public acceptance is crucial for a successful implementation; thus, understanding the people’s perspective is key. Descriptive statistics were employed to evaluate survey results from three different European regions, followed by a cluster analysis to define potential user profiles. This study revealed slightly different perceptions towards UAM between the analyzed regions, but also a generally positive attitude. The most important expected identified benefits from UAM were a decrease in congestion and pollution in city centers. High-acceptance segments are gender-balanced and correspond mostly to active population and frequent online shoppers that perceive value in drone deliveries, especially related to an increased convenience and speed. They support public investment in UAM and are willing to pay more for these services and to have their home flown over. Opposite attitudes were expressed by low-acceptance segments, which are female-dominated and include mostly non-frequent online shoppers. The identified user profiles in this study can support the development of public policy and marketing strategies to increase acceptance and adoption. © 2023 by the authors.","acceptance; cluster analysis; drones; e-commerce delivery; urban air mobility",{"$nulls":5},"ASSURED-UAM; European Union’s Horizon 2020 programme, (101006696, NORTE-01-0145-FEDER-000073); European Commission, EC; European Regional Development Fund, ERDF","This research was funded under the ASSURED-UAM and DynamiCITY projects. ASSURED-UAM is a project under the CIVITAS Initiative, one of the flagship programmes helping the European Commission achieve its ambitious mobility and transport goals. This project has received funding from the European Union’s Horizon 2020 programme under Grant Agreement 101006696. The work of A.L. is a result of project DynamiCITY: Fostering Dynamic Adaptation of Smart Cities to Cope with Crises and Disruptions, with reference NORTE-01-0145-FEDER-000073, supported by Norte Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF).","Kellermann R., Biehle T., Fischer L., Drones for parcel and passenger transportation: A literature review, Transp. Res. Interdiscip. Perspect, 4, (2020); Frachtenberg E., Practical Drone Delivery, Computer, 52, pp. 53-57, (2019); Cho S.-H., Kim M., Assessment of the environmental impact and policy responses for urban air mobility: A case study of Seoul metropolitan area, J. Clean. 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["Fessler A.; Cash P.; Thorhauge M.; Haustein S.","Fessler, Andreas (57480262100); Cash, Philip (47661004600); Thorhauge, Mikkel (57110485100); Haustein, Sonja (14067426200)","57480262100; 47661004600; 57110485100; 14067426200","A public transport based crowdshipping concept: Results of a field test in Denmark",2023.0,"Transport Policy",134.0,null,null,106.0,118.0,12.0,4.0,"10.1016/j.tranpol.2023.02.014","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85148898480&doi=10.1016%2fj.tranpol.2023.02.014&partnerID=40&md5=a6c1d4c61e53c1c0ce88835c9e0579a6","Technical University of Denmark, Department of Technology, Management and Economics, 2800 Kgs. Lyngby, Denmark; Northumbria University, School of Design, United Kingdom","Fessler A., Technical University of Denmark, Department of Technology, Management and Economics, 2800 Kgs. Lyngby, Denmark; Cash P., Northumbria University, School of Design, United Kingdom; Thorhauge M., Technical University of Denmark, Department of Technology, Management and Economics, 2800 Kgs. Lyngby, Denmark; Haustein S., Technical University of Denmark, Department of Technology, Management and Economics, 2800 Kgs. Lyngby, Denmark","Increasing e-commerce and accompanying last mile delivery traffic challenges cities worldwide in terms of congestion, emissions, and road safety. This paper presents the main results of a full-scale field test of a public transport based crowdshipping concept aiming to address these challenges, by utilizing passenger flow to reduce the amount of delivery vehicles entering central city districts. The aim of this work was to assess adoption potential as well as the practical and conceptual aspects that may affect this. The test took place in Denmark's capital region and northern Jutland over a two-month period, in which 28 automated parcel lockers (APLs) were placed at public transport stations/stops. Passengers were rewarded for bringing along empty test parcels on their trips, from APL to APL via an app developed for the purpose. Along with the app data, pre- and post-survey data was captured. The practical viability of the concept was validated from a user perspective, with a high degree of post-measure acceptance. Regression results show that ease of interacting with the service affected acceptance of the tested concept, but not the intention to participate in a future realized concept. Perceived behavioural control was the most important predictor of intention, acceptance and behaviour during the trial. Our results highlight the relevancy of contextualizing and supplementing intention as a practice-based measure for adoption propensity. © 2023 The Authors","Acceptance; Crowdshipping; Field test; Last-mile package delivery; Theory of Planned Behavior","Denmark; adaptive management; passenger ship; planning theory; public transport; regression analysis; testing method",{"$nulls":4},"Innovationsfonden, IFD, (8053-00221B)","This work was supported by the Innovation Fund Denmark under Grant 8053-00221B . ","Aarts H., Dijksterhuis A., The automatic activation of goal-directed behaviour: the case of travel habit, J. Environ. Psychol., (2000); Ajzen I., The theory of planned behavior. Organizational Behavior and Human Decision Processes, (1991); Ajzen I., Brown T.C., Carvajal F., Explaining the discrepancy between intentions and actions: the case of hypothetical bias in contingent valuation, Pers. Soc. Psychol. 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["Nham N.T.H.; Bao N.K.Q.; Ha L.T.","Nham, Nguyen Thi Hong (57543310400); Bao, Nguyen Khac Quoc (57283015800); Ha, Le Thanh (57216526632)","57543310400; 57283015800; 57216526632","NONLINEAR EFFECTS OF DIGITALIZATION ON EXPORT ACTIVITIES: AN EMPIRICAL INVESTIGATION IN EUROPEAN COUNTRIES",2023.0,"Technological and Economic Development of Economy",29.0,3.0,null,1041.0,1079.0,38.0,1.0,"10.3846/tede.2023.17061","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85160410849&doi=10.3846%2ftede.2023.17061&partnerID=40&md5=7377716f0615366533673d2e8ad11141","School of Finance, University of Economics Ho Chi Minh City (UEH), Ho Chi Minh, Viet Nam; Faculty of Economics, National Economics University, Ha Noi, Viet Nam","Nham N.T.H., School of Finance, University of Economics Ho Chi Minh City (UEH), Ho Chi Minh, Viet Nam; Bao N.K.Q., School of Finance, University of Economics Ho Chi Minh City (UEH), Ho Chi Minh, Viet Nam; Ha L.T., Faculty of Economics, National Economics University, Ha Noi, Viet Nam","Our study is the first to empirically analyze the nonlinear relationship between digitalization and export value and diversification. This paper measures the digital transformation process in terms of digital connectivity, uses of the internet, e-business, e-commerce, and e-government. The various econometrics techniques are applied for the database of 23 European countries during the period 2015-2020. The vital findings should be conveyed here. First, the bottlenecks of export values could be resolved by promoting digital transformation. However, the non-linear reverted U-shaped relationship between digitalization and export diversification suggests that positive effects only appear when the digital activities, especially in digital connectivity, humans with digital skills, use of internet services, or digital public services reaches a certain threshold. Second, the positive influence of digitalization on exports stems from a reduction in export cost and export time to deal with documentary and border compliance as well as improvements in competence and quality of logistic services and quality of trade and transport-related infrastructure, thus enhancing exports. Third, the role of digital connectivity and the integration of digital technology into business and commerce become especially important for export diversification. © 2023 The Author(s).","digital transformation; European countries; export value and diversification",{"$nulls":7},"Aditya A., Acharyya R., Export diversification, composition, and economic growth: Evidence from cross-country analysis, The Journal of International Trade & Economic Development, 22, 7, pp. 959-992, (2013); Agosin M.R., Alvarez R., Bravo-Ortega C., Determinants of export diversification around the world: 1962-2000, The World Economy, 35, 3, pp. 295-315, (2012); Alcacer J., Cantwell J., Piscitello L., Internationalization in the information age: A new era for places, firms, and international business networks?, Journal of International Business Studies, 47, 5, pp. 499-512, (2016); Ali M., Cantner U., Roy I., Knowledge spillovers through FDI and trade: The moderating role of quality-adjusted human capital, Journal of Evolutionary Economics, 26, 4, pp. 837-868, (2016); Arellano M., Bover O., Another look at the instrumental variable estimation of error-components models, Journal of Econometrics, 68, 1, pp. 29-51, (1995); Awan U., Sroufe R., Shahbaz M., Industry 4.0 and the circular economy: A literature review and recommendations for future research, Business Strategy and the Environment, 30, 4, pp. 2038-2060, (2021); Azar G., Ciabuschi F., Organizational innovation, technological innovation, and export performance: The effects of innovation radicalness and extensiveness, International Business Review, 26, 2, pp. 324-336, (2017); Beyond COVID-19: Supply Chain Resilience Holds Key to Recovery, (2020); Bayram M., Springer S., Garvey C.K., Ozdemir V., COVID-19 digital health innovation policy: A portal to alternative futures in the making, OMICS: A Journal of Integrative Biology, 24, 8, pp. 460-469, (2020); Beck N., Katz J.N., What to do (and not to do) with time-series cross-section data, American Political Science Review, 89, 3, pp. 634-647, (1995); Ben Hammouda H., Karingi S., Njuguna A., Sadni Jallab M., Diversification: Towards a New Paradigm for Africa’s Development, (2006); Bettiol M., Capestro M., Marchi V.D., Maria E.D., Industry 4.0 Investments in Manufacturing Firms and Internationalization, (2020); Blundell R., Bond S., Initial conditions and moment restrictions in dynamic panel data models, Journal of Econometrics, 87, 1, pp. 115-143, (1998); Bojnec S., Ferto I., Market-Creating Effect of the Internet on Food Trade, (2010); Bossong R., Rhinard M., The EU internal security strategy: Towards a more coherent approach to EU Security?, Studia Diplomatica, 66, 2, pp. 45-58, (2013); Branstetter L., Is foreign direct investment a channel of knowledge spillovers? 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Bao; School of Finance, University of Economics Ho Chi Minh City (UEH), Ho Chi Minh, Viet Nam; email: Nguyenbao@ueh.edu.vn",null,"Vilnius Gediminas Technical University",{"$nulls":5},2.0294913E7,null,null,null,"English","Technol. Econ. Develop. Econ.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85160410849"]
["Bukova B.; Tengler J.; Brumercikova E.; Brumercik F.; Kissova O.","Bukova, Bibiana (9241044300); Tengler, Jiri (57189065309); Brumercikova, Eva (57021891000); Brumercik, Frantisek (8374357700); Kissova, Olga (58100098700)","9241044300; 57189065309; 57021891000; 8374357700; 58100098700","Environmental Burden Case Study of RFID Technology in Logistics Centre",2023.0,"Sensors",23.0,3.0,1268.0,null,null,null,3.0,"10.3390/s23031268","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85147892969&doi=10.3390%2fs23031268&partnerID=40&md5=be9054db89cc1457c352215712ee5e4f","Faculty of Operation and Economics of Transport, University of Zilina, Zilina, 010 26, Slovakia; Faculty of Mechanical Engineering, University of Zilina, Zilina, 010 26, Slovakia; Institute of Lifelong Learning, University of Zilina, Zilina, 010 26, Slovakia","Bukova B., Faculty of Operation and Economics of Transport, University of Zilina, Zilina, 010 26, Slovakia; Tengler J., Faculty of Operation and Economics of Transport, University of Zilina, Zilina, 010 26, Slovakia; Brumercikova E., Faculty of Operation and Economics of Transport, University of Zilina, Zilina, 010 26, Slovakia; Brumercik F., Faculty of Mechanical Engineering, University of Zilina, Zilina, 010 26, Slovakia; Kissova O., Institute of Lifelong Learning, University of Zilina, Zilina, 010 26, Slovakia","Radio Frequency Identification (RFID) technology has established itself as an effective tool for identifying various objects in all human and business areas. There are many studies describing the use of this technology. However, scientific articles only marginally address the issue of recycling or reusing radio frequency identifiers. Radio frequency identifiers are defined as electronic waste by European Union legislation. This article deals with the environmental burden resulting from the use of radio frequency identifiers in a selected logistics centre and courier company in the Slovak and Czech Republic territories. The research and its relevance have become topical in the context of pandemics and with the increasing demand for products and courier services. In order to access the level of the above-mentioned environmental burden in a relevant way, an analysis of the circulation of transport units (pallets) and radio frequency identifiers in the selected logistics centre was carried out. The research results showed that the selected logistics centre generated annually 5.7 t of the e-waste from radio frequency identifiers placed on received pallets. The amount of 139 kg of metal was present in the e-waste quantity. The partial results of the research were applied to the e-commerce area. This article’s conclusion is dedicated to the characterization of possibilities of reducing the environmental burden from the use of radio frequency identifiers in logistics. © 2023 by the authors.","e-waste; environmental burden; RFID technology","Humans; Radio Frequency Identification Device; Radio Waves; Records; Recycling; Technology; Electronic Waste; Environmental technology; Radio waves; Wastes; Case-studies; E-wastes; Effective tool; Electronics wastes; Environmental burdens; European union; Logistics center; Radio frequencies identifiers; Radio frequency identification technology; Scientific articles; human; information processing; radio frequency identification device; radiofrequency radiation; recycling; technology; Radio frequency identification (RFID)",{"$nulls":4},"Ministerstvo školstva, vedy, výskumu a športu Slovenskej republiky, (045ŽU-4/2021)","The research was supported by the Cultural and Educational Grant Agency of the Ministry of Education, Science, Research and Sport of the Slovak Republic under project No. 045ŽU-4/2021. ","Kmet V., RFID—Technológia rádifrekvenčnej identifikácie, nové možnosti identifikácie tovarov, ATP J. Priem. Autom. A Inform, 9, pp. 86-88, (2008); David A., Mako P., Lizbetin J., Bohm P., The Impact of an environmental way of customer´s thinking on a range of choice from transport routes in maritime transport, Sustainability, 13, (2021); Fescioglu-Unver N., Choi S.H., Sheen D., Kumara S., RFID in production and service systems: Technology, applications and issue, Inf. Syst. Front, 17, pp. 1369-1380, (2015); Dedik M., Sperka A., Camaj J., Zabovska K., Traffic potential evaluation of the regions in the context of rail passenger transport—A case for Slovak Republic, Promet-Traffic Transp, 34, pp. 309-321, (2022); Sun R.T., Liu M.D., Zhao L., Research on logistics distribution path optimization based on PSO and IoT, Int. J. Wavelets Multiresolution Inf. Process, 17, (2019); Haibi A., Oufaska K., El Yassini K., Boulmalf M., Bouya M., Systematic mapping study on RFID Technology, IEEE Access, 10, pp. 6363-6380, (2022); Ruiz-Garcia L., Lunadei L., The role of RFID in agriculture: Applications, limitations and challenges, Comput. Electron. Agric, 79, pp. 42-50, (2011); Quino J., Maja J.M., Robbins J., Fernandez R.T., Owen J.S., Chappel M., RFID a drones: The next generation of plant inventory, Agriengineering, 3, (2021); Lejarreta-Andres J., Melai-Segui J., Bhattacharyya R., Vilajosana X., Sarma S.E., Toward low-cost RF-Based bulk fabric classification for the textile industry, IEEE Sens. J, 22, pp. 16586-16594, (2022); Benouakta S., Hutu F.D., Duroc Y., UHF RFID temperature sensors tag integrated into a textile yarn, Sensors, 22, (2022); Profetto L., Gherardelli M., Iadanza E., Radio Frequency Identification (RFID) in health care: Where are we? A scoping review, Health Technol, 12, pp. 879-891, (2022); Pielmeier J., Reinhart G., RFID integration as an application to industrialize and quality high-volume composite production, Proceedings of the 2015 International EURASIP Workshop on RFID Technology (EURFID), pp. 157-161; Seyfert R., Maibaum M., Kroll S., RFID data storage and their key role in exploitation of metallic second life materials, IEEE J. Radio Freq. Identif, 6, pp. 14-18, (2022); Zadorozhnyi Z.M., Murayskyi V., Shesternyak M., Hrytsyshyn A., Innovative NFC-validation system for accounting of income and expenses of public transport enterprises, Mark. Manag. Innov, 1, pp. 84-93, (2022); Mindur M., Qualitative and Temporal determinants in integrated supply chains, Proceedings of the 13th Scientific and Technical Conference on Transport Systems. Theory and Practice (TSTP), 2, pp. 27-37; Das R., Chang Y.H., Dyson M., RFID Forecast, Players and Opportunities 2022–2032, The Complete Analysis of the Global RFID Industry; Kolarovszki P., Tengler J., Impact of Sorting Machine on Life Cycle Passive UHF RFID Tags Placed on Letter Mail. Reliability and Statistics in Transportation and Communication (RelStat’15), pp. 138-146, (2015); Bukova B., Tengler J., Brumercikova E., A model of the environmental burden of RFID technology in the Slovak Republic, Sustainability, 13, (2021); Le Breton M., Liebault F., Baillet L., Charlety A., Larose E., Tedjini S., Dense and long-term monitoring of earth surface processes with passive RFID—A review, Earth-Sci. Rev, 234, (2022); Rimiene K., Grundey D., Logistics centre concept through evolution and definition, Inz. Ekon.-Eng. Econ, 4, pp. 87-95, (2007); Lizbetin J., Decision-making processes in introducing RFID technology in manufacturing company, Nase More, 65, pp. 289-292, (2018); Decky M., Remisova E., Mecar M., Bartuska L., Lizbetin J., Dreveny I., In situ Determination of Load Bearing Capacity of Soils on the Airfields, Proceedings of the World Multidisciplinary Earth Sciences Symposium, Wmess 2015, 15, pp. 11-18; The Annual Report 2021 of Logistics Centre.; Condemi A., Cucchiella F., Schettiny D., Circular economy and e-waste: An opportunity from RFID tags, Appl. Sci, 9, (2019); Zákon 119/2010 Z.Z. o obaloch (Act No. 119/2010 Coll.","F. Brumercik; Faculty of Mechanical Engineering, University of Zilina, Zilina, 010 26, Slovakia; email: brumercikf@fstroj.uniza.sk",null,"MDPI",{"$nulls":5},1.424822E7,null,null,3.6772309E7,"English","Sensors","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85147892969"]
["Osaragi T.; Taguchi Y.; Shiode N.; Shiode S.","Osaragi, Toshihiro (36933023000); Taguchi, Yuya (58363383800); Shiode, Narushige (6701758603); Shiode, Shino (6602698237)","36933023000; 58363383800; 6701758603; 6602698237","Evaluation of a Team-Based Collection and Delivery Operation",2023.0,"Sustainability (Switzerland)",15.0,11.0,9117.0,null,null,null,0.0,"10.3390/su15119117","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85163075370&doi=10.3390%2fsu15119117&partnerID=40&md5=f4ded6060de49931080ff9d889d20fc3","Department of Architecture and Building Engineering, School of Environment and Society, Tokyo Institute of Technology, Tokyo, 152-8550, Japan; Department of Geography, Geology and the Environment, Kingston University, Kingston upon Thames, KT1 2EE, United Kingdom; Department of Geography, University of London, London, Birkbeck, WC1E 7HX, United Kingdom","Osaragi T., Department of Architecture and Building Engineering, School of Environment and Society, Tokyo Institute of Technology, Tokyo, 152-8550, Japan; Taguchi Y., Department of Architecture and Building Engineering, School of Environment and Society, Tokyo Institute of Technology, Tokyo, 152-8550, Japan; Shiode N., Department of Geography, Geology and the Environment, Kingston University, Kingston upon Thames, KT1 2EE, United Kingdom; Shiode S., Department of Geography, University of London, London, Birkbeck, WC1E 7HX, United Kingdom","The rise in the volume of e-commerce is adding increasing pressure on the logistics of parcel delivery. To improve the efficiency of their operations, the parcel industry in Japan is exploring team-based collection and delivery (TCD), whereby the sales driver (SD) hands out parcels to the field crews (FC), who subsequently deliver them to the door. However, the efficiency of TCD is still understudied. This study proposes a method for optimizing the delivery route for TCD and evaluates the efficiency of the ongoing operation. The TCD delivery problem focuses on minimizing the task completion time using parameters derived through surveys of the actual operations. Comparison between seven different methods show that the newly proposed method of fuzzy c-means clustering with a genetic algorithm outperforms the rest, rapidly computing sufficiently accurate results. Results suggest that the proposed optimal route reduces the total delivery time by up to 18.7%. However, the amount of time saved varies considerably by the area and the number of parcels delivered. Additional constraints for improving driver safety, the cost-benefit of increasing FCs, and the impact on the environmental cost are also considered. The proposed method also helps spread the workload and the travel time of the FCs more evenly, thus further reducing the total delivery time. © 2023 by the authors.","delivery operation; optimisation; parcel industry; team-based delivery; travelling salesperson problem","Japan; comparative study; cost-benefit analysis; electronic commerce; genetic algorithm; logistics; travel time; working conditions",{"$nulls":6},"Gunjan M., Sonja M., Courier Services Market by Service Type (B2B, B2C, C2C), by Destination (Domestic, International), by End Use (Services, Wholesale and Retail Trade, Healthcare, Industrial and Manufacturing, Others): Global Opportunity Analysis and Industry Forecast, 2021–2031, Allied Market Research, (2022); Survey and Counting Methods for the Number of Courier Services in 2018, (2018); Results of “Survey on Mail Order and Redelivery” (December 2018 Survey), (2018); Sachan A., Datta S., Review of supply chain management and logistics research, Int. J. Phys. Distrib, 35, pp. 664-705, (2005); Haughton M.A., Measuring and managing the learning requirements of route reoptimization of delivery vehicles drivers, J. Bus. Logist, 23, pp. 45-66, (2002); Punakivi M., Yrjola H., Holmstrom J., Solving the last mile issue: Reception box or delivery box?, Int. J. Phys. Distrib, 31, pp. 427-439, (2001); Caplice C., Sheffi Y., Optimization-based procurement for transportation services, J. Bus. Logist, 24, pp. 109-128, (2003); Giddings A.P., Bailey T.G., Moore J.T., Optimality analysis of facility location problems using response surface methodology, Int. J. Phys. Distrib, 31, pp. 38-52, (2001); Gonzalez E.L., Fernandez M.A.R., Genetic optimisation of a fuzzy distribution model, Int. J. Phys. Distrib, 30, pp. 681-696, (2000); Lee T.-R., Ueng J.-H., A study of vehicle routing problems with load-balancing, Int. J. Phys. Distrib, 29, pp. 646-657, (1999); Koc C., Laporte G., Tukenmez I., A review of vehicle routing with simultaneous pickup and delivery, Comput. Oper. Res, 122, (2020); Li Y., Research trends on online shopping logistics with focus on the last mile problem, Bull. Fac. Commer. Meiji Univ, 100, pp. 115-128, (2018); Kawanishi Y., Suzuki T., Effect of the improvement in delivery method on vehicle mileage reduction in home delivery service system, J. City Plan. Inst. Jpn, 53, pp. 51-56, (2018); Liu Y., Suzuki T., Model analysis on delivery efficiency improvement combining truck and drone, Papers and Proceedings of the Geographic Information Systems Association [CD-ROM], (2019); Miyatake H., Nemoto T., Hyashi K., Delivery density requirements for the introduction of “team delivery” in a courier network, Jpn. J. Transp. Econ, 59, pp. 205-212, (2016); Gevaers R., Van de Voorde E., Vanelslander T., Characteristics of innovations in last-mile logistics: Using best practices, case studies and making the link with green and sustainable logistics, Proceedings of the European Transport Conference; Song L., Guan W., Cherrett T., Li B., Quantifying the greenhouse gas emissions of local collection-and-delivery points for last-mile deliveries, Transp. Res. Rec, 2340, pp. 66-73, (2013); Iwan S., Kijewska K., Lemke J., Analysis of parcel lockers’ efficiency as the last mile delivery solution—The results of the research in Poland, Transp. Res. Procedia, 12, pp. 644-655, (2015); Boyer K.K., Prud'homme A.M., Chung W., The last mile challenge: Evaluating the effects of customer density and delivery window patterns, J. Bus. Logist, 30, pp. 185-201, (2009); Campbell A.M., Savelsbergh M., Incentive schemes for attended home delivery services, Transp. Sci, 40, pp. 327-341, (2006); Dantzig G.B., Ramser J.H., The truck dispatching problem, Manag. Sci, 6, pp. 80-91, (1956); Ogawa M., Inoue M., Enumerating all the optimal solutions of multiple travelling salesman problem by using simpath algorithm, Inf. Process. Soc. Jpn, 114, pp. 321-328, (2014); Chang Y.S., Lee H.J., Optimal delivery routing with wider drone-delivery areas along a shorter truck-route, Expert Syst. Appl, 104, pp. 307-317, (2018); Nakayama T., Maeda M., Nakanishi S., Transport planning of supplies using genetic algorithms under consideration for roads of plural vehicles, Proceedings of the 21st Fuzzy System Symposium, pp. 290-293; Ono T., Kanagawa A., Takahashi H., Heuristic solution for multiple traveling salesman problems with multiple depots using fuzzy c-means clustering method, Inst. Electron. Inf. Commun. Eng. A, J87-A, pp. 938-948, (2004); Frederickson G.N., Hecht M.S., Kim C.E., Approximation algorithms for some routing problems, SIAM J. Comput, 7, pp. 178-193, (1978); Miyata E., Hamamatsu Y., An optimization method for the multi-route searching problem, Trans. Inst. Electr. Eng. Jpn, 118-C, pp. 1540-1541, (1998); Gillett B.E., Miller L.R., A heuristic algorithm for the vehicle-dispatch problem, Oper. Res, 22, pp. 340-349, (1974); Pahwa A., Jaller M., A cost-based comparative analysis of different last-mile strategies for e-commerce delivery, Transp. Res. E, 164, (2022); Liu D., Yan P., Pu Z., Wang Y., Kaisar E.I., Hybrid artificial immune algorithm for optimizing a Van-Robot E-grocery delivery system, Transp. Res. E, 154, (2021); Janjevic M., Winkenbach M., Merchan D., Integrating collection-and-delivery points in the strategic design of urban last-mile e-commerce distribution networks, Transp. Res. E, 131, pp. 37-67, (2019); Ozarik S.S., Veelenturf L.P., Woensel T.V., Laporte G., Optimizing e-commerce last-mile vehicle routing and scheduling under uncertain customer presence, Transp. Res. E, 148, (2021); Imada S., Nakajima J., Furukawa M., Practical Solution for n-TSP by Use of LCO, Proceedings of the The Japan Society for Precision Engineering Spring Meeting, H19, pp. 587-588; Kitano H., Genetic algorithms, J. Jpn. Soc. Artif. Intell, 7, pp. 26-37, (1992); Browne M., Allen J., Nemoto T., Visser J., Light goods vehicles in urban areas, Procedia Soc. Behav. Sci, 2, pp. 5911-5919, (2010); Munuzuri J., van Duin J.H.R., Escudero A., How efficient is city logistics? Estimating ecological footprints for urban freight deliveries, Procedia Soc. Behav. Sci, 2, pp. 6165-6176, (2010); Kawamura K., Rashidi L.H., Economic, environmental and congestion impacts of trucking, Procedia Soc. Behav. Sci, 2, pp. 5920-5930, (2010); Russo F., Comi A., Measures for sustainable freight transportation at urban scale: Expected goals and tested results in Europe, J. Urban Plan. Dev, 137, pp. 142-152, (2011); Qi W., Li L., Liu S., Shen Z.J.M., Shared mobility for last-mile delivery: Design, operational prescriptions, and environmental impact, Manuf. Serv. Oper. Manag, 20, pp. 737-751, (2018)","T. Osaragi; Department of Architecture and Building Engineering, School of Environment and Society, Tokyo Institute of Technology, Tokyo, 152-8550, Japan; email: osaragi.t.aa@m.titech.ac.jp",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85163075370"]
["Rafael A.-A.; Roel G.; Wouter D.","Rafael, Arevalo-Ascanio (58408973300); Roel, Gevaers (58408262100); Wouter, Dewulf (58408973400)","58408973300; 58408262100; 58408973400","Strategic Multi-Echelon and Cross-Modal CO2 Emissions Calculation in Parcel Distribution Networks: First Step Toward a Common Language",2023.0,"Transportation Research Record",2677.0,6.0,null,620.0,630.0,10.0,0.0,"10.1177/03611981221149431","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85163667109&doi=10.1177%2f03611981221149431&partnerID=40&md5=f87d68357f8047d4769c0c28cd1c9724","Department of Transport and Regional Economics, University of Antwerp, Antwerpen, Belgium; MooV, Flemish Institute for Technological Research (VITO), Mol, Belgium","Rafael A.-A., Department of Transport and Regional Economics, University of Antwerp, Antwerpen, Belgium, MooV, Flemish Institute for Technological Research (VITO), Mol, Belgium; Roel G., Department of Transport and Regional Economics, University of Antwerp, Antwerpen, Belgium; Wouter D., Department of Transport and Regional Economics, University of Antwerp, Antwerpen, Belgium","Sustainability in distribution networks is currently the focus of study at institutional, academic, and commercial levels. Reducing greenhouse gas emissions is on all the programmatic agendas, and the goals are clear for years toward carbon neutrality. As one of the main polluting sectors and growing trends with e-commerce, transport must align its efforts to contribute to the cause. In this paper, a strategic model is proposed for the calculation of CO2 emissions in the distribution of parcels. Novel in this research is that it integrates both line-haul transport and last-mile distribution at a strategic level and includes key elements such as time windows and population density in the calculation. Through an applied case in parcel distribution in Belgium, the calculation of CO2 emissions with the proposed model is illustrated. The model is enhanced by analyzing the time windows effect and the electrification of the last-mile fleet. The results concerning CO2 emissions in parcel distribution in Belgium show that it is possible to reduce emissions not only through the electrification of the fleet but also with an efficient distribution network. The effect of the network structure will be more evident with international shipments that include more polluting modes of transport. However, the results for Belgium show that the last mile is currently the most polluting segment. The proposed model could further be complemented by including reverse logistics, in-house calculation, and packaging emissions. © National Academy of Sciences: Transportation Research Board 2023.","air quality and greenhouse gas mitigation; emissions modeling; sustainability and resilience; transportation and sustainability","Carbon dioxide; Electric utilities; Fleet operations; Gas emissions; Greenhouse gases; Population statistics; Sustainable development; Air quality and greenhouse gas mitigation; Belgium; CO 2 emission; Emission model; Greenhouse gas mitigation; Last mile; Multiechelon; Sustainability and resilience; Time windows; Transportation and sustainability; Air quality",{"$nulls":6},"(2021); Sources of Greenhouse Gas Emissions | US EPA, (2020); CO2 Emissions by Sector, World 1990-2019, (2019); Cars, Planes, Trains: Where do CO<sub>2</sub> Emissions from Transport Come from?, Our World in Data, (2020); CO<sub>2</sub> Emissions from Cars: Facts and Figures (Infographics), News - European Parliament, (2019); ICAO Carbon Emissions Calculator; Guo Y., Hu F., Allaoui H., Boulaksil Y., A Distributed Approximation Approach for Solving the Sustainable Supply Chain Network Design Problem, International Journal of Production Research, 57, 11, pp. 3695-3718, (2019); Gong D.-C., Chen P.-S., Lu T.-Y., Multi-Objective Optimization of Green Supply Chain Network Designs for Transportation Mode Selection, Scientia Iranica, 24, 6, pp. 3355-3370, (2017); Yu F., Yang Y., Chang D., Carbon Footprint Based Green Supplier Selection Under Dynamic Environment, Journal of Cleaner Production, 170, pp. 880-889, (2018); Jerbi A., Jribi H., Aljuaid A.M., Hachicha W., Masmoudi F., Design of Supply Chain Transportation Pooling Strategy for Reducing CO<sub>2</sub> Emissions Using a Simulation-Based Methodology: A Case Study, Sustainability, 14, 4, (2022); Klein D., Wolf C., Schulz C., Weber-Blaschke G., Environmental Impacts of Various Biomass Supply Chains for the Provision of Raw Wood in Bavaria, Germany, with Focus on Climate Change, Science of The Total Environment, 539, pp. 45-60, (2016); Nurul H.R., Haslenda H., Yunus N.A., Klemes J.J., Integrated GIS-AHP Optimization for Bioethanol from Oil Palm Biomass Supply Chain Network Design, Chemical Engineering Transactions, 83, pp. 571-576, (2021); Lozano-Moreno J.A., Marechal F., Biomass Logistics and Environmental Impact Modelling for Sugar-Ethanol Production, Journal of Cleaner Production, 210, pp. 317-324, (2019); Mubarak A., Zainal F., Development of a Framework for the Calculation of CO2 Emissions in Transport and Logistics in Southeast Asia, International Journal of Technology, 4, pp. 787-796, (2018); Mubarak A., Rahman I., A Comparative Analysis of Carbon Emissions from Transportation and Logistics of the Consumer Goods Industry in Southeast Asia, International Journal of Technology, 11, 2, pp. 333-341, (2020); Edwards J.B., McKinnon A.C., Cullinane S.L., Comparative Analysis of the Carbon Footprints of Conventional and Online Retailing: A ‘Last Mile’ Perspective, International Journal of Physical Distribution & Logistics Management, 40, 1-2, pp. 103-123, (2010); Tsakalidis A., Krause J., Julea A., Peduzzi E., Pisoni E., Thiel C., Electric Light Commercial Vehicles: Are they the Sleeping Giant of Electromobility?, Transportation Research Part D: Transport and Environment, 86, (2020); Woody M., Craig M.T., Vaishnav P.T., Lewis G.M., Keoleian G.A., Optimizing Future Cost and Emissions of Electric Delivery Vehicles, Journal of Industrial Ecology, 26, 3, pp. 1108-1122, (2022); Davydenko I., Ehrler V., de Ree D., Lewis A., Tavasszy L., Towards a Global CO<sub>2</sub> Calculation Standard for Supply Chains: Suggestions for Methodological Improvements, Transportation Research Part D: Transport and Environment, 32, pp. 362-372, (2014); Davydenko I., Hopman M., van Gijlswijk R.N., Rondaij A., Spreen J.S., Towards Harmonization of Carbon Footprinting Methodologies, (2019); Wild P., Recommendations for a Future Global CO<sub>2</sub>-Calculation Standard for Transport and Logistics, Transportation Research Part D: Transport and Environment, 100, (2021); Calculating GHG Emissions for Freight Forwarding and Logistics Services, (2012); Konecny V., Petro F., Calculation of Selected Emissions from Transport Services in Road Public Transport, MATEC Web of Conferences, 134, (2017); Mckinnon A., Piecyk M., Measuring and Managing CO2 Emissions of European Chemical Transport, (2011); The GHG Emissions Calculation Tool, (2014); Green Logistics Method for the Ecological Assessment of Logistics Service Providers, (2015); Global Logistics Emissions Council Framework for Logistics Emissions Accounting and Reporting, (2019); Optimalisatie Transportplanning - Lean & Green; STREAM Freight Transport - Emissions of Freight Transport Modes, (2016); GHG Information for Transport Services, (2019); Vehicle Energy Consumption Calculation TOol – VECTO, (2018); Ecological Transport Information Tool for Worldwide Transports, (2019); BigMile Carbon Analytics – The Standard in CO2 Footprint Calculation and Optimization;  and Other Greenhouse Gases Emissions by Cabon-Care; OSCAR, Universal Postal Union, (2020); Carbon Calculator, (2022); Laporte G., Nobert Y., Exact Algorithms for the Vehicle Routing Problem, North-Holland Mathematics Studies, 132, C, pp. 147-184, (1987); 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Bergmann F.M., Wagner S.M., Winkenbach M., Integrating First-Mile Pickup and Last-Mile Delivery on Shared Vehicle Routes for Efficient Urban E-Commerce Distribution, Transportation Research Part B: Methodological, 131, pp. 26-62, (2020); Cardenas I.D., Dewulf W., Vanelslander T., Smet C., Beckers J., The E-Commerce Parcel Delivery Market and the Implications of Home B2C Deliveries vs Pick-up Points, International Journal of Transport Economics, 44, 2, pp. 235-256, (2017); Gevaers R., Van de Voorde E., Vanelslander T., Cost Modelling and Simulation of Last-Mile Characteristics in an Innovative B2C Supply Chain Environment with Implications on Urban Areas and Cities, Procedia - Social and Behavioral Sciences, 125, pp. 398-411, (2014); European E-Commerce Report 2022, (2022); Beckers J., Weekx S., Beutels P., Verhetsel A., COVID-19 and Retail: The Catalyst for E-Commerce in Belgium?, Journal of Retailing and Consumer Services, 62, (2021); Market Share Based on Volume within the Segment of Parcel and Express Mail Items, (2021); Retail Carbon Footprints: Measuring Impacts from Real Estate and Technology, (2021)","A.-A. Rafael; Department of Transport and Regional Economics, University of Antwerp, Antwerpen, Belgium; email: rafael.arevaloascanio@uantwerpen.be",null,"SAGE Publications Ltd",{"$nulls":5},3611981.0,null,"TRRED",null,"English","Transp Res Rec","Article","Final",null,"Scopus","2-s2.0-85163667109"]
["Banik D.; Ibne Hossain N.U.; Govindan K.; Nur F.; Babski-Reeves K.","Banik, Debapriya (57480766300); Ibne Hossain, Niamat Ullah (57193446293); Govindan, Kannan (54986334000); Nur, Farjana (57193446315); Babski-Reeves, Kari (6507403103)","57480766300; 57193446293; 54986334000; 57193446315; 6507403103","A decision support model for selecting unmanned aerial vehicle for medical supplies: context of COVID-19 pandemic",2023.0,"International Journal of Logistics Management",34.0,2.0,null,473.0,496.0,23.0,15.0,"10.1108/IJLM-06-2021-0334","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85125960675&doi=10.1108%2fIJLM-06-2021-0334&partnerID=40&md5=0419388b0b62e1cc8c0034ee283de9f5","Department of Industrial, Manufacturing and Systems Engineering (IMSE), The University of Texas at El Paso, El Paso, TX, United States; Department of Engineering Management, Arkansas State University, Jonesboro, AR, United States; Department of Technology and Innovation, Center for Sustainable Supply Chain Engineering, Danish Institute for Advanced Study, University of Southern Denmark, Odense, Denmark; Yonsei Frontier Lab, Yonsei University, Seoul, South Korea; Department of Industrial and Systems Engineering, Mississippi State University, Mississippi State, MS, United States","Banik D., Department of Industrial, Manufacturing and Systems Engineering (IMSE), The University of Texas at El Paso, El Paso, TX, United States; Ibne Hossain N.U., Department of Engineering Management, Arkansas State University, Jonesboro, AR, United States; Govindan K., Department of Technology and Innovation, Center for Sustainable Supply Chain Engineering, Danish Institute for Advanced Study, University of Southern Denmark, Odense, Denmark, Yonsei Frontier Lab, Yonsei University, Seoul, South Korea; Nur F., Department of Industrial and Systems Engineering, Mississippi State University, Mississippi State, MS, United States; Babski-Reeves K., Department of Industrial and Systems Engineering, Mississippi State University, Mississippi State, MS, United States","Purpose: In recent times, due to rapid urbanization and the expansion of the E-commerce industry, drone delivery has become a point of interest for many researchers and industry practitioners. Several factors are directly or indirectly responsible for adopting drone delivery, such as customer expectations, delivery urgency and flexibility to name a few. As the traditional mode of delivery has some potential drawbacks to deliver medical supplies in both rural and urban settings, unmanned aerial vehicles can be considered as an alternative to overcome the difficulties. For this reason, drones are incorporated in the healthcare supply chain to transport lifesaving essential medicine or blood within a very short time. However, since there are numerous types of drones with varying characteristics such as flight distance, payload-carrying capacity, battery power, etc., selecting an optimal drone for a particular scenario becomes a major challenge for the decision-makers. To fill this void, a decision support model has been developed to select an optimal drone for two specific scenarios related to medical supplies delivery. Design/methodology/approach: The authors proposed a methodology that incorporates graph theory and matrix approach (GTMA) to select an optimal drone for two specific scenarios related to medical supplies delivery at (1) urban areas and (2) rural/remote areas based on a set of criteria and sub-criteria critical for successful drone implementation. Findings: The findings of this study indicate that drones equipped with payload handling capacity and package handling flexibility get more preference in urban region scenarios. In contrast, drones with longer flight distances are prioritized most often for disaster case scenarios where the road communication system is either destroyed or inaccessible. Research limitations/implications: The methodology formulated in this paper has implications in both academic and industrial settings. This study addresses critical gaps in the existing literature by formulating a mathematical model to find the most suitable drone for a specific scenario based on its criteria and sub-criteria rather than considering a fleet of drones is always at one's disposal. Practical implications: This research will serve as a guideline for the practitioners to select the optimal drone in different scenarios related to medical supplies delivery. Social implications: The proposed methodology incorporates GTMA to assist decision-makers in order to appropriately choose a particular drone based on its characteristics crucial for that scenario. Originality/value: This research will serve as a guideline for the practitioners to select the optimal drone in different scenarios related to medical supplies delivery. © 2022, Emerald Publishing Limited.","COVID-19; Disruptions; Drone selection; Graph theory and matrix approach (GTMA); Medicals supplies; Unmanned aerial vehicle (UAV)",{"$nulls":7},"Adwibowo A., Assessments of heavy lift UAV quadcopter drone to support COVID 19 vaccine cold chain delivery for indigenous people in remote areas in South East Asia, (2021); Anbaroglu B., Parcel Delivery in an Urban Environment Using Unmanned Aerial Systems: A Vision Paper, (2017); Aurambout J.P., Gkoumas K., Ciuffo B., Last mile delivery by drones: an estimation of viable market potential and access to citizens across European cities, European Transport Research Review, 11, 1, (2019); Aziz N.F., Sorooshian S., Mahmud F., MCDM-AHP method in decision makings, ARPN Journal of Engineering and Applied Sciences, 11, 11, pp. 7217-7220, (2016); Baek D., Chen Y., Bocca A., Macii A., Macii E., Poncino M., Battery-aware energy model of drone delivery tasks, Proceedings of the International Symposium on Low Power Electronics and Design, pp. 1-6, (2018); 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Ibne Hossain; Department of Engineering Management, Arkansas State University, Jonesboro, United States; email: niamat.hossain@gmail.com",null,"Emerald Publishing",{"$nulls":5},9574093.0,null,null,null,"English","Int. J. Logist. Manage.","Article","Final",null,"Scopus","2-s2.0-85125960675"]
["Nanda P.; Patnaik S.","Nanda, Pragyan (57193560911); Patnaik, Srikanta (7102590512)","57193560911; 7102590512","A multi-agent coalition-based approach for order fulfilment in e-commerce",2023.0,"Decision Analytics Journal",7.0,null,100227.0,null,null,null,2.0,"10.1016/j.dajour.2023.100227","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85153273805&doi=10.1016%2fj.dajour.2023.100227&partnerID=40&md5=129e34241a0948761065167b3f94b937","SOA University, Odisha, Bhubaneswar, India; Interscience Institute of Management and Technology, Odisha, Bhubaneswar, India","Nanda P., SOA University, Odisha, Bhubaneswar, India; Patnaik S., Interscience Institute of Management and Technology, Odisha, Bhubaneswar, India","The rapid growth of e-commerce in the recent pandemic is driven by the wide adoption of digitization, extensive use of smartphones, affordable internet services, and the convenience of shopping from anywhere and anytime. Some key indexes for measuring the performance of the e-commerce organization include affordable deals, competitive prices, and efficiency in fulfilling orders while ensuring customer satisfaction. Customer review ratings are one of the significant metrics to measure customer satisfaction, influencing other customers to make purchase decisions. Therefore, favourable customer reviews and ratings of various products presented on e-commerce platforms provide competitive advantages to sellers. Usually, customers placing an order on an e-commerce platform are notified about the estimated delivery date. Consequently, after receiving the product delivery, customers give feedback in the form of review comments and ratings to communicate their satisfaction or dissatisfaction towards the seller. In case of delays in order fulfilment, the customers mostly give negative feedback along with poor ratings, which can affect the seller's reputation, thus impacting future sales. Therefore, the central idea of this research is to adopt a resilient order fulfilment approach by identifying the optimal set of sellers based on fulfilment cost, lead time for fulfilment and review rating score obtained from previous orders. The research work has been divided into three different phases. Firstly, significant constraints associated with an e-commerce fulfilment system have been identified from existing literature. The relationship between the lead time in order fulfilment and review rating score is studied. Finally, a multi-agent coalition-based framework is proposed for generating the Pareto-optimal set of reliable sellers to fulfil an order. Although sellers in an e-commerce marketplace are usually considered competitors of each other, a temporary coalition among the sellers for aggregated order fulfilment can minimize fulfilment costs. The proposed multi-agent coalition-based framework is implemented on real-time data to confirm the findings. © 2023 The Author(s)","Coalition-formation; Cost minimization; E-commerce marketplace; Lead time; Order fulfilment; Review score",{"$nulls":7},"North M.J., Macal C.M., Managing Business Complexity: Discovering Strategic Solutions with Agent-Based Modeling and Simulation, (2007); Martel A., Klibi W., Designing Value-Creating Supply Chain Networks, (2016); Mohamad A.H., Hassan G.F., Abd Elrahman A.S., Impacts of e-commerce on planning and designing commercial activities centers: A developed approach, Ain Shams Eng. J., 13, 4, (2022); Bask A., Lipponen M., Tinnila M., E-commerce logistics: a literature research review and topics for future research, Int. J. E-Serv. Mob. Appl. (IJESMA), 4, 3, pp. 1-22, (2012); Colla E., Lapoule P., E-commerce: exploring the critical success factors, Int. J. Retail Distrib. 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["Çavdar B.; Erkip N.","Çavdar, Bahar (56488145800); Erkip, Nesim (6602243535)","56488145800; 6602243535","Word-of-Mouth on Action: Analysis of Optimal Shipment Policy When Customers are Resentful",2023.0,"Omega (United Kingdom)",118.0,null,102865.0,null,null,null,3.0,"10.1016/j.omega.2023.102865","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85150437576&doi=10.1016%2fj.omega.2023.102865&partnerID=40&md5=7f04bc6faf8b96d46c96ba870a407646","Department of Engineering Technology and Industrial Distribution, Texas A&M University, College Station, TX, United States; Department of Industrial Engineering, Bilkent University, Ankara, Turkey","Çavdar B., Department of Engineering Technology and Industrial Distribution, Texas A&M University, College Station, TX, United States; Erkip N., Department of Industrial Engineering, Bilkent University, Ankara, Turkey","Word-of-Mouth (WoM) communication via online reviews plays a vital role in customers’ purchasing decisions. As such, retailers must consider the impact of WoM to manage customer perceptions and future demand. This paper considers an online shopping system with premium and regular customers. Building on the behavioral and operations management literature, we model customer preferences based on the perceived service quality indicated by WoM and integrate this into the retailer's operational problem to determine a shipment policy regarding the timing of consolidated shipments and the treatment of regular demand. First, we study the e-tailer's problem when they have no knowledge of WoM and only react to the changes in demand. We analyze the long-term behavior of customer demand and show that potential market size and customer sensitivity are the key parameters determining this behavior. Then, we build a model to integrate the knowledge of WoM into operational decision-making and partially characterize the optimal solution. We show that (i) underpromise-and-overdeliver can be a hurtful strategy since it creates a false sense of fast delivery for the regular service, (ii) relaxations in operational constraints may hurt profitability due to the associated difficulties of managing perceptions, and (iii) seeking a stationary policy can lead to suboptimal solutions; therefore, cyclic policies should also be considered when appropriate. © 2023","E-tailing; Endogenous demand; Shipment consolidation; Word-of-Mouth","Sales; Ships; Action analysis; Customer perceptions; E-tailing; Endogenous demand; On-line Shopping systems; Online reviews; Purchasing decisions; Regular customers; Shipment consolidation; Word-of-mouth communication; article; decision making; leisure; online shopping; perception; Decision making",{"$nulls":6},"Kaemingk D., (2022); Banker S., (2022); Kim W., Wang X.C., The adoption of alternative delivery locations in new york city: Who and how far?, Transportation Research Part A: Policy and Practice, 158, pp. 127-140, (2022); 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Du S., Wang L., Hu L., Omnichannel management with consumer disappointment aversion, International Journal of Production Economics, 215, pp. 84-101, (2019); Netessine S., Rudi N., Supply chain choice on the internet, Management Science, 52, 6, pp. 844-864, (2006); Chiang W.-Y.K., Monahan G.E., Managing inventories in a two-echelon dual-channel supply chain, European Journal of Operational Research, 162, 2, pp. 325-341, (2005); Cheung M., Elmachtoub A.N., Levi R., Shmoys D.B., The submodular joint replenishment problem, Mathematical Programming, 158, 1-2, pp. 207-233, (2016); Dick A.S., Lord K.R., The impact of membership fees on consumer attitude and choice, Psychology & Marketing, 15, 1, pp. 41-58, (1998); Haller A., Schwabe L., Sunk costs in the human brain, Neuroimage, 97, pp. 127-133, (2014); Soman D., The mental accounting of sunk time costs: Why time is not like money, Journal of Behavioral Decision Making, 14, 3, pp. 169-185, (2001); Johnson B.; Anders M., (2022)","B. Çavdar; Department of Engineering Technology and Industrial Distribution, Texas A&M University, College Station, United States; email: bcavdar@tamu.edu",null,"Elsevier Ltd",{"$nulls":5},3050483.0,null,"OMEGA",null,"English","Omega","Article","Final",null,"Scopus","2-s2.0-85150437576"]
["Pajić V.; Kilibarda M.; Andrejić M.","Pajić, Vukašin (57298127000); Kilibarda, Milorad (35368337500); Andrejić, Milan (55251649500)","57298127000; 35368337500; 55251649500","A Novel Hybrid Approach for Evaluation of Resilient 4PL Provider for E-Commerce",2023.0,"Mathematics",11.0,3.0,511.0,null,null,null,3.0,"10.3390/math11030511","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85147831645&doi=10.3390%2fmath11030511&partnerID=40&md5=1ddaa767dcdf4bef1c538e7c755ee717","Faculty of Transport and Traffic Engineering, University of Belgrade, Vojvode Stepe 305, Belgrade, 11000, Serbia","Pajić V., Faculty of Transport and Traffic Engineering, University of Belgrade, Vojvode Stepe 305, Belgrade, 11000, Serbia; Kilibarda M., Faculty of Transport and Traffic Engineering, University of Belgrade, Vojvode Stepe 305, Belgrade, 11000, Serbia; Andrejić M., Faculty of Transport and Traffic Engineering, University of Belgrade, Vojvode Stepe 305, Belgrade, 11000, Serbia","Today, e-commerce allows consumers access to a wide range of products on the global market, quick and convenient selection, purchase, ordering, and payment of products. Consumers expect to receive the products they bought online, very quickly, at favorable prices and delivery conditions. However, it is often not possible, because global supply chains are realized over large geographical distances, with a whole range of disruptions and challenges that need to be successfully overcome. With the aim of efficiently delivering products and meeting consumer expectations, retailers often leave this job to specialized and resilient logistics companies better known as fourth-party logistics (4PL) providers. On this occasion, it is necessary to conduct a very thorough evaluation of the logistics provider based on appropriate scientific approaches and models. In this paper, a new hybrid approach for the evaluation of resilient 4PLs was proposed, with the aim of providing appropriate support for the decision-making system on product delivery in e-commerce. The hybrid approach is based on the fuzzy full consistency method (FUCOM), evidence theory (ET), rule-based transformation (RBT), and weighted aggregated sum product assessment (WASPAS) methods. The proposed model was tested and applied to an example of an online retailer, which sells and delivers products originating from China and the countries of the Far East to the market of the Western Balkans and Southeastern Europe. Five 4PL providers were evaluated and ranked according to 10 criteria. According to the results, the most important criterion was IT capabilities, while the least important was cooperation. Additionally, sensitivity analysis was carried out to determine whether the final ranking will change. The obtained results showed that the proposed methodology represents a valuable decision support tool that can be used for solving not only the problem described in this paper but also similar problems. © 2023 by the authors.","4PL; e-commerce; evidence theory; fuzzy FUCOM; logistics; resilience; WASPAS",{"$nulls":5},"Ministarstvo Prosvete, Nauke i Tehnološkog Razvoja, MPNTR, (TR 36006)","This paper was supported by the Ministry of Education, Science, and Technological Development of the Republic of Serbia through the project TR 36006. ","Keenan M., Global Ecommerce Explained: Stats and Trends to Watch in 2022, (2022); Gurau C., Ranchhod A., Hackney R., Internet transactions and physical logistics: Conflict or complementarity?, Logist. Inf. Manag, 14, pp. 33-43, (2001); Delfmann W., Albers S., Gehring M., The impact of electronic commerce on logistics service providers, Int. J. Phys. Distrib. Logist. 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["Guru S.; Verma S.; Baheti P.; Dagar V.","Guru, Sunita (57221256589); Verma, Subir (56998052400); Baheti, Pratibha (58125747200); Dagar, Vishal (57218885592)","57221256589; 56998052400; 58125747200; 57218885592","Assessing the feasibility of hyperlocal delivery model as an effective distribution channel",2023.0,"Management Decision",61.0,6.0,null,1634.0,1655.0,21.0,20.0,"10.1108/MD-03-2022-0407","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85149324746&doi=10.1108%2fMD-03-2022-0407&partnerID=40&md5=17f406add615d29c8c9315268940ea33","Department of Operations, Institute of Management, Nirma University, Ahmedabad, India; Department of Supply Chain, DHL Express India Private Limited, New Delhi, India; Department of Economics, Great Lakes Institute of Management Gurgaon, Gurgaon, India; Department of Organizational Behavior, Institute of Management, Nirma University, Ahmedabad, India","Guru S., Department of Operations, Institute of Management, Nirma University, Ahmedabad, India; Verma S., Department of Organizational Behavior, Institute of Management, Nirma University, Ahmedabad, India; Baheti P., Department of Supply Chain, DHL Express India Private Limited, New Delhi, India; Dagar V., Department of Economics, Great Lakes Institute of Management Gurgaon, Gurgaon, India","Purpose: The successive waves of the Covid-19 SARS-II pandemic and the attendant lockdown imposed by the governments worldwide drove the economic activities to a halt. Offices and factories closed, production of goods and services declined and supply chains got severely disrupted. Many companies were embattled with the grim reality of shrinkage of aggregate demand, first due to supply shock and later due to loss of jobs and wages. Amidst all this, the handling and shipping of commodities became extremely complex. As the pandemic shifted consumer preference in favour of digital platforms, more and more fast-moving consumer goods (FMCG) companies were confronted with multiple strategies and choices of an appropriate distribution channel to ensure smooth delivery of raw materials and products. The present study aims to study this shift and its implications in the Indian context. Design/methodology/approach: A mix-method approach, integrating quantitative and qualitative analysis, is employed to investigate the factors influencing the selection of distribution channels amongst general trade, modern trade, e-commerce and hyperlocal for FMCG companies in India. The first phase of the study uses exploratory factor analysis (EFA), followed by the application of analytical hierarchy process (AHP) approach in a fuzzy environment to realise the priority weights and ranking of the identified factors. Finally, sensitivity analysis is performed to confirm the robustness of the fuzzy analytical hierarchy process (FAHP) outcomes. Findings: The study revealed that modern trade has emerged as the most favoured channel in the post-pandemic Indian economy. It has the potential to disrupt general trade. The study also revealed that the hyperlocal delivery model is not economically viable, and the partnership of FMCG companies with these applications is at best a short-term solution. However, it must be submitted that due to its sheer capability to ensure quick deliveries within a confined geographic area, hyperlocal delivery will gain momentum with the advancement of technology. Originality/value: This study can be seen as the first attempt to investigate the issues related to the selection of the distribution channels in the FMCG sector of India using multi-criteria decision-making technique (MCDM). © 2023, Emerald Publishing Limited.","COVID-19 impact on FMCG; Distribution channel; Efficiency; FAHP; Supply chain management",{"$nulls":5},"Nirma University, NU","The authors are extremely thankful to the Editor-in-Chief, the Associate Editor and three anonymous reviewers for their suggestions and feedback during the review process. The authors would further like to extend their gratitude to Prof Pradeep Kautish, Institute of Management, Nirma University, Ahmedabad for academic encouragement and motivation for this research endeavour.","Abraham O., Thakur T., Brasel K., Norton D., Rosenberger C.A., Development of the adolescent opioid safety and learning (AOSL) scale using exploratory factor analysis, Research in Social and Administrative Pharmacy, 18, 5, pp. 2796-2803, (2022); Affonso R., Marcotte F., Grabot B., Sales and operations planning: the supply chain pillar, Production Planning and Control, 19, 2, pp. 132-141, (2008); AlKheder S., AlKandari D., AlYatama S., Sustainable assessment criteria for airport runway material selection: a fuzzy analytical hierarchy approach, Engineering, Construction and Architectural Management, 29, 8, pp. 3091-3113, (2021); Andrejic M., Kilibarda M., Distribution channels selection using PCA-DEA approach, International Journal for Traffic and Transport Engineering, 5, 1, pp. 74-81, (2015); Anser M.K., Khan M.A., Awan U., Batool R., Zaman K., Imran M., Khan A., Bakar Z.A., The role of technological innovation in a dynamic model of the environmental supply chain curve: evidence from a panel of 102 countries, Processes, 8, 9, (2020); Azimifard A., Moosavirad S.H., Ariafar S., Designing steel supply chain and assessing the embedded CO2 emission based on the input-output table by using DEMATEL method, Management Decision, 56, 4, pp. 757-776, (2018); Balakrishnan P., Mishra D., Grofers founder says quick-commerce model has path to profitability, (2021); Ballou H.R., Business Logistics/Supply Chain Management, (2004); Barney J.B., Firm resources and sustained competitive advantage, Journal of Management, 17, 1, pp. 99-120, (1991); Blome C., Henke M., Single versus multiple sourcing: a supply risk management perspective, Supply Chain Risk, pp. 125-135, (2009); The last–mile delivery challenge, (2021); Ceia J.P.O., Cost-to-serve customers' optimization: macro project, (2014); Chalotra V., Inventory management and small firms growth: an analytical study in supply chain, Vision, 17, 3, pp. 213-222, (2013); Chen J., Achieving maximum supply chain efficiency, IIE Solutions, 29, 6, pp. 30-35, (1997); Cheng Y., Awan U., Ahmad S., Tan Z., How do technological innovation and fiscal decentralization affect the environment? 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Guru; Department of Operations, Institute of Management, Nirma University, Ahmedabad, India; email: sunita@nirmauni.ac.in",null,"Emerald Publishing",{"$nulls":5},251747.0,null,null,null,"English","Manage. Decis.","Article","Final",null,"Scopus","2-s2.0-85149324746"]
["Zhang C.; Gong T.","Zhang, Chen (57973889000); Gong, Taisheng (56399045500)","57973889000; 56399045500","The brand strategy and cross-border promotion of Han Chinese clothing under the digital economy",2023.0,"Electronic Commerce Research",23.0,1.0,null,257.0,277.0,20.0,7.0,"10.1007/s10660-022-09628-7","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85142366594&doi=10.1007%2fs10660-022-09628-7&partnerID=40&md5=ca19d931f1b4a8bbe6dc324f8daa5d51","College of Design and Art, Shaanxi University of Science and Technology, Xi’an, 710021, China","Zhang C., College of Design and Art, Shaanxi University of Science and Technology, Xi’an, 710021, China; Gong T., College of Design and Art, Shaanxi University of Science and Technology, Xi’an, 710021, China","The arrival of the digital economy era has impacted the traditional marketing strategies of apparel brands, but it has also created new marketing opportunities. Online shopping has become an important consumption method for the younger generation, and the global retail industry is gradually transforming towards e-commerce. As a clothing culture industry with Chinese characteristics, Han Chinese Clothing (HCC) is sought after by Han culture lovers at home and abroad. In this work, it summarizes the development status of HCC industry in recent years, and analyzes the digital marketing strategies of brands of HCC. The results are sorted out and reveal that the market scale of HCC brands expanded rapidly after 2019, and the public mainly learned about HCC culture through social media. At present, the digital marketing strategy of HCC brands has the problems of single marketing channels, unplanned activities, shallow content, and high timeliness, and low cost of cross-border transportation. For the digitalization and cross-border marketing of the HCC platform, it can build a flexible digital supply chain, strengthen social media marketing, integrate online and offline dual lines, enhance overseas marketing capabilities, and optimize strategies such as overseas warehouse layout. It is of great significance for enhancing consumer stickiness, expanding the influence of HCC brand, and reducing logistics costs. Cross-border e-commerce has become an emerging form of China’s foreign trade development, and more and more cross-border e-commerce in the apparel industry is gradually moving towards overseas markets. HCC cross-border e-commerce brands need to seize the opportunity of development, continuously optimize the cross-border operation model, and then realize the global development of Chinese brands and the inheritance and promotion of Chinese traditional culture. © 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.","Cross-border e-commerce; Digital economy; Digital marketing strategy; Han Chinese Clothing brand","Costs; Electronic commerce; International trade; Strategic planning; Brand strategy; Cross-border; Cross-border e-commerce; Digital economy; Digital marketing; Digital marketing strategy; E- commerces; Han chinese clothing brand; Marketing opportunities; Marketing strategy; Supply chains",{"$nulls":6},"Gomez-Herrera E., Martens B., Turlea G., The drivers and impediments for cross-border e-commerce in the EU, Information Economics and Policy, 28, pp. 83-96, (2014); Sun L., Lyu G., Yu Y., Et al., Cross-border e-commerce data set: Choosing the right fulfillment option, Manufacturing & Service Operations Management, 23, 5, pp. 1297-1313, (2021); Bala M., Verma D., A critical review of digital marketing, International Journal of Management IT & Engineering, 8, 10, pp. 321-339, (2018); Saura J.R., Using data sciences in digital marketing: Framework, methods, and performance metrics, Journal of Innovation & Knowledge, 6, 2, pp. 92-102, (2021); Hu S., Hanfu elements in modern fashion design and innovation, Asian Social Science, 10, (2014); Wang X., Colbert F., Legoux R., From niche interest to fashion trend: Hanfu clothing as a rising industry in China, International Journal of Arts Management, 23, 1, pp. 79-89, (2020); Chen J., Suh S., Development of hip-hop fashion design by applying Chinese hanfu elements to SCAMPER technique, Journal of Fashion Business, 25, 1, pp. 108-132, (2021); Li B., Cobb K., Cao H., Hanfu Rising: The simulation and evaluation of Chinese cultural garments: A multi-dimensional comparison study, In International Textile and Apparel Association Annual Conference Proceedings, 75, No. 1., (2018); Zhang Y., What is going on in China? 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Virtual Fitting Room: A tool to increase on-line and off-line exploratory behavior, patronage and purchase intentions, Journal of Retailing and Consumer Services, 40, pp. 279-286, (2018); Park D.H., Lee J., Han I., The effect of on-line consumer reviews on consumer purchasing intention: The moderating role of involvement, International Journal of Electronic Commerce, 11, 4, pp. 125-148, (2017); Edelman B., Brandi W., Risk, information, and incentives in online affiliate marketing, Journal of Marketing Research, 52, 1, pp. 1-12, (2015); Wang X., Xie J., Fan Z.P., B2C cross-border E-commerce logistics mode selection considering product returns, International Journal of Production Research, 59, 13, pp. 3841-3860, (2021); Qi X., Chan J.H., Hu J., Et al., Motivations for selecting cross-border e-commerce as a foreign market entry mode, Industrial Marketing Management, 89, pp. 50-60, (2020)","C. Zhang; College of Design and Art, Shaanxi University of Science and Technology, Xi’an, 710021, China; email: bs201011007@sust.edu.cn",null,"Springer",{"$nulls":5},1.3895753E7,null,null,null,"English","Electron. Commer. Res.","Article","Final",null,"Scopus","2-s2.0-85142366594"]
["Chen J.; Zhang J.; Pu C.; Wang P.; Wei M.; Hong S.","Chen, Junhua (56270946600); Zhang, Jiatong (57462553200); Pu, Chenggen (57194456356); Wang, Ping (57140993200); Wei, Min (26538271200); Hong, Seungho (55631939800)","56270946600; 57462553200; 57194456356; 57140993200; 26538271200; 55631939800","Distributed Logistics Resources Allocation with Blockchain, Smart Contract, and Edge Computing",2023.0,"Journal of Circuits, Systems and Computers",32.0,7.0,2350121.0,null,null,null,4.0,"10.1142/S0218126623501219","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85143624181&doi=10.1142%2fS0218126623501219&partnerID=40&md5=d90c1767a30883d84c7a84a78e3516fe","School of Computer Science and Technology, Chongqing University of Posts and Telecommunications, No. 2, Chongwen Road, Nan'an District, Chongqing, 400065, China; Key Laboratory of Industrial Internet of Things & Networked Control, Chongqing University of Posts and Telecommunications, No. 2, Chongwen Road, Nan'an District, Chongqing, 400065, China","Chen J., School of Computer Science and Technology, Chongqing University of Posts and Telecommunications, No. 2, Chongwen Road, Nan'an District, Chongqing, 400065, China, Key Laboratory of Industrial Internet of Things & Networked Control, Chongqing University of Posts and Telecommunications, No. 2, Chongwen Road, Nan'an District, Chongqing, 400065, China; Zhang J., Key Laboratory of Industrial Internet of Things & Networked Control, Chongqing University of Posts and Telecommunications, No. 2, Chongwen Road, Nan'an District, Chongqing, 400065, China; Pu C., School of Computer Science and Technology, Chongqing University of Posts and Telecommunications, No. 2, Chongwen Road, Nan'an District, Chongqing, 400065, China; Wang P., Key Laboratory of Industrial Internet of Things & Networked Control, Chongqing University of Posts and Telecommunications, No. 2, Chongwen Road, Nan'an District, Chongqing, 400065, China; Wei M., Key Laboratory of Industrial Internet of Things & Networked Control, Chongqing University of Posts and Telecommunications, No. 2, Chongwen Road, Nan'an District, Chongqing, 400065, China; Hong S., Key Laboratory of Industrial Internet of Things & Networked Control, Chongqing University of Posts and Telecommunications, No. 2, Chongwen Road, Nan'an District, Chongqing, 400065, China","The traditional centralized logistics resources allocation method can no longer adapt to the new business model of decentralized e-commerce, requiring transaction security for all parties involved in the logistics process. Utilizing blockchain and smart contract technologies to build logistics resources allocation network foundation and edge computing technology to assist the resource-constrained transport nodes in implementing complex computation, this paper proposes a distributed logistics resources allocation chain (DLRAChain) concept and designs a DLRAChain network that supports independent decision-making, fair bidding, and secure allocation of interests for all resources allocation participants. The corresponding system models are constructed according to the di®erent roles of DLRAChain participants. Furthermore, the logistics resources requester–provider negotiation process is formulated as a two-stage Stackelberg game. To resolve the optimization problem of the game, the iterative game algorithm (IGA) and distributed logistics resources allocation algorithm (DLRAA) are proposed. Finally, the utility of warehouse and transport nodes and reward of mobile edge computing (MEC) nodes are analyzed with experimental simulation results. The results demonstrate that the proposed models adequately address the DLRA problem, and that the proposed game and corresponding algorithms e±ciently achieve the optimal strategy, saving the response time of resources allocation participants. © 2023 World Scientific Publishing Co. Pte Ltd. All rights reserved.","blockchain; edge computing; Logistics resources allocation; smart contract; Stackelberg game","Blockchain; Computer games; Decision making; Game theory; Iterative methods; Mobile edge computing; Resource allocation; Allocation methods; Block-chain; Centralised; Edge computing; Logistic resource allocation; Logistics resources; New business models; Resources allocation; Stackelberg Games; Transport nodes; Smart contract",{"$nulls":4},"Chongqing Talent Plan Project, (cstc2021ycjhbgzxm0206); National Key Research and Development Program of China, NKRDPC, (2021YFB3301000)","This work is supported by the National Key Research and Development Program of China (2021YFB3301000) and the Chongqing Talent Plan Project (cstc2021ycjhbgzxm0206).","Abbas A. W., Marwat S. N. 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Comput, 2018, (2018); Zhou J., Cao K., Zhou X., Chen M., Wei T., Hu S., Throughput-conscious energy allocation and reliability-aware task assignment for renewable powered in-situ server systems, IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst, 41, pp. 516-529, (2022); Han Z., Niyato D., Saad W., Basar T., Hjorungnes A., Bayesian games, Game Theory in Wireless and Communication Networks: Theory, Models, and Applications, pp. 101-123, (2012); Aumann R. J., Brandenburger A., Epistemic conditions for Nash equilibrium, Readings in Formal Epistemology, Springer Graduate Texts in Philosophy, 1, pp. 863-894, (2016)","M. Wei; Key Laboratory of Industrial Internet of Things & Networked Control, Chongqing University of Posts and Telecommunications, Chongqing, No. 2, Chongwen Road, Nan'an District, 400065, China; email: weimin@cqupt.edu.cn",null,"World Scientific",{"$nulls":5},2181266.0,null,"JCSME",null,"English","J. Circuits Syst. Comput.","Article","Final",null,"Scopus","2-s2.0-85143624181"]
["Wang L.; Li X.; Zhu H.; Zhao Y.","Wang, Lin (57194064921); Li, Xia (58414417500); Zhu, Huiyu (57898812200); Zhao, Yang (56881805200)","57194064921; 58414417500; 57898812200; 56881805200","Influencing factors of livestream selling of fresh food based on a push-pull model: A two-stage approach combining structural equation modeling (SEM) and artificial neural network (ANN)",2023.0,"Expert Systems with Applications",212.0,null,118799.0,null,null,null,14.0,"10.1016/j.eswa.2022.118799","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85138452614&doi=10.1016%2fj.eswa.2022.118799&partnerID=40&md5=4bf7babd83b3963f3d17e09eb2218d1c","School of Business Administration Northeastern University, Shenyang, China; School of Management Northeastern University at Qinhuangdao, Qinhuangdao, China","Wang L., School of Business Administration Northeastern University, Shenyang, China, School of Management Northeastern University at Qinhuangdao, Qinhuangdao, China; Li X., School of Business Administration Northeastern University, Shenyang, China, School of Management Northeastern University at Qinhuangdao, Qinhuangdao, China; Zhu H., School of Business Administration Northeastern University, Shenyang, China, School of Management Northeastern University at Qinhuangdao, Qinhuangdao, China; Zhao Y., School of Business Administration Northeastern University, Shenyang, China, School of Management Northeastern University at Qinhuangdao, Qinhuangdao, China","Under the COVID-19, fresh food e-commerce has acquired new sales channels through live shopping, and the use of live broadcasts has become a hot spot in management and practice. However, there is little empirical evidence of the influence of live streaming on sales. This study combines the perspective of People-Goods-Scene and the push-pull theory, and proposes a two-stage method for forecasting sales volumes using structural equation models and artificial neural networks. It was found that the number of page views was the strongest predictor of live broadcast sales, while the numbers of interactive comments, live broadcasts with goods, and videos with goods, together with clean labels were weakly predictive. A comprehensive neural network model showed an accuracy of 83.76% in the prediction of live broadcast sales. These research results provide a theoretical basis for the prediction of fresh food shopping behavior in live-broadcast e-commerce from the perspectives of the consumers and the goods yard and provide ideas for the design of live broadcast content and optimization of user experience. © 2022 Elsevier Ltd","Artificial neural networks; Live delivery; Live shopping; Live streaming sales; Push-pull model","Consumer behavior; Electronic commerce; Forecasting; Neural networks; E- commerces; Fresh food; Live delivery; Live shopping; Live streaming; Live streaming sale; Push pull; Push-pull model; Structural equation models; Two-stage approaches; Sales",{"$nulls":4},"National Office for Philosophy and Social Sciences, NPOPSS, (21BGL133)","Funding: This research was supported by the National Social Science Fund of China (21BGL133). 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["Sıcakyüz Ç.; Erdebilli B.","Sıcakyüz, Çiğdem (58099476800); Erdebilli, Babek (57221604869)","58099476800; 57221604869","Is E-Trust a Driver of Sustainability? An Assessment of Turkish E-Commerce Sector with an Extended Intuitionistic Fuzzy ORESTE Approach",2023.0,"Sustainability (Switzerland)",15.0,13.0,10693.0,null,null,null,0.0,"10.3390/su151310693","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85164948451&doi=10.3390%2fsu151310693&partnerID=40&md5=a7c2d7c8d0345d6810b692bf8c699890","Department of Industrial Engineering, Ankara Science University, Ankara, 06570, Turkey; Department of Industrial Engineering, Ankara Yıldırım Beyazıt University, Ankara, 06760, Turkey","Sıcakyüz Ç., Department of Industrial Engineering, Ankara Science University, Ankara, 06570, Turkey; Erdebilli B., Department of Industrial Engineering, Ankara Yıldırım Beyazıt University, Ankara, 06760, Turkey","Due mainly to COVID-19 and the demanding work schedules of many individuals, online purchasing sites have become indispensable. However, the dynamic online environment and everchanging customer demands make sustainable competitiveness challenging for e-commerce platforms. Humans primarily influence the preference for online purchase platforms. This study aimed to discover Türkiye’s top popular online shopping sites by adopting an extended intuitionistic fuzzy ORESTE (Organisation, Rangement Et Synthèse De Données Relationnelles) approach. Our study targeted this by surveying female users of four online shopping platforms using IF-ORESTE. The criteria were determined according to customer preferences. These were as follows: easy accessibility to the platform, providing regular discounts and campaigns, advanced filtering settings, the contractual merchants’ reliability, quick delivery, being more affordable than competing platforms, positive feedback in user comments, having a large brand volume, having an installment option, and having partnered cargo companies. The least important factor was the large volume of brands on the online websites. Quick delivery of orders and positive feedback in reviews were equally important. Similarly, the decision-makers considered regular discounts and promotions and the comprehensive filtering settings as equally critical. However, these criteria were less significant than quick delivery and positive customer feedback. This work’s novelty lies in implementing the IF to the ORESTE in the Turkish e-commerce industry. The implications and future directions are discussed. © 2023 by the authors.","e-commerce website; intuitionistic fuzzy set; multi-criteria decision making (MCDM); online shopping; ORESTE","Turkey; accessibility; assessment method; cargo; competitiveness; COVID-19; electronic commerce; fuzzy mathematics; multicriteria analysis; shopping activity; surveying",{"$nulls":6},{"$cut":{"chars":22816,"head":"Hamilton J., The Strategic Change Matrix and Business Sustainability across COVID-19, Sustainability, 12, (2020); Hristoski I., Kostoska O., Kotevski Z., Dimovski T., Factors Affecting the Competitiveness of E-Commerce Firms: A Critical Appraisal, Proceedings of the International Balkan and Near Eastern Social Sciences Congress Series III. IBANESS Congress Series-Edirne/Turkey, pp. 1079-1090; Ngai E.W.T., Wat F.K.T., Fuzzy Decision Support System for Risk Analysis in E-Commerce Development, Decis. Support Syst, 40, pp. 235-255, (2005); Thorleuchter D., Van Den Poel D., Predicting E-Commerce Company Success by Mining the Text of Its Publicly-Accessible Website, Expert Syst. Appl, 39, pp. 13026-13034, (2012); VanHoose D., Ecommerce Economics, (2011); Zhang X., Liu P., Du Z., Research on E-Commerce Website Evaluation with Hybrid Decision-Making Index and Extension of the TOPSIS Method, Proceedings of the 2008 Third International Conference on Pervasive Computing and Applications, 1, pp. 106-109; Chevalier S., Retail E-Commerce Sales Worldwide from 2014 to 2026; Bernhardt G., Global Ecommerce Sales Growth Report for 2021–2026; Bakshi A., Ujala U., Pyngavil R.S., Impact of E-Commerce, Customers, Employees, Suppliers, Distributors and Competitors, Glob. J. Enterp. Inf. Syst, 1, pp. 54-62, (2009); Pastiu C.A., Oncioiu I., Gardan D.A., Maican S.S., Gardan I.P., Muntean A.C., The Perspective of E-Business Sustainability and Website Accessibility of Online Stores, Sustainability, 12, (2020); Liu C., Arnett K.P., Exploring the Factors Associated with Web Site Success in the Context of Electronic Commerce, Inf. Manag, 38, pp. 23-33, (2000); Zhang T., The Value of IT-Enabled Retailer Learning: Can Personalized Product Recommendations (PPRS) Improve Customer Store Loyalty in Electronic Markets?, (2005); Brynjolfsson Michael Smith E.D., Bailey J., Bakos Y., Banker R., Berry S., Hann I.-H., Hitt L., Mendelson H., Sorensen A., Bressan S., Et al., Frictionless Commerce? A Comparison of Internet and Conventional Retailers Frictionless Commerce?, Manag. Sci, 46, pp. 563-585, (2000); Gefen D., Customer Loyalty in E-Commerce, J. Assoc. Inf. Syst, 3, pp. 27-53, (2002); Evren R., Ulengin F., Yönetimde Çok Amaçlı Karar Verme, (1992); Jun F., Yu L., The Evaluation of B2C E-Commerce Web Sites Based on Fuzzy AHP, Proceedings of the Proceedings—International Symposium on Computer Science and Computational Technology, ISCSCT 2008, 2, pp. 792-795; Rouyendegh B.D., Topuz K., Dag A., Oztekin A., An AH.HP-IFT Integrated Model for Performance Evaluation of E-Commerce Web Sites, Inf. Syst. Front, 21, pp. 1345-1355, (2019); Dincer S.E., The Structural Analysis of Key Indicators of Turkish Manufacturing Industry: ORESTE and MAPPAC Applications, Eur. J. Sci. Res, 60, pp. 6-18, (2011); Melovic B., Sehovic D., Karadzic V., Dabic M., Cirovic D., Determinants of Millennials’ Behavior in Online Shopping—Implications on Consumers’ Satisfaction and e-Business Development, Technol. Soc, 65, (2021); Muller A., Laskowski N.M., Wegmann E., Steins-Loeber S., Brand M., Problematic Online Buying-Shopping: Is It Time to Considering the Concept of an Online Subtype of Compulsive Buying-Shopping Disorder or a Specific Internet-Use Disorder?, Curr. Addict. Rep, 8, pp. 494-499, (2021); Moon N.N., Talha I.M., Salehin I., An Advanced Intelligence System in Customer Online Shopping Behavior and Satisfaction Analysis, Curr. Res. Behav. Sci, 2, (2021); Kesharwani S., Sharma N., Swaying between Qualitative Information and Customers’ Expectation: An Assessment of Online Shopping Sites in India, Int. J. Inf. Technol, 12, pp. 789-795, (2020); Wan Y., Nakayama M., Sutcliffe N., The Impact of Age and Shopping Experiences on the Classification of Search, Experience, and Credence Goods in Online Shopping, Inf. Syst. e-Bus. Manag, 10, pp. 135-148, (2012); Chou S.W., Hsu C.S., Understanding Online Repurchase Intention: Social Exchange Theory and Shopping Habit, Inf. Syst. e-Bus. Manag, 14, pp. 19-45, (2016); Honkanen P., Olsen S.O., Verplanken B., Intention to Consume Seafood—The Importance o"}},"B. Erdebilli; Department of Industrial Engineering, Ankara Yıldırım Beyazıt University, Ankara, 06760, Turkey; email: babek.erdebilli2015@gmail.com",null,"Multidisciplinary Digital Publishing Institute (MDPI)",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85164948451"]
["Wang Z.; Chen S.; Ji S.; Pan Z.; Meng C.; Zhang J.; Li T.; Zheng Y.","Wang, Zhaoyuan (57189602097); Chen, Shun (57219876583); Ji, Shenggong (57203581902); Pan, Zheyi (57210644283); Meng, Chuishi (57188758851); Zhang, Junbo (36478099900); Li, Tianrui (7406372548); Zheng, Yu (56382645500)","57189602097; 57219876583; 57203581902; 57210644283; 57188758851; 36478099900; 7406372548; 56382645500","Housing rental suggestion based on e-commerce data",2023.0,"Knowledge-Based Systems",268.0,null,110474.0,null,null,null,1.0,"10.1016/j.knosys.2023.110474","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85150902207&doi=10.1016%2fj.knosys.2023.110474&partnerID=40&md5=51bd5833906bd0bc0d157a1fb8b5ee3f","School of Computing and Artificial Intelligence, Southwest Jiaotong University, Chengdu, 611756, China; JD Intelligent Cities Research, JD.com, Beijing, 100176, China; JD Intelligent Cities Business Unit, JD Digits, Beijing, 100176, China; Tencent Inc., Shenzhen, 518000, China","Wang Z., School of Computing and Artificial Intelligence, Southwest Jiaotong University, Chengdu, 611756, China, Tencent Inc., Shenzhen, 518000, China; Chen S., School of Computing and Artificial Intelligence, Southwest Jiaotong University, Chengdu, 611756, China; Ji S., School of Computing and Artificial Intelligence, Southwest Jiaotong University, Chengdu, 611756, China, Tencent Inc., Shenzhen, 518000, China; Pan Z., JD Intelligent Cities Research, JD.com, Beijing, 100176, China, JD Intelligent Cities Business Unit, JD Digits, Beijing, 100176, China; Meng C., JD Intelligent Cities Research, JD.com, Beijing, 100176, China, JD Intelligent Cities Business Unit, JD Digits, Beijing, 100176, China; Zhang J., School of Computing and Artificial Intelligence, Southwest Jiaotong University, Chengdu, 611756, China, JD Intelligent Cities Research, JD.com, Beijing, 100176, China, JD Intelligent Cities Business Unit, JD Digits, Beijing, 100176, China; Li T., School of Computing and Artificial Intelligence, Southwest Jiaotong University, Chengdu, 611756, China; Zheng Y., School of Computing and Artificial Intelligence, Southwest Jiaotong University, Chengdu, 611756, China, JD Intelligent Cities Research, JD.com, Beijing, 100176, China, JD Intelligent Cities Business Unit, JD Digits, Beijing, 100176, China","Because renting a house is a low-frequency behavior of people, the housing rental suggestion issue suffers from extremely sparse data. In this paper, we propose to investigate the issue based on e-commerce data, as the two scenarios share the same users, and, more importantly, we can characterize the users in terms of their consumption attitudes and behaviors (that can direct people to rent houses) from the massive online shopping orders, and extract labeled users (users who have both housing and working addresses) from the delivery records. Though e-commerce data can be utilized, developing such an approach is still challenging. This happens because only a tiny part of these users can be used as supervised information and it is non-trivial to fuse the e-commerce data with geographic and traffic data. To this end, we first propose to formulate the task pairwise way to use the labeled users more effectively, the target of which is to evaluate a user's satisfaction degree for a given house. Thereafter, we carefully design features of users and houses from the multi-source data and devise a novel deep network, entitled HouseCritic, to fuse the features and tackle the formulated problem. Notably, HouseCritic introduces meta-learning technology to design a fusion structure that can explicitly and effectively fuse extracted features and accordingly infer a satisfaction degree. Moreover, HouseCritic proposes to leverage unsupervised information, capable of effectively fusing data when the supervised information is insufficient. Finally, we conduct experiments on real-world data collected from Beijing, China. Experimental results demonstrate the advantages of the proposed approach over several baselines. Moreover, a system with the approach is being deployed in an e-commerce company. © 2023 Elsevier B.V.","Data fusion; Deep learning; House renting; Urban computing","Data fusion; Data mining; Deep learning; Electronic commerce; Deep learning; E- commerces; Geographic data; House renting; Low frequency behavior; Non-trivial; Online shopping; Sparse data; Traffic data; Urban computing; Houses",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (61773324); National Key Research and Development Program of China, NKRDPC, (2019FYB2101800)","This research was supported by the National Natural Science Foundation of China (No. 61773324 ) and the National Key R&D Program of China (No. 2019FYB2101800 ).","Williamson C., Shneiderman B., The dynamic HomeFinder: Evaluating dynamic queries in a real-estate information exploration system, Proceedings of the 15th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 338-346, (1992); Weng D., Zhu H., Bao J., Zheng Y., Wu Y., Homefinder revisited: finding ideal homes with reachability-centric multi-criteria decision making, Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, (2018); Colwell P.F., Dehring C.A., Turnbull G.K., Recreation demand and residential location, J. 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Res., 9, Nov, pp. 2579-2605, (2008)","T. Li; School of Computing and Artificial Intelligence, Southwest Jiaotong University, Chengdu, 611756, China; email: trli@swjtu.edu.cn",null,"Elsevier B.V.",{"$nulls":5},9507051.0,null,"KNSYE",null,"English","Knowl Based Syst","Article","Final",null,"Scopus","2-s2.0-85150902207"]
["Hamdan I.K.A.; Aziguli W.; Zhang D.; Sumarliah E.","Hamdan, Ihab K. A. (57362130300); Aziguli, Wulamu (8413050100); Zhang, Dezheng (24538189800); Sumarliah, Eli (57216867000)","57362130300; 8413050100; 24538189800; 57216867000","Machine learning in supply chain: prediction of real-time e-order arrivals using ANFIS",2023.0,"International Journal of System Assurance Engineering and Management",14.0,null,null,549.0,568.0,19.0,1.0,"10.1007/s13198-022-01851-7","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85146132538&doi=10.1007%2fs13198-022-01851-7&partnerID=40&md5=3d2b1fb8210d8b4f5c0c6c265aaefbc4","School of Computer and Communication Engineering, University of Science and Technology Beijing (USTB), Beijing, China; Faculty of Engineering, Al-Ihya Islamic University (UNISA), Kuningan, Indonesia","Hamdan I.K.A., School of Computer and Communication Engineering, University of Science and Technology Beijing (USTB), Beijing, China; Aziguli W., School of Computer and Communication Engineering, University of Science and Technology Beijing (USTB), Beijing, China; Zhang D., School of Computer and Communication Engineering, University of Science and Technology Beijing (USTB), Beijing, China; Sumarliah E., Faculty of Engineering, Al-Ihya Islamic University (UNISA), Kuningan, Indonesia","Accurate demand forecasting throughout the multi-channel supply chain (SC) enhances the managers’ decision-making capability in operational, tactical, and strategic aspects. However, the problem is that earlier publications about the real-time prediction of e-commerce order arrivals in the SC show some inadequacies. According to a systematic review from Tsolaki (ICT Express, 2022. https://doi.org/10.1016/j.icte.2022.02.001) who integrate logistics and machine learning (ML) methods in the past ten years, there are very few studies that focus on arrival time prediction like this study does, and none of them uses an adaptive neuro-fuzzy inference system (ANFIS) framework to predict e-order arrivals. Besides, (Policarpo in Comput Sci Rev 41:100414, 2021) review the existing publications that integrate e-commerce and ML techniques in the past five years; they reveal that previous studies pay heavier attentions to e-commerce initiative goals such as purchase and repurchase predictions, and none of them focuses on predicting e-order arrivals like this study does. Previous scholars investigate SC orders and prediction issues in a broader space, while this study attempts to predict hour-to-hour, actual-time order arrivals. Thus, this study presents a new data-empowered forecasting method to fill these research gaps. The motivation of this study is to build a method for predicting real-time e-orders arrivals in distribution hubs, enabling third-party logistics providers to handle the hourly-based e-order arrival rates more efficiently. This study tries to find the solution for the problem by developing a new ML forecasting method by integrating time-series data features and ANFIS, which has been proven to significantly reduce the issues’ computational complexity. This study creates a four-phase operation model to enable managers to adopt the suggested framework, and develops a systematized forecasting model to cross-confirm the framework’s outcomes. This study employs a descriptive case study and shows a satisfactory degree of precision of the suggested ML method in predicting the actual e-order arrivals in three e-retailers at three-hour cycle times. The findings reveal that the real-time forecasting is significant to boost the values of e-order arrivals in every day business operations. The novelty of this study lies on its novel contribution and purpose to build a method for predicting real-time e-orders arrivals in distribution hubs, enabling third-party logistics providers to handle the hourly-based e-order arrival rates more efficiently; and to develop a new ML forecasting method by integrating ANFIS and time-series data features. © 2023, The Author(s) under exclusive licence to The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden.","E-commerce; Machine learning; Real-time demand prediction; Supply chain management; Third-party logistics","Decision making; Electronic commerce; Fuzzy inference; Fuzzy neural networks; Fuzzy systems; Machine learning; Outsourcing; Supply chain management; Adaptive neuro-fuzzy inference; Demand prediction; E- commerces; Forecasting methods; Machine learning methods; Machine-learning; Neuro-fuzzy inference systems; Real- time; Real-time demand prediction; Third-party logistics; Forecasting",{"$nulls":6},"Adnan R.M., Mostafa R.R., Islam A.R.M.T., Kisi O., Kuriqi A., Heddam S., Estimating reference evapotranspiration using hybrid adaptive fuzzy inferencing coupled with heuristic algorithms, Comput Electron Agric, 191, (2021); Akbari M., Do T.N.A., A systematic review of machine learning in logistics and supply chain management: current trends and future directions, Benchmarking Int J, 28, 10, pp. 2977-3005, (2021); Alenezy A.H., Ismail M.T., Wadi S.A., Tahir M., Hamadneh N.N., Jaber J.J., Khan W.A., Forecasting stock market volatility using hybrid of adaptive network of fuzzy inference system and wavelet functions, J Math, (2021); AlRassas A.M., Al-qaness M.A.A., Ewees A.A., Ren S., Abd Elaziz M., Damasevicius R., Krilavicius T., Optimized ANFIS model using aquila optimizer for oil production forecasting, Processes, 9, 7, (2021); Amalnick M.S., Habibifar N., Hamid M., Bastan M., An intelligent algorithm for final product demand forecasting in pharmaceutical units, Int J Syst Assur Eng Manag, 11, 2, pp. 481-493, (2020); 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Singh R., Rathore S.S., Linear and non-linear bayesian regression methods for software fault prediction, Int J Syst Assur Eng Manag, 13, pp. 1864-1884, (2022); Sumarliah E., Risk assessment in the Islamic clothing supply chain management using best-worst method, IJIBE (Int J Islam Bus Ethics), 6, 1, pp. 1-26, (2021); Sumarliah E., Ahmad M.N., Usmanova K., Mousa K., Asad M., Reflecting coronavirus outbreak in the risk management of the apparel supply chain, IEEE Eng Manag Rev, 50, 1, pp. 31-42, (2021); Sumarliah E., Khan S.U., Khan I.U., Online hijab purchase intention: the influence of the Coronavirus outbreak, J Islam Mark, 12, 3, pp. 598-621, (2021); Sumarliah E., Li T., Wang B., Hijab fashion supply chain: A theoretical framework traversing consumers’ knowledge and purchase intention, In MATEC Web of Conferences. EDP Sciences., 308, (2020); Sumarliah E., Li T., Wang B., Indriya I., An examination of halal fashion supply chain management risks based on the fuzzy best-worst approach, Inf Resour Manag J (IRMJ), 34, 4, pp. 69-92, (2021); Sumarliah E., Li T., Wang B., Fauziyah F., Indriya I., Blockchain-empowered halal fashion traceability system in Indonesia, Int J Inf Syst Supply Chain Manag (IJISSCM), 15, 2, pp. 1-24, (2022); Sumarliah E., Li T., Wang B., Moosa A., Sackey I., The impact of customer halal supply chain knowledge on customer halal fashion purchase intention, Inf Resour Manag J (IRMJ), 34, 3, pp. 79-100, (2021); Sumarliah E., Usmanova K., Fauziyah F., Mousa K., Managing the risks in the clothing supply chain considering the coronavirus pandemic, Operations Supply Chain Manag Int J, 14, 4, pp. 576-587, (2021); Sumarliah E., Usmanova K., Mousa K., Indriya I., E-commerce in the fashion business: the roles of the COVID-19 situational factors, hedonic and utilitarian motives on consumers’ intention to purchase online, Int J Fash Des Technol Educ, 15, 2, pp. 167-177, (2022); Takagi T., Sugeno M., Fuzzy identification of systems and its applications to modeling and control, IEEE transactions on systems, man, and cybernetics, 1, pp. 116-132, (1985); Tsolaki K., Vafeiadis T., Nizamis A., Ioannidis D., Tzovaras D., Utilizing machine learning on freight transportation and logistics applications: a review, ICT Express, (2022); Tzalavra A.G., Andreadis I., Dalakleidi K.V., Constantinidis F., Zacharaki E.I., Nikita K.S., Dynamic contrast enhanced-magnetic resonance imaging radiomics combined with a hybrid adaptive neuro-fuzzy inference system-particle swarm optimization approach for breast tumour classification, Expert Syst, 39, 4, (2022); Wu Y., Tong G., The evaluation of agricultural enterprise's innovative borrowing capacity based on deep learning and BP neural network, Int J Syst Assur Eng Manag, (2021); Zardkoohi M., Molaeezadeh S.F., Long-term prediction of blood pressure time series using ANFIS system based on DKFCM clustering, Biomed Signal Process Control, 74, (2022); Zhang J., Onal S., Das R., Helminsky A., Das S., Fulfilment time performance of online retailers–an empirical analysis, Int J Retail Distrib Manag, 47, 5, pp. 493-510, (2019); Zhu L., Liu N., Game theoretic analysis of logistics service coordination in a live-streaming e-commerce system, Electron Commer Res, (2021)","E. Sumarliah; Faculty of Engineering, Al-Ihya Islamic University (UNISA), Kuningan, Indonesia; email: eliemolly@yahoo.com",null,"Springer",{"$nulls":5},9756809.0,null,null,null,"English","Intl. J. Syst. Assur. Eng. Manage.","Article","Final",null,"Scopus","2-s2.0-85146132538"]
["Makhmudov M.; Lee J.S.; Chung B.D.; Ko C.S.","Makhmudov, Muzaffar (57208503525); Lee, Jun Seop (57201494307); Chung, Byung Do (26533868200); Ko, Chang Seong (7202596739)","57208503525; 57201494307; 26533868200; 7202596739","ROBUST COLLABORATIVE DELIVERY SERVICE SYSTEM FOR UNCERTAIN DEMAND",2023.0,"ICIC Express Letters",17.0,6.0,null,701.0,708.0,7.0,0.0,"10.24507/icicel.17.06.701","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85182637796&doi=10.24507%2ficicel.17.06.701&partnerID=40&md5=916ee2e965fc3a8c675a21b95c50a562","Department of Industrial Management, New Uzbekistan University, 54 Mustaqillik Avenue, Mirzo-Ulugbek District, Tashkent, 100007, Uzbekistan; Department of Industrial and Management Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 04389, South Korea; Department of Industrial and Management Engineering, Kyungsung University, 309 Suyeong-ro, Nam-gu, Busan, 48434, South Korea","Makhmudov M., Department of Industrial Management, New Uzbekistan University, 54 Mustaqillik Avenue, Mirzo-Ulugbek District, Tashkent, 100007, Uzbekistan; Lee J.S., Department of Industrial and Management Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 04389, South Korea; Chung B.D., Department of Industrial and Management Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 04389, South Korea; Ko C.S., Department of Industrial and Management Engineering, Kyungsung University, 309 Suyeong-ro, Nam-gu, Busan, 48434, South Korea","The e-commerce market is growing rapidly with the impact of COVID-19, and the delivery service market is also growing proportionally. With the rapid increase in demand for delivery services, new delivery service companies are also appearing, and they are investing heavily to expand their market share in delivery services. Nevertheless, due to various factors such as inflation and difficulties in managing the logistics site, the rise of delivery service cost remains a problem to be overcome. Recently, studies on the introduction of a collaborative delivery service system as an alternative to solve these problems are being actively conducted. In this study, a design methodology using Robust Optimization (RO) for designing a service network under collaborative delivery considering the uncertainty of demand for delivery services is presented. We proposed a mathematical model for RO for collaborative delivery service. An example problem is carried out to explain RO’s approach and verify its feasibility using simulation analysis. © 2023 ISSN 1881-803X.","Collaboration; Delivery service; E-commerce; Robust optimization; Simulation analysis",{"$nulls":5},"National Research Foundation of Korea, NRF; Ministry of Education, Science and Technology, MEST, (NRF-2021R1F1A1056189)","2. Literature Review. Comparing the post-crisis period to the pandemic period, e-commerce development had a significant acceleration [2]. Due to the COVID-19, consumers are forced to use the Internet and develop the daily habit of buying goods and services online [3]. Global logistical networks have been significantly impacted by the pandemic issue [4]. The “bring-service-near-your-home” idea was explained by Choi [5], who also covered the financial support measures needed during the pandemic.","Eurominitor International, (2022); Kim R. Y., The impact of COVID-19 on consumers: Preparing for digital sales, IEEE Engineering Management Review, 48, 3, pp. 212-218, (2020); Abiad A., Arao R. M., Dagli S., Et al., The Economic Impact of the COVID-19 Outbreaks on Developing Asia, (2020); Yang S., Ning L., Jiang T., He Y., Dynamic impacts of COVID-19 pandemic on the regional express logistics: Evidence from China, Transport Policy, 111, pp. 111-124, (2021); Choi T. M., Innovative “bring-service-near-your-home” operations under corona-virus (COVID-19/SARS-CoV-2) outbreak: Can logistics become the messiah?, Transportation Research Part E:Logistics and Transportation Review, 140, (2020); Dones R. L. E., Young M. N., Demand on the of courier services during COVID-19 pandemic in the Philippines, 2020 7th International Conference on Frontiers of Industrial Engineering (ICFIE), pp. 131-134, (2020); Ferdinand F. N., Chung K. H., Ko H. J., Ko C. S., Genetic algorithm-based approach to multi-objective decision making model for strategic alliances in express courier services, ICIC Express Letters, 6, 4, pp. 929-934, (2012); Ferdinand F. N., Ko C. S., Coevolutionary algorithm based approach to the collaborative network design in express delivery services using coalitional game theory, ICIC Express Letters, 10, 11, pp. 2711-2717, (2016); Makhmudov M., Park Y. T., Sohn Y. H., Ko C. S., Network design for time-phased collaboration in delivery service, ICIC Express Letters, 15, 8, pp. 861-868, (2021); Makhmudov M., Lee G. M., Ko C. S., Fair profit distribution in delivery service collaboration considering service quality, International Journal of Industrial Engineering: Theory, Applications, and Practice, 28, 2, (2021); Jamalnia A., Yang J. B., Feili A., Xu D. L., Jamali G., Aggregate production planning under uncertainty: A comprehensive literature survey and future research directions, The International Journal of Advanced Manufacturing Technology, 102, 4, pp. 159-181, (2019); Baron O., Berman O., Fazel-Zarandi M. M., Roshanaei V., Almost robust discrete optimization, European Journal of Operational Research, 276, 2, pp. 451-465, (2019); Jalilvand-Nejad A., Shafaei R., Shahriari H., Robust optimization under correlated polyhedral uncertainty set, Computers & Industrial Engineering, 92, pp. 82-94, (2016); Soyster A. L., Convex programming with set-inclusive constraints and applications to inexact linear programming, Operations Research, 21, 5, pp. 1154-1157, (1973); Ben-Tal A., Nemirovski A., Robust solutions of linear programming problems contaminated with uncertain data, Mathematical Programming, 88, 3, pp. 411-424, (2000); Bertsimas D., Sim M., The price of robustness, Operations Research, 52, 1, pp. 35-53, (2004); Wei C., Li Y., Cai X., Robust optimal policies of production and inventory with uncertain returns and demand, International Journal of Production Economics, 134, 2, pp. 357-367, (2011); Jose Alem D., Morabito R., Production planning in furniture settings via robust optimization, Computers & Operations Research, 39, 2, pp. 139-150, (2012); Chung K. H., Rho J. J., Ko C. S., A strategic alliance model with regional monopoly of service centres in express courier services, International Journal of Services and Operations Management, 5, 6, pp. 774-786, (2009)","C.S. Ko; Department of Industrial and Management Engineering, Kyungsung University, Busan, 309 Suyeong-ro, Nam-gu, 48434, South Korea; email: csko@ks.ac.kr",null,"ICIC International",{"$nulls":5},"1881803X",null,null,null,"English","ICIC Express Lett.","Article","Final",null,"Scopus","2-s2.0-85182637796"]
["Paltrinieri S.; Bressi B.; Mazzini E.; Fugazzaro S.; Rondini E.; Giorgi Rossi P.; Costi S.","Paltrinieri, Sara (57202265674); Bressi, Barbara (57210474484); Mazzini, Elisa (57190090235); Fugazzaro, Stefania (56414950500); Rondini, Ermanno (15746039700); Giorgi Rossi, Paolo (57197200428); Costi, Stefania (6506545174)","57202265674; 57210474484; 57190090235; 56414950500; 15746039700; 57197200428; 6506545174","Activities Carried Out during the First COVID-19 Lockdown by Italian Citizens",2023.0,"International Journal of Environmental Research and Public Health",20.0,5.0,3906.0,null,null,null,1.0,"10.3390/ijerph20053906","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85149963240&doi=10.3390%2fijerph20053906&partnerID=40&md5=f5d0af923801fa1e06c4ad92f329a209","Physical Medicine and Rehabilitation Unit, Azienda Unità Sanitaria Locale-IRCCS di Reggio Emilia, Reggio Emilia, 42123, Italy; Public Health Sciences PhD Program, Department of Clinical Sciences and Community Health, University of Milan, Milan, 20122, Italy; PhD Program in Clinical and Experimental Medicine, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Reggio Emilia, 41124, Italy; Scientific Directorate Hospital Network, Azienda Unità Sanitaria Locale-IRCCS di Reggio Emilia, Reggio Emilia, 42123, Italy; Lega Italiana Contro i Tumori-LILT Reggio Emilia, Reggio Emilia, 42123, Italy; Regional Center for Education in Health Promotion-Luoghi di Prevenzione, Reggio Emilia, 42122, Italy; Epidemiology Unit, Azienda Unità Sanitaria Locale-IRCCS di Reggio Emilia, Reggio Emilia, 42122, Italy; Department of Surgery, Medicine, Dentistry and Morphological Sciences, Università di Modena e Reggio Emilia, Modena, 41124, Italy","Paltrinieri S., Physical Medicine and Rehabilitation Unit, Azienda Unità Sanitaria Locale-IRCCS di Reggio Emilia, Reggio Emilia, 42123, Italy, Public Health Sciences PhD Program, Department of Clinical Sciences and Community Health, University of Milan, Milan, 20122, Italy; Bressi B., Physical Medicine and Rehabilitation Unit, Azienda Unità Sanitaria Locale-IRCCS di Reggio Emilia, Reggio Emilia, 42123, Italy, PhD Program in Clinical and Experimental Medicine, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Reggio Emilia, 41124, Italy; Mazzini E., Scientific Directorate Hospital Network, Azienda Unità Sanitaria Locale-IRCCS di Reggio Emilia, Reggio Emilia, 42123, Italy; Fugazzaro S., Physical Medicine and Rehabilitation Unit, Azienda Unità Sanitaria Locale-IRCCS di Reggio Emilia, Reggio Emilia, 42123, Italy; Rondini E., Lega Italiana Contro i Tumori-LILT Reggio Emilia, Reggio Emilia, 42123, Italy, Regional Center for Education in Health Promotion-Luoghi di Prevenzione, Reggio Emilia, 42122, Italy; Giorgi Rossi P., Epidemiology Unit, Azienda Unità Sanitaria Locale-IRCCS di Reggio Emilia, Reggio Emilia, 42122, Italy; Costi S., Physical Medicine and Rehabilitation Unit, Azienda Unità Sanitaria Locale-IRCCS di Reggio Emilia, Reggio Emilia, 42123, Italy, Department of Surgery, Medicine, Dentistry and Morphological Sciences, Università di Modena e Reggio Emilia, Modena, 41124, Italy","The SARS-CoV-2 pandemic has altered how citizens engage in activities. This study describes the new activities citizens engaged in during the first lockdown, factors that helped them cope with the confinement, the supports they used the most, and which supports they would have liked to receive. This cross-sectional study consists of an online survey made of 49 questions that was completed by the citizens of the province of Reggio Emilia (Italy) from 4 May until 15 June 2020. The outcomes of this study were explored by focusing on four of the survey questions. Of the 1826 citizens who responded, 84.2% had started new leisure activities. Males, participants who lived in the plain or foothills, and those who experienced nervousness engaged less in new activities, while those whose employment status changed, whose lifestyle worsened, or whose use of alcohol increased engaged in more activities. The support of family and friends, leisure activities, continuing to work, and an optimistic attitude were perceived to be of help. Grocery delivery and hotlines providing any type of information and mental health support were used frequently; a lack of health and social care services and of support in reconciling work with childcare was perceived. Findings may help institutions and policy makers to better support citizens in any future circumstances requiring prolonged confinement. © 2023 by the authors.","confinement; COVID-19; human activities; leisure activities; occupations; pandemic; quarantine; resilience; SARS-CoV-2; work","Communicable Disease Control; COVID-19; Cross-Sectional Studies; Humans; Male; SARS-CoV-2; Surveys and Questionnaires; Emilia-Romagna; Italy; Reggio Emilia; alcohol consumption; child care; COVID-19; employment; lifestyle; mental health; recreational activity; adult; alcohol consumption; Article; child care; cooking; coping behavior; coronavirus disease 2019; cross-sectional study; daily life activity; employment status; family life; family support; female; friend; gardening; health care availability; health care policy; hotline; human; information dissemination; Italian (citizen); Italy; job performance; leisure; lifestyle modification; lockdown; male; mental health care; nervousness; normal human; online shopping; online system; optimism; pandemic; questionnaire; reading; rest; sex difference; social care; social media; social support; television viewing; voluntary worker; communicable disease control",{"$nulls":6},"Occupational therapy practice framework. 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Health Sci, 4, pp. 1-22, (2020); Yerkes M.A., Andre S.C.H., Besamusca J.W., Kruyen P.M., Remery C.L.H.S., van der Zwan R., Beckers D.G.J., Geurts S.A.E., ‘Intelligent’ lockdown, intelligent effects? results from a survey on gender (in)equality in paid work, the division of childcare and household work, and quality of life among parents in the Netherlands during the COVID-19 lockdown, PLoS ONE, 15, (2020); Tommasi M., Toro F., Arno S., Carrieri A., Conte M.M., Devastato M.D., Picconi L., Sergi M.R., Saggino A., Physical and psychological impact of the phase one lockdown for COVID-19 on Italians, Front. Psychol, 11, (2020); Impact of the COVID-19 Crisis on Short-and Medium-Term Consumer Behavior. Will the COVID-19 Crisis Have a Lasting Effect on Consumption?; Wang X.C., Kim W., Holguin-Veras J., Schmid J., Adoption of delivery services in light of the COVID pandemic: Who and how long?, Transp. Res. Part A Policy Pract, 154, pp. 270-286, (2021); De Gani S.M., Berger F., Guggiari E., Jaks R., Relation of corona-specific health literacy to use of and trust in information sources during the COVID-19 pandemic, BMC Public Health, 22, (2022); Moynihan R., Sanders S., Michaleff Z.A., Scott A.M., Clark J., To E.J., Jones M., Kitchener E., Fox M., Johansson M., Et al., Impact of COVID-19 pandemic on utilisation of healthcare services: A systematic review, BMJ Open, 11, (2021); Pecout C., Pain E., Chekroun M., Champeix C., Kulak C., Prieto R., van Vugt J., Gilchrist K., Laine-Pellet A.-F., Impact of the COVID-19 pandemic on patients affected by non-communicable diseases in Europe and in the USA, Int. J. Environ. Res. Public Health, 18, (2021); Antonazzo I.C., Fornari C., Maumus-Robert S., Cei E., Paoletti O., Conti S., Cortesi P.A., Mantovani L.G., Gini R., Mazzaglia G., Impact of COVID-19 lockdown, during the two waves, on drug use and emergency department access in people with epilepsy: An interrupted time-series analysis, Int. J. Environ. Res. Public Health, 18, (2021); Pena-Ramos J.A., Recuero-Lopez F., Sanchez-Bayon A., Sastre F.J., Evaluation of Spanish health system during the COVID-19 pandemic: Accountability and wellbeing results, Int. J. Environ. Res. Public Health, 18, (2021)","S. Costi; Physical Medicine and Rehabilitation Unit, Azienda Unità Sanitaria Locale-IRCCS di Reggio Emilia, Reggio Emilia, 42123, Italy; email: stefania.costi@unimore.it",null,"MDPI",{"$nulls":5},1.6617827E7,null,null,3.6900917E7,"English","Int. J. Environ. Res. Public Health","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85149963240"]
["Kłos M.J.; Sierpiński G.","Kłos, Marcin Jacek (57170060900); Sierpiński, Grzegorz (36663088400)","57170060900; 36663088400","Strategy for the Siting of Electric Vehicle Charging Stations for Parcel Delivery Service Providers",2023.0,"Energies",16.0,6.0,2553.0,null,null,null,3.0,"10.3390/en16062553","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85151397821&doi=10.3390%2fen16062553&partnerID=40&md5=f6d3572e895b9c0f3ab7d47cdcbfe17a","Department of Transport Systems, Traffic Engineering and Logistics, Faculty of Transport and Aviation Engineering, Silesian University of Technology, Gliwice, 44-100, Poland","Kłos M.J., Department of Transport Systems, Traffic Engineering and Logistics, Faculty of Transport and Aviation Engineering, Silesian University of Technology, Gliwice, 44-100, Poland; Sierpiński G., Department of Transport Systems, Traffic Engineering and Logistics, Faculty of Transport and Aviation Engineering, Silesian University of Technology, Gliwice, 44-100, Poland","The development of urban logistics is closely related to the inhabitants of specific areas. People are changing their shopping habits, hence the growing share of online shopping. The consequence of the foregoing is increased demand for parcel delivery to customers’ addresses as well as in-store and automated pick-up points. This has increased the number of couriers that provide parcel delivery services. To achieve sustainable development, there is a real need to convert conventional combustion engine fleets using greener solutions such as electric vehicles. However, introducing such vehicles on a large scale involves constraints such as the vehicle running range on a single charge, the price of a new fleet and of its maintenance, and the location of charging stations. This article focuses on the strategies for siting of charging stations intended to be used by the providers of parcel delivery services. Different strategies as well as a method for identifying optimal goal-specific locations have been proposed. The results show the limitations and challenges facing both the operators of parcel delivery services and local authorities that should also be involved in the development of charging points. Additionally, based on the method presented in the paper, operators can choose between different strategies depending on the particular requirements and local conditions. © 2023 by the authors.","charging stations; electric vehicle; electromobility; energy grid; geographical information systems; location; parcel delivery services; QGIS; range; spatial analysis","Charging (batteries); Electric vehicles; Fleet operations; Geographic information systems; Charging station; Delivery service; Electromobility; Energy grids; Geographical information; Geographical information system; Parcel delivery; Parcel delivery service; QGIS; Range; Spatial analysis; Location",{"$nulls":6},"Iwan S., Nurnberg M., Bejger A., Kijewska K., Malecki K., Unloading Bays as Charging Stations for EFV-Based Urban Freight Delivery System—Example of Szczecin, Energies, 14, (2021); Panagiotopoulos G., Kaliampakos D., Location Quotient-Based Travel Costs for Determining Accessibility Changes, J. Transp. 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Transp, 105, pp. 91-100, (2019)","G. Sierpiński; Department of Transport Systems, Traffic Engineering and Logistics, Faculty of Transport and Aviation Engineering, Silesian University of Technology, Gliwice, 44-100, Poland; email: grzegorz.sierpinski@polsl.pl",null,"MDPI",{"$nulls":5},1.9961073E7,null,null,null,"English","Energies","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85151397821"]
["Bafouni-Kotta A.; Villanueva J.; Kalakou S.; Dias J.G.","Bafouni-Kotta, Anastasia (57316543400); Villanueva, Jonathan (58189583800); Kalakou, Sofia (56008885200); Dias, José G. (9273716900)","57316543400; 58189583800; 56008885200; 9273716900","Upcoming drone delivery services: A perceptions-based clustering of citizens in Lisbon",2023.0,"Technology in Society",73.0,null,102250.0,null,null,null,1.0,"10.1016/j.techsoc.2023.102250","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85152968684&doi=10.1016%2fj.techsoc.2023.102250&partnerID=40&md5=35990981205de319ead49e98706ce726","Department of Business Administration, University of Patras, Achaia, Rion, GR26504, Greece; AirPlus International, Av. Emilio Cavenecia, Of. 701 y 702, Torre Cavenecia, Miraflores, Lima, Peru; Instituto Universitário de Lisboa (ISCTE-IUL), Business Research Unit (BRU-IUL), Avenida das Forças Armadas, Lisboa, 1649 026, Portugal","Bafouni-Kotta A., Department of Business Administration, University of Patras, Achaia, Rion, GR26504, Greece; Villanueva J., AirPlus International, Av. Emilio Cavenecia, Of. 701 y 702, Torre Cavenecia, Miraflores, Lima, Peru; Kalakou S., Instituto Universitário de Lisboa (ISCTE-IUL), Business Research Unit (BRU-IUL), Avenida das Forças Armadas, Lisboa, 1649 026, Portugal; Dias J.G., Instituto Universitário de Lisboa (ISCTE-IUL), Business Research Unit (BRU-IUL), Avenida das Forças Armadas, Lisboa, 1649 026, Portugal","Drones are an emerging technology that promises numerous benefits for delivery services. As e-commerce evolves and citizens become more familiar with parcel delivery services to their homes, drone services could become an alternative for last-mile logistics service providers. However, the potential diffusion of drone services will also be influenced by the public opinion. This study addresses the issue of citizens' perceptions of drone delivery services and uses the Metropolitan Area of Lisbon as a case study. Data was collected though a survey and analysed using a clustering approach. Six citizen clusters were identified: the drone-service supporters, the concerned about the package, the concerned with legal aspects, the drone-service neutrals, the likely supporters, and the non-supporters. The clusters vary according to socio-economic characteristics and members’ current satisfaction with the home delivery services. Logistics stakeholders can use the results of this study to successfully introduce drones into their logistics systems and benefit from the added value to the public. © 2023 Elsevier Ltd","Citizens perceptions; Clustering; Consumers preferences; Drone deliveries; Drone service development; Logistics services; Technology management","Lisboa [Portugal]; Lisbon; Portugal; Social aspects; Citizen perception; Clusterings; Consumers' preferences; Delivery service; Drone delivery; Drone service development; Logistics services; Perception-based; Services development; Technology managements; consumption behavior; logistics; metropolitan area; perception; preference behavior; service provision; service sector; stakeholder; technological development; transportation technology; Drones",{"$nulls":4},"Fundação para a Ciência e a Tecnologia, FCT, (UIDB/00315/2020)","We sincerely appreciate the valuable comments and suggestions from the Editor and the reviewers that helped us improve the quality of the article. This work was supported by Fundação para a Ciência e a Tecnologia , grant UIDB/00315/2020 . ","The parcel market in Europe - revenue by segment 2010–2020, (2019); Lee H.L., Chen Y., Gillai B., Rammohan S., Technological Disruption and Innovation in Last-Mile Delivery, (2016); Meng F., Liu G., Yang Z., Casazza M., Cui S., Ulgiati S., Energy efficiency of urban transportation system in Xiamen, China. An integrated approach, Appl. Energy, 186, pp. 234-248, (2017); Drone Package Delivery Industry Top Companies, (2022); Soffronoff J., Piscioneri P., Weaver A., Public Perception of Drone Delivery in the United States RARC Report, (2016); Kim S.H., Choice model based analysis of consumer preference for drone delivery service, J. Air Transport. Manag., 84, (2020); Klauser F., Pedrozo S., Big Data from the Sky: Popular Perceptions of Private Drones in Switzerland, (2017); Study on the Societal Acceptance of Urban Air Mobility in Europe, (2021); Sabino H., Almeida R.V.S., de Moraes L.B., da Silva W.P., Guerra R., Malcher C., Passos D., Passos F.G.O., A systematic literature review on the main factors for public acceptance of drones, Technol. Soc., 71, (2022); Yaprak U., Kilic F., Okumus A., Is the Covid-19 pandemic strong enough to change the online order delivery methods? Changes in the relationship between attitude and behavior towards order delivery by drone, Technol. Forecast. Soc. Change, 169, (2021); Watkins S., Burry J., Mohamed A., Marino M., Prudden S., Fisher A., Kloet N., Jakobi T., Clothier R., Ten questions concerning the use of drones in urban environments, Build. Environ., 167, (2020); Reddy L.B., DeLaurentis D., Opinion survey to reduce uncertainty in public and stakeholder perception of unmanned aircraft, Transport. Res. Rec., 2600, pp. 80-93, (2016); Osakwe C.N., Hudik M., Riha D., Stros M., Ramayah T., Critical factors characterizing consumers' intentions to use drones for last-mile delivery: does delivery risk matter?, J. Retailing Consum. Serv., 65, (2022); Hwang J., Lee J.S., Kim H., Perceived innovativeness of drone food delivery services and its impacts on attitude and behavioral intentions: the moderating role of gender and age, Int. J. Hospit. 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Change, 163, (2020); Zhu X., Segmenting the public's risk beliefs about drone delivery: a belief system approach, Telematics Inf., 40, pp. 27-40, (2019); Lin Tan L.K., Lim B.C., Park G., Low K.H., Seng Yeo V.C., Public acceptance of drone applications in a highly urbanized environment, Technol. Soc., 64, (2021); Aydin B., Public acceptance of drones: knowledge, attitudes, and practice, Technol. Soc., 59, (2019); Kotler P., Keller K.L., Marketing Management, (2000); Lewis M., The effect of shipping fees on customer acquisition, customer retention, and purchase quantities, J. Retailing, 82, pp. 13-23, (2006); Goodchild A., Toy J., Delivery by drone: an evaluation of unmanned aerial vehicle technology in reducing CO2 emissions in the delivery service industry, Transp Res D Transp Environ, 61, pp. 58-67, (2018); Chiang W.C., Li Y., Shang J., Urban T.L., Impact of drone delivery on sustainability and cost: realizing the UAV potential through vehicle routing optimization, Appl. Energy, 242, pp. 1164-1175, (2019); Park J., Kim S., Suh K., A comparative analysis of the environmental benefits of drone-based delivery services in urban and rural areas, Sustainability, (2018); Kellermann R., Biehle T., Fischer L., Drones for parcel and passenger transportation: a literature review, Transp. Res. Interdiscip. Perspect., 4, (2020); Zenezini G., Mangano G., De Marco A., Experts' opinions about lasting innovative technologies in City Logistics, Research in Transportation Business & Management, 45, (2022); Peppel M., Ringbeck J., Spinler S., How will last-mile delivery be shaped in 2040? A Delphi-based scenario study, Technol. Forecast. Soc. Change, 177, (2022); E-Commerce Statistics for Individuals, (2021); Use of Internet and Online Activities, (2019); Population of Portugal by Gender 1864-2020, (2021); Pettigrew S., Dana L.M., Norman R., Clusters of potential autonomous vehicles users according to propensity to use individual versus shared vehicles, Transport Pol., 76, pp. 13-20, (2019); Lee Y., Chen G.Y.H., Circella G., Mokhtarian P.L., Substitution or Complementarity? A Latent-Class Cluster Analysis of Ridehailing Impacts on the Use of Other Travel Modes, Three Southern US Cities, vol. 104, Transportation Research Part D - Transport and Environment 104, (2022); van't Veer R., Annema J.A., Araghi Y., Correia G.H.A., van Wee B., Mobility-as-a-Service (MaaS): a latent class cluster analysis to identify Dutch vehicle owners’ use intention, Transport. Res. Part A - Policy and Practice, 169, (2023); Tang W., Mokhtarian P.L., Accounting for taste heterogeneity in purchase channel intention modeling: an example from northern California for book purchases, Journal of Choice Modelling, 2, 2, pp. 148-172, (2009); Nagpal A., Jatain A., Gaur D., Review based on data clustering algorithms, IEEE Conference on Information and Communication Technologies, pp. 298-303, (2013); Molin E., Mokhtarian P., Kroesen M., Multimodal travel groups and attitudes: a latent class cluster analysis of Dutch travelers, Transport. Res. Part A - Policy and Practice, 83, pp. 14-29, (2016); Alonso-Gonzalez M.J., Hoogendoorn-Lanser S., van Oort N., Cats O., Hoogendoorn S., Drivers and barriers in adopting Mobility as a Service (MaaS) - a latent class cluster analysis of attitudes, Transport. Res. Part A - Policy and Practice, 132, pp. 378-401, (2020); Dias J.G., Vermunt J.K., Latent class modeling of website users' search patterns: implications for online market segmentation, J. Retailing Consum. Serv., 14, 6, pp. 359-368, (2007); Melnykov V., Maitra R., Finite mixture models and model-based clustering, Stat. Surv., 4, pp. 80-116, (2010); Dias J.G., Understanding latent class model selection criteria by concomitant variable latent class models, advances in latent class analysis: a festschrift, CILVR Series on Latent Variable Methodology. Charlotte, (2019); Schwarz G., Estimating the dimension of a model, Ann. Stat., 6, pp. 461-464, (1978); Rozler F., Manzey D., Principal components and varimax rotated components in event-related potential research: some remarks on their interpretation, Biol. Psychol., 13, pp. 3-26, (1981); Olawale F., Garwe D., Obstacles to the growth of new SMEs in South Africa: a principal component analysis approach, Afr. J. Bus. Manag., 4, pp. 729-738, (2010); Fraley C., Raftery A., Scruccs L., Mclust: Gaussian Mixture Modelling for Model-Based Clustering, Classification, and Density Estimation, (2016); Statista U.S., Social Reach by Age, (2019); Blasi S., Goobo E., Sedita S.R., Smart cities and citizen engagement: evidence from Twitter data analysis on Italian municipalities, Journal of Urban Management, 11, 2, pp. 153-165, (2022); Smith A., Dickinson J.E., Marsden G., Cherrett T., Oakey A., Grote M., Public acceptance of the use of drones for logistics: the state of play and moving towards more informed debate, Technol. Soc., 68, (2022); Urban Air Mobility and Sustainable Urban Mobility Planning - Practitioner Briefing, (2021); Jane Fox S., Drones, Foreseeing a “risky” business?Policing the challenge that flies above, Technol. Soc., 71, (2022)","S. Kalakou; Instituto Universitário de Lisboa (ISCTE-IUL), Business Research Unit (BRU-IUL), Lisboa, Avenida das Forças Armadas, 1649 026, Portugal; email: sofia.kalakou@iscte-iul.pt",null,"Elsevier Ltd",{"$nulls":5},"0160791X",null,null,null,"English","Technol. Soc.","Article","Final",null,"Scopus","2-s2.0-85152968684"]
["Kumar V.; Ya K.Z.; Lai K.-K.","Kumar, Vimal (57202530494); Ya, Kyaw Zay (57219894144); Lai, Kuei-Kuei (24476132800)","57202530494; 57219894144; 24476132800","Mapping the key challenges and managing the opportunities in supply chain distribution during COVID-19: a case of Myanmar pharmaceutical company",2023.0,"Journal of Global Operations and Strategic Sourcing",16.0,2.0,null,187.0,223.0,36.0,10.0,"10.1108/JGOSS-01-2022-0002","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85131039830&doi=10.1108%2fJGOSS-01-2022-0002&partnerID=40&md5=ad17cf2cfe658c9bb4f6a55f1522fff5","Department of Information Management, Chaoyang University of Technology, Taichung, Taiwan; Department of Business Administration, Chaoyang University of Technology, Taichung, Taiwan","Kumar V., Department of Information Management, Chaoyang University of Technology, Taichung, Taiwan; Ya K.Z., Department of Business Administration, Chaoyang University of Technology, Taichung, Taiwan; Lai K.-K., Department of Business Administration, Chaoyang University of Technology, Taichung, Taiwan","Purpose: This study aims to present a study on the supply chain process of a Myanmar-based pharmaceutical company (named ABC Pvt. Ltd. in this study) that produces pharmaceutical products across Myanmar and aims of bringing quality medical products and best care for Myanmar people’s health. The study aims to identify the key supply chain challenges and manage the opportunities executed by this pharmaceutical company to improve the supply chain process during the COVID-19 outbreak. Design/methodology/approach: This work used a case study and conducted semistructured interviews with the manager, senior managers and senior staff of the ABC Company to improve the supply chain process and develop a comprehensive structural relationship to rank them to streamline the uncertainties, real-time information and agility in a digital supply chain using grey relational analysis (GRA) method. Findings: From the data analysis and results, “Impact of political factor,” “Delay in import process” and “Weak internet connection,” and “Weak knowledge of the use of digital platform,” “Poor information sharing in online by employees” and “Information flow from top management to operational level” have been identified as top and bottom three key challenges, respectively. “Inventory management,” “Selection of transport method” and “Operational cost”, and “Marketing and brand Innovation,” “Online delivery of products” and “E-commerce enablement (Launching applications, tracking system)” are identified as the top and bottom three managing the opportunities, respectively. Research limitations/implications: The findings of the study help to supply chain decision-makers of the company in their establishment of key challenges and opportunities during the COVID-19 era. As a leading company, it always tries to add value to its product through a supply chain system, effective management teams and working with skillful decision-making toward satisfying the demand on time and monitoring the supplier performance. Originality/value: The novelty of this study is to identify the key supply chain challenges and opportunities by the GRA method to rank them, considering the case of Myanmar pharmaceutical manufacturing company as a case-based approach to measuring its performance during the COVID-19 outbreak era. This work will assist managers and practitioners help to the company to provide optimal services to its consumers on time in this critical situation. © 2022, Emerald Publishing Limited.","Challenges; COVID-19; GRA method; Opportunities; Pharmaceutical company; Supply chain distribution",{"$nulls":7},{"$cut":{"chars":24336,"head":"Abdallah A.B., Nabass I.H., Supply chain antecedents of agile manufacturing in a developing country context an empirical investigation, Journal of Manufacturing Technology Management, 29, 6, pp. 1042-1064, (2018); Abdolazimi O., Esfandarani M.S., Salehi M., Shishebori D., Shakhsi-Niaei M., Development of sustainable and resilient healthcare and non-cold pharmaceutical distribution supply chain for COVID-19 pandemic: a case study, The International Journal of Logistics Management, (2021); Adikaram A.S., Naotunna N.P.G.S.I., Priyankara H.P.R., Battling COVID-19 with human resource management bundling, employee relations, Employee Relations: The International Journal, 43, 6, pp. 1269-1289, (2021); Agyabeng-Mensah Y., Ahenkorah E., Afum E., Dacosta E., Green warehousing, logistics optimization, social values and ethics and economic performance: the role of supply chain sustainability, The International Journal of Logistics Management, 31, 3, pp. 549-574, (2020); Ahmad F., John B., A fuzzy quantitative model for assessing the performance of pharmaceutical supply chain under uncertainty, Kybernetes, (2021); Akintokunbo O.O., Adim C.V., Akintokunbo, oluwarotimi Odunayo1 and adim, chidiebere victor, Asian Journal of Economics, Business and Accounting, 19, 2, pp. 40-47, (2020); Alam S., Adnan Z.H., Baten M.A., Bag S., Assessing vulnerability of informal floating workers in Bangladesh before and during COVID-19 pandemic: a multi-method analysis, Benchmarking: An International Journal, (2021); Alhawari O., Bhutta K., Muzzafar A., You are entitled to access the full text of this document supply chain emerging aspects and future directions in the age of COVID-19: a systematic review, Uncertain Supply Chain Management, 9, 2, pp. 429-446, (2021); Al-Mansour J.F., Al-Ajmi S.A., Coronavirus ‘COVID-19’ – supply chain disruption and implications for strategy, economy, and management, The Journal of Asian Finance, Economics and Business, 7, 9, pp. 659-672, (2020); Almurisi S.H., Al Khalidi D., Al-Japairai K.A., Mahmood S., Chilakamarry C.R., Kadiyala C.B.N., Mohananaidu K., Impact of COVID 19 pandemic crisis on the health system and pharmaceutical industry, Letters in Applied NanoBioScience, 10, 2, pp. 2298-2308, (2020); Andersen P.H., Drejer I., Ostergaard C.R., Soberg P.V., Waehrens B.V., Supplier value creation configurations in high-cost countries, Journal of Global Operations and Strategic Sourcing, 12, 3, pp. 429-448, (2019); Anlesinya A., Susomrith P., Sustainable human resource management: a systematic review of a developing field, Journal of Global Responsibility, 11, 3, pp. 295-324, (2020); Ayati N., Saiyarsarai P., Nikfar S., Short and long term impacts of COVID-19 on the pharmaceutical sector, DARU Journal of Pharmaceutical Sciences, 28, 2, pp. 799-805, (2020); Bag S., Dhamija P., Luthra S., Huisingh D., How big data analytics can help manufacturing companies strengthen supply chain resilience in the context of the COVID-19 pandemic, The International Journal of Logistics Management, (2021); Bag S., Gupta S., Choi T.M., Kumar A., Roles of innovation leadership on using big data analytics to establish resilient healthcare supply chains to combat the COVID-19 pandemic: a multimethodological study, IEEE Transactions on Engineering Management, pp. 1-14, (2021); Bag S., Kilbourn P., Pisa N., Giannakis M., Key success factors for supply chain sustainability in COVID-19 pandemic: an ISM approach, IFIP International Conference on Advances in Production Management Systems, pp. 724-733, (2021); Bag S., Luthra S., Venkatesh V.G., Yadav G., Towards understanding key enablers to green humanitarian supply chain management practices, Management of Environmental Quality: An International Journal, 31, 5, pp. 1111-1145, (2020); Bag S., Yadav G., Dhamija P., Kataria K.K., Key resources for industry 4.0 adoption and its effect on sustainable production and circular economy: an empirical study, Journal of Cleaner Production, 281, pp. 1-12, (2021); Bag S., Yadav G., Wood L.C., Dhamija P., Joshi S., Industry 4.0 and the circular economy: resource meli"}},"K.Z. Ya; Department of Business Administration, Chaoyang University of Technology, Taichung, Taiwan; email: kzayya111@gmail.com",null,"Emerald Publishing",{"$nulls":5},2.3985364E7,null,null,null,"English","J. Global Operations Strategic Sourc.","Article","Final",null,"Scopus","2-s2.0-85131039830"]
["Seghezzi A.; Mangiaracina R.","Seghezzi, Arianna (57204964677); Mangiaracina, Riccardo (35325033800)","57204964677; 35325033800","Smart home devices and B2C e-commerce: a way to reduce failed deliveries",2023.0,"Industrial Management and Data Systems",123.0,5.0,null,1624.0,1645.0,21.0,0.0,"10.1108/IMDS-10-2022-0651","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85152045580&doi=10.1108%2fIMDS-10-2022-0651&partnerID=40&md5=6d8d7605ae7e518d808e2a3a2830532a","Politecnico di Milano, Milan, Italy","Seghezzi A., Politecnico di Milano, Milan, Italy; Mangiaracina R., Politecnico di Milano, Milan, Italy","Purpose: Failed deliveries (i.e. deliveries not accomplished due to the absence of customers) represent a critical issue in B2C (Business-to-consumer) e-commerce last-mile deliveries, implying high costs for e-commerce players and negatively affecting customer satisfaction. A promising option to reduce them would be scheduling deliveries based on the probability to find customers at home. This work proposes a solution based on presence data (gathered through Internet of Things [IoT] devices) to organise the delivery tours, which aims to both minimise the travelled distance and maximise the probability to find customers at home. Design/methodology/approach: The adopted methodology is a multi-method approach, based on interviews with practitioners. A model is developed and applied to Milan (Italy) to compare the performance of the proposed innovative solution with traditional home deliveries (both in terms of cost and delivery success rate). Findings: The proposed solution implies a significant reduction of missed deliveries if compared to the traditional operating mode. Accordingly, even if allocating the customers to time windows based on their availability profiles (APs) entails an increase in the total travel time, the average delivery cost per parcel decreases. Originality/value: On the academic side, this work proposes and evaluates an innovative last-mile delivery (LMD) solution that exploits new AI (Artificial Intelligence)-based technological trends. On the managerial side, it proposes an efficient and effective novel option for scheduling last-mile deliveries based on the use of smart home devices, which has a significant impact in reducing costs and increasing the service level. © 2023, Arianna Seghezzi and Riccardo Mangiaracina.","E-commerce; Innovation; Last-mile delivery","Automation; Electronic commerce; Internet of things; Sales; Travel time; B2C e-commerce; Business to consumer E commerces; Critical issues; E- commerces; High costs; Home devices; Innovation; Last mile; Last-mile delivery; Smart homes; Customer satisfaction",{"$nulls":6},"Al-Turjman F., Zahmatkesh H., Shahroze R., An overview of security and privacy in smart cities' IoT communications, Transactions on Emerging Telecommunications Technologies, 33, 3, (2022); Arnold F., Cardenas I., Sorensen K., Dewulf W., Simulation of B2C e-commerce distribution in Antwerp using cargo bikes and delivery points, European Transport Research Review, 10, 1, pp. 1-13, (2018); Baldacci R., Mingozzi A., Roberti R., Recent exact algorithms for solving the vehicle routing problem under capacity and time window constraints, European Journal of Operational Research, 218, 1, pp. 1-6, (2012); 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Florio A.M., Feillet D., Hartl R.F., The delivery problem: optimizing hit rates in e-commerce deliveries, Transportation Research Part B: Methodological, 117, pp. 455-472, (2018); Han S., Zhao L., Chen K., Luo Z.W., Mishra D., Appointment scheduling and routing optimization of attended home delivery system with random customer behaviour, European Journal of Operational Research, 262, 3, pp. 966-980, (2017); Hubner A., Kuhn H., Wollenburg J., Last mile fulfilment and distribution in omni-channel grocery retailing a strategic planning framework, International Journal of Retail and Distribution Management, 44, 3, pp. 228-247, (2016); Jick T.D., Mixing qualitative and quantitative methods: triangulation in action, Administrative Science Quarterly, 24, 4, pp. 602-611, (1979); Kandula S., Krishnamoorthy S., Roy D., A prescriptive analytics framework for efficient E-commerce order delivery, Decision Support Systems, 147, (2021); Kedia A., Kusumastuti D., Nicholson A., Acceptability of collection and delivery points from consumers' perspective: a qualitative case study of Christchurch city, Case Studies on Transport Policy, 5, 4, pp. 587-595, (2017); Konstantakopoulos G.D., Gayialis S.P., Kechagias E.P., Papadopoulos G.A., Tatsiopoulos I.P., An algorithmic approach for sustainable and collaborative logistics: a case study in Greece, International Journal of Information Management Data Insights, 1, 1, (2021); Lim S.F.W., Jin X., Srai J.S., Consumer-driven e-commerce: a literature review, design framework, and research agenda on last-mile logistics models, International Journal of Physical Distribution and Logistics Management, 48, 3, pp. 308-332, (2018); Ma B., Teo C.C., Wong Y.D., Consumers' preference for urban last-mile delivery: effects of value perception and long-term COVID-initiated contextual shifts, International Journal of Logistics Research and Applications, pp. 1-22, (2022); Mangiaracina R., Perego A., Seghezzi A., Tumino A., Innovative solutions to increase last-mile delivery efficiency in B2C e-commerce: a literature review, International Journal of Physical Distribution and Logistics Management, 49, 9, pp. 901-920, (2019); 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Song L., Cherrett T., McLeod F., Guan W., Addressing the last mile problem: transport impacts of collection and delivery points, Transportation Research Record, 2097, 1, pp. 9-18, (2009); Tsai Y.T., Tiwasing P., Customers' intention to adopt smart lockers in last-mile delivery service: a multi-theory perspective, Journal of Retailing and Consumer Services, 61, (2021); Urciuoli L., Hintsa J., Adapting supply chain management strategies to security–an analysis of existing gaps and recommendations for improvement, International Journal of Logistics Research and Applications, 20, 3, pp. 276-295, (2017); Van Duin J.H.R., De Goffau W., Wiegmans B., Tavasszy L.A., Saes M., Improving home delivery efficiency by using principles of address intelligence for B2C deliveries, Transportation Research Procedia, 12, pp. 14-25, (2016); Wang X., Yuen K.F., Wong Y.D., Teo C.C., An innovation diffusion perspective of e-consumers’ initial adoption of self-collection service via automated parcel station, The International Journal of Logistics Management, 29, 1, pp. 237-260, (2018); Yildiz B., Savelsbergh M., Service and capacity planning in crowd-sourced delivery, Transportation Research Part C: Emerging Technologies, 100, pp. 177-199, (2019)","A. Seghezzi; Politecnico di Milano, Milan, Italy; email: arianna.seghezzi@polimi.it",null,"Emerald Publishing",{"$nulls":5},2635577.0,null,"IMDSD",null,"English","Ind Manage Data Sys","Article","Final","All Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85152045580"]
["Oloruntobi O.; Mokhtar K.; Mohd Rozar N.; Gohari A.; Asif S.; Chuah L.F.","Oloruntobi, Olakunle (57210403278); Mokhtar, Kasypi (57188831324); Mohd Rozar, Norlinda (58170173800); Gohari, Adel (57192992303); Asif, Saira (36636749300); Chuah, Lai Fatt (56589691800)","57210403278; 57188831324; 58170173800; 57192992303; 36636749300; 56589691800","Effective technologies and practices for reducing pollution in warehouses - A review",2023.0,"Cleaner Engineering and Technology",13.0,null,100622.0,null,null,null,23.0,"10.1016/j.clet.2023.100622","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85151520383&doi=10.1016%2fj.clet.2023.100622&partnerID=40&md5=c061d256e72652527dd3b374be291ae5","Faculty of Maritime Studies, Universiti Malaysia Terengganu, Terengganu, Malaysia; Faculty of Built Environment and Surveying, Universiti Teknologi Malaysia, Skudai, Malaysia; Faculty of Sciences, Department of Botany, PMAS Arid Agriculture University, Punjab, Rawalpindi, 46300, Pakistan","Oloruntobi O., Faculty of Maritime Studies, Universiti Malaysia Terengganu, Terengganu, Malaysia; Mokhtar K., Faculty of Maritime Studies, Universiti Malaysia Terengganu, Terengganu, Malaysia; Mohd Rozar N., Faculty of Maritime Studies, Universiti Malaysia Terengganu, Terengganu, Malaysia; Gohari A., Faculty of Built Environment and Surveying, Universiti Teknologi Malaysia, Skudai, Malaysia; Asif S., Faculty of Sciences, Department of Botany, PMAS Arid Agriculture University, Punjab, Rawalpindi, 46300, Pakistan; Chuah L.F., Faculty of Maritime Studies, Universiti Malaysia Terengganu, Terengganu, Malaysia","This article examines the challenges of implementing the United Nation Sustainable Development Goals 2050 green initiative for warehouse management and operation and highlights a gap in the literature on specific strategies for reducing greenhouse gas emissions and pollution in warehousing and logistics operations. A four-step review process was used to analyze 75 recent research articles on environmental sustainability, smart energy consumption and warehouse green practices. Warehouse building configuration and operation were reviewed to identify critical environmental issues, along with green industrial building legislation in the European Union, the United States and Asia. This study found that increasing warehouse construction and renovations are worsening pollution and industrial waste production, while space demand in the United States will reach 560 × 106 by 2025. Findings showed that packaging waste from warehouses accounted for 12% of the 146.1 × 106 t of municipal solid waste in the United States landfills in 2018 and the industry's growth is increasing indoor and outdoor air pollution. Warehouses' energy consumption is also worsening due to their energy needs. This article proposes green warehouse practices and technologies as potential solutions to mitigate the environmental effects of the industry's growth. Legislation is needed to solve many warehousing issues as global e-commerce grows for better consumer accountability demands and efficiency gains. © 2023 The Authors","Energy consumption; GHG; Green warehouse; Legislation; Pollution; Sustainable development",{"$nulls":5},"U.S. Green Building Council, USGBC","The other most used green building certification system is Leadership in Energy and Environmental Design (LEED), which was a green building certification introduced by the US Green Building Council (USGBC). Alawneh et al. (2019) affirmed that LEED is the second internationally recognized certification system; this is like the standards earlier revealed but comprised a unique set of rating systems for green building design, construction, maintenance and operation. This also includes warehouses with different certification levels (e.g., from Certified to Platinum). In Singapore, a Green Mark Certificate BCA is awarded to newly constructed non-residential buildings (NRB) such as Green Mark Gold, GoldPLUS, or Platinum. The design of the building development shall also meet all the relevant criteria (Wu et al., 2020). The GSK-SN02 Warehouse and Redlion Warehouse have some of the most impressive facilities in Singapore, as stated by the author.",{"$cut":{"chars":20051,"head":"Abbasi T.U., Ahmad M., Asma M., Rozina, Munir M., Zafar M., Katubi K.M., Alsaiari N.S., Yahya A.E.M., Mubashir M., Chuah L.F., Bokhari A., High efficient conversion of Cannabis sativa L. biomass into bioenergy by using green tungsten oxide nano-catalyst toward s carbon neutrality, Fuel, (2023); Accorsi R., Bortolini M., Gamberi M., Manzini R., Pilati F., Multi-objective warehouse building design to optimize the cycle time, total cost, and carbon footprint, Int. J. Adv. Manuf. Technol., 92, pp. 839-854, (2017); Agyabeng-Mensah Y., Ahenkorah E., Afum E., Dacosta E., Tian Z., Green warehousing, logistics optimization, social values and ethics and economic performance: the role of supply chain sustainability, Int. J. Logist. Manag., 31, 3, pp. 549-574, (2020); Ahmad T., Iqbal J., Azmi Bustam M., Babar M., Tahir M.B., Sagir M., Irfan M., Asgharf H.M.A., Hassan A., Riaz A., Chuah L.F., Bokhari A., Mubashir M., Show P.L., Performance evaluation of phosphonium based deep eutectic solvents coated cerium oxide nanoparticles for CO<sub>2</sub> capture, Environ. Res., 222, (2023); Alawneh R., Ghazali F., Ali H., Asif M., A new index for assessing the contribution of energy efficiency in LEED 2009 certified green buildings to achieving UN sustainable development goals in Jordan, Int. J. Green Energy, 16, 6, pp. 490-499, (2019); Ali S.S., Kaur R., Khan S., Evaluating sustainability initiatives in warehouse for measuring sustainability performance: an emerging economy perspective, Ann. Oper. Res., 1, pp. 1-40, (2022); Alsaiari M., Bokhari A., Chuah L.F., Mubashir M., Harraz F.A., Almohana A.I., Show P.L., Awasthi M.K., Rizk M.A., Synthesis of methyl esters from Hippophae rhamnoides via pilot scale hydrodynamic cavitation intensification reactor, Renew. Energy, 205, pp. 238-247, (2023); Assanie L., Weiss M., Texas industrial building booms as economy, population grow, South. Econ., 2, pp. 7-10, (2019); Ameen M., Zafar M., Ramadan M.F., Ahmad M., Makhkamov T., Bokhari A., Mubashir M., Chuah L.F., Show P.L., Conversion of novel non-edible Bischofia javanica seed oil into methyl ester via recyclable zirconia-based phyto-nanocatalyst: A circular bioeconomy approach for eco-sustenance, Environ. Technol. Innov., (2023); Arshad S., Ahmad M., Munir M., Sultana S., Zafar M., Dawood S., Rozina, Alghamdi A.M., Asif S., Bokhari A., Mubashir M., Chuah L.F., Show P.L., Assessing the potential of green CdO<sub>2</sub> nano-catalyst for the synthesis of biodiesel using non-edible seed oil of Malabar Ebony, Fuel, 333, 2, (2023); Asif S., Klemes J.J., Mukhtar A., Saqib S., Chuah L.F., Bokhari A., Intensification of biodiesel synthesis in a cavitation system from Xanthium Spinosum oil, Chemical Engineering Transactions, 86, pp. 151-156, (2021); Bajec P., Tuljak-Suban D., Bajor I., A warehouse social and environmental performance metrics framework, Promet - Traffic & Transp., 32, 4, pp. 513-526, (2020); Bianchi M., Cordella M., Does circular economy mitigate the extraction of natural resources? Empirical evidence based on analysis of 28 European economies over the past decade, Ecol. Econ., 203, (2023); Bokhari A., Yusup S., Chuah L.F., Kamil R.N.M., Relative efficiency of esterified rubber seed oil in a hydrodynamic cavitation reactor and purification via distillation column, Chemical Engineering Transactions, 52, pp. 775-780, (2016); Burinskiene A., Lorenc A., Lerher T., A simulation study for the sustainability and reduction of waste in warehouse logistics, Int. J. Simulat. Model., 17, 3, pp. 485-497, (2018); Cao Y., Sun Y., Han N., Li X., Wang Q., Sun K., Si W., Wang F., Zhao X., Bokhari A., Mubashir M., Chuah L.F., Show P.L., Novel highly active and selective Co-N-S-C efficient ORR catalyst derived from in-situ egg gel pyrolysis, Fuel, 333, 1, (2023); Cheah K.W., Yusup S., Chuah L.F., Bokhari A., Physio-chemical studies of locally sourced non-edible oil: prospective feedstock for renewable diesel production in Malaysia, Procedia Eng., 148, pp. 451-458, (2016); Chuah L.F., Mokhtar K., Mhd Ruslan S.M., Abu Bakar A., Abdullah M.A., Osman N.H., Bokhari A.,"}},"L.F. Chuah; Faculty of Maritime Studies, Universiti Malaysia Terengganu, Terengganu, Malaysia; email: lfchuah@umt.edu.my",null,"Elsevier Ltd",{"$nulls":5},2.6667908E7,null,null,null,"English","Clean. Eng. Technol.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85151520383"]
["Yunus E.N.","Yunus, Erlinda Nusron (55355088700)",5.53550887E10,"Would compensation be necessary? The importance of service recovery strategy in e-retail delivery problems",2023.0,"International Journal of Productivity and Performance Management",72.0,5.0,null,1286.0,1303.0,17.0,1.0,"10.1108/IJPPM-05-2021-0273","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85118790606&doi=10.1108%2fIJPPM-05-2021-0273&partnerID=40&md5=b1305e7bd586cd690795ded2de43a0e9","Operations Management Department, Sekolah Tinggi Manajemen PPM, Jakarta, Indonesia","Yunus E.N., Operations Management Department, Sekolah Tinggi Manajemen PPM, Jakarta, Indonesia","Purpose: This study examines the different effects of service recovery strategies on customers' future intentions when online shoppers were experiencing delivery failures. Two types of problem severity are evaluated: wrong-product delivery (issues with the product quality or quantity) and late delivery. This study also investigates the impact of service criticality on the relationship between service recovery strategies and customers' future intentions. Design/methodology/approach: This study employs experimental research with 123 online shoppers as participants. Following the results, a subsequent test is conducted to examine the effect of participants' demographics on future intentions. Finally, the current study elaborates the findings using qualitative research, interviewing both sides impacted by the service failures: online shoppers and e-retail managers. Findings: The findings show that complementing product replacement with monetary compensation is the most effective strategy to improve repurchase intention after a dissatisfaction moment. This effect is indifferent to service criticality and severity. Age influences the participants' repurchase intentions, in which younger people are less tolerant of service failures. In contrast, gender and education level do not provide any differences. To prevent delivery failures, managers participating in this study suggest several best practices regarding systems and infrastructure, people and coordination and collaboration with logistics partners. Research limitations/implications: The study mainly examines a limited type of service and service failures. Further studies are encouraged to expand the variables and scenarios, as well as to employ more distinctive methods, to enrich the findings related to recovery strategy in the e-commerce industry. Practical implications: Given proper compensation, service failure could create momentum for online retailers to boost customer loyalty. This study suggests that managers design the most effective service recovery to win customers back to the business. Originality/value: This paper enriches the literature related to a service recovery strategy, particularly within the online shopping context. © 2021, Emerald Publishing Limited.","Delivery problems; Future intentions; Online retail; Service failure; Service recovery; Supply chain management",{"$nulls":7},"Anderson J.C., Gerbing D.W., Structural equation modeling in practice: a review and recommended two-step approach, Psychological Bulletin, 103, 3, pp. 411-423, (1988); Azemi Y., Ozuem W., Howell K.E., Lancaster G., An exploration into the practice of online service failure and recovery strategies in the Balkans, Journal of Business Research, 94, pp. 420-431, (2019); Bitner M.J., Booms B.H., Mohr L.A., Critical service encounters: the employee's viewpoint, Journal of Marketing, 58, 4, pp. 95-106, (1994); Bozic B., Siebert S., Martin G., A grounded theory study of factors and conditions associated with customer trust recovery in a retailer, Journal of Business Research, 109, pp. 440-448, (2020); 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e-Conomy SEA 2019, (2019); Hair J.F., Black W.C., Babin B.J., Multivariate Data Analysis, (2009); Hajli N., Sims J., Shanmugam M., A practical model for e-commerce adoption in Iran, Journal of Enterprise Information Management, 27, 6, pp. 719-730, (2014); Hart C.W., Heskett J.L., Sasser J.W., The profitable art of service recovery, Harvard Business Review, 68, 4, pp. 148-156, (1990); Hindranto F., Bisnis e-commerce semakin gurih, (2021); Hjort K., Hellstrom D., Karlsson S., Oghazi P., Typology of practices for managing consumer returns in internet retailing, International Journal of Physical Distribution and Logistics Management, 49, 7, pp. 767-790, (2019); Holloway B.B., Beatty S.E., Service failure in online retailing: a recovery opportunity, Journal of Service Research, 6, 1, pp. 92-105, (2003); How T.C., Yi H.K., Rajendran S.D., A study on service failure that influence repurchase intention in online retailing: a study among online shoppers in Klang Valley, E3S Web of Conferences, 136, (2019); Jain N.K., Gajjar H., Shah B.J., Sadh A., A conceptual framework for measuring e-fulfillment dimensions: a consumer perspective, Journal of Internet Commerce, 14, 3, pp. 363-383, (2015); Jain N.K., Gajjar H., Shah B.J., Sadh A., E-fulfillment dimensions and its influence on customers in e-tailing: a critical review, Asia Pacific Journal of Marketing and Logistics, 29, 2, pp. 347-369, (2017); Jain N.K., Gajjar H., Shah B.J., Electronic logistics service quality and repurchase intention in e-tailing: catalytic role of shopping satisfaction, payment options, gender and returning experience, Journal of Retailing and Consumer Services, 59, (2021); Jung N.Y., Seock Y.K., Effect of service recovery on customers' perceived justice, satisfaction, and word-of-mouth intentions on online shopping websites, Journal of Retailing and Consumer Services, 37, pp. 23-30, (2017); Jung N.Y., Seock Y.K., The role of communication channel in delivering service recovery in online shopping environment, International Journal of Electronic Marketing and Retailing, 9, 1, pp. 59-76, (2018); E-commerce in Indonesia – outlook, prospects, and challenges, (2014); Kautish P., Sharma R., Managing online product assortment and order fulfillment for superior e-tailing service experience: an empirical investigation, Asia Pacific Journal of Marketing and Logistics, 31, 4, pp. 1161-1192, (2019); Kautish P., Paul J., Sharma R., The effect of assortment and fulfillment on shopping assistance and efficiency: an e-tail servicescape perspective, Journal of Retailing and Consumer Services, 59, (2021); Kline R.B., Principles and Practice of Structural Equation Modeling, (2015); Levesque T.J., McDougall G.H., Service problems and recovery strategies: an experiment, Canadian Journal of Administrative Sciences/Revue Canadienne des Sciences de l'Administration, 17, 1, pp. 20-37, (2000); Lin H.H., Wang Y.S., Chang L.K., Consumer responses to online retailer's service recovery after a service failure, Managing Service Quality: An International Journal, 1, 5, pp. 511-534, (2011); Magnini V.P., Ford J.B., Markowski E.P., Honeycutt E.D., The service recovery paradox: justifiable theory or smoldering myth?, Journal of Services Marketing, 21, 3, pp. 213-225, (2007); Martin B., Strong C., O'Connor P., How psychologically entitled shoppers respond to service recovery apologies, European Journal of Marketing, 52, 9-10, pp. 2173-2190, (2018); Maxwell S.E., Delaney H.D., Kelley K., Designing Experiments and Analyzing Data: A Model Comparison Perspective, (2018); McCollough M.A., Bharadwaj S.G., The recovery paradox: an examination of consumer satisfaction in relation to disconfirmation, service quality, and attribution based theories, Marketing Theory and Applications, 119, (1992); Mentzer J.T., Gomes R., Krapfel R.E., Physical distribution service: a fundamental marketing concept?, Journal of the Academy of Marketing Science, 17, 1, pp. 53-62, (1989); Murfield M., Boone C.A., Rutner P., Thomas R., Investigating logistics service quality in omni-channel retailing, International Journal of Physical Distribution and Logistics Management, 47, 4, pp. 263-296, (2017); Roschk H., Gelbrich K., Identifying appropriate compensation types for service failures: a meta-analytic and experimental analysis, Journal of Service Research, 17, 2, pp. 195-211, (2014); Singh R., Rosengren S., Why do online grocery shoppers switch? An empirical investigation of drivers of switching in online grocery, Journal of Retailing and Consumer Services, 53, (2020); Soares R.R., Zhang T.T.C., Proenca J.F., Kandampully J., Why are Generation Y consumers the most likely to complain and repurchase?, Journal of Service Management, 28, 3, pp. 520-540, (2017); Sousa R., Voss C.A., The effects of service failures and recovery on customer loyalty in e‐services, International Journal of Operations & Production Management, 29, 8, pp. 834-864, (2009); Tarofder A.K., Nikhashemi S.R., Azam S.F., Selvantharan P., Haque A., The mediating influence of service failure explanation on customer repurchase intention through customers satisfaction, International Journal of Quality and Service Sciences, 8, 4, pp. 516-535, (2016); Estimates of global e-commerce 2019 and preliminary assessment of COVID-19 impact on online retail 2020, (2021); Wertz J., 3 emerging e-commerce growth trends to leverage in 2020, (2021); Yu Y., Wang X., Zhong R.Y., Huang G.Q., E-commerce logistics in supply chain management: implementations and future perspective in furniture industry, Industrial Management and Data Systems, 117, 10, pp. 2263-2286, (2017); Zhang Y., Smutkupt S., Online logistics service quality: a case study of Chinese home appliance retailing delivery, Journal of Supply Chain Management: Research and Practice, 15, 1, pp. 16-26, (2021)","E.N. Yunus; Operations Management Department, Sekolah Tinggi Manajemen PPM, Jakarta, Indonesia; email: yunus.erlinda@gmail.com",null,"Emerald Publishing",{"$nulls":5},1.7410401E7,null,null,null,"English","Int. J. Product. Perform. Manage.","Article","Final",null,"Scopus","2-s2.0-85118790606"]
["Tang Y.M.; Chau K.Y.; Lau Y.-Y.; Zheng Z.","Tang, Yuk Ming (55231482700); Chau, Ka Yin (57192810298); Lau, Yui-Yip (37087294800); Zheng, Zehang (58138934500)","55231482700; 57192810298; 37087294800; 58138934500","Data-Intensive Inventory Forecasting with Artificial Intelligence Models for Cross-Border E-Commerce Service Automation",2023.0,"Applied Sciences (Switzerland)",13.0,5.0,3051.0,null,null,null,5.0,"10.3390/app13053051","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85149939167&doi=10.3390%2fapp13053051&partnerID=40&md5=dc7c2716f7d677c62eae63a37c2ebf73","Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong; Faculty of Business, City University of Macau, Macao; Division of Business and Hospitality Management, College of Professional and Continuing Education, The Hong Kong Polytechnic University, Hong Kong","Tang Y.M., Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong, Faculty of Business, City University of Macau, Macao; Chau K.Y., Faculty of Business, City University of Macau, Macao; Lau Y.-Y., Division of Business and Hospitality Management, College of Professional and Continuing Education, The Hong Kong Polytechnic University, Hong Kong; Zheng Z., Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong","Building an adaptative, flexible, resilient, and reliable inventory management system provides a reliable supply of cross-border e-commerce commodities, enhances supply chain members with a flow of products, fulfills ever-changing customer requirements, and enables e-commerce service automation. This study uses an e-commerce company as a case study to collect intensive inventory data. The key process of the AI approach for an intensive data forecasting framework is constructed. The study shows that the AI model’s optimization process needs to be combined with the problems of specific companies and information for analysis and optimization. The study provides optimization suggestions and highlights the key processes of the AI-predicting inventory model. The XGBoost method demonstrates the best performance in terms of accuracy (RMSE = 46.64%) and reasonable computation time (9 min 13 s). This research can be generalized and used as a useful basis for further implementing algorithms in other e-commerce enterprises. In doing so, this study highlights the current trend of logistics 4.0 solutions via the adoption of robust data-intensive inventory forecasting with artificial intelligence models for cross-border e-commerce service automation. As expected, the research findings improve the alleviation of the bullwhip impact and sustainable supply chain development. E-commerce enterprises may provide a better plan for their inventory management so as to minimize excess inventory or stock-outs, and improve their sales strategies and promotional and marketing activities. © 2023 by the authors.","artificial intelligence; cross-border e-commerce; data-intensive; Extreme Gradient Boosting; inventory forecasting; model; replenishment automation; supply chain management",{"$nulls":7},"Tejesh B.S.S., Neeraja S., Warehouse inventory management system using IoT and open source framework, Alex. Eng. J, 57, pp. 3817-3823, (2018); Lau Y.-Y., Mazaheri A., A Vendor Managed Inventory with FIFO and LIFO Plans, J. Res. Sci. Eng. Technol, 8, pp. 43-59, (2020); Yui-Yip L., Zhang J., Ng A.K., Roozbeh P., Implications of a Pandemic Outbreak Risk: A Discussion on China’s Emergency Logistics in the Era of Coronavirus Disease 2019 (COVID-19), J. Int. Logist. Trade, 18, pp. 127-135, (2020); Wong S., Yeung J.K.W., Lau Y.-Y., So J., Technical Sustainability of Cloud-Based Blockchain Integrated with Machine Learning for Supply Chain Management, Sustainability, 13, (2021); Li W., Tang Y.M., Yu K.M., To S., Slc-gan: An automated myocardial infarction detection model based on generative adversarial networks and convolutional neural networks with single-lead electrocardiogram synthesis, Inf. Sci, 589, pp. 738-750, (2022); Saberi-Movahed F., Najafzadeh M., Mehrpooya A., Receiving More Accurate Predictions for Longitudinal Dispersion Coefficients in Water Pipelines: Training Group Method of Data Handling Using Extreme Learning Machine Conceptions, Water Resour. Manag, 34, pp. 529-561, (2020); Najafzadeh M., Homaei F., Farhadi H., Reliability assessment of water quality index based on guidelines of national sanitation foundation in natural streams: Integration of remote sensing and data-driven models, Artif. Intell. 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Tang; Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong; email: yukming.tang@polyu.edu.hk; Y.-Y. Lau; Division of Business and Hospitality Management, College of Professional and Continuing Education, The Hong Kong Polytechnic University, Hong Kong; email: yuiyip.lau@cpce-polyu.edu.hk",null,"MDPI",{"$nulls":5},2.0763417E7,null,null,null,"English","Appl. Sci.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85149939167"]
["Fu X.; Sun X.","Fu, Xiaoxi (57189367995); Sun, Xuecheng (57369409000)","57189367995; 57369409000","ANALYSIS OF PACKAGING RECYCLING PATTERNS USING MATHEMATICAL MODELING; [Análisis de patrones de reciclaje de empaques con modelación matemática]",2023.0,"Revista Internacional de Contaminacion Ambiental",38.0,null,null,109.0,116.0,7.0,0.0,"10.20937/RICA.54588","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85186629284&doi=10.20937%2fRICA.54588&partnerID=40&md5=77c3426c0582c4e88c531ce8f88e64a3","School of Economics and Management, Tianjin Sino-German University of Applied Sciences, Tianjin, 300350, China","Fu X., School of Economics and Management, Tianjin Sino-German University of Applied Sciences, Tianjin, 300350, China; Sun X., School of Economics and Management, Tianjin Sino-German University of Applied Sciences, Tianjin, 300350, China","With the rapid development of online shopping platforms, China’s express industry has embraced explosive growth, but, at the same time, numerous significant social problems also occur. Regarding the problems, how to deal with the large number of packaging from express delivery has become a growing concern for governments, e-commerce platforms, express enterprises, and ordinary consumers. Abandoned express packaging increases the cost of express enterprises and aggravates the environmental burden. Therefore, based on previous research, this paper tried to establish two recycling models and analyze their benefits through mathematical model deduction. By comparing the results, this paper aimed to set up a model to maximize express enterprises’ revenue from recycling packaging. According to the results, regardless of the governmental subsidies, the revenue from recycling packaging was bound up with the environmental awareness of residents and the recycling price. Through the comprehensive analysis, the author hopes that the results could provide express enterprises with the option of the best recycling model in different contexts and help governments formulate more ap-propriate recycling policies. © 2023, Centro de Ciencias de la Atmosfera, UNAM. All rights reserved.","Express packaging; mathematical modeling; optimization; recycling","China; electronic commerce; numerical model; optimization; packaging waste; recycling; subsidy system",{"$nulls":4},"Tianjin Education Commission, (2018SK154)","This paper is supported by the following funds: Tianjin Education Commission Scientific Research Project “Research on Express Packaging Recycling Path under Online-Offline Integration Mode” (Project Number: 2018SK154).","Bening C.R., Pruess J., Blum N.U., Towards a circular plastics economy: interacting barriers and contested solutions for flexible packaging recycling, Journal of Cleaner Production, 302, pp. 126-152, (2021); Cai K.H., Xie Y.F., Song Q.B., Ni Sheng, Wen Z.G., Identifying the status and differences between urban and rural residents’ behaviors and attitudes toward express packaging waste management in Guangdong province, China, Science of The Total Environment, 797, pp. 148-166, (2021); Chen D., Yang Z., Innovative method for recovering the electronic wastes in the universi-ties based on moral hazard, Management Review, 8, pp. 247-255, (2018); Chen H., Express packaging: How to dispose of massive garbage?, Ecological Economy, 32, 6, pp. 10-13, (2016); Ferdinand F.N., Hong B.K., Chang S.K., A genetic algorithm based heuristic for the design of pick-up and delivery routes for strategic alliance in express delivery services, IFAC Proceedings, 46, 9, pp. 1938-1943, (2013); Gu F., Guo J.F., Zhang W.J., Summers P.A., Hall P., From waste plastics to industrial raw ma-terials: A life cycle assessment of mechanical plastic recycling practice based on a real-world case study, Science of the Total Environment, 601, pp. 1192-1207, (2017); Gu F., Zhang W.J., Guo J.F., Hall P., Exploring “Internet plus Recycling”: Mass balance and life cycle assessment of a waste management system associ-ated with a mobile application, Science of the Total Environment, 649, pp. 172-185, (2019); Hayashi K., Nemoto T., Nakaharai S., The development of the parcel delivery service and its regulations in China, Procedia-Social and Behavioral Sciences, 125, 1, pp. 186-198, (2014); Hua Y.F., Dong F., Goodman J., How to lever-age the role of social capital in pro-environmental behavior: A case study of residents’ express waste recycling behavior in China, Journal of Cleaner Production, 280, 2, (2021); Li C., Zhu L., Optimal recovery strategies of home appliance trade-in scheme under EPR, Op-erations Research and Management Science, 26, 8, pp. 67-75, (2017); Liang Q., Deng H.P., He P., Fang W., Jiang H., Luo T., Effects of plant-derived smoke on seed germination of species common in subtropical China, Applied Ecology and Environmental Research, 18, 4, pp. 5175-5185, (2020); Liu W., Thoughts on promoting China’s express packaging legislation, Academic Journal of Zhongzhou, 3, pp. 62-66, (2018); Tian L.P., Sun Q., Li W.L., Systems dynamics based strategic model for recycling used household ap-pliances with environmental protection, Chinese Journal of Management Science, 28, 5, pp. 167-175, (2020); Xiong Z., Liang X., Study on recycling mode of closed-loop supply chain considering consumer environmental awareness, Soft Science, 28, 11, pp. 61-66, (2014); Yang J.H., Long R.Y., Chen H., Wu H., Lin A., He L., Willingness to participate in take-out packaging waste recycling: Relationship among effort level, advertising effect, subsidy and penalty, Waste Management, 121, pp. 141-152, (2021); Yang W.J., Zhao Y., Wang D., Et al., Using principal components analysis and IDW interpolation to deter-mine spatial and temporal changes of surface water quality of Xin’anjiang river in Huangshan, China, International Journal of Environmental Research and Public Health, 17, 8, (2020); Yu D., Mao Y., Gu B., Nojavan S., Jermsittiparsert K., Nasseri M., A new LQG optimal control strategy applied on a hybrid wind turbine/solid oxide fuel cell/ in the presence of the interval uncertainties, Sustainable Energy, Grids and Networks, 21, (2020); Yu H.N., Shen S.H., Qiang G., Gong X.B., Packing theory and volumetrics-based aggregate gra-dation design method, Journal of Materials in Civil Engineering, 32, 6, (2020); Zhang H., Study on the internal force of geomem-brane of landfill in hexavy metal contaminated area, Earth Sciences Research Journal, 24, 1, pp. 111-118, (2020); Zhang H., Zhong N., Zhang Z.G., Et al., Inspiration and experience of foreign express packaging recycling and processing system construction, Resource Development & Market, 33, 10, pp. 1231-1235, (2017); Zhu H., Research on shared express packaging design: Rethinking based on design practice, Decora-tion, 10, pp. 104-107, (2019)","X. Fu; School of Economics and Management, Tianjin Sino-German University of Applied Sciences, Tianjin, 300350, China; email: fuxiaoxi1984@126.com",null,"Centro de Ciencias de la Atmosfera, UNAM",{"$nulls":5},1884999.0,null,"RCAME",null,"English","Rev. Int. Contam. Ambient.","Article","Final","All Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85186629284"]
["He D.; Ceder A.A.; Zhang W.; Guan W.; Qi G.","He, Dongdong (57986638900); Ceder, Avishai (Avi) (7003304761); Zhang, Wenyi (55080985800); Guan, Wei (55702521101); Qi, Geqi (55571520600)","57986638900; 7003304761; 55080985800; 55702521101; 55571520600","Optimization of a rural bus service integrated with e-commerce deliveries guided by a new sustainable policy in China",2023.0,"Transportation Research Part E: Logistics and Transportation Review",172.0,null,103069.0,null,null,null,1.0,"10.1016/j.tre.2023.103069","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85149066875&doi=10.1016%2fj.tre.2023.103069&partnerID=40&md5=6df8df20ff8f748eecdfb81ddfb36f51","Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Ministry of Transport, Beijing Jiaotong University, Beijing, 100044, China; Faculty of Civil and Environmental Engineering and the Transportation Research Institute, Technion-Israel Institute of Technology, Technion City, Haifa, 32000, Israel","He D., Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Ministry of Transport, Beijing Jiaotong University, Beijing, 100044, China; Ceder A.A., Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Ministry of Transport, Beijing Jiaotong University, Beijing, 100044, China, Faculty of Civil and Environmental Engineering and the Transportation Research Institute, Technion-Israel Institute of Technology, Technion City, Haifa, 32000, Israel; Zhang W., Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Ministry of Transport, Beijing Jiaotong University, Beijing, 100044, China; Guan W., Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Ministry of Transport, Beijing Jiaotong University, Beijing, 100044, China; Qi G., Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Ministry of Transport, Beijing Jiaotong University, Beijing, 100044, China","Electronic business has expanded, resulting in flourishing rural e-commerce globally, and particularly in China. This paper introduces a novel rural public transit system that integrates passenger and freight services—a rural electric bus service that provides services for passengers and e-commerce packages. This blended service reduces logistical costs and generates additional income for the transit operator. The objective is to minimise cost for the transit user and operator by using a mixed-integer linear programming model that solves bus routing and bus trip scheduling for multiple rural towns; in addition, the model is tested by the Gurobi solver at small-scale instances. The developed solution is a hybrid heuristic algorithm based on adaptive large neighborhood search and tabu search approaches. Finally, a case study in China is conducted to examine the proposed cost-effective methodology and ensure that the integrated scheme will significantly save operational system costs without causing any passenger inconvenience. The research also shows how to optimally design the size of rural electric buses to reduce purchasing and maintenance costs. The optimal results of the case study, comprising 5 towns and 78 villages, show an annual cost saving of approximately ¥847,000 (approximately $121,000) and an annual mileage saving of approximately 66,000 km for the proposed scheme. In addition, the case study explicates key parameters selected for transfer package requirements and the effective deployment of the proposed scheme. © 2023 Elsevier Ltd","Adaptive large neighborhood search; Hybrid heuristic algorithm; Integrated passenger-freight transit; Mixed integer programming model; Public transport; Tabu search","China; Bus transportation; Cost effectiveness; Cost reduction; Electric buses; Electronic commerce; Heuristic algorithms; Integer programming; Adaptive large neighborhood searches; Bus services; Case-studies; E- commerces; Electric bus; Hybrid heuristic algorithms; Integrated passenger-freight transit; Mixed integer programming model; Public transport; Transit operators; adaptive management; freight transport; neighborhood; optimization; public transport; sustainability; transportation planning; transportation policy; Tabu search",{"$nulls":4},"Dutch government; National Natural Science Foundation of China, NSFC, (71621001, 71961137008, 91746201)","Funding text 1: This work was supported by the National Natural Science Foundation of China [NSFC, grant numbers 71961137008 , 71621001 , 91746201 ]. ; Funding text 2: Recent research on integrated passenger-freight transport mainly focused on social science. Bruzzone et al. (2021) proposed seven key performance indicators from operational, environmental, and social perspectives to evaluate the potential improvement of freight-passenger integration compared to current transport schemes. Kiba-Janiak et al. (2021) developed an urban maturity model to assess the maturity level of formulating and implementing sustainable integrated passenger-freight transport strategies. Le Pira et al. (2021) analysed the feasibility and sustainability benefits of integrating freight with passenger transport in a MaaS environment, and a framework for an extended version called MaaS4PaF is proposed. Finally, the potential impact of the integration is qualitatively assessed. With the support of funding from the Dutch government, several universities, transit operators, and urban logistics service providers in the Netherlands have jointly organised a cargo hitching project, which provides essential social and environmental benefits and a sustainable commercial model for the system ( Van Duin et al., 2019 ). Nocera et al. (2020) provide a theoretical framework for a good assessment and planning of the FLM through five distinct phases to reduce the adverse effects of the FLM, with an eye on the possible integration of freight and passengers. In short, as Cavallaro and Nocera (2021) emphasised, greater attention must be paid to the aspects studied in the social sciences, which may represent a further challenge for implementing integrated passenger and freight transportation. 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Serv., 49, pp. 316-326, (2019); Zhen L., Ma C., Wang K., Wang K., Xiao L., Zhang W., Multi-depot multi-trip vehicle routing problem with time windows and release dates, Transport. Res. Part E: Logist. Transport. Rev., 135, (2020); (2022)","W. Guan; Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Ministry of Transport, Beijing Jiaotong University, Beijing, 100044, China; email: weig@bjtu.edu.cn",null,"Elsevier Ltd",{"$nulls":5},1.3665545E7,null,null,null,"English","Transp. Res. Part E Logist. Transp. Rev.","Article","Final",null,"Scopus","2-s2.0-85149066875"]
["Hen K.W.; Seah C.S.; Witarsyah D.; Shaharudin S.M.; Loh Y.X.","Hen, Kai Wah (55893063300); Seah, Choon Sen (57193430848); Witarsyah, Deden (57192986806); Shaharudin, Shazlyn Milleana (57195628106); Loh, Yin Xia (58611987700)","55893063300; 57193430848; 57192986806; 57195628106; 58611987700","The study on Malaysia Agricultural E-Commerce (AE): A Customer Purchase Intention",2023.0,"International Journal on Informatics Visualization",7.0,3.0,null,704.0,709.0,5.0,0.0,"10.30630/joiv.7.3.1372","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85171899035&doi=10.30630%2fjoiv.7.3.1372&partnerID=40&md5=6d0d408731f43ab941973a74cf693cae","International College, Tunghai University, Taiwan; Faculty of Accountancy and Management, Universiti Tunku Abdul Rahman, Bandar Sungai Long, Kajang, Malaysia; Department of Information System, Telkom University, Bandung, Indonesia; Department of Mathematics, Faculty of Science and Mathematics, Universiti Pendidikan Sultan Idris, Perak, Tanjung Malim, Malaysia","Hen K.W., International College, Tunghai University, Taiwan; Seah C.S., Faculty of Accountancy and Management, Universiti Tunku Abdul Rahman, Bandar Sungai Long, Kajang, Malaysia; Witarsyah D., Department of Information System, Telkom University, Bandung, Indonesia; Shaharudin S.M., Department of Mathematics, Faculty of Science and Mathematics, Universiti Pendidikan Sultan Idris, Perak, Tanjung Malim, Malaysia; Loh Y.X., Faculty of Accountancy and Management, Universiti Tunku Abdul Rahman, Bandar Sungai Long, Kajang, Malaysia","Electronic commerce (E-Commerce) became an essential trading platform after the Covid-19 pandemic. From essential products to luxury brands, consumers can find almost everything on normal E-Commerce platforms except fresh agricultural products. Agricultural E-Commerce (AE) is introduced to overcome market needs, especially during the pandemic. Technology Acceptance Model (TAM) is studied and integrated with additional variables to determine the needs of AE in Malaysia. This study studied five variables (product quality, logistic service quality, perceived price & value, platform design quality, and platform security) to determine Malaysian consumers’ purchase intention towards AE. Five hypotheses were developed to identify the relationship between the variables. A total of 300 AE users have contributed their perceptions as respondents in this study through a survey questionnaire. The survey questionnaire was distributed through non-probability sampling techniques. The collected data were processed before the data analysis via Statistical Package for The Social Science (SPSS) version 25.0. Descriptive analysis and inferential analysis were conducted. The result shows that all five variables are significantly related to the purchase intention towards AE. The product quality has the highest significant value (0.805) towards the purchase intention on AE, followed by logistic service quality, platform security, platform design quality, and perceived price and value. Implications, limitations, and recommendations were also discussed to assist the AE stakeholders in improving their AE. © 2023, Politeknik Negeri Padang. All rights reserved.","Agricultural E-commerce; Malaysia; purchase intention; technology adoption",{"$nulls":5},"Geran Penyelidikan Universiti Fundamental, (2020-0172-103-01); Universiti Pendidikan Sultan Idris; Universitas Telkom, Tel-U","Funding text 1: ACKNOWLEDGMENT This research was supported by Universiti Pendidikan Sultan Idris (UPSI) through Geran Penyelidikan Universiti Fundamental (GPUF) 2020 (2020-0172-103-01). Thanks also to the research and community service department at Telkom University.; Funding text 2: This research was supported by Universiti Pendidikan Sultan Idris (UPSI) through Geran Penyelidikan Universiti Fundamental (GPUF) 2020 (2020-0172-103-01). Thanks also to the research and community service department at Telkom University.","Ma W., Liu D., Research on E-commerce Development of Small and Medium-sized Enterprises Under the Background of Internet +, 2021 2nd International Conference on E-Commerce and Internet Technology (ECIT), pp. 181-184, (2021); Low M. P., sen Seah C., Cham T.-H., Teoh S. H., Digitalization adoption for digital economy: an examination of Malaysian small medium-sized enterprises through the technology–organization– environment framework, Business Process Management Journal, 28, 7, pp. 1473-1494, (2022); Reardon T., Et al., E‐commerce’s fast‐tracking diffusion and adaptation in developing countries, Appl Econ Perspect Policy, 43, 4, pp. 1243-1259, (2021); Wen Y., Kong L., Liu G., Big Data Analysis of e-Commerce Efficiency and Its Influencing Factors of Agricultural Products in China, Mobile Information Systems, (2021); Har L. L., Rashid U. K., te Chuan L., Sen S. C., Xia L. Y., Revolution of Retail Industry: From Perspective of Retail 1.0 to 4.0, Procedia Comput Sci, 200, pp. 1615-1625, (2022); Cheong Y. S., sen Seah C., Loh Y. X., Loh L. H., Artificial Intelligence (Ai) In The Food And Beverage Industry: Improves The Customer Experience, 2021 2nd International Conference on Artificial Intelligence and Data Sciences (AiDAS), pp. 1-6, (2021); Kalim R., Arshed N., Ahmad W., Aligning the Real Sector Production with Human Development: Exploring Role of Multi-sector Collaboration, Soc Indic Res, 157, 3, pp. 955-976, (2021); Secinaro S., Dal Mas F., Massaro M., Calandra D., Exploring agricultural entrepreneurship and new technologies: academic and practitioners’ views, British Food Journal, 124, 7, pp. 2096-2113, (2022); Xie X., New Farmer Identity: The Emergence of a Post‐Productivist Agricultural Regime in China, Sociol Ruralis, 61, 1, pp. 52-73, (2021); Zhao X., Deng S., Zhou Y., The impact of reference effects on online purchase intention of agricultural products, Internet Research, 27, 2, pp. 233-255, (2017); Xia Loh Y., Et al., The Factors and Challenges affecting Digital Economy in Malaysia, (2021); sen Seah C., Et al., The Significance of Technology in Digitalising Malaysia Industries, (2021); Warlina L., Siddiq F. F., Valentina T., Designing website for online business in the agricultural sector, J Phys Conf Ser, 1402, 6, (2019); sen Seah C., Loh Y. X., Wong Y. S., Jalaludin F. W., Loh L. H., The Influence of COVID-19 Pandemic on Malaysian E-Commerce Landscape: The case of Shopee and Lazada, 2022 6th International Conference on E-Commerce, E-Business and E-Government, pp. 215-221, (2022); Davis F., Technology Acceptance Model: Origins, Working Papers on Information Systems, (1989); Yap W. Z., Sia B. C., Goh H. L., Cham T. H., Exploring the Technology Acceptance of Wearable Medical Devices Among the Younger Generation in Malaysia: The Role of Cognitive and Social Factors, pp. 667-679, (2023); Kumar A., Anand A., Pandita U., Arjun K. P., A Dynamic Online Shopping Website for Incorporating Different Business in a Single Platform, pp. 23-29, (2022); Narayanan S., Gruber J., Liedtke G., Antoniou C., Purchase intention and actual purchase of cargo cycles: Influencing factors and policy insights, Transp Res Part A Policy Pract, 155, pp. 31-45, (2022); Sainis G., Kriemadis A., Kapnisi D., The Impact of Sustainability and Total Quality Management on SMEs Financial Performance Under Crisis Conditions, pp. 235-255, (2022); Novita D., Budiarti A. P., Perceived security, trust, privacy, and continuance intention of e-commerce customer, (2022); Kim Sung Tae, Lee Hong-Hee, Hwang Taewon, Park Byeonghwa, The Impact of Relationship Quality on Supply Chain Performance in Logistics Outsourcing, Journal of Managerial Issues, (2022); Bhattacharya C., Saurabh S., Sanyal M., Hudnurkar M., Warehousing and Facility Location in E-Commerce, pp. 227-253, (2022); Zeng Y., Jia F., Wan L., Guo H., E-commerce in agri-food sector: a systematic literature review, International Food and Agribusiness Management Review, 20, 4, pp. 439-460, (2017); He X., Hu Y., Understanding the role of emotions in consumer adoption of electric vehicles: the mediating effect of perceived value, Journal of Environmental Planning and Management, 65, 1, pp. 84-104, (2022); Salem S. F., Alanadoly A. B., What drives Malaysian online fashion shopping? The mediating role of perceived value, Journal of Global Fashion Marketing, 13, 1, pp. 75-89, (2022); Alidoosti M., Nowroozi A., Nickabadi A., Semantic web Racer: Dynamic security testing of the web application against race condition in the business layer, Expert Syst Appl, 195, (2022); Ariwibowo P., Djuhartono T., E-Commerce (Marketplace) for Marketing of MSME Products in Balekambang Village-East Jakarta, KANGMAS: Karya Ilmiah Pengabdian Masyarakat, 2, 1, pp. 64-76, (2021); Chen T.-C., Liang Y.-S., Ko P.-S., Huang J.-C., Optimization Model of Cross-Border E-commerce Payment Security by Blockchain Finance, Wirel Commun Mob Comput, 2021, pp. 1-9, (2021); Febiyola D., Tien A., Personal Data Safety On The Digital Shopping Platform (Consumer Protection Assessment), (2021); Gao Z., Kim H.-H., Sim J.-Y., Research on Influencing Factors of Consumer Behavior of Fresh Agricultural Products E-commerce in China, Journal of Digital Convergence, 18, 6, pp. 167-175, (2020); Gregar J., Research Design (Qualitative, Quantitative and Mixed Methods Approaches), (2017); Sekaran Uma, Bougie Roger, Research methods for business: A skill building approach, (2016); McCombes S., An introduction to sampling methods, Scribbr, (2021); Yin C. W., Arif E. E. M., Theam T. S., Sen S. C., Ying T. C. Y., Huei C. T., Determinants of the Sustainability of Tech Startup: Comparison Between Malaysia and China, pp. 567-579, (2023)","C.S. Seah; Faculty of Accountancy and Management, Universiti Tunku Abdul Rahman, Kajang, Bandar Sungai Long, Malaysia; email: seahcs@utar.edu.my",null,"Politeknik Negeri Padang",{"$nulls":5},2.5499904E7,null,null,null,"English","Int. J. Inform. Vis.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85171899035"]
["Huang Z.; Wu Z.; Cao B.","Huang, Zuqing (8226660500); Wu, Zhen (57896926100); Cao, Bingbing (36626995800)","8226660500; 57896926100; 36626995800","Operation strategies of capital-constrained small and medium-sized enterprises based on blockchain technology",2023.0,"Frontiers in Energy Research",11.0,null,1226813.0,null,null,null,0.0,"10.3389/fenrg.2023.1226813","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85171576016&doi=10.3389%2ffenrg.2023.1226813&partnerID=40&md5=9e0d8f59a7d2a91d89378e500d9640ea","School of Management, Guangzhou University, Guangzhou, China","Huang Z., School of Management, Guangzhou University, Guangzhou, China; Wu Z., School of Management, Guangzhou University, Guangzhou, China; Cao B., School of Management, Guangzhou University, Guangzhou, China","Introduction: In reality, due to the low credit rating of small and medium-sized enterprises (SMEs), it is difficult for them to obtain sufficient financing from a single financier. This paper considers a dual-channel supply chain consisting of a capital-constrained manufacturer, an e-commerce platform (ECP), a third-party logistics company (3PL) and consumers. There are two innovations in this paper: the manufacturer obtains sufficient production funds through hybrid financing of the ECP and 3PL, and consumers want to know product information and compare prices. The contributions of this paper are to investigate new applications of blockchain in both hybrid financing and meeting consumer information search needs. Methodology: We discuss the operation and pricing decisions of supply chain in two scenarios. These two scenarios are without adopting blockchain (N) and with adopting blockchain (B). Then, we compare the equilibrium decisions in two scenarios. Results: The results show that the supply chain will adopt blockchain when certain conditions are met. The initial adoption of blockchain is bad for the ECP and 3PL. Further, we find that with the increase of financing ratio, the optimal financing interest rate of the ECP decreases, while the optimal financing interest rate of the 3PL increases. Discussion: The numerical analysis shows that the adoption of blockchain can be more profitable when the cost of information search is high. Management insights: In order to achieve supply chain coordination, the manufacturer should give subsidies the ECP and 3PL. Copyright © 2023 Huang, Wu and Cao.","blockchain; capital constraint; hybrid financing; information search costs of consumers; supply chain pricing","Blockchain; Cost benefit analysis; Information retrieval; Outsourcing; Block-chain; Capital constraints; Commerce platforms; E- commerces; Hybrid financing; Information search; Information search cost of consumer; Search costs; Small and medium-sized enterprise; Supply chain pricing; Supply chains",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (71871206)","This work is supported by the National Natural Science Foundation of China (Grant No. 71871206). ","Almutairi K., Dehshiri S., Dehshiri S., Hoa A., Dhanraj J., Mostafaeipour A., Et al., Blockchain technology application challenges in renewable Energy supply chain management, Environ. Sci. Pollut. Res, 30, pp. 72041-72058, (2022); Cai G., Chen X., Xiao Z., The roles of bank and trade credits: theoretical analysis and empirical evidence, Prod. 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Appl, 52, (2022)","Z. Wu; School of Management, Guangzhou University, Guangzhou, China; email: 1466362974@qq.com",null,"Frontiers Media SA",{"$nulls":5},"2296598X",null,null,null,"English","Front. Energy Res.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85171576016"]
["Zhang X.; Wei Y.; Hashim Z.","Zhang, Xin (58704078400); Wei, Yanqiu (58704679600); Hashim, Zrdplwa (58703622300)","58704078400; 58704679600; 58703622300","Improvement of Swarm Intelligence Algorithm and Its Application in Logistics Network Routing",2023.0,"Journal of Network Intelligence",8.0,4.0,null,1077.0,1094.0,17.0,0.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85177471226&partnerID=40&md5=1c58c29406ecdd1bf38e879a8ce97904","School of Business Applied Technology College of Soochow University, Kunshan, 215325, China; Fan Li Business School Shaoxing Vocational Technical College, Shaoxing, 312000, China; Faculty of Engineering Computing Science, Swinburne University of Technology, Kuching, 93350, Malaysia","Zhang X., School of Business Applied Technology College of Soochow University, Kunshan, 215325, China; Wei Y., Fan Li Business School Shaoxing Vocational Technical College, Shaoxing, 312000, China; Hashim Z., Faculty of Engineering Computing Science, Swinburne University of Technology, Kuching, 93350, Malaysia","The Vehicle Routing Problem (VRP) is a key aspect of logistics network routing, and an excellent routing optimization strategy can effectively improve the service experience of users and reduce transportation costs. With the explosive growth of e-commerce, the logistics network routing system is faced with a huge number of demand points and customer-specified receiving time slots, which poses a huge challenge for routing optimization of large-scale delivery. To address the problems of high total cost and low effective vehicle utilisation in the logistics network routing system, this work introduces a new swarm intelligence method, the pigeon-inspired optimization (PIO), and improves it. Two improvement strategies are proposed to address the strengths and weaknesses of the PIO algorithm. Firstly, by combining the high swarm dispersion of the quantum evolutionary algorithm and the fast convergence of the PIO, the PIO method is upgraded by mixing the algorithms to achieve the effect of complementing each other’s strengths and improving the global exploration ability of the PIO algorithm; secondly, a Gaussian variation operator is added to the PIO algorithm to enhance its local exploitation capa-bility and prevent prematurity in order to retain the variety in future iterations. Each individual contains information on both client points and routes. The effectiveness of the improved pigeon flock intelligence optimisation algorithm is verified through test function simulations. The effectiveness and rationality of the improved PIO algorithm is verified in a case study based on the Solmon arithmetic example, which has some engineering application value. © 2023, Taiwan Ubiquitous Information CO LTD. All rights reserved.","Pigeon-inspired op-timization; Routing optimization; Swarm intelligence algorithms; Time windows","Evolutionary algorithms; Swarm intelligence; Vehicle routing; ITS applications; Logistics network; Optimisations; Optimization algorithms; Pigeon-inspired op-timization; Routing optimization; Routing system; Swarm intelligence algorithms; Time windows; Vehicle Routing Problems; Routing algorithms",{"$nulls":4},"Zhejiang Philosophy and Social Science, (2022SJYB1537, 21NDJC315YBM); Zhejiang Soft Science","Funding text 1: Funding Statement. This work supported by the project ”Zhejiang Soft Science,; Funding text 2: This work supported by the project ”Zhejiang Soft Science, NO.2022C35079”, ”Zhejiang Philosophy and Social Science, NO.21NDJC315YBM”, and ”Research of Philosophy and Social Sciences in Jiangsu Universities, NO.2022SJYB1537”.","Wu T.-Y., Shao A., Pan J.-S., CTOA: Toward a Chaotic-Based Tumbleweed Optimization Algorithm, Mathematics, 11, 10, (2023); Wu T.-Y., Li H., Chu S.-C., CPPE: An Improved Phasmatodea Population Evolution Algorithm with Chaotic Maps, Mathematics, 11, 9, (1977); Ma Y., Peng Y., Wu T.-Y., Transfer learning model for false positive reduction in lymph node detection via sparse coding and deep learning, Journal of Intelligent & Fuzzy Systems, 43, 2, pp. 2121-2133, (2022); Zhang F., Wu T.-Y., Wang Y., Xiong R., Ding G., Mei P., Liu L., Application of Quantum Genetic Optimization of LVQ Neural Network in Smart City Traffic Network Prediction, IEEE Access, 8, pp. 104555-104564, (2020); Dethloff J., Relation between vehicle routing problems: an insertion heuristic for the vehicle routing problem with simultaneous delivery and pick-up applied to the vehicle routing problem with backhauls, Journal of the Operational Research Society, 53, 1, pp. 115-118, (2002); Adacher L., Optimization Heuristics for Dynamic Vehicle Routing Problems, International Journal of Simulation Systems, Science & Technology, 11, pp. 139-147, (2019); Chen C.-M., Lv S., Ning J., Wu J. M.-T., A Genetic Algorithm for the Waitable Time-Varying Multi-Depot Green Vehicle Routing Problem, Symmetry, 15, 1, (2023); Shaik A. L. H. P., Manoharan M. K., Pani A. K., Avala R. R., Chen C.-M., Gaussian Mu-tation–Spider Monkey Optimization (GM-SMO) Model for Remote Sensing Scene Classification, Remote Sensing, 14, 24, (2022); Wu J. M.-T., Teng Q., Huda S., Chen Y.-C., Chen C.-M., A Privacy Frequent Itemsets Mining Framework for Collaboration in IoT Using Federated Learning, ACM Transactions on Sensor Networks, 19, 2, pp. 1-15, (2023); Sun L., Wang B., Robust Optimisation Approach for Vehicle Routing Problems with Uncer-tainty, Mathematical Problems in Engineering, 2015, pp. 1-8, (2015); Alzaqebah M., Jawarneh S., Sarim H. M., Abdullah S., Bees Algorithm for Vehicle Routing Problems with Time Windows, International Journal of Machine Learning and Computing, 8, 3, pp. 236-240, (2018); Bektas T., Laporte G., Vigo D., Integrated vehicle routing problems, Computers & Operations Research, 55, pp. 126-138, (2015); Laporte G., Nobert Y., Taillefer S., Solving a Family of Multi-Depot Vehicle Routing and Location-Routing Problems, Transportation Science, 22, 3, pp. 161-172, (1988); Martins L. C., Tordecilla R. D., Castaneda J., Juan A. A., Faulin J., Electric Vehicle Routing, Arc Routing, and Team Orienteering Problems in Sustainable Transportation, Energies, 14, 16, pp. 5131-5146, (2021); Erdogan G., An open source Spreadsheet Solver for Vehicle Routing Problems, Computers & Operations Research, 84, pp. 62-72, (2017); Derrac J., Garcia S., Molina D., Herrera F., A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms, Swarm and Evolutionary Computation, 1, 1, pp. 3-18, (2011); Duan H., Qiao P., Pigeon-inspired optimization: a new swarm intelligence optimizer for air robot path planning, International Journal of Intelligent Computing and Cybernetics, 7, 1, pp. 24-37, (2014); Baker B. M., Ayechew M. A., A genetic algorithm for the vehicle routing problem, Computers & Operations Research, 30, 5, pp. 787-800, (2003); Yusuf I., Baba Mohd. S., Iksan N., Applied Genetic Algorithm for Solving Rich VRP, Applied Artificial Intelligence, 28, 10, pp. 957-991, (2014); Yu V. F., Redi A. A. N. P., Hidayat Y. A., Wibowo O. J., A simulated annealing heuristic for the hybrid vehicle routing problem, Applied Soft Computing, 53, pp. 119-132, (2017); Theurich F., Fischer A., Scheithauer G., A branch-and-bound approach for a Vehicle Routing Problem with Customer Costs, EURO Journal on Computational Optimization, 9, (2021); Nguyen M. A., Dang G. T.-H., Ha M. H., Pham M.-T., The min-cost parallel drone scheduling vehicle routing problem, European Journal of Operational Research, 299, 3, pp. 910-930, (2022); Zhang S., Gajpal Y., Appadoo S. S., A meta-heuristic for capacitated green vehicle routing problem, Annals of Operations Research, 269, 1-2, pp. 753-771, (2017); Olgun B., Koc C., Altiparmak F., A hyper heuristic for the green vehicle routing problem with simultaneous pickup and delivery, Computers & Industrial Engineering, 153, (2021); Alazzam H., Sharieh A., Sabri K. E., A feature selection algorithm for intrusion detection system based on Pigeon Inspired Optimizer, Expert Systems with Applications, 148, (2020); Zhao J., Zhou R., Pigeon-inspired optimization applied to constrained gliding trajectories, Nonlinear Dynamics, 82, 4, pp. 1781-1795, (2015); Dou R., Duan H., Pigeon inspired optimization approach to model prediction control for un-manned air vehicles, Aircraft Engineering and Aerospace Technology, 88, 1, pp. 108-116, (2016); Duan H., Wang X., Echo State Networks with Orthogonal Pigeon-Inspired Optimization for Image Restoration, IEEE Transactions on Neural Networks and Learning Systems, 27, 11, pp. 2413-2425, (2016); Qiu H., Duan H., A multi-objective pigeon-inspired optimization approach to UAV distributed flocking among obstacles, Information Sciences, 509, pp. 515-529, (2020); Tian A.-Q., Chu S.-C., Pan J.-S., Cui H., A Compact Pigeon-Inspired Optimization for Max-imum Short-Term Generation Mode in Cascade Hydroelectric Power Station, Sustainability, 12, 3, pp. 767-779, (2020)","Y. Wei; Fan Li Business School Shaoxing Vocational Technical College, Shaoxing, 312000, China; email: weiyq@sxvtc.edu.cn",null,"Taiwan Ubiquitous Information CO LTD",{"$nulls":5},2.4148105E7,null,null,null,"English","J. Network Intell.","Article","Final",null,"Scopus","2-s2.0-85177471226"]
["Yi W.","Yi, Wei (58313892500)",5.83138925E10,"Logistics scheduling optimisation and allocation of intercultural communication trade under internet of things and edge computing",2023.0,"International Journal of Grid and Utility Computing",14.0,"2024-03-02",null,156.0,168.0,12.0,0.0,"10.1504/IJGUC.2023.131017","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85161824309&doi=10.1504%2fIJGUC.2023.131017&partnerID=40&md5=9cdc493edff82cd92506b61e921d60df","College of Business Administration, Zibo Vocational Institute, Shandong, Zibo, China","Yi W., College of Business Administration, Zibo Vocational Institute, Shandong, Zibo, China","This exploration aims to expand the functions of the traditional logistics management system based on the Internet of Things (IoT), continuously shorten the scheduling time and reduce the omission rate of data transmission. First, a logistics scheduling platform based on the IoT is designed. The platform integrates photography, positioning, laser scanning, scheduling and other functions. Then, a real-time data transmission scheduling model and optimisation algorithm based on IoT, e-commerce and deep reinforcement learning are proposed. They can improve the efficiency of data scheduling and processing on the platform, and ensure data integrity. Finally, the model is tested and evaluated. The results show that the scheduling time of the designed model is controlled within 10 s. The model scheduling data integrity rate is 91% on average. The Long Short-Term Memory model’s prediction accuracy is higher than that of other models. The optimisation algorithm designed can significantly reduce the cost and time of IoT edge computing. This exploration provides technical support for cross-cultural communication and reasonable scheduling and allocation in trade. Copyright © 2023 Inderscience Enterprises Ltd.","deep reinforcement learning; edge computing; internet of things; logistics scheduling; LSTM","Commerce; Data handling; Data transfer; Edge computing; Information management; Internet of things; Long short-term memory; Optimization; Data integrity; Deep reinforcement learning; Edge computing; Intercultural communication; Logistics scheduling; LSTM; Optimization algorithms; Reinforcement learnings; Scheduling optimization; Scheduling/allocation; Reinforcement learning",{"$nulls":6},"Ali M.S., Vecchio M., Pincheira M., Et al., Applications of blockchains in the internet of things: a comprehensive survey, IEEE Communications Surveys and Tutorials, 21, 2, pp. 1676-1717, (2018); Ceken C., Abdurahman D., Simulation modeling of an iot based cold chain logistics management system, Sakarya University Journal of Computer and Information Sciences, 2, 2, pp. 89-100, (2019); Chani-Cahuana J., Fager C., Eriksson T., Lower bound for the normalized mean square error in power amplifier linearization, IEEE Microwave and Wireless Components Letters, 28, 5, pp. 425-427, (2018); Chen L., He Y., Wang Q., Et al., Joint optimization of sensing, decision-making and motion-controlling for autonomous vehicles: a deep reinforcement learning approach, IEEE Transactions on Vehicular Technology, 71, 5, pp. 4642-4654, (2022); Dai H.N., Zheng Z., Zhang Y., Blockchain for internet of things: a survey, IEEE Internet of Things Journal, 6, 5, pp. 8076-8094, (2019); Feriani A., Ekram H., Single and multi-agent deep reinforcement learning for AI-enabled wireless networks: a tutorial, IEEE Communications Surveys and Tutorials, 23, pp. 1226-1252, (2021); Fischer T., Krauss C., Deep learning with long short-term memory networks for financial market predictions, European Journal of Operational Research, 270, 2, pp. 654-669, (2018); Guo J., Song B., Chen S., Yu F.R., Du X., Guizani M., Context-aware object detection for vehicular networks based on edge-cloud cooperation, IEEE Internet of Things Journal, 7, 7, pp. 5783-5791, (2019); Hassan N., Gillani S., Ahmed E., Et al., The role of edge computing in internet of things, IEEE Communications Magazine, 56, 11, pp. 110-115, (2018); Kim M., Kim J., Jung M., Et al., Towards monocular vision-based autonomous flight through deep reinforcement learning, Expert Systems with Applications, 198, (2022); Kosareva L., Evreeva O., Zakirova O., Formation of language competence: modern issues and strategies in the area of cross-cultural communication, Space and Culture, 7, 3, pp. 149-159, (2019); Le X.H., Ho H.V., Lee G., Et al., Application of long short-term memory (LSTM) neural network for flood forecasting, Water, 11, 7, (2019); Lee C.K.M., Lv Y., Ng K.K.H., Et al., Design and application of internet of things-based warehouse management system for smart logistics, International Journal of Production Research, 56, 8, pp. 2753-2768, (2018); Li G., Yang Y., Li S., Et al., Decision making of autonomous vehicles in lane change scenarios: deep reinforcement learning approaches with risk awareness, Transportation Research Part C: Emerging Technologies, 134, (2022); Pradhan A., Bisoy S.K., Kautish S., Et al., Intelligent decision-making of load balancing using deep reinforcement learning and parallel PSO in cloud environment, IEEE Access, 10, pp. 76939-76952, (2022); Qiu T., Zheng K., Han M., Et al., A data-emergency-aware scheduling scheme for internet of things in smart cities, IEEE Transactions on Industrial Informatics, 14, 5, pp. 2042-2051, (2017); Reddy N.R., Reddy P.C., Padmavathamma M., Efficient traffic engineering strategies for improving the performance of TCP friendly rate control protocol, Future Internet, 9, 4, (2017); Seyedi B., Fotohi R., NIASHPT: a novel intelligent agent-based strategy using hello packet table (HPT) function for trust internet of things, The Journal of Supercomputing, 76, 9, pp. 6917-6940, (2020); Shu H., Liu T., Mu X., Et al., Driving tasks transfer using deep reinforcement learning for decision-making of autonomous vehicles in unsignalized intersection, IEEE Transactions on Vehicular Technology, 71, 1, pp. 41-52, (2022); Singh R.K., Rani M., Bhagavathula A.S., Et al., Prediction of the COVID-19 pandemic for the top 15 affected countries: advanced autoregressive integrated moving average (ARIMA) model, JMIR Public Health and Surveillance, 6, 2, (2020); Singh R.P., Javaid M., Haleem A., Et al., Internet of things (IoT) applications to fight against COVID-19 pandemic, Diabetes and Metabolic Syndrome: Clinical Research and Reviews, 14, 4, pp. 521-524, (2020); Singh V., Chen S.S., Singhania M., Et al., How are reinforcement learning and deep learning algorithms used for big data based decision making in financial industries – a review and research agenda, International Journal of Information Management Data Insights, 2, 2, (2022); Suprayitno H., Ratnasari V., Saraswati N., Et al., Sample based trip length distribution quality based on X^2 and mean absolute error value, IPTEK: The Journal for Technology and Science, 29, 1, pp. 5-10, (2018); Teunissen E., Gravenhorst K., Dowrick C., Et al., Implementing guidelines and training initiatives to improve cross-cultural communication in primary care consultations: a qualitative participatory European study, International Journal for Equity in Health, 16, 1, pp. 1-12, (2017); Wang Q., Tang C., Deep reinforcement learning for transportation network combinatorial optimization: a survey, Knowledge-Based Systems, 233, (2021); Wang W., Lu Y., Analysis of the mean absolute error (MAE) and the root mean square error (RMSE) in assessing rounding model, IOP Conference Series: Materials Science and Engineering, 324, 1, (2018); Wang W., Guo J., Wang Z., Et al., Abnormal flow detection in industrial control network based on deep reinforcement learning, Applied Mathematics and Computation, 409, (2021); Wang X., Yan H., Li J., An improved supervised learning defect prediction model based on cat swarm algorithm, Journal of Physics: Conference Series, 1087, 2, (2018); Xiao Y., Jia Y., Liu C., Cheng X., Yu J., Lv W., Edge computing security: state of the art and challenges, Proceedings of the IEEE, 107, 8, pp. 1608-1631, (2019); Yu Y., Si X., Hu C., Et al., A review of recurrent neural networks: LSTM cells and network architectures, Neural Computation, 31, 7, pp. 1235-1270, (2019); Zaninovic P.A., Zaninovic V., Skender H.P., The effects of logistics performance on international trade: EU15 vs. CEMS, Economic Research-Ekonomska Istraživanja, 34, 1, pp. 1566-1582, (2021); Zhang Q., Zhu B., Design of the information management system of the public logistics in the port of the collection and transportation environment, Journal of Coastal Research, 93, SI, pp. 1034-1040, (2019)","W. Yi; College of Business Administration, Zibo Vocational Institute, Zibo, Shandong, China; email: ev_890627@163.com",null,"Inderscience Publishers",{"$nulls":5},"1741847X",null,null,null,"English","Int. J. Grid Util. Comput.","Article","Final",null,"Scopus","2-s2.0-85161824309"]
["Du J.; Wang X.; Ma B.; Zhou F.","Du, Jianhui (57219570906); Wang, Xu (55951735500); Ma, Biao (58202490900); Zhou, Fuli (57189093462)","57219570906; 55951735500; 58202490900; 57189093462","Two-echelon joint delivery capacitated vehicle routing problem considering carbon emissions of online shopping",2023.0,"International Journal of Shipping and Transport Logistics",16.0,"2024-04-03",null,372.0,398.0,26.0,1.0,"10.1504/IJSTL.2023.129879","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85153863540&doi=10.1504%2fIJSTL.2023.129879&partnerID=40&md5=f04dc949d08cbae2736aa9373ff0f4d3","College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing, 400044, China; Chongqing Laboratory of Logistics, Chongqing University, China; School of Economics and Management, Zhengzhou University of Light Industry, Zhengzhou, 450000, China","Du J., College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing, 400044, China; Wang X., College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing, 400044, China, Chongqing Laboratory of Logistics, Chongqing University, China; Ma B., College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing, 400044, China; Zhou F., School of Economics and Management, Zhengzhou University of Light Industry, Zhengzhou, 450000, China","Under the environment of a sharing economy and the demand for a low-carbon economy, parcel express companies are compelled to take a fresh view of joint delivery (JD) to enhance horizontal cooperation in the express industry. The purpose of this study is to design an energy-efficient collaborative joint delivery network for different express companies to fulfil the express delivery task. This paper proposes a two-echelon joint delivery capacitated vehicle routing problem (2E-JDCVRP) considering carbon emissions and two distinct fleets of vehicles to optimise the express delivery network in metropolitan areas, while explicitly considering resource sharing between different enterprises. In the 2E-JDCVRP model, the first echelon network requires vehicles at the depots of different express companies to transport the customer demands to satellites that are limitedly shared. The second echelon network concerns the routing of vehicles shared by the satellites to serve all the customers. The objective is to minimise the total cost of the joint distribution of a number of enterprises. A hybrid heuristic algorithm is designed to compute a novel 2E-JDCVRP model that shares idle resources. Computational experiments were conducted to test and verify the efficiency and effectiveness of the proposed 2E-JDCVRP model. Copyright © 2023 Inderscience Enterprises Ltd.","2E-CVRP; green logistics; joint delivery; low-carbon economy; two-echelon vehicle routing problem; urban logistics management",{"$nulls":5},"National Natural Science Foundation of China, NSFC, (52105507); National Key Research and Development Program of China, NKRDPC, (2020YFB1712900)","This study was supported National Key R&D Program of China (Grant number 2020YFB1712900) and National Natural Science Foundation of China (No. 52105507). The authors also appreciate the editor and the anonymous referees for their manuscript processing and remarkable comments.","Andelmin J., Bartolini E., An exact algorithm for the green vehicle routing problem, Transportation Science, 51, 4, pp. 1288-1303, (2017); Arena F., Malara G., Musolino G., Rindone C., Romolo A., Vitetta A., From green-energy to green-logistics: a pilot study in an Italian port area, Transportation Research Procedia, 30, 2018, pp. 111-118, (2018); Bae H., Moon I., Multi-depot vehicle routing problem with time windows considering delivery and installation vehicles, Applied Mathematical Modelling, 40, 13–14, pp. 6536-6549, (2016); Baldacci R., Mingozzi A., Roberti R., Calvo R.W., An exact algorithm for the two-echelon capacitated vehicle routing problem, Operations Research, 61, 2, pp. 298-314, (2013); Barth M., Boriboonsomsin K., Real-world carbon dioxide impacts of traffic congestion, Transportation Research Record: Journal of the Transportation Research Board, 2058, 1, pp. 163-171, (2008); 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Salhi S., Imran A., Wassan N.A., The multi-depot vehicle routing problem with heterogeneous vehicle fleet: formulation and a variable neighborhood search implementation, Computers & Operations Research, 52, pp. 315-325, (2014); Schrage L., Formulation and structure of more complex/realistic routing and scheduling problems, Networks, 11, 2, pp. 229-232, (1981); Spliet R., Dabia S., Van Woensel T., The time window assignment vehicle routing problem with time-dependent travel times, Transportation Science, 52, 2, pp. 261-276, (2018); State Post Bureau of the People’s Republic of 2018; Subramanian A., Drummond L.M.A., Bentes C., Ochi L.S., Farias R., A parallel heuristic for the vehicle routing problem with simultaneous pickup and delivery, Computers & Operations Research, 37, 11, pp. 1899-1911, (2010); Sumichras R.T., Markham I.S., A heuristic and lower bound for a multi-depot routing problem, Computers & Operations Research, 22, 10, pp. 1047-1056, (1995); Toth P., Vigo D., Vehicle Routing: Problems, Methods, and Applications, (2014); Truck Rental Quote; Various Energy Carbon Emission Coefficient, (2014); Zhao Q., Wang W., De Souza R., A heterogeneous fleet two-echelon capacitated location-routing model for joint delivery arising in city logistics, International Journal of Production Research, 56, 15, pp. 5062-5080, (2017); Zhou L., Wang X., Ni L., Lin Y., Location-routing problem with simultaneous home delivery and customer’s pickup for city distribution of online shopping purchases, Sustainability, 8, 8, pp. 828-848, (2016)","X. Wang; College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing, 400044, China; email: wx921@163.com",null,"Inderscience Publishers",{"$nulls":5},1.7566517E7,null,null,null,"English","Int. J. Shipp. Transp. Logist.","Article","Final",null,"Scopus","2-s2.0-85153863540"]
["Chao-Hung C.","Chao-Hung, Chiang (58725626700)",5.87256267E10,"On the Study of Key Critical Factors to be the Cross-Border E-Commerce Air Hub",2023.0,"Journal of Aeronautics, Astronautics and Aviation ",55.0,4.0,null,573.0,582.0,9.0,0.0,"10.6125/JoAAA.202312_55(4).06","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85178027523&doi=10.6125%2fJoAAA.202312_55%284%29.06&partnerID=40&md5=07ea6ad57f90113db0c28fae839b95b9","Department of Shipping and Transportation of National Penghu University of Science and Technology, No.300 Liu-he Rd., Magong, Penghu, 880, Taiwan","Chao-Hung C., Department of Shipping and Transportation of National Penghu University of Science and Technology, No.300 Liu-he Rd., Magong, Penghu, 880, Taiwan","Cross-border e-commerce is a burgeoning opportunity for the logistics industry, boosting airport appeal as air hubs. Therefore, the study aims to identify crucial factors for air cargo terminals to become cross-border ecommerce hubs, elevating airport competitiveness. The Grey Relation Analysis and Analytic Hierarchy Process will be adopted to evaluate the weight of each factor and construct a comprehensive framework comprising three facets and twelve factors. The results showed that the most important criterion was the airport facilities and operations (C1), followed by the crossborder e-commerce demands (C2) and the economic environment of the airport (C3). Additionally, the supply chain players of cross-border ecommerce involved in the airport area, such as express, integrators, e-retailer platforms, and so on (F14), are also the vital sub-critical in the economic environment of the airport (C3). These elements can be substantiated through practical operations. Overall, the primary significant contribution of this framework can be helpful for airports seeking to develop cross-border ecommerce cargoes or air hubs to enhance airport competitiveness as crossborder e-commerce air hubs in the logistics and air transportation field. © 2023 The Aeronautical and Astronautical Society of the Republic of China. All rights reserved.","Air cargo terminal; Competitiveness; Cross-border e-commerce","Air transportation; Competition; Electronic commerce; Supply chains; Air cargo terminal; Air hubs; Competitiveness; Critical factors; Cross-border; Cross-border e-commerce; E- commerces; Economic environment; Gray relation analysis; Logistics industry; Airports",{"$nulls":6},"Air Cargo News, (2020); Air Cargo Week, ACI: E-commerce helps fuel growth at world's top airports, (2018); Air Cargo World, Amazon's $100 million investment in Lakeland Airport is approved, (2019); Air Cargo World, Amazon's $100 million investment in Lakeland Airport is approved, (2019); Business Chief, Alibaba's Cainiao to lead $1.53bn investment in Hong Kong logistics hub, (2020); Chao CC, Lin JF, A Study on Improvement of Airlines' Cargo Service Quality, Journal of Aeronautics, Astronautics and Aviation, 45, 3, pp. 161-170, (2013); Cargo Forwarder Global, (2020); Cross-border magazine, DHL Express invests €123 million at Cologne-Bonn Airport, (2019); Air cargo and e-commerce enabling global trade, (2019); Air cargo and e-commerce enabling global trade, (2019); E-commerce creates new opportunity for air cargo, (2021); Value of Air Cargo E-Commerce, (2022); Market Watch, Amazon Global Air May Redevelop Air Cargo Facilities at Newark Liberty Airport; Customs transit channel for ecommerce goods starts functioning, (2021); Robinson A, The Evolution of e-Commerce Logistics, (2014); SATS unveils $21 million e-commerce air hub, (2017); Supply Chain Dive, Is Amazon Air making Cincinnati a supply chain hub for small business?, (2021); The Edge marke, Alibaba's investment in Malaysia is US$100m and counting, (2018); The Load Star, Alibaba e-com hub will give Kuala Lumpur Airport a massive cargo boost, (2020); The Loadstar, E-commerce here to stay, which means a 'fundamental redesign' of supply chains, (2020); Civil Aeronautics Administration 2018Annual Report, (2018); Deng JL, Introduction to grey system theory, The Journal of grey system, 1, 1, pp. 1-24, (1989); Harrison A, Kortuem21 S, Optimized Analysis based on the Characteristics of Cross-Border ECommerce Logistics Business, International Journal of Smart Business and Technology, 6, 2, pp. 1-10, (2018); Huang SL, Chang YC, Cross-border e-commerce: consumers' intention to shop on foreign websites, Internet Research, 29, 6, pp. 1256-1279, (2019); Kim TY, Dekker R, Heij C, Cross-border electronic commerce: Distance effects and express delivery in European Union markets, International Journal of Electronic Commerce, 21, 2, pp. 184-218, (2017); Li H, Study on Countermeasures of Promoting the Development of Cross-border E-commerce in Fujian Free Trade Zone, 2018 2nd International Conference on Education Science and Economic Management (ICESEM 2018), pp. 1055-1059, (2018); Saaty TL, The Analytic Hierarchy Process: Planning, Priority Setting, Resources Allocation, (1980); Saaty TL, Theory and applications of the analytic network process: decision making with benefits, opportunities, costs, and risks, (2005); Saaty TL, A Scaling Method for Priorities in Hierarchical Structures, Journal of Mathematical Psychology, 15, pp. 234-281, (1977); Sung TK, Choi YS, Supporting e-commerce: Korea Customs Service's strategy, World Custom Organization, 78, pp. 44-47, (2015); Amazon expands air cargo network, (2021); Vaidya OS, Kumar S, Analytic hierarchy process: An overview of applications, European Journal of operational research, 169, 1, pp. 1-29, (2006); Van Asch T, Dewulf W, Kupfer F, Cardenas I, Van de Voorde E, Cross-border e-commerce logistics- Strategic success factors for airports, Research in Transportation Economics, 79, (2020); Van Asch T, Dewulf W, Kupfer F, Cardenas I, Van de Voorde E, Cross-border e-commerce logistics- Strategic success factors for airports, Research in Transportation Economics, 79, (2020); Yang Y, Selection Method of Cross-Border e- Commerce Export Logistics Mode Based on Collaborative Filtering Algorithm, Journal of Mathematics, (2022); Yu B, Bai C, Zhou Y, Research on Regional Imbalance of Cross-Border E-Commerce -Take Fujian Free Trade Zone as an Example, The 18th International Conference on Electronic Business, (2018); Zhao C, Xiu C, Yu G, FedEx and UPS Network Structure and Accessibility Analysis Based on Complex Network Theory, Complexity, (2021)","C. Chao-Hung; Department of Shipping and Transportation of National Penghu University of Science and Technology, No.300 Liu-he Rd., Magong, Penghu, 880, Taiwan; email: irenechiang77@gms.npu.edu.tw",null,"The Aeronautical and Astronautical Society of the Republic of China",{"$nulls":5},1.990771E7,null,null,null,"English","J. Aero. Astron. Aviat.","Article","Final",null,"Scopus","2-s2.0-85178027523"]
["Yang J.; Liang K.; Liu H.; Shan M.; Zhou L.; Kong L.; Li X.","Yang, Jianglong (57222724504); Liang, Kaibo (57224205013); Liu, Huwei (57203283116); Shan, Man (58187857700); Zhou, Li (57164286500); Kong, Lingjie (58667121600); Li, Xiaolan (58667121700)","57222724504; 57224205013; 57203283116; 58187857700; 57164286500; 58667121600; 58667121700","Optimizing e-commerce warehousing through open dimension management in a three-dimensional bin packing system",2023.0,"PeerJ Computer Science",9.0,null,"e1613",null,null,null,1.0,"10.7717/PEERJ-CS.1613","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85175014850&doi=10.7717%2fPEERJ-CS.1613&partnerID=40&md5=e3b4ad505b43ded9df37ed304ec828ac","School of Information, Beijing Wuzi University, Beijing, China; School of Management and Engineering, Capital University of Economics and Business, Beijing, China","Yang J., School of Information, Beijing Wuzi University, Beijing, China; Liang K., School of Management and Engineering, Capital University of Economics and Business, Beijing, China; Liu H., School of Information, Beijing Wuzi University, Beijing, China; Shan M., School of Information, Beijing Wuzi University, Beijing, China; Zhou L., School of Information, Beijing Wuzi University, Beijing, China; Kong L., School of Information, Beijing Wuzi University, Beijing, China; Li X., School of Information, Beijing Wuzi University, Beijing, China","In the field of e-commerce warehousing, maximizing the utilization of packing bins is a fundamental goal for all major logistics enterprises. However, determining the appropriate size of packing bins poses a practical challenge for many logistics companies. Given the limited research on the open-size 3D bin packing problem as well as the high complexity and lengthy computation time of existing models, this study focuses on optimizing multiple-bin sizes within the e-commerce context. Building upon existing research, we propose a hybrid integer programming model, denoted as the three dimensional multiple option dimensional rectangular packing problem (3DMODRPP), to address the multiple-bin size 3D bin packing problem. Additionally, we leverage well-established hardware and software technologies to propose a 3D bin packing system capable of accommodating multiple bin types with open dimensions. To reduce the complexity of the model and the number of constraints, we introduce a novel assumption method for 0–1 integer variables in the overlap and rotation constraints. By applying this approach, we significantly streamline the computational complexity associated with the model calculations. Furthermore, we refine the dataset by developing a customized version based on the classical Three-Dimensional One-Size Dependent Rectangular Packing Problem (3D-ODRPP) dataset, leading to improved outcomes. Through comprehensive analysis of the research results, our model exhibits remarkable advancements in addressing the strong heterogeneous bin packing problem, the weak heterogeneous bin packing problem, the actual bin packing problem, and the bin packing problem with multiple bin types and open sizes. Specifically, it significantly reduces model complexity and computation time and increases space utilization. The system designed in this study paves the way for practical applications based on the proposed model, providing researchers with broader research prospects and directions to expand the scope of investigation in the field of 3D bin packing. Consequently, this system contributes to solving complex 3D packing problems, reducing space waste, and enhancing transportation efficiency. © 2023 Yang et al.","E-commerce storage; Hybrid integer programming model; Open dimension; Portfolio optimization; Three-dimensional bin packing system","Integer programming; Three dimensional computer graphics; Warehouses; Bin packing problem; E- commerces; E-commerce storage; Hybrid integer programming model; Integer programming models; Open dimension; Packing systems; Portfolio optimization; Three-dimensional bin packing system; Three-dimensional bin packings; Electronic commerce",{"$nulls":4},"Beijing Wuzi University Youth Research Fund; Graduate Science and Technology Innovation Project of Capital University of Economics and Business, (2023KJCX062); Beijing Wuzi University, BWU, (2023XJQN14); Capital University of Economics and Business, CUEB","Funding text 1: This project is supported by the Beijing Wuzi University Youth Research Fund Project Name: Research on Intelligent E-commerce Unmanned Warehouse Packing and Loading Optimization Strategy and Green Recycling Mode; Project Number: 2023XJQN14, and by the Graduate Science and Technology Innovation Project of Capital University of Economics and Business (Project Name: Research on Goods Sorting on Conveyor Belts Based on Binocular Vision; Grant Number: 2023KJCX062). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.; Funding text 2: The following grant information was disclosed by the authors: Beijing Wuzi University Youth Research Fund: 2023XJQN14. The Graduate Science and Technology Innovation Project of Capital University of Economics and Business: 2023KJCX062.","Agarwal M, Biswas S, Sarkar C, Paul S, Paul HS., Jampacker: an efficient and reliable robotic bin packing system for cuboid objects, IEEE Robotics and Automation Letters, 6, 2, pp. 319-326, (2020); Alonso MT, Alvarez-Valdes R, Iori M, Parreno F., Mathematical models for multi container loading problems with practical constraints, Computers & Industrial Engineering, 127, pp. 722-733, (2019); Araujo LJ, Ozcan E, Atkin JA, Baumers M., Analysis of irregular three-dimensional packing problems in additive manufacturing: a new taxonomy and dataset, International Journal of Production Research, 57, 18, pp. 5920-5934, (2019); Borges YG, Miyazawa FK, Schouery RC, Xavier EC., Exact algorithms for classconstrained packing problems, Computers & Industrial Engineering, 144, (2020); The State Post Office announced the operation of the postal industry in 2022, (2022); The national collection and delivery of express parcels during the Spring Festival holiday in 2023 exceeded 700 million pieces, (2023); Dell'Amico M, Furini F, Iori M., A branch-and-price algorithm for the temporal bin packing problem, Computers & Operations Research, 114, (2020); Di Puglia Pugliese L, Guerriero F, Calbi R., Solving a three-dimensional binpacking problem arising in the groupage process: application to the port of Gioia Tauro, A view of operations research applications in Italy, 2, pp. 29-40, (2019); Elhedhli S, Gzara F, Yildiz B., Three-dimensional bin packing and mixed-case palletization, INFORMS Journal on Optimization, 1, 4, pp. 323-352, (2019); Erbayrak S, Ozkir V, Yildirim UM., Multi-objective 3D bin packing problem with load balance and product family concerns, Computers & Industrial Engineering, 159, (2021); Gzara F, Elhedhli S, Yildiz BC., The pallet loading problem: three-dimensional bin packing with practical constraints, European Journal of Operational Research, 287, 3, pp. 1062-1074, (2020); Harrath Y., A three-stage layer-based heuristic to solve the 3D bin-packing problem under balancing constraint, Journal of King Saud University-Computer and Information Sciences, 34, 8, pp. 6425-6431, (2022); Hernandez-Hernandez P, Castillo-Garcia N., Optimization of route planning for the package delivery problem using fuzzy clustering, Technological and industrial applications associated with intelligent logistics. Lecture notes in intelligent transportation and infrastructure, pp. 239-252, (2021); Huang Y, Lai L, Li W, Wang H., A differential evolution algorithm with ternary search tree for solving the three-dimensional packing problem, Information Sciences, 606, pp. 440-452, (2022); Junqueira L, Morabito R., On solving three-dimensional open-dimension rectangular packing problems, Engineering Optimization, 49, 5, pp. 733-745, (2017); Kuccuk M, Yildiz ST., Constraint programming-based solution approaches for three-dimensional loading capacitated vehicle routing problems, Computers & Industrial Engineering, 171, (2022); Li Y, Chen M, Huo J., A hybrid adaptive large neighborhood search algorithm for the large-scale heterogeneous container loading problem, Expert Systems with Applications, 189, (2022); Li D, Gu Z, Wang Y, Ren C, Lau FC., One model packs thousands of items with recurrent conditional query learning, Knowledge-Based Systems, 235, (2022); Lin M-H, Tsai J-F, Chang S-C., A superior linearization method for signomial discrete functions in solving three-dimensional open-dimension rectangular packing problems, Engineering Optimization, 49, 5, pp. 746-761, (2017); 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Tole K, Moqa R, Zheng J, He K., A simulated annealing approach for the circle bin packing problem with rectangular items, Computers & Industrial Engineering, 176, (2023); Tresca G, Cavone G, Carli R, Cerviotti A, Dotoli M., Automating bin packing: a layer building matheuristics for cost effective logistics, IEEE Transactions on Automation Science and Engineering, 19, 3, pp. 1599-1613, (2022); Trivella A, Pisinger D., The load-balanced multi-dimensional bin-packing problem, Computers & Operations Research, 74, pp. 152-164, (2016); Tsai J-F, Li H-L., A global optimization method for packing problems, Engineering Optimization, 38, 6, pp. 687-700, (2006); Tsai J-F, Wang P-C, Lin M-H., A global optimization approach for solving three-dimensional open dimension rectangular packing problems, Optimization, 64, 12, pp. 2601-2618, (2015); Vieira MV, Ferreira F, Duque JC, Almeida RM., On the packing process in a shoe manufacturer, Journal of the Operational Research Society, 72, 4, pp. 853-864, (2021); Wang C., 3D bin packing of online constrained variable size sphere based on computer simulation technology, Advances in Computer, Signals and Systems, 6, 4, pp. 94-98, (2022); Yang S, Song S, Chu S, Song R, Cheng J, Li Y, Zhang W., Heuristics integrated deep reinforcement learning for online 3d bin packing, IEEE Transactions on Automation Science and Engineering, pp. 1-12, (2023); Zhao J, Zhou L, Wang F, Liu H, Yang J., Multibox three-dimensional packing problems for heterogeneous extrudable items, Mathematical Problems in Engineering, 2022, pp. 1-12, (2022); Zhao H, Zhu C, Xu X, Huang H, Xu K., Learning practically feasible policies for online 3D bin packing, Science China Information Sciences, 65, 1, (2022)","M. Shan; School of Information, Beijing Wuzi University, Beijing, China; email: 22311087100015@bwu.edu.cn",null,"PeerJ Inc.",{"$nulls":5},2.3765992E7,null,null,null,"English","PeerJ Comput. Sci.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85175014850"]
["Jauhar S.K.; Chakma B.R.; Kamble S.S.; Belhadi A.","Jauhar, Sunil Kumar (56022578600); Chakma, B. Ripon (58313992600); Kamble, Sachin S. (36864045000); Belhadi, Amine (57192378881)","56022578600; 58313992600; 36864045000; 57192378881","Digital transformation technologies to analyze product returns in the e-commerce industry",2023.0,"Journal of Enterprise Information Management",{"$nulls":6},0.0,"10.1108/JEIM-09-2022-0315","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85161946359&doi=10.1108%2fJEIM-09-2022-0315&partnerID=40&md5=a45ef266afb8d48b788e1cf0284f214c","Indian Institute of Management Kashipur, Kashipur, India; EDHEC Business School, Roubaix, France; Rabat Business School, International University of Rabat, Rabat, Morocco","Jauhar S.K., Indian Institute of Management Kashipur, Kashipur, India; Chakma B.R., Indian Institute of Management Kashipur, Kashipur, India; Kamble S.S., EDHEC Business School, Roubaix, France; Belhadi A., Rabat Business School, International University of Rabat, Rabat, Morocco","Purpose: As e-commerce has expanded rapidly, online shopping platforms have become widespread in India and throughout the world. Product return, which has a negative effect on the E-Commerce Industry's economic and ecological sustainability, is one of the E-Commerce Industry's greatest challenges in light of the substantial increase in online transactions. The authors have analyzed the purchasing patterns of the customers to better comprehend their product purchase and return patterns. Design/methodology/approach: The authors utilized digital transformation techniques-based recency, frequency and monetary models to better understand and segment potential customers in order to address personalized strategies to increase sales, and the authors performed seller clustering using k-means and hierarchical clustering to determine why some sellers have the most sales and what products they offer that entice customers to purchase. Findings: The authors discovered, through the application of digital transformation models to customer segmentation, that over 61.15% of consumers are likely to purchase, loyal customers and utilize firm service, whereas approximately 35% of customers have either stopped purchasing or have relatively low spending. To retain these consumer segments, special consideration and an enticing offer are required. As the authors dug deeper into the seller clustering, we discovered that the maximum number of clusters is six, while certain clusters indicate that prompt delivery of the goods plays a crucial role in customer feedback and high sales volume. Originality/value: This is one of the rare study that develops a seller segmentation strategy by utilizing digital transformation-based methods in order to achieve seller group division. © 2023, Emerald Publishing Limited.","Customer purchase behavior; Forecasting delivery time; Product returns in e-business; Reverse logistics",{"$nulls":7},"Aghdaie M.H., Tafreshi P.F., Using two-stage clustering and conjoint analysis for benefit segmentation of Iranian laptop buyers, Proceedings of the 3rd International Conference on Emergency Management and Management Sciences (ICEMMS 2012), pp. 816-819, (2012); Agrawal S., Singh R.K., Forecasting product returns and reverse logistics performance: structural equation modelling, Management of Environmental Quality, 31, 5, pp. 1223-1237, (2020); Agrawal S., Singh R.K., Murtaza Q., Prioritizing critical success factors for reverse logistics implementation using fuzzy-TOPSIS methodology, Journal of Industrial Engineering International, 12, 1, pp. 15-27, (2016); Akter S., Wamba S.F., Mariani M., Hani U., How to build an A.I. climate-driven service analytics capability for innovation and performance in industrial markets?, Industrial Marketing Management, 97, pp. 258-273, (2021); Akturk M.S., Ketzenberg M., Heim G.R., Assessing impacts of introducing ship-to-store service on sales and returns in omnichannel retailing: a data analytics study, Journal of Operations Management, 61, pp. 15-45, (2018); Ambilkar P., Dohale V., Gunasekaran A., Bilolikar V., Product returns management: a comprehensive review and future research agenda, International Journal of Production Research, 60, 12, pp. 3920-3944, (2022); Bailey K., Macroeconomic fluctuations, economic policy and the Jamaican stock market (1991-1999), Social and Economic Studies, 50, 3-4, pp. 173-207, (2001); Balakrishnan J., Dwivedi Y.K., Conversational commerce: entering the next stage of AI-powered digital assistants, Annals of Operations Research, pp. 1-35, (2021); Bali T.G., Zhou H., Risk, uncertainty, and expected returns, Journal of Financial and Quantitative Analysis, 51, 3, pp. 707-735, (2016); Bawack R.E., Wamba S.F., Carillo K.D.A., Akter S., Artificial intelligence in E-Commerce: a bibliometric study and literature review, Electronic Markets, 32, 1, pp. 1-42, (2022); Bhattarai A., Retail apocalypse'now: analysts say 75,000 more U.S. stores could be doomed, The Washington Post, (2019); Cao K., Choi T.M., Optimal trade‐in return policies: is it wise to be generous?, Production and Operations Management, 31, 3, pp. 1309-1331, (2022); Chen D., Sain S.L., Guo K., Data mining for the online retail Industry: a case study of RFM model-based customer segmentation using data mining, Journal of Database Marketing and Customer Strategy Management, 19, 3, pp. 197-208, (2012); Christy A.J., Umamakeswari A., Priyatharsini L., Neyaa A., RFM ranking–An effective approach to customer segmentation, Journal of King Saud University-Computer and Information Sciences, 33, 10, pp. 1251-1257, (2021); Dahabiyeh L., Constantinides P., Legitimating digital technologies in industry exchange fields: the case of digital signatures, Information and Organization, 32, 1, (2022); Dissanayake D., Singh M., Managing returns in e-business, Journal of Internet Commerce, 6, 2, pp. 35-49, (2008); Dogan O., Aycin E., Bulut Z., Customer segmentation by using RFM model and clustering methods: a case study in retail industry, International Journal of Contemporary Economics and Administrative Sciences, 8, 1, pp. 1-19, (2018); Duong Q.H., Zhou L., Meng M., Van Nguyen T., Ieromonachou P., Nguyen D.T., Understanding product returns: a systematic literature review using machine learning and bibliometric analysis, International Journal of Production Economics, 243, (2022); Dwivedi Y.K., Hughes L., Kar A.K., Baabdullah A.M., Grover P., Abbas R., Wade M., Climate change and COP26: are digital technologies and information management part of the problem or the solution? 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Kamble; EDHEC Business School, Roubaix, France; email: Sachin.kamble@edhec.edu",null,"Emerald Publishing",{"$nulls":5},1.7410398E7,null,null,null,"English","J. Enterp. Inf. Manage.","Article","Article in press",null,"Scopus","2-s2.0-85161946359"]
["Yang X.; Wang C.; He X.; Zhang H.; Xu G.","Yang, Xia (57224940958); Wang, Chenyang (58313648100); He, Xiaozheng (35210409000); Zhang, Hedi (58313049700); Xu, Guangming (55768535900)","57224940958; 58313648100; 35210409000; 58313049700; 55768535900","Location Optimization for Community Smart Parcel Lockers Based on Bilevel Programming",2023.0,"Journal of Advanced Transportation",2023.0,null,1998188.0,null,null,null,0.0,"10.1155/2023/1998188","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85161878563&doi=10.1155%2f2023%2f1998188&partnerID=40&md5=2c6040f1ee7972e8a426e6e2c9a5f79f","Key Laboratory of Road and Traffic Engineering, The Ministry of Education, Tongji University, Shanghai, China; Department of Civil & Environmental Engineering, Rensselaer Polytechnic Institute, New York, United States; School of Traffic and Transportation Engineering, Central South University, Changsha, China","Yang X., Key Laboratory of Road and Traffic Engineering, The Ministry of Education, Tongji University, Shanghai, China; Wang C., Key Laboratory of Road and Traffic Engineering, The Ministry of Education, Tongji University, Shanghai, China; He X., Department of Civil & Environmental Engineering, Rensselaer Polytechnic Institute, New York, United States; Zhang H., Key Laboratory of Road and Traffic Engineering, The Ministry of Education, Tongji University, Shanghai, China; Xu G., School of Traffic and Transportation Engineering, Central South University, Changsha, China","With the rapid development of e-commerce and the dramatic upsurge in direct-to-consumer deliveries, the last-mile problem has become increasingly apparent. With the distinct advantages of bringing economies of scale and providing 24/7 contactless self-service, smart parcel lockers play a critical role in solving the last-mile problem. However, due to a lack of planning, myopia expansion, and an ambiguous profit model, smart parcel locker suppliers in China have been suffering huge economic losses, restricting their further development. In the study, on the basis of an in-depth analysis of the cost elements and major revenue sources of smart parcel lockers, we propose a bilevel programming model to optimize the location of community smart parcel lockers with the upper-level model maximizing the profit of a third-party smart parcel locker supplier and the lower-level model maximizing user satisfaction. Then, a solution algorithm based on the genetic algorithm is proposed. Finally, some numerical experiments are carried out based on a medium-scale residential community in Jiading District, Shanghai. The sensitivity analyses conducted in this study reveal how the user satisfaction evaluation and the investment budget influence the expected profit. The modelling framework and numerical results can provide third-party smart parcel locker suppliers with significant theoretical support and practical guidance on planning the investment budget and optimizing the smart parcel locker locations to maximize their profit.  © 2023 Xia Yang et al.",null,"Budget control; Genetic algorithms; Investments; Location; Losses; Sensitivity analysis; Bi-level programming; Contact less; E- commerces; Economy of scale; Investment budget; Last mile problems; Level model; Location optimization; Profit model; Third parties; Profitability",{"$nulls":6},"Chevalier S., Global Retail E-commerce Sales 2014-2025, (2022); Goodman R., Whatever you call it, just don't think of last-mile logistics, last, Global Logistics & Supply Chain Strategies, 9, 12, pp. 46-51, (2005); Gevaers R., Van De Voorde E., Vanelslander T., Cost modelling and simulation of last-mile characteristics in an innovative B2C supply chain environment with implications on urban areas and cities, Procedia - Social and Behavioral Sciences, 125, pp. 398-411, (2014); 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Post B., Shanghai Postal Industry Development Statistics Bulletin, (2020); Yu J., China's Smart Parcel Locker Industry Development Status and Future Development Trend, Courier Business Increase to Accelerate the Popularity of Smart Parcel Locker Applications, (2020); Question B., What Is the Normal Ratio of Receiving and Sending Items at the Courier Station?, (2022); Fengchao, Home of Hive Box, (2022); Durand B., Gonzalez-Feliu J., Urban logistics and E-grocery: Have proximity delivery services a positive impact on shopping trips?, Procedia - Social and Behavioral Sciences, 39, pp. 510-520, (2012)","X. Yang; Key Laboratory of Road and Traffic Engineering, The Ministry of Education, Tongji University, Shanghai, China; email: xia_yang@tongji.edu.cn",null,"Hindawi Limited",{"$nulls":5},1976729.0,null,"JATRD",null,"English","J Adv Transp","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85161878563"]
["Maheswari S.U.; Dhenakaran S.S.","Maheswari, S. Uma (58382554000); Dhenakaran, S.S. (42261423200)","58382554000; 42261423200","Improved ensemble based deep learning approach for sarcastic opinion classification",2023.0,"Multimedia Tools and Applications",{"$nulls":6},0.0,"10.1007/s11042-023-16891-9","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85173977442&doi=10.1007%2fs11042-023-16891-9&partnerID=40&md5=fdc994ed48cad2d066621f3bc80aa801","Department of Computer Science, Alagappa University, Tamil Nadu, Karaikudi, India","Maheswari S.U., Department of Computer Science, Alagappa University, Tamil Nadu, Karaikudi, India; Dhenakaran S.S., Department of Computer Science, Alagappa University, Tamil Nadu, Karaikudi, India","Sarcastic tweets or reviews confuse the public those who interested to buy the products from online and prior know about the customer’s opinion about the products. E-Commerce business people also come across this problem to understand the customer’s sarcastic opinion. To remove this problem and to help the online customers also to help the business people to know the customer’s opinion is sarcastic or non sarcastic this research work carried out identify the sarcastic opinion. In many existing methods for detecting sarcastic statements commonly followed the part of speech (POS) -Tag, N-Gram methods for extract the features, as well as represented the features by Term Frequency-Inverse Document Frequency (TF-IDF) and binary methods, and for feature selection utilized chi squared, information gain methods. Other than the above mentioned methods authors didn’t use the features such as Likes count, ReTweet count, Replies count from Tweets. Outlier from the features can be identified and detected; typically the outlier removed features will provide the best performance. Not but least, many researchers followed imbalanced dataset for sarcastic detection. These limitations are identified by this proposed work. The novelty of this proposed work is followed the hybrid techniques such as agglomerative clustering method for outlier detection, and outlier removed dataset fed as input to stacked auto encoder (SAE), finally classification and prediction completed by Ensemble of Logistic Regression, Random forest and Bi-Directional Long Short Term Memory(Bi-LSTM). Existing work doesn’t follow the outlier removal method with Deep Learning (DL) method for sarcastic opinion detection. The proposed work is completed with aid of Natural Language Processing (NLP), Python Libraries and Tweets about E-Commerce Amazon products. Proposed model obtained 99.3% accuracy in sarcasm prediction, this outperforming existing sarcasm detection algorithm. This result suggests that the proposed model was successful in detecting and analyzing sarcastic sentiment. © 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.","Agglomerative; Bi-LSTM; Hybrid model; Natural Language Processing; Sarcastic sentiment; TF-IDF","Anomaly detection; Classification (of information); Cluster analysis; Computational linguistics; Electronic commerce; Feature Selection; Inverse problems; Learning systems; Logistic regression; Natural language processing systems; Python; Sales; Statistics; Text processing; Agglomerative; Bi-directional; Bi-directional long short term memory; Hybrid model; Language processing; Learning approach; Natural language processing; Natural languages; Sarcastic sentiment; Term frequencyinverse document frequency (TF-IDF); Long short-term memory",{"$nulls":6},"Prasanna M.S.M., Shaila S.G., Vadivel A., Polarity classification on twitter data for classifying sarcasm using clause pattern for sentiment analysis, Multimed Tools Appl, pp. 1-37, (2023); 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Banfield S.R., Richmond V.P., McCroskey J.C., The effect of teacher misbehaviors on teacher credibility and affect for the teacher, Commun Educ, 55, 1, pp. 63-72, (2006); Saha S., Yadav J., Ranjan P., Proposed approach for sarcasm detection in twitter, Indian J Sci Technol, 10, 25, pp. 1-8, (2017); Eke C.I., Norman A.A., Shuib L., Nweke H.F., Sarcasm identification in textual data: systematic review, research challenges and open directions, Artif Intell Rev, 53, pp. 4215-4258, (2020); Samonte M.J.C., Dollete C.J.T., Capanas P.M.M., Flores M.L.C., Soriano C.B., Sentence-level sarcasm detection in English and Filipino tweets, Proceedings of the 4Th International Conference on Industrial and Business Engineering, pp. 181-186, (2018); Eke C.I., Norman A.A., Shuib L., Nweke H.F., A survey of user profiling: state-of-the-art, challenges, and solutions, IEEE Access, 7, pp. 144907-144924, (2019); Kumar H.K., Harish B.S., Sarcasm classification: a novel approach by using content based feature selection method, Procedia Comput Sci, 143, pp. 378-386, (2018); Schifanella R., de Juan P., Tetreault J., Cao L., Detecting sarcasm in multimodal social platforms, Proceedings of the 24Th ACM International Conference on Multimedia, pp. 1136-1145, (2016); Dharwal P., Choudhury T., Mittal R., Kumar P., Automatic sarcasm detection using feature selection, 2017 3Rd International Conference on Applied and Theoretical Computing and Communication Technology (Icatcct), pp. 29-34, (2017); Suhaimin M.S.M., Hijazi M.H.A., Alfred R., Coenen F., Modified framework for sarcasm detection and classification in sentiment analysis, Indones J Electr Eng Comput Sci, 13, 3, pp. 1175-1183, (2019); Kumar A., Sangwan S.R., Arora A., Nayyar A., Abdel-Basset M., Sarcasm detection using soft attention-based bidirectional long short-term memory model with convolution network, IEEE access, 7, pp. 23319-23328, (2019); Karthik E., Sethukarasi T., Sarcastic user behavior classification and prediction from social media data using firebug swarm optimization-based long short-term memory, J Supercomputing, pp. 1-25, (2022); 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Tan Y.Y., Chow C.O., Kanesan J., Chuah J.H., Lim Y., Sentiment analysis and sarcasm detection using deep multi-task learning, Wirel Pers Commun, 129, 3, pp. 2213-2237, (2023); Kandasamy V., Trojovsky P., Machot F.A., Kyamakya K., Bacanin N., Askar S., Abouhawwash M., Sentimental analysis of COVID-19 related messages in social networks by involving an N-gram stacked autoencoder integrated in an ensemble learning scheme, Sensors, 21, 22, (2021); Ahmed K., Nadeem M.I., Li D., Zheng Z., Ghadi Y.Y., Assam M., Mohamed H.G., Exploiting stacked autoencoders for improved sentiment analysis, Appl Sci, 12, 23, (2022); Mehndiratta P., Soni D., Identification of sarcasm in textual data: a comparative study, J Data Inf Sci, 4, 4, pp. 56-83, (2019); Mehndiratta P., Sachdeva S., Soni D., Detection of sarcasm in text data using deep convolutional neural networks, Scalable Comput, 18, 3, pp. 219-228, (2017); Kumar A., Narapareddy V.T., Srikanth V.A., Malapati A., Neti L.B.M., Sarcasm detection using multi-head attention based bidirectional LSTM, IEEE Access, 8, pp. 6388-6397, (2020); Bark O., Grigoriadis A., Pettersson J.A.N., Risne V., Siitova A., Yang H., A Deep Learning Approach for Identifying Sarcasm in Text, (2017); Du Y., Li T., Pathan M.S., Teklehaimanot H.K., Yang Z., An effective sarcasm detection approach based on sentimental context and individual expression habits, Cognit Comput, pp. 1-13, (2022); Manohar M.Y., Kulkarni P., Improvement sarcasm analysis using NLP and corpus based approach, 2017 International Conference on Intelligent Computing and Control Systems (ICICCS), pp. 618-622, (2017); Pandey A.C., Seth S.R., Varshney M., Sarcasm detection of amazon alexa sample set, Advances in Signal Processing and Communication: Select Proceedings of ICSC 2018, pp. 559-564, (2019); Alita D., Priyanta S., Rokhman N., Analysis of emoticon and sarcasm effect on sentiment analysis of indonesian language on twitter, J Inf Syst Eng Bus Intell, 5, 2, pp. 100-109, (2019); Shrawankar U., Chandankhede C., Sarcasm detection for workplace stress management, Int J Synth Emot, 10, 2, pp. 1-17, (2019); Hiai S., Shimada K., Sarcasm detection using RNN with relation vector, Int J Data Warehous Min, 15, 4, pp. 66-78, (2019); Majumder N., Poria S., Peng H., Chhaya N., Cambria E., Gelbukh A., Sentiment and sarcasm classification with multitask learning, IEEE Intell Syst, 34, 3, pp. 38-43, (2019); Naz F., Kamran M., Mehmood W., Khan W., Alkatheiri M.S., Alghamdi A.S., Alshdadi A.A., Automatic identification of sarcasm in tweets and customer reviews, J Intell Fuzzy Syst, 37, 5, pp. 6815-6828, (2019); Jain D., Kumar A., Garg G., Sarcasm detection in mash-up language using soft-attention based bi-directional LSTM and feature-rich CNN, Appl Soft Comput, 91, (2020); Ren L., Xu B., Lin H., Liu X., Yang L., Sarcasm detection with sentiment semantics enhanced multi-level memory network, Neurocomputing, 401, pp. 320-326, (2020); Sundararajan K., Palanisamy A., Multi-rule based ensemble feature selection model for sarcasm type detection in twitter, Comput Intell Neurosci, (2020); Prasanna M.S.M., Shaila S.G., Vadivel A., Phrase-level sentence patterns for estimating positive and negative emotions using neuro-fuzzy model for information retrieval applications, Multimedia Tools Appl, 80, pp. 20151-20190, (2021); Pandey R., Kumar A., Singh J.P., Tripathi S., Hybrid attention-based long short-term memory network for sarcasm identification, Appl Soft Comput, 106, (2021); Pandey R., Singh J.P., BERT-LSTM model for sarcasm detection in code-mixed social media post, J Intell Inf Syst, 60, 1, pp. 235-254, (2023); Chawla V., Kapoor Y., A hybrid framework for bot detection on twitter: Fusing digital DNA with BERT, Multimedia Tools Appl, pp. 1-24, (2023); Demsar J., Statistical comparisons of classifiers over multiple data sets, J Mach Learn Res, 7, pp. 1-30, (2006); Dong X., Yu Z., Cao W., Shi Y., Ma Q., A survey on ensemble learning, Front Comp Sci, 14, pp. 241-258, (2020); Potamias R.A., Siolas G., Stafylopatis A.G., A transformer-based approach to irony and sarcasm detection, Neural Comput Appl, 32, pp. 17309-17320, (2020); Amelio A., Bonifazi G., Corradini E., Di Saverio S., Marchetti M., Ursino D., Virgili L., Defining a deep neural network ensemble for identifying fabric colors, Appl Soft Comput, 130, (2022); Zia T., Akram M.S., Nawaz M.S., Shahzad B., Abdullatif A.M., Mustafa R.U., Lali M.I., Identification of hatred speeches on Twitter, , the IRES International Conference, pp. 27-32, (2016); Ahuja R., Bansal S., Prakash S., Venkataraman K., Banga A., Comparative study of different sarcasm detection algorithms based on behavioral approach, Procedia Comput Sci, 143, pp. 411-418, (2018); Tungthamthiti P., Shirai K., Mohd M., Recognition of sarcasms in tweets based on concept level sentiment analysis and supervised learning approaches, Proceedings of the 28Th Pacific Asia Conference on Language, Information and Computing, pp. 404-413, (2014); Rajadesingan A., Zafarani R., Liu H., Sarcasm detection on twitter: A behavioral modeling approach, Proceedings of the Eighth ACM International Conference on Web Search and Data Mining, pp. 97-106, (2015)","S.U. Maheswari; Department of Computer Science, Alagappa University, Karaikudi, Tamil Nadu, India; email: 17umeshrani@gmail.com",null,"Springer",{"$nulls":5},1.3807501E7,null,"MTAPF",null,"English","Multimedia Tools Appl","Article","Article in press",null,"Scopus","2-s2.0-85173977442"]
["Sucena M.P.; Cury M.V.Q.","Sucena, Marcelo Prado (58503452200); Cury, Marcus Vinicius Quintella (58503452300)","58503452200; 58503452300","Artificial Intelligence Applied to Assess Perceptions of the Quality of E-Commerce Logistics: Case Study of Rio de Janeiro",2023.0,"Brazilian Business Review",20.0,4.0,{"$nulls":4},0.0,"10.15728/bbr.2021.1177.en","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85165572803&doi=10.15728%2fbbr.2021.1177.en&partnerID=40&md5=3103fac0fb8bc008dcbe0dfe913f5c4c","Fundação Getulio Vargas - FGV, RJ, Rio de Janeiro, Brazil","Sucena M.P., Fundação Getulio Vargas - FGV, RJ, Rio de Janeiro, Brazil; Cury M.V.Q., Fundação Getulio Vargas - FGV, RJ, Rio de Janeiro, Brazil","The COVID-19 pandemic imposed many market changes, driven partially by new consumer needs. In the electronic commerce field, changes occurred in parallel to an upsurge in demand, directly impacting logistics service quality. Within that context, this paper seeks a way of assessing the quality of e-commerce logistics, based on end-customer perceptions at the close of the purchasing cycle. The objective is thus to develop a mathematical model based on the artificial intelligence precepts that can interpret qualitative expressions captured through a questionnaire. Such values form partial indexes and the E-Commerce Logistics Quality Index (IQLE). After processing 180 records, it was noted that three of the seven analyzed attributes scored below 5.0, denoting some concern, but also opening up opportunities for improvement and the development of marketing solutions. © 2023 FUCAPE Business School. All rights reserved.","Artificial Intelligence; E-commerce; IQLE; Logistics",{"$nulls":7},"Almeida L. N., More J. D., Villela L.E., Avaliacao Fuzzy Da Percepcao De Empresarios Do Apl De Moda Intima De Nova Friburgo Sobre O Desempenho Em Relacao A Sustentabilidade Ambiental, (2010); Ballou R. H., Business Logistics Management, (1992); Bittencourt G., Inteligência Artificial, (2001); Boente A. N. P., More J. D., Cosenza H. J. S. R., Avaliacao Fuzzy da Qualidade de Produtos de Software numa Fundacao Publica Estadual, VI Simpósio De Excelência Em Gestão E Tecnologia, (2009); Cordeiro C. de O., Machado W.V., Carvalho R.L.S., Heloisa M.B.C., Dacol S., A Visao Do Cliente Para Melhoria Da Qualidade Do Sistema De Transporte Coletivo Por Onibus, XXV Encontro Nacional De Engenharia De Produção, (2005); Davidaviciene V., Meidute I., Quality of e-Logistics in e-Commerce: Consumer Perception, 10th International Conference - Liberec Economic Forum, (2011); De Albuquerque A. P. G., Aplicação Do Modelo De Kano Em Companhias Aéreas: Discussão Da Satisfação Dos Clientes, (2019); De Barros F. K., A Qualidade Em Serviços Logísticos Como Um Fator Relevante Para A Lealdade Do Cliente De Comércio Eletrônico, (2016); De Farias B. L. A., De Oliveira L.A.B., Aplicação Do Modelo De Kano Para Avaliação Da Qualidade Em Serviços Prestados Por Um Restaurante Na Cidade Do Assú/RN, (2020); Deming W. E., Qualidade: A Revolução Da Administração, (1990); Dias J. E. G., Atributos de qualidade: aplicacao do modelo de Kano em uma industria especializada na producao e comercializacao de artefatos de borracha localizada na regiao Sul do Brasil, (2018); 1 em cada 4 brasileiros querem manter compras online diárias após a pandemia, (2021); Fonseca M. J., Borges A. A., O Uso Da Pesquisa De Satisfacao Do Consumidor Como Instrumento De Politica Publica: O Potencial De Uso No Caso Do Transporte Coletivo De Porto Alegre, Revista Interdisciplinar De Marketing, 1, 3, pp. 38-50, (2002); Gajewska T., Zimon D., Kaczor G., Madzik P., The impact of the level of customer satisfaction on the quality of e-commerce services, International Journal of Productivity and Performance Management, 69, 4, pp. 666-684, (2020); Guimaraes Junior D. S., De Sant'anna C. H. M., Soares E. J. O., De Melo F. J. C., De Medeiros D. D., Measurement of logistics service quality of e-commerce, International Journal of Logistics Systems and Management, 37, 1, pp. 1-17, (2020); Hua W., Jing Z., An Empirical Study on E-commerce Logistics Service Quality and Customer Satisfaction, The Fourteen Wuhan International Conference on E-Business - WHICEB, (2015); Ibanez D. E. S., Problemas De Valores De Contorno Envolvendo Teoria De Conjuntos Fuzzy, (2018); Lara J. E., Afonso T., Elias R. K., Afonso B. P. D., Tissot-Lara T. A., Marketing E Logistica: Em Busca Da Satisfacao E Lealdade Do Consumidor De Compras On-Line, Revista Horizontes Interdisciplinares da Gestão, 4, 2, pp. 80-103, (2020); Lin Y., Luo J., Cai S., Ma S., Rong K., Exploring the service quality in the e-commerce context: a triadic view, Industrial Management & Data Systems, 116, 3, pp. 388-415, (2016); Lopes I. L., Santos F. A. O., Pinheiro C. A. M., Inteligência Artificial, (2014); Maia L. C., Souza Filho R. G., Oliveira M. T. T., Avaliacao Da Percepcao Dos Atributos De Compra Relacionados Ao E-Commerce: Um Levantamento De Dados, (2019); Marchesini M. M. P., Alcantara R. L. C., Conceituando O Servico Logistico E Seus Elementos, Revista de Ciência & Tecnologia, 17, 33, pp. 65-86, (2012); Montevechi J. A. B., Pinho A. F., De Incertezas Em Algoritmos De Programacao De Operacoes, (1999); Oliveira H. A., Lógica Difusa - Aspectos Práticos E Aplicações, (1999); Pereira B. A., Pereira J. M., A Importancia da Logistica no E-Commerce, (2020); Pinho A. F., Montevechi J.A.B., Pamplona E. de O., Aplicacao De Numeros Fuzzy Triangulares Em Analises De Investimentos Em Situacoes De Incerteza - Metodo Baseado Na Teoria Dos Jogos, (1997); Porto E. C., Machado C. E., Souza E. P. S., Pacha F. R., Kasaya G. R., Atributos Logisticos Na Satisfacao Do Consumidor De E-Commerce, Administração de Empresas em Revista, 1, 14, pp. 185-204, (2019); Prodanov C. C., Freitas E. C., Metodologia Do Trabalho Científico: Métodos E Técnicas Da Pesquisa E Do Trabalho Acadêmico, (2013); Rachmawati D. Z., Agus A.A., E-Service and Logistics Service Quality in E-Commerce, Study Case: Shopee Indonesia, 3rd International Conference on Computer and Informatics Engineering (IC2IE), (2020); Rodrigues M. O., Avaliação Da Qualidade Do Transporte Coletivo Da Cidade De São Carlos, (2006); Ross T. J., Fuzzy Logic With Engineering Applications, (1995); Sa I. I. R., More J. D., Fernandes C. A., Um Enfoque Fuzzy Para Avaliacao Das Acoes Empresariais Segundo A Percepcao Do Consumidor Area Gestao Social E Ambiental, IV Simpósio De Excelência Em Gestão E Tecnologia, (2007); Shaw I. S., Simoes M. G., Controle E Modelagem Fuzzy, (1999); Silva M. B., Um Estudo Sobre Operações Aritméticas Com Números Fuzzy, (2020); Soares R. A. D., De Oliveira L. A. B., Aplicação Do Modelo Kano Para Avaliação Da Qualidade Em Serviços De Veículos Motorizados, (2019); Sucena M. P., Andrade T. B., Proposta de BSC com Modelo Neuro-Fuzzy: Um Estudo de Caso, Revista Engenharia e Tecnologia, 13, 13, pp. 110-122, (2021); Tanaka K., An Introduction To Fuzzy Logic For Practical Applications, (1997); Tontini G., Zanchett R., Atributos de satisfacao e lealdade em servicos logisticos, Gestão & Produção, 17, 4, pp. 801-816, (2010); Vasic N., Kilibarda M., Andrejic M., Jovic S., Satisfaction is a function of users of logistics services in e-commerce, Technology Analysis & Strategic Management, 33, 7, pp. 813-828, (2021); Yang Y., Humphreys P., McIvor R., Business service quality in an e-commerce environment, Supply Chain Management, 11, 3, pp. 195-201, (2006)",null,null,"FUCAPE Business School",{"$nulls":5},1.8082386E7,null,null,null,"English","Brazilian Bus. Rev.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85165572803"]
["Nguyen Q.-T.; Patrix J.; Oulmakki O.; Ramirez-Rios D.G.; Verny J.","Nguyen, Quoc-Thông (57204874715); Patrix, Jérémy (56132097300); Oulmakki, Ouail (58186615300); Ramirez-Rios, Diana G. (35957015800); Verny, Jérôme (30767875200)","57204874715; 56132097300; 58186615300; 35957015800; 30767875200","Last mile delivery of grocery bins in Paris: costs from routing strategies with autonomous delivery vehicles",2023.0,"International Journal of Integrated Supply Management",16.0,3.0,null,207.0,228.0,21.0,1.0,"10.1504/IJISM.2023.132180","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85166430252&doi=10.1504%2fIJISM.2023.132180&partnerID=40&md5=62dd092c584322f85f66f52d0f10b12e","Sofft Industries, 29 Rue de Montribloud, Lyon, 69009, France; Opal Research, 4 Rampe Cauchoise, Rouen, 76000, France; Neoma Business School, 1 Rue du Marechal Juin, Mont-Saint-Aignan, 76130, France; State University of New York at Buffalo, Buffalo, 14260, NY, United States","Nguyen Q.-T., Sofft Industries, 29 Rue de Montribloud, Lyon, 69009, France; Patrix J., Opal Research, 4 Rampe Cauchoise, Rouen, 76000, France; Oulmakki O., Neoma Business School, 1 Rue du Marechal Juin, Mont-Saint-Aignan, 76130, France; Ramirez-Rios D.G., State University of New York at Buffalo, Buffalo, 14260, NY, United States; Verny J., Neoma Business School, 1 Rue du Marechal Juin, Mont-Saint-Aignan, 76130, France","Last mile delivery is a major component in the growth of e-commerce, especially in urban areas. The deliveries in dense cities cause serious issues such as pollution and congestion. In this study, we compare the financial costs of different last mile delivery strategies of grocery bins by autonomous delivery vehicles in a scenario in Paris. The optimal delivery routes are calculated with the real dataset in urban areas of Paris. We compared delivery costs by using: logistical costs associated with vehicles and human resources, location data with time window constraints for establishments in Paris, and delivery scenarios obtained by solving vehicle routing problems. This research considers an economic analysis of daily delivery to help fleet operators optimise their costs by using these autonomous delivery vehicles while reducing CO2 emissions and congestion in urban areas. Copyright © 2023 Inderscience Enterprises Ltd.","autonomous delivery vehicle; clustering; cost simulation; emission; last mile; urban delivery; vehicle routing problem",{"$nulls":7},"Akeb H., Moncef B., Durand B., Building a collaborative solution in dense urban city settings to enhance parcel delivery: an effective crowd model in Paris, Transportation Research Part E: Logistics and Transportation Review, 119, pp. 223-233, (2018); La livraison du dernier kilomètre – enjeux et tendances pour une logistique renouvelée, (2018); Archetti C., Bertazzi L., Recent challenges in routing and inventory routing: e-commerce and last-mile delivery, Networks, 77, 2, pp. 255-268, (2021); Arenas I.G.P., Sanchez A.G., Armando C., Solano L., Medina L.B.R., CVRPTW model applied to the collection of food donations, Proceedings of the International Conference on Industrial Engineering and Operations Management, pp. 1307-1314, (2017); Arthur D., Vassilvitskii S., k-means++: The Advantages of Careful Seeding, (2006); Bansal P., Kockelman K.M., Forecasting Americans’ long-term adoption of connected and autonomous vehicle technologies, Transportation Research Part A: Policy and Practice, 95, pp. 49-63, (2017); Bansal P., Kockelman K.M., Singh A., Assessing public opinions of and interest in new vehicle technologies: an Austin perspective, Transportation Research Part C: Emerging Technologies, 67, pp. 1-14, (2016); Bradley P.S., Bennett K.P., Demiriz A., Constrained K-Means Clustering, 20, (2000); Braekers K., Ramaekers K., Van Nieuwenhuyse I., The vehicle routing problem: state of the art classification and review, Computers & Industrial Engineering, 99, pp. 300-313, (2016); Buchegger A., Lassnig K., Loigge S., Muhlbacher C., Steinbauer G., An autonomous vehicle for parcel delivery in urban areas, 2018 21st International Conference on Intelligent Transportation Systems (ITSC), (2018); Cordeau J-F., The VRP with Time Windows, (2000); Dablanc L., Beziat A., Parking for Freight Vehicles in Dense Urban Centers – The Issue of Delivery Areas in Paris, (2015); Dablanc L., Rouhier J., Lazarevic N., Klauenberg J., Liu Z., Koning M., de Oliveira L.K., Combes F., Coulombel N., Gardrat M., Et al., CITYLAB Deliverable 2.1, Observatory of Strategic Developments Impacting Urban Logistics (2018 version), (2018); Dantzig G.B., Ramser J.H., The truck dispatching problem, Management Science, 6, 1, pp. 80-91, (1959); Doole M., Ellerbroek J., Hoekstra J., Estimation of traffic density from drone-based delivery in very low level urban airspace, Journal of Air Transport Management, 88, (2020); Durand B., Gonzalez-Feliu J., Urban logistics and e-grocery: have proximity delivery services a positive impact on shopping trips?, Procedia-Social and Behavioral Sciences, 39, pp. 510-520, (2012); Ehrler V.C., Schoder D., Seidel S., Challenges and perspectives for the use of electric vehicles for last mile logistics of grocery e-commerce – findings from case studies in Germany, Research in Transportation Economics, 87, (2021); Galati A., Crescimanno M., Vrontis D., Siggia D., Contribution to the sustainability challenges of the food-delivery sector: finding from the Deliveroo Italy case study, Sustainability, 12, 17, (2020); Gevaers R., van de Voorde E., Vanelslander T., Et al., Characteristics of innovations in last-mile logistics-using best practices, case studies and making the link with green and sustainable logistics, Association for European Transport and Contributors, 1, (2009); Gkartzonikas C., Gkritza K., What have we learned? A review of stated preference and choice studies on autonomous vehicles, Transportation Research Part C: Emerging Technologies, 98, pp. 323-337, (2019); Google’s OR-Tools, (2019); Heldt B., Matteis T., von Schmidt A., Heinrichs M., Cool but dirty food? – Estimating the impact of grocery home delivery on transport and CO2 emissions including cooling, Research in Transportation Economics, 87, (2021); Holguin-Veras J., Wang C., Browne M., Hodge S.D., Wojtowicz J., The new york city off-hour delivery project: lessons for city logistics, Procedia-Social and Behavioral Sciences, 125, pp. 36-48, (2014); Intercommunalité-métropole de métropole du grand paris (200054781), (2022); Jacobo-Cabrera M., Caballero-Morales S-O., Martinez-Flores J-L., Cano-Olivos P., Decision model for the pharmaceutical distribution of insulin, International Conference on Applied Informatics, pp. 75-89, (2018); K-Means-Constrained 0.7.1, (2022); Kapser S., Abdelrahman M., Acceptance of autonomous delivery vehicles for last-mile delivery in Germany – extending UTAUT2 with risk perceptions, Transportation Research Part C: Emerging Technologies, 111, pp. 210-225, (2020); Kapser S., Abdelrahman M., Bernecker T., Autonomous delivery vehicles to fight the spread of COVID-19 – how do men and women differ in their acceptance?, Transportation Research Part A: Policy and Practice, 148, pp. 183-198, (2021); Kilby P., Prosser P., Shaw P., Guided local search for the vehicle routing problem with time windows, Meta-Heuristics: Advances and Trends in Local Search Paradigms for Optimization, pp. 473-486, (1999); Kucukoglu I., Dewil R., Cattrysse D., The electric vehicle routing problem and its variations: a literature review, Computers & Industrial Engineering, 161, (2021); Kuo Y., Using simulated annealing to minimize fuel consumption for the time-dependent vehicle routing problem, Computers & Industrial Engineering, 59, 1, pp. 157-165, (2010); La circulation limitée à 30 km/h dans presque tout Paris dès fin août, (2021); Li B., Liu S., Tang J., Gaudiot J-L., Zhang L., Kong Q., Autonomous last-mile delivery vehicles in complex traffic environments, Computer, 53, 11, pp. 26-35, (2020); Lim S., Jin X., Srai J., Last-Mile Logistics Structures: A Literature Review and Design Guideline, (2016); Lin J., Zhou W., Wolfson O., Electric vehicle routing problem, Transportation Research Procedia, 12, pp. 508-521, (2016); List of Companies Registered in the French National Electronic Register of Road Transport Companies and in the Register of Freight Forwarders, (2021); Marcucci E., Gatta V., Le Pira M., Chao T., Li S., Bricks or clicks? consumer channel choice and its transport and environmental implications for the grocery market in norway, Cities, 110, (2021); Ministère de la Transition Écologique et de la Cohésion des Territoires (2020) 6 millions de véhicules utilitaires légers en circulation au 1er janvier 2020; Molina J.C., Eguia I., Racero J., Guerrero F., Multi-objective vehicle routing problem with cost and emission functions, Procedia-Social and Behavioral Sciences, 160, pp. 254-263, (2014); Niu Y., Yang Z., Chen P., Xiao J., Optimizing the green open vehicle routing problem with time windows by minimizing comprehensive routing cost, Journal of Cleaner Production, 171, pp. 962-971, (2018); Olsson J., Hellstrom D., Palsson H., Framework of last mile logistics research: a systematic review of the literature, Sustainability, 11, 24, (2019); Openrouteservice, (2022); Peng Y., Wang X., Research on a vehicle routing schedule to reduce fuel consumption, 2009 International Conference on Measuring Technology and Mechatronics Automation, IEEE, 3, pp. 825-827, (2009); Ramirez-Villamil A., Jaegler A., Montoya-Torres J.R., Sustainable local pickup and delivery: the case of Paris, Research in Transportation Business & Management, (2021); Reed S., Campbell A.M., Thomas B.W., The value of autonomous vehicles for last-mile deliveries in urban environments, Management Science, 68, 1, pp. 280-299, (2022); Schneider M., Stenger A., Goeke D., The electric vehicle-routing problem with time windows and recharging stations, Transportation Science, 48, 4, pp. 500-520, (2014); Tan S-Y., Yeh W-C., The vehicle routing problem: state-of-the-art classification and review, Applied Sciences, 11, 21, (2021); CO2 Emissions (Metric Tons per Capita), (2020); Toth P., Vigo D., Vehicle Routing: Problems, Methods, and Applications, (2014); cithy L by TwinwHeel, (2022); Voudouris C., Tsang E., Guided local search and its application to the traveling salesman problem, European Journal of Operational Research, 113, 2, pp. 469-499, (1999); Voudouris C., Tsang E.P., Alsheddy A., Guided local search, Handbook of Metaheuristics, pp. 321-361, (2010); Wygonik E., Goodchild A., Evaluating CO2 emissions, cost, and service quality trade-offs in an urban delivery system case study, IATSS Research, 35, 1, pp. 7-15, (2011); Xiao Y., Zhao Q., Kaku I., Xu Y., Development of a fuel consumption optimization model for the capacitated vehicle routing problem, Computers & Operations Research, 39, 7, pp. 1419-1431, (2012); Zhang H., Zhang Q., Ma L., Zhang Z., Liu Y., A hybrid ant colony optimization algorithm for a multi-objective vehicle routing problem with flexible time windows, Information Sciences, 490, pp. 166-190, (2019)","J. Verny; Neoma Business School, Mont-Saint-Aignan, 1 Rue du Marechal Juin, 76130, France; email: jerome.verny@neoma-bs.fr",null,"Inderscience Publishers",{"$nulls":5},1.477536E7,null,null,null,"English","Int. J. Integr. Supply Manage.","Article","Final",null,"Scopus","2-s2.0-85166430252"]
["Liu Z.","Liu, Zhixu (58629683800)",5.86296838E10,"Unlocking Consumer Choices in the Digital Economy: Exploring Factors Influencing Online and Offline Purchases in the Emerging Pet Food Market",2023.0,"Journal of the Knowledge Economy",{"$nulls":6},0.0,"10.1007/s13132-023-01490-8","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85172991811&doi=10.1007%2fs13132-023-01490-8&partnerID=40&md5=f7896015e5f70470ec5aebf8759b8f21","Southwestern University of Finance and Economics, Sichuan, Chengdu, 611130, China","Liu Z., Southwestern University of Finance and Economics, Sichuan, Chengdu, 611130, China","The study focuses on understanding consumer behavior in the pet food market, specifically the factors influencing choices between online and offline purchases. With the rise of the pet economy and digital transformation, this research addresses a gap in understanding the intricacies of consumer decision-making in this niche market. A comprehensive survey was conducted targeting pet owners and potential consumers to explore the impact of factors like price, logistics, service, and quality on consumer behavior. Key findings highlight the significant influence of price sensitivity on consumers’ choices. Competitive prices drove online purchases, with consumers often seeking cost-effective options. Convenience and efficiency also played pivotal roles; faster shipping and efficient logistics favored online shopping. Novel factors influencing online purchases included logistics packaging quality, charitable associations, trust in logistics companies, and genuine product guarantees. These findings underscore the need for businesses to focus on price competitiveness, convenience, trust-building, and customer-centric services to thrive in the digital pet food market. The research contributes theoretically by enhancing understanding of consumer behavior in the digital landscape and managerially by offering insights for businesses to optimize strategies. Future research directions include exploring technological impacts like AI and virtual reality, diving deeper into psychological mechanisms driving consumer responses, and broadening the sample to include diverse age groups. This study enriches the existing knowledge of consumer behavior, digital marketing, and e-commerce strategies, guiding businesses in the evolving pet economy. © 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.","Consumer behavior; Digital economy; E-commerce; Industry 4.0; Pet economy; Pet food market",{"$nulls":7},{"$cut":{"chars":21749,"head":"Abbate T., Codini A., Aquilani B., Vrontis D., From knowledge ecosystems to capabilities ecosystems: When open innovation digital platforms lead to value co-creation, Journal of the Knowledge Economy, 13, pp. 290-304, (2022); Agwu M.E., Onwuegbuzie H.N., Effects of international marketing environments on entrepreneurship development, Journal of Innovation and Entrepreneurship, 7, 1, (2018); Ahmad A.H., Fauzi R.U.A., Ditta A.S.A., Idris I., Yazid M.F.M., The role of perceived benefits and perceived risks towards the consumers’ purchase intention via Ecommerce: An evidence from Indonesia, Solid State Technology, 63, 2s, pp. 3257-3274, (2020); Akpan I.J., Udoh E.A.P., Adebisi B., Small business awareness and adoption of state-of-the-art technologies in emerging and developing markets, and lessons from the COVID-19 pandemic, Journal of Small Business & Entrepreneurship, 34, 2, pp. 123-140, (2022); Alexieva B., There must be some system in this madness: Metaphor, polysemy, and wordplay in a cognitive linguistics framework, Traductio, pp. 137-154, (2016); Alimamy S., Gnoth J., I want it my way! The effect of perceptions of personalization through augmented reality and online shopping on customer intentions to co-create value, Computers in Human Behavior, 128, (2022); Alzoubi H., Alshurideh M., Kurdi B., Akour I., Aziz R., Does BLE technology contribute towards improving marketing strategies, customers’ satisfaction and loyalty? The role of open innovation, International Journal of Data and Network Science, 6, 2, pp. 449-460, (2022); Aragunde-Kohl U., Gomez-Galan J., Lazaro-Perez C., Martinez-Lopez J.A., Interaction and emotional connection with pets: A descriptive analysis from Puerto Rico, Animals, 10, 11, (2020); Banton S., Baynham A., Pezzali J.G., von Massow M., Shoveller A.K., Grains on the brain: A survey of dog owner purchasing habits related to grain-free dry dog foods, PLoS ONE, 16, 5, (2021); Barcelos A.M., Kargas N., Packham C., Mills D.S., Understanding the impact of dog ownership on autistic adults: Implications for mental health and suicide prevention, Scientific Reports, 11, 1, (2021); Batrancea L.M., Nichita A., Cocis A.D., Financial performance and sustainable corporate reputation: Empirical evidence from the airline business, Sustainability, 14, 20, (2022); Bentler P.M., Chou C.P., Practical issues in structural modeling, Sociological Methods & Research, 16, 1, pp. 78-117, (1987); Bilal M., Mehmood T., Nadeem F., Barbosa A.M., de Souza R.L., Pompeu G.B., Iqbal H.M., Enzyme-assisted transformation of lignin-based food bio-residues into high-value products with a zero-waste theme: A review, Waste and Biomass Valorization, pp. 1-18, (2022); Brandes S., The meaning of American pet cemetery gravestones, Ethnology: An International Journal of Cultural and Social Anthropology, 48, 2, pp. 99-118, (2009); Bussolari C.J., Habarth J., Katz R., Phillips S., Carmack B., Packman W., The euthanasia decision-making process: A qualitative exploration of bereaved companion animal owners, Bereavement Care, 37, 3, pp. 101-108, (2018); Carayannis E.G., Dezi L., Gregori G., Calo E., Smart environments and techno-centric and human-centric innovations for Industry and Society 5.0: A quintuple helix innovation system view towards smart, sustainable, and inclusive solutions, Journal of the Knowledge Economy, 13, pp. 926-955, (2022); Castelo-Branco I., Cruz-Jesus F., Oliveira T., Assessing Industry 4.0 readiness in manufacturing: Evidence for the European Union, Computers in Industry, 107, pp. 22-32, (2019); Chavez R., Yu W., Feng M., Wiengarten F., The effect of customer-centric green supply chain management on operational performance and customer satisfaction, Business Strategy and the Environment, 25, 3, pp. 205-220, (2016); Chen Y., Lu Y., Bulysheva L., Kataev M.Y., Applications of blockchain in industry 4.0: A review, Information Systems Frontiers, pp. 1-15, (2022); Chen N., Sun D., Chen J., Digital transformation, labour share, and industrial heterogeneity, Journal of Innovation & Knowledge, 7, 2, (2022); Cho M., Bonn M.A., Li J."}},"Z. Liu; Southwestern University of Finance and Economics, Chengdu, Sichuan, 611130, China; email: zhixuliu2002@163.com",null,"Springer",{"$nulls":5},1.8687865E7,null,null,null,"English","J. Knowl. Econ.","Article","Article in press",null,"Scopus","2-s2.0-85172991811"]
["Chen W.; Perez C.","Chen, Wei (57013681700); Perez, Candido (58725462700)","57013681700; 58725462700","A Brief Analysis of Logistics Customer Service Management",2023.0,"LOGI - Scientific Journal on Transport and Logistics",14.0,1.0,null,309.0,316.0,7.0,0.0,"10.2478/logi-2023-0028","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85178058703&doi=10.2478%2flogi-2023-0028&partnerID=40&md5=6fa449d25afcdbc85365f6d2ca7ed626","Baguio University, Department of Graduate School, Baguio City, Philippines","Chen W., Baguio University, Department of Graduate School, Baguio City, Philippines; Perez C., Baguio University, Department of Graduate School, Baguio City, Philippines","The quality of customer service determines the survival and development of logistics enterprises. In the highly competitive e-commerce field, it is necessary to continuously improve the customer service management level of logistics enterprises, and the application of big data can optimize customer service management of logistics enterprises in e-commerce. This paper analyzes the reasons for the low customer service satisfaction with domestic logistics enterprises in China, and then puts forward how to optimize customer service management of logistics enterprises in ecommerce based on big data in order to effectively promote the service quality of logistics enterprises. This study is contributing to the body of knowledge by developing a comprehensive framework to solve various e-logistics problems. Hence, the current study is helpful for e-logistics companies to mitigate e-logistic customer satisfaction problems.  © 2023 Wei Chen et al., published by Sciendo.","Big data; customer service management; logistics enterprises; optimization measures",{"$nulls":7},"Dandan S., Xiaohui Q., Research on Decision Optimization of Terminal Distribution Mode of E-commerce Express Delivery Enterprises Based on Big Data, Science & Technology and Innovation, 21, pp. 51-52, (2020); Wenyuan Z., Research on Customer Service Strategy in Cross-border Ecommerce Marketing in the Internet Era-Comment on Cross-border E-commerce Marketing Practice, Science and Technology Management Research, 42, 5, (2022); Zheng Z., Synthesis of sociological methods-Taking questionnaire and interview as examples, Social Sciences, pp. 93-100, (2016); Jiahong L., Cost dilemma and challenges faced by e-commerce supply chain in the context of digital intelligence, Logistics Technology, 45, 20, pp. 121-124, (2022); Yao D., Research on the optimization of customer service scheme of logistics enterprises, Journal of Marketing Community, 48, pp. 146-147, (2020); Wenlian G., Talk about enterprise logistics Customer Service Management, Gansu Science and Technology, 38, 1, (2009); Ling T., Management study on the relationship between grassroots employees and customer satisfaction in the service industry, Shopping Mall Modernization, 6, (2010); Xiaozhou S., On the Innovation of Customer Service Management in Third Party Logistics Enterprises, Research on Communication Power, 3, 2, (2019); Yuhai M., Research on logistics customer service management, Value Engineering, 32, 12, pp. 152-153, (2013); Yuming Y., Research on the optimization of e-commerce logistics enterprise customer service management based on big data, Neijiang Technology, 40, 1, (2019); Lingling L., Construction of third party pharmaceutical logistics customer service management system of y company, Logistics Technology and Application, 27, 2, (2022); Xinhao S., Logistics customer service analysis based on marketing channels, China Logistics and Procurement, 23, (2021); Zhijun C., Research on the construction of customer service evaluation system of third-party logistics enterprises based on big data, Journal of Kunming Metallurgy College, 36, 3, (2020); Yao T., Research on Optimization of Customer Service Plans for Logistics Enterprises, The Marketing Community, 48, (2020); Xiaohai L., Research on Customer Service Performance Evaluation of Guangzhou Feiyunda Logistics Co., Ltd. Brand (Second Half of the Month), 12, (2015); Yunchang L., Shaoren W., Research on customer service innovation of third party logistics, Logistics Technology, 35, 1, (2016); Leilei C., Hongbai Y., Rener Z., Architecture and implementation of international logistics customer service platform, Software Guide, 14, 1, (2015); Xiuli L., Analysis of logistics customer service based on marketing channel, Modern Business, pp. 150-151, (2015); Jun C., Ling Y., Analysis on enterprise logistics customer service and improving competitiveness, Management and Science and Technology of Small and Mediumsized Enterprises (Last Ten Days), 11, (2014); Liu L., Analysis of Market Promotion and Customer Service Problems and Countermeasures for Logistics Enterprises, National Circulation Economy, 4, pp. 12-15, (2023)","W. Chen; Baguio University, Department of Graduate School, Baguio City, Philippines; email: 278811242@qq.com",null,"Sciendo",{"$nulls":5},2.3363037E7,null,null,null,"English","LOGI Sci. J. Trans. Log.","Article","Final","All Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85178058703"]
["Sun J.; Karia N.B.","Sun, Jie (57223222770); Karia, Noorliza Binti (8450919100)","57223222770; 8450919100","Innovative Approaches to Assessing Cold Chain Logistics in B2C E-Commerce Environments",2023.0,"Journal of the Knowledge Economy",{"$nulls":6},0.0,"10.1007/s13132-023-01669-z","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85180187656&doi=10.1007%2fs13132-023-01669-z&partnerID=40&md5=91f78dce99077dc2ba0980d91bba4269","School of Management, Universiti Sains Malaysia, Gelugor 11800, Penang, Malaysia; School of Cold Chain Logistics and Supply Chain, Shandong Institute of Commerce and Technology, Jinan, 250103, China","Sun J., School of Management, Universiti Sains Malaysia, Gelugor 11800, Penang, Malaysia, School of Cold Chain Logistics and Supply Chain, Shandong Institute of Commerce and Technology, Jinan, 250103, China; Karia N.B., School of Management, Universiti Sains Malaysia, Gelugor 11800, Penang, Malaysia","The rapid growth of the Chinese fresh e-commerce market in recent years has driven a significant increase in market revenue. However, the escalating prevalence of customer complaints and negative reviews attributed to logistics service quality issues has raised critical concerns. The quality of logistics services is a pivotal element within e-commerce transactions and holds immense importance for the development of enterprises. This study integrates a literature review and empirical research to delve into the logistics service quality of fresh e-commerce suppliers. It commences with synthesizing pertinent literature and concepts associated with the quality of new e-commerce logistics services, underpinned by a comprehensive review of cold chain logistics and logistics service quality theories. Building upon this foundation, a preliminary evaluation index system is formulated, encompassing dimensions like professionalism, reliability, immediacy, convenience, and security. A survey involving 552 consumers of cold chain fresh products is conducted through the employment of questionnaire methodology and SPSS technology. The survey results are subsequently utilized to evaluate, analyze, and optimize 45 specific indicators, thus enhancing the precision and effectiveness of the evaluation process. This research not only contributes to the theoretical understanding of fresh e-commerce logistics service quality but also provides a valuable empirical framework to enhance the logistics services in the fresh e-commerce sector. The study’s findings and recommendations aim to promote greater industry competence and customer satisfaction, thus fostering the sustained growth of the fresh e-commerce market in China. © 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.","Customer experience; Online grocery shopping; Performance evaluation metrics; Quality assurance in logistics; Refrigerated supply chain",{"$nulls":7},{"$cut":{"chars":16869,"head":"Abdul Rahman N.S.F., Karim N.H., Md Hanafiah R., Abdul Hamid S., Mohammed A., Decision analysis of warehouse productivity performance indicators to enhance logistics operational efficiency, International Journal of Productivity and Performance Management, 72, 4, pp. 962-985, (2023); Adamu H., Bello U., Yuguda A.U., Tafida U.I., Jalam A.M., Sabo A., Qamar M., Production processes, techno-economic and policy challenges of bioenergy production from fruit and vegetable wastes, Renewable and Sustainable Energy Reviews, 186, (2023); Akhmedova A., Manresa A., Escobar Rivera D., Bikfalvi A., Service quality in the sharing economy: A review and research agenda, International Journal of Consumer Studies, 45, 4, pp. 889-910, (2021); Al Hawaj A.Y., Buallay A.M., A worldwide sectorial analysis of sustainability reporting and its impact on firm performance, Journal of Sustainable Finance & Investment, 12, 1, pp. 62-86, (2022); Al Mashalah H., Hassini E., Gunasekaran A., Bhatt D., The impact of digital transformation on supply chains through e-commerce: Literature review and a conceptual framework, Transportation Research Part e: Logistics and Transportation Review, 165, (2022); Alkouh A., Keddar K.A., Alatefi S., Remanufacturing of industrial electronics: A case study from the GCC region, Electronics, 12, 9, (2023); Allioui H., Mourdi Y., Exploring the full potentials of IoT for better financial growth and stability: A comprehensive survey, Sensors, 23, 19, (2023); Altuntas S., Kansu S., An innovative and integrated approach based on SERVQUAL, QFD and FMEA for service quality improvement: A case study, Kybernetes, 49, 10, pp. 2419-2453, (2020); Arabelen G., Kaya H.T., Assessment of logistics service quality dimensions: A qualitative approach, Journal of Shipping and Trade, 6, 1, pp. 1-13, (2021); Aung M.M., Chang Y.S., Food traceability, Cold Chain Management, pp. 119-135, (2022); Aung M.M., Chang Y.S., The development of cold chain, Cold Chain Management, pp. 17-43, (2022); Balana B., Olanrewaju O., Ambler K., de Brauw A., Bloem J., Kadjo D., Abdoulaye T., Innovations and policy design for development for cross-value chain services (Logistics and financial services) (, 2, (2023); Barroso C., Carrion G.C., Roldan J.L., Applying maximum likelihood and PLS on different sample sizes: Studies on SERVQUAL model and employee behavior model, In Handbook of Partial Least Squares: Concepts, Methods and Applications, pp. 427-447, (2009); Bhattacharya A., Fayezi S., Ameliorating food loss and waste in the supply chain through multi-stakeholder collaboration, Industrial Marketing Management, 93, pp. 328-343, (2021); Buldeo Rai H., Dablanc L., Hunting for treasure: A systematic literature review on urban logistics and e-commerce data, Transport Reviews, 43, 2, pp. 204-233, (2023); Cano J.A., Londono-Pineda A.A., Campo E.A., Fernandez S.A., Sustainable business models of e-marketplaces: An analysis from the consumer perspective, Journal of Open Innovation: Technology, Market, and Complexity, 9, 3, (2023); Cetinkale Z., Aydin N., Health care logistics network design and analysis on pandemic outbreaks: Insights from COVID-19, Transportation Research Record, 2677, 4, pp. 674-703, (2023); Chen X., Xu X., Lu Z., Zhang W., Yang J., Hou Y., Zhang F., Carbon footprint of a typical pomelo production region in China based on farm survey data, Journal of Cleaner Production, 277, (2020); Chen Y.T., Value creation mechanism for innovative e-commerce logistics services for fresh agricultural products, Agricultural Economy, 7, pp. 131-132, (2018); Cui L., He S., Deng H., Wang X., Sustaining customer loyalty of fresh food e-tailers: An empirical study in China, Asia Pacific Journal of Marketing and Logistics, 35, 3, pp. 669-686, (2023); Dandan Z., Research on improving service quality of logistics enterprises based on KANO model, Proceedings of the 2019 4Th International Conference on Social Sciences and Economic Development (ICSSED 2019), (2019); Erceg A., Damoska-Sekulowska J., E-logistics and e-SCM: How to increase competitiveness, LogForum, 15, 1, pp. 155-169,"}},"N.B. Karia; School of Management, Universiti Sains Malaysia, Penang, Gelugor 11800, Malaysia; email: noorliza@usm.my",null,"Springer",{"$nulls":5},1.8687865E7,null,null,null,"English","J. Knowl. Econ.","Article","Article in press",null,"Scopus","2-s2.0-85180187656"]
["Oulmakki O.; Verny J.; Janjevic M.; Khalfalli M.","Oulmakki, Ouail (58186615300); Verny, Jerome (30767875200); Janjevic, Milena (55809152100); Khalfalli, Marwa (57204328357)","58186615300; 30767875200; 55809152100; 57204328357","Empirical study on consumer’s acceptance of delivery robots in France",2023.0,"International Journal of Logistics Research and Applications",{"$nulls":6},2.0,"10.1080/13675567.2023.2235290","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85165510736&doi=10.1080%2f13675567.2023.2235290&partnerID=40&md5=1d07825c23065e5a7731cef2c3382201","MOBIS Institute, Noema Business School, France; Massachusetts Institute of Technology, MIT, United States; HIGHFI, France","Oulmakki O., MOBIS Institute, Noema Business School, France; Verny J., MOBIS Institute, Noema Business School, France; Janjevic M., Massachusetts Institute of Technology, MIT, United States; Khalfalli M., HIGHFI, France","The growth of e-commerce has led to an increase in delivery options, and various innovations, such as autonomous delivery robots (ADRs) are being developed to meet the important challenges of the last mile. Currently, in the testing state, consumer acceptance remains relatively unknown. This study aims to identify the factors that affect the level of consumer acceptance of autonomous robotic delivery in urban areas using consumers’ current knowledge of this technology. To answer this question, the factors that negatively or positively influence user acceptance are first determined, and then the validity of the relationships between the factors and user acceptance are tested empirically. The results show that participants of this study are neutral to ADRs, which is reasonable for newly developed technology. Utilitarian factors, such as performance expectancy, are the most important for potential users, followed by social influence, trust in technology, and innovativeness. Price sensibility, perceived risk, and hedonic motivation do not seem to affect the acceptance of ADRs at the current stage of development, whereas effort expectancy shows an atypical negative effect on the behavioural intention to use this technology. However, this study has several limitations that need to be considered, notably the small sample size, which does not allow the generalisation of the results to the French population. © 2023 Informa UK Limited, trading as Taylor & Francis Group.","autonomous delivery robots; consumer acceptance; last-mile delivery; Technology",{"$nulls":7},{"$cut":{"chars":18131,"head":"Adell E., Acceptance of Driver Support Systems, Proceedings of the European conference on human centred design for intelligent transport systems, pp. 475-486, (2010); Adell E., Varhelyi A., Nilsson L., The Definition of Acceptance and Acceptability, Driver Acceptance of new Technology. 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Verny; MOBIS Institute, Noema Business School, France; email: jerome.verny@neoma-bs.fr",null,"Taylor and Francis Ltd.",{"$nulls":5},1.3675567E7,null,null,null,"English","Int. J. Logist. Res. Applic.","Article","Article in press",null,"Scopus","2-s2.0-85165510736"]
["Fan Z.; Wang Y.; Ying Z.","Fan, Zhigang (35195644800); Wang, Yansu (58106432400); Ying, Zhenzhou (58106486800)","35195644800; 58106432400; 58106486800","Empowerment of Cross-Border E-Commerce Platforms for Small and Medium-Sized Enterprises: Evidence from China",2023.0,"Journal of Business-to-Business Marketing",30.0,1.0,null,33.0,44.0,11.0,2.0,"10.1080/1051712X.2023.2175633","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85148301044&doi=10.1080%2f1051712X.2023.2175633&partnerID=40&md5=bb37e8155014d99d7d1f359f2fc24b88","Alibaba Business School, Hangzhou Normal University, Hangzhou, China; School of Management, Zhejiang University, Hangzhou, China","Fan Z., Alibaba Business School, Hangzhou Normal University, Hangzhou, China; Wang Y., Alibaba Business School, Hangzhou Normal University, Hangzhou, China; Ying Z., School of Management, Zhejiang University, Hangzhou, China","Purpose: Although the important role of cross-border e-commerce platforms in supporting small and medium-sized enterprises (SMEs) has continuously attracted scholarly attention, existing research overlooks the perspective of value chain processes, which have become more crucial when facing a dual shock from resurgent protectionist policies and the COVID-19 pandemic. This paper deconstructs strategic flexibility from the perspective of value chain processes and further explores the mechanism of cross-border e-commerce platform empowerment on SME export performance. Methodology/approach: A total of 425 SMEs participating in cross-border e-commerce platforms were used as the research sample for this empirical study, subsequently analyzing the multiple mediating effects. Findings: The results show that strategic flexibility plays a partial mediating role between the empowerment of e-commerce platforms and SMEs’ export performance. Specifically, market flexibility shows a relatively weak significance unlike delivery flexibility, which shows the strongest significance. Originality/Value: Following the overall perspective of the platform ecosystem, this study expands and integrates traditional empowerment theory and value chain theory into one analytical framework. It investigates the mechanism through which e-commerce platform empowerment influences a firm's export performance. Practical implications: Managerial suggestions for collaborative innovation of cross-border e-commerce platforms and SMEs in China are proposed. SMEs should actively integrate into platforms according to their business characteristics, fully exploit the platform resources, and focus on improving their responsiveness to export markets. © 2023 Taylor & Francis Group, LLC.","Cross-border e-commerce platform; platform empowerment; small and medium-sized enterprises (SMEs); strategic flexibility",{"$nulls":5},"Humanities and Social Sciences Research Planning Fund; Ministry of Ed-ucation, (20YJA630013); National Office for Philosophy and Social Sciences, NPOPSS, (21BGL119)","The work was supported by the Humanities and Social Sciences Research Planning Fund Project of the Ministry of Ed-ucation [20YJA630013]; National Social Science Fund of China [21BGL119].","Ahmed A., Bhatti S.H., Golgeci I., Arslan A., Digital platform capability and organizational agility of emerging market manufacturing SMEs: The mediating role of intellectual capital and the moderating role of environmental dynamism, Technological Forecasting and Social Change, 177, (2022); 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Fan Z., Liu Y., Wu X., The impact of network embedding and organizational learning collaboration on strategic flexibility, Science Research Management, 35, 12, pp. 112-119, (2014); Gawer A., Digital platforms’ boundaries: The interplay of firm scope, platform sides, and digital interfaces, Long Range Planning, 54, 5, (2021); Goldman S.P., van Herk H., Verhagen T., Weltevreden J.W., Strategic orientations and digital marketing tactics in cross-border e-commerce: Comparing developed and emerging markets, International Small Business Journal, 39, 4, pp. 350-371, (2021); Gress D.R., Kalafsky R.V., Staffing considerations and international trade fairs for Korean SME exporters and innovators, Asian Journal of Business Research, 12, 1, pp. 21-38, (2022); Helfat C., Peteraf M.A., The dynamic resource—based view: Capability lifecycles, Strategic Management Journal, 24, 10, pp. 997-1010, (2003); Helm R., Krinner S., Endres H., Exploring the role of product development capability for transforming marketing intelligence into firm performance, Journal of Business-To-Business Marketing, 27, 1, pp. 19-40, (2020); 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Li K.J., Li X., Advance selling in marketing channels, Journal of Marketing Research, (2022); Li X., Li K.J., Beating the algorithm: Consumer manipulation, personalized pricing, and big data management, Manufacturing & Service Operations Management, 25, 1, pp. 36-49, (2022); Li L., Su F., Zhang W., Mao J.Y., Digital transformation by SME entrepreneurs: A capability perspective, Information Systems Journal, 28, 6, pp. 1129-1157, (2018); Liu Y., Dong J., Mei L., Shen R., Digital innovation and performance of manufacturing firms: An affordance perspective, Technovation, 119, (2022); Liu Y., Dong J., Ying Y., Jiao H., Status and digital innovation: A middle-status conformity perspective, Technological Forecasting and Social Change, 168, (2021); Liu A., Osewe M., Shi Y., Zhen X., Wu Y., Cross-border E-commerce development and challenges in China: A systematic literature review, Journal of Theoretical and Applied Electronic Commerce Research, 17, 1, pp. 69-88, (2021); Liu Z., Sampaio P., Pishchulov G., Mehandjiev N., Cisneros-Cabrera S., Schirrmann A., Jiru F., Bnouhanna N., The architectural design and implementation of a digital platform for industry 4.0 SME collaboration, Computers in Industry, 138, (2022); 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Sucheta N., N V.K., Strategic schemas, strategic flexibility, and firm performance: The moderating role of industry clockspeed, Strategic Management Journal, 28, 3, pp. 243-270, (2007); Venables A.J., Geography and international inequalities: The impact of new technologies, Journal of Industry Competition & Trade, 1, 2, pp. 21-44, (2001); Verhoef P.C., Broekhuizen T., Bart Y., Bhattacharya A., Dong J.Q., Fabian N., Haenlein M., Digital transformation: A multidisciplinary reflection and research agenda, Journal of Business Research, 122, pp. 889-901, (2021); Wang C., Liu T., Wen D., Li D., Vladislav G., Zhu Y., The impact of international electronic commerce on export trade: Evidence from China, Journal of Theoretical and Applied Electronic Commerce Research, 16, 7, pp. 2579-2593, (2021); Wilden R., Gudergan S.P., The impact of dynamic capabilities on operational marketing and technological capabilities: Investigating the role of environmental turbulence, Journal of the Academy of Marketing Science, 43, 2, pp. 181-199, (2015); Worren N., Moore K., Cardona P., Modularity, strategic flexibility, and firm performance: A study of the home appliance industry, Strategic Management Journal, 23, 12, pp. 1123-1140, (2002); Wu P.J., Lin K.C., Unstructured big data analytics for retrieving e-commerce logistics knowledge, Telematics and Informatics, (2017); Wu A., Song D., Liu Y., Platform synergy and innovation speed of SMEs: The roles of organizational design and regional environment, Journal of Business Research, 149, pp. 38-53, (2022); Yang Z., Su C., Fam K.S., Dealing with institutional distances in international marketing channels: Governance strategies that engender legitimacy and efficiency, Journal of Marketing, 76, 3, pp. 41-55, (2012); Yang J., Zheng B., Yang L., Research on cross-border e-commerce evaluation index system based on factor analysis, Finance and Trade Economics, 9, pp. 94-102, (2014); Yan Z., Lu X., Chen Y., Wang K., Institutional distance, internationalization speed and cross-border e-commerce platform utilization, Management Decision, 61, 1, pp. 176-200, (2022); Ying Y., Wang S., Liu Y., Make bricks without straw: Eco-innovation for resource-constrained firms in emerging markets, Technovation, 114, (2022); Zhou K.Z., Wu F., Technological capability, strategic flexibility, and product innovation, Strategic Management Journal, 31, 5, pp. 547-561, (2010)","Z. Ying; School of Management, Zhejiang University, Hangzhou City, Zhejiang Province, China; email: yingzhenzhou2011@163.com",null,"Routledge",{"$nulls":5},"1051712X",null,null,null,"English","J. Bus. Bus. Mark.","Article","Final",null,"Scopus","2-s2.0-85148301044"]
["Liu S.; Hassini E.","Liu, Si (58639449300); Hassini, Elkafi (23394835700)","58639449300; 23394835700","Freight last mile delivery: a literature review",2023.0,"Transportation Planning and Technology",{"$nulls":6},0.0,"10.1080/03081060.2023.2268601","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85173641079&doi=10.1080%2f03081060.2023.2268601&partnerID=40&md5=d9ec35514f5071ed89b23a300c110dce","DeGroote School of Business, McMaster University, Hamilton, ON, Canada","Liu S., DeGroote School of Business, McMaster University, Hamilton, ON, Canada; Hassini E., DeGroote School of Business, McMaster University, Hamilton, ON, Canada","The authors review the literature on last mile delivery logistics within commercial and humanitarian supply chains from 2010 to the end of 2021. The scope of the last mile, including last mile logistics, last mile distribution, and last-mile mile delivery, is covered. A unifying terminology of the major concepts in this field and a bibliometric analysis are provided. Based on the analysis, the authors further classify and discuss the literature into three clusters: humanitarian relief, commercial logistics, and emerging technologies. Within each generated cluster, research gaps and current trends are identified. Future research directions are suggested based on this literature review. © 2023 Informa UK Limited, trading as Taylor & Francis Group.","E-commerce; Humanitarian logistics; Last mile delivery; Logistics","Electronic commerce; Bibliometrics analysis; Delivery logistics; Emerging technologies; Humanitarian logistics; Humanitarian relief; Last mile; Last mile delivery; Literature reviews; Logistics technologies; Research gaps; Supply chains",{"$nulls":6},{"$cut":{"chars":32614,"head":"Agatz N., Bouman P., Schmidt M., Optimization Approaches for the Traveling Salesman Problem with Drone, Transportation Science, 52, 4, pp. 965-981, (2018); Ahmadi-Javid A., Amiri E., Meskar M., A Profit-Maximization Location-Routing-Pricing Problem: A Branch-and-Price Algorithm, European Journal of Operational Research, 271, 3, pp. 866-881, (2018); Ahmadi M., Seifi A., Tootooni B., A Humanitarian Logistics Model for Disaster Relief Operation Considering Network Failure and Standard Relief Time: A Case Study on San Francisco District, Transportation Research Part E-Logistics and Transportation Review, 75, pp. 145-163, (2015); Aized T., Srai J.S., Hierarchical Modelling of Last Mile Logistic Distribution System, The International Journal of Advanced Manufacturing Technology, 70, pp. 1053-1061, (2014); Akeb H., Moncef B., Durand B., Building A Collaborative Solution in Dense Urban City Settings to Enhance Parcel Delivery: An Effective Crowd Model in Paris, Transportation Research Part E-Logistics and Transportation Review, 119, pp. 223-233, (2018); Alcaraz J.J., Caballero-Arnaldos L., Vales-Alonso J., Rich Vehicle Routing Problem with Last-Mile Outsourcing Decisions, Transportation Research Part E-Logistics and Transportation Review, 129, pp. 263-286, (2019); Allen J., Bektas T., Cherrett T., Bates O., Friday A., McLeod F., Piecyk M., Piotrowska M., Nguyen T., Wise S., The Scope for Pavement Porters: Addressing the Challenges of Last-Mile Parcel Delivery in London, Transportation Research Record, 2672, 9, pp. 184-193, (2018); Allen J., Piecyk M., Piotrowska M., McLeod F., Cherrett T., Ghali K., Nguyen T., Et al., Understanding the Impact of E-Commerce on Last-Mile Light Goods Vehicle Activity in Urban Areas: The Case of London, Transportation Research Part D: Transport and Environment, 61, pp. 325-338, (2018); Altay N., Green III W.G., OR/MS Research in Disaster Operations Management, European Journal of Operational Research, 175, 1, pp. 475-493, (2006); Archetti C., Bertazzi L., Recent Challenges in Routing and Inventory Routing: E-Commerce and Last-Mile Delivery, Networks, 77, 2, pp. 255-268, (2021); Aria M., Cuccurullo C., Bibliometrix: An R-Tool for Comprehensive Science Mapping Analysis, Journal of Informetrics, 11, 4, pp. 959-975, (2017); Arslan A.M., Agatz N., Kroon L., Zuidwijk R., Crowdsourced Delivery—A Dynamic Pickup and Delivery Problem with Ad hoc Drivers, Transportation Science, 53, 1, pp. 222-235, (2019); Aurambout J.-P., Gkoumas K., Ciuffo B., Last Mile Delivery by Drones: An Estimation of Viable Market Potential and Access to Citizens Across European Cities, European Transport Research Review, 11, 1, pp. 1-21, (2019); Balcik B., Beamon B.M., Facility Location in Humanitarian Relief, International Journal of Logistics-Research and Applications, 11, 2, pp. 101-121, (2008); Balcik B., Beamon B.M., Smilowitz K., Last Mile Distribution in Humanitarian Relief, Journal of Intelligent Transportation Systems, 12, 2, pp. 51-63, (2008); Banyai T., Real-time Decision Making in First Mile and Last Mile Logistics: How Smart Scheduling Affects Energy Efficiency of Hyperconnected Supply Chain Solutions, Energies, 11, 7, (2018); Barbarosoglu G., Arda Y., A Two-Stage Stochastic Programming Framework for Transportation Planning in Disaster Response, Journal of the Operational Research Society, 55, pp. 43-53, (2004); Behrend M., Meisel F., The Integration of Item-Sharing and Crowdshipping: Can Collaborative Consumption be Pushed by Delivering Through the Crowd?, Transportation Research Part B: Methodological, 111, pp. 227-243, (2018); Behrend M., Meisel F., Fagerholt K., Andersson H., An Exact Solution Method for the Capacitated Item-Sharing and Crowdshipping Problem, European Journal of Operational Research, 279, 2, pp. 589-604, (2019); Bensalem A., Kin V., A Bibliometric Analysis of Reverse Logistics from 1992 to 2017, Supply Chain Forum: An International Journal, 20, 1, pp. 15-28, (2019); Bergmann F.M., Wagner S.M., Winkenbach M., Integrating First-Mile Pickup and Last-Mile Delivery on Shared Vehicle Routes for Efficient Ur"}},"S. Liu; DeGroote School of Business, McMaster University, Hamilton, Canada; email: 1lius278@mcmaster.ca",null,"Routledge",{"$nulls":5},3081060.0,null,null,null,"English","Transp. Plann. Technol.","Article","Article in press",null,"Scopus","2-s2.0-85173641079"]
["Sfichi A.; Zadobrischi E.; Sfichi N.; Bădeliță M.; Medrihan M.","Sfichi, Adrian (58076684400); Zadobrischi, Eduard (57211514241); Sfichi, Narcisa (58077790800); Bădeliță, Marian (58077790900); Medrihan, Mihai (58077791000)","58076684400; 57211514241; 58077790800; 58077790900; 58077791000","Utility of Sharing Economy Principles in the Development of Applications Dedicated to Construction Cost Estimation",2023.0,"Future Internet",15.0,1.0,2.0,null,null,null,0.0,"10.3390/fi15010002","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85146775459&doi=10.3390%2ffi15010002&partnerID=40&md5=e418f35a6cae58b80402bc89ed5b5e1c","Glocal Soft S.R.L, Strada Fântâna Albă Nr. 1, Suceava, 720247, Romania; Department of Computers, Electronics and Automation, Faculty of Electrical Engineering and Computer Science, “Stefan cel Mare” University, No. 13 Str. Universitatii, Suceava, 720229, Romania; Department of Computer Science, Technical University of Cluj-Napoca, Gh. Baritiu St. 26-28, Cluj-Napoca, 400027, Romania","Sfichi A., Glocal Soft S.R.L, Strada Fântâna Albă Nr. 1, Suceava, 720247, Romania; Zadobrischi E., Department of Computers, Electronics and Automation, Faculty of Electrical Engineering and Computer Science, “Stefan cel Mare” University, No. 13 Str. Universitatii, Suceava, 720229, Romania, Department of Computer Science, Technical University of Cluj-Napoca, Gh. Baritiu St. 26-28, Cluj-Napoca, 400027, Romania; Sfichi N., Glocal Soft S.R.L, Strada Fântâna Albă Nr. 1, Suceava, 720247, Romania; Bădeliță M., Glocal Soft S.R.L, Strada Fântâna Albă Nr. 1, Suceava, 720247, Romania; Medrihan M., Glocal Soft S.R.L, Strada Fântâna Albă Nr. 1, Suceava, 720247, Romania","This research aims to highlight the importance and notoriety that an application based on heuristic algorithms can have in the field of e-commerce in the construction niche, guiding us on participatory economy principles. The expansion of e-commerce has shaped a new directive and increased the complexity of logistics, being a topical and critical issue. Users want the goods to be delivered in a timely manner to the specified address and to benefit from the fastest services. These aspects are challenging to achieve given that most operations fall within the remit of specialized staff within an e-commerce company. In this context, a service-type software application dedicated to the construction field was created to increase productivity, applying the principles of the sharing economy and developing intelligent algorithms. Coestim is a cloud-based SaaS solution for construction work estimations and a marketplace for construction-market-related products. Equipment rental, specialists, tracking the traceability process, generating a quote, and increasing productivity are essential components of the developed application. © 2022 by the authors.","business model; Coestim; e-commerce; estimate construction costs; online shopping experience; optimization; price competition; quality service; SaaS","Application programs; Competition; Cost benefit analysis; Cost estimating; Electronic commerce; Software as a service (SaaS); Business models; Coestim; Construction costs; E- commerces; Estimate construction cost; Online shopping; Online shopping experience; Optimisations; Price competition; Quality services; Saa; Heuristic algorithms",{"$nulls":4},"European Regional Development Fund, ERDF","Project co-financed by the European Regional Development Fund through the Operational Program Competitiveness 2014–2020 “Center for the transfer of knowledge to enterprises in the field of ICT—CENTRIC”. 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Manag, 18, pp. 423-434, (2000); Wang X.J., Huang J., The Relationships between Key Stakeholders’ Project Performance and Project Success: Perceptions of Chinese Supervising Engineers, Int. J. Proj. Manag, 24, pp. 253-260, (2006); Al-Jibouri S.H.S., Monitoring systems and their effectiveness for project cost control in construction, International journal of project management, 21, pp. 145-154, (2003); Matthess M., Kunkel S., Structural change and digitalization in developing countries: Conceptually linking the two transformations, Technol. Soc, 63, (2020); Moeuf A., Pellerin R., Lamouri S., Tamayo-Giraldo S., Barbaray R., The Industrial Management of SMEs in the Era of Industry 4.0, Int. J. Prod. 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Soc, 3, pp. 103-109, (2019); Krizhevsky A., Sutskever I., Hinton G.E., Imagenet classification with deep convolutional neural networks, Advances in Neural Information Processing Systems 25, pp. 1097-1105, (2012); Marsh H.W., Hau K.T., Confirmatory factor analysis: Strategies for small sample sizes, Statistical Strategies for Small Sample Research, pp. 252-284, (1999); Arabyat Y.A., AlZubi A.A., Aldebei D.M., Al-oqaily S.Z., An Efficient Method for Pricing Analysis Based on Neural Networks, Risks, 10, (2022); Haigh T., Cleve Moler: Mathematical Software Pioneer and Creator of Matlab, IEEE Ann. Hist. Comput, 30, pp. 87-91, (2008); Sfichi A., Sfichi N., Badelita M., Medrihan M., Zadobrischi E., Utility of Designing Intelligent Algorithms to Streamline E-Commerce Operations and Construction Costs Estimates by Applying Principles of Sharing Economy: Coestim, Telecom, 3, pp. 484-503, (2022)","A. Sfichi; Glocal Soft S.R.L, Suceava, Strada Fântâna Albă Nr. 1, 720247, Romania; email: adrian.sfichi@glocalsoft.net; E. Zadobrischi; Department of Computers, Electronics and Automation, Faculty of Electrical Engineering and Computer Science, “Stefan cel Mare” University, Suceava, No. 13 Str. Universitatii, 720229, Romania; email: eduard.zadobrischi@usm.ro",null,"MDPI",{"$nulls":5},1.9995903E7,null,null,null,"English","Future Internet","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85146775459"]
["Shao Q.; Lo H.-W.; Liou J.J.H.; Tzeng G.-H.","Shao, Qigan (57201635780); Lo, Huai-Wei (57201915019); Liou, James J. H. (35760371100); Tzeng, Gwo-Hshiung (7006940708)","57201635780; 57201915019; 35760371100; 7006940708","A Data-Driven Model to Construct the Influential Factors of Online Product Satisfaction",2023.0,"International Journal of Information Technology and Decision Making",{"$nulls":6},0.0,"10.1142/S021962202350013X","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85148760303&doi=10.1142%2fS021962202350013X&partnerID=40&md5=c87af29958dd52ef52d75e350963832d","School of Business and Management, XiaMen University of Technology, No. 600, Ligong Road, XiaMen, 361024, China; Department of Industrial Engineering and Management, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliou, Yunlin, 64002, Taiwan; Department of Industrial Engineering and Management, National Taipei University of Technology, Sec. 3, Zhongxiao E. Rd. 1, Taipei, 10608, Taiwan; Graduate Institute of Urban Planning, College of Public Affairs, National Taipei University, 151 University Road, Sanxia District, New Taipei City, 237303, Taiwan","Shao Q., School of Business and Management, XiaMen University of Technology, No. 600, Ligong Road, XiaMen, 361024, China; Lo H.-W., Department of Industrial Engineering and Management, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliou, Yunlin, 64002, Taiwan; Liou J.J.H., Department of Industrial Engineering and Management, National Taipei University of Technology, Sec. 3, Zhongxiao E. Rd. 1, Taipei, 10608, Taiwan; Tzeng G.-H., Graduate Institute of Urban Planning, College of Public Affairs, National Taipei University, 151 University Road, Sanxia District, New Taipei City, 237303, Taiwan","Online shopping is becoming more prevalent, with consumers turning to e-commerce platforms to search for information about the goods and services they need. Users will usually check other consumer reviews on the platform as a reference while shopping. Online retailers can collect and analyze these online reviews to monitor consumer opinions about product quality, logistics services, packaging and other attributes to provide an accurate basis for product improvement and service optimization. This paper applies the Latent Dirichlet Allocation (LDA) algorithm to extract the critical factors that affect consumer satisfaction. More than 30,000 reviews of seven kinds of 3C (computer, communication, and consumer electronic) product categories obtained by crawler technology are analyzed. Then, the DEMATEL-ANP (DANP) method is applied to the extracted framework to build a cause-and-effect diagram of 3C product satisfaction model. The innovative LDA-DANP hybrid model clarifies the causal influence of the evaluation dimensions for 3C products sold online. The results show that brand value is the most important dimension affecting consumer online product satisfaction. Appearance design, logistics awareness service and product performance also have a positive influence on perceived service and brand value. Finally, some management implications and practical suggestions are proposed.  © 2023 World Scientific Publishing Company.","DANP; LDA; online reviews; Product satisfaction; text mining","Electronic commerce; Statistics; Brand values; Data-driven model; DEMATEL; DEMATEL-ANP; Influential factors; Latent Dirichlet allocation; Online products; Online reviews; Product satisfaction; Text-mining; Product design",{"$nulls":6},"Fan X. J., Chai Z. L., Deng N. Q., Dong X. B., Adoption of augmented reality in online retailing and consumers' product attitude: A cognitive perspective, Journal of Retailing and Consumer Services, 53, (2020); Jeong B., Yoon J., Lee J. M., Social media mining for product planning: A product opportunity mining approach based on topic modeling and sentiment analysis, International Journal of Information Management, 48, pp. 280-290, (2019); Guo Y., Barnes S. J., Jia Q., Mining meaning from online ratings and reviews: Tourist satisfaction analysis using latent irichlet allocation, Tourism Management, 59, pp. 467-483, (2017); Mariani M. M., Nambisan S., Innovation analytics and digital innovation experimentation: The rise of research-driven online review platforms, Technological Forecasting and Social Change, 172, (2021); Abirami M., Askarunisa A., Feature based sentiment analysis for service reviews, Journal of Universal Computer Science, 22, pp. 650-670, (2016); Vo L. V., Le H. T. T., Le D. V., Phung M. T., Wang Y. H., Yang F. J., Customer satisfaction and corporate investment policies, Journal of Business Economics and Management, 18, pp. 202-223, (2017); Jung Y., Suh Y., Mining the voice of employees: A text mining approach to identifying and analyzing job satisfaction factors from online employee reviews, Decision Support System, 123, (2019); Shah M., Yan X. B., Qayyum A., Naqvi R. A., Shah S. J., Mining topic and sentiment dynamics in physician rating websites during the early wave of the COVID-19 pandemic: Machine learning approach, International Journal of Medical Informatics, 149, (2021); Chiu W. Y., Tzeng G. H., Li H. L., A new hybrid MCDM model combining DANP with VIKOR to improve e-store business, Knowledge-Based Systems, 37, pp. 48-61, (2013); Shaw N., Eschenbrenner B., Baier D., Online shopping continuance after COVID-19: A comparison of Canada, Germany and the United States, Journal of Retailing and Consumer Services, 69, (2022); Melovic B., ehovic D., Karad V., Dabic M., Cirovic D., Determinants of Millennials' behavior in online shopping-Implications on consumers' satisfaction and e-business development, Technology in Society, 65, (2021); Rita P., Oliveira T., Farisa A., The impact of e-service quality and customer satisfaction on customer behavior in online shopping, Heliyon, 5, (2019); Duarte P., Silva S. C., Ferreira M. B., How convenient is it? Delivering online shopping convenience to enhance customer satisfaction and encourage e-WOM, Journal of Retailing and Consumer Services, 44, pp. 161-169, (2018); Wu L., The antecedents of customer satisfaction and its link to complaint intentions in online shopping: An integration of justice, technology, and trust, International Journal of Information Management, 33, pp. 166-176, (2013); Liao C., Lin H. N., Luo M. M., Chea S., Factors in°uencing online shoppers' repurchase intentions: The roles of satisfaction and regret, Information & Management, 54, pp. 651-668, (2017); Eger L., Kom rkov L., Egerov D., Micik M., The e (r)ect of COVID-19 on consumer shopping behaviour: generational cohort perspective, Journal of Retailing and Consumer Services, 61, (2021); Miah M. R., Hossian A., Shikder R., Saha T., Neger M., Evaluating the impact of social media on online shopping behavior during COVID-19 pandemic: A Bangladeshi consumers' perspectives, Heliyon, 8, (2022); Zhang Z. K., Cheung C. M. K., Lee M. K. O., Examining the moderating e (r)ect of inconsistent reviews and its gender di (r)erences on consumers' online shopping decision, International Journal of Information Management, 34, pp. 89-98, (2014); Wei P. S., Lu H. P., An examination of the celebrity endorsements and online customer reviews in°uence female consumers' shopping behavior, Computers in Human Behavior, 29, pp. 193-201, (2013); K€onig T. M., Hein N., Nimsgern V., A value perspective on online review platforms: Profiling preference structures of online shops and traditional companies, Journal of Business Research, 145, pp. 387-401, (2022); Gulfraz M. B., Sufyan M., Mustak M., Salminen J., Srivastava D. K., Understanding the impact of online customers' shopping experience on online impulsive buying: A study on two leading E-commerce platforms, Journal of Retailing and Consumer Services, 68, (2022); Leong C. K., Lee Y. H., Mak W. K., Mining sentiments in SMS texts for teaching evaluation, Expert Systems with Applications, 39, pp. 2584-2589, (2012); Sezgen E., Mason K. J., Mayer R., Voice of airline passenger: A text mining approach to understand customer satisfaction, Journal of Air Transport Management, 77, pp. 65-74, (2019); Leem B. H., Eum S. W., Using text mining to measure mobile banking service quality, Industrial Management & Data Systems, 121, pp. 993-1007, (2021); Chen S. Q., Guo X. T., Wu T. S., Ju X. F., Exploring the Online Doctor-Patient Interaction on Patient Satisfaction Based on Text Mining and Empirical Analysis, Information Processing & Management, 57, (2020); Hong W., Zheng C. Y., Wu L. H., Pu X. J., Analyzing the Relationship between Consumer Satisfaction and Fresh E-Commerce Logistics Service Using Text Mining Techniques, Sustainability, 11, (2019); Jia S. S., Motivation and satisfaction of Chinese and U.S. tourists in restaurants: A crosscultural text mining of online reviews, Tourism Management, 78, (2020); Berezina A. Bilgihan, Cobanoglu C., Okumus F., Understanding satisfied and dissatis fied hotel customers: Text mining of online hotel reviews, Journal of Hospitality Marketing & Management, 25, pp. 1-24, (2015); Villeneuve H., O'Brien W., Listen to the guests: Text-mining Airbnb reviews to explore indoor environmental quality, Building and Environment, 169, (2019); Situmeang F., de Boer N., Zhan A., Looking beyond the stars: A description of text mining technique to extract latent dimensions from online product reviews, International Journal of Market Research, 62, pp. 192-215, (2020); Chen W. K., Riantama D., Chen L. S., Using a text mining approach to hear voices of customers from social media toward the fast-food restaurant industry, Sustainability, 13, (2021); Lucini F. R., Tonetto L. M., Fogliatto F. S., Anzanello M. J., Text mining approach to explore dimensions of airline customer satisfaction using online customer reviews, Journal of Air Transport Management, 83, (2020); Chatterjee S., Goyal D., Prakash A., Sharma J., Exploring healthcare/health-product ecommerce satisfaction: A text mining and machine learning application, Journal of Business Research, 131, pp. 815-825, (2020); Huang S. Q., Zhang J., Yang C. X., Gu Q., Li M., Wang W. Q., The interval grey QFD method for new product development: Integrate with LDA topic model to analyze online reviews, Engineering Applications of Artificial Intelligence, 114, (2022); Guo Y. X., Wang F. F., Xing C., Lu X. L., Ming multi-brand characteristics from online reviews for competitive analysis: A brand joint model using latent Dirichlet allocation, Electronic Commerce Research and Applications, 53, (2022); Wang W. X., Feng Y., Dai W. Q., Topic analysis of online reviews for two competitive products using latent Dirichlet allocation, Electronic Commerce Research and Applications, 29, pp. 142-156, (2018); Sim Y., Lee S. K., Sutherland L., The impact of latent topic valence of online reviews on purchase intension for the accommodation industry, TourismManagement Perspectives, 40, (2021); Polyzos E., Wang F., Twitter and market e±ciency in energy markets: Evidence using LDA clustered topic extraction, Energy Economics, 114, (2022); Xie R. B., Chu S. K. W., Chiu D. K. K., Wang Y. S., Exploring public response to COVID-19 on Weibo with LDA topic modeling and sentiment analysis, Data and Information Management, 5, pp. 86-99, (2021); Celik E., Bilisik O. N., Erdogan M., Gumus A. T., Baracli H., An integrated novel interval type-2 fuzzy MCDM method to improve customer satisfaction in public transportation for Istanbul, Transportation Research Part E: Logistics and Transportation Review, 58, pp. 28-51, (2013); Liang X. D., Chen T., Ye M., Lin H. R., Li Z., A hybrid fuzzy BWM-VIKOR MCDM to evaluate the service level of bike-sharing companies: A case study from Chengdu, China, Journal of Cleaner Production, 298, (2021); Akdag H., Kalayci T., Karag€oz S., Giz D., The evaluation of hospital service quality by fuzzy MCDM, Applied Soft Computing, 23, pp. 239-248, (2014); Liang D. C., Dai Z. Y., Wang M. W., Assessing customer satisfaction of O2O takeaway based on online reviews by integrating fuzzy comprehensive evaluation with AHP and probabilistic linguistic term sets, Applied Soft Computing, 98, (2021); Hsu C. C., Liou J. J. H., Chuang Y. C., Integrating DANP and modified grey relation theory for the selection of an outsourcing provider, Expert Systems with Applications, 40, pp. 2297-2304, (2013); Liou J. J. H., Building an e (r)ective system for carbon reduction management, Journal of Cleaner Production, 103, pp. 353-361, (2015); Chiu W. Y., Tzeng G. W., Li H. L., A new hybrid MCDM model combing DANP with VIKOR to improve e-store business, Knowledge-Based Systems, 58, pp. 2297-2304, (2013); Hsu C. C., Liou J. J. H., Chuang Y. C., Integrating DANP and modified grey relation theory for the selection of an outsourcing provider, Expert Systems with Applications, 40, pp. 2297-2304, (2013); Yoon P., Kim W. K., The behavioral TOPSIS, Expert Systems with Applications, 89, pp. 266-272, (2017); Gupta H., Barua M. K., Supplier selection among SMEs on the basis of their green innovation ability using BWM and fuzzy TOPSIS, Journal of Cleaner Production, 152, pp. 242-258, (2017); Li Z. H., Yang H., Xu J., How to adopt mass customization strategy: Understanding the role of consumers' perceived brand value, Computers & Industrial Engineering, 173, (2022); Suraksha G., David G., Pantea F., The impact of brand value on brand competitiveness, Journal of Business Research, 112, pp. 210-222, (2020); Lee S., Park Y., The classification and strategic management of services in e-commerce: Development of service taxonomy based on customer perception, Expert Systems with Applications, 36, pp. 9618-9624, (2009); Lee, Charles V., The impact of consumers' perceptions regarding the ethics of online retailers and promotional strategy on their repurchase intention, International Journal of Information Management, 57, (2021); Aindrila C., Ramesh S., James R. M., An empirical analysis of consumer-unfriendly E-commerce terms of service agreements: Implications for customer satisfaction and business survival, Electronic Commerce Research and Applications, 53, (2022); Yang Y., Xu D. L., Yang J. B., Chen Y. W., An evidential reasoning-based decision support system for handling customer complaints in mobile telecommunications, Knowledge-Based Systems, 162, pp. 202-210, (2018); Kim J., Lim C., Customer complaints monitoring with customer review data analytics: An integrated method of sentiment and statistical process control analyses, Advanced Engineering Informatics, 49, (2021); Liu Y., Gan W. X., Zhang Q., Decision-making mechanism of online retailer based on additional online comments of consumers, Journal of Retailing and Consumer Services, 59, (2021); Wu J., Wu T., Schlegelmilch B., Seize the day: How online retailers should respond to positive reviews, Journal of Interactive Marketing, 52, pp. 52-60, (2020); Kou G., Yi K., Xiao H., Peng R., Reliability of a Distributed Data Storage System Considering the External Impacts, IEEE Transactions on Reliability, (2022); Xiao H., Yi K., Peng R., Kou G., Reliability of a distributed computing system with performance sharing, IEEE Transactions on Reliability, 71, 4, pp. 1555-1566, (2021); Kou G., Olgu Akdeniz, H. Dinçer and S. Y 1/4ksel, Fintech investments in European banks: a hybrid IT2 fuzzy multidimensional decision-making approach, Financial Innovation, 7, 1, pp. 1-28, (2021); Lin C., Kou G., Peng Y., Alsaadi F. E., Aggregation of the nearest consistency matrices with the acceptable consensus in AHP-GDM, Annals of Operations Research, 316, pp. 179-195, (2022)","J.J.H. Liou; Department of Industrial Engineering and Management, National Taipei University of Technology, Taipei, Sec. 3, Zhongxiao E. Rd. 1, 10608, Taiwan; email: jamesjhliou@gmail.com",null,"World Scientific",{"$nulls":5},2196220.0,null,null,null,"English","Int. J. Inf. Technol. Decis. Mak.","Article","Article in press",null,"Scopus","2-s2.0-85148760303"]
["Dinya L.","Dinya, László (58548561000)",5.8548561E10,"Sustainable wine tourism in a non-sustainable world",2023.0,"Ecocycles",9.0,2.0,null,78.0,87.0,9.0,0.0,"10.19040/ecocycles.v9i2.299","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85168755637&doi=10.19040%2fecocycles.v9i2.299&partnerID=40&md5=b71d8a876b7db5a0a71b16b83be13cbd","Hungarian University of Agriculture and Life Science, Gödöllo, Gyöngyös, Hungary","Dinya L., Hungarian University of Agriculture and Life Science, Gödöllo, Gyöngyös, Hungary","The 6th Conference of Wine Tourism, organized by the United Nations World Tourism Organization (UNWTO, 20222), dealt with very important questions regarding the future of wine tourism. It is obvious that the rapidly growing and increasingly complex social-economic-political and natural environmental challenges create a chaotic (non-sustainable) world in which the answers are possible through broad cooperation and radical innovations. This is the case with tourism, including wine tourism, because they are especially sensitively affected by these changes. (UNWTO, 20221) All of this goes far beyond the boundaries of the sector but, at the same time, creates broad opportunities for the active participation of all members in the value chain of wine tourism. Innovation in services, marketing, and partnerships creates broad opportunities for all value chain members, including travelers, companies, authorities, and locals, at a critical moment when active participation and conscious thinking can increase the value of wine tourism destinations and their environment. Failure to do so can significantly weaken the competitiveness of a given region. The work aimed at this may be the key to the future development of wine tourism and the survival of those interested who have lived from it until now. The last two years have brought significant changes in wine tourism and transformed travel logistics, wine experience planning, and consumer behavior. In addition, a number of challenges that had already appeared came to the fore-from digitalization to sustainability and network cooperation. Sustainability increasingly determines the services offered by wineries and vineyards and travellers' attitudes and purchasing decisions. Meanwhile, digitization and e-commerce have become vital tools in the hands of producers, distributors, and wine tourism businesses, as well as destinations. Necessary innovations in experiences, marketing, and partnerships create broad engagement opportunities for all value chain members. We are focusing on looking for answers to the following research questions, especially taking into account the Hungarian specialities:. © 2023 The Author(s).","Innovations; Sustainability; Wine tourism",{"$nulls":7},"Bohn R., Stop Fighting Fires, Harvard Business Review, (2000); Dinya L., Bioenergetic integrations in agricultural restructuring. (in Hungarian) Gazdálkodás, pp. 1-11, (2006); Dinya L., Biomass-based energy production and sustainable energy management, Magyar Tudomány, 2010, 8, pp. 912-925, (2010); Dinya L., Changing climate, nature and innovation challenges. (in Hungarian) Gazdálkodás, pp. 557-565, (2011); Dinya L., Sustainable regional development and regional development strategies. (in Hungarian) A Falu, XXX, 1, pp. 5-19, (2015); Dinya L., Nemethy S., Sustainable Energy Management as a Prerequisite for Sustainable Tourism and Rural Development, Environmental, Economic, and Social Implications, 68, (2012); Dinya L., Peura P., Et al., Implementing sustainable energy strategies the RESGEN Procedure, International Journal of Sustainable Economy, 1, pp. 1-26, (2013); Dinya L., New Method of Regional Sustainable Energy Strategies, Ecocycles, 1, (2015); Dinya L., Et al., Oenotourism and conservation: A holistic approach to special interest tourism from a cultural heritage perspective the Azienda Agricola Model, Ecocycles, 2, 1, (2016); Tourism outlook 2023-Turbulence in the travel industry, The Economist, pp. 1-8, (2022); Garfield S., 100 Knowledge Management Specialties, 50 KM Components, and 50 Alternative Names for KM, (2016); Klausmann-Dinya A., Dinya L., Social marketing tasks in connection with complex sustainability challenges, Journal of Central European Green Innovation, 9, 2, (2021); Martinez M. A., What Is Problem Solving?, The Phi Delta Kappan, 79, 8, pp. 605-609, (1998); Mora D., Wine pairs with sustainability, UNWTO 6th Global Conference on Wine Tourism, (2022); Moller K. K., Halinen A., Business Relationships and Networks: Managerial Challenge of Network Era, Industrial Marketing Management, 28, pp. 413-427, (1999); Sekhniashvili G., Wine tourism destination competitiveness: The case of Georgia, Ecocycles, 6, (2020); Szolnoki G., Et al., SUSTAINABLE WINE TOURISM-A GLOBAL SURVEY, pp. 1-88, (2022); What's next? Wine tourism pairs with Innovation, Sustainability and Creativity, (2022); 1: SUSTAINABLE DEVELOPMENT IN TOURISM, (2022); UNWTO Tourism Market Intelligence and Competitiveness Department (2022)2: World Tourism Barometer, 20, 5; Our common future (Brundtland report), (1987)","L. Dinya; Hungarian University of Agriculture and Life Science, Gyöngyös, Gödöllo, Hungary; email: dinya.laszlo@uni-mate.hu",null,"European Ecocycles Society",{"$nulls":5},2.416214E7,null,null,null,"English","Ecocycles","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85168755637"]
["Wan Y.; Wang S.; Hu Y.; Xie Y.","Wan, Yanchun (36349022000); Wang, Shudi (58295948900); Hu, Yujun (58295450900); Xie, Yanyang (58295296400)","36349022000; 58295948900; 58295450900; 58295296400","Multiobjective optimization of the storage location allocation of a retail e-commerce picking zone in a picker-to-parts warehouse",2023.0,"Engineering Letters",31.0,2.0,null,481.0,493.0,12.0,3.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85160605669&partnerID=40&md5=21fa3487d9acbf1980f2c97c955af866","Department of Electronic Commerce, South China University of Technology, Guangzhou, 510006, China; Guangdong Planning Research & Design Academy of China Post Group, Guangzhou, 510610, China","Wan Y., Department of Electronic Commerce, South China University of Technology, Guangzhou, 510006, China; Wang S., Department of Electronic Commerce, South China University of Technology, Guangzhou, 510006, China; Hu Y., Guangdong Planning Research & Design Academy of China Post Group, Guangzhou, 510610, China; Xie Y., Department of Electronic Commerce, South China University of Technology, Guangzhou, 510006, China","Storage location allocation has a great impact on the utilization of warehouse storage space, operation efficiency, cost and employee well-being. We establish a multiobjective model of storage location optimization of manual picking zones by adopting the principle of high delivery frequency priority, correlation principle and large-capacity priority principle. The intelligent genetic algorithm and particle swarm optimization (IGPSO) algorithm are used to solve the multiobjective model. By using the 3.6 million-order data of a retail e-coinmerce warehouse to optimize the storage location allocation, the results show that the maximum and average response time, the actual order picking time, the daily walking distance of the picker and other key indicators achieve good results. This research can be well applied to optimize the storage location allocation of similar retail e-cominerce warehouses. © 2023, International Association of Engineers. All rights reserved.","IGPSO algorithm; Large volume priority; Multiobjective optimization; Picker-to-parts warehouse; Storage location allocation","Digital storage; Genetic algorithms; Location; Particle swarm optimization (PSO); Sales; Warehouses; Genetic algorithm and particle swarm optimizations; Intelligent genetic algorithm; Intelligent genetic algorithm and particle swarm optimization algorithm; Large volume priority; Large volumes; Location-allocation; Multi-objectives optimization; Particle swarm optimization algorithm; Picker-to-part warehouse; Storage location; Storage location allocation; Multiobjective optimization",{"$nulls":4},"Guangdong Philosophy and Social Science Planning Discipline Co-construction Project; Guangdong Postgraduate Education Innovation Plan Project, (2022ANLK006); Guangzhou Philosophy and Social Science Planning, (2021GZGJ42); State Council, (/08)","This work was supported by Guangdong Philosophy and Social Science Planning Discipline Co-construction Project (No.GD22XGL07), Guangzhou Philosophy and Social Science Planning (No.2021GZGJ42), Annual project of State-owned Assets Supervision and Administration Commission of the State Council (No.700004-22ZB0002/08). Guangdong Postgraduate Education Innovation Plan Project (No.2022ANLK006).","de Koster R., Le-Duc T., Roodbergen K. J., Design and control of warehouse order picking： A literature review, European Journal of Operational Research, 182, 2, pp. 481-501, (2007); Roodbergen K. J., de Koster R., Routing order pickers in a warehouse with a middle aisle, European Journal of Operational Research, 133, 1, pp. 32-43, (2001); Pang K., Chan H., Data mining-based algorithm for storage location assignment in a randomised warehouse, International Journal of Production Research, 55, 14, pp. 4035-4052, (2017); Larco J. A., de Koster R., Roodbergen K. J., Dul J., Managing warehouse efficiency and worker discomfort through enhanced storage assignment decisions, International Journal of Production Research, 55, 21, pp. 6407-6422, (2017); Kubler P., Glock C. H., Bauernhansl T., A new iterative method for solving the joint dynamic storage location assignment, order batching and picker routing problem in manual picker-to-parts warehouses, Computers & Industrial Engineering, 147, (2020); Hausman W. H., Schwarz L. B., Graves S. C., Optimal storage assignment in automatic warehousing systems, Management Science, 22, 6, pp. 629-638, (1976); Quintanilla S., Pereza A., Ballestina F., Lino P, Heuristic algorithms for a storage location assignment problem in a chaotic warehouse, Engineering Optimization, 47, 10, pp. 1405-1422, (2015); Alfathi N., Lyhyaoui A., Sedqui A., Fusion of dedicated and shared storage to maximize the use of space of static warehouses, Journal of Industrial and Production Engineering, 36, 8, pp. 512-532, (2019); Otto A., Boysen N., Scholl A., Walter R., Ergonomic workplace design in the fast pick area, OR Spectrum, 39, 4, pp. 945-975, (2017); Xie J., Mei Y., Ernst A. T., Li X., Song A., A bi-level optimization model for grouping constrained storage location assignment problems, IEEE Transactions on Cybernetics, 48, 1, pp. 385-398, (2018); Wan Yanchun, Liu Yong, Integrating optimized fishbone warehouse layout, storage location assignment and picker routing, IAENG International Journal of Computer Science, 49, 3, pp. 957-974, (2022); Xu X., Ren C., Research on dynamic storage location assignment of picker-to-parts picking systems under traversing routing method, Complexity, 2020, pp. 1-12, (2020); Yang D., Wu Y., Ma W., Optimization of storage location assignment in automated warehouse, Microprocessors and Microsystems, 80, (2021); Jiao Y., Xing X., Zhang P., Xu L., Liu X., Multi-objective storage location allocation optimization and simulation analysis of automated warehouse based on multi-population genetic algorithm, Concurrent Engineering: Research and Applications, 26, 4, pp. 367-377, (2018); Ene S., Kucukoglu I., Aksoy A., Ozturk N., A genetic algorithm for minimizing energy consumption in warehouses, Energy, 114, pp. 973-980, (2016); Bortolini M., Faccio M., Ferrari E., Gamberi M., Pilati F., Time and energy optimal unit-load assignment for automatic S/R warehouses, International Journal of Production Economics, 190, pp. 133-145, (2017); Diefenbach H., Glock C. H., Ergonomic and economic optimization of layout and item assignment of a U-shaped order picking zone, Computers & Industrial Engineering, 138, (2019); Yan B., Yan C., Long F., Tan X., Multi-objective optimization of electronic product goods location assignment in stereoscopic warehouse based on adaptive genetic algorithm, Journal of Intelligent Manufacturing, 29, 6, pp. 1273-1285, (2018); Yang P., Peng Y., Ye B., Miao L., Integrated optimization of location assignment and sequencing in multi-shuttle automated storage and retrieval systems under modified 2n-command cycle pattern, Engineering Optimization, 49, 9, pp. 1604-1620, (2017); Zhang S., Fu L., Chen R., Mei Y., Optimizing the cargo location assignment of retail e-commerce based on an artificial fish swarm algorithm, Mathematical Problems in Engineering, 2020, pp. 1-14, (2020); Micale R., La Fata C. M., La Scalia G., A combined intervalvalued ELECTRE TRI and TOPSIS approach for solving the storage location assignment problem, Computers & Industrial Engineering, 135, pp. 199-210, (2019); Qu Qiang, Wang Hai-hua, Qi Mei-li, Improved Grey Wolf Optimizer with Differential Perturbation for Function Optimization, IAENG International Journal of Applied Mathematics, 52, 2, pp. 482-491, (2022); Chen Gonggui, Chen Yifan, Xiang Yi, Zhou Ping, Zeng Xianjun, Long Hongyu, Application of LADRC Based on the IMFO Algorithm for Multi-Area Interconnected AGC Problems, IAENG International Journal of Applied Mathematics, 52, 2, pp. 336-352, (2022); Chen H., Path planning of mobile robot using hybrid algorithm based on GA-IACO, Engineering Letters, 30, 2, pp. 582-589, (2022); Xian Huafeng, Che Jinxing, A Variable Weight Combined Model Based on Time Similarity and Particle Swarm Optimization for Shortterm Power Load Forecasting, IAENG International Journal of Computer Science, 48, 4, pp. 915-924, (2021); Wang Bo, Lv Bin, Song Ying, A Hybrid Genetic Algorithm with Integer Coding for Task Offloading in Edge-Cloud Cooperative Computing, IAENG International Journal of Computer Science, 49, 2, pp. 503-510, (2022); Pawlak Z., An inquiry into anatomy of conflicts, Information Sciences, 109, 1, pp. 65-78, (1998); Calzavara M, Glock CH, Grosse EH, Persona A, Sgarbossa F, Analysis of economic and ergonomic performance measures of different rack layouts in an order picking warehouse, Computers & Industrial Engineering, 111, pp. 527-536, (2017); Calzavara M, Glock CH, Grosse EH, Sgarbossa F, An integrated storage assignment method for manual order picking warehouses considering cost, workload and posture, International Journal of Production Research, 57, 8, pp. 2392-2408, (2018); Otto A, Boysen N, Scholl A, Walter R, Ergonomic workplace design in the fast pick area, OR Spectrum, 39, 4, pp. 945-975, (2017); Diefenbach H, Glock CH, Ergonomic and economic optimization of layout and item assignment of a U-shaped order picking zone, Computers & Industrial Engineering, 138, (2019)",null,null,"International Association of Engineers",{"$nulls":5},"1816093X",null,null,null,"English","Eng. Lett.","Article","Final",null,"Scopus","2-s2.0-85160605669"]
["Ju Q.; Ju Z.; Xiaoyi F.; Tianxin L.","Ju, Qiu (58283762300); Ju, Zhao (58283439500); Xiaoyi, Fang (57222155910); Tianxin, Li (58283439600)","58283762300; 58283439500; 57222155910; 58283439600","Analysis of a retailer′s BOPS strategy based on endogenous prices of third-party logistics services; [基于第三方物流服务定价的零售商 BOPS 策略研究]",2023.0,"Journal of Industrial Engineering and Engineering Management",37.0,3.0,null,169.0,177.0,8.0,1.0,"10.13587/j.cnki.jieem.2023.03.016","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85159904689&doi=10.13587%2fj.cnki.jieem.2023.03.016&partnerID=40&md5=9eee9751914db4925679e54b190f9cc1","School of Management, Hefei University of Technology, Hefei, 230009, China; Key Laboratory of Process Optimization and Intelligent Decision-making, Ministry of Education, Hefei, 230009, China; Ministry of Education Engineering Research Center for Intelligent Decision-Making & Information System Technologies, Hefei, 230009, China","Ju Q., School of Management, Hefei University of Technology, Hefei, 230009, China; Ju Z., School of Management, Hefei University of Technology, Hefei, 230009, China, Key Laboratory of Process Optimization and Intelligent Decision-making, Ministry of Education, Hefei, 230009, China, Ministry of Education Engineering Research Center for Intelligent Decision-Making & Information System Technologies, Hefei, 230009, China; Xiaoyi F., School of Management, Hefei University of Technology, Hefei, 230009, China; Tianxin L., School of Management, Hefei University of Technology, Hefei, 230009, China","Consumers′ requirements for online order fulfillment services are increasing as e-commerce develops further. Thus, discovering how best to fulfill consumers′ online orders as quickly as possible has become an urgent issue for retailers. The traditional method retailers have used to fulfill online orders is to cooperate with third-party logistical firms ( e. g., express firms). Third-party logistical firms ship products from the retailer to the consumer and charge the retailer a fee for that service. Recently, with the acceleration of online and offline channel integration, many retailers have begun to take advantage of new or existing brick-and-mortar stores to fulfill consumers′ online orders; that is, retailers allow consumers to buy online and pick up in-store (BOPS) to improve consumers′ shopping experience. This opportunity directly impacts the demand and pricing of any third-party logistical firm that provides s online order fulfillment services for the retailer. However, current literature on BOPS strategies has largely ignored potential pricing decisions of third-party logistical firms in response to retailers′ adoption of BOPS strategies. Such changes might lead to losses for the retailer. Thus, investigating the interaction between BOPS strategies and the pricing decisions of third-party logistical firms provides managerial insights for the development of e-commerce supply chains in an omnichannel retailing environment. For example, a supply chain includes a dual-channel retailer that sells the exact same products through the online and offline channels and uses the services of a third-party logistical firm; then, the retailer′s optimal online order fulfillment strategy in the presence of heterogeneous consumers in two dimensions should be investigated -the product valuation and the hassle cost of offline shopping. Specifically, in addition to fulfilling the online orders through the third-party logistical firm, the retailer should decide whether to implement a BOPS strategy that will allow customers to buy online and pick up in-store. To determine the impacts of the BOPS strategy on the retailer and third-party logistical firms, as well as the conditions under which the retailer should adopt this strategy, we develop a basic model in which the retailer does not adopt a BOPS strategy and a pricing game model of the retailer and the third-party logistical firm when the retailer does adopt the BOPS strategy. First, by comparing the retailer′s equilibrium profits before and after the implementation of the BOPS strategy, we discover that the logistics service level, the operation cost of the BOPS channel, and the degree of convenience for consumers to pick up products in the store are the important factors influencing whether a retailer should adopt the BOPS strategy or not. When the unit operating cost of the BOPS channel is low, customers′ channel transfer behavior is beneficial to the retailer. The lower the level of logistics services and the greater the convenience of an in-store pickup are, the more customers will transfer to the BOPS channel. This experience demonstrates that the adoption of the BOPS strategy is more favorable to the retailer. However, when the unit operating cost of the BOPS channel is high, any significant amount of customers′ channel transfer behavior increases the operations and cost pressure on the retailer. Therefore, the retailer will profit from implementing a BOPS strategy only if the third-party logistical firm offers high-level lowcost logistics services and picking up in the available bricks-and-mortar stores is highly inconvenient for consumers leading to fewer customers transferring to additional BOPS channels. Second, we analyze the impact of a BOPS strategy on equilibrium prices and the volume of online orders through several numerical examples. When adopting the BOPS strategy, the retailer raises the product price because BOPS generally improves the willingness to pay for products. Increasing product prices and switching consumers to the BOPS channel lead to a decrease in the number of online orders fulfilled by the third-party logistical firm. Only when the level of third-party logistics service is high, the cost of operating the BOPS channel is low, and the inconvenience of picking up the online order in the local store is high, the retailer will reduce the product price to induce new customers and expand the use of BOPS. In other words, at least initially, the third-party logistical firm can fulfill more online orders. Finally, we analyze how the BOPS strategy can affect the third-party logistical firm′s pricing of its services and its profitability. When the retailer adopts a BOPS strategy, the third-party logistical firm increases its service prices to compensate for the loss caused by a decrease in the number of fulfilled online orders. As the degree of the inconvenience of picking up online orders in the store increases, that is, the overall advantage of the BOPS strategy is weakened, the third-party logistical firm with high-level services would be less likely to increase its service price. When the costs of operating the BOPS channel and the inconvenience of picking up the online order in the store are high, the third-party logistical firm offering a high level of logistics service will decrease the service price after the retailer′s implementation of the BOPS strategy. The retailer can avoid excessive service prices from the third-party logistical firm by increasing investment in running the BOPS channels. Additionally, we find that the third-party logistical firm′s profit is damaged by the retailer′s BOPS strategy. This damage can be reduced by improving logistics service levels or cooperating with retailers with low advantages in implementing BOPS strategies. © 2023,Journal of Industrial Engineering and Engineering Management. All Rights Reserved.","BOPS strategy; Game; Logistics service pricing; Orders fulfillment",{"$nulls":5},"National Office for Philosophy and Social Sciences, NPOPSS, (18BGL265)","Received Date: 2020-11-27 　 　 　 Funded Project: Supported by the National Social Science Foundation of China (18BGL265 ). ∗Corresponding author","Buy online and pick up in-store，Shopex ERP empowered clothing brand play new retail; Gallino S, Moreno A., Integration of online and offline channels in retail: The impact of sharing reliable inventory availability information [J], Management Science, 60, 6, pp. 1434-1451, (2014); Cao J，So K C，, Yin S., Impact of an “online-to-store” channel on demand allocation，pricing and profitability, European Journal of Operational Research, 248, 1, pp. 234-245, (2016); Kim E，, Park M C，, Lee J., Determinants of the intention to use Buy-Online，Pickup In-Store ( BOPS): The moderating effects of situational factors and product type [J], Telematics and Informatics, 34, 8, pp. 1721-1735, (2017); Gao F，, Su X., Omnichannel retail operations with buy-online-and-pick-up-in-store, Management Science, 63, 8, pp. 2478-2492, (2017); Hu M，, Xu X，, Xue W，, Et al., Demand pooling in omnichannel operations[J], Management Science, 68, 2, pp. 809-1589, (2022); Lu J C，, Yang Y，, Han S Y，, Et al., Coordinated inventory policies for meeting demands from both store and online BOPS channels [J], Computers & Industrial Engineering, 145, (2020); Jin M，, Li G，, Cheng T C E., Buy online and pick up in-store: Design of the service area [J], European journal of operational research, 268, 2, pp. 613-623, (2018); MacCarthy B L，, Zhang L，, Muyldermans L., Best performance frontiers for buy-online-pickup-in-store order fulfilment [J], International Journal of Production Economics, 211, pp. 251-264, (2019); Niu B, Li B., O2O results in traffic congestion reduction and sustainability improvement: Analysis of “Online-to-Store” channel and uniform pricing strategy, Transportation Research Part E: Logistics and Transportation Review, 122, pp. 481-505, (2019); Zhang Q Y, Zhang G B, Zhang D H., A contrastive study of same price channel and BOPS in the context of “ Internet+” [J], Journal of Systems Science and Mathematical Sciences, 39, 8, pp. 1303-1313, (2019); Kong R X，, Guan Z Z，, Luo L., Research on omni-channel supply chain structure with BOPS, Chinese Journal of Management, 16, 7, pp. 1072-1080, (2019); Zhang P，, He Y，, Zhao X., Preorder-online， pickup-in-store” strategy for a dual-channel retailer, Transportation Research Part E: Logistics and Transportation Review, 122, pp. 27-47, (2019); Kong R，, Luo L，, Chen L，, Et al., The effects of BOPS implementation under different pricing strategies in omnichannel retailing [J], Transportation Research Part E: Logistics and Transportation Review, 141, (2020); Li Z H，, Yang W S，, Liu X H，, Et al., Channel integration strategy for omnichannel retail enterprise with online coupon, Systems Engineering-Theory & Practice, 40, 3, pp. 630-640, (2020); Shi X，, Dong C，, Cheng T C E., Does the buy-online-and-pick-up-in-store strategy with pre-orders benefit a retailer with the consideration of returns? 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Industrial Eng. Eng. Management","Article","Final",null,"Scopus","2-s2.0-85159904689"]
["Dong Q.; Chen N.; Wang S.","Dong, Qingxia (58833727100); Chen, Nana (58316419500); Wang, Shuai (58317500300)","58833727100; 58316419500; 58317500300","Supply chain resource scheduling optimization of e-commerce enterprises in international trade based on mobile edge computing",2023.0,"PeerJ Computer Science",9.0,null,"e1407",null,null,null,0.0,"10.7717/peerj-cs.1407","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85162122372&doi=10.7717%2fpeerj-cs.1407&partnerID=40&md5=ed6bddbd2983e3a0f8369423412ec63d","Shandong Vocational and Technical University of International Studies, Shandong, Rizhao, China; Rizhao Marine Engineering Vocational College, Shandong, Rizhao, China","Dong Q., Shandong Vocational and Technical University of International Studies, Shandong, Rizhao, China; Chen N., Shandong Vocational and Technical University of International Studies, Shandong, Rizhao, China; Wang S., Rizhao Marine Engineering Vocational College, Shandong, Rizhao, China","The cross-border e-commerce supply chain network (CBESCN) has extensive geographical coverage, trade barriers and complexity of cross-border logistics issues, which makes its construction and development face many challenges. This article focuses on solving the operation optimisation problem of CBESCN under the background of the Internet of Things. A genetic algorithm constructed and solved the resource scheduling model of the supply chain of e-commerce enterprises in international trade. In addition, the mobile edge computing (MEC) optimisation scheme based on partial computation unloading is involved. The initial offload ratio is set and supply chain resources are allocated, then the remaining computing resources are distributed according to the server's computing power. Finally, the offload is optimised according to the resource allocation. The experimental results show that time delay and cost adjustment strategies can improve the CBE supply chain's comprehensive ability. The supply chain optimisation scheme proposed in this article can effectively use supply chain resources according to the requirements of computing tasks to reduce the total delay of task execution and the consumption of node computing. © 2023 Dong et al.","International trade; MEC; Resource scheduling; Supply chain","Computation offloading; Genetic algorithms; International trade; Mobile edge computing; Unloading; Cross-border; E- commerces; E-commerce enterprise; Geographical coverage; Operations optimization; Optimization scheme; Resource-scheduling; Scheduling optimization; Supply chain network; Trade barriers; Supply chains",{"$nulls":6},"Abbas N, Zhang Y, Taherkordi A., Mobile edge computing: a survey, IEEE Internet of Things Journal, 5, 1, pp. 450-465, (2018); Albino V, Izzo C, Silvana Kuhtz, Input-output models for the analysis of a local/-global supply chain, International Journal of Production Economics, 78, 2, pp. 119-131, (2002); Bi SZ, Zhang YJ., Computation rate maximisation for wireless powered mobile-edge computing with binary computation offloading, IEEE Transactions on Wireless Communications, 17, 6, pp. 4177-4190, (2018); Bozorgchenani A, Tarchi D, Corazza GE., Mobile edge computing partial offloading techniques for mobile urban scenarios, Proceedings of 2018 IEEE global communications conference, (2018); Dai M, Liu Z, Guo Z., Edge computing unloading and resource allocation mechanism based on minimising terminal energy consumption and system delay, Journal of Electronics and Information, 41, 11, pp. 2684-2690, (2019); Eshraghi N, Liang B., Joint offloading decision and resource allocation with uncertain task computing requirement, Proceedings of IEEE INFOCOM 2019 -IEEE conference on computer communications, pp. 1414-1422, (2019); Gao Y, Zhang HR, Yu F., Joint computation offloading and resource allocation for mobile-edge computing assisted ultra-dense networks, Journal of Communications and Information Networks, 7, 1, pp. 96-106, (2022); Josilo S, Dan G., Wireless and computing resource allocation for selfish computation offloading in edge computing, Proceedings of IEEE INFOCOM 2019 - IEEE conference on computer communications, pp. 2467-2475, (2019); Li R, Li Q, Zhou J., ADRIoT: an edge-assisted anomaly detection framework against IoT-based network attacks, IEEE Internet of Things Journal, 9, 13, pp. 10576-10587, (2021); Lin L, Liao XF, Jin H., Computation offloading toward edge computing, Proceedings ofthelEEE, 107, 8, pp. 1584-1607, (2019); Liu J, Pan B, Zhang X., Mobile E-commerce information system based on industry cluster under edge computing, Mobile Information Systems, 2021, pp. 1-11, (2021); Liu Z, Li Z., A blockchain-based framework of cross-border e-commerce supply chain, International Journal of Information Management, 52, 10, pp. 37-59, (2020); Moghaddam Kamran S., Fuzzy multi-objective model for supplier selection and order allocation in reverse logistics systems under supply and demand uncertainty, Expert Systems with Applications, 42, pp. 6237-6254, (2015); Mukherjee M, Kumar S, Shojafar M, Zhang Q, Mavromoustakis CX., Joint task offloading and resource allocation for delay-sensitive fog networks, ICC 20192019 IEEE international conference on communications (ICC), (2019); Nguyen QH, Dressler F., A smartphone perspective on computation offloading—a survey, Computer Communications, 159, pp. 133-154, (2020); Toro EM, Franco JF, Echeverri MG., A multi-objective model for the green capacitated location-routing problem considering environmental impact, Computers & Industrial Engineering, 110, pp. 114-125, (2017); Wang Y, Jia F, Schoenherr T., Supply chain-based business model innovation: the case of a cross-border E-commerce company, Sustainability, 10, 12, (2018); Wang Y, Jia F, Schoenherr T., Cross-border e-commerce firms as supply chain integrators: the management of three flows, Industrial Marketing Management, 89, pp. 72-88, (2020); Wangfi S, Wang W, Tan Y., Internet cross-border service model based on 5G environment and cloud computing data platform, Microprocessors and Microsystems, 2020, (2020); Yan W, Zhou H, Li H., Decision and coordination of cross-border e-commerce supply chain: based on four modes of cooperation, Scientific Programming, (2021); Yu W, Hou G, Li J., Supply chain joint inventory management and cost optimisation based on ant colony algorithm and fuzzy model, Tehnički Vjesnik, 26, 6, pp. 1729-1737, (2019); Zhang X, Cai Y, Xiao L., Visitor information system of cross-border E-commerce platform based on mobile edge computing, Mobile Information Systems, 2021, pp. 1-10, (2021); Zhou L, Wang J, Li F., Risk aversion of B2C cross-border e-commerce supply chain, Sustainability, 14, 13, (2022); Zhu X, Chen SG, Chen SL., Energy and delay co-aware computation offloading with deep learning in fog computing networks, Proceedings of 2019 IEEE 38th international performance computing and communications conference, (2019)","Q. Dong; Shandong Vocational and Technical University of International Studies, Rizhao, Shandong, China; email: junedqx666@outlook.com",null,"PeerJ Inc.",{"$nulls":5},2.3765992E7,null,null,null,"English","PeerJ Comput. Sci.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85162122372"]
["Burlăcioiu C.; Boboc C.; Mirea B.; Dragne I.","Burlăcioiu, Cristina (58001410500); Boboc, Cristina (34871341100); Mirea, Bogdan (58169813900); Dragne, Ioana (58168903600)","58001410500; 34871341100; 58169813900; 58168903600","TEXT MINING IN BUSINESS. A STUDY OF ROMANIAN CLIENT’S PERCEPTION WITH RESPECT TO USING TELECOMMUNICATION AND ENERGY APPS",2023.0,"Economic Computation and Economic Cybernetics Studies and Research",57.0,1.0,null,221.0,234.0,13.0,0.0,"10.24818/18423264/57.1.23.14","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85151557396&doi=10.24818%2f18423264%2f57.1.23.14&partnerID=40&md5=d4b8121687b21a37612ad3c50a3212aa","ASEBUSS – The Institute for Business Administration, Bucharest, Romania; Department of Statistics and Econometrics, The Bucharest University of Economic Studies, Romania; The Bucharest University of Economic Studies, Romania; Advanced Digital Imaging Techniques, Faculty of Electronics, Telecommunications and Information Technology University POLITEHNICA of Bucharest, Romania","Burlăcioiu C., ASEBUSS – The Institute for Business Administration, Bucharest, Romania; Boboc C., Department of Statistics and Econometrics, The Bucharest University of Economic Studies, Romania; Mirea B., The Bucharest University of Economic Studies, Romania; Dragne I., Advanced Digital Imaging Techniques, Faculty of Electronics, Telecommunications and Information Technology University POLITEHNICA of Bucharest, Romania","New technologies have enabled companies to create new and contemporary designs and, at the same time, increase the efficiency of their operations. The Internet has amplified not only the e-commerce with products, but also with services. Paying and changing contracts online in only a few minutes for telecommunication and energy services are only two of the advantages of online APPs. The objective of this study is to show how to use and analyze the review data from customers on online applications or forums, providing very useful insights that could be used to improve company-customer relationships and gain business benefits. The data were collected by using the web scrapping method, obtaining a large amount of text. For the overall understanding of this large amount of text, sentiment analysis was used. Then, to classify the reviews into one of three classes: negative, positive or neutral feeling, five methods were used and compared: logistic regression, decision tree method, K Nearest Neighbors method, SVM algorithm, Naïve Bayes. © 2023, Bucharest University of Economic Studies. All rights reserved.","classification; machine learning; online APP`s; sentiment analysis; web scrapping",{"$nulls":7},"Angelopoulos M. K., Kontakou C., Data Analytics and Customer Experience in Industry: An Option, International Journal of Advances in Engineering and Management, 3, 3, pp. 1294-1300, (2021); Bijoyan D., Chakraborty S., An Improved Text Sentiment Classification Model Using TF-IDF and Next Word Negation, (2018); O'Brien M., Reviews and refinement: Using customer reviews to identify areas for improvement, (2017); Cioban S., Cross-Domain Sentiment Analysis of the Natural Romanian Language, Digital Economy. Emerging Technologies and Business Innovation. ICDEc 2021. Lecture Notes in Business Information Processing, 431, (2021); Guerreiro J., Moro S., Are Yelp's tips helpful in building influential consumers?, Tourism Management Perspectives, 24, pp. 151-154, (2017); Jia S., Motivation and satisfaction of Chinese and U.S. tourists in restaurants: A cross-cultural text mining of online reviews, Tourism Management, 78, (2020); Kim S., Lee W.S., Network text analysis of medical tourism in newspapers using text mining: The South Korea case, Tourism Management Perspectives, 31, pp. 332-339, (2019); Lupea M., Briciu A., Studying emotions in Romanian words using formal concept analysis, Computer Speech & Language, 57, (2019); Masala M., Ruseti S., Dascalu M., RoBERT – A Romanian BERT Model, pp. 6626-6637, (2020); Mehta P., Pandya D., A Review On Sentiment Analysis Methodologies, International Journal of Scientific and Technology Research, 9, pp. 601-607, (2020); Neagu D.C., Rus A.B., Grec M., Boroianu M.A., Bogdan N., Gal A., Towards Sentiment Analysis for Romanian Twitter Content, Algorithms, 2022, 15, (2022); Pezenka I., Weismayer C., Which factors influence locals’ and visitors’ overall restaurant evaluations?, International Journal of Contemporary Hospitality Management, 32, 9, pp. 2793-2812, (2020); AI Predictions 2021, (2021); Russu R. M., Vlad O., Dinsoreanu M., Potolea R., An Opinion Mining Approach For Romanian Language, Proceedings of IEEE 10th International Conference on Intelligent Computer Communication and Processing (ICCP), pp. 43-46, (2014)",null,null,"Bucharest University of Economic Studies",{"$nulls":5},"0424267X",null,null,null,"English","Econ. Comput. Econ. Cybern. Stud. Res.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85151557396"]
["Ahmed S.; Ashrafi D.M.; Paraman P.; Dhar B.K.; Annamalah S.","Ahmed, Selim (56098522600); Ashrafi, Dewan Mehrab (57201678834); Paraman, Pradeep (57226133309); Dhar, Bablu Kumar (57221674179); Annamalah, Sanmugam (54917589700)","56098522600; 57201678834; 57226133309; 57221674179; 54917589700","Behavioural intention of consumers to use app-based shopping on green tech products in an emerging economy",2023.0,"International Journal of Quality and Reliability Management",{"$nulls":6},0.0,"10.1108/IJQRM-05-2023-0164","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85180449792&doi=10.1108%2fIJQRM-05-2023-0164&partnerID=40&md5=c12a9c3a4e04c4fdb5ff39135c130797","College of Business Administration, International University of Business Agriculture and Technology, Dhaka, Bangladesh; Department of Business Administration, East West University, Dhaka, Bangladesh; Faculty of Business and Accounting, SEGi University, Petaling Jaya, Malaysia; Business Administration Division, Mahidol University, Bangkok, Thailand; Research and Innovation Management Centre, Graduate School of Business, SEGi University, Petaling Jaya, Malaysia","Ahmed S., College of Business Administration, International University of Business Agriculture and Technology, Dhaka, Bangladesh; Ashrafi D.M., Department of Business Administration, East West University, Dhaka, Bangladesh; Paraman P., Faculty of Business and Accounting, SEGi University, Petaling Jaya, Malaysia; Dhar B.K., Business Administration Division, Mahidol University, Bangkok, Thailand; Annamalah S., Research and Innovation Management Centre, Graduate School of Business, SEGi University, Petaling Jaya, Malaysia","Purpose: The purpose of this research article is to explore the behavioural intention of consumers to use app-based shopping for green-tech products in the emerging economy of Bangladesh. The study investigates the indirect effects of perceived ease of use, usefulness, perceived delivery and perceived security on the behavioural intention to use app-based shopping for purchasing green-tech products by considering the mediating role of perceived trust. Design/methodology/approach: A quantitative research approach was applied to collect data from the respondents who had previously used app-based shopping for green-tech products in Bangladesh. An online, self-administered survey questionnaire was used to collect data from 348 respondents. The survey data was analysed using SmartPLS-4 to measure the reliability and validity of the constructs. In addition, partial least squares structural equation modelling (PLS-SEM) was employed to test the research model and hypotheses. Findings: The study's results reveal that perceived usefulness, ease of use, security and delivery positively and significantly influence perceived trust, leading to a higher behavioural intention to use app-based shopping for green-tech products. Additionally, perceived trust significantly mediates the relationship between the behavioural intention to use app-based shopping and perceived usefulness, perceived ease of use, perceived security and perceived delivery. Practical implications: The study's findings have important implications for app-based shopping services to support customers interested in purchasing green-tech products in an emerging economy. The results also indicate that green-tech product companies must adopt new service delivery channels and ensure consumers' convenience and cost and time savings. The present research findings suggest that green-tech product companies need to ensure that they integrate digital technologies into their services for secure and timely delivery of products, improving customer convenience. Originality/value: The study's findings can be insightful for app-based shopping service providers to foster their businesses by focussing on developing a positive trust perception in the consumer's mind, leading to a positive intention to use the app-based shopping services. The present study will enrich the current literature by investigating how consumers' perceived trust affects their behavioural intention to use app-based online shopping for purchasing green-tech products. It will also expand the existing knowledge on app-based shopping by exploring how perceived delivery impacts perceived trust, which subsequently affects customers' intentions to adopt the purchase of green-tech products. © 2023, Emerald Publishing Limited.","App-based shopping; Behavioural intention; Customer service; Emerging economy; Green-tech product; PLS-SEM",{"$nulls":7},{"$cut":{"chars":19490,"head":"Aggarwal A., Rahul M., The effect of perceived security on consumer purchase intensions in electronic commerce, International Journal of Public Sector Performance Management, 4, 1, pp. 1-20, (2018); Ajzen I., The theory of planned behavior, Organizational Behavior and Human Decision Processes, 50, 2, pp. 179-211, (1991); Akbari M., Rezvani A., Shahriari E., Zuniga M.A., Pouladian H., Acceptance of 5 G technology: mediation role of trust and concentration, Journal of Engineering and Technology Management, 57, (2020); Akhtar N., Siddiqi U.I., Islam T., Paul J., Consumers’ untrust and behavioral intentions in the backdrop of hotel booking attributes, International Journal of Contemporary Hospitality Management, 34, 5, pp. 2026-2047, (2022); Al-Khalaf E., Choe P., Increasing customer trust towards mobile commerce in a multicultural society: a case of Qatar, Journal of Internet Commerce, 19, 1, pp. 32-61, (2020); Ali S., Khalid N., Javed H.M.U., Islam D.M., Consumer adoption of online food delivery ordering (OFDO) services in Pakistan: the impact of the COVID-19 pandemic situation, Journal of Open Innovation: Technology, Market, and Complexity, 7, 1, pp. 1-23, (2021); Almaiah M.A., Al-Rahmi A., Alturise F., Hassan L., Lutfi A., Alrawad M., Alkhalaf S., Al-Rahmi W.M., Al-sharaieh S., Aldhyani T.H., Investigating the effect of perceived security, perceived trust, and information quality on mobile payment usage through near-field communication (NFC) in Saudi arabia, Electronics, 11, 23, (2022); Almaiah M.A., Al-Otaibi S., Shishakly R., Hassan L., Lutfi A., Alrawad M., Qatawneh M., Alghanam O.A., Investigating the role of perceived risk, perceived security and perceived trust on smart m-banking application using SEM, Sustainability, 15, 13, (2023); Amin M., Rezaei S., Abolghasemi M., User satisfaction with mobile websites: the impact of perceived usefulness (PU), perceived ease of use (PEOU) and trust, Nankai Business Review International, 5, 3, pp. 258-274, (2014); Arora A., Rani N., Devi C., Gupta S., Factors affecting consumer purchase intentions of organic food through fuzzy AHP, International Journal of Quality and Reliability Management, 39, 5, pp. 1085-1103, (2022); Arora M., Singh H., Gupta S., What drives e-hailing apps adoption? An analysis of behavioral factors through fuzzy AHP, Journal of Science and Technology Policy Management, 13, 2, pp. 382-404, (2022); Arora A., Gupta S., Devi C., Walia N., Customer experiences in the era of artificial intelligence (AI) in context to FinTech: a fuzzy AHP approach, Benchmarking: An International Journal, 30, 10, pp. 4342-4369, (2023); Ashrafi D.M., Easmin R., Okay Google, good to talk to you, examining the determinants affecting users' behavioral intention for adopting voice assistants: does technology self-efficacy matter?, International Journal of Innovation and Technology Management, 20, 2, (2023); Ashrafi D.M., Alam I., Anzum M., An empirical investigation of consumers' intention for using ride-sharing applications: does perceived risk matter?, International Journal of Innovation and Technology Management, 18, 8, (2021); Ashrafi D.M., Dovash R.H., Kabir M.R., Determinants of fintech service continuance behavior: moderating role of transaction security and trust, Journal of Global Business and Technology, 18, 2, pp. 35-59, (2022); Asti W.P., Handayani P.W., Azzahro F., Influence of trust, perceived value, and attitude on customers' repurchase intention for E-grocery, Journal of Food Products Marketing, 27, 3, pp. 157-171, (2021); Belanche D., Flavian M., Perez-Rueda A., Mobile apps use and wom in the food delivery sector: the role of planned behavior, perceived security and customer lifestyle compatibility, Sustainability, 12, 10, pp. 1-21, (2020); Beldad A.D., Hegner S.M., Expanding the technology acceptance model with the inclusion of trust, social influence, and health valuation to determine the predictors of German users' willingness to continue using a fitness app: a structural equation modeling approach, International Journal of Human–Computer Interaction, 34, 9, pp. 882"}},"S. Ahmed; College of Business Administration, International University of Business Agriculture and Technology, Dhaka, Bangladesh; email: selim.ahmed@business.wub.edu.bd",null,"Emerald Publishing",{"$nulls":5},"0265671X",null,null,null,"English","Int. J. Qual. Reliab. Manage.","Article","Article in press",null,"Scopus","2-s2.0-85180449792"]
["Phan D.M.; Dinh H.T.","Phan, Duc Minh (57883742900); Dinh, Ha Thu (58497712100)","57883742900; 58497712100","DIGITAL TRANSFORMATION OF BUSINESS COMMUNITY IN GLOBALIZATION: AN EMPIRICAL STUDY IN A TYPICAL DEVELOPING COUNTRY",2023.0,"Eastern-European Journal of Enterprise Technologies",3.0,"13(123)",null,98.0,110.0,12.0,0.0,"10.15587/1729-4061.2023.283251","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85165337619&doi=10.15587%2f1729-4061.2023.283251&partnerID=40&md5=2add95635b5fd2edbaaa6e51d51d678a","Department of Political Economics, Academy of Journalism and Communication, Xuan Thuy, 36, Cau Giay, Hanoi, 100000, Viet Nam","Phan D.M., Department of Political Economics, Academy of Journalism and Communication, Xuan Thuy, 36, Cau Giay, Hanoi, 100000, Viet Nam; Dinh H.T., Department of Political Economics, Academy of Journalism and Communication, Xuan Thuy, 36, Cau Giay, Hanoi, 100000, Viet Nam","The research object focuses on the digital transformation (DX) process of the enterprises and corresponding management policies from the State. In the context of a transition economy, deeply integrated into the world economy, and facing competition pressure many times higher than the one in the domestic market, businesses have themselves prepared such things like the understanding of how DX is, how DX-ready they are, how much to invest and where they are on the path. The con-text of Vietnam is used as a good example of a developing country with progressing digitalization and fierce competition from abroad. Hence, the authors have carried out a positivist analysis, using quantitative and qualitative indicators to clarify the DX of the companie. Quantitative indicators refer to a 5-point scale or percentage point in the assessment, allowing the statements, by the survey participants or the researchers themselves, to have a uniform basis. Qualitative indicators are drawn from structured observations, in-depth interviews, and literature review, mainly focusing on two extremes, good and bad. As the main results of the study, almost 90 % of Vietnamese businesses raise awareness of DX to apply into their operations or to seek for DX solutions. Only 40 % of businesses have the budget to receive DX consulting and solutions, and up to 20 % of businesses have absolutely no budget for DX. The DX readiness is highest in industries whose activities are closely related to a direct supply of goods and ser-vices. The DX promotion may root from the increasing number of customers using the Internet alongside their savvy digital skills, or from digital logistics enabling the strong growth of e-commerce, and from favorable policies from the State. Still, concerns about personal data, costs of technology investment, or business habits changing are typical challenges © (2023), All Rights Reserved.","digital; digital competence; digital foundation; digital literacy; digital maturity; digital readiness; digital transformation; digitalization; DX; e-Commerce; e-Government",{"$nulls":5},"Academy of Journalism and Communication","We, the authors, acknowledge the valuable support of Le Thuy Anh, a young scientist of K40A1 (Economic Management cohorts), Academy of Journalism and Communication. Without some of her input, this research cannot be formed thoroughly.","Bhalla R., Osta E., Digital transformation and the COVID-19 challenge, Journal of Digital Banking, 5, 4, pp. 291-304, (2021); Báo cáo tóm (Formula presented) (Formula presented) (Formula presented) (Formula presented) (Formula presented) gia (2023); (Formula presented) (Formula presented) (Formula presented) 749/QĐ-TTg: Phê duyêt “(Formula presented) trinh Chuyên (Formula presented) (Formula presented) (Formula presented) gia d(Formula presented) (Formula presented) 2025, (Formula presented) (Formula presented) (Formula presented) năm 2030, (2020); Global Macro and Industry: Key Themes for 2022; Martin A., Digital Literacy and the “Digital Society”, Digital Literacies: Concepts, Policies, and Practices, pp. 151-176, (2008); Moser-Plautz B., Schmidthuber L., Digital government transformation as an organizational response to the COVID-19 pandemic, Government Information Quarterly, 40, 3, (2023); Sagayarajan S., Shaji George A., The Digital Transformation: Key Attributes and Challenges, The International Journal of Analytical and Experimental Modal Analysis, 11, 3, pp. 313-320, (2019); Guo X., Li M., Wang Y., Mardani A., Does digital transformation improve the firm’s performance? From the perspective of digitalization paradox and managerial myopia, Journal of Business Research, 163, (2023); Cui L., Wang Y., Can corporate digital transformation alleviate financial distress?, Finance Research Letters, 55, (2023); Westerman G., Calmejane C., Bonnet D., Ferraris P., McAfee A., Digital Transformation: A Roadmap for Billion-Dollar Organizations, (2011); Digital Transformation: A Primer; Matt C., Hess T., Benlian A., Digital Transformation Strategies, Business & Information Systems Engineering, 57, 5, pp. 339-343, (2015); ANH T. M., Foundations for Digital Transformation: The Case of Vietnam, Advances in Economics, Business and Management Research, (2021); Formula presented) nang (Formula presented) (Formula presented) (Formula presented), (2021); Formula presented) tay (Formula presented) (Formula presented) (Formula presented) cho doanh (Formula presented) (Formula presented) (Formula presented) Nam (2021); 2020 Asia Pacific SMB Digital Maturity Study; Nguyen H. H., Tran H. V., Digital society and society 5.0: Urgent issues for digital social transformation in Vietnam, Masyarakat, Kebudayaan Dan Politik, 35, 1, (2022); Báo cáo thuòng (Formula presented) (Formula presented) (Formula presented) (Formula presented) doanh (Formula presented) 2021 - Rào cån vá nhu (Formula presented) (Formula presented) (Formula presented) (Formula presented) (2021); Báo cáo thuòng (Formula presented) (Formula presented) (Formula presented) (Formula presented) doanh (Formula presented) 2022 - (Formula presented) (Formula presented) (Formula presented) sàng (Formula presented) (Formula presented) (Formula presented) (Formula presented) doanh (Formula presented) Viet Nam (2022); Le Viet H., Dang Quoc H., The Factors Affecting Digital Transformation in Vietnam Logistics Enterprises, Electronics, 12, 8, (2023); Nguyen T. H., Le X. C., Vu T. H. L., An Extended Technology-Organization-Environment (TOE) Framework for Online Retailing Utilization in Digital Transformation: Empirical Evidence from Vietnam, Journal of Open Innovation: Technology, Market, and Complexity, 8, 4, (2022); Pham H., Tran Q.-N., La G.-L., Doan H.-M., Vu T.-D., Readiness for digital transformation of higher education in the Covid-19 context: The dataset of Vietnam’s students, Data in Brief, 39, (2021); Duester E., The geopolitical and socioeconomic factors of digitization in Vietnam: Technology adoption in the art and cultural sector during the COVID-19 pandemic, Data and Information Management, 6, 2, (2022); The Global Talent Competitiveness Index 2022; Number of users of digital payments in Vietnam from 2017 to 2027; VLA White Book 2018: 25 Years of Growth and International Integration, (2018); 2023 Agility Emerging Markets Logistics Index; Vietnam Freight and Logistics Market - Growth, Trends, Covid-19 Impact, and Forecasts (2023 - 2028), (2023); (Formula presented) (Formula presented) (Formula presented) 221/QĐ-TTg: (Formula presented) (Formula presented), (Formula presented) sung (Formula presented) (Formula presented) so 200/QĐ-TTg ngày 14 tháng 02 năm 2017 (Formula presented) (Formula presented) phe (Formula presented) (Formula presented) (Formula presented) hành (Formula presented) (Formula presented) cao năng (Formula presented) (Formula presented) tranh và phát (Formula presented) (Formula presented) (Formula presented) logistics (Formula presented) Nam den näm 2025 (2021); (2020)","D.M. Phan; Department of Political Economics, Academy of Journalism and Communication, Hanoi, Xuan Thuy, 36, Cau Giay, 100000, Viet Nam; email: phanminhduc@ajc.edu.vn",null,"Technology Center",{"$nulls":5},1.7293774E7,null,null,null,"English","East. Eur. J. Enterp. Technol.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85165337619"]
["Zhang X.; Lyu W.; Han S.","Zhang, Xuefeng (58096767900); Lyu, Weihua (57197717142); Han, Su (58096719300)","58096767900; 57197717142; 58096719300","College Students Consumption Behavior Under the Background of E-Commerce and Smart Logistics Technologies",2023.0,"International Journal of e-Collaboration",19.0,7.0,{"$nulls":4},0.0,"10.4018/IJeC.316881","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85147729683&doi=10.4018%2fIJeC.316881&partnerID=40&md5=cc7e0f28dfccb5aba686a0be75383bae","Shanghai Customs College, China; Guilin Medical University, China; Fenghao Investment Management Co., Ltd, China","Zhang X., Shanghai Customs College, China; Lyu W., Guilin Medical University, China; Han S., Fenghao Investment Management Co., Ltd, China","The impact of online systems and processes worldwide makes online purchasing popular. College students are among the possible buyers of E-commerce. This study looks at the characteristics that influence college students’ online purchase intention in one of Chinese quickest cities. With smart logistics, it is possible to follow the transportation and dispatch of goods and services in almost real-time. Smart logistics has long been implemented by e-commerce enterprises, taxi apps, and food delivery services. The student’s Consumption Behavior Approach (SCBA) is suggested in this article. The survey collection is analyzed to group the learner’s research on online activityand smart logistics technology. Because the sample group is thus tiny, approaches are used. The findings reveal that fun, risk, and cultural pressure substantially influence pupils’ online buying behavior. SCBA grouping produces three behavioral sections: that mostly impacted by social power and perception of risk, that features by pleasure and online trust. © 2023 IGI Global. All rights reserved.","college students; consumer behavior; E-commerce; online shopping; smart logistics technology","Electronic commerce; Online systems; Risk perception; Sales; Students; Taxicabs; College students; E-commerce enterprise; Good and services; Logistics technologies; Online purchasing; Online shopping; Purchase intention; Real- time; Smart logistic technology; Systems and process; Consumer behavior",{"$nulls":6},"Al-Khayyal A., Alshurideh M., Al Kurdi B., Salloum S. A., Factors influencing electronic service quality on electronic loyalty in online shopping context: data analysis approach, Enabling AI Applications in Data Science, pp. 367-378, (2021); Amudha G., Narayanasamy P., Distributed location and trust based replica detection in wireless sensor networks, Wireless Personal Communications, 102, 4, pp. 3303-3321, (2018); Bucko J., Kakalejcik L., Ferencova M., Online shopping: Factors that affect consumer purchasing behavior, Cogent Business & Management, 5, 1, (2018); Burns D. J., Gupta P. B., Bihn H. C., Hutchins J., Showrooming: An exploratory empirical investigation of students’ attitudes and behavior, Information Systems Management, 35, 4, pp. 294-307, (2018); Chandrasekaran G., Nguyen T. N., Hemanth D. J., Multimodal sentimental analysis for social media applications: A comprehensive review, Wiley Interdisciplinary Reviews. Data Mining and Knowledge Discovery, 11, 5, (2021); Changchit C., Cutshall R., Lonkani R., Pholwan K., Pongwiritthon R., Determinants of online shopping influencing Thai consumers’ buying choices, Journal of Internet Commerce, 18, 1, pp. 1-23, (2019); Fu H., Manogaran G., Wu K., Cao M., Jiang S., Yang A., Intelligent decision-making of online shopping behavior based on the internet of things, International Journal of Information Management, 50, pp. 515-525, (2020); Gao J., Wang H., Shen H., Task failure prediction in cloud data centers using deep learning, IEEE Transactions on Services Computing, (2020); Gheisari M., Najafabadi H. E., Alzubi J. A., Gao J., Wang G., Abbasi A. A., Castiglione A., OBPP: An ontology-based framework for privacy-preserving in IoT-based smart city, Future Generation Computer Systems, 123, pp. 1-13, (2021); Gunasekaran A., Narayanasamy P., Analyzing the Network Performance of Various Replica Detection Algorithms in Wireless Sensor Network, Journal of Computational and Theoretical Nanoscience, 15, 3, pp. 989-994, (2018); Hwang Y. M., Lee K. C., Using an eye-tracking approach to explore gender differences in visual attention and shopping attitudes in an online shopping environment, International Journal of Human-Computer Interaction, 34, 1, pp. 15-24, (2018); Kesharwani S., Sharma N., Swaying between qualitative information and customers’ expectation: An assessment of online shopping sites in India, International Journal of Information Technology, 12, 3, pp. 789-795, (2020); Larson L. 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V., Multi-topic misinformation blocking with budget constraint on online social networks, IEEE Access: Practical Innovations, Open Solutions, 8, pp. 78879-78889, (2020); Rehman S. U., Bhatti A., Mohamed R., Ayoup H., The moderating role of trust and commitment between consumer purchase intention and online shopping behavior in the context of Pakistan, Journal of Global Entrepreneurship Research, 9, 1, pp. 1-25, (2019); Shamim K., Ahmad S., Alam M. A., COVID‐19 health safety practices: Influence on grocery shopping behavior, Journal of Public Affairs, 21, 4, (2021); Sharma S., Modeling the role of information on the spread of online shopping, Computational and Mathematical Methods, 3, 5, (2021); Smaldone F., D'Arco M., Marino V., Pellicano M., Brave Consumers for a New Digital World: Exploring Online Shopping Motives During Covid-19, The International Research & Innovation Forum, pp. 425-433, (2021); Soh P. Y., Heng H. B., Selvachandran G., Anh L. Q., Chau H. T. M., Son L. H., Abdel-Baset M., Manogaran G., Varatharajan R., Perception, acceptance, and willingness of older adults in Malaysia towards online shopping: A study using the UTAUT and IRT models, Journal of Ambient Intelligence and Humanized Computing, pp. 1-13, (2020); Tan G. W. H., Ooi K. B., Gender and age: Do they really moderate mobile tourism shopping behavior?, Telematics and Informatics, 35, 6, pp. 1617-1642, (2018); Yan X., Liu W., Lim M. K., Lin Y., Wei W., Exploring the factors to promote circular supply chain implementation in the smart logistics ecological chain, Industrial Marketing Management, 101, pp. 57-70, (2022); Zhao Y., Yu Y., Shakeel P. M., Montenegro-Marin C. E., Research on operational research-based financial model based on e-commerce platform, Information Systems and e-Business Management, pp. 1-17, (2021); Zhou M., Huang J., Wu K., Huang X., Kong N., Campy K. S., Characterizing Chinese consumers’ intention to use live e-commerce shopping, Technology in Society, 67, (2021)",null,null,"IGI Global",{"$nulls":5},1.5483673E7,null,null,null,"English","Int. J. e-Collab.","Article","Final","All Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85147729683"]
["Li J.","Li, Jialin (57255552800)",5.72555528E10,"A DYNAMIC PATH OPTIMIZATION MODEL OF IOT DELIVERY VEHICLES FOR E-COMMERCE LOGISTICS DISTRIBUTION",2023.0,"Scalable Computing",24.0,4.0,null,729.0,742.0,13.0,0.0,"10.12694/scpe.v24i4.2332","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85178441364&doi=10.12694%2fscpe.v24i4.2332&partnerID=40&md5=7e74f49373d93302c86ecb1a7c156abd","School of Management Engineering, Tangshan Polytechnic College, Tangshan, 063299, China","Li J., School of Management Engineering, Tangshan Polytechnic College, Tangshan, 063299, China","Logistics and distribution is a vital link to guarantee the stable supply of the e-commerce market and the healthy development of the industry. With the constant growth of the e-commerce, the efficiency and service quality of logistics and distribution have been paid more and more attention to. Therefore, the study firstly Considering distribution fixed cost, transportation penalty cost and carbon emission cost, the vehicle routing optimization model is transformed into the lowest transportation cost model, then uses an improved traditional artificial fish swarm algorithm to find the optimum way for this model, and finally verifies its performance and applicability through experiments. The performance test results show that the algorithm finds the optimal solution 3589 and 3590 in 63 and 78 iterations in the Oxford Robot Car dataset and Apollo Scape dataset, respectively; the average running time of the algorithm is 11.864s and 11.967s in the 10 operation time tests; in the operation function test, the algorithm. The algorithm was able to overcome the local optimal solution problem. The applicability simulation shows that this algorithm stabilizes after 53 iterations, the minimum cost of the optimal solution of the model is $41,224, and the total distance of distribution is 9035 km. The research algorithm is fast in finding the optimal value, which is close to it, indicating that the algorithm is highly efficient and reliable, and can greatly optimize the path of e-commerce logistics delivery vehicles, and give a theoretical foundation for the optimization of logistics delivery paths in other industries. © 2023 SCPE. All Rights Reserved.","Artificial Fish Swarm Algorithm; E-Commerce; Logistics and Distribution; Path Optimization","Costs; Electronic commerce; Internet of things; Optimization; Statistical tests; Vehicle routing; Vehicles; Artificial fishswarm algorithm(AFSA); Delivery vehicle; Dynamic paths; E- commerces; Logistic and distribution; Logistic distributions; Logistics delivery; Optimal solutions; Optimization models; Path optimizations; Optimal systems",{"$nulls":6},"Yang S., Optimization of Urban Logistics Distribution path under dynamic Traffic Network, International Core Journal Of Engineering, 6, pp. 243-248, (2020); Caso G. Alay, De Nardis L., Brunstrom A., Neri M., Di Benedetto M. G., Empirical Models For NB-IoT Path Loss, An Urban Scenario, 8, pp. 13774-13788, (2021); Lin C., Han G., Du J., Xu T., Shu L., Lv Z., Spatiotemporal congestion-aware path planning toward intelligent transportation systems in software-defined smart city loT, IEEE Internet Of Things Journal, 7, pp. 8012-8024, (2020); Guo Y., Mustafaoglu Z., Koundal D., Spam Detection Using Bidirectional Transformers and Machine Learning Classifier Algorithms, Journal Of Computational And Cognitive Engineering, 2, pp. 5-9, (2022); Keerthana G., Anandan P., Nachimuthu N., Robust hybrid artificial fish swarm simulated annealing optimization algorithm for secured free scale networks against malicious attacks, Comput. Mater, 66, pp. 903-917, (2021); Bai R., Chen X., Chen Z., Cui T., Gong S., He W., Zhang H., Analytics and machine learning in vehicle routing research, international Journal of Production Research, (2023); Abdirad M., Krishnan K., Gupta D., A two-stage metaheuristic algorithm for the dynamic vehicle routing problem in Industry 4.0 approach, journal of Management Analytics, (2021); Peng Y., Gao H., Path Optimization of Multi-trip Swap-body Vehicle Routing Problem with Time Window, journal of Transportation Systems Engineering & Information Technology, (2020); Dhanare R., Nagwanshi K., Varma S., Enhancing the route optimization using hybrid MAF optimization algorithm for the internet of vehicles, wireless Personal Communications, (2022); Bouziyane B., Dkhissi B., Cherkaoui M., Multiobjective optimization in delivering pharmaceutical products with disrupted vehicle routing problem, International Journal Of Industrial Engineering Computations, 11, pp. 299-316, (2020); Liu Y., Feng X., Yang Y., Ruan Z., Zhang L., Li K., Solving urban electric transit network problem by integrating Pareto artificial fish swarm, Journal of Intelligent Transportation Systems, (2022); Yin L., Yin H., Energy consumption parameter detection of green energy saving building based on artificial fish swarm algorithm, Journal Of Global Energy Issues, 44, pp. 498-510, (2022); Sheik Abdullah A., Assessment of risk factors in medical data using improved Binary Artificial Fish Swarm Algorithm with Classification upon Evaluation from F-Test, International Journal Of Swarm Intelligence Research (IJSIR), 13, pp. 1-26, (2022); Yuan M., Kan X., Chi C., Cao L., Shu H., Fan Y., An adaptive simulated annealing and artificial fish swarm algorithm for the optimization of multi-depot Intelligent Data Analysis, (2022); Bai S., Bao F., Zhao F., Liu M., Development of an Artificial Fish Swarm Algorithm Based on aWireless Sensor Networks in a Hydrodynamic Background, fluid Dynamics and Materials Processing, (2020); Srinivas T., Manivannan S., Black Hole and Selective Forwarding Attack Detection and Prevention in IoT in Health Care Sector: Hybrid meta-heuristic -based shortest path routing, Journal Of Ambient Intel ligence And Smart Environments, 13, pp. 133-156, (2021); Jain K., Saxena A., Simulation on supplier side bidding strategy at day-ahead electricity market using ant lion optimizer, journal of Computational and Cognitive Engineering, (2023); Mahantesh H., Guptha N., Optimized Path And Reduced Rule Caching Cost For Software Defined Network (SDN) Based Internet Of Things (IOT), Wireless Personal Communications, 120, pp. 2349-2365, (2021); Tirkolaee E., Goli A., Weber G., Fuzzy mathematical programming and self-adaptive artificial fish swarm algorithm for just-in-time energy-aware flow shop scheduling problem with outsourcing option, IEEE Transactions On Fuzzy Systems, 28, pp. 2772-2783, (2020); Tian Y., Li Y., Pan L., Research on group animation design technology based on artificial fish swarm algorithm, Journal Of Intelligent & Fuzzy Systems, 38, pp. 1137-1145, (2020)","J. Li; School of Management Engineering, Tangshan Polytechnic College, Tangshan, 063299, China; email: gzyljl@163.com",null,"West University of Timisoara",{"$nulls":5},1.8951767E7,null,null,null,"English","Scalable Comput. Pract. Exp.","Article","Final",null,"Scopus","2-s2.0-85178441364"]
["Chen X.I.N.","Chen, X.I.N. (58577595200)",5.85775952E10,"TIME WINDOW ORIENTED IOT VEHICLE PATHWAY STUDY FOR THE DYNAMICALLY CHANGING NEEDS OF E-COMMERCE CUSTOMERS",2023.0,"Scalable Computing",24.0,3.0,null,241.0,255.0,14.0,0.0,"10.12694/scpe.v24i3.2372","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85171301977&doi=10.12694%2fscpe.v24i3.2372&partnerID=40&md5=b337cb8f5da1be76c64a381d7bf86b81","Information Engineering College, Xinxiang Vocational and Technical College, Xinxiang, 453000, China","Chen X.I.N., Information Engineering College, Xinxiang Vocational and Technical College, Xinxiang, 453000, China","The main dynamic truck routing problem also presents a significant difficulty in the logistics sector, which is an unavoidable development trend of the contemporary technological changing society. A dynamic vehicle routing problem with time window model is suggested by the study in order to establish an effective and low-energy dynamic response method. The fundamental concept is to disrupt the conventional strategy of static dynamic consumers responding in time slots by dividing the dynamic time window into a static time window with several time slice intervals. The study makes use of cutting-edge ideas including dynamic attitude, before-and-after time slicing, and continuous optimisation while proposing a new method for model solution to optimise dynamic vehicle route issues effectively and affordably. The study employs the Solomon optimisation dataset and runs simulation studies on the Java platform to confirm its efficacy. The experimental findings demonstrated that the optimisation technique employed in the study reduced the cost of travelling by 83.8 miles while also considerably increasing the average vehicle utilisation by 3.6%. Because driving distance cost and vehicle number cost are typically positively connected with dynamic attitude, the study employs solutions that can increase dynamic response efficiency and save money. As a result, their robustness is higher. © 2023 SCPE","cost; dynamic demand; Internet of Things; path optimization; time windows","Computer software; Dynamic response; Dynamics; Optimization; Simulation platform; Vehicle routing; Vehicles; Changing needs; Development trends; Dynamic demand; Dynamic vehicle routing problems; E- commerces; Effective energy; Path optimizations; Routing problems; Time windows; Vehicle routing problem with time windows; Internet of things",{"$nulls":6},"Abdirad M., Krishnan K., Gupta D., Li X., A two-stage metaheuristic algorithm for the dynamic vehicle routing problem in industry 4.0 approach, Journal of Management Analysis, 8, pp. 69-83, (2021); Ambrosino D., Paolucci M., Special issue of networks: New network models and approaches for logistics and transportation, Networks, 78, pp. 227-228, (2021); Dai X., Chen M., Zhou Y., Optimal logistics transportation and route planning based on fpga processor real-time system and machine learning, Microprocessors and Microsystems, 80, (2021); Guo J., Long J., Xu X., Yuan M. Y., The vehicle routing problem of intercity ride-sharing between two cities, Transportation Research Part B: Methodological, 158, pp. 113-139, (2022); Himmich I., Hallaoui I. E., Soumis F., Primal column generation framework for vehicle and crew scheduling problems, Networks, 75, pp. 238-252, (2020); Li Y., Shen Y., Li J., A discrete artificial bee colony algorithm for stochastic vehicle scheduling, Complex System Modeling and Simulation, 2, pp. 238-252, (2022); Lin R., Huang H., Li M., An automated guided logistics robot for pallet transportation, Assembly Automation, 41, pp. 45-54, (2020); Merka Z., Perkov D., Bonin V., The significance of blockchain technology in digital transformation of logistics and transportation, International Journal of E-Services and Mobile Applications, 12, pp. 1-20, (2020); Olmez O. B., Gultekin C., Balcik B., Ozener A. E., A variable neighborhood search based matheuristic for a waste cooking oil collection network design problem, European Journal of Operational Research, 302, pp. 187-202, (2022); Ponmalar A., Dhanakoti V., Hybrid whale tabu algorithm optimized convolutional neural network architecture for intrusion detection in big data, Concurrency and computation: practice and experience, 34, pp. 7038-7052, (2022); Pottel S., Goel A., Scheduling activities with time-dependent durations and resource consumptions, European Journal of Operational Research, 301, pp. 445-457, (2022); Raeesi R., The electric vehicle routing problem with time windows and synchronised mobile battery swapping, Transportation Research Part B Methodological, 140, pp. 101-129, (2020); Coordinated routing of electric commercial vehicles with intra-route recharging and en-route battery swapping, European Journal of Operational Research, 301, pp. 82-109, (2022); Sbai I., Krichen S., A real-time decision support system for big data analytic: A case of dynamic vehicle routing problems, Procedia Computer Science, 176, pp. 938-947, (2020); Stellingwerf H. M., Lhc G., Laporte G., Behdani A. K. B., The quality-driven vehicle routing problem: Model and application to a case of cooperative logistics, International Journal of Production Economics, 231, (2021); Yang S., Ning L., Shang P., Tong L. C., Augmented lagrangian relaxation approach for logistics vehicle routing problem with mixed backhauls and time windows, Transportation Research Part E: Logistics and Transportation Review, 135, (2020); Zhang X., Chen L., Gendreau M., Langevin A., A branch-and-cut algorithm for the vehicle routing problem with two-dimensional loading constraints, European Journal of Operational Research, 302, pp. 259-269, (2022); Zhao Y., Du B., Li S., Agile satellite mission planning via task clustering and double-layer tabu algorithm, Computer Modeling in Engineering and Science, 122, pp. 235-257, (2020)","X.I.N. Chen; Information Engineering College, Xinxiang Vocational and Technical College, Xinxiang, 453000, China; email: chenx96321478@163.com",null,"West University of Timisoara",{"$nulls":5},1.8951767E7,null,null,null,"English","Scalable Comput. Pract. Exp.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85171301977"]
["Khandagale P.; Koh J.","Khandagale, Pooja (58536139200); Koh, Joon (35290464200)","58536139200; 35290464200","Effects of Digital Shadow Work on Foreign Users’ Emotions and Behaviors during the Use of Korean Online Shopping Sites",2023.0,"Asia Pacific Journal of Information Systems",33.0,2.0,null,389.0,417.0,28.0,0.0,"10.14329/apjis.2023.33.2.389","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85167896010&doi=10.14329%2fapjis.2023.33.2.389&partnerID=40&md5=3a900622f87138e728b83718ad1d3509","Department of Digital Future Convergence Service Interdisciplinary Program, Chonnam National University, South Korea; Department of Business Administration, Chonnam National University, South Korea","Khandagale P., Department of Digital Future Convergence Service Interdisciplinary Program, Chonnam National University, South Korea; Koh J., Department of Business Administration, Chonnam National University, South Korea","Social distancing required the use of doorstep delivery for nearly all purchases during the COVID-19 pandemic. Foreign users in Korea are forced to participate in superfluous tasks, leading to an increase in their anxiety and fatigue while online shopping. This study examines how digital shadow work stemming from the language barrier can affect the emotions and behaviors of foreign shoppers that use Korean shopping sites. By interviewing 37 foreign users in Korea, this draft examined their experiences, behaviors, and emotional output, classifying them into 14 codes and seven categories. Using grounded theory, we found that online shoppers’ emotions, feelings, experiences, and decision making may be changed in the stages of the pre-use, use, and post-use activities. User responses regarding shadow work and related obstacles can be seen with the continue, discontinue, and optional (occasional use) of Korean online shopping sites. Pleasure and satisfaction come from high efficiency and privileges, whereas anger and disappointment come from poor self-confidence and pessimism. Furthermore, buyer behavior and product orientation are identified as intervening conditions, while the online vs. offline shopping experiences are identified as contextual conditions. In conclusion, language barriers and other factors make online shopping difficult for foreign shoppers, which negatively affects their psychological mechanisms and buying behaviors. The implications from the study findings and future research are also discussed. © 2023, Asia Pacific Journal of Information Systems. All Rights Reserved.","Anxiety; Digital Shadow Work; Language Barrier; Online Shopping",{"$nulls":5},"Ministry of Education, MOE; National Research Foundation of Korea, NRF, (NRF-2021S1A3A 2A02089809)","This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2021S1A3A 2A02089809).","Agyapong H. 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L., Warrington P., An online pre purchase intentions model: The role of intention to search, Journal of Retailing, 77, 3, pp. 397-416, (2001); Venkatesh V., Speier-Pero C., Schuetz S. W., Why do people shop online? A comprehensive framework of consumers’ online shopping intentions and behaviours, Information Technology & People, 35, 5, pp. 1590-1620, (2022); Wang F., Head M., How can the web help build customer relationships? An empirical study on e-tailing, Information & Management, 44, 2, pp. 115-129, (2007); Weibin D., Ting S., Yiming Z., Chunli T., Factors affecting consumers’ online choice intention: A study based on Bayesian network, Frontiers in Psychology, 12, (2021); Wiesche M., Jurisch M. C., Yetton P. W., Krcmar H., Grounded theory methodology in information systems research, MIS Quarterly, 41, 3, pp. 685-701, (2017); Yamin M., Sinkovics R. R., Online internationalisation, psychic distance reduction and the virtuality trap, International Business Review, 16, 4, pp. 339-360, (2006)","J. Koh; Department of Business Administration, Chonnam National University, South Korea; email: kjoon@chonnam.ac.kr",null,"Korean Society of Management Information Systems",{"$nulls":5},2.2885404E7,null,null,null,"English","Asia Pac. J. Inf. Syst.","Article","Final",null,"Scopus","2-s2.0-85167896010"]
["Mahmoud S.J.H.; Noor N.M.B.M.; Bakar Z.A.","Mahmoud, Samar Jamal Hassan (58681441700); Noor, Noor Maizura Binti Mohamad (57216462971); Bakar, Zuriana Abu (8977769800)","58681441700; 57216462971; 8977769800","USER INTERFACE ANALYSIS AND A CASE STUDY OF E-COMMERCE IN JORDAN",2023.0,"Journal of Governance and Regulation",12.0,4.0,null,124.0,133.0,9.0,0.0,"10.22495/jgrv12i4art12","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85175701059&doi=10.22495%2fjgrv12i4art12&partnerID=40&md5=272e07a793df3c51f87c6b8f3fde88c9","Faculty of Ocean Engineering Technology and Informatics, Universiti Malaysia Terengganu (UMT), Kuala Nerus, Malaysia","Mahmoud S.J.H., Faculty of Ocean Engineering Technology and Informatics, Universiti Malaysia Terengganu (UMT), Kuala Nerus, Malaysia; Noor N.M.B.M., Faculty of Ocean Engineering Technology and Informatics, Universiti Malaysia Terengganu (UMT), Kuala Nerus, Malaysia; Bakar Z.A., Faculty of Ocean Engineering Technology and Informatics, Universiti Malaysia Terengganu (UMT), Kuala Nerus, Malaysia","This study conducts a systematic review of academic research on website user interfaces and e-commerce adoption in Jordan. The primary goal is to determine the most efficiently used characteristics of online user interfaces in terms of the most prominent journals, papers, and authors in the Jordanian context. Furthermore, a full content analysis of the 37 most influential publications is offered to identify important study qualities such as data characteristics, techniques, and major discoveries. The analysis identifies 177 papers on internet user interfaces from well-known journals. The findings demonstrate that academic papers are classified into five groups: 1) website design, 2) quality factors, 3) socio-psycho factors, 4) security issues, and 5) environmental variables. For future directions, it would be interesting to examine moderating/mediating elements, such as the technology acceptance model, with an emphasis on some characteristics such as competitiveness, delivery speed, quality, flexibility, and cost. The scholarly significance of this work comes in its thorough evaluation of website user interfaces and e-commerce adoption in Jordan, which provides useful insights and identifies relevant variables for future research and practical consequences. It adds to the existing literature and directs future academic research in this area. © 2023 The Authors.","E-Commerce; User Interfaces; Website",{"$nulls":7},"Abu-AlSondos I. A., Alkhwaldi A. F., Salhab H. A., Shehadeh M., Ali B. J. A., Customer attitudes towards online shopping: A systematic review of the influencing factors, International Journal of Data and Network Science, 7, 1, pp. 513-524, (2023); Alananzeh O. A., Almuhaisen F., Jawabreh O., Al Fahmawee E. A. D., Ali B. J. A., Ali A., The impact of job stability, work environment, administration, salary and incentives, functional justice, and employee expectation on the security staff‘s desire to continue working at the hotel, Journal of Statistics Applications & Probability, 12, 2, pp. 425-439, (2023); Al-Debei M. M., Akroush M. N., Ashouri M. I., Consumer attitudes towards online shopping: The effects of trust, perceived benefits, and perceived web quality, Internet Research, 25, 5, pp. 707-733, (2015); Alhaj A. A., Zanoon N. I., Alrabea A., Alnatsheh H. I., Jawabreh O., Abu-Fara M., Ali B. J. A., Improving the smart cities traffic management systems using VANETs and IoT features, Journal of Statistics Applications & Probability, 12, 2, pp. 405-414, (2023); Al-Qaisi L., Mesleh A., Al-Qaisi A., Sharadqh A., Zahran B., Alkasassbeh J., Olaimat M., Evaluation of e-commerce website functionality using a Mamdani fuzzy system, Engineering, Technology & Applied Science Research, 5, 5, pp. 860-863, (2015); Alqaraleh M. H., Almari M. O. S., Ali B., Oudat M. S., The mediating role of organizational culture on the relationship between information technology and internal audit effectiveness, Corporate Governance and Organizational Behavior Review, 6, 1, pp. 8-18, (2022); Alqaraleh M. H., Thuneibat N. S. M., Nour A., The factors affecting the adherence of Islamic accounting standards AAOIFI in Jordan, Journal of Governance & Regulation, 9, 4, pp. 69-75, (2020); Alrabei A. M., Al-Othman L. N., Al-Dalabih F. A. N., Taber T. A., Ali B., The impact of mobile payment on the financial inclusion rates, Information Sciences Letters, 11, 4, pp. 1033-1044, (2022); Al-Rawashdeh O. M., Jawabreh O., Ali B. J. A., Supply chain management and organizational performance: The moderating effect of supply chain complexity, Information Sciences Letters, 12, 3, pp. 1673-1684, (2023); Al-Tarawneh E. M., Alqaraleh M. H., Ali B. J. A., Bani Atta A. A., The impact of the efficiency and effectiveness of electronicaccounting information systems on the quality ofaccounting information, Information Sciences Letters, 12, 3, pp. 1685-1692, (2023); Bodker S., Through the interface: A human activity approach to user interface design, (2021); Cagnetti C., Gallo T., Silvestri C., Ruggieri A., Lean production and Industry 4.0: Strategy/management or technique/implementation? A systematic literature review, Procedia Computer Science, 180, pp. 404-413, (2021); Chiew K. L., Choo J. S.-F., Sze S. N., Yong K. S., Leverage website favicon to detect phishing websites, Security and Communication Networks, 2018, (2018); Daugherty P. J., Bolumole Y., Grawe S. J., The new age of customer impatience: An agenda for reawakening logistics customer service research, International Journal of Physical Distribution & Logistics Management, 49, 1, pp. 4-32, (2019); Doghan M., Albarq A., The effects of hedonic and utilitarian values on e-loyalty: Understanding the mediating role of e-satisfaction, International Journal of Data and Network Science, 6, 2, pp. 325-334, (2022); Dua P., Uddin S. F., Impact of perceived website cues on purchase experience and e-purchase intention of online apparel buyers, International Journal of Electronic Business, 17, 2, pp. 204-222, (2022); Hamzah M. H., Norain N. A. M., Abdullah A. H., Pronunciation research in the Malaysian context: A systematic review, LSP International Journal, 2, 1, pp. 63-73, (2015); Hasan L., Key design characteristics for developing usable e-commerce websites in the Arab world, Informing Science, 19, pp. 253-275, (2016); Jawabreh O., Shniekat N., Saleh M. M. A., Ali B., The strategic deployment of information systems attributes and financial performance in the hospitality industry, Information Sciences Letters, 11, 5, pp. 1419-1426, (2022); Khan A., Khusro S., Alam I., BlindSense: An accessibility-inclusive universal user interface for blind people, Engineering, Technology & Applied Science Research, 8, 2, pp. 2775-2784, (2018); Khashman N., Large A., Measuring cultural markers in Arabic government websites using Hofstede‘s cultural dimensions, DUXU 2011: Design, user experience, and usability. Theory, methods, tools and practice, pp. 431-439, (2011); Kim H., Fesenmaier D. R., Persuasive design of destination web sites: An analysis of first impression, Journal of Travel Research, 47, 1, pp. 3-13, (2008); Kumar A., Lata S., The system quality and customer satisfaction with website quality as mediator in online purchasing: A developing country perspectives, Journal of Operations and Strategic Planning, 4, 1, pp. 7-26, (2021); Lam D., Hoang T., Sajjanhar A., Identification of usability issues of interactive technologies in cultural heritage through heuristic evaluations and usability surveys, Multimodal Technologies and Interaction, 5, 12, (2021); Li Y., Zhao S., Bai L., Ali B. J., Institutional investor company social responsibility report and company performance, Applied Mathematics and Nonlinear Sciences, 7, 2, pp. 641-654, (2022); Majchrzak-Lepczyk J., Blaskova M., Value for the customer in the logistics service of e-commerce, SMART Supply Network, pp. 223-239, (2019); Misa T. J., Leonardo to the internet: Technology and culture from the renaissance to the present, (2022); Nawaiseh K. A., Alawamleh H., Al Shibly M., Almari M., Orabi T. A., Jerisat R., Ali B., Badadwa A., The relationship between the enterprise resource planning system and maintenance planning system: An empirical study, Information Sciences Letters, 11, 5, pp. 1335-1343, (2022); Park E. J., Kim E. Y., Funches V. M., Foxx W., Apparel product attributes, web browsing, and e-impulse buying on shopping websites, Journal of Business Research, 65, 11, pp. 1583-1589, (2012); Rahman R. U., Tomar D. S., A new web forensic framework for bot crime investigation, Forensic Science International: Digital Investigation, 33, (2020); Rosario A., Raimundo R., Consumer marketing strategy and E-commerce in the last decade: A literature review, Journal of Theoretical and Applied Electronic Commerce Research, 16, 7, pp. 3003-3024, (2021); Sekaran U., Bougie R., Research methods for business: A skill building approach, (2016); Shan R., Xiao X., Dong G., Zhang Z., Wen Q., Ali B., The influence of accounting computer information processing technology on enterprise internal control under panel data simultaneous equation, Applied Mathematics and Nonlinear Sciences, 8, 1, pp. 1685-1694, (2022); Shibly M., Alawamleh H. A., Nawaiseh K. A., Ali B. J., Almasri A., Alshibly E., The relationship between administrative empowerment and continuous improvement: An empirical study, Revista Gestão Inovação e Tecnologias, 11, 2, pp. 1681-1699, (2021); Shniekat N., AL Abdallat W., Al-Hussein M., Ali B., Influence of management information system dimensions on institutional performance, Information Sciences Letters, 11, 5, pp. 1435-1443, (2022); Thuneibat N. S. M., Ali B., Alqaraleh M. H., Thneibat H., The mediating role of innovation on the relationship between information technologies and reducing tax evasion, Information Sciences Letters, 11, 5, pp. 1359-1370, (2022); Zikmund W. G., Babin B. J., Carr J. C., Griffin M., Business research methods, (2012)",null,null,"Virtus Interpress",{"$nulls":5},2.2209352E7,null,null,null,"English","J. Govern. Reg.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85175701059"]
["Wahab S.N.; Tan A.; Roche O.","Wahab, Siti Norida (57204971443); Tan, Albert (57223655813); Roche, Olivier (55857717800)","57204971443; 57223655813; 55857717800","Comparison of Cross-Border Reverse Logistics of a Fast Fashion Brand in China",2023.0,"Operations and Supply Chain Management",16.0,1.0,null,25.0,35.0,10.0,0.0,"10.31387/oscm0520370","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85163498123&doi=10.31387%2foscm0520370&partnerID=40&md5=ab8880da43a939307063ac829d5b7ef3","Faculty of Business and Management, Universiti Teknologi MARA, Bandar Puncak Alam, Selangor, Malaysia; Asian Institute of Management, Makati, Philippines","Wahab S.N., Faculty of Business and Management, Universiti Teknologi MARA, Bandar Puncak Alam, Selangor, Malaysia; Tan A., Asian Institute of Management, Makati, Philippines; Roche O., Asian Institute of Management, Makati, Philippines","With the advent of \"Industry 4.0\" and the associated disruption caused by such rapid digital transformation, the logistics industry was able to develop cross-border delivery and increase demand for any given product. However, the risks associated with Cross-Border Reverse Logistics (CBRL) remain largely unexplored, and there is a paucity of research in this area. Hence, this study's objective is to investigate the e-commerce delivery system and CBRL model of a major fashion brand. The study is based on a case study approach comparing the CBRL processes of the Zara official site with one of their main channel partners, Alibaba. Data was collected through archival records, a secondary data bank and interviews with Zara representatives for a deeper analysis. The analysis reveals that both Zara and Alibaba's official sites currently have issues with their CBRL operations. The development of cross-border logistics represents a great opportunity to improve current Zara's and Alibaba's e-commerce platforms business model. In a very competitive market, a lack of a cross-border logistics system could represent a potential loss. Compared to local reverse logistics, cross-border remains at a relatively primitive stage. However, local reverse logistics can provide insights to Zara and Alibaba towards developing and improving CBRL. The case findings lay the foundation for a better understanding of CBRL e-commerce's challenges and support the need to optimize these systems to improve customer service in China. © 2023 Authors. All rights reserved.","cross-border; e-commerce; fast fashion industry; reverse logistics",{"$nulls":5},"FPP, (006/2021, 600-RMC/GPM SS 5/3 (077/2021); Faculty of Business and Management, Universiti Teknologi MARA; Universiti Teknologi MARA, UiTM, (600-TNCPI 5/3/DDF)","The authors gratefully acknowledge the financial support received from the Faculty of Business and Management, Universiti Teknologi MARA (UiTM), Grant/Award Number: 600-TNCPI 5/3/DDF (FPP) (006/2021) and 600-RMC/GPM SS 5/3 (077/2021).","Akan M., Erinc A., Guler M.G., Optimal Pricing And Inventory Strategies For Fashion Products Under Time-Dependent Interest Rate and Demand, Computers & Industrial Engineering, 154, (2021); Arrigo E., Global Sourcing in Fast Fashion Retailers: Sourcing Locations and Sustainability Considerations, Sustainability, 12, 2, (2020); Baek E., Lee H.K., Choo H.J., Cross-Border Online Shopping Experiences of Chinese Shoppers, Asia Pacific Journal of Marketing and Logistics, 32, 2, pp. 366-385, (2020); Bask A., Mervi L., Markku T., E-Commerce Logistics: A Literature Research Review and Topics for Future Research, International Journal of E-Services and Mobile Applications, 4, 3, pp. 1-22, (2012); Caro F., Jeremie G., Inventory Management of a Fast-Fashion Retail Network, Operations Research, 58, 2, pp. 257-273, (2010); Chan H.L., Choi T.M., Hui C.L., RFID Versus Bar-Coding Systems: Transactions Errors in Health Care Apparel Inventory Control, Decision Support Systems, 54, 1, pp. 803-811, (2012); Chen L., Yejun W., The Analysis of Cross-Border E-Commerce Strategic Develop Environment in Jinan, E-Commerce, 18, pp. 45-46, (2016); Chen N., Yang Y., The Impact of Customer Experience on Consumer Purchase Intention in Cross-Border E-Commerce-Taking Network Structural Embeddedness as Mediator Variable, Journal of Retailing and Consumer Services, 59, (2020); Chen Y.K, Chiu F.R., Liao H.C., Yeh C.H., Joint Optimization of Inventory Control and Product Placement on E-Commerce Websites Using Genetic Algorithms, Electronic Commerce Research, 16, 4, pp. 479-502, (2016); Choi T.M., Hui C.L., Liu N., Ng S.F., Yu Y., Fast Fashion Sales Forecasting With Limited Data and Time, Decision Support Systems, 59, pp. 84-92, (2014); Cui M., Li W., Cui L., Jia Y., Wu L., How Do Keystones Govern Their Business Ecosystems Through Resource Orchestration?, Industrial Management & Data Systems, (2022); Das D., Kumar R., Rajak M., Designing a Reverse Logistics Network for an E-Commerce Firm: A Case Study, Operations and Supply Chain Management: An International Journal, 13, 1, pp. 48-63, (2020); Gaur V., Saravanan K., Ananth R., Retail Inventory: Managing the Canary in the Coal Mine, California Management Review, 56, 2, pp. 55-76, (2014); Giuffrida M., Jiang H., Mangiaracina R., Investigating the Relationships Between Uncertainty Types and Risk Management Strategies in Cross-Border E-Commerce Logistics, The International Journal of Logistics Management, 32, 4, pp. 1406-1433, (2021); Giuffrida M., Riccardo M., Alessandro P., Angela T., Cross-Border B2C E-Commerce to Greater China and the Role Of Logistics: A Literature Review, International Journal of Physical Distribution & Logistics Management, 47, 9, pp. 772-795, (2017); Guerrero-Lorente J., Gabor A.F., Ponce-Cueto E., Omnichannel Logistics Network Design With Integrated Customer Preference for Deliveries and Returns, Computers & Industrial Engineering, 144, (2020); Gutierrez-Gutierrez L., de Leeuw S., Dubbers R., Logistics Services and Lean Six Sigma Implementation: A Case Study, International Journal of Lean Six Sigma, 7, 3, pp. 324-342, (2016); Han D., Yongjian Y., Dujuan W., Cheng T.C.E., Yunqiang Y., Integrated Production, Inventory, and Outbound Distribution Operations With Fixed Departure Times in A Three-Stage Supply Chain, Transportation Research Part E: Logistics and Transportation Review, 125, pp. 334-347, (2019); Hasan M.R., Yosef D., Tutul C.R., Yi F., Inventory Management With Online Payment and Preorder Discounts, Industrial Management & Data Systems, 120, 11, pp. 2001-2023, (2020); Hayakawa K., Mukunoki H., Urata S., Can E-Commerce Mitigate the Negative Impact of COVID-19 on International Trade?, The Japanese Economic Review, pp. 1-18, (2021); Hu Y., Rui M., Qianqian L., Study On Location Selection and Transportation Planning of Overseas Warehouse Considering Location Coordination, Chinese Journal of Management Science, (2021); Huang G.Q., Rene D.K., Yugang Y., Editorial: Online-to-Offline E-Commerce Operations Management (EOM), Transportation Research Part E: Logistics and Transportation Review, 138, 101920, (2020); Huo B., Haq M.Z.U., Gu M., The Impact of IT Application on Supply Chain Learning and Service Performance, Industrial Management & Data Systems, 120, 1, pp. 1-20, (2020); 2020 Annual Report, (2020); Jahed M.A., Quaddus M., Suresh N.C., Salam M.A., Khan E.A., Direct and Indirect Influences of Supply Chain Management Practices on Competitive Advantage in Fast Fashion Manufacturing Industry, Journal of Manufacturing Technology Management, 33, 3, pp. 598-617, (2022); Jaipuria S., Mahapatra S.S., An Improved Demand Forecasting Method to Reduce Bullwhip Effect in Supply Chains, Expert Systems with Applications, 41, 5, pp. 2395-2408, (2014); Jalil E.A., Pursuing Sustainability via Reverse Logistics: The Symbiosis Effect Between the Local Authorities and Householders, Operations and Supply Chain Management: An International Journal, 11, 1, pp. 26-35, (2017); Jian J., Lv L., Wan L., Exploring consumer Purchase Intention In Cross-Border E-Commerce: Evidence From ‘Belt And Road’ Countries, Asia Pacific Journal of Marketing and Logistics, (2022); Kalpoe R., Technology Acceptance and Return Management In Apparel E-Commerce, Journal of Supply Chain Management Science, 1, 3-4, pp. 118-137, (2020); Li Y., Analysis on the Cross-Border E-Commerce Under COVID-19, Advances in Social Science, Education and Humanities Research, pp. 147-150, (2021); Li Y., Chu F., Chu C., Zhu Z., An Efficient Three-Level Heuristic for the Large-Scaled Multi-Product Production Routing Problem with Outsourcing, European Journal of Operational Research, 272, 3, pp. 914-927, (2018); Lin Q., Research on Development of Cross-Border E-Commerce Overseas Warehouses in China in Big Data, Logistic sci-tech, 7, pp. 68-71, (2021); 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Yang Z., Qiang S., Current Status and Trend Analysis of China’s Import Cross-border E-commerce Development, Proceedings of the 2015 International Conference on Education Technology, Management and Humanities Science, (2015); Zaid A.A., Jaaron A.A.M., Talib Bon A., The Impact of Green Human Resource Management and Green Supply Chain Management Practices on sustainable Performance: an Empirical Study, Journal of Cleaner Production, 204, pp. 965-979, (2018); Zhang H., Research on the Development Strategy Go Overseas Warehouses Assisting Cross Border E-Commerce Under the Covid-19 Pandemic, E-commerce, 17, pp. 53-55, (2021); Zhang Q., Analysis on the Development Status and Countermeasures of Cross-Border E-Commerce Logistics in the Context of Big Data, China Management Informationization, 24, 18, pp. 82-83, (2021)","S.N. Wahab; Faculty of Business and Management, Universiti Teknologi MARA, Selangor, Bandar Puncak Alam, Malaysia; email: sitinorida23@uitm.edu.my",null,"Operations and Supply Chain Management Forum",{"$nulls":5},1.9793561E7,null,null,null,"English","Operations Supply Chain Manag.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85163498123"]
["Liu W.; Alqhatani A.; Asiri F.; Salwana E.","Liu, Weiguang (58634523500); Alqhatani, Abdulmajeed (57202047555); Asiri, Fatima (58117783400); Salwana, Ely (57194512218)","58634523500; 57202047555; 58117783400; 57194512218","Customer preference analysis towards online shopping decisions based on optimized feature extraction",2023.0,"Expert Systems",{"$nulls":6},0.0,"10.1111/exsy.13460","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85173451700&doi=10.1111%2fexsy.13460&partnerID=40&md5=70476256eab44f31c583b1b2a7690390","Jiuzhou Polytechnic, XuZhou, China; Department of Information Systems, College of Computer Science and Information Systems, Najran University, Najran, Saudi Arabia; Department of Information Systems, College of Computer Science, King Khalid University, Abha, Saudi Arabia; Institute of Visual Informatics, Universiti Kebangsaan Malaysia, Bangi, Malaysia","Liu W., Jiuzhou Polytechnic, XuZhou, China; Alqhatani A., Department of Information Systems, College of Computer Science and Information Systems, Najran University, Najran, Saudi Arabia; Asiri F., Department of Information Systems, College of Computer Science, King Khalid University, Abha, Saudi Arabia; Salwana E., Institute of Visual Informatics, Universiti Kebangsaan Malaysia, Bangi, Malaysia","Online shopping has become an essential part of modern life, with food delivery being one of the most popular services. In this study, we investigate the factors influencing customers' preferences in online food ordering, such as easy payment, customization, and fast delivery. Analysing customer ratings and reviews is crucial in ensuring the quality of food services and promoting a healthy lifestyle. However, the trustworthiness of online reviews remains a challenge. Based on their rating, new customers can get help from online shoppers for their preferences or demands. Data are collected from customer reviews through online platforms to improve food service quality in online shopping. This work aims to predict the preferences of customers in online shopping based on optimized feature extraction using Principal Component Analysis with a Social Spider Optimization (PCA-SSO) algorithm. Despite existing algorithms for analysing customer preferences, most may have inaccurate predictions or take time to analyse data. To overcome these challenges, this model of PCA-SSO is proposed to predict customers' more accurate online shopping preferences. This model provides valuable implications for online shopping owners regarding customer satisfaction. Compared to the accuracy rates of KNN (78.22%), LDA (83.16%), and PCA (88.56%) algorithms, our proposed algorithm of PCA-SSO achieved a higher accuracy of 93.54%. © 2023 John Wiley & Sons Ltd.","customer preference; online shopping; principal component analysis; social spider optimization algorithm","Customer satisfaction; Electronic commerce; Extraction; Feature extraction; Forecasting; Sales; Customer preferences; Decision-based; Features extraction; Foodservices; Online shopping; Optimisations; Optimization algorithms; Preference analysis; Principal-component analysis; Social spider optimization algorithm; Principal component analysis",{"$nulls":6},"Ahani A., Nilashi M., Yadegaridehkordi E., Sanzogni L., Tarik A.R., Knox K., Samad S., Ibrahim O., Revealing customers' satisfaction and preferencesthrough online review analysis: The case of Canary Islands hotels, Journal of Retailing and Consumer Services, 331-343, pp. 51-343, (2019); Ali Mohammadirokni M., Emadlou A., Yuan J.J., The strategic resources of a gastronomy creative city: The case of San Antonio, Texas, Journal of Gastronomy and Tourism, 5, 4, pp. 237-252, (2021); Ara J., Hasan M.T., Al Omar A., Bhuiyan H., Understanding customer sentiment: Lexical analysis of restaurant reviews. 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A multilevelapproach, International Journal of Contemporary Hospitality Management, 2019, 31, pp. 953-977, (2019); Libai B., Bart Y., Gensler S., Hofacker C.F., Kaplan A., Kotterheinrich K., Kroll E.B., Brave new world? On AI and themanagement of customer relationships, Journal of Interactive Marketing, 51, pp. 44-56, (2020); Liu X., Shi T., Zhou G., Liu M., Yin Z., Yin L., Zheng W., Emotion classification for short texts: An improved multi-label method. Humanities and social sciences, Communications, 10, 1, (2023); Liu X., Tong D., Huang J., Zheng W., Kong M., Zhou G., What matters in the e-commerce era? Modelling and mapping shop rents in Guangzhou, China, Land Use Policy, 123, (2022); Luo Y., Xu X., Predicting the helpfulness of online restaurant reviews using different machine learning algorithms: A case study of yelp, Sustainability, 11, (2019); Mathayomchan B., Taecharungroj V., How was your meal? Examining customer experience using Google maps reviews, International Journal of Hospitality Management, 90, (2020); Nagpal M., Kansal K., Chopra A., Gautam N., Jain V.K., Effective approach for sentiment analysis of food delivery apps, Advances in intelligent systems and computing, pp. 527-536, (2020); Ni Q., Guo J., Wu W., Wang H., Wu J., Continuous influence-based community partition for social networks, IEEE Transactions on Network Science and Engineering, 9, 3, pp. 1187-1197, (2022); Nie W., Bao Y., Zhao Y., Liu A., Long dialogue emotion detection based on commonsense knowledge graph guidance, IEEE Transactions on Multimedia, pp. 1-15, (2023); Qin X., Liu Z., Liu Y., Liu S., Yang B., Yin L., Liu M., Zheng W., User OCEAN personality model construction method using a BP neural network, Electronics, 11, 19, (2022); Rababah M., Maydanchi M., Pouya S., Basiri M., Azad A.N., Haji F., Aminjarahi M., Data visualization of traffic violations in Maryland, US. arXiv preprint arXiv:2208.10543, (2022); Shaeeali N.S., Mohamed A., Mutalib S., Customer reviews analytics on food delivery services in social media: A review, IAES International Journal of Artificial Intelligence, 2020, 9, pp. 691-699, (2020); Skinner H., Chatzopoulou E., Gorton M., Perceptions of localness and authenticity regarding restaurant choice in tourism settings, Journal of Travel & Tourism Marketing, 2020, 37, pp. 155-168, (2020); Suciati A., Budi I., Aspect-based sentiment analysis and emotion detection for code-mixed review, International Journal of Advanced Computer Science and Applications, 2020, 11, pp. 179-186, (2020); Suhartanto D., Helmi Ali M., Tan K.H., Sjahroeddin F., Kusdibyo L., Loyalty toward online food delivery service: The role ofE-service quality and food quality, Journal of Foodservice Business Research, 22, pp. 81-97, (2019); Sun J., Li S., Xu C., Liu J., Simulation analysis and optimization of garment manufacturing process based on Em-plant software, Journal of Computational Methods in Sciences and Engineering, 21, pp. 1727-1738, (2021); Tian G., Lu L., McIntosh C., What factors affect consumers' dining sentiments and their ratings: Evidence from restaurant onlinereview data, Food Quality and Preference, 88, (2021); Wang H., Cui Z., Liu R., Fang L., Sha Y., A multi-type transferable method for missing link prediction in heterogeneous social networks, IEEE Transactions on Knowledge and Data Engineering, pp. 1-13, (2023); Wang X., Zhao C., Wang Y., Xiao H., Multi objective optimization model and algorithm of logistics service transaction matching on Blockchain platform, Journal of Computational Methods in Sciences and Engineering, 21, pp. 1843-1855, (1843); Xie X., Jin X., Wei G., Chang C., Monitoring and early warning of SMEs' shutdown risk under the impact of global pandemic shock, Systems, 11, 5, (2023); Xu J., Guo K., Sun P.Z.H., Driving performance under violations of traffic rules: Novice vs. Experienced Drivers. IEEE Transactions on Intelligent Vehicles, (2022); Xu J., Pan S., Sun P.Z.H., Park S.H., Guo K., Human-factors-in-driving-loop: Driver identification and verification via a deep learning approach using psychological behavioral data, IEEE Transactions on Intelligent Transportation Systems (IEEE-TITS), 24, 3, pp. 3383-3394, (2022); Xu J., Zhang X., Park S.H., Hu J., The improvement of road driving safety guided by visual In attentional blindness, IEEE Transactions on Intelligent Transportation Systems, 23, 6, pp. 4972-4981, (2022); Zenggang X., Mingyang Z., Xuemin Z., Sanyuan Z., Fang X., Xiaochao Z., Yunyun W., Xiang L., Social similarity routing algorithm based on socially aware networks in the big data environment, Journal of Signal Processing Systems, 94, pp. 1253-1267, (2022); Zhu H., Xue M., Wang Y., Yuan G., Li X., Fast visual tracking with Siamese oriented region proposal network, IEEE Signal Processing Letters, 29, pp. 1437-1441, (2022); Zuhaib M., Shaikh F.A., Energies, 15, 21, (2022)","W. Liu; Jiuzhou Polytechnic, XuZhou, 221116, China; email: 00978@jzp.edu.cn",null,"John Wiley and Sons Inc",{"$nulls":5},2664720.0,null,"EXSYE",null,"English","Expert Syst","Article","Article in press",null,"Scopus","2-s2.0-85173451700"]
["Yanhong L.; Jianxiong Z.","Yanhong, Liu (58283762200); Jianxiong, Zhang (57218664691)","58283762200; 57218664691","The impact of internet celebrity live delivery on the profitability of sales enterprises; [网红带货对销售企业盈利影响研究]",2023.0,"Journal of Industrial Engineering and Engineering Management",37.0,3.0,null,60.0,68.0,8.0,0.0,"10.13587/j.cnki.jieem.2023.03.006","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85159871935&doi=10.13587%2fj.cnki.jieem.2023.03.006&partnerID=40&md5=cca5196c3025008696ab3f34e71201f3","Department of Management and Economics, Tianjin University, Tianjin, 300072, China","Yanhong L., Department of Management and Economics, Tianjin University, Tianjin, 300072, China; Jianxiong Z., Department of Management and Economics, Tianjin University, Tianjin, 300072, China","Due to the absence of physical evaluation in online shopping, consumers have no idea about the exact value of products. In recent years, the business model of “weblebrity marketing” has been widely introduced by online brands to alleviate consumers′ uncertainty about product value. Weblebrities with influence and product selection skills are hired to promote and sell products to consumers in real time on livestreaming platforms. As proven, the collaboration between weblebrities and brands is a success and brings huge benefits. In the pre-sale on November 11, 2021, Li Jiaqi and Viya reached a cumulative trading value of RMB 10. 653 billion and 8. 552 billion, respectively. However, the prosperity of “weblebrity marketing” combines some things to watch out for. Compared with the previous sales model, “weblebrity marketing” is frequently accompanied by a higher return rate. China Consumer News reported an alarming return rate of 40% for some weblebrities. According to a report published by China Consumers Association in 2020, 60. 5% of respondents who refuse to buy through “weblebrity marketing” were concerned about the quality of products, and 44. 1% felt there was an extensive impulse purchase. When selling products, brands are not sure whether their products are of high or low value to consumers. After the production selection of weblebrities, brands enter into a partnership with them and have them convince consumers in the market that the products are of high value. Through observation, there are two types of consumers, namely rational consumers and impulsive consumers. Based on prior information about a product′s value and the weblebrity′s ability to select products, rational consumers perform Bayesian updates to get posterior information about the product and decide whether to buy it or not. Impulse consumers, by contrast, buy into the hype of weblebrities. For each transaction, the weblebrity is rewarded with a commission. After receiving the product, consumers decide whether to return it based on its true value. Where returns occur, they have to pay certain costs (e. g. hassle and mailing costs) before being refunded in full. The brand will receive the product, but will not ask the weblebrity to return the commission for the transaction. In spite of the academic concerns about “ weblebrity marketing”, scholars have mostly conducted research through qualitative rather than quantitative analysis. In view of this, this paper builds a mathematical model to address the following two questions: (1) How does the ability of weblebrities to select products affect the pricing and profitability of brands? (2) How does the proportion of impulsive consumers in the market affect the pricing and profitability of brands? In this paper, a Bayesian update model of consumers is established. Through the sales model of “weblebrity marketing”, brands sell their products to a market of rational and impulsive consumers. Watching the weblebrities′ judgment on the value of products, consumers are faced with the first decision-making, i. e., to buy or to give up. After the purchase, consumers decide whether to return or keep the product. Impulsive consumers completely trust weblebrities′ propaganda, while rational consumers make estimates of product value based on a priori information and weblebrities′ product selection ability. According to their behavior in the marketplace, consumers are classified into three types: (1) Type A, who keeps all the products they buy, regardless of their actual value; (2) Type B, who keeps the high-value products they buy and return the low-value ones; and (3) Type C, who returns all the products they buy. It goes in a sequence that: weblebrities announce the high value of products, rational and impulsive consumers enter the market and decide whether to buy the products, weblebrities make profits, rational and impulsive consumers decide whether to return the products, and brands make profits. This paper identifies how weblebrities′ product selection ability and impulse consumers′ proportion in the market affect brands′ profitability, especially brands should work with weblebrities with what selection ability and they should develop what pricing strategies in markets with different proportions of impulse consumers. Conclusions are: First, brands′ profits are non-monotonically correlated with weblebrities′ product selection ability at low proportions of impulse consumers; incrementally correlated with weblebrities′ product selection ability at high proportions of impulse consumers. Second, brands′ profits are decreasingly correlated with impulse consumers′ proportion at low selection ability of weblebrities; non-monotonically correlated with impulse consumers′ proportion at medium selection ability of weblebrities; and increasingly correlated with impulse consumers′ proportion at high selection ability of weblebrities. The findings have considerable implications for management: First, brands should minimize returns by reducing consumer uncertainty about product value rather than changing prices. Second, in the product sales model of “weblebrity marketing”, brands should attach importance to weblebrities′ product selection ability and impulse consumers′ proportion in the market. Specifically, markets with a small proportion of impulsive consumers are more beneficial to brands when the weblebrities they cooperate with are less able to select products. The more impulse consumers there are, the lower the price of products. Conversely, markets with a large proportion of impulsive consumers are more beneficial to brands when the selected weblebrities are good at selecting products. The more impulse consumers there are, the higher the price should be. Lastly, the higher the commission for weblebrities they cooperate with, the lower the price brands should set © 2023, Journal of Industrial Engineering and Engineering Management.All Rights Reserved.","Bayesian update; Internet celebrity live delivery; Pricing; Return policy",{"$nulls":5},"National Natural Science Foundation of China, NSFC, (71971152)","Received Date: 2021-05-02 　 　 　 Funded Project: Supported by the National Natural Science Foundation of China (71971152). ∗Corresponding author","Feng J，Li X，, Zhang X Q, Online Product Reviews-Triggered Dynamic Pricing: Theory and Evidence[J ], Information Systems Research, 30, 4, pp. 1107-1123, (2019); Kwark Y，, Chen J Q，, Raghunathan S., Online Product Reviews: Implications for Retailers and Competing Manufacturers [J], Information Systems Research, 25, 1, pp. 93-110, (2014); Sahoo N，, Dellarocas C，, Srinivasan S., The Impact of Online Product Reviews on Product Returns [J], Information Systems Research, 29, 3, pp. 723-738, (2018); Ananthakrishnan U M，, Li B B，, Smith M D., A Tangled Web: Should Online Review Portals Display Fraudulent Reviews? [J], Information Systems Research, 31, 3, pp. 950-971, (2020); Ke Z H, Daniel J B., Do Online Friends Bring Out the Best in Us? The Effect of Friend Contributions on Online Review Provision [J], Information Systems Research, 31, 4, pp. 1322-1336, (2020); Liu Y，, Liao X W，, Liu Y., The influence of online reviews on application software and platform pricing strategies[J], Journal of Systems Engineering, 29, 4, pp. 560-570, (2014); Na R S，, Cui X L., Study on the model of emotional information dissemination of online word-of-mouth products on social networks [J], Journal of Systems Engineering, 34, 3, pp. 324-334, (2019); Proserpio D，, Zervas G., Online Reputation Management: Estimating the Impact of Management Responses on Consumer Reviews, Marketing Science, 36, 5, pp. 645-665, (2017); Yin D Z, Mitra S, Zhang H., Research Note-When Do Consumers Value Positive vs. Negative Reviews? An Empirical Investigation of Confirmation Bias in Online Word of Mouth, Information Systems Research, 27, 1, pp. 131-144, (2016); Zhang F L, Zhang Y, Xu X L., Research on Retailer's Return Strategy Based on Strategic Customer Behavior, Journal of Management Science, 20, 11, pp. 100-113, (2017); Letizia P, Pourakbar M, Harrison T., The Impact of Consumer Returns on the Multichannel Sales Strategies of Manufacturers[J], Production & Operations Management, 27, 2, pp. 323-349, (2018); Zhao S S, Wu F, Shu L., E-commerce companies considering the return of goods to decide on the promised delivery date and effort level [J], Journal of Management Engineering, 33, 3, pp. 101-108, (2019); Tran T, Gurnani H, Desiraju R., Optimal Design of Return Policies [J], Marketing Science, 37, 4, pp. 649-667, (2018); Nageswaran L, Cho S H, Alan S W., Consumer Return Policies in Omnichannel Operations [J], Management Science, 66, 12, pp. 5558-5575, (2020); Ertekin N, Michael E K, Gregory R H., Assessing Impacts of Store and Salesperson Dimensions of Retail Service Quality on Consumer Returns [J], Production and Operations Management, 29, 5, pp. 1232-1255, (2020); Wang Y F, Tian Z J, Xie J P., Research on Pre-sale and Return Strategy Based on Strategic Consumers[J], Journal of Management Engineering, 34, 1, pp. 79-85, (2020); Shi G Q, Wang Y, Duan Y L, Et al., Research on the contract selection between manufacturers and e-commerce platforms in the case of direct sales channels [J], Journal of Management Engineering, 35, 1, pp. 179-188, (2021); Zhong L, Nie J J., The impact of manufacturer's risk hedging mechanism on opening direct sales channels [J], Journal of Management Engineering, 35, 3, pp. 220-228, (2021)",null,null,"Zhejiang University",{"$nulls":5},1.0046062E7,null,null,null,"English","J. Industrial Eng. Eng. Management","Article","Final",null,"Scopus","2-s2.0-85159871935"]
["Yang G.; He X.","Yang, Ge (58627659200); He, Xingwang (58628197500)","58627659200; 58628197500","Enhancing the Efficacy of Pharmaceutical E-Commerce Through Omni-Channel Coordination",2023.0,"International Journal of Information Systems and Supply Chain Management",16.0,1.0,null,1.0,20.0,19.0,0.0,"10.4018/IJISSCM.330147","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85172927821&doi=10.4018%2fIJISSCM.330147&partnerID=40&md5=8d8577df9ca22756dbc77f47c9f597f4","Anhui Business College, China","Yang G., Anhui Business College, China; He X., Anhui Business College, China","In the current era of e-commerce, the pharmaceutical industry has not experienced the same level of growth as regular commodities due to the high costs associated with home delivery and the perceived risks associated with purchasing drugs online. This paper proposes an omni-channel strategy to address these challenges, involving an “order online, home-delivery offline” approach between e-pharmacies and drugstores, with telemedicine serving as a coordination mechanism between e-pharmacies and hospital doctors. The proposed strategy achieves a seamless patient experience during online diagnosis. To analyze its feasibility, the paper employs optimization techniques to compare the profits of supply chain members in both omni-channel and non-omni-channel scenarios. The results demonstrate that the proposed strategy is both practical and efficient, boosting patients’ trust in e-commerce and improving the profitability of the pharmaceutical industry. © 2023 IGI Global. All rights reserved.","Home-Delivery; Imbalanced; Omni-Channel Coordination Strategy; Pharmaceutical E-Commerce; Three-Channel","Controlled drug delivery; Diagnosis; Electronic commerce; Supply chains; Targeted drug delivery; 'current; Channel coordination; Coordination strategy; E- commerces; Home delivery; Imbalanced; Omni-channel coordination strategy; Pharmaceutical E-commerce; Pharmaceutical industry; Three channel; Profitability",{"$nulls":4},"Nature Science Foundation of Anhui Educational Committee, (KJ2021A1480)","This work was supported by the Nature Science Foundation of Anhui Educational Committee (Grant No. KJ2021A1480).","Brynjolfsson E., Hu Y. J., Rahman M. S., Competing in the age of omnichannel retailing, (2013); Chen J., Chen B., When should the offline retailer implement price matching?, European Journal of Operational Research, 277, 3, pp. 996-1009, (2019); Chen M. W., Beijing patients to pay less for drugs, more for doctors, (2017); Chen X., The current status and development countermeasures of online pharmacies in China, Open Journal of Social Sciences, 6, 4, pp. 224-231, (2018); Gao F., Su X., Omnichannel retail operations with buy-online-and-pick-up-in-store, Management Science, 63, 8, pp. 2478-2492, (2016); He Y., Xu Q., Wu P., Omnichannel retail operations with refurbished consumer returns, International Journal of Production Research, 58, 1, pp. 271-290, (2020); Hughes C. M., McElnay J. C., Fleming G. F., Benefits and risks of self medication, Drug Safety, 24, 14, pp. 1027-1037, (2001); Jiang Y., Liu L., Lim A., Optimal pricing decisions for an omni‐channel supply chain with retail service, International Transactions in Operational Research, 27, 6, pp. 2927-2948, (2020); Kim J. C., Chun S. 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C., Using online user-generated reviews to predict offline box-office sales and online DVD store sales in the O2O era, Journal of Theoretical and Applied Electronic Commerce Research, 14, 1, pp. 68-83, (2019); Li C., Huang Z., Subsidy strategy of pharmaceutical e-commerce platform based on two-sided market theory, PLoS One, 14, 10, (2019); Li F., Li S., Gu J., Whether to delay the release of ebooks or not? An analysis of optimal publishing strategies for book publishers, Journal of Theoretical and Applied Electronic Commerce Research, 14, 2, pp. 124-137, (2019); Liao P., Ye F., Wu X., A comparison of the merchant and agency models in the hotel industry, International Transactions in Operational Research, 26, 3, pp. 1052-1073, (2019); Liu L., Feng L., Xu B., Deng W., Operation strategies for an omni-channel supply chain: Who is better off taking on the online channel and offline service?, Electronic Commerce Research and Applications, 39, (2020); Liu X., Xu Y. C., Yang X., Disease profiling in pharmaceutical e-commerce, Expert Systems with Applications, 178, (2021); Luo Y., Li Y., Ye Q., Impacts of online additional reviews on the sales volume of cross-border pharmaceutical e-commerce platforms, Journal of Global Information Technology Management, 25, 1, pp. 83-101, (2022); Srivastava M. S., Bhadauria A., Dhaneshwar S., E commerce in pharmaceutical business in India: Prospects & challenges, International Journal of Research and Analytical, (2018); Tang W., Xie J., Lu Y., Liu Q., Malone D., Ma A., Effects on the medical revenue of comprehensive pricing reform in Chinese urban public hospitals after removing drug markups: Case of Nanjing, Journal of Medical Economics, 21, 4, pp. 326-339, (2018); Tao Z., Gou Q., Zhang J., A local seller’s app channel strategy concerning delivery, International Journal of Production Research, 58, 1, pp. 220-255, (2020); Wang P., Zhang R., Tang B., Pricing model and influential factors analysis of drug trade service platform, LISS, pp. 221-226, (2015); Wang Y., Mei S., Xu R., Yang D., Zhong W., Channel competition in omni‐channel supply chain considering social media advertising, Managerial and Decision Economics, 44, 6, pp. 3354-3366, (2023); Wu J., Dong M., Research on customer satisfaction of pharmaceutical e-commerce logistics service under service encounter theory, Electronic Commerce Research and Applications, 58, (2023); Xu Q., Wang W. J., Liu Z., Tong P., The influence of online subsidies service on online-to-offline supply chain, Asia-Pacific Journal of Operational Research, 35, 2, (2018); Yu X., Wang S., Zhang X., Ordering decision and coordination of a dual-channel supply chain with fairness concerns under an online-to-offline model, Asia-Pacific Journal of Operational Research, 36, 2, (2019); Zhang P., He Y., Zhao X., “Preorder-online, pickup-in-store” strategy for a dual-channel retailer, Transportation Research Part E, Logistics and Transportation Review, 122, pp. 27-47, (2019); Zhang S., Zhu L., Drugs quality supervision strategy of different distribution channels in pharmaceutical supply chain, Frontiers in Public Health, 10, (2022); Zhang T., Li G., Cheng T. C. E., Shum S., Consumer inter‐product showrooming and information service provision in an omni‐channel supply chain, Decision Sciences, 51, 5, pp. 1232-1264, (2020); Zhang W. Y., Transaction value of medical e-commerce in China 2016 to 2021, Statista, (2023)",null,null,"IGI Global",{"$nulls":5},1.9355726E7,null,null,null,"English","Int. J. Inf. Syst. Supply Chain Manage.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85172927821"]
["Garola G.; Siragusa C.; Seghezzi A.; Mangiaracina R.","Garola, Giovanni (58483227800); Siragusa, Chiara (57204969259); Seghezzi, Arianna (57204964677); Mangiaracina, Riccardo (35325033800)","58483227800; 57204969259; 57204964677; 35325033800","Managing COVID-19 disruption: the response of express couriers and lessons learned to improve resilience",2023.0,"International Journal of Logistics Management",34.0,7.0,null,121.0,141.0,20.0,2.0,"10.1108/IJLM-03-2022-0114","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85164474438&doi=10.1108%2fIJLM-03-2022-0114&partnerID=40&md5=5ba60062efefad358c7e2a0f9a7a1632","Department of Management, Economics and Industrial Engineering, Politecnico di Milano, Milan, Italy","Garola G., Department of Management, Economics and Industrial Engineering, Politecnico di Milano, Milan, Italy; Siragusa C., Department of Management, Economics and Industrial Engineering, Politecnico di Milano, Milan, Italy; Seghezzi A., Department of Management, Economics and Industrial Engineering, Politecnico di Milano, Milan, Italy; Mangiaracina R., Department of Management, Economics and Industrial Engineering, Politecnico di Milano, Milan, Italy","Purpose: Coronavirus disease 2019 (COVID-19) led most companies to redefine their sales channels, pushing toward e-Commerce. This increase in the online sales of products resulted in significant pressure on the logistics sector. The purpose of this paper is to investigate how express couriers responded to the pandemic period and allowed for business continuity. Design/methodology/approach: A multiple case study involving five express couriers was conducted. Collected information was coded, then a framework is proposed to discuss the results with the support of the resource-based view and dynamic capabilities view concepts. Findings: The study highlights how couriers leveraged most of their resources to respond to the pandemic threat. Four recurrent continuity enablers to foster the reconfiguration of resources were identified. Specifically, the study points out the key role of employees, digital technologies, visibility and knowledge as enablers that played a crucial role toward continuity. In addition, valuable lessons learned by practitioners to foster resilience in future disruption are highlighted. Originality/value: Concerning academia, the present research aims to be among the first ones to provide empirical and practical insights on the impact of COVID-19 among express couriers. Considering practitioners, it identifies lessons learned that could be applied to the sector in future disruption. © 2023, Giovanni Garola, Chiara Siragusa, Arianna Seghezzi and Riccardo Mangiaracina.","COVID-19; Dynamic capabilities; Express couriers; Last-mile; Pandemic; Resilience",{"$nulls":7},"Aday S., Aday M.S., Impact of COVID-19 on the food supply chain, Food Quality and Safety, 4, pp. 167-180, (2020); Alaimo L.S., Fiore M., Galati A., How the COVID-19 pandemic is changing online food shopping human behaviour in Italy, Sustainability (Switzerland), 12, 22, pp. 1-18, (2020); Anastasiadou E., Chrissos Anestis M., Karantza I., Vlachakis S., The coronavirus' effects on consumer behaviour and supermarket activities: insights from Greece and Sweden, International Journal of Sociology and Social Policy, 40, 9-10, pp. 893-907, (2020); Ardjmand E., Singh M., Shakeri H., Tavasoli A., Young W.A., Mitigating the risk of infection spread in manual order picking operations: a multi-objective approach, Applied Soft Computing, 100, (2021); Barney J.B., Firm resources and sustained competitive advantage, Journal of Management, 17, 1, pp. 99-120, (1991); Bharma R., Dani S., Burnard K., Resilience: the concept, a literature review and future directions, International Journal of Production Research, 49, 18, pp. 5375-5393, (2011); Birkie S.E., Trucco P., Kaulio M., Disentangling core functions of operational resilience: a critical review of extant literature, International Journal of Supply Chain and Operations Resilience, 1, 1, pp. 76-103, (2014); Cavallo C., Sacchi G., Carfora V., Resilience effects in food consumption behaviour at the time of Covid-19: perspectives from Italy, Heliyon, 6, 12, (2020); Choi T.-M., Innovative “bring-service-near-your-home” operations under corona-virus (COVID-19/SARS-CoV-2) outbreak: can logistics become the Messiah?, Transportation Research Part E: Logistics and Transportation Review, 140, (2020); Choi T.-M., Risk analysis in logistics systems: a research agenda during and after the COVID-19 pandemic, Transportation Research Part E: Logistics and Transportation Review, 145, (2021); Christopher M., Logistics and Supply Chain Management, (2011); Christopher M., Peck H., Building the resilient supply chain, The International Journal of Logistics Management, 15, 2, pp. 1-13, (2004); Cichosz M., Wallenburg C.M., Knemeyer A.M., Digital transformation at Logistics service providers: barriers, success factors and leading practices, The International Journal of Logistic Management, 31, 2, pp. 209-238, (2020); Dannenberg P., Fuchs M., Wiedemann T., Riedler C., Digital transition by COVID-19 pandemic? The German food online retail, Journal of Economic and Human Geography, 111, 3, pp. 543-560, (2020); Dovbischuk I., Innovation-oriented dynamic capabilities of logistics service providers, dynamic resilience and firm performance during the COVID-19 pandemic, The International Journal of Logistics Management, 33, 2, pp. 499-519, (2022); Eisenhardt K.M., Building theories from case study research, Academy of Management Review, 14, 4, pp. 532-550, (1989); Eisenhardt K.M., Jeffrey A.M., Dynamic capabilities: what are they?, Strategic Management Journal, 21, 10-11, pp. 1105-1121, (2000); Gammelgaard B., Editorial: the qualitative case study, The International Journal of Logistics Management, 28, 4, pp. 910-913, (2017); Gammelgaard B., Kumar S., Pattnaik D., Joshi R., Thirty years of the international journal of logistics management – a retrospective analysis, The International Journal of Logistics Management, 31, 2, pp. 173-208, (2020); Gioia D.A., Price K.N., Hamilton A.L., Thomas J.B., Forging an identity: an insider-outsider study of processes involved in the formation of organizational identity, Administrative Science Quarterly, 55, 1, pp. 1-46, (2010); 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Garola; Department of Management, Economics and Industrial Engineering, Politecnico di Milano, Milan, Italy; email: giovanni.garola@polimi.it",null,"Emerald Publishing",{"$nulls":5},9574093.0,null,null,null,"English","Int. J. Logist. Manage.","Article","Final","All Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85164474438"]
["Abdul-Jabbar S.S.; Farhan A.K.","Abdul-Jabbar, Safa S. (57447951800); Farhan, Alaa K. (57195385426)","57447951800; 57195385426","Secure QR-Code Generation in Healthcare",2023.0,"Karbala International Journal of Modern Science",9.0,2.0,null,307.0,315.0,8.0,0.0,"10.33640/2405-609X.3294","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85164824119&doi=10.33640%2f2405-609X.3294&partnerID=40&md5=17ecaacd05a7442aa49b48225f2f06c8","Computer Science Department, College of Science for Women, University of Baghdad, Baghdad, Iraq; Computer Science Department, University of Technology, Baghdad, Iraq","Abdul-Jabbar S.S., Computer Science Department, College of Science for Women, University of Baghdad, Baghdad, Iraq, Computer Science Department, University of Technology, Baghdad, Iraq; Farhan A.K., Computer Science Department, University of Technology, Baghdad, Iraq","QR codes have become ubiquitous across several industries, including e-commerce, education, and healthcare. In the healthcare sector, QR codes are increasingly used to relay essential information regarding medical products, patient history, and healthcare education. In addition, QR codes have proven to help secure and preserve patient records during transmissions. This paper aims to develop and analyze the implementation of QR code technology for healthcare applications. The proposed approach involves generating a unique QR code for each patient's information, facilitating data transmission between nodes such as hospitals. With its small size, the QR code provides a simple solution to transfer patient records, reducing internet capacity requirements and minimizing latency. The proposed system utilizes advanced techniques such as Diffie Hellman and logistic map for key generation and distribution, hash algorithm and Lorenz equation for key mask generation, the salting algorithm for data integrity, DNA encoding, and Huffman Algorithm for data coding. The proposed system's usability was tested with 366 patient records, and the results indicate that 99.76% of data was saved with a compression ratio of 416.8 for each patient record. Moreover, the comparative analysis demonstrated that the proposed strategy outperforms other data capacity, security, and integrity methods. Overall, the proposed system can revolutionize data transmission and security in the healthcare sector, ensuring the safety and confidentiality of patient records. © 2023 University of Kerbala.","Chaos systems; DNA Coding; Huffman coding; Patient records; QR-Codes; Quick response codes",{"$nulls":7},"Liu S., Fu Z., Yu B., A two-level QR code scheme based on polynomial secret sharing, Multimed. Tool. Appl, 78, (2019); Tikhonov A., On double-sided QR-codes, (2019); Chen C., QR code authentication with embedded message authentication code, Mobile Network. 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Engl, 99, (2017); Das S.K., Smart Design and its Applications: Challenges and Techniques, Part of the Springer Tracts in Nature-Inspired Computing Book Series (STNIC), (2021); Li C., Hu P., Lau W., AuthPaper: protecting paper-based documents and credentials using Authenticated 2D barcodes, 2015 IEEE International Conference on Communications (ICC), (2015); Uzun V., Sami B., Evaluation and implementation of QR code identity Tag system for healthcare in Turkey, Springer Plus, 5, (2016); Jelic I., Vrkic D., QR codes in library - does anyone use them?, 6th international convention on information and communication technology, electronics and microelectronics (MIPRO), IEEE, (2013); Hugues O., Fuchs P., Nannipieri O., New augmented reality taxonomy: technologies and features of augmented environment, Handbook of Augmented Reality, (2011); Lin P.Y., Chen Y.H., High payload secret hiding technology for QR codes 1, EURASIP Journal on Image and Video Processing, (2017); Ali A., Farhan A.K., Enhancement of QR code Capacity by encrypted lossless compression technology for verification of secure E-Document, IEEE Access, 8, (2020); Jannat U.K., Kumar M.M., Islam S.A., Cloud based QR code for confidential message, Int. 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Fractals, 95, (2017); Fadhil S.A., Farhan A.K., Color visual cryptography based on three dimensional chaotic map 22, Iraqi Journal of Computers, Communications, Control and Systems Engineering, (2022); Ghys E., The Lorenz Attractor, a Paradigm for Chaos, Part of the Progress in Mathematical Physics Book Series, 66, (2013); Ali N.A., Rahma A.M.S., Shaker S.H., 3D textured model encryption using 2D logistic and 3D Lorenz chaotic map, Iraqi Journal of Computers, Communications, Control and Systems Engineering, 21, (2021); Abid S., Saad S., Yaseen A., Proposed neural network with FFT transfer function to estimate Loranz Dynamical Map, Adv. Comput, 9, (2019); Ali N.A., Rahma A.M.S., Shaker S.H., Multi-level encryption for 3D mesh model based on 3D Lorenz chaotic map and random number generator, Int. J. Electr. Comput. Eng, 12, (2022); Shaker S.H., HMAC modification using new random key generator 14, Iraqi Journal of Computers, Communications, Control and Systems Engineering, (2014); Al Farawn A., Rjeib H.D., Ali N.S., Al-Sadawi B., Secured e-payment system based on automated authentication data and iterated salted hash algorithm 18, TELKOMNIKA (Telecommunication Computing Electronics and Control), (2020); Wang X., Su Y., An Audio encryption algorithm based on DNA coding and chaotic system, IEEE Access, 8, (2020); Xue X., Dongsheng Z., Changjun Z., New insights into the existing image encryption algorithms based on DNA coding, PLoS One, 15, (2020); Shah A., Sethi M., The improvised gzip, A technique for real time lossless data compression 6, EAI Endorsed Transactions on Context-Aware Systems and Applications, (2019); Zhang S., Jichen S., Shengkang C., Constrained Optimal Querying: Huffman Coding and beyond, (2022); Kodituwakku S., Amarasinghe U., Comparison Study of lossless data compression algorithms for text data, IOSR J. Comput. Eng, 11, (2013); Bacanin N., Bezdan T., Tuba E., Strumberger I., Tuba M., Monarch butterfly optimization based convolutional neural network design, Mathematics, 8, (2020); Wei Y., Othman Z., Daud K.M., Yin S., Luo Q., Zhou Y., Equilibrium optimizer and Slime Mould algorithm with variable neighborhood search for job shop scheduling problem, Mathematics, 10, (2022); Li J., Lei H., Alavi A.H., Wang G.G., Elephant herding optimization: variants, hybrids, and applications, Mathematics, 8, (2020)","S.S. Abdul-Jabbar; Computer Science Department, College of Science for Women, University of Baghdad, Baghdad, Iraq; email: safa.s@csw.uobaghdad.edu.iq",null,"University of Kerbala",{"$nulls":5},"2405609X",null,null,null,"English","Karbala Int. J. Modern Sci.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85164824119"]
["Ceccato R.; Gastaldi M.","Ceccato, Riccardo (57202726454); Gastaldi, Massimiliano (26537273500)","57202726454; 26537273500","Last mile distribution using cargo bikes: a simulation study in Padova",2023.0,"European Transport - Trasporti Europei",null,90.0,3.0,null,null,null,0.0,"10.48295/ET.2023.90.3","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85152596162&doi=10.48295%2fET.2023.90.3&partnerID=40&md5=0678f27b26abbc8e740577100b0bf219","University of Padova, Department of Civil, Environmental and Architectural Engineering, Via F. Marzolo 9, Padova, 35131, Italy; University of Padova, Department of General Psychology, Via Venezia, 8, Padova, 35131, Italy","Ceccato R., University of Padova, Department of Civil, Environmental and Architectural Engineering, Via F. Marzolo 9, Padova, 35131, Italy; Gastaldi M., University of Padova, Department of Civil, Environmental and Architectural Engineering, Via F. Marzolo 9, Padova, 35131, Italy, University of Padova, Department of General Psychology, Via Venezia, 8, Padova, 35131, Italy","The recent growth of e-Commerce has induced an increasing freight demand, which could lead to negative externalities, in particular in urban areas. To foster sustainable development of cities and increase their livability, many local authorities are implementing urban vehicle access regulations, such as low-emission zones, banning the circulation of polluting vehicles. These measures prompted the adoption of new sustainable freight transport solutions for last mile deliveries, such as cargo bikes. The aim of this paper is to describe the study for the implementation of such a system. The procedure was tested (1) to define the location of a transshipment facility where parcels are moved from vans to cargo bikes, (2) to estimate the environmental and economic sustainability of the system, and (3) to quantify the effects of uncertainty in the final results. The framework was applied to the city center of Padova (Italy), where two sets of delivery system were considered: the first with traditional vans starting from an existing urban consolidation center and the second with manual and electric cargo bikes starting from a micro-depot. In particular, demand of home deliveries was estimated for a typical weekday; routes of freight transport means were defined by an optimization procedure; these data were used as input to a Discrete Event Simulation model. A sensitivity analysis was carried out modelling the potential uncertainty associated with load/unload times and travel speed of means, due to traffic congestion. Several scenarios were tested considering three locations as potential transshipment points. Outcomes of the simulations were used to estimate key performance indicators, evaluating the environmental and economic effects of the two delivery schemes. Results highlighted the potentiality of cargo bikes as a sustainable delivery system, and the impacts of uncertainty on the ranking of alternative options (i.e. micro-hubs). © 2023 Institute for Transport Studies in the European Economic Integration. All rights reserved.","city logistics; discrete event simulation; last mile distribution; sustainability; urban freight delivery","Benchmarking; Bicycles; Freight transportation; Sensitivity analysis; Sustainable development; Traffic congestion; Uncertainty analysis; Urban growth; Urban transportation; City logistics; Delivery systems; Discrete-event simulations; Freight deliveries; Freight transport; Last mile; Last mile distribution; Simulation studies; Uncertainty; Urban freight delivery; Discrete event simulation",{"$nulls":6},"Arnold F., Cardenas I., Sorensen K., Dewulf W., Simulation of B2C e-commerce distribution in Antwerp using cargo bikes and delivery points, European Transport Research Review, 10, 1, (2018); Borghetti F., Caballini C., Carboni A., Grossato G., Maja R., Barabino B., The Use of Drones for Last-Mile Delivery: A Numerical Case Study in Milan, Italy, Sustainability (Switzerland), 14, 3, pp. 1-19, (2022); Browne M., Allen J., Leonardi J., Evaluating the use of an urban consolidation centre and electric vehicles in central London, IATSS Research, 35, 1, pp. 1-6, (2011); Carotenuto P., Ceccato R., Gastaldi M., Giordani S., Rossi R., Salvatore A., Comparing home and parcel lockers’ delivery systems: a math-heuristic approach, Transportation Research Procedia, 62, pp. 91-98, (2022); Carotenuto P., Gastaldi M., Giordani S., Rossi R., Rabachin A., Salvatore A., Comparison of various urban distribution systems supporting e-commerce. Point-to-point vs collection-point-based deliveries, Transportation Research Procedia, 30, pp. 188-196, (2018); Choubassi C., Seedah D. P. K., Jiang N., Walton C. M., Economic analysis of cargo cycles for urban mail delivery, Transportation Research Record, 2547, pp. 102-110, (2016); Annuario statistico comunale - capitolo 2, (2021); Dablanc L., Giuliano G., Holliday K., O'Brien T., Best practices in urban freight management, Transportation Research Record, 2379, pp. 29-38, (2013); Dalla Chiara G., Alho A. R., Cheng C., Ben-Akiva M., Cheah L., Exploring Benefits of Cargo-Cycles versus Trucks for Urban Parcel Delivery under Different Demand Scenarios, Transportation Research Record, 2674, 5, pp. 553-562, (2020); Dybdalen A., Ryeng E. O., Understanding how to ensure efficient operation of cargo bikes on winter roads, Research in Transportation Business and Management, (2021); Elbert R., Friedrich C., Urban consolidation and cargo bikes: A simulation study, Transportation Research Procedia, 48, pp. 439-451, (2020); Estrada M., Roca-Riu M., Stakeholder’s profitability of carrier-led consolidation strategies in urban goods distribution, Transportation Research Part E: Logistics and Transportation Review, 104, pp. 165-188, (2017); Fikar C., Hirsch P., Gronalt M., A decision support system to investigate dynamic last-mile distribution facilitating cargo-bikes, International Journal of Logistics Research and Applications, 21, 3, pp. 300-317, (2018); Hofmann W., Assmann T., Neghabadi Zp. D., Cung V. D., Tolujevs J., A simulation tool to assess the integration of cargo bikes into an urban distribution system, 5th International Workshop on Simulation for Energy, Sustainable Development and Environment, (2017); Holguin-Veras J., Jaller M., Sanchez-Diaz I., Campbell S., Lawson C. T., Freight Generation and Freight Trip Generation Models, Modelling Freight Transport, pp. 43-63, (2014); Il report annuale di idealo sull’e-commerce italiano, (2021); Popolazione Residente, (2011); Jlassi S., Tamayo S., Gaudron A., Simulation Applied to Urban Logistics: A State of the Art, City Logistics, 3, pp. 65-87, (2018); Lebeau P., Macharis C., van Mierlo J., Maes G., Implementing electric vehicles in urban distribution: A discrete event simulation, World Electric Vehicle Journal, 6, 1, pp. 38-47, (2013); Llorca C., Moeckel R., Study of cargo bikes for parcel deliveries under different supply, demand and spatial conditions, 2020 Forum on Integrated and Sustainable Transportation Systems, FISTS, 2020, pp. 39-44, (2020); Llorca Carlos, Moeckel R., Assesment of the potential of cargo bikes and electrification for last-mile parcel delivery by means of simulation of urban freight flows, European Transport Research Review, 13, 1, (2021); de Mello Bandeira R. A., Goes G. V., Schmitz Goncalves D. N., D'Agosto M. de A., Oliveira C. M., Electric vehicles in the last mile of urban freight transportation: A sustainability assessment of postal deliveries in Rio de Janeiro-Brazil, Transportation Research Part D: Transport and Environment, 67, January, pp. 491-502, (2019); Melo S., Baptista P., Evaluating the impacts of using cargo cycles on urban logistics: integrating traffic, environmental and operational boundaries, European Transport Research Review, 9, 2, (2017); Narayanan S., Antoniou C., Electric cargo cycles - A comprehensive review, Transport Policy, 116, pp. 278-303, (2022); Niels T., Hof M. T., Bogenberger K., Design and Operation of an Urban Electric Courier Cargo Bike System, IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC, 2018-Novem, pp. 2531-2537, (2018); Ntziachristos L., Samaras Z., Kouridis C., Samaras C., Hassel D., Mellios G., Mccrae I., Hickman J., Zierock H., Keller M., Rexeis M., Andre M., Winther M., Pastramas N., Boulter P., Katsis P., Joumard R., Rijkeboer R., Geivanidis S., EMEP/EEA Air pollutant emission inventory guidebook 2019, (2019); Robichet A., Nierat P., Delivering Paris by cargo bikes: ecological commitment or economically feasible? The case of a parcel service company, Transportation Research Record, (2021); Russo F., Comi A., City Characteristics and Urban Goods Movements: A Way to Environmental Transportation System in a Sustainable City, Procedia - Social and Behavioral Sciences, 39, pp. 61-73, (2012); Sheth M., Butrina P., Goodchild A., McCormack E., Measuring delivery route cost trade-offs between electric-assist cargo bicycles and delivery trucks in dense urban areas, European Transport Research Review, 11, 1, (2019); World Urbanization Prospects 2018, (2018); Zhang L., Matteis T., Thaller C., Liedtke G., Simulation-based Assessment of Cargo Bicycle and Pick-up Point in Urban Parcel Delivery, Procedia Computer Science, 130, pp. 18-25, (2018)","R. Ceccato; University of Padova, Department of Civil, Environmental and Architectural Engineering, Padova, Via F. Marzolo 9, 35131, Italy; email: riccardo.ceccato@dicea.unipd.it",null,"Institute for Transport Studies in the European Economic Integration",{"$nulls":5},1.8253997E7,null,null,null,"English","Eur. Transp. Trasporti Eur.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85152596162"]
["Baek T.H.","Baek, Tae Hyun (56363629100)",5.63636291E10,"Digital Advertising in the Age of Generative AI",2023.0,"Journal of Current Issues and Research in Advertising",44.0,3.0,null,249.0,251.0,2.0,1.0,"10.1080/10641734.2023.2243496","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85169308052&doi=10.1080%2f10641734.2023.2243496&partnerID=40&md5=46eac50c0873ebd092852abc7687bc72","Department of Media and Communication, Sungkyunkwan University, Seoul, South Korea","Baek T.H., Department of Media and Communication, Sungkyunkwan University, Seoul, South Korea","Artificial intelligence (AI) is significantly reshaping branded content delivery and consumer engagement in the advertising industry. Generative AI, exemplified by ChatGPT, is anticipated to have a substantial impact on all digital advertising domains worldwide. This special issue delves into the exploration of future trends in global digital advertising in the era of generative AI. The research articles within this special issue encompass a diverse array of topics, ranging from consumer responses to AI-generated virtual influencers in the metaverse and livestreaming e-commerce to the influence of anthropomorphic virtual agents, privacy concerns in online behavioral advertising, understanding of AI-driven ethnic affinity targeting, and the role of relational bonds within online gaming communities. © 2023 American Academy of Advertising.",{"$nulls":8},"Aalberts R.J., Nill A., Poon P.S., Online Behavioral Targeting: What Does the Law Say?, Journal of Current Issues & Research in Advertising, 37, 2, pp. 95-112, (2016); Baek T.H., Bakpayev M., Yoon S., Kim S., Smiling AI Agents: How Anthropomorphism and Broad Smiles Increase Charitable Giving, International Journal of Advertising, 41, 5, pp. 850-867, (2022); Baek T.H., Kim M., Ai Robo-Advisor Anthropomorphism: The Impact of Anthropomorphic Appeals and Regulatory Focus on Investment Behaviors, Journal of Business Research, 164, (2023); Baek T.H., Yoo C.Y., Yoon S., Augment Yourself through Virtual Mirror: The Impact of Self-Viewing and Narcissism on Consumer Responses, International Journal of Advertising, 37, 3, pp. 421-439, (2018); Bakpayev M., Baek T.H., van Esch P., Yoon S., Programmatic Creative: AI Can Think but It Cannot Feel, Australasian Marketing Journal, 30, 1, pp. 90-95, (2022); Feng Y., Xie Q., Demystifying Novelty Effects: An Analysis of Consumer Responses to YouTube Videos Featuring Augmented Reality out-of-Home Advertising Campaigns, Journal of Current Issues & Research in Advertising, 40, 1, pp. 36-53, (2019); Haikel-Elsabeh M., Virtual Influencers versus Real Influencers Advertising in the Metaverse, Understanding the Perceptions, and Interactions with Users, Journal of Current Issues & Research in Advertising, 44, 3, pp. 252-273, (2023); Kim M., Kim J., How an Online Gaming Community Advertises Brands to Members: The Roles of Relational Bonds and Trust Transfer, Journal of Current Issues & Research in Advertising, 44, 3, pp. 274-294, (2023); Rodgers S., Themed Issue Introduction: Promises and Perils of Artificial Intelligence and Advertising, Journal of Advertising, 50, 1, pp. 1-10, (2021); Saad S.B., Toward Better Digital Advertising: The Role of the Anthropomorphic Virtual Agent, Journal of Current Issues & Research in Advertising, 44, 3, pp. 295-331, (2023); Digital advertising: Worldwide, (2023); Wan A., Jiang M., Can Virtual Influencers Replace Human Influencers in Live-Streaming eCommerce? An Exploratory Study from Practitioners’ and Consumers’ Perspectives, Journal of Current Issues & Research in Advertising, 44, 3, pp. 332-372, (2023); Yun J.T., Strycharz J., Building the Future of Digital Advertising One Block at a Time: How Blockchain Technology Can Change Advertising Practice and Research, Journal of Current Issues & Research in Advertising, 44, 1, pp. 24-37, (2023); Zhang W., Rodgers S., Linking Ethnicity Targeting with Artificial Intelligence and Data Collection: Perceptions and Behavioral Responses of Black Consumers, Journal of Current Issues & Research in Advertising, 44, 3, pp. 373-391, (2023); Zhang D., Voorveld H., Boerman S.C., Privacy Concerns Matter, Knowledge Does Not: Investigating Effects of Online Behavioral Advertising among Chinese and Dutch Adults, Journal of Current Issues & Research in Advertising, 44, 3, pp. 392-410, (2023)","T.H. Baek; Department of Media and Communication, Sungkyunkwan University, Seoul, South Korea; email: tbaek@skku.edu",null,"Routledge",{"$nulls":5},1.0641734E7,null,null,null,"English","J. Curr. Issues Res. Advert.","Article","Final",null,"Scopus","2-s2.0-85169308052"]
["Guo Q.; Wang N.","Guo, Qinge (57217990051); Wang, Nengmin (24923769600)","57217990051; 24923769600","The Vehicle Routing Problem with Simultaneous Pickup and Delivery Considering the Total Number of Collected Goods",2023.0,"Mathematics",11.0,2.0,311.0,null,null,null,1.0,"10.3390/math11020311","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85146763338&doi=10.3390%2fmath11020311&partnerID=40&md5=b90f22d6d902ee210a328c4f962b5770","School of Management, Xi’an Jiaotong University, Xi’an, 710049, China; School of Economics and Management, Xi’an Technological University, Xi’an, 710021, China","Guo Q., School of Management, Xi’an Jiaotong University, Xi’an, 710049, China, School of Economics and Management, Xi’an Technological University, Xi’an, 710021, China; Wang N., School of Management, Xi’an Jiaotong University, Xi’an, 710049, China","As a consequence of e-commerce development, large quantities of returned goods are shipped every day. The vehicle routing problem with simultaneous delivery and pickup (VRPSDP) has become one of the most important areas of logistics management. Most related studies are aimed at minimizing travel time. However, the total number of collected goods is also very important to logistics companies. Thus, only considering the traveling time cannot reflect actual practice. To effectively optimize these operations for logistics companies, this paper introduces the vehicle routing problem with simultaneous pickup and delivery considering the total number of collected goods. Based on the principles of considering the number of collected goods, a bi-objective vehicle routing model minimizing the total travel time and maximizing the total number of collected goods simultaneously is developed. A polynomial time approximation algorithm based on the (Formula presented.) -constraint method is designed to address this problem, and the approximation ratio of the algorithm is analyzed. Finally, the validity and feasibility of the proposed model and algorithm are verified by test examples, and several managerial insights are derived from the sensitivity analysis. © 2023 by the authors.","approximation algorithm; bi-objective programming; the number of collected goods; vehicle routing problem; VRPSPD",{"$nulls":5},"Xi’an Science and Technology Plan Soft Science Project, (22RKYJ0069); National Natural Science Foundation of China, NSFC, (71732006, 72192830, 72192834)","This research was funded by the Major projects of National Natural Science Foundation of China, grant number 72192830 & 72192834, the Key Project of National Natural Science Foundation of China, grant number 71732006, Xi’an Science and Technology Plan Soft Science Project, grant number 22RKYJ0069.","Min H., The multiple vehicle routing problem with simultaneous delivery and pick-up points, Transp. Res, 23, pp. 377-386, (1989); Awd H., Elshaer R., A Taxonomic Review of Metaheuristic Algorithms for Solving the Vehicle Routing Problem and Its Variants, Comput. Ind. Eng, 140, (2019); Dell'Amico M., Righini G., Salani M., A branch-and-price approach to the vehicle routing problem with simultaneous distribution and collection, Transp. Sci, 40, pp. 237-247, (2006); Rieck J., Zimmermann J., A branch-and-cut approach to the vehicle routing problem with simultaneous delivery and pick-up, Operations Research Proceedings 2008, pp. 301-306, (2009); Subramanian A., Uchoa E., Ochi L.S., New lower bounds for the vehicle routing problem with simultaneous pickup and delivery, Experimental Algorithms. SEA 2010. Lecture Notes in Computer Science, 6049, (2010); Subramanian A., Uchoa E., Pessoa A.A., Ochi L.S., Branch-and-cut with lazy separation for the vehicle routing problem with simultaneous pickup and delivery, Oper. Res. Lett, 39, pp. 338-341, (2011); Archetti C., Speranza M.G., Boccia M., Sforza A., Sterle C., A branch-and-cut algorithm for the inventory routing problem with pickups and deliveries, Eur. J. Oper. Res, 282, pp. 886-895, (2020); Subramanian A., Uchoa E., Pessoa A.A., Ochi L.S., Branch-cut-and-price for the vehicle routing problem with simultaneous pickup and delivery, Optim. Lett, 7, pp. 1569-1581, (2013); Li C., Gong L., Luo Z., Lim A., A branch-and-price- and-cut algorithm for a pickup and delivery problem in retailing, Omega, 89, pp. 71-91, (2019); Dethloff J., Vehicle routing and reverse logistics: The vehicle routing problem with simultaneous delivery and pick-up, OR Spektrum, 23, pp. 79-96, (2001); Kalayci C.B., Kaya C., An ant colony system empowered variable neighbourhood search algorithm for the vehicle routing problem with simultaneous pickup and delivery, Expert Syst. Appl, 66, pp. 163-175, (2016); Zachariadis E.E., Tarantilis C.D., Kiranoudis C.T., Vehicle routing strategies for pick-up and delivery service under two dimensional loading constraints, Oper. Res, 17, pp. 115-143, (2017); Simsir F., Ekmekci D., A metaheuristic solution approach to capacitied vehicle routing and network optimization, Eng. Sci. Technol. Int. J, 22, pp. 727-735, (2019); Li J., Pardalos P., Sun H., Pei J., Zhang Y., Iterated local search embedded adaptive neighbourhood selection approach for the multi-depot vehicle routing problem with simultaneous deliveries and pickups, Expert Syst. Appl, 42, pp. 3551-3561, (2015); Hs A., Yc A., Hg B., Collection and distribution of returned remanufactured products in a vehicle routing problem with pickup and delivery considering sustainable and green criteria, J. Clean. Prod, 172, pp. 960-970, (2018); Avci M., Topaloglu S., A hybrid metaheuristic algorithm for heterogeneous vehicle routing problem with simultaneous pickup and delivery, Expert Syst. Appl, 53, pp. 160-171, (2016); Zhang Z., Cheang B., Li C., Lim A., Multi-commodity demand fulfillment via simultaneous pickup and delivery for a fast fashion retailer, Comput. Oper. Res, 103, pp. 81-96, (2019); Wang Y., Ran L., Guan X., Zou Y., Multi-Depot pickup and delivery problem with resource sharing, J. Adv. Transp, 2021, (2021); Wang C., Mu D., Zhao F., Sutherland J., A parallel simulated annealing method for the vehicle routing problem with simultaneous pickup-delivery and time windows, Comput. Ind. Eng, 83, pp. 111-122, (2015); Carolina L., Guillermo G., Enrique C., Moltedo A., Johnson F., Paredes F., An improved particle swarm optimization algorithm for the VRP with simultaneous pickup and delivery and time windows, Lat. Am. Trans, 16, pp. 1732-1740, (2018); Hornstra R.P., Silva A., Roodbergen K.J., Coelho L.C., The vehicle routing problem with simultaneous pickup and delivery and handing costs, Comput. Oper. Res, 115, (2019); Liu Q., Liu W.J., Study on modeling and optimization of SVRPSDP based on ACS-RSM, Proceedings of the IEEE Conference on Grey Systems and Intelligent Services, pp. 791-794; Peng X., Research on Reverse Logistics Vehicle Routing Problem under Stochastic Recovery Demand with Time Windows, Master’s Thesis, (2013); Jia Y.J., Gu H.Y., Xi Y.G., Rolling horizon scheduling algorithm for dynamic vehicle scheduling system, J. Southeast Univ, 21, pp. 92-96, (2005); Hu Z.-H., Sheu J.-B., Zhao L., Lu C.-C., A dynamic closed-loop vehicle routing problem with uncertainty and incompatible goods, Transp. Res. Part C, 55, pp. 273-297, (2015); Fan H., Liu P., Wu J., Lu C.C., Hybrid genetic algorithm with variable neighborhood descent for the vehicle routing problem with simultaneous stochastic pickup and deterministic delivery, Syst. Eng.-Theory Pract, 39, pp. 2646-2659, (2019); Fan H., Liu P., Liu T., The multi-depot vehicle routing problem with simultaneous deterministic delivery and stochastic pickup based on joint distribution, ACTA Autom. Sin, 47, pp. 1646-1660, (2021); Minis I., Tatarakis A., Stochastic single vehicle routing problem with delivery and pick up and a defined customer sequence, Eur. J. Oper. Res, 213, pp. 37-51, (2011); Zhu L., Sheu J.B., Failure-specific cooperative recourse strategy for simultaneous pickup and delivery problem with stochastic demands, Eur. J. Oper. Res, 271, pp. 896-912, (2018); Zhou R., Research on Optimization Models and Algorithms for Vehicle Routing Problem with Simultaneous Pickup and Delivery, Ph.D. Thesis, (2016); Ma Y., Li Z., Yan F., Feng C., A hybrid priority-based genetic algorithm for simultaneous pickup and delivery problems in reverse logistics with time windows and multiple decision-makers, Soft Comput, 23, pp. 6697-6714, (2019); Fan H., Liu H., Liu P., Ren X., Heterogeneous fleet vehicle routing problem with simultaneous deterministic delivery and fuzzy pickup, Control Theory Appl, 38, (2021); Berube J., Gendreau M., Potvin J., An exact ε-constraint method for bi-objective combinatorial optimization problems: Application to the traveling salesman problem with profits, Eur. J. Oper. Res, 194, pp. 39-50, (2009); Christofides N., Worst Case Analysis of a New Heuristic for the Traveling Salesman Problem, (1976); Bompadre A., Dror M., Orlin J., Improved bounds for vehicle routing solutions, Discret. Optim, 3, pp. 299-316, (2006)","N. Wang; School of Management, Xi’an Jiaotong University, Xi’an, 710049, China; email: wangnm@mail.xjtu.edu.cn",null,"MDPI",{"$nulls":5},2.227739E7,null,null,null,"English","Mathematics","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85146763338"]
["Barata S.F.P.G.; Ferreira F.A.F.; Carayannis E.G.; Ferreira J.J.M.","Barata, Sofia F. P. G. (58480809300); Ferreira, Fernando A. F. (37115389700); Carayannis, Elias G. (7006225155); Ferreira, Joao J. M. (25959981800)","58480809300; 37115389700; 7006225155; 25959981800","Determinants of E-Commerce, Artificial Intelligence, and Agile Methods in Small- and Medium-Sized Enterprises",2023.0,"IEEE Transactions on Engineering Management",null,null,null,1.0,15.0,14.0,3.0,"10.1109/TEM.2023.3269601","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85164383056&doi=10.1109%2fTEM.2023.3269601&partnerID=40&md5=f0537993614d45d0708b13c3bd875095","ISCTE Business School, University Institute of Lisbon, Lisbon, Portugal; ISCTE Business School, BRU-IUL, University Institute of Lisbon, Lisbon, Portugal; Department of Information Systems and Technology Management, George Washington University School of Business, Washington, DC, USA; NECE Research Unit, University of Beira Interior, Covilh&#x00E3;, Portugal","Barata S.F.P.G., ISCTE Business School, University Institute of Lisbon, Lisbon, Portugal; Ferreira F.A.F., ISCTE Business School, BRU-IUL, University Institute of Lisbon, Lisbon, Portugal; Carayannis E.G., Department of Information Systems and Technology Management, George Washington University School of Business, Washington, DC, USA; Ferreira J.J.M., NECE Research Unit, University of Beira Interior, Covilh&#x00E3;, Portugal","Small- and medium-sized enterprises (SMEs) are constrained by scarce resources, yet they are under strong pressure to maintain a competitive position in global markets, especially during crises such as the coronavirus disease-19 (COVID-19) pandemic. In this context, electronic commerce (hereafter e-commerce) platforms combining artificial intelligence (AI) and agile methods have been thriving. On the one hand, AI is a better way to process the data essential to platform customization and optimization. On the other hand, agile adoption ensures iterative software delivery as well as improved management practices that reduce uncertainty and allow SMEs to adapt more easily to new market requirements. A limited number of studies have covered all three topics, especially in relation to these companies. This research focused on creating an innovative model to identify determinants that favor or inhibit SME development of e-commerce, AI, and agile method projects. The model was developed using cognitive mapping&#x2014;based on strategic options development and analysis&#x2014;and decision-making trial and evaluation laboratory technique. Recommendations were generated to help SMEs use these tools to acquire a stronger competitive position in global markets. IEEE","Agile methods; Artificial intelligence; artificial intelligence (AI); cognitive mapping; Companies; Decision making; decision-making trial and evaluation laboratory (DEMATEL); e-commerce; Electronic commerce; multiple-criteria decision analysis (MCDA); Software; strategic options development and analysis (SODA); Technological innovation; technology; Uncertainty","Artificial intelligence; Decision support systems; Decision theory; Electronic commerce; International trade; Iterative methods; Mapping; Operations research; Supply chains; Uncertainty analysis; Agile methods; Artificial intelligence; Cognitive mapping; Decision-making trial and evaluation laboratory; Decisions makings; E- commerces; Multiple criteria decision analysis; Multiple-criteria decision analyse; Software; Strategic option development and analyse; Strategic options; Technological innovation; Technology; Uncertainty; Decision making",{"$nulls":9},"Institute of Electrical and Electronics Engineers Inc.",{"$nulls":5},189391.0,null,"IEEMA",null,"English","IEEE Trans Eng Manage","Article","Article in press",null,"Scopus","2-s2.0-85164383056"]
["Chaubey D.S.; Sharma L.S.; Subramanian K.R.","Chaubey, D.S. (57189497335); Sharma, L.S. (57215502245); Subramanian, K.R. (58109010300)","57189497335; 57215502245; 58109010300","Social Network Marketing and its Influence on Online Purchase of Grocery Products during Covid-19 Pandemic: Mediating Role of Brand Awareness",2023.0,"International Journal of Electronic Commerce Studies",13.0,4.0,null,39.0,60.0,21.0,0.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85148439596&partnerID=40&md5=f41c58134264d02ca0851efc25d844f3","Uttaranchal University, India; Mizoram University, India; Thinketh Labs, India","Chaubey D.S., Uttaranchal University, India; Sharma L.S., Mizoram University, India; Subramanian K.R., Thinketh Labs, India","Digital technologies in the present day have witnessed phenomenal growth in the field of marketing and advertising of products. The online shopping is a relatively growing phenomenon, which is attracting a lot of attention in the present Covid-19 pandemic period. The influence of social networking sites (SNS) is being so widely discussed around the world and a number of studies have been on the use of SNS among consumers in India. Many grocery shoppers are concerned about exposing themselves to Covid-19 by going to stores and have chosen to buy groceries online by either stepping up the online delivery service or pickup services, or by trying for the first time.Several studies have primarily discussed how businesses communicate with consumers, but the gap in the study is whether social media can actually change consumers' knowledge of brands.The aim of this study is to analyze factors that influence the customer in adapting to social networks in order to increase brand awareness and intention to purchase food products online. The paper also examines the mediating role of brand awareness to the relationship of SNS and intention to purchase. © 2023 Academy of Taiwan Information Systems Research. All rights reserved.","Brand awareness; Digital marketing; Digital technologies; Social media; Social network sites","India; advertising; consumption behavior; COVID-19; digitization; epidemic; marketing; networking; social media; social network; knowledge",{"$nulls":6},"WHO Director-General's opening remarks at the media briefing on COVID-19-11 March 2020, (2020); Akhtar N., Tahir M., Asghar Z., Impact of social media marketing on consumer purchase intention, International Review of Social Sciences, 4, 10, pp. 385-394, (2016); Alkaya A., Taskin E., The impact of social media pages on consumer equity and purchase intention: An empirical study of mobile operators, Journal of Business Research Turk, 9, 3, pp. 122-133, (2017); Manzoor U., Baig S. A., Hashim Md., Sami A., Impact of social media marketing on consumer's purchase intentions: The mediating role of customer trust, International Journal of Entrepreneurial Research, 3, pp. 41-48, (2020); Kaplan A. M., Haenlein M., Users of the world, unite! The challenges and opportunities of social media, Business Horizons, 53, 1, pp. 59-68, (2010); Zabadi A., Abdullah M., Dammas A., Investigate, World Wide Journal of Multidisciplinary Research and Development, 3, 8, pp. 38-49, (2017); Hajli N., Social commerce constructs and consumer's intention to buy, International Journal of Information Management, 35, 2, pp. 183-191, (2015); Dedeoglu B. B., Taheri B., Okumus F., Gannon M., Understanding the importance that consumers attach to social media sharing (ISMS): Scale development and validation, Tourism Management, 76, (2020); Appel G., Grewal L., Hadi R., Stephen A. T., The future of social media in marketing, Journal of the Academy of Marketing Science, 48, 1, pp. 79-95, (2020); Scarth M., The influence of social media communication on South Africa Millennial consumer purchase intentions of motor vehicle brands, Masters dissertation in Business Administration, (2017); Social media: An Introduction, (2012); Kahle L., Valette-Florence P., Ebrary I., Marketplace Lifestyles in an Age of Social Media: Theory and Methods, (2012); Alnsour Md., Tayeh Z. A., Impact of social media use on brand awareness: an applied study on Jordanian banks that uses Facebook, International Journal of Electronic Banking, 1, 4, pp. 341-357, (2019); Hutter K., Hautz J., Dennhardt S., Fuller J., The impact of user interactions in social media on brand awareness and purchase intention: The case of MINI on Facebook, Journal of Product & Brand Management, 22, 5, pp. 342-351, (2013); Nawaz A., Abbas G., Javed Md. F., Mughal N., Nabeel Md., Impact of social media and voice of customer (voc) in decision making process an empirical study of higher education institutions of Pakistan, Middle-East Journal of Scientific Research, 23, 6, pp. 1069-1075, (2015); Arif Md., Kanwal S., Adoption of social media technologies and their impact on students' academic performance: The only way for future survival of distance education students in Pakistan, Pakistan Journal of Information Management & Libraries, 18, 1, pp. 25-36, (2016); Hollebeek L., Glynn M., Brodie R., Consumer brand engagement in social media: Conceptualization, scale development and validation, Journal of Interactive Marketing, 28, 2, (2014); Shahid Z., Hussain T., Azafar F., The impact of brand awareness on the consumers' purchase intention, Journal of Accounting and Marketing, 6, 1, pp. 34-38, (2017); Wu S., Ho L., The influence of perceived innovation and brand awareness on purchase intention of innovation product - An example of iPhone, International Journal of Innovation and Technology Management, 11, 4, pp. 1-22, (2014); Hafez M., Measuring the impact of corporate social responsibility practices on brand equity in the banking industry in Bangladesh: The mediating effect of corporate image and brand awareness, International Journal of Bank Marketing, 36, 5, pp. 806-822, (2018); Surucu O., Ozturk Y., Okumus F., Bilgihan A., Brand awareness, image, physical quality and employee behavior as building blocks of customer-based brand equity: Consequences in the hotel context, Journal of Hospitality and Tourism Management, 40, pp. 114-124, (2019); Alhaddad A. A., The effect of advertising awareness on brand equity in social media, International Journal of e-Education, e-Business, e-Management and e-Learning, 5, 2, (2015); Aghazadeh H., Bakhshizadeh E., Evaluating the effectiveness of electronic advertisement based on the hierarchy of effects model: The case of the garment industry, Journal of New Economy and Commerce, 6, 21-22, pp. 123-144, (2010); Johns R., Perrott B., The impact of internet banking on business-customer relationships (are you being self-served?), International Journal of Bank Marketing, 26, 7, pp. 465-482, (2008); Dehghani M., Tumer M., A research on effectiveness of Facebook advertising on enhancing purchase intention of consumers, Computers in Human Behavior, 49, pp. 597-600, (2015); Brill J., Likert scale, Encyclopedia of survey research methods, pp. 428-430, (2008); Venkatesh V., Davis F. D., A theoretical extension of the technology acceptance model: Four longitudinal field studies, Management Science, 46, 2, pp. 186-204, (2000); Legris P., Ingham J., Collerette P., Why do people use information technology? A critical review of the technology acceptance model, Information and Management, 40, 3, pp. 191-204, (2003); Kim H., Chan H., Gupta S., Value-based adoption of mobile internet: An empirical investigation, Decision Support Systems, 43, pp. 111-126, (2007); Amoroso D., Hunsinger D., Understanding consumers' acceptance of online purchasing, Journal of Information Technology Management, 20, 1, pp. 15-41, (2009); Nofala R., Calicioglub C., Aljuhmanic H. Y., The impact of social networking sites advertisement on consumer purchasing decision: The mediating role of brand awareness, International Journal of Data and Network Science, 4, pp. 139-156, (2020); Kala D., Chaubey D. S., Consumers' attitude and purchase intention towards counterfeit products: Empirical evidence from Uttarakhand state, Amity Business Review, 18, pp. 80-91, (2017); Ibrahim B., Aljarah A., Dataset of relationships among social media marketing activities, brand loyalty, revisit intention. Evidence from the hospitality industry in Northern Cyprus, Data in Brief, 21, pp. 1823-1828, (2018); Jamali M., Khan R., The impact of consumer interaction on social media on brand awareness and purchase intention! Case study of Samsung, Journal of Marketing and Logistics, 1, 1, pp. 125-140, (2018); Seo E. J., Park J. W., A study on the effects of social media marketing activities on brand equity and customer response in the airline industry, Journal of Air Transport Management, 66, pp. 36-41, (2018); Shaouf A., Lu K., Li X., The effect of web advertising visual design on online purchase intention: An examination across gender, Computers in Human Behavior, 60, pp. 622-634, (2016); Sharma S., Singh S., Kujur F., Das G., Social media activities and its influence on customer-brand relationship: An empirical study of apparel retailers' activity in India, Journal of Theoretical and Applied Electronic Commerce Research, 16, pp. 602-617, (2021); Bhakar S., Bhakar S., Kushwaha K., The effectiveness of e-advertisement towards customer purchase intention: Indian perspective, Proceedings of 10th International Conference on Digital Strategies for Organizational Success, (2018); Bilal G., Ahmed M. A., Shehzad M. N., Role of social media and social networks in consumer decision making: A case of the garment sector, International Journal of Multidisciplinary Sciences and Engineering, 5, 3, pp. 1-9, (2014); Permatasari A., Kuswadi E., The impact of social media on consumers' purchase intention: A study of ecommerce sites in Jakarta, Indonesia, Review of Integrative Business and Economics Research, 6, pp. 321-335, (2017); Langaro D., Rita P., Salgueiro M. F., Do social networking sites contribute for building brands? Evaluating the impact of users' participation on brand awareness and brand attitude, Journal of Marketing Communications, 24, 2, pp. 146-168, (2018); Huang Z., Benyoucef M., The effects of social commerce design on consumer purchase decision-making: An empirical study, Electronic Commerce Research and Applications, 25, pp. 40-58, (2017); Liang T., Lai H., Effect of store design on consumer purchases: An empirical study of on-line bookstores, Information & Management, 39, pp. 431-444, (2002)",null,null,"Academy of Taiwan Information Systems Research",{"$nulls":5},2.0739729E7,null,null,null,"English","Int. J. Electron. Commer. Stud.","Article","Final",null,"Scopus","2-s2.0-85148439596"]
["Chen C.; Nakayama M.; Ractham P.","Chen, Charlie (7501949741); Nakayama, Makoto (7401792580); Ractham, Peter (14036025900)","7501949741; 7401792580; 14036025900","Increasing the intention of Gen Zers to adopt drone delivery services based on a three-step decision-making process",2023.0,"Cogent Business and Management",10.0,1.0,2188987.0,null,null,null,1.0,"10.1080/23311975.2023.2188987","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85150394768&doi=10.1080%2f23311975.2023.2188987&partnerID=40&md5=9fba4ebd13c2c324cb35354512a18839","Department of Computer Information Systems and Supply Chain Management, Appalachian State University, Boone, NC, United States; School of Computing, Jarvis College of Computing and Digital Media DePual University, IL, United States; Department of Management Information System, Thammasat Business School, Thammasat University, Thailand","Chen C., Department of Computer Information Systems and Supply Chain Management, Appalachian State University, Boone, NC, United States; Nakayama M., School of Computing, Jarvis College of Computing and Digital Media DePual University, IL, United States; Ractham P., Department of Management Information System, Thammasat Business School, Thammasat University, Thailand","Generation Zers are digital natives who may be early adopters of drone delivery services for e-commerce. Therefore, e-commerce vendors must understand what causes Gen Zers to believe, desire, and intend to adopt drone delivery services. Gen Zers were surveyed regarding their decision-making processes using the DITTO research framework (Diversity, Individualism, Teamwork, Technology, and Organizational Support) and belief-desire-intention theory. A survey was conducted with 83 Gen Zers from the United States, and data was analyzed using multilinear regression analysis. Many important implications can be drawn from the analysis results. Before Gen Zers adopt drone delivery services, the “seeing is believing” moment appears to be essential, according to the analysis. Moreover, e-commerce vendors should emphasize drone delivery’s relative advantages in terms of speed and environmental protection. Based on our findings, Gen Zers are rational decision-makers when it comes to adopting drone delivery services. To motivate Gen Zers to use drone delivery services, it is imperative to help them develop the belief and increase their desire. © 2023 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license.","Drone Delivery; E-Commerce; Generation Z; Last Mile Delivery",{"$nulls":7},"Ajzen I., Fishbein M., The prediction of behavioral intentions in a choice situation, Journal of Experimental Social Psychology, 5, 4, pp. 400-421, (1969); Ali S.S., Kaur R., Gupta H., Ahmad Z., Elnaggar G., Determinants of an organization’s readiness for drone technologies adoption, IEEE Transactions on Engineering Management, (2021); Al-Jabri I.M., Sohail M.S., Mobile banking adoption: Application of diffusion of innovation theory, Journal of Electronic Commerce Research, 13, 4, pp. 379-391, (2012); Bagozzi R.P., The legacy of the technology acceptance model and a proposal for a paradigm shift, Journal of the Association for Information Systems, 8, 4, (2007); Bansal H.S., Taylor S.F., St. James Y., “Migrating” to new service providers: Toward a unifying framework of consumers’ switching behaviors, Journal of the Academy of Marketing Science, 33, 1, pp. 96-115, (2005); Bassiouni D.H., Hackley C., ‘Generation Z’children’s adaptation to digital consumer culture: A critical literature review, Journal of Customer Behaviour, 13, 2, pp. 113-133, (2014); Bishop P., Hines A., Collins T., The current state of scenario development: An overview of techniques, Foresight, 9, 1, pp. 5-25, (2007); Bratman M.E., Intentions, Plans, and Practical Reason, (1987); Bratman M.E., Cognitivism About Practical Reason. 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Changes in the relationship between attitude and behavior towards order delivery by drone, Technological Forecasting and Social Change, 169, (2021); Yoo W., Yu E., Jung J., Drone delivery: Factors affecting the public’s attitude and intention to adopt, Telematics and Informatics, 35, 6, pp. 1687-1700, (2018); Yuen K.F., Wang X., Ng L.T.W., Wong Y.D., An investigation of customers’ intention to use self-collection services for last-mile delivery, Transport Policy, 66, pp. 1-8, (2018); Zhang T., Tao D., Qu X., Zhang X., Lin R., Zhang W., The roles of initial trust and perceived risk in public’s acceptance of automated vehicles, Transportation Research Part C: Emerging Technologies, 98, pp. 207-220, (2019)","P. Ractham; Department of Management Information System, Thammasat Business School, Thammasat University, Thailand; email: peter@tbs.tu.ac.th",null,"Cogent OA",{"$nulls":5},2.3311975E7,null,null,null,"English","Cogent Bus. Manag.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85150394768"]
["Chen G.","Chen, Guofang (58168910300)",5.81689103E10,"The development dilemma and countermeasures of Chinese cross-border e-commerce enterprises under the background of big data",2023.0,"Journal of Computational Methods in Sciences and Engineering",23.0,2.0,null,1087.0,1099.0,12.0,0.0,"10.3233/JCM-226632","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85151543317&doi=10.3233%2fJCM-226632&partnerID=40&md5=8f03c42a9d4bc379c08ec89267f173d9","School of Economics and Management, Jiaozuo University, Jiaozuo, Henan, 454000, China","Chen G., School of Economics and Management, Jiaozuo University, Jiaozuo, Henan, 454000, China","Cross-border e-commerce has gradually emerged with the popularity of the Internet in the world. It represents a new business model of e-commerce. The public is still the same as the daily shopping model on e-commerce platforms. However, cross-border e-commerce can be divided into two parts at home and abroad. With the continuous emergence of new social models such as the Metaverse, the data generated by online social networking is becoming larger and larger, and data science has developed accordingly, and the effective use of data has become the key to the rapid development of various industries. Big data technology is the key to data science. A data processing and analysis technology generated in the development process, its use in the development of cross-border e-commerce enterprises will help enterprises to create products that are more in line with the actual requirements of the masses, increase the profits of enterprise operations, and allow enterprises to complete the era of data science smooth transition. This paper first describes the big data technology and related theories of cross-border e-commerce, and then takes Alibaba as an example to describe the SWOT analysis of my country's cross-border e-commerce enterprises, and then analyzes the development dilemma of China's cross-border e-commerce enterprises, and finally designs The development strategy of my country's cross-border e-commerce enterprises based on big data is presented. Through a questionnaire survey of cross-border e-commerce enterprises that use big data technology in my country, it is found that cross-border e-commerce enterprises that combine big data technology have a greater understanding of overseas customers' consumption psychology, integration of warehousing and logistics resources, and talent training. promote. © 2023 - IOS Press. All rights reserved.","Big data; countermeasures; cross-border e-commerce enterprises; predicament","Data handling; Data Science; Electronic commerce; Social networking (online); Countermeasure; Cross-border; Cross-border e-commerce enterprise; Data technologies; E- commerces; E-commerce enterprise; New business models; Predicament; Public IS; Shopping model; Big data",{"$nulls":6},"Xing Y., Qiu Z.P., Research on the spatiotemporal evolution pattern of China?s e-commerce development, Enterp Econ, 9, pp. 140-147, (2022); Liu S.W., Chen W., Tang H.T., E-commerce development and domestic unified market: Integration or segmentation: Based on bilateral stochastic frontier model, J Hunan Univ (Soc Sci Ed, 36, 4, pp. 56-67, (2022); Ma G.X., Wang H.W., Reflection and reconstruction of the registration exemption system for e-commerce operators, J Beijing Union Univ (Humanities Soc Sci Ed)., 20, 3, pp. 80-89+100, (2022); Li M.L., E-commerce development and financial support based on the Internet era, Bus Exhib Econ, 13, pp. 32-34, (2022); Zhang M., Shi Y.M., Zou H., Research on the coupling and coordinated development of urbanization and regional ecommerce in the Yangtze River Delta, J Taiyuan City Vocational Tech Coll, 6, pp. 11-14, (2022); Fan M.L., Wang D., The impact of e-commerce on Chinese foreign trade enterprises, China Dev, 3, pp. 73-80, (2022); Shen L., Research on the impact of e-commerce on international trade and countermeasures, Bus Exhib Econ, 10, pp. 48-50, (2022); Zhang Y., On the influence and innovation of e-commerce on enterprise management, China Mark, 15, pp. 190-192, (2022); Gao N.N., The influence and countermeasures of e-commerce on future marketing methods, China Mark, 15, pp. 133-135, (2022); Li R.Y., Opportunities, difficulties and countermeasures for the development of cross-border e-commerce in my country under the background of RCEP, Mod Bus, 15, pp. 46-48, (2022); Long J., The legitimacy and system optimization of competition clauses in the Electronic Commerce Law, J Dalian Univ Technol (Soc Sci Ed, 43, 4, pp. 72-82, (2022); Qu D., He J.F., Can e-commerce promote urban-rural integration in the context of rural revitalization?, Sankei Rev, 13, 3, pp. 148-160, (2022); Liu J.X., Exploration on the development mode and optimization path of cross-border e-commerce under the background of the new era, Mod Commer, 13, pp. 76-78, (2022); Zhou Z.Y., Li H., Spatial economic growth process and control analysis of e-commerce logistics, China Storage Transp, 5, pp. 118-119, (2022); Yue Y.D., Wang W., Research on the application of cloud computing technology in e-commerce, Mod Shopping Malls, 8, pp. 41-43, (2022); Zhao D.D., Discussion on enterprise cost management in e-commerce environment, Mod Bus, 12, pp. 57-59, (2022); Liu X.H., Application research and analysis of e-commerce information system in chain operation mode, Mod Shopping Malls, 7, pp. 27-29, (2022); Tao T., Fan K.X., Zhu Z.Y., Digital rural construction and county industrial structure upgrade: A quasi-natural experiment based on the comprehensive demonstration policy of e-commerce in rural areas, China Circ Econ, 36, 5, pp. 3-13, (2022); Xue J., International financial trade innovation based on the background of e-commerce, Trade Fair Econ, 7, pp. 77-79, (2022); Wu X.N., The role of e-commerce in regional economic development, Bus Exhib Econ, 7, pp. 58-60, (2022); Ma D.M., Research on the development of rural e-commerce under the background of Internet +, China Bus Rev, 7, pp. 46-48, (2022); Le J.J., Analysis on the construction mode of the online marketing system of agricultural products in the e-commerce era, Bus Exhib Econ, 6, pp. 67-69, (2022); Cao Z.L., Research on innovation of e-commerce marketing model for leather products, China Leather, 51, 4, pp. 136-139, (2022); Zhang H.M., Research on enterprise marketing model innovation based on e-commerce perspective, National Circ Econ, 8, pp. 20-22, (2022); Qian G.X., Su R.N., The influence of e-commerce development on the optimization and upgrading of industrial structure, J Inner Mongolia Univ (Philos Soc Sci Ed, 54, 2, pp. 96-107, (2022); Ma S.Y., Hu F.Z., Research on the development countermeasures of Chinese cross-border import e-commerce enterprises based on SCP theory, Technol Mark, 26, 8, pp. 185-186, (2019)","G. Chen; School of Economics and Management, Jiaozuo University, Henan, Jiaozuo, 454000, China; email: guofang_chen@outlook.com",null,"IOS Press BV",{"$nulls":5},1.4727978E7,null,null,null,"English","J. Comput. Methods Sci. Eng.","Article","Final",null,"Scopus","2-s2.0-85151543317"]
["VAN Phuong T.; Nguyen K.Q.; Nguyen L.T.; Vu N.K.","VAN Phuong, TO (57580366600); Nguyen, Khanh Quoc (57206239244); Nguyen, Luong Trong (57218632530); Vu, Nghiep Ke (57244467500)","57580366600; 57206239244; 57218632530; 57244467500","Impacts of the COVID-19 Pandemic on Vietnam's Marine Fisheries",2023.0,"Asian Fisheries Science",36.0,2.0,null,68.0,78.0,10.0,0.0,"10.33997/j.afs.2023.36.2.002","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85167362618&doi=10.33997%2fj.afs.2023.36.2.002&partnerID=40&md5=82258e9d7f6db13bfd6fe6b5bad87659","Institute of Science and Fishing Technology, Nha Trang University, Khanh Hoa, 57000, Viet Nam","VAN Phuong T., Institute of Science and Fishing Technology, Nha Trang University, Khanh Hoa, 57000, Viet Nam; Nguyen K.Q., Institute of Science and Fishing Technology, Nha Trang University, Khanh Hoa, 57000, Viet Nam; Nguyen L.T., Institute of Science and Fishing Technology, Nha Trang University, Khanh Hoa, 57000, Viet Nam; Vu N.K., Institute of Science and Fishing Technology, Nha Trang University, Khanh Hoa, 57000, Viet Nam","Vietnam’s capture fisheries play a significant role in the country’s socioeconomic development. However, COVID-19 has seriously impacted Vietnam’s coastal communities and marine fisheries. This study aimed to assess the effect of the COVID-19 pandemic on Vietnam’s marine fisheries, recommend solutions to help fishers recover their operations and suggest long-term policies for similar pandemics in the future. A survey was conducted in 12 coastal provinces across Vietnam’s North, North Central, South Central and South West regions using mixed methods, including online questionnaires and group discussions via Google Meet from June to August 2021. The study involved 109 fishing vessel captains, fishers and owners who participated when social distancing in most coastal provinces was still enforced. The results showed that 87 % of the fishers experienced negative to strongly negative impacts of COVID-19 on their fisheries activities. The most significant difficulties faced by fishers were accessing the fishing port and dealing with the logistics procedures of docking and departure, accounting for 77.1 %, 72.5 % and 76.1 %, respectively. The fishers also reported reduced seafood demand and price, and difficulties in seafood transportation. Most respondents expected the government to effectively support fisheries activities and facilitate seafood marketing during an ongoing pandemic. The results of this study are crucial in developing policy solutions to restore disrupted fish supply chains, enhancing online selling or e-commerce in fisheries marketing, and implementing timely subsidy policies to support Vietnam’s marine fisheries sectors during a pandemic. © 2023, Asian Fisheries Society. All rights reserved.","challenges during pandemic; fisheries; negative impact of COVID-19; pandemic","Viet Nam; COVID-19; fishery management; fishing; policy approach; questionnaire survey; seafood; socioeconomic impact",{"$nulls":6},"Airam G.M., Lorena C.M., David J.A., Ana E.R., Raibel N.G., Airam S.N., Angelo S.D.P., Castro J.J., Preliminary assessment of the impact of COVID-19 Pandemic in the small-scale and recreational fisheries of the Canary Islands, Marine Policy, 133, (2021); Anh V., People in the Central region can follow urgent news about Typhoon Noru via Zalo of the provinces, (2022); Aura C.M., Nyamweya C.S., Odoli C.O., Owiti H., Njiru J.M., Otuo P.W., Waithaka E., Malala J., Consequences of calamities and their management: The case of COVID-19 pandemic and flooding on inland capture fisheries in Kenya, Great Lakes Research, 45, pp. 1767-1775, (2020); Azra M.N., Kasan N.A., Othman R., Noor G.A.G.R., Mazelan S., Jamari Z.B., Sara G., Ikhwanuddin M., Impact of COVID-19 on aquaculture sector in Malaysia: Findings from the first national survey, Aquaculture Reports, 19, (2021); Bennett N.J, Elena M.F., Natalie C.B., Dyhia B., Stacy D.J., John N.K., Sangeeta M., Joeri S., David G., Patrick C., The COVID-19 Pandemic, Small-Scale Fisheries and Coastal Fishing Communities, Coastal Management, 48, pp. 336-347, (2020); Chanrachkij I., Laongmanee P., Lanmeen J., Suasi T., Sornkliang J., Tiaye R., Yasook N., Putsa S., Chumchuen S.V., Severity of the Impacts of COVID-19 Pandemic on small-scale fisheries of Thailand: A preliminary assessment, Fish for the People, 18, pp. 43-47, (2020); Dang N.B., Salim M., Kenneth J., Hung P.T.H., Effectiveness of formal institutions in managing marine fisheries for sustainable fisheries development: A case study of a coastal commune in Vietnam, Ocean & Coastal Management, 137, pp. 175-184, (2017); Current status and solutions to improve the efficiency of seafood fishing, processing and consumption in 2021 and orientation to 2030, (2021); How is COVID-19 affecting the fisheries and aquaculture food systems?, (2020); The impact of COVID-19 on fisheries and aquaculture – A global assessment from the perspective of regional fishery bodies: Initial assessment; 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(2021); White C., Study provides a first comprehensive look at COVID’s impact on US seafood industry, (2020); Coronavirus disease (COVID-19) pandemic, (2023)","T. VAN Phuong; Institute of Science and Fishing Technology, Nha Trang University, Khanh Hoa, 57000, Viet Nam; email: phuongtv@ntu.edu.vn","Gopal N.; Central Institute of Fisheries Technology (CIFT), Matsyapuri P.O., Cochin, Kerala; Williams M.J.; 17 Agnew Street, Aspley, QLD; Porter M.; Kusakabe K.; Asian Institute of Technology, School of Environment, Resources and Development, P.O. Box 4, Klong Luang, Pathumthani; Choo P.S.; 147 Cangkat Delima Satu, Island Glades, Penang","Asian Fisheries Society",{"$nulls":5},1166514.0,null,null,null,"English","Asian Fish. Sci.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85167362618"]
["Arumugam T.; Hameed S.S.; Sanjeev M.A.","Arumugam, Thangaraja (57192373271); Hameed, S. Shahul (57208907567); Sanjeev, M.A. (56703377600)","57192373271; 57208907567; 56703377600","Buyer behaviour modelling of rural online purchase intention using logistic regression",2023.0,"International Journal of Management and Enterprise Development",22.0,2.0,null,139.0,157.0,18.0,0.0,"10.1504/IJMED.2023.130153","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85153859150&doi=10.1504%2fIJMED.2023.130153&partnerID=40&md5=00db7d4049700f7b0fd7666837f18c6f","Vellore Institute of Technology, Chennai, India; Department of Business Administration, Sadakathullah Appa College, Tamil Nadu, Tirunelveli, India; Symbiosis Center for Management and Human Resources Development, Symbiosis International (Deemed University), Pune, India","Arumugam T., Vellore Institute of Technology, Chennai, India; Hameed S.S., Department of Business Administration, Sadakathullah Appa College, Tamil Nadu, Tirunelveli, India; Sanjeev M.A., Symbiosis Center for Management and Human Resources Development, Symbiosis International (Deemed University), Pune, India","Improvements in connectivity, smartphone adoption, data usage, a competitive e-commerce space, innovations in financial technologies, and logistics growth are expected to push the Indian e-commerce industry to 200 billion dollars by 2026. The growth will mainly be propelled by the rural populace – constituting 68% of the Indian population and accounting for half of its consumption. It will be primarily driven by their increasing aspirations, brand consciousness, and value search against a stagnant urban market. However, such growth depends on the marketer’s understanding of rural consumers, whose online consumer behaviour has not been well investigated. The current study tries to bridge this gap by studying the antecedents of rural e-commerce adoption. The results indicate that service quality, enjoyment, and trust are the most critical parameters for rural e-commerce adoption. The study results can help e-commerce market participants design suitable intervention strategies to improve their rural sales and returns. Copyright © 2023 Inderscience Enterprises Ltd.","consumer behaviour; enjoyment; information quality; logistic regression; modelling; online shopping; past experience; returns; rural; service quality; trust; website quality",{"$nulls":7},"Abbas M., India’s growing data usage, smartphone adoption to boost Digital India initiatives: top bureaucrat, (2021); Al-Debei M.M., Akroush M.N., Ashori M.I., Consumer attitudes towards online shopping the effects of trust, perceived benefits, and perceived web quality, Internet Research, 25, 5, pp. 707-733, (2015); Alharthey B., The role of online trust in forming online shopping intentions, International Journal of Online Marketing, 10, 1, pp. 1-26, (2020); Ang C., Mapped: The World’s Fastest Growing eCommerce Markets, (2021); Barari M., Ross M., Surachartkumtonkun J., Negative and positive customer shopping experience in an online context, Journal of Retailing and Consumer Services, 53, 1, (2020); Bhat S.A., Darzi M.A., Online service quality determinants and e-trust in internet shopping: a psychometric approach, Vikalpa: The Journal for Decision Makers, 45, 4, pp. 207-222, (2020); Bianchi C., Andrews L., Risk, trust, and consumer online purchasing behaviour: a Chilean perspective, International Marketing Review, 29, 3, pp. 253-275, (2012); Biedenbach T., Soderholm A., The challenge of organizing change in hypercompetitive industries: a literature review, Journal of Change Management, 8, 2, pp. 123-145, (2008); E-Commerce in Rural India: Tapping The Untapped Market, (2022); Changchit C., Et al., Determinants of online shopping influencing Thai consumer’s buying choices, Journal of Internet Commerce, 18, 1, pp. 1-23, (2019); Chen N., Yang X., Xiong T., Research on the Influencing Factors of 90s Generation College Students’ Willingness to Online Shopping, pp. 147-151, (2018); Childers T.L., Carr C.L., Peck J., Carson S.J., Hedonic and utilitarian motivations for online retail shopping behavior, Journal of Retailing, 77, 4, pp. 511-535, (2001); Constantinides E., Fountain S.J., Web 2.0: conceptual foundations and marketing issues, Journal of Direct, Data and Digital Marketing Practice, 9, 3, pp. 231-244, (2008); D'Aveni R.A., Hyper-competition: Managing the Dynamics of Strategic Maneuvering, (2010); Dai W., Et al., Like or want? 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Evidence from India, International Journal of Management and Enterprise Development, 19, 4, pp. 378-397, (2020); Jeng S.P., Huang L.S., Chou Y.J., Teng C., Do consumers perceive money-back guarantees as believable? 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L., Sapp S., Laczniak R., Consumer adoption of the internet: the case of apparel shopping, Psychology and Marketing, 20, 12, pp. 1095-1118, (2003); Zeithaml V.A., Parasuraman A., Malhotra A., Service quality delivery through websites: a critical review of extant knowledge, Journal of the Academy of Marketing Science, 30, 4, pp. 362-375, (2002)","M.A. Sanjeev; Symbiosis Center for Management and Human Resources Development, Symbiosis International (Deemed University), Pune, India; email: ma_sanjeev@scmhrd.edu",null,"Inderscience Publishers",{"$nulls":5},1.468433E7,null,null,null,"English","Int. J. Manage. Enterp. Dev.","Article","Final",null,"Scopus","2-s2.0-85153859150"]
["Deepthi B.; Bansal V.","Deepthi, B. (57686785400); Bansal, Vikram (57959606900)","57686785400; 57959606900","Employing TAM model to investigate the factors influencing quick commerce applications adoption using structural equation modelling technique",2023.0,"International Journal of Management and Enterprise Development",22.0,4.0,null,348.0,365.0,17.0,0.0,"10.1504/IJMED.2023.134670","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85177200397&doi=10.1504%2fIJMED.2023.134670&partnerID=40&md5=db61a632fa21824ccf4d146cda2520aa","Atal Bihari Vajpayee School of Management and Entrepreneurship, Jawaharlal Nehru University, New Delhi, India","Deepthi B., Atal Bihari Vajpayee School of Management and Entrepreneurship, Jawaharlal Nehru University, New Delhi, India; Bansal V., Atal Bihari Vajpayee School of Management and Entrepreneurship, Jawaharlal Nehru University, New Delhi, India","Quick commerce applications are increasingly extending their footprint all over the world as a direct consequence of the increasing need for speedy delivery from today’s consumers. Quick commerce, also known as q-commerce, is the next generation of e-commerce, and as the name indicates, it is all about being quick. Q-commerce also goes by the moniker quick commerce. Utilising the technology acceptance model (TAM), the objective of this study is to identify the factors that have the most impact on the degree to which people are willing to use Q-commerce apps. In order to validate the hypotheses included within the suggested model, the structural equation modelling (SEM) technique was used. This study makes use of survey research, and the data was gathered from 277 participants residing in various metropolitan cities in India. According to the findings, the link between the intention of ordering through Q-commerce apps and the perceived benefits (PB), perceived ease of use (PEU), social influence (SI) and socio-demographic factors (SDF) are significantly and positively correlated with one another. The study’s results may aid organisations operating in the Q-commerce market in comprehending the aspects influencing the customers’ ordering behaviour. Copyright © 2023 Inderscience Enterprises Ltd.","Q-commerce; SEM; structural equation modelling; TAM; technology acceptance model",{"$nulls":7},"Ahmad N., Feroz I., Anjum A., Usability analysis of educational information systems from student’s perspective, Proceedings of the 2020 International Conference on Big Data in Management, pp. 130-135, (2020); Ajzen I., From intentions to actions: a theory of planned behaviour, Action Control, pp. 11-39, (1985); Ajzen I., The theory of planned behaviour, Organizational Behaviour and Human Decision Processes, 50, 2, pp. 179-211, (1991); Ajzen I., Fishbein M., Understanding Attitudes and Predicting Social Behaviour, (1980); Almaiah M.A., Alamri M.M., Proposing a new technical quality requirements for mobile learning applications, J. Theor. Appl. Inf. 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Venkatesh V., Davis F.D., A theoretical extension of the technology acceptance model: Four longitudinal field studies, Management Science, 46, 2, pp. 186-204, (2000); Venkatesh V., Morris M.G., Davis G.B., Davis F.D., User acceptance of information technology: toward a unified view, MIS Quarterly, 27, 3, pp. 425-478, (2003); Venkatesh V., Thong J.Y., Xu X., Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology, MIS Quarterly, 36, 1, pp. 157-178, (2012); Weimann G., The strength of weak conversational ties in the flow of information and influence, Social Networks, 5, 3, pp. 245-267, (1983); Wymer S.A., Regan E.A., Factors influencing e‐commerce adoption and use by small and medium businesses, Electronic Markets, 15, 4, pp. 438-453, (2005); Zhang Z., Gu C., Effects of consumer social interaction on trust in online group-buying contexts: an empirical study in China, Journal of Electronic Commerce Research, 16, 1, (2015)","B. Deepthi; Atal Bihari Vajpayee School of Management and Entrepreneurship, Jawaharlal Nehru University, New Delhi, India; email: deepthy.spandan@gmail.com",null,"Inderscience Publishers",{"$nulls":5},1.468433E7,null,null,null,"English","Int. J. Manage. Enterp. Dev.","Article","Final",null,"Scopus","2-s2.0-85177200397"]
["Viet N.Q.; de Leeuw S.; van Herpen E.","Viet, Nguyen Quoc (57200566153); de Leeuw, Sander (24402540300); van Herpen, Erica (7801408497)","57200566153; 24402540300; 7801408497","The impact of social vs environmental sustainability information disclosure on consumer choice of delivery time with varying sustainability concerns",2023.0,"International Journal of Physical Distribution and Logistics Management",53.0,11.0,null,26.0,52.0,26.0,2.0,"10.1108/IJPDLM-09-2021-0392","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85152577934&doi=10.1108%2fIJPDLM-09-2021-0392&partnerID=40&md5=0e17a0f7cb9723aa02aaedb35d567320","Operations Research and Logistics Group, Marketing and Consumer Behaviour Group, Wageningen University and Research, Wageningen, Netherlands; Operations Research and Logistics Group, Wageningen University and Research, Wageningen, Netherlands; Nottingham Business School, Nottingham Trent University, Nottingham, United Kingdom; Marketing and Consumer Behaviour Group, Wageningen University and Research, Wageningen, Netherlands","Viet N.Q., Operations Research and Logistics Group, Marketing and Consumer Behaviour Group, Wageningen University and Research, Wageningen, Netherlands; de Leeuw S., Operations Research and Logistics Group, Wageningen University and Research, Wageningen, Netherlands, Nottingham Business School, Nottingham Trent University, Nottingham, United Kingdom; van Herpen E., Marketing and Consumer Behaviour Group, Wageningen University and Research, Wageningen, Netherlands","Purpose: This paper investigates the impact of sustainability information disclosure on consumers' choice of order-to-delivery lead-time in relation to consumers' sustainability concern. Design/methodology/approach: Based on two choice experiments with participants from the Netherlands (n = 348) and the United Kingdom (n = 1,387), the impact of sustainability information disclosure was examined in connection with consumers' concerns for environmental and social sustainability. Information on environmental impact (carbon emission) and social impact (warehouse workers and drivers' well-being) was considered and compared. Findings: Disclosing sustainability impact information significantly increased consumers' preference and choice for longer delivery times, with equivalent effects for environmental and social impact information. Consumers' relevant (environmental or social) sustainability concern as personality traits enhanced effects on preferences, as did priming of environmental concern. Research limitations/implications: Future research may consider differences between product categories or e-commerce companies' reputation in sustainability activities. Practical implications: The findings provide opportunities for online retailers to influence consumer choice of delivery time, especially through disclosing environmental and/or social sustainability information. Originality/value: This study fills a gap in the literature on sustainability information disclosure to actively steer consumer choice of delivery time, particularly regarding the effect of social sustainability impact information in comparison to its environmental counterpart. © 2023, Nguyen Quoc Viet, Sander de Leeuw and Erica van Herpen.","Choice experiment; Consumer behavior; Delivery preference; Last-mile logistics; Online retail; Priming",{"$nulls":7},"Abbasi M., Nilsson F., Developing environmentally sustainable logistics. 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Eco-labels and quality in the organic wine market, Business and Society, 56, 2, pp. 318-356, (2017); Dhar R., Kim E.Y., Seeing the forest or the trees: implications of construal level theory for consumer choice, Journal of Consumer Psychology, 17, 2, pp. 96-100, (2007); Online shopping ever more popular in 2020, (2021); Fisher M.L., Santiago G., Xu J.J., The value of rapid delivery in omnichannel retailing, Journal of Marketing Research, 56, 5, pp. 732-748, (2019); Francis J.E., Davis T., Adolescents' sustainability concerns and reasons for not consuming sustainably, International Journal of Consumer Studies, 39, 1, pp. 43-50, (2015); Gawor T., Hoberg K., Customers' valuation of time and convenience in e-fulfillment, International Journal of Physical Distribution and Logistics Management, 49, 1, pp. 75-98, (2019); Harmon-Jones E., Harmon-Jones C., Cognitive dissonance theory after 50 Years of development, Zeitschrift Fur Sozialpsychologie, 38, 1, pp. 7-16, (2007); Harmon-Jones E., Mills J., An introduction to cognitive dissonance theory and an overview of current perspectives on the theory, Cognitive Dissonance: Reexamining a Pivotal Theory in Psychology, pp. 3-24, (2019); Haws K.L., Page Winterich K., Naylor R.W., Seeing the world through GREEN-tinted glasses: green consumption values and responses to environmentally friendly products, Journal of Consumer Psychology, 24, 3, pp. 336-354, (2014); Hosta M., Zabkar V., Antecedents of environmentally and socially responsible sustainable consumer behavior, Journal of Business Ethics, 171, 2, pp. 273-293, (2021); Leading retailers set to test environmental labels, as IGD mobilises industry to develop harmonised solution, (2022); Ignat B., Chankov S., Do E-commerce customers change their preferred last-mile delivery based on its sustainability impact?, The International Journal of Logistics Management, 31, 3, pp. 521-548, (2020); IRU's annual global driver shortage survey, (2022); Jaller M., Pahwa A., Evaluating the environmental impacts of online shopping: a behavioral and transportation approach, Transportation Research Part D: Transport and Environment, 80, (2020); Ji-Hyland C., Allen D., What do professional drivers think about their profession? An examination of factors contributing to the driver shortage, International Journal of Logistics Research and Applications, 25, 3, pp. 231-246, (2022); Lee E.-J., Choi H., Han J., Kim D.H., Ko E., Kim K.H., How to ‘Nudge’ your consumers toward sustainable fashion consumption: an FMRI investigation, Journal of Business Research, 117, September 2019, pp. 642-651, (2020); Liobikiene G., Bernatoniene J., Why determinants of green purchase cannot be treated equally? The case of green cosmetics: literature review, Journal of Cleaner Production, 162, pp. 109-120, (2017); Lynn A., Lynn M., Experiments and quasi-experiments: methods for evaluating marketing options, Cornell Hotel and Restaurant Administration Quarterly, 44, 2, pp. 75-84, (2003); Mangiaracina R., Perego A., Seghezzi A., Tumino A., Innovative solutions to increase last-mile delivery efficiency in B2C e-commerce: a literature review, International Journal of Physical Distribution and Logistics Management, 49, 9, pp. 901-920, (2019); Miller J.W., Golicic S.L., Fugate B.S., Developing and testing a dynamic theory of motor carrier safety, Journal of Business Logistics, 38, 2, pp. 96-114, (2017); Motoshita M., Sakagami M., Kudoh Y., Tahara K., Inaba A., Potential impacts of information disclosure designed to motivate Japanese consumers to reduce carbon dioxide emissions on choice of shopping method for daily foods and drinks, Journal of Cleaner Production, 101, pp. 205-214, (2015); Munoz-Villamizara A., Velazquez-Martineza J.C., Haroa P., Ferrera A., Marino R., The environmental impact of fast shipping ecommerce in inbound logistics operations: a case study in Mexico, Journal of Cleaner Production, 283, (2021); Nguyen D.H., de Leeuw S., Dullaert W., Bram P., Foubert J., What is the right delivery option for you? Consumer preferences for delivery attributes in online retailing, Journal of Business Logistics, 40, 4, pp. 299-321, (2019); Reczek R.W., Trudel R., White K., Focusing on the forest or the trees: how abstract vs concrete construal level predicts responses to eco-friendly products, Journal of Environmental Psychology, 57, pp. 87-98, (2018); Rondoni A., Grasso S., Consumers behaviour towards carbon footprint labels on food: a review of the literature and discussion of industry implications, Journal of Cleaner Production, 301, (2021); Sallnas U., Bjorklund M., Consumers’ influence on the greening of distribution–exploring the communication between logistics service providers, e-tailers and consumers, International Journal of Retail and Distribution Management, 48, 11, pp. 1177-1193, (2020); Shao J., Unal E., What do consumers value more in green purchasing ? Assessing the sustainability practices from demand side of business, Journal of Cleaner Production, 209, pp. 1473-1483, (2019); Thogersen J., Alfinito S., Goal activation for sustainable consumer choices: a comparative study of Denmark and Brazil, Journal of Consumer Behaviour, 19, 6, pp. 556-569, (2020); Thomas R., Darby J.L., Dobrzykowski D., Hoek R., Decomposing social sustainability: signaling theory insights into supplier selection decisions, Journal of Supply Chain Management, 57, 4, pp. 117-136, (2021); Tokar T., Williams B.D., Fugate B.S., I heart logistics—just don't ask me to pay for it: online shopper behavior in response to a delivery carrier upgrade and subsequent shipping charge increase, Journal of Business Logistics, 41, 3, pp. 182-205, (2020); Trope Y., Liberman N., Construal-level theory of psychological distance, Psychological Review, 117, 2, (2010); Wang X., Yuen K.F., Wong Y.D., Teo C.C., It is green, but is it fair? Investigating consumers' fairness perception of green service offerings, Journal of Cleaner Production, 181, pp. 235-248, (2018); White K., Habib R., Hardisty D.J., How to shift consumer behaviors to Be more sustainable: a literature review and guiding framework, Journal of Marketing, 83, 3, pp. 22-49, (2019)","S. de Leeuw; Operations Research and Logistics Group, Wageningen University and Research, Wageningen, Netherlands; email: sander.deleeuw@wur.nl",null,"Emerald Publishing",{"$nulls":5},9600035.0,null,null,null,"English","Int. J. Phys. Distrib. Logist. Manage.","Article","Final","All Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85152577934"]
["Uvet H.; Dickens J.; Anderson J.; Glassburner A.; Boone C.A.","Uvet, Hasan (57216582084); Dickens, John (57225691670); Anderson, Jason (57191975185); Glassburner, Aaron (57202422793); Boone, Christopher A. (57214709692)","57216582084; 57225691670; 57191975185; 57202422793; 57214709692","A hybrid e-logistics service quality approach: modeling the evolution of B2C e-commerce",2023.0,"International Journal of Logistics Management",{"$nulls":6},0.0,"10.1108/IJLM-06-2023-0238","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85176947279&doi=10.1108%2fIJLM-06-2023-0238&partnerID=40&md5=15e65811afa8a682362c660ae4113ae5","Department of Economics, Marketing, and Supply Chain Management, School of Business, Georgia Gwinnett College, Lawrenceville, GA, United States; Department of Operational Sciences, Graduate School of Engineering and Management, Air Force Institute of Technology, Wright-Patterson AFB, OH, United States; Department of Marketing Quantitative Analysis and Business Law, College of Business, Mississippi State University, Mississippi State, MS, United States","Uvet H., Department of Economics, Marketing, and Supply Chain Management, School of Business, Georgia Gwinnett College, Lawrenceville, GA, United States; Dickens J., Department of Operational Sciences, Graduate School of Engineering and Management, Air Force Institute of Technology, Wright-Patterson AFB, OH, United States; Anderson J., Department of Operational Sciences, Graduate School of Engineering and Management, Air Force Institute of Technology, Wright-Patterson AFB, OH, United States; Glassburner A., Department of Operational Sciences, Graduate School of Engineering and Management, Air Force Institute of Technology, Wright-Patterson AFB, OH, United States; Boone C.A., Department of Marketing Quantitative Analysis and Business Law, College of Business, Mississippi State University, Mississippi State, MS, United States","Purpose: This research paper aims to examine two hybrid models of logistics service quality (LSQ) and its influence on satisfaction, loyalty and future purchase intention in a business-to-consumer (B2C) e-commerce context. This study extends the literature for LSQ by incorporating the second-order assurance quality construct, which comprises personnel contact quality, order discrepancy handling and order returns, into one of the hybrid models. Design/methodology/approach: A survey-based approach is used to collect data. Participant responses to questions concerning multiple LSQ dimensions and behavioral perceptions from their most recent online shopping experience are measured using structural equation modeling. Findings: Findings highlight the importance of including a second-order construct assurance quality as a more explanatory model. Results illustrate that online ordering procedures and assurance quality impact customer satisfaction more than other prominent LSQ dimensions. Furthermore, the findings revealed a customer loyalty is a partial mediator between customer satisfaction and future purchase intention. This underscores the significance of improved logistics services as a competitive edge for e-commerce retailers. Research limitations/implications: Implications are limited to the e-commerce B2C domain. Practical implications: The findings of this study underscore critical LSQ dimensions that garner greater satisfaction and retention in the online shopping experience. The results indicate that the effective and efficient handling of the initial order and any order problem significantly influences customer satisfaction and reaps the long-term benefits of customer retention. Originality/value: The authors present and empirically test a hybrid model of LSQ in a B2C e-commerce domain that captures many of the important elements of the customer experience as espoused in the literature. © 2023, Emerald Publishing Limited.","Customer satisfaction; E-commerce; Future purchase intention; Logistics service quality; Loyalty; Online retail",{"$nulls":7},{"$cut":{"chars":25068,"head":"Abrams V.K., Global ecommerce forecast 2021, (2021); Adana S., Manuj I., Herburger M., Cevikparmak S., Celik H., Uvet H., Linking decentralization in decision-making to resilience outcomes: a supply chain orientation perspective, The International Journal of Logistics Management, (2023); Aguinis H., Villamor I., Ramani R.S., MTurk research: review and recommendations, Journal of Management, 47, 4, pp. 823-837, (2021); Amorim P., Dehoratius N., Online shoppers don't always care about faster delivery, MIT Sloan Management Review, 63, 1, pp. 12-14, (2021); Anderson J.C., Gerbing D.W., Structural equation modeling in practice: a review and recommended two-step approach, Psychological Bulletin, 103, 3, pp. 411-423, (1988); Bagozzi R.P., Yi Y., On the evaluation of structural equation models, Journal of the Academy of Marketing Science, 16, 1, pp. 74-94, (1988); Bentler P.M., Comparative fit indexes in structural models, Psychological Bulletin, 107, 2, pp. 238-246, (1990); Bentler P.M., Bonett D.G., Significance tests and goodness of fit in the analysis of covariance structures, Psychological Bulletin, 88, 3, (1980); Bhattacharjya J., Ellison A., Tripathi S., An exploration of logistics related customer service provision on Twitter: the case of e-retailers, International Journal of Physical Distribution and Logistics Management, 46, 6-7, pp. 659-680, (2016); Bhattacherjee A., Understanding information systems continuance: an expectation-confirmation model, MIS Quarterly, 25, 3, pp. 351-370, (2001); Bianchi E., Bruno J.M., Sarabia-Sanchez F.J., The impact of perceived CSR on corporate reputation and purchase intention, European Journal of Management and Business Economics, 28, pp. 206-221, (2019); Bienstock C.C., Mentzer J.T., Bird M.M., Measuring physical distribution service quality, Journal of the Academy of Marketing Science, 25, 1, pp. 31-44, (1997); Bienstock C.C., Royne M.B., Sherrell D., Stafford T.F., An expanded model of logistics service quality: incorporating logistics information technology, International Journal of Production Economics, 113, 1, pp. 205-222, (2008); Bollen K.A., Stine R.A., Bootstrapping goodness-of-fit measures in structural equation models, Sociological Methods and Research, 21, 2, pp. 205-229, (1992); Bouzaabia R., Bouzaabia O., Capatina A., Retail logistics service quality: a cross‐cultural survey on customer perceptions, International Journal of Retail and Distribution Management, 41, 8, pp. 627-647, (2013); Cao M., Zhang Q., Supply chain collaboration: impact on collaborative advantage and firm performance, Journal of Operations Management, 29, 3, pp. 163-180, (2011); Cao Y., Ajjan H., Hong P., Post-purchase shipping and customer service experiences in online shopping and their impact on customer satisfaction: an empirical study with comparison, Asia Pacific Journal of Marketing and Logistics, 30, 2, pp. 400-416, (2018); Cevikparmak S., Celik H., Adana S., Uvet H., Sauser B., Nowicki D., Scale development and validation of Transaction Cost Economics typology for contracts: a systems thinking approach, Journal of Purchasing and Supply Management, 28, 3, (2022); Chernev A., Blair S., Doing well by doing good: the benevolent halo of corporate social responsibility, Journal of Consumer Research, 41, 6, pp. 1412-1425, (2015); Chi H.K., Yeh H.R., Shih C., The impact of brand awareness on consumer purchase intention: the mediating effect of perceived quality and brand loyalty, Journal of International Management Studies, 4, 1, pp. 135-144, (2009); Cho E., Making reliability reliable: a systematic approach to reliability coefficients, Organizational Research Methods, 19, 4, pp. 651-682, (2016); Closs D.J., Savitskie K., Internal and external logistics information technology integration, The International Journal of Logistics Management, 14, 1, pp. 63-76, (2003); Collier J.E., Bienstock C.C., Measuring service quality in e-retailing, Journal of Service Research, 8, 3, pp. 260-275, (2006); Collins A., Henchion M., O'Reilly P., Logistics customer service: performance of Irish food exporters, Internation"}},"H. Uvet; Department of Economics, Marketing, and Supply Chain Management, School of Business, Georgia Gwinnett College, Lawrenceville, United States; email: huvet@ggc.edu",null,"Emerald Publishing",{"$nulls":5},9574093.0,null,null,null,"English","Int. J. Logist. Manage.","Article","Article in press",null,"Scopus","2-s2.0-85176947279"]
["Dahan A.A.","Dahan, A.A. (57216511095)",5.7216511095E10,"Digital Shopping and Consumers’ Perceptions in the United Arab Emirates",2023.0,"Journal of Statistics Applications and Probability",12.0,3.0,null,1373.0,1383.0,10.0,0.0,"10.18576/jsap/120339","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85168280561&doi=10.18576%2fjsap%2f120339&partnerID=40&md5=17006d73e3b89c11710e3b175b3b077d","Finance and Accounting Department, Faculty of Business Administration, American University in the Emirates, Dubai, United Arab Emirates","Dahan A.A., Finance and Accounting Department, Faculty of Business Administration, American University in the Emirates, Dubai, United Arab Emirates","The purpose of this research is to analyse the perception of digital shoppers in the United Arab Emirates (UAE)., A survey was conducted, which included: students, employees, and professionals from different fields of UAE society. The findings show about 89 percent of those surveyed are familiar with online shopping and some of them are found comfortable that their personal information is kept confidential. Some participants still have concerns about the safety and the accuracy of online shopping. The findings show that about 45 percent of those surveyed think that online shopping is still risky. The results also show that about 20 percent of the surveyed population believe that delay in product delivery, lack of accuracy on websites, and information insufficiency are reasons services that do not comply with the needs of buyers and therefore still prefer traditional shopping over online shopping. The study concludes that there is a need for building safety awareness among shoppers which companies need to focus on. Furthermore, companies need to continually improve its offering of online services. This will result in providing customers with accurate information and in enhancing the products’ time delivery. © 2023 NSP Natural Sciences Publishing Cor.","Digital shopping consumer's perception; economic analysis",{"$nulls":7},"Lowe A., UAE holds largest share of e-commerce sales in region, (2012); Ghandour A., An Analysis of Factors Affecting Growth and Barriers of E-Commerce in UAE, International Conference on Intelligent Systems, Control & Manufacturing Technology (ICICMT’2015); Timers P., Electronic Commerce - strategies & models for business-to business trading, (2002); Zhou L., Dai L., Zhang D., Online Shopping Acceptance Model - A Factors in Online Shopping, Journal of Electronic Commerce Research, 8, 1, (2007); Bhattacherjee A, Understanding information systems continuance: an expectation confirmation model, MIS Quarterly, 25, 3, pp. 351-370, (2001); Hsu C.L., Lu H.P., Why do people play on-line games? 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Delivering online shopping convenience to enhance customer satisfaction and encourage e-WOM, Journal of Retailing and Consumer Services, 44, pp. 161-169, (2018); Hidayat A., Wijaya T., Ishak A., Catyanadika P., Consumer Trust as the Antecedent of Online Consumer Purchase Decision, Information Article – MDPI, Information, 12, (2021); Singh S., Study of Consumer Perception of Digital Payment Mode, Journal of Internet Banking and Commerce, (2017); Gao F., A study of online purchase intention: based on the perspective of customer trust, International Conference on Management and Service Science, MASS, (2011); Check I., Ho Y., Consumer electronics e-retailing: why the alliance of vendors’ e-service quality, trust and trustworthiness matters, Procedia – Soc. Behav. Sci, 219, pp. 804-800, (2016); Chang K., Cheung W., Tang M., Building trust online: interactions among trust building mechanisms, Inf. 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Lib, 35, pp. 2-20, (2017); Ying Li C., How social Commerce constructs influence customers' social shopping intention? An empirical study of a social commerce website, Technological Forecasting and Social Change, 144, pp. 282-294, (2019)","A.A. Dahan; Finance and Accounting Department, Faculty of Business Administration, American University in the Emirates, Dubai, United Arab Emirates; email: abdulkarim.dahan@aue.ae",null,"Natural Sciences Publishing",{"$nulls":5},2.0908423E7,null,null,null,"English","J. Stat. App. Prob.","Article","Final",null,"Scopus","2-s2.0-85168280561"]
["Kumar V.; Nanda P.","Kumar, Vikas (55239201700); Nanda, Pooja (57220414320)","55239201700; 57220414320","Determinants of the success of MSMEs in India: a policy vs. technology perspective",2023.0,"International Journal of Technology, Policy and Management",23.0,1.0,null,102.0,122.0,20.0,0.0,"10.1504/IJTPM.2023.129471","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85153850061&doi=10.1504%2fIJTPM.2023.129471&partnerID=40&md5=df5cbf7a55946ba8318ed449332ef0b8","Central University of Haryana, Jant-Pali, Haryana, Mahendragarh, 123031, India; Sushant University, Sector 55, Golf Course Road, Haryana, Gurugram, 122011, India","Kumar V., Central University of Haryana, Jant-Pali, Haryana, Mahendragarh, 123031, India; Nanda P., Sushant University, Sector 55, Golf Course Road, Haryana, Gurugram, 122011, India","The Indian micro, small and medium enterprises (MSMEs) sector is extremely diverse in terms of size, variety of products, service areas, and types of technology being used. It supports the industrial development of rural and backward areas, decreasing provincial discrimination, and ensuring better, unbiased delivery of national revenue and capital. This paper explores the various aspects of the development of MSMEs in India from the perspectives of technology and policy. Specific roles of technology along with domestic and international policies have been analysed to identify their impact on the development of MSMEs. Internet, e-commerce, mobile communication, online payment systems, computer aided designing and social media have been identified as the most important technological determinants of the success of MSMEs. Whereas the impact and provisions of a number of government schemes and initiatives have been presented along with their role in the development of specific categories of MSMEs. Copyright © 2023 Inderscience Enterprises Ltd.","digital India; export lines of credit; government policy; micro, small and medium enterprises; MSMEs; technology integration","Mobile commerce; Digital india; Export line; Export line of credit; Micro-enterprises; Product service; Service area; Small-and-medium enterprise; Technology Integration; Online systems",{"$nulls":6},"Ahad M.T., Exploring the usage of the mobile phones by SMEs in the achievement of vision 2020 goals, Journal of Mobile Technologies, Knowledge, and Society, 2016, 2016, pp. 1-18, (2016); Ainin S., Parveen F., Moghavvemi S., Jaafar N.I., Shuib N.L.M., Factors influencing the use of social media by SMEs and its performance outcomes, Industrial Management and Data Systems, 115, 3, pp. 570-588, (2015); Ayodeji O.G., Kumar V., Social media analytics: a tool for the success of online retail industry, Int. J. Services Operations and Informatics, 10, 1, pp. 79-95, (2019); Ayodeji O.G., Kumar V., Web analytics and online retail: ethical perspective, techniques and practices, International Journal of Technoethics (IJT), 11, 2, pp. 18-33, (2020); Bala Subrahmanya M.H., Small industry and globalization: implications, performance and prospects, Economic and Political Weekly, 29, 18, pp. 1826-1834, (2004); Bargal H., Dashmishra M., Sharma A., Performance analysis of small scale industries – A study of pre-liberalization and post-liberalization period, International Journal of Business and Management, 1, 2, pp. 17-26, (2009); Bhattarai K., Negi V., FDI and economic performance of firms in India, Studies in Microeconomics, 8, 1, pp. 44-74, (2020); Bi Z.M., Lang S.Y., Shen W., Wang L., Reconfigurable manufacturing systems: the state of the art, International Journal of Production Research, 46, 4, pp. 967-992, (2008); (2018); (2019); (2019); Chew H.E., Ilavarasan P.V., Levy M.R., When there’s a will, there might be a way: the economic impact of mobile phones and entrepreneurial motivation on female-owned microenterprises, Proceedings of the Sixth International Conference on Information and Communication Technologies and Development: Full Papers-Volume, 1, pp. 196-204, (2013); (2021); Dannenberg P., Lakes T., The use of mobile phones by Kenyan exportOrientated small-scale farmers: insights from fruit and vegetable farming in the Mt. 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(2019); (2018); The New Wave Indian MSME-An action agenda for growth, (2016); Kumar V., Gupta G., Strategic Management During a Pandemic, (2021); Kumar V., Ayodeji O.G., Determinants of the success of online retail in India, International Journal of Business Information Systems (IJBIS), 37, 2, pp. 246-262, (2021); Kumar V., Nanda P., Social media to social media analytics: ethical challenges, International Journal of Technoethics (IJT), 10, 2, pp. 57-70, (2019); Kumar V., Nanda P., Social media as a tool in higher education: a pedagogical perspective, Handbook of Research on Diverse Teaching Strategies for the Technology-Rich Classroom, IGI Global, pp. 239-253, (2020); Kumar V., Pradhan P., Reputation management through online feedbacks in e-business environment, International Journal of Enterprise Information Systems (IJEIS), 12, 1, pp. 21-37, (2016); Kumar V., Saurabh M., Mobile marketing campaigns: practices, challenges and opportunities, International Journal of Business Innovation and Research (IJBIR), 21, 4, pp. 523-539, (2020); Kumar V., Vidhyalakshmi P., Cloud computing for business sustainability, Asia-Pacific Journal of Management Research and Innovation, 8, 4, pp. 461-474, (2012); Lata M., Kumar V., Smart energy management in green cities, Handbook of Green Engineering Technologies for Sustainable Smart Cities, pp. 105-120, (2021); Laudon K.C., Laudon J.P., Management Information Systems, (2015); Mishra P., Study on impact of digital transformation on MSME growth prospects in India, International Journal of Research and Analytical Reviews, 6, 1, pp. 611-613, (2019); Mittal S., Kumar V., Adoption of mobile wallets in India: an analysis, IUP Journal of Information Technology, 14, 1, pp. 42-57, (2018); Mohanty J.J., A study on micro, small and medium enterprises (MSMEs) in India: status and its performance, International Journal of Research and Scientific Innovation (IJRSI), 5, 5, pp. 106-113, (2018); Monthly Economic Review, (2020); MSME (2017–2018) Annual Report Government of India; MSME (2020–2021) Annual Report Government on India; Mukherjee S., Challenges to Indian micro small scale and medium enterprises in the era of globalization, Journal of Global Entrepreneurship Research, 8, 1, pp. 1-19, (2018); Mustapha S., E-payment technology effect on bank performance in emerging economies–evidence from Nigeria, Journal of Open Innovation: Technology, Market, and Complexity, 4, 4, pp. 43-57, (2018); Neirotti P., Raguseo E., Paolucci E., How SMEs develop ICT-based capabilities in response to their environment, Journal of Enterprise Information Management, 31, 1, pp. 10-37, (2018); Neog N., Usage of digital banking services by rural population: a study in Sivasagar district of Assam, International Journal of Scientific and Technology Research, 8, 12, pp. 3301-3304, (2019); Ojo A., Janowski T., Awotwi J., Enabling development through governance and mobile technology, Government Information Quarterly, 30, pp. S32-S45, (2013); Eleventh Five Year Plan, (2008); Pooja P., Micro, Small and Medium Enterprises (MSMEs) in the Indian Economy Business Development Strategy, (2009); (2021); (2019); Rotberg R.I., Aker J.C., Mobile phones: uplifting week and failed states, The Washington Quarterly, 36, 1, pp. 111-125, (2013); Saurabh M., Kumar V., Technology integration for the success of B2C M-commerce in India: opportunities and challenges, IUP Journal of Information Technology, 13, 1, pp. 24-35, (2017); Shabbir M.S., Ghazi M.S., Mehmood A.R., Impact of social media applications on small business entrepreneurs, Arabian Journal of Business and Management Review, 6, 3, pp. 203-205, (2016); Shaik M., Ramesh K., Ajay Kumar K., Sekhar Babu G., Performance of MSMEs sector in India, SSRG International Journal of Economics and Management Studies, 4, 3, pp. 608-614, (2017); Singh P., Singh D., Technology development in MSMEs, International Journal of Application Or Innovation in Engineering and Management (IJAIEM), 3, 3, pp. 164-170, (2014); (2021); Kumar S.V., Ernestivita G., Entrepreneurial parameters and performance of MSMEs in east java province of Indonesia, International Journal of Business Innovation and Research (IJBIR), 23, 2, pp. 267-282, (2020); 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Nanda; Sushant University, Gurugram, Sector 55, Golf Course Road, Haryana, 122011, India; email: poojan73@gmail.com",null,"Inderscience Publishers",{"$nulls":5},1.4684322E7,null,null,null,"English","Int. J. Technol. Policy Manage.","Article","Final",null,"Scopus","2-s2.0-85153850061"]
["Kalkha H.; Khiat A.; Bahnasse A.; Ouajji H.","Kalkha, Hicham (57452283100); Khiat, Azeddine (57193027037); Bahnasse, Ayoub (57189848864); Ouajji, Hassan (57188879248)","57452283100; 57193027037; 57189848864; 57188879248","The Rising Trends of Smart E-Commerce Logistics",2023.0,"IEEE Access",11.0,null,null,33839.0,33857.0,18.0,3.0,"10.1109/ACCESS.2023.3252566","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85149873391&doi=10.1109%2fACCESS.2023.3252566&partnerID=40&md5=798b6ee88b47149ba5829913c6e1df1a","University Hassan II of Casablanca, Laboratory Computing, Artificial Intelligence and Cyber Security (2IACS), ENSET of Mohammedia, Casablanca, 20000, Morocco; ENSAM of Casablanca, Laboratory Engineering of Structures, Processes, Intelligent Systems, and Computer Science (ISPS2I), Casablanca, 20670, Morocco","Kalkha H., University Hassan II of Casablanca, Laboratory Computing, Artificial Intelligence and Cyber Security (2IACS), ENSET of Mohammedia, Casablanca, 20000, Morocco; Khiat A., University Hassan II of Casablanca, Laboratory Computing, Artificial Intelligence and Cyber Security (2IACS), ENSET of Mohammedia, Casablanca, 20000, Morocco; Bahnasse A., ENSAM of Casablanca, Laboratory Engineering of Structures, Processes, Intelligent Systems, and Computer Science (ISPS2I), Casablanca, 20670, Morocco; Ouajji H., University Hassan II of Casablanca, Laboratory Computing, Artificial Intelligence and Cyber Security (2IACS), ENSET of Mohammedia, Casablanca, 20000, Morocco","Smart Logistics (SL) offers a competitive advantage for e-commerce by utilizing Information and Communication Technologies (ICT) such as IoT, AI, Blockchain, Cloud computing, 5G, etc. This technology automates, optimizes, and enables real-time tracking and monitoring of shipments, predicts, and prevents delays, and optimizes delivery routes and schedules. It also provides greater visibility and control, allowing e-commerce businesses to react quickly and efficiently to changes in demand or supply. The purpose of this study is to investigate the impact of digitalization on trade logistics in e-commerce, emphasizing the significance of smart logistics for the e-commerce industry. We reviewed 288 articles published in the last decade in the Scopus database to assess the maturity of research in this area. For researchers, this study provides a better understanding of smart e-commerce logistics and identifies research gaps in the literature. For e-commerce professionals, it can help them adopt the latest technological trends in their logistics. Through a systematic literature review and network analysis approach, the study has contributed by identifying 5 clusters related to ICT application fields in e-commerce and 5 clusters related to important ICT enablers in smart logistics. We also identified several research gaps and areas for future study, including the underutilization of computer vision technology and the need for further research on product quality inspection and accessibility for people with disabilities. Additionally, we suggest exploring the power of deep learning to solve Vehicle Routing Problems (VRP) and optimizing sensing data volume for minimizing costs associated with data storage and transfer. This study provides a comprehensive overview of the state of the art in smart logistics for e-commerce and serves as a guide for future research in this field.  © 2023 IEEE.","5G; artificial intelligence; blockchain; cloud computing; e-commerce logistics; ICT; information and communication technologies; SL; smart e-commerce logistics; Smart logistics; supply chain; trends","5G mobile communication systems; Blockchain; Cloud computing; Competition; Deep learning; Digital storage; Electronic commerce; Market Research; Vehicle routing; 5g; 5g mobile communication; Block-chain; Cloud-computing; E- commerces; E-commerce logistic; Information and Communication Technologies; Market researches; Mobile communications; Smart e-commerce logistic; Smart logistic; Systematic; Trend; Supply chains",{"$nulls":6},"Rejeb A., Simske S., Rejeb K., Treiblmaier H., Zailani S., Internet of Things research in supply chain management and logistics: A bibliometric analysis, Internet Things, 12, (2020); Lin B., Collins Cole J., Su R.K., Supply Chain Costing: An Activity-Based Perspective, (2001); Balouei Jamkhaneh H., Shahin R., Tortorella G.L., Analysis of logistics 4.0 service quality and its sustainability enabler scenarios in emerging economy, Cleaner Logistics Supply Chain, 4, (2022); Inamdar Z., Raut R., Narwane V.S., Gardas B., Narkhede B., Sagnak M., A systematic literature review with bibliometric analysis of big data analytics adoption from period 2014 to 2018, J. 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Finance, 11, 14, pp. 561-571, (2014); Praveen K.B., Kumar P., Prateek J., Pragathi G., Madhuri J., Inventory management using machine learning, Int. J. Eng. Res. Technol., 9, 6, pp. 866-869, (2020); Narayan A., Krishnan A., Ponraj A.S., IoT based comprehensive retail malpractice detection and payment system, Proc. IEEE Int. Conf. Electron., Comput. Commun. Technol. (CONECCT), pp. 1-8, (2020); Yamamoto Y., Kawabe T., Tsuruta S., Damiani E., Yoshitaka A., Mizuno Y., Knauf R., IoT-aware online shopping system enhanced with gaze analysis, Proc. World Autom. Congr. (WAC), pp. 1-6, (2016); Tang J., Liu F., Lu S., Qin S., Shao S., Research on the new generation electronic payment system applied in 'the belt and road, Proc. Int. Conf. e-commerce Internet Technol. (ECIT), pp. 5-9, (2020); Esenogho E., Djouani K., Kurien A.M., Integrating artificial intelligence Internet of Things and 5G for next-generation smartgrid: A survey of trends challenges and prospect, IEEE Access, 10, pp. 4794-4831, (2022); Huang Y., Wang X., Research on the influence of intelligent recommendation function on user behavior in highly digitized network platforms, Proc. IEEE Int. Conf. Electron. Technol., Commun. Inf. (ICETCI), pp. 250-254, (2021)","H. Kalkha; University Hassan II of Casablanca, Laboratory Computing, Artificial Intelligence and Cyber Security (2IACS), ENSET of Mohammedia, Casablanca, 20000, Morocco; email: hicham.kalkha-etu@etu.univh2c.ma",null,"Institute of Electrical and Electronics Engineers Inc.",{"$nulls":5},2.1693536E7,null,null,null,"English","IEEE Access","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85149873391"]
["Na X.; Lindu Z.; Jing C.; Hui Y.","Na, Xu (58510438600); Lindu, Zhao (24833408200); Jing, Chen (58510795400); Hui, Yu (58510974800)","58510438600; 24833408200; 58510795400; 58510974800","Research on community e-commerce supply chain cooperation with consideration of the Net Promoter Score (NPS); [考虑净推荐值( NPS) 的社区电商供应链 合作优化决策研究]",2023.0,"Journal of Industrial Engineering and Engineering Management",37.0,4.0,null,233.0,243.0,10.0,0.0,"10.13587/j.cnki.jieem.2023.04.020","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85166089132&doi=10.13587%2fj.cnki.jieem.2023.04.020&partnerID=40&md5=b649bed23411338afb9b9be52d485d99","Southeast University, School of Economics and Management, Nanjing, 210000, China; Shandong Technology and Business University, School of Business Administration, Yantai, 264005, China; Harbin University of Science and Technology, School of Automation, Harbin, 150080, China","Na X., Southeast University, School of Economics and Management, Nanjing, 210000, China, Shandong Technology and Business University, School of Business Administration, Yantai, 264005, China; Lindu Z., Southeast University, School of Economics and Management, Nanjing, 210000, China; Jing C., Southeast University, School of Economics and Management, Nanjing, 210000, China; Hui Y., Harbin University of Science and Technology, School of Automation, Harbin, 150080, China","The economic development of community stores directly affects people′s livelihood and the foundation of the community. A digital supply chain system can be built for community stores with the community e-commerce model, to effectively match people with goods, and to help community stores create a convenient 15-minute life circle. This paper discusses the optimized design for cooperative decision-making in community e-commerce platforms and community stores. Findings are of theoretical and practical significance, offering further insight on means to ensure the healthy and sustainable development of community e-commerce supply chains. In general, a community e-commerce supply chain is composed of a community e-commerce platform and a community store. Ecommerce platforms use either the “commission” or the “gross profit-sharing” model when cooperating with a community store. With the commission model, the community store receives commissions based on order quantity and acts as a service point to provide customers with delivery services. Community e-commerce platforms such as Meituan Youxuan and Duoduo Maicai cooperate with community stores using this model. The gross profit-sharing model involves an alliance between the platform and the community store, where a certain proportion of gross profit is divided between the parties. Community e-commerce platforms such as Tao CAI CAI and Jingxi use this model with community stores. The two cooperation models vary in terms of how profit is calculated, the levels of service offered by the community e-commerce platforms and small stores, and their products′ retail prices. Considering that community ecommerce comprises social and commercial aspects, its success is influenced by people who are willing to promote products and those who will not. The Net Promoter Score (NPS) collects this data. The “demand diffusion process” is provided with the “bass diffusion” model to describe the form-spread process of the word-of-mouth, and the market demand functions are constructed using the utility theory of consumer behavior. Game theory is also used to analyze key issues such as optimal service levels and cooperative decisionmaking, as well as the establishment of the final price for products by the community e-commerce platform and the small store under the two cooperation modes. The results show that: (1) Under the commission model, the optimal service level of small stores climbs with the increase of commission. However, the relationships between the commission and the final product price as well as the services offered on the platform and the market demand are comprehensively affected by the service cost coefficient of the platform and the community small stores. Thus, there are three different cooperation models identified. (2) Within a reasonable range, there is no ideal commission that would maximize a platform′s profits, which means that the commission model cannot guarantee the long-term development of community e-commerce business. (3) The service cost coefficient also affects the relationship between the sharing ratio and the final product price, the platform and convenience store service levels, as well as the gross-profit sharing ratio. This reflects the benefit distribution concept of “those who work more, get more”. (4) The consumer service sensitivity coefficient and the word-of-mouth diffusion coefficient also affect the optimal gross profit-sharing ratio, reminding managers to make the decision regarding gross-profit sharing based on the characteristics of consumer groups and product properties. (5) The greater the unit flow value under the two cooperation models, the greater the necessity for the platform and store to improve product quality and service levels. In summary, quality and price form the basis for the sustainable and healthy development of community e-commerce business, especially in the Internet era where “traffic is king”. It is not feasible to rely on low-price marketing to obtain traffic. Only by improving product quality and the purchase process, and leader service NPS value can ensure the retention of old customers and help attract new ones. Furthermore, cost reduction and increased efficiency are key to the development of community e-commerce. Relying on the digital management technology of the community e-commerce platform can help ensure the smart selection and manufacturingaccording-to-sale of products in small community stores. To improve marketing skills and service level through platform guidance, and to build an efficient and accurate supply chain operation system through connecting farmers, suppliers, products, consumer and demand information in real time. © 2023, Journal of Industrial Engineering and Engineering Management. All Rights Reserved.","Bath diffusion model; Community e-commerce; Net Promoter Score (NPS); Service level; Supply chain cooperation",{"$nulls":5},"National Natural Science Foundation of China, NSFC, (72071039); China Postdoctoral Science Foundation, (2021M690606); Natural Science Foundation of Shandong Province, (ZR2020QG022)","Received Date: 2022-05-06 　 　 　 Funded Project: Supported by the National Natural Science Foundation of China (72071039), the China Postdoctoral Science Foundation (2021M690606), and the Natural Science Foundation of Shandong Province(ZR2020QG022). ∗Corresponding author","Li P, Wei H, Wang G Y, Et al., Research on retailer's business model based on product quality and service level, Journal of Industrial Engineering/Engineering Management, 134, 5, pp. 169-182, (2020); Hu J S, Ji Y J, Ma D Q., Research on quality and service strategy of ECSC enterprises based on consumer utility, Systems Engineering-Theory & Practice, 40, 10, pp. 2602-2616, (2020); Duan Y L, Wang Y., Strategic introduction of the marketplace channel considering e-commerce platform service investment, Chinese Journal of Management Science, 30, 5, pp. 167-179, (2022); Hasiloglu M, Kaya O., An analysis of price, service and commission rate decisions in online sales made through E-commerce platforms [J], Computers & Industrial Engineering, 162, (2021); Wang Y Y, Fan R J, Shen L, Et al., Research on different dominant models of three-echelon e-commerce supply chain considering product quality and sales service, Journal of Industrial Engineering/Engineering Management, 35, 5, pp. 258-268, (2021); Wang Y, Fan R, Shen L, Et al., Decisions and coordination of green e-commerce supply chain considering green manufacturer* s fairness concerns, International Journal of Production Research, 58, 24, pp. 7471-7489, (2020); Liu M L, Dan B, Ma S X., Optimal strategies and coordination of fresh e-commerce supply chain considering freshness-keeping effort and value-added service [ J ], Chinese Journal of Management Science, 28, 8, pp. 76-88, (2020); Dan B, Zhang S G, Zhou M S., Strategies for warranty service in a dual-channel supply chain with value-added service competition [ J ], International Journal of Production Research, 56, 17, pp. 5677-5699, (2018); Ren X, Herty M, Zhao L., Optimal price and service decisions for sharing platform and coordination between manufacturer and platform with recycling [ J ], Computers & Industrial Engineering, 147, 3, (2020); You W, Shu H, Luo S., Competition, cooperation, and performance: an empirical investigation of Chinese online sellers [ J ], Information Systems and e-Business Management, 16, 4, pp. 743-760, (2018); Qiu Q J, Hao Z Y, Li Jiang, Strategic information flow under the influence of industry structure, European Journal of Operational Research, 298, 3, pp. 1175-1191, (2022); Niu B Z, Xie F F, Chen L, Et al., Join logistics sharing alliance or not? Incentive analysis of competing E-commerce firms with promised-delivery-time [ J ], International Journal of Production Economics, 224, (2020); Dan B, Zhang H Y, Zhang X M, Et al., Should an online manufacturer partner with a competing or noncompeting retailer for physical showrooms?, International Transactions in Operational Research, 28, 5, pp. 2691-2714, (2021); Li M L, Zhang X M, Dan B., Competition and cooperation in a supply chain with an offline showroom under asymmetric information [ J ], International Journal of Production Research, 58, 19, pp. 5964-5979, (2020); Wang P, Du S F, Hu L, Et al., Logistics choices in a platform supply chain: A co-opetitive perspective[ J], Journal of the Operational Research Society, 74, 1, pp. 93-111, (2023); Fan X, Yin Z, Liu Y., The value of horizontal cooperation in online retail channels [ J ], Electronic Commerce Research and Applications, 39, (2020); Zhu X, Yang C, Liu K, Et al., Cooperation and decision making in a two-sided market motivated by the externality of a third-party social media platform, Annals of Operations Research, 316, pp. 117-142, (2021); Tian Y, Dan B, Liu M L, Et al., Sales mode selection and coordination for an O2O fresh produce supply chain when freshness-keeping effort affecting demand, Chinese Journal of Management Science, 30, 8, pp. 173-184, (2022); Guo Z L, Chen J Q., Multigeneration product diffusion in the presence of strategic consumers [ J ], Information Systems Research, 29, 1, pp. 206-224, (2018); Cheng Y S, Li H Y, Anders T., Advance selling with double marketing efforts in a newsvendor framework [ J ], Computers & Industrial Engineering, 118, pp. 352-365, (2018); Bass F M., A new product growth for model consumer durables[ J], Management Science, 15, 5, pp. 215-227, (1969); Bilginer O, Erhun F., Production and sales planning in capacitated new product introductions [ J ], Production & Operations Management, 24, 1, pp. 42-53, (2015); Xiao T J, Xu T T., Coordinating price and service level decisions for a supply chain with deteriorating item under vendor managed inventory [ J ], International Journal of Production Econo-mics, 145, 2, pp. 743-752, (2013); Ma P, Wang H Y, Shang J., Contract design for two-stage supply chain coordination: Integrating manufacturer-quality and retailermarketing efforts [ J ], International Journal of Production Economics, 146, 2, pp. 745-755, (2013)",null,null,"Zhejiang University",{"$nulls":5},1.0046062E7,null,null,null,"English","J. Industrial Eng. Eng. Management","Article","Final",null,"Scopus","2-s2.0-85166089132"]
["Khosasih M.M.; Lisana L.","Khosasih, Mikhael Ming (57422982100); Lisana, Lisana (57222742146)","57422982100; 57222742146","Intention to Adopt Online Food Delivery Using Augmented Reality Mobile Apps: A Perspective of SOR Framework",2023.0,"International Journal on Advanced Science, Engineering and Information Technology",13.0,2.0,null,618.0,624.0,6.0,0.0,"10.18517/ijaseit.13.2.17245","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85158847271&doi=10.18517%2fijaseit.13.2.17245&partnerID=40&md5=87cb9316bc1e4b981f62c09e741d8d59","Department of Informatics Engineering, Faculty of Engineering, Universitas Surabaya, Jl. Raya Kalirungkut, Surabaya, 60293, Indonesia","Khosasih M.M., Department of Informatics Engineering, Faculty of Engineering, Universitas Surabaya, Jl. Raya Kalirungkut, Surabaya, 60293, Indonesia; Lisana L., Department of Informatics Engineering, Faculty of Engineering, Universitas Surabaya, Jl. Raya Kalirungkut, Surabaya, 60293, Indonesia","Globally, the COVID-19 pandemic has affected all sectors, including the food and beverage industry. The pandemic has changed customers' behavior from dine-in services to online food ordering systems. Technology advancements make ordering food easier with Online Food Delivery (OFD) service. However, before buying food online, consumers require a physical assessment to decide to buy the food or beverage. Augmented Reality (AR) is a popular technology to show 3D virtual elements. Meanwhile, the stimulus organism response (SOR) framework can be used to analyze consumers' behavior. More specifically, the SOR model has been used to evaluate the user's behavior intention to accept online shopping apps. However, in the OFD context, there is a lack of research investigating the customer's intention to use the AR app based on the SOR perspective. This study aims to assess the factors influencing consumers' intention to adopt augmented reality apps. 52 AR OFD app customers participate in this study. Partial Least Square-Structural Equation Modeling (PLS-SEM) and SMARTPLS 3 was used to analyze the research model. This study evaluated from measurement and structural model. The measurement model using factor loading, Composite Reliability (CR), Average Variance Extracted (AVE), and heterotrait-monotrait (HTMT) ratio. The structural model assessed the variance inflation factor (VIF), R2, path coefficient (β), f2, and p-value. The results showed the significance of food image on hedonic, utilitarianism, and perceived informativeness. Furthermore, hedonism was the only determinant that positively influenced the customers' intention to use the AR OFD apps. © IJASEIT is licensed under a Creative Commons Attribution-Share Alike 4.0 International License.","Augmented reality; e-commerce; mobile application; online food delivery; stimulus-organism-response",{"$nulls":7},"Brewer P., Sebby A. G., The effect of online restaurant menus on consumers' purchase intentions during the COVID-19 pandemic, Int. J. Hosp. Manag, 94, (2021); Gavilan D., Balderas-Cejudo A., Fernandez-Lores S., Martinez-Navarro G., Innovation in online food delivery: Learnings from COVID-19, Int. J. Gastron. Food Sci, 24, (2021); Hong C., H. (Hailey) Choi, E. K. (Cindy) Choi, and H. W. (David) Joung, \"Factors affecting customer intention to use online food delivery services before and during the COVID-19 pandemic, J. Hosp. Tour. Manag, 48, pp. 509-518, (2021); Saad A. 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S., How perceived communication source and food value stimulate purchase intention of organic food: An examination of the stimulus-organism-response (SOR) model, J. Clean. Prod, 312, (2021); Chopdar P. K., Balakrishnan J., Consumers response towards mobile commerce applications: S-O-R approach, Int. J. Inf. Manage, 53, (2019); Hewei T., Youngsook L., Factors affecting continuous purchase intention of fashion products on social E-commerce: SOR model and the mediating effect, Entertain. Comput, 41, (2022); Hanadian N., Indonesia: favorite food delivery apps 2020 | Statista, (2021); Chen H.-P., The Driving Success Factors of the Online Food Ordering System - Empirical Evidence from the UTAUT Model, (2017); Kartono R., Tjahjadi J. 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Serv, 60, (2021); Hincapie M., Diaz C., Valencia A., Contero M., Guemes-Castorena D., Educational applications of augmented reality: A bibliometric study, Comput. Electr. Eng, 93, (2021); Cuomo M. T., Tortora D., Festa G., Ceruti F., Metallo G., Managing omni-customer brand experience via augmented reality: A qualitative investigation in the Italian fashion retailing system, Qual Mark. Res, 23, 3, pp. 427-445, (2020); Rodrigues J. M. F., Ramos C. M. Q., Pereira J. A. R., Sardo J. D. P., Cardoso P. J. S., Mobile Five Senses Augmented Reality System: Technology Acceptance Study, IEEE Access, 7, (2019); Wei J., Zhao Shengdong, Nakatsu R., Duh H. B. L., When AR meets food: A structural overview of the research space on multifacets of food, 11th IEEE Int. Symp. Mix. Augment. Real. 2012 - Arts, Media, Humanit. Pap. 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Res, 126, pp. 578-590, (2021); Amanah D., Harahap D. A., Visual Appeal Model for Consumer Online Impulsive Purchases in Indonesia, Int. J. Sci. Technol. Res, 9, pp. 388-397, (2020); Ozturk A. B., Nusair K., Okumus F., Hua N., The role of utilitarian and hedonic values on users' continued usage intention in a mobile hotel booking environment, Int. J. Hosp. Manag, 57, pp. 106-115, (2016); Fauzi A. A., Sheng M. L., Ride-hailing apps' continuance intention among different consumer groups in Indonesia: the role of personal innovativeness and perceived utilitarian and hedonic value, Asia Pacific J. Mark. Logist, 33, 5, pp. 1195-1219, (2020); Huang Y. M., Students’ Continuance Intention Toward Programming Games: Hedonic and Utilitarian Aspects, Int. J. Hum. Comput. Interact, 36, 4, pp. 393-402, (2020); Rese A., Baier D., Geyer-Schulz A., Schreiber S., How augmented reality apps are accepted by consumers: A comparative analysis using scales and opinions, Technol Forecast. Soc. Change, 124, pp. 306-319, (2017); Vahdat A., Alizadeh A., Quach S., Hamelin N., Would you like to shop via mobile app technology? The technology acceptance model, social factors and purchase intention, Australas. Mark. J, pp. 1-10, (2020); Hair J. F., Risher J. J., Sarstedt M., Ringle C. M., When to use and how to report the results of PLS-SEM, Eur. Bus. Rev, 31, 1, pp. 2-24, (2019); Nikolopoulou K., Gialamas V., Lavidas K., Habit, hedonic motivation, performance expectancy and technological pedagogical knowledge affect teachers’ intention to use mobile internet, Comput. Educ. Open, 2, (2021)","M.M. Khosasih; Department of Informatics Engineering, Faculty of Engineering, Universitas Surabaya, Jl. Raya Kalirungkut, Surabaya, 60293, Indonesia; email: mikhaelming@staff.ubaya.ac.id",null,"Insight Society",{"$nulls":5},2.0885334E7,null,null,null,"English","Int. J. Adv. Sci. Eng. Inf. Technol.","Article","Final","All Open Access; Green Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85158847271"]
["Woo S.H.; Park H.J.; Cho S.W.; Kim K.H.","Woo, Sung Hun (58731479400); Park, Hyun Ji (57220123722); Cho, Sung Won (57204914214); Kim, Ki Hong (57202965774)","58731479400; 57220123722; 57204914214; 57202965774","Proactive berth scheduling with data-driven buffer time in container terminals",2023.0,"International Transactions in Operational Research",{"$nulls":6},0.0,"10.1111/itor.13412","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85178198814&doi=10.1111%2fitor.13412&partnerID=40&md5=60fb93f038701de61694e713d73d50ac","Department of Applied Artificial Intelligence, Korea University, Seoul, South Korea; Department of Industrial and Management Engineering, Korea University, Seoul, South Korea; Department of Management Engineering, Dankook University, Cheonan, South Korea; Maritime Digital Transformation Research Center, Korea Research Institute of Ships and Ocean Engineering, Daejeon, South Korea","Woo S.H., Department of Applied Artificial Intelligence, Korea University, Seoul, South Korea; Park H.J., Department of Industrial and Management Engineering, Korea University, Seoul, South Korea; Cho S.W., Department of Management Engineering, Dankook University, Cheonan, South Korea, Maritime Digital Transformation Research Center, Korea Research Institute of Ships and Ocean Engineering, Daejeon, South Korea; Kim K.H., Department of Industrial and Management Engineering, Korea University, Seoul, South Korea","Global shipment volumes have been increasing due to changes in the business environment of e-commerce and manufacturing. Consequently, container vessels carry more cargo for international trade, increasing uncertainties in terminal management. Terminal operators manage terminals by establishing a proactive schedule that responds to disruptions such as vessel delays, and the introduction of buffer time is a representative proactive strategy. In this study, by analyzing historical delay data with machine learning, we propose data-driven buffer times to consider the heterogeneous arrival uncertainty of vessels. Thus, we proactive scheduling with data-driven buffer times according to the desired robustness levels. This is a novel study on berth scheduling that applies data mining approaches to improve operations research techniques. Numerical experiments were conducted on the berth scheduling with time-invariant quay crane assignment using real-life data to validate the effectiveness of the proposed method. These experimental results revealed that applying the data-driven buffer time could effectively reduce the cost incurred at the terminal by balancing baseline and recovery costs. In addition, our proposed methodology ensured the quality of the solution compared with a stochastic method and reduced the computational burden of a stochastic problem by using the data-driven buffer times obtained prior to the solution construction. Therefore, the proposed method can be introduced into terminal operations to overcome the deficiencies of traditional approaches in terms of academic perspective. © 2023 International Federation of Operational Research Societies.","berth allocation and quay crane assignment problem; container terminal operations; data-driven buffer time; EM-algorithm; gaussian mixture model; maritime logistics; rolling-horizon heuristic; statistical learning","Balancing; Combinatorial optimization; Cranes; Data mining; Gaussian distribution; International trade; Learning systems; Numerical methods; Operations research; Port terminals; Railroad yards and terminals; Stochastic systems; Transfer cases (vehicles); Berth allocation; Berth allocation and quay crane assignment problem; Container terminal operation; Data driven; Data-driven buffer time; EM algorithms; Gaussian Mixture Model; Maritime logistics; Quay crane assignment problems; Rolling horizon; Rolling-horizon heuristic; Statistical learning; Uncertainty analysis",{"$nulls":4},"Ministry of Oceans and Fisheries, MOF, (1525014892); Ministry of Science, ICT and Future Planning, MSIP, (2021R1A4A1029124); National Research Foundation of Korea, NRF; Korea Research Institute of Ships and Ocean Engineering, KRISO","The authors would like to acknowledge the anonymous reviewers for their valuable comments and suggestions that have helped improve the manuscript. In addition, this research was supported by the Korea Research Institute of Ships and Ocean engineering a grant from the Endowment Project of “Development of Intelligent Container Stacking Service Technology for Digital Ports” funded by the Ministry of Oceans and Fisheries(1525014892) and also supported by the National Research Foundation of Korea grant funded by the Korea government (MSIT) (No.2021R1A4A1029124).",{"$cut":{"chars":17184,"head":"Al-Refaie A., Abedalqader H., Optimal berth scheduling and sequencing under unexpected events, Journal of the Operational Research Society, 73, 2, pp. 430-444, (2022); Biernacki C., Celeux G., Govaert G., Assessing a mixture model for clustering with the integrated completed likelihood, IEEE Transactions on Pattern Analysis and Machine Intelligence, 22, 7, pp. 719-725, (2000); Bierwirth C., Meisel F., A survey of berth allocation and quay crane scheduling problems in container terminals, European Journal of Operational Research, 202, 3, pp. 615-627, (2010); Bierwirth C., Meisel F., A follow-up survey of berth allocation and quay crane scheduling problems in container terminals, European Journal of Operational Research, 244, 3, pp. 675-689, (2015); Bohning D., A review of reliable maximum likelihood algorithms for semiparametric mixture models, Journal of Statistical Planning and Inference, 47, 1-2, pp. 5-28, (1995); Cho S.W., Park H.J., Kim A., Park J.H., GMM-based online optimization for container stacking in port container terminals, Computers & Industrial Engineering, 173, (2022); Cho S.W., Park H.J., Lee C., An integrated method for berth allocation and quay crane assignment to allow for reassignment of vessels to other terminals, Maritime Economics & Logistics, 23, 1, pp. 123-153, (2021); Corne D., Dhaenens C., Jourdan L., Synergies between operations research and data mining: the emerging use of multi-objective approaches, European Journal of Operational Research, 221, 3, pp. 469-479, (2012); Cosar K., Thomas B., The geopolitics of international trade in Southeast Asia, Review of World Economics, 157, 1, pp. 207-219, (2021); Du Y., Xu Y., Chen Q., A feedback procedure for robust berth allocation with stochastic vessel delays, 2010 8th World Congress on Intelligent Control and Automation, pp. 2210-2215, (2010); Dui H., Zheng X., Wu S., Resilience analysis of maritime transportation systems based on importance measures, Reliability Engineering & System Safety, 209, (2021); Dulebenets M.A., Application of evolutionary computation for berth scheduling at marine container terminals: parameter tuning versus parameter control, IEEE Transactions on Intelligent Transportation Systems, 19, 1, pp. 25-37, (2017); Dulebenets M.A., An adaptive island evolutionary algorithm for the berth scheduling problem, Memetic Computing, 12, 1, pp. 51-72, (2020); Dulebenets M.A., Kavoosi M., Abioye O., Pasha J., A self-adaptive evolutionary algorithm for the berth scheduling problem: towards efficient parameter control, Algorithms, 11, 7, (2018); Fuentes G., Generating bunkering statistics from AIS data: a machine learning approach, Transportation Research Part E: Logistics and Transportation Review, 155, (2021); Golias M., Portal I., Konur D., Kaisar E., Kolomvos G., Robust berth scheduling at marine container terminals via hierarchical optimization, Computers & Operations Research, 41, pp. 412-422, (2014); Golias M.M., A bi-objective berth allocation formulation to account for vessel handling time uncertainty, Maritime Economics & Logistics, 13, 4, pp. 419-441, (2011); Guo L., Wang J., Zheng J., Berth allocation problem with uncertain vessel handling times considering weather conditions, Computers & Industrial Engineering, 158, (2021); Hendriks M., Laumanns M., Lefeber E., Udding J.T., Robust cyclic berth planning of container vessels, OR Spectrum, 32, 3, pp. 501-517, (2010); Hyndman R.J., Koehler A.B., Another look at measures of forecast accuracy, International Journal of Forecasting, 22, 4, pp. 679-688, (2006); Imai A., Chen H.C., Nishimura E., Papadimitriou S., The simultaneous berth and quay crane allocation problem, Transportation Research Part E: Logistics and Transportation Review, 44, 5, pp. 900-920, (2008); Imai A., Nishimura E., Papadimitriou S., The dynamic berth allocation problem for a container port, Transportation Research Part B: Methodological, 35, 4, pp. 401-417, (2001); Imai A., Sun X., Nishimura E., Papadimitriou S., Berth allocation in a container port: using a continuous location space approach, Transportation Resear"}},"S.W. Cho; Department of Management Engineering, Dankook University, Cheonan, South Korea; email: sungwon.cho@dankook.ac.kr",null,"John Wiley and Sons Inc",{"$nulls":5},9696016.0,null,null,null,"English","Int. Trans. Oper. Res.","Article","Article in press",null,"Scopus","2-s2.0-85178198814"]
["Aserkar R.","Aserkar, Rajiv (57192264663)",5.7192264663E10,"Fabrizex: creating a technology platform for global supply chains",2023.0,"Emerald Emerging Markets Case Studies",13.0,1.0,null,1.0,17.0,16.0,0.0,"10.1108/EEMCS-02-2023-0042","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85159601193&doi=10.1108%2fEEMCS-02-2023-0042&partnerID=40&md5=0adfd6b037ba991a28798353ea0773f5","Department of Management, S P Jain School of Global Management, Singapore, Singapore","Aserkar R., Department of Management, S P Jain School of Global Management, Singapore, Singapore","Subject area: Supply Chain Management, Technology, Procurement, Supply Chain Finance Learning outcomes: The key learning objectives are as follows: to gain critical insights into e-commerce supply chains of fashion garments; understand the importance of digitization to manage the risks due to supply chain disruptions; evaluate the role of digitization to improve supply chain performance; understand the importance of supply chain finance in maintaining a healthy buyer–supplier relationship; and appreciate the role of supply chain digitization to transform a regional supply chain into a global supply chain. Case overview/synopsis: This case highlights the challenges faced by fashion garments industry due to fragmented nature of their supply chains, where the manufacturing base was in the east and most of the consumers in the west. Digitization can create a bridge to integrate these supply chains to drive out their inefficiency, fragility and vulnerability to disruptions. Complexity academic level: The case could be discussed in 90 min of an Operations Management, Supply Chain Management and Technology Management class at MBA or Executive MBA level. Supplementary Material: Teaching notes are available for educators only. Subject code: CSS 9: Operations and Logistics. © 2023, Emerald Publishing Limited.","Asia; B2B; B2C; E-commerce; Logistics; Operations management; Platform; Procurement; Supply Chain; Supply chain management; Supply chain strategy; Technology",{"$nulls":7},"Alsaad A., Mohamad R., Ismail N.A., The contingent role of dependency in predicting the intention to adopt B2B e-commerce, Information Technology for Development, 25, 4, pp. 686-714, (2019); Chenneveau D., Mancini M., Shinghal S., A resilient return for Asia’s manufacturing and supply chains?\\?}, (2020); Christopher M., Peck H., Building the resilient supply chain, The International Journal of Logistics Management, 15, 2, pp. 1-13, (2004); Giri S., Rai S.S., Dynamics of garment supply chain, International Journal of Managing Value and Supply Chains, 4, 4, (2013); (2023); Jeon B.W., Um J., Yoon S.C., Suk-Hwan S., An architecture design for smart manufacturing execution system, Computer-Aided Design and Applications, 14, 4, pp. 472-485, (2017); Mak H.Y., Max Shen Z.J., When triple‐a supply chains meet digitalization: the case of JD. com's C2M model, Production and Operations Management, 30, 3, pp. 656-665, (2021); Natsuda K., Goto K., Thoburn J., Challenges to the Cambodian garment industry in the global garment value chain, The European Journal of Development Research, 22, 4, pp. 469-493, (2010); Rakib M.A., Adnan A., Challenges of ready-made garments sector in Bangladesh: Ways to overcome, BUFT Journal, 3, 1, pp. 84-85, (2015); Remy N., Speelman E., Swartz S., Style that is sustainable: a new fast fashion formula, (2016); Towers N., Song Y., Assessing the future challenges in strategic sourcing commodity from China: a case-study analysis, Asia Pacific Business Review, 16, 4, pp. 527-544, (2010); Uzzaman A., Et al., Utilizing RFID for supply chain business process: a case study, World Congress on ICT for Development, WCID’09 September 2–4, 2009, (2009); Zhou Y., Xu M., Di R., Research on the radical innovation of C2M business model-a case study on redcollar MTM men's suits in China, International Journal of Business and Management, 11, 4, pp. 194-202, (2016)","R. Aserkar; Department of Management, S P Jain School of Global Management, Singapore, Singapore; email: lotusa@rediffmail.com",null,"Emerald Publishing",{"$nulls":5},2.0450621E7,null,null,null,"English","Emerald Emerg. Mark. Case Stud.","Article","Final",null,"Scopus","2-s2.0-85159601193"]
["Chen Z.; Liu J.; Wang Y.","Chen, Zhi (58682805000); Liu, Jie (58682576800); Wang, Ying (58682116700)","58682805000; 58682576800; 58682116700","Big data swarm intelligence optimization algorithm application in the intelligent management of an E-commerce logistics warehouse",2023.0,"Journal of Cases on Information Technology",26.0,1.0,{"$nulls":4},0.0,"10.4018/JCIT.332809","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85175786754&doi=10.4018%2fJCIT.332809&partnerID=40&md5=c6b114b301b4773738a7588867d0734c","Research Center for Agricultural Industry and Digital Economy, Guangdong Open University, Guangzhou, China; Logistics Center, China Tobacco Guizhou Industrial Co., Ltd, Guiyang, China; College of Economics and Management, Guangdong Open University, Guangzhou, China","Chen Z., Research Center for Agricultural Industry and Digital Economy, Guangdong Open University, Guangzhou, China; Liu J., Logistics Center, China Tobacco Guizhou Industrial Co., Ltd, Guiyang, China; Wang Y., College of Economics and Management, Guangdong Open University, Guangzhou, China","A dynamic mutation probability formula is utilized to optimize the model. In order to solve the logistics warehouse path problem, the ant colony optimization algorithm, optimized by a genetic algorithm, is employed to construct a logistics warehouse path optimization model. This model effectively optimizes the logistics warehouse paths. Test results comparing the convergence and distribution of non-inferior solutions demonstrated that the proposed model outperforms others in terms of convergence and non-inferior solution distribution. In practical logistics warehouse optimization, applying the proposed model to optimize cargo locations can significantly enhance the effectiveness of the objective function. The optimization resulted in improvements for all four objective functions related to cargo location, with reduction rates of 10.38%, 30.88%, 51.78%, and 88.49%, respectively. For the optimization of logistics warehouse paths, the original distance was 47.6m, which was reduced to 27.8m after optimization. Consequently, the picking distance decreased by 41.60%. © 2023 IGI Global. All rights reserved.","E-commerce warehouse; Intelligent management; Particle Swarm Optimization; Path optimization; Test","Ant colony optimization; Big data; Electronic commerce; Genetic algorithms; Particle swarm optimization (PSO); Swarm intelligence; E-commerce warehouse; Intelligent management; Objective functions; Optimisations; Particle swarm; Particle swarm optimization; Path optimizations; Swarm intelligence optimization algorithm; Swarm optimization; Test; Warehouses",{"$nulls":6},"Barma M., Modibbo U. M., Multiobjective mathematical optimization model for municipal solid waste management with economic analysis of reuse/recycling recovered waste materials, Journal of Computational and Cognitive Engineering, 1, 3, pp. 122-137, (2022); Beiki H., Seyedhosseini S. M., Ghezavati V. R., Seyedaliakbar S. M., Multi-objective optimization of multi-vehicle relief logistics considering satisfaction levels under uncertainty, International Journal of Engineering, 33, 5, pp. 814-824, (2020); Boonmee C., Kasemset C., The multi-objective fuzzy mathematical programming model for humanitarian relief logistics, Industrial Engineering & Management Systems, 19, 1, pp. 197-210, (2020); Ershadi M. M., Shemirani H. S., A multi-objective optimization model for logistic planning in the crisis response phase, Journal of Humanitarian Logistics and Supply Chain Management, 12, 1, pp. 30-53, (2022); Ghasemi P., Goodarzian F., Abraham A., A new humanitarian relief logistic network for multiobjective optimization under stochastic programming, Applied Intelligence, 52, 12, pp. 13729-13762, (2022); Gupta S., Haq A., Ali I., Sarkar B., Significance of multi-objective optimization in logistics problem for multi-product supply chain network under the intuitionistic fuzzy environment, Complex & Intelligent Systems, 7, 4, pp. 2119-2139, (2021); Hu X., Chuang Y. F., E-commerce warehouse layout optimization: Systematic layout planning using a genetic algorithm, Electronic Commerce Research, 23, 1, pp. 97-114, (2023); Minashkina D., Happonen A., A systematic literature mapping of current academic research linking warehouse management systems to the third-party logistics context, Acta Logistica, 10, 2, pp. 209-228, (2023); Pan J. S., Fu Z., Hu C. C., Tsai P. W., Chu S. C., Rafflesia optimization algorithm applied in the logistics distribution centers location problem, Wangji Wanglu Jishu Xuekan, 23, 7, pp. 1541-1555, (2022); Praneetpholkrang P., Kanjanawattana S., A multi-objective optimization model for shelter locationallocation in response to humanitarian relief logistics, The Asian Journal of Shipping and Logistics, 37, 2, pp. 149-156, (2021); Pu X., Lu X., Han G., An improved optimization algorithm for a multi-depot vehicle routing problem considering carbon emissions, Environmental Science and Pollution Research International, 29, 36, pp. 54940-54955, (2022); Qin H., Xiao J., Ge D., Xin L., Gao J., He S., Hu H., Carlsson J. G., JD.com: Operations research algorithms drive intelligent warehouse robots to work, INFORMS Journal on Applied Analytics, 52, 1, pp. 42-55, (2022); Shadkam E., Khajooei S., Rajabi R., The new TOPCO hybrid algorithm to solve multi-objective optimisation problems: The integrated stochastic problem of production-distribution planning in the supply chain, International Journal of Computational Systems Engineering, 6, 3, pp. 143-157, (2021); Sun J., Zhang D. J., Hu H., Van Mieghem J. A., Predicting human discretion to adjust algorithmic prescription: A large-scale field experiment in warehouse operations, Management Science, 68, 2, pp. 846-865, (2022); Sun X., Hu W., Xue X., Dong J., Multi-objective optimization model for planning metro-based underground logistics system network: Nanjing case study, Journal of Industrial and Management Optimization, 19, 1, pp. 170-196, (2022); Surury F., Syauqi A., Purwanto W. W., Multi-objective optimization of petroleum product logistics in Eastern Indonesia region, The Asian Journal of Shipping and Logistics, 37, 3, pp. 220-230, (2021); Tufano A., Accorsi R., Manzini R., A machine learning approach for predictive warehouse design, International Journal of Advanced Manufacturing Technology, 119, 3-4, pp. 2369-2392, (2022); Waziri T. A., Yakasai B. M., Assessment of some proposed replacement models involving moderate fix-up, Journal of Computational and Cognitive Engineering, 2, 1, pp. 28-37, (2023); Xidias E. K., Zacharia P. T., Nearchou A., SERobWaS: A support environment for a robot-based warehousing system, International Journal of Advanced Manufacturing Technology, 126, 9-10, pp. 3905-3919, (2023); Yousefi Nejad Attari M., Ebadi Torkayesh A., Malmir B., Neyshabouri Jami E., Robust possibilistic programming for joint order batching and picker routing problem in warehouse management, International Journal of Production Research, 59, 14, pp. 4434-4452, (2021); Zhao K., Zhu M., Xiao B., Yang X., Gong C., Wu J., Joint RFID and UWB technologies in intelligent warehousing management system, IEEE Internet of Things Journal, 7, 12, pp. 11640-11655, (2020)",null,null,"IGI Global",{"$nulls":5},1.5487717E7,null,null,null,"English","J. Cases Inf. Technol.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85175786754"]
["Mookerjee J.; Chattopadhyay S.; Rajkumar M.","Mookerjee, Joydeep (58024206200); Chattopadhyay, Subir (57204676813); Rajkumar, M. (57210474451)","58024206200; 57204676813; 57210474451","Systematic review: disruptive innovation in non-branded retail markets",2023.0,"International Journal of Systematic Innovation",7.0,6.0,null,20.0,35.0,15.0,0.0,"10.6977/IJoSI.202306_7(6).0003","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85164584194&doi=10.6977%2fIJoSI.202306_7%286%29.0003&partnerID=40&md5=15b5c2cf623bf63428adec61c5387b96","ICFAI University, Jharkhand, India","Mookerjee J., ICFAI University, Jharkhand, India; Chattopadhyay S., ICFAI University, Jharkhand, India; Rajkumar M., ICFAI University, Jharkhand, India","The coronavirus pandemic has significantly impacted the retail industry, with changes in consumer shopping patterns and a shift towards online and home delivery services. While branded retailers have adapted to the e-commerce solutions and seen a rise in sales, non-branded retailers have faced disruptions in their supply chain and local market participation. The study found that consumer choices shifted towards healthcare products rather than brand loyalty, resulting in a scarcity of branded products and encouraging the purchase of local unbranded goods. The garment industry supply chain was heavily impacted, and some employees and daily laborers lost their jobs. Retailers are now preparing for post-pandemic conditions, including changes in employee and operations. The paper presents a systematic review of the disruptions created by local retailers and their innovative strategies in the post-pandemic era, providing insights into the consequences and challenges the retail industry faces. Additionally, the study highlights the need for retailers to monitor their liquidity and adjust their short-term cash estimates to survive in an unstable market with reoccurring lockdowns. Finally, the paper discusses the opportunities for more informed retailers to improve their market position by addressing sustainable and ethical concerns that have become increasingly relevant due to the pandemic. © 2023, International Journal of Systematic Innovation. All Rights Reserved.","Covid-19; Market Disruption; Retail Market; Unbranded Retails",{"$nulls":7},"Aday S., Aday M. S., Impact of COVID-19 on the food supply chain, Food Quality and Safety, pp. 167-180, (2020); Amabibi F., THE IMPLICATIONS AND IMPACT OF COVID-19 PREVENTIVE MEASURES IN NIGERIA: A CASE OF PORT-HARCOURT CITY AND OBIO/AKPOR LOCAL GOVERNMENTS IN RIVERS STATE (MARCH 2020-AUGUST 2020) Chinnah, Promise Chinwe, (2020); Amrit A., Structural Transformation of Retail Sector: A Literature Survey; Aromolaran A., Muyanga M., Impact of COVID-19 on food systems and rural livelihoods in Nigeria, (2020); Atmar H., Begley S., Fuerst J., Rickert S., The next normal: Retail M&A and partnerships after COVID-19, (2020); Aydinli A., Lamey L., Millet K., ter Braak A., How do customers alter their basket composition when they perceive the retail store to be crowded? An empirical study, Journal of Retailing, (2020); Banga K., Keane J., Mendez-Parra M, Africa trade and Covid-19, (2020); Bhatt V., Grover S., Sharma A., COVID-19 pandemic, lockdown and the Indian labor market: Evidence from PLFS 2017-18 (No. 2020-023), (2020); Cambefort M., How the COVID-19 Pandemic is Challenging Consumption, Markets, Globalization & Development Review, (2020); Chakraborty S., Impact of COVID-19 on Indian consumers and their buying behavior, Journal of Retailing and Consumer Services, (2020); Chen C., Dasgupta S., Huynh T., Xia Y., Were Stay-at-Home Orders During Covid-19 Harmful for Business? The Market’s View, (2020); Chenarides L., Richards T. J., Rickard B., COVID-19 impact on fruit and vegetable markets: One year later, Canadian Journal of Agricultural Economics/Revue canadienne d’agroeconomie, (2021); Christensen C. M., The innovator's dilemma: When new technologies cause great firms to fail, (1997); Cowley C., COVID-19 Disruptions in the US Meat Supply Chain, (2020); Cretan R., Light D., COVID-19 in Romania: transnational labor, geopolitics, and the Roma ‘outsiders’, Eurasian Geography and Economics, pp. 559-572, (2020); Freeman E., Impacts of the COVID-19 Pandemic: How Retail, Office and Industrial May Be Affected by Changes, Human Behavior, (2020); GOLDFARB A., COURSES TAUGHT, Organization Science, pp. 1056-1073, (2020); Gupta S., Purohit H., Impact of COVID-19 on Indian e-commerce industry: An empirical study, Journal of Retailing and Consumer Services, (2020); Hao F., Xiao Q., Chon K., COVID-19 and China’s hotel industry: Impacts, a disaster management framework, and post-pandemic agenda, International journal of hospitality management, (2020); Hayes D. J., Schulz L. L., Hart C. E., Jacobs, A descriptive analysis of the COVID-19 impacts on US pork, turkey, and egg markets, Agribusiness, pp. 122-141, (2021); Hobbs J. E., Food supply chains during the COVID-19 pandemic, Canadian Journal of Agricultural Economics, (2020); Jaelani A. K., Ayu I. G., Rachmi K., Karjoko L., The impact of corona virus on supply chain of halal tourism management in west Nusa Tenggara, International Journal of Supply Chain Management, pp. 823-831, (2020); Jones P., Comfort D., A commentary on the COVID-19 crisis, sustainability and the service industries, Journal of Public Affairs, (2020); Kumar A., Khan F., AN OVERVIEW OF ORGANIZED & UNORGANIZED RETAILING IN INDIA, (2020); Kumar M. S., Raut R. D., Narwane V. S., Narkhede B. E., Applications of industry 4.0 to overcome the COVID-19 operational challenges, Diabetes & Metabolic Syndrome: Clinical Research & Reviews, pp. 1283-1289, (2020); Lee J. H., Kim Y. J., The impact of disruptive innovation on the retail industry: A case study of Alibaba, Journal of Open Innovation: Technology, Market, and Complexity, 7, (2021); Li X., Li Y., Disruptive innovation in the retail industry: A systematic literature review, Journal of Retailing and Consumer Services, (2021); Li X., Zhang Y., The impact of consumer panic buying on the retail supply chain during the COVID-19 pandemic, Journal of Business Research, pp. 1-10, (2023); Liverpool-Tasie L. S., Reardon T., Belton, Essential non-essentials: COVID-19 policy missteps in Nigeria rooted in persistent myths about A frican food supply chains, Applied Economic Perspectives and Policy, pp. 205-224, (2020); Lusk J., Impacts of coronavirus on food markets, (2020); Mahajan K., Tomar S., COVID-19 and Supply Chain Disruption: Evidence from Food Markets in India, American journal of agricultural economics, pp. 35-52, (2021); Medberg G., Gronroos C., Value-in-use and service quality: do customers see a difference?, Journal of Service Theory and Practice, (2020); Nadvi K., Pasquali G., Godfrey S., Understanding regional value chains through the interaction of public and private governance: Insights from Southern Africa’s apparel sector, Journal of International Business Policy, pp. 1-22, (2020); Nguyen T. T., Nguyen T. H., The impact of COVID-19 on the restaurant industry: A global perspective, Journal of Hospitality and Tourism Management, pp. 67-77, (2021); Nithya S., Chirputkar A., THE ANALYSIS OF IMPACT OF COVID-19 ON RETAIL CONSUMER BEHAVIOR AND BUSINESS MODELS, PalArch’s Journal of Archaeology of Egypt/Egyptology, pp. 4384-4401, (2020); Noble J., Competition law in times of crisis tackling the COVID-19 challenge: a producer perspective, Journal of Antitrust Enforcement, pp. 293-295, (2020); Ntounis N, Mumford C., Lorono-Leturiondo M. P., How safe is it to shop? Estimating the amount of space needed to safely social distance in various retail environments, Safety Science, (2020); Parsons K., Barling D., England’s Food Policy Response to Covid-19: Review of policy issues and interventions, (2021); Pasquali G., Godfrey S., Apparel Regional Value Chains and COVID-19: Insights from Eswatini, pp. 1-12, (2020); Poonia V., Goyal M. K., Madramootoo C. A., Impact of COVID-19 on Agro-Food Industry and Transitions Towards Food Security, Integrated Risk of Pandemic: Covid-19 Impacts, Resilience and Recommendations, pp. 255-273, (2020); Ramsey A. F., Goodwin B. K., Hahn W. F., Holt M. T., Impacts of COVID-19 and price transmission in US meat markets, Agricultural Economics, (2021); Richards T. J., Rickard B., COVID-19 impact on fruit and vegetable markets, Canadian Journal of Agricultural Economics/Revue canadienne d’agroeconomie, pp. 189-194, (2020); Roggeveen A. L., Grewal D., Karsberg J., Forging meaningful consumer-brand relationships through creative merchandise offerings and innovative merchandising strategies, Journal of Retailing, pp. 81-98, (2021); Rosemberg M. A., Health and safety considerations for hotel cleaners during Covid-19, Occupational Medicine, pp. 382-383, (2020); Samila S., Goldfarb A., Silverman B., COVID, on-premise retail format, and productmarket concentration, Covid Economics, (2020); Sharma M., Luthra S., Joshi S., Kumar A., Accelerating retail supply chain performance against pandemic disruption: adopting resilient strategies to mitigate the long-term effects, Journal of Enterprise Information Management, (2021); Shetty G., Nougarahiya S., Mandloi D., COVID-19 and Indian Commerce: An Analysis of Fast Moving Consumer Goods (FMCG), and Retail Industries of Tomorrow, Int J Cur Res Rev, 23, (2020); Singh R., Kumar A., Impact of COVID-19 on Indian consumers and their buying behavior: A study of the unorganized retail sector, Journal of Retailing and Consumer Services, (2020); Singh V. K., Pawar D. S., Shekam L., Dutt V., Impact of COVID 19 on FMCG Sector, Journal of Critical Reviews, pp. 4477-4484, (2020); Smith A. F., Why Waste Food?, (2020); Stanciu S., Radu R. I., Sapira V., Consumer Behavior in Crisis Situations. Research on the Effects of COVID-19 in Romania, (2020); Sulaiman M. B., Ahmed M. N., Shabbir M. S., Covid-19 challenges and human resource management in organized retail operations, Utopia and Praxis Latinoamericana, pp. 81-92, (2020); Swinnen J., McDermott J., COVID-19 and global food security, EuroChoices, pp. 26-33, (2020); Vijai C., Nivetha P., A Study on Coronavirus (COVID-19) Impact of Consumer Buying Behavior with Special Reference to Chennai City, International Conference on COVID-19 Studies, (2020); Yu K. D., Aviso K. B., Modeling the Economic Impact and Ripple Effects of Disease Outbreaks, Process Integr Optim Sustain, (2020); Zhang Y., Li X., The impact of disruptive innovation on the pricing strategies of nonbranded retailers in the retail industry, Journal of Retailing and Consumer Services, (2021)","J. Mookerjee; ICFAI University, Jharkhand, India; email: joydee.m20@iujharkhand.edu.in1",null,"Society of Sytematic Innovation",{"$nulls":5},2.0777973E7,null,null,null,"English","International J. Systematic Innovation","Article","Final",null,"Scopus","2-s2.0-85164584194"]
["Yu G.; Yu W.","Yu, Guangtian (58740972900); Yu, Wangtianhua (58739247800)","58740972900; 58739247800","DESIGN AND IMPLEMENTATION OF VEHICLE SCHEDULING OPTIMIZATION FOR SMART LOGISTICS PLATFORM POWERED BY HADOOP BIG DATA",2023.0,"Scalable Computing",24.0,4.0,null,755.0,767.0,12.0,0.0,"10.12694/scpe.v24i4.2351","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85178400315&doi=10.12694%2fscpe.v24i4.2351&partnerID=40&md5=ab156c455f7db0ac87ff9eaa9077d015","Commercial College, Suzhou Industrial Park Institute of Vocational Technology, Suzhou, 215123, China; Commercial College, The University of Manchester, North Manchester, YO103DU, United Kingdom","Yu G., Commercial College, Suzhou Industrial Park Institute of Vocational Technology, Suzhou, 215123, China; Yu W., Commercial College, The University of Manchester, North Manchester, YO103DU, United Kingdom","E-commerce has become the mainstream consumption mode for people, and with the continuous increase of online shopping business volume, controlling logistics costs has become an urgent problem to be solved. In order to solve the challenges in vehicle scheduling and achieve a scientific and reasonable vehicle scheduling scheme, this research is based on Hadoop Big data platform, introduces the concept of time axis, and builds a vehicle scheduling model based on Hadoop intelligent platform. Based on quantum genetic algorithm and combined with MapReduce model, a quantum improved genetic algorithm is constructed to solve vehicle scheduling optimization problems. The results show that the traditional quantum genetic algorithm converges after 20 iterations, achieving an optimal value of 575 and taking 360 seconds. The improved quantum genetic algorithm converged after 10 iterations and achieved an optimal value of 675, taking 200 seconds. Compared with quantum genetic algorithm, the improved quantum genetic algorithm reduces the time spent by 44.4%. Selecting customer data from a certain logistics company for testing, the improved algorithm shortens the delivery time and achieves the design of the optimal path scheduling plan. This study optimized transportation routes and resource scheduling, reduced transportation costs, and played an important role in optimizing vehicle scheduling in the logistics industry. © 2023 SCPE. All Rights Reserved.","Hadoop big data; MapReduce model; path planning cost; quantum genetic algorithm; vehicle scheduling","Costs; Electronic commerce; Genetic algorithms; Motion planning; Optimal systems; Scheduling algorithms; Transportation routes; Vehicles; Design and implementations; Hadoop big data; Logistics platforms; MapReduce models; Online shopping; Optimal values; Path planning cost; Quantum genetic algorithm; Scheduling optimization; Vehicle scheduling; Big data",{"$nulls":6},"Tian Z., Zhong R., Vatankhah Barenji A., Others A, blockchain-based evaluation approach for customer delivery satisfaction in sustainable urban logistics, International Journal Of Production Research, 59, pp. 2229-2249, (2021); Bie Y., Ji J., Wang X., Qu X., Optimization of electric bus scheduling considering stochastic volatilities in trip travel time and energy consumption, Computer-Aided Civil And Infrastructure Engineering, 36, pp. 1530-1548, (2021); Luo H., Dridi M., Grunder O., branch-and-price algorithm for a routing and scheduling problem from economic and environmental perspectives, RAIRO - Operations Research, 56, pp. 3267-3292, (2022); Yami A., Okafor D., Modibbo U., An Optimal Warehouse Management for Production Companies, The Journal Of Scientific And Engineering Research, 7, pp. 238-243, (2020); Midaoui M., Qbadou M., Mansouri K., Novel Approach of Smart Logistics for the Health-Care Sector Using Genetic Algorithm, Advances In Science Technology And Engineering Systems Journal, 5, pp. 1143-1152, (2020); Andrade-Michel A., Rlos-Solls Y., And B., reliable driver scheduling for public bus transportation systems, Transportation Research Part B Methodological, 145, pp. 290-301, (2021); Lin H., Tang C., Intelligent bus operation optimization by integrating cases and data driven based on business chain and enhanced quantum genetic algorithm, IEEE Transactions On Intel ligent Transportation Systems, 23, pp. 9869-9882, (2021); Ning T., Huang Y., Low carbon emission management for flexible job shop scheduling: A study case in China, Journal Of Ambient Intelligence And Humanized Computing, 14, pp. 789-805, (2023); Li D., Shi R., Yao N., Eal-Time Patient-Specific ECG Arrhythmia Detection By Quantum Genetic Algorithm Of Least Squares Twin SVM, Journal Of Beijing Institute Of Technology, 29, pp. 32-40, (2020); Yang Y., Wang P., Multi-scale quantum free particle optimization algorithm for solving travelling salesman problem, Journal Of Computer Applications, 40, pp. 1278-1283, (2020); Sun Z., Anbarasan M., Praveen Kumar D., Design of online intelligent English teaching platform based on artificial intelligence techniques, Computational Intel ligence, 37, pp. 1166-1180, (2021); Zan J., Research on robot path perception and optimization technology based on whale optimization algorithm, Journal Of Computational And Cognitive Engineering, 1, pp. 201-208, (2022); Kim H., Lim D., Lee S., Deep learning-based dynamic scheduling for semiconductor manufacturing with high uncertainty of automated material handling system capability, IEEE Transactions On Semiconductor Manufacturing, 33, pp. 13-22, (2020); Dharma F., Shabrina S., Noviana A., Prediction of Indonesian inflation rate using regression model based on genetic algorithms, Jurnal Online Informatika, 5, pp. 45-52, (2020); Cheng G., Wang C., Xu C., novel hyper-chaotic image encryption scheme based on quantum genetic algorithm and compressive sensing, Multimedia Tools And Applications, 79, pp. 29243-29263, (2020); Debnath S., Fuzzy quadripartitioned neutrosophic soft matrix theory and its decision-making approach, Journal Of Computational And Cognitive Engineering, 1, pp. 88-93, (2022); Hu L., Yang S., Luo X., Yuan H., Sedraoui K., Zhou M., distributed framework for large-scale protein-protein interaction data analysis and prediction using mapreduce, IEEE/CAA Journal Of Automatica Sinica, 9, pp. 160-172, (2021); Kannimuthu S., Chakravarthy D., Discovery of interesting itemsets for web service composition using hybrid genetic algorithm, Neural Processing Letters, 54, pp. 3913-3939, (2022); Xavier A., Kesavan R., Hybrid Elliptic Curve Cryptographic Approach for Data Privacy and Authentication in Secured Map Reduce Layer (SMR) for Optimized CPU Utilization, IETE Journal Of Research, 69, pp. 670-683, (2023); Tariq Jamal A., Ben Ishak A., Abdel-Khalek S., Tumor edge detection in mammography images using quantum and machine learning approaches, Neural Computing And Applications, 33, pp. 7773-7784, (2021)","G. Yu; Commercial College, Suzhou Industrial Park Institute of Vocational Technology, Suzhou, 215123, China; email: Guangtian_Yu@outlook.com",null,"West University of Timisoara",{"$nulls":5},1.8951767E7,null,null,null,"English","Scalable Comput. Pract. Exp.","Article","Final",null,"Scopus","2-s2.0-85178400315"]
["Zhou L.; Sharma A.K.; Kanhaiya K.; Nandal A.; Dhaka A.","Zhou, Liang (57324643900); Sharma, Arpit Kumar (57342897300); Kanhaiya, Kishan (57226359073); Nandal, Amita (55328038100); Dhaka, Arvind (56901093300)","57324643900; 57342897300; 57226359073; 55328038100; 56901093300","Sentiment analysis using RNN model with LSTM",2023.0,"International Journal of Intelligent Systems Technologies and Applications",21.0,3.0,null,229.0,249.0,20.0,0.0,"10.1504/IJISTA.2023.133701","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174070831&doi=10.1504%2fIJISTA.2023.133701&partnerID=40&md5=cbaa7bcfc9a4b2e7c6de43385eccf503","Jiading District Central Hospital, Affiliated Shanghai University of Medicine and Health Sciences, Shanghai, China; Center for Medicine Intelligent and Development, China Hospital Development Institute, Shanghai Jiao Tong University, Shanghai, China; Department of Computer and Communication Engineering, Manipal University, Jaipur, India; Netaji Subhas University of Technology, Dwarka Sector-3, Dwarka, Delhi, 110078, India","Zhou L., Jiading District Central Hospital, Affiliated Shanghai University of Medicine and Health Sciences, Shanghai, China, Center for Medicine Intelligent and Development, China Hospital Development Institute, Shanghai Jiao Tong University, Shanghai, China; Sharma A.K., Department of Computer and Communication Engineering, Manipal University, Jaipur, India; Kanhaiya K., Netaji Subhas University of Technology, Dwarka Sector-3, Dwarka, Delhi, 110078, India; Nandal A., Department of Computer and Communication Engineering, Manipal University, Jaipur, India; Dhaka A., Department of Computer and Communication Engineering, Manipal University, Jaipur, India","In today’s digital world with a rapid increase in e-commerce portals, the consumers are more oriented towards seeking out online reviews, feedback, or ratings over a product during the online buying process. In this research work, we tried to investigate the relationship between the review ratings and the sentiment of reviews in the form of their polarity. We have tried to predict the sentiments over the given reviews by implementing various machine learning techniques, i.e., logistic regression, support vector machine (SVM), k-nearest neighbours (KNN), and recurrent neural network (RNN). The machine learning techniques predict the sentiments of provided reviews in two scenarios, i.e., scenario 1 – negative (–) and positive (+) and scenario 2 – negative (–), neutral (0) and positive (+). In this paper, we have proposed the architecture for predicting the sentiments with better accuracy over other techniques. Copyright © 2023 Inderscience Enterprises Ltd.","CNN; convolutional neural networks; K-nearest neighbours; KNN; recurrent neural networks; RNN; sentiment analysis; support vector machine; SVM","Electronic commerce; Forecasting; Logistic regression; Long short-term memory; Nearest neighbor search; Support vector regression; Convolutional neural network; Digital world; E- commerces; K-near neighbor; Machine learning techniques; Nearest-neighbour; Recurrent neural network model; Sentiment analysis; Support vectors machine; Sentiment analysis",{"$nulls":4},"Foundation of National Key R&D Program of China, (2020YFC2008700); Foundation of the Program of Shanghai Academic/Technology Research Leader; Science and Technology Innovation Action Plan, (22XD1401300, 23DZ2204100); National Natural Science Foundation of China, NSFC, (82072228); Shanghai Municipal Commission of Economy and Informatization, SHEITC, (202001007)","This work is supported by the Foundation of National Key R&D Program of China [Grant number 2020YFC2008700]; the National Natural Science Foundation of China [Grant number 82072228]; the Foundation of Shanghai Municipal Commission of Economy and Informatization [Grant number 202001007]; the Foundation of the Program of Shanghai Academic/Technology Research Leader under the Science and Technology Innovation Action Plan [Grant number 22XD1401300]; the Foundation of the Technical Standards Program Under the Science and Technology Innovation Action Plan [Grant number 23DZ2204100].","Coyne E., Smit J., Guner L., Sentiment Analysis for Amazon.com Reviews, A Report-Big Data in Media Technology (DM2583), (2019); Haque T., Saber N., Shah F., Sentiment analysis on large scale Amazon product reviews, IEEE International Conference on Innovative Research and Development (ICIRD), (2018); Lourdusamy R., Abraham S., A survey on text pre-processing techniques and tools, International Journal of Computer Sciences and Engineering, 6, 3, pp. 148-157, (2018); Tan W., Wang X., Xu X., Sentiment Analysis for Amazon Reviews, (2018); Chaudhari M.S., Choudhari N.K., Data visualization as a preprocessing step in designing of data mining tools visualizing time series pattern of rainfall data, International Conference on System Modeling & Advancement in Research Trends (SMART), pp. 99-103, (2018); Etuk E., Mohamed T., Time series analysis of monthly rainfall data for the Gadaref rainfall station, Sudan, by SARIMA methods, International Journal of Scientific Research in Knowledge, 2, 7, pp. 320-332, (2014); Gottschall A., West S., Enders C., A comparison of item-level and scale-level multiple imputation for questionnaire batteries, Journal Multivariate Behavioral Research, 47, 1, pp. 1-25, (2012); Schouten K., Frasincar F., Survey on aspect-level sentiment analysis, IEEE Transactions on Knowledge and Data Engineering, 28, 3, pp. 813-830, (2016); Xu R., Xia Y., Wong K., Li W., Opinion annotation in online Chinese product reviews, Proceedings of the International Conference on Language Resources and Evaluation (LREC), (2008); Pankaj P., Muskan P., Soni N., Sentiment analysis on customer feedback data: Amazon product reviews, International Conference on Machine Learning, Big Data, Cloud and Parallel Computing (Com-IT-Con), pp. 320-322, (2019); Saad S.E., Yang J., Twitter sentiment analysis based on ordinal regression, IEEE Access, 7, pp. 163677-163685, (2019); Elli M., Soledad M., Wang Y., Amazon reviews, business analytics with sentiment analysis, Computer Science, (2016); Xu Y., Wu X., Wang Q., Sentiment Analysis of Yelps Ratings Based on Text Reviews, (2015); Nowak J., Taspinar A., Scherer R., LSTM recurrent neural networks for short text and sentiment classification, International Conference on Artificial Intelligence and Soft Computing (ICAISC), LNCS, 10246, pp. 553-562, (2017); Fu X., Yang J., Li J., Fang M., Wang H., Lexicon-enhanced LSTM with attention for general sentiment analysis, IEEE Access, 6, pp. 71884-71891, (2018); Fang X., Zhan J., Sentiment analysis using product review data, Journal of Big Data, 2, 1, pp. 1-14, (2015); Zhou Z., Xu L., Amazon Food Review Classification using Deep Learning and Recommender System, (2009); Paknejad S., Sentiment Classification on Amazon Reviews Using Machine Learning Approaches, (2018); Rezaee Z., Dorestani A., Aliabadi S., Application of time series analyses in big data: practical, research, and education implications, Journal of Emerging Technologies in Accounting, 15, 1, pp. 183-197, (2018); Gurusamy V., Kannan S., Preprocessing techniques for text mining, Conference RTRICS, (2014); Heimerl F., Lohmann S., Lange S., Ertl T., Word cloud explorer: text analytics based on word clouds, 47th Hawaii International Conference on System Sciences, pp. 1833-1842, (2014); Alsaeedi A., Khan M.Z., A study on sentiment analysis techniques of Twitter data, International Journal of Advanced Computer Science and Applications (IJACSA), 10, 2, pp. 361-374, (2019); Bhatt A., Et al., Amazon review classification and sentiment analysis, International Journal of Computer Science and Information Technologies, 6, 6, pp. 5107-5110, (2015); Yu S., Et al., SentiDiff: combining textual information and sentiment diffusion patterns for Twitter sentiment analysis, IEEE Transactions on Knowledge and Data Engineering, 32, 10, pp. 2026-2039, (2020); Du S., Et al., Multi-attention fusion modeling for sentiment analysis of educational big data, Big Data Mining and Analytics, 3, 4, pp. 311-319, (2020); Sherratt R.S., Et al., Sentiment analysis for e-commerce product reviews in Chinese based on sentiment lexicon and deep learning, IEEE Access, 8, pp. 23522-23530, (2020); Jiang H., Et al., Refined global word embeddings based on sentiment concept for sentiment analysis, IEEE Access, 9, pp. 37075-37085, (2021); Jin G., Et al., Sentiment analysis of Danmaku videos based on naïve Bayes and sentiment dictionary, IEEE Access, 8, pp. 75073-75084, (2020)","A. Nandal; Department of Computer and Communication Engineering, Manipal University, Jaipur, India; email: amita_nandal@yahoo.com",null,"Inderscience Publishers",{"$nulls":5},1.7408865E7,null,null,null,"English","Int. J. Intell. Syst. Technol. Appl.","Article","Final",null,"Scopus","2-s2.0-85174070831"]
["Tang Y.M.; Chau K.Y.; Kuo W.T.; Liu X.X.","Tang, Yuk Ming (55231482700); Chau, Ka Yin (57192810298); Kuo, Wei Ting (57320391200); Liu, Xiao Xiao (58074753200)","55231482700; 57192810298; 57320391200; 58074753200","IoT-Based Information System on Cold-Chain Logistics Service Quality (ICCLSQ) Management in Logistics 4.0",2023.0,"Information Systems Frontiers",{"$nulls":6},3.0,"10.1007/s10796-023-10393-7","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85153048893&doi=10.1007%2fs10796-023-10393-7&partnerID=40&md5=e5cee21a3c5b2b8ea78eef3998282f51","Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong; Faculty of Business, City University of Macau, Macao","Tang Y.M., Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong, Faculty of Business, City University of Macau, Macao; Chau K.Y., Faculty of Business, City University of Macau, Macao; Kuo W.T., Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong; Liu X.X., Faculty of Business, City University of Macau, Macao","This study aims to develop a model to assess the impact of IoT technologies on cold-chain logistics service quality management and information of fresh product e-commerce in logistics 4.0. With eight primary characteristics and 40 dimension-related variables, we created a theoretical framework of IoT-based Cold-chain Logistics Service Quality (ICCLSQ) management through a structural equation model. A follow-up online poll of 522 previous fresh product purchasers who experienced features of logistics 4.0 was undertaken to assess customer expectations regarding the quality of information management and logistics service qualities in fresh product e-commerce. Statistical analysis was undertaken to investigate the attribute correlations and linear regressions were performed for analysis. Customers’ pleasure, return motivation, security and privacy are the four-logistics service quality scale dimensions in fresh products information management. The new theoretical model enables a better understanding of the LSQ factors that affect customer satisfaction on the information management of fresh product e-commerce enterprises, as well as enhancing the deployment of their services in light of Logistics 4.0. © 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.","E-commerce; Fresh product; Information management; Internet of Things (IoT); Logistics 4.0; Logistics service quality; Theoretical model","Customer satisfaction; Electronic commerce; Internet of things; Quality of service; Sales; Cold chain logistics; E- commerces; Fresh product; Internet of thing; Internet of things technologies; Logistic 4.0; Logistics service qualities; Quality information; Service quality management; Theoretical modeling; Information management",{"$nulls":6},{"$cut":{"chars":19536,"head":"Agus A.A., Yudoko G., Mulyono N., Imaniya T., E-Commerce performance, digital marketing capability and supply chain capability within e-commerce platform: longitudinal study before and after COVID-19, International Journal of Technology, 12, 2, pp. 360-370, (2021); Al Kattan I., Al Khudairi T., Simulation of inventory control system in a supply chain using RFID, International Journal of Information Systems Supply Chain Management, 3, 1, pp. 68-86, (2010); Ali I., Nagalingam S., Gurd B., A resilience model for cold chain logistics of perishable products, The International Journal of Logistics Management, 29, 3, pp. 922-941, (2018); Online Purchasing Behavior of Malaysia’s Young Consumers, (2013); Attaran M., RFID: An enabler of supply chain operations, Supply Chain Management: An International Journal, 12, 4, pp. 249-257, (2007); Badia-Melis R., Mc Carthy U., Ruiz-Garcia L., Garcia-Hierro J., Villalba J.R., New trends in cold chain monitoring applications-A review, Food Control, 86, pp. 170-182, (2018); Bienstock C.C., Mentzer J.T., Bird M.M., Measuring physical distribution service quality, Journal of the Academy of Marketing Science, 25, 1, (1997); Bienstock C.C., Royne M.B., Sherrell D., Stafford T.F., An expanded model of logistics service quality: Incorporating logistics information technology, International Journal of Production Economics, 113, 1, pp. 205-222, (2008); Boadi P.O., Guoxin L., Sai A.A., Karikari A.F., Customer dissatisfaction and unfavorable word of mouth, Human Systems Management, 37, 4, pp. 445-451, (2018); Bollen K.A., A new incremental fit index for general structural equation models, Sociological Methods Research, 17, 3, pp. 303-316, (1989); Borsboom D., Mellenbergh G.J., Van Heerden J., The concept of validity, Psychological Review, 111, 4, (2004); Brakus J.J., Schmitt B.H., Zarantonello L., Brand experience: What is it? How is it measured? Does it affect loyalty?, Journal of Marketing, 73, 3, pp. 52-68, (2009); Cai X., Chen J., Xiao Y., Xu X., Yu G., Fresh-product supply chain management with logistics outsourcing, Omega, 41, 4, pp. 752-765, (2013); Cang Y., Wang D., A comparative study on the online shopping willingness of fresh agricultural products between experienced consumers and potential consumers, Sustainable Computing: Informatics Systems, 30, (2021); Chau K.Y., Tang Y.M., Liu X., Ip Y.K., Tao Y., Investigation of critical success factors for improving supply chain quality management in manufacturing, Enterprise Information Systems, 15, 10, pp. 1418-1437, (2021); Chen M.C., Lu C.C., Liu Y.C., Optimal consolidation of fresh agricultural products in a multi-temperature joint distribution system, The International Journal of Logistics Management, 29, 3, pp. 887-901, (2018); Chen M.C., Hsu C.L., Lee L.H., Service quality and customer satisfaction in pharmaceutical logistics: An analysis based on Kano model and importance-satisfaction model, International Journal of Environmental Research Public Health, 16, 21, (2019); Chow K., Choy K.L., Lee W.B., On the design of a real-time knowledge‐based system for managing logistics operations, Intelligent Systems in Accounting Finance Management: International Journal, 14, 1-2, pp. 3-25, (2006); Churchill G.A., Iacobucci D., Marketing research: Methodological foundations, (2006); Cronin Jr J.J., Brady M.K., Hult G.T.M., Assessing the effects of quality, value, and customer satisfaction on consumer behavioral intentions in service environments, Journal of Retailing, 76, 2, pp. 193-218, (2000); Sustaining customer loyalty of fresh food e-tailers: An empirical study in China, Asia Pacific Journal of Marketing and Logistics; Da Xu L., He W., Li S., Internet of things in industries: A survey, IEEE Transactions on Industrial Informatics, 10, 4, pp. 2233-2243, (2014); Davis B.R., Mentzer J.T., Logistics service driven loyalty: an exploratory study, Journal of Business Logistics, 27, 2, pp. 53-73, (2006); Davis-Sramek B., Mentzer J.T., Stank T.P., Creating consumer durable retailer customer loyalty through order fulfillment service operations, Journal of Oper"}},"Y.M. Tang; Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong; email: yukming.tang@polyu.edu.hk",null,"Springer",{"$nulls":5},1.3873326E7,null,null,null,"English","Inf. Syst. Front.","Article","Article in press",null,"Scopus","2-s2.0-85153048893"]
["Tran M.N.; Nguyen Q.T.; Nguyen N.H.P.","Tran, Mai Ngoc (57216396641); Nguyen, Quyen Thi (58117469800); Nguyen, Nhung Hong Phuong (58280910600)","57216396641; 58117469800; 58280910600","Factors Influencing the Satisfaction of E-logistics Customers in Vietnam: The Mediating Role of Information Technology",2023.0,"International Journal of Electronic Commerce Studies",13.0,4.0,null,81.0,96.0,15.0,0.0,"10.7903/ijecs.2096","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85148870569&doi=10.7903%2fijecs.2096&partnerID=40&md5=6d16f6bf80cbcbeba3a941dd956b2766","Banking Academy of Vietnam, Viet Nam","Tran M.N., Banking Academy of Vietnam, Viet Nam; Nguyen Q.T., Banking Academy of Vietnam, Viet Nam; Nguyen N.H.P., Banking Academy of Vietnam, Viet Nam","The study focused on the factors contributing to customer satisfaction in e-logistic services. The questionnaire used in this study was developed based on previous studies with proven validity. The structural equation model (SEM) was tested using SPSS and Amos 22 with a sample size of 320 respondents. Research results revealed four factors that affect customer satisfaction: payment method, shipping information, information security, and shipping time. Shipping cost and order fulfillment were found to have insignificant impacts. Information technology was proven to have a mediating role in improving customer satisfaction. The study results will be helpful for the government in developing and supporting E-commerce and E-logistics in Vietnam. In addition, it will help companies operating in this field understand their customers' needs better, thus attracting new customers, retaining current customers, and improving customer satisfaction. © 2023 Academy of Taiwan Information Systems Research. All rights reserved.","customer satisfaction; e-commerce; e-logistics; information security; payment method; shipping duration; shipping information","Viet Nam; cost; cost analysis; information technology; logistics; shipping",{"$nulls":6},"Cruz Netro Z. G., Medina Alvarez J. E., Cartas Carrillo A., Garza Flores R., Solid waste management in Mexico's offshore platform construction: determining potential supply for a reverse logistics process, Netnomics, 17, 1, pp. 71-94, (2016); Quyet N. X., Lan T. T. N., Phân tích các yếu tố ảnh hưởng đến dịch vụ hậu cần điện tử (e-logistics) tại tp. Hồ Chí Minh, Tạp chí khoa học công nghệ và thực phẩm, 19, 2, (2020); Grant D., Juntunen J., Juga J., Juntunen M., Investigating brand equity of third-party service providers, Journal of Services Marketing, 28, 3, pp. 214-222, (2014); Oliver R. L., Linda G., Effect of Satisfaction and Its Antecedents on Consumer Preference and Intention, ACR North American Advances, (1981); Tuan N. A., Ly N. T. V., Các yếu tố tác động đến sự hài lòng về chất lượng dịch vụ logistics-trường hợp Công ty Trách nhiệm Hữu hạn Thương mại Dịch vụ Dương Vy, Economics-Law and Management, 4, 3, (2020); Zailani S., Jafarzadeh S., Iranmanesh M., Nikbin D., Selim N. I. I., Halal logistics service quality: conceptual model and empirical evidence, British Food Journal, 120, 11, pp. 2599-2614, (2018); Politis Y., Giovanis A., Binioris S., Logistics service quality and its effects on customer satisfaction in the manufacturing companies' supply chains: Empirical evidence from Greece, Journal of Modelling in Management, 9, 2, pp. 215-237, (2014); Chaisaengduean K., Market orientation and logistics service process quality: an empirical investigation in the logistics service providers in Thailand, international academic multidisciplinary research conference in Vienna 2019, (2019); Sutrisno A., Andajani E., Widjaja F. N., The effects of service quality on customer satisfaction and loyalty in a logistics company, KnE Social Sciences, (2019); Gong W., Kan X., Logistic Service Development of E-commerce: A case study of AliExpress - an online international trade platform in China, (2013); Imran M., Hamid S., Aziz A., Hameed W., The contributing factors towards e-logistic customer satisfaction: a mediating role of information technology, Uncertain Supply Chain Management, 7, 1, pp. 63-72, (2019); Iskandar Y., Ramantoko G., Factors Affecting The Adoption of E-logistics in Indonesian E-Commerce Industry Using TOE Framework, Sustainable Collaboration in Business, Technology, Information and Innovation (SCBTII), 1, 1, (2018); Hwang B.-N., Huang C.-Y., Wu C.-H., A TOE Approach to Establish a Green Supply Chain Adoption Decision Model in the Semiconductor Industry, Sustainability, 8, 2, (2016); Ramanathan R., The moderating roles of risk and efficiency on the relationship between logistics performance and customer loyalty in e-commerce, Transportation Research Part E: Logistics and Transportation Review, 46, 6, pp. 950-962, (2010); Luhur Prianto A., Wongsurawat K., Yama A., Critically assessing the factors contributing toward e-logistics customer satisfaction by considering mediating role of information technology: A case study of Thailand food sector, World Food Policy, 6, 1, pp. 7-22, (2020); Graham D., Manikas I., Folinas D., E-logistics and e-supply chain management: Applications for evolving business, IGI Global, (2013); Lina Z., Guiling Z., Weiwei D., Empirical Analysis of Factors Influencing Logistic Service Satisfaction of Customer of Taobao, Technology and Method, 33, 5, pp. 215-217, (2014); Xia W., Tingting Y., Factors of influencing service satisfaction in express under e-commerce environment-as YuanTong Express for example, Modern Business Trade Industry, 24, pp. 47-48, (2016); Ali A., Haseeb M., Radio frequency identification (RFID) technology as a strategic tool towards higher performance of supply chain operations in textile and apparel industry of Malaysia, Uncertain Supply Chain Management, 7, 2, pp. 215-226, (2019); Ma S., Fast or free shipping options in online and Omni-channel retail? The mediating role of uncertainty on satisfaction and purchase intentions, The International Journal of Logistics Management, (2017); Chou Y., Lee C., Chung J., Understanding m-commerce payment systems through the analytic hierarchy process, Journal of Business Research, 57, 12, pp. 1423-1430, (2004); Dai X., Grundy J., NetPay: An off-line, decentralized micro-payment system for thin-client applications, Electronic Commerce Research and Applications, 6, 1, pp. 91-101, (2007); Stroborn K., Heitmann A., Leibold K., Frank G., Internet payments in Germany: a classificatory framework and empirical evidence, Journal of Business Research, 57, 12, pp. 1431-1437, (2004); Almohaimmeed B. M., Restaurant quality and customer satisfaction, International Review of Management and Marketing, 7, 3, pp. 42-49, (2017); Roozbahani F. S., Hojjati S. N., Azad R., The role of e-payment tools and e-banking in customer satisfaction case study: Pasargad bank e-payment company, International Journal of Advanced Networking and Applications, 7, 2, (2015); Trautman L. J., Managing cyberthreat, Santa Clara Computer & High Tech. LJ, 33, (2016); Abrazhevich D., Electronic payment systems: A user-centered perspective and interaction design, (2004); Guan S.-U., Hua F., A multi-agent architecture for electronic payment, International Journal of Information Technology & Decision Making, 2, pp. 497-522, (2003); Hair J. F., Black W. C., Babin B. J., Anderson R. E., Tatham R. L., Multivariate data analysis. Uppersaddle River, Multivariate Data Analysis (5th ed) Upper Saddle River, 5, 3, pp. 207-219, (1998); Anderson J. C., Gerbing D. W., Structural equation modeling in practice: A review and recommended two-step approach, Psychological bulletin, 103, 3, (1988); Kline P., Handbook of psychological testing, (2013); Fornell C., A national customer satisfaction barometer: The Swedish experience, Journal of marketing, 56, 1, pp. 6-21, (1992); Byrne B. M., Structural equation modeling with Mplus: Basic concepts, applications, and programming, (2013)","M.N. Tran; Banking Academy of Vietnam, Viet Nam; email: maitn@hvnh.edu.vn",null,"Academy of Taiwan Information Systems Research",{"$nulls":5},2.0739729E7,null,null,null,"English","Int. J. Electron. Commer. Stud.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85148870569"]
["Ahmed J.U.; Ahmed A.; Mazid T.S.; Gani M.O.","Ahmed, Jashim Uddin (7102828008); Ahmed, Asma (55448645200); Mazid, Tabassum Sufia (58157482000); Gani, Mohammad Osman (57220369895)","7102828008; 55448645200; 58157482000; 57220369895","Chari: A FMCG B2B platform with incorporation of Fintech",2023.0,"Journal of Information Technology Teaching Cases",{"$nulls":6},0.0,"10.1177/20438869231163600","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85150912322&doi=10.1177%2f20438869231163600&partnerID=40&md5=be296dd64052ad12ace428b0424565bc","Department of Management, School of Business and Economics, North South University, Dhaka, Bashundhara, Bangladesh; InterResearch, Bashundhara, Dhaka, Bangladesh; Department of Marketing, Bangladesh University of Professionals, Mirpur Cantonment, Dhaka, Bangladesh","Ahmed J.U., Department of Management, School of Business and Economics, North South University, Dhaka, Bashundhara, Bangladesh; Ahmed A., InterResearch, Bashundhara, Dhaka, Bangladesh; Mazid T.S., InterResearch, Bashundhara, Dhaka, Bangladesh; Gani M.O., Department of Marketing, Bangladesh University of Professionals, Mirpur Cantonment, Dhaka, Bangladesh","Morocco is an African country containing a very large market for e-commerce, which further expanded during the 2020–2022 COVID-19 pandemic. However, a few obstacles, like low internet penetration and lack of digital payment systems, are acting as obstacles for the local e-commerce service providers to reach potential in the country. Chari is one such B2B company whose operations changed the landscape of logistics and distribution among the FMCG businesses in Morocco. The company also exercises a B2B2C model, which it achieved through acquiring Karny.ma and Axa Credit, enabling its customers to use a lending and financial transaction tracking model. However, the industry is quite competitive, with offline retailers like TradeDepot, WaystoCap (acquired by MaxAB), and Sokowatch deciding to exploit the possibilities online. Apart from the rising competition, Chari still faces challenges in additional expansion due to the improper and inadequate infrastructure of the country. However, if it can overcome the external threats and utilize the geographical location of Morocco to its advantage, Chari has enormous potential to flourish both locally and globally. © Association for Information Technology Trust 2023.","Africa; B2B; Chari; E-commerce; fintech; Morocco",{"$nulls":7},"Beradda E.M., Morocco: Chari, a new start-up that relies on tradition. The Africa Report, (2021); Trade Depot. Digest Africa Companies; The e-commerce market in Morocco; Creating Markets in Morocco, (2019); Kene-Okafor T., B2B e-commerce platform Chari is acquiring the credit line of axa assurance in Morocco for $22M. TechCrunch, (2022); Kene-Okafor T., MaxAB gets an extra $15M, acquires YC-backed Moroccan startup WaystoCap. TechCrunch, (2021); Rahhou J., Visa and CMI to digitize B2B payments in Morocco, (2022); Sinclair M., Exploring Morocco’s growing e-commerce sector, (2022); Santosdiaz R., Fintech landscape in Morocco 2022, (2022); Whitehouse D., Sokowatch bets business-to-business E-commerce can beat Jumia’s retail in West Africa. The africa report, (2021)","J.U. Ahmed; Department of Management, School of Business and Economics, North South University, Bashundhara, Dhaka, Bangladesh; email: jashimahmed@hotmail.com",null,"SAGE Publications Inc.",{"$nulls":5},2.0438869E7,null,null,null,"English","J. Infor. Technol. Teach. Classes","Article","Article in press",null,"Scopus","2-s2.0-85150912322"]
["Altarturi H.H.M.; Nor A.R.M.; Jaafar N.I.; Anuar N.B.","Altarturi, Hamza H. M. (57202201791); Nor, Adibi Rahiman Md (56642540900); Jaafar, Noor Ismawati (15848399900); Anuar, Nor Badrul (22733749500)","57202201791; 56642540900; 15848399900; 22733749500","A bibliometric and content analysis of technological advancement applications in agricultural e-commerce",2023.0,"Electronic Commerce Research",{"$nulls":6},3.0,"10.1007/s10660-023-09670-z","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85146708824&doi=10.1007%2fs10660-023-09670-z&partnerID=40&md5=69aedc6a1082b464869f09972b14c8ca","Department of Computer System and Technology, Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur, 50603, Malaysia; Institute for Advanced Studies, University of Malaya, Kuala Lumpur, 50603, Malaysia; Department of Operation and Management Information System, Faculty of Business and Accountancy, University of Malaya, Kuala Lumpur, 50603, Malaysia","Altarturi H.H.M., Department of Computer System and Technology, Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur, 50603, Malaysia; Nor A.R.M., Institute for Advanced Studies, University of Malaya, Kuala Lumpur, 50603, Malaysia; Jaafar N.I., Department of Operation and Management Information System, Faculty of Business and Accountancy, University of Malaya, Kuala Lumpur, 50603, Malaysia; Anuar N.B., Department of Computer System and Technology, Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur, 50603, Malaysia","Given the severe difficulties and challenges being faced during the current COVID-19 pandemic, agribusinesses must consider alternative means to market and sell agriproducts using e-commerce and advanced technologies. Agricultural e-commerce that utilizes advanced technologies can promote sustainable economic growth and gender equality and, therefore, helps achieve the Sustainable Development Goals. It also allows farmers access to new markets where they can bypass intermediaries, leading to higher income, less waste, and fresher produce for customers. The usefulness of using agricultural e-commerce depends on the efficiency of addressing the emerging challenges from merging perspectives of agricultural and e-commerce fields. Literature reviews addressed both fields from different perspectives, however, most literature addresses the agriculture and e-commerce fields separately, leading to unclarity in understanding the differences between agriproducts and other products. This study aims to present a comprehensive and robust roadmap of technological advancements and challenges in agricultural e-commerce through a thorough bibliometric and content analysis and provide a conceptual architecture for best practices. The bibliometric and content analysis sheds light on the agricultural e-commerce categories, challenges, and limitations. This study identifies the most influential research and topic trends, determines the topical discipline areas, and provides visions and directions for future research in the field of agricultural e-commerce. It discusses the challenges of agricultural e-commerce and agriproducts and how advanced technologies help solve such challenges. This study summarises the best practice implementation of agricultural e-commerce by providing strong logistics, implementing standardization, including information knowledge of agriproducts, and creating a traceability information system. The result of this paper is presented as a proposed conceptual architecture for agricultural e-commerce that addresses the abovementioned best practice concepts and utilizes the Blockchain and IoT technologies to provide innovative solutions for the agricultural e-commerce stakeholders. Finally, this study provides prospects for future research on advanced technologies in agricultural e-commerce. © 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.","Advanced technology; Agriculture; Bibliometric; Blockchain; e-commerce; Internet of Things","Agricultural technology; Electronic commerce; Internet of things; Sustainable development; 'current; Advanced technology; Best practices; Bibliometric; Bibliometrics analysis; Block-chain; Conceptual architecture; Content analysis; E- commerces; Technological advancement; Blockchain",{"$nulls":6},{"$cut":{"chars":18679,"head":"Aboody D., Lev B., Information asymmetry, R&D, and insider gains, The journal of Finance, 55, 6, pp. 2747-2766, (2000); Abrizah A., Zainab A.N., Kiran K., Raj R.G., LIS journals scientific impact and subject categorization: a comparison between Web ofScience and Scopus, Scientometrics, 94, 2, pp. 721-740, (2012); Altarturi B.H.M., Othman A.H.A., Behavioral intention of using a complementary currency in Palestine, The Importance of New Technologies and Entrepreneurship in Business Development. in the Context of Economic Diversity in Developing Countries, pp. 1084-1107, (2021); Altarturi H., Saadoon M., Anuar N.B., Cyber parental control: a bibliometric study, Children and Youth Services Review, (2020); Arfaoui A., Ibrahimi K., Trabelsi F., Biochar application to soil under arid conditions: a bibliometric study of research status and trends, Arabian Journal of Geosciences, (2019); Aria M., Cuccurullo C., bibliometrix: an R-tool for comprehensive science mapping analysis, Journal of Informetrics, 11, 4, pp. 959-975, (2017); Balasubramanian G.K., Balakrishnan M., Ch S., Soam S., Status and scope of e-commerce in agribusiness in India, International Research Journal of Management and Commerce, (2018); Banerjee T., Mishra M., Debnath N.C., Choudhury P., Implementing E-commerce model for agricultural produce: a research roadmap, Periodicals of Engineering and Natural Sciences (PEN), 7, 1, pp. 302-310, (2019); Bao J., The analysis and strategy of information asymmetry in e-commerce, 2011 International Conference on E-Business and E-Government (ICEE), (2011); Barenji A.V., Wang W., Li Z., Guerra-Zubiaga D.A., Intelligent E-commerce logistics platform using hybrid agent based approach, Transportation research part e: Logistics and transportation review, 126, pp. 15-31, (2019); Bhende M., Avatade M.S., Patil S., Mishra P., Prasad P., Shewalkar S., Digital Market: E-Commerce Application For Farmers, 2018 Fourth International Conference on Computing Communication Control and Automation (ICCUBEA), (2018); Bornmann L., Haunschild R., Citation score normalized by cited references (CSNCR): the introduction of a new citation impact indicator, Journal of Informetrics, 10, 3, pp. 875-887, (2016); A comparison between two main academic literature collections: Web of Science and scopus databases, Web of Science and Scopus Databases, 22, (2013); Chen H., Challenges and Countermeasures of Hunan Agricultural Electronic Commerce from the Angle of Internet: A theoretical review, Destech Transactions on Social Science, Education and Human Science, (2017); Chen Q., Research on the Agricultural E-Commerce in Consumer’s Perspective, (2016); Chen T., Wang D., Combined application of blockchain technology in fractional calculus model of supply chain financial system, Chaos, Solitons & Fractals., 131, (2020); Chevalier S., Retail e-commerce sales worldwide from 2014 to 2024, Statista, (2021); Cobo M.J., Lopez-Herrera A.G., Herrera-Viedma E., Herrera F., An approach for detecting, quantifying, and visualizing the evolution of a research field: a practical application to the fuzzy sets theory field, Journal of Informetrics, 5, 1, pp. 146-166, (2011); Cristobal-Fransi E., Montegut-Salla Y., Ferrer-Rosell B., Daries N., Rural cooperatives in the digital age: an analysis of the internet presence and degree of maturity of agri-food cooperatives’e-commerce, Journal of Rural Studies, 74, pp. 55-66, (2020); Das D., Dutta P., Performance analysis of a closed-loop supply chain with incentive-dependent demand and return, The International Journal of Advanced Manufacturing Technology, 86, 1, pp. 621-639, (2016); Delima R., Budi H., Andriyanto N., Wibowo A., Development of purchasing module for agriculture e-Commerce using Dynamic System Development Model, Int. J. Adv. Comput. Sci. Appl, 9, 10, (2018); Della Corte V., Del Gaudio G., Sepe F., Sciarelli F., Sustainable tourism in the open innovation realm: a bibliometric analysis, Sustainability, 11, 21, (2019); Dey K., Shekhawat U., Blockchain for sustainable e-agriculture: literature review, architecture for data mana"}},"N.B. Anuar; Department of Computer System and Technology, Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur, 50603, Malaysia; email: badrul@um.edu.my",null,"Springer",{"$nulls":5},1.3895753E7,null,null,null,"English","Electron. Commer. Res.","Article","Article in press","All Open Access; Bronze Open Access","Scopus","2-s2.0-85146708824"]
["Qi Z.; Tijun F.; Yang S.","Qi, Zheng (58510439600); Tijun, Fan (22978899800); Yang, Song (58511494500)","58510439600; 22978899800; 58511494500","Impact of traceability technology investment on supply chains for fresh product under pre-position warehouse mode; [前置仓模式下的生鲜农产品供应链追溯 技术投资决策研究]",2023.0,"Journal of Industrial Engineering and Engineering Management",37.0,4.0,null,165.0,178.0,13.0,0.0,"10.13587/j.cnki.jieem.2023.04.014","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85166031819&doi=10.13587%2fj.cnki.jieem.2023.04.014&partnerID=40&md5=976f9a7ff64548e8355a395af7ec4e04","School of Management, Shanghai University of Engineering Science, Shanghai, 201620, China; School of Business, East China University of Science and Technology, Shanghai, 200237, China; Glorious Sun School of Business and Management, Donghua University, Shanghai, 200051, China","Qi Z., School of Management, Shanghai University of Engineering Science, Shanghai, 201620, China; Tijun F., School of Management, Shanghai University of Engineering Science, Shanghai, 201620, China, School of Business, East China University of Science and Technology, Shanghai, 200237, China; Yang S., Glorious Sun School of Business and Management, Donghua University, Shanghai, 200051, China","Since China′s fresh e-commerce industry is developing rapidly with the rise of platform economy and the rapid popularization of the Internet, many enterprises are involved in the field of fresh e-commerce. However, due to the freshness of consumer preference and the high frequency of purchase, the pre-position warehouse mode of fresh e-commerce has gradually become a new development trend. Many e-commerce enterprises adopt such mode to reduce intermediate links and shorten the distribution time, so as to ensure the freshness and quality of products and improve operation efficiency. Fresh agricultural products are different from ordinary products, which need refrigerated trucks in the transportation process, with relatively high logistics cost as well as quantity and quality loss. How to reduce the loss of products and improve the profits of the supply chain has become an important problem to be solved in the operation of the fresh product supply chain. In practice, fresh e-commerce has begun to apply traceability technology to reduce the loss of fresh products, which can not only identify the exact information of products by tracking products through labels, but also avoid losses caused by inaccurate inventory location of each node in the supply chain. Therefore, it is urgent to study the optimal decision-making of fresh agricultural products supply chain under the pre-position warehouse mode, and how to invest in traceability technology to reduce product loss, maximize supply chain profits, and improve the performance of fresh agricultural supply chain. This paper considers a fresh agricultural product supply chain composed of the supplier and the fresh e-commerce with two preposition warehouses. The supplier can offer a single variety of fresh agricultural products to fresh e-commerce. In view of the freshness and perishability of fresh products, we combine the two cases of supplier delivery to warehouse and fresh e-commerce self delivery, then adopt the method of game theory to construct the supply chain decision model when supplier and fresh electricity supplier respectively invest in traceability technology. We analyze the influence of quantity loss, freshness loss and transportation distance on the decision-making of fresh agricultural products supply chain under pre-position warehouse mode. Then we discuss how to reduce the quantity loss and freshness loss of fresh products through traceability technology, investigate the optimal decision of fresh agricultural products supply chain under the investment traceability technology, and how to choose the way of delivery to maximize profits when investing in traceability technology. In the case of supplier delivery to the warehouse, the fresh e-commerce determines the optimal order quantity of agricultural products respectively according to the market demand function of the region where the two pre-position warehouses are located. The supplier shall transport the products to two different pre-position warehouses according to the order quantity of fresh e-commerce, then formulate the optimal wholesale price. The fresh e-commerce determines the optimal retail price in the region where the two pre-position warehouses are located for sales. In case of the fresh e-commerce self delivery, the fresh e-commerce determines the optimal product order quantity respectively according to the market demand function of the region where the two preposition warehouses are located. The supplier determines the optimal wholesale price according to the order quantity of fresh e-commerce. The fresh e-commerce transports the products to two pre-position warehouses respectively, and then formulates the optimal retail price for sales. Finally, we study the influence of loss coefficient and other factors on the optimal decision-making of fresh agricultural products supply chain under different delivery conditions through the example analysis, then explore the change trend of supply chain profit before and after investment traceability technology. The research reveals that: (1) when the inventory availability of products is within the threshold range, the fresh e-commerce can improve its profit by choosing the way of self delivery. When the inventory availability of products exceeds the threshold range, the way of supplier delivery to the warehouse can improve its profit. (2) The supply chain can gain more profits by increasing the order quantity of long-distance pre-warehouse under the mode of supplier delivery to warehouse and increasing the order quantity of short-distance prewarehouse under the mode of fresh e-commerce self-picking goods. (3) When the supply chain invests in traceability technology, the total profit of fresh agricultural products supply chain can be significantly improved than that without traceability technology, and the total profit of supply chain is positively correlated with inventory availability. (4) In the delivery to warehouse mode, the fresh ecommerce investment in traceability technology can make the supply chain obtain greater profits. In the self delivery mode, the supplier investment in traceability technology can make the supply chain obtain greater profits. From the above analysis, it can be seen that when the supplier invests in traceability technology, the profit of fresh e-commerce in the self delivery mode increases with the label cost of traceability technology, while the profits of supplier and supply chain decrease with the increase of traceability technology label cost. The supply chain can obtain more profits under the fresh e-commerce self delivery mode than under the supplier delivery to warehouse mode. However, the supplier can make greater profits in the fresh e-commerce self delivery mode than in the supplier delivery to warehouse mode, while fresh e-commerce can make greater profits in the supplier delivery to warehouse mode than in the self delivery mode. Hence, the supplier and the fresh e-commerce can make reasonable decisions according to specific conditions. © 2023, Journal of Industrial Engineering and Engineering Management. All Rights Reserved.","Fresh product; Pre-position warehouse; Supply chain decisions; Traceability technology",{"$nulls":5},"National Natural Science Foundation of China, NSFC, (71901141, 71972071, 72032001)","Received Date: 2021-04-30 　 　 　 Funded Project: Supported by the National Natural Science Foundation of China (72032001, 71901141, 71972071). ∗Corresponding author","Ding L, Hu B, Chang S, Et al., A game analysis on RFID technology and parallel importation based on gray market traceability [ J], Chinese Journal of Management Science, 29, 2, pp. 78-88, (2021); Ma X L, Wang J, Bai Q G, Et al., Optimization of a three-echelon cold chain considering freshness-keeping efforts under cap-andtrade regulation in Industry 4. 0[J], International Journal of Production Economics, 220, pp. 107-121, (2020); Avinadav T, Chernonog T, Lahav Y., Dynamic pricing and promotion expenditures in an EOQ model of perishable products[J], Annals of Operations Research, 248, 1, pp. 75-91, (2017); Zheng Q, Fan T J., Design of incentive contract for fresh agricultural products supply chain considering risk preference, Journal of Industrial Engineering and Engineering Management, 32, 2, pp. 171-178, (2018); Tunuguntla V, Basu P, Rakshit K, Et al., Sponsored search advertising and dynamic pricing for perishable products under inventory-linked customer willingness to pay[J], European Journal of Operational Research, 276, 1, pp. 119-132, (2019); Li S, Zhang J, Tang W., Joint dynamic pricing and inventory control policy for a stochastic inventory system with perishable products[J], International Journal of Production Research, 53, 10, pp. 2937-2950, (2015); Ou-yang L Y, Wu K S, Yang C T, Et al., Optimal order policy in response to announced price increase for deteriorating items with limited special order quantity[J], International Journal of Systems Science, 47, 3, pp. 718-729, (2016); Zheng Y T, Li J B, Chen Z Y, Et al., Optimal decisions of cold chain distributor under uncertain in demand, Journal of Management Sciences in China, 22, 1, pp. 94-106, (2019); Zheng Q, Zhou L, Fan T J, Et al., Joint procurement and pricing of fresh produce for multiple retailers with a quantity discount contract[J], Transportation Research Part E, 130, pp. 16-36, (2019); Liu M L, Dan B, Ma S X., Optimal strategies and coordination of fresh e-commerce supply chain considering freshness-keeping effort and value-added service[J], Chinese Journal of Management Science, 28, 8, pp. 76-88, (2020); Pu X J, Jin D L., The operational efficiency measurement of agrifood supply chains: the single “farmer-supermarket direct purchase” vs. dual channel, Chinese Journal of Management Science, 25, 1, pp. 98-105, (2017); Yang L, Tang R H., Comparisons of sales modes for a fresh product supply chain with freshness-keeping effort [J], Transportation Research Part E, 125, pp. 425-448, (2019); Khan M A, Shaikh A A, Konstantaras I., Inventory models for perishable items with advanced payment, linearly time-dependent holding cost and demand dependent on advertisement and selling price[J], International Journal of Production Economics, 230, 4, pp. 1-18, (2020); Cao X N, Wang Y M, Xue F H, Et al., Coordination strategies for dual-channel supply chain of fresh agricultural products considering the fresh-keeping effort of supplier[J], Chinese Journal of Management Science, 29, 3, pp. 109-118, (2021); Bai Q G, Xu X H, Pan W., Joint pricing and inventory model for deteriorating items with multi-channel distribution system [ J], Journal of Industrial Engineering and Engineering Management, 31, 3, pp. 84-92, (2017); Yang H, Chen W., Game modes and investment cost locations in radio-frequency identification ( RFID) adoption [ J], European Journal of Operational Research, 286, 3, pp. 883-896, (2020); Tao F, Fan T J, Lai K K, Et al., Impact of RFID technology on inventory control policy, Journal of the Operational Research Society, 68, 2, pp. 207-220, (2017); Wang Q Y, Tao F, Fan T J, Et al., Research on decision-making of two supply chains with RFID technology[J], Chinese Journal of Management Science, 28, 11, pp. 120-129, (2020); Yang H X, Luo J W., The impact of pricing power and revenue sharing on incentives for RFID adoption[J], Journal of Industrial Engineering and Engineering Management, 34, 1, pp. 46-54, (2020); Dai B, Nu Y, Xie X, Et al., Interactions of traceability and reliability optimization in a competitive supply chain with product recall[J], European Journal of Operational Research, 290, 1, pp. 116-131, (2021); Sunny J, Undralla N, Madhusudanan P V., Supply chain transparency through blockchain-based traceability: An overview with demonstration [ J], Computers & Industrial Engineering, 150, pp. 106-115, (2020); Kong G, Rajagopalan S, Zhang H., Revenue sharing and information leakage in a supply chain[J], Management Science, 59, 3, pp. 556-572, (2013); Feng H, Wang X, Duan Y, Et al., Applying blockchain technology to improve agri-food traceability: A review of development methods, benefits and challenges[J], Journal of Cleaner Production, 260, pp. 121-136, (2020)",null,null,"Zhejiang University",{"$nulls":5},1.0046062E7,null,null,null,"English","J. Industrial Eng. Eng. Management","Article","Final",null,"Scopus","2-s2.0-85166031819"]
["Risberg A.; Jafari H.; Sandberg E.","Risberg, Andreas (57467118300); Jafari, Hamid (56500130400); Sandberg, Erik (35362933400)","57467118300; 56500130400; 35362933400","A configurational approach to last mile logistics practices and omni-channel firm characteristics for competitive advantage: a fuzzy-set qualitative comparative analysis",2023.0,"International Journal of Physical Distribution and Logistics Management",53.0,11.0,null,53.0,70.0,17.0,3.0,"10.1108/IJPDLM-04-2022-0123","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85152446035&doi=10.1108%2fIJPDLM-04-2022-0123&partnerID=40&md5=f75655a6cdb0919d9c66273baf939ad7","Department of Supply Chain and Operations Management, School of Engineering, Jönköping University, Jönköping, Sweden; Department of Management and Engineering, Linköping University, Linköping, Sweden","Risberg A., Department of Supply Chain and Operations Management, School of Engineering, Jönköping University, Jönköping, Sweden; Jafari H., Department of Supply Chain and Operations Management, School of Engineering, Jönköping University, Jönköping, Sweden; Sandberg E., Department of Management and Engineering, Linköping University, Linköping, Sweden","Purpose: The purpose is to explore how the configurations resulting from the interplay of last mile logistics practices and firm characteristics are associated with firm performance in an omni-channel context. Design/methodology/approach: Drawing on configuration theory (CT), the authors use fuzzy-set qualitative comparative analysis (fsQCA) to analyze data on 72 Swedish omni-channel retailers. Findings: Four configurations are identified—store-oriented small and medium-sized enterprises (SME's), online-oriented SME's, large store-oriented retailers and large online-oriented retailers. The results show that while offering a wide range of delivery options is necessary to achieve high performance, it is not sufficient, and that returns and fulfilment should be simultaneously considered. For instance, large high-performers leverage their stores and warehouses for fulfilment and returns in an integrated way irrespective of sales channel-mix. However, SME's appear to focus on fulfilment simplicity with less-costly delivery alternatives, where store-oriented SME's leverage stores and the online-oriented counterparts leverage warehouses. Consequently, the authors develop a configurational taxonomy and discuss a set of recipes which provide insights for researchers and practitioners. Research limitations/implications: The study provides a more comprehensive understanding of the pathways to success, and potential pitfalls, in the last mile logistics context. Originality/value: This study applies a novel methodology in the field, namely fsQCA, to explore the paths to competitive advantage. It covers a wide range of stages in the LM including back-end fulfilment, delivery and returns. It also provides insight into the logistics practices of both SME's and large omni-channel retailers. © 2023, Andreas Risberg, Hamid Jafari and Erik Sandberg.","e-commerce; Firm performance; Fuzzy-set qualitative comparative analysis (fsQCA); Last mile logistics; Omni-channel; SME",{"$nulls":5},"European Regional Development Fund, ERDF","The authors would like to thank the e-Merge research project (20201932) co-financed by the European Regional Development Fund, and Dr. Mohsin Malik for sharing his extensive QCA knowledge.","Aastrup J., Halldorsson A., Epistemological role of case studies in logistics: a critical realist perspective, International Journal of Physical Distribution and Logistics Management, 38, pp. 746-763, (2008); Agatz N.A.H., Fleischmann M., Van Nunen J.E.E., E-fulfillment and multi-channel distribution - a review, European Journal of Operational Research, 187, pp. 339-356, (2008); Arend R.J., Wisner J.D., Small business and supply chain management: is there a fit?, Journal of Business Venturing, 20, pp. 403-436, (2005); Bell R.G., Filatotchev I., Aguilera R.V., Corporate governance and investors' perceptions of foreign IPO value: an institutional perspective, Academy of Management Journal, 57, pp. 301-320, (2014); Bernon M., Cullen J., Gorst J., Online retail returns management: integration within an omni-channel distribution context, International Journal of Physical Distribution and Logistics Management, 46, pp. 584-605, (2016); Buldeo Rai H., Verlinde S., Macharis C., The ‘next day, free delivery’ myth unravelled: possibilities for sustainable last mile transport in an omnichannel environment, International Journal of Retail and Distribution Management, 47, pp. 39-54, (2019); Cao D., Wang Y., Berkeley N., Tjahjono B., Configurational conditions and sustained competitive advantage: a fsQCA approach, Long Range Planning, 55, 4, (2021); Chopra S., How omni-channel can be the future of retailing, Decision, 43, pp. 135-144, (2016); Davis-Sramek B., Ishfaq R., Gibson B.J., Defee C., Examining retail business model transformation: a longitudinal study of the transition to omnichannel order fulfillment, International Journal of Physical Distribution and Logistics Management, 50, pp. 557-576, (2020); De Leeuw S., Minguela-Rata B., Sabet E., Boter J., Sigurdardottir R., Trade-offs in managing commercial consumer returns for online apparel retail, International Journal of Operations and Production Management, 36, pp. 710-731, (2016); Eriksson E., Norrman A., Kembro J., Contextual adaptation of omni-channel grocery retailers' online fulfilment centres, International Journal of Retail and Distribution Management, 47, pp. 1232-1250, (2019); SME definition, Internal Market, Industry, Entreprenurship, and SMEs, (2020); Fiss P.C., A set-theoretic approach to organizational configurations, Academy of Management Review, 32, pp. 1180-1198, (2007); Fiss P.C., Building better causal theories: a fuzzy set approach to typologies in organization research, Academy of Management Journal, 54, pp. 393-420, (2011); Flynn B.B., Huo B., Zhao X., The impact of supply chain integration on performance: a contingency and configuration approach, Journal of Operations Management, 28, pp. 58-71, (2010); Galeazzo A., Furlan A., Lean bundles and configurations: a fsQCA approach, International Journal of Operations and Production Management, 38, pp. 513-533, (2018); Gallino S., Moreno A., Integration of online and offline channels in retail: the impact of sharing reliable inventory availability information, Management Science, 60, pp. 1434-1451, (2014); Gao F., Su X., Omnichannel retail operations with buy-online-and-pick-up-in-store, Management Science, 63, pp. 2478-2492, (2017); Greckhamer T., Furnari S., Fiss P.C., Aguilera R.V., Studying configurations with qualitative comparative analysis: best practices in strategy and organization research, Strategic Organization, 16, pp. 482-495, (2018); Grewal D., Gauri D.K., Roggeveen A.L., Sethuraman R., Strategizing retailing in the new technology era, Journal of Retailing, 97, pp. 6-12, (2021); Handel S., Svensk handels hållbarhetsundersökning 2019, (2020); Handelsradet, Handelsfakta” [online]. 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A comparison study of marketing skills and logistics infrastructure of small and large wholesaler™, International Business Review, 22, pp. 687-698, (2013); Risberg A., A systematic literature review on e-commerce logistics: towards an e-commerce and omni-channel decision framework, International Review of Retail, Distribution and Consumer Research, 33, 1, pp. 67-91, (2022); Risberg A., Jafari H., Last mile practices in e-commerce: framework development and empirical analysis of Swedish firms, International Journal of Retail and Distribution Management, 50, pp. 942-961, (2022); Risberg A., Jafari H., Last mile practices in e-commerce: framework development and empirical analysis of Swedish firms, International Journal of Retail and Distribution Management, 50, pp. 942-961, (2022); Rubinson C., Presenting qualitative comparative analysis: notation, tabular layout, and visualization, Methodological Innovations, 12, 2, (2019); Russo I., Confente I., From dataset to qualitative comparative analysis (QCA)—challenges and tricky points: a research note on contrarian case analysis and data calibration, Australasian Marketing Journal (AMJ), 27, pp. 129-135, (2019); Sallnas U., Bjorklund M., Consumers' influence on the greening of distribution – exploring the communication between logistics service providers, e-tailers and consumers, International Journal of Retail and Distribution Management, 48, pp. 1177-1193, (2020); Salonen A., Zimmer M., Keranen J., Theory development in servitization through the application of fsQCA and experiments, International Journal of Operations and Production Management, 41, pp. 746-769, (2021); Sanchez-Torres J.A., Juarez-Acosta F., Modelling SME e-commerce with IMAES, Journal of Business and Industrial Marketing, 34, pp. 137-149, (2019); Sandberg E., Abrahamsson M., Logistics capabilities for sustainable competitive advantage, International Journal of Logistics Research and Applications, 14, pp. 61-75, (2011); Shen Z.M., Sun Y., Strengthening supply chain resilience during COVID-19: a case study of JD.com, Journal of Operations Management, (2021); Sirmon D.G., Hitt M.A., Ireland R.D., Managing firm resources in dynamic environments to create value: looking inside the black box, Academy of Management Review, 32, pp. 273-292, (2007); Srai J.S., Gregory M., A supply network configuration perspective on international supply chain development, International Journal of Operations and Production Management, 28, pp. 386-411, (2008); Vaaland T.I., Heide M., Can the SME survive the supply chain challenges?, Supply Chain Management: An International Journal, 12, pp. 20-31, (2007); Vanelslander T., Deketele L., Van Hove D., Commonly used e-commerce supply chains for fast moving consumer goods: comparison and suggestions for improvement, International Journal of Logistics, 16, pp. 243-256, (2013); Wollenburg J., Holzapfel A., Hubner A., Kuhn H., Configuring retail fulfillment processes for omni-channel customer steering, International Journal of Electronic Commerce, 22, pp. 540-575, (2018); Wollenburg J., Hubner A., Kuhn H., Trautrims A., From bricks-and-mortar to bricks-and-clicks: logistics networks in omni-channel grocery retailing, International Journal of Physical Distribution and Logistics Management, 48, pp. 415-438, (2018); The future of the last-mile ecosystem: transition roadmaps for public- and private-sector players, (2020); Zhao X.D., Sum C.C., Qi Y.N., Zhang H.Y., Lee T.S., A taxonomy of manufacturing strategies in China, Journal of Operations Management, 24, pp. 621-636, (2006)","A. Risberg; Department of Supply Chain and Operations Management, School of Engineering, Jönköping University, Jönköping, Sweden; email: andreas.risberg@ju.se",null,"Emerald Publishing",{"$nulls":5},9600035.0,null,null,null,"English","Int. J. Phys. Distrib. Logist. Manage.","Article","Final","All Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85152446035"]
["Suhendar A.; Setiadi R.; Artati A.; Rohman A.","Suhendar, Ade (58512489700); Setiadi, Ronald (58513699400); Artati, Artati (58513699500); Rohman, Abdul (57956599000)","58512489700; 58513699400; 58513699500; 57956599000","The New Trend: Why Indonesian Digital Start-Up Employees are Opting for Quiet Quitting?",2023.0,"WSEAS Transactions on Computer Research",11.0,null,15.0,166.0,180.0,14.0,1.0,"10.37394/232018.2023.11.15","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85166183946&doi=10.37394%2f232018.2023.11.15&partnerID=40&md5=6fa580bc73c8069aa45e60ab3bc78d45","Department of Management, Binus Business School Master Program, Bina Nusantara University, Jakarta, 11480, Indonesia","Suhendar A., Department of Management, Binus Business School Master Program, Bina Nusantara University, Jakarta, 11480, Indonesia; Setiadi R., Department of Management, Binus Business School Master Program, Bina Nusantara University, Jakarta, 11480, Indonesia; Artati A., Department of Management, Binus Business School Master Program, Bina Nusantara University, Jakarta, 11480, Indonesia; Rohman A., Department of Management, Binus Business School Master Program, Bina Nusantara University, Jakarta, 11480, Indonesia","Our study examined variable JS, OC, and OCB on QQ within the context of Indonesian digital start-ups. A survey was conducted on 269 employees from digital start-ups in various sectors, such as transportation and logistics, food delivery, e-commerce, fintech, digital payments and wallets, and online learning platforms. Quantitative analysis with SmartPLS 4.0 was used to process the primary data and obtain the SEM. It showed that six out of seven hypotheses were accepted. The direct effect simulation revealed that JS and OC significantly influenced OCB and QQ. Additionally, OCB significantly impacted QQ and mediated the effect of OC on QQ but failed to mediate the relationship between JS and QQ. This research indicates that mitigating the QQ phenomenon requires a comprehensive focus on improving JS, fostering OC, and encouraging OCB. In addition, the findings can be leveraged to devise more effective human resource strategies, including competitive compensation packages, performance-based bonuses, and market-aligned salaries to increase JS. Also, the study underscores the need for promoting a positive work culture and employee development opportunities to augment OC and OCB. Ultimately, these insights guide the creation of human resource policies that can enhance employee performance and commitment, thereby contributing to a company's overall success and productivity. © 2023, World Scientific and Engineering Academy and Society. All rights reserved.","Job satisfaction (JS); Organizational citizenship behavior (OCB); Organizational commitment (OC); Quiet quitting (QQ)",{"$nulls":7},"Bezdrob M., Sunje A., Transient nature of the employees’ job satisfaction: The case of the IT industry in Bosnia and Herzegovina, European Research on Management and Business Economics, 27, 2, (2021); Dziuban C., Graham C. R., Moskal P. D., Norberg A., Sicilia N., Blended learning: the new normal and emerging technologies, International Journal of Educational Technology in Higher Education, 15, 1, (2018); Selezneva I. V., Shtiller M. V., Tussupova L. A., Sembin A. B., Tulegenova M. S., Specifics of project management in modern conditions of digital transformation of the economy, Electronic Government, an International Journal, 1, 1, (2023); Wolor C. W., Kurnianti D., Zahra S. F., Martono S., The importance of work-life balance on employee performance millennial generation in Indonesia, Journal of Critical Reviews, 7, 9, (2020); Formica S., Sfodera F., The Great Resignation and Quiet Quitting paradigm shifts: An overview of current situation and future research directions, Journal of Hospitality Marketing and Management, 31, 8, (2022); Vallas S., Et al., The Creativity Hoax: Precarious Work and the Gig Economy, New Technol Work Employ, 34, 1, (2022); Chung H., van der Lippe T., Flexible Working, Work–Life Balance, and Gender Equality: Introduction, Soc Indic Res, 151, 2, (2020); Lata M., Chaudhary R., Workplace Spirituality and Experienced Incivility at Work: Modeling Dark Triad as a Moderator, Journal of Business Ethics, 174, 3, (2021); Reichelt M., Makovi K., Sargsyan A., The impact of COVID-19 on gender inequality in the labor market and gender-role attitudes, European Societies, 23, S1, (2021); Hutagalung I., Soelton M., Octaviani A., The role of work life balance for organizational commitment, Management Science Letters, 10, 15, (2020); Bowers A., Wu J., Lustig S., Nemecek D., Loneliness influences avoidable absenteeism and turnover intention reported by adult workers in the United States, Journal of Organizational Effectiveness, 9, 2, (2022); Asst R., Yikilmaz I., Quiet Quitting: A Conceptual Investigation, Anadolu 10th International Conference on Social Science, (2022); Schlee R. P., Eveland V. B., Harich K. R., From Millennials to Gen Z: Changes in student attitudes about group projects, Journal of Education for Business, 95, 3, pp. 139-147, (2020); Zenger J., Folkman J., Employee Engagement: Quiet Quitting Is About Bad Bosses, Not Bad Employees, Harv Bus Rev, (2022); Grego-Planer D., The relationship between organizational commitment and quizenship behaviors in the public and private sectors, Sustainability (Switzerland), 11, 22, (2019); Dermonde M., Fischer B. B., Franchising Strategies in Startups: Building an Analytical Framework, Latin American Business Review, (2022); Centobelli P., Cerchione R., Esposito E., Passaro R., Quinto I., The undigital behavior of innovative startups: empirical evidence and taxonomy of digital innovation strategies, International Journal of Entrepreneurial Behaviour and Research, 28, 9, pp. 219-241, (2022); Mahand T., Caldwell C., Quiet quitting – Causes and opportunities, Business and Management Research, 12, 1, (2023); Smith J. R., Micich L. A., McWilliams D. L., Organization Citizenship and Employee Withdrawal Behavior in the Workplace, International Journal of Human Resource Studies, 6, 3, (2016); Wolff M. B., O'Connor P. J., Wilson M. G., Gay J. L., Associations Between Occupational and Leisure-Time Physical Activity With Employee Stress, Burnout and Well-Being Among Healthcare Industry Workers, American Journal of Health Promotion, 35, 7, (2021); Scanlan J. N., Et al., Workplace experiences of mental health consumer peer workers in New South Wales, Australia: A survey study exploring job satisfaction, burnout and turnover intention, BMC Psychiatry, 20, 1, (2020); Massoud S. F., Moussa S. M., Hanafy S. A., El Backly R. M., Evaluation of the Microhardness of Root Canal Dentin After Different Irrigation Protocols (in Vitro Study), Alexandria Dental Journal, 42, 1, pp. 73-79, (2017); Labrague L. J., Nwafor C. E., Tsaras K., Influence of toxic and transformational leadership practices on nurses’ job satisfaction, job stress, absenteeism and turnover intention: A cross-sectional study, J Nurs Manag, 28, 5, (2020); Ahmad A., The relationship among job characteristics organizational commitment and employee turnover intentions: A reciprocation perspective, Journal of Work-Applied Management, 10, 1, (2018); Tremblay M., Simard G., Mathlouthi W., When Positive is Better and Negative Stronger: A study of Job Satisfaction, OCB and Absenteeism, Academy of Management Proceedings, 2016, 1, (2016); Wang T., Abrantes A. C. M., Liu Y., Intensive care units nurses’ burnout, organizational commitment, turnover intention and hospital workplace violence: A cross-sectional study, Nurs Open, 10, 2, pp. 1102-1115, (2023); Rohman A., The antecedents of employee's performance in research center, International Journal of Business and Applied Social Science, pp. 18-24, (2022); Novitasari D., Asbari M., Wijayanti L. M., Hyun C. C., Farhan M., The Role of Religiosity, Leadership Style, Job Satisfaction and Organizational Citizenship Behavior Mediation on Woman Teachers’ Performance, Solid State Technology, 63, 6, pp. 2953-2967, (2020); Belwalkar S., Vohra V., Pandey A., The relationship between workplace spirituality, job satisfaction and organizational citizenship behaviors – an empirical study, Social Responsibility Journal, 14, 2, pp. 410-430, (2018); Dasgupta M., Dey A. K., Mediating role of job crafting in the relationship between organisational culture and employee engagement, International Journal of Indian Culture and Business Management, 22, 1, (2021); Lee S. H., Achieving corporate sustainability performance: The influence of corporate ethical value, and leader-member exchange on employee behaviors and organizational performance, Fashion and Textiles, 7, 1, (2020); Wang P., Walumbwa F. O., Family‐ friendly programs, organizational commitment, and work withdrawal: the moderating role of transformational leadership, Pers Psychol, 60, 2, pp. 397-427, (2007); Park H. Y., Christie R. L., Sype G. E., Organizational Commitment and Turnover Intention in Union and Non-Union Firms, Sage Open, 4, 1, (2014); Dubey P., Pathak A. K., Sahu K. K., Analysing workplace spirituality as a mediator in the link between job satisfaction and organisational citizenship behaviour, Management Matters, 19, 2, pp. 109-128, (2022); Soelton S., Vizano N., Parmariza N. A., Abadi Y., Zulfriadi, Recognizing the Role of Job Satisfaction in Predicting the Relationship Between Political Organization, Organizational Climate, and Organizational Culture on Organizational Citizenship Behaviour on Liquor Distributor Companies in Indonesia, European Journal of Business and Management, (2020); PURWANTO A., Purba J. T., Bernarto I., Sijabat R., Effect of Transformational Leadership, Job Satisfaction, and Organizational Commitments on Organizational Citizenship Behavior, Inovbiz: Jurnal Inovasi Bisnis, 9, 1, (2021); Adam I. S., Buana H., Effect Job Satisfaction, Workload And Organizational Commitment To Withdrawal Behavior In Non Government Employees In State Employees In Television And Radio Parliament, Journal of Economics, Finance And Management Studies, (2022); Massoudi A. H., Jameel A. S., Ahmad A. R., Stimulating Organizational Citizenship Behavior by Applying Organizational Commitment and Satisfaction, International Journal of social Sciences and Economic Review, pp. 20-27, (2020); de las Heras-Rosas C., Herrera J., Rodriguez-Fernandez M., Organisational commitment in healthcare systems: A bibliometric analysis, International Journal of Environmental Research and Public Health, 18, 5, (2021); Fidyah D. N., Setiawati T., Influence of Organizational Culture and Employee Engagement on Employee Performance: Job Satisfaction as Intervening Variable, Integrative Business & Economics, 9, 4, (2019); Dirgahayu P. P., The Influence of Organizational Commitment, Quality of Work Life (QWL) on Organizational Citizenship Behavior (OCB) and Employees Performance, Journal of Advanced Research in Dynamical and Control Systems, 12, pp. 812-824, (2020); Asgari A., Mezginejad S., Taherpour F., The role of leadership styles in organizational citizenship behavior through the mediation of perceived organizational support and job satisfaction, Innovar, 30, 75, (2020); Bouranta N., Chitiris L., Paravantis J., The relationship between internal and external service quality, International Journal of Contemporary Hospitality Management, 21, 3, pp. 275-293, (2009); Taherdoost H., What Is the Best Response Scale for Survey and Questionnaire Design; Review of Different Lengths of Rating Scale / Attitude Scale / Likert Scale, International Journal of Academic Research in Management (IJARM), 8, 1, pp. 1-10, (2019); Bhardwaj P., Types of sampling in research, Journal of the Practice of Cardiovascular Sciences, 5, 3, (2019); Sarstedt M., Ringle C. M., Hair J. F., Partial Least Squares Structural Equation Modeling, Handbook of Market Research, pp. 587-632, (2022); Ketchen D. J., A Primer on Partial Least Squares Structural Equation Modeling, Long Range Plann, 46, 1–2, pp. 184-185, (2013); Cheela V. R. S., Ranjan V. P., Goel S., John M., Dubey B., Pathways to sustainable waste management in Indian Smart Cities, Journal of Urban Management, 10, 4, (2021)",null,null,"World Scientific and Engineering Academy and Society",{"$nulls":5},1.9918755E7,null,null,null,"English","WSEAS Trans. Comput. Res.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85166183946"]
["Ho J.-Y.; Ju G.; Hong S.; An J.; Lee C.C.","Ho, Jae-Yun (56999691800); Ju, Gyeong (58677428600); Hong, Seoeui (58677428700); An, Jaeyoung (58555214100); Lee, Choong C. (7410158434)","56999691800; 58677428600; 58677428700; 58555214100; 7410158434","Factors influencing customer satisfaction with AR shopping assistant applications in e-commerce: an empirical analysis utilizing text-mining techniques",2023.0,"Aslib Journal of Information Management",{"$nulls":6},0.0,"10.1108/AJIM-03-2023-0089","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85175526969&doi=10.1108%2fAJIM-03-2023-0089&partnerID=40&md5=f546d1c570c3a72689716e57e61b7078","Creative Technology Management, Underwood International College, Yonsei University, Seoul, South Korea; Graduate School of Infromation, Yonsei University, Seoul, South Korea; Graduate Program in Technology and Business Administration, Yonsei University, Seoul, South Korea","Ho J.-Y., Creative Technology Management, Underwood International College, Yonsei University, Seoul, South Korea; Ju G., Graduate School of Infromation, Yonsei University, Seoul, South Korea; Hong S., Graduate Program in Technology and Business Administration, Yonsei University, Seoul, South Korea; An J., Graduate School of Infromation, Yonsei University, Seoul, South Korea; Lee C.C., Graduate School of Infromation, Yonsei University, Seoul, South Korea","Purpose: This study investigates the key factors that influence customer satisfaction when interacting with augmented reality shopping assistance applications (ARSAPs). ARSAPs grant consumers the capability to experience products in a virtually simulated user environment before product acquisition. With the development of mobile e-commerce due to breakthroughs in smartphone and augmented reality (AR) technologies, there is an increasing potential for these emergent AR mobile services, yet there is a need for further improvement. Design/methodology/approach: This study initially explored the key satisfaction factors for ARSAPs by utilizing topic modeling of a collection of actual user reviews. These factors are subsequently revisited and complemented by existing literature, and finally verified through logistic regression analysis supported by sentiment analysis. Findings: This study identified the key factors that influence customer satisfaction with ARSAPs, including visuality, sense of reality, credibility, format, completeness, understandability, relevance, flexibility, response time, reliability, availability, ease of use and privacy. In particular, two additional factors (i.e. visuality and sense of reality) were newly identified as important in the context of AR, despite their previous omissions in existing literature. Originality/value: This study is the first to investigate the key factors that influence customer satisfaction with ARSAPs from users' perspectives, utilizing topic modeling of a large amount of real-world data on actual user feedback. By identifying new factors (i.e. visuality and sense of reality) that were not identified in previous literature, this study provides important academic implications for a broader understanding of AR and related technologies that are essential elements of the metaverse. This study also provides valuable insights for developers and companies in the e-commerce industry on how to optimize AR applications and develop more targeted and effective marketing strategies in this field. © 2023, Emerald Publishing Limited.","Augmented reality; Customer satisfaction; E-commerce; Logistic regression; M-commerce; Text mining",{"$nulls":5},"Yonsei University; Ministry of Education, MOE; National Research Foundation of Korea, NRF, (NRF-2021S1A5A2A01065452)","This study was supported by a Yonsei University Research Grant (2021) and the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2021S1A5A2A01065452).","Alves C., Luis Reis J., The intention to use E-commerce using augmented reality-the case of IKEA place, International Conference on Information Technology and Systems, 1137, pp. 114-123, (2020); Anand K., Arya V., Suresh S., Sharma A., Quality dimensions of augmented reality-based mobile apps for smart-tourism and its impact on customer satisfaction and reuse intention, Tourism Planning and Development, 20, 2, pp. 236-259, (2022); 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An interactivity and vividness perspective, Journal of Interactive Marketing, 39, 1, pp. 89-103, (2017); Yoon D.J., An J.H., Kim G.D., A guideline for 3D object's shadow representation: based on categories of AR application services, Journal of Digital Contents Society, 21, 7, pp. 1211-1222, (2020)","C.C. Lee; Graduate School of Infromation, Yonsei University, Seoul, South Korea; email: cclee@yonsei.ac.kr",null,"Emerald Publishing",{"$nulls":5},2.0503806E7,null,null,null,"English","Aslib J. Inf. Manage.","Article","Article in press",null,"Scopus","2-s2.0-85175526969"]
["Sharma A.; Bhatt S.; Kapri S.S.; Anuj","Sharma, Ajay (57752575600); Bhatt, Sumit (58672876500); Kapri, Shyam Sundar (58673035300); Anuj (57747646800)","57752575600; 58672876500; 58673035300; 57747646800","An examination of adoption of cash on delivery payment method among e-shoppers in India: role of perceived security, risk, privacy and trust",2023.0,"International Journal of Electronic Business",18.0,4.0,null,373.0,391.0,18.0,0.0,"10.1504/IJEB.2023.134118","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85175330353&doi=10.1504%2fIJEB.2023.134118&partnerID=40&md5=479209e9be65bdb8904452cdc5a4f751","Graphic Era Hill University, Uttarakhand, Dehradun, 248002, India","Sharma A., Graphic Era Hill University, Uttarakhand, Dehradun, 248002, India; Bhatt S., Graphic Era Hill University, Uttarakhand, Dehradun, 248002, India; Kapri S.S., Graphic Era Hill University, Uttarakhand, Dehradun, 248002, India; Anuj, Graphic Era Hill University, Uttarakhand, Dehradun, 248002, India","Online marketing is a rising mode of selling products all over the world. E-shoppers use various modes of payment. This study explores and examines the factors which influence e-commerce users to adopt the cash on delivery (COD) mode of payment while shopping online. This is an empirical study done using data gathered from 387 Indian e-shoppers. This study reveals that the adoption of COD results from a sense of perceived security. Further, in online shopping perceived trust in vendors and payment systems, privacy and perceived safety from financial risk play a major role, as their presence leads to perceived security. This study is useful for marketers to understand the payment behaviour of e-shoppers in India and in the development of strategies, policies, and technologies to make a more secure e-shopping platform. Copyright © 2023 Inderscience Enterprises Ltd.","cash on delivery; COD; financial risk; India; online shopping; privacy; security; trust","E-learning; Online systems; Cash-on-delivery; E-shoppers; Financial risks; India; Online shopping; Perceived securities; Privacy; Security; Trust; Electronic commerce",{"$nulls":6},"Al-dweeri R.M., Obeidat Z.M., Al-dwiry M.A., Alshurideh M.T., Alhorani A.M., The impact of e-service quality and e-loyalty on online shopping: moderating effect of e-satisfaction and e-trust, International Journal of Marketing Studies, (2017); Anjum S., Chai J., Drivers of cash-on-delivery method of payment in e-commerce shopping: evidence from Pakistan, SAGE Open, 10, 3, (2020); Arshad A., Zafar M., Fatima I., Khan S.K., The impact of perceived risk on online buying behavior, International Journal of New Technology and Research, 1, 8, pp. 13-18, (2015); Ashoer M., The impact of perceived risk on consumer purchase intention in Indonesia; a social commerce study, Conference: Proceeding of the International Conference on Accounting, Management, Economics and Social Sciences (ICAMESS), (2016); Athique A., A great leap of faith: the cashless agenda in Digital India, New Media and Society, 21, 8, pp. 1697-171, (2019); Barkhordari M., Nourollah Z., Mashayekhi H., Mashayekhi Y., Ahangar M.S., Factors influencing adoption of e-payment systems: an empirical study on Iranian customers, Information Systems and E-Business Management, (2017); Bentler P.M., Yuan K.H., Structural equation modeling with small samples: test statistics, Multivariate Behavioral Research, 34, 2, pp. 181-197, (1999); Chanana N., Goele S., Future of e-commerce in India, International Journal of Computing and Business Research, 8, (2012); Chapell A., Eye on privacy, Target Marketing, 28, 10, (2005); Chellappa R.K., Pavlou P.A., Perceived information security, financial liability and consumer trust in electronic commerce transactions, Logistics Information Management, 15, 5, pp. 358-368, (2002); Chiejina C., Olamide S.E., Investigating the significance of the “pay on delivery” option in the emerging prosperity of the Nigerian e-commerce sector, Journal of Marketing and Management, 5, 1, pp. 120-135, (2014); Chin W.W., Newsted P.R., Structural equation modelling analysis with small samples using partial least squares, Statistical Strategies for Small Sample Research, pp. 307-341, (1999); Davis F.D., Technology Acceptance Model for Empirically Testing New End-user Information Systems Theory and Results, (1986); Durmus B., Ulusu Y., Akgun S., The effect of perceived risk on online shopping through trust and WOM, International Journal of Management and Applied Science, 3, 9, pp. 103-108, (2017); Eid M.I., Determinants of e-commerce customer satisfaction, trust, and loyalty in Saudi Arabia, Journal of Electronic Commerce Research, 12, 1, pp. 78-93, (2011); Fornell C., Larcker D.F., Structural equation models with unobservable variables and measurement error: algebra and statistics, Journal of Marketing Research, 18, 1, pp. 39-50, (1981); Gefen D., Karahanna E., Straub D., Trust and TAM in online shopping: an integrated model, MIS Quarterly, 27, pp. 51-90, (2003); Gurung A., Raja M.K., Online privacy and security concerns of consumers, Information and Computer Security, 24, 4, pp. 348-371, (2016); Hair J.F., Sarstedt M., Hopkins L.G., Kuppelwieser V., Partial least squares structural equation modelling (PLS-SEM): an emerging tool in business research, European Business Review, 26, 2, pp. 106-121, (2014); Hair J., Black W., Babin B., Anderson R., Multivariate Data Analysis, (2010); Hair J.F., Black W.C., Babin B.J., Anderson R.E., Tatham R.L., Multivariate Data Analysis, (2006); Halaweh M., Intention to adopt the cash on delivery (COD) payment model for e-commerce transactions: an empirical study, 16th IFIP International Conference on Computer Information Systems and Industrial Management (CISIM), pp. 628-637, (2017); Halaweh M., Cash on delivery (COD) as an alternative payment method for e-commerce transactions: analysis and implications, International Journal of Socio Technology and Knowledge Development, 10, 4, pp. 1-12, (2018); Haque U.N., Mazumder R., A study on the relationship between customer loyalty and customer trust in online shopping, International Journal of Online Marketing, 10, 2, pp. 1-16, (2012); Hong W., Thong J.Y.L., Internet privacy concerns: an integrated conceptualization and four empirical studies, MIS Quarterly, 37, 1, pp. 275-298, (2013); Hooper D., Coughlan J., Mullen M.R., Evaluating model fit: a synthesis of the structural equation modelling literature, 7th European Conference on Research Methodology for Business and Management Studies, (2008); Hu P.J., Chau P.Y.K., Sheng O.R.L., Tam K. 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Portland International Conference, pp. 38-45, (2001); Liao C., Liu C.C., Chen K., Examining the impact of privacy, trust and risk perceptions beyond monetary transactions: an integrated model, Electronic Commerce Research and Applications, 10, 6, pp. 702-715, (2011); Lim B., Lee H., Kurnia S., Exploring the reasons for a failure of electronic payment systems: a case study of an Australian company, Journal of Research and Practice in Information Technology, 39, 4, pp. 231-244, (2007); Ling K.C., Chai L.T., Piew T.H., The effects of shopping orientations, online trust and prior online purchase experience toward customers’ online purchase intention, International Business Research, (2010); McKnight D., Choudhury V., Kacmar C., Developing and validating trust measures for e-commerce: an integrative typology, Information Systems Research, 13, 3, pp. 334-359, (2002); Nguyen H.V., Tran H., Van Huy L., Nguyen N., Do M., Nguyen N., Online book shopping in Vietnam: the impact of the COVID-19 pandemic situation, Publishing Research Quarterly, 36, (2020); Oney E., Guven G.O., Rizvi W.H., The determinants of electronic payment systems usage from consumers’ perspective, Economic Research – Ekonomska Istraživanja, 30, 1, pp. 394-415, (2017); Palvia P., Editorial preface the world IT project: a program on international research and call for participation, Journal of Global Information Technology Management, 16, 2, pp. 1-5, (2013); Paul L., John I., Pierre C., Why do people use information technology? 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Bhatt; Graphic Era Hill University, Dehradun, Uttarakhand, 248002, India; email: 2017sumitb@gmail.com",null,"Inderscience Publishers",{"$nulls":5},1.4706067E7,null,null,null,"English","Int. J. Electron. Bus.","Article","Final",null,"Scopus","2-s2.0-85175330353"]
["Zhang X.Y.; Lee S.Y.","Zhang, Xin Yue (58558313100); Lee, Sang Yoon (55716420200)","58558313100; 55716420200","A research on users' behavioral intention to adopt Internet of Things (IoT) technology in the logistics industry: the case of Cainiao Logistics Network",2023.0,"Journal of International Logistics and Trade",21.0,1.0,null,41.0,60.0,19.0,1.0,"10.1108/JILT-11-2022-0067","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85169453564&doi=10.1108%2fJILT-11-2022-0067&partnerID=40&md5=bb32061db1d445720c19d8767fcf4c6e","Graduate School of Logistics, Inha University, Incheon, South Korea","Zhang X.Y., Graduate School of Logistics, Inha University, Incheon, South Korea; Lee S.Y., Graduate School of Logistics, Inha University, Incheon, South Korea","Purpose - In the current dynamic business environment, Internet of Things (IoT) is employed by a number of companies in the logistics industry to achieve intelligent sorting, network optimization, real-time tracking and simplifying last-mile service. Although logistics entities are trying to introduce IoT into their business areas, users' perception of this new technology is still limited. This paper aims to develop a research model for the factors influencing the user adoption of IoT technology in the logistics industry. Design/methodology/approach - In this study, based on the major theories on the application of new technologies such as technology acceptance model (TAM), technology-organization-environment (TOE) and innovation diffusion theory (IDT), a new research model was established to identify factors affecting customers' behavioral intention (BI) to adopt IoT technology provided by logistics companies. In addition, the authors surveyed unspecified customers of Cainiao Logistics Network, which is in charge of the logistics operation of Alibaba Group, China's largest e-commerce company, and tested the causality between the latent variables presented in the model using the structural equation model (SEM). Findings - This empirical study shows that the support system of a logistics company and users' innovative propensity significantly affect perceived ease of use (PEOU) and BI for logistics services to which IoT technology is applied. It also presents that users' perceived security and enjoyment significantly affect perceived usefulness (PU) and BI. In addition, it was possible to confirm that the causal structure between variables suggested by TAM that PEOU has a significant effect on PU and BI, and PU has a substantial effect on BI. Practical implications - Logistics companies should expand and upgrade technical support systems so that customers can flexibly accept logistics services with IoT technology and make efforts to alleviate customers' concerns about personal information leakage. In addition, it is necessary to find customers with an inclusive attitude toward using new technologies, to induce them to become leading users of logistics devices with IoT technology and to find various ways to amplify their enjoyment. Through a strategic approach to these technical and individual factors, it will be possible to boost customers' intention to use IoT logistics services. Originality/value - As far as the authors know, this paper is the first study to set significant factors that affect users' BI to use IoT technology-applied logistics services provided by logistics companies and empirically analyze the causal relationships between proposed latent variables. © Xin Yue Zhang and Sang Yoon Lee.","Cainiao Logistics Network; Internet of Things (IoT); TAM; User adoption behavioral intention",{"$nulls":5},"Inha University, Inha","© Xin Yue Zhang and Sang Yoon Lee. Published in Journal of International Logistics and Trade. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons. org/licences/by/4.0/legalcode This work was supported by INHA University research grant.","Ajzen I., From Intentions to Actions: A Theory of Planned Behavior, Action Control, pp. 11-39, (1985); Ajzen I., The theory of planned behavior, Organizational Behavior and Human Decision Processes, 50, 2, pp. 179-211, (1991); Alalwan A.A., Dwivedi Y.K., Rana N.P., Factors influencing adoption of mobile banking by Jordanian bank customers: extending UTAUT2 with trust, International Journal of Information Management, 37, 3, pp. 99-110, (2017); Al-Gahtani S.S., Empirical investigation of e-learning acceptance and assimilation: a structural equation model, Applied Computing and Informatics, 12, 1, pp. 27-50, (2016); Al-Khaldi M.A., Wallace R.O., The influence of attitudes on personal computer utilization among knowledge workers: the case of Saudi Arabia, Information and Management, 36, 4, pp. 185-204, (1999); Al-Qaseemi S.A., Almulhim H.A., Almulhim M.F., Chaudhry S.R., IoT architecture challenges and issues: lack of standardization, FTC 2016 - Proceedings of Future Technologies Conference, pp. 731-738, (2017); Al-Sharafi M. 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Al-Sharafi M.A., Arshah R.A., Abo-Shanab E.A., Elayah N., The effect of security and privacy perceptions on customers' trust to accept internet banking services: an extension of TAM, Journal of Engineering and Applied Sciences, 11, 3, pp. 545-552, (2016); Das C., A Study on Validity of Modified Technology Acceptance Model of Mobile, (2011); Gao L., Bai X., A unified perspective on the factors influencing consumer acceptance of internet of things technology, Asia Pacific Journal of Marketing and Logistics, 26, 2, pp. 211-231, (2014); Ginters E., Martin-Gutierrez J., Low cost augmented reality and RFID application for logistics items visualization, Procedia Computer Science, 26, pp. 3-13, (2013); Liu G., Logistics service innovation based on demand, International Conference on Mechatronics and Intelligent Robotics, pp. 220-224, (2018); Silva-Trevino J.G., Macias-Hernandez B.A., Tello-Leal E., Delgado-Rivas J.G., The relationship between service quality, customer satisfaction, and customer loyalty: a case study of a trading company in Mexico, CienciaUAT, 152, 2021, pp. 85-101, (2021); Yan J., Xin S., Liu Q., Xu W., Yang L., Fan L., Wang Q., Intelligent supply chain integration and management based on cloud of things, International Journal of Distributed Sensor Networks, 10, 3, (2014); Yang J., Research on Acquisition Model of Enterprise IoT RFID Technology, (2011)","S.Y. Lee; Graduate School of Logistics, Inha University, Incheon, South Korea; email: sylee@inha.ac.kr",null,"Jungseok Research Institute of International Logistics and Trade",{"$nulls":5},1.7382122E7,null,null,null,"English","J. Intl. Logist. Trade","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85169453564"]
["Ma H.-L.; Sun Y.; Mo D.Y.; Wang Y.","Ma, Hoi-Lam (57074895600); Sun, Yige (57222326940); Mo, Daniel Y. (14822088000); Wang, Yue (35175219400)","57074895600; 57222326940; 14822088000; 35175219400","Impact of passenger unused baggage capacity on air cargo delivery",2023.0,"Annals of Operations Research",{"$nulls":6},0.0,"10.1007/s10479-023-05248-y","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85149293994&doi=10.1007%2fs10479-023-05248-y&partnerID=40&md5=85d777fb4c3bdb5639ac352975ac9dcf","Department of Supply Chain and Information Management, The Hang Seng University of Hong Kong, Hong Kong; Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong","Ma H.-L., Department of Supply Chain and Information Management, The Hang Seng University of Hong Kong, Hong Kong; Sun Y., Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong; Mo D.Y., Department of Supply Chain and Information Management, The Hang Seng University of Hong Kong, Hong Kong; Wang Y., Department of Supply Chain and Information Management, The Hang Seng University of Hong Kong, Hong Kong","Air cargo demand has strong growth owing to the international trade, especially the popularity of e-commerce. Currently, many giant carriers have their own aircraft, operating their own air cargo flights to efficiently facilitate their operations, shorten the delivery lead time, and expand their service network level. Meanwhile, they also deliver by using passenger flights operated by passenger airlines, e.g., Cathay Pacific, British Airway. In practice, passenger airlines usually reserve certain capacity on each passenger flight for the storage of passengers’ baggage. However, in reality, this capacity usually may not be fully utilized and result in unused space. Thus, the objective of this paper is to analyze how much efficiency can be obtained by using the unused baggage capacity for cargo delivery. To tackle this air cargo demands-to-flights assignment problem, a new hybrid genetic algorithm is proposed. The optimization algorithm makes use of the genetic algorithm for optimization of the demands-to-flights assignment problem, while a labelling algorithm to determine the optimal path for indirect flight. Numerical experiments are conducted based on the real flight data of an international airline in Hong Kong. The results indicate that the delivery efficiency can be enhanced. © 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.","Air cargo airlines; Baggage capacity; Demand-to-flight assignment; Optimization; Passenger airlines",{"$nulls":5},"Research Grants Council of the Hong Kong Special Administration Region, China, (UGC/FDS14/E03/20)","The work described in this paper was supported by a grant from the Research Grants Council of the Hong Kong Special Administration Region, China (UGC/FDS14/E03/20). ","Archetti C., Peirano L., Speranza M.G., Optimization in multimodal freight transportation problems: A Survey, European Journal of Operational Research, 299, pp. 1-20, (2021); Azadian F., Murat A.E., Chinnam R.B., Dynamic routing of time-sensitive air cargo using real-time information, Transportation Research Part E: Logistics and Transportation Review, 48, 1, pp. 355-372, (2012); Bilegan I.C., Crainic T.G., Wang Y., Scheduled service network design with revenue management considerations and an intermodal barge transportation illustration, European Journal of Operational Research, 300, 1, pp. 164-177, (2022); World Air Cargo Forecast, pp. 2020-2039, (2020); Brandt F., Nickel S., The air cargo load planning problem-a consolidated problem definition and literature review on related problems, European Journal of Operational Research, 275, 2, pp. 399-410, (2019); Chan H.K., Chung S.H., Optimisation approaches for distributed scheduling problems, International Journal of Production Research, 51, 9, pp. 2571-2577, (2013); Chen S.C., Kuo S.Y., Chang K.W., Wang Y.T., Improving the forecasting accuracy of air passenger and air cargo demand: The application of back-propagation neural networks, Transportation Planning and Technology, 35, 3, pp. 373-392, (2012); Chung S.H., Applications of smart technologies in logistics and transport: A review, Transportation Research Part E: Logistics and Transportation Review, 153, (2021); Chung S.H., Ma H.L., Chan H.K., Maximizing recyclability and reuse of tertiary packaging in production and distribution network, Resources, Conservation and Recycling, 128, pp. 259-266, (2018); Chung S.H., Ma H.L., Hansen M., Choi T.M., Data science and analytics in aviation, Transportation Research Part E: Logistics and Transportation Review, 134, (2020); Delgado F., Mora J., A matheuristic approach to the air-cargo recovery problem under demand disruption, Journal of Air Transport Management, 90, (2021); Delgado F., Sirhan C., Katscher M., Larrain H., Recovering from demand disruptions on an air cargo network, Journal of Air Transport Management, 85, (2020); Derigs U., Friederichs S., Air cargo scheduling: Integrated models and solution procedures, Or Spectrum, 35, 2, pp. 325-362, (2013); Derigs U., Friederichs S., Schafer S., A new approach for air cargo network planning, Transportation Science, 43, 3, pp. 370-380, (2009); Feng B., Li Y., Shen Z.J.M., Air cargo operations: Literature review and comparison with practices, Transportation Research Part C: Emerging Technologies, 56, pp. 263-280, (2015); Khan W.A., Chung S.H., Awan M.U., Wen X., Machine learning facilitated business intelligence (Part I): Neural networks learning algorithms and applications, Industrial Management & Data Systems, 120, 1, pp. 164-195, (2019); Khan W.A., Chung S.H., Awan M.U., Wen X., Machine learning facilitated business intelligence (Part II): Neural networks optimization techniques and applications, Industrial Management & Data Systems, 120, pp. 164-195, (2020); Lange A., Does cargo matter? The impact of air cargo operations on departure on-time performance for combination carriers, Transportation Research Part A: Policy and Practice, 119, pp. 214-223, (2019); Larsen O., Mikkelsen G., An interactive system for the loading of cargo aircraft, European Journal of Operational Research, 4, 6, pp. 367-373, (1980); Lee C.K., Zhang S., Ng K.K., Design of an integration model for air cargo transportation network design and flight route selection, Sustainability, 11, 19, (2019); Li D., Huang H.C., Chew E.P., Morton A.D., Simultaneous fleet assignment and cargo routing using benders decomposition, In: Container Terminals and Cargo Systems, pp. 315-331, (2007); Lin C.C., Chen Y.C., The integration of Taiwanese and Chinese air networks for direct air cargo services, Transportation Research Part A: Policy and Practice, 37, 7, pp. 629-647, (2003); Morrell P.S., Klein T., Moving boxes by air: The economics of international air cargo, (2018); Shaban I.A., Wang Z.X., Chan F.T.S., Chung S.H., Eltoukhy A.E.E., Qu T., Price setting for extra-baggage service for a combination carrier using the newsvendor setup, Journal of Air Transport Management, 78, pp. 1-14, (2019); Tang C.H., Yan S., Chen Y.H., An integrated model and solution algorithms for passenger, cargo, and combi flight scheduling, Transportation Research Part E: Logistics and Transportation Review, 44, 6, pp. 1004-1024, (2008); Yan S., Chen S.C., Chen C.H., Air cargo fleet routing and timetable setting with multiple on-time demands, Transportation Research Part E: Logistics and Transportation Review, 42, 5, pp. 409-430, (2006); Zhang A., Zhang Y., A model of air cargo liberalization: passenger vs. all-cargo carriers, Transportation Research Part E: Logistics and Transportation Review, 38, 3-4, pp. 175-191, (2002)","Y. Sun; Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong; email: yige-jessica.sun@connect.polyu.hk",null,"Springer",{"$nulls":5},2545330.0,null,null,null,"English","Ann. Oper. Res.","Article","Article in press",null,"Scopus","2-s2.0-85149293994"]
["Teng Z.; He Y.; Wu R.","Teng, Zhuoqi (57206199097); He, Yugang (57204808857); Wu, Renhong (57211134547)","57206199097; 57204808857; 57211134547","E-Commerce: Does Sustainable Logistics Development Matter?",2023.0,"Sustainability (Switzerland)",15.0,1.0,579.0,null,null,null,3.0,"10.3390/su15010579","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85146033676&doi=10.3390%2fsu15010579&partnerID=40&md5=f0d5aa7cf2e39fb752afbc23db07f332","College of Business Administration, Henan Finance University, Zhengzhou, 451464, China; College of Liberal Arts, Sejong University, Seoul, 05006, South Korea; School of Management, Kyung Hee University, Seoul, 02447, South Korea","Teng Z., College of Business Administration, Henan Finance University, Zhengzhou, 451464, China; He Y., College of Liberal Arts, Sejong University, Seoul, 05006, South Korea; Wu R., School of Management, Kyung Hee University, Seoul, 02447, South Korea","With the rise of the information industry in recent years, logistics and e-commerce have grown significantly. Logistics are regarded as an essential assurance for the execution of e-commerce transactions. Therefore, this article examines the effect of sustainable logistics development on China’s e-commerce by assessing province data from 2005 to 2020. Using the province and year fixed-effects model for empirical research, the following three empirical conclusions are reached: (1) the development of logistics has a favorable effect on e-commerce; (2) the dynamic link between logistics development and e-commerce is moderated by the speed of logistics development in a U-shaped manner; (3) the aforementioned two conclusions are dissimilar in the eastern, central, and western regions. On the basis of these three findings, several matching recommendations are made. This can serve as a point of reference for the sustainable growth of logistics and e-commerce in the near future. This paper can also contribute to the current literature. © 2022 by the authors.","e-commerce; moderation effect; province and year fix-effects model; sustainable logistics development; U-shaped manner","China; electronic commerce; industrial development; logistics; sustainability; sustainable development",{"$nulls":4},"Research Start-up Foundation of Henan Finance University, (2021BS009); Universities’ Humanities and Social Science General Research project of Henan Province, (2023-ZZJH-018); National Office for Philosophy and Social Sciences, NPOPSS, (22BJY202)","This research is supported by Universities’ Humanities and Social Science General Research project of Henan Province (2023-ZZJH-018), Research Start-up Foundation of Henan Finance University (2021BS009), and General project of the National Social Science Foundation in 2022 (22BJY202).","Wakabayashi K., Suzuki K., Watanabe A., Karasawa Y., Analysis and Suggestion of an E-Commerce Logistics Solution: Effects of Introduction of Cloud Computing Based Warehouse Management System in Japan, Logistics Operations, Supply Chain Management and Sustainability, pp. 567-573, (2014); Hidayatno A., Destyanto A.R., Fadhil M., Model Conceptualization on E-Commerce Growth Impact to Emissions Generated from Urban Logistics Transportation: A Case Study of Jakarta, Energy Procedia, 156, pp. 144-148, (2019); Cho J.J.-K., Ozment J., Sink H., Logistics Capability, Logistics Outsourcing and Firm Performance in an e-Commerce Market, Int. 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Cities Soc, 82, (2022); Li L., Lee C.P., Ding X., Qin Y., Wijerathna-Yapa A., Broda M., Otegui M.S., Millar A.H., Defects in Autophagy Lead to Selective in Vivo Changes in Turnover of Cytosolic and Organelle Proteins in Arabidopsis, Plant Cell, 34, pp. 3936-3960, (2022); Wang K., Wang X., Cheng S., Cheng L., Wang R., National Emissions Inventory and Future Trends in Greenhouse Gases and Other Air Pollutants from Civil Airports in China, Environ. Sci. Pollut. Res, 29, pp. 81703-81712, (2022)","Y. He; College of Liberal Arts, Sejong University, Seoul, 05006, South Korea; email: 1293647581@sejong.ac.kr",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85146033676"]
["Bruni M.E.; Khodaparasti S.; Perboli G.","Bruni, Maria Elena (14040099200); Khodaparasti, Sara (57194522752); Perboli, Guido (16176293900)","14040099200; 57194522752; 16176293900","Energy Efficient UAV-Based Last-Mile Delivery: A Tactical-Operational Model With Shared Depots and Non-Linear Energy Consumption",2023.0,"IEEE Access",11.0,null,null,18560.0,18570.0,10.0,5.0,"10.1109/ACCESS.2023.3247501","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85149368677&doi=10.1109%2fACCESS.2023.3247501&partnerID=40&md5=9a1b2c0fc37bc09389783e499994f4a3","University of Calabria, Department of Mechanical, Energy and Management Engineering, Rende, 87036, Italy; Digep - Politecnico di Torino, Turin, 10129, Italy; Cirrelt, Montreal, H3T 1J4, Canada","Bruni M.E., University of Calabria, Department of Mechanical, Energy and Management Engineering, Rende, 87036, Italy; Khodaparasti S., Digep - Politecnico di Torino, Turin, 10129, Italy; Perboli G., Digep - Politecnico di Torino, Turin, 10129, Italy, Cirrelt, Montreal, H3T 1J4, Canada","This paper studies the drone-aided last-mile delivery problem with shared depot resources. Our research motivation comes from E-commerce logistics, where big companies such as Amazon, are already filing up patents for the development of drone-friendly fulfillment centers towers that could serve as both charging hubs and convenient pit stops for delivery drones to pick up and drop off packages efficiently. We mainly focus on the tactical decisions about the selection of shared fulfillment centers used as the drone launch and retrieve stations and the fleet size plans. The operational drone route decisions are also incorporated into a unified framework to account for the mutual impact between tactical and operational plans. Moreover, we consider explicitly the non-linear and load-dependent nature of the energy consumption function for drone batteries. The problem is formulated as a mixed integer program with linear constraints, developed in the realm of layered networks, where the non-linear nature of energy consumption and its load dependency are incorporated and efficiently handled without the need of approximating non-linear terms. The proposed model is tested on an extensive set of instances with up to 75 customers, showing its computational efficiency. Insights about the route costs and spatial configuration of depots are also discussed.  © 2013 IEEE.","drone delivery; E-commerce; Last-mile delivery; multi-depot routing problem; non-linear energy consumption; UAV","Computational efficiency; Drones; Electronic commerce; Energy efficiency; Integer programming; Network layers; Secondary batteries; Battery; Drone delivery; Energy-consumption; Last mile; Last-mile delivery; Linear energy; Load modeling; Multi depots; Multi-depot routing problem; Non linear; Non-linear energy consumption; Payload; Routing problems; Routings; Energy utilization",{"$nulls":4},"Politecnico di Torino, POLITO; China Agricultural Research System, CARS; interdepartmental Center for Automotive Research and Sustainable mobility","ACKNOWLEDGMENT While working on this article, Guido Perboli was the Head of the Urban Mobility and Logistics Systems (UMLS) initiative of the interdepartmental Center for Automotive Research and Sustainable mobility (CARS) at the Politecnico di Torino, Turin, Italy, and the representative in the Logistic Table in the Regional Council of Piedmont for the Politecnico di Torino.","Perboli G., Rosano M., Parcel delivery in urban areas: Opportunities and threats for the mix of traditional and green business models, Transp. Res. C, Emerg. Technol., 99, pp. 19-36, (2019); Perboli G., Brotcorne L., Bruni M.E., Rosano M., A new model for last-mile delivery and satellite depots management: The impact of the on-demand economy, Transp. Res. E, Logistics Transp. Rev., 145, pp. 102-184, (2021); Crainic T.G., Perboli G., Ricciardi N., City logistics, Network Design With Applications in Transportation and Logistics, pp. 507-537, (2021); Perboli G., Rosano M., Saint-Guillain M., Rizzo P., Simulation- optimisation framework for city logistics: An application on multimodal last-mile delivery, IET Intell. Transp. Syst., 12, 4, pp. 262-269, (2018); Wei W., Wang J., Fang Z., Chen J., Ren Y., Dong Y., 3U: Joint design of UAV-USV-UUV networks for cooperative target hunting, IEEE Trans. Veh. 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Transp., 2019, pp. 1-13, (2019); Li X., Li P., Zhao Y., Zhang L., Dong Y., A hybrid large neighborhood search algorithm for solving the multi depotUAVswarm routing problem, IEEE Access, 9, pp. 104115-104126, (2021); Gouveia L., Leitner M., Ruthmair M., Layered graph approaches for combinatorial optimization problems, Comput. Oper. Res., 102, pp. 22-38, (2019)","M.E. Bruni; University of Calabria, Department of Mechanical, Energy and Management Engineering, Rende, 87036, Italy; email: mariaelena.bruni@unical.it",null,"Institute of Electrical and Electronics Engineers Inc.",{"$nulls":5},2.1693536E7,null,null,null,"English","IEEE Access","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85149368677"]
["Liu Z.; Niu Y.; Guo C.; Jia S.","Liu, Zhiqiang (55714784000); Niu, Yanqi (57964549800); Guo, Caiyun (57884861400); Jia, Shitong (57964365500)","55714784000; 57964549800; 57884861400; 57964365500","A Vehicle Routing Optimization Model for Community Group Buying Considering Carbon Emissions and Total Distribution Costs",2023.0,"Energies",16.0,2.0,931.0,null,null,null,2.0,"10.3390/en16020931","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85146425279&doi=10.3390%2fen16020931&partnerID=40&md5=079788211dacaff8e5075b2e1f64545b","School of Management Engineering and Business, Hebei University of Engineering, Handan, 056038, China","Liu Z., School of Management Engineering and Business, Hebei University of Engineering, Handan, 056038, China; Niu Y., School of Management Engineering and Business, Hebei University of Engineering, Handan, 056038, China; Guo C., School of Management Engineering and Business, Hebei University of Engineering, Handan, 056038, China; Jia S., School of Management Engineering and Business, Hebei University of Engineering, Handan, 056038, China","Under the background of the normalization of COVID-19 prevention and control and the rapid development of e-commerce, community group buying has occupied the market by providing low-priced, fast, and green consumer goods, but with it, the logistics and distribution volume of goods has also increased sharply. In order to reduce environmental pollution and the carbon emissions caused by transportation in the community group buying logistics distribution, it is necessary to investigate a suitable method to optimize vehicle distribution routes and reduce carbon emissions. Taking the lowest total costs of logistics and distribution and the smallest carbon emissions, this article introduces soft time window function and carbon emissions parameters, takes the delivery of goods from the community group buying distribution center in Wu’an Town, Hebei Province to customer points in 14 townships as an example, an optimization model for the distribution route of low carbon vehicles for community group buying based on improved genetic algorithm was constructed, AHP-EW fusion technology was used to calculate carbon emissions and cost weights, and compared with the traditional genetic algorithm and ant colony algorithm two typical heuristic algorithms, the feasibility of the proposed model and the advantages of the improved algorithm are verified, and the research results showed that it can reduce the costs and carbon emissions of vehicle distribution, provide decision-making reference for community group buying logistics enterprise distribution, and promote energy conservation and environmental sustainable development. © 2023 by the authors.","carbon emissions; community group buying; genetic algorithm; sustainable development; vehicle routing optimization","Ant colony optimization; Carbon; Decision making; Distribution of goods; Environmental protection; Heuristic algorithms; Routing algorithms; Sustainable development; Vehicle routing; Vehicles; Carbon emissions; Community group; Community group buying; Distribution costs; Distribution route; Group buying; Normalisation; Optimization models; Prevention and controls; Vehicle routing optimization; Genetic algorithms",{"$nulls":6},"Song W., Yuan S., Yang Y., He C., A Study of Community Group Purchasing Vehicle Routing Problems Considering Service Time Windows, Sustainability, 14, (2022); Li L.L., Research on the Development of Community Group Buying Based on the Perspective of New Retail, Mod. 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["Ukenna S.I.; Idoko E.C.; Egharevba M.E.","Ukenna, Stephen Ikechukwu (36705277600); Idoko, Edwin Chukwuemeka (57204919137); Egharevba, Matthew E. (57191664177)","36705277600; 57204919137; 57191664177","Undergraduates' e-shopping inhibitors in a developing market context: stimulus-organism-response approach",2023.0,"International Journal of Electronic Business",18.0,3.0,null,346.0,371.0,25.0,0.0,"10.1504/IJEB.2023.132197","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85166384981&doi=10.1504%2fIJEB.2023.132197&partnerID=40&md5=915223c23ca327948c6c9709e24e4c22","Standpoint Consulting Ltd., FT 215 Temples Lodge, Udoko Housing Estate, Awka, Nigeria; Department of Marketing, University of Nigeria, Enugu Campus, Enugu, Nigeria; Department of Sociology, College of Management and Social Sciences, Covenant University, Ota, Nigeria","Ukenna S.I., Standpoint Consulting Ltd., FT 215 Temples Lodge, Udoko Housing Estate, Awka, Nigeria; Idoko E.C., Department of Marketing, University of Nigeria, Enugu Campus, Enugu, Nigeria; Egharevba M.E., Department of Sociology, College of Management and Social Sciences, Covenant University, Ota, Nigeria","Originally, shopping in most developing economies takes place in designated marketplaces and physical neighbourhood stores. Few decades ago, e-shops, are attractive alternate shopping channels that emerged in the retail ecosystem. E-channel among university undergraduates is quietly becoming fashionable as technology-enabled transactions become ubiquitous in many developing economies. Despite observed fast-expanding Generation Z consumers (born between 1995–2012) that are largely internet-savvy, under-utilisation of e-shops for shopping appears apparent among most university undergraduates. Therefore, this study seeks to unmask those factors that restrain e-shopping behaviour of undergraduates. Self-administered questionnaire was used to collect data from 320 undergraduates who have made online purchase at least once. Judgemental sampling technique was utilised in respondents’ recruitment. Partial least square-structural equation modelling was used in analysis. Findings indicate that explored independent variables – perceived product quality, delivery time, delivery cost, customer relationship/communication, product price, and misinterpretation of customers’ order/s emerged as significant inhibitory factors of online shopping; e-shopping intention also predicts e-shops’ patronage. Underpinned by the stimulus-organism-response (SOR) theory, this study expands frontiers of e-shopping literature by examining unexplored inhibitory factors culminating in e-shop patronage inhibitory model. Practice and theoretical implications of the findings were discussed. Copyright © 2023 Inderscience Enterprises Ltd.","consumer behaviour; e-shop/s; e-shopping; electronic shop/s; electronic shopping; Generation Y; inhibiting factors; Nigeria; undergraduates","Electronic commerce; Public relations; Retail stores; Sales; E-shop/s; E-shoppers; E-shopping; E-shops; Electronic shop/s; Electronic shopping; Generation Y; Inhibiting factors; Nigeria; Undergraduate; Consumer behavior",{"$nulls":6},"Agatz N.A., Fleischmann M., Van Nunen J.A., E-fulfilment and multi-channel distribution: a review, European Journal of Operational Research, 187, 2, pp. 339-356, (2008); Anderson J.C., Gerbing D.W., Structural equation modeling in practice: a review and recommended two-step approach, Psychological Bulletin, 103, 3, pp. 411-423, (1988); Antwi S., Ameyaw M.A., Adamu M.M., What drives online shopping among tertiary students in Ghana: the role of attitude and subjective norm, Journal of Applied Management and Advanced Research, 2, 2, pp. 94-108, (2020); Anubha D.N., Jain M.K., Stockpiling during COVID-19: the solicitation of the stimulus-organism-response model, Vision, pp. 1-15, (2022); Aragoncillo L., Orus C., Impulse buying behaviour: an online-offline comparative and the impact of social media, Spanish Journal of Marketing, 22, 1, pp. 42-62, (2018); Arora A.P., Kishor N., Factors determining purchase intention and behaviour of consumers towards luxury fashion brands in India: empirical evidence, British Journal of Marketing Studies, 7, 4, pp. 34-58, (2019); Babin B.J., Darden W., Griffin M., Work and/or fun: measuring hedonic and utilitarian shopping value, J. 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The impact of retailer type and shopping risk on price dispersion, Journal of Retailing, 94, 2, pp. 136-153, (2018); Ziaullah M., E-loyalty: the influence of product quality and delivery services on e-trust and e-satisfaction in China, International Journal of Advancements in Research & Technology, 3, 10, pp. 20-31, (2014)","E.C. Idoko; Department of Marketing, University of Nigeria, Enugu, Enugu Campus, Nigeria; email: edwin.idoko@unn.edu.ng",null,"Inderscience Publishers",{"$nulls":5},1.4706067E7,null,null,null,"English","Int. J. Electron. Bus.","Article","Final",null,"Scopus","2-s2.0-85166384981"]
["Ma X.; Li W.; Li Y.; Wu J.; Zheng S.","Ma, Xiaoye (57222639891); Li, Weina (57222639771); Li, Yuming (58187694300); Wu, Jun (58606037400); Zheng, Shiyong (57105452800)","57222639891; 57222639771; 58187694300; 58606037400; 57105452800","STUDY ON THE PROMOTING EFFECT OF CROSS-BORDER E-COMMERCE ON REGIONAL ECONOMY – TAKING GUANGXI AS AN EXAMPLE",2023.0,"Journal of Environmental Protection and Ecology",24.0,3.0,null,1087.0,1094.0,7.0,0.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85163148010&partnerID=40&md5=07de2ded46c569f026c976755f593390","Guilin University of Electronic Technology, Guilin, 541 000, China; Tangshan Normal University, Tangshan, 063 000, China; Hezhou University, Hezhou, 054 289, China","Ma X., Guilin University of Electronic Technology, Guilin, 541 000, China; Li W., Tangshan Normal University, Tangshan, 063 000, China; Li Y., Hezhou University, Hezhou, 054 289, China; Wu J., Guilin University of Electronic Technology, Guilin, 541 000, China; Zheng S., Guilin University of Electronic Technology, Guilin, 541 000, China","Based on the analysis of the important role of cross-border e-commerce in boosting the innovative development of regional economy, the article takes Guangxi as an example and analyses its cross-border e-commerce development profile and shortcomings. It was suggested that Guangxi cross-border e-commerce development can do a good job of top-level design, optimise the cross-border e-commerce process, build a cross-border e-commerce platform, develop a new mode of logistics operation, accelerate the training of talents, and continuously improve the product quality, strengthen the application of big data and artificial intelligence technology, and continuously improve the core competitiveness of cross-border e-commerce enterprises. © 2023, Scibulcom Ltd.. All rights reserved.","cross-border e-commerce; ecology; Guangxi; regional economy","China; Guangxi Zhuangzu; artificial intelligence; border region; competitiveness; electronic commerce; information and communication technology; innovation; regional economy; technology adoption",{"$nulls":6},"YUE S. W., Evaluation of the Coordinated Development of Chengdu-Chongqing Ecological Civilization Construction Based on the Gray Correlation-distance Coordinated Coupling Model, J Environ Prot Ecol, 22, (2021); WANG Y., LIANG Z., CHEN H., Influence Mechanism of Technical Innovation Capability on Green Growth, J Environ Prot Ecol, 21, 5, (2020); LIU C., The Myth of Informatization in Rural Areas: the Case of China’s Sichuan Province, Government Information Quarterly, 29, (2012); ZHOU Y. Y., Study on the Relationship between Sewage Treatment and Economic Development, Fresen Environ Bull, 28, (2019); SUN Y. N., SUN W. H., A New Water Purification Process with Comprehensive Application of Electrostatic Adsorption, Magnetization and Photocatalyst, Fresen Environ Bull, 28, (2019); HUANGFU Y. R., LIU L., Rural Construction Method Based on the Concept of Ecological Environment Protection, J Environ Prot Ecol, 22, (2021); TONG L. L., On the Green Supply Chain Decision-making Mechanism and Environment-friendly Sustainable Development of Technology Oriented Enterprises, J Environ Prot Ecol, 22, (2021); YU L., Low Carbon Ecocity: New Approach for Chinese Urbanisation, Habitat Int, 44, (2014); NI C., YANG S. T., Luo Y., ZHOU X., HOU L.P., The Spatial-temporal Difference Analysis of Cultivated Land Use Intensity in Heilongjiang Province based on Circular Economy, Geogr Res, 34, 2, (2015); KORHONEN J., HONKASALO A., JYRI S., Circular Economy: the Concept and Its Limita-tions, Ecol Econ, 143, (2018); GEISSDOERFER M., SAVAGET P., BOCKEN N. M. P., The Circular Economy – a New Sus-tainability Paradigm, J Clean Prod, 143, (2017); KIRCHHERR J., REIKE D., HEKKERT M., Conceptualizing the Circular Economy: an Analysis of 114 Definitions, Resour Conserv Recycl, 127, (2017); GREGSON N., CRANG M., FULLER S., Interrogating the Circular Economy: the Moral Economy of Resource Recovery in the EU, Econ Soc, 44, 2, (2015)","Y. Li; Hezhou University, Hezhou, 054 289, China; email: liyuming8899@outlook.com",null,"Scibulcom Ltd.",{"$nulls":5},1.3115065E7,null,null,null,"English","J. Environ. Prot. Ecol.","Article","Final",null,"Scopus","2-s2.0-85163148010"]
["Titiloye I.; Sarker M.A.A.; Jin X.; Watts B.","Titiloye, Ibukun (57226501414); Sarker, Md Al Adib (57781601900); Jin, Xia (35722440500); Watts, Brian (57847923200)","57226501414; 57781601900; 35722440500; 57847923200","Examining channel choice preferences for grocery shopping during the Covid-19 pandemic",2023.0,"International Journal of Transportation Science and Technology",{"$nulls":6},6.0,"10.1016/j.ijtst.2023.03.006","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85151299418&doi=10.1016%2fj.ijtst.2023.03.006&partnerID=40&md5=657ae6e6e87874255f28adcbff4e4b68","Department of Civil and Environmental Engineering, Florida International University, 10555 W. Flagler Street, EC 3725, Miami, 33174, FL, United States; Department of Civil and Environmental Engineering, Florida International University, 10555 W. Flagler Street, EC 3603, Miami, 33174, FL, United States; Performance & Trends, Forecasting & Trends Office, Florida Department of Transportation, United States","Titiloye I., Department of Civil and Environmental Engineering, Florida International University, 10555 W. Flagler Street, EC 3725, Miami, 33174, FL, United States; Sarker M.A.A., Department of Civil and Environmental Engineering, Florida International University, 10555 W. Flagler Street, EC 3725, Miami, 33174, FL, United States; Jin X., Department of Civil and Environmental Engineering, Florida International University, 10555 W. Flagler Street, EC 3603, Miami, 33174, FL, United States; Watts B., Performance & Trends, Forecasting & Trends Office, Florida Department of Transportation, United States","Research on grocery shopping channel preferences has been growing in the wake of the Covid-19 pandemic. However, few studies have utilized the discrete choice experiment (DCE) to elicit choices in hypothetical scenarios. Moreover, attitudinal factors, which may better explain preference heterogeneity, are rarely considered. Given that the evolution of shopping behavior in the context of the Covid-19 pandemic has huge implications for transportation planning and modeling, this study aims to examine consumers’ grocery shopping channel preferences through a DCE that was constructed with three grocery shopping channels (home delivery, curbside pickup, and in-store) and five time–cost attributes (product price, shopping time, delivery time, delivery cost, and travel time). 8,603 responses were elicited from 1,229 Florida residents between February and April 2021. Information on various aspects of respondents’ shopping attitudes as well as their socio-demographic and household attributes, grocery shopping activities, and distance to the grocery store were also collected. Using mixed logit modeling for analyses, results indicate that individuals with low education, in low- to middle-income earning households, with three or more household vehicles, and having full access to a vehicle tended to prefer in-store shopping. Also, perceived security risk, pro-alternative mobility options, pro-local store shopping, and shorter distances to grocery stores predisposed individuals toward in-store shopping. Alternatively, females, young and middle-aged individuals, workers, and individuals in large households tended to prefer home delivery and curbside pickup. Technology savviness, pro-environment, pro-online shopping, and shopping enjoyment were also drivers of home delivery and curbside pickup purchases, while cost and time consciousness did not show significant effects. Overall, the findings in this study have implications for retailers, transportation planners, and policymakers. © 2023 Tongji University and Tongji University Press","Attitudes; Covid-19; E-grocery; Online shopping; Travel behavior",{"$nulls":5},"U.S. Department of Transportation, DOT; Florida Department of Transportation, FDOT, (BDV29 977-59)","This research is sponsored by the Florida Department of Transportation (BDV29 977-59). The thoughts, outcomes, and conclusions stated in this paper are those of the authors and not essentially those of the Florida Department of Transportation or the U.S. Department of Transportation. All the authors have contributed to the work described, reviewed and approved the final version of the manuscript.","(2021); Alaimo L.S., Fiore M., 12, (2020); Aull B., Begley S., Chandra V., Mathur V.; Baarsma B., Groenewegen J., COVID-19 and the demand for online grocery shopping: empirical evidence from the Netherlands, Economist (Netherlands), 169, 4, pp. 407-421, (2021); Berg J., Henriksson M., In search of the ‘good life’: Understanding online grocery shopping and everyday mobility as social practices, J. Transp. Geogr., 83, January, (2020); Bin E., Andruetto C., Susilo Y., Pernestal A., The trade-off behaviours between virtual and physical activities during the first wave of the COVID-19 pandemic period, Eur. Transp. Res. Rev., 13, 1, pp. 1-19, (2021); Chang H.H., Meyerhoefer C.D., COVID-19 and the demand for online food shopping services: empirical evidence from Taiwan, Am. J. Agric. Econ., 103, 2, pp. 448-465, (2021); Chocarro R., Cortinas M., Villanueva M.L., Situational variables in online versus offline channel choice, Electron. Commer. Res. Appl., 12, 5, pp. 347-361, (2013); Costello A.B., Osborne J.W., Best practices in exploratory factor analysis: four recommendations for getting the most from your analysis, Pract. Assess. Res. Eval., 10, 7, (2005); Crocco F., Eboli L., Mazzulla G., Individual attitudes and shopping mode characteristics affecting the use of e-shopping and related travel, Transp. Telecommun., 14, 1, pp. 45-56, (2013); (2020); Dias F.F., Lavieri P.S., Sharda S., Khoeini S., Bhat C.R., Pendyala R.M., Pinjari A.R., Ramadurai G., Srinivasan K.K., A comparison of online and in-person activity engagement: the case of shopping and eating meals, Transp. Res. Part C: Emerg. Technol., 114, February, pp. 643-656, (2020); Distefano C., Zhu M., Mindrila D., Understanding and using factor scores: considerations for the applied researcher, Pract. Assess. Res. Eval., 14, (2009); Ellison B., McFadden B., Rickard B.J., Wilson N.L.W., Examining food purchase behavior and food values during the COVID-19 pandemic, Appl. Econ. Perspect. Policy, 43, 1, pp. 58-72, (2021); Eriksson N., Stenius M., Online grocery shoppers due to the Covid-19 pandemic - an analysis of demographic and household characteristics, Procedia Comput. Sci., 196, pp. 93-100, (2022); pp. 79-94, (2013); Grashuis J., Skevas T., Segovia M., 12, (2020); Hensher D., Rose J., (2015); Hesham F., Riadh H., Sihem N., 13, (2021); Hood N., Urquhart R., Newing A., Heppenstall A., Sociodemographic and spatial disaggregation of e-commerce channel use in the grocery market in Great Britain, J. Retail. Consum. Serv., 55, (2020); (2021); Kim W., Wang X., (2021); Kuhfeld W., (2005); Kvalsvik F., Understanding the role of situational factors on online grocery shopping among older adults, J. Retail. Consum. Serv., 68, (2022); Lo A., Duffy E., Ng S.W., Who's grocery shopping online and why: cross-sectional analysis of a nationally-representative sample since the pandemic, Curr. Develop. Nutr., 5, (2021); Maltese I., le Pira M., Marcucci E., Gatta V., Evangelinos C., Grocery or @grocery: a stated preference investigation in Rome and Milan, Res. Transp. Econ., 87, (2021); Marcucci E., Gatta V., le Pira M., Chao T., Li S., Bricks or clicks? Consumer channel choice and its transport and environmental implications for the grocery market in Norway, Cities, 110, (2021); Meister A., Winkler C., Schmid B., Axhausen K., In-store or online grocery shopping before and during the COVID-19 pandemic, Travel Behav. Soc., 30, pp. 291-301, (2023); (2021); Motte-Baumvol B., Belton-Chevallier L., Dablanc L., Morganti E., Belin-Munier C., Spatial dimensions of E-shopping in France, Asian Transp. Stud., 4, pp. 585-600, (2017); (2021); Saphores J.D., Xu L., E-shopping changes and the state of E-grocery shopping in the US - evidence from national travel and time use surveys, Res. Transp. Econ., 87, (2021); Sarker M.A.A., Rahimi A., Azimi G., Jin X., Investigating older adults’ propensity toward ridesourcing services, J. Transp. Eng., Part A: Syst., 148, 9, (2022); Schmid B., Axhausen K.W., In-store or online shopping of search and experience goods: a hybrid choice approach, J. Choice Model., 31, January 2018, pp. 156-180, (2019); Schmid B., Schmutz S., Axhausen K.; Shamim K., Ahmad S., Alam M.A., COVID-19 health safety practices: influence on grocery shopping behavior, J. Public Aff., 21, 4, (2021); Shamshiripour A., Rahimi E., Shabanpour R., Mohammadian A., (2020); Shen H., Namdarpour F., Lin J., Investigation of online grocery shopping and delivery preference before, during, and after COVID-19, Transp. Res. Interdiscip. Perspect., 14, (2022); Suel E., le Vine S., Polak J., Empirical application of expenditure diary instrument to quantify relationships between in-store and online grocery shopping: case study of greater London, Transp. Res. Rec., 2496, pp. 45-54, (2015); Train K., (2009); Truong D., Truong M.D., How do customers change their purchasing behaviors during the COVID-19 pandemic?, J. Retail. Consum. Serv., 67, (2022); Tyrvainen O., Karjaluoto H., Online grocery shopping before and during the COVID-19 pandemic: a meta-analytical review, Telematics Inform., 71, (2022); (2019); (2021); Wang K., Gao Y., Liu Y., Nurul Habib K., Exploring the choice between in-store versus online grocery shopping through an application of Semi-Compensatory Independent Availability Logit (SCIAL) model with latent variables, J. Retail. Consum. Serv., 71, (2023); Warganegara D.L., Hendijani R., 14, (2022); Watkins M.W., Exploratory factor analysis: a guide to best practice, J. Black Psychol., 44, 3, pp. 219-246, (2018); Zhen F., Du X., Cao J., Mokhtarian P.L., The association between spatial attributes and e-shopping in the shopping process for search goods and experience goods: evidence from Nanjing, J. Transp. Geogr., 66, January, pp. 291-299, (2018); Zwerina K., Huber J., Kuhfeld W., (2010)","X. Jin; Department of Civil and Environmental Engineering, Florida International University, Miami, 10555 W. Flagler Street, EC 3603, 33174, United States; email: xjin1@fiu.edu",null,"KeAi Communications Co.",{"$nulls":5},2.046043E7,null,null,null,"English","Int. J. Trans. Sci. Tech.","Article","Article in press","All Open Access; Gold Open Access","Scopus","2-s2.0-85151299418"]
["Shixin X.; Xu W.; Jianhui D.; Jian Z.; Peiji L.","Shixin, Xie (58284054300); Xu, Wang (58283242200); Jianhui, Du (58283242300); Jian, Zhong (58283407500); Peiji, Liu (58284209700)","58284054300; 58283242200; 58283242300; 58283407500; 58284209700","The design and optimization of two-echelon vehicle routing problem for multi-commodity multi-depot logistics network considering intra-city delivery service; [考虑同城配送的多产品多中心两级物流网络设计 及车辆路径研究]",2023.0,"Journal of Industrial Engineering and Engineering Management",37.0,3.0,null,178.0,190.0,12.0,0.0,"10.13587/j.cnki.jieem.2023.03.017","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85159889605&doi=10.13587%2fj.cnki.jieem.2023.03.017&partnerID=40&md5=0f2772606d19b36e1b7fe766aaaf4219","College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing, 400030, China; Chongqing Key Laboratory of Logistics, Chongqing University, Chongqing, 400030, China","Shixin X., College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing, 400030, China; Xu W., College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing, 400030, China, Chongqing Key Laboratory of Logistics, Chongqing University, Chongqing, 400030, China; Jianhui D., College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing, 400030, China; Jian Z., College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing, 400030, China; Peiji L., College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing, 400030, China","With the coordinated development of the express industry and e-commerce, the explosive growth of express parcel volume and the diversity of express product types make the single processing center model of express companies unable to meet the processing needs of various express products. In addition, the volume of intra-city express parcels also shows a continuous growth trend. However, the timeliness of intra-city express and the utilization rate of urban logistics resources are not considered simultaneously in the current delivery model. Therefore, it is necessary to build an efficient urban express delivery network so as to reduce the workload of the processing center, improve the delivery timeliness of express products, and fully use the urban logistics resources. Based on the analysis of the existing delivery system and related literature, it is found that: (1) The current researches on the two-echelon vehicle routing problem are mainly based on the situation of a single type of express product, and the multi-product twoechelon vehicle routing problem is rarely studied. However, in the operations of express companies, the multi-product two-echelon vehicle routing problem is closer to the actual operation situation. (2) Most of the existing logistics networks of express companies have only one processing center, which undertakes the responsibility of processing multiple express products, resulting in low processing efficiency and low differentiation between products. In order to deal with this problem, it is an effective measure to set up processing centers according to product types, namely multi-processing centers. (3) Most researches on intra-city express delivery consider intracity delivery requirements alone, and few scholars combine it with inter-city express delivery requirement, which fails to achieve the coordinated delivery of intra-city express and inter-city express, leading to a low utilization rate of urban logistics resources and negative externalities to the urban environment. For filling the gaps, this paper designs an urban distribution network that integrates intra-city and inter-city delivery to support multiple express products and builds a multi-depot two-echelon ring vehicle routing problem (MD-2ER-VRP) optimization model. In order to alleviate the workload of the processing center, improve various types of express products′ delivery timeliness, and enhance the utilization rate of terminal logistics resources, based on the comprehensive consideration of the delivery problems of the intra-city express and inter-city express, this paper innovatively designs an urban delivery network that integrates intra-city and intercity delivery to support multiple express products. First, multiple processing centers are set up according to the types of express products, and each processing center visits a portion of distribution centers. Distribution centers directly visited by a processing center need to visit distribution centers that are not directly visited by this processing center. In this way, a mutual visit distribution network can be formed between the distribution centers. Second, intra-city express parcels collected at distribution centers are transported by this mutual visit distribution network. Finally, each distribution center visits customers who need services. When the distribution centers visit each other, the ring distribution network is innovatively introduced to shorten the delivery time of express parcels and increase the flexibility of the entire logistics delivery network. More importantly, the intra-city express parcels do not need to go through a processing center, so that the transportation and processing time can be shortened. For inter-city express parcels, each processing center does not have to visit every distribution center, which will effectively solve the problem of urban traffic restrictions for large vehicles. This paper has established a multi-objective mathematical optimization model that minimizes the total cost of the system′s vehicle path and the total time of express parcel delivery. Aiming at this model, the non-dominated sorting genetic algorithm (NSGA-Ⅱ) is used to solve it, and the practicability and effectiveness of the model and algorithm are verified by examples. Through simulation experiments, it is found that: (1) The genetic algorithm, adaptive genetic algorithm, and NSGA-Ⅱ are applied to solve the examples with 200, 250, and 300 customers respectively for 10 times. It is verified by the average values of the total cost of vehicle routing and the total delivery time of express parcels that NSGA-Ⅱ outperforms the genetic algorithm and adaptive genetic algorithm. (2) The MD2E-R-VRP model and the multi-depot two-echelon vehicle routing problem (MD-2E-VRP) model are used to solve an example with 300 customers. It is found that the MD-2E-R-VRP model has an excellent optimization effect, especially in the optimization of the total cost of the vehicle path and the average vehicle loading rate. In addition, the total cost of vehicle routing has been reduced by 16. 70%, and the vehicle loading rate has been increased from 62. 13% to 67. 37%. ( 3) The established MD-2E-R-VRP model innovatively introduces a ring distribution network, which effectively shortens the delivery time of express parcels, and reduces the total delivery time of express parcels by 2. 22%. In summary, the designed urban delivery network that integrates intra-city and inter-city delivery to support multiple products and the constructed MD-2E-R-VRP optimization model in this paper set up the processing centers for inter-city express parcels according to their product types, and inter-city express and intra-city express share the urban logistics resources through the ring distribution network. It can effectively deal with the problems of the processing center′s heavy workload, unobvious degree of distinction between express products, and low utilization of urban logistics resources. © 2023,Journal of Industrial Engineering and Engineering Management. All Rights Reserved.","NSGA-II; Problem of multi-depot distribution network; Ring distribution network; Two-echelon vehicle routing problem; Urban logistics",{"$nulls":5},"Humanities and Social Sciences Foundation; Ministry of Education of the People's Republic of China, MOE, (19YJA630122); National Key Research and Development Program of China, NKRDPC, (2018YFB1403602); Graduate Scientific Research and Innovation Foundation of Chongqing, (CYS20007)","Received Date: 2021-02-23 　 　 　 Funded Project: Supported by the Humanities and Social Sciences Foundation Program of the Ministry of Education (19YJA630122), the National Key R&D Program of China (2018YFB1403602) and the Graduate Research and Innovation Foundation of Chongqing(CYS20007). ∗Corresponding author","Meng L, Liu F J, Chen S Y, Et al., Can I Evoke You? 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Pang Y, Luo H L, Xing L N, Et al., A survey of vehicle routing optimization problems and solution methods, Control Theory and Applications, 36, 10, pp. 1573-1584, (2019)",null,null,"Zhejiang University",{"$nulls":5},1.0046062E7,null,null,null,"English","J. Industrial Eng. Eng. Management","Article","Final",null,"Scopus","2-s2.0-85159889605"]
["Shen A.","Shen, Aiming (58068967300)",5.80689673E10,"Design of internet of things service system for logistics engineering by using the blockchain technology",2023.0,"International Journal of Grid and Utility Computing",14.0,"2024-03-02",null,182.0,190.0,8.0,0.0,"10.1504/IJGUC.2023.131003","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85161839904&doi=10.1504%2fIJGUC.2023.131003&partnerID=40&md5=9bdf361751169fe1dfab5280a9a0bc0b","School of Management Engineering, Liaoning Institute of Science and Engineering, Jinzhou, China","Shen A., School of Management Engineering, Liaoning Institute of Science and Engineering, Jinzhou, China","With the rapid progress of information technology, the application of the Internet of things (IoT) technology has become more common, which also brings greater challenges to the IoT service system. Most small and medium-sized foreign trade enterprises rely on the third-party cross-border e-commerce platform to carry out retail export business. The logistics service system has the problems of long time-consuming and high transportation and management costs. The centralised management system makes the cooperation and information sharing between IoT devices under different platforms difficult, and the device privacy data are easily leaked. In order to solve the above problems and improve the level of logistics warehousing management, an intelligent warehousing management system (WMS) has become a hot topic. Blockchain technology is introduced to build an intelligent WMS model based on the existing technical level of warehouse management. Copyright © 2023 Inderscience Enterprises Ltd.","blockchain technology; IoT services; logistics engineering; warehouse management","Blockchain; Information management; International trade; Supply chain management; Warehouses; Web services; Block-chain; Blockchain technology; Foreign trade enterprise; Internet of thing service; Internet of things technologies; Logistics engineering; Management systems; Service systems; Third parties; Warehouse management; Internet of things",{"$nulls":6},"Ahmed S.Z., Blockchain hyperledger with non-linear machine learning: a novel and secure educational accreditation registration and distributed ledger preservation architecture, Applied Sciences, 12, 5, (2022); Anusha T., A comprehensive study of the trends and analysis of distributed ledger technology and blockchain technology in the healthcare industry, Frontiers in Blockchain, (2022); Berneis M., Bartsch D., Winkler H., Applications of blockchain technology in logistics and supply chain management – insights from a systematic literature review, Logistics, 5, 3, (2021); Chen C., Mao J., Gan X.W., Design of automated warehouse management system, MATEC Web of Conferences, 232, (2018); Debasis M., Divya A., Moaiteq A.H., Et al., Blockchain interoperability: towards a sustainable payment system, Sustainability, 14, 2, (2022); Deng M.X., Mao J., Gan X.W., Development of automated warehouse management system, MATEC Web of Conferences, 232, (2018); Fang W.T., Mohsen Z., Chen Z.Y., Secure and privacy preserving consensus for second-order systems based on Paillier encryption, Systems & Control Letters, 148, (2021); Gao L.M., Celimuge W., Du Z.Y., Et al., Toward efficient blockchain for the internet of vehicles with hierarchical blockchain resource scheduling, Electronics, 11, 5, (2022); Grunt M., Blazejewski A., Pecolt S., Et al., BelBuk system – smart logistics for sustainable city development in terms of the deficit of a chemical fertilizers, Energies, 15, 13, (2022); Gufran K.M., Noor H.D., Khaleeq Z.U., Smart warehouse management system: architecture, real-time implementation and prototype design, Machines, 10, 2, (2022); Huang C.F., Zhang W., Xue L., Virtual reality scene modeling in the context of Internet of Things, Alexandria Engineering Journal, 61, 8, pp. 39-44, (2022); Jayaprakash J.S., Balasubramanian K., Sulaiman R., Et al., Cloud data encryption and authentication based on enhanced Merkle hash tree method, Computers, Materials & Continua, 72, 1, pp. 519-534, (2022); Lavish K., Singh G.G., Naveen C., Et al., Efficient and robust image communication techniques for 5G applications in smart cities, Energies, 14, 13, (2021); Lele P., Development of intelligent warehouse management system based on internet of things technology, IOP Conference Series: Materials Science and Engineering, 750, (2020); Lu P., Liu P.P., Xu J.T., Design of intelligent warehouse management system based on MVC, International Journal of Advanced Network, Monitoring and Controls, 6, 2, pp. 79-87, (2021); Park J., Lim H., Privacy-preserving federated learning using homomorphic encryption, Applied Sciences, 12, 2, (2022); Pavol Z., Ephemeral keys authenticated with Merkle trees and their use in IoT applications, Sensors, 21, 6, (2021); Sami B.S., Prosumer in smart grids based on intelligent edge computing: a review on artificial intelligence scheduling techniques, Ain Shams Engineering Journal, 13, 1, (2022); Seth B., Dalal S., Le D.N., Et al., Secure cloud data storage system using hybrid Paillier–Blowfish algorithm, Computers, Materials & Continua, 67, 1, pp. 779-798, (2021); Shubham J., Adoption of blockchain technology for privacy and security in the context of Industry 4.0, Wireless Communications and Mobile Computing, (2022); Soumyashree P., Debasish J., Kumar M.B., Et al., Authentication and key management in distributed IoT using blockchain technology, IEEE Internet of Things Journal, 8, 16, pp. 12947-12954, (2021); Tang G.H., Zeng H., Visualisation technology in digital intelligent warehouse management system, International Journal of Grid and Utility Computing, 12, 4, pp. 406-414, (2021); Vivek V., Framework for incorporating human factors into production and logistics systems, International Journal of Production Research, 60, 2, pp. 402-419, (2022); Wang L., Wang X., Cai X.L., The common warehouse model and profit distribution of the express industry, Algorithms, 14, 2, (2021); Wang L.S., Chen J., Lu Y.L., Manufacturer’s channel and logistics strategy in a supply chain, International Journal of Production Economics, 248, (2022); Wang R.B., Li Y.N., Xu H.Y., Et al., Electronic scoring scheme based on real Paillier encryption algorithms, IEEE Access, 7, pp. 128043-128053, (2019); Wu Y., Wu Y.P., Cimen H., Et al., P2P energy trading: blockchain-enabled P2P energy society with multi-scale flexibility services, Energy Reports, 8, pp. 3614-3628, (2022); Xu S.Y., Chen J., Wu M.G., Et al., E-commerce supply chain process optimization based on whole-process sharing of internet of things identification technology, Computer Modeling in Engineering & Sciences, 126, 2, pp. 843-854, (2021); Yang N., Design and application of logistics warehouse management system in iron and steel enterprises under the background of computer big data, International Journal of Intelligent Information and Management Science, 10, 6, pp. 50-55, (2021); Yin H., Gu L.Y., Chen J., Et al., Design and application of storage and inspection integration assembly line for distribution automation terminal based on RFID technology, Journal of Physics: Conference Series, 2170, 1, (2022); Zhang F., Qiao Q.Z., Wang J.J., Et al., Data-driven AI emergency planning in process industry, Journal of Loss Prevention in the Process Industries, 1, 1, (2022); Zhang M.Z., Zheng J., Design of warehouse management system based on L Company, Industrial Engineering and Innovation Management, 4, 1, pp. 1-14, (2021); Zhang Z.M., Ren D., Lan Y.F., Et al., Price competition and blockchain adoption in retailing markets, European Journal of Operational Research, 300, 2, pp. 647-660, (2022)","A. Shen; School of Management Engineering, Liaoning Institute of Science and Engineering, Jinzhou, China; email: 573703269@qq.com",null,"Inderscience Publishers",{"$nulls":5},"1741847X",null,null,null,"English","Int. J. Grid Util. Comput.","Article","Final",null,"Scopus","2-s2.0-85161839904"]
["Gruzauskas V.; Burinskiene A.; Krisciunas A.","Gruzauskas, Valentas (57190140811); Burinskiene, Aurelija (54787462500); Krisciunas, Andrius (54893410800)","57190140811; 54787462500; 54893410800","Application of Information-Sharing for Resilient and Sustainable Food Delivery in Last-Mile Logistics",2023.0,"Mathematics",11.0,2.0,303.0,null,null,null,4.0,"10.3390/math11020303","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85146789454&doi=10.3390%2fmath11020303&partnerID=40&md5=b4851355be5e6f16cad7442eed380800","Department of Business Technologies and Entrepreneurship, Vilnius Gediminas Technical University, Saulėtekio al. 11, Vilnius, LT-10223, Lithuania; Business Management Faculty, Vilnius Gediminas Technical University, Saulėtekio al. 11, Vilnius, LT-10223, Lithuania; Department of Applied Informatics, Faculty of Informatics, Kaunas University of Technology, Studentu Str. 50, Kaunas, LT-51368, Lithuania","Gruzauskas V., Department of Business Technologies and Entrepreneurship, Vilnius Gediminas Technical University, Saulėtekio al. 11, Vilnius, LT-10223, Lithuania; Burinskiene A., Business Management Faculty, Vilnius Gediminas Technical University, Saulėtekio al. 11, Vilnius, LT-10223, Lithuania; Krisciunas A., Department of Applied Informatics, Faculty of Informatics, Kaunas University of Technology, Studentu Str. 50, Kaunas, LT-51368, Lithuania","The growing food demand, the tendency for organic food, and the adaptation of the e-commerce business model require new food supply chain management approaches. On the one hand, 30% of the world’s produced food is wasted, and CO2 emissions are rapidly growing due to transport. On the other hand, the increasingly complex and dynamic environment is decreasing the effectiveness of food supply chains. Because of these trends, sustainability and resilience are becoming more relevant to food supply chains. Therefore, the objective of this paper is to propose a strategy based on information exchange to improve food quality and decrease the level of CO2 emission in last-mile deliveries of food products. To achieve this goal, an agent-based model of last-mile deliveries was developed. The model simulated traffic flow and traffic accidents as disturbances in the system while measuring the level of CO2 emission and food quality of the network. The simulation compares information sharing between all vehicles in the urban area and without information sharing in four scenarios of the food industry. In practice, information sharing is achieved by using connected vehicle technology. The use of information sharing between vehicles in last-mile delivery processes allows the development of a self-organizing system, which would adapt to disturbances and lead to the development of sustainability in the long run. © 2023 by the authors.","food supply chain; information sharing; resilience; sustainability; urban logistics",{"$nulls":5},"Lietuvos Mokslo Taryba, (P-PD-22-009)","The research was funded by the Research Council of Lithuania, “Dynamic routing for e-grocery delivery following sustainability (DREGS)”, No. P-PD-22-009.","World Population Prospects, (2015); Conrad H., Alan C., Katherine R., The Future of World Religions: Population Growth Projections, 2010–2050, (2015); The Global State of Online Grocery, (2017); World Urbanization Prospects, (2014); The Future of Food and Agriculture: Trends and Challenges, (2017); Ranieri L., Digiesi S., Silvestri B., Roccotelli M., A review of last mile logistics innovations in an externalities cost reduction vision, Sustainability, 10, (2018); Food Losses and Food Waste, 2016, pp. 1-12, (2016); Calvert S.C., Snelder M., A methodology for road traffic resilience analysis and review of related concepts, Transp. 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Simul, 7, pp. 12-24, (2013); Wiseman Y., Autonomous Vehicles, Encyclopedia of Information Science and Technology, pp. 1-11, (2020); Figliozzi M.A., Carbon emissions reductions in last mile and grocery deliveries utilizing air and ground autonomous vehicles, Transp. Res. Part D Transp. Environ, 85, (2020)","V. Gruzauskas; Department of Business Technologies and Entrepreneurship, Vilnius Gediminas Technical University, Vilnius, Saulėtekio al. 11, LT-10223, Lithuania; email: valentas.gruzauskas@vilniustech.lt",null,"MDPI",{"$nulls":5},2.227739E7,null,null,null,"English","Mathematics","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85146789454"]
["Imran M.A.; Hyun K.","Imran, Md Ashraful (58698144600); Hyun, Kate (57190497905)","58698144600; 57190497905","In-store shopping trip predictions and impact factors during COVID-19 emergencies",2023.0,"Transportation Planning and Technology",{"$nulls":6},0.0,"10.1080/03081060.2023.2282059","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85176958409&doi=10.1080%2f03081060.2023.2282059&partnerID=40&md5=2ca9aef28551570db9f73aa506813c6b","Department of Civil Engineering, University of Texas at Arlington, Arlington, TX, United States","Imran M.A., Department of Civil Engineering, University of Texas at Arlington, Arlington, TX, United States; Hyun K., Department of Civil Engineering, University of Texas at Arlington, Arlington, TX, United States","Despite the rapid growth of online shopping during COVID-19, a significant number of consumers still prefer in-store shopping. This study leverages two years (i.e. pre-pandemic and pandemic) of smartphone location data to develop machine learning (ML) models, specifically Random Forest (RF) and Extreme Gradient Boosting (XGBoost), for predicting community (e.g. block group (BG)) level in-store shopping trips for department stores, shopping malls, supermarkets, and wholesale stores. This study identifies that temperature, accessibility to stores, and the number of online shopping last-mile delivery are the three most important factors influencing shopping trips; specifically, the extent of online shopping is a critical determinant for supermarkets and wholesale store trip-makings before and during the pandemic. The models developed and important determinants of shopping trips will provide useful insight for shopping trip demand forecasting as well as impact assessments of relevant policies on in-store shopping demand during emergencies. © 2023 Informa UK Limited, trading as Taylor & Francis Group.","COVID-19; e-commerce; machine learning; shopping facilities; shopping trips","Adaptive boosting; Electronic commerce; Forecasting; Forestry; Machine learning; Random forests; Retail stores; E- commerces; Impact factor; Location data; Machine learning models; Machine-learning; Online shopping; Rapid growth; Shopping facility; Shopping trip; Smart phones; COVID-19",{"$nulls":6},"Arabi M., Hyun K., Mattingly S., Imran M.A., Post-pandemic Last-mile and Shopping Center Trip Estimations Using Scenario Analysis, Transportation Research Board Annual Meeting, (2023); Arranz-Lopez A., Soria-Lara J.A., Witlox F., Paez A., Measuring Relative Non-motorized Accessibility to Retail Activities, International Journal of Sustainable Transportation, 13, 9, pp. 639-651, (2019); (2019); Bhasin H., (2023); Brewster M., (2022); Brooks C., (2015); (2016); Cao X., Douma F., Cleaveland F., Influence of E-shopping on Shopping Travel: Evidence from Minnesota’s Twin Cities, Transportation Research Record: Journal of the Transportation Research Board, 2157, 1, pp. 147-154, (2010); Cao X., Xu Z., Douma F., The Interactions between E-shopping and Traditional In-store Shopping: An Application of Structural Equations Model, Transportation, 39, 5, pp. 957-974, (2012); Chakraborty R., (2021); Chapman J., Fox E.H., Bachman W., Frank L.D., Thomas J., Reyes A.R., (2021); Cheshmehzangi A., Revisiting the Built Environment: 10 Potential Development Changes and Paradigm Shifts Due to COVID-19, Journal of Urban Management, 10, 2, pp. 166-175, (2021); (2022); Road Use Statistics Great Britain 2016, (2016); DePhillipo N.N., Chahla J., Busler M., LaPrade R.F., Mobile Phone GPS Data and Prevalence of COVID-19 Infections: Quantifying Parameters of Social Distancing in the U.S, Archives of Bone and Joint Surgery, 9, 2, (2021); Diaz-Gutierrez J.M., Mohammadi-Mavi H., Ranjbari A., COVID-19 Impacts on Online and In-store Shopping Behaviors: Why they Happened and Whether they will Last Post Pandemic, Transportation Research Record: Journal of the Transportation Research Board, (2023); Ding Y., Lu H., The Interactions between Online Shopping and Personal Activity Travel Behavior: An Analysis with a GPS-based Activity Travel Diary, Transportation, 44, 2, pp. 311-324, (2017); Downs R.M., The Cognitive Structure of an Urban Shopping Center, Environment and Behavior, 2, 1, pp. 13-39, (1970); Escobedo J., (2020); Etminani-Ghasrodashti R., Hamidi S., Online Shopping as a Substitute or Complement to In-store Shopping Trips in Iran?, Cities, 103, August, (2020); Farag S., Krizek K.J., Dijst M., E-shopping and its Relationship with In-store Shopping: Empirical Evidence from the Netherlands and the USA, Transport Reviews, 26, 1, pp. 43-61, (2006); Farag S., Schwanen T., Dijst M., Faber J., Shopping Online and/or In-store? A Structural Equation Model of the Relationships between E-shopping and In-store Shopping, Transportation Research Part A: Policy and Practice, 41, 2, pp. 125-141, (2007); Ferrell C.E., Home-based Teleshopping and Shopping Travel: Where Do People Find the Time?, Transportation Research Record: Journal of the Transportation Research Board, 1926, 1, pp. 212-223, (2005); Ghirelli C., Gonzalez A., Herrera J.L., Hurtado S., Weather, Mobility and the Evolution of the Covid-19 Pandemic, Journal of Economic Studies, 50, 3, pp. 625-641, (2023); Gould J., Golob T.F., Will Electronic Home Shopping Reduce Travel?, ACCESS Magazine, 1, 12, pp. 26-31, (1998); Hahm Y., Yoon H., Choi Y., The Effect of Built Environments on the Walking and Shopping Behaviors of Pedestrians; A Study with GPS Experiment in Sinchon Retail District in Seoul, South Korea, Cities, 89, June, pp. 1-13, (2019); Hale T., Angrist N., Goldszmidt R., Kira B., Petherick A., Phillips T., Webster S., Et al., A Global Panel Database of Pandemic Policies (Oxford COVID-19 Government Response Tracker), Nature Human Behaviour, 5, 4, pp. 529-538, (2021); Handy S.L., Regional versus Local Accessibility: Variations in Suburban Form and the Effects on Non-work Travel, (1992); Hayrullahoglu G., Varol C., Understanding Mobility Dynamics Using Urban Functions during the COVID-19 Pandemic: Comparison of Pre-and Post-new Normal Eras, Asia-Pacific Journal of Regional Science, 6, 3, pp. 1087-1109, (2022); Hsu M.K., Huang Y., Swanson S., Grocery Store Image, Travel Distance, Satisfaction and Behavioral Intentions: Evidence from a Midwest College Town, International Journal of Retail & Distribution Management, 38, 2, pp. 115-132, (2010); (2020); Irawan M.Z., Wirza E., Understanding the Effect of Online Shopping Behavior on Shopping Travel Demand through Structural Equation Modeling, Journal of the Eastern Asia Society for Transportation Studies, 11, pp. 614-625, (2015); Jiao J., Moudon A.V., Drewnowski A., Does Urban Form Influence Grocery Shopping Frequency? A Study from Seattle, Washington, USA, International Journal of Retail & Distribution Management, 44, 9, pp. 903-922, (2016); Kim J.O., Jin B., Korean Consumers’ Patronage of Discount Stores: Domestic vs Multinational Discount Store Shoppers’ Profiles, Journal of Consumer Marketing, 18, 3, pp. 236-253, (2001); Lee R.J., Sener I.N., Mokhtarian P.L., Handy S.L., Relationships between the Online and In-store Shopping Frequency of Davis, California Residents, Transportation Research Part A: Policy and Practice, 100, pp. 40-52, (2017); Li A., Zhao P., Haitao H., Mansourian A., Axhausen K.W., How did Micro-mobility Change in Response to COVID-19 Pandemic? A Case Study Based on Spatial-temporal-Semantic Analytics, Computers, Environment and Urban Systems, 90, November, (2021); Liu B., Widener M.J., Smith L.G., Farber S., Minaker L.M., Patterson Z., Larsen K., Gilliland J., Disentangling Time Use, Food Environment, and Food Behaviors Using Multi-channel Sequence Analysis, Geographical Analysis, 54, 4, pp. 881-917, (2022); (2020); Mendolia S., Stavrunova O., Yerokhin O., Determinants of the Community Mobility during the COVID-19 Epidemic: The Role of Government Regulations and Information, Journal of Economic Behavior & Organization, 184, April, pp. 199-231, (2021); Miah M.M., Hyun K.K., Mattingly S.P., Khan H., Estimation of Daily Bicycle Traffic Using Machine and Deep Learning Techniques, Transportation, pp. 1-54, (2022); Moniruzzaman M., Paez A., Nurul Habib K.M., Morency C., Mode Use and Trip Length of Seniors in Montreal, Journal of Transport Geography, 30, June, pp. 89-99, (2013); Olya G., (2022); (2021); Roob C., (2023); Rose D., Richards R., Food Store Access and Household Fruit and Vegetable Use among Participants in the US Food Stamp Program, Public Health Nutrition, 7, 8, pp. 1081-1088, (2004); Salon D., Conway M.W., Da Silva D.C., Chauhan R.S., Derrible S., Mohammadian A.K., Et al., The Potential Stickiness of Pandemic-induced Behavior Changes in the United States, Proceedings of the National Academy of Sciences, 118, 27, (2021); Scott C., (2019); Shamshiripour A., Rahimi E., Shabanpour R., Mohammadian A.K., How is COVID-19 Reshaping Activity-travel Behavior? Evidence from a Comprehensive Survey in Chicago, Transportation Research Interdisciplinary Perspectives, 7, (2020); Shi K., De Vos J., Yang Y., Witlox F., Does E-shopping Replace Shopping Trips? Empirical Evidence from Chengdu, China, Transportation Research Part A: Policy and Practice, 122, April, pp. 21-33, (2019); (2018); (2022); (2022); Thanasi-Boce M., Kwiatek P., Labadze L., The Importance of Distance and Attraction in Patronizing a Shopping Mall, Journal of Place Management and Development, 14, 2, pp. 222-238, (2020); Thomas L., Berk C.C., (2020); Torres-Reyna O., (2007); Twardzik E., Judd S., Bennett A., Hooker S., Howard V., Hutto B., Clarke P., Colabianchi N., Walk Score and Objectively Measured Physical Activity within a National Cohort, Journal of Epidemiology and Community Health, 73, 6, pp. 549-556, (2019); Vilhelmson B., Urbanisation and Everyday Mobility. Long-term Changes of Travel in Urban Areas of Sweden, Cybergeo, (2005); Weltevreden J.W.J., Rotem-Mindali O., Mobility Effects of B2c and C2c E-commerce in the Netherlands: A Quantitative Assessment, Journal of Transport Geography, 17, 2, pp. 83-92, (2009); (2023); (2023); Xue C., Wu Q., Sun M., Bai P., Chen Y., The Interaction between E-shopping and Shopping Trips: An Analysis with 2017 NHTS, Complexity, 2021, pp. 1-12, (2021); Zboraj M., (2021); Zhen F., Cao X., Mokhtarian P.L., Xi G., Associations between Online Purchasing and Store Purchasing for Four Types of Products in Nanjing, China, Transportation Research Record, 2566, 1, pp. 93-101, (2016); Zhou Y., Wang X.C., Explore the Relationship between Online Shopping and Shopping Trips: An Analysis with the 2009 NHTS Data, Transportation Research Part A: Policy and Practice, 70, December, pp. 1-9, (2014)","M.A. Imran; Department of Civil Engineering, University of Texas at Arlington, Arlington, 425 Nedderman Hall, 76019, United States; email: mxi3942@mavs.uta.edu",null,"Routledge",{"$nulls":5},3081060.0,null,null,null,"English","Transp. Plann. Technol.","Article","Article in press",null,"Scopus","2-s2.0-85176958409"]
["Sanghi N.; Chandra Balodi K.; Gupta V.","Sanghi, Nirmit (58081859900); Chandra Balodi, Krishna (58082385200); Gupta, Vivek (58081684700)","58081859900; 58082385200; 58081684700","“The emergence of the Indian hyperlocal grocery delivery industry: Dunzo v/s Blinkit”",2023.0,"Journal of Information Technology Teaching Cases",{"$nulls":6},2.0,"10.1177/20438869231151449","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85147031873&doi=10.1177%2f20438869231151449&partnerID=40&md5=f57ecd18125d46c6ae37dc3bf06554a7","Indian Institute of Management Lucknow, Lucknow, India; Strategic Management, Indian Institute of Management Lucknow, Lucknow, India; IT Systems Area, Indian Institute of Management Lucknow, Lucknow, India","Sanghi N., Indian Institute of Management Lucknow, Lucknow, India; Chandra Balodi K., Strategic Management, Indian Institute of Management Lucknow, Lucknow, India; Gupta V., IT Systems Area, Indian Institute of Management Lucknow, Lucknow, India","This case details the evolution of the Hyperlocal Grocery Delivery Industry in India and a comparative analysis between Dunzo and Blinkit. The case describes the macro and industry level imperatives, growth drivers and competitive dynamics, and the resultant evolution of alternate business models. In an emerging economy context traditionally characterized by institutional voids, technological and infrastructural challenges, and a lack of entrepreneurial resources, the evolution, proliferation, and growth of the Hyperlocal Delivery business model makes for an intriguing story. We intend to make readers aware of the industry dynamics and allow them to use strategy, technological innovation, and the fundamentals of platform businesses frameworks from strategy, innovation, and platform businesses domains to evaluate the value proposition and offering that these firms have for consumers and the operational model to craft winning strategies in this emerging industry. © Association for Information Technology Trust 2023.","consumer-packaged goods makers; e-commerce horizontals; e-grocery players; Omnichannel players; restaurant aggregators; standalone quick commerce players",{"$nulls":7},"Bhalla K., 'These two 19-year-olds scaled Zepto into a $900 million company in nine months', (2022); Zomato to soon launch ‘Zomato Instant’ for 10-min food delivery, (2022); Food and Drink E-Commerce in India, February 2022, (2022); Manchanda K., Ashrafi S., Dunzo’s Losses Widen to INR 464 Cr in Fy 2022 While Revenue Doubles, (2022); Kamel M., Montgolfier J.D., Athanassiou M., Mol A.D., Online Grocery Strategy: A Reality Check for Disruptors and Incumbents, (2022); Kashyaap S., [Product roadmap] Starting out on WhatsApp, how Dunzo became India's go-to hyperlocal delivery start-up, (2020); Kashyap H., Dunzo, Blinkit or Zepto: India’s Speedsters Stack Up In The Qcommerce Battle, (2022); 'India to Have Around 900 Million Internet Users by 2025: Report', (2022); Maloo M., How Grofers Evolved into a Zomato Subsidiary Called Blinkit', (2022); The state of grocery retail in India, (2022); Patil U., Sandoval L., Sawant A., COVID-19 accelerates the growth of india’s online grocery market, (2021); Food Delivery Platform Zomato to Acquire Blinkit in 4,447-cr. Deal, (2022); Rajadhyaksha N., India Could be an Upper Middle Income Country Within a Decade, (2022); Revenue From Operation of Dunzo in FY 2018-2022, (2022); Revenue From Operations of Blinkit in FY 2017-2021, (2022); Tandon S., Big Bazaar Set to Offer Two-Hour Delivery, (2021); (2022); Tyagi G., Vardhan J., ‘BlinkIt Revenue Crosses 2, 700 Cr in FY21; losses pile up to Rs 6, 127 Cr’, (2022); Vardhan J., Tyagi G., Dunzo revenue jumps 66% to Rs 46 Cr in FY21, outstanding losses balloon to Rs 768 Cr, (2021)","K. Chandra Balodi; Strategic Management, Indian Institute of Management Lucknow, Lucknow, India; email: krishna.balodi@iiml.ac.in",null,"SAGE Publications Inc.",{"$nulls":5},2.0438869E7,null,null,null,"English","J. Infor. Technol. Teach. Classes","Article","Article in press",null,"Scopus","2-s2.0-85147031873"]
["Xiaoling J.; Bin D.; Shengnan W.; Ludan X.","Xiaoling, Jiang (58148664500); Bin, Dan (57421427800); Shengnan, Wu (58386331700); Ludan, Xu (58148953400)","58148664500; 57421427800; 58386331700; 58148953400","How do fresh produce e-tailers solve the dilemma of “cost-time-experience” in logistics? A case study of Freshippo; [生鲜电商如何突破物流“ 成本-时效-体验” 困局 ———基于盒马鲜生的案例研究]",2023.0,"Journal of Industrial Engineering and Engineering Management",37.0,2.0,null,222.0,239.0,17.0,0.0,"10.13587/j.cnki.jieem.2023.02.021","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85150418131&doi=10.13587%2fj.cnki.jieem.2023.02.021&partnerID=40&md5=cfacecabe6af21602a6f8930c853ff80","School of Economics and Business Administration, Chongqing University, Chongqing, 400044, China; Chongqing Key Laboratory of Logistics, Chongqing University, Chongqing, 400030, China","Xiaoling J., School of Economics and Business Administration, Chongqing University, Chongqing, 400044, China, Chongqing Key Laboratory of Logistics, Chongqing University, Chongqing, 400030, China; Bin D., School of Economics and Business Administration, Chongqing University, Chongqing, 400044, China, Chongqing Key Laboratory of Logistics, Chongqing University, Chongqing, 400030, China; Shengnan W., School of Economics and Business Administration, Chongqing University, Chongqing, 400044, China, Chongqing Key Laboratory of Logistics, Chongqing University, Chongqing, 400030, China; Ludan X., School of Economics and Business Administration, Chongqing University, Chongqing, 400044, China, Chongqing Key Laboratory of Logistics, Chongqing University, Chongqing, 400030, China","With the popularization of Internet applications and changes in the consumption patterns of urban residents, fresh produce e-commerce develops rapidly in China. However, the market share of fresh produce e-commerce increases slowly. Many fresh produce e-tailers have difficulty in achieving efficient and sustainable business operations. One of the critical reasons is the contradiction of cost control and logistics service level adjustment. Furthermore, the government clearly states accelerating the development of new logistics service modes and cold-chain logistics for fresh produce e-commerce. It indicates that the operations management of fresh produce e-commerce needs to be improved, and highlights that logistics is essential for the development of fresh produce e-commerce.As fresh produce is perishable and consumer demand has to be immediately satisfied, online products’ delivery time and distance are limited. Hence, fresh produce e-tailers are asked to build temperature-controlled warehouses and implement the cold-chain logistics layout, which results in a high level of logistics cost. Meanwhile, the consumption habits of fresh produce consumers are gradually changing. In addition to purchasing high freshness produce from the e-tailers, consumers request for a higher level of logistics time and experience. For instance, they expect for half-an-hour instant delivery service, dynamic changes within permitted delivery places and delivery time, and traceability of the entire logistics process. Moreover, with the environment becoming highly volatile owing to emergency events and other factors, fresh produce e-tailers’ efforts to solve the logistics dilemma have generated little effect and the former logistics achievements are unsustainable. And with consumption upgradation accelerating, consumer demand for fresh produce logistics increases constantly, fresh produce e-tailers are in turn thrown into the dilemma of “cost-time-experience” in logistics caused by environmental vulnerability. Therefore, fresh produce e-tailers urgently solve the dilemma between controlling cost and satisfying consumer demand for logistics time and experience to maintain operational efficiency. However, existing literature treats logistics mainly as a selective activity developed by catering to others’ needs, highlighting logistics as the external factor for fresh produce e-tailers. They ignore the endogenous importance of logistics to the development of fresh produce e-tailers, resulting in insufficient practical and theoretical analysis of how fresh produce e-tailers endogenously develop logistics. Especially, it is still difficult to explain the above critical issues. On such a background, how fresh produce e-tailers can solve the dilemma of “cost-time-experience” in logistics is becoming one of the important research topics in operations management of fresh produce e-commerce that needs further exploration. Motivated by the above discussion, we explore how fresh produce e-tailers can solve the dilemma of “cost-time-experience” in logistics. Since our research aims to answer the “how” questions, we select the case study method, an inductive approach that is well suited for developing theory. According to the theoretical sampling principle, we select Freshippo, a revelatory and exemplary Chinese fresh produce e-tailer, as the case study object. And we adopt a variety of different data collection methods, such as semi-structured interviews, archival materials, and on-site observations collecting abundant data to enhance the richness and depth of our study and ensuring the diversity of data sources enables triangulation of our findings. To analyze a typical case more carefully, based on multiple data sources, we conduct a preliminary analysis and systematically comb the logistics layout and development process of Freshippo into the high-demand fresh produce market under new retail trends. In particular, we deeply unfold the causes, solving processes, and results of Freshippo’ s logistics dilemma. And we identify three critical practices, i. e., building logistics legitimacy, logistics effectiveness, and logistics inclusiveness of fresh produce e-tailers. Then, following the coding procedure, we encode the qualitative data obtained and ensure the whole process of data processing is iterative until the conceptual framework is at high validity. Finally, the above inductive analysis shows a three-tiered data structure consisting of first-order concepts, second-order themes and aggregate dimensions. Based on the case analysis and coding structure, we develop a conceptual model about how fresh produce e-tailers can solve the logistics dilemma. Fresh produce e-tailers solve the logistics dilemma in a successive process to construct key logistics characteristics until fitting with the operational goals that have been balanced in cost and elaborated consumer demand. In the first phase of the model, fresh produce e-tailers face the logistics dilemma caused by cost input. They should build logistics legitimacy and form a community with consumers generating scale effects to become the market mainstream. In the second phase of the model, facing the logistics dilemma caused by the non-formula feature of consumption, fresh produce e-tailers should build logistics effectiveness and do deep community involvement providing effective service to establish the market advantage. In the third phase of the model, troubled by the logistics dilemma caused by environmental vulnerability, fresh produce e-tailers should build logistics inclusiveness and construct a consumption intelligence system responding to demand resiliently to keep a market-leading position. During the entire process, fresh produce e-tailers should iterate logistics construction activities and evolve with consumers, which enable logistics network capabilities to upgrade to satisfy demand better. Moreover, the model captures two characteristics, the vulnerability and prospecting in the logistics dilemma-solving results. The e-tailers can build the prospecting of fresh produce and logistics service from the positive effect of solving process. Through further discussion of the conceptual model, we propose the long-chained management principles of how fresh produce e-tailers realize logistics goals, called “connecting, advocating, collaborating”. Understanding the logistics dilemma-solving process requires looking beyond a single stage and static analysis. We suggest that fresh produce e-tailers pay attention to the laws of dynamic context, which can shed light on how to solve the logistics dilemma and give new insights to their operations management from a dynamic process perspective. To this end, we propose a conceptual model about how fresh produce e-tailers can solve the logistics dilemma, endogenously develop the logistics and realize the logistics goals, in the process going from building logistics legitimacy, effectiveness, to inclusiveness. Our work contributes understanding in fresh produce e-commerce logistics related areas and enriches the theory of operations management of fresh produce e-tailers. For managerial implications, our findings might be more generalizable to other fresh produce e-tailers who are troubled in developing logistics and want to achieve operational objectives © 2023, Journal of Industrial Engineering and Engineering Management.All Rights Reserved.","Case study; Cost-time-experience; Fresh produce e-commerce; Freshippo; Logistics",{"$nulls":5},"National Natural Science Foundation of China, NSFC, (72171029); Fundamental Research Funds for the Central Universities, (2022CDSKXYJG007); National Office for Philosophy and Social Sciences, NPOPSS, (15ZDB169)","Received Date: 2021-05-04 　 　 　 Funded Project: Supported by the National Natural Science Foundation of China (72171029), the Major Program of the National Social Science Foundation of China (15ZDB169) and the Fundamental Research Funds for the Central Universities (2022CDSKXYJG007). ∗Corresponding author","The data report for fresh produce e-commerce market of China in the first half of 2020; General Office of the State Council of China, Opinions of the General Office of the State Council on accelerating new consumption with new types of operations and models, Gazette of the State Council of the People’ s Republic of China, 28, pp. 23-27, (2020); 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Yin R K., Case study research: Design and methods [M], (2009); Xiao J H, Wu Y, Liu Y, Et al., New product development innovation with customer digitalized engagement: A comparative case study from the firm-customer coevolutionary perspective, Journal of Management World, 34, 8, pp. 154-173, (2018); Gioia D A, Corley K G, Hamilton A L., Seeking qualitative rigor in inductive research: Notes on the Gioia methodology, Organizational Research Methods, 16, 1, pp. 15-31, (2013); Tian Z L, Cheng P F, Yang W, Et al., The formation and evolution of the legitimacy in the process of the participation in the cooperate community: The case studies on Baibuting and Wanke, Journal of Management World, 12, pp. 134-151, (2014); Li Z G, Du X, Zhang J W., Research on the mechanism of business ecosystem reshaping of core enterprise from the spin-off perspective: A case study on Mengniu series entrepreneurship, Journal of Management World, 36, 11, pp. 80-96, (2020)",null,null,"Zhejiang University",{"$nulls":5},1.0046062E7,null,null,null,"English","J. Industrial Eng. Eng. Management","Article","Final",null,"Scopus","2-s2.0-85150418131"]
["Zhang P.; He Y.; Xu H.","Zhang, Peng (57195936962); He, Yong (55629044400); Xu, Henry (56144076600)","57195936962; 55629044400; 56144076600","Fresh product e-retailer’s sales strategy choice: free shipping, package, or combined strategy?",2023.0,"Journal of the Operational Research Society",{"$nulls":6},0.0,"10.1080/01605682.2023.2249523","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85169137843&doi=10.1080%2f01605682.2023.2249523&partnerID=40&md5=9c3cc9b7e6699d04fc1fe62c50937a5c","Yangzhou University, Yangzhou, China; Southeast University, Nanjing, China; The University of Queensland, Brisbane, Australia","Zhang P., Yangzhou University, Yangzhou, China; He Y., Southeast University, Nanjing, China; Xu H., The University of Queensland, Brisbane, Australia","Cold chain technology and online platform have enabled the rapid development of fresh food e-commerce. However, most fresh product e-retailers are losing money. This paper aims to answer the questions: Can the free shipping strategy, package strategy, and combined package and free shipping strategy (i.e., KF strategy) improve a fresh product e-retailer’s performance, and which strategy is the most effective? By deriving the optimal decisions of customers and/or the e-retailer under different strategies, we find that the e-retailer should adopt the free shipping strategy or the KF strategy if the shipping cost is higher than the threshold. Furthermore, some managerial insights are obtained. First, compared with the general strategy, the e-retailer needs to further reduce the price when the shipping cost is lower than the threshold despite bearing the shipping cost under the free shipping strategy or KF strategy. Second, the free shipping strategy or KF strategy is generally used to increase the customer’s single order quantity. However, if the shipping cost is higher than the threshold, the e-retailer should use these two strategies to reduce the single order quantity. Lastly, if the e-retailer wants to reduce its average logistics cost, the package strategy is a better choice. © Operational Research Society 2023.","free shipping strategy; Fresh product e-retailer; package strategy","Electronic commerce; Sales; Ships; Cold chain; Free shipping; Free shipping strategy; Fresh product e-retailer; Ordering quantity; Package strategy; Sales strategies; Shipping cost; Shipping Package; Strategy choices; Cost reduction",{"$nulls":6},"Agi M.A.N., Soni H.N., Joint pricing and inventory decisions for perishable products with age-, stock-, and price-dependent demand rate, Journal of the Operational Research Society, 71, 1, pp. 85-99, (2020); Alvarez-Albelo C.D., The role of complementarity of goods in a mixed bundling strategy, Economics and Business Letters, 9, 1, pp. 31-40, (2020); Cao Q., Tang Y., Perera S., Zhang J., Manufacturer-versus retailer-initiated bundling: Implications for the supply chain, Transportation Research Part E: Logistics and Transportation Review, 157, (2022); Chang S.H., Dong Y., Wang X.Y., Optimal shipping policy in retail competition and its effect on customers, Electronic Commerce Research and Applications, 45, (2021); Chen T., Yang F., Guo X., Retailer-driven bundling when valuation discount exists, Journal of the Operational Research Society, 71, 12, pp. 2027-2041, (2020); Chen T., Yang F., Guo X., Optimal bundling in a distribution channel in the presence of substitutability and complementarity, International Journal of Production Research, 59, 4, pp. 1145-1165, (2021); Chen Y., Zhang T., Interpersonal bundling, Management Science, 61, 6, pp. 1456-1471, (2015); Chiang W.K., Chhajed D., Hess J.D., Direct marketing, indirect profits: A strategic analysis of dual-channel supply-chain design, Management Science, 49, 1, pp. 1-20, (2003); Choi H.S., Chen C., The effects of discount pricing and bundling on the sales of game as a service: An empirical investigation, Journal of Electronic Commerce Research, 20, 1, pp. 21-34, (2019); (2015); Feng L., Dynamic pricing, quality investment, and replenishment model for perishable items, International Transactions in Operational Research, 26, 4, pp. 1558-1575, (2019); Giri R.N., Mondal S.K., Maiti M., Bundle pricing strategies for two complementary products with different channel powers, Annals of Operations Research, 287, 2, pp. 701-725, (2020); Guo X., Li B., Liu Y., Liang L., Eliminating the inconvenience of carrying: Optimal pricing of delivery service for retailers, Service Science, 9, 3, pp. 181-191, (2017); Halmenschlager C., Mantovani A., On the private and social desirability of mixed bundling in complementary markets with cost savings, Information Economics and Policy, 39, pp. 45-59, (2017); Herbon A., Levner E., Cheng T.C.E., Perishable inventory management with dynamic pricing using time–temperature indicators linked to automatic detecting devices, International Journal of Production Economics, 147, pp. 605-613, (2014); Honhon D., Pan X.A., Improving profits by bundling vertically differentiated products, Production and Operations Management, 26, 8, pp. 1481-1497, (2017); Huang Y.S., Ho J.W., Wu G.J., A study on promotion with strategic two-stage customized bundling, Journal of Retailing and Consumer Services, 68, (2022); (2015); Kaplan G., Menzio G., The morphology of price dispersion, International Economic Review, 56, 4, pp. 1165-1206, (2015); Kawamoto D., pp. 394-393, (2008); Kim H.M., The effect of salience on mental accounting: How integration versus segregation of payment influences purchase decisions, Journal of Behavioral Decision Making, 19, 4, pp. 381-391, (2006); Lepthien A., Clement M., Shipping fee schedules and return behavior, Marketing Letters, 30, 2, pp. 151-165, (2019); Lewis M., Singh V., Fay S., An empirical study of the impact of nonlinear shipping and handling fees on purchase incidence and expenditure decisions, Marketing Science, 25, 1, pp. 51-64, (2006); Li C., Chu M., Zhou C., Xie W., Is it always advantageous to add-on item recommendation service with a contingent free shipping policy in platform retailing?, Electronic Commerce Research and Applications, 37, (2019); Li D., Wang H., Effects of retailers’ free shipping promotions on manufacturers’ product sales and product review ratings in multichannel retailing, Managerial and Decision Economics, 43, 6, pp. 1912-1925, (2022); Li M., Feng H., Chen F., Kou J., Numerical investigation on mixed bundling and pricing of information products, International Journal of Production Economics, 144, 2, pp. 560-571, (2013); Li N., Wang Z., Optimal pricing and ordering strategies for dual-channel retailing with different shipping policies, Journal of Industrial and Management Optimization, 19, 2, pp. 1236-1261, (2023); Mantin B., Jiang L., Strategic inventories with quality deterioration, European Journal of Operational Research, 258, 1, pp. 155-164, (2017); Martinez-Salazar I., Angel-Bello F., Alvarez A., A customer-centric routing problem with multiple trips of a single vehicle, Journal of the Operational Research Society, 66, 8, pp. 1312-1323, (2015); Priyan S., Mala P., Optimal inventory system for pharmaceutical products incorporating quality degradation with expiration date: A game theory approach, Operations Research for Health Care, 24, (2020); Rabbani M., Zia N.P., Rafiei H., Joint optimal dynamic pricing and replenishment policies for items with simultaneous quality and physical quantity deterioration, Applied Mathematics and Computation, 287-288, pp. 149-160, (2016); Rofin T.M., Mahanty B., Fulfillment mode selection for Indian online sellers under free and flat rate shipping policies, Electronic Commerce Research, 21, 2, pp. 263-296, (2021); Shan H., Zhang C., Wei G., Bundling or unbundling? Pricing strategy for complementary products in a green supply chain, Sustainability, 12, 4, (2020); Shao X.F., Free or calculated shipping: Impact of delivery cost on supply chains moving to online retailing, International Journal of Production Economics, 191, pp. 267-277, (2017); Shehu E., Papies D., Neslin S.A., Free shipping promotions and product returns, Journal of Marketing Research, 57, 4, pp. 640-658, (2020); Tandon U., Mittal A., Manohar S., Examining the impact of intangible product features and e-commerce institutional mechanics on consumer trust and repurchase intention, Electronic Markets, 31, 4, pp. 945-964, (2021); Yao Y., Zhang J., Pricing for shipping services of online retailers: Analytical and empirical approaches, Decision Support Systems, 53, 2, pp. 368-380, (2012); Yang C.Y., Feng Y.H., Whinston A., Dynamic pricing and information disclosure for fresh produce: An artificial intelligence approach, Production and Operations Management, 31, 1, pp. 155-171, (2022); Zhou S., Song B., Gavirneni S., Bundling decisions in a two-product duopoly-lead or follow?, European Journal of Operational Research, 284, 3, pp. 980-989, (2020)","Y. He; Southeast University, Nanjing, China; email: hy@seu.edu.cn",null,"Taylor and Francis Ltd.",{"$nulls":5},1605682.0,null,"JORSD",null,"English","J.Oper.Res.Soc.","Article","Article in press",null,"Scopus","2-s2.0-85169137843"]
["Zhou P.; Zhang Y.; Akyol S.","Zhou, Pei (58688302000); Zhang, Yibo (58687579100); Akyol, Sinem (57189581853)","58688302000; 58687579100; 57189581853","A Novel Consumer Preference Model Based on Blockchain and Topic Similarity Clustering in Cross-Border E-Commerce",2023.0,"Journal of Organizational and End User Computing",35.0,1.0,{"$nulls":4},0.0,"10.4018/JOEUC.333062","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85176215845&doi=10.4018%2fJOEUC.333062&partnerID=40&md5=573daf4bebc2fb8d8272913641628263","Jiaozuo Normal College, China; Firat University, Turkey","Zhou P., Jiaozuo Normal College, China; Zhang Y., Jiaozuo Normal College, China; Akyol S., Firat University, Turkey","Nowadays, countries in the world have frequent economic exchanges, and the scale of cross-border E-Commerce (CBEC) is getting larger and larger. CBEC refers to trading, payment, logistics, customs clearance, and other transactions. It also refers to the services between countries or regions through Internet technology and e-commerce platforms. In this article, the authors proposed a consumer preference model by blockchain and topic similarity clustering to obtain more consumer preference information. First, this article builds a blockchain-based consumer information collection system for CBEC to extract various features of consumers in CBEC. Secondly, by improving the performance of multiple characteristics of consumers, the accuracy of consumer preference prediction is improved. Finally, a method of consumer preference prediction based on topic similarity clustering is proposed to obtain consumers’ purchase preference types. Experimental results show that the method can reach 84.3% of the H-mean, getting the best predictive performance and assisting CBEC by predicting consumer preferences. © 2023 IGI Global. All rights reserved.","Blockchain; CBEC; Consumer preference; Topic Similarity Clustering","Blockchain; Forecasting; Block-chain; Clusterings; Consumer preference modeling; Consumers' preferences; Cross-border; Cross-border E-commerce; Economic exchange; Model-based OPC; Topic similarity; Topic similarity clustering; Electronic commerce",{"$nulls":6},"Al-Alawi B. M., Bradley T. H., Total cost of ownership, payback, and consumer preference modeling of plug-in hybrid electric vehicles, Applied Energy, 103, pp. 488-506, (2013); Al-Samarraie H., Selim H., Teo T., Zaqout F., Isolation and distinctiveness in the design of e-learning systems influence user preferences, Interactive Learning Environments, 25, 4, pp. 452-466, (2017); Amin M. A., Nowsin N., Hossain I., Bala T., Impact of social media on consumer buying behavior through online value proposition: A study on e-commerce business in Bangladesh, BUFT Journal of Business and Economics (BJBE), (2020); Chung J., Rao V. R., A general consumer preference model for experience products: Application to internetrecommendationservices, JMR,JournalofMarketingResearch, 49, 3, pp. 289-305, (2012); Haboucha C. J., Ishaq R., Shiftan Y., User preferences regarding autonomous vehicles, Transportation Research Part C, Emerging Technologies, 78, pp. 37-49, (2017); Kawa A., Zdrenka W., Conception of integrator in cross-border e-commerce, LogForum, 12, 1, pp. 63-73, (2016); Lai J., Research on cross-border E-commerce logistics supply under block chain, 2019 International Conference on Computer Network, Electronic and Automation (ICCNEA), pp. 214-218, (2019); Liao F., Molin E., Timmermans H., Wee B., Consumer preferences for business models in electric vehicle adoption, Transport Policy, 73, pp. 12-24, (2019); Liao Q., Shao M., Discussion on payment application in cross-border e-commerce platform from the perspective of blockchain. E3S Web of Conferences, EDP Sciences, 235, (2021); Liu J., Wang Y., Tao H., An improved matrix factorization model under multidimensional context situation, 2015 IEEE/CIC International Conference on Communications in China (ICCC), pp. 1-6, (2015); Liu Z., Lei S., Guo Y., Zhou Z., The interaction effect of online review language style and product type on consumers’ purchase intentions, Palgrave Communications, 6, 1, pp. 1-8, (2020); Ma S. C., Fan Y., Guo J. F., Xu J. H., Zhu J. N., Analysing online behaviour to determine Chinese consumers’ preferences for electric vehicles, Journal of Cleaner Production, 229, pp. 244-255, (2019); Maiya A. S., Rolfe R. M., Topic similarity networks: Visual analytics for large document sets, 2014 IEEE International Conference on Big Data (Big Data), pp. 364-372, (2014); Nguyen D. H., De Leeuw S., Dullaert W., Foubert B., What is the right delivery option for you? Consumer preferences for delivery attributes in online retailing, Journal of Business Logistics, 40, 4, pp. 299-321, (2019); Peinelt N., Nguyen D., Liakata M., tBERT: Topic models and BERT joining forces for semantic similarity detection, Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pp. 7047-7055, (2020); Saeed T. U., Burris M. W., Labi S., Sinha K. C., An empirical discourse on forecasting the use of autonomous vehicles using consumers’ preferences, Technological Forecasting and Social Change, 158, (2020); Silva S. C., Duarte P., Machado J. C., Martins C., Cause-related marketing in online environment: The role of brand-cause fit, perceived value, and trust, International Review on Public and Nonprofit Marketing, 17, 2, pp. 135-157, (2020); Terragni S., Fersini E., Messina E., Word embedding-based topic similarity measures, International Conference on Applications of Natural Language to Information Systems, pp. 33-45, (2021); Tondello G. F., Mora A., Nacke L. E., Elements of gameful design emerging from user preferences, Proceedings of the Annual Symposium on Computer-Human Interaction in Play, pp. 129-142, (2017); Viciunaite V., Alfnes F., Informing sustainable business models with a consumer preference perspective, Journal of Cleaner Production, 242, (2020); Wang F., Building Dongguan cross border e-commerce industry” closed loop” ecosystem with blockchain Technology, 2021 2nd International Conference on E-Commerce and Internet Technology (ECIT), pp. 155-158, (2021); Wang Y., Li P., Tao H., Meng R., Liu J., Bayesian graphic model based user preference prediction for future personalized service provisioning, 2015 IEEE/CIC International Conference on Communications in China (ICCC), pp. 1-6, (2015); Xie G., Research on optimizing the business model of cross-border e-commerce based on blockchain technology, Academic Journal of Business & Management, 3, 4, pp. 71-74, (2021); Xie G., Huang L., Apostolidis C., Huang Z., Cai W., Li G., Assessing consumer preference for overpackaging solutions in e-commerce, International Journal of Environmental Research and Public Health, 18, 15, (2021); Yenipazarli A., Incentives for environmental research and development: Consumer preferences, competitive pressure and emissions taxation, European Journal of Operational Research, 276, 2, pp. 757-769, (2019); Zhao H., Jiang L., Su C., To defend or not to defend? How responses to negative customer review affect prospective customers’ distrust and purchase intention, Journal of Interactive Marketing, 50, 1, pp. 45-64, (2020); Zheng L., Analysis of computer-based blockchain technology in cross-border e-commerce platforms, Mobile Information Systems, 2022, (2022); Zheng L., Cui S., Yue D., Zhao X., User interest modeling based on browsing behavior, 2010 3rd International Conference on Advanced Computer Theory and Engineering (ICACTE), (2010); Zhu Q., Li Y., Agricultural research recommendation algorithm based on consumer preference model of e-commerce, Future Generation Computer Systems, 88, pp. 151-155, (2018); Zhu W., Mou J., Benyoucef M., Exploring purchase intention in cross-border E-commerce: A three stage model, Journal of Retailing and Consumer Services, 51, pp. 320-330, (2019)",null,null,"IGI Global",{"$nulls":5},1.5462234E7,null,null,null,"English","J. Organ. End User Comput.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85176215845"]
["Zuhanda M.K.; Suwilo S.; Sitompul O.S.; Mardiningsih; Caraka R.E.; Kim Y.; Noh M.","Zuhanda, Muhammad Khahfi (57204882999); Suwilo, Saib (6504683544); Sitompul, Opim Salim (46661988300); Mardiningsih (57192100322); Caraka, Rezzy Eko (57190489490); Kim, Yunho (55699527100); Noh, Maengseok (14523365800)","57204882999; 6504683544; 46661988300; 57192100322; 57190489490; 55699527100; 14523365800","Optimization of Vehicle Routing Problem in the Context of E-commerce Logistics Distribution",2023.0,"Engineering Letters",31.0,1.0,null,279.0,286.0,7.0,0.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85151963574&partnerID=40&md5=4625f24a02e10a1f43f3cd6cc87c93d9","Faculty of Engineering, Universitas Medan Area, Medan, Indonesia; Department of Mathematics, Universitas Sumatera Utara, Medan, Indonesia; Research Organization for Electronics and Informatics, National Research and Innovation Agency (BRIN), Indonesia; Department of Mathematical Sciences, Ulsan National Institute of Science and Technology, South Korea; Data and Information Sciences College of Information Technology and Convergence, Pukyong National University, Busan, South Korea","Zuhanda M.K., Faculty of Engineering, Universitas Medan Area, Medan, Indonesia; Suwilo S., Department of Mathematics, Universitas Sumatera Utara, Medan, Indonesia; Sitompul O.S., Department of Mathematics, Universitas Sumatera Utara, Medan, Indonesia; Mardiningsih, Department of Mathematics, Universitas Sumatera Utara, Medan, Indonesia; Caraka R.E., Research Organization for Electronics and Informatics, National Research and Innovation Agency (BRIN), Indonesia; Kim Y., Department of Mathematical Sciences, Ulsan National Institute of Science and Technology, South Korea; Noh M., Data and Information Sciences College of Information Technology and Convergence, Pukyong National University, Busan, South Korea","2E-MDCVRP is a multi-depot, capacity, two-echelon vehicle routing issue. Satellites make it possible to collect and sort orders. In this paper, a 2E-MDCVRP model will be designed to be applied to e-commerce. In the completion stage, the researcher developed a 2E-MDCVRP solution with two stages of completion. The first stage is finding the best route for the satellite to travel to the customer. In the first stage of work, satellites are plotted as centroids in clusters using the k-Means algorithm to obtain k-set clusters. To determine route scheduling using the RNN algorithm in determining travel routes in the second echelon. The second stage uses the trial-and-error method to determine the first echelon's routing schedule. This research aims to minimize the operational application, fuel consumption, vehicle maintenance, vehicle oil change, and handling costs. Moreover, at the end of the paper, the researcher simulate the model that has been built and test the model's effectiveness by comparing it with the classic MDCVRP model, which is similar to the Same-Day Delivery model. The test results show that the 2E-MDCVRP model can make better total distance and cost improvements than the classic MDCVRP model carried out by Same-day Delivery. © 2023, International Association of Engineers. All rights reserved.","2E-MDCVRP; E-Commerce; Last Mile; Logistics Distribution; Optimization","Electronic commerce; K-means clustering; Vehicle routing; 2e-MDCVRP; E- commerces; K-mean algorithms; Last mile; Logistic distributions; Multi depots; Optimisations; Sort orders; Travel routes; Vehicle Routing Problems; Satellites",{"$nulls":4},"National Research Foundation of Korea, NRF, (NRF-2020R1F1A1A01049528, NRF-2021R1A4A1032924, NRF-2022R1A5A1033624)","Manuscript received January 13, 2022; revised January 30, 2023. Rezzy Eko Caraka is partially supported by the National Research Foundation of Korea (NRF-2021R1A4A1032924). Yunho Kim acknowledges support from the National Research Foundation of Korea (NRF-2020R1F1A1A01049528, NRF-2022R1A5A1033624).","Sarkar B., Dey B. 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K., Binary Particle Swarm Optimization Algorithm Based on Z-shaped Probability Transfer Function to Solve 0-1 Knapsack Problem, IAENG International Journal of Computer Science, 48, 2, pp. 294-303, (2021); Shen X., Zhang X., Yu Z., A New Hybrid Cuckoo Search for the Resources-Constrained Project Scheduling Problem, IAENG International Journal of Computer Science, 48, 2, pp. 304-315, (2021); Cios K. J., Pedrycz W., Swiniarski R. W., Kurgan L. A., Data mining: A knowledge discovery approach, (2007); Gandomi A. H., Yang X. S., Talatahari S., Alavi A. H., Firefly algorithm with chaos, Communications in Nonlinear Science and Numerical Simulation, (2013); Goffe W. L., Ferrier G. D., Rogers J., Global optimization of statistical functions with simulated annealing, Journal of Economics, (1994); Hong W. C., Dong Y., Zhang W. Y., Chen L. Y., Panigrahi B. 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A., Shahbazi F., Application of SAW, TOPSIS and fuzzy TOPSIS models in cultivation priority planning for maize, rapeseed and soybean crops, Geoderma, 310, pp. 178-190, (2016); Passino K. M., Bacterial Foraging Optimization, International Journal of Swarm Intelligence Research, 1, 1, pp. 1-16, (2010); Haidar A., Verma B., A novel approach for optimizing climate features and network parameters in rainfall forecasting, Soft Computing, 22, 24, pp. 8119-8130, (2018); Kasiviswanathan K. S., Cibin R., Sudheer K. P., Chaubey I., Constructing prediction interval for artificial neural network rainfall runoff models based on ensemble simulations, Journal Hydrology, (2013); Caraka R. E., Et al., Evolving Hybrid Cascade Neural Network Genetic Algorithm Space-Time Forecasting, Symmetry (Basel), 13, 1158, pp. 1-20, (2021); Zuhairoh F., Rosadi D., Real-time forecasting of the COVID-19 epidemic using the richards model in South Sulawesi, Indonesia, Indonesian Journal of Science and Technology, 5, 3, pp. 456-462, (2020); Chew L. W., Chia W. C., minn Ang L., Seng K. P., An optimum approach for image compression: Tuned degree-K zerotree Wavelet coding, I IAENG International Journal of Computer Science, 36, 2, pp. 175-182, (2009); Caraka R. E., Chen R. C., Yasin H., Lee Y., Pardamean B., Hybrid Vector Autoregression Feedforward Neural Network with Genetic Algorithm Model for Forecasting Space-Time Pollution Data, Indonesian Journal of Science and Technology, 6, pp. 243-266, (2021); Niku J., Brooks W., Herliansyah R., Hui F. K. C., Taskinen S., Warton D. I., Efficient estimation of generalized linear latent variable models, PLoS One, 14, 5, pp. 1-20, (2019); Zhang X., Yu Z., Hu Y., Yang J., Milling Force Prediction of Titanium Alloy Based on Support Vector Machine and Ant Colony Optimization, IAENG International Journal of Computer Science, 48, 2, pp. 223-235, (2021); Chen G., Zhang A., Zhao C., Zhang Z., Optimal Placement and Capacity of Combined DGs and SCs in Radial Distribution Networks Based on PSO-OS Algorithm, IAENG International Journal of Computer Science, 48, 2, pp. 236-249, (2021); Hu G., Du B., Wang X., Wei G., An enhanced black widow optimization algorithm for feature selection, Knowledge-Based Systems, 235, (2022); Huang H., Xue C., Zhang W., Guo M., Torsion design of CFRP-CFST columns using a data-driven optimization approach, Engineering Structures, 251, (2022); Aliramezani M., Koch C. R., Shahbakhti M., Modeling, diagnostics, optimization, and control of internal combustion engines via modern machine learning techniques: A review and future directions, Progress in Energy and Combustion Science, 88, (2020); Zuhanda M.K., Suwilo S., Sitompul O.S., Mardiningsih, A combination k-means clustering and 2-opt algorithm for solving the two echelon e-commerce logistic distribution, Logforum, 18, 2, pp. 213-225, (2022)","R.E. Caraka; Research Organization for Electronics and Informatics, National Research and Innovation Agency (BRIN), Indonesia; email: rezzy.eko.caraka@brin.go.id; Y. Kim; Department of Mathematical Sciences, Ulsan National Institute of Science and Technology, South Korea; email: yunhokim@unist.ac.kr",null,"International Association of Engineers",{"$nulls":5},"1816093X",null,null,null,"English","Eng. Lett.","Article","Final",null,"Scopus","2-s2.0-85151963574"]
["Zhao H.; Li M.","Zhao, Hongxiang (58911219900); Li, Meiyan (57215305311)","58911219900; 57215305311","Study on Joint Distribution Mode and Evolutionary Game of Express Enterprises in Rural Areas",2023.0,"Sustainability (Switzerland)",15.0,2.0,1520.0,null,null,null,1.0,"10.3390/su15021520","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85169081651&doi=10.3390%2fsu15021520&partnerID=40&md5=a18c13daa1a2cd212af26e490e5d19e3","College of Energy and Mining Engineering, Shandong University of Science and Technology, Qingdao, 266590, China","Zhao H., College of Energy and Mining Engineering, Shandong University of Science and Technology, Qingdao, 266590, China; Li M., College of Energy and Mining Engineering, Shandong University of Science and Technology, Qingdao, 266590, China","Express delivery in rural areas of China has many problems, such as high delivery cost and low efficiency. As an effective way to solve the difficulties of rural delivery, it is important to study the innovation and application of a joint distribution model. In the background, this paper takes express delivery enterprises in rural areas as the research object. First, it proposes to construct a three-level “county-town-village” joint distribution system in which e-commerce platforms participate. Next, it establishes an evolutionary game model of express delivery enterprise joint distribution alliance and solves it. Finally, the model is analyzed through numerical simulation. The results show that the distribution system of express delivery enterprises in rural areas is affected by excess returns, early input costs, operating costs, cooperation risks, penalty costs, learning and absorption capacity of enterprises and other factors. After introducing the rewards and punishments of e-commerce platforms as an independent influencing factor in the evolutionary game model, the shorter time for express companies to finally make cooperation strategies indicates that the rewards and punishments of e-commerce platforms have a positive significance in promoting the rapid development and stable operation of a rural logistics joint distribution system. © 2023 by the authors.","evolutionary game; joint distribution system; numerical analysis; rural express; system stability","China; absorption; distribution system; electronic commerce; innovation",{"$nulls":4},"Effect Evaluation System of First-Class Undergraduate Majors in Shandong Province, (2021JXY058); Research on the Development Trend and Countermeasures of Industrial Internet in Shandong Province, (2021RZB02007); National Natural Science Foundation of China, NSFC, (71971130)","This research was funded by the Natural Science Foundation of China (grant No. 71971130), Research on the Construction Path and Effect Evaluation System of First-Class Undergraduate Majors in Shandong Province (grant No. 2021JXY058) and Research on the Development Trend and Countermeasures of Industrial Internet in Shandong Province (grant No. 2021RZB02007).","The 50th China Internet Development Statistics Report, (2022); Statistical Bulletin of Postal Industry Development 2021, (2022); China Statistical Yearbook, (2021); Zhou J., Liu C., Xu W., Li L., Zhou M., Hou H., Logistics Network Structure and self-organizing effect of Express enterprises under the background of E-commerce: A case study of ZTO Express, Econ. 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Li; College of Energy and Mining Engineering, Shandong University of Science and Technology, Qingdao, 266590, China; email: skd994322@sdust.edu.cn",null,"Multidisciplinary Digital Publishing Institute (MDPI)",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85169081651"]
["Pilati F.; Tronconi R.","Pilati, Francesco (7004935679); Tronconi, Riccardo (57225953101)","7004935679; 57225953101","Multi-objective optimisation for sustainable few-to-many pickup and delivery vehicle routing problem",2023.0,"International Journal of Production Research",{"$nulls":6},0.0,"10.1080/00207543.2023.2220826","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85163064007&doi=10.1080%2f00207543.2023.2220826&partnerID=40&md5=e54076ac95126c6c5dd1adf978c9efad","Department of Industrial Engineering, University of Trento, Trento, Italy","Pilati F., Department of Industrial Engineering, University of Trento, Trento, Italy; Tronconi R., Department of Industrial Engineering, University of Trento, Trento, Italy","E-commerce is a continuously growing sector significantly affected by sustainability issues during the last few years. To deal with economic, environmental and social sustainability aspects, e-commerce platforms consolidate orders to pick-up several requests from the same location, defining the so-called Few-to-Many Pick-up and Delivery Vehicle Routing Problem (F-M VRPPD). The proposed contribution addresses the optimisation of this problem by developing a multi-objective simulated annealing algorithm distinguished by four tailored Local Search (LS) operators specifically developed to increase the probability to identify feasible solutions and decrease the computational time. This algorithm is validated with several instances of a case study e-commerce platform based in an European mountain region. Firstly, the original LS operators are compared to benchmark literature ones to solve identical problems, reporting better performance in 84% of these instances. Furthermore, for the most relevant scenarios significant results are presented and discussed concerning the economic, environmental and social performance of the defined solutions according to the characteristics of the instances, as the routes height profile and the drivers’ metabolic energy consumption. The tri-dimensional Pareto frontiers suggest how through a slight worsening in the economic objective function it is possible to improve the social one by up to 18.3% on average. © 2023 Informa UK Limited, trading as Taylor & Francis Group.","environmental impact; multi-objective; pick-up and delivery; social sustainability; Vehicle routing problem","Benchmarking; Electronic commerce; Energy utilization; Environmental impact; Pickups; Simulated annealing; Sustainable development; Vehicle routing; Vehicles; Commerce platforms; Delivery vehicle; E- commerces; Local search operators; Multi objective; Multi-objectives optimization; Pickup and delivery; Social sustainability; Sustainability issues; Vehicle Routing Problems; Multiobjective optimization",{"$nulls":6},"Abdullahi H., Reyes-Rubiano L., Ouelhadj D., Faulin J., Juan A.A., Modelling and Multi-Criteria Analysis of the Sustainability Dimensions for the Green Vehicle Routing Problem, European Journal of Operational Research, 292, 1, pp. 143-154, (2021); 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Pilati; Department of Industrial Engineering, University of Trento, Trento, via Sommarive 9, 38123, Italy; email: francesco.pilati@unitn.it",null,"Taylor and Francis Ltd.",{"$nulls":5},207543.0,null,"IJPRB",null,"English","Int J Prod Res","Article","Article in press",null,"Scopus","2-s2.0-85163064007"]
["Liu S.","Liu, Shihui (58314088600)",5.83140886E10,"Application of the multi-objective model under the fuzzy differential equation to logistics operation of internet of things",2023.0,"International Journal of Grid and Utility Computing",14.0,"2024-03-02",null,205.0,215.0,10.0,0.0,"10.1504/IJGUC.2023.131006","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85161906360&doi=10.1504%2fIJGUC.2023.131006&partnerID=40&md5=432b1cf67bd66f091099ccec4223348b","College of Science and Technology, Ningbo University, Cixi, China","Liu S., College of Science and Technology, Ningbo University, Cixi, China","This paper aims to explore the application of the Multi-Objective Model (MOM) in the logistics operation of an e-commerce platform. E-commerce is a new business model, and people are studying the use of various technologies to optimise its operation mode. On this basis, the logistics operation on the e-commerce platform is studied by using the method of moments based on deep learning, Fuzzy Differential Equations (FDEs) and the Internet of Things. On the ImageNet data set, the parameter initialisation of the network is trained and detected. The initial learning rate of the network is 0.0003, and 45,000 iterations are needed to reduce the learning rate. The convergence and stability of FDEs are of great significance for the accuracy of data on e-commerce platforms. The results show that the correlation between web page accessibility and revenue on the e-commerce platform is 0.011, and this data acquisition is based on traditional methods. Copyright © 2023 Inderscience Enterprises Ltd.","e-commerce; fuzzy differential equation; internet of things; logistics; multi-objective model","Data acquisition; Deep learning; Differential equations; Electronic commerce; Learning algorithms; Method of moments; Websites; Commerce platforms; Data set; E- commerces; Fuzzy differential equations; Learning rates; Logistic operations; Multiobjective modeling; New business models; Operation mode; Various technologies; Internet of things",{"$nulls":6},"Amin R., Nazir S., Garcia-Magarino I., A collocation method for numerical solution of nonlinear delay integrodifferential equations for wireless sensor network and internet of things, Sensors, 20, 7, (2020); Anter A.M., Ali M., Feature selection strategy based on hybrid crow search optimization algorithm integrated with chaos theory and fuzzy c-means algorithm for medical diagnosis problems, Soft Computing, 24, 3, pp. 1565-1584, (2020); Baladeh A.E., Cheraghi M., Khakzad N., A multi-objective model to optimal selection of safety measures in oil and gas facilities, Process Safety and Environmental Protection, 125, pp. 71-82, (2019); Bhatti A., Akram H., Basit H.M., Et al., E-commerce trends during COVID-19 pandemic, International Journal of Future Generation Communication and Networking, 13, 2, pp. 1449-1452, (2020); Bouzembrak Y., Kluche M., Gavai A., Et al., Internet of things in food safety: literature review and a bibliometric analysis, Trends in Food Science and Technology, 94, pp. 54-64, (2019); Boysen N., De Koster R., Weidinger F., Warehousing in the e-commerce era: a survey, European Journal of Operational Research, 277, 2, pp. 396-411, (2019); Byun J., Woo S., Tolcha Y., Et al., Oliot epcis: engineering a web information system complying with epc information services standard towards the internet of things, Computers in Industry, 94, pp. 82-97, (2018); Carlos-Mancilla M.A., Luque-Vega L.F., Guerrero-Osuna H.A., Et al., Educational mechatronics and internet of things: a case study on dynamic systems using meiot weather station, Sensors, 21, 1, (2020); Ding Y., Jin M., Li S., Et al., Smart logistics based on the internet of things technology: an overview, International Journal of Logistics Research and Applications, 24, 4, pp. 323-345, (2021); Han W., The analysis on Chinese e-commerce tax losses based on the perspective of information asymmetry, Electronic Commerce Research, 20, 3, pp. 651-677, (2020); Huang Y., Chai Y., Liu Y., Et al., Architecture of next-generation e-commerce platform, Tsinghua Science and Technology, 24, 1, pp. 18-29, (2018); Ingaldi M., Ulewicz R., Evaluation of quality of the e-commerce service, International Journal of Ambient Computing and Intelligence (IJACI), 9, 2, pp. 55-66, (2018); Khan H.U., Uwemi S., Possible impact of e-commerce strategies on the utilisation of e-commerce in Nigeria, International Journal of Business Innovation and Research, 15, 2, pp. 231-246, (2018); Kumar S., Tiwari P., Zymbler M., Internet of Things is a revolutionary approach for future technology enhancement: a review, Journal of Big Data, 6, 1, pp. 1-21, (2019); Kwilinski A., Volynets R., Berdnik I., Et al., E-commerce: concept and legal regulation in modern economic conditions, Journal of Legal, Ethical and Regulatory Issues, 22, pp. 1-6, (2019); Lee H.C., Ke K.H., Monitoring of large-area IoT sensors using a LoRa wireless mesh network system: design and evaluation, IEEE Transactions on Instrumentation and Measurement, 67, 9, pp. 2177-2187, (2018); Li L., Xu Y., Zhang Z., Et al., A prediction-based charging policy and interference mitigation approach in the wireless powered internet of things, IEEE Journal on Selected Areas in Communications, 37, 2, pp. 439-451, (2018); Pelaez G., Izquierdo P., Rubio H., Et al., Dynamics and embedded internet of things input shaping control for overhead cranes transporting multibody payloads, Sensors, 18, 6, (2018); Qu Z., Zhang G., Hong T., Et al., Architecture and network model of time-space uninterrupted space information network, IEEE Access, 7, pp. 27677-27688, (2019); Radulescu R., Mannion P., Roijers D.M., Et al., Multi-objective multi-agent decision making: a utility-based analysis and survey, Autonomous Agents and Multi-Agent Systems, 34, 1, pp. 1-52, (2020); Rizzo L., Longo L., An empirical evaluation of the inferential capacity of defeasible argumentation, non-monotonic fuzzy reasoning and expert systems, Expert Systems with Applications, 147, (2020); Rong H., Ge M., Zhang G., Et al., An approach for detecting fault lines in a small current grounding system using fuzzy reasoning spiking neural p systems, International Journal of Computers Communications and Control, 13, 4, pp. 521-536, (2018); Sennan S., Somula R., Luhach A.K., Et al., Energy efficient optimal parent selection based routing protocol for internet of things using firefly optimization algorithm, Transactions on Emerging Telecommunications Technologies, 32, 8, (2021); Su L., Peng Y., Kong R., Et al., Impact of e-commerce adoption on farmers’ participation in the digital financial market: evidence from rural China, Journal of Theoretical and Applied Electronic Commerce Research, 16, 5, pp. 1434-1457, (2021); Suppatvech C., Godsell J., Day S., The roles of internet of things technology in enabling servitized business models: a systematic literature review, Industrial Marketing Management, 82, pp. 70-86, (2019); Thaichon P., Surachartkumtonkun J., Quach S., Et al., Hybrid sales structures in the age of e-commerce, Journal of Personal Selling and Sales Management, 38, 3, pp. 277-302, (2018); Tian L., Vakharia A.J., Tan Y., Et al., Marketplace, reseller, or hybrid: strategic analysis of an emerging E commerce model, Production and Operations Management, 27, 8, pp. 1595-1610, (2018); Tran L.T.T., Managing the effectiveness of e-commerce platforms in a pandemic, Journal of Retailing and Consumer Services, 58, (2021); Wang H., Chen J., Research on the transformation strategy of international port logistics service under the cross border e-commerce environment, International Journal of Innovative Computing Information and Control, 15, 2, pp. 803-810, (2019); Wang J., Fei Z., Chang Q., Et al., Energy saving operation of manufacturing system based on dynamic adaptive fuzzy reasoning Petri net, Energies, 12, 11, (2019); Yu D., Xu Z., Wang W., Bibliometric analysis of fuzzy theory research in China: a 30-year perspective, Knowledge-Based Systems, 141, pp. 188-199, (2018); Zarbakhshnia N., Soleimani H., Goh M., Et al., A novel multi-objective model for green forward and reverse logistics network design, Journal of Cleaner Production, 208, pp. 1304-1316, (2019); Zhang F., Kodituwakku H.A.D.E., Hines J.W., Et al., Multilayer data-driven cyber-attack detection system for industrial control systems based on network, system, and process data, IEEE Transactions on Industrial Informatics, 15, 7, pp. 4362-4369, (2019)","S. Liu; College of Science and Technology, Ningbo University, Cixi, China; email: liushihui@nbu.edu.cn",null,"Inderscience Publishers",{"$nulls":5},"1741847X",null,null,null,"English","Int. J. Grid Util. Comput.","Article","Final",null,"Scopus","2-s2.0-85161906360"]
["Li L.","Li, Lifeng (58577352200)",5.85773522E10,"Deep Learning Algorithm Aided E-Commerce Logistics Node Layout Optimization Based on Internet of Things Network",2023.0,"EAI Endorsed Transactions on Scalable Information Systems",10.0,4.0,null,1.0,13.0,12.0,0.0,"10.4108/eetsis.v10i3.3089","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85171281474&doi=10.4108%2feetsis.v10i3.3089&partnerID=40&md5=02bb851525484e6e20cd57b7a397206f","Shenyang polytechnic college, Liaoning, Shenyang, 110045, China","Li L., Shenyang polytechnic college, Liaoning, Shenyang, 110045, China","INTRODUCTION: In recent years, e-commerce has shown a booming trend. Influenced by e-commerce, people's logistics needs have also increased sharply in recent years. OBJECTIVES: Research on the node layout and optimization of e-commerce logistics is conducive to improving the scientificity and rationality of logistics node layout, improving logistics distribution efficiency, reducing logistics distribution costs, and better meeting consumers’ logistics needs. However, due to the unreasonable layout of logistics nodes in some areas, it has brought huge logistics cost investment to e-commerce companies, and also laid hidden dangers for the long-term development of e-commerce companies. METHODS: Based on this, this paper studied the node layout and optimization of e-commerce logistics by using IoT big data and deep learning algorithms, and proposed an improved logistics node layout scheme based on IoT big data and deep learning algorithms. The experimental research was carried out from five aspects: the transportation cost of logistics, the efficiency of logistics distribution, the accuracy of logistics information transmission, the location and traffic conditions of logistics nodes, and the evaluation of the plan by e-commerce enterprises. RESULTS: The research results showed that the improved logistics node layout scheme can improve the efficiency of logistics distribution by 3.69% and the accuracy of logistics information transmission by 4.34%, and can reduce the logistics transportation cost of e-commerce enterprises. CONCLUSION: The node locations selected by the improved logistics node layout scheme are more reasonable, and e-commerce companies have higher evaluations of the improved logistics node layout scheme. © 2023 Lifeng Li, licensed to EAI.","Deep Learning Algorithm; E-commerce Logistics; Improved Logistics Node Layout Scheme; IoT Big Data; Logistics Node Layout and Optimization","Behavioral research; Cost reduction; Deep learning; Efficiency; Electronic commerce; Internet of things; Learning algorithms; Deep learning algorithm; E- commerces; E-commerce logistic; Improved logistic node layout scheme; IoT big data; Layout schemes; Logistic node layout and optimization; Node layouts; Optimisations; Big data",{"$nulls":6},"He L Z, Pang Y., Research on the layout and optimization of multi-level fresh fruit and vegetable e-commerce logistics nodes in county and rural areas, Logistics Engineering and Management, 44, 4, pp. 84-88, (2022); Pathakota P, Zaid K, Dhara A., Learning to Minimize Cost-to-Serve for Multi-Node Multi-Product Order Fulfilment in Electronic Commerce, Computer Engineering and Applications, 12, 4, pp. 36-38, (2021); Zou Y, Si W., Research on Logistics Distribution in E-commerce Environment Based on Particle Swarm Optimization Algorithm, Journal of Physics: Conference Series, 1881, 4, pp. 42056-42059, (2021); Beranek L, Remes R., Distribution of Node Characteristics in Evolving Tripartite Network, Entropy, 22, 3, pp. 235-263, (2020); Wang X L, Tang J R., Rural E-commerce Logistics Layout and Rural Residents’ Consumption–Tracking Based on Rural Taobao, Business Economics Research, 23, 7, pp. 77-81, (2021); Wang H Z., Optimization of logistics node layout of international dry ports in Shaanxi Province under the background of “One Belt and One Road”, Logistics Technology, 37, 9, pp. 66-69, (2018); Wu M W, Yao Z S., Layout of cold chain logistics nodes in Gansu Province under the “One Belt, One Road” initiative, Integrated Transportation, 19, 4, pp. 66-67, (2021); Chen Dongliang, Wawrzynski Pawel, Lv Zhihan, Cyber Security in Smart Cities: A Review of Deep Learning-based Applications and Case Studies, Sustainable Cities and Society, (2020); Lv H., Analysis on the development mode of intelligent logistics based on the Internet of Things and cloud computing in the era of big data, Communication World, 12, 5, pp. 106-110, (2017); Li S S., Application of smart logistics system based on Internet of Things in the era of big data, Electronic Technology and Software Engineering, 14, 6, pp. 189-190, (2018); Hopkins J, Hawking P., Big Data Analytics and IoT in logistics: a case study, The International Journal of Logistics Management, 29, 6, pp. 575-591, (2018); Raman S, Patwa N, Niranjan I., Impact of big data on supply chain management, International Journal of Logistics Research and Applications, 42, 7, pp. 579-596, (2018); Zhang X B, Li W J, Zhou J., Research on logistics distribution route optimization algorithm based on deep learning, Modern Computer: Mid-term, 14, 5, pp. 14-20, (2017); Li M, Li W J., Research on swarm intelligence recommendation algorithm for logistics service transactions based on deep learning, Modern Computer, 27, 34, pp. 1-11, (2021); Li T J, Huang B, Liu J Y., Application of Convolutional Neural Network Object Detection Algorithm in Logistics Warehouse, Computer Engineering, 44, 6, pp. 176-181, (2018); Li Y, Zuo Y, Song H, Lv Z, Deep learning in security of internet of things, IEEE Internet of Things Journal, 99, (2021); Wang X C, Yang Y P, Ji L G., The application of entropy weight coefficient method in the planning and layout of grain logistics nodes in the new era-taking coastal passages as an example, Cereals, Oils and Food Science and Technology, 30, 4, pp. 23-27, (2022); Chen H L, Zhao S, Yang H B., Spatial layout optimization of logistics supply chain nodes around the capital circulation circle, Economic Geography, 40, 7, pp. 115-123, (2020); Liu Z, Pan M, Li Y M., Research on node layout of logistics network in Henan Province based on PCA-SNA model, Logistics Technology, 27, 3, pp. 28-34, (2019); Hurtado P A, Dorneles C, Frazzon E., Big Data application for E-commerce's Logistics: A research assessment and conceptual model, IFAC-PapersOnLine, 52, 13, pp. 838-843, (2019); Dou J., Analysis and Research on Influencing Factors of Gansu Logistics Demand Based on Grey Relevance Model——In the Background of One Belt One Road, Logistics Engineering and Management, 24, 5, pp. 47-50, (2017); Lv Y L., Research on regional logistics demand forecasting based on support vector machine, Chinese Market, 37, 2, pp. 144-147, (2018); Zhou W., Lei X., Priority-aware resource scheduling for UAV-mounted mobile edge computing networks, IEEE Trans. Vehic. Tech, PP, 99, pp. 1-6, (2023); Zhou W., Zhou F., Profit maximization for cache-enabled vehicular mobile edge computing networks, IEEE Trans. Vehic. Tech, PP, 99, pp. 1-6, (2023); Zheng X., Gao C., Intelligent computing for WPT-MEC aided multi-source data stream, EURASIP J. Adv. Signal Process, 2023, 1; Wu Y., Gao C., Intelligent resource allocation scheme for cloud-edge-end framework aided multi-source data stream, EURASIP J. Adv. Signal Process, 2023, 1; Ling J., Gao C., DQN based resource allocation for NOMA-MEC aided multi-source data stream, EURASIP J. Adv. Signal Process, 2023, 44, pp. 1-15, (2023); He L., Tang X., Learning-based MIMO detection with dynamic spatial modulation, IEEE Transactions on Cognitive Communications and Networking, PP, 99, pp. 1-12, (2023)","L. Li; Shenyang polytechnic college, Shenyang, Liaoning, 110045, China; email: 2016122476@jou.edu.cn",null,"European Alliance for Innovation",{"$nulls":5},2.0329407E7,null,null,null,"English","Endor. Trans. Scalable. Inf. Syst.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85171281474"]
["Kim M.; Kim Y.","Kim, Mirye (57562410000); Kim, Youngmin (57295082600)","57562410000; 57295082600","Parcel Classification and Positioning of Intelligent Parcel Storage System Based on YOLOv5",2023.0,"Applied Sciences (Switzerland)",13.0,1.0,437.0,null,null,null,6.0,"10.3390/app13010437","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85145550974&doi=10.3390%2fapp13010437&partnerID=40&md5=10e6e80cb6077f5ace57e3de130cef11","Department of Systems Engineering, Ajou University, Suwon, 16499, South Korea","Kim M., Department of Systems Engineering, Ajou University, Suwon, 16499, South Korea; Kim Y., Department of Systems Engineering, Ajou University, Suwon, 16499, South Korea","Parcel storage provides last-mile delivery services as part of the logistics process. In order to build an intelligent system for parcel storage, we conducted a study on parcel box recognition using AI’s deep learning technology. Box detection and location estimation studies were conducted using the YOLOv5 model for parcel recognition, and this model is presently being applied to many studies because it has excellent object recognition and is faster than previous models. The YOLOv5 model is classified into small, medium, large, and xlarge according to the size and performance of the model. In this study, these four models were compared and analyzed to perform an experiment showing the optimal parcel box recognition performance. As a result of the experiment, it was determined that the precision, recall, and F1 of the YOLOv5large model were 0.966, 0.899, and 0.932, respectively, showing a stronger performance than the other models. Additionally, the size of the YOLOv5large is half that of YOLOv5xlarge, and the YOLOv5large showed the optimal performance in object recognition of the parcel box. Therefore, it seems that the basis for building an intelligent parcel storage system, which shows optimal efficiency in real time using the YOLOv5large model, can be laid through the parcel object recognition experiment conducted in this study. © 2022 by the authors.","box detection; e-commerce logistics; object detection; parcel storage system; YOLOv5",{"$nulls":5},"Korea Evaluation Institute of Industrial Technology, KEIT, (20014664)","This work was supported by a grant from R&D program of the Korea Evaluation Institute of Industrial Technology (20014664).","Louis E., Courier Management System, Master’s Thesis, (2021); Wang W., Zhong Y.C., Ma J.M., The status quo and future of smart parcel cabinets in the development of smart technology in my country’s logistics express industry, Mod. Bus, 34, pp. 20-21, (2018); Zhang S.Z., Lee C.K.M., Flexible vehicle scheduling for urban last mile logistics: The emerging technology of shared reception box, Proceedings of the 2016 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM 2016), pp. 1913-1917; Kolarovszki P., Vaculik J., Intelligent storage system based on automatic identification, Transp. Telecommun. J, 15, pp. 185-195, (2014); Muzhir S., Al-Ani M., Packages tracking using RFID technology, Int. J. Bus. ICT, 1, pp. 12-20, (2015); Mohd A., Rashid R.A., Hamid A.H.F.A., Sarijari M.A., Rahim M.R.A., Sayuti H., Rashid M.R.A., Development of android-based apps for courier service management, Indones. J. Electr. Eng. Comput. Sci, 15, pp. 1027-1036, (2019); Bushanam V.N., Reddy C.H., An Efficient CNN a deep learning approach applied on the image matching context, Int. J. Eng. Technol, 7, pp. 507-512, (2018); Kim M., Kwon Y., Kim J., Kim Y., Image Classification of Parcel Boxes under the Underground Logistics System Using CNN MobileNet, Appl. Sci, 12, (2022); Kim M., Improvement of Recognition Performance through Refinement of Parcel Damage Classification Algorithm based on CNN, Ph.D. Thesis, (2022); Chen X., E-Commerce Logistics Inspection System Based on Artificial Intelligence Technology in the Context of Big Data, Secur. Commun. Netw, 2022, (2022); Yao J., Qi J., Zhang J., Shao H., Yang J., Li X., A real-time detection algorithm for Kiwifruit defects based on YOLOv5, Electronics, 10, (2021); Ruan J., Design and Implementation of Target Detection Algorithm Based on YOLO, (2019); Redmon J., Divvala S., Girshick R., Farhadi A., You only look once: Unified, real-time object detection, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 79-788; Redmon J., Farhadi A., YOLO9000: Better, faster, stronger, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 7263-7271; Redmon J., Farhadi A., Yolov3: An incremental improvement, arXiv, (2018); Bochkovskiy A., Wang C.Y., Liao H.Y.M., Yolov4: Optimal speed and accuracy of object detection, arXiv, (2020); Jiang P., Ergu D., Liu F., Cai Y., Ma B., A Review of Yolo algorithm developments, Procedia Comput. Sci, 199, pp. 1066-1073, (2022); Jamtsho Y., Riyamongkol P., Waranusast R., Real-time Bhutanese license plate localization using YOLO, ICT Express, 6, pp. 121-124, (2020); Fan S., Liang X., Huang W., Zhang V.J., Pang Q., He X., Li L., Zhang C., Real-time defects detection for apple sorting using NIR cameras with pruning-based YOLOV4 network, Comput. Electron. Agric, 193, (2022); Chen S., Yang D., Liu J., Tian Q., Zhou F., Automatic weld type classification, tacked spot recognition and weld ROI determination for robotic welding based on modified YOLOv5, Robot. Comput.-Integr. Manuf, 81, (2023); Song Q., Li S., Bai Q., Yang J., Zhang X., Li Z., Duan Z., Object Detection Method for Grasping Robot Based on Improved YOLOv5, Micromachines, 12, (2021); Benjumea A., Teeti I., Cuzzolin F., Bradley A., YOLO-Z: Improving small object detection in YOLOv5 for autonomous vehicles, arXiv, (2021); Dong X., Yan S., Duan C., A lightweight vehicles detection network model based on YOLOv5, Eng. Appl. Artif. Intell, 113, (2022); Xiong R., Yang Y., He D., Zheng K., Zheng S., Xing C., Liu T., On layer normalization in the transformer architecture, Proceedings of the International Conference on Machine Learning (PMLR 2020), 119, pp. 10524-10533; Zhou F., Zhao H., Nie Z., Safety helmet detection based on YOLOv5, Proceedings of the 2021 IEEE International Conference on Power Electronics, Computer Applications (ICPECA), pp. 6-11; Yang Y., Zhang L., Du M., Bo J., Liu H., Ren L., Deen M.J., A comparative analysis of eleven neural networks architectures for small datasets of lung images of COVID-19 patients toward improved clinical decisions, Comput. Biol. Med, 139, (2021); Davis J., Goadrich M., The relationship between Precision-Recall and ROC curves, Proceedings of the 23rd international conference on Machine learning, pp. 233-240; Nepal U., Eslamiat H., Comparing YOLOv3, YOLOv4 and YOLOv5 for autonomous landing spot detection in faulty UAVs, Sensors, 22, (2011); Maxwell A.E., Warner T.A., Guillen L.A., Accuracy assessment in convolutional neural network-based deep learning remote sensing studies—Part 1: Literature review, Remote Sens, 13, (2021)","Y. Kim; Department of Systems Engineering, Ajou University, Suwon, 16499, South Korea; email: pretty0m@ajou.ac.kr",null,"MDPI",{"$nulls":5},2.0763417E7,null,null,null,"English","Appl. Sci.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85145550974"]
["Nguyen Q.-T.; Patrix J.; Oulmakki O.; Ramirez-Rios D.G.; Verny J.","Nguyen, Quoc-Thông (57204874715); Patrix, Jérémy (56132097300); Oulmakki, Ouail (58186615300); Ramirez-Rios, Diana G. (35957015800); Verny, Jérôme (30767875200)","57204874715; 56132097300; 58186615300; 35957015800; 30767875200","Estimating costs and CO2 emissions for last mile delivery of groceries in Paris using alternative modes and routing strategies",2023.0,"International Journal of Logistics Research and Applications",{"$nulls":6},0.0,"10.1080/13675567.2023.2283074","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85177554727&doi=10.1080%2f13675567.2023.2283074&partnerID=40&md5=97512630bd943eef9c212789618f92c8","Sofft Industries, Lyon, France; Opal Research, Rouen, France; Neoma Business School, Rouen, France; Department of Industrial and Systems Engineering, The State University of New York at Buffalo, Buffalo, NY, United States","Nguyen Q.-T., Sofft Industries, Lyon, France; Patrix J., Opal Research, Rouen, France; Oulmakki O., Neoma Business School, Rouen, France; Ramirez-Rios D.G., Department of Industrial and Systems Engineering, The State University of New York at Buffalo, Buffalo, NY, United States; Verny J., Neoma Business School, Rouen, France","Last mile delivery is a significant component in the growth of e-commerce, especially in urban areas. The deliveries in dense cities cause several serious issues such as air/noise pollution and congestion. In this study, we compare the financial costs and CO2 emissions from different last mile delivery strategies of grocery bins in a scenario in Paris with four types of delivery vehicles (diesel/electric vans, cargo bikes, and autonomous delivery vehicles). We use costs associated with each vehicle type, location data with constraints for establishments in Paris, and delivery scenarios obtained by solving the vehicle routing problem for an overall cost comparison. We consider an economic analysis of the daily delivery to optimise the costs and estimate the CO2 emissions. The results highlight the competitiveness among last mile delivery and reflect the transition knowing the transport expenses since 2018: electric van costs become competitive with diesel ones, it concluded by some perspectives with cargo bikes and autonomous vehicles with their current limits. The strategies show a great impact on overall cost and emissions, which are vital in the development of sustainable urban last-mile delivery. © 2023 Informa UK Limited, trading as Taylor & Francis Group.","clustering; delivery costs; last mile problem; urban delivery; vehicle emission costs; Vehicle routing problem",{"$nulls":5},"French Environment and Energy Management Agency; French Ministry of Ecology; Ministère de l'Education Nationale, de l'Enseignement Superieur et de la Recherche, MESR","ADEME: French Environment and Energy Management Agency, under the supervision of the French Ministry of Ecology and the Ministry of Higher Education and Research. 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Verny; Neoma Business School, Rouen, France; email: jerome.verny@neoma-bs.fr",null,"Taylor and Francis Ltd.",{"$nulls":5},1.3675567E7,null,null,null,"English","Int. J. Logist. Res. Applic.","Article","Article in press",null,"Scopus","2-s2.0-85177554727"]
["Shcherbakov R.A.; Privorotskaya S.G.; Vishnevskiy K.O.","Shcherbakov, Roman A. (57384760400); Privorotskaya, Sofya G. (57385678100); Vishnevskiy, Konstantin O. (57194113437)","57384760400; 57385678100; 57194113437","Diffusion of digital technologies in the face of external shocks: The case of the COVID-19 pandemic",2023.0,"Business Informatics",17.0,1.0,null,37.0,52.0,15.0,0.0,"10.17323/2587-814X.2023.1.37.52","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85160315641&doi=10.17323%2f2587-814X.2023.1.37.52&partnerID=40&md5=f019091776b25c8a26bd74e023a9cab2","Laboratory for Science and Technology Studies, Institute for Statistical Studies and Economics of Knowledge, HSE University, 20, Myasnitskaya Street, Moscow, 101000, Russian Federation; Digital Technologies Research Unit, Digital Economics Centre, Institute for Statistical Studies and Economics of Knowledge, HSE University, 20, Myasnitskaya Street, Moscow, 101000, Russian Federation; Digital Economics Centre, Institute for Statistical Studies and Economics of Knowledge, HSE University, 20, Myasnitskaya Street, Moscow, 101000, Russian Federation","Shcherbakov R.A., Laboratory for Science and Technology Studies, Institute for Statistical Studies and Economics of Knowledge, HSE University, 20, Myasnitskaya Street, Moscow, 101000, Russian Federation; Privorotskaya S.G., Digital Technologies Research Unit, Digital Economics Centre, Institute for Statistical Studies and Economics of Knowledge, HSE University, 20, Myasnitskaya Street, Moscow, 101000, Russian Federation; Vishnevskiy K.O., Laboratory for Science and Technology Studies, Institute for Statistical Studies and Economics of Knowledge, HSE University, 20, Myasnitskaya Street, Moscow, 101000, Russian Federation, Digital Economics Centre, Institute for Statistical Studies and Economics of Knowledge, HSE University, 20, Myasnitskaya Street, Moscow, 101000, Russian Federation","This paper investigates the impact of external shocks on the spread of digital technologies. Using the example of the COVID-19 pandemic, we identify and describe four patterns that reflect the uneven response of different digital technologies to external conditions undergoing transformation. The patterns differ in both the magnitude of the pandemic's impact and the timing of the resulting effects. Video conferencing, business continuity and telemedicine services showed a dramatic increase in demand at the beginning of COVID-19 and a gradual decline in the later stages. A more moderate response in the early weeks of the pandemic is typical of e-commerce and online entertainment. Delayed effects are seen in digital logistics services and digital currencies, which reacted much later than other technologies. Finally, a slow decline in significance after the pandemic began has been observed for biometrics and cybersecurity technologies. Similar patterns may describe the transformation of the spread of digital technologies not only under the influence of COVID-19, but also in the face of dramatic economic and social changes of other origins. © 2023 The Author(s).","COVID-19; digital diffusion; digital technology; digital transformation; economic shock; market adaptation",{"$nulls":5},"National Research University Higher School of Economics, ВШЭ","This article was prepared within the Basic Research Program of the National Research University Higher School of Economics.","Sokhulu L.H., Students' experiences of using digital technologies to address their personal research needs during the COVID-19 lockdown, African Identities, 19, 4, pp. 436-452, (2021); Beardsley M., Albo L., Aragon P., Hernandez-Leo D., Emergency education effects on teacher abilities and motivation to use digital technologies, British Journal of Educational Technology, 52, 4, pp. 1455-1477, (2021); Bokolo A.J., Use of telemedicine and virtual care for remote treatment in response to COVID-19 pandemic, Journal of Medical Systems, 44, 7, pp. 1-9, (2020); Papadopoulos T., Baltas K.N., Balta M.E., The use of digital technologies by small and medium enterprises during COVID-19: Implications for theory and practice, International Journal of Information Management, 55, (2020); Oldekop J.A., Horner R., Hulme D., Et al., COVID-19 and the case for global development, World Development, 134, (2020); Caselli F., Coleman W.J., Cross-country technology diffusion: The case of computers, American Economic Review, 91, 2, pp. 328-335, (2001); Geroski P.A., Models of technology diffusion, Research Policy, 29, 4-5, pp. 603-625, (2000); Mayer J., Technology diffusion, human capital and economic growth in developing countries, (2001); Lin H.F., Lin S.M., Determinants of e-business diffusion: A test of the technology diffusion perspective, Technovation, 28, 3, pp. 135-145, (2008); Vishnevskiy K., Gokhberg L., Dementiev V., Et al., Digital technologies in the Russian economy, (2021); Nicoletti G., von Rueden C., Andrews D., Digital technology diffusion: A matter of capabilities, incentives or both?, European Economic Review, 128, (2020); Rao K.U., Kishore V.V.N., A review of technology diffusion models with special reference to renewable energy technologies, Renewable and Sustainable Energy Reviews, 14, 3, pp. 1070-1078, (2010); Gerosk P.A., Models of technology diffusion, Research policy, 29, 4-5, pp. 603-625, (2000); Christensen C.M., Exploring the limits of the technology S-curve. 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["Toraman Y.; Bayirli M.; Ramadani V.","Toraman, Yavuz (58568976900); Bayirli, Mehmet (58628456100); Ramadani, Veland (48561305200)","58568976900; 58628456100; 48561305200","New technologies in small business models: use of electric vehicles in last-mile delivery for fast-moving consumer goods",2023.0,"Journal of Small Business and Enterprise Development",{"$nulls":6},0.0,"10.1108/JSBED-08-2023-0375","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85177089337&doi=10.1108%2fJSBED-08-2023-0375&partnerID=40&md5=391376b50431a44665c0eaecdbb15697","Istanbul Nisantasi Universitesi, Sariyer, Turkey; Alanya Alaaddin Keykubat Universitesi, Alanya, Turkey; South East European University, Tetovo, North Macedonia","Toraman Y., Istanbul Nisantasi Universitesi, Sariyer, Turkey; Bayirli M., Alanya Alaaddin Keykubat Universitesi, Alanya, Turkey; Ramadani V., South East European University, Tetovo, North Macedonia","Purpose: The share of fast-moving consumer goods (FMCG) in e-commerce has increased, particularly after COVID-19, alongside the growing volume of e-commerce transactions. The increased number of orders necessitates the optimization of delivery operations. This situation has made using different technologies in last-mile delivery processes necessary. Currently, used electric vehicles (EVs) play a significant role in integrating these technologies into delivery operations. Adapting to new technologies emerges as a critical need for small enterprises to survive in the face of advancing technologies. In this context, the main purpose of this paper is to examine and identify attitudes of small businesses toward EVs’ usage in last-mile delivery for FMCG. Design/methodology/approach: The theoretical frameworks commonly used in studies investigating new technologies, namely the theory of planned behavior (TPB) and technology acceptance model (TAM) have been employed. The analysis of the study was conducted using partial least squares-structural equation modeling (PLS-SEM) and the Smart PLS software package. Findings: When examining the results of the study, a significant and positive relationship was found between compatibility and enjoyment with perceived usefulness. Furthermore, a significant and positive relationship was identified between attitude toward use, perceived behavioral control and perceived usefulness. Ultimately, a strong relationship was found between intention, which is a precursor to active usage and attitude. Based on the obtained data, it can be concluded that EVs can be actively used in last-mile delivery in the future. Originality/value: In FMCG processes in Türkiye, EVs are limitedly used in last-mile delivery operations. However, there are very few studies on the use of EVs in FMCG. Therefore, it is expected that the current research will contribute to the literature by providing information on the factors that influence the acceptance of EV usage and their implications. The TAM and TPB models were used in the current study. © 2023, Emerald Publishing Limited.","E-commerce; Electric vehicles; Last-mile delivery; Logistics business model; Supply chain management; Türkiye",{"$nulls":7},"Acikgoz F., Elwalda A., De Oliveira M.J., Curiosity on cutting-edge technology via theory of planned behavior and diffusion of innovation theory, International Journal of Information Management Data Insights, 3, 1, (2023); Ajzen I., The theory of planned behavior, Organizational Behavior and Human Decision Processes, 50, 2, pp. 179-211, (1991); Ajzen I., Sheikh S., Action versus inaction: anticipated affect in the theory of planned behavior, Journal of Applied Social Psychology, 43, 1, pp. 155-162, (2013); Al-Rahmi W.M., Yahaya N., Aldraiweesh A.A., Alamri M.M., Aljarboa N.A., Alturki U., Aljeraiwi A.A., Integrating technology acceptance model with innovation diffusion theory: an empirical investigation on students' intention to use E-learning systems, IEEE Access, 7, pp. 26797-26809, (2019); Baltazar J.R., Fernandes C.I., Ramadani V., Hughes M., Family business succession and innovation: a systematic literature review, Review of Managerial Science, 17, 8, pp. 2897-2920, (2023); Bawack R.E., Wamba S.F., Carillo K.D.A., Akter S., Artificial intelligence in E-Commerce: a bibliometric study and literature review, Electronic Markets, 32, 1, pp. 297-338, (2022); Bhatti A., Akram H., Basit H.M., Khan A.U., Raza S.M., Naqvi M.B., E-commerce trends during COVID-19 Pandemic, International Journal of Future Generation Communication and Networking, 13, 2, pp. 1449-1452, (2020); Bosnjak M., Ajzen I., Schmidt P., The theory of planned behavior: selected recent advances and applications, Europe's Journal of Psychology, 16, 3, pp. 352-356, (2020); Byun H., Chiu W., Bae J.S., Exploring the adoption of sports brand apps: an application of the modified technology acceptance model, International Journal of Asian Business and Information Management (IJABIM), 9, 1, pp. 52-65, (2018); Cai L., Yuen K.F., Xie D., Fang M., Wang X., Consumer's usage of logistics technologies: integration of habit into the unified theory of acceptance and use of technology, Technology in Society, 67, (2021); Davis F.D., Perceived usefulness, perceived ease of use, and user acceptance of information technology, MIS Quarterly, 13, 3, pp. 319-340, (1989); Davis F.D., Bagozzi R.P., Warshaw P.R., User acceptance of computer technology: a comparison of two theoretical models, Management Science, 35, 8, pp. 982-1003, (1989); Davis F.D., Granic A., Marangunic N., The Technology Acceptance Model 30 Years of TAM. Technology, (2023); Drucker P., Technology, Management and Society, (2012); Fernandes C., Ferreira J.J., Mota Veiga P., Kraus S., Dabic M., Digital entrepreneurship platforms: mapping the field and looking towards a holistic approach, Technology in Society, 70, August, (2022); Ferreira J.J., Fernandes I.C., Mota Veiga P., Caputo A., The interactions of entrepreneurial attitudes, abilities and aspirations in the (twin) environmental and digital transitions? 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Gender, social influence, and their role in technology acceptance and usage behavior, MIS Quarterly, 24, 1, pp. 115-139, (2000); Wallace E., Buil I., Antecedents and consequences of conspicuous green behavior on social media: incorporating the virtual self-identity into the theory of planned behavior, Journal of Business Research, 157, (2023); Wang S., Fan J., Zhao D., Yang S., Fu Y., Predicting consumers' intention to adopt hybrid electric vehicles: using an extended version of the theory of planned behavior model, Transportation, 43, pp. 123-143, (2016); Won D., Chiu W., Byun H., Factors influencing consumer use of a sport-branded app: the technology acceptance model integrating app quality and perceived enjoyment, Asia Pacific Journal of Marketing and Logistics, 35, 5, pp. 1112-1133, (2023); Zhang X., Chang M., Applying the extended technology acceptance model to explore taiwan's generation Z's behavioral intentions toward using electric motorcycles, Sustainability, 15, 4, (2023); Zhang K., Guo H., Yao G., Li C., Zhang Y., Wang W., Modeling acceptance of electric vehicle sharing based on theory of planned behavior, Sustainability, 10, 12, (2018); Zeqiri J., Ramadani Z., Aloulou W., The effect of perceived convenience and perceived value on intention to repurchase in online shopping: the mediating effect of e-WOM and trust, Economic Research-Ekonomska Istraživanja, 36, 3, (2023)","V. Ramadani; South East European University, Tetovo, North Macedonia; email: v.ramadani@seeu.edu.mk",null,"Emerald Publishing",{"$nulls":5},1.4626004E7,null,null,null,"English","J. Small Bus. Enterp. Dev.","Article","Article in press",null,"Scopus","2-s2.0-85177089337"]
["Machado-León J.L.; MacKenzie D.; Goodchild A.","Machado-León, José L. (57034266000); MacKenzie, Don (57209595482); Goodchild, Anne (15062559900)","57034266000; 57209595482; 15062559900","An empirical analysis of passenger vehicle dwell time and curb management strategies for ride-hailing pick-up/drop-off operations",2023.0,"Transportation",{"$nulls":6},1.0,"10.1007/s11116-023-10380-6","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85150018971&doi=10.1007%2fs11116-023-10380-6&partnerID=40&md5=53f83640a678a487c26eb8c41abe74c2","Department of Civil and Environmental Engineering, University of Washington, Box 352700, Seattle, 98195-2700, WA, United States","Machado-León J.L., Department of Civil and Environmental Engineering, University of Washington, Box 352700, Seattle, 98195-2700, WA, United States; MacKenzie D., Department of Civil and Environmental Engineering, University of Washington, Box 352700, Seattle, 98195-2700, WA, United States; Goodchild A., Department of Civil and Environmental Engineering, University of Washington, Box 352700, Seattle, 98195-2700, WA, United States","With the dramatic and recent growth in demand for curbside pick-up and drop-off by ride-hailing services, as well as online shopping and associated deliveries, balancing the needs of roadway users is increasingly critical. Local governments lack tools to evaluate the impacts of curb management strategies that prioritize different users’ needs. The dwell time of passenger vehicles picking up/dropping off (PUDO) passengers, including ride-hailing vehicles, taxis, and other cars, is a vital metric for curb management, but little is understood about the key factors that affect it. This research used a hazard-based duration modeling approach to describe the PUDO dwell times of over 6,000 passenger vehicles conducted in Seattle, Wash. Additionally, a before-after study approach was used to assess the effects of two curb management strategies: adding PUDO zones and geofencing. Results showed that the number of passenger maneuvers, location and time of day, and traffic and operation management factors significantly affected PUDO dwell times. PUDO operations took longer with more passengers, pick-ups (as opposed to drop-offs), vehicle´s trunk access, curbside stops, and in the afternoon. More vehicles at the curb and in adjacent travel lanes were found to be related to shorter PUDO dwell times but with a less practical significance. Ride-hailing vehicles tended to spend less time conducting PUDOs than other passenger vehicles and taxis. Adding PUDO zones, together with geofencing, was found to be related to faster PUDO operations at the curb. Suggestions are made for the future design of curb management strategies to accommodate ride-hailing operations. © 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.","Curb management; Dwell time; Parking; Ride-hailing","Pickups; Vehicles; Curb management; Dwell time; Empirical analysis; Growth in demands; Local government; Management strategies; Online shopping; Passengers vehicles; Picking up-dropping; Ride-hailing; Drops",{"$nulls":4},"King County Metro; Seattle Department of Transportation","The data collection for this research was funded by a gift to the University of Washington on behalf of the Seattle Department of Transportation, Amazon.com, Sound Transit, and King County Metro. ","AlHadidi T., Rakha H.A., Modeling bus passenger boarding/alighting times: a stochastic approach, Transp. Res. Interdisciplinary Perspect, 2, (2019); Arnott R., Rowse J., Curbside parking time limits, Transp. Res. 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Transportation Network Companies—Pilot Program Operating Agreement, (2017); Ranjbari A., Machado-Leon J.L., Chiara D., Mackenzie G., Testing Curbside Management Strategies to mitigate the impacts of Ridesourcing Services on Traffic. Transp. Res. Rec, 0361198120957314, (2020); Schneider T., Taxi, Uber, and Lyft Usage in New York City, Toddwschneider.Com, (2020); Seattle Department of Construction and Inspections (SDCI)., (2017); Tncs Today. San Francisco County Transportation Authority, (2017); Sharman B.W., Roorda M.J., Habib K.M.N., Comparison of Parametric and Nonparametric Hazard Models for Stop Durations on Urban Tours with Commercial Vehicles, Transp. Res. Rec, 2269, 1, pp. 117-126, (2012); Smith A., Wylie A., Salzberg A., Womeldorff E., Rubendall G., Ballus-Armet I., A Data Driven Approach to Understanding and Planning for Curb Space Utility (No. 19–02196). Article 19–02196, Transportation Research Board 98Th Annual Meetingtransportation Research Board, (2019); Su Q., Wang D.Z.W., Morning commute problem with supply management considering parking and ride-sourcing, Transp. Res. Part C: Emerg. Technol, 105, pp. 626-647, (2019); Tirachini A., Ride-hailing, travel behaviour and sustainable mobility: an international review, Transportation, 47, 4, pp. 2011-2047, (2020); Sea-Tac-International-Airport | Airports | Drive. Uber. Retrieved January 17, From, (2023); Your Guide to Pickups and Dropoffs at UC Irvine. Uber Blog., (2018); Washington S., Karlaftis M.G., Mannering F., Anastasopoulos P., Statistical and Econometric Methods for Transportation Data Analysis, (2020); Winter K., Cats O., Martens K., van Arem B., Relocating shared automated vehicles under parking constraints: assessing the impact of different strategies for on-street parking, Transportation, 48, 4, pp. 1931-1965, (2021); Xu Z., Yin Y., Zha L., Optimal parking provision for ride-sourcing services, Transp. Res. Part B: Methodological, 105, pp. 559-578, (2017); Yadav A.K., Velaga N.R., Modelling brake transition time of young alcohol-impaired drivers using hazard-based duration models, Accid. Anal. Prev, 157, (2021); Yu M., Bayram A., Management of the curb space allocation in urban transportation system, International Transactions in Operational Research, n a, n a., (2021)","J.L. Machado-León; Department of Civil and Environmental Engineering, University of Washington, Seattle, Box 352700, 98195-2700, United States; email: jlmaleon@uw.edu",null,"Springer",{"$nulls":5},494488.0,null,null,null,"English","Transportation","Article","Article in press",null,"Scopus","2-s2.0-85150018971"]
["Barrichello A.; Morano R.S.; dos Santos E.G.","Barrichello, Alcides (56638629400); Morano, Rogerio Scabim (55617371900); dos Santos, Emerson Gomes (58710037600)","56638629400; 55617371900; 58710037600","Online purchase decision after viewing ads: Factors related to sociodemographic and internet use on different digital channels",2023.0,"International Journal of Internet Marketing and Advertising",19.0,"2024-02-01",null,20.0,41.0,21.0,0.0,"10.1504/IJIMA.2023.132778","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85170437761&doi=10.1504%2fIJIMA.2023.132778&partnerID=40&md5=ccbd6375278e8dcd43c40790ce1b363f","Centro de Ciências Sociais e Aplicadas, Universidade Presbiteriana Mackenzie, Rua Consolação, 930, SP, São Paulo, 01302-000, Brazil; Instituto de Ciências Ambientais, Químicas e Farmacêuticas, Instituto de Ciência e Tecnologia, Universidade Federal de São Paulo - UNIFESP, Rua São Nicolau, 210, 4o. andar, sala 41 - Centro, SP, Diadema, 09913-030, Brazil; Escola Paulista de Política, Economia e Negócios, Universidade Federal de São Paulo - UNIFESP, . andar, sala 301 - Jardim das Flores, SP, Osasco, 06110-295, Brazil","Barrichello A., Centro de Ciências Sociais e Aplicadas, Universidade Presbiteriana Mackenzie, Rua Consolação, 930, SP, São Paulo, 01302-000, Brazil; Morano R.S., Instituto de Ciências Ambientais, Químicas e Farmacêuticas, Instituto de Ciência e Tecnologia, Universidade Federal de São Paulo - UNIFESP, Rua São Nicolau, 210, 4o. andar, sala 41 - Centro, SP, Diadema, 09913-030, Brazil; dos Santos E.G., Escola Paulista de Política, Economia e Negócios, Universidade Federal de São Paulo - UNIFESP, . andar, sala 301 - Jardim das Flores, SP, Osasco, 06110-295, Brazil","This research aims to assess the factors related to sociodemographic and internet use that influence consumers to purchase after viewing ads on websites or through apps, social media, messaging apps, e-mail, and video. A database obtained from the 2018 ICT Households survey containing 4, 115 responses representing the Brazilian population who had made an online purchase of a product or service within 12 months was used and analysed using logistic regression models. The main results indicate that age influences the purchase after viewing ads in emails. The level of education is important when the advertisement was made on websites or apps, and social media. The frequency of internet use and the frequency of online shopping also matter for purchase on the different digital channels researched. Regarding academic contributions, the factors are evaluated concomitantly and with data reflecting the population of the entire country, opens a new way of thinking about how to segment customers via one of the components of the marketing mix: promotion. The support to marketing professionals regarding the effectiveness of ads on different digital channels is among this study’s practical contributions. © 2023 Inderscience Enterprises Ltd.","advertisement; advertising on the net; consumer behaviour; customer relationship; digital marketing; e-commerce; marketing; online advertising; purchase after viewing ads; social media",{"$nulls":7},"Abayi M., Khoshtinat B., Study of the impact of advertising on online shopping tendency for airline tickets by considering motivational factors and emotional factors, Procedia Economics and Finance, 36, 16, pp. 532-539, (2016); Ajzen I., The theory of planned behavior, Organizational Behavior and Human Decision Processes, 50, pp. 179-211, (1991); Akbari M., Different impacts of advertising appeals on advertising attitude for high and low involvement products, Global Business Review, 16, 3, pp. 478-493, (2015); Alalwan A.A., Et al., Social media in marketing: a review and analysis of the existing literature, Telematics and Informatics, 34, 7, pp. 1177-1190, (2017); Alijani G.S., Et al., Effectiveness of online advertisement factors in recalling a product, Academy of Marketing Studies Journal, 14, 1, pp. 1-10, (2010); Appiah O., Rich media, poor media: The impact of audio/video vs. text/picture testimonial ads on browsers’ evaluations of commercial web sites and online products, Journal of Current Issues and Research in Advertising, 28, 1, pp. 73-86, (2006); Aswathy R.V., Nair V.R., A study on digital marketing and its impact, Our Heritage, 68, 30, pp. 7557-7561, (2020); Barrichello A., Et al., Repurchase intent online and its determinants: a Brazilian perspective, Revista Gestão & Tecnologia, 16, 2, pp. 199-217, (2016); Bauer R.A., Greyser S.A., Advertising in America: The Consumer View, (1968); Belanche D., Flavian C., Perez-Rueda A., User adaptation to interactive advertising formats: The effect of previous exposure, habit and time urgency on ad skipping behaviors, Telematics and Informatics, 34, 7, pp. 961-972, (2017); Bernritter S.F., Verlegh P.W.J., Smit E.G., Why nonprofits are easier to endorse on social media: the roles of warmth and brand symbolism, Journal of Interactive Marketing, 33, pp. 27-42, (2016); Bolton R.N., Et al., Understanding generation Y and their use of social media: a review and research agenda, Journal of Service Management, 24, 3, pp. 245-267, (2013); Breuer R., Brettel M., Short- and long-term effects of online advertising: differences between new and existing customers, Journal of Interactive Marketing, 26, 3, pp. 155-166, (2012); Caro A., Et al., Inovatividade, envolvimento, atitude e experiência na adoção da compra on-line, Revista de Administração de Empresas, 51, 6, pp. 568-584, (2011); Colliander J., Marder B., Snap happy’ brands: increasing publicity effectiveness through a snapshot aesthetic when marketing a brand on Instagram, Computers in Human Behavior, 78, pp. 34-43, (2018); Coulter K.S., Roggeveen A., Like it or not’ consumer responses to word-of-mouth communication in on-line social networks, Management Research Review, 35, 9, pp. 878-899, (2012); Dankwa D.D., Social media advertising and consumer decision-making: the mediating role of consumer engagement, International Journal of Internet Marketing and Advertising, 15, 1, pp. 29-53, (2021); de Haan E., Wiesel T., Pauwels K., The effectiveness of different forms of online advertising for purchase conversion in a multiple-channel attribution framework, International Journal of Research in Marketing, 33, 3, pp. 491-507, (2016); Dominguez-Almendros S., Benitez-Parejo N., Gonzalez-Ramirez A.R., Logistic regression models, Allergol Immunopathol (Madr), 39, 5, pp. 295-305, (2011); Drews W., Schemer C., eTourism for all? 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The ‘golden quadrant’ shifts as a function of congruity with the product type, targets’ individual differences, and advertising appeal type, Basic and Applied Social Psychology, 37, 2, pp. 131-141, (2015)","A. Barrichello; Centro de Ciências Sociais e Aplicadas, Universidade Presbiteriana Mackenzie, São Paulo, Rua Consolação, 930, SP, 01302-000, Brazil; email: alcidesbarrichel@uol.com.br",null,"Inderscience Publishers",{"$nulls":5},1.4775212E7,null,null,null,"English","Int. J. Internet Mark. Advert.","Article","Final",null,"Scopus","2-s2.0-85170437761"]
["Pečman J.; Vrábel J.; Mašek J.; Šedivý J.; Stopková M.; Bartuška L.","Pečman, Jan (57224216737); Vrábel, Ján (57189065721); Mašek, Jaroslav (55674270500); Šedivý, Josef (57204826316); Stopková, Mária (57209207082); Bartuška, Ladislav (56896017000)","57224216737; 57189065721; 55674270500; 57204826316; 57209207082; 56896017000","PACKAGING WASTE RESEARCH RESPONDING TO THE RISE OF TRANSPORT AND LOGISTICS VOLUMES DURING THE COVID-19 PANDEMIC",2023.0,"Archives of Automotive Engineering",101.0,3.0,null,50.0,66.0,16.0,0.0,"10.14669/AM/172451","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174237405&doi=10.14669%2fAM%2f172451&partnerID=40&md5=418cb55632843a4fcb9794e0e2beecea","Department of Transport and Logistics, Institute of Technology and Business, Okružní 517/10, 37001, Czech Republic; Faculty of Operation and Economics of Transport and Communications, University of Žilina, Slovakia; Department of Natural Sciences, Institute of Technology and Business, Czech Republic","Pečman J., Department of Transport and Logistics, Institute of Technology and Business, Okružní 517/10, 37001, Czech Republic; Vrábel J., Faculty of Operation and Economics of Transport and Communications, University of Žilina, Slovakia; Mašek J., Faculty of Operation and Economics of Transport and Communications, University of Žilina, Slovakia; Šedivý J., Department of Natural Sciences, Institute of Technology and Business, Czech Republic; Stopková M., Department of Transport and Logistics, Institute of Technology and Business, Okružní 517/10, 37001, Czech Republic; Bartuška L., Department of Transport and Logistics, Institute of Technology and Business, Okružní 517/10, 37001, Czech Republic","The management of packaging material and its transport flow, including waste management, has become the focus of attention in recent decades, not least because of the emphasis on the requirements of sustainable development. Due to ever-increasing volume various types of packages, i.e. coming not only from industrial production, transport and trade, where its management is regulated, organized and controlled, but also packaging waste that is generated in households and where this waste ends at best sorted into containers according to material and in the worst case as municipal waste, or it is used as fuel in the incinerator. Author´s team defined the research idea in the direction of packaging waste, coming from online shopping, logistics and shipment distribution. The research was conducted over the year 2021 in the Czech Republic, during the Covid-19 pandemic, when online shopping was on its rise and, for many people, it became as a partly substitute for regular shopping in the future. In regard to an analytical part of the research, specific empirical methods were applied. The research hypothesis is evaluated statistically using a pairwise test. The presentation of the research per se is preceded by a literature review with citations of legislative articles and scientific papers related to the topic discussed. This section is followed by a description of the paradox in terms of online trading. The next part of the article presents the research findings, their summary and related conclusions. © 2023 Authors. All rights reserved.","Covid-19; e-commerce; logistics; packaging waste; shipping package; transport",{"$nulls":5},"European Regional Development Fund, ERDF","This publication was created thanks to support under the Operational Program Integrated Infrastructure for the project: Identification and possibilities of implementation of new technological measures in transport to achieve safe mobility during a pandemic caused by COVID-19 (ITMS code: 313011AUX5), co-financed by the European Regional Development Fund.","Brinker J., Gunduz H.I., Optimization of demand-related packaging sizes using a p-median approach, International Journal of Advanced Manufacturing Technology, 87, 5–8, pp. 2259-2268, (2016); Bartok O., Kozak V., Bauerova R., Online grocery shopping: the customers’ perspective in the Czech Republic, Equilibrium. Quarterly Journal of Economics and Economic Policy (Toruń), 16, 3, pp. 679-695, (2021); Camps-Posino L., Batlle-Bayer L., Bala A., Song G., Qian H., Aldacoet R., Et al., Potential climate benefits of reusable packaging in food delivery services. A Chinese case study, The Science of the Total Environment, 794, pp. 148570-148570, (2021); Waste characterization - Nomenclature - Part 2: Names and definitions related to waste management, (2011); Czech Act Nr. 477/2001 Packaging Act and on Amendments to Certain Acts; Directive 94/62/EC of the European Parliament packaging and packaging waste, (1994); Directive 75/442/EHS on waste, (1975); Kim Y., Kang J., Chun H., Is online shopping packaging waste a threat to the environment?, Economics Letters, 214, C, (2022); Klemes J.J., Van Fan Y., Jiang P., COVID19 pandemic facilitating energy transition opportunities, International Journal of Energy Research, 45, 3, pp. 3457-3463, (2021); Kotzab H., Munch H., de Faultrier B., Teller C., Environmental retail supply chains: when global Goliaths become environmental Davids, International Journal of Retail & Distribution Management, 39, 9, pp. 658-681, (2011); Mouratidis K., Papagiannakis A., COVID-19, internet, and mobility: The rise of telework, telehealth, e-learning, and e-shopping, Sustainable Cities and Society, 74, pp. 103182-103182, (2021); Palsson H., Pettersson F., Winslott Hiselius L., Energy consumption in e-commerce versus conventional trade channels - Insights into packaging, the last mile, unsold products and product returns, Journal of Cleaner Production, 164, pp. 765-778, (2017); Samson-Brek I., Matuszewska A., Possibilities of reducing greenhouse gas emissions in agriculture on the example of a biogas plant, The Archives of Automotive Engineering – Archiwum Motoryzacji, 86, 4, pp. 127-142, (2019); Verghese K., Lewis H., Lockrey S., Williams H., Packaging’s Role in Minimizing Food Loss and Waste Across the Supply Chain, Packaging Technology and Science, An International Journal; Wilson M., COVID’s Impact on Packaging and Supply Chains; Zimmermann T., Bliklen R., Single-use vs. reusable packaging in e-commerce: comparing carbon footprints and identifying break-even points, GAIA - Ecological Perspectives for Science and Society, 29, 3, pp. 176-183, (2020)",null,null,"Lukasiewicz Research Network - Automotive Industry Institute",{"$nulls":5},"1234754X",null,null,null,"English","Arch. Automot. Eng.","Article","Final","All Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85174237405"]
["Lv H.","Lv, Hua (57758742300)",5.77587423E10,"E-commerce consumer behavior analysis based on big data",2023.0,"Journal of Computational Methods in Sciences and Engineering",23.0,2.0,null,651.0,661.0,10.0,0.0,"10.3233/JCM-226628","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85151519036&doi=10.3233%2fJCM-226628&partnerID=40&md5=17583e8ee96bc0a89be559ef80160475","School of Economics and Management, Jiaozuo University, Jiaozuo, Henan, 454000, China","Lv H., School of Economics and Management, Jiaozuo University, Jiaozuo, Henan, 454000, China","In the background of the widespread development of big data technology, the actual behavior of e-commerce consumers is affected by different consumer environment and consumer demand. This article conducts in-depth inquiry and analysis of the behavior of different e-commerce users, and more accurately conducts a comprehensive analysis and effective assessment of various factors that affect consumer behavior. The factors and measures of consumer behavior are comprehensively judged to get the evaluation model closer to consumer behavior. By conducting a comprehensive full-process research on different e-commerce platforms, consumer behavior, consumption habits, and consumption processes, a comprehensive full-process research, more effective channel methods and dependence on consumers' purchase of goods, conduct a comprehensive research other factors of behavior, such as transportation logistics, environmental conditions, advertising, and other factors, conduct comprehensive judgment and analysis, and provide important theoretical basis and certain research in order to promote and improve the orderly development of consumer behavior and e-commerce environment. The research adopts modeling and analysis methods, through the evaluation of the research model, it can be seen that under the background of big data, e-commerce consumer behavior presents the trend of data, diversification and complexity. Factors affecting consumer behavior are more diverse and complex. It effectively expands the research field of e-commerce consumer behavior analysis, and provides scientific reference for the development of e-commerce. © 2023 - IOS Press. All rights reserved.","analysis and research; behavior; Big data technology; consumer; consumer behavior; data mining; e-commerce platform; e-commerce users; online shopping platform","Big data; Data mining; Electronic commerce; Purchasing; Analyse and research; Behavior; Big data technology; Commerce platforms; Consumer; Data technologies; E- commerces; E-commerce platform; E-commerce user; Online shopping; Online shopping platform; Consumer behavior",{"$nulls":6},"Xing Y., Qiu Z.P., Research on the spatiotemporal evolution pattern of China?s e-commerce development, Enterp Econ, 9, pp. 140-147, (2022); Liu S.W., Chen W., Tang H.T., E-commerce development and domestic unified market: Integration or segmentation-Based on bilateral stochastic frontier model, J Hunan Univ (Soc Sci Ed, 36, 4, pp. 56-67, (2022); Feng X.F., Exploration and practice of the ideological and political integration path of cross-border e-commerce courses, Mod Commer Ind, 43, 18, pp. 31-32, (2022); Xu X.X., On the security obligations of e-commerce platform operators, China Bus Rev, 13, pp. 57-59, (2022); Wang Z.X., Zhang Y.N., Liu X.X., Analysis of enterprise informatization and e-commerce development in Heilongjiang Province, Stat Consult, 3, pp. 17-20, (2022); Fan M.L., Wang D., The impact of e-commerce on Chinese foreign trade enterprises, China Dev, 22, 3, pp. 73-80, (2022); Liu D.D., Enlightenment from the development model and driving force of Japanese agricultural products e-commerce, Sci Technol Inf, 20, 13, pp. 110-112, (2022); Cui L.J., Research on the construction of big data platform for third-party e-commerce enterprises, Mod Bus, 17, pp. 46-48, (2022); Liu F.J., Meng L., Duan S., Li Y.Y., Research on the paradox of search cost and consumer expected regret-Based on the U\" curve hypothesis and verification, J Manage Eng, 36, 4, pp. 50-64, (2022); Fan Y.F., Zhang X.D., How power distance beliefs influence consumer behavior: A research review and prospect, Foreign Econ Manage, 44, 8, pp. 138-152, (2022); Ding J., Wang W., Gong Q., Research on consumer behavior and cigarette precision marketing strategy in big data era, China Mark, 22, pp. 136-138, (2022); Lin C.C., Research on factors affecting e-commerce customers? repurchase behavior, Mall Mod, 15, pp. 41-43, (2020); Tang W.Y., Zhang D.Y., Prediction and analysis of consumer confidence index based on internet search data, J West China Norm Univ (Nat Sci Ed, 43, 3, pp. 334-341, (2022); Pu F.Q., Ma S.Z., Consumers in digital trade: Roles, behaviors and rights, J Shanghai Bus School, 23, 1, pp. 15-30, (2022); Ma S.Z., Pu F.Q., Factors affecting the export of e-commerce platforms and their spillover effects-A study based on the perspective of consumer keyword search, Int Trade Issues, 1, pp. 37-54, (2022); Zhou X.H., Tang J.Y., Tian X., Research on the influence of consumer behavior on sales performance in B2C e-commerce platforms-empirical evidence from e-commerce enterprises, Proceedings of the 16th 2021) Annual Conference of China Management, pp. 784-794, (2021); Cai X.W., Analysis of e-commerce operation data, Mod Mark (Bus Ed, 4, pp. 126-127, (2021); Han F., Online shopping perceived risk measurement and consumer behavior based on e-commerce data, Mod Bus, 25, pp. 16-18, (2021); Miao Z.Q., The influence of consumer behavior choices on the market strategy of commercial and trade circulation enterprises, National Circ Econ, 25, pp. 22-24, (2021); Wang L.L., Research on consumer information search behavior based on mobile social network, Shandong Soc Sci, 10, pp. 183-187, (2020)","H. Lv; School of Economics and Management, Jiaozuo University, Henan, Jiaozuo, 454000, China; email: lvhua_vip@outlook.com",null,"IOS Press BV",{"$nulls":5},1.4727978E7,null,null,null,"English","J. Comput. Methods Sci. Eng.","Article","Final",null,"Scopus","2-s2.0-85151519036"]
["Saldanha A.","Saldanha, Avil (57226796542)",5.7226796542E10,"Zepto – 10-min grocery delivery service",2023.0,"Emerald Emerging Markets Case Studies",13.0,2.0,null,1.0,15.0,14.0,0.0,"10.1108/EEMCS-10-2022-0372","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85166947335&doi=10.1108%2fEEMCS-10-2022-0372&partnerID=40&md5=c6d50276edd5381e3733607d4b8f82a7","Department of Marketing, St. Joseph's Institute of Management, Bangalore, India","Saldanha A., Department of Marketing, St. Joseph's Institute of Management, Bangalore, India","Supplementary materials: Teaching notes are available for educators only. Learning outcomes: Learning objectives are as follows: critically analyze the business model of the Instant Grocery Delivery Model like Zepto; infer the importance of competitor analysis in determining the success of a startup; and analyze customer complaints and develop a corrective action plan. Case overview / synopsis: The focus of this case is the controversy faced by Zepto due to its aggressive 10-min instant delivery service. This case discusses the negative publicity and criticism faced by Zepto from various influential netizens like members of the parliament, a well-known industrialist and independent experts questioning the 10-min express delivery plan that could endanger the lives of its delivery partners. The case also discusses customer complaints and the negative publicity faced by Zepto in digital forums and social media. The primary focus of this case is the dilemma faced by Zepto’s young founders in resolving the criticism faced by Zepto due to its 10-min delivery model and due to mounting customer complaints regarding poor product quality and deficient service. The key managerial decision that the protagonists are facing is whether should Zepto continue to operate in the 10-min delivery model or should it increase the delivery time to 15 to 20 min. Complexity academic level: Undergraduate students studying Marketing courses in Commerce and Business Management streams can use this case. Subject Code: CSS 8: Marketing. © 2023, Emerald Publishing Limited.","Customer complaints; Customer dissatisfaction; Customer satisfaction; Customer service; E-commerce; Entrepreneurship; Instant delivery; Marketing; Online grocery delivery; Retailing; Zepto",{"$nulls":7},"Anand S., Zepto success story - delivering groceries in 10 mins, (2022); Arora S., Zomato acquired Blinkit for Rs 4,447 crore in all-stock deal, (2022); Babu N.M., The risks they take to deliver your groceries in 10 minutes, (2022); Bhalla K., A netizen is seeking roll back of the 10 minute delivery feature on Swiggy, Dunzo, Zepto and Grofers, (2022); Top 8 instant grocery delivery apps in India 2023 (delivery in 10 minutes), (2023); (2022); Zepto case study, (2022); Zepto business model: All you need to know, (2022); Madhukalya A., How two 19-year-old Stanford dropouts founded Zepto, (2021); Malik B., Our riders operate within 3-km radius: Zepto on driver safety, (2022); Mittal P.B.A.A., Why nobody is talking about 10-minute deliveries anymore, (2022); Absurd’: Karti Chidambaram slams Zomato’s 10-minute food delivery, says will raise issue in parliament, (2022); (2022); Patel N., What is Instamart & How it works? | Swiggy Instamart near me details, (2022); Rudra T., Tata’s BigBasket enters the qcommerce segment with BBNow, (2022); Sharma M., What’s the hype around 10-minute delivery concept? Pros & cons, (2022); Sridharan S., India: 2-Minutes meal to 10-Minutes delivery, (2022); Sriram M., Exclusive: Advertising regulator questions 10 minute delivery upstart Zepto over ‘potential…, (2022); Subramaniam N., Founded by teens, Zepto raises $60 Mn to join online grocery race, (2021); Thathoo C., TMC MP Mahua Moitra slams 10-Minute delivery, calls for its regulation, (2022); Anand Mahindra isn’t impressed with 10-min delivery, but gives Zepto boss a “fair” chance to explain his 9, (2022); Blinkit on Zomato plate: Board OKs Rs 4,447cr deal, (2022); From Zepto to Blinkit, all the apps offering 10-minute delivery service in India, (2022); Albinder Dhindsa the accidental entrepreneur, (2015)","A. Saldanha; Department of Marketing, St. Joseph's Institute of Management, Bangalore, India; email: avilsaldanha@gmail.com",null,"Emerald Publishing",{"$nulls":5},2.0450621E7,null,null,null,"English","Emerald Emerg. Mark. Case Stud.","Article","Final",null,"Scopus","2-s2.0-85166947335"]
["Temporelli A.; Brambilla P.C.; Brivio E.; Girardi P.","Temporelli, Andrea (57193263817); Brambilla, Paola Cristina (56357892800); Brivio, Elisabetta (57711526800); Girardi, Pierpaolo (54891913200)","57193263817; 56357892800; 57711526800; 54891913200","Last Mile Logistics Life Cycle Assessment: A Comparative Analysis from Diesel Van to E-Cargo Bike",2022.0,"Energies",15.0,20.0,7817.0,null,null,null,6.0,"10.3390/en15207817","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85140756049&doi=10.3390%2fen15207817&partnerID=40&md5=c5ee2cbaef05c98c222375bc045bf537","Ricerca Sistema Energetico—RSE Spa, Via R. Rubattino 54, Milan, 20134, Italy","Temporelli A., Ricerca Sistema Energetico—RSE Spa, Via R. Rubattino 54, Milan, 20134, Italy; Brambilla P.C., Ricerca Sistema Energetico—RSE Spa, Via R. Rubattino 54, Milan, 20134, Italy; Brivio E., Ricerca Sistema Energetico—RSE Spa, Via R. Rubattino 54, Milan, 20134, Italy; Girardi P., Ricerca Sistema Energetico—RSE Spa, Via R. Rubattino 54, Milan, 20134, Italy","With the proliferation of e-commerce, the field of last-mile logistics has grown increasingly, highlighting the need to manage the environmental consequences of this phenomenon, especially to achieve decarbonization targets for cities and to improve citizens’ quality of life. Within this framework, the authors carried out a last-mile logistics life cycle assessment, to analyse and compare different logistics vehicle options performing the same service in an urban context: an electric four-wheel cargo bike, an electric van, a plug-in hybrid van, and a diesel van. The assessment shows that the e-cargo bike performs better for all the impact categories considered. The second-best option is the e-van, while the diesel van shows the worst environmental results. Focusing on decarbonization, the replacement of a diesel van with an electric one or with an e-cargo bike allows a reduction of 173 g CO2 eq/km and 250 g CO2 eq/km, respectively. Similar results are obtained for Photochemical Ozone Formation with associated emissions of 0.18, 0.31, 0.45 and 0.49 g NMVOC eq/km for the e-cargo bike, e-van, plug in hybrid van and diesel van, respectively. The only exceptions are Human Health impact categories, Acidification and Respiratory inorganics, for which the plug-in hybrid van performs worst, and Resource use, Mineral and Metals, for which the electric van performs worst. © 2022 by the authors.","e-cargo bike; e-logistics; environmental impacts; last mile logistics; life cycle assessment; urban logistics","Bicycles; Carbon dioxide; Decarbonization; Diesel engines; Environmental impact; Comparative analyzes; Decarbonisation; E- commerces; E-cargo bike; e-Logistics; Last mile; Last mile logistic; Life cycle assessment; Plug-in-hybrid; Urban logistics; Life cycle",{"$nulls":4},"Italian Electrical System; Royal Society of Edinburgh, RSE; Ministero dello Sviluppo Economico, MiSE","This work has been financed by the Research Fund for the Italian Electrical System under the Contract Agreement between RSE S.p.A. and the Ministry of Economic Development—General Directorate for the Electricity Market, Renewable Energy and Energy Efficiency, Nuclear Energy in compliance with the Decree of 16 April 2018.","The First and Last Mile—The Key to Sustainable Urban Transport—Transport and Environment Report 2019, (2019); Lebeau P., De Cauwer C., Van Mierlo J., Macharis C., Verbeke W., Coosemans T., Conventional, hybrid, or electric vehicles: Which technology for an urban distribution centre?, Sci. World J, 2015, (2015); A European Green Deal, (2019); Bosona T., Urban freight last mile logistics—Challenges and opportunities to improve sustainability: A literature review, Sustainability, 12, (2020); Croci E., Donelli M., Colelli F., An LCA comparison of last-mile distribution logistics scenarios in Milan and Turin municipalities, Case Stud. Transp. Policy, 9, pp. 181-190, (2021); Oliveira C., Albergaria De Mello Bandeira R., Vasconcelos Goes G., Schmitz Goncalves D.N., D'Agosto M.D.A., Sustainable vehicles-based alternatives in last mile distribution of urban freight transport: A systematic literature review, Sustainability, 9, (2017); Saenz-Esteruelas J., Figliozzi M., Serrano A., Faulin J., Electrifying last-mile deliveries: A carbon footprint comparison between internal combustion engine and electric vehicles, International Conference on Smart Cities, pp. 76-84, (2016); Hill N., Amaral S., Morgan-Price S., Determining the Environmental Impacts of Conventional and Alternatively Fuelled Vehicles through LCA: Final Report, (2020); Hottle T., Caffrey C., McDonald J., Dodder R., Critical factors affecting life cycle assessments of material choice for vehicle mass reduction, Transp. Res. Part D Transp. Environ, 56, pp. 241-257, (2017); Burnham A., Updated Vehicle Specifications in the GREET Vehicle-Cycle Model, (2012); Marmiroli B., Venditti M., Dotelli G., Spessa E., The transport of goods in the urban environment: A comparative life cycle assessment of electric, compressed natural gas and diesel light-duty vehicles, Appl. Energy, 260, (2020); Giordano A., Fischbeck P., Matthews H., Environmental and economic comparison of diesel and battery electric delivery vans to inform city logistics fleet replacement strategies, Transp. Res. Part D Transp. Environ, 64, pp. 216-229, (2018); Yang L., Hao C., Chai Y., Life Cycle Assessment of Commercial Delivery Trucks: Diesel, Plug-in Electric and Battery-Swap Electric, Sustainability, 10, (2018); Shahraeen M., Ahmed S., Malek K., Van Drimmelen B., Kjeang E., Life cycle emissions and cost of transportation systems: Case study on diesel and natural gas for light duty trucks in municipal fleet operations, J. Nat. Gas Sci. Eng, 24, pp. 26-34, (2015); Cecchel S., Chindamo D., Collotta M., Cornacchia G., Panvini A., Tomasoni G., Gadola M., Lightweighting in light commercial vehicles: Cradle-to-grave life cycle assessment of a safety-relevant component, Int. J. Life Cycle Assess, 23, pp. 2043-2054, (2018); Siragusa C., Tumino A., Mangiaracina R., Perego A., Electric vehicles performing last-mile delivery in B2C e-commerce: An economic and environmental assessment, Int. J. Sustain. Transp, 16, pp. 22-33, (2020); Bachmann C., Chingcuanco F., MacLean H., Roorda M., Life-cycle assessment of diesel-electric hybrid and conventional diesel trucks for deliveries, J. Transp. Eng, 141, (2015); Lee D.Y., Thomas V.M., Parametric modeling approach for economic and environmental life cycle assessment of medium-duty truck electrification, J. Clean. Prod, 142, pp. 3300-3321, (2017); Garrain D., Lechon Y., Exploratory environmental impact assessment of the manufacturing and disposal stages of a new PEM fuel cell, Int. J. Hydrogen Energy, 39, pp. 1769-1774, (2014); Schunemann J., Finke S., Severengiz S., Schelte N., Gandhi S., Life Cycle Assessment on Electric Cargo Bikes for the Use-Case of Urban Freight Transportation in Ghana, Procedia CIRP, 105, pp. 721-726, (2022); Marques D.L., Coelho M.C., A Literature Review of Emerging Research Needs for Micromobility—Integration through a Life Cycle Thinking Approach, Future Transp, 2, pp. 135-164, (2022); Fraselle J., Limbourg S.L., Vidal L., Cost and Environmental Impacts of a Mixed Fleet of Vehicles, Sustainability, 13, (2021); Heilmann B.H., Reinthaler M.R., Ganev B.G., Eibl M.E., Does the introduction of small electric cargo vehicles into a logistics concept for last mile delivery of parcels and groceries in urban areas reduce its environmental impact?, Proceedings of the 7th Transport Research Arena TRA; Saenz Esteruelas J.M., An Evaluation of the Environmental Impact Reduction in the Urban Delivery Logistics Using Tricycles: A Case Study in Portland, OR, USA, Master’s thesis, (2016); Letnik T., Marksel M., Luppino G., Bardi A., Bozicnik S., Review of policies and measures for sustainable and energy efficient urban transport, Energy, 163, pp. 245-257, (2018); Environmental Management—Life Cycle Assessment—Principles and Framework, (2006); Environmental Management—Life Cycle Assessment—Requirements and Guidelines, (2006); Faccio M., Gamberi M., New city logistics paradigm: From the “last mile” to the “last 50 miles” sustainable distribution, Sustainability, 7, pp. 14873-14894, (2015); La Logistica Urbana in Una Visione Integrata, (2020); Wernet G., Bauer C., Steubing B., Reinhard J., Moreno-Ruiz E., Weidema B., The Ecoinvent database version 3 (part I): Overview and methodology, Int. J. Life Cycle Assess, 21, pp. 1218-2016, (2016); Carvalho M.L., Temporelli A., Girardi P., Life cycle assessment of stationary storage systems within the Italian electric network, Energies, 14, (2021); Fazio S., Castellani V., Sala S., Schau E., Secchi M., Zampori L., Diaconu E., Supporting Information to the Characterisation Factors of Recommended EF Life Cycle Impact Assessment Methods, (2018); Zampori L., Pant R., Suggestions for Updating the Product Environmental Footprint (PEF), (2019); Girardi P., Gargiulo A., Brambilla P.C., A comparative LCA of an electric vehicle and an internal combustion engine vehicle using the appropriate power mix: The Italian case study, Int. J. Life Cycle Assess, 20, pp. 1127-1142, (2015); Wrighton S., Reiter K., CycleLogistics–moving Europe forward, Transp. Res. Procedia, 12, pp. 950-958, (2015); Garrone F., Cazzaniga A.C.M., Terruggia R., Bartalesi D., Zanon F., Guagliardi G.A., Lazzari R., Risultati della sperimentazione di casi d’uso per servizi elettrici sulla piattaforma Fog INtelliGent Edge Reactive (FINGER), (2021); Simons A., Road transport: New life cycle inventories for fossil-fuelled passenger cars and non-exhaust emissions in ecoinvent v3, Int. J. Life Cycle Assess, 21, pp. 1299-1313, (2016); Carvalho M.L., Marmiroli B., Girardi P., Life cycle assessment of Italian electricity production and comparison with the European context, Energy Rep, 8, pp. 561-568, (2022); Dati Statistici—Dati generali, (2018); Peters J.F., Baumann M., Zimmermann B., Braun J., Weil M., The environmental impact of Li-Ion batteries and the role of key parameters–A review, Renew. Sustain. Energy Rev, 67, pp. 491-506, (2017); Rapporto rifiuti Speciali, (2020); Manca F., O'Dwyer E., Sivakumar A., Rolim C., Gomes R., Tatti A., Causone F., De Antonellis S., Temporelli A., Girardi P., Deliverable D8.7—Final Economic, Social and Environmental Appraisal. Sharing Cities, Call: H2020-SCC-2015, (2021); Burnham A., Wang M., Wu Y., Development and Applications of GREET 2.7--The Transportation Vehicle-CycleModel, (2006); Ntziachristos L., Boulter P., Road Vehicle Tyre and Brake Wear. Road Surface Wear. EMEP/CORINAIR Emission Inventory Guidebook, (2009); Del Duce A., Gauch M., Althaus H.J., Electric passenger car transport and passenger car life cycle inventories in ecoinvent version 3, Int. J. Life Cycle Assess, 21, pp. 1314-1326, (2016); Produzione nazionale di idrocarburi—anno 2019, (2019); La situazione energetica nazionale nel 2019, (2020); Girardi P., Brambilla P.C., Mela G., Life Cycle Air Emissions External Costs Assessment for Comparing Electric and Traditional Passenger Cars, Integr. Environ. Assess. Manag, 16, pp. 140-150, (2020); Saxena S., Le Floch C., MacDonald J., Moura S., Quantifying EV battery end-of-life through analysis of travel needs with vehicle powertrain models, J. Power Sources, 282, pp. 265-276, (2015); Brambilla P.C., Temporelli A., Mela G., Molocchi A., Brivio F., LCA della Mobilità Urbana dalle Persone alle Merci, (2021); Saenz J.F.M., Faulin J., Assessment of the carbon footprint reductions of tricycle logistics services, Transp. Res. Rec, 2570, pp. 48-56, (2016); Aiello G., Quaranta S., Certa A., Inguanta R., Optimization of urban delivery systems based on electric assisted cargo bikes with modular battery size, taking into account the service requirements and the specific operational context, Energies, 14, (2021)","A. Temporelli; Ricerca Sistema Energetico—RSE Spa, Milan, Via R. Rubattino 54, 20134, Italy; email: andrea.temporelli@rse-web.it",null,"MDPI",{"$nulls":5},1.9961073E7,null,null,null,"English","Energies","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85140756049"]
["Akturk M.S.; Mallipeddi R.R.; Jia X.","Akturk, M. Serkan (57200417757); Mallipeddi, Rakesh R. (57223012695); Jia, Xingzhi (57482669200)","57200417757; 57223012695; 57482669200","Estimating impacts of logistics processes on online customer ratings: Consequences of providing technology-enabled order tracking data to customers",2022.0,"Journal of Operations Management",68.0,"2024-07-06",null,775.0,811.0,36.0,3.0,"10.1002/joom.1204","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85134801544&doi=10.1002%2fjoom.1204&partnerID=40&md5=67d9222ffb89649a9a79aac5976f325f","Management Department, Clemson University, Wilbur O. and Ann Powers College of Business, Clemson, SC, United States; Fisher College of Business, The Ohio State University, Columbus, OH, United States; School of Business, Renmin University of China, Beijing, China","Akturk M.S., Management Department, Clemson University, Wilbur O. and Ann Powers College of Business, Clemson, SC, United States; Mallipeddi R.R., Fisher College of Business, The Ohio State University, Columbus, OH, United States; Jia X., School of Business, Renmin University of China, Beijing, China","Recent advances in logistics tracking technologies have enabled e-commerce firms to both accurately track the shipments and obtain accurate estimates of delivery times. With customers constantly tracking the status of their orders, the effects of logistics processes on customers' evaluation of their online shopping experience are relatively unknown as academic literature provides little guidance. Drawing upon the expectation-disconfirmation theory and attribution theory, and using a unique dataset assembled in collaboration with an e-commerce firm, we empirically investigate the effects of order processing and delivery times on online customer ratings. We also estimate the impact of positive deviation (i.e., early delivery) and negative deviation (i.e., late delivery) from the promised delivery date on online customer ratings and whether the impact of delivery status (early or late) depends on order cost and freight cost. Our empirical findings demonstrate that longer order processing and delivery times are associated with lower ratings. Our results also highlight that the late delivery of an order is negatively associated with ratings and that the order cost amplifies this effect. Furthermore, freight cost reduces both the negative effect of late delivery and the positive effect of early delivery on online ratings. Our results also indicate that there exist curvilinear relationships between online ratings and the number of days an online order is late or early. Specifically, the negative effect of a late delivery follows a convex-shape curve such that its impact decreases as the number of days an online order is late increases. Likewise, the positive effect of an early delivery increases at a decreasing rate as the number of days an online order is early increases. Our supplementary analyses further account for potential endogeneity issues and corroborate our main results with additional empirical evidence obtained through alternative model specifications and estimation strategies. We present important theoretical implications and managerial takeaways from our findings. © 2022 Association for Supply Chain Management, Inc.","e-commerce firms; logistics tracking; online customer ratings; order processing times; shipment delays","Cost benefit analysis; Electronic commerce; Ships; Delivery time; E- commerces; E-commerce firm; Logistic tracking; Logistics process; Online customer rating; Online customers; Online orders; Order processing time; Shipment delay; Sales",{"$nulls":6},{"$cut":{"chars":19474,"head":"Agatz N.A.H., Fleischmann M., van Nunen J.A.E.E., E-fulfillment and multi-channel distribution – A review, European Journal of Operational Research, 187, 2, pp. 339-356, (2008); Akturk M.S., Ketzenberg M., Exploring the competitive dimension of omnichannel retailing, Management Science, 68, 4, pp. 2732-2750, (2022); Akturk M.S., Ketzenberg M., Impact of competitive store closures on a major retailer, Production and Operations Management, 31, 2, pp. 715-730, (2022); Akturk M.S., Ketzenberg M., Heim G.R., Assessing impacts of introducing ship-to-store service on sales and returns in omnichannel retailing: A data analytics study, Journal of Operations Management, 61, pp. 15-45, (2018); Angrist J.D., Pischke J., Mostly harmless econometrics: An empiricist's companion, (2008); Balasubramanian S., Mail versus mall: A strategic analysis of competition between direct marketers and conventional retailers, Marketing Science, 17, 3, pp. 181-195, (1998); Bell D.R., Gallino S., Moreno A., How to win in an omnichannel world, MIT Sloan Management Review, 56, 1, pp. 44-53, (2014); Bertini M., Wathieu L., Research note—Attention arousal through price partitioning, Marketing Science, 27, 2, pp. 236-246, (2008); Bhattacherjee A., Understanding information systems continuance: An expectation-confirmation model, MIS Quarterly, 25, pp. 351-370, (2001); Bleichrodt H., Schmidt U., Zank H., Additive utility in prospect theory, Management Science, 55, 5, pp. 863-873, (2009); Bolton L.E., Warlop L., Alba J.W., Consumer perceptions of price (un) fairness, Journal of Consumer Research, 29, 4, pp. 474-491, (2003); Bolumole Y.A., The supply chain role of third-party logistics providers, The International Journal of Logistics Management, 12, 2, pp. 87-102, (2001); Bower A.B., Maxham J.G., Return shipping policies of online retailers: Normative assumptions and the long-term consequences of fee and free returns, Journal of Marketing, 76, 5, pp. 110-124, (2012); Boyer K.K., Hult G.T.M., Extending the supply chain: Integrating operations and marketing in the online grocery industry, Journal of Operations Management, 23, 6, pp. 642-661, (2005); Brickman P., Ryan K., Wortman C.B., Causal chains: Attribution of responsibility as a function of immediate and prior causes, Journal of Personality and Social Psychology, 32, 6, pp. 1060-1067, (1975); Buell R.W., Kim T., Tsay C., Creating reciprocal value through operational transparency, Management Science, 63, 6, pp. 1673-1695, (2017); Burke R.R., Technology and the customer interface: What consumers want in the physical and virtual store, Journal of the Academy of Marketing Science, 30, 4, (2002); Castano R., Flores D., Consumer behavior in emerging markets, The Oxford handbook of management in emerging markets, (2019); Chakravarti D., Krish R., Paul P., Srivastava J., Partitioned presentation of multicomponent bundle prices: Evaluation, choice and underlying processing effects, Journal of Consumer Psychology, 12, 3, pp. 215-229, (2002); Chen P., Hong Y., Liu Y., The value of multidimensional rating systems: Evidence from a natural experiment and randomized experiments, Management Science, 64, 10, pp. 4629-1647, (2018); Chevalier J.A., Mayzlin D., The effect of word of mouth on sales: Online book reviews, Journal of Marketing Research, 43, 3, pp. 345-354, (2006); Choi S., Mattila A.S., Perceived controllability and service expectations: Influences on customer reactions following service failure, Journal of Business Research, 61, 1, pp. 24-30, (2008); Churchill G.A., Surprenant C., An investigation into the determinants of customer satisfaction, Journal of Marketing Research, 19, 4, pp. 491-504, (1982); Last mile delivery wars: How to keep your promises and win with reliability. Tech. rep, (2019); Corbett L.M., Claridge G.S., Key manufacturing capability elements and business performance, International Journal of Production Research, 40, 1, pp. 109-131, (2002); Coye R.W., Managing customer expectations in the service encounter, International Journal of Service Industry Management, 15, 1, pp. 54-71, (2004); Crant J"}},"X. Jia; School of Business, Renmin University of China, Beijing, China; email: xingzhi.jia@ruc.edu.cn",null,"John Wiley and Sons Inc",{"$nulls":5},2726963.0,null,"JOTME",null,"English","J Oper Manage","Article","Final",null,"Scopus","2-s2.0-85134801544"]
["Lv C.; Zhang C.; Ren Y.; Meng L.","Lv, Chang (57214856599); Zhang, Chaoyong (8724865400); Ren, Yaping (57194720991); Meng, Leilei (57192211382)","57214856599; 8724865400; 57194720991; 57192211382","A fuzzy correlation based heuristic for Dual-mode integrated Location routing problem",2022.0,"Computers and Operations Research",146.0,null,105923.0,null,null,null,3.0,"10.1016/j.cor.2022.105923","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85132918526&doi=10.1016%2fj.cor.2022.105923&partnerID=40&md5=701c29f0810332eeb0723b89a1a70106","State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China; School of Mechanical Engineering, Hubei University of Technology, Wuhan, China; Jinan University, Guangzhou, 510632, China; School of Computer Science, Liaocheng University, Liaocheng, 252059, China","Lv C., State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China; Zhang C., State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China, School of Mechanical Engineering, Hubei University of Technology, Wuhan, China; Ren Y., Jinan University, Guangzhou, 510632, China; Meng L., School of Computer Science, Liaocheng University, Liaocheng, 252059, China","This paper focuses on a variant location routing problem (LRP) named Dual-mode integrated Location Routing Problem (DMI-LRP) in modern supply logistics system. The warehouses in DMI-LRP supply the demands of retailers and online-shopping customers simultaneously and the retailers and customers follow two different order cycles. The problem is presented in a two-echelon structure where products are transported from the plant to the distribution centers (DCs) in the first echelon, and from the DCs to retailers and customers in the second echelon. The mathematical formulation is given together with some valid inequalities to strengthen the model for exact method. We propose the fuzzy correlation (FC) based location for DCs and allocation for retailers and customers in LRP. Also, a fuzzy correlation arc based adaptive neighborhood search (FCA-AVNS) algorithm is designed for path planning. The proposed method is tested on three adapted benchmark instances and the results are compared with exact method and another three heuristics. The numerical experiments demonstrate the feasibility and efficiency of the proposed method especially in solving large-scale problems. © 2022 Elsevier Ltd","Fuzzy correlation; Heuristics; Location routing; Logistics; Variable neighborhood search","Benchmarking; Heuristic methods; Location; Numerical methods; Optimization; Sales; Warehouses; Distribution centres; Dual modes; Exact methods; Fuzzy correlations; Heuristic; Location routing problem; Location-routing; Logistics system; Supply logistics; Variable neighborhood search; Motion planning",{"$nulls":4},"Project of International Cooperation and Exchanges NSFC, (51861165202); Science and technology development project of Jilin Province, (20180101058JC); National Natural Science Foundation of China, NSFC, (51575211, 51705263, 51805330); Higher Education Discipline Innovation Project, (B16019)","This work was partially supported by the Project of International Cooperation and Exchanges NSFC, China [Grant No. 51861165202 ], the National Natural Science Foundation of China [Grant Nos. 51575211 , 51705263 , 51805330 ], the 111 Project of China [Grant No. B16019 ] and the Science and technology development project of Jilin Province, China [Grant No. 20180101058JC ].","Barreto S., Ferreira C., Paixao J., Santos B.S., Using clustering analysis in a capacitated location-routing problem, European J. Oper. Res., 179, 3, pp. 968-977, (2007); Belenguer J.-M., Benavent E., Prins C., Prodhon C., Wolfler Calvo R., A branch-and-cut method for the capacitated location-routing problem, Comput. Oper. Res., 38, 6, pp. 931-941, (2011); Capelle T., Cortes C.E., Gendreau M., Rey P.A., Rousseau L.-M., A column generation approach for location-routing problems with pickup and delivery, European J. Oper. Res., 272, 1, pp. 121-131, (2019); Catanzaro D., Gourdin E., Labbe M., Ozsoy F.A., A branch-and-cut algorithm for the partitioning-hub location-routing problem, Comput. Oper. Res., 38, 2, pp. 539-549, (2011); Contardo C., Hemmelmayr V., Crainic T.G., Lower and upper bounds for the two-echelon capacitated location-routing problem, Comput. Oper. Res., 39, 12, pp. 3185-3199, (2012); Darvish M., Archetti C., Coelho L.C., Speranza M.G., Flexible two-echelon location routing problem, European J. Oper. Res., 277, 3, pp. 1124-1136, (2019); De Camargo R.S., De Miranda G., Lokketangen A., A new formulation and an exact approach for the many-to-many hub location-routing problem, Appl. Math. Model., 37, 12, pp. 7465-7480, (2013); Derbel H., Jarboui B., Hanafi S., Chabchoub H., Genetic algorithm with iterated local search for solving a location-routing problem, Expert Syst. Appl., 39, 3, pp. 2865-2871, (2012); Drexl M., Schneider M., A survey of variants and extensions of the location-routing problem, European J. Oper. Res., 241, 2, pp. 283-308, (2015); Dukkanci O., Kara B.Y., Bektas T., The green location-routing problem, Comput. Oper. Res., 105, pp. 187-202, (2019); Escobar J.W., Linfati R., Baldoquin M.G., Toth P., A granular variable tabu neighborhood search for the capacitated location-routing problem, Transp. Res. B, 67, pp. 344-356, (2014); Escobar J.W., Linfati R., Toth P., A two-phase hybrid heuristic algorithm for the capacitated location-routing problem, Comput. Oper. 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B, 95, pp. 340-363, (2017); Huang S.-H., Solving the multi-compartment capacitated location routing problem with pickup–delivery routes and stochastic demands, Comput. Ind. Eng., 87, pp. 104-113, (2015); Jarboui B., Derbel H., Hanafi S., Mladenovic N., Variable neighborhood search for location routing, Comput. Oper. Res., 40, 1, pp. 47-57, (2013); Karaoglan I., Altiparmak F., Kara I., Dengiz B., A branch and cut algorithm for the location-routing problem with simultaneous pickup and delivery, European J. Oper. Res., 211, 2, pp. 318-332, (2011); Karaoglan I., Altiparmak F., Kara I., Dengiz B., The location-routing problem with simultaneous pickup and delivery: Formulations and a heuristic approach, Omega, 40, 4, pp. 465-477, (2012); Karimi H., The capacitated hub covering location-routing problem for simultaneous pickup and delivery systems, Comput. Ind. Eng., 116, pp. 47-58, (2018); Lopes R.B., Ferreira C., Santos B.S., A simple and effective evolutionary algorithm for the capacitated location–routing problem, Comput. Oper. Res., 70, pp. 155-162, (2016); Lv C., Zhang C., Lian K., Ren Y., Meng L., A hybrid algorithm for the static bike-sharing re-positioning problem based on an effective clustering strategy, Transp. Res. B, 140, pp. 1-21, (2020); Lv C., Zhang C., Lian K., Ren Y., Meng L., A two-echelon fuzzy clustering based heuristic for large-scale bike sharing repositioning problem, Transp. Res. B, 160, pp. 54-75, (2022); Martinez-Salazar I.A., Molina J., Angel-Bello F., Gomez T., Caballero R., Solving a bi-objective transportation location routing problem by metaheuristic algorithms, European J. Oper. Res., 234, 1, pp. 25-36, (2014); Nadizadeh A., Hosseini Nasab H., Solving the dynamic capacitated location-routing problem with fuzzy demands by hybrid heuristic algorithm, European J. Oper. Res., 238, 2, pp. 458-470, (2014); Nedjati A., Izbirak G., Arkat J., Bi-objective covering tour location routing problem with replenishment at intermediate depots: Formulation and meta-heuristics, Comput. Ind. Eng., 110, pp. 191-206, (2017); Nguyen V.-P., Prins C., Prodhon C., A multi-start iterated local search with tabu list and path relinking for the two-echelon location-routing problem, Eng. Appl. Artif. Intell., 25, 1, pp. 56-71, (2012); Nguyen V.-P., Prins C., Prodhon C., Solving the two-echelon location routing problem by a GRASP reinforced by a learning process and path relinking, European J. Oper. Res., 216, 1, pp. 113-126, (2012); Pichka K., Bajgiran A.H., Petering M.E., Jang J., Yue X., The two echelon open location routing problem: Mathematical model and hybrid heuristic, Comput. Ind. Eng., 121, pp. 97-112, (2018); Prodhon C., Prins C., A survey of recent research on location-routing problems, European J. Oper. Res., 238, 1, pp. 1-17, (2014); Rahmani Y., Oulamara A., Cherif W.R., Multi-products location-routing problem with pickup and delivery: Two-echelon model, IFAC Proc. Vol., 46, 7, pp. 198-203, (2013); Rath S., Gutjahr W.J., A math-heuristic for the warehouse location–routing problem in disaster relief, Comput. Oper. Res., 42, pp. 25-39, (2014); Rodriguez-Martin I., Salazar-Gonzalez J.-J., Yaman H., A branch-and-cut algorithm for the hub location and routing problem, Comput. Oper. Res., 50, pp. 161-174, (2014); Ting C.-J., Chen C.-H., A multiple ant colony optimization algorithm for the capacitated location routing problem, Int. J. Prod. Econ., 141, 1, pp. 34-44, (2013); Tuzun D., Burke L.I., A two-phase tabu search approach to the location routing problem, European J. Oper. Res., 116, 1, pp. 87-99, (1999); Yang X., Bostel N., Dejax P., A MILP model and memetic algorithm for the Hub Location and Routing problem with distinct collection and delivery tours, Comput. Ind. Eng., 135, pp. 105-119, (2019); Yu V.F., Lin S.-Y., A simulated annealing heuristic for the open location-routing problem, Comput. Oper. Res., 62, pp. 184-196, (2015); Yu V.F., Lin S.-W., Lee W., Ting C.-J., A simulated annealing heuristic for the capacitated location routing problem, Comput. Ind. Eng., 58, 2, pp. 288-299, (2010); Zare Mehrjerdi Y., Nadizadeh A., Using greedy clustering method to solve capacitated location-routing problem with fuzzy demands, European J. Oper. Res., 229, 1, pp. 75-84, (2013); Zhang B., Li H., Li S., Peng J., Sustainable multi-depot emergency facilities location-routing problem with uncertain information, Appl. Math. Comput., 333, pp. 506-520, (2018)","C. Zhang; State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China; email: zcyhust@hust.edu.cn",null,"Elsevier Ltd",{"$nulls":5},3050548.0,null,"CMORA",null,"English","Comp. Oper. Res.","Article","Final",null,"Scopus","2-s2.0-85132918526"]
["Bortolini M.; Calabrese F.; Galizia F.G.","Bortolini, Marco (54779261700); Calabrese, Francesca (57200828927); Galizia, Francesco Gabriele (57195803564)","54779261700; 57200828927; 57195803564","Crowd Logistics: A Survey of Successful Applications and Implementation Potential in Northern Italy",2022.0,"Sustainability (Switzerland)",14.0,24.0,16881.0,null,null,null,1.0,"10.3390/su142416881","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85144872468&doi=10.3390%2fsu142416881&partnerID=40&md5=9794e30b2a0afa37632168e12f31978d","Department of Industrial Engineering, Alma Mater Studiorum University of Bologna, Viale del Risorgimento 2, Bologna, 40136, Italy","Bortolini M., Department of Industrial Engineering, Alma Mater Studiorum University of Bologna, Viale del Risorgimento 2, Bologna, 40136, Italy; Calabrese F., Department of Industrial Engineering, Alma Mater Studiorum University of Bologna, Viale del Risorgimento 2, Bologna, 40136, Italy; Galizia F.G., Department of Industrial Engineering, Alma Mater Studiorum University of Bologna, Viale del Risorgimento 2, Bologna, 40136, Italy","Nowadays, last-mile logistics represents the least efficient stage of supply chains, covering up to 28% of the total delivery cost and causing significant environmental emissions. In the last few years, a wide range of collaborative economy business models has emerged across the globe, rapidly changing the way services were traditionally provided and consumed. Crowd logistics (CL) is a new strategy for supporting fast shipping services, entrusting the management of the last-mile delivery to the crowd, i.e., normal people, who agree to deliver goods to customers located along the route they have to travel, using their own transport means, in exchange for a small reward. Most existing studies have focused on evaluating the opportunities and challenges provided by CL through theoretical analysis and literature reviews, while others have proposed models for designing such emerging distribution networks. However, papers analyzing real successful applications of CL worldwide are lacking, despite being in high demand. This study attempted to fill this gap by providing, at first, an overview of real CL applications around the globe to set the stage for future successful implementations. Then, the implementation potential of CL in northern Italy was assessed through a structured questionnaire delivered to a panel of 214 people from the Alma Mater Studiorum University of Bologna (Italy) to map the feasibility of a crowd-based system in this area. The results revealed that about 91% of the interviewees were interested in using this emerging delivery system, while the remaining respondents showed some concern about the protection of their privacy and the safeguarding of the goods during transport. A relevant percentage of the interviewees were available to join the system as occasional drivers (ODs), with a compensation policy preference for a fixed fee per delivery rather than a variable reward based on the extra distance traveled to deliver the goods. © 2022 by the authors.","crowd logistics; e-commerce; last-mile delivery; parcel delivery; social crowd","Alma; Bologna [Emilia-Romagna]; Canada; Emilia-Romagna; Italy; Quebec [Canada]; business development; compensation system; cost analysis; electronic commerce; implementation process; logistics; shipping",{"$nulls":6},"Morganti E., Seidel S., Blanquart C., Dablanc L., Lenz B., The impact of e-commerce on final deliveries: Alternative parcel delivery services in France and Germany, Transp. Res. Procedia, 4, pp. 178-190, (2014); Kafle N., Zou B., Lin J., Design and modeling of a crowdsource-enabled system for urban parcel relay and delivery, Transp. Res. Part B Methodol, 99, pp. 62-82, (2017); Allen J., Piecyk M., Piotrowska M., McLeod F., Cherrett T., Ghali K., Nguyen T., Bektas T., Bates O., Friday A., Et al., Understanding the impact of e-commerce on last-mile light goods vehicle activity in urban areas: The case of London, Transp. Res. Part D Transp. Environ, 61, pp. 325-338, (2018); Rechavi A., Toch E., Crowd logistics: Understanding auction-based pricing and couriers’ strategies in crowdsourcing package delivery, J. Intell. Transp. Syst, 26, pp. 129-144, (2020); Glaser S., Jahnke H., Strassheim N., Opportunities and challenges of crowd logistics on the last mile for courier, express and parcel service providers—A literature review, Int. J. Logist. Res. Appl, pp. 1-29, (2021); Lone S., Harboul N., Weltevreden J.W.J., 2021 European E-Commerce Report. Hogeschool van Amsterdam, (2021); Rouges J.F., Montreuil B., Crowdsourcing delivery: New interconnected business models to reinvent delivery, Proceedings of the 1st International Physical Internet Conference, 1, pp. 1-19; Carbone V., Rouquet A., Roussat C., The rise of crowd logistics: A new way to co-create logistics value, J. Bus. Logist, 38, pp. 238-252, (2017); Huang K., Ardiansyah M.N., A decision model for last-mile delivery planning with crowdsourcing integration, Comput. Ind. Eng, 135, pp. 898-912, (2019); Wang Y., Zhang D., Liu Q., Shen F., Lee L.H., Towards enhancing the last-mile delivery: An effective crowd-tasking model with scalable solutions, Transp. Res. Part E Logist. Transp. Rev, 93, pp. 279-293, (2016); Belgin O., Karaoglan I., Altiparmak F., Two-echelon vehicle routing problem with simultaneous pickup and delivery: Mathematical model and heuristic approach, Comput. Ind. Eng, 115, pp. 1-16, (2018); Pichka K., Bajgiran A.H., Petering M.E., Jang J., Yue X., The two echelon open location routing problem: Mathematical model and hybrid heuristic, Comput. Ind. Eng, 121, pp. 97-112, (2018); Rai H.B., Verlinde S., Macharis C., Shipping outside the box. Environmental impact and stakeholder analysis of a crowd logistics platform in Belgium, J. Clean. Prod, 202, pp. 806-816, (2018); Ermagun A., Stathopoulos A., Crowd-shipping delivery performance from bidding to delivering, Res. Transp. Bus. Manag, 41, (2021); Slabinac M., Innovative solutions for a “Last-Mile” delivery–A European experience, Bus. Logist. Mod. Manag, 15, pp. 111-129, (2015); Allen S.D., Zhu Q., Sarkis J., Expanding conceptual boundaries of the sustainable supply chain management and circular economy nexus, Clean. Logist. Supply Chain, 2, (2021); Dehghan-Bonari M., Bakhshi A., Aghsami A., Jolai F., Green supply chain management through call option contract and revenue-sharing contract to cope with demand uncertainty, Clean. Logist. Supply Chain, 2, (2021); Demartini M., Tonelli F., Govindan K., An investigation into modelling approaches for industrial symbiosis: A literature review and research agenda, Clean. Logist. Supply Chain, 3, (2021); Malek J., Desai T.N., A framework for prioritizing the solutions to overcome sustainable manufacturing barriers, Clean. Logist. Supply Chain, 1, (2021); Rifkin J., The Zero Marginal Cost Society: The Internet of Things, the Collaborative Commons, and the Eclipse of Capitalism, (2014); Mladenow A., Bauer C., Strauss C., Crowd logistics”: The contribution of social crowds in logistics activities, Int. J. Web Inf. Syst, 12, (2016); Buldeo Rai H., Verlinde S., Merckx J., Macharis C., Crowd logistics: An opportunity for more sustainable urban freight transport?, Eur. Transp. Res. Rev, 9, pp. 1-13, (2017); Buldeo Rai H., Verlinde S., Merckx J., Macharis C., Can the crowd deliver? Analysis of crowd logistics’ types and stakeholder support, City Logistics 3 towards Sustainable and Liveable Cities, pp. 89-108, (2018); Frehe V., Mehmann J., Teuteberg F., Understanding and assessing crowd logistics business models–using everyday people for last mile delivery, J. Bus. Ind. Mark, 32, (2017); Rzesny-Cieplinska J., Szmelter-Jarosz A., Assessment of the crowd logistics solutions—The stakeholders’ analysis approach, Sustainability, 11, (2019); Szmelter-Jarosz A., Rzesny-Cieplinska J., Priorities of urban transport system stakeholders according to crowd logistics solutions in city areas. A sustainability perspective, Sustainability, 12, (2019); Huang L., Xie G., Blenkinsopp J., Huang R., Bin H., Crowdsourcing for sustainable urban logistics: Exploring the factors influencing crowd workers’ participative behavior, Sustainability, 12, (2020); Zhang M., Xia Y., Li S., Wu W., Wang S., Crowd logistics platform’s informative support to logistics performance: Scale development and empirical examination, Sustainability, 11, (2019); Alharbi A., Cantarelli C., Brint A., Crowd Models for Last Mile Delivery in an Emerging Economy, Sustainability, 14, (2022); Akeb H., Moncef B., Durand B., Building a collaborative solution in dense urban city settings to enhance parcel delivery: An effective crowd model in Paris, Transp. Res. Part E Logist. Transp. Rev, 119, pp. 223-233, (2018); Archetti C., Savelsbergh M., Speranza M.G., The vehicle routing problem with occasional drivers, Eur. J. Oper. Res, 254, pp. 472-480, (2016); Macrina G., Pugliese L.D.P., Guerriero F., Lagana D., The vehicle routing problem with occasional drivers and time windows, International Conference on Optimization and Decision Science, pp. 577-587, (2017); Feng L., Zhou L., Gupta A., Zhong J., Zhu Z., Tan K.C., Qin K., Solving generalized vehicle routing problem with occasional drivers via evolutionary multitasking, IEEE Trans. Cybern, 51, (2019); Archetti C., Guerriero F., Macrina G., The online vehicle routing problem with occasional drivers, Comput. Oper. Res, 127, (2021); Martin-Santamaria R., Lopez-Sanchez A.D., Delgado-Jalon M.L., Colmenar J.M., An Efficient Algorithm for Crowd Logistics Optimization, Mathematics, 9, (2021); Kadam P., Bhalerao S., Sample size calculation, Int. J. Ayurveda Res, 1, (2010); Boynton P.M., Greenhalgh T., Selecting, designing, and developing your questionnaire, BMJ, 328, pp. 1312-1315, (2004); Mladenow A., Bauer C., Strauss C., Crowdsourcing in logistics: Concepts and applications using the social crowd, Proceedings of the 17th International Conference on Information Integration and Web-Based Applications & Services, pp. 1-8; Odongo B., How Crowd Sourcing Is Changing the Face of Last Mile Delivery: Crowd Logistics, Bachelor’s Thesis, (2018)","F.G. Galizia; Department of Industrial Engineering, Alma Mater Studiorum University of Bologna, Bologna, Viale del Risorgimento 2, 40136, Italy; email: francesco.galizia3@unibo.it",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85144872468"]
["Hasbi I.; Syahputra S.; Syarifuddin S.; Wijaksana T.I.; Farías P.","Hasbi, Imanuddin (57218671333); Syahputra, Syahputra (57212172162); Syarifuddin, Syarifuddin (57219546704); Wijaksana, Tri Indra (57193347934); Farías, Pablo (7003980616)","57218671333; 57212172162; 57219546704; 57193347934; 7003980616","THE IMPACT OF DISCOUNT APPEAL OF FOOD ORDERING APPLICATION ON CONSUMER SATISFACTION IN SOUTHEAST ASIA",2022.0,"Journal of Eastern European and Central Asian Research",9.0,6.0,null,978.0,991.0,13.0,10.0,"10.15549/jeecar.v9i6.956","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85143307402&doi=10.15549%2fjeecar.v9i6.956&partnerID=40&md5=afb1e3b2d04841784fa6b4e2b54dad90","Telkom University, Bandung, Indonesia; Universidad de Chile, Santiago de Chile, Chile","Hasbi I., Telkom University, Bandung, Indonesia; Syahputra S., Telkom University, Bandung, Indonesia; Syarifuddin S., Telkom University, Bandung, Indonesia; Wijaksana T.I., Telkom University, Bandung, Indonesia; Farías P., Universidad de Chile, Santiago de Chile, Chile","This study aims to determine the effect of discounts on interest, selection, and satisfaction in the food and beverage ordering application service. In the current digital era, food and beverage ordering applications are widely used by the public, one of which is a food e-commerce website and application. We conducted this research with 100 respondents who are subscribers of food e-commerce websites and applications in Indonesia. The analysis was carried out using path analysis using the SmartPLS version 3. The results of this study indicate that discounts have a significant and positive effect on customers' selection, interest, and satisfaction in the food e-commerce website application. The influence given is also quite significant because it is the strength of food e-commerce websites. © 2022, Institute of Eastern Europe and Central Asia. All rights reserved.","consumer behaviour; discount; e-commerce; online food delivery",{"$nulls":5},"Universitas Telkom, Tel-U","This research was supported by Telkom University for the publication.","Ahmad Z., Hassan N. M., Khattak M. N., Moustafa M. 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["Cao K.; Su Y.; Xu Y.; Guo Q.","Cao, Kaiying (57191091909); Su, Yunyi (57466617800); Xu, Yuqiu (57214329160); Guo, Qiang (56390923300)","57191091909; 57466617800; 57214329160; 56390923300","Channel selection for retailers in platform economy under cap-and-trade policy considering different power structures",2022.0,"Electronic Commerce Research and Applications",56.0,null,101205.0,null,null,null,9.0,"10.1016/j.elerap.2022.101205","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85139597367&doi=10.1016%2fj.elerap.2022.101205&partnerID=40&md5=a0d3640c42827caee5a26877fa95c436","School of Tourism, Haihan University, Haikou, 570228, China; School of Public Policy and Administration, Nanchang University, 999 Xuefu Avenue, Nanchang, 330031, China","Cao K., School of Tourism, Haihan University, Haikou, 570228, China; Su Y., School of Public Policy and Administration, Nanchang University, 999 Xuefu Avenue, Nanchang, 330031, China; Xu Y., School of Public Policy and Administration, Nanchang University, 999 Xuefu Avenue, Nanchang, 330031, China; Guo Q., School of Tourism, Haihan University, Haikou, 570228, China","With the outbreak of COVID-19 and some environmental problems in recent years, consumers prefer to shop online and purchase green products. Considering the benefit of the e-commerce platform, offline retailers face the challenge of whether to enter e-commerce platforms. Moreover, different power structures may affect retailer encroachment in the platform economy. Thus, we develop theoretical models considering retailer channel selections, different power structures between a retailer and a manufacturer, and cap-and-trade policy. The main results show that the optimal channel selection of the retailer is affected by the annual service fee, the power structure and the carbon trading price. An interesting result is that the retailer entering the platform has a good chance to reduce the total carbon emissions. In the extensions, we consider online reviews, consumers’ channel preferences, the carbon emission of the logistics, and the shipping cost, and find that the robustness of the main results still holds. © 2022 Elsevier B.V.","Cap-and-trade policy; Carbon reduction; Channel selection; E-commerce platform; Power structure","Carbon; COVID-19; Emission control; Sales; Cap and trade; Cap-and-trade policy; Carbon emissions; Carbon reduction; Channel selection; Commerce platforms; E- commerces; E-commerce platform; Power structures; Trade policies; Electronic commerce",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (71801121, 72041026, 72061024)","This research is partly supported by the National Natural Science Foundation of China (Grant Nos. 71801121; 72061024; 72041026). ","Abhishek V., Jerath K., Zhang Z.J., Agency selling or reselling? Channel structures in electronic retailing, Manage. 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J. Prod. Econ., 191, pp. 37-50, (2017); Zhao J., Hou X., Guo Y., Wei J., Pricing policies for complementary products in a dual-channel supply chain, Appl. Math. Model., 49, pp. 437-451, (2017); Zhao J., Tang W., Wei J., Pricing decision for substitutable products with retail competition in a fuzzy environment, Int. J. Prod. Econ., 135, 1, pp. 144-153, (2012); Zheng B., Yu N., Jin L., Xia H., Effects of power structure on manufacturer encroachment in a closed-loop supply chain, Comput. Ind. Eng., 137, (2019); Zhou R., Liao Y., Shen W., Yang S., Channel selection and fulfillment service contracts in the presence of asymmetric service information, Int. J. Prod. Econ., 222, (2020)","Q. Guo; School of Tourism, Haihan University, Haikou, 570228, China; email: gq@hainanu.edu.cn",null,"Elsevier B.V.",{"$nulls":5},1.5674223E7,null,null,null,"English","Elect. Commer. Res. Appl.","Article","Final",null,"Scopus","2-s2.0-85139597367"]
["Motte-Baumvol B.; Belton Chevallier L.; Bonin O.","Motte-Baumvol, Benjamin (35727151200); Belton Chevallier, Leslie (54388492600); Bonin, Olivier (56699971100)","35727151200; 54388492600; 56699971100","Does e-grocery shopping reduce CO2 emissions for working couples’ travel in England?",2023.0,"International Journal of Sustainable Transportation",17.0,5.0,null,515.0,526.0,11.0,4.0,"10.1080/15568318.2022.2074326","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85130929198&doi=10.1080%2f15568318.2022.2074326&partnerID=40&md5=5b549b1512a7897cb9a4e2eb40c750bf","UMR CNRS ThéMA, Université de Bourgogne-Franche-Comté, Dijon, France; AME DEST, Université Gustave Eiffel, Champs-sur-Marne, France; UMR-T LVMT, Université Gustave Eiffel, Champs-sur-Marne, France","Motte-Baumvol B., UMR CNRS ThéMA, Université de Bourgogne-Franche-Comté, Dijon, France; Belton Chevallier L., AME DEST, Université Gustave Eiffel, Champs-sur-Marne, France; Bonin O., UMR-T LVMT, Université Gustave Eiffel, Champs-sur-Marne, France","This research provides new evidence about the relationship between online and in-store shopping. This article uses data for England from the UK National Travel Survey (NTS) which covers a full week and also provides information about grocery shopping practices (online and in-store). We examine the effects of online purchases on the grocery shopping practices of working couples and their related CO2 emissions. Our analysis reveals a substitution effect between in-store trips and online shopping combined with home delivery and a 37% reduction in household CO2 emissions for grocery shopping. It appears that buying groceries online combined with a home delivery system makes it possible to significantly cut emissions for grocery shopping trips, or at least to offset the effects of in-store trips by the households with the highest emissions. No rebound effect is observed for other trip motives, i.e. it is not because people make fewer trips for in-store grocery shopping that they make more trips for leisure, personal or other motives. © 2022 Taylor & Francis Group, LLC.","CO<sub>2</sub> emissions; ICT; mobility; NTS; online shopping; SEM; travel behavior","England; United Kingdom; Carbon dioxide; Leisure; CO 2 emission; England; Grocery shopping; Home delivery; ICT; Mobility; National travel surveys; Online shopping; Substitution effect; Travel behaviour; carbon emission; electronic commerce; emission control; information and communication technology; travel behavior; Electronic commerce",{"$nulls":4},"Mobile Lives Forum; SNCF","This study was funded by Mobile Lives Forum (SNCF)","Allen J., Piecyk M., Piotrowska M., McLeod F., Cherrett T., Ghali K., Nguyen T., Bektas T., Bates O., Friday A., Wise S., Austwick M., Understanding the impact of e-commerce on last-mile light goods vehicle activity in urban areas: The case of London, Transportation Research Part D: Transport and Environment, 61, pp. 325-338, (2018); Atkins K.G., Kumar A., Kim Y.-K., Smart grocery shopper segments, Journal of International Consumer Marketing, 28, 1, pp. 42-53, (2016); Bhat C.R., Frusti T., Zhao H., Schonfelder S., Axhausen K.W., Intershopping duration: An analysis using multiweek data, Transportation Research Part B: Methodological, 38, 1, pp. 39-60, (2004); Bjorgen A., Bjerkan K.Y., Hjelkrem O.A., E-groceries: Sustainable last mile distribution in city planning, Research in Transportation Economics, 87, (2019); Brand C., Schwanen T., Anable J., Online omnivores’ or ‘willing but struggling’? Identifying online grocery shopping behavior segments using attitude theory, Journal of Retailing and Consumer Services, 57, (2020); Cao X., E-shopping, spatial attributes, and personal travel, Transportation Research Record: Journal of the Transportation Research Board, 2135, 1, pp. 160-169, (2009); Cao X., The relationships between e-shopping and store shopping in the shopping process of search goods, Transportation Research Part A: Policy and Practice, 46, 7, pp. 993-1002, (2012); Chocarro R., Cortinas M., Villanueva M.-L., Situational variables in online versus offline channel choice, Electronic Commerce Research and Applications, 12, 5, pp. 347-361, (2013); Cohen P., West S.G., Aiken L.S., Applied multiple regression/correlation analysis for the behavioral sciences, (2014); Cohen-Blankshtain G., Rotem-Mindali O., Key research themes on ICT and sustainable urban mobility, International Journal of Sustainable Transportation, 10, 1, pp. 9-17, (2016); Cornick P., Byron C., Templeton I., Hurn J., Cant J., National Travel Survey 2018, Technical Report, (2019); Dablanc L., Morganti E., Arvidsson N., Woxenius J., Browne M., Saidi N., The rise of on-demand ‘instant deliveries’ in European Cities, Supply Chain Forum: An International Journal, 18, 4, pp. 203-217, (2017); National Travel Survey 2018 factsheets, (2019); Durand B., Gonzalez-Feliu J., Urban logistics and e-grocery: Have proximity delivery services a positive impact on shopping trips?, Procedia–Social and Behavioral Sciences, 39, pp. 510-520, (2012); Edwards J.B., McKinnon A.C., Cullinane S.L., Comparative analysis of the carbon footprints of conventional and online retailing, International Journal of Physical Distribution & Logistics Management, 40, 1-2, pp. 103-123, (2010); Elms J., de Kervenoael R., Hallsworth A., Internet or store? An ethnographic study of consumers’ internet and store-based grocery shopping practices, Journal of Retailing and Consumer Services, 32, pp. 234-243, (2016); ICT usage in households and by individuals, (2018); Eurostat regional yearbook, (2021); Farag S., Schwanen T., Dijst M., Empirical investigation of online searching and buying and their relationship to shopping trips, Transportation Research Record: Journal of the Transportation Research Board, 1926, 1, pp. 242-251, (2005); Farag S., Schwanen T., Dijst M., Faber J., Shopping online and/or in-store? A structural equation model of the relationships between e-shopping and in-store shopping, Transportation Research Part A: Policy and Practice, 41, 2, pp. 125-141, (2007); Ferrell C., Home-based teleshoppers and shopping travel: Do teleshoppers travel less?, Transportation Research Record: Journal of the Transportation Research Board, 1894, 1, pp. 241-248, (2004); Gim T.H.T., Analyzing the city-level effects of land use on travel time and CO2 emissions: A global mediation study of travel time, International Journal of Sustainable Transportation, (2021); Golob T.F., Structural equation modeling for travel behavior research, Transportation Research Part B: Methodological, 37, 1, pp. 1-25, (2003); Harris P., Usuriaga D., An investigation of offline/online channel patronage transference in the UK grocery sector, Marketing transformation: Marketing practice in an ever changing world, pp. 53-59, (2018); Hischier R., Car vs. packaging—A first, simple (environmental) sustainability assessment of our changing shopping behaviour, Sustainability, 10, 9, (2018); Jaller M., Pahwa A., Evaluating the environmental impacts of online shopping: A behavioral and transportation approach, Transportation Research Part D: Transport and Environment, 80, (2020); Le H.T.K., Carrel A.L., Shah H., Impacts of online shopping on travel demand: a systematic review, Transport Reviews, 42, 3, pp. 273-295, (2022); Mattioli G., Anable J., Gross polluters for food shopping travel: An activity-based typology, Travel Behaviour and Society, 6, pp. 19-31, (2017); Online Grocery Retailing—UK, March 2018, (2018); Mokhtarian P.L., Telecommunications and Travel: The case for complementarity, Journal of Industrial Ecology, 6, 2, pp. 43-57, (2008); Mokhtarian P.L., A conceptual analysis of the transportation impacts of B2C e-commerce, Transportation, 31, 3, pp. 257-284, (2004); Mokhtarian P.L., Ory D.T., Cao X., Shopping-related attitudes: A factor and cluster analysis of Northern California shoppers, Environment and Planning B: Planning and Design, 36, 2, pp. 204-228, (2009); Motte-Baumvol B., Belton-Chevallier L., Dablanc L., Morganti E., Belin-Munier C., Spatial dimensions of E-shopping in France, Asian Transport Studies, 4, 3, pp. 585-600, (2017); Pernot D., Internet shopping for everyday consumer goods: An examination of the purchasing and travel practices of click and pickup outlet customers, Research in Transportation Economics, 87, (2021); Pernot D., Aguilera A., Grocery shopping in the internet age: Places, temporalities and travel behavior of drive-in supermarkets’ customers, Netcom. Networks and Communication Studies, 31, 3-4, pp. 463-488, (2017); Ren F., Kwan M.-P., The impact of geographic context on e-shopping behavior, Environment and Planning B: Planning and Design, 36, 2, pp. 262-278, (2009); Rosqvist L.S., Hiselius L.W., Online shopping habits and the potential for reductions in carbon dioxide emissions from passenger transport, Journal of Cleaner Production, 131, pp. 163-169, (2016); Salomon I., Koppelman F., A framework for studying teleshopping versus store shopping, Transportation Research Part A: General, 22, 4, pp. 247-255, (1988); Saphores J.-D., Xu L., E-shopping changes and the state of E-grocery shopping in the US—Evidence from national travel and time use surveys, Research in Transportation Economics, 87, (2021); Schmid B., Axhausen K.W., In-store or online shopping of search and experience goods: A hybrid choice approach, Journal of Choice Modelling, 31, pp. 156-180, (2019); Schwanen T., Kwan M.-P., The Internet, mobile phone and space-time constraints, Geoforum, 39, 3, pp. 1362-1377, (2008); Schwanen T., Kwan M.-P., Ren F., The Internet and the gender division of household labour, The Geographical Journal, 180, 1, pp. 52-64, (2014); Shah H., Carrel A.L., Le H.T.K., What is your shopping travel style? Heterogeneity in US households’ online shopping and travel, Transportation Research Part A: Policy and Practice, 153, pp. 83-98, (2021); Shahmohammadi S., Steinmann Z.J., Tambjerg L., van Loon P., King J.H., Huijbregts M.A., Comparative greenhouse gas footprinting of online versus traditional shopping for fast-moving consumer goods: A stochastic approach, Environmental Science & Technology, 54, 6, pp. 3499-3509, (2020); Sim L.L., Koi S.M., Singapore’s Internet shoppers and their impact on traditional shopping patterns, Journal of Retailing and Consumer Services, 9, 2, pp. 115-124, (2002); Spurlock C.A., Todd-Blick A., Wong-Parodi G., Walker V., Children, income, and the impact of home delivery on household shopping trips, Transportation Research Record: Journal of the Transportation Research Board, 2674, 10, pp. 335-350, (2020); Stinson M., Enam A., Moore A., Auld J., Citywide impacts of E-commerce: Does parcel delivery travel outweigh household shopping travel reductions?, Proceedings of the 2nd ACM/EIGSCC Symposium on Smart Cities and Communities, (2019); Suel E., Polak J.W., Development of joint models for channel, store, and travel mode choice: Grocery shopping in London, Transportation Research Part A: Policy and Practice, 99, pp. 147-162, (2017); van Loon P., Deketele L., Dewaele J., McKinnon A., Rutherford C., A comparative analysis of carbon emissions from online retailing of fast moving consumer goods, Journal of Cleaner Production, 106, pp. 478-486, (2015); Weltevreden J.W., Substitution or complementarity? How the Internet changes city centre shopping, Journal of Retailing and Consumer Services, 14, 3, pp. 192-207, (2007); Wygonik E., Goodchild A.V., Urban form and last-mile goods movement: Factors affecting vehicle miles travelled and emissions, Transportation Research Part D: Transport and Environment, 61, pp. 217-229, (2018); Zhai Q., Cao X., Zhen F., Relationship between online shopping and store shopping in the shopping process: empirical study for search goods and experience goods in Nanjing, China, Transportation Research Record: Journal of the Transportation Research Board, 2673, 11, pp. 38-47, (2019); Zhai Q., Cao X., Mokhtarian P.L., Zhen F., The interactions between e-shopping and store shopping in the shopping process for search goods and experience goods, Transportation, 44, 5, pp. 885-904, (2017)","B. Motte-Baumvol; UMR CNRS ThéMA, Université de Bourgogne-Franche-Comté, Dijon, France; email: benjamin.motte@u-bourgogne.fr",null,"Taylor and Francis Ltd.",{"$nulls":5},1.5568318E7,null,null,null,"English","Intl. J. Sustainable Transp.","Article","Final",null,"Scopus","2-s2.0-85130929198"]
["Tuyen D.T.T.; Van Hop N.","Tuyen, Do Thi Thanh (57575183800); Van Hop, Nguyen (55664372300)","57575183800; 55664372300","A dynamic game approach for the vehicle routing problem with returns",2023.0,"Engineering Optimization",55.0,6.0,null,891.0,906.0,15.0,0.0,"10.1080/0305215X.2022.2048829","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85128216763&doi=10.1080%2f0305215X.2022.2048829&partnerID=40&md5=3226ab5534775d3aefe06f529d7e4e32","School of Industrial Engineering and Management, International University, VNU-HCMC, Ho Chi Minh City, Viet Nam","Tuyen D.T.T., School of Industrial Engineering and Management, International University, VNU-HCMC, Ho Chi Minh City, Viet Nam; Van Hop N., School of Industrial Engineering and Management, International University, VNU-HCMC, Ho Chi Minh City, Viet Nam","In this article, a dynamic game approach is proposed to deal with the vehicle routing problem with random product returns. A mixed-integer programming model is developed. Then, a three-phase procedure is designed for sequencing the delivery with random returns. The first phase uses a local search-based procedure to generate the initial delivery sequence without returns. Then, the estimated probability of return is embedded in the game model to choose the best near Nash equilibrium solution to modify the delivery sequence. Finally, the distribution sequence is updated with the actual returns for the best-expected pay-off solution. To confirm the advantage of the proposed method, numerical experiments and sensitivity analyses are conducted for a real case of an e-commerce company in Viet Nam. © 2022 Informa UK Limited, trading as Taylor & Francis Group.","game theory; product returns; Vehicle routing problem","Integer programming; Numerical methods; Sensitivity analysis; Vehicle routing; Vehicles; Dynamic game; Game approach; Game models; Local search; Mixed integer programming model; Product returns; Search-based; Three phase; Three phasis; Vehicle Routing Problems; Game theory",{"$nulls":6},"Agarwal Y.K., Venkateshan P., A New Model for the Asymmetric Vehicle Routing Problem with Simultaneous Pickups and Deliveries, Operations Research Letters, 48, 1, pp. 48-54, (2020); Avci M., Topaloglu S., A Hybrid Metaheuristic Algorithm for Heterogeneous Vehicle Routing Problem with Simultaneous Pickup and Delivery, Expert Systems with Applications, 53, pp. 160-171, (2016); Belgin O., Karaoglan I., Altiparmak F., Two-Echelon Vehicle Routing Problem with Simultaneous Pickup and Delivery: Mathematical Model and Heuristıc Approach, Computers & Industrial Engineering, 115, pp. 1-16, (2018); Belhaiza S., A Game Theoretic Approach for the Real-Life Multiple-Criterion Vehicle Routing Problem With Multiple Time Windows, IEEE Systems Journal, 12, 2, pp. 1251-1262, (2018); Florio A.M., Hartl R.F., Minner S., Optimal A Priori Tour and Restocking Policy for the Single-Vehicle Routing Problem with Stochastic Demands, European Journal of Operational Research, 285, 1, pp. 172-182, (2020); Gaur D.R., Mudgal A., Singh R.R., Improved Approximation Algorithms for Cumulative VRP with Stochastic Demands, Discrete Applied Mathematics, 280, pp. 133-143, (2020); Gutierrez A., Dieulle L., Labadie N., Velasco N., A Hybrid Metaheuristic Algorithm for the Vehicle Routing Problem with Stochastic Demands, Computers and Operations Research, 99, pp. 135-147, (2018); Hornstra R.P., Silva A., Roodberngen K.J., Coelho L.C., The Vehicle Routing Problem with Simultaneous Pickup and Delivery and Handling Costs, Computers and Operations Research, 115, (2020); Koch H., Bortfeldt A., Wascher G., A Hybrid Algorithm for the Vehicle Routing Problem with Backhauls, Time Windows and Three-Dimensional Loading Constraints, Operations Research-Spektrum, 40, pp. 1029-1075, (2018); Koc C., Laporte G., Vehicle Routing with Backhauls: Review and Research Perspectives, Computers and Operations Research, 91, pp. 79-91, (2018); Louveaux F.V., Salazar-Gonzalez J.J., Exact Approach for the Vehicle Routing Problem with Stochastic Demands and Preventive Returns, Transportation Science, 52, 6, pp. 1463-1478, (2018); Luo Z., Qin H., Zhang D., Lim A., Adaptive Large Neigborhood Search Heuristics for the Vehicle Routing Problem with Stochastic Demands and Weight-Related Cost, Transportation Research Part E, 85, pp. 69-89, (2016); Markov I., Bierlaire M., Cordeau J.F., Maknoon Y., Varone S., Waste Collection Inventory Routing with Non-stationary Stochastic Demands, Computers and Operations Research, 113, (2020); Marques A., Soares R., Santos M.J., Amorim P., Integrated Planning of Inbound and Outbound Logistics with a Rich Vehicle Routing Problem with Backhauls, Omega, 92, (2020); Oesterle J., Bauernhansl T., Exact Method for the Vehicle Routing Problem with Mixed Linehaul and Backhaul Customers, Heterogeneous Fleet, Time Window and Manufacturing Capacity, Procedia CIRP, 41, pp. 573-578, (2016); Pholin S., Likasiri C., 3-Phase Heuristics for Capacitated Multiple-Depot Vehicle Routing Problem with Separate Backhaul and Linehaul with a Case Study on Corn Residue Management System, Computers & Industrial Engineering, 158, (2021); Queiroga E., Frota Y., Sadykov R., Subramanian A., Uchoa E., Vidal T., On the Exact Solution of Vehicle Routing Problems with Backhauls, European Journal of Operational Research, 287, pp. 76-89, (2020); Reil S., Bortfeldt A., Monch L., Heuristics for Vehicle Routing Problems with Backhauls, Time Windows, and 3D Loading Constraints, European Journal of Operational Research, 266, pp. 877-894, (2018); Salavati-Khoshghalb M., Gendreau M., Jabali O., Rei W., An Exact Algorithm to Solve the Vehicle Routing Problem with Stochastic Demands Under an Optimal Restocking Policy, European Journal of Operational Research, 273, 1, pp. 175-189, (2019); Santos M.J., Curcio E., Mulati M.H., Amorim P., Miyazawa F.K., A Robust Optimization Approach for the Vehicle Routing Problem with Selective Backhauls, Transportation Research–Part E, 136, (2020); Sethanan K., Jamrus T., Hybrid Differential Evolution Algorithm and Genetic Operator for Multi-trip Vehicle Routing Problem with Backhauls and Heterogeneous Fleet in the Beverage Logistics Industry, Computers & Industrial Engineering, 146, (2020); Silva P.P.B., Zuluaga A.H.E., Description of the Classification of Publications and the Models Used in Solving of the Vehicle Routing Problem with Pickup and Delivery, Revista Ingenierías Universidad De Medellín, 15, 28, pp. 287-306, (2016); Sun D.H., He W., Zheng L.J., Liao X.Y., Scheduling Flexible Job Shop Problem Subject to Machine Breakdown with Game Theory, International Journal of Production Research, 52, 13, pp. 3858-3876, (2014); Yang S., Ning L., Shang P., Tong L.C., Augmented Lagrangian Relaxation Approach for Logistics Vehicle Routing Problem with Mixed Backhauls and Time Windows, Transportation Research–Part E, 135, (2020); Yang S., Ning L., Tong L.C., Shang P., Optimizing Electric Vehicle Routing Problems with Mixed Backhauls and Recharging Strategies in Multi-dimensional Representation Network, Expert Systems with Applications, 176, (2021)","N. Van Hop; School of Industrial Engineering and Management, International University, VNU-HCMC, Ho Chi Minh City, Viet Nam; email: nvhop@hcmiu.edu.vn",null,"Taylor and Francis Ltd.",{"$nulls":5},"0305215X",null,"EGOPA",null,"English","Eng Optim","Article","Final",null,"Scopus","2-s2.0-85128216763"]
["Makhmudov M.; Chung K.H.; Natalia F.; Ko C.S.","Makhmudov, Muzaffar (57208503525); Chung, Ki Ho (26663426700); Natalia, Friska (36782085000); Ko, Chang Seong (7202596739)","57208503525; 26663426700; 36782085000; 7202596739","DYNAMIC DESIGN FOR COLLABORATIVE DELIVERY SERVICES",2022.0,"ICIC Express Letters",16.0,11.0,null,1241.0,1248.0,7.0,1.0,"10.24507/icicel.16.11.1241","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85140387315&doi=10.24507%2ficicel.16.11.1241&partnerID=40&md5=9b0d29f0b630252bd980cd9d2d33f4d9","Department of Industrial and Management Engineering, Kyungsung University, 309 Suyeong-ro, Nam-gu, Busan, 48434, South Korea; Department of Business Administration, Kyungsung University, 309 Suyeong-ro, Nam-gu, Busan, 48434, South Korea; Department of Information Systems, Universitas Multimedia Nusantara, Scientia Boulevard, Gading Serpong, Banten, Tangerang, 15811, Indonesia","Makhmudov M., Department of Industrial and Management Engineering, Kyungsung University, 309 Suyeong-ro, Nam-gu, Busan, 48434, South Korea; Chung K.H., Department of Business Administration, Kyungsung University, 309 Suyeong-ro, Nam-gu, Busan, 48434, South Korea; Natalia F., Department of Information Systems, Universitas Multimedia Nusantara, Scientia Boulevard, Gading Serpong, Banten, Tangerang, 15811, Indonesia; Ko C.S., Department of Industrial and Management Engineering, Kyungsung University, 309 Suyeong-ro, Nam-gu, Busan, 48434, South Korea","Over the last years, e-commerce has been surging rapidly due to rapid spread of the coronavirus pandemic (COVID-19). Customers' demands and requirements are increasing as the importance of e-commerce grows globally, and finding optimal solutions to fully satisfy their wants is regarded an urgent issue of the global world. As a result of increased global output and the development of new technologies, the demand for delivery services has grown at an exponential rate. This study involves a dynamic design collaboration model in delivery service to overcome the intense competition under such market conditions. Also, a strategic decision-making model is designed as collaboration of delivery companies for the number of equal periods, during which the participant companies are forced to have their facilities/service open or closed (while their participation in collaboration system is not discontinued) in order to increase the efficiency and profitability of the collaboration system. A mathematical model is developed as multi-objective programming problem with profit maximization of the overall collaboration and incremental profit of each participating company. A numerical example is developed to demonstrate the model's applicability. ICIC International © 2022.","Delivery service; Dynamic collaboration; e-commerce; Network design",{"$nulls":5},"National Research Foundation of Korea, NRF; Ministry of Education, Science and Technology, MEST, (NRF-2019S1A5A2A03052217)","Acknowledgment. This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (NRF-2019S1A5A2A03052217).","Insider Intelligence, Top 10 Countries, Ranked by Retail Ecommerce Sales, 2020 & 2021, (2020); Kim R. Y., The impact of COVID-19 on consumers: Preparing for digital sales, IEEE Engineering Management Review, (2020); Abiad A., Arao R. M., Dagli S., Et al., The economic impact of the COVID-19 outbreak on developing Asia, Asian Development Bank, 128, (2020); Sheth J., Impact of COVID-19 on consumer behavior: Will the old habits return or die?, Journal of Business Research, 117, pp. 280-283, (2020); Yang S., Ning L., Jiang T., Dynamic impacts of COVID-19 pandemic on the regional express logistics: Evidence from China, Transport Policy, 111, pp. 111-124, (2021); Chung K. H., Rho J. J., Ko C. S., A strategic alliance model with regional monopoly of service centres in express courier services, International Journal of Services and Operations Management, 5, 6, pp. 774-786, (2009); Chung K. H., Ko H. J., Ferdinand F. N., Ko C. S., A fuzzy set-theoretic approach to the weak strategic alliance for the survival of multiple service center in express courier services, ICIC Express Letters, 5, 2, pp. 385-389, (2011); Chung K. H., Ko S. Y., Lee C. U., Ko C. S., Sustainable collaboration model with monopoly of service centers in express delivery services based on Shapley value allocation, International Journal of Industrial Engineering, 23, 3, pp. 166-173, (2016); Chung K. H., Ko S. Y., Ko C. S., A cooperative game theoretic network design for collaborative operation of service centers and consolidation terminals in delivery services, The International Journal of Industrial Engineering: Theory, Applications and Practice, 25, 1, pp. 18-28, (2018); Ferdinand F. N., Chung K. H., Ko H. J., Ko C. S., Genetic algorithm-based approach to multi-objective decision making model for strategic alliances in express courier services, ICIC Express Letters, 6, 4, pp. 929-934, (2012); Makhmudov M., Park Y. T., Sohn Y. H., Ko C. S., Network design for time-phased collaboration in delivery service, ICIC Express Letters, 15, 8, pp. 861-868, (2021); Audy J. F., D'Amours S., Lehoux N., Coordination in collaborative logistics, International Workshop on Supply Chain Models for Shared Resource Management, (2010); Frisk M., Lundgren M. G., Jomsten K., Cost allocation in collaborative forest transportation, European Journal of Operational Research, 205, pp. 448-458, (2010); Kalai E., Games in coalitional form, The New Palgrave Dictionary of Economics, pp. 1-13, (2008); Ferdinand F. N., Ko C. S., Coevolutionary algorithm based approach to the collaborative network design in express delivery services using coalitional game theory, ICIC Express Letters, 10, 11, pp. 2711-2717, (2016); Makhmudov M., Lee G., Ko C. S., Fair profit distribution in delivery service collaboration considering service quality, International Journal of Industrial Engineering: Theory, Applications, and Practice, 28, 2, (2021)","C.S. Ko; Department of Industrial and Management Engineering, Kyungsung University, Busan, 309 Suyeong-ro, Nam-gu, 48434, South Korea; email: csko@ks.ac.kr",null,"ICIC International",{"$nulls":5},"1881803X",null,null,null,"English","ICIC Express Lett.","Article","Final",null,"Scopus","2-s2.0-85140387315"]
["Gras C.; Herr N.; Newman A.","Gras, Camille (57266225200); Herr, Nathalie (55858191600); Newman, Alantha (14009161500)","57266225200; 55858191600; 14009161500","A decision aid algorithm for long-haul parcel transportation based on hierarchical network structure",2023.0,"International Journal of Production Research",61.0,21.0,null,7198.0,7212.0,14.0,0.0,"10.1080/00207543.2022.2147233","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85142652777&doi=10.1080%2f00207543.2022.2147233&partnerID=40&md5=557eae3fa6ea90d70567db0b9fe895b3","Institute of Engineering Université Grenoble Alpes, CNRS, Grenoble INP, Grenoble, France; Probayes, Montbonnot, France","Gras C., Institute of Engineering Université Grenoble Alpes, CNRS, Grenoble INP, Grenoble, France; Herr N., Probayes, Montbonnot, France; Newman A., Institute of Engineering Université Grenoble Alpes, CNRS, Grenoble INP, Grenoble, France","With the explosion of e-commerce, optimising parcel transportation has become increasingly important. We study the long-haul stage of parcel transportation which takes place between sorting centres and delivery depots and is performed on a two-level hierarchical network. In our case study, we describe the application framework of this industrial problem faced by a French postal company: There are two vehicle types that must be balanced over the network on a daily basis, and there are two possible sorting points for each parcel, which allows a better consolidation of parcels. These industrial constraints are formalised in the Long-Haul Parcel Transportation Problem (LHPTP). We present a Mixed Integer Linear Program (MILP) and a hierarchical algorithm with aggregation of demands which uses the MILP as a subroutine. We perform numerical experiments on large-size datasets provided by a postal company, which consist of approximately 2500 demands on a network of 225 sites. These tests enable the tuning of certain parameters resulting in a tailored heuristic for the LHPTP. Our algorithm can serve as a decision aid tool for transportation managers to build daily transportation plans, modeled on solutions produced given daily demand forecasts and can also be used to improve the network design. © 2022 Informa UK Limited, trading as Taylor & Francis Group.","hierarchical network; long-haul transportation; network design; Optimisation; parcel transportation","Decision support systems; Integer programming; Large dataset; Decision aids; Hierarchical network; Long haul; Long-haul transportation; Mixed integer linear program; Mixed integer-linear programmes; Network design; Optimisations; Parcel transportation; Transportation problem; Subroutines",{"$nulls":4},"Nicolas Teypaz; Association Nationale de la Recherche et de la Technologie, ANRT, (2019/0351)","This work is funded by ANRT, CIFRE n° 2019/0351. The authors thank Nicolas Teypaz (Probayes) for ideas and discussion and Sylvain Ducomman (Probayes) for comments.","Baumung M.N., Gunduz H.I., Consolidation of Residual Volumes in a Parcel Service Provider's Long-Haul Transportation Network, Computational Logistics, (2015); Bryan D.L., O'Kelly M.E., Hub-and-spoke Networks in Air Transportation: An Analytical Review, Journal of Regional Science, 39, 2, pp. 275-295, (1999); Cohn A., Root S., Wang A., Mohr D., Integration of the Load-matching and Routing Problem with Equipment Balancing for Small Package Carriers, Transportation Science, 41, 2, pp. 238-252, (2007); Crainic T.G., Service Network Design in Freight Transportation, European Journal of Operational Research, 122, 2, pp. 272-288, (2000); Crainic T.G., Long-Haul Freight Transportation, Handbook of Transportation Science, pp. 451-516, (2003); Cuda R., Guastaroba G., Grazia Speranza M., A Survey on Two-echelon Routing Problems, Computers & Operations Research, 55, pp. 185-199, (2015); Farias K., Hadj-Hamou K., Yugma C., Model and Exact Solution for a Two-Echelon Inventory Routing Problem, International Journal of Production Research, 59, 10, pp. 3109-3132, (2021); Gonzalez-Feliu J., Two-echelon Freight Transport Optimisation: Unifying Concepts Via a Systematic Review, Working Papers on Operations Management, 2, 1, pp. 18-30, (2011); Gras C., (2021); Gras C., Cung V.-D., Herr N., Newman A., (2021); Hans-Jurgen S., (2012); Hu Z., Askin R.G., Hu G., Hub Relay Network Design for Daily Driver Routes, International Journal of Production Research, 57, 19, pp. 6130-6145, (2019); Jiang L., Dhiaf M., Dong J., Liang C., Zhao S., A Traveling Salesman Problem with Time Windows for the Last Mile Delivery in Online Shopping, International Journal of Production Research, 58, 16, pp. 5077-5088, (2020); Lee J.-H., Moon I., A Hybrid Hub-and-spoke Postal Logistics Network with Realistic Restrictions: a Case Study of Korea Post, Expert Systems with Applications, 41, 11, pp. 5509-5519, (2014); Leung J.M.Y., Magnanti T.L., Singhal V., Routing in Point-to-Point Delivery Systems: Formulations and Solution Heuristics, Transportation Science, 24, 4, pp. 245-260, (1990); Lin C.-C., Chen S.-H., The Hierarchical Network Design Problem for Time-definite Express Common Carriers, Transportation Research Part B: Methodological, 38, 3, pp. 271-283, (2004); Lin C.-C., Chen S.-H., An Integral Constrained Generalized Hub-and-spoke Network Design Problem, Transportation Research Part E: Logistics and Transportation Review, 44, 6, pp. 986-1003, (2008); Meisen M., (2015); Meng Q., Wang X., Intermodal Hub-and-spoke Network Design: Incorporating Multiple Stakeholders and Multi-type Containers, Transportation Research Part B: Methodological, 45, 4, pp. 724-742, (2011); O'Kelly M.E., A Quadratic Integer Program for the Location of Interacting Hub Facilities, European Journal of Operational Research, 32, 3, pp. 393-404, (1987); O'Kelly M.E., A Geographer's Analysis of Hub-and-spoke Networks, Journal of Transport Geography, 6, 3, pp. 171-186, (1998); O'Kelly M.E., Miller H.J., The Hub Network Design Problem: A Review and Synthesis, Journal of Transport Geography, 2, 1, pp. 31-40, (1994); Rahmani Y., Ramdane Cherif-Khettaf W., Oulamara A., The Two-echelon Multi-products Location-routing Problem with Pickup and Delivery: Formulation and Heuristic Approaches, International Journal of Production Research, 54, 4, pp. 999-1019, (2016); (2021); Timperio G., Tiwari S., Manuel Gaspar Sanchez J., Adrian Garcia Martin R., de Souza R., Integrated Decision Support Framework for Distribution Network Design, International Journal of Production Research, 58, 8, pp. 2490-2509, (2020); Wang X., Huang G.Q., When and How to Share First-Mile Parcel Collection Service, European Journal of Operational Research, 288, pp. 153-169, (2020); Zapfel G., Wasner M., Planning and Optimization of Hub-and-spoke Transportation Networks of Cooperative Third-party Logistics Providers, International Journal of Production Economics, 78, 2, pp. 207-220, (2002); Zhang W., Payan A.P., Mavris D.N., (2021); Zhang J., Wu Y., Liu P., (2007)","C. Gras; Institute of Engineering, Université Grenoble Alpes, CNRS, Grenoble INP, G-SCOP, Grenoble, 38000, France; email: camille.gras@grenoble-inp.org",null,"Taylor and Francis Ltd.",{"$nulls":5},207543.0,null,"IJPRB",null,"English","Int J Prod Res","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85142652777"]
["Sfichi A.; Sfichi N.; Bădeliță M.; Medrihan M.; Zadobrischi E.","Sfichi, Adrian (58076684400); Sfichi, Narcisa (58077790800); Bădeliță, Marian (58077790900); Medrihan, Mihai (58077791000); Zadobrischi, Eduard (57211514241)","58076684400; 58077790800; 58077790900; 58077791000; 57211514241","Utility of Designing Intelligent Algorithms to Streamline E-Commerce Operations and Construction Costs Estimates by Applying Principles of Sharing Economy: Coestim",2022.0,"Telecom",3.0,3.0,null,484.0,503.0,19.0,1.0,"10.3390/telecom3030026","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85146819266&doi=10.3390%2ftelecom3030026&partnerID=40&md5=108dfaa62f1d43fda14a0756174db30b","Glocal Soft SRL, Strada Fântâna Albă nr. 1, Suceava, 720247, Romania; Department of Computers, Electronics and Automation, Faculty of Electrical Engineering and Computer Science, “Stefan Cel Mare” University, No. 13. Str. Universitatii, Suceava, 720229, Romania; Department of Computer Science, Technical University of Cluj-Napoca, Gh. Baritiu Str. 26–28, Cluj-Napoca, 400027, Romania","Sfichi A., Glocal Soft SRL, Strada Fântâna Albă nr. 1, Suceava, 720247, Romania; Sfichi N., Glocal Soft SRL, Strada Fântâna Albă nr. 1, Suceava, 720247, Romania; Bădeliță M., Glocal Soft SRL, Strada Fântâna Albă nr. 1, Suceava, 720247, Romania; Medrihan M., Glocal Soft SRL, Strada Fântâna Albă nr. 1, Suceava, 720247, Romania; Zadobrischi E., Department of Computers, Electronics and Automation, Faculty of Electrical Engineering and Computer Science, “Stefan Cel Mare” University, No. 13. Str. Universitatii, Suceava, 720229, Romania, Department of Computer Science, Technical University of Cluj-Napoca, Gh. Baritiu Str. 26–28, Cluj-Napoca, 400027, Romania","Through technological advances and the use of online platforms, the perfect environment was created to revolutionize the field of construction. Over the years, this field has faced difficulties in optimizing resources and reducing time and costs, but the maneuverability and operability of the project delivery process, of which are crucial elements. The economic and industrial crises of the last decade have exerted enormous pressure in the process of maximizing quality, being necessary models and algorithms to obtain an ideal recipe. This article presents the first proposal of a metaheuristic algorithm capable of optimizing the most important objectives of service providers in the time-quality-cost ratio without reaching a compromise disadvantaging one of the basic characteristics. The model is applied in the generation of estimates, revolutionizing the field of construction, based on the cost-estimate motto that leads to the abbreviation Coestim. © 2022 by the authors.","big data; data fusion; e-commerce; IoT; multi-objective optimization; time-cost-quality; web application",{"$nulls":5},"European Regional Development Fund, ERDF","Project co-financed by the European Regional Development Fund through the Operational Program Competitiveness 2014–2020 “Center for the transfer of knowledge to enterprises in the field of ICT—CENTRIC”.","Gu S., Slusarczyk B., Hajizada S., Kovalyova I., Sakhbieva A., Impact of the COVID-19 Pandemic on Online Consumer Purchasing Behavior, J. Theor. Appl. Electron. Commer. Res, 16, pp. 2263-2281, (2021); Guthrie C., Fosso-Wamba S., Arnaud J.B., Online consumer resilience during a pandemic: An exploratory study of e-commerce behavior before, during and after a COVID-19 lockdown, J. Retail. Consum. Serv, 61, (2021); Sohn S., A contextual perspective on consumers’ perceived usefulness: The case of mobile online shopping, J. Retail. Consum. Serv, 38, pp. 22-33, (2017); Trstenjak M., Opetuk T., Cajner H., Hegedic M., Industry 4.0 Readiness Calculation—Transitional Strategy Definition by Decision Support Systems, Sensors, 22, (2022); Di Nardo M., Yu H., Special Issue “Industry 5.0: The Prelude to the Sixth Industrial Revolution, Appl. Syst. Innov, 4, (2021); Sukrat S., Papasratorn B., An architectural framework for developing a recommendation system to enhance vendors’ capability in C2C social commerce, Soc. Netw. Anal. Min, 8, (2018); Yu P., Gong R., Sampat M., Blockchain technology in China’s digital economy: Balancing regulation and innovation, Regulatory Aspects of Artificial Intelligence on Blockchain, pp. 132-157, (2022); Domagala A., Grobler-Debska K., Was J., Kucharska E., Post-Implementation ERP Software Development: Upgrade or Reimplementation, Appl. Sci, 11, (2021); Matende S., Ogao P.J., Enterprise Resource Planning (ERP) System Implementation: A Case for User Participation, Procedia Technol, 9, pp. 518-526, (2013); Crossing Borders, (2021); Li B., Lei Q., Hybrid IoT and Data Fusion Model for e-Commerce Big Data Analysis, Wirel. Commun. Mob. Comput, 2022, pp. 1-16, (2022); Shen L., Research on E-Commerce Website Design Based on User Experience—Taking Online Digital Printing as an Example, Master’s Thesis, (2013); Garrett J.J., Elements of User Experience, pp. 52-56, (2011); Du L., Zhong X., Research on UGC type models of socialized e-commerce websites based on user experience, Design, 4, pp. 82-84, (2014); Habibi F., Birgani O., Koppelaar H., Radenovic S., Using fuzzy logic to improve the project time and cost estimation based on Project Evaluation and Review Technique (PERT), J. Proj. Manag, 3, pp. 183-196, (2018); Bhosale V., Shastri S.S., Khandare M.A., A Review of Genetic Algorithm used for optimizing scheduling of Resource Constraint construction projects, Int. Res. J. Eng. Technol, 4, pp. 2869-2872, (2017); Zareei S., Project scheduling for constructing biogas plant using critical path method, Renew. Sustain. Energy Rev, 81, pp. 756-759, (2018); Abdul Hussien F.T., Rahma A.M.S., Abdulwahab H.B., An E-Commerce Recommendation System Based on Dynamic Analysis of Customer Behavior, Sustainability, 13, (2021); Wang B., Ye F., Xu J., A Personalized Recommendation Algorithm Based on the User’s Implicit Feedback in E-Commerce, Future Internet, 10, (2018); Agdas D., Warne D.J., Osio-Norgaard J., Masters F.J., Utility of Genetic Algorithms for Solving Large-Scale Construction Time-Cost Trade-Off Problems, J. Comput. Civ. Eng, 32, (2018); Yildirim H.A., Akcay C., Time-cost optimization model proposal for construction projects with genetic algorithm and fuzzy logic approach, Rev. Construcción, 18, pp. 554-567, (2019); Akcay C., Manisali E., Fuzzy decision support model for the selection of contractor in construction works, Rev. Construcción, 17, pp. 258-266, (2018); Ji S.-H., Ahn J., Lee H.-S., Han K., Cost Estimation Model Using Modified Parameters for Construction Projects, Adv. Civ. Eng, 2019, pp. 1-10, (2019); Cheng M.-Y., Hoang N.-D., Interval estimation of construction cost at completion using least squares support vector machine, J. Civ. Eng. Manag, 20, pp. 223-236, (2014); Hossin M., Sulaiman M.N., A Review on Evaluation Metrics for Data Classification Evaluations, Int. J. Data Min. Knowl. Manag. Process, 5, (2015); Krantz J., Larsson J., Exploring the Case Study Usage in Construction Engineering and Management Research, ICCREM, 2017, pp. 38-46, (2017); Tzeng G.H., Yang Y., Lin C.T., Chie C., Hierarchical MADM with fuzzy integral for evaluating enterprise intranet web sites, Inf. Sci, 169, pp. 409-426, (2005); Li L., Mao C., Sun H., Yuan Y., Lei B., Digital twin driven green performance evaluation methodology of intelligent manufacturing: Hybrid model based on fuzzy rough-sets AHP, multistage weight synthesis, and PROMETHEE II, Complexity, 2020, pp. 1-24, (2020); Aouam T., Chang S.I., Lee E.S., Fuzzy MADM: An outranking method, Eur. J. Oper. Res, 145, pp. 317-328, (2003)","A. Sfichi; Glocal Soft SRL, Suceava, Strada Fântâna Albă nr. 1, 720247, Romania; email: adrian.sfichi@glocasoft.net; E. Zadobrischi; Department of Computers, Electronics and Automation, Faculty of Electrical Engineering and Computer Science, “Stefan Cel Mare” University, Suceava, No. 13. Str. Universitatii, 720229, Romania; email: eduard.zadobrischi@usm.ro",null,"MDPI",{"$nulls":5},2.6734001E7,null,null,null,"English","Telecom.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85146819266"]
["Wicaksono S.; Lin X.; Tavasszy L.A.","Wicaksono, Satrio (57225371622); Lin, Xiao (57013801300); Tavasszy, Lóránt A. (41762713200)","57225371622; 57013801300; 41762713200","Market potential of bicycle crowdshipping: A two-sided acceptance analysis",2022.0,"Research in Transportation Business and Management",45.0,null,100660.0,null,null,null,13.0,"10.1016/j.rtbm.2021.100660","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85107037515&doi=10.1016%2fj.rtbm.2021.100660&partnerID=40&md5=c5d090dd910979d9fe3abb1841375573","Dept. Transport and Planning, Delft University of Technology, Delft, Netherlands","Wicaksono S., Dept. Transport and Planning, Delft University of Technology, Delft, Netherlands; Lin X., Dept. Transport and Planning, Delft University of Technology, Delft, Netherlands; Tavasszy L.A., Dept. Transport and Planning, Delft University of Technology, Delft, Netherlands","Crowdshipping has recently emerged as a sustainable option for urban parcel delivery, where transport tasks are carried out by regular citizens who are engaged in a passenger trip, instead of the usual professional carriers. A key challenge for such as service offering is to maintain a sustainable network of customers (demand) and couriers (supply). This paper quantitatively explores how demand and supply functions for bicycle crowdshipping meet in a parcel delivery market. Earlier literature has identified factors that determine the success of this business model. We build on this to estimate the potential of the new services, by means of a market equilibrium model. A case study is presented from the Netherlands which uses tailor-made surveys, bicycle trip data and online shopping statistics. The study quantifies the importance of influencing factors. The insights can be used to design a bike crowdshipping platform which brings together the demand and the supply sides effectively. Future research could go into platform design, more accurate behavioral models as well as into advanced pricing approaches. © 2021 The Authors","Acceptance analysis; Bicycle; City logistics; Crowdshipping; Demand; Market potential; Supply",{"$nulls":7},"Arslan A., Agatz N., Klapp M., Splitting shopping and delivery tasks in an on-demand personal shopper service, (2019); Bierlaire M., BIOGEME: A free package for the estimation of discrete choice models, Swiss transport research conference, pp. 19-21, (2003); Carson R.T., Louviere J.J., Anderson D.A., Arabie P., Bunch D.S., Hensher D.A., Timmermans H., Experimental analysis of choice, Marketing letters, 54, pp. 351-367, (1994); Caussade S., de Dios Ortuzar J., Rizzi L.I., Hensher D.A., Assessing the influence of design dimensions on stated choice experiment estimates, Transportation Research Part B: Methodological, 39, 7, pp. 621-640, (2005); Cen C., Cheng S.F., Lau H.C., Misra A., Towards City-scale mobile crowdsourcing: Task recommendations under trajectory uncertainties, Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence (IJCAI 2015): Buenos Aires, Argentina, 25–31 July 2015., pp. 1113-1119, (2015); Centraal Bureau voor de Statistiek, Transport and mobility report, (2016); Chen C., Pan S., Wang Z., Zhong R.Y., Et al., Using taxis to collect citywide E-commerce reverse flows: A crowdsourcing solution, International Journal of Production Research, 55, 7, pp. 1833-1844, (2017); Chi P.-Y., Batra A., Hsu M., Mobile crowdsourcing in the wild: Challenges from a global community, 20th international conference on human-computer interaction with mobile devices and services adjunct, pp. 410-415, (2018); cyclelogistics.eu, CityChangerCargoBike: General analysis report, (2019); Ermagun A., Stathopoulos A., To bid or not to bid: An empirical study of the supply determinants of crowd-shipping, Transportation Research Part A: Policy and Practice, 116, pp. 468-483, (2018); Ermagun A., Shamshiripour A., Stathopoulos A., Performance analysis of crowd-shipping in urban and suburban areas, Transportation, pp. 1-31, (2019); European Environment Agency, Monitoring CO2 emissions from new passenger cars and vans in 2015, (2015); Frehe V., Mehmann J., Teuteberg F., Understanding and assessing crowd logistics business models–using everyday people for last mile delivery, The Journal of Business and Industrial Marketing, 32, 1, pp. 75-97, (2017); Gatta V., Marcucci E., Nigro M., Serafini S., Sustainable urban freight transport adopting public transport-based crowdshipping for B2C deliveries, European Transport Research Review, 11, 1, (2019); Guglielmo C., Turns out amazon, touting drone delivery, does sell lots of products that weigh less than 5 pounds, (2013); Huber J., Zwerina K., The importance of utility balance in efficient choice designs, Journal of Marketing Research, 33, 3, pp. 307-317, (1996); KiM Netherlands Institute for Transport Policy Analysis, Mobility report 2016, (2016); Kontoleon A., Yabe M., Assessing the impacts of alternative “opt-out”formats in choice experiment studies: Consumer preferences for genetically modified content and production information in food, Journal of Agricultural policy Resources, 5, 1, pp. 1-43, (2003); Le T.V., Ukkusuri S.V., Crowd-shipping services for last mile delivery: Analysis from survey data in two countries, 97th Annual Meeting Transportation Research Board, (2018); Le T.V., Ukkusuri S.V., Selectivity correction in discrete-continuous models for the willingness to work as crowd-shippers and travel time tolerance, 97th Annual Meeting Transportation Research Board, (2018); Le T.V., Ukkusuri S.V., Modeling the willingness to work as crowd-shippers and travel time tolerance in emerging logistics services, Travel Behaviour and Society, 15, pp. 123-132, (2019); Le T.V., Stathopoulos A., van Woensel T., Ukkusuri S.V., Supply, demand, operations, and management of crowd-shipping services: A review and empirical evidence, Transportation Research Part C: Emerging Technologies, 103, pp. 83-103, (2019); Louviere J.J., Hensher D.A., Swait J.D., Stated choice methods: Analysis and applications, (2000); Lozza R., Crowdsourcing logistics in e-commerce b2c: A model to evaluate costs in different scenarios, School of industrial and information engineering, (2016); Maes J., Vanelslander T., The use of bicycle messengers in the logistics chain, concepts further revised, Procedia - Social and Behavioral Sciences, 39, pp. 409-423, (2012); Marcucci E., Le Pira M., Carrocci C.S., Gatta V., Pieralice E., Connected shared mobility for passengers and freight: Investigating the potential of crowdshipping in urban areas, Proceedings of the 2017 5th IEEE international conference on models and technologies for intelligent transportation systems (MT-ITS), pp. 839-843, (2017); McKinnon A.C., A communal approach to reducing urban traffic levels, (2016); Miller J., Nie Y., Stathopoulos A., Crowdsourced urban package delivery: Modeling traverler willingness to work as crowdshippers, Transportation Research Record, 2610, 1, pp. 67-75, (2017); Molin E., An introduction to stated choice experiment, Lecture Notes, (2016); Paleti R., Vovsha P., Givon D., Birotker Y., Impact of individual daily travel pattern on value of time, Transportation, 42, 6, pp. 1003-1017, (2015); Paloheimo H., Lettenmeier M., Waris H., Transport reduction by crowdsourced deliveries – A library case in Finland, Journal of Cleaner Production, 132, pp. 240-251, (2016); Punel A., Stathopoulos A., Modeling the acceptability of crowdsourced goods deliveries: Role of context and experience effects, Transportation Research Part E: Logistics and Transportation Review, 105, pp. 18-38, (2017); Punel A., Ermagun A., Stathopoulos A., Studying determinants of crowd-shipping use, Travel Behaviour and Society, 12, pp. 30-40, (2018); Punel A., Ermagun A., Stathopoulos A., How Different Are Crowd-shipping Users and Non-users?, 97th Transportation Research Board Annual Meeting, (2018); PYMNTS, Lyft has 35 percent of us rideshare market, (2018); Rouges J.-F., Montreuil B., Crowdsourcing delivery: New interconnected business models to reinvent delivery, 1st international physical internet conference, pp. 1-19, (2014); Rudolph C., Gruber J., Cargo cycles in commercial transport: Potentials, constraints, and recommendations, Research in Transportation Business & Management, 24, pp. 26-36, (2017); Soto Setzke D., Pflugler C., Schreieck M., Frohlich S., Wiesche M., Krcmar H., Matching drivers and transportation requests in crowdsourced delivery systems, 23rd Americas conference on information systems, pp. 1-10, (2017); Statista, Preferred delivery locations among online consumers in the Netherlands in 2015, (2015); Statista, Total number of licensed drivers in the U.S. in 2018, by state, (2020); Weltevreden J.W.J., B2c e-commerce logistics: The rise of collection-and-delivery points in the Netherlands, International Journal of Retail & Distribution Management, 36, 8, pp. 638-660, (2008)","X. Lin; Dept. Transport and Planning, Delft University, Netherlands; email: x.lin@tudelft.nl",null,"Elsevier Ltd",{"$nulls":5},2.2105395E7,null,null,null,"English","Res. Transport. Bus. Manage.","Article","Final","All Open Access; Green Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85107037515"]
["Ma Z.","Ma, Zhijun (57469710300)",5.74697103E10,"An Optimization Algorithm of Overseas Surgical Warehouse Location of Cross-Border Medical Supply Chain Network Based on Parallel Big Data Mining",2023.0,"Journal of Testing and Evaluation",51.0,1.0,"JTE20210449",null,null,null,0.0,"10.1520/JTE20210449","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85125381517&doi=10.1520%2fJTE20210449&partnerID=40&md5=3fa9cb4a484894ed00a0cc41a4b4f2ac","School of Management Science and Engineering, Zhengzhou University of Aeronautics, No. 15, Wenyuan West Rd., Zhengdongxinqu, Henan province, Zhengzhou, 450046, China","Ma Z., School of Management Science and Engineering, Zhengzhou University of Aeronautics, No. 15, Wenyuan West Rd., Zhengdongxinqu, Henan province, Zhengzhou, 450046, China","Because the current algorithm fails to combine the actual needs of the demand area to build the market-value evaluation system, the user satisfaction and optimal probability decrease, and the minimum cost of the system increases. This paper proposes an optimization algorithm of overseas surgical warehouse location in the cross-border medical supply chain network based on parallel big data mining. Taking the overseas warehouse location problem of cross-border e-commerce enterprises as the research background, the paper establishes an overseas warehouse with parallel big data mining technology in the case of domestic supply points determined, so as to meet the demand of the overseas market for distribution services. According to the cross-border transportation cost, local transportation cost, and warehouse building operation cost, the total logistics cost of overseas warehouse mode is composed; the actual demand of overseas warehouse location is analyzed; and the market value is introduced into the decision-making of overseas warehouse location. Through the preliminary analysis of the factors affecting the market value, combined with the level analysis method, the market-value evaluation system of demand area is constructed, and the market value right of each demand area is calculated. By introducing the concept of time window, the customer satisfaction function is established based on whether the delivery time meets the customer's psychological expectation; by introducing market value and customer satisfaction, the multi-objective location model of customer satisfaction considering cost and market value is established. The improved particle swarm optimization algorithm is applied to the multi-objective model to solve the multi-objective location problem with constraints, so as to obtain a higher market share and determine the best location. Simulation results show that the proposed algorithm can effectively improve user satisfaction and optimal probability and reduce the lowest cost of the system. Copyright © 2022 by ASTM International","Cross-border supply chain network; Location optimization algorithm; Overseas warehouse; Parallel big data mining","Big data; Commerce; Competition; Costs; Customer satisfaction; Decision making; Hospitals; Location; Particle swarm optimization (PSO); Sales; Supply chains; Surgery; Warehouses; Cross-border; Cross-border supply chain network; Customers' satisfaction; Market values; Network-based; Optimization algorithms; Oversea warehouse; Parallel big data mining; Supply chain network; Warehouse location; Data mining",{"$nulls":6},"Chang F.-J., Chen P.-A., Lu Y.-R., Huang E., Chang K.-Y., Real-Time Multi-step-ahead Water Level Forecasting by Recurrent Neural Networks for Urban Flood Control, Journal of Hydrology, 517, pp. 836-846, (2014); Elci A., Tamer Ayvaz M., Differential-evolution algorithm based optimization for the site selection of groundwater production wells with the consideration of the vulnerability concept, Journal of Hydrology, 511, pp. 736-749, (2014); Xu Y., The capability improvement strategy of cross-border e-commerce supply chain service providers, Financial Forum, 9, 2; Thompson R.G., Takada K., Kobayakawa S., Optimisation of parking guidance and information systems display configurations, Transportation Research Part C: Emerging Technologies, 9, 1, pp. 69-85, (2001); Wu Q., Chen Z., Wang L., Lin H., Jiang Z., Li S., Chen D., Real-time dynamic path planning of mobile robots: A novel hybrid heuristic optimization algorithm, Sensors, 20, 1, (2019); Tang Z.C., Guo C.L., Hou P.X., Fan Y.B., Jia D.M., Optimal planning of electric vehicle charging stations location based on hybrid particle swarm optimization, Advanced Materials Research, 724-725, pp. 1355-1360, (2013); Zhang F., Liang J., Zhang L., Han X., Energy storage capacity optimization for wind farms considering optimal expected output and SOC, Dianli Xitong Zidonhua/Automation of Electric Power Systems, 38, 24, pp. 12-19, (2014); Wang D.-W., Zhang G.-X., Model and algorithm for optimization of rescue center location of emergent catastrophe, Frontiers of Electrical and Electronic Engineering in China, 1, 3, pp. 265-268, (2006); Ma C., Li Y., He R., Diao A., Research on Multi-objective Optimization Model and Its Improved Genetic Algorithm for Emergency Evacuation, Advanced Science Letters, 7, pp. 672-675, (2012); Wang Y., Assogba K., Liu Y., Ma X., Xu M., Wang Y., Two-echelon location-routing optimization with time windows based on customer clustering, Expert Systems with Applications, 104, pp. 244-260, (2018); Wei H., Li A., Jia N., Research on optimization and design of sustainable urban underground logistics network framework, Sustainability, 12, 21, (2020); Ju L., Tan Q., Lu Y., Tan Z., Zhang Y., Tan Q., A CVaR-Robust-Based Multi-objective Optimization Model and Three-Stage Solution Algorithm for a Virtual Power Plant Considering Uncertainties and Carbon Emission Allowances, International Journal of Electrical Power & Energy Systems, 107, pp. 628-643, (2019); Sheriff K.M.M., Nachiappan S., Min H., Combined Location and Routing Problems for Designing the Quality-Dependent and Multi-product Reverse Logistics Network, Journal of The Operational Research Society, 65, 6, pp. 873-887, (2014); Rajesh P., Naveen C., Venkatesan A.K., Shajin F.H., An optimization technique for battery energy storage with wind turbine generator integration in unbalanced radial distribution network, Journal of Energy Storage, 43, (2021); Shojaeian S., Naeeni E.S., Dolatshahi M., Khani H., A PSO-DP based method to determination of the optimal number, location, and size of FACTS devices in power systems, Advances in Electrical and Computer Engineering, 14, 1, pp. 109-114, (2014); Hagelsteen K., Johansson B.-M., Bergenfelz A., Mathieu C., Identification of warning signs during selection of surgical trainees, Journal of Surgical Education, 76, 3, pp. 684-693, (2019); Matthew G.J., Nuttall W.J., Mestel B., Dooley L.S., A dynamic simulation of low-carbon policy influences on endogenous electricity demand in an isolated island system, Energy Policy, 109, pp. 121-131, (2017); Rashidi S., Saghaei A., Sadjadi S.J., Said-Nezhad S., Optimizing supply chain network design with location-inventory decisions for perishable items: A Pareto-based MOEA approach, Scientia Iranica, 23, 6, pp. 3025-3045, (2016); Yang Z., Chu F., Chen H., A cut-and-solve based algorithm for the single-source capacitated facility location problem, European Journal of Operational Research, 221, 3, pp. 521-532, (2012); Li Y.L., Wang C., Research on Feasible Direction Variation of Multi-objective Genetic Algorithms and Simulation, Applied Mechanics and Materials, 644-650, pp. 1965-1968, (2014); Li J., Chu F., Chen H., Model and algorithm for the vendor-warehouse transportation and inventory problem in a three-level distribution system, IFAC Proceedings Volumes, 41, 2, pp. 13097-13102, (2008); Firoozi Z., Tang S.H., Ariafar S., Ariffin M.K.A.M., An optimization approach for a joint location inventory model considering quantity discount policy, Arabian Journal for Science and Engineering, 38, 4, pp. 983-991, (2013); Ahuja R.K., Cunha C.B., Very large-scale neighborhood search for the k-constraint multiple knapsack problem, Journal of Heuristics, 11, 5-6, pp. 465-481, (2005); Zhao S., Zhang K., A distributionally robust optimization approach to reconstructing missing locations and paths using high-frequency trajectory data, Transportation Research Part C: Emerging Technologies, 102, pp. 316-335, (2019)","Z. Ma; School of Management Science and Engineering, Zhengzhou University of Aeronautics, Zhengzhou, No. 15, Wenyuan West Rd., Zhengdongxinqu, Henan province, 450046, China; email: gary_2000@126.com",null,"ASTM International",{"$nulls":5},903973.0,null,"JTEVA",null,"English","J Test Eval","Article","Final",null,"Scopus","2-s2.0-85125381517"]
["Sapry H.R.Md.; Nordin N.; Ahmad A.R.; Baskaran S.","Sapry, Hairul Rizad Md (56300099700); Nordin, Nurfaziq (57979346700); Ahmad, Abd Rahman (57214510723); Baskaran, Shathees (57202010861)","56300099700; 57979346700; 57214510723; 57202010861","Investigation of Customer Purchase Intention Towards Car Battery On-Site Delivery Services",2022.0,"Journal of Optimization in Industrial Engineering",15.0,2.0,null,249.0,255.0,6.0,0.0,"10.22094/joie.2022.1962052.1970","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85142518185&doi=10.22094%2fjoie.2022.1962052.1970&partnerID=40&md5=f6e1ad209dffd3a006418796657fc97d","Universiti Kuala Lumpur, Malaysia Institute of Industrial Technology (UniKL MITEC), Malaysia; Universiti Tun Hussion Onn (UTHM), Malaysia; Universiti Teknologi Malaysia (UTM), Malaysia","Sapry H.R.Md.; Nordin N., Universiti Kuala Lumpur, Malaysia Institute of Industrial Technology (UniKL MITEC), Malaysia; Ahmad A.R., Universiti Tun Hussion Onn (UTHM), Malaysia; Baskaran S., Universiti Teknologi Malaysia (UTM), Malaysia","This study investigates the factors that influence customers' purchase intention among Bateriku.com customers. Through a self-administered questionnaire, data were collected from eighty-eight (88) customers who had experience using the service of on-site delivery of a car battery. This study is aimed to investigate perceptions of the customer on a new business model introduced by Bateriku.com for the purchase of the car battery and how this perception impacts the actual purchase that the customers make. This study will turn out to be a benchmark in comparing with the traditional purchase processes of the car battery and to understand the factors influencing the customers towards their purchase of the car battery using a new business process. Three (3) independent variables were identified namely technology, service marketing, and people to investigate its impact on actual purchase by employing multiple regression analysis. The results of the study indicated that service marketing has a significant influence on customer purchase intention for the car battery on-site delivery. The results also showed the impact of technology in improving customer confidence towards the new business model. The recommendations are also provided to Bateriku.com to exploit the advancement in technology to minimize further human interaction during the inquiry process to introduce process standardization for efficient operation. This study presents a foundational framework for future researchers to embark on new avenues in producing in-depth insights about new business models in acquiring car batteries and related services. © 2022 Qazvin Islamic Azad University. All rights reserved.","Car Battery On-Site Delivery; Customer Purchase Intention; E-commerce",{"$nulls":7},"Reemah Abdulghader Abu, Et al., Challenges of security, protection and trust on E-commerce: A case study of online purchasing in Libya, International Journal of Advanced Research in Computer and Communication Engineering, 1, 3, (2012); Demangeot C., Broderick A. J., Consumer perceptions of online shopping environments, Psychology & Marketing, 30, 6, pp. 461-469, (2010); Haque A., Anwar N., Yasmin F., Sarwar A., Ibrahim Z., Momen A., Purchase intention of foreign products: A study on the Bangladeshi consumer perspective, SAGE Open, 5, 2, (2015); Hoque M. R., Ali M. A., Mahfuz M. A., An Empirical Investigation on the adoption of e-commerce in Bangladesh, Asia Pacific Journal of Information Systems, 25, 1, (2015); Gong W., Stump R. L., Maddox L. M., Factors influencing consumers’ online shopping in China, Journal of Asia Business Studies, 7, 3, pp. 214-230, (2013); Liu X., He M., Gao F., Xie P., An empirical study of online shopping customer satisfaction in China: A holistic perspective, International Journal of Retail & Distribution Management, 36, 11, pp. 919-940, (2008); Katawetawaraks C., Wang C. L., Online shopper behavior: Influences of online shopping decision, Asian Journal of Business Research, 1, 2, (2011); Koufaris M., Kambil A., LaBarbera P. A., Consumer behavior in web-based commerce: An empirical study, International Journal of Electronic Commerce, 6, 2, pp. 115-138, (2001); Kim C., Zhao W., Yang K. H., An empirical study on the integrated framework of e-CRM in online shopping, Journal of Electronic Commerce in Organizations, 6, 3, pp. 1-19, (2008); Koufaris M., Applying model and technology flow theory behavior acceptance to the online consumer, Information Systems Research, 13, 2, pp. 205-223, (2002); Laforet S., Li X., Consumers' attitudes toward online and mobile banking in China, International Journal of Bank Marketing, 23, 5, pp. 362-380, (2005); Liao S. H., Chu P. H., Chen Y. J., Chang C. C., Mining customer knowledge for exploring online group buying behavior, Expert Systems with Applications, 39, 3, pp. 3708-3716, (2012); Lee G., Lin H., Customer perceptions of e‐ service quality in online shopping, International Journal of Retail & Distribution Management, 33, 2, pp. 161-176, (2005); Mudambi S. M., Schuff D., What makes a helpful online review? A study of customer reviews on Amazon. com, MIS Quarterly, 34, 1, pp. 185-200, (2010); Silverio-Fernandez Manuel, What is a smart device? - a conceptualization within the paradigm of the internet of things, (2018); Rahman Mohammad Anisur, Consumer buying behavior towards online shopping: An empirical study on Dhaka city, Bangladesh, Journal Cogent Business & Management, 5, 1, (2018); Pallant J., SPSS Survival Manual: A Step by Step Guide to Data Analysis Using SPSS for Windows (Version 12), (2002); Pallant J., SPSS Survival Manual: A Step by Step Guide to Data Analysis Using SPSS, (2005); Sabbir Rahman M., Dynamics of consumers' perception, demographic characteristics and consumers' behavior towards the selection of a restaurant: An exploratory study on Dhaka city consumers, Business Strategy Series, 13, 2, pp. 75-88, (2012); Tabachnick B. G., Fidell L. S., Using Multivariate Statistics, (2001); Vegiayan K. D., Ming C. W., Harun M. L. O., Online shopping and customer satisfaction in Malaysia, International Journal of Marketing Practices, 1, 1, pp. 43-51, (2013); Zuroni M. J., Goh H. L., Factors influencing consumers’ attitude towards e-commerce purchases through online shopping, International Journal of Humanities and Social Science, 2, 4, pp. 223-230, (2012)","H.R.Md. Sapry; Universiti Kuala Lumpur, Malaysia Institute of Industrial Technology (UniKL MITEC), Malaysia; email: hairulrizad@unikl.edu.my",null,"Qazvin Islamic Azad University",{"$nulls":5},2.2519904E7,null,null,null,"English","J. Optim. Ind. Eng.","Article","Final",null,"Scopus","2-s2.0-85142518185"]
["Schaap H.; Schiffer M.; Schneider M.; Walther G.","Schaap, Hendrik (57931535500); Schiffer, Maximilian (57193122624); Schneider, Michael (57192278274); Walther, Grit (22942752600)","57931535500; 57193122624; 57192278274; 22942752600","A Large Neighborhood Search for the Vehicle Routing Problem with Multiple Time Windows",2022.0,"Transportation Science",56.0,5.0,null,1369.0,1392.0,23.0,7.0,"10.1287/trsc.2021.1120","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85140031167&doi=10.1287%2ftrsc.2021.1120&partnerID=40&md5=198d522cd7c97b9916fdb133dd7a10cc","Chair of Operations Management, School of Business and Economics, RWTH Aachen University, Aachen, 52072, Germany; School of Management, Munich Data Science Institute, Technical University of Munich, Munich, 80333, Germany; Deutsche Post Chair – Optimization of Distribution Networks, School of Business and Economics, RWTH Aachen University, Aachen, 52072, Germany","Schaap H., Chair of Operations Management, School of Business and Economics, RWTH Aachen University, Aachen, 52072, Germany; Schiffer M., School of Management, Munich Data Science Institute, Technical University of Munich, Munich, 80333, Germany; Schneider M., Deutsche Post Chair – Optimization of Distribution Networks, School of Business and Economics, RWTH Aachen University, Aachen, 52072, Germany; Walther G., Chair of Operations Management, School of Business and Economics, RWTH Aachen University, Aachen, 52072, Germany","User-centered logistics that aim at customer satisfaction are gaining importance because of growing e-commerce and home deliveries. Customer satisfaction can be strongly increased by offering narrow delivery time windows. However, there is a tradeoff for the logistics provider because user-friendly delivery time windows might decrease operational flexibility. Against this background, we study the vehicle routing problem with multiple time windows (VRPMTW) that determines a set of optimal routes such that each customer is visited once within one out of several time windows. We present a large neighborhood search–based metaheuristic for the VRPMTW that contains a dynamic programming component to optimally select a time window for each customer on a route, and we present computationally efficient move descriptors for all search operators. We evaluate the performance of our algorithm on the Belhaiza instance set for the objectives of minimizing traveled distance and duration. For the former objective, we provide new best-known solutions for 9 of 48 instances, and for the latter, we provide new best-known solutions for 13 of 48 instances. Overall, our algorithm provides the best average solution quality over the full benchmark set among all available algorithms. Furthermore, we design new benchmark instances that reflect planning tasks in user-centered last-mile logistics. Based on these, we present managerial studies that show the benefit of our algorithm for practitioners and allow to derive insights on how to offer time windows to customers. We show that offering multiple time windows can be economically beneficial for the logistics service providers and increases customer flexibility simultaneously. Copyright: © 2022 INFORMS.","dynamic programming; efficient route evaluation; multiple time windows; vehicle routing","Benchmarking; Customer satisfaction; Sales; Vehicle routing; Vehicles; Customers' satisfaction; Delivery time windows; E- commerces; Efficient route evaluation; Large neighbourhood searches; Multiple time windows; Route evaluations; Time windows; User-centred; Vehicle Routing Problems; Dynamic programming",{"$nulls":4},"Bundesministerium für Wirtschaft und Energie, BMWi, (01ME16003B)","Funding: This work was partially funded by the Bundesministerium für Wirtschaft und Energie within Project iMove [Grant 01ME16003B]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/trsc.2021.1120.","Amorim P, Parragh SN, Sperandio F, Almada-Lobo B, A rich vehicle routing problem dealing with perishable food: A case study, TOP, 22, 2, pp. 489-508, (2014); Baltz A, El Ouali M, Jager G, Sauerland V, Srivastav A, Exact and heuristic algorithms for the travelling salesman problem with multiple time windows and hotel selection, J. Oper. Res. Soc, 66, 4, pp. 615-626, (2015); Belhaiza S, Hansen P, Laporte G, A hybrid variable neighborhood tabu search heuristic for the vehicle routing problem with multiple time windows, Comput. Oper. Res, 52, pp. 269-281, (2014); Belhaiza S, M'Hallah R, Ben Brahim G, A new hybrid genetic variable neighborhood search heuristic for the vehicle routing problem with multiple time windows, Proc. IEEE Congress on Evolutionary Computation, pp. 1319-1326, (2017); Belhaiza S, M'Hallah R, Ben Brahim G, Laporte G, Three multistart data-driven evolutionary heuristics for the vehicle routing problem with multiple time windows, J. Heuristics, 25, 3, pp. 485-515, (2019); Bell WJ, Dalberto LM, Fisher ML, Greenfield AJ, Jaikumar R, Kedia P, Mack RG, Et al., Improving the distribution of industrial gases with an on-line computerized routing and scheduling optimizer, Interfaces, 13, 6, pp. 4-23, (1983); Bogue ET, Ferreira HS, Noronha TF, Prins C, A column generation and a post optimization VNS heuristic for the vehicle routing problem with multiple time windows, Optim. Lett, 16, 1, pp. 79-95, (2022); Clarke G, Wright JW, Scheduling of vehicles from a central depot to a number of delivery points, Oper. Res, 12, 4, pp. 568-581, (1964); Cordeau JF, Laporte G, Mercier A, A unified tabu search heuristic for vehicle routing problems with time windows, J. Oper. Res. Soc, 52, 8, pp. 928-936, (2001); de Jong C, Kant G, Vliet A, On finding minimal route duration in the vehicle routing problem with multiple time windows, (1996); Favaretto D, Moretti E, Pellegrini P, Ant colony system for a VRP with multiple time windows and multiple visits, J. Interdisciplinary Math, 10, 2, pp. 263-284, (2007); Ferreira HS, Bogue ET, Noronha TF, Belhaiza S, Prins C, Variable neighborhood search for vehicle routing problem with multiple time windows, Electronic Notes Discrete Math, 66, pp. 207-214, (2018); Fisher ML, Optimal solution of vehicle routing problems using minimum k-trees, Oper. Res, 42, 4, pp. 626-642, (1994); Head T, Kumar M, Nahrstaedt H, Louppe G, Shcherbatyi I, scikit-optimize/scikit-optimize (v0.9.0), Zenodo, (2021); Hemmelmayr VC, Cordeau JF, Crainic TG, An adaptive large neighborhood search heuristic for two-echelon vehicle routing problems arising in city logistics, Comput. Oper. Res, 39, 12, pp. 3215-3228, (2012); Hiermann G, Puchinger J, Ropke S, Hartl RF, The electric fleet size and mix vehicle routing problem with time windows and recharging stations, Eur. J. Oper. Res, 252, 3, pp. 995-1018, (2016); Hoogeboom M, Dullaert W, Lai D, Vigo D, Efficient neighborhood evaluations for the vehicle routing problem with multiple time windows, Transportation Sci, 54, 2, pp. 400-416, (2020); Ibaraki T, Imahori S, Kubo M, Masuda T, Uno T, Yagiura M, Effective local search algorithms for routing and scheduling problems with general time-window constraints, Transportation Sci, 39, 2, pp. 206-232, (2005); Kindervater GAP, Savelsbergh MWP, Vehicle routing: Handling edge exchanges, Local Search in Combinatorial Optimization, pp. 337-360, (1997); Kytojoki J, Nuortio T, Braysy O, Gendreau M, An efficient variable neighborhood search heuristic for very large scale vehicle routing problems, Comput. Oper. Res, 34, 9, pp. 2743-2757, (2007); Larsen R, Pacino D, Fast delta evaluation for the vehicle routing problem with multiple time windows, (2019); Nagata Y, Braysy O, Dullaert W, A penalty-based edge assembly memetic algorithm for the vehicle routing problem with time windows, Comput. Oper. Res, 37, 4, pp. 724-737, (2010); Or I, Traveling salesman-type problems and their relation to the logistics of regional blood banking, (1976); Paulsen N, Diedrich F, Jansen K, Heuristic approaches to minimize tour duration for the TSP with multiple time windows, Proc. 15th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (Dagstuhl-Leibniz-Zentrum fuer Informatik), pp. 42-55, (2015); Pisinger D, Ropke S, A general heuristic for vehicle routing problems, Comput. Oper. Res, 34, 8, pp. 2403-2435, (2007); Pisinger D, Ropke S, Large neighborhood search, Handbook of Metaheuristics, (2010); Potvin JY, Rousseau JM, An exchange heuristic for routing problems with time windows, J. Oper. Res. Soc, 46, 12, pp. 1433-1446, (1995); Ribeiro G, Laporte G, An adaptive large neighborhood search heuristic for the cumulative capacitated vehicle routing problem, Comput. Oper. Res, 39, 3, pp. 728-735, (2012); Ropke S, Pisinger D, An adaptive large neighborhood search heuristic for the pickup and delivery problem with time windows, Transportation Sci, 40, 4, pp. 455-472, (2006); Schneider M, Sand B, Stenger A, A note on the time travel approach for handling time windows in vehicle routing problems, Comput. Oper. Res, 40, 10, pp. 2564-2568, (2013); Shaw P, Using constraint programming and local search methods to solve vehicle routing problems, Principles and Practice of Constraint Programming—CP98, pp. 417-431, (1998); Solomon MM, Algorithms for the vehicle routing and scheduling problems with time window constraints, Oper. Res, 35, 2, pp. 254-265, (1987); Tricoire F, Romauch M, Doerner KF, Hartl RF, Heuristics for the multi-period orienteering problem with multiple time windows, Comput. Oper. Res, 37, 2, pp. 351-367, (2010); Vidal T, Crainic TG, Gendreau M, Prins C, A unified solution framework for multi-attribute vehicle routing problems, Eur. J. Oper. Res, 234, 3, pp. 658-673, (2014); Xu H, Chen ZL, Rajagopal S, Arunapuram S, Solving a practical pickup and delivery problem, Transportation Sci, 37, 3, pp. 347-364, (2003)","M. Schiffer; School of Management, Munich Data Science Institute, Technical University of Munich, Munich, 80333, Germany; email: schiffer@tum.de",null,"INFORMS Inst.for Operations Res.and the Management Sciences",{"$nulls":5},411655.0,null,"TRSCB",null,"English","Transp Sci","Article","Final",null,"Scopus","2-s2.0-85140031167"]
["Dhaigude S.A.; Mohan B.C.","Dhaigude, Soma Amol (57385143700); Mohan, Bijuna C. (55747046100)","57385143700; 55747046100","Logistics Service Quality in Online Shopping: A Bibliometric Analysis",2023.0,"Journal of Internet Commerce",22.0,1.0,null,157.0,188.0,31.0,4.0,"10.1080/15332861.2021.2011598","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121683631&doi=10.1080%2f15332861.2021.2011598&partnerID=40&md5=5c4a233c16360b0daa5cd25be2bd1a85","School of Management, National Institute of Technology Karnataka, Surathkal, India","Dhaigude S.A., School of Management, National Institute of Technology Karnataka, Surathkal, India; Mohan B.C., School of Management, National Institute of Technology Karnataka, Surathkal, India","This paper outlines the main areas and latest developments of logistics service quality (LSQ) in the context of business to consumer (B2C) online shopping and proposes future research directions. More specifically, this paper has three objectives: What is the status of research of LSQ in B2C e-tailing? Which themes involving the field are the most popular among scholars? What are the possibilities for future research? This study examined a sample of 177 papers from the Scopus and ISI Web of Science databases to find research activity on LSQ in B2C online shopping between 2001 and early 2021 using bibliometric analysis. The methodology involves selecting, analyzing, and classifying 177 papers into authors, journals, time, focus areas, keywords, country, citation, co-citation, and thematic distribution analysis. Four major themes have emerged, LSQ for integrating traditional retail with omnichannel retail; LSQ and inventory management; LSQ and supply chain collaboration and LSQ transformation to E-LSQ. It gives researchers and scholars information to help them work on new developments of LSQ in B2C e-tailing and create strategies, models, and structures for increasing firm performance and customer satisfaction. © 2021 Taylor & Francis Group, LLC.","Bibliometric analysis; business to consumer; internet commerce; logistics service quality; omnichannel retailing; online shopping",{"$nulls":7},{"$cut":{"chars":22374,"head":"Abu ELSamen A.A., Online service quality and brand equity: The mediational roles of perceived value and customer satisfaction, Journal of Internet Commerce, 14, 4, pp. 509-530, (2015); Acimovic J., Graves S.C., Making better fulfillment decisions on the fly in an online retail environment, Manufacturing & Service Operations Management, 17, 1, pp. 34-51, (2015); Agatz N.A., Fleischmann M., Van Nunen J.A., E-fulfillment and multichannel distribution–a review, European Journal of Operational Research, 187, 2, pp. 339-356, (2008); Ahmad A., Rahman O., Khan M.N., Consumer's perception of website service quality: An empirical study, Journal of Internet Commerce, 15, 2, pp. 125-141, (2016); Ahn T., Ryu S., Han I., The impact of Web quality and playfulness on user acceptance of online retailing, Information & Management, 44, 3, pp. 263-275, (2007); Akar E., Customers’ online purchase intentions and customer segmentation during the period of COVID-19 pandemic, Journal of Internet Commerce, 20, 3, pp. 371-331, (2021); AlRyalat S.A.S., Malkawi L.W., Momani S.M., Comparing bibliometric analysis using PubMed, Scopus, and Web of Science databases, Journal of Visualized Experiments, 152, (2019); (2020); Bell D.R., Gallino S., Moreno A., How to win in an omnichannel world, MIT Sloan Management Review, 56, 1, (2014); Bienstock C.C., Mentzer J.T., Bird M.M., Measuring physical distribution service quality, Journal of the Academy of Marketing Science, 25, 1, pp. 31-44, (1997); Bienstock C.C., Royne M.B., Sherrell D., Stafford T.F., An expanded model of logistics service quality: Incorporating logistics information technology, International Journal of Production Economics, 113, 1, pp. 205-222, (2008); Bonilla C.A., Merigo J.M., Torres-Abad C., Economics in Latin America: A bibliometric analysis, Scientometrics, 105, 2, pp. 239-252, (2015); Bouzaabia O., van Riel A.C., Semeijn J., Managing in‐store logistics: A fresh perspective on retail service, Journal of Service Management, 24, 2, pp. 112-129, (2013); Bouzaabia R., Bouzaabia O., Capatina A., Retail logistics service quality: A cross‐cultural survey on customer perceptions, International Journal of Retail & Distribution Management, 41, 8, pp. 627-647, (2013); Bressolles G., Lang G., KPIs for performance measurement of e-fulfillment systems in multichannel retailing, International Journal of Retail & Distribution Management, 48, 1, pp. 35-52, (2019); Brozovic D., Strategic flexibility: A review of the literature, International Journal of Management Reviews, 20, 1, pp. 3-31, (2018); Brynjolfsson E., Hu Y.J., Rahman M.S., Competing in the age of omnichannel retailing, (2013); Cancino C.A., Merigo J.M., Coronado F.C., A bibliometric analysis of leading universities in innovation research, Journal of Innovation & Knowledge, 2, 3, pp. 106-124, (2017); Cancino C., Merigo J.M., Coronado F., Dessouky Y., Dessouky M., Forty years of computers & industrial engineering: A bibliometric analysis, Computers & Industrial Engineering, 113, pp. 614-629, (2017); Cao K., Xu Y., Wu Q., Wang J., Liu C., Optimal channel and logistics service selection strategies in the e-commerce context, Electronic Commerce Research and Applications, 48, (2021); Cherrett T., Dickinson J., McLeod F., Sit J., Bailey G., Whittle G., Logistics impacts of student online shopping–evaluating delivery consolidation to halls of residence, Transportation Research Part C: Emerging Technologies, 78, pp. 111-128, (2017); Chiu W.T., Ho Y.S., Bibliometric analysis of tsunami research, Scientometrics, 73, 1, pp. 3-17, (2007); Choi D., Chung C.Y., Young J., Sustainable online shopping logistics for customer satisfaction and repeat purchasing behavior: Evidence from China, Sustainability, 11, 20, (2019); Coppola D., (2021); Danvila-del-Valle I., Estevez-Mendoza C., Lara F.J., Human resources training: A bibliometric analysis, Journal of Business Research, 101, pp. 627-636, (2019); Davis E.R., The role of logistics service quality in creating customer loyalty, pp. 48106-41346, (2006); Davis-Sramek B., Mentzer J.T., Stank T.P., Creating consumer "}},"S.A. Dhaigude; School of Management, National Institute of Technology Karnataka, Surathkal, Karnataka, India; email: somalilhare@gmail.com",null,"Routledge",{"$nulls":5},1.5332861E7,null,null,null,"English","J. Internet Commer.","Article","Final",null,"Scopus","2-s2.0-85121683631"]
["Lee C.K.M.; Ng C.K.; Chung S.Y.; Keung K.L.","Lee, Carman Ka Man (24468281700); Ng, Chun Kit (55772552500); Chung, Sui Ying (57214995159); Keung, Kin Lok (57204574840)","24468281700; 55772552500; 57214995159; 57204574840","Cloud-based Cyber-Physical Logistics System with Nested MAX-MIN Ant Algorithm for E-commerce logistics",2023.0,"Expert Systems with Applications",211.0,null,118643.0,null,null,null,3.0,"10.1016/j.eswa.2022.118643","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85136577347&doi=10.1016%2fj.eswa.2022.118643&partnerID=40&md5=1ed48ef870f762300dffd2878ea86609","Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong","Lee C.K.M., Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong; Ng C.K., Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong; Chung S.Y., Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong; Keung K.L., Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong","E-commerce logistics have required rapid and efficient e-fulfillment services to deliver goods to consumers within a short time window to fulfill the customer order requirement. This paper seeks to address how an E-commerce Logistics Company can utilize the Cyber-Physical Logistics System (CPLS) and Internet of Things (IoT), which may unlock the potential for solving the order assignments and the vehicle routing problems on a new twist. The CPLS allocates orders to suitable vehicles and plans the best route in order to maximize the order fulfillment rate through cloud computing to reduce local computation power. This paper presents a novel Nested MAX-MIN Ant System (MMAS) to tackle a Vehicle Routing Problem (VRP) that can serve as the core element of the CPLS. The objective is to perform to maximize the orders, minimize the total traveling cost and satisfy all the problem constraints. This paper intends to address the issues associated with the VIP priority and drop-off point limitations to make the solution route more realistic and enhance accuracy. The numerical experiences show that the CPLS is implemented successfully in a Hong Kong-based E-commerce Logistics Company with promising performance within reasonable computation times and new better solutions. © 2022 Elsevier Ltd","Ant Colony Optimization; Cyber-Physical Logistics System; Meta-heuristic technique; Order assignment problem; Vehicle routing problem","Ant colony optimization; Combinatorial optimization; Cyber Physical System; Electronic commerce; Internet of things; Vehicle routing; Vehicles; Assignment problems; Cloud-based; Cybe-physical logistic system; Cyber physicals; Logistics company; Logistics system; Meta-heuristic techniques; Order assignment; Order assignment problem; Vehicle Routing Problems; Heuristic methods",{"$nulls":4},"Department of Industrial and Systems Engineering; The Government of the Hong Kong SAR, (ITS/324/17FX/K.ZM31); Innovation and Technology Commission, ITC; Hong Kong Polytechnic University, PolyU","This work was supported in part the Hong Kong Polytechnic University, Hong Kong, Our gratitude is also extended to the Research Committee and the Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong and The Innovation and Technology Commission, The Government of the Hong Kong SAR, Hong Kong under Project ITS/324/17FX/K.ZM31. The authors would like to express their appreciation to the anonymous case company for their assistance with the data collection.","Asghari M., Al-e S.M.J.M., Green vehicle routing problem: A state-of-the-art review, International Journal of Production Economics, 231, (2021); Braekers K., Ramaekers K., Van Nieuwenhuyse I., The vehicle routing problem: State of the art classification and review, Computers & industrial engineering, 99, pp. 300-313, (2016); Cai L., Lv W., Xiao L., Xu Z., Total carbon emissions minimization in connected and automated vehicle routing problem with speed variables, Expert Systems with Applications, 165, (2021); Catay B., Ant colony optimization and its application to the vehicle routing problem with pickups and deliveries, Natural intelligence for scheduling, planning and packing problems, pp. 219-244, (2009); Dantzig G.B., Ramser J.H., The truck dispatching problem, Management Science, 6, 1, pp. 80-91, (1959); El-Sherbeny N.A., Vehicle routing with time windows: An overview of exact, heuristic and metaheuristic methods, Journal of King Saud University-Science, 22, 3, pp. 123-131, (2010); 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Lee; Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong; email: ckm.lee@polyu.edu.hk",null,"Elsevier Ltd",{"$nulls":5},9574174.0,null,"ESAPE",null,"English","Expert Sys Appl","Article","Final",null,"Scopus","2-s2.0-85136577347"]
["Letnik T.; Hanžič K.; Luppino G.; Mencinger M.","Letnik, Tomislav (57191032499); Hanžič, Katja (58034325800); Luppino, Giuseppe (55998859900); Mencinger, Matej (6603500136)","57191032499; 58034325800; 55998859900; 6603500136","Impact of Logistics Trends on Freight Transport Development in Urban Areas",2022.0,"Sustainability (Switzerland)",14.0,24.0,16551.0,null,null,null,2.0,"10.3390/su142416551","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85144954508&doi=10.3390%2fsu142416551&partnerID=40&md5=bac380589307c707d42c3e7e9c5da08e","Faculty of Civil Engineering, Transportation Engineering and Architecture, University of Maribor, Smetanova 17, Maribor, 2000, Slovenia; Institute for Transport and Logistics—ITL, Viale Aldo Moro 38, Bologna, 40127, Italy","Letnik T., Faculty of Civil Engineering, Transportation Engineering and Architecture, University of Maribor, Smetanova 17, Maribor, 2000, Slovenia; Hanžič K., Faculty of Civil Engineering, Transportation Engineering and Architecture, University of Maribor, Smetanova 17, Maribor, 2000, Slovenia; Luppino G., Institute for Transport and Logistics—ITL, Viale Aldo Moro 38, Bologna, 40127, Italy; Mencinger M., Faculty of Civil Engineering, Transportation Engineering and Architecture, University of Maribor, Smetanova 17, Maribor, 2000, Slovenia","City logistics is subject to constant development, generated by new logistics trends and high customers’ expectations. With the aim of creating an effective, acceptable, and sustainable city logistics policy, it is therefore essential to understand logistics trends and their expected impact on the development of urban freight transport in the future. In this paper, we explore and compare the expectations of public authorities, business, and academia regarding the short-, medium-, and long-term impacts of different logistics trends on urban logistics. Following a literature review, the expert survey was used to assess the expected impact and time horizon. According to the respondents, “e-commerce”, “automated vehicles”, “electric vehicles”, “grey power logistics”, “omni-channel logistics”, and the “desire for speed” will have the greatest impact on urban freight transport in the future. An interesting observation concerns some differences of opinion between public and private stakeholders. In general, the business community believes that the identified trends will have a greater impact on urban logistics in a shorter period of time, while public authorities believe that the mentioned trends will have a less strong impact on urban logistics in a longer time scale. This shows the need for more active collaboration between them in the policy-making process. © 2022 by the authors.","logistics trends; policy making; stakeholders’ perspective; urban freight","business development; freight transport; logistics",{"$nulls":4},"Interreg, (CE222-SULPITER); Javna Agencija za Raziskovalno Dejavnost RS, ARRS, (P1-0288)","This research was partially funded by Interreg CENTRAL EUROPE, project CE222-SULPITER and ARRS (Slovenia), Research program No P1-0288.","Ville S., Gonzalez-Feliu J., Dablanc L., The Limits of Public Policy Intervention in Urban Logistics: Lessons from Vicenza (Italy), Eur. Plan. 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Psychol, 78, pp. 98-104, (1993); Cronbach L.J., Coefficient alpha and the internal structure of tests, Psychometrika, 16, pp. 297-334, (1951); Quak H., Lindholm M., Tavasszy L., Browne M., From Freight Partnerships to City Logistics Living Labs—Giving Meaning to the Elusive Concept of Living Labs, Transp. Res. Procedia, 12, pp. 461-473, (2016); Van Woensel L., Evidence for Policy-Making: Foresight-Based Scientific Advice|Think Tank|European Parliament; Lin C., Choy K., Pang G., Ng M.T.W., A data mining and optimization-based real-time mobile intelligent routing system for city logistics, Proceedings of the 2013 IEEE 8th International Conference on Industrial and Information Systems, pp. 156-161, (2013)","M. Mencinger; Faculty of Civil Engineering, Transportation Engineering and Architecture, University of Maribor, Maribor, Smetanova 17, 2000, Slovenia; email: matej.mencinger@um.si",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85144954508"]
["Risberg A.","Risberg, Andreas (57467118300)",5.74671183E10,"A systematic literature review on e-commerce logistics: towards an e-commerce and omni-channel decision framework",2023.0,"International Review of Retail, Distribution and Consumer Research",33.0,1.0,null,67.0,91.0,24.0,15.0,"10.1080/09593969.2022.2089903","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85132443477&doi=10.1080%2f09593969.2022.2089903&partnerID=40&md5=4fcfb02d259bf9f37c76dd1b56b5eded","Department of Supply Chain & Operations Management, School of Engineering, Jönköping University, Jönköping, Sweden","Risberg A., Department of Supply Chain & Operations Management, School of Engineering, Jönköping University, Jönköping, Sweden","e-Commerce is the fastest-growing sales channel, while omni-channel retailing is becoming the new retailing standard. Omni-channel logistics is an essential complex aspect of omni-channel retailing, especially considering the increased consumer demand for seamless shopping experiences. This systematic literature review aims to synthesize the contemporary e-commerce logistics literature and to develop a logistics decision framework. This review shows how the focus of e-commerce logistics literature has evolved to multi-channel logistics, and lately to omni-channel logistics. The recent boom in omni-channel logistics publications highlights the importance of logistics in omni-channel retailing with increased complexity and a myriad of logistics design options. An omni-channel logistics decision framework covering 43 decision elements within supply and internal distribution, last mile consumer steering, last mile back-end fulfilment, last mile delivery, and reverse logistics is created by synthesizing 373 articles. This review identifies research opportunities and encourages researchers to complement existing narrower studies with broader empirical studies focusing on the elements’ interplay, and configuration studies associated with firm performance. The framework and future research avenues support retail executives in designing logistics, in decision-making and in developing strategies. © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.","e-commerce; last mile; logistics; omni-channel; Systematic literature review",{"$nulls":5},"European Regional Development Fund, ERDF, (20201932)","The author would like to thank the e-Merge research project (20201932) co-financed by the European Regional Development Fund, research assistants at Jönköping University, Librarian Stefan Carlstein at the Jönköping University Library, and senior retail logistics researchers Professor Joakim Wikner and Assistant Professor Hamid Jafari at Jönköping University. ",{"$cut":{"chars":23310,"head":"Abdulkader M.M.S., Gajpal Y., ElMekkawy T.Y., Vehicle Routing Problem in omni-channel Retailing Distribution Systems, International Journal of Production Economics, 196, pp. 43-55, (2018); Agatz N.A.H., Fleischmann M., van Nunen J.A.E.E., E-fulfillment and multi-channel Distribution - A Review, European Journal of Operational Research, 187, 2, pp. 339-356, (2008); Akeb H., Moncef B., Durand B., Building a Collaborative Solution in Dense Urban City Settings to Enhance Parcel Delivery: An Effective Crowd Model in Paris, Transportation Research Part E: Logistics and Transportation Review, 119, pp. 223-233, (2018); Aktas E., Bourlakis M., Zissis D., Collaboration in the Last Mile: Evidence from Grocery Deliveries, International Journal of Logistics Research and Applications, 24, 3, pp. 227-241, (2021); Anosike A., Loomes H., Udokporo C.K., Garza-Reyes J.A., Exploring the Challenges of Electric Vehicle Adoption in Final Mile Parcel Delivery, International Journal of Logistics Research and Applications, pp. 1-25, (2021); Asmare A., Zewdie S., Omnichannel Retailing Strategy: A Systematic Review, International Review of Retail, Distribution and Consumer Research, (2021); Bernon M., Cullen J., Gorst J., Online Retail Returns Management: Integration within an omni-channel Distribution Context, International Journal of Physical Distribution and Logistics Management, 46, 6-7, pp. 584-605, (2016); Binos T., Adamopoulos A., Bruno V., Decision Support Research in Warehousing and Distribution: A Systematic Literature Review, International Journal of Information Technology and Decision Making, 19, 3, pp. 653-693, (2020); Booth A., Papaioannou D., Sutton A., Systematic Approaches to a Successful Literature Review, (2012); Boyer K.K., Hult G.T.M., Extending the Supply Chain: Integrating Operations and Marketing in the Online Grocery Industry, Journal of Operations Management, 23, 6, pp. 642-661, (2005); Boyer K.K., Prud'homme A.M., Chung W., The Last Mile Challenge: Evaluating the Effects of Customer Density and Delivery Window Patterns, Journal of Business Logistics, 30, 1, pp. 185-201, (2009); Brynjolfsson E., Hu Y.J., Rahman M.S., Competing in the Age of Omnichannel Retailing, MIT Sloan Management Review, 54, 4, pp. 1-7, (2013); Buldeo Rai H., Verlinde S., Macharis C., The “Next Day, Free Delivery” Myth Unravelled: Possibilities for Sustainable Last Mile Transport in an Omnichannel Environment, International Journal of Retail and Distribution Management, 47, 1, pp. 39-54, (2019); Buldeo Rai H., Verlinde S., Macharis C., Schoutteet P., Vanhaverbeke L., Logistics Outsourcing in Omnichannel Retail: State of Practice and Service Recommendations, International Journal of Physical Distribution and Logistics Management, 49, 3, pp. 267-286, (2019); Byrom J., Medway D., Cyber Solutions to Remote Problems? Online Trading in British Overseas territories–a Review and Research Agenda, International Review of Retail, Distribution and Consumer Research, 14, 1, pp. 71-82, (2004); Cai Y.J., Lo C.K.Y., Omni-channel Management in the New Retailing Era: A Systematic Review and Future Research Agenda, International Journal of Production Economics, 229, (2020); Cao L., Business Model Transformation in Moving to A cross-channel Retail Strategy: A Case Study, International Journal of Electronic Commerce, 18, 4, pp. 69-96, (2014); Cao L., Li L., The Impact of Cross-Channel Integration on Retailers’ Sales Growth, Journal of Retailing, 91, 2, pp. 198-216, (2015); Cao K., Xu Y., Wu Q., Wang J., Liu C., Optimal Channel and Logistics Service Selection Strategies in the e-commerce Context, Electronic Commerce Research and Applications, 48, (2021); Davis-Sramek B., Ishfaq R., Gibson B.J., Defee C., Examining Retail Business Model Transformation: A Longitudinal Study of the Transition to Omnichannel Order Fulfillment, International Journal of Physical Distribution and Logistics Management, 50, 5, pp. 557-576, (2020); de Araujo A.C., Matsuoka E.M., Ung J.E., Massote A., Sampaio M., An Exploratory Study on the Returns Management Process in an Online Retailer, Internation"}},"A. Risberg; Department of Supply Chain & Operations Management, School of Engineering, Jönköping University, Jönköping, Sweden; email: andreas.risberg@ju.se",null,"Routledge",{"$nulls":5},9593969.0,null,null,null,"English","Int. Rev. Retail Distrib. Consum. Res.","Article","Final","All Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85132443477"]
["Roy D.","Roy, Debopriyo (7402438591)",7.402438591E9,"An Assembly Line Approach to Technical Communication Pedagogy with Intelligent Content Design and Delivery",2022.0,"International Journal of Information and Education Technology",12.0,9.0,null,934.0,939.0,5.0,0.0,"10.18178/ijiet.2022.12.9.1703","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85134800570&doi=10.18178%2fijiet.2022.12.9.1703&partnerID=40&md5=aebf001d1ff0a75d23f2a12fd84bcc3f","Center for Language Research, School of Computer Science and Engineering, The University of Aizu, Aizuwakamatsu-shi, Japan","Roy D., Center for Language Research, School of Computer Science and Engineering, The University of Aizu, Aizuwakamatsu-shi, Japan","Topic-based intelligent content design with a better understanding of semantic web schemas could be the new focus for technical communication (TC) pedagogy in academia-a major shift away from designing standalone static documents. A new such TC course focused on the basics of how XML, RDFS, and OWL schema contribute to the semantic web for CCMS and CDP, including the basics of how faceted search works and ontology creation happens for simple e-commerce based, tourism, healthcare, and consumer product information design. The course also attempted to expose students to a basic understanding of iiRDS – the standard that enables dynamic information request and delivery in the era of the Internet of Things and Industry 4.0; and how Microsoft HoloLens-a mixed reality platform caters to intelligent information processing in Toyota and smart city contexts, as case studies. This was an introductory course with conceptual development being the focus, and not programming skills. With this course, we wanted to introduce students to the new industry documentation standards and initiate a process in pedagogy that will ultimately lead to bridging the extreme shortage of qualified job applicants in the industry coming from content strategy as a new field of practice. This paper focused on a pilot study initiating an exercise to explore the extent to which such a course helps teach information management in an English as Foreign Language (EFL) context for computer science majors, within the scope of content language integrated learning (CLIL) and project-based language learning (PBLL). © 2022 by the authors.","CDP; CMS; delivery; document; faceted search; Intelligent content; semantic web; topic",{"$nulls":5},"Karlsruhe University of Applied Sciences","I would like to thank Prof. Dr. Wolfgang Ziegler from the Karlsruhe University of Applied Sciences, Germany for all his help and support.","Hackos J., Foreword, Digital Literacy for Technical Communication: 21st-Century Theory and Practice, pp. 7-10, (2009); Dicks S., The effects of digital literacy on the nature of technical communication work, Digital Literacy for Technical Communication: 21st-Century Theory and Practice, pp. 51-82, (2009); Andersen R., Rhetorical work in the age of content management: Implications for the field of technical communication, Journal of Business and Technical Communication, 28, 2, pp. 115-157, (2014); Swarts J., Recycled writing: Assembling actor networks from reusable content, Journal of Business and Technical Communication, 24, pp. 127-163, (2010); Zhang L., Chen S., Dong H., Saddik A., Visualizing Toronto city data with HoloLens: Using augmented reality for a city model, IEEE Consumer Electronics Magazine, 7, 3, pp. 73-80, (2018); Davis N., Toyota makes mixed reality magic with Unity and Microsoft HoloLens 2, Unity Blog, (2020); Ziegler W., Drivers of digital information services: Intelligent information architectures in technical communication, Proc. the ETLTC ACM Chapter International Conference, pp. 48-52, (2019); Blakeslee A. M., Spilka R., The state of research in technical communication, Technical Communication Quarterly, 13, pp. 73-92, (2004)","D. Roy; Center for Language Research, School of Computer Science and Engineering, The University of Aizu, Aizuwakamatsu-shi, Japan; email: droy@u-aizu.ac.jp",null,"International Journal of Information and Education Technology",{"$nulls":5},2.0103689E7,null,null,null,"English","Int. J. Inf.  Educ. Technol.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85134800570"]
["Kızıl K.U.; Yıldız B.","Kızıl, Kerim U. (57226151503); Yıldız, Barış (56421693300)","57226151503; 56421693300","Public Transport-Based Crowd-Shipping with Backup Transfers",2023.0,"Transportation Science",57.0,1.0,null,174.0,196.0,22.0,4.0,"10.1287/trsc.2022.1157","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85136981896&doi=10.1287%2ftrsc.2022.1157&partnerID=40&md5=025f86ccd67844b106863fbad04e2f94","Department of Industrial Engineering, Koç University, Istanbul, 34450, Turkey","Kızıl K.U., Department of Industrial Engineering, Koç University, Istanbul, 34450, Turkey; Yıldız B., Department of Industrial Engineering, Koç University, Istanbul, 34450, Turkey","With the rising urbanization and booming e-commerce, traditional last-mile delivery systems fail to satisfy the need for faster, cheaper, and more environmentally friendly deliveries. Several new approaches are put forward as an alternative to classical delivery systems in this regard, yet none of them offers the same level of flexibility, capacity, reliability, and managerial control by itself. This paper proposes a new last-mile delivery model that combines several new approaches and technologies to address this issue. More precisely, we suggest using public transit as a backbone network completed by automated service points, crowd-shipping, and backup transfers with zero-emission vehicles to provide a low-cost and environmentally friendly express delivery service. The design problem for the envisioned system is formulated as a two-stage stochastic program, and a branch-and-price (BP) algorithm is devised to solve it. Taking advantage of the nearly decomposable structure that would emerge in possible real-world applications, our study presents the first example of using decomposition branching in a BP framework to enhance computational efficiency. Extensive computational studies and simulations with real-world data reveal valuable managerial insights for the proposed system and attest to the efficacy of the suggested methodology. Copyright: © 2022 INFORMS.","branch-and-price; crowd-shipping; decomposition branching; discrete-event simulation; last-mile logistics; physical Internet; public transport","Computational efficiency; Integer programming; Ships; Stochastic systems; Branch and price; Crowd-shipping; Decomposition branching; Delivery systems; Discrete-event simulations; Last mile; Last-mile logistic; New approaches; Physical internet; Public transport; Discrete event simulation",{"$nulls":4},"Türkiye Bilimsel ve Teknolojik Araştırma Kurumu, TÜBİTAK, (218M605); Bilim Akademisi","Funding: This work was supported by Türkiye Bilimsel ve Teknolojik Aras¸tirma Kurumu [Grant 218M605] and Bilim Akademisi. Supplemental Material: The online appendices are available at https://doi.org/10.1287/trsc.2022.1157.","Alumur S, Kara BY, Network hub location problems: The state of the art, Eur. J. Oper. Res, 190, 1, pp. 1-21, (2008); Alumur SA, Kara BY, Karasan OE, The design of single allocation incomplete hub networks, Transportation Res. Part B: Methodological, 43, 10, pp. 936-951, (2009); Alumur SA, Campbell JF, Contreras I, Kara BY, Marianov V, O'Kelly ME, Perspectives on modeling hub location problems, Eur. J. Oper. Res, 291, 1, pp. 1-17, (2021); Archetti C, Savelsbergh M, Speranza MG, The vehicle routing problem with occasional drivers, Eur. J. Oper. Res, 254, 2, pp. 472-480, (2016); Arslan AM, Agatz N, Kroon L, Zuidwijk R, Crowdsourced delivery—A dynamic pickup and delivery problem with ad hoc drivers, Transportation Sci, 53, 1, pp. 222-235, (2019); Azcuy I, Agatz N, Giesen R, Designing integrated urban delivery systems using public transport, Transportation Res., Part E Logist. 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Res, 65, 3, pp. 595-620, (2017); Yildiz B, Savelsbergh M, Service and capacity planning in crowd-sourced delivery, Transportation Res. C Emerging Tech, 100, pp. 177-199, (2019); Yildiz B, Boland N, Savelsbergh M, Decomposition branching for mixed integer programming, Oper. Res, (2022); Yildiz B, Karasan OE, Yaman H, Branch-and-price approaches for the network design problem with relays, Comput. Oper. Res, 92, pp. 155-169, (2018); Yildiz B, Yaman H, Karasan OE, Hub location, routing, and route dimensioning: Strategic and tactical intermodal transportation hub network design, Transportation Sci, 55, 6, pp. 1351-1369, (2021); Zuo T, Wei H, Rohne A, Determining transit service coverage by non-motorized accessibility to transit: Case study of applying gps data in cincinnati metropolitan area, J. Transportation Geography, 67, pp. 1-11, (2018); Zurel O, Van Hoyweghen L, Braes S, Seghers A, Parcel lockers, an answer to the pressure on the last mile delivery?, New Business and Regulatory Strategies in the Postal Sector, pp. 299-312, (2018)","B. Yıldız; Department of Industrial Engineering, Koç University, Istanbul, 34450, Turkey; email: byildiz@ku.edu.tr",null,"INFORMS Inst.for Operations Res.and the Management Sciences",{"$nulls":5},411655.0,null,"TRSCB",null,"English","Transp Sci","Article","Final",null,"Scopus","2-s2.0-85136981896"]
["Abbagani V.; Kadali B.R.","Abbagani, Vishnu (58093927500); Kadali, B. Raghuram (56237024300)","58093927500; 56237024300","Explore the Factors Contributing to Online Versus Store Shopping in Transportation Perspective: Evidence from India",2022.0,"European Transport - Trasporti Europei",null,89.0,2.0,null,null,null,0.0,"10.48295/ET.2022.89.2","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85147544939&doi=10.48295%2fET.2022.89.2&partnerID=40&md5=49aedc5ea26feded48e42bfc6d9a05e0","Department of Civil Engineering, VNIT Nagpur, Nagpur, 440010, India; Department of Civil Engineering, NIT Warangal, Warangal, 506004, India","Abbagani V., Department of Civil Engineering, VNIT Nagpur, Nagpur, 440010, India; Kadali B.R., Department of Civil Engineering, NIT Warangal, Warangal, 506004, India","In recent times, there has been a growing demand for e-shopping as compared to in-store shopping due to rapid changes in technology as well as extensive usage of the internet. E-shopping has changed people's shopping and travel behaviour. Due to the increase in internet usage, there is a tremendous change in people's shopping choices and it further impacts the travel patterns in urban communities. In this context, the proposed study evaluates people's shopping choice behaviour in an urban scenario. To fulfil the proposed objective, a questionnaire survey has been conducted in order to understand consumer behaviour about their shopping choices as well as the number of online orders that have been made by the user during the specified duration of time (viz., during the last one month). To analyse the collected data, a principal component based logistic regression analysis has been adopted to estimate the significant contributing factors affecting consumer shopping choices. The results show that motivational factors (viz., saving in travel time and better prices) have a significant positive impact on online shopping; however, there are concerns such as delivery time as well as care required during online payment. The frequency of using online shopping mode and recently made purchases has had a significant positive impact on online shopping. Further, it has been concluded that higher income levels and higher occupation levels negatively impact e-shopping choice. The results are useful for transport planners to predict the transformation in people's travel behaviour with respect to shopping trips in present and future scenarios. © 2022 Institute for Transport Studies in the European Economic Integration. All rights reserved.","E-shopping; motivational factors; shopping choice; store shopping; travel behaviour","Consumer behavior; Electronic commerce; Principal component analysis; E-shopping; Growing demand; Internet usage; Motivational factor; Online shopping; Shopping behaviour; Shopping choice; Store shopping; Travel behaviour; Travel patterns; Travel time",{"$nulls":6},"Alyoubi A. 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O., Schaap N. T. W., Impact of different shopping stages on shopping-related travel behaviour: Analyses of the Netherlands Mobility Panel data, Transportation, (2019); Hsiao M.-H., Shopping mode choice: Physical store shopping versus e-shopping, Transportation Research Part E: Logistics and Transportation Review, 45, 1, pp. 86-95, (2009); Huang M.H., Information load: its relationship to online exploratory and shopping behavior, International Journal of Information Management, 20, pp. 337-347, (2000); Indian Ecommerce Industry Report, (2020); Jiao J., Moudon A.V., Drewnowsk A., Grocery Shopping How Individuals and Built Environments Influence Choice of Travel Mode, Transportation Research Record, 2230, pp. 85-95, (2011); Lachapelle U., Jean-Germain F., Personal Use of the Internet and travel: Evidence from the Canadian General Social survey's 2010 time Use module, Travel Behaviour and Society, 14, pp. 81-91, (2019); Li C.C., Wu H.Y., Chang Y.F., The critical factors impact on online customer satisfaction, Procedia Computer Science, 3, pp. 276-281, (2011); Liu W., Batra R., Wang H., Product Touch and Consumers' Online and Offline Buying: The Role of Mental Representation, Journal of Retailing, 93, 3, pp. 369-381, (2017); Maat K., Konings R., Accessibility or innovation? Store shopping trips versus online shopping, Transportation Research Record, 2672, 50, pp. 1-10, (2018); Mokhtarian P.L., Salomon I., How derived is the demand for travel? Some conceptual and measurement considerations, Transportation Research Part A: Policy and Practice, 35, 8, pp. 695-719, (2001); Mokhtarian P.L., A conceptual analysis of the transportation impacts of B2C e-commerce, Transportation, 31, pp. 257-284, (2004); Pettersson F., Hiselius W.L., Koglin T., E-commerce and urban planning - comparing knowledge claims in research and planning practice, Urban, Planning and Transport Research, 6, 1, pp. 1-21, (2018); Rohm A.J., Swaminathan V., A typology of online shoppers based on shopping motivations, Journal of Business Research, 57, pp. 748-757, (2004); Rotem-Mindali O., Salomon I., The impacts of E-retail on the choice of shopping trips and delivery: some preliminary findings, Transportation Research Part A, 41, pp. 176-189, (2007); Shen L., He Y., Li L.H., Chau K.W., Impacts of online shopping convenience and physical retail proximity on housing prices in Shenzhen, 2016-2018, Journal of Housing and the Built Environment, pp. 1-20, (2020); Shi K., De vos J., Yang Y., Witlox F., Does shopping replaces shopping trips? Empirical evidence from Chengdu China, Transportation Research Part A: Policy and Practice, 122, pp. 21-33, (2019); Sim L.L., Koi S.Z., Singapore's Internet shoppers and their impact on traditional shopping patterns, Journal of Retailing and Consumer Services, 9, pp. 115-124, (2002); Sinai T., Waldfogel J., Geography and the Internet: Is the Internet a substitute or complement for cities?, Journal of Urban Economies, 56, pp. 1-24, (2004); Suel E., Polak J.W., Incorporating online shopping into travel demand modelling: challenges, progress, and opportunities, Transport Reviews, 38, 5, pp. 576-601, (2017); Weltevreden J.W.J., Substitution or complementarity? How the Internet changes city centre shopping, Journal of Retailing and Consumer Services, 14, 3, pp. 192-207, (2007); Zhou Y., Wang X., Explore the relationship between online shopping and shopping trips: An analysis with the 2009 NHTS data, Transportation Research Part A, 70, pp. 1-9, (2014)","V. Abbagani; Department of Civil Engineering, VNIT Nagpur, Nagpur, 440010, India; email: brkadali@nitw.ac.in",null,"Institute for Transport Studies in the European Economic Integration",{"$nulls":5},1.8253997E7,null,null,null,"English","Eur. Transp. Trasporti Eur.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85147544939"]
["Pasaribu F.; Sari W.P.; Ni Bulan T.R.; Astuty W.","Pasaribu, Fajar (57190028998); Sari, Warsani Purnama (57214222101); Ni Bulan, Tapi Rondang (57887722200); Astuty, Widia (57192807907)","57190028998; 57214222101; 57887722200; 57192807907","The effect of e-commerce service quality on customer satisfaction, trust and loyalty",2022.0,"International Journal of Data and Network Science",6.0,4.0,null,1077.0,1084.0,7.0,9.0,"10.5267/j.ijdns.2022.8.001","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137890427&doi=10.5267%2fj.ijdns.2022.8.001&partnerID=40&md5=fbd9e5a6bbac6ca66ea212ba6adf7e45","Universitas Muhammadiyah Sumatera Utara, Indonesia; Universitas Medan Area, Indonesia; Universitas Harapan Medan, Indonesia; Universitas Muhammadiyah Sumatera Utara, Indonesia","Pasaribu F., Universitas Muhammadiyah Sumatera Utara, Indonesia; Sari W.P., Universitas Medan Area, Indonesia; Ni Bulan T.R., Universitas Harapan Medan, Indonesia; Astuty W., Universitas Muhammadiyah Sumatera Utara, Indonesia","This study aims to explain the effect of service quality on satisfaction, service quality on trust, service quality on loyalty, satisfaction on loyalty and trust on loyalty. The population in this study are all consumers who have made transactions at an Indonesian marketplace, Shopee.co.id. The number of respondents used as a sample is 300 respondents. The results showed a significant influence between variables in the four interaction effects, namely service quality on satisfaction, service quality on trust, satisfaction with loyalty, and trust in loyalty. Meanwhile the insignificant effect was service quality on loyalty, the results of the total effect calculation also showed that Trust is a mediating variable between service quality and loyalty. marketing stimuli that can be carried out include maintaining cash on delivery services to increase customer trust, optimizing customer satisfaction through service improvement, providing more organized information so that consumers are easier and more comfortable in transacting, providing a 'tracking order' stage for customers, so that customers can monitor the progress of product orders. For further research, it is hoped that it can develop more variables under study and make comparisons of other e-commerce both in Indonesia and internationally. © 2022 by the authors; licensee Growing Science, Canada.","Customer loyalty; Customer satisfaction; Customer trust; Service quality",{"$nulls":7},"Akbar M. M., Parvez N., Impact of service quality, trust, and customer satisfaction on customers loyalty, ABAC journal, 29, 1, pp. 24-38, (2009); Are A. K. P., Setyorini R., Pengaruh Electronic Word of Mouth dan Kepercayaan Konsumen terhadap Niat Beli Produk di Shopee Indonesia, Dinamika Ekonomi-Jurnal Ekonomi dan Bisnis, 12, 2, pp. 216-230, (2019); Assauri S., Manajemen Pemasaran dan Pemasaran Jasa, (2013); Baker J., Grewal D., Parasuraman A., The influence of store environment on quality inferences and store image, Journal of the academy of marketing science, 22, 4, pp. 328-339, (1994); Basu S., Handoko T. 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G., Cheng-cai T. A. N. G., Jia-ming L. I. U., A Measuring Model on Tourist Satisfaction Index in Cultural Creative-type Tourism Destination--A Case of 798 Art Zone in Beijing, Tourism Tribune/Lvyou Xuekan, 26, 9, (2011); Kasmir S. E., Etika Customer Service, (2005); Kassim N., Abdullah N. A., The effect of perceived service quality dimensions on customer satisfaction, trust, and loyalty in e-commerce settings, Asia Pacific Journal of Marketing and Logistics, 22, 3, (2010); Kotler P., Amstrong G., Principles of Marketing Global, England: Pearson Education, 6, pp. 47-48, (2012); Kotler P., Keller K. L., Manajemen Pemasaran Jasa, (2011); Laudon K. C., Traver C. G., E-commerce: business, technology, society, (2014); Madjid R., Customer trust as relationship mediation between customer satisfaction and loyalty at Bank Rakyat Indonesia (BRI) Southeast Sulawesi, The international journal of Engineering and science (IJES), 2, 5, pp. 48-60, (2013); Nanehkaran Y. A., An Introduction to Electronic Commerce, International Journal of Scientific & Technology Research, 2, 4, (2013); Nazar R., Syahram, Pengaruh Privasi, Keamanan, Kepercayaan, dan Pengalaman Terhadap Niat untuk Bertransaksi Secara Online, (2011); Nunnally J. C., Bernstein I., Elements of statistical description and estimation, Psychometric theory, 3, 127, (1994); Oliver R. L., Satisfaction: A Behavioral Perspective on the Consumer, (1997); Parasuraman A., Zeithaml V. A., Berry L. L., SERVQUAL: A multiple-item scale for measuring consumer per- ceptions of service quality, Journal of Retailing, 64, pp. 12-40, (1988); Peter J. P., Olson J. C., Consumer Behavior & Marketing Strategy, (2010); Prabowo H., Darman D., Noegraheni E., Analisis Kepercayaan dalam C2C E-Commerce terhadap Keputusan Pembelian dan Dampaknya terhadap Repurchase pada Kaskus, Binus Business Review, 5, 1, pp. 301-314, (2014); Reichheld F. F., Sasser W. E. J., Zero Defections Quality Comes to Services, Harvard Business Review, 68, 5, pp. 105-111, (1990); Rerung R. R., E-Commerce, Menciptakan Daya Saing Melalui Teknologi Informasi, (2018); Ribbink D., van Riel A. C., Liljander V., Streukens S., Emerald Article: Comfort your online customer: Quality, trust and loyalty on the internet, Managing Service Quality, 14, 6, pp. 446-456, (2004); Rumondang A., Sudirman A., Sitorus S., Kusuma A. H. P., Manuhutu M., Sudarso A., Arif N. F., Pemasaran Digital dan Perilaku Konsumen, (2020); Shin J. I., Chung K. H., Oh J. S., Lee C. W., The effect of site quality on repurchase intention in Internet shopping through mediating variables: The case of university students in South Korea, International Journal of Information Management, 33, 3, pp. 453-463, (2013); Singh J., Sirdeshmukh D., Agency and Trust Mechanisms in Consumer Satisfaction and Loyalty Judgments, Journal of the Academy of Marketing Science, 28, 1, pp. 150-167, (2000); Spreng R. A., Mackoy R. D., An empirical examination of a model of perceived service quality and satisfaction, Journal of retailing, 72, 2, pp. 201-214, (1996); Srinivasan S. S., Anderson R., Ponnavolu K., Customer loyalty in e-commerce: an exploration of its antecedents and consequences, Journal of retailing, 78, 1, pp. 41-50, (2002); Subatri T., Konsep sistem informasi, (2012); Sudaryono D., Manajemen Pemasaran teori dan implementasi, (2016); Sudirman A., Sherly S., Butarbutar M., Nababan T. S., Puspitasari D., Loyalitas Pelanggan Pengguna Gojek Ditinjau Dari Aspek Kualitas Pelayanan Dan Kepuasan Konsumen, Procuratio: Jurnal Ilmiah Manajemen, 8, 1, pp. 63-73, (2020); Sularto L., Pengaruh Privasi, Kepercayaan dan Pengalaman Terhadap Niat Beli Konsumen Melalui Internet, Jurnal Ekonomi & Bisnis, 3, 9, pp. 138-155, (2004); Supranto J., Pengukuran Tingkat Kepuasan Pelanggan: Untuk Menaikkan Pangsa Pasar, (2001); Sureshchandar G. S., Chandrasekharan R., Anantharaman R. N., The relationship between service quality and customer satisfaction-a factor specific approach, Journal of Services Marketing, 16, 4, pp. 363-379, (2002); Tjiptono F., Gregorius C., Service Quality dan Satisfaction, (2016); Tomlinson E. C., Lewicki R. J., Dineen B. R., Dealing with damaged trust: How to rebuild trust and temper distrust, annual meeting of the Academy of Management, (2002); Turban E., King D., Lee J. K., Liang T. P., Turban D. C., Business-to-business E-commerce, pp. 161-207, (2015); Wahyuni S., Praninta A., The Influence of Brand Equity and Service Quality on Purchase Decisions on Garuda Indonesia Airline Services, Research Horizon, 1, 1, pp. 28-38, (2021); Wibowo B., The Role of Creative Economy-Based Startups on Member Economic Improvement and Economic Resilience, Research Horizon, 1, 5, pp. 172-178, (2021); Zhang K. Z., Benyoucef M., Zhao S. J., Building brand loyalty in social commerce: The case of brand microblogs, Electronic Commerce Research and Applications, 15, pp. 14-25, (2016)","F. Pasaribu; Universitas Muhammadiyah Sumatera Utara, Indonesia; email: fajarpasaribu@umsu.ac.id",null,"Growing Science",{"$nulls":5},2.5618148E7,null,null,null,"English","Int. J.  Data  Netw.  Sci.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85137890427"]
["Jena S.K.","Jena, Sarat Kumar (55260424200)",5.52604242E10,"Impact of bundling on the omnichannel supply chain under price competition",2022.0,"Journal of Business and Industrial Marketing",37.0,12.0,null,2468.0,2487.0,19.0,6.0,"10.1108/JBIM-06-2021-0315","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124229535&doi=10.1108%2fJBIM-06-2021-0315&partnerID=40&md5=38d1dee1006aedaecfe2741f44009d3c","Department of Operations Management and Decision Sciences, Xavier Institute of Management, XIM University, Bhubaneswar, India","Jena S.K., Department of Operations Management and Decision Sciences, Xavier Institute of Management, XIM University, Bhubaneswar, India","Purpose: Many e-commerce firms suffer from high returns because of inaccurate and incomplete product information. Omnichannel and bundling settings can help firms improve operational efficiency and lower returns costs. However, no studies have been conducted on omnichannel supply chains considering bundling strategies. The purpose of this study is to examine the comparison between test-in-store-and-buy-online (TSBO) and online retail, comparing manufacturers’ bundling with retailers’ bundling. Design/methodology/approach: The supply chain discussed here consists of two competitive manufacturers and one retailer. The retailer sells both manufacturers' products online and displays one manufacturer's product in a showroom who bears the display cost. Stackelberg game theory is used to develop mathematical models that help manufacturers and retailers make the most effective decisions. Here, the manufacturer is the Stackelberg leader, while the retailer is the follower. Using the backward induction approach, the authors determined the optimal values for selling price, wholesale price and service effort level. Findings: The results show that the total TSBO retailing profit under manufacturer bundling is highest when the second manufacturer integrates with the online retailer. The result additionally establishes that when the bundling cost exceeds a certain threshold (1.5), the total profit is higher for the non-integrated type of supply chain channel as compared to the integrated retailer bundling-based configuration. Practical implications: The operations and logistics manager will likely undertake the TSBO omnichannel strategy during manufacturers bundling and retailer bundling under the integrated strategy. Originality/value: The main contribution of the study is to examine the effect of TSBO retailing on supply chains profit and individual decision-making under different bundling strategies. The authors developed different mathematical models in the TSBO retailing and bundling context and extended the earlier work in the area of integration frame. © 2022, Emerald Publishing Limited.","Bundling; Competition; Omnichannel; Pricing; Supply chain; TSBO",{"$nulls":7},"Abhishek V., Jerath K., Zhang Z.J., Agency selling or reselling? Channel structures in electronic retailing, Management Science, 62, 8, pp. 2259-2280, (2016); Adams W.J., Yellen J.L., Commodity bundling and the burden of monopoly, The Quarterly Journal of Economics, 90, 3, pp. 475-498, (1976); Alaei A.M., Taleizadeh A.A., Rabbani M., Marketplace, reseller, or web-store channel: the impact of the return policy and cross-channel spillover from marketplace to web-store, Journal of Retailing and Consumer Services, 65, 1, (2020); Ali F., Young J., US ecommerce grows 32.4% in 2020, (2021); Banciu M., Gal-Or E., Mirchandani P., Bundling strategies when products are vertically differentiated and capacities are limited, Management Science, 56, 12, pp. 2207-2223, (2010); Basak S., Basu P., Avittathur B., Sikdar S., A game-theoretic analysis of multichannel retail in the context of ‘show rooming’, Decision Support Systems, 103, pp. 34-45, (2017); Beheshtian-Ardakani A., Fathian M., Gholamian M., A novel model for product bundling and direct marketing in e-commerce based on market segmentation, Decision Science Letters, 7, 1, pp. 39-54, (2018); Bell S.J., Auh S., Eisingerich A.B., Unraveling the customer education paradox: when, and how, should firms educate their customers?, Journal of Service Research, 20, 3, pp. 306-321, (2017); Brohan M., Reducing the rate of returns, (2013); Cachon G.P., Supply chain coordination with contracts, Handbooks in Operations Research and Management Science, 11, pp. 227-339, (2003); Cao X., Ke T.T., Cooperative search advertising, Marketing Science, 38, 1, pp. 44-67, (2019); Cataldo A., Ferrer J.C., Optimal pricing and composition of multiple bundles: a two-step approach, European Journal of Operational Research, 259, 2, pp. 766-777, (2017); Chen T., Yang F., Guo X., Retailer-driven bundling when valuation discount exists, Journal of the Operational Research Society, 71, 12, pp. 2027-2041, (2020); Chen T., Yang F., Guo X., Optimal bundling in a distribution channel in the presence of substitutability and complementarity, International Journal of Production Research, 59, 4, pp. 1145-1165, (2021); 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Jena; Department of Operations Management and Decision Sciences, Xavier Institute of Management, XIM University, Bhubaneswar, India; email: saratkumar.jena@gmail.com",null,"Emerald Publishing",{"$nulls":5},8858624.0,null,null,null,"English","J. Bus. Ind. Mark.","Article","Final",null,"Scopus","2-s2.0-85124229535"]
["Guan G.; Liu D.; Zhai J.","Guan, Gaofeng (53984005600); Liu, Dong (58034170800); Zhai, Jiayang (58034507900)","53984005600; 58034170800; 58034507900","Factors Influencing Consumer Satisfaction of Fresh Produce E-Commerce in the Background of COVID-19—A Hybrid Approach Based on LDA-SEM-XGBoost",2022.0,"Sustainability (Switzerland)",14.0,24.0,16392.0,null,null,null,3.0,"10.3390/su142416392","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85144929662&doi=10.3390%2fsu142416392&partnerID=40&md5=1abb38f50094790d8a6d3a780e716174","School of Economics and Management, Zhejiang University of Science and Technology, Hangzhou, 310012, China; School of Economics and Management, Southwest Jiaotong University, Chengdu, 610031, China; School of Science, Zhejiang University of Science and Technology, Hangzhou, 310012, China","Guan G., School of Economics and Management, Zhejiang University of Science and Technology, Hangzhou, 310012, China, School of Economics and Management, Southwest Jiaotong University, Chengdu, 610031, China; Liu D., School of Economics and Management, Zhejiang University of Science and Technology, Hangzhou, 310012, China; Zhai J., School of Science, Zhejiang University of Science and Technology, Hangzhou, 310012, China","In order to clarify the influencing factors of fresh produce e-commerce consumer satisfaction in the context of COVID-19, a hybrid approach based on LDA-SEM-XGBoost was proposed by studying online reviews. Firstly, topic elements were extracted through the LDA topic model, PLS-SEM was established to explore the paths between variables, and XGBoost models were applied to rank the importance of each topic variable based on satisfaction. The results showed that epidemic factors had a significant impact on logistics factors, product factors, and platform factors, with the epidemic factors having the greatest impact on logistics factors. Logistics factors, product factors, platform factors, and epidemic factors had a significant impact on consumer satisfaction, with logistics factors having the greatest impact on satisfaction. The topic variables affecting fresh produce e-commerce consumer satisfaction were, in order: logistics time, shipping speed, product quality, delivery speed, after-sales strategy, logistics packaging, product price, the impact of COVID-19, marketing strategy, and product brand. Based on these findings, recommendations are made for the sustainable production and marketing of fresh produce. © 2022 by the authors.","consumer satisfaction; COVID-19; online review; PLS-SEM; XGBoost","consumption behavior; COVID-19; electronic commerce; logistics; marketing",{"$nulls":4},"Humanities and Social Science Fund of Ministry of Education of China, (22YJAZH023)","This work was supported by the Ministry of Education of Humanities and Social Science Project (No.22YJAZH023).","Pu M., Chen X., Zhong Y., Overstocked Agricultural Produce and Emergency Supply System in the COVID-19 Pandemic: Responses from China, Foods, 10, (2021); Sheth J., Impact of COVID-19 on consumer behavior: Will the old habits return or die?, J. Bus. Res, 117, pp. 280-283, (2020); Chetty R., Friedman J., Hendren N., Stepner M., The Opportunity Insights Team. The Economic Impacts of COVID-19: Evidence from a New Public Database Built Using Private Sector Data, NBER Work. 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Liu; School of Economics and Management, Zhejiang University of Science and Technology, Hangzhou, 310012, China; email: liudong0913@126.com",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85144929662"]
["Xiu F.-R.; Chen C.; Song Z.; Wang S.; Qi Y.","Xiu, Fu-Rong (24170277700); Chen, Chuanzhong (57917303600); Song, Zhiqi (57204963121); Wang, Siyi (57916534600); Qi, Yingying (7401900818)","24170277700; 57917303600; 57204963121; 57916534600; 7401900818","A novel resource conversion strategy of waste plastic express packaging bags using supercritical water-ammonia process: Optimization by response surface methodology",2022.0,"Process Safety and Environmental Protection",168.0,null,null,142.0,149.0,7.0,3.0,"10.1016/j.psep.2022.09.072","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85139359454&doi=10.1016%2fj.psep.2022.09.072&partnerID=40&md5=83e3d1547abe68ed09226d8499279b8a","College of Geology and Environment, Xi'an University of Science and Technology, Xi' an, 710054, China","Xiu F.-R., College of Geology and Environment, Xi'an University of Science and Technology, Xi' an, 710054, China; Chen C., College of Geology and Environment, Xi'an University of Science and Technology, Xi' an, 710054, China; Song Z., College of Geology and Environment, Xi'an University of Science and Technology, Xi' an, 710054, China; Wang S., College of Geology and Environment, Xi'an University of Science and Technology, Xi' an, 710054, China; Qi Y., College of Geology and Environment, Xi'an University of Science and Technology, Xi' an, 710054, China","With the rapid development of e-commerce and express delivery industries, a large number of waste plastic express packaging bags (WPEPBs) are generated and urgent to be safely disposed. In this work, a novel resource conversion strategy was developed to produce high value-added chemicals from WPEPBs by supercritical water ammonia (SWA) process without any catalyst. WPEPBs could be converted into two parts by the SWA process: oil and solid residue. More than 80 % of the oil was identified as long-chain alkanes and alkenes due to the decomposition of polyethylene (PE) contained in WPEPBs. The presence of NH3 in SWA was beneficial to improve the production of long-chain alkenes. The plasticizers in WPEPBs including bisphenol A (BPA) and phthalate ester (DEHP) could be efficiently converted into aniline (≈15%) and 2-ethylhexanol (≈4 %) due to the high reactivity of NH3 in the SWA process. Compared with the degradation of WPEPBs in supercritical water, the SWA process could reduce side effects and improve the purity of target products. High-purity CaCO3 powder could be further recovered from the solid residue. The optimal parameters of the SWA process for the conversion of WPEPBs by Response Surface Methodology (RSM) were 440.5 ℃, 90 min, and CNH3 of 4.8 wt%. The conversion ratio of WPEPBs (CWPEPBs) and CaCO3 recovery ratio (RCaCO3) were 99.10 % and 98.85 %, respectively. In contrast to traditional methods for recycling of plastic waste such as mechanical recycling and incineration, the SWA process is believed to be a clean and high-efficiency resource conversion strategy for WPEPBs. © 2022 The Institution of Chemical Engineers","Resource conversion; Response surface methodology; Supercritical water ammonia process; Waste plastic express packaging bags","Aniline; Calcite; Calcium carbonate; Packaging; Plastic recycling; Polypropylenes; Solvents; Surface properties; E- commerces; Long-chain alkenes; Process optimisation; Resource conversion; Response-surface methodology; Solid residues; Supercritical water; Supercritical water ammonia process; Waste plastic; Waste plastic express packaging bag; Ammonia",{"$nulls":4},"Natural Science Basic Research Project of Shaanxi Province of China, (2021JZ-52); National Natural Science Foundation of China, NSFC, (22278331)","This work was supported financially by the National Natural Science Foundation of China (No. 22278331 ) and the Natural Science Basic Research Project of Shaanxi Province of China (No. 2021JZ-52 ). ","Akhtar J., Amin N.A.S., A review on process conditions for optimum bio-oil yield in hydrothermal liquefaction of biomass, Renew. Sustain. Energy Rev., 15, 3, pp. 1615-1624, (2011); Bai B., Liu Y., Zhang H., Zhou F., Han X., Wang Q., Jin H., Experimental investigation on gasification characteristics of polyethylene terephthalate (PET) microplastics in supercritical water, Fuel, 262, (2020); Barhoum A., Rahier H., Abou-Zaied R.E., Rehan M., Dufour T., Hill G., Dufresne A., Effect of cationic and anionic surfactants on the application of calcium carbonate nanoparticles in paper coating, ACS Appl. Mater. Inter., 6, 4, pp. 2734-2744, (2014); Cai K., Xie Y., Song Q., Sheng N., Wen Z., Identifying the status and differences between urban and rural residents' behaviors and attitudes toward express packaging waste management in Guangdong Province, China, Sci. Total. Environ., 797, (2021); Chen W.-T., Jin K., Linda Wang N.-H., Use of supercritical water for the liquefaction of polypropylene into oOil, ACS Sustain. Chem. Eng., 7, 4, pp. 3749-3758, (2019); Corchado J., Espinosa-Garcia J., Hu W.-P., Rossi I., Truhlar D., Dual-level reaction-path dynamics (the III approach to VTST with semiclassical tunneling). Application to OH + NH<sub>3</sub> –>H2O + NH<sub>2</sub>, J. Phys. Chem., 99, pp. 687-694, (1995); Ennis C.P., Lane J.R., Kjaergaard H.G., McKinley A.J., Identification of the water amidogen radical complex, J. Am. Chem. Soc., 131, 4, pp. 1358-1359, (2009); Fan W., Xu M., Dong X., Wei H., Considerable environmental impact of the rapid development of China's express delivery industry, Resour. Conserv. 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Fluids, 13, 1-3, pp. 247-252, (1998); Xiu F.-R., Li Y., Qi Y., Yu X., He J., Lu Y., Gao X., Deng Y., Song Z., A novel treatment of waste printed circuit boards by low-temperature near-critical aqueous ammonia: Debromination and preparation of nitrogen-containing fine chemicals, Waste Manag., 84, pp. 355-363, (2019); Xu Z., Xiong X., Zhao Y., Xiang W., Wu C., Pollutants delivered every day: Phthalates in plastic express packaging bags and their leaching potential, J. Hazard. Mater., 384, (2020); Zaman H.U., Beg M.D.H., Effect of CaCO<sub>3</sub> contents on the properties of polyethylene nanocomposites sheets, Fibers Polym., 15, 4, pp. 839-846, (2014); Zhao X., Korey M., Li K., Copenhaver K., Tekinalp H., Celik S., Kalaitzidou K., Ruan R., Ragauskas A.J., Ozcan S., Plastic waste upcycling toward a circular economy, Chem. Eng. J., 428, (2022); Zhou H., Ren Y., Li Z., Xu M., Wang Y., Ge R., Kong X., Zheng L., Duan H., Electrocatalytic upcycling of polyethylene terephthalate to commodity chemicals and H<sub>2</sub> fuel, Nat. Commun., 12, 1, (2021)","F.-R. Xiu; College of Geology and Environment, Xi'an University of Science and Technology, Xi' an, 710054, China; email: xiufurong@xust.edu.cn",null,"Institution of Chemical Engineers",{"$nulls":5},9575820.0,null,null,null,"English","Process Saf. Environ. Prot.","Article","Final",null,"Scopus","2-s2.0-85139359454"]
["Lee C.S.; Lim D.-W.","Lee, Chang Su (56100698000); Lim, Dong-Won (57205459816)","56100698000; 57205459816","CNN-Based Inspection Module for Liquid Carton Recycling by the Reverse Vending Machine",2022.0,"Sustainability (Switzerland)",14.0,22.0,14905.0,null,null,null,0.0,"10.3390/su142214905","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85142672725&doi=10.3390%2fsu142214905&partnerID=40&md5=f91924a910b3ac96e5512c54accd1a33","Department of Electrical and Electronic Engineering, The University of Suwon, Hwaseong, 18323, South Korea; Department of Mechanical Engineering, The University of Suwon, Hwaseong, 18323, South Korea","Lee C.S., Department of Electrical and Electronic Engineering, The University of Suwon, Hwaseong, 18323, South Korea; Lim D.-W., Department of Mechanical Engineering, The University of Suwon, Hwaseong, 18323, South Korea","To protect our planet, the material recycling of domestic waste is necessary. Since the COVID-19 pandemic began, the volume of domestic waste has surged overwhelmingly, and many countries suffered from poor waste management. Increased demand for food delivery and online shopping led to a huge surge in plastic and paper waste which came from natural resources. To reduce the consumption of resources and protect the environment from pollution, such as that from landfills, waste should be recycled. One of precious recyclable materials from household waste is liquid cartons that are made of high-quality paper. To promote sustainable recycling, this paper proposes a vision-based inspection module based on convolutional neural networks via transfer learning (CNN-TL) for collecting liquid packaging cartons in the reverse vending machine (RVM). The RVM is an unmanned automatic waste collector, and thus it needs the intelligence to inspect whether a deposited item is acceptable or not. The whole processing algorithm for collecting cartons, including the inspection step, is presented. When the waste is inserted into the RVM by a user after scanning the barcode on the waste, it is relocated to the inspection module, and the item is weighed. To develop the inspector, an experimental set-up with a video camera was built for image data generation and preparation. Using the image data, the inspection agent was trained. To make a good selection for the model, 17 pretrained CNN models were evaluated, and DenseNet121 was selected. To access the performance of the cameras, four different types were also evaluated. With the same CNN model, this paper found the effect of the number of training epochs being set to 10, 100, and 500. In the results, the most accurate agent was the 500-epoch model, as expected. By using the RVM process logic with this model, the results showed that the accuracy of detection was over 99% (overall probability from three inspections), and the time to inspect one item was less than 2 s. In conclusion, the proposed model was verified for whether it would be applicable to the RVM, as it could distinguish liquid cartons from other types of paper waste. © 2022 by the authors.","artificial intelligence; convolutional neural networks; liquid carton; paper waste; recycling; reverse vending machine; transfer learning","artificial intelligence; domestic waste; learning; plastic; recycling",{"$nulls":4},"University of Suwon, USW","The work was supported by the University of Suwon (2021). The authors thank Yong-Ho Hong for his thoughtful advice. The authors are also thankful for the data preparation by Young-Min Cha. ","Di Maria F., Beccaloni E., Bonadonna L., Cini C., Confalonieri E., La Rosa G., Milana M.R., Testai E., Scaini F., Minimization of spreading of SARS-CoV-2 via household waste produced by subjects affected by COVID-19 or in quarantine, Sci. Total Environ, 743, (2020); Nzediegwu C., Chang S.X., Improper solid waste management increases potential for COVID-19 spread in developing countries, Resour. Conserv. Recycl, 161, (2020); Peng J., Wu X., Wang R., Li C., Zhang Q., Wei D., Medical waste management practice during the 2019-2020 novel coronavirus pandemic: Experience in a general hospital, Am. J. Infect. Control, 48, pp. 918-921, (2020); Yousefi M., Oskoei V., Jonidi Jafari A., Farzadkia M., Hasham Firooz M., Abdollahinejad B., Torkashvand J., Municipal solid waste management during COVID-19 pandemic: Effects and repercussions, Environ. Sci. Pollut. Res, 28, pp. 32200-32209, (2021); Yoon J., Yoon Y., Yun S.L., Lee W., The Current State of Management and Disposal of Wastes Related to COVID-19: A review, J. Korean Soc. Environ. Eng, 43, pp. 739-746, (2021); Paper company paper-pack recycling report, Survey on Paper-Pack Dispose and Recycling, pp. 74-88, (2005); Bobulski J., Kubanek M., Project of Sorting System for Plastic Garbage in Sorting Plant Based on Artificial Intelligence, Proceedings of the CS & IT Conference Proceedings, 10; Mariya D., Usman J., Mathew E.N., Aa P.H.H., Reverse vending machine for plastic bottle recycling, Int. J. Comput. Sci. Technol, 8, pp. 65-70, (2020); Mwangi H.W., Mokoena M., Using deep learning to detect polyethylene terephthalate (PET) bottle status for recycling, Glob. J. Comput. Sci. Technol, 19, pp. 1-6, (2019); Lopez M., Sevilla B.C., Simborio Y.D., Canizares R.P., Reverse Vending Machine with Power Output for Mobile Devices using Vision–Based System, Proceedings of the 2021 IEEE 13th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), pp. 1-6; Ahmed I., Ahmad M., Ahmad A., Jeon G., Top view multiple people tracking by detection using deep SORT and YOLOv3 with transfer learning: Within 5G infrastructure, Int. J. Mach. Learn. Cybern, 12, pp. 3053-3067, (2021); Zhao L., Li S., Object detection algorithm based on improved YOLOv3, Electronics, 9, (2020); Meng S., Chu W.T., A study of garbage classification with convolutional neural networks, Proceedings of the 2020 Indo—Taiwan 2nd International Conference on Computing, Analytics and Networks (Indo-Taiwan ICAN), pp. 152-157; Amin Z.M.A., Sami K.N., Hassan R., An approach of classifying waste using transfer learning method, Int. J. Perceptive Cogn. Comput, 7, pp. 41-52, (2021); Burkart N., Huber M.F., A survey on the explainability of supervised machine learning, J. Artif. Intell. Res, 70, pp. 245-317, (2021); Hasan M.M., Srizon A.Y., Sayeed A., Hasan M.A.M., High performance classification of caltech-101 with a transfer learned deep convolutional neural network, Proceedings of the 2021 International Conference on Information and Communication Technology for Sustainable Development (ICICT4SD), pp. 35-39; Glock K., Napier C., Gary T., Gupta V., Gigante J., Schaffner W., Wang Q., Measles Rash Identification Using Transfer Learning and Deep Convolutional Neural Networks, Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), pp. 3905-3910; Patil M., Shaikh N., Zalte M.S., Waste Classification Using ANN, CNN And Transfer Learning, CNN And Transfer Learning, (2022); West J., Ventura D., Warnick S., Spring Research Presentation: A Theoretical Foundation for Inductive Transfer, 1, (2007); Huang G., Liu Z., Van Der Maaten L., Weinberger K.Q., Densely connected convolutional networks, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4700-4708; Mao W.L., Chen W.C., Wang C.T., Lin Y.H., Recycling waste classification using optimized convolutional neural network, Resour. Conserv. Recycl, 164, (2021); Nandhini S., Ashokkumar K., An automatic plant leaf disease identification using DenseNet-121 architecture with a mutation-based henry gas solubility optimization algorithm, Neural Comput. Appl, 34, pp. 5513-5534, (2022); Chhabra M., Kumar R., A Smart Healthcare System Based on Classifier DenseNet 121 Model to Detect Multiple Diseases, Mobile Radio Communications and 5G Networks, pp. 297-312, (2022)","D.-W. Lim; Department of Mechanical Engineering, The University of Suwon, Hwaseong, 18323, South Korea; email: dwlim@suwon.ac.kr",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85142672725"]
["Savadkoohi B.T.","Savadkoohi, B. Ture (57190064812)",5.7190064812E10,"THE WORLD OF E-COMMERCE: THE PROCESS FROM DIGITAL SIGNATURE UP TO MARKET BASKET ANALYSIS",2022.0,"International Journal on Technical and Physical Problems of Engineering",14.0,3.0,null,202.0,206.0,4.0,1.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85139450969&partnerID=40&md5=c3358fa1eba6eb3c0afe3cac400b5def","Department of Computer and Electrical Engineering, Seraj Higher Education Institute, Tabriz, Iran","Savadkoohi B.T., Department of Computer and Electrical Engineering, Seraj Higher Education Institute, Tabriz, Iran","Nowadays, with rapid development of electronic commerce (E-commerce), information security is a fundamental requirement for transaction processing over the internet. Moreover, any information related to consumer behaviors has paid more and more attention in E-commerce market. Thus, in order to data analysis, market basket analysis is used for knowledge discovery. For this aim, first, digital signature that is based on modified RSA is applied for E-commerce security because of its data integrity protection and privacy. Then, in order to predict customer favorite product logistic regression, Apriori algorithm and online Adaboost is applied. © 2022, International Organization on 'Technical and Physical Problems of Engineering'. All rights reserved.","Apriori Algorithm; Logistic Regression; Modified RSA; Online Adaboost",{"$nulls":7},"Islek I., GunduzOguduc S., A Hierarchical Recommendation System for E-commerce using Online User Reviews, Journal of Electronic Commerce Research and Applications, 52, (2022); Savadkoohi B.T., Nik Mohammadi P., Applying Wormhole Approach to Design a Hierachy in a Relational Datbase for Quick Data Access, Journal of Technical and Physical Problems of Engineering (IJTPE), 13, 2, pp. 144-148, (2021); Wu S., E-Commerce Decision Support System Based on Internet of Things, Journal of Ambient Intelligence and Humanized Computing, pp. 1-7, (2018); Scholz M., Dorner V., Schryen G., Benlian A., A Configuration-Based Recommender System for Supporting E-Commerce Decisions, European Journal of Operational Research, 259, 1, pp. 205-215, (2017); Bhatia N.L., Shukla V.K., Punhani R., Dubey S.K., Growing Aspects of Cyber Security in E-Commerce, IEEE International Conference on Communication Information and Computing Technology, (2021); Maqsood F., Ahmed M., Mumtaz M., Cryptography: A Comparative Analysis for Modern Techniques, Journal of Advanced Computer Science and Application, 8, 6, pp. 442-448, (2017); Ture Savadkoohi B., Aliakbari M., Predicting Customer Favorite Products in E-commerce, International Conference on Innovation and Research in Engineering Sciences, (2020); Ture Savadkoohi B., Geyratmand K., Increase the Security of Digital Signature for E-commerce, International Conference on Electrical Engineering, Mechanical Engineering and Computer, (2019); Manjula K.G., Ravikumar M.N., Color Image Encryption and Decryption Using DES Algorithm, Journal of Engineering and Technology, 3, 7, pp. 1715-1718, (2016); Mitchell C., On the Security of 2-Key Triple DES, Journal of IEEE Transactions on Information Theory, 62, 11, pp. 6260-6267, (2016); Wang Y., Su C., Horng C., Wu C., Huang C., Single-and Multi-Core Configurable AES Architectures for Flexible Security, Journal of IEEE Transactions on very Large-Scale Integration (VLSI) Systems, 18, 4, pp. 541-552, (2010); Bansal A., Agrawal A., Providing Security, Integrity and Authentication Using ECC Algorithm in Cloud Storage, IEEE International Conference on Computer Communication and Informatics (ICCCI), (2017); Laiphrakpam D., Khumanthem M., Medical Image Encryption Based on Improved ElGamal Encryption Technique, Journal of Optik, 147, pp. 88-102, (2017); Jaju S., Chowhan S., A Modified RSA Algorithm to Enhance Security for Digital Signature, IEEE International Conference and Workshop on Computing and Communication, (2015); Jaju S., Chowhan S., Analytical Study of Modified RSA Algorithms for Digital Signature, Journal on Recent and Innovation Trends in Computing and Communication, 3, 3, pp. 944-949, (2015); Patel G., Panchal K., Patel S., A Comprehensive Study on Various Modifications in RSA Algorithm, Journal of Engineering Development and Research, 1, 3, pp. 161-163, (2014); Tint S., Survey on Asymmetric Algorithm Using RSA Different Modified Models, Journal Computer Applications, 1, 2, pp. 27-35, (2014); Chhabra A., Mathur S., Modified RSA Algorithm: A Secure Approach, International Conference on Computational Intelligence and Communication Networks, (2011); Lax G., Buccafurri F., Caminit G., Digital Document Signing: Vulnerabilities and Solution, Journal of Information Security: A Global Perspective, 24, 1-3, pp. 1-14, (2015); Hernaandez Ardieta J., Enhancing the Reliability of Digital Signatures as Non-Repudiation Evidence under a Holistic Threat Model, (2011); Thomas C.G., Jose R., A Comparative Study on Different Hashing Algorithms, Journal of Innovative Research in Computer and Communication Engineering, 3, 7, pp. 170-175, (2015); Agung A., Dewi P., Shaugi A., Salman M., Analysis and Comparison of MD5 and SHA-1 Algorithm Implementation in Simple-O Authentication Based Security System, IEEE International Conference on QiR, (2013); Rao A., Krian J., Poornalatha G., Application of Market-Basket Analysis on Healthcare, Journal of System Assurance Engineering and Management, (2021); Gayathri B., Efficient Market Basket Analysis Based on FP-Bonsai, International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC), (2017); Chavan G., Gaikwad N., Samal T., Sonule A., Palivela H., Patil A.C., Various Mining Techniques Defined for Mining Product Valuation Instances in Market Basket Data, International Conference on Green Computing Communication and Electrical Engineering (ICGCCEE), (2014); Yu J., Gao M., Rong W., Rong Y., Xiong Q., A Social Recommender Based on Factorization and Distance Metric Learning, Journal of IEEE, 5, pp. 21557-21566, (2017); Koren Y., Bell R., Volinsky C., Matrix Factorization Technique for Recommender System, Journal of IEEE Computer Society, 42, 8, pp. 30-37, (2009); Kasap O., Ekmekci N., Ketenci U., Combining Logistic Regression Analysis and Association Rule Mining via MLR Algorithm, International Conference on Software Engineering Advances, (2016); Nie G., Rowe W., Zhang L., Tian Y., Shi Y., Credit Card Churn Forecasting by Logistic Regression and Decision Tree, Journal of Expert System with Application, 38, 12, pp. 15273-15285, (2011); Sheng G., Hou H., Jaing X., Chen Y., A Novel Association Rule Mining Method of Big Data for Power Transformers state Parameters Based on Probabilistic Graph Model, Journal of IEEE Transactions on Smart Grid, 9, 2, pp. 695-702, (2018); Hu W., Gao J., Wang Y., Wu O., Maybank S., Online Adaboost-Based Parameterized Method for Dynamic Distributed Network Intrusion Detection, Journal of IEEE Transactions on Cybrnetics, 44, 1, pp. 66-82, (2014); Golabi F., Shamsi M., Sadaaghi M.H., Barzegar A., Hejazi M., Development of a New Oligonucleotide Block Location-Based Feature Extraction (BLBFE) Method for the Classification of Riboswitches, Journal of Molecular and Genomics, 295, pp. 525-534, (2020); Lopes P., Roy B., Dynamic Recommendation System using Web Usage Mining for E-commerce Users, International Conference on Advanced Computing Technologies and Applications, (2015); Briand L.C., Wust J., Daly J.W., Poter D.V., Exploring the Relationships in Object-Oriented Systems, Journal of Systems and Software, 51, 3, pp. 245-273, (2000)","B.T. Savadkoohi; Department of Computer and Electrical Engineering, Seraj Higher Education Institute, Tabriz, Iran; email: bita.turesavadkoohi@gmail.com",null,"International Organization on 'Technical and Physical Problems of Engineering'",{"$nulls":5},2.0773528E7,null,null,null,"English","Int. J. Tech. Phys. Probl. Eng.","Article","Final",null,"Scopus","2-s2.0-85139450969"]
["Ouyang Z.; Leung E.K.H.; Huang G.Q.","Ouyang, Zhiyuan (57329730900); Leung, Eric Ka Ho (57328966600); Huang, George Q. (7403425048)","57329730900; 57328966600; 7403425048","Community logistics for dynamic vehicle dispatching: The effects of community departure “time” and “space”",2022.0,"Transportation Research Part E: Logistics and Transportation Review",165.0,null,102842.0,null,null,null,5.0,"10.1016/j.tre.2022.102842","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135721977&doi=10.1016%2fj.tre.2022.102842&partnerID=40&md5=5b589a364b4095d91bdbcccb1e1e15ad","Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Pokfulam, Hong Kong; Management School, University of Liverpool, Liverpool, L69 7ZH, United Kingdom","Ouyang Z., Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Pokfulam, Hong Kong; Leung E.K.H., Management School, University of Liverpool, Liverpool, L69 7ZH, United Kingdom; Huang G.Q., Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Pokfulam, Hong Kong","The rise of e-commerce has completely transformed the dynamicity and problem nature of last-mile delivery, owing to significant B2C customer demand in compact urban areas. Given the unprecedented growths of urban last-mile deliveries, this paper proposes a novel postponement prioritized-route optional approach, namely Community Logistics (CL), as a new logistics tool to manage dynamic arrivals of delivery requests received in e-commerce hubs. Each vehicle is responsible for serving a “community”. At each decision epoch, fragmented e-commerce delivery requests arrived at the depot are either allocated to a community or postponed to later epochs for actual last-mile delivery. With an objective of consolidating newly arrived requests, we develop two dynamic policies – temporal and spatial, respectively for temporally delaying vehicle's departure and spatially allocating more pre-partitioned geographical cells into one community. The main contribution of this study lies in a spatiotemporal relativity analysis and a comparative analysis. The former demonstrates the essence of incorporating both dynamic community departure times and dynamic community regions into managing urban e-commerce deliveries, whereas the latter validates the merits of Community Logistics against dynamic vehicle routing solutions. In the end, we call for further developments of community logistics strategies to address the impacts of urban deliveries due to the rise of e-commerce and online shopping. © 2022 Elsevier Ltd","Community logistics (CL); Dynamic delivery dispatching; E-commerce last-mile delivery; Megacities deliveries; Serving region generation problem (SRGP); Urban logistics","Urban growth; Vehicle routing; Vehicles; Community logistic; Departure time; Dynamic delivery dispatching; E- commerces; E-commerce last-mile delivery; Last mile; Megacities; Megacity delivery; Serving region generation problem; Urban logistics; electronic commerce; logistics; megacity; urban transport; Electronic commerce",{"$nulls":6},"Banerjee D., Erera A.L., Toriello A., Fleet sizing and service region partitioning for same-day delivery systems, Transport. Sci., (2022); Bender M., Kalcsics J., Meyer A., Districting for parcel delivery services–A two-Stage solution approach and a real-World case study, Omega, 96, (2020); Braekers K., Ramaekers K., Van Nieuwenhuyse I., The vehicle routing problem: State of the art classification and review, Comput. Ind. Eng., 99, pp. 300-313, (2016); Carlsson J.G., Dividing a territory among several vehicles, INFORMS Journal on Computing, 24, 4, pp. 565-577, (2012); Carlsson J.G., Delage E., Robust partitioning for stochastic multivehicle routing, Oper. Res., 61, 3, pp. 727-744, (2013); Gendreau M., Guertin F., Potvin J.Y., Seguin R., Neighborhood search heuristics for a dynamic vehicle dispatching problem with pick-ups and deliveries, Transport. Res. C: Emerg. Technol., 14, 3, pp. 157-174, (2006); Glover F., Laguna M., Tabu search. In Handbook of combinatorial optimization, Handbook of Combinatorial Optimization, pp. 2093-2229, (1999); Gonzalez-Ramirez R.G., Smith N.R., Askin R.G., Miranda P.A., Sanchez J.M., A hybrid metaheuristic approach to optimize the districting design of a parcel company, J. Appl. Res. Technol., 9, 1, pp. 19-35, (2011); Hintsch T., Irnich S., Large multiple neighborhood search for the clustered vehicle-routing problem, Eur. J. Oper. Res., 270, 1, pp. 118-131, (2018); Holland J.H., Genetic algorithms, Scientific Am., 267, 1, pp. 66-72, (1992); Huang Y., Savelsbergh M., Zhao L., Designing logistics systems for home delivery in densely populated urban areas, Transport. Res. B: Methodol., 115, pp. 95-125, (2018); Jia Y.-H., Chen W.-N., Gu T., Zhang H., Yuan H., Lin Y., Yu W.-J., Zhang J., A dynamic logistic dispatching system with set-based particle swarm optimization, IEEE Trans. Syst. 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Sci., 53, 1, pp. 203-221, (2019); Voccia S.A., Campbell A.M., Thomas B.W., The same-day delivery problem for online purchases, Transport. Sci., 53, 1, pp. 167-184, (2019); Wassan N., Nagy G., Vehicle routing problem with deliveries and pickups: modelling issues and meta-heuristics solution approaches, Int. J. Transport., 2, 1, pp. 95-110, (2014); Winkenbach M., Kleindorfer P.R., Spinler S., Enabling urban logistics services at La Poste through multi-echelon location-routing, Transport. Sci., 50, 2, pp. 520-540, (2016); (2020); Yu G., Yang Y., Dynamic routing with real-time traffic information, Oper. Res. Int. J., 19, 4, pp. 1033-1058, (2019); Zhou L., Zhen L., Baldacci R., Boschetti M., Dai Y., Lim A., A Heuristic Algorithm for solving a large-scale real-world territory design problem, Omega (United Kingdom), 103, (2021)","G.Q. Huang; Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Pokfulam, Hong Kong; email: gqhuang@hku.hk",null,"Elsevier Ltd",{"$nulls":5},1.3665545E7,null,null,null,"English","Transp. Res. Part E Logist. Transp. Rev.","Article","Final",null,"Scopus","2-s2.0-85135721977"]
["He D.","He, Dan (57571610800)",5.75716108E10,"Research on Optimization of Supermarket Chain Distribution Routes Under O2O Model",2022.0,"Process Integration and Optimization for Sustainability",6.0,3.0,null,837.0,844.0,7.0,0.0,"10.1007/s41660-022-00246-2","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85127952557&doi=10.1007%2fs41660-022-00246-2&partnerID=40&md5=4b3225f9b3a9503901acad120f27a02b","International Business College, Zhejiang Industry & Trade Vocational College, Zhengjiang, Wenzhou, 325003, China","He D., International Business College, Zhejiang Industry & Trade Vocational College, Zhengjiang, Wenzhou, 325003, China","Dealing with the store distribution problems in transformation and upgrading of supermarket chains under Online-to-Offline (O2O) e-commerce model and considering the factors that affect the distribution cost and customer satisfaction, such as distribution distance, number of distribution vehicles, and delivery time, an O2O store distribution optimization model has been constructed with the purpose of minimizing total distribution cost. Moreover, a two-stage heuristic algorithm for ordering nearest distribution and mileage saving planning has been designed. The applicability and effectiveness of the model and method have been verified by enterprise case data collected. The results have shown that the total cost of distribution is obviously reduced compared with the accounting results of related models, which is suitable for supermarket chains or single-store retail enterprises with low probability of order splitting and distribution due to the shortage of certain products. © 2022, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.","Chain stores; Mileage saving method; O2O; Optimization model for distribution","Costs; Customer satisfaction; Optimization; Probability distributions; Retail stores; Chain distribution; Chain store; Distribution costs; Distribution route; Mileage saving method; O2O; Optimisations; Optimization model for distribution; Optimization models; Supermarket chains; Heuristic algorithms",{"$nulls":6},"He D., Study on the distribution path optimization of fresh department stores in online to offline supermarket chain, J Zhejiang Vocational and Technical College of Industry and Trade, 21, 1, pp. 47-52, (2021); Li S., Chen H., Optimization of fresh food distribution route with time window based on NSGA II, J Shanghai Maritime University, 41, 2, pp. 58-64, (2020); Meng X., Hu R., Qian B., Effective Hyrid PBIL algorithm for vehicle routing problem with time, Windows Syst Eng Theory Pract, 34, 10, pp. 2701-2709, (2014); Mester D., Braysy O., Dullaert W., A multi-parametric evolution strategies algorithm for vehicle routing, Problems Expert Systems with Applications, 32, 2, pp. 508-517, (2007); Wang C., Shang Y., Khayatnezhad M., Fuzzy stress-based modeling for probabilistic irrigation planning using copula-NSPSO, Water Resour Manage, 35, 14, pp. 4943-4959, (2021); Wang H., Khayatnezhad M., Yousefi N., Using an optimized soil and water assessment tool by deep belief networks to evaluate the impact of land use and climate change on water resources, (2022); Wang S., Ma J., Li W., Khayatnezhad M., Daneshvar Rouyendegh B., An optimal configuration for hybrid sofc, gas turbine, and proton exchange membrane electrolyzer using a developed aquila optimizer, Int J Hydrog Energy, 47, 14, pp. 8943-8955, (2022); Wu P., Liu H., Peng J., Ncertain planning model of supermarket logistics distribution with time, Window Operation Manag, 24, 6, pp. 58-64, (2015); Xin Y., Shi S., Yang H., Online-to-offline chain store distribution optimization model based on order splitting, J Transp Syst Ing Inf Technol, 20, 5, pp. 212-217, (2020); Xu Y.P., Ouyang P., Xing S.M., Qi L.Y., Khayatnezhad M Jafari H., Optimal structure design of a PV/FC HRES using amended Water Strider Algorithm, Energy Rep, 7, pp. 2057-2067, (2021); Yang Y., Lang M., Hu S., Research on the model of vehicle routing problem with time windows and its improved simulated annealing algorithm, J Ind Eng Eng Manag, 20, 3, pp. 107-204, (2006); Yao Z., Vehicle routing optimization of fresh food distribution in chain supermarket with time, Window Commercial times, 29, pp. 28-29, (2014); Zhang J., Khayatnezhad M., Ghadimi N., Optimal model evaluation of the proton-exchange membrane fuel cells based on deep learning and modified African vulture optimization algorithm. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 44, 1, pp. 287-305, (2022); Zhu P., Saadati H., Khayatnezhad M., Application of probability decision system and particle swarm optimization for improving soil moisture content, Water Supply, 21, 8, pp. 4145-4152, (2021)","D. He; International Business College, Zhejiang Industry & Trade Vocational College, Wenzhou, Zhengjiang, 325003, China; email: hdboom2006@163.com",null,"Springer",{"$nulls":5},2.5094238E7,null,null,null,"English","Process. Integr. Optim. Sustain.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85127952557"]
["Weinstein A.T.; Anti K.; Ochoa E.","Weinstein, Art T. (26434975200); Anti, Kristen (57286376800); Ochoa, Esteban (57285445600)","26434975200; 57286376800; 57285445600","World’s biggest retailer launches Walmart Plus and customers have their say",2022.0,"Journal of Business Strategy",43.0,6.0,null,381.0,390.0,9.0,4.0,"10.1108/JBS-07-2021-0133","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85116505920&doi=10.1108%2fJBS-07-2021-0133&partnerID=40&md5=fbce5007ec464e4af42edf624a7dd33c","Department of Marketing, Nova Southeastern University, Fort Lauderdale, FL, United States","Weinstein A.T., Department of Marketing, Nova Southeastern University, Fort Lauderdale, FL, United States; Anti K., Department of Marketing, Nova Southeastern University, Fort Lauderdale, FL, United States; Ochoa E., Department of Marketing, Nova Southeastern University, Fort Lauderdale, FL, United States","Purpose: The Covid crisis led to a huge worldwide shift in consumer behavior. In response, Walmart’s revised business strategy promoted their online delivery service known as Walmart Plus. This study aims to critique the potential of this new venture via a customer value analysis. Design/methodology/approach: Using the customer value funnel, Walmart’s market environment, organizational factors, customer perceptions and business performance are examined. An exploratory survey collected data from South Florida residents on awareness and interest in Walmart Plus. Findings: The changing marketplace forced Walmart to quickly adapt to online buyers and emphasize the value of their retail and grocery products. Walmart Plus is an alternative to Amazon Prime and can assist the company gain market share in regional grocery markets. Research limitations/implications: This work is largely conceptual and presents a case study featuring a limited sample in one metropolitan statistical area. While the findings are insightful, it may not be representative of the US market. Practical implications: Corporate executives and entrepreneurs must respond to changing market conditions and rethink their business models to deliver superior customer value. This requires introducing innovative services and digital initiatives to compete successfully. The paper concludes with recommendations for management and questions for consideration. Originality/value: Walmart is the dominant American retailer and a global leader. While there has been considerable research on this retail giant, there has been limited analysis of their digital initiatives such as Walmart Plus. © 2021, Emerald Publishing Limited.","Customer value; E-commerce; Grocery industry; Marketing strategy; Online shopping; Retail management; Walmart",{"$nulls":7},"Best R., 5 Key suppliers of Walmart, (2021); Brown S., Walmart plus review: a fast delivery service for groceries and lots more, c/net tech, (2020); Top 2,173 Walmart reviews, (2021); Hanbury M., This is what the average Walmart shopper looks like, (2020); Herrera S., Calderon A., Amazon’s long reach, Wall Street Journal, (2021); Monteros M., Walmart+ gains traction 5 months after launch, (2021); Morgan B., What Walmart plus means for the future of retail, (2021); Walmart – statistics & facts, Statista, (2021); Publix continues domination of Florida’s retail marketplace, (2020); Quick facts - United States, US department of commerce, (2020); (2021); (2020); The business of better, (2021); Weinstein A., Superior Customer Value – Finding and Keeping Customers in the Now Economy, (2019); Survey: consumers say Walmart is the top grocer for value, chain store age, (2021)","A.T. Weinstein; Department of Marketing, Nova Southeastern University, Fort Lauderdale, United States; email: art@nova.edu",null,"Emerald Publishing",{"$nulls":5},2756668.0,null,null,null,"English","J. Bus. Strategy","Article","Final",null,"Scopus","2-s2.0-85116505920"]
["Xue D.; Zhao X.; Dong J.; Ren R.; Xu Y.; Chen Z.","Xue, Dan (58131232400); Zhao, Xiaojing (56170214300); Dong, Jianjun (55477996200); Ren, Rui (55424159200); Xu, Yuanxian (57207760982); Chen, Zhilong (55705590600)","58131232400; 56170214300; 55477996200; 55424159200; 57207760982; 55705590600","Critical Success Factors of Underground Logistics Systems from the Project Life Cycle Perspective",2022.0,"Buildings",12.0,11.0,1979.0,null,null,null,0.0,"10.3390/buildings12111979","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85149462037&doi=10.3390%2fbuildings12111979&partnerID=40&md5=6864fa23d1babe13772fcdea528eb908","School of Defense Engineering, Army Engineering University of PLA, Nanjing, 210007, China; School of Management and Economics, Beijing Institute of Technology, Beijing, 100081, China; College of Civil Engineering, Nanjing Tech University, Nanjing, 211816, China","Xue D., School of Defense Engineering, Army Engineering University of PLA, Nanjing, 210007, China; Zhao X., School of Management and Economics, Beijing Institute of Technology, Beijing, 100081, China; Dong J., College of Civil Engineering, Nanjing Tech University, Nanjing, 211816, China; Ren R., School of Defense Engineering, Army Engineering University of PLA, Nanjing, 210007, China; Xu Y., School of Defense Engineering, Army Engineering University of PLA, Nanjing, 210007, China; Chen Z., School of Defense Engineering, Army Engineering University of PLA, Nanjing, 210007, China","The surging demand for logistics systems brought about by the vigorous development of e-commerce makes urban traffic more and more congested. The need for a sustainable transition in terms of urban transportation infrastructure also encourages the further innovation of logistics systems. The urban underground logistics system (ULS) emerges as a promising alternative for realizing efficient large-scale freight distribution in megacities. However, there are relatively few studies that have explored the factors that determine the uptake of ULSs in practice. This paper thus aims to identify the critical success factors of ULSs throughout project life cycle stages. Firstly, a desktop study and a study using the Delphi method were conducted to extract the critical success factors (CSFs) of ULS projects. Secondly, a questionnaire survey was conducted to collect data on the perceived significance of the selected success factors from ULS professionals. Thirdly, the intergroup comparison of the significance of CSFs and exploratory factory analysis were used to ascertain the critical factors and latent determinants influencing the development of ULS projects. In total, 36 CSFs in the four life cycle stages of ULS projects were finalized. The identified factors represent the seven latent determinants in developing a ULS project, namely, overall feasibility and acceptance of the ULS, prototype system, and business model, competence and resources for ULS construction and operation, station layout and intermodal transportation, government policies and incentives, long-term planning of the underground space and logistics network, and market investigation and forecasting. The research findings of the paper help guide practitioners and policy makers on decisions made during ULS planning and construction and provide a reference performance evaluation framework for ULS projects. © 2022 by the authors.","critical success factor; life cycle; project development; sustainable transport; underground logistics system",{"$nulls":5},"National Natural Science Foundation of China, NSFC, (71631007, 71971214); Natural Science Foundation of Jiangsu Province, (BK20210437)","This research is financially supported by the Natural Science Foundation of Jiangsu Province (Grants BK20210437) and the National Natural Science Foundation of China (Grants 71631007, 71971214).","Coulombel N., Dablanc L., Gardrat M., Koning M., The Environmental Social Cost of Urban Road Freight: Evidence from the Paris Region, Transp. Res. Part D Transp. Environ, 63, pp. 514-532, (2018); Munoz-Villamizar A., Santos J., Montoya-Torres J.R., Velazquez-Martinez J.C., Measuring Environmental Performance of Urban Freight Transport Systems: A Case Study, Sustain. Cities Soc, 52, (2020); ITF Transport Outlook 2021, (2021); Qian Q., Present state, problems and development trends of urban underground space in China, Tunn. Undergr. Space Technol, 55, pp. 280-289, (2016); Visser J., The development of underground freight transport: An overview, Tunn. Undergr. Space Technol, 80, pp. 123-127, (2018); Wang Y.X., Wang Z.Q., Construction of underground logistics network mathematical model, J. Eng. Math, 37, pp. 664-672, (2020); Chen D.C., Yu Y., Liang Y.X., Zhao X., Wang X., Han Y., Lu J., Chen C., Zhu S., Pan Y., Design of urban intelligent underground logistics system based on big data, Tunn. 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Energy Rev, 68, pp. 370-379, (2017); Dampier A., Marinov M.A., Study of the feasibility and potential implementation of metro-based freight transportation in Newcastle upon Tyne, Urban Rail Transit, 1, pp. 164-182, (2015); He M., Sun L., Zeng X., Liu W., Tao S., Node Layout Plans for Urban Underground Logistics Systems Based on Heuristic bat Algorithm, Comput. Commun, 154, pp. 465-480, (2020); Braet J., The environmental impact of container pipeline transport compared to road transport: Case study in the Antwerp Harbor region and some general extrapolations, Int. J. Life Cycle Assess, 16, pp. 886-896, (2011); Rezaie N., Tabesh A., Najafifi M., Ma B., Mousavipour S.H., Evaluation of applications and the comparison of routes for underground freight transportation in Texas, Proceedings of the Pipelines 2016 Conference, pp. 847-856; Vernimmen B., Dullaert W., Geens E., Notteboom T., T'Jollyn B., Van Gilsen W., Winkelmans W., Underground Logistics Systems: A Way to Cope with Growing Internal Container Traffic in the Port of Antwerp?, Transp. Plan. Technol, 30, pp. 391-416, (2007); van der Heijden M.C., van Harten A., Ebben M.J.R., Saanen Y.A., Valentin E.C., Verbraeck A., Using Simulation to Design an Automated Underground System for Transporting Freight Around Schiphol Airport, Interfaces, 32, pp. 1-19, (2002); Kelly J., Marinov M., Innovative Interior Designs for Urban Freight Distribution Using Light Rail Systems, Urban Rail Transit, 3, pp. 238-254, (2017); Zhao X., Hwang B.G., Yu G.S., Identifying the critical risks in underground rail international construction joint ventures: Case study of Singapore, Int. J. Proj. Manag, 31, pp. 554-566, (2013); Hwang B.G., Zhao X., Yu G.S., Risk identification and allocation in underground rail construction joint ventures: Contractors’ perspective, J. Civ. Eng. Manag, 22, pp. 758-767, (2016); Yang M.C., A Study of Prototypes, Design Activity, and Design Outcome, Des. Stud, 26, pp. 649-669, (2005); Dong J., Hu W., Yan S., Ren R., Zhao X., Network Planning Method for Capacitated Metro-Based Underground Logistics System, Adv. Civ. Eng, 2018, (2018); Hu Y., Zhang K., Yang J., Wu Y., Application of Hierarchical Facility Location-Routing Problem with Optimization of an Underground Logistic System: A Case Study in China, Math. Probl. Eng, 2018, (2018); Zhong Y., Luo S., Bao M., Lv X., Dynamic Network Planning of Underground Logistics System on Uncertainty Graph, Math. Probl. Eng, 2019, (2019); Hu W., Dong J., Hwang B.-G., Ren R., Chen Z., A preliminary prototyping approach for emerging metro-based underground logistics systems: Operation mechanism and facility layout, Int. J. Prod. Res, 59, pp. 7516-7536, (2020); Hu W., Dong J., Yuan J., Ren R., Chen Z., Cheng H., Agent-based modeling approach for evaluating underground logistics system benefits and long-term development in megacities, J. Manag. Sci. Eng, 7, pp. 266-286, (2022); Hu W., Dong J., Hwang B.-G., Ren R., Chen Z., Network planning of urban underground logistics system with hub-and-spoke layout: Two phase cluster-based approach, Eng. Constr. Archit. Manag, 27, pp. 2079-2105, (2020); Field A., Discovering Statistics with IBM SPSS Statistics, (2013); Stein D., Stein R., Beckmann D., Schoesser B., CargoCap: Feasibility study of transporting containers through underground pipelines, Proceedings of the 4th International Symposium on Underground Freight Transportation by Capsule Pipelines and Other Tube/Tunnel Systems; Liu H., Lenau C.W., A LIM-PCP system for freight transportation in underground cities, Proceedings of the 12th International Conference of the Associated Research Centers for Urban Underground Space; Ott R., Longnecker M., An Introduction to Statistical Methods and Data Analysis, (2008); Hwang B.G., Zhao X., Yang K.W., Effect of BIM on rework in construction projects in Singapore: Status quo, magnitude, impact, and strategies, J. Constr. Eng. Manag, 145, (2019); Chou Y.M., Polansky A.M., Mason R.L., Transforming non-normal data to normality in statistical process control, J. Qual. Technol, 30, pp. 133-141, (1998); Zhao X., Hwang B.G., Lim J., Job satisfaction of project managers in green construction projects: Constituents, barriers, and improvement strategies, J. Clean. Prod, 246, (2020); Tixier A., Hallowell M., Albert A., van Boven L., Kleiner B., Psychological antecedents of risk-taking behavior in construction, J. Constr. Eng. Manag, 140, (2014); Tavakol M., Dennick R., Making sense of Cronbach’s alpha, Int. J. Med. Educ, 2, (2011); Watkins M.W., Exploratory factor analysis: A guide to best practice, J. Black Psychol, 44, pp. 219-246, (2018); Howard M.C., A review of exploratory factor analysis decisions and overview of current practices: What we are doing and how can we improve?, Int. J. Hum.-Comput. Interact, 32, pp. 51-62, (2016); Tabachnick B.G., Fidell L.S., Ullman J.B., Using Multivariate Statistics, (2006); Egbunike O.N., Potter A.T., Are freight pipelines a pipe dream? A critical review of the UK and European perspective, J. Transp. Geogr, 19, pp. 499-508, (2011); Xu Y., Dong J., Ren R., Yang K., Chen Z., The impact of metro-based underground logistics system on city logistics performance under COVID-19 epidemic: A case study of Wuhan, China, Transp. Policy, 116, pp. 81-95, (2022); Guo D., Chen Y., Yang J., Tan Y.H., Zhang C., Chen Z., Planning and application of underground logistics systems in new cities and districts in China, Tunn. Undergr. Space Technol, 113, (2021); Zhao L., Li H., Li M., Sun Y., Hu Q., Mao S., Li J., Xue J., Location selection of intra-city distribution hubs in the metro-integrated logistics system, Tunn. Undergr. Space Technol, 80, pp. 246-256, (2018); Wiese A., Kellner J., Lietke B., Toporowski W., Zielke S., Sustainability in retailing–a summative content analysis, Int. J. Retail. Distrib. Manag, 40, pp. 318-335, (2012)","X. Zhao; School of Management and Economics, Beijing Institute of Technology, Beijing, 100081, China; email: xiaojzhao@bit.edu.cn",null,"MDPI",{"$nulls":5},2.0755309E7,null,null,null,"English","Buildings","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85149462037"]
["Dadouchi C.; Agard B.; Montreuil B.","Dadouchi, Camélia (57203683671); Agard, Bruno (57203235538); Montreuil, Benoit (7003796719)","57203683671; 57203235538; 7003796719","Context-Aware Interactive Knowledge-Based Recommendation",2022.0,"SN Computer Science",3.0,6.0,472.0,null,null,null,1.0,"10.1007/s42979-022-01328-1","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85138238850&doi=10.1007%2fs42979-022-01328-1&partnerID=40&md5=b3d1a25fd3e87a348ca9452bcd7b0f10","Départment de mathématique et génie industriel, Polytechnique Montréal, Montréal, H3T1J4, QC, Canada; Physical Internet Center, H. Milton Stewart School of Industrial and Systems Engineering, Atlanta, 30332, GA, United States","Dadouchi C., Départment de mathématique et génie industriel, Polytechnique Montréal, Montréal, H3T1J4, QC, Canada; Agard B., Départment de mathématique et génie industriel, Polytechnique Montréal, Montréal, H3T1J4, QC, Canada; Montreuil B., Physical Internet Center, H. Milton Stewart School of Industrial and Systems Engineering, Atlanta, 30332, GA, United States","Recommender systems have widely been used in the past few years as a recipe to success in e-commerce. Already, 35 percent of what consumers purchase on Amazon and 75 percent of what they watch on Netflix come from product recommendation (MacKenzie et al. in How retailers can keep up with consumers. Technical report. McKinsey & Company, London, 2013). However, in the context of high-end products such as cars, computers, apartments, or financial services, traditional approaches are not the best choice since it is infeasible to collect enough customer behavioral information or feedback over numerous items (Burke et al. in Ai Mag 32:13–8, 2011). Accordingly, since brick and mortar outlets remain the channel of choice for those kinds of products, recommender systems need to adjust to a context in which inventory and customer information are limited. To achieve this goal, we propose a context-aware interactive knowledge-based recommendation to make recommendation to customers who walk into a store, even when no previous information about the customers is available. This technique works in 3 stages: stage 1, contextual pre-filtering, stage 2, interactive exploration and stage 3, constraint-based recommendation. The methodology was developed with an industrial partner in the domain of sport vehicles and is illustrated step by step with an example inspired from this partnership. The proposed method enables an iterative exploration of the products in-store, creates a learning base to learn customers’ interests and recommends a suitable product with regards to logistics, contracts and product’s availability in the network. The method has been tested on our industrial partners’ data and validated by domain experts. This work is a step toward the creation of a continuously evolving learning base of customers’ interests that can be used to adjust sale’s strategy and to develop new products, designs and features that better meet the ever-changing demand of customers. © 2022, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.","Context-aware; in-store recommendation; Knowledge-based; Recommender systems; supply chain",{"$nulls":5},"Natural Sciences and Engineering Research Council of Canada, NSERC, (RDCPJ 492021-15)","The authors would like to acknowledge the National Sciences and Engineering Research Council of Canada (NSERC) for funding this work under grant RDCPJ 492021-15, and for providing other support for this research. The authors also declare that they have no conflict of interest. ","Mackenzie I., Meyer C., Noble S., How Retailers Can Keep up with Consumers. Technical Report, (2013); Burke R., Felfernig A., Goker M.H., Recommender systems: an overview, Ai Mag, 32, pp. 13-18, (2011); Rajamma R.K., Paswan A.K., Ganesh G., Services purchased at brick and mortar versus online stores, and shopping motivation, J Serv Market, 21, 3, pp. 200-212, (2007); He C., Parra D., Verbert K., Interactive recommender systems: a survey of the state of the art and future research challenges and opportunities, Expert Syst Appl, 56, pp. 9-27, (2016); Herlocker J.L., Konstan J.A., Riedl J., Explaining collaborative filtering recommendations, Proceedings of the 2000 ACM Conference on Computer Supported Cooperative Work, pp. 241-250, (2000); Adomavicius G., Tuzhilin A., Context-aware recommender systems. Recommender systems handbook, pp. 217-253, (2011); Shen Y., Deng Y., Ray A., Jin H., Interactive recommendation via deep neural memory augmented contextual bandits, Proceedings of the 12Th ACM Conference on Recommender Systems, pp. 122-130, (2018); Felfernig A., Reducing development and maintenance efforts for web-based recommender applications, Int J Web Eng Technol, 3, 3, pp. 329-351, (2007); Derhami S., Montreuil B., Bau G., Assessing product availability in omnichannel retail networks in the presence of on-demand inventory transshipment and product substitution, Omega, 102, (2021); Adomavicius G., Tuzhilin A., Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions, IEEE Trans Knowl Data Eng, 17, 6, pp. 734-749, (2005); Candillier L., Meyer F., Boulle M., Comparing state-of-the-art collaborative filtering systems, International Workshop on Machine Learning and Data Mining in Pattern Recognition, Springer, pp. 548-562, (2007); Schafer J.B., Frankowski D., Herlocker J., Sen S., Collaborative filtering recommender systems, pp. 291-324, (2007); Bobadilla J., Ortega F., Hernando A., Gutierrez A., Recommender systems survey, Knowl-Based Syst, 46, pp. 109-132, (2013); Abbas A., Zhang L., Khan S.U., A survey on context-aware recommender systems based on computational intelligence techniques, Computing, 97, 7, pp. 667-690, (2015); Verbert K., Manouselis N., Ochoa X., Wolpers M., Drachsler H., Bosnic I., Duval E., Context-aware recommender systems for learning: a survey and future challenges, IEEE Trans Learn Technol, 5, 4, pp. 318-335, (2012); Burke R., Knowledge-based recommender systems, Encycl Libr Inf Syst, 69, pp. 175-186, (2000); Felfernig A., Kiener A., Knowledge-based interactive selling of financial services with fsadvisor, Proceedings of the National Conference on Artificial Intelligence, 20, (2005); Jiang Z., Wang W., Benbasat I., Multimedia-based interactive advising technology for online consumer decision support, Commun ACM, 48, 9, pp. 92-98, (2005); Thompson C.A., Goker M.H., Langley P., A personalized system for conversational recommendations, J Artif Intell Res, 21, pp. 393-428, (2004); Towle B., Quinn C., Knowledge based recommender systems using explicit user models, Proceedings of the AAAI Workshop on Knowledge-Based Electronic Markets, pp. 74-77, (2000); Hariri N., Mobasher B., Burke R., Context adaptation in interactive recommender systems, Proceedings of the 8Th ACM Conference on Recommender Systems, pp. 41-48, (2014); Yu T., Mengshoel O., Meroux D., Jiang Z., Machine learning with decision trees and multi-armed bandits: An interactive vehicle recommender system, Technical Report 2019-01-1079, SAE International, (2019); Lacerda A., Multi-objective ranked bandits for recommender systems, Neurocomputing, 246, pp. 12-24, (2017); Cunningham M.S., The major dimensions of perceived risk, Risk Taking Inf Handl Consumer Behavior, 1967, pp. 82-111, (1967); Mitchell V.-W., Understanding consumers’ behaviour: can perceived risk theory help?, Manage Dec, 30, (1992); Munthiu M.-C., The buying decision process and types of buying decision behavior, Sibiu Alma Mater Univ J Ser A Econ Sci, 2, 4, pp. 27-33, (2009); Dinsdale A., Berdichevskiy A., The Future is Now Transforming the Automotive Customer Experience, (2018); Bitner M.J., Servicescapes: the impact of physical surroundings on customers and employees, J Market, 56, 2, pp. 57-71, (1992); Kotler P., Atmospherics as a marketing tool, J Retail, 49, 4, pp. 48-64, (1973); Solomon M.R., Surprenant C., Czepiel J.A., Gutman E.G., A role theory perspective on dyadic interactions: the service encounter, J Market, 49, 1, pp. 99-111, (1985); Crosby L.A., Stephens N., Effects of relationship marketing on satisfaction, retention, and prices in the life insurance industry, J Market Res, 24, 4, pp. 404-411, (1987); Crosby L.A., Evans K.R., Cowles D., Relationship quality in services selling: an interpersonal influence perspective, J Market, 54, 3, pp. 68-81, (1990); Car-buyers want to spend more time with salespeople, Study Says, (2019); Helander M.G., Khalid H.M., Lim T.Y., Peng H., Yang X., Emotional needs of car buyers and emotional intent of car designers, Theor Issues Ergon Sci, 14, 5, pp. 455-474, (2013); Khalid H.M., Making use of scenarios in human factors assessment validation of citarasa analysis system, Southeast Asian Network of Ergonomics Societies Conference (SEANES), IEEE, 20, pp. 1-6, (2012); Tsai H.-C., Hsiao S.-W., Evaluation of alternatives for product customization using fuzzy logic, Inf Sci, 158, pp. 233-262, (2004); Salvador F., Forza C., Principles for efficient and effective sales configuration design, Int J Mass Custom, 2, 1-2, pp. 114-127, (2007); Kandaswami K., Tiwar A., Driving through the consumer’s Mind: Steps in the Buying Process, (2014); Schreiner T., Rese A., Baier D., Multichannel personalization: identifying consumer preferences for product recommendations in advertisements across different media channels, J Retail Consumer Serv, 48, pp. 87-99, (2019); Li Q., Li K., You X., Bu S., Liu Z., Place recognition based on deep feature and adaptive weighting of similarity matrix, Neurocomputing, 199, pp. 114-127, (2016); Nowak E., Jurie F., Learning visual similarity measures for comparing never seen objects, 2007 IEEE Conference on Computer Vision and Pattern Recognition, IEEE, pp. 1-8, (2007); Gomaa W.H., Fahmy A.A., Et al., A survey of text similarity approaches, Int J Comput Appl, 68, 13, pp. 13-18, (2013); Kusiak A., Smith M., Data mining in design of products and production systems, Annu Rev Control, 31, 1, pp. 147-156, (2007); Nobauer M., Seyff N., Groher I., Similarity analysis within product line scoping: An evaluation of a semi-automatic approach, International Conference on Advanced Information Systems Engineering, Springer, pp. 165-179, (2014); Dadouchi C., Agard B., Lowering penalties related to stock-outs by shifting demand in product recommendation systems, Dec Support Syst, 114, pp. 61-69, (2018); Subramanian S., Harsha P., Demand modeling in the presence of unobserved lost sales, Manage Sci, 67, 6, pp. 3803-3833, (2021)","C. Dadouchi; Départment de mathématique et génie industriel, Polytechnique Montréal, Montréal, H3T1J4, Canada; email: camelia.dadouchi@polymtl.ca",null,"Springer",{"$nulls":5},"2662995X",null,null,null,"English","SN COMPUT. SCI.","Article","Final",null,"Scopus","2-s2.0-85138238850"]
["Leung E.K.H.; Ouyang Z.; Huang G.Q.","Leung, Eric K.H. (57328966600); Ouyang, Zhiyuan (57329730900); Huang, George Q. (7403425048)","57328966600; 57329730900; 7403425048","Community logistics: a dynamic strategy for facilitating immediate parcel delivery to smart lockers",2023.0,"International Journal of Production Research",61.0,9.0,null,2936.0,2961.0,25.0,2.0,"10.1080/00207543.2022.2073480","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85131003460&doi=10.1080%2f00207543.2022.2073480&partnerID=40&md5=fb1f6da3239f090a1318eecf39e3b14d","School of Management, University of Liverpool, Liverpool, United Kingdom; Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Pokfulam, Hong Kong","Leung E.K.H., School of Management, University of Liverpool, Liverpool, United Kingdom; Ouyang Z., Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Pokfulam, Hong Kong; Huang G.Q., Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Pokfulam, Hong Kong","The COVID Pandemic since early 2019 has imposed significant effects on our life. In the retail and logistics sector, the large-scale national lockdown has drastically driven e-commerce sales because the e-marketplace has become the only sales channel. Whilst the pandemic has accelerated the shift towards a more digital world and led to an irreversible dependence on e-commerce retailing, the pressure is on retailers and logistics service providers to respond to the growing demand for immediate delivery in the e-commerce era. Given the integration of smart lockers into developing a more favourable environment which potentially makes immediate delivery more feasible, this paper introduces a novel, dynamic delivery strategy, namely Community Logistics Strategy (CLS), for formulating and updating the new delivery plan in real time as new delivery requests to smart lockers arrive. To shed light on the effect of dynamic order arrival towards delivery planning, the CLS attempts to update the delivery plan by taking new requests into account in real time. Simulation results reveal the superiority of the proposed strategy in managing e-commerce delivery requests, especially within megacities where consumers are highly dense in a compact geographical area. © 2022 Informa UK Limited, trading as Taylor & Francis Group.","Community Logistics Strategy; dynamic vehicle dispatching; e-commerce last-mile delivery; instant delivery problems; real-time scheduling; spatial and temporal postponement","Locks (fasteners); Sales; Community logistic strategy; Delivery problems; Dynamic vehicle dispatching; E- commerces; E-commerce last-mile delivery; Instant delivery problem; Last mile; Logistics strategy; Real time scheduling; Spatial and temporal postponement; Vehicle dispatching; Electronic commerce",{"$nulls":4},"Guangdong Special Support Talent Program – Innovation and Entrepreneurship Leading Team, (201909010006, 2019BT02S593); Guangdong Special Support Talent Program–Innovation and Entrepreneurship Leading Team; RGC, (17203518)","Funding text 1: The authors would like to acknowledge partial financial supports from funding sources, including the 2019 Guangdong Special Support Talent Program – Innovation and Entrepreneurship Leading Team (China) (2019BT02S593), 2018 Guangzhou Leading Innovation Team Program (201909010006) and HKSAR RGC GRF Project (17203518). ; Funding text 2: The authors would like to acknowledge partial financial supports from funding sources, including the 2019 Guangdong Special Support Talent Program–Innovation and Entrepreneurship Leading Team (China) (2019BT02S593), 2018 Guangzhou Leading Innovation Team Program (201909010006) and HKSAR RGC GRF Project (17203518).","Archetti C., Jabali O., Speranza M.G., Multi-period Vehicle Routing Problem with Due Dates, Computers & Operations Research, 61, pp. 122-134, (2015); Banerjee D., Erera A.L., Toriello A., Fleet Sizing and Service Region Partitioning for Same-Day Delivery Systems, Transportation Science, (2022); Behnke M., Recent Trends in Last Mile Delivery: Impacts of Fast Fulfillment, Parcel Lockers, Electric or Autonomous Vehicles, and More,  Logistics Management, pp. 141-156, (2019); Bianchessi N., Drexl M., Irnich S., The Split Delivery Vehicle Routing Problem with Time Windows and Customer Inconvenience Constraints, Transportation Science, 53, 4, pp. 1067-1084, (2019); Braekers K., Ramaekers K., Van Nieuwenhuyse I., The Vehicle Routing Problem: State of the Art Classification and Review, Computers & Industrial Engineering, 99, pp. 300-313, (2016); Braysy O., Gendreau M., Vehicle Routing Problem with Time Windows, Part I: Route Construction and Local Search Algorithms, Transportation Science, 39, 1, pp. 104-118, (2005); Braysy O., Gendreau M., Vehicle Routing Problem with Time Windows, Part II: Metaheuristics, Transportation Science, 39, 1, pp. 119-139, (2005); Cardenas I., Borbon-Galvez Y., Verlinden T., Van de Voorde E., Vanelslander T., Dewulf W., City Logistics, Urban Goods Distribution and Last Mile Delivery and Collection, Competition and Regulation in Network Industries, 18, 1-2, pp. 22-43, (2017); Chen X., Ulmer M.W., Thomas B.W., Deep Q-Learning for Same-day Delivery with Vehicles and Drones, European Journal of Operational Research, 298, 3, pp. 939-952, (2022); Dabia S., Ropke S., Van Woensel T., Cover Inequalities for a Vehicle Routing Problem with Time Windows and Shifts, Transportation Science, 53, 5, pp. 1354-1371, (2019); Deutsch Y., Golany B., A Parcel Locker Network as a Solution to the Logistics Last Mile Problem, International Journal of Production Research, 56, 1-2, pp. 251-261, (2018); Ducret R., Parcel Deliveries and Urban Logistics: Changes and Challenges in the Courier Express and Parcel Sector in Europe—The French Case, Research in Transportation Business & Management, 11, pp. 15-22, (2014); Ferrucci F., Bock S., Real-time Control of Express Pickup and Delivery Processes in a Dynamic Environment, Transportation Research Part B: Methodological, 63, pp. 1-14, (2014); Giuffrida M., Mangiaracina R., Tumino A., Home Delivery vs Parcel Lockers: An Economic and Environmental Assessment, Proceedings of XXI Summer School “Francesco Turco”–Industrial Systems Engineering, Palermo, pp. 225-230, (2012); Hemmelmayr V.C., Cordeau J.F., Crainic T.G., An Adaptive Large Neighborhood Search Heuristic for Two-Echelon Vehicle Routing Problems Arising in City Logistics, Computers & Operations Research, 39, 12, pp. 3215-3228, (2012); Iwan S., Kijewska K., Lemke J., Analysis of Parcel Lockers’ Efficiency as the Last Mile Delivery Solution–the Results of the Research in Poland, Transportation Research Procedia, 12, pp. 644-655, (2016); Kallehauge B., Larsen J., Madsen O.B., Solomon M.M., Vehicle Routing Problem with Time Windows. Column Generation, pp. 67-98, (2005); Klapp M.A., Erera A.L., Toriello A., The Dynamic Dispatch Waves Problem for Same-Day Delivery, European Journal of Operational Research, 271, 2, pp. 519-534, (2018); Lan Y.L., Liu F.G., Huang Z., Ng W.W., Zhong J., Two-Echelon Dispatching Problem With Mobile Satellites in City Logistics, IEEE Transactions on Intelligent Transportation Systems, 23, 1, pp. 84-96, (2020); Lawler E.L., The Traveling Salesman Problem: A Guided Tour of Combinatorial Optimization, (1985); Lemke J., Iwan S., Korczak J., Usability of the Parcel Lockers from the Customer Perspective–the Research in Polish Cities, Transportation Research Procedia, 16, pp. 272-287, (2016); Lenstra J.K., Kan A.R., Complexity of Vehicle Routing and Scheduling Problems, Networks, 11, 2, pp. 221-227, (1981); Mangiaracina R., Perego A., Seghezzi A., Tumino A., Innovative Solutions to Increase Last-Mile Delivery Efficiency in B2C e-Commerce: A Literature Review, International Journal of Physical Distribution & Logistics Management, 49, 9, pp. 901-920, (2019); Poot A., Kant G., Wagelmans A.P.M., A Savings Based Method for Real-Life Vehicle Routing Problems, Journal of the Operational Research Society, 53, 1, pp. 57-68, (2002); Rossit D.G., Vigo D., Tohme F., Frutos M., Visual Attractiveness in Routing Problems: A Review, Computers & Operations Research, 103, pp. 13-34, (2019); Savelsbergh M., Van Woensel T., 50th Anniversary Invited Article—City Logistics: Challenges and Opportunities, Transportation Science, 50, 2, pp. 579-590, (2016); Schwerdfeger S., Boysen N., Optimizing the Changing Locations of Mobile Parcel Lockers in Last-Mile Distribution, European Journal of Operational Research, 285, 3, pp. 1077-1094, (2020); Shao S., Xu G., Li M., Huang G.Q., Synchronizing e-Commerce City Logistics with Sliding Time Windows, Transportation Research Part E: Logistics and Transportation Review, 123, pp. 17-28, (2019); Solomon M.M., Algorithms for the Vehicle Routing and Scheduling Problems with Time Window Constraints, Operation Research, 35, 2, pp. 254-265, (1987); Stroh A.M., Erera A.L., Toriello A., Tactical Design of Same-day Delivery Systems, Management Science, (2021); Tsai Y.T., Tiwasing P., Customers’ Intention to Adopt Smart Lockers in Last-Mile Delivery Service: A Multi-Theory Perspective, Journal of Retailing and Consumer Services, 61, (2021); Ulmer M.W., Mattfeld D.C., Koster F., Budgeting Time for Dynamic Vehicle Routing with Stochastic Customer Requests, Transportation Science, 52, 1, pp. 20-37, (2018); Ulmer M.W., Streng S., Same-Day Delivery with Pickup Stations and Autonomous Vehicles, Computers & Operations Research, 108, pp. 1-19, (2019); (2020); Vakulenko Y., Hellstrom D., Hjort K., What's in the Parcel Locker? Exploring Customer Value in e-Commerce Last Mile Delivery, Journal of Business Research, 88, pp. 421-427, (2018); van Heeswijk W.J., Mes M.R., Schutten J.M., The Delivery Dispatching Problem with Time Windows for Urban Consolidation Centers, Transportation Science, 53, 1, pp. 203-221, (2019); Voccia S.A., Campbell A.M., Thomas B.W., The Same-day Delivery Problem for Online Purchases, Transportation Science, 53, 1, pp. 167-184, (2019); Wang X., Yuen K.F., Wong Y.D., Teo C.C., An Innovation Diffusion Perspective of e-Consumers’ Initial Adoption of Self-Collection Service via Automated Parcel Station, International Journal of Logistics Management, 29, 1, pp. 237-260, (2018); Wang X., Zhan L., Ruan J., Zhang J., How to Choose “Last Mile” Delivery Modes for E-Fulfillment, Mathematical Problems in Engineering, 2014, (2014); Wang Y., Zhao L., Savelsbergh M., Wu S., Multi-Period Workload Balancing in Last-Mile Urban Delivery, Transportation Science, (2022); Wen M., Cordeau J.F., Laporte G., Larsen J., The Dynamic Multi-Period Vehicle Routing Problem, Computers & Operations Research, 37, 9, pp. 1615-1623, (2010); Xiao Z., Wang J.J., Lenzer J., Sun Y., Understanding the Diversity of Final Delivery Solutions for Online Retailing: A Case of Shenzhen, China, Transportation Research Procedia, 25, pp. 985-998, (2017); Zurel O., Hoyweghen L.V., Braes S., Seghers A., Parcel Lockers, an Answer to the Pressure on the Last Mile Delivery?, New Business and Regulatory Strategies in the Postal Sector. Topics in Regulatory Economics and Policy, pp. 299-312, (2018)","G.Q. Huang; Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Pokfulam, Hong Kong; email: gqhuang@hku.hk",null,"Taylor and Francis Ltd.",{"$nulls":5},207543.0,null,"IJPRB",null,"English","Int J Prod Res","Article","Final",null,"Scopus","2-s2.0-85131003460"]
["Lee S.; Hong D.; Kim J.; Baek D.; Chang N.","Lee, Seonhoon (58375673200); Hong, Dooyoung (57220180031); Kim, Jaemin (56701365300); Baek, Donkyu (36996444900); Chang, Naehyuck (7202467837)","58375673200; 57220180031; 56701365300; 36996444900; 7202467837","Congestion-Aware Multi-Drone Delivery Routing Framework",2022.0,"IEEE Transactions on Vehicular Technology",71.0,9.0,null,9384.0,9396.0,12.0,6.0,"10.1109/TVT.2022.3179732","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85131764580&doi=10.1109%2fTVT.2022.3179732&partnerID=40&md5=bf37feaea0ddd6035e22bdc48dc08b99","the School of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 34141, South Korea; the Myongji University, Gyeongi, 17058, South Korea; the School of Electronics Engineering, Chungbuk National University, Chungcheongbuk-do, 28644, South Korea","Lee S., the School of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 34141, South Korea; Hong D., the School of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 34141, South Korea; Kim J., the Myongji University, Gyeongi, 17058, South Korea; Baek D., the School of Electronics Engineering, Chungbuk National University, Chungcheongbuk-do, 28644, South Korea; Chang N., the School of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 34141, South Korea","Drones have been attracting the attention of diverse industries thanks to their superior maneuverability. Logistics companies especially keep trying to utilize drones for fast delivery following the growing market size of e-commerce. Accordingly, methods for safely operating multi-drone have been researched, and many researchers have proposed various optimal or near-optimal routing methods. However, such methods have some problems that cause routing failures or huge routing computation time in a drone-dense space due to many collisions. In this paper, we propose a centralized framework that deals with enormous collisions and obtains collision-free paths rapidly. We first build a drone energy consumption model with a data-driven method using flight experiment data of a commercial drone to estimate the drone battery state-of-charge (SoC). Then, we develop a novel routing method that generates collision-free paths by considering both the congestion of the space and the SoC of each drone. The proposed method is inspired by the VLSI circuit routing method that connects all signal nets among thousands of logic components. Through numerous delivery routing simulations, we confirm that the proposed method achieves a maximum of 6 times higher routing success rate with a 10x faster runtime compared with the state-of-the-art optimal method. In addition, we validate that the proposed method is applicable to delivery routing problems with various drone battery capacities. © 2022 IEEE.","drone delivery; drone energy consumption; multi-drone path planning; Unmanned aerial vehicle","Angle of attack; Antennas; Charging (batteries); Computation theory; Drones; Maneuverability; Motion planning; Secondary batteries; Traffic congestion; Collision-free paths; Congestion-aware; Drone delivery; Drone energy consumption; Energy-consumption; Multidrone path planning; Routing frameworks; Routing methods; Routings; Energy utilization",{"$nulls":4},"Development of Artificial Intelligence Technology; Ministry of Science, ICT and Future Planning, MSIP, (2020-0-00440); National Research Foundation of Korea, NRF, (2019R1F1A1060525, 2020R1A6A1A12047945, 2020R1F1A1074843); Institute for Information and Communications Technology Promotion, IITP","This work was supported in part by the Institute of Information & communications Technology Planning & Evaluation (IITP) under a grant funded by the Korean Government (MSIT) (No. 2020-0-00440, by the Development of Artificial Intelligence Technology that Continuously Improves Itself as the Situation Changes in the Real World) and in part by the National Research Foundation of Korea under grants funded by the MSIT (No. 2019R1F1A1060525, No. 2020R1A6A1A12047945, and No. 2020R1F1A1074843).","MATRICE 600 PRO; Amazon Prime Air; UPS Flight Forward; Unmanned Aircraft System Traffic Management; Wang J., Jiang C., Han Z., Ren Y., Maunder R.G., Hanzo L., Taking drones to the next level: Cooperative distributed unmanned-aerial-vehicular networks for small and mini drones, IEEE Veh. 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Saf., pp. 1-6, (2019); Hu Y., Yao Y., Ren Q., Zhou X., 3D multi-UAV cooperative velocity-aware motion planning, Future Gener. Comput. Syst., 102, pp. 762-774, (2020); Hong D., Lee S., Cho Y.H., Baek D., Kim J., Chang N., Least-energy path planning with building accurate power consumption model of rotary unmanned aerial vehicle, IEEE Trans. Veh. Technol., 69, 12, pp. 14803-14817, (2020); Hong D., Lee S., Cho Y.H., Baek D., Kim J., Chang N., Energy-efficient online path planning of multiple drones using reinforcement learning, IEEE Trans. Veh. Technol., 70, 10, pp. 9725-9740, (2021); Stern R., Et al., Multi-agent pathfinding: Definitions, variants, and benchmarks, Proc. 12th Annu. Symp. Combinatorial Search, pp. 151-158, (2019); Yu J., LaValle S., Structure and intractability of optimal multi-robot path planning on graphs, Proc. 27th AAAI Conf. Artif. Intell., pp. 1443-1449, (2013); Silver D., Cooperative pathfinding, Proc. 1st Artif. Intell. Interactive Digit. Entertainment Conf., pp. 117-122, (2005); Sharon G., Stern R., Felner A., Sturtevant N.R., Conflict-based search for optimal multi-agent pathfinding, Artif. Intell., 219, pp. 40-66, (2015); Choudhury S., Solovey K., Kochenderfer M.J., Pavone M., Efficient large-scale multi-drone delivery using transit networks, J. Artif. Intell. Res., 70, pp. 757-788, (2021); Huang H., Savkin A.V., Huang C., Reliable path planning for drone delivery using a stochastic time-dependent public transportation network, IEEE Trans. Intell. Transp. Syst., 22, 8, pp. 4941-4950, (2021); Huang H., Savkin A.V., Huang C., Round trip routing for energy-efficient drone delivery based on a public transportation network, IEEE Trans. Transport. Electrific., 6, 3, pp. 1368-1376, (2020); Barer M., Sharon G., Stern R., Felner A., Suboptimal variants of the conflict-based search algorithm for the multi-agent pathfinding problem, Proc. 7th Annu. Symp. Combinatorial Search, pp. 961-962, (2014); Ho F., Salta A., Geraldes R., Goncalves A., Cavazza M., Prendinger H., Multi-agent path finding for UAV traffic management, Proc. 18th Int. Conf. Auton. Agents MultiAgent Syst., pp. 131-139, (2019); Ma H., Li J., Kumar T.K., Koenig S., Lifelong multi-agent path finding for online pickup and delivery tasks, Proc. 16th Int. Conf. Auton. Agents Multiagent Syst., pp. 837-845, (2017); Li J., Tinka A., Kiesel S., Durham J.W., Kumar T.S., Koenig S., Lifelong multi-agent path finding in large-scale warehouses, Proc. 2th Int. Conf. Auton. Agents Multi-Agent Syst., pp. 1898-1900, (2020); Garey M.R., Johnson D.S., Computers and Intractability; A Guide to the Theory of NP-Completeness, (1990); Liu Z., Sengupta R., An energy-based flight planning system for unmanned traffic management, Proc. Annu. IEEE Int. Syst. Conf., pp. 1-7, (2017); Yacef F., Rizoug N., Bouhali O., Estaca M.H., Optimization of energy consumption for quadrotor UAV, Proc. Int. Micro Air Veh. Conf. Flight Competition, pp. 18-21, (2017); Bezzo N., Mohta K., Nowzari C., Lee I., Kumar V., Pappas G.J., Online planning for energy-efficient and disturbance-aware UAV operations, Proc. IEEE/RSJ Int. Conf. Intell. Robots Syst., pp. 5027-5033, (2016); McMurchie L., Ebeling C., Pathfinder: A negotiation-based performance-driven router for FPGAs, Proc. 3rd Int. ACM Symp. Field-Programmable Gate Arrays, pp. 111-117, (1995); Murray K.E., Et al., VTR 8: High-performance cad and customizable FPGAarchitecturemodelling, ACMTrans.ReconfigurableTechnol.Syst., 13, 2, pp. 1-55, (2020); Leishman G.J., Principles of Helicopter Aerodynamics With CD Extra, (2006)","D. Baek; the School of Electronics Engineering, Chungbuk National University, Chungcheongbuk-do, 28644, South Korea; email: donkyu@cbnu.ac.kr; N. Chang; the School of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 34141, South Korea; email: naehyuck@cad4x.kaist.ac.kr",null,"Institute of Electrical and Electronics Engineers Inc.",{"$nulls":5},189545.0,null,"ITVTA",null,"English","IEEE Trans. Veh. Technol.","Article","Final",null,"Scopus","2-s2.0-85131764580"]
["Kim N.; Montreuil B.; Klibi W.; Zied Babai M.","Kim, Nayeon (57221292951); Montreuil, Benoit (7003796719); Klibi, Walid (15056048500); Zied Babai, M. (23974512700)","57221292951; 7003796719; 15056048500; 23974512700","Network inventory deployment for responsive fulfillment",2023.0,"International Journal of Production Economics",255.0,null,108664.0,null,null,null,4.0,"10.1016/j.ijpe.2022.108664","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85141918172&doi=10.1016%2fj.ijpe.2022.108664&partnerID=40&md5=2df91fe0b84f1412b7400b4a1c2d3bf9","Physical Internet Center, Supply Chain & Logistics Institute, Georgia Institute of Technology, Atlanta, GA, United States; School of Industrial & Systems Engineering, Georgia Institute of Technology, Atlanta, GA, United States; Centre of Excellence for Supply Chain Innovation & Transportation (CESIT), Kedge Business School, Bordeaux, France","Kim N., Physical Internet Center, Supply Chain & Logistics Institute, Georgia Institute of Technology, Atlanta, GA, United States, School of Industrial & Systems Engineering, Georgia Institute of Technology, Atlanta, GA, United States; Montreuil B., Physical Internet Center, Supply Chain & Logistics Institute, Georgia Institute of Technology, Atlanta, GA, United States, School of Industrial & Systems Engineering, Georgia Institute of Technology, Atlanta, GA, United States; Klibi W., Physical Internet Center, Supply Chain & Logistics Institute, Georgia Institute of Technology, Atlanta, GA, United States, Centre of Excellence for Supply Chain Innovation & Transportation (CESIT), Kedge Business School, Bordeaux, France; Zied Babai M., Centre of Excellence for Supply Chain Innovation & Transportation (CESIT), Kedge Business School, Bordeaux, France","Customer expectations on fulfillment responsiveness is growing with prevalent home delivery practices via e-retails or omnichannel operations. Tight responsiveness requirements, such as x-hour delivery, requires physical availability of inventory near demand locations. This raises a need for a broad and dense inventory network and a smart inventory deployment model. Although building such a decentralized network is financially unviable for most companies, the recently emerging Physical Internet can enable affordable access to a decentralized network by transforming the asset-driven logistics to service-driven logistics. Under such context, we build a Newsvendor-based inventory model with partial pooling, induced by responsiveness requirements, followed by a pragmatic heuristic inventory solution, W-solution. Through numerical experiments we investigate the advantage of the decentralized network and W-solution over the centralized network and an allocation-based inventory model, a pre-allocation model. The results demonstrate that decentralization can increase profit significantly by capturing more demand through more responsive fulfillment. That is, extra sales exceed the cost saving from risk-pooling in centralized system. The W-solution saves extra cost by exploiting pooling more smartly than the pre-allocation model, especially under decentralized network. We also show that the W-solution does not always result in less inventory than the pre-allocation model but rather it depends on sales margin unlike the common rule of thumb for inventory pooling. Furthermore, through the case of a drop-ship manufacturer in the US market, we provide empirical evidence of the benefit of network decentralization over the risk pooling when responsive fulfillment is required. © 2022 Elsevier B.V.","Decentralized network; E-commerce; Inventory deployment; Network inventory; Partial pooling; Physical internet; Responsiveness","Inventory control; Allocation model; Decentralisation; Decentralized networks; Inventory deployment; Inventory modeling; Network inventory; Partial pooling; Physical internet; Responsiveness; Risk pooling; Sales",{"$nulls":4},"Claude Bernier; South Shore Furniture","The authors thank South Shore Furniture for a superb collaboration and Claude Bernier, VP IT at South Shore, for his relentless support.","Acimovic J., Graves S.C., Making better fulfillment decisions on the fly in an online retail environment, Manuf. Serv. Oper. 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Sci., 67, 1, pp. 185-200, (2021); Yang Y., Pan S., Ballot E., A model to take advantage of physical internet for vendor inventory management, IFAC-PapersOnLine, 48, 3, pp. 1990-1995, (2015); Yang Y., Pan S., Ballot E., Mitigating supply chain disruptions through interconnected logistics services in the physical internet, Int. J. Prod. Res., 55, 14, pp. 3970-3983, (2017); Yang H., Schrage L., Conditions that cause risk pooling to increase inventory, European J. Oper. Res., 192, 3, pp. 837-851, (2009); Zhang J., Onal S., Das S., The dynamic stocking location problem–dispersing inventory in fulfillment warehouses with explosive storage, Int. J. Prod. Econ., 224, (2020); Zhong Y., Zheng Z., Chou M.C., Teo C.-P., Resource pooling and allocation policies to deliver differentiated service, Manage. Sci., 64, 4, pp. 1555-1573, (2017)","M. Zied Babai; Centre of Excellence for Supply Chain Innovation & Transportation (CESIT), Kedge Business School, Bordeaux, France; email: mohamed-zied.babai@kedgebs.com",null,"Elsevier B.V.",{"$nulls":5},9255273.0,null,"IJPCE",null,"English","Int J Prod Econ","Article","Final",null,"Scopus","2-s2.0-85141918172"]
["McGiverin S.S.","McGiverin, Sean S. (58283610000)",5.828361E10,"Regulating Alcohol Delivery by Third-Party Providers in Iowa",2022.0,"Iowa Law Review",108.0,1.0,null,445.0,467.0,22.0,0.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85159883511&partnerID=40&md5=9d98b24bad37ff6a520b06d896eebf2b","The University of Iowa, College of Law, United States","McGiverin S.S., The University of Iowa, College of Law, United States","Since the repeal of Prohibition in 1933, most states have relied on some form of a three-tier system to regulate the manufacture, distribution, and sale of alcohol. With the rapid changes in technology, e-commerce, and consumer habits today, the use of unlicensed third-party providers (“TPPs”) to solicit and deliver alcohol orders on behalf of licensed retailers threatens to upend alcohol regulation and the three-tier system. This would be undesirable because it might frustrate several goals of alcohol regulation such as protecting public health and safety, ensuring a fair and orderly alcohol market, and holding entities involved in the alcohol industry accountable to the public. Examining Iowa Code section 123.46A, Iowa's third-party alcohol delivery law that was enacted in July 2021, this Note argues that more effective regulation of TPP activity can be achieved by: (1) issuing TPP licenses, (2) requiring licensed retailers to exercise control over every part of the transaction facilitated by TPPs, and (3) amending Iowa's tied-house law to prohibit manufacturers and distributors from acquiring an economic interest in TPPs. © 2022 University of Iowa. All rights reserved.",{"$nulls":8},"Decious Elijah, New Iowa Law Allows Cocktails to Be Brought to Your Door, GAZETTE, (2021); Phelps Becky, New Iowa Law Allows for Expanded Home Delivery of Alcohol, KCRG, (2021); Reynolds Signs Law Allowing Third-Party Services to Deliver Alcohol in Iowa, KCCI, (2021); Ruggless Ron, Pandemic Fuels Widespread Changes in Alcohol Laws, NATION'S REST. NEWS, (2020); Bordner Alexa, Note, How New York Drinks: If and How Third-Party Providers Can Integrate with the Three-Tier System, BROOK. L. REV, 83, (2017); Sumagaysay Levi, The Pandemic Has More than Doubled Food-Delivery Apps' Business. Now What?, MARKET WATCH, (2020); About Us, DRIZLY; Campisi Victoria, Delivery Landscape Changing as DoorDash, Rivals Go All in on Alcohol, FOOD INSTITUTE, (2021); Saunders Evan W., Note, It's 1919 Somewhere: What Tennessee Wine & Spirits Retailers Association v. Thomas Means for the National Hangover of the Twenty-First Amendment, the Dormant Commerce Clause, and Federal Legalization of Intoxicating Substances, BROOK. L. REV, 86, (2020); STATE OF IOWA: ALCOHOLIC BEVERAGES DIV., ALCOHOLIC BEVERAGE CONTROL STUDY, pp. 5-9, (2018); RORABAUGH W. J., PROHIBITION: A CONCISE HISTORY, (2018); Hamm Richard Francis, Origins of the Eighteenth Amendment: The Prohibition Movement in the Federal System, 1880-1920, (1987); Elias Roni A., Three Cheers for Three Tiers: Why the Three-Tier System Maintains Its Legal Validity and Social Benefits After Granholm, DEPAUL BUS. & COM. L.J, 14, (2015); Reese Jessica R., Note, A Post-Granholm Analysis of Iowa's Regulatory Framework for Wine Distribution, IOWA L. REV, 94, 665, pp. 671-673, (2009); James Clark Distilling Co. v. W. Md. Ry. Co, U.S, 242, (1917); Bd. of Equalization v. Young's Mkt. Co, U.S, 299, (1936); Indianapolis Brewing Co. v. Liquor Control Comm'n, U.S, 305, (1939); U.S. CONST. art. I; U.S. CONST. art. I; FELDMAN NOAH R., SULLIVAN KATHLEEN M., CONSTITUTIONAL LAW, pp. 227-228, (2016); Bacchus Imps., Ltd. v. Dias, U.S, 468, (1984); Granholm v. Heald, U.S, 544, (2005); Granholm, U.S, 544; Granholm, U.S, 544; Granholm, U.S, 544; New Energy Co. of Ind. v. Limbach, U.S, 486, (1988); North Dakota v. United States, U.S, 495, (1990); ABD STUDY; ABD STUDY; ABD STUDY; Ruggless Ron, One Year In, COVID-19 Pandemic Continues to Impact Independent Restaurants, REST. HOSP, (2021); Cole Gail, States Revisiting Covid-Inspired Cocktail-to-Go Laws and Taxes, CPA ADVISOR, (2021); Fantozzi Joanna, DoorDash Is Expanding Its Alcohol Delivery Program, NATION'S RESTAURANT NEWS, (2021); Why Alcohol Delivery Will Still Be a Big Opportunity Post-Pandemic, REST. DIVE, (2021); Robson Patrick L., Regulating Third-Party Food Delivery Services During COVID-19, NAT'L L. REV, (2021); Cheng Michelle, The Food Delivery Industry Is Learning It Needs to Keep Restaurants Happy, QUARTZ, (2021); Hildebrandt Eleanor, Businesses See Delayed Start to Home Alcohol Delivery, TIMES-REPUBLICAN, (2021); Iowa Alcoholic Beverages Division, ALCOHOLIC BEVERAGES DIV; ABD STUDY; IOWA CODE, (2022); LEGIS. SERVS. AGENCY, ISSUE REVIEW: IOWA'S CRAFT BEER INDUSTRY, pp. 15-16, (2018); LEGIS. SERVS. AGENCY, pp. 15-16; ABD STUDY, pp. 10-11; Auen v. Alcoholic Beverages Div, N.W.2d, 679, (2004); Akin Katie, Slushies? Flasks? Bars Look to Creative Ideas After To-Go Cocktail Bill Passes, DES MOINES REG, (2020); IOWA CODE, (2022); REGUL. BULL. NO. RB-2021-01, THIRD-PARTY DELIVERY OF ALCOHOLIC BEVERAGES, pp. 1-2, (2021); REGULATORY BULLETIN; Third Party Providers, CAL. DEP'T OF ALCOHOLIC BEVERAGE CONTROL, pp. 2050-2051; Third Party Providers; GRAHAM THOMAS, TEX. ALCOHOLIC BEVERAGE COMM'N, MARKETING PRACTICES ADVISORY - MPA056: WINE SHIPPING AND THIRD PARTY ADVERTISERS/PAYMENT PROCESSING SERVICES, (2013); ADVISORY OPINION ON ONLINE THIRD PARTY ADVERTISERS AND PAYMENT PROCESSING SERVICES, (2014)",null,null,"University of Iowa",{"$nulls":5},210552.0,null,null,null,"English","Iowa Law Rev.","Article","Final",null,"Scopus","2-s2.0-85159883511"]
["Miao M.; Jalees T.; Zaman S.I.; Khan S.; Hanif N.-U.-A.; Javed M.K.","Miao, Miao (56526297900); Jalees, Tariq (57194162427); Zaman, Syed Imran (57202534694); Khan, Sherbaz (57360727500); Hanif, Noor-ul-Ain (57361013900); Javed, Muhammad Kashif (57217773858)","56526297900; 57194162427; 57202534694; 57360727500; 57361013900; 57217773858","The influence of e-customer satisfaction, e-trust and perceived value on consumer's repurchase intention in B2C e-commerce segment",2022.0,"Asia Pacific Journal of Marketing and Logistics",34.0,10.0,null,2184.0,2206.0,22.0,36.0,"10.1108/APJML-03-2021-0221","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85120478626&doi=10.1108%2fAPJML-03-2021-0221&partnerID=40&md5=02336acf5f1fc30d07a7ae10ee455197","Business School, Yango University, Fuzhou, China; Karachi Institute of Economics and Technology, Karachi, Pakistan; Department of Business Administration, Jinnah University for Women, Karachi, Pakistan; School of Economics and Management, Southwest Jiaotong University, Chengdu, China; Sichuan University, Chengdu, China","Miao M., Business School, Yango University, Fuzhou, China; Jalees T., Karachi Institute of Economics and Technology, Karachi, Pakistan; Zaman S.I., Department of Business Administration, Jinnah University for Women, Karachi, Pakistan, School of Economics and Management, Southwest Jiaotong University, Chengdu, China; Khan S., Department of Business Administration, Jinnah University for Women, Karachi, Pakistan; Hanif N.-U.-A., Department of Business Administration, Jinnah University for Women, Karachi, Pakistan; Javed M.K., Sichuan University, Chengdu, China","Purpose: This research study investigates the factors that influence e-customer satisfaction, e-trust, perceived value and consumers repurchase intention in the context of the B2C e-commerce segment. It investigates the mediation effect of e-customer satisfaction, e-trust and perceived value on repurchase intention. It also examines the moderating role of prior online experience. Design/methodology/approach: Based on the adapted questionnaire, pre-recruited enumerators collected the data from five leading business universities of Karachi. They distributed 425 questionnaires and received 415 questionnaires. The study has used Partial Least Square-Structure Equation Modeling (PLS-SEM) technique for data analysis. Findings: We have tested 20 hypotheses, of which our results do not support five, including two direct, two mediating. Our results support all the direct hypotheses except the following two: (1) delivery service affects e-satisfaction (2) customer services quality effect on trust. We did not find support for the following two mediating hypotheses (1) e-satisfaction mediates delivery services and repurchase intention, (2) service quality mediates customers' service quality and repurchase intention. Our results do not support one moderating relationship. Prior online experience moderates e-perceived value and repurchase intention. Research limitations/implications: This research provides valuable information to the online retailers of B2C e-commerce, which can help them make strategies based on their consumers' behavior and encourage them to make repeat purchases from online retailing stores. It allows future researchers to replicate the model in cross-cultural studies in different product categories. Originality/value: We have examined the moderating effect of prior online experience between (e-satisfaction, e-trust and perceived value) on the repurchase intention. © 2021, Emerald Publishing Limited.","Business to consumer; e-Customer satisfaction; e-Trust; Perceived value; PLS-SEM; Repurchase intention",{"$nulls":5},"National Natural Science Foundation of China, NSFC, (72172129); National Office for Philosophy and Social Sciences, NPOPSS, (20BSH103)","This research is supported by the National Natural Science Foundation of China (Grant No. 72172129) and National Social Science Foundation of China (Grant No. 20BSH103). 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Zaman; Department of Business Administration, Jinnah University for Women, Karachi, Pakistan; email: s.imranzaman@gmail.com",null,"Emerald Publishing",{"$nulls":5},1.3555855E7,null,null,null,"English","Asia Pac. J. Mark. Logist.","Article","Final",null,"Scopus","2-s2.0-85120478626"]
["Mashalah H.A.; Hassini E.; Gunasekaran A.; Bhatt (Mishra) D.","Mashalah, Heider Al (57828104400); Hassini, Elkafi (23394835700); Gunasekaran, Angappa (56238759300); Bhatt (Mishra), Deepa (57828881700)","57828104400; 23394835700; 56238759300; 57828881700","The impact of digital transformation on supply chains through e-commerce: Literature review and a conceptual framework",2022.0,"Transportation Research Part E: Logistics and Transportation Review",165.0,null,102837.0,null,null,null,28.0,"10.1016/j.tre.2022.102837","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135292472&doi=10.1016%2fj.tre.2022.102837&partnerID=40&md5=648fd1278c3ed131f5be2c1c36b8c4b9","School of Computational Science & Engineering, McMaster University, Canada; DeGroote School of Business, McMaster University, Canada; School of Business Administration, Penn State Harrisburg, 777 West Harrisburg Pike, Middletown, 17057-4846, PA, United States; Montpellier Business School, 2300 Avenue des Moulins, Montpellier, 34185, France","Mashalah H.A., School of Computational Science & Engineering, McMaster University, Canada; Hassini E., DeGroote School of Business, McMaster University, Canada; Gunasekaran A., School of Business Administration, Penn State Harrisburg, 777 West Harrisburg Pike, Middletown, 17057-4846, PA, United States; Bhatt (Mishra) D., Montpellier Business School, 2300 Avenue des Moulins, Montpellier, 34185, France","One of the profound impacts of digitalization on supply chains is manifested through e-commerce. The latter has significantly grown during the last two decades, with further amplifications during the COVID-19 pandemic. This has created operational and policy making challenges for firms when deciding about how best to manage the resulting growth in e-commerce. While the impact of e-commerce on supply chains has been widely recognized in the literature, there was no effort to systematically review the literature, conceptualize some of the challenges and propose future research directions. This paper fills this gap by reviewing 153 publications from 1999 to 2019. We classify the reviewed literature based on which supply chain drivers were investigated, as well as, the employed research methodology. In addition, we conduct network and content analysis to uncover the main research themes and potential research directions namely, developing analytical centred; modelling based ecosystem for environment; leveraging data mining to enhance sustainability; balance between growth and sustainability; consumer demand and uncertainty; coordination in e-commerce logistics; last mile alternatives and cost management of innovative technique implementations. Furthermore, based on our literature review, we propose a conceptual framework where we interlink supply chain stages with a firm's business strategy, digital transformation strategy and performance. © 2022","Digital transformation; e-commerce; Network analysis; Supply chains; Systematic literature review","Data mining; Electronic commerce; Sustainable development; Uncertainty analysis; Conceptual frameworks; Content analysis; Digital transformation; E- commerces; Future research directions; Literature reviews; Policy making; Potential researches; Research methodologies; Systematic literature review; conceptual framework; corporate strategy; electronic commerce; industrial performance; innovation; literature review; network analysis; supply chain management; transportation economics; uncertainty analysis; Supply chains",{"$nulls":6},{"$cut":{"chars":32620,"head":"Aboolian R., Sun Y., Koehler G.J., A location–allocation problem for a web services provider in a competitive market, European J. Oper. Res., 194, 1, pp. 64-77, (2009); Adebanjo D., Laosirihongthong T., Adoption of web-based order-processing systems: experiences from tier-1 suppliers in the automotive supply chain, Prod. Plan. Control, 25, 15, pp. 1287-1301, (2014); Agatz N.A., Fleischmann M., Van Nunen J.A., E-fulfillment and multi-channel distribution–A review, European J. Oper. Res., 187, 2, pp. 339-356, (2008); Ageron B., Gunasekaran A., Spalanzani A., Sustainable supply management: An empirical study, Int. J. Prod. Econ., 140, 1, pp. 168-182, (2012); Akter S., Wamba S.F., Big data analytics in E-commerce: a systematic review and agenda for future research, Electron. Mark., 26, 2, pp. 173-194, (2016); Albanese J., Manning B., Revive: How To Transform Traditional Businesses Into Digital Leaders, (2015); Ali F., US ecommerce grows 44.0% in 2020, (2021); Allen J., Piecyk M., Piotrowska M., McLeod F., Cherrett T., Ghali K., Nguyen T., Bektas T., Bates O., Friday A., Et al., Understanding the impact of e-commerce on last-mile light goods vehicle activity in urban areas: the case of london, Transp. Res. D, 61, pp. 325-338, (2018); Ambrosino D., Scutella M.G., Distribution network design: new problems and related models, European J. Oper. Res., 165, 3, pp. 610-624, (2005); Angeles R., Nath R., Business-to-business e-procurement: success factors and challenges to implementation, Supply Chain Manage. Int. J., 12, 2, pp. 104-115, (2007); Aoyama Y., Ratick S., Schwarz G., Modeling the impact of business-to-business electronic commerce on the organization of the logistics industry, Geogr. Anal., 37, 1, pp. 46-68, (2005); Arnold F., Cardenas I., Sorensen K., Dewulf W., Simulation of B2C e-commerce distribution in antwerp using cargo bikes and delivery points, Eur. Transp. Res. Rev., 10, 1, (2018); Asadi S., Halina M.D., Organizational research in the field of green IT: A systematic literature review from 2007 to 2016, Telemat. Inform., 34, 7, pp. 1191-1249, (2017); Baglieri E., Secchi R., Croom S., Exploring the impact of a supplier portal on the buyer-supplier relationship. The case of Ferrari auto, Ind. Mark. Manage., 36, 7, pp. 1010-1017, (2007); Bahrami B., Aghezzaf E.-H., Limere V., Enhancing the order picking process through a new storage assignment strategy in forward-reserve area, Int. J. Prod. Res., 57, 21, pp. 6593-6614, (2019); Balakrishnan A., Sundaresan S., Zhang B., Browse-and-switch: Retail-online competition under value uncertainty, Prod. Oper. Manage., 23, 7, pp. 1129-1145, (2014); Barnett G.A., Encyclopedia of Social Networks, (2011); Barone V., Crocco F., Mongelli D.W., Models of choice between shopping and e-shopping, Applied Mechanics and Materials, Vol. 442, pp. 607-616, (2014); Barua A., Kriebel C., Mukhopadhyay T., Information technologies and business value: An analytic and empirical investigation, Inf. Syst. Res., 6, 1, pp. 3-23, (1995); Basak S., Basu P., Avittathur B., Sikdar S., A game theoretic analysis of multichannel retail in the context of “showrooming”, Decis. Support Syst., 103, pp. 34-45, (2017); Basbas S., The impact of e-commerce on transport, Internet Society II: Advances in Education, Commerce & Governance, WIT Transactions on Information and Communication Technologies, 36, pp. 353-361, (2006); Bask A., Lipponen M., Tinnila M., E-commerce logistics: a literature research review and topics for future research, Int. J. E-Serv. Mob. Appl. (IJESMA), 4, 3, pp. 1-22, (2012); Batarfi R., Jaber M.Y., Aijazzar S.M., A profit maximization for a reverse logistics dual-channel supply chain with a return policy, Comput. Ind. Eng., 106, pp. 58-82, (2017); Bates O., Friday A., Intangible commodities with free delivery: finding the limit in digitally mediated e-commerce and workforce injustice, Proceedings of the 2018 Workshop on Computing Within Limits (LIMITS ‘18), pp. 1-8, (2018); Bates O., Friday A., Allen J., Cherrett T., Mcleod F., Bektas T., Nguyen T., Piecyk M., Piotrowska M., Wise S., Davies N., "}},"A. Gunasekaran; School of Business Administration, Middletown, Penn State Harrisburg, 777 West Harrisburg Pike, 17057-4846, United States; email: aqg6076@psu.edu",null,"Elsevier Ltd",{"$nulls":5},1.3665545E7,null,null,null,"English","Transp. Res. Part E Logist. Transp. Rev.","Article","Final",null,"Scopus","2-s2.0-85135292472"]
["Mainardes E.W.; Coutinho A.R.S.; Alves H.M.B.","Mainardes, Emerson Wagner (35764807800); Coutinho, Ananda Raquel Silva (57931771700); Alves, Helena Maria Batista (35208145700)","35764807800; 57931771700; 35208145700","The influence of the ethics of E-retailers on online customer experience and customer satisfaction",2023.0,"Journal of Retailing and Consumer Services",70.0,null,103171.0,null,null,null,6.0,"10.1016/j.jretconser.2022.103171","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85140082937&doi=10.1016%2fj.jretconser.2022.103171&partnerID=40&md5=5bd24deca5ea9b485242d7f8b897a890","FUCAPE Business School, Av. Fernando Ferrari, 1358, Boa Vista, Zip code: 29.075-505, ES, Vitória, Brazil; FUCAPE Business School - Maranhão, Av. dos Holandeses, Quadra 08, n. 01, 2° Andar, Ed. Biadene, Ponta do Farol, Zip code: 65077-635, MA, São Luís, Brazil; University of Beira Interior, Estr. do Sineiro 56, Zip code: 6200-209, Covilhã, Portugal","Mainardes E.W., FUCAPE Business School, Av. Fernando Ferrari, 1358, Boa Vista, Zip code: 29.075-505, ES, Vitória, Brazil; Coutinho A.R.S., FUCAPE Business School - Maranhão, Av. dos Holandeses, Quadra 08, n. 01, 2° Andar, Ed. Biadene, Ponta do Farol, Zip code: 65077-635, MA, São Luís, Brazil; Alves H.M.B., University of Beira Interior, Estr. do Sineiro 56, Zip code: 6200-209, Covilhã, Portugal","The COVID-19 pandemic and the lockdown pushed people to buy more online. With the increase in online shopping, there was also an increase in ethical issues with electronic retailers resulting from problems with products, misleading price practices, lack of customers’ personal and financial data protection, non-delivery of goods, and misleading advertising. This study aimed to determine whether consumers’ perceptions of e-retailers’ ethics influence online customer experience and satisfaction when purchasing products and services. A research model was developed based on the literature on ethics in e-commerce. To fulfill the objective, a research model on consumer perceptions of ethics in online retailing was tested based on answers of 501 Brazilian online shoppers. Data were gathered through an online questionnaire and analyzed using structural equation modeling with an estimation of minimum least squares. The results indicated significant relations between the e-retailer's ethics, the online experience, and customer satisfaction with the mediation of ethical beliefs, suggesting that the e-retailer's ethics can potentially stimulate a good online consumer experience and satisfaction when purchasing on the internet and may contribute to the relationship between the consumer and the e-retailer. Furthermore, ethical beliefs can mediate these relations, collaborating with the effect of e-retailers’ ethics on the consumer's experience and satisfaction. These results represent an advance in the study of new ethical dimensions in electronic retail, which currently are reduced to security and privacy issues. In practice, this study resulted in new knowledge about ethical practices that can guide electronic retailers in the adoption of new customer prospecting strategies. It also highlights the importance of improving regulations that prevent certain behaviors from happening. © 2022 Elsevier Ltd","Customer satisfaction; e-commerce; Ethical beliefs; Online experience; Retailer ethics","consumption behavior; electronic commerce; ethics; guideline; information and communication technology; Internet; least squares method; perception; retailing",{"$nulls":4},"FAPES/Brazil, (228/2019, 599/2018, 84513772, 85395650); Fundação para a Ciência e a Tecnologia, FCT, (UID/GES/04630/2020); Conselho Nacional de Desenvolvimento Científico e Tecnológico, CNPq, (307202/2021-6); Instituto FUCAPE de Tecnologias Sociais, IFTS, (2021–2024)","This research was supported by Brazilian National Council for Scientific and Technological Development (CNPq/Brazil) , project 307202/2021-6 , by Foundation for Research Support of Espírito Santo (FAPES/Brazil) , projects 84513772 (599/2018) and 85395650 (228/2019), by Portuguese Science Foundation (FCT/Portugal) through NECE (Núcleo de Estudos em Ciências Empresariais) , project UID/GES/04630/2020, and by IFTS (Instituto Fucape de Tecnologias Sociais) , project 2021–2024. 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Res., 57, 4, pp. 597-622, (2019); Witek L., Kuzniar W., Green purchase behavior: the effectiveness of sociodemographic variables for explaining green purchases in emerging market, Sustainability, 13, 1, (2021); Yang Z., Ngo Q.V., Nguyen C.X.T., Ethics of retailers and consumer behavior in e-commerce: context of developing country with roles of trust and commitment, Int. J. Asian Bus. Inf. Manag., 11, 1, pp. 107-126, (2020); Yang Z., Ngo Q.V., Chen Y., Nguyen C.X.T., Hoang H.T., Does ethics perception foster consumer repurchase intention? Role of trust, perceived uncertainty, and shopping habit, Sage Open, 9, 2, (2019); Zerbini C., Vergura D.T., Latusi S., A new model to predict consumers' willingness to buy fair-trade products, Food Res. Int., 122, pp. 167-173, (2019); Zollo L., The consumers' emotional dog learns to persuade its rational tail: toward a social intuitionist framework of ethical consumption, J. Bus. Ethics, 168, 2, pp. 295-313, (2021)","E.W. Mainardes; FUCAPE Business School, Vitória, Av. Fernando Ferrari, 1358, Boa Vista, Zip code: 29.075-505, ES, Brazil; email: emerson@fucape.br",null,"Elsevier Ltd",{"$nulls":5},9696989.0,null,null,null,"English","J. Retail. Consum. Serv.","Article","Final",null,"Scopus","2-s2.0-85140082937"]
["Qin H.; Simchi-Levi D.; Ferer R.; Mays J.; Merriam K.; Forrester M.; Hamrick A.","Qin, Hanzhang (57225997443); Simchi-Levi, David (7004509983); Ferer, Ryan (57904730100); Mays, Jonathan (57904535800); Merriam, Ken (57904535900); Forrester, Megan (57903706900); Hamrick, Alex (58241735500)","57225997443; 7004509983; 57904730100; 57904535800; 57904535900; 57903706900; 58241735500","Trading safety stock for service response time in inventory positioning",2022.0,"Production and Operations Management",31.0,12.0,null,4462.0,4474.0,12.0,2.0,"10.1111/poms.13869","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85138694716&doi=10.1111%2fpoms.13869&partnerID=40&md5=9076aadc7e928b183e6acd828e822b01","Center for Computational Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA, United States; Institute for Data, Systems, and Society, Department of Civil and Environmental Engineering, and Operations Research Center, Massachusetts Institute of Technology, Cambridge, MA, United States; Kurt Salmon, Part of Accenture Strategy, Atlanta, GA, United States; Supply Chain Analytics, The Home Depot, Atlanta, GA, United States","Qin H., Center for Computational Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA, United States; Simchi-Levi D., Institute for Data, Systems, and Society, Department of Civil and Environmental Engineering, and Operations Research Center, Massachusetts Institute of Technology, Cambridge, MA, United States; Ferer R., Kurt Salmon, Part of Accenture Strategy, Atlanta, GA, United States; Mays J., Kurt Salmon, Part of Accenture Strategy, Atlanta, GA, United States; Merriam K., Kurt Salmon, Part of Accenture Strategy, Atlanta, GA, United States; Forrester M., Supply Chain Analytics, The Home Depot, Atlanta, GA, United States; Hamrick A., Supply Chain Analytics, The Home Depot, Atlanta, GA, United States","We study an inventory placement optimization problem where demand is sensitive to service response time, under the online retailing setting. The main challenge is to achieve the optimal trade-off between revenue benefits from shorter delivery time and the increase in inventory cost associated with placing inventory closer to market demand. To predict the effects of modified demand under service response time variations, we introduce a demand prediction and elasticity model to quantify the sensitivity in demand for particular product categories. Of course, shortening response time by positioning products close to market demand may increase inventory costs. Hence, the team developed a novel data-driven two-stage stochastic programming approach complementing the demand prediction and elasticity model, which optimally trades safety stock with service response time and hence revenue increase. We then illustrate the impact of our approach through data provided by an e-commerce retailer in North America. Our approach offers supply chain managers a general-purpose decision support tool that optimizes the inventory network to generate recommended stocking levels for stores, distribution centers, and warehouses on a daily basis. © 2022 Production and Operations Management Society.","online retailing; risk pooling; sales forecast; service quality; supply chain network",{"$nulls":5},"MIT Alliance in Business Analytics; MIT Alliance in Business Analytics","Funding text 1: This research was supported by Accenture through the MIT Alliance in Business Analytics. ; Funding text 2: This research was supported by Accenture through the MIT Alliance in Business Analytics.","Alptekinoglu A., Banerjee A., Paul A., Jain N., Inventory pooling to deliver differentiated service, Manufacturing & Service Operations Management, 15, 1, pp. 33-44, (2013); Aouad A., Elmachtoub A., Ferreira K., McNellis R., Market segmentation trees, (2022); Atamturk A., Berenguer G., Shen Z.-J., A conic integer programming approach to stochastic joint location-inventory problems, Operations Research, 60, 2, pp. 366-381, (2012); Barlow R.E., Brunk H.D., The isotonic regression problem and its dual, Journal of the American Statistical Association, 67, 337, pp. 140-147, (1972); Bell D.R., Gallino S., Moreno A., Offline showrooms in omnichannel retail: Demand and operational benefits, Management Science, 64, 4, pp. 1629-1651, (2018); Benjaafar S., Cooper W.L., Kim J.-S., On the benefits of pooling in production-inventory systems, Management Science, 51, 4, pp. 548-565, (2005); Bertsimas D., Dunn J., Mundru N., Optimal prescriptive trees, INFORMS Journal on Optimization, 1, 2, pp. 164-183, (2019); Bimpikis K., Markakis M.G., Inventory pooling under heavy-tailed demand, Management Science, 62, 6, pp. 1800-1813, (2016); Chen N., Gallego G., Tang Z., The use of binary choice forests to model and estimate discrete choices, (2022); Corbett C.J., Rajaram K., A generalization of the inventory pooling effect to nonnormal dependent demand, Manufacturing & Service Operations Management, 8, 4, pp. 351-358, (2006); Cui R., Li M., Li Q., Value of high-quality logistics: Evidence from a clash between SF Express and Alibaba, Management Science, 66, 9, pp. 3879-3902, (2020); Eppen G.D., Note–effects of centralization on expected costs in a multi-location newsboy problem, Management Science, 25, 5, pp. 498-501, (1979); Ferreira K.J., Lee B.H.A., Simchi-Levi D., Analytics for an online retailer: Demand forecasting and price optimization, Manufacturing & Service Operations Management, 18, 1, pp. 69-88, (2016); Fisher M.L., Gallino S., Xu J.J., The value of rapid delivery in omnichannel retailing, Journal of Marketing Research, 56, 5, pp. 732-748, (2019); Gao F., Su X., Omnichannel service operations with online and offline self-order technologies, Management Science, 64, 8, pp. 3595-3608, (2018); Govindarajan A., Sinha A., Uichanco J., Distribution-free inventory risk pooling in a multilocation newsvendor, Management Science, 67, 4, pp. 2272-2291, (2021); Lim M.K., Mak H.-Y., Shen Z.J.M., Agility and proximity considerations in supply chain design, Management Science, 63, 4, pp. 1026-1041, (2017); Mak H.-Y., Shen Z.J.M., Integrated modeling for location analysis, Foundations and Trends® in Technology, Information and Operations Management, 9, 1-2, pp. 1-152, (2016); Nievergelt Y., The concept of elasticity in economics, SIAM Review, 25, 2, pp. 261-265, (1983); Shapiro A., Monte carlo simulation approach to stochastic programming Proceedings of the 2001 winter simulation conference (cat. no. 01CH37304), 1, pp. 428-431, (2001); Shen Z.J.M., Coullard C., Daskin M.S., A joint location-inventory model, Transportation Science, 37, 1, pp. 40-55, (2003); Shu J., Teo C.-P., Shen Z.J.M., Stochastic transportation-inventory network design problem, Operations Research, 53, 1, pp. 48-60, (2005); Simchi-Levi D., Sun R., Wu M.X., Zhu R., Calibrating sales forecast in a pandemic using competitive online non-parametric regression, (2022); Global e-commerce jumps to $26.7 trillion, fuelled by covid-19, (2021); Yang C., Hu Z., Zhou S.X., Multilocation newsvendor problem: Centralization and inventory pooling, Management Science, 67, 1, pp. 185-200, (2021)","D. Simchi-Levi; Institute for Data, Systems, and Society, Department of Civil and Environmental Engineering, and Operations Research Center, Massachusetts Institute of Technology, Cambridge, 02139, United States; email: dslevi@mit.edu",null,"John Wiley and Sons Inc",{"$nulls":5},1.0591478E7,null,null,null,"English","Prod. Oper. Manage.","Article","Final",null,"Scopus","2-s2.0-85138694716"]
["Weiss C.","Weiss, Catharine (56489628200)",5.64896282E10,"Fashion retailing in the metaverse",2022.0,"Fashion, Style and Popular Culture",9.0,4.0,null,523.0,538.0,15.0,4.0,"10.1386/fspc_00159_1","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85139471891&doi=10.1386%2ffspc_00159_1&partnerID=40&md5=71b2e1106086292a3eb428903d9870a1","Lasell University, 1844 Commonwealth Avenue, Newton, 02466, MA, United States","Weiss C., Lasell University, 1844 Commonwealth Avenue, Newton, 02466, MA, United States","As fashion and retail technologies have become more sophisticated, consumers are vastly connected to the multiverse, both through the cloud and the integration of physical and digital spaces called phygital. This type of omnichannel commerce has become a requirement for brands to stay relevant. Developing parallel to the world of omnichannel has been digital gaming. Imagine these two worlds converged into one concept. Enter the metaverse. The idea of the metaverse or a virtual alternative reality is not new. With various iterations in pop culture, the concept of escaping into another dimension, whether dystopian or utopian, is part of the human psyche. Fast forward to a virtual post-pandemic society, the concept of the metaverse and the community it develops is timely. The metaverse allows the consumer to dive into a far more stimulating and immersive experience that have fashion brands collectively strategizing their deliveries. This article will conduct a discourse analysis on the metaverse and its gaming roots, how fashion and retail hope to build community and compelling applications of brand deliveries through these digital worlds. The article will review the adoption challenges that may arise with the consumer, applications that are kink free, privacy protection, regulation, payment systems, adoption of entrance devices and brand deliveries using NFTs or non-fungible tokens. © 2022 Intellect Ltd.","digital branding; digital consumer; digital fashion; e-commerce; fashion and retail metaverse; future of retail; NFT",{"$nulls":7},"Abloh Virgil, Virgial Abloh Instagram, Instagram, (2021); Anyanwu Obi, WWD: Nike unveils “Nikeland” experience in Roblox, Currently from AT&T | Yahoo, (2021); Facebook renames itself Meta to emphasize its “metaverse” vision, AP News, (2021); Becoming with: The new immersive Topshop virtual reality campaign, (2021); Tokens.com’s subsidiary closes the largest metaverse land acquisition in history, Businesswire, (2021); The metaverse mall and why it matters, CB Insights, (2021); Clark Peter Allen, What is the metaverse? Here’s why it matters, Time, (2021); Duffield Benjamin, 2149: The Aftermath, (2021); The Sims 4, (2021); Hackl Cathy, The metaverse is coming and it’s a very big deal, Forbes, (2020); Holbrook Sara, The metaverse reimagines retail, The Robin Report, (2021); Hopp Deven, Sephora facts, Byrdie, (2021); Isaac Mike, To build the metaverse, Meta first wants to build stores, New York Times, (2021); Jaekel Brielle, Sephora tries on augmented reality for update, Retail Dive, (2021); Lee Lik-Hang, Braud Tristan, Zhou Pengyuan, Lin Wang, Xu Dianlei, Lin Zijun, Kumar Abhishek, Bermejo Carlos, Hui Pan, All one needs to know about metaverse: A complete survey on technological singularity, virtual ecosystem, and research agenda, Journal of Latex Class Files, 14, 8, pp. 1-47, (2021); Second Life, (2021); Dior creates its own virtual reality headset, LVMH, (2021); Malik Daniyal, So far over 5 million headsets have been sold, Digital Information World, (2021); McDowell Maghan, Is it time to hire a chief metaverse officer?, Vogue Business, (2021); Mozee Carla, Facebook’s metaverse project will help drive as much as 22% upside in the stock, Bank of America says, MSN, (2021); Newton Casey, Mark in the Metaverse from The Verge, (2021); Pokémon Go, (2021); O'Brien Matt, Chan Kelvin, Explainer: What is the metaverse and how will it work, AP News, (2021); Ondrejka Cory, Escaping the gilded cage: User created content and building the metaverse, New York Law School Review, 49, pp. 81-101, (2004); Papagiannidis Savvas, Bourlakis Michael, Staging the new retail drama: At a metaverse near you!, The Journal of Virtual Worlds Research, 2, 5, pp. 3-17, (2010); Redding Neil, What the metaverse means for retail, Medium, (2021); Topshop use virtual reality headsets for catwalk, Retail Innovation, (2020); Vans launch a metaverse experience in the popular Roblox game, Retail Innovation, (2021); Roblox, (2021); Rowgow Maury, How will companies market virtual marketplace, CISION PRWeb, (2021); Saunders Neil, Is retail ready to enter the metaverse?, RetailWire, (2021); Stein Scott, Facebook goes Meta: What is the metaverse and why is Big Tech obsessed?, CNET, (2021); Stephenson Neal, Snow Crash, Neal Stephenson, (2021); Spielberg Steven, Ready Player One, (2018); Trumball Douglas, Brainstorm, (1983); Wachowskis The, The Matrix, (1999); Welcome to the Metaverse, (2021); The future of reality, Wired, (2021); Wunderman Thompson, Into the Metaverse, (2021); Zoobylife, (2019)","C. Weiss; Lasell University, Newton, 1844 Commonwealth Avenue, 02466, United States; email: cweiss@lasell.edu",null,"Intellect Ltd.",{"$nulls":5},2.0500726E7,null,null,null,"English","Fash.Styl Pop. Cult.","Article","Final",null,"Scopus","2-s2.0-85139471891"]
["Bagwari A.; Sinha A.; Singh N.K.; Garg N.; Kanti J.","Bagwari, Ashish (48761086600); Sinha, Anurag (57561268800); Singh, N.K. (57201815386); Garg, Namit (57892951600); Kanti, Jyotshana (56780225300)","48761086600; 57561268800; 57201815386; 57892951600; 56780225300","CBIR-DSS: Business Decision Oriented Content-Based Recommendation Model for E-Commerce",2022.0,"Information (Switzerland)",13.0,10.0,479.0,null,null,null,5.0,"10.3390/info13100479","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85140618872&doi=10.3390%2finfo13100479&partnerID=40&md5=6c9c110cdc9312a84708c388791385a9","Department of Electronics and Communication Engineering, WIT, Uttarakhand Technical University, Dehradun, 248007, India; Department of Computer Science, IGNOU, New Delhi, 110068, India; Department of CSE, Birla Institute of Technology, Ranchi, Mesra, 834001, India; Department of Maths and Computing, Indian Institute of Technology, Kanpur, 208016, India; Advanced and Innovative Research Laboratory, Dehradun, 248001, India","Bagwari A., Department of Electronics and Communication Engineering, WIT, Uttarakhand Technical University, Dehradun, 248007, India; Sinha A., Department of Computer Science, IGNOU, New Delhi, 110068, India; Singh N.K., Department of CSE, Birla Institute of Technology, Ranchi, Mesra, 834001, India; Garg N., Department of Maths and Computing, Indian Institute of Technology, Kanpur, 208016, India; Kanti J., Advanced and Innovative Research Laboratory, Dehradun, 248001, India","Business-based decision support systems have been proposed for a few decades in the e-commerce and textile industries. However, these Decision Support Systems (DSS) have not been so productive in terms of business decision delivery. In our proposed model, we introduce a content-based image retrieval model based on a DSS and recommendations system for the textile industry, either offline or online. We used the Fashion MNIST dataset developed by Zalando to train our deep learning model. Our proposed hybrid model can demonstrate how a DSS can be integrated with a system that can separate customers based on their personal characteristics in order to tailor recommendations of products using behavioral analytics, which is trained based on MBTI personality data and Deap EEG data containing numerous pre-trained EEG brain waves. With this hybrid, a DSS can also show product usage analytics. Our proposed model has achieved the maximum accuracy compared to other proposed state-of-the-art models due to its qualitative analysis. In the first section of our analysis, we used a deep learning algorithm to train our CBIR model based on different classifiers such as VGG-net, Inception-Net, and U-net which have achieved an accuracy of 98.2% with a 2% of minimized error rate. The result was validated using different performance metrics such as F-score, F-weight, Precision, and Recall. The second part of our model has been tested on different machine learning algorithms with an accuracy rate of 89.9%. Thus, the entire model has been trained, validated, and tested separately to gain maximum efficiency. Our proposal for a DSS system, which integrates several subsystems with distinct functional sets and several model subsystems, is what makes this study special. Customer preference is one of the major problems facing merchants in the textile industry. Additionally, it can be extremely difficult for retailers to predict customer interests and preferences to create products that fulfill those needs. The three innovations presented in this work are a conceptual model for personality characterization, utilizing an amalgamation of an ECG classification model, a suggestion for a textile image retrieval model using Denoising Auto-Encoder, and a language model based on the MBTI for customer rating. Additionally, we have proposed a section showing how blockchain integration in data pre-processing can enhance its security and AI-based software quality assurance in a multi-model system. © 2022 by the authors.","big data; business; content-based image retrieval; image processing; MBTI factor; natural language processing; recommendation system; textile","Big data; Data handling; Decision support systems; Deep learning; Electronic commerce; Learning algorithms; Learning systems; Metals; Natural language processing systems; Quality assurance; Sales; Search engines; Software testing; Textile industry; Textiles; Business decisions; Content-Based Image Retrieval; Contents-based image retrievals; Images processing; Language processing; MBTI factor; Model-based OPC; Natural language processing; Natural languages; Retrieval models; Recommender systems",{"$nulls":6},"Ahmad H., Asghar M.U., Asghar M.Z., Khan A., Mosavi A.H., A Hybrid Deep Learning Technique for Personality Trait Classification from Text, IEEE Access, 9, pp. 146214-146232, (2021); Ali I., Lashari H.N., Hassan S.M., Maitlo A., Qureshi B.H., Image Denoising with Color Scheme by Using Autoencoders, Int. J. Comput. Sci. Netw. Secur, 18, (2018); Anju J., Shreelekshmi R., FSeCBIR: A Faster Secure Content-Based Image Retrieval for Cloud, Softw. Impacts, 11, (2022); Babenko A., Slesarev A., Chigorin A., Lempitsky V., Neural Codes for Image Retrieval, arXiv, (2014); Chen Y., Wang J.Z., Krovetz R., An unsupervised learning approach to content-based image retrieval, Proceedings of the Seventh International Symposium on Signal Processing and Its Applications, 2003, 1, pp. 197-200; Christian H., Suhartono D., Chowanda A., Zamli K.Z., Text based personality prediction from multiple social media data sources using pre-trained language model and model averaging, J. Big Data, 8, (2021); Dagnew T.M., Castellani U., Advanced Content Based Image Retrieval for Fashion, Image Analysis and Processing—ICIAP, 9279, pp. 705-715, (2015); Deshmane M., Madhe S., ECG Based Biometric Human Identification Using Convolutional Neural Network in Smart Health Applications, Proceedings of the 2018 Fourth International Conference on Computing Communication Control and Automation (ICCUBEA), pp. 1-6; Dewan H., Thepade S.D., Image Retrieval Using Low Level and Local Features Contents: A Comprehensive Review, Appl. Comput. Intell. Soft Comput, 2020, (2020); Dharani T., Aroquiaraj I.L., A survey on content based image retrieval, Proceedings of the 2013 International Conference on Pattern Recognition, Informatics and Mobile Engineering, pp. 485-490; Di Crosta A., Ceccato I., Marchetti D., La Malva P., Maiella R., Cannito L., Cipi M., Mammarella N., Palumbo R., Verrocchio M.C., Et al., Psychological factors and consumer behavior during the COVID-19 pandemic, PLoS ONE, 16, (2021); Dorneles S.O., Francisco R., Barbosa D.N.F., Barbosa J.L.V., Context Awareness in Recognition of Affective States: A Systematic Mapping of the Literature, Int. J. Hum.-Comput. Interact, 212, pp. 1-19, (2022); Dos Santos V., Paraboni I., Myers-Briggs personality classification from social media text using pre-trained language models, J. Univers. Comput. Sci, 28, pp. 378-395, (2022); Feng H., Golshan H.M., Mahoor M.H., A wavelet-based approach to emotion classification using EDA signals, Expert Syst. Appl, 112, pp. 77-86, (2018); Imani M., Montazer G.A., A survey of emotion recognition methods with emphasis on E-Learning environments, J. Netw. Comput. Appl, 147, (2019); Laaksonen J., Koskela M., Laakso S., Oja E., PicSOM–content-based image retrieval with self-organizing maps, Pattern Recognit. Lett, 21, pp. 1199-1207, (2000); Li M., Jullien S., Ariannezhad M., de Rijke M., A Next Basket Recommendation Reality Check, arXiv, (2022); Li T.-M., Chao H.-C., Zhang J., Emotion classification based on brain wave: A survey, Hum. Cent. Comput. Inf. Sci, 9, (2019); Liu C., Wang S., Jia G., Exploring E-Commerce Big Data and Customer-Perceived Value: An Empirical Study on Chinese Online Customers, Sustainability, 12, (2020); Marques O., Mayron L.M., Borba G.B., Gamba H.R., An Attention-Driven Model for Grouping Similar Images with Image Retrieval Applications, EURASIP J. Adv. Signal Process, 2007, (2006); Wong K.-M., Cheung K.-W., Po L.-M., MIRROR: An Interactive Content Based Image Retrieval System, Proceedings of the 2005 IEEE International Symposium on Circuits and Systems, pp. 1541-1544; Zong K., Yuan Y., Montenegro-Marin C.E., Kadry S.N., Or-Based Intelligent Decision Support System for E-Commerce, J. Theor. Appl. Electron. Commer. Res, 16, pp. 1150-1164, (2021); Roy B., Banerjee S., Pal S., e\\Effective web based on Social Media Data, Ph.D. Thesis, (2021); Liu Y., Zhang D., Lu G., Ma W.-Y., A survey of content-based image retrieval with high-level semantics, Pattern Recognit, 40, pp. 262-282, (2007); Lehmann T.M., Guld M.O., Deselaers T., Keysers D., Schubert H., Spitzer K., Ney H., Wein B.B., Automatic categorization of medical images for content-based retrieval and data mining, Comput. Med. Imaging Graph, 29, pp. 143-155, (2005); Miranda-Correa J.A., Abadi M.K., Sebe N., Patras I., AMIGOS: A Dataset for Affect, Personality and Mood Research on Individuals and Groups, arXiv, (2017); Nandi A., Xhafa F., Subirats L., Fort S., Real-Time Emotion Classification Using EEG Data Stream in E-Learning Contexts, Sensors, 21, (2021); Phan T.-D.-T., Kim S.-H., Yang H.-J., Lee G.-S., EEG-Based Emotion Recognition by Convolutional Neural Network with Multi-Scale Kernels, Sensors, 21, (2021); Sharma S., Dhole A., Content Based Image Retrieval Based on Shape Feature using Accurate Legendre Moments and Support Vector Machines, Int. J. Sci. Eng. Comput. Technol, 3, (2013); Stankov L., Low Correlations between Intelligence and Big Five Personality Traits: Need to Broaden the Domain of Personality, J. Intell, 6, (2018); Trojacanec K., Dimitrovski I., Loskovska S., Content based image retrieval in medical applications: An improvement of the two-level architecture, Proceedings of the IEEE EUROCON 2009, pp. 118-121; Velmurugan M.S., Narayanasamy K., Application of Decision Support System in E-commerce, Commun. IBIMA, 5, (2008); Yadegaridehkordi E., Noor N.F.B.M., Bin Ayub M.N., Affal H.B., Hussin N.B., Affective computing in education: A systematic review and future research, Comput. Educ, 142, (2019); Zhang D., Islam M., Lu G., A review on automatic image annotation techniques, Pattern Recognit, 45, pp. 346-362, (2012); Zheng B., Computer-Aided Diagnosis in Mammography Using Content-Based Image Retrieval Approaches: Current Status and Future Perspectives, Algorithms, 2, pp. 828-849, (2009)","A. Bagwari; Department of Electronics and Communication Engineering, WIT, Uttarakhand Technical University, Dehradun, 248007, India; email: ashishbagwari@ieee.org",null,"MDPI",{"$nulls":5},2.0782489E7,null,null,null,"English","Information","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85140618872"]
["Shi Y.; Lin Y.; Lim M.K.; Tseng M.-L.; Tan C.; Li Y.","Shi, Yuhe (57194195858); Lin, Yun (36655835400); Lim, Ming K. (7201473042); Tseng, Ming-Lang (44261803600); Tan, Changlu (57843984400); Li, Yan (57207042390)","57194195858; 36655835400; 7201473042; 44261803600; 57843984400; 57207042390","An intelligent green scheduling system for sustainable cold chain logistics",2022.0,"Expert Systems with Applications",209.0,null,118378.0,null,null,null,17.0,"10.1016/j.eswa.2022.118378","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135915638&doi=10.1016%2fj.eswa.2022.118378&partnerID=40&md5=136b0c44fa16c4c2f23b323ca7a87a41","School of Management Science and Real Estate, Chongqing University, Chongqing, 400000, China; Adam Smith Business School, University of Glasgow, Glasgow, United Kingdom; Institute of Innovation and Circular Economy, Asia University, Taiwan; Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, Taiwan; Chongqing Agricultural Investment Logistics Development Co., Ltd., Chongqing, 400000, China; College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing, 400000, China","Shi Y., School of Management Science and Real Estate, Chongqing University, Chongqing, 400000, China; Lin Y., School of Management Science and Real Estate, Chongqing University, Chongqing, 400000, China; Lim M.K., Adam Smith Business School, University of Glasgow, Glasgow, United Kingdom; Tseng M.-L., Institute of Innovation and Circular Economy, Asia University, Taiwan, Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, Taiwan; Tan C., Chongqing Agricultural Investment Logistics Development Co., Ltd., Chongqing, 400000, China; Li Y., College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing, 400000, China","This study proposes an intelligent green scheduling system for cold chain logistics (IGSS-CCL) to support the integration and coordination of resources. Post-COVID-19, the traditional cold product market is rapidly converting to retail stores and e-commerce portals owing to social distancing restrictions, which creates a requirement and opportunities for the development of cold chain logistics. However, urban governance requirements, such as pandemic prevention, traffic restriction, energy conservation, and emissions reduction, have added challenges to this development. Therefore, it is vital to design a cold chain logistics scheduling system that considers the economic, safety, and environmental factors. The proposed system includes three parts: (1) the framework structure of the cold chain logistics intelligent scheduling system; (2) a multi-objective scheduling optimization model to allow for efficient and dynamic coordination between the distribution, demand, and external environment; and (3) a two-stage optimization algorithm based on Dijkstra's algorithm and a non-dominated sorting genetic algorithm to support intelligent scheduling operations. Numerical experiments were conducted to analyze the performance of the proposed system and demonstrate its application. The results highlight that multi-objective tactical optimization in the IGSS-CCL is conducive to saving resources, protecting the environment, and promoting the sustainable development of cold chain logistics, which remains ahead of the traditional single-objective optimization method. Managers can use the suggested IGSS-CCL as a decision-support tool to control and supervise the scheduling operations of cold chain logistics. © 2022 Elsevier Ltd","Carbon emission; Cold chain logistics; Intelligent green scheduling system; Multi-objective; Two-stage optimization algorithm","Carbon; COVID-19; Decision support systems; Emission control; Genetic algorithms; Multiobjective optimization; Scheduling; Scheduling algorithms; Sustainable development; Carbon emissions; Cold chain logistics; Green scheduling; Intelligent green scheduling system; Intelligent scheduling; Multi objective; Optimization algorithms; Scheduling systems; Two stage optimizations; Two-stage optimization algorithm; Retail stores",{"$nulls":4},"Chongqing Technology Innovation and Application Development Special Project, (cstc2021jscx-gksbX0069); Fundamental Research Funds for the Central Universities, (2021CDJSKJC14); National Social Science Fund of China, NSSFC, (18BJY066)","This work was supported by the Chinese National Funding of Social Science (grant number 18BJY066 ); and the Fundamental Research Funds for the Central Universities (grant number 2021CDJSKJC14). Chongqing Technology Innovation and Application Development Special Project (grant number cstc2021jscx-gksbX0069). We would like to thank Editage ( www.editage.cn ) for English language editing. ",{"$cut":{"chars":16735,"head":"Aday S., Aday M.S., Impact of COVID-19 on the food supply chain, Food Quality and Safety, 4, 4, pp. 167-180, (2020); Agatz N., Bouman P., Schmidt M., Optimization Approaches for the Traveling Salesman Problem with Drone, Transportation Science, 52, 4, pp. 965-981, (2018); Al Theeb N., Smadi H.J., Al-Hawari T.H., Aljarrah M.H., Optimization of vehicle routing with inventory allocation problems in Cold Supply Chain Logistics, Computers & Industrial Engineering, 142, (2020); Ali A.F., Tawhid M.A., A hybrid particle swarm optimization and genetic algorithm with population partitioning for large scale optimization problems, Ain Shams Engineering Journal, 8, 2, pp. 191-206, (2017); Ambrosini C., Routhier J.L., Objectives, methods and results of surveys carried out in the field of urban freight transport: An international comparison, Transport Reviews, 24, 1, pp. 57-77, (2004); Awad M., Ndiaye M., Osman A., Vehicle routing in cold food supply chain logistics: A literature review, International Journal of Logistics Management, 32, 2, pp. 592-617, (2021); Babagolzadeh M., Shrestha A., Abbasi B., Zhang Y., Woodhead A., Zhang A., Sustainable cold supply chain management under demand uncertainty and carbon tax regulation, Transportation Research Part D: Transport and Environment, 80, (2020); Berk E., Gurler U., Analysis of the (Q, r) Inventory Model for Perishables with Positive Lead Times and Lost Sales, Operations Research, 56, 5, pp. 1238-1246, (2008); Bogue R., Growth in e-commerce boosts innovation in the warehouse robot market, Industrial Robot-an International Journal, 43, 6, pp. 583-587, (2016); Bortolini M., Faccio M., Ferrari E., Gamberi M., Pilati F., Fresh food sustainable distribution: Cost, delivery time and carbon footprint three-objective optimization, Journal of Food Engineering, 174, pp. 56-67, (2016); Boysen N., Schwerdfeger S., Weidinger F., Scheduling last-mile deliveries with truck-based autonomous robots, European Journal of Operational Research, 271, 3, pp. 1085-1099, (2018); Carlsson J.G., Song S., Coordinated Logistics with a Truck and a Drone, Management Science, 64, 9, pp. 4052-4069, (2018); Chen Y., Wang Y., Wang H., Hu Z., Hua L., Controlling urban traffic-one of the useful methods to ensure safety in Wuhan based on COVID-19 outbreak, Safety Science, 131, (2020); Chen F., Zhou J., Wang C., Li C., Lu P., A modified gravitational search algorithm based on a non-dominated sorting genetic approach for hydro-thermal-wind economic emission dispatching, Energy, 121, pp. 276-291, (2017); (2015); Chowdhury A., Karmakar G., Kamruzzaman J., Islam S., Trustworthiness of Self-Driving Vehicles for Intelligent Transportation Systems in Industry Applications, IEEE Transactions on Industrial Informatics, 17, 2, pp. 961-970, (2021); Cui Y., Geng Z., Zhu Q., Han Y., Review: Multi-objective optimization methods and application in energy saving, Energy, 125, pp. 681-704, (2017); De A., Singh S.P., A resilient pricing and service quality level decision for fresh agri-product supply chain in post-COVID-19 era, International Journal of Logistics Management (ahead-of-print), (2021); Deb K., Agrawal S., Pratap A., Meyarivan T., A fast elitist non-dominated sorting genetic algorithm for multi-objective optimization: NSGA-II, International conference on parallel problem solving from nature, pp. 849-858, (2000); Deb K., Jain H., An Evolutionary Many-Objective Optimization Algorithm Using Reference-Point-Based Nondominated Sorting Approach, Part I: Solving Problems With Box Constraints, IEEE Transactions on Evolutionary Computation, 18, 4, pp. 577-601, (2014); Dijkstra E.W., A note on two problems in connexion with graphs, Numerische Mathematik, 1, 1, pp. 269-271, (1959); El Mokrini A., Aouam T., A decision-support tool for policy makers in healthcare supply chains to balance between perceived risk in logistics outsourcing and cost-efficiency, Expert Systems with Applications, 201, (2022); Esmizadeh Y., Bashiri M., Jahani H., Almada-Lobo B., Cold chain management in hierarchical operational hub networks, Transportation Research Part"}},"Y. Lin; School of Management Science and Real Estate, Chongqing University, Chongqing, 400000, China; email: linyun@cqu.edu.cn",null,"Elsevier Ltd",{"$nulls":5},9574174.0,null,"ESAPE",null,"English","Expert Sys Appl","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85135915638"]
["Buldeo Rai H.; Touami S.; Dablanc L.","Buldeo Rai, Heleen (57195135422); Touami, Sabrina (57396353800); Dablanc, Laetitia (15118955600)","57195135422; 57396353800; 15118955600","Autonomous e-commerce delivery in ordinary and exceptional circumstances. The French case",2022.0,"Research in Transportation Business and Management",45.0,null,100774.0,null,null,null,17.0,"10.1016/j.rtbm.2021.100774","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85122269013&doi=10.1016%2fj.rtbm.2021.100774&partnerID=40&md5=48f883932611611234e782accf0debb8","Gustave Eiffel University, Logistics City chair, France","Buldeo Rai H., Gustave Eiffel University, Logistics City chair, France; Touami S., Gustave Eiffel University, Logistics City chair, France; Dablanc L., Gustave Eiffel University, Logistics City chair, France","Automation represents the next big buzz in transport and promises many advantages beneficial for society, including a more efficient use of space, energy, time, as well as reduced costs. An impressive range of autonomous vehicles is introduced, covering applications for personal and goods transport. In particular in response to the global pandemic linked to COVID-19, autonomous vehicles were proposed and celebrated as safe and reliable home delivery solutions of the future. In the midst of visionary trend reports, eye-catching press releases and promising research simulations, the actual applicability of autonomous vehicles in an e-commerce context remains difficult to assess. This lack of clarity holds for delivery automation in ordinary situations as well as in exceptional circumstances, such as those presented by a severe health crisis. To understand the state of practice and future potential of autonomous vehicles for e-commerce delivery in cities, we carried out desk and field research on the topic. This article structures the different types of autonomous e-commerce delivery vehicles and scenarios and discusses their state of practice and potential in ordinary as well as in exceptional circumstances. The study focusses on France, against a comprehensive international backdrop. © 2022 Elsevier Ltd","Autonomous vehicles; City logistics; COVID-19; Delivery drone; Delivery robot; Urban goods transport",{"$nulls":5},"Université Gustave Eiffel; Université Gustave Eiffel, UGE","Funding text 1: This work is supported by the Logistics City Chair of the Université Gustave Eiffel, as well as by the City on the Move-VEDECOM Institute.; Funding text 2: While six out of ten transport companies surveyed in the questionnaire indicate that follower sidewalk robots are most promising for urban deliveries, five believe in the potential of semi-autonomous sidewalk robots. The questionnaire points out that other autonomous delivery vehicle types are perceived as less interesting, which is confirmed by French initiatives past and planned. La Poste carried out experiments in several cities in France with follower robots that support delivery staff. In addition, it set up an experiment in the city of Montpellier to test the sidewalk robot of French autonomous vehicle developer TwinswHeel, still in progress in May 2021. The experiment with TwinswHeel is part of the SAM project financed by the French Agency for Ecological Transition: “Safety and acceptability of autonomous driving and mobility”. The project follows the national strategy for the development of autonomous vehicles that was presented by the French Government in May 2018. ","Ahmed A., Robomart launch, (2021); Albrecht C., Postmates’ serve robot spotted (and filmed) making deliveries in LA, The Spoon, (2019); Allen J., Browne M., Woodburn A., London freight data report: 2014 update, (2014); Allen J., Piecyk M., Piotrowska M., McLeod F., Cherrett T., Ghali K., Nguyen T., Bektas T., Bates O., Friday A., Wise S., Austwick M., Understanding the impact of e-commerce on last-mile light goods vehicle activity in urban areas: the case of London, Transportation Research Part D: Transport and Environment, 61, pp. 325-338, (2018); Arora N., Charm T., Grimmelt A., Ortega M., Robinson K., Sexauer C., Staack Y., Whitehead S., Yamakawa N., A global view of how consumer behavior is changing amid COVID-19, (2020); Bright J., Zipline begins US medical delivery with drone program honed in Africa, TechCrunch, (2020); Buldeo Rai H., The net environmental impact of online shopping, beyond the substitution bias, Journal of Transport Geography, 93 103058, (2021); Buldeo Rai H., Touami S., E-commerce: Vers l'automatisation du transport de marchandises en ville?, Transports Infrastructures & Mobilité, 522, (2020); Buldeo Rai H., Verlinde S., Macharis C., The “next day, free delivery” myth unravelled: Possibilities for sustainable last mile transport in an omnichannel environment, International Journal of Retail & Distribution Management, 47, 1, pp. 39-54, (2019); Chitta S., Jain R.K., Last mile delivery using drones, (2017); Condliffe J., Why sidewalk delivery robots still need safety drivers, MIT Technology Review, (2018); Coulombel N., Dablanc L., Gardrat M., Koning M., The environmental social cost of urban road freight: Evidence from the Paris region, Transportation Research Part D: Transport and Environment, 63, pp. 514-532, (2018); Creswell J.W., Miller D.L., Determining validity in qualitative inquiry, Theory Into Practice, 39, 3, pp. 124-130, (2000); Crowe S., Nuro driverless vehicles approved for delivery tests in California, The Robot Report, (2020); Dablanc L., Buldeo Rai H., Barometer of urban logistics in lockdown, (2020); Daimler, Mercedes-Benz vans invests in starship technologies, the world's leading manufacturer of delivery robots, Daimler Global Media Site, (2017); Deloison T., Hannon E., Huber A., Heid B., Klink C., Sahay R., Wolff C., The future of the last-mile ecosystem: Transition roadmaps for public- and private-sector players, (2020); Eisenhardt K.M., Building theories from case study research, The Academy of Management Review, 14, 4, pp. 532-550, (1989); European Commission, European innovation scoreboard, (2020); Farriol G., Un robot qui porte vos courses a été testé dans un centre commercial à Paris (vidéo), Soirmag, (2018); Figliozzi M.A., Carbon emissions reductions in last mile and grocery deliveries utilizing air and ground autonomous vehicles, Transportation Research Part D: Transport and Environment, 85, (2020); Figliozzi M.A., Jennings D., Autonomous delivery robots and their potential impacts on urban freight energy consumption and emissions, Transportation Research Procedia, 46, 2019, pp. 21-28, (2020); Ford, Agility robotics to sell first digit robots to ford to accelerate exploration of commercial vehicle customer applications, (2020); Ford Europe, Autolivery, (2017); Forestieri K., Facing financial trouble, Mountain View's downtown businesses turn to delivery bots, Mountain View Voice, (2020); Fraunhofer, ZF-ZUKUNFTSSTUDIE 2016 Die letzte Meile, (2016); Garaude P., TwinswHeel s'attaque avec ses robots aux livraisons en centre-ville, Maddyness, (2021); Gardet M., Des robots autonomes TwinswHeel dans les rues d'Occitanie dès 2023, La Tribune, (2021); Ghaffarzadeh K., Jiao N., Mobile robots, autonomous vehicles, and drones in logistics, warehousing, and delivery 2020-2040, IDTechEx, (2019); Gong W., ITPO Shanghai partners with White Rhino Auto company Robot delivery vehicles deployed to help with COVID-19, ITPO Shanghai, (2019); Goodchild A., Toy J., Delivery by drone: An evaluation of unmanned aerial vehicle technology in reducing CO2 emissions in the delivery service industry, Transportation Research Part D: Transport and Environment, 61, pp. 58-67, (2018); Harwood R., The challenges to developing fully autonomous drone technology, Ansys, (2019); Hawkins A.J., Thousands of autonomous delivery robots are about to descend on US college campuses, The Verge, (2019); Hawkins A.J., Nuro gets the green light to test driverless delivery robots in California, The Verge, (2020); Hoffmann T., Prause G., On the regulatory framework for last-mile delivery robots, Machines, 6, 3, pp. 6-8, (2018); INSEE, Population présente sur le territoire avant et après le début du confinement, (2020); Jaller M., Otero C., Pourrahmani E., Fulton L., Automation, electrification, and shared mobility in freight, (2020); Jennings D., Figliozzi M.A., A study of sidewalk autonomous delivery robots and their potential impacts on freight efficiency and travel, Transportation Research Record, 2673, 6, pp. 317-326, (2019); Joerss M., Schroder J., Neuhaus F., Klink C., Mann F., Parcel delivery – The future of last mile, (2016); Kohli S., Timelin B., Fabius V., Moulvad Veranen S., How COVID-19 is changing consumer behavior-now and forever, (2020); Kucher D., The unmanned vehicle that meets the needs of people under quarantine: Hercules, Somag News, (2020); Lebeau P., Macharis C., Freight transport in Brussels and its impact on road traffic, Brussels Studies, 32, (2014); Lienert P., Lanhee Lee J., Automated delivery cashes in on pandemic-driven demand, (2020); van Lier T., The development of an external cost calculator framework for evaluating the sustainability of transport solutions, (2014); Meisenzahl M., How Asia, the US, and Europe are using robots to replace and help humans fight coronavirus by delivering groceries, sanitizing hospitals, and monitoring patients, Business Insider, (2020); Mercedes-Benz, Pilot project for on-demand delivery, 2016, (2016); Murphy M., This might be the fastest delivery drone in the world, Quartz, (2018); Nuro, Delivering safety: Nuro's approach, (2018); OECD, Unpacking E-commerce – Business models, trends and policies, (2019); Ogbonyenitan G., Kiwibots are not fully Autonomous and are controlled by operators in Colombia, Techidence, (2019); Pani A., Mishra S., Golias M., Figliozzi M., Evaluating public acceptance of autonomous delivery robots during COVID-19 pandemic, Transportation Research Part D, (2020); 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Soesilo D., Meier P., Lessard-Fontaine A., Du Plessis J., Stuhlberger C., Drones et action humanitaire: Guide sur l'utilisation des systèmes embarqués lors de situations de crise humanitaire, (2016); Swiss Post, Swiss Post to transport laboratory samples between University Hospital and University of Zurich, Swiss Post, (2018); Tomer A., Kane J., Mapping freight: The highly concentrated nature of goods trade in the United States, (2014); Touami S., Les robots de livraison en ville, une solution à venir?, (2020); Transport Intelligence, DHL unveils drone delivery service in China, Transport Intelligence, (2019); TRB, Research needs statements on automated vehicles, shared mobility, pandemics, and equity, (2020); Tsukimori O., Robot-maker ZMP targets tractors, taxis and carts for elderly, The Japan Times, (2020); UPS, UPS and Waymo partner to begin self-driving package pickup in Arizona, UPS Pressroom, (2020); Wayland M., CVS Pharmacy partners with Nuro to test self-driving vehicle prescription delivery, CNBC, (2020); Yin R.K., Case study reserach – Design and methods, Applied social research methods series, 5, (1984)","H. Buldeo Rai; Gustave Eiffel University, Logistics City chair, France; email: heleen.buldeo-rai@univ-eiffel.fr",null,"Elsevier Ltd",{"$nulls":5},2.2105395E7,null,null,null,"English","Res. Transport. Bus. Manage.","Article","Final",null,"Scopus","2-s2.0-85122269013"]
["Bukoye O.T.; Gadiraju S.","Bukoye, Oyegoke Teslim (56337971500); Gadiraju, Sathvik (58532679800)","56337971500; 58532679800","Optimal consolidation center to improve urban freight transport: a case of student accommodation in a higher education institution",2022.0,"Multimodal Transportation",1.0,3.0,100032.0,null,null,null,2.0,"10.1016/j.multra.2022.100032","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85164515300&doi=10.1016%2fj.multra.2022.100032&partnerID=40&md5=534836c9cd7b28be0bcac7f0d6d5c222","Information, Decisions and Operations (IDO) Division, School of Management, University of Bath, Bath, BA2 7AY, United Kingdom","Bukoye O.T., Information, Decisions and Operations (IDO) Division, School of Management, University of Bath, Bath, BA2 7AY, United Kingdom; Gadiraju S., Information, Decisions and Operations (IDO) Division, School of Management, University of Bath, Bath, BA2 7AY, United Kingdom","Cities across the world are expanding as a result of urbanization, resulting in growing demand for goods and services, mainly through online sales. This has resulted in the need for an urban consolidation center (UCC) to minimize travel and optimize deliveries, particularly in student accommodation settings. In this paper, we examine how an optimal consolidation center can improve urban freight transport. We conducted a multi-method and in-depth case study of student halls of residence within a UK higher education institution. In addition, we analyzed a rich secondary dataset including location, parcel, and vehicle data. We developed and tested three scenarios to present an optimal urban consolidation scenarios model using a Vehicle Routing Problem (VRP) solver; indicating the transportation costs, distance travelled, and CO2 emitted. The operationalization of the optimal UCC as well as the limitations on direct and indirect cost, accessibility, and collaboration are discussed. Our findings show the impact of having an ideal pickup point that would give students the ability to collect their parcels effortlessly and make the return of goods easier for students. As such, we extend extant studies on the implications for urban consolidation center theory and practice. © 2022","Consolidation center; e-Commerce; Freight transport; Higher education institution; Student residence; Urban",{"$nulls":7},"Aktas E., Bourlakis M., Zissis D., Collaboration in the last mile: evidence from grocery deliveries, Int. J. of Logist. Res. and Appl., 24, 3, pp. 227-241, (2021); Allen J., Browne M., Woodburn A., Leonardi J., A review of urban consolidation centers in the supply chain based on a case study approach, Supply Chain Forum: An Int. J., 15, 4, pp. 100-112, (2014); Allen J., Browne M., Woodburn A., Leonardi J., The role of urban consolidation centers in sustainable freight transport, Transp. 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["Wang M.; Zhang C.; Bell M.G.H.; Miao L.","Wang, Mengtong (57353031100); Zhang, Canrong (7405490618); Bell, Michael G.H. (25822259900); Miao, Lixin (7005303290)","57353031100; 7405490618; 25822259900; 7005303290","A branch-and-price algorithm for location-routing problems with pick-up stations in the last-mile distribution system",2022.0,"European Journal of Operational Research",303.0,3.0,null,1258.0,1276.0,18.0,12.0,"10.1016/j.ejor.2022.03.058","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85132671292&doi=10.1016%2fj.ejor.2022.03.058&partnerID=40&md5=8f87ae98d81eb4137e94b2dd592e9b4f","Department of Industrial Engineering, Tsinghua University, Beijing, 100084, China; Division of Logistics and Transportation, Shenzhen International Graduate School, Tsinghua University, Shenzhen, 518055, China; Institute of Transport and Logistics Studies, The University of Sydney, NSW, 2006, Australia; Intelligent Transportation and Logistics Systems Laboratory, Tsinghua-Berkeley Shenzhen Institute, Shenzhen, 518055, China","Wang M., Department of Industrial Engineering, Tsinghua University, Beijing, 100084, China, Division of Logistics and Transportation, Shenzhen International Graduate School, Tsinghua University, Shenzhen, 518055, China; Zhang C., Division of Logistics and Transportation, Shenzhen International Graduate School, Tsinghua University, Shenzhen, 518055, China; Bell M.G.H., Institute of Transport and Logistics Studies, The University of Sydney, NSW, 2006, Australia; Miao L., Division of Logistics and Transportation, Shenzhen International Graduate School, Tsinghua University, Shenzhen, 518055, China, Intelligent Transportation and Logistics Systems Laboratory, Tsinghua-Berkeley Shenzhen Institute, Shenzhen, 518055, China","In catering to the needs of the growing e-commerce demand and environmentally friendly urban delivery solutions, package delivery companies are increasingly focusing on user experience and sustainable operations, such as alternative delivery methods (e.g., pick-up stations) and green delivery vehicles (e.g., electric vehicles). We consider designing a location-routing problem with pick-up stations (LRP-PS) where the location of pick-up stations to open and the delivery plan of green vehicles (GVs) are optimized simultaneously. The purpose is to satisfy the total demand while minimizing the sum of opening cost and handling cost of pick-up stations and the fixed cost and routing cost of GVs. Then, we present a compact mixed-integer programming formulation to define the LRP-PS and reveal some interesting properties of the optimal solution. We propose an effective branch-and-price (B&P) algorithm to solve the LRP-PS, which is demonstrated to outperform greatly commercial branch-and-cut solvers such as CPLEX in the computational study. Finally, through a comprehensive analysis of several key parameters (e.g., coverage ranges of pick-up stations and battery driving ranges of GVs), we assess the impact of pick-up stations on this last-mile distribution system and provide some helpful business insights for package delivery companies. © 2022 Elsevier B.V.","Branch-and-price; Location-routing; Logistics; Pick-up stations","Location; Pickups; Routing algorithms; Vehicle routing; Vehicles; Branch and price; Branch-and-price algorithms; Delivery company; Distribution systems; E- commerces; Last mile; Location routing problem; Location-routing; Package delivery; Pick-up station; Integer programming",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (71771130, 71872092); Natural Science Foundation of Guangdong Province, (2021B1515020059)","This work is supported by the National Natural Science Foundation of China under Grant No. 71771130 and No. 71872092, and Natural Science Foundation of Guangdong Province, China, under Grant No. 2021B1515020059. ","Allahyari S., Salari M., Vigo D., A hybrid metaheuristic algorithm for the multi-depot covering tour vehicle routing problem, European Journal of Operational Research, 242, 3, pp. 756-768, (2015); (2017); Archetti C., Bianchessi N., Speranza M.G., A column generation approach for the split delivery vehicle routing problem, Networks, 58, 4, pp. 241-254, (2011); Archetti C., Savelsbergh M.W., Speranza M.G., To split or not to split: That is the question, Transportation Research Part E: Logistics and Transportation Review, 44, 1, pp. 114-123, (2008); Augerat P., Naddef D., Belenguer J., Benavent E., Corberan A., Rinaldi G., (1995); Baldacci R., Dell'Amico M., Gonzalez J.S., The capacitated m-ring-star problem, Operations Research, 55, 6, pp. 1147-1162, (2007); Beasley J., Nascimento E., The vehicle routing-allocation problem: A unifying framework, Top, 4, 1, pp. 65-86, (1996); Bektas T., Erdogan G., Ropke S., Formulations and branch-and-cut algorithms for the generalized vehicle routing problem, Transportation Science, 45, 3, pp. 299-316, (2011); 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Veenstra M., Roodbergen K.J., Coelho L.C., Zhu S.X., A simultaneous facility location and vehicle routing problem arising in health care logistics in the netherlands, European Journal of Operational Research, 268, 2, pp. 703-715, (2018); Wang Y., Peng S., Zhou X., Mahmoudi M., Zhen L., Green logistics location-routing problem with eco-packages, Transportation Research Part E: Logistics and Transportation Review, 143, (2020); Yang J., Sun H., Battery swap station location-routing problem with capacitated electric vehicles, Computers & Operations Research, 55, pp. 217-232, (2015); Yu Y., Wang S., Wang J., Huang M., A branch-and-price algorithm for the heterogeneous fleet green vehicle routing problem with time windows, Transportation Research Part B: Methodological, 122, pp. 511-527, (2019); Zhang S., Chen M., Zhang W., A novel location-routing problem in electric vehicle transportation with stochastic demands, Journal of Cleaner Production, 221, pp. 567-581, (2019); Zhou L., Baldacci R., Vigo D., Wang X., A multi-depot two-echelon vehicle routing problem with delivery options arising in the last mile distribution, European Journal of Operational Research, 265, 2, pp. 765-778, (2018)","C. Zhang; Division of Logistics and Transportation, Shenzhen International Graduate School, Tsinghua University, Shenzhen, 518055, China; email: crzhang@sz.tsinghua.edu.cn",null,"Elsevier B.V.",{"$nulls":5},3772217.0,null,"EJORD",null,"English","Eur J Oper Res","Article","Final",null,"Scopus","2-s2.0-85132671292"]
["Pintado E.; De Oliveira L.C.; Garcia J.E.","Pintado, Eduardo (57465793800); De Oliveira, Lia Coelho (57216323490); Garcia, Jorge Esparteiro (57104146700)","57465793800; 57216323490; 57104146700","Using EPP Boxes in a Dark Store: A New Approach to Simplify Food Retail E-Commerce Deliveries",2022.0,"Business Systems Research",13.0,3.0,null,130.0,143.0,13.0,1.0,"10.2478/bsrj-2022-0029","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85145582468&doi=10.2478%2fbsrj-2022-0029&partnerID=40&md5=f283713d546e1809f070641d0dda0a0e","Instituto Superior de Contabilidade e Administracao Do Instituto Politecnico Do Porto, Porto, Portugal; INESC TEC, Porto, Portugal; Polytechnic Institute of Viana Do Castelo, Portugal; ADiT-LAB, Polytechnic Institute Viana Do Castelo and INESC TEC, Porto, Portugal","Pintado E., Instituto Superior de Contabilidade e Administracao Do Instituto Politecnico Do Porto, Porto, Portugal; De Oliveira L.C., INESC TEC, Porto, Portugal, Polytechnic Institute of Viana Do Castelo, Portugal; Garcia J.E., ADiT-LAB, Polytechnic Institute Viana Do Castelo and INESC TEC, Porto, Portugal","Background: E-commerce has emerged as a good response to the pandemic of COVID-19. However, the costs of providing a service, which includes a driver and a vehicle, in a regular vehicle that can transport goods that need positive cold (0° to 5°C) are very high. Objectives: This paper aims to investigate how a big Portuguese retailer company can reduce its dependence on refrigerated vehicles, simplifying operations and reducing the costs of transporting positive and negative cold food. Methods/Approach: This research was carried out in a food retailer Portuguese company, more precisely in a Dark Store dedicated to the online channel. The study was developed based on the AS-IS/TO-BE process analysis methodology, starting with the analysis of the current situation, giving rise to the so-called AS-IS model. Results: It was possible to reduce costs associated with transporting positive cold goods. As a result, there are 30% fewer costs associated with order transportation. With an additional 10% in space optimization with the gain of space within the galley of each vehicle. Conclusions: The costs of transporting positive and negative cold foods were decreased, and substituting vehicles with room temperature transport reduced the need for refrigerated vehicles.  © 2022 Eduardo Pintado et al., published by Sciendo.","Case study; Dark Store; E-commerce; Food Retail; Sustainability; Transportation",{"$nulls":7},"Alberto Lopes J., Tsochatzis E.D., Robouch P., Hoekstra E.J., Influence of preheating of food contact polypropylene cups on its physical structure and on the migration of additives, Food Packaging and Shelf Life, 20, (2019); Alves S., J. 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Syst. Res.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85145582468"]
["Rodrigue J.-P.","Rodrigue, Jean-Paul (7005441482)",7.005441482E9,"Home-based parcel deliveries: Consumer and logistics patterns from retail digitalization",2022.0,"Case Studies on Transport Policy",10.0,4.0,null,2413.0,2419.0,6.0,3.0,"10.1016/j.cstp.2022.11.004","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85141569634&doi=10.1016%2fj.cstp.2022.11.004&partnerID=40&md5=fe1bd7a8beb6ecbcbd7f86e0c98de76d","Dept of Global Studies & Geography, Hofstra University, 11549, NY, United States; Distinguished Fellow, Hagler Institute for Advanced Study / Department of Maritime Administration, Texas A&M University-Galveston, United States","Rodrigue J.-P., Dept of Global Studies & Geography, Hofstra University, 11549, NY, United States, Distinguished Fellow, Hagler Institute for Advanced Study / Department of Maritime Administration, Texas A&M University-Galveston, United States","The paper investigates the current retail paradigm shift by looking at the emerging distributional strategies and practices of e-commerce firms, including the changing landscape of city logistics. It is based on a long-term survey of home deliveries in a large residential apartment building that tracks daily parcel deliveries by carrier. Empirical evidence from this delivery point survey is used to substantiate retail digitalization trends, which have resulted in changes in the distribution pattern with the growth of home deliveries. The growth of the delivery footprint in terms of the space consumed by parcels within buildings waiting to be picked up by their consignees is becoming evident. Further, major online retailers are undertaking vertical integration strategies, such as having their own delivery arrangements, which is reflected in the shift in the relative share of carriers used for home deliveries. The survey provided concrete trends in terms of temporal frequency of deliveries on an annual, weekly, daily, and hourly scale. © 2022 World Conference on Transport Research Society","Consumer behavior; Delivery point survey; Digitalization; E-commerce; Home deliveries; Logistics","consumption behavior; digital image; electronic commerce; logistics; retailing",{"$nulls":6},"Allen J., Browne M., Cherrett T., Survey techniques in urban freight transport studies, Transport Reviews, 32, 3, pp. 287-311, (2012); Beckers J., Cardenas I., Sanchez-Diaz I., Managing household freight: The impact of online shopping on residential freight trips, Transport Policy, 125, pp. 299-311, (2022); Chava S., Oettl A., Singh M., (2018); Colaco R., de Abreu e Silva J., Exploring the Interactions between Online Shopping, In-Store Shopping, and Weekly Travel Behavior using a 7-Day Shopping Survey in Lisbon, Portugal, Transportation Research Record, 2675, 5, pp. 379-390, (2021); Dablanc L., Morganti E., Arvidsson N., Woxenius J., Browne M., Saidi N., The rise of on-demand 'Instant Deliveries' in European cities, Supply Chain Forum: An International Journal, 18, 4, pp. 203-217, (2017); Escand P., Chen Q., Conway A., Parking Conditions for Residential Delivery in New York City: A Case Study Analysis, Transportation Research Record, 2672, 9, pp. 204-215, (2018); Hagberg J., Sundstrom M., Nicklas E.-Z., The digitalization of retailing: an exploratory framework, International Journal of Retail & Distribution Management, 44, 7, pp. 694-712, (2016); Holguin-Veras J., Sanchez-Diaz I., Browne M., Sustainable Urban Freight Systems and Freight Demand Management, Transportation Research Procedia, 12, pp. 40-52, (2016); Holmes T.J., The Diffusion of Wal-Mart and the Economies of Density, Econometrica, 79, 1, pp. 253-302, (2011); Institute of Transportation Engineers, Trip Generation Handbook, 2nd Edition: An ITE Recommended Practice, (2004); Jaller M., Pahwa A., Evaluating the environmental impacts of online shopping: A behavioral and transportation approach, Transportation Research Part D: Transport and Environment, 80, (2020); Kirby-Hawkins E., Birkin M., Clarke G., An investigation into the geography of corporate e-commerce sales in the UK grocery market, Environment and Planning B: Urban Analytics and City Science, 46, 6, pp. 1148-1164, (2019); Morganti E., Seidel S., Blanquart C., Dablanc L., Lenz B., The impact of e-commerce on final deliveries: alternative parcel delivery services in France and Germany, Transportation Research Procedia, 4, pp. 178-190, (2014); Oka H., Hagino Y., Kenmochi T., Tani R., Nishi R., Endo K., Fukuda D., Predicting travel pattern changes of freight trucks in the Tokyo Metropolitan area based on the latest large-scale urban freight survey and route choice modeling, Transportation Research Part E: Logistics and Transportation Review, 129, pp. 305-324, (2019); Outwater M., Smith C., Wies K., Yoder S., Sana B., Chen J., Tour based and supply chain modeling for freight: integrated model demonstration in Chicago, Transportation Letters, 5, 2, pp. 55-66, (2013); Pernot D., Internet shopping for Everyday Consumer Goods: An examination of the purchasing and travel practices of click and pickup outlet customers, Research in Transportation Economics, 87, (2021); Rodrigue J.-P., The Distribution Network of Amazon: Analyzing the Footprint of Freight Digitalization, Journal of Transport Geography, 88, (2020); Salas J., Chen Q., (2018); Saphores J.-D., Xu L.U., E-shopping changes and the state of E-grocery shopping in the US - Evidence from national travel and time use surveys, Research in Transportation Economics, 87, (2021); Seaton H.E., The new e-commerce/home delivery retail distribution paradigm, Journal of Transportation Management, 29, 1, pp. 7-25, (2018); Toilier F., Serouge M., Routhier J.-L., Patier D., pp. 570-583, (2016); van Duin J.H.R., Wiegmans B.W., Van Arem B., van Amstel Y., From home delivery to parcel lockers: a case study in Amsterdam, Transportation Research Procedia, 46, pp. 37-44, (2020); Visser J., Nemoto T., Browne M., Home Delivery and the Impacts on Urban Freight Transport: A Review, Procedia - Social and Behavioral Sciences, 125, pp. 15-27, (2014); Zuopeng X., Wang J.J., 46, 1, pp. 2-20, (2018)",null,null,"Elsevier Ltd",{"$nulls":5},"2213624X",null,null,null,"English","Case Stud. Transp. Policy","Article","Final",null,"Scopus","2-s2.0-85141569634"]
["Bhat S.A.; Mir A.A.; Islam S.B.","Bhat, Suhail Ahmad (57190001272); Mir, Ajaz Akbar (58442862000); Islam, Sheikh Basharul (57223860148)","57190001272; 58442862000; 57223860148","Scale Purification and Validation: A Methodological Approach to Sustainable Online Retailing",2022.0,"Vikalpa",47.0,3.0,null,217.0,234.0,17.0,0.0,"10.1177/02560909221123632","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85139115886&doi=10.1177%2f02560909221123632&partnerID=40&md5=11bb635683a96723e40520541eded253","Department of Management Studies, University of Kashmir, Srinagar, India; University of Kashmir, Srinagar, India","Bhat S.A., Department of Management Studies, University of Kashmir, Srinagar, India; Mir A.A., University of Kashmir, Srinagar, India; Islam S.B., Department of Management Studies, University of Kashmir, Srinagar, India","Sustainability in the e-commerce business has created an overwhelming interest among practitioners and researchers. The different business models adopted by the e-retailers in India lack sustainable aspects, hindering them from generating sustainable revenues. To accomplish such goals, e-retailers need to focus on sustainable factors such as trust, innovation, timely delivery of goods, usability, internet speed and customer support service. In view of this, the article is aimed to create an instrument that captures sustainable online retailing by developing, measuring and empirically validating a scale. The validity of the scale was established by adopting a proper psychometric scale development procedure. The study found that after applying various judgmental and statistical criteria to the initial scale of 26 items, 17 items were retained with the removal of nine items sequentially at different steps. The dropped items could not meet the set thresholds of different criterion. Results of the study suggested that trust and internet speed in the present context are key determinants of sustainable e-retailing. The study focused on the online retail sector only. Methodological developments in other areas might lead to different results if the chosen criteria were to be repeated there. Both judgmental and statistical procedures need to be used with proper consensus. The practical implications of the study involve five constructs that e-marketers and practitioners could adopt to provide better customer experience resulting in higher customer satisfaction. The authors demonstrated a detailed procedure for scale purification. This procedure will help researchers in this area and in adjacent disciplines build greater consistency regarding applying methodological steps in scale purification. It will also assist reviewers and editors with tools to identify methodological errors while making review decisions. Such a scale will help in bringing standardization of the research carried out in sustainable online retailing. © 2022 Indian Institute of Management, Ahmedabad.","Purification; Scale Development; Statistical and Judgmental Criteria; Sustainable Online Retailing; Validation",{"$nulls":7},{"$cut":{"chars":17936,"head":"Agag G., El-masry A., Alharbi N., Ahmed Almamy A., Development and validation of an instrument to measure online retailing ethics, Internet Research, 26, 5, pp. 1158-1180, (2016); Agarwal R., Prasad J., A conceptual and operational definition of personal innovativeness in the domain of information technology, Information Systems Research, 9, 2, pp. 204-215, (1998); Ahn T., Ryu S., Han I., The impact of the online and offline features on the user acceptance of internet shopping malls, Electronic Commerce Research Application, 3, 4, pp. 405-420, (2003); Anand S., Kaur H., Fashion self-congruity: Scale development and validation, Journal of Fashion Marketing and Management, 22, 2, pp. 158-175, (2018); Arora S., Kaur H., Exploring the bank selection criteria in India: Scale development and validation, International Journal of Bank Marketing, 37, 3, pp. 666-690, (2019); Ashworth C.J., Schmidt R.A., Pioch E.A., Hallsworth A., Web-weaving, International Journal of Retail and Distribution Management, 34, 6, pp. 497-511, (2006); Back K., The effects of image congruence on customers’ brand loyalty in the upper middle-class hotel industry, Journal of Hospitality and Tourism Research, 29, 4, pp. 448-467, (2005); Balaji M.S., Chakraborti R., Stadium atmosphere: scale development and validation in Indian context, Journal of Indian Business Research, 7, 1, pp. 45-66, (2015); Balderjahn I., Buerke A., Kirchgeorg M., Peyer M., Seegebarth B., Wiedmann K.P., Consciousness for sustainable consumption: scale development and new insights in the economic dimension of consumers’ sustainability, AMS Review, 3, 4, pp. 181-192, (2013); Bansal G., Zahedi F.M., Gefen D., Do context and personality matter? Trust and privacy concerns in disclosing private information online, Information and Management, 53, 1, pp. 1-21, (2016); Bearden W.O., Netemeyer R.G., Haws K.L., Handbook of marketing scales: multi-item measures for marketing and consumer behavior research, (2011); Bhat S.A., Darzi M.A., Bhat S.-U., Sustainable business model in B2C online retailing: An Indian consumer perspective, Technological innovations for sustainability and business growth, pp. 147-185, (2020); Bigne-Alcaniz E., Ruiz-Mafe C., Aldas-Manzano J., Sanz-Blas S., Influence of online shopping information dependency and innovativeness on internet shopping adoption, Online Information Review, 32, 5, pp. 648-667, (2008); Borsboom D., Mellenbergh G.J., van Heerden J., The concept of validity, Psychological Review, 111, 4, pp. 1061-1071, (2004); Byrne B.M., Structural equation modeling with AMOS: basic concepts, applications, and programming, (2010); Cao Y., Ajjan H., Hong P., Post-purchase shipping and customer service experiences in online shopping and their impact on customer satisfaction: An empirical study with comparison, Asia Pacific Journal of Marketing and Logistics, 30, 2, pp. 400-416, (2018); Chahal H., Bakshi P., Examining intellectual capital and competitive advantage relationship, International Journal of Bank Marketing, 33, 3, pp. 376-399, (2015); Chawla H., Never mind online. Come offline, Live Mint, (2015); Chen J., Dibb S., Consumer trust in the online retail context: Exploring the antecedents and consequences, Psychology & Marketing, 27, 4, pp. 323-346, (2010); Costanza R., Patten B.C., Defining and predicting sustainability, Ecological Economics, 15, 3, pp. 192-196, (1995); Damanpour F., Organisational size and innovation, Organisation Studies, 13, 3, pp. 375-402, (1992); Davis F.D., Perceived usefulness, perceived ease of use, and user acceptance, MIS Quarterly, 13, 3, pp. 319-341, (1989); Dawes J., Do data characteristics change according to the number of scale points used, International Journal of Market Research, 50, 1, pp. 61-77, (2008); Delcourt C., Gremler D.D., Riel A.C.R., van Birgelen M.J.H., Employee emotional competence construct conceptualisation and validation of a customer-based measure, Journal of Service Research, 19, 1, pp. 72-87, (2016); Dellaert B., Kahn B.E., How tolerable is delay? Consumers’ evaluations of internet web sites after waiting, Jour"}},null,null,"SAGE Publications Ltd",{"$nulls":5},2560909.0,null,null,null,"English","Vikalpa","Article","Final",null,"Scopus","2-s2.0-85139115886"]
["Yun J.J.; Zhao X.; Ma L.; Liu Z.; Yang B.","Yun, JinHyo Joseph (55419994900); Zhao, Xiaofei (57193208482); Ma, Lei (57204118720); Liu, Zheng (57190680108); Yang, Bo (58460155900)","55419994900; 57193208482; 57204118720; 57190680108; 58460155900","Open innovation dynamics and evolution in the mobile payment industry–comparative analysis among Daegu, Cardiff, and Nanjing",2023.0,"European Planning Studies",31.0,5.0,null,862.0,884.0,22.0,3.0,"10.1080/09654313.2022.2132784","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85139845402&doi=10.1080%2f09654313.2022.2132784&partnerID=40&md5=f95b050bee0f7d2a5b391a4fb9f9e874","DGIST, and Open Innovation Academy of SOI, Daegu, South Korea; Nanjing University of Science and Technology, Nanjing, China; Cardiff Metropolitan University, Cardiff, United Kingdom; Swansea University, Swansea, United Kingdom","Yun J.J., DGIST, and Open Innovation Academy of SOI, Daegu, South Korea; Zhao X., DGIST, and Open Innovation Academy of SOI, Daegu, South Korea; Ma L., Nanjing University of Science and Technology, Nanjing, China; Liu Z., Cardiff Metropolitan University, Cardiff, United Kingdom; Yang B., Swansea University, Swansea, United Kingdom","The understanding of smart payment industry in the financialization under digital transformation will be the clue to capture the future directions and dynamics of modern capitalism economy. Is there any differences in smart payment industry according to capitalist economy condition among Daegu, Cardiff, and Nanjing ? By answering to this research question through comparative analysis of 3 regions based on qualitative interview method, this study found out as follows. First, there are different payment industry context among 3 regions; Daegu, card payment majority; Cardiff, transition from card payment to smart payment; Nanjing, Smart payment majority. Second, Economic contexts of regions could give direct impacts of the development of mobile payment industry such as the lock in the card industry at Daegu in South Korea, or the well-developed smart delivery platform of E-commerce at Nanjing in China, or the long history of capitalist economy which had increased the labor condition of laborer at Cardiff in Wales. Third, from the qualitative interview researches on 3 regions, gave 2 additional grounded theories such as the future direction of smart payment industry, and the double locked-in the card industry at Daegu in South Korea. © 2022 Informa UK Limited, trading as Taylor & Francis Group.","business model; Cardiff; Daegu; Mobile or smart payment; Nanjing; open innovation","Cardiff [Cardiff (ADS)]; Cardiff [Wales]; China; Jiangsu; Nanjing [Jiangsu]; South Korea; Taegu [South Korea]; Taegu [Taegu (ADS)]; United Kingdom; Wales; capitalism; comparative study; electronic commerce; future prospect; information and communication technology; innovation; mobile communication; qualitative analysis; smart city",{"$nulls":4},"Society of Open Innovation Research Fund, (SOI202201); Korea Evaluation Institute of Industrial Technology, KEIT; Daegu Gyeongbuk Institute of Science and Technology, DGIST, (22-IT-10-02)","Funding text 1: This work was mainly (80%) supported by the DGIST(Daegu Gyeongbuk Institute of Science and Technology) 22-IT-10-02. Additionally (20%), this work supported by The Society of Open Innovation Research Fund (Reference; SOI202201). This study received financial support on the research trip to UK from the research project “industrial technology R&D-regional R&D linkage increase, and regional innovation ecosystem activating oriented R&D project planning research” by KEIT (Korea Evaluation Institute of Industrial Technology).; Funding text 2: This study received financial support on the research trip to UK from the research project “industrial technology R&D-regional R&D linkage increase, and regional innovation ecosystem activating oriented R&D project planning research” by KEIT (Korea Evaluation Institute of Industrial Technology). ","Al-Nawayseh M., Fintech in COVID-19 and Beyond: What Factors are Affecting Customers’ Choice of FinTech Applications?, Journal of Open Innovation: Technology, Market, and Complexity, 6, 4, pp. 1-15, (2020); Allums S., Designing Mobile Payment Experiences: Principles and Best Practices for Mobile Commerce, (2014); Baxter R., Your Customers Will Never Want to Leave, The Forever Transaction; How to Build a Subscription Model so Compelling, (2020); Botsman R., Who Can You Trust? How Technology Brought Us Together–and Why It Could Drive us Apart, (2017); Chomsky N., Requiem for the American Dream: The 10 Principles of Concentration of Wealth & Power, (2017); Christensen C., Ojomo E., Dillon K., The Prosperity Paradox: How Innovation Can Lift Nations out of Poverty, (2019); Christophers B., The Limits to Financialization, Dialogues in Human Geography, 5, 2, pp. 183-200, (2015); Cooke P., Regionally Asymmetric Knowledge Capabilities and Open Innovation: Exploring ‘Globalisation 2’–A New Model of Industry Organisation, Research Policy, 34, 8, pp. 1128-1149, (2005); Dahlberg T., Guo J., Ondrus J., A Critical Review of Mobile Payment Research, Electronic Commerce Research and Applications, 14, 5, pp. 265-284, (2015); Diamond J., Robinson J., (2010); Diamond J., Robinson J., Natural Experiments of History, (2010); Dittrich K., Duysters G., Networking as a Means to Strategy Change: The Case of Open Innovation in Mobile Telephony, Journal of Product Innovation Management, 24, 6, pp. 510-521, (2007); Dore R., Financialization of the Global Economy, Industrial and Corporate Change, 17, 6, pp. 1097-1112, (2008); Dunning T., Natural Experiments in the Social Sciences: A Design-Based Approach, (2012); Evans D., Schmalensee R., Matchmakers: The New Economics of Multisided Platforms, (2016); Ferguson N., The Ascent of Money: A Financial History of the World, (2008); Flick U., Doing Interview Research: The Essential How to Guide, (2021); Gary Silverman J., (2021); Gerpott T., Kornmeier K., Determinants of Customer Acceptance of Mobile Payment Systems, International Journal of Electronic Finance, 3, 1, pp. 1-30, (2009); Goldfinch P., A Global Guide to Fintech and Future Payment Trends, (2018); Gomber P., Koch J., Siering M., Digital Finance and FinTech: Current Research and Future Research Directions, Journal of Business Economics, 87, 5, pp. 537-580, (2017); Herzberg A., Payments and Banking with Mobile Personal Devices, Communications of the ACM, 46, 5, pp. 53-58, (2003); Jeon S., Pak D., An Exploratory Study on Fintech Regulations and Start-ups: Focusing on the US, China, and Korea Cases, Asia-Pacific Journal of Business Venturing and Entrepreneurship, 15, 1, pp. 45-57, (2020); Karnouskos S., Mobile Payment: A Journey Through Existing Procedures and Standardization Initiatives, IEEE Communications Surveys & Tutorials, 6, 4, pp. 44-66, (2004); Khan A., Ali A., Factors Affecting Retailer’s Adoption of Mobile Payment Systems: A SEM-Neural Network Modeling Approach, Wireless Personal Communications, 103, 3, pp. 2529-2551, (2018); Kim C., Mirusmonov M., Lee I., An Empirical Examination of Factors Influencing the Intention to Use Mobile Payment, Computers in Human Behavior, 26, 3, pp. 310-322, (2010); Kim E., Shin K., Evolution of Open Innovation by Value-Based Network Perspective: The Case of Korean Smart Home Industry, Science, Technology and Society, 26, 2, pp. 223-241, (2021); Lapavitsas C., Theorizing Financialization, Work, Employment and Society, 25, 4, pp. 611-626, (2011); Leckel A., Veilleux S., Dana L., Local Open Innovation: A Means for Public Policy to Increase Collaboration for Innovation in SMEs, Technological Forecasting and Social Change, 153, (2020); 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Puschmann T., Fintech, Business & Information Systems Engineering, 59, 1, pp. 69-76, (2017); Shin Y., Choi Y., Feasibility of the FinTech Industry as an Innovation Platform for Sustainable Economic Growth in Korea, Sustainability, 11, 19, (2019); Sumanjeet S., Emergence of Payment Systems in the Age of Electronic Commerce: The State of Art, Global Journal of International Business Research, 2, (2009); Thakor A., Fintech and Banking: What do We Know?, Journal of Financial Intermediation, 41, (2020); Todtling F., Prud'homme van Reine P., Dorhofer S., Open Innovation and Regional Culture–Findings from Different Industrial and Regional Settings, European Planning Studies, 19, 11, pp. 1885-1907, (2011); Torkkeli M., Kotonen T., Ahonen P., Regional Open Innovation System as a Platform for SMEs: A Survey, International Journal of Foresight and Innovation Policy, 3, 4, pp. 336-350, (2007); Tsai W., Huang B., Liu J., Tsaur T., Lin S., The Application of Web ATMs in e-Payment Industry: A Case Study, Expert Systems with Applications, 37, 1, pp. 587-597, (2010); Turban E., Brahm J., Smart Card-Based Electronic Card Payment Systems in the Transportation Industry, Journal of Organizational Computing and Electronic Commerce, 10, 4, pp. 281-293, (2000); Van der Zwan N., Making Sense of Financialization, Socio-Economic Review, 12, 1, pp. 99-129, (2014); Vlaisavljevic V., Medina C., Van Looy B., The Role of Policies and the Contribution of Cluster Agency in the Development of Biotech Open Innovation Ecosystem, Technological Forecasting and Social Change, 155, (2020); Wang C., Quan X., The Effect of R&D Alliance Diversity and Network Position on Firm Innovation Performance: Evidence from the Emerging Biotechnology Industry, Science, Technology and Society, 22, 3, pp. 407-424, (2017); Yang S., Lu Y., Gupta S., Cao Y., Zhang R., Mobile Payment Services Adoption Across Time: An Empirical Study of the Effects of Behavioral Beliefs, Social Influences, and Personal Traits, Computers in Human Behavior, 28, 1, pp. 129-142, (2012); Yun J., How do we Conquer the Growth Limits of Capitalism? Schumpeterian Dynamics of Open Innovation, Journal of Open Innovation: Technology, Market, and Complexity, 1, 2, (2015); Yun J., Zhao X., Ma L., Xu Z., Liu Z., (2020)","J.J. Yun; DGIST, and Open Innovation Academy of SOI, Daegu, South Korea; email: jhyun@dgist.ac.kr",null,"Routledge",{"$nulls":5},9654313.0,null,null,null,"English","Eur. Plann. Stud.","Article","Final",null,"Scopus","2-s2.0-85139845402"]
["Buldeo Rai H.; Dablanc L.","Buldeo Rai, Heleen (57195135422); Dablanc, Laetitia (15118955600)","57195135422; 15118955600","Hunting for treasure: a systematic literature review on urban logistics and e-commerce data",2023.0,"Transport Reviews",43.0,2.0,null,204.0,233.0,29.0,12.0,"10.1080/01441647.2022.2082580","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85131349435&doi=10.1080%2f01441647.2022.2082580&partnerID=40&md5=c47a946c4f8298d01ef43454caf06624","Logistics City Chair, Univ Gustave Eiffel, Champs-sur-Marne, France","Buldeo Rai H., Logistics City Chair, Univ Gustave Eiffel, Champs-sur-Marne, France; Dablanc L., Logistics City Chair, Univ Gustave Eiffel, Champs-sur-Marne, France","Online retail channels increasingly shape consumers’ purchase behaviour: we access a diversity of product types through web-shops; employ both smartphones and digital screens in stores; navigate the retail space by browsing online; and order pantry items, fresh groceries as well as prepared foods to be delivered at our doorsteps. The profound impact of online retail on mobility in cities, where the concentration of consumers resides, is, therefore, an extensively investigated and growing topic of interest in research. In the field of urban logistics, studies that evaluate the various impacts of e-commerce or propose efficiency or sustainability-enhancing applications are plentiful. Regardless, the general lack of solid urban e-commerce logistics data is supported widely. In this study, we systematically review the literature to identify and compare the types of e-commerce data that are currently known, employed and disclosed in urban logistics research as well as the data sources that provide access to them. Within the set of identified data, knowledge concentrates on consumer preferences and number of deliveries related to e-commerce. However, our findings confirm the general data paucity, specifically on delivery trip-related information such as deliveries per trip, number of delivery rounds and vehicle specificities. Discrepancies are found in methodologies to collect and compile data, as well as data units used (e.g., orders, parcels, deliveries) that cause large variations in information possibly diverging from reality. The study contributes to current literature and practice by compiling and analysing currently available data on urban e-commerce logistics and by presenting recommendations and best practices for future enhancements in this research field. Based on the systematic literature review, we propose a common data agenda for urban e-commerce logistics research, focused on addressing data gaps and topics that are under-developed and un-developed; pursuing data collection standardisation; disclosing data collection methodologies and sources; and specifying temporal and spatial information as well as units of data. Some data methodologies and sources can be recommended for future research: using interviews to collect quantitative data; collaborating with sector organisations; exploring open maps; employing existing household and time use surveys; and leveraging technological opportunities and new ways of collecting data. © 2022 Informa UK Limited, trading as Taylor & Francis Group.","City logistics; E-commerce data; E-commerce mobility; Urban freight transport; Urban logistics","electronic commerce; freight transport; literature review; logistics; urban transport",{"$nulls":6},"(2018); Akeb H., Moncef B., Durand B., Building a collaborative solution in dense urban city settings to enhance parcel delivery: An effective crowd model in Paris, Transportation Research Part E: Logistics and Transportation Review, 119, pp. 223-233, (2018); Allen J., Piecyk M., Piotrowska M., McLeod F., Cherrett T., Ghali K., Austwick M., Understanding the impact of e-commerce on last-mile light goods vehicle activity in urban areas: The case of London, Transportation Research Part D: Transport and Environment, 61, pp. 325-338, (2018); Alves R., Lima R.D.S., de Sena D.C., de Pinho A.F., Holguin-Veras J., Agent-based simulation model for evaluating urban freight policy to e-commerce, Sustainability, 11, 15, pp. 1-19, (2019); Arnold F., Cardenas I., Sorensen K., Dewulf W., Simulation of B2C e-commerce distribution in Antwerp using cargo bikes and delivery points, European Transport Research Review, 10, 2, (2018); Beckers J., Cardenas I., Verhetsel A., Identifying the geography of online shopping adoption in Belgium, Journal of Retailing and Consumer Services, 45, pp. 33-41, (2018); Bergmann F.M., Wagner S.M., Winkenbach M., Integrating first-mile pickup and last-mile delivery on shared vehicle routes for efficient urban e-commerce distribution, Transportation Research Part B: Methodological, (2020); Bjorgen A., Bjerkan K.Y., Hjelkrem O.A., E-groceries: Sustainable last mile distribution in city planning, Research in Transportation Economics, (2019); Buldeo Rai H., Verlinde S., Macharis C., City logistics in an omnichannel environment. The case of Brussels, Case Studies on Transport Policy, (2019); Cardenas I., Beckers J., Vanelslander T., E-commerce last-mile in Belgium: Developing an external cost delivery index, Research in Transportation Business and Management, 24, January, pp. 123-129, (2017); Cardenas I., Dewulf W., Vanelslander T., Smet C., Beckers J., The e-commerce parcel delivery market and the implications of home B2C deliveries vs pick-up points, International Journal of Transport Economics, 44, 2, pp. 1724-2185, (2017); Carotenuto P., Gastaldi M., Giordani S., Rossi R., Rabachin A., Salvatore A., Comparison of various urban distribution systems supporting e-commerce. 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Revista Brasileira de Gestão Urbana, 11, pp. 1-17, (2019); Deutsch Y., Golany B., A parcel locker network as a solution to the logistics last mile problem, International Journal of Production Research, 56, 1-2, pp. 251-261, (2018); (2019); Fink A., (2013); Gardrat M., Toilier F., Patier D., Routhier J.-L., (2016); Gatta V., Marcucci E., Nigro M., Patella S.M., Serafin S., Public transport-based crowdshipping for sustainable city logistics: Assessing economic and environmental impacts, Sustainability, 11, 145, pp. 1-14, (2018); Gatta V., Marcucci E., Nigro M., Serafini S., Sustainable urban freight transport adopting public transport-based crowdshipping for B2C deliveries, European Transport Research Review, 11, 13, pp. 1-14, (2019); Guo J., Wang X., Fan S., Gen M., Forward and reverse logistics network and route planning under the environment of low-carbon emissions: A case study of Shanghai fresh food e-commerce enterprises, Computers and Industrial Engineering, 106, pp. 351-360, (2017); Guo X., Jaramillo Y.J.L., Bloemhof-Ruwaard J., Claassen G.D.H., On integrating crowdsourced delivery in last-mile logistics: A simulation study to quantify its feasibility, Journal of Cleaner Production, 241, (2019); Heitz A., Launay P., Beziat A., Heterogeneity of logistics facilities: An issue for a better understanding and planning of the location of logistics facilities, European Transport Research Review, 11, 5, (2019); Holguin-Veras J., Ramirez-Rios D., Kalahasthi L., Amaral J.C., (2019); Huang Y., Savelsbergh M., Zhao L., Designing logistics systems for home delivery in densely populated urban areas, Transportation Research Part B: Methodological, 115, pp. 95-125, (2018); Iwan S., Kijewska K., Lemke J., Analysis of parcel lockers’ efficiency as the last mile delivery solution–The results of the research in Poland, Transportation Research Procedia, 12, pp. 644-655, (2016); Jaller M., Pahwa A., Evaluating the environmental impacts of online shopping: A behavioral and transportation approach, Transportation Research Part D: Transport and Environment, 80, (2020); 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Mangiaracina R., Marchet G., Perotti S., Tumino A., A review of the environmental implications of B2C e-commerce: A logistics perspective, International Journal of Physical Distribution & Logistics Management, 45, 6, pp. 565-591, (2015); McDonald N., Yuan Q., Naumann R., Urban freight and road safety in the era of e-commerce, Traffic Injury Prevention, 20, 7, pp. 764-770, (2019); Melo S., Baptista P., Evaluating the impacts of using cargo cycles on urban logistics: Integrating traffic, environmental and operational boundaries, European Transport Research Review, 9, 30, (2017); Morganti E., Dablanc L., Fortin F., Final deliveries for online shopping: The deployment of pickup point networks in urban and suburban areas, Research in Transportation Business and Management, 11, pp. 23-31, (2014); Moroz M., Polkowski Z., The last mile issue and urban logistics: Choosing parcel machines in the context of the ecological attitudes of the Y generation consumers purchasing online, Transportation Research Procedia, (2016); Moshref-Javadi M., Hemmati A., Winkenbach M., A truck and drones model for last-mile delivery: A mathematical model and heuristic approach, Applied Mathematical Modelling, (2020); Oliveira L.K.D., Morganti E., Dablanc L., Oliveira R.L.M.D., Analysis of the potential demand of automated delivery stations for e-commerce deliveries in Belo Horizonte, Brazil, Research in Transportation Economics, (2017); Pan S., Chen C., Zhong R.Y., Pan S., Chen C., Zhong R.Y., A crowdsourcing solution to collect e-commerce reverse flows in metropolitan areas, Incom2015, pp. 2058-2063, (2015); Perboli G., Rosano M., Saint-Guillain M., Rizzo P., Simulation-optimisation framework for city logistics: An application on multimodal last-mile delivery, IET Intelligent Transport Systems, 12, 4, pp. 262-269, (2018); Petticrew M., Systematic reviews from astronomy to zoology: Myths and misconceptions, BMJ (Clinical Research Ed), 322, 7278, pp. 98-101, (2001); (2018); Rajan J., Rajesh B., Sustainable performance of cargo bikes to improve the delivery time using traffic simulation model, FME Transactions, 48, pp. 411-418, (2020); Rosano M., Demartini C.G., Lamberti F., Perboli G., A mobile platform for collaborative urban freight transportation, Transportation Research Procedia, 30, pp. 14-22, (2018); Serafini S., Nigro M., Gatta V., Marcucci E., Sustainable crowdshipping using public transport: A case study evaluation in Rome, Transportation Research Procedia, 30, pp. 101-110, (2018); Seuring S., Gold S., Seuring S., Gold S., (2012); Simoni M.D., Marcucci E., Gatta V., Claudel C.G., Potential last-mile impacts of crowdshipping services: A simulation-based evaluation, Transportation, (2019); Sutton A.J., Abrams K.R., Jones D.R., Sheldon T.A., Song F., Systematic reviews of trials and other studies, Health Technology Assessment, 2, 19, pp. 111-272, (1998); Wang C., Zhou Y., Deliveries to residential units: A rising form of freight transportation in the U.S, Transportation Research Part C: Emerging Technologies, 58, pp. 46-55, (2015); Wang Y., Zhang D., Liu Q., Shen F., Lee L.H., Towards enhancing the last-mile delivery: An effective crowd-tasking model with scalable solutions, Transportation Research Part E: Logistics and Transportation Review, 93, pp. 279-293, (2016); Xue S., Li G., Yang L., Liu L., Nie Q., Mehmood M.S., Spatial pattern and influencing factor analysis of attended collection and delivery points in Changsha City, China. Chinese Geographical Science, 29, 6, pp. 1078-1094, (2019); Yuen K.F., Wang X., Ng L.T.W., Wong Y.D., An investigation of customers’ intention to use self-collection services for last-mile delivery, Transport Policy, 66, pp. 1-8, (2018); Zhang L., Matteis T., Thaller C., Liedtke G., Simulation-based assessment of cargo bicycle and pick-up point in urban parcel delivery, Procedia Computer Science, 130, pp. 18-25, (2018); Zhou L., Baldacci R., Vigo D., Wang X., A multi-depot two-echelon vehicle routing problem with delivery options arising in the last mile distribution, European Journal of Operational Research, (2018)","H. Buldeo Rai; Logistics City Chair, Univ Gustave Eiffel, Champs-sur-Marne, 6–8 Avenue Blaise Pascal, 77420, France; email: heleen.buldeo-rai@univ-eiffel.fr",null,"Routledge",{"$nulls":5},1441647.0,null,null,null,"English","Transp. Rev.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85131349435"]
["Kiani Mavi R.; Kiani Mavi N.; Olaru D.; Biermann S.; Chi S.","Kiani Mavi, Reza (37073094400); Kiani Mavi, Neda (55957551100); Olaru, Doina (6603617344); Biermann, Sharon (6701698925); Chi, Sae (57218679579)","37073094400; 55957551100; 6603617344; 6701698925; 57218679579","Innovations in freight transport: a systematic literature evaluation and COVID implications",2022.0,"International Journal of Logistics Management",33.0,4.0,null,1157.0,1195.0,38.0,9.0,"10.1108/IJLM-07-2021-0360","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85129173376&doi=10.1108%2fIJLM-07-2021-0360&partnerID=40&md5=373d01f15979101a515e60396fdc6b8c","Faculty of Business and Law, Edith Cowan University, Joondalup, Australia; Business School, The University of Western Australia, Perth, Australia; Planning and Transport Research Centre, The University of Western Australia, Perth, Australia","Kiani Mavi R., Faculty of Business and Law, Edith Cowan University, Joondalup, Australia; Kiani Mavi N., Faculty of Business and Law, Edith Cowan University, Joondalup, Australia; Olaru D., Business School, The University of Western Australia, Perth, Australia; Biermann S., Planning and Transport Research Centre, The University of Western Australia, Perth, Australia; Chi S., Planning and Transport Research Centre, The University of Western Australia, Perth, Australia","Purpose: This paper systematically evaluates the existing literature of innovations in freight transport, including all modes, to uncover the key research themes and methodologies employed by researchers to study innovations and their implications in this industry. It analyses the role of transport and the impact of innovations during crises, such as COVID-19. Design/methodology/approach: Qualitative and quantitative analysis of the innovations in freight transport unravels the pre-requisites of such endeavours in achieving a resilient and sustainable transport network that effectively and efficiently operates during a crisis. The authors performed keyword co-occurrence network (KCON) analysis and research focus parallelship network (RFPN) analysis using BibExcel and Gephi to determine the major resulting research streams in freight transport. Findings: The RFPN identified five emerging themes: transport operations, technological innovation, transport economics, transport policy and resilience and disaster management. Optimisation and simulation techniques, and more recently, artificial intelligence and machine learning (ML) approaches, have been used to model and solve freight transport problems. Automation innovations have also penetrated freight and supply chains. Information and communication technology (ICT)-based innovations have also been found to be effective in building resilient supply chains. Research limitations/implications: Given the growth of e-commerce during COVID-19 and the resulting logistics demand, along with the need for transporting food and medical emergency products, the role of automation, optimisation, monitoring systems and risk management in the transport industry has become more salient. Transport companies need to improve their operational efficiency using innovative technologies and data science for informed decision-making. Originality/value: This paper advises researchers and practitioners involved in freight transport and innovation about main directions and gaps in the field through an integrated approach for evaluating research undertaken in the area. This paper also highlights the role of crisis, e.g. COVID-19, and its impacts on freight transport. Major contributions of this paper are as follows: (1) a qualitative and quantitative, systematic and effective assessment of the literature on freight transport through a network analysis of keywords supplemented by a review of the text of 148 papers; (2) unravelling major research areas; (3) identifying innovations in freight transport and their classification as technological and non-technological and (4) investigating the impact of crises and disruptions in freight transport. © 2022, Emerald Publishing Limited.","Co-occurrence analysis; COVID-19; Crisis; Freight transport; Innovation; Network analysis; Systematic literature evaluation",{"$nulls":7},{"$cut":{"chars":30727,"head":"Adams T.M., Bekkem K.R., Toledo-Duran E.J., Freight resilience measures, Journal of Transportation Engineering, 138, pp. 1403-1409, (2012); Agbo A.A., Li W., Zheng L., Zhang Y., Atombo C., Optimisation of intermodal freight transport network, European Transport - Trasporti Europei, 63, pp. 1-19, (2017); Alessandrini A., Filippi F., Ortenzi F., Orecchini F., Evaluation of a multipurpose hybrid vehicle concept, World Electric Vehicle Journal, 4, pp. 1-9, (2011); Aloi A., Alonso B., Benavente J., Cordera R., Echaniz E., Gonzalez F., Ladisa C., Lezama-Romanelli R., Lopez-Parra A., Mazzei V., Perrucci L., Prieto-Quintana D., Rodriguez A., Sanudo R., Effects of the COVID-19 lockdown on urban mobility: empirical evidence from the city of Santander (Spain), Sustainability, 12, 9, (2020); Altig D., Baker S., Barrero J.M., Bloom N., Bunn P., Chen S., Davis S.J., Leather J., Meyer B., Mihaylov E., Mizen P., Parker N., Renault T., Smietanka P., Thwaites G., Economic uncertainty before and during the COVID-19 pandemic, Journal of Public Economics, 191, (2020); Ambra T., Caris A., Macharis C., Towards freight transport system unification: reviewing and combining the advancements in the physical internet and synchromodal transport research, International Journal of Production Research, 57, 6, pp. 1606-1623, (2019); Andersson M., Sternberg H., Implications of mobile devices on ITS freight roadmaps ahead, World Journal of Science Technology and Sustainable Development, 10, pp. 152-162, (2013); Ashraf M.H., Yalcin M.G., Zhang J., Ozpolat K., Is the US 3PL industry overcoming paradoxes amid the pandemic?, The International Journal of Logistics Management, (2021); Australian transport assessment and planning guidelines: T2 cost benefit analysis, (2018); Baldini G., Nai Fovino I., Masera M., Luise M., Pellegrini V., Bagagli E., Rubino G., Malangone R., Stefano M., Senesi F., An early warning system for detecting GSM-R wireless interference in the high-speed railway infrastructure, International Journal of Critical Infrastructure Protection, 3, pp. 140-156, (2010); Barrett C.B., Actions now can curb food systems fallout from COVID-19, Nature Food, 1, 6, pp. 319-320, (2020); Barua L., Zou B., Zhou Y., Machine learning for international freight transportation management: a comprehensive review, Research in Transportation Business and Management, 34, (2020); Bastug S., Yercan F., An explanatory approach to assess resilience: an evaluation of competitive priorities for logistics organizations, Transport Policy, 103, pp. 156-166, (2021); Bassett H.R., Lau J., Giordano C., Suri S.K., Advani S., Sharan S., Preliminary lessons from COVID-19 disruptions of small-scale fishery supply chains, World Development, 143, (2021); Behiri W., Belmokhtar-Berraf S., Chu C., Urban freight transport using passenger rail network: scientific issues and quantitative analysis, Transportation Research Part E: Logistics and Transportation Review, 115, pp. 227-245, (2018); Bektas T., Ehmke J.F., Psaraftis H.N., Puchinger J., The role of operational research in green freight transportation, European Journal of Operational Research, 274, pp. 807-823, (2019); Benantar A., Abourraja M.N., Boukachour J., Boudebous D., Duvallet C., On the integration of container availability constraints into daily drayage operations arising in France: modelling and optimization, Transportation Research Part E: Logistics and Transportation Review, 140, (2020); Besinovic N., Resilience in railway transport systems: a literature review and research agenda, Transport Reviews, 40, pp. 457-478, (2020); Blesz A.E.J., Sellitto M.A., Ferreira A.R., Herrmann F.F., Sell C.L., Ramos P.V., Dos Santos Gruginskie L.A., Innovation in the road freight transport market: case studies, Interciencia, 42, 10, pp. 692-697, (2017); Bontekoning Y.M., Macharis C., Trip J.J., Is a new applied transportation research field emerging?––a review of intermodal rail–truck freight transport literature, Transportation Research Part A: Policy and Practice, 38, pp. 1-34, (2004); Bravo J.J., Vidal C.J., Freight transportation func"}},"R. Kiani Mavi; Faculty of Business and Law, Edith Cowan University, Joondalup, Australia; email: r.kianimavi@ecu.edu.au",null,"Emerald Publishing",{"$nulls":5},9574093.0,null,null,null,"English","Int. J. Logist. Manage.","Article","Final",null,"Scopus","2-s2.0-85129173376"]
["Elhan-Kayalar Y.; Sawada Y.; van der Meulen Rodgers Y.","Elhan-Kayalar, Yesim (57981356200); Sawada, Yasuyuki (14020518200); van der Meulen Rodgers, Yana (6602496860)","57981356200; 14020518200; 6602496860","Gender, entrepreneurship, and coping with the COVID-19 pandemic: The case of GoFood merchants in Indonesia",2022.0,"Asia and the Pacific Policy Studies",9.0,3.0,null,222.0,245.0,23.0,3.0,"10.1002/app5.362","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85143767256&doi=10.1002%2fapp5.362&partnerID=40&md5=3acf181806843c875874c540654b5ca1","Economic Research and Regional Cooperation Department, Asian Development Bank, Manila, Philippines; Faculty of Economics, University of Tokyo, Tokyo, Japan; School of Management & Labor Relations, Rutgers University, Piscataway, NJ, United States","Elhan-Kayalar Y., Economic Research and Regional Cooperation Department, Asian Development Bank, Manila, Philippines; Sawada Y., Faculty of Economics, University of Tokyo, Tokyo, Japan; van der Meulen Rodgers Y., School of Management & Labor Relations, Rutgers University, Piscataway, NJ, United States","This paper examines business performance and crisis-mitigation strategies among micro, small, and medium-sized enterprises (MSMEs) in Indonesia during the COVID-19 pandemic. We utilise a new primary dataset based on administrative records, survey data, and follow-up interviews with merchants using the digital application GoFood, an on-demand cooked food delivery service. Three empirical findings emerge: first, the overall employment size of women-owned businesses shrank more than men-owned businesses after the onset of the pandemic; second, women were more likely than men to cut personal expenditures and use government assistance as crisis-mitigation strategies; and third, competition increased sharply as new merchants entered the platform, with the service areas of both incumbents and entrants shrinking over time. These results have implications for policies on womenʼs entrepreneurship, the uptake of business development services, and financing programs for MSMEs. © 2022 Asian Development Bank and Asian Development Bank Institute. Asia & the Pacific Policy Studies published by Crawford School of Public Policy of the Australian National University and John Wiley & Sons Australia, Ltd.","COVID-19; digitalisation; e-commerce; MSMEs; women",{"$nulls":5},"International Labour Process Conference; SMERU Research Institute; Asian Development Bank, ADB","The authors would like to thank GoJek Indonesia for collaboration on this study. They would like to acknowledge SMERU Research Institute, Takahiro Yabe, and Zixu Chen for their research assistance. The authors also thank the participants at the Asian Development Bank Instituteʼs 2021 Conference on The Social and Economic Impact of Online Commerce on Women, and the 2022 International Labour Process Conference, for their helpful feedback. The views expressed in this publication are those of the authors and do not necessarily reflect the views and policies of the Asian Development Bank, its Board of Governors, or the governments they represent. Any remaining errors are the authorsʼ responsibility. No funding or grant has been received for this research.","Asian Economic Integration Report 2021, (2021); Berry S.T., Waldfogel J., Free entry and social inefficiency in radio broadcasting, The RAND Journal of Economics, 30, 3, pp. 397-420, (1999); Esquivias M.A., Sethi N., Ramandha M.D., Jayanti A.D., Financial inclusion dynamics in Southeast Asia: An empirical investigation on three countries, Business Strategy & Development, 4, 2, pp. 203-215, (2021); Fafchamps M., Lund S., Risk-sharing networks in rural Philippines, Journal of Development Economics, 71, 2, pp. 261-287, (2003); Gibson J., Olivia S., Direct and indirect effects of Covid-19 on life expectancy and poverty in Indonesia, Bulletin of Indonesian Economic Studies, 56, 3, pp. 325-344, (2020); Women and e-commerce in Southeast Asia, (2021); Care work and care jobs for the future of decent work, (2018); The COVID-19 response: Getting gender equality right for a better future for women at work, (2020); Jappelli T., Pistaferri L., The economics of consumption: Theory and evidence, (2017); Kabeer N., Razavi S., Rodgers Y., Feminist economic perspectives on the COVID-19 pandemic, Feminist Economics, 27, 1-2, pp. 1-29, (2021); Kawaguchi K., Shum M., Uetake K., On the optimal food delivery platform size: Evidence from Indonesia using administrative data, (2021); Food delivery platforms in South-East Asia: January 2022, (2022); Morgan P., Trinh L., Impacts of COVID-19 on households in ASEAN countries and their implications for human capital development, (2021); Olivia S., Gibson J., Nasrudin R., Indonesia in the time of Covid-19, Bulletin of Indonesian Economic Studies, 56, 2, pp. 143-174, (2020); Most used app for food delivery orders in Indonesia as of August 2021, (2021); Roser M., Ritchie H., Ortiz-Ospina E., Hasell J., Coronavirus pandemic (COVID-19), (2021); Samphantharak K., Townsend R.M., Households as corporate firms: An analysis of household finance using integrated household surveys and corporate financial accounting, (2009); Sawada Y., Preferences, behavior, and welfare outcomes against disasters: A review, Handbook on the Economics of Disasters, (2022); Sihotang J., Puspokusumo R.A.A.W., Sun Y., Munandar D., Core competencies of women entrepreneur in building superior online business performance in Indonesia, Management Science Letters, 10, 7, pp. 1607-1612, (2020); Sparrow R., Dartanto T., Hartwig R., Indonesia under the new normal: Challenges and the way ahead, Bulletin of Indonesian Economic Studies, 56, 3, pp. 269-299, (2020); Online food delivery: Indonesia, (2022); Suryahadi A., Al Izzati R., Suryadarma D., Estimating the impact of Covid-19 on poverty in Indonesia, Bulletin of Indonesian Economic Studies, 56, 2, pp. 175-192, (2020); Tambunan T., The impact of the economic crisis on micro, small, and medium enterprises and their crisis mitigation measures in Southeast Asia with reference to Indonesia, Asia & the Pacific Policy Studies, 6, 1, pp. 19-39, (2019); Temenggung D., Saputro A., Rinaldi R., Pane D., Managing recovery and seizing reform opportunities, Bulletin of Indonesian Economic Studies, 57, 1, pp. 1-28, (2021); Townsend R.M., Risk and insurance in village India, Econometrica, 62, 3, pp. 539-591, (1994); Unlocking the lockdown: The gendered effects of COVID-19 on achieving the SDGs in Asia and the Pacific, (2020); Women UN, Leveraging digitalization to cope with COVID-19: An Indonesia case study on women-owned micro and small businesses, (2020); Value creation and capture: Implications for developing countries, (2019); Women entrepreneurs in Indonesia: A pathway to increasing shared prosperity, 2016, (2016); World development indicators, (2022)","Y. Elhan-Kayalar; Economic Research and Regional Cooperation Department, Asian Development Bank, Metro Manila, 6 ADB Avenue, Mandaluyong, 1550, Philippines; email: yelhan@adb.org",null,"John Wiley and Sons Ltd",{"$nulls":5},2.050268E7,null,null,null,"English","Asia Pacafic Policy. Stud.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85143767256"]
["Jeong H.Y.; Song B.D.; Lee S.","Jeong, Ho Young (57208662882); Song, Byung Duk (55320728900); Lee, Seokcheon (7601422142)","57208662882; 55320728900; 7601422142","Optimal scheduling and quantitative analysis for multi-flying warehouse scheduling problem: Amazon airborne fulfillment center",2022.0,"Transportation Research Part C: Emerging Technologies",143.0,null,103831.0,null,null,null,7.0,"10.1016/j.trc.2022.103831","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135819007&doi=10.1016%2fj.trc.2022.103831&partnerID=40&md5=29583d4cb2a9276161d0f9d801e1b1d2","School of Industrial Engineering, Purdue University, 315 N. Grant St., West Lafayette, 47907, IN, United States; Department of Industrial and Management Systems Engineering, Kyung Hee University, 1732 Deogyeong-daero, Giheung-gu, Yongin-si, Gyeonggi-do, South Korea; Department of Big Data Analytics, Graduate School, Kyung Hee University, 1732 Deogyeong-daero, Giheung-gu, Yongin-si, Gyeonggi-do, South Korea","Jeong H.Y., School of Industrial Engineering, Purdue University, 315 N. Grant St., West Lafayette, 47907, IN, United States; Song B.D., Department of Industrial and Management Systems Engineering, Kyung Hee University, 1732 Deogyeong-daero, Giheung-gu, Yongin-si, Gyeonggi-do, South Korea, Department of Big Data Analytics, Graduate School, Kyung Hee University, 1732 Deogyeong-daero, Giheung-gu, Yongin-si, Gyeonggi-do, South Korea; Lee S., School of Industrial Engineering, Purdue University, 315 N. Grant St., West Lafayette, 47907, IN, United States","The outstanding advantages of unmanned aerial vehicles (UAVs) have led to an intensive study of the UAV system over the past decade. A variety of potential UAV applications are emerging nowadays, and UAV delivery is one in the limelight. However, one of the critical issues for UAV delivery service is how UAVs can be persistently used within their fundamental limited battery capacity. One recent approach to alleviate the weaknesses is using a cooperative system of UAVs with movable stations for the delivery logistics. The movable stations move across the field of operation, providing persistent delivery service using UAVs by efficiently replenishing the consumables of UAVs. In this study, one of the compelling cooperative delivery services called the flying warehouse system is investigated. The concept of the flying warehouse delivery service has firstly filed as a patent by the e-commerce giant Amazon. The service utilizes airborne fulfillment centers (AFCs), an airship that floats at an altitude of around 45,000. The airship has stocked with inventory, and when a customer places an order, UAVs fly down and deliver the package. The AFC is a novel delivery system that allows delivery in under 10 min and expands Amazon Prime members' access to UAV shipping. On the other hand, AFC is a challenging system that must extract the simultaneous operating schedule of the different system elements. For this purpose, mixed integer linear programming (MILP) is developed. The proposed MILP enables the derivation of service schedules of multiple AFCs and their components. The validity of the MILP is tested through case studies and quantitatively investigated system managerial issues. In addition, we proposed a clustering-based solution approach to provide computational efficiency for real-world case problems. © 2022 Elsevier Ltd","Airborne fulfillment center; Flying warehouse; Managerial guidelines; Mathematical optimization; Rolling horizon approach; UAV delivery","Airships; Computational efficiency; Integer programming; Lime; Managers; Scheduling; Unmanned aerial vehicles (UAV); Warehouses; Aerial vehicle; Airborne fulfillment center; Delivery service; Flying warehouse; Managerial guideline; Mathematical optimizations; Rolling horizon; Rolling horizon approach; Unmanned aerial vehicle delivery; Vehicle delivery; aircraft; conceptual framework; guideline; numerical model; optimization; quantitative analysis; unmanned vehicle; Antennas",{"$nulls":4},"National Research Foundation of Korea, NRF, (2019R1F1A1060289)","This work was supported by the National Research Foundation of Korea (NRF) funded by the Korea Government under Grant 2019R1F1A1060289. ","Agatz N., Bouman P., Schmidt M., Optimization approaches for the traveling salesman problem with drone, Transport. Sci., 52, 4, pp. 965-981, (2018); (2016); Berg P. W., Isaacs S., Blodgett K.L., (2016); Boysen N., Fedtke S., Schwerdfeger S., Last-mile delivery concepts: a survey from an operational research perspective, OR Spectrum, pp. 1-58, (2020); (2016); Chung S.H., Sah B., Lee J., Optimization for drone and drone-truck combined operations: A review of the state of the art and future directions, Comput. Oper. Res., 123, (2020); De Freitas J.C., Penna P.H.V., A variable neighborhood search for flying sidekick traveling salesman problem, Int. Trans. Oper. Res., 27, 1, pp. 267-290, (2020); Dell'Amico M., Montemanni R., Novellani S., Drone-assisted deliveries: new formulations for the flying sidekick traveling salesman problem, Optim. Lett., pp. 1-32, (2019); (2018); (2012); (2014); (2018); High D. R., Cox D.C., (2020); Jeong H.Y., Song B.D., Lee S., Truck-drone hybrid delivery routing: Payload-energy dependency and No-Fly zones, Int. J. Prod. Econ., 214, pp. 220-233, (2019); Jeong H.Y., Song B.D., Lee S., The Flying Warehouse Delivery System: A Quantitative Approach for the Optimal Operation Policy of Airborne Fulfillment Center, IEEE Trans. Intell. Transport. Syst., 22, 12, pp. 7521-7530, (2021); Li M., Zhen L., Wang S., Lv W., Qu X., Unmanned aerial vehicle scheduling problem for traffic monitoring, Comput. Ind. Eng., 122, pp. 15-23, (2018); Macrina G., Pugliese L.D.P., Guerriero F., Laporte G., Drone-aided routing: A literature review, Transportation Research Part C: Emerging Technologies, 120, (2020); Murray C.C., Chu A.G., The flying sidekick traveling salesman problem: Optimization of drone-assisted parcel delivery, Transportation Research Part C: Emerging Technologies, 54, pp. 86-109, (2015); Oswald E., (2017); Rottondi C., Malandrino F., Bianco A., Chiasserini C.F., Stavrakakis I., Scheduling of emergency tasks for multiservice UAVs in post-disaster scenarios, Comput. Netw., 184, (2021); Song B.D., Park K., Kim J., Persistent UAV delivery logistics: MILP formulation and efficient heuristic, Comput. Ind. Eng., 120, pp. 418-428, (2018); Song B.D., Jun S., Jung H.Y., Lee S., Movable Unmanned Aerial System: Optimization of System, Resource Design and Drone Routing, Procedia Manuf., 39, pp. 300-306, (2019); (2020); Wang K., Pesch E., Kress D., Fridman I., Boysen N., The Piggyback Transportation Problem: Transporting drones launched from a flying warehouse, Eur. J. Oper. Res., 296, 2, pp. 504-519, (2022); Yadav J., Sharma M., A Review of K-mean Algorithm, Int. J. Eng. Trends Technol., 4, 7, pp. 2972-2976, (2013); Yurek E.E., Cenk Ozmutlu H., A decomposition-based iterative optimization algorithm for traveling salesman problem with drone, Transport. Res. Part C: Emerg. Technol., 91, pp. 249-262, (2018)","B.D. Song; Department of Industrial and Management Systems Engineering, Kyung Hee University, Yongin-si, 1732 Deogyeong-daero, Giheung-gu, South Korea; email: bdsong@khu.ac.kr",null,"Elsevier Ltd",{"$nulls":5},"0968090X",null,null,null,"English","Transp. Res. Part C Emerg. Technol.","Article","Final",null,"Scopus","2-s2.0-85135819007"]
["Xu L.; Li F.; Huang K.; Ning J.","Xu, Liyan (57189037543); Li, Fu (57219825720); Huang, Keqing (57930012600); Ning, Jing (57929254900)","57189037543; 57219825720; 57930012600; 57929254900","A Two-Layer Location Choice Model Reveals What’s New in the “New Retail”",2023.0,"Annals of the American Association of Geographers",113.0,3.0,null,635.0,657.0,22.0,1.0,"10.1080/24694452.2022.2115972","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85139946559&doi=10.1080%2f24694452.2022.2115972&partnerID=40&md5=d0590c9bed64adf65be1d21fe918d706","College of Architecture and Landscape Architecture, Peking University, China","Xu L., College of Architecture and Landscape Architecture, Peking University, China; Li F., College of Architecture and Landscape Architecture, Peking University, China; Huang K., College of Architecture and Landscape Architecture, Peking University, China; Ning J., College of Architecture and Landscape Architecture, Peking University, China","The New Retail is an emerging e-commerce model in recent years. It claims innovation in creating competitive advantages through intensive Internet-based data to promote online-to-offline interactions. Whether this self-claimed innovation would cause a different rationale in the choice of store locations is a subject worthy of investigation. In this article, taking Beijing’s Starbucks and Luckin coffee stores as cases, we build a two-layer business location choice model to examine the problem. The model consists of a macroscale (city-wide) submodel and a microscale (street block) submodel. Results show that the macroscale store location choice logics for the two are consistent, with differences predicted by economic geographical laws, thus rejecting the hypothesis of the big-data-driven location choice advantage for the New Retail. Results from the microscale model, however, suggest that the difference between the two brands is better explained with cognition and behavioral theories, where the delivery agents, rather than the customers’ environmental cognition characteristics, shape the New Retail’s peculiar store location preference over less “fancy” urban locales. We argue this unique location preference is indeed something new in the New Retail. We conclude the article with discussions on the relevance of the cognitive and behavioral perspectives in the business location choice problem, and suggest incorporating the microscale layer that explicitly considers these aspects in addressing the problem in real-world settings. © 2022 by American Association of Geographers.","business location choice; consumer preference; Luckin; Starbucks; the New Retail","Beijing [China]; China; business; electronic commerce; industrial location; location decision; location-allocation model; retailing",{"$nulls":6},"Alexander C., A pattern language: Towns, buildings, construction, (1977); Alonso W., Location and land use: Toward a general theory of land rent., (1964); Arentze T.A., Timmermans H.J.P., A spatial decision support system for retail plan generation and impact assessment, Transportation Research Part C: Emerging Technologies, 8, 1-6, pp. 361-380, (2000); Aventze T., Intelligent GIS: Location decisions and strategic planning, Journal of Retailing and Consumer Services, 5, 4, pp. 257-258, (1998); Ballantyne P., Integrating the who, what, and where of U.S. retail center geographies, Annals of the American Association of Geographers.; Batty M., Digital twins, Environment and Planning B: Urban Analytics and City Science, 45, 5, pp. 817-820, (2018); Bell P.A., Green T.C., Fisher J.D., Baum A.S., Environmental psychology, (2001); Berry B.J.L., Garrison W.L., Alternate explanations of urban rank–size relationships, Annals of the Association of American Geographers, 48, 1, pp. 83-91, (1958); Birkin M., Clarke G., Clarke M., Retail location planning in an era of multi-channel growth., (2017); Brown S., Retail location at the micro-scale: Inventory and prospect, The Service Industries Journal, 14, 4, pp. 542-576, (1994); Cairncross F., The death of distance: How the communications revolution is changing our lives, Choice Reviews Online, 39, 5, pp. 39-2883, (2002); Castillo-Manzano J.I., Lopez-Valpuesta L., Urban retail fabric and the metro: A complex relationship. 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Zhou C., Luo Y., Shang Y., Research progress of commercial geography in China, Acta Geographica Sinica, 59, 6, (2004)",null,null,"Taylor and Francis Ltd.",{"$nulls":5},2.4694452E7,null,null,null,"English","Ann.  Am. Assoc. Geogr.","Article","Final",null,"Scopus","2-s2.0-85139946559"]
["Wang Y.; Jing Z.; Lyu J.","Wang, Yanfeng (58032893100); Jing, Zaifang (58032720900); Lyu, Jie (57219256206)","58032893100; 58032720900; 57219256206","Study on Sustainable Development Strategy of Rural E-Commerce in the Northeast of China—A Case Study of 11 Villages, 11 Towns and 4 Counties",2022.0,"Sustainability (Switzerland)",14.0,24.0,16610.0,null,null,null,0.0,"10.3390/su142416610","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85144903414&doi=10.3390%2fsu142416610&partnerID=40&md5=715bff095e784279840625db5a383a07","Agricultural and Forestry Economics and Management, College of Economics and Management, Shenyang Agricultural University, Shenyang, 110866, China","Wang Y., Agricultural and Forestry Economics and Management, College of Economics and Management, Shenyang Agricultural University, Shenyang, 110866, China; Jing Z., Agricultural and Forestry Economics and Management, College of Economics and Management, Shenyang Agricultural University, Shenyang, 110866, China; Lyu J., Agricultural and Forestry Economics and Management, College of Economics and Management, Shenyang Agricultural University, Shenyang, 110866, China","Using field research data from 11 towns and 11 villages in 4 counties of Shenyang, data building, coding and analysis were conducted through Nvivo 11 to distill the influencing factors of rural e-commerce development in Shenyang into advantages, disadvantages, opportunities and threats. Combined with the SWOT-AHP model, the weights of each influencing factor on rural e-commerce development were obtained by scoring by experts from five aspects, including government, enterprises, farmers, etc. The results show that the weak infrastructure and high cost of express delivery are important factors affecting the development of rural e-commerce, confirming the folk experience of “to get rich, first build roads”. At the same time, the awakening of brand awareness and the strengthening of technology services are advantages and opportunities for the development of rural e-commerce. Finally, according to the different combinations of influencing factors, we proposed a breakthrough strategy for rural e-commerce development based on “external help + internal drive”, supplemented by “cooperation + demonstration leading” and “industrial upgrading + channel integration”. © 2022 by the authors.","case study; rural e-commerce; strategic choice; sustainable development; SWOT-AHP","China; Liaoning; Shenyang; electronic commerce; rural area; spatiotemporal analysis; strategic approach; sustainable development",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (71873090); National Key Research and Development Program of China, NKRDPC, (2016YFD0300210)","This research was funded by the National Key Research and Development Program of China, grant number 2016YFD0300210, and the National Natural Science Foundation of China, grant number 71873090.","Li Y., Ke J.S., Three-level digital divide: Income growth and income distribution effects of the rural digital economy, Agric. 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Econ, 8, pp. 119-126, (2019); Wang X.D., Liu Y.H., Analysis of farmers’ willingness and behavioral deviations in e-commerce sales--based on survey data from 54 counties in Jiangxi Province, J. Agric. For. Econ. Manag, 3, pp. 316-325, (2021); Qiu Z.X., Zhou Y.H., Analysis of the mechanism of the role of e-commerce on rural households’ income increase-a micro test based on the effective matching of demand and supply, China Rural. Econ, 4, pp. 36-52, (2021); Zeng Y.W., Guo H.D., Jin S.Q., Is e-commerce beneficial to farmers’ income?—Evidence from Shuyang, Jiangsu, China Rural Econ, 2, pp. 49-64, (2018); Liu J., Yu Y.L., The mediating effect of rural e-commerce on farmers’ income-empirical evidence based on provincial panel data, Bus. Econ. Res, 20, pp. 98-101, (2021); Qin F., Wang J.C., Xu Q., How can the digital economy promote farmers’ income?—Evidence from the development of rural e-commerce, Econ. 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Lyu; Agricultural and Forestry Economics and Management, College of Economics and Management, Shenyang Agricultural University, Shenyang, 110866, China; email: jieluesy@syau.edu.cn",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85144903414"]
["Bhat C.R.","Bhat, Chandra R. (57883776900)",5.78837769E10,"Data Collection Methods and Activity-Travel Behavior Analysis in a Fast Evolving Technological Future",2022.0,"ITE Journal (Institute of Transportation Engineers)",92.0,10.0,null,29.0,33.0,4.0,1.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85152976331&partnerID=40&md5=0bd7ec24ebcf7e52d5ecbbce775ca3f4","New Orleans, LA, United States","Bhat C.R., New Orleans, LA, United States","The past 2 years of COVID have disrupted activity-travel patterns in more ways than one. The typical commute-centered every-weekday individual travel pattern is no longer the usual norm, as individuals increasingly work from different work locations (including home, a third work place, and the regular work place) on different workdays. In addition, COVID has accelerated what was already an increasing e-commerce trend before the pandemic, as individuals and households now make continuous and seamless decisions regarding in-person participations versus virtual participations (the latter of which can still have travel repercussions in the form of, for example, a person trip being replaced by a commodity delivery trip). © 2022 ITE J. All rights reserved.",null,"Activity-travel behavior; Activity-travel patterns; Data collection method; E- commerces; Travel behaviour analysis; Travel patterns; Work place",{"$nulls":6},"Triplett N., The dynamogenic factors in pacemaking and competition, The American Journal of Psychology, 9, 4, pp. 507-533, (1898); Hamilton A.F.D.C., Lind F., Audience effects: What can they tell us about social neuroscience, theory of mind and autism?, Culture and Brain, 4, 2, pp. 159-177, (2016); Ajzen I., Theory of planned behavior, Organizational Behavior and Human Decision Processes, 50, 2, pp. 179-211, (1991); Venkatesh V., Davis F.D., A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies, 46, 2, pp. 186-204, (2000)",null,null,"Institute of Transportation Engineers",{"$nulls":5},1628178.0,null,"ITEJD",null,"English","ITE J","Article","Final",null,"Scopus","2-s2.0-85152976331"]
["Khaliq Z.; Farooq S.U.; Khan D.A.","Khaliq, Zubair (57423387800); Farooq, Sheikh Umar (55259943800); Khan, Dawood Ashraf (35761464100)","57423387800; 55259943800; 35761464100","A deep learning-based automated framework for functional User Interface testing",2022.0,"Information and Software Technology",150.0,null,106969.0,null,null,null,8.0,"10.1016/j.infsof.2022.106969","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85133933090&doi=10.1016%2fj.infsof.2022.106969&partnerID=40&md5=4d5ebb5702050216d90ba1c22512170f","University of Kashmir, India","Khaliq Z., University of Kashmir, India; Farooq S.U., University of Kashmir, India; Khan D.A., University of Kashmir, India","Context: The use of automation tools in software testing helps keep pace with the timeline of the deliverables. Over time with the inclusion of continuous integration/continuous delivery (CI/CD) pipelines, automation tools are becoming less effective. The testing community is turning to AI to help keep the pace. Objective: We study the use of transformers to automate the process of test case generation directly from the User Interface (UI) element description instead of relying on the test specification document from which test cases are extracted manually. We also demonstrate the capability of the proposed approach in repairing flaky tests. Method: We employ object detection algorithms EfficientDet and DEtectionTRansformer for detecting the elements from an application UI automatically without requiring a tester to locate complex-scripted UI elements. We also use Tesseract to automatically identify the text present on the UI elements. We transform the generated UI element description to actual test designer-written test cases using text-generation transformers like GPT-2 and T5. The generated test cases are then translated into executable test scripts using a simple parser. We carry out our cases study on 30 e-commerce applications. Results: The percentage of correct executable test cases generated by the framework employing EfficientDet is 93.82% and employing DEtectionTRansformer is 98.08%. The framework eliminates an average of 96.05% flakiness across the applications selected for the study. Conclusion: It is concluded that the proposed approach can be used with current automation tools in the industry to enhance their capability in generating test cases and repairing the flaky tests. © 2022 Elsevier B.V.","Automated testing; Deep learning; Software testing; Transformers; UI functional testing","Automation; Deep learning; Electric transformer testing; Object detection; Repair; Software testing; Automated testing; Automation tools; Deep learning; Executables; Functional testing; Interface elements; Software testings; Test case; Transformer; User interface functional testing; User interfaces",{"$nulls":6},"Khaliq Z., Farooq S.U., Khan D.A., Artificial intelligence in software testing : Impact, problems, challenges and prospect, (2022); Nguyen B.-N., Robbins B.J., Banerjee I., Memon A., GUITAR: an innovative tool for automated testing of GUI-driven software, Autom. Softw. 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Softw., 171, (2021); Khaliq Z.; Tan M., Pang R., Le Q.V., EfficientDet: Scalable and efficient object detection, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR, pp. 10778-10787, (2020); Carion N., Massa F., Synnaeve G., Usunier N., Kirillov A., Zagoruyko S., End-to-end object detection with transformers, (2020); Vaswani A., Shazeer N., Parmar N., Uszkoreit J., Jones L., Gomez A.N., Kaiser L., Polosukhin I., Attention is all you need, (2017); He K., Zhang X., Ren S., Sun J., Deep Residual Learning for Image Recognition, pp. 770-778, (2016); Radford A., Et al., Language models are unsupervised multitask learners, (2019); Raffel C., Shazeer N., Roberts A., Lee K., Narang S., Matena M., Zhou Y., Li W., Liu P.J., Exploring the limits of transfer learning with a unified text-to-text transformer, (2019); Papineni K., Et al., Bleu: a method for automatic evaluation of machine translation, (2002); Khaliq Z., Farooq S.U., Khan D.A., Transformers for GUI testing: A plausible solution to automated test case generation and flaky tests, Computer, 55, 3, pp. 64-73, (2022); Russakovsky O., Li L.-J., Fei-Fei L., Best of both worlds: Human-machine collaboration for object annotation, 2015 IEEE Conference on Computer Vision and Pattern Recognition, CVPR, pp. 2121-2131, (2015); Labs Q.; Said M.; YANIK M.; Kulkarni A.; Pol S.; Coppola R., Morisio M., Torchiano M., Ardito L., Scripted GUI testing of android open-source apps: Evolution of test code and fragility causes, Empir. Softw. Engg., 24, 5, pp. 3205-3248, (2019); Memon A.M., Banerjee I., Nagarajan A., Ripping G.U.I., (2003); Memon A., Automated gui regression testing using ai planning, pp. 51-99, (2004); Huang S., Cohen M.B., Memon A.M., Repairing GUI test suites using a genetic algorithm, 2010 Third International Conference on Software Testing, Verification and Validation, pp. 245-254, (2010); Marchetto A., Tonella P., Using search-based algorithms for Ajax event sequence generation during testing, Empir. Softw. Eng., 16, pp. 103-140, (2011); Mariani L., Pezze M., Riganelli O., Santoro M., AutoBlackTest: a tool for automatic black-box testing, 2011 33rd International Conference on Software Engineering (ICSE), pp. 1013-1015, (2011); Alegroth E., Feldt R., Kolstrom P., Maintenance of automated test suites in industry: An empirical study on Visual GUI Testing, Inf. Softw. Technol., 73, pp. 66-80, (2016); Nass M., Alegroth E., Feldt R., Why many challenges with GUI test automation (will) remain, Inf. Softw. Technol., 138, (2021); Raina S., Agarwal A.P., An automated tool for regression testing in web applications, SIGSOFT Softw. Eng. Notes, 38, 4, pp. 1-4, (2013); Choudhary S.R., Zhao D., Versee H., Orso A., WATER: Web application TEst repair, ETSE ’11, pp. 24-29, (2011); Brisset S., Rouvoy R., Seinturier L., Pawlak R., Erratum: Leveraging flexible tree matching to repair broken locators in web automation scripts, Inf. Softw. Technol., 144, (2022); Stocco A., Yandrapally R., Mesbah A., Visual web test repair, ESEC/FSE 2018, pp. 503-514, (2018); Chang N., Wang L., Pei Y., Mondal S.K., Li X., Change-based test script maintenance for android apps, 2018 IEEE International Conference on Software Quality, Reliability and Security, QRS, pp. 215-225, (2018)","Z. Khaliq; University of Kashmir, India; email: zikayem@gmail.com",null,"Elsevier B.V.",{"$nulls":5},9505849.0,null,"ISOTE",null,"English","Inf Software Technol","Article","Final",null,"Scopus","2-s2.0-85133933090"]
["Modgil S.; Singh R.K.; Hannibal C.","Modgil, Sachin (55314774400); Singh, Rohit Kumar (56102264100); Hannibal, Claire (57216866815)","55314774400; 56102264100; 57216866815","Artificial intelligence for supply chain resilience: learning from Covid-19",2022.0,"International Journal of Logistics Management",33.0,4.0,null,1246.0,1268.0,22.0,118.0,"10.1108/IJLM-02-2021-0094","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85111098048&doi=10.1108%2fIJLM-02-2021-0094&partnerID=40&md5=bb0eda91ef2721ae1d6b7925cccd9023","Operations Management, International Management Institute – Kolkata, Kolkata, India; Faculty of Business and Law, Liverpool John Moores University, Liverpool, United Kingdom","Modgil S., Operations Management, International Management Institute – Kolkata, Kolkata, India; Singh R.K., Operations Management, International Management Institute – Kolkata, Kolkata, India; Hannibal C., Faculty of Business and Law, Liverpool John Moores University, Liverpool, United Kingdom","Purpose: Many supply chains have faced disruption during Covid-19. Artificial intelligence (AI) is one mechanism that can be used to improve supply chain resilience by developing business continuity capabilities. This study examines how firms employ AI and consider the opportunities for AI to enhance supply chain resilience by developing visibility, risk, sourcing and distribution capabilities. Design/methodology/approach: The authors have gathered rich data by conducting semistructured interviews with 35 experts from the e-commerce supply chain. The authors have adopted a systematic approach of coding using open, axial and selective methods to map and identify the themes that represent the critical elements of AI-enabled supply chain resilience. Findings: The results of the study highlight the emergence of five critical areas where AI can contribute to enhanced supply chain resilience; (1) transparency, (2) ensuring last-mile delivery, (3) offering personalized solutions to both upstream and downstream supply chain stakeholders, (4) minimizing the impact of disruption and (5) facilitating an agile procurement strategy. Research limitations/implications: The study offers interesting implications for bridging the theory–practice gap by drawing on contemporary empirical data to demonstrate how enhancing dynamic capabilities via AI technologies further strengthens supply chain resilience. The study also offers suggestions for utilizing the findings and proposes a framework to strengthen supply chain resilience through AI. Originality/value: The study presents the dynamic capabilities for supply chain resilience through the employment of AI. AI can contribute to readying supply chains to reduce their risk of disruption through enhanced resilience. © 2021, Emerald Publishing Limited.","Covid-19; Dynamic capabilities; Supply chain design; Supply chain resilience",{"$nulls":7},"Adobor H., Supply chain resilience: an adaptive cycle approach, International Journal of Logistics Management, 31, 3, pp. 443-463, (2020); Alora A., Barua M.K., The effect of supply chain disruptions on shareholder wealth in small and mid-cap companies, Supply Chain Management: An International Journal, 26, 2, pp. 212-223, (2020); Barratt M., Choi T.Y., Li M., Qualitative case studies in operations management: trends, research outcomes, and future research implications, Journal of Operations Management, 29, 4, pp. 329-342, (2011); Baryannis G., Validi S., Dani S., Antoniou G., Supply chain risk management and artificial intelligence: state of the art and future research directions, International Journal of Production Research, 57, 7, pp. 2179-2202, (2019); 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A bibliometric review and research agenda, Technological Forecasting and Social Change, (2020); Wamba S.F., Edwards A., Akter S., Social media adoption and use for improved emergency services operations: the case of the NSW SES, Annals of Operations Research, 283, 1-2, pp. 225-245, (2019); Wamba S.F., Queiroz M.M., Wu L., Sivarajah U., Big data analytics-enabled sensing capability and organizational outcomes: assessing the mediating effects of business analytics culture, Annals of Operations Research, (2020); Wang-Mlynek L., Foerstl K., Barriers to multi-tier supply chain risk management, International Journal of Logistics Management, 31, 3, pp. 465-487, (2020); Wen J., He L., Zhu F., Swarm robotics control and communications: imminent challenges for next generation smart logistics, IEEE Communications Magazine, 56, 7, pp. 102-107, (2018); Wollschlaeger M., Sauter T., Jasperneite J., The future of industrial communication: automation networks in the era of the internet of things and industry 4.0, IEEE Industrial Electronics Magazine, 11, 1, pp. 17-27, (2017); Wong C.W., Lirn T.C., Yang C.C., Shang K.C., Supply chain and external conditions under which supply chain resilience pays: an organizational information processing theorization, International Journal of Production Economics, (2020); Alvesson M., Sandberg J., Generating research questions through problematization, Academy of Management Review, 36, 2, pp. 247-271, (2011); Min H., Artificial intelligence in supply chain management: theory and applications, International Journal of Logistics: Research and Applications, 13, 1, pp. 13-39, (2010); Sandberg J., Alvesson M., Ways of constructing research questions: gap-spotting or problematization?, Organization, 18, 1, pp. 23-44, (2011)","S. Modgil; Operations Management, International Management Institute – Kolkata, Kolkata, India; email: s.modgil@imi-k.edu.in",null,"Emerald Publishing",{"$nulls":5},9574093.0,null,null,null,"English","Int. J. Logist. Manage.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85111098048"]
["Guo S.; Singh M.; Goodarzi S.","Guo, Siqiang (57823821000); Singh, Manjeet (57199045224); Goodarzi, Shadi (57204963386)","57823821000; 57199045224; 57204963386","Enhance picking viability in E-commerce warehouses under pandemic",2023.0,"International Journal of Production Research",61.0,15.0,null,5302.0,5321.0,19.0,3.0,"10.1080/00207543.2022.2101400","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135159969&doi=10.1080%2f00207543.2022.2101400&partnerID=40&md5=6622acaf1c3f69af48183f10f9f00cb4","Operations Research and Industrial Engineering, The University of Texas at Austin, Austin, TX, United States; Global Operations Science & Analytics, DHL Supply Chain, Westerville, United States; California State University, Mihaylo College of Business and Economics, Fullerton, CA, United States","Guo S., Operations Research and Industrial Engineering, The University of Texas at Austin, Austin, TX, United States; Singh M., Global Operations Science & Analytics, DHL Supply Chain, Westerville, United States; Goodarzi S., Operations Research and Industrial Engineering, The University of Texas at Austin, Austin, TX, United States, California State University, Mihaylo College of Business and Economics, Fullerton, CA, United States","The COVID-19 pandemic has caused critical challenges for e-commerce warehouses that strive to fulfill surging customer demand while facing a high virus infection risk. Current literature on picking optimization overlooks warehouse safety under pandemic conditions. Meanwhile, scattered storage and zone-wave-batch picking have been used in parallel by many large e-commerce warehouses, these two operational policies have not been considered together in picking optimization studies. This paper fills these gaps by solving an order batching problem considering scattered storage, zone-wave-batch picking, and pickers’ proximity simultaneously. We formulate and solve the mathematical model of the discussed problem and propose the Aisle-Based Constructive Batching Algorithm (ABCBA) to help warehouses pick more efficiently and safely. Experiments with extensive datasets from a major third-party logistics (3PL) company show that, compared to the current picking strategy, ABCBA can reduce the total picking time and the virus infection risk due to pickers’ proximity by 46% and 72%, respectively. Compared to other heuristics like tabu + nLSA3 (Yang, Zhao, and Guo 2020), ABCBA gets better results using less computation time. © 2022 Informa UK Limited, trading as Taylor & Francis Group.","Covid-19 pandemic; e-commerce warehouses; order batching; picking optimization; scattered storage; sustainability","Electronic commerce; Outsourcing; Viruses; Warehouses; 'current; Covid-19 pandemic; Critical challenges; E- commerces; E-commerce warehouse; Optimisations; Order batching; Picking optimization; Scattered storage; Virus infection; Optimization",{"$nulls":6},"Ardjmand E., Singh M., Shakeri H., Tavasoli A., Young II W.A., Mitigating the Risk of Infection Spread in Manual Order Picking Operations: A Multi-Objective Approach, Applied Soft Computing, 100, (2020); Bisschop J., AIMMS Optimization Modeling, (2006); Boysen N., De Koster R., Weidinger F., Warehousing in the e-Commerce era: A Survey, European Journal of Operational Research, 277, 2, pp. 396-411, (2019); (2021); Chia Jane C., Storage Location Assignment in a Distribution Center”, International Journal of Physical Distribution & Logistics Management, 30, 1, pp. 55-71, (2000); Chiang D.M.H., Lin C.P., Chen M.C., The Adaptive Approach for Storage Assignment by Mining Data of Warehouse Management System for Distribution Centres, Enterprise Information Systems, 5, 2, pp. 219-234, (2011); Daniels R.L., Rummel J.L., Schantz R., A Model for Warehouse Order Picking, European Journal of Operational Research, 105, 1, pp. 1-17, (1998); Dauod H., Won D., Real-time Order Picking Planning Framework for Warehouses and Distribution Centres, International Journal of Production Research, pp. 1-20, (2021); De Koster R., Le-Duc T., Roodbergen K.J., Design and Control of Warehouse Order Picking: A Literature Review, European Journal of Operational Research, 182, 2, pp. 481-501, (2007); De Koster M.B.M., Van der Poort E.S., Wolters M., Efficient Order Batching Methods in Warehouses, International Journal of Production Research, 37, 7, pp. 1479-1504, (1999); De Lombaert T., Braekers K., De Koster R., Ramaekers K., In Pursuit of Humanised Order Picking Planning: Methodological Review, Literature Classification and Input from Practice, International Journal of Production Research, pp. 1-31, (2022); D'Haen R., Braekers K., Ramaekers K., Integrated Scheduling of Order Picking Operations Under Dynamic Order Arrivals, International Journal of Production Research, pp. 1-22, (2022); Eidelson J., Soper S., (2020); Gademann A.J.R.M., Van Den Berg J.P., Van Der Hoff H.H., An Order Batching Algorithm for Wave Picking in a Parallel-Aisle Warehouse, IIE Transactions, 33, 5, pp. 385-398, (2001); Gue K.R., Meller R.D., Skufca J.D., The Effects of Pick Density on Order Picking Areas with Narrow Aisles, IIE Transactions, 38, 10, pp. 859-868, (2006); Henn S., Wascher G., Tabu Search Heuristics for the Order Batching Problem in Manual Order Picking Systems, European Journal of Operational Research, 222, 3, pp. 484-494, (2012); Hong S., Order Batch Formations for Less Picker Blocking in a Narrow-Aisle Picking System, Industrial Engineering and Management Systems, 14, 3, pp. 289-298, (2015); Hong S., Johnson A.L., Peters B.A., Batch Picking in Narrow-Aisle Order Picking Systems with Consideration for Picker Blocking, European Journal of Operational Research, 221, 3, pp. 557-570, (2012); Kong X.T., Zhu M., Liu Y., Qin K., Huang G.Q., An Advanced Order Batching Approach for Automated Sequential Auctions with Forecasting and Postponement, International Journal of Production Research, pp. 1-16, (2022); Mellema P.M., Smith C.A., Simulation Analysis of Narrow-Aisle Order Selection Systems, Proceedings of the 20th Conference on Winter Simulation, pp. 597-602, (1988); Morawska L., Tang J.W., Bahnfleth W., Bluyssen P.M., Boerstra A., Buonanno G., Yao M., How Can Airborne Transmission of COVID-19 Indoors be Minimised?, Environment International, 142, (2020); Ntounis N., Mumford C., Lorono-Leturiondo M., Parker C., Still K., How Safe is it to Shop? Estimating the Amount of Space Needed to Safely Social Distance in Various Retail Environments, Safety Science, 132, (2020); (2020); Pan C.H., Liu S.Y., A Comparative Study of Order Batching Algorithms, Omega, 23, 6, pp. 691-700, (1995); Pan J.C.H., Wu M.H., Throughput Analysis for Order Picking System with Multiple Pickers and Aisle Congestion Considerations, Computers & Operations Research, 39, 7, pp. 1661-1672, (2012); Parikh P.J., Meller R.D., A Note on Worker Blocking in Narrow-Aisle Order Picking Systems When Pick Time is non-Deterministic, IIE Transactions, 42, 6, pp. 392-404, (2010); Petersen C.G., Considerations in Order Picking Zone Configuration, International Journal of Operations & Production Management, 22, 7, pp. 793-805, (2002); Petersen C.G., Aase G., A Comparison of Picking, Storage, and Routing Policies in Manual Order Picking, International Journal of Production Economics, 92, 1, pp. 11-19, (2004); Ratliff H.D., Rosenthal A.S., Order-picking in a Rectangular Warehouse: A Solvable Case of the Traveling Salesman Problem, Operations Research, 31, 3, pp. 507-521, (1983); Rosenwein M.B., A Comparison of Heuristics for the Problem of Batching Orders for Warehouse Selection, International Journal of Production Research, 34, 3, pp. 657-664, (1996); Saylam S., Celik M., Sural H., The min–max Order Picking Problem in Synchronised Dynamic Zone-Picking Systems, International Journal of Production Research, pp. 1-19, (2022); Schrotenboer A.H., Wruck S., Roodbergen K.J., Veenstra M., Dijkstra A.S., Order Picker Routing with Product Returns and Interaction Delays, International Journal of Production Research, 55, 21, pp. 6394-6406, (2017); Staudt F.H., Alpan G., Di Mascolo M., Rodriguez C.M.T., Warehouse Performance Measurement: A Literature Review, International Journal of Production Research, 53, 18, pp. 5524-5544, (2015); (2020); Van Gils T., Ramaekers K., Braekers K., Depaire B., Caris A., Increasing Order Picking Efficiency by Integrating Storage, Batching, Zone Picking, and Routing Policy Decisions, International Journal of Production Economics, 197, pp. 243-261, (2018); Vuorinen V., Aarnio M., Alava M., Alopaeus V., Atanasova N., Auvinen M., Osterberg M., Modelling Aerosol Transport and Virus Exposure with Numerical Simulations in Relation to SARS-CoV-2 Transmission by Inhalation Indoors, Safety Science, 130, (2020); Weidinger F., Picker Routing in Rectangular Mixed Shelves Warehouses, Computers & Operations Research, 95, pp. 139-150, (2018); Wruck S., Vis I.F., Boter J., Risk Control for Staff Planning in e-Commerce Warehouses, International Journal of Production Research, 55, 21, pp. 6453-6469, (2017); Yang P., Zhao Z., Guo H., Order Batch Picking Optimization Under Different Storage Scenarios for e-Commerce Warehouses, Transportation Research Part E: Logistics and Transportation Review, 136, (2020); Zhong S., Giannikas V., Merino J., McFarlane D., Cheng J., Shao W., Evaluating the Benefits of Picking and Packing Planning Integration in e-Commerce Warehouses, European Journal of Operational Research, (2021); Zulj I., Kramer S., Schneider M., A Hybrid of Adaptive Large Neighborhood Search and Tabu Search for the Order-Batching Problem, European Journal of Operational Research, 264, 2, pp. 653-664, (2018)","S. Goodarzi; Operations Research and Industrial Engineering, The University of Texas at Austin, Austin, United States; email: goodarzi@utexas.edu",null,"Taylor and Francis Ltd.",{"$nulls":5},207543.0,null,"IJPRB",null,"English","Int J Prod Res","Article","Final",null,"Scopus","2-s2.0-85135159969"]
["Arunkumar A.; Ramabalan S.; Elayaraja D.","Arunkumar, A. (57746714300); Ramabalan, S. (23103952500); Elayaraja, D. (55315041300)","57746714300; 23103952500; 55315041300","Optimum Design of Stair-Climbing Robots Using Taguchi Method",2023.0,"Intelligent Automation and Soft Computing",35.0,1.0,null,1229.0,1244.0,15.0,2.0,"10.32604/iasc.2023.027388","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85132142973&doi=10.32604%2fiasc.2023.027388&partnerID=40&md5=1439c42ab8c977b24dd1c0ecff40cc7c","Department of Mechanical Engineering, E.G.S. Pillay Engineering College, Tamilnadu, Nagapattinam, India; Department of Mechanical Engineering, QIS College of Engineering and Technology, Andhra Pradesh, Ongole, India","Arunkumar A., Department of Mechanical Engineering, E.G.S. Pillay Engineering College, Tamilnadu, Nagapattinam, India; Ramabalan S., Department of Mechanical Engineering, E.G.S. Pillay Engineering College, Tamilnadu, Nagapattinam, India; Elayaraja D., Department of Mechanical Engineering, QIS College of Engineering and Technology, Andhra Pradesh, Ongole, India","Environmental issues like pollution are major threats to human health. Many systems are developed to reduce pollution. In this paper, an optimal mobile robot design to reduce pollution in Green supply chain management system. Green supply chain management involves as similating environmentally and eco-nomically feasible solutions into the supply chain life-cycle. Smartness, advanced technologies, and advanced networks are becoming pillars of a sustainable supply chain management system. At the same time, there is much change happening in the logistics industry. They are moving towards a new logistics model. In the new model, robotic logistics has a vital role. The reasons for this change are the rapid growth of the e-commerce business and the shortage of workers. The advantages of using robotic logistics are reduction in human errors, faster delivery speed, bet-ter customer satisfaction, more safety for workers, and high workforce adaptabil-ity. A robot with rocker-bogie suspension is a six-wheeled mobile platform that has a distinctive potential to keep all wheels on the ground continuously. It has been designed to traverse rough and uneven terrain by distributing the load over its wheels equally. However, there is a limitation to achieving high-speed mobility against vertical barriers. In this research, an optimal design of product delivery wheeled robots for a sustainable supply chain system is proposed to ensure higher adaptability and maximum stability during climbing staircases. The design parameters of the proposed robot are optimized using Taguchi Method. The aim is to get a smooth trajectory of the robot’s center-of-mass. The proposed approach rea-lizes a robot with much-improved stability which can climb over heights more than the size of the wheel (i.e., 3 times the radius of wheels). The results reveal that the modified rocker-bogie system not only increases the stair-climbing cap-ability but also thwarts instability due to overturning of a wheel of the robot. © 2023, Tech Science Press. All rights reserved.","Green supply chain management; optimum design; robotic logistics; rocker-bogie mechanism; stair-climbing wheeled mobile robot; taguchi method",{"$nulls":7},"Battua V. V., Ventayenb R. J. M., Firosc A., Yadav R., Unmanned six-wheel bogie rover with robotic arm for surveillance and fixing objects, Turkish Journal of Computer and Mathematics Education, 12, 10, pp. 2066-2075, (2021); Hamim F. A., Probal I. A., Ahmed A. S., Islam M. A., Siddik M. A. B., An enhanced prototype of rover for space exploration, Advances in Astronautics Science and Technology, 3, 1, pp. 75-96, (2020); Illahi U., Mirf M. S., Maintaining efficient logistics and supply chain management operations during and after coronavirus (COVID-19) pandemic: Learning from the past experiences, Environment, Development and Sustainability, 12, pp. 1-22, (2021); Liu J., Xu L., Chen S., Xu H., Cheng G., Et al., Development of a bio-inspired wall-climbing robot composed of spine wheels, adhesive belts and eddy suction cup, Robotica, 39, 1, pp. 3-22, (2021); Mathiyazhagan K., Nangia S., Senthilkumar A., Elangovan K., Savita K., Et al., Modelling the interrelationship of risks for green supply chain management adoption: A DEMATEL approach, International Journal of Logistics Systems and Management, 30, 3, pp. 414-440, (2020); Qu S., Yang H., Ji Y., Low-carbon supply chain optimization considering warranty period and carbon emission reduction level under cap-and-trade regulation, Environment, Development and Sustainability, 36, pp. 1-28, (2021); Yildizbasi A., Ozturk C., Efendioglu D., Bulkan S., Assessing the social sustainable supply chain indicators using an integrated fuzzy multi-criteria decision-making methods: A case study of Turkey, Environment, Development and Sustainability, 23, pp. 4285-4320, (2021); Li Z., Deng C., Zhao K., Human-cooperative control of a wearable walking exoskeleton for enhancing climbing stair activities, IEEE Transactions on Industrial Electronics, 67, 4, pp. 3086-3095, (2020); Sathiya V., Chinnadurai M., Ramabalan S., Appolloni A., Mobile robots and evolutionary optimization algorithms for green supply chain management in a used-car resale company, Environment, Development and Sustainability, 23, pp. 9110-9138, (2021); Hanafi D., Rahman A., Azlan K., The mobile robot development for air pollution tele data capture, Journal TeknologiElektro, Universitas MercuBuana, 7, 2, pp. 95-100, (2016); Gonzalez-de-Soto M., Emmi L., Benavides C., Garcia I., Reducing air pollution with hybrid-powered robotic tractors for precision agriculture, Biosystems Engineering, 143, pp. 79-94, (2016); Saada R., Green transportation in green supply chain management, Green Supply Chain, (2020); Aguiar G. T., Oliveira G. A., Tan K. H., Kazantsev N., Setti D., Sustainable implementation success factors of AGVs in the Brazilian industry supply chain management, Procedia Manufacturing, 39, pp. 1577-1586, (2019); Jiang H., Xu G., Zeng W., Gao F., Design and kinematic modelling of a passively-actively transformable mobile robot, Mechanism and Machine Theory, 142, pp. 103591-103612, (2019); Harrington B. D., Voorhees C. J., The challenges of designing the rocker-bogie suspension for the Mars exploration rover, the Proc. of Aerospace Mechanisms Symp, pp. 19-21, (2004); Yadav V. G., Kazmi T., Harshith K., Augmented reality tourism using tele-rover, Proc. of 7th Int. Conf. on Computing for Sustainable Global Development (INDIACom), pp. 124-129, (2020); Visconte C., Cavallone P., Carbonari L., Botta A., Quaglia G., Design of a mechanism with embedded suspension to reconfigure the agri_Q locomotion layout, Robotics, 10, 1, (2021); Probal I. A., Hamim F. A., Islam M. A., Siddik M. A. B., Mars rover and its strategic implementation, Proc. of Int. Conf. on Information and Communication Technology for Sustainable Development (ICICT4SD), pp. 215-219, (2021); Ullrich F., Haydar A., Sukkarieh G. S., Design optimization of a Mars rovers rocker-bogie mechanism using genetic algorithms, Proc. of 10th Australian Space Science Conf, pp. 199-210, (2011); Lindemann R. A., Voorhees C. J., Mars exploration rover mobility assembly design, test and performance, Proc. IEEE Int. Conf. on Systems, Man and Cybernetics, 1, (2005); Ryu S., Lee Y., Seo T., Shape-morphing wheel design and analysis for step climbing in high speed locomotion, IEEE Robotics and Automation Letters, 5, 2, pp. 1977-1982, (2020); Lopez-Arreguin A. J. R., Montenegro S., Improving limitations of rover missions in the moon and planets by unifying vehicle–terrain interaction models, Advances in Astronautics Science and Technology, 3, 1, pp. 17-28, (2020); Rout B. K., Mittal R. K., Parametric design optimization of 2-dof R–R planar manipulator—A design of experiment approach, Robotics and Computer-Integrated Manufacturing, 24, 2, pp. 239-248, (2008); Kim H., Kim D., Yang H., Lee K., Seo K., Et al., Development of a wall-climbing robot using a tracked wheel mechanism, Journal of Mechanical Science and Technology, 22, 8, pp. 1490-1498, (2008); Lee K., Kim J., Controller gain tuning of a simultaneous multi-axis PID control system using the taguchi method, Control Engineering Practice, 8, 8, pp. 949-958, (2000); Shivam Kumar J. A., Subramaniam P., Mercy L., Raj S. D., Design and fabrication of smart rover using rocker bogie mechanism, AIP Conference Proceedings, 2311, pp. 1-15, (2020); Kim K., Kim Y., Kim J., Kim H. S., Seo T., Optimal trajectory planning for 2-DOF adaptive transformable wheel, IEEE Access, 8, pp. 14452-14459, (2020)","A. Arunkumar; Department of Mechanical Engineering, E.G.S. Pillay Engineering College, Nagapattinam, Tamilnadu, India; email: aarunkumaregs@gmail.com",null,"Tech Science Press",{"$nulls":5},1.0798587E7,null,null,null,"English","Intell. Autom. Soft Comp.","Article","Final","All Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85132142973"]
["Wang P.; Du S.; Hu L.; Tang W.","Wang, Pei (57413188100); Du, Shaofu (25930733800); Hu, Li (56525783700); Tang, Wenzhi (57077451500)","57413188100; 25930733800; 56525783700; 57077451500","Logistics choices in a platform supply chain: A co-opetitive perspective",2023.0,"Journal of the Operational Research Society",74.0,1.0,null,93.0,111.0,18.0,9.0,"10.1080/01605682.2021.2023675","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85122849985&doi=10.1080%2f01605682.2021.2023675&partnerID=40&md5=7c8222eaece6ac4d07f51497f7f2f62f","University of Science and Technology of China, Hefei, China; Nanjing University of Finance and Economics, Nanjing, China; Hefei University, Hefei, China","Wang P., University of Science and Technology of China, Hefei, China; Du S., University of Science and Technology of China, Hefei, China; Hu L., Nanjing University of Finance and Economics, Nanjing, China; Tang W., Hefei University, Hefei, China","With the popularity and development of the platform economy, numerous enterprises are choosing to cooperate with e-commerce platforms to expand online market, and the cooperation modes have exhibited innovation and diversification. This paper focuses on a new platform-based co-opetitive supply chain whereby a flagship store operated by the manufacturer (MFS) and a self-run store operated by the platform (PSS) coexist in the platform market. The manufacturer acts as the platform’s upstream contract manufacturer and downstream competitor. We answer a key question that the manufacturers are facing: when should they adopt the high-level logistics service (HLS) provided by the platform? Two cases with exogenous and endogenous HLS charge are analyzed respectively. Our results show that under the case of exogenous HLS charge, the manufacturer should always select HLS when the HLS charge is low. Counterintuitively, if the product’s market potential is limited, the HLS is still profitable for the manufacturer despite a high HLS charge. When the HLS charge is endogenous, we find that the platform can adjust the HLS charge to induce the manufacturers to give up low-level logistics service (LLS) and choose HLS, which will achieve a win-win situation. © 2022 Operational Research Society.","e-commerce; game theory; logistics; retailing; Supply chain","Electronic commerce; Manufacture; Supply chains; Commerce platforms; Contract manufacturers; Down-stream; E- commerces; Enterprise IS; Logistics services; Market potential; Online markets; Retailing; Win-win; Game theory",{"$nulls":4},"Top-Notch Young Talents Program of China; National Natural Science Foundation of China, NSFC, (71801210, 71904041, 71921001, 72071193); Fundamental Research Funds for the Central Universities","This research was supported by the National Natural Science Foundation of China (Grant Nos. 71801210, 72071193, 71904041, 71921001), Top-Notch Young Talents Program of China, and the Fundamental Research Funds for the Central Universities. The authors thank the editors and the anonymous review team for their insightful comments and suggestions that immensely helped to improve this paper.","Abhishek V., Jerath K., Zhang Z.J., Agency selling or reselling? Channel structures in electronic retailing, Management Science, 62, 8, pp. 2259-2280, (2016); Agatz N.A., Fleischmann M., van Nunen J.A., E-fulfillment and multi-channel distribution–A review, European Journal of Operational Research, 187, 2, pp. 339-356, (2008); From connecting to empowering: “Intelligence+” helps China’s high-quality economic development, (2019); Ansari A., Mela C.F., Neslin S.A., Customer channel migration, Journal of Marketing Research, 45, 1, pp. 60-76, (2008); Bilgicer T., Jedidi K., Lehmann D.R., Neslin S.A., Social contagion and customer adoption of new sales channels, Journal of Retailing, 91, 2, pp. 254-271, (2015); Brandenburger A.M., Nalebuff B.J., Co-opetition, (1996); Cai G.G., Channel selection and coordination in dual-channel supply chains, Journal of Retailing, 86, 1, pp. 22-36, (2010); Cao L., Li L., The impact of cross-channel integration on retailers’ sales growth, Journal of Retailing, 91, 2, pp. 198-216, (2015); Chen J., Liang L., Yao D.-Q., Factory encroachment and channel selection in an outsourced supply chain, International Journal of Production Economics, 215, pp. 73-83, (2019); Chen J., Zhang H., Sun Y., Implementing coordination contracts in a manufacturer Stackelberg dual-channel supply chain, Omega, 40, 5, pp. 571-583, (2012); Chen Y.-J., Shum S., Xiao W., Should an OEM retain component procurement when the cm produces competing products?, Production and Operations Management, 21, 5, pp. 907-922, (2012); Choi T.-M., He Y., Peer-to-peer collaborative consumption for fashion products in the sharing economy: Platform operations, Transportation Research Part E: Logistics and Transportation Review, 126, pp. 49-65, (2019); Du S., Wang L., Hu L., Zhu Y., Platform-led green advertising: Promote the best or promote by performance, Transportation Research Part E: Logistics and Transportation Review, 128, pp. 115-131, (2019); Dzyabura D., Jagabathula S., Offline assortment optimization in the presence of an online channel, Management Science, 64, 6, pp. 2767-2786, (2018); Eilon S., The effect of a price war in a duopoly, Omega, 21, 6, pp. 619-627, (1993); Emrich O., Paul M., Rudolph T., Shopping benefits of multichannel assortment integration and the moderating role of retailer type, Journal of Retailing, 91, 2, pp. 326-342, (2015); Evans D., Schmalensee R., Markets with two-sided platforms, Issues in Competition Law and Policy, (2008); Hagiu A., Wright J., Multi-sided platforms, International Journal of Industrial Organization, 43, pp. 162-174, (2015); Hagiu A., Merchant or two-sided platform?, Review of Network Economics, 6, 2, pp. 115-133, (2007); He P., Wen J., Ye S., Li Z., Logistics service sharing and competition in a dual-channel e-commerce supply chain, Computers & Industrial Engineering, 149, (2020); He P., Zhang S., He C., Impacts of logistics resource sharing on b2c e-commerce companies and customers, Electronic Commerce Research and Applications, 34, (2019); Herhausen D., Binder J., Schoegel M., Herrmann A., Integrating bricks with clicks: Retailer-level and channel-level outcomes of online–offline channel integration, Journal of Retailing, 91, 2, pp. 309-325, (2015); Kapoor R., Agarwal S., Sustaining superior performance in business ecosystems: Evidence from application software developers in the iOS and android smartphone ecosystems, Organization Science, 28, 3, pp. 531-551, (2017); Li J., Konus U., Pauwels K., Langerak F., The hare and the tortoise: Do earlier adopters of online channels purchase more?, Journal of Retailing, 91, 2, pp. 289-308, (2015); Lim W.S., Tan S.J., Outsourcing suppliers as downstream competitors: Biting the hand that feeds, European Journal of Operational Research, 203, 2, pp. 360-369, (2010); Luo Z., Chen X., Wang X., The role of co-opetition in low carbon manufacturing, European Journal of Operational Research, 253, 2, pp. 392-403, (2016); McGuire T.W., Staelin R., An industry equilibrium analysis of downstream vertical integration, Marketing Science, 2, 2, pp. 161-191, (1983); Niu B., Chen K., Fang X., Yue X., Wang X., Technology specifications and production timing in a co-opetitive supply chain, Production and Operations Management, 28, 8, pp. 1990-2007, (2019); Niu B., Li Q., Mu Z., Chen L., Ji P., Platform logistics or self-logistics? restaurants’ cooperation with online food-delivery platform considering profitability and sustainability, International Journal of Production Economics, 234, (2021); Niu B., Wang Y., Guo P., Equilibrium pricing sequence in a co-opetitive supply chain with the ODM as a downstream rival of its OEM, Omega, 57, pp. 249-270, (2015); Niu B., Xie F., Chen L., Xu X., Join logistics sharing alliance or not? incentive analysis of competing e-commerce firms with promised-delivery-time, International Journal of Production Economics, 224, (2019); Consumer view winter 2020: Convenience and the Consumer, (2020); Pauwels K., Neslin S.A., Building with bricks and mortar: The revenue impact of opening physical stores in a multichannel environment, Journal of Retailing, 91, 2, pp. 182-197, (2015); Qin X., Liu Z., Tian L., The strategic analysis of logistics service sharing in an e-commerce platform, Omega, 92, (2020); Qin X., Liu Z., Tian L., The optimal combination between selling mode and logistics service strategy in an e-commerce market, European Journal of Operational Research, 289, 2, pp. 639-651, (2021); Rao S., Goldsby T.J., Griffis S.E., Iyengar D., Electronic logistics service quality (e-LSQ): Its impact on the customer’s purchase satisfaction and retention, Journal of Business Logistics, 32, 2, pp. 167-179, (2011); Ren S., Choi T.-M., Lee K.-M., Lin L., Intelligent service capacity allocation for cross-border-e-commerce related third-party-forwarding logistics operations: A deep learning approach, Transportation Research Part E: Logistics and Transportation Review, 134, (2020); Ryan J.K., Sun D., Zhao X., Competition and coordination in online marketplaces, Production and Operations Management, 21, 6, pp. 997-1014, (2012); Singh N., Vives X., Price and quantity competition in a differentiated duopoly, The Rand Journal of Economics, 15, 4, pp. 546-554, (1984); Spiegel Y., Horizontal subcontracting, The RAND Journal of Economics, 24, 4, pp. 570-590, (1993); Tian L., Vakharia A.J., Tan Y., Xu Y., Marketplace, reseller, or hybrid: Strategic analysis of an emerging e-commerce model, Production and Operations Management, 27, 8, pp. 1595-1610, (2018); Wang P., Chaudhry S., Li L., Hu M., Huang F., Hou H., Chen Y., Bulysheva L., Customized logistics service and online shoppers’ satisfaction: An empirical study, Internet Research, (2016); Wang Y., Niu B., Guo P., On the advantage of quantity leadership when outsourcing production to a competitive contract manufacturer, Production and Operations Management, 22, 1, pp. 104-119, (2013); Wang Z., Delivering meals for multiple suppliers: Exclusive or sharing logistics service, Transportation Research Part E: Logistics and Transportation Review, 118, pp. 496-512, (2018); Wen W., Zhou P., Zhang F., Carbon emissions abatement: Emissions trading vs consumer awareness, Energy Economics, 76, pp. 34-47, (2018); Yan Y., Zhao R., Liu Z., Strategic introduction of the marketplace channel under spillovers from online to offline sales, European Journal of Operational Research, 267, 1, pp. 65-77, (2018); Yan Y., Zhao R., Xing T., Strategic introduction of the marketplace channel under dual upstream disadvantages in sales efficiency and demand information, European Journal of Operational Research, 273, 3, pp. 968-982, (2019); Yao D., Liu J., Competitive pricing of mixed retail and e-tail distribution channels, Omega, 33, 3, pp. 235-247, (2005); Zhang J., Xu Q., He Y., Omnichannel retail operations with consumer returns and order cancellation, Transportation Research Part E: Logistics and Transportation Review, 118, pp. 308-324, (2018); Zhu F., Liu Q., Competing with complementors: An empirical look at amazon.com, Strategic Management Journal, 39, 10, pp. 2618-2642, (2018)","L. Hu; Department of E-commerce, School of International Economics and Trade, Nanjing University of Finance and Economics, Nanjing, 210046, China; email: huli@ustc.edu.cn",null,"Taylor and Francis Ltd.",{"$nulls":5},1605682.0,null,"JORSD",null,"English","J.Oper.Res.Soc.","Article","Final",null,"Scopus","2-s2.0-85122849985"]
["Chi C.; Wu S.; Xia D.; Wu Y.","Chi, Cheng (57214457339); Wu, Shasha (57189441516); Xia, Delong (57209218191); Wu, Yaohua (56523547600)","57214457339; 57189441516; 57209218191; 56523547600","Dynamic Picking and Storage Optimization of Robotic Picking Systems",2023.0,"Wireless Personal Communications",128.0,1.0,null,1.0,23.0,22.0,0.0,"10.1007/s11277-021-09190-9","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85142499142&doi=10.1007%2fs11277-021-09190-9&partnerID=40&md5=26fa72e7c5d2a56e9fb555a1d1d8245f","School of Mechanical and Electrical Engineering, Shandong Jianzhu University, Jinan, China; School of Control Science and Engineering, Shandong University, Jinan, China","Chi C., School of Mechanical and Electrical Engineering, Shandong Jianzhu University, Jinan, China; Wu S., School of Control Science and Engineering, Shandong University, Jinan, China; Xia D., School of Control Science and Engineering, Shandong University, Jinan, China; Wu Y., School of Control Science and Engineering, Shandong University, Jinan, China","With the development of e-commerce and the improvement of logistics requirements, more and more ‘parts-to-picker’ picking systems begin to replace the inefficient ‘picker-to-parts’ picking systems in various scenarios. As the mainstream ‘parts-to-picker’ system, the robotic mobile fulfillment system has been attracting much attention in recent years. In addition to the customer's changing requirements, the rapid response of the picking system to the order is particularly important. In the above context, to seek a breakthrough in the picking system's picking efficiency without increasing the cost of additional equipment, the storage allocation of the pods becomes very important. This article focuses on the dynamic storage allocation of robotic mobile fulfillment system, which has positive theoretical and practical significance. By analyzing the pod storage process of the robotic mobile fulfillment system, a dynamic pod storage allocation model suitable for the robotic mobile fulfillment system is established with the goal of minimizing the pod handling distance. Two dynamic pod storage allocation strategies are proposed for the system. By simulating the picking systems of different scales, the effectiveness of the dynamic storage allocation strategy is verified, which has a certain reference to the operation of the robotic mobile fulfillment system in practice. © 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.","Parts-to-picker; Robotic picking; Simulation analysis; Storage allocation","Warehouses; Allocation strategy; Dynamic storage allocation; E- commerces; Part-to-picker; Picking system; Rapid response; Robotic picking; Simulation analysis; Storage allocation; Storage optimization; Robotics",{"$nulls":6},"Bartholdi J.J., Hackman S.T., Warehouse and distribution science[M], (2008); Wurman P.R., Coordinating hundreds of cooperative, Autonomous Vehicles in Warehouses. Ai Magazine, 29, 1, (2008); Mountz M.C., D'andrea R., Laplante J.A., Et al., Inventory System with Mobile Drive Unit and Inventory Holder, (2008); Zou B., Gong Y., Xu X., Yuan Z., Assignment rules in robotic mobile fulfilment systems for online retailers, International Journal of Production Research, 55, 20, pp. 6175-6192, (2017); Nigam S., Roy D., de Koster R., Adan I., Analysis of class-based storage strategies for the mobile shelf-based order pick system, 13Th IMHRC Proc, (2014); Yuan R., Cezik T., Graves S.C., Velocity-based storage assignment in semi-automated storage systems, SSRN Electronic Journal, 28, 2, pp. 354-373, (2016); Lamballais T., Roy D., De Koster M.B.M., Estimating performance in a robotic mobile fulfillment system, European Journal of Operational Research, 256, 3, pp. 976-990, (2017); Boysen N., Briskorn D., Emde S., Parts-to-picker based order processing in a rack-moving mobile robots environment, European Journal of Operational Research, 262, pp. 550-562, (2017); Zou B., Xu X., De Koster R., Evaluating battery charging and swapping strategies in a robotic mobile fulfillment system, European Journal of Operational Research, 267, 2, pp. 733-753, (2018); Alnamoly M.H., Alzohairy A.M., El-Henawy I.M., A survey on gel images analysis software tools, Journal of Intelligent Systems and Internet of Things, 1, 1, pp. 40-47, (2021); Ilayaraja M., Particle swarm optimization based multihop routing techniques in mobile ADHOC networks, International Journal of Wireless and Ad Hoc Communication, 1, 1, pp. 47-56, (2020); Sharma A., Tayal S., Bansal R., Verma S., Energy efficiency techniques in heterogeneous networks, Journal of Cybersecurity and Information Management, 2, 1, pp. 13-23, (2021); Chhabra H., Mohan V., Rani A., Et al., Robust nonlinear fractional order fuzzy PD plus fuzzy I controller applied to robotic manipulator, Neural Computing and Applications, 32, pp. 2055-2079, (2020); Recupero D.R., Spiga F., Knowledge acquisition from parsing natural language expressions for humanoid robot action commands, Information Processing & Management, 57, 6, (2020)","Y. Wu; School of Control Science and Engineering, Shandong University, Jinan, China; email: yaohua.wu@sdu.edu.cn",null,"Springer",{"$nulls":5},9296212.0,null,"WPCOF",null,"English","Wireless Pers Commun","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85142499142"]
["Wang C.; Ma L.","Wang, Chengwei (57956529200); Ma, Liang (55721012400)","57956529200; 55721012400","Digital transformation of citizens’ evaluations of public service delivery: evidence from China",2022.0,"Global Public Policy and Governance",2.0,4.0,null,477.0,497.0,20.0,2.0,"10.1007/s43508-022-00054-x","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85141388139&doi=10.1007%2fs43508-022-00054-x&partnerID=40&md5=3731a777b85ca65b8aa0b30d9b759798","School of Public Administration and Policy, Renmin University of China, 59 Zhongguancun Avenue, Haidian District, Beijing, 100872, China; Department of Public Policy, City University of Hong Kong, Hong Kong","Wang C., School of Public Administration and Policy, Renmin University of China, 59 Zhongguancun Avenue, Haidian District, Beijing, 100872, China, Department of Public Policy, City University of Hong Kong, Hong Kong; Ma L., Department of Public Policy, City University of Hong Kong, Hong Kong","Thanks to the development of digital technologies and their applications in public service delivery, ratings by citizens of service quality have been transforming from paper/phone surveys to digital interfaces, similar to what has happened in e-commerce. How does digitalization drive the change in ratings by citizens? Are citizens more satisfied when they rate public services online? We provide empirical answers to these questions based on data from the government service evaluation system in a Chinese city. We found that digital interfaces facilitate the behavior of citizens making evaluations and boost citizen satisfaction compared with offline channels. Specifically, interfaces displayed on mobile applications significantly facilitate evaluations by citizens and improve citizen satisfaction. The results provide theoretical and practical implications for understanding the digital transformation of public service ratings. © 2022, The Author(s), under exclusive licence to Institute for Global Public Policy, Fudan University.","Administrative burden; Digital transformation; E-government; Evaluations by citizens; Public service performance",{"$nulls":5},"Outstanding Innovative Talents Cultivation; National Natural Science Foundation of China, NSFC, (72274203); Renmin University of China, RUC; Beijing Social Science Fund, (21DTR058)","The authors would like to thank the National Natural Sciences Foundation of China (Grant/Award Number: 72274203), the Outstanding Innovative Talents Cultivation Funded Programs 2021 of Renmin University of China, and Beijing Social Science Fund (No. 21DTR058) for financial support. The correspondence for this article should go to Liang Ma. ","Arendsen R., Peters O., ter Hedde M., van Dijk J., Does e-government reduce the administrative burden of businesses? An assessment of business-to-government systems usage in the Netherlands, Government Information Quarterly, 31, 1, pp. 160-169, (2014); Baltagi B.H., Bresson G., Pirotte A., Fixed effects, random effects or Hausman–Taylor?: a pretest estimator, Economics Letters, 79, 3, pp. 361-369, (2003); Barnes C.Y., Henly J.R., They are underpaid and understaffed: how clients interpret encounters with street-level bureaucrats, Journal of Public Administration Research and Theory, 28, 2, pp. 165-181, (2018); Bartels K.P.R., Public encounters: the history and future of face-to-face contact between public professionals and citizens, Public Administration, 91, 2, pp. 469-483, (2013); Behn R.D., Designing performancestat: or what are the key strategic choices that a jurisdiction or agency must make when adapting the compstat/citistat class of performance strategies?, Public Performance & Management Review, 32, 2, pp. 206-235, (2008); Bell E., Ter-Mkrtchyan A., Wehde W., Smith K., Just or unjust? how ideological beliefs shape street-level bureaucrats’ perceptions of administrative burden, Public Administration Review, 81, 4, pp. 610-624, (2021); Bozeman B., Youtie J., Robotic bureaucracy: administrative burden and red tape in university research, Public Administration Review, 80, 1, pp. 157-162, (2020); Brown J.T., Carey G., Malbon E., What is in a form? Examining the complexity of application forms and administrative burden, Australian Journal of Public Administration, 80, 4, pp. 933-964, (2021); Carey G., Dickinson H., Malbon E., Weier M., Duff G., Burdensome administration and its risks: competing logics in policy implementation, Administration & Society, 52, 9, pp. 1362-1381, (2020); Escobar M.P., Demeritt D., Paperwork and the decoupling of audit and animal welfare: The challenges of materiality for better regulation, Environment and Planning c: Politics and Space, 35, 1, pp. 169-190, (2016); Fan Z., Christensen T., Ma L., Policy attention and the adoption of public sector innovation, Public Management Review, (2022); Liao F., Singular or plural? Administrative burden and doing business in China, Journal of Chinese Governance, (2020); Gao J., How does chinese local government respond to citizen satisfaction surveys? a case study of Foshan City, Australian Journal of Public Administration, 71, 2, pp. 136-147, (2012); Goodsell C.T., The public encounter and its study: Where state and citizen meet, (1981); Heinrich C.J., Presidential address: “a thousand petty fortresses”: administrative burden in U.S. immigration policies and its consequences, Journal of Policy Analysis and Management, 37, 2, pp. 211-239, (2018); Herd P., DeLeire T., Harvey H., Moynihan D.P., Shifting administrative burden to the state: the case of medicaid take-up, Public Administration Review, 73, s1, pp. S69-S81, (2013); Keiser L.R., Miller S.M., Does Administrative burden influence public support for government programs? evidence from a survey experiment, Public Administration Review, 80, 1, pp. 137-150, (2020); Lindgren I., Madsen C.O., Hofmann S., Melin U., Close encounters of the digital kind: a research agenda for the digitalization of public services, Government Information Quarterly, 36, 3, pp. 427-436, (2019); Lipsky M., Street-Level Bureaucracy: The Dilemmas of the Individual in Public Service, (1983); Lipsky M., Street-level bureaucracy: Dilemmas of the individual in public service, (2010); Ma L., Performance management and citizen satisfaction with the government: evidence from Chinese municipalities, Public Administration, 95, 1, pp. 39-59, (2017); Ma L., Wu X., Citizen engagement and co-production of e-government services in China, Journal of Chinese Governance, 5, 1, pp. 68-89, (2020); Moynihan D., Herd P., Harvey H., Administrative burden: learning, psychological, and compliance costs in citizen-state interactions, Journal of Public Administration Research and Theory, 25, 1, pp. 43-69, (2015); Peeters R., Trujillo Jimenez H., O'Connor E., Ogarrio Rojas P., Gonzalez Galindo M., Morales Tenorio D., Low-trust bureaucracy: understanding the Mexican bureaucratic experience, Public Administration and Development, 38, 2, pp. 65-74, (2018); Prokop C., Tepe M., Talk or type? The effect of digital interfaces on citizens' satisfaction with standardized public services, . Public Administration, N/A(N/A)., (2021); So B.W.Y., Civic engagement in the performance evaluation of the public sector in China: Building horizontal accountability to enhance vertical accountability, Public Management Review, 16, 3, pp. 341-357, (2014); Linking Citizen Satisfaction Data to Performance Measures: A Preliminary Evaluation, Public Performance & Management Review, 24, 1, pp. 30-52, (2000); Tummers L., Weske U., Bouwman R., Grimmelikhuijsen S., The impact of red tape on citizen satisfaction: an experimental study, International Public Management Journal, 19, 3, pp. 320-341, (2016); Wandaogo A.A., Does digitalization improve government effectiveness? Evidence from developing and developed countries, Applied Economics, 54, 33, pp. 3840-3860, (2022)","L. Ma; Department of Public Policy, City University of Hong Kong, Hong Kong; email: liangma@ruc.edu.cn",null,"Springer",{"$nulls":5},2.7306291E7,null,null,null,"English","Glob. Publ. Policy Govern.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85141388139"]
["Sandoval M.G.; Álvarez-Miranda E.; Pereira J.; Ríos-Mercado R.Z.; Díaz J.A.","Sandoval, M. Gabriela (57207309921); Álvarez-Miranda, Eduardo (39260996600); Pereira, Jordi (55426276000); Ríos-Mercado, Roger Z. (6602712384); Díaz, Juan A. (7401603810)","57207309921; 39260996600; 55426276000; 6602712384; 7401603810","A novel districting design approach for on-time last-mile delivery: An application on an express postal company",2022.0,"Omega (United Kingdom)",113.0,null,102687.0,null,null,null,12.0,"10.1016/j.omega.2022.102687","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85131511386&doi=10.1016%2fj.omega.2022.102687&partnerID=40&md5=9bc134b9bb95899863db9a0d00dd5445","Department of Computers, Electronics and Mechatronics, Universidad de las Américas Puebla (UDLAP), Puebla, San Andrés Cholula, 72820, Mexico; School of Economics and Business, Universidad de Talca, Talca, Chile; Instituto Sistemas Complejos de Ingeniería, Chile; Faculty of Engineering and Sciences, Universidad Adolfo Ibáñez, Viña del Mar, Chile; UPF - Barcelona School of Management, Barcelona, Spain; Universidad Autónoma de Nuevo León (UANL), Graduate Program in Systems Engineering, Department of Mechanical and Electrical Engineering, San Nicolás de los Garza, Mexico; Department of Actuary, Physics and Mathematics, Universidad de las Américas Puebla (UDLAP), Puebla, San Andrés Cholula, 72820, Mexico","Sandoval M.G., Department of Computers, Electronics and Mechatronics, Universidad de las Américas Puebla (UDLAP), Puebla, San Andrés Cholula, 72820, Mexico; Álvarez-Miranda E., School of Economics and Business, Universidad de Talca, Talca, Chile, Instituto Sistemas Complejos de Ingeniería, Chile; Pereira J., Faculty of Engineering and Sciences, Universidad Adolfo Ibáñez, Viña del Mar, Chile, UPF - Barcelona School of Management, Barcelona, Spain; Ríos-Mercado R.Z., Universidad Autónoma de Nuevo León (UANL), Graduate Program in Systems Engineering, Department of Mechanical and Electrical Engineering, San Nicolás de los Garza, Mexico; Díaz J.A., Department of Actuary, Physics and Mathematics, Universidad de las Américas Puebla (UDLAP), Puebla, San Andrés Cholula, 72820, Mexico","Last-mile logistics corresponds to the last leg of the supply chain, i.e., the delivery of goods to final customers, and they comprise the core activities of postal and courier companies. Because of their role in the supply chain, last-mile operations are critical for the perception of customers regarding the performance of the whole logistic process. In this sense, the sustained growth of e-commerce, which has been abruptly catalyzed by the irruption of the COVID-19 pandemic, has hanged the habits of customers and overtaxed the operational side of delivery companies, hindering their viability and forcing their adaptation to the novel conditions. Many of these habits will remain after we overcome the sanitary crisis, which will permanently reshape the structure and emphasis of postal supply chains, demanding companies to implement organizational and operational changes to adapt to these new challenges. In this work we address a last-mile logistic design problem faced by a courier and delivery company in Chile, although the same problem is likely to arise in the last-mile delivery operation of other postal companies, in particular in the operation of express delivery services. The operational structure of the company is based on the division of an urban area into smaller territories (districts) and the outsourcing of the delivery operation of each territory to a last-mile contractor. Because of the increasing volume of postal traffic and a decreasing performance of the service, in particular for the case of express deliveries, the company is forced to redesign its current territorial arrangement. Such redesign results in a novel optimization problem that resembles a classical districting problem with the additional quality of service requirements. This novel problem is first formulated as a mathematical programming model and then a specially tailored heuristic is designed for solving it. The proposed approach is tested on instances from the real-life case study, and the obtained results show significant improvements in terms of the percentage of on-time deliveries achieved by the proposed solution when compared to the current districting design of the company. By performing a sensitivity analysis considering different levels of demand, we show that the proposed approach is effective in providing districting designs capable of enduring significant increases in the demand for express postal services. © 2022","Districting; Heuristics; Last-mile delivery; Postal delivery; Supply chain management","Mathematical programming; Quality of service; Sales; Sensitivity analysis; 'current; Delivery company; Delivery of goods; Design approaches; Districting; Heuristic; Last mile; Last-mile delivery; Performance; Postal delivery; article; Chile; habit; heuristics; human; postal mail; sensitivity analysis; urban area; Supply chain management",{"$nulls":4},"National Agency of Research and Development; Fondo Nacional de Desarrollo Científico y Tecnológico, FONDECYT, (1180670); Consejo Nacional de Ciencia y Tecnología, CONACYT, (FC2016-2/1948); Instituto de Sistemas Complejos de Ingeniería, ISCI, (ANID PIA/BASAL AFB180003)","E. Álvarez-Miranda acknowledges the support of the National Agency of Research and Development (ANID), Chile, through the grant FONDECYT N.1180670 and through the Complex Engineering Systems Institute ANID PIA/BASAL AFB180003. Roger Ríos-Mercado was supported by the Mexican Council for Science and Technology under its Frontier Science Program (grant FC2016-2/1948 ).","(2020); Bard J.F., Jarrah A.I., Large-scale constrained clustering for rationalizing pickup and delivery operations, Transp Res, Part B, 43, 5, pp. 542-561, (2009); Bates O., Friday A., Allen J., Cherrett T., McLeod F., Bektas T., Et al., Transforming last-mile logistics: opportunities for more sustainable deliveries, Proceedings of the 2018 CHI conference on human factors in computing systems, Montreal, Canada, pp. 1-14, (2018); Behroozi M., Carlsson J.G., Computational geometric approaches to equitable districting: a survey, Optimal districting and territory design, International series in operations research and management science, 284, pp. 57-74, (2020); Bektas T., Gouveia L., Requiem for the Miller–Tucker–Zemlin subtour elimination constraints?, Eur J Oper Res, 236, 3, pp. 820-832, (2014); Bender M., Kalcsics J., Nickel S., Pouls M., A branch-and-price algorithm for the scheduling of customer visits in the context of multi-period service territory design, Eur J Oper Res, 269, 1, pp. 382-396, (2018); Bender M., Kalcsics J., Meyer A., Districting for parcel delivery services—A two-stage solution approach and a real-world case study, Omega, 96, (2020); Benzarti E., Sahin E., Dallery Y., Operations management applied to home care services: Analysis of the districting problem, Decis Support Syst, 55, 2, pp. 587-598, (2013); Butsch A., Districting problems: new geometrically motivated approaches, (2016); Butsch A., Kalcsics J., Laporte G., Districting for arc routing, INFORMS J Comput, 26, 4, pp. 809-824, (2014); Caro F., Shirabe T., Guignard M., Weintraub A., School redistricting: embedding GIS tools with integer programming, J Oper Res Soc, 55, 8, pp. 836-849, (2004); Chapleau L., Ferland J.A., Rousseau J.M., Clustering for routing in densely populated areas, Eur J Oper Res, 20, 1, pp. 48-57, (1985); Cox E., A method of assigning numerical and percentage values to the degree of roundness of sand grains, J Paleontol, 1, 3, pp. 179-183, (1927); Crew M., Brennan T., Postal and delivery innovation in the digital economy, Topics in regulatory economics and policy, 50, (2015); Croes G., A method for solving traveling-salesman problems, Oper Res, 6, 6, pp. 791-812, (1958); de la Poix de Freminville P., Desaulniers G., Rousseau L.-M., Perron S., A column generation heuristic for districting the price of a financial product, J Oper Res Soc, 66, 6, pp. 965-978, (2015); Demaziere D., Mercier D., Mail carriers’ routes: managerial standards, collective regulation and work activity strategies, Sociol Trav, 48, pp. e1-e21, (2006); Desrochers M., Laporte G., Improvements and extensions to the Miller–Tucker–Zemlin subtour elimination constraints, Oper Res Lett, 10, 1, pp. 27-36, (1991); Diglio A., Peiro J., Piccolo C., da Gama F.S., Solutions for districting problems with chance-constrained balancing requirements, Omega, 103, (2021); Dragendorf J., Mohr D., Ecker T., Neuhaus F., Briest P., Beretzky E., Et al., The endgame for postal networks: how to win in the age of e-commerce, Report, (2019); Duque J.C., Ramos R., Surinach J., Supervised regionalization methods: a survey, Int Reg Sci Rev, 30, 3, pp. 195-220, (2007); Fernandez E., Kalcsics J., Nickel S., Rios-Mercado R.Z., A novel maximum dispersion territory design model arising in the implementation of the WEEE-directive, J Oper Res Soc, 61, 3, pp. 503-514, (2010); Garcia-Ayala M.G., Gonzalez-Velarde J.L., Rios-Mercado R.Z., Fernandez E., A novel model for arc territory design: promoting Eulerian districts, Int Trans Oper Res, 23, 3, pp. 433-458, (2016); Gentry S., Chow E., Massie A., Segev D., Gerrymandering for justice: redistricting U.S. liver allocation, Interfaces, 45, 5, pp. 462-480, (2015); Gunawan A., Lau H., Vansteenwegen P., Orienteering problem: a survey of recent variants, solution approaches and applications, Eur J Oper Res, 255, 2, pp. 315-332, (2016); Hales T., The honeycomb conjecture, Discrete Comput Geom, 25, 1, pp. 1-22, (2001); Haugland D., Ho S.C., Laporte G., Designing delivery district for the vehicle routing problem with stochastic demands, Eur J Oper Res, 180, 3, pp. 997-1010, (2007); Hong S., Wolak F., Relative prices and electronic substitution: changes in household-level demand for postal delivery services from 1986 to 2004, J Econom, 145, 1-2, pp. 226-242, (2008); Huerta-Munoz D.L., Rios-Mercado R.Z., Ruiz R., An iterated greedy heuristic for a market segmentation problem with multiple attributes, Eur J Oper Res, 261, 1, pp. 75-87, (2017); (2019); Ivanov D., Viable supply chain model: integrating agility, resilience and sustainability perspectives–lessons from and thinking beyond the COVID-19 pandemic, Ann Oper Res, (2020); Ivanov D., Dolgui A., Viability of intertwined supply networks: extending the supply chain resilience angles towards survivability. 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Álvarez-Miranda; School of Economics and Business, Universidad de Talca, Talca, Chile; email: ealvarez@utalca.cl",null,"Elsevier Ltd",{"$nulls":5},3050483.0,null,"OMEGA",null,"English","Omega","Article","Final",null,"Scopus","2-s2.0-85131511386"]
["Corejova T.; Jucha P.; Padourova A.; Strenitzerova M.; Stalmachova K.; Valicova A.","Corejova, Tatiana (36598165500); Jucha, Peter (57226769070); Padourova, Anna (57220155205); Strenitzerova, Mariana (6506800375); Stalmachova, Katarina (57216375697); Valicova, Alexandra (57221783925)","36598165500; 57226769070; 57220155205; 6506800375; 57216375697; 57221783925","E-commerce and last mile delivery technologies in the European countries",2022.0,"Production Engineering Archives",28.0,3.0,null,217.0,224.0,7.0,7.0,"10.30657/pea.2022.28.26","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135880806&doi=10.30657%2fpea.2022.28.26&partnerID=40&md5=5b3d0b05a6e8e7511306622103665de0","University of Zilina, Univerzitna 1, Zilina, 01026, Slovakia","Corejova T., University of Zilina, Univerzitna 1, Zilina, 01026, Slovakia; Jucha P., University of Zilina, Univerzitna 1, Zilina, 01026, Slovakia; Padourova A., University of Zilina, Univerzitna 1, Zilina, 01026, Slovakia; Strenitzerova M., University of Zilina, Univerzitna 1, Zilina, 01026, Slovakia; Stalmachova K., University of Zilina, Univerzitna 1, Zilina, 01026, Slovakia; Valicova A., University of Zilina, Univerzitna 1, Zilina, 01026, Slovakia","Society, companies and institutions are involved in a digital transformation that can be pervaded in various industries or sectors, and this also applies to communication, sales and distribution channels. The possibilities of e-commerce have also increased and world trade has been further developed. In 2020, more than two billion people bought goods or services over the Internet. Customer satisfaction depends on the solution of the last mile process, the method of picking up shipments as well as the time and place of picking up the shipment. The most common forms of off-premises delivery are automated parcel locker or machine (APM) and pick-up and drop-off delivery (PUDO). The aim of the paper is to analyse the level of the PUDO and APM network in European countries and in the V4 countries with regard to the size of the country and the population. For this purpose, it was necessary to focus on determining the population per 1 PUDO and the number of inhabitants per 1 APM in individual European countries and subsequently in the V4 countries. The obtained data were processed and recalculated in Excel. The results showed that within European countries the best values were achieved by Finland with 526 inhabitants per 1 PUDO and Spain with 188 inhabitants per 1 APM. Regarding the V4 countries, the Czech Republic achieved the best value in the case of inhabitants on PUDO with 729 inhabitants per 1 PUDO and in the case of APM Poland with 3,184 inhabitants per 1 APM. © 2022 Tatiana Corejova et al., published by Sciendo.","automated parcel machine; e-commerce; last mile delivery; out of home delivery; pick-up and drop-off delivery",{"$nulls":7},"Abraham A., How Technology is Improving Last-Mile Delivery in 2020, (2020); Bachanova P., Corejova T., Rostasova M., The green issues of postal industry in Europe, 3rd Central European Conference in Regional Science-CERS, pp. 901-905, (2009); Coppola D., E-commerce worldwide-statistics & facts, (2021); What is Last Mile Delivery? Part 1: How Omnichannel Retail is Affecting Transportation & Logistics, (2021); Dobroselskyi M., Madlenak R., Laitkep D., Analysis of return logistics in e-commerce companies on the example of the Slovak Republic, Transportation Research Procedia: 14th International Scientific Conference on Sustainable, Modern and Safe Transport, TRANSCOM 2021, 55, pp. 318-325, (2021); Drodziel P., Winska M., Madlenak R., Szumski P., Optimization of the position of the local distribution centre of the regional post logistics network, Transport Problems, 12, 3, pp. 43-50, (2017); Ecommerce D.B., E-commerce market analysis: The eCommerce market in Slovakia, (2021); E-commerce statistics, 2021, (2021); Faugere L., Montreuil B., Hyperconnected City Logistics: Smart Lockers Terminals & Last Mile Delivery Networks, Proceedings of the 3rd International Physical Internet Conference, (2016); Garbarova M., Bachanova P.H., Vartiak L., Purchasing behaviour of e-commerce customers, Global Scientific Conference on Management and Economics in Manufacturing: Management and economics in manufacturing, pp. 160-165, (2017); Gnap J., Benova D., ogistika poslednej míle, (2018); Honorato M., What No One Tells You About Last Mile Delivery, (2016); Chen P., Chen Y.J., Hu X.T., Li S.X., Can online markets attract high-guality products?, Economic Modelling, 51, pp. 65-71, (2015); Iwan S., Kijewska K., Lemke J., Analysis of parcel lockers' efficiency as the last mile delivery solution-the results of the research in Poland, Transportation Research Procedia: The 9th International Conference on City Logistics, 12, pp. 644-655, (2016); Janjevic M., Winkenbach M., Characterizing urban last-mile distribution strategies in mature and emerging e-commerce markets, Transportation Research Part A: Policy and Practice, 133, pp. 164-196, (2020); Kawa A., Out-of-Home Delivery as a Solution of the Last Mile Problem in E-commerce, book: Smart and Sustainable Supply Chain and Logistics-Trends, Challenges, Methods and Best Practices, (2020); Keil R., Krone D., Kremenova I., Madlenak R., Communication networks as base for mobility-Trend development of network architectures, Communications-Scientific Letters of University of Zilina, 17, 2, pp. 80-85, (2015); Ko S.Y., Sari R.P., Makhmudov M., Ko C.S., Collaboration Model for Service Clustering in Last-Mile Delivery, Sustainability, 12, 14, pp. 1-18, (2020); Koncova D., Kremenova I., Fabus J., Proposal for a change in the type of devices used for submitting of postal items by using the Saaty's method, a case study for the postal sector, Transportation Research Procedia: 14th International scientific conference on sustainable, modern and safe transport, TRANSCOM, 55, pp. 236-243, (2021); Kvasnicova T., Kremenova I., Fabus J., Babusiak B., E-commerce user experience: do we feel under pressure during online shopping?, WMSCI 2016-20th World Multi-Conference on Systemics, Cybernetics and Informatics, Proceedings, 2, pp. 41-44, (2016); Lakshmi D., Pick-Up and Drop-Off Services: How PUDOs Can Redefine Delivery Efficiency and Convenience? Locus Blog, (2021); Lebaron J., Ecommerce Trends for 2021, (2021); Lone S., Harboul N., Weltevreden J.W.J., European E-commerce Report, (2021); Lu S.H., Et al., The Last Mile: Managing Driver Helper Dispatching for Package Delivery Services, Journal of Business Logistics, 41, 3, pp. 206-221, (2020); MacKo O., Ako nakupovali zákazníci internetových obchodov v pandemickom roku, (2021); Madlenak R., Madlenakova L., Multi-criteria evaluation of e-shop methods of delivery from the customer's perspective, Transport problems, 15, 1, pp. 5-14, (2020); Madlenak R., Madlenakova L., Stefunko J., The variant approach to the optimization of the postal transportation network in the conditions of the Slovak Republic, Transport and Telecommunication, 16, 3, pp. 237-245, (2015); Madlenak R., Madlenakova L., Comparison of regional postal transportation networks in Zilina Region, Transport Means-Proceedings of the Internationational Conference: 19st International Scientific Conference Transport Means, pp. 277-280, (2015); Madlenakova L., Madlenak R., Rudawska A., Drodziel P., On the problem of quantitative analysis of the concentration on the postal and logistics market, Transport Means, Proceedings of the Internationational Conference: 21st International Scientific Conference Transport Means, pp. 693-698, (2017); Parcel delivery: The future of last mile. Travel, Transport and Logistics, (2016); Morganti E., Dablanc L., Fortin F., Final deliveries for online shopping: The deployment of pickup point networks in urban and suburban areas, Research in Transportation Business & Management, 11, pp. 23-31, (2014); Orenstein I., Raviv T., Sadan E., Flexible parcel delivery to automated parcel lockers: models, solution methods and analysis, EURO Journal on Transportation and Logistics, 8, pp. 683-711, (2019); Sitek P., Wikarek J., Capacitated vehicle routing problem with pickup and alternative delivery (CVRPPAD): model and implementation using hybrid approach, Annals of Operations Research, 273, pp. 257-277, (2019); Strenitzerova M., Gana J., Customer Satisfaction and Loyalty as a Part of Customer-Based Corporate Sustainability in the Sector of Mobile Communications Services, Sustainability, 10, 5, (2018); Turska S., Madlenakova L., Concept of smart postal mailbox, Transport Research Procedia: 13th International Scientific Conference on Sustainable, Modern and Safe Transport, TRANSCOM 2019, 40, pp. 1199-1207, (2019); Uzzaman A., 10 technology trends that will impact our lives in 2020, (2019); Vakulenko Y., Shams P., Hellstrom D., Hjort K., Service innovation in e-commerce last mile delivery: Mapping the e-customer journey, Journal of Business Research, 101, pp. 461-468, (2019)","T. Corejova; University of Zilina, Zilina, Univerzitna 1, 01026, Slovakia; email: tatiana.corejova@fpedas.uniza.sk",null,"Sciendo",{"$nulls":5},2.3535156E7,null,null,null,"English","Pord. Eng. Arch.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85135880806"]
["Ma Z.; Gao Q.; Chen Y.","Ma, Zhaoyi (57203120771); Gao, Qin (35483682700); Chen, Yue (56919488000)","57203120771; 35483682700; 56919488000","Post-Purchase Trust in e-Commerce: A Theoretical Framework and a Text Mining-Based Assessment Method",2023.0,"International Journal of Human-Computer Interaction",39.0,8.0,null,1643.0,1661.0,18.0,1.0,"10.1080/10447318.2022.2065046","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85131052213&doi=10.1080%2f10447318.2022.2065046&partnerID=40&md5=e43531e0d60ea9d4f90702ae725eeb9f","Department of Industrial Engineering, Tsinghua University, Beijing, China","Ma Z., Department of Industrial Engineering, Tsinghua University, Beijing, China; Gao Q., Department of Industrial Engineering, Tsinghua University, Beijing, China; Chen Y., Department of Industrial Engineering, Tsinghua University, Beijing, China","Post-purchase trust is formed after an online transaction is completed and the product or service is experienced. It influences consumers’ repurchase intention and the reputation of vendors. The aim of the current study was to deepen our understanding of post-purchase trust in e-Commerce and to develop a text mining-based assessment method by mining consumers’ online comments. By combining the expectancy-confirmation theory and product evaluation theory, this study proposes a comprehensive model of post-purchase trust encompassing consumers’ evaluation of product, delivery, service, and website. The model was verified by a survey involving 249 consumers. The results indicate that both product evaluation factors and transaction supporting factors have positive impacts on post-purchase trust. Based on this theoretical model, we proposed a text mining-based method to measure these factors through text-mining of consumers’ comments. To demonstrate the feasibility and benefits of the method, the method was applied to analyze 1,015,484 consumers’ comments on personal computer products from jd.com, a major Chinese e-Commerce website. The results suggest that the proposed method can provide practitioners with diagnostic suggestions to promote post-purchase trust and understand consumers better. HIGHLIGHTS Integration of the consumers’ product evaluation model and expectation-confirmation theory is proposed to investigate post-purchase trust in e-commerce. The confirmation of delivery, service, website, and perceived value of products affect consumer satisfaction, thereby affect post-purchase trust. Perceived value is positively affected by perceived price and perceived quality, which can be increased by consumers’ evaluation of the appearance, authenticity, and brand reputation of the product. The proposed model can be used to design text mining-based tools to monitor important factors of post-purchase trust via text mining. © 2022 Taylor & Francis Group, LLC.",null,"Data mining; Electronic commerce; Personal computers; Quality control; Websites; 'current; Consumer evaluation; Delivery service; E- commerces; Online transaction; Perceived value; Product evaluation; Repurchase intention; Text-mining; Theoretical framework; Sales",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (71942005)","This study was supported by the National Natural Science Foundation of China (Project no. 71942005).",{"$cut":{"chars":17736,"head":"Al Karim R., Customer satisfaction in online shopping: A study into the reasons for motivations and inhibitions, IOSR Journal of Business and Management, 11, 6, pp. 13-20, (2013); Anderson R.E., Srinivasan S.S., E-satisfaction and e-loyalty: A contingency framework, Psychology and Marketing, 20, 2, pp. 123-138, (2003); Bart Y., Shankar V., Sultan F., Urban G.L., Are the drivers and role of online trust the same for all web sites and consumers? A large-scale exploratory empirical study, Journal of Marketing, 69, 4, pp. 133-152, (2005); Beverland M.B., Farrelly F.J., The quest for authenticity in consumption: consumers’ purposive choice of authentic cues to shape experienced outcomes, Journal of Consumer Research, 36, 5, pp. 838-856, (2010); Bhargava K., Gujral T., Chawla M., Gujral T., Comment based seller trust model for e-commerce, International Conference on Computational Techniques in Information and Communication Technologies, pp. 387-391, (2016); Bhattacherjee A., Understanding information systems continuance: An expectation-confirmation model, MIS Quarterly, 25, 3, pp. 351-370, (2001); Bollen K.A., Structural equations with latent variables, (1989); Brucks M., Zeithaml V.A., Naylor G., Price and brand name as indicators of quality dimensions for consumer durables, Journal of the Academy of Marketing Science, 28, 3, pp. 359-374, (2000); Carlson J., O'Cass A., Ahrholdt D., Assessing customers’ perceived value of the online channel of multichannel retailers: A two country examination, Journal of Retailing and Consumer Services, 27, pp. 90-102, (2015); Chang M.K., Cheung W., Tang M., Building trust online: Interactions among trust building mechanisms, Information & Management, 50, 7, pp. 439-445, (2013); Chavan M.P., Kulkarni R., Mining E-commerce feedback comments using multi-dimensional trust computation, Journal of Multidisciplinary Engineering Science and Technology, 2, 7, pp. 1883-1887, (2015); Chen S.C., Dhillon G.S., Interpreting dimensions of consumer trust in E-commerce, Information Technology and Management, 4, 2-3, pp. 303-318, (2003); Chen Y.-Y., Huang H.-L., Hsu Y.-C., Tseng H.-C., Lee Y.-C., Confirmation of expectations and satisfaction with the Internet shopping: The Role of Internet self-efficacy, Computer and Information Science, 3, 3, (2010); Chiang C.-F., Jang S.S., The effects of perceived price and brand image on value and purchase intention: Leisure travelers’ attitudes toward online hotel booking, Journal of Hospitality & Leisure Marketing, 15, 3, pp. 49-69, (2007); China e-commerce report(2017), (2017); Chin W.W., Issues and opinion on structural equation modeling, MIS Quarterly, 22, 1, pp. 7-16, (1998); Chin W.W., Gopal A., Adoption intention in GSS: Relative importance of beliefs, Data Base for Advances in Information Systems, 26, 2-3, pp. 42-64, (1995); Chin W.W., Gopal A., Salisbury W.D., Advancing the theory of adaptive structuration: The development of a scale to measure faithfulness of appropriation, Information Systems Research, 8, 4, pp. 342-367, (1997); Chitturi R., Raghunathan R., Mahajan V., Delight by design: The role of hedonic versus utilitarian benefits, Journal of Marketing, 72, 3, pp. 48-63, (2008); Chiu C.M., Hsu M.H., Sun S.Y., Lin T.C., Sun P.C., Usability, quality, value and e-learning continuance decisions, Computers & Education, 45, 4, pp. 399-416, (2005); Collomb A., Costea C., Joyeux D., Hasan O., Brunie L., (2014); Creusen M.E.H., Schoormans J.P.L., The different roles of product appearance in consumer choice, Journal of Product Innovation Management, 22, 1, pp. 63-81, (2005); Curtin R., Presser S., Singer E., The effects of response rate changes on the index of consumer sentiment, Public Opinion Quarterly, 64, 4, pp. 413-428, (2000); Dabholkar P.A., Shepherd C., Thorpe D.I., A comprehensive framework for service quality: An investigation of critical conceptual and measurement issues through a longitudinal study, Journal of Retailing, 76, 2, pp. 139-173, (2000); Darby M.R., Karni E., Free competition and the optimal amount of fraud, The Journal of Law and Economics, 16"}},"Q. Gao; Department of Industrial Engineering, Tsinghua University, Beijing, 100084, China; email: gaoqin@tsinghua.edu.cn",null,"Taylor and Francis Ltd.",{"$nulls":5},1.0447318E7,null,null,null,"English","Int. J. Hum.-Comput. Interact.","Article","Final",null,"Scopus","2-s2.0-85131052213"]
["Mehmood M.S.; Jin A.; Rehman A.; Ahamad M.I.; Li G.","Mehmood, Muhammad Sajid (57214795943); Jin, Annan (57218367926); Rehman, Adnanul (57223242139); Ahamad, Muhammad Irfan (57204149061); Li, Gang (56948472900)","57214795943; 57218367926; 57223242139; 57204149061; 56948472900","Spatial variability and accessibility of collection and delivery points in Nanjing, China",2022.0,"Computational Urban Science",2.0,1.0,27.0,null,null,null,2.0,"10.1007/s43762-022-00054-x","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85139794973&doi=10.1007%2fs43762-022-00054-x&partnerID=40&md5=ad15c5f4e0e7d9352e86795c977f6315","College of Urban and Environmental Sciences, Northwest University, Xi’an, 710127, China; Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, Northwest University, Xi’an, 710127, China; Department of Geography, Government College University Lahore, Lahore, 54000, Pakistan","Mehmood M.S., College of Urban and Environmental Sciences, Northwest University, Xi’an, 710127, China, Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, Northwest University, Xi’an, 710127, China; Jin A., College of Urban and Environmental Sciences, Northwest University, Xi’an, 710127, China, Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, Northwest University, Xi’an, 710127, China; Rehman A., College of Urban and Environmental Sciences, Northwest University, Xi’an, 710127, China; Ahamad M.I., Department of Geography, Government College University Lahore, Lahore, 54000, Pakistan; Li G., College of Urban and Environmental Sciences, Northwest University, Xi’an, 710127, China, Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, Northwest University, Xi’an, 710127, China","Collection and delivery points are an alternative to home delivery and represent an important opportunity to reduce delivery failures in urban areas. As online shopping has become increasingly popular, different accessibility modes such as walking, cycling, and driving are considered for the collection of parcels at collection and delivery points (CDPs). The primary objective of the present study was to assess the spatial variability and accessibility of CDPs in Nanjing City, China. The point of interest (POI) data of 1224 CDPs (including 424 China Post Stations and 800 Cainiao Stations), and population and gross domestic product data were employed for the spatial analysis. The results showed that China Post Stations and Cainiao Stations were distributed in Nanjing as clusters at α = 0.01. Both types (51.1% China Post Stations and 63.2% Cainiao Stations) of CDPs were aggregated in the high population density areas. Moreover, 28.0% of China Post Stations and 50.9% of Cainiao Stations were located in high GDP density areas. The overall spatial distribution of China Post Stations in population and GDP density areas was medium, while that of the Cainiao Stations was high. There was a significant correlation between the spatial distribution of the CDPs, population, and GDP. There were significant spatial accessibility differences to CDPs among different accessibility modes like walking, cycling, and driving. Walking and cycling mode accessibility to China Post Stations and Cainiao Stations were 13.8 and 25.3% and 9.2 and 28.9%, respectively while 71.8% of China Post Stations and 71.1% of Cainiao Stations were accessed by driving. The findings of this study would be beneficial for policymakers and practitioners to develop related policies, to assist companies in building up more sustainable urban logistics and a booming CDPs’ network in the future. © 2022, The Author(s).","Accessibility; CDPs; Logistic enterprises; Nanjing; Spatial correlation",{"$nulls":5},"Northwest University, NWU","This study was supported by grants from the Tang Scholar Program of Northwest University (No. 2016). ","Ahvenniemi H., Huovila A., How do cities promote urban sustainability and smartness? An evaluation of the city strategies of six largest Finnish cities, Environment, Development and Sustainability, 23, pp. 4174-4200, (2021); Allen J., Thorne G., Browne M., BESTUFS Good Practice Guide on Urban Freight Transport, (2007); Anselin L., Getis A., Spatial statistical analysis and geographic information systems, The Annals of Regional Science, 26, 1, pp. 19-33, (1992); Bowes P., (2016); Boyer K.K., Prud'homme A.M., Chung W., The last mile challenge: Evaluating the effects of customer density and delivery window patterns, Journal of Business Logistics, 30, 1, pp. 185-201, (2009); Bureau S.P., Guiding Opinions of the State Post Bureau on Strengthening and Improving the Management of Express Terminal Services., (2017); Cardenas I., Beckers J., Vanelslander T., E-commerce last-mile in Belgium: Developing an external cost delivery index, Research in Transportation Business & Management, 24, pp. 123-129, (2017); Chen W., Liu L., Liang Y., Retail center recognition and spatial aggregating feature analysis of retail formats in Guangzhou based on POI data, Geographical Research, 35, 4, pp. 703-716, (2016); Cidell J., Concentration and decentralization: The new geography of freight distribution in US metropolitan areas, Journal of Transport Geography, 18, 3, pp. 363-371, (2010); Clement J., Global Retail E-Commerce Sales 2014–2021, (2019); Consoli D., The Global Market of Small Businesses by E-Commerce Platforms, Challenges of the Knowledge Society, (2016); Dell'Amico M., Hadjidimitriou S., Innovative logistics model and containers solution for efficient last-mile delivery, Procedia-Social and Behavioral Sciences, 48, pp. 1505-1514, (2012); Diaz-Varela E.R., Vazquez-Gonzalez I., Marey-Perez M.F., Alvarez-Lopez C.J., Assessing methods of mitigating wildlife–vehicle collisions by accident characterization and spatial analysis, Transportation Research Part d: Transport and Environment, 16, 4, pp. 281-287, (2011); du Preez D., Zuidgeest M., Behrens R., A quantitative clustering analysis of paratransit route typology and operating attributes in Cape Town, Journal of Transport Geography, 80, C, (2019); Edwards J.B., McKinnon A.C., Cullinane S.L., Comparative analysis of the carbon footprints of conventional and online retailing: A, International Journal of Physical Distribution & Logistics Management, 40, 1-2, pp. 103-123, (2010); Edwards J., McKinnon A., Cherrett T., McLeod F., Song L., Carbon dioxide benefits of using collection–delivery points for failed home deliveries in the United Kingdom, Transportation Research Record, 2191, 1, pp. 136-143, (2010); Feng J., Yang Z., Factors influencing travel behavior of urban elderly people in Nanjing, Progress in Geography, 34, 12, pp. 1598-1608, (2015); Gonzalez-Feliu J., Ambrosini C., Routhier J.L., New trends on urban goods movement: Modeling and simulation of e-commerce distribution. European Transport, 50, Paper-N, (2012); Haustein S., Nielsen T.A.S., European mobility cultures: A survey-based cluster analysis across 28 European countries, Journal of Transport Geography, 54, pp. 173-180, (2016); Iwan S., Kijewska K., Lemke J., Analysis of parcel lockers’ efficiency as the last mile delivery solution–the results of the research in Poland, Transportation Research Procedia, 12, pp. 644-655, (2016); Jia R., Khadka A., Kim I., Traffic crash analysis with point-of-interest spatial clustering, Accident Analysis & Prevention, 121, pp. 223-230, (2018); Kamarainen V., Saranen J., Holmstrom J., The reception box impact on home delivery efficiency in the e-grocery business, International Journal of Physical Distribution and Logistics Management, 31, 6, pp. 414-426, (2001); Kedia A., Kusumastuti D., Nicholson A., Acceptability of collection and delivery points from consumers’ perspective: A qualitative case study of Christchurch city, Case Studies on Transport Policy, 5, 4, pp. 587-595, (2017); Kumar R., Mishra R.K., Chandra S., Hussain A., Evaluation of urban transport-environment sustainable indicators during Odd-Even scheme in India, Environment, Development and Sustainability, 23, pp. 17240-17262, (2021); Lei C., China Online Retail Market Data Monitoring Report. E.-C. R, Cente, (2018); Lemke J., Iwan S., Korczak J., Usability of the parcel lockers from the customer perspective–the research in Polish Cities, Transportation Research Procedia, 16, pp. 272-287, (2016); Liu L., Zhang C., Feng J., Xiao L., He Z., Zhou S., The spatial-temporal distribution and influencing factors of fraud crime in ZG city, China. Acta Geogr. Sin, 72, pp. 315-328, (2017); McKinnon A.C., Tallam D., Unattended delivery to the home: An assessment of the security implications, International Journal of Retail and Distribution Management, 31, 1, pp. 30-41, (2003); McLeod F.N., Cherrett T.J., Quantifying the environmental benefits of collection/delivery points, Or Insight, 22, 3, pp. 127-139, (2009); McLeod F., Cherrett T., Song L., Transport impacts of local collection/delivery points, International Journal of Logistics, 9, 3, pp. 307-317, (2006); Morganti E., Dablanc L., Fortin F., Final deliveries for online shopping: The deployment of pickup point networks in urban and suburban areas, Research in Transportation Business & Management, 11, pp. 23-31, (2014); Ord J.K., Getis A., Local spatial autocorrelation statistics: Distributional issues and an application, Geographical Analysis, 27, 4, pp. 286-306, (1995); Ord J.K., Getis A., Testing for local spatial autocorrelation in the presence of global autocorrelation, Journal of Regional Science, 41, 3, pp. 411-432, (2001); O'sullivan P., Online Shopping: Pearls and Pitfalls for New Zealand Consumers–How to Increase Consumer Protection and Build Consumer Confidence, Researchspace@ Auckland]., (2017); Punakivi M., Yrjola H., Holmstrom J., Solving the last mile issue: Reception box or delivery box?, International Journal of Physical Distribution and Logistics Management, 31, 6, pp. 427-439, (2001); Schweitzer L., Environmental justice and hazmat transport: A spatial analysis in southern California, Transportation Research Part d: Transport and Environment, 11, 6, pp. 408-421, (2006); Song L., Cherrett T., McLeod F., Guan W., Addressing the last mile problem: Transport impacts of collection and delivery points, Transportation Research Record, 2097, 1, pp. 9-18, (2009); Song L., Guan W., Cherrett T., Li B., Quantifying the greenhouse gas emissions of local collection-and-delivery points for last-mile deliveries, Transportation Research Record, 2340, 1, pp. 66-73, (2013); Taniguchi E., Kakimoto Y., Modeling effects of e-commerce on urban freight transport, Logistics Systems for Sustainable Cities, 10, pp. 135-146, (2004); Van Duin J., De Goffau W., Wiegmans B., Tavasszy L., Saes M., Improving home delivery efficiency by using principles of address intelligence for B2C deliveries, Transportation Research Procedia, 12, 2, pp. 14-25, (2016); Visser J., Nemoto T., Browne M., Home delivery and the impacts on urban freight transport: A review, Procedia-Social and Behavioral Sciences, 125, pp. 15-27, (2014); Wenhao Y., Tinghua A., The visualization and analysis of POI features under network space supported by kernel density estimation, Acta Geodaetica Et Cartographica Sinica, 44, 1, (2015); Wu C., Ye X., Ren F., Du Q., Check-in behaviour and spatio-temporal vibrancy: An exploratory analysis in Shenzhen, China, Cities, 77, pp. 104-116, (2018); Xu J.-J., Hong L., Impact factors of choosing willingness for picking up service, Engineering and Technology, 6, 14, pp. 2509-2513, (2013); Xu J., Jiang L., Wang S., Construction of Pick-Up Points in China E-Commerce Logistics. (Ed.), (2014); Yang X., Status of third party logistics–a comprehensive review, Journal of Logistics Management, 3, 1, pp. 17-20, (2014)","G. Li; College of Urban and Environmental Sciences, Northwest University, Xi’an, 710127, China; email: liglzu@gmail.com",null,"Springer",{"$nulls":5},2.7306852E7,null,null,null,"English","Comput. Urban Sci.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85139794973"]
["Al-Adwan A.S.; Al-Debei M.M.; Dwivedi Y.K.","Al-Adwan, Ahmad Samed (57126225800); Al-Debei, Mutaz M. (35753216500); Dwivedi, Yogesh K. (35239818900)","57126225800; 35753216500; 35239818900","E-commerce in high uncertainty avoidance cultures: The driving forces of repurchase and word-of-mouth intentions",2022.0,"Technology in Society",71.0,null,102083.0,null,null,null,34.0,"10.1016/j.techsoc.2022.102083","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85136117479&doi=10.1016%2fj.techsoc.2022.102083&partnerID=40&md5=2102b0ddae4eac3057c1a32c48567ede","Department of Electronic Business and Commerce, Business School, Al-Ahliyya Amman University, Amman, Jordan; Department of Business Analytics Technology, Business School, Al-Ahliyya Amman University, Amman, Jordan; Department of Management Information Systems, Business School, The University of Jordan, Amman, Jordan; Emerging Markets Research Centre (EMaRC), School of Management, Swansea University, Bay Campus, Room #323, Fabian Bay, Swansea, SA1 8EN, Wales, United Kingdom; Department of Management, Symbiosis Institute of Business Management, Pune & Symbiosis International (Deemed University), Maharashtra, Pune, India","Al-Adwan A.S., Department of Electronic Business and Commerce, Business School, Al-Ahliyya Amman University, Amman, Jordan; Al-Debei M.M., Department of Business Analytics Technology, Business School, Al-Ahliyya Amman University, Amman, Jordan, Department of Management Information Systems, Business School, The University of Jordan, Amman, Jordan; Dwivedi Y.K., Emerging Markets Research Centre (EMaRC), School of Management, Swansea University, Bay Campus, Room #323, Fabian Bay, Swansea, SA1 8EN, Wales, United Kingdom, Department of Management, Symbiosis Institute of Business Management, Pune & Symbiosis International (Deemed University), Maharashtra, Pune, India","This study proposes and empirically tests a contextualized model for investigating repurchase intentions of e-commerce consumers as well as their word-of-mouth (WOM) intentions in high uncertainty avoidance cultures and based on a synthesis of the S–O-R paradigm and Information Processing Theory (IPT). Data for the study were collected from 560 Jordanian online customers and analysed using structural equation modelling (PLS-SEM). The findings demonstrated that the dimensions of policy service quality including cash-on-delivery (COD) payment options and return policy leniency, positively influenced customer trust. In addition, electronic logistics service quality (LSQ) dimensions positively impacted customer satisfaction. Furthermore, it was found that satisfaction of online consumers is a major driver of their trust, repurchase, and WOM intentions. While customer trust was revealed as a key enabler of repurchase intention, its effect on WOM was insignificant. The findings provide useful implications for both practice and future research. © 2022 Elsevier Ltd","Cash on delivery; e-commerce; Online shopping; Repurchase intention; Return policy leniency; Satisfaction; Trust; Uncertainty avoidance; WOM","Jordan; Electronic commerce; Quality of service; Sales; Cash-on-delivery; Customer trust; E- commerces; Online shopping; Repurchase intention; Return policy; Return policy leniency; Satisfaction; Trust; Uncertainty avoidance; electronic commerce; empirical analysis; marketing; numerical model; shopping activity; Customer satisfaction",{"$nulls":6},{"$cut":{"chars":32736,"head":"Gawor T., Hoberg K., Customers' valuation of time and convenience in e-fulfillment, Int. J. Phys. Distrib. Logist. Manag., 49, 1, pp. 75-98, (2019); Tandon U., Kiran R., Sah A.N., The influence of website functionality, drivers and perceived risk on customer satisfaction in online shopping: an emerging economy case, Inf. Syst. E Bus. Manag., 16, 1, pp. 57-91, (2018); Sahney S., Ghosh K., Shrivastava A., Buyer's motivation” for online buying: an empirical case of railway e-ticketing in Indian context, J. Asia Busi. Stud., 8, 1, pp. 43-64, (2014); Vasic N., Kilibarda M., Kaurin T., The influence of online shopping determinants on customer satisfaction in the Serbian market, J. theoretical and applied elect. commerce res., 14, 2, pp. 70-89, (2019); Hamed S., El-Deeb S., Cash on delivery as a determinant of e-commerce growth in emerging markets, J. Global Market., 33, 4, pp. 242-265, (2020); Harris P., Riley F.D., Riley D., Hand C., Online and store patronage: a typology of grocery shoppers, Int. J. Retail Distrib. Manag., 45, 4, pp. 419-445, (2017); Harake W., Strategic Assessment: the 2019 Project Pipeline for Jordan and Investment Opportunities, pp. 1-34, (2019); (2021); Statista, eCommerce - Jordan | Statista Market Forecast, (2021); Sector Profile: Transportation and Logistics, (2018); Al-Omoush K.S., de Lucas Ancillo A., Gavrila S.G., The role of cultural values in social commerce adoption in the Arab world: an empirical study, Technol. Forecast. Soc. Change, 176, (2022); SaleCycle, (2018); Hofstede G., Organizations and Cultures: Software of the Mind, (1991); Yildirim E., Barutcu M.T., How uncertainty avoidance, power distance and indulgence affect social commerce expenditure? An investigation based on Facebook, Int. J. Sport Cultu. Sci., 4, 4, pp. 403-421, (2016); Yao Y., Boardman R., Vazquez D., Cultural Considerations in social commerce: the differences and potential opportunities in China, Social Commerce, pp. 43-58, (2019); Kwak J., Zhang Y., Yu J., Legitimacy building and e-commerce platform development in China: the experience of Alibaba, Technol. Forecast. Soc. Change, 139, pp. 115-124, (2019); Zhu L., Thatcher S., National information ecology: a new institutional economics perspective on global e-commerce adoption, J. Electron. Commer. Res., 11, 1, pp. 53-72, (2010); Ayob A.H., E-commerce adoption in ASEAN: who and where?, Future business J., 7, 1, pp. 1-11, (2021); Zhang X., Investigation of e‐commerce in China in a geographical perspective, Growth Change, 50, 3, pp. 1062-1084, (2019); Azam M.S., Morsalin M., Rakib M.R.H.K., Pramanik S.A.K., Adoption of Electronic Commerce by Individuals in Bangladesh, (2021); Ahamed A.J., Limbu Y., Pham L., Van Nguyen H., Understanding Vietnamese consumer intention to use online retailer websites: application of the extended technology acceptance model, Int. J. E-Adoption (IJEA), 12, 2, pp. 1-15, (2020); Lim Y.M., Cham T.H., A profile of the Internet shoppers: evidence from nine countries, Telematics Inf., 32, 2, pp. 344-354, (2015); Yadav R., Mahara T., Factors affecting e-commerce adoption by handicraft SMEs of India, J. Electron. Commer. Org., 17, 4, pp. 44-57, (2019); Garg A.K., Choeu T., The adoption of electronic commerce by small and medium enterprises in Pretoria East, Electron. J. Inf. Syst. Dev. Ctries., 68, 1, pp. 1-23, (2015); Lawrence J.E., Tar U.A., Barriers to e-commerce in developing countries, Info. society and justice J., 3, 1, pp. 23-35, (2010); Oxley J.E., Yeung B., E-commerce readiness: institutional environment and international competitiveness, J. Int. Bus. Stud., 32, 4, pp. 705-723, (2001); Chang M.K., Cheung W., Tang M., Building trust online: interactions among trust building mechanisms, Inf. Manag., 50, 7, pp. 439-445, (2013); Al-Adwan A.S., Kokash H., Adwan A.A., Alhorani A., Yaseen H., Building customer loyalty in online shopping: the role of online trust, online satisfaction and electronic word of mouth, Int. J. Electron. Market. Retailing., 11, 3, pp. 278-306, (2020); Al-Adwan A.S., Revealing the influential factors driving social commerce ado"}},"M.M. Al-Debei; Department of Business Analytics Technology, Business School, Al-Ahliyya Amman University, Amman, Jordan; email: mdebei@ammanu.edu.jo",null,"Elsevier Ltd",{"$nulls":5},"0160791X",null,null,null,"English","Technol. Soc.","Article","Final",null,"Scopus","2-s2.0-85136117479"]
["Chen S.; Wang Y.; Han S.; Lim M.K.","Chen, Shan (57740900600); Wang, Yibing (57324232900); Han, Shuihua (16202478800); Lim, Ming K. (7201473042)","57740900600; 57324232900; 16202478800; 7201473042","Evaluation of fresh food logistics service quality using online customer reviews",2023.0,"International Journal of Logistics Research and Applications",26.0,8.0,null,917.0,933.0,16.0,7.0,"10.1080/13675567.2021.1998398","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85118532684&doi=10.1080%2f13675567.2021.1998398&partnerID=40&md5=c1c3e7ac3df8e3bc3b58d87839956e7b","School of Economics and Management, Fuzhou University of International Studies and Trade, Fuzhou, China; Department of Management Science, School of Management, Xiamen University, Xiamen, China; Centre for Business in Society, Faculty of Business and Law, Coventry University, Coventry, United Kingdom","Chen S., School of Economics and Management, Fuzhou University of International Studies and Trade, Fuzhou, China; Wang Y., Department of Management Science, School of Management, Xiamen University, Xiamen, China; Han S., Department of Management Science, School of Management, Xiamen University, Xiamen, China; Lim M.K., Centre for Business in Society, Faculty of Business and Law, Coventry University, Coventry, United Kingdom","Improving the quality of cold chain logistics services is a great challenge for fresh food e-commerce companies. Traditionally, the evaluation of logistics service quality has been carried out mainly through questionnaire surveys and expert groups, which are time-consuming and laborious. Unlike previous studies, in this study, we used a latent Dirichlet allocation model to explore logistics services using customer reviews on the ‘fresh food’ category of JD.com, one of China’s most popular e-commerce websites. By revising the evaluation index system for logistics service quality, we put forward an evaluation system that covers six dimensions: reliability, security, timeliness, economy, pleasantness and convenience. We then incorporated sentiment analysis technology and the TF-IDF (Term Frequency-Inverse Document Frequency) algorithm to obtain a total score for the service quality of JD’s fresh food logistics. This study provides a reference for other B2C fresh e-commerce enterprises on the implementation of logistics service quality evaluation and management. © 2021 Informa UK Limited, trading as Taylor & Francis Group.","evaluation system; fresh food e-commerce; Logistics service quality; online reviews; text mining",{"$nulls":5},"National Natural Science Foundation of China, NSFC, (71671152)","This study is partially supported by National Natural Science Foundation of China under Grant No.71671152. Fruitful discussion with co-authors is gratefully acknowledged. ","Buyukozkan G., Cifci G., A Combined Fuzzy AHP and Fuzzy TOPSIS Based Strategic Analysis of Electronic Service Quality in Healthcare Industry, Expert Systems with Applications, 39, 3, pp. 2341-2354, (2012); Choi T.M., Incorporating Social Media Observations and Bounded Rationality Into Fashion Quick Response Supply Chains in the Big Data Era, Transportation Research Part E: Logistics and Transportation Review, 114, pp. 386-397, (2018); Colla E., Lapoule P., E-commerce: Exploring the Critical Success Factors, International Journal of Retail & Distribution Management, 40, 11, pp. 842-864, (2012); Filieri R., McLeay F., Tsui B., Lin Z.B., Consumer Perceptions of Information Helpfulness and Determinants of Purchase Intention in Online Consumer Reviews of Services, Information & Management, 55, 8, pp. 956-970, (2018); Ha S., Stoel L., Consumer e-Shopping Acceptance: Antecedents in a Technology Acceptance Model, Journal of Business Research, 62, 5, pp. 565-571, (2009); Han Y.X., Xie G.Y., Determinants of Customer Perceived Online Shopping Logistics Service Quality Value: An Empirical Study from China, International Journal of Logistics Research and Applications, 22, 6, pp. 614-637, (2019); Kilibarda M., Nikolicic S., Andrejic M., Measurement of Logistics Service Quality in Freight Forwarding Companies: A Case Study of the Serbian Market, The International Journal of Logistics Management, 27, 3, pp. 770-794, (2016); Kumar N., Benbasat I., The Influence of Recommendations and Consumer Reviews on Evaluations of Websites, Information Systems Research, 17, 4, pp. 425-439, (2006); Lee C.K.H., Tse Y.K., Improving Peer-to-Peer Accommodation Service Based on Text Analytics, Industrial Management and Data Systems, 121, 2, (2021); Li X.L., Wu C.J., Mai F., The Effect of Online Reviews on Product Sales: A Joint Sentiment-Topic Analysis, Information & Management, 56, 2, pp. 172-184, (2019); Liao C.-N., Kao H.-P., An Evaluation Approach to Logistics Service Using Fuzzy Theory, Quality Function Development and Goal Programming, Computers and Industrial Engineering, 68, pp. 54-64, (2014); Liu Y., Jiang C.Q., Zhao H.M., Assessing Product Competitive Advantages from the Perspective of Customers by Mining User-Generated Content on Social Media, Decision Support Systems, 123, pp. 1-13, (2019); Lucini F.R., Tonetto L.M., Fogliatto F.S., Anzanello M.J., Text Mining Approach to Explore Dimensions of Airline Customer Satisfaction Using Online Customer Reviews, Journal of Air Transport Management, 83, Mar., pp. 101760.1-101760.12, (2020); Ma J., Tse Y.K., Wang X.J., Zhang M.H., Examining Customer Perception and Behaviour Through Social Media Research–An Empirical Study of the United Airlines Overbooking Crisis, Transportation Research Part E: Logistics and Transportation Review, 127, pp. 192-205, (2019); Matthias O., Fouweather I., Gregory I., Vernon A., Making Sense of Big Data–Can It Transform Operations Management?, International Journal of Operations and Production Management, 37, 1, pp. 37-55, (2017); Mudambi S.M., Schuff D., What Makes a Helpful Online Review? A Study of Customer Reviews on Amazon.com, MIS Quarterly, 34, 1, pp. 185-200, (2010); Munzel A., Kunz W.H., Creators, Multipliers, and Lurkers: Who Contributes and Who Benefits at Online Review Sites, Social Science Electronic Publishing, 25, 1, pp. 49-74, (2014); Murfield M., Boone C.A., Rutner P., Et al., Investigating Logistics Service Quality in Omni-Channel Retailing, International Journal of Physical Distribution and Logistics Management, 47, 4, pp. 263-296, (2017); Pan Y., Zhang J.Q., Born Unequal: A Study of the Helpfulness of User-Generated Product Reviews, Journal of Retailing, 87, 4, pp. 598-612, (2011); Parasuraman A., Zeithaml V.A., Berry L.L., SERVQUAL: A Multiple-Item Scale for Measuring Consumer Perceptions of Service Quality, Journal of Retailing, 64, 1, pp. 12-40, (1988); Parasuraman A., Zeithaml V.A., Malhotra A., ES-QUAL: A Multiple-Item Scale for Assessing Electronic Service Quality, Journal of Service Research, 7, 3, pp. 213-233, (2005); Rajendran S., Improving the Performance of Global Courier & Delivery Services Industry by Analyzing the Voice of Customers and Employees Using Text Analytics, International Journal of Logistics Research and Applications. Published Online, (2020); Roca J.C., Garcia J.J., De La Vega J.J., The Importance of Perceived Trust, Security and Privacy in Online Trading Systems, Information Management & Computer Security, 17, 2, pp. 96-113, (2009); Sheng J., Amankwah-Amoah J., Wang X., A Multidisciplinary Perspective of Big Data in Management Research, International Journal of Production Economics, 191, 1, pp. 97-112, (2017); Sohn J.I., Woo S.H., Kim T.W., Assessment of Logistics Service Quality Using the Kano Model in a Logistics-Triadic Relationship, International Journal of Logs Management, 28, 2, pp. 680-698, (2017); Tan K.H., Ji G., Lim C., Tseng M.L., Using Big Data to Make Better Decisions in the Digital Economy, International Journal of Production Economics, 55, 1, pp. 4998-5000, (2017); Thai V.V., Logistics Service Quality: Conceptual Model and Empirical Evidence, International Journal of Logistics Research and Applications, 16, 2, pp. 114-131, (2013); Udo G.J., Bagchi K.K., Kirs P.J., An Assessment of Customers’ e-Service Quality Perception, Satisfaction and Intention, International Journal of Information Management, 30, 6, pp. 481-492, (2010); Verbic M., Discussing the Parameters of Preservation of Perishable Goods in a Cold Logistic Chain Model, Applied Economics, 38, 2, pp. 137-147, (2006); Xiao S., Wei C.P., Dong M., Crowd Intelligence: Analyzing Online Product Reviews for Preference Measurement, Information & Management, 53, 2, pp. 169-182, (2016); Xu J., Cao Z.P., Logistics Service Quality Analysis Based on Gray Correlation Method, International Journal of Business and Management, 3, 1, pp. 58-61, (2008); Yang L., Tang R.H., Comparisons of Sales Modes for a Fresh Product Supply Chain with Freshness-Keeping Effort, Transportation Research Part E: Logistics and Transportation Review, 125, pp. 425-448, (2019); Zeithaml V.A., Parasuraman A., Malhotra A., (2000)","S. Han; Department of Management Science, School of Management, Xiamen University, Xiamen, China; email: hansh@xmu.edu.cn",null,"Taylor and Francis Ltd.",{"$nulls":5},1.3675567E7,null,null,null,"English","Int. J. Logist. Res. Applic.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85118532684"]
["Quan N.H.; Binh N.T.; Ly B.T.","Quan, Nguyen Hong (57210928823); Binh, Nguyen Thi (57346045500); Ly, Bui Thi (57346858100)","57210928823; 57346045500; 57346858100","Impact of smart locker use on customer satisfaction of online shoppers in Vietnam",2022.0,"Humanities and Social Sciences Communications",9.0,1.0,403.0,null,null,null,4.0,"10.1057/s41599-022-01428-6","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85141203064&doi=10.1057%2fs41599-022-01428-6&partnerID=40&md5=22aec4a4e4a7bb26ab034928dcb34d2f","Foreign Trade University, Hanoi, Viet Nam","Quan N.H., Foreign Trade University, Hanoi, Viet Nam; Binh N.T., Foreign Trade University, Hanoi, Viet Nam; Ly B.T., Foreign Trade University, Hanoi, Viet Nam","In recent years, smart lockers have been increasingly utilised in the last-mile delivery stage of e-commerce. Although this technological advance has received significant scientific attention, especially in developed countries, little is known about the general behaviour of Smart Locker users. This study aimed to explore the impact of smart locker use on customer satisfaction with online shopping experience. We used structural equation modelling to analyse data collected from 442 smart locker users in Vietnam. The results revealed that convenience, privacy and security, and reliability attributes significantly impacted the satisfaction of smart locker users through the mediators of perceived value and transaction costs. These findings are expected to reinforce the utilised theories and enrich theoretical research on self-service technologies in last-mile delivery and their influence on consumer behaviour. © 2022, The Author(s).",{"$nulls":6},"Foreign Trade University, (FTURP02-2020-10)","This research is funded by the Foreign Trade University (FTU) under the research programme number FTURP02-2020-10. 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Binh; Foreign Trade University, Hanoi, Viet Nam; email: ntbinh@ftu.edu.vn",null,"Springer Nature",{"$nulls":5},2.6629992E7,null,null,null,"English","Hum. Soc. Sci. Comm","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85141203064"]
["Balaska V.; Tsiakas K.; Giakoumis D.; Kostavelis I.; Folinas D.; Gasteratos A.; Tzovaras D.","Balaska, Vasiliki (57204061279); Tsiakas, Kosmas (57222999334); Giakoumis, Dimitrios (35147896000); Kostavelis, Ioannis (35484641300); Folinas, Dimitrios (6506784509); Gasteratos, Antonios (6701673537); Tzovaras, Dimitrios (13105681700)","57204061279; 57222999334; 35147896000; 35484641300; 6506784509; 6701673537; 13105681700","A Viewpoint on the Challenges and Solutions for Driverless Last-Mile Delivery",2022.0,"Machines",10.0,11.0,1059.0,null,null,null,7.0,"10.3390/machines10111059","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85149932704&doi=10.3390%2fmachines10111059&partnerID=40&md5=7eba8515208a0ee0750db83e2ee17de0","Department of Production and Management Engineering, Democritus University of Thrace, Komotini, 691 00, Greece; Centre for Research and Technology Hellas, Information Technologies Institute, Thessaloniki, 570 01, Greece; Department of Supply Chain Management, International Hellenic University, Thessaloniki, 570 01, Greece","Balaska V., Department of Production and Management Engineering, Democritus University of Thrace, Komotini, 691 00, Greece; Tsiakas K., Department of Production and Management Engineering, Democritus University of Thrace, Komotini, 691 00, Greece, Centre for Research and Technology Hellas, Information Technologies Institute, Thessaloniki, 570 01, Greece; Giakoumis D., Centre for Research and Technology Hellas, Information Technologies Institute, Thessaloniki, 570 01, Greece; Kostavelis I., Centre for Research and Technology Hellas, Information Technologies Institute, Thessaloniki, 570 01, Greece, Department of Supply Chain Management, International Hellenic University, Thessaloniki, 570 01, Greece; Folinas D., Department of Supply Chain Management, International Hellenic University, Thessaloniki, 570 01, Greece; Gasteratos A., Department of Production and Management Engineering, Democritus University of Thrace, Komotini, 691 00, Greece; Tzovaras D., Centre for Research and Technology Hellas, Information Technologies Institute, Thessaloniki, 570 01, Greece","The occurring growth in e-commerce comes along with an increasing number of first-time delivery failures due to the customer’s absence at the delivery location. Failed deliveries result in rework, causing a significant impact on the carriers’ delivery cost. Hence, the last mile is the portion of a journey that involves moving people and commodities from a transportation hub to a final destination, which should be an efficient process. The above-mentioned concept is used in supply chain management and transportation planning. The paper at hand is a position paper that aims to scrutinize the concept of driverless last-mile delivery, with autonomous vehicles, in order to highlight and stress the challenges and limitations in the existing technology that hinder level five autonomous driving. Specifically, this work documents the current capabilities of the existing autonomous vehicles’ perception and cognition system and outlines their future skills towards addressing complete autonomous last-mile delivery, as well as efficient robotic process automation in logistics from warehouse/distribution center to hub’s delivery. © 2022 by the authors.","autonomous vehicles; driverless delivery; last-mile automation; last-mile delivery challenges; perception and cognition challenges",{"$nulls":7},"Boonsothonsatit G., Hankla N., Choowitsakunlert S., Strategic Design for Warehouse 4.0 Readiness in Thailand, Proceedings of the 2020 2nd International Conference on Management Science and Industrial Engineering, pp. 214-218; Marsden N., Bernecker T., Zollner R., Sussmann N., Kapser S., BUGA: log–A real-world laboratory approach to designing an automated transport system for goods in Urban Areas, Proceedings of the 2018 IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC), pp. 1-9, (2018); Taniguchi E., City logistics for sustainable and liveable cities, Green Logistics and Transportation, pp. 49-60, (2015); Faisal A., Kamruzzaman M., Yigitcanlar T., Currie G., Understanding autonomous vehicles, J. 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Comput, 21, pp. 264-277, (2020); Zaman U.K.U., Aqeel A.B., Naveed K., Asad U., Nawaz H., Gufran M., Development of Automated Guided Vehicle for Warehouse Automation of a Textile Factory, Proceedings of the 2021 International Conference on Robotics and Automation in Industry (ICRAI), pp. 1-6, (2021); Cao J., Zhang S., Research and Design of RFID-based Equipment Incident Management System for Industry 4.0, Proceedings of the 2016 4th International Conference on Electrical & Electronics Engineering and Computer Science (ICEEECS 2016), pp. 889-894, (2016)","V. Balaska; Department of Production and Management Engineering, Democritus University of Thrace, Komotini, 691 00, Greece; email: vbalaska@pme.duth.gr",null,"MDPI",{"$nulls":5},2.0751702E7,null,null,null,"English","Mach.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85149932704"]
["Lin J.; Nie Y.M.; Kawamura K.","Lin, Jane (57200149177); Nie, Yu Marco (23568634300); Kawamura, Kazuya (23982686100)","57200149177; 23568634300; 23982686100","An Autonomous Modular Mobility Paradigm",2023.0,"IEEE Intelligent Transportation Systems Magazine",15.0,1.0,null,378.0,386.0,8.0,2.0,"10.1109/MITS.2022.3159484","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85127753502&doi=10.1109%2fMITS.2022.3159484&partnerID=40&md5=882aeba23d4bfed8f5607ab4e3d41c54","University of Illinois at Chicago, Department of Civil, Materials, and Environmental Engineering, Chicago, 60607, IL, United States; Northwestern University, Department of Civil and Environmental Engineering, Evanston, 60208, IL, United States; University of Illinois at Chicago, Department of Urban Planning and Policy, Chicago, 60607, IL, United States","Lin J., University of Illinois at Chicago, Department of Civil, Materials, and Environmental Engineering, Chicago, 60607, IL, United States; Nie Y.M., Northwestern University, Department of Civil and Environmental Engineering, Evanston, 60208, IL, United States; Kawamura K., University of Illinois at Chicago, Department of Urban Planning and Policy, Chicago, 60607, IL, United States","In the United States, public transit vehicles have a very low average load factor (10.1-12.4%), resulting in an excessive waste of seat capacity and poor fuel economy per passenger mile served. This problem is gravely exacerbated by the COVID-19 pandemic, which at its peak had caused more than 70% reduction in transit ridership nationwide. On the other hand, the rapid uptake of e-commerce, also accelerated by the pandemic, has put tremendous pressure on last-mile delivery. A co-modality system that integrates transit services with last-mile logistics offers a promising solution to better utilization/sharing of vehicle capacity and supporting infrastructure. Here we show such a system may be implemented based on Autonomous Modular Vehicle Technology (AMVT). At the core of AMVT is the ability to operate a fleet of modular autonomous vehicles or pods that can be moved, stationed, joined, and separated in real time. Coupling modularity with autonomy is poised to enable co-modality and beyond. We describe an AMVT bimodality system that provides integrated public transit and last-mile logistics services with a fleet of pods and discuss relevant research challenges and opportunities, research approaches, and real-world adoption issues.  © 2009-2012 IEEE.",null,"Fleet operations; Solid wastes; Urban transportation; % reductions; Last mile; Load factors; Lower average; Modular vehicles; Modulars; Public transit; Transit riderships; Transit vehicles; Vehicle technology; Fuel economy",{"$nulls":4},"National Science Foundation, NSF, (2127677)","The research is funded by the National Science Foundation (#2127677) Civil Infrastructure.","Report year national transit summary and trends: Appendix, National Transit Database (NTD), Washington, DC, USA, (2015); Chicago bus fleet information, ChicagoBus.org, (2022); Alternative Fuels Data Center, (2022); Public transportation ridership report-2020 second quarter, American Public Transportation Association (APTA), Washington, DC, USA, (2020); E-commerce in the time of COVID-19, OECD, Paris, France, (2020); 6 ways to reduce your last mile delivery costs in your business, Fixlastmile, (2022); NEXT, (2022); Dubai: A testing ground for future transport, CNN, (2022); Lambret F., UK to follow France in banning petrol and diesel cars by 2040-Going all electric, Electrek, (2020); Liu T., Ceder A., Rau A., Using deficit function to determine the minimum fleet size of an autonomous modular public transit system, Transp. 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J, 57, 4, pp. 399-428, (2018); Apichottanakul A., Thanawaritwatthana N., Arunyanart S., Profiting logistics businesses through optimised light rail transit system: Application to the city of Bangkok, Cogent Eng, 8, 1, pp. 111-951, (2021); Xie C.D., Wang X.F., Fukuda D., On the pricing of urban rail transit with track sharing freight service, Sustainability, 12, 7, (2020); Simoni M.D., Marcucci E., Gatta V., Claudel C.G., Potential last-mile impacts of crowdshipping services: A simulation-based evaluation, Transportation, 47, 4, pp. 1933-1954, (2020); Gatta V., Marcucci E., Nigro M., Serafini S., Sustainable urban freight transport adopting public transport-based crowdshipping for B2C deliveries, Eur. Transport Res. Rev, 11, 1, (2019); Gatta V., Marcucci E., Nigro M., Patella S.M., Serafini S., Public transport-based crowdshipping for sustainable city logistics: Assessing economic and environmental impacts, Sustainability, 11, 1, (2019); Cheng G., Guo D., Shi J., Qin Y., Planning city-wide package distribution using crowdsourced public transportation systems, IEEE Access, 7, pp. 1234-1246, (2019); Huang H.L., Savkin A.V., Huang C., Round trip routing for energy-efficient drone delivery based on a public transportation network, IEEE Trans. Transport. Electrific, 6, 3, pp. 1368-1376, (2020); AMVT Intro, (2021); Gendreau M., Guertin F., Potvin J.-Y., Taillard E., Parallel tabu search for real-Time vehicle routing and dispatching, Transp. Sci, 33, 4, pp. 381-390, (1999); Bent R., Van Hentenryck P., Scenario-based planning for partially dynamic vehicle routing with stochastic customers, Oper. Res, 52, 6, pp. 977-987, (2004); Seconmandi N., Margot F., Reoptimization approaches for the vehicle-routing problem with stochastic demands, Oper. Res, 57, 1, pp. 214-230, (2009); Curtis T., Merritt M., Chen C., Perlmutter D., Berez D., Ellis B., Partnerships between transit agencies and transportation network companies (TNCs), Transportation Research Board, Washington DC, USA, TCRP Research Rep, 204, (2019); Kuhr J., Bhat C.R., Duthie J., Ruiz N., Ridesharing & public-private partnerships: Current issues, a proposed framework and benefits, The 96th Transportation Research Board Annual Meeting, (2017); Schwieterman J.P., Livingston M., Slot Der S.Van, Partners in Transit: A Review of Partnerships between Transportation Network Companies and Public Agencies in the United States, (2018); Westervelt M., Schank J., Huang E., Partnerships with technology-enabled mobility companies: Lessons learned, J. Transp. Res. Board, Transp. Res. Rec, 2649, 1, pp. 106-112, (2017); Infrastructure financing intelligence specializing in public-private partnership, InfraPPP, (2022)","J. Lin; University of Illinois at Chicago, Department of Civil, Materials, and Environmental Engineering, Chicago, 60607, United States; email: janelin@uic.edu",null,"Institute of Electrical and Electronics Engineers Inc.",{"$nulls":5},1.939139E7,null,null,null,"English","IEEE Intell. Transp. Syst. Mag.","Article","Final",null,"Scopus","2-s2.0-85127753502"]
["Halbauer I.; Jacob S.; Klarmann M.","Halbauer, Ingo (57443000500); Jacob, Saskia (57790291700); Klarmann, Martin (20436212800)","57443000500; 57790291700; 20436212800","Brand presentation order in voice shopping: Understanding the effects of sequential product presentation",2022.0,"Journal of Retailing",98.0,4.0,null,759.0,778.0,19.0,2.0,"10.1016/j.jretai.2022.06.002","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85133751112&doi=10.1016%2fj.jretai.2022.06.002&partnerID=40&md5=ed0e1f7c89aa3075c932d01a77a6b00c","Karlsruhe Institute of Technology (KIT), Institute of Information Systems and Marketing (IISM), Zirkel 2, Building 20.21, Room 107, Karlsruhe, 76131, Germany","Halbauer I., Karlsruhe Institute of Technology (KIT), Institute of Information Systems and Marketing (IISM), Zirkel 2, Building 20.21, Room 107, Karlsruhe, 76131, Germany; Jacob S., Karlsruhe Institute of Technology (KIT), Institute of Information Systems and Marketing (IISM), Zirkel 2, Building 20.21, Room 107, Karlsruhe, 76131, Germany; Klarmann M., Karlsruhe Institute of Technology (KIT), Institute of Information Systems and Marketing (IISM), Zirkel 2, Building 20.21, Room 107, Karlsruhe, 76131, Germany","Nearly half of US households own a smart speaker with voice shopping functionality. Voice shopping product presentation is inherently sequential due to the audio delivery of information, which may give retailers the opportunity to influence customer decisions through the order in which brands are presented. This research examines the effect of brand order presentation in voice shopping and its impact on high-equity versus low-equity brands. Moreover, this research considers the moderating effect of product presentation format (simultaneous vs. sequential, audio vs. visual) on the impact of brand presentation order. The results of six experiments with more than 1,000 participants provide evidence that consumers attempt to balance competing concerns about risk in voice shopping with search costs because products are presented sequentially and information is reduced. If high-equity brands are presented first, the choice distribution in voice shopping is unimodal, with a peak at the first-presented products. However, a bimodal choice distribution results if low-equity brands are presented first. Importantly, choice distribution in voice shopping differs markedly from choice distribution when products are presented simultaneously and visually, as in online shopping. © 2022","Brand equity; Branding; Sequential search; Voice shopping",{"$nulls":5},"Alexander Mädche; European Marketing Academy; Sven Feurer; Torsten Bornemann; Wiebke Klingemann; Karlsruhe Institute of Technology, KIT, (GRK2739/1, INST_12138411-1_FUGG); Deutsche Forschungsgemeinschaft, DFG","Funding text 1: This paper is based on the first author's doctoral dissertation. Studies 1a, 1b, and 3 described in this paper were conducted in the Karlsruhe Decision & Design Lab (KD 2 Lab), which was funded by the DFG and the Karlsruhe Institute of Technology (INST_12138411-1_FUGG). The paper is funded by a DFG project (GRK2739/1 – Project Nr. 447089431 – Research Training Group: KD²School – Designing Adaptive Systems for Economic Decisions). The authors thank Verena Sauter for her invaluable help in running the lab experiments described in this paper. We thank Torsten Bornemann, Sven Feurer, Wiebke Klingemann, and Alexander Mädche as well as participants of the 47th and 48th Annual Conferences of the European Marketing Academy, for their advice and feedback. ; Funding text 2: This paper is based on the first author's doctoral dissertation. Studies 1a, 1b, and 3 described in this paper were conducted in the Karlsruhe Decision & Design Lab (KD2Lab), which was funded by the DFG and the Karlsruhe Institute of Technology (INST_12138411-1_FUGG). The paper is funded by a DFG project (GRK2739/1 – Project Nr. 447089431 – Research Training Group: KD²School – Designing Adaptive Systems for Economic Decisions). The authors thank Verena Sauter for her invaluable help in running the lab experiments described in this paper. We thank Torsten Bornemann, Sven Feurer, Wiebke Klingemann, and Alexander Mädche as well as participants of the 47th and 48th Annual Conferences of the European Marketing Academy, for their advice and feedback.","Basu S., Savani K., Choosing One at a Time? 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Examining the Role of AI Powered Voice Assistants in Influencing Consumer Brand Engagement, Journal of Business Research, 124, pp. 312-328, (2021); Mehta N., Rajiv S., Srinivasan K., Price Uncertainty and Consumer Search: A Structural Model of Consideration Set Formation, Marketing Science, 22, 1, pp. 58-84, (2003); Millroth P., Guath M., Juslin P., Memory and Decision Making: Effects of Sequential Presentation of Probabilities and Outcomes in Risky Prospects, Journal of Experimental Psychology: General, 148, 2, (2019); Mogilner C., Shiv B., Iyengar S.S., Eternal Quest for the Best: Sequential (vs. Simultaneous) Option Presentation Undermines Choice Commitment, Journal of Consumer Research, 39, 6, pp. 1300-1312, (2013); Montgomery C.A., Wernerfelt B., Risk Reduction and Umbrella Branding, Journal of Business, 65, 1, pp. 31-50, (1992); Narasimhan C., Wilcox R.T., Private Labels and the Channel Relationship: A Cross-Category Analysis, Journal of Business, 71, 4, pp. 573-600, (1998); Purington A., Taft J., Sannon S., Bazarova N.N., Taylor S.H., Alexa is My New BFF: Social Roles, User Satisfaction, and Personification of the Amazon Echo, Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems, pp. 2853-2859, (2017); Roets A., Hiel A.V., Item Selection and Validation of a Brief, 15-Item Version of the Need for Closure Scale, Personality and Individual Differences, 50, 1, pp. 90-94, (2011); Salisbury L.C., Feinberg F.M., All Things Considered? 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The Effect of Visual Presentation on Imagery and Product Evaluation, International Journal of Research in Marketing, 38, 4, pp. 935-952, (2021); Zwick R., Et al., Consumer Sequential Search: Not Enough or Too Much?, Marketing Science, 22, 4, pp. 503-519, (2003)","M. Klarmann; Karlsruhe Institute of Technology (KIT), Institute of Information Systems and Marketing (IISM), Karlsruhe, Zirkel 2, Building 20.21, Room 107, 76131, Germany; email: martin.klarmann@kit.edu",null,"Elsevier Ltd",{"$nulls":5},224359.0,null,null,null,"English","J. Retail.","Article","Final",null,"Scopus","2-s2.0-85133751112"]
["Rusli R.; Mohammad M.Z.; Azreena Kamaluddin N.; Bakar H.; Hafzi Md Isa M.","Rusli, Rusdi (57193577588); Mohammad, Mazlina Zaira (57224352593); Azreena Kamaluddin, Noor (57932051500); Bakar, Harun (55935640800); Hafzi Md Isa, Mohd (56500655400)","57193577588; 57224352593; 57932051500; 55935640800; 56500655400","A comparison of characteristics between food delivery riders with and without traffic crash experience during delivery in Malaysia",2022.0,"Case Studies on Transport Policy",10.0,4.0,null,2244.0,2250.0,6.0,7.0,"10.1016/j.cstp.2022.10.006","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85140084573&doi=10.1016%2fj.cstp.2022.10.006&partnerID=40&md5=4b56e7b10a41b86ed6373d444dd5a4e5","School of Civil Engineering, College of Engineering, Universiti Teknologi MARA, Selangor, Shah Alam, 40450, Malaysia; Prevention, Medical and Rehabilitation Division, Social Security Organization (SOCSO), Ministry of Human Resources, Menara PERKESO, 281, Jalan Ampang, Kuala Lumpur, 50538, Malaysia","Rusli R., School of Civil Engineering, College of Engineering, Universiti Teknologi MARA, Selangor, Shah Alam, 40450, Malaysia; Mohammad M.Z., School of Civil Engineering, College of Engineering, Universiti Teknologi MARA, Selangor, Shah Alam, 40450, Malaysia; Azreena Kamaluddin N., School of Civil Engineering, College of Engineering, Universiti Teknologi MARA, Selangor, Shah Alam, 40450, Malaysia; Bakar H., Prevention, Medical and Rehabilitation Division, Social Security Organization (SOCSO), Ministry of Human Resources, Menara PERKESO, 281, Jalan Ampang, Kuala Lumpur, 50538, Malaysia; Hafzi Md Isa M., Prevention, Medical and Rehabilitation Division, Social Security Organization (SOCSO), Ministry of Human Resources, Menara PERKESO, 281, Jalan Ampang, Kuala Lumpur, 50538, Malaysia","The rapid development of e-commerce and the spread of the COVID-19 virus created many new jobs opportunity including food delivery riders known as P-Hailing riders. The number of food delivery riders has increased drastically, especially in Malaysia. Consequently, the number of food delivery riders involved in traffic crashes also increased. This study aimed to examine the characteristics of food delivery riders involved in traffic crashes during delivery and to compare with the characteristics of food delivery riders without any traffic crash history. This paper explores and compares general characteristics, previous experience of working and receiving traffic tickets, and knowledge of road safety. Due to unavailable official records about the number of active food delivery riders in Malaysia, this study focuses on riders who registered as members of the Malaysian P-Hailing Association, PENGHANTAR. A total of 225 food delivery riders participated in the online survey conducted through Google Form. Categorical data analysis techniques were used to examine the different characteristics of food delivery riders with and without traffic crash experiences. Results show that the odds ratio of young and full-time riders are respectively about 2.05 times and 1.79 times higher than being involved in traffic crashes. Other factors that increase the odds of being involved in traffic crashes include having more than two years of experience in delivery, an average distance travelled of>100 km a day, working previously in the food and grocery sector, and without working experience. The findings from this study will help related agencies to design and develop awareness programs targeting this group of riders. © 2022 World Conference on Transport Research Society","Food delivery riders; Motorcycle; P-Hailing; Riding behaviours; Traffic crash","Malaysia; COVID-19; viral disease; virus",{"$nulls":6},"Self-Employment Social Security Act 2017 (Act 789) (2017), (2017); Ashkrof P., de Almeida Correia G.H., Cats O., van Arem B., Understanding ride-sourcing drivers’ behaviour and preferences: Insights from focus groups analysis, Res. Transp. Bus Manag., 37, (2020); Bernama, Socso: Over 150 accidents involving delivery riders from March to June last year, Bernama, (2021); Byun J.H., Jeong B.Y., Park M.H., Characteristics of motorcycle crashes of food delivery workers, J. Ergon. Soc. Korea, 36, 2, pp. 157-168, (2017); Byun J.H., Park M.H., Jeong B.Y., Effects of age and violations on occupational accidents among motorcyclists performing food delivery, Work., 65, 1, pp. 53-61, (2020); Dave G.; Dave G.; Employment Act 1995 (Act 265) (1995); Hair J.F., Black W.C., Babin B.J., Anderson R.E., Multivariate Data Analysis, (2018); Haworth N., Rowden P., pp. 1-16, (2010); Kulanthayan S., See L.G., Kaviyarasu Y., Afiah M.Z.N., Prevalence and determinants of non-standard motorcycle safety helmets amongst food delivery workers in Selangor and Kuala Lumpur, Injury., 43, 5, pp. 653-659, (2012); Luca D.L., Do traffic tickets reduce motor vehicle accidents? Evidence from a natural experiment, J. Policy Anal. Manag., 34, 1, pp. 85-106, (2015); Lyon C., Persaud B., Donnell E., Safety evaluation of the SafetyEdge treatment for pavement edge drop-offs on two-lane rural roads, Transp. Res. Rec., 2672, 30, pp. 1-8, (2018); M B.; Manan M.M.A., Varhelyi A., Motorcycle fatalities in Malaysia, IATSS Res., 36, 1, pp. 30-39, (2012); Murugiah S.; Nair K.S., Impact of E-Commerce on Global Business And Opportunities–A Conceptual Study, Dubai Int. J. Adv. Eng. Manag. Res., 2, 2, (2017); Nguyen-Phuoc D.Q., Nguyen H.A., De Gruyter C., Su D.N., Nguyen V.H., Exploring the prevalence and factors associated with self-reported traffic crashes among app-based motorcycle taxis in Vietnam, Transp. Policy, 81, pp. 68-74, (2019); Oviedo-Trespalacios O., Risky business: Comparing the riding behaviours of food delivery and private bicycle riders., Accident Analysis & Prevention, 177, (2022); Oxley J., Yuen J., Ravi M.D., Hoareau E., Mohammed M.A.A., Bakar H., Et al., Commuter motorcycle crashes in Malaysia: An understanding of contributing factors, Ann. Adv. Automot. Med., 57, (2013); Papakostopoulos V., Nathanael D., The Complex Interrelationship of Work-Related Factors Underlying Risky Driving Behavior of Food Delivery Riders in Athens, Greece, Saf Health Work [Internet]., 12, 2, pp. 147-153, (2021); Rios P.A.A., Mota E.L.A., Ferreira L.N., Cardoso J.P., Ribeiro V.M., de Souza B.S., Factors associated with traffic accidents among drivers: findings from a population-based study, Cien Saude Colet., 25, pp. 943-955, (2020); Rusli R., Haque M.M., King M., Voon W.S., A Comparison of Road Traffic Crashes along Mountainous and Non-Mountainous Roads in Sabah, Malaysia, The 2015 Australasian Road Safety Conference, (2015); Shin D.S., Byun J.H., Jeong B.Y., Crashes and traffic signal violations caused by commercial motorcycle couriers, Saf Health Work., 10, 2, pp. 213-218, (2019); Supramani S., 70% of p-hailing riders disobey traffic rules while on delivery runs: Miros, The Sun Daily., (2021); Tamrin S.; Tran N.A.T., Nguyen H.L.A., Nguyen T.B.H., Nguyen Q.H., Huynh T.N.L., Pojani D., Et al., Health and safety risks faced by delivery riders during the Covid-19 pandemic, J. Transp. Heal., 25, (2022); Wang X., Chen J., Quddus M., Zhou W., Shen M., Influence of familiarity with traffic regulations on delivery riders'e-bike crashes and helmet use: Two mediator ordered logit models, Accid. Anal. Prev., 159, (2021); Wang Z., Neitzel R.L., Zheng W., Wang D., Xue X., Jiang G., Road safety situation of electric bike riders: A cross-sectional study in courier and take-out food delivery population, Traffic Inj. Prev., 22, 7, pp. 564-569, (2021); Zhang Y., Huang Y., Wang Y., Casey T.W., Who uses a mobile phone while driving for food delivery? The role of personality, risk perception, and driving self-efficacy, J. Safety Res., 73, pp. 69-80, (2020); Zheng Y., Ma Y., Guo L., Cheng J., Zhang Y., Crash involvement and risky riding behaviors among delivery riders in China: the role of working conditions, Transp. Res. Rec., 2673, 4, pp. 1011-1022, (2019)","R. Rusli; School of Civil Engineering, College of Engineering, Universiti Teknologi MARA, Shah Alam, Selangor, 40450, Malaysia; email: rusdirusli@uitm.edu.my",null,"Elsevier Ltd",{"$nulls":5},"2213624X",null,null,null,"English","Case Stud. Transp. Policy","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85140084573"]
["Hassan M.; Shakil S.; Moon N.N.; Islam M.M.; Hossain R.A.; Mariam A.; Nur F.N.","Hassan, Mahmudul (58277997100); Shakil, Shahriar (57827610600); Moon, Nazmun Nessa (56605973300); Islam, Mohammad Monirul (57221640879); Hossain, Refath Ara (57226796188); Mariam, Asma (57215332145); Nur, Fernaz Narin (56606237900)","58277997100; 57827610600; 56605973300; 57221640879; 57226796188; 57215332145; 56606237900","Sentiment analysis on Bangla conversation using machine learning approach",2022.0,"International Journal of Electrical and Computer Engineering",12.0,5.0,null,5562.0,5572.0,10.0,3.0,"10.11591/ijece.v12i5.pp5562-5572","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135276072&doi=10.11591%2fijece.v12i5.pp5562-5572&partnerID=40&md5=f000d9f2823236578f5258b8d62e981b","Department of Computer Science and Engineering, Faculty of Science and Information Technology, Daffodil International University, Dhaka, Bangladesh; Department of Computer Science and Engineering, Faculty of Science and Information Technology, Notre Dame University, Dhaka, Bangladesh","Hassan M., Department of Computer Science and Engineering, Faculty of Science and Information Technology, Daffodil International University, Dhaka, Bangladesh; Shakil S., Department of Computer Science and Engineering, Faculty of Science and Information Technology, Daffodil International University, Dhaka, Bangladesh; Moon N.N., Department of Computer Science and Engineering, Faculty of Science and Information Technology, Daffodil International University, Dhaka, Bangladesh; Islam M.M., Department of Computer Science and Engineering, Faculty of Science and Information Technology, Daffodil International University, Dhaka, Bangladesh; Hossain R.A., Department of Computer Science and Engineering, Faculty of Science and Information Technology, Daffodil International University, Dhaka, Bangladesh; Mariam A., Department of Computer Science and Engineering, Faculty of Science and Information Technology, Daffodil International University, Dhaka, Bangladesh; Nur F.N., Department of Computer Science and Engineering, Faculty of Science and Information Technology, Notre Dame University, Dhaka, Bangladesh","Nowadays, online communication is more convenient and popular than face-to-face conversation. Therefore, people prefer online communication over face-to-face meetings. Enormous people use online chatting systems to speak with their loved ones at any given time throughout the world. People create massive quantities of conversation every second because of their online engagement. People's feelings during the conversation period can be gleaned as useful information from these conversations. Text analysis and conclusion of any material as summarization can be done using sentiment analysis by natural language processing. The use of communication for customer service portals in various e-commerce platforms and crime investigations based on digital evidence is increasing the need for sentiment analysis of a conversation. Other languages, such as English, have well-developed libraries and resources for natural language processing, yet there are few studies conducted on Bangla. It is more challenging to extract sentiments from Bangla conversational data due to the language's grammatical complexity. As a result, it opens vast study opportunities. So, support vector machine, multinomial naïve Bayes, k-nearest neighbors, logistic regression, decision tree, and random forest was used. From the dataset, extracted information was labeled as positive and negative. © 2022 Institute of Advanced Engineering and Science. All rights reserved.","Accuracy rate; Detection approach; Natural language processing; Sentiment analysis; Support vector machine; Tokenizer",{"$nulls":7},"Alm C. O., Roth D., Sproat R., Emotions from text, Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing, pp. 579-586, (2005); Lin C., He Y., Joint sentiment/topic model for sentiment analysis, Proceeding of the 18th ACM conference on Information and knowledge management, 375, (2009); Nasukawa T., Yi J., Sentiment analysis: capturing favorability using natural language processing, Proceedings of the 2nd International Conference on Knowledge Capture, K-CAP 2003, pp. 70-77, (2003); Maas A. L., Daly R. E., Pham P. T., Huang D., Ng A. Y., Potts C., Learning word vectors for sentiment analysis, Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, 1, pp. 142-150, (2011); Bhowmik N. R., Arifuzzaman M., Mondal M. R. H., Sentiment analysis on Bangla text using extended lexicon dictionary and deep learning algorithms, Array, 13, (2022); Aurpa T. T., Sadik R., Ahmed M. S., Abusive Bangla comments detection on Facebook using transformer-based deep learning models, Social Network Analysis and Mining, 12, 1, (2022); Rahib M. R. H. K., Tamim A. H., Tahmeed M. Z., Hossain M. J., Emotion detection based on Bangladeshi people's social media response on COVID-19, SN Computer Science, 3, 2, (2022); Faruque M. A., Rahman S., Chakraborty P., Choudhury T., Um J.-S., Singh T. P., Ascertaining polarity of public opinions on Bangladesh cricket using machine learning techniques, Spatial Information Research, 30, 1, pp. 1-8, (2022); Iqbal M. D. A., Das A., Sharif O., Hoque M. M., Sarker I. H., BEmoC: a corpus for identifying emotion in Bengali texts, SN Computer Science, 3, 2, (2022); Shetu S. F., Saifuzzaman M., Parvin M., Moon N. N., Yousuf R., Sultana S., Identifying the writing style of bangla language using natural language processing, 2020 11th International Conference on Computing, Communication and Networking Technologies (ICCCNT), pp. 1-6, (2020); Mamun M. M. R., Sharif O., Hoque M. M., Classification of textual sentiment using ensemble technique, SN Computer Science, 3, 1, (2022); Neethu M. S., Rajasree R., Sentiment analysis in Twitter using machine learning techniques, 2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT), pp. 1-5, (2013); Jain A. P., Dandannavar P., Application of machine learning techniques to sentiment analysis, 2016 2nd International Conference on Applied and Theoretical Computing and Communication Technology (iCATccT), pp. 628-632, (2016); Rahman M., Dey E. K., Datasets for aspect-based sentiment analysis in bangla and its baseline evaluation, Data, 3, 2, (2018); Saifuzzaman M., Shetu S. F., Moon N. N., Nur F. N., Ali M. H., IoT based street lighting using dual axis solar tracker and effective traffic management system using deep learning: bangladesh context, 2020 11th International Conference on Computing, Communication and Networking Technologies (ICCCNT), pp. 1-5, (2020); Saifuzzaman M., Moon N. N., Nur F. N., IoT based street lighting and traffic management system, 2017 IEEE Region 10 Humanitarian Technology Conference (R10-HTC), pp. 121-124, (2017); Hasan R., Islam S., Rahman M. H., Saifuzzaman M., Shetu S. F., Moon N. N., Implementation of low cost real-time attendance management system: a comparative study, 2020 8th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO), pp. 1098-1101, (2020); Shetu S. F., Saifuzzaman M., Moon N. N., Nur F. N., A survey of botnet in cyber security, 2019 2nd International Conference on Intelligent Communication and Computational Techniques (ICCT), pp. 174-177, (2019); Podder K. K., Et al., Bangla sign language (BdSL) alphabets and numerals classification using a deep learning model, Sensors, 22, 2, (2022); Hossain M., Et al., Prediction on domestic violence in Bangladesh during the COVID-19 outbreak using machine learning methods, Applied System Innovation, 4, 4, (2021); Al-Smadi M., Qawasmeh O., Talafha B., Quwaider M., Human annotated Arabic dataset of book reviews for aspect based sentiment analysis, 2015 3rd International Conference on Future Internet of Things and Cloud, pp. 726-730, (2015); Khan L., Amjad A., Afaq K. M., Chang H.-T., Deep sentiment analysis using CNN-LSTM architecture of English and Roman Urdu text shared in social media, Applied Sciences, 12, 5, (2022); Chen M., Ubul K., Xu X., Aysa A., Muhammat M., Connecting text classification with image classification: a new preprocessing method for implicit sentiment text classification, Sensors, 22, 5, (2022); Schouten K., van der Weijde O., Frasincar F., Dekker R., Supervised and unsupervised aspect category detection for sentiment analysis with co-occurrence data, IEEE Transactions on Cybernetics, 48, 4, pp. 1263-1275, (2018); Zou H., Xiang K., Sentiment classification method based on blending of emoticons and short texts, Entropy, 24, 3, (2022)","N.N. Moon; Department of Computer Science and Engineering, Daffodil International University, Dhaka, 1207, Bangladesh; email: moon@daffodilvarsity.edu.bd",null,"Institute of Advanced Engineering and Science",{"$nulls":5},2.0888708E7,null,null,null,"English","Int. J. Electr. Comput. Eng.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85135276072"]
["Li X.B.","Li, X.B. (57216417594)",5.7216417594E10,"A comparative study of different algorithms for optimizing the path of multi-point logistics distribution",2022.0,"Advances in Transportation Studies",58.0,null,null,153.0,162.0,9.0,0.0,"10.53136/979122180230610","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85139976758&doi=10.53136%2f979122180230610&partnerID=40&md5=fc785d2f78b87f369ab93a7fe1d00687","Shandong Women's University, Shandong, Jinan, 250300, China","Li X.B., Shandong Women's University, Shandong, Jinan, 250300, China","Logistics delivery is an important part of online shopping services. Excellent delivery path planning can not only improve consumer experience but also greatly reduce costs. This paper studied the optimization of multi-point logistics distribution paths, calculated distribution paths by the ant colony algorithm and the genetic algorithm, performed simulation experiments on the two algorithms, and compared them with the traditional greedy algorithm. The results showed that the total transportation cost of the distribution path planned by the greedy algorithm was the highest, followed by the ant colony algorithm and the genetic algorithm, and the computation time of the ant colony algorithm was the longest, followed by the genetic algorithm and the greedy algorithm. © 2022, Aracne Editrice. All rights reserved.","Ant colony algorithm; Genetic algorithm; Multi-point distribution; Path planning","Ant colony optimization; Motion planning; Ant colonies algorithm; Comparatives studies; Delivery path; Greedy algorithms; Logistic distributions; Logistics delivery; Multi-point distribution; Multi-points; Online shopping; Reduce costs; Genetic algorithms",{"$nulls":6},"Sheu J.B., Kundu T., Forecasting time-varying logistics distribution Hows in the One Belt-One Road strategic context, Transportation Research Part E: Logistics and Transportation Review, 117, pp. 5-22, (2017); Sun J., Wang X., Study on the E-Commerce Logistics Distribution Modes of Fresh Agricultural Products, Applied Mechanics and Materials, 746, pp. 1895-1901, (2015); Guo J., Ma S., Environmental impact assessment for city logistics distribution systems, Environmental Engineering Research, (2017); Wang Y., Zhou F.L., Wang Y., Research and application of genetic algorithm in path planning of logistics distribution vehicle, AIP Conference Proceedings, 1864, pp. 20047-20047, (2017); Jing C., Optimization Route of Food Logistics Distribution Based on Genetic and Graph Cluster Scheme Algorithm, Advance Journal of Food Science Technology, 8, pp. 359-362, (2015); Yu F., Zhou Y., Optimization of E-Commerce Logistics Distribution Path Algorithm under the Background of Big Data, Journal of Physics: Conference Series, 1744, (2021); Ning T., Wang J., Han Y., Logistics distribution de-carbonization pathways and effect in China: A systematic analysis using VRPSDP model, International Journal of Low-Carbon Technologies, 16, pp. 1404-1411, (2021); Qian W.W., Zhao X., Ji K., Region Division in Logistics Distribution With a Two-Stage Optimization Algorithm, IEEE Access, 8, pp. 212876-212887, (2020); Xiang C., Hu L., Qi C., Cold Chain Logistics Distribution Routing Optimization Based on Realistic Delivery Time and Ant Colony, IOP Conference Series Materials Science and Engineering, 768, (2020); Wang J., Lim M.K., Tseng M.L., Yang Y., Promoting low carbon agenda in the urban logistics network distribution system, Journal of Cleaner Production, 211, pp. 146-160, (2019); Zhang G., Solving route optimisation problem in logistics distribution through an improved ant colony optimisation algorithm, International Journal of Services Operations and Informatics, 8, (2017); Zhang Q., Cao X., Multi-objective clustering optimization algorithm for paper-making enterprises' logistics distribution routes under e-commerce environment, Paper Asia, pp. 26-32, (2019); Wang J., Research on the optimization of path information in the process of logistics distribution by improved ant colony algorithm, Italian Journal of Pure and Applied Mathematics, pp. 343-352, (2019); Wang C.L., Wang Y., Zeng Z.Y., Lin C.Y., Yu Q.L., Research on Logistics Distribution Vehicle Scheduling Based on Heuristic Genetic Algorithm, Complexity, 2021, pp. 1-8, (2021); Wang Y., Zhou H., Wang Y., Research and application of genetic algorithm in path planning of logistics distribution vehicle, AIP Conference Proceedings, 1864, pp. 20047-20047, (2017); Simi D., Kovacevic I., Svircevic V., Simic S., Hybrid Firefly Model in Routing Heterogeneous Fleet of Vehicles in Logistics Distribution, Logic Journal of IGPL, 23, (2015); Gu W., Liu Y., Wei L., Dong B., A Hybrid Optimization Algorithm for Travelling Salesman Problem Based on Geographical Information System for Logistics Distribution, LISS, 8, pp. 1641-1646, (2015)","X.B. Li; Shandong Women's University, Jinan, Shandong, 250300, China; email: b2x3n9@yeah.net",null,"Aracne Editrice",{"$nulls":5},1.8245463E7,null,null,null,"English","Adv. Transp. Stud.","Article","Final",null,"Scopus","2-s2.0-85139976758"]
["Hong J.; Zhan C.; Lau K.H.","Hong, Jiangtao (23004982100); Zhan, Chenlin (57766416100); Lau, Kwok Hung (15056340300)","23004982100; 57766416100; 15056340300","Leveraging joint distribution in urban express delivery to lessen environmental impacts: a case study",2022.0,"Nankai Business Review International",13.0,4.0,null,567.0,586.0,19.0,1.0,"10.1108/NBRI-08-2021-0060","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85132908417&doi=10.1108%2fNBRI-08-2021-0060&partnerID=40&md5=9aa1cbca65fc5f07f252505aeab9bcf3","International Business School, Shanghai University of International Business and Economics, Shanghai, China; School of Accounting, Information Systems and Supply Chain, RMIT University, Melbourne, Australia","Hong J., International Business School, Shanghai University of International Business and Economics, Shanghai, China; Zhan C., International Business School, Shanghai University of International Business and Economics, Shanghai, China; Lau K.H., School of Accounting, Information Systems and Supply Chain, RMIT University, Melbourne, Australia","Purpose: This paper aims to explore the use of joint distribution to reduce environmental cost of express delivery in urban logistics. Design/methodology/approach: An optimization model was developed to help design the joint distribution network. A real case in Songjiang University Town of Shanghai, China, was used to explore empirically the potential benefit of the design. Performance of the proposed joint distribution was compared with that of the current distribution design using separate deliveries. Findings: The findings show that, using joint distribution in express delivery, a significant saving in economic cost (up to a reduction of 25%) and environmental cost (up to a reduction of 87%) can be achieved. Research limitations/implications: This study provides a reference for joint distribution network design for last-mile delivery in urban logistics. Practical implications: Express delivery companies can explore the use of joint distribution to reduce operating cost and increase distribution efficiency of the industry. Social implications: Joint distribution can facilitate maximization of vehicle utilization and reduction of delivery trips. This will help reduce fuel consumption, carbon emission, as well as other externalities, such as noise and traffic congestion. Originality/value: Research in joint distribution to date focuses mainly on reduction in operating cost only. Consideration of environmental impact is relatively limited. This paper fills the gap in the literature by using a real case to illustrate the significant benefit of joint distribution in reducing the negative impact of urban logistics on the environment. © 2022, Emerald Publishing Limited.","E-commerce; Environmental impact; Joint distribution; Last-mile delivery; Optimization; Urban logistics",{"$nulls":5},"Shanghai talent development funding, (2020134)","This research was sponsored by Shanghai talent development funding (#2020134).","Abbasi M., Nilsson F., Developing environmentally sustainable logistics: exploring themes and challenges from a logistics service providers’ perspective, Transportation Research Part D: Transport and Environment, 46, pp. 273-283, (2016); Afifi S., Dang D.C., Moukrim A., Heuristic solutions for the vehicle routing problem with time windows and synchronized visits, Optimization Letters, 10, 3, pp. 511-525, (2016); Central economic work conference: China’s carbon dioxide emissions will reach a peak by 2030 and achieve carbon neutrality by 2060, (2020); Boysen N., Schwerdfeger S., Weidinger F., Scheduling last-mile deliveries with truck-based autonomous robots, European Journal of Operational Research, 271, 3, pp. 1085-1099, (2018); Brown J.R., Guiffrida A.L., Carbon emissions comparison of last mile delivery versus customer pickup, International Journal of Logistics Research and Applications, 17, 6, pp. 503-521, (2014); Crainic T.G., Ricciardi N., Storchi G., Models for evaluating and planning city logistics systems, Transportation Science, 43, 4, pp. 432-454, (2009); De Souza R., Goh M., Lau H.C., Ng W.S., Tan P.S., Collaborative urban logistics–synchronizing the last mile a Singapore research perspective, Procedia - Social and Behavioral Sciences, 125, pp. 422-431, (2014); Dorling K., Heinrichs J., Messier G.G., Magierowski S., Vehicle routing problems for drone delivery, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 47, 1, pp. 70-85, (2016); Du J., Wang X., Tu Z., Incentive model of a joint delivery alliance considering moral hazard, Research in Transportation Business and Management, 41, (2021); Ferencz A., Deak Z., Notari M., Environmentally conscious consumption in Hungary, Roczniki (Annals), (2017); Fontaine C., Haarman A., Schmid S., The stakeholder theory, Edlays Education, 1, pp. 1-33, (2006); Freeman R.E., Strategic Management: A Stakeholder Approach, (1984); Implementation opinions on further reducing logistics costs, (2020); Gu S., Slusarczyk B., Hajizada S., Kovalyova I., Sakhbieva A., Impact of the covid-19 pandemic on online consumer purchasing behavior, Journal of Theoretical and Applied Electronic Commerce Research, 16, 6, pp. 2263-2281, (2021); Gulati R., Alliances and networks, Strategic Management Journal, 19, 4, pp. 293-317, (1998); Gulati R., Network location and learning: the influence of network resources and firm capabilities on alliance formation, Strategic Management Journal, 20, 5, pp. 397-420, (1999); Guo X., Jaramillo Y.J.L., Bloemhof-Ruwaard J., Claassen G.D.H., On integrating crowdsourced delivery in last-mile logistics: a simulation study to quantify its feasibility, Journal of Cleaner Production, 241, (2019); He Y., Wang X., Lin Y., Zhou F., Optimal partner combination for joint distribution alliance using integrated fuzzy EW-AHP and TOPSIS for online shopping, Sustainability, 8, 4, pp. 1-18, (2016); He Y., Wang X., Lin Y., Zhou F., Zhou L., Sustainable decision making for joint distribution center location choice, Transportation Research Part D: Transport and Environment, 55, pp. 202-216, (2017); He Y., Zhou F., Qi M., Wang X., Joint distribution: service paradigm, key technologies and its application in the context of Chinese express industry, International Journal of Logistics Research and Applications, 23, 3, pp. 211-227, (2020); Hemmelmayr V.C., Cordeau J.F., Crainic T.G., An adaptive large neighborhood search heuristic for two-echelon vehicle routing problems arising in city logistics, Computers and Operations Research, 39, 12, pp. 3215-3228, (2012); Jiao Z.L., Service mode and development trend of the ‘last-mile delivery’ of e-commerce logistics, Contemporary Logistics in China, pp. 239-261, (2016); Joshi Y., Rahman Z., Predictors of young consumer’s green purchase behavior, Management of Environmental Quality: An International Journal, 27, 4, pp. 452-472, (2016); Kuo J.C., Chen M.C., Developing an advanced multi-temperature joint distribution system for the food cold chain, Food Control, 21, 4, pp. 559-566, (2010); Lavie D., The competitive advantage of interconnected firms: an extension of the resource-based view, Academy of Management Review, 31, 3, pp. 638-658, (2006); Lee D.H., Dong M., Bian W., The design of sustainable logistics network under uncertainty, International Journal of Production Economics, 128, 1, pp. 159-166, (2010); Li L., Wang X., Lin Y., Zhou F., Chen S., Cooperative game-based profit allocation for joint distribution alliance under online shopping environment, Asia Pacific Journal of Marketing and Logistics, 31, 2, pp. 302-326, (2019); Lin J., Chen Q., Kawamura K., Sustainability SI: logistics cost and environmental impact analyses of urban delivery consolidation strategies, Networks and Spatial Economics, 16, 1, pp. 227-253, (2016); Liu G., Hu J., Yang Y., Xia S., Lim M.K., Vehicle routing problem in cold chain logistics: a joint distribution model with carbon trading mechanisms, Resources. Conservation and Recycling, 156, (2020); Mangiaracina R., Perego A., Seghezzi A., Tumino A., Innovative solutions to increase last-mile delivery efficiency in B2C e-commerce: a literature review, International Journal of Physical Distribution and Logistics Management, 49, 9, pp. 901-920, (2019); Mathews J.A., Competitive dynamics and economic learning: an extended resource‐based view, Industrial and Corporate Change, 12, 1, pp. 115-145, (2003); Melkonyan A., Gruchmann T., Lohmar F., Kamath V., Spinler S., Sustainability assessment of last-mile logistics and distribution strategies: the case of local food networks, International Journal of Production Economics, 228, (2020); Mitroff I.I., Stakeholders of the Organizational Mind, (1983); Orjuela-Castro J.A., Orejuela-Cabrera J.P., Adarme-Jaimes W., Last mile logistics in mega-cities for perishable fruits, Journal of Industrial Engineering and Management, 12, 2, pp. 318-327, (2019); Pirkul H., Jayaraman V., A multi-commodity, multi-plant, capacitated facility location problem: formulation and efficient heuristic solution, Computers and Operations Research, 25, 10, pp. 869-878, (1998); Powell W.W., Staw B., Cummings L.L., Neither market nor hierarchy, Research in Organizational Behavior, 12, pp. 295-336, (1990); Roberts B., Mackay M., IT supporting supplier relationships: the role of electronic commerce, European Journal of Purchasing and Supply Management, 4, 2-3, pp. 175-184, (1998); Seghezzi A., Mangiaracina R., Tumino A., Perego A., Pony express’ crowdsourcing logistics for last-mile delivery in B2C e-commerce: an economic analysis, International Journal of Logistics Research and Applications, pp. 1-17, (2020); Official website of Songjiang district, Shanghai, (2020); Soysal M., Bloemhof-Ruwaard J.M., Van Der Vorst J.G., Modelling food logistics networks with emission considerations: the case of an international beef supply chain, International Journal of Production Economics, 152, pp. 57-70, (2014); Taniguchi E., City Logistics: Network Modelling and Intelligent Transport Systems, (2001); Taniguchi E., Noritake M., Yamada T., Izumitani T., Optimal size and location planning of public logistics terminals, Transportation Research Part E: Logistics and Transportation Review, 35, 3, pp. 207-222, (1999); Thomson E.S., Laing A.W., ‘The net generation’: children and young people, the internet and online shopping, Journal of Marketing Management, 19, 3-4, pp. 491-512, (2003); Thorelli H.B., Networks: between markets and hierarchies, Strategic Management Journal, 7, 1, pp. 37-51, (1986); The 17 goals, (2022); Wang D., Li J., Tarasov A., Technical and energy efficiency of urban logistics in China: empirical analysis of 216 prefecture-level cities, Mathematical Problems in Engineering, 2021, (2021); Wang Y., Ma X., Xu M., Wang L., Wang Y., Liu Y., A methodology to exploit profit allocation in logistics joint distribution network optimization, Mathematical Problems in Engineering, 2015, (2015); Wang Y., Zhang D., Liu Q., Shen F., Lee L.H., Towards enhancing the last-mile delivery: an effective crowd-tasking model with scalable solutions, Transportation Research Part E: Logistics and Transportation Review, 93, pp. 279-293, (2016); Williamson O.E., Markets and Hierarchies: Analysis and Antitrust Implications, (1975); Williamson O.E., The Economic Institutions of Capitalism: Firms, Markets, Relational Contracting, (1985); Williamson O.E., The Mechanisms of Governance, (1996); Williamson O.E., Transaction cost economics: how it works; where it is headed, De Economist, 146, 1, pp. 23-58, (1998); Xu W., Yang H., Urban common delivery model analysis and system design, Applied Mechanics and Materials, 339, 7, pp. 772-777, (2013); Yu X., He M., Zhang Q., Pang J., Game analysis of the ‘last kilometer’ joint distribution driven by the block chain, Operations Research and Management Science, 29, 1, pp. 17-22, (2020); Zissis D., Aktas E., Bourlakis M., Collaboration in urban distribution of online grocery orders, The International Journal of Logistics Management, 29, 4, pp. 1196-1214, (2018); Zhang Q.Y., Chen J.H., Tao Y.M., Researches on joint distribution in urban logistics, Advanced Materials Research, 472-475, pp. 3240-3243, (2012)","K.H. Lau; School of Accounting, Information Systems and Supply Chain, RMIT University, Melbourne, Australia; email: charles1_lau@163.com",null,"Emerald Publishing",{"$nulls":5},2.0408749E7,null,null,null,"English","Nankai Bus. Rev. Int.","Article","Final",null,"Scopus","2-s2.0-85132908417"]
["Roy D.; Dutta M.","Roy, Deepjyoti (57668125800); Dutta, Mala (56249599400)","57668125800; 56249599400","An Improved Cat Swarm Search-Based Deep Ensemble Learning Model for Group Recommender Systems",2022.0,"Journal of Information and Knowledge Management",21.0,3.0,2250032.0,null,null,null,7.0,"10.1142/S0219649222500320","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85131066610&doi=10.1142%2fS0219649222500320&partnerID=40&md5=afb1b0fde74a2dc0c1328593692878c3","Computer Science and Engineering, Assam Down Town University, Assam, Guwahati, India","Roy D., Computer Science and Engineering, Assam Down Town University, Assam, Guwahati, India; Dutta M., Computer Science and Engineering, Assam Down Town University, Assam, Guwahati, India","Recommender systems are often employed in different fields such as music, travel, and movies. The recommender systems are broadly utilised nowadays due to the emergence of social activities, in which particular recommendations are offered by group recommender systems. It is a system for recommending the items to a set of users together based on their preferences. The user preferences are used from the behavioural and social aspects of group members to enhance the quality of products recommended in various groups for generating the group recommendations. These group recommender systems solve the cold start problem, which is raised in an individual recommendation system. The ultimate aim of this paper is to design and develop a new Improved Deep Ensemble Learning Model (ID-ELM) for the group recommender systems concerning different application-oriented datasets. Initially, the datasets from different applications like healthcare, e-commerce, and e-learning are gathered from benchmark sources and split the data into various groups. These data are given to the pre-processing for making it fit for further processing. The pre-processing steps like stop word removal, stemming, and punctuation removal are performed here. Then the features are extracted using the Continuous Bag of Words Model (CBOW), and Principal Component Analysis (PCA) is used for dimension reduction. These features are fed to the ID-ELM, in which the optimised Convolutional Neural Network (CNN) extracts the significant features from the pooling layer, and the fully connected layer is replaced by a set of classifiers termed Neural Networks (NN), AdaBoost, and Logistic Regression (LR). Finally, the ranking of the ensemble learning model based on the group reviews extends the recommendation outcome. The optimised CNN is proposed by the Adaptive Seeking Range-based Cat Swarm Optimisation (ASR-CSO) for attaining better results. This model is validated on the benchmark datasets to show the efficiency of the designed model with different meta-heuristic-based algorithms and classification algorithms.  © 2022 World Scientific Publishing Co.","AdaBoost; Group recommender systems; improved deep ensemble learning model; logistic regression; neural networks; optimised convolutional neural adaptive seeking range-based cat swarm optimisation","Adaptive boosting; Classification (of information); Convolution; Deep learning; Electronic commerce; Heuristic algorithms; Multilayer neural networks; Recommender systems; Social aspects; Convolutional neural network; Ensemble learning; Group recommender systems; Improved deep ensemble learning model; Learning models; Logistics regressions; Neural-networks; Optimized convolutional neural adaptive seeking range-based cat swarm optimization; Range-based; Swarm optimization; Benchmarking",{"$nulls":6},"Abirami RN, Vincent PMDR, Srinivasan K, Tariq U, Chang C-Y, Deep CNN and Deep GAN in computational visual perception-driven image analysis, Complexity, 2021, (2021); Ashwini K, Vincent PMDR, Srinivasan K, Chang C-Y, Deep learning assisted neonatal cry classification via support vector machine models, Frontiers in Public Health, (2021); Bobadilla J, Ortega F, Hernando A, Gutierrez A, Recommender systems survey, Knowledge-Based Systems, 46, pp. 109-132, (2013); Bouzidi A, Ri+/- ME, Barkatou M, Cat swarm optimization for solving the open shop scheduling problem, International Journal of Industrial Engineering, 15, pp. 367-378, (2019); Chen YL, Cheng LC, Chuang CN, A group recommendation system with consideration of interactions among group members, Expert System with Applications, 34, 3, pp. 2082-2090, (2007); Christensen I, Schia+/-no S, Armentano M, GIST: Social group recommendation in the tourism domain, Journal of Intelligent Information Systems, 47, 2, pp. 209-231, (2016); Dau A, Salim N, Rabiu I, Osman A, Weighted aspect-based opinion mining using deep learning for recommender system, Expert Systems with Applications, 140, (2020); Feng S, Cao J, Improving group recommendations via detecting comprehensive correlative information, Multimedia Tools and Applications, 76, 1, pp. 1355-1377, (2017); Ferretto LR, Bellei EA, Biduski D, Bin LCP, Moro MM, Cervi CR, Marchi ACBD, A physical activity recommender system for patients with arterial hypertension, IEEE Access, 8, pp. 61656-61664, (2020); Guo Z, Tang C, Niu W, Fu Y, Wu T, Xia H, Tang H, Fine-grained recommendation mechanism to curb astroturfing in crowdsourcing systems, IEEE Access, 5, pp. 15529-15541, (2017); Guo Z, Zeng W, Wang H, Shen Y, An enhanced group recommender system by exploiting preference relation, IEEE Access, 7, pp. 24852-24864, (2019); Guo X, Lin W, Li Y, Liu Z, Yang L, Zhao S, Zhu Z, DKEN: Deep knowledgeenhanced network for recommender systems, Information Sciences, 540, pp. 263-277, (2020); Hassan M, Hamada M, Evaluating the performance of a neural network-based multi-criteria recommender system, International Journal of Spatio-Temporal Data Science, 1, 1, pp. 54-69, (2019); Hu YC, Recommendation using neighborhood methods with preference-relation-based similarity, Information Sciences, 284, pp. 18-30, (2014); Huang Z, Xu X, Zhu H, Zhou M, An e±cient group recommendation model with multiattention-based neural networks, IEEE Transactions on Neural Networks and Learning Systems, 31, 11, pp. 4461-4474, (2020); Ji K, Chen Z, Sun R, Ma K, Yuan Z, Xu G, GIST: A generative model with individual and subgroup based topics for group recommendation, Expert System with Applications, 94, pp. 81-93, (2018); Jiang J, Li W, Dong A, Gou Q, Luo X, A Fast Deep AutoEncoder for highdimensional and sparse matrices in recommender systems, Neurocomputing, 412, pp. 381-391, (2020); Kagita VR, Pujari AK, Padmanabhan V, Virtual user approach for group recommender systems using precedence relations, Information Sciences, 294, pp. 15-30, (2015); Katarya R, Verma OP, A collaborative recommender system enhanced with particle swarm optimization technique, Multimedia Tools and Applications, 75, 15, pp. 9225-9239, (2016); Katarya R, Verma OP, Recommender system with grey wolf optimizer and FCM, Neural Computing and Applications, 30, pp. 1679-1687, (2018); Kim D, Park C, Oh J, Lee S, Yu H, Convolutional matrix factorization for document context-aware recommendation, Proceedings of the RecSys '16, pp. 233-240, (2016); Kiran R, Kumar P, Bhasker B, DNNRec: A novel deep learning-based hybrid recommender system, Expert Systems with Applications, 144, (2020); Kompan M, Bielikova M, Group recommendations: Survey and perspectives, Computing and Informatics, 33, 2, pp. 446-476, (2014); Koren Y, Bell R, Volinsky C, Matrix factorization techniques for recommender systems, Computer, 42, 8, pp. 30-37, (2009); Liu S, Li G, Tran T, Jiang Y, Preference relation-based Markov random fields for recommender systems, Machine Learning, 106, 4, pp. 523-546, (2017); Ortega F, Hernando A, Bobadilla J, Kang JH, Recommending items to group of users using matrix factorization based collaborative filtering, Information Sciences, 345, pp. 313-324, (2016); Pham MC, Cao Y, Klamma R, Jarke M, A clustering approach for collaborative filtering recommendation using social network analysis, Journal of Universal Computer Science, 17, 4, pp. 583-604, (2011); Pramanik S, Haldar R, Kumar A, Pathak S, Mitra B, Deep learning-driven venue recommender for event-based social networks, IEEE Transactions on Knowledge and Data Engineering, 32, 11, pp. 2129-2143, (2020); Reddy GT, Reddy MPK, Lakshmanna K, Kaluri R, Rajput DS, Srivastava G, Baker T, Analysis of dimensionality reduction techniques on big data, IEEE Access, 8, pp. 54776-54788, (2020); Seo Y-D, Kim Y-G, Lee E, Seol K-S, Baik D-K, An enhanced aggregation method considering deviations for a group recommendation, Expert System with Applications, 93, 1, pp. 299-312, (2018); Singal SM, Tejal, Juneja B, AdaBoosting for case-based recommendation system, International Conference on Information Technology (InCITe) - The Next Generation IT Summit on the Theme - Internet of Things: Connect your Worlds, pp. 62-66, (2016); Skowron P, Faliszewski P, Lang J, Finding a collective set of items: From proportional multi representation to group recommendation, Artificial Intelligence, 241, pp. 191-216, (2016); Srinivasan K, Cherukuri AK, Vincent DR, Garg A, Chen B-Y, An e±cient implementation of Artificial Neural Networks with k-fold cross-validation for process optimization, Journal of Internet Technology, 20, 4, pp. 1213-1225, (2019); Srinivasan K, Garg L, Datta D, Alaboudi AA, Jhanjhi NZ, Agarwal R, Thomas AG, Performance comparison of deep CNN models for detecting driver's distraction, Computers, Materials & Continua, 68, 3, (2021); Tian H, Cai H, Wen J, Li S, A music recommendation system based on logistic regression and eXtreme Gradient Boosting, International Joint Conference on Neural Networks (IJCNN), pp. 1-6, (2019); Tripathi AK, Mittal H, Saxena P, Gupta S, A new recommendation system using map-reduce-based tournament empowered Whale optimization algorithm, Complex & Intelligent Systems, 7, pp. 297-309, (2021); Verma P, Khandelwal B, Word embeddings and its application in deep learning, International Journal of Innovative Technology and Exploring Engineering (IJITEE), 8, 11, pp. 1-5, (2019); Vincent DR, Deepa N, Elavarasan D, Srinivasan K, Chauhdary SH, Iwendi C, Sensors driven AI-based agriculture recommendation model for assessing land suitability, Sensors, 19, 17, (2019); Wang Z, Liao J, Cao Q, Qi H, Wang Z, Friendbook: A semantic-based friend recommendation system for social networks, IEEE Transactions on Mobile Computing, 14, 3, pp. 538-551, (2015); Yang X, Guo Y, Liu Y, Steck H, A survey of collaborative filtering based social recommender systems, IEEE Computer Communications, 41, pp. 1-10, (2013); Zaidi SFA, Awan FM, Lee M, Woo H, Le C-G, Applying convolutional neural networks with different word representation techniques to recommend bug fixers, IEEE Access, 8, pp. 213729-213747, (2020)",null,null,"World Scientific",{"$nulls":5},2196492.0,null,null,null,"English","J. Inf. Knowl. Manage.","Article","Final",null,"Scopus","2-s2.0-85131066610"]
["Huang W.; Hu P.; Tsai F.-S.; Liu Y.; Huang Y.","Huang, Wei (58342054200); Hu, Peiqi (58034646400); Tsai, Fu-Sheng (58694877800); Liu, Yinke (58033802500); Huang, Yu (57998050700)","58342054200; 58034646400; 58694877800; 58033802500; 57998050700","Smart Sales Empower Small Farmers: An Integrated Matching Method between Suppliers and Consumers Based on the Information Axiom",2022.0,"Sustainability (Switzerland)",14.0,24.0,16937.0,null,null,null,1.0,"10.3390/su142416937","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85144911852&doi=10.3390%2fsu142416937&partnerID=40&md5=4898908de1fe1eb2a38a5caeb2b14790","School of Management and Economics, North China University of Water Resources and Electric Power, Zhengzhou, 450046, China; Department of Business Administration, Cheng Shiu University, Kaohsiung, 10650, Taiwan; Department of Public Education, Zhengzhou University of Economics and Business, Zhengzhou, 451191, China","Huang W., School of Management and Economics, North China University of Water Resources and Electric Power, Zhengzhou, 450046, China; Hu P., School of Management and Economics, North China University of Water Resources and Electric Power, Zhengzhou, 450046, China; Tsai F.-S., School of Management and Economics, North China University of Water Resources and Electric Power, Zhengzhou, 450046, China, Department of Business Administration, Cheng Shiu University, Kaohsiung, 10650, Taiwan; Liu Y., School of Management and Economics, North China University of Water Resources and Electric Power, Zhengzhou, 450046, China; Huang Y., Department of Public Education, Zhengzhou University of Economics and Business, Zhengzhou, 451191, China","Small farmers’ sustainable development has important significance for narrowing the gap between urban and rural areas and hastening the promotion of general prosperity in China. Currently, China still has 240 million small farmers. The sale of agricultural products is an important source of their income. Constrained by their small scale, lack of capital, and technology, small farmers often have to adopt a household operation mode. This decentralized agricultural production and operation mode results in significant difficulties for small farmers to benefit from planting and selling agricultural products. Many efforts have been made to help them, such as establishing agricultural product information platforms that can provide supply and demand information to facilitate small farmers’ sales. However, imbalances between suppliers and consumers and cross-regional transaction difficulties still exist. To promote the sustainable development of small farmers, this study develops an intelligent matching method for the transaction of agricultural products between suppliers and consumers. Firstly, a unique attribute set for agricultural products was established. Because most agricultural products are fresh, perishable, and not easily preserved, the general attributes (brand, logistics distance, product grade, and price) of commodities and the specific attributes (freshness, maturity, product certification, seasonal products, place of origin, and product safety) of agricultural products were taken into account. Secondly, by combining fuzzy mathematics with the information axiom, improved amount of information calculation methods for both quantitative and qualitative attributes were put forward. Thirdly, based on the amount of information about all attributes and with the goal of maximizing the transaction-matching degree for both the supplier and consumer, a multiobjective optimization model was proposed. Finally, the effectiveness and accuracy of the method were verified through a case study. In order to solve the dilemma of small farmers, this study proposes an integrated matching method for agricultural product transactions based on the information axiom. Through case verification, this method has good feasibility and effectiveness. It has broad application prospects which can be applied to information portals, e-commerce platforms, and other fields. The application of this method can empower small farmers’ capabilities, facilitate agricultural product sales, and promote small farmers’ sustainable development. © 2022 by the authors.","matching problem; rural e-commerce; sales promotion; small farmer; sustainable development","China; agricultural production; electronic commerce; integrated approach; sustainable development",{"$nulls":4},"Henan Province Higher Education Teaching Reform Research and Practice Project; North China University of Water Conservancy and Electric Power, NCWU, (YK-2021-118); National Office for Philosophy and Social Sciences, NPOPSS, (19BGL224); Major Science and Technology Projects in Anhui Province, (201110210300)","This research was funded by the National Social Science Foundation of China (NSSFC), grant number 19BGL224; Major Science and Technology Projects in Henan Province, China, grant number 201110210300; Postgraduate Innovation Project of North China University of Water Resources and Electric Power, grant number YK-2021-118; Henan Province Higher Education Teaching Reform Research and Practice Project, 2021.","Leng K., Bi Y., Jing L., Fu H.-C., Van Nieuwenhuyse I., Research on agricultural supply chain system with double chain architecture based on blockchain technology, Futur. 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["Du J.; Wang X.; Wu X.; Zhou F.; Zhou L.","Du, Jianhui (57219570906); Wang, Xu (55951735500); Wu, Xin (57869045700); Zhou, Fuli (57189093462); Zhou, Lin (57868712000)","57219570906; 55951735500; 57869045700; 57189093462; 57868712000","Multi-objective optimization for two-echelon joint delivery location routing problem considering carbon emission under online shopping",2023.0,"Transportation Letters",15.0,8.0,null,907.0,925.0,18.0,7.0,"10.1080/19427867.2022.2112857","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137034331&doi=10.1080%2f19427867.2022.2112857&partnerID=40&md5=9aa2b8862d2ac168ee480d400f82616e","College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing, China; Chongqing Key Laboratory of Logistics, Chongqing University, Chongqing, China; School of Economics and Management, Zhengzhou University of Light Industry, Zhengzhou, China; College of Management, Chongqing University of Technology, Chongqing, China","Du J., College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing, China, Chongqing Key Laboratory of Logistics, Chongqing University, Chongqing, China; Wang X., College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing, China, Chongqing Key Laboratory of Logistics, Chongqing University, Chongqing, China; Wu X., College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing, China; Zhou F., School of Economics and Management, Zhengzhou University of Light Industry, Zhengzhou, China; Zhou L., College of Management, Chongqing University of Technology, Chongqing, China","A sharp increasing number of online shopping parcels and scattered customers lead each express company to invest a lot logistics resources, but its utilization rate is low. Each express company faces the challenge of improving customer satisfaction and market competitiveness while ensuring the total costs are under control. This paper develops a novel joint delivery (JD) model to reduce operation costs and carbon emission via strengthening horizontal cooperation and resource sharing among express companies. Furthermore, it designs a multi-depot two-echelon joint delivery location routing problem (MD-2E-JDLRP) mathematic model for JD considering multi-objectives and proposes a hybrid heuristic algorithm to solve the MD-2E-JDLRP. The performance of this algorithm was tested by benchmarks and a case study. Finally, a case study is conducted to verify the effectiveness of the MD-2E-JDLRP model. The obtained results show the JD model can effectively reduce costs and carbon emissions while ensuring higher customer satisfaction. © 2022 Informa UK Limited, trading as Taylor & Francis Group.","carbon emission; joint delivery; location routing problem; online shopping; Urban logistics","Benchmarking; Carbon; Cost reduction; Electronic commerce; Heuristic algorithms; Location; Multiobjective optimization; Sales; Carbon emissions; Case-studies; Customers' satisfaction; Delivery models; Joint delivery; Location routing problem; Logistics resources; Multi-objectives optimization; Online shopping; Urban logistics; Customer satisfaction",{"$nulls":4},"Humanities and Social Sciences Research Planning Project of Chongqing Education Commission, (22SKGH433); Key Technologies R&D Programme of Henan Province; Chongqing Postdoctoral Science Foundation, (cstc2020jcyj-bshX0048); National Natural Science Foundation of China, NSFC, (71801025); Science and Technology Department of Gansu Province, (222102210005); National Key Research and Development Program of China, NKRDPC, (2020YFB1712900); Henan Key Laboratory of Non-ferrous Metal Materials Science and Processing Technology","Funding text 1: This study was supported by National Key R&D Program of China (Grant number: 2020YFB1712900), National Natural Science Foundation of China (Grant 71801025), the Humanities and Social Sciences Research Planning Project of Chongqing Education Commission in 2022 (No.22SKGH433), Postdoctoral Science Foundation of Chongqing (cstc2020jcyj-bshX0048) and Key Technologies R&D Programme of Henan Province from Henan Science and Technology Department (222102210005). The authors also appreciate the editor and the anonymous referees for their manuscript processing and remarkable comments. ; Funding text 2: This work was supported by the National Natural Science Foundation of China [Grant 71801025]; the Humanities and Social Sciences Research Planning Project of Chongqing Education Commission [22SKGH433]; Henan Key Laboratory of Non-ferrous Metal Materials Science and Processing Technology [222102210005]; Postdoctoral Science Foundation of Chongqing [cstc2020jcyj-bshX0048]; National Key Research and Development Program of China [2020YFB1712900]. This study was supported by National Key R&D Program of China (Grant number: 2020YFB1712900), National Natural Science Foundation of China (Grant 71801025), the Humanities and Social Sciences Research Planning Project of Chongqing Education Commission in 2022 (No.22SKGH433), Postdoctoral Science Foundation of Chongqing (cstc2020jcyj-bshX0048) and Key Technologies R&D Programme of Henan Province from Henan Science and Technology Department (222102210005). The authors also appreciate the editor and the anonymous referees for their manuscript processing and remarkable comments.","Afshar-Bakeshloo M., Mehrabi A., Safari H., Maleki M., Jolai F., A Green Vehicle Routing Problem with Customer Satisfaction Criteria, Journal of Industrial Engineering International, 12, 4, pp. 529-544, (2016); Ahmadizar F., Zeynivand M., Arkat J., Two-level Vehicle Routing with cross-docking in A three-echelon Supply Chain: A Genetic Algorithm Approach, Applied Mathematical Modelling, 39, 22, pp. 7065-7081, (2015); Alireza F., Ardjmand E., Young W.A., Weckman G.R., A multi-objective two-echelon location-routing Problem for Cash Logistics: A Metaheuristic Approach, Applied Soft Computing, (2021); Alvarez P., Lerga I., Serrano-Hernandez A., Faulin J., The Impact of Traffic Congestion When Optimising Delivery Routes in Real Time. 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Wang; College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing, Sichuan, 400044, China; email: wx921@163.com",null,"Taylor and Francis Ltd.",{"$nulls":5},1.9427867E7,null,null,null,"English","Transp. Lett.","Article","Final",null,"Scopus","2-s2.0-85137034331"]
["Kang J.W.O.O.; Ramizo D.M.","Kang, Jong Woo (58085709200); Ramizo, Dorothea M. (57195279947)","58085709200; 57195279947","Nexus of Technology Adoption, E-commerce, and Global Value Chains: The Case of Asia",2022.0,"Asian Development Review",39.0,2.0,null,45.0,73.0,28.0,0.0,"10.1142/S0116110522500147","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85147178856&doi=10.1142%2fS0116110522500147&partnerID=40&md5=f209c1dcac29ba531b430b160cb062ac","Asian Development Bank, Metro Manila, Philippines","Kang J.W.O.O., Asian Development Bank, Metro Manila, Philippines; Ramizo D.M., Asian Development Bank, Metro Manila, Philippines","Existing literature has examined either the key drivers of global value chain (GVC) exports or the factors affecting e-commerce growth. Studies that investigate the impact of e-commerce, in particular business-to-consumer (B2C) e-commerce, on GVCs are largely missing. The growing prevalence of digital platforms centered around e-commerce marketplaces motivates this study to examine if e-commerce growth in an economy can affect its GVC exports and how information and communication technology infrastructure and technology adoption measures, payment systems, and delivery mechanisms can facilitate this growth. Panel ordinary least squares, feasible generalized least squares, and two-stage least squares estimations are used to determine the relationship between GVC exports and e-commerce sales. The results indicate empirical evidence of the positive impact of B2C e-commerce on GVC exports. The robust and positive impact of B2C e-commerce on GVC exports-when instrumented by secure internet servers, internet bandwidth, and digital payment schemes-suggests growth of B2C e-commerce in an economy can contribute to its GVC participation.  © 2022 Asian Development Bank.","digital payment; e-commerce; GVC; ICT infrastructure","Asia; electronic commerce; export; information and communication technology; least squares method; supply chain management; technology adoption",{"$nulls":6},"Antras Pol, Conceptual Aspects of Global Value Chains, (2020); Caves Richard E., Multinational Enterprise and Economic Analysis, (2007); Coe David, Helpman Elhanan, International R&D Spillovers, European Economic Review, 39, 5, pp. 859-887, (1995); Coe David, Helpman Elhanan, Hoffmaister Alexander, North–South R&D Spillovers, The Economic Journal, 107, 440, pp. 134-149, (1997); (2019); Gereffi Gary, Humphrey John, Sturgeon Timothy, The Governance of Global Value Chains, Review of International Political Economy, 12, 1, pp. 78-104, (2005); Grossman Gene M., Helpman Elhanan, Innovation and Growth in the Global Economy, (1991); Ho Shu-Chun, Kauffman Robert J., Liang Ting-Peng, The Impact of Internet-based Selling Technology: A Hybrid Growth Theory Perspective with Cross-Model Inference, Information Technology and Management, 12, 4, pp. 409-429, (2011); Ignatenko Anna, Raei Faezeh, Mircheva Borislava, Global Value Chains: What are the Benefits and Why do Countries Participate?, (2019); Inomata Satoshi, Impact of New Technologies on the Organization of Global Value Chains: Dynamic Transformations within Global Value Chain Typology, (2017); Inomata Satoshi, Taglioni Daria, Technological Progress, Diffusion, and Opportunities for Developing Countries: Lessons from China, Global Value Chain Development Report 2019: Technological Innovation, Supply Chain Trade, and Workers in a Globalised World, pp. 83-101, (2019); Financial Access Survey; Statistics—United Nations; Kang Jong Woo, Wang Tengfei, Ramizo Dorothea, The Role of Technology in Business-to-Consumer E-Commerce: Evidence from Asia, (2021); Keller Wolfgang, Are International R&D Spillovers Trade-related? 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An Analysis of Trade in Value Added Data, Thailand and the World Economy, 38, 1, pp. 1-28, (2020); Wang Zhi, Wei Shang-Jin, Zhu Kunfu, Quantifying International Production Sharing at the Bilateral and Sectoral Levels, (2014); World Development Indicators; Xing Zhongwei, The Impacts of Information and Communications Technology and E-commerce on Bilateral Trade Flows, International Economics and Economic Policy, 15, 3, pp. 565-586, (2018)","J.W.O.O. Kang; Asian Development Bank, Metro Manila, Philippines; email: jkang@adb.org",null,"World Scientific",{"$nulls":5},1161105.0,null,null,null,"English","Asian Dev. Rev.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85147178856"]
["Rawat K.; Kumar S.","Rawat, Kavita (57973459200); Kumar, Sunita (55925408400)","57973459200; 55925408400","A Meta-Analysis on the Determinants of Online Product Reviews with Moderating Effect of Product Type",2022.0,"Academic Journal of Interdisciplinary Studies",11.0,6.0,null,313.0,323.0,10.0,1.0,"10.36941/ajis-2022-0170","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85142338987&doi=10.36941%2fajis-2022-0170&partnerID=40&md5=7b2261feea405301a6181e7a1da21bd2","School of Business & Management, CHRIST (Deemed to be University), Dharmaram College Post, Hosur Road, Karnataka, Bengaluru, 560029, India","Rawat K., School of Business & Management, CHRIST (Deemed to be University), Dharmaram College Post, Hosur Road, Karnataka, Bengaluru, 560029, India; Kumar S., School of Business & Management, CHRIST (Deemed to be University), Dharmaram College Post, Hosur Road, Karnataka, Bengaluru, 560029, India","The technological advances in digital space have provided a renewed impetus for business to expand their footprint across digital modes. The growth of the internet and the ease of its access to the masses has encouraged many businesses to go online. Online e-commerce platforms make it easy to search, locate and place orders. Technology-assisted supply chains and fast delivery mechanisms ensure that users don't have to go elsewhere to fulfill their needs. To earn loyalty and customer satisfaction, e-commerce platforms have evolved into a sophisticated recommender system. It has evolved from just an informational source to a participative mode where users can share their experiences about their purchases. Customer values other user experiences more than the information provided by the seller. The presence of many conflicting and contradicting reviews can make the task of making rational decisions difficult for many users. Many studies were performed to understand what constitutes a review helpful and came up with different or mixed outcomes. The present study reviews the factors that influence online customer reviews helpful. Meta-analysis was performed to reconcile the mixed findings of different factors of online review helpfulness. The meta-analysis found that with the moderating effect of product type, factors like review length, readability, rating, reputation, and expertise positively correlate with helpfulness. Further, the customer finds moderate reviews more helpful in terms of polarity. Meta-analysis has a mix of findings for the selected data points in the study. The mixed findings include product type (search, experience, or other) and helpfulness measurement criteria. © 2022 Kavita Rawat and Sunita Kumar. 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PACIS 2014, pp. 52-63, (2014); Yin G., Zhang Q., Li Y., Effects of Emotional Valence and Arousal on Consumer Perceptions of Online Review Helpfulness, Twentieth Americas Conference on Information Systems, pp. 1-11, (2014); Zhiming L., Li H., Lu L., An investigation of online review helpfulness based on movie reviews, African Journal of Business Management, 8, 12, pp. 441-450, (2014); Zhu F., Zhang X., Impact of Online Consumer Reviews on Sales: The Moderating Role of Product and Consumer Characteristics, Journal of Marketing, 74, 2, pp. 133-148, (2010); Zhu L., Yin G., He W., Is This Opinion Leader’s Review Useful? Peripheral Cues For Online Review Helpfulness, Journal of Electronic Commerce Research, 15, 4, pp. 267-280, (2014)",null,null,"Richtmann Publishing Ltd",{"$nulls":5},2.2813993E7,null,null,null,"English","Acad. J. Interdiscip. Stud.","Article","Final","All Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85142338987"]
["Altuntaş Vural C.; Aktepe Ç.","Altuntaş Vural, Ceren (57062354700); Aktepe, Çağlar (57224948989)","57062354700; 57224948989","Why do some sustainable urban logistics innovations fail? The case of collection and delivery points",2022.0,"Research in Transportation Business and Management",45.0,null,100690.0,null,null,null,8.0,"10.1016/j.rtbm.2021.100690","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85108703030&doi=10.1016%2fj.rtbm.2021.100690&partnerID=40&md5=71ac027439d4c72dc374d21e29b5405d","Chalmers University of Technology, Technology Management and Economics, Division: Service Management and Logistics, Gothenburg, Sweden; Dokuz Eylul University, International Trade, Izmir, Turkey","Altuntaş Vural C., Chalmers University of Technology, Technology Management and Economics, Division: Service Management and Logistics, Gothenburg, Sweden; Aktepe Ç., Dokuz Eylul University, International Trade, Izmir, Turkey","Combined with current trends in e-commerce, demand for urban logistic services are putting significant pressure on the environment. While some European examples show that collection-and-delivery points (CDPs) offer a sustainable solution, this is not always the case. This paper explores the mechanisms that support CDPs as sustainable urban logistics innovations while providing viable market offerings. To do so, it analyses a failure case using multiple data sources, such as a consumer survey, interviews and secondary data. Using diffusion of innovations (DoI) theory, the study explains how CDP failed in a developing market setting. Sustainable logistics innovations fail due to both supply chain-related and market-related factors. Significant factors on the supply chain side include network structures, IT integration and diverse value propositions while the market side includes consumer market characteristics, regulations, security issues and convenience of existing alternatives. Important factors for success include looking for horizontal collaboration opportunities, building strong network partnerships with customers and distribution channel actors. CDPs should be positioned as sustainable solutions and complemented with other urban logistics services to diversify the value proposition. © 2021","Collection-and-delivery points; Diffusion-of-innovations theory; E-retailing; Pick-up points; Sustainability; Urban logistics",{"$nulls":7},"Allen J., Browne M., Holguin-Veras J., Sustainability strategies for city logistics, Green logistics improving the environmental sustainability of logistics, pp. 293-319, (2015); Arnold F., Cardenas I., Sorensen K., Dewulf W., Simulation of B2C e-commerce distribution in Antwerp using cargo bikes and delivery points, European Transport Research Review, 10, 2, pp. 1-13, (2018); Atmaca H.E., Turgut D., Kargo şirketi seçimine yönelik kriterlerin belirlenmesinde Türkiye genelinde bir saha araştırması, Çukurova Üniversitesi İİBF Dergisi, 19, 2, pp. 65-79, (2015); Baltar F., Brunet I., Socail research 2.0: Virtual snowball sampling method using Facebook, Internet Research, 22, 1, pp. 57-74, (2012); Bjorklund M., Abrahamsson M., Johansson H., Critical factors for viable business models for urban consolidation centres, Research in Transportation Economics, 64, pp. 36-47, (2017); 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Altuntaş Vural; Chalmers University of Technology, Technology Management and Economics, Division: Service Management and Logistics, Gothenburg, Sweden; email: ceren.altuntasvural@chalmers.se",null,"Elsevier Ltd",{"$nulls":5},2.2105395E7,null,null,null,"English","Res. Transport. Bus. Manage.","Article","Final","All Open Access; Green Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85108703030"]
["Baghla S.; Gupta G.","Baghla, Seema (57914361100); Gupta, Gaurav (57189248336)","57914361100; 57189248336","Performance Evaluation of Various Classification Techniques for Customer Churn Prediction in E-commerce",2022.0,"Microprocessors and Microsystems",94.0,null,104680.0,null,null,null,5.0,"10.1016/j.micpro.2022.104680","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85139232525&doi=10.1016%2fj.micpro.2022.104680&partnerID=40&md5=675876260da22b0fb79f21b0a17466d4","Department of Computer Science and Engineering, Punjabi University, Punjab, Patiala, India","Baghla S., Department of Computer Science and Engineering, Punjabi University, Punjab, Patiala, India; Gupta G., Department of Computer Science and Engineering, Punjabi University, Punjab, Patiala, India","It is always a challenge to predict the customers on the verge of churn accurately in e-commerce due to the complexity of features and dynamicity of data and develop effective churn prediction models to predict potential churners accurately. This paper presents an in-depth comparison between four machine learning techniques namely neural network, support vector machine, Naïve Bayes and random forest, and Adam deep learning technique, for predicting customer churn in e-commerce. The classification techniques are implemented on benchmarked Brazilian e-commerce dataset. For the feature selection, principal component analysis and neighborhood component analysis techniques have been used. A balanced dataset, consisting of 11224 samples, is taken for study. The performance of the developed models is evaluated using the performance metrics viz. accuracy, sensitivity, specificity, true positive value, and true negative value. It has been found that the random forest classifier for the features selected using the neighborhood component analysis technique gives the highest prediction accuracy of 99.35% in comparison to classifiers used in this work as well as classifiers used by previous researchers. Additionally, the accuracy of the classifiers for features selected using the neighborhood component analysis technique is higher as compared to the principal component analysis technique. In future, authors are working further to improve the performance of the developed model by incorporating more features as well as evaluation parameters and proposing new models using convolutional neural networks. The authors also intend to use more than one dataset for the training of the models in the future. © 2022 Elsevier B.V.","Adam deep learning; Classification techniques; Customer churn prediction; E-commerce; Feature selection; Machine learning; Performance metrics","Classification (of information); Convolutional neural networks; Decision trees; Deep neural networks; Electronic commerce; Feature Selection; Forecasting; Logistic regression; Random forests; Sales; Support vector regression; Adam deep learning; Analysis techniques; Classification technique; Customer churn prediction; E- commerces; Features selection; Machine-learning; Neighborhood component analysis; Performance metrices; Principal-component analysis; Principal component analysis",{"$nulls":6},"Yu X., Guo S., Guo J., Huang X., An extended support vector machine forecasting framework for customer churn in e-commerce, Expert Syst. 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Appl., 18, 1, pp. 1-19, (2019); Dhote S., Vichoray C., Pais R., Baskar S., Shakeel P.M., Hybrid geometric sampling and AdaBoost based deep learning approach for data imbalance in E‑commerce, Electro. Commer. Res, 20, 2, pp. 259-274, (2020); Caigny A.D., Coussement K., DeBock K.W., Lessmann S., Incorporating textual information in customer churn prediction models based on a convolutional neural network, Int. J. Forecas., 36, 4, pp. 1563-1578, (2020); Jain H., Khunteta A., Srivastava S., Telecom churn prediction and used techniques, datasets and performance measures: A review, Telecom Syst, 76, pp. 613-630, (2021)","S. Baghla; Department of Computer Science and Engineering, Punjabi University, Patiala, Punjab, India; email: seemabaghla@pbi.ac.in",null,"Elsevier B.V.",{"$nulls":5},1419331.0,null,"MIMID",null,"English","Microprocessors Microsyst","Article","Final",null,"Scopus","2-s2.0-85139232525"]
["Sun W.; Zhang J.; Shen H.; Li G.; Wang H.; He F.; Bi F.","Sun, Wenjie (57211977424); Zhang, Jin (55866351600); Shen, Hao (57215900432); Li, Guoqi (55881421400); Wang, Hongjian (57949848300); He, Feng (57949906700); Bi, Feng (57949979200)","57211977424; 55866351600; 57215900432; 55881421400; 57949848300; 57949906700; 57949979200","Connectivity and centrality: Geovisualization of express networks in China",2023.0,"Environment and Planning B: Urban Analytics and City Science",50.0,1.0,null,281.0,283.0,2.0,0.0,"10.1177/23998083221136562","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85141020168&doi=10.1177%2f23998083221136562&partnerID=40&md5=148e3023f2b9f400299bb2e888d0f9cd","Southwest Jiaotong University, China; Shenzhen Qianhai Baidi Network Co, Ltd, China","Sun W., Southwest Jiaotong University, China; Zhang J., Southwest Jiaotong University, China; Shen H., Southwest Jiaotong University, China; Li G., Southwest Jiaotong University, China; Wang H., Southwest Jiaotong University, China; He F., Shenzhen Qianhai Baidi Network Co, Ltd, China; Bi F., Shenzhen Qianhai Baidi Network Co, Ltd, China","Express delivery volume is an important indicator of intercity e-commerce trading activities, offering a new vision for glimpsing the intercity linkages. However, it has been a challenge to reveal the spatial distribution of intercity express flows due to the limitations on the use of express parcel data by most companies. The study maps the spatial pattern of intercity express connection intensity and identifies the urban centrality, supported by waybill data from China. Intercity express connections form a triangular corridor centred on the ‘Pearl River Delta–Yangtze River Delta–Beijing-Tianjin-Hebei’ urban agglomerations. Shenzhen, Guangzhou, Jinhua, Shanghai, Beijing, Quanzhou, Xingtai, etc., exhibit higher centrality for their strong consumption power or commodity production capacity. These cities also develop relatively strong connections with national central cities (Chengdu, Chongqing, Wuhan, Tianjin, etc.) and provincial capitals (Changsha, Urumqi, Hulun Buir, etc.). The cities on the western side of the Hu-line present low centrality and weak connections with the eastern cities and form sub-network with the provincial capital cities as the core. © The Author(s) 2022.","centrality; Connectivity; intercity express; waybill data","Beijing [China]; Changsha; Chengdu; China; Chongqing; Fujian; Guangdong; Guangzhou; Hebei; Hubei; Hunan; Jinhua; Quanzhou; Shanghai; Shenzhen; Sichuan; Tianjin; Urumqi; Wuhan; Xingtai; Xinjiang Uygur; Zhejiang; agglomeration; electronic commerce; energy use; industrial production; railway transport; spatial distribution; urban transport",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (42271195, 72173101)","The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the National Natural Science Foundation of China [42271195, 72173101].","Dong L., Yuan X.H., Li M., Et al., A gridded establishment dataset as a proxy for economic activity in China, Scientific Data, 8, (2021); Rai H.B., Dablanc L., Hunting for treasure: a systematic literature review on urban logistics and e-commerce data, Transport Reviews, (2022); Ren M.Y., Xiao Z.P., Wang J.J., Spatial pattern of intercity less-than-truckload logistics networks in China, Acta Geographica Sinica, 75, pp. 820-832, (2020); Song Z.Y., The geography of online shopping in China and its key drivers, Environment and Planning B-Urban Analytics and City Science, 49, pp. 259-274, (2022); Wang M.J., Yan Z.H., Yu B., Et al., Spatial pattern and change of e-commerce specialized villages and influence factors based on the data of Taobao villages in China from 2015 to 2020, Progress in Geography, 41, pp. 838-853, (2022)","G. Li; Southwest Jiaotong University, China; email: guoqi@swjtu.edu.cn",null,"SAGE Publications Ltd",{"$nulls":5},2.3998083E7,null,null,null,"English","Environ. Plann.","Article","Final",null,"Scopus","2-s2.0-85141020168"]
["Nanayakkara P.R.; Jayalath M.M.; Thibbotuwawa A.; Perera H.N.","Nanayakkara, Pamal R. (57855099600); Jayalath, Madushan Madhava (57255192200); Thibbotuwawa, Amila (57203454779); Perera, H. Niles (57195406834)","57855099600; 57255192200; 57203454779; 57195406834","A circular reverse logistics framework for handling e-commerce returns",2022.0,"Cleaner Logistics and Supply Chain",5.0,null,100080.0,null,null,null,11.0,"10.1016/j.clscn.2022.100080","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85136482891&doi=10.1016%2fj.clscn.2022.100080&partnerID=40&md5=de7122971500b20d0477c9f03b82baa3","Center for Supply Chain, Operations and Logistics Optimization, Department of Transport and Logistics Management, University of Moratuwa, Katubedda, 10400, Sri Lanka; Professor H.Y. Ranjit Perera Institute for Applied Research, Nugegoda, 10250, Sri Lanka","Nanayakkara P.R., Center for Supply Chain, Operations and Logistics Optimization, Department of Transport and Logistics Management, University of Moratuwa, Katubedda, 10400, Sri Lanka; Jayalath M.M., Center for Supply Chain, Operations and Logistics Optimization, Department of Transport and Logistics Management, University of Moratuwa, Katubedda, 10400, Sri Lanka, Professor H.Y. Ranjit Perera Institute for Applied Research, Nugegoda, 10250, Sri Lanka; Thibbotuwawa A., Center for Supply Chain, Operations and Logistics Optimization, Department of Transport and Logistics Management, University of Moratuwa, Katubedda, 10400, Sri Lanka, Professor H.Y. Ranjit Perera Institute for Applied Research, Nugegoda, 10250, Sri Lanka; Perera H.N., Center for Supply Chain, Operations and Logistics Optimization, Department of Transport and Logistics Management, University of Moratuwa, Katubedda, 10400, Sri Lanka, Professor H.Y. Ranjit Perera Institute for Applied Research, Nugegoda, 10250, Sri Lanka","Global e-commerce sales are growing rapidly adding complexities to their supply chains. There are an increasing trend of product returns along with the growth of global e-commerce platforms, placing a huge significance on reverse logistics management. E-commerce being a competitive industry, factors such as environmental concerns, customer awareness, and legal pressure have led the firms to pay attention to the circular economy and sustainability concepts while managing their reverse logistics. Considering the above factors, this paper proposes a three-stage, circular reverse logistics framework for handling e-commerce returns. We introduce a novel method of applying ward-like hierarchical clustering with geographical constraints on returns data to identify return patterns as the first stage. As the second stage, a circular economy network was introduced among different parties to commit towards the circular economy. We develop a mixed integer linear programming model upon the above circular economy network in the third stage to capture different facets of the reverse logistics in e-commerce and optimize the network. At the final stage, the model is validated with a case study based on an e-commerce firm engaged in consumer electrical and electronics. The decision support system which is an output of this study will help the decision makers in e-commerce firms to embrace circular economy and optimize the reverse logistics network, while handling product returns. © 2022 The Authors","Circular economy network; Clustering; Decision support system; E-commerce; Reverse logistics network design",{"$nulls":5},"University of Moratuwa, (SRC/LT/2021/22)","The authors would like to acknowledge the financial support given by the University of Moratuwa, Sri Lanka, through the University Senate Research Committee research grant : SRC/LT/2021/22 for this research.","Agrawal S., Singh R.K., Analyzing disposition decisions for sustainable reverse logistics: Triple Bottom Line approach, Resour. Conserv. Recycl., 150, (2019); Bernon M., Tjahjono B., Ripanti E.F., Aligning retail reverse logistics practice with circular economy values: an exploratory framework, Prod. Plan. Control., 29, pp. 483-497, (2018); Chang Q.Q., Zheng H.Z., An effective strategy for non-defective reverse logistics, 2014 IEEE Int, Conf. Inf. Autom. ICIA, 2014, pp. 1273-1277, (2014); Chavent M., Kuentz V., Labenne A., Saracco J., (2017); Chavent M., Kuentz-Simonet V., Labenne A., Saracco J., (2018); Correa H.L., Xavier L.H., (2013); Das D., Kumar R., Rajak M.K., (2020); (2017); de Oliveira C.T., Monica M.M.M., Campos L.M.S., Understanding the Brazilian expanded polystyrene supply chain and its reverse logistics towards circular economy, J. Clean. Prod., 235, pp. 562-573, (2019); de Oliveira Neto G.C., de Jesus Cardoso A., Correia A.M.S., Economic and environmental assessment of recycling and reuse of electronic waste: multiple case studies in Brazil and Switzerland, Resour. Conserv. Recycl., 127, pp. 42-55, (2017); Dennis S., (2018); Dhakal M., Hudson Smith M., Newbery R., Secondary market: a significant aspect in reverse logistics and sustainability, Int. J. Sustain. Econ. Soc. Cult. Context, 12, 1, pp. 25-35, (2016); Dutta P., Mishra A., Khandelwal S., Katthawala I., A multiobjective optimization model for sustainable reverse logistics in Indian E-commerce market, J. Clean. Prod., 249, (2020); Elkington J., Triple bottom line.pdf, Environ. Qual. Manag., 8, pp. 37-51, (1998); (2015); Forti V., Balde C.P., Kuehr R., Bel G., (2020); Gao X., Cao C., A novel multi-objective scenario-based optimization model for sustainable reverse logistics supply chain network redesign considering facility reconstruction, J. Clean. Prod., 270, (2020); Ghisellini P., Ripa M., Ulgiati S., Exploring environmental and economic costs and benefits of a circular economy approach to the construction and demolition sector. A literature review, J. Clean. Prod., 178, pp. 618-643, (2018); Guo J., Liu X., Jo J., Dynamic joint construction and optimal operation strategy of multi-period reverse logistics network: a case study of Shanghai apparel E-commerce enterprises, J. Intell. Manuf., 28, pp. 819-831, (2017); Guo J., Wang X., Fan S., Gen M., Forward and reverse logistics network and route planning under the environment of low-carbon emissions: A case study of Shanghai fresh food E-commerce enterprises, Comput. Ind. Eng., 106, pp. 351-360, (2017); Hawks K., What is reverse logistics?, Reverse Logist. Mag., 1, 1, pp. 12-13, (2006); Homrich A.S., Galvao G., Abadia L.G., Carvalho M.M., The circular economy umbrella: trends and gaps on integrating pathways, J. Clean. Prod., 175, pp. 525-543, (2018); Isernia R., Passaro R., Quinto I., Thomas A., The reverse supply chain of the e-waste management processes in a circular economy framework: evidence from Italy, Sustain, 11, (2019); Julianelli V., Caiado R.G.G., Scavarda L.F., (2020); Kuo T.C., Chiu M.C., Chung W.H., Yang T.I., The circular economy of LCD panel shipping in a packaging logistics system, Resour. Conserv. Recycl., 149, pp. 435-444, (2019); Larsen S.B., Masi D., Jacobsen P., Godsell J., (2018); Lechner G., Reimann M., Integrated decision-making in reverse logistics: an optimisation of interacting acquisition, grading and disposition processes, Int. J. Prod. Res., 58, pp. 5786-5805, (2020); Li Y., Lu M., Liu B., A two-stage algorithm for the closed-loop location-inventory problem model considering returns in E-commerce, Math. Probl. Eng., 2014, (2014); Liu D., Network site optimization of reverse logistics for E-commerce based on genetic algorithm, Neural Comput. Appl., 25, pp. 67-71, (2014); Olist D., Magioli F., Brazilian E-commerce public dataset by olist, Kaggle, (2018); Ottoni M., Dias P., Xavier L.H., A circular approach to the e-waste valorization through urban mining in Rio de Janeiro, Brazil, J. Clean. Prod., 261, (2020); Peck P., Delaney K., Richter J.L., Peck P., (2020); Perera H.N., Perera H.Y.R., Applications of pixel oriented mobility modelling in transport & logistics, Lect. Notes Logist., pp. 337-348, (2022); Ramanathan R., An empirical analysis on the influence of risk on relationships between handling of product returns and customer loyalty in E-commerce, Int. J. Prod. Econ., 130, pp. 255-261, (2011); Rashid A., Asif F.M.A., Krajnik P., Nicolescu C.M., Resource Conservative Manufacturing: an essential change in business and technology paradigm for sustainable manufacturing, J. Clean. Prod., 57, pp. 166-177, (2013); Returns R., (2021); Rogers D.S., Lambert D.M., Croxton K.L., Garcia-Dastugue S.J., The returns management process, Int. J. Logist. Manage., 13, pp. 1-18, (2002); Rollecke F.J., Huchzermeier A., Schroder D., Returning customers: the hidden strategic opportunity of returns management, Calif Manage. Rev., 60, pp. 176-203, (2018); (2019); Shokohyar S., Mansour S., Simulation-based optimisation of a sustainable recovery network for waste from electrical and electronic equipment (WEEE), Int. J. Comput. Integr. Manuf., 26, pp. 487-503, (2013); Shokouhyar S., Aalirezaei A., Designing a sustainable recovery network for waste from electrical and electronic equipment using a genetic algorithm, Int. J. Environ. Sustain. Dev., 16, pp. 60-79, (2017); Sun Q., Research on the influencing factors of reverse logistics carbon footprint under sustainable development, Environ. Sci. Pollut. Res., 24, pp. 22790-22798, (2017); Thibbotuwawa A., Nielsen P., Bocewicz G., Banaszak Z., UAVs fleet mission planning subject to weather fore-cast and energy consumption constraints, Adv. Intell. Syst. Comput., 920, pp. 104-114, (2020); Thibbotuwawa A., Bocewicz G., Nielsen P., Banaszak Z., UAV mission planning subject to weather forecast constraints, Adv. Intell. Syst. Comput., 1004, pp. 65-76, (2020); Tong X., Wang T., Chen Y., Wang Y., Towards an inclusive circular economy: quantifying the spatial flows of e-waste through the informal sector in China, Resour. Conserv. Recycl., 135, pp. 163-171, (2018); Vlachos D., Dekker R., Return handling options and order quantities for single period products, Eur. J. Oper. Res., 151, pp. 38-52, (2003); Wang C.N., Dang T.T., Nguyen N.A.T., Outsourcing reverse logistics for e-commerce retailers: a two-stage fuzzy optimization approach, Axioms, 10, (2021); Yu H., Solvang W.D., (2013); Yu H., Solvang W.D., A stochastic programming approach with improved multi-criteria scenario-based solution method for sustainable reverse logistics design of waste electrical and electronic equipment (WEEE), Sustain, 8, (2016); Zhou X., Zhou Y., Designing a multi-echelon reverse logistics operation and network: a case study of office paper in Beijing, Resour. Conserv. Recycl., 100, pp. 58-69, (2015)","A. Thibbotuwawa; Center for Supply Chain, Operations and Logistics Optimization, Department of Transport and Logistics Management, University of Moratuwa, Katubedda, 10400, Sri Lanka; email: amilat@uom.lk",null,"Elsevier Ltd",{"$nulls":5},2.7723909E7,null,null,null,"English","Clean. Logist. Supply Chain","Article","Final","All Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85136482891"]
["Luo Y.; Liu Y.; Wu Z.; Xing L.","Luo, Yuanyuan (57391652400); Liu, Yanfang (55995709500); Wu, Zihao (57198579118); Xing, Lijun (57197744689)","57391652400; 55995709500; 57198579118; 57197744689","An assessing framework for the proper allocation of collection and delivery points from the residents' perspective",2022.0,"Research in Transportation Business and Management",45.0,null,100776.0,null,null,null,5.0,"10.1016/j.rtbm.2021.100776","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85122005935&doi=10.1016%2fj.rtbm.2021.100776&partnerID=40&md5=cd5e2399efda9b0dd487e130d87d56ea","School of Resource and Environment Science, Wuhan University, 129 Luoyu Road, Wuhan, 430079, China; Key Laboratory of Geographical Information System, Ministry of Education, Wuhan University, 129 Luoyu Road, Wuhan, 430079, China; Key School of Resources and Environmental Science, Hubei University, Wuhan, 430062, China","Luo Y., School of Resource and Environment Science, Wuhan University, 129 Luoyu Road, Wuhan, 430079, China; Liu Y., School of Resource and Environment Science, Wuhan University, 129 Luoyu Road, Wuhan, 430079, China, Key Laboratory of Geographical Information System, Ministry of Education, Wuhan University, 129 Luoyu Road, Wuhan, 430079, China; Wu Z., School of Resource and Environment Science, Wuhan University, 129 Luoyu Road, Wuhan, 430079, China; Xing L., Key School of Resources and Environmental Science, Hubei University, Wuhan, 430062, China","Along with the advancement of information technology, the prevalence of e-commerce has promoted the rapid development of the express delivery industry. In relation to this, collection and delivery points (CDPs) have become important places to facilitate convenience for residents. Thus far, the majority of studies focused on the logistic transportation perspective without considering residents' convenience. Therefore, this study proposes an assessing framework of four CDP features from the perspective of residents' convenience, with a focus on Wuhan City. In particular, descriptive statistics and spatial analysis were conducted to analyze patterns of service target, adjacency, accessibility, and agglomeration. In addition, regression analysis was conducted on the indicators of adjacency and accessibility, combined with policy and socioeconomic factors. Through this framework, the overserved and underserved areas in Wuhan City were identified on a community level based on CDP location. Several results were obtained as follows. 1) CDPs mainly serve residents in residential and commercial land and that attended CDPs are farther from the urban area than unattended CDPs. 2) The levels of delivery comfort and delivery efficiency of suburban residents are generally lower than those of downtown residents, while the level of delivery efficiency near colleges and universities is higher. 3) Overserved areas are found in urban locations, while underserved areas are located in suburban locations. Moreover, residents near the edge of city centers enjoy higher CDP accessibility than those located in the center. In terms of age, the accessibility inequity is pronounced in the over 60 age group. 4) The spatial distribution of CDPs is in aggregation, and unattended CDPs are more compact than attended CDPs. 5) Finally, policies and socioeconomic factors have different effects on CDPs' adjacency and accessibility. Overall, these findings may provide a realistic estimation of residents' situation to help private firms design better CDP layouts and create efficient delivery systems as well as to help public authorities develop equal and effective planning policies and strategies related to CDPs. © 2021 Elsevier Ltd","Collection and delivery points; E-commerce; Resident convenience; Urban logistics",{"$nulls":5},"National Key Research and Development Program of China, NKRDPC, (2017YFB0503601)","Supported by the National Key Research and Development Program (Grant No: 2017YFB0503601 ).",{"$cut":{"chars":18872,"head":"Aljohani K., Thompson R.G., Impacts of logistics sprawl on the urban environment and logistics: Taxonomy and review of literature, Journal of Transport Geography, 57, pp. 255-263, (2016); Allen J., Piecyk M., Piotrowska M., McLeod F., Cherrett T., Ghali K., Nguyen T., Bektas T., Bates O., Friday A., Wise S., Austwick M., Understanding the impact of e-commerce on last-mile light goods vehicle activity in urban areas: The case of London, Transportation Research Part D: Transport and Environment, 61, pp. 325-338, (2018); Banyai T., Illes B., Banyai A., Smart scheduling: An integrated first mile and last mile supply approach, Complexity, 2018, (2018); Bard J.F., Jarrah A.I., Integrating commercial and residential pickup and delivery networks: A case study, Omega, 41, pp. 706-720, (2013); Bergmann F.M., Wagner S.M., Winkenbach M., Integrating first-mile pickup and last-mile delivery on shared vehicle routes for efficient urban e-commerce distribution, Transportation Research Part B: Methodological, 131, pp. 26-62, (2020); Boyer K.K., Prud'homme A.M., Chung W., The last mile challenge: Evaluating the effects of customer density and delivery window patterns, Journal of Business Logistics, 30, pp. 185-201, (2009); Buldeo Rai H., Verlinde S., Macharis C., The “next day, free delivery” myth unravelled: Possibilities for sustainable last mile transport in an omnichannel environment, International Journal of Retail & Distribution Management, 47, pp. 39-54, (2019); Buldeo Rai H., Verlinde S., Macharis C., Unlocking the failed delivery problem? Opportunities and challenges for smart locks from a consumer perspective, (2019); Cardenas I., Borbon-Galvez Y., Verlinden T., Van de Voorde E., Vanelslander T., Dewulf W., City logistics, urban goods distribution and last mile delivery and collection, Competition and Regulation in Network Industries, 18, pp. 22-43, (2017); Carotenuto P., Gastaldi M., Giordani S., Rossi R., Rabachin A., Salvatore A., Comparison of various urban distribution systems supporting e-commerce. Point-to-point vs collection-point-based deliveries, Transportation Research Procedia, 30, pp. 188-196, (2018); de Carvalho N.L.A., Ribeiro P.C.C., Garcia-Martos C., Fernandez C.G., Vieira J.G.V., Urban distribution centres in historical cities from the perspective of residents, retailers and carriers, Research in Transportation Economics, 77, (2019); Caspersen E., Navrud S., The sharing economy and consumer preferences for environmentally sustainable last mile deliveries, Transportation Research Part D: Transport and Environment, 95, (2021); CECRC, Chinese E-commerce logistics consumption complaint data and typical case reports, (2020); Chang H.-S., Liao C.-H., Exploring an integrated method for measuring the relative spatial equity in public facilities in the context of urban parks, Cities, 28, pp. 361-371, (2011); Chen J., Wu F., Lu T., The financialization of rental housing in China: A case study of the asset-light financing model of long-term apartment rental, Land Use Policy, 105442, (2021); Chen Y., Yu J., Yang S., Wei J., Consumer's intention to use self-service parcel delivery service in online retailing: An empirical study, Internet Research, 28, pp. 500-519, (2018); Collins A.T., Behavioural influences on the environmental impact of collection/delivery points, Green logistics and transportation: A sustainable supply chain perspective, pp. 15-34, (2015); Curtis C., Scheurer J., Planning for sustainable accessibility: Developing tools to aid discussion and decision-making, Progress in Planning, 74, pp. 53-106, (2010); Dadashpoor H., Rostami F., Alizadeh B., Is inequality in the distribution of urban facilities inequitable? Exploring a method for identifying spatial inequity in an Iranian city, Cities, 52, pp. 159-172, (2016); Dai D., Racial/ethnic and socioeconomic disparities in urban green space accessibility: Where to intervene?, Landscape and Urban Planning, 102, pp. 234-244, (2011); De Oliveira G.S., Bialek J., Marcus R.J., McCarthy R., Dose-ranging effect of systemic diphenhydramine on postoperative quality of re"}},"Y. Liu; School of Resource & Environment Science, Wuhan University, Wuhan, 129 Luoyu Road, 430079, China; email: yfliu610@163.com",null,"Elsevier Ltd",{"$nulls":5},2.2105395E7,null,null,null,"English","Res. Transport. Bus. Manage.","Article","Final",null,"Scopus","2-s2.0-85122005935"]
["Jiménez-Rodríguez E.; Vázquez-Cano E.; Cebrián-Hernández Á.; López-Meneses E.","Jiménez-Rodríguez, Enrique (54684182600); Vázquez-Cano, Esteban (55548952900); Cebrián-Hernández, Ángeles (57221910146); López-Meneses, Eloy (56495544200)","54684182600; 55548952900; 57221910146; 56495544200","Influence of Computer Knowledge and Level of Education on Spanish Citizens’ Propensity to Use E-Commerce",2022.0,"Social Science Computer Review",40.0,6.0,null,1376.0,1392.0,16.0,2.0,"10.1177/08944393211007313","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85104960633&doi=10.1177%2f08944393211007313&partnerID=40&md5=73addac5ae00305f1c748c8048ea5a0d","Universidad Pablo de Olavide, Sevilla, Spain; Universidad Nacional de Educación a Distancia (UNED), Madrid, Spain; Universidad de Sevilla, Spain","Jiménez-Rodríguez E., Universidad Pablo de Olavide, Sevilla, Spain; Vázquez-Cano E., Universidad Nacional de Educación a Distancia (UNED), Madrid, Spain; Cebrián-Hernández Á., Universidad de Sevilla, Spain; López-Meneses E., Universidad Pablo de Olavide, Sevilla, Spain","This article analyzes the influence of Spanish citizens’ computer knowledge and level of education on their tolerance of, or aversion to, risk in the online purchase of goods and services. To this end, annual survey data from Spain’s National Statistics Institute were used to know the incidence in e-commerce of the following variables: “computer knowledge,” “electronic commerce,” and “socioeconomic characteristics.” A method based on the design of a computer knowledge indicator was used, followed by a bivariate logistic regression to determine computer knowledge and level of education. The results show that the higher the level of computer knowledge, the greater the impulse to buy online and the higher the tolerance of risk. There was also a positive relation between level of education and propensity to buy; the higher the level of education, the greater the propensity. © The Author(s) 2021.","computer knowledge; digital competence; e-commerce; level of education; Spain",{"$nulls":5},"Ministerio de Ciencia, Innovación y Universidades, MCIU, (RTI2018-099764-B-100)","The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported by Ministerio de Ciencia, Innovación y Universidades (grant ID: RTI2018-099764-B-100).","Abad-Segura E., . Gonzalez-Zarmar M.D., . Lopez-Meneses E., . Vazquez-Cano. E., Financial technology: Review of trends, approaches and management, Mathematics, 8, (2020); Ajzen I., Fishbein M., Understanding Attitudes and Predicting Social Behavior. 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Vázquez-Cano; Universidad Nacional de Educación a Distancia (UNED), Madrid, Spain; email: evazquez@edu.uned.es",null,"SAGE Publications Inc.",{"$nulls":5},8944393.0,null,null,null,"English","Soc. Sci. Comput. Rev.","Article","Final",null,"Scopus","2-s2.0-85104960633"]
["Lin Y.H.; Wang Y.; Lee L.H.; Chew E.P.","Lin, Yun Hui (57216781261); Wang, Yuan (57079310600); Lee, Loo Hay (55667526300); Chew, Ek Peng (7102013740)","57216781261; 57079310600; 55667526300; 7102013740","Omnichannel facility location and fulfillment optimization",2022.0,"Transportation Research Part B: Methodological",163.0,null,null,187.0,209.0,22.0,7.0,"10.1016/j.trb.2022.07.005","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85134372555&doi=10.1016%2fj.trb.2022.07.005&partnerID=40&md5=742fe07a08681f023039fe8117d451df","School of Business, University College Dublin, Ireland; School of Business, Singapore University of Social Sciences, Singapore; Department of Industrial Systems Engineering & Management, National University of Singapore, Singapore","Lin Y.H., School of Business, University College Dublin, Ireland; Wang Y., School of Business, Singapore University of Social Sciences, Singapore; Lee L.H., Department of Industrial Systems Engineering & Management, National University of Singapore, Singapore; Chew E.P., Department of Industrial Systems Engineering & Management, National University of Singapore, Singapore","E-commerce has been evolving towards omnichannel as we have witnessed many once pure e-retailers opening physical stores or showrooms to enable customers to inspect the product and quickly assess product fit. In omnichannel transportation operations, these stores can strategically fulfill online orders to improve delivery efficiency and reduce transportation costs. Motivated by this trend, this paper studies a pure e-retail company that plans to introduce the offline channel with physical stores and practice omnichannel distribution. For the e-retailer, opening stores can benefit from the reduced transportation cost and the increased revenue, both of which inherently depend on how customers choose channels and stores to make purchases. To this end, we employ a discrete choice model to estimate customers’ choices and then propose a modeling framework that jointly optimizes the location of stores and the omnichannel fulfillment strategy to maximize the profit, accounting for the revenue, the transportation cost, and the fixed operating cost of stores. To solve the model of practical scale, we develop a branch-and-cut algorithm, which leverages Benders cuts that are generated on-the-fly using two analytical separation functions. Our computational studies suggest that the proposed algorithm is efficient for solving large-scale problems. Finally, we conduct sensitivity analysis and draw insightful observations. © 2022 Elsevier Ltd","Discrete choice model; Facility location; Omnichannel fulfillment; Omnichannel retailing; Transportation","Cost benefit analysis; Cost reduction; Electronic commerce; Integer programming; Location; Retail stores; Sales; Sensitivity analysis; Discrete choice models; E retails; Facilities locations; Omnichannel fulfillment; Omnichannel retailing; Online orders; Optimisations; Physical stores; Transportation cost; Transportation operations; consumption behavior; discrete choice analysis; electronic commerce; strategic approach; transportation system; Computational efficiency",{"$nulls":6},"Aboolian R., Berman O., Krass D., Competitive facility location and design problem, European J. Oper. Res., 182, 1, pp. 40-62, (2007); Ahumada A., Ulku L., Luce rule with limited consideration, Math. 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["Beckers J.; Cardenas I.; Sanchez-Diaz I.","Beckers, Joris (57191037901); Cardenas, Ivan (57191038157); Sanchez-Diaz, Ivan (55365754800)","57191037901; 57191038157; 55365754800","Managing household freight: The impact of online shopping on residential freight trips",2022.0,"Transport Policy",125.0,null,null,299.0,311.0,12.0,9.0,"10.1016/j.tranpol.2022.06.009","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85141649892&doi=10.1016%2fj.tranpol.2022.06.009&partnerID=40&md5=2b41c64f6da82a6353955e6399761568","Department of Transport and Regional Economics, University of Antwerp, Prinsstraat 13, Antwerpen, 2000, Belgium; Department of Technology Management and Economics, Chalmers University of Technology, Sweden","Beckers J., Department of Transport and Regional Economics, University of Antwerp, Prinsstraat 13, Antwerpen, 2000, Belgium; Cardenas I., Department of Transport and Regional Economics, University of Antwerp, Prinsstraat 13, Antwerpen, 2000, Belgium; Sanchez-Diaz I., Department of Technology Management and Economics, Chalmers University of Technology, Sweden","Freight transport management and planning traditionally relies on freight transport models. However, e-commerce has changed the way freight is transported and requires a paradigm shift in such models. In contrast to conventional purchases in physical outlets, there is a spatial and temporal disconnection between the purchase and the reception of goods bought online. While traditionally the shopper brings home the purchases, the courier, express and parcel (CEP) sector must bridge this leg for the online retail channel by delivering the parcel to the household. These new type of freight trips have been ignored in the literature on freight modeling. Given the increasing number of urban freight trips destined for households, this omission implies significant errors when demonstrating transport impacts, identifying potential innovations, or assessing policy initiatives with these models. Therefore, we develop a framework that demonstrates how households' online consumption translates into freight trips. Three key factors in this framework seem to determine the magnitude of freight traffic originated by household's online shopping: (i) consumer shopping behavior, (ii) the supplier network and distribution system designed by the online store, and (iii) the fragmentation of the CEP market and the density of the delivery network. The identification of these three key factors provides a framework for policy action to mitigate the impact of household freight. © 2022 The Authors","Consumer behavior; Delivery location; Freight generation; Online shopping; Urban logistics planning","consumption behavior; freight transport; logistics; shopping activity; transportation planning; urban planning",{"$nulls":4},"Fonds Wetenschappelijk Onderzoek, FWO, (1270021N)","The research was supported by the FWO (Grant 1270021N ). JB is a postdoctoral fellow fundamental research of the Research Foundation - Flanders.","Adler T.J., Ben-Akiva M., Joint-choice Model for Frequency, Destination, and Travel Mode for Shopping Trips, (1976); Alho A.R., e Silva J.D.A., de Sousa J.P., Blanco E., Improving mobility by optimizing the number, location and usage of loading/unloading bays for urban freight vehicles, Transport. Res. 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Spatial Econ., 18, 3, pp. 633-656, (2018); Vrechopoulos A.P., Siomkos G.J., Doukidis G.I., Internet shopping adoption by Greek consumers, Eur. J. Innovat. Manag., 4, 3, pp. 142-153, (2001); Wang X.C., Zhou Y., Deliveries to residential units : a rising form of freight transportation in the U. S, Transport. Res. Part C, 58, pp. 46-55, (2015); Weltevreden J.W.J., Substitution or complementarity? How the Internet changes city centre shopping, J. Retailing Consum. Serv., 14, 3, pp. 192-207, (2007); Zhou Y., Wang X.C., Explore the relationship between online shopping and shopping trips: an analysis with the 2009 NHTS data, Transport. Res. Pol. Pract., 70, pp. 1-9, (2014)","J. Beckers; Department of Transport and Regional Economics, University of Antwerp, Antwerpen, Prinsstraat 13, 2000, Belgium; email: joris.beckers@uantwerpen.be",null,"Elsevier Ltd",{"$nulls":5},"0967070X",null,null,null,"English","Transp. Policy","Article","Final","All Open Access; Green Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85141649892"]
["Anosike A.; Loomes H.; Udokporo C.K.; Garza-Reyes J.A.","Anosike, Anthony (12804373700); Loomes, Helena (57267373800); Udokporo, Chinonso Kenneth (57214726972); Garza-Reyes, Jose Arturo (35310169200)","12804373700; 57267373800; 57214726972; 35310169200","Exploring the challenges of electric vehicle adoption in final mile parcel delivery",2023.0,"International Journal of Logistics Research and Applications",26.0,6.0,null,683.0,707.0,24.0,21.0,"10.1080/13675567.2021.1978409","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85115439648&doi=10.1080%2f13675567.2021.1978409&partnerID=40&md5=05099335c69c786bbb4d926c441d6141","Centre for Supply Chain Improvement, University of Derby, Derby, United Kingdom; Derby Business School, University of Derby, Derby, United Kingdom","Anosike A., Centre for Supply Chain Improvement, University of Derby, Derby, United Kingdom; Loomes H., Derby Business School, University of Derby, Derby, United Kingdom; Udokporo C.K., Centre for Supply Chain Improvement, University of Derby, Derby, United Kingdom; Garza-Reyes J.A., Centre for Supply Chain Improvement, University of Derby, Derby, United Kingdom","The rise in e-commerce has increased last mile parcel deliveries, in turn affecting the sustainability of transport. With the worldwide efforts to minimise fossil fuel use including the UK Government's plans to end the sales of new petrol and diesel vehicles by 2035, alternative fuels need to be explored. Currently, one of the most promising solutions is the electric vehicle (EV) which produces zero tailpipe emissions. This paper aims to explore the challenges of adopting EVs in final mile parcel deliveries, and thus identify potential directions for future research. To achieve this, we developed a systematic literature review to understand the nature of these challenges better and provide a background from which to acquire more information from leading logistics companies in the form of in-depth interviews. We found that the companies encountered different challenges based on their fleet sizes, schedule and capacity to implement the required structural and infrastructural changes to support the efficient running of their last mile delivery operations on EVs. © 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.","concept map; concept map; electric vehicles; last mile logistics; Systematic literature review; thematic analysis",{"$nulls":7},"Ahani P., Arantes A., Melo S., A Portfolio Approach for Optimal Fleet Replacement Toward Sustainable Urban Freight Transportation, Transportation Research Part D, 48, pp. 357-368, (2016); (2018); Barnett-Page E., Thomas J., (2009); Berkeley N., Bailey D., Jones A., Jarvis D., Assessing the Transition Towards Battery Electric Vehicles: A Multi-Level Perspective on Drivers of, and Barriers to, Take up, Transportation Research Part A, 106, pp. 320-332, (2017); Biresselioglu M.E., Kaplan M.D., Yilmaza B.K., Electric Mobility in Europe: A Comprehensive Review of Motivators and Barriers in Decision Making Processes, Transportation Research Part A, 109, pp. 1-13, (2018); Breunig U., Baldacci R., Hartl R.F., Vidal T., The Electric Two-echelon Vehicle Routing Problem, Computers and Operations Research, 103, pp. 198-210, (2019); Bryman A., Bell E., Business Research Methods, (2015); Cassia A.R., Costa I., da Silva V.H.C., de Oliveira Neto G.C., Systematic Literature Review for the Development of a Conceptual Model on the Relationship Between Knowledge Sharing, Information Technology Infrastructure and Innovative Capability, Technology Analysis & Strategic Management, 32, pp. 801-821, (2020); Christensen L., Klauenberg J., Kveiborg O., Rudolph C., Suitability of Commercial Transport for a Shift to Electric Mobility with Denmark and Germany as Use Cases, Research in Transportation Economics, 64, pp. 48-60, (2017); Collis J., Hussey R., (2003); Darlington A., (2020); de Mello Bandeira R.A., Goes G.V., Goncalves D.N.S., Marcio de A.D., de Oliveira C.M., Electric Vehicles in the Last Mile of Urban Freight Transportation: A Sustainability Assessment of Postal Deliveries in Rio de Janeiro-Brazil, Transportation Research Part D: Transport and Environment, 67, pp. 491-502, (2019); Feng W., Figliozzi M., Conventional vs Electric Commercial Vehicle Fleets: A Case Study of Economic and Technological Factors Affecting the Competitiveness of Electric Commercial Vehicles in the USA, Procedia-Social and Behavioral Sciences, 39, pp. 702-711, (2012); 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Saunders M., Lewis P., Thornhill A., Research Methods for Business Students, (2016); Schiffer M., Walther G., Strategic Planning of Electric Logistics Fleet Networks: A Robust Location-Routing Approach, Omega, 80, pp. 31-42, (2018); Schucking M., Jochem P., Fichtner W., Wollersheim O., Stella K., Charging Strategies for Economic Operations of Electric Vehicles in Commercial Applications, Transportation Research Part D, 51, pp. 173-189, (2017); Vosooghi R., Puchinger J., Bischoff J., Jankovic M., Vouillon A., Shared Autonomous Electric Vehicle Service Performance: Assessing the Impact of Charging Infrastructure, Transportation Research Part D: Transport and Environment, 81, (2020); Wikstrom M., Hansson L., Alvfors P., Socio-technical Experiences from Electric Vehicle Utilisation in Commercial Fleets, Applied Energy, 123, pp. 82-93, (2014); Wikstrom M., Hansson L., Alvfors P., An End Has a Start–Investigating the Usage of Electric Vehicles in Commercial Fleets, Energy Procedia, 75, pp. 1932-1937, (2016)","C.K. Udokporo; Centre for Supply Chain Improvement, University of Derby, Derby, United Kingdom; email: c.udokporo@derby.ac.uk",null,"Taylor and Francis Ltd.",{"$nulls":5},1.3675567E7,null,null,null,"English","Int. J. Logist. Res. Applic.","Article","Final","All Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85115439648"]
["Park D.; Ryu D.","Park, Daehyeon (57216920251); Ryu, Doojin (35280774000)","57216920251; 35280774000","E-commerce retail and reverse factoring: A newsvendor approach",2023.0,"Managerial and Decision Economics",44.0,1.0,null,416.0,423.0,7.0,4.0,"10.1002/mde.3690","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135794646&doi=10.1002%2fmde.3690&partnerID=40&md5=b8da4d54deceff9130408603e2a2e1ea","College of Economics, Sungkyunkwan University, Seoul, South Korea","Park D., College of Economics, Sungkyunkwan University, Seoul, South Korea; Ryu D., College of Economics, Sungkyunkwan University, Seoul, South Korea","This study builds a theoretical model to examine how supply chain finance (SCF) services using fintech can ease e-commerce suppliers' capital constraints. Despite the innovation in the logistics industry during the Fourth Industrial Revolution and the increasing online shopping in the post-COVID era, small e-commerce enterprises may fail to grow owing to their budget constraints. Reverse factoring is believed to ease such suppliers' capital constraints. We analyze the effect of reverse factoring using the capital-constrained newsvendor model, and we consider the impacts of additional funding from SCF services. Our results show that SCF services reduce e-commerce suppliers' initial orders and, thus, alleviate their budget constraints. This finding suggests that the discount factor of reverse factoring should be higher to ease small suppliers' budget constraints and allow the e-commerce industry to grow sustainably. © 2022 John Wiley & Sons Ltd.",{"$nulls":6},"Ministry of Science, ICT and Future Planning, MSIP, (2022R1A2C1010596); National Research Foundation of Korea, NRF","This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT; Ministry of Science and ICT) (No. 2022R1A2C1010596). We extend our gratitude to Antony W. Dnes (the editor) and Daehan Kim for their valuable comments. 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Ryu; College of Economics, Sungkyunkwan University, Seoul, 25-2, Sungkyunkwan-ro, Jongno-gu, 03063, South Korea; email: sharpjin@skku.edu",null,"John Wiley and Sons Ltd",{"$nulls":5},1436570.0,null,null,null,"English","Manage. Decis. Econ.","Article","Final",null,"Scopus","2-s2.0-85135794646"]
["Pongeluppe L.S.","Pongeluppe, Leandro S. (57210338528)",5.7210338528E10,"The favela effect: Spatial inequalities and firm strategies in disadvantaged urban communities",2022.0,"Strategic Management Journal",43.0,13.0,null,2777.0,2808.0,31.0,3.0,"10.1002/smj.3414","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85130268692&doi=10.1002%2fsmj.3414&partnerID=40&md5=1b1ae5ed4bcd246dd8ae96717bf24afa","Rotman School of Management, University of Toronto, Toronto, ON, Canada","Pongeluppe L.S., Rotman School of Management, University of Toronto, Toronto, ON, Canada","Research summary: E-commerce firms make fewer products available and charge higher delivery prices to customers inside Brazilian favelas than they do to customers immediately outside favelas, despite the absence of infrastructure impediments at the favela borders. This phenomenological study uses mixed methods to investigate firm heterogeneity in these practices. The analysis shows that some firms treat favela consumers more equitably than their competitors. These firms (i) invest in physical stores inside and outside favelas, which are complementary to their online marketplaces, and (ii) engage genuinely with employees and consumers, which reflects their stakeholder orientation. By examining how firms operate in disadvantaged communities, scholars can enrich core theoretical constructs in strategic management, particularly by integrating insights from the fields of critical geography and urban economics. Managerial summary: This study investigates whether firms operate differently in disadvantaged communities compared to co-located nondisadvantaged areas. Findings show that operations in disadvantaged communities, such as favelas (Brazilian urban slums), demand specific investments that support transactions and contribute to realizing the underdeveloped potential of those communities. Firms succeed in commercial endeavors within disadvantaged communities by redeploying their resources and cultivating a stakeholder culture concomitantly. This strategy enables superior performance and the change-making of structural inequalities to help alleviate poverty and develop urban communities. © 2022 John Wiley & Sons Ltd.","complementary assets; disadvantaged communities; mixed methods; socioeconomic inequality; spatial inequality; stakeholder theory; sustainable development goals","Investments; Strategic planning; Complementary assets; Disadvantaged community; Firm strategy; Mixed method; Socio-economics; Socioeconomic inequality; Spatial inequality; Stakeholder theory; Sustainable development goal; Urban community; Electronic commerce",{"$nulls":6},"Acquisti A., Brandimarte L., Loewenstein G., Privacy and human behaviour in the age of information, Science, 347, 6221, pp. 509-515, (2015); Allcott H., Diamond R., Dube J.-P., Handbury J., Rahkovsky I., Schnell M., Food deserts and the causes of nutritional inequality, Quarterly Journal of Economics, 134, 4, pp. 1793-1844, (2019); Amis J., Barney J., Mahoney J.T., Wang H., Why we need a theory of stakeholder governance—And why this is a hard problem, Academy of Management Review, 45, 3, pp. 499-503, (2020); Anderson J., Markides C., Kupp M., The last frontier: Market creation in conflict zones, deep rural areas, and urban slums, California Management Review, 52, 4, pp. 6-28, (2010); Angrist J.D., Pischke J.-S., Mostly harmless econometrics: An empiricist's companion, (2008); Bansal P., DesJardine M., Business sustainability: It is about time, Strategic Organization, 12, 1, pp. 70-78, (2014); Barney J.B., Firm resources and sustained competitive advantage, Journal of Management, 17, 1, pp. 99-120, (1991); Barney J.B., Is the resource-based “view” a useful perspective for strategic management research? 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Pongeluppe; Rotman School of Management, University of Toronto, Toronto, M5S 3E6, Canada; email: l.pongeluppe@rotman.utoronto.ca",null,"John Wiley and Sons Ltd",{"$nulls":5},1432095.0,null,"SMAJD",null,"English","Strategic Manage J","Article","Final",null,"Scopus","2-s2.0-85130268692"]
["Rautela H.; Janjevic M.; Winkenbach M.","Rautela, Himanshu (57226605312); Janjevic, Milena (55809152100); Winkenbach, Matthias (57189308132)","57226605312; 55809152100; 57189308132","Investigating the financial impact of collection-and-delivery points in last-mile E-commerce distribution",2022.0,"Research in Transportation Business and Management",45.0,null,100681.0,null,null,null,5.0,"10.1016/j.rtbm.2021.100681","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85112090864&doi=10.1016%2fj.rtbm.2021.100681&partnerID=40&md5=810de6edbac6f39f05dbe123e0c64f88","Massachusetts Institute of Technology, 77 Massachusetts Ave, Cambridge, 02139, MA, United States","Rautela H., Massachusetts Institute of Technology, 77 Massachusetts Ave, Cambridge, 02139, MA, United States; Janjevic M., Massachusetts Institute of Technology, 77 Massachusetts Ave, Cambridge, 02139, MA, United States; Winkenbach M., Massachusetts Institute of Technology, 77 Massachusetts Ave, Cambridge, 02139, MA, United States","The rapid growth in e-commerce volumes, coupled with customer expectations of faster, flexible and cheaper parcel deliveries is increasing the pressure on retailers to design the most efficient delivery network. Collection-and-delivery points (CDPs aggregate demand for both forward and return flows and help minimize additional tours in the case of failed deliveries. In this paper, we formulate an optimization model that integrates CDPs in the design of the overall distribution network, including the location of upstream transshipment facilities. The model accounts for changes in demand density due to the placement of CDPs. It considers demand aggregation at the CDP for both forward and return flows, and the impact of failed deliveries and failed return pickups on the routing cost. The model considers different route options and solves them using extended routing cost approximation formulae thus allowing the implementation of the model on large-scale problems. We then apply the model to solve a real-world case study on the distribution network of a major Brazilian retailer. The results demonstrate that failed deliveries and failed return pickups increase both the last-mile cost and the overall cost of distribution, and CDPs effectively reduce these costs by aggregating the demand and minimizing travel time. © 2021 Elsevier Ltd","Collection-and-delivery points; E-commerce; Last-mile distribution; Urban logistics",{"$nulls":7},"451 Research, 451 Research's global unified commerce forecast uncovers dramatic shifts in consumer spending patterns, (2018); Aksen D., Altinkemer K., A location-routing problem for the conversion to the “click-and-mortar” retailing: The static case, European Journal of Operational Research, 186, 2, pp. 554-575, (2008); Ambrosino D., Grazia Scutella M., Distribution network design: New problems and related models, European Journal of Operational Research, 165, 3, pp. 610-624, (2005); BigCommerce, (2018); Boccia M., Crainic T.G., Sforza A., Sterle C., A metaheuristic for a two echelon location-routing problem, pp. 288-301, (2010); Brown J.R., Guiffrida A.L., Carbon emissions comparison of last mile delivery versus customer pickup, International Journal of Logistics Research and Applications, 17, 6, pp. 503-521, (2014); Bruns A., Klose A., Stahly P., Restructuring of Swiss parcel delivery services, OR-Spektrum, 22, 2, pp. 285-302, (2000); Business Insider Intelligence, The crowdsourced delivery market continues to improve last mile supply chain economics in the e-commerce era. Business insider, (2019); Collins A.T., Behavioural influences on the environmental impact of collection/delivery points, Green logistics and transportation: A sustainable supply chain perspective, pp. 15-34, (2015); Crainic T.G., Sforza A., Sterle C., Location-routing models for two-echelon freight distribution system design Bureaux de Montréal: Bureaux de Québec, (2011); Daganzo C.F., The distance traveled to visit N points with a maximum of C stops per vehicle: An analytic model and an application, Transportation Science, 18, 4, pp. 331-350, (1984); Drexl M., Schneider M., A survey of variants and extensions of the location-routing problem, European Journal of Operational Research, 241, 2, pp. 283-308, (2015); Guerrero-Lorente J., Ponce-Cueto E., Blanco E.E., A model that integrates direct and reverse flows in Omnichannel logistics networks, Engineering systems and networks, pp. 89-97, (2017); Guerrero-Lorente J., Gabor A.F., Ponce-Cueto E., Omnichannel logistics network design with integrated customer preference for deliveries and returns, Computers and Industrial Engineering, 144, (2020); Jacobsen S.K., Madsen O.B.G., A comparative study of heuristics for a two-level routing-location problem, European Journal of Operational Research, 5, 6, pp. 378-387, (1980); Janjevic M., Winkenbach M., Merchan D., Integrating collection-and-delivery points in the strategic design of urban last-mile e-commerce distribution networks, Transportation Research Part E: Logistics and Transportation Review, 131, pp. 37-67, (2019); Karaoglan I., Altiparmak F., Kara I., Dengiz B., The location-routing problem with simultaneous pickup and delivery: Formulations and a heuristic approach, (2011); Lin J.-R., Lei H.-C., Distribution systems design with two-level routing considerations, Annals of Operations Research, 172, 1, pp. 329-347, (2009); Maranzana F.E., On the location of supply points to minimize transport costs, The Journal of the Operational Research Society, 15, 3, pp. 261-270, (1964); McKinsey and Company, Parcel delivery: The future of last mile, (2016); McLeod F., Cherrett T., Song L., Transport impacts of local collection/delivery points, International Journal of Logistics Research and Applications, 9, 3, pp. 307-317, (2006); Merchan D., Winkenbach M., High-resolution last-mile network design, City logistics, 3, pp. 201-214, (2018); Morganti E., Seidel S., Blanquart C., Dablanc L., Lenz B., The impact of E-commerce on final deliveries: Alternative parcel delivery services in France and Germany, Transportation Research Procedia, 4, pp. 178-190, (2014); Morganti E., Dablanc L., Fortin F., Final deliveries for online shopping: The deployment of pickup point networks in urban and suburban areas, Research in Transportation Business and Management, 11, pp. 23-31, (2014); Nagy G., Salhi S., Location-routing: Issues, models and methods, European Journal of Operational Research, 177, 2, pp. 649-672, (2007); Post and Parcel, The true cost implications of failed deliveries, (2018); Prodhon C., Prins C., A survey of recent research on location-routing problems, European Journal of Operational Research, 238, 1, pp. 1-17, (2014); Salhi S., Nagy G., A cluster insertion heuristic for single and multiple depot vehicle routing problems with backhauling, The Journal of the Operational Research Society, 50, 10, pp. 1034-1042, (1999); Salhi S., Rand G.K., The effect of ignoring routes when locating depots, European Journal of Operational Research, 39, 2, pp. 150-156, (1989); Savelsbergh M., Van Woensel T., 50th anniversary invited article—city logistics: Challenges and opportunities, Transportation Science, 50, 2, pp. 579-590, (2016); Shopify, The plague of ecommerce return rates and how to maintain profitability, (2019); Smilowitz K.R., Daganzo C.F., Continuum approximation techniques for the design of integrated package distribution systems, Networks, 50, 3, pp. 183-196, (2007); Snoeck A., Winkenbach M., Mascarino E.E., Establishing a robust urban logistics network at FEMSA through stochastic multi-echelon location routing, City logistics, 2, pp. 59-78, (2018); Visser J., Nemoto T., Browne M., Home delivery and the impacts on urban freight transport: A review, Procedia - Social and Behavioral Sciences, 125, pp. 15-27, (2014); Weltevreden J.W.J., B2c e-commerce logistics: The rise of collection-and-delivery points in the Netherlands, International Journal of Retail & Distribution Management, 36, 8, pp. 638-660, (2008); Winkenbach M., Janjevic M., Classification of last-mile delivery models for e-commerce distribution: A global perspective, City logistics, 1, pp. 209-229, (2018); Winkenbach M., Kleindorfer P.R., Spinler S., Enabling urban logistics services at La Poste through multi-echelon location-routing, Transportation Science, 50, 2, pp. 520-540, (2016); World Economic Forum, Delivering the goods: E commerce logistics transformation, (2018)","M. Janjevic; Massachusetts Institute of Technology, Cambridge, 77 Massachusetts Ave, 02139, United States; email: mjanjevi@mit.edu",null,"Elsevier Ltd",{"$nulls":5},2.2105395E7,null,null,null,"English","Res. Transport. Bus. Manage.","Article","Final",null,"Scopus","2-s2.0-85112090864"]
["Kervola H.; Kallionpää E.; Liimatainen H.","Kervola, Henri (58106523200); Kallionpää, Erika (37861706900); Liimatainen, Heikki (57110111300)","58106523200; 37861706900; 57110111300","Delivering Goods Using a Baby Pram: The Sustainability of Last-Mile Logistics Business Models",2022.0,"Sustainability (Switzerland)",14.0,21.0,14031.0,null,null,null,1.0,"10.3390/su142114031","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85148290080&doi=10.3390%2fsu142114031&partnerID=40&md5=e1ff32a85a11a70f7ac80ba97548b5fd","Transport Research Centre Verne, Tampere University, Tampere, 33014, Finland","Kervola H., Transport Research Centre Verne, Tampere University, Tampere, 33014, Finland; Kallionpää E., Transport Research Centre Verne, Tampere University, Tampere, 33014, Finland; Liimatainen H., Transport Research Centre Verne, Tampere University, Tampere, 33014, Finland","This study compares the differences in the attitudes of last-mile delivery companies operating with different business models toward economic, environmental, and social sustainability. The economic perspective focuses on productivity, the environment, and social sustainability, and where the environment and social sustainability are concerned, on carbon neutrality goals and means, and on what societal factors companies consider important, respectively. In this multi-case qualitative study, a literature review was carried out and 11 semi-structured expert interviews were conducted in companies representing three business model categories: crowdshipping companies, last-mile providers, and traditional logistics service providers. Based on this study, crowdshipping and last-mile companies were largely loss making, whereas logistics service providers were profitable. The first two groups invest heavily in growth, which explains the loss. All logistics service providers, half of the last-mile providers, and no crowdshipping companies set a carbon neutrality target. The biggest difference in environmental measures comes from the fact that in the crowdshipping business model deliveries are performed partly in conjunction with other travel, emphasizing job creation in society and freedom of work. In contrast, the last-mile and traditional logistics companies emphasized the responsibilities of the employer. For the scientific community, this study provides new insights into the subject from the perspective of different business models. For management, this research provides insight into the views of other companies that can be utilized in future decision making. For example, if the legislation of crowdshipping becomes clearer, then traditional companies could consider using it in their own operations to overcome labor shortages. © 2022 by the authors.","business models; crowdshipping; crowdsourced delivery; e-commerce; last mile; last mile logistics; logistics service provider; responsibility; stakeholder; sustainability","business development; crowdsourcing; electronic commerce; environmental legislation; labor market; literature review; logistics; stakeholder; sustainability",{"$nulls":4},"Auramo foundation; Reijo Rautauoma foundation","This research was funded by Auramo foundation and Reijo Rautauoma foundation.","Wang X., Zhan L., Ruan J., Zhang J., How to Choose “Last Mile” Delivery Modes for E-Fulfillment, Math. Probl. Eng, 2014, (2014); Last Mile Logistics Worldwide; Gevaers E.R., Voorde V.D., Vanelslander T., Characteristics of Innovations in Last Mile Logistics—Using Best Practices, Case Studies and Making the Link with Green and Sustainable Logistics, Proceedings of the European Transport Conference, pp. 1-8; EU Economy and Society to Meet Climate Ambitions; Urban freight Research & Innovation Maps; Boysen N., Fedtke S., Schwerdfeger S., Last-mile delivery concepts: A survey from an operational research perspective, OR Spektrum, 43, pp. 1-58, (2020); Savelsbergh M., Van Woensel T., 50th Anniversary invited article—City logistics: Challenges and opportunities, Transp. Sci, 50, pp. 579-590, (2016); Kiba-Janiak M., Marcinkowski J., Jagoda A., Skowronska A., Sustainable last mile delivery on e-commerce market in cities from the perspective of various stakeholders. Literature review, Sustain. 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Interact, 6, (2022); Mohlmann M., Zalmanson L., Hands on the Wheel: Navigating Algorithmic Management and Uber Drivers’ Autonomy, Proceedings of the ICIS 2017 Transforming Society with Digital Innovation Transform; Dablanc L., Morganti E., Arvidsson N., Woxenius J., Browne M., Saidi N., The rise of on-demand ‘Instant Deliveries’ in European cities, Supply Chain Forum Int. J, 18, pp. 203-217, (2017); Zarra A., Simonelli F., Lenaerts K., Luo M., Baiocco S., Ben S., Li W., Echikson W., Kilhoffer Z., Sustainability in the Age of Platforms, Supply Chain. Forum, 18, pp. 203-217, (2017); de Groen W.P., Maselli I., The Impact of the Collaborative Economy on the Labour Market, (2016); Moncef B., Dupuy M.M., Last-mile logistics in the sharing economy: Sustainability paradoxes, Int. J. Phys. Distrib. Logist. Manag, 51, pp. 508-527, (2021); Hauben H., Lenaerts K., Wayaert W., The Platform Economy and Precarious Work, (2020); Yin R.K., Case Study Research and Applications Design and Methods, (2018); Eisenhardt K.M., Building Theories from Case Study Research, Acad. Manag. Rev, 14, (1989); Yin R.K., Media Reviews, (2003); Saunders M., Lewis P., Thornhill A., Research Methods for Business Students, (2019); Kvale S., Interviews: An Introduction to Qualitative Research Interviewing, (1996); Evans D.S., Schmalensee R., Failure to Launch: Critical Mass in Platform Businesses, Rev. Netw. Econ, 9, pp. 1-10, (2010)","H. Kervola; Transport Research Centre Verne, Tampere University, Tampere, 33014, Finland; email: henri.kervola@jamk.fi",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85148290080"]
["Haouassi M.; Kergosien Y.; Mendoza J.E.; Rousseau L.-M.","Haouassi, Mustapha (57193716302); Kergosien, Yannick (57204260583); Mendoza, Jorge E. (55346932600); Rousseau, Louis-Martin (7005245914)","57193716302; 57204260583; 55346932600; 7005245914","The integrated orderline batching, batch scheduling, and picker routing problem with multiple pickers: the benefits of splitting customer orders",2022.0,"Flexible Services and Manufacturing Journal",34.0,3.0,null,614.0,645.0,31.0,7.0,"10.1007/s10696-021-09425-8","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85136837106&doi=10.1007%2fs10696-021-09425-8&partnerID=40&md5=ccdb5ed89751bb7e62075dcc1bba9d74","Université de Tours, LIFAT EA 6300, CNRS, ROOT ERL CNRS 7002, 64 Avenue Jean Portalis, Tours, 37200, France; Ecole Polytechnique de Montréal, CIRRELT, 2900 Boulevard Edouard-Montpetit H3T 1J4, Montréal, Canada; HEC Montréal, CIRRELT, 3000 Chemin de la côte Sainte Catherine H3T 2A7, Montréal, Canada","Haouassi M., Université de Tours, LIFAT EA 6300, CNRS, ROOT ERL CNRS 7002, 64 Avenue Jean Portalis, Tours, 37200, France, Ecole Polytechnique de Montréal, CIRRELT, 2900 Boulevard Edouard-Montpetit H3T 1J4, Montréal, Canada; Kergosien Y., Université de Tours, LIFAT EA 6300, CNRS, ROOT ERL CNRS 7002, 64 Avenue Jean Portalis, Tours, 37200, France; Mendoza J.E., HEC Montréal, CIRRELT, 3000 Chemin de la côte Sainte Catherine H3T 2A7, Montréal, Canada; Rousseau L.-M., Ecole Polytechnique de Montréal, CIRRELT, 2900 Boulevard Edouard-Montpetit H3T 1J4, Montréal, Canada","Fast delivery is one of the most popular services in e-commerce retail. It consists in shipping the items ordered on-line in short times. Customer orders in this segment come with deadlines, and respecting this latter is pivotal to ensure a high service quality. The most time-consuming process in the warehouse is order picking. It consists in regrouping orders into batches, assigning those batches to order pickers, sequencing the batches assigned to each order picker such that the orders deadlines are satisfied, and the picking time is minimized. To speed up the order picking operations, e-commerce warehouses implement new logistical practices. In this paper, we study the impact of splitting the orders (assigning the orderlines of an order to multiple pickers). We thus generalize the integrated orders batching, batch scheduling, and picker routing problem by allowing the orders splitting and propose a route first-schedule second heuristic to solve the problem. In the routing phase, the heuristic divides the orders into clusters and constructs the picking tours that retrieve the orderlines of each cluster using a split-based procedure. In the scheduling phase, the constructed tours are assigned to pickers such that the orders deadlines are satisfied using a constraint programming formulation. On a publicly available benchmark, we compare our results against a state-of-the-art iterated local search algorithm designed for the non-splitting version of the problem. Results show that splitting the customer orders using our algorithm reduces the picking time by 30% on average with a maximum reduction of 60%. © 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.","Hard due-dates; Order picking; Route first-schedule second heuristic; Splitting customer orders","Computer programming; Constraint theory; Electronic commerce; Scheduling; Warehouses; Batch-scheduling; Constraint programming; Customer orders; Iterated local search; Order pickers; Picker routing; Service Quality; State of the art; Sales",{"$nulls":4},"Region Centre-val-de-Loire in France; Universiteit Gent; Institut de Valorisation des Données, IVADO","Funding text 1: The authors would like to thank Pr. Birger Raa from Ghent University for sharing the code of the combined heuristic.; Funding text 2: This research was partially funded by Region Centre-val-de-Loire in France and Institut de Valorisation des Données (IVADO) in Canada. ","Constraint-based scheduling: Applying constraint programming to scheduling problems, vol, 39, (2012); Boysen N., Fedtke S., Weidinger F., Optimizing automated sorting in warehouses: the minimum order spread sequencing problem, Eur J Oper Res, 270, 1, pp. 386-400, (2018); Boysen N., de Koster R., Weidinger F., Warehousing in the e-commerce era: a survey, Eur J Oper Res, 277, 2, pp. 396-411, (2019); Boysen N., Stephan K., Weidinger F., Manual order consolidation with put walls: the batched order bin sequencing problem, EURO J Transp Logist, 8, 2, pp. 169-193, (2019); Briant O., Cambazard H., Cattaruzza D., Catusse N., Ladier A.L., Ogier M., An efficient and general approach for the joint order batching and picker routing problem, Eur J Oper Res, 285, 2, pp. 497-512, (2020); Bue M., Cattaruzza D., Ogier M., Semet F., 2019) a Two-Phase Approach for an Integrated Order Batching and Picker Routing Problem., pp. 3-18, (2018); Cambazard H., Catusse N., Fixed-parameter algorithms for rectilinear Steiner tree and rectilinear traveling salesman problem in the plane, Eur J Oper Res, 270, 2, pp. 419-429, (2018); Clarke G., Wright J.W., Scheduling of vehicles from a central depot to a number of delivery points, Oper Res, 12, 4, pp. 568-581, (1964); De Koster R., Le-Duc T., Roodbergen K.J., Design and control of warehouse order picking: a literature review, Eur J Oper Res, 182, 2, pp. 481-501, (2007); Desrochers M., Laporte G., Improvements and extensions to the Miller–Tucker–Zemlin subtour elimination constraints, Oper Res Lett, 10, 1, pp. 27-36, (1991); Drury J., Towards more efficient order picking, IMM Monograph, (1988); Gademann N., Velde S., Order batching to minimize total travel time in a parallel-aisle warehouse, IIE Trans, 37, 1, pp. 63-75, (2005); Ham A.M., Cakici E., Flexible job shop scheduling problem with parallel batch processing machines: MIP and CP approaches, Comput Ind Eng, 102, pp. 160-165, (2016); Henn S., Order batching and sequencing for the minimization of the total tardiness in picker-to-part warehouses, Flexible Serv Manuf J, 27, 1, pp. 86-114, (2015); Henn S., Schmid V., Metaheuristics for order batching and sequencing in manual order picking systems, Comput Ind Eng, 66, 2, pp. 338-351, (2013); Henn S., Koch S., Wascher G., Order batching in order picking warehouses: A survey of solution approaches, Warehousing in the Global Supply Chain, pp. 105-137, (2012); Hooker J.N., van Hoeve W.J., Constraint programming and operations research, Constraints, 23, 2, pp. 172-195, (2018); Kulak O., Sahin Y., Taner M.E., Joint order batching and picker routing in single and multiple-cross-aisle warehouses using cluster-based Tabu search algorithms, Flexible Serv Manuf J, 24, 1, pp. 52-80, (2012); Laborie P., An update on the comparison of mip, cp and hybrid approaches for mixed resource allocation and scheduling, International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research, pp. 403-411, (2018); Laborie P., Rogerie J., Shaw P., Vilim P., IBM ilog CP optimizer for scheduling, Constraints, 23, 2, pp. 210-250, (2018); Le-Duc T., De Koster R.B., Travel distance estimation and storage zone optimization in a 2-block class-based storage strategy warehouse, Int J Prod Res, 43, 17, pp. 3561-3581, (2005); Loffler M., Boysen N., Schneider M., Picker routing in agv-assisted order picking systems, (2018); Masae M., Glock C.H., Vichitkunakorn P., Optimal order picker routing in a conventional warehouse with two blocks and arbitrary starting and ending points of a tour, Int J Prod Res, 58, 17, pp. 5337-5358, (2020); Masae M., Glock C.H., Vichitkunakorn P., Optimal order picker routing in the chevron warehouse, IISE Trans, 52, 6, pp. 665-687, (2020); Ozturkoglu O., Hoser D., A discrete cross aisle design model for order-picking warehouses, Eur J Oper Res, 275, 2, pp. 411-430, (2019); Ozturkoglu O., Gue K.R., Meller R.D., Optimal unit-load warehouse designs for single-command operations, IIE Trans, 44, 6, pp. 459-475, (2012); Pansart L., Catusse N., Cambazard H., Exact algorithms for the order picking problem, Comput Oper Res, 100, pp. 117-127, (2018); Prins C., A simple and effective evolutionary algorithm for the vehicle routing problem, Comput Oper Res, 31, 12, pp. 1985-2002, (2004); Ratliff H.D., Rosenthal A.S., Order-picking in a rectangular warehouse: a solvable case of the traveling salesman problem, Oper Res, 31, 3, pp. 507-521, (1983); Roodbergen K.J., Layout and routing methods for warehouses, (2001); Roodbergen K.J., De Koster R., Routing order pickers in a warehouse with a middle aisle, Eur J Oper Res, 133, 1, pp. 32-43, (2001); Scholz A., Wascher G., Order batching and picker routing in manual order picking systems: the benefits of integrated routing, CEJOR, 25, 2, pp. 491-520, (2017); Scholz A., Schubert D., Wascher G., Order picking with multiple pickers and due dates-simultaneous solution of order batching, batch assignment and sequencing, and picker routing problems, Eur J Oper Res, 263, 2, pp. 461-478, (2017); Retail E-Commerce Revenue in Canada from 2017 to 2023, (2019); Theys C., Braysy O., Dullaert W., Raa B., Using a tsp heuristic for routing order pickers in warehouses, Eur J Oper Res, 200, 3, pp. 755-763, (2010); Tompkins J.A., White J.A., Bozer Y.A., Tanchoco J.M.A., Facilities Planning, (2010); Tsai C.Y., Liou J.J.H., Huang T.M., Using a multiple-ga method to solve the batch picking problem: considering travel distance and order due time, Int J Prod Res, 46, 22, pp. 6533-6555, (2008); Valle C.A., Beasley J.E., da Cunha A.S., Optimally solving the joint order batching and picker routing problem, Eur J Oper Res, 262, 3, pp. 817-834, (2017); Van Gils T., Ramaekers K., Caris A., de Koster R.B., Designing efficient order picking systems by combining planning problems: state-of-the-art classification and review, Eur J Oper Res, 267, 1, pp. 1-15, (2018); Van Gils T., Caris A., Ramaekers K., Braekers K., Formulating and solving the integrated batching, routing, and picker scheduling problem in a real-life spare parts warehouse, Eur J Oper Res, 277, 3, pp. 814-830, (2019); Wascher G., Order picking: A survey of planning problems and methods, Supply Chain Management and Reverse Logistics, pp. 323-347, (2004); Weidinger F., Picker routing in rectangular mixed shelves warehouses, Comput Oper Res, 95, pp. 139-150, (2018)","J.E. Mendoza; HEC Montréal, CIRRELT, Montréal, 3000 Chemin de la côte Sainte Catherine H3T 2A7, Canada; email: jorge.mendoza@hec.ca",null,"Springer",{"$nulls":5},1.9366582E7,null,null,null,"English","Flexible Serv Manuf J","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85136837106"]
["Liu C.; Ma T.","Liu, Chao (57222132825); Ma, Tengfei (57219568779)","57222132825; 57219568779","Green logistics management and supply chain system construction based on internet of things technology",2022.0,"Sustainable Computing: Informatics and Systems",35.0,null,100773.0,null,null,null,23.0,"10.1016/j.suscom.2022.100773","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85133292582&doi=10.1016%2fj.suscom.2022.100773&partnerID=40&md5=fff830d1494aa01400b17a7dc5867c55","Faculty of Management and Economics, Kunming University of Science and Technology, Yunnan, Kunming, 650093, China; School of Marxism, Yunnan University, Yunnan, Kunming, 650500, China","Liu C., Faculty of Management and Economics, Kunming University of Science and Technology, Yunnan, Kunming, 650093, China; Ma T., School of Marxism, Yunnan University, Yunnan, Kunming, 650500, China","The Internet of Things technology is an important part of modern intelligent systems. It plays an important role in the development of information, and it is also indispensable in industry, trade, manufacturing and daily life. The explosive development of e-commerce in recent years has contributed to the rapid growth of the logistics industry. However, due to the substantial increase in online orders, serious environmental pollution has also appeared in the logistics industry, and the society is paying more and more attention to it. The reliability assessment of the supply chain and the analysis of the green logistics innovation strategy have improved the environmental pollution of the logistics industry and reduced the vehicle emissions in transportation by 26.9%. In addition, the data system for green packaging and green warehousing has been updated, and the accuracy of information circulation has increased by 45.97%. Effectively reduce costs in all aspects of the logistics industry, and the first to develop green logistics will undoubtedly take the initiative in the development of the logistics industry. Green logistics is considered to be one of the trends in the future development of logistics industry. © 2022","Environmental health; Green logistics; Internet of Things; Supply chain","Environmental technology; Intelligent systems; Pollution; Reliability analysis; Supply chains; Daily lives; Environmental health; Environmental pollutions; Green logistics; Internet of things technologies; Logistic management; Logistics industry; Logistics supply; Supply chain systems; System construction; Internet of things",{"$nulls":6},"Tu M., Ming K.L., Yang M.F., IoT-based production logistics and supply chain system – Part 1, Ind. Manag. Data Syst., 118, 1, pp. 65-95, (2018); Khan S., Zhang Y., Anees M., Et al., Green supply chain management, economic growth and environment: a GMM based evidence, J. Clean. Prod., 185, JUN.1, pp. 588-599, (2018); Fazili M., Venkatadri U., Cyrus P., Et al., Physical Internet, conventional and hybrid logistic systems: a routing optimisation-based comparison using the Eastern Canada road network case study, Int. J. Prod. Res., 55, 9-10, pp. 2703-2730, (2017); Liu J., Yuan C., Hafeez M., Et al., The relationship between environment and logistics performance: evidence from Asian countries, J. Clean. Prod., 204, PT.1–1178, pp. 282-291, (2018); Zhao S., Zhu Q., Remanufacturing supply chain coordination under the stochastic remanufacturability rate and the random demand, Ann. Oper. Res., 257, 1-2, pp. 661-695, (2017); Gang W., Gunasekaran A., Modeling and analysis of sustainable supply chain dynamics, Ann. Oper. Res., 250, 2, pp. 521-536, (2017); Ulku M.A., Hsuan J., Towards sustainable consumption and production: competitive pricing of modular products for green consumers, J. Clean. Prod., 142, pt.4, pp. 4230-4242, (2017); Zheng C., Cao W., Hybrid high-order semantic graph representation learning for recommendations, Disco Internet Things, 1, (2021); Laari S., Toyli J., Ojala L., Supply chain perspective on competitive strategies and green supply chain management strategies, J. Clean. Prod., 141, JAN.10, pp. 1303-1315, (2017); Malakouti M., Rezaei S., Shahijan M.K., Agile supply chain management (ASCM): a management decision-making approach, Asia Pac. J. Mark. Logist., 1, 1, pp. 171-182, (2017); Huang Y.S., Fang C.C., Lin Y.A., Inventory management in supply chains with consideration of logistics, green investment and different carbon emissions policies, Comput. Ind. Eng., 139, Jan., (2020); Gao J., Xiao Z., Et al., (2018); Zhou D., Yu Y., Wang Q., Et al., Effects of a generalized dual-credit system on green technology investments and pricing decisions in a supply chain, J. Environ. Manag., 247, Oct.1, pp. 269-280, (2019); Zhao-Hui W.U., Research on the application of internet of things technology to digital museum construction, Acta Geosci. Sin., 38, 2, pp. 293-298, (2017); Dong L., Mingyue R., Guoying M., Application of internet of things technology on predictive maintenance system of coal equipment, Procedia Eng., 174, Complete, pp. 885-889, (2017); Ke G., Jiang Q., Application of internet of things technology in the construction of wisdommuseum, Concurr. Comput. Pract. Exp., 31, 10, (2019); Li X., Jianmin H., Hou B., Zhang P., pp. 907-922; Tsai S.-B., Wei Y.-M., Chen K.-Y., Et al., Evaluating green suppliers from green environmental perspective, Environ. Plan. B-Plan. Des., 43, 5, pp. 941-959, (2016); Shanshan Z., Shancang, Et al., Blockchain enabled industrial internet of things technology, IEEE Trans. Comput. Soc. Syst., 6, 6, pp. 1442-1453, (2019); Adi E., Anwar A., Baig Z., Et al., Machine learning and data analytics for the IoT, Neural Comput. Appl., 32, pp. 16205-16233, (2020); Reda H.T., Mahmood A., Diro A., Et al., Firefly-inspired stochastic resonance for spectrum sensing in CR-based IoT communications, Neural Comput. Applic, 32, pp. 16011-16023, (2020); Tu M., An exploratory study of Internet of Things (IoT) adoption intention in logistics and supply chain management A mixed research approach, Int. J. Logist. Manag., 29, 1, pp. 131-151, (2018); Zelbst P.J., Green K.W., Sower V.E., Et al., The impact of RFID, IIoT, and blockchain technologies on supply chain transparency, J. Manuf. Technol. Manag., 31, 3, pp. 441-457, (2019)","T. Ma; School of Marxism, Yunnan University, Kunming, Yunnan, 650500, China; email: better@ynu.edu.cn",null,"Elsevier Inc.",{"$nulls":5},2.2105379E7,null,null,null,"English","Sustainable Computing: Informatics and Systems","Article","Final",null,"Scopus","2-s2.0-85133292582"]
["Correia I.; Melo T.","Correia, Isabel (55932134300); Melo, Teresa (57914496000)","55932134300; 57914496000","Distribution network redesign under flexible conditions for short-term location planning",2022.0,"Computers and Industrial Engineering",174.0,null,108747.0,null,null,null,2.0,"10.1016/j.cie.2022.108747","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85141752353&doi=10.1016%2fj.cie.2022.108747&partnerID=40&md5=fdb3af38d6557430fddad994bab5536a","Center for Mathematics and Applications (NovaMath), FCT NOVA and Department of Mathematics, FCT NOVA, Universidade NOVA de Lisboa, Caparica, P 2829-516, Portugal; Business School, Saarland University of Applied Sciences, Saarbrücken, 66123, Germany","Correia I., Center for Mathematics and Applications (NovaMath), FCT NOVA and Department of Mathematics, FCT NOVA, Universidade NOVA de Lisboa, Caparica, P 2829-516, Portugal; Melo T., Business School, Saarland University of Applied Sciences, Saarbrücken, 66123, Germany","E-commerce has experienced a remarkable growth in recent years. This trend is gradually driving retailers to shift from typical warehouse rental contracts with rigid conditions and long-term commitments to flexible alternatives that provide storage space on demand. This strategy gives retailers the ability to respond dynamically to variations in demand, thereby improving customer service. In this paper, we address this trend by considering a two-echelon, multi-commodity distribution network operated by a retailer and whose configuration can be changed over a multi-period planning horizon. Location decisions concern the intermediate facilities and are framed by flexible and scalable conditions. Accordingly, the retailer needs to decide which company-owned facilities should be retained, and where, when and for how long new facilities should be leased from a set of potential sites with given capacities. In this setting, a facility can be leased at the same location for several non-consecutive periods. In addition to location decisions, also procurement, inventory, and distribution decisions need to be made to satisfy customer demand at minimum total cost. We develop a mixed-integer linear programming formulation for this problem and propose various families of additional inequalities that prove to be very useful to find high-quality solutions. To measure the impact of the new business model, we also consider alternative approaches with limited flexibility and scalability that are frequently encountered in practice. Our computational study gives useful insights on the trade-offs achieved by each of the different approaches with respect to total cost, network redesign decisions, and various logistics functions. © 2022 Elsevier Ltd","Distribution network redesign; Mixed-integer linear programming; Short-term storage space rental; Valid inequalities","Costs; Customer satisfaction; Economic and social effects; Location; Sales; Condition; Distribution network redesign; Integer Linear Programming; Location decisions; Mixed integer linear; Mixed-integer linear programming; Short term storage; Short-term storage space rental; Storage spaces; Valid inequality; Integer programming",{"$nulls":4},"Fundação para a Ciência e a Tecnologia, FCT, (UIDB/00297/2020, UIDP/00297/2020)","Acknowledgments: This work was partially funded by FCT - Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) , I.P., under the scope of the projects UIDB/00297/2020 and UIDP/00297/2020 (Center for Mathematics and Applications). This support is gratefully acknowledged. ","Allman A., Zhang Q., Dynamic location of modular manufacturing facilities with relocation of individual modules, European Journal of Operational Research, 286, pp. 494-507, (2020); Alumur S.A., Nickel S., Saldanha-da-Gama F., Secerdin Y., Multi-period hub network design problems with modular capacities, Annals of Operations Research, 246, pp. 289-312, (2016); Antunes A., Peeters D., On solving complex multi-period location models using simulated annealing, European Journal of Operational Research, 130, pp. 190-201, (2001); Arabani A.B., Farahani R.Z., Facility location dynamics: An overview of classifications and applications, Computers & Industrial Engineering, 62, pp. 408-420, (2012); Badri H., Bashiri M., Hejazi T.H., Integrated strategic and tactical planning in a supply chain network design with a heuristic solution method, Computers & Operations Research, 40, pp. 1143-1154, (2013); Bashiri M., Badri H., Talebi J., A new approach to tactical and strategic planning in production-distribution networks, Applied Mathematical Modelling, 36, pp. 1703-1717, (2012); Becker T., Lier S., Werners B., Value of modular production concepts in future chemical industry production networks, European Journal of Operational Research, 276, pp. 957-970, (2019); Ceschia S., Gansterer M., Mancini S., Meneghetti A., The on-demand warehousing problem, International Journal of Production Research, (2022); Cordeau J.F., Klibi W., Nickel S., Logistics network design, Network design with applications to transportation and logistics, pp. 599-625, (2021); Correia I., Melo T., Multi-period capacitated facility location under delayed demand satisfaction, European Journal of Operational Research, 255, pp. 729-746, (2016); Correia I., Melo T., A multi-period facility location problem with modular capacity adjustments and flexible demand fulfillment, Computers & Industrial Engineering, 255, pp. 729-746, (2017); Correia I., Melo T., Saldanha-da-Gama F., Comparing classical performance measures for a multi-period, two-echelon supply chain network design problem with sizing decisions, Computers & Industrial Engineering, 64, pp. 366-380, (2013); Cortinhal M.J., Lopes M.J., Melo M.T., Dynamic design and re-design of multi-echelon, multi-product logistics networks with outsourcing opportunities: A computational study, Computers & Industrial Engineering, 90, pp. 118-131, (2015); Darvish M., Archetti C., Coelho L.C., Speranza M.G., Flexible two-echelon location routing problem, European Journal of Operational Research, 277, pp. 1124-1136, (2019); Darvish M., Coelho L.C., Sequential versus integrated optimization: Production, location, inventory control, and distribution, European Journal of Operational Research, 268, pp. 203-2143, (2018); Dias J., Captivo M.E., Climaco J., Efficient primal-dual heuristic for a dynamic location problem, Computers & Operations Research, 34, pp. 1800-1823, (2007); Emirhuseyinoglu G., Ekici A., Dynamic facility location with supplier selection under quantity discount, Computers & Industrial Engineering, 134, pp. 64-74, (2019); Gourdin E., Klopfenstein O., Multi-period capacitated location with modular equipments, Computers & Operations Research, 35, pp. 661-682, (2008); Hinojosa Y., Kalcsics J., Nickel S., Puerto J., Velten S., Dynamic supply chain with inventory, Computers & Operations Research, 35, pp. 371-391, (2008); Jacobsen S.K., Multiperiod capacitated location models, Discrete location theory, (1990); Jena S.D., Cordeau J.-F., Gendron B., Dynamic facility location with generalized modular capacities, Transportation Science, 49, pp. 484-499, (2015); Jena S.D., Cordeau J.-F., Gendron B., Solving a dynamic facility location problem with partial closing and reopening, Computers & Operations Research, 67, pp. 143-154, (2016); Kembro J.H., Norrman A., Eriksson E., Adapting warehouse operations and design to omni-channel logistics - a literature review and research agenda, International Journal of Physical Distribution and Logistics Management, 48, pp. 890-912, (2018); Kumar S., Narkhede B.E., Jain K., Revisiting the warehouse research through an evolutionary lens: a review from 1990 to 2019, International Journal of Production Research, 59, pp. 3470-3492, (2021); Leuschner R., Carter C.R., Goldsby T.J., Rogers Z.S., Third-party logistics: A meta-analytic review and investigation of its impact on performance, Journal of Supply Chain Management, 50, pp. 21-43, (2014); Marasco A., Third-party logistics: A literature review, International Journal of Production Economics, 113, pp. 127-147, (2008); Marufuzzaman M., Gedik R., Roni M.S., A Benders based rolling horizon algorithm for a dynamic facility location problem, Computers & Industrial Engineering, 98, pp. 462-469, (2016); Melo M.T., Nickel S., Saldanha da Gama F., Dynamic multi-commodity capacitated facility location: a mathematical modeling framework for strategic supply chain planning, Computers & Operations Research, 33, pp. 181-208, (2006); Melo M.T., Nickel S., Saldanha-da-Gama F., Facility location and supply chain management: a review, European Journal of Operational Research, 196, pp. 401-412, (2009); Nickel S., Saldanha da Gama F., Multi-period facility location, Location science, pp. 303-326, (2019); Parodos L., Tsolakis O., Tsoukos G., Xenou E., Ayfantopoulou G., Business model analysis of smart city logistics solutions using the business model canvas: The case of an on-demand warehousing E-marketplace, Future Transport, 2, pp. 467-481, (2022); Sauvey C., Melo T., Correia I., Heuristics for a multi-period facility location problem with delayed demand satisfaction, Computers & Industrial Engineering, 139, (2020); Shulman A., An algorithm for solving dynamic capacitated plant location problems with discrete expansion sizes, Operations Research, 39, pp. 423-436, (1991); Statista, E-commerce worldwide - statistics & facts, (2022); Statista, Retail e-commerce sales worldwide from 2014 to 2026, (2022); Thanh P.N., Bostel N., Peton O., A dynamic model for facility location in the design of complex supply chains, International Journal of Production Economics, 113, pp. 678-693, (2008); Torres-Soto J.E., Ulster H., Dynamic-demand capacitated facility location problems with and without relocation, International Journal of Production Research, 49, pp. 3979-4005, (2011); Van Roy T.J., Erlenkotter D., Dual-based procedure for dynamic facility location, Management Science, 28, pp. 1091-1105, (1982); Wilhelm W., Han X., Lee C., Computational comparison of two formulations for dynamic supply chain reconfiguration with capacity expansion and contraction, Computers & Operations Research, 40, pp. 2340-2356, (2013); Wolsey L.A., Integer programming, Wiley-interscience series in discrete mathematics and optimization, (1998); Zhu W., Ng S.C.H., Wang Z., Zhao X., The role of outsourcing management process in improving the effectiveness of logistics outsourcing, International Journal of Production Economics, 188, pp. 29-40, (2017)","T. Melo; Business School, Saarland University of Applied Sciences, Saarbrücken, 66123, Germany; email: teresa.melo@htwsaar.de",null,"Elsevier Ltd",{"$nulls":5},3608352.0,null,"CINDD",null,"English","Comput Ind Eng","Article","Final",null,"Scopus","2-s2.0-85141752353"]
["Bae K.-H.; Mustafee N.; Lazarova-Molnar S.; Zheng L.","Bae, Ki-Hwan (56414099300); Mustafee, Navonil (57666502800); Lazarova-Molnar, Sanja (23393330900); Zheng, Long (57188758507)","56414099300; 57666502800; 23393330900; 57188758507","Hybrid modeling of collaborative freight transportation planning using agent-based simulation, auction-based mechanisms, and optimization",2022.0,"Simulation",98.0,9.0,null,753.0,771.0,18.0,13.0,"10.1177/00375497221075614","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85125059886&doi=10.1177%2f00375497221075614&partnerID=40&md5=3b9f55ae350fa7d5b6a2b0b8576aaa5b","Industrial Engineering, Colorado Christian University, United States; Centre for Simulation, Analytics and Modelling, (CSAM) University of Business School, Exeter, United Kingdom; University of Southern Denmark, Denmark; University of Louisville, United States","Bae K.-H., Industrial Engineering, Colorado Christian University, United States; Mustafee N., Centre for Simulation, Analytics and Modelling, (CSAM) University of Business School, Exeter, United Kingdom; Lazarova-Molnar S., University of Southern Denmark, Denmark; Zheng L., University of Louisville, United States","The sharing economy is a peer-to-peer economic model characterized by people and organizations sharing resources. With the emergence of such economies, an increasing number of logistics providers seek to collaborate and derive benefit from the resultant economic efficiencies, sustainable operations, and network resilience. This study investigates the potential for collaborative planning enabled through a Physical Internet-enabled logistics system in an urban area that acts as a freight transport hub with several e-commerce warehouses. Our collaborative freight transportation planning approach is realized through a three-layer structured hybrid model that includes agent-based simulation, auction mechanism, and optimization. A multi-agent model simulates a complex transportation network, an auction mechanism facilitates allocating transport services to freight requests, and a simulation–optimization technique is used to analyze strategic transportation planning under different objectives. Furthermore, sensitivity analyses and Pareto efficiency experiments are conducted to draw insights regarding the effect of parameter settings and multi-objectives. The computational results demonstrate the efficacy of our developed model and solution approach, tested on a real urban freight transportation network in a major US city. © The Author(s) 2022.","agent-based simulation; auction-based mechanism; Hybrid modeling; multi-objective optimization; physical Internet","Economics; Efficiency; Freight transportation; Multi agent systems; Multiobjective optimization; Sensitivity analysis; Urban planning; Urban transportation; Agent based simulation; Auction-based mechanism; Auctions mechanisms; Economic models; Hybrid model; Multi-objectives optimization; Optimisations; Peer to peer; Physical internet; Transportation planning; Pareto principle",{"$nulls":6},"US census bureau news—quarterly retail e-commerce sales, 3rd quarter (CB19-170), Economic Indicators Division, (2019); Anderson W.P., Leinbach T.R., E-commerce, logistics and the future of globalized freight, Globalized freight transport: intermodality, e-commerce, logistics and sustainability, pp. 167-187, (2007); Belien J., Boute R., Creemers S., Et al., Collaborative shipping: logistics in the sharing economy, ORMS Today, (2017); Chapman R.L., Soosay C., Kandampully J., Innovation in logistic services and the new business model: a conceptual framework, Manag Serv Qual, 12, pp. 358-371, (2002); Srinivasan A., Leveque P., Digitising freight—one truck at a time: a Frost & Sullivan perspective on the emerging digital freight brokerage systems, (2016); Benjelloun A., Crainic T.G., Bigras Y., Towards a taxonomy of city logistics projects, Procd Soc Behv, 2, pp. 6217-6228, (2010); Dablanc L., Goods transport in large European cities: difficult to organize, difficult to modernize, Transp Res A: Pol, 41, pp. 280-285, (2007); Montreuil B., Meller R.D., Ballot E., Physical Internet foundations, Service orientation in holonic and multi agent manufacturing and robotics, pp. 151-166, (2013); Ferrell W., Ellis K., Kaminsky P., Et al., Horizontal collaboration: opportunities for improved logistics planning, Int J Prod Res, 58, pp. 4267-4284, (2020); Tolk A., Harper A., Mustafee N., Hybrid models as transdisciplinary research enablers, Eur J Oper Res, 291, pp. 1075-1090, (2021); Pan S., Trentesaux D., Ballot E., Et al., Horizontal collaborative transport: survey of solutions and practical implementation issues, Int J Prod Res, 57, pp. 5340-5361, (2019); Montreuil B., Toward a Physical Internet: meeting the global logistics sustainability grand challenge, Logist Res, 3, pp. 71-87, (2011); Rajahonka M., Bask A., Yawar S.A., Et al., The Physical Internet as enabler of new business models enhancing greener transports and the circular economy, Sustainable and efficient transport, pp. 70-94, (2019); Sarraj R., Ballot E., Pan S., Et al., Interconnected logistic networks and protocols: simulation-based efficiency assessment, Int J Prod Res, 52, pp. 3185-3208, (2014); Hakimi D., Montreuil B., Labarthe O., Supply web: concept and technology, Proceedings of 7th annual international symposium on supply chain management, pp. 1-21, (2009); Oktaei P., Physical Internet enabled transit centers: business modeling and profitability assessment, (2015); Douma A., Schuur P.C., Van Der Heijden M.C., Applying revenue management to agent-based transportation planning, 169, (2006); Hakimi D., Montreuil B., Sarraj R., Et al., Simulating a Physical Internet enabled mobility web: the case of mass distribution in France, pp. 1-10; Meller R.D., Lin Y.H., Ellis K.P., The impact of standardized metric Physical Internet containers on the shipping volume of manufacturers, IFAC P Ser, 45, pp. 364-371, (2012); Cruijssen F., Cools M., Dullaert W., Horizontal cooperation in logistics: opportunities and impediments, Transport Res E: Log, 43, pp. 129-142, (2007); Krajewska M.A., Kopfer H., Laporte G., Et al., horizontal cooperation among freight carriers: request allocation and profit sharing, J Oper Res Soc, 59, pp. 1483-1491, (2008); Fazili M., Venkatadri U., Cyrus P., Et al., Physical Internet, conventional, and hybrid logistics systems: a routing optimisation-based comparison using the eastern Canada road network case study, Int J Prod Res, 55, pp. 2703-2730, (2017); Gansterer M., Hartl R., Collaborative vehicle planning: a survey, Eur J Oper Res, 268, pp. 1-12, (2018); Mustafee N., Powell J.H., From hybrid simulation to hybrid systems modelling, pp. 1430-1439; Qiao B., Pan S., Ballot E., Dynamic pricing model for less-than-truckload carriers in the Physical Internet, J Intell Manuf, 30, pp. 2631-2643, (2019); Pan S., Xu X., Ballot E., Auction based transport services allocation in Physical Internet: a simulation framework, pp. 1-13; Wang X., Kopfer H., Collaborative transportation planning of less-than-truckload freight: a route-based request exchange mechanism, OR Spectrum, 36, pp. 357-380, (2014); Xu X., Pan S., Ballot E., Game theoretic contribution to horizontal cooperation in logistics, pp. 1-10; Berger S., Bierwirth C., Solutions to the request reassignment problem in collaborative carrier networks, Transport Res E: Log, 46, pp. 627-638, (2010); Chang Y., Makatsoris H., Supply chain modelling using simulation, Int J Simul Model, 2, pp. 24-30, (2001); Axlerod R., Advancing the art of simulation in the social sciences, Simulating social phenomena, pp. 21-40, (1997); Macal C.M., North M.J., Tutorial on agent-based modelling and simulation, J Simul, 4, pp. 151-162, (2010); Carson Y., Maria A., Simulation optimization: methods and applications, pp. 118-126; April J., Glover F., Kelly J., Portfolio optimization for capital investment projects, pp. 1546-1554; Better M., Glover F., Kochenberger G., Et al., Simulation optimization: applications in risk management, Int J Inf Tech Decis, 7, pp. 571-587, (2008); Banks J., Carson J.S., Nelson B.L., Et al., Discrete event systems simulation, (2000); Swisher J.R., Jacobson S.H., Hyden P.D., Et al., A survey of simulation optimization techniques and procedures, pp. 119-128; Xiao H., Lee L.H., Morrice D., Et al., Ranking and selection for terminating simulation under sequential sampling, IISE Trans, 53, pp. 735-750, (2021); Kou G., Xiao H., Gao M., Et al., Optimal computing budget allocation for the vector evaluated genetic algorithm in multi-objective simulation optimization, Automatica, 129, (2021); Brailsford S., Eldabi T., Kunc M., Et al., Hybrid simulation modelling in operational research: a state-of-the-art review, Eur J Oper Res, 278, pp. 721-737, (2019); Powell J.H., Mustafee N., Widening requirements capture with soft methods: an investigation of hybrid M&S studies in healthcare, J Oper Res Soc, 68, pp. 1211-1222, (2017); Davidsson P., Henesey L., Ramstedt L., Et al., An analysis of agent-based approaches to transport logistics, Transport Res C, 13, pp. 255-271, (2005); Serrano-Hernandez A., Faulin J., Hirsch P., Et al., Agent-based simulation for horizontal cooperation in logistics and transportation: from the individual to the grand coalition, Simul Model Pract Th, 85, pp. 47-59, (2018); Mustafee N., Bischoff E.E., Analysing trade-offs in container loading: combining load plan construction heuristics with agent-based simulation, Int Trans Oper Res, 20, pp. 471-491, (2013); Gesing B., Sharing economy logistics, Technical report, DHL Customer Solutions & Innovation, Troisdorf, (2017); Barichard V., Ehrgott M., Gandibleux X., Et al., Multiobjective programming and goal programming: theoretical results and practical applications, (2009); De Farias L.R.C., Braga P.H.M., Bassani H.F., Et al., MOEA/D with uniformly randomly adaptive weights, pp. 641-648; Drakaki M., Tzionas P., A Colored Petri Net-based modeling method for supply chain inventory management, Simulation, (2021); Sencer A., Karaismailoglu A., A simulation and analytic hierarchy process based decision support system for air cargo warehouse capacity design, Simulation, (2021); Sadeghi M., Bagheri M., Pishvaee M.S., Evaluation of rail terminals in container ports using simulation: a case study, Simulation, 97, pp. 809-820, (2021); De La Torre R., Corlu C., Faulin J., Et al., Simulation, optimization, and machine learning in sustainable transportation systems: models and applications, Sustainability, 13, (2021)","K.-H. Bae; Industrial Engineering, Colorado Christian University, United States; email: kbae04@vt.edu",null,"SAGE Publications Ltd",{"$nulls":5},375497.0,null,"SIMUA",null,"English","Simulation","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85125059886"]
["Kneese T.","Kneese, Tamara (56717755200)",5.67177552E10,"Keep it Oakland: e-commerce meets social justice",2022.0,"Media, Culture and Society",44.0,2.0,null,370.0,381.0,11.0,6.0,"10.1177/01634437211048342","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85116596798&doi=10.1177%2f01634437211048342&partnerID=40&md5=00003180d9385b77c354aadaa922931c","University of San Francisco, United States","Kneese T., University of San Francisco, United States","This article examines the labor involved with the upkeep of social media accounts for Oakland-based brick-and-mortar boutiques and their digital storefronts, particularly as businesses move their wares online during shelter-in-place amid the ongoing Covid-19 pandemic. Focusing on independent shops in Oakland, California, particularly those which are part of Oakland’s Indie Alliance – a coalition of independent small business owners – this article explores the role of shop workers in producing the authentic aesthetics of themselves and store accounts as a replacement for brick-and-mortar shops. How do small-scale shop owners and clerks make platforms, which were not designed with their needs in mind, work for them? How does sellers’ performance of the local interface with a global digital marketplace and platform infrastructures? In what ways do existing racial hierarchies and structural inequalities affect shop personnel’s experiences of platforms and apps meant to facilitate business transactions? I focus on the Oakland Indie Alliance’s Covid Recovery and Repair funds, which employ social media and crowdfunding platforms or payment apps to provide assistance to local businesses, particularly those which are BIPOC and/or immigrant owned, connecting commercial and social justice oriented goals. © The Author(s) 2021.","authenticity; e-commerce; hashtag activism; influencers; logistics; platforms; racial capitalism; retail; social justice",{"$nulls":7},"Oakland City Council task force aims to cut police Department’s budget ‘to invest in community, (2020); Adams M., Raisborough J., What can sociology say about fair trade?: Class, reflexivity and ethical consumption, Journal of Sociology, 42, 6, pp. 1165-1182, (2008); Benjamin R., Race After Technology, (2019); Dubal V., The drive to precarity: A political history of work, regulation, & labor advocacy in San Francisco’s taxi & uber economies, 38, Berkeley J. Emp. & Lab, (2017); Duffy B.E., Hund E., Having it all” on social media: Entrepreneurial femininity and self-branding among fashion bloggers, Social Media + Society, 1, 2, pp. 1-11, (2015); Duffy B.E., Pinch A., Sannon S., Et al., The nested precarities of creative labor on social media, Social Media + Society, pp. 1-12, (2021); Eubanks V., Automating Inequality, (2018); Gill T., Beauty Shop Politics: African American Women's Activism in the Beauty Industry, (2010); Hotchkiss S., What will become of Oakland’s black lives matter murals?, KQED, (2020); Jackson S., Bailey M., Welles B.F., #HashtagActivism: Networks of Race & Gender Justice, (2020); Kneese T., Palm M., Brick-and-Platform: Listing labor in teh digital vintage economy, Social Media + Society, pp. 1-11, (2020); McElroy E., Werth A., Deracinated dispossessions: On the foreclosures of ‘Gentrification’ in Oakland, CA, Antipode, 51, 3, pp. 878-898, (2019); McMillan Cottom T., Where platform capitalism and racial capitalism meet: The sociology of race and Racism in the Digital Society, Sociology of Race and Ethnicity, 6, 4, pp. 441-449, (2020); McNeill D., Governing a city of unicorns: Technology capital and the urban politics of San Francisco, Urban Geography, 37, 4, pp. 494-513, (2016); Maharawal M.M., Black lives matter, gentrification and the security state in the San Francisco Bay Area, Anthropological Theory, 17, 3, pp. 338-364, (2017); Marwick A., ‘They’re really profound women, they’re entrepreneurs’: Conceptions of authenticity in fashion blogging, (2013); Micheletti M., Political Virtual and Shopping: Individuals, Consumerism, and Collective Action, (2003); Nelson A., Body and Soul: The Black Panther Party and the Fight Against Medical Discrimination, (2013); Nieborg D.B., Duffy B.E., Poell T., Studying platforms and cultural production: Methods, institutions, and practices, Social Media + Society, pp. 1-7, (2020); Noble S., Algorithms of Oppression: How Search Engines Reinforce Racism, (2018); Popken B., Why are so many black-owned small businesses shut out of PPP loans?, NBC News, (2020); Sobande F., ‘We’re all in this together’: Commodified notions of connection, care and community in brand responses to COVID-19, European Journal of Cultural Studies, 23, 6, pp. 1033-1037, (2020); Ticona J., Mateescu A., Trusted strangers: Carework platforms’ cultural entrepreneurship in the on-demand economy, New Media & Society, 20, 11, pp. 4384-4404, (2018); Turner F., From Counterculture to Cyberculture, (2006); Vincent J., Blackout Tuesday posts are drowning out vital information shared under the BLM Hashtag, The Verge, (2020); Wood A.K., Friedline T., The deadly mix of individual responsibility and racial capitalism, Current Affairs, (2021)","T. Kneese; University of San Francisco, United States; email: tkneese@usfca.edu",null,"SAGE Publications Ltd",{"$nulls":5},1634437.0,null,null,null,"English","Media Cult. Soc.","Article","Final",null,"Scopus","2-s2.0-85116596798"]
["Koengkan M.; Fuinhas J.A.; Belucio M.; Alavijeh N.K.; Salehnia N.; Machado D.; Silva V.; Dehdar F.","Koengkan, Matheus (57194179002); Fuinhas, José Alberto (58552830000); Belucio, Matheus (57207845793); Alavijeh, Nooshin Karimi (57217071389); Salehnia, Nasrin (57197710569); Machado, Daniel (57450490600); Silva, Vinícius (57450673600); Dehdar, Fatemeh (57220310432)","57194179002; 58552830000; 57207845793; 57217071389; 57197710569; 57450490600; 57450673600; 57220310432","The Impact of Battery-Electric Vehicles on Energy Consumption: A Macroeconomic Evidence from 29 European Countries",2022.0,"World Electric Vehicle Journal",13.0,2.0,36.0,null,null,null,18.0,"10.3390/wevj13020036","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124526265&doi=10.3390%2fwevj13020036&partnerID=40&md5=d952e5e58b0240339268462b3a53e3fa","GOVCOPP, Department of Economics, Management, Industrial Engineering and Tourism (DEGEIT), University of Aveiro, Aveiro, 3810-193, Portugal; CeBER, Faculty of Economics, University of Coimbra, Coimbra, 3004-512, Portugal; Economy of Francesco (EoF) Academy, CEFAGE, University of Évora, Évora, 7000-809, Portugal; Department of Economics, Faculty of Economics and Administrative Sciences, Ferdowsi University of Mashhad, Mashhad, 1357, Iran; School of Earth and Environmental Science, Seoul National University, Seoul, 151-742, South Korea; Faculty of Economics, University of Coimbra, Coimbra, 3004-512, Portugal; GEPEA/EPUSP, University of São Paulo, São Paulo, 05508-010, Brazil; Faculty of Economics and Administration (FEP), University of Malaya, Kuala Lumpur, 50603, Malaysia","Koengkan M., GOVCOPP, Department of Economics, Management, Industrial Engineering and Tourism (DEGEIT), University of Aveiro, Aveiro, 3810-193, Portugal; Fuinhas J.A., CeBER, Faculty of Economics, University of Coimbra, Coimbra, 3004-512, Portugal; Belucio M., Economy of Francesco (EoF) Academy, CEFAGE, University of Évora, Évora, 7000-809, Portugal; Alavijeh N.K., Department of Economics, Faculty of Economics and Administrative Sciences, Ferdowsi University of Mashhad, Mashhad, 1357, Iran; Salehnia N., School of Earth and Environmental Science, Seoul National University, Seoul, 151-742, South Korea; Machado D., Faculty of Economics, University of Coimbra, Coimbra, 3004-512, Portugal; Silva V., GEPEA/EPUSP, University of São Paulo, São Paulo, 05508-010, Brazil; Dehdar F., Faculty of Economics, University of Coimbra, Coimbra, 3004-512, Portugal, Faculty of Economics and Administration (FEP), University of Malaya, Kuala Lumpur, 50603, Malaysia","The impact of battery electric vehicles (BEV) on energy consumption was researched modeling energy consumption against BEVs, Gross Domestic Product (GDP) and e-commerce, using annual data from 2010 to 2020, for twenty-nine European countries, with quantile regression and OLS with fixed effects econometric techniques. It was found that GDP and e-commerce impact energy consumption positively, and BEVs reduce energy consumption. These findings support that efficiency gains could not reduce energy consumption, and e-commerce, via extra packaging, further usage of computer processors, and cryptocurrencies to purchase products are hampering the environment. BEVs were revealed to be more energy-efficient than conventional cars. Thus, energy conservation policies to combat global warming and climate change arise. First, policies should offer an alternative packaging system to lower the negative environmental impacts of additional packaging for online purchases, stimulate smaller packages, free up additional space on the transport, enhance the delivery system efficiency, and promote alternative delivery systems. Second, offering subsidies for purchasing BEVs or tax rebates will increase the adoption rate of electric vehicles and combine this policy with the CO2 emissions’ regulations to stimulate the demand for BEVs. Finally, affordable charging points should be provided and customer awareness of the benefits of BEVs should be improved. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.","Battery-electric vehicles; E-commerce; Econometrics; Economics; Energy consumption; Europe; Macroeconomics; Quantile regression","Electronic commerce; Energy utilization; Environmental impact; Global warming; Packaging; Plug-in electric vehicles; Sales; Secondary batteries; Statistics; Battery-electric vehicles; E- commerces; Energy-consumption; Europe; European Countries; Fixed effects; Gross domestic products; Macroeconomic; Quantile regression; Reduce energy consumption; Energy efficiency",{"$nulls":4},"Fundação para a Ciência e a Tecnologia, FCT, (UIDB/05037/2020)","This work was financially supported by the research unit on Governance, Competitiveness and Public Policy UIDB/04058/2020 and UIDP/04058/2020, funded by national funds through FCT—Fundacção para a Ciência e a Tecnologia; and CeBER R&D unit funded by national funds through FCT—Fundação para a Ciência e a Tecnologia, I.P., project UIDB/05037/2020.","New Registrations of Electric Vehicles in EUROPE, (2021); 2050 Long-Term Strategy, (2020); Trade in Electric and Hybrid Electric Cars on the Rise, (2021); Key World Energy Statistics 2020, (2020); Vehicles and Fleet, (2021); Electric Vehicles and the Energy Sector—Impacts on Europe’s Future Emissions, (2016); Final Energy Consumption, (2021); Fuinhas J.A., Koengkan M., Leitao N.C., Nwani C., Uzuner G., Dehdar F., Relva S., Peyerl D., Effect of battery electric vehicles on greenhouse gas emissions in 29 European Union countries, Sustainability, 13, (2021); Teixeira A.C.R., Sodre J.R., Impacts of replacement of engine powered vehicles by electric vehicles on energy consumption and CO<sub>2</sub> emissions, Transp. Res. Part D Transp. Environ, 59, pp. 375-384, (2018); Sriwilai A., Pattaraprakorn W., Chutiprapat V., Sansilah C., Bhasaputra P., The study on the effect of electric car to energy consumption in Thailand, Proceedings of the 2016 13th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications, and Information Technology (ECTI-CON), pp. 1-5, (2016); Wu X., Freese D., Cabrera A., Kitch W.A., Electric vehicles’ energy consumption measurement and estimation, Transp. Res. Part D Transp. Environ, 34, pp. 52-67, (2015); Dias M.V.X., Haddad J., Horta N.L., Costa B.D., Passos da Cruz R.A., Akira Y.R., Goncalves J.L., The impact on electricity demand and emissions due to the introduction of electric cars in the São Paulo power system, Energy Policy, 65, pp. 298-304, (2014); Baran R.L., Loureiro L.F., The introduction of electric vehicles in Brazil: Impacts on oil and electricity consumption, Technol. Forecast. Soc. Chang, 80, pp. 907-917, (2013); Helmers E., Marx P., Electric cars: Technical characteristics and environmental impacts, Environ. Sci. Eur, 24, pp. 1-14, (2012); Vliet O.V., Brouwer A.V., Kuramochi K., Broek M.V., Faaij A., Energy use, cost and CO<sub>2</sub> emissions of electric cars, J. Power Sources, 196, pp. 2298-2310, (2011); Salihi J.T., Energy requirements for electric cars and their impact on electric power generation and distribution systems, IEEE Trans. Ind. Appl, 9, pp. 516-532, (1973); Nielsen H.L., Jorgensen K., Electric Vehicles and Renewable Energy in the Transport Sector—Energy System Consequences, pp. 1-82, (2000); Sobol L., Dyjakon A., The influence of power sources for charging the batteries of electric cars on CO<sub>2</sub> emissions during daily driving: A case study from Poland, Energies, 13, (2020); Holmberg K., Erdemir A., The impact of tribology on energy use and CO<sub>2</sub> emission globally and in combustion engines and electric cars, Tribol. Int, 135, pp. 389-396, (2019); Koengkan M., Fuinhas J.A., Does the overweight epidemic cause energy consumption? A piece of empirical evidence from the European region, Energy, 216, (2021); Buhari D.G.A., Lorente D.B., Nasir M.A., European commitment to COP21 and the role of energy consumption, FDI, trade and economic complexity in sustaining economic growth, J. Environ. Manag, 273, (2020); Wang Q., Su M., Li R., Ponce P., The effects of energy prices, urbanisation, and economic growth on energy consumption per capita in 186 countries, J. Clean. 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Rev, 22, pp. 493-507, (2002); Hidayatno A., Destyanto A.R., Fadhil M., Model conceptualization on E-commerce growth impact to emissions generated from urban logistics transportation: A case study of Jakarta, Energy Procedia, 156, pp. 144-148, (2019); Weber C.L., Koomey J.G., Matthews H.C., The energy and climate change implications of different music delivery methods, J. Ind. Ecol, 14, pp. 754-769, (2010); Cholette S., Venkat K., The energy and carbon intensity of wine distribution: A study of logistical options for delivering wine to consumers, J. Clean. 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Comput, 2, pp. 117-119, (1992); Persyn D., Westerlund J., Error-correction–based cointegration tests for panel data, STATA J, 8, pp. 232-241, (2008); Koengkan M., Fuinhas J.A., Silva N., Exploring the capacity of renewable energy consumption to reduce outdoor air pollution death rate in Latin America and the Caribbean region, Environ. Sci. Pollut. Res, 28, pp. 1656-1674, (2021); Fuinhas J.A., Marques A.C., Koengkan M., Are renewable energy policies upsetting carbon dioxide emissions? The case of Latin America countries, Environ. Sci. Pollut. Res, 24, pp. 15044-15054, (2017); Koengkan M., Fuinhas J.A., Is gender inequality an essential driver in explaining environmental degradation? Some empirical answers from the CO<sub>2</sub> emissions in European Union countries, Environ. Impact Assess. Rev, 90, (2021)","M. Koengkan; GOVCOPP, Department of Economics, Management, Industrial Engineering and Tourism (DEGEIT), University of Aveiro, Aveiro, 3810-193, Portugal; email: matheus.belucio@hotmail.com",null,"MDPI",{"$nulls":5},2.0326653E7,null,null,null,"English","World Electr. Veh. J.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85124526265"]
["Jiang L.; Sun P.; Xu J.; Yang D.; Xu L.; Shi Y.","Jiang, Lingyun (16506896700); Sun, Pengfei (57224321860); Xu, Jia (55506790200); Yang, Dejun (55717957100); Xu, Lijie (57191476764); Shi, Yu (57224315649)","16506896700; 57224321860; 55506790200; 55717957100; 57191476764; 57224315649","Cooperative Package Assignment for Heterogeneous Express Stations",2022.0,"IEEE Transactions on Intelligent Transportation Systems",23.0,7.0,null,8467.0,8476.0,9.0,2.0,"10.1109/TITS.2021.3082919","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85107374686&doi=10.1109%2fTITS.2021.3082919&partnerID=40&md5=8fc6c40da4b22f23b907d81cd060a67c","Nanjing University of Posts and Telecommunications, Jiangsu Key Laboratory of Big Data Security and Intelligent Processing, Nanjing, 210023, China; Colorado School of Mines, Department of Computer Science, Golden, 80401, CO, United States; Inner Mongolia University, College of Computer Science, Hohhot, 010021, China","Jiang L., Nanjing University of Posts and Telecommunications, Jiangsu Key Laboratory of Big Data Security and Intelligent Processing, Nanjing, 210023, China; Sun P., Nanjing University of Posts and Telecommunications, Jiangsu Key Laboratory of Big Data Security and Intelligent Processing, Nanjing, 210023, China; Xu J., Nanjing University of Posts and Telecommunications, Jiangsu Key Laboratory of Big Data Security and Intelligent Processing, Nanjing, 210023, China; Yang D., Colorado School of Mines, Department of Computer Science, Golden, 80401, CO, United States; Xu L., Nanjing University of Posts and Telecommunications, Jiangsu Key Laboratory of Big Data Security and Intelligent Processing, Nanjing, 210023, China; Shi Y., Inner Mongolia University, College of Computer Science, Hohhot, 010021, China","The success of online shopping accelerates the development of express delivery business with economic and efficient service. Current express delivery systems usually deliver the packages in noncooperation mode and cannot jointly optimize the express fee and moving cost of users. This paper proposes the cooperative package assignment system by lumping packages at the same express station to share the express fee, and proposes a novel pricing structure to stimulate the express stations to join the system without revenue loss by introducing cooperation cost. We formulate the cooperative package assignment (CPA) problem with heterogeneous express stations for joint optimization of users' express fee and moving cost. Then, an approximate algorithm, CPAA, is proposed for the CPA problem based on the greedy approach using submodular function minimization. We show that the designed algorithm achieves computational efficiency and guaranteed approximation. Furthermore, we model the large-scale CPA problem as CPA-game and present a game theoretic algorithm, CPAGA. We show that CPA-game has at least one Nash Equilibrium, and CPAGA finally converges to a pure Nash Equilibrium. Through extensive simulations, we demonstrate that CPAA and CPAGA show great advantages in terms of comprehensive cost, which is 28.1% and 19.9% lower than that in noncooperation mode on average, respectively. Moreover, CPAGA shows great scalability and is more suitable for large-scale cooperative package assignment systems.  © 2000-2011 IEEE.","coalition formation game; Cooperative package assignment; express station; submodular function","Approximation algorithms; Computational efficiency; Economics; Game theory; Approximate algorithms; Comprehensive costs; Cooperation costs; Extensive simulations; Greedy approaches; Joint optimization; Pricing structures; Submodular function minimization; Costs",{"$nulls":4},"National Science Foundation, NSF, (1717315); National Natural Science Foundation of China, NSFC, (61872191, 61872193, 62072254)","This work was supported in part by the NSFC under Grant 61872193, Grant 61872191, and Grant 62072254 and in part by the NSF under Grant 1717315","Statistical Report of China Postal Industry, (2020); Analysis of Double Eleven Market, (2019); Xue G., Xu J., Wu H., Lu W., Xu L., Incentive mechanism for rational miners in bitcoin mining pool, Inf. Syst. Frontiers, 23, 2, pp. 317-327, (2021); Xu J., Rao Z., Xu L., Yang D., Li T., Incentive mechanism for multiple cooperative tasks with compatible users in mobile crowd sensing via online communities, IEEE Trans. Mobile Comput., 19, 7, pp. 1618-1633, (2020); Xu J., Hu S., Wu S., Zhou K., Dai H., Xu L., Cooperative charging as service: Scheduling for mobile wireless rechargeable sensor networks, Proc. IEEE Int. Conf. Distrib. Comput. Syst. (ICDCS), (2021); Wang Q., Zhang K., Mu D., Research on the collaboration of express service network based on resource integration, Proc. Int. Conf. Logistics, Informat. Service Sci. (LISS), pp. 1-4, (2016); Yao X., Cheng Y., Song M., Assessment of collaboration in city logistics: From the aspects of profit and CO2 emissions, Int. J. Logistics Res. Appl., 22, 6, pp. 576-591, (2019); Liu Y., EMS cooperative pricing mechanism optimization for electronic commerce, Proc. Int. Conf. Intell. Transp., Big Data Smart City (ICITBS), pp. 420-423, (2018); Ko S., Cho S., Lee C., Pricing and collaboration in last mile delivery services, Sustainability, 10, 12, (2018); Chung K.H., Ko S.Y., Lee C.U., Ko C.S., Sustainable collaboration model with monopoly of service centers in express delivery services based on shapley value allocation, Int. J. Ind. Eng., 23, 3, pp. 166-173, (2016); Hong S., Lv R., Hong P., Cost sharing of terminal joint distribution of express industry, IET Intell. Transp. Syst., 12, 7, pp. 166-173, (2016); Ferdinand F.N., Chung K.H., Collaborative system design in express delivery services: Formulation and solution heuristic, ICIC Exp. Lett. B, Appl.: Int. J. Res. Surv., 5, 1, pp. 1-8, (2014); Kim Y.J., Ferdinand F.N., Lee H.K., Collaboration-based profitable tour design with pick-up and delivery in express courier services, ICIC Exp. Lett., Int. J. Res. Surv., 5, 10, pp. 3625-3630, (2011); Ferdinand F.N., Chang K., Coevolutionary algorithm based approach to the collaborative network design in express delivery services using coalitional game theory, ICIC Exp. Lett., 10, pp. 2711-2717, (2016); Dahl S., Derigs U., Cooperative planning in express carrier networks-An empirical study on the effectiveness of a real-time decision support system, Decis. Support Syst., 51, 3, pp. 620-626, (2011); Vazirani V.V., Approximation Algorithms, pp. 322-326, (2013); Iwata S., Fleischer L., Fujishige S., A combinatorial strongly polynomial algorithm for minimizing submodular functions, J. ACM, 48, 4, pp. 761-777, (2001); (2020); (2020); (2020); (2020); Saad W., Han Z., Debbah M., Hjorungnes A., Basar T., Coalitional game theory for communication networks, IEEE Signal Process. Mag., 26, 5, pp. 77-97, (2009); Matsui A., Best response dynamics and socially stable strategies, J. Econ. Theory, 57, 2, pp. 343-362, (1992); Monderer D., Shapley L.S., Potential games, Games Econ. Behav., 14, 1, pp. 124-143, (1996); Nisan N., Roughgarden T., Tardos E., Vazirani V., Algorithmic Game Theory, (2007); Maharjan S., Zhu Q., Zhang Y., Gjessing S., Basar T., Dependable demand response management in the smart grid: A stackelberg game approach, IEEE Trans. Smart Grid, 4, 1, pp. 120-132, (2013); Mortensen D.T., The matching process as a noncooperative bargaining game, The Economics of Information and Uncertainty, pp. 233-258, (1982)","J. Xu; Nanjing University of Posts and Telecommunications, Jiangsu Key Laboratory of Big Data Security and Intelligent Processing, Nanjing, 210023, China; email: xujia@njupt.edu.cn",null,"Institute of Electrical and Electronics Engineers Inc.",{"$nulls":5},1.524905E7,null,null,null,"English","IEEE Trans. Intell. Transp. Syst.","Article","Final",null,"Scopus","2-s2.0-85107374686"]
["Priyan S.; Udayakumar R.; Mala P.; Prabha M.; Ghosh A.","Priyan, S. (49362141500); Udayakumar, R. (57199322772); Mala, P. (57197774892); Prabha, M. (57210360334); Ghosh, Ananya (57408026200)","49362141500; 57199322772; 57197774892; 57210360334; 57408026200","A sustainable dual-channel inventory model with trapezoidal fuzzy demand and energy consumption",2022.0,"Cleaner Engineering and Technology",6.0,null,100400.0,null,null,null,15.0,"10.1016/j.clet.2022.100400","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85122632097&doi=10.1016%2fj.clet.2022.100400&partnerID=40&md5=0ce27133ec18ae5d40eb39023442d927","Faculty of Mathematics, Department of Information Technology & Engineering, Amity University Tashkent, Uzbekistan; Department of Mathematics, Dr. N.G.P Institute of Technology, Coimbatore, Tamil Nadu, India; Department of Mathematics, Kamaraj College of Engineering and Technology, Madurai, 625701, Tamil Nadu, India; Department of Mathematics, PSNA College of Engineering and Technology, Dindigul, 624001, Tamil Nadu, India; Faculty of Tourism, Department of Management and Social Science, Amity University Tashkent, Uzbekistan","Priyan S., Faculty of Mathematics, Department of Information Technology & Engineering, Amity University Tashkent, Uzbekistan; Udayakumar R., Department of Mathematics, Dr. N.G.P Institute of Technology, Coimbatore, Tamil Nadu, India; Mala P., Department of Mathematics, Kamaraj College of Engineering and Technology, Madurai, 625701, Tamil Nadu, India; Prabha M., Department of Mathematics, PSNA College of Engineering and Technology, Dindigul, 624001, Tamil Nadu, India; Ghosh A., Faculty of Tourism, Department of Management and Social Science, Amity University Tashkent, Uzbekistan","Most of the consumers relied heavily on e-commerce for products and services for the past few years due to the recent COVID-19 pandemic. This kind of an unexpected behaviour among the consumer society has taken every industry by surprise so that many industries have begun operating online and offline businesses to ensure future competitiveness. Firms introducing online sales are deplorably facing many challenges in terms of logistics and delivery processes, such as short lead times, flexible delivery, capacity of warehouse, and the production process for controlling carbon emissions. Keeping these challenges in mind, a sustainable dual-channel vendor-buyer supply chain model has considered for a controllable emission under fuzzy demand and energy consumption. The model deals with limitation on warehouse floor-space area, and the warehouse divides into two stages such as one for satisfying online orders and the other for satisfying offline orders. The demand rate and energy consumptions are treated as the trapezoidal fuzzy number, and we use the signed distance method to defuzzify the fuzzy joint expected total cost. The objective focuses on obtaining a trade-off between cost and emissions, thereby determining the optimal production-distribution strategy and a proper sustainable plan for handling both online and offline orders. The aforesaid scenario is mathematically formulated in the form of constrained non-linear programme (NLP) and derive a Lagrangean multiplier method to solve it. An iterative solution algorithm is designed, and for better illustration of the developed theory, numerical analysis is carried out followed by a wide discussion on the sensitivity analysis for various parameters. Our results indicate that the optimal solutions of the sustainable fuzzy model slightly fluctuate from the solutions of the sustainable crisp model. According to results, considering the uncertainty in the system is a crucial factor to achieve the economic and environmental sustainability of the production sector. The research reveals that the practitioners should be careful in accounting flexibility in the input factors demand and energy to tackle the uncertainties that always fit the real situation. © 2022 The Authors","Carbon emission; Dual channel; Lagrangean multiplier; Trapezoidal number",{"$nulls":7},"Abdullah A.H.A., Umar M.M., Ali A.S., Irfan A., Multi-objective optimization modelling of sustainable green supply chain in inventory and production management, Alex. Eng. J., 60, pp. 5129-5146, (2021); Alawneh F., Zhang G., Dual-channel warehouse and inventory management with stochastic demand, Transport. Res. Part E, 112, pp. 84-106, (2018); Arash S., Controllable carbon emissions in an inventory model for perishable items under trade credit policy for credit-risk customers, Carbon Capture Science & Technology, 1, (2021); Asif I.M., Byung S.K., A multi-constrained SC model with optimal production rate in relation to quality of products under stochastic fuzzy demand, Comput. Ind. Eng., 149, (2020); Aslani A., Heydari J., Transshipment contract for coordination of a green dual-channel supply chain under channel disruption, J. Clean. Prod., (2019); Benjaafar S., Li Y., Daskin M., Carbon footprint and the management of supply chains: insights from simple models, IEEE Trans. Autom. Sci. Eng., 10, pp. 99-116, (2013); Bikash K.D., Shaktipada B., Biswajit S., Involvement of controllable lead time and variable demand for a smart manufacturing system under a supply chain management, Expert Syst. Appl., 184, (2021); Biswajit S., Bikash K.D., Sarla P., Mitali S., A single-stage cleaner production system with random defective rate and remanufacturing, Comput. Ind. Eng., 150, (2020); Chen Y.K., Chiu F.R., Lin W.H., Huang Y.C., An integrated model for online product placement and inventory control problem in a drop-shipping optional environment, Comput. Ind. Eng., 117, (2018); Ghasemkhani A., Et al., An integrated production inventory routing problem for multi perishable products with fuzzy demands and time windows, IFAC-PapersOnLine, 52, pp. 523-528, (2019); Hadi M., Aliakbar H., A multi-objective model for cleaner production-transportation planning in manufacturing plants via fuzzy goal programming, J. Manuf. Syst., 44, pp. 230-242, (2017); Hadi M., Babak S., Iraj M., Alireza A.K., Sustainable dual-channel closed-loop supply chain network with new products for the lighting industry, Comput. Ind. Eng., 162, (2021); Hammami R., Nouira I., Frein Y., Carbon emissions in a multi-echelon production inventory model with lead time constraints, Int. J. Prod. Econ., 16, pp. 292-307, (2015); He P., He Y., Xu H., Channel structure and pricing in a dual-channel closed-loop supply chain with government subsidy, Int. J. Prod. 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Model., 40, pp. 7318-7335, (2016); Javad S., Seyed T.A.N., Two parameter tuned multi-objective evolutionary algorithms for a bi-objective vendor managed inventory model with trapezoidal fuzzy demand, Appl. Soft Comput., 30, pp. 567-576, (2015); Jinsen G., Bin C., Wei X., Yuanguang Z., Yong-Wu Z., Impacts of pre-sales service and delivery lead time on dual-channel supply chain design, Comput. Ind. Eng., 147, (2020); Jianteng X., Qi Q., Qingguo B., Coordinating a dual-channel supply chain with price discount contracts under carbon emission capacity regulation, Appl. Math. Model., 56, pp. 449-468, (2018); Jingna J., Zhiyong Z., Lei Y., Carbon emission reduction decisions in the retailor/dual-channel supply chain with consumers' preference, J. Clean. Prod., 141, pp. 852-867, (2017); Jian L., Qin S., Li M., Production and transportation outsourcing decisions in the supply chain under single and multiple carbon policies, J. Clean. 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Manag., 58, (2021); Xu L., Wang C., Zhao J., Decision and coordination in the dual-channel supply chain considering cap-and-trade regulation, J. Clean. Prod., 197, pp. 551-561, (2018); Yanlai L., Fangming Z., A two-warehouse inventory model for deteriorating items under conditionally permissible delay in payment, Appl. Math. Model., 35, pp. 2221-2231, (2011); Yosef D., Hui M.W., Sustainable economic production quantity models: an approach toward a cleaner production, Journal of Advanced Management Science, 6, pp. 206-212, (2018); Yao J.S., Wu K., Ranking fuzzy numbers based on decomposition principle and signed distance, Fuzzy Set Syst., 116, pp. 275-288, (2000)","S. Priyan; Faculty of Mathematics, Department of Information Technology & Engineering, Amity University Tashkent, Uzbekistan; email: jaisilpriyan@gmail.com",null,"Elsevier Ltd",{"$nulls":5},2.6667908E7,null,null,null,"English","Clean. Eng. Technol.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85122632097"]
["Torres F.; Gendreau M.; Rei W.","Torres, Fabian (57672428600); Gendreau, Michel (7005646783); Rei, Walter (26768255500)","57672428600; 7005646783; 26768255500","Vehicle Routing with Stochastic Supply of Crowd Vehicles and Time Windows",2022.0,"Transportation Science",56.0,3.0,null,631.0,653.0,22.0,9.0,"10.1287/trsc.2021.1101","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85133457196&doi=10.1287%2ftrsc.2021.1101&partnerID=40&md5=bf19bbfa7640b2c2b8f07a189f744650","Centre interuniversitaire de recherche sur les reseaux d’entreprise,, la logistique et le transport (CIRRELT), Montréal, H3T 1J4, QC, Canada; Département de mathématiques et de génie industriel, Polytechnique Montréal, Montréal, H3C 3A7, QC, Canada; Département de management et technologie, Université de Québec à Montréal, Montréal, H2L 2C4, QC, Canada","Torres F., Centre interuniversitaire de recherche sur les reseaux d’entreprise,, la logistique et le transport (CIRRELT), Montréal, H3T 1J4, QC, Canada, Département de mathématiques et de génie industriel, Polytechnique Montréal, Montréal, H3C 3A7, QC, Canada; Gendreau M., Centre interuniversitaire de recherche sur les reseaux d’entreprise,, la logistique et le transport (CIRRELT), Montréal, H3T 1J4, QC, Canada, Département de mathématiques et de génie industriel, Polytechnique Montréal, Montréal, H3C 3A7, QC, Canada; Rei W., Centre interuniversitaire de recherche sur les reseaux d’entreprise,, la logistique et le transport (CIRRELT), Montréal, H3T 1J4, QC, Canada, Département de management et technologie, Université de Québec à Montréal, Montréal, H2L 2C4, QC, Canada","The growth of e-commerce has increased demand for last-mile deliveries, increasing the level of congestion in the existing transportation infrastructure in urban areas. Crowdsourcing deliveries can provide the additional capacity needed to meet the growing demand in a cost-effective way. We introduce a setting where a crowd-shipping platform sells heterogeneous products of different sizes from a central depot. Items sold vary from groceries to electronics. Some items must be delivered within a time window, whereas others need a customer signature. Furthermore, customer presence is not guaranteed, and some deliveries may need to be returned to the depot. Delivery requests are fulfilled by a fleet of professional drivers and a pool of crowd drivers. We present a crowd-shipping platform that standardizes crowd drivers’ capacities and compensates them to return undelivered packages back to the depot. We formulate a two-stage stochastic model, and we propose a branch and price algorithm to solve the problem exactly and a column generation heuristic to solve larger problems quickly. We further develop an analytical method to calculate upper bounds on the supply of vehicles and an innovative cohesive pricing problem to generate columns for the pool of crowd drivers. Computational experiments are carried out on modified Solomon instances with a pool of 100 crowd vehicles. The branch and price algorithm is able to solve instances of up to 100 customers. We show that the value of the stochastic solution can be as high as 18% when compared with the solution obtained from a deterministic simplification of the model. Significant cost reductions of up to 28% are achieved by implementing crowd drivers with low compensations or higher capacities. Finally, we evaluate what happens when crowd drivers are given the autonomy to select routes based on rational and irrational behavior. There is no cost increase when crowd drivers are rational and select routes that have a higher compensation first. However, when crowd drivers are irrational and select routes randomly, the cost can increase up to 4.2% for some instances. 2021 INFORMS","city logistics; column generation; crowd drivers; crowd logistics; crowd shipping; dynamic programming; occasional drivers; stochastic programming","Cost effectiveness; Cost reduction; Dynamic programming; Fleet operations; Integer programming; Lakes; Linear programming; Problem solving; Sales; Stochastic models; Stochastic systems; Traffic congestion; Urban growth; Urban transportation; Vehicle routing; Branch-and-price algorithms; City logistics; Column generation; Crowd driver; Crowd logistic; Crowd shipping; E- commerces; Occasional driver; Stochastics; Time windows; Stochastic programming",{"$nulls":4},"Canada Research Chair in Stochastic Opti-mization of Transport and Logistics Systems; Ecuadorian Secre-taría de Educación Superior, Ciencia, Tecnología e Inovación; Stochastic Optimization of Transport and Logistics Systems; Polytechnique Montréal; Natural Sciences and Engineering Research Council of Canada, NSERC, (70732901, RGPIN/4696-2016, RGPIN38816-10); Secretaría de Educación Superior, Ciencia, Tecnología e Innovación, SENESCYT","Funding text 1: Funding: This research was partially funded by the Canadian Natural Sciences and Engineering Research Council under its Discovery Grants research program [under Grants 70732901, RGPIN38816-10, and RGPIN/4696-2016], as well as the Canada Research Chair in Stochastic Opti-mization of Transport and Logistics Systems, Polytechnique Montréal, and the Ecuadorian Secre-taría de Educación Superior, Ciencia, Tecnología e Inovación (SENESCYT) under its international scholarships program.; Funding text 2: Funding: This research was partially funded by the Canadian Natural Sciences and Engineering Research Council under its Discovery Grants research program [under Grants 70732901, RGPIN38816-10, and RGPIN/4696-2016], as well as the Canada Research Chair in Stochastic Optimization of Transport and Logistics Systems, Polytechnique Montréal, and the Ecuadorian Secretaría de Educación Superior, Ciencia, Tecnología e Inovación (SENESCYT) under its international scholarships program.","AmazonFlex, (2021); Archetti C, Guerriero F, Macrina G, The online vehicle routing problem with occasional drivers, Comput. Oper. Res, 127, 2021, (2021); Archetti C, Savelsbergh M, Speranza MG, The vehicle routing problem with occasional drivers, Eur. J. Oper. Res, 254, 2, pp. 472-480, (2016); Arslan AM, Agatz N, Kroon L, Zuidwijk R, Crowdsourced delivery: A dynamic pickup and delivery problem with ad hoc drivers, Transportation Sci, 53, 1, pp. 222-235, (2019); Asdecker B, Zirkelbach F, What drives the drivers? A qualitative perspective on what motivates the crowd delivery workforce, Proc. 53rd Hawaii Internat. Conf. System Sci, pp. 4011-4020, (2020); Baldacci R, Mingozzi A, Roberti R, New route relaxation and pricing strategies for the vehicle routing problem, Oper. Res, 59, 5, pp. 1269-1283, (2011); Barr A, Wohl J, Exclusive: Walmart may get customers to deliver packages to online buyers, Reuters, (2013); Costa L, Contardo C, Desaulniers G, Exact branch-price-and-cut algorithms for vehicle routing, Transportation Sci, 53, 4, pp. 946-985, (2019); Dahle L, Andersson H, Christiansen M, The vehicle routing problem with dynamic occasional drivers, Proc. Internat. Conf. Comput. Logist, pp. 49-63, (2017); Dahle L, Andersson H, Christiansen M, Speranza MG, The pickup and delivery problem with time windows and occasional drivers, Comput. Oper. Res, 109, pp. 122-133, (2019); Dayarian I, Savelsbergh M, Crowdshipping and same-day delivery: Employing in-store customers to deliver online orders, Production Oper. Management, 29, 9, pp. 2153-2174, (2020); Errico F, Desaulniers G, Gendreau M, Rei W, Rousseau LM, The vehicle routing problem with hard time windows and stochastic service times, EURO J. 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Soc, 62, 4, pp. 742-749, (2011); Psaraftis HN, Wen M, Kontovas CA, Dynamic vehicle routing problems: Three decades and counting, Networks, 67, 1, pp. 3-31, (2016); Salavati-Khoshghalb M, Gendreau M, Jabali O, Rei W, An exact algorithm to solve the vehicle routing problem with stochastic demands under an optimal restocking policy, Eur. J. Oper. Res, 273, 1, pp. 175-189, (2019); Sampaio A, Savelsbergh M, Veelenturf L, Van Woensel T, Crowd-based city logistics, Sustainable Transportation and Smart Logistics: Decision-Making Models and Solutions, pp. 381-400, (2019); Schoolov K, What it’s really like to be an Amazon Flex delivery driver as prime one-day shipping expands, CNBC, (2019); Semuels A, I delivered packages for Amazon and it was a nightmare, The Atlantic, (2018); Sundararajan A, The Sharing Economy: The End of Employment and the Rise of Crowd-Based Capitalism, (2016); Teodorovic D, Krcmar-Nozic E, Pavkovic G, The mixed fleet stochastic vehicle routing problem, Transportation Planning Techn, 19, 1, pp. 31-43, (1995)",null,null,"INFORMS Inst.for Operations Res.and the Management Sciences",{"$nulls":5},411655.0,null,"TRSCB",null,"English","Transp Sci","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85133457196"]
["Peppel M.; Ringbeck J.; Spinler S.","Peppel, Marcel (57415956200); Ringbeck, Jürgen (54584237900); Spinler, Stefan (7006502092)","57415956200; 54584237900; 7006502092","How will last-mile delivery be shaped in 2040? A Delphi-based scenario study",2022.0,"Technological Forecasting and Social Change",177.0,null,121493.0,null,null,null,20.0,"10.1016/j.techfore.2022.121493","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85123021000&doi=10.1016%2fj.techfore.2022.121493&partnerID=40&md5=8b3680b0836a8a3694680d103443d91c","WHU - Otto Beisheim School of Management, Burgplatz 2, Vallendar, 56179, Germany","Peppel M., WHU - Otto Beisheim School of Management, Burgplatz 2, Vallendar, 56179, Germany; Ringbeck J., WHU - Otto Beisheim School of Management, Burgplatz 2, Vallendar, 56179, Germany; Spinler S., WHU - Otto Beisheim School of Management, Burgplatz 2, Vallendar, 56179, Germany","Last-mile delivery (LMD) has experienced tremendous growth in recent years, primarily driven by e-commerce. The LMD sector is characterized by strong competition, with new entrants addressing unexplored business segments, while digitization and more sustainable operations are shifting current industry standards. This paper explores upcoming trends in the LMD sector using a Delphi-based scenario study for 2040. We develop projections of future consumer behavior, delivery technologies, delivery services, and regulation to validate them by conducting a two-round Delphi study among 36 experts from the LMD industry, academia, and politics. Based on the results, three future scenarios are identified by fuzzy c-means clustering, set within the context of innovation diffusion theory and the technology acceptance model. There is expert consensus on the scope of technologies that will be used in 2040 and how consumers’ preferences may change, but the future design of delivery services is less certain. The identified scenarios provide managerial and policy guidance for logistics service providers, suppliers, municipalities, and e-commerce retailers to adapt their long-term strategies. © 2022 Elsevier Inc.","Cluster analysis; Delphi study; Delphi-based scenario study; Fuzzy clustering; Last-mile delivery; Scenario planning","Competition; Consumer behavior; Electronic commerce; Fuzzy clustering; Business segments; Delivery service; DELPHI study; Delphi-based scenario study; Digitisation; E- commerces; Last mile; Last-mile delivery; Scenario Planning; Scenario studies; cluster analysis; consumption behavior; Delphi analysis; electronic commerce; scenario analysis; Cluster analysis",{"$nulls":6},{"$cut":{"chars":20643,"head":"Aiello G., Quaranta S., Certa A., Inguanta R., Optimization of urban delivery systems based on electric assisted cargo bikes with modular battery size, taking into account the service requirements and the specific operational context, Energies, 14, (2021); Akkermans H.A., Bogerd P., Yucesan E., Van Wassenhove L.N., The impact of ERP on supply chain management: exploratory findings from a European Delphi study, Eur. J. Oper. Res., 146, pp. 284-301, (2003); Al-Rahmi W.M., Yahaya N., Aldraiweesh A.A., Alamri M.M., Aljarboa N.A., Alturki U., Aljeraiwi A.A., Integrating technology acceptance model with innovation diffusion theory: an empirical investigation on students’ intention to use e-learning systems, IEEE Access, 7, pp. 26797-26809, (2019); Allen J., Piecyk M., Piotrowska M., McLeod F., Cherrett T., Ghali K., Nguyen T., Bektas T., Bates O., Friday A., Wise S., Austwick M., Understanding the impact of e-commerce on last-mile light goods vehicle activity in urban areas: the case of London, Transp. Res. D: Transp. Environ., 61, pp. 325-338, (2018); Arnold F., Cardenas I., Sorensen K., Dewulf W., Simulation of B2C e-commerce distribution in Antwerp using cargo bikes and delivery points, Eur. Transp. Res. Rev., 10, pp. 1-13, (2018); Bastida-Molina P., Hurtado-Perez E., Penalvo-Lopez E., Moros-Gomez M.C., Assessing transport emissions reduction while increasing electric vehicles and renewable generation levels, Transp. Res. D: Transp. Environ., 88, (2020); Beiderbeck D., Frevel N., von der Gracht H.A., Schmidt S.L., Schweitzer V.M., The impact of COVID-19 on the European football ecosystem–A Delphi-based scenario analysis, Technol. Forecast. Soc. Change, 165, (2021); Beiderbeck D., Frevel N., Heiko A., Schmidt S.L., Schweitzer V.M., Preparing, conducting, and Analyzing Delphi surveys: Cross-disciplinary practices, New directions, and Advancements, (2021); Belton I., MacDonald A., Wright G., Hamlin I., Improving the practical application of the Delphi method in group-based judgment: a six-step prescription for a well-founded and defensible process, Technol. Forecast. Soc. Change, 147, pp. 72-82, (2019); Best R.J., An experiment in Delphi estimation in marketing decision making, J. Mark. Res., 11, pp. 447-452, (1974); Bezdek J.C., Objective Function clustering, in: Pattern Recognition With Fuzzy Objective Function Algorithms, pp. 43-93, (1981); Bezdek J.C., Keller J., Krisnapuram R., Pal N., Fuzzy Models and Algorithms For Pattern Recognition and Image Processing, 4, (1999); Bijl R., Delphi in a future scenario study on mental health and mental health care, Futures, 24, pp. 232-250, (1992); Bishop P., Hines A., Collins T., The current state of scenario development: an overview of techniques, Foresight, 9, pp. 5-25, (2007); Bjorklund M., Johansson H., Urban consolidation centre–A literature review, categorisation, and a future research agenda, Int. J. Phys. Distrib. Logist. Manag., 48, pp. 745-764, (2018); Bokrantz J., Skoogh A., Berlin C., Stahre J., Maintenance in digitalised manufacturing: Delphi-based scenarios for 2030, Int. J. Prod. Econ., 191, pp. 154-169, (2017); Bolger F., Wright G., Improving the Delphi process: lessons from social psychological research, Technol. Forecast. Soc. Change, 78, pp. 1500-1513, (2011); Bonaccorsi A., Apreda R., Fantoni G., Expert biases in technology foresight. why they are a problem and how to mitigate them, Technol. Forecast. Soc. Change, 151, (2020); Boysen N., Fedtke S., Schwerdfeger S., Last-mile delivery concepts: a survey from an operational research perspective, OR Spectrum, 43, pp. 1-58, (2021); Boysen N., Schwerdfeger S., Weidinger F., Scheduling last-mile deliveries with truckbased autonomous robots, Eur. J. Oper. Res., 271, pp. 1085-1099, (2018); Broaddus A., Browne M., Allen J., Sustainable freight: impacts of the London congestion charge and low emissions zones, Transp. Res. Rec., 2478, pp. 1-11, (2015); Brown B.B., Helmer-Hirschberg O.A., Improving the Reliability of Estimates Obtained from a Consensus of Experts, pp. 1-13, (1964); Charrad M., Ghazzali N., Boiteau V., Niknafs "}},"M. Peppel; WHU - Otto Beisheim School of Management, Vallendar, Burgplatz 2, 56179, Germany; email: marcel.peppel@whu.edu",null,"Elsevier Inc.",{"$nulls":5},401625.0,null,null,null,"English","Technol. Forecast. Soc. Change","Article","Final",null,"Scopus","2-s2.0-85123021000"]
["Sułkowski Ł.; Kolasińska-Morawska K.; Brzozowska M.; Morawski P.; Schroeder T.","Sułkowski, Łukasz (36020726100); Kolasińska-Morawska, Katarzyna (57204931506); Brzozowska, Marta (57793207600); Morawski, Paweł (57224686948); Schroeder, Tomasz (57793767800)","36020726100; 57204931506; 57793207600; 57224686948; 57793767800","Last Mile Logistics Innovations in the Courier-Express-Parcel Sector Due to the COVID-19 Pandemic",2022.0,"Sustainability (Switzerland)",14.0,13.0,8207.0,null,null,null,14.0,"10.3390/su14138207","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85133826592&doi=10.3390%2fsu14138207&partnerID=40&md5=3820a143a8afd2657b000eb2f0848b16","Faculty of Management and Social Communication, Department of Management of Higher Education Institutions, Jagiellonian University, Cracow, 30-348, Poland; Department of International Management, Cracow University of Economics Management Institute, Cracow, 31-510, Poland; Faculty of Law and Social Sciences, Department of Management, Jan Kochanowski University of Kielce, Kielce, 25-369, Poland; Faculty of Organization and Management, Lodz University of Technology, Lodz, 90-924, Poland","Sułkowski Ł., Faculty of Management and Social Communication, Department of Management of Higher Education Institutions, Jagiellonian University, Cracow, 30-348, Poland; Kolasińska-Morawska K., Department of International Management, Cracow University of Economics Management Institute, Cracow, 31-510, Poland; Brzozowska M., Faculty of Law and Social Sciences, Department of Management, Jan Kochanowski University of Kielce, Kielce, 25-369, Poland; Morawski P., Faculty of Organization and Management, Lodz University of Technology, Lodz, 90-924, Poland; Schroeder T., Department of International Management, Cracow University of Economics Management Institute, Cracow, 31-510, Poland","The development of the e-commerce market worldwide, which was already dynamic, was accelerated by the SARS-CoV-2 virus. Millions of incoming orders required analogue support from the CEP sector (courier-express-parcels sector) to provide the desired “customer experience”. In the context of whether the habit of shopping in virtual reality will become permanent, it is worth considering what shape the logistics services will take in the last mile after the pandemic? Or, will customers return to shopping in the real world? A subject for these considerations was an analysis of the impact of the SARS-CoV-2 virus pandemic on the technologization of last mile logistics services, resulting in an increase in the level of “customer experience”, with Poland as an example. The research methods used were participant observations and critical analysis of collected materials. The obtained results made it possible to conduct a descriptive and explanatory nomothetic study based on an Internet questionnaire. The authors formulated a diagnosis about the possibilities of using the potential of customer experience for the development of enterprises based on technologization of last mile deliveries. The recommendations can be used by scientists and managers in the CEP industry to redefine business models based on the technology of logistics customer service processes. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.","COVID-19; innovations; last mile; logistics services; technologies","Poland [Central Europe]; business; COVID-19; critical analysis; industrial development; Internet; logistics; questionnaire survey; shopping activity; virtual reality",{"$nulls":4},"Jagiellonian University; Uniwersytet Jana Kochanowskiego w Kielcach; Politechnika Lódzka; Uniwersytet Ekonomiczny w Krakowie, UEK, (71/ZZN/2021/DOS)","Funding: This research was funded Jagiellonian University, Faculty of Management and Social Communication, Jan Kochanowski University of Kielce, Cracow University of Economics (Doskonałos´ć Badawcza nr 71/ZZN/2021/DOS), Lodz University of Technology.","Jafari N., Azarian M., Yu H., Moving from Industry 4.0 to Industry 5.0: What Are the Implications for Smart Logistics?, Logistics, 6, (2022); Schafer S., Pinnow C., Industrie 4.0. Grundlagen und Anwendungen: Branchentreff der Berliner Wissenschaft und Industrie, (2015); Bounsoville T., Logistik 4.0. 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Rev, 9, pp. 19-33, (2021); Mitch L., Pandemic Scrambles the Semiconductor Supply Chain, Engineering, 9, pp. 10-12, (2021); Salvatore D., The Global Financial Crisis: Predictions, Causes, Effects, Policies, Reforms and Prospects, J. Econ. Asymmetries, 7, pp. 1-20, (2010); Mihm S., Dr. Doom, New York Times, (2008); Bennington A., Nouriel Roubini on the Origins of the G-Zero World, 2011, CNBC; Ioana A., Semenescu A., Ghiban A., Opportunities and Challenges in Overcoming the Economic Crisis, Procedia Econ. Financ, 6, pp. 73-80, (2013); Hobbs J.E., Food supply chains during the COVID-19 pandemic, Can. J. Agric. Econ.-Rev. Can. D Agroecon, 68, pp. 171-176, (2020); Dennerlein J.T., Burke L., Sabbath E.L., Williams J.A.R., Peters S.E., Wallace L., Karapanos M., Sorensen G., An Integrative Total Worker Health Framework for Keeping Workers Safe and Healthy During the COVID-19 Pandemic, Hum. 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Eng, 7, (2013); Cohen Y., Faccio M., Pilati F., Yao Z., Design and management of digital manufacturing and assembly systems in the Industry 4.0 era, Int. J. Adv. Manuf. Technol, 105, pp. 3565-3577, (2019); Wang J., Ma Y., Zhang L., Gao R., Wu D., Deep learning for smart manufacturing: Methods and applications, J. Manuf. Syst, 48, pp. 144-156, (2018); Bahrin M.A.K., Othman M.F., Azli N.H.N., Talib M.F., Industry 4.0: A review on industrial automation and robotic, J. Teknol, 78, pp. 6-13, (2016); Faccio M., Persona A., Sgarbossa F., Zanin G., Multi-stage supply network design in case of reverse flows: A closed-loop approach, Int. J. Oper. Res, 12, pp. 157-191, (2011); Erol S., Jager A., Hold P., Ott K., Sihn W., Tangible Industry 4.0: A Scenario-Based Approach to Learning for the Future of Production, Procedia CIRP, 54, pp. 13-18, (2016); Jahn M., Ein Weg zu Industrie 4.0. Geschäftsmodell für Produktion und After Sales, (2016)","P. Morawski; Faculty of Organization and Management, Lodz University of Technology, Lodz, 90-924, Poland; email: pawel.morawski.1@p.lodz.pl",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85133826592"]
["Zhang X.; Liu X.","Zhang, X. (57207318254); Liu, X. (56972743900)","57207318254; 56972743900","A two-stage robust model for express service network design with surging demand",2022.0,"European Journal of Operational Research",299.0,1.0,null,154.0,167.0,13.0,10.0,"10.1016/j.ejor.2021.06.031","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85110449456&doi=10.1016%2fj.ejor.2021.06.031&partnerID=40&md5=348592748af9f7ed600313931abd3ee5","Department of Industrial Engineering & Management, Shanghai Jiao Tong University, Shanghai, 200240, China","Zhang X., Department of Industrial Engineering & Management, Shanghai Jiao Tong University, Shanghai, 200240, China; Liu X., Department of Industrial Engineering & Management, Shanghai Jiao Tong University, Shanghai, 200240, China","In the periods following sales on online shopping carnivals, demand for express transportation is expected to precipitously surge within a short time, potentially causing express system overload and delivery delays. In this study, we address a service network design problem of a hub-and-spoke structured express transportation network during periods of surging demands. We consider a new strategy of upgrading existing spokes into temporary hubs to expand the network capacity with low costs. We propose a two-stage bi-objective robust model based on a time-space network to integrate the spoke-upgrading selection, service-scheduling, and vehicle-routing for designing an express service network that is both efficient and economic. To solve the model, we develop an enhanced column-and-constraint generation algorithm. Finally, a case study of a real express logistics company in China is demonstrated to validate the effectiveness of the proposed strategy and to offer decision support in real problems. © 2021 Elsevier B.V.","Capacity expansion; Column and constraint generation; Express service network design; Logistics; Robust optimization","Decision support systems; Logistics; Vehicle routing; Capacity expansion; Column generation; Constraints generation; Express service network design; Express services; Express transportations; Online shopping; Robust modeling; Robust optimization; Service network designs; Optimization",{"$nulls":6},"An K., Lo H.K., Ferry service network design with stochastic demand under user equilibrium flows, Transportation Research Part B: Methodological, 66, pp. 70-89, (2014); An Y., Zeng B., Zhang Y., Zhao L., Reliable p-median facility location problem: Two-stage robust models and algorithms, Transportation Research Part B: Methodological, 64, pp. 54-72, (2014); Andersen J., Christiansen M., Designing new European rail freight services, Journal of the Operational Research Society, 60, 3, pp. 348-360, (2009); 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Wang Z., Qi M., Robust service network design under demand uncertainty, Transportation Science, 54, 3, pp. 676-689, (2020); Wang Z., Qi M., Cheng C., Zhang C., A hybrid algorithm for large-scale service network design considering a heterogeneous fleet, European Journal of Operational Research, (2019); Zeng B., Zhao L., Solving two-stage robust optimization problems using a column-and-constraint generation method, Operations Research Letters, 41, 5, pp. 457-461, (2013); Zhang C., Xu Y., Dong Z.Y., Probability-weighted robust optimization for distributed generation planning in microgrids, IEEE Transactions on Power Systems, 33, 6, pp. 7042-7051, (2018); Zhang M., Janic M., Tavasszy L.A., A freight transport optimization model for integrated network, service, and policy design, Transportation Research Part E, 77, pp. 61-76, (2015); Zhu E., Crainic T.G., Gendreau M., Scheduled service network design for freight rail transportation, Operations research, 62, 2, pp. 383-400, (2014)","X. Liu; Shanghai, Department of Industrial Engineering & Management, Shanghai Jiao Tong University, 200240, China; email: x_liu@sjtu.edu.cn",null,"Elsevier B.V.",{"$nulls":5},3772217.0,null,"EJORD",null,"English","Eur J Oper Res","Article","Final",null,"Scopus","2-s2.0-85110449456"]
["Lin G.; Chang H.; Li X.; Li R.; Zhao Y.","Lin, Guannv (57353213000); Chang, Huimin (57204161313); Li, Xiang (57222187018); Li, Rong (57222185163); Zhao, Yan (56252527300)","57353213000; 57204161313; 57222187018; 57222185163; 56252527300","Integrated environmental impacts and C-footprint reduction potential in treatment and recycling of express delivery packaging waste",2022.0,"Resources, Conservation and Recycling",179.0,null,106078.0,null,null,null,12.0,"10.1016/j.resconrec.2021.106078","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85119925254&doi=10.1016%2fj.resconrec.2021.106078&partnerID=40&md5=943b0ab65ee83bc9b7adae003c11b525","School of Environment, Beijing Normal University, Beijing, 100875, China","Lin G., School of Environment, Beijing Normal University, Beijing, 100875, China; Chang H., School of Environment, Beijing Normal University, Beijing, 100875, China; Li X., School of Environment, Beijing Normal University, Beijing, 100875, China; Li R., School of Environment, Beijing Normal University, Beijing, 100875, China; Zhao Y., School of Environment, Beijing Normal University, Beijing, 100875, China","The rapid development of e-commerce has resulted in a large amount of express delivery package waste (EDPW). The optimisation of EDPW systems is important to achieve low-carbon development. To quantify the impact and C-footprint reduction potential, a comprehensive life cycle assessment enhanced by parameterisation and global sensitivity analysis was conducted on Chinese EDPW systems managing fractions of cardboard, paper and envelope, foamed plastic, soft plastic and woven bag. Material flow analysis reveals that 65% of the EDPW is recycled and cardboard is the dominant contributor. The environmental impacts from EDPW to most impact categories are marginal, but the loads to global warming potentials and human toxicity are significant, mainly attributed to the energy and material consumption during package production. From C-footprint perspective, managing 1,000kg of EDPW would generate a load of 834.88 kg CO2-eq from raw material production and a saving of -524.55 kg CO2-eq from material and energy recovery. Paper and cardboard incineration can achieve carbon reduction with biogenic-CO2 emissions, while plastic incineration releases significant fossil-CO2 that counteracts the savings from energy recovery. Global sensitivity analysis identified proportion of incineration, heat and electricity recovery ratios in incinerators and recycling ratio of cardboard as the major contributors to result uncertainty. Optimising these parameters can achieve a carbon reduction of 177.86 kg CO2-eq per 1,000kg of EDPW. This paper provides a comprehensive view of the environmental impacts of EDPW in waste management system and novel insights into further optimisation and development of the system from a low-carbon perspective. © 2021 Elsevier B.V.","Express delivery packaging waste; Global sensitivity analysis; Global warming potential; Integrated environmental impact; Life cycle assessment","Carbon Dioxide; Effluent Treatment; Life Cycle; Plastic Containers; Recycling; Carbon; Carbon dioxide; Cardboard; Environmental impact; Global warming; Plastic containers; Recycling; Sensitivity analysis; Uncertainty analysis; Waste treatment; carbon; carbon dioxide; plastic; Carbon reduction; Energy recovery; Express delivery packaging waste; Global sensitivity analysis; Global warming potential; Integrated environmental impact; Optimisations; Packaging waste; Reduction potential; Waste systems; carbon footprint; electronic commerce; emission control; environmental impact assessment; global warming; integrated approach; life cycle analysis; recycling; sensitivity analysis; waste disposal; waste treatment; Article; Article; carbon dioxide emission; carbon dioxide equivalent; carbon footprint; China; controlled study; electricity; energy recovery; environmental impact; express delivery package waste; flow measurement; fossil; greenhouse effect; incineration; incinerator; life cycle assessment; plastic waste; recycling; sensitivity analysis; solid waste; solid waste management; uncertainty; waste site; woven bag; Life cycle",null,"carbon, 7440-44-0; carbon dioxide, 124-38-9, 58561-67-4",{"$nulls":4},"pp. 2018-2020, (2021); (2020); Benini L., Mancini L., Sala S., Schau E., Manfredi S., Pant R., (2014); Beylot A., Muller S., Descat M., Menard Y., Villeneuve J., Life cycle assessment of the French municipal solid waste incineration sector, Waste Manag., 80, pp. 144-153, (2018); Bisinella V., Conradsen K., Christensen T.H., Astrup T.F., A global approach for sparse representation of uncertainty in Life Cycle Assessments of waste management systems, Int. J. Life Cycle Assess., 21, pp. 378-394, (2016); (2014); Christensen T.H., Damgaard A., Levis J., Zhao Y., Bjorklund A., Arena U., Barlaz M.A., Starostina V., Boldrin A., Astrup T.F., Bisinella V., Application of LCA modelling in integrated waste management, Waste Manag., 118, pp. 313-322, (2020); Clavreul J., Baumeister H., Christensen T.H., Damgaard A., An environmental assessment system for environmental technologies, Environ. Modelling & Software, 60, pp. 18-30, (2014); Duan H.B., Song G.H., Qu S., Dong X.B., Xu M., Post-consumer packaging waste from express delivery in China, Resour. Conserv. Recycl., 144, pp. 137-143, (2019); Fan W.G., Xu M., Dong X.B., Wei H.J., Considerable environmental impact of the rapid development of China's express delivery industry, Resour. Conserv. Recycl., 126, pp. 174-176, (2017); (2019); Han W.Y., Research On the Resource Environmental Impact and Co-Benefits of Resources Utilization of Food waste: Case Study of Lanzhou city, (2018); Hong J., Li X., Environmental assessment of recycled printing and writing paper: a case study in China, Waste Manag., 32, pp. 264-270, (2012); (2020); Kang P., Song G.H., Xu M., Miller T.R., Wang H.K., Zhang H., Liu G., Zhou Y., Ren J.S., Zhong R.Y., Duan H.B., Low-carbon pathways for the booming express delivery sector in China, Nat. Commun., 12, pp. 1-8, (2021); Khandelwal H., Thalla A.K., Kumar S., Kumar R., Life cycle assessment of municipal solid waste management options for India, Bioresour. Technol., 288, (2019); Liu W., Zhu Q., Zhou X., Peng C., Comparative analyses of different biogenic CO2 emission accounting systems in life cycle assessment, Sci. Total Environ., 652, pp. 1456-1462, (2019); Peng H.W., Gao K., Liu Q.F., pp. 48-52, (2019); Ren J.S., Tian C.X., Li J.H., Hao L., Liang Y.Y., pp. 138-142, (2019); Su Y.H., Duan H.B., Wang Z.N., Song G.H., Kang P., Chen D.J., Characterizing the environmental impact of packaging materials for express delivery via life cycle assessment, J. Clean. Prod., 274, (2020); Tang L.L., Life cycle environmental impact assessment of construction waste treatment, Recycl. Resour. Circular Econ., 12, pp. 29-31, (2019); Villarrubia-Gomez P., Cornell S.E., Fabres J., Marine plastic pollution as a planetary boundary threat – The drifting piece in the sustainability puzzle, Mar. Policy, 96, pp. 213-220, (2018); Yang N., Zhang H., Chen M., Shao L.M., He P.J., Greenhouse gas emissions from MSW incineration in China: impacts of waste characteristics and energy recovery, Waste Manag., 32, pp. 2552-2560, (2012); Yi Y., Wang Z.Y., Wennersten R., Sun Q., Life cycle assessment of delivery packages in China, Energy Procedia, 105, pp. 3711-3719, (2017); (2018); Yu H.Y., Zhu Z.H., Zhang Z.Y., Yu J.M., Oeser M., Wang D.Y., Recycling waste packaging tape into bituminous mixtures towards enhanced mechanical properties and environmental benefits, J. Clean. Prod., 229, pp. 22-31, (2019); Zhang M.L., Cai H.Y., Chen J.L., Jiao X.Y., Gu M., Wang X.M., Liu Y.Y., Present situation and development countermeasure of express packaging waste management: a case study on chongqing, Environ. Sanitation Eng., 28, pp. 9-14, (2020)","Y. Zhao; School of Environment, Beijing Normal University, Beijing, 100875, China; email: yanzhao@bnu.edu.cn",null,"Elsevier B.V.",{"$nulls":5},9213449.0,null,"RCREE",null,"English","Resour. Conserv. Recycl.","Article","Final",null,"Scopus","2-s2.0-85119925254"]
["Giménez-Palacios I.; Parreño F.; Álvarez-Valdés R.; Paquay C.; Oliveira B.B.; Carravilla M.A.; Oliveira J.F.","Giménez-Palacios, Iván (57208919404); Parreño, Francisco (8300754300); Álvarez-Valdés, Ramón (6602700483); Paquay, Célia (56293394600); Oliveira, Beatriz Brito (56050541500); Carravilla, Maria Antónia (20733457400); Oliveira, José Fernando (7202452488)","57208919404; 8300754300; 6602700483; 56293394600; 56050541500; 20733457400; 7202452488","First-mile logistics parcel pickup: Vehicle routing with packing constraints under disruption",2022.0,"Transportation Research Part E: Logistics and Transportation Review",164.0,null,102812.0,null,null,null,5.0,"10.1016/j.tre.2022.102812","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85145797446&doi=10.1016%2fj.tre.2022.102812&partnerID=40&md5=67a6f8e8e9555e4820e1696590360081","Departamento de Matemáticas, University of Castilla-La Mancha, Albacete, Spain; Departament d'Estadística i Investigació Operativa, University of Valencia, Valencia, Spain; HEC Liège, Management School of the University of Liège, Liège, Belgium; INESC TEC, Faculty of Engineering, University of Porto, Porto, Portugal","Giménez-Palacios I., Departamento de Matemáticas, University of Castilla-La Mancha, Albacete, Spain; Parreño F., Departamento de Matemáticas, University of Castilla-La Mancha, Albacete, Spain; Álvarez-Valdés R., Departament d'Estadística i Investigació Operativa, University of Valencia, Valencia, Spain; Paquay C., HEC Liège, Management School of the University of Liège, Liège, Belgium; Oliveira B.B., INESC TEC, Faculty of Engineering, University of Porto, Porto, Portugal; Carravilla M.A., INESC TEC, Faculty of Engineering, University of Porto, Porto, Portugal; Oliveira J.F., INESC TEC, Faculty of Engineering, University of Porto, Porto, Portugal","First-mile logistics tackles the movement of products from retailers to a warehouse or distribution centre. This first step towards the end customer has been pushed by large e-commerce platforms forming extensive networks of partners and is critical for fast deliveries. First-mile pickup requires efficient methods different from those developed for last-mile delivery, among other reasons due to the complexity of cargo features and volume — increasing the relevance of advanced packing methods. More importantly, the problem is essentially dynamic and the pickup process, in which the vehicle is initially empty, is much more flexible to react to disruptions arising when the vehicles are en route. We model the static first-mile pickup problem as a vehicle routing problem for a heterogeneous fleet, with time windows and three-dimensional packing constraints. Moreover, we propose an approach to tackle the dynamic problem, in which the routes can be modified to accommodate disruptions — new customers’ demands and modified requests of known customers that are arriving while the initially established routes are being covered. We propose three reactive strategies for addressing the disruptions depending on the number of vehicles available, and study their results on a newly generated benchmark for dynamic problems. The results allow quantifying the impact of disruptions depending on the strategy used and can help the logistics companies to define their own strategy, considering the characteristics of their customers and products and the available fleet. © 2022","Disruption; First-mile logistics; Packing; Vehicle routing","Fleet operations; Pickups; Sales; Vehicles; Commerce platforms; Disruption; Distribution centres; Dynamic problem; E- commerces; End customers; First mile; First-mile logistic; Last mile; Packing constraints; electronic commerce; merchant ship; routing; transportation development; transportation planning; Vehicle routing",{"$nulls":4},"Ministerio de Ciencia, Innovación y Universidades, MCIU, (RTI2018-094940-B-100); Fundação para a Ciência e a Tecnologia, FCT, (POCI-01-0145-FEDER-029609); European Regional Development Fund, ERDF; Junta de Comunidades de Castilla-La Mancha, JCCM, (SBPLY/17/180501/000282); Programa Operacional Temático Factores de Competitividade, POFC","This work has been partially supported by the Spanish Ministry of Science, Innovation, and Universities , project RTI2018-094940-B-100, partially financed by FEDER funds , by the Junta de Comunidades de Castilla-La Mancha, Spain , project SBPLY/17/180501/000282, partially financed by FEDER funds , and by the ERDF — European Regional Development Fund through the Operational Programme for Competitiveness and Internationalization — COMPETE 2020 Programme and by National Funds through the Portuguese funding agency, FCT — Fundação para a Ciência e a Tecnologia, I.P. , within project POCI-01-0145-FEDER-029609. The authors would like to thank the two anonymous reviewers for their valuable comments, which helped to improve this work. ","Allahviranloo M., Chow J.Y., Recker W.W., Selective vehicle routing problems under uncertainty without recourse, Transp. Res. E, 62, pp. 68-88, (2014); Alvarez D., Alvarez-Valdes R., Parreno F., A grasp algorithm for the container loading problem with multi-drop constraints, Pesqui. Oper., 35, pp. 1-24, (2015); Alvarez-Valdes R., Parreno F., Tamarit J.M., A GRASP/Path Relinking algorithm for two- and three-dimensional multiple bin-size bin packing problems, Comput. Oper. Res., 40, 12, pp. 3081-3090, (2013); Amaya J., Delgado-Lindeman M., Arellana J., Allen J., Urban freight logistics: What do citizens perceive?, Transp. Res. E, 152, May, (2021); Andrade C.E., Toso R.F., Goncalves J.F., Resende M.G., The multi-parent biased random-key genetic algorithm with implicit path-relinking and its real-world applications, European J. Oper. 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E, 88, pp. 146-166, (2016); Yu G., Qi X., Disruption Management: Framework, Models and Applications, (2004); Zhang J., Liu F., Tang J., Li Y., The online integrated order picking and delivery considering Pickers’ learning effects for an O2O community supermarket, Transp. Res. E, 123, pp. 180-199, (2019); Zhang Z., Tafreshian A., Masoud N., Modular transit: Using autonomy and modularity to improve performance in public transportation, Transp. Res. E, 141, (2020); Zhen X., Li Y., Cai G.G., Shi D., Transportation disruption risk management: Business interruption insurance and backup transportation, Transp. Res. E, 90, pp. 51-68, (2016)","I. Giménez-Palacios; Departamento de Matemáticas, University of Castilla-La Mancha, Albacete, Spain; email: ivan.gimenez@uv.es",null,"Elsevier Ltd",{"$nulls":5},1.3665545E7,null,null,null,"English","Transp. Res. Part E Logist. Transp. Rev.","Article","Final","All Open Access; Green Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85145797446"]
["Orenstein I.; Raviv T.","Orenstein, Ido (54389722600); Raviv, Tal (8613408500)","54389722600; 8613408500","Parcel delivery using the hyperconnected service network",2022.0,"Transportation Research Part E: Logistics and Transportation Review",161.0,null,102716.0,null,null,null,3.0,"10.1016/j.tre.2022.102716","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85129458301&doi=10.1016%2fj.tre.2022.102716&partnerID=40&md5=4dbb201c1c38bec8e34365c89a6d3b23","Department of Industrial Engineering, Tel Aviv University, Israel","Orenstein I., Department of Industrial Engineering, Tel Aviv University, Israel; Raviv T., Department of Industrial Engineering, Tel Aviv University, Israel","The small parcel delivery industry is experiencing rapid growth, primarily driven by the growth of the e-commerce sector. We introduce a logistic model for delivering parcels to service points that are used as drop-off, pickup, and intermediate storage locations. A parcel may be carried from its origin to its destination in several legs via several possible intermediate service points. Such a system constitutes a hyperconnected service network (HCSN). The HCSN is a generalization of the current practice of using a hierarchical, tree-like service network (TLSN), where a parcel can switch vehicles only in a large sorting facility (hub) and a service point is served by a single route. The HCSN topology presents an opportunity to improve the delivery process by reducing the total distance that parcels are carried while still exploiting the possibility of shipment consolidation. In addition, such a system may save resources that are associated (and tied for an extended period) with the construction and operation of a large sorting facility. In this paper, we develop tools to design and operate a successful HCSN for parcel delivery – a parcel routing mechanism and a math heuristic for routing and scheduling of the vehicles that transfer the parcels in the network. The effectiveness of the proposed tools and the advantages of the HCSN are demonstrated by a simulation study. © 2022 Elsevier Ltd","Hyperconnected service network; Network design; Parcel delivery; Physical internet; Transportation and logistics; Vehicle routing","Network routing; Vehicles; E- commerces; Hyperconnected service network; Intermediate storage; Logistics model; Network design; Parcel delivery; Physical internet; Rapid growth; Services network; Transportation and logistic; electronic commerce; Internet; logistics; network design; road transport; routing; transportation planning; transportation system; Vehicle routing",{"$nulls":4},"Shlomo-Shmeltzer Institute for Smart Transportation in Tel Aviv University; Israel Science Foundation, ISF; Ministry of Science and Technology, Israel","Funding text 1: This research was supported by the Israeli Ministry of Science and Technology. ; Funding text 2: This research was supported by the Israel Science Foundation. ; Funding text 3: The first author was partially supported by a scholarship from the Shlomo-Shmeltzer Institute for Smart Transportation in Tel Aviv University. 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Res., 52, 11, pp. 3185-3208, (2014); Savelsbergh M.W.P., Sol M., The general pickup and delivery problem, Transp. Sci., 29, 1, pp. 17-29, (1995); Schobel A., Line planning in public transportation: models and methods, OR Spectrum, 34, 3, pp. 491-510, (2012); Sternberg H., Norrman A., The Physical Internet–review, analysis and future research agenda, Int. J. Phys. Distribution & Logistics Manage., 47, 8, pp. 736-762, (2017); Treiblmaier H., Mirkovski K., Lowry P.B., (2016); Toyoglu H., Karasan O.E., Kara B.Y., A new formulation approach for location-routing problems, Networks and Spatial Econ., 12, 4, pp. 635-659, (2012); Ulmer M.W., Streng S., Same-Day Delivery with Pickup Stations and Autonomous Vehicles, Comput. Oper. Res., 108, pp. 1-19, (2019); Venkatadri U., Krishna K.S., Ulku M.A., On Physical Internet logistics: modeling the impact of consolidation on transportation and inventory costs, IEEE Trans. Autom. Sci. Eng., 13, 4, pp. 1517-1527, (2016); Wasner M., Zapfel G., An integrated multi-depot hub-location vehicle routing model for network planning of parcel service, Int. J. Prod. Econ., 90, 3, pp. 403-419, (2004); Wieberneit N., Service network design for freight transportation: a review, OR Spectrum, 30, 1, pp. 77-112, (2007)","I. Orenstein; Department of Industrial Engineering, Tel Aviv University, Israel; email: ido.orenstein1986@gmail.com",null,"Elsevier Ltd",{"$nulls":5},1.3665545E7,null,null,null,"English","Transp. Res. Part E Logist. Transp. Rev.","Article","Final",null,"Scopus","2-s2.0-85129458301"]
["Masteguim R.; Cunha C.B.","Masteguim, Rhandal (57224512626); Cunha, Claudio B. (56963654600)","57224512626; 56963654600","An Optimization-Based Approach to Evaluate the Operational and Environmental Impacts of Pick-Up Points on E-Commerce Urban Last-Mile Distribution: A Case Study in São Paulo, Brazil",2022.0,"Sustainability (Switzerland)",14.0,14.0,8521.0,null,null,null,4.0,"10.3390/su14148521","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137170759&doi=10.3390%2fsu14148521&partnerID=40&md5=784d4d7d2bca0defda30c47224ff16b6","Graduate Program in Logistic Systems Engineering, Escola Politécnica, Universidade de São Paulo, Sao Paulo, 05508-220, Brazil","Masteguim R., Graduate Program in Logistic Systems Engineering, Escola Politécnica, Universidade de São Paulo, Sao Paulo, 05508-220, Brazil; Cunha C.B., Graduate Program in Logistic Systems Engineering, Escola Politécnica, Universidade de São Paulo, Sao Paulo, 05508-220, Brazil","Online sales have steadily increased in recent years. Unlike the traditional retail shopping model, e-commerce must deliver custom orders to highly dispersed locations. Consequently, negative effects have been observed in large urban and densely populated areas, such as congestion and pollution. Pick-up points (PPs) are fast-growing solutions that provide parcel delivery and picking services at diverse locations throughout major city centers. This paper describes an optimization-based approach aimed to investigate the conditions in which a network of pick-up points can be more efficient than home deliveries from operational and environmental points of view in urban last-mile distribution. Differently from the related literature, in which analytical models were employed, we use optimization and algorithms to determine the economic and environmental benefits of packages destined for pick-up points instead of home deliveries. The framework was applied to the city of São Paulo, in Brazil. Several scenarios were evaluated, comprising different densities and percentages of deliveries destined for PPs. The results show that PPs can be a promising alternative for reducing the environmental externalities, as fleet and vehicle mileage can be reduced by more than 50%. © 2022 by the authors.","e-commerce; last-mile distribution; pick-up points","Brazil; Sao Paulo [Brazil]; electronic commerce; environmental economics; environmental impact; optimization; urban area; urban transport",{"$nulls":4},"Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, CAPES; Conselho Nacional de Desenvolvimento Científico e Tecnológico, CNPq, (309424/2018-6, 88887.513264/2020-00)","The first author acknowledges CAPES (Brazil’s Coordination for the Improvement of Higher Education Personnel) and the second author Brazil’s CCP (National Council for Scientific and Technological Development) for the financial support (grant numbers 88887.513264/2020-00 and 309424/2018-6, respectively).","Chopra K., What Target Is Doing Right in The Pandemic Era E-Commerce Race. 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Manag, 11, pp. 23-31, (2014); Iwan S., Kijewska K., Lemke J., Analysis of Parcel Lockers’ Efficiency as the Last Mile Delivery Solution—The Results of the Research in Poland, Transp. Res. Procedia, 12, pp. 644-655, (2016); Lemke J., Iwan S., Korczak J., Usability of the Parcel Lockers from the Customer Perspective—The Research in Polish Cities, Transp. Res. Procedia, 16, pp. 272-287, (2016); Saad S.M., Bahadori R., Sustainability evaluation of last mile food delivery: Pick up point using lockers versus home delivery, International Food Operations and Processing Simulation Workshop (FoodOPS), pp. 37-42, (2018); Ghajargar M., Zenezini G., Montanaro T., Home delivery services: Innovations and emerging needs, IFAC-Paper, 49, pp. 1371-1376, (2016); Cardenas I.D., Dewulf W., Vanelslander T., Beckers J., Smet C., The e-commerce parcel delivery market and the implications of home B2C deliveries vs. pick-up points, Int. J. Transp. Econ, 44, pp. 235-256, (2017); Melkonyan A., Gruchmann T., Lohmar F., Kamath V., Spinler S., Sustainability assessment of last-mile logistics and distribution strategies: The case of local food networks, Int. J. Prod. Econ, 228, (2020); Rabe M., Gonzalez-Feliu J., Chicaiza-Vaca J., Tordecilla R.D., Simulation-Optimization Approach for Multi-Period Facility Location Problems with Forecasted and Random Demands in a Last-Mile Logistics Application, Algorithms, 14, (2021); Durand B., Gonzalez-Feliu J., Urban logistics and e-grocery: Have proximity delivery services a positive impact on shopping trips?, Procedia-Soc. Behav. Sci, 39, pp. 510-520, (2012); Gonzalez-Feliu J., Ambrosini C., Routhier J.L., New trends on urban goods movement: Modelling and simulation of e-commerce distribution, Eur. Transp, 50, (2012); Nemoto T., An Experimental Cooperative Parcel Pick-up System Using the Internet in the Central Business District in Tokyo, Logistics Systems for Sustainable Cities, pp. 309-320, (2004); Hayashi K., Nemoto T., Visser J.J., E-commerce and city logistics solution, City Logistics: Mapping the Future, pp. 56-78, (2014); Gata V., Marcucci E., Nigro M., Patella S.M., Serafini S., Public transport-based crowdshipping for sustainable city logistics: Assessing economic and environmental impacts, Sustainability, 11, (2018); Kiba-Janiak M., Marcinkowski J., Jagoda A., Skowronska A., Sustainable last mile delivery on e-commerce market in cities from the perspective of various stakeholders, Lit. Rev. Sustain. Cities Soc, 71, (2021); Braekers K., Ramaekers K., Van Nieuwenhuyse I., The vehicle routing problem: State of the art classification and review, Comput. Ind. 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Eng, 1, pp. 453-480, (2010); Longhurst J.W., Brebbia C.A., Urban Transport and the Environment in the 21st Century, (2013); Laranjeiro P.F., Merchan D., Godoy L.A., Giannotti M., Yoshizaki H.T.Y., Winkenbach M., Cunha C.B., Using GPS data to explore speed patterns and temporal fluctuations in urban logistics: The case of São Paulo, Brazil, J. Transp. Geogr, 76, pp. 114-129, (2019); Merchan D., Winckenbach M., An empirical validation and data-driven extension of continuum approximation approaches for urban route distances, Netwoks, 73, pp. 418-433, (2019)","R. Masteguim; Graduate Program in Logistic Systems Engineering, Escola Politécnica, Universidade de São Paulo, Sao Paulo, 05508-220, Brazil; email: rhandal_fm@hotmail.com",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85137170759"]
["de Araújo F.A.; Dos Reis J.G.M.; da Silva M.T.; Aktas E.","de Araújo, Fernanda Alves (57191034019); Dos Reis, João Gilberto Mendes (36665996500); da Silva, Marcia Terra (25930759000); Aktas, Emel (14059584200)","57191034019; 36665996500; 25930759000; 14059584200","A Fuzzy Analytic Hierarchy Process Model to Evaluate Logistics Service Expectations and Delivery Methods in Last-Mile Delivery in Brazil",2022.0,"Sustainability (Switzerland)",14.0,10.0,5753.0,null,null,null,8.0,"10.3390/su14105753","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85130414633&doi=10.3390%2fsu14105753&partnerID=40&md5=c1dd3094719d81135dc71b329612851f","Postgraduate Program in Production Engineering, Universidade Paulista—UNIP, SP, Sao Paulo, 04026-002, Brazil; Postgraduate Program in Business Administration, Universidade Paulista—UNIP, SP, Sao Paulo, 04026-002, Brazil; Social and Applied Sciences Center, Mackenzie Presbyterian University—MPU, SP, Sao Paulo, 01302-907, Brazil; Cranfield School of Management, Cranfield University, College Road, Cranfield, MK43 0AL, United Kingdom","de Araújo F.A., Postgraduate Program in Production Engineering, Universidade Paulista—UNIP, SP, Sao Paulo, 04026-002, Brazil; Dos Reis J.G.M., Postgraduate Program in Production Engineering, Universidade Paulista—UNIP, SP, Sao Paulo, 04026-002, Brazil, Postgraduate Program in Business Administration, Universidade Paulista—UNIP, SP, Sao Paulo, 04026-002, Brazil, Social and Applied Sciences Center, Mackenzie Presbyterian University—MPU, SP, Sao Paulo, 01302-907, Brazil; da Silva M.T., Postgraduate Program in Production Engineering, Universidade Paulista—UNIP, SP, Sao Paulo, 04026-002, Brazil; Aktas E., Cranfield School of Management, Cranfield University, College Road, Cranfield, MK43 0AL, United Kingdom","Nowadays, postal services and third-party logistics services (3PL) have been pressured by the increasing demand for delivery services. Therefore, they need to improve their last-mile delivery strategies to meet customers’ expectations. This paper aims to investigate how logistics service expectations affect the delivery process in urban areas using a multiple-criteria decision support system based on the Fuzzy Analytic Hierarchy Process (FAHP). We developed a decision-making model employing six criteria and five delivery methods indicated in the literature and collected information from 27 experts working in academia and local and multinational third-party logistics providers in Brazil to validate this model. The results indicate that cost (21.4%) and tracking and tracing (19.3%) are the most important two criteria in the decision model, and the best delivery methods are smart lockers (21.8%) followed by small trucks (21.3%). Our results suggest that service expectations regarding last-mile delivery are aligned with extensive use of road transport and the increase in e-commerce sales can raise greenhouse gas emissions and compromise the environment in urban areas. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.","Analytical Hierarchy Process; B2C; Brazilian e-commerce; fuzzy logic; last-mile delivery; small parcels","Brazil; analytical hierarchy process; decision support system; electronic commerce; fuzzy mathematics; greenhouse gas; logistics; road transport; tracking; urban area",{"$nulls":4},"Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, CAPES, (001)","Funding: This research was funded by CAPES, grant number 001.","Allen J., Piecyk M., Piotrowska M., McLeod F., Cherrett T., Ghali K., Nguyen T., Bektas T., Bates O., Friday A., Et al., Understanding the impact of e-commerce on last-mile light goods vehicle activity in urban areas: The case of London, Transp. Res. Part D Transp. 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Res, 28, pp. 47-63, (2018); Petrobras Reajustou Gasolina e Diesel 13 Vezes no último ano; Alta Recente é a Maior; Maxner T., Dalla Chiara G., Goodchild A., Identifying the Challenges to Sustainable Urban Last-Mile Deliveries: Perspectives from Public and Private Stakeholders, Sustainability, 14, (2022); Suatmadi A.Y., Creutzig F., Otto I.M., On-Demand Motorcycle Taxis Improve Mobility, Not Sustainability, Case Stud. Transp. Policy, 7, pp. 218-229, (2019); Tang C.S., Veelenturf L.P., The strategic role of logistics in the industry 4.0 era, Transp. Res. Part E Logist. Transp. Rev, 129, pp. 1-11, (2019); Manners-Bell J., Future of Logistics, (2019); Delfmann W., ten Hompel M., Kersten W., Logistics as a Science—Central Research Questions in the Era of the Fourth Industrial Revolution, Logist. Res, 11, pp. 1-13, (2018); Schwab K., Zahidi S., McLennan M., The Global Risks Report 2021, (2021); Kedia A., Kusumastuti D., Nicholson A., Establishing Collection and Delivery Points to Encourage the Use of Active Transport: A Case Study in New Zealand Using a Consumer-Centric Approach, Sustainability, 11, (2019)","F.A. de Araújo; Postgraduate Program in Production Engineering, Universidade Paulista—UNIP, Sao Paulo, SP, 04026-002, Brazil; email: fernanda.logistica@gmail.com; J.G.M. Dos Reis; Postgraduate Program in Production Engineering, Universidade Paulista—UNIP, Sao Paulo, SP, 04026-002, Brazil; email: joao.reis@docente.unip.br",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85130414633"]
["Zhang Q.; Mao H.","Zhang, Qianli (57712091800); Mao, Haijun (7201796677)","57712091800; 7201796677","An Integrated Method for Locating Logistic Centers in a Rural Area",2022.0,"Sustainability (Switzerland)",14.0,9.0,5563.0,null,null,null,1.0,"10.3390/su14095563","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85130768154&doi=10.3390%2fsu14095563&partnerID=40&md5=f5d5819744a6f021e07ec8b6fdb02dd5","School of Transportation, Southeast University, Nanjing, 211189, China","Zhang Q., School of Transportation, Southeast University, Nanjing, 211189, China; Mao H., School of Transportation, Southeast University, Nanjing, 211189, China","Transport has long been considered a concern for rural residents around the world. Rural express logistics, one of the transport topics, is associated with rural residents’ convenience as well as e-commerce development. As key nodes in the network, logistic centers need to be properly located to improve the delivery efficiency. This paper provides an integrated method for locating logistic centers which is of strong feasibility: on one hand, the proposed method seeks to maximize coverage of express service; on the other hand, considerations are given to operational profitability of the centers, ensuring overall viability for the plan. Specifically, the Holt–Winters model is used for demand prediction. Total predicted demand is then allocated to each town according to population, gross regional product, and some other indicators. A maximal covering model is applied to select logistic centers based on demand under different service radius and numbers of logistic centers. Revenue evaluation is then conducted for the selected logistic centers to evaluate their future operating conditions. The proposed method is applied in rural areas in Lhasa, China. Numerical analysis suggested that 12 of the selected 22 logistic centers could make a profit by 2025. Finally, policy recommendations are given for the development of rural logistic systems. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.","Holt–Winters model; logistics network design; maximal covering model; revenue evaluation; rural logistics","California; China; Lhasa; United States; Winters; Xizang; electronic commerce; logistics; numerical model; profitability; rural area; viability",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (71901059); Natural Science Foundation of Jiangsu Province, (BK20210250)","Funding: This research and the APC was funded by the Natural Science Foundation of Jiangsu Province in China (BK20210250) and the National Natural Science Foundation of China (71901059).","George B., Henry G., John R., Rural Transport: Improving Its Contribution to Growth and Poverty Reduction in Sub-Saharan Africa, (2012); Paul S., Simon E., John H., Anna T., Improving Rural Mobility: Options for Developing Motorized and Nonmotorized Transport in Rural Areas, (2002); Peter R., Shyam K.C., Cordula R., Rural Access Index: A Key Development Indicator, (2006); Rural Communities Expanding Horizons: The Benefits of Public Transportation, (2012); Enoch M.P., Cross R., Potter N., Davidson C., Taylor S., Brown R., Huang H., Parsons J., Tucker S., Wynne E., Et al., Future local passenger transport system scenarios and implications for policy and practice, Transp. Policy, 90, pp. 52-67, (2020); Donnges C., Rural Transport and Local Government Units: How to Improve Rural Transport for the Rural Poor, (2001); Vitale Brovarone E., Cotella G., Improving rural accessibility: A multilayer approach, Sustainability, 12, (2022); Fu H., Li H., Research on the Optimization of Rural Logistics Development in Henan Province, Int. J. Soc. Sci. Educ. Res, 3, pp. 181-185, (2020); Jin E.T., Research on Innovation of Agricultural Products Circulation System under Digital Rural Strategy, (2020); Wang M., Chen X., Analysis of influencing factors of urban and rural logistics distribution in Hainan province based on AHP, China Tequ Econ, 11, pp. 81-86, (2020); Li X., Ramshani M., Huang Y., Cooperative maximal covering models for humanitarian relief chain management, Comput. Ind. 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J. Forecast, 17, pp. 269-286, (2001); Ripley B.D., Pattern Recognition and Neural Networks, (2009)","H. Mao; School of Transportation, Southeast University, Nanjing, 211189, China; email: maohaijun@seu.edu.cn",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85130768154"]
["Meng G.","Meng, Gaofei (57829594300)",5.78295943E10,"E-Commerce Logistics System Based on Discrete Dynamic Modeling Analysis",2022.0,"Frontiers in Energy Research",10.0,null,930999.0,null,null,null,0.0,"10.3389/fenrg.2022.930999","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135371027&doi=10.3389%2ffenrg.2022.930999&partnerID=40&md5=121440037b5cbafe87fd6eedc911f1df","Hebei Chemical and Pharmaceutical College, Shijiazhuang, China","Meng G., Hebei Chemical and Pharmaceutical College, Shijiazhuang, China","The development of green logistics in a low-carbon environment is an important way for logistics companies to reduce operating costs, and it is also a strategic measure to strengthen the construction of ecological civilization. This study improves the bat algorithm for single-delivery express delivery and multi-delivery, determines the optimal target and seeks the optimal solution, establishes the optimal logistics distribution scheme combined with corporate profits, and finally, compares it with other algorithms to verify the feasibility of the model. In the same experimental environment, it is proven that the performance of the built model is about 20% higher than that of other methods, and the planned path is the most reasonable. In the future application of e-commerce logistics system, it is a more efficient, reasonable, and perfect discrete logistics model. Copyright © 2022 Meng.","bat algorithm; discrete dynamic modeling; e-commerce; energy conservation and emission reduction; logistics system; low-carbon environment","Carbon; Electronic commerce; Emission control; Bat algorithms; Discrete dynamic models; Dynamic model analysis; E- commerces; Energy conservation and emission reductions; Green logistics; Logistics company; Logistics system; Low carbon; Low-carbon environment; Operating costs",{"$nulls":6},"Asokan A., Popescu D.E., Jude A., Hemanth J., Bat Algorithm Based Non-linear Contrast Stretching for Satellite Image Enhancement, Geosciences, 10, 2, pp. 45-50, (2020); Atefi R., Salari M., Coelho L.C., Renaud J., The Open Vehicle Routing Problem with Decoupling Points, Eur. J. Operat. Res, 7, 4, (2018); Bayzid M.S., Warnow T., Gene Tree Parsimony for Incomplete Gene Trees: Addressing True Biological Loss, Algori. Mol. Biol, 13, 8, pp. 1-106, (2018); Cai X., Wang L., Kang Q., Wu Q., Bat Algorithm with Gaussian Walk, Ijbic, 6, 3, pp. 166-174, (2014); Chen H., The Promotion and Optimization of Big Data Analysis on E-Commerce Marketing, Chin. Mark, 1009, 18, pp. 136-137, (2019); Chen R., Shen Y.-M., Hong W., Neural-like Encoding Particle Swarm Optimization for Periodic Vehicle Routing Problems, Expert Syst. Appl, 138, (2019); Dantzig G., Ramser J.H., The Truck Dispatching Problem, Manag. Sci, 6, 1, pp. 80-91, (2021); Eliguzel N., Cetinkaya C., Dereli T., A Novel Approach for Text Categorization by Applying Hybrid Genetic Bat Algorithm through Feature Extraction and Feature Selection Methods, Expert Syst. Appl, 202, (2022); Fachini R., Armentano V., Exact and Heuristic Dynamic Programming Algorithms for the Traveling Salesman Problem with Flexible Time Windows, Optim. 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J, 90, 1, pp. 22-27, (2020); Wu Y., Guo Y., Toyoda M., Policy Iteration Approach to the Infinite Horizon Average Optimal Control of Probabilistic Boolean Networks, IEEE Trans. Neural Netw. Learn Syst, 32, 6, pp. 2910-2924, (2021); Yong J., He F., Li H., Zhou W., A Novel Bat Algorithm Based on Cross Boundary Learning and Uniform Explosion Strategy, Appl. Math. A J. Chin. Univ, 34, 4, pp. 480-502, (2019); Zhang L.P., Chai Y., Improved Genetic Algorithm for Vehicle Routing Problem, Comput. Eng. Appl, 13, 13, pp. 203-206, (2010); Zhang W., Hu Y., He H., Liu Y., Chen A., Linear and Dynamic Programming Algorithms for Real-Time Task Scheduling with Task Duplication, J. Supercomput, 75, 2, pp. 82-89, (2019); Zhang Y., Qian T., Tang W., Buildings-to-distribution-network Integration Considering Power Transformer Loading Capability and Distribution Network Reconfiguration, Energy, 244, (2022); Zheng F., Pang Y., Liu M., Xu Y., Dynamic Programming Algorithms for the General Quay Crane Double-Cycling Problem with Internal-Reshuffles, J. Comb. Optim, 39, 3, pp. 430-440, (2020)","G. Meng; Hebei Chemical and Pharmaceutical College, Shijiazhuang, China; email: menggaofei1@163.com",null,"Frontiers Media S.A.",{"$nulls":5},"2296598X",null,null,null,"English","Front. Energy Res.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85135371027"]
["Kang X.; Pang H.","Kang, Xinyue (57431131600); Pang, Haiyun (57644482800)","57431131600; 57644482800","City selection for fresh produce e-commerce's market entry strategy: Based on the perspective of urban logistics competitiveness",2022.0,"Transportation Research Interdisciplinary Perspectives",13.0,null,100537.0,null,null,null,7.0,"10.1016/j.trip.2022.100537","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85123689628&doi=10.1016%2fj.trip.2022.100537&partnerID=40&md5=1180f76e1caec87ed1de0cbcf323768a","School of Business and Economics, Zhejiang University of Science and Technology, 318 Liu He Street, Hangzhou, 310012, China","Kang X., School of Business and Economics, Zhejiang University of Science and Technology, 318 Liu He Street, Hangzhou, 310012, China; Pang H., School of Business and Economics, Zhejiang University of Science and Technology, 318 Liu He Street, Hangzhou, 310012, China","Urban logistics is critical for fresh produce e-commerce (FPE), and the impressive advancement of urban logistics takes a leading role in increasing online grocery player's competitiveness. This research analyzes the characteristics of logistics of fresh food e-commerce and constructs an evaluation index of city logistics competitiveness (CLC), also known as urban logistics competitiveness (ULC) based on basic requirement scale, efficiency enhancers level and technology and innovation level. Observing thirty-seven cities in China's Yangtze River Delta, we evaluate and classify their urban logistics competitiveness score through the improved TODIM (an acronym in Portuguese of interactive and multiple attribute decision making) method: entropy weight-TODIM method and K-means cluster analysis using MATLAB software. Through TODIM calculation and clustering evaluation, four groups of cities are extracted and suggestions on new market entry strategiesto the fresh food e-commerce industry are provided. © 2022","Fresh produce e-commerce; K-means cluster analysis; Multi-criteria decision-making method; Urban logistics competitiveness",{"$nulls":7},"Awasthi A., Chauhan S.S., A hybrid approach integrating Affinity Diagram, AHP and fuzzy TOPSIS for sustainable city logistics planning, Appl. Math. Modell., 36, 2, pp. 573-584, (2012); Blitstein J.L., Frentz F., Jilcott Pitts S.B., A mixed-method examination of reported benefits of online grocery shopping in the united states and Germany: is health a factor?, J. Food Products Market., 26, 3, pp. 212-224, (2020); Buldeo Rai H., Verlinde S., Macharis C., City logistics in an omnichannel environment. 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Manuf., 28, 1, pp. 229-243, (2017); (2017); Wu Z., Huang S., Hu W., Research on the selection of green building projects based on combination weighting-improved topsis, Method J. World Sci. Res. J., 6, (2020); Xu W., Gong X., Factor cluster analysis of qingdao port logistics competitiveness, Logistics, 4, (2020); Zhou P., Research on the accounting supervision management in bidding and tendering for enterprise materials supplies, Proc. Eng., 37, pp. 58-63, (2012)","H. Pang; School of Business and Economics, Zhejiang University of Science and Technology, Hangzhou, 318 Liu He Street, 310012, China; email: 102073@zust.edu.cn",null,"Elsevier Ltd",{"$nulls":5},2.5901982E7,null,null,null,"English","Transp.  Res.  Interdiscip.  Perspect.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85123689628"]
["Yu B.; Shan W.; Sheu J.-B.; Diabat A.","Yu, Bin (35774921200); Shan, Wenxuan (57191261264); Sheu, Jiuh-Biing (7201928686); Diabat, Ali (26646404900)","35774921200; 57191261264; 7201928686; 26646404900","Branch-and-price for a combined order selection and distribution problem in online community group-buying of perishable products",2022.0,"Transportation Research Part B: Methodological",158.0,null,null,341.0,373.0,32.0,7.0,"10.1016/j.trb.2022.03.001","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85125838257&doi=10.1016%2fj.trb.2022.03.001&partnerID=40&md5=58e6720b19583dc054840fa6bf315673","School of Transportation Science and Engineering, Beihang University, Beijing, China; BDBC, Beihang University, Beijing, 100191, China; Department of Business Administration, National Taiwan University, No.1, Sec.4, Roosevelt Road, Taipei, 106, Taiwan; Division of Engineering, New York University Abu Dhabi, Saadiyat Island, Abu Dhabi, 129188, United Arab Emirates; Department of Civil and Urban Engineering, Tandon School of Engineering, New York University, Brooklyn, 11201, NY, United States","Yu B., School of Transportation Science and Engineering, Beihang University, Beijing, China, BDBC, Beihang University, Beijing, 100191, China; Shan W., School of Transportation Science and Engineering, Beihang University, Beijing, China, BDBC, Beihang University, Beijing, 100191, China; Sheu J.-B., Department of Business Administration, National Taiwan University, No.1, Sec.4, Roosevelt Road, Taipei, 106, Taiwan; Diabat A., Division of Engineering, New York University Abu Dhabi, Saadiyat Island, Abu Dhabi, 129188, United Arab Emirates, Department of Civil and Urban Engineering, Tandon School of Engineering, New York University, Brooklyn, 11201, NY, United States","As a new social e-commerce model, online community group-buying of perishable products has been under examined. This paper addresses a real-world delivery problem faced in common by an online community group-buying operators, in which operators may suffer revenue loss from product deterioration during delivery. Since delivery quantities of candidate orders may be beyond capacity resources, this paper investigates a new combined order selection and periodic vehicle routing problem with time windows for perishable products. An online community group-buying operator can design daily online community group-buying delivery plan by deciding to serve which customers, to deliver which products and delivery quantities to be transported. To solve this problem, we propose a branch-and-price algorithm that strongly relies on a new label setting algorithm with partial label dominance and a strong bounding strategy based on the definition of Pareto-optimal delivery patterns. Since en-route delivery quantities depend on the interval between two consecutive services, our label setting algorithm is also applicable to the pricing subproblem for the discrete split delivery vehicle routing problem. We conduct a case study on a real-world instance and propose management insights into the structure of delivery plan facing inadequate capacity resources. Numerical experiments on 64 randomly generated instances demonstrate the effectiveness of the proposed branch-and-price algorithm. © 2022 Elsevier Ltd","Branch-and-price; Discrete split delivery; Multi-commodity; Multi-period; Perishability; Vehicle routing problem with profits","Costs; Deterioration; Electronic commerce; Integer programming; Pareto principle; Product design; Social networking (online); Branch and price; Discrete split delivery; Multi-commodity; Multi-period; On-line communities; Perishability; Routing problem with profits; Split delivery; Vehicle routing problem with profit; Vehicle Routing Problems; algorithm; commodity market; consumption behavior; electronic commerce; model; optimization; Vehicle routing",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (MOST 108-2410-H-002-225-MY3, U1811463); Ministry of Science and Technology, Taiwan, MOST","This research was supported in National Natural Science Foundation of China ( U1811463 ). This work was also supported by Grant MOST 108-2410-H-002-225-MY3 from the Ministry of Science and Technology of Taiwan, R.O.C. ","Abbasi B., Mirzazadeh A., Mohammadi M., Multi stage investment planning and customer selection in a two echelon multi-period supply chain, Sci. Iran., 26, 5, pp. 3032-3050, (2018); Alessandra F., Karina Olbrich D.S., Magali M., Consumer interpretation of ready to drink orange juice and nectar labelling, Int. J. Food Sci. Technol., 48, 6, pp. 1296-1302, (2013); Alkaabneh F., Diabat A., Gao H.O., Benders decomposition for the inventory vehicle routing problem with perishable products and environmental costs, Comput. Oper. Res., 113, (2020); Amorim P., Belo-Filho M.A.F., Toledo F.M.B., Almeder C., Almada-Lobo B., Lot sizing versus batching in the production and distribution planning of perishable goods, Int. J. Prod. 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Res., 170, 1, pp. 24-43, (2006); Yan S., Chu J.C., Hung W.C., A customer selection and vehicle scheduling model for moving companies, Transp. Lett., 12, 9, pp. 613-622, (2020); Yao B., Chen C., Song X., Yang X., Fresh seafood delivery routing problem using an improved ant colony optimization, Ann. Oper. Res., 273, 1, pp. 163-186, (2019); Zhang G., Shang J., Yildirim P., Optimal pricing for group buying with network effects, Omega, 63, pp. 69-82, (2016); Zhang L., Chen T., Yu B., Wang C., Suburban demand responsive transit service with rental vehicles, IEEE Trans. Intell. Transp. Syst., 22, 4, pp. 2391-2403, (2021)","J.-B. Sheu; Department of Business Administration, National Taiwan University, Taipei, No.1, Sec.4, Roosevelt Road, 106, Taiwan; email: jbsheu@ntu.edu.tw",null,"Elsevier Ltd",{"$nulls":5},1912615.0,null,null,null,"English","Transp. Res. Part B Methodol.","Article","Final",null,"Scopus","2-s2.0-85125838257"]
["Su Q.; Xiong Y.; Cui T.; Xiao J.","Su, Qingmu (57216761807); Xiong, Yihan (57482509500); Cui, Teng (57482349000); Xiao, Jingjing (57880291600)","57216761807; 57482509500; 57482349000; 57880291600","Research on the Differences of Location Characteristics between Offline and Online Catering Spaces Under O2O E-Commerce",2022.0,"Environment and Urbanization ASIA",13.0,1.0,null,153.0,167.0,14.0,2.0,"10.1177/09754253221076350","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85126062735&doi=10.1177%2f09754253221076350&partnerID=40&md5=58f2fc42e7248b93d6660ca82121b5c4","School of Architecture and Planning, Fujian University of Technology, Fuzhou, China; China Academy of Urban Planning Design, Beijing, China; Department of Urban Planning, National Cheng Kung University, Tainan, China; Department of Earth Sciences, National Cheng Kung University, Tainan, China","Su Q., School of Architecture and Planning, Fujian University of Technology, Fuzhou, China; Xiong Y., China Academy of Urban Planning Design, Beijing, China; Cui T., Department of Urban Planning, National Cheng Kung University, Tainan, China; Xiao J., Department of Earth Sciences, National Cheng Kung University, Tainan, China","The development of O2O (online to offline) e-commerce and instant delivery has not only made it easy to access information, but also it has overcome the limitation of walking distance, promoting the transformation of traditional commercial space and making online catering a common form of food consumption. Studying the spatial distribution of urban catering industry under new technologies is helpful to understand the current development of the catering industry, which is of great significance for guiding the development of the catering industry. However, the trend and mechanism of changes need to be further studied. Based on the spatial distribution of urban catering industry, this study establishes a framework for analysing offline and online catering spaces. In this framework, big data are used to conduct GIS kernel density analysis and spatial autocorrelation analysis to investigate the spatial distribution laws of the catering industry, and multinomial logistic regression analysis is applied to explore the main factors influencing location selection of offline and online catering spaces. The main results include the following: (a) the new pattern of catering space still follows the traditional location selection theory and (b) population density and road network density are the main factors affecting the catering space in Shenzhen. © 2022 National Institute of Urban Affairs.","location difference; multinomial logistic regression; Offline catering; online catering; spatial density","autocorrelation; data set; electronic commerce; GIS; regression analysis; spatial distribution; technology adoption; urban area",{"$nulls":4},"National Office for Philosophy and Social Sciences, NPOPSS, (21CSS001)","The APC was funded by Youth project of National Social Science Foundation of China [21CSS001].","Boschma R., Weltevreden J., The evolutionary nature of b2c e-commerce in inner cities, (2011); Builes-Jaramillo A., Lotero L., Closeness matters. 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Wang S., Hao F., Jiang L., Locations and their determinants of large-scale commercial sites in Changchun, China, Acta Geographica Sinica, 70, 6, pp. 893-905, (2015); Wang Z., Ginzler C., Waser L.T., Assessing structural changes at the forest edge using kernel density estimation, Forest Ecology and Management, 456, (2020); Wu X., Nie L., Xu M., Zhao L., Distribution planning problem for a high-speed rail catering service considering time-varying demands and pedestrian congestion: A lot-sizing-based model and decomposition algorithm, Transportation Research Part E: Logistics and Transportation Review, 123, pp. 61-89, (2019); Xi G., Cao X., Zhen F., The impacts of same day delivery online shopping on local store shopping in Nanjing, China, Transportation Research Part A: Policy and Practice, 136, 1, pp. 35-47, (2020); Xia C., Yeh A.G.O., Zhang A., Analyzing spatial relationships between urban land use intensity and urban vitality at street block level: A case study of five Chinese megacities, Landscape and Urban Planning, 193, (2020); Xia C., Zhang A., Wang H., Yeh A.G.O., Predicting the expansion of urban boundary using space syntax and multivariate regression model, Habitat International, 86, 2, pp. 126-134, (2019); Xiao C., Chen W., Yuan F., Cheng S., Spatial pattern and location decision of chain supermarkets within large cities: A case study of Suguo supermarkets in Nanjing, Geographical Research, 32, pp. 465-475, (2013); Yang Y., Gong Y., Land L.P.W., Chesney T., Understanding the effects of physical experience and information integration on consumer use of online to offline commerce, International Journal of Information Management, 51, (2020); Zhang C., Research on the O2O logistics distribution strategy and assessment of takeout catering, (2017); Zhu Q., Wu J., Li X., Xiong B., China’s regional natural resource allocation and utilization: A DEA-based approach in a big data environment, Journal of Cleaner Production, 142, pp. 809-818, (2017)","T. Cui; Department of Urban Planning, National Cheng Kung University, Tainan, China; email: 401746617@qq.com",null,"Sage Publications India Pvt. Ltd",{"$nulls":5},9754253.0,null,null,null,"English","Environ. Urban ASIA","Article","Final",null,"Scopus","2-s2.0-85126062735"]
["Giuffrida N.; Fajardo-Calderin J.; Masegosa A.D.; Werner F.; Steudter M.; Pilla F.","Giuffrida, Nadia (57194461021); Fajardo-Calderin, Jenny (55680892400); Masegosa, Antonio D. (24344824700); Werner, Frank (57014525200); Steudter, Margarete (57680069500); Pilla, Francesco (54411156200)","57194461021; 55680892400; 24344824700; 57014525200; 57680069500; 54411156200","Optimization and Machine Learning Applied to Last-Mile Logistics: A Review",2022.0,"Sustainability (Switzerland)",14.0,9.0,5329.0,null,null,null,17.0,"10.3390/su14095329","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85129868425&doi=10.3390%2fsu14095329&partnerID=40&md5=5e169d8a7d4ce0373ca0ef17c369f0ee","School of Architecture, Planning and Environmental Policy, University College Dublin, Richview Campus, Belfield, Dublin, D04 V1W8, Ireland; DeustoTech, Faculty of Engineering, University of Deusto, Av. Universidades 24, Bilbao, 48007, Spain; Software AG, Altenkesseler Straße 17, Saarbrücken, 66115, Germany","Giuffrida N., School of Architecture, Planning and Environmental Policy, University College Dublin, Richview Campus, Belfield, Dublin, D04 V1W8, Ireland; Fajardo-Calderin J., DeustoTech, Faculty of Engineering, University of Deusto, Av. Universidades 24, Bilbao, 48007, Spain; Masegosa A.D., DeustoTech, Faculty of Engineering, University of Deusto, Av. Universidades 24, Bilbao, 48007, Spain; Werner F., Software AG, Altenkesseler Straße 17, Saarbrücken, 66115, Germany; Steudter M., Software AG, Altenkesseler Straße 17, Saarbrücken, 66115, Germany; Pilla F., School of Architecture, Planning and Environmental Policy, University College Dublin, Richview Campus, Belfield, Dublin, D04 V1W8, Ireland","The growth in e-commerce that our society has faced in recent years is changing the view companies have on last-mile logistics, due to its increasing impact on the whole supply chain. New technologies are raising users’ expectations with the need to develop customized delivery experiences; moreover, increasing pressure on supply chains has also created additional challenges for suppliers. At the same time, this phenomenon generates an increase in the impact on the liveability of our cities, due to traffic congestion, the occupation of public spaces, and the environmental and acoustic pollution linked to urban logistics. In this context, the optimization of last-mile deliveries is an imperative not only for companies with parcels that need to be delivered in the urban areas, but also for public administrations that want to guarantee a good quality of life for citizens. In recent years, many scholars have focused on the study of logistics optimization techniques and, in particular, the last mile. In addition to traditional optimization techniques, linked to the disciplines of operations research, the recent advances in the use of sensors and IoT, and the consequent large amount of data that derives from it, are pushing towards a greater use of big data and analytics techniques—such as machine learning and artificial intelligence—which are also in this sector. Based on this premise, the aim of this work is to provide an overview of the most recent literature advances related to last-mile delivery optimization techniques; this is to be used as a baseline for scholars who intend to explore new approaches and techniques in the study of last-mile logistics optimization. A bibliometric analysis and a critical review were conducted in order to highlight the main studied problems, the algorithms used, and the case studies. The results from the analysis allow the studies to be clustered into traditional optimization models, machine learning approaches, and mixed methods. The main research gaps and limitations of the current literature are assessed in order to identify unaddressed challenges and provide research suggestions for future ap-proaches. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.","city logistics; freight transport; vehicle routing problem","electronic commerce; freight transport; literature review; machine learning; public administration; quality of life; urban area",{"$nulls":4},"Horizon 2020 Framework Programme, H2020, (861540); European Commission, EC, (H2020MG-2018-2020); Royal Irish Academy, RIA","Funding: This article was partially funded by the European Commission through the SENATOR project (H2020MG-2018-2020, RIA, project n. 861,540).","E-Commerce Statistics for Individuals, (2021); Sustainable Urban Logistics. 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Giuffrida; School of Architecture, Planning and Environmental Policy, University College Dublin, Dublin, Richview Campus, Belfield, D04 V1W8, Ireland; email: nadia.giuffrida@ucd.ie",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85129868425"]
["Luo R.; Ji S.; Ji Y.","Luo, Rongjuan (57203231891); Ji, Shoufeng (15119083600); Ji, Yuanyuan (57416784300)","57203231891; 15119083600; 57416784300","An active-learning Pareto evolutionary algorithm for parcel locker network design considering accessibility of customers",2022.0,"Computers and Operations Research",141.0,null,105677.0,null,null,null,12.0,"10.1016/j.cor.2021.105677","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85123027630&doi=10.1016%2fj.cor.2021.105677&partnerID=40&md5=c748f740d6b9bbe59464608b12fa43a0","School of Logistics, Yunnan University of Finance and Economics, Kunming, 650221, China; School of Business Administration, Northeastern University, Shenyang, 110167, China","Luo R., School of Logistics, Yunnan University of Finance and Economics, Kunming, 650221, China; Ji S., School of Business Administration, Northeastern University, Shenyang, 110167, China; Ji Y., School of Business Administration, Northeastern University, Shenyang, 110167, China","The parcel delivery, which is one of the most important components in urban last-mile logistics, has been an increasing challenge with the rapid growth of e-commerce. To improve the efficiency of urban last-mile logistics, parcel locker has been widely advocated as an innovative alternative to the parcel delivery. In this paper, we concentrate on a multi-objective parcel locker network design problem (MOPLNDP), which is motivated by a real-life network design problem in urban last-mile logistics. The ultimate goal of MOPLNDP is to optimize the total cost of the network and the accessibility of customers to parcel locker stations, which is different from previous network design problems in logistics systems. Firstly, we establish the mathematical model of MOPLNDP based on which relevant problem-specific solution properties and heuristics are presented. Secondly, an active-learning Pareto evolutionary algorithm (ALPEA) is proposed to solve MOPLNDP. The proposed ALPEA relies on an elitist nondominated sorting method to discover promising search regions and a novel active-learning refinement mechanism to intensively find high-quality solutions in given search regions. Finally, experimental results on 70 random instances with different scales and a real-life case study are reported, from which the encouraging numerical results and management insights are obtained. © 2021 Elsevier Ltd","Accessibility; Active learning; Multi-objective optimization; Parcel locker network design; Urban last-mile logistics","Artificial intelligence; Evolutionary algorithms; Learning algorithms; Learning systems; Locks (fasteners); Urban growth; Active Learning; Last mile; Multi objective; Multi-objectives optimization; Network design; Network design problems; Parcel delivery; Parcel locker network design; Search region; Urban last-mile logistic; Multiobjective optimization",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (71572031, 71971049)","This work was partially supported by the National Natural Science Foundation of China (Grant Numbers 71971049 and 71572031 ).","Arulselvan A., Bley A., Ljubic I., The incremental connected facility location problem, Comput. 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Heuristics, 18, pp. 91-118, (2012); Syam S., Cote M.J., A location-allocation model for service providers with application to not-for-profit health care organizations, Omega, 38, 3-4, pp. 157-166, (2010); Tsai Y.T., Tiwasing P., Customers’ intention to adopt smart lockers in last-mile delivery service: A multi-theory perspective, (2021); Ulmer M.W., Streng S., Same-day delivery with pickup stations and autonomous vehicles, Comput. Oper. Res., 108, pp. 1-19, (2019); Vakulenko Y., Hellstrom D., Hjort K., What's in the parcel locker? Exploring customer value in e-commerce last mile delivery, J. Bus. Res., 88, 7, pp. 421-427, (2018); Wang F., Tang Q., Planning toward equal accessibility to services: a quadratic programming approach, Environ. Plann. B Plann. Design., 40, 2, pp. 195-212, (2013); Wang Y., Ong T., Lee L.H., Chew E.P., Capacitated competitive facility location problem of self-collection lockers by using public big data, The 13th IEEE Conference on Automation Science and Engineering, (2017); Zhang Q., Li H., MOEA/D: A multiobjective evolutionary algorithm based on decomposition, IEEE Trans. Evol. Comput., 11, 6, pp. 712-731, (2007)","S. Ji; School of Business Administration, Northeastern University, Shenyang, 110167, China; email: sfji@mail.neu.edu.cn",null,"Elsevier Ltd",{"$nulls":5},3050548.0,null,"CMORA",null,"English","Comp. Oper. Res.","Article","Final",null,"Scopus","2-s2.0-85123027630"]
["Alharbi A.; Cantarelli C.; Brint A.","Alharbi, Ahmad (57425936000); Cantarelli, Chantal (35730797500); Brint, Andrew (6602457419)","57425936000; 35730797500; 6602457419","Crowd Models for Last Mile Delivery in an Emerging Economy",2022.0,"Sustainability (Switzerland)",14.0,3.0,1401.0,null,null,null,7.0,"10.3390/su14031401","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85123412844&doi=10.3390%2fsu14031401&partnerID=40&md5=1c6b80af671534ad0adfa21833d7decb","Management School, University of Sheffield, Sheffield, S10 1FL, United Kingdom","Alharbi A., Management School, University of Sheffield, Sheffield, S10 1FL, United Kingdom; Cantarelli C., Management School, University of Sheffield, Sheffield, S10 1FL, United Kingdom; Brint A., Management School, University of Sheffield, Sheffield, S10 1FL, United Kingdom","The dramatic rise in online shopping means that the last mile delivery (LMD) task is becoming extremely important. However, last mile delivery faces many economic, social, and environmental challenges. A fast-growing innovative solution is Crowd Logistics Delivery (CLD). This study investigates how CLD is meeting these challenges in a rapidly emerging economy (Saudi Arabia). It uses semi-structured interviews to analyse CLD from the perspectives of multiple stake-holders, focusing on its implementation, benefits to different stakeholders, and its limitations. While the findings of this study broadly support the work of other studies in this area, it provides several new insights. It observed three different business models being used for CLD: B2B, B2C, and C2C. It identified the internal success factors of each business model, including registration, assigning orders, compensation, and the payment model. It revealed the motivations for stakeholders to use CLD as a last mile delivery solution, such as LMD-related benefits and the social impact on society. In addition, the study highlighted the four main challenges these CLD implementations face that impede their success: legislation, availability of supply/drivers, trust, and culture. These results add to the rapidly expanding field of CLD. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.","Business model; Crowd logistics; Last mile delivery; Stakeholder analysis","Saudi Arabia; business development; electronic commerce; innovation; social impact; stakeholder",{"$nulls":4},"College of Science Research Center; Taibah University; Deanship of Scientific Research, King Saud University","Acknowledgments: The authors are grateful for the suggestions from the three anonymous reviewers. The outline map of Saudi Arabia used in Figure 1 was downloaded 27 December 2021 from the free clip art site http://www.clker.com/clipart-52349.html. This project was supported by Taibah University, Deanship of Scientific Research, College of Science Research Center.","Hubner A., Kuhn H., Wollenburg J., Last mile fulfilment and distribution in omni-channel grocery retailing: A strategic planning framework, Int. J. Retail Distrib. Manag, 44, pp. 228-247, (2016); Rouges J.-F., Montreuil B., Crowdsourcing Delivery: New Interconnected Business Models to Reinvent Delivery, Proceedings of the 1st International Physical Internet Conference, (2014); Mehmann J., Frehe V., Teuteberg F., Crowd logistics—A literature review and maturity model, Innovations and Strategies for Logistics and Supply Chains: Technologies, Business Models and Risk Management, 20, pp. 117-145, (2015); Frehe V., Mehmann J., Teuteberg F., Understanding and assessing crowd logistics business models—Using everyday people for last mile delivery, J. Bus. Ind. Mark, 32, pp. 75-97, (2017); Buldeo Rai H., Verlinde S., Merckx J., Macharis C., Crowd logistics: An opportunity for more sustainable urban freight transport?, Eur. Transp. Res. 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Rev, 105, pp. 18-38, (2017); Bubner N., Helbig R., Jeske M., Logistics Trend Radar, DHL Trend Research, (2014); Wang Y., Zhang D., Liu Q., Shen F., Lee L.H., Towards enhancing the last-mile delivery: An effective crowd-tasking model with scalable solutions, Transp. Res. Part E Logist. Transp. Rev, 93, pp. 279-293, (2016); Pfenning K., Verbesserung Durch Crowd Logistics Sourcing. Verkehrsrundschau: Who Is Who Logistik, (2014); Our Common Future: The World Commission on Environment and Development, (1987); Soubbotina T.P., Beyond Economic Growth: An Introduction to Sustainable Development, (2004); Botsman R., Crowdshipping: Using the crowd to transform delivery, AFR Boss Magazine; Arslan A.M., Agatz N., Kroon L., Zuidwijk R., Crowdsourced delivery—A dynamic pickup and delivery problem with ad hoc drivers, Transp. Sci, 53, pp. 222-235, (2019); Chen M., Wang D., Sun Y., Liu C., Bai Z., Service evaluation of public bicycle scheme from a user perspective, Transp. Res. Rec. J. Transp. Res. 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Manag, 29, pp. 285-308, (2003); Cornelius R.D., Stepniczka A., Chu K., Initiating an Agreement in an e-Commerce Environment, (2006); Ketokivi M., Turkulainen V., Seppala T., Rouvinen P., Ali-Yrkko J., Why locate manufacturing in a high-cost country? A case study of 35 production location decisions, J. Oper. Manag, 49, pp. 20-30, (2017); Gross Domestic Product 2020; (2020); Bryman A., Bell E., Harley B., Business Research Methods, (2018); Mason J., Qualitative Researching, (2002); Collis J., Hussey R., Business Research: A Practical Guide for Undergraduate and Postgraduate Students, (2013); Braun V., Clarke V., Using thematic analysis in psychology, Qual. Res. Psychol, 3, pp. 77-101, (2006); Wilkinson S., Women with breast cancer talking causes: Comparing content, biographical and discursive analyses, Fem. Psychol, 10, pp. 431-460, (2000); Asmussen K.J., Creswell J.W., Campus response to a student gunman, J. High. Educ, 66, pp. 575-591, (1995); Buldeo Rai H., Verlinde S., Merckx J., Macharis C., Can the crowd deliver? Analysis of crowd logistics’ types and stake-holder support, City Logist. 3 Towards Sustain. Liveable Cities, (2018); Chen C.C., Chen Y.C., Dynamic programming model for attended delivery time slot management, Transp. Res. Rec, 2548, pp. 43-52, (2016)","A. Alharbi; Management School, University of Sheffield, Sheffield, S10 1FL, United Kingdom; email: aalharbi5@sheffield.ac.uk",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85123412844"]
["Cota P.M.; Nogueira T.H.; Juan A.A.; Ravetti M.G.","Cota, Priscila M. (57188560263); Nogueira, Thiago H. (56414522500); Juan, Angel A. (56129392700); Ravetti, Martín G. (16204085000)","57188560263; 56414522500; 56129392700; 16204085000","Integrating vehicle scheduling and open routing decisions in a cross-docking center with multiple docks",2022.0,"Computers and Industrial Engineering",164.0,null,107869.0,null,null,null,10.0,"10.1016/j.cie.2021.107869","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121358382&doi=10.1016%2fj.cie.2021.107869&partnerID=40&md5=a0a5a2edb3d8d969f346ab599ab51fda","Departament of Production Engineering, Universidade Federal de Minas Gerais, Brazil; Departament of Production Engineering, Universidade Federal de Viçosa, Brazil; Departament of Statistics and Operations Research, Universitat Politècnica de València, Spain; Departament of Computer Science, Universidade Federal de Minas Gerais, Brazil","Cota P.M., Departament of Production Engineering, Universidade Federal de Minas Gerais, Brazil; Nogueira T.H., Departament of Production Engineering, Universidade Federal de Viçosa, Brazil; Juan A.A., Departament of Statistics and Operations Research, Universitat Politècnica de València, Spain; Ravetti M.G., Departament of Computer Science, Universidade Federal de Minas Gerais, Brazil","Society is facing a series of challenges, as the growth in urban population, the expansion of e-commerce, the pandemic moment (COVID-19), and many others leading to changes in companies’ supply chain, like reducing product delivery time and attention to consumer welfare, the environmental impact, to mention a few. The efficient management of logistic solutions such as cross-docking can contribute to improving the supply chain performance. Here we focus on the integration of scheduling of trucks and routing decisions; the integration of these strategies can significantly reduce costs and help organize the distribution centers and the customers’ services. This article analyzes the integrated problem in which trucks’ scheduling in a cross-docking center with multiple docks is combined with the associated open vehicle routing problem, called Open Vehicle Routing Problem With Cross-Docking (OVRPCD). This approach aims to minimize penalties caused by delays in servicing customers. First, a mixed-integer linear programming model is proposed to solve small instances optimally. Next, two heuristics are proposed to contribute to the solution of the two problems in an integrated way. These heuristics are: the Vehicle Routing Cross-Docking Heuristic (VRCDH) and the Cross-Docking Vehicle Routing Heuristic (CDVRH), each focusing on one of the problems. We also propose a Prioritization Lagrangian Heuristic (PLH) based on a model decomposition to improve the solutions found. These three heuristics are compared, considering two search approaches (i) a constructive version (HC) using the swap heuristic; and (ii) a version using the Variable Neighborhood Search (VNS) metaheuristic framework. The VNS-enhanced versions of the heuristics outperform the previous ones. Still, the same relation holds regarding the three heuristics, i.e.: the PLH heuristic outperforms the VRCDH one, while the latter outperforms the CDVRH one. Finally, we propose a polynomial-time framework, called Robust Dynamic Prioritization Lagrangian Heuristic (RDPLH), which extends PLH, considering trucks’ release dates and travel times uncertainties, approximating our problem to a real cross-docking center. The framework's simplicity and the quality of the results allow us to assert that this approach can be used in real cross-docking centers (CDCs). © 2021 Elsevier Ltd","Cross-docking; Heuristics; Uncertainties; Vehicle scheduling","Docks; Environmental impact; Hydraulic structures; Integer programming; Lagrange multipliers; Population statistics; Supply chains; Travel time; Trucks; Urban growth; Vehicle routing; Crossdocking; Docking centers; Heuristic; Lagrangian heuristics; Open vehicle routing problems; Prioritization; Routing decisions; Routing heuristics; Uncertainty; Vehicle scheduling; Scheduling",{"$nulls":4},"Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, CAPES; Conselho Nacional de Desenvolvimento Científico e Tecnológico, CNPq; Fundação de Amparo à Pesquisa do Estado de Minas Gerais, FAPEMIG; Fundação de Desenvolvimento da Pesquisa, FUNDEP","This research was partially funded by FAPEMIG, CAPES and CNPq, Brazil. MGR acknowledges support from FUNDEP. ","Ahmadizar F., Zeynivand M., Arkat J., Two- level vehicle routing with cross-docking in a three-echelon supply chain: A genetic algorithm approach, Applied Mathematical Modelling, 9, 22, pp. 7065-7081, (2015); Baniamerian A., Bashiri M., Zabihi F., A modified variable neighborhood search hybridized with genetic algorithm for vehicle routing problems with cross-docking, Electronic Notes in Discrete Mathematics, 66, pp. 143-150, (2018); Chen F., Song K., Minimizing makespan in two-stage hybrid cross docking scheduling problem, Computers & Operations Research, 36, pp. 2066-2073, (2009); Cota P.M., Gimenez B.M., Araujo D.P., Nogueira T.H., de Souza M.C., Ravetti M.G., Time-indexed formulation and polynomial time heuristic for a multi-dock truck scheduling problem in a cross-docking centre, Computers & Industrial Engineering, 95, pp. 135-143, (2016); Dondo R., Cerda J., A sweep-heuristic based formulation for the vehicle routing problem with cross-docking, Computers and Chemical Engineering, 48, pp. 293-311, (2013); Dondo R., Cerda J., A monolithic approach to vehicle routing and operations scheduling of a cross-dock system with multiple dock doors, Computers & Chemical Engineering, 63, pp. 184-205, (2014); Dondo R., Cerda J., The heterogeneous vehicle routing and truck scheduling problem in a multi- door cross-dock system, Computers & Chemical Engineering, 76, pp. 42-62, (2015); Dondo R., Mendez C.A., Cerda J., The multi-echelon vehicle routing problem with cross docking in supply chain management, Computers & Chemical Engineering, 35, 12, pp. 3002-3024, (2011); Grangier P., Gendreau M., Lehuede F., Rousseau L.M., A matheuristic based on large neighborhood search for the vehicle routing problem with cross-docking, Computers and Operations Research, 84, pp. 116-126, (2017); Grangier P., Gendreau M., Lehuede F., Rousseau L.M., The vehicle routing problem with cross-docking and resource constraints, (2019); Gruler A., Panadero J., de Armas J., Moreno J.A., Juan A.A., Combining variable neighborhood search with simulation for the inventory routing problem with stochastic demands and stock-outs, Computers & Industrial Engineering, 123, pp. 278-288, (2018); 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Konur D., Golias M.M., Analysis of different approaches to cross-dock truck scheduling with truck arrival time uncertainty, Computers & Industrial Engineering, 65, 4, pp. 663-672, (2013); Ladier A.L., Alpan G., Cross-docking operations: Current research versus industry practice, Omega, 62, pp. 145-162, (2016); Lawler E.L., On Scheduling Problems with Deferral Costs, Management Sciences, 11, 2, (1964); Lee Y.H., Jung J.W., Lee K.M., Vehicle routing scheduling for cross-docking in the supply chain, Computers & Industrial Engineering, 51, pp. 247-256, (2006); Liao C.J., Lin Y., Shih S.C., Vehicle routing with cross-docking in the supply chain, Expert Systems with Applications, 37, 10, pp. 6868-6873, (2010); Mohtashami A., A novel dynamic genetic algorithm-based method for vehicle scheduling in cross docking systems with frequent unloading operation, Computers & Industrial Engineering, 90, pp. 221-240, (2015); Morais V.W., Mateus G.R., Noronha T.F., Iterated local search heuristics for the Vehicle Routing Problem with Cross-Docking, Expert Systems with Applications, 41, 16, pp. 7495-7506, (2014); 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Theeb N.A., Al-Araidah O., Aljarrah M.H., Optimization of the Heterogeneous Vehicle Routing Problem with Cross Docking Logistic System, Logistics Research, (2019); Wen M., Larsen J., Clausen J., Cordeau J.F., Laporte G., Vehicle routing with cross- docking, Journal of Operational Research Society, 60, pp. 1708-1718, (2009); Yu V.F., Jewpanya P., Redi A.P., Open vehicle routing problem with cross-docking, Computers & Industrial Engineering, 94, pp. 6-17, (2016)","M.G. Ravetti; Departament of Computer Science, Universidade Federal de Minas Gerais, Brazil; email: martin@dcc.ufmg.br",null,"Elsevier Ltd",{"$nulls":5},3608352.0,null,"CINDD",null,"English","Comput Ind Eng","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85121358382"]
["Cao K.; Su Y.; Xu Y.; Wang J.","Cao, Kaiying (57191091909); Su, Yunyi (57466617800); Xu, Yuqiu (57214329160); Wang, Jia (57202630140)","57191091909; 57466617800; 57214329160; 57202630140","Optimal channel selection of remanufacturing firms with considering asymmetric information in platform economy",2022.0,"RAIRO - Operations Research",56.0,3.0,null,1259.0,1281.0,22.0,1.0,"10.1051/ro/2022041","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85130930741&doi=10.1051%2fro%2f2022041&partnerID=40&md5=2ace706074c9b50f85fd9223f1c0923a","School Of Tourism, Hainan University, Haikou, 570228, China; School Of Public Policy And Administration, Nanchang University, 999 Xuefu Avenue, Nanchang, 330031, China; School Of Tourism & Tourism Research Institute, Nanchang University, 999 Xuefu Avenue, Nanchang, 330031, China","Cao K., School Of Tourism, Hainan University, Haikou, 570228, China; Su Y., School Of Public Policy And Administration, Nanchang University, 999 Xuefu Avenue, Nanchang, 330031, China; Xu Y., School Of Public Policy And Administration, Nanchang University, 999 Xuefu Avenue, Nanchang, 330031, China; Wang J., School Of Tourism & Tourism Research Institute, Nanchang University, 999 Xuefu Avenue, Nanchang, 330031, China","With the rapid development of e-commerce platforms, and considering that online return rate is relatively high and third-party stores on e-commerce platforms need to adopt third-party logistics, thus remanufacturing firms face the challenge of deciding whether to enter e-commerce platforms. To address this challenge, our paper considers a remanufacturing firm, an e-commerce platform, and a third-party logistics provider. Moreover, according to whether the remanufacturing firm enters the platform and whether the information is symmetrical, we develop three theoretical models: Model NP (the firm doesna't enter platform), Model YP (the firm enters platform with symmetric information) and Model YA (the firm enters platform with asymmetric information). Some main insights are obtained. We find that whether remanufacturing firms should enter the platform depends not only on the annual service fee charged by the platform but also on the carbon tax price set by the government. Interestingly, improved consumersa'satisfaction with online remanufactured products is not necessarily conducive to enhancing the willingness of remanufacturing firms to enter e-commerce platforms. Finally, we find that when the production quantity constraint of the remanufactured products is not binding, if the actual production cost of remanufactured products is high and consumersa'satisfaction with offline remanufactured products is relatively low, information disclosure will benefit remanufacturing firms, however, when the production quantity constraint of the remanufactured products is binding, information disclosure has no impact on the remanufacturing firmsa'profits and operational decisions. © 2022 The authors. Published by EDP Sciences, ROADEF, SMAI.","Channel choice; E-commerce platform; Logistics service; Remanufacturing; Return service","Costs; Outsourcing; Taxation; Asymmetric information; Channel choice; Commerce platforms; E- commerces; E-commerce platform; Logistics services; Production quantity; Remanufactured products; Remanufacturing; Return service; Electronic commerce",{"$nulls":4},"College of Humanities & Social Science Research Base Project of Jiangxi Province, (JD20099); National Natural Science Foundation of China, NSFC, (71801121, 72061024); National Office for Philosophy and Social Sciences, NPOPSS, (21CGL025)","Acknowledgements. This research is partly supported by the National Natural Science Foundation of China (Grant Nos. 71801121; 72061024), the National Social Science Foundation of China (Grant No. 21CGL025), and the College of Humanities & Social Science Research Base Project of Jiangxi Province (2020) (Grant No. JD20099).","Cao K., Choi T.-M., Optimal trade-in return policies: Is it wise to be generous?, Prod. Oper. Manage., 31, pp. 1309-1331, (2022); Cao K., Xu X., Bian Y., Sun Y., Optimal trade-in strategy of business-to-consumer platform with dual-format retailing model, Omega, 82, pp. 181-192, (2019); Cao K., Xu Y., Cao J., Xu B., Wang J., Whether a retailer should enter an e-commerce platform taking into account consumer returns, Int. Trans. Oper. Res., 27, pp. 2878-2898, (2020); Cao K., Xu B., Wang J., Optimal trade-in and warranty period strategies for new and remanufactured products under carbon tax policy, Int. J. Prod. 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Res., 55, pp. 679-699, (2021); Ye F., Xie Z., Tong Y., Li Y., Promised delivery time: Implications for retailer-s optimal sales channel strategy, Comput. Ind. Eng., 144, (2020); Zhang J., Gou Q., Liang L., Huang Z., Supply chain coordination through cooperative advertising with reference price effect, Omega, 41, pp. 345-353, (2013)","Y. Xu; School Of Public Policy And Administration, Nanchang University, Nanchang, 999 Xuefu Avenue, 330031, China; email: 15779845652@163.com",null,"EDP Sciences",{"$nulls":5},2.8047303E7,null,null,null,"English","RAIRO Oper. Res.","Article","Final","All Open Access; Green Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85130930741"]
["Prajapati D.; Chelladurai H.; Zhou F.; Ip A.W.H.; Pratap S.","Prajapati, Dhirendra (57215023349); Chelladurai, H. (24075425500); Zhou, Fuli (57189093462); Ip, Andrew W.H. (57194906440); Pratap, Saurabh (56667217800)","57215023349; 24075425500; 57189093462; 57194906440; 56667217800","Sustainable multi-products delivery routing network design for two-echelon supplier selection problem in B2B e-commerce platform",2022.0,"RAIRO - Operations Research",56.0,4.0,null,2115.0,2137.0,22.0,5.0,"10.1051/ro/2022072","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85134471853&doi=10.1051%2fro%2f2022072&partnerID=40&md5=57ec69c2fd38a8eca20c63ed2d5664ec","Department of Mechanical Engineering, Indian Institute of Information Technology, Design and Manufacturing Jabalpur, Madhya Pradesh, Jabalpur, India; School of Economics and Management, Zhengzhou University of Light Industry, Zhengzhou, China; Department of Mechanical Engineering, University of Saskatchewan, Saskatoon, Canada; Department of Mechanical Engineering, Indian Institute of Technology (BHU), Uttar Pradesh, Varanasi, India","Prajapati D., Department of Mechanical Engineering, Indian Institute of Information Technology, Design and Manufacturing Jabalpur, Madhya Pradesh, Jabalpur, India; Chelladurai H., Department of Mechanical Engineering, Indian Institute of Information Technology, Design and Manufacturing Jabalpur, Madhya Pradesh, Jabalpur, India; Zhou F., School of Economics and Management, Zhengzhou University of Light Industry, Zhengzhou, China; Ip A.W.H., Department of Mechanical Engineering, University of Saskatchewan, Saskatoon, Canada; Pratap S., Department of Mechanical Engineering, Indian Institute of Technology (BHU), Uttar Pradesh, Varanasi, India","This paper examines the environmental impact produced by multi-vehicle transportation on a sustainable supply chain (SC) network. The relevance of green principles is gaining momentum day by day, which has forced the governments to introduce carbon emission schemes for the transportation associated with the firms. Various countries around the globe are introducing carbon-pricing schemes, in which a carbon tax is imposed based on the amount of anthropogenic emissions. A firm, which sets environmental standards for the emission associated with its operational activities, should design a transportation network based on the trade-off between its economic efficiency and the carbon emission. In this paper, the main focus is to design a sustainable supply chain network. A mixed-integer-non-linear-programming (MINLP) model is formulated to minimize the overall cost incurred in a multi-vehicle, multi-product sustainable transportation network. The meta-heuristic approach i.e., Hybrid Chemical Reaction Optimization Algorithm with Tabu search (CRO-TS) and LINGO solver have been used to solve the proposed model. This analysis can guide the government to encourage the logistics service providers to capitalize on anthropogenic gas emission systems and simultaneously design the tax policy on carbon emission. © 2022 American Society of Civil Engineers (ASCE). All rights reserved.","Carbon emission; Chemical reaction optimization algorithm; LINGO; Multi-vehicle transportation; Sustainable transportation network design; Tabu search","Carbon; Costs; Economic and social effects; Environmental impact; Gas emissions; Heuristic methods; Nonlinear programming; Product design; Supply chains; Sustainable development; Tabu search; Vehicles; Carbon emissions; Chemical reaction optimization algorithms; LINGO; Multi-products; Multi-vehicle transportation; Multi-vehicles; Network design; Sustainable transportation; Sustainable transportation network design; Transportation network; Integer programming",{"$nulls":6},"Abyazi-Sani R., Ghanbari R., An efficient tabu search for solving the uncapacitated single allocation hub location problem, Comput. Ind. 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Prod. Res, 59, pp. 6291-6310, (2021)","S. Pratap; Department of Mechanical Engineering, Indian Institute of Information Technology, Design and Manufacturing Jabalpur, Jabalpur, Madhya Pradesh, India; email: saurabh.mec@iitbhu.ac.in",null,"EDP Sciences",{"$nulls":5},2.8047303E7,null,null,null,"English","RAIRO Oper. Res.","Article","Final","All Open Access; Green Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85134471853"]
["Bocken N.M.P.; Harsch A.; Weissbrod I.","Bocken, Nancy M.P. (24328581100); Harsch, Alisa (57431892900); Weissbrod, Ilka (57189236388)","24328581100; 57431892900; 57189236388","Circular business models for the fastmoving consumer goods industry: Desirability, feasibility, and viability",2022.0,"Sustainable Production and Consumption",30.0,null,null,799.0,814.0,15.0,30.0,"10.1016/j.spc.2022.01.012","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85123729871&doi=10.1016%2fj.spc.2022.01.012&partnerID=40&md5=acc7c11ffba3dd7da46ef38423eb5252","School of Business and Economics, Maastricht Sustainability Institute, Maastricht University, Tapijn 11 Building D, P.O. Box 616, Maastricht, 6200 MD, Netherlands; Lund University, IIIEE, Tegnérsplatsen 4, Lund, 223 50, Sweden; Leuphana University of Lüneburg, Centre for Sustainability Management, Scharnhorststrasse 1, Lüneburg, 21335, Germany","Bocken N.M.P., School of Business and Economics, Maastricht Sustainability Institute, Maastricht University, Tapijn 11 Building D, P.O. Box 616, Maastricht, 6200 MD, Netherlands, Lund University, IIIEE, Tegnérsplatsen 4, Lund, 223 50, Sweden; Harsch A., School of Business and Economics, Maastricht Sustainability Institute, Maastricht University, Tapijn 11 Building D, P.O. Box 616, Maastricht, 6200 MD, Netherlands; Weissbrod I., Leuphana University of Lüneburg, Centre for Sustainability Management, Scharnhorststrasse 1, Lüneburg, 21335, Germany","Fast-moving consumer goods (FMCGs) are products that have a short useful lifetime and are typically designed for single or limited uses followed by disposal. The disposable nature of FMCGs combined with ineffective waste recovery systems is causing global environmental problems. Various reusable packaging business models have emerged to tackle these problems; however, their influence is still low in practice. Testing the feasibility, desirability, and viability of innovative circular business models enables their implementation and scaling. In this context, this study explores the success factors, drivers, and barriers of an FMCGs reuse business model. The case company is an internationally scaling company pursuing a potentially disruptive circular business model. A mixed methods approach is used, involving semi-structured interviews with innovators on two variations of the FMCG reuse business model (in-store and e-commerce) followed by a consumer survey in the city of Berlin to test perceptions of these business models. Five success factors were identified: brand and retailer partnerships, consumer participation, operations efficiency, business model profitability, and the establishment of an ecosystem. The main driver for consumers to participate in the circular business model is the potential positive environmental impact, although there were concerns about added environmental impact related to logistics in the e-commerce model. In addition, convenience and accessibility of the reuse model are important for consumers. Costs are identified as a predominant barrier for companies to engage in reusability. Based on the research findings, recommendations for expanding FMCG reuse business models are developed. © 2022 The Author(s)","Business model experimentation; Circular business model; Circular economy; Deposit system; Deposit-refund; Fast-moving consumer goods; Radical innovation; Reusable packaging","Electronic commerce; Environmental impact; Reusability; Business model experimentation; Business models; Circular business model; Circular economy; Deposit system; Deposit-refund; Fast moving consumer goods; Model experimentations; Radical innovation; Reusable packaging; Deposits",{"$nulls":4},"European Union's Horizon 2020′s European research Council; European Research Council, ERC, (850159)","Nancy Bocken received funding from the European Union's Horizon 2020′s European research Council (ERC) funding scheme under grant agreement No 850159, Project Circular X ( www.circularx.eu ). ","Ahrens S., (2021); Achterberg E., Hinfelaar J., Bocken N.M.P., Master circular business models with the Value Hill, White paper, (2016); Allwood J.M., Squaring the circular economy: the role of recycling within a hierarchy of material management strategies, Handbook of Recycling, pp. 445-477, (2014); Antikainen M., Bocken N., Experimenting with circular business models—a process-oriented approach, Palgrave Studies in Sustainable Business in Association with Future Earth. Innovation for Sustainability: Business Transformations Towards a Better World, pp. 353-374, (2019); Antikainen M., Valkokari K., A framework for sustainable circular business model innovation, Technol. Innov. Manag. Rev., 6, 7, pp. 5-12, (2016); Baldassarre B., Konietzko J., Brown P., Calabretta G., Bocken N., Karpen I.O., Hultink E.J., Addressing the design-implementation gap of sustainable business models by prototyping: a tool for planning and executing small-scale pilots, J. Clean. 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Rev., 11, pp. 124-133, (2019); Zhou G., Gu Y., Wu Y., Gong Y., Mu X., Han H., Chang T., A systematic review of the deposit-refund system for beverage packaging: operating mode, key parameter and development trend, J. Clean. Prod., 251, 2, (2020)","N.M.P. Bocken; School of Business and Economics, Maastricht Sustainability Institute, Maastricht University, Maastricht, Tapijn 11 Building D, P.O. Box 616, 6200 MD, Netherlands; email: Nancy.Bocken@maastrichtuniversity.nl",null,"Elsevier B.V.",{"$nulls":5},2.3525509E7,null,null,null,"English","Sustain. Prod. Consum.","Article","Final","All Open Access; Green Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85123729871"]
["Kusuma P.D.; Kallista M.","Kusuma, Purba Daru (56206181600); Kallista, Meta (56242309600)","56206181600; 56242309600","Pickup and delivery problem in the collaborative city courier service by using genetic algorithm and nearest distance",2022.0,"Bulletin of Electrical Engineering and Informatics",11.0,2.0,null,1026.0,1036.0,10.0,3.0,"10.11591/eei.v11i2.3223","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85128283378&doi=10.11591%2feei.v11i2.3223&partnerID=40&md5=84593b52ceba5c195d50efb793fe707a","Faculty of Electrical Engineering, Telkom University, Bandung, Indonesia","Kusuma P.D., Faculty of Electrical Engineering, Telkom University, Bandung, Indonesia; Kallista M., Faculty of Electrical Engineering, Telkom University, Bandung, Indonesia","One problem in collaborative pickup delivery problem (PDP) was excessive outsourced jobs. It happened in many studies on the collaborative PDP. Besides, the revenue sharing in it was unclear although important. This work aimed to propose a novel collaborative PDP model which minimizes total travel distance while maintains low outsourced jobs. It proposed several contributions. First, it prioritized internal jobs first rather than full collaborative model. Second, it proposed new revenue sharing model. It adopted cluster-first route-second and mixed pickup and delivery. It was developed by combining the genetic algorithm and nearest distance algorithm where the genetic algorithm was used in the clustering process and the nearest distance was used in the routing process. The simulation result shows that the proposed model was better than the comparing models: (1) combined K-means and genetic algorithm model (KMGA) and (2) combined simulated annealing and last-in first-out (SNLIFO) model. When the number of orders was high (300 units), the total travel distance of the proposed model was 37 percent lower than the KMGA model and 30 percent lower than the SNLIFO model. In average, the outsourcing rate of the proposed model was 70 percent lower than the previous models. © 2022, Institute of Advanced Engineering and Science. All rights reserved.","Courier service; COVID-19; E-commerce; Genetic algorithm; Nearest distance; Vehicle routing problem",{"$nulls":5},"Universitas Telkom, Tel-U","This work is funded and supported by Telkom University, Indonesia","Phuc P. N. K., Thao N. L. P., Ant colony optimization for multiple pickup and multiple delivery vehicle routing problem with time window and heterogeneous fleets, Logistics, 5, 28, pp. 1-13, (2021); Wolfinger D., Salazar-Gonzalez J. J., The pickup and delivery problem with split loads and transshipments: a branch-and-cut solution approach, European Journal of Operational Research, 289, pp. 470-484, (2021); Wassan N. A., Nagy G., Vehicle routing problem with deliveries and pickups: modelling issues and meta-heuristics solution approaches, International Journal of Transportation, 2, 1, pp. 95-110, (2014); Khaoula B., Youssef B., Ghizlane B., Multi-depots vehicle routing problem with simultaneous delivery and pickup and inventory restrictions: formulation and resolution, International Journal of Advanced Computer Science and Applications, 10, 2, pp. 110-120, (2019); Ahmed A. K. M. F., Sun J. U., Bilayer local search enhanced particle swarm optimization for the capacitated vehicle routing problem, Algorithms, 11, 3, pp. 1-22, (2018); Wang Y., Ran L., Guan X., Zou Y., Multi-depot pickup and delivery problem with resource sharing, Journal of Advanced Transportation, 2021, pp. 1-22, (2021); Deng S., Yuan Y., Wang Y., Wang H., Koll C., Collaborative multicenter logistics delivery network optimization with resource sharing, PLOS ONE, 15, 11, pp. 1-31, (2020); Perez H. H., Gonzalez J. J. 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Y., Simulated annealing algorithm for solving pickup and delivery problem with LIFO, time duration and limited vehicle number, IOP Conf. Series: Material Science and Engineering, 697, pp. 1-6, (2019); Andriansyah N. Prasanti, Sentia P. M., Pickup and delivery problem with LIFO, time duration, and limited vehicle number, MATEC Web of Conference, 204, pp. 1-6, (2018); Puspita F. M., Simanjuntak S. B., Melati R., Octarina S., Demand robust counterpart open capacitated vehicle routing problem time windows and deadline model of garbage transportation with LINGO 13.0, International Journal of Electrical and Computer Engineering, 10, 6, pp. 6380-6388, (2020); Yuan X., Zhang Q., Zeng J., Modeling and solution of vehicle routing problem with grey time windows and multi-objective constraints, Journal of Advanced Transportation, 2021, pp. 1-12, (2021); Ju B., Kim M., Moon I., Vehicle routing problem considering reconnaissance and transportation, Sustainability, 13, 3188, pp. 1-19, (2021); Sze S. N., Sek S. Y. D., Sze J. F., Cheah W. S., Chiew K. L., Vehicle routing problem with simultaneous pickup and delivery, International Journal on Advanced Science Engineering and Information Technology, 10, 4, pp. 1360-1366, (2020); Alhujaylan A. I., Hosny M. I., A GRASP-based solution construction approach for the multi-vehicle profitable pickup and delivery problem, International Journal of Advanced Computer Science and Application, 10, 4, pp. 111-120, (2019); Wang Y., Li Q., Guan X., Fan J., Liu Y., Wang H., Collaboration and resource sharing in the multidepot multiperiod vehicle routing problem with pickups and deliveries, Sustainability, 12, 5966, pp. 1-32, (2020); Jahangir H., Mohammadi M., Pasandideh S. H. R., Nobari N. Z., Comparing performance of genetic and discrete invasive weed optimization algorithms for solving the inventory routing problem with an incremental delivery, Journal of Intelligent Manufacturing, 30, 6, pp. 2327-2353, (2018); Braekers K., Ramaekers K., Niewenhuyse I. V., The vehicle routing problem: state of the art classification review, Computers & Industrial Engineering, 99, pp. 300-313, (2016); Normasari N. M. E., Yu V. F., Bakhtiyar C., Sukoyo, A simulated annealing heuristic for the capacitated green vehicle routing problem, Mathematical Problems in Engineering, 2019, pp. 1-19, (2019); Okulewicz M., Mandziuk J., The impact of particular components of the PSO-based algorithm solving the dynamic vehicle routing problem, Applied Soft Computing, 58, pp. 586-604, (2017); Shao S., Guan W., Ran B., He Z., Bi J., Electric vehicle routing problem with charging time and variable travel time, Mathematical Problems in Engineering, 2017, pp. 1-13, (2017); Suyanto A. T. Wibowo, Faraby S. A., Saadah S., Rismala R., Evolutionary Rao algorithm, Journal of Computational Science, 53, pp. 1-23, (2021); Xu J., Improved genetic algorithm to solve the scheduling problem of college english courses, Complexity, 2021, pp. 1-11, (2021); Katoch S., Chauhan S. S., Kumar V., A review on genetic algorithm: past, present, and future, Multimedia Tools and Applications, 80, pp. 8091-8126, (2021); Liu T., Zou G., Evaluation of mechanical properties of materials based on genetic algorithm optimizing BP Neural network, Computational Intelligence and Neuroscience, 2021, pp. 1-12, (2021); Zhang W., Gajpal Y., Appadoo S. S., Wei Q., Multi-depot green vehicle routing problem to minimize carbon emissions, Sustainability, 12, 8, pp. 1-19, (2020); Peng B., Wu L., Yi Y., Chen X., Solving the multi-depot green vehicle routing problem by a hybrid evolutionary algorithm, Sustainability, 12, 2127, pp. 1-19, (2020); Masudin I., Sa'diyah R., Utama D. M., Restuputri D. P., Jie F., Capacitated vehicle routing problems: nearest neighbour vs. tabu search, International Journal of Computer Theory and Engineering, 11, 4, pp. 76-79, (2019); Sari D. P., Masruroh N. A., Asih A. M. S., Extended maximal covering location and vehicle routing problems in designing smartphone waste collection channels: a case study of Yogyakarta province, Indonesia, Sustainability, 13, 16, pp. 1-23, (2021); Sarjono H., Determination of best route to minimize transportation costs using nearest neighbor procedure, Applied Mathematical Sciences, 8, 62, pp. 3063-3074, (2014); Zheng W., Liao Z., Qin J., Using a four-step heuristic algorithm to design personalized day tour route within a tourist attraction, Tourism Management, 62, pp. 335-349, (2017); Kim S., Moon I., Traveling salesman problem with a drone station, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 49, 1, pp. 42-52, (2019)","P.D. Kusuma; Faculty of Electrical Engineering, Telkom University, Bandung, Indonesia; email: purbodaru@telkomuniversity.ac.id",null,"Institute of Advanced Engineering and Science",{"$nulls":5},2.0893191E7,null,null,null,"English","Bull. Electr. Eng. Inform.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85128283378"]
["Alekseenko A.P.","Alekseenko, Aleksandr P. (57214460559)",5.7214460559E10,"Legal Regulation of China’s Cross-border E-Commerce Comprehensive Pilot Areas: A Russian Perspective",2022.0,"China and WTO Review",8.0,1.0,null,7.0,28.0,21.0,2.0,"10.14330/cwr.2022.8.1.01","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85131121491&doi=10.14330%2fcwr.2022.8.1.01&partnerID=40&md5=43d5c5116c48b383c0122b7c2bee84d4","Saint-Petersburg University, Department of Commercial Law, 7–9, Universitetskaya nab., St. Petersburg, 199034, Russian Federation","Alekseenko A.P., Saint-Petersburg University, Department of Commercial Law, 7–9, Universitetskaya nab., St. Petersburg, 199034, Russian Federation","Since 2015 China has been actively developing the cross-border e-commerce comprehensive pilot areas. They are one of the mechanisms that the PRC has been promoting international trade in the digital era. Enterprises registered in the cross-border e-commerce comprehensive pilot areas enjoy preferential tax policies and may draw upon the support measures delivered by provinces and municipalities. The State Council also introduced the “Six Systems and Two Platforms” principle which revolutionized the sphere of public administration of cross-border e-commerce trade. This helps to solve many the problems concerning taxation, customs clearance and logistics. Analysis of Chinese legislation and local regulations illustrates that the PRC elaborated a new type of economic zone integrating small and medium sized enterprises into the global trade market. A comparison of Chinese policy with a Russian initiative to introduce new experimental regimes for foreign online trade shows that both states could cooperate by establishing a joint mechanism for cross-border e-commerce promotion. Russia also could use China’s experience in order to launch its own system of cross-border e-commerce support. © 2022, Yijun Institute of International Law. All rights reserved.","CBEC Pilot Area; Cross-Border E-Commerce; Digital Economy; E-Commerce; Russia",{"$nulls":5},"Russian Foundation for Basic Research, РФФИ, (21-511-93004)","* Associate Professor of Saint-Petersburg University (Department of Commercial Law). Ph.D. in Law (Ural State U.). ORCID: http://orcid.org/0000-0003-0707-8372. The reported study was funded by RFBR, project number 21-511-93004: «The rule of law in the digital economy in China and Russia: current state, challenges and future development». The author may be contacted at: alekseenko.a.p@ gmail.com /Address: 7–9, Universitetskaya nab., St. Petersburg, 199034, Russian Federation.","Globaldata; Majcherczyk M., Bai S., Digital Silk Road-The Role of Cross-border E-Commerce in Facilitating Trade, J. 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Theor. Appl. Electron. Commer. Res., 69, (2022); Tu Y., He Y., Cross-Border E-Commerce: Policies and Practices, (2020); (2018); Bo L., Wang H., Research on the competitive strategy of cross-border e-commerce comprehensive pilot area based on the spatial competition, Scientific Programming, (2016); Wang C., (2019); Li X., Cross-border E-Commerce Industry to Promote the “Belt and Road”: Experience, Dilemmas and Inspiration--Taking the practice of Hangzhou Comprehensive Pilot Zone as an Example, 4 First J. Party School of CPC Hangzhou, (2018); Wang J., Zheng H., “One Belt, One Road” Regional Customs Clearance Integration Construction: An Analysis Based on the Perspective of Cross-border E-Commerce, 4 J. Beijing Tech. & Bus. U. (Social Sciences), (2017); (2017); Zhang L., Zhao S., Cross-border E-Commerce and Cross-border Logistics in Yunnan Province Under the Background of the One Belt and One Road Based on Big Data Analysis, Big Data Analytics for Cyber-Physical System in Smart City, 1303, (2021); Fu H., Analysis of the Impact of the E-Commerce Law on the Cross-border E-Commerce Comprehensive Pilot Area-Taking Shijiazhuang Cross-border E-commerce Comprehensive Pilot Area as an example, 5 Hebei Enterprise [河北企业], (2021); Law of the Russian Federation on Protection of the Consumers’ Rights No. 2300, (2021); Meeting on the Regulation of Cross-Border Electronic Commerce, (2020); The State Duma, (2021); Everyone is trading: The first bond zone in Russia will appear in Tatarstan, RBK, (2021); Interfax, (2021); Report on the Development of Digital (Internet) Trade of the EAEU, (2019); Goncharuk I., Customs management of supply chains in cross-border trade: New in Russian practice, Scientific Papers of the Northwestern Institute of Management of RANEPA, 12, 4, (2021); (2021); NE China airport sees robust cargo throughput to Russia, Xinhuanet, (2022); (2018); Song L., Fruitful Achievements of Heilongjiang Province in construction of online Silk Road, Rev. Bus. & Econ. Studies, 7, 1, (2019); China, Russia enjoy booming cross-border e-commerce cooperation, CGTN, (2019); Su W., Wang Y., Qian S.Z., Balezentis T., Streimikiene D., Creating a Sustainable Policy Framework for Cross-border E-Commerce in China, 11 Sustainability, (2019); (2015); Lai Y., China’s cross-border e-commerce: Current status, development trend and policy suggestions, China and the World Economy, (2017); Jiang Y., Guo L., Liu H., Opportunities, challenges and countermeasures for the development of Sino-Russian cross-border e-commerce under the background of “One Belt and One Road, Eurasian Econ, 4, (2021); China and Russia Sign the Memorandum of Understanding on E-Commerce Cooperation, (2018); Zhou X., Russian-Chinese Cross-Border Economic Cooperation Zones: Prospects for Cooperation between Russia and China, (2020)","A.P. Alekseenko; Saint-Petersburg University, Department of Commercial Law, St. Petersburg, 7–9, Universitetskaya nab., 199034, Russian Federation; email: alekseenko.a.p@gmail.com",null,"Yijun Institute of International Law",{"$nulls":5},2.3838221E7,null,null,null,"English","Chi. WTO. Rev.","Article","Final","All Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85131121491"]
["Kemp N.J.; Li L.; Keoleian G.A.; Kim H.C.; Wallington T.J.; De Kleine R.","Kemp, Nicholas J. (57225456923); Li, Luyao (57234968600); Keoleian, Gregory A. (7004102663); Kim, Hyung Chul (55739549800); Wallington, Timothy J. (7102358724); De Kleine, Robert (38761199500)","57225456923; 57234968600; 7004102663; 55739549800; 7102358724; 38761199500","Carbon Footprint of Alternative Grocery Shopping and Transportation Options from Retail Distribution Centers to Customer",2022.0,"Environmental Science and Technology",56.0,16.0,null,11798.0,11806.0,8.0,2.0,"10.1021/acs.est.2c02050","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85136133538&doi=10.1021%2facs.est.2c02050&partnerID=40&md5=5027f499a84abcd56cb9703ce6544141","Center for Sustainable Systems, School for Environment and Sustainability, University of Michigan, 440 Church Street, Ann Arbor, 48109, MI, United States; Research and Innovation Center, Ford Motor Company, Dearborn, 48121, MI, United States","Kemp N.J., Center for Sustainable Systems, School for Environment and Sustainability, University of Michigan, 440 Church Street, Ann Arbor, 48109, MI, United States; Li L., Center for Sustainable Systems, School for Environment and Sustainability, University of Michigan, 440 Church Street, Ann Arbor, 48109, MI, United States; Keoleian G.A., Center for Sustainable Systems, School for Environment and Sustainability, University of Michigan, 440 Church Street, Ann Arbor, 48109, MI, United States; Kim H.C., Research and Innovation Center, Ford Motor Company, Dearborn, 48121, MI, United States; Wallington T.J., Research and Innovation Center, Ford Motor Company, Dearborn, 48121, MI, United States; De Kleine R., Research and Innovation Center, Ford Motor Company, Dearborn, 48121, MI, United States","The COVID-19 pandemic has accelerated the growth of e-commerce and automated warehouses, vehicles, and robots and has created new options for grocery supply chains. We report and compare the greenhouse gas (GHG) emissions for a 36-item grocery basket transported along 72 unique paths from a centralized warehouse to the customer, including impacts of micro-fulfillment centers, refrigeration, vehicle automation, and last-mile transportation. Our base case is in-store shopping with last-mile transportation using an internal combustion engine (ICE) SUV (6.0 kg CO2e). The results indicate that emissions reductions could be achieved by e-commerce with micro-fulfillment centers (16-54%), customer vehicle electrification (18-42%), or grocery delivery (22-65%) compared to the base case. In-store shopping with an ICE pick-up truck has the highest emissions of all paths investigated (6.9 kg CO2e) while delivery using a sidewalk automated robot has the least (1.0 kg CO2e). Shopping frequency is an important factor for households to consider, e.g. halving shopping frequency can reduce GHG emissions by 44%. Trip chaining also offers an opportunity to reduce emissions with approximately 50% savings compared to the base case. Opportunities for grocers and households to reduce grocery supply chain carbon footprints are identified and discussed. © 2022 American Chemical Society. All rights reserved.","autonomous vehicle; greenhouse gas emissions; Grocery e-commerce; last-mile; micro-fulfillment center; shopping frequency; trip chaining","Carbon Footprint; COVID-19; Greenhouse Effect; Greenhouse Gases; Humans; Pandemics; Transportation; Autonomous vehicles; Carbon footprint; Electric vehicles; Electronic commerce; Emission control; Gas emissions; Internal combustion engines; Sales; Supply chains; Warehouses; Autonomous Vehicles; E- commerces; Greenhouse gas emissions; Grocery e-commerce; Grocery shopping; Last mile; Micro-fulfillment center; Retail distribution; Shopping frequency; Trip chaining; COVID-19; Article; automation; carbon footprint; combustion; controlled study; electronic commerce; grocery store; human; refrigeration; retail outlet; shopping mall; traffic and transport; carbon footprint; greenhouse effect; greenhouse gas; pandemic; traffic and transport; Greenhouse gases",null,"Greenhouse Gases, ",null,null,"Ford-University of Michigan Alliance Program, (N028450); Fordham University, FU, (N024420)","This research was supported by the Ford-University of Michigan Alliance Program (N028450) and the Ford University Research Program (N024420). The authors wish to thank Alex Harrison and Erik Petrovskis at Meijer, Shelie Miller at University of Michigan, and Olia Vradiy for their valuable input. While this article is believed to contain correct information, Ford Motor Company (Ford) does not expressly or impliedly warrant, nor assume any responsibility, for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, nor represent that its use would not infringe the rights of third parties. Reference to any commercial product or process does not constitute its endorsement. This article does not provide financial, safety, medical, consumer product, or public policy advice or recommendation. Readers should independently replicate all experiments, calculations, and results. The views and opinions expressed are of the authors and do not necessarily reflect those of Ford. This disclaimer may not be removed, altered, superseded or modified without prior Ford permission.","Perrier S., A Year of Reckoning for Grocery E-commerce; Redman R., Online Grocery to More Than Double Market Share by 2025; Gee I.M., Davidson F.T., Speetles B.L., Webber M.E., Deliver Me from Food Waste: Model Framework for Comparing the Energy Use of Meal-Kit Delivery and Groceries, J. Clean. Prod., 236, (2019); Wilson R., Saavedra S., Micro-Fulfillment Centers for Grocery: How Thinking Small Can Be A Big Win; Nayak V., In the Midst of the Apocalypse, Artificial Intelligence Can Save Brick and Mortar Retailers, CUNY Acad. Work, (2019); Bovet D., The Food Supply Chain - What 'S Changed and What Lies Ahead ?; Melendez S., What if Your Grocery Orders Were Prepared in A Tiny Robot Warehouse; Albrecht C., Takeoff Technologies to Have 40 Automated Fulfillment Centers Operating This Year; Cirjevskis A., Do Synergies Pop up Magically in Digital Transformation-Based Retail M&A? Valuing Synergies with Real Options Application, J. Open Innov. Technol. Mark. Complex., 6, 1, (2020); Thomasson E., Fares M., The Food Giant behind Peapod and Stop & Shop Will Build \"robot Supermarkets\" in A Bold Move to Keep Up in the Online Grocery Wars; Harrison A., Meijer Supply Chain Strategy and Services, (2021); Harrison A., Meijer Supply Chain Strategy and Services, (2021); Joerss B.M., Neuhaus F., Schroder J., How Customer Demands Are Reshaping Last-Mile Delivery, McKinsey Q., 17, pp. 1-5, (2016); Global Warming of 1.5°C. An IPCC Special Report on the Impacts of Global Warming of 1.5°C above Pre-Industrial Levels and Related Global Greenhouse Gas Emission Pathways, in the Context of Strengthening the Global Response to the Threat of Climate Change, Ipcc - Sr15, 2, pp. 17-20, (2018); Goodchild A., Wygonik E., Mayes N., An Analytical Model for Vehicle Miles Traveled and Carbon Emissions for Goods Delivery Scenarios, Eur. Transp. Res. Rev., 10, 1, (2018); Figliozzi M.A., Carbon Emissions Reductions in Last Mile and Grocery Deliveries Utilizing Air and Ground Autonomous Vehicles, Transp. Res. Part D Transp. Environ., 85, (2020); Van Loon P., Deketele L., Dewaele J., McKinnon A., Rutherford C., A Comparative Analysis of Carbon Emissions from Online Retailing of Fast Moving Consumer Goods, J. Clean. Prod., 106, 2015, pp. 478-486, (2015); Rizet C., Browne M., Cornelis E., Leonardi J., Assessing Carbon Footprint and Energy Efficiency in Competing Supply Chains: Review - Case Studies and Benchmarking, Transp. Res. Part D Transp. Environ., 17, 4, pp. 293-300, (2012); Lee D.Y., Thomas V.M., Brown M.A., Electric Urban Delivery Trucks: Energy Use, Greenhouse Gas Emissions, and Cost-Effectiveness, Environ. Sci. Technol., 47, 14, pp. 8022-8030, (2013); Siragusa C., Tumino A., E-Grocery: Comparing the Environmental Impacts of the Online and Offline Purchasing Processes, Int. J. Logist. Res. Appl., pp. 1-27, (2021); Shahmohammadi S., Steinmann Z.J.N., Tambjerg L., Van Loon P., King J.M.H., Huijbregts M.A.J., Comparative Greenhouse Gas Footprinting of Online versus Traditional Shopping for Fast-Moving Consumer Goods: A Stochastic Approach, Environ. Sci. Technol., 54, 6, pp. 3499-3509, (2020); Stolaroff J.K., Samaras C., O'Neill E.R., Lubers A., Mitchell A.S., Ceperley D., Energy Use and Life Cycle Greenhouse Gas Emissions of Drones for Commercial Package Delivery, Nat. Commun., 9, 1, pp. 1-13, (2018); Siikavirta H., Punakivi M., Karkkainen M., Linnanen L., Effects of E-Commerce on Greenhouse Gas Emissions: A Case Study of Grocery Home Delivery in Finland, J. Ind. Ecol., 6, 2, pp. 83-97, (2002); Heldt B., Matteis T., Von Schmidt A., Heinrichs M., Cool but Dirty Food? - Estimating the Impact of Grocery Home Delivery on Transport and CO2 Emissions Including Cooling, Res. Transp. Econ., (2019); Johansson A., Johansson G., Lundqvist P., Akesson I., Odenrick P., Akselsson R., Evaluation of a Workplace Redesign of a Grocery Checkout System, Appl. Ergon., 29, 4, pp. 261-266, (1998); Harrison A., Meijer Supply Chain Strategy and Services, (2021); Harrison A., Meijer Supply Chain Strategy and Services, (2021); The Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation (GREET) Model 2020; 7 Facts about Grocery Shopping That Might Shock You; Lake R., Grocery Shopping Statistics: 23 Fun Size Facts to Know; Harrison A., Meijer Supply Chain Strategy and Services, (2021); Greenhouse Gas Impacts of Food Retailing, Department of Environment, Food & Rural Affairs in the United Kingdom, 5, 20, pp. 1-51, (2008); Li L., He X., Keoleian G.A., Chul Kim H., De Kleine R., Wallington T.J., Kemp N.J., Life Cycle Greenhouse Gas Emissions for Last-Mile Parcel Delivery by Automated Vehicles and Robots, Environ. Sci. Technol., (2021); Figliozzi M.A., Carbon Emissions Reductions in Last Mile and Grocery Deliveries Utilizing Air and Ground Autonomous Vehicles, Transp. Res. Part D Transp. Environ., 85, (2020); Kim H.C., Wallington T.J., Life Cycle Assessment of Vehicle Lightweighting: A Physics-Based Model to Estimate Use-Phase Fuel Consumption of Electrified Vehicles, Environ. Sci. Technol., 50, 20, pp. 11226-11233, (2016); Primerano F., Taylor M.A.P., Pitaksringkarn L., Tisato P., Defining and Understanding Trip Chaining Behaviour, Transportation (Amst)., 35, 1, pp. 55-72, (2007); Popkowski Leszczyc P.T.L., Timmermans H., Experimental Choice Analysis of Shopping Strategies, J. Retail., 77, 4, pp. 493-509, (2001); Harris D., How Far Do Americans Drive to Work on Average?; Duncan M., How Much Can Trip Chaining Reduce VMT? A Simplified Method, Transportation (Amst)., 43, 4, pp. 643-659, (2016); Consumers' Weekly Grocery Shopping Trips in the United States from 2006 to 2019, (2019); Heller M.C., Keoleian G.A., Willett W.C., Toward a Life Cycle-Based, Diet-Level Framework for Food Environmental Impact and Nutritional Quality Assessment: A Critical Review, Environ. Sci. Technol., 47, 22, pp. 12632-12647, (2013)","G.A. Keoleian; Center for Sustainable Systems, School for Environment and Sustainability, University of Michigan, Ann Arbor, 440 Church Street, 48109, United States; email: gregak@umich.edu",null,"American Chemical Society",{"$nulls":5},"0013936X",null,"ESTHA",3.5930734E7,"English","Environ. Sci. Technol.","Article","Final",null,"Scopus","2-s2.0-85136133538"]
["Jia X.","Jia, Xinzhong (57844015800)",5.78440158E10,"Research on the Optimization of Cold Chain Logistics Distribution Path of Agricultural Products E-Commerce in Urban Ecosystem From the Perspective of Carbon Neutrality",2022.0,"Frontiers in Ecology and Evolution",10.0,null,966111.0,null,null,null,4.0,"10.3389/fevo.2022.966111","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135936726&doi=10.3389%2ffevo.2022.966111&partnerID=40&md5=e4fa0154236d81f1e3cd13fdd048df55","School of Industry and Commerce, Shandong Management University, Jinan, China","Jia X., School of Industry and Commerce, Shandong Management University, Jinan, China","In order to further cope with climate change, achieve green and low-carbon economic development and further improve the construction of ecological civilization, a research method for optimization of cold chain logistics distribution path of agricultural products e-commerce from the perspective of carbon neutrality was proposed. This method takes full account of the requirements of distribution path optimization, it is based on ecological theory and applies ecological methods to study the structure, function and dynamics of human-centered urban ecosystems, as well as the laws of interaction between system components and between the system and the surrounding ecosystems, which is in line with the optimization goal of minimizing distribution operating costs, and the ant colony algorithm is used to construct the cost optimization model of cold chain logistics distribution path based on the weight limit of distribution vehicles and the time window limit. By comparison of simulation experiments, the best parameter solution is 2,873.9931. The difference with other combinations is only 1–2%, and the optimal parameter matching of the algorithm isα = 1,β = 2,ρ = 0.5. Experiments show that the optimal parameter combination is determined on the basis of reflecting different distribution results. Copyright © 2022 Jia.","carbon neutralization; cold chain logistics; distribution path; optimization; urban ecosystem",{"$nulls":7},"Aboulfotouh K., Cui Z., Williams R.O., Next-generation covid-19 vaccines should take efficiency of distribution into consideration, AAPS PharmSciTech, 22, 126, (2021); Chen Y., Location and path optimization of green cold chain logistics based on improved genetic algorithm from the perspective of low carbon and environmental protection, Fresenius Environ. Bull, 30, pp. 5961-5973, (2021); Cui H., Intelligent coordination distribution of the whole supply chain based on the internet of things, Complexity, 2021, pp. 1-12, (2021); Cui S., Pei X., Jiang Y., Wang G., Fan X., Yang Q., Et al., Liquefaction within a bedding fault: understanding the initiation and movement of the Daguangbao landslide triggered by the 2008 Wenchuan Earthquake (Ms = 8.0), Eng. Geol, 295, (2021); Dai Z., Ye C., Analysis and evaluation of key elements of optimal regulation of green supply chain from the perspective of low carbon, Wirel. Commun. Mob. Comput, 2022, pp. 1-11, (2022); Guo Z., Xiao Z., Research on online calibration of lidar and camera for intelligent connected vehicles based on depth-edge matching, Nonlinear Eng, 10, pp. 469-476, (2021); He Y., Kusiak A., Performance assessment of wind turbines: data-derived quantitative metrics, IEEE Trans. Sustain. Energy, 9, pp. 65-73, (2017); Huang R., Zhang S., Zhang W., Yang X., Progress of zinc oxide-based nanocomposites in the textile industry, IET Collab. Intell. Manuf, 3, pp. 281-289, (2021); Jani D.B., Supply cold chain and logistics in food industries, Sci. Technol. Built Environ, 16, pp. 18-21, (2021); Li H., Short-term wind power prediction via spatial temporal analysis and deep residual networks, Front. Energy Res, 10, (2022); Li H., SCADA data based wind power interval prediction using LUBE-based deep residual networks, Front. Energy Res, 10, (2022); Li H., Deng J., Feng P., Pu C., Arachchige D., Cheng Q., Short-term nacelle orientation forecasting using bilinear transformation and ICEEMDAN framework, Front. Energy Res, 9, (2021); Li H., Deng J., Yuan S., Feng P., Arachchige D., Monitoring and identifying wind turbine generator bearing faults using deep belief network and EWMA control charts, Front. Energy Res, 9, (2021); Li H., He Y., Xu Q., Deng J., Li W., Wei Y., Detection and segmentation of loess landslides via satellite images: a two-phase framework, Landslides, 19, pp. 673-686, (2022); Lian J., An optimization model of cross-docking scheduling of cold chain logistics based on fuzzy time window, J. Intell. Fuzzy Syst, 41, pp. 1901-1915, (2021); Liu X., Ahmadi Z., H2O and H2S adsorption by assistance of a heterogeneous carbon boron nitrogen nanocage: computational study, Main Group Chem, 21, pp. 185-193, (2021); Liu Z., Guo H., Zhao Y., Hu B., Huang B., Research on the optimized route of cold chain logistics transportation of fresh products in context of energy-saving and emission reduction, Math. Biosci. Eng, 18, pp. 1926-1940, (2021); Ning T., An L., Duan X., Optimization of cold chain distribution path of fresh agricultural products under carbon tax mechanism: a case study in china, J. Intell. Fuzzy Syst, 40, pp. 10549-10558, (2021); Qu X., Sun X., How to improve the function of government carbon tax in promoting enterprise carbon emission reduction: from the perspective of three-stage dynamic game, Environ. Sci. Pollu. Res, 29, pp. 31348-31362, (2022); Rollo A.M., Rollo A., Mora C., The tree-lined path to carbon neutrality, Nat. Rev. Earth Environ, 1, 332, (2020); Ross J.C., Saidu Y., NZuobontane D., Voukings M.Z., Embrey S.R., Application of the remaining vaccine vial monitor life calculation to field temperature monitoring data to improve visibility into cold chain equipment performance, Vaccine, 38, pp. 7683-7687, (2020); Sharma A., Kumar R., Risk-energy aware service level agreement assessment for computing quickest path in computer networks, Int. J. Reliab. Saf, 13, pp. 96-124, (2019); Shi M., Forecast of china’s carbon emissions under the background of carbon neutrality, Environ. Sci. Pollu. Res, 29, pp. 43019-43033, (2022); Shui W., Li M., Integrated pricing and distribution planning for community group purchase of fresh agricultural products, Sci. Program, 2020, pp. 1-15, (2020); Zhou J., Wei J., Yang T., Zhang P., Liu F., Chen J., Seepage channel development in the crown pillar: insights from induced microseismicity, Int. J. Rock Mech. Min. Sci, 145, (2021)","X. Jia; School of Industry and Commerce, Shandong Management University, Jinan, China; email: user05330533@126.com",null,"Frontiers Media S.A.",{"$nulls":5},"2296701X",null,null,null,"English","Front. ecol. evol.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85135936726"]
["Stroh A.M.; Erera A.L.; Toriello A.","Stroh, Alexander M. (57764973800); Erera, Alan L. (7801316807); Toriello, Alejandro (26634454600)","57764973800; 7801316807; 26634454600","Tactical Design of Same-Day Delivery Systems",2022.0,"Management Science",68.0,5.0,null,3444.0,3463.0,19.0,11.0,"10.1287/mnsc.2021.4041","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85132912719&doi=10.1287%2fmnsc.2021.4041&partnerID=40&md5=63b9c191f38a41c0d7b6b140ff4ba941","H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, 30332, GA, United States","Stroh A.M., H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, 30332, GA, United States; Erera A.L., H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, 30332, GA, United States; Toriello A., H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, 30332, GA, United States","We study tactical models for the design of same-day delivery (SDD) systems. Same-day fulfillment in e-commerce has seen substantial growth in recent years, and the underlying management of such services is complex. Although the literature includes operational models to study SDD, they tend to be detailed, complex, and computationally difficult to solve, and thus may not provide any insight into tactical SDD design variables and their impact on the average performance of the system. We propose a simplified vehicle-dispatching model that captures the “average” behavior of an SDD system from a single stocking location by utilizing continuous approximation techniques. We analyze the structure of optimal vehicle-dispatching policies given our model for two important instance families—the single-vehicle case and the case in which the delivery fleet is large—and develop techniques to find these policies that require only simple computations. We also leverage these results to analyze the case of a finite fleet, proposing a heuristic policy with a worst-case approximation guarantee. We then demonstrate with several example problem settings how this model and these policies can help answer various tactical design questions, including how to select a fleet size, determine an order cutoff time, and combine SDD and overnight order delivery operations. We validate model predictions empirically against a detailed operational model in a computational case study using geographic and Census data for the northeastern metro Atlanta region, and we demonstrate that our model predicts the average number of orders served and dispatch time to within 1%. Copyright: © 2021 INFORMS","e-commerce; same-day delivery; tactical design; vehicle routing","Electronic commerce; Fleet operations; Population statistics; Structural optimization; Vehicles; Delivery systems; Design variables; E- commerces; Operational modeling; Performance; Same-day delivery; Tactical design; Tactical models; Tacticals; Vehicles dispatching models; Vehicle routing",{"$nulls":6},"Albareda-Sambola M, Fernandez E, Laporte G, The dynamic multiperiod vehicle routing problem with probabilistic information, Comput. Oper. Res, 48, pp. 31-39, (2014); Amazon launches same day delivery in seven major cities and expands Saturday delivery options [press release], (2009); Prime free same-day delivery expands to 11 new metro areas [press release], (2016); Amazon expands free shipping to everyone for the holiday season [press release], (2018); Order with prime free same-day delivery, (2019); Applegate D, Bixby R, Chvatal V, Cook W, The Traveling Salesman Problem: A Computational Study, Princeton Series in Applied Mathematics, (2011); Beardwood J, Halton JH, Hammersley JM, The shortest path through many points, Math. Proc. Cambridge Philos. Soc, 55, 4, pp. 299-327, (1959); Bent RW, Van Hentenryck P, Scenario-based planning for partially dynamic vehicle routing with stochastic customers, Oper. Res, 52, 6, pp. 977-987, (2004); Digital commerce survey: Annual survey 2017, (2017); Campbell A, Thomas B, Probabilistic traveling salesman problem with deadlines, Transportation Sci, 42, 1, pp. 1-21, (2008); Carlsson JG, Dividing a territory among several vehicles, INFORMS J. Comput, 24, 4, pp. 565-577, (2012); Carlsson JG, Song S, Coordinated logistics with a truck and a drone, Management Sci, 64, 9, pp. 4052-4069, (2018); Ceven E, Gue KR, Optimal wave release times for order fulfillment systems with deadlines, Transportation Sci, 51, 1, pp. 52-66, (2017); Daganzo CF, The length of tours in zones of different shapes, Transportation Res. Part B Methodological, 18, 2, pp. 135-145, (1984); Same-day delivery, (2019); Figliozzi MA, Analysis of the efficiency of urban commercial vehicle tours: Data collection, methodology, and policy implications, Transportation Res. Part B Methodological, 41, 9, pp. 1014-1032, (2007); Franceschetti A, Jabali O, Laporte G, Continuous approximation models in freight distribution management, TOP, 25, 3, pp. 413-433, (2017); Johnson DS, McGeoch LA, Rothberg EE, Asymptotic experimental analysis for the Held-Karp traveling salesman bound, SODA’96 Proc. Seventh Annu. ACM-SIAM Sympos. Discrete Algorithms, pp. 341-350, (1996); Klapp M, Optimization for same-day delivery operations, (2016); Klapp MA, Erera AL, Toriello A, The dynamic dispatch waves problem for same-day delivery, Eur. J. Oper. Res, 271, 2, pp. 519-534, (2018); Klapp MA, Erera AL, Toriello A, The one-dimensional dynamic dispatch waves problem, Transportation Sci, 52, 2, pp. 402-415, (2018); Lim MK, Mak H-Y, Shen Z-JM, Agility and proximity considerations in supply chain design, Management Sci, 63, 4, pp. 1026-1041, (2017); Liu S, He L, Shen Z-JM, On-time last-mile delivery: Order assignment with travel-time predictors, Management Sci, (2020); Nabila A, Gendreau M, Potvin J-Y, A dynamic vehicle routing problem with multiple delivery routes, Ann. Oper. Res, 199, 1, pp. 103-112, (2012); Newell GF, Daganzo CF, Design of multiple-vehicle delivery tours I: A ring-radial network, Transportation Res. Part B Methodological, 20, 5, pp. 345-363, (1986); Distance matrix API, (2019); Reyes D, Erera AL, Savelsbergh MWP, Complexity of routing problems with release dates and deadlines, Eur. J. Oper. Res, 266, 1, pp. 29-34, (2018); Ulmer MW, Delivery deadlines in same-day delivery, Logistics Res, 10, 3, pp. 1-15, (2017); Ulmer MW, Dynamic pricing and routing for same-day delivery, Transportation Sci, 54, pp. 1016-1033, (2020); Ulmer MW, Thomas BW, Same-day delivery with a heterogeneous fleet of drones and vehicles, Networks, 72, 4, pp. 475-505, (2018); Ulmer MW, Thomas BW, Mattfeld DC, Preemptive depot returns for a dynamic same-day delivery problem, EURO J. Transportation Logist, 8, 4, pp. 327-361, (2019); Annual retail trade survey: Sales estimates (1992-2016), (2018); Census explorer, (2019); Van Heeswijk W, Mes M, Schutten J, The delivery dispatching problem with time windows for urban consolidation centers, Transportation Sci, 53, 1, pp. 203-221, (2019); Voccia SA, Campbell AM, Thomas BW, The probabilistic traveling salesman problem with time windows, EURO J. Transportation Logist, 2, 1-2, pp. 89-107, (2013); Voccia SA, Campbell AM, Thomas BW, The same-day delivery problem for online purchases, Transportation Sci, 53, 1, pp. 167-184, (2017); Wang H, Odoni A, Approximating the performance of a “last mile” transportation system, Transportation Sci, 50, 2, pp. 659-675, (2016)","A. Toriello; H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, 30332, United States; email: atoriello@isye.gatech.edu",null,"INFORMS Inst.for Operations Res.and the Management Sciences",{"$nulls":5},251909.0,null,"MSCIA",null,"English","Manage Sci","Article","Final",null,"Scopus","2-s2.0-85132912719"]
["Alkaabi K.A.","Alkaabi, Khaula Abdulla (16202142000)",1.6202142E10,"Customers’ purchasing behavior toward home-based SME products: evidence from UAE community",2022.0,"Journal of Enterprising Communities",16.0,3.0,null,472.0,493.0,21.0,4.0,"10.1108/JEC-11-2020-0187","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85108116495&doi=10.1108%2fJEC-11-2020-0187&partnerID=40&md5=9e8ba54c481a4f3799d981a1fcec7c20","Department of Geography and Urban Sustainability, United Arab Emirates University, Al Ain City, United Arab Emirates","Alkaabi K.A., Department of Geography and Urban Sustainability, United Arab Emirates University, Al Ain City, United Arab Emirates","Purpose: The purpose of this study is to explore factors influencing customers’ purchasing behavior toward home-based small and medium enterprise (SME) products. Moreover, this study explores customer perception of home-based SME products and services, as assesses their satisfaction with the parking area layouts and delivery service systems of home-based SMEs. Design/methodology/approach: Relevant variables were drawn from the literature review. A well-structured, internet-based customer questionnaire was developed for this empirical study and sent to a targeted sample of 117 respondents. The statistical methodologies such as ranking scale analysis, analysis of variance and Pearson’s correlation were used to assess the gathered data using SPSS software. Findings: The main findings revealed that 83% of the customers perceived the quality of home-based SME products and services as “at least good,” and that convenience was ranked as 21.1% with the most crucial factor for customers, which includes easy access, effective delivery and quicker processes. Moreover, the study reveals that approximately 50.4% of customers rated the parking area layouts as “at least good,” while 33.9% considered it dissatisfactory. The evidence from the correlation analysis indicates that consumers’ purchasing behavior correlates significantly with accessibility, ease of finding online shopping sites and availability of parking areas at a 95% significance level. Research limitations/implications: The research findings will bring insights to SME owners and entrepreneurs to infer and fulfill customer expectations and achieve brand loyalty. However, research limitations include the relatively small sample size, as well as the study, focuses on home-based SMEs’ consumer behavior which cannot be generalized to other firm types. Practical implications: This study provides useful information on the factors and issues influencing the purchasing behavior of customers toward home-based SME products in the UAE. Understanding of SMEs owners of customer experience would facilitate planning adequate strategies addressing customers’ needs, behaviors, expectations and future opportunities. Also, logistic and delivery companies can further support SME’s growth by providing an efficient delivery experience taking into consideration the quality of product condition and duration of the delivery cycle. Originality/value: Home-based SMEs are emerging as intrinsic to the economic diversification process, especially in fast-growing and ambitious countries such as the UAE. The research objectives have drawn a better understanding of consumers’ preferences, perceptions and purchasing behavior which would better facilitate the growth and sustainability of home-based SMEs based on the UAE context. © 2021, Emerald Publishing Limited.","ANOVA; Customer behavior; Customer perception; Home-based SMEs; Products and services; UAE",{"$nulls":5},"United Arab Emirates University, UAEU, (G00002615)","Funding: The project was funded by UAE University Office of Sponsored Research-Center for Public Policy and Leadership (Fund # G00002615; 2017-2019).","Alkaabi K., Effects of geographic distribution of small and medium-size enterprises on growth, innovation, and economic contributions: a case study of UAE, International Journal of Applied Geospatial Research (IJAGR), 11, 4, (2020); Ariff M.S.M., Yun L.O., Zakuan N., Ismail K., The impacts of service quality and customer satisfaction on customer loyalty in internet banking, Procedia - Social and Behavioral Sciences, 81, pp. 469-473, (2013); Bauboniene Z., Guleviciute G., E-commerce factors influencing consumers online shopping decision, Social Technologies, 5, 1, pp. 74-81, (2015); Brucks M., Zeithaml V.A., Naylor G., Price and brand name as indicators of quality dimensions for consumer durables, Journal of the Academy of Marketing Science, 28, 3, pp. 359-374, (2000); Calvo-Porral C., Levy-Mangin J.P., Store brands' purchase intention: examining the role of perceived quality, European Research on Management and Business Economics, 23, 2, pp. 90-95, (2017); Chen J., Development of Chinese small and medium-sized enterprises, Journal of Small Business and Enterprise Development, 13, 2, pp. 140-147, (2006); Chiou Y.C., Liu C.H., Advance purchase behaviors of air tickets, Journal of Air Transport Management, 57, pp. 62-69, (2016); Global innovation index 2020: who will finance innovations? Ithaca, Fontainebleau, and Geneva, (2020); Dubai statistics center news, (2018); Global ecommerce report, (2018); Farooq M.S., Salam M., Fayolle A., Jaafar N., Ayupp K., Impact of service quality on customer satisfaction in Malaysia airlines: a PLS-SEM approach, Journal of Air Transport Management, 67, pp. 169-180, (2018); Gerson R.F., Measuring customer satisfaction: a guide to managing quality service, (1993); Homburg C., Hoyer W.D., Koschate N., Customers' reactions to price increases: do customer satisfaction and perceived motive fairness matter, Journal of the Academy of Marketing Science, 33, 1, pp. 36-49, (2005); Hussain R., Al Nasser A., Hussain Y.K., Service quality and customer satisfaction of a UAE-based airline: an empirical investigation, Journal of Air Transport Management, 42, pp. 167-175, (2015); Iberahim H., Mohd Taufik N.K., Mohd Adzmir A.S., Saharuddin H., Customer satisfaction on reliability and responsiveness of self service technology for retail banking services, Procedia Economics and Finance, 37, pp. 13-20, (2016); MSME country indicators 2014, (2014); Jiang H., Zhang Y., An investigation of service quality, customer satisfaction and loyalty in China’s airline market, Journal of Air Transport Management, 57, pp. 80-88, (2016); Kasiri L.A., Guan Cheng K.T., Sambasivan M., Sidin S.M., Integration of standardization and customization: impact on service quality, customer satisfaction, and loyalty, Journal of Retailing and Consumer Services, 35, pp. 91-97, (2017); Kattara H.S., Weheba D., El-Said O.A., The impact of employee behaviour on customers' service quality perceptions and overall satisfaction, Tourism and Hospitality Research, 8, 4, pp. 309-323, (2008); Kim N.Y., Park J.W., A study on the impact of airline service delays on emotional reactions and customer behavior, Journal of Air Transport Management, 57, pp. 19-25, (2016); The truth about online consumers: 2017 global online consumer report, (2017); Lee W.I., Cheng S.Y., Shih Y.T., Effects among product attributes, involvement, word-of-mouth, and purchase intention in online shopping, Asia Pacific Management Review, 22, 4, pp. 223-229, (2017); Mandler T., Won S., Kim K., Consumers' cognitive and affective responses to brand origin misclassifications: does confidence in brand origin identification matter?, Journal of Business Research, 80, pp. 197-209, (2017); Munusamy J., Chelliah S., An investigation of impact of service strategy on customers’ satisfaction in the budget airline industry in Malaysia: a case study of Air Asia, Contemporary Marketing Review, 1, 1, pp. 1-13, (2011); Negricea C.I., Edu T., Avram E.M., Establishing influence of specific academic quality on student satisfaction, Procedia – Social and Behavioral Sciences, 116, pp. 4430-4435, (2014); Omar M.S., Ariffin H.F., Ahmad R., Service quality, customers’ satisfaction and the moderating effects of gender: a study of Arabic restaurants, Procedia - Social and Behavioral Sciences, 224, pp. 384-392, (2016); Papadopoulos N., Heslop L., Country equity and country branding: problems and prospects, Journal of Brand Management, 9, 4, pp. 294-314, (2002); Pharr J.M., Synthesizing country-of-origin research from the last decade: is the concept still salient in an era of global brands?, Journal of Marketing Theory and Practice, 13, 4, pp. 34-45, (2005); Top 10 countries, states and cities with the highest number of e commerce stores, (2018); Saleh Y., ICT, social media and COVID-19: evidence from informal home-based business community in Kuwait city, Journal of Enterprising Communities: People and Places in the Global Economy, (2020); Solomon M.R., Consumer Behavior: Buying, Having, and Being, (2009); Number of digital buyers worldwide from 2014 to 2021, (2018); Veale R., Quester P., Do consumer expectations match experience? Predicting the influence of price and country of origin on perceptions of product quality, International Business Review, 18, 2, pp. 134-144, (2009); World trade report 2016, (2016); Zavareh F.B., Ariff M.S.M., Jusoh A., Zakuan N., Bahari A.Z., Ashourian M., E-service quality dimensions and their effects on E-customer satisfaction in internet banking services, Procedia - Social and Behavioral Sciences, 40, pp. 441-445, (2012); Zhao R., Geng Y., Liu Y., Tao X., Xue B., Consumers’ perception, purchase intention, and willingness to pay for carbon-labeled products: a case study of Chengdu in China, Journal of Cleaner Production, 171, pp. 1664-1671, (2018); Gupta A.K., Shukla A.V., Store choice behaviour for consumer durables in NCT-Delhi: effect of shopper’s, Paradigm, 19, 2, pp. 152-169, (2015)","K.A. Alkaabi; Department of Geography and Urban Sustainability, United Arab Emirates University, Al Ain City, United Arab Emirates; email: khaula.alkaabi@uaeu.ac.ae",null,"Emerald Publishing",{"$nulls":5},1.7506204E7,null,null,null,"English","J. Enterprising Communities","Article","Final",null,"Scopus","2-s2.0-85108116495"]
["Miljenović D.; Beriša B.","Miljenović, Dejan (56401054000); Beriša, Bono (57790147900)","56401054000; 57790147900","Pandemics trends in E-commerce: drop shipping entrepreneurship during COVID-19 pandemic",2022.0,"Pomorstvo",36.0,1.0,null,31.0,43.0,12.0,5.0,"10.31217/p.36.1.4","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85133699652&doi=10.31217%2fp.36.1.4&partnerID=40&md5=cc1abebbcd0520e1ebb707de5162b2e7","University of Rijeka, Faculty of Economics and Business, Department of Entrepreneurial Economics, I. Filipovića 4, Rijeka, 51000, Croatia; University of St. Andrews, School of Management, The Gateway, N. Haugh, St. Andrews, KY16 9RJ, United Kingdom","Miljenović D., University of Rijeka, Faculty of Economics and Business, Department of Entrepreneurial Economics, I. Filipovića 4, Rijeka, 51000, Croatia; Beriša B., University of St. Andrews, School of Management, The Gateway, N. Haugh, St. Andrews, KY16 9RJ, United Kingdom","Drop shipping represents a delivery business model based on e-commerce logistics, which is very relevant in the global pandemic crisis. In this model, buyers order products and services directly from the manufacturer over the Internet through the intermediary of a drop shipper who ensures the easiest and fastest delivery. Drop shipper is a type of e-commerce entrepreneur that offers goods using online logistics infrastructure to ensure direct physical delivery from the manufacturer to the retailer or customer. This includes drop shipping as a business model to Industry 4.0 (i.e. the digital economy). This paper elaborates how a particular e-commerce model affects the development and improvement of global supply chains. Aim of this paper is to research how entrepreneur can lower its costs along drop shipping supply chain by managing inventory ratios or cost of stock. This enables drop shipping to greatly facilitate market access for cash-strapped entrepreneurs. We also conducted a simulation of optimized drop shipping process to show that there is a constant adaptability for entrepreneurs using drop shipping, especially among small and medium enterprises (SMEs). The timeliness of drop shipping is that it has facilitated as a global delivery solution in relation to the coronavirus disease pandemic (COVID-19). Moreover, drop shipping is based on a Activity-Based Costing (ABC model) whose quantitative efficiency has been proven by scientific analysis and research results. Finally, the legal aspects of drop shipping are given importance in the situation of COVID-19 which had a crucial impact on international trade in 2020, especially in predicting shortterm trade trends. Due to this within this paper we also examined the effects of the ˝coronavirus˝ on global e-commerce. Global drop shipping data ensures qualitative predictions considering pandemic environment, social distancing issues and internet trade curves which are more than useful in today’s changing business conditions. © 2022, University of Rijeka, Faculty of Maritime Studies Rijeka. All rights reserved.","COVID-19; Drop shipping; Entrepreneurship; International trade; Internet; Supply chain","COVID-19; electronic commerce; entrepreneur; epidemic; international trade; Internet; supply chain management",{"$nulls":6},"Aquino A., Social Media Challenges for Ecommerce Business in Coronavirus Crisis, (2020); Ayanso A., Moustapha D., Nair S. K., Inventory rationing via drop-shipping in Internet retailing: A sensitivity analysis, European Journal of Operational Research, 171, 1, pp. 135-152, (2006); Bailey J.P., Rabinovich E., The adoption of inventory postponement and speculation: An empirical assessment of oligopolistic Internet retailers, Transportation Research Part E: Logistics and Transportation Review, 42, 4, pp. 258-271, (2006); Chopra S., Meindl P., Supply Chain Management: Strategy, Planning and Operation, (2013); Cicak J., Računovodstveno procesiranje kriptovaluta, Računovodstvo, revizija I financije, 29, 1, pp. 57-62, (2019); Clement J., E-commerce share of total retail sales worldwide 2015-2023, (2019); Clement J., Global retail e-commerce sales 2014-2023, (2020); Content Square: l’impact du COVID-19 sur l’eCommerce, (2020); Creyts C. A., Weisskopf N., E-Commerce Drop shipping: Building a CPG Supply Chain, (2016); Hanser S., Jimenez G, Tulio F.O., Rodrigues, Misia M. Dantas, Cristiano A.V. Cavalcante: A dynamic inventory rationing policy for business-to-consumer e-tail stores in a supply disruption context, Computers & Industrial Engineering, 142, (2020); Khouja M., The evaluation of drop shipping option for e-commerce retailers, Computers & Industrial Engineering, 41, 2, pp. 109-126, (2001); The Future of the Medium-Sized Business: 7 Trends Driving SMEs’ Digital Transformation, (2019); Li F., Yijian T., Xiaolong G., Who is the free rider in the drop-shipping supply chain?, International Journal of Information Engineering and Electronic Business, 3, 3, (2011); Rabinovich E., Bailey J.P., Physical distribution service quality in Internet retailing: service pricing, transaction attributes, and firm attributes, Journal of Operations Management, 21, 6, pp. 651-672, (2004); Randall T., Netessine S., Rudi N., Should you take the virtual fulfillment path?, Supply Chain management Review, 6, 6, pp. 52-58, (2002); Reuschke D., Mason C., The engagement of home-based businesses in the digital economy, Futures, (2020); Sabanoglu T., Weekly trend in year-on-year growth of online retail orders in fashion and accessories category in the United Kingdom from January to April 2020, (2020); Samadi B., Nogoev A., Yazdanifard R., Mohseni S., The Evolution and Development of E-Commerce Market and E-Cash, 2nd International Conference on Measurement and Control Engineering, (2011); Daily containerized cargo traffic from China to the U.S. 2020; Szyszko M., Rutkowska A., Forward-looking component in consumers expectations and inflation forecast targeting: the case of six European economies, Proceeding of Rijeka Faculty of Economics: Journal of Economics and Business, 37, 1, pp. 77-112, (2019); Threlfall D., Drop shipping 101: How to start, run and grow an ecommerce business without inventory, (2011); Vasicek D., Dmitrovic V., Cicak J., Accounting of cryptocurrencies under IFRS, 8th INTERNATIONAL SCIENTIFIC SYMPOSIUM ECONOMY OF EASTERN CROATIA – VISION AND GROWTH, pp. 550-563, (2019); Xiao J., Wu Y., Xie K., Hu Q., Managing the e-commerce disruption with IT-based innovations: Insights from strategic renewal perspectives, Information & Management, 56, 1, pp. 122-139, (2019); Youderian A., Hayes M., The ultimate guide to drop shipping, (2013)","D. Miljenović; University of Rijeka, Faculty of Economics and Business, Department of Entrepreneurial Economics, Rijeka, I. Filipovića 4, 51000, Croatia; email: dejan.miljenovic@efri.hr",null,"University of Rijeka, Faculty of Maritime Studies Rijeka",{"$nulls":5},1.3320718E7,null,null,null,"English","Pomosrtvo","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85133699652"]
["He Z.; Pan W.","He, Zhongyu (55973244700); Pan, Weijie (57767219200)","55973244700; 57767219200","Food Acquisition during the COVID-19 Lockdown and Its Associations with the Physical–Digital Integrated Community Food Environment: A Case Study of Nanjing, China",2022.0,"International Journal of Environmental Research and Public Health",19.0,13.0,7993.0,null,null,null,1.0,"10.3390/ijerph19137993","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85132981817&doi=10.3390%2fijerph19137993&partnerID=40&md5=b870e19f3fec1710295cb1ca9715bf42","School of Architecture and Urban Planning, Nanjing University, Nanjing, 210093, China","He Z., School of Architecture and Urban Planning, Nanjing University, Nanjing, 210093, China; Pan W., School of Architecture and Urban Planning, Nanjing University, Nanjing, 210093, China","The COVID-19 pandemic and measures such as lockdowns affect food access, dietary choices, and food security. We conducted an online survey among 517 respondents during early 2020 in Nanjing, China to explore respondents’ food acquisition behaviors before and during the pandemic and associations with the community food environment. Using geographic analysis and binary logistic models, we revealed that despite inconvenience regarding food acquisition, no food security issues occurred during lockdown in Nanjing. The pandemic changed the access and frequency of obtaining food; meanwhile, pre-pandemic habits had a strong impact on food acquisition behavior. Online and in-store food acquisition showed a substitution relationship, with online food access playing a crucial role in food acquisition. Physical and digit food outlets are highly integrated in Chinese urban communities, and both objectively measured and perceived accessibility of these food outlets had a significant association with the food acquisition methods and transportation mode chosen by people during this public health crisis. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.","accessibility; community food environment; COVID-19; digital food environment; food acquisition; online shopping","China; Communicable Disease Control; COVID-19; Food; Humans; Pandemics; China; Jiangsu; Nanjing [Jiangsu]; accessibility; COVID-19; epidemic; food availability; food supplementation; food supply; information and communication technology; Internet; pandemic; public health; shopping activity; transportation mode; adult; Article; catering service; China; coronavirus disease 2019; food access; food industry; food security; geography; human; lockdown; major clinical study; online shopping; pandemic; public health problem; retail outlet; supermarket; traffic and transport; urban population; communicable disease control; epidemiology; food",{"$nulls":4},"National Science Foundation Committee of China, (51678288)","Funding: This research was funded by the National Science Foundation Committee of China under the Grant No. 51678288.","Kansiime M.K., Tambo J.A., Mugambi I., Bundi M., Kara A., Owuor C., COVID-19 implications on household income and food security in Kenya and Uganda: Findings from a rapid assessment, World Dev, 137, (2021); Ahmed S., Downs S.M., Yang C., Chunlin L., Broek N.T., Ghosh-Jerath S., Rapid tool based on a food environment typology framework for evaluating effects of the COVID-19 pandemic on food system resilience, Food Secur, 12, pp. 773-778, (2020); Hall C.M., Fieger P., Prayag G., Dyason D., Panic Buying and Consumption Displacement during COVID-19: Evidence from New Zealand, Economies, 9, (2021); Scarmozzion F., Visioli F., COVID-19 and the subsequent lockdown modified dietary habits of almost half the population in an Italian sample, Foods, 9, (2020); Braut B., Migheli M., Truant E., Household mobility in food purchasing during COVID-19 lockdown: Evidence from Torino, Italy, Cities, 122, (2022); Ben Hassen T., El Bilali H., Allahyari M.S., Impact of COVID-19 on food behavior and consumption in Qatar, Sustainability, 12, (2020); Adams E.L., Caccavale L.J., Smith D., Bean M.K., Food insecurity, the home food environment, and parent feeding practices in the era of COVID-19, Obesity, 28, pp. 2056-2063, (2020); Leone L.A., Fleischhacker S., Anderson S.B., Harper K., Winkler M., Racine E., Baquero B., Gittelsohn J., Healthy food retail during the COVID-19 pandemic: Challenges and future directions, Int. 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Food Sec, 18, pp. 93-101, (2018); Hu L., Zhao C., Wang M., Su S., Weng M., Wang W., Dynamic healthy food accessibility in a rapidly urbanizing metropolitan area: Socioeconomic inequality and relative contribution of local factors, Cities, 105, (2020); Glanz K., Salis J.F., Saelen B.E., Frank L.D., Healthy nutrition environments: Concepts and measures, Am. J. Health Promot, 19, pp. 330-333, (2005); Lytle L.A., Sokol R.L., Measures of the food environment: A systematic review of the field, 2007–2015, Health Place, 44, pp. 18-34, (2017); Gibson D.M., The neighborhood food environment and adult weight status: Estimates from longitudinal data, Am. J. 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Biol, 10, pp. 1-13, (2012); Kolak M., Bradley M., Block D.R., Pool L., Garg G., Toman C.K., Boatright K., Lipiszko D., Koschinsky J., Kershaw K., Et al., Urban foodscape trends: Disparities in healthy food access in Chicago, 2007–2014, Health Place, 52, pp. 231-239, (2018); Gregson J., Poverty, Sprawl, and Restaurant Types Influence Body Mass Index of Residents in California Counties, Public Health Rep, 126, pp. 141-149, (2011); Howard P.H., Fitzpatrick M., Fulfrost B., Proximity of food retailers to schools and rates of overweight ninth grade students: An ecological study in California, BMC Public Health, 11, (2011); Powell L.M., Bao Y., Food prices, access to food outlets and child weight, Econ. Hum. Biol, 7, pp. 64-72, (2009); Black J.L., Macinko J., Dixon L.B., Fryer J.G.E., Neighborhoods and obesity in New York City, Health Place, 16, pp. 489-499, (2010); Salois M.J., Obesity and diabetes, the built environment, and the ‘local’ food economy in the United States, 2007, Econ. Hum. Biol, 10, pp. 35-42, (2012); Gamba R.J., Schuchter J., Rutt C., Seto E.Y.W., Measuring the Food Environment and its Effects on Obesity in the United States: A Systematic Review of Methods and Results, J. Community Health, 40, pp. 464-475, (2014); Xu H.W., Short S.E., Liu T., Dynamic relations between fast-food restaurant and body weight status: A longitudinal and multilevel analysis of Chinese adults, J. Epidemiol. Community Health, 67, pp. 271-279, (2013); Ntarladima A., Karssenberg D., Poelman M., Grobbee D.E., Lu M., Schmitz O., Strak M., Janssen N., Hoek G., Vaartjes I., Associations between the fast-food environment and diabetes prevalence in the Netherlands: A cross-sectional study, Lancet Planet Health, 6, pp. e29-e39, (2022); Morland K.B., Evenson K.R., Obesity prevalence and the local food environment, Health Place, 15, pp. 491-495, (2009); Granheim S.I., Lovhaug A.L., Terragni L., Torheim L.E., Thurston M., Mapping the digital food environment: A systematic scoping review, Obes. Rev, 23, (2021); Brandt E.J., Silvestri D.M., Mande J.R., Holland M.L., Ross J.S., Availability of Grocery Delivery to Food Deserts in States Participating in the Online Purchase Pilot, JAMA Netw. Open, 2, (2019); Garaus M., Wagner U., Manzinger S., Happy grocery shopper: The creation of positive emotions through affective digital signage content, Technol. Forecast. Soc. Chang, 124, pp. 295-305, (2017); Shi K., Shao R., De Vos J., Witlox F., Do e-shopping attitudes mediate the effect of the built environment on online shopping frequency of e-shoppers?, Int. J. Sustain. Transp, 9, pp. 1-11, (2021); Huang Y.R., Huang D.N., Nguyen Q.C., Census tract food Tweets and chronic disease outcomes in the US, 2015–2018, Int. J. Environ. Res. Public Health, 16, (2019); Zhou P.L., Li R.F., Liu K., The neighborhood food environment and the onset of childhood obesity: A retrospective time-trend study in a mid-sized city in China, Front. Public Health, 9, (2021); Maimaiti M., Zhao X., Jia M., Ru Y., Zhu S., How we eat determines what we become: Opportunities and challenges brought by food delivery industry in a changing world in China, Eur. J. Clin. Nutr, 72, pp. 1282-1286, (2018); Yan S.J., Qu X.T., Lan Y.Y., Research on the Impact of New Retail on Consumer Behavior, Proceedings of the 2018 2nd International Conference on Advances in Management Science And Engineering (AMSE 2018), 292, pp. 287-294, (2018); Lu M.J., Wang R., Li P.Y., Comparative analysis of online fresh food shopping behavior during normal and COVID-19 crisis periods, Br. Food J, 124, pp. 968-986, (2021); Laguna L., Fiszman S., Puerta P., Chaya C., Tarrega A., The impact of COVID-19 lockdown on food priorities. Results from a preliminary study using social media and an online survey with Spanish consumers, Food Qual. Prefer, 86, (2020); Chen J., Zhang Y., Zhu S., Liu L., Does COVID-19 Affect the Behavior of Buying Fresh Food? Evidence from Wuhan, China, Int. J. Environ. Res. Public Health, 18, (2021); Shi K., De Vos J., Yang Y., Witlox F., Does e-shopping replace shopping trips? Empirical evidence from Chengdu, China, Transp. Res. Part A Policy Pract, 122, pp. 21-33, (2019); Cao X., The relationships between e-shopping and store shopping in the shopping process of search goods, Transp. Res. Part A, 46, pp. 993-1002, (2012); Pitt E., Gallegos D., Comans T., Cameron C., Thornton L., Exploring the influence of local food environments on food behaviours: A systematic review of qualitative literature, Public Health Nutr, 20, pp. 2393-2405, (2017); Karpyn A., Young C.R., Collier Z., Glanz K., Correlates of Healthy Eating in Urban Food Desert Communities, Int. J. Environ. Res. Public Health, 17, (2020); Fan S., Teng P., Chew P., Smith G., Copeland L., Food system resilience and COVID-19—Lessons from the Asian experience, Glob. Food Secur, 28, (2021); Chang M., Green L., Cummins S., All change. Has COVID-19 transformed the way we need to plan for a healthier and more equitable food environment?, Urban Des. Int, 26, pp. 291-295, (2021)","Z. He; School of Architecture and Urban Planning, Nanjing University, Nanjing, 210093, China; email: hezy@nju.edu.cn",null,"MDPI",{"$nulls":5},1.6617827E7,null,null,3.5805653E7,"English","Int. J. Environ. Res. Public Health","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85132981817"]
["Rokicki T.; Bórawski P.; Bełdycka-Bórawska A.; Szeberényi A.; Perkowska A.","Rokicki, Tomasz (57193094616); Bórawski, Piotr (56568304000); Bełdycka-Bórawska, Aneta (57202094055); Szeberényi, András (57226837859); Perkowska, Aleksandra (57213149715)","57193094616; 56568304000; 57202094055; 57226837859; 57213149715","Changes in Logistics Activities in Poland as a Result of the COVID-19 Pandemic",2022.0,"Sustainability (Switzerland)",14.0,16.0,10303.0,null,null,null,9.0,"10.3390/su141610303","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137747984&doi=10.3390%2fsu141610303&partnerID=40&md5=31e7d76fe8d1462fddae175c5d3e988c","Institute of Economics and Finance, Warsaw University of Life Sciences, Warsaw, 02-787, Poland; Faculty of Agriculture and Forestry, University of Warmia and Mazury in Olsztyn, Olsztyn, 10-719, Poland; Institute of Marketing, Budapest Metropolitan University, Budapest, 1148, Hungary","Rokicki T., Institute of Economics and Finance, Warsaw University of Life Sciences, Warsaw, 02-787, Poland; Bórawski P., Faculty of Agriculture and Forestry, University of Warmia and Mazury in Olsztyn, Olsztyn, 10-719, Poland; Bełdycka-Bórawska A., Faculty of Agriculture and Forestry, University of Warmia and Mazury in Olsztyn, Olsztyn, 10-719, Poland; Szeberényi A., Institute of Marketing, Budapest Metropolitan University, Budapest, 1148, Hungary; Perkowska A., Institute of Economics and Finance, Warsaw University of Life Sciences, Warsaw, 02-787, Poland","The main objective of this article is to identify the direction of change in logistical activities and their critical segments as a result of the COVID-19 pandemic in a country that is an important logistical hub of Europe. The specific objectives are to identify changes in logistical activities, especially during the COVID-19 pandemic, to determine the dynamics of changes in business revenues and in quantitative parameters for total logistics services and their segments during the pandemic, to establish the relationship between the economic situation and parameters related to logistics services, including during the COVID-19 pandemic. Using the method of purposive selection, Poland, which is well developed in logistics and aspires to be a crucial logistical hub of Europe, was selected for the study. The analysed period covered the years 2015–2021. The material sources were the literature on the subject and data from reports on individual logistics segments. Dynamic indicators with a fixed and variable base, coefficient of variation and Kendall’s tau correlation coefficient were used for analysis and presentation. It was found that the COVID-19 pandemic accelerated changes in logistics activities. These changes included digitalisation, the development of the e-commerce market, multi-channel sales and the development of these services, and the introduction of automation and artificial intelligence. In all activities, 2020 was the most challenging year, but there was generally a reduction in revenue growth and, less often, stagnation. Logistics companies gained in the second year of the pandemic (2021) when implemented solutions generated record revenues. Among the winning segments were logistics services in general, especially sea freight forwarding, warehousing services, courier services related to e-commerce, and a lesser extent, freight transport. Losses were incurred in the segment related to passenger transport. COVID-19 became a positive catalyst for change. The logistics industry ultimately benefited from the pandemic. Additionally, due to the pandemic, logistics operations have had greater sustainability, contributing to resource conservation and environmental protection. © 2022 by the authors.","courier services; digitisation of logistics; innovations in logistics; logistics companies; logistics market; passenger transport; smart logistics; transport of goods; warehouse rental; warehouse space","Europe; Poland [Central Europe]; electronic commerce",{"$nulls":6},"Erkan B., The importance and determinants of logistics performance of selected countries, J. Emerg. Issues Econ. Financ. 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Bus, 9, pp. 177-183, (2022); Liu W., Liang Y., Bao X., Qin J., Lim M.K., China’s logistics development trends in the post COVID-19 era, Int. J. Logist. Res. Appl, 25, pp. 965-976, (2022); Gupta A., Singh R.K., Applications of emerging technologies in logistics sector for achieving circular economy goals during COVID 19 pandemic: Analysis of critical success factors, Int. J. Logist. Res. Appl, 2021, pp. 1-22, (2021); Dovbischuk I., Innovation-oriented dynamic capabilities of logistics service providers, dynamic resilience and firm performance during the COVID-19 pandemic, Int. J. Logist. Manag, 33, pp. 499-519, (2022); Dilyard J., Zhao S., You J.J., Digital innovation and Industry 4.0 for global value chain resilience: Lessons learned and ways forward, Thunderbird Int. Bus. Rev, 63, pp. 577-584, (2021); Alesiuniene K.S., Simanaviciene Z., Bickauske D., Mosiiuk S., Belova I., Increasing the effectiveness of food supply chain logistics through digital transformation, Indep. J. Manag. Prod, 12, pp. 677-701, (2021); Lachvajderova L., Kadarova J., Kopec J., Rybarova D., Postpandemic innovative trends in logistics, distribution and supply chain, Adv. Logist. Syst. Theory Pract, 16, pp. 19-30, (2022); de Andres Gonzalez O., Koivisto H., Mustonen J.M., Keinanen-Toivola M.M., Digitalization in Just-In-Time Approach as a Sustainable Solution for Maritime Logistics in the Baltic Sea Region, Sustainability, 13, (2021); Pernestal A., Engholm A., Bemler M., Gidofalvi G., How Will Digitalization Change Road Freight Transport? Scenarios Tested in Sweden, Sustainability, 13, (2020); Todorovic V., Maslaric M., Bojic S., Jokic M., Mircetic D., Nikolicic S., Solutions for More Sustainable Distribution in the Short Food Supply Chains, Sustainability, 10, (2018)","T. Rokicki; Institute of Economics and Finance, Warsaw University of Life Sciences, Warsaw, 02-787, Poland; email: tomasz_rokicki@sggw.edu.pl",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85137747984"]
["Wahyudi T.; Arroufu D.S.","Wahyudi, Tri (58125650800); Arroufu, Dava Septya (58125650900)","58125650800; 58125650900","IMPLEMENTATION OF DATA MINING PREDICTION DELIVERY TIME USING LINEAR REGRESSION ALGORITHM",2022.0,"Journal of Applied Engineering and Technological Science",4.0,1.0,null,84.0,92.0,8.0,2.0,"10.37385/jaets.v4i1.918","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85149262490&doi=10.37385%2fjaets.v4i1.918&partnerID=40&md5=d21a6b493111ec77d4a14a0a5128e3d3","Information System Department, STIKOM Cipta Karya Informatika, Jakarta, Indonesia","Wahyudi T., Information System Department, STIKOM Cipta Karya Informatika, Jakarta, Indonesia; Arroufu D.S., Information System Department, STIKOM Cipta Karya Informatika, Jakarta, Indonesia","In the current era of modernization, online shopping has become a habit of the people, and is closely related to freight forwarding services in charge of delivering online shopping items from the seller to the buyer. So that buyers need a fast and safe delivery service to ensure the goods sent on time to their destination. Customer satisfaction is one of the most important factors in the shipping business. However, there are several obstacles that occur in the field that cause delays in the delivery of goods. Therefore, one solution that can be used to overcome this problem is to use data mining technology to predict delivery times. Using 1,000 datasets consisting of 4 Attributes, data processing will be carried out with prediction techniques using the Linear Regression algorithm. By utilizing data when the goods are taken, when the goods are on the way, until they reach the buyer, they can produce forecasts or predictions and produce several analyzes so that in the future there will be no delivery delays. Based on the RMSE (Root Mean Square Error) value which serves to generate the level value the error of the prediction results using this method and in an RMSE value of 0.370 %. It can be concluded that using the Linear Regression algorithm is proven to be accurate in predicting delivery times. © 2022, Intellectual Research and Development Education Foundation (YRPI). All rights reserved.","Data Mining; Delivery; Linear Regression; Prediction",{"$nulls":7},"Ahmad R., Alsmadi I., Machine learning approaches to IoT security: A systematic literature review, Internet of Things, 14, (2021); Artin J., Valizadeh A., Ahmadi M., Kumar S. A., Sharifi A., Presentation of a novel method for prediction of traffic with climate condition based on ensemble learning of neural architecture search (NAS) and linear regression, Complexity, (2021); Baihaqi D. I., Handayani A. N., Pujianto U., Rahman A. A., Kurniawan Y. I., Sulaksono J., Irawan R. H., Fahmi I. N., Iman Q., Wahyu A., Agustina W., Furqon M. T., Rahayudi B., Tungadi E., Thalib I., Nur M., Utomo Y., Firasari E., Khultsum U., Sosial B., Klasterisasi Dana Bantuan Pada Program Keluarga Harapan (PKH) Menggunakan Metode K-Means, Jurnal Teknologi Informasi Dan Ilmu Komputer, 3, 1, pp. 1231-1236, (2021); Bengnga A., Ishak R., Prediksi Jumlah Mahasiswa Registrasi Per Semester Menggunakan Linier Regresi Pada Universitas Ichsan Gorontalo, ILKOM Jurnal Ilmiah, 10, 2, pp. 136-143, (2018); Camargo C., Goncalves J., Conde M. A., Rodriguez-Sedano F. J., Costa P., Garcia-Penalvo F. J., Systematic Literature Review of Realistic Simulators Applied in Educational Robotics Context, Sensors, 21, 12, (2021); Cosenza D. N., Korhonen L., Maltamo M., Packalen P., Strunk J. L., Naesset E., Tome M., Comparison of linear regression, k-nearest neighbour and random forest methods in airborne laser-scanning-based prediction of growing stock, Forestry: An International Journal of Forest Research, 94, 2, pp. 311-323, (2021); Emioma C. C., Edeki S. O., Stock price prediction using machine learning on least-squares linear regression basis, Journal of Physics: Conference Series, 1734, 1, (2021); Hafizah Tugiono, Maya W. R., Penerapan Data Mining Dalam Memprediksi Jumlah Penumpang Pada CV. Surya Mandiri Sukses Dengan Menggunakan Metode Regresi Linier, Jurnal Teknologi Informasi Dan Sistem Komputer TGD, 2, 1, pp. 54-61, (2019); Hasanah M. A., Soim S., Handayani A. S., Implementasi CRISP-DM Model Menggunakan Metode Decision Tree dengan Algoritma CART untuk Prediksi Curah Hujan Berpotensi Banjir, Journal of Applied Informatics and Computing, 5, 2, pp. 103-108, (2021); Hertina H., Nurwahid M., Haswir H., Sayuti H., Darwis A., Rahman M., Hamzah M. L., Data mining applied about polygamy using sentiment analysis on Twitters in Indonesian perception, Bulletin of Electrical Engineering and Informatics, 10, 4, pp. 2231-2236, (2021); Gilyen A., Song Z., Tang E., An improved quantum-inspired algorithm for linear regression, Quantum, 6, (2022); Kohli S., Godwin G. T., Urolagin S., Sales prediction using linear and KNN regression, Advances in machine learning and computational intelligence, pp. 321-329, (2021); Kumar S., Kar A. K., Ilavarasan P. V., Applications of text mining in services management: A systematic literature review, International Journal of Information Management Data Insights, 1, 1, (2021); Laia D., Buulolo E., Sirait M. J. F., Implementasi Data Mining Untuk Memprediksi Pemesanan Driver Go-Jek Online Dengan Menggunakan Metode Naive Bayes (Studi Kasus: Pt. Go-Jek Indonesia), KOMIK (Konferensi Nasional Teknologi Informasi Dan Komputer), 2, 1, pp. 434-439, (2018); Liantoni F., Klasifikasi Daun Dengan Perbaikan Fitur Citra Menggunakan Metode K-Nearest Neighbor, Jurnal ULTIMATICS, 7, 2, pp. 98-104, (2016); Nofitri R., Irawati N., Integrasi Metode Neive Bayes Dan Software Rapidminer Dalam Analisis Hasil Usaha Perusahaan Dagang, JURTEKSI (Jurnal Teknologi Dan Sistem Informasi), 6, 1, pp. 35-42, (2019); Ozturk O. B., Basar E., Multiple linear regression analysis and artificial neural networks based decision support system for energy efficiency in shipping, Ocean Engineering, 243, (2022); Pink M., Djohan N., Effect of ecommerce post-purchase activities on customer retention in Shopee Indonesia, Enrichment: Journal of Management, 12, 1, pp. 519-526, (2021); Saltz J. S., CRISP-DM for Data Science: Strengths, Weaknesses and Potential Next Steps, 2021 IEEE International Conference on Big Data (Big Data), pp. 2337-2344, (2021); Schroer C., Kruse F., Gomez J. M., A systematic literature review on applying CRISP-DM process model, Procedia Computer Science, 181, pp. 526-534, (2021); Widiyanto P., Endri E., Sakti R. F. J., Setiawan E. B., Manfaluthy M., Suryaningsih L., Limakrisna N., The relationship between service quality, timeliness of arrival, departure flip ship logistics and people and customer satisfaction: A case in Indonesia, Academy of Entrepreneurship Journal, 27, 6, pp. 1-12, (2021); Zhang Y., Sales Forecasting of Promotion Activities Based on the Cross-Industry Standard Process for Data Mining of E-commerce Promotional Information and Support Vector Regression, J. Comput, 32, pp. 212-225, (2021)","T. Wahyudi; Information System Department, STIKOM Cipta Karya Informatika, Jakarta, Indonesia; email: triwahyudi100390@gmail.com",null,"Intellectual Research and Development Education Foundation (YRPI)",{"$nulls":5},2.7156087E7,null,null,null,"English","J. Appl. Eng. Technol. Sci.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85149262490"]
["Yan Y.; Chow A.H.F.; Ho C.P.; Kuo Y.-H.; Wu Q.; Ying C.","Yan, Yimo (57673562500); Chow, Andy H.F. (57672460900); Ho, Chin Pang (56145479500); Kuo, Yong-Hong (57200538311); Wu, Qihao (57674114700); Ying, Chengshuo (57202425435)","57673562500; 57672460900; 56145479500; 57200538311; 57674114700; 57202425435","Reinforcement learning for logistics and supply chain management: Methodologies, state of the art, and future opportunities",2022.0,"Transportation Research Part E: Logistics and Transportation Review",162.0,null,102712.0,null,null,null,36.0,"10.1016/j.tre.2022.102712","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85129696892&doi=10.1016%2fj.tre.2022.102712&partnerID=40&md5=9efb5306f7b2e34a7b37a6ca9ebcb43f","Department of Industrial and Manufacturing Systems Engineering, the University of Hong Kong, Hong Kong; Department of Advanced Design and Systems Engineering, City University of Hong Kong, Hong Kong; School of Data Science, City University of Hong Kong, Hong Kong; HKU Musketeers Foundation Institute of Data Science, the University of Hong Kong, Hong Kong; Yangtze Delta Region Academy of Beijing Institute of Technology, China","Yan Y., Department of Industrial and Manufacturing Systems Engineering, the University of Hong Kong, Hong Kong; Chow A.H.F., Department of Advanced Design and Systems Engineering, City University of Hong Kong, Hong Kong; Ho C.P., School of Data Science, City University of Hong Kong, Hong Kong; Kuo Y.-H., Department of Industrial and Manufacturing Systems Engineering, the University of Hong Kong, Hong Kong, HKU Musketeers Foundation Institute of Data Science, the University of Hong Kong, Hong Kong; Wu Q., Department of Industrial and Manufacturing Systems Engineering, the University of Hong Kong, Hong Kong; Ying C., Yangtze Delta Region Academy of Beijing Institute of Technology, China","With advances in technologies, data science techniques, and computing equipment, there has been rapidly increasing interest in the applications of reinforcement learning (RL) to address the challenges resulting from the evolving business and organisational operations in logistics and supply chain management (SCM). This paper aims to provide a comprehensive review of the development and applications of RL techniques in the field of logistics and SCM. We first provide an introduction to RL methodologies, followed by a classification of previous research studies by application. The state-of-the-art research is reviewed and the current challenges are discussed. It is found that Q-learning (QL) is the most popular RL approach adopted by these studies and the research on RL for urban logistics is growing in recent years due to the prevalence of E-commerce and last mile delivery. Finally, some potential directions are presented for future research. © 2022 Elsevier Ltd","Actor-critic methods; Logistics; Markov decision process; Neural network; Q-learning; Reinforcement learning; Supply chain","Learning systems; Markov processes; Supply chain management; Actor-Critic methods; Logistics and supply chain management; Management methodologies; Markov Decision Processes; Neural-networks; Organisational; Q-learning; Reinforcement learnings; State of the art; Technology data; artificial neural network; electronic commerce; future prospect; logistics; machine learning; Markov chain; supply chain management; urban transport; Reinforcement learning",{"$nulls":4},"Chow Sang Sang Group Research Fund; Chow Sang Sang Holdings International Limited, (9229059, 9229076); Germany/Hong Kong Joint Research Scheme Germany Academic Exchange Service; Guangdong Special Support Talent Program – Innovation and Entrepreneurship Leading Team, (2019BT02S593); Deutscher Akademischer Austauschdienst, DAAD, (G-HKU703/19); National Natural Science Foundation of China, NSFC, (72032005); Research Grants Council, University Grants Committee, 研究資助局, (17200820)","The authors are grateful to the Co-EIC, Associate Editor, and Reviewers for their comments and suggestions. The work described in this paper was partially supported by grants from Chow Sang Sang Group Research Fund sponsored by Chow Sang Sang Holdings International Limited (Project No. 9229059 and 9229076 ). The research of the third author was partially supported by the National Natural Science Foundation of China (Project No. 72032005 ). The research of the fourth author was partially supported by the Research Grants Council (RGC) (General Research Fund) 17200820 ), the Germany/Hong Kong Joint Research Scheme Germany Academic Exchange Service (DAAD) and RGC of Hong Kong ( G-HKU703/19 ), and the 2019 Guangdong Special Support Talent Program – Innovation and Entrepreneurship Leading Team (China) ( 2019BT02S593 ). ",{"$cut":{"chars":32725,"head":"Achamrah F.E., Riane F., Limbourg S., Solving inventory routing with transshipment and substitution under dynamic and stochastic demands using genetic algorithm and deep reinforcement learning, Int. J. Prod. Res., pp. 1-18, (2021); Afridi M.T., Nieto-Isaza S., Ehm H., Ponsignon T., Hamed A., A deep reinforcement learning approach for optimal replenishment policy in a vendor managed inventory setting for semiconductors, 2020 Winter Simulation Conference (WSC), pp. 1753-1764, (2020); Ahamed T., Zou B., Farazi N., Tulabandhula T., Deep reinforcement learning for crowdsourced urban delivery: System states characterization, heuristics-guided action choice, and rule-interposing integration, (2020); Ahamed T., Zou B., Farazi N.P., Tulabandhula T., Deep reinforcement learning for crowdsourced urban delivery, Transp. Res. B, 152, pp. 227-257, (2021); Ahn K., Park J., Cooperative zone-based rebalancing of idle overhead hoist transportations using multi-agent reinforcement learning with graph representation learning, IISE Trans., 53, 10, pp. 1140-1156, (2021); Aissani N., Bekrar A., Trentesaux D., Beldjilali B., Dynamic scheduling for multi-site companies: A decisional approach based on reinforcement multi-agent learning, J. Intell. Manuf., 23, 6, pp. 2513-2529, (2012); Alkouz B., Bouguettaya A., A reinforcement learning approach for re-allocating drone swarm services, (2021); Alves J.C., Mateus G.R., Deep reinforcement learning and optimization approach for multi-echelon supply chain with uncertain demands, International Conference on Computational Logistics, pp. 584-599, (2020); Alves J.C., Silva D.M.D., Mateus G.R., Applying and comparing policy gradient methods to multi-echelon supply chains with uncertain demands and lead times, International Conference on Artificial Intelligence and Soft Computing, pp. 229-239, (2021); Andersen P., Goodwin M., Granmo O., Towards model-based reinforcement learning for industry-near environments, International Conference on Innovative Techniques and Applications of Artificial Intelligence, pp. 36-49, (2019); Ardestani-Jaafari A., Delage E., The value of flexibility in robust location–transportation problems, Transp. Sci., 52, 1, pp. 189-209, (2018); Asadi A., Nurre Pinkley S., A stochastic scheduling, allocation, and inventory replenishment problem for battery swap stations, Transp. Res. E, 146, (2021); Asadi A., Pinkley S.N., Drones for medical delivery considering different demands classes: A Markov decision process approach for managing health centers dispatching medical products, (2021); Bacon P.-L., Harb J., Precup D., (2017); Bae J., Gandhi D., Kothari J., Shankar S., Bae J., Patwa P., Sukumaran R., TV S., Yu V., Misra K., Murali S., Saxena A., Jakimowicz K., Sharma V., Iyer R., Mehra A., Radunsky A., Katiyar P., Anand S., Advani S., Dhaliwal J., Raskar R., Challenges in equitable COVID-19 vaccine distribution: A roadmap for digital technology solutions, (2021); Behzadian B., Hasan Russel R., Petrik M., Ho C.P., Optimizing percentile criterion using robust MDPs, Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, Proceedings of Machine Learning Research, 130, pp. 1009-1017, (2021); Bellemare M.G., Dabney W., Munos R., A distributional perspective on reinforcement learning, International Conference on Machine Learning, pp. 449-458, (2017); Bello I., Pham H., Le Q.V., Norouzi M., Bengio S., Neural combinatorial optimization with reinforcement learning, (2016); Bertsekas D., Reinforcement and Optimal Control, (2019); Bertsekas D., Rollout, Policy Iteration, and Distributed Reinforcement Learning, (2021); Bertsimas D., Thiele A., A robust optimization approach to inventory theory, Oper. Res., 54, 1, pp. 150-168, (2006); Bono G., Dibangoye J.S., Matignon L., Pereyron F., Simonin O., SULFR: Simulation of urban logistic for reinforcement, PGMRL 2018Workshop on Prediction and Generative Modeling in Reinforcement Learning, pp. 1-5, (2018); Boute R.N., Gijsbrechts J., van Jaarsveld W., Vanvuchelen N., Deep reinforcement learning for inventory control: A roadm"}},"Y.-H. Kuo; Department of Industrial and Manufacturing Systems Engineering, the University of Hong Kong, Hong Kong; email: yhkuo@hku.hk",null,"Elsevier Ltd",{"$nulls":5},1.3665545E7,null,null,null,"English","Transp. Res. Part E Logist. Transp. Rev.","Article","Final",null,"Scopus","2-s2.0-85129696892"]
["Juliet Orji I.; Ojadi F.; Kalu Okwara U.","Juliet Orji, Ifeyinwa (56406384000); Ojadi, Frank (55837756700); Kalu Okwara, Ukoha (57360462600)","56406384000; 55837756700; 57360462600","The nexus between e-commerce adoption in a health pandemic and firm performance: The role of pandemic response strategies",2022.0,"Journal of Business Research",145.0,null,null,616.0,635.0,19.0,29.0,"10.1016/j.jbusres.2022.03.034","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85126627256&doi=10.1016%2fj.jbusres.2022.03.034&partnerID=40&md5=933ee533986ceac9ccb2a0b770ca8384","Research Center for Smarter Supply Chain, Dongwu Business School, Soochow University, Jiangsu Province, Suzhou, 215021, China; Department of Operations Management, Lagos Business School, Pan- Atlantic University, Lagos, Nigeria; Department of Economics and Development Studies, Alex Ekwueme Federal University, Ebonyi State, Nigeria","Juliet Orji I., Research Center for Smarter Supply Chain, Dongwu Business School, Soochow University, Jiangsu Province, Suzhou, 215021, China; Ojadi F., Department of Operations Management, Lagos Business School, Pan- Atlantic University, Lagos, Nigeria; Kalu Okwara U., Department of Economics and Development Studies, Alex Ekwueme Federal University, Ebonyi State, Nigeria","This paper takes the initial step in exploring how pandemic response strategies interact with other enablers of e-commerce adoption in the logistics sector and also determines their effect on firm performance. Drawing on a rich data pool from selected Nigerian logistics firms in the global logistics value chains, the interrelationships between the pandemic response strategies and other e-commerce adoption enablers were obtained using an intuitionistic-based decision-making trial and evaluation laboratory (IF- DEMATEL). A robust ranking of these was determined using multi-objective optimization based on ratio analysis plus full multiplicative form (MULTIMOORA). Then, the effect of the e-commerce adoption enablers on firm performance and the mediating role of pandemic response strategies on this relationship were determined using simple additive weighting (SAW). The results indicate that technical related enablers are the highest ranked followed by pandemic response strategies and suggest that e-commerce adoption in a health pandemic is strongly linked with financial and operational benefits. Specifically, the technical enablers have the highest effect on delivery time while pandemic response strategies have the highest effect on profit and customer satisfaction. Moreover, pandemic response strategies partially mediate the relationship between other e-commerce adoption enablers and firm performance. Hence, this study provides significant constructs that enrich the literature on IT adoption in a health pandemic for the increased competitiveness of global value chains. © 2022 Elsevier Inc.","COVID-19 pandemic; E- commerce; Global value chain; Logistics firms; Supply chain management",{"$nulls":7},{"$cut":{"chars":25680,"head":"Abed S.S., Social commerce adoption using TOE framework: An empirical investigation of Saudi Arabian SMEs, International Journal of Information Management, 53, (2020); Abou- Shouk M.A., Lim W.M., Megicks P., Using competing models to evaluate the role of environmental pressures in ecommerce adoption by small and medium sized travel agents in a developing country, Tourism Management, 52, pp. 327-339, (2016); Abumalloh R.A., Ibrahim O., Nilashi M., Loyalty of young female Arabic customers towards recommendation agents: A new model for B2C E-commerce, Technology in Society, 61, (2020); Ahmadi H., Nilashi M., Shamoradi L., Ibrahim O., Hospital information system adoption: Expert perspectives on an adoption framework for Malaysian public hospitals, Computers in Human Behavior, 67, pp. 161-189, (2017); Ali I., Arslan A., Chowdhury M., Khan Z., Tarba S.Y., Reimagining global food value chains through effective resilience to COVID-19 shocks, Journal of Business Research, (2021); Asante D., He Z., Adjei N.O., Asante B., Exploring the barriers to renewable energy adoption utilizing MULTIMOORA- EDAS method, Energy Policy, 142, (2020); Asosheh A., pp. 136-145, (2012); Balmer J.M.T., Lin Z., Chen W., He X., The role of corporate brand image for B2B relationships of logistics service providers in China, Journal of Business Research, 117, pp. 850-861, (2020); Barkatullah A.H., Djumadi, Does self- regulation provide legal protection and security to e-commerce consumers?, Electronic Commerce Research and Applications, 30, pp. 94-101, (2018); Barenji A.V., Wang W.M., Li Z., Guerra- Zubiaga D.A., Intelligent e- commerce logistics platform using hybrid agent based approach, Transportation Research Part E: Logistics and Transportation Review, 126, pp. 15-31, (2019); Barnes S.J., Information management research and practice in the post- COVID- 19 world, International Journal of Information Management, 55, (2020); Barney J.B., Firm resources and sustained competitive advantage, Journal of Management, 17, 1, pp. 99-121, (1991); Benitez J., Ray G., Henseler J., Impact of information technology infrastructure flexibility on mergers and acquisitions, MIS Quarterly, 42, 1, pp. 25-43, (2018); Benitez J., Chen Y., Teo T., Ajamieh A., Evolution of the impact of e-business technology on operational competence and firm profitability: A panel data investigation, Information Management, 55, 1, pp. 120-130, (2018); Biswas T.K., Abbasi A., Chakrabortty R.K., An MCDM integrated adaptive simulated annealing approach for influence maximization in social networks, Information Sciences, 556, pp. 27-48, (2021); Brauers W.K.M., (2010); Brauers W.K.M., Zavadskas E.K., MULTIMOORA optimization used to decide on a bank loan to buy property, Technological and Economic Development of Economy, 17, 1, pp. 174-188, (2011); Budd L., Ison S., Responsible transport: A post-covid-19 agenda for transport policy and practice, Transportation Research Interdisciplinary perspectives, 6, 100, (2020); Burgos D., Ivanov D., Food retail supply chain resilience and the COVID-19 pandemic: A digital twin-based impact analysis and improvement directions, Transportation Research Part E: Logistics and Transportation Review, 152, (2021); Buyukozkan G., Guleryuz S., Karpak B., A new combined IF- DEMATEL and IF- ANP approach for CRM partner evaluation, International Journal of Production Economics, 191, pp. 194-206, (2017); Campbell-Grossman C., Hudson D.B., Hanna K.M., Ramamurthy B., Sivadasan V., Ease of use and acceptability of a smartphone app for young, low- income mothers, Journal of Technological Behavioral Science, 3, pp. 5-11, (2018); Chahal H., Gupta m., Bhan N. & Cheng T.C.E., Operations management research grounded in the resource-based view: A meta- analysis, International Journal of Production Economics, 230, (2020); Chaparro- P.J., Agudo- Peregrina A.F., Pascual- Miguel F.J., Conjoint analysis of drivers and inhibitors of e- commerce adoption, Journal of Business Research, 69, 4, pp. 1277-1282, (2016); Chen P., Effects of the entropy weight on TOPSIS, Expert Systems with Applicat"}},"I. Juliet Orji; Research Center for Smarter Supply Chain, Dongwu Business School, Soochow University, Suzhou, Jiangsu Province, 215021, China; email: ifyorji09@yahoo.com",null,"Elsevier Inc.",{"$nulls":5},1482963.0,null,"JBRED",null,"English","J. Bus. Res.","Article","Final",null,"Scopus","2-s2.0-85126627256"]
["Karaoǧlu M.; Kara G.","Karaoǧlu, Mehmet (57242785700); Kara, Gökhan (13409011000)","57242785700; 13409011000","Two-Stage Heuristic Algorithm Proposal for Urban E-Commerce Deliveries",2022.0,"Asia-Pacific Journal of Operational Research",39.0,3.0,2150034.0,null,null,null,2.0,"10.1142/S0217595921500342","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85114105918&doi=10.1142%2fS0217595921500342&partnerID=40&md5=a5495bc335da83a9380b02984be3f875","Department of Transportation Services, Mersin University, Mersin, Turkey; Department of Maritime Transportation, Management Engineering, Istanbul University-Cerrahpaşa, Istanbul, 34320, Turkey","Karaoǧlu M., Department of Transportation Services, Mersin University, Mersin, Turkey; Kara G., Department of Maritime Transportation, Management Engineering, Istanbul University-Cerrahpaşa, Istanbul, 34320, Turkey","In today's intensive competition conditions, it is an inevitable necessity for the companies operating in the e-commerce sector to manage their physical distribution processes efficiently and effectively. The most important step in e-commerce logistics processes is the last step delivery operations in the city. In order for these operations to be carried out quickly and efficiently, delivery vehicles and personnel must be optimally led. These problems, referred to as vehicle routing problem (VRP) in the literature, include determining the least cost routes that vehicles will cover to meet customer needs. In this study, the urban delivery problems of the enterprises operating in the online retail sector are examined. In line with these problems, VRP for urban e-commerce deliveries has been modified; open, multi-depot, distribution aggregation, time-window VRP is discussed. A mathematical model for the modified VRP has been developed and a new heuristic algorithm consisting of two stages has been developed for large-scale problems. The developed algorithm was tested on three different cases. The results are compared with the solution of the nearest neighbor method and the performance of the proposed algorithm is presented.  © 2022 World Scientific Publishing Co.","E-logistics; physical distribution; vehicle routing problems","Heuristic algorithms; Vehicle routing; Vehicles; Delivery vehicle; Distribution process; Large-scale problem; Least cost routes; Logistics process; Nearest neighbor method; Two-stage heuristic algorithms; Vehicle routing problem; Electronic commerce",{"$nulls":6},"Atmaca E, Bir kargo ?sirketinde ara?c rotalama problemi ve uygulamasi, Turk Bilim Araşt?rma Vakf?Dergisi, 2, 5, pp. 12-27, (2012); Bae H, Moon I, Multi-depot vehicle routing problem with time windows considering delivery and installation vehicles, Applied Mathematical Modelling, 40, pp. 6536-6549, (2016); Ballou RH, Business Logistics Management Planning, Organizing, and Controlling the Supply Chain, (1999); Baykasoglu A, Kaplanoglu V, A multi-Agent approach to load consolidation in transportation, Advances in Engineering Software, 42, 7, pp. 477-490, (2011); Bayles D, E-Commerce Logistics & Fulfilment: Delivering the Goods, (2001); Bellmore M, Nemhauser GL, The traveling salesman problem: A survey, Operations Research, 16, pp. 538-558, (1968); Bianchess N, Righini G, Heuristic algorithms for the vehicle routing problem with simultaneous pick-up and delivery, Computers & Operations Research, 34, pp. 578-594, (2009); Bromage N, Keep the customer satisfied, Supply Management, 6, 10, pp. 34-36, (2001); Christofides N, Mingozzi A, Toth P, The vehicle routing problem, Combinatorial Optimization, (1979); Clarke G, Wright JW, Scheduling of vehicles from a central depot to a number of delivery points, Operations Research, 12, pp. 568-581, (1964); Cordeau JF, Gendreau M, Hertz A, Laporte G, Sormany JS, New heuristics for the vehicle routing problem, Les Cahiers du Gerad, 33, (2004); Comert SE, Yazgan HR, Gorgulu N, A two-stage solution method for vehicle routing problem with simultaneous pick-up and delivery, International Journal of Advances in Engineering and Pure Sciences, 2, pp. 107-125, (2019); Crainic TG, Nguyen PK, Toulouse M, Synchronized multi-Trip multi-Traffic pickup & delivery in city logistics, Journal of the Faculty of Engineering and Architecture of Gazi University, 27, 3, pp. 569-576, (2012); Dagher N, Online Grocery Shopping, (1998); Dantzig GB, Ramser JB, The truck dispatching problem, Management Science, 6, pp. 80-91, (1959); Dethloff J, Vehicle routing and reverse logistics: The vehicle routing problem with simultaneous delivery and pick-up, OR Spectrum, 23, pp. 79-96, (2001); Dondo R, Cerda J, A cluster-based optimization approach for the multi depot heterogeneous fleet vehicle routing problem with time windows, European Journal of Operation Research, 176, 3, pp. 1478-1507, (2007); Elbasan S, Karbon ayak izini dikkate alan e?s zamanli topla-dagit ara?c rotalama, (2015); Fisher ML, Optimal solution of vehicle routing problems using minimum K-Trees, Operations Research, 42, 4, pp. 626-642, (1994); Fleszar K, Osman IH, Hindi KS, A variable neighbourhood search algorithm for the open vehicle routing problem, European Journal of Operational Research, 195, pp. 803-809, (2009); Gajpal Y, Abad P, An ant colony system (ACS) for vehicle routing problem with simultaneous delivery and pickup, Computers & Operations Research, 36, (2009); Gambardella LM, Vehicle routing problems (VRPs), (2000); Gencer C, Aydogan KE, Kocaba S, Insans?z hava ara?clarinin rota planlamasi i?cin bir karar destek sistemi, Kara Harp Okulu Savunma Bilimleri Dergisi, 8, 2, pp. 59-73, (2009); Gillett BE, Miller LR, A heuristic algorithm for the vehicle-dispatch problem, Operations Research, 22, 2, pp. 340-349, (1974); Guglielmo C, Can webvan deliver the goods?, (2000); Hosny MI, Mumford CL, The single vehicle pickup and delivery problem with time windows: Intelligent operators for heuristic and metaheuristic algorithms, Journal of Heuristics, 16, pp. 417-439, (2010); Jones R, A company tackles e-deliveries, (2000); Kiremit?ci B, Kiremit S, Keskinturk T, Zaman pencereli ?cok ara?cli dagitim toplamali rotalama problemi i?cin ger?cek degerli genetik algoritma yakla?simi, Istanbul University, School of Business Journal, 43, 2, pp. 391-403, (2014); Ko?c C, Karaoglan I, C? ok kullanimli ve zaman pencereli ara?c rotalama problemi i?cin bir matematiksel model, Journal of the Faculty of Engineering and Arcchitecture of Gazi University, 27, 3, pp. 569-576, (2012); Kumar SN, Panneerselvam R, A time-dependent vehicle routing problem with time windows for e-commerce supplier site pickups using genetic algorithm, Intelligent Information Management, 7, pp. 181-194, (2015); Kucuk M, A constraint programming approach for the pickup and delivery problem with time windows, Pamukkale University Journal of Engineering Sciences, 25, 9, pp. 1041-1049, (2019); Laseter T, Houston P, Chung A, Byrne S, Turner M, Devendran A, The last mile to nowhere, Strategy Business, 2000, 20, pp. 40-49, (2000); Li F, Golden B, Wasil E, The open vehicle routing problem: Algorithms, largescale test problems, and computational results, Computers & Operations Research, 34, pp. 2918-2930, (2007); McKinnon A, Forster M, European logistical and supply chain trends 1999 2005: The results of a Delphi survey, Logistics Research Network 2000 Conf. Proc, (2000); Moons S, Ramaekers K, Caris A, Arda Y, Integration of order picking and vehicle routing in a B2C e-commerce context, Flexible Services and Manufacturing Journal, 30, pp. 813-843, (2018); Min H, The multiple vehicle routing problem with simultaneous delivery and pickup points, Transportation Research Part A: General, 23, 5, pp. 377-386, (1989); Nagy G, Salhi S, Heuristic algorithms for single and multiple depot vehicle routing problems with pickups and deliveries, European Journal of Operational Research, 162, 1, pp. 126-141, (2005); Punakivi M, Hannu Yrjoelae H, Holmstroem J, Solving the last mile issue: Reception box or delivery box?, International Journal of Physical Distribution & Logistics Management, 6, 31, pp. 427-439, (2001); Reda S, Internet food retailers face tough picking, delivery issues, Stores, 50, (1998); Renaud J, Boctor F, Laporte G, An improved petal heuristic for the vehicle routing problem, Journal of Operational Research Society, 47, pp. 329-336, (1996); Rosenkrantz D, Stearns R, Philip M, An analysis of several heuristics for the traveling salesman problem, SIAM Journal on Computing, 6, 3, pp. 563-581, (1977); Schrage L, Formulation and structure of more complex/realistic routing and scheduling problems, Networks, 11, pp. 229-232, (1981); Simchi-Levi D, Bramel J, Logic of Logistics: Theory, Algorithms & Applications for Logistics Management, (1997); Solomon M, Algorithms for the vehicle routing and scheduling problems with time window constraints, Operations Research, 35, 2, pp. 254-265, (1987); Ta?sk?n A, Ara?c planlama problemi ve problem i?cin web tabanli cografi bilgi sistemi tasarimi, (2012); Terry E, Jensen T, Fernanda B, Burton S, The last mile: An examination of effects of online retail delivery strategies on consumers, Journal of Business Logistics, 24, 2, pp. 177-203, (2003); Thangiah SR, Salhi S, Genetic clustering: An adaptive heuristic for the multidepot vehicle routing problem, Applied Artificial Intelligence, 15, pp. 361-383, (2001); Toth P, Vigo D, The Vehicle Routing Problem, (2002); Tufek?ciler H, A solution approach for bicriteria open vehicle routing problem, (2008); Yazgan HR, Buyuky?lmaz RG, A solution approach for vehicle routing problem with simultaneous pickup and delivery, Sakarya University Journal of Science, 22, 2, pp. 436-449, (2018); Yucenur G, Demirel N, A cluster-based optimization approach for the multi depot heterogeneous fleet vehicle routing problem with time windows, European Journal of Operation Research, 176, 3, pp. 1478-1507, (2011)","M. Karaoǧlu; Department of Transportation Services, Mersin University, Mersin, Turkey; email: mehmetkaraoglu@mersin.edu.tr",null,"World Scientific",{"$nulls":5},2175959.0,null,"APJRE",null,"English","Asia Pac J Oper Res","Article","Final",null,"Scopus","2-s2.0-85114105918"]
["Jiang M.; Huang G.Q.","Jiang, Min (57219938315); Huang, George Q. (7403425048)","57219938315; 7403425048","Intralogistics synchronization in robotic forward-reserve warehouses for e-commerce last-mile delivery",2022.0,"Transportation Research Part E: Logistics and Transportation Review",158.0,null,102619.0,null,null,null,7.0,"10.1016/j.tre.2022.102619","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85123761686&doi=10.1016%2fj.tre.2022.102619&partnerID=40&md5=24f4b4259f837f811fc8cb8cca95228c","HKU Laboratory for Physical Internet, Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Pokfulam, Hong Kong","Jiang M., HKU Laboratory for Physical Internet, Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Pokfulam, Hong Kong; Huang G.Q., HKU Laboratory for Physical Internet, Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Pokfulam, Hong Kong","This paper treats intralogistics processing in a typical robotic forward-reserve e-commerce warehouse involving a reserve area with manual order-picking operations and a forward area with robotic parts-to-picker order sorting operations. It is critical to synchronize intralogistics operations between the two areas considering delivery requirements to optimize the performance in terms of makespan and costs. This challenge is formulated as a delivery-driven intralogistics synchronization (DDIS) problem. This paper develops a tailored variable neighborhood search solution method. A series of comprehensive numerical experiments under various scenarios show the superiority and stability of the DDIS as benchmarked with sequential approaches. A substantial reduction can be achieved in both makespan and forward area size, indicating significantly improved intralogistics operational efficiency and space utilization. Managerial insights are also discussed for specific action plans regarding the market size, the labor force, and the trolley configuration. © 2022","Forward-reserve warehouses; Intralogistics operations; Robotic warehouse systems; Synchronization","Electronic commerce; Optimization; Synchronization; Warehouses; E- commerces; Forward-reserve; Forward-reserve warehouse; Intralogistic operation; Last mile; Makespan; Order-picking; Picking operations; Robotic warehouse system; Warehouse systems; electronic commerce; logistics; optimization; performance assessment; robotics; Robotics",{"$nulls":6},"Albareda-sambola M., Alonso-ayuso A., Molina E., De blas C.S., Variable neighborhood search for order batching in a warehouse, Asia-Pacif. J. Operat. Res., 26, 5, pp. 655-683, (2009); Ardjmand E., Shakeri H., Singh M., Sanei Bajgiran O., Minimizing order picking makespan with multiple pickers in a wave picking warehouse, Int. J. Prod. Econ., 206, pp. 169-183, (2018); Azadeh K., De Koster R., Roy D., Robotized and automated warehouse systems: Review and recent developments, Transp. Sci., 53, 4, pp. 917-945, (2019); Bartholdi J.J., Hackman S.T., Allocating space in a forward pick area of a distribution center for small parts, IIE Trans., 40, 11, pp. 1046-1053, (2008); Bartholdi J.J., Hackman S.T., Warehouse & distribution science: Release 0.98, (2017); Boysen N., Briskorn D., Emde S., Parts-to-picker based order processing in a rack-moving mobile robots environment, Eur. J. Oper. Res., 262, 2, pp. 550-562, (2017); Boysen N., de Koster R., Weidinger F., Warehousing in the e-commerce era: A survey, Eur. J. Oper. Res., 277, 2, pp. 396-411, (2019); Boysen N., Fedtke S., Weidinger F., Optimizing automated sorting in warehouses: The minimum order spread sequencing problem, Eur. J. Oper. 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Rev., 123, pp. 180-199, (2019); Zhang J., Wang X., Huang K., On-line scheduling of order picking and delivery with multiple zones and limited vehicle capacity, Omega, 79, pp. 104-115, (2018); Zhuang Y., Zhou Y., Yuan Y., Hu X., Hassini E., Order Picking Optimization with Rack-Moving Mobile Robots and Multiple Workstations, Eur. J. Oper. Res., (2021); Zou B., Xu X., Gong Y., De Koster R., Evaluating battery charging and swapping strategies in a robotic mobile fulfillment system, Eur. J. Oper. Res., 267, 2, pp. 733-753, (2018)","G.Q. Huang; HKU Laboratory for Physical Internet, Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Pokfulam, Hong Kong; email: gqhuang@hku.hk",null,"Elsevier Ltd",{"$nulls":5},1.3665545E7,null,null,null,"English","Transp. Res. Part E Logist. Transp. Rev.","Article","Final",null,"Scopus","2-s2.0-85123761686"]
["Sitorus C.; So I.G.; Furinto A.; Kosasih W.","Sitorus, Charles (57804611400); So, Idris Gautama (56007500000); Furinto, Asnan (35264335800); Kosasih, Wibowo (57205020119)","57804611400; 56007500000; 35264335800; 57205020119","DIGITIZING IN BUSINESS MODEL INNOVATION: PRELIMINARY RESEARCH OF COURIER, EXPRESS, AND PARCEL SECTORS",2022.0,"Journal of Theoretical and Applied Information Technology",100.0,12.0,null,3923.0,3934.0,11.0,0.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85134257837&partnerID=40&md5=f31c935f0184634c6fd7b2d06d70ea28","BINUS Business School, Bina Nusantara University, Indonesia; BINUS Business School Undergraduate Program, Bina Nusantara University, Indonesia","Sitorus C., BINUS Business School, Bina Nusantara University, Indonesia; So I.G., BINUS Business School Undergraduate Program, Bina Nusantara University, Indonesia; Furinto A.; Kosasih W.","This study aims to identify digital business model innovations carried out by Indonesian courier service companies to meet customer needs. This research also uses three case studies and several references or previous research as the main data sources. This study uses a qualitative approach with the Historical method, with the sampling method used is a purposive sample with three case studies at DiDi Taxi, Cisco, Dell companies. This study found that e-commerce needs to make some innovations in adjusting to the needs of today's customers, especially in the era of digitalization. Some of the innovations that can be done consist of product terms, service features, customer satisfaction, involvement in the e-commerce marketplace, and in terms of delivery patterns. Based on this, this study designs several recommendations based on crucial issues that need to be studied further from the issue of digital business innovation models in Indonesian courier service companies. The results of this study are expected to be able to recommend several crucial issues that need to be studied further from the issue of digital business innovation models in Indonesian courier service companies. Therefore, this review is expected to initiate further research related to the scope of the research. © 2022 Little Lion Scientific. All rights reserved.","Business Model Innovation; Case-Study; Courier; Digitalization; Express; Parcel Sectors",{"$nulls":7},"Adams Jerome M., The Value of Worker Well-Being, Public Health Reports, 134, 6, (2019); Amit Raphael, Zott Christoph, Value Creation in E-Business, Strategic Management Journal, 22, 6-7, pp. 493-520, (2001); Amit Raphael, Zott Christoph, Creating Value through Business Model Innovation, MIT Sloan Management Review, 53, 3, pp. 41-49, (2012); Baden-Fuller Charles, Haefliger Stefan, Business Models and Technological Innovation, Long Range Planning, 46, 6, pp. 419-426, (2013); Bharadwaj Anandhi, El Sawy Omar A., Pavlou Paul A., Venkatraman N., Digital Business Strategy: Toward a next Generation of Insights, MIS Quarterly: Management Information Systems, 37, 2, (2013); Bjork Jennie, Boccardelli Paolo, Magnusson Mats, Ideation Capabilities for Continuous Innovation, Creativity and Innovation Management, 19, 4, (2010); Boh Wai Fong, Huang Cheng Jen, Wu Anne, Investor Experience and Innovation Performance: The Mediating Role of External Cooperation, Strategic Management Journal, 41, 1, (2020); 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Wirtz Bernd W., Digital Business Models: Concepts, Models, and the Alphabet Case Study, 25, (2019); Xu Xin, Thong James Y. L., Tam Kar Yan, Winning Back Technology Disadopters: Testing a Technology Readoption Model in the Context of Mobile Internet Services, Journal of Management Information Systems, 34, 1, (2017); Yoo Youngjin, Computing in Everyday Life: A Call for Research on Experiential Computing, MIS Quarterly: Management Information Systems, 34, (2010); Zhao Jie, Wei Zelong, Yang Dong, Organizational Search, Dynamic Capability, and Business Model Innovation, IEEE Transactions on Engineering Management, (2019)",null,null,"Little Lion Scientific",{"$nulls":5},1.9928645E7,null,null,null,"English","J. Theor. Appl. Inf. Technol.","Article","Final",null,"Scopus","2-s2.0-85134257837"]
["Seghezzi A.; Siragusa C.; Mangiaracina R.","Seghezzi, Arianna (57204964677); Siragusa, Chiara (57204969259); Mangiaracina, Riccardo (35325033800)","57204964677; 57204969259; 35325033800","Parcel lockers vs. home delivery: a model to compare last-mile delivery cost in urban and rural areas",2022.0,"International Journal of Physical Distribution and Logistics Management",52.0,3.0,null,213.0,237.0,24.0,20.0,"10.1108/IJPDLM-03-2020-0072","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124225684&doi=10.1108%2fIJPDLM-03-2020-0072&partnerID=40&md5=9d1bba737c713b57334f783aac16274f","Department of Management, Economics and Industrial Engineering, Politecnico di Milano, Milan, Italy","Seghezzi A., Department of Management, Economics and Industrial Engineering, Politecnico di Milano, Milan, Italy; Siragusa C., Department of Management, Economics and Industrial Engineering, Politecnico di Milano, Milan, Italy; Mangiaracina R., Department of Management, Economics and Industrial Engineering, Politecnico di Milano, Milan, Italy","Purpose: This paper investigates the economic performances of two business-to-consumer (B2C) e-commerce last-mile delivery options –parcel lockers (PLs) and traditional home delivery (HD) in contexts where e-commerce is still at its early stages. It analyses and compares two different implementation contexts, urban and rural areas. Design/methodology/approach: This study develops an analytical model that estimates delivery costs for both the PL and HD options. The model is applied to two base cases (representative of urban and rural areas in Italy), and sensitivity analyses are subsequently performed on a set of key variables/parameters (i.e. PL density, PL fill rate and PL annual costs). To support the model development and application, interviews with practitioners (Edwards et al., 2011) were performed. Findings: PLs imply lower delivery cost than HD, independently from the implementation area (urban or rural): advantages mainly derive from the higher delivery density and the drastic reduction of failed deliveries. Benefits entailed by PLs are more significant in rural areas due to lower PL investments and annual costs, as well as higher HD costs. Originality/value: This paper offers insights to both academics and practitioners. On the academic side, it develops a model to compare the delivery cost of PL and HD, which includes the analysis of urban and rural contexts. This could serve as a platform for developing/informing future analytical/optimisation contributions. On the managerial side, it may support practitioners in making decisions about the implementation of PLs and HD, to benchmark their costs and to identify the main variables and parameters at play. © 2021, Emerald Publishing Limited.","B2C e-Commerce; Innovation; Last-mile delivery; Parcel lockers",{"$nulls":7},"Akhavan M., Ghiara H., Mariotti I., Sillig C., Logistics global network connectivity and its determinants. A European City network analysis, Journal of Transport Geography, 82, (2020); Allen J., Piecyk M., Piotrowska M., McLeod F., Cherrett T., Ghali K., Nguyen T., Bektas T., Bates O., Friday A., Wise S., Austwick M., Understanding the impact of e-commerce on last-mile light goods vehicle activity in urban areas: the case of London, Transportation Research Part D: Transport and Environment, 61, pp. 325-338, (2018); Bertrand J.W.M., Fransoo J.C., Operations management research methodologies using quantitative modeling, International Journal of Operations & Production Management, 22, 2, pp. 241-264, (2002); Borocz P., Singh S.P., Measurement and analysis of delivery van vibration levels to simulate package testing for parcel delivery in Hungary, Packaging Technology and Science, 31, 5, pp. 342-352, (2018); Boyer K.K., Prud'homme A.M., Chung W., The last mile challenge: evaluating the effects of customer density and delivery window patterns, Journal of Business Logistics, 30, pp. 185-201, (2009); Cuzzocrea A., Nolich M., Ukovich W., A big-data-analytics framework for supporting logistics problems in smart-city environments, Procedia Computer Science, 159, pp. 2589-2597, (2019); Deutsch Y., Golany B., A parcel locker network as a solution to the logistics last mile problem, International Journal of Production Research, 56, 1-2, pp. 251-261, (2018); Edwards J.B., McKinnon A.C., Cullinane S.L., Comparative analysis of the carbon footprints of conventional and online retailing, International Journal of Physical Distribution and Logistics Management, 40, pp. 103-123, (2010); Edwards J., McKinnon A., Cullinane S., Comparative carbon auditing of conventional and online retail supply chains: a review of methodological issues, Supply Chain Management: An International Journal, 6, 1, pp. 57-63, (2011); Enthoven D.L.J.U., Jargalsaikhan B., Roodbergen K.J., uit het Broek M.A.J., Schrotenboer A.H., The two-echelon vehicle routing problem with covering options: city logistics with cargo bikes and parcel lockers, Computers and Operations Research, 118, (2020); Faugere L., Montreuil B., Smart locker bank design optimization for urban omnichannel logistics: assessing monolithic vs. modular configurations, Computers and Industrial Engineering, 139, (2020); Figliozzi M.A., The impacts of congestion on commercial vehicle tour characteristics and costs, Transportation Research Part E: Logistics and Transportation Review, 46, 4, pp. 496-506, (2010); Figliozzi M.A., Kingdon L., Wilkitzki A., Freight distribution tours in congested urban areas: characteristics and implications for carriers' operations and data collection efforts, Transportation Research Board 86th Annual Meeting, (2007); Gevaers R., Van de Voorde E., Vanelslander T., Cost modelling and simulation of last-mile characteristics in an innovative B2C supply chain environment with implications on urban areas and cities, Procedia Social and Behavioral Sciences, 125, pp. 398-411, (2014); Giordano A., Fischbeck P., Matthews H.S., Environmental and economic comparison of diesel and battery electric delivery vans to inform city logistics fleet replacement strategies, Transportation Research Part D: Transport and Environment, 64, pp. 216-229, (2018); Giuffrida M., Mangiaracina R., Miragliotta G., Perotti S., Tumino A., Modelling the environmental impact of omni-channel purchasing in the apparel industry: the role of logistics, International Journal of Logistics Systems and Management, 34, 4, pp. 431-456, (2019); Goel A., Rousseau L.M., Truck driver scheduling in Canada, Journal of Scheduling, 15, 6, pp. 783-799, (2012); Harland C., Telgen J., Callender G., Grimm R., Patrucco A., Implementing government policy in supply chains: an international coproduction study of public procurement, Journal of Supply Chain Management, 55, 2, pp. 6-25, (2019); Iwan S., Korczak J., Lemke J., Usability of the parcel lockers from the customer perspective - the research in Polish Cities, Transportation Research Procedia, 12, pp. 272-287, (2016); Iwan S., Kijewska K., Lemke J., Analysis of parcel lockers' efficiency as the last mile delivery solution—the results of the research in Poland, Transporationt Research Procedia, 12, pp. 644-655, (2016); Jick T.D., Mixing qualitative and quantitative methods: triangulation in action, Administrative Science Quarterly, 24, 4, pp. 602-611, (1979); Lachapelle U., Burke M., Brotherton A., Leung A., Parcel locker systems in a car dominant city: location, characterisation and potential impacts on city planning and consumer travel access, Journal of Transport Geography, 71, pp. 1-14, (2018); Lagorio A., Pinto R., Golini R., City logistics issues in small-medium cities: an overview of the Bergamo case from an industrial engineering perspective, Proceedings of the XIX Summer School F. Turco, (2014); Lin Y.H., Wang Y., He D., Lee L.H., Last-mile delivery: optimal locker location under multinomial logit choice model, Transportation Research Part E: Logistics and Transportation Review, 142, (2020); Mangiaracina R., Perego A., Perotti S., Tumino A., Assessing the environmental impact of logistics in online and offline B2C purchasing processes in the apparel industry, International Journal of Logistics Systems and Management, 23, 1, pp. 98-124, (2016); Mangiaracina R., Perego A., Seghezzi A., Tumino A., Innovative solutions to increase last-mile delivery efficiency in B2C e-commerce: a literature review, International Journal of Physical Distribution and Logistics Management, 49, 9, pp. 901-920, (2019); McKinnon A.C., Tallam D., Unattended delivery to the home: an assessment of the security implications, International Journal of Retail and Distribution Management, 31, 1, pp. 30-41, (2003); Mohrman S.A., Lawler E.E., Generating knowledge that drives change, Academy of Management Perspectives, 26, 1, pp. 41-51, (2012); Nutting P.A., Rost K., Dickinson M., Werner J.J., Dickinson P., Smith J.L., Gallovic B., Barriers to initiating depression treatment in primary care practice, Journal of General Internal Medicine, 17, 2, pp. 103-111, (2002); Palsson H., Pettersson F., Hiselius L.W., Energy consumption in e-commerce versus conventional trade channels-Insights into packaging, the last mile, unsold products and product returns, Journal of Cleaner Production, 164, pp. 765-778, (2017); Pan S., Giannikas V., Han Y., Grover-Silva E., Qiao B., Using customer- related data to enhance e-grocery home delivery, Industrial Management and Data Systems, 117, 9, pp. 1917-1933, (2017); Pinto R., Zambetti M., Lagorio A., Pirola F., A network design model for a meal delivery service using drones, International Journal of Logistics Research and Applications, 23, 4, pp. 354-374, (2019); Ranieri L., Digiesi S., Silvestri B., Roccotelli M., A review of last mile logistics innovations in an externalities cost reduction vision, Sustainability, 10, 3, pp. 782-799, (2018); Redi A.A.N.P., Jewpanya P., Kurniawan A.C., Persada S.F., Nadlifatin R., Dewi O.A.C., A simulated annealing algorithm for solving two-echelon vehicle routing problem with locker facilities, Algorithms, 13, 9, pp. 1-14, (2020); Reiner G., Supply chain management research methodology using quantitative models based on empirical data, Springer Books, pp. 431-444, (2005); Schwerdfeger S., Boysen N., Optimizing the changing locations of mobile parcel lockers in last-mile distribution, European Journal of Operational Research, 285, 3, (2020); Seghezzi A., Mangiaracina R., Investigating multi-parcel crowdsourcing logistics for B2C e-commerce last-mile deliveries, International Journal of Logistics Research and Applications, pp. 1-18, (2021); Seghezzi A., Mangiaracina R., Tumino A., Perego A., Pony express’ crowdsourcing logistics for last-mile delivery in B2C e-commerce: an economic analysis, International Journal of Logistics Research and Applications, 24, 5, pp. 456-472, (2020); Siikavirta H., Punakivi M., Karkkainen M., Linnanen L., Effects of e‐commerce on greenhouse gas emissions: a case study of grocery home delivery in Finland, Journal of Industrial Ecology, 6, 2, pp. 83-97, (2002); Siragusa C., Tumino A., Mangiaracina R., Perego A., Electric vehicles performing last-mile delivery in B2C e-commerce: an economic and environmental assessment, International Journal of Sustainable Transportation, pp. 1-16, (2020); Sitek P., Wikarek J., Capacitated vehicle routing problem with pick-up and alternative delivery (CVRPPAD): model and implementation using hybrid approach, Annals of Operations Research, 273, 1-2, pp. 257-277, (2019); Sitek P., Wikarek J., Rutczynska-Wdowiak K., Capacitated vehicle routing problem with pick-up, alternative delivery and time windows (CVRPPADTW): a hybrid approach, Advances in Intelligent Systems and Computing, 1004, pp. 33-40, (2020); Song L., Cherrett T., McLeod F., Guan W., Addressing the last mile problem: transport impacts of collection and delivery points, Transportation Research Record, 2097, 1, pp. 9-18, (2009); Song L., Mao B., Wu Z., Wang J., Investigation of home delivery models and logistics services in China, Transportation Research Record, 2673, 9, pp. 11-22, (2019); Vakulenko Y., Hellstrom D., Hjort K., What's in the parcel locker? Exploring customer value in e-commerce last mile delivery, Journal of Business Research, 88, pp. 421-427, (2018); Van Duin J.H.R., Wiegmans B.W., van Arem B., van Amstel Y., From home delivery to parcel lockers: a case study in Amsterdam, Transportation Research Procedia, 46, pp. 37-44, (2020); Vanelslander T., Deketele L., Van Hove D., Commonly used e-commerce supply chains for fast moving consumer goods: comparison and suggestions for improvement, International Journal of Logistics Research and Applications, 16, pp. 243-256, (2013); Veenstra M., Roodbergen K.J., Coelho L.C., Zhu S.X., A simultaneous facility location and vehicle routing problem arising in health care logistics in The Netherlands, European Journal of Operational Research, 268, 2, pp. 703-715, (2018); Wang X., Zhan L., Ruan J., Zhang J., How to choose ‘last mile’ delivery modes for E-fulfillment, Mathematical Problems in Engineering, 1, pp. 1-11, (2014); Wang X., Yuen K.F., Wong Y.D., Teo C.C., An innovation diffusion perspective of e-consumers’ initial adoption of self-collection service via automated parcel station, The International Journal of Logistics Management, 29, 1, pp. 237-260, (2018); Wang Y., Bi M., Lai J., Chen Y., Locating movable parcel lockers under stochastic demands, Symmetry, 12, 12, pp. 1-21, (2020); Wang Y., Bi M., Chen Y., A scheduling strategy of mobile parcel lockers for the last mile delivery problem, Promet – Traffic – Traffico, 32, 6, pp. 875-885, (2020); Woods J.C., Randall M.R., The net present value of future investment opportunities: its impact on shareholder wealth and implications for capital budgeting theory, Financial Management, 18, 2, pp. 85-92, (1989); Yang G., Huang Y., Fu Y., Huang B., Sheng S., Mao L., Huang S., Xu Y., Le J., Ouyang Y., Yin Q., Parcel locker location based on a bilevel programming model, Mathematical Problems in Engineering, 2020, pp. 1-12, (2020); Zenezini G., Lagorio A., Pinto R., De Marco A., Golini R., The collection-and-delivery points implementation process from the courier, express and parcel operator's perspective, IFAC-PapersOnLine, 51, 11, pp. 594-599, (2018)","A. Seghezzi; Department of Management, Economics and Industrial Engineering, Politecnico di Milano, Milan, Italy; email: arianna.seghezzi@polimi.it",null,"Emerald Group Holdings Ltd.",{"$nulls":5},9600035.0,null,null,null,"English","Int. J. Phys. Distrib. Logist. Manage.","Article","Final",null,"Scopus","2-s2.0-85124225684"]
["Bogue R.","Bogue, Robert (22936667400)",2.29366674E10,"Warehouse robot market boosted by Covid pandemic and technological innovations",2022.0,"Industrial Robot",49.0,2.0,null,181.0,186.0,5.0,1.0,"10.1108/IR-11-2021-0270","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121439309&doi=10.1108%2fIR-11-2021-0270&partnerID=40&md5=64e4c0298c0e3db5215e96a0890189e2","Okehampton, United Kingdom","Bogue R., Okehampton, United Kingdom","Purpose: This paper aims to provide details of recent commercial and technological developments that are driving robotic warehouse automation. Design/methodology/approach: Following a short introduction, this first provides a commercial background and identifies the factors driving the market growth. It then gives examples of robotics companies, products and applications that exploit innovations in artificial intelligence (AI). It then considers future prospects, and finally, brief conclusions are drawn. Findings: Amazon’s acquisition of Kiva led to a community of new robot manufacturers and the realisation by major e-commerce companies that robotic automation would be required to maintain competitiveness. The Covid pandemic caused a surge in e-commerce and a critical shortage of labour, which further highlighted the need for automation and boosted robotic deployments. Recent advances in AI have resulted in a rapidly growing community of companies producing AI-powered robots which offer advanced capabilities such as mixed product picking, sorting and kitting. These are being deployed by a growing number of e-commerce and logistics companies and are paving the way towards ever-higher levels of warehouse automation. Full automation will soon become a reality. Originality/value: This paper identifies the factors driving the rapidly developing warehouse robot business by considering the companies, products, technology and applications. © 2021, Emerald Publishing Limited.","Artificial intelligence; E-commerce; Robot; Warehouse","Intelligent robots; Robotics; Warehouses; Commercial development; Company products; Design/methodology/approach; E- commerces; Future prospects; Market growth; Robot; Technological development; Technological innovation; Warehouse automation; Electronic commerce",{"$nulls":7},"R. Bogue; Okehampton, United Kingdom; email: robbogue@aol.com",null,"Emerald Group Holdings Ltd.",{"$nulls":5},"0143991X",null,"IDRBA",null,"English","Ind. Robot","Article","Final",null,"Scopus","2-s2.0-85121439309"]
["Liu L.","Liu, Liangchao (57826748800)",5.78267488E10,"Optimization of agriculture logistics supply chain financing mode based on big data analysis technology",2022.0,"Journal of Commercial Biotechnology",27.0,1.0,null,129.0,140.0,11.0,0.0,"10.5912/jcb1081","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85138471663&doi=10.5912%2fjcb1081&partnerID=40&md5=c877d3382e03b4b6a5d824df911021c9","College of Economics and Management, Jiaozuo University, Jiaozuo, 454000, China","Liu L., College of Economics and Management, Jiaozuo University, Jiaozuo, 454000, China","With the rapid development of information technology, supply chain financing mode based on e-commerce platform arises at the historic moment. Starting from the background and significance of supply chain financing of e-commerce platform, this paper compares four supply chain financing modes under e-commerce platform with traditional financing modes, constructs the performance evaluation index system of e-commerce platform by using a balanced scorecard, and makes a brief evaluation by using double fuzzy model, In order to realize the optimization design of logistics supply chain financing mode based on big data analysis technology, the practicability of the design method is verified through practical analysis. © 2022 ThinkBiotech LLC. All rights reserved.","Agriculture Logistics supply chain; big data analysis; Financing mode","Big data; Data handling; Electronic commerce; Finance; Information analysis; Supply chains; Agriculture logistic supply chain; Big data analyse; Commerce platforms; E- commerces; Financing mode; Logistics supply chains; Mode-based; Optimisations; Supply chain financings; Technology supply chains; agriculture; article; balanced scorecard; big data; electronic commerce; financial management; fuzzy logic; Agriculture",{"$nulls":6},"Awad F.H., Hamad M.M., Improved k-Means Clustering Algorithm for Big Data Based on Distributed SmartphoneNeural Engine Processor, Electronics, 11, 6, (2022); Chernonog T., Avinadav T., Pricing and advertising in a supply chain of perishable products under asymmetric information, International Journal of Production Economics, 209, pp. 249-264, (2019); Dey B.K., Bhuniya S., Sarkar B., Involvement of controllable lead time and variable demand for a smart manufacturing system under a supply chain management, Expert Systems with Applications, 184, (2021); Jingming L., Et al., Research on credit risk measurement of small and micro enterprises based on the integrated algorithm of improved GSO and ELM, Mathematical Problems in Engineering, 2020, (2020); Khatib E.J., Barco R., Optimization of 5G networks for smart logistics, Energies, 14, 6, (2021); Kogler C., Stenitzer A., Rauch P., Simulating combined self-loading truck and semitrailer truck transport in the wood supply chain, Forests, 11, 12, (2020); Leofante F., Et al., Integrated synthesis and execution of optimal plans for multi-robot systems in logistics, Information systems frontiers, 21, 1, pp. 87-107, (2019); Mahmoudi M., Parviziomran I., Reusable packaging in supply chains: A review of environmental and economic impacts, logistics system designs, and operations management, International Journal of Production Economics, 228, (2020); Niu Q., Yang F., The impact of advance selling strategies on a three-echelon supply chain in the presence of social influence, Mathematical Problems in Engineering, 2020, (2020); Osaba E., Et al., Data-driven optimization for transportation logistics and smart mobility applications [guest editorial], IEEE Intelligent Transportation Systems Magazine, 12, 4, pp. 6-9, (2020); Palys M.J., Allman A., Daoutidis P., Exploring the benefits of modular renewable-powered ammonia production: A supply chain optimization study, Industrial & Engineering Chemistry Research, 58, 15, pp. 5898-5908, (2018); Pan S., Et al., Digital interoperability in logistics and supply chain management: state-of-the-art and research avenues towards Physical Internet, Computers in industry, 128, (2021); Prabhu R.M., Et al., Logistics optimization in supply chain management using clustering algorithms, Scalable Computing: Practice and Experience, 21, 1, pp. 107-114, (2020); Rabbani M., Abazari A., Farrokhi-Asl H., An economic analysis for integrated bi-objective biofuel supply chain design using support vector machine, Journal of Industrial Engineering and Management Studies, 7, 2, pp. 77-97, (2020); Rau H., Budiman S.D., Monteiro C.N., Improving the sustainability of a reverse supply chain system under demand uncertainty by using postponement strategies, Waste Management, 131, pp. 72-87, (2021); Roth S., Nikolla A., Vorgehen zur erstellung einer digitalisierungsroadmap für das supply-chain-management, Zeitschrift für wirtschaftlichen Fabrikbetrieb, 115, 9, pp. 634-640, (2020); Sahin B., Soylu A., Multi-layer, multisegment iterative optimization for maritime supply chain operations in a dynamic fuzzy environment, Ieee Access, 8, pp. 144993-145005, (2020); Sannino G., Et al., Artificial intelligence for mobile health data analysis and processing, (2019); Shahid M.L.U.R., Et al., Interactive visual analytics tool for multidimensional quantitative and categorical data analysis, Information Visualization, 19, 3, pp. 234-246, (2020); Zhang Y., Chen W., Optimal production and financing portfolio strategies for a capital-constrained closed-loop supply chain with OEM remanufacturing, Journal of Cleaner Production, 279, (2021)",null,null,"ThinkBiotech LLC",{"$nulls":5},1.4628732E7,null,"JCBOA",null,"English","J. Commer. Biotechnol.","Article","Final",null,"Scopus","2-s2.0-85138471663"]
["Foster I.S.; Liu S.Y.; Hoffs C.T.; LeBoa C.; Chen A.S.; Rummo P.E.","Foster, Isabelle S. (57702214600); Liu, Samantha Y. (57702484800); Hoffs, Charlie T. (57219091955); LeBoa, Christopher (57193515850); Chen, Andrew S. (57703017500); Rummo, Pasquale E. (56201599400)","57702214600; 57702484800; 57219091955; 57193515850; 57703017500; 56201599400","Disparities in SNAP online grocery delivery and implementation: Lessons learned from California during the 2020-21 COVID pandemic",2022.0,"Health and Place",76.0,null,102811.0,null,null,null,9.0,"10.1016/j.healthplace.2022.102811","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85130432280&doi=10.1016%2fj.healthplace.2022.102811&partnerID=40&md5=30cd5d752aa15f13a833c356f48ae9a7","Freeman Spogli Institute for International Studies: FSI, Stanford University, 450 Serra Mall, Stanford, 94305, CA, United States; Department of Civil and Environmental Engineering, Stanford University, 450 Serra Mall, Stanford, 94305, CA, United States; Department of Chemical Engineering, Stanford University, 450 Serra Mall, Stanford, 94305, CA, United States; Department of Infectious Disease and Geographic Medicine, Stanford University, 450 Serra Mall, Stanford, 94305, CA, United States; Department of Computer Science, Stanford University, Stanford University, 450 Serra Mall, Stanford, 94305, CA, United States; Department of Population Health, NYU Grossman School of Medicine, 550 1st Ave, New York, 10016, NY, United States","Foster I.S., Freeman Spogli Institute for International Studies: FSI, Stanford University, 450 Serra Mall, Stanford, 94305, CA, United States; Liu S.Y., Department of Civil and Environmental Engineering, Stanford University, 450 Serra Mall, Stanford, 94305, CA, United States; Hoffs C.T., Department of Chemical Engineering, Stanford University, 450 Serra Mall, Stanford, 94305, CA, United States; LeBoa C., Department of Infectious Disease and Geographic Medicine, Stanford University, 450 Serra Mall, Stanford, 94305, CA, United States; Chen A.S., Department of Computer Science, Stanford University, Stanford University, 450 Serra Mall, Stanford, 94305, CA, United States; Rummo P.E., Department of Population Health, NYU Grossman School of Medicine, 550 1st Ave, New York, 10016, NY, United States","During the COVID-19 pandemic in 2020, the Supplemental Nutrition Assistance Program (SNAP) Online Purchasing Pilot (OPP) was rapidly expanded across the US. This program, enabling direct-to-home grocery delivery, could be a transformative step towards improving fresh-food access. However, lack of information on which areas are serviced by SNAP OPP hinders the identification of potential demographic and regional disparities in access. Lessons from the initial implementation period are critical for understanding continuing inequities and informing the implementation of future programs. In California, SNAP OPP expanded food access for 85.9% of the state's SNAP households in 2020–21. Coverage was significantly greater in urban areas, covering 87.2% of CalFresh households in urban limited food access areas as compared with 29.9% of CalFresh households in rural limited food access areas. County-level COVID-19 rates did not have a meaningful association with SNAP OPP coverage. © 2022 Elsevier Ltd","Government food assistance; Health policy; Implementation lessons; Online grocery delivery; Supplemental nutrition assistance program (SNAP) online purchasing pilot (OPP)","COVID-19; Family Characteristics; Food Assistance; Food Supply; Humans; Pandemics; Poverty; California; United States; accessibility; COVID-19; disease spread; epidemic; food market; health policy; state role; Article; California; coronavirus disease 2019; demography; food access; food assistance; government; health care policy; household; household income; human; incidence; online shopping; pandemic; population density; purchasing; rural area; social inequality; urban area; webshop; whole food; catering service; epidemiology; family size; pandemic; poverty",{"$nulls":4},"Derek Ouyang","We thank the Basketful team, Jim Lesch and Joel LaFrance, for their assistance with data collection. We also wish to express our appreciation for the help provided by Dr. Michael Kevane, Dr. Andrew S. Starbird, Dr. William Behrman, Nicolas Rodriguez, Kevin Ji, David Foster, and Derek Ouyang. Their input and advice on data analysis techniques and statistical analysis has been invaluable throughout this research effort.","Taillie L.S., Ng S.W., Popkin B.M., Walmart and other food retail chains: trends and disparities in the nutritional profile of packaged food purchases, Am. J. Prev. Med., 50, pp. 171-179, (2016); ALDI, FAQs - grocery delivery & curbside pickup | ALDI US, (2021); Appelhans B.M., Lynch E.B., Martin M.A., Nackers L.M., Cail V., Woodrick N., Feasibility and acceptability of Internet grocery service in an urban food desert, Chicago, 2011-2012, Prev. Chronic Dis., 10, (2013); Basketful, Basketful home, (2021); Brandt E.J., Silvestri D.M., Mande J.R., Holland M.L., Ross J.S., Availability of grocery delivery to food deserts in states participating in the online purchase pilot, JAMA Netw. Open, 2, (2019); Brones A., Karen Washington: it's not a food desert, it's food apartheid, (2018); California Association of Food Banks, CalFresh + online EBT webinar: what CalFresh advocates and outreach workers need to know, (2020); Caswell J.A., Yaktine A.L., Allotments C., S Board F., Council N.R., History, Background, and Goals of the Supplemental Nutrition Assistance Program, Supplemental Nutrition Assistance Program: Examining the Evidence to Define Benefit Adequacy, (2013); (2019); (2021); COVID-19 and your health, Centers for Dis. Contr. Prevent., (2020); Chester J., Kopp K., Montgomery K., Does buying groceries online put SNAP participants at risk? Center for digital democracy, (2020); Cohen N., Tomaino Fraser K., Arnow C., Mulcahy M., Hille C., Online grocery shopping by NYC public housing residents using supplemental nutrition assistance program (SNAP) benefits: a service ecosystems perspective, Sustainability, 12, (2020); Cuadros D.F., Branscum A.J., Mukandavire Z., Miller F.D., MacKinnon N., Dynamics of the COVID-19 epidemic in urban and rural areas in the United States, Ann. Epidemiol., 59, pp. 16-20, (2021); 2019 broadband deployment report [WWW document]. Federal communications commission, (2019); FoodMaxx, (2021); Foster I., Polselli A., Hoffs C., de Nocker C., LeBoa C., Rummo P., Brandt E.J., Rimm E., SNAP online purchasing research brief. unBox, (2021); Granheim S.I., Lovhaug A.L., Terragni L., Torheim L.E., Thurston M., Mapping the digital food environment: a systematic scoping review, Obes. Rev., 23, (2022); Gregory C.A., Deb P., Does SNAP improve your health?, Food Pol., 50, pp. 11-19, (2015); Headrick G., Khandpur N., Perez C., Taillie L.S., Bleich S.N., Rimm E.B., Moran A., Content analysis of online grocery retail policies and practices affecting healthy food access, J. Nutr. Educ. Behav., (2021); Jilcott Pitts S.B., Ng S.W., Blitstein J.L., Gustafson A., Niculescu M., Online grocery shopping: promise and pitfalls for healthier food and beverage purchases, Publ. Health Nutr., 21, pp. 3360-3376, (2018); Jones J.W., COVID-19 working paper: supplemental nutrition assistance program and pandemic electronic benefit transfer redemptions during the coronavirus pandemic, (2021); Keith-Jennings B., Llobrera J., Dean S., Links of the supplemental nutrition assistance program with food insecurity, poverty, and health: evidence and potential, Am. J. Publ. Health, 109, pp. 1636-1640, (2019); Larson N., Story M., A review of environmental influences on food choices, Ann. Behav. Med., 38, pp. s56-s73, (2009); Leighton M., AmazonFresh vs. Amazon Pantry — here's the difference between Amazon's grocery delivery services, (2020); Lucky Supermarkets, Stores | Lucky supermarkets, (2021); Mercatus, eGrocery adoption: the new reality for grocery shopper behavior. Mercatus, (2020); Miller S.R., Knudson W.A., Nutrition and cost comparisons of select canned, frozen, and fresh fruits and vegetables, Am. J. Lifestyle Med., 8, pp. 430-437, (2014); Miller I.F., Becker A.D., Grenfell B.T., Metcalf C.J.E., Disease and healthcare burden of COVID-19 in the United States, Nat. Med., 26, pp. 1212-1217, (2020); Moran A., Headrick G., Khandpur N., Promoting equitable expansion of the SNAP online purchasing pilot, (2021); COVID-19 economic Relief Bill, (2021); New York Times, Covid-19 data | dev portal, (2021); Oyebode O., Gordon-Dseagu V., Walker A., Mindell J.S., Fruit and vegetable consumption and all-cause, cancer and CVD mortality: analysis of Health Survey for England data, J. Epidemiol. Community Health, 68, pp. 856-862, (2014); Rhone A., Ploeg M.V., Williams R., Breneman V., Understanding low-income and low-access census tracts across the nation: subnational and subpopulation estimates of access to healthy food, (2019); Richardson A.S., Ghosh-Dastidar M., Beckman R., Florez K.R., DeSantis A., Collins R.L., Dubowitz T., Can the introduction of a full-service supermarket in a food desert improve residents' economic status and health?, Ann. Epidemiol., 27, pp. 771-776, (2017); Rogus S., Guthrie J.F., Niculescu M., Mancino L., Online grocery shopping knowledge, attitudes, and behaviors among SNAP participants, J. Nutr. Educ. Behav., 52, pp. 539-545, (2020); Save Mart, Stores | Save Mart supermarkets, (2021); Save Mart, The Save Mart companies is the first northern California conventional grocer to offer EBT SNAP payments through Instacart | Save Mart supermarkets, (2021); Sevilla N., Food apartheid: racialized access to healthy affordable food, (2021); Testa A., Jackson D.B., Semenza D.C., Vaughn M.G., Food deserts and cardiovascular health among young adults, Publ. Health Nutr., 24, pp. 117-124, (2021); UCLA Healthy Campus Initiative, The language of our food system: food apartheid and food sovereignty - EatWell, (2021); United States Census Bureau, Census - table results, (2019); SNAP data tables | food and nutrition service, (2022); US Congress, Text - H.R.1319 - 117th congress (2021-2022): American Rescue plan act of 2021 | Congress.gov | library of congress, (2021); USDA E.R.S., Rural-urban Continuum codes, (2020); USDA, SNAP online purchasing to cover 90% of households, (2020); USDA, Stores accepting SNAP online | food and nutrition service, (2021); USDA, SNAP eligibility | food and nutrition service, (2022); UT Austin, ‘Food Apartheid’ (Not ‘Desert’), (2020); Walmart, Store pickup, (2021)","I.S. Foster; Freeman Spogli Institute for International Studies: FSI, Stanford University, Stanford, 450 Serra Mall, 94305, United States; email: ifoster@alumni.stanford.edu",null,"Elsevier Ltd",{"$nulls":5},1.3538292E7,null,"HEPLF",3.5605572E7,"English","Health Place","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85130432280"]
["Lu L.; Hu S.; Ren Y.; Kang K.; Li B.","Lu, Lin (55474691700); Hu, Song (57874368700); Ren, Yuelin (57874179800); Kang, Kai (57874179900); Li, Beibei (57873266900)","55474691700; 57874368700; 57874179800; 57874179900; 57873266900","Research on Extension Design of Emergency Cold Chain Logistics from the Perspective of Carbon Constraints",2022.0,"Sustainability (Switzerland)",14.0,15.0,9083.0,null,null,null,1.0,"10.3390/su14159083","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137190863&doi=10.3390%2fsu14159083&partnerID=40&md5=862a4aa9040b9da0701f472ab6b5abb5","School of Economics and Management, Guangxi Normal University, Guilin, 541000, China","Lu L., School of Economics and Management, Guangxi Normal University, Guilin, 541000, China; Hu S., School of Economics and Management, Guangxi Normal University, Guilin, 541000, China; Ren Y., School of Economics and Management, Guangxi Normal University, Guilin, 541000, China; Kang K., School of Economics and Management, Guangxi Normal University, Guilin, 541000, China; Li B., School of Economics and Management, Guangxi Normal University, Guilin, 541000, China","Extenics has unique advantages in solving contradictions by using formal models to explore the possibility of expanding things and the laws and methods of development and innovation. This paper studies the specific application of the extension strategy generation method in emergency cold chain logistics, in order to solve the problem that the emergency plan is difficult to cover in the face of an emergency. The purpose of this paper is to provide ideas for the generation of strategies to solve the contradictions of cold chain logistics in complex emergency scenarios. Giving full play to the unique advantages of extenics in solving contradictory problems, this paper analyzes the core problems, objectives and conditions of emergency cold chain logistics in four links with the case scenario of the COVID-19 pandemic outbreak, extends and generates 10 measures to form 36 schemes, and evaluates the combination schemes quantitatively and objectively using the dependent function and superiority evaluation formula. In addition, the consideration of carbon constraints is added to the selection of the scheme, and the specific plan of integrating e-commerce platform, expert guidance, establishing temporary cold storage transfer and contactless distribution is designed. The research results provide support for meeting the needs of emergency logistics schemes in different situations and optimizing the energy efficiency of the scheme while ensuring humanitarian support. At the same time, the application of extenics basic-element formal language also provides a reference for further applying artificial intelligence to the design of emergency logistics schemes. © 2022 by the authors.","carbon constraints; cold chain logistics; emergency logistics; extenics; strategy generation","energy efficiency",{"$nulls":4},"Guangxi Philosophy and Social Science Research Project, (21FYJ055)","This study was supported by Guangxi Philosophy and Social Science Research Project: Research on the transformation and upgrading path and countermeasures of Guangxi manufacturing industry under the Internet business ecological environment (21FYJ055). We would like to express our sincere gratitude to the anonymous reviewers, and the editors for their truly valuable comments.",{"$cut":{"chars":17063,"head":"Lehtveer M., Hedenus F., Nuclear power as a climate mitigation strategy– technology and proliferation risk, J. Risk. Res, 18, pp. 273-290, (2015); Zhou L., Wu X., Xu Z., Fujita H., Emergency decision making for natural disasters: An overview, Int. J. Disast. Risk. Re, 27, pp. 567-576, (2018); Zhou D., Fan C., Chen A., Evolution mechanism and driving factors of unconventional emergencies in megacities: An empirical study based on 102 cases in the world, Nat. Hazards, 107, pp. 513-530, (2020); Rong L., Tan H., Emergency chain reaction model based on disaster pregnant environment, Sys. Engine, 30, pp. 40-47, (2012); Jiang P., Wang Y., Liu C., Hu Y., Xie J., Evaluating Critical Factors Influencing the Reliability of Emergency Logistics Systems Using Multiple-Attribute Decision Making, Symmetry, 12, (2020); Cai W., Overview of Extenics, Syst. Eng.-Theory. Pract, 1, pp. 77-85, (1998); Cai W., Yang C.Y., Basic theory and method system of Extenics, Chinese Sci. Bull, 58, pp. 1190-1199, (2013); Yang C.Y., Li X.S., Research progress of extension innovation method and its application, Ind. Eng. J, 15, pp. 131-137, (2012); Thome A.M.T., Scavarda L.F., Scavarda A.J., Conducting systematic literature review in operations management, Prod. Plan. Control, 27, pp. 408-420, (2016); Moher D., Liberati A., Tetzlaff J., Altman D.G., Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement, Phys. Ther, 89, pp. 873-880, (2009); Page M.J., McKenzie J.E., Bossuyt P.M., Boutron I., Hoffmann T.C., Mulrow C.D., Shamseer L., Tetzlaff J.M., Akl E.A., Brennan S.E., Et al., The PRISMA 2020 statement: An updated guideline for reporting systematic reviews, Int. J. Surg, 88, (2021); Anisya T., Mitsuko M., Logistics training: Necessity or luxury?, Educ. Emerg, 22, pp. 60-61, (2005); Manopiniwes W., Nagasawa K., Irohara T., Humanitarian Relief Logistics with Time Restriction: Thai Flooding Case Study, Ind. Eng. Manage. Sys. Int. J, 13, pp. 398-407, (2014); Ahmadi M., Seifi A., Tootooni B., A humanitarian logistics model for disaster relief operation considering network failure and standard relief time: A case study on San Francisco district, Transport Res. E-Log, 75, pp. 145-163, (2015); Baharmand H., Comes T., Lauras M., Bi-objective multi-layer location-allocation model for the immediate aftermath of sudden-onset disasters, Transport. Res. E-Log, 127, pp. 86-110, (2019); Sun Q., Liu S., Locating abrupt disaster emergency logistics centres using improved artificial bee colony (IABC) algorithm, Sci. Progress, 104, (2021); Boonmee C., Arimura M., Asada T., Facility location optimization model for emergency humanitarian logistics, Int. J. Disast. Risk Reduct, 24, pp. 485-498, (2017); Tofighi S., Torabi S., Mansouri S., Humanitarian Logistics Network Design under Mixed Uncertainty, Eur. J. Oper. Res, 250, pp. 239-250, (2016); Haghi M., Ghomi S.M.T.F., Jolai F., Developing a robust multi-objective model for pre/post disaster times under uncertainty in demand and resource, J. Clean. Prod, 154, pp. 188-202, (2017); Sheu J., An emergency logistics distribution approach for quick response to urgent relief demand in disasters, Transport Res. E-log, 43, pp. 687-709, (2007); Li L., Tang S., An Artificial Emergency Logistics-Planning System for Severe Disasters, IEEE Intell. Syst, 23, pp. 86-88, (2008); Ozdamar L., Ekinci E., Kuecuekyazici B., Emergency Logistics Planning in Natural Disasters, An. Oper. Res, 129, pp. 217-245, (2004); Yi W., Ozdamar L., A dynamic logistics coordination model for evacuation and support in disaster response activities, Eur. J. Oper. Res, 179, (2005); Zhang Y., Liu J., Emergency Logistics Scheduling Under Uncertain Transportation Time Using Online Optimization Methods, IEEE Access, 9, pp. 36995-37010, (2021); Feizollahi S., Shirmohammadi A., Kahreh Z., Investigation the requirements of supply and distribution emergency logistics management and categorization its sub-criteria using AHP: A case study, Manage. Sci. Lett, 2, (2012); L'Hermitte C., Nair N., A blockchain-enabled framework for sharing logistics res"}},"S. Hu; School of Economics and Management, Guangxi Normal University, Guilin, 541000, China; email: husong498617199@163.com",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85137190863"]
["Agrawal D.K.","Agrawal, Durgesh Kumar (55185438000)",5.5185438E10,"Determining behavioural differences of Y and Z generational cohorts in online shopping",2022.0,"International Journal of Retail and Distribution Management",50.0,7.0,null,880.0,895.0,15.0,23.0,"10.1108/IJRDM-12-2020-0527","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85125098366&doi=10.1108%2fIJRDM-12-2020-0527&partnerID=40&md5=b1f47909b75907f6d6559709134f2708","ITS School of Management, Ghaziabad, India","Agrawal D.K., ITS School of Management, Ghaziabad, India","Purpose: The present study aims at examining the behavioural differences of the Y and Z generational cohorts in online shopping for physical products. Design/methodology/approach: Logistic regressions (LRs) were conducted to identify positively significant, negatively significant and insignificant variables/items of shopping motives to determine online shopping behavioural differences of both cohorts. Findings: While shopping online, the Gen Y cohort focuses on rational decisions, and Gen Z derives enjoyment, learning, exploration and has a deal-hunting behaviour. Gen Y incorporates actual shopping experiences shared on social media, is relatively less individualistic and more social, unlike Gen Z youths who significantly value reviews and ratings. Both cohorts carry a high-product risk and sacrifice many hedonic motives. Y and Z cohorts perceive financial risk and a product's performance-related risks, respectively. The Z cohort has an intrinsic passion for digital technology whereas Gen Y uses it purposely. Thus, both have distinctive online shopping behaviours apart from some similarities. Practical implications: Online retailers can use the findings of this study to develop more effective marketing strategies to serve both the cohorts better who have largely mutually exclusive online shopping behaviours. Originality/value: The study measured actual behaviours on contemporary and comprehensive variables/items of utilitarian and hedonic motives, and associated perceived risks in online shopping exclusively. Therefore, the results offer significant, realistic and useful theoretical contributions in the present context to the existing literature on the subject matter along with valuable inputs to the practitioners. © 2022, Emerald Publishing Limited.","Generation Y; Generation Z; Hedonic motives; Online shopping behaviour; Perceived risks; Utilitarian motives",{"$nulls":7},"Agrawal D.K., Addendum to Internet based distribution systems: a contemporary commentary, Information Systems: Debates, Applications and Impacts, pp. 136-140, (2019); Agrawal D.K., Agrawal D.P., Singh D., The Internet based distribution systems: a framework for adoption, Decisions, 33, 1, pp. 21-46, (2006); Ariffin S.K., Mohan T., Yen-Nee G., Influence of consumers’ perceived risk on consumers’ online purchase intention, Journal of Research in Interactive Marketing, 12, 3, pp. 309-327, (2018); Arnold M.J., Reynolds K.E., Hedonic shopping motivations, Journal of Retailing, 79, 1, pp. 77-95, (2003); Atulkar S., Kesari B., Satisfaction, loyalty and re-patronage intentions: role of hedonic shopping Values, Journal of Retailing and Consumer Services, 39, pp. 23-34, (2017); Brynjolfsson E., Hu Y.J., Rahman M.S., Competing in the age of omni-channel retailing, MIT Sloan Management Review, 54, 4, pp. 23-29, (2013); Burt G., Indian shoppers move to bricks-and-clicks from bricks versus clicks, (2019); Bush A.J., Hair J.K., An assessment of the mall intercept as a data collection method, Journal of Marketing Research, 22, 2, pp. 158-167, (1985); Caplan E., Brand loyalty, Dealerscope, 20, May, (2005); Davis R., Smith S.D., Lang B.U., A comparison of online and offline gender and goal-directed shopping online, Journal of Retailing and Consumer Services, 38, pp. 118-125, (2017); Dorie A., Loranger D., The multi-generation generational differences in channel activity, International Journal of Retail and Distribution Management, 48, 4, pp. 395-416, (2020); Eastman J.K., Liu J., The impact of generational cohorts on status consumption: an exploratory look at generational cohort and demographics on status consumption, Journal of Consumer Marketing, 29, 2, pp. 93-102, (2012); Evangelista F., Low B.K., Nguyen M.T., How shopping motives, store attributes and demographic factors influence store format choice in Vietnam: a logistic regression analysis, Asia Pacific Journal of Marketing and Logistics, 32, 1, pp. 149-168, (2019); Forsythe S., Liu C., Shannon D., Gardner L.C., Development of a scale to measure the perceived benefits and risks of online shopping, Journal of Interactive Marketing, 20, 2, pp. 55-75, (2006); Hall A., Towers N., Shaw D.R., Understanding how millennial shoppers decide what to buy: digitally connected unseen journeys, International Journal of Retail and Distribution Management, 45, 5, pp. 498-517, (2017); Heitz-Spahn S., Cross-channel free-riding consumer behaviour in a multichannel environment: an investigation of shopping motives, socio-demographics and product categories, Journal of Retailing and Consumer Services, 20, pp. 570-578, (2013); Heng Y., Zhifeng G., Yuan Y.J., Chen X., Exploring hidden factors behind online food shopping from Amazon reviews: a topic mining approach, Journal of Retailing and Consumer Services, 42, pp. 161-168, (2018); Hirschman E.C., Holbrook M.B., Hedonic consumption: emerging concepts, methods and propositions, Journal of Marketing, 46, 2, pp. 92-101, (1982); Ho H.C., Awan M., The gender effect on consumer attitudes toward payment methods: the case of online Chinese customers, Journal of Internet Commerce, 18, 2, pp. 141-169, (2019); Horvath C., Adiguzel F., Shopping enjoyment to the extreme: hedonic shopping motivations and compulsive buying in developed and emerging markets, Journal of Business Research, 86, pp. 300-310, (2018); James G., Witten D., Hastie T., Tibshirani R., An Introduction to Statistical Learning, (2013); Jong M.D., Dijk M.V., Disrupting beliefs: a new approach to the business-model innovation, McKinsey Quarterly, (2015); Kardes F., Cronley M., Cline T., Consumer Behaviour, (2014); Kim A., McInerney P., Smith T.S., Yamakawa N., What makes Asia–Pacific’s Generation Z different?, (2020); Kumar A., Kashyap A.K., Leveraging utilitarian perspective of online shopping to motivate online shoppers, International Journal of Retail and Distribution Management, 46, 30, pp. 247-263, (2018); Kurz C., Li G., Vine D.J., Are Millennials Different?. Finance and Economics Discussion Series, 2018-080, (2018); Kwak H., Fox R.J., Zinkhan G.M., What products can be successfully promoted and sold via the internet?, Journal of Advertising Research, pp. 23-38, (2002); Lee S.-G., Trimi S., Yang C.-G., Perceived usefulness factors of online reviews: a study of Amazon.com, Journal of Computer Information Systems, 58, 4, pp. 344-352, (2017); Lee S.H., Luster S., The social network implications of prestigious goods among young adults: evaluating the self vs. others, Journal of Consumer Marketing, 32, 3, pp. 199-208, (2015); Leung L., Generational differences in content generation in social media: the roles of gratifications sought and of narcissism, Computers in Human Behaviour, 29, 3, pp. 997-1006, (2013); Li K., Chen Y., Zhang L., Exploring the influence of online reviews and motivating factors on sales: a meta-analytic study and the moderating role of product category, Journal of Retailing and Consumer Services, 55, pp. 102-107, (2020); Lissitsa S., Kol O., Generation X vs. Generation Y – a decade of online shopping, Journal of Retailing and Consumer Services, 31, pp. 304-312, (2016); MacKenzie S.B., Podsakoff P.M., Common method bias in marketing: causes, mechanisms, and procedural remedies, Journal of Retailing, 88, pp. 542-555, (2012); Malhotra N.K., Dash S., Marketing Research: An Applied Orientation, (2011); Martin J., Mortimer G., Andrews L., Re-examining online customer experience to include purchase frequency and perceived risk, Journal of Retailing and Consumer Services, 25, pp. 81-95, (2015); McIntosh-Elkins J., McRitchie K., Scoones M., From the silent generation to generation X, Y and Z: strategies for managing the generation mix, Proceedings of the 35th Annual ACM SIGUCCS Fall Conference, pp. 240-246, (2007); Moore M., Interactive media usage amongst Millennial consumers, Journal of Consumer Marketing, 29, 6, pp. 436-444, (2012); Nisel R., Analysis of consumer characteristics which influence the determinants of buying decisions by the logistic regression model, Logistics Information Management, 14, 3, pp. 223-228, (2001); Noble S.M., Haytko D.L., Melancon J.P., What drives college-age Generation Y consumers?, Journal of Business Research, 62, 6, pp. 617-628, (2009); Okado E.M., Justification effect on consumer choice of hedonic and utilitarian goods, Journal of Marketing Research, 42, 1, pp. 43-53, (2005); Ozkan M., Solmaz B., Mobile addiction of Generation Z and its effects on their social life, Procedia-Social and Behavioural Sciences, 205, pp. 92-98, (2015); Pandey S., Chawla D., Online customer experience (OCE) in clothing e-retail: exploring OCE dimensions and their impact on satisfaction and loyalty–Does gender matter?, International Journal of Retail and Distribution Management, 46, 3, pp. 323-346, (2018); Pappas N., Marketing strategies, perceived risks, and consumer trust in online buying behaviour, Journal of Retailing and Consumer Services, 29, pp. 92-103, (2016); Parment A., Generation Y vs. Baby Boomers: shopping behaviour, buyer involvement and implications for retailing, Journal of Retailing and Consumer Services, 20, 2, pp. 189-199, (2013); Pentecost R., Donoghue S., Thaichon P., Emerging from my youth–intra-cohort segmentation, International Journal of Retail and Distribution Management, 47, 5, pp. 571-588, (2019); Prensky M., Digital natives, digital immigrants, On the Horizon, 9, 5, pp. 1-6, (2001); Priporas C.-C., Stylos N., Fotiadis A.K., Generation Z consumers’ expectations of interactions in smart retailing: a future agenda, Computers in Human Behaviour, 77, pp. 374-381, (2017); Rahulan M., Troynikov O., Watson C., Janta M., Senner V., Consumer behaviour of generational cohorts for compression sportswear, Journal of Fashion Marketing Management, 19, 1, pp. 87-104, (2015); Ringler C., Nancy J., Sirianni N.J., Gustafsson A., Peck J., Look but don’t touch! The impact of active interpersonal haptic blocking on compensatory touch and purchase behaviour, Journal of Retailing, 95, 4, pp. 186-203, (2019); Schiffman L.G., Wisenblit J., Kumar S.R., Consumer Behaviour, (2016); Schewe C., Meredith G., Segmenting global markets by generational cohorts: determining motivations by age, Journal of Consumer Behaviour, 4, pp. 51-63, (2004); Singh R., Why do online grocery shoppers switch or stay? An exploratory analysis of consumers’ response to online grocery shopping experience, International Journal of Retail and Distribution Management, 47, 12, pp. 1300-1317, (2019); Sramova B., Pavelka J., Gender differences and wellbeing values in adolescent online shopping, International Journal of Retail and Distribution Management, 47, 6, pp. 623-642, (2019); Reach of top online retail categories worldwide, (2018); Suman S.K., Srivastava P., Vadera S., Exploring the behaviour of Indian consumers towards online discounts, International Journal of Electronic Marketing and Retailing, 10, 1, pp. 78-94, (2019); Tauber E.M., Why people do shop?, Journal of Marketing, 36, 4, pp. 46-49, (1972); Tongco M.D.C., Purposive sampling as a tool for informant selection, Ethnobotany Research and Applications, 5, pp. 147-158, (2007); Vittinghoff E., McCulloch C.E., Relaxing the rule of ten events per variable in logistic and cox regression, American Journal of Epidemiology, 165, 6, pp. 710-718, (2007); Wooldridge J.M., Introductory Econometrics: A Modern Approach, (2013); Yarrow K., Decoding the New Consumer Mind, (2014); Zhu B., Kowatthanakul S., Satanasavapak P., Generation Y consumer online repurchase intention in Bangkok Based on Stimulus-Organism-Response (SOR) model, International Journal of Retail and Distribution Management, 48, 1, pp. 53-69, (2020)","D.K. Agrawal; ITS School of Management, Ghaziabad, India; email: agrawal_dk2001@yahoo.com",null,"Emerald Group Holdings Ltd.",{"$nulls":5},9590552.0,null,null,null,"English","Int. J. Retail Disrtib. Manage.","Article","Final",null,"Scopus","2-s2.0-85125098366"]
["Tuli R.; Soneji H.; Vahora S.; Churi P.; Bangalore N.M.","Tuli, Rohan (57565759300); Soneji, Hitesh (57566342400); Vahora, Sahil (57566540000); Churi, Prathamesh (57188831747); Bangalore, Nagachetan M. (36902538200)","57565759300; 57566342400; 57566540000; 57188831747; 36902538200","PixJS: A novel chaos-based approach for image encryption",2022.0,"Concurrency and Computation: Practice and Experience",34.0,17.0,"e6990",null,null,null,3.0,"10.1002/cpe.6990","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85127798965&doi=10.1002%2fcpe.6990&partnerID=40&md5=b94cfa8f4e317b4003050c9724d9c540","Artificial Intelligence and Adaptive Systems, University of Sussex, Brighton, United Kingdom; Computer Engineering Department, Mukesh Patel School of Technology Management & Engineering, NMIMS University, Mumbai, India; Visio ingenii, Milton Keynes, United Kingdom","Tuli R., Artificial Intelligence and Adaptive Systems, University of Sussex, Brighton, United Kingdom; Soneji H., Computer Engineering Department, Mukesh Patel School of Technology Management & Engineering, NMIMS University, Mumbai, India; Vahora S., Computer Engineering Department, Mukesh Patel School of Technology Management & Engineering, NMIMS University, Mumbai, India; Churi P., Computer Engineering Department, Mukesh Patel School of Technology Management & Engineering, NMIMS University, Mumbai, India; Bangalore N.M., Visio ingenii, Milton Keynes, United Kingdom","Image encryption has variety of applications in the healthcare, military, e-commerce, and education sectors. Along with processing images for various applications, secure storage of such images is essential. For many years, encryption of images is a fruitful method for the secure transmission of multimedia data that carries sensitive information across multiple mediums. There is umpteen number of image encryption methods available which exhibit improved performance either in time, space, or susceptance to attacks in a controlled environment. Few image encryption algorithms have higher computational complexity, whereas some are immune to a handful of attacks (either differential, statistical, brute force, or known-plaintext and chosen-plain text attacks). We have developed a novel chaos-based image encryption algorithm—PixJS for 8-bit grayscale images based on linear feedback shift register, logistic map, and jumbling process. The algorithm was initially proposed for the text-based passwords called as jumbling-salting algorithm in 2014. We conducted a comprehensive analysis of the proposed algorithm on sets of symmetric and asymmetric images (10 samples each) and addressed four research questions primarily based on speed and security parameters. After conducting thorough experimentation, we found that our algorithm outperformed existing algorithms in security and has proven to be resistant to statistical, differential, brute-force, known plain text, and chosen plain text attacks. © 2022 John Wiley & Sons, Ltd.","brute force attack; chaos; chosen plain text attacks; encryption; image; jumbling; known plain text attack; PixJS; statistical attack","Digital storage; Image enhancement; Military applications; Military photography; Shift registers; Brute-force attack; Chosen plain text attack; Image; Image encryption algorithm; Images encryptions; Jumbling; Known-plain text attack; PixJS; Plain text; Statistical attacks; Cryptography",{"$nulls":6},"Xia L., Cui J., Shen R., Xu X., Gao Y., Li X., A survey of image semantics-based visual simultaneous localization and mapping: application-oriented solutions to autonomous navigation of mobile robots, Int J Adv Robot Syst, 17, 3, (2020); Wu J., Xie J., Bardakoff A., Blattner T., Keyrouz W., Bhattacharyya S.S., CGMBE: a model-based tool for the design and implementation of real-time image processing applications on CPU–GPU platforms, J Real-Time Image Process, 18, 3, pp. 561-583, (2021); Loan N.A., Parah S.A., Sheikh J.A., Akhoon J.A., Bhat G.M., Hiding electronic patient record (EPR) in medical images: a high capacity and computationally efficient technique for e-healthcare applications, J Biomed Inform, 73, pp. 125-136, (2017); Slimani I., Zaarane A., Hamdoun A., Atouf I., Vehicle license plate localization and recognition system for intelligent transportation applications. 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Proceedings of the 2017 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC); 2017:858-863; Chen Y., Tang C., Ye R., Cryptanalysis and improvement of medical image encryption using high-speed scrambling and pixel adaptive diffusion, Signal Process, 167, (2020); Khan M., Shah T., A literature review on image encryption, Dent Tech 3D Res, 5, 4, (2014); Li M., Fan H., Xiang Y., Li Y., Zhang Y., Cryptanalysis and improvement of a chaotic image encryption by first-order time-delay system, IEEE MultiMedia, 25, 3, pp. 92-101, (2018); Kumar M., Saxena A., Vuppala S.S., Survey A., On chaos based image encryption techniques BT - multimedia security using chaotic maps: principles and methodologies, Multimedia Security Using Chaotic Maps: Principles and Methodologies. 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Churi; Computer Engineering Department, Mukesh Patel School of Technology Management & Engineering, NMIMS University, Mumbai, India; email: prathamesh.churi@gmail.com",null,"John Wiley and Sons Ltd",{"$nulls":5},1.5320626E7,null,"CCPEB",null,"English","Concurr. Comput. Pract. Exper.","Article","Final",null,"Scopus","2-s2.0-85127798965"]
["Yu X.; Zhan D.; Liu L.; Lv H.; Xu L.; Du J.","Yu, Xu (55535815700); Zhan, Dingjia (57222709371); Liu, Lei (56612510500); Lv, Hongwu (35242857800); Xu, Lingwei (55606481600); Du, Junwei (55235436800)","55535815700; 57222709371; 56612510500; 35242857800; 55606481600; 55235436800","A Privacy-Preserving Cross-Domain Healthcare Wearables Recommendation Algorithm Based on Domain-Dependent and Domain-Independent Feature Fusion",2022.0,"IEEE Journal of Biomedical and Health Informatics",26.0,5.0,null,1928.0,1936.0,8.0,51.0,"10.1109/JBHI.2021.3069629","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85103786354&doi=10.1109%2fJBHI.2021.3069629&partnerID=40&md5=1ce6796399170e8462d9c8b68df1298d","Qingdao University Of Science And Technology, College Of Information Science And Technology, Shandong, Qingdao, 266061, China; Xidian University, State Key Laboratory Of Integrated Service Networks, Shanxi, Xi'an, 710071, China; Harbin Engineering University, College Of Computer Science And Technology, Heilongjiang, Harbin, 150001, China","Yu X., Qingdao University Of Science And Technology, College Of Information Science And Technology, Shandong, Qingdao, 266061, China; Zhan D., Qingdao University Of Science And Technology, College Of Information Science And Technology, Shandong, Qingdao, 266061, China; Liu L., Xidian University, State Key Laboratory Of Integrated Service Networks, Shanxi, Xi'an, 710071, China; Lv H., Harbin Engineering University, College Of Computer Science And Technology, Heilongjiang, Harbin, 150001, China; Xu L., Qingdao University Of Science And Technology, College Of Information Science And Technology, Shandong, Qingdao, 266061, China; Du J., Qingdao University Of Science And Technology, College Of Information Science And Technology, Shandong, Qingdao, 266061, China","Recently, recommender systems are applied to provide personalized recomendation for healthcare wearables. However, due to the sparsity problem, traditional recommendation algorithms are difficult to achieve desired performance. Considering that consumers often buy and rate other types of items on E-commerce platforms, we can leverage significant information in the auxiliary domains to improve the recommendation performance of healthcare wearables, which can be regarded as cross-domain recommendation. However, traditional cross-domain recommendation model cannot fully represent user's characteristics and fail to consider the leaks of original auxiliary domain ratings during the information transfer process. To overcome the two shortcomings, this paper proposes a Privacy-Preserving Cross-Domain Healthcare Wearables Recommendation algorithm (PPCDHWRec). Firstly, user's characteristics are divided into domain-dependent features and domain-independent features, which complement each other and fully depict the user's characteristics. Secondly, inspired by the latent factor model, we factorize the original rating information of each auxiliary domain by Funk-SVD and Orthogonal Nonnegative Matrix Tri-Factorization (ONMTF) model, to obtain user's domain-dependent and domain-independent features, respectively. Finally, the Factorization Machine algorithm is used to fuse the obtained user's features with the target domain information to provide the recommendation results. By hiding the item latent factors obtained in the factorization process, PPCDHWRec ensures that the original information cannot be inferred from the transferred user hidden vector. Hence, PPCDHWRec is a privacy-preserving recommendation model. Experiments on two groups of auxiliary domains, having high and low correlations with target domain, show the effectiveness of PPCDHWRec.  © 2013 IEEE.","Domain-Dependent feature; domain-independent feature; factorization machine; feature fusion; healthcare wearables recommendation; privacy-preserving cross-domain recommendation","Algorithms; Delivery of Health Care; Humans; Privacy; Wearable Electronic Devices; Electronic commerce; Factorization; Health care; Privacy by design; Wearable technology; Cross-domain recommendations; Domain independents; Factorization machines; Information transfers; Latent factor models; Non-negative matrix; Recommendation algorithms; Recommendation performance; Article; artificial neural network; behavior; biofeedback; commercial phenomena; computer model; health care; health care personnel; learning; machine learning; nonhuman; research; social network; training; algorithm; electronic device; health care delivery; human; privacy; Recommender systems",{"$nulls":4},"Shandong Province Colleges, and Universities Young Talents Initiation Program, (2019KJN047); Key Technology Research and Development Program of Shandong, (2018GGX101052); National Natural Science Foundation of China, NSFC, (61273180, 61402246, U1806201); Natural Science Foundation of Shandong Province, (ZR2019MF014, ZR2020QF003)","Manuscript received January 21, 2021; revised February 25, 2021 and March 5, 2021; accepted March 14, 2021. Date of publication April 1, 2021; date of current version May 5, 2022. This work was supported in part by the National Natural Science Foundation of China under Grants 61402246, 61273180, and U1806201, in part by the Natural Science Foundation of Shandong Province under Grants ZR2019MF014 and ZR2020QF003, in part by the Key Research, and Development program of Shandong Province under Grant 2018GGX101052, and in part by Shandong Province Colleges, and Universities Young Talents Initiation Program under Grant 2019KJN047. (Corresponding author: Hongwu Lv.) Xu Yu, Dingjia Zhan, Lingwei Xu, and Junwei Du are with the College of Information Science and Technology, Qingdao University of Science and Technology, Qingdao, Shandong 266061, China (e-mail: yuxu0532@qust.edu.cn; zhandingjia_qust@163.com; xulw@ qust.edu.cn; djwqd@163.com).","Wang S., Et al., Blockchain-powered parallel healthcare systems based on the ACP approach, IEEE Trans. Computat. 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Syst., pp. 1-1, (2020); Xiao Y., Xiao L., Lu X., Zhang H., Yu S., Poor H.V., Deep reinforcement learning based user profile perturbation for privacy aware recommendation, IEEE Internet Things J., 8, 6, pp. 4560-4568, (2021); Feng P., Zhu H., Liu Y., Chen Y., Zheng Q., Differential privacy protection recommendation algorithm based on student learning behavior, Proc. IEEE Int. Conf. E-Bus. Eng., pp. 285-288, (2018); Kohavi R., Et al., A study of cross-validation and bootstrap for accuracy estimation and model selection, Proc. Int. Joint Conf. Artif. Intell., pp. 1137-1145, (1995)","H. Lv; Harbin Engineering University, College Of Computer Science And Technology, Heilongjiang, Harbin, 150001, China; email: lvhongwu@hrbeu.edu.cn",null,"Institute of Electrical and Electronics Engineers Inc.",{"$nulls":5},2.1682194E7,null,"ITIBF",3.3793406E7,"English","IEEE J. Biomedical Health Informat.","Article","Final",null,"Scopus","2-s2.0-85103786354"]
["Chen R.; Meng Q.; Jia P.","Chen, Rui (57206901327); Meng, Qiang (7202535468); Jia, Peng (57203985401)","57206901327; 7202535468; 57203985401","Container port drayage operations and management: Past and future",2022.0,"Transportation Research Part E: Logistics and Transportation Review",159.0,null,102633.0,null,null,null,20.0,"10.1016/j.tre.2022.102633","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85125232401&doi=10.1016%2fj.tre.2022.102633&partnerID=40&md5=043b9c8952af33d6d974e84d44e10799","Department of Civil and Environmental Engineering, National University of Singapore, Singapore, 117576, Singapore; School of Maritime Economics and Management, Dalian Maritime University, Dalian, 116026, China","Chen R., Department of Civil and Environmental Engineering, National University of Singapore, Singapore, 117576, Singapore; Meng Q., Department of Civil and Environmental Engineering, National University of Singapore, Singapore, 117576, Singapore; Jia P., School of Maritime Economics and Management, Dalian Maritime University, Dalian, 116026, China","Although long-haul intermodal container transportation combines multiple transportation modes including shipping, the most critical aspect of enabling door-to-door service is container port drayage operation. Container port drayage connects customers and container ports and provides an effective solution to the first/last-mile problem faced by the container logistics industry. Therefore, container port drayage has a significant impact not only on the economic advantages of the long-haul intermodal container transportation chain, but also the management, environment and social benefits of the stakeholders involved. In this paper, we comprehensively review the existing literature on container port drayage studies from different methodological angles (e.g., model development and algorithm design) and technological angles (e.g., autonomous truck and blockchain). Moreover, with the shifting of industrial focus from traditional operations and management of container port drayage towards e-commerce platforms, we identify potential issues for future research directions. © 2022 Elsevier Ltd","Algorithms; Container port drayage; Drayage operations and management; Mathematical models","Containers; Economic and social effects; Intermodal transportation; Container logistics; Container port drayage; Container ports; Drayage operation and management; Effective solution; Intermodal container transportations; Last mile problems; Long haul; Operation and management; Transportation mode; algorithm; container terminal; containerization; future prospect; numerical model; port operation; Industrial research",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (72174035); Liaoning Revitalization Talents Program, (XLYC2008030)","This study is supported by the research project Ref. NOL18RP02 founded by the NOL Fellowship. The third author acknowledges the support of National Natural Science Foundation of China ( 72174035 ) and Liaoning Revitalization Talents Program ( XLYC2008030 ) for this study. ","Adams-Guppy J., Guppy A., Truck driver fatigue risk assessment and management: a multinational survey, Ergonomics, 46, pp. 763-779, (2003); Ahmad R.W., Hasan H., Jayaraman R., Salah K., Omar M., Blockchain applications and architectures for port operations and logistics management, Res. Transp. Bus. Manage., (2021); Ashrafi M., Walker T.R., Magnan G.M., Adams M., Acciaro M., A review of corporate sustainability drivers in maritime ports: a multi-stakeholder perspective, Maritime Policy Manage., 47, pp. 1027-1044, (2020); Bhoopalam A.K., Agatz N., Zuidwijk R., Planning of truck platoons: A literature review and directions for future research, Transp. Res. B, 107, pp. 212-228, (2018); Bierwirth C., Meisel F., A survey of berth allocation and quay crane scheduling problems in container terminals, European J. 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["Parvin M.; Asimiran S.B.; Ayub A.F.B.M.","Parvin, Morsheda (57218285280); Asimiran, Soaib Bin (26530857400); Ayub, Ahmad Fauzi Bin Mohd (7003656130)","57218285280; 26530857400; 7003656130","Impact of introducing e-commerce on small and medium enterprises – a case on logistics provider",2022.0,"Society and Business Review",17.0,3.0,null,469.0,484.0,15.0,4.0,"10.1108/SBR-10-2020-0131","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85133473948&doi=10.1108%2fSBR-10-2020-0131&partnerID=40&md5=84fad7f4de68cbad96acbbc5723c7d7b","Faculty of Educational Studies, Universiti Putra Malaysia, Serdang, Malaysia; Department of Foundations of Education, Faculty of Educational Studies, Universiti Putra Malaysia, Serdang, Malaysia","Parvin M., Faculty of Educational Studies, Universiti Putra Malaysia, Serdang, Malaysia; Asimiran S.B., Department of Foundations of Education, Faculty of Educational Studies, Universiti Putra Malaysia, Serdang, Malaysia; Ayub A.F.B.M., Department of Foundations of Education, Faculty of Educational Studies, Universiti Putra Malaysia, Serdang, Malaysia","Purpose: Small and medium enterprises (SME) significantly alleviate poverty and generate employment to achieve sustainable economic growth. Using electronic devices, e-commerce allows an immediate and advanced communication service to accomplish business transactions. Considering logistics provider as a case, this paper aims to examine the impact of adopting an e-commerce technology on its customers’ and agents’ satisfaction. Design/methodology/approach: The authors use the difference in difference methodology to examine these effects and find positive impacts on both customers and service providers. Findings: As SMEs are widely considered as the powerhouse of an economy, the authors’ findings suggest that using e-commerce not only makes an SME agent more efficient but also accelerates an SME business transaction, which ultimately helps to achieve sustainable economic growth. Originality/value: A few studies are conducted in examining the impact of SME on economy. However, according to the authors’ knowledge, this is the first research that examines the impact of e-commerce on SME. © 2020, Emerald Publishing Limited.","e-commerce; Small and medium enterprise; Successful SME business model",{"$nulls":7},"Achrol R.S., Kotler P., Marketing in the network economy, Journal of Marketing, 63, pp. 146-163, (1999); Alam G.M., Parvin M., Roslan S., Growth of private university business following ‘oligopoly’ and ‘SME’ approaches: an impact on the concept of university and on society, Society and Business Review, (2020); Al-Natour S., Benbasat I., Cenfetelli R., The adoption of online shopping assistants: perceived similarity as an antecedent to evaluative beliefs, Journal of the Association for Information Systems, 12, 5, pp. 347-374, (2011); Anwar M., Ali Shah S.Z., Managerial networking and business model innovation: empirical study of new ventures in an emerging economy, Journal of Small Business and Entrepreneurship, 32, 3, pp. 265-286, (2020); Arcand M., PromTep S., Brun I., Rajaobelina L., Mobile banking service quality and customer relationships, International Journal of Bank Marketing, 35, 7, pp. 1067-1089, (2017); 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Applying trust to social commerce, Journal of Computer Information Systems, 59, 1, pp. 32-42, (2019); (2020); Uzoka F.M.E., Shemi A.P., Seleka G.G., Behavioral influences on e‐commerce adoption in a developing country context, The Electronic Journal of Information Systems in Developing Countries, 31, 1, pp. 1-15, (2007); Vakulenko Y., Shams P., Hellstrom D., Hjort K., Service innovation in e-commerce last mile delivery: mapping the e-customer journey, Journal of Business Research, 101, 7, pp. 461-468, (2019); Ramanathan R., Ramanathan U., Hsiao H.L., The impact of e-commerce on Taiwanese SMEs: marketing and operations effects, International Journal of Production Economics, 140, 2, pp. 934-943, (2012)","M. Parvin; Faculty of Educational Studies, Universiti Putra Malaysia, Serdang, Malaysia; email: mparvin222@yahoo.com",null,"Emerald Group Holdings Ltd.",{"$nulls":5},1.746568E7,null,null,null,"English","Soc. Bus. Rev.","Article","Final",null,"Scopus","2-s2.0-85133473948"]
["Zhan Y.; Jiang Y.","Zhan, Yajun (57855861300); Jiang, Yiping (55965631200)","57855861300; 55965631200","Integrated Optimization of Order Allocation and Last-Mile Multi-Temperature Joint Distribution for Fresh Agriproduct Community Retail",2022.0,"Sustainability (Switzerland)",14.0,15.0,9790.0,null,null,null,5.0,"10.3390/su14159790","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85136486789&doi=10.3390%2fsu14159790&partnerID=40&md5=c34f79cd384856b16163666f07e1bd37","College of Information Management, Nanjing Agricultural University, Nanjing, 210031, China","Zhan Y., College of Information Management, Nanjing Agricultural University, Nanjing, 210031, China; Jiang Y., College of Information Management, Nanjing Agricultural University, Nanjing, 210031, China","Community retail is an important research issue in the field of fresh agriproduct e-commerce. This paper focuses on the problem of last-mile multi-temperature joint distribution (MTJD), which combines time coupling, order allocation, and vehicle scheduling. Firstly, according to the temperature of a refrigerated truck in multi-temperature zones, a split-order packing decision is proposed to integrate the different types of fresh agriproduct. Then, the order allocation strategy is incorporated into a comprehensive picking and distribution schedule, while taking into account the time-coupling of picking, distribution, and delivery time limit. To improve consumer satisfaction and reduce order fulfillment costs, an optimization model combining multi-item order allocation and vehicle scheduling is established, to determine the optimal order allocation scheme and distribution route. Finally, taking fresh agriproduct community retail in the Gulou District of Nanjing as an example, the effectiveness and feasibility of the model are illustrated. The numerical results of medium- to large-scale examples show that, compared with the variable neighborhood search algorithm (VNS) and genetic algorithm (GA), the mixed genetic algorithm (MGA) can save 29% of CPU time and 65% of iterations. This study considers the integrated optimization of multiple links, to provide scientific decision support for fresh agriproduct e-commerce enterprises. © 2022 by the authors.","multi-temperature joint distribution; order consolidation; order splitting; picking","China; Jiangsu; Nanjing [Jiangsu]; electronic commerce; genetic algorithm; neighborhood; optimization; packing; temperature",{"$nulls":4},"Jin Shanbao Institute for Agriculture & Rural Development, (YZKKT2021011); National Training Program of Innovation and Entrepreneurship for Undergraduates, (202110307060); Natural Science Foundation of Jiangsu Province, (21GLC003); Nanjing Agricultural University, NAU, (SKCX2020009); Fundamental Research Funds for the Central Universities","This research was funded by the Social Science Foundation of Jiangsu Province, China (21GLC003), the Research Fund of Jin Shanbao Institute for Agriculture & Rural Development (YZKKT2021011), Fundamental Research Funds for the Central Universities (NAU: SKCX2020009), Outstanding Young Scholar of Jiangsu Qing Lan Program and the National Training Program of Innovation and Entrepreneurship for Undergraduates (202110307060).","Chen M.C., Lu C.C., Liu Y.C., Optimal consolidation of fresh agricultural products in a multi-temperature joint distribution system, Int. 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Logist, 4, pp. 399-419, (2015); Wang B.C., Qian Q.Y., Gao J.J., The optimization of warehouse location and resources distribution for emergency rescue under uncertainty, Adv. Eng. Inform, 48, (2021); Mausser H., Normalization and other topics in multi-objective optimization, Proceedings of the First Fields—MITACS Industrial Problems Workshop; Huang M., Li L., Hu X., Time-space network optimization method for split order consolidation on sorting center of large-scale online supermarket, J. Ind. Eng. Eng. Manag, 35, pp. 163-172, (2021); Nodali N., Hsiao H.I., Jelena V., Time-temperature abuse in the food cold chain: Review of issues, challenges, and recommendations, Food Control, 89, pp. 12-21, (2018); Schubert D., Kuhn H., Andreas H., Same-day deliveries in omnichannel retail: Integrated order picking and vehicle routing with vehicle-site dependencies, Nav. Res. Logist, 68, pp. 721-744, (2021)","Y. Jiang; College of Information Management, Nanjing Agricultural University, Nanjing, 210031, China; email: ypjiang@njau.edu.cn",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85136486789"]
["Zhang H.; Yu L.; Fei S.","Zhang, Hao (57864404200); Yu, Lei (56304346700); Fei, Shumin (7005943243)","57864404200; 56304346700; 7005943243","Design of Dual-LiDAR High Precision Natural Navigation System",2022.0,"IEEE Sensors Journal",22.0,7.0,null,7231.0,7239.0,8.0,6.0,"10.1109/JSEN.2022.3153900","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85128157700&doi=10.1109%2fJSEN.2022.3153900&partnerID=40&md5=f6cc0605c0e1d0ac6bf4a17f0103c8a3","School of Mechanical and Electric Engineering, Soochow University, Suzhou, 215000, China; State Key Laboratory of Computer Aided Design and Computer Graphics, Zhejiang University, Hangzhou, 310058, China; School of Automation, Southeast University, Nanjing, 210000, China","Zhang H., School of Mechanical and Electric Engineering, Soochow University, Suzhou, 215000, China; Yu L., School of Mechanical and Electric Engineering, Soochow University, Suzhou, 215000, China, State Key Laboratory of Computer Aided Design and Computer Graphics, Zhejiang University, Hangzhou, 310058, China; Fei S., School of Automation, Southeast University, Nanjing, 210000, China","With the further development of online shopping and the impact of the COVID-19 pandemic, the logistics industry has further increased the demand for unmanned, automated warehousing and logistics handling. To realize intelligent warehousing and logistics handling, reliable positioning navigation technology is indispensable. Therefore, this paper designs a Dual-lidar high-precision natural navigation system based on the ROS (Robot Operating System) platform, which can fulfill the basic warehousing and logistics requirements. The natural navigation system uses the Lidar-SLAM method based on graph optimization to construct the 2D environment map, the PF (Particle Filter) algorithm in MRPT (Mobile Robot Programming Toolkit) is used for system positioning, and the real-time correction algorithm is used for motion control. On the built hardware platform, the navigation system completed the fixed-point cruise navigation task, and finally achieved a navigation accuracy of 4 cm and an average repeatable navigation accuracy of 6 mm. The designed navigation system has reference significance for multi-sensor fusion navigation. In reality, it can be applied to the transportation of warehousing and logistics, and it is expected to be mass-produced in the future.  © 2001-2012 IEEE.","2D Lidar-SLAM; Natural navigation; real-time correction; ROS","Fixed platforms; Machine design; Mobile robots; Optical radar; Robot programming; 2d lidar-SLAM; Further development; High-precision; Logistics industry; Natural navigation; Navigation accuracy; Navigation technology; Online shopping; Real-time corrections; Robot operating system; Navigation systems",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (61873176); Soochow University","This work was supported in part by the National Natural Science Foundation of China under Grant 61873176 and in part by the Tang Scholar of Soochow University","Su S., Et al., Positioning accuracy improvement of automated guided vehicles based on a novel magnetic tracking approach, IEEE Intell. Transp. Syst. 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Robot., 31, 5, pp. 1147-1163, (2015); Li C., Yu L., Fei S., Real-time 3D motion tracking and reconstruction system using camera and IMU sensors, IEEE Sensors J., 19, 15, pp. 6460-6466, (2019); Durrant-Whyte H., Bailey T., Simultaneous localization and mapping: Part I, IEEE Robot. Autom. Mag., 13, 2, pp. 99-110, (2006); Bailey T., Durrant-Whyte H., Simultaneous localization and mapping (SLAM): Part II, IEEE Robot. Autom. Mag., 13, 3, pp. 108-117, (2006); Cadena C., Et al., Past, present, and future of simultaneous localization and mapping: Toward the robust-perception age, IEEE Trans. Robot., 32, 6, pp. 1309-1332, (2016); Castellanos J.A., Martinez-Cantin R., Tardos J.D., Neira J., Robocentric map joining: Improving the consistency of EKF-SLAM, Robot. Auto. Syst., 55, 1, pp. 21-29, (2007); Montemerlo M., Et al., FastSLAM: A factored solution to the simultaneous localization and mapping problem, Proc. Nat. Conf. Artif. 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["Rita P.; Ramos R.F.","Rita, Paulo (14629383400); Ramos, Ricardo F. (57210466897)","14629383400; 57210466897","Global Research Trends in Consumer Behavior and Sustainability in E-Commerce: A Bibliometric Analysis of the Knowledge Structure",2022.0,"Sustainability (Switzerland)",14.0,15.0,9455.0,null,null,null,21.0,"10.3390/su14159455","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137231470&doi=10.3390%2fsu14159455&partnerID=40&md5=f493da8a012d552604e57e2c6737afec","NOVA Information Management School (NOVA IMS), Universidade Nova de Lisboa, Campus de Campolide, Lisboa, 1070-312, Portugal; Instituto Politécnico de Coimbra, ESTGOH, Rua General Santos Costa, Oliveira do Hospital, 3400-124, Portugal; Instituto Universitário de Lisboa, ISTAR-IUL, Av. Forças Armadas, Lisboa, 1649-026, Portugal; Centro de Investigação em Ciências Económicas e Empresariais (CICEE), Universidade Autónoma de Lisboa, Rua de Santa Marta, Palácio dos Condes do Redondo 56, Lisboa, 1169-023, Portugal","Rita P., NOVA Information Management School (NOVA IMS), Universidade Nova de Lisboa, Campus de Campolide, Lisboa, 1070-312, Portugal; Ramos R.F., Instituto Politécnico de Coimbra, ESTGOH, Rua General Santos Costa, Oliveira do Hospital, 3400-124, Portugal, Instituto Universitário de Lisboa, ISTAR-IUL, Av. Forças Armadas, Lisboa, 1649-026, Portugal, Centro de Investigação em Ciências Económicas e Empresariais (CICEE), Universidade Autónoma de Lisboa, Rua de Santa Marta, Palácio dos Condes do Redondo 56, Lisboa, 1169-023, Portugal","Consumers are conscious of increasing online purchases and demand sustainable consumption friendly actions. Although there is increasing interest in this topic, the research status, development, and structure of consumer behavior and sustainability in e-commerce research is scarce. This study aims to analyze the intellectual, conceptual, and social knowledge of consumer behavior and sustainability in e-commerce research to generate new understandings. Data from 104 articles were collected from the Scopus database, and a bibliometric analysis was conducted. Results revealed a close relationship between the topic and city logistics, big data analysis, customer engagement, circular economy, online services, and omnichannel retail, showing the different research approaches and the transversal themes related to the topic. This study contributes to the sustainability academic research by identifying trends and suggesting future research topics. © 2022 by the authors.","bibliometric; consumer behavior; e-commerce; sustainability","academic research; consumption behavior; database; electronic commerce; sustainability; trend analysis",{"$nulls":4},"Centro de Investigação em Gestão de Informação; MagIC; NOVA IMS; Fundação para a Ciência e a Tecnologia, FCT","Paulo Rita was supported through the FCT (Fundação para a Ciência e a Tecnologia) under UIDB/04152/2020—Centro de Investigação em Gestão de Informação (MagIC)/NOVA IMS.","Keenan M., Global Ecommerce Explained: Stats and Trends to Watch in 2022; von Abrahams K., Global Ecommerce Forecast, (2021); Wagner G., Schramm-Klein H., Steinmann S., Online Retailing across E-Channels and e-Channel Touchpoints: Empirical Studies of Consumer Behavior in the Multichannel e-Commerce Environment, J. Bus. 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Ethics, 166, pp. 89-114, (2020)","P. Rita; NOVA Information Management School (NOVA IMS), Universidade Nova de Lisboa, Lisboa, Campus de Campolide, 1070-312, Portugal; email: prita@novaims.unl.pt; R.F. Ramos; Instituto Politécnico de Coimbra, ESTGOH, Oliveira do Hospital, Rua General Santos Costa, 3400-124, Portugal; email: ricardo_ramos@iscte-iul.pt",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85137231470"]
["della Porta D.; Chesta R.E.; Cini L.","della Porta, Donatella (6602283482); Chesta, Riccardo Emilio (57195335605); Cini, Lorenzo (57194101118)","6602283482; 57195335605; 57194101118","Mobilizing against the odds. Solidarity in action in the platform economy; [Mobiliser contre vents et marées. La solidarité en action dans l’économie des plateformes]; [Mobilisierung trotz Widrigkeiten. Praktizierte Solidarität in der Plattformökonomie]",2022.0,"Berliner Journal fur Soziologie",32.0,2.0,null,213.0,241.0,28.0,6.0,"10.1007/s11609-022-00471-z","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85129722296&doi=10.1007%2fs11609-022-00471-z&partnerID=40&md5=90e15e0be954de740c7d956ae4ef5fc4","Faculty of Political and Social Sciences, Scuola Normale Superiore, Palazzo Strozzi, Piazza degli Strozzi, Florence, 50123, Italy","della Porta D., Faculty of Political and Social Sciences, Scuola Normale Superiore, Palazzo Strozzi, Piazza degli Strozzi, Florence, 50123, Italy; Chesta R.E., Faculty of Political and Social Sciences, Scuola Normale Superiore, Palazzo Strozzi, Piazza degli Strozzi, Florence, 50123, Italy; Cini L., Faculty of Political and Social Sciences, Scuola Normale Superiore, Palazzo Strozzi, Piazza degli Strozzi, Florence, 50123, Italy","The relationship between working conditions and the development of collective solidarity has been much debated in sociology over the past century. The article contributes to this debate by exploring two recent cases of worker mobilization in the context of the Italian platform economy, concerning Amazon delivery drivers and food delivery couriers. Both groups developed specific identity frames in the course of their mobilizations in four Italian cities between 2018 and 2019, which differed significantly. The article explains those differences through a theoretical framework that bridges social movement and labor studies. While Amazon delivery drivers adopted a mobilizing strategy aimed narrowly at improving their conditions as Amazon workers, food delivery couriers elaborated a broader identity framing as precarious platform workers. The difference can be connected to specific features of labor organization, in particular regarding the diverse conditions met by digital innovation in the two sectors: While Amazon drivers belong to a technologically advanced segment (e-commerce) of a traditional sector (logistics), food delivery couriers are part of a new, platform-based sector. The article shows how such sectoral variation affected ways of collectively organizing, forms of solidarity and identity framing. © 2022, The Author(s).","Collective identity; Digital workers; Labor movement; Labor process; Platform economy",{"$nulls":5},"Scuola Normale Superiore, SNS; Horizon 2020 Framework Programme, H2020, (101028811)","Open Access funding provided by Scuola Normale Superiore within the CRUICARE Agreement.","Alberti G., Pero D., Migrating industrial relations migrant workers’ initiative within and outside trade unions, British Journal of Industrial Relations, 56, pp. 693-715, (2018); Altenried M., The platform as factory: crowdwork and the hidden labor behind artificial intelligence, Capital & Class, 44, 2, pp. 145-158, (2020); Atzeni M., Workplace conflict: mobilization and solidarity in Argentina, (2016); Bennett A., Case study methods: design, use, and comparative advantages, Models, number & cases. 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An inquiry into the global struggles of the gig economy, (2021); Wright E.O., Class counts: comparative studies in class analysis, (1997); Yin R.K., Case study research: design and methods, (2013); Zanella C., Milano, protesta ai cancelli di Amazon, Picchetto Dei Driver: “Oggi Niente Consegne, (2017); IC1: Interview with Food Delivery Courier, (2018); IC2: Interview with Food Delivery Courier, (2018); IC3: Interview with Food Delivery Courier, (2018); IC4: Interview with Food Delivery Courier, (2018); IC5: Interview with Food Delivery Courier, (2018); IC6: Interview with Food Delivery Courier, (2018); IC7: Interview with Food Delivery Courier, (2018); IC8: Interview with Food Delivery Courier, (2018); IC9: Interview with Food Delivery Courier, (2018); ID1: Interview with Regional Secretary of FILT-CGIL Lombardia, (2019); ID2: Interview with Amazon Driver, (2019); ID3: Interview with Amazon Driver, (2019); ID4: Interview with Amazon Driver, (2019); ID5: Interview with Amazon Driver, (2019); FN: Field Notes from Participant Observation at the Worker Assembly Buccinasco, (2019)","D. della Porta; Faculty of Political and Social Sciences, Scuola Normale Superiore, Florence, Palazzo Strozzi, Piazza degli Strozzi, 50123, Italy; email: donatella.dellaporta@sns.it",null,"Springer VS",{"$nulls":5},8631808.0,null,null,null,"English","Berl. J. Soziol.","Article","Final","All Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85129722296"]
["Tsai C.-A.; Chang C.-W.","Tsai, Cheng-An (35077298500); Chang, Che-Wei (57129234400)","35077298500; 57129234400","Development of a Partial Shipping Fees Pricing Model to Influence Consumers’ Purchase Intention under the COVID-19 Pandemic",2022.0,"Energies",15.0,5.0,1846.0,null,null,null,5.0,"10.3390/en15051846","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85126270107&doi=10.3390%2fen15051846&partnerID=40&md5=93c2bdfbb2099a18377a8c8a3be284d7","Department of Business Administration, Shih Chien University, Taipei, 104336, Taiwan; Department of Recreational & Graduate Institute of Recreational Sport Management, National Taiwan University of Sport, Taichung City, 404401, Taiwan","Tsai C.-A., Department of Business Administration, Shih Chien University, Taipei, 104336, Taiwan; Chang C.-W., Department of Recreational & Graduate Institute of Recreational Sport Management, National Taiwan University of Sport, Taichung City, 404401, Taiwan","The COVID-19 pandemic is accelerating the rapid development of the digital economy. Previous studies have indicated that shipping fees are essential in delivery strategies and significantly impact order generation rates. According to market research, 68% of consumers would increase their orders to reach the minimum threshold for free delivery. However, previous studies have focused on the problem of setting free shipping thresholds, so the existing model of the e-commerce platform only allows consumers to choose whether to pay the total shipping fees or conditional free delivery with a free shipping threshold. A lack of literature concerns the partial pay for shipping fees before reaching the free shipping threshold. Therefore, this study proposes a new pricing model for shipping strategy that allows consumers to pay partial shipping fees. This model can increase the flexibility of consumer choice, thus increasing consumers’ willingness to purchase, which in turn increases the revenue of the e-commerce platform. The model was validated for 9-month on the e-commerce platform of a Smart-Integration company. The results showed that after introducing the new pricing model, the e-commerce platform’s sales grew by about 9%. This proposed model’s theoretical extension and empirical results can remedy the research gap in the extant literature. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.","COVID-19; E-commerce platform; Partial pay; Shipping fees; Socio-economic factors","Costs; Market Research; Sales; Ships; Commerce platforms; Consumer purchase; COVID-19; E- commerces; E-commerce platform; Free shipping; Partial pay; Pricing models; Shipping fee; Socio-economic factor; Electronic commerce",{"$nulls":6},"Global Ecommerce Jumps to $26.7 Trillion, COVID-19 Boosts Online Sales; COVID’s Impact on Online Shopping; The Fermentation of the “House Economy” Has Led to the Growth of Online Sales; How Did the Consumer & Lifestyle Industry Change in Taiwan during the Peak of the Epidemic?; The Psychology of E-Commerce Consumption: Six Rules, the Secret of Making Consumers Buy, (2021); Shao X., Free or calculated shipping: Impact of delivery cost on supply chains moving to online retailing, Int. J. Prod. Econ, 191, pp. 267-277, (2017); Leng M., Becerril-Arreola R., Joint pricing and contingent free-shipping decisions in B2C transactions, Prod. 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Policy, 133, (2021); Mangiaracina R., Perego A., Seghezzi A., Tumino A., Innovative solutions to increase last-mile delivery efficiency in B2C e-commerce: A literature review, Int. J. Phys. Distrib. Logis. Manag, 49, pp. 901-920, (2019); Silverman B.G., Bachann M., Al-Akharas K., Implications of buyer decision theory for design of e-commerce websites, Int. J. Hum. Comput. Stud, 55, pp. 815-844, (2001); Zong K., Yuan Y., Montenegro-Marin C.E., Kadry S.N., Or-based intelligent decision support system for ecommerce, J. Theor. Appl. Electron. Commer. Res, 16, pp. 1150-1164, (2021); Chandra Y.U., Karya S., Hendrawaty M., Decision support systems for customer to buy products with an integration of reviews and comments from marketplace ecommerce sites in Indonesia: A proposed model, Int. J. Adv. Sci. Eng. Inf. Technol, 9, pp. 1171-1176, (2019); Wu J., Li L., Xu L.D., A randomized pricing decision support system in electronic commerce, Decis. Support Syst, 58, pp. 43-52, (2014); Ji P., Zhang H., Wang J., A fuzzy decision support model with sentiment analysis for items comparison in ecommerce: The case study of http://PConline.com, IEEE Trans. Syst. Man Cybern. Syst, 49, pp. 1993-2004, (2019); Hu M., Huang F., Hou H., Chen Y., Bulysheva L., Customized logistics service and online shoppers’ satisfaction: An empirical study, Internet Res, 26, pp. 484-497, (2016); Smart-Integration Healthsafe Market","C.-W. Chang; Department of Recreational & Graduate Institute of Recreational Sport Management, National Taiwan University of Sport, Taichung City, 404401, Taiwan; email: chewei@gm.ntus.edu.tw",null,"MDPI",{"$nulls":5},1.9961073E7,null,null,null,"English","Energies","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85126270107"]
["Han B.R.; Sun T.; Chu L.Y.; Wu L.","Han, Brian Rongqing (57215899091); Sun, Tianshu (57207451220); Chu, Leon Yang (55666484800); Wu, Lixia (57215899182)","57215899091; 57207451220; 55666484800; 57215899182","COVID-19 and E-Commerce Operations: Evidence from Alibaba",2022.0,"Manufacturing and Service Operations Management",24.0,3.0,null,1388.0,1405.0,17.0,18.0,"10.1287/msom.2021.1075","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85132240169&doi=10.1287%2fmsom.2021.1075&partnerID=40&md5=53ddde9779132b35a8940b26145da2f0","Gies College of Business, University of Illinois at Urbana-Champaign, Champaign, 61820, IL, United States; Marshall School of Business, University of Southern California, Los Angeles, 90089, CA, United States; Cheung Kong Graduate School of Business, Beijing, 100006, China; Alibaba Group Inc, Hangzhou, 311121, China","Han B.R., Gies College of Business, University of Illinois at Urbana-Champaign, Champaign, 61820, IL, United States; Sun T., Marshall School of Business, University of Southern California, Los Angeles, 90089, CA, United States; Chu L.Y., Cheung Kong Graduate School of Business, Beijing, 100006, China; Wu L., Alibaba Group Inc, Hangzhou, 311121, China","Problem definition: This paper investigates the impact of COVID-19 on e-commerce sales and the underlying operational driver. Academic/practical relevance: As COVID-19 continues to disrupt offline retail, anecdotal evidence suggests a rapid growth of e-commerce. However, the pandemic may also significantly decrease offline logistics capacity, which in turn decreases e-commerce sales. Then, how does e-commerce respond to COVID-19, and what are the corresponding opportunities and challenges? Methodology: We leverage e-commerce sales data from Alibaba and construct a city-day panel across three years, representing sales for all buyers and sellers on the platform across 339 cities in mainland China. We develop three identification strategies to estimate the overall impact of COVID-19 (based on a year-on-year comparison), the impact of COVID-19 intensity (based on the different number of cases across cities), and the impact of corresponding containment measures (leveraging policy changes of checkpoint, partial shutdown, and complete shutdown measures across cities). Results: We provide two key findings. First, across different identification strategies, we observe a common drop and recovery pattern, which illustrates the digital resilience of e-commerce during the pandemic. For example, we estimate an overall decrease of 22% in e-commerce sales during the period of the Wuhan shutdown (January 23–April 7, 2020). However, it recovers in most cities within five weeks. Second, we identify a key operational driver—logistics capacity—that significantly explains the decline and recovery of e-commerce sales during and after the outbreak. Managerial implications: We provide important evidence on how e-commerce responds to and recovers from COVID-19, contrary to the common perception. The evidence in the recovery phase can also inform platforms and policymakers to design digital strategies and invest in logistics infrastructure. © 2022 INFORMS","containment measures; COVID-19; digital resilience; e-commerce; logistics","Electronic commerce; Recovery; Sales; Anecdotal evidences; Buyers and sellers; Containment measure; Digital resilience; E- commerces; E-commerce operations; Identification strategies; Offline; Problem definition; Rapid growth; COVID-19",{"$nulls":6},"Acemoglu D, Autor DH, Lyle D, Women, war, and wages: The effect of female labor supply on the wage structure at mid-century, J. Political Econom, 112, 3, pp. 497-551, (2004); Adda J, Economic activity and the spread of viral diseases: Evidence from high frequency data, Quart. J. 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Han; Gies College of Business, University of Illinois at Urbana-Champaign, Champaign, 61820, United States; email: brianhan@illinois.edu",null,"INFORMS Inst.for Operations Res.and the Management Sciences",{"$nulls":5},1.5234614E7,null,"MSOMF",null,"English","Manuf. Serv. Oper. Manage.","Article","Final",null,"Scopus","2-s2.0-85132240169"]
["Pahwa A.; Jaller M.","Pahwa, Anmol (57214588705); Jaller, Miguel (36158256500)","57214588705; 36158256500","A cost-based comparative analysis of different last-mile strategies for e-commerce delivery",2022.0,"Transportation Research Part E: Logistics and Transportation Review",164.0,null,102783.0,null,null,null,16.0,"10.1016/j.tre.2022.102783","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85132699427&doi=10.1016%2fj.tre.2022.102783&partnerID=40&md5=115574f76ac497233f3d6902d67f676d","Department of Civil and Environmental Engineering, University of California, One Shields Ave, Davis, 95616, CA, United States; Department of Civil and Environmental Engineering, Sustainable Freight Research Center, Institute of Transportation Studies, University of California, One Shields Ave, Davis, 95616, CA, United States","Pahwa A., Department of Civil and Environmental Engineering, University of California, One Shields Ave, Davis, 95616, CA, United States; Jaller M., Department of Civil and Environmental Engineering, Sustainable Freight Research Center, Institute of Transportation Studies, University of California, One Shields Ave, Davis, 95616, CA, United States","The growth of e-commerce has bridged the gap between the consumer and the retailer, bringing prosperity for both. However, in a quest to achieve even larger profits and market share, e-retailers compete to offer consumers cheaper shipping, expedited deliveries, free returns, and other lucrative deals. To keep pace with these growing needs of e-commerce, e-retailers have piloted various alternative distribution strategies. To aid a fuller understanding of the costs and benefits of these distribution strategies in diverse delivery environments, this work develops a multi-echelon last-mile distribution model using Continuous Approximation (CA) techniques. The model results suggest that traditional last-mile delivery with diesel trucks is a good fit for e-retailers delivering in dense environments with lenient temporal constraints (parcel service), a strategy that allows for demand consolidation and thus low-cost low-emission distribution. For e-retailers delivering in sparsely populated environments with stringent temporal constraints (grocery delivery), this work finds outsourcing alternatives (crowdsourced delivery, customer self-collection) to render low-cost distribution albeit with high emissions. As a result, the authors suggest the use of low-volume low-pollution vehicles from smaller consolidation facilities close to the market to provide expedited deliveries at fairly low costs and emissions. The analysis bolsters the case for the use of electric trucks for last-mile deliveries, as the study finds an electric truck fleet to not only eliminate tailpipe emissions but also to lower distribution costs compared to a diesel truck fleet. Thus, with this work the authors discuss the opportunities and challenges associated with different last-mile strategies for e-commerce delivery. © 2022 Elsevier Ltd","Collection-points; Continuous Approximation; Crowdsourcing; E-commerce; Last-mile delivery; Micro-hubs","comparative study; consolidation; crowdsourcing; diesel; electronic commerce",{"$nulls":6},"(2019); Akeb H., Moncef B., Durand B., Building a collaborative solution in dense urban city settings to enhance parcel delivery: An effective crowd model in Paris, Transportation Research Part E: Logistics and Transportation Review, 119, pp. 223-233, (2018); Ansari S., Basdere M., Li X., Ouyang Y., Smilowitz K., Advancements in continuous approximation models for logistics and transportation systems: 1996–2016, Transportation Research Part B: Methodological, 107, pp. 229-252, (2018); Arnold F., Cardenas I., Sorensen K., Dewulf W., Simulation of B2C e-commerce distribution in Antwerp using cargo bikes and delivery points, European Transport Research Review, 10, 1, (2017); Brown J.R., Guiffrida A.L., Carbon emissions comparison of last mile delivery versus customer pickup, International Journal of Logistics Research and Applications, 17, 6, pp. 503-521, (2014); Browne M., Allen J., Leonardi J., Evaluating the use of an urban consolidation centre and electric vehicles in central London, IATSS Research, 35, 1, pp. 1-6, (2011); Burke A., Miller M., (2020); (2018); (2016); (2017); Cavdar B., Sokol J., A distribution-free TSP tour length estimation model for random graphs, Eur. 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Res., 294, 3, pp. 1059-1077, (2021); Janjevic M., Ndiaye A., Investigating the theoretical cost-relationships of urban consolidation centres for their users, Transportation Research Part A: Policy and Practice, 102, pp. 98-118, (2017); Lasdon L.S., Waren A.D., Jain A., Ratner M., Design and testing of a generalized reduced gradient code for nonlinear programming, ACM Transactions on Mathematical Software (TOMS), 4, 1, pp. 34-50, (1978); Lemardele C., Estrada M., Pages L., Bachofner M., Potentialities of drones and ground autonomous delivery devices for last-mile logistics, Transportation Research Part E: Logistics and Transportation Review, 149, (2021); Lin J., Zhou W., Du L., Is on-demand same day package delivery service green?, Transportation Research Part D: Transport and Environment, 61, pp. 118-139, (2018); Marten A.L., Newbold S.C., Estimating the social cost of non-CO2 GHG emissions: Methane and nitrous oxide, Energy Policy, 51, pp. 957-972, (2012); Melo S., Baptista P., Costa A., Comparing the Use of Small Sized Electric Vehicles with Diesel Vans on City Logistics, Procedia - Social and Behavioral Sciences, 111, pp. 1265-1274, (2014); Moshref-Javadi M., Lee S., Winkenbach M., Design and evaluation of a multi-trip delivery model with truck and drones, Transportation Research Part E: Logistics and Transportation Review, 136, (2020); Nicholas M., (2019); Park H., Park D., Jeong I.-J., An effects analysis of logistics collaboration in last-mile networks for CEP delivery services, Transp. Policy, 50, pp. 115-125, (2016); Perboli G., Brotcorne L., Bruni M.E., Rosano M., A new model for Last-Mile Delivery and Satellite Depots management: The impact of the on-demand economy, Transportation Research Part E: Logistics and Transportation Review, 145, (2021); Pourrahmani E., Jaller M., Crowdshipping in Last Mile Deliveries: Operational Challenges and Research Opportunities, Socio-Economic Planning Sciences, 78, (2021); Stolaroff J.K., Samaras C., O'Neill E.R., Lubers A., Mitchell A.S., Ceperley D., Energy use and life cycle greenhouse gas emissions of drones for commercial package delivery, Nat. Commun., 9, 1, pp. 1-13, (2018); Tipagornwong C., Figliozzi M., Analysis of Competitiveness of Freight Tricycle Delivery Services in Urban Areas, Transportation Research Record: J. Transportation Research Board, 2410, 1, pp. 76-84, (2014); (2017); Census Bureau U.S., Estimated Quarterly U.S. Retail Sales (Adjusted), (2021); Alternative Fuels Data Center, Maps and Data - Vehicle Weight Classes & Categories, (2020); UPS U.P., (2016); Ups, UPS Pulse of the Online Shopper™, UPS., (2018); Wang Y., Zhang D., Liu Q., Shen F., Lee L.H., Towards enhancing the last-mile delivery: An effective crowd-tasking model with scalable solutions, Transportation Research Part E: Logistics and Transportation Review, 93, pp. 279-293, (2016); Wiese A., Toporowski W., Zielke S., Transport-related CO2 effects of online and brick-and-mortar shopping: A comparison and sensitivity analysis of clothing retailing, Transportation Research Part D: Transport Environment, 17, 6, pp. 473-477, (2012); Winkenbach M., Kleindorfer P.R., Spinler S., Enabling urban logistics services at La Poste through multi-echelon location-routing, Transportation Science, 50, 2, pp. 520-540, (2016)","A. Pahwa; Department of Civil and Environmental Engineering, University of California, Davis, One Shields Ave, 95616, United States; email: anmpahwa@ucdavis.edu",null,"Elsevier Ltd",{"$nulls":5},1.3665545E7,null,null,null,"English","Transp. Res. Part E Logist. Transp. Rev.","Article","Final",null,"Scopus","2-s2.0-85132699427"]
["Diaz R.; Phan C.; Golenbock D.; Sanford B.","Diaz, Rafael (16136670700); Phan, Canh (57729808900); Golenbock, Daniel (57729514400); Sanford, Benjamin (57729809000)","16136670700; 57729808900; 57729514400; 57729809000","A prescriptive framework to support express delivery supply chain expansions in highly urbanized environments",2022.0,"Industrial Management and Data Systems",122.0,7.0,null,1707.0,1737.0,30.0,3.0,"10.1108/IMDS-02-2022-0076","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85131450614&doi=10.1108%2fIMDS-02-2022-0076&partnerID=40&md5=57c2399222c034ac644e3e2f9521351f","VMASC, Old Dominion University, Norfolk, VA, United States; Viec.Co Corp, Ho Chi Minh, Viet Nam; Clariant Corp, Charlotte, NC, United States; Yak Mat, East Columbia, MS, United States","Diaz R., VMASC, Old Dominion University, Norfolk, VA, United States; Phan C., Viec.Co Corp, Ho Chi Minh, Viet Nam; Golenbock D., Clariant Corp, Charlotte, NC, United States; Sanford B., Yak Mat, East Columbia, MS, United States","Purpose: With the proliferation of e-commerce companies, express delivery companies must increasingly maintain the efficient expansion of their networks in accordance with growing demands and lower margins in a highly uncertain environment. This paper provides a framework for leveraging demand data to determine sustainable network expansion to fulfill the increasing needs of startups in the express delivery industry. Design/methodology/approach: While the literature points out several hub assignment methods, the authors propose an alternative spherical-clustering algorithm for densely urbanized population environments to strengthen the accuracy and robustness of current models. The authors complement this approach with straightforward mathematical optimization and simulation models to generate and test designs that effectively align environmentally sustainable solutions. Findings: To examine the effects of different degrees of demand variability, the authors analyzed this approach's performance by solving a real-world case study from an express delivery company's primary market. The authors structured a four-stage implementation framework to facilitate practitioners applying the proposed model. Originality/value: Previous investigations explored driving distances on a spherical surface for facility location. The work considers densely urbanized population and traffic data to simultaneously capture demand patterns and other road dynamics. The inclusion of different population densities and sustainability data in current models is lacking; this paper bridges this gap by posing a novel framework that increases the accuracy of spherical-clustering methods. © 2022, Emerald Publishing Limited.","Last-mile; Multi-period hub assignment optimization; Simulation; Spherical-clustering algorithms","Clustering algorithms; Population statistics; Spheres; Supply chains; Sustainable development; Current modeling; Delivery company; E- commerces; Growing demand; Last mile; Multi-period; Multi-period hub assignment optimization; Optimisations; Simulation; Spherical-clustering algorithm; Optimization",{"$nulls":4},"ODU-VMASC, (300770-010)","The authors would like to thank the subject matter experts and anonymous reviewers for their insightful guidance and suggestions. This research was supported in part by ODU-VMASC Internal Research and Development Project 300770-010: Exploring Additional Applications of Supply Chain Management, AI, and Cybersecurity.","Agatz N.A., Fleischmann M., Van Nunen J.A., E-fulfillment and multi-channel distribution–A review, European Journal of Operational Research, 187, 2, pp. 339-356, (2008); Alcacer J., Herman K., Intel: Strategic Decisions in Locating a New Assembly and Test Plant (A), pp. 713-406, (2012); Ballou R.H., Business Logistics/supply Chain Management: Planning, Organizing, and Controlling the Supply Chain, (2007); Bartke S., Schwarze R., No perfect tools: trade-offs of sustainability principles and user requirements in designing support tools for land-use decisions between greenfields and brownfields, Journal of Environmental Management, 153, pp. 11-24, (2015); Baykasoglu A., Subulan K., A multi-objective sustainable load planning model for intermodal transportation networks with a real-life application, Transportation Research Part E: Logistics and Transportation Review, 95, pp. 207-247, (2016); 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Springer Series in Supply Chain Management, (2017); Mattioli D., Amazon to expand shipments of nonessential items, continue adding staff, The Wall Street Journal, (2020); Melo M.T., Nickel S., Saldanha-Da-Gama F., Facility location and supply chain management–A review, European Journal of Operational Research, 196, 2, pp. 401-412, (2009); Mourad A., Puchinger J., Van Woensel T., Integrating autonomous delivery service into a passenger transportation system, International Journal of Production Research, 59, 7, pp. 2116-2139, (2021); Muller O., Junglas I., Brocke J.V., Debortoli S., Utilizing big data analytics for information systems research: challenges, promises and guidelines, European Journal of Information Systems, 25, 4, pp. 289-302, (2016); Murphy P., Wood D., Contemporary Logistics, (2008); Mwemezi J.J., Huang Y., Optimal facility location on spherical surfaces: algorithm and application, New York Science Journal, 4, 7, pp. 21-28, (2011); Olson P., Dummett B., Amazon gets go ahead for U.K. food-delivery investment, Thanks to Coronavirus, The Wallstreet Journal, (2020); Ozdamar L., Demir O., A hierarchical clustering and routing procedure for large scale disaster relief logistics planning, Transportation Research Part E: Logistics and Transportation Review, 48, 3, pp. 591-602, (2012); Pan F., Nagi R., Robust supply chain design under uncertain demand in agile manufacturing, Computers and Operations Research, 37, 4, pp. 668-683, (2010); Pan S., Zhang L., Thompson R.G., Ghaderi H., A parcel network flow approach for joint delivery networks using parcel lockers, International Journal of Production Research, 59, 7, pp. 2090-2115, (2020); Porter M.E., The five competitive forces that shape strategy, Harvard Business Review, 86, 1, pp. 25-40, (2008); Provost F., Fawcett T., Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking, (2013); Rezaee A., Dehghanian F., Fahimnia B., Beamon B., Green supply chain network design with stochastic demand and carbon price, Annals of Operations Research, 250, 2, pp. 463-485, (2017); Rizzo E., Pesce M., Pizzol L., Alexandrescu F.M., Giubilato E., Critto A., Marcomini A., Bartke S., Brownfield regeneration in Europe: identifying stakeholder perceptions, concerns, attitudes and information needs, Land Use Policy, 48, pp. 437-453, (2015); Sarkis J., Kouhizadeh M., Zhu Q.S., Digitalization and the greening of supply chains, Industrial Management and Data Systems, 121, 1, pp. 65-85, (2021); Schubert E., Sander J., Ester M., Kriegel H.P., Xu X., DBSCAN revisited, revisited: why and How you should (still) use DBSCAN, ACM Transactions on Database Systems (TODS), 42, 3, pp. 1-21, (2017); Shapiro J.F., Modeling the Supply Chain, (2001); Simon J.L., The Economics of Population Growth, (2019); Snyder L.V., Facility location under uncertainty: a review, IIE Transactions, 38, 7, pp. 547-564, (2006); Sterling G., COVID-consumers: pessimistic, but spending more online, (2020); Susmitha M.K., Impact of COVID 19 on E-commerce, Journal of Interdisciplinary Cycle Research, 12, 9, pp. 1161-1165, (2021); Valasis, Changes in consumer behavior and media consumption amid COVID-19, (2020); Valinsky J., Walmart just hired 150,000 workers. It's hiring 50,000 more as coronavirus continues”, CNN Business, (2020); Wang C., Chen S., A distributionally robust optimization for blood supply network considering disasters, Transportation Research Part E: Logistics and Transportation Review, 134, (2020); Yang L., Zhou X., Optimizing on-time arrival probability and percentile travel time for elementary path finding in time-dependent transportation networks: linear mixed integer programming reformulations, Transportation Research Part B: Methodological, 96, pp. 68-91, (2017); Zenk S.N., Lachance L.L., Schulz A.J., Mentz G., Kannan S., Ridella W., Neighborhood retail food environment and fruit and vegetable intake in a multiethnic urban population, American Journal of Health Promotion, 23, 4, pp. 255-264, (2009); Zetina C.A., Contreras I., Cordeau J.-F., Nikbakhsh E., Robust uncapacitated hub location, Transportation Research Part B: Methodological, 106, pp. 393-410, (2017); Zhalechian M., Tavakkoli-Moghaddam R., Zahiri B., Mohammadi M., Sustainable design of a closed-loop location-routing-inventory supply chain network under mixed uncertainty, Transportation Research Part E: Logistics and Transportation Review, 89, pp. 182-214, (2016); Zhang Y., Sun L., Hu X., Zhao C., Order consolidation for the last-mile split delivery in online retailing, Transportation Research Part E: Logistics and Transportation Review, 122, pp. 309-327, (2019); Zhao J., Huang L., Lee D.-H., Peng Q., Improved approaches to the network design problem in regional hazardous waste management systems, Transportation Research Part E: Logistics and Transportation Review, 88, pp. 52-75, (2016); Zokaee S., Jabbarzadeh A., Fahimnia B., Sadjadi S.J., Robust supply chain network design: an optimization model with real world application, Annals of Operations Research, 257, pp. 15-44, (2017)","R. Diaz; VMASC, Old Dominion University, Norfolk, United States; email: rdiaz@odu.edu",null,"Emerald Group Holdings Ltd.",{"$nulls":5},2635577.0,null,"IMDSD",null,"English","Ind Manage Data Sys","Article","Final",null,"Scopus","2-s2.0-85131450614"]
["Huang H.-L.; Chen Y.-Y.; Sun S.-C.","Huang, Hui-Ling (55738316000); Chen, Yue-Yang (57428078200); Sun, Shan-Ciao (57428185000)","55738316000; 57428078200; 57428185000","Conceptualizing the Internet Compulsive-Buying Tendency: What We Know and Need to Know in the Context of the COVID-19 Pandemic",2022.0,"Sustainability (Switzerland)",14.0,3.0,1549.0,null,null,null,5.0,"10.3390/su14031549","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85123517662&doi=10.3390%2fsu14031549&partnerID=40&md5=f06bb402fb38d95b0cbbd42d3bd2c995","Department of Business Administration, Chang Jung Christian University, Tainan City, 71101, Taiwan; Department of Business Administration, I-Shou University, Kaohsiung City, 84001, Taiwan","Huang H.-L., Department of Business Administration, Chang Jung Christian University, Tainan City, 71101, Taiwan; Chen Y.-Y., Department of Business Administration, I-Shou University, Kaohsiung City, 84001, Taiwan; Sun S.-C., Department of Business Administration, I-Shou University, Kaohsiung City, 84001, Taiwan","Over the past decade, new innovative products and services have been introduced into the marketplace using advanced technology. The enticement of new products lures consumers to buy compulsively. Because of the convenience and the characteristics of online shopping, it will increase the incidence of compulsive-buying behavior. Meanwhile, due to the fact that the COVID-19 pandemic is continuing to spread around the world, consumers may change their decision-mak-ing and behavior to shop online more frequently and intensively. The repetitive shopping online means more cardboard, delivery transportations, and vehicles and that more goods will be pro-duced. It will result in an unfriendly result for the environment. Given the critical role of compulsive buying in the emerging Internet retail environment, it is necessary to develop and validate an instrument to measure the Internet compulsive-buying tendency (ICBT). Therefore, a rigorous meas-urement-scale-development procedure was applied to evaluate the initial 31 items. After two rounds of data collection and assessment, the final instrument contained 18 items that fall into four subconstructs: the tendency to spend online, feelings about online shopping and spending, dys-functional online spending, and online post-purchase guilt. These factors can provide a basis for predicting tendencies toward Internet compulsive shopping and can be used to evaluate consumers’ abnormal behavior in online-shopping circumstances. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.","Internet compulsive buying; Internet compulsive-buying tendency (ICBT); Measurement-scale development","conceptual framework; COVID-19; decision making; Internet; retailing; shopping activity",{"$nulls":4},"Ministry of Science and Technology, Taiwan, MOST, (NSC100-2410-H-214-005-MY2)","Funding: This research was funded by the Ministry of Science and Technology (MOST), Taiwan (R.O.C.) under Contract No. NSC100-2410-H-214-005-MY2.","Chen L.D., Gillenson M.L., Sherrell D.L., Enticing online consumers: An extended technology acceptance perspective, Inf. Manag, 39, pp. 705-719, (2002); Liu Q., Zhang X., Huang S., Zhang L., Zhao Y., Exploring consumers’ buying behavior in a large online promotion activity: The role of psychological distance and involvement, J. Theor. Appl. Electron. Commer. 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Res, 13, pp. 477-491, (2013); Lim W.M., Editorial: History, lessons, and ways forward from the COVID-19 pandemic, Int. J. Qual. Innov, 5, pp. 101-108, (2021); Koch J., Frommeyer B., Schewe G., Online shopping motives during the COVID-19 pandemic-Lessons from the crisis, Sustain-ability, 12, (2020); Muangmee C., Kot S., Meekaewkunchorn N., Kassakorn N., Khalid B., Factors determining the behavioral intention of using food delivery apps during COVID-19 pandemics, J. Theor. Appl. Electron. Commer. Res, 16, pp. 1297-1310, (2021); Alaimo L.S., Fiore M., Galati A., How the Covid-19 Pandemic Is Changing Online Food Shopping Human Behaviour in Italy, Sustainability, 12, (2020); Harrel F.E., Lee K.L., A comparison of the discrimination of discriminant analysis and logistic regression under multivariate normality, Biostatistics: Statistics in Biomedical, Public Health and Environmental Sciences, pp. 333-343, (1985)","Y.-Y. Chen; Department of Business Administration, I-Shou University, Kaohsiung City, 84001, Taiwan; email: ray@isu.edu.tw",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85123517662"]
["Fonseca-Galindo J.C.; de Castro Surita G.; Neto J.M.; de Castro C.L.; Lemos A.P.","Fonseca-Galindo, Juan Camilo (57214693066); de Castro Surita, Gabriela (57221148565); Neto, José Maia (57215378286); de Castro, Cristiano Leite (25929885000); Lemos, André Paim (25638788000)","57214693066; 57221148565; 57215378286; 25929885000; 25638788000","A multi-agent system for solving the Dynamic Capacitated Vehicle Routing Problem with stochastic customers using trajectory data mining",2022.0,"Expert Systems with Applications",195.0,null,116602.0,null,null,null,4.0,"10.1016/j.eswa.2022.116602","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124583373&doi=10.1016%2fj.eswa.2022.116602&partnerID=40&md5=c0d3ef5d11f638f6c0f052d131e51198","Graduate Program in Electrical Engineering, Federal University of Minas Gerais, Av. Antônio Carlos 6627, Belo Horizonte, MG, 31270-901, Brazil; Graduate Program in Electrical Engineering, University of Campinas, Cidade Universitária Zeferino Vaz, Barão Geraldo, Campinas, SP, Brazil","Fonseca-Galindo J.C., Graduate Program in Electrical Engineering, Federal University of Minas Gerais, Av. Antônio Carlos 6627, Belo Horizonte, MG, 31270-901, Brazil; de Castro Surita G., Graduate Program in Electrical Engineering, University of Campinas, Cidade Universitária Zeferino Vaz, Barão Geraldo, Campinas, SP, Brazil; Neto J.M., Graduate Program in Electrical Engineering, Federal University of Minas Gerais, Av. Antônio Carlos 6627, Belo Horizonte, MG, 31270-901, Brazil; de Castro C.L., Graduate Program in Electrical Engineering, Federal University of Minas Gerais, Av. Antônio Carlos 6627, Belo Horizonte, MG, 31270-901, Brazil; Lemos A.P., Graduate Program in Electrical Engineering, Federal University of Minas Gerais, Av. Antônio Carlos 6627, Belo Horizonte, MG, 31270-901, Brazil","The worldwide growth of e-commerce has created new challenges for logistics companies, such as delivering products quickly and cheaply. This paper presents a heuristic to solve the last-mile route creation problem dynamically. The heuristic is based on a multi-agent system integrated with trajectory data mining techniques to extract territorial patterns and use them to solve the Dynamic Capacitated Vehicle Routing Problem with Stochastic Customers. Our solution approach is focused on a linear-time heuristic that depends only on the Warehouse system configurations and not on the total number of packages processed, which is suitable for express delivery logistics companies that must process a large number of packages per day. We compare our proposal with benchmark algorithms from the literature; additionally, we evaluate its performance and robustness under different scenarios. Results show that our solution approach is effective for scenarios in which routes must be set dynamically from a continuous stream of packages. © 2022","Big Data; Data mining; Dynamic Capacitated Vehicle Routing Problem with stochastic customers; E-commerce logistics; Multi-agent systems","Benchmarking; Big data; Electronic commerce; Multi agent systems; Sales; Stochastic systems; Vehicle routing; Vehicles; Capacitated vehicle routing problem; Data-mining techniques; Dynamic capacitated vehicle routing problem with stochastic customer; E- commerces; E-commerce logistic; Last mile; Logistics company; Solution approach; Stochastics; Trajectory data minings; Data mining",{"$nulls":4},"Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, CAPES","This work has been supported by the Brazilian agency CAPES .","Agarwal P.K., Fox K., Munagala K., Nath A., Pan J., Taylor E., Subtrajectory clustering: Models and algorithms, Proceedings of the 37th ACM SIGMOD-SIGACT-SIGAI symposium on principles of database systems, SIGMOD/PODS ’18, pp. 75-87, (2018); 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Fonseca-Galindo; Graduate Program in Electrical Engineering, Federal University of Minas Gerais, Belo Horizonte, MG, Av. Antônio Carlos 6627, 31270-901, Brazil; email: juankmilofg@ufmg.br",null,"Elsevier Ltd",{"$nulls":5},9574174.0,null,"ESAPE",null,"English","Expert Sys Appl","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85124583373"]
["Chen J.-F.; Wang L.; Wang S.; Wang X.; Ren H.","Chen, Jing-fang (57210165481); Wang, Ling (55312114400); Wang, Shengyao (52063958300); Wang, Xing (57219286531); Ren, Hao (57477519700)","57210165481; 55312114400; 52063958300; 57219286531; 57477519700","An effective matching algorithm with adaptive tie-breaking strategy for online food delivery problem",2022.0,"Complex and Intelligent Systems",8.0,1.0,null,107.0,128.0,21.0,11.0,"10.1007/s40747-021-00340-x","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85134004113&doi=10.1007%2fs40747-021-00340-x&partnerID=40&md5=07c21dc5f34d9b4d30e00d673a43569c","Department of Automation, Tsinghua University, Beijing, 100084, China; Meituan, Beijing, 100102, China","Chen J.-F., Department of Automation, Tsinghua University, Beijing, 100084, China; Wang L., Department of Automation, Tsinghua University, Beijing, 100084, China; Wang S., Meituan, Beijing, 100102, China; Wang X., Department of Automation, Tsinghua University, Beijing, 100084, China; Ren H., Meituan, Beijing, 100102, China","With the prosperity of e-commerce, ordering food online has become increasingly prevalent nowadays. Derived from the dispatching problem in Meituan, a real online food delivery (OFD) platform in China, this paper addresses an OFD problem (OFDP). To solve the OFDP efficiently, an effective matching algorithm with adaptive tie-breaking strategy (MAATS) is proposed by collaboratively fusing the optimization methods with machine learning (ML) techniques. First, to efficiently generate a partial solution with a certain quality, a best-matching heuristic is proposed. Second, to break the ties occurring in the best-matching heuristic and obtain a complete solution with high quality, multiple tie-breaking operators are designed. Third, to adapt to different scenarios, the tie-breaking operators are utilized in a dynamic way which is achieved by using ML methods including decision trees and a specially-designed deep neural network. Fourth, problem-specific features are extracted as decision information to assist the ML models to predict the best tie-breaking operator for use in the current scenario. Preliminary offline simulations are carried out on real historical data sets to validate the effectiveness of the proposed algorithm. Moreover, rigorous online A/B tests are conducted to evaluate the performance of MAATS in practical applications. The results of offline and online tests demonstrate both the effectiveness of MAATS to solve the OFDP and the application value to improve customer satisfaction and delivery efficiency on Meituan platform. © 2021, The Author(s).","Adaptive tie-breaking; Dispatching problem; Machine learning; Online food delivery; Problem-specific",{"$nulls":5},"National Natural Science Foundation of China, NSFC, (61873328); China National Funds for Distinguished Young Scientists, (61525304)","This study is supported by the National Science Fund for Distinguished Young Scholars of China (No. 61525304) and the National Natural Science Foundation of China (No. 61873328), and Meituan. 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Wolpert D.H., Macready W.G., No free lunch theorems for optimization, IEEE Trans Evol Comput, 1, pp. 67-82, (1997); Yeo V.C.S., Goh S.-K., Rezaei S., Consumer experiences, attitude and behavioral intention toward online food delivery (OFD) services, J Retail Consum Serv, 35, pp. 150-162, (2017); Yildiz B., Savelsbergh M., Provably high-quality solutions for the meal delivery routing problem, Transp Sci, 53, pp. 1372-1388, (2019); Yildiz H., Johnson M.P., Roehrig S., A genetic algorithm for the home-delivered meals location-routing problem, Heinz Coll Res, (2005); Yu H., Luo X., Wu T., Online pickup and delivery problem with constrained capacity to minimize latency, J Comb Optim, (2020); Zhang M.-L., Zhou Z.-H., A review on multi-label learning algorithms, IEEE Trans Knowl Data Eng, 26, pp. 1819-1837, (2014); Zheng H., Wang S., Cha Y., Et al., A two-stage fast heuristic for food delivery route planning problem, Informs Annual Meeting, (2019); Zheng J., Wang S., Wang L., Et al., A two-stage algorithm for fuzzy online order dispatching problem. I, (2020); Zhu Z., Xiao J., He S., Et al., A multi-objective memetic algorithm based on locality-sensitive hashing for one-to-many-to-one dynamic pickup-and-delivery problem, Inf Sci, 329, pp. 73-89, (2016)","L. Wang; Department of Automation, Tsinghua University, Beijing, 100084, China; email: wangling@tsinghua.edu.cn",null,"Springer International Publishing",{"$nulls":5},2.1994536E7,null,null,null,"English","Complex Intell. Syst.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85134004113"]
["Borghetti F.; Caballini C.; Carboni A.; Grossato G.; Maja R.; Barabino B.","Borghetti, Fabio (56085173800); Caballini, Claudia (32367453400); Carboni, Angela (57197522709); Grossato, Gaia (57460259000); Maja, Roberto (24332560300); Barabino, Benedetto (14038614700)","56085173800; 32367453400; 57197522709; 57460259000; 24332560300; 14038614700","The Use of Drones for Last-Mile Delivery: A Numerical Case Study in Milan, Italy",2022.0,"Sustainability (Switzerland)",14.0,3.0,1766.0,null,null,null,35.0,"10.3390/su14031766","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124939213&doi=10.3390%2fsu14031766&partnerID=40&md5=40cabbabed3617f51abf657c5ddc91f3","Mobility and Transport Laboratory, Design Department, Politecnico di Milano, Via Candiani 72, Milano, 20158, Italy; Department DIATI-Transport Systems, Politecnico di Torino, Corso Duca degli Abruzzi 24, Torino, 10129, Italy; Department of Civil Engineering, Architecture, Land, Environment and Mathematics (DICATAM), University of Brescia, Via Branze 43, Brescia, 25123, Italy","Borghetti F., Mobility and Transport Laboratory, Design Department, Politecnico di Milano, Via Candiani 72, Milano, 20158, Italy; Caballini C., Department DIATI-Transport Systems, Politecnico di Torino, Corso Duca degli Abruzzi 24, Torino, 10129, Italy; Carboni A., Department DIATI-Transport Systems, Politecnico di Torino, Corso Duca degli Abruzzi 24, Torino, 10129, Italy; Grossato G., Mobility and Transport Laboratory, Design Department, Politecnico di Milano, Via Candiani 72, Milano, 20158, Italy; Maja R., Mobility and Transport Laboratory, Design Department, Politecnico di Milano, Via Candiani 72, Milano, 20158, Italy; Barabino B., Department of Civil Engineering, Architecture, Land, Environment and Mathematics (DICATAM), University of Brescia, Via Branze 43, Brescia, 25123, Italy","The increasing use of e-commerce introduces major challenges for last-mile delivery, which is critical to ensure smooth functioning of supply chains. Besides the speed and cost of delivery, which are the most important factors for last-mile logistics, environmental and social sustainability factors are taking on an increasingly important role, especially in urban areas. In this perspective, last-mile delivery by drones could be a good choice both in terms of transport speed and sustainability. Being electrically powered, drones can reduce environmental impact; moreover, they enable the reduction of road congestion since they do not interfere with land infrastructures. The goal of this study is to analyse the viability of drones for last-mile delivery in the Italian city of Milan. A stated preference survey was carried out to assess end-user propensity towards drones. Using these results, a goods delivery service by drones was designed. Furthermore, a preliminary financial analysis was performed to evaluate the benefits for a company that would provide such a transport service. Findings show that last-mile delivery by drones can be successfully used to deliver small and light packages, reducing environmental and social impacts, and ensuring profits for the transport provider. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.","City logistics; Drones; Environmental sustainability; Last-mile delivery; Parcel delivery; Road congestion; Safety; Smart city; Social sustainability; Transportation planning; Urban logistics","Milan [Milano]; electrical power; electronic commerce; social impact; supply chain management; sustainability; traffic congestion",{"$nulls":6},"Rao C., Goh M., Zhao Y., Zheng J., Location selection of city logistics centers under sustainability, Transp. Res. Part D Transp. Environ, 36, pp. 29-44, (2015); Perboli G., Rosano M., Parcel delivery in urban areas: Opportunities and threats for the mix of traditional and green business models, Transp. Res. Part C Emerg. 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Inform, 40, pp. 27-40, (2019); Eissfeldt H., Vogelpohl V., Stolz M., Papenfuss A., Biella M., Belz J., Kugler D., The acceptance of civil drones in Germany, CEAS Aeronaut. J, 11, pp. 665-676, (2020); Osakwe C.N., Hudik M., Riha D., Stros M., Ramayah T., Critical factors characterizing consumers’ intentions to use drones for last-mile delivery: Does delivery risk matter?, J. Retail. Consum. Serv, 65, (2021); Benarbia T., Kyamakya K., A Literature Review of Drone-Based Package Delivery Logistics Systems and Their Implementation Feasibility, Sustainability, 14, (2021); Sudbury A.W., Hutchinson E.B., A Cost Analysis of Amazon Prime Air (Drone Delivery), J. Econ. Educ, 16, pp. 1-12, (2016)",null,null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85124939213"]
["Stofkova K.R.; Laitkep D.; Stofkova Z.","Stofkova, Katarina Repkova (56646475700); Laitkep, Dominik (57226767038); Stofkova, Zuzana (57003685100)","56646475700; 57226767038; 57003685100","Shopping Behavior in the Context of the Digital Economy",2022.0,"Journal of Risk and Financial Management",15.0,2.0,39.0,null,null,null,6.0,"10.3390/jrfm15020039","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85130490531&doi=10.3390%2fjrfm15020039&partnerID=40&md5=8d6b8ac433ee07f755744bd89f4c7343","Department of Communication, University of Zilina, Univerzitna 1, Zilina, 010 26, Slovakia; Department of Economy, University of Zilina, Univerzitna 1, Zilina, 010 26, Slovakia","Stofkova K.R., Department of Communication, University of Zilina, Univerzitna 1, Zilina, 010 26, Slovakia; Laitkep D., Department of Communication, University of Zilina, Univerzitna 1, Zilina, 010 26, Slovakia; Stofkova Z., Department of Economy, University of Zilina, Univerzitna 1, Zilina, 010 26, Slovakia","Consumers shop to meet their needs. When buying, they always compare and evaluate the available alternatives to the goods. The purchasing process involves various factors. These factors can also be described as attributes that can affect consumers during the purchasing process. Identifying important attributes can be really challenging for the digital economy and global markets. Most retailers do not have accurate knowledge of the attitudes and characteristics of their customers, which greatly affects purchasing processes. Combining accurate knowledge of the combination of attributes can increase revenue and improve retailers’ market position. The aim of this paper is to present the results of primary research, processed by reducing the number of attributes influencing purchasing behavior using factor analysis. The target group of the primary research was women who bought mostly online. The most important factors influencing women’s shopping behavior are traditional influences such as online payment for orders, diversity of delivery options, nicely crafted sites, and store reviews, but also the influences of social networks. Another important factor is the possibility of in-store purchases and payments for cash purchases. The results of this research will complement the view of women’s consumer behavior, thus creating the conditions for retailers to react to this target group. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.","consumers; e-commerce; purchasing behavior; social networks; women’s purchase intentions",{"$nulls":7},"Agus Anna Amalyah, Yudoko Gatot, Mulyono Nurbudi, Imaniya Taliya, E-Commerce Performance, Digital Marketing Capability and Supply Chain Capability within E-Commerce Platform: Longitudinal Study Before and After COVID-19, International Journal of Technology, 12, pp. 360-370, (2021); Taha Ali, Viktoria Tonino Pencarelli, Skerhakova Veronika, Fedorko Richard, Kosikova Martina, The Use of Social Media and Its Impact on Shopping Behavior of Slovak and Italian Consumers during COVID-19 Pandemic, Sustainability, 13, (2021); Alraja Mansour Naser, Kashoob Maryam Ali Said, Transformation to electronic purchasing: An empirical investigation, TELKOMNIKA (Telecommunication Computing Electronics and Control), 17, pp. 1209-1219, (2019); de Almeida Fabricio, Incerti Taynara, Leite Rodrigo Reis, Gomes Guilherme Ferreira, Ferreira Gomes Jose Henrique, Paiva Anderson Paulo, Balestrassi Pedro Paulo, A multivariate GR&R approach to variability evaluation of measuring instruments in resistance spot welding process, Journal of Manufacturing Processes, 36, pp. 465-479, (2018); Aslam Farhan, Aimin Wang, Li Mingze, Rehman Khaliq Ur, Innovation in the Era of IoT and Industry 5.0: Absolute Innovation Management (AIM) Framework, Information, 11, (2020); Barnett Tim, Pearson Allison W., Pearson Rodney, Kellermanns Franz W., Five-factor model personality traits as predictors of perceived and actual usage of technology, European Journal of Information Systems, 24, pp. 374-390, (2015); Bro Rasmus, Kier Henk A. L., A new efficient method for determining the number of components in PARAFAC models, Journal of Chemometrics, 17, pp. 274-286, (2003); Bucko Jozef, Kakalejcik Lukas, Ferencova Martina, Online shopping: Factors that affect consumer purchasing behavior, Cogent Business & Management, 5, (2018); Civelek Mehmet, Gajdka Krzysztof, Svetlik Jaroslav, Vavrecka Vladimir, Differences in the usage of online marketing and social media tools: Evidence from Czech, Slovakian and Hungarian SMEs, Equilibrium. Quarterly Journal of Economics and Economic Policy, 15, pp. 537-563, (2020); Dempsey Nicola, Bramley Glen, Power Sinead, Brown Caroline, The social dimension of sustainable development: Defining urban social sustainability, Sustainable Development, 19, pp. 289-300, (2011); Drugau-Constantin Andrea, Is Consumer Cognition Reducible to Neurophysiological Functioning?, Economics, Management, and Financial Markets, 14, pp. 9-14, (2019); Duncan Jennifer L., Josiam Bharath M., Kim Young Hoon, Kalldin Alexandria C., Using factor-cluster analysis to segment patrons of casual dining establishments in the United States, British Food Journal, 117, pp. 1377-1398, (2015); Fu Hanliang, Manogaran Gunasekaran, Wu Kuang, Cao Ming, Jiang Song, Yang Aimin, Intelligent decision-making of online shopping behavior based on internet of things, International Journal of Information Management, 50, pp. 515-525, (2020); Gburova Jaroslava, Fedorko Richard, Online shops and online shopping from the point of view of the Slovak consumer, the 36th International Scientific Conference on Economic and Social Development—Building Resilient Society, pp. 134-140, (2018); Ghobakhloo Morteza, Industry 4.0, digitization, and opportunities for sustainability, Journal of Cleaner Production, 252, (2020); Giao Ha Nam Khanh, Customer Satisfaction at Tiki. vn E-Commerce Platform, Journal of Asian Finance, Economics, and Business, 7, pp. 173-183, (2020); Graessley Scott, Horak Jakub, Kovacova Maria, Valaskova Katarina, Poliak Milos, Consumer Attitudes and Behaviors in the Technology-Driven Sharing Economy: Motivations for Participating in Collaborative Consumption, Journal of Self-Governance and Management Economics, 7, pp. 25-30, (2019); Hennessy Brittany, Influencer: Building Your Personal Brand in the Age of Social Media, pp. 18-19, (2018); Slovaks Set a New Record on E-Shops—They Spent 1.36 Billion Euros, (2019); Hollowell Jane Catherine, Rowland Zuzana, Kliestik Tomas, Kliestikova Jana, Dengov Victor V., Customer Loyalty in the Sharing Economy Platforms: How Digital Personal Reputation and Feedback Systems Facilitate Interaction and Trust between Strangers, Journal of Self-Governance and Management Economics, 7, pp. 13-18, (2019); Hoyer Wayne D., Macinnis Deborah J., Consumer Behavior, (2009); Hu Litze, Bentler Peter M., Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives, Structural Equation Modeling, 6, pp. 1-55, (2009); Jabbour Charbel J. Chiappetta, de Sousa Jabbour Ana Beatriz Lopes, Sarkis Joseph, Filho Moacir Godinho, Unlocking the circular economy through new business models based on large-scale data: An integrative framework and research agenda, Technological Forecasting and Social Change, 144, pp. 546-552, (2019); Jankalova Miriam, Kurotova Jana, Sustainability Assessment Using Economic Value Added, Sustainability, 12, (2020); Jeon Hyeon Gyu, Kim Cheong, Lee Jungwoo, Lee Kun Chang, Understanding E-Commerce Consumers’ Repeat Purchase Intention: The Role of Trust Transfer and the Moderating Effect of Neuroticism, Frontiers in Psychology, 12, (2021); Consumer Trends Report Q4 2021, (2021); Kakalejcik Lukas, Bucko Jozef, Mobile Shopers: Ako Nakupujú Majitelia Smartfónov. [Mobile Shopers: How Smartphone Owners Shop], (2018); Lim Yi Jin, Osman Abdullah, Salahuddin Shahrul Nizam, Romle Abdul Rahim, Abdullah Safizal, Factors influencing online shopping behavior: The mediating role of purchase intention, the 7th International Economics & Business Management Conference (IEBMC 2015), (2016); Meilhan Deborah, Customer Value Co-Creation Behavior in the Online Platform Economy, Journal of Self-Governance and Management Economics, 7, pp. 19-24, (2019); The Behavioral Economics of Decision Making: Explaining Consumer Choice in Terms of Neural Events, Economics, Management, and Financial Markets, 14, pp. 16-20, (2019); Misik Tomas, Stofkova Jana, Stalmasekova Natalia, Survey of increasing digital skills of university students, the 11th Annual International Conference of Education, Research and Innovation, pp. 3949-3956, (2018); Online Shoping: Fashion First, (2018); OECD Economic Outlook, 2021, 2, (2021); Pollak Frantisek, Konecny Michal, Sceulovs Deniss, Innovations in the Management of E-Commerce: Analysis of Customer Interactions during the COVID-19 Pandemic, Sustainability, 13, (2021); Polman Evan, Wu Kaiyang, Decision making for others involving risk: A review and meta-analysis, Journal of Economic Psychology, 77, (2020); Popescu Gheorghe H., Ciurlau Florin Cristian, Making Decisions in Collaborative Consumption: Digital Trust and Reputation Systems in the Sharing Economy, Journal of Self-Governance and Management Economics, 7, pp. 7-12, (2019); Slovak E-Commerce Is Not Slowing Down, (2021); Soltes Viktor, Stofko Stanislav, Selected aspects of quality of life during the process of globalization, pp. 2439-2446, (2017); Stefko Robert, Bacik Radovan, Fedorko Richard, Olearova Maria, Rigelsky Martin, Analysis of consumer preferences related to the use of digital devices in the e-commerce dimension, Entrepreneurship and Sustainability, 7, pp. 25-33, (2019); Taher Al-Lami Ghadi, E-Commerce: Advantages and Limitations, International Journal of Academic Research in Accounting Finance and Management Sciences, 11, pp. 153-165, (2021); Tutz Gerhard, Hierarchical models for the analysis of Likert scales in regression and item response analysis, International Statistical Review, 89, pp. 18-35, (2021); Valaskova Katarina, Durana Pavol, Adamko Peter, Changes in Consumers’ Purchase Patterns as a Consequence of the COVID-19 Pandemic, Mathematics, 9, (2021); Vijayasarathy Leo R., Predicting consumer intentions to use on-line shopping: The case for an augmented technology acceptance model, Information & Management, 41, pp. 747-762, (2004); Work Programme on Electronic Commerce, (1998); Zafar Muhammad Wasif, Saud Shah, Hou Fujun, The impact of globalization and financial development on environmental quality: Evidence from selected countries in the Organization for Economic Co-operation and Development (OECD), Environmental Science and Pollution Research, 26, pp. 13246-13262, (2019)","K.R. Stofkova; Department of Communication, University of Zilina, Zilina, Univerzitna 1, 010 26, Slovakia; email: katarina.stofkova@fpedas.uniza.sk",null,"MDPI",{"$nulls":5},1.9118074E7,null,null,null,"English","J. Risk. Financ. Manag.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85130490531"]
["Jharni K.; Hlyal M.; El Alami J.","Jharni, Khalil (57217197067); Hlyal, Mustapha (56523339000); El Alami, Jamila (55987066300)","57217197067; 56523339000; 55987066300","PHYSICAL INTERNET: A REVIEW OF MATHEMATICAL PROGRAMMING MODELS",2022.0,"Journal of Theoretical and Applied Information Technology",100.0,4.0,null,1071.0,1089.0,18.0,2.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85126146902&partnerID=40&md5=a583c28484efb2e82f8ee51bd2c65093","LASTIMI Laboratory, High School of Technology in Sale, Mohammed V University, Rabat, Morocco; CELOG, Superior School of Textile and Clothing, Casablanca, Morocco","Jharni K., LASTIMI Laboratory, High School of Technology in Sale, Mohammed V University, Rabat, Morocco; Hlyal M., CELOG, Superior School of Textile and Clothing, Casablanca, Morocco; El Alami J., LASTIMI Laboratory, High School of Technology in Sale, Mohammed V University, Rabat, Morocco","The development of digital technology has facilitated the growth of e-commerce and the recent pandemic has changed the purchasing process and strongly impacted supply chains. These must adapt in order to keep their performance level. As a response to this challenge, the concept of the Physical Internet, which is based on the Digital Internet, looks promising. Hence, we can take advantage of advances in information technology to develop the Physical Internet and to accelerate its implementation. In this paper, we propose a review of the Physical Internet literature based on mathematical programming to answer the following questions: (1) what is the coverage of nodes and links in a supply chain by the current literature on the Physical Internet? (2) What mathematical programming models and formulations are used for modeling and optimizing the problems of supply chains in the context of the Physical Internet? (3) How are sustainability aspects addressed by the proposed models? Following the qualitative content analysis method, we worked in detail on 60 publications up to 2022. We studied them through three categories and presented the quantitative and qualitative results. These findings led us to propose our perception of the supply chain in the context of the physical Internet and in particular the issues of considering a supply network instead of a supply chain. Finally, we raised questions and proposed research opportunities before concluding.  © 2022 Little Lion Scientific.","Literature Review; Logistics; Mathematical Programming; Physical Internet; Supply Chain",{"$nulls":7},"Montreuil B., Toward a Physical Internet: Meeting the global logistics sustainability grand challenge, Logist. Res, 3, 2-3, pp. 71-87, (2011); Hakimi D., Et al., Simulating a physical internet enabled mobility web: The case of mass distribution in France, 9th Int. Conf. Model. Optim. SIMulation-MOSIM'12, (2012); Jharni K., Hlyal M., El Alami J., Physical Internet: Literature review and research opportunities, IOP Conf. Ser. Mater. Sci. Eng, 827, 1, (2020); The physical internet, Economist, (2006); Treiblmaier H., Mirkovski K., Lowry P. B., Conceptualizing the Physical Internet: Literature Review, Implications and Directions for Future Research, (2016); Pan S., Ballot E., Huang G. Q., Montreuil B., Physical Internet and interconnected logistics services: Research and applications, International Journal of Production Research, (2017); Montreuil B., Meller R. D., Ballot E., Physical Internet Foundations, IFAC Proc. Vol, 45, 6, pp. 26-30, (2012); Ballot E., Gobet O., Montreuil B., Physical internet enabled open hub network design for distributed networked operations, (2012); feng Ji S., shuai Peng X., juan Luo R., An integrated model for the productioninventory-distribution problem in the Physical Internet, Int. J. Prod. Res, (2019); shuai Peng X., feng Ji S., ting Ji T., Promoting sustainability of the integrated production-inventory-distribution system through the Physical Internet, Int. J. Prod. Res, (2019); Nouiri M., Bekrar A., Trentesaux D., An energy-efficient scheduling and rescheduling method for production and logistics systems, Int. J. Prod. Res, (2019); Di Febbraro A., Giglio D., Sacco N., On Exploiting Ride-Sharing and Crowd-Shipping Schemes within the Physical Internet Framework, (2018); Ben Mohamed I., Klibi W., Labarthe O., Deschamps J. C., Babai M. Z., Modelling and solution approaches for the interconnected city logistics, Int. J. Prod. Res, (2017); Yao J., Optimisation of one-stop delivery scheduling in online shopping based on the physical Internet, Int. J. Prod. Res, (2017); Chen C., Pan S., Wang Z., Zhong R. Y., Using taxis to collect citywide E-commerce reverse flows: A crowdsourcing solution, Int. J. Prod. Res, (2017); Forrester J. W., Industrial dynamics, (1961); Towill D. R., The seamless supply chain -The predator's strategic advantage, Int. J. Technol. Manag, 13, 1, (1997); Melo M. 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G., Gendreau M., Jemai L., Planning hyperconnected, urban logistics systems, (2020); Shi Y., Chen M., Qu T., Liu W., Cai Y., Digital connectivity in an innovative joint distribution system with real-time demand update, Comput. Ind, 123; Faugere L., White C., Montreuil B., Mobile access hub deployment for urban parcel logistics, Sustain, 12, 17, (2020); Peng X., Ji S., Thompson R. G., Zhang L., Resilience planning for Physical Internet enabled hyperconnected production-inventory-distribution systems, Comput. Ind. Eng, 158; Lai M., Cai X., Less-than-truckload shipper collaboration in the physical internet, (2020); Hu Z., Askin R. G., Hu G., Hub relay network design for daily driver routes, Int. J. Prod. Res, (2019); Herrmann E., Kunze O., Facility Location Problems in City Crowd Logistics, (2019); Habibi M. K. K., Allaoui H., Goncalves G., Collaborative hub location problem under cost uncertainty, Comput. Ind. 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Rev, 12, 1, (2020); Puskas E., Bohacs G., CONCEPTUAL FRAMEWORK FOR HEAVY-DUTY VEHICLE PLATOONING IN PHYSICAL INTERNET SYSTEMS; Chargui T., Bekrar A., Reghioui M., Trentesaux D., A simulation-optimization approach for two-way scheduling/grouping in a road-rail physical internet hub, IFACPapersOnLine, (2019); Zhong R. Y., Xu C., A job-shop scheduling model with real-time feedback for physical internet-based manufacturing shopfloor, (2016); Kong X. T. R., Chen J., Luo H., Huang G. Q., Scheduling at an auction logistics centre with physical internet, Int. J. Prod. Res, (2016); Guo D., Et al., Synchroperation in industry 4.0 manufacturing, Int. J. Prod. Econ, 238; Chargui T., Bekrar A., Reghioui M., Trentesaux D., Proposal of a multi-agent model for the sustainable truck scheduling and containers grouping problem in a Road-Rail physical internet hub, Int. J. Prod. Res, (2019); Park J. 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J, 7, 3, (2011); Qiao B., Pan S., Ballot E., Revenue optimization for less-than-truckload carriers in the Physical Internet: Dynamic pricing and request selection, Comput. Ind. Eng, (2018); Lafkihi M., Pan S., Ballot E., The price of anarchy for centralising or decentralising freight transport organisation through serious gaming, IFAC-PapersOnLine, (2019); Lafkihi M., Pan S., Ballot E., Rulebased incentive mechanism design for a decentralised collaborative transport network, Int. J. Prod. Res, (2019); Fatnassi E., Klibi W., Deschamps J. C., Labarthe O., Exploring mobility networks inter-connectivity for an on-demand transshipment of goods in urban areas, (2016); Sternberg H. S., Denizel M., Toward the Physical Internet-Logistics Service Modularity and Design Implications, Journal of Business Logistics, 42, 1, (2021)",null,null,"Little Lion Scientific",{"$nulls":5},1.9928645E7,null,null,null,"English","J. Theor. Appl. Inf. Technol.","Article","Final",null,"Scopus","2-s2.0-85126146902"]
["Din A.U.; Han H.; Ariza-Montes A.; Vega-Muñoz A.; Raposo A.; Mohapatra S.","Din, Ashraf Ud (57486872200); Han, Heesup (21233360400); Ariza-Montes, Antonio (57217331422); Vega-Muñoz, Alejandro (57210374490); Raposo, António (55257860600); Mohapatra, Shruti (57214844501)","57486872200; 21233360400; 57217331422; 57210374490; 55257860600; 57214844501","The Impact of COVID-19 on the Food Supply Chain and the Role of E-Commerce for Food Purchasing",2022.0,"Sustainability (Switzerland)",14.0,5.0,3074.0,null,null,null,31.0,"10.3390/su14053074","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85126271155&doi=10.3390%2fsu14053074&partnerID=40&md5=e9f0af04f57aab2a7b4de68cbc11af73","School of Transportation and Logistics, Southwest Jiaotong University, Chengdu, 610031, China; College of Hospitality and Tourism Management, Sejong University, 98 Gunja-Dong, Gwanjin-Gu, Seoul, 143-747, South Korea; Social Matters Research Group, Universidad Loyola Andalucía, Escritor Castilla Aguayo 4, Córdoba, 14004, Spain; Public Policy Observatory, Universidad Autónoma de Chile, 425 Pedro de Valdivia Avenue, Santiago, Providencia, 7500912, Chile; CBIOS (Research Center for Biosciences and Health Technologies), Universidade Lusófona de Humanidades e Tecnologias, Campo Grande 376, Lisboa, 1749-024, Portugal; Faculty of Agriculture, Sri Sri University, Bidyadharpur Arilo, Odisha, Cuttack, 754006, India","Din A.U., School of Transportation and Logistics, Southwest Jiaotong University, Chengdu, 610031, China; Han H., College of Hospitality and Tourism Management, Sejong University, 98 Gunja-Dong, Gwanjin-Gu, Seoul, 143-747, South Korea; Ariza-Montes A., Social Matters Research Group, Universidad Loyola Andalucía, Escritor Castilla Aguayo 4, Córdoba, 14004, Spain; Vega-Muñoz A., Public Policy Observatory, Universidad Autónoma de Chile, 425 Pedro de Valdivia Avenue, Santiago, Providencia, 7500912, Chile; Raposo A., CBIOS (Research Center for Biosciences and Health Technologies), Universidade Lusófona de Humanidades e Tecnologias, Campo Grande 376, Lisboa, 1749-024, Portugal; Mohapatra S., Faculty of Agriculture, Sri Sri University, Bidyadharpur Arilo, Odisha, Cuttack, 754006, India","The world has been plagued by an unforeseen threat to public health by the appearance of COVID-19, which has impacted the world’s economy and the worldwide supply chain. The unexpected pandemic (COVID-19) quickly spread across the world, leaving not a single country unaffected by the worldwide pandemic. At the start of COVID-19, several countries adopted social distancing and lockdowns due to the virus. The existing pandemic’s discriminatory aspect has a negative influence on human health and the standard of living, as well as worldwide trade, supply chains, and major economies. COVID-19 has been shown to have an effect throughout the broader food supply chain, one of the largest significant sectors of any country, from the field to the consumers. There are currently substantial concerns regarding food production, manufacturing, delivery, and consumption in light of emerging issues within the food supply chain. Limitations on the mobility of workers, variations in consumer demands, the shutdown of food manufacturing industries, limited food trading regulations, and financial stress throughout the food supply chain are all results of the COVID-19 pandemic. The pandemic (COVID-19) has changed consumer behavior and affected the business and economic sector. The purpose of this study was to explore the application of the Q-technique in the investigation of online consumer and manufacturer behavior in relation to end-user food purchases via digital marketing skills, supply chain possibilities, food purchaser and consumer happiness, and e-commerce infrastructure efficiency under the influence of COVID-19. The results show that in the crisis of supply chain management, clarifying the import food industry e-commerce supply chain crisis items, and determining their priority and strength can help enterprises make emergency decisions regarding supply chain operation; they can also be used as a reference for enterprises to use in responding to the crisis. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.","COVID-19; E-commerce; Food purchasing; Supply chain","COVID-19; electronic commerce; food supply; public health",{"$nulls":6},"Agarwal K.M., Mohapatra S., Sharma P., Sharma S., Bhatia D., Mishra A., Study and overview of the novel corona virus disease (COVID-19), Sensors Int, 1, (2020); Agrahari R., Mohanty S., Vishwakarma K., Nayak S.K., Samantaray D., Mohapatra S., Update vision on COVID-19: Structure, immune pathogenesis, treatment and safety assessment, Sensors Int, 2, (2021); Andersen K.G., Rambaut A., Lipkin W.I., Holmes E.C., Garry R.F., The proximal origin of SARS-CoV-2, Nat. Med, 26, pp. 450-452, (2020); Behloul N., Baha S., Shi R., Meng J., Role of the GTNGTKR motif in the N-terminal receptor-binding domain of the SARS-CoV-2 spike protein, Virus Res, 286, (2020); Helm D., The Environmental Impacts of the Coronavirus, Environ. Resour. Econ, 76, pp. 21-38, (2020); Hu B., Guo H., Zhou P., Shi Z.-L., Characteristics of SARS-CoV-2 and COVID-19, Nat. Rev. Microbiol, 19, pp. 141-154, (2021); Johnson M.C., Lyddon T.D., Suarez R., Salcedo B., LePique M., Graham M., Ricana C., Robinson C., Ritter D.G., Optimized Pseudotyping Conditions for the SARS-COV-2 Spike Glycoprotein, J. Virol, 94, pp. e01062-20, (2020); Lvov D.K., Alkhovsky S.V., Source of the COVID-19 pandemic: Ecology and genetics of coronaviruses (Betacoronavirus: Coronaviridae) SARS-CoV, SARS-CoV-2 (subgenus Sarbecovirus), and MERS-CoV (subgenus Merbecovirus), Vopr. Virusol, 65, pp. 62-70, (2020); Ma Q., Chang C.-C., Lin C.-T., Detecting the Crisis of Supply Chain Management on E-Commerce for Sustainability Using Q-Technique, Sustainability, 13, (2021); Mohapatra S., Priyanka V., Mohapatra S., Kohli I., Mishra R.K., Impact of corona virus covid-19 on the global economy, Int. J. Agric. Stat. Sci, 16, pp. 771-778, (2020); Mohapatra S., Mishra Y., Dash L., COVID-19: Analysing the Legal Nuances of the Lockdown Order, Indian J. Forensic Med. Toxicol, 14, pp. 612-616, (2020); Rosenbloom D., Markard J., A COVID-19 recovery for climate, Science, 368, (2020); Rugani B., Caro D., Impact of COVID-19 outbreak measures of lockdown on the Italian Carbon Footprint, Sci. Total Environ, 737, (2020); Singhal T., A Review of Coronavirus Disease-2019 (COVID-19), Indian J. Pediatr, 87, pp. 281-286, (2020); COVID-19 and Smallholder Producers’ Access to Markets, (2020); Tan H.W., Xu Y., Lau A.T.Y., Angiotensin-converting enzyme 2: The old door for new severe acute respiratory syndrome coronavirus 2 infection, Rev. Med. Virol, 30, (2020); University J.H., COVID-19 Dashboard by the Center for Systems Science and Engineering (CSSE); Sharma S.K., Mohapatra S., Sharma R.C., Alturjman S., Altrjman C., Mostarda L., Stephan T., Retrofitting Existing Buildings to Improve Energy Performance, Sustainability, 14, (2022); Sharma S.K., Sharma R.C., Lee J., Effect of Rail Vehicle–Track Coupled Dynamics on Fatigue Failure of Coil Spring in a Suspension System, Appl. Sci, 11, (2021); Sharma S.K., Sharma R.C., Lee J., In situ and experimental analysis of longitudinal load on carbody fatigue life using nonlinear damage accumulation, Int. J. Damage Mech, (2021); Bhardawaj S., Sharma R., Sharma S., Ride Analysis of Track-Vehicle-Human Body Interaction Subjected to Random Excitation, J. Chin. Soc. Mech. Eng, 41, pp. 229-238, (2020); Bhardawaj S., Sharma R.C., Sharma S.K., Development of multibody dynamical using MR damper based semi-active bio-inspired chaotic fruit fly and fuzzy logic hybrid suspension control for rail vehicle system, Proc. Inst. Mech. Eng. Part K J. Multi-Body Dyn, 234, pp. 723-744, (2020); Sharma S.K., Lee J., Design and Development of Smart Semi Active Suspension for Nonlinear Rail Vehicle Vibration Reduction, Int. J. Struct. Stab. Dyn, 20, (2020); Lin Y., Marjerison R.K., Choi J., Chae C., Supply Chain Sustainability during COVID-19: Last Mile Food Delivery in China, Sustainability, 14, (2022); Wang S., Assessing the Food Safety and Quality Assurance System during the COVID-19 Pandemic, Sustainability, 14, (2022); Tort O.O., Vayvay O., Cobanoglu E., A Systematic Review of Sustainable Fresh Fruit and Vegetable Supply Chains, Sustainability, 14, (2022); Hyland J.J., Macken-Walsh A., Multi-Actor Social Networks: A Social Practice Approach to Understanding Food Hubs, Sustain-ability, 14, (2022)","A.U. Din; School of Transportation and Logistics, Southwest Jiaotong University, Chengdu, 610031, China; email: ashrafiawazir88@yahoo.com; H. Han; College of Hospitality and Tourism Management, Sejong University, Seoul, 98 Gunja-Dong, Gwanjin-Gu, 143-747, South Korea; email: heesup.han@gmail.com",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85126271155"]
["Fatehi S.; Wagner M.R.","Fatehi, Soraya (57200122333); Wagner, Michael R. (57190670516)","57200122333; 57190670516","Crowdsourcing Last-Mile Deliveries",2022.0,"Manufacturing and Service Operations Management",24.0,2.0,null,791.0,809.0,18.0,12.0,"10.1287/msom.2021.0973","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85132216602&doi=10.1287%2fmsom.2021.0973&partnerID=40&md5=b0471f75a975a8a4e3c38b41f41e2826","Naveen Jindal School of Management, University of Texas at Dallas, Richardson, 75080, TX, United States; Michael G. Foster School of Business, University of Washington, Seattle, 98195, WA, United States; Amazon.com, Seattle, 98109, WA, United States","Fatehi S., Naveen Jindal School of Management, University of Texas at Dallas, Richardson, 75080, TX, United States; Wagner M.R., Michael G. Foster School of Business, University of Washington, Seattle, 98195, WA, United States, Amazon.com, Seattle, 98109, WA, United States","Problem definition: Because of the emergence and development of e-commerce, customers demand faster and cheaper delivery services. However, many retailers find it challenging to efficiently provide fast and on-time delivery services to their customers. Academic/practical relevance: Amazon and Walmart are among the retailers that are relying on independent crowd drivers to cope with on-demand delivery expectations. Methodology: We propose a novel robust crowdsourcing optimization model to study labor planning and pricing for crowdsourced last-mile delivery systems that are utilized for satisfying on-demand orders with guaranteed delivery time windows. We develop our model by combining crowdsourcing, robust queueing, and robust routing theories. We show the value of the robust optimization approach by analytically studying how to provide fast and guaranteed delivery services utilizing independent crowd drivers under uncertainties in customer demands, crowd availability, service times, and traffic patterns; we also allow for trend and seasonality in these uncertainties. Results: For a given delivery time window and an on-time delivery guarantee level, our model allows us to analytically derive the optimal delivery assignments to available independent crowd drivers and their optimal hourly wage. Our results show that crowdsourcing can help firms decrease their delivery costs significantly while keeping the promise of on-time delivery to their customers. Managerial implications: We provide extensive managerial insights and guidelines for how such a system should be implemented in practice. © 2021 INFORMS","crowdsourcing; on-demand deliveries; queueing theory; robust optimization","Managers; Optimization; Queueing theory; Sales; Customer demands; Delivery service; Delivery time windows; Guaranteed delivery; Last mile; On demands; On-demand delivery; On-time delivery; Robust optimization; Uncertainty; Crowdsourcing",{"$nulls":6},"Flex Amazon, What is Amazon Flex?, (2019); All Amazon flex warehouse & delivery locations, (2018); Arslan AM, Agatz N, Kroon LG, Zuidwijk R, Crowdsourced delivery: A dynamic pickup and delivery problem with ad-hoc drivers, Transportation Sci, 53, 1, pp. 222-235, (2019); Asdecker B, Zirkelbach F, What drives the drivers? A qualitative perspective on what motivates the crowd delivery workforce, Proc. 53rd Hawaii Internat. Conf. System Sci, pp. 4011-4020, (2020); Bai J, So KC, Tang CS, Chen X, Wang H, Coordinating supply and demand on an on-demand service platform with impatient customers, Manufacturing Service Oper. Management, 21, 3, pp. 556-570, (2019); Bandi C, Bertsimas D, Youssef N, Robust queueing theory, Oper. Res, 63, 3, pp. 676-700, (2015); Bandi C, Bertsimas D, Youssef N, Robust transient analysis of multi-server queueing systems and feed-forward networks, Queueing Systems, 89, 3, pp. 351-413, (2018); Bandi C, Trichakis N, Vayanos P, Robust multiclass queuing theory for wait time estimation in resource allocation systems, Management Sci, 65, 1, pp. 152-187, (2019); Bearwood J, Halton JH, Hammersley JM, The shortest path through many points, Math. Proc. Cambridge Philos. Soc, 55, 4, pp. 299-327, (1959); Benjaafar S, Ding JY, Kong G, Taylor T, Labor welfare in on-demand service platforms, (2018); Benjaafar S, Kong G, Li X, Courcoubetis C, Peer-to-peer product sharing: Implications for ownership, usage, and social welfare in the sharing economy, Management Sci, 65, 2, pp. 477-493, (2019); Ben-Tal A, El Ghaoui L, Nemirovski A, Robust Optimization, (2009); Bertsimas DJ, Van Ryzin G, Stochastic and dynamic vehicle routing in the Euclidean plane with multiple capacitated vehicles, Oper. Res, 41, 1, pp. 60-76, (1993); Cachon GP, Retail store density and the cost of greenhouse gas emissions, Management Sci, 60, 8, pp. 1907-1925, (2014); Cachon GP, Daniels KM, Lobel R, The role of surge pricing on a service platform with self-scheduling capacity, Manufacturing Service Oper. Management, 19, 3, pp. 368-384, (2017); Cao J, Olvera-Cravioto M, Shen ZJM, Last-mile shared delivery: A discrete sequential packing approach, (2018); Carlsson JG, Delage E, Robust partitioning for stochastic multivehicle routing, Oper. Res, 61, 3, pp. 727-744, (2013); Clarke G, Wright JW, Scheduling of vehicles from a central depot to a number of delivery points, Oper. Res, 12, 4, pp. 568-581, (1964); Cook C, Diamond R, Hall J, List JA, Oyer P, The gender earnings gap in the gig economy: Evidence from over a million rideshare drivers, (2018); Croes GA, A method for solving traveling salesman problems, Oper. Res, 6, 6, pp. 791-812, (1958); Dong J, Ibrahim R, Flexible workers or full-time employees? on staffing systems with a blended workforce, Oper. Res, 68, 4, pp. 1238-1264, (2020); Ducklow L, Amazon flex—how many packages are in a shift?, (2016); Increase your savings with FedEx, (2019); FedEx SameDay city economy, (2016); FedEx SameDay city priority delivery service, (2016); FedEx SameDay city standard delivery service, (2016); Gounaris CE, Wiesemann W, Floudas CA, The robust capacitated vehicle routing problem under demand uncertainty, Oper. Res, 61, 3, pp. 677-693, (2013); Gurvich I, Lariviere M, Moreno A, Operations in the on-demand economy: Staffing services with self-scheduling capacity, (2016); He L, Mak HY, Rong Y, Shen ZJM, Service region design for urban electric vehicle sharing systems, Manufacturing Service Oper. Management, 19, 2, pp. 309-327, (2017); Same-day shipping is key to fighting Amazon, Business Insider, (2017); Ivy C, Amazon flex - Denver - 1st day, (2016); Johnson DS, McGeoch LA, The traveling salesman problem: A case study in local optimization. A case study in local optimization, Local Search in Combinatorial Optimization, pp. 215-310, (1997); Kim E, FedEx will no longer provide express shipping for Amazon in the US, CNBC, (2019); Kingman JFC, The heavy traffic approximation in the theory of queues, Proc. Sympos. Congestion Theory, pp. 137-169, (1974); Krivulin NK, A recursive equations based representation for the G/G/m queue, Appl. Math. Lett, 7, 3, pp. 73-77, (1994); Kuhn D, Esfahani PM, Nguyen VA, Shafieezadeh-Abadeh S, Wasserstein distributionally robust optimization: Theory and applications in machine learning, Operations Research & Management Science in the Age of Analytics, TutORials in Operations Research, pp. 130-166, (2019); Larson RC, Odoni AR, 6.4.12 Single-Depot VRP, (1981); Levy A, FedEx Dumps Amazon Before Amazon Dumps It, The Motley Fool, (2019); Li B, Krushinsky D, Woensel TV, Reijers HA, An adaptive large neighborhood search heuristic for the share-a-ride problem, Comput. Oper. Res, 66, 2016, pp. 170-180, (2016); Lindley DV, The theory of queues with a single server, Math. Proc. Cambridge Philos. Soc, 48, 2, pp. 277-289, (1952); Liu S, He L, Shen Z-JM, On-time last mile delivery: Order assignment with travel time predictors, Management Sci, (2020); Lore M, Serving customers in new ways: Walmart begins testing associate delivery, (2017); Mamani H, Nassiri S, Wagner M, Closed-form solutions for robust inventory management, Management Sci, 63, 5, pp. 1625-1643, (2016); Phillips EE, e-Commerce companies get creative in quest for last mile space, Wall Street Journal, (2018); Postmates Courier Driver hourly salaries in the United States, (2018); Qi W, Li L, Liu S, Shen ZJM, Shared mobility for last-mile delivery: Design, operational prescriptions, and environmental impact, Manufacturing Service Oper. Management, 20, 4, pp. 737-751, (2018); Walmart ends its grocery delivery partnerships with Uber and Lyft after they fail to take off, CNBC, (2018); Speed limits, (2018); Simchi-Levi D, Chen X, Bramel J, The Logic of Logistics, (2014); Steele JM, Subadditive Euclidean functionals and nonlinear growth in geometric probability, Ann. Probab, 9, 3, pp. 365-376, (1981); Steele JM, Probability Theory and Combinatorial Optimization, (1997); Sungur I, Ordonez F, Dessouky M, A robust optimization approach for the capacitated vehicle routing problem with demand uncertainty, IIE Trans, 40, 5, pp. 509-523, (2008); Taylor T, On-demand service platforms, Manufacturing Service Oper. Management, 20, 4, pp. 704-720, (2018); Wagner M, Robust inventory management: An optimal control approach, Oper. Res, 66, 2, pp. 426-477, (2018); Wells G, Stevens L, Amazon conducts first commercial drone delivery, Wall Street Journal, (2016); Whitt W, Approximations for the gi/g/m queue, Production Oper. Management, 2, 2, pp. 114-161, (1993)",null,null,"INFORMS Inst.for Operations Res.and the Management Sciences",{"$nulls":5},1.5234614E7,null,"MSOMF",null,"English","Manuf. Serv. Oper. Manage.","Article","Final",null,"Scopus","2-s2.0-85132216602"]
["Merkert R.; Bliemer M.C.J.; Fayyaz M.","Merkert, Rico (35253669500); Bliemer, Michiel C.J. (6506715804); Fayyaz, Muhammad (57213735577)","35253669500; 6506715804; 57213735577","Consumer preferences for innovative and traditional last-mile parcel delivery",2022.0,"International Journal of Physical Distribution and Logistics Management",52.0,3.0,null,261.0,284.0,23.0,33.0,"10.1108/IJPDLM-01-2021-0013","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85125107562&doi=10.1108%2fIJPDLM-01-2021-0013&partnerID=40&md5=9060d3aad1cb22ebe6154faa767a580b","Institute of Transport and Logistics Studies, The University of Sydney Business School, Sydney, Australia","Merkert R., Institute of Transport and Logistics Studies, The University of Sydney Business School, Sydney, Australia; Bliemer M.C.J., Institute of Transport and Logistics Studies, The University of Sydney Business School, Sydney, Australia; Fayyaz M., Institute of Transport and Logistics Studies, The University of Sydney Business School, Sydney, Australia","Purpose: The purpose of this research is to reveal consumer preferences towards innovative last-mile parcel delivery and more specifically unmanned aerial delivery drones, in comparison to traditional postal delivery (postie) and the recent rise of parcel lockers in Australia. The authors investigate competitive priorities and willingness to pay for key attributes of parcel delivery (mode, speed, method and time window), the role of contextual moderators such as parcel value and security and opportunities for logistics service providers in the growing e-commerce market. Design/methodology/approach: A survey involving stated choice experiments has been conducted among 709 respondents in urban Australia. The authors estimated panel error component logit models, derived consumer priorities and deployed 576 Monte Carlo simulations to forecast potential delivery mode market shares. Findings: The study results suggest that people prefer postie over drone delivery, all else equal, but that drone deliveries become competitive with large market shares if they live up to the premise that they can deliver faster and cheaper. Both drone and postie become less attractive relative to parcel lockers when there is no safe place to leave a parcel at a residence, highlighting the importance of situational context and infrastructure at the receiving end of last-mile delivery. The authors identified opportunities for chargeable add-on services, such as signature for postie and 2-h parcel deliveries for drones. Originality/value: The authors offer timely and novel insights into consumers preferences towards aerial drone parcel deliveries compared to postie and lockers. Going beyond the extant engineering/operations research literature, the authors provide a starting point and add new dimensions/moderators for last-mile parcel delivery choice analysis and empirical evidence of market potential and competitive attributes of innovative versus traditional parcel delivery alternatives. © 2022, Emerald Publishing Limited.","Aerial drones; Choice experiments; e-commerce; Last-mile delivery; Parcel lockers; WTP",{"$nulls":5},"University of Sydney Business School","The authors acknowledge the comments received from three anonymous reviewers, colleagues at ITLS, and various industry partners who guided the experiment design, in particular Australia Post. The authors are grateful for the financial support received from the Future Transport Research Group at the University of Sydney Business School. ","Australian Bureau of statistics, general community profile, (2016); Education and Work, Australia, (2021); Akyol D.E., de Koster R.B.M., Determining time windows in urban freight transport: a city cooperative approach, Transportation Research Part E: Logistics and Transportation Review, 118, pp. 34-50, (2018); Bliemer M.C.J., Rose J.M., Chorus C.G., Detecting dominance in stated choice data and accounting for dominance-based scale differences in logit models, Transportation Research Part B: Methodological, 102, pp. 83-104, (2017); Boysen N., Fedtke S., Schwerdfeger S., Last-mile delivery concepts: a survey from an operational research perspective, OR Spectrum, 43, pp. 1-58, (2021); Buldeo Rai H., Verlinde S., Macharis C., The ‘next day, free delivery’ myth unravelled: possibilities for sustainable last mile transport in an omnichannel environment, International Journal of Retail and Distribution Management, 47, 1, pp. 39-54, (2019); Buldeo Rai H., Verlinde S., Macharis C., Unlocking the failed delivery problem? 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Consumer preferences for delivery attributes in online retailing, Journal of Business Logistics, 40, 4, pp. 299-321, (2019); Orme B.K., Getting Started with Conjoint Analysis:Strategies for Product Design and Pricing Research, (2020); Osakwe C.N., Hudik M., Riha D., Stros M., Ramayah T., Critical factors characterizing consumers’ intentions to use drones for last-mile delivery: does delivery risk matter?, Journal of Retailing and Consumer Services, 65, March, (2022); Pani A., Mishra S., Golias M., Figliozzi M., Evaluating public acceptance of autonomous delivery robots during COVID-19 pandemic, Transportation Research Part D: Transport and Environment, 89, (2020); Perera S., Dawande M., Janakiraman G., Mookerjee V., Retail deliveries by drones: how will logistics networks change?, Production Operations Management, 29, pp. 2019-2034, (2020); Pitney Bowes parcel shipping index, (2021); Australia Post doubles the number of parcel locker locations, (2021); Prasad G., Abishek P., Karthick R., Influence of unmanned aerial vehicle in medical product transport, International Journal of Intelligent Unmanned Systems, 7, 2, pp. 88-94, (2019); Pugliese L.D.P., Guerriero F., Macrina G., Using drones for parcels delivery process, Procedia Manufacturing, 42, pp. 488-497, (2020); Revelt D., Train K., Mixed logit with repeated choices: households choices of appliance efficiency level, Review of Economics and Statistics, 80, 4, pp. 647-657, (1998); Rose J.M., Bliemer M.C.J., Constructing efficient stated choice designs, Transport Reviews, 29, 5, pp. 587-617, (2009); Rossolov A., A last-mile delivery channel choice by E-shoppers: assessing the potential demand for automated parcel lockers, International Journal of Logistics Research and Applications, (2021); Sandor Z., Wedel M., Designing conjoint choice experiments using managers' prior beliefs, Journal of Marketing Research, 38, 4, pp. 430-444, (2001); Shahzaad B., Bouguettaya A., Mistry S., Neiat A.G., Composing drone-as-a-service (DAAS) for delivery, IEEE International Conference on Web Services (ICWS), pp. 28-32, (2019); eCommerce report 2020, (2020); Svanberg M., Guidelines for establishing practical relevance in logistics and supply chain management research, International Journal of Physical Distribution and Logistics Management, 50, 2, pp. 215-232, (2020); Droning on - the pandemic is giving unmanned deliveries a fillip, The Economist, (2020); Tokar T., Williams B.D., Fugate B.S., I heart logistics—just don't ask me to pay for it: online shopper behavior in response to a delivery carrier upgrade and subsequent shipping charge increase, Journal of Business Logistics, 41, 3, pp. 182-205, (2020); Tsai Y.-T., Tiwasing P., Customers' intention to adopt smart lockers in last-mile delivery service: a multi-theory perspective, Journal of Retailing and Consumer Services, 61, (2021); Public perception of drone delivery in the United States, (2016); Vakulenko Y., Hellstrom D., Hjort K., What's in the parcel locker? 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Merkert; Institute of Transport and Logistics Studies, The University of Sydney Business School, Sydney, Australia; email: rico.merkert@sydney.edu.au",null,"Emerald Group Holdings Ltd.",{"$nulls":5},9600035.0,null,null,null,"English","Int. J. Phys. Distrib. Logist. Manage.","Article","Final",null,"Scopus","2-s2.0-85125107562"]
["Parodos L.; Tsolakis O.; Tsoukos G.; Xenou E.; Ayfantopoulou G.","Parodos, Leonidas (57219989579); Tsolakis, Orestis (57302120400); Tsoukos, George (57219985615); Xenou, Elpida (57194451353); Ayfantopoulou, Georgia (58245381700)","57219989579; 57302120400; 57219985615; 57194451353; 58245381700","Business Model Analysis of Smart City Logistics Solutions Using the Business Model Canvas: The Case of an On-Demand Warehousing E-Marketplace",2022.0,"Future Transportation",2.0,2.0,null,467.0,481.0,14.0,3.0,"10.3390/futuretransp2020026","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85141768398&doi=10.3390%2ffuturetransp2020026&partnerID=40&md5=8946b9ad1bab2a3ea1d9476122df30f1","Centre for Research and Technology Hellas, Hellenic Institute of Transport, Thessaloniki, 57001, Greece; New Technologies and Innovation Department, TREDIT S.A, Thessaloniki, 55135, Greece","Parodos L., Centre for Research and Technology Hellas, Hellenic Institute of Transport, Thessaloniki, 57001, Greece; Tsolakis O., Centre for Research and Technology Hellas, Hellenic Institute of Transport, Thessaloniki, 57001, Greece; Tsoukos G., New Technologies and Innovation Department, TREDIT S.A, Thessaloniki, 55135, Greece; Xenou E., Centre for Research and Technology Hellas, Hellenic Institute of Transport, Thessaloniki, 57001, Greece; Ayfantopoulou G., Centre for Research and Technology Hellas, Hellenic Institute of Transport, Thessaloniki, 57001, Greece","The rapid rise of e-commerce and advances in the technological sector have enabled the emergence of modern business models on e-marketplaces. Digital and on-demand e-marketplaces have become increasingly popular, responding to the trend of the sharing economy in various business sectors, but there is little guidance on how to develop the respective business models in order to ensure the long-term sustainability of such companies. The present paper is based upon the development and operation of an innovative on-demand warehousing e-marketplace in Greece as a one stop-shop for on-demand warehousing services. The purpose of this paper is to identify the necessary components for developing a successful innovative business model for a viable and effective on-demand warehousing platform. The identification of the value proposition of the proposed e-marketplace, the necessary business infrastructure and the customer interface are described, analyzed and adapted to the Greek Market. Furthermore, this paper also describes the cost structure and the revenue streams of the proposed on-demand warehousing e-marketplace. © 2022 by the authors.","business model canvas; e-marketplace; innovation; on-demand warehousing; sustainable business models",{"$nulls":5},"CREATE, (T1EDK-04383); European Union and Greek national funds; Operational Program Competitiveness, Entrepreneurship and Innovation; RESEARCH; European Regional Development Fund, ERDF","This research has been co-financed by the European Regional Development Fund of the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation, under the call RESEARCH—CREATE—INNOVATE (project code: T1EDK-04383).","Tauscher K., Laudien S.M., Understanding platform business models: A mixed methods study of marketplaces, Eur. Manag. J, 36, pp. 319-329, (2018); Veile J.W., Schmidt M.-C., Voigt K.-I., Toward a new era of cooperation: How industrial digital platforms transform business models in Industry 4.0, J. Bus. Res, 143, pp. 387-405, (2022); Schwanholz J., Leipold S., Sharing for a circular economy? An analysis of digital sharing platforms’ principles and business models, J. Clean. Prod, 269, (2020); Ruggieri R., Savastano M., Scalingi A., Bala D., D'Ascenzo F., The impact of digital platforms on business models: An empirical investigation on innovative start-ups, Manag. Mark, 13, pp. 1210-1225, (2018); World Urbanization Prospects: 2018 Revision, (2018); Morfoulaki M., Mikiki F., Kotoula N., Myrovali G., Integrating City Logistics into Urban Mobility Policies, Proceedings of the 7th International Congress on Transportation Research; Savelsbergh M., Woensel T.V., 50th Anniversary Invited Article—City Logistics: Challenges and Opportunities, Transp. Sci, 50, pp. 579-590, (2016); Neghabadi P.D., Samuel K.E., Espinouse M.-L., Systematic literature review on city logistics: Overview, classification and analysis, Int. J. Prod. Res, 57, pp. 865-887, (2019); Viu-Roig M., Alvarez-Palau E.J., The Impact of E-Commerce-Related Last-Mile Logistics on Cities: A Systematic Literature Review, Sustainability, 12, (2020); The Future of Last Mile Logistics, (2020); COVID-19 and the Retail Sector: Impact and Policy Responses, OECD Policy Responses to Coronavirus (COVID-19), (2020); COVID-19 and e-Commerce: A Global Review, (2021); Allen J., Piecyk M., Piotrowska M., McLeod F., Cherrett T., Ghali K., Nguyen T., Bektas T., Bates O., Friday A., Et al., Understanding the impact of e-commerce on last-mile light goods vehicle activity in urban areas: The case of London, Transp. Res. Part D Transp. Environ, 61, pp. 325-338, (2018); Arnold F., Cardenas I., Dewulf K.K.S.W., Simulation of B2C e-commerce distribution in Antwerp using cargo bikes and delivery points, Eur. Transp. Res. Rev, 10, (2018); Click & Collect in the UK, (2016); Smart Choices for Cities: Making Urban Freight Logistics More Sustainable, s.l.: CIVITAS Forum Network, (2020); Sundararajan A., From Zipcar to Sharing Economy, Harv. Bus. Rev, 1, pp. 1-2, (2013); Friedman G.C., Workers without employers: Shadow corporations and the rise of the gig economy, Rev. Keynes. Econ, 2, pp. 171-188, (2014); Yaraghi N., Ravi S., The Current and Future State of the Sharing Economy. Brookings India IMPACT Series No. 032017, SSRN, pp. 1-38, (2017); Conger K., Griffith E., The Results Are in for the Sharing Economy. 2020. They Are Ugly. The New York Times; Batool M., Ghulam H., Hayat M.A., Naeem M.Z., Ejaz A., Imran Z.A., Spulbar C., Birau R., Gorun T.H., How COVID-19 has shaken the sharing economy? An analysis using Google trends data, Econ. Res. Ekon. Istraž, 34, pp. 2374-2386, (2020); DuBois D., Impact of the Coronavirus on Global Short-Term Rental Markets-AirDNA-Short-Term Vacation Rental Data and Analytics, (2020); O'Brien S.A., The Ride Hailing Industry Is Getting Turned on Its Head by Coronavirus—hCNN, (2020); Koetsier J., COVID-19 App Economy: Instacart, Walmart, Costco Way Up, Uber and Lyft Drop Like Rocks, (2020); Groen W.P., Lenaerts K., Bosc R., Paquier F., Impact of digitalisation and the on-demand economy on labour markets and the consequences for employment and industrial relations, Final. Study CEPS Spec. Rep, 1, (2017); Teece D.J., Business Models, Business Strategy and Innovation, Long Range Plan, 43, pp. 172-194, (2010); Xenou E., Parodos L., Tsoukos G., Aifandopoulou G., Maleas Z., The Rise of the on-Demand Warehousing: Is the Greek Market Ready for This Change?, pp. 835-844, (2020); Third Party Logistics. Industry Study, (2018)","L. Parodos; Centre for Research and Technology Hellas, Hellenic Institute of Transport, Thessaloniki, 57001, Greece; email: lparodos@certh.gr",null,"Multidisciplinary Digital Publishing Institute (MDPI)",{"$nulls":5},2.673759E7,null,null,null,"English","Future. Transp.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85141768398"]
["Torres F.; Gendreau M.; Rei W.","Torres, Fabian (57672428600); Gendreau, Michel (7005646783); Rei, Walter (26768255500)","57672428600; 7005646783; 26768255500","Crowdshipping: An open VRP variant with stochastic destinations",2022.0,"Transportation Research Part C: Emerging Technologies",140.0,null,103677.0,null,null,null,14.0,"10.1016/j.trc.2022.103677","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85129747406&doi=10.1016%2fj.trc.2022.103677&partnerID=40&md5=a0badd9c4aa8c2b2c055e877bc361c3a","CIRRELT, Canada; Département de Mathématiques et de Génie Industriel, Polytechnique Montréal, Canada; Département de Management et Technologie, Université de Québec à Montréal, Canada","Torres F., CIRRELT, Canada, Département de Mathématiques et de Génie Industriel, Polytechnique Montréal, Canada; Gendreau M., CIRRELT, Canada, Département de Mathématiques et de Génie Industriel, Polytechnique Montréal, Canada; Rei W., CIRRELT, Canada, Département de Management et Technologie, Université de Québec à Montréal, Canada","E-commerce continues to grow throughout the world due to people's preference to stay at home rather than going to a brick-and-mortar retail store. COVID-19 has exacerbated this trend. Concurrently, crowd-shipping has been gaining in popularity due to both the increase in e-commerce and the current pressures due to COVID-19. We consider a setting where a crowd-shipping platform can fulfill heterogeneous delivery requests from a central depot with a fleet of professionally driven vehicles and a pool of capacitated occasional drivers. We divide delivery requests into sectors to represent different neighborhoods in a city. Occasional drivers have unknown destinations that can be anywhere inside the sectors. Route duration constraints are modeled to motivate participation and increase the probability of route-acceptance by keeping routes short. We assume that occasional drivers will choose routes that are better compensated and that the probability of route-acceptance is dependent on other routes being offered. We propose a two-stage stochastic model to formulate the problem. We use a branch-and-price algorithm capable of solving 50-customer instances, and develop a heuristic that can solve larger 100-customer instances quickly. An upper bound for the total number of occasional drivers is used to reduce the number of constraints in the master problem and reduce the complexity of the pricing problems. We show that occasional drivers with destinations far from the depot reduce the cost by over 30%, while occasional drivers with destinations that are near the depot reduce the cost by 20%. We show that route duration constraints and capacity constraints can restrict the occasional driver routes and both need to simultaneously increase in order to have cost reductions. This setting of crowd-shipping is a viable option for last-mile deliveries. © 2022 Elsevier Ltd","City logistics; Column generation; Crowd drivers; Crowd-logistics; Crowd-shipping; Dynamic programming; Occasional drivers; Stochastic programming","Cost reduction; Electronic commerce; Fleet operations; Integer programming; Linear programming; Retail stores; Ships; Stochastic models; Stochastic programming; Stochastic systems; 'current; City logistics; Column generation; Crowd driver; Crowd-logistic; Crowd-shipping; E- commerces; Neighbourhood; Occasional driver; Stochastics; electronic commerce; neighborhood; shipping; stochasticity; urban transport; Dynamic programming",{"$nulls":4},"Polytechnique Montréal; Natural Sciences and Engineering Research Council of Canada, NSERC; Secretaría de Educación Superior, Ciencia, Tecnología e Innovación, SENESCYT","This research was partially funded by the Canadian Natural Sciences and Engineering Research Council (NSERC) under its Discovery Grants research program, as well as the Canada Research Chair in Stochastic Optimization of Transport and Logistics Systems , by Polytechnique Montréal , and by the Ecuadorian Secretaría de Educación Superior, Ciencia, Tecnología e Inovación (SENESCYT) under its international scholarships program. We would like to thank Compute Canda for the resources provided to run computational experiments.","Alnaggar A., Gzara F., Bookbinder J.H., Crowdsourced delivery: A review of platforms and academic literature, Omega, 98, (2021); AmazonFlex A., AmazonFlex, (2021); Archetti C., Guerriero F., Macrina G., The online vehicle routing problem with occasional drivers, Comput. Oper. Res., 127, (2021); Archetti C., Savelsbergh M., Speranza M.G., The vehicle routing problem with occasional drivers, European J. Oper. Res., 254, 2, pp. 472-480, (2016); Arslan A.M., Agatz N., Kroon L., Zuidwijk R., Crowdsourced delivery: A dynamic pickup and delivery problem with ad hoc drivers, Transp. Sci., 53, 1, pp. 222-235, (2019); Asdecker B., Zirkelbach F., (2020); Baldacci R., Mingozzi A., Roberti R., New route relaxation and pricing strategies for the vehicle routing problem, Oper. Res., 59, 5, pp. 1269-1283, (2011); Bhatti A., Akram H., Basit H.M., Khan A.U., Raza S.M., Naqvi M.B., E-commerce trends during COVID-19 pandemic, Int. J. Future Gener. Commun. Netw., 13, 2, pp. 1449-1452, (2020); Costa L., Contardo C., Desaulniers G., Exact branch-price-and-cut algorithms for vehicle routing, Transp. Sci., 53, 4, pp. 946-985, (2019); Dahle L., Andersson H., Christiansen M., The vehicle routing problem with dynamic occasional drivers, International Conference on Computational Logistics, pp. 49-63, (2017); Dahle L., Andersson H., Christiansen M., Speranza M.G., The pickup and delivery problem with time windows and occasional drivers, Comput. Oper. Res., 109, pp. 122-133, (2019); Dayarian I., Savelsbergh M., Crowdshipping and same-day delivery: Employing in-store customers to deliver online orders, Optim. Online, pp. 07-6142, (2017); Debreu G., Representation of a preference ordering by a numerical function, Decis. Process., 3, pp. 159-165, (1954); Desaulniers G., Desrosiers J., Solomon M.M., Column Generation, Vol. 5, (2006); Fukasawa R., Longo H., Lysgaard J., Aragao M.P.D., Reis M., Uchoa E., Werneck R.F., Robust branch-and-cut-and-price for the capacitated vehicle routing problem, Math. Program., 106, 3, pp. 491-511, (2006); Gao X., Shi X., Guo H., Liu Y., To buy or not buy food online: The impact of the COVID-19 epidemic on the adoption of e-commerce in China, PLoS One, 15, 8, (2020); Gdowska K., Viana A., Pedroso J.P., Stochastic last-mile delivery with crowdshipping, Transp. Res. Procedia, 30, pp. 90-100, (2018); Gendreau M., Jabali O., Rei W., Chapter 8: Stochastic vehicle routing problems, Vehicle Routing: Problems, Methods, and Applications, Second Edition, pp. 213-239, (2014); Macrina G., Guerriero F., The green vehicle routing problem with occasional drivers, New Trends in Emerging Complex Real Life Problems, pp. 357-366, (2018); Macrina G., Pugliese L.D.P., Guerriero F., Laporte G., Crowd-shipping with time windows and transshipment nodes, Comput. Oper. Res., 113, (2020); Mrkela L., Stanimirovic Z., A variable neighborhood search for the budget-constrained maximal covering location problem with customer preference ordering, Oper. Res., pp. 1-39, (2021); Pecin D., Pessoa A., Poggi M., Uchoa E., Improved branch-cut-and-price for capacitated vehicle routing, Math. Program. Comput., 9, 1, pp. 61-100, (2017); Poggi M., Uchoa E., Chapter 3: New exact algorithms for the capacitated vehicle routing problem, Vehicle Routing: Problems, Methods, and Applications, Second Edition, pp. 59-86, (2014); Raj M., Sundararajan A., You C., Covid-19 and digital resilience: Evidence from uber eats, (2020); Righini G., Salani M., New dynamic programming algorithms for the resource constrained elementary shortest path problem, Netw.: Int. J., 51, 3, pp. 155-170, (2008); Sampaio A., Savelsbergh M., Veelenturf L., Van Woensel T., Crowd-based city logistics, Sustainable Transportation and Smart Logistics, pp. 381-400, (2019); Sanchez D.G., Parra N.G., Ozden C., Rijkers B., Which jobs are most vulnerable to COVID-19? What an analysis of the European union reveals, World Bank Res. Policy Briefs, (2020); Torres F., Gendreau M., Rei W., Vehicle routing with stochastic supply of crowd vehicles and time windows, CIRRELT, (2020); Wolsey L.A., Integer Programming, (2020)","F. Torres; Département de Mathématiques et de Génie Industriel, Polytechnique Montréal, Canada; email: fabian.torres@epfl.ch",null,"Elsevier Ltd",{"$nulls":5},"0968090X",null,null,null,"English","Transp. Res. Part C Emerg. Technol.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85129747406"]
["Beteto A.; Melo V.; Lin J.; Alsultan M.; Dias E.M.; Korte E.; Johnson D.A.A.; Moghadasi N.; Polmateer T.L.; Lambert J.H.","Beteto, Alinne (57426592800); Melo, Vidal (35325123800); Lin, Jessica (57195127215); Alsultan, Marwan (57203789877); Dias, Eduardo Mario (8434109300); Korte, Elizabeth (57244819100); Johnson, DeAndre A. (57427408800); Moghadasi, Negin (57245262900); Polmateer, Thomas L. (57192069217); Lambert, James H. (7401837124)","57426592800; 35325123800; 57195127215; 57203789877; 8434109300; 57244819100; 57427408800; 57245262900; 57192069217; 7401837124","Anomaly and cyber fraud detection in pipelines and supply chains for liquid fuels",2022.0,"Environment Systems and Decisions",42.0,2.0,null,306.0,324.0,18.0,2.0,"10.1007/s10669-022-09843-5","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85123464402&doi=10.1007%2fs10669-022-09843-5&partnerID=40&md5=34d22affa7e67e8ca6052e3b81068eb5","University of Sao Paulo, São Paulo, 05508-900, Brazil; University of Virginia, Charlottesville, 22903, VA, United States; King Saud University, Riyadh, 11692, Saudi Arabia","Beteto A., University of Sao Paulo, São Paulo, 05508-900, Brazil; Melo V., University of Sao Paulo, São Paulo, 05508-900, Brazil; Lin J., University of Virginia, Charlottesville, 22903, VA, United States; Alsultan M., King Saud University, Riyadh, 11692, Saudi Arabia; Dias E.M., University of Sao Paulo, São Paulo, 05508-900, Brazil; Korte E., University of Virginia, Charlottesville, 22903, VA, United States; Johnson D.A.A., University of Virginia, Charlottesville, 22903, VA, United States; Moghadasi N., University of Virginia, Charlottesville, 22903, VA, United States; Polmateer T.L., University of Virginia, Charlottesville, 22903, VA, United States; Lambert J.H., University of Virginia, Charlottesville, 22903, VA, United States","A recent large-scale information disruption of the Colonial Pipeline across the USA has highlighted the cyber vulnerabilities of the supply chains of liquid fuels. Information disruption and associated anomalies have become routine events for critical infrastructure of sociotechnical systems. The logistics systems that support energy commodity supply chains are vulnerable to information threats that evolve throughout the system life cycles. Among the prevalent threats energy supply chains are malicious hacking, fraud, information theft, ransomware, and related irregular activities. Fraud and malicious activity are not new in the supply chains for liquid fuels, though mechanisms and consequences may be changing. This paper addresses information anomalies that are on a spectrum of errors, lost data, fraud, cyber, ransomware and related disruptions to logistics systems that support e-commerce and distribution of liquid fuels, particularly for challenges associated with human and organizational errors whose frequencies may be increasing in the latest pandemic. The lessons learned can help to improve the anomalies monitoring systems thus protecting the interests of consumers, industry, and the government. A case featuring fuels distribution, cyber-physical-systems and the internet of things (IoT) is presented to illustrate several issues that are challenging the design and operation of government-mandated inspection and detection processes for fraud and anomalies. In particular, an Authenticator and Transmitter System (SAT) concept is described for remote monitoring of fuel distribution points via a secure communication channel between the fuel pumps and government regulators. The data collected in this approach are used to analyze the behavior of fuel distribution points and detect anomalous behaviors that could indicate fraud and/or fraud-like precursors to other information disruptions. The method technologies that are described in this paper helps to detect precursors of fraud and other information irregularities in their earliest stages, and to enhance policies that protect the information systems of fuel pipelines and their related logistics systems. Methods such as described herein are integrated among layers of complex information technologies to protect the interests of the energy sector, consumers, and government. © 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.","Data analysis; Energy sector; Logistics; Ransomware; Systems engineering; Trust","United States; commodity; detection method; electronic commerce; energy efficiency; fuel; government; infrastructure; logistics; pipeline; supply chain management",{"$nulls":4},"Commonwealth Center for Advanced Logistics Systems; UCRC Center for Hardware and Embedded Systems Security and Trust; National Science Foundation, NSF, (1916760); U.S. Army Corps of Engineers, USACE","This effort was supported in part by the US National Science Foundation I/UCRC Center for Hardware and Embedded Systems Security and Trust (NSF Award 1916760); the Commonwealth Center for Advanced Logistics Systems; Systems Planning & Analysis, Inc.; Fermata LLC; and the US Army Corps of Engineers. ","Adepoju O., Wosowei J., Lawte S., Jaiman H., Comparative evaluation of credit card fraud detection using machine learning techniques, Proceedings of the 2019 Global Conference for Advancement in Technology (GCAT), (2019); Almutairi A., Wheeler J.P., Slutzky D.L., Lambert J.H., Integrating stakeholder mapping and risk scenarios to improve resilience of cyber-physical-social networks, Risk Anal, (2019); Andrews D.J., Polmateer T.L., Wheeler J.P., Slutzky D.L., Lambert J.H., Enterprise risk and resilience of electric-vehicle charging infrastructure and the future mobile power grid, Curr Sustain Renew Energy Rep Transport, 7, pp. 9-15, (2020); Cars and Light Trucks, pp. 2013-2017; Anton-Haro C., Dohler M., Machine-to-machine (M2M) communications, architecture performance and applications, pp. 1-23, (2014); Begian C., Kettani H., Analysis of fuel pump skimming devices, Proceedings of the 2020 the 4Th International Conference on Information System and Data Mining, pp. 157-162, (2020); Beteto A., Proposta De automação Para Controle Da vazão De combustíveis líquidos Como Nova Abordagem De giscalização Para O Gerenciamento De Riscos Em Postos Revendedores, (2019); Bundi D., Maraga M.J., Effects of cybercrime on oil and gas industry, Glob Sci J, 8, 6, (2020); Carrasco R.S., Silcilia-Urban M.A., Evaluation of deep neural networks for reduction of credit card fraud alerts, IEEE Access, (2020); Catota F.E., Morgan M.G., Sicker D.C., Cybersecurity education in a developing nation: the Ecuadorian environment, J Cybersecurity, (2019); Collier Z.A., Lambert J.H., Principles and methods of model validation for model risk reduction, IEEE Environ Syst Decis, 39, pp. 146-153, (2019); Collier Z.A., Linkov I., DiMase D., Walters S., Tehranipoor M., Lambert J.H., Cybersecurity standards: managing risk and creating resilience, IEEE Comput, 47, 9, pp. 70-76, (2014); Coma-Puig B., Carmona J., Gavalda R., Alcoverro S., Martin V., Fraud detection in energy consumption: A supervised approach, Proceedings of the 2016 IEEE International Conference on Data Science and Advanced Analytics (DSAA), pp. 120-129, (2016); Dahee C., Kyungho L., An artificial intelligence approach to financial fraud detection under IoT environment: a survey and implementation, Security Commun Netw, (2018); Davis M.V., Strategies to Prevent and Detect Occupational Fraud in Small Retail Businesses, (2019); Dong C., Wang H., Ni D., Liu Y., Chen Q., Impact evaluation of cyber-attacks on traffic flow of connected and automated vehicles, IEEE Access, 8, pp. 86824-86835, (2020); Fenza G., Gallo M., Loia V., Drift-aware methodology for anomaly detection in smart grid, IEEE Access, 7, pp. 9645-9657, (2019); Ferdous A.H.M.I., Et al., A hybrid structured PCF for fuel adulteration detection in terahertz regime, Sens Bio-Sens Res, (2021); Golan M.S., Et al., Trends and applications of resilience analytics in supply chain modeling: systematic literature review in the context of the COVID 19 pandemic, Environmental Systems and Decisions, 40, pp. 222-243, (2020); Golfarelli M., Rizzi S., A model-driven approach to automate data visualization in big data analytics, Sage J, 19, 1, pp. 24-47, (2019); Gottwalt F., Chang E.J., Dillon T.S., Contextual anomaly detection methods for addressing intrusion detection: Security & forensics book chapter, IGI Global, (2021); General Accreditation Guidance—Validation and verification of quantitative and qualitative test methods., (2018); Hosseini S.S., Noorosana R., Performance evaluation of EWMA and CUSUM control charts to detect anomalies in social networks using average and standard deviation of degree measures, Qual Reliab Eng Int, 34, 4, pp. 477-500, (2018); Hou E., Miller K., Hero A., Anomaly detection in the monitoring of nuclear facilities. University of Michigan., (2018); Kara I., Aydos M., Cyber fraud: Detection and analysis of the crypto-ransomware, In: Proceedings of the 2020 11Th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)., (2020); Kott A., Et al., Cyber resilience: by design or by intervention?, Computer, 54, 8, pp. 112-117, (2021); Lewis J., English C., Gesick J., Mukkamala S., Validation Process Methods, (2018); Linkov I., Baiardi F., Florin M.V., Greer S., Lambert J.H., Pollock M., Rickli J.M., Applying resilience to hybrid threats, IEEE Secur Priv, 17, 5, pp. 78-83, (2019); Linkov I., Baiardi F., Florin M.V., Greer S., Lambert J.H., Pollack M., Rickli J.M., Roslycky L., Seager T., Thorisson H., Trump B.D., Apply resilience to hybrid threats, IEEE Security Privacy Mag, (2019); Maldonado K., Et al., Situational strategic awareness monitoring surveillance system—microcomputer and microcomputer clustering used for intelligent, economical, scalable, and deployable approach for safeguarding materials, J Imaging Sci Technol, (2019); Maniraj S.P., Saini A., Sarkar S.D., Ahmed S., Credit card fraud detection using machine learning and data science, Int J Eng Res Technol, (2019); Melo V., Augusto Z., Castro S., Autenticador E Transmissor (SAT): Modelo tecnológico De automação E Controle De Processos Em Cidades Inteligentes Com Exemplo De aplicação Ao Setor tributário, (2015); Muggah R., Thompson N.B., Brazil struggles with effective cyber-crime response, Instituto Igarapé, (2018); Muggah R., Thompson N., Brazil's cybercrime problem, Foreign Affairs. Available, (2019); Osborne C., Colonial pipeline attack: Everything you need to know., (2021); Papale G., Sgaglione L., SDD sentinel: A support tool for detecting and investigating electronic transaction frauds, Proceedings of the 2017 IEEE International Conference on Internet of Things (Ithings) and IEEE Green Computing and Communications (Greencom) and IEEE Cyber, Physical and Social Computing (Cpscom) and IEEE Smart Data (Smartdata), pp. 318-323, (2017); Pereira Franco dos Santos A., Et al., Fuel quality monitoring by color detection, Color Detect, (2020); Roege P.E., Collier Z.A., Chevardin V., Chouinard P., Florin M.V., Lambert J.H., Nielsen K., Nogal M., Todorovic B., Bridging the gap from cyber security to resilience, Proceedings of the NATO Science for Peace and Security Series C:Environmental Security., (2017); Rosa-Aquino P., Danner C., What we know about the colonial pipeline shutdown, Intelligencer, (2021); Ryman-Tubb N., Krause P., Neural network rule extraction to detect credit card fraud, Engineering Applications of Neural Networks, Proceedings of the EANN 2011, AIAI 2011 IFIP Advances in Information and Communication Technology, 363, (2011); Sahu A., Et al., Multi-source multi-domain data fusion for cyberattack detection in power systems, IEEE Access, 9, pp. 119118-119138, (2021); Sample Procedure for Method Validation, NIST; Santoyo S., A Brief Overview of Outlier Detection Techniques, (2017); Smith R.G., Urbas G., Controlling Fraud on the Internet: A CAPA Perspective: Report for the Confederation of Asian and Pacific Accountants. Research and Public Policy Series, No, (2001); Thorisson H., Lambert J.H., Angeler D.G., Baiardi F., Taveter K., Vasheasta A., Resilience of critical infrastructure systems to hybrid threats with information disruption, Proceedings of the Resilience and Hybrid Threats: Security and Integrity for the Digital World, 55, 13, (2019); Wieringa R., Empirical research methods for technology validation: scaling up to practice, J Syst Softw, 95, pp. 19-31, (2014)","D.A.A. Johnson; University of Virginia, Charlottesville, 22903, United States; email: psa9rm@virginia.edu",null,"Springer",{"$nulls":5},2.1945403E7,null,null,null,"English","Enviro. Sys. Decis.","Article","Final",null,"Scopus","2-s2.0-85123464402"]
["Lai G.; Liu H.; Xiao W.; Zhao X.","Lai, Guoming (14121434700); Liu, Huihui (56799273700); Xiao, Wenqiang (14833550200); Zhao, Xinyi (57226738409)","14121434700; 56799273700; 14833550200; 57226738409","“Fulfilled by Amazon”: A Strategic Perspective of Competition at the e-Commerce Platform",2022.0,"Manufacturing and Service Operations Management",24.0,3.0,null,1406.0,1420.0,14.0,29.0,"10.1287/msom.2022.1078","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85131008588&doi=10.1287%2fmsom.2022.1078&partnerID=40&md5=a52943cbd81d3a35d91ac9ce9e860b36","University of Texas at Austin, Austin, 78712, TX, United States; China University of Petroleum (Beijing), Beijing, 102200, China; New York University, New York, 10012, NY, United States","Lai G., University of Texas at Austin, Austin, 78712, TX, United States; Liu H., China University of Petroleum (Beijing), Beijing, 102200, China; Xiao W., New York University, New York, 10012, NY, United States; Zhao X., New York University, New York, 10012, NY, United States","Problem definition: This paper examines the economic effects of the fulfillment services offered by Amazon (FBA) to the third-party sellers on its retail platform. Academic/practical relevance: Logistics is critical for e-commerce. It is intriguing that the third-party sellers that use FBA may directly compete with Amazon. By FBA, their service levels are substantially improved and so is their competitiveness. Such a phenomenon has been little investigated in prior literature. Methodology: We develop a strategic competition model where Amazon and a representative third-party seller engage in both price and service competition. Results: Interestingly, we find that although FBA may intensify the service competition between Amazon and the third-party seller, it can mitigate their price competition besides the direct revenue Amazon collects from the service. The latter effects dominate the former when the cross-service sensitivity of the consumers is either sufficiently low or sufficiently high. Therefore, not only the third-party sellers but also Amazon may benefit from FBA. Moreover, because the sales of Amazon’s products may increase because of FBA, its OEM (original equipment manufacturer) supplier may gain from FBA also. These findings extend to the settings where the third-party seller is Amazon’s OEM supplier, cross-price and cross-service sensitivities are correlated, or the parties set their retail prices sequentially. Managerial implications: Our analysis provides insights about when FBA is more likely to be beneficial and when it can be harmful. They are useful for understanding the impacts of FBA on both Amazon and the third-party sellers. © 2022 INFORMS","e-commerce platform; FBA; price; service competition","Costs; Electronic commerce; Sales; Commerce platforms; E- commerces; E-commerce platform; FBA; Original equipment manufacturers; Price; Problem definition; Service competition; Strategic perspectives; Third parties; Competition",{"$nulls":6},"Abhishek V, Jerath K, Zhang ZJ, Agency selling or reselling? Channel structures in electronic retailing, Management Sci, 62, 8, pp. 2258-2280, (2015); Help grow your business with fulfillment by amazon, (2018); Arya A, Mittendorf B, Sappington DE, The bright side of supplier encroachment, Marketing Sci, 26, 5, pp. 651-659, (2007); Banker RD, Khosla I, Sinha KK, Quality and competition, Management Sci, 44, 9, pp. 1167-1320, (1998); Bernstein F, Federgruen A, A general equilibrium model for industries with price and service competition, Oper. Res, 52, 6, pp. 868-886, (2004); Cattani K, Gilland W, Heese HS, Swaminathan J, Boiling frogs: Pricing strategies for a manufacturer adding a direct channel that competes with the traditional channel, Production Oper. Management, 15, 1, pp. 40-56, (2006); Chen X, Wang X, Xia Y, Production coopetition strategies for competing manufacturers that produce partially substitutable products, Production Oper. 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["Al-Ali A.S.M.A.; Sisodia G.S.; Gupta B.; Venugopalan M.","Al-Ali, Ahmed Saleh Mohamed Alichleh (57614748300); Sisodia, Gyanendra Singh (56341671100); Gupta, Bhumika (57211980640); Venugopalan, Murale (56117697200)","57614748300; 56341671100; 57211980640; 56117697200","Change Management and Innovation Practices during Pandemic in the Middle East E-Commerce Industry",2022.0,"Sustainability (Switzerland)",14.0,8.0,4566.0,null,null,null,3.0,"10.3390/su14084566","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85128703285&doi=10.3390%2fsu14084566&partnerID=40&md5=c8345605d77cee012c7929088d1eb671","College of Business Administration, Ajman University, Ajman, 20550, United Arab Emirates; Research Lab LITEM, Management, Marketing, and Strategy, Institut Mines-Telecom Business School, Evry, 91011, France; Alliance School of Business, Alliance University, Bangaluru, 562106, India; Department of Management, Amrita Vishwavidyapeetham, AIMS Campus, Kochi, 682041, India","Al-Ali A.S.M.A., College of Business Administration, Ajman University, Ajman, 20550, United Arab Emirates; Sisodia G.S., College of Business Administration, Ajman University, Ajman, 20550, United Arab Emirates; Gupta B., Research Lab LITEM, Management, Marketing, and Strategy, Institut Mines-Telecom Business School, Evry, 91011, France, Alliance School of Business, Alliance University, Bangaluru, 562106, India; Venugopalan M., Department of Management, Amrita Vishwavidyapeetham, AIMS Campus, Kochi, 682041, India","This study highlights the appropriateness of innovation management principles to success-fully manage radical change in the e-commerce industry during the COVID-19 period. The study focuses on transforming delivery platforms in the context of popular e-commerce organizations in the U.A.E. We conducted the study through interviews, and the results reflect the development of three major themes (shifting consumer behavior, implementation of innovation, and innovation for effective change management) since the beginning of the COVID-19 pandemic. During the transition stage, critical aspects concerning product delivery have emerged to stabilize logistics performance with sustainability. The study suggests that firms need to be faster and more flexible to address the market uncertainty through innovative practices. Similar organizations can use this study to develop mechanisms to improve their delivery systems. Additionally, the study also argues that collaborative innovation significantly contributes to the enhancement of consumers’ well-being and boosts economic growth. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.","change management; consumer behaviour; COVID-19; e-commerce; innovation; middle east; pandemic","Middle East; consumption behavior; COVID-19; electronic commerce; innovation; logistics; market",{"$nulls":4},"Ajman University, AU","We are thankful to Ajman University for supporting us with the Article Processing Charges.","John I., Covid Sparks UAE e-Commerce Boom—Khaleej Times; Bracco F.C., Attalla K., El-Sharawy O., Accelerating Digital Adoption: How the Dual Shocks of COVID-19 and Oil Prices Are Energizing e-Commerce in the Middle East—PwC; How e-Commerce Giant Noon Has Adapted to Drive Sales During Pandemic; Kohli S., Timeline B., Fabius V., Moulvard Veran S., How COVID-19 is Changing Consumer Behavior—Now and Forever, (2020); Mehta S., Saxena T., Purohit N., The New Consumer Behaviour Paradigm amid COVID-19: Permanent or Transient?, J. 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Serv, 58, (2021); Prasetyo Y.T., Tanto H., Mariyanto M., Hanjaya C., Young M.N., Persada S.F., Miraja B.A., Redi A.A.N.P., Factors Affecting Customer Satisfaction and Loyalty in Online Food Delivery Service during the COVID-19 Pandemic: Its Relation with Open Innovation, J. Open Innov. Technol. Mark. Complex, 7, (2021); Eger L., Komarkova L., Egerova D., Micik M., The effect of COVID-19 on consumer shopping behaviour: Generational cohort perspective, J. Retail. Consum. Serv, 61, (2021)","G.S. Sisodia; College of Business Administration, Ajman University, Ajman, 20550, United Arab Emirates; email: singh_gis@yahoo.co.in",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85128703285"]
["Lai N.Y.G.; Kuah A.T.H.; Kim C.H.; Wong K.H.","Lai, Nai Yeen Gavin (57211713464); Kuah, Adrian T. H. (24391196700); Kim, Chang H. (57193888471); Wong, Kok Hoong (57218586194)","57211713464; 24391196700; 57193888471; 57218586194","Toward sustainable express deliveries for online shopping: Reusing packaging materials through reverse logistics",2022.0,"Thunderbird International Business Review",64.0,4.0,null,351.0,362.0,11.0,5.0,"10.1002/tie.22259","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85126002462&doi=10.1002%2ftie.22259&partnerID=40&md5=75d32e5371065c10b715991a02bb3c7c","Faculty of Science and Engineering, University of Nottingham Ningbo China, Ningbo, China; JCU Singapore Business School, James Cook University Australia, Singapore campus, Singapore","Lai N.Y.G., Faculty of Science and Engineering, University of Nottingham Ningbo China, Ningbo, China; Kuah A.T.H., JCU Singapore Business School, James Cook University Australia, Singapore campus, Singapore; Kim C.H., JCU Singapore Business School, James Cook University Australia, Singapore campus, Singapore; Wong K.H., Faculty of Science and Engineering, University of Nottingham Ningbo China, Ningbo, China","The COVID-19 pandemic has led to an increase in online purchases, which has inevitably raised the demand for express delivery packaging materials (EDPMs). This study proposes a reverse logistics reuse framework that extends the EDPM life cycle by drawing on insights and conclusions from a review of the literature on supply chain management and materials science to achieve a sustainable e-commerce system. A key benefit of reverse logistics is its effectiveness in exploiting opportunities for resource reuse, which is preferred to recycling. By extending service life through resource optimization, recycling, and recovery processes, the novel reuse framework based on reverse logistics can be implemented with minimal changes to existing forward logistics systems, potentially leading to more sustainable online shopping. This study proposes a novel combination of reusable packaging materials and reverse logistics as a viable and more environmentally friendly practice, in line with circular economy goals. © 2022 The Authors. Thunderbird International Business Review published by Wiley Periodicals LLC.","circular economy; packaging materials; recovery; recycle; reuse; reverse logistics",{"$nulls":5},"Australian University Librarians; James Cook University, as part of the Wiley; James Cook University, JCU","Open access publishing facilitated by James Cook University, as part of the Wiley - James Cook University agreement via the Council of Australian University Librarians. 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["Fava N.; Laganà V.R.; Nicolosi A.","Fava, Nadia (35956211200); Laganà, Valentina Rosa (57204628824); Nicolosi, Agata (35797448400)","35956211200; 57204628824; 35797448400","The Impact of COVID-19 on Municipal Food Markets: Resilience or Innovative Attitude?",2022.0,"Journal of Open Innovation: Technology, Market, and Complexity",8.0,2.0,87.0,null,null,null,3.0,"10.3390/joitmc8020087","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85130183046&doi=10.3390%2fjoitmc8020087&partnerID=40&md5=54946f4b5518bc540119efec8b56ff13","Department of Engyniering Construction, University of Giromna Plaça Sant Domènec, 3 Edifici Les Àligues, Girona, 17004, Spain; Department of Agriculture, Mediterranean University of Reggio Calabria, Feo de Vito, Reggio Calabria, 89122, Italy","Fava N., Department of Engyniering Construction, University of Giromna Plaça Sant Domènec, 3 Edifici Les Àligues, Girona, 17004, Spain; Laganà V.R., Department of Agriculture, Mediterranean University of Reggio Calabria, Feo de Vito, Reggio Calabria, 89122, Italy; Nicolosi A., Department of Agriculture, Mediterranean University of Reggio Calabria, Feo de Vito, Reggio Calabria, 89122, Italy","The pandemic has accelerated the search for innovative product/process/service solutions in city markets as well as the search for “open innovation challenges” more in line with current needs. The aim of the research is to understand the adaptation mechanisms of the local food system and, in particular, of the public space of the market system. The article analyses the change produced by the COVID-19 pandemic in the municipal markets of Sant Feliu de Guixols, Costa Brava, Spain. The data were collected through a semi-structured questionnaire administered to food sellers and contextually to a group of consumers. Factor analysis and the AGIL model were applied to the data collected and were confirmed with cluster analysis. The analysis highlights that the resilience of sellers is no longer sufficient and in many cases, they have equipped themselves with innovative solutions to meet the new customer demands arising from the pandemic (food delivery, e-commerce, take-away food, digital media, etc.). The document concludes with a discussion of food markets and innovations introduced in this period. Further studies can focus on the relationships between food practices and the transformation of urban spaces so that the food market can support new social practices that promote the food transition. The change would represent a switch which would provide traditionally less powerful actors, such as producers, the opportunity to reformulate the food supply chain in a way more linked to the territory. It would also create a resilient dimension for managing other possible food crises and present a challenge to achieving the ultimate goals of the businesses. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.","AGIL model; cluster analysis; consumer survey; COVID-19; factor analysis; municipal food market; open innovation; seller survey",{"$nulls":5},"Consell Comarcal del Baix Ampurdà","Funding: This research was funded by Consell Comarcal del Baix Ampurdà, Spain.","Bakalis S., Valdramidis V.P., Argyropoulos D., Ahrne L., Chen J., Cullen P.J., Cummins E., Datta A.K., Emmanouilidis C., Foster T., Perspectives from CO+RE: How COVID-19 changed our food systems and food security paradigms, Curr. Res. Food Sci, 3, pp. 166-172, (2020); Bisoffi S., Ahrne L., Aschemann-Witzel J., Baldi A., Cuhls K., DeClerck F., Duncan J., Hansen H.O., Hudson R.L., Kohl J., Et al., COVID-19 and Sustainable Food Systems: What Should We Learn Before the Next Emergency, Front. Sustain. 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Peasant Stud, 47, pp. 1393-1417, (2020); Picchioni F., Po J.Y.T., Forsythe L., Strengthening resilience in response to COVID-19: A call to integrate social reproduction in sustainable food systems, Can. J. Dev. Stud. Rev. Can. Détudes Dév, 42, pp. 28-36, (2021); Nicolosi A., Fava N., Marciano C., Consumers’ Preferences for Local Fish Products in Catalonia, Calabria and Sicily, New Metropolitan Perspectives, pp. 103-112, (2019); Gonzalez S., Contested marketplaces: Retail spaces at the global urban margins, Prog. Hum. Geogr, 44, pp. 877-897, (2020); Morales A., Public Marketplaces Promoting Resilience and Sustainability, Sustainability, 13, (2021); Nicolosi A., Cortese L., Petulla M., Lagana V.R., Di Gregorio D., Privitera D., Sustainable Attitudes of Local People on the Purchase of Local Food. 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["Amornkitvikai Y.; Tham S.Y.; Harvie C.; Buachoom W.W.","Amornkitvikai, Yot (55754665400); Tham, Siew Yean (35175267900); Harvie, Charles (6603964100); Buachoom, Wonlop Writthym (56299957200)","55754665400; 35175267900; 6603964100; 56299957200","Barriers and Factors Affecting the E-Commerce Sustainability of Thai Micro-, Small- and Medium-Sized Enterprises (MSMEs)",2022.0,"Sustainability (Switzerland)",14.0,14.0,8476.0,null,null,null,11.0,"10.3390/su14148476","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137174053&doi=10.3390%2fsu14148476&partnerID=40&md5=6c44327a369d8f145e44d3ef9ad110d5","College of Population Studies, Chulalongkorn University, Bangkok, 10330, Thailand; Regional Economic Studies, ISEAS—Yusof Ishak Institute, Heng Mui Keng Terrace, Singapore, 119614, Singapore; Economics Discipline, Faculty of Business and Law, University of Wollongong, Wollongong, 2522, NSW, Australia; KMITL Business School, King Mongkut’s Institute of Technology Ladkrabang, Bangkok, 10520, Thailand","Amornkitvikai Y., College of Population Studies, Chulalongkorn University, Bangkok, 10330, Thailand; Tham S.Y., Regional Economic Studies, ISEAS—Yusof Ishak Institute, Heng Mui Keng Terrace, Singapore, 119614, Singapore; Harvie C., Economics Discipline, Faculty of Business and Law, University of Wollongong, Wollongong, 2522, NSW, Australia; Buachoom W.W., KMITL Business School, King Mongkut’s Institute of Technology Ladkrabang, Bangkok, 10520, Thailand","It is anticipated that e-commerce will contribute to achieving the 17th Sustainable Development Goal, which seeks to improve implementation mechanisms and revitalize global partnerships for sustainable development. However, MSMEs still face a digital gap compared to large enterprises, which affects their e-commerce sustainability. The study’s objective is to examine the factors and barriers affecting the e-commerce sustainability of Thai micro-, small- and medium-sized enterprises (MSMEs) based on a survey of retail and food and beverage (F&B) service MSMEs in metropolitan Bangkok. Estimations confirm the significance of the TOE framework for Thai MSMEs. Internal e-commerce tools (i.e., smartphones and websites) and external e-commerce platforms (i.e., social media, e-marketplaces, and food delivery platforms) can enhance e-commerce sustainability. However, the age of firms and owners (CEOs) affects e-commerce sustainability negatively. Exports, B2B e-commerce, and e-commerce experience can promote the e-commerce sustainability of Thai MSMEs. However, they perceive that many consumers are still not literate in using e-commerce. In addition, Thailand still has insufficient security to prevent hacking and malware. Therefore, Thai entrepreneurs’ e-commerce literacy is insufficient to enhance their e-commerce sustainability. On the other hand, sustainable e-commerce can increase customer satisfaction, loyalty, and trust through customer support, leading to more long-term online shopping. Hence, this study focuses on e-commerce sustainability-based economic dimensions, as measured by the percentage of e-commerce sales to total sales (e-commerce utilization/intensity). © 2022 by the authors.","e-commerce; food and beverage; micro-, small- and medium-sized enterprises (MSMEs); retail; sustainability; Thailand","Bangkok; Central Region [Thailand]; Krung Thep Mahanakhon; Thailand; Thailand; electronic commerce",{"$nulls":4},"ISEAS - Yusof Ishak Institute, (220618)","The survey questionnaire of this research was funded by ISEAS-Yusof Ishak Institute, Singapore; grant number [220618].","Chen L., Improving Digital Connectivity For E-commerce: A Policy Framework and Empirical Note for ASEAN, (2020); Khandelwal U., Yadav S.K., Tripathi V., Agrawal V., E-consumer conformity and its impact on consumer attitude, J. Asia Bus. 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Mark, 15, pp. 30-57, (2007); McIntyre D.P., Srinivasan A., Chintakananda A., The persistence of platforms: The role of network, platform, and complementor attributes, Long Range Plan, 54, (2020); Moghavvemi S., Factors Influencing the Use of Social Media By SMEs and Its Performance Outcomes, Ind. Manag. Amp Data Syst, 115, pp. 570-588, (2015); Hsu Y.-L., Facebook as international eMarketing strategy of Taiwan hotels, Int. J. Hosp. Manag, 31, pp. 972-980, (2012); Tarsakoo P., Charoensukmongkol P., Dimensions of social media marketing capabilities and their contribution to business performance of firms in Thailand, J. Asia Bus. Stud, 14, pp. 441-461, (2019); Pasadilla G.O., Wirjo A., Liu J., Promoting Ecommerce to Globalize MSME, (2017); Sethi K., Biswas B., Balodi K.C., Mobilizing B2B Electronic Marketplace: An Exploratory Study of Critical Success Factors among Indian Start-ups, Glob. Bus. Rev, (2021); Niu B., Li Q., Mu Z., Chen L., Ji P., Platform logistics or self-logistics? Restaurants’ cooperation with online food-delivery platform considering profitability and sustainability, Int. J. Prod. Econ, 234, (2021); Belarmino A., Raab C., Tang J., Han W., Exploring the motivations to use online meal delivery platforms: Before and during quarantine, Int. J. Hosp. Manag, 96, (2021); Wymer S.A., Regan E.A., Factors Influencing e-commerce Adoption and Use by Small and Medium Businesses, Electron. Mark, 15, pp. 438-453, (2005); Khoo V., Ahmi A., Saad R.A.-J., E-Commerce Adoption Research: A Review of Literature, J. Soc. Sci. Res, 6, pp. 90-99, (2018); Kshetri N., Barriers to e-commerce and competitive business models in developing countries: A case study, Electron. Commer. Res. Appl, 6, pp. 443-452, (2007); Abualrob A.A., Kang J., The barriers that hinder the adoption of e-commerce by small businesses, Inf. Dev, 32, pp. 1528-1544, (2016); MacGregor R.C., Vrazalic L., A basic model of electronic commerce adoption barriers, J. Small Bus. Enterp. Dev, 12, pp. 510-527, (2005); Definition of MSMEs; Levine D.M., Stephan D.F., Szabat K.A., Statistics for Manager Using Microsoft Excel, Glabal Edition, (2016); Robinson R.S., Purposive Sampling, Encyclopedia of Quality of Life and Well-Being Research, pp. 5243-5245, (2014); Etikan I., Comparison of Convenience Sampling and Purposive Sampling, Am. J. Theor. Appl. Stat, 5, (2016); Rahman M.S., The Advantages and Disadvantages of Using Qualitative and Quantitative Approaches and Methods in Language “Testing and Assessment” Research: A Literature Review, J. Educ. Learn, 6, pp. 102-112, (2016); Given L., Replication, The SAGE Encyclopedia of Qualitative Research Methods, pp. 755-756, (2008); Amore M.D., Murtinu S., Tobit models in strategy research: Critical issues and applications, Glob. Strategy J, 11, pp. 331-355, (2019); Long J.S., Regression Models for Categorical and Limited Dependent Variables, (1997); Amornkitvikai Y., Lee C., Determinants of E-Commerce Adoption and Utilisation by SMEs in Thailand, (2020); Vongsraluang N., Bhatiasevi V., The determinants of social commerce system success for SMEs in Thailand, Inf. Dev, 33, pp. 80-96, (2016); Amornkitvikai Y., Tham S.Y., Tangpoolcharoen J., Barriers and Factors Affecting E-commerce Utilization of Thai Small and Medium-Sized Enterprises in Food and Beverage and Retail Services, Glob. Bus. Rev, (2021)","W.W. Buachoom; KMITL Business School, King Mongkut’s Institute of Technology Ladkrabang, Bangkok, 10520, Thailand; email: wonlop.bu@kmitl.ac.th",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85137174053"]
["Zhen L.; Baldacci R.; Tan Z.; Wang S.; Lyu J.","Zhen, Lu (57150275500); Baldacci, Roberto (6602371948); Tan, Zheyi (57209306932); Wang, Shuaian (57195297860); Lyu, Junyan (57221165739)","57150275500; 6602371948; 57209306932; 57195297860; 57221165739","Scheduling heterogeneous delivery tasks on a mixed logistics platform",2022.0,"European Journal of Operational Research",298.0,2.0,null,680.0,698.0,18.0,3.0,"10.1016/j.ejor.2021.06.057","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85111678413&doi=10.1016%2fj.ejor.2021.06.057&partnerID=40&md5=584e61fe21a20eed125b56db96566345","School of Management, Shanghai University, Shanghai, China; Department of Electrical, Electronic, and Information Engineering, University of Bologna, Cesena, Italy; Department of Logistics & Maritime Studies, The Hong Kong Polytechnic University, Hong Kong","Zhen L., School of Management, Shanghai University, Shanghai, China; Baldacci R., Department of Electrical, Electronic, and Information Engineering, University of Bologna, Cesena, Italy; Tan Z., School of Management, Shanghai University, Shanghai, China; Wang S., Department of Logistics & Maritime Studies, The Hong Kong Polytechnic University, Hong Kong; Lyu J., School of Management, Shanghai University, Shanghai, China","Large e-commerce retailers usually establish their own logistics systems. Such systems make use of their own dedicated fleets but will also use a crowdsourced delivery mode by hiring occasional fleets. These mixed logistics systems with both dedicated and occasional fleets serve both retailers’ internal delivery tasks and external tasks requested by local businesses. This paper studies the problem of scheduling heterogeneous (internal and external) delivery tasks on a mixed logistics platform with multiple depots and two types of vehicles (dedicated and occasional). A delivery task is executed by either a dedicated vehicle or an occasional vehicle. The dedicated vehicles depart from and return to the platform's depots; the occasional vehicles depart from their original location and pick up goods from depots or external pickup locations, fulfill the delivery tasks, and finish their route at the final delivery location. We propose mixed integer programming models and column generation-based solution methods to solve the problem. A computational study is conducted based on a series of randomly generated instances and real-world instances involving 15 depots, 120 internal customers, 15 external delivery tasks, and 38 dedicated and occasional vehicles. The results obtained demonstrate the efficiency of the column generation-based solution methods. Moreover, the effectiveness of the proposed models is validated by a significant cost saving in comparison to intuitive decision rules. A sensitivity analysis is also conducted to derive a number of managerial implications. © 2021 Elsevier B.V.","Close-open mixed multi-depot vehicle routing problem; Crowdsourced delivery; e-commerce logistics; Heterogeneous fleet; Or in service industries","Crowdsourcing; Electronic commerce; Fleet operations; Integer programming; Location; Logistics; Pickups; Sales; Scheduling; Sensitivity analysis; Vehicle routing; Close-open mixed multi-depot vehicle routing problem; Column generation; Crowdsourced delivery; Delivery task; E-commerce logistic; Heterogeneous fleet; Logistics platforms; Logistics system; OR in service industries; Solution methods; Vehicles",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (71831008, 72025103, 72071173)","This research is supported by the National Natural Science Foundation of China (Grant No. 72025103 , 71831008 , 72071173 ).","Alnaggar A., Fatma G., Bookbinder J.H., Crowdsourced delivery: A review of platforms and academic literature, Omega, 98, (2021); Applegate D.L., Bixby R.E., Chavatal V., Cook W.J., The travelling salesman problem, a computational study, (2006); Archetti C., Speranza M.G., Vigo D., Chapter 10: vehicle routing problems with profits, Vehicle routing, pp. 273-297, (2014); Arslan A.M., Agatz N., Kroon L., Zuidwijk R., Crowdsourced delivery—A dynamic pickup and delivery problem with ad hoc drivers, Transportation Science, 53, 1, pp. 222-235, (2019); Azadeh A., Farrokhi-Asl H., The close-open mixed multi depot vehicle routing problem considering internal and external fleet of vehicles, Transportation Letters, 11, 2, pp. 78-92, (2019); Azi N., Gendreau M., Potvin J.Y., An exact algorithm for a vehicle routing problem with time windows and multiple use of vehicles, European Journal of Operational Research, 202, 3, pp. 756-763, (2010); Aziez I., Cote J.-F., Coelho L.C., Exact algorithms for the multi-pickup and delivery problem with time windows, European Journal of Operational Research, 284, 3, pp. 906-919, (2020); Baldacci R., Bartolini E., Mingozzi A., An exact algorithm for the pickup and delivery problem with time windows, Operations Research, 59, 2, pp. 414-426, (2011); Baldacci R., Mingozzi A., Roberti R., New route relaxation and pricing strategies for the vehicle routing problem, Operations Research, 59, 5, pp. 1269-1283, (2011); Baldacci R., Mingozzi A., Roberti R., Recent exact algorithms for solving the vehicle routing problem under capacity and time window constraints, European Journal of Operational Research, 218, 1, pp. 1-6, (2012); Baldacci R., Mingozzi A., Roberti R., Calvo R.W., An exact algorithm for the two-echelon capacitated vehicle routing problem, Operations Research, 61, 2, pp. 298-314, (2013); Battarra M., Cordeau J.-F., Iori M., Chapter 6: Pickup-and-delivery problems for goods transportation, Vehicle routing, pp. 161-191, (2014); Bergmann F.M., Wagner S.M., Winkenbach M., Integrating first-mile pickup and last-mile delivery on shared vehicle routes for efficient urban e-commerce distribution, Transportation Research Part B, 131, pp. 26-62, (2020); Bertsimas D., Jaillet P., Martin S., Online vehicle routing: The edge of optimization in large-scale applications, Operations Research, 67, 1, pp. 143-162, (2019); Brandao J., A memory-based iterated local search algorithm for the multi-depot open vehicle routing problem, European Journal of Operational Research, 284, 2, pp. 559-571, (2020); Casazza M., Ceselli A., Calvo R.W., A route decomposition approach for the single commodity split pickup and split delivery vehicle routing problem, European Journal of Operational Research, 289, 3, pp. 897-911, (2021); Chu C.W., Hsu H.L., A heuristic algorithm for multiple trip vehicle routing problems with time window constraint and outside carrier selection, Maritime Business Review, 4, 3, pp. 256-273, (2019); Clarke G., Wright. 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Wang K., Zhen L., Wang S., Laporte G., Column generation for integrated berth allocation, quay crane and yard assignment problem, Transportation Science, 52, 4, pp. 812-834, (2018); Wolfinger D., Salazar-Gonzalez J.-J., The pickup and delivery problem with split loads and transshipments: A branch-and-cut solution approach, European Journal of Operational Research, 289, 2, pp. 470-484, (2021); Yang H., Qin X., Ke J., Ye J., Optimizing matching time interval and matching radius in on-demand ride-sourcing markets, Transportation Research Part B, 131, pp. 84-105, (2020); Yao Y., Zhu X., Dong H., Wu S., Wu H., Tong L.C., Et al., ADMM-based problem decomposition scheme for vehicle routing problem with time windows, Transportation Researach Part B, 129, pp. 156-174, (2019)","S. Wang; Department of Logistics & Maritime Studies, The Hong Kong Polytechnic University, Hong Kong; email: wangshuaian@gmail.com",null,"Elsevier B.V.",{"$nulls":5},3772217.0,null,"EJORD",null,"English","Eur J Oper Res","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85111678413"]
["Arrieta-Prieto M.; Ismael A.; Rivera-Gonzalez C.; Mitchell J.E.","Arrieta-Prieto, Mario (57226028656); Ismael, Abdelrahman (57226788315); Rivera-Gonzalez, Carlos (57225214952); Mitchell, John E. (55478373700)","57226028656; 57226788315; 57225214952; 55478373700","Location of urban micro-consolidation centers to reduce the social cost of last-mile deliveries of cargo: A heuristic approach",2022.0,"Networks",79.0,3.0,null,292.0,313.0,21.0,7.0,"10.1002/net.22076","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85112638258&doi=10.1002%2fnet.22076&partnerID=40&md5=96c37dec0709902a5eba7eaa1dbe9edb","Department of Statistics, Universidad Nacional de Colombia, Bogotá, Colombia; Department of Civil and Environmental Engineering, Rensselaer Polytechnic Institute, Troy, NY, United States; Department of Mathematical Sciences, Rensselaer Polytechnic Institute, Troy, NY, United States","Arrieta-Prieto M., Department of Statistics, Universidad Nacional de Colombia, Bogotá, Colombia; Ismael A., Department of Civil and Environmental Engineering, Rensselaer Polytechnic Institute, Troy, NY, United States; Rivera-Gonzalez C., Department of Civil and Environmental Engineering, Rensselaer Polytechnic Institute, Troy, NY, United States; Mitchell J.E., Department of Mathematical Sciences, Rensselaer Polytechnic Institute, Troy, NY, United States","Urban deliveries of goods have become a rising challenge due to the increase of online shopping in addition to the traditional business-to-business (B2B) dynamics. To maintain a satisfactory level of service, carriers must conduct delivery operations under restrictive environments, creating undesirable externalities such as congestion and pollution. Urban micro-consolidation centers (UMCs) are defined as on-street or off-street spaces where all the deliveries within a certain radius are dropped and reconsolidated to be delivered by more sustainable last-leg modes. Their main purpose is to mitigate such negative externalities. This work formulates the last-mile delivery problem assisted by UMCs as a mixed-integer quadratically-constrained program and develops a greedy heuristic solution, inspired by the decomposition algorithms for large-scale optimization. The simulation results and a case study in Manhattan, New York show how the heuristic provides reasonable results with respect to the exact solution while also shedding light on how its solution can be utilized for freight-efficient urban design and policy planning. © 2021 Wiley Periodicals LLC.","bilevel mixed-integer program; decomposition algorithm; facility location; greedy heuristic; last-mile logistics; urban consolidation","Heuristic methods; Integer programming; Urban planning; Business to business; Decomposition algorithm; Delivery problems; Heuristic approach; Large-scale optimization; Manhattan , New York; Mixed integer quadratically constrained programs; Negative externalities; Heuristic algorithms",{"$nulls":6},"Alumur S., Kara B.Y., Network hub location problems: The state of the art, Eur. J. Oper. Res., 190, pp. 1-21, (2008); An analysis of the operational costs of trucking: 2018 update. Technical report, (2018); Baker L., (2020); Beardwood J., Halton J.H., Hammersley J.M., The shortest path through many points, Math. Proc. Cambridge Philos. Soc., 55, pp. 299-327, (1959); Boeing G., Urban spatial order: Street network orientation, configuration, and entropy, Appl. Netw. Sci., 4, (2019); Borland K.M., Ecommerce will continue to shape retail for years, (2019); Chen Q., Conway A., (2016); Conejo A.J., Castillo E., Minguez R., Garcia-Bertrand R., Decomposition techniques in mathematical programming: Engineering and science applications, (2006); Conway A., Fatisson P.E., Eickemeyer P., Cheng J., Peters D., (2012); Dempe S., Zemkoho A.B., The bilevel programming problem: Reformulations, constraint qualifications and optimality conditions, Math. Program., 138, pp. 447-473, (2013); Dolan S., (2019); Social cost of carbon, Technical report, (2016); Cost effectiveness tables summary, Technical report, (2017); Field B.C., Field M.K., Environmental economics: An introduction, 7th. McGraw-Hill Education, Sustain. Human Develop., (2016); Figliozzi M.A., Planning approximations to the average length of vehicle routing problems with varying customer demands and routing constraints, Transp. Res. Record, 2089, pp. 1-8, (2008); Haag M., Hu W., (2019); Intelligent last mile solutions for Hamburg, (2018); Holguin-Veras J., Necessary conditions for off-hour deliveries and the effectiveness of urban freight road pricing and alternative financial policies in competitive markets, Transp. Res. Part A: Pol. Practice, 42, pp. 392-413, (2008); Holguin-Veras J., Brom M., (2008); Holguin-Veras J., Encarnacion T., Gonzalez-Calderon C.A., Winebrake J., Wang C., Kyle S., Herazo-Padilla N., Kalahasthi L., Adarme W., Cantillo V., Yoshizaki H., Direct impacts of off-hour deliveries on urban freight emissions, Transp. Res. D Transp. Environ., 61, pp. 84-103, (2018); Kumar S.N., Panneerselvam R., A survey on the vehicle routing problem and its variants, Intell. Inf. Manage., 4, pp. 66-74, (2012); Mallozzi L., D'Amato E., Pardalos P.M., Spatial interaction models, (2017); Nagy G., Salhi S., Location-routing: Issues, models and methods, Eur. J. Oper. Res., 177, pp. 649-672, (2007); Pluto and map Pluto, (2019); Panero M.A., Shin H.S., Lopez D.P., Urban distribution centers: A means to reducing freight vehicle miles traveled, Technical report, (2011); Parr T., (2017); Radu G., Miller T., (2019); Rodrigue J.P., The geography of transport systems, (2020); Saharidis G.K., Ierapetritou M.G., Resolution method for mixed integer bi-level linear problems based on decomposition technique, J. Glob. Optim., 44, pp. 29-51, (2009); Sheth M., Butrina P., Goodchild A., McCormack E., Measuring delivery route cost trade-offs between electric-assist cargo bicycles and delivery trucks in dense urban areas, Eur. Transp. Res. Rev., 11, (2019); (2019); The Alliance for logistics innovation through collaboration in Europe and the European road transport advisory council, Urban freight - research and innovation roadmap, Technical report, (2015); Torentelle M., Tsamboulas D., Moraiti P., Elicitation of the good practices on urban freight transport, Technical report, (2012); Twisse F., Micro depots in Meisengasse, (2018); World urbanization prospects: The 2014 revision, Technical report, (2015); (2020); (2020); Ye J.J., Constraint qualifications and KKT conditions for bilevel programming problems, Math. Oper. Res., 31, pp. 811-824, (2006); Zaleski A., (2017)","M. Arrieta-Prieto; Department of Statistics, Universidad Nacional de Colombia, Bogotá, Colombia; email: mearrietap@unal.edu.co",null,"John Wiley and Sons Inc",{"$nulls":5},283045.0,null,null,null,"English","Networks","Article","Final",null,"Scopus","2-s2.0-85112638258"]
["Prajapati D.; Chan F.T.S.; Chelladurai H.; Lakshay L.; Pratap S.","Prajapati, Dhirendra (57215023349); Chan, Felix T. S. (7202586517); Chelladurai, H. (24075425500); Lakshay, Lakshay (57653390700); Pratap, Saurabh (56667217800)","57215023349; 7202586517; 24075425500; 57653390700; 56667217800","An Internet of Things Embedded Sustainable Supply Chain Management of B2B E-Commerce",2022.0,"Sustainability (Switzerland)",14.0,9.0,5066.0,null,null,null,18.0,"10.3390/su14095066","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85129113595&doi=10.3390%2fsu14095066&partnerID=40&md5=c23e1108f01f4a893cb6fb5826a2ff97","Department of Mechanical Engineering, Indian Institute of Information Technology, Design and Manufacturing, Jabalpur, 482005, India; Department of Decision Sciences, Macau University of Science and Technology, Taipa, Macao; Department of Mechanical Engineering, Indian Institute of Information Technology (BHU), Varanasi, 221005, India","Prajapati D., Department of Mechanical Engineering, Indian Institute of Information Technology, Design and Manufacturing, Jabalpur, 482005, India; Chan F.T.S., Department of Decision Sciences, Macau University of Science and Technology, Taipa, Macao; Chelladurai H., Department of Mechanical Engineering, Indian Institute of Information Technology, Design and Manufacturing, Jabalpur, 482005, India; Lakshay L., Department of Mechanical Engineering, Indian Institute of Information Technology (BHU), Varanasi, 221005, India; Pratap S., Department of Mechanical Engineering, Indian Institute of Information Technology (BHU), Varanasi, 221005, India","Adopting digital technologies in a business can help with sustainable supply chain management. These technologies can make e-commerce development faster and empower the emergence of B2B e-commerce businesses. In this study, our focus was to develop a framework for an Internet of things (IoT) embedded sustainable supply chain to deliver textile items using a B2B e-commerce business model. We formulated a mixed-integer non-linear programming (MINLP) model to minimize the total supply chain cost, including the B2B orders’ packaging, handling, and transportation, with carbon emission taxation. Furthermore, the purchasing cost of the RFID tags and IoT facilities that were provided on the transport vehicles was high. The proposed model was solved by using the global solver in the LINGO software package and finding the optimized value of the total supply chain network cost. We tested the proposed model in different case scenarios, i.e., small-to significant-sized problems. Then, a sensitivity analysis was performed to observe the variations in the overall cost of the supply chain network when there were changes in the main parameters of the proposed model. The results of the models showed that models can be helpful for efficient logistics planning and supply chain design. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.","Digital technologies; E-commerce; Internet of things (IoT); Logistics; Sustainable supply chain; Textile products","carbon emission; cost analysis; electronic commerce; Internet; sensitivity analysis; supply chain management; sustainability",{"$nulls":6},"Zhang Z., Growth Rate of Textile Industry across India FY 2010-FY 2020 This Statistic Illustrates the Growth Rate of Textile Industry across India from Fiscal Year 2010 to Fiscal Year 2020, The Growth Rate of Textile Industry across India Was Estimated to Be 8, (2022); Anitha K., Reddy K.P., Krishnamoorthy N., Jaiswal S., IoT’s in Enabling the Supply Chain Visibility and Connectivity and Optimization of Performance, Mater. Today Proc, (2021); Khan I.S., Ahmad M.O., Majava J., Industry 4.0 and Sustainable Development: A Systematic Mapping of Triple Bottom Line, Circular Economy and Sustainable Business Models Perspectives, J. Clean. Prod, 297, (2021); Sarkar B.D., Shankar R., Understanding the Barriers of Port Logistics for Effective Operation in the Industry 4.0 Era: Data-Driven Decision Making, Int. J. Inf. Manag. Data Insights, 1, (2021); Deepu T.S., Ravi V., Supply Chain Digitalization: An Integrated MCDM Approach for Inter-Organizational Information Systems Selection in an Electronic Supply Chain, Int. J. Inf. Manag. Data Insights, 1, (2021); Geissbauer R., Vedso J., Schrauf S., A Strategist’s Guide to Industry 4.0: Global Businesses Are about to Integrate Their Operations into a Seamless Digital Whole, and Thereby Change the World, pp. 1-15, (2016); Tan W.C., Sidhu M.S., Review of RFID and IoT Integration in Supply Chain Management, Oper. Res. 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Res, 58, pp. 5113-5131, (2020); Rejeb A., Simske S., Rejeb K., Treiblmaier H., Zailani S., Internet of Things Research in Supply Chain Management and Logistics: A Bibliometric Analysis, Internet Things, 12, (2020); Ekren B.Y., Mangla S.K., Turhanlar E.E., Kazancoglu Y., Li G., Lateral Inventory Share-Based Models for IoT-Enabled E-Commerce Sustainable Food Supply Networks, Comput. Oper. Res, 130, (2021); Muthu S.S., Sustainability in the Textile Industry: Textile Science and Clothing Technology, (2017); Acar E., Kilic M., Guner M., Measurement of Sustainability Performance in Textile Industry by Using a Multi-Criteria Decision-Making Method, Tekst. Konfeksiyon, 25, pp. 3-9, (2015); Shen B., Li Q., Dong C., Perry P., Sustainability Issues in Textile and Apparel Supply Chains, Sustainability, 9, (2017); Kazancoglu I., Kazancoglu Y., Yarimoglu E., Kahraman A., A Conceptual Framework for Barriers of Circular Supply Chains for Sustainability in the Textile Industry, Sustain. Dev, 28, pp. 1477-1492, (2020); Oelze N., Sustainable Supply Chain Management Implementation-Enablers and Barriers in the Textile Industry, Sustainability, 9, (2017); Nunes L.J.R., Godina R., Matias J.C.D.O., Technological Innovation in Biomass Energy for the Sustainable Growth of Textile Industry, Sustainability, 11, (2019); Muthu S.S., Gardetti M.A., Sustainability in the Textile and Apparel Industries: Sourcing Synthetic and Novel Alternative Raw Materials: Sustainable Textiles: Production, Processing, Manufacturing & Chemistry, (2020); Sadowski A., Dobrowolska B., Skowron-Grabowska B., Bujak A., Polish Textile and Apparel Industry: Global Supply Chain Management Perspective, Autex Res. J, 21, pp. 262-271, (2021); Hempel P.S., Kwong Y.K., B2B E-Commerce in Emerging Economies: I-Metal.Com’s Non-Ferrous Metals Exchange in China, J. Strateg. Inf. Syst, 10, pp. 335-355, (2001); Claycomb C., Iyer K., Germain R., Predicting the Level of B2B E-Commerce in Industrial Organizations, Ind. Mark. Manag, 34, pp. 221-234, (2005); Ma S., Li G., Liu M., Procurement Competition in the Presence of IoT-Enabled B2B E-Commerce, Electron. Commer. Res. Appl, 49, (2021); Prajapati D., Chan F.T.S., Daultani Y., Pratap S., Sustainable Vehicle Routing of Agro-Food Grains in the e-Commerce Industry, Int. J. Prod. Res, pp. 1-26, (2022); Zhang M., Pratap S., Zhao Z., Prajapati D., Huang G.Q., Forward and Reverse Logistics Vehicle Routing Problems with Time Horizons in B2C E-Commerce Logistics, Int. J. Prod. Res, 59, pp. 6291-6310, (2020); Garg R., Kiwelekar A.W., Netak L.D., Ghodake A., I-Pulse: A NLP Based Novel Approach for Employee Engagement in Logistics Organization, Int. J. Inf. Manag. Data Insights, 1, (2021); Kushwaha A.K., Kar A.K., Dwivedi Y.K., Applications of Big Data in Emerging Management Disciplines: A Literature Review Using Text Mining, Int. J. Inf. Manag. Data Insights, 1, (2021); Konstantakopoulos G.D., Gayialis S.P., Kechagias E.P., Papadopoulos G.A., Tatsiopoulos I.P., An Algorithmic Approach for Sustainable and Collaborative Logistics: A Case Study in Greece, Int. J. Inf. Manag. Data Insights, 1, (2021); Atabaki M.S., Khamseh A.A., Mohammadi M., A Priority-Based Firefly Algorithm for Network Design of a Closed-Loop Supply Chain with Price-Sensitive Demand, Comput. Ind. Eng, 135, pp. 814-837, (2019); Yadollahinia M., Teimoury E., Paydar M.M., Tire Forward and Reverse Supply Chain Design Considering Customer Relationship Management, Resour. Conserv. Recycl, 138, pp. 215-228, (2018); Prajapati D., Zhou F., Zhang M., Chelladurai H., Pratap S., Sustainable Logistics Network Design for Multi-Products Delivery Operations in B2B e-Commerce Platform, Sādhanā, pp. 1-13, (2021); Prajapati D., Kumar M.M., Pratap S., Chelladurai H., Zuhair M., Sustainable Logistics Network Design for Delivery Operations with Time Horizons in B2B E-Commerce Platform, Logistics, 5, (2021); Dwivedi A., Jha A., Prajapati D., Sreenu N., Pratap S., Meta-Heuristic Algorithms for Solving the Sustainable Agro-Food Grain Supply Chain Network Design Problem Supply Chains, Mod. Supply Chain Res. Appl, 7, pp. 2631-3971, (2020); Li G., Development of Cold Chain Logistics Transportation System Based on 5G Network and Internet of Things System, Microprocess. Microsyst, 80, (2021)","F.T.S. Chan; Department of Decision Sciences, Macau University of Science and Technology, Taipa, Macao; email: tschan@must.edu.mo",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85129113595"]
["Colaço R.; de Abreu e Silva J.","Colaço, Rui (57374364100); de Abreu e Silva, João (57767750900)","57374364100; 57767750900","Exploring the e-shopping geography of Lisbon: Assessing online shopping adoption for retail purchases and food deliveries using a 7-day shopping survey",2022.0,"Journal of Retailing and Consumer Services",65.0,null,102859.0,null,null,null,12.0,"10.1016/j.jretconser.2021.102859","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121240819&doi=10.1016%2fj.jretconser.2021.102859&partnerID=40&md5=5d06ebb92a9d8d097a56d95062d261fa","CERIS - Civil Engineering Research and Innovation for Sustainability, Department of Civil Engineering, Instituto Superior Técnico, Lisboa, 1049-001, Portugal","Colaço R., CERIS - Civil Engineering Research and Innovation for Sustainability, Department of Civil Engineering, Instituto Superior Técnico, Lisboa, 1049-001, Portugal; de Abreu e Silva J., CERIS - Civil Engineering Research and Innovation for Sustainability, Department of Civil Engineering, Instituto Superior Técnico, Lisboa, 1049-001, Portugal","E-shopping is growing globally, and the COVID-19 pandemic further accentuated this tendency. In this paper, online shopping adoption is analysed in Lisbon immediately before the pandemic outbreak. By focusing on an urban area, the impact of variables such as internet access or access to delivery services is controlled, thus enhancing the remaining components of the online purchase. The results show that online shopping is spatially dependent in an intraurban environment as a reflex of residential location preferences of different socioeconomic groups. Moreover, as internet access and delivery services become widespread, residential location preferences may come to explain e-shopping adoption both in urban and non-urban environments. The e-shopping geography of Lisbon suggests that age and affluence are determinants in explaining e-shopping adoption, with a marked distinction between central areas and more peripheral ones, some of which include extensive social housing projects. Hence, if retailers move online, shopping opportunities may become scarce for some consumers due to their socioeconomic status and consequent residential preferences. Nevertheless, strategic partnerships between retailers and the public sector may be devised to improve shopping opportunities. Physical stores can be encouraged to locate in areas where consumers are less prone to shop online. E-shopping adoption may also be encouraged by the public sector by promoting digital literacy, especially considering that the share of the older population is growing in Portugal as in most European countries. © 2021 Elsevier Ltd","e-shopping geography; Food deliveries; Residential preferences","Lisboa [Portugal]; Lisbon; Portugal; electronic commerce; food industry; retailing; shopping activity; survey",{"$nulls":4},"Fundação para a Ciência e a Tecnologia, FCT, (SFRH/BD/136003/2018)","The authors would like to thank Fundação para a Ciência e a Tecnologia ( FCT ) for Rui Colaço's PhD grant SFRH/BD/136003/2018 , and the two anonymous reviewers for their valuable comments and suggestions.","Airbnb, Get the data - inside Airbnb. 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Serv., (2022); Sheth J., Impact of Covid-19 on consumer behavior: will the old habits return or die?, J. Bus. Res., 117, pp. 280-283, (2020); Singleton A.D., Et al., Measuring the spatial vulnerability of retail centres to online consumption through a framework of e-resilience, Geoforum, 69, pp. 5-18, (2016); Uber, Uber Movement: let's find smarter ways forward, together, (2021); van Wee B., Witlox F., COVID-19 and its long-term effects on activity participation and travel behaviour: a multiperspective view, J. Transport Geogr., 95, March, (2021); Weltevreden J., Substitution or complementarity? How the Internet changes city centre shopping, J. Retailing Consum. Serv., 14, 3, pp. 192-207, (2007); Weltevreden J., Rotem-Mindali O., Mobility effects of b2c and c2c e-commerce in the Netherlands: a quantitative assessment, J. Transport Geogr., 17, 2, pp. 83-92, (2009); Xi G., Cao X., Zhen F., The impacts of same day delivery online shopping on local store shopping in Nanjing, China, Transport. Res. Pol. Pract., 136, pp. 35-47, (2020); Zehir C., Et al., E-S-Quality, perceived value and loyalty intentions relationships in internet retailers, Procedia - Social and Behavioral Sciences, 150, September, pp. 1071-1079, (2014); Zhai Q., Et al., The interactions between e-shopping and store shopping in the shopping process for search goods and experience goods, Transportation, 44, 5, pp. 885-904, (2017)","R. Colaço; CERIS - Civil Engineering Research and Innovation for Sustainability, Department of Civil Engineering, Instituto Superior Técnico, Lisboa, 1049-001, Portugal; email: r.colaco@tecnico.ulisboa.pt",null,"Elsevier Ltd",{"$nulls":5},9696989.0,null,null,null,"English","J. Retail. Consum. Serv.","Article","Final",null,"Scopus","2-s2.0-85121240819"]
["Zhao J.","Zhao, Jinfang (57217044243)",5.7217044243E10,"Study on the cost allocation method to maximize the benefit of e-commerce enterprises in the cloud computing environment",2022.0,"Concurrency and Computation: Practice and Experience",34.0,13.0,"e5889",null,null,null,0.0,"10.1002/cpe.5889","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85085936956&doi=10.1002%2fcpe.5889&partnerID=40&md5=8014aebfa3b2af3d35e85c42f7aeccfc","Department of Business Administration, Tourism College of Zhejiang, Hangzhou, China","Zhao J., Department of Business Administration, Tourism College of Zhejiang, Hangzhou, China","Cloud computing is a brand-new IT service delivery model. It is a key strategic technology and means to lead the innovation of the information industry in the future. It can effectively solve the dynamic demand and final cost of e-commerce enterprise resources, and it can reduce costs for e-commerce enterprises to improve management, promote information development, and achieve resource integration. It is a key factor in shaping and enhancing the competitiveness of enterprises. Fuzzy paradigm should be understood and used at the level of world view and methodology, and should be recognized that it has different forms and properties in different disciplines. Based on the cloud computing environment, this article proposes a task allocation model, taking into account the utility functions of different users, and maximizing the overall terminal benefits by assigning computational tasks on a large number of terminals to virtual machine instances. The simulation results show that the overall benefit of the terminal under this allocation model is significantly higher than that of the overall terminal under the centralized task allocation model. © 2020 John Wiley & Sons, Ltd.","cloud computing; cost allocation; maximize; task assignment; ubiquitous computing","Cloud computing; Competition; Electronic commerce; Enterprise resource management; Information management; Cloud computing environments; Computational task; E-commerce enterprise; Information development; Information industry; Resource integration; Strategic technologies; Utility functions; Costs",{"$nulls":6},"Aminsoofi A., Irfan Khan M., Fazaleamin F.A., A review on data security in cloud computing, Int J Comput Appl, 96, 2, pp. 95-96, (2017); Zheng Z., Huang T., Zhang H., Sun S., Wen J., Wang P., Towards a resource migration method in cloud computing based on node failure rule, J Intell Fuzzy Syst, 31, 5, pp. 2611-2618, (2016); Huang Z., Tang J., Shan G., Ni J., Chen Y., Wang C., An efficient passenger-hunting recommendation framework with multitask deep learning, IEEE IoT J, 6, pp. 7713-7721, (2019); Albertario L., (2015); Zheng Z., Zheng Z., Towards an improved heuristic genetic algorithm for static content delivery in cloud storage, Comput Electr Eng, 12, 5, pp. 25-32, (2017); Yan Y., Guo P., Cheng B., Zheng Z., An experimental case study on the relationship between workload and resource consumption in a commercial web server, J Comput Sci, 5, 9, pp. 324-330, (2017); Dikaiakos M.D., Katsaros D., Mehra P., Pallis G., Vakali A., Cloud computing: distributed internet computing for IT and scientific research, IEEE Internet Comput, 13, 5, pp. 10-13, (2009); Yang X., Wallom D., Waddington S., Et al., Cloud computing in e-science: research challenges and opportunities, J Supercomput, 70, 1, pp. 408-464, (2014); Sundarraj R.P., Venkatraman S., (2015); Mishra J., Dash S.K., Dash S., (2012); Wang L., Liu X., Lin E.A., A new generation intelligent cloud computing data center of China's civil aviation, Comput Moderniz, (2016); Yang L., Cao J., Yuan Y., Li T., Han A., Chan A., A framework for partitioning and execution of data stream applications in mobile cloud computing, ACM Sigmetr Perform Evaluat Rev, 40, 4, pp. 23-32, (2013); Akter S., Wamba S.F., Big data analytics in E-commerce: a systematic review and agenda for future research, Electron Markets, 26, 2, pp. 1-22, (2016); Zhao W.X., Li S., Chang E.Y., Et al., Connecting social media to E-commerce: cold-start product recommendation using microblogging information, IEEE Trans Knowl Data Eng, 28, 5, pp. 1147-1159, (2016); Zhang X.Z., (2007); Lan M., Cloud computing: rebuilding EPC management mode, Appl Mech Mater, 170-173, pp. 3603-3616, (2012); Weihua W.U., Research on development patterns of EC based on \"cloud computing, J Intell, 15, 4, pp. 48-56, (2011); Wen Y., Zhang W., Luo H., (2012); Cuervo E., Balasubramanian A., Cho D., Et al., (2010); Aggarwal B., Chitnis P., Dey A., Et al., (2011); Huang Z., Shan G., Cheng J., Sun J., TRec: an efficient recommendation system for hunting passengers with deep neural networks, Neural Comput Appl, 31, S1, pp. 209-222, (2019)","J. Zhao; Department of Business Administration, Tourism College of Zhejiang, Hangzhou, China; email: gjam21@163.com",null,"John Wiley and Sons Ltd",{"$nulls":5},1.5320626E7,null,"CCPEB",null,"English","Concurr. Comput. Pract. Exper.","Article","Final",null,"Scopus","2-s2.0-85085936956"]
["Prajapati D.; Zhou F.; Dwivedi A.; Singh T.; Lakshay L.; Pratap S.","Prajapati, Dhirendra (57215023349); Zhou, Fuli (57189093462); Dwivedi, Ashish (57208524270); Singh, Tripti (57216981666); Lakshay, Lakshay (57653390700); Pratap, Saurabh (56667217800)","57215023349; 57189093462; 57208524270; 57216981666; 57653390700; 56667217800","Sustainable Agro-Food Supply Chain in E-Commerce: Towards the Circular Economy",2022.0,"Sustainability (Switzerland)",14.0,14.0,8698.0,null,null,null,7.0,"10.3390/su14148698","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137173009&doi=10.3390%2fsu14148698&partnerID=40&md5=cf5809e31b865ee57d26d9e630dda854","Department of Mechanical Engineering, Indian Institute of Information Technology, Design and Manufacturing, Jabalpur, 452005, India; School of Economics and Management, Zhengzhou University of Light Industry, Zhengzhou, 450000, China; Jindal Global Business School, O.P. Jindal Global University, Sonipat, 131029, India; Department of Mechanical Engineering, Indian Institute of Technology (BHU), Varanasi, 221005, India","Prajapati D., Department of Mechanical Engineering, Indian Institute of Information Technology, Design and Manufacturing, Jabalpur, 452005, India; Zhou F., School of Economics and Management, Zhengzhou University of Light Industry, Zhengzhou, 450000, China; Dwivedi A., Jindal Global Business School, O.P. Jindal Global University, Sonipat, 131029, India; Singh T., Department of Mechanical Engineering, Indian Institute of Information Technology, Design and Manufacturing, Jabalpur, 452005, India; Lakshay L., Department of Mechanical Engineering, Indian Institute of Technology (BHU), Varanasi, 221005, India; Pratap S., Department of Mechanical Engineering, Indian Institute of Technology (BHU), Varanasi, 221005, India","The continuous decline in the sustainable agro-food supply chain (AFSC) towards a Circular Economy (CE) has become a matter of great concern for the key stakeholders, including government organizations, businesses, end-users, and farmers. In line with this, the main purpose of this study is to develop a sustainable food Supply Chain Network (SCN). The SCN enables the collection of agro-food grains from different farmers’ locations and delivers the same to food processing units. To design an efficient and effective sustainable pickup and delivery network, a Mixed-Integer Non-Linear Programming (MINLP) mathematical model is formulated. The proposed model achieves the sustainability goal by minimizing the collection costs. The developed MINLP model is solved by using an exact optimization approach in LINGO 18 software. Further, to test the efficacy of the developed model, various computational experiments are performed, varying from small to large size data. The results of these experiments reflect that our model can support businesses in designing an efficient and effective sustainable pickup and delivery network. Lastly, it has been shown that innovative packaging materials can help to minimize the wastage of food. © 2022 by the authors.","circular economy (CE); cost factor innovative food packaging materials; e-commerce supply chain; environmental sustainability; exact optimization","electronic commerce; food processing; government; optimization; supply chain management; sustainability",{"$nulls":6},"Yadav G., Luthra S., Jakhar S.K., Mangla S.K., Rai D.P., A Framework to Overcome Sustainable Supply Chain Challenges through Solution Measures of Industry 4.0 and Circular Economy: An Automotive Case, J. Clean. Prod, 254, (2020); Cammarano A., Perano M., Michelino F., Del Regno C., Caputo M., SDG-Oriented Supply Chains: Business Practices for Procurement and Distribution, Sustainability, 14, (2022); Dwivedi A., Agrawal D., Jha A., Gastaldi M., Paul S.K., D'Adamo I., Addressing the Challenges to Sustainable Initiatives in Value Chain Flexibility: Implications for Sustainable Development Goals, Glob. J. Flex. Syst. Manag, 22, pp. 179-197, (2021); Casali G.L., Perano M., Tartaglione A.M., Zolin R., How Business Idea Fit Affects Sustainability and Creates Opportunities for Value Co-Creation in Nascent Firms, Sustainability, 10, (2018); Dwivedi A., Jha A., Prajapati D., Sreenu N., Pratap S., Meta-Heuristic Algorithms for Solving the Sustainable Agro-Food Grain Supply Chain Network Design Problem, Mod. Supply Chain. Res. Appl, 2, pp. 161-177, (2020); Langley S., Phan-le N.T., Brennan L., Parker L., Jackson M., Francis C., Lockrey S., Verghese K., Alessi N., The Good, the Bad, and the Ugly: Food Packaging and Consumers, Sustainability, 13, (2021); Dwivedi A., Jha A., Yadav V., Bansal M., Srivastava H., A Framework for Blockchain Technology Adoption in Food Supply Chain, Operations and Supply Chain Management in the Food Industry, pp. 95-114, (2022); Rupo D., Perano M., Centorrino G., Sanchez A.V., A Framework Based on Sustainability, Open Innovation, and Value Cocreation Paradigms-A Case in an Italian Maritime Cluster, Sustainability, 10, (2018); Dwivedi A., Paul S.K., A framework for digital supply chains in the era of circular economy: Implications on environmental sustainability, Bus. Strat. Environ, 31, pp. 1249-1274, (2022); Prajapati D., Chan F.T.S., Daultani Y., Pratap S., Sustainable Vehicle Routing of Agro-Food Grains in the e-Commerce Industry, Int. J. Prod. Res, pp. 1-26, (2022); Beltran M., Tjahjono B., Bogush A., Juliao J., Teixeira E.L.S., Food Plastic Packaging Transition towards Circular Bioeconomy: A Systematic Review of Literature, Sustainability, 13, (2021); Meherishi L., Narayana S.A., Ranjani K.S., Sustainable Packaging for Supply Chain Management in the Circular Economy: A Review, J. Clean. Prod, 237, (2019); Bauer A., Tacker M., Uysal-unalan I., Cruz R.M.S., Varzakas T., Krauter V., Recyclability and Redesign Challenges in Multilayer Flexible Food Packaging—A Review, Foods, 10, (2021); Matthews C., Moran F., Jaiswal A.K., A Review on European Union’s Strategy for Plastics in a Circular Economy and Its Impact on Food Safety, J. Clean. Prod, 283, (2021); Schmidt Rivera X.C., Leadley C., Potter L., Azapagic A., Aiding the Design of Innovative and Sustainable Food Packaging: Integrating Techno-Environmental and Circular Economy Criteria, Energy Procedia, 161, pp. 190-197, (2019); Guillard V., Gaucel S., Fornaciari C., Angellier-Coussy H., Buche P., Gontard N., The Next Generation of Sustainable Food Packaging to Preserve Our Environment in a Circular Economy Context, Front. Nutr, 5, (2018); Maiyar L.M., Thakkar J.J., Robust Optimisation of Sustainable Food Grain Transportation with Uncertain Supply and Intentional Disruptions, Int. J. Prod. Res, 58, pp. 5651-5675, (2020); Kapoor R., Ghosh P., Kumar M., Sengupta S., Gupta A., Kumar S.S., Vijay V., Kumar V., Kumar Vijay V., Pant D., Valorization of Agricultural Waste for Biogas Based Circular Economy in India: A Research Outlook, Bioresour. 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Eng, 109, pp. 369-389, (2017); Patidar R., Venkatesh B., Pratap S., Daultani Y., A Sustainable Vehicle Routing Problem for Indian Agri-Food Supply Chain Network Design, Proceedings of the 2018 International Conference on Production and Operations Management Society (POMS), pp. 1-5; Patidar R., Agrawal S., Pratap S., Development of Novel Strategies for Designing Sustainable Indian Agri-Fresh Food Supply Chain, Sadhana-Acad. Proc. Eng. Sci, 43, (2018); Parashar S., Sood G., Agrawal N., Modelling the Enablers of Food Supply Chain for Reduction in Carbon Footprint, J. Clean. Prod, 275, (2020); Mogale D.G., Cheikhrouhou N., Tiwari M.K., Modelling of Sustainable Food Grain Supply Chain Distribution System: A Bi-Objective Approach, Int. J. Prod. Res, 58, pp. 5521-5544, (2020); Kappelman A.C., Sinha A.K., Optimal Control in Dynamic Food Supply Chains Using Big Data, Comput. Oper. Res, 126, (2021); Esteso A., Alemany M.M.E., Ortiz A., Impact of Product Perishability on Agri-Food Supply Chains Design, Appl. Math. Model, 96, pp. 20-38, (2021); Prajapati D., Zhou F., Zhang M., Chelladurai H., Pratap S., Sustainable Logistics Network Design for Multi-Products Delivery Operations in B2B e-Commerce Platform, Sādhanā, 46, (2021); Prajapati D., Kumar M.M., Pratap S., Chelladurai H., Zuhair M., Sustainable Logistics Network Design for Delivery Operations with Time Horizons in B2B E-Commerce Platform, Logistics, 5, (2021); Prajapati D., Zhou F., Cheikhrouhou N., Pratap S., Minimizing the Time Window for Delivery of Orders in B2B E- Commerce, Proceedings of the 5th International Conference on Industrial Engineering (ICIE), pp. 1-6; Zarbakhshnia N., Soleimani H., Goh M., Razavi S.S., A Novel Multi-Objective Model for Green Forward and Reverse Logistics Network Design, J. Clean. Prod, 208, pp. 1304-1316, (2019); Prajapati D., Chan F.T.S., Chelladurai H., Lakshay L., Pratap S., An Internet of Things Embedded Sustainable Supply Chain Management of B2B E-Commerce, Sustainability, 14, (2022); Rao H.S., Reducing Carbon Emissions from Transport Projects, 16, pp. 1-96, (2010); Ciccullo F., Cagliano R., Bartezzaghi G., Perego A., Implementing the Circular Economy Paradigm in the Agri-Food Supply Chain: The Role of Food Waste Prevention Technologies, Resour. Conserv. Recycl, 164, (2021)","A. Dwivedi; Jindal Global Business School, O.P. Jindal Global University, Sonipat, 131029, India; email: ashish0852@gmail.com",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85137173009"]
["Ornati M.; Picco-Schwendener A.; Marazza S.","Ornati, Michela (57218095146); Picco-Schwendener, Anna (36185763100); Marazza, Suzanna (57761395300)","57218095146; 36185763100; 57761395300","Sizing up the body: Virtual fit platforms in fashion e-commerce",2022.0,"International Journal of Fashion Studies",9.0,1.0,null,199.0,218.0,19.0,3.0,"10.1386/infs_00066_1","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85132666691&doi=10.1386%2finfs_00066_1&partnerID=40&md5=0fae7bae9ceec86a828af8027ad351a6","Università della Svizzera italiana (USI), Via Giuseppe Buffi 13, Lugano, CH-6904, Switzerland; University of Applied Sciences of Southern Switzerland (SUPSI), Via Cantonale 16E, Manno, CH-6928, Switzerland","Ornati M., Università della Svizzera italiana (USI), Via Giuseppe Buffi 13, Lugano, CH-6904, Switzerland, University of Applied Sciences of Southern Switzerland (SUPSI), Via Cantonale 16E, Manno, CH-6928, Switzerland; Picco-Schwendener A., Università della Svizzera italiana (USI), Via Giuseppe Buffi 13, Lugano, CH-6904, Switzerland; Marazza S., Università della Svizzera italiana (USI), Via Giuseppe Buffi 13, Lugano, CH-6904, Switzerland","Dress is an embodied experience which is dematerialized online. In a fashion e-commerce website, clothes cannot be touched, nor worn prior to purchase and delivery; this engenders issues of fit and thus, returns. To solve this issue, fashion companies are turning to size recommendation and virtual fit service platforms. Simply put, virtual fit systems algorithmically match customer body data to fashion items which are potentially the right size and fit. This process aims to create value for all parties involved: for brands, by improving customer satisfaction and reducing returns; for customers, by facilitating choices; and for platform providers, by the sale of services and tools. However, as research in online platforms in other fields suggests (van Dijck 2014: 197; van Dijck et al. 2018), virtual fit services are driven by mechanisms of datafication, curation and commodification of fashion consumers’ bodily data – which in turn raise issues related to privacy and inclusivity. To the best of the authors’ knowledge, virtual fit platforms and their effects on the datafication of dress embodiment have heretofore not been discussed in fashion studies literature. This article spotlights the growing phenomena, open-ing avenues for further research in the field. © 2022 Intellect Ltd Article. English language.","body scanning; datafication; digital fashion; fashion e-commerce; personalization; privacy; sizing; virtual fit",{"$nulls":7},"Can the promise of a perfect fit disrupt fashion?, Morgan Stanley, (2018); Arnett George, Sizing tech takes on fashion’s expensive returns problem, Vogue Business, (2019); Opinion 05/2014 on Anonymisation Techniques, (2014); Guidelines on Automated Individual Decision-Making and Profiling for the Purpose of Regulation, (2018); Barassi Veronica, Child Data Citizen: How Tech Companies are Profiling us from Before Birth, (2020); Baytar Fatma, Chung Telin, Shin Eonyou, Evaluating garments in augmented reality when shopping online, Journal of Fashion Marketing and Management: An International Journal, 24, 4, pp. 667-683, (2020); Beck Marie, Crie Dominique, I virtually try it … I want it! 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Fash. Stud.","Article","Final",null,"Scopus","2-s2.0-85132666691"]
["Vazquez-Noguerol M.; Comesaña-Benavides J.; Poler R.; Prado-Prado J.C.","Vazquez-Noguerol, Mar (57204391550); Comesaña-Benavides, Jose (55279823300); Poler, Raul (22734966200); Prado-Prado, J. Carlos (6506733203)","57204391550; 55279823300; 22734966200; 6506733203","An optimisation approach for the e-grocery order picking and delivery problem",2022.0,"Central European Journal of Operations Research",30.0,3.0,null,961.0,990.0,29.0,15.0,"10.1007/s10100-020-00710-9","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85091300311&doi=10.1007%2fs10100-020-00710-9&partnerID=40&md5=736c8fc3f32c48c52f4fc797f059da9f","Grupo de Ingeniería de Organización (GIO), Business Organization and Marketing Department, School of Industrial Engineering, University of Vigo, Galicia, Spain; Research Centre on Production Management and Engineering (CIGIP), Universitat Politècnica de València, Plaza Ferrándiz y Carbonell, 2, Alicante, Alcoy, 03801, Spain","Vazquez-Noguerol M., Grupo de Ingeniería de Organización (GIO), Business Organization and Marketing Department, School of Industrial Engineering, University of Vigo, Galicia, Spain; Comesaña-Benavides J., Grupo de Ingeniería de Organización (GIO), Business Organization and Marketing Department, School of Industrial Engineering, University of Vigo, Galicia, Spain; Poler R., Research Centre on Production Management and Engineering (CIGIP), Universitat Politècnica de València, Plaza Ferrándiz y Carbonell, 2, Alicante, Alcoy, 03801, Spain; Prado-Prado J.C., Grupo de Ingeniería de Organización (GIO), Business Organization and Marketing Department, School of Industrial Engineering, University of Vigo, Galicia, Spain","Traditional supermarket chains that are adopting an omni-channel approach must now carry out the order picking and delivery processes to serve online orders, previously done by the customer. The complexity of the logistics processes has increased, therefore modelling and optimising e-grocery operations becomes definitely important. Since there are few studies modelling order picking and delivery processes, we propose an approach that simultaneously optimises the decision variables of different functions which have traditionally been treated separately. In this study, we present a linear programming model for store-based e-fulfilment strategies with multiple picking locations. The proposed model optimises the allocation of online orders to stores, based on the e-fulfilment costs. As well as minimising the picking and delivery costs, the proposed approach consolidates workloads in order to avoid idle times and reduce the amount of resources required. A weighted sum method is applied to compute the solution, integrating parameters that represent different store features such as the product range, sales mode and physical store activities. The proposed model has been tested on one of the largest grocery sellers, showing that substantial savings can be achieved by reallocating orders to different stores, time windows and delivery vehicles. By focusing on optimising e-fulfilment resources, this approach serves as a guide for traditional grocery sellers to redesign their supply chains and to facilitate decision-making at a managerial level. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature.","e-commerce; e-grocery; MILP; Omni-channel retailing; Optimisation; Order fulfilment",{"$nulls":5},"Universidade de Vigo","Funding was provided by Universidade de Vigo.","Agatz N., Campbell A., Fleischmann M., Savelsbergh M., Time slot management in attended home delivery, Transp Sci, 45, 3, pp. 435-449, (2011); Aksoy A., Integrated model for renewable energy planning in Turkey, Int J Green Energy, 16, 1, pp. 34-48, (2019); Al-nawayseh M.K., Alnabhan M.M., Al-Debei M.M., Balachandran W., An adaptive decision support system for last mile logistics in E-commerce: a study on online grocery shopping, Int J Decis Support Syst Technol, 5, 1, pp. 40-65, (2013); Chapter 10: Vehicle routing problems with profits. 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Vazquez-Noguerol; Grupo de Ingeniería de Organización (GIO), Business Organization and Marketing Department, School of Industrial Engineering, University of Vigo, Galicia, Spain; email: marfernandezvazquez@uvigo.es",null,"Springer Science and Business Media Deutschland GmbH",{"$nulls":5},"1435246X",null,null,null,"English","Cent. Eur. J. Oper. Res.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85091300311"]
["Kang N.; Shen H.; Xu Y.","Kang, Ningxuan (56378210700); Shen, Hao (57204198554); Xu, Ye (57803616200)","56378210700; 57204198554; 57803616200","JD.com Improves Delivery Networks by a Multiperiod Facility Location Model",2022.0,"Interfaces",52.0,2.0,null,133.0,148.0,15.0,2.0,"10.1287/inte.2021.1077","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85134213903&doi=10.1287%2finte.2021.1077&partnerID=40&md5=029d1c2bd0e14d5165b8416cc79624af","JD.com, Beijing, 100101, China; School of Business, Renmin University of China, Beijing, 100872, China; Bianlifeng, Beijing, 100028, China","Kang N., JD.com, Beijing, 100101, China; Shen H., School of Business, Renmin University of China, Beijing, 100872, China; Xu Y., Bianlifeng, Beijing, 100028, China","Because delivery systems play an increasingly significant role in modern life, it is of strategical importance to design an efficient and adaptive delivery network. JD.com is the largest business-to-consumer e-commerce company by revenue in China and has built the largest amount of logistics infrastructure nationwide. In this study, we developed an optimization model to automatically make annual plans of the delivery stations that minimize operational costs. We built an optimization algorithm by adopting a multiperiod facility location model a using mixed-integer linear programming (MILP) method and proposing applicable techniques to solve the model. The results demonstrate that our model generates improved plans compared with manually planning in terms of both operational cost and delivery distance. The tool described in this paper helps JD.com save on delivery costs and gain operational benefits in designing delivery networks. © 2021 INFORMS","delivery networks; dynamic facility location problem; mixed-integer linear programming",{"$nulls":5},"National Natural Science Foundation of China, NSFC, (72001206)","History: This paper was refereed. Funding: This work was supported by the National Natural Science Foundation of China [Grant 72001206].","Aardal K, Capacitated facility location: Separation algorithm and computational experience, Math. Programming, 81, pp. 149-175, (1998); Aktas E, Ozaydin O, Bozkaya B, Ulengin F, Onsel S, Optimizing fire station locations for the Istanbul Metropolitan Municipality, Interfaces, 43, 3, pp. 240-255, (2013); Allen JD, Tobin RL, Calderan A, Verizon optimizes work center locations to reduce installation and repair operations costs, Interfaces, 47, 2, pp. 111-121, (2017); Arabani AB, Farahani RZ, Facility location dynamics: An overview of classifications and applications, Comput. Indust. Engrg, 62, 1, pp. 408-420, (2012); Canel C, Khumawala BM, Multi-period international facilities location: An algorithm and application, Internat. J. 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Res, 263, 1, pp. 173-187, (2017); van den Berg PL, Legemaate GAG, van der Mei RD, Increasing the responsiveness of firefighter services by relocating base stations in Amsterdam, Interfaces, 47, 4, pp. 352-361, (2017); Wesolowsky GO, Truscott WG, The multiperiod location-allocation problem with relocation of facilities, Management Sci, 22, 1, pp. 57-65, (1975); Xie S, Chen X, Wang Z, Ouyang Y, Somani K, Huang J, Integrated planning for multiple types of locomotive work facilities under location, routing, and inventory considerations, Interfaces, 46, 5, pp. 391-408, (2016)","H. Shen; School of Business, Renmin University of China, Beijing, 100872, China; email: shenhao@rmbs.ruc.edu.cn",null,"INFORMS Inst.for Operations Res.and the Management Sciences",{"$nulls":5},922102.0,null,null,null,"English","Interfaces","Article","Final",null,"Scopus","2-s2.0-85134213903"]
["Yu H.; Huang M.; Chao X.; Yue X.","Yu, Hao (57226769487); Huang, Min (57996768400); Chao, Xiuli (7005883607); Yue, Xiaohang (15838243100)","57226769487; 57996768400; 7005883607; 15838243100","Truthful multi-attribute multi-unit double auctions for B2B e-commerce logistics service transactions",2022.0,"Transportation Research Part E: Logistics and Transportation Review",164.0,null,102814.0,null,null,null,11.0,"10.1016/j.tre.2022.102814","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85133284967&doi=10.1016%2fj.tre.2022.102814&partnerID=40&md5=b7b2a2cdc2815d3b076efa7f31e4a071","College of Information Science and Engineering, State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Liaoning, Shenyang, 110819, China; Department of Industrial and Operations Engineering, University of Michigan, Ann Arbor, 48109, MI, United States; University of Wisconsin Milwaukee, Milwaukee, 53201, WI, United States","Yu H., College of Information Science and Engineering, State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Liaoning, Shenyang, 110819, China; Huang M., College of Information Science and Engineering, State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Liaoning, Shenyang, 110819, China; Chao X., Department of Industrial and Operations Engineering, University of Michigan, Ann Arbor, 48109, MI, United States; Yue X., University of Wisconsin Milwaukee, Milwaukee, 53201, WI, United States","This study investigates truthful multi-attribute multi-unit double auction mechanism design problem for B2B e-commerce logistics service transactions (LSTs). The optimization problem of the auctioneer is modeled as an integer program to maximize social welfare where the utility of shippers is related to their monetary profits and non-price attributes of corresponding carriers. To handle the information asymmetry of price and non-price attributes, a Multi-Attribute Multi-unit Trade Reduction (MA-MTR) mechanism is proposed to resolve the problem in a decentralized setting. A family of Enhanced Multi-Attribute Multi-unit Trade Reduction (E-MA-MTR) mechanisms is then designed to achieve fair allocation and capture the auctioneer's tradeoff between various operational objectives. A family of Improved Multi-Attribute Multi-unit Trade Reduction (I-MA-MTR) auction mechanisms with elaborate efficiency-loss-alleviation strategies is further proposed to ameliorate efficiency performance. Theoretical analysis manifests that all above mechanisms satisfy incentive compatibility (IC), balanced budget (BB), individual rationality (IR) and asymptotical efficiency (AsE). Numerical results further demonstrate the superiority of the MA-MTR mechanism over its single-attribute counterpart, verify the effectiveness of relevant strategies in the E-MA-MTR and I-MA-MTR mechanisms and shed light on the choice of alternative mechanisms. © 2022 Elsevier Ltd","Incentive compatibility; Logistics service transactions; Mechanism design; Multi-attribute auction; Truthful double auction","Budget control; Electronic commerce; Integer programming; Machine design; Double auction; Incentive compatibility; Logistic service transaction; Logistics services; Mechanism design; Multi-attribute auction; Multi-attributes; Multi-unit; Reduction mechanisms; Truthful double auction; auction; design; electronic commerce; incentive; logistics; optimization; service sector; Efficiency",{"$nulls":4},"111 Project 2.0, (B08015); Fundamental Research Funds for State Key Laboratory of Synthetical Automation for Process Industries, (2013ZCX11); National Natural Science Foundation of China, NSFC, (71620107003); Liaoning Revitalization Talents Program, (XLYC1802115)","This work is supported by the NSFC Major International (Regional) Joint Research Project Grant No. 71620107003; the Liaoning Revitalizing Talent Program No. XLYC1802115; the Fundamental Research Funds for State Key Laboratory of Synthetical Automation for Process Industries Grant No. 2013ZCX11; the 111 Project 2.0 (No. B08015). 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B: Meth., 56, pp. 136-160, (2013); Zhang B.O., Yao T., Friesz T.L., Sun Y., A tractable two-stage robust winner determination model for truckload service procurement via combinatorial auctions[J], Transport. Res. B-Meth., 78, pp. 16-31, (2015); Zhang J., Xiang J., Cheng T.C.E., Hua G., Chen C., An optimal efficient multi-attribute auction for transportation procurement with carriers having multi-unit supplies[J], Omega, 83, pp. 249-260, (2019); Zhang Q., Wang Z., Huang M., Yu Y., Fang S., Heterogeneous multi-depot collaborative vehicle routing problem[J], Transport. Res. B: Meth., 160, pp. 1-20, (2022)","M. Huang; Northeastern University (NEU), Shenyang, Liaoning, 110004, China; email: mhuang@mail.neu.edu.cn",null,"Elsevier Ltd",{"$nulls":5},1.3665545E7,null,null,null,"English","Transp. Res. Part E Logist. Transp. Rev.","Article","Final",null,"Scopus","2-s2.0-85133284967"]
["Rodionov D.; Kryzhko D.; Tenishev T.; Uimanov V.; Abdulmanova A.; Kvikviniia A.; Aksenov P.; Solovyov M.; Kolomenskii F.; Konnikov E.","Rodionov, Dmitriy (56087793300); Kryzhko, Darya (57221203892); Tenishev, Timur (57728557000); Uimanov, Victor (57728344300); Abdulmanova, Alsu (57728557100); Kvikviniia, Ani (57728132300); Aksenov, Pavel (57219607023); Solovyov, Mark (57728132400); Kolomenskii, Fedor (57728344400); Konnikov, Evgenii (57195328037)","56087793300; 57221203892; 57728557000; 57728344300; 57728557100; 57728132300; 57219607023; 57728132400; 57728344400; 57195328037","Methodology for Assessing the Digital Image of an Enterprise with Its Industry Specifics",2022.0,"Algorithms",15.0,6.0,177.0,null,null,null,14.0,"10.3390/a15060177","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85131367297&doi=10.3390%2fa15060177&partnerID=40&md5=ae31b7316d16ba38630bda6d1676cab7","Graduate School of Industrial Economics, Peter the Great St. Petersburg Polytechnic University, Saint Petersburg, 195251, Russian Federation","Rodionov D., Graduate School of Industrial Economics, Peter the Great St. Petersburg Polytechnic University, Saint Petersburg, 195251, Russian Federation; Kryzhko D., Graduate School of Industrial Economics, Peter the Great St. Petersburg Polytechnic University, Saint Petersburg, 195251, Russian Federation; Tenishev T., Graduate School of Industrial Economics, Peter the Great St. Petersburg Polytechnic University, Saint Petersburg, 195251, Russian Federation; Uimanov V., Graduate School of Industrial Economics, Peter the Great St. Petersburg Polytechnic University, Saint Petersburg, 195251, Russian Federation; Abdulmanova A., Graduate School of Industrial Economics, Peter the Great St. Petersburg Polytechnic University, Saint Petersburg, 195251, Russian Federation; Kvikviniia A., Graduate School of Industrial Economics, Peter the Great St. Petersburg Polytechnic University, Saint Petersburg, 195251, Russian Federation; Aksenov P., Graduate School of Industrial Economics, Peter the Great St. Petersburg Polytechnic University, Saint Petersburg, 195251, Russian Federation; Solovyov M., Graduate School of Industrial Economics, Peter the Great St. Petersburg Polytechnic University, Saint Petersburg, 195251, Russian Federation; Kolomenskii F., Graduate School of Industrial Economics, Peter the Great St. Petersburg Polytechnic University, Saint Petersburg, 195251, Russian Federation; Konnikov E., Graduate School of Industrial Economics, Peter the Great St. Petersburg Polytechnic University, Saint Petersburg, 195251, Russian Federation","This study provides a framework for the comparative assessment of the key industry aspects of competitiveness among logistics services and the logistics systems of enterprises in the informational environment. Frequently, the relationships between a consumer and a company created by means of the informational environment determine how the enterprise positions itself in the market. For instance, the evaluation of a company’s representation in the information field is an essential aspect of determining the company’s competitiveness. The study suggests a set of special metrics for measuring the representation of digital components and other aspects of an enterprise’s digital image via data gathering and analysis of the most encountered tokens. The proposed automated analysis algorithm allows companies to examine their image in the digital environment and implement effective decisions. The functionality of the algorithm fosters data collection, helping to form the desired image of the company. Tokens of several thematic groups on social media are collected during the process, and the most significant of them that are valuable for the competitiveness of the enterprise are extracted. The outcome can be used for the tracking of the dynamics of key parameters of an enterprise’s image and for conducting a comparative analysis of the digital image of its competitors. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.","brand; competitiveness; data; delivery service; digital image; e-commerce; information environment; logistics; social networks; supply chain","Image analysis; Social networking (online); Supply chains; Brand; Comparative assessment; Delivery service; Digital image; E- commerces; Information environment; Logistics services; Logistics system; Social network; Special metric; Competition",{"$nulls":4},"Ministry of Education and Science of the Russian Federation, Minobrnauka, (075-15-2021-1333)","Funding: The research was partially funded by the Ministry of Science and Higher Education of the Russian Federation under the strategic academic leadership program ‘Priority 2030’ (agreement 075-15-2021-1333, dated 30 September 2021).","Markov A., Finance as Technology: IT of the 19th Century, Hooligan Econ, 3, (2019); Rudskaya I., Kryzhko D., Shvediani A., Missler-Behr M., Regional Open Innovation Systems in a Transition Economy: A Two-Stage DEA Model to Estimate Effectiveness, J. Open Innov. Technol. Market Complex, 8, (2022); Polyanin A., Golovina T., Avdeeva I., Vertakova Y., Kharlamov A., Standardization of business processes based on the use of digital platforms, Proceedings of the 33rd International Business Information Management Association Conference, pp. 3904-3912, (2019); Kharlamov A.V., Kharlamova T.L., Sustainable development of the Russian economy in the context of global instability, Proceedings of the 33rd International Business Information Management Association Conference, IBIMA 2019: Education Excellence and Innovation Management through Vision 2020, pp. 822-830, (2019); Rudskaia I., Rodionov D., The concept of total innovation management as a mechanism to enhance the competitiveness of the national innovation system, Proceedings of the 2018 International Conference on Internet and e-Business, pp. 246-251, (2018); Rodionov D., Nikolova L., Abramchikova N., Velikova M., Mazuba K.R.J., Development of the analysis model of innovative projects efficiency management in the context of digitalization, Proceedings of the 2nd International Scientific Conference on Innovations in Digital Economy: SPBPU IDE-2020, pp. 1-7, (2020); Konnikov E., Konnikova O., Rodionov D., Yuldasheva O., Analyzing Natural Digital Information in the Context of Market Research, Information, 12, (2021); Reuschkea D., Mason C., Syrett S., Digital futures of small businesses and entrepreneurial opportunity, Futures, 135, (2021); Sjaholm E., Lien L., Timmermans B., Belik I., Pandey S., Stability in turbulent times? The effect of digitalization on the sustainability of competitive advantage, J. Bus. Res, 128, pp. 360-369, (2021); Popkova E., Bruno S., A Digital Economy to Develop Policy Related to Transport and Logistics. Predictive Lessons from Russia, Land Use Policy, 99, (2020); Tipping A., Kauschke P., Shifting Patterns, The Future of the Logistics Industry. PwC, pp. 16-17, (2016); Kondrashova M., Features of image development in the modern digital space, Communications in the Era of Digital Change, pp. 25-28, (2020); Esber D., Wong J., Discussions in Digital: Surveying the Brand-Building Landscape, (2020); Ageeva E., Melewar T., Foroudi P., Dennis C., Jin Z., Examining the influence of corporate website favorability on corporate image and corporate reputation: Findings from fsQCA, J. Bus. Res, 89, pp. 287-304, (2018); Macko V., The evolution of the concept of image: Digital image, Sci. Educ. Probl. Dev. Trends, pp. 104-107, (2016); Verkhovtseva O., Vorobyov P., Transformation of the company’s image in the digital environment, Goverment Bus. Mod. Probl. Econ, pp. 217-220, (2017); Pardo C., Pagani M., Savinien J., The strategic role of social media in business-to-business contexts, Ind. Mark. Manag, 101, pp. 82-97, (2022); Balmer J., Zhibin L., Weifeng C., Xinming H., The role of corporate brand image for B2B relationships of logistics service providers in China, J. Bus. Res, 117, pp. 850-861, (2020); Brenner B., Hummel V., Digital Twin as Enabler for an Innovative Digital Shopfloor Management System in the ESB Logistics Learning Factory at Reutlinge–University, Procedia Manuf, 9, pp. 198-205, (2017); Tadic S., Veljovic M., Home delivery: A framework for structuring, Int. J. Traffic Transp. Eng. IJTTE, 11, pp. 30-74, (2021); Schaar D., Govers J., Escudero R., Lukic V., Zaleski M., Why Parcel Companies Need to Make Every Delivery Special, (2020); Joerss M., Schroder M., Neuhaus F., Klink C., Mann F., Parcel delivery: The future of last mile, McKinsey & Company, pp. 11-13, (2016); Samusev N., Organization of cargo delivery for online commerce, taking into account refunds, State Munic. Adm. Sci. Notes, pp. 78-84, (2019); Politkovskaya I., Tkacheva M., Balandina V., The state and development of the potential of public catering enterprises in the conditions of the coronavirus pandemic, Econ. Bus. Theory Pract, 220, pp. 220-225, (2020); Pestov A., Startup of the food delivery business in the digital economy: Type of service, organizational and managerial aspects (based on the case study of LLC Yandex.Food”, LLC «Delivery Club»), Int. Res. J, 85, pp. 112-118, (2019); Hofman B., Hang Z., Performance and Prospects of Global Logistics, Keynote Speech at the CaiNiao Global Smart Logistics Conference, (2017); Hemanth S., Exponential Growth Of the Logistics Sector Provides a Career To Many, Entrepreneur, (2021); Munuzuri J., Van Duin R., Escudero A., How efficient is city logistics? Estimating ecological footprints for urban freight deliveries, Procedia-Soc. Behav. Sci, 2, pp. 6165-6176, (2010); Mommens K., Buldeo Rai H., Lier T., Macharis C., Delivery to homes or collection points? A sustainability analysis for urban, urbanised and rural areas in Belgium, J. Transp. Geogr, 94, (2021); Saboya B., Solange A., The relationship between human values and conscious ecological behavior among consumers: Evidence from Brazil, Clean. Responsible Consum, 3, (2021); Gonzalez-Morales A., Mitrovic J., Ceballos Garcia R., Ecological consumer neuroscience for competitive advantage and business or organizational differentiation, Eur. Res. Manag. Bus. Econ, 26, pp. 174-180, (2020); Gupta M., Dharwal M., Green entrepreneurship and sustainable development: A conceptual framework, Mater. Today Proc, 49, pp. 3603-3606, (2021); Unilever, (2019); Jie Y., Pishi X., Lipeng S., Limeng Y., Blaanand M., Social media data analytics for business decision making system to competitive analysis, Inf. Processing Manag, 59, (2022); Raj A., Dingus R., Hu M., Krush M., Social media: Influencing customer satisfaction in B2B sales, Ind. Mark. Manag, 53, pp. 172-180, (2016); Korobov M., Morphological Analyzer and Generator for Russian and Ukrainian Languages, Anal. Images Soc. Netw. Texts, 542, pp. 320-332, (2015); Yin Z., Rong J., Zhi-Hua Z., Understanding bag-of-words model: A statistical framework, Int. J. Mach. Learn. Cybern, 1, pp. 43-52, (2010); Rogers A., Romanov A., Rumshisky A., Volkova S., Gronas M., Gribov A., RuSentiment: An Enriched Sentiment Analysis Dataset for Social Media in Russian, Proceedings of the 27th International Conference on Computational Linguistics, pp. 755-763, (2018); Maaten L., Hinton G., Visualizing Data Using t-SNE, J. Mach. Learn. Res, 9, pp. 2579-2605, (2008); Delivery Club and WWF RUSSIA Have Launched a Virtual Restaurant for Rare Wild Animals, WWF RUSSIA, (2020); How to Make Russian Cities with Millions of People Convenient for Cyclists: A Study by Delivery Club and Strelka Design Bureau, (2021); Press Center Delivery Club, (2021)","D. Kryzhko; Graduate School of Industrial Economics, Peter the Great St. Petersburg Polytechnic University, Saint Petersburg, 195251, Russian Federation; email: kryzhko_da@spbstu.ru",null,"MDPI",{"$nulls":5},1.9994893E7,null,null,null,"English","Algorithms","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85131367297"]
["Liu W.; Sun X.","Liu, Weiliang (57226645823); Sun, Xu (57197816635)","57226645823; 57197816635","Energy-Aware and Delay-Sensitive Management of a Drone Delivery System",2022.0,"Manufacturing and Service Operations Management",24.0,3.0,null,1294.0,1310.0,16.0,2.0,"10.1287/msom.2021.1056","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85132220729&doi=10.1287%2fmsom.2021.1056&partnerID=40&md5=7fb377c6541f10938a27a4bacb136e93","Department of Industrial Systems Engineering and Management, National University of Singapore, Singapore, 119077, Singapore; Department of Industrial and Systems Engineering, University of Florida, Gainesville, 32603, FL, United States","Liu W., Department of Industrial Systems Engineering and Management, National University of Singapore, Singapore, 119077, Singapore; Sun X., Department of Industrial and Systems Engineering, University of Florida, Gainesville, 32603, FL, United States","Problem definition: This paper considers a drone delivery system that delivers packages to multiple locations using a model that captures three distinctive features of interest: first, a battery-operated drone that can fly a limited number of distance units on a full battery; second, a set of demand locations with different flight distances and service-level requirements; and third, an adjustable flight speed to trade off energy efficiency for faster deliveries. By leveraging drone speed, job sequencing, and admission control, the system operator strives to achieve two managerial objectives: (i) to minimize energy- and congestion-related costs and (ii) to maximize the use of the battery energy between consecutive battery replacements. Academic/practical relevance: E-commerce and shipping companies worldwide are testing and launching commercial drone delivery services to residences. According to a recent study, such services are expected to grow to $100 billion market by the end of the next decade. Our work focuses on improving drone delivery operations, which can reduce costs and improve user satisfaction. Methodology: Focusing on the first objective, we approximate system dynamics using diffusion processes and derive an optimal control policy for the approximating system. Results: Interpreting that policy in the context of the physical system while taking into account the second objective, we devise an implementable set of speed control, job sequencing, and admission strategies. The sequencing strategy, which selects a portfolio of jobs (termed as an activity) to be accomplished within a full battery cycle, results in a win-win scenario—it allows both objectives to be approximately optimized at the same time. Managerial implications: Using the activity-based prioritization scheme provides opportunities to improve the overall performance of the system. Additionally, to achieve the intended job prioritization, the system operator can rely on a small set of activities that are of equal size to the number of job classes. © 2022 INFORMS","diffusion analysis; drones; dynamic programming; queuing theory; service operations; stochastic methods; stochastic optimal control; transportation","Drones; Economic and social effects; Electric batteries; Energy efficiency; Managers; Power management; Queueing theory; Stochastic systems; Traffic congestion; Delivery systems; Diffusion analysis; Energy aware; Energy delay; Job sequencing; Queuing theory; Service operations; Stochastic methods; Stochastic optimal control; System operator; Dynamic programming",{"$nulls":4},"Na-tional University of Singapore; University of Florida's faculty startup fund","Funding: Part of the research was conducted while W. Liu was an undergraduate research intern at the University of Florida. W. Liu has been supported by the President's Graduate Fellowship at the Na-tional University of Singapore. The research of X. Sun has been funded in part by the University of Florida's faculty startup fund.","Agatz N, Bouman P, Schmidt M, Optimization approaches for the traveling salesman problem with drone, Transportation Sci, 52, 4, pp. 965-981, (2018); Ata B, Dynamic power control in a wireless static channel subject to a quality-of-service constraint, Oper. Res, 53, 5, pp. 842-851, (2005); Ata B, Tongarlak MH, On scheduling a multiclass queue with abandonments under general delay costs, Queueing Systems, 74, 1, pp. 65-104, (2013); Ata B, Zachariadis KE, Dynamic power control in a fading downlink channel subject to an energy constraint, Queueing Systems, 55, 1, pp. 41-69, (2007); Ata B, Harrison J, Shepp LA, Drift rate control of a brownian processing system, Ann. Appl. 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Res, 57, 1, pp. 94-108, (2009); Sacramento D, Pisinger D, Ropke S, An adaptive large neighborhood search metaheuristic for the vehicle routing problem with drones, Transportation Res. Part C Emerging Tech, 102, pp. 289-315, (2019); Sasaki T, Ukyo Y, Novak P, Memory effect in a lithium-ion battery, Nature Materials, 12, 6, pp. 569-575, (2013); Schermer D, Moeini M, Wendt O, A matheuristic for the vehicle routing problem with drones and its variants, Transportation Res. Part C Emerging Tech, 106, September, pp. 166-204, (2019); Singireddy SRR, Daim TU, Technology roadmap: Drone delivery–Amazon Prime Air, Infrastructure and Technology Management, pp. 387-412, (2018); Stolaroff JK, Samaras C, O'Neill ER, Lubers A, Mitchell AS, Ceperley D, Energy use and life cycle greenhouse gas emissions of drones for commercial package delivery, Nature Comm, 9, 1, pp. 1-13, (2018); Torabbeigi M, Lim GJ, Kim SJ, Drone delivery scheduling optimization considering payload-induced battery consumption rates, J. Intelligent Robotic Systems, 97, 3, pp. 471-487, (2020); Van Mieghem JA, Dynamic scheduling with convex delay costs: The generalized cμ rule, Ann. Appl. Probab, 5, 3, pp. 809-833, (1995); Wang Z, Sheu JB, Vehicle routing problem with drones, Transportation Res. Part B: Methodol, 122, April, pp. 350-364, (2019); Xie S, Hu X, Qi S, Tang X, Lang K, Xin Z, Brighton J, Model predictive energy management for plug-in hybrid electric vehicles considering optimal battery depth of discharge, Energy, 173, April, pp. 667-678, (2019); Zafer M, Modiano E, Optimal rate control for delay-constrained data transmission over a wireless channel, IEEE Trans. Inform. Theory, 54, 9, pp. 4020-4039, (2008)","X. Sun; Department of Industrial and Systems Engineering, University of Florida, Gainesville, 32603, United States; email: xusun@ufl.edu",null,"INFORMS Inst.for Operations Res.and the Management Sciences",{"$nulls":5},1.5234614E7,null,"MSOMF",null,"English","Manuf. Serv. Oper. Manage.","Article","Final",null,"Scopus","2-s2.0-85132220729"]
["Yao C.; Chen S.; Yang Z.","Yao, Canqi (57223438696); Chen, Shibo (57211958193); Yang, Zaiyue (56060645200)","57223438696; 57211958193; 56060645200","Joint Routing and Charging Problem of Multiple Electric Vehicles: A Fast Optimization Algorithm",2022.0,"IEEE Transactions on Intelligent Transportation Systems",23.0,7.0,null,8184.0,8193.0,9.0,15.0,"10.1109/TITS.2021.3076601","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85105873276&doi=10.1109%2fTITS.2021.3076601&partnerID=40&md5=41d3eb13a902bf39fa01b97efe5041c6","School of Mechatronics Engineering, Harbin Institute of Technology, Harbin, 150000, China; Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems, Department of Mechanical and Energy Engineering, Southern University of Science and Technology, Shenzhen, 518055, China; Guangdong Provincial Key Laboratory of Human, Augmentation and Rehabilitation Robotics in Universities, Southern University of Science and Technology, Shenzhen, 518055, China","Yao C., School of Mechatronics Engineering, Harbin Institute of Technology, Harbin, 150000, China, Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems, Department of Mechanical and Energy Engineering, Southern University of Science and Technology, Shenzhen, 518055, China, Guangdong Provincial Key Laboratory of Human, Augmentation and Rehabilitation Robotics in Universities, Southern University of Science and Technology, Shenzhen, 518055, China; Chen S., Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems, Department of Mechanical and Energy Engineering, Southern University of Science and Technology, Shenzhen, 518055, China, Guangdong Provincial Key Laboratory of Human, Augmentation and Rehabilitation Robotics in Universities, Southern University of Science and Technology, Shenzhen, 518055, China; Yang Z., Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems, Department of Mechanical and Energy Engineering, Southern University of Science and Technology, Shenzhen, 518055, China, Guangdong Provincial Key Laboratory of Human, Augmentation and Rehabilitation Robotics in Universities, Southern University of Science and Technology, Shenzhen, 518055, China","Logistics has gained great attentions with the prosperous development of e-commerce, which is often seen as the classic optimal vehicle routing problem. Meanwhile, electric vehicle (EV) has been widely used in logistic fleet to curb the emission of green house gases in recent years. Thus, solving the optimization problem of joint routing and charging of multiple EVs is in a urgent need, whose objective function includes charging time, charging cost, EVs travel time, usage fees of EV and revenue from serving customers. This joint problem is formulated as a mixed integer programming (MIP) problem, which, however, is NP-hard due to integer restrictions and bilinear terms from the coupling between routing and charging decisions. The main contribution of this paper lies at proposing an efficient two-stage algorithm that can decompose the original MIP problem into two linear programming (LP) problems, by exploiting the exactness of LP relaxation and eliminating the coupled term. This algorithm can achieve a near-optimal solution in polynomial time. In addition, another variant algorithm is proposed based on the two-stage one, to further improve the quality of solution. Compared with the state-of-the-art algorithm, extensive simulations are implemented to validate the effectiveness of the proposed algorithm.  © 2000-2011 IEEE.","Electric vehicle; linear programming; mixed integer programming; routing problem","Electric vehicles; Fleet operations; Greenhouse gases; Integer programming; Linear programming; NP-hard; Polynomial approximation; Routing algorithms; Travel time; Vehicle routing; Extensive simulations; Mixed integer programming (MIP); Near-optimal solutions; Objective functions; Optimization problems; Quality of solution; State-of-the-art algorithms; Two-stage algorithm; Charging time",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (61873118, 61903179); Science, Technology and Innovation Commission of Shenzhen Municipality, (RCBS20200714114918137, ZDSYS20200811143601004); National Key Research and Development Program of China, NKRDPC, (2019YFB1705401)","This work was supported in part by the National Key Research and Development Program of China under Grant 2019YFB1705401, in part by the Natural Science Foundation of China under Grant 61873118 and Grant 61903179, and in part by the Science, Technology and Innovation Commission of Shenzhen Municipality under Grant ZDSYS20200811143601004 and Grant RCBS20200714114918137","Buchholz K., 87 Billion Parcels Were Shipped in 2018; Juan A., Mendez C., Faulin J., De Armas J., Grasman S., Electric vehicles in logistics and transportation: A survey on emerging environmental, strategic, and operational challenges, Energies, 9, 2, (2016); Shama E., Amazon is Purchasing 100, 000 Rivian Electric Vans, the Largest Order of EV Delivery Vehicles Ever; Toth P., Vigo D., The Vehicle Routing Problem, (2002); Tang X., Bi S., Zhang Y.-J.-A., Distributed routing and charging scheduling optimization for Internet of electric vehicles, IEEE Internet Things J., 6, 1, pp. 136-148, (2019); Chen T., Zhang B., Pourbabak H., Kavousi-Fard A., Su W., Optimal routing and charging of an electric vehicle fleet for high-efficiency dynamic transit systems, IEEE Trans. Smart Grid, 9, 4, pp. 3563-3572, (2018); Cerna F.V., Pourakbari-Kasmaei M., Romero R.A., Rider M.J., Optimal delivery scheduling and charging of EVs in the navigation of a city map, IEEE Trans. Smart Grid, 9, 5, pp. 4815-4827, (2018); Yu J.J.Q., Two-stage request scheduling for autonomous vehicle logistic system, IEEE Trans. Intell. Transp. Syst., 20, 5, pp. 1917-1929, (2019); Yang H., Yang S., Xu Y., Cao E., Lai M., Dong Z., Electric vehicle route optimization considering time-of-use electricity price by learnable partheno-genetic algorithm, IEEE Trans. Smart Grid, 6, 2, pp. 657-666, (2015); Lam A.Y.S., Leung Y.-W., Chu X., Autonomous-vehicle public transportation system: Scheduling and admission control, IEEE Trans. Intell. Transp. Syst., 17, 5, pp. 1210-1226, (2016); Abdulaal A., Cintuglu M.H., Asfour S., Mohammed O.A., Solving the multivariant EV routing problem incorporating V2G and G2 V options, IEEE Trans. Transport. Electrific., 3, 1, pp. 238-248, (2017); Schneider M., Stenger A., Goeke D., The electric vehicle-routing problem with time windows and recharging stations, Transp. Sci., 48, 4, pp. 500-520, (2014); Keskin M., Catay B., Partial recharge strategies for the electric vehicle routing problem with time windows, Transp. Res. C, Emerg. Technol., 65, pp. 111-127, (2016); Sassi O., Cherif-Khettaf W.R., Oulamara A., Multi-start iterated local search for the mixed fleet vehicle routing problem with heterogenous electric vehicles, Proc. Eur. Conf. Evol. Comput. Combinat. Optim. Copenhagen, pp. 138-149, (2015); Pourazarm S., Cassandras C.G., Optimal routing of energyaware vehicles in transportation networks with inhomogeneous charging nodes, IEEE Trans. Intell. Transp. Syst., 19, 8, pp. 2515-2527, (2018); Yu J.J.Q., Lam A.Y.S., Autonomous vehicle logistic system: Joint routing and charging strategy, IEEE Trans. Intell. Transp. Syst., 19, 7, pp. 2175-2187, (2018); Pourazarm S., Cassandras C.G., Wang T., Optimal routing and charging of energy-limited vehicles in traffic networks, Int. J. Robust Nonlinear Control, 26, 6, pp. 1325-1350, (2016); Dijkstra's Algorithm; Ahuja R.K., Magnanti T.L., Orlin J.B., Network Flows-Theory, Algorithms and Applications, (1993); Minimum-Cost Flow Problem; Desaulniers G., Errico F., Irnich S., Schneider M., Exact algorithms for electric vehicle-routing problems with time windows, Oper. Res., 64, 6, pp. 1388-1405, (2016); IBM ILOG CPLEX optimization studio CPLEX user's manual, 8, (2017); Zhu X., Chen H., Yang L.T., Yin S., Energy-aware rolling-horizon scheduling for real-time tasks in virtualized cloud data centers, Proc. IEEE 10th Int. Conf. High Perform. Comput. Commun. IEEE Int. Conf. Embedded Ubiquitous Comput., pp. 1119-1126, (2013)","Z. Yang; Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems, Department of Mechanical and Energy Engineering, Southern University of Science and Technology, Shenzhen, 518055, China; email: yangzy3@sustech.edu.cn",null,"Institute of Electrical and Electronics Engineers Inc.",{"$nulls":5},1.524905E7,null,null,null,"English","IEEE Trans. Intell. Transp. Syst.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85105873276"]
["Batmunkh A.","Batmunkh, Altanshagai (57457895200)",5.74578952E10,"Carbon Footprint of The Most Popular Social Media Platforms",2022.0,"Sustainability (Switzerland)",14.0,4.0,2195.0,null,null,null,6.0,"10.3390/su14042195","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124847434&doi=10.3390%2fsu14042195&partnerID=40&md5=f29f7c3e02985a61f0abd4729de8038e","octoral School of Economic and Regional Sciences, Hungarian University of Agriculture and Life Sciences (MATE), Pater Karoly utca 1, Budapest, 2100, Hungary","Batmunkh A., octoral School of Economic and Regional Sciences, Hungarian University of Agriculture and Life Sciences (MATE), Pater Karoly utca 1, Budapest, 2100, Hungary","The advent of easily accessible technology, e-commerce, online streaming, and social networking platforms has led to massive amounts of data being stored and processed every second. The IT infrastructures needed to support this digital age consume a large amount of energy and have a negative impact on the environment. There have been several different efforts to estimate the carbon footprint of the internet, but there is no proven exact method for it. Therefore, the goals of this paper are, first—to critically review the carbon emission calculation methods and compare the results, and second—to publicize the environmental impact of our daily simple habit of internet usage. We calculated the carbon footprint of the most popular four online services (TikTok, Facebook, Netflix, and YouTube) by using top-cited methods such those from Obringer, the Shift Project, Andrae, and Hintemann and Hinterholze. When comparing the emitted carbon dioxide, the weighted average of online video streaming usage per day is 51 times more than 14 h of an airplane ride. Netflix generates the highest CO2 emissions among the four applications due to its high-resolution video delivery and its number of users. © 2022 by the author. Licensee MDPI, Basel, Switzerland.","Carbon dioxide; Emission; Internet; Sustainable","carbon dioxide; carbon emission; carbon footprint; Internet; social media; social network; sustainable development",{"$nulls":6},"Ferreboeuf H., Berthoud F., Bihouix P., Fabre P., Kaplan D., Lefevre L., Lean ICT, Towards Digital Sobriety, (2019); Jumie Y., Roshan M., A critical analysis of Power Usage Effectiveness and its use in communicating data center energy consumption, Energy Build, 64, pp. 90-94, (2013); Koomey P.J.G., Growth in Data Enter Electricity Use 2005 to 2010, (2011); Koot M., Wijnhoven F., Usage impact on data center electricity needs: A system dynamic forecasting model, Appl. Energy, 291, (2021); (2020); Amir G., Carbon innumeracy, PLOS ONE, 13, (2018); Reddy V., Setz B., Subrahmanya G., Rao V., Gangadharan G., Aiello M., Metrics for sustianable data centers, IEEE Trans. Sustianable Comput, 2, pp. 290-303, (2017); Tomitsch M., World Economic Forum, World Economic Forum, 8 February 2022; Jens M., Dag L., The energy and carbon footprint of the global ICT and E&M sectors 2010–2015, Sustainability, 10, (2018); Networking C.V., Cisco Global Cloud Index: White Paper, (2021); Anders S., Tomas E., On global electricity usage of communication technology: Trends to 2030, Challenges, 6, pp. 117-157, (2015); Liu Y., Wei X., Xiao J., Energy consumption and emission mittigation prediction based on data center traffic and PUE for global data centers, Glob. Energy Interconnect, 3, pp. 272-282, (2020); Lange S., Pohl J., Santarius T., Digitalization and energy consumption Does ICT reduce energy demand, Ecol. Econ, 176, (2020); Mohammad S., Khorshed A., Information and Communication Technology, electricity consumption and economic growth in OECD countries: A panel data analysis, Electr. Power Energy Syst, 76, pp. 185-193, (2016); Ham S.-W., Kim M.-H., Choi B.-N., Jeong J.-W., Simplified server model to simulate data center cooling energy consumption, Energy Build, 86, pp. 328-339, (2015); Bill W., Connectria, (2019); Qingyuan Z., Jing L., Yifeng J., Optimization of energy consumption of green data center in e-commerce, Sustain. Comput. Inform. Syst, 23, pp. 103-110, (2019); Lanzisera S., Nordman B., Brown R., Data network equipment energy use and savings potential in buildings, Energy Effic, 5, pp. 149-162, (2012); Berners-Lee M., How Bad Are Bananas? The Carbon Footprint of Everything, (2010); Luo H., Cheng F., Huelsenbeck L., Smith N., Comparison between conventional solvothermal and aqueous solution-based production of UiO-66-NH2: Life cycle assessment, techno-economic assessment, and implications for CO<sub>2</sub> capture and storage, Environ. Chem. Eng, 9, (2021); Lee J.W., Li R., Integration of fossil energy systems with CO<sub>2</sub> sequestration through NH<sub>4</sub> HCO<sub>3</sub> production, Energy Convers. Manag, 44, pp. 1535-1546, (2002); Bordage F., The environmental footprint of the digital world, Greenit.Fr, pp. 4-39, (2019); Andrae A.S., New perspectives on internet electricity use in 2030, Eng. Appl. Sci, 3, pp. 19-31, (2020); Obringer R., Rachunok B., Maia-Silva D., Arbabzadeh M., Nateghi R., Madani K., The overlooked environmental footprint of increasing Internet use, Resour. Conserv. Recycl, 167, pp. 1-4, (2021); Hintemann R., Hinterholzer S., Energy Consumption of Data Centers Worldwide, (2019); Laura D., Marks U., Makonin D., Rodriguez-Silva A., Przedpelski D., Tackling the Carbon Footprint of Streaming Media; Andrae A.S., Prediction Studies of Electricity Use of Global Computing in 2030, Sci. Eng. Investig, 8, pp. 27-33, (2019)","A. Batmunkh; octoral School of Economic and Regional Sciences, Hungarian University of Agriculture and Life Sciences (MATE), Budapest, Pater Karoly utca 1, 2100, Hungary; email: batmunkh.altanshagai@phd.uni-mate.hu",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85124847434"]
["Haryanti T.; Subriadi A.P.","Haryanti, Tining (57214670632); Subriadi, Apol Pribadi (55843868800)","57214670632; 55843868800","E-commerce acceptance in the dimension of sustainability",2022.0,"Journal of Modelling in Management",17.0,2.0,null,715.0,745.0,30.0,9.0,"10.1108/JM2-05-2020-0141","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85106749095&doi=10.1108%2fJM2-05-2020-0141&partnerID=40&md5=bdfbf061d969598d736f47d57a2090d2","Universitas Muhammadiyah Surabaya, Surabaya, Indonesia; Fakultas Teknologi Informasi, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia","Haryanti T., Universitas Muhammadiyah Surabaya, Surabaya, Indonesia; Subriadi A.P., Fakultas Teknologi Informasi, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia","Purpose: Technology presents e-commerce as an alternative buying and selling place that is accepted by the public. The high growth of e-commerce has an impact on the sustainability of both the economic dimension, the social dimension and the environmental dimension. Indonesia is the country with the fastest-growing e-commerce but also has the second-largest plastic waste in the world. The synergy of sustainability for e-commerce is an interesting and awaited innovation. This is because sustainability has become the responsibility of all countries in the world. Design/methodology/approach: A theoretical understanding of the context of sustainability in e-commerce separately focuses on a company perspective and the use of green products from a consumer perspective. It requires the involvement of e-commerce stakeholders as a whole to get comprehensive research results. The use of qualitative research methods with exploratory approaches is used in this study to reveal the concept of sustainability in e-commerce in Indonesia. Findings: This study found similarities in the topic of acceptance of sustainability in e-commerce with a unified theory of acceptance and use of technology (UTAUT) including performance expectancy, effort expectancy, facilitating conditions, social influence and habits. Changes to the variables were revealed due to changes in the e-commerce phase. The variable trust is in the introduction phase and builds trust in e-commerce. Currently, in Indonesia, the e-commerce phase is in a phase of growth and value formation. Habit creation and dependence is a requirement for value formation. Several new topics were proposed in this study, namely, awareness, security, logistics and user interface and user experience (UX). The establishment of an e-commerce identity through UX clearly shows its target market. The e-commerce phase and the topics involved in it can become a reference for e-commerce regulation-making in Indonesia. Research limitations/implications: This study is limited to e-commerce in Indonesia with data processing limited to February 2020. Practical implications: The results of this study provide an overview of increasing the intention to use e-commerce through human acceptance and engineering dimensions. This research also reveals the stages of e-commerce in Indonesia that can be used as a reference for determining the right regulations for e-commerce and the trade-offs for sustainability. Originality/value: This study produces additional references to the intention to use technology by completing the UTAUT model. This study reveals changes in variables in perceived value that are interesting for further research along with technological developments and changes in people’s habits. Exploration carried out can add references to the application of sustainability in e-commerce, especially in developing countries. © 2021, Emerald Publishing Limited.","E-commerce; Information systems; Management information systems; Perceived value; Stage; Sustainability; UTAUT",{"$nulls":7},{"$cut":{"chars":21376,"head":"Andonova V., Online disintermediation: differences in the behavior of traditional retailers in adopting E-commerce, Management Research, (2003); Arnold F., Cardenas I., Sorensen K., Dewulf W., Simulation of B2C e-commerce distribution in Antwerp using cargo bikes and delivery points, European Transport Research Review, 10, 1, (2018); Bergman M., 7 quality of inferences in mixed methods research: calling for an integrative framework, Advances in Mixed Methods Research, (2014); Bernard M., 5 key stakeholders for B2B ecommerce success, (2020); Bhandari U., Chang K., Neben T., Understanding the impact of perceived visual aesthetics on user evaluations: an emotional perspective, Information and Management, (2019); Biagi F., Falk M., The impact of ICT and e-commerce on employment in Europe, Journal of Policy Modeling, 39, 1, (2017); How the generations shop online, (2019); Bird J., What a waste: online retail’s big packaging problem, (2018); Bank Indonesia: Transaksi E-Commerce per Bulan Capai Rp 13 T, (2019); Boddy C.R., Sample size for qualitative research, Qualitative Market Research: An International Journal, 19, 4, (2016); Carrillo D., Duncan R.E., Ploetz J.N., Campbell A.F., Ploetz R.C., Pena J.E., Lateral transfer of a phytopathogenic symbiont among native and exotic ambrosia beetles, Plant Pathology, 63, 1, pp. 54-62, (2014); Carrillo J.E., Vakharia A.J., Wang R., Environmental implications for online retailing, European Journal of Operational Research, 239, 3, (2014); Chan F.T.S., Yee-Loong Chong A., Zhou L., An empirical investigation of factors affecting e-collaboration diffusion in SMEs, International Journal of Production Economics, 138, 2, (2012); Chen S.C., Lin C.P., The impact of customer experience and perceived value on sustainable social relationship in blogs: an empirical study, Technological Forecasting and Social Change, 96, (2015); Chiu C.M., Huang H.Y., Yen C.H., Antecedents of trust in online auctions, Electronic Commerce Research and Applications, 9, 2, (2010); Chofreh A.G., Goni F.A., Klemes J.J., Sustainable enterprise resource planning systems implementation: a framework development, Journal of Cleaner Production, 198, pp. 1345-1354, (2018); Chueamuangphan K., Visvanathan C., Kashyap P., Packaging waste from E-commerce: consumers’ awareness and concern, Sustainable Waste Management: Policies and Case Studies, 1, pp. 27-41, (2019); Tren dan Peluang Industri E-Commerce di Indonesia 2020, (2020); Why UX design is key to online marketplace success, (2019); Cohen D.C.B., Qualitative research guidelines project, (2006); Cohen J.B., Areni C.S., Affect and consumer behavior, Handbook of Consumer Behavior, (1991); Cresswell J.W., Five qualitative traditions of inquiry, Qualitative Inquiry and Research Design: Choosing among Five Traditions, (1998); Creswell J.W., Qualitative Inquiry and Research Design: Choosing among Five Approaches (Third Edit), (2015); Cui M., Pan S.L., Newell S., Cui L., Strategy, resource orchestration and E-commerce enabled social innovation in rural China, Journal of Strategic Information Systems, (2017); Das K., Tamhane T., Vatterott B., Wibowo P., Wintels S., The Digital Archipelago: How Online Commerce is Driving Indonesia’s Economic Development, (2018); Indonesia Jadi Negara dengan pertumbuhan E-commerce Tercepat di Dunia, (2019); Meningkat, startup logistik kian menjamur artikel ini telah tayang di katadata.co.id dengan judul ‘Aktivitas Belanja e-commerce meningkat, startup logistik kian menjamur’, (2019); DeLone W.H., McLean E.R., The DeLone and McLean model of information systems success: a ten-year update, Journal of Management Information Systems, (2003); Design S., 7 Simple habits of highly successful UX designers in shopee, (2019); Dworkin S.L., Sample size policy for qualitative studies using in-depth interviews, Archives of Sexual Behavior, 41, 6, (2012); Eddles-Hirsch K., Phenomenology and educational research, International Journal of Advanced Research (IJAR)., (2015); Efrem Siregar C.I., Transaksi tokopedia 2019 Rp 222 T, kontribusi 1,5% ke PDB, (2019); Eka R., Layana"}},"T. Haryanti; Universitas Muhammadiyah Surabaya, Surabaya, Indonesia; email: tining.haryanti@gmail.com",null,"Emerald Group Holdings Ltd.",{"$nulls":5},1.7465664E7,null,null,null,"English","J. Model. Manage.","Article","Final",null,"Scopus","2-s2.0-85106749095"]
["Castiglione M.; Comi A.; De Vincentis R.; Dumitru A.; Nigro M.","Castiglione, Marisdea (57435152800); Comi, Antonio (55567496900); De Vincentis, Rosita (57225972999); Dumitru, Andreea (57872333300); Nigro, Marialisa (36158289300)","57435152800; 55567496900; 57225972999; 57872333300; 36158289300","Delivering in Urban Areas: A Probabilistic-Behavioral Approach for Forecasting the Use of Electric Micromobility",2022.0,"Sustainability (Switzerland)",14.0,15.0,9075.0,null,null,null,8.0,"10.3390/su14159075","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137177854&doi=10.3390%2fsu14159075&partnerID=40&md5=7032a95577775d572924e0f6bfb70d76","Department of Engineering, Roma Tre University, Via Vito Volterra 62, Rome, 00146, Italy; Department of Enterprise Engineering, University of Rome Tor Vergata, Via del Politecnico 1, Rome, 00133, Italy","Castiglione M., Department of Engineering, Roma Tre University, Via Vito Volterra 62, Rome, 00146, Italy; Comi A., Department of Enterprise Engineering, University of Rome Tor Vergata, Via del Politecnico 1, Rome, 00133, Italy; De Vincentis R., Department of Engineering, Roma Tre University, Via Vito Volterra 62, Rome, 00146, Italy; Dumitru A., Department of Engineering, Roma Tre University, Via Vito Volterra 62, Rome, 00146, Italy; Nigro M., Department of Engineering, Roma Tre University, Via Vito Volterra 62, Rome, 00146, Italy","Urban delivering is facing some significant changes that are heading towards unsustainable scenarios. At the same time, local administrations as well as city planners are involved in promoting new solutions that can help to improve city sustainability and livability. In this context, electric micromobility could offer a valuable contribution. In fact, electric micromobility systems such as e-bikes and e-scooters, both at an individual level or as a shared service, could represent sustainable mobility options for city logistics, especially for specific classes of parcel delivery, users’ characteristics and travelled distances. Considering both the growth of e-commerce and the spreading of new options for delivering parcels (e.g., crowdshipping), electric micromobility (e-bikes and e-scooters) could support the penetration and acceptability of such new options, limiting the impacts of delivery operations. After analysis of the current e-commerce background and a review of the current delivery options to satisfy delivery demand, crowdshipping stands out. Thus, the potential shift from private transport to e-micromobility for crowdshipping is investigated, assuming that potential crowdshippers may, mainly, be commuters. The methodology is based on using probabilistic-behavioral models developed within random utility theory, which allow the potential shift towards e-micromobility for commuting to be forecasted. The models were calibrated in Rome, where more than 200 interviews with commuters were available. © 2022 by the authors.","city logistics; crowdshipping; e-bikes; e-scooters; electric micromobility; floating car data; random utility models","Italy; Lazio; Roma [Lazio]; Rome; calibration; commuting; electronic commerce; forecasting method; logistics; methodology; numerical model; probability; sustainability; urban area; urban planning",{"$nulls":6},"WCED World Commission on Environment and Development—Our Common Future, (1987); Interagency Report for Second Global Sustainable Transport Conference, (2021); Transforming Our World: The 2030 Agenda for Sustainable Development, (2015); Guidelines for Developing and Implementing a Sustainable Urban Mobility Plan, (2019); TAP for Uncertain Futures, (2021); Russo F., Comi A., Investigating the Effects of City Logistics Measures on the Economy of the City, Sustainability, 12, (2020); Comi A., Savchenko L., Last-Mile Delivering: Analysis of Environment-Friendly Transport, Sustain. Cities Soc, 74, (2021); Gonzalez-Feliu J., Sustainability Evaluation of Green Urban Logistics Systems: Literature Overview and Proposed Framework, Developing Eco-Cities Through Policy, Planning, and Innovation, pp. 192-233, (2020); Iwan S., Kijewska K., Johansen B.G., Eidhammer O., Malecki K., Konicki W., Thompson R.G., Analysis of the Environmental Impacts of Unloading Bays Based on Cellular Automata Simulation, Transp. Res. Part D Transp. Environ, 61, pp. 104-117, (2018); Vaishnav P.K., Sharma S., Sharma P., Analytical Review Analysis for Screening COVID-19 Disease, Int. J. Mod. Res, 1, pp. 22-29, (2021); Wang X., Kim W., Holguin-Veras J., Schmid J., Adoption of Delivery Services in Light of the COVID Pandemic: Who and How Long?, Transp. Res. Part A Policy Pract, 154, pp. 270-286, (2021); Arnold F., Cardenas I., Sorensen K., Dewulf W., Simulation of B2C E-Commerce Distribution in Antwerp Using Cargo Bikes and Delivery Points, Eur. Transp. Res. Rev, 10, (2018); Dablanc L., Morganti E., Arvidsson N., Woxenius J., Browne M., Saidi N., The Rise of On-Demand ‘Instant Deliveries’ in European Cities, Supply Chain Forum Int. J, 18, pp. 203-217, (2017); Janjevic M., Winkenbach M., Characterizing Urban Last-Mile Distribution Strategies in Mature and Emerging e-Commerce Markets, Transp. Res. Part A Policy Pract, 133, pp. 164-196, (2020); Lim S.F.W.T., Jin X., Srai J.S., Consumer-Driven e-Commerce: A Literature Review, Design Framework, and Research Agenda on Last-Mile Logistics Models, Int. J. Phys. Distrib. Logist. Manag, 48, pp. 308-332, (2018); Simoni M.D., Marcucci E., Gatta V., Claudel C.G., Potential Last-Mile Impacts of Crowdshipping Services: A Simulation-Based Evaluation, Transportation, 47, pp. 1933-1954, (2020); Pan S., Zhang L., Thompson R.G., Ghaderi H., A Parcel Network Flow Approach for Joint Delivery Networks Using Parcel Lockers, Int. J. Prod. Res, 59, pp. 2090-2115, (2021); Ruiz-Meza J., Meza-Peralta K., Montoya-Torres J.R., Gonzalez-Feliu J., Location of Urban Logistics Spaces (ULS) for Two-Echelon Distribution Systems, Axioms, 10, (2021); Auf Dem Weg Zu Null Emissionen in Deutschland, (2021); Serafini S., Nigro M., Gatta V., Marcucci E., Sustainable Crowdshipping Using Public Transport: A Case Study Evaluation in Rome, Transp. Res. Procedia, 30, pp. 101-110, (2018); Adams-Prassl J., Risak M., Comparative Labor Law & Policy Journal, Forthcoming Oxford Legal Studies Research Paper No. 8/2016, (2016); Ipeirotis P.G., Analyzing the Amazon Mechanical Turk Marketplace, XRDS, 17, pp. 16-21, (2010); Kittur A., Chi E.H., Suh B., Crowdsourcing User Studies with Mechanical Turk, Proceedings of the Twenty-Sixth Annual CHI Conference on Human Factors in Computing Systems—CHI ’08, (2008); Blanquart C., Carbone V., Collaborative Supply Chains and Environmental Awareness: A Typology in Terms of Proximity, Supply Chain Forum: Int. J, 15, pp. 28-41, (2014); Miller J., Nie Y., Stathopoulos A., Crowdsourced Urban Package Delivery: Modeling Traveler Willingness to Work as Crowdshippers, Transp. Res. Rec, 2610, pp. 67-75, (2017); Gatta V., Marcucci E., Nigro M., Patella S., Serafini S., Public Transport-Based Crowdshipping for Sustainable City Logistics: Assessing Economic and Environmental Impacts, Sustainability, 11, (2018); Marcucci E., Le Pira M., Carrocci C.S., Gatta V., Pieralice E., Connected Shared Mobility for Passengers and Freight: Investigating the Potential of Crowdshipping in Urban Areas, Proceedings of the 2017 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS), pp. 839-843, (2017); Devari A., Nikolaev A.G., He Q., Crowdsourcing the Last Mile Delivery of Online Orders by Exploiting the Social Networks of Retail Store Customers, Transp. Res. Part E Logist. Transp. Rev, 105, pp. 105-122, (2017); Galkin A., Schlosser T., Capayova S., Takacs J., Kopytkov D., Attitudes of Bratislava Citizens to Be a Crowd-Shipping Non-Professional Courier, Transp. Res. Procedia, 55, pp. 152-158, (2021); Le T.V., Ukkusuri S.V., Modeling the Willingness to Work as Crowd-Shippers and Travel Time Tolerance in Emerging Logistics Services, Travel Behav. Soc, 15, pp. 123-132, (2019); Punel A., Ermagun A., Stathopoulos A., Studying Determinants of Crowd-Shipping Use, Travel Behav. Soc, 12, pp. 30-40, (2018); Gatta V., Marcucci E., Nigro M., Serafini S., Sustainable Urban Freight Transport Adopting Public Transport-Based Crowdshipping for B2C Deliveries, Eur. Transp. Res. Rev, 11, (2019); Choubassi C., An Assessment of Cargo Cycles in Varying Urban Contexts, Master’s Thesis, (2015); Moolenburgh E.A., van Duin J.H.R., Balm S., van Altenburg M., van Amstel W.P., Logistics Concepts for Light Electric Freight Vehicles: A Multiple Case Study from the Netherlands, Transp. Res. Procedia, 46, pp. 301-308, (2020); Dupljanin D., Mirkovic M., Dumnic S., Culibrk D., Milisavljevic S., Sarac D., Urban Crowdsourced Last Mile Delivery: Mode of Transport Effects on Fleet Performance, Int. J. Simul. Model, 18, pp. 441-452, (2019); Paloheimo H., Lettenmeier M., Waris H., Transport Reduction by Crowdsourced Deliveries—A Library Case in Finland, J. Clean. Prod, 132, pp. 240-251, (2016); Binetti M., Caggiani L., Camporeale R., Ottomanelli M., A Sustainable Crowdsourced Delivery System to Foster Free-Floating Bike-Sharing, Sustainability, 11, (2019); Browne M., Allen J., Leonardi J., Evaluating the Use of an Urban Consolidation Centre and Electric Vehicles in Central London, IATSS Res, 35, pp. 1-6, (2011); Nocerino R., Colorni A., Lia F., Lue A., E-Bikes and E-Scooters for Smart Logistics: Environmental and Economic Sustainability in Pro-E-Bike Italian Pilots, Transp. Res. 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Environ, 94, (2021); Ben-Akiva M.E., Lerman S.R., Discrete Choice Analysis: Theory and Application to Travel Demand, (1985); Train K., Discrete Choice Methods with Simulation, (2009); Nigro M., Castiglione M., Maria Colasanti F., De Vincentis R., Valenti G., Liberto C., Comi A., Exploiting Floating Car Data to Derive the Shifting Potential to Electric Micromobility, Transp. Res. Part A Policy Pract, 157, pp. 78-93, (2022)","R. De Vincentis; Department of Engineering, Roma Tre University, Rome, Via Vito Volterra 62, 00146, Italy; email: rosita.devincentis@uniroma3.it; A. Comi; Department of Enterprise Engineering, University of Rome Tor Vergata, Rome, Via del Politecnico 1, 00133, Italy; email: comi@ing.uniroma2.it",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85137177854"]
["Rybaczewska M.; Sparks L.","Rybaczewska, Maria (57210842759); Sparks, Leigh (7102080046)","57210842759; 7102080046","Ageing consumers and e-commerce activities",2022.0,"Ageing and Society",42.0,8.0,null,1879.0,1898.0,19.0,4.0,"10.1017/S0144686X20001932","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85099939080&doi=10.1017%2fS0144686X20001932&partnerID=40&md5=0c67c72aaacb7053004df3e8cf0c7cc8","University of Stirling, Stirling, United Kingdom; University of Social Sciences (Społeczna Akademia Nauk), Lódź, Poland","Rybaczewska M., University of Stirling, Stirling, United Kingdom, University of Social Sciences (Społeczna Akademia Nauk), Lódź, Poland; Sparks L., University of Stirling, Stirling, United Kingdom","Technology, and particularly the internet, has transformed consumer and business behaviours. An ageing population is impacted by these contextual and operational changes. Understanding these impacts within an ageing population is important for businesses, organisations and individuals, and their e-commerce activities. Our study increases understanding about the online behaviour of older consumers. Our research question is: what is the impact of age and individual and household characteristics on the online behaviour of older consumers? This is important given the increasing assumption that all consumers are digitally enabled. We use data from the first wave of an innovative longitudinal study in Scotland (HAGIS - Healthy Ageing in Scotland) to explore ageing consumers and e-commerce activities. The United Kingdom (including Scotland) is the world's third largest e-commerce market, thus providing a suitable context. Our findings point to a shifting relationship between ageing consumers and e-commerce activities. Age is related to e-commerce activities but the 'break-point' for these activities is older than normally identified in academic and business practice. Sex is not a differentiator of activity but marital status is. Age and the contextual situation impact e-commerce, and have implications for access and capability, and link to questions over isolation. Important issues are raised for business and organisational practice, around service and other delivery for older people.  Copyright © The Author(s), 2021. Published by Cambridge University Press.","ageing; customers; e-commerce; internet; Scotland","Scotland; United Kingdom; accessibility; aging population; consumption behavior; elderly population; electronic commerce; information and communication technology; Internet; market conditions; consumer; electronic commerce; healthy aging; household; human; Internet; longitudinal study; marriage; review; Scotland",{"$nulls":6},"Where does the logistic regression analysis stand in marketing literature? 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Exploring the impact of everyday digital technology use on the wellbeing of older adults, Ageing & Society, 38, pp. 1307-1331, (2018); Cognition, persuasion and decision making in older consumers, Marketing Letters, 16, pp. 429-441, (2005); Consumer decision making and aging: Current knowledge and future directions, Journal of Consumer Psychology, 19, pp. 2-16, (2009); It's not how old you are but how you are old: A review on aging and consumer behavior, Management Review Quarterly, 66, pp. 267-297, (2016)","M. Rybaczewska; University of Stirling, Stirling, United Kingdom; email: maria.rybaczewska@stir.ac.uk",null,"Cambridge University Press",{"$nulls":5},"0144686X",null,null,null,"English","Ageing Soc.","Article","Final","All Open Access; Green Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85099939080"]
["Wen L.","Wen, Long (57454069200)",5.74540692E10,"Development Analysis of Cross-Border E-Commerce Logistics Based on Big Data Technology Under Safety Law Protection",2022.0,"International Journal of Information Systems in the Service Sector",14.0,2.0,{"$nulls":4},6.0,"10.4018/IJISSS.290547","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124646397&doi=10.4018%2fIJISSS.290547&partnerID=40&md5=dbb1dafa04ebc8dbc318a85a2d16fbe9","Hunan Vocational College of Modern Logistics, China","Wen L., Hunan Vocational College of Modern Logistics, China","Big data technology can effectively improve the logistics level of cross-border e-commerce. Firstly, difficulties existing in international logistics management and the necessity of international logistics supply chain management are discussed. Secondly, challenges and opportunities of big data technology to cross-border e-commerce are analyzed respectively. Big data logistics and its characteristics are studied in depth. The cross-border e-commerce sales forecast model is established based on GM(1,1), and the proposed model is verified based on case study. Simulation results show that the prediction model can improve the prediction precision of sales amount. Finally, integration measurements of big data and cross-border e-commerce are put forward under a suitable local law protection. Copyright © 2022, IGI Global.","1); Cross-Border E-Commerce; GM(1; Logistics; Safety Law Protection","Electronic commerce; Forecasting; Sales; Supply chain management; System theory; 1); Cross-border; Cross-border E-commerce; Data technologies; E- commerces; GM(1; Logistic management; Logistics supply chain managements; Safety law protection; Safety laws; Big data",{"$nulls":6},"Bathelt H., Li P., Processes of building cross-border knowledge pipelines, Research Policy, 49, 3, (2020); Chien-wen S., Chen M., Wang C., Analyzing the trend of O2O commerce by bilingual text mining on social media, Computers in Human Behavior, 101, 12, pp. 474-483, (2019); Govindan K., Gholizadeh H., Robust network design for sustainable-resilient reverse logistics network using big data: A case study of end-of-life vehicles, Transportation Research Part E, Logistics and Transportation Review, 149, (2021); Janjevic M., Winkenbach M., Characterizing urban last-mile spread strategies in mature and emerging e-commerce markets, Transportation Research Part A, Policy and Practice, 133, 3, pp. 164-196, (2020); Kwak J., Zhang Y., Yu J., Legitimacy building and e-commerce platform development in China: The experience of Alibaba, Technological Forecasting and Social Change, 139, 2, pp. 115-124, (2019); Kwok D. W. P., Meschi P.-X., Bertrand O., In CEOs we trust: When religion matters in cross-border acquisitions. The case of a multifaith country, International Business Review, 29, 4, (2020); Leung K. H., Choy K. L., Paul K. 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H., Drivers and barriers to cross-border e-commerce: Evidence from Spanish individual behavior, Telecommunications Policy, 42, 6, pp. 464-473, (2018); Wang Y., Dang Y., Li Y., Liu S., An approach to increase prediction precision of GM(1,1) model based on optimization of the initial condition, Expert Systems with Applications, 37, 8, pp. 5640-5644, (2010); Wang Y., Jia F., Schoenherr T., Gong Y., Chen L., Cross-border e-commerce firms as supply chain integrators: The management of three flows, Industrial Marketing Management, 89, 8, pp. 72-88, (2020); Wang Z.-X., Li D.-D., Zheng H.-H., Model comparison of GM(1,1) and DGM(1,1) based on Monte-Carlo simulation, Physica A, 542, 3, (2020); Wang Z.-X., Wang Z.-W., Li Q., Forecasting the industrial solar energy consumption using a novel seasonal GM(1,1) model with dynamic seasonal adjustment factors, Energy, 200, 6, (2020); Wu P.-J., Lin K.-C., Unstructured big data analytics for retrieving e-commerce logistics knowledge, Telematics and Informatics, 35, 1, pp. 237-244, (2018); Yousuf Al-Bahadly, Avci, A modified GM(1,1) model to accurately predict wind speed, Sustainable Energy Technologies and Assessments, 43, (2021); Zheng K., Zhang Z., Song B., Bin Song, E-commerce logistics distribution mode in big-data context: A case analysis of JD.COM, Industrial Marketing Management, 86, pp. 154-162, (2020); Zhu Z., Bai Y., Dai W., Liu D., Hu Y., Quality of e-commerce agricultural products and the safety of the ecological environment of the origin based on 5G Internet of Things technology, Environmental Technology & Innovation, 22, 5, (2021)",null,null,"IGI Global",{"$nulls":5},1.9355688E7,null,null,null,"English","Int. J. Inf. Syst. Serv. Sect.","Article","Final",null,"Scopus","2-s2.0-85124646397"]
["Truden C.; Maier K.; Jellen A.; Hungerländer P.","Truden, Christian (57200151691); Maier, Kerstin (57201555005); Jellen, Anna (57221159396); Hungerländer, Philipp (55349290500)","57200151691; 57201555005; 57221159396; 55349290500","Computational Approaches for Grocery Home Delivery Services",2022.0,"Algorithms",15.0,4.0,125.0,null,null,null,4.0,"10.3390/a15040125","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85129058139&doi=10.3390%2fa15040125&partnerID=40&md5=cc8ae54a2238e1f0a855dd7eadb1f770","Department of Mathematics, University of Klagenfurt, Klagenfurt, 9020, Austria; Department of Operations, Energy, and Environmental Management, University of Klagenfurt, Klagenfurt, 9020, Austria; MANSIO Karl Popper Kolleg, University of Klagenfurt, Klagenfurt, 9020, Austria","Truden C., Department of Mathematics, University of Klagenfurt, Klagenfurt, 9020, Austria, Department of Operations, Energy, and Environmental Management, University of Klagenfurt, Klagenfurt, 9020, Austria; Maier K., Department of Mathematics, University of Klagenfurt, Klagenfurt, 9020, Austria, MANSIO Karl Popper Kolleg, University of Klagenfurt, Klagenfurt, 9020, Austria; Jellen A., MANSIO Karl Popper Kolleg, University of Klagenfurt, Klagenfurt, 9020, Austria; Hungerländer P., Department of Mathematics, University of Klagenfurt, Klagenfurt, 9020, Austria","The steadily growing popularity of grocery home-delivery services is most likely based on the convenience experienced by its customers. However, the perishable nature of the products imposes certain requirements during the delivery process. The customer must be present when the delivery arrives so that the delivery process can be completed without interrupting the cold chain. Therefore, the grocery retailer and the customer must mutually agree on a time window during which the delivery can be guaranteed. This concept is referred to as the attended home delivery (AHD) problem in the scientific literature. The phase during which customers place orders, usually through a web service, constitutes the computationally most challenging part of the logistical processes behind such services. The system must determine potential delivery time windows that can be offered to incoming customers and incrementally build the delivery schedule as new orders are placed. Typically, the underlying optimization problem is a vehicle routing problem with a time windows. This work is concerned with a case given by an international grocery retailer’s online shopping service. We present an analysis of several efficient solution methods that can be employed to AHD services. A framework for the operational planning tools required to tackle the order placement process is provided. However, the basic framework can easily be adapted to be used for many similar vehicle routing applications. We provide a comprehensive computational study comparing several algorithmic strategies, combining heuristics utilizing local search operations and mixed-integer linear programs, tackling the booking process. Finally, we analyze the scalability and suitability of the approaches. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.","attended home delivery; grocery home delivery; vehicle routing problem with time windows","Integer programming; Vehicle routing; Vehicles; Web services; Attended home delivery; Computational approach; Delivery process; Grocery home delivery; Grocery retailer; Home delivery; Home delivery services; Most likely; Time windows; Vehicle routing problem with time windows; Sales",{"$nulls":4},"Amt der Kärntner Landesregierung","Funding: Christian Truden is supported by a grant from the Government of Carinthia within the CARINTHIja 2020 project.","Internet Purchases by Individuals (Until 2019) (Online Data Code: ISOC_EC_IBUY); Internet Purchases by Individuals (2020 Onwards) (online data code: ISOC_EC_IB20); Internet Purchases—Goods or Services (2020 Onwards) (online data code: ISOC_EC_IBGS); The future of Grocery; Breitbarth E., Gross W., Zienau A., Protecting vulnerable people during pandemics through home delivery of essential supplies: a distribution logistics model, J. 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["Tolstoy D.; Nordman E.R.; Vu U.","Tolstoy, Daniel (26322155100); Nordman, Emilia Rovira (23036353800); Vu, Uyen (57212758211)","26322155100; 23036353800; 57212758211","The indirect effect of online marketing capabilities on the international performance of e-commerce SMEs",2022.0,"International Business Review",31.0,3.0,101946.0,null,null,null,32.0,"10.1016/j.ibusrev.2021.101946","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85120962941&doi=10.1016%2fj.ibusrev.2021.101946&partnerID=40&md5=89271d78ef355f0eb38887d9420fbfbd","Department of Marketing and Strategy Stockholm School of Economics, Stockholm, Sweden; School of Business, Society and Engineering, Mälardalen University, Västerås, Sweden and Department of Marketing and Strategy, Stockholm School of Economics, Stockholm, Sweden; House of Innovation, Stockholm School of Economics, Stockholm, Sweden","Tolstoy D., Department of Marketing and Strategy Stockholm School of Economics, Stockholm, Sweden; Nordman E.R., School of Business, Society and Engineering, Mälardalen University, Västerås, Sweden and Department of Marketing and Strategy, Stockholm School of Economics, Stockholm, Sweden; Vu U., House of Innovation, Stockholm School of Economics, Stockholm, Sweden","International e-commerce is a strong global trend pushed by a tail wind of bolstering economic policies, changing customer behaviors, and improved logistics and technologies. This study investigates the reasons for performance variations among international e-commerce SMEs. Building on the capabilities perspective and market orientation literature, a research model is developed and tested with linear regression and mediation analysis on an effective sample of 99 Swedish SMEs which use e-commerce as an international sales channel. Our study shows that online marketing capabilities are necessary but not sufficient to increase performance among these companies. Our results show that marketing ambidexterity, reflected by both market-driven and market-driving approaches, is instrumental to leverage the effect of online marketing capabilities. © 2021 The Authors","Cross-border e-commerce; International e-commerce; International performance; Market orientation; Marketing ambidexterity; Online marketing capability; SMEs",{"$nulls":5},"Torsten Söderbergs Stiftelse, TSS, (E19/16, ET2/18)","Two of the authors are grateful for the financial support from the Torsten Söderberg Foundation [Projects: E19/16 and ET2/18] during the data-collection and writing-stages of producing this research article. The authors affirm that the manuscript is free of external influence from this and other research councils/foundations. 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["Polydoropoulou A.; Tsirimpa A.; Karakikes I.; Tsouros I.; Pagoni I.","Polydoropoulou, Amalia (6602644697); Tsirimpa, Athena (16302812600); Karakikes, Ioannis (57202973318); Tsouros, Ioannis (57195940669); Pagoni, Ioanna (55754084400)","6602644697; 16302812600; 57202973318; 57195940669; 55754084400","Mode Choice Modeling for Sustainable Last-Mile Delivery: The Greek Perspective",2022.0,"Sustainability (Switzerland)",14.0,15.0,8976.0,null,null,null,1.0,"10.3390/su14158976","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137251585&doi=10.3390%2fsu14158976&partnerID=40&md5=dcecb47d990acaa06e0a1bd0337343ab","Department of Shipping, Trade and Transport, University of the Aegean, Chios, 82100, Greece","Polydoropoulou A., Department of Shipping, Trade and Transport, University of the Aegean, Chios, 82100, Greece; Tsirimpa A., Department of Shipping, Trade and Transport, University of the Aegean, Chios, 82100, Greece; Karakikes I., Department of Shipping, Trade and Transport, University of the Aegean, Chios, 82100, Greece; Tsouros I., Department of Shipping, Trade and Transport, University of the Aegean, Chios, 82100, Greece; Pagoni I., Department of Shipping, Trade and Transport, University of the Aegean, Chios, 82100, Greece","As the private sector is under heavy pressure to serve the ever-growing e-commerce market, the potential of implementing new disruptive mobility/logistics services for increasing the level of the current last-mile delivery (LMD) services, is emerging. Vehicle automation technology, characterized by high-capacity utilization and asset intensity, appears to be a prominent response to easing this pressure, while contributing to mitigation of the adverse effects associated with the deployment of LMD activities. This research studied the perceptions of Greek end-users/consumers, regarding the introduction of autonomous/automated/driverless vehicles (AVs) in innovative delivery services. To achieve this, a mixed logit model was developed, based on a Stated Preferences (SP) experiment, designed to capture the demand of alternative last-mile delivery modes/services, such as drones, pods, and autonomous vans, compared to traditional delivery services. The results show that the traditional delivery, i.e., having a dedicated delivery person who picks up the parcels at a consolidation point and delivers them directly to the recipients while driving a non-autonomous vehicle—conventional van, bike, e-bike, e-scooter—remains the most acceptable delivery method. Moreover, the analysis indicated that there is no interest yet in deploying home deliveries with drones or AVs, and that participants are unwilling to pay extra charges for having access to more advanced last-mile delivery modes/services. Thus, it is important to promote the benefits of innovative modes and services for LMD, in order to increase public awareness and receptivity in Greece. © 2022 by the authors.","autonomous vehicles; drones; last-mile delivery; mixed logit model; mode choice",{"$nulls":5},"European Commission, EC, (MIS-5047041)","This research is co-financed by Greece and the European Union through the operational programme “Competitiveness, Entrepreneurship and Innovation” in the context of the project “Intelligent Research Infrastructure for Shipping, Supply Chain, Transport and Logistics (ENIRISST+)” (MIS-5047041).","E-Sales and Turnover from E-Sales, EU-27, 2010 to 2019; Number of Internet Users in EU Countries as of December 2020; E-Commerce Statistics for Individuals; Iwan S., Kijewska K., Lemke J., Analysis of parcel lockers’ efficiency as the last mile delivery solution–the results of the research in Poland, Transp. Res. 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Manag, 51, pp. 403-422, (2021); Zeugner-Roth K.P., Zabkar V., Diamantopoulos A., Consumer ethnocentrism, national identity, and consumer cosmopolitanism as drivers of consumer behavior: A social identity theory perspective, J. Int. Mark, 23, pp. 25-54, (2015); Bierlaire M., PythonBiogeme: A short introduction. Report TRANSP-OR 160706, Series on Biogeme, Transport and Mobility Laboratory, School of Architecture, Civil and Environmental Engineering, Ecole Polytechnique Fédérale de Lausanne, (2016); Karakikes I., Nathanail E., Using the Delphi Method to Evaluate the Appropriateness of Urban Freight Transport Solutions, Smart Cities, 3, pp. 1428-1447, (2020); The Delivery Revolution: Are People Ready to Embrace Drones and Robots?, (2021); Liu H., Yang R., Wang L., Liu P., Evaluating initial public acceptance of highly and fully autonomous vehicles, Int. J. Hum. Comp. Inter, 35, pp. 919-931, (2019); Kuru K., Khan W., A Framework for the Synergistic Integration of Fully Autonomous Ground Vehicles with Smart City, IEEE Access, 9, pp. 923-948, (2021); Palmer A., Amazon Wins FAA Approval for Prime Air Drone Delivery Fleet, (2020); COVID-19 Has Changed Online Shopping Forever, Survey Shows, (2020); E-Commerce in the Times of COVID-19, (2021)","I. Karakikes; Department of Shipping, Trade and Transport, University of the Aegean, Chios, 82100, Greece; email: ikarakikes@aegean.gr",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85137251585"]
["Yuan Y.; Xu Z.; Zhang Y.","Yuan, Yayi (57223106039); Xu, Zeshui (55502698400); Zhang, Yixin (57190126079)","57223106039; 55502698400; 57190126079","The DEMATEL–COPRAS hybrid method under probabilistic linguistic environment and its application in Third Party Logistics provider selection",2022.0,"Fuzzy Optimization and Decision Making",21.0,1.0,null,137.0,156.0,19.0,24.0,"10.1007/s10700-021-09358-9","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85104832263&doi=10.1007%2fs10700-021-09358-9&partnerID=40&md5=6f41487191a08d75d671eaf3d7d453f3","Business School, Sichuan University, Chengdu, 610064, China","Yuan Y., Business School, Sichuan University, Chengdu, 610064, China; Xu Z., Business School, Sichuan University, Chengdu, 610064, China; Zhang Y., Business School, Sichuan University, Chengdu, 610064, China","With the emergence of outsourcing logistics and the rapid development of the e-commerce business, Third Party Logistics (TPL) plays an indispensable role in modern business. In the TPL provider selection process, uncertain information brings more challenges to decision makers. This paper uses probabilistic linguistic term sets (PLTSs) to describe uncertain decision making information. Firstly, we propose an improved Decision Making Trial and Evaluation Laboratory method, which allows a certain relationship between decision criteria and calculates criteria weights in multi-criteria decision making (MCDM) problems. Then, in order to make full use of uncertain TPL provider information and maximize the values of data, the probabilistic linguistic complex proportional assessment method is proposed and applied to solve the MCDM problems under probabilistic linguistic environment, which needs much less computation than other MCDM methods. Finally, an application example of TPL provider selection is presented to demonstrate the proposed method. A comparative analysis is further conducted to validate the effectiveness of the proposed method. © 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.","COPRAS method; DEMATEL method; Multiple criteria group decision making; Probabilistic lingustic term sets; Third Party Logistics providers","Linguistics; Outsourcing; Comparative analysis; Complex proportional assessments; Decision making trial and evaluation laboratories; Linguistic environment; Multi-criteria decision making; Third party logistics; Third party logistics providers; Uncertain informations; Decision making",{"$nulls":4},"Teacher-Student Joint Innovation Research Fund of Business School of Sichuan University, (H2018016); UK-China Joint Research and Innovation Partnership Fund, (201806240416); National Natural Science Foundation of China, NSFC, (71771155, 72071135)","This study was funded by the National Natural Science Foundation of China (Nos. 72071135, 71771155), the scholarship under the UK-China Joint Research and Innovation Partnership Fund PhD Placement Programme (No. 201806240416) and the Teacher-Student Joint Innovation Research Fund of Business School of Sichuan University (No. H2018016). ","Dadashpour I., Bozorgi-Amiri A., Evaluation and ranking of sustainable third-party logistics providers using the D-analytic hierarchy process, International Journal of Engineering, 33, 11, pp. 2233-2244, (2020); Das M.C., Sarkar B., Ray S., A framework to measure relative performance of Indian technical institutions using integrated fuzzy AHP and COPRAS methodology, Socio-Economic Planning Sciences, 46, 3, pp. 230-241, (2012); Gabus A., Fontela E., World problems, an invitation to further thought within the framework of DEMATEL, pp. 1-8, (1972); Gorabe D., Pawar D., Pawar N., Selection of industrial robots using complex proportional assessment method, American International Journal of Research in Science, Technology, Engineering and Mathematics, 5, 2, pp. 140-143, (2014); He S.S., Wang Y.T., Peng J.J., Wang J.Q., Risk ranking of wind turbine systems through an improved FMEA based on probabilistic linguistic information and the TODIM method, Journal of the Operational Research Society, (2021); Herrera F., Herrera-Viedma E., Verdegay J.L., A sequential selection process in group decision making with a linguistic assessment approach, Information Sciences, 85, 4, pp. 223-239, (1995); Liao H.C., Jiang L.S., Xu Z.S., Xu J.P., Herrera F., A linear programming method for multiple criteria decision making with probabilistic linguistic information, Information Sciences, 415, pp. 341-355, (2017); Lin M.W., Xu Z.S., Probabilistic linguistic distance measures and their applications in multi-criteria group decision making, Soft Computing Applications for Group Decision-Making and Consensus Modeling, pp. 411-440, (2018); Organ A., Yalcin E., Performance evaluation of research assistants by COPRAS method, European Scientific Journal, 12, 10, pp. 102-109, (2016); Pang Q., Wang H., Xu Z.S., Probabilistic linguistic term sets in multi-attribute group decision making, Information Sciences, 369, pp. 128-143, (2016); Rodriguez R.M., Martinez L., Herrera F., Hesitant fuzzy linguistic term sets for decision making, IEEE Transactions on Fuzzy Systems, 20, 1, pp. 109-119, (2011); Shyur H.J., Shih H.S., A hybrid MCDM model for strategic vendor selection, Mathematical and Computer Modelling, 44, 7-8, pp. 749-761, (2006); Tavana M., Momeni E., Rezaeiniya N., Mirhedayatian S.M., Rezaeiniya H., A novel hybrid social media platform selection model using fuzzy ANP and COPRAS-G, Expert Systems with Applications, 40, 14, pp. 5694-5702, (2013); Wen X., Yan M., Xian J., Yue R., Peng A., Supplier selection in supplier chain management using Choquet integral-based linguistic operators under fuzzy heterogeneous environment, Fuzzy Optimization and Decision Making, 15, 3, pp. 307-330, (2016); Wu X.L., Liao H.C., Xu Z.S., Hafezalkotob A., Herrera F., Probabilistic linguistic MULTIMOORA: A multi-criteria decision making method based on the probabilistic linguistic expectation function and the improved Borda rule, IEEE Transactions on Fuzzy Systems, 26, 6, pp. 3688-3702, (2018); Xia M.M., Xu Z.S., Hesitant fuzzy information aggregation in decision making, International Journal of Approximate Reasoning, 52, 3, pp. 395-407, (2011); Xu Z.S., Uncertain multiple attribute decision making: Methods and applications, (2015); Xu Z.S., Wang H., On the syntax and semantics of virtual linguistic terms for information fusion in decision making, Information Fusion, 34, pp. 43-48, (2016); Yamazaki M., Ishibe K., Yamashita S., Miyamoto I., Kurihara M., Shindo H., An analysis of obstructive factors to welfare service using DEMATEL method, Reports of the Faculty of Engineering, 48, pp. 25-30, (1997); Yazdani M., Alidoosti A., Zavadskas E.K., Risk analysis of critical infrastructures using fuzzy COPRAS, Economic research-Ekonomska istraživanja, 24, 4, pp. 27-40, (2011); Yu P.L., A class of solutions for group decision problems, Management Science, 19, 8, pp. 936-946, (1973); Zavadskas E.K., Kaklauskas A., Multiple criteria evaluation of buildings, (1996); Zhang X., Xing X., Probabilistic linguistic VIKOR method to evaluate green supply chain initiatives, Sustainability, 9, 7, (2017); Zhang Y.X., Xu Z.S., Liao H.C., An ordinal consistency-based group decision making process with probabilistic linguistic preference relation, Information Sciences, 467, pp. 179-198, (2018); Zheng Y.H., Xu Z.S., He Y., Liao H.C., Severity assessment of chronic obstructive pulmonary disease based on hesitant fuzzy linguistic COPRAS method, Applied Soft Computing, 69, pp. 60-71, (2018)","Z. Xu; Business School, Sichuan University, Chengdu, 610064, China; email: xuzeshui@263.net",null,"Springer",{"$nulls":5},1.5684539E7,null,null,null,"English","Fuzzy Optim. Decis. Mak.","Article","Final",null,"Scopus","2-s2.0-85104832263"]
["Lee S.Y.; Han S.R.; Song B.D.","Lee, Seung Yeob (57484208100); Han, So Rim (57484208200); Song, Byung Duk (55320728900)","57484208100; 57484208200; 55320728900","Simultaneous cooperation of Refrigerated Ground Vehicle (RGV) and Unmanned Aerial Vehicle (UAV) for rapid delivery with perishable food",2022.0,"Applied Mathematical Modelling",106.0,null,null,844.0,866.0,22.0,16.0,"10.1016/j.apm.2022.02.024","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85126083111&doi=10.1016%2fj.apm.2022.02.024&partnerID=40&md5=2a7be1794ac80948eaae542205cae446","Department of Industrial and Management Systems Engineering, Kyung Hee University, 1732 Deogyeong-daero, Yongin-si, Gyeonggi-do, Giheung-gu, South Korea; Department of Big Data Analytics, Graduate School, Kyung Hee University, 1732 Deogyeong-daero, Giheung-gu, Gyeonggi-do, Yongin-si, South Korea","Lee S.Y., Department of Industrial and Management Systems Engineering, Kyung Hee University, 1732 Deogyeong-daero, Yongin-si, Gyeonggi-do, Giheung-gu, South Korea; Han S.R., Department of Big Data Analytics, Graduate School, Kyung Hee University, 1732 Deogyeong-daero, Giheung-gu, Gyeonggi-do, Yongin-si, South Korea; Song B.D., Department of Industrial and Management Systems Engineering, Kyung Hee University, 1732 Deogyeong-daero, Yongin-si, Gyeonggi-do, Giheung-gu, South Korea, Department of Big Data Analytics, Graduate School, Kyung Hee University, 1732 Deogyeong-daero, Giheung-gu, Gyeonggi-do, Yongin-si, South Korea","With the growth of e-commerce, various types of last-mile delivery services have emerged to meet customer needs. Among the most notable of these are “rapid delivery” and “perishable food delivery” services. Owing to their advantages, the use of unmanned aerial vehicles (UAVs), which are both fast and inexpensive, has received considerable interest for rapid delivery. However, because of the inherent limitations of UAVs, they are used in conjunction with other ground vehicles. In contrast, maintaining freshness during delivery of perishable food is crucial for customer satisfaction and hygiene. Consequently, the cooperative operation of refrigerated ground vehicles (RGVs) with UAVs is necessary for rapid and fresh delivery services. RGVs can focus on the delivery of perishable foods and large-sized general products in such an operation, whereas UAVs can focus on small-sized general goods. In this study, the cooperative operation of RGVs and UAVs was investigated for the rapid delivery of perishable food. Mixed integer linear programming (MILP) was developed to derive optimal delivery schedules for RGVs and UAVs with the objective of minimizing the maximum service completion time of delivery vehicles. Additionally, an RGV-UAV route generating algorithm (R-U RGA) was presented to efficiently derive optimal, near-optimal, or qualified vehicle schedules when the MILP fails to derive optimal schedules in a reasonable time. The validity of the proposed MILP model was verified through a case study. The usefulness of the R-U RGA was confirmed through numerical experiments conducted on instances of various sizes. Additionally, numerical tests were performed to compare the benefits of the RGV-only delivery system and the proposed cooperative delivery system. These tests conducted in terms of economic, environmental, and service factors; they quantitatively elucidate the tradeoffs between the two systems. © 2022 Elsevier Inc.","Heuristic; Last mile delivery; Mathematical optimization; Perishable food; Refrigerated ground vehicle; Unmanned aerial vehicle","Antennas; Customer satisfaction; Ground vehicles; Unmanned aerial vehicles (UAV); Cooperative operation; Delivery service; Heuristic; Integer Linear Programming; Last mile; Last mile delivery; Mathematical optimizations; Mixed integer linear; Perishable food; Refrigerated ground vehicle; Integer programming",{"$nulls":4},"National Research Foundation of Korea, NRF, (2019R1F1A1060289)","This work was supported by the National Research Foundation of Korea (NRF) funded by the Korean Government under Grant 2019R1F1A1060289. ","Uatay G., Cho D.S., Lee H.Y., Gaging customer response to dawn delivery service using social big data, Culinary Sci. Hospital. 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Technol., 12, 2, pp. 239-250, (2014); Chao C., Zhihui T., Baozhen Y., Optimization of two-stage location–routing–inventory problem with time-windows in food distribution network, Annal. Oper. Res., 273, 1-2, pp. 111-134, (2019); Goodchild A., Toy J., Delivery by drone: an evaluation of unmanned aerial vehicle technology in reducing CO2 emissions in the delivery service industry, Transp. Res. Part D, 61, pp. 58-67, (2018); Eun J., Song B.D., Lee S., Lim D.E., Mathematical investigation on the sustainability of UAV logistics, Sustainability, 11, 21, (2019)","B.D. Song; Department of Industrial and Management Systems Engineering, Kyung Hee University, Giheung-gu, 1732 Deogyeong-daero, Yongin-si, Gyeonggi-do, South Korea; email: bdsong@khu.ac.kr",null,"Elsevier Inc.",{"$nulls":5},"0307904X",null,"AMMOD",null,"English","Appl. Math. Model.","Article","Final",null,"Scopus","2-s2.0-85126083111"]
["Che Z.-H.; Chiang T.-A.; Luo Y.-J.","Che, Zhen-Hua (8336607800); Chiang, Tzu-An (15069627200); Luo, Yun-Jhen (57459982600)","8336607800; 15069627200; 57459982600","Multiobjective Optimization for Planning the Service Areas of Smart Parcel Locker Facilities in Logistics Last Mile Delivery",2022.0,"Mathematics",10.0,3.0,422.0,null,null,null,17.0,"10.3390/math10030422","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124975404&doi=10.3390%2fmath10030422&partnerID=40&md5=44cbcbab313597f5f6c2604a077fd885","Department of Industrial Engineering and Management, National Taipei University of Technology, Taipei, 106, Taiwan; Department of Business Administration, National Taipei University of Business, Taipei, 100, Taiwan; Manufacturing Department, Taiwan Semiconductor Manufacturing Company, Taichung, 407, Taiwan","Che Z.-H., Department of Industrial Engineering and Management, National Taipei University of Technology, Taipei, 106, Taiwan; Chiang T.-A., Department of Business Administration, National Taipei University of Business, Taipei, 100, Taiwan; Luo Y.-J., Manufacturing Department, Taiwan Semiconductor Manufacturing Company, Taichung, 407, Taiwan","The planning of the location service areas of smart parcel locker facilities became a critical aspect of logistics last mile delivery. In e-commerce, the efficiency of delivering merchandise from retailer warehouses to customers determines the competitiveness of retailers and delivery operators. The considerable increases in e-commerce transactions and safety concerns under the COVID-19 (Coronavirus disease 2019) pandemic made home delivery services even more inefficient than before, which resulted in the considerable increase in social costs. In numerous countries, smart parcel lockers were adopted to increase delivery efficiency, decrease the risk of COVID-19 infection, and reduce the burden on society. This study proposed a multiobjective optimization mathematical model for investigating the planning of the location service areas of smart parcel locker facilities, and then the optimization mathematical model was solved using a combination of the Taguchi method (TA) and nondominant sorting genetic algorithm II (NSGA-II). Finally, this composite approach was applied to a case study in producing favorable solutions for facility location service area planning. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.","E-commerce; Home delivery; Logistics last mile delivery; Nondominant sorting genetic algorithm II; Smart parcel locker",{"$nulls":5},"Ministry of Science and Technology, Taiwan, MOST, (109-2221-E-027-077, MOST 110-2221-E-027-111)","This work is supported by the Ministry of Science and Technology of Taiwan (MOST 109-2221-E-027-077 and MOST 110-2221-E-027-111).","Chevalier S., Global Retail e-Commerce Sales 2014-2024, Statista, (2021); Goodman R.W., Whatever you call it, just don’t think of last-mile logistics, last, Glob. Logist. Supply Chain. 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Soft Comput, 65, pp. 280-291, (2018); Zitzler E., Laumanns M., Thiele L., SPEA2: Improving the strength pareto evolutionary algorithm, Proceedings of the EUROGEN 2001, pp. 95-100, (2002); Rahimi-Vahed A.R., Mirghorbani S.M., Rabbani M., A new particle swarm algorithm for a multi-objective mixed-model assembly line sequencing problem, Soft Comput, 11, pp. 997-1012, (2007); Farsangi M.M., Nezamabadi-Pour H., Lee K.Y., Multi-objective VAr planning with SVC for a large power system using PSO and GA, Proceedings of the 2006 IEEE PES Power Systems Conference and Exposition, pp. 274-279, (2002); Rojas I., Gonzalez J., Pomares H., Merelo J.J., Castillo P.A., Romero G., Statistical analysis of the main parameters involved in the design of a genetic algorithm, IEEE Trans. Syst. Man Cybern. Syst, 32, pp. 31-37, (2002); Su P.L., Chen Y.S., Implementation of a genetic algorithm on MD-optimal designs for multivariate response surface models, Expert Syst. Appl, 39, pp. 3207-3212, (2012); Ghezavati V., Hosseinifar P., Application of efficient metaheuristics to solve a new bi-objective optimization model for hub facility location problem considering value at risk criterion, Soft Comput, 22, pp. 195-212, (2018); Rayat F., Musavi M., Bozorgi-Amiri A., Bi-objective reliable location-inventory-routing problem with partial backordering under disruption risks: A modified AMOSA approach, Appl. Soft Comput, 59, pp. 622-643, (2017)","T.-A. Chiang; Department of Business Administration, National Taipei University of Business, Taipei, 100, Taiwan; email: phdallen@ntub.edu.tw",null,"MDPI",{"$nulls":5},2.227739E7,null,null,null,"English","Mathematics","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85124975404"]
["Luo N.","Luo, Ning (57608471800)",5.76084718E10,"Innovation of E-Commerce Development Model under the Background of Artificial Intelligence and Wireless Communication",2022.0,"Wireless Communications and Mobile Computing",2022.0,null,8572911.0,null,null,null,3.0,"10.1155/2022/8572911","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85130373553&doi=10.1155%2f2022%2f8572911&partnerID=40&md5=bff7f5ff364cc97928b87553205cd6a9","Finance, Heriot-Watt University, Edinburgh, EH144AS, United Kingdom","Luo N., Finance, Heriot-Watt University, Edinburgh, EH144AS, United Kingdom","E-commerce refers to the business operation and profit model based on the network environment. Studying the e-commerce model will help to tap the development potential of e-commerce, innovate the content and form of e-commerce, and also help e-commerce companies expand marketing channels and improve sales capabilities. There are many types of e-commerce models, such as BtoB, BtoC, and CtoC, as well as new models such as BtoQ and BtoB. With the development of wireless communications and artificial intelligence, the market scale of e-commerce has gradually expanded, and e-commerce has become a mainstream consumer channel for people. Promoting the development of e-commerce is an issue that e-commerce companies need to pay attention to. This article uses questionnaire surveys and case analysis methods to study e-commerce companies. The results show that the e-commerce market is huge, but the traditional e-commerce model also has a series of problems. It also proposes innovative paths for e-commerce development models, such as logistics acceleration, brand innovation, and payment method innovation, which have important reference significance for the development of e-commerce enterprises. It is suggested that different types of enterprises combine their own comprehensive strength and actual needs to choose e-commerce development strategies suitable for their own development, so as to achieve sustainable development.  © 2022 Ning Luo.",null,"Artificial intelligence; Planning; Surveys; Sustainable development; Business operation; Development model; E- commerces; E-commerce development; E-commerce model; Model-based OPC; Network environments; Operations Modeling; Profit model; Wireless communications; Electronic commerce",{"$nulls":6},"Kuang Y.C., Research on mobile e-commerce business models based on smart terminals, Chinese Market, 55, 41, pp. 114-115, (2016); Sun K., Lu Z.L., Research on the application development trend of artificial intelligence in e-commerce, Guizhou Social Sciences, 61, 9, pp. 136-143, (2019); Fang F., Research on mobile e-commerce marketing model based on smart phones, E-commerce, 49, 4, pp. 63-64, (2020); Ma S.G., Song H.X., Research on countermeasures for the development of cross-border e-commerce enterprises driven by artificial intelligence, Business Economics, 531, 11, pp. 161-163, (2020); Liu M.L., Wang J., Research on the integration path of artificial intelligence technology and cross-border e-commerce talent training, Market Modernization, 892, 7, pp. 65-66, (2019); Xiao C.Q., Research on the characteristics, status quo and trend of the intelligent development of e-commerce, Market Modernization, 924, 15, pp. 39-42, (2020); Wang C., Guo W.G., Research on the development countermeasures of Anhui agricultural products E-commerce based on O<sub>2</sub>O model, Rural Practical Science and Technology Information, 22, 11, pp. 14-17, (2019); Li B., Xiao G., Lu R., Deng R., Bao H., On feasibility and limitations of detecting false data injection attacks on power grid state estimation using D-FACTS devices, IEEE Transactions on Industrial Informatics, 16, 2, pp. 854-864, (2020); Mi C., Chen J., Zhang Z., Huang S., Postolache O., Visual sensor network task scheduling algorithm at automated container terminal, IEEE Sensors Journal, 22, 6, pp. 6042-6051, (2022); Huang L., A preliminary study on artificial intelligence and E-commerce management, Marketing Circle, 43, pp. 233-234, (2019); Yang K.Y., Research on cross-border e-commerce logistics optimization based on artificial intelligence technology, Modern Economic Information, 12, pp. 372-372, (2019); Ju X., Fan C., Wang M., Li R., Discussion on the application of artificial intelligence in e-commerce, Electronic Commerce, 10, pp. 21-22, (2020); Zhu G., Zhu Z., Zhu Y., Ge H., Theory and case analysis of cross-border e-commerce logistics system construction under the background of artificial intelligence, Logistics Engineering and Management, 40, 11, pp. 31-35, (2018); Zhao E.G., Research on the integration of e-commerce and artificial intelligence technology, China Science and Technology Information, 23, pp. 115-116, (2017); Zhu S.S., Yang S.X., Qiu N., Research on artificial intelligence to promote the development of smart logistics, Science & Technology Information, 17, 25, pp. 246-247, (2019); Lin Z., Research on the development path of E-commerce in the \"internet +\" era, Modern Marketing (Late Period), 10, pp. 110-111, (2020); Wu L., Research on the \"smart+\" e-commerce innovation and entrepreneurship training model of college students using visual internet technology in 5G environment, Computer Knowledge and Technology, 16, 24, pp. 239-241, (2020); Lin J.H., Analysis on the application of artificial intelligence technology in the field of e-commerce, China Business Forum, 45, 2, pp. 19-20, (2019); Zhu Y.Q., Tang N., Analysis of the current situation of Suzhou cross-border e-commerce export logistics, Industry and Technology Forum, 21, 3, (2022); Lv F.H., Analysis of marketing channel integration in e-commerce environment, Business 2.0 (Economic Management), 2, 3, (2022); Zijing H., Overseas live-streaming e-commerce companies are actively testing the tide, Chinese and Foreign Toy Manufacturing, 1, (2022); Wang Y., Internet +\" rural e-commerce development strategy, Cooperative Economy and Technology, 2, (2022); Lin X., Xiong C., Jian L., Exploration on the training mode of e-commerce professionals based on the background of innovation and integration - Taking the Guangdong Ocean Engineering Vocational and Technical School as an example, Vocational Education, 1, 2, (2022); Wang J., Reflections on the marketing of retail industry in the e-commerce era, China Business Theory, 1, (2022); Rao J.W., Research on the marketing mode of agricultural products in the e-commerce era, Shanghai Business, 1, (2022); Cao S.S., The application of e-commerce in the marketing of small and medium-sized enterprises, Time-honored Brand Marketing, 1, (2022); Li K.J., Liu L.S., Thinking about the orientation of e-commerce professionals training, Shanghai Business, 1, (2022); Wang J.L., Research on precision marketing of e-commerce enterprises under the background of big data, The Economist, 1, (2022); Lei Y., Cao H., Zeng H., Dong Y., Feng W., Ding K., Hao X., Wang Z., Zhang Y., Terahertz wireless communication technology for future large-capacity communication, Telemetry and Remote Control, 42, 6, (2021); Liu J.M., Key technologies and development status of 5G wireless communication, China New Communication, 23, 6, (2021); Chen J.C., The impact of 5G mobile wireless communication technology on the development of the Internet of Things industry, Electronic Technology and Software Engineering, 15, (2021); Zhang L.Q., Research on the application of ZigBee wireless communication technology based on the era of tea culture, Fujian Tea, 43, 1, (2021)","N. Luo; Finance, Heriot-Watt University, Edinburgh, EH144AS, United Kingdom; email: luoning_edu@outlook.com",null,"Hindawi Limited",{"$nulls":5},1.5308669E7,null,null,null,"English","Wireless Commun. Mobile Comput.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85130373553"]
["Wang S.","Wang, Shenxiang (57204788023)",5.7204788023E10,"Study on Cold Chain Logistics Operation and Risk Control of Fresh e-Commerce Products",2022.0,"Advances in Multimedia",2022.0,null,7272370.0,null,null,null,2.0,"10.1155/2022/7272370","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135975318&doi=10.1155%2f2022%2f7272370&partnerID=40&md5=9b3a96bfb8b1c20279612fd87dc3a000","College of Intelligent Cold-chain Industries, Guangzhou College of Technology and Business, Guangdong, Guangzhou, 510850, China","Wang S., College of Intelligent Cold-chain Industries, Guangzhou College of Technology and Business, Guangdong, Guangzhou, 510850, China","With the rapid development of the Internet, my country's e-commerce market has been very active in recent years, and the number of e-commerce platforms and the volume of product transactions have achieved rapid development. However, through the investigation of the main circulation products of e-commerce brands, it can be found that the output value of my country's e-commerce industry as a whole in the fresh food field is very low. Many fresh products are prone to various risks during the circulation process, resulting in large losses on the platform and online agricultural products e-commerce. There is a shortage of fresh cold chain equipment and cold chain technicians, which directly affects the stable and healthy development of fresh cold chain logistics in China. This paper analyzes the existing operation mode of e-commerce, analyzes the main bottleneck of the operation of the fresh cold chain, and puts forward corresponding suggestions to enhance the awareness of risk control, so as to better promote the benign operation of agricultural products cold logistics and provide some reference for the optimization of e-commerce fresh cold chain logistics.  © 2022 Shenxiang Wang.",null,"Electronic commerce; Cold chain; Cold chain logistics; Commerce platforms; E- commerces; Fresh food; Logistic operations; Operations control; Output values; Paper analysis; Risks controls; Agricultural products",{"$nulls":6},"Viu-Roig M., Alvarez-Palau E.J., The impact of E-commerce-related last-mile logistics on cities: A systematic literature review, Sustainability, 12, 15, pp. 235-238, (2020); Witkowski K., Koralewska M., Huk K., Logistics models in E-commerce, Research Papers Faculty of Materials Science and Technology Slovak University of Technology, 28, 46, pp. 90-97, (2020); Kong X., Zhong R.Y., Zhao Z., Cyber physical ecommerce logistics system: An implementation case in Hong Kong, Computers & Industrial Engineering, 139, pp. 1-15, (2020); Sachan R.K., Kumar T., Kushwaha D.S., Solving the e-commerce logistics problem using anti-predatory NIA, International Journal of Intelligent Engineering Informatics, 8, 1, (2020); Kamchatova E., Logistics providers as integrators of intelligent supply chain systems: An innovative aspect, Scientific Research and Development. Economics of the Firm, 9, 2, pp. 28-34, (2020); Mazlan M.T., Challenge E-commerce to the logistics courier services provider during MCO in Malaysia, IOSR Journal of Business and Management, 23, 2, pp. 59-62, (2021); Cahyadi E.R., Widianti K.R., Slamet A.S., The use behavior of tracking and tracing services in E-commerce logistics, Jurnal Manajemen Dan Organisasi, 12, 1, pp. 10-20, (2021); Kim J., Kim M., Im S., Competitiveness of e Commerce firms through ESG logistics, Sustainability, 13, 18, pp. 44-48, (2021); Settey T., Gnap J., Benova D., The growth of E-commerce due to COVID-19 and the need for urban logistics centers using electric vehicles: Bratislava case study, Sustainability, 13, 8, pp. 336-341, (2021); Dobroselskyi M., Madlenak R., Laitkep D., Analysis of return logistics in e-commerce companies on the example of the Slovak Republic, Transportation Research Procedia, 55, pp. 318-325, (2021); Das D., Kumar R., Rajak M.K., Designing a reverse logistics network for an E-commerce firm: A case study, Operations and Supply Chain Management: International Journal, 13, 1, pp. 48-63, (2020); Lahkani M.J., Wang S., Urbanski M., Egorova M., Sustainable B2B E-commerce and blockchain-based supply chain finance, Sustainability, 12, 33, pp. 54-59, (2020); Ren S., Choi T.M., Lee K.M., Lin L., Intelligent service capacity allocation for cross-border-E-commerce related third-party-forwarding logistics operations: A deep learning approach, Transportation Research Part E: Logistics and Transportation Review, 134, (2020); Giuffrida M., Mangiaracina R., Perego A., Cross-border B2C e-commerce to China: An evaluation of different logistics solutions under uncertainty, International Journal of Physical Distribution & Logistics Management, 50, 3, pp. 56-62, (2020); Rath S.B., Basu P., Mandal P., Financing models for an online seller with performance risk in an E-commerce marketplace, Transportation Research Part E: Logistics and Transportation Review, 155, 34, pp. 668-674, (2021); Giuffrida M., Jiang H., Mangiaracina R., Investigating the relationships between uncertainty types and risk management strategies in cross-border e-commerce logistics, International Journal of Logistics Management, 32, 4, pp. 39-44, (2021); Han J.W., Zuo M., Zuo W.Y., Zuo J.H., Lu E.L., Yang X.T., A comprehensive review of cold chain logistics for fresh agricultural products: Current status, challenges, and future trends, Trends in Food Science & Technology, 109, 12, pp. 536-551, (2021); Du H., Study on risk control of fresh supply chain demand interruption under computer E-commerce environment, Journal of Physics: Conference Series, 1992, 3, (2021); Adeniran A.O., Akinsehinwa F.O., Olorunfemi S.O., Factors influencing the acceptance and patronage of E-commerce logistics operations in Nigeria, Bulletin of the National Research Centre, 46, 1, pp. 675-683, (2022); Asdecker B., Building the E-commerce supply chain of the future: What influences consumer acceptance of alternative places of delivery on the last-mile, Logistics, 5, 37, pp. 65-70, (2021)","S. Wang; College of Intelligent Cold-chain Industries, Guangzhou College of Technology and Business, Guangzhou, Guangdong, 510850, China; email: v11314014@stu.ahu.edu.cn",null,"Hindawi Limited",{"$nulls":5},1.687568E7,null,null,null,"English","Adv. Multimedia","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85135975318"]
["Mu W.; Ding H.","Mu, Wei (57909672100); Ding, Heping (57665619000)","57909672100; 57665619000","E-Commerce Intelligent Logistics Data Based on Neural Network Model",2022.0,"Mobile Information Systems",2022.0,null,8993365.0,null,null,null,1.0,"10.1155/2022/8993365","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85138969707&doi=10.1155%2f2022%2f8993365&partnerID=40&md5=2a08733592731d2577fe89fd8b456913","College of Business, Suzhou University, Anhui, Suzhou, 234000, China; Center for International Education, Philippine Christian University, Manila, 1004, Philippines","Mu W., College of Business, Suzhou University, Anhui, Suzhou, 234000, China; Ding H., College of Business, Suzhou University, Anhui, Suzhou, 234000, China, Center for International Education, Philippine Christian University, Manila, 1004, Philippines","Not only e-commerce is developing rapidly, but also intelligent logistics technology is becoming more and more mature. In daily life, we can track the logistics information synchronously. On the smartphone app, the logistics information can be viewed at any time. However, the current processing algorithms are not enough for the exponentially increasing data volume and increasingly complex data types. This paper aims to analyze the massive data generated by e-commerce intelligent logistics. In this paper, a new classification algorithm is proposed, which is improved on the ordinary ladder classification algorithm, and artificial neural networks are added for automatic iterative update learning, which can automatically classify a large amount of data. The experimental results show that the classification error rate of the improved algorithm is less than 5%, and when the sample size is less than 30,000, the improved algorithm can significantly outperform the original algorithm. © 2022 Wei Mu and HePing Ding.",null,"Electronic commerce; Neural networks; Classification algorithm; Current processing; Daily lives; E- commerces; Improved * algorithm; Logistics information; Logistics technologies; Neural network model; Processing algorithms; Smartphone apps; Iterative methods",{"$nulls":6},"Eric Y.H., Chen, A neural network model of cortical information processing in schizophrenia II - Role of hippocampal-cortical interaction: A review and a model, Canadian Journal of Psychiatry, 40, 1, pp. 21-26, (2017); Kasap B., Van Opstal A.J., A spiking neural network model of the midbrain superior colliculus that generates saccadic motor commands, Biological Cybernetics, 111, 3-4, pp. 249-268, (2017); Funes E., Allouche Y., Beltran G., Aguliera M.P., Jimenez A., A predictive artificial neural network model as a simulator of the extra virgin olive oil elaboration process, Journal of Near Infrared Spectroscopy, 25, 4, pp. 278-285, (2017); Kang I.S., Yang Y.K., Lee H.E., Park J.C., Moon J.W., Development of an artificial neural network model for a predictive control of cooling systems, KIEAE Journal, 17, 5, pp. 69-76, (2017); Kirch M., Poenicke O., Richter K., RFID in logistics and production -applications, research and visions for smart logistics zones, Procedia Engineering, 178, COMPLETE, pp. 526-533, (2017); Humayun M., Jhanjhi N.Z., Hamid B., Ahmed G., Emerging smart logistics and transportation using IoT and blockchain, IEEE Internet of Things Magazine, 3, 2, pp. 58-62, (2020); Choi H.J., Jung H.J., Smart logistics trends and application of IoT in Pyeongtaek P, The E-Business Studies, 18, 6, pp. 145-158, (2017); Guan S., Smart E-commerce logistics construction model based onBD analytics[J], Journal of Intelligent and Fuzzy Systems, 40, 2, pp. 1-9, (2020); Prest G., The new era of smart city logistics, Inbound Logistics, 37, 11, (2017); Wl A., Jh A., Xy A., Tang O., Smart logistics transformation collaboration between manufacturers and logistics service providers: A supply chain contracting perspective - ScienceDirect, Journal of Management Science and Engineering, 6, 1, pp. 25-52, (2021); Issaoui Y., Khiat A., Bahnasse A., Smart logistics: Study of the application of blockchain technology[J], Procedia Computer Science, 160, pp. 267-217, (2019); Zsifkovits H., Woschank M., Smart Logistics - Technologiekonzepte und Potentiale, BHM Berg- Und Hüttenmännische Monatshefte, 164, 1, pp. 42-45, (2019); Matthias B., Smart Logistics verbindet Virtualitat mit Realitat, SMM: Schweizer Maschinenmarkt, 119, 8, pp. 42-43, (2018); Wen J., He L., Zhu F., Swarm robotics control and communications: Imminent challenges for next generation smart logistics, IEEE Communications Magazine, 56, 7, pp. 102-107, (2018); Mihatsch G., Reith U., Kniess P., Banerjee A., Smart logistics from the first mile to the last, ATZ Worldwide, 120, 11, pp. 46-51, (2018); Dunja K., Analyse smart logistics: Zukunftsaussichten der Lieferkonzepte[J], IBusiness Executive Summary, 27, 5, pp. 26-27, (2017); Leonard, Heilig, Stefan, SMART PORT LOGISTICS OPPORTUNITIES and CHALLENGES for TRANSITIONING to SMARTER PORT OPERATIONS, Port Technology International, (2017); Mario G.C.A.C., Filippo P., Gigliola V., Erina F., Nedo C., Rosa D.L., Evaluating the impact of smart technologies on harbor's logistics via BPMN modeling and simulation, Information Technology and Management, 18, 3, pp. 223-239, (2017); Cimino M.G.C.A., Palumbo F., Vaglini G., Ferro E., Celandroni N., La Rosa D., Evaluating the impact of smart technologies on harbor's logistics via BPMN modeling and simulation, Information Technology and Management, 18, 3, pp. 223-239, (2017); Liu S., Zhang Y., Liu Y., Wang L., Wang X.V., An \"internet of Things\" enabled dynamic optimization method for smart vehicles and logistics tasks, Journal of Cleaner Production, 215, pp. 806-820, (2019); Sun F., Shi G., Study on the Application of Big Data Techniques for the Third-Party Logistics Using Novel Support Vector Machine algorithm, Journal of Enterprise Information Management, 35, pp. 1168-1184, (2021)","H. Ding; College of Business, Suzhou University, Suzhou, Anhui, 234000, China; email: dingheping@ahszu.edu.cn",null,"Hindawi Limited",{"$nulls":5},"1574017X",null,null,null,"English","Mob. Inf. Sys.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85138969707"]
["Moganathan S.A.S.; Razali S.N.A.B.M.; Mustapha A.; Sukiman S.L.B.; Rahman R.A.; Shafi M.A.","Moganathan, Shamine A/P S. (57963028800); Razali, Siti Noor Asyikin binti Mohd (57192414066); Mustapha, Aida (57200530694); Sukiman, Safra Liyana binti (57218764112); Rahman, Rosshairy Abd (55534309400); Shafi, Muhammad Ammar (56656106000)","57963028800; 57192414066; 57200530694; 57218764112; 55534309400; 56656106000","Comparison of Metaheuristic Techniques for Parcel Delivery Problem: Malaysian Case Study",2022.0,"International Journal of Advanced Computer Science and Applications",13.0,10.0,null,266.0,274.0,8.0,0.0,"10.14569/IJACSA.2022.0131033","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85141803856&doi=10.14569%2fIJACSA.2022.0131033&partnerID=40&md5=fb9964a00d3359acf26b85f5c6779572","Department of Mathematics and Statistics Faculty of Applied Sciences and Technology, Universiti Tun Hussein Onn Malaysia Pagoh Education Hub, Johor, Pagoh, 84600, Malaysia; Centre for Language Studies, Universiti Tun Hussein Onn Malaysia, Johor, Parit Raja,Batu Pahat, 86400, Malaysia; School of Quantitative Sciences Universiti Utara Malaysia, Kedah, Sintok, 06010, Malaysia; Department of Technology and Management Faculty of Technology Management and Business Universiti Tun Hussein Onn Malaysia, Johor, Parit Raja,Batu Pahat, 86400, Malaysia","Moganathan S.A.S., Department of Mathematics and Statistics Faculty of Applied Sciences and Technology, Universiti Tun Hussein Onn Malaysia Pagoh Education Hub, Johor, Pagoh, 84600, Malaysia; Razali S.N.A.B.M., Department of Mathematics and Statistics Faculty of Applied Sciences and Technology, Universiti Tun Hussein Onn Malaysia Pagoh Education Hub, Johor, Pagoh, 84600, Malaysia; Mustapha A., Department of Mathematics and Statistics Faculty of Applied Sciences and Technology, Universiti Tun Hussein Onn Malaysia Pagoh Education Hub, Johor, Pagoh, 84600, Malaysia; Sukiman S.L.B., Centre for Language Studies, Universiti Tun Hussein Onn Malaysia, Johor, Parit Raja,Batu Pahat, 86400, Malaysia; Rahman R.A., School of Quantitative Sciences Universiti Utara Malaysia, Kedah, Sintok, 06010, Malaysia; Shafi M.A., Department of Technology and Management Faculty of Technology Management and Business Universiti Tun Hussein Onn Malaysia, Johor, Parit Raja,Batu Pahat, 86400, Malaysia","Most people preferred e-commerce ensuing the Coronavirus Disease-2019 (COVID-19) outbreak, resulting in delivery companies receiving large quantities of parcels to be delivered to clients. Hurdle emerges when delivery person needs to convey items to a large number of households in a single journey as they never face this situation before. As a result, they seek the quickest way during the trip to reduce delivery costs and time. Since the delivery challenge has been classified as an NP-hard (non-deterministic polynomial-time hard)) problem, this study aims to search the shortest distance, including the runtime for the real case study located in Melaka, Malaysia. Hence, two metaheuristic approaches are compared in this study namely, Ant-Colony Optimization (ACO) and Genetic Algorithm (GA). The results show that the GA strategy outperforms the ACO technique in terms of distance, price, and runtime for moderate data sizes that is less than 90 locations. © 2022, International Journal of Advanced Computer Science and Applications. All Rights Reserved.","Ant-colony optimization; Comparison; Cost; Delivery problem; Genetic algorithm; Runtime","Ant colony optimization; Artificial intelligence; Polynomial approximation; Case-studies; Comparison; Delivery company; Delivery costs; Delivery problems; E- commerces; Malaysians; Meta-heuristic techniques; Parcel delivery; Runtimes; Genetic algorithms",{"$nulls":4},"Universiti Tun Hussein Onn Malaysia, UTHM, (E15216, H633, Q162)","ACKNOWLEDGMENT Communication of this research is made possible through monetary assistance by Universiti Tun Hussein Onn Malaysia and the UTHM Publisher’s Office via Publication Fund E15216, TIER 1 Grant (Q162) and also GPPS Grant (H633).","How COVID-19 triggered the digital and e-commerce turning point, (2022); Ongcunaruk W., Ongkunaruk P., Janssens G. K., Genetic algorithm for a delivery problem with mixed time windows, Computers & Industrial Engineering, 159, (2021); Malaysia E-Commerce Digital Trends in 2022 and the Role of Logistics; Bhatti A., Akram H., Basit H. M., Khan A. U., Raza S. M., Naqvi M. B., E-commerce trends during COVID-19 Pandemic, International Journal of Future Generation Communication and Networking, 13, 2, pp. 1449-1452, (2020); eCommerce - Malaysia | Statista Market Forecast, (2022); Gohain M., IMPACT OF COVID-19 ON MALAYSIAN ECOMMERCE, International Journal on Recent Trends in Business and Tourism (IJRTBT), 5, 4, pp. 8-10, (2021); Kee D. M. H., Nasser S. N. A., Sany N. S. M., Azhar T. I., Roslan Z. H., Amli N. A., The strategy, impact, and challenges faced by Pos Malaysia Berhad during the COVID-19 crisis, Journal of the Community Development in Asia (JCDA), 4, 2, pp. 13-25, (2021); Mazlan M., Challenge E-Commerce to the logistics courier services provider during MCO in Malaysia, IOSR Journal of Business and Management, 23, 2, pp. 59-62, (2021); Muller J., Malaysia: domestic courier items delivered 2020 | Statista, (2022); Konstantakopoulos G. D., Gayialis S. P., Kechagias E. P., Vehicle routing problem and related algorithms for logistics distribution: A literature review and classification, Operational research, 22, 3, (2022); Herdianti W., Gunawan A. A., Komsiyah S., Distribution cost optimization using pigeon inspired optimization method with reverse learning mechanism, Procedia Computer Science, 179, pp. 920-929, (2021); Issues and Challenges of Logistics in Malaysia: a Perspective - PHDessay.com, (2022); Huerta I. I., Neira D. A., Ortega D. A., Varas V., Godoy J., Asin-Acha R., Improving the state-of-the-art in the Traveling Salesman Problem: An Anytime Automatic Algorithm Selection, Expert Systems with Applications, 187, (2022); Boryczka U., Szwarc K., An effective hybrid harmony search for the asymmetric travelling salesman problem, Engineering Optimization, (2019); Grahadian K., Sandy I. A., A New Metaheuristic Farmland Fertility Algorithm to Solve Asymmetric Travelling Salesman Problem, International Journal of Engineering Technology and Natural Sciences, 3, 1, pp. 9-15, (2021); BAS E., ULKER E., Dıscrete social spider algorithm for the travelling salesman problem, Artificial Intelligence Review, 54, 2, pp. 1063-1085, (2021); Skinderowicz R., Improving Ant Colony Optimization efficiency for solving large TSP instances, Applied Soft Computing, 120, (2022); Eremeev A., Kovalenko Y., Optimal recombination and adaptive restarts improve GA performance on the asymmetric TSP, Proceedings of the Genetic and Evolutionary Computation Conference Companion, pp. 29-30, (2021); Saravana S., Arulselvi S., A Fuzzy-GA Based controlling System for Wireless sensor networks, I3CAC 2021: Proceedings of the First International Conference on Computing, Communication and Control System, I3CAC 2021; Schroeders U., Wilhelm O., Olaru G., Meta-heuristics in short scale construction: ANT colony optimization and genetic algorithm, PLoS One, 11, 11, (2016); Mallawaarachchi V., How to define a Fitness Function in a Genetic Algorithm?, (2022); Kirk J., Multiple traveling salesmen problem – genetic algorithm, MATLAB Central File Exchange, (2021); Qi A., Zhao D., Yu F., Heidari A. A., Wu Z., Cai Z., Chen M., Directional mutation and crossover boosted ant colony optimization with application to COVID-19 X-ray image segmentation, Computers in biology and medicine, 148, (2022); Almaalei N. N. H., Razali S. N. A. M., Review of ACO algorithm on network and scheduling problem, Compusoft, 8, 7, (2019); Yoo K.S., Han S.Y., A modified ant colony optimization algorithm for dynamic topology optimization, Computers and Structures, 123, pp. 68-78, (2013); Almaalei N. N., Razali S. N. A. M., Abdulwahab A. N. M., Alduais M., An efficient algorithm to improve oil - gas pipelines path, International Journal of Engineering and Technology, 7, 4, pp. 5412-5418, (2018); Almaalei N. N., Razali S. N. A. M., Performance Evaluation of Different Short Path Algorithms to Improve Oil-Gas Pipelines, International Journal of Advanced Computer Science and Applications, 10, 11, pp. 62-67, (2019); (2022); Loo H.S., Chew B.C., Hamid S.R., Exploring the factors and strategies in implementation of sustainable land transport system in Ayer Keroh, Melaka, Journal of Advanced Manufacturing Technology, 12, 1, pp. 159-174, (2018); (2022); Alobaedy M. M., Khalaf A. A., Muraina I. D., Analysis of the number of ants in ant colony system algorithm, In 2017 5th International Conference on Information and Communication Technology (ICoIC7), pp. 1-5, (2017)",null,null,"Science and Information Organization",{"$nulls":5},"2158107X",null,null,null,"English","Intl. J. Adv.  Comput. Sci. Appl.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85141803856"]
["Tao Y.; Lin C.; Wei L.","Tao, Yi (36476868000); Lin, Changhui (57921119600); Wei, Lijun (56612625800)","36476868000; 57921119600; 56612625800","Metaheuristics for a Large-Scale Vehicle Routing Problem of Same-Day Delivery in E-Commerce Logistics System",2022.0,"Journal of Advanced Transportation",2022.0,null,8253175.0,null,null,null,1.0,"10.1155/2022/8253175","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85139559368&doi=10.1155%2f2022%2f8253175&partnerID=40&md5=c345b921f2c99cef62e3d6f220585fca","School of Management, Guangdong University of Technology, China; Key Laboratory of Computer Integrated Manufacturing System, School of Electromechanical Engineering, Guangdong University of Technology, 510006, China","Tao Y., School of Management, Guangdong University of Technology, China; Lin C., School of Management, Guangdong University of Technology, China; Wei L., Key Laboratory of Computer Integrated Manufacturing System, School of Electromechanical Engineering, Guangdong University of Technology, 510006, China","In this paper, we introduce a new variant of large-scale vehicle routing problem that arises in the goods distribution of city e-commerce logistics, the multi-depot vehicle routing problem with order split and allocation (MD-CVRP-OSA), which incorporates the issue of split and allocation of online orders into traditional VRP. A mathematical formulation is constructed for the MD-CVRP-OSA, and an efficient metaheuristics algorithm based on a variable neighborhood search (VNS) solution framework is designed to solve it. The proposed method is tested on a large family of instances, including real-world data collected from JD.com, and the effectiveness of the VNS algorithm and also the algorithm components are analyzed.  © 2022 Yi Tao et al.",null,"Distribution of goods; Heuristic algorithms; Optimization; Vehicle routing; Vehicles; E- commerces; Large-scales; Logistics system; Mathematical formulation; Meta-heuristics algorithms; Metaheuristic; Multi-depot vehicle routing problems; Online orders; Variable neighborhood search; Vehicle Routing Problems; Electronic commerce",{"$nulls":6},"Dayarian I., Savelsbergh M., Clarke J.-P., Same-day delivery with drone resupply, Transportation Science, 54, 1, pp. 229-249, (2020); Klapp M.A., Erera A.L., Toriello A., The dynamic dispatch waves problem for same-day delivery, European Journal of Operational Research, 271, 2, pp. 519-534, (2018); Dayarian I., Savelsbergh M., Crowdshipping and same-day delivery: Employing in-store customers to deliver online orders, Production and Operations Management, 29, 9, pp. 2153-2174, (2020); Stroh A.M., Erera A.L., Toriello A., Tactical Design of Same-day Delivery Systems, Management Science, 68, 5, pp. 3444-3463, (2022); Voccia S.A., Campbell A.M., Thomas B.W., The same-day delivery problem for online purchases, Transportation Science, 53, 1, pp. 167-184, (2019); Van Heeswijk W.J.A., Mes M.R.K., Schutten J.M.J., The delivery dispatching problem with time windows for urban consolidation centers, Transportation Science, 53, 1, pp. 203-221, (2019); Toth P., Vigo D., Vehicle Routing: Problems, Methods, and Applications, Second Edition. MOS-SIAM Series on Optimization, (2014); Braekers K., Ramaekers K., Nieuwenhuyse I.V., The vehicle routing problem: State of the art classification and review, Computers & Industrial Engineering, 99, pp. 300-313, (2016); Tan S.Y., Yeh W.C., The vehicle routing problem: State-of-the-art classification and review, Applied Sciences, 11, 21, (2021); Drexl M., Schneider M., A survey of variants and extensions of the location-routing problem, European Journal of Operational Research, 241, 2, pp. 283-308, (2015); Prodhon C., Prins C., A survey of recent research on location-routing problems, European Journal of Operational Research, 238, 1, pp. 1-17, (2014); Montoya-Torres J.R., Lopez Franco J., Nieto Isaza S., Felizzola Jimenez H., Herazo-Padilla N., A literature review on the vehicle routing problem with multiple depots, Computers & Industrial Engineering, 79, pp. 115-129, (2015); Chen D., Yang Z., Multiple depots vehicle routing problem in the context of total urban traffic equilibrium, Journal of Advanced Transportation, 2017, (2017); Li J., Ma Y., Gao R., Cao Z., Lim A., Song W., Zhang J., Deep reinforcement learning for solving the heterogeneous capacitated vehicle routing problem, IEEE Transactions on Cybernetics, pp. 1-14, (2021); Ma Y., Li J., Cao Z., Song W., Guo H., Gong Y., Chee Y.M., Efficient Neural Neighborhood Search for Pickup and Delivery Problems, (2022); Li J., Xin L., Cao Z., Lim A., Song W., Zhang J., Heterogeneous attentions for solving pickup and delivery problem via deep reinforcement learning, IEEE Transactions on Intelligent Transportation Systems, 23, 3, pp. 2306-2315, (2022); Gulczynski D., Golden B., Wasil E., The multi-depot split delivery vehicle routing problem: An integer programming-based heuristic, new test problems, and computational results, Computers & Industrial Engineering, 61, 3, pp. 794-804, (2011); Ray S., Soeanu A., Berger J., Debbabi M., The multi-depot split-delivery vehicle routing problem: Model and solution algorithm, Knowledge-Based Systems, 71, pp. 238-265, (2014); Izar S., Suwilo S., Multi-depot vehicle routing problem with split delivery and time windows, Bulletin of Mathematics, 8, pp. 169-177, (2016); Wang X., Golden B., Wasil E., Zhang R., The min-max split delivery multi-depot vehicle routing problem with minimum service time requirement, Computers and Operations Research, 71, pp. 110-126, (2016); Mladenovic N., Hansen P., Variable neighborhood search, Computers & Operations Research, 24, 11, pp. 1097-1100, (1997); Hansen P., Mladenovie N., Brimberg J., Perez J.A.M., Gendreau M., Potvin J.-Y., Variable neighborhood search, Handbook of Metaheuristics, pp. 57-97, (2019); Fong J., Salhi S., Wassan N., The cumulative capacitated vehicle routing problem with min-sum and minmax objectives: An effective hybridisation of adaptive variable neighbourhood search and large neighbourhood search, Transportation Research Part B: Methodological, 101, pp. 162-184, (2017); Stenger A., Vigo D., Enz S., Schwind M., An adaptive variable neighborhood search algorithm for a vehicle routing problem arising in small package shipping, Transportation Science, 47, 1, (2013); Wei L., Zhang Z., Zhang D., Lim A., A variable neighborhood search for the capacitated vehicle routing problem with two-dimensional loading constraints, European Journal of Operational Research, 243, 3, (2015); Olender P., Ogryczak W., A revised variable neighborhood search for the discrete ordered median problem, European Journal of Operational Research, 274, 2, pp. 445-465, (2019); Clarke G., Wright J., Scheduling of vehicles from a central depot to a number of delivery points, Operations Research, 12, 4, pp. 568-581, (1964); Ozsen R., Thonemann U.W., An Optimal Expediting Policy for Periodic-review Inventory Systems, (2012)","L. Wei; Key Laboratory of Computer Integrated Manufacturing System, School of Electromechanical Engineering, Guangdong University of Technology, 510006, China; email: villagerwei@gdut.edu.cn",null,"Hindawi Limited",{"$nulls":5},1976729.0,null,"JATRD",null,"English","J Adv Transp","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85139559368"]
["Yang M.-F.; Shih P.-H.; Pan J.C.-H.; Li M.-C.","Yang, Ming-Feng (55703292600); Shih, Po-Hsun (54586021500); Pan, Jason Chao-Hsien (7404098325); Li, Mei-Chun (57283265300)","55703292600; 54586021500; 7404098325; 57283265300","The optimal layout design for minimizing operating costs in a picker-to-part warehousing system",2022.0,"International Journal of Advanced Manufacturing Technology",118.0,"2024-08-07",null,2523.0,2537.0,14.0,4.0,"10.1007/s00170-021-08026-x","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85116199631&doi=10.1007%2fs00170-021-08026-x&partnerID=40&md5=8a0a6523ef97cfa85103fc1a814ddc15","Department of Transportation Science, Intelligent Maritime Research Center, National Taiwan Ocean University, No. 2, Beining Rd., Zhongzheng Dist., Keelung, 202301, Taiwan; Department of Information Management, Vanung University, 1 Van-Nung Road, Chung-Li, Tao-Yuan, 32061, Taiwan; Department of Business Administration, Takming University of Science and Technology, 43 Huanshan Road, Section 1, Taipei, 11451, Taiwan","Yang M.-F., Department of Transportation Science, Intelligent Maritime Research Center, National Taiwan Ocean University, No. 2, Beining Rd., Zhongzheng Dist., Keelung, 202301, Taiwan; Shih P.-H., Department of Information Management, Vanung University, 1 Van-Nung Road, Chung-Li, Tao-Yuan, 32061, Taiwan; Pan J.C.-H., Department of Business Administration, Takming University of Science and Technology, 43 Huanshan Road, Section 1, Taipei, 11451, Taiwan; Li M.-C., Department of Transportation Science, Intelligent Maritime Research Center, National Taiwan Ocean University, No. 2, Beining Rd., Zhongzheng Dist., Keelung, 202301, Taiwan","The decision problems in the design and control of warehousing order picking process include layout design, storage assignment, routing, and order batching policies. Previous researches on layout design for pick-and-pass systems are not abundant. However, a pick-and-pass system is a commonly used approach because of the growth of e-commerce and the faster delivery of small and frequent orders. This paper presents an algorithm to determine the number of zones, and the number of picking bins and racks in each zones for the pick-and-pass systems such that both investment and operational costs can be minimized. A cycle time evaluation model is developed and incorporated into the proposed algorithm to aid a warehouse designer to quickly evaluate design alternatives for warehouse configurations. The result indicates that the cycle time evaluation model appears to be sufficiently accurate for practical purpose and the optimal layout can be determined by the proposed algorithm. © 2021, The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature.","Optimal layout; Order picking; Pick-and-pass system; Warehouse management","Operating costs; Cycle time evaluation; Evaluation models; Layout designs; Optimal layout; Optimal layout design; Order-picking; Pick and pass; Pick-and-pass system; Warehouse management; Warehousing systems; Warehouses",{"$nulls":6},"Coyle J.J., Langley C.J., Bardi E.J., The management of business logistics: instructor’s manual with test bank to accompany, (1996); De Koster R., Le-Duc T., Roodbergen K.J., Design and control of warehouse order picking: a literature review, Eur J Oper Res, 182, 2, pp. 481-501, (2007); Petersen C.G., Aase G., A comparison of picking, storage, and routing policies in manual order picking, Int J Prod Econ, 92, 1, pp. 11-19, (2004); Gu J., Goetschalckx M., McGinnis L.F., Research on warehouse design and performance evaluation: a comprehensive review, Eur J Oper Res, 203, 3, pp. 539-549, (2010); Bassan Y., Roll Y., Rosenblatt M.J., Internal layout design of a warehouse, AIIE Trans, 12, 4, pp. 317-322, (1980); Rosenblatt M.J., Roll Y., Warehouse design with storage policy considerations, Int J Prod Res, 22, 5, pp. 809-821, (1984); Rosenblatt M.J., Roll Y., Warehouse capacity in a stochastic environment, Int J Prod Res, 26, 12, pp. 1847-1851, (1988); Park Y.H., Webster D.B., Design of class-based storage racks for minimizing travel time in a three-dimensional storage system, Int J Prod Res, 27, 9, pp. 1589-1601, (1989); Pandit R., Palekar U.S., Response time considerations for optimal warehouse layout design, J Eng Ind, 115, 3, pp. 322-328, (1993); Larson T.N., March H., Kusiak A., A heuristic approach to warehouse layout with class-based storage, IIE Trans, 29, 4, pp. 337-348, (1997); Caron F., Marchet G., Perego A., Optimal layout in low-level picker-to-part systems, Int J Prod Res, 38, 1, pp. 101-117, (2000); Roodbergen K.J., Layout and Routing Methods for Warehouses (No. EPS-2001-004-LIS), (2001); Petersen C.G., Considerations in order picking zone configuration, Int J Oper Prod Manag, 22, 7, pp. 793-805, (2002); Le-Duc T., de Koster M.B.M., Determining number of zones in a pick-and-pack order picking system, (2005); Heragu S.S., Du L., Mantel R.J., Schuur P.C., Mathematical model for warehouse design and product allocation, Int J Prod Res, 43, 2, pp. 327-338, (2005); Parikh P.J., Meller R.D., A travel-time model for a person-onboard order picking system, Eur J Oper Res, 200, 2, pp. 385-394, (2010); Kuo R.J., Kuo P.H., Chen Y.R., Zulvia F.E., Application of metaheuristics-based clustering algorithm to item assignment in a synchronized zone order picking system, Appl Soft Comput, 46, pp. 143-150, (2016); Petersen C.G., Aase G.R., Improving order picking efficiency with the use of cross aisles and storage policies, Open J Bus Manag, 5, 1, (2017); Cano J.A., Correa-Espinal A.A., Gomez-Montoya R.A., Mathematical programming modeling for joint order batching, sequencing and picker routing problems in manual order picking systems, J King Saud Univ-Eng Sci, 32, 3, pp. 219-228, (2020); Bortolini M., Faccio M., Ferrari E., Gamberi M., Pilati F., Design of diagonal cross-aisle warehouses with class-based storage assignment strategy, Int J Adv Manuf Technol, 100, 9, pp. 2521-2536, (2019); Hsieh S., Tsai K.C., A BOM oriented class-based storage assignment in an automated storage/retrieval system, Int J Adv Manuf Technol, 17, 9, pp. 683-691, (2001); Tompkins J.A., White J.A., Bozer Y.A., Tanchoco J.M.A., Facilities planning, (2010); De Koster R., Performance approximation of pick-to-belt order picking systems, Eur J Oper Res, 72, 3, pp. 558-573, (1994); Yu M., De Koster R.B., The impact of order batching and picking area zoning on order picking system performance, Eur J Oper Res, 198, 2, pp. 480-490, (2009); Pan J.C.H., Wu M.H., A study of storage assignment problem for an order picking line in a pick-and-pass warehousing system, Comput Ind Eng, 57, 1, pp. 261-268, (2009); Pan L., Huang J.Z., Chu S.C., Order batching and picking in a synchronized zone order picking system, 2011 IEEE International Conference on Industrial Engineering and Engineering Management, pp. 156-160, (2011); Hong S., The effects of picker-oriented operational factors on hand-off delay in a bucket brigade order picking system, OR Spectrum, 40, 3, pp. 781-808, (2018); Hong S., A performance evaluation of bucket brigade order picking systems: analytical and simulation approaches, Comput Ind Eng, 135, pp. 120-131, (2019); Tappia E., Roy D., Melacini M., De Koster R., Integrated storage-order picking systems: technology, performance models, and design insights, Eur J Oper Res, 274, 3, pp. 947-965, (2019); Maloney D., Seeing the light, Mod Mater Handl, 55, 9, pp. 49-51, (2000); Jane C.C., Laih Y.W., A clustering algorithm for item assignment in a synchronized zone order picking system, Eur J Oper Res, 166, 2, pp. 489-496, (2005); Brynzer H., Johansson M.I., Design and performance of kitting and order picking systems, Int J Prod Econ, 41, 1-3, pp. 115-125, (1995); Muppani V.R., Adil G.K., Efficient formation of storage classes for warehouse storage location assignment: a simulated annealing approach, Omega, 36, 4, pp. 609-618, (2008); Petersen C.G., Schmenner R.W., An evaluation of routing and volume-based storage policies in an order picking operation, Decis Sci, 30, 2, pp. 481-501, (1999); Jewkes E., Lee C., Vickson R., Product location, allocation and server home base location for an order picking line with multiple servers, Comput Oper Res, 31, 4, pp. 623-636, (2004)","M.-C. Li; Department of Transportation Science, Intelligent Maritime Research Center, National Taiwan Ocean University, Keelung, No. 2, Beining Rd., Zhongzheng Dist., 202301, Taiwan; email: 10968015@email.ntou.edu.tw",null,"Springer Science and Business Media Deutschland GmbH",{"$nulls":5},2683768.0,null,"IJATE",null,"English","Int J Adv Manuf Technol","Article","Final",null,"Scopus","2-s2.0-85116199631"]
["D’Hondt J.; Juwet M.; Demeester E.; Slaets P.","D’Hondt, Jordi (57196347192); Juwet, Marc (57196348004); Demeester, Eric (22733543900); Slaets, Peter (15137408000)","57196347192; 57196348004; 22733543900; 15137408000","DEVELOPMENT OF AN ELECTRIC TRICYCLE FOR SERVICE COMPANIES AND LAST-MILE PARCEL DELIVERY",2022.0,"Transport Problems",17.0,2.0,null,175.0,187.0,12.0,2.0,"10.20858/tp.2022.17.2.15","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135734829&doi=10.20858%2ftp.2022.17.2.15&partnerID=40&md5=89b34bca4ee263117d861a930e26a7db","KU Leuven, Department of Robotics, Automation and Mechatronics, Gebroeders de Smetstraat 1, Gent, 9000, Belgium; KU Leuven, Department of Robotics, Automation and Mechatronics, Wetenschapspark 27 - box 15152, Diepenbeek, 3590, Belgium; KU Leuven, Department of Robotics, Automation and Mechatronics, Andreas Vesaliusstraat 13 - box 2600, Leuven, 3000, Belgium","D’Hondt J., KU Leuven, Department of Robotics, Automation and Mechatronics, Gebroeders de Smetstraat 1, Gent, 9000, Belgium; Juwet M., KU Leuven, Department of Robotics, Automation and Mechatronics, Gebroeders de Smetstraat 1, Gent, 9000, Belgium; Demeester E., KU Leuven, Department of Robotics, Automation and Mechatronics, Wetenschapspark 27 - box 15152, Diepenbeek, 3590, Belgium; Slaets P., KU Leuven, Department of Robotics, Automation and Mechatronics, Andreas Vesaliusstraat 13 - box 2600, Leuven, 3000, Belgium","In many city centres and some large urban areas, access restrictions are imposed on trucks and vans. On the other hand, the number of e-commerce packages to be delivered daily is increasing rapidly, and service companies of all kinds also have to serve their customers in these areas. The use of cargo bikes is seen as a possible solution. The direct reason for this research is the observation that there is still room for a new type of cargo bike that meets the needs of the outlined target groups. This article summarises how the quality function deployment (QFD) method has been used for the systematic development of an electric cargo tricycle that meets these needs. The developed tricycle distinguishes itself from existing cargo bikes mainly by its loading capacity, stability and manoeuvrability. The prototype tests performed by professional couriers were so positive that a pilot series was built. © 2022 Silesian University of Technology. All rights reserved.","cargo bike; e-commerce; last-mile delivery; QFD method; tricycle",{"$nulls":7},"Reiter K., Wrighton S., Rzewnicki R., Potential to shift goods transport from cars to bicycles in European cities, Moving Europe forward, (2014); Sustainable and Smart Mobility Strategy – putting European transport on track for the future, (2020); Caggiani L., Colovic A., Prencipe L.P., Ottomanelli M., A green logistics solution for last-mile deliveries considering e-vans and e-cargo bikes, Transportation Research Procedia, 52, pp. 75-82; Verlinghieri E., Itova I., Collignon N., Aldred R., The Promise of Low-Carbon Freight, (2021); Wrighton S., Reiter K., CycleLogistics – Moving Europe Forward!, Transportation Research Procedia, 12, pp. 950-958; Giglio C., Musmanno R., Palmieri R., Cycle logistics projects in Europe: Intertwining bike-related success factors and region-specific public policies with economic results, Applied sciences, 11, pp. 1-31, (2021); Arnold F., Cardenas I., Sorensen K., Dewulf W., Simulation of B2C e-commerce distribution in Antwerp using cargo bikes and delivery points, European Transport Research Review, 10, 1; Nowak D., How sustainable is the Pedal Me fleet?, Pedal Me, (2021); Mucowska M., Trends of Environmentally Sustainable Solutions of Urban Last-Mile Deliveries on the E-Commerce Market – A Literature Review, Sustainability, 13, 11, (2021); Clement J., Coronavirus impact on retail e-commerce website traffic worldwide as of June 2020, by average monthly visits; Villa R., Monzon A., Mobility Restrictions and E-Commerce: Holistic Balance in Madrid Centre during COVID-19 Lockdown, Economie, 9, 2, (2021); Buch T.S., Greibe P., Bredde af cykelstier: Analyse af adfærd og kapacitet. [In Danish: Width of cycle paths: Analysis of behavior and capacity], (2014); Regulation (EU) No 168/2013 of the European Parliament and of the Council of 15 January 2013 on the approval and market surveillance of two- or three-wheel vehicles and quadricycles (Text with EEA relevance); Roetynck A., Electric Cargo Bikes: Technical Rules & Regulations, ECLF conference, (2017); de Groot R., Ontwerpwijzer fietsverkeer. [In Dutch: Design guide for bicycle traffic], (2016); Koninklijk besluit houdende algemeen reglement op de politie van het wegverkeer en van het gebruik van de openbare weg, (1975); Vlaanderen M., Ontwerpichtljinen voor fietsvoorzieningen. [In Dutch: Design guidelines for bicycle services], (2017); Vademecum fietsvoorzieningen – Minimumbreedte fietspaden. [In Dutch: Vademecum bicycle facilities – Minimum width of bicycle paths], (2018); Danish Guidelines for planning and design, (2000); Greibe P., Buch T.S., Capacity and Behaviour on One-way Cycle Tracks of Different Widths, Transportation Research Procedia, 15, pp. 122-136; Fransen G., Van bakfietsen tot snelle elektrische fietsen: wie mag er wel op het fietspad en wie niet? [In Dutch: From cargo bikes to fast electric bikes: who is allowed on the cycle path and who is not?], (2020); Behrensen A., Sumer A., European Cargo Bike Industry Survey Results, City Changer Cargo Bike; Wens S., Vlaanderen F., Fiets DNA, (2018); Behrensen A., European Cargo Bike Industry Survey, Cyclelogistics, (2021); Farman G., Cargo Bike Analysis and Field Testing, Topsector Logistiek, (2020); Behrensen A., Sumer A., First European Cargo Bike Industry Survey Results, City Changer Cargo Bike, (2020); Narayanan S., Gruber J., Liedtke G., Antoniou C., Purchase intention and actual purchase of cargo cycles: Influencing factors and policy insights, Transportation Research Part A: Policy and Practice, 155, pp. 31-45; Blazejewski L., Sherriff G., Davies N., Delivering The Last Mile Scoping the Potential for E-cargo Bikes Healthy Active Cities, (2020); Lenz B., Riehle E., Bikes for urban freight?, Transportation research record, 2379, pp. 39-45, (2013); Clements S., Cycle Logistics Study, (2019); van Amstel Walther Ploos, DHL Netherlands presents their new cargo bike: the Chariot, City Logistics, (2021); Lessons from our e-bike journey, (2020); FedEx Express Continues Journey Towards Zero Emissions Delivery, as Edinburgh, Glasgow and Cambridge Become the Next UK Cities to Welcome E-cargo Bikes, (2021); Gruber J., Narayanan S., Travel Time Differences between Cargo Cycles and Cars in Commercial Transport Operations, Transportation research record, 2673, 8, pp. 623-637, (2019); Cargo Bike Ziegler. A revolutionary, eco-friendly freight solution for Brussels, (2022); The Tender will handle everything you throw at it; Brust E., Zweirad-Industrie-Verband (ZIV) Wirtschaftspressekonferenz. [In German: Bicycle Industry Association (ZIV) Business Press Conference], (2021); Orchard K., Cluzel C., Cycle Freight Study. An independent study commissioned by Transport for London, (2018); Gruber J., Ergebnisse des größten Lastenradtests Europas Umweltfreundlich und effizient: Lastenräder im dienstlichen und gewerblichen Einsatz. [In German: Results of the largest cargo bike test in Europe Environmentally friendly and efficient: cargo bikes in official and commercial use], (2021); Ferguson J., Cargo Bike Crazy: The Potential of Delivering Goods By Bike; Cairns S., Sloman L., Potential for e-cargo bikes to reduce congestion and pollution from vans in cities, (2019); Maritan D., Practical Manual of Quality Function Deployment, (2014); Cycles - Electrically powere assisted cycles - EPAC Bicycles EN 15194, (2017); Bahrami M., Mokhtari H., Dindar A., Energy regeneration technique for electric vehicles driven by a brushless DC motor, IET Power Electronics, 12, 13, pp. 3397-3402; Tournon E., Venet P., Barbedette B., Lelievre A., Aubry J., Sari A., Efficiency Comparison between Series Hybrid Bike and Traditional Bike, Fourteenth International Conference on Ecological Vehicles and Renewable Energies (EVER), pp. 1-7, (2019); Zawirski K., Nowopolski K., Wicher B., Janiszewski D., Fabianski B., Siembab K., Gearless Pedaling Electric Driven Tricycle, Analysis and Simulation of Electrical and Computer Systems. Lecture Notes in Electrical Engineering, 324, (2015); Song C., Shao Y., Song S., Peng S., Xiao F., A Novel Electric Bicycle Battery Monitoring System Based on Android Client, Journal of engineering (Cairo, Egypt), 2017, pp. 1-11, (2017); Ustun O., Tanc G., Kivanc O.C., Tosun G., In pursuit of proper BLDC motor design for electric bicycles, 2016 XXII International Conference on Electrical Machines (ICEM), pp. 1808-1814, (2016); Dieltiens S., D'Hondt J., Juwet M., Versteyhe M., Development of a low-cost measurement system to determine 3-dimensional pedal loads during in-situ cycling, Transport Problems, 14, 4, pp. 151-159, (2019)","J. D’Hondt; KU Leuven, Department of Robotics, Automation and Mechatronics, Gent, Gebroeders de Smetstraat 1, 9000, Belgium; email: jordi.dhondt@kuleuven.be",null,"Silesian University of Technology",{"$nulls":5},1.8960596E7,null,null,null,"English","Transp. Probl.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85135734829"]
["Shen H.; He Y.","Shen, Hong (57190168933); He, Yujia (57203278208)","57190168933; 57203278208","The geopolitics of infrastructuralized platforms: the case of Alibaba",2022.0,"Information Communication and Society",25.0,16.0,null,2363.0,2380.0,17.0,7.0,"10.1080/1369118X.2022.2128599","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85139445918&doi=10.1080%2f1369118X.2022.2128599&partnerID=40&md5=4aabf26b34254cc6a51be23ab07ee9dc","Human-Computer Interaction Institute, Pittsburgh, Carnegie Mellon University, United States; Patterson School of Diplomacy and International Commerce, University of Kentucky, United States","Shen H., Human-Computer Interaction Institute, Pittsburgh, Carnegie Mellon University, United States; He Y., Patterson School of Diplomacy and International Commerce, University of Kentucky, United States","Contemporary digital platforms have become increasingly infrastructuralized, and started to raise geopolitical tensions with their global expansion. Amidst the heightened geopolitical competition between the US and China, the growing power of Chinese infrastructuralized platforms has made them the center of recent geopolitical dynamics. Drawing from an exploratory case study, this paper discusses Alibaba, one of the most prominent Chinese Internet giants, as an infrastructuralized platform, and highlights its geopolitical struggles. Often perceived as an e-commerce company, Alibaba has become ‘infrastructuralized’: its now-massive digital empire has moved beyond e-commerce, expanding into almost every aspect of China’s and global digital economy such as logistics, finance, offline retailing, and cloud computing. This paper traces three highly visible cases in Alibaba’s global journey–its failed deal with MoneyGram in 2017, the uneven global journey of Alibaba Cloud, and the construction of the electronic World Trade Platform–to illustrate three key dimensions of the geopolitics of infrastructuralized platforms–namely, the geopolitics of everyday data, the geopolitics of the visibility-invisibility tension, and the geopolitics of modularity. By doing so, it contributes to the following two areas of scholarship. On the one hand, it contributes to the growing literature on ‘infrastructures and platforms’ by foregrounding the geopolitical dimensions of Chinese infrastructuralized platforms. On the other hand, it adds to the literature on the ‘geopolitics of infrastructures’ by bringing in a new type of infrastructure, complementing previous discussions on the geopolitics of traditional material infrastructures. © 2022 Informa UK Limited, trading as Taylor & Francis Group.","Alibaba; Chinese Internet; Geopolitics; infrastructuralized platforms; infrastructures; platforms",{"$nulls":5},"Qatar National Library, QNL","Open Access funding provided by the Qatar National Library.","(2016); (2020); (2020); Anastasiadou I., Iron silk roads: The geopolitics of past and present initiatives for the revival of Eurasian trade through overland transport corridors, Cambridge Journal of Regions, Economy and Society, 12, 1, pp. 57-75, (2019); Bahgat G., Pipeline diplomacy: The geopolitics of the Caspian Sea region, International Studies Perspectives, 3, 3, pp. 310-327, (2002); Baldwin C.Y., Clark K.B., Design rules: The power of modularity, 1, (2000); Baldwin C.Y., Woodard C.J., The architecture of platforms: A unified view, Platforms, Markets and Innovation, pp. 19-44, (2009); Barfield C., (2018); Bogost I., Montfort N., Platform studies: Frequently questioned answers, Digital Arts and Culture, 12-15, December, pp. 1-6, (2009); Bowker C.G., Star S.L., Sorting things out: Classification and its consequences, (2000); Bueger C., Liebetrau T., Protecting hidden infrastructure: The security politics of the global submarine data cable network, Contemporary Security Policy, pp. 1-23, (2021); Cartwright M., Internationalising state power through the Internet: Google, Huawei and geopolitical struggle, Internet Policy Review, 9, 3, pp. 1-18, (2020); Chandran N., (2018); Chen J.Y., Qiu J.L., Digital utility: Datafication, regulation, labor, and DiDi’s platformization of urban transport in China, Chinese Journal of Communication, 12, 3, pp. 274-289, (2019); Chitkara H., Alibaba Cloud’s future is still bright, despite US efforts to thwart its growth, Business Insider, (2020); DeNardis L., Protocol politics: The globalization of Internet governance, (2009); DeNardis L., Opening standards: The global politics of interoperability, (2011); (2020); Edwards P.N., Bowker G.C., Jackson S.J., Williams R., Introduction: An agenda for infrastructure studies, Journal of the Association for Information Systems, 10, 5, pp. 364-374, (2009); (2019); Fichtner L., What kind of cyber security? Theorising cyber security and mapping approaches, Internet Policy Review, 7, 2, pp. 1-19, (2018); Gillespie T., The politics of ‘platforms’, New Media & Society, 12, 3, pp. 347-364, (2010); Graham S., Marvin S., Splintering urbanism: Networked infrastructures, technological mobilities and the urban condition, (2001); Gray J., The geopolitics of ‘platforms’: The TikTok challenge, Internet Policy Review, (2021); Guo C.F., (2021); He Y., (2019); He Y., Tritto A., Urban Utopia or pipe dream? Examining Chinese-invested smart city development in Southeast Asia, Third World Quarterly, 43, 9, pp. 2244-2268, (2022); Headrick D.R., The invisible weapon: Telecommunications and international politics, 1851-1945, (1991); Hern A., Fitness tracking app Strava gives away location of secret US army bases, The Guardian, 28, (2018); Herr T., (2020); Hillman J.E., (2021); Hu T., A prehistory of the cloud, (2015); Hughes T.P., Networks of power: Electrification in western society, 1880-1930, (1983); Jacobides M.G., Cennamo C., Gawer A., Towards a theory of ecosystems, Strategic Management Journal, 39, 8, pp. 2255-2276, (2018); Jia F., Bennett M.M., Chinese infrastructure diplomacy in Russia: The geopolitics of project type, location, and scale, Eurasian Geography and Economics, 59, 3-4, pp. 340-377, (2018); Jia L., Liang F., The globalization of TikTok: Strategies, governance and geopolitics, Journal of Digital Media & Policy, 12, 2, pp. 273-292, (2021); Keohane R.O., Nye J.S., Power and interdependence in the information age, Foreign Affairs, 77, 5, (1998); Kubota Y., Lin L., In the New China, Didi’s data becomes a problem, The Wall Street Journal, (2021); Kumar P.P., Kuar D., (2018); Langlois G., Elmer G., The research politics of social media platforms, Culture Machine, 14, pp. 1-17, (2013); Logan S., The geopolitics of tech: Baidu’s Vietnam, Internet Policy Observatory, (2015); Lu J., (2017); (2016); (2017); Mashayekhi R., Could a Western Union–MoneyGram deal help two giants fend off fintech disrupters?, Fortune, (2020); McDonald J., (2014); (2018); Mosco V., To the cloud: Big data in a turbulent world, (2014); Mueller M., Ruling the root: Internet governance and the taming of cyberspace, (2002); Mueller M., Networks and states: The global politics of Internet governance, (2010); Napoli P.M., User data as public resource: Implications for social media regulation, Policy & Internet, 11, 4, pp. 439-459, (2019); Naughton B., Chinese industrial policy and the digital silk road: The case of Alibaba in Malaysia, Asia Policy, 27, 1, pp. 23-39, (2020); Pethokoukis J., (2018); Plantin J.C., De Seta G., WeChat as infrastructure: The techno-nationalist shaping of Chinese digital platforms, Chinese Journal of Communication, 12, 3, pp. 257-273, (2019); Plantin J.C., Lagoze C., Edwards P.N., Sandvig C., Infrastructure studies meet platform studies in the age of google and Facebook, New Media & Society, 20, 1, pp. 293-310, (2018); Ragin C.C., Becker H.S., What is a case?: Exploring the foundations of social inquiry, (1992); Rosenbach E., Mansted K., (2019); Roumeliotis G., (2018); Schiller D., Geopolitical-economic conflict and network infrastructures, Chinese Journal of Communication, 4, 1, pp. 90-107, (2011); Schiller D., Reconstructing public utility networks: A program for action, International Journal of Communication, 14, (2020); Seth S., World’s top 10 Internet companies, Investopedia, (2018); Shen H., China and global Internet governance: Toward an alternative analytical framework, Chinese Journal of Communication, 9, 3, pp. 304-324, (2016); Shen H., Across the Great (Fire) Wall: China and the Global Internet, (2017); Shen H., Building a digital silk road? Situating the Internet in China's belt and road initiative, International Journal of Communication, 12, (2018); Shen H., Faklaris C., Jin H., Dabbish L., Hong J.I., I an't even buy apples if I don't use mobile pay?' When mobile payments become infrastructural in China, Proceedings of the ACM on Human-Computer Interaction, 4, CSCW2, pp. 1-26, (2020); Shen H., Alibaba: Infrastructuring global China, (2021); Star S.L., The ethnography of infrastructure, American Behavioral Scientist, 43, 3, pp. 377-391, (1999); Starosielski N., The undersea network, (2015); Tang M., Huawei versus the United States? The geopolitics of exterritorial Internet infrastructure, International Journal of Communication, 14, pp. 4556-4577, (2020); (2017); Tworek H., News from Germany: The competition to control world communications, 1900-1945, (2019); Tzin S.T., My Say: Development plans must make ‘Made in Malaysia’ great again, The Edge Malaysia, (2021); (2020); Vila Seoane M.F., Alibaba’s discourse for the digital silk road: The electronic world trade platform and ‘inclusive globalization’, Chinese Journal of Communication, 13, 1, pp. 68-83, (2020); Winseck D., The geopolitical economy of the global Internet infrastructure, Journal of Information Policy, 7, pp. 228-267, (2017); Yang L., Lin L., Zhai K., Alibaba’s winning cloud formula is coming under pressure, Wall Street Journal, (2021); Yean T.S., (2018); Yean T.S., (2020); Zhang Z., Infrastructuralization of Tik Tok: Transformation, power relationships, and platformization of video entertainment in China, Media, Culture & Society, 43, 2, pp. 219-236, (2021); Zimmerman E.J., The foreign risk review modernization act: How CFIUS became a tech office, Berkeley Technology Law Journal, 34, pp. 1267-1304, (2019)","H. Shen; Human-Computer Interaction Institute, Carnegie Mellon University, Pittsburgh, 5000 Forbes Ave, 15213, United States; email: hongshenus@gmail.com",null,"Routledge",{"$nulls":5},"1369118X",null,null,null,"English","Inf. Commun. Soc.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85139445918"]
["Barile D.; Secundo G.; Del Vecchio P.","Barile, Domenica (58017489300); Secundo, Giustina (8246738300); Del Vecchio, Pasquale (25927024200)","58017489300; 8246738300; 25927024200","Food 4.0 for competing during the COVID-19 pandemic: experimenting digitalization in family firms",2022.0,"European Journal of Innovation Management",{"$nulls":6},1.0,"10.1108/EJIM-07-2022-0373","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85144049224&doi=10.1108%2fEJIM-07-2022-0373&partnerID=40&md5=06e6b32819f230741013eb5d09f42508","Department of Management, Finance and Technology, University LUM Giuseppe Degennaro, Casamassima, Italy","Barile D., Department of Management, Finance and Technology, University LUM Giuseppe Degennaro, Casamassima, Italy; Secundo G., Department of Management, Finance and Technology, University LUM Giuseppe Degennaro, Casamassima, Italy; Del Vecchio P., Department of Management, Finance and Technology, University LUM Giuseppe Degennaro, Casamassima, Italy","Purpose: Within food industry several changes and innovations are affecting the management of the entire supply chain (production, logistics, etc.). As strategy for the survival and competition, digitalization has assumed a crucial role during the pandemic emergence by causing the reconfiguration of traditional chains and business models. Framed in these premises, the research analyses how digital technologies have innovated the sub-chains of bakery products and pasta within food industry with reference to customers' interactions, delivery and marketing during the COVID-19 pandemic emergence. Design/methodology/approach: Moving from a critical literature review about the perspectives of digital technologies within the tradition of food industry, action research has been adopted to analyze in deep a case study of the start-up “ArteBianca Delivery” located in South Italy. Through this method, researchers have been deeply involved within the start-up to face the challenge of transforming the marketing and customer care into digital ones due to the COVID-19 restriction. Findings: Findings provide empirical evidence about the reconfiguration of the traditional business model of a family firm in the food sector into a digital one with the start-up “ArteBianca Delivery”. The marketing, delivery, e-commerce and customer care components of the business models have been supported and enhanced through the adoption of digital tools, such as mobile applications and social technologies useful both for users and for a more urgent digitization of company. Practical implications: Implications for practice can be identified into the pattern of digital transformation implemented as well as in the opportunity of replication and contextualization of the results to other companies looking for setting up a digital strategy. Originality/value: Elements of original contribution can be identified into: (1) the exploration of digital transformation in food family firms caused by the pandemic emergence, (2) the contextualization of the digital transformation to the sub-chains of bakery and pasta and (3) the geographical location of the case. © 2022, Emerald Publishing Limited.","Action research; Digital marketing; Digital transformation; Family firm; Food 4.0",{"$nulls":7},{"$cut":{"chars":17057,"head":"Alwan H.B., Ku-Mahamud K.R., Big data: definition, characteristics, life cycle, applications, and challenges, IOP Conference Series: Materials Science and Engineering, 769, 1, (2020); Amanullah M.A., Habeeb R.A.A., Nasaruddin F.H., Gani A., Ahmed E., Nainar A.S.M., Imran M., Deep learning and big data technologies for IoT security, Computer Communications, 151, pp. 495-517, (2020); Ambrish D.R., Entrepreneurship development: an approach to economic empowerment of women, International Journal of Multidisciplinary Approach and Studies, 1, 6, pp. 224-232, (2014); Barenfanger R., Otto B., Proposing a capability perspective on digital business models, 2015 IEEE 17th Conference on Business Informatics, 1, pp. 17-25, (2015); Benabdellah A.C., Benghabrit A., Bouhaddou I., Big data for supply chain management: opportunities and challenges, 2016 IEEE/ACS 13th International Conference of Computer Systems and Applications (AICCSA), pp. 1-6, (2016); Bowen R., Morris W., The digital divide: implications for agribusiness and entrepreneurship. Lessons from Wales, Journal of Rural Studies, 72, pp. 75-84, (2019); Brem A., Viardot E., Nylund P.A., Implications of the coronavirus (COVID-19) outbreak for innovation: which technologies will improve our lives?, Technological Forecasting and Social Change, 163, (2021); Bresciani S., Open, networked and dynamic innovation in the food and beverage industry, British Food Journal, 119, 11, pp. 2290-2293, (2017); Bresciani S., Thrassou A., Vrontis D., Change through innovation in family businesses: evidence from an Italian sample, World Review of Entrepreneurship, Management and Sustainable Development, 9, 2, pp. 195-215, (2013); Bresciani S., Ferraris A., Del Giudice M., The management of organizational ambidexterity through alliances in a new context of analysis: internet of Things (IoT) smart city projects, Technological Forecasting and Social Change, 136, pp. 331-338, (2018); Buchi G., Cugno M., Castagnoli R., Smart factory performance and industry 4.0, Technological Forecasting and Social Change, 150, (2020); Cappa F., Oriani R., Peruffo E., McCarthy I., Big data for creating and capturing value in the digitalized environment: unpacking the effects of volume, variety, and veracity on firm performance, Journal of Product Innovation Management, 38, 1, pp. 49-67, (2021); Cappa F., Franco S., Rosso F., Citizens and cities: leveraging citizen science and big data for sustainable urban development, Business Strategy and the Environment, 31, 2, pp. 648-667, (2022); Casprini E., De Massis A., Di Minin A., Frattini F., Piccaluga A., How family firms execute open innovation strategies: the Loccioni case, Journal of Knowledge Management, pp. 1459-1485, (2017); Chesbrough H., Crowther A.K., Beyond high tech: early adopters of open innovation in other industries, R&D Management, 36, 3, pp. 229-236, (2006); Chrisman J.J., Chua J.H., De Massis A., Frattini F., Wright M., The ability and willingness paradox in family firm innovation, Journal of Product Innovation Management, 32, 3, pp. 310-318, (2015); Cimini C., Boffelli A., Lagorio A., Kalchschmidt M., Pinto R., How do industry 4.0 technologies influence organisational change? An empirical analysis of Italian SMEs, Journal of Manufacturing Technology Management, 32, 3, pp. 695-721, (2021); Corvello V., Verteramo S., Giglio C., Turning crises into opportunities in the service sector: how to build antifragility in small and medium service enterprises, The TQM Journal, ahead-of-print, ahead-of-print, (2022); Corvello V., Verteramo S., Nocella I., Ammirato S., Thrive during a crisis: the role of digital technologies in fostering antifragility in small and medium-sized enterprises, Journal of Ambient Intelligence and Humanized Computing, pp. 1-13, (2022); Costa A.I.A., Greco M., Grimaldi M., Cricelli L., Corvello V., Inter-organisational innovation processes in the European food and drink industry, International Journal of Management and Enterprise Development, 15, 2-3, pp. 191-208, (2016); Dahlander L., Gann D.M., How open is innovation?, Research Policy, 39, 6,"}},"P. Del Vecchio; Department of Management, Finance and Technology, University LUM Giuseppe Degennaro, Casamassima, Italy; email: delvecchio@lum.it",null,"Emerald Publishing",{"$nulls":5},1.460106E7,null,null,null,"English","Eur. J. Innov. Manage.","Article","Article in press",null,"Scopus","2-s2.0-85144049224"]
["Lan S.","Lan, Shundong (57870936100)",5.78709361E10,"Path Optimization and Logistics Economic Benefits Based on Sparsely Sampled GPS Trajectory Data",2022.0,"Mobile Information Systems",2022.0,null,3350120.0,null,null,null,0.0,"10.1155/2022/3350120","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137131789&doi=10.1155%2f2022%2f3350120&partnerID=40&md5=9cb19215093a8dec70a30f6e926f36e1","College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China; School of Economics and Management, Hubei University of Arts and Science, Hubei, Xiangyang, 441053, China","Lan S., College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China, School of Economics and Management, Hubei University of Arts and Science, Hubei, Xiangyang, 441053, China","Affected by the technological revolution of the Internet and the rise of e-commerce, the logistics, and transportation industry has become the main artery of the economy, and higher requirements are placed on logistics and distribution. Nowadays, how to minimize the cost of logistics distribution is an important research goal of logistics economic benefits. To this end, this article investigates and discusses the logical distribution based on interval variables, and on the basis of previous studies, has carried out some fruitful research and attempts on the logical distribution model and solving algorithm. The beginning of this article explains the research background and the importance of this article. Analyzed and reviewed the current research status at home and abroad, and pointed out that the fuzzy and probabilistic methods used in previous studies to describe the variable assumptions used were too strong. The method used in this article to characterize interval variables does not need to know the probability distribution and density function that the variables obey, so it has more applicability. However, in view of the widespread popularity of sensor equipment and mobile communication equipment, more and more sparsely sampled trajectories, such as road patrol data, company employee check-in data, and base station data, are always poorly sampled for flight path data used to connect to mobile phones. The method of collecting this type of data is different from traditional GPS data and does not require items with GPS positioning equipment. The scanning width is much better than traditional trajectory data, but the scanning accuracy of a single object is insufficient. The intersection recognition method based on GPS trajectory data effectively improves the economic benefits of logistics transportation. In this paper, the study of sparsely sampled GPS trajectory data and intersection identification methods is applied to improve the economic efficiency of logistics and promote the development of the economic efficiency of logistics.  © 2022 Shundong Lan.",null,"Economic analysis; Economic and social effects; Efficiency; Mobile telecommunication systems; Probability density function; Probability distributions; Trajectories; E- commerces; Economic benefits; Economic efficiency; Interval variable; Logistics and transportations; Logistics industry; Path optimizations; Technological revolution; Trajectories datum; Transportation industry; Global positioning system",{"$nulls":6},"Tang C.S., Veelenturf L.P., The strategic role of logistics in the industry 4.0 era, Transportation Research Part E: Logistics and Transportation Review, 129, pp. 1-11, (2019); Wieczorek L., Ignaciuk P., Continuous genetic algorithms as intelligent assistance for resource distribution in logistic systems, Data, 3, 4, (2018); Dymowa L., Sevastjanov P., Fuzzy Simulation and Optimization of Production and Logistic Systems,\" Studies in Fuzziness & Soft Computing, (2010); Anily S., Bramel J., Vehicle routing and the supply chain management, Quantitative Models For Supply Chain Management, International Series in Operations Research & Management Science, 17, (1999); Ballou R.H., Business Logistics Management: Planning, Organizing, and Controlling the Supply Chain, (2004); Cattaruzza D., Absi N., Feillet D., Gonzalez-Feliu J., Vehicle routing problems for city logistics, EURO Journal on Transportation and Logistics, 6, 1, pp. 51-79, (2017); Chen B., Qu R., Bai R., Laesanklang W., A hyper-heuristic with two guidance indicators for bi-objective mixed-shift vehicle routing problem with time windows, Applied Intelligence, 48, 12, pp. 4937-4959, (2018); Lu H.C., Yang Y.W., Su L.T., Ant colony optimization solutions for logistic route planning with pick-up and delivery, pp. 808-813; Chen L., Ma M., Sun L., Heuristic swarm intelligent optimization algorithm for path planning of agricultural product logistics distribution, Journal of Intelligent and Fuzzy Systems, 37, 4, pp. 4697-4703, (2019); Liu W., Route optimization for last-mile distribution of rural E-commerce logistics based on ant colony optimization, IEEE Access, 8, (2020); Feng Z., Constructing rural e-commerce logistics model based on ant colony algorithm and artificial intelligence method, Soft Computing, 24, 11, pp. 7937-7946, (2020); Frisk M., Jonsson A., Sellman S., Flisberg P., Ronnqvist M., Wennergren U., Route optimization as an instrument to improve animal welfare and economics in pre-slaughter logistics, PLoS One, 13, 3, (2018); Samaranayake P., Toncich D., Integration of production planning, project management and logistics systems for supply chain management, International Journal of Production Research, 45, 22, pp. 5417-5447, (2007); Xidias E.K., Nearchou A.C., Aspragathos N.A., Integrating path planning, routing, and scheduling for logistics operations in manufacturing facilities, Cybernetics & Systems, 43, 3, pp. 143-162, (2012); Barenji A.V., Wang W.M., Li Z., Guerra-Zubiaga D.A., Intelligent e-commerce logistics platform using hybrid agent based approach, Transportation Research Part E: Logistics and Transportation Review, 126, pp. 15-31, (2019); Hesse M., Rodrigue J.-P., The transport geography of logistics and freight distribution, Journal of Transport Geography, 12, 3, pp. 171-184, (2004); Sun Y., Geng N., Gong S., Yang Y., Research on improved genetic algorithm in path optimization of aviation logistics distribution center, Journal of Intelligent and Fuzzy Systems, 38, 1, pp. 29-37, (2020); Liu X.H., Zhang D., Zhang J., Zhang T., Zhu H., A path planning method based on the particle swarm optimization trained fuzzy neural network algorithm, Cluster Computing, 24, 3, pp. 1901-1915, (2021); Roy P., Mahapatra G.S., Dey K.N., Neuro-genetic approach on logistic model based software reliability prediction, Expert Systems with Applications, 42, 10, pp. 4709-4718, (2015); Zheng K., Zhang Q., Hu Y., Wu B., Design of fuzzy system-fuzzy neural network-backstepping control for complex robot system, Information Sciences, 546, pp. 1230-1255, (2021); Paul A., Saravanan V., Thangaiah P.R., Data mining analytics to minimize logistics cost, International Journal of Advances in Science and Technology, 2, 3, pp. 89-107, (2011); Zu E., Shu M.H., Huang J.C., Hsu B.M., Hu C.M., Management problems of modern logistics information system based on data mining, Mobile Information Systems, 2021, (2021)","S. Lan; College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China; email: 201309020223@stu.sdnu.edu.cn",null,"Hindawi Limited",{"$nulls":5},"1574017X",null,null,null,"English","Mob. Inf. Sys.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85137131789"]
["Stojanov M.","Stojanov, Michal (57226856476)",5.7226856476E10,"Q-COMMERCE – THE NEXT GENERATION E-COMMERCE",2022.0,"Business Management",2022.0,1.0,null,17.0,34.0,17.0,2.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85132657949&partnerID=40&md5=30726989305458b8c90439831e3b69b4","Department of Economics and Management of Commerce and Services, University of Economics – Varna, Bulgaria","Stojanov M., Department of Economics and Management of Commerce and Services, University of Economics – Varna, Bulgaria","Q-commerce is a product of the integration of information and communication technologies and the migration of product exchange in the online environment, which in combination with the possibilities of physical delivery within a relatively short period of time, creates a new business segment for product exchange. In the course of the article, general and specific methods such as the descriptive method, situational and content analysis are used. This paper presents the nature, features, status and future development of Q-commerce as the next generation of e-commerce. Q-commerce is a business model that is gaining momentum, which is a product of rapid development and penetration of digital technologies in human and business life, increasing concentration of urban population, anti-epidemic restrictions imposed during the pandemic of COVID-19. © 2022, Dimitar A Tsenov Academy of Economics. All rights reserved.","dark warehouse; delivery-on-demand; e-commerce; quick commerce",{"$nulls":7},"Anand G., Dark stores turn critical quick commerce drivers for leading e-grocers, (2021); Clarence-Smith L., Get wise or get eaten, grocers are warned, Times, The (United Kingdom), pp. 44-45, (2021); (2022); D'Mello S., Q-commerce to unlock $20b of Mena digital economy, (2021); Company Presentation (November 2020), (2020); Dimitrova V., Zhelyazkova D., Grozdeva D., Stojanov M., Sales management, (2011); Grindey J., We are Sick and Tired of Waiting So Q’ing is Going to Replace Queuing, (2021); Hausmann L., Herrmann N. A., Krause J., Netzer T., Same-day delivery: The next evolutionary step in parcel logistics, (2014); New 'quick commerce' channel worth £1.4bn*, according to IGD estimate, (2021); Ivanova D., Efficiency in the last mile in logistics, (2020); Jindal R. P., Gaur D. K., Li w., Ma Y., Omnichannel battle between Amazon and Walmart: Is the focus on delivery the best strategy?, Journal of business research, 122, pp. 270-280, (2021); Klintner S., Vinberg J., Conditions for executing a q-fulfillment process in the warehouse of a retailer of consumables: Based on a case study at Staples, (2021); Mirkovic I., What is Q-Commerce?, (2021); Mitsostergiou E., How quickly will Q-commerce continue to grow? (Savills plc), (2021); Ordinance No H-18 of 13 December 2006 on Registration and Reporting through Fiscal Devices of Sales in Trade Sites, the Requirements to Software for Their Management and Requirements to the Persons, Who Carry out Sales Through Electronic Shop; Ordinance № 12 of 18 November 2021 on the specific requirements for distance food trade, (2021); (2021); Sahay P., Direct to consumer & quick commerce among others to drive e-com sales in next decade, (2021); Tele2 and foodora in a new collaboration on, (2021); Online Food Delivery Services Market Growth To Accelerate At Rate Of 11% As Per The Business Research Company's Online Food Delivery Services Global Market Report 2021, (2021); Quick Commerce | New Generation Delivery Explained, (2021); Watts A., What is the Future of Q-Commerce? 5 Experts’ Predictions for the On Demand Delivery Industry, (2021); (2022)","M. Stojanov; Department of Economics and Management of Commerce and Services, University of Economics – Varna, Bulgaria; email: michal.stojanov@ue-varna.bg",null,"Dimitar A Tsenov Academy of Economics",{"$nulls":5},8616604.0,null,null,null,"English","Bus. Manag.","Article","Final",null,"Scopus","2-s2.0-85132657949"]
["Salvador-Grijalva O.M.; Avilés-Sacoto S.V.; Mosquera-Recalde G.E.","Salvador-Grijalva, Osmar Martín (57890309100); Avilés-Sacoto, Sonia Valeria (56527314500); Mosquera-Recalde, Galo Eduardo (57210971241)","57890309100; 56527314500; 57210971241","Application of a mobile facility routing problem in a delivery company",2022.0,"International Journal of Operational Research",44.0,4.0,null,496.0,521.0,25.0,0.0,"10.1504/ijor.2022.125130","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85138115667&doi=10.1504%2fijor.2022.125130&partnerID=40&md5=bf7f74e20e262e5741d2e44cec943a24","Universidad San Francisco de Quito (USFQ), Campus Cumbayá, Diego de Robles s/n, Pichincha, Quito, 170157, Ecuador; Departamento de Ingeniería Industrial Colegio de Ciencias e Ingenierías, Instituto de Innovación en Productividad y Logística CATENA-USFQ, Universidad San Francisco de Quito (USFQ), Diego de Robles y Vía Interocenica, Pichincha, Quito, 170901, Ecuador","Salvador-Grijalva O.M., Universidad San Francisco de Quito (USFQ), Campus Cumbayá, Diego de Robles s/n, Pichincha, Quito, 170157, Ecuador; Avilés-Sacoto S.V., Departamento de Ingeniería Industrial Colegio de Ciencias e Ingenierías, Instituto de Innovación en Productividad y Logística CATENA-USFQ, Universidad San Francisco de Quito (USFQ), Diego de Robles y Vía Interocenica, Pichincha, Quito, 170901, Ecuador; Mosquera-Recalde G.E., Departamento de Ingeniería Industrial Colegio de Ciencias e Ingenierías, Instituto de Innovación en Productividad y Logística CATENA-USFQ, Universidad San Francisco de Quito (USFQ), Diego de Robles y Vía Interocenica, Pichincha, Quito, 170901, Ecuador","In the last years, the growth of e-commerce has caused several changes in the way of how companies administrate their facilities and the transportation of their vehicles. Nowadays, companies must deal with small orders, short delivery schedules and a variable workload. This paper proposes a methodology, based the Ecuadorian company ZDelivery, to optimise the delivery of products with the use of mobile facilities. A series of tools are employed to solve the problem. In first place, a clustering technique is used to find strategic points within the city where the mobile facilities can be located. Then, an adaptation of a mobile facility routing problem is applied to determine the location and time where the mobile facilities should be located. Finally, to solve the model, the Monte Carlo method is applied to handle the uncertainty of the demand. This methodology applied to ZDelivery gives an optimal route for the fleet of the mobile facilities of the company between Friday's nights and Saturday's mornings where the strategic points in which the mobile facilities need to be located are specified for each mobile facility in intervals of 15 minutes.  © 2022 Inderscience Enterprises Ltd.","clustering; costs; delivery; demand; mobile facility; Monte Carlo simulation; routing problem; strategic points; time window; transportation; vehicles",{"$nulls":7},"Afshar-Nadjafi B., Afshar-Nadjafi A., Multi-depot time dependent vehicle routing problem with heterogeneous fleet and time windows, International Journal of Operational Research, 26, 1, (2016); Ahmad P.H., Dang S., Performance evaluation of clustering algorithm using different datasets, International Journal of Advance Research in Computer Science and Management Studies, 3, 1, pp. 167-173, (2015); Ahmadian S., Friggstad Z., Swamy C., Local-search based approximation algorithms for mobile facility location problems, Proceedings of the Twenty-fourth Annual ACM-SIAM Symposium on Discrete Algorithms, pp. 1607-1621, (2013); Ayadi M., Chabchoub H., Yassine A., A new mathematical formulation for the static demand responsive transport problem, International Journal of Operational Research, 29, 4, (2017); Bespamyatnikh S., Bhattacharya B., Kirkpatrick D., Segal M., Mobile facility location, Proceedings of the 4th International Workshop on Discrete Algorithms and Methods for Mobile Computing and Communications, pp. 46-53, (2000); Boysen N., de Koster R., Weidinger F., Warehousing in the e-commerce era: a survey, European Journal of Operational Research, pp. 1-16, (2018); Cardenas-Barron L.E., Gonzalez-Velarde J.L., Trevino-Garza G., Garza-Nunez D., Heuristic algorithm based on reduce and optimize approach for a selective and periodic inventory routing problem in a waste vegetable oil collection environment, International Journal of Production Economics, 211, pp. 44-59, (2019); Changdar C., Mahapatra G.S., Pal R.K., A modified genetic algorithm-based approach to solve constrained solid TSP with time window using interval valued parameter, International Journal of Operational Research, 26, 4, pp. 398-421, (2016); Chen L., Gendreau M., Ha M.H., Langevin A., A robust optimization approach for the road network daily maintenance routing problem with uncertain service time, Transportation Research Part E: Logistics and Transportation Review, 85, pp. 40-51, (2016); Colombo F., Cordone R., Lulli G., The multimode covering location problem, Computers and Operations Research, 67, pp. 25-33, (2016); Drakulic D., Takaci A., Maric M., Fuzzy covering location problems with different aggregation operators, Filomat, 31, 2, pp. 513-522, (2017); Latin America Ecommerce 2018, (2018); Estrada E., Graph and Network Theory in Physics, (2013); Friggstad Z., Salavatipour M.R., Minimizing movement in mobile facility location problems, Proceedings - Annual IEEE Symposium on Foundations of Computer Science, FOCS, pp. 357-366, (2008); Garcia S., Marin A., Covering location problems, Location Science, pp. 93-114, (2015); Halkidi M., Batistakis Y., Vazirgiannis M., On clustering validation techniques, Journal of Intelligent Information Systems, 17, 2-3, pp. 107-145, (2001); Halper R., Raghavan S., The mobile facility routing problem, Transportation Science, 45, 3, pp. 413-434, (2011); He R., Xu W., Sun J., Zu B., Balanced K-means algorithm for partitioning areas in large-scale vehicle routing problem, Third International Symposium on Intelligent Information Technology Application, (2009); Hillier F., Lieberman G., Introduction to Operations Research, (2015); Ilango M., Mohan V., A survey of grid based clustering algorithms, International Journal of Engineering Science and Technology, 2, 8, pp. 3441-3446, (2010); Kallehauge B., Larsen J., Madsen O.B., Solomon M.M., Vehicle routing problem with time windows, Column Generation, (2005); Kim G., Ong Y.S., Cheong T., Tan P.S., Solving the Dynamic Vehicle Routing Problem Under Traffic Congestion, 17, 8, (2016); Knapp B., Clark D., Batye R., (2015); Laudon K.C., Traver C., E-commerce 2017, (2018); Lei C., Lin W.H., Miao L., A multicut L-shaped based algorithm to solve a stochastic programming model for the mobile facility routing and scheduling problem, European Journal of Operational Research, 238, 3, pp. 699-710, (2014); Lei C., Lin W.H., Miao L., A two-stage robust optimization approach for the mobile facility fleet sizing and routing problem under uncertainty, Computers and Operations Research, 67, pp. 75-89, (2016); Lievano J., Gil R., Efecto del comercio electrónico en empresas tradicionales del sector comercial en Colombia, Revista Global de Negocios, 6, 2, pp. 41-50, (2018); Lopez J., Martinez J., Evaluación del consumo de combustible de vehículos livianos en el distrito metropolitano de Quito, (2013); Makarova I., Shubenkova K., Pashkevich A., Logistical costs minimization for delivery of shot lots by using logistical information systems, Procedia Engineering, 178, pp. 330-339, (2017); Marin A., Martinez-Merino L.I., Rodriguez-Chia A.M., Saldanha-da-Gama F., Multi-period stochastic covering location problems: modeling framework and solution approach, European Journal of Operational Research, 268, 2, pp. 432-449, (2018); Moradi E., Bidkhori M., Single facility location problem, Facility Location Concepts, Models, Algorithms and Case Studies, pp. 37-68, (2009); Noorizadegan M., Chen B., Vehicle routing with probabilistic capacity constraints, European Journal of Operational Research, 270, 2, pp. 544-555, (2018); Okulewicz M., Mandziuk J., Dynamic vehicle routing problem: a Monte Carlo approach, 2nd ITRIA Conference, pp. 119-138, (2015); Qi M., Cheng C., Wang X., Rao W., Mobile Facility Routing Problem with Service-time-related Demand, (2017); Ranieri L., Digiesi S., Silvestri B., Roccotelli M., A review of last mile logistics innovations in an externalities cost reduction vision, Sustainability, 10, 3, (2018); Saket S., Pandya S., An overview of partitioning algorithms in clustering techniques, International Journal of Advanced Research in Computer Engineering & Technology, 5, 6, pp. 2278-1323, (2016); Sanchez-Arocha O., Trevino-Garza G., Cardenas-Barron L.E., Meneses-Preciado C.V., A framework for solving routing problems for small and medium size companies, International Journal of Applied and Computational Mathematics, 4, 94, (2018); Saxena A., Prasad M., Gupta A., Bharill N., Patel O.P., Tiwari A., Lin C., Et al., A review of clustering techniques and developments, Neurocomputing, (2017); Schiffer M., Schneider M., Walther G., Laporte G., Vehicle routing and location routing with intermediate stops: a review, Transportation Science, (2019); Schmid V., Solving the dynamic ambulance relocation and dispatching problem using approximate dynamic programming, European Journal of Operational Research, 219, 3, pp. 611-621, (2012); Schmid V., Doerner K.F., Ambulance location and relocation problems with time-dependent travel times, European Journal of Operational Research, 207, 3, pp. 1293-1303, (2010); Sharma S.K., Routroy S., Yadav U., Vehicle routing problem: recent literature review of its variants, International Journal of Operational Research, 33, 1, (2018); Shreider Y.A., The Monte Carlo Method: The Method of Statistical Trials, (2014); Takes F., Kosters W., Applying Monte Carlo Techniques to the Capacitated Vehicle Routing Problem, (2010); Valdivieso C., Valdivieso R., Valdivieso O., Determinación del tamaño muestral mediante el uso de árboles de decision, 11, pp. 148-176, (2011); Yu Y., Wang X., Zhong R., Huang G., E-commerce logistics in supply chain management: practice perspective, Procedia CIRP, 52, pp. 179-185, (2016); Zambrano C., Acosta G., Loor J., Suarez B., Jaramillo C., Oviedo B., A sales route optimization mobile application applying a genetic algorithm and the Google Maps navigation system, Information Technology and Systems, pp. 517-527, (2019); Zhao Y., Karypis G., Evaluation of hierarchical clustering algorithms for document datasets, Proceedings of the Eleventh International Conference on Information and Knowledge Management - CIKM '02, (2002); Zhen L., Wang K., Hu H., Chang D., A simulation optimization framework for ambulance deployment and relocation problems, Computers and Industrial Engineering, 72, 1, pp. 12-23, (2014)","S.V. Avilés-Sacoto; Departamento de Ingeniería Industrial Colegio de Ciencias e Ingenierías, Instituto de Innovación en Productividad y Logística CATENA-USFQ, Universidad San Francisco de Quito (USFQ), Quito, Diego de Robles y Vía Interocenica, Pichincha, 170901, Ecuador; email: svaviless@usfq.edu.ec",null,"Inderscience Publishers",{"$nulls":5},1.7457645E7,null,null,null,"English","Int. J. Oper. Res.","Article","Final",null,"Scopus","2-s2.0-85138115667"]
["Chauhan S.; Goyal S.; Gupta P.; Jaiswal M.; Mehta N.","Chauhan, Sumedha (56612803400); Goyal, Sandeep (55343897100); Gupta, Parul (57861954300); Jaiswal, Mahadeo (7003354436); Mehta, Nikhil (23018928000)","56612803400; 55343897100; 57861954300; 7003354436; 23018928000","An empirical investigation of determinants for adoption of C2C auction marketplaces",2022.0,"International Journal of Business Information Systems",40.0,1.0,null,117.0,136.0,19.0,1.0,"10.1504/IJBIS.2022.122903","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85130497409&doi=10.1504%2fIJBIS.2022.122903&partnerID=40&md5=401d42e4f43ba1d45f7ca4952eb7505a","O.P. Jindal Global University, Sonipat Narela Road, Near Jagdishpur Village, Haryana, Sonipat, 131001, India; LM Thapar School of Management, Dera Bassi Campus, Off Derabassi, Barwala Road, Mohali, 140507, India; Management Development Institute Gurgaon, Block C, Sukhrali, Sector 17, Haryana, Gurugram, 122007, India; Indian Institute of Management Sambalpur, Odisha, 768019, India; Bryan School of Business and Economics, University of North Carolina at Greensboro, 1400 Spring Garden St, Greensboro, 27412, NC, United States","Chauhan S., O.P. Jindal Global University, Sonipat Narela Road, Near Jagdishpur Village, Haryana, Sonipat, 131001, India; Goyal S., LM Thapar School of Management, Dera Bassi Campus, Off Derabassi, Barwala Road, Mohali, 140507, India; Gupta P., Management Development Institute Gurgaon, Block C, Sukhrali, Sector 17, Haryana, Gurugram, 122007, India; Jaiswal M., Indian Institute of Management Sambalpur, Odisha, 768019, India; Mehta N., Bryan School of Business and Economics, University of North Carolina at Greensboro, 1400 Spring Garden St, Greensboro, 27412, NC, United States","In the last two decades, online and real-time interactions have grown significantly between individual buyers and sellers. Consumer-to-consumer (C2C) electronic-commerce (e-commerce) has been increasingly adopted by the people as a direct interface for buying and selling products or services. This research focuses on identifying the key determinants for adoption of C2C auction marketplaces, especially online auctions. Rogers’ (2003) diffusion of innovation (DoI) theory has been used as the guiding framework for this study as C2C e-commerce falls into the category of technological innovation. Research methodology involves quantitative survey of 278 consumers of C2C auction marketplace in India and the application of logistic regression to determine the impact of DoI attributes on C2C e-commerce adoption. Research findings indicate that relative advantage, observability, perceived security, age, and gender influence the adoption of C2C auction marketplaces. However, compatibility, complexity, and trialability do not significantly influence the adoption of C2C auction market places. Copyright © 2022 Inderscience Enterprises Ltd.","C2C; consumer-to-consumer; diffusion of innovation; DoI; e-commerce; India; innovation",{"$nulls":7},"Abdul-Ghani E., Hyde K.F., Marshall R., Emic and etic interpretations of engagement with a consumer-to-consumer online auction site, Journal of Business Research, 64, 10, pp. 1060-1066, (2011); Adjei M.T., Noble S.M., Noble C.H., The influence of C2C communications in online brand communities on customer purchase behaviour, Journal of the Academy of Marketing Science, 38, 5, pp. 634-653, (2010); Agag G., El-masry A., Alharbi N. S., Almamy A.A., Development and validation of an instrument to measure online retailing ethics, Internet Research, 26, 5, pp. 1158-1180, (2016); Ahmad K., Moufeed Ayyash M., Ali Al-Qudah O.M., The effect of culture values on consumer intention to use Arabic e-commerce websites in Jordan: an empirical investigation, International Journal of Business Information Systems, 29, 2, pp. 155-182, (2018); Al-Qirim N., The adoption of eCommerce communications and applications technologies in small businesses in New Zealand, Electronic Commerce Research and Applications, 6, 4, pp. 462-473, (2007); Alrawi K.W., Sabry K.A., E-commerce evolution: a Gulf region review, International Journal of Business Information Systems, 4, 5, pp. 509-526, (2009); Alrousan M.K., Jones E., A conceptual model of factors affecting e-commerce adoption by SME owner/managers in Jordan, International Journal of Business Information Systems, 21, 3, pp. 269-308, (2016); Andreopoulou Z.S., Koutroumanidis T., Manos B., The adoption of e-commerce for wood enterprises, International Journal of Business Information Systems, 4, 4, pp. 440-459, (2009); Armstrong M., Competition in two-sided markets, The RAND Journal of Economics, 37, 3, pp. 668-691, (2006); Arpaci I., Computers in human behavior understanding and predicting students’ intention to use mobile cloud storage services, Computers in Human Behavior, 58, pp. 150-157, (2016); Azmi A., Sapiei N.S., Mustapha M.Z., Abdullah M., SMEs’ tax compliance costs and IT adoption: the case of a value-added tax, International Journal of Accounting Information Systems, 23, pp. 1-13, (2016); Chang C., Chen C., Examining hedonic and utilitarian bidding motivations in online auctions: impacts of time pressure and competition, International Journal of Electronic Commerce, 19, 2, pp. 39-65, (2015); Chauhan S., Goyal S., Platform ecosystems: the expert opinion, Journal of Information Technology Case and Application Research, 20, 2, pp. 86-89, (2018); Chauhan S., Mukhopadhyay S., Jaiswal M., The adoption of mobile app for B2C transaction in platform marketplace: An empirical examination of key drivers, Journal of Information Technology Case and Application Research, 20, 1, pp. 9-22, (2018); Chen C., Perceived risk, usage frequency of mobile banking services, Managing Service Quality: an International Journal, 23, 5, pp. 410-436, (2013); Chen J.V., Su B.C., Widjaja A.E., Facebook C2C social commerce: a study of online impulse buying, Decision Support Systems, 83, pp. 57-69, (2016); Chen X., Huang Q., Davison R. M., Economic and social satisfaction of buyers on consumer-to-consumer platforms: the role of relational capital, International Journal of Electronic Commerce, 21, 2, pp. 219-248, (2017); Chin A.G., Harris M.A., Brookshire R., A bidirectional perspective of trust and risk in determining factors that influence mobile app installation, International Journal of Information Management, 39, pp. 49-59, (2018); Christou E., Investigating attitudes towards mobile commerce for travel products, Turizam: međunarodni znanstveno-stručni časopis, 58, 1, pp. 7-18, (2010); Chu H.C., A conceptual model of motivations for consumer resale on C2C websites, Service Industries Journal, 33, 15–16, pp. 1527-1543, (2013); Chung K.C., Holdsworth D.K., Culture and behavioural intent to adopt mobile commerce among the Y Generation: comparative analyses between Kazakhstan, Morocco and Singapore, Young Consumers, 13, 3, pp. 224-241, (2012); Cooper J., The digital divide: the special case of gender, Journal of Computer Assisted Learning, 22, 5, pp. 320-334, (2006); Daim T., Basoglu N., Tanoglu I., A critical assessment of information technology adoption: technical, organisational and personal perspectives, International Journal of Business Information Systems, 6, 3, pp. 315-335, (2010); Deng Z., Lu Y., Wang B., Understanding Chinese enterprises’ adoption of enterprise short message services: combining IDT and TTF, International Journal of Services Technology and Management, 12, 2, pp. 192-215, (2009); Dutta S., Omolayole O., Are there differences between men and women in information technology innovation adoption behaviors: a theoretical study, The Journal of Business Diversity, 16, 1, pp. 106-114, (2016); Evans P.C., Gawer A., The Rise of the Platform Enterprise: A Global Survey, (2016); Fan Q., Lee J.Y., Kim J.I., The impact of web site quality on flow-related online shopping behaviors in C2C e-marketplaces: a cross-national study, Managing Service Quality, 23, 5, pp. 364-387, (2013); C2C Ecommerce in India Takes Baby Steps as Growing Number of Startups Look to Organise Space, (2017); Gao L., Waechter K.A., Bai X., Understanding consumers’ continuance intention towards mobile purchase: a theoretical framework and empirical study – a case of China, Computers in Human Behavior, 53, pp. 249-262, (2015); Goyal S., Sergi B.S., Esposito M., Literature review of emerging trends and future directions of e-commerce in global business landscape, World Review of Entrepreneurship, Management and Sustainable Development, 15, 1, pp. 226-255, (2019); Grandon E., Pearson J.M., E-commerce adoption: perceptions of managers/owners of small and medium sized firms in Chile, Communications of the Association for Information Systems, 13, 1, pp. 81-102, (2004); Hagiu A., Wright J., Multi-sided platforms, International Journal of Industrial Organization, 43, pp. 162-174, (2015); Huang L.Y., Hsieh Y.J., Consumer electronics acceptance based on innovation attributes and switching costs: the case of e-book readers, Electronic Commerce Research and Applications, 11, 3, pp. 218-228, (2012); Iansiti M., Levien R., Creating value in your business ecosystem, Harvard Business Review, 82, 3, pp. 68-78, (2004); 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Chauhan; O.P. Jindal Global University, Sonipat, Sonipat Narela Road, Near Jagdishpur Village, Haryana, 131001, India; email: sumedha.chauhan@gmail.com",null,"Inderscience Publishers",{"$nulls":5},1.7460972E7,null,null,null,"English","Int. J. Bus. Inf. Syst.","Article","Final",null,"Scopus","2-s2.0-85130497409"]
["Mu W.; Ding H.","Mu, Wei (57909672100); Ding, Heping (57665619000)","57909672100; 57665619000","C2C Model E-Commerce Credit Evaluation Model Based on Artificial Intelligence",2022.0,"Mobile Information Systems",2022.0,null,4820393.0,null,null,null,0.0,"10.1155/2022/4820393","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85139435389&doi=10.1155%2f2022%2f4820393&partnerID=40&md5=eb215cf52af5e045673ace137c9fd213","College of Business, Suzhou University, Anhui, Suzhou, 234000, China; Center for International Education, Philippine Christian University, Manila, 1004, Philippines","Mu W., College of Business, Suzhou University, Anhui, Suzhou, 234000, China; Ding H., College of Business, Suzhou University, Anhui, Suzhou, 234000, China, Center for International Education, Philippine Christian University, Manila, 1004, Philippines","The development of network computer technology and artificial intelligence technology promotes the generation of software agents. However, online shopping has inherent information asymmetry due to the anonymity and liquidity of C2C (Customer to Customer) transactions. In the virtual environment, buyers cannot see the physical products, and they do not experience online shopping in person. They can only select products through the seller's pictures and descriptions. After payment, there may be some problems, such as sending the wrong product, the seller does not deliver the goods after receiving the goods, or the seller does not receive the payment after delivery, etc. Therefore, the credit problem is the bottleneck for the development of online shopping business. Therefore, in order to ensure the transaction security of buyers and sellers, major C2C online trading platforms at home and abroad have established a credit evaluation mechanism. However, due to the reliability of e-commerce technology, the legal environment of e-commerce, the ethical environment of e-commerce, and the problems of existing credit evaluation indicators. The development of e-commerce in China is very slow. Therefore, actively exploring the credit model of Chinese e-commerce is of great significance to promoting the development of Chinese market economy. In this paper, AI technology analyzes the credit evaluation management method of C2C e-commerce website for transaction participants. This paper summarizes some key factors that affect the establishment of C2C credit, and further finds that there are some problems in the credit evaluation model involved in the e-commerce process. These problems stem from the inability to properly deal with the current development of e-commerce in China. There are problems with its evaluation system and honest transaction process. In order to better promote the development of e-commerce, in view of the above problems, this paper proposes a new model of C2C e-commerce credit system based on the game theory model of e-commerce buyers and sellers of AI technology, and further improves the evaluation model and related measures to completely solve the problem. Credit value generally shows a growth trend, but the trend is not obvious.  © 2022 Wei Mu and HePing Ding.",null,"Artificial intelligence; Computer networks; Game theory; Sales; Software agents; Virtual reality; AI Technologies; Artificial intelligence technologies; Buyers and sellers; Computer technology; Credit evaluation model; Credit evaluations; E- commerces; Model-based OPC; Network computers; Online shopping; Electronic commerce",{"$nulls":6},"Ba S., Whinston A.B., Zhang H., Building trust in online auction markets through an economic incentive mechanism, Decision Support, 35, (2003); Murray K.B., A test of services marketing theory: Consumer information acquisition activities, Journal of Marketing, 55, (1991); Grazioli S., Deceived under target online. jarvenpaa, Communications of the ACM, 46, (2003); Gregg D., Reputation systems in reducing on line auction fraud, International Journal of Electronic Commeree, (2006); Kauffman R., Charles A.W., Running Up the Bid:modeling Seller Opportunism in Internet Auctions, (2000); Macinnes I., Causes of Disputes in Online Auctions, Electronic Markets, 15, 2, pp. 146-157, (2005); Strad T.J., Ramaswami S.N., Trust worthinessin C2C online markets, Communications of the ACM, 45, 12, pp. 45-49, (2002); Chrysanthos D., Analyzing the Economic Efficiency of eBay-like Online Reputation Reporting Mechanisms, Economical Comment, (2001); Donna L., Thomas P., Novak M.P., Building Consumer Trust in Online Environments: The Case for Information Privacy, Communications of the ACM, (1998); Lee B., Yoo B., Internalization of Electronic \"auction Market\" and Information Asymmetry in Electronic Commerce, 11th Workshop on Information Systems and Economics (WISE 1999), (1999); Beth T., Borcherding M., Klein B., Valuation of trust in open networks, Proceedings of the Third European Symposium on Research in Computer Security, (1994); Glen L.U., Fareena S., Willian J.Q., Placing trust at the center of your Internet strategy, Sloan Management Review, 42, pp. 39-48, (2000); Jingan Z., Xiane G., Trust Evaluation Model Based on Fuzzy Logic for C2C E-Commerce, Proceedings of the International Symposium on Information Engineering and Electronic Commerce, (2009); Lu J.C., Liao J., E-Commerce Customer credit evaluation based on AHP, Proceedings of the Software Engineering and Service Sciences, (2010); McKnight D.H., Kacmar C.J., Choudhury V., Shifting Factors and the Ineffectiveness of Third Party Assurance Seals: A Two-Stage Model of Initial Trust in a Web Business, Electronic Markets, 14, 3, pp. 252-266, (2004); Josang A., Hird S., Simulating the effect of reputation system markets, Proceeding of the First International Conference on Trust Management, (2003); Mui L., Mohtashemi M., Halberstadt A., A computational model for trust and reputation, Proceedings of the 35th Hawaii International Conference on System Sciences, (2002); Josang A., Knapskog S.J., A Metric for Trusted Systems. Global IT Security, (1998); Josang A., Trust-based decision making for electronic transactions, Proceedings of the 4th Nordic Workshop on Secure Computer System(NORDSEC99), (1999); Kang S., Yuanjing G., Chaohua L., The Model of Credit Evaluation in C2C E-Commerce, Proceedings of the Information Management and Engineering, (2010); Bolton R.N., Drew J.H., A multistage model of customers assessments of service quality and value, Journal of Consumer Research, 17, 4, (1991); Josang A., Ismail R., Boyd C., A survey of trust and reputation sys-tems for online service provision, Decision Support, 43, 2, pp. 618-644, (2007); Cabral L., Hortacsu A., The dynamics of seller reputation: Theory and evidence from eBay, NBER Working Paper Series, (2004); Resnick P., Zeckhauser R., Friedman E., Kuwabara K., Reputation systems, Communications of the ACM, 43, pp. 45-48, (2000); Ba S., Pavlou P.A., Evidence of the effect of trust building technology in electronic markets: Price premiums and buyer behavior, MIS Quarterly, 26, 3, (2002); McDonald C.G., Slawson V.C.J., Reputation in an Internet Auction Market, Economic Inquiry, 40, pp. 633-650, (2002); Bin Y., Munindar P., Mechanism of Reputation Management in Electronic communities, Proceedings of Fourth International Workshop on Cooperative Information Agents, (2000); Kollock P., The production of trust in online markets, Advances in Group Processes, 16, pp. 99-123, (1999); Lee M.K., Turban E., A trust model for consumer Internet shopping, International Journal of Electronic Commerce, 6, pp. 75-91, (2011); Mui L., Mohtashemi M., A computational model for trust and rePutation, Proceedings of the 35th Annual Hawaii International Conference on System Sciences, (2002)","H. Ding; College of Business, Suzhou University, Suzhou, Anhui, 234000, China; email: dingheping@ahszu.edu.cn",null,"Hindawi Limited",{"$nulls":5},"1574017X",null,null,null,"English","Mob. Inf. Sys.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85139435389"]
["Kim H.; Woo J.; Hyun K.H.","Kim, Hwan (55148213900); Woo, Jongbum (57875212800); Hyun, Kyung Hoon (56236871600)","55148213900; 57875212800; 56236871600","PlicAR: Enhancing Online Product Evaluation and Shopping Experience through an Augmented Reality Based 3D Model Visualization Service; [PlicAR: 증강현실 기반 3D 모형 구축 기술을 통한 온라인 쇼핑 경험 증진]",2022.0,"Archives of Design Research",35.0,3.0,null,181.0,195.0,14.0,0.0,"10.15187/adr.2022.08.35.3.181","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137289301&doi=10.15187%2fadr.2022.08.35.3.181&partnerID=40&md5=2c036487c8d22c22c0b6a8b574856dc3","Department of Interior Architecture Design, Research Assistant Professor, Hanyang University, Seoul, South Korea; RECON Labs, Chief Product Officer, Seoul, South Korea; Department of Interior Architecture Design, Assistant Professor, Hanyang University, Seoul, South Korea","Kim H., Department of Interior Architecture Design, Research Assistant Professor, Hanyang University, Seoul, South Korea; Woo J., RECON Labs, Chief Product Officer, Seoul, South Korea; Hyun K.H., Department of Interior Architecture Design, Assistant Professor, Hanyang University, Seoul, South Korea","Background The online commerce (E-commerce) market has been growing steadily every year due to the convenience of allowing customers to purchase products without going to a brick-and mortar store. However, customers still visit offline stores to check the actual size, shape, and details of the product. In this context, augmented reality (AR) commerce using augmented reality technology is emerging as a new alternative to online and offline stores. Through several studies, AR commerce has been found to have a positive effect on the purchasing decision process of customers. However, few attempts have been conducted to understand the experience of using AR commerce services from the point of view of users, not customers. Therefore, this study finds user experience (UX) factors that AR commerce should consider supporting clear delivery of product information and users' universal shopping experience and suggests a method for improving them. Methods We collected participant opinions on AR commerce services through an online survey (sample size = 100) as a preliminary study to investigate the essential UX design components for AR commerce services. By extracting meaningful words and analyzing the word list from the participants’responses, we identified ‘3D model quality and ‘accessibility’as the essential UX components. In this respect, we developed PlicAR to enhance the AR commerce experience. Finally, an extensive online survey (sample size = 400) was conducted. It was confirmed that the experience of using PlicAR improved when compared to the existing AR commerce service. Results By comparing PlicAR and IKEA Place through the comparative experiment, ‘3D model quality’and ‘system accessibility’were revealed as unique advantages of PlicAR. From the results, it was confirmed that the improved 3D model quality and system accessibility enhanced the AR commerce experience. Conclusions In order to provide AR content, high-quality 3D model production is a prerequisite for an improved AR commerce experience. However, 3D model production requires time and resources. For this reason, such tasks can only be conducted by largely capitalized corporates. In this respect, we propose a PlicAR with a 3D model reconstruction method using neural rendering and web-based accessibility. The two key features of PlicAR allow small and medium-sized third party sellers to create and provide AR content to promote their products directly. © This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons. org/licenses/by nc/3.0/), which permits unrestricted educational and non-commercial use, provided the original work is properly cited","Ar commerce design; Automatic 3d model reconstruction; Online marketplace; Ux design",{"$nulls":5},"Ministry of Science, ICT and Future Planning, MSIP; National Landcare Programme, NLP; Institute for Information and Communications Technology Promotion, IITP","This work was supported by Institute of Information & communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT) (No.2021-0-00968, Developing State-of-Art 2D sketch to 3D model Conversion and Refinement Methods Inspired by NLP Translation Model)","Alves C., Luis Reis J., The Intention to Use E-Commerce Using Augmented Reality - The Case of IKEA Place, Advances in Intelligent Systems and Computing, 1137 AISC, pp. 114-123, (2020); Di W., Sundaresan N., Piramuthu R., Bhardwaj A., Is a picture really worth a thousand words? - On the role of images in e-commerce, WSDM 2014 - Proceedings of the 7th ACM International Conference on Web Search and Data Mining, pp. 633-641, (2014); Kaushik K., Mishra R., Rana N. P., Dwivedi Y. K., Exploring reviews and review sequences on e-commerce platform: A study of helpful reviews on Amazon, Journal of Retailing and Consumer Services, 45, pp. 21-32, (2018); Kowalczuk P., Siepmann, Adler J., Cognitive, affective, and behavioral consumer responses to augmented reality in e-commerce: A comparative study, Journal of Business Research, 124, pp. 357-373, (2021); Lu Y., Smith S., Augmented Reality E-Commerce Assistant System: Trying While Shopping, Human-Computer Interaction. Interaction Platforms and Techniques. HCI 2007. Lecture Notes in Computer Science, 4551, (2007); Maity M., Dass M., Consumer decision-making across modern and traditional channels: E-commerce, m-commerce, in-store, Decision Support Systems, 61, 1, pp. 34-46, (2014); Manchanda M., Deb M., On m-Commerce Adoption and Augmented Reality: A Study on Apparel Buying Using m-Commerce in Indian Context, Journal of Internet Commerce, 20, 1, pp. 84-112, (2021); Plic AR., Your AR Commerce Made Easy with PlicAR, (2022); U.S. retail e-commerce sales share 2021, (2021); Sen S., Lerman D., Why are you telling me this? An examination into negative consumer reviews on the Web, Journal of Interactive Marketing, 21, 4, pp. 76-94, (2007)","H. Kim; Department of Interior Architecture Design, Research Assistant Professor, Hanyang University, Seoul, South Korea; email: hoonhello@hanyang.ac.kr",null,"Korean Society of Design Science",{"$nulls":5},1.2268046E7,null,null,null,"English","Arch. Des. Res.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85137289301"]
["Akil S.; Ungan M.C.","Akil, Siber (58540743900); Ungan, Mustafa Cahit (56148897900)","58540743900; 56148897900","E-commerce logistics service quality: Customer satisfaction and loyalty",2022.0,"Journal of Electronic Commerce in Organizations",20.0,1.0,{"$nulls":4},11.0,"10.4018/JECO.292473","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85139798855&doi=10.4018%2fJECO.292473&partnerID=40&md5=9d222b7d06c64c484cdb73fd5d52a44d","Sakarya University, Turkey","Akil S., Sakarya University, Turkey; Ungan M.C., Sakarya University, Turkey","With the recent developments in technology, globalization, and the COVID-19 pandemic, the volume of e-commerce logistics activity has been growing rapidly. However, a literature review for this study indicated that there is a lack of research on commerce logistics service quality. This study intends to fill this gap in the literature. It aims to identify the e-commerce logistics service quality factors that affect customer satisfaction. It is also interested in identifying if there is any relationship between the satisfaction of e-commerce customers and their loyalty. Data from 1,562 e-commerce customers living in Turkey were collected via a web-based survey. The results were analysed using structural equation modelling. Timeliness, order condition, order accuracy, and order discrepancy handling were found to have a positive effect on customer satisfaction. A positive relationship between customer satisfaction and customer loyalty was also found. © 2022 IGI Global. All rights reserved.","Customer Loyalty; Customer Satisfaction; E-Commerce; Logistics Service Quality",{"$nulls":7},"Anderson J. C., Gerbing D. W., Structural equation modeling in practice: A review and recommended two-step approach, Psychological Bulletin, 103, 3, pp. 411-423, (1988); Bienstock C. C., Royne M. B., Sherrell D., Stafford T. 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Economics and Business, 7, 8, pp. 333-344, (2020); Gil-Saura I., Ruiz-Molina M. E., Logistics service quality and buyer customer relationships: The moderating role of technology in B2B and B2C contexts, Service Industries Journal, 31, 7, pp. 1109-1123, (2011); Gil-Saura I., Ruiz-Molina M. E., Servera-Frances D., Logistic service quality and technology: A comparison between supplier-retailer and retailer-consumer relationships, International Review of Retail, Distribution and Consumer Research, 18, 5, pp. 495-510, (2008); Grant D., Juntunen J., Jari J., Mari J., Investigating brand equity of third-party service providers, Journal of Services Marketing, 28, 3, pp. 214-222, (2014); Gremler D. D., Brown S. W., Service loyalty: its nature, importance, and implications, Proceedings American Marketing Association, pp. 171-180, (1996); Guthrie G., Fosso-Wamba S., Arnaud J. B., Online consumer resilience during a pandemic: An exploratory study of e-commerce behavior before, during and after a COVID-19 lockdown, Journal of Retailing and Consumer Services, 61, pp. 1-15, (2021); Hair J. F., Anderson R. E., Tatham R. L., Black W. C., Multivariate Data Analysis, (1998); Hair J. F., Page M., Brunsveld N., Essentials of Business Research Methods, (2020); Hendayani R., Dharmawan M. C., Strategies for improving the quality of logistics courier services through priority problem-solving based on multiclass classification, IOP Conference Series: Materials Science and Engineering, (2020); Henseler J., Dijkstra T. K., Sarstedt M., Ringle C. M., Diamantopoulos A., Straub D. W., Ketchen D. J., Hair J. F., Hult G. T. M., Calantone R. J., Common beliefs and reality about partial least squares: Comments on Ronkko & Evermann, Organizational Research Methods, 17, 2, pp. 182-209, (2014); Hu L., Bentler P. 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C., Fernie J., The interface between retailers and logistics service providers in the online market, European Journal of Marketing, 45, 3, pp. 334-357, (2011); Yang Y., Wang R., Research on composition and characteristics of logistics capability based on customer value, 2019 International Conference on Emerging Researches in Management, Business, Finance and Economics (ERMBFE 2019), pp. 639-643, (2019); Yeo G. T., Thai V. V., Roh S. Y., An analysis of port service quality and customer satisfaction: The case of korean container ports, The Asian Journal of Shipping and Logistics, 31, 4, pp. 437-447, (2015); Zailani S., Jafarzadeh S., Iranmanesh M., Nikbin D., Selim N. I. I., Halal logistics service quality: Conceptual model and empirical evidence, British Food Journal, 120, 11, pp. 2599-2614, (2018); Zhang Q., Huang Y., Yan W., Wang Y., The impact of logistics factors on customer reviews in e-commerce, International Journal of Multimedia and Ubiquitous Engineering, 10, 7, pp. 201-212, (2015); Zlatkovic M. M., Survey of customer satisfaction: The example of freight distribution center, 1st Logistics International Conference Belgrade, pp. 215-220, (2013)",null,null,"IGI Global",{"$nulls":5},1.5392937E7,null,null,null,"English","J. Electr. Commer. Organ.","Article","Final","All Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85139798855"]
["Zheng L.","Zheng, Luyao (57925224300)",5.79252243E10,"Analysis of Computer-Based Blockchain Technology in Cross-Border E-commerce Platforms",2022.0,"Mobile Information Systems",2022.0,null,5083518.0,null,null,null,2.0,"10.1155/2022/5083518","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85139737363&doi=10.1155%2f2022%2f5083518&partnerID=40&md5=da03f84cbf42a449a3389a8ddc9b68b5","Accounting, North China Electric Power University, Baoding, 71000, China","Zheng L., Accounting, North China Electric Power University, Baoding, 71000, China","Under the background of economic globalization and the rapid development of computer technology in the global coverage of the Internet, the integration of the world economy has been strengthened, and the continuous innovation of technology and foreign trade formats has promoted the rapid development of e-commerce, but there are also small e-commerce entities, weak high trade trust cost, high logistics payment cost, long cycle time, and adjustments caused by data flow. The decentralization, information sharing, irreversibility, and smart contract technology of computer blockchain can change the business model of traditional industries and promote business and social change. Based on the current trend of e-commerce development, this thesis analyzes the problems in the development of e-commerce, discusses the innovation of e-commerce business models, constructs the framework of e-commerce, and gives the issues of trust, customs supervision, payment and other issues. Solution. The logistics and data flow encountered in e-commerce using computer blockchain technology has low emissivity of information, high cost of data format conversion, and it is not easy to form a consensus.  © 2022 Luyao Zheng.",null,"Data flow analysis; Data handling; Data transfer; Economic and social effects; International trade; Block-chain; Business models; Commerce platforms; Computer technology; Cross-border; Dataflow; E- commerces; Economic globalization; Global coverage; World economy; Blockchain",{"$nulls":6},"Huang J., Comparison of e-commerce regulations in Chinese and American ftas: Converging approaches, diverging contents, and polycentric directions?, Netherlands International Law Review, 64, 2, pp. 309-337, (2017); Nurgazina J., Pakdeetrakulwong U., Moser T., Reiner G., Distributed ledger technology applications in food supply chains: A review of challenges and future research directions, Sustainability, 13, 8, (2021); Li J., Greenwood D., Kassem M., Blockchain in the built environment and construction industry: A systematic review, conceptual models and practical use cases, Automation in Construction, 102, pp. 288-307, (2019); Capece G., Lorenzi F., Blockchain and healthcare: Opportunities and prospects for the EHR, Sustainability, 12, 22, (2020); Ainsworth R.T., Viitasaari V., Payroll tax & the blockchain, Tax Notes International, March, 13, pp. 1007-1024, (2017); Yilma K.M., Abraha H.H., The Internet and regulatory responses in Ethiopia: Telecoms, cybercrimes, privacy, e-commerce, and the new media, Mizan Law Review, 9, 1, (2015); Amponsah A.A., Adekoya A.F., Weyori B.A., Improving the financial security of national health insurance using Cloud-based blockchain technology application, International Journal of Information Management Data Insights, 2, 1, (2022); Malby S., Strengthening the rule of law through technology, Commonwealth Law Bulletin, 43, 3-4, pp. 307-317, (2017); Olatunji T., Advancing the Cause of fintech in Nigeria through regulation, The Gravitas Review of Business & Property Law, 11, 4, pp. 17-34, (2020); Reddy S., Implementing a south african e-dispute resolution system for consumer disputes, Obiter, 41, 2, pp. 371-395, (2020); Ezuwore-Obodoekwe C.N., As E., Se E., Chukwubuzo A.F., A critical analysis of cashless banking policy in Nigeria, IOSR Journal of Business and Management, 16, 5, pp. 30-42, (2014); Yao Q.M., Baker L.T., Lohrke F.T., Building and sustaining trust in remote work by platform-dependent entrepreneurs on digital labor platforms: Toward an integrative framework, Journal of Business Research, 149, pp. 327-339, (2022); Allen J.G., Lastra R.M., Border problems: Mapping the third border, The Modern Law Review, 83, 3, pp. 505-538, (2020); Balamurugan S., Ayyasamyio A., Suresh Joseph K., A review on privacy and security challenges in the Internet of things (IoT) to protect the device and communications networks, International Journal of Computer Science and Information Security, 16, 6, pp. 58-62, (2018); Brynjolfsson E., Hitt L.M., Beyond computation: Information technology, organizational transformation and business performance, The Journal of Economic Perspectives, 14, 4, pp. 23-48, (2000); Hart P., Saunders C., Power and trust: Critical factors in the adoption and use of electronic data interchange, Organization Science, 8, 1, pp. 23-42, (1997); Mishra A., Alzoubi Y.I., Gill A.Q., Anwar M.J., Cybersecurity enterprises policies: A Comparative study, Sensors, 22, 2, (2022); Bergamaschi M., Bettinelli C., Lissana E., Picone P.M., Past, ongoing, and future debate on the interplay between internationalization and digitalization, Journal of Management & Governance, 25, 4, pp. 983-1032, (2021); Tran-Dang H., Kim D.S., The physical Internet in the era of digital transformation: Perspectives and open issues, IEEE Access, 9, pp. 164613-164631, (2021); Taylor S., Todd P.A., Understanding information technology usage: A test of competing models, Information Systems Research, 6, 2, pp. 144-176, (1995)","L. Zheng; Accounting, North China Electric Power University, Baoding, 71000, China; email: zhengluyao@ncepu.edu.cn",null,"Hindawi Limited",{"$nulls":5},"1574017X",null,null,null,"English","Mob. Inf. Sys.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85139737363"]
["Gao S.; Meng W.","Gao, Shurui (57291667900); Meng, Weidong (57191250139)","57291667900; 57191250139","Development of a Personalized Recommendation System for E-Commerce Products for Distributed Storage Systems",2022.0,"Computational Intelligence and Neuroscience",2022.0,null,4752981.0,null,null,null,1.0,"10.1155/2022/4752981","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85133147776&doi=10.1155%2f2022%2f4752981&partnerID=40&md5=d64c0fdbc0f3f2c3a0e3d086e343ca4f","School of Economics and Management, Beijing-Tianjin-Hebei Collaborative Development Management Innovation Research Center, Yanshan University, Qinhuangdao, 066004, China","Gao S., School of Economics and Management, Beijing-Tianjin-Hebei Collaborative Development Management Innovation Research Center, Yanshan University, Qinhuangdao, 066004, China; Meng W., School of Economics and Management, Beijing-Tianjin-Hebei Collaborative Development Management Innovation Research Center, Yanshan University, Qinhuangdao, 066004, China","Because the distributed storage system is based on network technology, it can store data in multiple independent low-cost physical storage devices, and it is also suitable for large-capacity storage, so it has become more and more popular. Today, common applications of distributed storage systems include cloud storage services, data center storage services, and P2P storage services. Typical ones are GFS, HDFS, OceanStore, and Dynamo. Due to regional and economic differences, the development level of global e-commerce (b2c) is very inconsistent. b2c contains the following key tags: buying and selling, which is the core of the website platform. E-commerce provides business users with transparent information and high-quality cheap products. Logistics is the basic guarantee for customers to execute transactions, and it is also a strict indicator of the website platform. There will be many visits during the operation of the e-commerce system, and the number of users in the early stage will increase exponentially. A safe and efficient e-commerce system can provide users with one-stop transaction support and convenient transaction processes. The personalized recommendation system has formulated some rules for certain fields, based on these rules, and defined certain types of knowledge for certain items to meet the needs of certain users and use the defined reasoning rules to generate recommendation results.  © 2022 Shurui Gao and Weidong Meng.",null,"Commerce; Computer Communication Networks; Consumer Behavior; Delivery of Health Care; Electronic commerce; Linear systems; Peer to peer networks; Recommender systems; Virtual storage; Cloud storage services; Datacenter; Distributed storage system; E-commerce systems; Large capacity storage; Low-costs; Network technologies; Personalized recommendation systems; Service data; Storage services; commercial phenomena; computer network; consumer attitude; health care delivery; Websites",{"$nulls":6},"Wang Q., Wang C., Ren K., Lou W., Li J., Enabling public auditability and data dynamics for storage security in cloud computing, IEEE Transactions on Parallel and Distributed Systems, 22, 5, pp. 847-859, (2010); Al-Somali S.A., Gholami R., Clegg B., A stage-oriented model (SOM) for e-commerce adoption: A study of Saudi Arabian organisations, Journal of Manufacturing Technology Management, 26, 1, pp. 2-35, (2015); Lu L., Reardon T., An economic model of the evolution of food retail and supply chains from traditional shops to supermarkets to e - Commerce, American Journal of Agricultural Economics, 100, 5, pp. 1320-1335, (2018); Davila A., Gupta M., Palmer R., Moving procurement systems to the Internet, European Management Journal, 21, 1, pp. 11-23, (2003); Liu X., Walsh J., Development of cross-border e-commerce in the context of China's foreign trade strategy, City University Research Journal, 9, 4, pp. 776-787, (2019); Dutta P., Choi T.M., Somani S., Butala R., Blockchain technology in supply chain operations: Applications, challenges and research opportunities, Transportation Research Part E: Logistics and Transportation Review, 142, (2020); Ye M., Yin P., Lee W.-C., Lee D.-L., Exploiting Geographical Influence for Collaborative Point-of-interest Recommendation, pp. 325-334; Zheng V.W., Cao B., Zheng Y., Xie X., Yang Q., Collaborative Filtering Meets Mobile Recommendation: A User-centered Approach, pp. 236-241; Hua Z., Be K., Shi Q., Research on the information tracing model for cross-border e-commerce products based on blockchain, E3S Web of Conferences, 235, 4, (2021); Liu Z., Li Z., A blockchain-based framework of cross-border e-commerce supply chain, International Journal of Information Management, 52, (2019); Chandrasekar Subramaniam M.J.S., A study of the value and impact of B2B e-commerce: The case of web-based procurement, International Journal of Electronic Commerce, 6, 4, pp. 19-40, (2002); Liao Q., Wang Y., Prospect and Challenges of Cross-border Payment Posed by Digital Currency-from the Perspective of Blockchain Coalition; Hallikainen H., Laukkanen T., Trustworthiness in e-commerce: A replication study of competing measures, Journal of Business Research, 126, pp. 644-653, (2021); Li S., Structure optimization of e-commerce platform based on artificial intelligence and blockchain technology, Wireless Communications and Mobile Computing, 2020, 12, (2020)","S. Gao; School of Economics and Management, Beijing-Tianjin-Hebei Collaborative Development Management Innovation Research Center, Yanshan University, Qinhuangdao, 066004, China; email: 2021001632@poers.edu.pl",null,"Hindawi Limited",{"$nulls":5},1.6875265E7,null,null,3.5769278E7,"English","Comput. Intell. Neurosci.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85133147776"]
["Panasenko S.; Seifullaeva M.; Ramazanov I.; Mayorova E.; Nikishin A.; Vovk A.M.","Panasenko, Svetlana (58334061000); Seifullaeva, Maisa (57189524504); Ramazanov, Ibragim (57204852929); Mayorova, Elena (56208986700); Nikishin, Alexander (57193392032); Vovk, A.M. (57965549100)","58334061000; 57189524504; 57204852929; 56208986700; 57193392032; 57965549100","Impact of the Pandemic on the Development and Regulation of Electronic Commerce in Russia",2022.0,"International Journal of Advanced Computer Science and Applications",13.0,5.0,null,652.0,658.0,6.0,2.0,"10.14569/IJACSA.2022.0130576","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85131395309&doi=10.14569%2fIJACSA.2022.0130576&partnerID=40&md5=bcae6a62bdab3b7d0bb9eff29b528ddf","Plekhanov Russian University of Economics, Moscow, Russian Federation","Panasenko S., Plekhanov Russian University of Economics, Moscow, Russian Federation; Seifullaeva M., Plekhanov Russian University of Economics, Moscow, Russian Federation; Ramazanov I., Plekhanov Russian University of Economics, Moscow, Russian Federation; Mayorova E., Plekhanov Russian University of Economics, Moscow, Russian Federation; Nikishin A., Plekhanov Russian University of Economics, Moscow, Russian Federation; Vovk A.M., Plekhanov Russian University of Economics, Moscow, Russian Federation","The article deals with topical issues of legal support for the development of electronic commerce in the Russian Federation. The analysis of the main categories of e-commerce has been carried out, the content of which is standardized in domestic regulatory legal acts, the following is among them: elements of the purchase and sale process, the concept of types of trading activities, electronic signature, digital assets, digital currency, smart contracts, digital transactions, etc.). The categories have been defined, the concept of which is absent in the normative legal acts of Russia: the concept of digital goods, e-commerce infrastructure, e-commerce services, delivery channels in online stores, the concept of a courier/courier service, the concept of smart applications, the definition of varieties of online stores, etc. The problem of research is defined: insufficiently effective legal support of economic activity in electronic commerce. An imperfect system of planning strategies for the development of trade organizations in the online environment has been revealed. The conclusions have been formed that the process of digitalization and the consequences of the pandemic have a significant impact on the dynamics of legal support for the development of electronic commerce, but its level is currently not high enough and requires improvement (by making additions to several regulatory legal acts, such as the Law on Trade, the Strategy for the Development of Electronic Commerce in Russia, etc.). The study used system, situational, complex methods, graphical, block grouping, methods of comparative analysis of normative legal acts, and synthesis of conclusions and proposals © 2022. International Journal of Advanced Computer Science and Applications.All Rights Reserved","Delivery channels; Development; Digital product; Digitalization; Electronic commerce; Informatization; Legal support; Online stores; Russian federation; Strategy","Laws and legislation; Planning; Delivery channels; Development; Digital products; Digitalization; E- commerces; Informatization; Legal supports; Online store; Russian federation; Strategy; Electronic commerce",{"$nulls":4},"Ministry of Education and Science of the Russian Federation, Minobrnauka, (FSSW-2020-0009)","ACKNOWLEDGMENT The research was carried out within the framework of the state task of the Ministry of Science and Higher Education of the Russian Federation FSSW-2020-0009 \"Development of a methodology for managing the competitiveness of enterprises in the field of commodity circulation in the digital economy\".","Gulomrizoi G., Pravovye izderzhki ispolneniya zakona ob elektronnoi torgovle v islamskoi respublike Iran [Legal costs of enforcing the law on electronic commerce in the Islamic Republic of Iran], Vestnik Tadzhikskogo natsionalnogo universiteta, 3-6, pp. 97-99, (2013); Belyavskaya Yu. 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E., Legislative aspects of the strategic development of the regions of Kazakhstan [Zakonodatelnye aspekty strategicheskogo razvitiya regionov Kazakhstana], Proceedings of the Sixth International Scientific and Practical Conference \"Problems and Prospects for the Development of Economics and Management in Russia and Abroad\" [Sbornik trudov Shestoi mezhdunarodnoi nauchno-prakticheskoi konferentsii \"Problemy i perspektivy razvitiya ekonomiki i menedzhmenta v Rossii i za rubezhom\"], pp. 301-311, (2014); Kandybko N. V., Denisov D. B., Petroshenko A. I., Legal aspects of the use of electronic commerce technologies in public procurement to ensure defense [Pravovye aspekty primeneniya tekhnologii elektronnoi torgovli v gosudarstvennykh zakupkakh dlya obespecheniya oborony], Vestnik voennogo prava, 1, pp. 51-58, (2021); Makarevich M. L., Rudneva T. 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Yu., Modern trends in the development of markets of goods and services No. 7, Article in the open archive, 7, (2020); President of the Russian Federation, Decree of the President of the Russian Federation of December 5, 2016 No. 646 \"On the approval of the Information Security Doctrine of the Russian Federation, (2016); President of the Russian Federation, Decree of the President of the Russian Federation of May 9, 2017 No. 203 \"On the Strategy for the development of the information society in the Russian Federation for 2017-2030, (2017); Central Bank of the Russian Federation, Remote identification, (2021); Federal Law (draft) of March 20, 2018 No. 419059-7 \"On digital financial assets, (2018); State Duma of the Federal Assembly of the Russian Federation, Federal Law of July 31, 2020 No. 259-FZ \"On digital financial assets, digital currency and on Amendments to Certain Legislative Acts of the Russian Federation, Sobranie Zakonodatel’stva Rossiiskoi Federatsii [SZ RF] [Collection of Legislation of the RF], 31; State Duma of the Federal Assembly of the Russian Federation, Federal Law of July 7, 2003 No. 126-FZ (as amended on June 6, 2019) \"On communications, Sobranie Zakonodatel’stva Rossiiskoi Federatsii [SZ RF] [Collection of Legislation of the RF]",null,null,"Science and Information Organization",{"$nulls":5},"2158107X",null,null,null,"English","Intl. J. Adv.  Comput. Sci. Appl.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85131395309"]
["Bottani E.; Tebaldi L.; Rossi M.; Casella G.","Bottani, Eleonora (14035135900); Tebaldi, Letizia (57204497688); Rossi, Mariachiara (57220834981); Casella, Giorgia (57197832906)","14035135900; 57204497688; 57220834981; 57197832906","A simulation study on how to optimally store products in a warehouse of a fashion supply chain selling through an e-commerce channel",2022.0,"International Journal of Simulation and Process Modelling",18.0,2.0,null,89.0,100.0,11.0,2.0,"10.1504/ijspm.2022.126100","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85140853330&doi=10.1504%2fijspm.2022.126100&partnerID=40&md5=0e530763d5894f0d9d2161a830a43f58","Department of Engineering and Architecture, University of Parma, Parco Area delle Scienze, 181/A, Parma, 43124, Italy","Bottani E., Department of Engineering and Architecture, University of Parma, Parco Area delle Scienze, 181/A, Parma, 43124, Italy; Tebaldi L., Department of Engineering and Architecture, University of Parma, Parco Area delle Scienze, 181/A, Parma, 43124, Italy; Rossi M., Department of Engineering and Architecture, University of Parma, Parco Area delle Scienze, 181/A, Parma, 43124, Italy; Casella G., Department of Engineering and Architecture, University of Parma, Parco Area delle Scienze, 181/A, Parma, 43124, Italy","Where is it convenient the most to allocate a determined product? This paper, by means of a simulation tool, makes an attempt to answer this question, for the specific case of an e-commerce warehouse in which fashion items are stored. According to the typical steps of the Deming cycle, after having studied the current situation (AS IS scenario) of items allocation, a simulated one (TO BE scenario) was developed for studying a new allocation strategy, and for its assessment four key performance indicators were considered: the storage and picking productivity (both expressed in terms of processed units per hour), the % of FIFO batch for multi-customer orders and the time spent for batching (measured in hours). Results from the implementation show an improvement of the KPIs under investigation, as well as the observation of the specific targets set, and consequently an optimisation of picking activities. Copyright © 2022 Inderscience Enterprises Ltd.","case study; e-commerce; fashion supply chain; logistics; PDCA; picking optimisation; product allocation optimisation; simulation; warehouse optimisation","Benchmarking; Electronic commerce; Warehouses; Allocation optimization; Case-studies; E- commerces; Fashion supply chain; Optimisations; PDCA; Picking optimization; Product allocation optimization; Product allocations; Simulation; Warehouse optimisation; Supply chains",{"$nulls":6},"Absaitovna E.M., Jamshedovna M.D., Features of online marketing in the field of retail, Journal of Critical Reviews, 7, 5, pp. 325-326, (2020); Balasoui A.E., Unfair competition in online commerce, Romanian Economic Business Review, 10, 2, pp. 39-47, (2015); Bao J., Geng X., Yu P., Research on the construction of e-commerce credit system based on blockchain, ICMTMA 2020, Proceedings of the 12th International Conference on Measuring Technology and Mechatronics Automation, pp. 776-669, (2020); Bashir R., Gaur B., Kumar Sharma B., An analytical view of the moderating effect of gender on online purchase behavior, International Journal on Emerging Technologies, 11, 1, pp. 324-328, (2020); Becerril A., Cybersecurity and e-commerce in free trade agreements, Mexican Law Review, 13, 1, pp. 3-29, (2021); Bottani E., Ferretti G., Montanari R., Rinaldi M., Analysis and optimization of inventory management policies for perishable food products: a simulation study, International Journal of Simulation and Process Modelling, 9, 1–2, pp. 16-32, (2014); Carpio C.E., Lange K.Y., Trends in e-commerce for the food marketing system, CAB Reviews: Perspectives in Agriculture, Veterinary Science, Nutrition and Natural Resources, 10, 23, pp. 1-8, (2015); Clement J., E-commerce Worldwide – Statistics & Facts, (2020); Das D., Kumar R., Rajak M.K., Designing a reverse logistics network for an e-commerce firm: a case study, Operations and Supply Chain Management, 13, 1, pp. 48-63, (2020); De Koster R., Le-Duc T., Roodbergen J., Design and control of warehouse order picking: a literature review, European Journal of Operational Research, 182, 2, pp. 481-501, (2007); Delfmann W., Albers S., Gehring M., The impact of electronic commerce on logistics service providers, International Journal of Physical Distribution & Logistisc Management, 32, 3, pp. 203-222, (2002); Dirgantari P.D., Hidayat Y.M., Mahphoth M.H., Nugraheni R., Level of use and satisfaction of e-commerce customers in Covid-19 pandemic period: an information system success model (ISSM) approach, Indonesian Journal of Science & Technology, 5, 2, pp. 261-270, (2020); Donati L., Iotti E., Mordonini G., Prati A., Fashion product classification through deep learning and computer vision, Applied Sciences, 9, 7, (2019); E-commerce Statistics for Individuals, (2020); Ferrao A.M., Alturas B., The online purchasing decision process and consumer loyalty of fashion industry products: influence of social media and “opinion makers, CISTI 2018, 13th Iberian Conference on Information Systems and Technologies, pp. 1-6, (2018); Gonzalez Briones A., Chamoso P., Lopez Barriuso A., Review of the main security problems with multi-agent systems used in e-commerce applications, Advances in Distributed Computing and Artificial Intelligence Journal, 5, 3, (2016); Guercini S., Mir Bernal P., Prentice C., New marketing in fashion e-commerce, Journal of Global Fashion Marketing, 9, 1, pp. 1-8, (2018); Guigoures R., Ho Y.K., Koriagin E., Sheik A.S., Bergmann U., Shirvany R., A hierarchical bayesian model for size recommendation in fashion, RecSys 2018, Proceedings of the 12th ACM Conference on Recommender Systems, (2018); Harrison J.R., Lin Z., Carroll G.R., Carley K.M., Simulation modeling in organizational and management research, Academy of Management Review, 32, 4, pp. 1229-1245, (2007); Hu X., Feng S., Liu J., Yang A., Wang G., Xu H., Return model selection and pricing strategy for a dual-channel retailer, Discrete Dynamics in Nature and Society, 2020, pp. 1-20, (2020); Huang S-L., Chang Y-C., Cross-border e-commerce: consumers’ intention to shop on foreign websites, Internet Research, 29, 6, pp. 1256-1279, (2019); Johnson C.N., The benefits of PDCA, Quality Progress, 35, 5, (2002); Khrais L.T., Investigation use of social media, mobile apps, and the impacts of enlarging e-commerce, ICACCS 2020: 6th International Conference on Advanced Computing and Communication Systems, pp. 1365-1372, (2020); 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A structural equation model for cross-border online purchasing behavior, The International Review of Retail, Distribution and Consumer Research, 30, 1, pp. 46-67, (2019); Sheik A-S., Guigoures R., Koriagin E., Ho Y.K., Shirvany R., Vollgraf R., Bergmann U., A deep learning system for predicting size and fit in fashion e-commerce, RecSys 2019, Proceedings of the 13th ACM Conference on Recommender Systems, (2019); Sun P., Veelenturf L.P., Hewitt M., Van Woensell T., Adaptive large neighborhood search for the time-dependent profitable pickup and delivery problem with time windows, Transportation Research Part E: Logistics and Transportation Review, 138, (2020); Tebaldi L., Murino T., Bottani E., An adapted version of the water wave optimization algorithm for the vehicle routing problem with time windows with application to a real case using probe data, Sustainability, 12, 9, (2020); Tian Y., Steward C., History of e-commerce, Encyclopedia of E-Commerce, E-Government, and Mobile Commerce, 2, (2006); Tran L-T., Managing the effectiveness of e-commerce platforms in a pandemic, Journal of Retailing and Consumer Services, 58, 7–8, (2021); Van Asch T., Dewful W., Kupfer F., Cardenas I., Van de Voorde E., Cross-border e-commerce logistics – strategic success factors for airports, Research in Transportation Economics, 79, (2020); Van der Gaast J.P., de Koster R.B.M., Adan I.J.B.F, Optimizing product allocation in a polling-based milkrun picking system, IISE Transactions, 51, 5, pp. 486-500, (2019); Vieira A.A.C., Dias L.M.S., Pereira G.A.B., Oliveira J.A., Do Sameiro Carvalho M., Martins P., Simulation model generation for warehouse management: case study to test different storage strategies, International Journal of Simulation and Process Modelling, 13, 4, pp. 324-336, (2018); Wang Q., Zhao J., Ma L., Modelling and implementation of an intelligent stowage simulator for container ships, International Journal of Simulation and Process Modelling, 15, 3, pp. 201-212, (2020); Wardhani A.K., Identifying consumer review through web design and online advertisement in online shop, International Journal of Data and Network Science, 4, 3, pp. 289-296, (2020); Weinstein A.T., Business models for the now economy, Journal of Business Strategies, (2020); Xie C., Xiao X., Design and implementation of rural e-commerce operation system based on web technology, Journal of Physics, Conference Series, 1533, (2020); Xue L., Parker C.J., Hart C., How to design fashion retail’s virtual reality platforms, International Journal of Retail & Distribution Management, 48, 10, pp. 1057-1076, (2020); Yang P., Zhao Z., Guo H., Order batch picking optimization under different storage scenarios for e-commerce warehouses, Transportation Research Part E: Logistics and Transportation Review, 136, 14, (2020); Yu Y., Yu C., Xu G., Zhong R.Y., Huang G.Q., An operation synchronization model for distribution center in e-commerce logistics service, Advanced Engineering Informatics, 43, (2020); Zou Y., Zhang D., Qi M., Order picking system optimization based on picker-robot collaboration, ACM International Conference, Proceeding Series, pp. 1-6, (2019)","E. Bottani; Department of Engineering and Architecture, University of Parma, Parma, Parco Area delle Scienze, 181/A, 43124, Italy; email: eleonora.bottani@unipr.it",null,"Inderscience Publishers",{"$nulls":5},1.7402123E7,null,null,null,"English","Int. J. Simul. Process Model.","Article","Final",null,"Scopus","2-s2.0-85140853330"]
["Cao C.; Huang S.","Cao, Cong (57468352500); Huang, Shanshan (58031016100)","57468352500; 58031016100","How Can SMEs Boost Trust Through Third-Party Means? Tracing the Multi-Dimensional Institutional Basis of Online Trust",2022.0,"IEEE Access",10.0,null,null,127149.0,127167.0,18.0,1.0,"10.1109/ACCESS.2022.3226889","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85144776013&doi=10.1109%2fACCESS.2022.3226889&partnerID=40&md5=6fa3afbe9c9dc6e9e8ebfdf7e0913ba9","Zhejiang University of Technology, School of Management, Hangzhou, Zhejiang, 310023, China","Cao C., Zhejiang University of Technology, School of Management, Hangzhou, Zhejiang, 310023, China; Huang S., Zhejiang University of Technology, School of Management, Hangzhou, Zhejiang, 310023, China","Consumers are reluctant to engage in e-commerce, due in part, to a lack of trust in the e-merchants, in the e-commerce technology and in the business process. Few prior studies investigating consumers' trust behaviour in relation to e-retailers have addressed different combinations of third-party services and third-party platforms. However, the importance of both of these to the cross-border e-commerce market is self-evident. This paper aims to explore the development of institutional trust in platforms based on the level of the third-party services provided and ultimately, to develop a complete study of online transaction intentions as driven by the platform institutions. An online survey was conducted to collect the data, and 445 respondents completed and returned the questionnaire. Based on the structure of the data, partial least squares structural equation modelling was used to assess the effects of specific factors on institutional trust and on initial trust. Preliminary findings suggest that third-party logistics, payments and certification significantly enhance consumers' trust in an online platform system and in turn, their trust in the e-retailers. Furthermore, the perceived usefulness of a platform and the trustworthiness of word-of-mouth comment can both significantly influence online trust. The study builds an extended online trust model to explore in greater detail. On the one hand, the model will enable platform management to understand users' demands for third-party services better and so improve the platform system. On the other hand, the model can help e-retailers to form a comprehensive understanding of the third-party platform system, and it can guide them in making use of a platform to improve their sales performance.  © 2013 IEEE.","E-commerce; e-WOM; institution-based trust; online trust; SMEs; third party; trust transfer theory","Biological systems; Electronic commerce; Least squares approximations; Outsourcing; Biological system modeling; E-WOM; Institution-based trusts; Online trust; Quality assessment; SME; Third parties; Trust management; Trust transfer; Trust transfer theory; Uncertainty; Sales",{"$nulls":6},{"$cut":{"chars":22824,"head":"Al-Omoush K.S., Ribeiro-Navarrete S., Lassala C., Skare M., Networking and knowledge creation: Social capital and collaborative innovation in responding to the COVID-19 crisis, J. Innov. Knowl, 7, 2; Hilmersson F.P., Hilmersson M., Networking to accelerate the pace of SME innovations, J. Innov. Knowl, 6, 1, pp. 43-49; Li L., Su F., Zhang W., Mao J.-Y., Digital transformation by SME entrepreneurs: A capability perspective, Inf. Syst. J, 28, 6, pp. 1129-1157, (2018); Zhang F., Yang Y., Trust model simulation of cross border e-commerce based on machine learning and Bayesian network, J. Ambi-ent Intell. Humanized Comput, 2021, 2021, pp. 1-11; Salam A.F., Iyer L., Palvia P., Singh R., Trust in e-commerce, Commun ACM, 48, 2, pp. 72-77, (2005); Yang Y., Research on the optimization of the supplier intelligent management system for cross-border e-commerce platforms based on machine learning, Inf. Syst. E-Bus. Manage, 18, 4, pp. 851-870, (2020); Liu G., Yang Q., Wang H., Lin X., Wittie M.P., Assessment of multihop interpersonal trust in social networks by three-valued subjective logic, Proc. IEEE Conf. Comput. Commun., Toronto, ON, Canada, pp. 1698-1706, (2014); Irissappane A.A., Zhang J., A case-based reasoning framework to choose trust models for different E-marketplace environments, J. Artif. Intell. Res, 52, pp. 477-505, (2015); Mavlanova T., Benbunan-Fich R., Lang G., The role of external and internal signals in e-commerce, Decis. Support Syst, 87, pp. 59-68, (2016); Zhang P., Ge Y., Lee H.-M., E-WOM's impact on app development, J. Comput. Inf. Syst, 60, 5, pp. 418-427, (2020); Bakar Z.A., Sazili S.M., Zaini M.K., Ali J., Information elements of a website that promotes trust in e-commerce, Proc. Int. Conf. User Sci. Eng, pp. 55-58, (2010); Yadav R., Bhatnagar S., Channel collaboration in e-commerce: A study on channel relationship from the perspective of vendors selling on online platforms, the e-retailers, Transforming Organizations Through Flexible Systems Management, pp. 223-241, (2020); Brengman M., Karimov F.P., The effect of web communities on consumers' initial trust in B2C e-commerce websites, Manage. Res. Rev, 35, 9, pp. 791-817, (2012); Pan X., Wang H., You W., Zhang M., Yang Y., Assessing the reliability of electronic products using customer knowledge discovery, Rel. Eng. Syst. Saf, 199, (2020); Tsai J.C.-A., Hung S.-Y., Examination of community identification and interpersonal trust on continuous use intention: Evidence from experienced online community members, Inf. Manage, 56, 4, pp. 552-569, (2019); Pawar S.S., Yalla P., Trust-based quality awareness using combinatorial auction web service selection in service-based systems, Int. J. Adv. Intell. Paradigms, 14, 3-4, pp. 297-309, (2019); Ejdys J., Gulc A., Trust in courier services and its antecedents as a determinant of perceived service quality and future intention to use courier service, Sustainability, 12, 21, (2020); Salo J., Karjaluoto H., A conceptual model of trust in the online environment, Online Inf. Rev, 31, 5, pp. 604-621, (2007); McKnight D.H., Chervany N.L., What trust means in e-commerce customer relationships: An interdisciplinary conceptual typology, Int. J. Electron. Commerce, 6, 2, pp. 35-59, (2001); Shek S.P.W., Sia C.-L., Lim K.H., A preliminary assessment of different trust formation models: The effect of third party endorsements on online shopping, Proc. 36th Annu. Hawaii Int. Conf. Syst. Sci, (2003); Baah-Peprah P., Shneor R., A trust-based crowdfunding campaign marketing framework: Theoretical underpinnings and big-data analytics practice, Int. J. Big Data Manage, 2, 1, pp. 1-24; Briggs P., Simpson B., De Angeli A., Personalisation and trust: A reciprocal relationship?, Designing Personalized User Experiences ECommerce, pp. 39-55, (2004); Durkan P., Durkin M., Gillen J., Exploring efforts to engender online trust, Int. J. Entrepreneurial Behav. Res, 9, 3, pp. 93-110, (2003); Lim K.H., Sia C.L., Lee M.K.O., Benbasat I., Do i trust you online, and if so, will i buy? An empirical study of two trust-building strategies, J. Manage. Inf. Syst"}},"C. Cao; Zhejiang University of Technology, School of Management, Zhejiang, Hangzhou, 310023, China; email: congcao@zjut.edu.cn",null,"Institute of Electrical and Electronics Engineers Inc.",{"$nulls":5},2.1693536E7,null,null,null,"English","IEEE Access","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85144776013"]
["Mei M.","Mei, Mei (57773546600)",5.77735466E10,"Research on real-time acquisition method of logistics location information of electric commerce based on ranking threshold",2022.0,"International Journal of Information Technology and Management",21.0,"2024-03-02",null,215.0,232.0,17.0,0.0,"10.1504/IJITM.2022.123402","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85133211586&doi=10.1504%2fIJITM.2022.123402&partnerID=40&md5=7e6a5d57fa75c6fd2a3d934963c1d073","Department of Finance and Economics, Nanchong Vocational and Technical College, Nan Chong, 637000, China","Mei M., Department of Finance and Economics, Nanchong Vocational and Technical College, Nan Chong, 637000, China","In order to overcome the problems of high energy consumption, poor real-time performance and low quality in current methods of collecting positioning information of e-commerce logistics, this paper proposes a real-time method of collecting positioning information of e-commerce logistics based on ranking threshold. By adjusting the mechanism of sensor nodes, the deployment of information acquisition nodes is realised. Redundant data in e-commerce logistics positioning information is removed by comparator, and sorting threshold method is introduced. The real-time collection of e-commerce logistics positioning information is completed by classifying and processing e-commerce logistics positioning information with mixed features. The experimental results show that the energy consumption factor of the proposed method is less than 1.8, the information transmission delay is less than 0.2, and the user satisfaction is more than 90%. It proves that the proposed method is more effective and robust. © 2022 Inderscience Enterprises Ltd.. All rights reserved.","e-commerce logistics positioning information; information collection; redundant data; sorting threshold","Classification (of information); Electronic commerce; Energy utilization; Sensor nodes; E- commerces; E-commerce logistic positioning information; High energy consumption; Information collections; Location information; Positioning information; Real time acquisition; Real time performance; Redundant data; Sorting threshold; Sorting",{"$nulls":6},"Alomar M., Cox A.M., Scholars' research-related personal information collections, Aslib Journal of Information Management, 68, 3, pp. 155-173, (2016); Anagnostopoulos C., Intelligent contextual information collection in internet of things, International Journal of Wireless Information Networks, 23, 2, pp. 1-12, (2016); Chen L., Cai S., Li B., Et al., A novel signal acquisition platform of human cardiovascular information with noninvasive method, Review of Scientific Instruments, 88, 8, pp. 658-245, (2017); Chen S., Gan M., Guo Q., The influence of online storage products information visualization on e-commerce logistics efficiency, China Business and Market, 31, 2, pp. 41-48, (2017); Deng Y.J., Li M., Yu Q., Et al., Logistics distribution route optimization and charging navigation of electric vehicle based on real-time information sensing, Southern Power System Technology, 11, 2, pp. 41-49, (2017); Fattahi M., Govindan K., Integrated forward/reverse logistics network design under uncertainty with pricing for collection of used products, Annals of Operations Research, 253, 2, pp. 193-225, (2017); Fu Y.B., Hu H., Zhang F.Q., Et al., Research on real-time status of monitoring supply chain logistics, Railway Transport and Economy, 39, 3, pp. 36-41, (2017); Kim R., Choi J., Lim H., Channel-aware repetitive data collection in wireless sensor networks, International Journal of Communication Systems, 30, 2, pp. 1375-1383, (2017); Lo C.C., Kuo Y.H., Traffic-aware routing protocol with cooperative coverage-oriented information collection method for VANET, IET Communications, 11, 1, pp. 444-450, (2017); Lo C.C., Kuo Y.H., Traffic-aware routing protocol with cooperative coverage-oriented information collection method for VANET, IET Communications, 11, 7, pp. 444-450, (2017); Lv W.J., Huo S.R., Qiao Y.N., Research and application of grid integration system for power energy metering and acquisition, Journal of China Academy of Electronics and Information Technology, 13, 8, pp. 103-108, (2018); Martin R., Aler R., Galvan I.M., A filter attribute selection method based on local reliable information, Applied Intelligence, 48, 1, pp. 35-45, (2018); Qin J., Jin L.S., Mesiar R., Et al., Eliciting different lattice dominance points to evaluate distribution information, IEEE Transactions on Fuzzy Systems, 17, 1, (2018); Ren Q.Q., Sun B.B., Liu Y., Et al., A circular structure based information collection algorithm in wireless sensor networks, Journal of Beijing University of Posts and Telecommunications, 39, 3, pp. 58-62, (2016); Wang J., Jiang C., Zhu H., Et al., Internet of vehicles: sensing-aided transportation information collection and diffusion, IEEE Transactions on Vehicular Technology, 67, 1, pp. 3813-3825, (2018); Wang Y., Sun F., Jia M., Online monitoring method for multiple operating batch processes based on local collection standardization and multi-model dynamic PCA, Canadian Journal of Chemical Engineering, 94, 8, pp. 1965-1976, (2016); Xin X., Liu X., Li K., Et al., Minimal perfect hashing-based information collection protocol for RFID systems, IEEE Transactions on Mobile Computing, 29, 2, (2017); Zhang H.L., Chen L., Tang Y., Et al., Design of remote emergency channel platform for electric information acquisition system, Electric Power, 51, 5, pp. 113-120, (2018); Zhang Q., Zheng H., Lan J., Et al., An autonomous information collection and dissemination model for large-scale urban road networks, IEEE Transactions on Intelligent Transportation Systems, 17, 5, pp. 1085-1095, (2016); Zhang Y.L., Wu Z.T., Zhang Z.G., Design and experimental research of GPS information acquisition system based on virtual instrument technology, Jiangsu Agricultural Sciences, 44, 4, pp. 415-418, (2016); Zhang M., Gong S.P., Huo X.H., Et al., Research and application of automatic transmission line for electricity information collection terminal, Automation & Instrumentation, 36, 7, pp. 157-159, (2017); Zhang S.H., Vast web hanging code information acquisition method simulation automatically, Computer Simulation, 34, 1, pp. 280-283, (2017); Zhu Z.Y., Chen Z.Q., Modeling of intelligent e-commerce logistics service system based on object-oriented time Petri nets, CAAI Transactions on Intelligent Systems, 13, 6, pp. 303-313, (2018)","M. Mei; Department of Finance and Economics, Nanchong Vocational and Technical College, Nan Chong, 637000, China; email: 201910019@36haojie.com",null,"Inderscience Publishers",{"$nulls":5},1.4614111E7,null,null,null,"English","Int. J. Inf. Technol. Manage.","Article","Final",null,"Scopus","2-s2.0-85133211586"]
["Strickland P.; Williams K.M.","Strickland, Paul (55145738100); Williams, Kim M. (56003909800)","55145738100; 56003909800","The adoption of smart industry 4.0 app technology and harnessing e-WOM in the wine industry caused by a global pandemic: a case study of the Yarra Valley in Australia",2022.0,"Journal of Hospitality and Tourism Insights",{"$nulls":6},2.0,"10.1108/JHTI-05-2022-0175","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137988916&doi=10.1108%2fJHTI-05-2022-0175&partnerID=40&md5=c8c3a1a63efa7e4c66880e1c80b8a34b","Department of Management and Marketing, La Trobe University - Bundoora Campus, Melbourne, Australia; Department of Higher Education, William Angliss Institute of TAFE, Melbourne, Australia","Strickland P., Department of Management and Marketing, La Trobe University - Bundoora Campus, Melbourne, Australia; Williams K.M., Department of Higher Education, William Angliss Institute of TAFE, Melbourne, Australia","Purpose: This exploratory study aims to examine how wine stakeholders' are adopting innovative advancements in smart industry 4.0 application technology (SI4.0AT) coupled with electronic word-of-mouth (e-WOM) techniques to increase winery visitation and wine sales, prior to and during a global pandemic in the Yarra Valley in Victoria, Australia. Design/methodology/approach: A qualitative interpretivist geographical bounded case study approach was used to collect data from fifteen Victorian wine stakeholder's prior to and during the global pandemic COVID-19. A thematic analysis was applied to interpret participant responses and how they viewed, reacted to and harnessed S14.0AT and e-WOM to continue and increase wine sales. Findings: The findings suggest few wine stakeholders' were actively implementing SI4.0AT prior to the global pandemic, COVID -19. With the forced closure of wineries to visitors across Australia, most small to medium-sized wineries immediately changed their business models to concentrate on domestic e-commerce wine sales and home delivery. To support these new business models, e-WOM techniques were quickly adopted or increased whereas other S14.0AT technologies were not, due to financial restraints. Research limitations/implications: The number of participants used in this study is a limitation, however, this can be overcome by replicating this study in other wine regions. This research focused on the wine stakeholders' viewpoint only and may not be easily generalised. Future studies may examine the “what” aspect of SI4.0AT is being used and e-WOM content such as investigating what consumers are saying about these wineries, the method of communication and the motivations for consumers to engage with a winery. Practical implications: The implications for the wine industry and overall results offer insight into the wine stakeholders' perceptions of SI4.0AT and e-WOM and consequent marketing strategy of wineries in the Yarra Valley, Victoria, both pre- and during forced face-to-face winery closures due to a global pandemic. Wineries need to continue to harness and leverage the benefits of e-WOM wine marketing in their marketing strategies and continue to explore the affordability of 4.0 app technology and Tourism 4.0 options. Originality/value: This study is the first attempt at investigating how wine stakeholders' view; react to and harness SI4.0AT and e-WOM through formalised online marketing strategies which should continue to be investigated in the future. © 2022, Emerald Publishing Limited.","4.0 app technol; COVID-19; e-WOM; ogy; SI4.0AT; Victoria; Wine",{"$nulls":7},"Aramendia-Muneta M.E., Olarte-Pascual C., Ollo-Lopez A., Key image attributes to elicit likes and comments on Instagram, Journal of Promotion Management, 29, 1, pp. 50-76, (2021); Bilotta E., Bertacchini F., Gabriele L., Giglio S., Pantano P.S., Romita T., Industry 4.0 technologies in tourism education: nurturing students to think with technology, Journal of Hospitality, Leisure, Sport and Tourism Education, 29, pp. 1-11, (2021); Bodkhe U., Tanwar S., Parekh K., Khanpara P., Tyagi S., Kumar N., Alazb A.N., Blockchain for industry 4.0: a comprehensive review, IEEE Access, 8, pp. 79764-79800, (2020); Bruwer J., Lesschaeve I., Sources of information Used by tourists Travelling to visit Canadian winery tasting rooms, Tourism Planning and Development, 9, 3, pp. 269-289, (2012); Bruwer J., Lockshin L., Saliba A., Hirche M.M., Australian wine industry cellar door research study 2013. Grape and wine research and development corporation: university of South Australia, (2014); Caruana S., Schembri C., The significance of electronic word-of-mouth (e-WOM) content in the shaping of the visitor's perception of quality and value, Successful Social Media and Ecommerce Strategies in the Wine Industry, pp. 103-124, (2016); Chen Y.F., Law R., A review of research on electronic word-of-mouth in hospitality and tourism management, International Journal of Hospitality and Tourism Administration, 17, 4, pp. 347-372, (2016); Chen Y., Weng S.L., Behavioral study of social media followers of a music event: a case study of a Chinese music festival, Journal of Hospitality and Tourism Insights, 4, 2, pp. 163-182, (2021); Chong S., Business process management for SMEs: an exploratory study of implementation factors for the Australian wine industry, Journal of Information Systems and Small Business, 1, 1-2, pp. 41-58, (2007); Cosenza T.R., Solomon M.R., Kwon W.S., Credibility in the blogosphere: a study of measurement and influence of wine blogs as an information source, Journal of Consumer Behaviour, 14, 2, pp. 71-91, (2015); Creswell J.W., Qualitative Enquiry and Research Design: Choosing Among Five Approaches, (2013); Davidow M., The bottom-line Impact of organisational Responses to customer complaints, Journal of Hospitality and Tourism Research, 24, 4, pp. 473-490, (2000); De Angelis M., Guido L., Amatulli C., Electronic word-of-mouth in the service industry: an empirical analysis on sharing economy services, Exploring the Power of Electronic Word-Of-Mouth in the Services Industry, pp. 179-197, (2020); Dean D.L., Forbes S.L., Are customers having e-conversations about your wine? The importance of online discussion forums as electronic word of mouth for wine marketers, Successful Social Media and Ecommerce Strategies in the Wine Industry, pp. 115-132, (2016); Dolan R., Conduit J., Frethey-Bentham C., Fahy J., Goodman S., Social media engagement behaviour, European Journal of Marketing, 53, 10, pp. 2213-2243, (2019); Dubois M., Agnoli L., Cardebat J., Compes R., Faye B., Frick B., Simon-Elorz K., Did wine consumption change during the COVID-19 Lockdown in France, Italy, Spain, and Portugal?, Journal of Wine Economics, 16, 2, pp. 131-168, (2021); Erkan I., Evans C., The influence of eWOM in social media on consumers' purchase intentions: an extended approach to information adoption, Computers in Human Behaviour, 61, pp. 47-55, (2016); Ferrer J., Villanueva E., A managerial survey to discuss wine business models, International Journal of Wine Business Research, 33, 1, pp. 102-117, (2021); Gartner W., Image formation process, Journal of Travel and Tourism Marketing, 2, 2-3, pp. 191-215, (1994); Gillham B., Research Interviewing, (2007); Gopalakrishnan N., Guilherme T., Impact of COVID-19 outbreak on employee performance – Moderating role of industry 4.0 base technologies, International Journal of Production Economics, 234, (2021); Haller C., Hess-Misslin I., Mereaux J.P., Aesthetics and conviviality as key factors in a successful wine tourism experience, International Journal of Wine Business Research, 33, 2, pp. 176-196, (2021); Halliday J., Halliday Wine Companion 2021. The Bestselling and Definitive Guide to Australian Wine, (2020); Hussain S., Guangju W., Jafar R.M.S., Ilyas Z., Mustafa G., Jianzhou Y., Consumers' online information adoption behaviour: motives and antecedents of electronic word of mouth communications, Computers in Human Behaviour, 80, pp. 22-32, (2018); Jalilvand M.R., Esfahani S.S., Samiei N., Electronic word-of-mouth: challenges and opportunities, Procedia Computer Science, 3, pp. 42-46, (2011); Jeong H.J., Koo D.M., Combined effects of valence and attributes of e-WOM on consumer judgment for message and product, Internet Research, 25, 1, pp. 2-29, (2015); Kanje P., Charles G., Tumsifu E., Mossberg L., Andersson T., Customer engagement and eWOM in tourism, Journal of Hospitality and Tourism Insights, 3, 3, pp. 273-289, (2020); Karatepe O.M., Customer complaints and organizational responses: the effects of complainants' perceptions of justice on satisfaction and loyalty, International Journal of Hospitality Management, 25, 1, pp. 69-90, (2006); Lee C.H., Cranage D.A., Toward understanding consumer processing of negative online word-of-mouth communication: the roles of opinion consensus and organizational response strategies, Journal of Hospitality and Tourism Research, 38, 3, pp. 330-360, (2014); Lee K.T., Koo D.M., Effects of attribute and valence of e-WOM on message adoption: moderating roles of subjective knowledge and regulatory focus, Computers in Human Behaviour, 28, 5, pp. 1974-1984, (2012); Line N.D., Hanks L., Dogru T., A reconsideration of the EWOM construct in restaurant research: what are we really measuring?, International Journal of Contemporary Hospitality Management, 32, 11, pp. 3479-3500, (2020); Mukhopadhyay S., Pandey R., Rishi B., Electronic word of mouth (eWOM) research–a comparative bibliometric analysis and future research insight, Journal of Hospitality and Tourism Insights, (2022); Peceny U.S., Urbancic J., Mokorel S., Juralt V., Ilijas T., Tourism 4.0: challenges in marketing a paradigm shift, Consumer Behaviour and Marketing IntekOpen, pp. 1-19, (2019); Pelet J.E., Barton M., Chapuis C., Towards the implementation of digital through wifi and IoT in wine tourism: perspectives from professionals of wine and tourism, Management and Marketing of Wine Tourism Business. Theory Practice and Cases, pp. 207-236, (2018); Ravichandran T., Deng C., Huang D., Effects of managerial response to E-WOM on consumer attitude, Proceedings of the Thirty Sixth International Conference on Information Systems, pp. 1-10, (2015); Reyes-Menendez A., Correia M.B., Matos N., Adap C., Understanding online consumer behaviour and eWOM strategies for sustainable business management in the tourism industry, Sustainability, 12, 21, (2020); Santos S., Caldas F., do Espirito Santo P.M., Augusto L., Oliveira A., Winery word of mouth: the role of brand prestige, brand credibility and wine experience, ICTR 2022 5th International Conference on Tourism Research, (2022); Santos V., Ramos P., Sousa B., Valeri M., Towards a framework for the global wine tourism system, Journal of Organizational Change Management, 35, 2, pp. 348-360, (2022); Schultz F.R., Word of mouth impulses boost wines of Germany: a case study, Successful Social Media and Ecommerce Strategies in the Wine Industry, pp. 55-73, (2016); Senecal S., Nantel J., The influence of online product recommendations on consumers' online choices, Journal of Retailing, 80, 2, pp. 159-169, (2004); Sigala M., Part II, capturing the market: marketing, distribution and promotion, Management and Marketing of Wine Tourism Business. Theory Practice and Cases, pp. 135-138, (2018); Sigala M., Robinson R.N.S., Introduction: the evolution of wine business tourism management, Management and Marketing of Wine Tourism Business. Theory Practice and Cases, pp. 1-21, (2018); Sigala M., Robinson R.N.S., Haller C., The impact of social media on the behaviour of wine tourists: a typology of power sources, Management and Marketing of Wine Tourism Business. Theory Practice and Cases, pp. 139-154, (2018); Sorooshian S., Azizan N.A., Ismail Y., Influence of readiness measures on planning tourism digital shift, Academy of Strategic Management Journal, 20, 2, pp. 1-6, (2021); Spieske A., Birkel H., Improving supply chain resilience through industry 4.0: a systematic literature review under the impressions of the COVID-19 pandemic, Computers and Industrial Engineering, 158, (2021); Strickland P., Innovative wine tourism marketing strategies in the Victorian wine industry: a wine stakeholders' perspective, (2022); Strickland P., Frost W., Williams K.M., Laing J., The acceptance or rejection of social media: a case study of Rochford Winery Estate in Victoria, Australia, Tourism, Culture and Communication, 13, 1, pp. 19-27, (2013); Strickland P., Williams K.M., Laing J., Frost W., The use of social media in the wine event industry: a case study of the high country harvest in Australia, Successful Social Media & Ecommerce Strategies in the Wine Industry, pp. 74-92, (2016); Szolnoki G., Dolan R., Forbes S., Thach L., Goodman S., Using social media for consumer interaction: an international comparison of winery adoption and activity, Wine Economics and Policy, 7, 2, pp. 109-119, (2018); Tracy S.J., Qualitative quality: eight ‘Big-Tent’ criteria for excellent qualitative research, Qualitative Inquiry, 16, 10, pp. 837-851, (2010); Trawnih A., Yaseen H., Al-Adwan A.S., Alsoud R., Jaber O.A., Factors influencing social media adoption among SMES during COVID -19 crisis, Journal of Management Information and Decision Sciences, 24, 6, pp. 1-18, (2021); Veal A.J., Research Methods for Leisure and Tourism: A Practical Guide, (2017); 2017-2021 Victorian wine industry development strategy, (2019); Walters T., Using thematic analysis in tourism research, Tourism Analysis, 21, 1, pp. 107-116, (2016); Williams K.M., Wine tourism: from Winescape to cellardoorscape, Tourism Analysis, 26, 2-3, pp. 245-248, (2021); Yarra Valley, (2020); Facts and figures. Victorian wine industry snapshot, (2020); Wittwer G., Anderson K., COVID-19's impact on Australian wine markets and regions, Agricultural and Resource Economics, 16, 2, pp. 117-130, (2021); Yin R.K., Study Research: Design and Methods, (2017); Gammack J.G., Wine tourism and sustainable development in regional Australia. Global Wine Tourism, Research, Management and Marketing, pp. 59-66, (2006); Jiang Y., Rao Y., Balaji M.S., Xu A.D.X., Travel posts on WeChat moments: a model for eWOM effectiveness, Tourism Analysis, 25, pp. 123-136, (2020); Pucci T., Casprini E., Nosi C., Zanni L., Does social media usage affect online purchasing intention for wine? The moderating role of subjective and objective knowledge, British Food Journal, 121, 2, pp. 275-288, (2019)","P. Strickland; Department of Management and Marketing, La Trobe University - Bundoora Campus, Melbourne, Australia; email: p.strickland@latrobe.edu.au",null,"Emerald Publishing",{"$nulls":5},2.5149792E7,null,null,null,"English","J. Hosp. Tour. Insight.","Article","Article in press",null,"Scopus","2-s2.0-85137988916"]
["Xie W.; Chen C.; Sithipolvanichgul J.","Xie, Wei (58250991800); Chen, Charlie (7501949741); Sithipolvanichgul, Juthamon (57222027366)","58250991800; 7501949741; 57222027366","Understanding e-commerce customer behaviors to use drone delivery services: A privacy calculus view",2022.0,"Cogent Business and Management",9.0,1.0,2102791.0,null,null,null,4.0,"10.1080/23311975.2022.2102791","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135262799&doi=10.1080%2f23311975.2022.2102791&partnerID=40&md5=6f4c620d4856f9e611f400c281bb9cfc","Department of Computer Information Systems and Supply Chain Management, Walker College of Business, Appalachian State University, Boone, NC, United States; Department of Accounting, Thammasat Business School, Thammasat University, Phra Nakhon, Thailand","Xie W., Department of Computer Information Systems and Supply Chain Management, Walker College of Business, Appalachian State University, Boone, NC, United States; Chen C., Department of Accounting, Thammasat Business School, Thammasat University, Phra Nakhon, Thailand; Sithipolvanichgul J., Department of Accounting, Thammasat Business School, Thammasat University, Phra Nakhon, Thailand","Drone delivery is an emerging service at the early adoption stage. It is imperative to understand what it takes for the public to accept such emerging services. This study asks what mechanism influences people’s switching intention in e-commerce drone delivery services. A 7 points Likert scale questionnaire were developed after the two rounds of pretest and a total of 83 surveys were collected from a business school in USA. This study applies privacy calculus theory and technology anxiety in innovation to develop a research model. An empirical survey and structural equation modeling analysis with SmartPLS and a consistent PLS algorithm are used to understand the hedging effect of relative advantages of drone delivery services and technology anxiety on the switching intention of e-commerce consumers. Theoretically, this research adds the e-commence literature, suggesting that people appreciate drone delivery’s speed and environmental protection advantages. However, privacy risk severity and vulnerability are not significant predictors of technology anxiety, negatively impacting switching intention. This study also provided practical contribution to improve the service development of e-commerce company to deliver their products to their customers with the most efficient resources being used. © 2022 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license.","Drone delivery; risk; security; technology anxiety",{"$nulls":7},{"$cut":{"chars":16819,"head":"Abdel Hamid Saleh M., Althonayan A., Alhabib A., Alrasheedi E., Alqahtani G., Customer satisfaction and brand switching intention: A study of mobile services in Saudi Arabia, Expert Journal of Marketing, 3, 2, pp. 62-20, (2015); Agarwal R., Prasad J., The antecedents and consequents of user perceptions in information technology adoption, Decision Support Systems, 22, 1, pp. 15-29, (1998); Al-Jabri I.M., Sohail M.S., Mobile banking adoption: Application of diffusion of innovation theory, Journal of Electronic Commerce Research, 13, 4, pp. 379-391, (2012); Alwateer M., Loke S.W., Emerging drone services: Challenges and societal issues, IEEE Technology and Society Magazine, 39, 3, pp. 47-51, (2020); Anderson C.L., Agarwal R., Practicing safe computing: A multimethod empirical examination of home computer user security behavioral intentions, MIS Quarterly, 34, 3, pp. 613-643, (2010); Arndt A.D., Ford J.B., Babin B.J., Luong V., Collecting samples from online services: How to use screeners to improve data quality, International Journal of Research in Marketing, 39, 1, pp. 117-133, (2022); Austin R., Unmanned aircraft systems: UAVS design, development and deployment, (2011); Bansal H.S., Taylor S.F., St. James Y., “Migrating” to new service providers: Toward a unifying framework of consumers’ switching behaviors, Journal of the Academy of Marketing Science, 33, 1, pp. 96-115, (2005); Berinsky A.J., Margolis M.F., Sances M.W., Separating the shirkers from the workers? Making sure respondents pay attention on self‐administered surveys, American Journal of Political Science, 58, 3, pp. 739-753, (2014); Bishop P., Hines A., Collins T., The current state of scenario development: An overview of techniques, Foresight, (2007); Bolen M.C., From traditional wristwatch to smartwatch: Understanding the relationship between innovation attributes, switching costs and consumers’ switching intention, Technology in Society, 63, (2020); Bordonaba-Juste M., Lucia-Palacios L., Perez-Lopez R., Generational differences in valuing usefulness, privacy and security negative experiences for paying for cloud services, Information Systems and e-Business Management, 18, 1, pp. 35-60, (2020); Borghetti F., Caballini C., Carboni A., Grossato G., Maja R., Barabino B., The use of drones for last-mile delivery: A numerical case study in Milan, Italy, Sustainability, 14, 3, (2022); Byrne B.M., Using multitrait–multimethod analyses in testing for evidence of construct validity, Principles and Methods of Test Construction: Standards and Recent Advances, 3, pp. 288-307, (2016); Cebeci U., Ince O., Turkcan H., Understanding the intention to use Netflix: An extended technology acceptance model approach, International Review of Management and Marketing, 9, 6, (2019); Chen H., Hu Z., Solak S., Improved delivery policies for future drone-based delivery systems, European Journal of Operational Research, 294, 3, pp. 1181-1201, (2021); Chen C., Leon S., Ractham P., Tan A.W.K., Will customers adopt last-mile drone delivery services? An analysis of drone delivery in the emerging market economy, Cogent Business & Management, 9, 1, (2022); Chin W.W., The partial least squares approach to structural equation modeling, Modern Methods for Business Research, 295, 2, pp. 295-336, (1998); Cho H., Li P., Goh Z.H., Privacy risks, emotions, and social media: A coping model of online privacy, ACM Transactions on Computer-Human Interaction (TOCHI), 27, 6, pp. 1-28, (2020); Clarke R., The regulation of civilian drones’ impacts on behavioural privacy, Computer Law & Security Review, 30, 3, pp. 286-305, (2014); Fagan M.H., Neill S., Wooldridge B.R., An empirical investigation into the relationship between computer self-efficacy, anxiety, experience, support and usage, Journal of Computer Information Systems, 44, 2, pp. 95-104, (2004); Falk R.F., Miller N.B., A primer for soft modeling, (1992); Featherman M.S., Hajli N., Self-service technologies and e-services risks in social commerce era, Journal of Business Ethics, 139, 2, pp. 251-269, (2016); Fornell C., Larcker D.F., Structural equatio"}},"J. Sithipolvanichgul; Department of Accounting, Thammasat Business School, Thammasat University, Phra Nakhon, Thailand; email: juthamon@tbs.tu.ac.th",null,"Cogent OA",{"$nulls":5},2.3311975E7,null,null,null,"English","Cogent Bus. Manag.","Article","Final",null,"Scopus","2-s2.0-85135262799"]
["Modgil S.; Dwivedi Y.K.; Rana N.P.; Gupta S.; Kamble S.","Modgil, Sachin (55314774400); Dwivedi, Yogesh K. (35239818900); Rana, Nripendra P. (50262828700); Gupta, Shivam (55851943244); Kamble, Sachin (36864045000)","55314774400; 35239818900; 50262828700; 55851943244; 36864045000","Has Covid-19 accelerated opportunities for digital entrepreneurship? An Indian perspective",2022.0,"Technological Forecasting and Social Change",175.0,null,121415.0,null,null,null,74.0,"10.1016/j.techfore.2021.121415","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85120916952&doi=10.1016%2fj.techfore.2021.121415&partnerID=40&md5=c9148d98cd72a91a70b93bba331c87c0","Department of Operations Management, International Management Institute Kolkata, 2/4 C, Judges Ct Rd, Alipore, Kolkata, 700027, West Bengal, India; School of Management, Swansea University Bay Campus, Swansea, SA1 8EN, United Kingdom; College of Business and Economics Qatar University, P.O. Box 2713, Doha, Qatar; Department of Information Systems Supply Chain Management & Decision Support, NEOMA Business School, 59 Rue Pierre Taittinger, Reims, 51100, France; EDHEC Business School, 24 Avenue Gustave Delory, Roubaix, 59057, France","Modgil S., Department of Operations Management, International Management Institute Kolkata, 2/4 C, Judges Ct Rd, Alipore, Kolkata, 700027, West Bengal, India; Dwivedi Y.K., School of Management, Swansea University Bay Campus, Swansea, SA1 8EN, United Kingdom; Rana N.P., College of Business and Economics Qatar University, P.O. Box 2713, Doha, Qatar; Gupta S., Department of Information Systems Supply Chain Management & Decision Support, NEOMA Business School, 59 Rue Pierre Taittinger, Reims, 51100, France; Kamble S., EDHEC Business School, 24 Avenue Gustave Delory, Roubaix, 59057, France","Covid-19 has challenged many businesses to orient themselves towards digital solutions for their survival. Due to the rising digital wave during Covid-19, there has been a plethora of opportunities for aspiring entrepreneurs to enter the market. Hence, this study focuses on understanding emerging areas and technologies for digital entrepreneurship. This study adopted a qualitative approach with semi-structured interviews through the lens of the diffusion of innovations theory. A total of 23 entrepreneurs responded and presented their views on Covid-19-induced opportunities for digital entrepreneurship. A structured process of open, axial, and selective coding was adopted for the thematic analysis. The study presents a framework based on four promising propositions. Results of the thematic analysis indicate the emergence of digital entrepreneurship opportunities in technology (EdTech, FinTech, cybersecurity), healthcare (diagnostics, virtual care, fitness), entertainment (over the top, gaming, social media), and e-commerce (contactless delivery, payment methods, augmented reality). In this study, entrepreneurs presented their views based on their experience with the platform or technology they operated. To this end, the present study offers implications both for scholars and entrepreneurs working in and aspiring to digital entrepreneurship along with future scope of research. © 2021 The Author(s)","Covid-19; Diffusion of innovations; Digital entrepreneurship; Emerging Technologies","India; Covid-19; Diffusion of innovations; Diffusions of innovation theories; Digital entrepreneurship; Digital solutions; Emerging technologies; Qualitative approach; Semi structured interviews; Thematic analysis; Through the lens; COVID-19; entrepreneur; innovation; Internet; qualitative analysis; technology adoption; Augmented reality",{"$nulls":4},"Emerald South Asia; National Natural Science Foundation of China, NSFC","Shivam Gupta is a Professor at NEOMA Business School, France with a demonstrated history of working in the higher education industry. Skilled in Statistics, Cloud Computing, Big Data Analytics, Artificial Intelligence and Sustainability. Strong education professional with a Doctor of Philosophy (PhD) focused in Cloud Computing and Operations Management from Indian Institute of Technology (IIT) Kanpur. Followed by PhD, postdoctoral research was pursued at Freie Universität Berlin and SUSTech, China. He has completed HDR from University of Montpellier, France. He has published several research papers in reputed journals and has been the recipient of the International Young Scientist Award by the National Natural Science Foundation of China (NSFC) in 2017 and winner of the 2017 Emerald South Asia LIS award. ","Abubakre M., Faik I., Mkansi M., (2021); Algharabat R., Alalwan A.A., Rana N.P., Dwivedi Y.K., Three dimensional product presentation quality antecedents and their consequences for online retailers: the moderating role of virtual product experience, J. Retail. Consum. Serv., 36, pp. 203-217, (2017); Amin K.P., Griffiths M.D., Dsouza D.D., (2020); Bacq S., Geoghegan W., Josefy M., Stevenson R., Williams T.A., The COVID-19 Virtual Idea Blitz: marshaling social entrepreneurship to rapidly respond to urgent grand challenges, Bus. Horiz., 63, 6, pp. 705-723, (2020); Bagcchi S., The world's largest COVID-19 vaccination campaign. The Lancet, Infect. Dis., 21, 3, pp. 322-323, (2021); Bai C., Quayson M., Sarkis J., (2021); Barrett M., Davidson E., Prabhu J., Vargo S.L., Service innovation in the digital age, MIS Q., 39, 1, pp. 135-154, (2015); Bentlage E., Ammar A., How D., Ahmed M., Trabelsi K., Chtourou H., Brach M., Practical recommendations for maintaining active lifestyle during the COVID-19 pandemic: a systematic literature review, Int. J. Environ. Res. Public Health, 17, 17, pp. 1-22, (2020); Brem A., Viardot E., Nylund P.A., (2021); Cao Z., Shi X., A systematic literature review of entrepreneurial ecosystems in advanced and emerging economies, Small Bus. Econ., 57, 1, pp. 75-110, (2021); Carter L., Weerakkody V., Phillips B., Dwivedi Y.K., Citizen adoption of e-government services: exploring citizen perceptions of online services in the United States and United Kingdom, Inf. Syst. Manag., 33, 2, pp. 124-140, (2016); Datta P., Nwankpa J.K., (2021); De R., Pandey N., Pal A., (2020); Dwivedi Y.K., Ismagilova E., Hughes D.L., Carlson J., Filieri R., Jacobson J., Wang Y., (2021); Dwivedi Y.K., Hughes D.L., Coombs C., Constantiou I., Duan Y., Edwards J.S., Upadhyay N., (2020); Elia G., Margherita A., Passiante G., (2020); ET, COVID-19 to Accelerate Digital Adoption in India; Jio helped Spur Internet Usage, (2020); Iivari N., Sharma S., (2020); Islam N., Marinakis Y., Majadillas M.A., Fink M., Walsh S.T., (2020); Jafari-Sadeghi V., Garcia-Perez A., Candelo E., Couturier J., Exploring the impact of digital transformation on technology entrepreneurship and technological market expansion: the role of technology readiness, exploration and exploitation, J. Bus. Res., 124, pp. 100-111, (2021); Janssen M., Rana N.P., Slade E.L., Dwivedi Y.K., Trustworthiness of digital government services: deriving a comprehensive theory through interpretive structural modelling, Public Manag. Rev., 20, 5, pp. 647-671, (2018); Jnr B.A., Use of telemedicine and virtual care for remote treatment in response to COVID-19 pandemic, J. Med. Syst., 44, 7, pp. 1-9, (2020); Johnston L.A., World trade, e-commerce, and COVID-19, China Rev., 21, 2, pp. 65-86, (2021); Kamble S.S., Gunasekaran A., Kumar V., Belhadi A., Foropon C., (2021); Kapoor K., Bigdeli A.Z., Dwivedi Y.K., Schroeder A., Beltagui A., Baines T., A socio-technical view of platform ecosystems: systematic review and research agenda, J. Bus. Res., 128, pp. 94-108, (2021); Kim R.H., Gaukler G.M., Lee C.W., Improving healthcare quality: a technological and managerial innovation perspective, Technol. Forecast. Soc. Change, 113, pp. 373-378, (2016); (2020); Lallie H.S., Shepherd L.A., Nurse J.R., Erola A., Epiphaniou G., Maple C., Bellekens X., (2021); Leech B.L., Asking questions: techniques for semi structured interviews, PS: Polit. Sci. Polit., 35, 4, pp. 665-668, (2002); Liu H., Li X., Wang S., (2021); Madnani D., Fernandes S., Madnani N., Analysing the impact of COVID-19 on over-the-top media platforms in India, Int. J. Pervasive Comput. Commun., 16, 5, pp. 457-475, (2020); Marcati A., Guido G., Peluso A.M., The role of SME entrepreneurs’ innovativeness and personality in the adoption of innovations, Res. Policy, 37, 9, pp. 1579-1590, (2008); McCracken G., The Long Interview (Vol. 13), (1988); (2021); (2019); Munoz P., Naude W., Williams N., Williams T., (2020); Nambisan S., Digital entrepreneurship: toward a digital technology perspective of entrepreneurship, Entrep. Theory Pract., 41, 6, pp. 1029-1055, (2017); Papadopoulos T., Baltas K.N., Balta M.E., The use of digital technologies by small and medium enterprises during COVID-19: implications for theory and practice, Int. J. Inf. Manag., 55, (2020); (2020); Rachul C., Marcon A.R., Collins B., Caulfield T., COVID-19 and ‘immune boosting'on the internet: a content analysis of Google search results, BMJ Open, 10, 10, (2020); Rana N.P., Dwivedi Y.K., Williams M.D., Weerakkody V., Adoption of online public grievance redressal system in India: toward developing a unified view, Comput. Human Behav., 59, pp. 265-282, (2016); Ratten V., Coronavirus (covid-19) and entrepreneurship: changing life and work landscape, J. Small Bus. Entrepreneurship, 32, 5, pp. 503-516, (2020); Rogers E., Diffusion of Innovations, (1962); Rogers E.M., Singhal A., Quinlan M.M., Diffusion of Innovations, pp. 432-448, (2014); Rogers E.M., Diffusion of Innovations, (1995); Schiavone F., Mancini D., Leone D., Lavorato D., (2021); Secundo G., Gioconda M.E.L.E., (2021); Shareef M.A., Dwivedi Y.K., Wright A., Kumar V., Sharma S.K., Rana N.P., Lockdown and sustainability: an effective model of information and communication technology, Technol. Forecast. Soc. Change, 165, (2021); Sharma S., Singh G., Sharma R., Jones P., Kraus S., Dwivedi Y.K., (2020); Sion G., Smart city big data analytics: urban technological innovations and the cognitive internet of things, Geopolit., Hist. Int. Relat., 11, 2, pp. 69-75, (2019); Song A.K., The digital entrepreneurial ecosystem—a critique and reconfiguration, Small Bus. Econ., 53, 3, pp. 569-590, (2019); Srinivasan A., Venkatraman N., Entrepreneurship in digital platforms: a network-centric view, Strateg. Entrepreneurship J., 12, 1, pp. 54-71, (2018); Subramanian S.V., (2021); Sussan F., Acs Z.J., The digital entrepreneurial ecosystem, Small Bus. Econ., 49, 1, pp. 55-73, (2017); Szalavetz A., Digital transformation–enabling factory economy actors’ entrepreneurial integration in global value chains?, Post-Communist Econ., 32, 6, pp. 771-792, (2020); (2021); Vasenska I., Dimitrov P., Koyundzhiyska-Davidkova B., Krastev V., Durana P., Poulaki I., Financial transactions using FINTECH during the covid-19 crisis in Bulgaria, Risks, 9, 3, pp. 1-28, (2021); Volberda H.W., Khanagha S., Baden-Fuller C., Mihalache O.R., Birkinshaw J., (2021); Wang C., Teo T.S., Dwivedi Y., Janssen M., (2021); Zahra S.A., (2021); Zajicek H., Meyers A., Digital health entrepreneurship, Digital Health, pp. 271-287, (2018)","N.P. Rana; College of Business and Economics Qatar University, Doha, P.O. Box 2713, Qatar; email: nrananp@gmail.com",null,"Elsevier Inc.",{"$nulls":5},401625.0,null,null,null,"English","Technol. Forecast. Soc. Change","Article","Final","All Open Access; Green Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85120916952"]
["Yutia S.N.; Fathiana R.Z.; Fajriyah S.Z.","Yutia, Syifa Nurgaida (57215112323); Fathiana, Rana Zaini (57866544000); Fajriyah, Siti Zahrotul (57865930100)","57215112323; 57866544000; 57865930100","Blockchain-based Smart Contract for Decentralized Marketplace",2022.0,"International Journal on Informatics Visualization",6.0,"2024-02-02",null,475.0,480.0,5.0,2.0,"10.30630/joiv.6.2-2.1121","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85136981096&doi=10.30630%2fjoiv.6.2-2.1121&partnerID=40&md5=9b61ae5969f5b68bd5cb5affb2a6ff2c","Faculty of Information Technology, Telkom Institute of Technology Jakarta, Jakarta, 11710, Indonesia","Yutia S.N., Faculty of Information Technology, Telkom Institute of Technology Jakarta, Jakarta, 11710, Indonesia; Fathiana R.Z., Faculty of Information Technology, Telkom Institute of Technology Jakarta, Jakarta, 11710, Indonesia; Fajriyah S.Z., Faculty of Information Technology, Telkom Institute of Technology Jakarta, Jakarta, 11710, Indonesia","The advance of information technology has a growing influence on one of the most popular social trends: online shopping. The rising popularity of online shopping among the general public, as indicated by the growth in the number of online purchasers each year, has prompted business owners to pursue online ventures. The marketplace is intrinsically tied to online buying activity that connects merchants and customers, allowing customers to search for various goods and services from various providers. However, service failures are vulnerable to centralized market systems that emerge frequently. When the company's services to customers fail to satisfy consumer expectations. A breakdown in purchasing and selling essential services, including product delivery and customer support, is referred to as service failure. As a result, not only does this harm confidence, but it may also cause clients to migrate to an alternative marketplace. The marketplace's competitiveness is based on consumer confidence. The decentralized marketplace can address this security concern. A decentralized marketplace is meant to build a system that does not require the confidence of a third party using blockchain technology and smart contracts that can record all transactions clearly and consistently, allowing them to serve as a single point of truth between distrusting entities. The findings largely support the feasibility of Ethereum Smart Contracts to construct a decentralized marketplace. However, there are some places where further study and development are needed. © 2022, Politeknik Negeri Padang. All rights reserved.","Blockchain; decentralized marketplace; ethereum; service of failure; smart contract",{"$nulls":7},"Sfenrianto S., Wijaya T., Wang G., Assessing the buyer trust and satisfaction factors in the E-marketplace, Journal of Theoretical and Applied Electronic Commerce Research, 13, 2, pp. 43-57, (2018); Hidayanto A. N., Shihab M. R., Trust Transfer and Its Effects on The Continuance Usage of Mobile Service in B2C E-marketplaces Comparing the approaches of small, medium, and large organisations in achieving IT and business alignment View project IT Governance on Higher Education View project, (2017); Staff I., 2018 International Conference on Information Management and Technology (ICIMTech), (2018); Wang W., Chen R., Rui C., Association for Information Systems AIS Electronic Library (AISeL) How to Retain Your Customers: The Impact of Consumer Trust and Commitment in E-marketplaces Recommended Citation How to Retain Your Customers: The Impact of Consumer Trust and Commitment in E-marketplaces; Doong H.-S., Wang H.-C., Shih H.-C., Exploring Loyalty Intention in the Electronic Marketplace, Electronic Markets, 18, 2, pp. 142-149, (2008); Greiner M. E., Wang H., Building consumer-to-consumer trust in E-finance marketplaces: An empirical analysis, International Journal of Electronic Commerce, 15, 2, pp. 105-136, (2010); Safari A., Customers’ international online trust-Insights from focus group interviews, Journal of Theoretical and Applied Electronic Commerce Research, 7, 2, pp. 59-72, (2012); Ling K. C., bin Daud D., Piew T. H., Keoy K. H., Hassan P., Perceived Risk, Perceived Technology, Online Trust for the Online Purchase Intention in Malaysia, International Journal of Business and Management, 6, 6, (2011); Kim M.-S., Ahn J.-H., A Model for Buyer’s Trust in the E-marketplace; Ranganthan V. P., Dantu R., Paul A., Mears P., Morozov K., A decentralized marketplace application on the ethereum blockchain, Proceedings-4th IEEE International Conference on Collaboration and Internet Computing, CIC 2018, pp. 90-97, (2018); Nakamoto S., Bitcoin: A Peer-to-Peer Electronic Cash System; Christidis K., Devetsikiotis M., Blockchains and Smart Contracts for the Internet of Things, IEEE Access, 4, pp. 2292-2303, (2016); Zheng Z., Xie S., Dai H., Chen X., Wang H., An Overview of Blockchain Technology: Architecture, Consensus, and Future Trends, Proceedings-2017 IEEE 6th International Congress on Big Data, BigData Congress 2017, pp. 557-564, (2017); 2019 Joint International Conference on Digital Arts, Media and Technology with ECTI Northern Section Conference on Electrical, Electronics, Computer and Telecommunications Engineering (ECTI DAMT-NCON), (2019); I. C. E. Society, I. of Electrical, and E. Engineers, 2015 IEEE 4th Global Conference on Consumer Electronics (GCCE), (2015); Wang L., Shen X., Li J., Shao J., Yang Y., Cryptographic primitives in blockchains, Journal of Network and Computer Applications, 127, pp. 43-58, (2019); Goi B. M., Siddiqi M. U., Chuah H. T., Computational complexity and implementation aspects of the incremental hash function, IEEE Transactions on Consumer Electronics, 49, 4, pp. 1249-1255, (2003); Tasatanattakool P., Techapanupreeda C., Blockchain: Challenges and applications, International Conference on Information Networking, 2018, pp. 473-475, (2018); Puthal D., Malik N., Mohanty S. P., Kougianos E., Das G., Everything You Wanted to Know about the Blockchain: Its Promise, Components, Processes, and Problems, IEEE Consumer Electronics Magazine, 7, 4, pp. 6-14, (2018); Wust K., Gervais A., Do you need a blockchain?, Proceedings-2018 Crypto Valley Conference on Blockchain Technology, CVCBT 2018, pp. 45-54, (2018); Cachin C., Vukolic M., Blockchain Consensus Protocols in the Wild, (2017); Wang S., Ouyang L., Yuan Y., Ni X., Han X., Wang F. Y., Blockchain-Enabled Smart Contracts: Architecture, Applications, and Future Trends, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 49, 11, pp. 2266-2277, (2019); Nie J.-Y., Institute of Electrical and Electronics Engineers, and IEEE Computer Society, 2017 IEEE International Conference on Big Data: proceedings, (2017)","S.N. Yutia; Faculty of Information Technology, Telkom Institute of Technology Jakarta, Jakarta, 11710, Indonesia; email: syifanurgaida@ittelkom-jkt.ac.id",null,"Politeknik Negeri Padang",{"$nulls":5},2.5499904E7,null,null,null,"English","Int. J. Inform. Vis.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85136981096"]
["Daultani Y.; Cheikhrouhou N.; Pratap S.; Prajapati D.","Daultani, Yash (56677743400); Cheikhrouhou, Naoufel (21833890500); Pratap, Saurabh (56667217800); Prajapati, Dhirendra (57215023349)","56677743400; 21833890500; 56667217800; 57215023349","Forward and Reverse Logistics Network Design with Sustainability for New and Refurbished Products in E-commerce",2022.0,"Operations and Supply Chain Management",15.0,4.0,null,540.0,550.0,10.0,2.0,"10.31387/oscm0580365","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85149949978&doi=10.31387%2foscm0580365&partnerID=40&md5=c3d2f770aef36bbf621b54f8663c09e1","Operations Management Group, Indian Institute of Management Lucknow, India; Geneva School of Business Administration, HES-SO, University of Applied Sciences Western Switzerland, Switzerland; Department of Mechanical Engineering, Indian Institute of Technology (BHU), Varanasi, India; Department of Mechanical Engineering, Indian Institute of Information Technology Jabalpur, India","Daultani Y., Operations Management Group, Indian Institute of Management Lucknow, India; Cheikhrouhou N., Geneva School of Business Administration, HES-SO, University of Applied Sciences Western Switzerland, Switzerland; Pratap S., Department of Mechanical Engineering, Indian Institute of Technology (BHU), Varanasi, India; Prajapati D., Department of Mechanical Engineering, Indian Institute of Information Technology Jabalpur, India","There has been an enormous growth in the availability of refurbished goods in the online marketplace. These days, consumers can buy either the new products or refurbished products based on their budget and individual preferences. As a result, e-commerce firms need to redesign their existing forward and reverse logistics networks while focusing on supply chain sustainability. This paper proposes a novel forward and reverses logistics network design (FRLND) along with a consumer pickup and demand facility within the promised time window while addressing the complexities related to e-commerce platforms, suppliers, manufacturers, third-party logistics providers, retailers, and customer tiers. A mixed-integer non-linear programming (MINLP) model is developed to minimize the overall anticipated cost that consists of costs related to procurement, production, inventory holding, shortages, material for return units, recycling, repairing, disposal, and transportation cost, across the entire supply chain network. The problem under consideration is NP-hard in nature. The special challenges of the problem in consideration are to consider all pickup and distribution nodes of retailers/customers within the range of promising time horizons. For solution purposes, the Block-based Genetic Algorithm, Fruit-fly Algorithm, and CPLEX are used. Computational experiments show the comparative charts and trends that are put on to an extensive range of practical scenarios. The experiments reveal that the Genetic Algorithm performs well than the Fruit Fly algorithm in terms of rate of convergence and solution quality in all cases of interest. CPLEX solution provides the minimum optimal value. © 2022 Operations and Supply Chain Management Forum. All rights reserved.","forward logistics; industry 4.0; logistics; meta-heuristics; multi-modal transportation; refurbished products; reverse logistics; supply chain network design; sustainability",{"$nulls":7},"Afia N., Computers & Industrial Engineering A Stochastic Model for Forward - Reverse Logistics Network Design Under Risk, Computers & Industrial Engineering, 58, 3, pp. 423-431, (2010); Atabaki M. S., Khamseh A. A., Mohammadi M., A Priority-Based Firefly Algorithm for Network Design of A Closed-Loop Supply Chain with Price-Sensitive Demand, Computers & Industrial Engineering, 135, pp. 814-837, (2019); Bowden Z. E., Ragsdale C. T., The General Pickup and Delivery Problem with Backtracking Restrictions, International Journal of Operational Research, 39, 4, pp. 539-561, (2020); Cantillo L. A., Cantillo V., Miranda P. A., Optimisation Approach to Solve the Truck Loading and Delivery Problem at Long Haul Distances with Heterogeneous Products and Fleet, International Journal of Operational Research, 40, 1, pp. 92-116, (2021); Choudhary A., Sarkar S., Settur S., Tiwari M. K., A Carbon Market Sensitive Optimization Model for Integrated Forward-Reverse Logistics, International Journal of Production Economics, 164, pp. 433-444, (2015); Daultani Y., Cheikhrouhou N., Pratap S., Prajapati D., Designing Forward and Reverse Supply Chain Network for Refurbished Products, Proceedings of the 9th International Conference on Operations and Supply Chain Management, pp. 15-18, (2019); Daultani Y., Kumar S., Vaidya O. S., Tiwari M. K., A Supply Chain Network Equilibrium Model for Operational and Opportunism Risk Mitigation, International Journal of Production Research, 53, 18, pp. 5685-5715, (2015); Deb K., Goel T., Controlled Elitist Non-Dominated Sorting Genetic Algorithms for Better Convergence, Evolutionary Multi-Criterion Optimization, pp. 67-81, (2001); Dwivedi A., Jha A., Prajapati D., Sreenu N., Pratap S., Meta-Heuristic Algorithms for Solving the Sustainable Agro-Food Grain Supply Chain Network Design Problem, Modern Supply Chain Research and Applications, pp. 2631-3871, (2020); Gooran A. N., Rafiei H., Rabbani M., Evaluation and Designing Reverse Logistics for Risk-Neutral and Risk-Seeking Decision Makers, International Journal of Operational Research, 39, 1, pp. 24-49, (2020); Govindan K., Fattahi M., Keyvanshokooh E., Supply Chain Network Design Under Uncertainty: A Comprehensive Review and Future Research Directions, European Journal of Operational Research, 263, 1, pp. 108-141, (2017); Goswami M., De A., Habibi M. K. K., Daultani Y., Examining Freight Performance of Third-Party Logistics Providers within the Automotive Industry in India: An Environmental Sustainability Perspective, International Journal of Production Research, 58, 24, pp. 7565-7592, (2020); Goswami M., Daultani Y., Make-in-India and Industry 4.0: technology readiness of select firms, barriers and socio-technical implications, The TQM Journal, (2021); Guo J., Wang X., Fan S., Gen M., Forward and Reverse Logistics Network and Route Planning under the Environment of Low-Carbon Emissions: A Case Study of Shanghai Fresh Food E-commerce Enterprises, Computers & Industrial Engineering, 106, pp. 351-360, (2017); Handaya, Susanto H., Marimin D., Sustainable Agro-industry Logistics Solutions using Spatial Analysis, Operations and Supply Chain Management: An Internatiola Journal, 15, 1, pp. 148-163, (2022); Hardjomidjojo H., Yusianto R., Marimin M., Suprihatin S., Sustainable Agro-industry Logistics Solutions using Spatial Analysis, Operations and Supply Chain Management: An Internatiola Journal, 15, 1, pp. 41-55, (2022); Harms R., Linton J. D., Willingness to Pay for Eco-Certified Refurbished Products: The Effects of Environmental Attitudes and Knowledge, Journal of Industrial Ecology, 20, 4, pp. 893-904, (2016); Islam I., Nielsen M., Schulze-Ehlers B., Badiuzzaman, Exploring Performance Deficits in the Fish Feed Supply Chain of Bangladesh, Operations and Supply Chain Management: An Internatiola Journal, 15, 1, pp. 136-147, (2022); Kannan D., Diabat A., Alrefaei M., Govindan K., Yong G., A Carbon Footprint Based Reverse Logistics Network Design Model, Resources, Conservation and Recycling, 67, pp. 75-79, (2012); McWilliams D., Lennon C., Lowery J., Impact of Experience and Education on Risk Attitude and Risk Perception of Supply Chain Management Professionals, Operations and Supply Chain Management: An International Journal, 15, 1, pp. 56-68, (2022); Mohammadi M., Musa S. N., Omar M. B., Optimisation of Multi-Plant Capacitated Lot-Sizing Problems in An Integrated Supply Chain Network Using Calibrated Metaheuristic Algorithms, International Journal of Operational Research, 39, 3, pp. 325-363, (2020); Nagpal G., Chanda U., Seth H., The First Half-Century of Decision Modelling for Substitutable Products: A Literature Review and Bibliographic Analysis, Operations and Supply Chain Management: An International Journal, 14, 3, pp. 261-276, (2021); Pan Wen-Tsao, A new Fruit Fly Optimization Algorithm: Taking the Financial Distress Model as An Example, Knowledge-based Systems, 26, pp. 69-74, (2012); Pratap S., Manoj Kumar B., Cheikhrouhou N., Tiwari M.K, The Robust Quay Crane Allocation for A Discrete Bulk Material Handling Port, IEEE International Conference Industrial Engineering & Engineering Management, (2016); Ramezani M., Bashiri M., Tavakkoli-Moghaddam R., A New Multi-Objective Stochastic Model for A Forward/Reverse Logistic Network Design with Responsiveness and Quality Level, Applied Mathematical Modelling, 37, 1-2, pp. 328-344, (2013); Rao H. S., Reducing Carbon Emissions from Transport Projects, Evaluation Knowledge Brief, 16, pp. 1-96, (2010); Gen M., Lin L., Yun Y., Inoue H., Recent Advances in Hybrid Priority-based Genetic Algorithms for Logistics and SCM Network Design, Computers & Industrial Engineering, 125, pp. 394-412, (2018); Patidar R., Venkatesh B., Pratap S., Daultani Y., A Sustainable Vehicle Routing Problem for Indian Agri-Food Supply Chain Network Design, International Conference on Production and Operations Management Society (POMS), pp. 1-5, (2018); Prajapati D., Zhou F., Zhang M., Chelladurai H., Pratap S., Sustainable Logistics Network Design for Multi-Products Delivery Operations in B2B E-Commerce Platform, Sādhanā, 46, 2, pp. 1-13, (2021); Prajapati D., Manoj Kumar M., Chelladurai H., Pratap Saurabh, Sustainable Logistics Network Design for Delivery Operations with Time Horizons in B2B E-Commerce Platform, Logistics, 5, pp. 1-12, (2021); Prajapati D., Chan F.T.S., Daultani Y., Pratap S., Sustainable Vehicle Routing of Agro-Food Grains in the E-Commerce Industry, International Journal Of Production Research, pp. 1-27, (2022); Sahu S., Rao N., Barriers to Adoption of Supply Chain Management in India: A Theoretical Model and Scale Development, Operations and Supply Chain Management: An Internatiola Journal, 14, 4, pp. 476-495, (2020); Schipper L., Fabian H., Leather J., Transport and Carbon Dioxide Emissions: Forecasts, Options Analysis, and Evaluation, ADB Sustainable Development Working Paper Series, 9, (2009); Serrano C., Aggoune-Mtalaa W., Sauer N., Dynamic Models for Green Logistic Networks Design, IFAC Proceedings Volumes (IFAC-PapersOnline), 46, 9, pp. 736-741, (2013); Sharma E., Singla J., Sustainable Supply Chain Practices (SSCPs) and Organizational Performance: A Mediating Role of Functional Constructs, Operations and Supply Chain Management: An International Journal, 14, 4, pp. 456-466, (2021); Singh G., Daultani Y., Sahu R., Investigating the barriers to growth in the Indian food processing sector, OPSEARCH, 59, 2, pp. 441-459, (2022); Tanai Yertai, Dechenaux Emmanuel, Patuwo Eddy B., Guiffrida Alfred L., Bargaining in a Closed-Loop Supply Chain With Consumer Returns, International Journal of Operational Research, 41, 2, pp. 168-195, (2021); Zarbakhshnia N., Soleimani H., Goh M., Razavi S. S., A Novel Multi-Objective Model for Green Forward and Reverse Logistics Network Design, Journal of Cleaner Production, 208, pp. 1304-1316, (2018); Zhang M., Pratap S., Huang G. Q., Zhao Z., Optimal Collaborative Transportation Service Trading in B2B E-Commerce Logistics, International Journal of Production Research, 55, 18, pp. 5485-5501, (2017); Zhang M., Fu Yufang, Zhao Z., Pratap S., Huang G. Q., Game theoretic Analysis of Horizontal Carrier Coordination with Revenue Sharing in E-Commerce Logistics, International Journal of Production Research, 57, 5, pp. 1524-1551, (2019); Zhang M., Pratap S., Zhao Z., Prajapati D., Huang G.Q., Forward and Reverse Logistics Vehicle Routing Problems with Time Horizons in B2C E-Commerce Logistics, International Journal of Production Research, pp. 1-20, (2020)","Y. Daultani; Operations Management Group, Indian Institute of Management Lucknow, India; email: yash.daultani@gmail.com",null,"Operations and Supply Chain Management Forum",{"$nulls":5},1.9793561E7,null,null,null,"English","Operations Supply Chain Manag.","Article","Final",null,"Scopus","2-s2.0-85149949978"]
["Ball J.; Zhang J.; Stanley J.; Waa A.; Gurram N.; Edwards R.","Ball, Jude (57050067600); Zhang, Jane (55150047900); Stanley, James (57208096305); Waa, Andrew (12646414900); Gurram, Niveditha (57212032907); Edwards, Richard (7403979498)","57050067600; 55150047900; 57208096305; 12646414900; 57212032907; 7403979498","Has increasing internet use due to smartphone uptake contributed to the decline in adolescent smoking?",2022.0,"Drug and Alcohol Review",41.0,2.0,null,365.0,376.0,11.0,2.0,"10.1111/dar.13378","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85114372655&doi=10.1111%2fdar.13378&partnerID=40&md5=3d8568cd63fb0bd3901df0e54ca3b22d","Department of Public Health, University of Otago, Wellington, New Zealand; Eru Pōmare Māori Health Research Centre, University of Otago, Wellington, New Zealand; Te Hiringa Hauora/Health Promotion Agency, Wellington, New Zealand","Ball J., Department of Public Health, University of Otago, Wellington, New Zealand; Zhang J., Department of Public Health, University of Otago, Wellington, New Zealand; Stanley J., Department of Public Health, University of Otago, Wellington, New Zealand; Waa A., Eru Pōmare Māori Health Research Centre, University of Otago, Wellington, New Zealand; Gurram N., Te Hiringa Hauora/Health Promotion Agency, Wellington, New Zealand; Edwards R., Department of Public Health, University of Otago, Wellington, New Zealand","Introduction: The emergence of low-cost smartphone technology has coincided with major declines in adolescent smoking and other risk behaviours. This study explores the relationship between internet use and smoking in adolescents and investigates whether rising internet use contributed to the decline in smoking between 2012 and 2018. Methods: Data were drawn from a nationally representative New Zealand survey of students aged 14–15 (N = 11 299), conducted biennially between 2012 and 2018. We used logistic regression to explore the association between internet use and smoking and test whether increasing time on the internet was associated with declining adolescent smoking over the study period. Results: The proportion of students spending 5+ hours per day online increased from 15% to 35%. Heavy internet use was not a protective factor for smoking at the individual level. In 2016/2018, some types of past week internet use were associated with decreased risk of smoking (e.g. doing schoolwork, finding out about news), some were associated with increased risk (e.g. social media use) and others appeared to have no association with smoking (e.g. gaming, online shopping). The relative risk of smoking was lower in 2018 relative to 2012 (relative risk 0.68, 95% confidence interval 0.51, 0.90, after adjustment for demographic factors). Adding internet use to the model did not help to account for smoking decline. Discussion and Conclusions: We found no evidence that increasing time spent on the internet during the 2012–2018 period (during which smartphones became ubiquitous) contributed to the decline in adolescent smoking. © 2021 Australasian Professional Society on Alcohol and other Drugs.","adolescent; internet use; prevention; social media; tobacco","Adolescent; Humans; Internet; Internet Use; Smartphone; Smoking; Students; Tobacco Smoking; adolescent; epidemiology; human; Internet; smartphone; smoking; student",{"$nulls":4},"University of Otago","The authors would like to acknowledge the schools and students who participated in the Youth Insights Surveys and thank Te Hiringa Hauroa/Health Promotion Agency for providing access to the data. This research was funded by a University of Otago Research Grant. 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Doctoral thesis, (2019); Pape H., Rossow I., Brunborg G.S., Adolescents drink less: how, who and why? 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Owens P.E., No teens allowed: the exclusion of adolescents from public spaces, Landsc J, 21, pp. 156-163, (2002); ASH year 10 snapshot survey: topline results, (2014); Tucker J.S., Green H.D., Zhou A.J., Miles J.N.V., Shih R.A., D'Amico E.J., Substance use among middle school students: associations with self-rated and peer-nominated popularity, J Adolesc, 34, pp. 513-519, (2011); Sargent J.D., Tanski S., Stoolmiller M., Hanewinkel R., Using sensation seeking to target adolescents for substance use interventions, Addiction, 105, pp. 506-514, (2010)","J. Ball; Department of Public Health, University of Otago, Wellington, New Zealand; email: jude.ball@otago.ac.nz",null,"John Wiley and Sons Inc",{"$nulls":5},9595236.0,null,null,3.4487593E7,"English","Drug Alcohol Rev.","Article","Final",null,"Scopus","2-s2.0-85114372655"]
["Guo H.; Zou T.","Guo, Hongli (57728150100); Zou, Tong (57728900200)","57728150100; 57728900200","Cross-Border E-Commerce Platform Logistics and Supply Chain Network Optimization Based on Deep Learning",2022.0,"Mobile Information Systems",2022.0,null,2203322.0,null,null,null,3.0,"10.1155/2022/2203322","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85131358360&doi=10.1155%2f2022%2f2203322&partnerID=40&md5=7f8be92efa59c62098d6c931c882f5d6","Business School, Shandong Jianzhu University, Shandong, Jinan, 250101, China; School of International Economics and Trade, Shandong University of Finance and Economics, Shandong, Jinan, 250002, China","Guo H., Business School, Shandong Jianzhu University, Shandong, Jinan, 250101, China; Zou T., School of International Economics and Trade, Shandong University of Finance and Economics, Shandong, Jinan, 250002, China","E-commerce and logistics are symbioses with each other, but cross-border e-commerce (CBEC) still cannot break away from cross-border logistics. With the progress of economic internationalization, economic and trade ties around the world have become closer and closer, and the level of international business exchanges has been improved. The rise of multinational e-commerce has also caused unprecedented difficulties to multinational logistics and supply chain management. The application of deep neural networks in various fields provides opportunities for cross-border e-commerce platforms to solve these problems. The existing logistics distribution model cannot keep up with the development of CBEC and has become a constraint and bottleneck for the development of CBEC. Therefore, this article introduces deep learning neural network to cross-border logistics and supply chain based on the analysis of the existing cross-border logistics model and supply chain model and the status quo of e-commerce development. It optimizes the existing cross-border logistics and supply chain network in order to break through the current bottleneck in the development of CBEC. This paper shows through research that introducing deep learning neural networks into CBEC logistics and supply chain can improve the efficiency of logistics and supply chain. Compared with the previous efficiency, the efficiency of network optimization can be increased to about 50%, reducing the cost of cross-border logistics and supply chain. The research in this article has great theoretical and guiding significance for the development of CBEC. © 2022 Hongli Guo and Tong Zou.",null,"Deep neural networks; Efficiency; Supply chain management; Break-away; Commerce platforms; Cross-border; E- commerces; International business; Internationalisation; Learning neural networks; Logistics and supply chain management; Network optimization; Supply chain network; Electronic commerce",{"$nulls":4},"Humanities and Social Science Project of Shandong Province, (2021-YYJJ-29)","This study was supported by the Humanities and Social Science Project of Shandong Province, China (Grant No. 2021-YYJJ-29), project name: “Research on the Development Path of Shandong Cross-Border E-Commerce under the Digital Economy.”","Jiang W., Sha E.H.M., Zhuge Q., Wu L., Efficient assignment algorithms to minimize operation cost for supply chain networks in agile manufacturing, Computers & Industrial Engineering, 108, pp. 225-239, (2017); Alglawe A., Schiffauerova A., Kuzgunkaya O., Shiboub I., Supply chain network design based on cost of quality and quality level analysis, The TQM Journal, 31, 3, pp. 467-490, (2019); Zhang H.W., Man X., Wang Y., Song Q.-S., Stanley D., Hui K.-M., Zhang X.-W., Characterization of a double WAP domain-containing protein from the red swamp crayfish Procambarus clarkii, Fish & Shellfish Immunology, 71, 4, pp. 329-337, (2017); Sun P., Gu L., Optimization of cross-border e-commerce logistics supervision system based on Internet of Things technology, Complexity, 2021, 4, (2021); Ene S., Ozturk N., Multi-objective green supply chain network optimization, Global Journal of Business, Economics and Management: Current Issues, 7, 1, pp. 15-24, (2018); Zheng J., Yang X., Chen Y., Zhao Q., Tian S., Huang H., Xu Y., Onset of bladder and motor symptoms in multiple system atrophy: differences according to phenotype, Clinical Autonomic Research, 27, 2, pp. 103-106, (2017); Yan W., Zhou H., Li H., Decision and coordination of cross-border E-commerce supply chain: based on four modes of cooperation, Scientific Programming, 2021, 33, (2021); Runge M., Growth of CBEC hubs, SupplyChainBrain, 21, 1, (2017); Tang X.-s., Ding Y., Hao K., A novel method based on line-segment visualizations for hyper-parameter optimization in deep networks, International Journal of Pattern Recognition and Artificial Intelligence, 32, 3, (2018); Aghdam M.Y., Tabbakh S.K., Chabok S.M., Khairabadi M., Optimization of air traffic management efficiency based on deep learning enriched by the long short-term memory (LSTM) and extreme learning machine (ELM), Journal of Big Data, 8, 1, pp. 1-26, (2021); Khalilzadeh M., Derikvand H., A multi-objective supplier selection model for green supply chain network under uncertainty, Journal of Modelling in Management, 13, 3, pp. 605-625, (2018); Sajedinejad A., Chaharsooghi S.K., Multi-criteria supplier selection decisions in supply chain networks: a multi-objective optimization approach, Industrial Engineering & Management Systems, 17, 3, pp. 392-406, (2018); Zijm H., Klumpp M., Regattieri A., Heragu S., Operations, logistics and supply chain management, Lecture Notes in Logistics, pp. 593-610, (2019); Fang Z., Wang Q., Cross-border E-commerce supply chain risk evaluation with FUZZY-ISM model, Security and Communication Networks, 2021, 1, (2021); Grover A.S., Syed A.A., Supply Chain Management & E-commerce: A Review, India Quarterly, 22, 4, pp. 5148-5153, (2019); Widyarto W.O., Identification of performance indicators base on logistic capability for supply chain performance measurement in e-commerce, Asia Proceedings of Social Sciences, 4, 2, pp. 53-56, (2019); Zhang X., Sun J., He Y., Empirical research on the influence mechanism of cross-border ecommerce logistics collaboration, Clinica Chimica Acta, 42, 3, pp. 1032-1037, (2017); Yu H., Study on the innovation and mode comparative of E-business supply chain under the background of Cross border trading, Boletin Tecnico/Technical Bulletin, 55, 14, pp. 281-289, (2017); He W., Xu Y., Cross-border electronic commerce development present situation and the innovation research in China, American Journal of Industrial and Business Management, 8, 8, pp. 1825-1842, (2018); Kong X.T., Zhong R.Y., Zhao Z., Shao S., Li M., Lin P., Chen Y., Wu W., Shen L., Yu Y., Huang G.Q., Cyber physical ecommerce logistics system: an implementation case in Hong Kong, Computers & Industrial Engineering, 139, (2020)","T. Zou; School of International Economics and Trade, Shandong University of Finance and Economics, Jinan, Shandong, 250002, China; email: 161849018@masu.edu.cn",null,"Hindawi Limited",{"$nulls":5},"1574017X",null,null,null,"English","Mob. Inf. Sys.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85131358360"]
["Yujie H.; Qiuxia H.","Yujie, Hou (57733866500); Qiuxia, Hao (57733697600)","57733866500; 57733697600","Innovative Mode of Logistics Management of \"internet of Things + Blockchain\"-Integrated E-Commerce Platform",2022.0,"Computational Intelligence and Neuroscience",2022.0,null,7766228.0,null,null,null,0.0,"10.1155/2022/7766228","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85131623164&doi=10.1155%2f2022%2f7766228&partnerID=40&md5=bdc88bf02f667cc4ee2d0840d5f86f11","School of International Business, Qingdao Huanghai University, Shandong, Qingdao, 7266000, China","Yujie H., School of International Business, Qingdao Huanghai University, Shandong, Qingdao, 7266000, China; Qiuxia H., School of International Business, Qingdao Huanghai University, Shandong, Qingdao, 7266000, China","The innovation of logistics management mode plays a great role in promoting the operation timeliness of an e-commerce platform. The question of how to realize the research on the innovation mode of logistics management of the e-commerce platform with the integration of \"Internet of things + blockchain\"is the current development trend. Based on this, this paper studies the influencing factors of logistics management of an e-commerce platform under the discrete analysis strategy of \"Internet of things + blockchain.\"First, the logistics management analysis model of an e-commerce platform integrating \"Internet of things + blockchain\"is proposed. The dynamic correlation function is used to simulate the logistics information in the e-commerce platform. Through the extreme value of the dynamic correlation function curve in the detection process, the operation signal is restored, and then its logistics management is analyzed. Second, the influencing factors in the logistics management of the e-commerce platform are analyzed, comprehensive analysis is done by using the \"Internet of things + blockchain\"integration model, the dynamic logistics information in the operation of the e-commerce platform is accurately gathered, and the multidimensional hierarchical method is used for quality evaluation. Finally, the effectiveness of the logistics management analysis model of the e-commerce platform is verified by many experiments.  © 2022 Hou Yujie and Hao Qiuxia.",null,"Blockchain; Commerce; Internet; Internet of Things; Blockchain; Electronic commerce; Factor analysis; Quality control; 'current; Analysis models; Block-chain; Commerce platforms; Dynamic correlation function; E- commerces; Logistic management; Logistics information; Management analysis; Management modes; commercial phenomena; Internet; Internet of things",{"$nulls":6},"Tang S., Yu F., Zhao Y., Zhou Y., Deng W., Construction and verification of retinal vessel segmentation innovation mode and optimization strategy of B2C E-commerce logistics distribution under big data, Sustainability, 12, (2020); Pollak F., Konen M., Eulovs D., Innovations in the management of E-commerce: Analysis of customer interactions during the COVID-19 pandemic, Sustainability, 13, (2021); Villa R., Monzon A., A metro-based system as sustainable alternative for urban logistics in the era of E-commerce, Sustainability, 13, (2021); Wang C., Analyzing the effects of cross-border E-commerce industry transfer using big data, Mobile Information Systems, 2021, 8, pp. 1-12, (2021); Xia L., Liu S., Intelligent IoT-based cross-border e-commerce supply chain performance optimization, Wireless Communications and Mobile Computing, 2021, 121, pp. 1-13, (2021); Jiang Y., Lai P., Chang C.H., Yuen K.F., Li S., Wang X., Sustainable management for fresh food E-commerce logistics services, Sustainability, 13, (2021); Sun P., Gu L., Optimization of cross-border e-commerce logistics supervision system based on Internet of things technology, Complexity, 2021, 4, (2021); Dong Z., Construction of mobile E-commerce platform and analysis of its impact on E-commerce logistics customer satisfaction, Complexity, 2021, (2021); Liu Y., Liang S., Ding R., BCG-induced trained immunity in macrophage: Reprograming of glucose metabolism: BCG-induced trained immunity by enhanced glycolysis and glutamine-driven tricarboxylic acid cycle in macrophage, International Reviews of Immunology, 39, 3, pp. 83-96, (2020); De-Ku L.I., The innovation in logistics management in the light of E-commerce, China Business and Market, 87, 18, pp. 529-531, (2013); Gunasekaran A., Sarkis J., Research and applications in e-commerce and third-party logistics management, International Journal of Production Economics, 113, 1, pp. 123-126, (2008); Abuidris Y., Kumar R., Yang T., Secure large-scale E-voting system based on blockchain contract using a hybrid consensus model combined with sharding, ETRI Journal, 43, 2, (2021); Lee S., Kim M., Lee J., Hsu R.H., Quek T.Q., Is blockchain suitable for data freshness? An age-of-information perspective, IEEE Network, 35, 99, pp. 1-8, (2021); Wang T., Zhang M., Springer C.H., Yang C., How to promote industrial park recycling transformation in China: An analytic framework based on critical material flow, Environmental Impact Assessment Review, 87, 5, (2021); Huang H., Yue Z., Peng X., He L., Chen W., Dai H.N., Zheng Z., Guo S., Elastic resource allocation against imbalanced transaction assignments in sharding-based permissioned blockchains, IEEE Transactions on Parallel and Distributed Systems, 33, (2022); Luo Q., Zhou Y., Hou W., Peng L., A hierarchical blockchain architecture based V2G market trading system, Applied Energy, 307, (2022); Sikorski J.J., Haughton J., Kraft M., Blockchain technology in the chemical industry: Machine-to-machine electricity market, Applied Energy, 195, JUN.1, pp. 234-246, (2017); Underwood S., Blockchain beyond bitcoin, Communications of the ACM, 59, 11, pp. 15-17, (2016); Huang C., Chen G., Gong Y., Delay-Constrained buffer-aided relay selection in the Internet of things with decision-assisted reinforcement learning, IEEE Internet of Things Journal, 8, 99, (2021); Affia I., Aamer A., An internet of things-based smart warehouse infrastructure: Design and application, Journal of Science and Technology Policy Management, 13, 1, pp. 90-109, (2021); Chen X., Music emotion analysis based on PSO-BP neural network and big data analysis, Computational Intelligence and Neuroscience, 2021, (2021); Rachana Harish A., Liu X.L., Zhong R.Y., Huang G.Q., Log-flock: A blockchain-enabled platform for digital asset valuation and risk assessment in E-commerce logistics financing, Computers & Industrial Engineering, 151, (2021); Liu Z., Li Z., A blockchain-based framework of cross-border e-commerce supply chain, International Journal of Information Management, 52, (2020); Li M., Shao S., Ye Q., Xu G., Huang G.Q., Blockchain-enabled logistics finance execution platform for capital-constrained E-commerce retail, Robotics and Computer-Integrated Manufacturing, 65, (2020)","H. Yujie; School of International Business, Qingdao Huanghai University, Qingdao, Shandong, 7266000, China; email: houyj@qdhhc.edu.cn",null,"Hindawi Limited",{"$nulls":5},1.6875265E7,null,null,3.5676947E7,"English","Comput. Intell. Neurosci.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85131623164"]
["Gao P.; Zhao L.","Gao, Peng (58363648900); Zhao, Liang (57204415903)","58363648900; 57204415903","Study on Deep Learning Technology to Construct E-Commerce Industry Marketing Promotion Model",2022.0,"Security and Communication Networks",2022.0,null,9958398.0,null,null,null,4.0,"10.1155/2022/9958398","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85140979637&doi=10.1155%2f2022%2f9958398&partnerID=40&md5=db6bb10e086d399b3ddf7bf043a9184e","School of Business Administration, Guangxi University of Finance and Economics, Guangxi, Nanning, China; Student Affairs Office, Beijing City University, Beijing, China","Gao P., School of Business Administration, Guangxi University of Finance and Economics, Guangxi, Nanning, China; Zhao L., Student Affairs Office, Beijing City University, Beijing, China","In recent years, with the development of Internet, Internet technology has swept the world and become a new round of scientific and technological revolution in the world economy. Network marketing has become the \"darling\"of marketing, with a multidimensional and multilevel marketing layout, which provides a carrier platform for the promotion of enterprise marketing strategy. The traditional network marketing mode is mainly in the form of advertising push, with pop-ups, screen overlays, top search rankings, loading videos, texts, and pictures. Nowadays, Internet technology and social media have promoted the development of community e-commerce models. Live delivery is a new sales model, which has promoted economic development. It has many advantages, such as interactivity, real-time, and transparency. Compared with the traditional e-commerce model, it is more suitable for the development requirements of the new era. Live delivery is a new sales model, which promotes economic development. This paper starts with the AdaBoost algorithm and marketing mode of STP and 4P marketing theory, in order to reduce the execution cost of marketing. In this way, it proves that using online marketing can not only reduce the cost but also improve the marketing effect. Through the new network marketing promotion mode and algorithm described in this paper, the cost can be reduced by 17%, and the promotion effect is remarkable. © 2022 Peng Gao and Liang Zhao.",null,"Adaptive boosting; Deep learning; Economic and social effects; Electronic commerce; Engineering education; Learning systems; E-commerce model; Economic development; Internet technology; Learning technology; Marketing strategy; Multilevels; Network marketing; Scientific revolutions; Technological revolution; World economy; Cost reduction",{"$nulls":6},"Wang J., Zou Y., Lei P., Sherratt R.S., Wang L., Research on recurrent neural network based crack opening prediction of concrete dam, Journal of Internet Technology, 21, 4, pp. 1151-1160, (2020); Pu B., Li K., Li S., Zhu N., Automatic fetal ultrasound standard plane recognition based on deep learning and IIoT, IEEE Transactions on Industrial Informatics, 17, 11, pp. 7771-7780, (2021); Cao D., Zeng K., Wang J., Pradip kumar sharma, xiaomin ma, and yonghe liu BERT-based deep spatial-temporal network for taxi demand prediction, IEEE Transactions on Intelligent Transportation Systems, 23, (2021); Li Q.L., The innovation of tourism marketing model on E-commerce environment, Advanced Materials Research, 926-930, pp. 4041-4044, (2014); Chen C., Li K., Teo S.G., Zou X., Li K., Zeng Z., Citywide traffic flow prediction based on multiple gated spatio-temporal convolutional neural networks, ACM Transactions on Knowledge Discovery from Data, 14, 4, (2020); Yan X.X., Hu Z.Q., Xu J., Liu J.Y., Research on the social E-commerce marketing model based on SICAS model in China, International Journal of Marketing Studies, 9, 3, (2017); Wang J., Yang Y., Wang T., Sherratt R., Zhang J., Big data service architecture: A survey, Journal of Internet Technology, 21, 2, pp. 393-405, (2020); Malucelli A., Palzer D., Oliveira E., Ontology-based Services to help solving the heterogeneity problem in e-commerce negotiations, Electronic Commerce Research and Applications, 5, 1, pp. 29-43, (2006); Chen J., Li K., Bilal K., Zhou X., Li K., Yu P.S., A Bi-layered parallel training architecture for large-scale convolutional neural networks, IEEE Transactions on Parallel and Distributed Systems, 30, 5, pp. 965-976, (2019); Zhang J., Zhong S., Wang T., Chao H.-C., Wang J., Blockchain-based systems and applications: A survey, Journal of Internet Technology, 21, 1, pp. 1-14, (2020); Fensel D., McGuiness D.L., Schulten E., Wee Keong L., Guanghao Y., Ontologies and electronic commerce, IEEE Intelligent Systems, 16, 1, pp. 8-14, (2001); Turban E., King D., Lee J.K., Liang T.P., Turban D.C., Electronic commerce, A Managerial and Social Networks Perspective, 2012, pp. 161-207, (2015); Coleman C., Bill I., E-COMMERCE billIreland, Computer Law & Security Report, 16, 4, pp. 248-251, (2000); Boyd E.A., Bilegan I.C., Revenue management and E-commerce, Management Science, 49, 10, pp. 1363-1386, (2003); Turban E., King D., Lee J.K., Liang T.P., Turban D.C., (2015), Electronic Commerce: A Managerial and Social Networks Perspective. 8th Ed, pp. 361-401, (2018); Constantinides E., The 4S web-marketing mix model, Electronic Commerce Research and Applications, 1, 1, pp. 57-76, (2003); Yu L.J., Ai H.L., Research on the marketing mode of searching engine based on E-commerce environment, Applied Mechanics and Materials, 427, pp. 2846-2850, (2013); Constantinides E., The 4S Web-marketing Mix Model. Electronic Commerce Research and Applications, pp. 57-76, (2002); Hamidizadeh M.R., Hajkarimi A., Naeiji M.J., Designing and explaining the model of persistent customer loyalty in e-commerce: A study in the e-retailer's web sites, New Marketing Research Journal, 1, 2, pp. 79-92, (2011); Wei M., School of Management, Univ. X, 361005 X, et al. A Research on the E-commerce Applied to the Construction of Marketing Model, Journal of Sichuan University (Engineering Science Edition), S1, pp. 233-237, (2007); Wei M., School of Management, Univ. X, 361005 X A research on the E-commerce applied to the construction of marketing model, Journal of Sichuan University (Engineering Science Edition), S1, (2007); Li D., Xue W., Pei Y., Research on comprehensive evaluation of network marketing performance in O2O model-measuring by GIOWA operator, Journal of Electronic Commerce in Organizations, 5, 8, pp. 13-25, (2014); Wen-Juan L.I., Zhou Y., The preliminary study of E-commerce marketing model of tourism enterprise:A case study of the establishment and marketing of Taobao.com tourism online, Journal of Shaoyang University(Social Science Edition), 8, 11, (2013); You T., A study on innovating tea marketing development model in the electronic commerce environment, Journal of Heihe University, 8, 9, pp. 12-16, (2018); Li L., Miao Y., Innovation of E-commerce fresh agricultural products marketing based on big internet data platform, Revista de la Facultad de Ingenieria, 32, 1, pp. 475-486, (2017); Wu J., Shi L., Yu Y., Gonzalezc E.D.S., Weiyi H., Litao S., Zhang Y., Evaluation of precision marketing effectiveness of community E-commerce-an AISAS based model, Sustainable Operations and Computers, 31, 2, pp. 5-9, (2021); Berthon P., Pitt L., Cyr D., Campbell C., E-readiness and trust: Macro and micro dualities for e-commerce in a global environment, International Marketing Review, 25, 6, pp. 700-714, (2008); Kim H.B., Kim T.T., Shin S.W., Modeling roles of subjective norms and eTrust in customers' acceptance of airline B2C eCommerce websites, Tourism Management, 30, 2, pp. 266-277, (2009); Zhao H., Liu Z., Yao X., Yang Q., A machine learning-based sentiment analysis of online product reviews with a novel term weighting and feature selection approach, Information Processing & Management, 58, 5, (2021); Duan M., Li K., Liao X., Li K., A parallel multiclassification algorithm for big data using an extreme learning machine, IEEE Transactions on Neural Networks and Learning Systems, 29, 6, pp. 2337-2351, (2018)","L. Zhao; Student Affairs Office, Beijing City University, Beijing, China; email: 2111602048@e.gzhu.edu.cn",null,"Hindawi Limited",{"$nulls":5},1.9390114E7,null,null,null,"English","Secur. Commun. Networks","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85140979637"]
["Zhang F.","Zhang, Fan (57223009324)",5.7223009324E10,"Economic Research on Multiple Linear Regression in Fruit Market inspection and Management",2022.0,"Applied Mathematics and Nonlinear Sciences",{"$nulls":6},0.0,"10.2478/amns.2022.2.0183","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85140384735&doi=10.2478%2famns.2022.2.0183&partnerID=40&md5=f000c6a9ac60d1abdaa221fd5a8a53dc","Economy and Trade School, Shanghai Urban Construction Vocational College, Shanghai, 201415, China","Zhang F., Economy and Trade School, Shanghai Urban Construction Vocational College, Shanghai, 201415, China","Based on the hypothesis test of multiple regression models, this paper discusses three different implementation methods of permutation tests and analyzes their manifestations and application effects in regularization models. The two implementation methods are used for the first time to discover the Markov edge of the regularization model, which expands the application range of the replacement test method. The fruit market uses an e-commerce platform to connect farmers, leading enterprises, financial institutions, and logistics companies. Using information technology as a means, it uses the network to implement online transactions, online financing, online pledges, and online management to achieve information. New flow of finance, capital flow and logistics. Based on the theory of information asymmetry, system theory, and synergy theory, it is found that there is a linkage effect between the online supply of fresh agricultural products and the risk system. Various interest systems have affected the risks of online supply of fresh agricultural products by affecting the risks of financing companies, e-commerce platform risks, financial institution risks and other risks. The quantitative ridge regression model can well solve the shortcomings that MRLM-P cannot be applied to collinear data sets; on low-dimensional data sets, there is a classic regularization model of Markov edge discovery performance similar to MRLM-P; permutation The two newly-implemented implementation methods are slightly inferior to the previous implementation methods; Markov edge theory can effectively perform \"dimensional reduction\" operation on the spectral information matrix, and both correction models can well reflect the spectral information of the detection object. Dependence. information on platform financing companies, and assume regulatory responsibilities in the transaction process. Financial institutions should also carefully select cooperative e-commerce platforms and determine the appropriate financing rate based on the results of risk prediction, so as to effectively reduce the risk of online supply is of great significance. © The Author(s), 2022.","economic research; fruit market; inspection and supervision; multiple linear regression","Electronic commerce; Finance; Fruits; Object detection; Online systems; Commerce platforms; E- commerces; Economic research; Financial institution; Fresh agricultural products; Fruit market; Inspection and supervision; Multiple linear regressions; Online supplies; Regularization models; Multiple linear regression",{"$nulls":6},"Ahmad R., Farooqi A., Zhang J., Et al., Steady flow of a power law fluid through a tapered non-symmetric stenotic tube[J], Applied Mathematics and Nonlinear Sciences, 4, 1, pp. 249-260, (2019); Harisha R.P.S., Lokesha V., Et al., Degree Sequence of Graph Operator for some Standard Graphs[J], Applied Mathematics and Nonlinear Sciences, 5, 2, pp. 99-108, (2020); Ohsawa Y., Hayashi T., Tangled string for sequence visualization as fruit of ideas in Innovators Marketplace on Data Jackets[J], Intelligent decision technologies, 10, 3, pp. 235-247, (2016); Iriarte A., Yaez P., Villalobos P., Et al., Carbon Footprint of Southern Hemisphere Fruit Exported to Europe: The Case of Chilean Apple to the UK[J], Journal of Cleaner Production, 293, 6, (2021); Cicero N., Albergamo A., Salvo A., Et al., Chemical characterization of a variety of cold-pressed gourmet oils available on the Brazilian market[J], Food Research International, 109, pp. 517-525, (2018); Della L.J., Tailoring interventions for increasing fruit and vegetable consumption among urban and rural African American audiences: Applying market decision-analysis to the intervention design processes[J], Fire Safety Journal, 23, 4, pp. 413-438, (2015); Bo Y.L., Shamsudin R., Baharudin B., Et al., Performance Study of a Jatropha Curcas L. Fruit Shelling Machine for Kernel Recovery in Biodiesel Production[J], Applied Engineering in Agriculture, 31, pp. 755-765, (2015); Simmons D., Tracing the Impact of Baby-Boom Generation on the Economic Market Is No Trivial Pursuit[J], Journal of Contaminant Hydrology, 182, 3, pp. 287-296, (2015); Gao Z., Pang G., Li L., Et al., Design of hand-operated piggyback jaw gripper type simplified picker for pear[J], Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering, 35, 1, pp. 39-45, (2019); Sanderson V., Bamber N., Pelletier D.N., Cradle-to-market life cycle assessment of Okanagan (Canada) cherries: Helicopters, seasonal migrant labour and flying fruit - ScienceDirect[J], Journal of Cleaner Production, 229, pp. 1283-1293, (2019); Sanchez-Ramirez R.A., Charles V., Gonzalez-Araya M.C., Et al., Measuring the performance of a dehydration plant of apples[J], Applied Mathematical Modelling, 40, 21-22, pp. 9118-9130, (2016)","F. Zhang; Economy and Trade School, Shanghai Urban Construction Vocational College, Shanghai, 201415, China; email: zfansky@163.com",null,"Sciendo",{"$nulls":5},2.4448656E7,null,null,null,"English","Appl. Math. Nonlinear Sci.","Article","Article in press","All Open Access; Gold Open Access","Scopus","2-s2.0-85140384735"]
["Zhang H.; Xue L.; Jiang Y.; Song M.; Wei D.; Liu G.","Zhang, Hui (57276245700); Xue, Li (36684312200); Jiang, Yinhua (57210286466); Song, Mingwei (42662504100); Wei, Dingrui (57255792300); Liu, Gang (57201565364)","57276245700; 36684312200; 57210286466; 42662504100; 57255792300; 57201565364","Food delivery waste in Wuhan, China: Patterns, drivers, and implications",2022.0,"Resources, Conservation and Recycling",177.0,null,105960.0,null,null,null,14.0,"10.1016/j.resconrec.2021.105960","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85117148388&doi=10.1016%2fj.resconrec.2021.105960&partnerID=40&md5=8e34676d9ce1d652858e3019d0262095","School of Chemistry and Environmental Engineering, Wuhan Institute of Technology, Wuhan, 430205, China; Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China; SDU Life Cycle Engineering, Department of Green Technology, University of Southern Denmark, Odense, 5230, Denmark; School of Management, Wuhan Institute of Technology, Wuhan, 430205, China; College of Resources and Environment, Huazhong Agricultural University, Wuhan, 430070, China","Zhang H., School of Chemistry and Environmental Engineering, Wuhan Institute of Technology, Wuhan, 430205, China; Xue L., Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China, SDU Life Cycle Engineering, Department of Green Technology, University of Southern Denmark, Odense, 5230, Denmark; Jiang Y., School of Management, Wuhan Institute of Technology, Wuhan, 430205, China; Song M., College of Resources and Environment, Huazhong Agricultural University, Wuhan, 430070, China; Wei D., School of Chemistry and Environmental Engineering, Wuhan Institute of Technology, Wuhan, 430205, China; Liu G., SDU Life Cycle Engineering, Department of Green Technology, University of Southern Denmark, Odense, 5230, Denmark","With the rapid development of e-commerce and the modern fast-paced life in large Chinese cities, food delivery services have become an important part of daily life and inevitably result in significant amount of food delivery waste (FDW) and environmental impacts. However, the scales, patterns, and impacts of FDW remain hitherto poorly understood. This study, based on direct weighing method (810 samples) and questionnaire survey (889 samples), aims to address such gaps with a case study for Wuhan, a typical first-tier city in central China. Our results showed that Wuhan's total FDW added up to 177.6 (± 52.9) kilotons in 2019, in which white-collar workers contribute the most (58%) and packaging waste takes up a significant share (32%). When packaging waste is excluded, the amount of FDW varied significantly among consumer groups, i.e., 154 ± 69, 187 ± 97, and 249 ± 124 g/cap/order for urban residents, college students, and white-collar workers, respectively, indicating the predominant role of consumer characteristics on FDW generation. Wuhan's total FDW related carbon emissions were approximately 168.3 kilotons CO2e; and this can be reduced by 25% if waste-to-energy technology can be implemented as planned and by 55% if the avoidable part of FDW can be prevented. Raising awareness and encouraging thriftiness (e.g., via education and public campaigns), nudging and pricing to minimize irrational food purchase, and reducing unnecessary packing and use of disposal dishware, are suggested as important FDW reduction strategies. © 2021","Consumer food waste; Driving factors; Food delivery; Food waste reduction; Greenhouse gas emissions","China; Hubei; Wuhan; Environmental impact; Gas emissions; Greenhouse gases; Students; Consumer food waste; Driving factors; Food delivery; Food waste; Food waste reduction; Greenhouse gas emissions; Packaging waste; Waste reduction; Workers'; carbon emission; consumption behavior; electronic commerce; food waste; greenhouse gas; packaging waste; adult; age; Article; carbon emission; case study; China; college student; consciousness; consumer attitude; controlled study; educational status; female; food delivery waste; food packaging; food waste; gender; household; human; male; questionnaire; restaurant; shopping; traffic and transport; urban population; white collar worker; Surveys",{"$nulls":4},"ZDBS-SSW-DQC; Hubei Provincial Department of Education, (B2020053); Chinese Academy of Sciences, CAS; Wuhan Institute of Technology, WIT, (19QD44)","We acknowledge financial support from Key Projects of Chinese Academy of Sciences (ZDBS-SSW-DQC), the Scientific Research Fund of Wuhan Institute of Technology (19QD44), and Education Department of Hubei Province (B2020053). Our deepest appreciation goes to all the student volunteers, survey respondents, office building and residential property management staff, and restaurant employees for assistance and cooperation in our field suvey. We devoted this work to all medical staff, professionals, and general public who helped fight COVID-19 in Wuhan in a memorable Spring, 2020.","Aschemann-Witzel J., De Hooge I., Amani P., Bech-Larsen T., Oostindjer M., Consumer-related food waste: causes and potential for action, Sustainability, 7, 6, pp. 6457-6477, (2015); Boschini M., Falasconi L., Cicatiello C., Franco S., Why the waste? A large-scale study on the causes of food waste at school canteens, J. Clean. Prod., 246, 10, (2020); De Clercq D., Wen Z., Fan F., Caicedo L., Biomethane production potential from restaurant food waste in megacities and project level-bottlenecks: a case study in Beijing, Renew. Sust. Energ. Rev., 59, pp. 1676-1685, (2016); Dhir A., Talwar S., Kaur P., Malibari A., Food waste in hospitality and food services: a systematic literature review and framework development approach, J. Clean Prod., 270, (2020); Djekic I., Miloradovic Z., Djekic S., Tomasevic I., Household food waste in Serbia – Attitudes, quantities and global warming potential, J. Clean. Prod., 229, pp. 44-52, (2019); FAO'S Work On Climate Change GHG Emissions, (2016); Gallego-Schmid A., Mendoza J.M.F., Azapagic A., Environmental impacts of takeaway food containers, J. Clean. Prod., 211, pp. 417-427, (2019); Zamri G.B., Azizal N., Nakamura S., Okada S., Nordin N.H., Othman N., Akhir F.N., Sobian A., Kaida A., Hara H., Delivery, impact and approach of household food waste reduction campaigns, J. Clean. Prod, 246, 10, (2020); Ji L., Total volume of market trade in food delivery serveive will amount to 60 billion USD in 2019 in China with an annual increase rate of 30.8%, Econ. 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Sci., 31, pp. 40-49, (2016); Liu D., Zhu X., Wang Y., China's agricultural green total factor productivity based on carbon emission: an analysis of evolution trend and influencing factors, J. Clean. Prod., 278, (2021); Lu Z., Online fast delivery food \"smart restaurant\", the internet is reshaping Chinese dining tables, People News.2018-06-11, (2018); Martindale W., Using consumer surveys to determine food sustainability, Brit. Food J., 116, 7, pp. 1194-1204, (2014); Mattar L., Abiad M.G., Chalak A., Diab M., Hassan H., Attitudes and behaviors shaping household food waste generation: lessons from Lebanon, J. Clean. Prod., 198, pp. 1219-1223, (2018); China Statistical Yearbook in 2018, (2018); Thirteenth Five-Year Plan For the Construction of Environmentally Sound Treatment Facilities For Municipal Domestic Waste (2016-2020). China National Development and Reform Commission (NDRC) & Ministry of Housing and Urban-Rural Development, (2015); Pinto R.S., Pinto R.M.D.S., Melo F.F.S., Campos S.S., Cordovil C.M.-D.-S., A simple awareness campaign to promote food waste reduction in a University canteen, Waste Manag, 76, pp. 28-38, (2018); Report of business model and investment strategic planning analysis on China online takeaway industry (2020-2025), Professional Integrity Quality Service (PIQS). Professional Integrity Quality Service (PIQS), (2020); Podsakoff P.M., Mackenzie S.B., Lee J.Y., Podsakoff N.P., Common method biases in behavioral research: a critical review of the literature and recommended remedies, J. Appl. Psychol., 88, 5, pp. 879-903, (2003); Schott A.B.S., Andersson T., Food waste minimization from a life-cycle perspective, J. Environ. 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Manag, 39, 8, (2020); Wang L.-E., Liu G., Liu X., Liu Y., Gao J., Zhou B., Gao S., Cheng S., The weight of unfinished plate: a survey based characterization of restaurant food waste in Chinese cities, Waste Manag., 66, pp. 3-12, (2017); Wu Z.H., Is food delivery serveice cheap? what is the true nature of Manjian Youfei activity ?, Xinhua News.2018-01-01, (2018); Wu Y., Tian X., Li X., Yuan H., Liu G., Characteristics, influencing factors, and environmental effects of plate waste at university canteens in Beijing, China. Resour. Conserv. Recy., 149, pp. 151-159, (2019); (2020); (2016); (2019); Xue L., Liu X., Lu S., Cheng G., Hu Y., Liu J., Dou Z., Cheng S., Liu G., China's food loss and waste embodies increasing environmental impacts, Nat. Food, 2, 7, pp. 519-528, (2021); Xue L., Liu G., Parfitt J., Liu X., Van H.E., Stenmarck A., O'Connor C., K A.S., Cheng S., Missing food, missing data? A critical review of global food losses and food waste data, Environ. Sci. Technol., 51, 12, pp. 6618-6633, (2017); Yang Y., Bao W., Xie G.H., Estimate of restaurant food waste and its biogas production potential in China, J. Clean. Prod., 211, pp. 309-320, (2019); Ye Q., Hu L., Liu S., Wastes resulted from 50 million takeaway food threatens urban ecology environment, Xinhua News. 2019-12-19, (2019); Zhang H., Duan H., Andric J.M., Song M., Yang B., Characterization of household food waste and strategies for its reduction: a Shenzhen City case study, Waste Manag., 78, pp. 426-433, (2018); Zhang H., Liu G., Xue L., Zuo J., Chen T., Vuppaladadiyam A., Duan H., Anaerobic digestion based waste-to-energy technologies can halve the climate impact of China's fast-growing food waste by 2040, J. Clean. Prod., 277, (2020); Zhou Y., Et al., Sharing tableware reduces waste generation, emissions and water consumption in China's takeaway packaging waste dilemma, Nat. Food, 1, pp. 552-561, (2020)","G. Liu; SDU Life Cycle Engineering, Department of Green Technology, University of Southern Denmark, Odense, 5230, Denmark; email: gli@igt.sdu.dk",null,"Elsevier B.V.",{"$nulls":5},9213449.0,null,"RCREE",null,"English","Resour. Conserv. Recycl.","Article","Final","All Open Access; Green Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85117148388"]
["Liu Q.","Liu, Qi (57893849700)",5.78938497E10,"The Development Relationship between Cross-Border e-Commerce and Internet of Things Technology Coupling in Digital Economy Based on Neural Network Model",2022.0,"Computational and Mathematical Methods in Medicine",2022.0,null,8981618.0,null,null,null,1.0,"10.1155/2022/8981618","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85138145262&doi=10.1155%2f2022%2f8981618&partnerID=40&md5=693c772d98148da610143b165e657eb9","Guangdong University of Science and Technology, Guangdong, Dongguan, 523083, China","Liu Q., Guangdong University of Science and Technology, Guangdong, Dongguan, 523083, China","Compared with the traditional trading model, the problem of information asymmetry in export cross-border e-commerce (CBEC) transactions actually exists. Since the buyers and sellers of export CBEC are located in different countries, it is difficult for both parties to make accurate judgments on each other's credit. Besides, the number of export CBEC financing is relatively small, and the financing situation is not optimistic. Fortunately, the Internet of Things (IOT) technology has a wide range of applications and strong social penetration, especially in e-commerce, which can effectively improve payment, logistics, and distribution. By employing the concept of the IOT, this paper expounds the application of the IOT in the e-commerce transaction process and the impact of the IOT on the development of e-commerce. Besides, this paper also proposes some security issues in the application of the IOT in e-commerce. In addition, this paper analyzes the relationship and development trend of CBEC and IOT technology; meanwhile, it also points out the practical problems currently faced by combining the regional advantage of a certain region. The e-commerce industry develops IOT technology and drives innovation-driven development in the region. In addition, this paper builds an evaluation index system for the development of export CBEC enterprises based on the analysis of the problems and reasons by using the sample data to train the BP neural network and using the test samples to test the model. It is found that the model accuracy rate is 89.47%. Then, this paper also takes the export CBEC company A as an example to conduct empirical research and to prove the operability of the credit evaluation model. Finally, it provides relevant suggestions for improving the credit evaluation system of export CBEC enterprises.  © 2022 Qi Liu.",null,"Commerce; Data Collection; Humans; Internet of Things; Neural Networks, Computer; Technology; Digital storage; Electronic commerce; Neural networks; Buyers and sellers; Cross-border; Digital economy; E- commerces; E-commerce enterprise; E-commerce transactions; Information asymmetry; Internet of things technologies; Neural network model; Trading models; article; artificial neural network; back propagation neural network; cross coupling reaction; economic aspect; electronic commerce; empirical research; human; internet of things; security; commercial phenomena; information processing; technology; Internet of things",{"$nulls":6},"Pan L.P., Fu X., Li Y.Q., SME participation in cross-border e-commerce as an entry mode to foreign markets: A driver of innovation or not?, Electronic Commerce Research, 2, pp. 1-30, (2022); Xu M., Wang P.S., Research on developing cross-border E-commerce and promoting the transformation and upgrading of foreign trade in Anhui Province, International Journal of Social Science and Education Research, 5, 3, pp. 1-7, (2022); Lin G.L., Lu D.P., Research on countermeasures for high-quality development of cross-border E-commerce in Zhejiang Province under the background of new development pattern, Frontiers in Economics and Management, 3, 3, pp. 1-10, (2022); Li L.Q., Cross-border E-commerce intelligent information recommendation system based on deep learning, Computational Intelligence and Neuroscience, 2022, (2022); Zhou J.X., Shen G.Q., Yoon S.H., Jin X., Customization of on-site assembly services by integrating the internet of things and BIM technologies in modular integrated construction, Automation in Construction, 126, pp. 321-332, (2021); Paudel N., Neupane R.C., A general architecture for a real-time monitoring system based on the Internet of Things, Internet of Things, 14, pp. 21-32, (2021); Hu F., Qiu L., Xi X., Zhou H., Hu T., Su N., Zhou H., Li X., Yang S., Duan Z., Dong Z., Wu Z., Zhou H., Zeng M., Wan T., Wei S., Has COVID-19 changed China's digital trade? - Implications for health economics, Frontiers in Public Health, 10, pp. 831549-831549, (2022); Huang K., Madnick S., Zhang F., Siegel M., Varieties of public-private co-governance on cybersecurity within the digital trade: Implications from Huawei's 5G, Journal of Chinese Governance, 7, 1, pp. 81-110, (2022); Shadikhodjaev S., Technological neutrality and regulation of digital trade: How far can we go?, European Journal of International Law, 32, 4, pp. 1221-1247, (2021); Zhang H., Trade openness and green total factor productivity in China: The role of ICT-based digital trade, Frontiers in Environmental Science, 9, pp. 98-102, (2021); Huang K.M., Madnick S., Choucri N., Zhang F., A systematic framework to understand transnational governance for cybersecurity risks from digital trade, Global Policy, 12, 5, pp. 625-638, (2021); Wen L., Development analysis of cross-border E-commerce logistics based on big data technology under safety law protection, International Journal of Information Systems in the Service Sector, 14, 2, pp. 1-14, (2022); Chen N., Analysis of the correlation between cross-border E-commerce and economic growth based on hierarchical multilevel gray evaluation model, Journal of Mathematics, 2022, (2022); Chen T.G., Qiu Y., Wang B., Yang J., Analysis of effects on the dual circulation promotion policy for cross-border E-commerce B2B export trade based on system dynamics during COVID-19, Systems, 10, 1, pp. 13-13, (2022); Mu W.Z., Analysis and warning model of logistics risks of cross-border E-commerce, Discrete Dynamics in Nature and Society, 2022, (2022); Jing W.J., Construction of an E-commerce system based on 5G and Internet of Things technology, International Journal of Information Systems and Supply Chain Management (IJISSCM), 15, 2, pp. 1-19, (2021); Du J., Yu Z.Y., Building a cross-border E-commerce ecosystem model based on block chain + Internet of Things, Security and Communication Networks, 2021, (2021); Zhang Y., Wen J.T., The IoT electric business model: Using blockchain technology for the Internet of Things, Peer-to-Peer Networking and Applications, 10, 4, pp. 983-994, (2017); Khastavaneh H., Ebrahimpour K., Segmentation of diabetic retinopathy lesions in retinal fundus images using multi-view convolutional neural networks, Iranian Journal of Radiology, 16, (2019); Li H., Li T., Yao Q., Li W., Yang L., Sun G., Risk assessment of power monitoring system based on fuzzy analytical hierarchy process, Journal of Physics: Conference Series, 2137, 1, pp. 12023-12031, (2021); Wang T., Research on the impact of cross-border E-commerce in Henan Province on foreign trade enterprises, International Journal of Education and Management, 6, 4, pp. 1-8, (2021); Hu L., Liu G.Z., Normative study on website translation of cross-border E-commerce in China under the belt and road initiative[J], Academic Journal of Business & Management, 3, 11, pp. 76-87, (2021); Lei Y., Qiu X.D., Research on the evaluation of cross-border E-commerce overseas strategic climate based on decision tree and adaptive boosting classification models, Frontiers in Psychology, 12, pp. 803989-803989, (2021); Zhao M.X., Transformation and upgrading strategies of foreign trade enterprises based on cross-border E-commerce, International Journal of Education and Teaching Research, 2, 4, pp. 1-7, (2021); Dong Y.J., Zhang Y., Implementation of distributed operation and maintenance of cross-border e-commerce platform based on cloud native architecture, Security and Communication Networks, 2021, (2021)","Q. Liu; Guangdong University of Science and Technology, Dongguan, Guangdong, 523083, China; email: liuqi@gdust.edu.cn",null,"Hindawi Limited",{"$nulls":5},"1748670X",null,null,3.6124174E7,"English","Comp. Math. Methods Med.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85138145262"]
["Zeng Q.","Zeng, Qingju (57735306500)",5.77353065E10,"Characteristic Analysis and Route Optimization of Heterogeneous Neural Network in Logistics Allocation System",2022.0,"Computational Intelligence and Neuroscience",2022.0,null,1713183.0,null,null,null,2.0,"10.1155/2022/1713183","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85131703863&doi=10.1155%2f2022%2f1713183&partnerID=40&md5=2722dab477aaf85d5684edbb87159bdd","Business School, Chongqing City Vocational College, Chongqing, Yongchuan, 402160, China","Zeng Q., Business School, Chongqing City Vocational College, Chongqing, Yongchuan, 402160, China","Logistics distribution vehicle scheduling plays an important role in the supply chain. With the wide application of e-commerce technology and the increasing diversification of urban industrial and commercial development mode, the optimal scheduling of logistics distribution vehicles can improve the economic benefits of logistics and realize the scientization of logistics. Aiming at the problems existing in the logistics allocation system, this paper proposes a logistics allocation system model based on a heterogeneous neural network, uses the heterogeneous neural network to optimize vehicle scheduling, and gives the specific steps to solve the problem of optimal scheduling of distribution vehicles. The simulation consequences exhibit that the proposed technique cannot solely efficaciously clear up the automobile scheduling optimization model and however additionally has low pc complexity, excessive computational effectivity, and speedy convergence speed. The practicability and effectiveness of the improved algorithm are verified. When the number of distribution customers and distribution cycle is the same, the proposed algorithm effectively reduces the total distribution mileage, reduces the number of vehicles, and improves the efficiency of logistics distribution. © 2022 Qingju Zeng.",null,"Algorithms; Commerce; Computer Simulation; Logistic Models; Neural Networks, Computer; Commercial vehicles; Economic and social effects; Supply chains; Allocation systems; Characteristics analysis; Distribution vehicles; E- commerces; Industrial development; Logistic distributions; Neural-networks; Optimal scheduling; Route optimization; Vehicle scheduling; algorithm; commercial phenomena; computer simulation; statistical model; Scheduling",{"$nulls":6},"Zhang J.P., Cloud computing optimized logistics vehicle routing algorithm, Mechanical Design and Manufacturing, 15, 2, pp. 168-170, (2022); Chen Y.Y., Chen L., Reverse optimization method for vehicle routing problem, Journal of Shanghai Jiaotong University, 56, 1, pp. 81-88, (2022); Xu H., Analysis of supply chain management operation mode and optimization path of logistics enterprises in the era of big data, Rural Economy, Science and Technology, 32, 24, pp. 124-126, (2021); Ye P., Research on optimal logistics transportation route planning method based on particle swarm optimization, Microcomputer Applications, 37, 12, pp. 158-161, (2021); Cai W.Z., Research on logistics distribution path optimization based on big data, Electronic Technology and Software Engineering, 13, 2, pp. 122-123, (2021); Wang Y., Research on air logistics distribution path optimization method based on ant colony algorithm, Journal of Information Technology, 22, 11, pp. 76-80, (2021); Zhang Q., Construction of logistics transportation optimal path optimization model based on improved ant colony algorithm, Automation Technology and Application, 40, 11, pp. 122-126, (2021); Wan G.H., Chen C.M., Xu F., Gao X.D., Wu C.Z., Zeng L., Gan L., Li X.F., Xu J.H., Deng M., Xu Q., Research on tobacco logistics distribution path optimization based on neural network, Journal of Hubei Institute of Engineering, 41, 6, pp. 97-101, (2021); Xu X.F., Jiang M.Y., Deng Y.R., Research on dynamic path optimization of integrated reverse logistics collaborative distribution, Journal of Management Science, 24, 10, pp. 106-112, (2021); Wu J., Logistics distribution path optimization problem, Modern Business, 25, 2, pp. 20-21, (2018); Zhou X.C., Yang T.T., Liu X.F., Pan Y.X., Intelligent logistics distribution route optimization method based on improved ant colony algorithm, Journal of Inner Mongolia Normal University, 46, 6, pp. 888-892, (2017); Muradov M.V., Ryazan V.V., Biryukova V.A., Petrov D.I., Petrov I.B., Inverse problems of heterogeneous geological layers exploration seismology solution by methods of machine learning, Lobachevskii Journal of Mathematics, 42, 7, pp. 1728-1737, (2021); Romain E.L., Giuliani D., Deep-neural network approaches for speech recognition with heterogeneous groups of speakers including children, Natural Language Engineering, 23, 3, pp. 325-350, (2016); Chen X.Q., Research and Simulation of logistics path optimization based on continuous Hopfield network, Computing Technology and Automation, 40, 3, pp. 143-146, (2021); Chen J., Liu Z., Research on cold chain logistics path optimization based on ant colony algorithm, Transportation Technology and Economy, 23, 5, pp. 38-44, (2021); Sun L.L., Shi W.X., Jiang Q., Zhang M., Summary of research on logistics distribution route optimization considering vehicle utilization, China Logistics and Procurement, 33, 16, pp. 64-66, (2021); Jin J.T., He W.J., Xu C.Y., Zhang J.Y., Dai D., Research on logistics distribution path optimization based on improved ant colony algorithm, Mall Modernization, 17, 10, pp. 46-48, (2021); Kai J., Yang J.Y., Jiang Q.C., Wang Y.Q., Kai J.J., Research on logistics distribution path based on ant colony algorithm, Logistics Engineering and Management, 40, 2, pp. 74-76, (2018); Zhu Z.G., Guang X.P., Guo M., Multi vehicle logistics distribution path optimization under uncertain environment, Transportation Technology and Economy, 23, 2, pp. 6-12, (2021); Kong Z.Y., Research on vehicle routing planning considering energy consumption optimization and time adjustment, Value Engineering, 39, 13, pp. 111-113, (2020); Kaushik A.K., A Hybrid approach of fuzzy c-means clustering and neural network to make energy-efficient heterogeneous wireless sensor network, International Journal of Electrical and Computer Engineering, 6, 2, pp. 674-675, (2015); Emerson A., Jinn T., Daniels B.C., Locating decision-making circuits in a heterogeneous neural network, Frontiers in Applied Mathematics & Statistics, 4, 11, pp. 11-13, (2018); Khan M.A., Zhang Y.D., Alhassan M., Seifedine K., Shui-Hua W., Tanzila S., Tassawar I., A fused heterogeneous deep neural network and robust feature selection framework for human actions recognition, Arabian Journal for Science and Engineering, 12, 6, pp. 1-3, (2021); Su J.H., Simulation research on optimal selection of automatic logistics distribution route, Computer Simulation, 36, 8, pp. 408-411, (2019); Yang J.Q., Cao L., Urban cold chain logistics path optimization with multiple logistics centers, Logistics Technology, 38, 7, pp. 71-75, (2019); Zou J.H., Discussion on logistics path optimization method based on hybrid genetic algorithm, Computer Products and Circulation, 17, 12, pp. 128-130, (2018); Wang T., Pan Y., Pan F., Zhu X.F., Distribution route optimization of fresh agricultural products based on improved artificial bee colony algorithm, Guangdong Agricultural Science, 45, 10, pp. 143-149, (2018); Chen C., Optimization of logistics vehicle routing problem based on improved genetic algorithm, Information Technology and Informatization, 27, 9, pp. 41-43, (2018); Wang L., Cai C., Pei A.H., Xiao R.N., Ye J., Research on the optimal path of multiple pick-up vehicles in logistics distribution based on improved ant colony algorithm, Highway Traffic Technology, 14, 5, pp. 317-320, (2018); Wang Z.L., Research on development mode and path optimization of shared logistics, Times Economic and Trade, 23, 12, pp. 6-7, (2018)","Q. Zeng; Business School, Chongqing City Vocational College, Yongchuan, Chongqing, 402160, China; email: 023381@cqcvc.edu.cn",null,"Hindawi Limited",{"$nulls":5},1.6875265E7,null,null,3.5685131E7,"English","Comput. Intell. Neurosci.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85131703863"]
["Wang S.; Yang L.; Yao Y.; Zhang Q.; Shang P.","Wang, Shuai (57852571100); Yang, Liya (56174456200); Yao, Yu (57201189174); Zhang, Qin (57202919011); Shang, Pan (56708208600)","57852571100; 56174456200; 57201189174; 57202919011; 56708208600","Equity-oriented vehicle routing optimization for catering distribution services with timeliness requirements",2022.0,"IET Intelligent Transport Systems",16.0,2.0,null,163.0,185.0,22.0,2.0,"10.1049/itr2.12136","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85118493120&doi=10.1049%2fitr2.12136&partnerID=40&md5=06a1bd2959c2fd3f8f5bffb13cfc57fc","School of Traffic and Transportation, Beijing Jiaotong University, Beijing, China; School of Public Administration, Renmin University of China, Beijing, China","Wang S., School of Traffic and Transportation, Beijing Jiaotong University, Beijing, China; Yang L., School of Public Administration, Renmin University of China, Beijing, China; Yao Y., School of Traffic and Transportation, Beijing Jiaotong University, Beijing, China; Zhang Q., School of Traffic and Transportation, Beijing Jiaotong University, Beijing, China; Shang P., School of Traffic and Transportation, Beijing Jiaotong University, Beijing, China","The rapid development in the catering services and urban logistics industries has significantly promoted the prosperity of business-to-consumer (B2C) e-commerce urban logistics distribution, which is gaining increasing interest from food producers, distribution platforms, and consumers. Unlike traditional logistics supply chains, catering distribution services have strong timeliness and consideration of delivery delay. Traditional distribution platforms usually group commodities by their origins or destinations and then transport each group with one logistics vehicle. However, for a logistics distribution area with limited commodities, the vehicle capacity cannot be fully utilized if one vehicle can only transport commodities with the same origin or destination. Therefore, a mixed-load strategy is proposed in which commodities with different origins or destinations in a distribution area could be transported by the same vehicle to improve vehicle capacity utilization. A mixed-load strategy would further cause delivery sequencing problems, leading to different delivery delays for customers. This study proposed an equity-oriented vehicle routing problem for food distribution services with timeliness requirements considering a mixed-loading strategy and vehicle capacity constraints. For the above problem, a multi-commodity flow optimization model was constructed for the equity-oriented vehicle routing problem and a mixed-load strategy based on a time-discretized space-time-state network representation. An augmented Lagrangian relaxation approach was utilized to reformulate the original model and thus effectively solve the proposed model. Furthermore, the augmented Lagrangian model was decomposed and linearized into a series of shortest path searching subproblems and iteratively solved by a dynamic programming algorithm using an alternating direction method of multipliers (ADMM)-based solution framework. Finally, the proposed model and solution approaches were tested on numerous networks. © 2021 The Authors. IET Intelligent Transport Systems published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology",null,"Constrained optimization; Dynamic programming; Iterative methods; Lagrange multipliers; Supply chains; Vehicles; Business to Consumer; Delivery delay; Distribution area; Distribution services; Logistic distributions; Logistics industry; Urban logistics; Vehicle routing optimization; Vehicle Routing Problems; Vehicle's capacity; Vehicle routing",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (72001020, No.U2034208); China Postdoctoral Science Foundation, (2020M670128); Beijing Municipal Natural Science Foundation, (L201016); Fundamental Research Funds for the Central Universities, (2020YJS085)","This paper is supported by the Fundamental Research Funds for the Central Universities (2020YJS085), the Joint Funds of the National Natural Science Foundation of China (No.U2034208), National Natural Science Foundation of China (No. 72001020), China Postdoctoral Science Foundation (No. 2020M670128) and Beijing Municipal Natural Science Foundation (No. L201016) ","Jao N., (2019); Zheng K., Zhang Z., Song B., E-commerce logistics distribution mode in big-data context: A case analysis of JD. 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Part B: Methodol., 97, pp. 157-181, (2017); Rey F., Hokayem P., Lygeros J., A tailored ADMM approach for power coordination in variable speed drives, IFAC-PapersOnLine, 50, 1, pp. 7403-7408, (2017); Berbeglia G., Cordeau J.F., Gribkovskaia I., Laporte G., Static pickup and delivery problems: A classification scheme and survey, Top, 15, 1, pp. 1-31, (2007); Nair D.J., Rey D., Dixit V.V., Fair allocation and cost-effective routing models for food rescue and redistribution, IISE Trans., 49, 12, pp. 1172-1188, (2017); de Camargo R.S., de Miranda G., Lokketangen A., A new formulation and an exact approach for the many-to-many hub location-routing problem, Appl. Math. Modell., 37, 12-13, pp. 7465-7480, (2013)","P. Shang; School of Traffic and Transportation, Beijing Jiaotong University, Beijing, China; email: shangpan@bjtu.edu.cn",null,"John Wiley and Sons Inc",{"$nulls":5},"1751956X",null,null,null,"English","IET Intel. Transport Syst.","Article","Final",null,"Scopus","2-s2.0-85118493120"]
["Chen N.","Chen, Nie (57463896300)",5.74638963E10,"Research on E-Commerce Database Marketing Based on Machine Learning Algorithm",2022.0,"Computational Intelligence and Neuroscience",2022.0,null,7973446.0,null,null,null,1.0,"10.1155/2022/7973446","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85133954452&doi=10.1155%2f2022%2f7973446&partnerID=40&md5=87f2657ab915d3067479867f5382d45c","Department of Electronic Commerce, Zhejiang Business Technology Institute, Ningbo, 315012, China","Chen N., Department of Electronic Commerce, Zhejiang Business Technology Institute, Ningbo, 315012, China","From simple commercial relations to complex online transactions at this stage, it not only highlights the progress of science and technology, but also indirectly explains the diversified evolution of marketing methods and means. In marketing, database marketing has been favored by more marketers with its low cost and high efficiency and has become the \"rookie\"in marketing in recent years. However, as a kind of prediction and ferry, database marketing tends to be applied after simple data analysis in unpredictable market and in practice. In contrast, database marketing combined with machine learning algorithms has always been a depression in the marketing field. Therefore, this paper takes e-commerce as the research object and carries out database marketing research based on machine learning algorithm from four stages: theoretical preparation, status analysis, model construction, and results application. Firstly, the connotation, advantages, and specific operation procedures of database marketing are discussed. At the same time, four excellent machine learning algorithms including logistic regression, random forest, support vector machine, and gradient boosted decision tree (GBDT) are selected to explain the basic principles and algorithm introduction, respectively, laying a theoretical foundation for the model training chapter. Secondly, it analyzes the current situation of e-commerce from the distribution of marketing objects, the proportion of marketing channels, and the composition of marketing methods and finds new marketing ideas based on the main problems existing at the present stage of database marketing using machine learning algorithm. Thirdly, on the premise of marketing ideas, data acquisition, data processing, and positive and negative sample setting. At the same time, four machine learning algorithms are used to combine features from the perspectives of consumers, stores, and the relationship between consumers and stores. Finally, by substituting the predicted sample into the model for testing, the crowd whose predicted score is between 80 and 99 is selected to be put into the market as the model predicted crowd, and it is proposed that e-commerce should mainly adopt the database marketing method of model prediction. On the one hand, machine learning algorithm can solve the problem of uneven distribution of marketing objects, and on the other hand, it can effectively prevent the loss of potential consumers. In addition, the application strategy of optimizing other database marketing methods and assisting model prediction to improve marketing effect is also put forward.  © 2022 Nie Chen.",null,"Algorithms; Commerce; Machine Learning; Marketing; Support Vector Machine; Data acquisition; Data handling; Database systems; Electronic commerce; Forecasting; Learning algorithms; Marketing; Regression analysis; Support vector machines; Database marketing; E- commerces; Low-costs; Low-high; Machine learning algorithms; Model prediction; On-machines; Online transaction; Science and Technology; Simple++; algorithm; commercial phenomena; machine learning; marketing; support vector machine; Decision trees",{"$nulls":6},"Qian Y., Exploration of machine algorithms based on deep learning model and feature extraction, Mathematical Biosciences and Engineering, 18, 6, pp. 7602-7618, (2021); Xu J., Deng X., Yan F., Application of machine learning algorithm in anesthesia, Acta Academiae Medicinae Sinicae, 42, 5, pp. 696-701, (2020); 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Ingrisch M., Schoppe F., Paprottka K., Fabritius M., Strobl F.F., De Toni E.N., Ilhan H., Todica A., Michl M., Paprottka P.M., Prediction of 90Y radioembolization outcome from pretherapeutic factors with random survival forests, Journal of Nuclear Medicine, 59, 5, pp. 769-773, (2018); Wang Y., Chen L., Jo J., Wang Y., Joint t-SNE for comparable projections of multiple high-dimensional datasets, IEEE Transactions on Visualization and Computer Graphics, 28, 1, pp. 623-632, (2022); Raza A., Bardhan S., Xu L., Yamijala S.S.R.K.C., Lian C., Kwon H., Wong B.M., A machine learning approach for predicting defluorination of per- and polyfluoroalkyl substances (PFAS) for their efficient treatment and removal, Environmental Science and Technology Letters, 6, 10, pp. 624-629, (2019); Kang B., Garcia Garcia D., Lijffijt J., Santos-Rodriguez R., De Bie T., Conditional t-SNE: More informative t-SNE embeddings, Machine Learning, 110, 10, pp. 2905-2940, (2021); Althuwaynee O.F., Aydda A., Hwang I.-T., Lee Y.-K., Kim S.-W., Park H.-J., Lee M.-S., Park Y., Uncertainty reduction of unlabeled features in landslide inventory using machine learning t-SNE clustering and data mining apriori association rule algorithms, Applied Sciences, 11, 2, (2021); Bayat B., Van Der Tol C., Verhoef W., Retrieval of land surface properties from an annual time series of Landsat TOA radiances during a drought episode using coupled radiative transfer models, Remote Sensing of Environment, 47, 1, pp. 339-349, (2018); Pezzotti N., Thijssen J., Mordvintsev A., Hollt T., Van Lew B., Lelieveldt B.P.F., Eisemann E., Vilanova A., GPGPU linear complexity t-SNE optimization, IEEE Transactions on Visualization and Computer Graphics, 26, 1, pp. 1172-1181, (2020); Adat V., Gupta B.B., Security in Internet of Things: Issues, challenges, taxonomy, and architecture, Telecommunication Systems, 67, 3, pp. 423-441, (2018); Lu H., Li M.-J., He T., Wang S., Narayanan V., Chan K.S., Robust coreset construction for distributed machine learning, IEEE Journal on Selected Areas in Communications, 38, 10, pp. 2400-2417, (2020); Greengard S., The algorithm that changed quantum machine learning, Communications of the ACM, 62, 8, pp. 15-17, (2019); Li H., Fang C., Lin Z., Accelerated first-order optimization algorithms for machine learning, Proceedings of the IEEE, 108, 11, pp. 2067-2082, (2020); Jisu P., Hyuk, Park, Jong, Enhanced machine learning algorithms: Deep learning, reinforcement learning, and q-learning, Journal of Information Processing Systems, 16, 5, pp. 1001-1007, (2020); Rosenberg M.A., Trusting magic, Circulation, 143, 13, pp. 1299-1301, (2021); Richardson A., Van Florenstein Mulder T., Vehbi T., Nowcasting GDP using machine-learning algorithms: A real-time assessment, International Journal of Forecasting, 37, 2, pp. 941-948, (2021); Cui J., Tian K., Edge detection algorithm optimization and simulation based on machine learning method and image depth information, IEEE Sensors Journal, 20, 20, (2020); Sun Y.-G., Hwang Y.M., Young K.I.M.J.I.N., Performance of real-time image recognition algorithm based on machine learning, Journal of Satellite, Information and Communications, 12, 3, pp. 69-73, (2017); Rosario A., Raimundo R., Consumer marketing strategy and E-commerce in the last decade: A literature review, Journal of Theoretical and Applied Electronic Commerce Research, 16, 7, pp. 3003-3024, (2021); Klaus T., Changchit C., Toward an understanding of consumer attitudes on online review usage, Journal of Computer Information Systems, 59, 3, pp. 277-286, (2019); Anson J., Boffa M., Helble M., Consumer arbitrage in cross-border e-commerce, Review of International Economics, 27, 4, pp. 1234-1251, (2019); Walsh G., Brylla D., Do product returns hurt relational outcomes? some evidence from online retailing, Electronic Markets, 27, 4, pp. 329-339, (2017); Zhou L., Wang W., Xu J., Liu T., Gu J., Perceived information transparency in B2C e-commerce: An empirical investigation, Information & Management, 55, 7, pp. 912-927, (2018); Defranco J.F., Kshetri N., Voas J., Rearchitecting the malls: The shifting U.S. Retail landscape, Computer, 54, 2, pp. 86-90, (2021); Wang D., Guo X., Research on evaluation model of music education informatization system based on machine learning, Scientific Programming, 2022, 4, (2022)","N. Chen; Department of Electronic Commerce, Zhejiang Business Technology Institute, Ningbo, 315012, China; email: 20820048@zbti.edu.cn",null,"Hindawi Limited",{"$nulls":5},1.6875265E7,null,null,3.5814538E7,"English","Comput. Intell. Neurosci.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85133954452"]
["Bi W.; Liang Y.","Bi, Wentai (57846792000); Liang, Yuan (57846574400)","57846792000; 57846574400","Risk Assessment of Operator's Big Data Internet of Things Credit Financial Management Based on Machine Learning",2022.0,"Mobile Information Systems",2022.0,null,5346995.0,null,null,null,2.0,"10.1155/2022/5346995","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85136003479&doi=10.1155%2f2022%2f5346995&partnerID=40&md5=218646ddc7e5586a41cc2345f77fe878","College of Economics and Management, Henan Agricultural University, Henan, Zhengzhou, 450046, China; College of Economics and Management, Jilin Agricultural University, Jilin, Changchun, 130118, China","Bi W., College of Economics and Management, Henan Agricultural University, Henan, Zhengzhou, 450046, China; Liang Y., College of Economics and Management, Jilin Agricultural University, Jilin, Changchun, 130118, China","Credit risk evaluation innovation is of incredible importance to monetary establishments. AI innovation can fundamentally work on the precision and versatility of credit risk evaluation. This paper aims to study the risk assessment of operator big data Internet of Things credit financial management based on machine learning. It proposes machine learning-related algorithms, including the introduction of logistic model and decision tree model, as well as related concepts of credit financial management risk. This paper proposes that big data can be better used to reduce financial risk management problems and proposes specific actions based on the actual situation of the company. This paper selects company A for financial risk management evaluation through case analysis and compares it with three major e-commerce companies. The experimental results show that the earnings per share of company A is between -0.99 and 0. Company A is still in a state of loss in recent years, and there are certain debt risks, operational risks, and capital risks.  © 2022 Wentai Bi and Yuan Liang.",null,"Big data; Decision trees; Finance; Internet of things; Machine learning; Risk management; Credit-risk evaluations; Decision-tree model; Financial managements; Financial risk management; Logistics decisions; Logistics model; Machine-learning; On-machines; Related algorithms; Risks assessments; Risk assessment",{"$nulls":6},"Tavera Romero C.A., Ortiz J.H., Khalaf O.I., Rios Prado A., Business intelligence: Business evolution after industry 4.0, Sustainability, 13, 18, (2021); Li L., Zhang J., Research and analysis of an enterprise E-commerce marketing system under the big data environment, Journal of Organizational and End User Computing, 33, 6, pp. 1-19, (2021); Yang J., Luo D., The P2P risk assessment model based on the improved AdaBoost-SVM algorithm, Journal of Financial Risk Management, 6, 2, pp. 201-209, (2017); Lam T.Y., Siwingwa N., Risk management and contingency sum of construction projects, Journal of Financial Management of Property and Construction, 22, 3, pp. 237-251, (2017); Nolde N., Zhou C., Extreme value analysis for financial risk management, Annual Review of Statistics and Its Application, 8, 1, pp. 217-240, (2021); Mukhlis E.N.A., Damayanti S.M., Enterprise risk management to minimizing financial distress condition using analytical Hierarchy process method in PT. XYZ, European Journal of Business and Management Research, 6, 1, pp. 76-86, (2021); Buczak A.L., Guven E., A survey of data mining and machine learning methods for cyber security intrusion detection, IEEE Communications Surveys & Tutorials, 18, 2, pp. 1153-1176, (2016); Voyant C., Notton G., Kalogirou S., Nivet M.L., Paoli C., Motte F., Fouilloy A., Machine learning methods for solar radiation forecasting: A review, Renewable Energy, 105, MAY, pp. 569-582, (2017); Zhou L., Pan S., Wang J., Vasilakos A.V., Machine learning on big data: Opportunities and challenges, Neurocomputing, 237, MAY10, pp. 350-361, (2017); Kavakiotis I., Tsave O., Salifoglou A., Vlahavas N., Chouvarda I., Chouvarda I., Machine learning and data mining methods in diabetes research, Computational and Structural Biotechnology Journal, 15, C, pp. 104-116, (2017); Lv Z., Han Y., Singh A.K., Manogaranlv H., Trustworthiness in industrial IoT systems based on artificial intelligence, IEEE Transactions on Industrial Informatics, 17, 2, pp. 1496-1504, (2021); Xl A., Hao L.A., Wang W., Zheng Y., Lv H., Lv Z., Big Data Analysis of the Internet of Things in the Digital Twins of Smart City Based on Deep Learning, 128, pp. 167-177, (2021); Poret N., Twilley R.R., Coronado-Molina R.M., Object-based correction of LiDAR DEMs using RTK-GPS data and machine learning modeling in the coastal Everglades, Environmental Modelling & Software, 112, 3, pp. 491-496, (2018); Liu S., Wang X., Liu M., Zhu J., Towards better analysis of machine learning models: A visual analytics perspective, Visual Informatics, 1, 1, pp. 48-56, (2017); Wang P., Han W., Construction of a new financial E-commerce model for small and medium-sized enterprise financing based on multiple linear logistic regression, Journal of Organizational and End User Computing, 33, 6, pp. 1-18, (2021); Drton M., Plummer M., A Bayesian information criterion for singular models, Journal of the Royal Statistical Society: Series B, 79, 2, pp. 323-380, (2017); Lamperti F., Roventini A., Sani A., Agent-based model calibration using machine learning surrogates, Journal of Economic Dynamics and Control, 90, MAY, pp. 366-389, (2018); Zheng T., Xie W., Xu L., He X., Zhang Y., You M., Yang Y., Chen Y., A machine learning-based framework to identify type 2 diabetes through electronic health records, International Journal of Medical Informatics, 97, JAN, pp. 120-127, (2017); Kolouri S., Park S.R., Thorpe M., Slepcev D., Rohde G.K., Optimal mass transport: Signal processing and machine-learning applications, IEEE Signal Processing Magazine, 34, 4, pp. 43-59, (2017); Zhang L., Tan J., Han D., Zhu H., From machine learning to deep learning: Progress in machine intelligence for rational drug discovery, Drug Discovery Today, 22, 11, pp. 1680-1685, (2017); Schrider D.R., Kern A.D., Supervised machine learning for population genetics: A new paradigm, Trends in Genetics, 34, 4, pp. 301-312, (2018); Butler K.T., Davies D.W., Cartwright H., Isayev O., Walsh A., Machine learning for molecular and materials science, Nature, 559, 7715, pp. 547-555, (2018); Fatima M., Pasha M., Survey of machine learning algorithms for disease diagnostic, Journal of Intelligent Learning Systems and Applications, 9, 1, pp. 1-16, (2017); Sanchez-Lengeling B., Aspuru-Guzik A., Inverse molecular design using machine learning: Generative models for matter engineering, Science, 361, 6400, pp. 360-365, (2018)","Y. Liang; College of Economics and Management, Jilin Agricultural University, Changchun, Jilin, 130118, China; email: liangyuan@mails.jlau.edu.cn",null,"Hindawi Limited",{"$nulls":5},"1574017X",null,null,null,"English","Mob. Inf. Sys.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85136003479"]
["Qin H.; Xiao J.; Ge D.; Xin L.; Gao J.; He S.; Hu H.; Carlsson J.G.","Qin, Hengle (57803353600); Xiao, Jun (57804919500); Ge, Dongdong (7006758739); Xin, Linwei (55359404700); Gao, Jianjun (56600976800); He, Simai (7402690815); Hu, Haodong (57803882300); Carlsson, John Gunnar (36469820700)","57803353600; 57804919500; 7006758739; 55359404700; 56600976800; 7402690815; 57803882300; 36469820700","JD.com: Operations Research Algorithms Drive Intelligent Warehouse Robots to Work",2022.0,"Interfaces",52.0,1.0,null,42.0,55.0,13.0,15.0,"10.1287/inte.2021.1100","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85133088523&doi=10.1287%2finte.2021.1100&partnerID=40&md5=50f61870d18c532c6d302876d88ebbf9","Research Institute for Interdisciplinary Sciences, Shanghai University of Finance and Economics, Shanghai, 200433, China; Department of AI and Big Data, JD Logistics, JD.com, Beijing, 100176, China; Booth School of Business, University of Chicago, Illinois, Chicago, 60637, United States; Department of Industrial and Systems Engineering, University of Southern California, Los Angeles, 90089, CA, United States","Qin H., Research Institute for Interdisciplinary Sciences, Shanghai University of Finance and Economics, Shanghai, 200433, China, Department of AI and Big Data, JD Logistics, JD.com, Beijing, 100176, China; Xiao J., Department of AI and Big Data, JD Logistics, JD.com, Beijing, 100176, China; Ge D., Research Institute for Interdisciplinary Sciences, Shanghai University of Finance and Economics, Shanghai, 200433, China; Xin L., Booth School of Business, University of Chicago, Illinois, Chicago, 60637, United States; Gao J., Research Institute for Interdisciplinary Sciences, Shanghai University of Finance and Economics, Shanghai, 200433, China; He S., Research Institute for Interdisciplinary Sciences, Shanghai University of Finance and Economics, Shanghai, 200433, China; Hu H., Research Institute for Interdisciplinary Sciences, Shanghai University of Finance and Economics, Shanghai, 200433, China; Carlsson J.G., Department of Industrial and Systems Engineering, University of Southern California, Los Angeles, 90089, CA, United States","JD.com pioneered same-day delivery as a standard service in China’s business-to-consumer e-commerce sector in 2010. To balance the urgent need to meet growing demands while maintaining high-quality logistics services, the company built intelligent warehouses that use analytics to significantly improve warehouse efficiency. The brain of the intelligent warehouse system is the dispatching algorithm for storage rack-moving robots, which makes real-time dispatching decisions among robots, racks, and workstations after solving large-scale integer programs in seconds. The intelligent warehouse technology has helped the company decrease its fulfillment expense ratio to a world-leading level of 6.5%. The construction of intelligent warehouses has led to estimated annual savings of hundreds of millions of dollars. In 2020, JD.com delivered 90% of its first-party-owned retail orders on the same day or on the day after the order was placed. The agility of such intelligent warehouses has allowed JD.com to handle 10 times the normal volume of orders during peak sales seasons and has also helped the company respond quickly to COVID-19 and ensure the rapid recovery of production capabilities. © 2022 INFORMS","automatic guided vehicle (AGV); cutting planes; dispatching; e-commerce; Edelman Award; integer program; intelligent warehouse; order fulfillment; order picking; robotic system",{"$nulls":5},"National Natural Science Foundation of China, NSFC, (11471205, 11831002, 61573244, 71825003, 71971132, 72150001)","Funding: D. Ge is partially supported by the National Natural Science Foundation of China [Grants 11831002, 11471205, and 72150001]. J. Gao is partially supported by the National Natural Science Foundation of China [Grants 71971132 and 61573244]. S. He is partially supported by the National Natural Science Foundation of China [Grant 71825003].","Azadeh K, De Koster R, Debjit R, Robotized and automated warehouse systems: Review and recent developments, Transportation Sci, 53, 4, pp. 917-945, (2019); Banker S, Robots in the warehouse: It’s not just Amazon, (2016); Bartholdi JJ, Hackman ST, Warehouse & Distribution Science: Release 0.97, (2016); Bersimas D, Tsitsiklis JN, Introduction to Linear Optimization, (1997); Boysen N, Briskorn D, Emde S, Parts-to-picker based order processing in a rack-moving mobile robots environment, Eur. J. Oper. Res, 262, 2, pp. 550-562, (2017); Burkard RE, Cela E, Linear assignment problems and extensions, Handbook of Combinatorial Optimization, pp. 75-149, (1999); Intelligence drives modernization, JD.com’s unmanned warehouse begins digital China, (2018); Across China, (2017); Cezik T, Graves SC, Liu A, Velocity-based stowage policy for semi-automated fulfillment system, (2021); JD.com sets up first unmanned warehouse in Jiading, (2017); Eisenstein DD, Analysis and optimal design of discrete order picking technologies along a line, Naval Res. Logist, 55, 4, pp. 350-362, (2008); JD.com fully automated warehouse in Shanghai, (2017); JD.com announces establishment of JD Logistics business group, (2017); Media coverage of JD.com's unmanned warehouse, (2018); Huang E, In China, a robot has started delivering packages to people, (2017); Lin J, Singer PW, In China, an e-commerce giant builds the world’s biggest delivery drone, (2017); Mountz MC, D'Andrea R, LaPlante JA, Lyons DP, Mansfield PK, Amsbury BW, Inventory system with mobile drive unit and inventory holder, (2008); Palmer A, Chinese e-commerce company is running a nearly autonomous warehouse with almost ZERO human employees, (2018); Sierksma G, Zwols Y, Linear and Integer Optimization: Theory and Practice, (2015); Wang Z, Sheu J-B, Teo C-P, Xue G, Robot scheduling for mobile-rack warehouses: Human-robot coordinated order picking systems, Production Oper. Management, (2021); Wulfraat M, A supply chain consultant evaluation of Kiva systems (Amazonrobotics), (2012); Wurman PR, D'Andrea R, Mountz M, Coordinating hundreds of cooperative, autonomous vehicles in warehouses, AI Magazine, 29, 1, pp. 9-19, (2008); Yuan R, Cezik T, Graves SC, Stowage decisions in multi-zone storage systems, Internat. J. Production Res, 56, 1–2, pp. 333-343, (2018); Yuan R, Graves SC, Cezik T, Velocity-based storage assignment in semi-automated storage systems, Production Oper. Management, 28, 2, pp. 354-373, (2019)","H. Qin; Research Institute for Interdisciplinary Sciences, Shanghai University of Finance and Economics, Shanghai, 200433, China; email: qinhengle@jd.com; J. Xiao; Department of AI and Big Data, JD Logistics, JD.com, Beijing, 100176, China; email: xiaojun@jd.com; D. Ge; Research Institute for Interdisciplinary Sciences, Shanghai University of Finance and Economics, Shanghai, 200433, China; email: ge.dongdong@shufe.edu.cn; L. Xin; Booth School of Business, University of Chicago, Chicago, Illinois, 60637, United States; email: linwei.xin@chicagobooth.edu; J. Gao; Research Institute for Interdisciplinary Sciences, Shanghai University of Finance and Economics, Shanghai, 200433, China; email: gao.jianjun@shufe.edu.cn; S. He; Research Institute for Interdisciplinary Sciences, Shanghai University of Finance and Economics, Shanghai, 200433, China; email: simaihe@mail.shufe.edu.cn; H. Hu; Research Institute for Interdisciplinary Sciences, Shanghai University of Finance and Economics, Shanghai, 200433, China; email: hu.haodong@shufe.edu.cn; J.G. Carlsson; Department of Industrial and Systems Engineering, University of Southern California, Los Angeles, 90089, United States; email: jcarlsso@usc.edu",null,"INFORMS Inst.for Operations Res.and the Management Sciences",{"$nulls":5},922102.0,null,null,null,"English","Interfaces","Article","Final",null,"Scopus","2-s2.0-85133088523"]
["Zhang X.; Shao P.","Zhang, Xin (57144738600); Shao, Pengfei (57887957500)","57144738600; 57887957500","Logistics Information Traceability Mechanism of Fresh E-Commerce Based on Image Recognition Technology",2022.0,"Applied Bionics and Biomechanics",2022.0,null,2949216.0,null,null,null,1.0,"10.1155/2022/2949216","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137932223&doi=10.1155%2f2022%2f2949216&partnerID=40&md5=8a4a1bdb55523f2b5e401f30e9ab5469","College of Business, Jiaxing University, Zhejiang, Jiaxing, 314001, China; Zhejiang Wanli University, Zhejiang, Ningbo, 315100, China","Zhang X., College of Business, Jiaxing University, Zhejiang, Jiaxing, 314001, China; Shao P., Zhejiang Wanli University, Zhejiang, Ningbo, 315100, China","Logistics migration and movement require precise information updates for traceability and visibility of goods through E-commerce platforms. Computer vision and digital image processing techniques are used for visual identification and tracking through different warehouses and delivery points. In this article, an incessant visualized tracking scheme (IVTS) is designed for identifying and tracking E-commerce logistics throughout the migration points. This scheme endorsed computer vision technology for logistics recognition and labelled data detection. In this scheme, the labelled logistics data is verified for its similarity in different migrating locations and to the endpoint. Based on the dimensional features and regional-pixel similarity factor, it is verified using the deep neural network. This learning process identifies dimensional variations due to logistics displacement and position suppressing the similarity variations. It is performed based on the migration and information available to prevent tracking errors. For the varying locations and logistics displacement, the error pixel regions are identified and trained for possible similarity detection. The proposed scheme effectively improves visual accuracy, tracking maximization, and logistics detection by reducing dimensional errors.  © 2022 Xin Zhang and Pengfei Shao.",null,"Computer vision; Electronic commerce; Errors; Image recognition; Pixels; Commerce platforms; Computer vision technology; Delivery point; Digital image processing technique; Image recognition technology; Information updates; Logistics information; Tracking scheme; Visual identification; Visual Tracking; article; computer vision; deep neural network; electronic commerce; human; image processing; learning; visibility; Deep neural networks",{"$nulls":6},"Fuqua D., Hespeler S., Commodity demand forecasting using modulated rank reduction for humanitarian logistics planning, Expert Systems with Applications, 206, (2022); Kundu T., Sheu J.B., Kuo H.T., Emergency logistics management - Review and propositions for future research, Transportation Research Part E: Logistics and Transportation Review, 1641, (2022); Lei N., Intelligent logistics scheduling model and algorithm based on Internet of Things technology, Alexandria Engineering Journal, 61, 1, pp. 893-903, (2022); Rouari A., Moussaoui A., Chahir Y., Rauf H.T., Kadry S., Deep CNN-based autonomous system for safety measures in logistics transportation, Soft Computing, 25, 18, pp. 12357-12370, (2021); Chen Y.H., Intelligent algorithms for cold chain logistics distribution optimization based on big data cloud computing analysis, Journal of Cloud Computing, 9, 1, pp. 1-12, (2020); Shan P.F., Image segmentation method based on K-mean algorithm, EURASIP Journal on Image and Video Processing, 2018, 1, (2018); Borstell H., Reggelin T., Towards virtual commissioning of image-based information systems for state detection in logistics, IFAC-Papers OnLine, 52, 13, pp. 2463-2470, (2019); Zhao X., Pu F., Wang Z., Chen H., Xu Z., Detection, tracking, and geolocation of moving vehicle from uav using monocular camera, IEEE Access, 7, pp. 101160-101170, (2019); Elngar A.A., Arafa M., Fathy A., Moustafa B., Mahmoudm O., Shaban M., Fawzy N., Image classification based on CNN: A survey, Journal of Cybersecurity and Information Management, 6, 1, pp. 18-50, (2021); Mishal S.M., Murtadha M., Text Classification Using Convolutional Neural Networks, Fusion: Practice and Applications, 7, 1, pp. 53-65, (2022); Huk K., Kurowski M., Innovations and new possibilities of vehicle tracking in transport and forwarding, Wireless Networks, 28, 1, pp. 481-491, (2022); Wei P., Yu X., Di Z., Dai X., Wang B., Zeng Y., Design of Robot Automatic Navigation under Computer Intelligent Algorithm and Machine Vision, Journal of Industrial Information Integration, 281, (2022); Yildiz S., Aydemir O., Memis A., Varli S., A turnaround control system to automatically detect and monitor the time stamps of ground service actions in airports: A deep learning and computer vision based approach, Engineering Applications of Artificial Intelligence, 1141, (2022); Borold A., Teucke M., Rust J., Freitag M., Recognition of car parts in automotive supply chains by combining synthetically generated training data with classical and deep learning based image processing, Procedia CIRP, 93, pp. 377-382, (2020); Castaneda J., Cardona J.F., Martins L.D.C., Juan A.A., Supervised machine learning algorithms for measuring and promoting sustainable transportation and green logistics, Transportation Research Procedia, 58, pp. 455-462, (2021); Li X.T., Wang J., Yang C.Y., Risk prediction in financial management of listed companies based on optimized BP neural network under digital economy, Journal of Manufacturing Processes, (2022); Qiu S., Cheng K., Cui L., Zhou D., Guo Q., A moving vehicle tracking algorithm based on deep learning, Journal of Ambient Intelligence and Humanized Computing, pp. 1-7, (2020); Li D., Deng L., Cai Z., Design of traffic object recognition system based on machine learning, Neural Computing and Applications, 33, 14, pp. 8143-8156, (2021); Ji Z., Kang X., Zhang K., Duan P., Hao Q., A two-stage multi-focus image fusion framework robust to image mis-registration, IEEE Access, 7, pp. 123231-123243, (2019); Yang X., Han M., Tang H., Li Q., Luo X., Detecting defects with support vector machine in logistics packaging boxes for edge computing, IEEE Access, 8, pp. 64002-64010, (2020); Li Z.W., He Y.L., Liu X.Z., Zhou Y.L., Long-term monitoring for track slab in high-speed rail via vision sensing, IEEE Access, 8, pp. 156043-156052, (2020); Dai H., Zeng Y., Wang Z., Lin H., Lin M., Gao H., Song S., Meng M.Q.-H., Prior knowledge-based optimization method for the reconstruction model of multicamera optical tracking system, IEEE Transactions on Automation Science and Engineering, 17, 4, pp. 2074-2084, (2020); Wang T., Hardin R.G.I.V., Ward J.K., Wanjura J.D., Barnes E.M., A smart cotton module tracking and monitoring system for handling logistics and cover damage, Computers and Electronics in Agriculture, 1931, (2022); Schluter M., Lickert H., Schweitzer K., Bilge P., Briese C., Dietrich F., Kruger J., AI-enhanced identification, inspection and sorting for reverse logistics in remanufacturing, Procedia CIRP, 98, pp. 300-305, (2021); Sellevold E., May T., Gangi S., Kulakowski J., McDonnell I., Hill D., Grabowski M., Asset tracking, condition visibility and sustainability using unmanned aerial systems in global logistics, Transportation Research Interdisciplinary Perspectives, 810, (2020); Abosuliman S.S., Almagrabi A.O., Computer vision assisted human computer interaction for logistics management using deep learning, Computers & Electrical Engineering, 961, (2021); Wen Z., Liu D., Liu X., Zhong L., Lv Y., Jia Y., Deep learning based smart radar vision system for object recognition, Journal of Ambient Intelligence and Humanized Computing, 10, 3, pp. 829-839, (2019); Tripicchio P., D'Avella S., Unetti M., Efficient localization in warehouse logistics: A comparison of LMS approaches for 3D multilateration of passive UHF RFID tags, The International Journal of Advanced Manufacturing Technology, 120, 7-8, pp. 4977-4988, (2022); Jiao H., Chen G., Global self-localization of redundant robots based on visual tracking, International Journal of System Assurance Engineering and Management, pp. 1-9, (2021); Roa-Garzon M.A., Gambaro E.F., Florek-Jasinska M., Endres F., Ruess F., Schaller R., Emmerich C., Muenster K., Suppa M., Vision-based solutions for robotic manipulation and navigation applied to object picking and distribution, KI-Künstliche Intelligenz, 33, 2, pp. 171-180, (2019)","X. Zhang; College of Business, Jiaxing University, Jiaxing, Zhejiang, 314001, China; email: zcxin9@163.com",null,"Hindawi Limited",{"$nulls":5},1.1762322E7,null,null,null,"English","Appl. Bionics Biomech.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85137932223"]
["Shi J.","Shi, Jihua (57888679100)",5.78886791E10,"Research on Optimization of Cross-Border e-Commerce Logistics Distribution Network in the Context of Artificial Intelligence",2022.0,"Mobile Information Systems",2022.0,null,3022280.0,null,null,null,2.0,"10.1155/2022/3022280","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137897336&doi=10.1155%2f2022%2f3022280&partnerID=40&md5=ddf211cf358594c46510643dfde440af","Business School, Guangzhou College of Technology and Business, Guangzhou, 510850, China","Shi J., Business School, Guangzhou College of Technology and Business, Guangzhou, 510850, China","The continuous innovation of artificial intelligence technology has led to industrial upgrading and industry transformation in various industries, and e-commerce logistics has borne the brunt. Artificial intelligence relies on the intelligence of a large number of operations and decisions in the process of logistics operations, as well as the integration of transport, storage, distribution, packaging, loading and unloading, and other aspects of the production process and the hierarchy of the system, which has become an important engine to promote the upgrading of logistics equipment and technology, the innovation of production links and processes, the change in the structure of supply and demand of traditional logistics jobs, and the renewal of the traditional form of logistics. The application of artificial intelligence and the development of a new generation of information technology, including big data, has opened the era of intelligent logistics. And the continuous deepening of China's foreign trade makes the demand for cross-border e-commerce logistics surge, and the importance of cross-border e-commerce logistics has been rapidly highlighted. Hence, it becomes urgent to construct a cross-line Internet business coordinated operations improvement model by consolidating man-made consciousness innovation. In view of investigating the activity techniques of cross-line online business coordinated factors, this paper advances the improvement methodology of cross-line web-based business operations advancement way with regard to man-made reasoning. By concentrating on the ongoing circumstance and issues of cross-line web-based business coordinated factor circulation module and consolidating the idea of wise strategies, the appropriation stage, the way transportation stage, and freight conveyance phase of Internet business coordinated factor dissemination activity are advanced, in order to accomplish the motivation behind lessening the expense of end dispersion, working on the effectiveness of dissemination, and expanding consumer loyalty.  © 2022 Jihua Shi.",null,"Artificial intelligence; Digital storage; Electronic commerce; International trade; Websites; Artificial intelligence technologies; Continuous innovation; Cross-border; E- commerces; Industrial upgrading; Loading and unloading; Logistic operations; Logistics distribution networks; Optimisations; Web-based business; Unloading",{"$nulls":6},"Zhu Z., Bai Y., Dai W., Liu D., Hu Y., Quality of e-commerce agricultural products and the safety of the ecological environment of the origin based on 5G Internet of Things technology, Environmental Technology & Innovation, 22, (2021); Wang Z., Zhu H., Optimization of e-commerce logistics of marine economy by fuzzy algorithms, Journal of Intelligent and Fuzzy Systems, 38, 4, pp. 3813-3821, (2020); Ding Y., Jin M., Li S., Feng D., Smart logistics based on the internet of things technology: An overview, International Journal of Logistics Research and Applications, 24, 4, pp. 323-345, (2021); Modgil S., Singh R.K., Hannibal C., Artificial intelligence for supply chain resilience: Learning from Covid-19, International Journal of Logistics Management, (2021); Konstantakopoulos G.D., Gayialis S.P., Kechagias E.P., Vehicle routing problem and related algorithms for logistics distribution: A literature review and classification, Operational Research, 23, pp. 1-30, (2020); Nicola M., Alsafi Z., Sohrabi C., Kerwan A., Al-Jabir A., Iosifidis C., Agha M., Agha R., The socio-economic implications of the coronavirus pandemic (COVID-19): A review, International Journal of Surgery, 78, pp. 185-193, (2020); Morrison W.M., China's economic rise: History, trends, challenges, and implications for the United States, Current Politics and Economics of Northern and Western Asia, 28, 23, pp. 189-242, (2019); Mosteanu N.R., Faccia A., Ansari A., Shamout M.D., Capitanio F., Sustainability integration in supply chain management through systematic literature review, Calitatea, 21, 176, pp. 117-123, (2020); Huang J., Yang W., Tu Y., Financing mode decision in a supply chain with financial constraint, International Journal of Production Economics, 220, (2020); Shen Z., Research on the application of computer internet of things in intelligent logistics management, Journal of Physics: Conference Series, 1648, 4, (2020); Wen J., He L., Zhu F., Swarm robotics control and communications: Imminent challenges for next generation smart logistics, IEEE Communications Magazine, 56, 7, pp. 102-107, (2018); Wu G., Research on the development path of logistics management innovation in e-commerce environment, IOP Conference Series: Earth and Environmental Science, 714, 4, (2021); Ali S.S., Kaur R., Effectiveness of corporate social responsibility (CSR) in implementation of social sustainability in warehousing of developing countries: A hybrid approach, Journal of Cleaner Production, 324, (2021); Dutta P., Talaulikar S., Xavier V., Kapoor S., Fostering reverse logistics in India by prominent barrier identification and strategy implementation to promote circular economy, Journal of Cleaner Production, 294, (2021); Russell S., Human Compatible: Artificial Intelligence and the Problem of Control, (2019); Guo S., Zhang X., Zheng Y., Du Y., An autonomous path planning model for unmanned ships based on deep reinforcement learning, Sensors, 20, 2, (2020); Zhang X., Zhou M., Liu H., Hussain A., A cognitively inspired system Architecture for the mengshi cognitive vehicle, Cognitive Computation, 12, 1, pp. 140-149, (2020); Gibbs M.T., Technology requirements, and social impacts of technology for at-scale coral reef restoration, Technology in Society, 66, (2021); Lorenc A., Lerher T., PickupSimulo-prototype of intelligent software to support warehouse managers decisions for product allocation problem, Applied Sciences, 10, 23, (2020); Zhang D., Pee L.G., Cui L., Artificial intelligence in E-commerce fulfillment: A case study of resource orchestration at Alibaba's Smart Warehouse, International Journal of Information Management, 57, (2021); Wang F., Lu E., Wang Y., Qiu G., Lu H., Efficient stereo visual simultaneous localization and mapping for an autonomous unmanned forklift in an unstructured warehouse, Applied Sciences, 10, 2, (2020); Ceder A.A., Urban mobility and public transport: Future perspectives and review, International Journal on the Unity of the Sciences, 25, 4, pp. 455-479, (2021); Abduljabbar R., Dia H., Liyanage S., Bagloee S.A., Applications of artificial intelligence in transport: An overview, Sustainability, 11, 1, (2019); Fatemidokht H., Rafsanjani M.K., Gupta B.B., Hsu C.H., Efficient and secure routing protocol based on artificial intelligence algorithms with UAV-assisted for vehicular ad hoc networks in intelligent transportation systems, IEEE Transactions on Intelligent Transportation Systems, 22, 7, pp. 4757-4769, (2021); Zhang K., Leng S., Peng X., Pan L., Maharjan S., Zhang Y., Artificial intelligence inspired transmission scheduling in cognitive vehicular communications and networks, IEEE Internet of Things Journal, 6, 2, pp. 1987-1997, (2019); Kelly C.J., Karthikesalingam A., Suleyman M., Corrado G., King D., Key challenges for delivering clinical impact with artificial intelligence, BMC Medicine, 17, 1, pp. 195-199, (2019); Klumpp M., Zijm H., Logistics innovation and social sustainability: How to prevent an artificial divide in human-computer interaction, Journal of Business Logistics, 40, 3, pp. 265-278, (2019); Kohl M., Knauer S., Fottner J., Industry 4.0 in logistics and associated employee competencies-a technology providers' perspective, International Conference on Human Interaction and Emerging Technologies, pp. 377-383, (2020); Bistron M., Piotrowski Z., Artificial intelligence applications in military systems and their influence on sense of security of citizens, Electronics, 10, 7, (2021); Ramadoss T.S., Alam H., Seeram R., Artificial intelligence and Internet of Things enabled circular economy, International Journal of Engineering Science, 7, 9, pp. 55-63, (2018)","J. Shi; Business School, Guangzhou College of Technology and Business, Guangzhou, 510850, China; email: shijihua@gzgs.edu.cn",null,"Hindawi Limited",{"$nulls":5},"1574017X",null,null,null,"English","Mob. Inf. Sys.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85137897336"]
["Novitasari N.; Anwar N.","Novitasari, Nia (57202990995); Anwar, Nashirudin (57917993200)","57202990995; 57917993200","Enhanced Technology for Logistics Courier Delivery Using RFID Label to Minimize Processing Time",2022.0,"International Journal on Informatics Visualization",6.0,3.0,null,610.0,617.0,7.0,0.0,"10.30630/joiv.6.3.1229","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85139431323&doi=10.30630%2fjoiv.6.3.1229&partnerID=40&md5=44749a1cb087c0c769f0b92556f5afaa","Department of Logistics Engineering, Telkom University, Bandung, 40257, Indonesia; Sefatech.id, Bandung, 40192, Indonesia","Novitasari N., Department of Logistics Engineering, Telkom University, Bandung, 40257, Indonesia; Anwar N., Sefatech.id, Bandung, 40192, Indonesia","Courier services have become a sector that has experienced a growth spurt during the Covid-19 pandemic. The soaring growth of courier services is due to e-commerce in Indonesia. Increased people's digital activities show this during the pandemic, including online or online shopping. Data from the Indonesian Ministry of Finance shows that purchase transactions via e-commerce increased 18.1 percent to 98.3 million, with a total transaction value of 9.9 percent to Rp20.7 trillion. Fast and efficient delivery and pick-up of goods is the core operation of courier services. The biggest challenge for courier service providers is how to compete with other companies that offer the same type of service. Service users are increasingly demanding the security and reliability of delivery services so that they can meet the expectations of service users. The expectations of service users used as targets for company achievement are (1) reliability (on time, accuracy, integrity), (2) convenience (collecting units, delivery coverage, operating hours), (3) services, and (4) cost. Based on the activities in courier services, the potential for errors or inefficiencies in processing time is in the pre-delivery activities. In the pre-delivery activity is also the initial activity used to input the data base, collect goods, distribute goods and so on. This research proposes that RFID Label technology can overcome errors and increase process time efficiency in shipping goods on courier services, especially in pre-delivery and delivery activities. © 2022, Politeknik Negeri Padang. All rights reserved.","Courier services; intelligent technology; IoT; logistics; RFID label",{"$nulls":7},"Indonesia C., Bisnis Logistik dan Jasa Kurir Melejit di Tengah Corona, CNN Indonesia, (2020); Jintana J., Sopadang A., Ramingwong S., Idea selection of new service for courier business: The opportunity of data analytics, Int. J. Eng. Bus. Manag, 13, pp. 1-20, (2021); Musyafah A. A., Khasna H. W., Turisno B. E., Perlindungan Konsumen Jasa Pengiriman Barang Dalam Hal Terjadi Keterlambatan Pengiriman Barang, Law Reform, 14, 2, (2018); Izzah N., Rifai D., Yao L., Relationship-courier partner logistics and e-commerce enterprises in Malaysia: A review, Indian J. Sci. Technol, 9, 9, pp. 1-10, (2016); Award T. B., Top Brand Index Courier Service 2021, Top Brand Award, (2021); Astuti J., Fatma E., Evaluasi Pemilihan Penyedia Jasa Kurir Berdasarkan Metode Analytical Hierarchy Process (Ahp), J. Manaj. Ind. Dan Logistik, 1, 1, (2017); Muhammad M. A., Yusoff N. S., Tharra N., Ahmad F., Melan M., Logistics Service Quality of Courier Providers Among Student in Uum, pp. 275-286, (2017); Vidyapeetham A. V., Assessment and Improvement of processes using customer-centric tools in the context of Courier Service; Chopra S., Meindl P., Kalra D. V., Supply Chain Management Strategy, Planning, and Operation, 6, (2016); Leon D., Farahana I., Kamsin B., Logistics System By Using; Rfid Technology,” vol. 17, no. 7, pp. 8659–8667, 2020. [11] A. Gulc, \"Determinants of courier service quality in e-commerce from customers' perspective, Qual. Innov. Prosper, 24; Gulc A., Multi-stakeholder perspective of courier service quality in B2C e-commerce, PLoS One, 16, 5, pp. 1-18, (2021); Agu MN, Ci N., Bo O., Enhancing Courier Service with the Development of an Interactive Mobile App in Android Platform, IOSR J. Mob. Comput. Appl, 2, 2, pp. 2394-2442, (2015); Emmanuel Prince B., Bakon K. A., A Study on The Need to Implement a Courier Service Application on Android Smartphones, Int. J. Inf. Syst. Eng, 4, 2, pp. 28-42, (2016); Ericko Y., Pengaruh Logistic Service Quality Terhadap Kepuasan Dan Loyalitas Konsumen Kentucky Fried Chicken Di Surabaya, Br. Food J, 101, 5–6, pp. 493-496, (2015); Arabelen G., Kaya H. T., Assessment of logistics service quality dimensions: a qualitative approach, J. Shipp. Trade, 6, 1, pp. 1-13, (2021); Todorovic V., Neag M., Lazarevic M., On the usage of RFID tags for tracking and monitoring of shipped perishable goods, Procedia Eng, 69, pp. 1345-1349, (2014); Khan S., Impact of Information Technology on Internal Supply Chain Management Implementation of RFID Tags, Eur. J. Bus. Manag. Res, 5, 2, pp. 1-9, (2020); Muzhir S., Al-Ani M., Packages Tracking Using RFID Technology, Int. J. Bus. ICT, 1, 3–4, (2015); Ahmad M., Akmal M., Karim A., Hafiz M., Bin Zaidi A., RFID Application in Courier Services, Int. J. Perceptive Cogn. Comput; Chanchaichujit J., Balasubramanian S., Charmaine N. S. M., A systematic literature review on the benefit-drivers of RFID implementation in supply chains and its impact on organizational competitive advantage, Cogent Bus. Manag, 7, 1, pp. 108-112, (2020); Zhang X., Dong Q., Hu F., Applications of RFID in logistics and supply chains: An overview, ICLEM 2012 Logist. Sustain. Econ. Dev.-Technol. Manag. Effic.-Proc. 2012 Int. Conf. Logist. Eng. Manag, pp. 1399-1404, (2012); Desingh V., Panchuk P., An Overview of RFID Technology Applications and Diffusion in Supply Chain Management, Int. J. Pure Appl. Math, 119, 10, pp. 1291-1305, (2018); Kurniawan D. A., Analisis Penerapan Rfid Untuk Menurunkan Biaya Logistik, J. Transp. Multimoda, 13, 1, pp. 11-20, (2017); Kgobe P., Ozor P. A., Integration of radio frequency identification technology in supply chain management: A critical review, Oper. Supply Chain Manag, 14, 4, pp. 289-300, (2021); Zhou W. H., De Jiang N., Yan C. C., Research on Anti-Collision Algorithm of RFID Tags in Logistics System, Procedia Comput. Sci, 154, pp. 460-467, (2018)","N. Novitasari; Department of Logistics Engineering, Telkom University, Bandung, 40257, Indonesia; email: novitasarinia@telkomuniversity.ac.id",null,"Politeknik Negeri Padang",{"$nulls":5},2.5499904E7,null,null,null,"English","Int. J. Inform. Vis.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85139431323"]
["Muangpan T.","Muangpan, Thanyaphat (57207950048)",5.7207950048E10,"Customer satisfaction indicators in transportation and distribution factors of online shopping company",2022.0,"Cogent Business and Management",9.0,1.0,2108217.0,null,null,null,1.0,"10.1080/23311975.2022.2108217","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135930191&doi=10.1080%2f23311975.2022.2108217&partnerID=40&md5=5365f070cd710b82d437c10a194729b4","Faculty of Logistics, Burapha University, Saen Suk, Thailand","Muangpan T., Faculty of Logistics, Burapha University, Saen Suk, Thailand","The commercial business model has changed to electronic market channels and electronic distribution. Electronic commerce (E-commerce) and shopping online generate profits and reduce costs. Many businesses are creating new channels using digital network technology. This research explores the factors and indicators of customer satisfaction for transportation and distribution in an online shopping company. Survey research and exploratory factor analysis (EFA) is applied to analyse the data collection concerning Chinese customers in Thailand who have used the services of an online shopping company. This research tested the results for validity, reliability, and Kaiser-Meyer-Olkin (KMO) statistical approach. Factor loadings confirm the factor explanations and the common threshold of 0.7. Furthermore, customer satisfaction in transportation and the distribution management model achieves with the three main factors and fifteen key indicators. The three factors are the Responsibility of Product and delivery in transportation and distribution, customer services in transportation and distribution, and customer communication in transportation and distribution. These fifteen indicators and the information are to improve the e-commerce business model to create a competitive advantage and increase market share. © 2022 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license.","Customer satisfaction indicators; distribution; electronic commerce (e-commerce); shopping online; Transportation",{"$nulls":7},"Chang H.H., Wang H.W., The moderating effect of customer perceived value on online shopping behaviour, Online Information Review, 35, 3, pp. 333-313, (2011); Chiang W.Y., To establish online shoppers’ markets and rules for dynamic CRM systems An empirical case study in Taiwan, Internet Research, 22, 5, pp. 613-625, (2012); Hair J.F., Black W.C., Babin B.J., Anderson R.E., Tatham R., Multivariate data analysis, (2006); Janjevic M., Winkenbach M., Characterising urban last-mile distribution strategies in mature and emerging e-commerce markets, Transportation Research Part A, 133, pp. 164-196, (2020); Kazancoglu I., Aydin H., An investigation of consumers’ purchase intentions towards omni-channel shopping A qualitative exploratory study, International Journal of Retail & Distribution Management, 46, 10, pp. 959-976, (2018); Kennedy A., Coughlan J., Online shopping portals: An option for traditional retailers?, International Journal of Retail & Distribution Management, 34, 7, pp. 516-528, (2006); Khan M.A., Zubair S.S., Malik M., An assessment of e-service quality, e - satisfaction and e-loyalty Case of online shopping in Pakistan, South Asian Journal of Business Studies, 8, 3, pp. 283-302, (2019); Kumar A., Kashyap A.K., Leveraging utilitarian perspective of online shopping to motivate online shoppers, International Journal of Retail & Distribution Management, 46, 3, pp. 247-263, (2018); Lim H., Shiode N., The impact of online shopping demand on physical distribution networks: A simulation approach, International Journal of Physical Distribution & Logistics Management, 41, 8, pp. 732-749, (2011); Liu M., Zhang Q., Gao S., Huang J., The spatial aggregation of rural e-commerce in China: An empirical investigation into Taobao Villages, Journal of Rural Studies, 80, pp. 403-417, (2020); Liu M., Min S., Ma W., Liu T., The adoption and impact of E-commerce in rural China: Application of an endogenous switching regression model, Journal of Rural Studies, 83, pp. 106-116, (2021); Maskey R., Fei J., Nguyen H.O., Use of exploratory factor analysis in maritime research, The Asian Journal of Shipping and Logistics, 34, 2, pp. 91-111, (2018); Mentzer J.T., Gomes R., Krapfel R.E., Physical distribution service: A fundamental marketing concept?, Journal of the Academy of Marketing Science, 17, 1, pp. 53-62, (1989); Morganosky M.A., Cude B.J., Consumer response to online grocery shopping, International Journal of Retail & Distribution Management, 28, 1, pp. 17-26, (2000); Muangpan T., Suthiwartnarueput K., Key performance indicators of sustainable port: Case study of the eastern economic corridor in Thailand, Cogent Business & Management, 6, 1, pp. 1-18, (2019); Nogueira G.P.M., Rangel J.J.A., Shimoda E., Sustainable last-mile distribution in B2C e-commerce: Do consumers really care?, Cleaner and Responsible Consumption, 3, pp. 1-9, (2021); O'Driscoll F., What matters most: An exploratory multivariate study of satisfaction among first year hotel/hospitality management students, Quality Assurance in Education, 20, 3, pp. 237-258, (2012); Qin Y., Muangpan T., Assessment of customer satisfaction factors in transportation and distribution: A case study of Jing Dong company, Academic Journal of Graduate School Sripatum University, 18, 1, pp. 169-181, (2021); Shi H., Sun L., Teng Y., Hu X., An online intelligent vehicle routing and scheduling approach for B2C e-commerce urban logistics distribution, Procedia Computer Science, 159, pp. 2533-2542, (2019); Shun W.J., The Third-Party Logistics Service Quality Evaluation System Based on Customer Satisfaction, Logistics Engineering and Management, 6, pp. 17-19, (2018); Sreeram A., Kesharwani A., Desai S., Factors affecting satisfaction and loyalty in online grocery shopping: An integrated model, Journal of Indian Business Research, 9, 2, pp. 107-132, (2017); Weltevreden J.W.J., B2c e-commerce logistics: The rise of collection-and-delivery points in The Netherlands, International Journal of Retail & Distribution Management, 36, 8, pp. 638-660, (2008); Yamane T., Statistics, An IntroductoryAnalysis, (1967); Yu R.C., Research on Service Quality Evaluation of E-commerce Oriented Distribution Center, Journal of Harbin University of Commerce (Natural Sciences Edition), 26, 6, pp. 718-722, (2010); Yu Y., Yu C., Xu G., Zhong R.Y., Huang G.Q., An operation synchronisation model for distribution center in E-commerce logistics service, Advanced Engineering Informatics, 43, pp. 1-12, (2020); Zheng Q., Chen J., Zhang R., Wang H.H., What factors affect Chinese consumers’ online grocery shopping? Product attributes e-vendor characteristics and consumer perceptions, China Agricultural Economic Review, 12, 2, pp. 193-213, (2020); Zissis D., Aktas E., Bourlakis M., Collaboration in urban distribution of online grocery orders, The International Journal of Logistics Management, 29, 4, pp. 1196-1214, (2018)","T. Muangpan; Faculty of Logistics, Burapha University, Saen Suk, Thailand; email: thanya.donut@gmail.com",null,"Cogent OA",{"$nulls":5},2.3311975E7,null,null,null,"English","Cogent Bus. Manag.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85135930191"]
["Sonia; Chidambaran S.","Sonia (57211843294); Chidambaran, Subramanian (58094056900)","57211843294; 58094056900","Time paradox in transportation problems",2022.0,"International Journal of Operational Research",45.0,4.0,null,540.0,552.0,12.0,0.0,"10.1504/IJOR.2020.10034414","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85147559158&doi=10.1504%2fIJOR.2020.10034414&partnerID=40&md5=4154ab81e067104aaa4551d8ebf30a78","Indian Institute of Management, Lucknow, India","Sonia, Indian Institute of Management, Lucknow, India; Chidambaran S., Indian Institute of Management, Lucknow, India","The boom in e-commerce industry in recent years is reshaping delivery landscape and logistics needs to keep pace with this rapid e-commerce growth. One of the most important customer satisfaction KPIs in the e-commerce industry is to reduce the delivery time and is a key focus area for the market players. The present paper attempts to address this challenge by introducing the concept of a paradox in a time minimising transportation problem (TMTP) which is a concave minimisation problem. The paradoxical situations in cost minimising transportation problems, fixed charge transportation problems, minimum cost flow problems and in many other variants of transportation problem have been extensively researched and well applied except for TMTPs. After defining the time paradox in a TMTP, we develop the condition of its existence. Further, a comparative study of paradox for a cost minimising and time minimising transportation problems has also been carried out. We then discuss the immunity conditions for a time matrix. At the end, the method for finding the best paradoxical solution along with practical applications is also presented. Copyright © 2022 Inderscience Enterprises Ltd.","bottleneck transportation problem; BTP; time minimising transportation problem; time paradox; TMTP",{"$nulls":7},"Adlakha V., Kowalski K., A quick sufficient solution to the more-for-less paradox in the transportation problem, Omega, 26, 4, pp. 541-547, (1998); Adlakha V., Kowalski K., Vemuganti R., Lev B., More-for-less algorithm for fixed-charge transportation problems, Omega, 35, 1, pp. 116-127, (2007); Ahuja R.K., Algorithms for the minimax transportation problem, Naval Research Logistics Quarterly, 33, 4, pp. 725-739, (1986); Al Kautsar M.M., Silalahi B.P., Guritman S., Paradox in a d-dimensional transportation problem, International Journal of Pure and Applied Mathematics, 118, 3, pp. 547-557, (2018); Appa G.M., Reply to l.g.proll, Operational Research Quarterly, 24, pp. 636-639, (1973); Arora S., Ahuja A., A paradox in a fixed charge transportation problem, Indian Journal of Pure and Applied Mathematics, 31, 7, pp. 809-822, (2002); Arora S., Puri M.C., On lexicographic optimal solutions in transportation problems, Optimization, 39, 4, pp. 383-403, (1997); Arsham H., Postoptimality analyses of the transportation problem, Journal of The Operational Research Society, 43, 2, pp. 121-139, (1992); Arsham H., Oblak M., Perturbation analysis of general lp models: a unified approach to sensitivity, parametric, tolerance, and more-for-less analysis, Math. Comput. Model, 13, 8, pp. 79-102, (1990); Arvidsson N., The milk run revisited: a load factor paradox with economic and environmental implications for urban freight transport, Transportation Research Part A: Policy and Practice, 51, pp. 56-62, (2013); Bagloee S.A., Johansson K.H., Asadi M., A hybrid machine-learning and optimization method for contraflow design in post-disaster cases and traffic management scenarios, Expert Systems with Applications, 124, pp. 67-81, (2019); Charnes A., Klingman D., The more-for-less paradox in the distribution model, Cachiers du Centre dEtudes de Recherche Operationelle, 13, 1, pp. 11-22, (1971); Charnes A., Duffuaa S., Ryan M., The more-for-less paradox in linear programming, European Journal of Operational Research, 31, 2, pp. 194-197, (1987); D'Ambrosio C., Gentili M., Cerulli R., The optimal value range problem for the interval (immune) transportation problem, Omega, (2019); Deineko V.G., Klinz B., Woeginger G.J., Which matrices are immune against the transportation paradox?, Discrete Applied Mathematics, 130, 3, pp. 495-501, (2003); Dhamala T.N., Adhikari I.M., On evacuation planning optimization problems from transit-based perspective, International Journal of Operations Research, 15, 1, (2018); Dibaei M., Ghaffari A., More flow for lesser cost in a non-linear transportation problem, South Asian Journal of Mathematics, 5, 4, pp. 172-182, (2015); Garfinkel R.S., Rao M.R., The bottleneck transportation problem, Naval Research Logistics Quarterly, 18, 4, pp. 465-472, (1971); Giri P.K., Maiti M.K., Maiti M., Simulation approach to solve fuzzy fixed charge multi-item solid transportation problems under budget constraint, International Journal of Operational Research, 32, 1, pp. 56-91, (2018); Gupta A., Puri M.C., More-for-less paradox in minimum cost network flow problem, Optimization, 33, 2, pp. 167-177, (1995); Gupta K., Arora M.R., More for less method to minimize the unit transportation cost of a capacitated transportation problem with bounds on rim conditions, OPSEARCH, 54, 3, pp. 460-474, (2017); Gupta A., Khanna S., Puri M.C., Paradoxical situations in transportation problems, Cahiers du Centre dEtudes de Recherche Operationnelle, 34, 1, pp. 37-49, (1992); Gupta A., Khanna S., Puri M.C., A paradox in linear fractional transportation problems with mixed constraints, Optimization, 27, 4, pp. 375-387, (1993); Hammer P.L., Time-minimizing transportation problems, Naval Research Logistics Quarterly, 16, 3, pp. 345-357, (1969); Hammer P.L., Communication on the bottleneck transportation problem and some remarks on the time transportation problem, Naval Research Logistics Quarterly, 18, 4, pp. 487-490, (1971); Inzlicht M., Shenhav A., Olivola C.Y., The effort paradox: effort is both costly and valued, Trends in Cognitive Sciences, 22, 4, pp. 337-349, (2018); Javaid S., Jalil S.A., Asim Z., A model for uncertain multi-objective transportation problem with fractional objectives, International Journal of Operational Research, 14, 1, pp. 11-25, (2017); Kavitha K., Pandian P., Sensitivity analysis of costs in interval transportation problems, Applied Mathematical Sciences, 6, 92, pp. 4569-4576, (2012); Kumar H., Kumar P., Sharma M., A genetic algorithm for a flow shop scheduling problem with breakdown interval, transportation time and weights of jobs, International Journal of Operational Research, 35, 4, pp. 470-483, (2019); Pandian P., Natarajan G., A new method for finding an optimal more for less solution of transportation problems with mixed constraints, International Journal of Contemporary Mathematical Sciences, 5, 19, pp. 931-942, (2010); Porchelvi R.S., Anitha M., Paradox in a linear multi objective transportation problem, Annals of Pure and Applied Mathematics, 15, 2, pp. 185-192, (2017); Ryan M.J., Applications of a more for less result to labour markets and to auctions, Applied Economics Letters, 12, 8, pp. 485-488, (2005); Shiripour S., Mahdavi-Amiri N., Mahdavi I., A nonlinear model for location-allocation-routing problem in transportation network with intelligent travel times, International Journal of Operational Research, 29, 3, pp. 400-431, (2017); Sonia, Khandelwal A., Pseudo paradox in minimum cost network flow problem, International Journal of Operational Research, 30, 2, pp. 220-232, (2017); Szwarc W., The transportation paradox, Naval Research Logistics Quarterly, 18, 2, pp. 185-202, (1971)","Sonia; Indian Institute of Management, Lucknow, India; email: Sonia@iiml.ac.in",null,"Inderscience Publishers",{"$nulls":5},1.7457645E7,null,null,null,"English","Int. J. Oper. Res.","Article","Final",null,"Scopus","2-s2.0-85147559158"]
["Ma X.; Wang F.","Ma, Xuan (57916866900); Wang, Fan (57917057800)","57916866900; 57917057800","Logistic Distribution Route Optimization Based on RFID and Sensor Technology",2022.0,"Wireless Communications and Mobile Computing",2022.0,null,7599539.0,null,null,null,0.0,"10.1155/2022/7599539","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85139364359&doi=10.1155%2f2022%2f7599539&partnerID=40&md5=276eed3ecd1a48b3b58d6c92450ea2ed","Shijiazhuang Post & Telecommunication Technical College, Hebei, Shijiazhuang, 050021, China","Ma X., Shijiazhuang Post & Telecommunication Technical College, Hebei, Shijiazhuang, 050021, China; Wang F., Shijiazhuang Post & Telecommunication Technical College, Hebei, Shijiazhuang, 050021, China","In order to solve the problem that the traditional e-commerce logistic distribution path optimization algorithm takes a long time to find the optimal path, this paper presents the best ways for exporting based on RFID and sensor technology. First, the integration algorithm is used to divide the logistic area; then, the purpose of various goals to improve the performance of the export consists of five things: Measuring weight, measuring time, measuring the importance of customers, window measuring time, and general measurement method. Finally, determine the weight distribution target and find ways to better the target according to the differences in e-commerce logistics to improve the efficiency of e-commerce logistic distribution methods. Experimental results show that the optimal time to find the optimal method is less than 2 minutes, while the custom algorithm takes 3 minutes to find the optimal method. Conclusion. The logistic distribution optimization algorithm based on RFID and sensor technology takes less time to find a better way than the traditional process and can meet the needs of e-commerce logistic distribution layer standard optimization. © 2022 Xuan Ma and Fan Wang.",null,"Electronic commerce; Distribution route; E- commerces; Logistic distributions; Optimal methods; Optimal paths; Optimization algorithms; Path optimizations; RFID Technology; Route optimization; Sensor technologies; Optimization",{"$nulls":6},"Yang S., Optimization of urban logistics distribution path under dynamic traffic network, International Core Journal of Engineering, 6, 1, pp. 243-248, (2020); Somkereki A.E., Ioan P., Historical landmarks of the management of major urban logistics projects in imperial timisoara, Analecta Technica Szegedinensia, 14, 1, pp. 1-8, (2020); Liu W., Route optimization for last-mile distribution of rural e-commerce logistics based on ant colony optimization, Access, 8, pp. 12179-12187, (2020); Ondieki K.M., Swaption pricing under libor market model using Monte-Carlo method with simulated annealing optimization, Journal of Mathematical Finance, 12, 2, pp. 435-462, (2022); Ottow-Henning E., Keij B., Does group intervention make a difference for the speech sound development of dutch pre-school children with developmental language disorder?, International Journal of Speech-Language Pathology, 22, 6, pp. 696-707, (2020); Muhammad G., Alhussein M., Convergence of artificial intelligence and internet of things in smart healthcare: A case study of voice pathology Detection, Access, 9, pp. 89198-89209, (2021); Xiao W., Liu C., Wang H., Zhou M., Muhammad G., Blockchain for secure-gas: Blockchain-powered secure natural gas iot system with ai-enabled gas prediction and transaction in smart city, IEEE Internet of Things Journal, 8, 8, pp. 6305-6312, (2020); Chouhan B., Tak N., Gehlot H.S., Phenotypic characterization and molecular identifi-cation of n 2 fixing symbiotic rhizobia of Dichrostachys cinerea from arid and semi-arid soils of Rajasthan, India, Plant Archives, 20, 2, pp. 5899-5906, (2020); Chen S., Ning Z., Lin W., Chen S., Application of intelligent blood temperature and humidity monitoring system in blood station, Natural Science, 14, 5, pp. 186-192, (2022); Li H., Liu Y., Yang J., A novel fcs-mpc method of multi-level apf is proposed to improve the power quality in renewable energy generation connected to the grid, Sustainability, 13, 8, (2021); Rus C., Negru N., Patrascoiu N., Low-cost system to acquire environmental parameters in urban areas in the context of iot, Journal of Environmental Protection and Ecology, 20, 3, pp. 1451-1461, (2019); Mammadova T., Writing and information literacy: Major steps to impede the use of unreliable sources for academic purposes, Azerbaijan Journal of Educational Studies, 1, 1, pp. 163-176, (2020); Tri P., High quality human resources development to satisfied the globalization in Vietnam: Defiances and solutions, Psychology (Savannah, Ga.), 58, 2, pp. 1-12, (2021); Zhang Y., Zuo T., Fang L., Li J., Xing Z., An improved mahakil oversampling method for imbalanced dataset classification, IEEE Access, 9, pp. 16030-16040, (2020); Sharma A., Kumar R., A framework for pre-computated multi-constrained quickest QoS path algorithm, Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 9, 3-6, pp. 73-77, (2017); Jayakumar J., Conceptual implementation of artificial intelligent based E-mobility controller in smart city environment, Wireless Communications and Mobile Computing, 2021, (2021); Chen J., Liu J., Liu X., Xiaoyi X., Zhong F., Decomposition of toluene with a combined plasma photolysis (CPP) reactor: Influence of UV irradiation and byproduct analysis, Plasma Chemistry and Plasma Processing, 41, 1, pp. 409-420, (2021); Huang R., Yan P., Yang X., Knowledge map visualization of technology hotspots and development trends in China's textile manufacturing industry, IET Collaborative Intelligent Manufacturing, 3, 3, pp. 243-251, (2021); Zhang Q., Relay vibration protection simulation experimental platform based on signal reconstruction of MATLAB software, Nonlinear Engineering, 10, 1, pp. 461-468, (2021)","F. Wang; Shijiazhuang Post & Telecommunication Technical College, Shijiazhuang, Hebei, 050021, China; email: 201812210202026@zcmu.edu.cn",null,"Hindawi Limited",{"$nulls":5},1.5308669E7,null,null,null,"English","Wireless Commun. Mobile Comput.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85139364359"]
["Peters C.; Thomas J.","Peters, Cara (35607576200); Thomas, Jane (55493191600)","35607576200; 55493191600","Black Friday: Has the game changed?",2022.0,"Journal of Global Fashion Marketing",13.0,4.0,null,344.0,359.0,15.0,0.0,"10.1080/20932685.2022.2085600","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85133542809&doi=10.1080%2f20932685.2022.2085600&partnerID=40&md5=d19706250e9a8a8f16297dd408d73a0a","Department of Management and Marketing, Winthrop University, Rock Hill, SC, United States","Peters C., Department of Management and Marketing, Winthrop University, Rock Hill, SC, United States; Thomas J., Department of Management and Marketing, Winthrop University, Rock Hill, SC, United States","Previous research on Black Friday consumption rituals has focused on planning and shopping for an in-store customer experience. In recent times, however, consumer perceptions and shopping behaviors related to Black Friday have begun to shift. Consumers are shopping earlier, moving online, taking advantage of delivery and curbside pickup, and expecting retailers to provide a safe, socially distanced shopping experience. This study was grounded in theory from social change within the field of sociology. The purpose of this study was to examine how various factors, such as the pandemic, retailer strategies, online shopping, cultural trends are reshaping consumers’ views and shopping behaviors related to Black Friday. Data were collected via 31 phenomenological interviews with consumers who have shopped on Black Friday in the past. Results were analyzed according to the protocol for phenomenology and were presented in the form of themes that emerged from the data. Overall, consumers believed that Black Friday had changed and had become less impactful. Changes were due to store policies and procedures around safety during the pandemic, retailers extending the number of days and weeks for Black Friday shopping, the convenience and breadth of products available among a plethora of online shopping alternatives, the impact of the economy on the ability to shop, and how the name Black Friday has negative associations for some shoppers. Managerial implications for retailers were discussed as the game of Black Friday has changed. Implications included strategies retailers can use to entice consumers as they try to revamp Black Friday and engage shoppers in the future. © 2022 Korean Scholars of Marketing Science.","Black Friday; consumption rituals; holiday shopping; retail store strategies; sales promotion strategies",{"$nulls":7},"Adams K., How local retailers are reinventing the black Friday shopping experience during Covid-19, (2020); Bartiromo M., Black Friday 2020: Coronavirus pandemic shopping trends force retailers to rethink holiday shopping, (2020); Bell G.C., Weathers M.R., Hastings S.O., Peterson E.B., Investigating the celebration of black Friday as a communication ritual, Journal of Creative Communications, 9, 3, pp. 235-251, (2014); Cain A., Black Friday has been a shopping bonanza for the last two decades. Here’s how it has evolved over the years, (2019); Creswell J.W., Qualitative inquiry and research design: Choosing among five traditions, (1998); Dupuy B., How black Friday became associated with sales, (2019); Frank A., What’s in a name? for some brands, a racist history that needs to be toppled, (2020); Gatti C., The dark history of black Friday; Groenewald T., A phenomenological research design illustrated, International Journal of Qualitative Methods, 3, 1, pp. 42-55, (2004); Howland D., Black Friday is early again this year, and maybe forever, (2021); Jaiyeoba O., Tendai D.S., Makanyeza C., Black Friday shopping behavior among generation y consumers in Botswana: An application of the stimulus-organism-response theory, African Journal of Business and Economic Research, 15, 4, pp. 45-69, (2020); Kapner S., Black Friday shopping is back, but the doorbusters aren’t, (2021); Kempen E., Tobias-Mamina R.J., Applying behavioral reasoning theory to South African female consumers’ emerging apparel-shopping behavior during COVID-19, Journal of Global Fashion Marketing, (2022); Kovacs A., Tomas S.T., Black Friday shopping in Hungary, Scientific Papers of the University of Pardubice, Series D XXVII, 46, pp. 18-29, (2019); Kwon H.J., Brinthaupt T.M., The motives, characteristics and experiences of US black Friday shoppers, Journal of Global Fashion Marketing, 6, 4, pp. 292-302, (2015); Lee J.S., Chun S., Choi J., South Korean consumers’ experiences and underlying shopping mechanism of black Friday, Journal of Distribution Science, 17, 11, pp. 63-72, (2019); Lennon S.J., Johnson K.K.P., Lee J., A perfect storm for consumer misbehavior: Shopping on black Friday, Clothing and Textiles Research Journal, 29, 2, pp. 119-134, (2011); Lennon S.J., Kim M., Lee J., Johnson K.K.P., Effects of emotions, sex, self-control, and public self-consciousness on black Friday misbehavior, Journal of Global Fashion Marketing, 8, 3, pp. 163-179, (2017); Lennon S.J., Kim M., Lee J., Johnson K.K.P., Consumer emotions on black Friday: Antecedents and consequences, Journal of Research for Consumers, 32, (2018); Lennox A., Shields A., Guilar P., A very British black Friday: Retailers lose out as black friday becomes the domain of discounters, Journal of Brand Strategy, 5, 3, pp. 282-288, (2016); Lobao L., Rulli J., Economic change and its extraeconomic consequences, Environment & Planning, 28, 4, pp. 606-611, (1996); Logan L.A., An analysis of the black Friday consumer, (2014); Lunden I., Black Friday online shopping comes in $9B, $3.6B on smartphones, Techcrunch Com, (2020); Mackenzie D., Knowing machines: Essays on technological change, (1996); Maheshwari S., Black Friday sales were up, but reflected the challenges facing retailers, (2021); Malin Z., The evolution of Black Friday shopping—and what 2021 may bring, (2021); Marx K., Das kapital: A critique of political economy, (2010); Merton R., Social theory and social structure, (1957); Miles M., Huberman A.M., Qualitative data analysis: A sourcebook for new methods, (1994); Moustakas C., Phenomenological research methods, (1994); Black Friday 2020 results: Top 3 insights on consumer trends, (2020); Nordquist C., Black Friday shopping trends are changing, (2021); Otnes C., McGrath M.A., Perceptions and realities of male shopping behavior, Journal of Retailing, 77, 1, pp. 111-137, (2001); Scheidel W., The great leveler: Violence and history of inequality from the stone age to the twenty-first century, (2017); Siddiqui K., Brand equity trend analysis for fashion brands (2001-2021), Journal of Global Fashion Marketing, (2022); Simpson L., Taylor L., O'Rourke K., Shaw K., An analysis of consumer behavior on black Friday, (2011); Smith O., Ramen T., Shopping with violence: Black Friday sales in the British context, Journal of Consumer Culture, 3, pp. 677-694, (2015); Son S., Bae J., Kim K.H., The effect of perceived agility on intention to reuse omni-channel: Focused on mediating effect of integration quality of omni-channel, Journal of Global Fashion Marketing, 12, 4, pp. 375-389, (2021); Sopadjieva E., Dholakia U.M., Benjamin B., A study of 46,000 shoppers shows that omni-channel retailing works, (2017); Statt N., How the pandemic has changed Black Friday and holiday shopping for good, (2021); Svotwa T.D., Roberts-Lombard M., Jaiyeoba O., Black Friday rituals, customer perceived value and loyalty among young adult customers in South Africa: A stimulus-organism-response perspective, Cogent Business & Management, 7, 1, (2020); Swilley E., Goldsmith R.E., Black Friday and cyber Monday: Understanding consumer intentions on two major shopping days, Journal of Retailing and Consumer Services, 20, 1, pp. 43-50, (2013); Thomas J.B., Peters C., An exploratory investigation of black Friday consumption rituals, International Journal of Retail & Distribution Management, 39, 7, pp. 522-537, (2011); Thomas L., Black Friday 2020 online shopping surges 22% to record $9 billion, Adobe says, (2020); Thomas L., Black Friday shopping in stores drops 28% from pre-pandemic levels, CNBC, (2021); Thompson C.J., Locander W.B., Pollio H.R., Putting consumer research back into consumer behavior: The philosophy and method of existential phenomenology, The Journal of Consumer Research, 16, pp. 133-146, (1989); Vago S., Social change, (2004)","C. Peters; Department of Marketing, Winthrop University, Rock Hill, 701 Oakland Ave, 29733, United States; email: petersc@winthrop.edu",null,"Routledge",{"$nulls":5},2.0932685E7,null,null,null,"English","J. Glob. Fash. Mark.","Article","Final",null,"Scopus","2-s2.0-85133542809"]
["Safiullin L.N.; Sakhbieva A.I.; Bulatova E.I.","Safiullin, Lenar N. (55694209500); Sakhbieva, Amina I. (57318581700); Bulatova, Elvira I (57192265030)","55694209500; 57318581700; 57192265030","RESEARCH OF CONSUMER BEHAVIOR DURING THE PANDEMIC: DIGITAL SOLUTIONS IN THE LOCKDOWN ERA",2022.0,"Procedia Environmental Science, Engineering and Management",9.0,3.0,null,653.0,660.0,7.0,0.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85159092841&partnerID=40&md5=66f9f4db8cb4c05b2b70a5588f7f20fc","Kazan Federal University, Department of Financial Markets and Financial Institutions, 18 Kremlin Street, Kazan, 420008, Russian Federation","Safiullin L.N., Kazan Federal University, Department of Financial Markets and Financial Institutions, 18 Kremlin Street, Kazan, 420008, Russian Federation; Sakhbieva A.I., Kazan Federal University, Department of Financial Markets and Financial Institutions, 18 Kremlin Street, Kazan, 420008, Russian Federation; Bulatova E.I., Kazan Federal University, Department of Financial Markets and Financial Institutions, 18 Kremlin Street, Kazan, 420008, Russian Federation","The COVID-19 pandemic crisis has been one of the most important and devastating events in the past two years. Scientists from various fields have studied the consequences of this crisis using comparative and analytical research methods. Based on their findings, it can be concluded that digital transformation is now a prerequisite for any company's activities. Social media has been important in society prior to the pandemic, but is now gaining even more momentum. Companies from various industries can develop an advantageous interaction and promotional channel on social networks. For small businesses, utilizing social media to sell groceries for home delivery is an effective way to embark on a digital transformation process. For larger organizations, digital social media can assist in building societies around their brands, particularly during times of uncertainty and high user traffic. In addition, organizations need to consider ways to minimize consumer risks, which can be divided into two main types: risks of infection and risks of fraud and data abuse in e-commerce transactions. The risk of infection is expected to decrease as a result of massive vaccination campaigns. To address the risk of fraud in online transactions, businesses can eliminate probable fraud risks through security protocols, integrations, and a blend of communications, technologies, and promotion through licensed operators. © 2022, Procedia Environmental Science, Engineering and Management. All Rights Reserved.","consumer behavior; digital solutions; digitalization; pandemic",{"$nulls":5},"Kazan Federal University","The current study has been supported by the Kazan Federal University Strategic Academic Leadership Program.","Ahmed R.R., Streimikiene D., Rolle J.A., Pham A.D., The COVID-19 pandemic and the antecedants for the impulse buying behavior of US citizens, Journal of Competitiveness, 12, pp. 5-14, (2020); Alaimo L.S., Fiore M., Galati A., How the COVID-19 pandemic is changing online food shopping human behaviour in Italy, Sustainability, 12, (2020); Alshuaybat W.A.M., Factors affecting students' satisfaction with academic advisory services in Jordan: A case study of Al Shoubak College, Eurasian Journal of Educational Research, 95, pp. 98-117, (2021); Barnes S.J., Diaz M., Arnaboldi M., Understanding panic buying during COVID-19: A text analytics approach, Expert Systems with Applications, 169, (2021); Baumert T., de Obesso M.M., Valbuena E., How does the terrorist experience alter consumer behaviour? An analysis of the Spanish case, Journal of Business Research, 115, pp. 357-364, (2020); Campbell B.L., Rihn A.L., Campbell J.H., Impact of the Coronavirus pandemic on plant purchasing in Southeastern United States, Agribusiness, 37, pp. 160-170, (2021); Cruz-Cardenas J., Guadalupe-Lanas J., Ramos-Galarza C., Palacio-Fierro A., Drivers of technology readiness and motivations for consumption in explaining the tendency of consumers to use technologybased services, Journal of Business Research, 122, pp. 217-225, (2021); Finston S., Thompson N., A new vision for europe’s bioeconomy in a post-COVID world, Journal of Commercial Biotechnology, 26, pp. 61-71, (2021); Foroudi P., Tabaghdehi S.A.H., Marvi R., The gloom of the COVID-19 shock in the hospitality industry: A study of consumer risk perception and adaptive belief in the dark cloud of a pandemic, International Journal of Hospitality Management, 92, (2021); Galanakis C.M., Rizou M., Aldawoud T.M., Ucak I., Rowan N.J., Innovations and technology disruptions in the food sector within the COVID-19 pandemic and post-lockdown era, Trends in Food Science and Technology, 110, pp. 193-200, (2021); Guthrie C., Fosso-Wamba S., Arnaud J.B., Online consumer resilience during a pandemic: An exploratory study of e-commerce behavior before, during and after a COVID-19 lockdown, Journal of Retailing and Consumer Services, 61, (2021); Jezewska-Zychowicz M., Plichta M., Krolak M., Consumers’ fears regarding food availability and purchasing behaviors during the COVID-19 pandemic: The importance of trust and perceived stress, Nutrients, 12, (2020); Khorsandi Z., Afshinpour M., Molaei F., Askandar R.H., Keshavarzipour F., Abbasi M., Sadeghi-Aliabadi H., Design and synthesis of novel phe-phe hydroxyethylene derivatives as potential coronavirus main protease inhibitors, Journal of Biomolecular Structure and Dynamics, 30, pp. 1-9, (2021); Okon E.O., Consequence of environmental policy on the dynamics of economic growth and environmental degradation in Nigeria, International Journal of Social Sciences and Humanity Studies, 13, pp. 195-217, (2021); Quiroz-Gomez S., Guzman-Moreno M., Miranda-De La Cruz A., Garcia-Hernandez J. M., Arcos-Castillo K.D.C., Contrera-Madrigal J.D., Knowledge, attitudes, and practices toward the COVID-19 pandemic in Tabasco, Mexico, American Journal of Health Behavior, 46, pp. 29-38, (2022); Sayyida S., Hartini S., Gunawan S., Husin S.N., The impact of the COVID-19 pandemic on retail consumer behavior, Aptisi Transactions on Management (ATM), 5, pp. 79-88, (2021); Sheth J., Impact of Covid-19 on consumer behavior: Will the old habits return or die?, Journal of business research, 117, pp. 280-283, (2020); Troise C., O'Driscoll A., Tani M., Prisco A., Online food delivery services and behavioural intention-a test of an integrated TAM and TPB framework, British Food Journal, 4, pp. 165-169, (2020); Vermeulen H., Gouse M., Delport M., Louw M., Miller T., Consumer acceptance of sugar derived from genetically modified sugarcane in South Africa, AgBioForum, 22, pp. 1-12, (2020); Yang X., Potential consequences of COVID-19 for sustainable meat consumption: the role of food safety concerns and responsibility attributions, British Food Journal, 8, pp. 90-94, (2020)","L.N. Safiullin; Kazan Federal University, Department of Financial Markets and Financial Institutions, Kazan, 18 Kremlin Street, 420008, Russian Federation; email: lenar_s@mail.ru",null,"National Society of Environmental Science and Engineering (SNSIM)",{"$nulls":5},2.3929537E7,null,null,null,"English","Procedia Environ. Sci. Eng. Manag.","Article","Final",null,"Scopus","2-s2.0-85159092841"]
["Chen C.; Leon S.; Ractham P.","Chen, Charlie (7501949741); Leon, Steve (57197707847); Ractham, Peter (14036025900)","7501949741; 57197707847; 14036025900","Will customers adopt last-mile drone delivery services? An analysis of drone delivery in the emerging market economy",2022.0,"Cogent Business and Management",9.0,1.0,2074340.0,null,null,null,13.0,"10.1080/23311975.2022.2074340","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85130579659&doi=10.1080%2f23311975.2022.2074340&partnerID=40&md5=d0c5bfc84989b59e323e3ab00054226f","Department of Computer Information Systems and Supply Chain Management, Walker College of Business, Appalachian State University, NC, United States; Department of Marketing Supply Chain Management, Walker College of Business, Appalachian State University, NC, United States; Department of Management Information System, Thammasat Business School, Thammasat University, Thailand","Chen C., Department of Computer Information Systems and Supply Chain Management, Walker College of Business, Appalachian State University, NC, United States; Leon S., Department of Marketing Supply Chain Management, Walker College of Business, Appalachian State University, NC, United States; Ractham P., Department of Management Information System, Thammasat Business School, Thammasat University, Thailand","Drone delivery services are novelty concepts to most people in emerging market economies. To gain competitive advantages, retailers in emerging market need to be proactive in understanding the key factors contributing to the acceptance of last-mile drone delivery services by general users. This study offers personal and social perspectives of the adoption of drone delivery services by Thai users. A total of 391 respondents participated in an online survey. The PLS-SEM method was used to perform the data analysis. The analysis results show that personal innovativeness and opinion passions are antecedents for Thai users’ perceived ease of use. However, these two antecedents do not affect Thai users’ perceived usefulness for drone delivery services. In addition, perceived privacy risk has a negative moderating effect on the relationship between PEOU and the adoption of drone delivery services. In contrast, Thai users’ perceived privacy risk has no significant moderating effect on the relationship between PU and the intention to adopt drone delivery services. Lastly, PEOU has a significant positive effect on the intention of users to adopt drone delivery services, whereas PU does not have any significant effect. These findings provide theoretical and practical implications on the moderating effect of perceived privacy risks on the relationships between perceptions and the intention to adopt the last-mile drone delivery service. © 2022 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license.","Drone delivery service; E-Commerce; emerging market; last mile e-commerce",{"$nulls":7},"Agarwal R., Prasad J., A conceptual and operational definition of personal innovativeness in the domain of information technology, Information Systems Research, 9, 2, pp. 204-218, (1998); Akkarakantrakorn S., Guidelines for the management of digital evidence gathering concerning online shopping fraud, Thammasat Review, 23, 1, pp. 138-159, (2020); AL-JA'AFREH A., Al-Adaileh R., The impact of electronic word of mouth on consumers purchasing intention, Journal of Theoretical and Applied Information Technology, 98, 2, (2020); Amin M., Rezaei S., Abolghasemi M., User satisfaction with mobile websites: The impact of perceived usefulness (PU), perceived ease of use (PEOU) and trust, Nankai Business Review International, 5, 3, pp. 258-274, (2014); Bahmanziari T., Pearson J.M., Crosby L., Is trust important in technology adoption? A policy capturing approach, Journal of Computer Information Systems, 43, 4, pp. 46-54, (2003); Berger J., Word of mouth and interpersonal communication: A review and directions for future research, Journal of Consumer Psychology, 24, 4, pp. 586-607, (2014); Buttle F.A., Word of mouth: Understanding and managing referral marketing, Journal of Strategic Marketing, 6, 3, pp. 241-254, (1998); Chamola V., Hassija V., Gupta V., Guizani M., A comprehensive review of the COVID-19 pandemic and the role of IoT, drones, AI, blockchain, and 5G in managing its impact, Ieee Access, 8, pp. 90225-90265, (2020); Chayomchai A., The online technology acceptance model of generation-Z people in Thailand during COVID-19 crisis, Management and Marketing, Challenges for the Knowledge Society, 15, s1, pp. 496-513, (2020); Cheung M.L., Leung W.K., Chan H., Driving healthcare wearable technology adoption for generation Z consumers in Hong Kong, Young Consumers, 22, 1, pp. 10-27, (2021); Chin W.W., The partial least squares approach for structural equation modeling, Modern methods for business research, pp. 295-336, (1998); Chin W.W., How to write up and report PLS analyses, Handbook of partial least squares, pp. 655-690, (2010); Chiu E.M., The determinants of trade on conflict–some evidence from emerging market economies, Thammasat Review, 22, 2, pp. 36-49, (2019); Chung N., Koo C., The use of social media in travel information search, Telematics and Informatics, 32, 2, pp. 215-229, (2015); Covington T., Could delivery drones be the next tech privacy violation? 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A critical review of the technology acceptance model, Information & Management, 40, 3, pp. 191-204, (2003); Leon S., Chen C., Ratcliffe A., Consumers’ perceptions of last mile drone delivery, International Journal of Logistics Research and Applications, pp. 1-20, (2021); Li H., Wu J., Gao Y., Shi Y., Examining individuals’ adoption of healthcare wearable devices: An empirical study from privacy calculus perspective, International Journal of Medical Informatics, 88, pp. 8-17, (2016); Liu D., Lai M.C., Tsay W.D., Determinants analysis of drone delivery service adoption, 2020 3rd IEEE International Conference on Knowledge Innovation and Invention (ICKII), pp. 1-4, (2020); Lule I., Omwansa T.K., Waema T.M., Application of technology acceptance model (TAM) in m-banking adoption in Kenya, International Journal of Computing & ICT Research, 6, 1, (2012); Manakitsomboon H., Severity of the coronavirus (COVID-19) pandemic impact on hotels in Thailand as of January 2021, (2021); Maria S., Pusriadi T., Hakim Y.P., Darma D.C., The effect of social media marketing, word of mouth, and effectiveness of advertising on brand awareness and intention to buy, Jurnal Manajemen Indonesia, 19, 2, pp. 107-122, (2019); Mathew A.O., Jha A.N., Lingappa A.K., Sinha P., Attitude towards drone food delivery services—role of innovativeness, perceived risk, and green image, Journal of Open Innovation: Technology, Market, and Complexity, 7, 2, (2021); Michels M., von Hobe C.-F., Weller von Ahlefeld P.J., Musshoff O., The adoption of drones in German agriculture: A structural equation model, Precision Agriculture, 22, 6, pp. 1728-1748, (2021); Naidoo Y., Stopforth R., Bright G., Development of an UAV for search & rescue applications, Paper presented at the IEEE Africon’11, (2011); Business Insights on Emerging Markets 2021, (2021); Park J., Kim S., Suh K., A comparative analysis of the environmental benefits of drone-based delivery services in urban and rural areas, Sustainability, 10, 3, (2018); Peter J.P., Reliability: A review of psychometric basics and recent marketing practices, Journal of Marketing Research, 16, 1, pp. 6-17, (1979); Ringle C.M., Sarstedt M., Straub D.W., Editor’s comments: A critical look at the use of PLS-SEM in” MIS Quarterly”, MIS Quarterly, 36, 1, pp. 3-14, (2012); Ringle C., Wende S., Becker J.-M., SmartPLS 3, (2015); Rogers E.M., New product adoption and diffusion, Journal of Consumer Research, 2, 4, pp. 290-301, (1976); Rogers E.M., Medina U.E., Rivera M.A., Wiley C.J., Complex adaptive systems and the diffusion of innovations, The Innovation Journal: The Public Sector Innovation Journal, 10, 3, pp. 1-26, (2005); Rogers E.M., Diffusion of innovations, (2010); Rosen E., The anatomy of buzz: How to create word of mouth marketing, (2002); Saxon S., Sodprasert J., Sucharitakul V., Reimagining travel: Thailand tourism after the COVID-19 pandemic, (2021); Shafiee M.M., Bazargan N.A., Kazeminia A., Modeling customer electronic trust in online stores: A risk reduction approach, International Conference on e-Commerce with focus on e-Tourism, e-Service, Health Tourism, 14-15 April 2017, Isfahan, Iran., (2017); Shafiee M.M., Bazargan N.A., Behavioral customer loyalty in online shopping: The role of e-service quality and e-recovery, Journal of Theoretical and Applied Electronic Commerce Research, 13, 1, pp. 26-38, (2018); Shafiee M.M., The effect of destination image on tourist satisfaction, intention to revisit and WOM: An empirical research in foursquare social media, 10th International Conference on e-Commerce in Developing Countries: With Focus on e-Tourism, ECDC 2016 2016| conference-paper DOI, 10, (2020); Siddiqui M.S., Siddiqui U.A., Khan M.A., Alkandi I.G., Saxena A.K., Siddiqui J.H., Creating electronic word of mouth credibility through social networking sites and determining its impact on brand image and online purchase intentions in India, Journal of Theoretical and Applied Electronic Commerce Research, 16, 4, pp. 1008-1024, (2021); Tom N.M.F., Crashed! Why drone delivery is another tech idea not ready to take off, International Business Research, 13, 7, (2020); Torabbeigi M., Lim G.J., Kim S.J., Drone delivery scheduling optimization considering payload-induced battery consumption rates, Journal of Intelligent & Robotic Systems, 97, 3, pp. 471-487, (2020); Tsai W., Ghoshal S., Social capital and value creation: The role of intrafirm networks, Academy of Management Journal, 41, 4, pp. 464-476, (1998); Van Petegem W., The Future Digital Scholar, (2021); Wang T., Yeh R.K.J., Chen C., Tsydypov Z., What drives electronic word-of-mouth on social networking sites? Perspectives of social capital and self-determination, Telematics and Informatics, 33, 4, pp. 1034-1047, (2016); Wood C., Barriers to innovation diffusion for social robotics start-ups and methods of crossing the chasm, (2017); Yaprak U., Kilic F., Okumus A., Is the Covid-19 pandemic strong enough to change the online order delivery methods? Changes in the relationship between attitude and behavior towards order delivery by drone, Technological Forecasting and Social Change, 169, (2021); Yoo W., Yu E., Jung J., Drone delivery: Factors affecting the public’s attitude and intention to adopt, Telematics and Informatics, 35, 6, pp. 1687-1700, (2018); Zhang T., Tao D., Qu X., Zhang X., Lin R., Zhang W., The roles of initial trust and perceived risk in public’s acceptance of automated vehicles, Transportation Research Part C: Emerging Technologies, 98, pp. 207-220, (2019)","P. Ractham; Management Information System, Thammasat Business School, Thailand; email: Peter@tbs.tu.ac.th",null,"Cogent OA",{"$nulls":5},2.3311975E7,null,null,null,"English","Cogent Bus. Manag.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85130579659"]
["You T.; S B.","You, Tao (57350555100); S, Balamurugan (57220162375)","57350555100; 57220162375","Internet of things-assisted integrated framework for electronic market application",2022.0,"Electronic Library",40.0,"2024-02-01",null,1.0,17.0,16.0,2.0,"10.1108/EL-07-2020-0197","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85119678951&doi=10.1108%2fEL-07-2020-0197&partnerID=40&md5=2f6b3b350d42ea700b78ed1d62386194","Hohai University, Nanjing, China; iRCS, Coimbatore, India","You T., Hohai University, Nanjing, China; S B., iRCS, Coimbatore, India","Purpose: The widespread use of the internet and the rapid development of the internet of things in information technology have increased the need for network-enabled marketing. It is important to service a broad class involving logistics, buyer, seller and end-users. During various phases of the sales, purchases and marketing process, IoT will influence decision-making. Electronic commerce is a new form of trade under the development of modern information technology. Design/methodology/approach: In this paper, the integrated neutrosophic framework based on the internet of things (INF-IoT) has been proposed to support marketers and companies to make a powerful marketing strategy using identified data from IoT devices. Findings: The experimental results show that the proposed method has high performance and very efficient. Originality/value: This approach may reduce business activity to its core components, which include, in the simplest case, a value proposal, distribution channels and customers, and explain how a network of multi-actors generates a product and services, distributes and uses the value in production. Furthermore, an efficient interface is provided by the logistic module to maintain an order list. © 2020, Emerald Publishing Limited.","E-commerce; Electronic market; Integrated framework; Internet of things; Logistics","article; electronic commerce; information technology; internet of things; marketing",{"$nulls":6},"Abdel-Basset M., Gunasekaran M., Mohamed M., Chilamkurti N., A framework for risk assessment, management and evaluation: Economic tool for quantifying risks in supply chain, Future Generation Computer Systems, 90, pp. 489-502, (2019); Abomhara M., Cyber security and the internet of things: vulnerabilities, threats, intruders and attacks, Journal of Cyber Security and Mobility, 4, 1, pp. 65-88, (2015); Akter S., Wamba S.F., Big data analytics in E-commerce: a systematic review and agenda for future research, Electronic Markets, 26, 2, pp. 173-194, (2016); Alaa M., Zaidan A.A., Zaidan B.B., Talal M., Kiah M.L.M., A review of smart home applications based on internet of things, Journal of Network and Computer Applications, 97, pp. 48-65, (2017); Al-Momani A.M., Mahmoud M.A., Ahmad M.S., Modeling the adoption of internet of things services: a conceptual framework, International Journal of Applied Research, 2, 5, pp. 361-367, (2016); Dhote S., Vichoray C., Pais R., Baskar S., Shakeel P.M., Hybrid geometric sampling and AdaBoost based deep learning approach for data imbalance in E-commerce, Electronic Commerce Research, 20, 2, (2019); Guo P., Han M., Cao N., Shen Y., The research on innovative application of E-commerce in IoT era, 2017 IEEE International Conference on Computational Science and Engineering (CSE) and IEEE International Conference on Embedded and Ubiquitous Computing (EUC), 2, pp. 410-413, (2017); Hsieh M.Y., Interdisciplinarily exploring the most potential IoT technology determinants in the omnichannel E-commerce purchasing Decision-Making processes, Applied Sciences, 10, 2, (2020); Khanna A., Kaur S., Evolution of internet of things (IoT) and its significant impact in the field of precision agriculture, Computers and Electronics in Agriculture, 157, pp. 218-231, (2019); Khrais L.T., Azizi T.A., Analyzing consumer attitude toward mobile payment technology and its role in booming the E-commerce business, Journal of Talent Development and Excellence, 12, 3, pp. 1069-1076, (2020); Kshetri N., The evolution of the internet of things industry and market in China: an interplay of institutions, demands and supply, Telecommunications Policy, 41, 1, pp. 49-67, (2017); Mahdavinejad M.S., Rezvan M., Barekatain M., Adibi P., Barnaghi P., Sheth A.P., Machine learning for internet of things data analysis: a survey, Digital Communications and Networks, 4, 3, pp. 161-175, (2018); Maple C., Security and privacy in the internet of things, Journal of Cyber Policy, 2, 2, pp. 155-184, (2017); Mishra S., Rastogi C., Future of E-commerce in India, Studies in Indian Place Names, 40, 69, pp. 345-351, (2020); Ng I.C., Wakenshaw S.Y., The internet-of-Things: Review and research directions, International Journal of Research in Marketing, 34, 1, pp. 3-21, (2017); Ramasamy P., Ranganathan V., Palanisamy V., Kadry S., Securing one-time password generation using elliptic-curve cryptography with self-portrait photograph for mobile commerce application, Multimedia Tools and Applications, pp. 1-19, (2019); Ray P.P., A survey on internet of things architectures, Journal of King Saud University - Computer and Information Sciences, 30, 3, pp. 291-319, (2018); Ruan D.X., Wu D., Wu X.B., The internet of things technology in logistics application: Stages, trend and drive modes, 2012 International Symposium on Management of Technology (ISMOT), pp. 452-455, (2012); Turban E., Whiteside J., King D., Outland J., Mobile commerce and the internet of things, Introduction to Electronic Commerce and Social Commerce, pp. 167-199, (2017); Warkentin M., Orgeron C., Using the security triad to assess blockchain technology in public sector applications, International Journal of Information Management, 52, (2020)","T. You; Hohai University, Nanjing, China; email: youtao280@hotmail.com",null,"Emerald Group Holdings Ltd.",{"$nulls":5},2640473.0,null,"ELLID",null,"English","Electron. Libr.","Article","Final",null,"Scopus","2-s2.0-85119678951"]
["Wei Z.","Wei, Zongchao (57751224900)",5.77512249E10,"High Performance Computing Simulation of Intelligent Logistics Management Based on Shortest Path Algorithm",2022.0,"Computational Intelligence and Neuroscience",2022.0,null,7930553.0,null,null,null,0.0,"10.1155/2022/7930553","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85132243102&doi=10.1155%2f2022%2f7930553&partnerID=40&md5=3335e8a2c5120f6cfc0f7bca6100ae54","Developing and Planning Department, Yellow River Conservancy Technical Institute, Kaifeng, 475004, China","Wei Z., Developing and Planning Department, Yellow River Conservancy Technical Institute, Kaifeng, 475004, China","At present, e-commerce drives the logistics industry to develop greatly, but at the same time, there is a huge demand in this field, such as lower cost and higher efficiency. Facing the needs of logistics management development, it needs the blessing of intelligent technology, which involves countless fields at present. Intelligent logistics management has become a hot spot at present. What needs to be solved in this respect is how to shorten the transportation distance and save costs. To solve this problem, this paper proposes to introduce the shortest path algorithm. This paper compares the Dijkstra algorithm with the A∗ algorithm under the background of logistics management and finds that the latter is more suitable for this field with huge amount of information. In order to improve the performance of the A∗ algorithm, this paper introduces ant colony algorithm, which can better avoid obstacles. Combining these two algorithms, a ∗-ant colony algorithm is obtained. The algorithm absorbs the advantages of the two algorithms, while maintaining high efficiency and good stability. These characteristics are very satisfying in the field of logistics management. Through the performance test and simulation experiment, it is concluded that the algorithm has excellent optimization ability and can reduce the cost for this field. © 2022 Zongchao Wei.",null,"Algorithms; Computer Simulation; Industry; Transportation; Ant colony optimization; Graph theory; A* algorithm; Ant colonies algorithm; E- commerces; Higher efficiency; Logistic management; Logistics industry; Low-costs; Low-high; Performance computing; Shortest path algorithms; algorithm; computer simulation; industry; procedures; traffic and transport; Efficiency",{"$nulls":6},"Wang S.X., The improved dijkstra's shortest path algorithm and its application[J], Procedia Engineering, 29, 1, pp. 1186-1190, (2012); Lim Y., Kim H., A shortest path algorithm for real road network based on path overlap[J], Journal of the Eastern Asia Society for Transportation Studies, 6, pp. 1426-1438, (2005); Antonio J.K., Huang G.M., Tsai W., A fast distributed shortest path algorithm for a class of hierarchically clustered data networks, IEEE Transactions on Computers, 41, 6, pp. 710-724, (1992); Climaco J., Martins E., A bicriterion shortest path algorithm[J], European Journal of Operational Research, 11, 4, pp. 399-404, (1982); Jian Z., Jiang M., Yuan F., Identification of age-related macular degeneration related genes by applying shortest path algorithm in protein-protein interaction network[J], BioMed Research International, 2013, 4-6, (2013); Lin P.L., Chang S., A shortest path algorithm for a nonrotating object among obstacles of arbitrary shapes, IEEE Transactions on Systems, Man, and Cybernetics, 23, 3, pp. 825-833, (1993); Dubuisson-Jolly M.P., Gupta A., Tracking deformable templates using a shortest path algorithm, Computer Vision and Image Understanding, 81, 1, pp. 26-45, (2001); Seraj M., Wong C.Y., Impacts of different mobile user interfaces on students' satisfaction for learning d shortest path algorithm, International Journal of Interactive Mobile Technologies (IJIM), 8, 4, pp. 24-30, (2014); Yi M.L., Lan B., Xiao M.F., Design of GPS-based intelligent logistics management system[J], Ence Technology & Engineering, 6-7, 6, pp. 485-490, (2008); Marzantowicz L., Changes in contemporary logistics management in the light of intelligent logistics, Kwartalnik Nauk O Przedsiȩbiorstwie, 50, 1, pp. 62-71, (2019); Zhang T., Hua Y., Luo H., Chen H., Shao M., Zhou Y., Liu B., Fu X., Huang G., John Man-Tak C., Huang G., Journal of Traditional Chinese Medicine = Chung i Tsa Chih Ying Wen Pan, 37, 3, pp. 341-354, (2017); Jiao Y.B., Based on the electronic commerce environment of intelligent logistics system construction, Advanced Materials Research, 850-851, pp. 1057-1060, (2013); Yang C., Hu X., Gu W., Liu T., Research on the c intelligent logistics, Zhongguo Yi Liao Qi Xie Za Zhi = Chinese Journal of Medical Instrumentation, 43, 6, pp. 462-465, (2019); Zhou L.X., Liu K., Intelligent logistics transportation system[J], Journal of Tongji University, 58, 58, pp. 55-70, (2002); Guo Y., Qu J., Study on intelligent logistics management information system based on IOT and cloud computation in big data era, The Open Cybernetics & Systemics Journal, 9, 1, pp. 934-941, (2015)","Z. Wei; Developing and Planning Department, Yellow River Conservancy Technical Institute, Kaifeng, 475004, China; email: weizongchao@yrcti.edu.cn",null,"Hindawi Limited",{"$nulls":5},1.6875265E7,null,null,3.5720907E7,"English","Comput. Intell. Neurosci.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85132243102"]
["Chokoe S.C.; Oyekale A.S.","Chokoe, S.C. (57930584900); Oyekale, A.S. (57200949556)","57930584900; 57200949556","PERCEPTIONS OF ONLINE SHOPPING AND DETERMINANTS OF CONSUMERS’ ONLINE PURCHASE OF FOOD GROCERIES IN POLOKWANE LOCAL MUNICIPALITY, SOUTH AFRICA",2022.0,"African Journal of Food, Agriculture, Nutrition and Development",22.0,7.0,null,20905.0,20923.0,18.0,0.0,"10.18697/ajfand.112.21040","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85140020546&doi=10.18697%2fajfand.112.21040&partnerID=40&md5=39161532667d570c72cdae45348cec38","Department of Agricultural Economics and Extension, North-West University, Mafikeng Campus, Mmabatho, 2735, South Africa","Chokoe S.C., Department of Agricultural Economics and Extension, North-West University, Mafikeng Campus, Mmabatho, 2735, South Africa; Oyekale A.S., Department of Agricultural Economics and Extension, North-West University, Mafikeng Campus, Mmabatho, 2735, South Africa","Online purchase of food groceries is a development in the food retail market that is being driven by recent advances in the Information and Communication Technologies (ICTs). Consumers are, therefore, complying with these emerging trends by testing some of the online shopping platforms to form a behavioural compliance as required by some cashless economic policies being implemented in some African countries. Although considered to be convenient, online shopping is bewildered with a lot of risks. The aim of this study was to analyse the perceptions of consumers on online shopping risks and determine the factors influencing them to purchase food groceries online. The data were collected from 173 respondents selected by simple random sampling. The data were collected using structured questionnaire that was administered by trained enumerators. Descriptive statistics and logit regression were used for data analysis. The analyses were carried out by STATA software. The results showed that 11% of the respondents were using online platforms to purchase food groceries, 57.2% were aware of the existence of online platforms to purchase food groceries, 84.4% perceived online purchase of food groceries as convenient, and 62.4% perceived it as risky. The results of the Logit regression model showed that delivery fee, level of education, employment status, use of phone tablets for internet browsing, use of laptops to browse the internet, perceived online convenience and perceived online risk had statistically significant relationships (p<0.05) with consumers’ decision to purchase food groceries online. It was recommended that in order to encourage active online sales, there is the need to educate consumers on the benefits of purchasing food groceries online, using broadcasting platforms such as radio, television and social media. There is also a need for the South African government to strengthen policies to reduce associated risks of online transactions © 2022, African Journal of Food, Agriculture, Nutrition and Development.All Rights Reserved.","Consumers; Delivery fee; Food groceries; Online purchase; South africa",{"$nulls":7},"National report on e-commerce development in South Africa, (2017); Gordon A, Bhowan K, Factors that influence online shopping behaviour, Alternation, 12, pp. 143-169, (2005); Ilhan BY, Iscioglu TE, Effect of women’s labor market status on online grocery shopping, the case of Turkey, Eurasian Business Review, 5, 2, pp. 371-396, (2015); Bashir R, Mehboob I, Bhatti W, Effects of online shopping trends on consumers-buying behavior: An empirical study of Pakistan, Journal of Management and Research, 2, 2, pp. 1-24, (2015); Steyn F, Coetzee A, Klopper H, A survey of car guards in Tshwane: Implications for private security policy and practice, SA Crime Quarterly, 52, pp. 15-24, (2015); Ranadive A, An empirical study on the online grocery shopping intentions of consumers in Vadodara City, International Journal of Management and Social Sciences Research, 4, 3, pp. 2319-4421, (2015); Kavitha R, A study on consumer awareness and determinants of online shopping, International Journal of Management Research & Review, 5, 8, pp. 636-642, (2015); Nawi NC, Mamun AA, Hamsani NHB, Muhayiddin MNB, Effect of consumer demographic and risk factors on online purchase behavior in Malaysia, Societies, 9, 10, pp. 1-11, (2019); Shi K, De Vos J, Yang Y, Witlox F, Does e-shopping replace shopping trips? Empirical evidence from Chengdu, China, Transportation Research Part A, 122, pp. 21-33, (2019); Lubis AN, Evaluating the customer preference of online shopping: Demographic factors and online application issue, Academy of Strategic Management Journal, 17, 2, pp. 1-13, (2018); Banerjee N, Dutta A, Dasgupta T, A study on customers’ attitude towards online shopping: An Indian perspective, Indian Journal of Marketing, 40, 11, pp. 36-42, (2010); Clemes MD, Gan C, Zhang J, An empirical analysis of online shopping adoption in Beijing, China, Journal of Retailing and Consumer Service, 21, pp. 364-375, (2014); Long QN, The factors that influence Australian online shopping adoption: An empirical analysis, (2016); Ali S, Saleem M, Ahmed ME, Khan MM, Shah N, Rafiq S, Models for online grocery shopping: A study of Pakistani online market, Journal of Internet and E-Business Studies, pp. 1-15, (2017); Liao Z, Cheung M, Internet based e-shopping and consumer attitude: an empirical study, Information and Management, 38, pp. 299-306, (2001); Kim E, Hong T, Segmenting customers in online stores from factors that affect the customer’s intention to purchase, Journal of Psychology and Marketing, 20, 7, pp. 383-388, (2010); Seitz C, Pokrivcak J, Toth M, Plevny M, Online retailing in Germany: an explorative analysis, Journal of Business Economics and Management, 18, 16, pp. 1243-1263, (2017); Gordon A, Bhowan K, Factors that influence online shopping behaviour, Alternation, 12, pp. 143-169, (2005); Kang C, Moon J, Kim T, Choe Y, Why consumers go to online grocery: comparing vegetables with grains, the 49th Hawaii International Conference on System Sciences, pp. 3604-3613, (2016); Belanche D, Casalo L, Guivaliu M, Website usability, consumer satisfaction and the intention to use a website: The moderating effect of perceived risk, Journal of Retailing and Consumer Service, 19, pp. 124-132, (2012); Khan SA, Liang Y, Shahzad S, An empirical study of perceived factors affecting customer satisfaction to re-purchase intention in online stores in China, Journal of Service and Management, 8, pp. 291-305, (2015); Polokwane Local Municipality 974 from census 2011; City of Polokwane - Naturally progressive: 2019/20 integrated development plan, (2019); Adeogun OA, Ajana AM, Yarhere MT, Adeogun MO, Application of Logit model in adoption decision: A study of hybrid Clarias in Lagos State, Nigeria, American-Eurasian Journal Agricultural & Environmental Science, 4, 4, pp. 468-472, (2008); Daoud JI, Multicollinearity and regression analysis, Journal of Physics Conference Series, 949, pp. 1-6, (2017); Makweya L and IB Oluwatayo Consumers’ preference and willingness to pay for graded beef in Polokwane Municipality, South Africa, (2018); What is-store for online grocery shopping: Omnichannel strategies to reach crossover shoppers, Nielsen Global Connected Commerce Report, pp. 1-37, (2017); Meixian L, Convenience and online consumer shopping behaviour: A business anthropological case study based on the contingent valuation method, Anthropologist, 21, 1-2, pp. 8-17, (2015); Zaini ZMM, Ramli N, Ghani FA, Online grocery shopping: The effect of time availability on Malaysian consumer preferences, World Applied Science Journal, 12, pp. 60-67, (2011); Hiser J, Nayga RM, Capps OJ, An exploratory analysis of familiarity and willingness to use online food shopping services in a local area in Texas, Journal of Distribution Research, 28, 1, pp. 78-90, (1999); Nabareseh S, Osakwe CN, Klimek P, Chovancova MA, Comparative study of consumers’ readiness for internet shopping in two African emerging economies: Some preliminary findings, Mediterranean Journal of Social Science, 5, 23, pp. 1882-1889, (2014); Tanadi T, Samadi B, Gharleghi B, The impact of perceived risks and perceived benefits to improve an online intention among generation-Y in Malaysia, Asian Social Science, 11, 26, pp. 226-238, (2015)","A.S. Oyekale; Department of Agricultural Economics and Extension, North-West University, Mafikeng Campus, Mmabatho, 2735, South Africa; email: asoyekale@gmail.com",null,"African Scholarly Science Communications Trust (ASSCAT)",{"$nulls":5},1.6845358E7,null,null,null,"English","Afr. J. Food Agric. Nutr. Dev.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85140020546"]
["Sun Y.; Lian F.; Yang Z.-Z.","Sun, Yu (57210638171); Lian, Feng (57205115945); Yang, Zhong-Zhen (8383785100)","57210638171; 57205115945; 8383785100","Optimizing the location of physical shopping centers under the clicks-and-mortar retail mode",2022.0,"Environment, Development and Sustainability",24.0,2.0,null,2288.0,2314.0,26.0,2.0,"10.1007/s10668-021-01534-6","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85106719147&doi=10.1007%2fs10668-021-01534-6&partnerID=40&md5=09f111b6ca6c9d33231090c19f8a73f5","Ningbo University, Ningbo, China","Sun Y., Ningbo University, Ningbo, China; Lian F., Ningbo University, Ningbo, China; Yang Z.-Z., Ningbo University, Ningbo, China","To compete with online e-commerce, traditional retailing is implementing a new retail mode that combines online sales with physical stores, which may change the channel, transport mode and logistics cost of retail commodities from manufacturers to end consumers. In this context, it is necessary for physical retailers to relocate their shopping centers in order to maximize profits. This paper develops a location optimization model for physical shopping centers based on consumer shopping choices (platform choices and store choices), carbon tax policy and the economic scale of transport under the new retail mode. This model is applied to optimize the number and scale of physical shopping centers and corresponding locations with the objective of maximizing the retail profit under the new retail mode. The results show that under the new retail mode, the number of shopping centers, the scale of an individual physical store and the total retail logistics cost decrease, while the retail profit increases. This work lays a theoretical basis for retailers to build online and offline retail systems and rationally determines the spatial distribution of shopping centers in a city. © 2021, The Author(s), under exclusive licence to Springer Nature B.V.","Location model; Logistics cost; online shopping; Physical store; Retailer; Shopping center","cost analysis; economic conditions; logistics; optimization; policy approach; pollution tax; profitability; spatial distribution; urban area",{"$nulls":6},"Andong R.F., Sajor E., Urban sprawl, public transport, and increasing CO<sub>2</sub> emissions: the case of Metro Manila, Philippines. Environment Development and Sustainability, 19, 1, pp. 99-123, (2017); Cazabat G., Belu M.G., Popa I., Et al., Models and practice of retail location on the romanian market, Amfiteatru Economic, 19, 45, pp. 493-508, (2017); Chen C.Z., Wang N., Adaptive selection of crossover and mutation probability of genetic algorithm and its mechanism, Control Theory and Applications, 19, 1, pp. 41-43, (2002); Dilek H., Karaer O., Nadar E., Retail location competition under carbon penalty, European Journal of Operational Research, 269, 1, pp. 146-158, (2018); Dou X., Cui H., Low-carbon society creation and socio-economic structural transition in China, Environment, Development and Sustainability, 19, 5, pp. 1577-1599, (2017); Gao J.J., Wang Y.J., Guo Y.J., Minimum cost model of distribution systems under demand uncertainty, Journal of Northeastern University (natural Science), 23, 1, pp. 87-90, (2002); Geng Y.H., Study on site selection of shopping center by gis buffer analysis, Geomatics and Spatial Information Technology, 34, 2, pp. 169-171, (2011); 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Huang T., Bergman D., Gopal R., Predictive and prescriptive analytics for location selection of add-on retail products, Production and Operations Management, 28, 7, pp. 1858-1877, (2019); Jiang Z.M., Wang W., How will different depreciation rates affect the estimation of china's capital stock, Statistics and Information Forum, 32, 1, pp. 9-14, (2017); Khan K., Su C.W., Tao R., Hao L.N., Urbanization and carbon emission: Causality evidence from the new industrialized economies, Environment, Development and Sustainability, 22, pp. 7193-7213, (2019); Li G., Zhang T., Tayi G.K., Inroad into omni-channel retailing: physical showroom deployment of an online retailer, European Journal of Operational Research, 283, 2, pp. 676-691, (2019); Li L.N., Analysis on the transformation and development path of retail physical stores under the impact of e-commerce, Journal of Commercial Economics, 2016, 18, pp. 108-109, (2016); Lin G., Chen X., Liang Y., The location of retail stores and street centrality in Guangzhou, China, Applied Geography, 100, pp. 12-20, (2018); Liu W.G., Guo L.H., Research on collaborative development model of traditional retailers’ physical retail and online retail, Journal of Beijing Technology and Business University (social Sciences), 28, 4, pp. 38-43, (2013); Luo G.X., The relativity of e-commerce taxation, China Business, 2013, 13, pp. 46-47, (2013); Mardones C., Munoz T., Environmental taxation for reducing greenhouse gases emissions in Chile: an input-output analysis, Environment, Development and Sustainability, 20, 6, pp. 2545-2563, (2018); Marianov V., Eiselt H.A., Luer-Villagra A., Effects of multipurpose shopping trips on retail store location in a duopoly, European Journal of Operational Research, 269, 2, pp. 782-792, (2018); Musah M., Kong Y., Mensah I.A., Antwi S.K., Donkor M., The connection between urbanization and carbon emissions: A panel evidence from West Africa, Environment, Development and Sustainability, pp. 1-28, (2020); Otto J.R., Chung Q.B., A framework for cyber-enhanced retailing: Integrating e-commerce retailing with brick-and-mortar retailing, Electronic Markets, 10, 3, pp. 185-191, (2000); Piovani D., Molinero C., Wilson A., Urban retail location: insights from percolation theory and spatial interaction modeling, PLoS ONE, 12, 10, pp. 1-13, (2017); Reigadinha T., Godinho P., Dias J., Portuguese food—Exploring three classic theories of retail location, Journal of Retailing and Consumer Services, 34, pp. 102-116, (2017); Ross A., Khajehnezhad M., Otieno W., Aydas O., Integrated location-inventory modelling under forward and reverse product flows in the used merchandise retail sector: A multi-echelon formulation, European Journal of Operational Research, 259, 2, pp. 664-676, (2017); Tyworth J.E., Zeng A.Z., Estimating the effects of carrier transit-time performance on logistics cost and service, Transportation Research Part A, 32, 2, pp. 89-97, (1998); Waddington T., Clarke G., Clarke M.C., Hood N., Newing A., Accounting for temporal demand variations in retail location models, Geographical Analysis, 51, 4, pp. 426-447, (2019); Wang S.L., Lu Y., Parameter estimation of a class of nonlinear stochastic differential equations, Journal of Jilin University (science Edition), 55, 2, pp. 289-293, (2017); Xi G., Cao X., Zhen F., The impacts of same day delivery online shopping on local store shopping in Nanjing, China, Transportation Research Part A, 136, C, pp. 35-47, (2020); Yahoo M., Othman J., Carbon and energy taxation for CO<sub>2</sub> mitigation: A CGE model of the Malaysia, Environment Development & Sustainability, 19, 1, pp. 1-24, (2017); Yang Z.Z., Moodie D.R., Locating urban logistics terminals and shopping centres in a Chinese city, International Journal of Logistics Research and Applications, 14, 3, pp. 165-177, (2011); Yildiz N., Tuysuz F., A hybrid multi-criteria decision making approach for strategic retail location investment: Application to Turkish food retailing, Socio Economic Planning Sciences, 68, C, pp. 1-25, (2019); Zambrano-Rey G., Lopez-Ospina H., Perez J., Retail store location and pricing within a competitive environment using constrained multinomial logit, Applied Mathematical Modelling, 75, pp. 521-534, (2019); Zhang B.G., New Retail Outlets, Corporate Corporate, 2018, 7, pp. 66-68, (2018); Zhang X.L., Yao L., The impact of e-commerce on the development mode innovation of offline physical stores: Based on the comparison of online and offline business formats, Commercial times, 19, pp. 127-129, (2016); Zhao N., Hong G.B., Two-stage estimation for count data models with endogenous explanatory variable of multinomial distribution, Statistics and Information Forum, 33, 8, pp. 19-30, (2018); Zolfani S.H., Aghdaie M.H., Derakhti A., Zavadskas E.K., Varzandeh M.H.M., Decision making on business issues with foresight perspective; an application of new hybrid MCDM model in shopping mall locating, Expert Systems with Applications, 40, 17, pp. 7111-7121, (2013)","Z.-Z. Yang; Ningbo University, Ningbo, China; email: yangzhongzhen@nbu.edu.cn",null,"Springer Science and Business Media B.V.",{"$nulls":5},"1387585X",null,"EDSNB",null,"English","Environ. Dev. Sustainability","Article","Final",null,"Scopus","2-s2.0-85106719147"]
["Gong Y.; Isom T.; Lu P.; Yang X.; Wang A.","Gong, Yaobang (57205686469); Isom, Tanner (58035171200); Lu, Pan (55797810600); Yang, Xianfeng (57191309786); Wang, Aaron (58380044900)","57205686469; 58035171200; 55797810600; 57191309786; 58380044900","Modeling the impact of COVID-19 on transportation at later stage of the pandemic: A case study of Utah",2022.0,"Journal of Intelligent Transportation Systems: Technology, Planning, and Operations",{"$nulls":6},1.0,"10.1080/15472450.2022.2157212","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85145060422&doi=10.1080%2f15472450.2022.2157212&partnerID=40&md5=7c7ea62e1f0b192f115473bb657f5120","Department of Civil and Environmental Engineering, University of Utah, Salt Lake City, UT, United States; Upper Great Plains Transportation Institute, North Dakota State University, Fargo, ND, United States; Department of Civil and Environmental Engineering, University of Maryland, College Park, MD, United States","Gong Y., Department of Civil and Environmental Engineering, University of Utah, Salt Lake City, UT, United States; Isom T., Department of Civil and Environmental Engineering, University of Utah, Salt Lake City, UT, United States; Lu P., Upper Great Plains Transportation Institute, North Dakota State University, Fargo, ND, United States; Yang X., Department of Civil and Environmental Engineering, University of Maryland, College Park, MD, United States; Wang A., Department of Civil and Environmental Engineering, University of Utah, Salt Lake City, UT, United States","The global COVID-19 pandemic has had a great impact on transportation across the United States. However, there is a lack of studies investigating the pandemic’s impact on vehicular traffic at the later stage of the pandemic. Therefore, this paper studies the change of freeway traffic patterns in two metropolitan counties in the State of Utah at the latter stage of the pandemic. We found that with the relaxation of travel restriction and the COVID vaccine, vehicular traffic has recovered to equaling, if not exceeding, pre-pandemic levels. Truck traffic is higher than the pre-pandemic level due to the growth of online shopping and on-demand delivery. To help responsive agencies to prepare for the near-future traffic pattern, a traffic prediction model based on an innovative approach integrating machine learning with graph theory is proposed. The evaluation shows that the proposed prediction model has a desirable performance. The mean absolute percentage prediction error is between 0.38% and 1.74% for different jurisdictions. On average, the modal outperforms the traditional long short-term memory model by 31.20% in terms of root mean squared prediction error. © 2022 Taylor & Francis Group, LLC.","COVID-19; machine learning; traffic forecasting","Forecasting; Graph theory; Machine learning; Traffic control; Case-studies; Freeway traffic; Late stage; Machine-learning; On demands; Online shopping; Traffic Forecasting; Traffic pattern; Travel restrictions; Truck traffic; COVID-19",{"$nulls":6},"Study: COVID-19 changing commuter traffic patterns–AASHTO journal, (2020); Abadi M., Agarwal A., Barham P., Brevdo E., Chen Z., Citro C., Corrado G.S., Davis A., Dean J., Devin M., Ghemawat S., Goodfellow I.J., Harp A., Irving G., Isard M., Jia Y., Jozefowicz R., Kaiser L., Kudlur M., Zheng X., TensorFlow: Large-scale machine learning on heterogeneous distributed systems, (2016); When You’ve Been Fully Vaccinated, (2021); Chollet F., Keras, GitHub repository, (2015); Christidis P., Christodoulou A., Navajas-Cawood E., Ciuffo B., The post-pandemic recovery of transport activity: Emerging mobility patterns and repercussions on future evolution, Sustainability 2021, Vol. 13, Page 6359, 13, 11, (2021); Data61 C., StellarGraph machine learning library, GitHub Repository, (2018); Defferrard M., Bresson X., Vandergheynst P., Convolutional neural networks on graphs with fast localized spectral filtering, Advances in Neural Information Processing Systems, 29, pp. 3844-3852, (2016); Glaeser E.L., Gorback C., Redding S.J., How much does covid-19 increase with mobility? evidence from New York and four other U.S. cities, (2020); Hochreiter S., Schmidhuber J., Gambardella L.M., Schmidhuber J., Long short-term memory, Neural Computation, 9, 8, pp. 1735-1780, (1997); Horsley S., GDP drops at 32.9% rate, the worst U.S. contraction ever : Coronavirus updates : NPR, (2020); Jiang W., Luo J., Graph neural network for traffic forecasting: A survey, (2021); Katrakazas C., Michelaraki E., Sekadakis M., Yannis G., A descriptive analysis of the effect of the COVID-19 pandemic on driving behavior and road safety, Transportation Research Interdisciplinary Perspectives, 7, (2020); Kim K., Impacts of COVID-19 on transportation: Summary and synthesis of interdisciplinary research, Transportation Research Interdisciplinary Perspectives, 9, (2021); Le Q.V., Jaitly N., Hinton G.E., A simple way to initialize recurrent networks of rectified linear units, (2015); Li X., Zheng Y., Alshehri M.D., Hai L., Balasubramanian V., Zeng M., Nie G., A hierarchical framework for interactive behaviour prediction of heterogeneous traffic participants based on graph neural network, IEEE Transactions on Intelligent Transportation Systems, 23, (2021); Mathieu E., Ritchie H., Ortiz-Ospina E., Roser M., Hasell J., Appel C., Giattino C., Rodes-Guirao L., A global database of COVID-19 vaccinations, Nature Human Behaviour, 5, (2021); Maze T.H., Agarwal M., Burchett G., Whether weather matters to traffic demand, traffic safety, and traffic operations and flow, Transportation Research Record: Journal of the Transportation Research Board, 1948, 1, pp. 170-176, (2006); Find a Station | Data Tools | Climate Data Online (CDO) | National Climatic Data Center (NCDC), (2020); Rothengatter W., Zhang J., Hayashi Y., Nosach A., Wang K., Oum T.H., Pandemic waves and the time after Covid-19–Consequences for the transport sector, Transport Policy, 110, pp. 225-237, (2021); Shamshiripour A., Rahimi E., Shabanpour R., Mohammadian A., How is COVID-19 reshaping activity-travel behavior? Evidence from a comprehensive survey in Chicago, Transportation Research Interdisciplinary Perspectives, 7, (2020); (2017); Tang J., Zeng J., Spatiotemporal gated graph attention network for urban traffic flow prediction based on license plate recognition data, Computer-Aided Civil and Infrastructure Engineering, 37, 1, pp. 3-23, (2022); Case counts: coronavirus, (2021); Special orders | coronavirus, (2021); PeMS @ UDOT, (2019); Seasonally adjusted unemployment rates by county, (2021); Xiong X., Ozbay K., Jin L., Feng C., Dynamic origin–destination matrix prediction with line graph neural networks and kalman filter, Transportation Research Record: Journal of the Transportation Research Board, 2674, 8, pp. 491-503, (2020); Yuan J., Abdel-Aty M., Gong Y., Cai Q., Real-time crash risk prediction using long short-term memory recurrent neural network, Transportation Research Record, (2019); Yuan Y., Zhang Z., Yang X.T., Zhe S., Macroscopic traffic flow modeling with physics regularized Gaussian process: A new insight into machine learning applications in transportation, Transportation Research Part B: Methodological, 146, pp. 88-110, (2021); Zhang J., Lee J., Interactive effects between travel behaviour and COVID-19: A questionnaire study, Transportation Safety and Environment, 3, 2, pp. 166-177, (2021); Zhao L., Song Y., Zhang C., Liu Y., Wang P., Lin T., Deng M., Li H., T-GCN: A temporal graph convolutional network for traffic prediction, IEEE Transactions on Intelligent Transportation Systems, 21, 9, pp. 3848-3858, (2020); Zhu J., Han X., Deng H., Tao C., Zhao L., Tao L., Li H., KST-GCN: A knowledge-driven spatial-temporal graph convolutional network for traffic forecasting, (2020)","X. Yang; Department of Civil and Environmental Engineering, University of Maryland, College Park, 20742, United States; email: xtyang@umd.edu",null,"Taylor and Francis Ltd.",{"$nulls":5},1.547245E7,null,null,null,"English","J. Intell. Transp. Syst. Technol. Plann. Oper.","Article","Article in press",null,"Scopus","2-s2.0-85145060422"]
["Fan G.; Fan B.; Xu H.; Wang C.","Fan, Ganglong (36917618400); Fan, Bo (57929743600); Xu, Hongsheng (55493778800); Wang, Chuqiao (57929366900)","36917618400; 57929743600; 55493778800; 57929366900","Research on the virtual simulation experiment evaluation model of e-commerce logistics smart warehousing based on multidimensional weighting",2022.0,"Open Computer Science",12.0,1.0,null,314.0,322.0,8.0,1.0,"10.1515/comp-2022-0249","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85139967190&doi=10.1515%2fcomp-2022-0249&partnerID=40&md5=be3cc1473815d9f0267a5d654869e961","College of Electronic Commerce, Luoyang Normal University, Henan, Luoyang, 471934, China; Henan Key Laboratory for Big Data Processing & Analytics of Electronic Commerce, Luoyang Normal University, Henan, Luoyang, 471934, China; School of Artificial Intelligence, V.n. Karazin Kharkiv National University, Kharkiv, Ukraine","Fan G., College of Electronic Commerce, Luoyang Normal University, Henan, Luoyang, 471934, China, Henan Key Laboratory for Big Data Processing & Analytics of Electronic Commerce, Luoyang Normal University, Henan, Luoyang, 471934, China; Fan B., School of Artificial Intelligence, V.n. Karazin Kharkiv National University, Kharkiv, Ukraine; Xu H., College of Electronic Commerce, Luoyang Normal University, Henan, Luoyang, 471934, China, Henan Key Laboratory for Big Data Processing & Analytics of Electronic Commerce, Luoyang Normal University, Henan, Luoyang, 471934, China; Wang C., College of Electronic Commerce, Luoyang Normal University, Henan, Luoyang, 471934, China, Henan Key Laboratory for Big Data Processing & Analytics of Electronic Commerce, Luoyang Normal University, Henan, Luoyang, 471934, China","Through the analysis of the current research situation at home and abroad, this article finds that there is a lack of evaluation standards and methods in the virtual simulation experiment of e-commerce logistics smart warehousing. Therefore, it seriously affects the standardization and rationality of the experiment. To solve the problems in the evaluation of the current virtual simulation experiment, this article proposes a virtual simulation experiment evaluation model of e-commerce logistics smart warehousing based on multidimensional weighting. This article firstly sorts out the basic process of e-commerce logistics smart warehousing experiment activities and establishes the evaluation object. Then, based on the duality degree of the output results of the experimental steps, it proposes a method that conforms to the corresponding operation steps. Thus, a three-dimensional evaluation model of the completion degree of the operation steps, the reasonable degree of the operation steps, and the completion time of the operation steps are constructed. An automatic scoring evaluation model is proposed based on the combination of three-dimensional weighted evaluation of experimental steps. Finally, the feasibility and convenience of the evaluation model are verified through the experiment analysis.  © 2022 Ganglong Fan et al., published by De Gruyter.","e-commerce logistics; evaluation model; multi-dimensional; smart warehousing; virtual simulation","Electronic commerce; Virtual reality; Current research situation; E- commerces; E-commerce logistic; Evaluation methods; Evaluation models; Evaluation standard; Multi dimensional; Situation at home and abroad; Smart warehousing; Virtual simulations; Warehouses",{"$nulls":4},"2022 Henan Province Science and Technology, (222102210316); National Natural Science Foundation of China, NSFC, (61272015)","Funding information: This work was supported by National Natural Science Funds of China (61272015) and 2022 Henan Province Science and Technology Research Project: “Construction and Application of Intelligent Ontology in Internet of Things Based on Semantic Concept Model” (222102210316). ","Na L., Design of physics and chemistry and biology experimental examination for senior high school entrance examination system based on virtual reality technology, Educ. Teach. Forum, 21, pp. 275-276, (2019); Xuyang C., Li S., A study on influencing factors of behavioral intention in distance learning in virtual environment, China Adult Educ, 2, pp. 3-6, (2019); Zhang Y., Pang W., Research on comprehensive evaluation of virtual simulation experiment teaching project in colleges and universities based on fuzzy hierarchy analytic, Comput. Knowl. Technol., 17, 25, pp. 275-277, (2021); Zhang M., Research on the learning evaluation system in the virtual simulation experiment environment, Jiangnan Univ, (2020); Wanguo Y., Lina S., Research on SVM⁃based intelligent evaluation analysis method for software engineering experiment, Mod. Electron. Tech., 44, 22, pp. 183-186; Liu M., Evaluation model of online experiment operation behavior based on BP neural network, Wirel. Internet Technol., 14, pp. 36-37, (2015); Zheng R., Zheng G., An artificial intelligence data mining technology based evaluation model of education on political and ideological strategy of students, J. Intell. Fuzzy Syst., 40, 5, pp. 1-12, (2020); Xie H., Zhan Y.H., Research on the whole process evaluation of biology virtual simulation experiment course based on artificial intelligence technology, Res. Biol. Teach. Coll. Univ., 11, 1, pp. 35-41; Wu X., Xiong J., College physics experiment operation examination based on worksheet and observation assessment, Res. Explor. Lab., 31, 2, pp. 141-143, (2012); Chen S., Lin Z., Construction of a quantitative evaluation system for physical chemistry experiment, Res. Explor. Lab., 38, 4, pp. 179-183, (2019); Sun F., Sun J., Liu G., Research on evaluation of virtual simulation experiment teaching project, Exp. Technol. Manag., 37, 7, pp. 187-190, (2020); Xu H., Dong X., Evaluation method on warfighting experimentation, J. Inf. Eng. Univ., 22, 2, pp. 241-245, (2021); Zhu Z., Liu L., Xu L., Development and practice of virtual simulation experiment of steel spring floating slab vibration reduction track, Exp. Technol. Manag., 38, 12, pp. 112-116; Zhang L., Tang S., Lv L., An finite iterative algorithm for sloving periodic Sylvester bimatrix equations, J. Frankl. Inst., 357, 15, pp. 10757-10772, (2020); Lv L., Wu Z., Zhang L., Gupta B.B., Tian Z., An edge-AI based forecasting approach for improving smart microgrid efficiency, IEEE Trans. Ind. Inform., 3, (2022); Zhang L., Huang Z., Liu W., Guo Z., Zhang Z., Weather radar echo prediction method based on convolution neural network and Long Short-Term memory networks for sustainable e-agriculture, J. Clean. Prod., 298, (2021); Xu H., Fan G., Song Y., Novel key indicators selection method of financial fraud prediction model based on machine learning hybrid mode, Mob. Inf. Syst., 2022; Zhang L., Xu C., Gao Y., Han Y., Du X., Tian Z., Improved Dota2 lineup recommendation model based on a bidirectional LSTM, Tsinghua Sci. Technol., 25, 6, pp. 712-720, (2020)","G. Fan; College of Electronic Commerce, Luoyang Normal University, Luoyang, Henan, 471934, China; email: fanganglong@lynu.edu.cn",null,"Walter de Gruyter GmbH",{"$nulls":5},2.2991093E7,null,null,null,"English","Open Comput. Sci.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85139967190"]
["Mehta R.; Mathur M.","Mehta, Ritu (55498577000); Mathur, Mahima (57216656265)","55498577000; 57216656265","Vakrangee: changing lives in rural India",2022.0,"Emerald Emerging Markets Case Studies",12.0,4.0,null,1.0,21.0,20.0,0.0,"10.1108/EEMCS-11-2021-0376","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85140931670&doi=10.1108%2fEEMCS-11-2021-0376&partnerID=40&md5=9b7fce8f2310798d4569e05eec1c1653","Department of Marketing, Indian Institute of Management Calcutta, Kolkata, India; Department of Marketing, Prin LN Welingkar Institute of Management Development and Research, Mumbai, India","Mehta R., Department of Marketing, Indian Institute of Management Calcutta, Kolkata, India; Mathur M., Department of Marketing, Prin LN Welingkar Institute of Management Development and Research, Mumbai, India","Learning outcomes: The learning outcomes are as follows: to design an appropriate strategy for firms to succeed in low-income, price-sensitive markets; to appreciate how business model innovation can help to overcome the obstacles faced by firms when serving rural and semi-urban markets in an emerging economy; to identify possible threats to the business model and evaluate strategies to sustain growth in a dynamic environment; and to allow students to consider sources for competitive advantage and how to build a sustainable business model in low-income markets. Case overview/synopsis: The case details the growth story of Vakrangee Limited (Vakrangee) from a technology consultancy firm to a technology-driven firm focused on creating the largest last-mile retail network providing various services in underserved parts of India, mainly rural India. The firm launched retail outlets called Vakrangee Kendras (VKs) in 2011 that evolved from non-exclusive stores offering a single line of e-governance services into technology-enabled franchisee-based exclusive stores that offered a multiple line of services such as banking, finance, insurance, ATM, e-commerce and logistics. VK however is witnessing competition from different players in different segments. Additionally, the dynamic business environment such as the growing penetration of smartphones and internet usage, heterogeneous needs of customers and government policies pose further threat to the company’s growth in the future. In the wake of these challenges, what should Vakrangee do to sustain its growth? Should it focus on cost-leadership or differentiation for strategic positioning? Complexity academic level: This case can be used in an MBA or an executive management program, in courses on strategic management, entrepreneurship, services marketing and rural marketing. Supplementary materials: Teaching notes are available for educators only. Subject code: CSS 3: Entrepreneurship. © 2022, Emerald Publishing Limited.","Competitive advantage; Growth strategy; Marketing strategy; Services marketing; Strategic management; Sustainable competitive advantage; Value creation",{"$nulls":7},"Vakrangee and HDFC ERGO general insurance company enter into corporate agency agreement, (2022); Vakrangee awarded 'financial services retailer of the year, (2022); Vakrangee gains on strategic tie-up with Indian oil corporation, (2022); Vakrangee launches 3,300+ NextGen vakrangee kendras across India, (2022); Vakrangee ties up with netmeds marketplace, (2022); Banking on the future: Vision 2020, (2022); Vakrangee partners with ZEE5, (2022); Financial inclusion in rural India, January 2020, (2022); Vakrangee 2.0- interim report on next gen Vakrangee outlets, (2022); Hammond A., Kramer W.J., Tran J., Katz R., Walker C., The next 4 billion –market size and business strategy at the base of the pyramid, World resource institute, (2007); Vakrangee’s competitors, (2022); Financial inclusion (2009-2012), (2022); Annual report FY 2017-18, (2022); Annual report FY 2018-19, (2022); Annual report FY 2019-20, (2022); Corporate presentation, (2022)","R. Mehta; Department of Marketing, Indian Institute of Management Calcutta, Kolkata, India; email: ritumehta@iimcal.ac.in",null,"Emerald Publishing",{"$nulls":5},2.0450621E7,null,null,null,"English","Emerald Emerg. Mark. Case Stud.","Article","Final",null,"Scopus","2-s2.0-85140931670"]
["Kunnapapdeelert S.; Johnson J.V.; Phalitnonkiat P.","Kunnapapdeelert, Siwaporn (24175771600); Johnson, James Vincent (57715172600); Phalitnonkiat, Passarin (57211292454)","24175771600; 57715172600; 57211292454","GREEN LAST-MILE ROUTE PLANNING FOR EFFICIENT E-COMMERCE DISTRIBUTION",2022.0,"Engineering Management in Production and Services",14.0,1.0,null,1.0,12.0,11.0,2.0,"10.2478/emj-2022-0001","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85134488265&doi=10.2478%2femj-2022-0001&partnerID=40&md5=b2f1ad256c275529e24562d046a9eae7","Burapha University, International College, Thailand","Kunnapapdeelert S., Burapha University, International College, Thailand; Johnson J.V., Burapha University, International College, Thailand; Phalitnonkiat P., Burapha University, International College, Thailand","This study aims to design vehicle routes based on cost minimisation and the minimisation of greenhouse gasses (GHG) emissions to help companies solve the vehicle routing problem with pickup and delivery (VRPPD) via particle swarm optimisation (PSO). An effective metaheuristics search technique called particle swarm optimisation (PSO) was applied to design the optimal route for these problems. Simulated data from Li and Lim (2001) were used to evaluate the PSO performance for solving green vehicle routing problems with pickup and delivery (Green VRPPD). The findings suggest that green vehicle routing problems with pickup and delivery should be used when distributing products to customers living in a specific area called a cluster. However, the design of vehicle routes by Green VRPPD costs more when used to distribute products to customers living randomly in a coverage service area. When logistics providers decide to use Green VRPPD instead of VRPPD, they need to be concerned about possible higher costs if an increase in the number of vehicles is needed. PSO has been confirmed for solving VRPPD effectively. The study compared the results based on the use of two different objective functions with fuel consumption from diesel and liquefied petroleum gas (LPG). It indicates that solving VRPPD by considering the emissions of direct greenhouse gases as an objective function provides cleaner routes, rather than considering total cost as the objective function for all test cases. However, as Green VRPPD requires more vehicles and longer travel distances, this requires a greater total cost than considering the total cost as the objective function. Considering the types of fuels used, it is obvious that LPG is more environmentally friendly than diesel by up to 53.61 %. This paper should be of interest to a broad readership, including those concerned with vehicle routing problems, transportation, logistics, and environmental management. The findings suggest that green vehicle routing problems with pickup and delivery should be used when distributing products to a cluster. However, the design of vehicle routes by Green VRPPD costs more when used to distribute products to customers living randomly in a coverage service area. When logistics providers decide to use Green VRPPD instead of VRPPD, they need to be concerned about possible higher costs if an increase in the number of vehicles is needed.  © 2022 S. Kunnapapdeelert et al.","e-commerce; green; last-mile; particle swarm optimisation; routing","Costs; Diesel engines; Electronic commerce; Environmental management; Genetic algorithms; Greenhouse gases; Particle swarm optimization (PSO); Product design; Vehicle routing; Vehicles; E- commerces; Green; Last mile; Objective functions; Particle swarm; Particle swarm optimization; Pickup and delivery; Routings; Swarm optimization; Vehicle Routing Problems; Sales",{"$nulls":4},"Burapha University International College; Ministerstwo Edukacji i Nauki, MNiSW","The publication of the article for 11th International Conference on Engineering, Project, and Production Management - EPPM2021 was financed in the framework of the contract no. DNK/ SN/465770/2020 by the Ministry of Science and Higher Education within the \"Excellent Science\" programme. This work was financially supported by the Burapha University International College","Al-Tit A.A., E-commerce drivers and barriers and their impact on e-customer loyalty in small and medium-sized enterprises (SMES), Business: Theory and Practice, 21, 1, pp. 146-157, (2020); Bansal S., Wadhawan S., A hybrid of sine cosine and particle swarm optimization (HSPS) for solving heterogeneous fixed fleet vehicle routing problem, International Journal of Applied Metaheuristic Computing (IJAMC), 12, 1, pp. 41-65, (2021); Belmecheri F., Prins C., Yalaoui F., Amodeo L., Particle swarm optimization algorithm for a vehicle routing problem with heterogeneous fleet, mixed backhauls, and time windows, Journal of Intelligent Manufacturing, 24, 4, pp. 775-789, (2013); Bent R., Van Hentenryck P., A two-stage hybrid algorithm for pickup and delivery vehicle routing problems with time windows, Computers & Operations Research, 33, 4, pp. 875-893, (2006); Bruglieri M., Mancini S., Pisacane O., The green vehicle routing problem with capacitated alternative fuel stations, Computers & Operations Research, 112, (2019); Chen M.C., Hsiao Y.H., Reddy R.H., Tiwari M.K., The self-learning particle swarm optimization approach for routing pickup and delivery of multiple products with material handling in multiple cross-docks, Transportation Research Part E: Logistics and Transportation Review, 91, pp. 208-226, (2016); Chen N., Yang Y., The impact of customer experience on consumer purchase intention in cross-border E-commerce - taking network structural embeddedness as mediator variable, Journal of Retailing and Consumer Services, 59, (2021); Creput J.C., Koukam A., Kozlak J., Lukasik J., An evolutionary approach to pickup and delivery problem with time windows, International Conference on Computational Science, pp. 1102-1108, (2004); Fan H., Zhang Y., Tian P., Lv Y., Fan H., Time-dependent multi-depot green vehicle routing problem with time windows considering temporal-spatial distance, Computers & Operations Research, 129, (2021); Faugere L., Montreuil B., Smart locker bank design optimization for urban omnichannel logistics: Assessing monolithic vs. modular configurations, Computers & Industrial Engineering, 139, (2020); 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Lagos C., Guerrero G., Cabrera E., Moltedo A., Johnson F., Paredes F., An improved particle swarm optimization algorithm for the VRP with simultaneous pickup and delivery and time windows, IEEE Latin America Transactions, 16, 6, pp. 1732-1740, (2018); Lemke J., Iwan S., Korczak J., Usability of the parcel lockers from the customer perspective - the research in Polish Cities, Transportation Research Procedia, 16, pp. 272-287, (2016); Li H., Lim A., A metaheuristic for the pickup and delivery problem with time windows, International Journal on Artificial Intelligence Tools, 12, 2, pp. 173-186, (2003); Liu X., Zhang K., Chen B., Zhou J., Miao L., Analysis of logistics service supply chain for the One Belt and One Road initiative of China, Transportation Research Part E: Logistics and Transportation Review, 117, pp. 23-39, (2018); Mehlawat M.K., Gupta P., Khaitan A., Pedrycz W., A hybrid intelligent approach to integrated fuzzy multiple depot capacitated green vehicle routing problem with split delivery and vehicle selection, IEEE Transactions on Fuzzy Systems, 28, 6, pp. 1155-1166, (2019); Mutinda Kitukutha N., Vasa L., Olah J., The Impact of COVID-19 on the economy and sustainable e-commerce, Forum Scientiae Oeconomia, 9, 2, pp. 47-72, (2021); Norouzi N., Sadegh-Amalnick M., Tavakkoli-Moghaddam R., Modified particle swarm optimization in a time-dependent vehicle routing problem: minimizing fuel consumption, Optimization Letters, 11, pp. 121-134, (2017); Qin X., Liu Z., Tian L., The optimal combination between selling mode and logistics service strategy in an e-commerce market, European Journal of Operational Research, 289, 2, pp. 639-651, (2021); Ready C., Environmental reporting guidelines: Including mandatory greenhouse gas emissions reporting guidance, (2013); Rita P., Oliveira T., Farisa A., The impact of e-service quality and customer satisfaction on customer behavior in online shopping, Heliyon, 5, 10, (2019); Shi Y., Eberhart R., A modified particle swarm optimizer, IEEE international conference on evolutionary computation proceedings. 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No. 98TH8360), pp. 69-73, (1998); Sruthi A., Anbuudayasankar S.P., Jeyakumar G., Energy-efficient green vehicle routing problem, International Journal of Information Systems and Supply Chain Management (IJISSCM), 12, 4, pp. 27-41, (2019); Tsang Y.P., Wu C.H., Lam H.Y., Choy K.L., Ho G.T.S., Integrating Internet of Things and multi-temperature delivery planning for perishable food E-commerce logistics: a model and application, International Journal of Production Research, 59, 5, pp. 1534-1556, (2021); Ubeda S., Faulin J., Serrano A., Arcelus F.J., Solving the green capacitated vehicle routing problem using a tabu search algorithm, Lecture Notes in Management Science, 6, 1, pp. 141-149, (2014); Inventory of US Greenhouse Gas Emissions and Sinks: 1990-1997, (1999); Vakulenko Y., Shams P., Hellstrom D., Hjort K., Service innovation in e-commerce last mile delivery: Mapping the e-customer journey, Journal of Business Research, 101, pp. 461-468, (2019); Van Lopik K., Schnieder M., Sharpe R., Sinclair M., Hinde C., Conway P., West A., Maguire M., Comparison of in-sight and handheld navigation devices toward supporting industry 4.0 supply chains: First and last mile deliveries at the human level, Applied Ergonomics, 82, (2020); Xu X., Wang C., Li J., Shi C., Green Transportation and Information Uncertainty in Gasoline Distribution: Evidence from China, Emerging Markets Finance and Trade, 57, 11, pp. 1-19, (2019); Yu Y., Wang S., Wang J., Huang M., A branch-and-price algorithm for the heterogeneous fleet green vehicle routing problem with time windows, Transportation Research Part B: Methodological, 122, pp. 511-527, (2019); Yu Y., Yu C., Xu G., Zhong R.Y., Huang G.Q., An operation synchronization model for distribution center in E-commerce logistics service, Advanced Engineering Informatics, 43, (2020); Yuen K.F., Wang X., Ma F., Wong Y.D., The determinants of customers' intention to use smart lockers for last-mile deliveries, Journal of Retailing and Consumer Services, 49, pp. 316-326, (2019); Zhang X., Zhou G., Cao J., Wu A., Evolving strategies of e-commerce and express delivery enterprises with public supervision, Research in Transportation Economics, 80, (2020); Zhou M., Zhao L., Kong N., Campy K.S., Xu G., Zhu G., Cao X., Wang S., Understanding consumers' behavior to adopt self-service parcel services for last-mile delivery, Journal of Retailing and Consumer Services, 52, (2020); Zhu L., Hu D., Study on the vehicle routing problem considering congestion and emission factors, International Journal of Production Research, 57, 19, pp. 6115-6129, (2019)","S. Kunnapapdeelert; Burapha University, International College, Thailand; email: siwapornk@go.buu.ac.th",null,"De Gruyter Open Ltd",{"$nulls":5},2.5436597E7,null,null,null,"English","Eng.  Manag.  Prod.  Serv.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85134488265"]
["Hansopaheluwakan S.; Arief Elidjen M.; Utami Tjhin V.","Hansopaheluwakan, S. (57208330493); Arief Elidjen, M. (56820271200); Utami Tjhin, V. (58062252400)","57208330493; 56820271200; 58062252400","The Factors Influencing E-Customer Satisfaction and Its Impact on E-Customer Loyalty Moderated by Guanxi in Pandemic Era",2022.0,"Journal of System and Management Sciences",12.0,6.0,null,252.0,263.0,11.0,2.0,"10.33168/JSMS.2022.0616","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85146190627&doi=10.33168%2fJSMS.2022.0616&partnerID=40&md5=82f57077ab1080b638acabb88595d298","Research in Management, Binus Business School, Bina Nusantara University, Indonesia","Hansopaheluwakan S., Research in Management, Binus Business School, Bina Nusantara University, Indonesia; Arief Elidjen M., Research in Management, Binus Business School, Bina Nusantara University, Indonesia; Utami Tjhin V., Research in Management, Binus Business School, Bina Nusantara University, Indonesia","The quality level of integration between the channels is important and becomes one of the most significant innovations in fashion industry. Besides, the logistics service quality can also influence the e-customer satisfaction and get the e-customer loyalty. This study is conducted to indicate the relationship between those variables for apparel. The research data will be collected using online questionnaire with 303 e-customers with omnichannel experience in fashion during pandemic era. This quantitative research will be analyzed by using Structural Equation Model. The finding of this research is the logistic service quality and omnichannel customer experience significantly influence e-customer satisfaction and e-customer loyalty. However, omnichannel integrated quality has no impact to e-customer satisfaction and e-customer loyalty, even moderated with guanxi. The novelty of this study is the use of guanxi as moderating. This research supports the fashion industry in e-commerce to get their customer satisfaction and customer loyalty. © 2022, Success Culture Press. All rights reserved.","e-customer loyalty; e-customer satisfaction; fashion industry; logistic service quality; omnichannel",{"$nulls":7},"Berlianto M. P., Pengaruh Kualitas Layanan-E, Kepuasan-E, Dan Kepercayaan-E Terhadap Kesetiaan-E Pada Gojek, Business Management Journal, 13, 1, pp. 1-28, (2017); Berlianto M. P., Pengaruh Kualitas Layanan-E, Kepuasan-E, Dan Kepercayaan-E Terhadap Kesetiaan-E Pada Gojek, Business Management Journal, 13, 1, pp. 1-28, (2017); Cao L., Li L., Determinants of retailers’ cross-channel integration: An innovation diffusion perspective on omni-channel retailing, Journal of Interactive Marketing, 44, pp. 1-16, (2018); Cresswell J. W., Cresswell J. D., Research Design: Qualitative, Quantitative, and Mixed Methods Approaches (5th ed.), (2018); Ghofar A., Islam S. M. N., Yoo W. S., Lee Y., Park J. K., Zeithaml Berry, Parasunaman, The nature and determinants of costumer expectations of services.pdf, Contributions to Management Science, 17, 2, pp. 1-12, (1988); Giao H. N. K., Vuong B. N., Quan T. N., The influence of website quality on consumer’s e-loyalty through the mediating role of e-trust and e-satisfaction: An evidence from online shopping in Vietnam, Uncertain Supply Chain Management, 8, 2, pp. 351-370, (2020); Hallowell R., The relationships of customer satisfaction, customer loyalty, and profitability: An empirical study, International Journal of Service Industry Management, 7, 4, pp. 27-42, (1996); Hamouda M., Omni-channel banking integration quality and perceived value as drivers of consumers’ satisfaction and loyalty, Journal of Enterprise Information Management, 32, 4, pp. 608-625, (2019); DIGITAL 2021: INDONESIA, (2021); Hossain T. M. T., Akter S., Kattiyapornpong U., Dwivedi Y., Reconceptualizing integration quality dynamics for omnichannel marketing, Industrial Marketing Management, (2020); Lemon K. N., Verhoef P. C., Understanding customer experience throughout the customer journey, Journal of Marketing, 80, 6, pp. 69-96, (2016); Lenka U., Suar D., Mohapatra P. K. J., Service quality, customer satisfaction, and customer loyalty in Indian commercial banks, Journal of Entrepreneurship, 18, 1, pp. 47-64, (2009); Lynch S., Barnes L., Omnichannel fashion retailing: Examining the customer decision-making journey, Journal of Fashion Marketing and Management, 24, 3, pp. 471-493, (2020); Nugroho R., Atmojo P., Budiastuti D., Abbas B. S., Kosala R., social sciences & humanities the effect of e-wom and structural assurances mediated by guanxi towards customer behavioral loyalty, Pertanika J. Soc. Sci. & Hum, 27, 3, pp. 1593-1607, (2019); Rodriguez-Torrico P., Trabold Apadula L., San-Martin S., San JoseCabezudo R., Have an omnichannel seamless interaction experience! Dimensions and effect on consumer satisfaction, Journal of Marketing Management, (2020); Rodriguez P. G., Villarreal R., Valino P. C., Blozis S., A PLS-SEM approach to understanding e-SQ, e-satisfaction and e-loyalty for fashion e-retailers in Spain, Journal of Retailing and Consumer Services, 57, (2020); Sai Vijay T., Prashar S., Sahay V., The influence of online shopping values and web atmospheric cues on e-loyalty: Mediating role of e-satisfaction, Journal of Theoretical and Applied Electronic Commerce Research, 14, 1, pp. 1-15, (2019); Senic V., Marinkovic V., Examining the effect of different components of customer value on attitudinal loyalty and behavioral intentions, International Journal of Quality and Service Sciences, 6, 2–3, pp. 134-142, (2014); Shen X. L., Li Y. J., Sun Y., Wang N., Channel integration quality, perceived fluency and omnichannel service usage: The moderating roles of internal and external usage experience, Decision Support Systems, 109, pp. 61-73, (2018); Sorkun M. F., Yumurtaci Huseyinoglu I. O., Boruhan G., Omni-channel capability and customer satisfaction: Mediating roles of flexibility and operational logistics service quality, International Journal of Retail and Distribution Management, 48, 6, pp. 629-648, (2020); Thakur R., The moderating role of customer engagement experiences in customer satisfaction–loyalty relationship, European Journal of Marketing, 53, 7, pp. 1278-1310, (2019); Verhoef P. C., Kannan P. K., Inman J. J., From multi-channel retailing to omni-channel retailing. Introduction to the special issue on multi-channel retailing, Journal of Retailing, 91, 2, pp. 174-181, (2015); Wan Ju S, An empirical study on the influence of service quality of association on customer satisfaction: the moderating effect of willingness to participate, Journal of System and Management Sciences, 12, 4, pp. 39-56, (2022)","S. Hansopaheluwakan; Research in Management, Binus Business School, Bina Nusantara University, Indonesia; email: scherly.hansopaheluwakan@binus.ac.id",null,"Success Culture Press",{"$nulls":5},1.8166075E7,null,null,null,"English","J. Syst. Manag. Sci.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85146190627"]
["Zhu Z.; Zhu M.","Zhu, Zhihui (58833007300); Zhu, Meifang (58728909000)","58833007300; 58728909000","Evaluation Method of Performance of Cross-Border e-Commerce System Based on Fuzzy DEA Model",2022.0,"Mobile Information Systems",2022.0,null,1456584.0,null,null,null,1.0,"10.1155/2022/1456584","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85138389156&doi=10.1155%2f2022%2f1456584&partnerID=40&md5=f9d4e7b773f3e7ea4ca198e5e1a0580d","Guangzhou Maritime University, Guangzhou, 510725, China; Guangdong Lingnan Institute of Technology, Guangzhou, 511510, China","Zhu Z., Guangzhou Maritime University, Guangzhou, 510725, China; Zhu M., Guangdong Lingnan Institute of Technology, Guangzhou, 511510, China","Cross-border e-commerce trade is an important form of trade that is different from traditional international trade. Nowadays, cross-border e-commerce is more and more widely used in foreign trade activities. Cross-border e-commerce system has its own development constraints, such as the imperfection of cross-border e-commerce platforms, the security loopholes of cross-border payment, the slow development of supporting logistics, and the lag of policies, which will affect its development to varying degrees, thus affecting the performance of e-commerce enterprises in using cross-border e-commerce for foreign trade activities. Therefore, it is necessary to explore the factors of cross-border e-commerce system performance and compare the strength of various factors, which has certain theoretical and practical significance. Therefore, based on the analysis of performance data, this paper will establish a performance evaluation model for an e-commerce system, aiming at providing standards and a basis for performance evaluation of system performance. In order to continuously improve the accuracy of cross-border e-commerce performance evaluation and to achieve the accuracy of cross-border e-commerce evaluation and decision-making, a cross-border e-commerce system performance evaluation model based on the fuzzy DEA model is innovatively proposed. By combining the average analysis results of descriptive statistical data, the regression test is conducted on the performance evaluation samples of cross-border e-commerce systems. The fuzzy feature clustering method is used to classify and identify the performance of big data in the cross-border e-commerce system. According to the fusion results of cross-border e-commerce performance information, the principal component analysis and adaptive game decision are carried out, and the game decision model is established. Combined with the fuzzy DEA evaluation method, the performance of the cross-border e-commerce system can be quantified and evaluated. The F statistical analysis method is used to test the effectiveness of the performance evaluation of the cross-border e-commerce system. From the test results, it can be seen that the performance evaluation accuracy of the cross-border e-commerce system using this model is relatively high, and the confidence level is also relatively good. Finally, according to the conclusion of the study, the author puts forward the counter-measures for future research.  © 2022 Zhihui Zhu and Meifang Zhu.",null,"Cluster analysis; Decision making; Electronic commerce; Principal component analysis; Commerce platforms; Cross-border; DEA models; E- commerces; E-commerce systems; Evaluation methods; Performance; Performance evaluation models; Performances evaluation; Systems performance; International trade",{"$nulls":6},"Chen H., Chen P., Yang H., Li W., An empirical analysis of pricing power of offshore and onshore RMB interest rates - Based on spillover index and its dynamic path, International Finance Research, 350, 6, pp. 86-96, (2016); Liu K., Wang Z., Zou H., The influence of monetary policy on the dynamic process of short-term market interest rate-An empirical study based on SHIBOR, Contemporary Economic Science, 38, 2, pp. 30-40, (2016); Marcel F., Capital flows push versus pull factors and the global financial crisis, Journal of International Economics, 88, 2, pp. 341-356, (2011); Taguchi H., Sahoo P., Nataraj G., Capital flows and asset prices: Empirical evidence from emerging and developing economies, International Economics, 141, 5, pp. 1-14, (2015); Luo Z., Du J., Hu A., How to avoid risks for internet financial platform managers, Economist, 7, pp. 32-34, (2016); Sherman H.X., Zhou Y., Analysis of the elements of network security and information security in Internet finance, Journal of Sichuan University Social Science Edition, 4, pp. 27-36, (2015); Min B.A.I., Yafeng Q.I.N., Short-sales constraints and liquidity change:cross-sectional evidence from the Hong Kong market, Pacific-Basin Finance Journal, 26, pp. 98-122, (2014); Olesya L.O.B.A.N.O.V.A., Shahid S.H., Arun J.P., Shot sales ban and stock market liquidity:the comparison of NYSE and NASDAQ-listed stocks, International Journal of Finance, 23, 2, pp. 6750-6763, (2011); William F., JOHNSON. Did margin rules and financial development affect returns and volatility during the market crash of 2007-2008?, Journal of Investing, 19, 3, pp. 33-45, (2010); Luo R., Ming M., Wu K., Nonlinear dynamic analysis of linkage between China's stock market and bond market, Journal of Central University of Finance & Economics, 34, 3, pp. 39-47, (2014)","Z. Zhu; Guangzhou Maritime University, Guangzhou, 510725, China; email: 99968571@qq.com",null,"Hindawi Limited",{"$nulls":5},"1574017X",null,null,null,"English","Mob. Inf. Sys.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85138389156"]
["Zhang M.; Lu J.; Ma N.; Cheng T.C.E.; Hua G.","Zhang, M. (57201356508); Lu, J. (58428729200); Ma, N. (58592333600); Cheng, T.C.E. (13302593800); Hua, G. (24724222400)","57201356508; 58428729200; 58592333600; 13302593800; 24724222400","A Feature Engineering and Ensemble Learning Based Approach for Repeated Buyers Prediction",2022.0,"International Journal of Computers, Communications and Control",17.0,6.0,4988.0,null,null,null,3.0,"10.15837/ijccc.2022.6.4988","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85144952380&doi=10.15837%2fijccc.2022.6.4988&partnerID=40&md5=2b89016a8101a288e2bd2b14492a89db","Department of Management Science and Engineering, School of Economics and Management Beijing Forestry University, China No. 35 Qinghua East Road,Haidian, Beijing, 100083, China; National Science Library, Chinese Academy of Sciences, 33 Beisihuan Xilu,Zhongguancun, Beijing, 100190, China; School of Economics and Management, University of Chinese Academy of Sciences, No.19A Yuquan Road, Beijing, 100049, China; Department of Logistics and Maritime Studies, The Hong Kong Polytechnic University, M923,Li Ka Shing Tower, Hong Kong; Department of Logistics Management, School of Economics and Management, Beijing Jiaotong University, China Siyuan East Building,Beijing Jiaotong University,Haidian, Beijing, 100044, China","Zhang M., Department of Management Science and Engineering, School of Economics and Management Beijing Forestry University, China No. 35 Qinghua East Road,Haidian, Beijing, 100083, China; Lu J., National Science Library, Chinese Academy of Sciences, 33 Beisihuan Xilu,Zhongguancun, Beijing, 100190, China, School of Economics and Management, University of Chinese Academy of Sciences, No.19A Yuquan Road, Beijing, 100049, China; Ma N., Department of Management Science and Engineering, School of Economics and Management Beijing Forestry University, China No. 35 Qinghua East Road,Haidian, Beijing, 100083, China; Cheng T.C.E., Department of Logistics and Maritime Studies, The Hong Kong Polytechnic University, M923,Li Ka Shing Tower, Hong Kong; Hua G., Department of Logistics Management, School of Economics and Management, Beijing Jiaotong University, China Siyuan East Building,Beijing Jiaotong University,Haidian, Beijing, 100044, China","The global e-commerce market is growing at a rapid pace, but the percentage of repeat buyers is low. According to Tmall, the repurchase rate is only 6.1%, while research shows that a 5% increase in the repurchase rate can lead to a 25% to 95% increase in profit. To increase the repurchase rate, merchants need to predict potential repeat buyers and convert them into repurchasers. Therefore, it is necessary to predict repeat buyers. In this paper we build a prediction model of repeat purchasers using Tmall’s dataset. First, we build high-quality feature engineering for e-commerce scenarios by manual construction and algorithmic selection. We introduce the synthetic minority oversampling technique (SMOTE) algorithm to solve the data imbalance problem and improve prediction performance. Then we train classical classifiers including factorization machine and logistic regression, and ensemble learning classifiers including extreme gradient boosting, and light gradient boosting machine machines. Finally, we construct a two-layer fusion model based on the Stacking algorithm to further enhance prediction performance. The results show that through a series of innovations such as data imbalance processing, feature engineering, and fusion models, the model area under curve (AUC) value is improved by 0.01161. Our findings provide important implications for managing e-commerce platforms and the platform merchants. © 2021 by the authors. Licensee Agora University, Oradea, Romania. This is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial 4.0 International License.","Ensemble learning; Feature engineering; Fusion model; Repeat buyer prediction",{"$nulls":5},"National Natural Science Foundation of China, NSFC, (71901027); Beijing Forestry University, BJFU, (2021KCSZXY010)","Supported by Natural Science Foundation of China(71901027); Beijing Forestry University 2021 Course Ideological and Political Teaching, Research and Teaching Reform Project, \"Management Model and Basic Decision-making\" project(2021KCSZXY010)","Abel F., Gao Q., Houben G. J., Tao K., Analyzing user modeling on twitter for personalized news recommendations, International Conference on User Modeling, Adaptation, And Personalization, pp. 1-2, (2011); Belem F. M., Silva R. M., de Andrade C. M., Person G., Mingote F., Ballet R., Alponti H., de Oliveira H. P., Almeida J. M., Goncalves M. 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O., Polat S. O., Katircioglu M., Kastro Y., Real-time prediction of online shoppers’ purchasing intention using multilayer perceptron and LSTM recurrent neural networks, Neural Computing and Applications, 31, 10, pp. 6893-6908, (2019); Schapire R. E., Freund Y., A decision-theoretic generalization of on-line learning and an application to boosting, Journal of computer and system sciences, 55, 1, pp. 119-139, (1997); Shen Y., Xu X., Cao J., Reconciling predictive and interpretable performance in repeat buyer prediction via model distillation and heterogeneous classifiers fusion, Neural Computing and Applications, 32, 13, pp. 9495-9508, (2020); Tripathi P., Singh S., Chhajer P., Trivedi M. C., Singh V. K., Analysis and prediction of extent of helpfulness of reviews on E-commerce websites, Materials Today: Proceedings, 33, pp. 4520-4525, (2020); Van Nguyen T., Zhou L., Chong A. Y. L., Li B., Pu X., Predicting customer demand for remanufactured products: A data-mining approach, European Journal of Operational Research, 281, 3, pp. 543-558, (2020); Wolpert D. H., Stacked generalization, Neural networks, 5, 2, pp. 241-259, (1992); Wu P. J., Yang D., E-Commerce Workshop Scheduling Based on Deep Learning and Genetic Algorithm, Int. Journal of Simulation Model ling, 20, 1, pp. 192-200, (2021); Xu J., Kim H.K., A study on the factors influencing consumers’ purchase intention towards Chinese beauty industry: focusing on SNS characteristic elements, Journal of Logistics, Informatics and Service Science, 8, 2, pp. 47-64, (2021); Yin X. C., Liu C. P., Han Z., Feature combination using boosting, Pattern Recognition Letters, 26, 14, pp. 2195-2205, (2005); Zhang H., Dong J., Prediction of repeat customers on E-commerce platform based on blockchain, Wireless Communications and Mobile Computing, 2020, (2020); Zhang Z., Zeng D. D., Abbasi A., Peng J., Zheng X., A random walk model for item recommendation in social tagging systems, ACM Transactions on Management Information Systems, 4, 2, pp. 1-24, (2013)","N. Ma; Department of Management Science and Engineering, School of Economics and Management Beijing Forestry University, Haidian,Beijing, China No. 35 Qinghua East Road, 100083, China; email: maning@bjfu.edu.cn",null,"Agora University",{"$nulls":5},1.8419836E7,null,null,null,"English","Int. J. Comput. Commun. Control","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85144952380"]
["Liu G.; Zhu Y.","Liu, Guangqian (57748633400); Zhu, Yiming (57748952200)","57748633400; 57748952200","Logistics Optimization Strategy Based on Deep Neural Framework",2022.0,"Computational Intelligence and Neuroscience",2022.0,null,8367155.0,null,null,null,1.0,"10.1155/2022/8367155","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85132160329&doi=10.1155%2f2022%2f8367155&partnerID=40&md5=b3b10c74264829d2f9503e931c61073e","College of Business Administration and Accountancy, De la Salle University-Dasmariñas, Cavite, 4115, Philippines","Liu G., College of Business Administration and Accountancy, De la Salle University-Dasmariñas, Cavite, 4115, Philippines; Zhu Y., College of Business Administration and Accountancy, De la Salle University-Dasmariñas, Cavite, 4115, Philippines","We propose a logistics optimization method based on improved graph convolutional networks to address the current problem of low product delivery rate and untimely product delivery during the peak period of e-commerce activities. Our method can learn excellent planning strategies from previous data and can give the best logistics strategy in time during the peak logistics period, which improves the product delivery rate and delivery time of logistics and greatly enhances the return on investment. First, we add a tensor rotation module to the graph convolution layer to better capture the global features of logistics nodes. Then we add inception structures in the temporal convolution layer to build multiscale temporal convolution filters to obtain temporal information of logistics nodes in different time-aware domains and reduce arithmetic power. Finally, we cooperate with e-commerce platforms to adopt logistics data as the experimental database. The experimental results show that our method greatly accelerates the logistics planning speed, improves the product delivery rate, ensures the timely delivery of products, and increases the return on investment. © 2022 Guangqian Liu and Yiming Zhu.",null,"Commerce; Databases, Factual; Electronic commerce; Investments; Profitability; Convolutional networks; Current problems; E- commerces; Learn+; Logistics optimization; Optimization method; Optimization strategy; Peak period; Product delivery; Returns on investment; commercial phenomena; factual database; Convolution",{"$nulls":6},"Amudha G., Narayanasamy P., Distributed location and trust based replica detection in wireless sensor networks, Wireless Personal Communications, 102, 4, pp. 3303-3321, (2018); Hu L., Nguyen N.-T., Tao W., Leu M.C., Liu X.F., Shahriar D.M.R., Sunny S.M.N.A.L., Modeling of cloud-based digital twins for smart manufacturing with MT connect, Procedia Manufacturing, 26, pp. 1193-1203, (2018); Manogaran G., Balasubramanian V., Rawal B.S., Saravanan V., Marin C.E.M., Ramachandran V., Kumar P.M., Multi-variate data fusion technique for reducing sensor errors in intelligent transportation systems, IEEE Sensors Journal, 21, 14, pp. 15564-15573, (2021); Ding Y., Jin M., Li S., Feng D., Smart logistics based on the internet of things technology: An overview, International Journal of Logistics Research and Applications, 24, 4, pp. 323-345, (2021); Dhote S., Vichoray C., Pais R., Baskar S.P., Hybrid geometric sampling and AdaBoost based deep learning approach for data imbalance in E-commerce, Electronic Commerce Research, 20, 2, pp. 259-274, (2020); Nguyen N.T., Leu M.C., Liu X.F., RTEthernet: Real-time communication for manufacturing cyberphysical systems, Transactions on Emerging Telecommunications Technologies, 29, 7, (2018); Khatib E.J., Barco R., Optimization of 5G networks for smart logistics, Energies, 14, 6, (2021); Wang H., Zhang Y., Ding W., Zhu Y., Lu H., Yue H., Dai X., Li D., Zhu X., Xu X., 7, pp. 1-9, (2021); Manogaran G., Hsu C.-H., Rawal B.S., Muthu B.C.X.G., ISOF: Information scheduling and optimization framework for improving the performance of agriculture systems aided by industry 4.0, IEEE Internet of Things Journal, 8, 5, pp. 3120-3129, (2021); Preeth S.K., Dhanalakshmi R., Kumar R., Shakeel P.M., An adaptive fuzzy rule based energy efficient clustering and immune-inspired routing protocol for WSN-assisted IoT system, Journal of Ambient Intelligence and Humanized Computing, pp. 1-13, (2018); Amudha G., Dilated transaction access and retrieval: Improving the information retrieval of blockchain-assimilated internet of things transactions, Wireless Personal Communications, pp. 1-21, (2021); Gao J., Wang H., Shen H., Machine Learning Based Workload Prediction in Cloud Computing, pp. 1-9; Gong S., Samuel D.J.R., Pandian S., Meta heuristic feature optimization for ontology-based data security in a campus workplace with robotic assistance, Work, 68, 3, pp. 913-922, (2021); Zaghloul A., Zhang T., Amin M., Latif A.A.A.E.L., Color Encryption Scheme Based on Adapted Quantum Logistic Map, 9159, pp. 412-415; Cao Y., Jia F., Manogaran G., Efficient traceability systems of steel products using blockchain-based industrial internet of things, IEEE Transactions on Industrial Informatics, 16, 9, pp. 6004-6012, (2020); Bhardwaj A., Shah S.B.H., Shankar A., Alazab M.M.T.R., Penetration testing framework for smart contract Blockchain, Peer-to-Peer Networking and Applications, 14, 5, pp. 2635-2650, (2021); Xue M., Xiu G., Saravanan V., Montenegro-Marin C.E., Cloud Computing with AI for Banking and E-Commerce Applications, (2020); El-Latif A.A.A., Abd-El-Atty B., Venegas-Andraca S.E., Elwahsh H.M., Providing end-to-end security using quantum walks in IoT networks, IEEE Access, 8, pp. 92687-92696, (2020); Gaber T., Abdelwahab S., Elhoseny M., Hassanien A.E., Trust-based secure clustering in WSN-based intelligent transportation systems, Computer Networks, 146, pp. 151-158, (2018); Liang T., Wang H., Consumer decision-making and smart logistics planning based on FPGA and convolutional neural network, Microprocessors and Microsystems, 80, (2021); Alsahfi T., Almotairi M., Elmasri R., A survey on trajectory data warehouse, Spatial Information Research, 28, 1, pp. 53-66, (2020); Dharmasiri P., Kavalchuk I., Akbari M., Novel implementation of multiple automated ground vehicles traffic real time control algorithm for warehouse operations: Djikstra approach, Operations and Supply Chain Management: International Journal, 13, 4, pp. 396-405, (2020); 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Kipf T.N., Welling M., Semi-supervised Classification with Graph Convolutional Networks, (2016); Shi L., Zhang Y., Cheng J., Lu H., Two-stream Adaptive Graph Convolutional Networks for Skeleton-based Action Recognition, pp. 12026-12035; Jia Z., Lin Y., Wang J., Ning X., He Y., Zhou R., Zhou Y., Lehman I.W.L.H., Multi-view spatial-temporal graph convolutional networks with domain generalization for sleep stage classification, IEEE Transactions on Neural Systems and Rehabilitation Engineering, 29, pp. 1977-1986, (2021); Jia Z., Cai X., Jiao Z., Multi-modal physiological signals based squeeze-and-excitation network with domain adversarial learning for sleep staging, IEEE Sensors Journal, (2022); Sam S.M., Kamardin K., Sjarif N.N.A., Mohamed N., Offline signature verification using deep learning convolutional neural network (CNN) architectures GoogLeNet inception-v1 and inception-v3, Procedia Computer Science, 161, pp. 475-483, (2019); Chen F., Wei J., Xue B., Zhang M., Feature fusion and kernel selective in Inception-v4 network, Applied Soft Computing, 119, (2022); Abdul W., Alsulaiman M., Amin S.U., Faisal M., Muhammad G., Albogamy F.R., Bencherif M.A., Ghaleb H., Intelligent real-time Arabic sign language classification using attention-based inception and BiLSTM, Computers & Electrical Engineering, 95, (2021); Jia Z., Junyu J., Zhou X., Zhou Y., Hybrid Spiking Neural Network for Sleep EEG Encoding, Science China Information Sciences, 65, 4, (2022); Jia Z., Lin Y., Liu Y., Jiao Z.J., Refined nonuniform embedding for coupling detection in multivariate time series, Physical Review A, 101, 6, (2020); Jia Z., Cai X., Hu Y., Jiao J., Zehui J.I., Delay propagation network in air transport systems based on refined nonlinear Granger causality, Transportation Business: Transport Dynamics, 10, 1, pp. 586-598, (2022)","Y. Zhu; College of Business Administration and Accountancy, De la Salle University-Dasmariñas, Cavite, 4115, Philippines; email: zyx0043@dlsud.edu.ph",null,"Hindawi Limited",{"$nulls":5},1.6875265E7,null,null,3.5707201E7,"English","Comput. Intell. Neurosci.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85132160329"]
["Zeng M.; Liu R.; Gao M.; Jiang Y.","Zeng, Minling (57796271800); Liu, Runmin (57223883619); Gao, Ming (57226303727); Jiang, Yizhang (55437846600)","57796271800; 57223883619; 57226303727; 55437846600","Demand Forecasting for Rural E-Commerce Logistics: A Gray Prediction Model Based on Weakening Buffer Operator",2022.0,"Mobile Information Systems",2022.0,null,3395757.0,null,null,null,13.0,"10.1155/2022/3395757","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85133978960&doi=10.1155%2f2022%2f3395757&partnerID=40&md5=bc0b945721f8c9341d2e4c0e6f68a1d3","Department of Finance and Economics, Software Engineering Institute of Guangzhou, Guangzhou, 510000, China; College of Sports Engineering & Information Technology, Wuhan Sports University, Wuhan, 430079, China; College of Sports Science and Technology, Wuhan Sports University, Wuhan, 430079, China; School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi, 214122, China","Zeng M., Department of Finance and Economics, Software Engineering Institute of Guangzhou, Guangzhou, 510000, China; Liu R., College of Sports Engineering & Information Technology, Wuhan Sports University, Wuhan, 430079, China; Gao M., College of Sports Science and Technology, Wuhan Sports University, Wuhan, 430079, China; Jiang Y., School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi, 214122, China","With the advancement of Internet technology and the widespread use of mobile smartphones, urban e-commerce is becoming increasingly saturated. Rural e-commerce ushered in a new era of development. How to improve rural logistics carrying capacity to keep up with the development of rural e-commerce and better serve the development of rural e-commerce has become a hot topic. The purpose of this study is to predict logistics demand in the context of the development of rural e-commerce. We develop an indicator system for forecasting rural logistics demand in Guangdong Province. The GM (1,1) gray forecasting model with a weakening buffer operator was used to forecast rural logistics demand in Guangdong Province. According to the results, the prediction model has good matching and precision. It was also found that demand for rural logistics in Guangdong Province will generally rise in the short to medium term. Based on the findings of this study, the government should stimulate demand for rural consumer goods, encourage technological innovation, develop an Internet-rural logistics mode, and meet the supply requirements of rural logistics based on the situation of each region.  © 2022 Minling Zeng et al.",null,"Buffer storage; Mobile commerce; System theory; Demand forecasting; E- commerces; Grey prediction model; Guangdong Province; Hot topics; Internet technology; Logistics demand; Model-based OPC; Rural logistics; Smart phones; Forecasting",{"$nulls":6},"Xiong Z.K., How to build a three-level logistics system to break through the \"last-mile\" of rural e-commerce, Agr Eng Technol, 39, 24, (2019); Li X.Q., Analysis on the optimization of agricultural products logistics distribution system, J. Commer. Econ., 24, pp. 95-97, (2017); Crowell J.F., Report of the industrial commission on the distribution of farm products US Gov, Print. Office, 3, (1901); Holl A., Mariotti I., Highways and firm performance in the logistics industry, Journal of Transport Geography, 72, pp. 139-150, (2018); Li Y., A cloud computing-based intelligent forecasting method for cross-border E-commerce logistics costs, Advances in Mathematical Physics, 2000, (2022); Ren X., Tan J., Qiao Q., Wu L., Ren L., Meng L., Demand forecast and influential factors of cold chain logistics based on a grey model, Mathematical Biosciences and Engineering, 19, 8, pp. 7669-7686, (2022); Wang C.Q., Analysis of development factors of rural logistics system based on ISM model, J. Fujian Bus. Univ., 1, pp. 62-67, (2020); Hao C., Analysis on the influencing factors of rural logistics distribution network construction, Agricultural Economics, 6, pp. 143-144, (2018); Gebresenbet G., Bosona T., Logistics and Supply Chains in Agriculture and Food Pathways to Supply Chain Excellence, (2012); Bernhardt H., Mederle M., Treiber M., Woerz S., Aspects of Digization in Agricultural Logistics in Germany Sci, (2018); Zhou Y.R., Yuan B., System reform and reconstruction of rural logistics under the concept of smart circulation, Converter, 2021, 8, pp. 426-436, (2022); Huang F.H., Gong R.F., Jiang X.L., Research on the cooperative development mode of rural e-commerce and rural logistics - A case study of Hunan province, Of Commer. Econ, 12, 22, pp. 114-116, (2017); Yang Y., Hu Y.L., Research on the business mode of rural logistics in China under the background of supply-side reform, Commer Econ, 34, 9, pp. 100-102, (2019); Pan J.Q., The research on the combined forecast and strategy of Henan province's rural logistics demand Log, Engineering Management, 32, 1, pp. 54-56+59, (2010); Ding H.P., Hu F.G., Guo Y.X., Demand forecast of rural logistics in Anhui province based on GM (1, 1) model, Guangxi Norm. Univ. Nationalities, 34, 5, pp. 46-49, (2017); Gong L., On the forecast of rural logistics demands based on the grey neural network model, Heihe Univ, 9, 12, pp. 35-36, (2018); Wang X.L., Zhang X.Y., On necessity and feasibility of establishing rural logistics system in China, Res. Agr. Modernization, 22, 4, pp. 263-266, (2002); Wang X.L., Primary discussion about the development of agricultural industrialization and the establishment of country logistics system Probl, Of Agr. Econ, 56, 4, pp. 23-26+79, (2003); Yi X.Q., Fu H.L., Liu G.H., Analysis on the development prospect of rural logistics in China Agr, Economic Times, 77, 4, pp. 51-52, (2004); Chen J.H., The cultivation and development of rural logistics market Hunan Agr, Science, 6, pp. 5-7, (2006); Chen J., Action of the modern rural logistics in increase of peasant's incomes, J. Hebei Agr. Sci., 3, pp. 158-159, (2008); Liu W., Preliminary study on logistics distribution mode of rural e-commerce in China Rural Econ, Science and Technology, 24, 9, pp. 48-49+59, (2013); Hu Y.L., Bao J.H., Research on China's rural logistics business model under the background of supply side reform: Current situation, defects and optimization path Mod, Economic Research, 12, pp. 127-132, (2018); Zhang X.L., Research on the path of rural logistics development under the rural revitalization strategy Contemp, Economics and Management, 41, 4, pp. 46-51, (2019); Li S.R., Construction of rural logistics system based on agricultural industrialization Log, The Tech, 33, 1, pp. 34-36+40, (2014); Yang Y., Development of the regional freight transportation demand prediction models based on the regression analysis methods, Neurocomputing, 158, pp. 42-47, (2015); Zhao Y.J., Chen Y., Application of time series analysis in logistics demand forecasting Log, The Tech, 40, 6, pp. 12-14, (2017); Yang Z., Cao Z.Q., Li J.H., Forecast of the demand analysisof agricultural cold chain in Guangxi based on grey prediction method Log, Engineering Management, 39, 9, pp. 86-88, (2017); Zhao G., Research on logistics distribution demand prediction based on grey Markov model, Math. Pract. Theor., 41, 21, pp. 17-21, (2011); Li R., Zhang W.Y., Rui L.I., Energy demand forecast in the logistics sector based on RBF neural networks Resour, Science, 38, 3, pp. 450-460, (2016); Li H.-Z., Guo S., Li C.-J., Sun J.-Q., A hybrid annual power load forecasting model based on generalized regression neural network with fruit fly optimization algorithm, Knowledge-Based Systems, 37, 2, pp. 378-387, (2013); Lin M.M., Chen J.Y., Chen M.M., Design of Regional logistics traffic volume distribution forecast system for agricultural products, Shandong Agr. Sci., 48, 11, pp. 149-151, (2016); Yu L.J., Yang L., Jiang Y.Q., Prediction and analysis of demand for logistics talent in Shandong province based on combined forecasting method Log, Engineering Management, 39, 1, pp. 175-177, (2017); Guo J., Liu J.P., Ren H.S., Liu X.L., Combination forecasting analysis of agricultural product logistics demand in China - Based on PLS, BP neural network and ARIMA model, Jiamusi Univ. (Natural Science Edition), 35, 5, pp. 852-856, (2017); Shao M.C., Analysis and Forecast of Rural Logistics Demand in Henan Province, (2012); Huang L.J., Xie G.J., Blenkinsoj, Huang L.Y., Hou B., Crowdsourcing for sustainable urban logistics: Exploring the factors influencing, Crowd Workers' Participative Behavior Sustainability, 12, 8, pp. 1-20, (2020); Bin H., Zhao F., Xie G., Huang L., Wang H., Zhu R., Jiang L., Crowd-sourcing a way to sustainable urban logistics: What factors influence enterprises' willingness to implement crowd logistics?, IEEE Access, 8, pp. 225064-225075, (2020); Deng J.L., Control problems of grey systems Sys, & Contr. Lett., 1, 5, pp. 288-294, (1982); Liu S.F., The three axioms of buffer operator and their application to GM (1, 1) prediction, J. Gray Syst., 3, 1, (1991); Xie N.M., Liu S.F., A new applicative weakening buffer operator Chin, J. Manage. Sci., 11, Z1, pp. 46-48, (2003); Dang Y.G., Liu S.F., Liu B., Study on the buffer weakening operator Chin, J. Manage. Sci., 5, 2, pp. 108-111, (2004); Guan Y.Q., Liu S.F., Study on the weakening buffer operator sequence Chin, J. Manage. Sci., 15, 4, pp. 89-92, (2007); Cui J., Dang Y.G., Liu S.F., Analysis on modeling accuracy of GM (1, 1) based on new weakening operators Syst, Eng-Theor & Pract., 29, 7, pp. 132-138, (2009); Ning X., Wang Y., Tian W., Liu L., Cai W., A biomimetic covering learning method based on principle of homology continuity, ASP Transactions on Pattern Recognition and Intelligent Systems, 1, 1, pp. 9-16, (2021); Ye J., Li B.J., Liu F., Forecasting effect and applicability of weakening buffer operators on GM (1, 1), Syst. Eng-Theor & Pract., 34, 9, (2014); Shan Z.P., Ma D.S., Research and application on grey forecasting the GM (1, 1) model, J. Gansu Lianhe Univ.: Nature and Science, 24, 5, pp. 24-27, (2010); Huang P., Hao M., Du Y.H., Chen Y.H., Prediction of grain yield of Sichuan based on GM (1, 1) model, Journal of Agriculture (Victoria), 7, 10, pp. 96-100, (2017); Huang L.J., Zhao W.D., Xie G.J., Xie H., Yi Q.Z., Evaluating and optimizing city E-commerce competitiveness based on FA-CA Model: A case from 32 cities in China, Revista de la Facultad de Ingenieria, 32, pp. 298-308, (2017); Zhao S., Zhao K., Zhang P., Spatial inequality in China's housing market and the driving mechanism, Land, 10, 8, (2021)","M. Gao; College of Sports Science and Technology, Wuhan Sports University, Wuhan, 430079, China; email: gaoming418@whsu.edu.cn",null,"Hindawi Limited",{"$nulls":5},"1574017X",null,null,null,"English","Mob. Inf. Sys.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85133978960"]
["Damayanti D.D.; Novitasari N.; Setyawan E.B.; Muttaqin P.S.","Damayanti, Dida Diah (54946411500); Novitasari, Nia (57202990995); Setyawan, Erlangga Bayu (57200528421); Muttaqin, Prafajar Suksessanno (57217119054)","54946411500; 57202990995; 57200528421; 57217119054","Intelligent Warehouse Picking Improvement Model for e-Logistics Warehouse Using Single Picker Routing Problem and Wave Picking",2022.0,"International Journal on Informatics Visualization",6.0,2.0,null,418.0,426.0,8.0,1.0,"10.30630/joiv.6.2.1006","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85133678263&doi=10.30630%2fjoiv.6.2.1006&partnerID=40&md5=baa22c7af40b2f1a13739f6ade30d293","Department of Industrial Engineering, Telkom University, Bandung, 40257, Indonesia; Department of Logistics Engineering, Telkom University, Bandung, 40257, Indonesia","Damayanti D.D., Department of Industrial Engineering, Telkom University, Bandung, 40257, Indonesia; Novitasari N., Department of Logistics Engineering, Telkom University, Bandung, 40257, Indonesia; Setyawan E.B., Department of Logistics Engineering, Telkom University, Bandung, 40257, Indonesia; Muttaqin P.S., Department of Logistics Engineering, Telkom University, Bandung, 40257, Indonesia","— The development and use of technological innovations have changed people's behavior from an industrial society to an information society. It can be seen in the increase in people's consumption patterns from trading through physical stores (offline) to trading through electronic systems, often referred to as e-commerce. Logistics services are distribution actors in the downstream line which are tasked with delivering products from the fulfillment center from e-commerce to the end customer. The uncertainty of the number of requests is the biggest challenge for logistics service players. The growth of e-commerce has also led to an increase in sales volume in e-commerce which has given rise to a new generation of warehouses that are specifically tailored to the special needs of online retailers who directly serve the demands of end-customers in the business-to-consumer (B2C) segment. Traditional warehousing systems cannot handle orders with the characteristics of many transactions but smaller sizes. In addition, warehouses that handle e-commerce are also required to have a fast process in the warehouse because shipments must be made on the same day. In this study, the author aims to perform calculations to find the optimal order picking time in the warehouse, so orders in e-commerce can be processed faster by comparing the picking process time using ordinary Single Picker Routing Problem (SPRP) and combined with the concept of wave picking using Genetic Algorithm (GA). Based on a theoretical study in this paper, the combination between SPRP and wave picking can reduce 42.28% picking time. © 2022, Politeknik Negeri Padang. All rights reserved.","E-commerce; intelligent warehouse; logistic; order picking; Single Picker Routing Problem (SPRP); wave picking",{"$nulls":7},"Setyawan E. B., Novitasari N., Muttaqin P. S., Prediksi Volatilitas Harga Jual Produk Pada E-Commerce untuk Independent Stockashtic Data Menggunakan Simulasi Monte Carlo, KAIZEN Manag. Syst. Ind. Eng. J, 3, 1, (2020); Singh G., Kaur H., Singh A., Dropshipping in E-Commerce, pp. 7-14, (2018); Yu Y., Wang X., Zhong R. Y., Huang G. Q., E-commerce Logistics in Supply Chain Management: Practice Perspective, Procedia CIRP, 52, pp. 179-185, (2016); Bopage G., Nanayakkara J., Vidanagamachchi K., A strategic model to improve the last mile delivery performance in ecommerce parcel delivery, Proc. Int. Conf. Ind. Eng. Oper. Manag, 2019, pp. 2018-2019, (2019); Petersen C. G., Cao X., Aase G. R., COVID-19 Pandemic Implications for Order Picking Operations, Open J. Bus. Manag, pp. 2866-2878, (2021); Shiau J. Y., Huang J. A., Wave planning for cart picking in a randomized storage warehouse, Appl. Sci, 10, 22, pp. 1-28, (2020); Turban E., King D., Lee J. K., Liang T.-P., Turban D., Electronic Commerce: A Managerial and Social Networks Perspective, (2015); Kalakota R., Whinston A. B., Fronties of Electronic Commerce, (2009); Rizaldi A., Madany Z., Impact of E-Commerce in Industry, Int. J. Res. Appl. Technol, 1, 2, pp. 59-64, (2021); Laudon K. C., E-commerce 2017: business, technology, society, (2017); Tarn J. M., Razi M. A., Wen H. J., Perez A. A., E‐fulfillment: the strategy and operational requirements, Logist. Inf. Manag, 16, 5, pp. 350-362, (2003); Supply Chain Management Terms and Glossary, (2013); Kotler P., Keller K. L., A Framework for Marketing Management, (2016); Bowersox D., Closs D. J., Cooper M. B., Supply Chain Logistics Management, (2002); Lu C. S., Liao C. H., Yang C. C., Segmenting manufacturers’ investment incentive preferences for international logistics zones, Int. J. Oper. Prod. Manag, 28, 2, pp. 106-129, (2008); Rahman N. K. N. A., Abidin S. Z., Zandi G. R., Amin M., Hartani N. H., E-commerce logistic and supply chain management: Evidence from Indonesian perspectives, Int. J. Supply Chain Manag, 7, 6, pp. 25-32, (2018); Dilip A. M., Mohd E. G., E-Commerce and Logistics: An Exploratory Study; Kawa A., Fulfillment service in e-commerce logistics, LogForum, 13, 4, pp. 429-438, (2015); Kawa A., Fulfilment as logistics support for E-tailers: An empirical studies, Sustain, 13, 11, (2021); Dembinska I., The Impact of E-Commerce Development on the Warehouse Space Market in Poland, Econ. Cult, 13, 2, pp. 5-13, (2016); Ghezzi A., Mangiaracina R., Perego A., Shaping the E-Commerce logistics strategy: A decision framework, Int. J. Eng. Bus. Manag, 4, 1, pp. 1-13, (2012); Kembro J. H., Norrman A., Eriksson E., Adapting warehouse operations and design to omni-channel logistics: A literature review and research agenda, Int. J. Phys. Distrib. Logist. Manag, 48, 9, pp. 890-912, (2018); Richards G., Warehouse Management: A Complete Guide to Improving Efficiency and Minimizing Costs in the Modern Warehouse, (2017); Rimele A., Grangier P., Gamache M., Gendreau M., Rousseau L.-M., E-commerce warehousing: learning a storage policy, pp. 1-19, (2021); Frazelle E. H., World-Class Warehousing and Material Handling; Boysen N., de Koster R., Weidinger F., Warehousing in the e-commerce era: A survey, Eur. J. Oper. Res, 277, 2, pp. 396-411, (2019); Damayanti D. D., Setyawan E. B., Andrawina L., Santosa B., Warehouse picking model for single picker routing problem in multi dimensional warehouse layout using genetic algorithm approach to minimize delay, Adv. Intell. Syst. Comput, 700, 2018, pp. 124-134, (2018); Goeke D., Schneider M., Modeling single-picker routing problems in classical and modern warehouses, INFORMS J. Comput, 33, 2, pp. 436-451, (2021); Masae M., Glock C. H., Vichitkunakorn P., Optimal order picker routing in a conventional warehouse with two blocks and arbitrary starting and ending points of a tour, Int. J. Prod. Res, 58, 17, pp. 5337-5358, (2020); Cano J. A., Formulations for joint order picking problems in low-level picker-to-part systems, Bull. Electr. Eng. Informatics, 9, 2, pp. 834-842, (2020); Setyawan E. B., Damayanti D. D., Kamil A. A., Multi-criteria Mathematical Model for Partial Double Track Railway Scheduling in Urban Rail Network, IEEE Int. Conf. Ind. Eng. Eng. Manag, 2019, pp. 1416-1420, (2019); Popovic V., Kilibarda M., Andrejic M., Jereb B., Dragan D., A new sustainable warehouse management approach for workforce and activities scheduling, Sustain, 13, 4, pp. 1-19, (2021); Liang J., Wu Z., Zhu C., Zhang Z. H., An estimation distribution algorithm for wave-picking warehouse management, J. Intell. Manuf, 33, 4, pp. 929-942, (2022); Gademann A. J. R. M. nou., Van Den Berg J. P., Van Der Hoff H. H., An order batching algorithm for wave picking in a parallel-aisle warehouse, IIE Trans. (Institute Ind. Eng, 33, 5, pp. 385-398, (2001); Aboelfotoh A., Singh M., Suer G., Order batching optimization for warehouses with cluster-picking, Procedia Manuf, 39, 2019, pp. 1464-1473, (2019); Janssens G. K., Moons S., Ramaekers K., Caris A., Batch Order and Discrete Order Picking Integrated with Vehicle Routing Decisions, Inf. Technol. Manag. Sci, 24, pp. 60-67, (2021); Kulak O., Sahin Y., Taner M. E., Joint order batching and picker routing in single and multiple-cross-aisle warehouses using cluster-based tabu search algorithms, Flex. Serv. Manuf. J, 24, 1, pp. 52-80, (2012); Alam T., Qamar S., Dixit A., Benaida M., Genetic algorithm: Reviews, implementations and applications, Int. J. Eng. Pedagog, 10, 6, pp. 57-77, (2021); Zhang J., An Improved Genetic Algorithm for Vehicle Routing Problem, Adv. Intell. Syst. Comput, 1282, 1, pp. 163-169, (2021); Forno A. J. D., Pereira F. A., Forcellini F. A., Kipper L. M., Value stream mapping: A study about the problems and challenges found in the literature from the past 15 years about application of Lean tools, Int. J. Adv. Manuf. Technol, 72, 5–8, pp. 779-790, (2014); Sultan S., Khodabandehloo A., Improvement of Value Stream Mapping and Internal Logistics through Digitalization: A study in the context of Industry 4. 0, pp. 1-90, (2020)","D.D. Damayanti; Department of Industrial Engineering, Telkom University, Bandung, 40257, Indonesia; email: didadiah@telkomuniversity.ac.id",null,"Politeknik Negeri Padang",{"$nulls":5},2.5499904E7,null,null,null,"English","Int. J. Inform. Vis.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85133678263"]
["Tan L.; Zhang A.; Li S.; Ding M.; Liu P.","Tan, Lin (57217381377); Zhang, Ailing (57223266275); Li, Sha (57217728949); Ding, Minghua (57809736500); Liu, Pengfei (57809667300)","57217381377; 57223266275; 57217728949; 57809736500; 57809667300","Design and Simulation of Logistics Network Model Based on Particle Swarm Optimization Algorithm",2022.0,"Computational Intelligence and Neuroscience",2022.0,null,1862911.0,null,null,null,2.0,"10.1155/2022/1862911","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85134428514&doi=10.1155%2f2022%2f1862911&partnerID=40&md5=4b1f1efeea82aa0882464812573932ac","Shandong Vocational and Technical University of International Studies, Rizhao, 276800, China; Rizhao Economic and Technological Development Zone Economic Development Group Co., LTD, Rizhao, 26800, China","Tan L., Shandong Vocational and Technical University of International Studies, Rizhao, 276800, China; Zhang A., Shandong Vocational and Technical University of International Studies, Rizhao, 276800, China; Li S., Shandong Vocational and Technical University of International Studies, Rizhao, 276800, China; Ding M., Shandong Vocational and Technical University of International Studies, Rizhao, 276800, China; Liu P., Rizhao Economic and Technological Development Zone Economic Development Group Co., LTD, Rizhao, 26800, China","With the continuous development of e-commerce, logistics and express services have penetrated into every aspect of people's life. Research on the optimization of logistics network model is helpful to reduce the waste of routes, improve the utilization rate of transportation tools and hubs, and thus reduce the organizational cost of logistics. In this paper, the basic model of hub-and-spoke network (HSN) is constructed based on the principle of minimizing the connection distance and total cost between hubs. By discretizing the particles in the continuous motion space, the discrete particle swarm optimization (PSO) algorithm is designed and the Exchange () exchange function is used to improve its search strategy to update the individual optimal value and the global optimal value. Finally, the improved double-layer discrete PSO algorithm is obtained to solve the logistics network model. The results show that the optimized PSO algorithm has faster convergence speed and higher precision, and the application of the logistics network model is helpful to integrate logistics resources, reduce logistics costs, and improve logistics efficiency.  © 2022 Lin Tan et al.",null,"Algorithms; Computer Simulation; Humans; Transportation; Cost reduction; Optimal systems; Transportation routes; Continuous development; Design and simulation; Discrete particle swarm optimization algorithm; E-commerce services; Express services; Logistic network modeling; Logistics services; Model-based OPC; Optimal values; Particle swarm optimization algorithm; algorithm; computer simulation; human; traffic and transport; Particle swarm optimization (PSO)",{"$nulls":6},"Liu C., Guan M., Duan D., Spatial pattern and influencing factors of China's intercity technology transfer network, Acta Geographica Sinica, 73, 8, pp. 1462-1477, (2018); Wang X., Wang S., Construction of hub spoke logistics network in Central China: Based on the analysis of highway and railway transportation costs, Progress in Geographical Sciences, 31, 12, (2012); Tian M., Analysis and application of mathematical modeling in logistics network model, Science and Technology Information, 20, 1, pp. 32-34, (2022); Zhang X., B2C E-commerce logistics network optimization model, Journal of Global Information Management, 30, 3, (2021); Chen S., Gao Z., Application of genetic algorithm in location selection of competitive logistics distribution center, Highway Transportation Technology, 22, 8, pp. 138-141, (2005); Shan Y., Wu X., Research on logistics cost optimization of dynamic multi-path unit construction based on MPSO, Journal of Wuhan University of Technology, 39, 5, pp. 1029-1034, (2015); Yue D., Fourth Party Logistics Network Design of Industry Innovation Mode Considering Customer Behavior, (2018); Meng L., Li W., Research on group intelligence recommendation algorithm for logistics service transaction based on deep learning, Modern Computer, 27, 34, pp. 1-11, (2021); Hu W., Dong J., Hwang B.G., Ren R., Chen Z., Hybrid optimization procedures applying for two-echelon urban underground logistics network planning: A case study of Beijing, Computers & Industrial Engineering, 144, (2020); Lee J.H., Moon I., A hybrid hub-and-spoke postal logistics network with realistic restrictions: A case study of Korea Post, Expert Systems with Applications, 41, 11, pp. 5509-5519, (2014); Wang L., HSN Design Considering Logistics Service Level, (2021); Yan H., Shao X., Hai F., Ding C., Node selection of modern regional logistics network based on hub and spoke theory, Computer Integrated Manufacturing System, 18, 6, pp. 1299-1305, (2012); Ma Y., Improvement of PSO in financial risk model, Lecture Notes in Electrical Engineering, pp. 1693-1697, (2022)","L. Tan; Shandong Vocational and Technical University of International Studies, Rizhao, 276800, China; email: tanlintl@stu.ahu.edu.cn",null,"Hindawi Limited",{"$nulls":5},1.6875265E7,null,null,3.5845888E7,"English","Comput. Intell. Neurosci.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85134428514"]
["Madani B.; Ndiaye M.","Madani, Batool (57211785670); Ndiaye, Malick (7006670047)","57211785670; 7006670047","Hybrid Truck-Drone Delivery Systems: A systematic literature review",2022.0,"IEEE Access",null,null,null,1.0,1.0,0.0,12.0,"10.1109/ACCESS.2022.3202895","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137612619&doi=10.1109%2fACCESS.2022.3202895&partnerID=40&md5=591daead3bf7c96e1ad20f8ec5eaac86","Department of Industrial Engineering, American University of Sharjah, Sharjah, United Arab Emirates","Madani B., Department of Industrial Engineering, American University of Sharjah, Sharjah, United Arab Emirates; Ndiaye M., Department of Industrial Engineering, American University of Sharjah, Sharjah, United Arab Emirates","Owing to the continued development of e-commerce, logisticians now have an outstanding obligation to tackle last-mile delivery challenges. A number of logistics providers have suggested the incorporation of drones with trucks to provide a more flexible delivery system. This paper analyzes the content of 95 publications related to hybrid truck-drone delivery systems (HTDDS) in the context of last-mile delivery. First, a brief overview of the potential implementation of drone delivery systems is presented, including their integration with other vehicles. The overview aims to demonstrate the operational characteristics of such systems and their implications. Then, the surveyed literature is classified based on vehicles roles, system configuration, problem formulation, and solution methods. In relation to this research, several key findings and potential research directions are discussed. Despite the high level of interest in HTDDS research, it is still in its early phases and requires improvements in various areas. The payload capacity, speed, range, and energy consumption are all factors that must be considered in the modeling of drone characteristics. Almost all studies identify customer requests before the delivery operation begins. However, customer demands for immediate delivery present an opportunity for real-time optimization to provide solutions for e-commerce activities. Environmental issues are developing, as the last-mile delivery problem is regarded as the most polluting portion of the supply chain. Thus, more consideration should be given to the environmental impact of HTDDS. Finally, research on drone routing related to air traffic management has received relatively little attention. Author","Costs; Drones; Drones; Electronic commerce; hybrid truck-drone delivery systems; last-mile delivery; Optimization; Product delivery; routing; Routing; Transportation; Uninterruptible power systems",{"$nulls":10},"Institute of Electrical and Electronics Engineers Inc.",{"$nulls":5},2.1693536E7,null,null,null,"English","IEEE Access","Article","Article in press","All Open Access; Gold Open Access","Scopus","2-s2.0-85137612619"]
["Xiong X.; Huang R.; He C.","Xiong, Xin (58093941000); Huang, Runan (58093941100); He, Cuixian (58093828800)","58093941000; 58093941100; 58093828800","Research on intelligent path planning technology of logistics robots based on Giraph architecture",2022.0,"International Journal of Computing Science and Mathematics",16.0,3.0,null,252.0,264.0,12.0,1.0,"10.1504/IJCSM.2022.10053251","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85147549856&doi=10.1504%2fIJCSM.2022.10053251&partnerID=40&md5=46a0cd70a7a3299c99856cd711150ff4","School of Intelligent Manufacturing, Guangzhou Panyu Polytechnic, Vanke Golden Chengpin C4-801, No. 818 Dexian Road, Shawan Town, Panyu District, Guangdong Province, Guangzhou City, 511483, China; School of Intelligent Manufacturing, Guangzhou Panyu Polytechnic, Shawan Market, Panyu District, Guangdong, Guangzhou, 511483, China","Xiong X., School of Intelligent Manufacturing, Guangzhou Panyu Polytechnic, Vanke Golden Chengpin C4-801, No. 818 Dexian Road, Shawan Town, Panyu District, Guangdong Province, Guangzhou City, 511483, China; Huang R., School of Intelligent Manufacturing, Guangzhou Panyu Polytechnic, Shawan Market, Panyu District, Guangdong, Guangzhou, 511483, China; He C., School of Intelligent Manufacturing, Guangzhou Panyu Polytechnic, Shawan Market, Panyu District, Guangdong, Guangzhou, 511483, China","In the development of modern e-commerce, the logistics robot is an important part of the intelligent warehouse. Especially in large-scale warehouses, the operation efficiency of logistics robots largely depends on the processing ability of patrol efficiency. In order to solve the problems of difficult path planning and complex operation in the logistics robot operating system, based on the analysis of the traditional path algorithm, an improved logistics robot path planning algorithm based on graph architecture, CAA*path planning algorithm, is proposed and used to solve the conflict-free path planning problem of the logistics robot in the intelligent logistics warehouse. The improved CAA*path planning algorithm is compared with the traditional a*algorithm, ant colony algorithm, simulated annealing algorithm, ant colony optimisation algorithm and genetic algorithm. The simulation analysis shows that the improved CAA*path planning algorithm is more efficient in time operation. Under the same number of tasks and the same map specification, the improved CAA*path planning algorithm takes less time and runs more efficiently. Copyright © 2022 Inderscience Enterprises Ltd.","cloud computing; Giraph architecture; intelligence; logistics robot; route planning; warehouse","Ant colony optimization; Computer architecture; Efficiency; Intelligent robots; Motion planning; Robot Operating System; Robot programming; Simulated annealing; Warehouses; Cloud-computing; E- commerces; Giraph architecture; Intelligence; Intelligent path planning; Intelligent warehouse; Large-scales; Logistic robot; Path-planning algorithm; Route planning; Genetic algorithms",{"$nulls":4},"Key Project of Education and Teaching Reform of Guangzhou Panyu Polytechnic, (2017JGZ06); Key platform and scientific research project of Guangdong Provincial Department of education “research and application of key technologies of cloud brain robot system mechanism, (2018GKZDXM005)","This work is supported by Key platform and scientific research project of Guangdong Provincial Department of education “research and application of key technologies of cloud brain robot system mechanism” (No: 2018GKZDXM005); Key Project of Education and Teaching Reform of Guangzhou Panyu Polytechnic (No: 2017JGZ06).","Akr M., Hekimolu B., Deniz C., Path planning for industrial robot milling applications, Procedia Computer Science, 158, pp. 27-36, (2019); Alotaibi E.T.S., Al-Rawi H., A complete multi-robot path-planning algorithm, Autonomous Agents and Multi Agent Systems, 32, 5, pp. 1-48, (2018); Bogataj D., Battini D., Calzavara M., Persona A., The response latency in global production and logistics: a trade-off between robotization and globalization of a chain, Procedia Manufacturing, 39, pp. 1428-1437, (2019); Cai K., Wang C., Cheng J., Song S., Silva C., Meng Q.H., Mobile robot path planning in dynamic environments: a survey, Instrumentation, 6, pp. 92-102, (2019); Chen Y., Rosolia U., Ames A.D., Decentralized task and path planning for multi-robot systems, IEEE Robotics and Automation Letters, 6, 3, pp. 4337-43344, (2020); Fang W., Wang C., Zhao R., Application of simulated annealing particle swarm optimization in complex three-dimensional path planning, Journal of Physics: Conference Series 2021, 1873, 1, pp. 119-142, (2021); Hou X., Haptic teleoperation of a multirotor aerial robot using path planning with human intention estimation, Intelligent Service Robotics, 14, 11, pp. 1-14, (2020); Hu B., Xu S., Cao Z., Multi-robot path planning for each robot with several jobs in a single trip, IFAC-PapersOnLine, 53, 5, pp. 279-284, (2020); Lamini C., Benhlima S., Elbekri A., Genetic algorithm based approach for autonomous mobile robot path planning, Procedia Computer Science, 127, pp. 180-189, (2018); Lee W.J., Kwag S.I., Ko Y.D., Optimal capacity and operation design of a robot logistics system for the hotel industry, Tourism Management, 76, pp. 1039711-10397110, (2020); Leofante F., Abraham E., Niemueller T., Lakemeyer G., Tacchella A., Integrated synthesis and execution of optimal plans for multi-robot systems in logistics, Information Systems Frontiers, 21, 1, pp. 87-107, (2019); Li F., Fan X., Hou Z., A firefly algorithm with self-adaptive population size for global path planning of mobile robot, IEEE Access, 8, pp. 168951-168964, (2020); Petkovic T., Puljiz D., Markovic I., Hein B., Human intention estimation based on hidden Markov model motion validation for safe flexible robotized warehouses, Robotics and Computer-Integrated Manufacturing, 57, pp. 182-196, (2019); Roy D., Nigam S., Koster R.D., Adan I., Resing J., Robot-storage zone assignment strategies in mobile fulfillment systems, Transportation Research Part E Logistics and Transportation Review, 122, pp. 119-142, (2019); Sangiovanni B., Incremona G.P., Piastra M., Ferrara A., Self-configuring robot path planning with obstacle avoidance via deep reinforcement learning, IEEE Control Systems Letters, 5, 2, pp. 397-402, (2020); Seder M., Petrovic L., Persic J., Popovic G., Petkovic T., Selek A., Bicanic B., Cvisic I., Josic D., Markovic I., Petrovic I., Open platform based mobile robot control for automation in manufacturing logistics – sciencedirect, IFAC-PapersOnLine, 52, 22, pp. 95-100, (2019); Stefan E., Morteza L., Daniele M., Erion P., Integrating temporal reasoning and sampling-based motion planning for multi-goal problems with dynamics and time windows, IEEE Robotics and Automation Letters, 3, 4, pp. 3473-3480, (2018); Wang C., Cheng J., Chi W., Yan T., Meng Q.H., Semantic-aware informative path planning for efficient object search using mobile robot, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 51, 8, pp. 1-14, (2019); Zambom A.Z., Seguin B., Zhao F., Robot path planning in a dynamic environment with stochastic measurements, Journal of Global Optimization, 73, 2, pp. 389-410, (2019); Zhang F., Li N., Yuan R., Fu Y., Robot path planning algorithm based on reinforcement learning, Journal of Huazhong University of Science and Technology (Natural Science Edition), 46, 12, pp. 65-70, (2018); Zhang H., Wang Y., Zheng J., Yu J., Path planning of industrial robot based on improved RRT algorithm in complex environments, IEEE Access, 6, pp. 53296-53306, (2018); Zhu D., IoT and big data based cooperative logistical delivery scheduling method and cloud robot system, Future Generation Computer Systems, 86, pp. 709-715, (2018)","R. Huang; School of Intelligent Manufacturing, Guangzhou Panyu Polytechnic, Guangzhou, Shawan Market, Panyu District, Guangdong, 511483, China; email: gzpyp@gzpyp.edu.cn",null,"Inderscience Publishers",{"$nulls":5},1.7525055E7,null,null,null,"English","Int. J. Comput. Sci. Math.","Article","Final",null,"Scopus","2-s2.0-85147549856"]
["Zuhanda M.K.; Suwilo S.; Sitompul O.S.; Mardiningsih","Zuhanda, Muhammad Khahfi (57204882999); Suwilo, Saib (6504683544); Sitompul, Opim Salim (46661988300); Mardiningsih (57192100322)","57204882999; 6504683544; 46661988300; 57192100322","A COMBINATION K-MEANS CLUSTERING AND 2-OPT ALGORITHM FOR SOLVING THE TWO ECHELON E-COMMERCE LOGISTIC DISTRIBUTION",2022.0,"Logforum",18.0,2.0,null,213.0,225.0,12.0,4.0,"10.17270/J.LOG.2022.734","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85138287885&doi=10.17270%2fJ.LOG.2022.734&partnerID=40&md5=fbd5b76220db1a1cfc9dbc2f8aa73b60","Graduate School of Mathematics, Universitas Sumatera Utara, Medan, Indonesia; Department of Mathematics, Universitas Sumatera Utara, Medan, Indonesia; Department of Information Technology, Universitas Sumatera Utara, Medan, Indonesia","Zuhanda M.K., Graduate School of Mathematics, Universitas Sumatera Utara, Medan, Indonesia; Suwilo S., Department of Mathematics, Universitas Sumatera Utara, Medan, Indonesia; Sitompul O.S., Department of Information Technology, Universitas Sumatera Utara, Medan, Indonesia; Mardiningsih, Department of Mathematics, Universitas Sumatera Utara, Medan, Indonesia","Background: The rise of e-commerce in the community makes competition between logistics companies increasingly tight. Every e-commerce application offers the convenience and choices needed by the community. The Two-Echelon Vehicle Routing Problem (2E-VRP) model has been widely developed in recent years. 2E-VRP makes it possible for customers to combine shipments from several different stores due to satellites in their distribution stream. The aim of this paper is to optimize a two-echelon logistics distribution network for package delivery on e-commerce platforms, where vans operate in the first echelon and motorcycles operate in the second echelon. The problem is formulated as 2E-VRP, where total travel costs and fuel consumption are minimized. This optimization is based on determining the flow in each echelon and choosing the optimal routing solution for vans and motorcycles. Methods: This paper proposes a combination of the K-means Clustering Algorithm and the 2-opt Algorithm to solve the optimization problem. Many previous studies have used the K-means algorithm to help streamline the search for solutions. In the solution series, clustering is carried out between the satellite and the customer in the first echelon using the K-means algorithm. To determine the optimal k-cluster, we analyzed it using the silhouette, gap statistic, and elbow methods. Furthermore, the routing at each echelon is solved by the 2-opt heuristic method. At the end of the article, we present testing of several instances with the different number of clusters. The study results indicate an influence on the determination of the number of clusters in minimizing the objective function. Results: This paper looks at 100 customers, 10 satellites, and 1 depot. By working in two stages, the first stage is the resolution of satellite and customer problems, and the second stage is the resolution of problems between the satellite and the depots. We compare distance and cost solutions with a different number of k-clusters. From the test results, the number of k-clusters shows an effect of number and distance on the solution. Conclusions: In the 2E-VRP model, determining the location of the cluster between the satellite and the customer is very important in preparing the delivery schedule in logistics distribution within the city. The benefit is that the vehicle can divide the destination according to the location characteristics of the satellite and the customer, although setting the how many clusters do not guarantee obtaining the optimal distance. And the test results also show that the more satellites there are, the higher the shipping costs. For further research, we will try to complete the model with the metaheuristic genetic algorithm method and compare it with the 2-opt heuristic method. © 2022, Poznan School of Logistics. All rights reserved.","2-opt algorithm; e-commerce; K-means clustering; logistic distribution; two echelon vehicle routing problem",{"$nulls":7},"Arkhand M., Jannat Z., Murase K., Capacitated Vehicle Routing Problem Solving using Adaptive Sweep and Velocity Tentative PSO, International Journal of Advanced Computer Science and Applications, 8, 12, pp. 288-295, (2017); Agardi A., Kovacs L., Banyai T., An Attraction Map Framework of a Complex Multi-Echelon Vehicle Routing Problem with Random Walk Analysis, Applied Sciences, 11, 5, pp. 1-23, (2021); Barma P.S., Dutta J., Mukherjee A., A 2-opt guided discrete antlion optimizationalgorithm for multi-depotvehicle routing problem, Decision Making: Applications in Management and Engineering, 2, 2, (2019); Breunig U., Baldacci R., Hartl R.F., Vidal T., The electric two-echelon vehicle routing problem, Computers and Operations Research, 103, pp. 1-28, (2019); Chen C., Demir E., Huang Y., An adaptive large neighborhood search heuristic for the vehicle routing problem with time windows and delivery robots, European Journal of Operational Research, 294, 3, (2021); El-Mandouh A.M., Mahmoud H.A., Abd-Elmegid L.A., Haggag M.H., Optimized K-means clustering model based on gap statistic, International Journal of Advanced Computer Science and Applications, 10, 1, pp. 183-188, (2019); Englert M., Roglin H., Vocking B., Worst case and probabilistic analysis of the 2-opt algorithm for the TSP, Algorithmica, 68, pp. 190-264, (2014); Erniyati, Citra P., The implementation of the Kruskal algorithm for the search for the shortest path to the location of a building store in the city of Bogor, IOP Conference Series: Materials Science and Engineering, 621, 1, pp. 1-9, (2019); He Y., Wen J., Huang M., Study on emergency relief VRP based on clustering and PSO, 11th International Conference on Computational Intelligence and Security, 1, pp. 43-47, (2016); Hougardy S., Zaiser F., Zhong X., The approximation ratio of the 2-Opt Heuristic for the metric Traveling Salesman Problem, Operations Research Letters, 48, 4, pp. 401-404, (2020); Ikotun A.M., Almutari M.S., Ezugwu A.E., K-means-based nature-inspired metaheuristic algorithms for automatic data clustering problems: Recent advances and future directions, Applied Sciences (Switzerland), 11, 23, pp. 1-61, (2021); Kassem S., Korayem L., Khorshid M., Tharwat A., A hybrid bat algorithm to solve the capacitated vehicle routing problem, Novel Intelligent and Leading Emerging Sciences Conference, 1, pp. 222-225, (2019); Kovacs L., Agardi A., Banyai T., Fitness landscape analysis and edge weighting-based optimization of vehicle routing problems, Processes, 8, 11, pp. 1-22, (2020); Lee K., Chae J., Song B., Choi D., A model for sustainable courier services: Vehicle routing with exclusive lanes, Sustainability (Switzerland), 12, 3, pp. 1-19, (2020); Leon Villalba A.F., Cristina Gonzalez La Rotta E., Comparison of Dbscan and K-means clustering methods in the selection of representative clients for a vehicle routing model, Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2020 - Conference Proceedings, 1, pp. 1-6, (2020); Li H., Wang H., Chen J., Bai M., Two-echelon vehicle routing problem with time windows and mobile satellites, Transportation Research Part B: Methodological, 138, pp. 179-201, (2020); Li H., Wang H., Chen J., Bai M., Two-echelon vehicle routing problem with satellite bi-synchronization, European Journal of Operational Research, 288, 3, (2021); Liu D., Liu D., Deng Z., Mao X., Yang Y., Yang Y., Kaisar E.I., Two-Echelon Vehicle-Routing Problem: Optimization of Autonomous Delivery Vehicle-Assisted E-Grocery Distribution, IEEE Access, 8, pp. 108705-108719, (2020); McNabb M.E., Weir J.D., Hill R.R., Hall S.N., Testing local search move operators on the vehicle routing problem with split deliveries and time windows, Computers and Operations Research, 56, pp. 93-109, (2015); Rahman A., Asih H.M., Optimizing shipping routes to minimize cost using particle swarm optimization, International Journal of Industrial Optimization, 1, 1, (2020); Rana S.M.S., Hoque M.R., Kabir M.H., Evaluation of Security Threat of ZigBee Protocol to Enhance the Security of ZigBee based IoT Platform, Journal of Applied Science and Technology, 11, pp. 37-45, (2019); Redi A.A.N.P., Jewpanya P., Kurniawan A.C., Persada S.F., Nadlifatin R., Dewi O.A.C., A simulated annealing algorithm for solving two-echelon vehicle routing problem with locker facilities, Algorithms, 13, 9, pp. 1-14, (2020); Sabo C., Pop P.C., Horvat-Marc A., On the selective vehicle routing problem, Mathematics, 8, 5, pp. 1-11, (2020); Saputra D.M., Saputra D., Oswari L.D., Effect of Distance Metrics in Determining K-Value in K-means Clustering Using Elbow and Silhouette Method, Advances in Intelligent Systems Research, 172, pp. 341-346, (2020); Shi C., Wei B., Wei S., Wang W., Liu H., Liu J., A quantitative discriminant method of elbow point for the optimal number of clusters in clustering algorithm, Eurasip Journal on Wireless Communications and Networking, 1, pp. 1-15, (2021); Rizkallah W., Ahmed M., Darwish M., A clustering algorithm for solving the vehicle routing assignment problem in polynomial time, International Journal of Engineering & Technology, 9, 1, pp. 1-13, (2020); Xia X., Liao W., Zhang Y., Peng X., A discrete spider monkey optimization for the vehicle routing problem with stochastic demands, Applied Soft Computing, 111, pp. 1-13, (2021); Yan X., Huang H., Hao Z., Wang J., A Graph-Based Fuzzy Evolutionary Algorithm for Solving Two-Echelon Vehicle Routing Problems, IEEE Transactions on Evolutionary Computation, 24, 1, pp. 129-141, (2020); Zhang Y., Zhou S., Ji X., Chen B., Liu H., Xiao Y., Chang W., The Mathematical Model and an Genetic Algorithm for the Two-Echelon Electric Vehicle Routing Problem, Journal of Physics: Conference Series, 1813, pp. 1-7, (2021)",null,null,"Poznan School of Logistics",{"$nulls":5},1.8952038E7,null,null,null,"English","Logforum","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85138287885"]
["Hu H.; Zhang Y.; Wei J.; Zhan Y.; Zhang X.; Huang S.; Ma G.; Deng Y.; Jiang S.","Hu, Haoyuan (57212514272); Zhang, Ying (58747489600); Wei, Jiangwen (57212508109); Zhan, Yang (55872524000); Zhang, Xinhui (57810854400); Huang, Shaojian (57811702300); Ma, Guangrui (57210846322); Deng, Yuming (57188765558); Jiang, Siwei (57810646000)","57212514272; 58747489600; 57212508109; 55872524000; 57810854400; 57811702300; 57210846322; 57188765558; 57810646000","Alibaba Vehicle Routing Algorithms Enable Rapid Pick and Delivery",2022.0,"Interfaces",52.0,1.0,null,27.0,41.0,14.0,5.0,"10.1287/inte.2021.1108","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85134502388&doi=10.1287%2finte.2021.1108&partnerID=40&md5=bd18be86e8cac05486db4c0d56ed48f1","Cainiao Network, Zhejiang, Hangzhou, 311100, China; Alibaba Group, Zhejiang, Hangzhou, 310052, China; Lazada Group, Singapore, 068811, Singapore","Hu H., Cainiao Network, Zhejiang, Hangzhou, 311100, China; Zhang Y., Cainiao Network, Zhejiang, Hangzhou, 311100, China; Wei J., Cainiao Network, Zhejiang, Hangzhou, 311100, China; Zhan Y., Cainiao Network, Zhejiang, Hangzhou, 311100, China; Zhang X., Alibaba Group, Zhejiang, Hangzhou, 310052, China; Huang S., Alibaba Group, Zhejiang, Hangzhou, 310052, China; Ma G., Alibaba Group, Zhejiang, Hangzhou, 310052, China; Deng Y., Alibaba Group, Zhejiang, Hangzhou, 310052, China; Jiang S., Lazada Group, Singapore, 068811, Singapore","Alibaba Group pioneered integrated online and offline retail models to allow customers to place online orders of e-commerce and grocery products at its participating stores or restaurants for rapid delivery—in some cases, in as little as 30 minutes after an order has been placed. To meet these service commitments, quick online routing decisions must be made to optimize order picking routes at warehouses and delivery routes for drivers. The solutions to these routing problems are complicated by stringent service commitments, uncertainties, and complex operations in warehouses with limited space. Alibaba has developed a set of algorithms for vehicle routing problems (VRPs), which include an open-architecture adaptive large neighborhood search to support the solution of variants of routing problems and a deep learning-based approach that trains neural network models offline to generate almost instantaneous solutions online. These algorithms have been implemented to solve VRPs in several Alibaba subsidiaries, have generated more than $50 million in annual financial savings, and are applicable to the broader logistics industry. The success of these algorithms has fermented an inner-source community of operations researchers within Alibaba, boosted the confidence of the company’s executives in operations research, and made operations research one of the core competencies of Alibaba Group. © 2022 INFORMS","adaptive large neighborhood search; deep reinforcement learning; Edelman Award; inner source; last-mile delivery; vehicle routing problems",{"$nulls":7},"Alibaba group anounces September quarter 2020 results, (2020); Bello I, Pham H, Le QV, Norouzi M, Bengio S, Neural combinatorial optimization with reinforcement learning, (2016); Bertsimas D, Jaillet P, Sebastien M, Online vehicle routing: The edge of optimization in large-scale applications, Oper. Res, 67, 1, pp. 143-162, (2019); Bertsimas D, Delarue A, Eger W, Hanlon J, Martin S, Bus routing optimization helps Boston public schools design better policies, INFORMS J. Appl. Anal, 50, 1, pp. 37-49, (2020); Duan L, Zhan Y, Hu H, Gong Y, Wei J, Zhang X, Xu Y, Efficiently solving the practical vehicle routing problem: A novel joint learning approach, Proc. 26th ACM SIGKDD Internat. Conf. Knowledge Discovery Data Mining, pp. 3054-3063, (2020); Francois V, Arda Y, Crama Y, Adaptive large neighborhood search for multi-trip vehicle routing with time windows, Transportation Sci, 53, 6, pp. 1706-1720, (2019); Holland C, Levis J, Nuggehalli R, Santilli B, Winters J, UPS optimizes delivery routes, Interfaces, 47, 1, pp. 8-23, (2017); Hollis BL, Green PJ, Real-life vehicle routing with time windows for visual attractiveness and operational robustness, Asia-Pacific J. Oper. Res, 29, 4, (2012); James JQ, Yu W, Gu J, Online vehicle routing with neural combinatorial optimization and deep reinforcement learning, IEEE Trans. Intelligent Transportation Systems, 20, 10, pp. 3806-3817, (2019); Kant G, Jacks M, Aantjes C, Coca-Cola enterprises optimizes vehicle routes for efficient product delivery, Interfaces, 38, 1, pp. 40-50, (2008); Kool W, Van Hoof H, Welling M, Attention, learn to solve routing problems! Preprint, (2018); Laporte G, Musmanno R, Vocaturo F, An adaptive large neighborhood search heuristic for the capacitated vehicle arc-routing problem with stochastic demands, Transportation Sci, 44, 1, pp. 125-135, (2010); Nazari M, Oroojlooy A, Takac M, Snyder L, Reinforcement learning for solving the vehicle routing problem, Proc. 32nd Conf. Neural Inform. Processing Systems, pp. 9861-9871, (2018); Capacitated VRP instances, (2013); Pisinger D, Ropke S, A general heuristic for vehicle routing problems, Comput. Oper. Res, 34, 8, pp. 2403-2435, (2007); Pisinger D, Ropke S, Large neighborhood search, Handbook of Metaheuristics, International Series in Operations Research and Management Science, 146, pp. 399-419, (2010); Ropke S, Pisinger D, An adaptive large neighborhood search heuristic for the pickup and delivery problem with time windows, Transportation Sci, 40, 4, pp. 455-472, (2006); Rossit DG, Vigo D, Tohme F, Frutos M, Visual attractiveness in routing problems: A review, Comput. Oper. Res, 103, March, pp. 13-34, (2019); Sahoo S, Kim S, Kim BI, Kraas B, Popov A, Routing optimization for waste management, Interfaces, 35, 1, pp. 24-36, (2005); Stol KJ, Fitzgerald B, Inner source—Adopting open source development practices in organizations: A tutorial, IEEE Software, 32, 4, pp. 60-67, (2015); Ulmer MW, Thomas BW, Campbell AM, Woyak N, The restaurant meal delivery problem: Dynamic pickup and delivery with deadlines and random ready time, Transportation Sci, 55, 1, pp. 75-100, (2021); Zhang D, 2021 Edelman finalist: Alibaba, INFORMS, 39, (2021); Zhang Y, Zhang D, Wang L, He Z, Hu H, Balancing exploration and exploitation in the memetic algorithm via a switching mechanism for the large-scale VRPTW, Database Systems for Advanced Applications, Lecture Notes in Computer Science, 12112, pp. 324-331, (2020)","X. Zhang; Alibaba Group, Hangzhou, Zhejiang, 310052, China; email: maisui.zxh@alibaba-inc.com",null,"INFORMS Inst.for Operations Res.and the Management Sciences",{"$nulls":5},922102.0,null,null,null,"English","Interfaces","Article","Final",null,"Scopus","2-s2.0-85134502388"]
["Shaik S.; Kuruppuarachchi L.N.; Franchetti M.J.","Shaik, Salma (57441412100); Kuruppuarachchi, Lakshika Nishadhi (57212144519); Franchetti, Matthew John (6507291860)","57441412100; 57212144519; 6507291860","CARBON FOOTPRINT IMPACT OF HOLIDAY e-COMMERCE: A CASE STUDY OF SAO PAULO, BRAZIL",2022.0,"Environmental Engineering and Management Journal",21.0,4.0,null,687.0,698.0,11.0,1.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85132751647&partnerID=40&md5=482cd40e1975fd23e95de0d2b94b59c3","The University of Toledo, 2801 W. Bancroft St, Toledo, 43606, OH, United States","Shaik S., The University of Toledo, 2801 W. Bancroft St, Toledo, 43606, OH, United States; Kuruppuarachchi L.N., The University of Toledo, 2801 W. Bancroft St, Toledo, 43606, OH, United States; Franchetti M.J., The University of Toledo, 2801 W. Bancroft St, Toledo, 43606, OH, United States","The current study investigates the environmental impacts of e-commerce during holiday season by calculating the carbon emissions of the package delivery trucks. Two years of e-commerce data for Sao Paulo city from 2016 to 2018 were statistically analyzed and carbon emissions were calculated using the US EPA CO2 emissions standard for road trucks. After thorough data cleaning and data exploration, February and September months were considered for regular e-commerce while November, December were accounted for holiday e-commerce. One sided z-test at a significance level of 0.05 was performed to statistically compare the CO2 emissions of regular and holiday e-commerce. Results show that holiday e-commerce contributed to around 32% of the total orders in 2017 and the CO2 emissions were significantly higher at around 2 times more than those of regular e-commerce. The top 2 product categories that contributed to the CO2 emissions (grams) for regular e-commerce were health and beauty (313.31g) and home (246.32g) respectively whereas for holiday e-commerce, furniture (746.73g) and home (349.45g) were top product categories. Learning from our study, we believe that this research contributes to and paves way for further research and future development in the understanding of environmental impacts of increased online shopping trends which leads to a rise in fuel consumption and emissions by the package delivery trucks. © 2022 Gheorghe Asachi Technical University of Iasi, Romania. All rights reserved.","carbon footprint; e-commerce; holiday shopping; python; statistical analysis",{"$nulls":7},"2020 Holiday Shopping Trends, (2021); ASOS Greenhouse Gas Report - 2016/17, (2017); Bryant R.L., Peering into the Abyss: Environment, Research, and Absurdity in the ‘Age of id’, The International Handbook of Environmental Sociology, (2010); Carbon Footprint Factsheet, (2020); Collaco F.M., Simoes S.G., Dias L.P., Duic N., Seixas J., Bermann C., The dawn of urban energy planning - Synergies between energy and urban planning for Sao Paulo (Brazil) megacity, Journal of Cleaner Production, 215, pp. 458-479, (2019); Conzachi K., Rethink Black Friday and Cyber Monday, (2020); Cloudpay, (2020); Delfmann W., Albers S., Gehring M., The impact of electronic commerce on logistics service providers, International Journal of Physical Distribution & Logistics Management, 32, pp. 203-222, (2002); Dost F., Maier E., E-Commerce effects on energy consumption: a multi-year ecosystem-level assessment, Journal of Industrial Ecology, 22, pp. 799-812, (2017); Edwards J.B., McKinnon A.C., Cullinane S.L., Carbon auditing the ‘last mile’: modelling the environmental impacts of conventional and online nonfood shopping, (2009); Overview of Greenhouse Gases, Greenhouse Gas Emissions, (2020); Feichtinger S., Gronalt M., The environmental impact of transport activities for online and in-store shopping: A systematic literature review to identify relevant factors for quantitative assessments, Sustainability, 13, (2021); Fessenden M., What was the first thing sold on the Internet?, Smithsonian Magazine, (2015); Foster L., Black Friday: Brands opt out for environment reasons, (2019); Franchetti M.J., Apul D., Carbon Footprint Analysis: Concepts, Methods, Implementation, and Case Studies, (2012); Calculating Distance, (2018); Gonzalez P.J.C., Nguyen V.T., Araki M., Shiga S., The role of powertrain electrification in achieving deep decarbonization in road freight transport, Energies, 13, (2020); Greening P., Piecyk M., Palmer A., Dadhich P., (2019); Guimaraes C.A., IBGE estimates Brazilian population at 211.8 million inhabitants, (2020); Hooper A., Murray D., E-Commerce Impacts on the Trucking Industry, (2019); Hurst L., Is Black Friday bad for the environment? 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Franchetti; The University of Toledo, Toledo, 2801 W. Bancroft St, 43606, United States; email: matthew.franchetti@utoledo.edu",null,"Gheorghe Asachi Technical University of Iasi, Romania",{"$nulls":5},1.5829596E7,null,null,null,"English","Environ. Eng. Manage. J.","Article","Final",null,"Scopus","2-s2.0-85132751647"]
["Vongurai R.","Vongurai, Rawin (55445562200)",5.54455622E10,"Key Drivers of Operational Performance of E-commerce Distribution Service Providers in Thailand",2022.0,"Journal of Distribution Science",20.0,12.0,null,89.0,98.0,9.0,0.0,"10.15722/jds.20.12.202212.89","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85144922585&doi=10.15722%2fjds.20.12.202212.89&partnerID=40&md5=8614548d4875d3795bdfa074260f3c36","School of Business and Advanced Technology Management, Assumption University, Thailand","Vongurai R., School of Business and Advanced Technology Management, Assumption University, Thailand","Purpose: Due to the rapid growth of e-commerce in Thailand, the operational excellence of distribution service providers has been elevated. Thus, this research investigated the key drivers of operational performance of e-commerce distributors in Thailand. The research contains key variables: the analytics capabilities of an organization, supply chain disruption orientation, innovation capability, and operational performance. Research design, data, and methodology: An online survey is administered to top managers and key personnel (N=425) employed for at least one year in Thailand's top five e-commerce distributors. The sampling methods were conducted using purposive sampling, quota sampling, and convenience sampling. Confirmatory Factor Analysis and Structural Equation Model were applied to analyze and confirm the model's goodness-of-fit and hypothesis testing. Results: The findings reveal that an organization’s analytics capabilities significantly affect supply chain disruption orientation and supply chain resilience. Furthermore, operational performance is affected by supply chain disruption, supplier quality management, and innovation capability. Nevertheless, supply chain resilience and digital supply chain have no significant effect on operational performance. Conclusions: The results imply that supply chain digitalization could drive higher operational performance. Distribution businesses are encountering transformation and disruption, which should address the high level of a digital supply chain, innovation, and quality management to maximize their profit margin and delivery service quality. © The Author(s) This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://Creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original work is properly cited.","Digital supply chain; Distribution; Innovation capability; Operational performance; Quality management",{"$nulls":7},"Agarwal R., Dhar V., Big data,data science,and analytics: The opportunity and challenge for IS research, Information Systems Research, 25, 3, pp. 443-448, (2014); Ambulkar S., Blackhurst J., Grawe S., Firm’s resilience to supply chain disruptions: Scale development and empirical examination, Journal of Operations Management, 33, 1, (2015); Arbuckle J. 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Distribution Science","Article","Final",null,"Scopus","2-s2.0-85144922585"]
["Chen X.; Chen R.; Yang C.","Chen, Xiaozhong (57226820298); Chen, Rongli (57226816972); Yang, Cairu (57226815884)","57226820298; 57226816972; 57226815884","Research to key success factors of intelligent logistics based on IoT technology",2022.0,"Journal of Supercomputing",78.0,3.0,null,3905.0,3939.0,34.0,6.0,"10.1007/s11227-021-04009-7","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85112738695&doi=10.1007%2fs11227-021-04009-7&partnerID=40&md5=ac633017988bbe8f17816b5efadf4a38","Department of Logistics Engineering, Dongguan Polytechnic, Dongguan, 523808, China; Department of Computer Engineering, Dongguan Polytechnic, Dongguan, 523808, China; Department of Physical Eduction, Dongguan Polytechnic, Dongguan, 523808, China","Chen X., Department of Logistics Engineering, Dongguan Polytechnic, Dongguan, 523808, China; Chen R., Department of Computer Engineering, Dongguan Polytechnic, Dongguan, 523808, China; Yang C., Department of Physical Eduction, Dongguan Polytechnic, Dongguan, 523808, China","Technologies such as intelligent collection, transmission and processing of the IoT have rapidly improved logistics efficiency and significantly reduced costs, and they will eventually realize intelligent logistics management with tactics. This paper described the use of the analytic hierarchy process (AHP) method to construct key success factors for application of IoT technology in intelligent logistics. This entailed document collation, expert interviews and collation of secondary data relating to the IoT industry and intelligent logistics. The evaluation factors that determine key success factors comprise five major factors and 21 evaluations. The findings of this paper will provide a reference basis for companies seeking to develop intelligent logistics. The results show that the most important aspect of application of IoT technology to intelligent logistics is technical services. The important critical indicators are as follows: information collection capabilities; wireless communication capabilities; lower operating costs; effective market information facilitating development of more products; ensuring the integrity of data and ensuring confidentiality of information; tracking systems for cargo status; provision of e-commerce logistics services; and the determination of high-level corporate executives to promote collection of huge amounts of useful data through IoT technology. This involves big data analysis, through which effective information is generated in order to develop more products or services, and to improve business performance. © 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.","Analytic Hierarchy Process (AHP); Intelligent Logistics; Internet of Things (IoT); Key Success Factors (KSF)","Analytic hierarchy process; Costs; Operating costs; Security of data; Analytic hierarchy process (ahp); Business performance; Corporate executives; Information collections; Logistics efficiency; Logistics management; Lower operating costs; Wireless communication capabilities; Internet of things",{"$nulls":4},"Horizontal Project of Dongguan Polytechnic, (2017H02, JGZD202040)","This work is supported by Dongguan Polytechnic \"Logistics Management Research and Service Innovation team\" (No. CXTD201803), “Excellent textbooks of Production and operations practice” (Grant No. GC21020404020), “Horizontal Project of Dongguan Polytechnic\" (Grant No. 2017H02), “Key projects of teaching reform of Dongguan Polytechnic, China (Grant No. JGZD202040)” ","Swamy S., Kota S., An empirical study on system level aspects of internet of things (IoT), IEEE Access, 8, pp. 188082-188134, (2020); Pribyl O., Pribyl P., Lom M., Svitek M., Modeling of smart cities based on ITS architecture, IEEE Intell Transp Syst Magazine, 11, 4, pp. 28-36, (2019); Lin C., Lin M., Application of big data in a multicategory product-service system for global logistics support, IEEE Eng Manage Rev, 47, 4, pp. 108-118, (2019); De Vass T., Shee H., Miah S., The effect of ‘Internet of Things’ on supply chain integration and performance: an organisational capability perspective, Australas J Inf Syst, 22, pp. 1-29, (2018); Chen X., Li M., Zhong H., Ma Y., Hsu C., DNNOff: offloading DNN-based Intelligent IoT applications in mobile edge computing, IEEE Trans Ind Inform, Publish Online, (2021); Humayun M., Jhanjhi N., Hamid B., Ahmed G., Emerging intelligent logistics and transportation using IoT and blockchain, IEEE Internet Things Mag, 3, 2, pp. 58-62, (2020); El-Hadidy M., Yasser Y., Realistic Chipless RFID Tag Modeling, Mathematical Framework and 3D EM Simulation, 2019 IEEE International Conference on Rfid Technology and Applications (RFID-TA), pp. 201-206, (2019); Zhu F., Lv Y., Chen Y., Wang X., Xiong G., Wang F., Parallel transportation systems: toward IoT-enabled smart urban traffic control and management, IEEE Trans Intell Transp Syst, 21, 10, pp. 4063-4071, (2020); Zhang Y., Guo Z., Lv J., Liu Y., A framework for smart production-logistics systems based on CPS and industrial IoT, IEEE Trans Ind Inf, 14, 9, pp. 4019-4032, (2018); Guo Z., Zhang Y., Zhao X., Song X., CPS-based self-adaptive collaborative control for smart production-logistics systems, IEEE Trans Cybern, 51, 1, pp. 188-198, (2021); Meneghello F., Calore M., Zucchetto D., Polese M., Zanella A., IoT: Internet of Threats? 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Commun Workshop Conf (CCWC), pp. 0852-0858, (2019); Chen S., Wang C., Ou S., The Key Success Factors of Developing Intelligent Logistics Within Pharmaceutical Industry in Fujian Free Trade Area, 2017 International Conference on Green Informatics (ICGI), pp. 149-154, (2017); Li M., Zhu Y., Zhang J., Identification of key success factors in intelligent manufacturing enterprises, I: 2019 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), pp. 1436-1439, (2019); Masamha T., Mnkandla E., Jaison A., Logistic regression analysis of information communication technology projects' critical success factor, A Focus Comput Netwo Proj IEEE AFRICON, (2017); Istiqomah D., Windarni V., Comparative analysis of the implementation of the AHP and AHP-PROMETHEE for the selection of training participants, 2019 4Th International Conference on Information Technology, Information Systems and Electrical Engineering (ICITISEE), pp. 67-72, (2019); Gusti S., Analisa dan Penerapan Metode AHP dan Promethee untuk Menentukan Guru Berprestasi, J Ilm Rekayasa dan Manaj Sist Inf, 4, 1, pp. 48-55, (2018); Salehi K., An integrated approach of fuzzy AHP and fuzzy VIKOR for personnel selection problem, Global J Manage Stud Res, 3, 3, pp. 89-95, (2016); Chen X., Chen S., Ma Y., Liu B., Zhang Y., Huang G., An adaptive offloading framework for android applications in mobile edge computing, Sci China Inf Sci, 62, 8, (2019); Chunan A., Feidong F., A supplement to saaty's consistency theory of judgment matrix in the analytic hierarchy process, 2017 3Rd IEEE International Conference on Control Science and Systems Engineering (ICCSSE), pp. 603-607, (2017); Zhang Y., Huang G., Liu X., Zhang W., Mei H., Yang S., Refactoring android Java code for on-demand computation offloading, ACM SIGPLAN Conference on Object-Oriented Programming, (2012); Lin B., Huang Y., Zhang J., Hu J., Chen X., LI J., Cost-driven offloading for DNN-based applications over cloud, edge and end devices, IEEE Trans Industr Inf, 16, 8, pp. 5456-5466, (2020); Chen X., Zhu C.Z., Min G., Zheng X., Rong C., Resource allocation for cloud-based software services using prediction-enabled feedback control with reinforcement learning, IEEE Trans Cloud Comput, Publish Online, (2021); Chen X., Lin J., Ma Y., Lin B., Wang H., Huang G., Self-adaptive resource allocation for cloud-based software services based on progressive QoS prediction model, Sci China Inform Sci, 62, 11, (2019); Chen X., Wang H., Ma Y., Zheng X., Guo L., Self-adaptive resource allocation for cloud-based software service based on iterative QoS prediction model, Futur Gener Comput Syst, 105, pp. 287-296, (2020)","R. Chen; Department of Computer Engineering, Dongguan Polytechnic, Dongguan, 523808, China; email: 23458920@qq.com",null,"Springer",{"$nulls":5},9208542.0,null,"JOSUE",null,"English","J Supercomput","Article","Final",null,"Scopus","2-s2.0-85112738695"]
["Bui V.D.; Nguyen H.P.; Mai Nguyen T.T.","Bui, Viet Duc (57222549399); Nguyen, Hoang Phuong (57220130198); Mai Nguyen, Thi Tuyet (58113698400)","57222549399; 57220130198; 58113698400","Recent applications for improving the last-mile delivery in urbanism logistics",2022.0,"International Journal of Knowledge-Based Development",12.0,"2024-04-03",null,328.0,346.0,18.0,1.0,"10.1504/IJKBD.2022.128901","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85148674085&doi=10.1504%2fIJKBD.2022.128901&partnerID=40&md5=3f6896f2c9cc663f1edc6647bd383292","Faculty of Business Administration, HUTECH University, Ho Chi Minh, 008428, Viet Nam; Academy of Political Regional II, Ho Chi Minh City, Ho Chi Minh, 008428, Viet Nam","Bui V.D., Faculty of Business Administration, HUTECH University, Ho Chi Minh, 008428, Viet Nam; Nguyen H.P., Academy of Political Regional II, Ho Chi Minh City, Ho Chi Minh, 008428, Viet Nam; Mai Nguyen T.T., Academy of Political Regional II, Ho Chi Minh City, Ho Chi Minh, 008428, Viet Nam","Along with the increase in population, the increase in demand for freight in e-commerce has complicated the transportation of goods with increasing transportation costs. The demand for e-commerce has also increased rapidly, especially during the current outbreak of the COVID-19 epidemic. Along with this need, the paper presents the current situation of freight transportation in the last mile of the e-commerce industry and new trends to improve the conditions in the last-mile delivery. Through published studies, several applications in last-mile delivery have also been identified for comparison with other costing methods. Studies also show that the application of new technologies in last-mile delivery can optimise costs, the environment, as well as delivery policies for companies. The paper also points out that the difficulty in applying and managing new technologies is very complicated and requires policies from managers. This can also be considered a new research direction that contributes to promoting new technologies in last-mile delivery to reduce time and costs for delivery companies as well as customer costs for last-mile delivery. Copyright © 2022 Inderscience Enterprises Ltd.","e-commerce; environment; last-mile delivery; logistics; optimisation; supply chain; sustainability; urbanism","Costs; Electronic commerce; Freight transportation; Regional planning; Sustainable development; 'current; Current situation; E- commerces; Environment; Last mile; Last-mile delivery; Optimisations; Transportation cost; Transportation of goods; Urbanism; Supply chains",{"$nulls":6},"Arnold F., Cardenas I., Sorensen K., Dewulf W., Simulation of B2C E-commerce distribution in antwerp using cargo bikes and delivery points, European Transport Research Review, 10, 1, (2018); Awwad M., Shekhar A., Sundaranarayanan Iyer A., Sustainable last-mile logistics operation in the era of E-commerce, Proceedings of the International Conference on Industrial Engineering and Operations Management, pp. 584-591, (2018); Balestra L., Schjolberg I., Modelling and simulation of a zero-emission hybrid power plant for a domestic ferry, International Journal of Hydrogen Energy, 46, 18, pp. 10924-10938, (2021); Berdichevskiy A., Gan C.W., Full speed ahead: supercharging electric mobility in southeast Asia, Deloitte, pp. 16-16, (2021); Bertram R.F., Chi T., A study of companies' Business responses to fashion e-commerce's environmental impact, International Journal of Fashion Design, Technology and Education, 11, 2, pp. 254-264, (2018); Bilik J., Parcel machines-green solution for green cities, Presentation at 1st International Conference, Green Logistics for Greener Cities, pp. 142-153, (2014); Bjorgen A., Bjerkan K.Y., Hjelkrem O.A., E-groceries: sustainable last mile distribution in city planning, Research in Transportation Economics, 87, (2021); Bjorgen A., Fossheim K., Macharis C., Criteria for successful stakeholder participation in collaborative urban mobility planning, VREF Conference on Urban Freight, pp. 17-19, (2018); Bjorgen A., Seter H., Kristensen T., Pitera K., The potential for coordinated logistics planning at the local level: a norwegian in-depth study of public and private stakeholders, Journal of Transport Geography, 76, pp. 34-41, (2019); Boffey D., World's first electrified road for charging vehicles opens in Sweden, The Guardian, (2018); Boyer K., Boyer K.K., Frohlich M.T., Tomas G., Hult M., Extending the Supply Chain: How Cutting-Edge Companies Bridge the Critical Last Mile Into Customers' Homes, (2005); Boysen N., Fedtke S., Schwerdfeger S., Last-mile delivery concepts: a survey from an operational research perspective, OR Spectrum, 43, 1, pp. 1-58, (2021); Browne M., Brettmo A., Lindholm M., Stakeholder engagement and partnerships for improved urban logistics, Urban Logistics. 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Nguyen; Academy of Political Regional II, Ho Chi Minh City, Ho Chi Minh, 008428, Viet Nam; email: nghoangphuong11@gmail.com",null,"Inderscience Publishers",{"$nulls":5},2.0404468E7,null,null,null,"English","Int. J. Knowl. Based Dev.","Article","Final",null,"Scopus","2-s2.0-85148674085"]
["An H.S.; Park A.; Song J.M.; Chung C.","An, Hyun Sang (57224681884); Park, Arim (57221977145); Song, Ju Myung (57200392488); Chung, Christina (16308829800)","57224681884; 57221977145; 57200392488; 16308829800","Consumers’ adoption of parcel locker service: protection and technology perspectives",2022.0,"Cogent Business and Management",9.0,1.0,2144096.0,null,null,null,4.0,"10.1080/23311975.2022.2144096","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85142809791&doi=10.1080%2f23311975.2022.2144096&partnerID=40&md5=0b93c8d1cd523c9a3a007db0928efc0f","Paseka School of Business, Minnesota State University Moorhead, Moorhead, MN, United States; Department of Marketing and Supply Chain Management, North Carolina Agricultural and Technical State University, Greensboro, NC, United States; Department of Operations and Information Systems, Manning School of Business, University of Massachusetts Lowell, Lowell, MA, United States; Anisfield School of Business, Ramapo College of New Jersey, Mahwah, NJ, United States","An H.S., Paseka School of Business, Minnesota State University Moorhead, Moorhead, MN, United States; Park A., Department of Marketing and Supply Chain Management, North Carolina Agricultural and Technical State University, Greensboro, NC, United States; Song J.M., Department of Operations and Information Systems, Manning School of Business, University of Massachusetts Lowell, Lowell, MA, United States; Chung C., Anisfield School of Business, Ramapo College of New Jersey, Mahwah, NJ, United States","This study examines consumers’ decision to select parcel locker service with regard to privacy concerns and perceptions toward technology based on protection motivation theory and the technology acceptance model. A total of 310 consumers using online shopping and delivery services in the 10 most populated metropolitan areas in the United States were recruited. The responses in the final sample were analyzed by using Structural Equation Modeling (SEM). The findings of this study show that consumers’ perceived trust in technology-based service (rather than privacy concerns) more strongly evoke parcel locker service adoption intention in consumers’ sequential decision-making process, which encompasses threat/coping appraisal, protection motivation, perceived innovativeness from a new service, service trust, perceived usefulness, perceived ease of use, and attitude toward the new service—outdoor parcel locker service. This study provides managerial implications for retailers who need to deliver packages to consumers. This study attempts to understand consumers’ decision-making process toward adopting parcel locker service by considering two approaches: technology assessment and privacy protection. © 2022 The Author(s). 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Won D., Chiu W., Byun H., Factors influencing consumer use of a sport-branded app: The technology acceptance model integrating app quality and perceived enjoyment, Asia Pacific Journal of Marketing and Logistics, (2022); Yan J., Kim Y., Heo J., Using a technology acceptance model to empirically examine Chinese consumers’ intention to use intelligent express lockers, Korean Society of Supply Chain Management, 19, 2, pp. 107-114, (2019); Yuen K.F., Wang X., Ma F., Wong Y.D., The determinants of customers’ intention to use smart lockers for last-mile deliveries, Journal of Retailing and Consumer Services, 49, pp. 316-326, (2019)","A. Park; Department of Marketing and Supply Chain Management, North Carolina Agricultural and Technical State University, Greensboro, 27411, United States; email: apark@ncat.edu",null,"Cogent OA",{"$nulls":5},2.3311975E7,null,null,null,"English","Cogent Bus. Manag.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85142809791"]
["Hu J.; Xu L.","Hu, Jinjuan (57890373000); Xu, Ling (57750239200)","57890373000; 57750239200","Cross-Border E-Commerce Business Model Based on Big Data and Blockchain",2022.0,"Mobile Information Systems",2022.0,null,9986371.0,null,null,null,2.0,"10.1155/2022/9986371","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85138113335&doi=10.1155%2f2022%2f9986371&partnerID=40&md5=39b38aac3ca247d1627b5243fc300720","Business School, Xinyang Vocational and Technical College, Henan, Xinyang, 464000, China; School of Electronics and Information, Nanchang Institute of Technology, Jiangxi, Nanchang, 330044, China","Hu J., Business School, Xinyang Vocational and Technical College, Henan, Xinyang, 464000, China; Xu L., School of Electronics and Information, Nanchang Institute of Technology, Jiangxi, Nanchang, 330044, China","In the context of the rapid development of Internet technology, the integration of the world economy has been strengthened. The continuous innovation of technology and foreign trade business forms has promoted the rapid development of cross-border e-commerce (CBE). Based on the research on the development status of CBE, this paper analyzes the reasons for the above problems in the development of CBE and discusses the innovation of CBE business models based on blockchain. Its purpose is to study the CBE business model based on big data and blockchain. This paper proposes to build a CBE framework system based on blockchain. It also uses blockchain technology (BT) to provide solutions to the problems of trust, customs supervision, cross-border payment, cross-border logistics, and cross-border data flow encountered in CBE. According to experimental statistics, China's CBE exports were 7.29 trillion yuan, an increase of 40.1%, and imports were 3.76 trillion yuan, an increase of 16.5%.  © 2022 Jinjuan Hu and Ling Xu.",null,"Big data; Electronic commerce; International trade; Block-chain; Business models; Continuous innovation; Cross-border; Development status; E- commerces; E-commerce business; Internet technology; Model-based OPC; World economy; Blockchain",{"$nulls":6},"Ballestar M.T., Grau-Carles P., Sainz J., Customer segmentation in e-commerce: A, Journal of Business Research, 88, pp. 407-414, (2018); Tyagi M., New e-commerce policy to shake online retail business in India, International Dyer, 203, 6, pp. 13-14, (2018); Hu L., E-Commerce trade consumption payment security and privacy based on improved B2C model, International Journal on Network Security, 21, 4, pp. 545-550, (2019); Kwak J., Zhang Y., Yu J., Legitimacy building and e-commerce platform development in China: The experience of Alibaba, Technological Forecasting and Social Change, 139, pp. 115-124, (2019); Monroe R.W., Barrett P.T., The evolving B2B E-commerce and supply chain management: A chronological mémoire, Journal of Business Management, 25, 1, pp. 49-67, (2019); Wu P.-J., Lin K.-C., Unstructured big data analytics for retrieving e-commerce logistics knowledge, Telematics and Informatics, 35, 1, pp. 237-244, (2018); Sun M., Zhang J., Research on the application of block chain big data platform in the construction of new smart city for low carbon emission and green environment, Computer Communications, 149, pp. 332-342, (2020); Yang J., Wen J., Jiang B., Wang H., Blockchain-based sharing and tamper-proof framework of big data networking, IEEE Network, 34, 4, pp. 62-67, (2020); Xu C., Wang K., Li P., Guo S., Luo J., Ye B., Guo M., Making big data open in edges: A resource-efficient blockchain-based approach, IEEE Transactions on Parallel and Distributed Systems, 30, 4, pp. 870-882, (2019); Kaplan A.M., Michael H., Digital transformation and disruption: On big data, blockchain, artificial intelligence, and other things, Business Horizons, 62, 6, pp. 679-681, (2019); Chen J., Lv Z., Song H., Design of personnel big data management system based on blockchain, Future Generation Computer Systems, 101, pp. 1122-1129, (2019); Reyna A., Martin C., Chen J., Soler E., Diaz M., On blockchain and its integration with IoT. Challenges and opportunities, Future Generation Computer Systems, 88, pp. 173-190, (2018); Bera B., Das A.K., Sutrala A.K., Private blockchain-based access control mechanism for unauthorized UAV detection and mitigation in Internet of Drones environment, Computer Communications, 166, 3, pp. 91-109, (2021); Liu K., Qiu X., Chen W., Chen X., Zheng Z., Optimal pricing mechanism for data market in blockchain-enhanced Internet of things, IEEE Internet of Things Journal, 6, 6, pp. 9748-9761, (2019); Chen R.Y., A traceability chain algorithm for artificial neural networks using T-S fuzzy cognitive maps in blockchain, Future Generation Computer Systems, 80, pp. 198-210, (2018); Rathore S., Park J.H., A blockchain-based deep learning approach for cyber security in next generation industrial cyber-physical systems, IEEE Transactions on Industrial Informatics, 17, 8, pp. 5522-5532, (2021); Li H., Zhang C., Mahmoud M., Lu R., Guest editorial introduction to the special section on blockchains in emerging vehicular social networks, IEEE Transactions on Vehicular Technology, 69, 6, pp. 5732-5735, (2020); Shrikanth G., TODAY, companies expect niche skills and proficiency in digital technologies from students, Dataquest, 36, 6, pp. 66-68, (2018); Turner A., Irwin A.S.M., Bitcoin transactions: A digital discovery of illicit activity on the blockchain, Journal of Financial Crime, 25, 1, pp. 109-130, (2018); Wang H., Li Y., Zhao X., Yang F., An algorithm based on Markov chain to improve edge cache hit ratio for blockchain-enabled IoT, China Communications, 17, 9, pp. 66-76, (2020)","L. Xu; School of Electronics and Information, Nanchang Institute of Technology, Nanchang, Jiangxi, 330044, China; email: dr.lingxu@nut.edu.cn",null,"Hindawi Limited",{"$nulls":5},"1574017X",null,null,null,"English","Mob. Inf. Sys.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85138113335"]
["Mishra K.N.; Mishra V.P.; Saket S.; Mishra S.P.","Mishra, Kamta Nath (57192188286); Mishra, Ved Prakash (57195472330); Saket, Shashwat (57565796700); Mishra, Shivam Prakash (57565796800)","57192188286; 57195472330; 57565796700; 57565796800","Hybrid approach for deception tracing in smart cities using LR and n-fold intelligent machine learning techniques",2022.0,"International Journal of Management Practice",15.0,4.0,null,460.0,487.0,27.0,0.0,"10.1504/IJMP.2022.10048751","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135413131&doi=10.1504%2fIJMP.2022.10048751&partnerID=40&md5=ad7438d79d48bd40e1a49819726d64d2","Department of Computer Science and Engineering, Birla Institute of Technology, Jharkhand, India; Department of Computer Science and Engineering, Amity University, Dubai, United Arab Emirates","Mishra K.N., Department of Computer Science and Engineering, Birla Institute of Technology, Jharkhand, India; Mishra V.P., Department of Computer Science and Engineering, Amity University, Dubai, United Arab Emirates; Saket S., Department of Computer Science and Engineering, Birla Institute of Technology, Jharkhand, India; Mishra S.P., Department of Computer Science and Engineering, Birla Institute of Technology, Jharkhand, India","One of the fiendishly difficult tasks to perform in this computational era is deceit detection in credit and debit cards. In the current online and digital era recognising authentic identities is important for e-commerce websites so that genuine and fraudulent people could be segregated efficiently. In this paper, logistic regression (LR) and n-fold intelligent machine learning (IML) techniques are used for preventing and detecting the fraud in cloud and IoT connected surroundings. During experimental analysis, authors observed that the methodology proposed in this paper is reliable, accurate, and efficient for identifying the fraud in cloud and IoT-based surroundings of smart city societies. © 2022 Inderscience Enterprises Ltd.","cloud-IoT-based distributed surroundings; confusion matrix; deception detection; fraudulent; logistic regression; machine learning; mean-recall-score; ROC curve",{"$nulls":7},"Aleskerov E., Freisleben B., Rao B., CARDWATCH: a neural network-based database mining system for credit card fraud detection, Proc. of the IEEE/IAFE on Comp. Intel. for Fin. 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Conf. on Info Technology New Generations, pp. 122-126, (2015); Chen, Rong-Chang, Et al., Detecting credit card fraud by using questionnaire-responded transaction model based on support vector machines, Intelligent Data Engg. & Automated Learning - IDEAL, 3177, pp. 800-806, (2004); Chen R., Chiu M., Huang Y., Chen L., Detecting credit card fraud by using questionnaire responded transaction model based on SVMs, Proc. of IDEAL2004, pp. 800-806, (2004); De Zoort F.T., Harrison P.D., Understanding auditors' sense of responsibility for detecting fraud within organizations, J. of Business Ethics, 149, 4, pp. 857-874, (2018); Dheepa V., Dhanapal R., Behavior based credit card fraud detection using support vectors machines, ICTACT J. of Soft Comp, 2, 4, pp. 391-397, (2012); Fiore U., De Santis A., Perla F., Zanetti P., Palmieri F., Using generative adversarial networks for improving classification effectiveness in credit card fraud detection, Information Science, 479, pp. 448-455, (2019); Gaikwad J.R., Deshmane A.B., Somavanshi H.V., Patil S.V., Badgujar R.A.J.I.J.o.I.T., Engineering E., Credit card fraud detection using decision tree induction algorithm, 4, 6, pp. 66-69, (2014); Garner D., Gen algo for credit card fraud detection, IEEE Trans, 2, 6, pp. 292-294, (2011); Huber W., Forensic auditing, fraud theory and the end of the fraud triangle, J. of Theo. 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Business and Mgmnt, 14, 3, pp. 19-26, (2017); Lu Q., Ju C., Research on credit card fraud detection model based on class weighted support vector machine, J. of Convergence Info Tech, l, 6, pp. 62-68, (2011); Maaten L.J.P., Hinton G.E., Visualizing high-dimensional data using t-SNE, J. of Machine Learn Research, 9, 11, pp. 3221-3245, (2014); Maes S., Karl T., Bram V., Manderick B., Credit card fraud detection using Bayesian and neural network, Interactive Image-Guided Neurosurgery, pp. 261-270, (1993); Manuaba I.B.K., Sutedja I., Bahana R., The evaluation of supervised classifier models to develop a machine learning API for predicting cardiovascular disease risk, ICIC Express Lett, 14, 3, pp. 219-226, (2020); Masoumeh Z., Seeja K.R., Alam M.A., Analysis of credit card fraud detection techniques: based on certain design criteria, Int. J. of Comp. Apps, 52, 3, pp. 35-42, (2012); Mishra V.P., Shukla B., Process mining in intrusion detection-the need of current digital world, International Conference on Advanced Informatics for Computing Research, pp. 238-246, (2017); Mishra V.P., Shukla B., Bansal A., Analysis of alarms to prevent the organizations network in real-time using process mining approach, Cluster Computing, 22, 3, pp. 7023-7030, (2019); Murli D., Jami S., Jog D., Nath S., Management J.I.J.o.S.R.i.T., Credit card fraud detection using neural networks, International Journal of Students Research in Technology & Management, 2, 2, pp. 84-88, (2015); Nathalie J., Learning from Imbalanced Data Sets: A Comparison of Various Strategies, (2002); Nian K., Zhang H., Tayal A., Coleman T., Li Y., Auto insurance fraud detection using unsupervised spectral ranking for anomaly, J. of Finance and Data Sc, 2, 1, pp. 58-75, (2016); Patel R.D., Singh D.K., Engineering J.I.J.o.S.C., Credit card fraud detection & prevention of fraud using genetic algorithm, 2, 6, pp. 292-294, (2013); Phua C., Lee V., Smith K., Gayler R., A comprehensive survey of data mining-based fraud detection research, Computing Research Repository, pp. 1-14, (2010); Sahin Y., Duman E., Detecting credit card fraud by ANN and logistic regression, International Symposium on Innovations in Intelligent Systems and Applications, pp. 315-319, (2011); Samaneh S., Zahra Z., Reza E.A., Amir H.M., A Survey of Credit Card Fraud Detection Techniques: Data and Technique Oriented Perspective, pp. 1-10, (2016); Sanjay K.S., Danti A., Online fake review identification based on decision rules, IJATCSE, 8, 2, pp. 140-143, (2019); Seyedeh N.F., Ravinesh D., Mohd S., Mauro C., Shahaboddin S., Computational intelligence approaches for energy load forecasting in smart energy management grids: state of the art, future challenges, and research directions, Energies, 11, 3, pp. 1-31, (2018); Singh D., Ruhl R., Samuel H., Attack tree for modelling unauthorized EMV card transactions at POS terminals, ICISSP, pp. 494-502, (2018); Suman, Mitail B., Survey paper on credit card fraud detection, Int. J. of Advanced Research in Comp. Engg. & Tech, 3, 3, pp. 827-832, (2014); Syeda M., Yan Q.Z., Yi P., Parallel granular neural networks for fast credit card fraud detection, Proc. of the IEEE Int. Conf, pp. 572-577, (2002); Vardhani P.R., Priyadarshini Y.I., Narasimhulu Y., CNN data mining algorithm for detecting credit card fraud, Book - Soft Computing and Medical Bioinformatics, pp. 85-93, (2019); Wang S., Liu G., Li Z., Xuan S., Yan C., Jiang C., Credit card fraud detection using capsule network, IEEE Int. Conf. Syst. Man, Cybern, pp. 3679-3684, (2018); Xie X., Et al., Generative adversarial network-based credit card fraud detection, Commun. Signal Process. Syst, pp. 1007-1014, (2020); Zareapoor M., Shamsolmoali P.J.P.c.s., Application of credit card fraud detection: based on bagging ensemble classifier, International Conference on Computer, Communication and Convergence (ICCC 2015), Journal - Procedia Computer Science, 48, pp. 679-685, (2015)","V.P. Mishra; Department of Computer Science and Engineering, Amity University, Dubai, United Arab Emirates; email: mishra.ved@gmail.com",null,"Inderscience Publishers",{"$nulls":5},1.4779064E7,null,null,null,"English","Int. J. Manage. Pract.","Article","Final",null,"Scopus","2-s2.0-85135413131"]
["Ma M.","Ma, Meng (57861665000)",5.7861665E10,"Construction and Realization Path Analysis of Cross-Border E-Commerce Logistics Collaboration Model",2022.0,"Advances in Multimedia",2022.0,null,7758785.0,null,null,null,0.0,"10.1155/2022/7758785","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85136685336&doi=10.1155%2f2022%2f7758785&partnerID=40&md5=15b4cc2959f57c03480c2bc43f6bbae4","College of Finance and Economics, Xinxiang Vocational and Technical College, Henan, Xinxiang, 453000, China","Ma M., College of Finance and Economics, Xinxiang Vocational and Technical College, Henan, Xinxiang, 453000, China","In order to improve the synergy effect of cross-border e-commerce slogistics, this paper combines intelligent logistics communication technology to construct a cross-border e-commerce collaborative logistics model. Moreover, this paper proposes a parallel energy-efficient routing algorithm based on 3D cell space to improve the system operation effect. In addition, this paper deeply analyzes the data fusion function performed by MA when accessing nodes and proposes a data fusion criterion to judge the necessity of data fusion on nodes. Finally, this paper balances the energy consumption of e-commerce logistics data fusion and data transmission so that the sum of the two is minimized. The data simulation analysis shows that the cross-border e-commerce logistics collaboration model proposed in this paper has certain effects, and it can be applied to the actual operation of cross-border e-commerce.  © 2022 Meng Ma.",null,"Electronic commerce; Energy efficiency; Energy utilization; Regression analysis; Cell spaces; Collaboration models; Collaborative logistics; Communicationtechnology; Cross-border; E- commerces; Energy efficient routing; Logistics model; Path analysis; Synergy effect; Data fusion",{"$nulls":6},"Tran-Dang H., Krommenacker N., Charpentier P., Kim D.S., Toward the internet of things for physical internet: Perspectives and challenges, IEEE Internet of Things Journal, 7, 6, pp. 4711-4736, (2020); Pal A., Kant K., Using blockchain for provenance and traceability in internet of things-integrated food logistics, Computer, 52, 12, pp. 94-98, (2019); Qu T., Thurer M., Wang J., Wang Z., Fu H., Li C., Huang G.Q., System dynamics analysis for an Internet-of-Things-enabled production logistics system, International Journal of Production Research, 55, 9, pp. 2622-2649, (2017); Ding Y., Jin M., Li S., Feng D., Smart logistics based on the internet of things technology: An overview, International Journal of Logistics Research and Applications, 24, 4, pp. 323-345, (2021); Gu Y., Liu Q., Research on the application of the internet of things in reverse logistics information management, Journal of Industrial Engineering and Management, 6, 4, pp. 963-973, (2013); Chen J., Zhao W., Logistics automation management based on the Internet of things, Cluster Computing, 22, 6, pp. 13627-13634, (2019); Huang S., Guo Y., Zha S., Wang Y., An internet-of-things-based production logistics optimisation method for discrete manufacturing, International Journal of Computer Integrated Manufacturing, 32, 1, pp. 13-26, (2019); Yadav S., Garg D., Luthra S., Selection of third-party logistics services for internet of things-based agriculture supply chain management, International Journal of Logistics Systems and Management, 35, 2, pp. 204-230, (2020); Tsang Y.P., Wu C.H., Lam H.Y., Choy K.L., Ho G.T., Integrating Internet of Things and multi-temperature delivery planning for perishable food E-commerce logistics: A model and application, International Journal of Production Research, 59, 5, pp. 1534-1556, (2021); Cho S., Kim J., Smart logistics model on internet of things environment, Advanced Science Letters, 23, 3, pp. 1599-1602, (2017); Kupriyanovsky V., Alenkov V., Stepanenko A., Pokusaev O., Katzin D., Akimov A., Vlasova I., On development of transport and logistics industries in the European Union: Open BIM, Internet of Things and cyber-physical systems, International Journal of Open Information Technologies, 6, 2, pp. 54-100, (2018); Hawkins M., Cyber-Physical production networks, internet of things-enabled sustainability, and smart factory performance in industry 4.0-based manufacturing systems, Economics, Management, and Financial Markets, 16, 2, pp. 73-83, (2021); Kalaivani C., Indhumathi G., Application of internet of things (iot) in logistics industry, IJRAR-International Journal of Research and Analytical Reviews (IJRAR), 5, 3, pp. 114-118, (2018); Alsayaydeh J.A.J., Stratified model of the internet of things infrastructure∗ jamil abedalrahim jamil alsayaydeh,\" vadym shkarupylo,\" mohd saad bin Hamid,\"Stepan skrupsky and\" andrii oliinyk\" fakulti teknologi Kejuruteraan,\"Center for advanced computing technology, universiti teknikal Malaysia melaka, Journal of Engineering and Applied Sciences, 13, 20, pp. 8634-8638, (2018); Yang H., Kumara S., Bukkapatnam S.T., Tsung F., The internet of things for smart manufacturing: A review, IISE Transactions, 51, 11, pp. 1190-1216, (2019); Suma V., Towards sustainable industrialization using big data and internet of things, Journal of ISMAC, 1, 1, pp. 24-38, (2019); Knieps G., Internet of Things, future networks, and the economics of virtual networks, Competition and Regulation in Network Industries, 18, 3-4, pp. 240-255, (2017)","M. Ma; College of Finance and Economics, Xinxiang Vocational and Technical College, Xinxiang, Henan, 453000, China; email: mm0688@126.com",null,"Hindawi Limited",{"$nulls":5},1.687568E7,null,null,null,"English","Adv. Multimedia","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85136685336"]
["Alsibaei M.; Haridy S.; Badar M.A.","Alsibaei, Mohammad (57211787866); Haridy, Salah (36173648800); Badar, M. Affan (55665319200)","57211787866; 36173648800; 55665319200","Same day delivery in B2C e-commerce systems in the UAE context",2022.0,"International Journal of Advanced Operations Management",14.0,4.0,null,333.0,365.0,32.0,0.0,"10.1504/IJAOM.2022.10052791","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85147749012&doi=10.1504%2fIJAOM.2022.10052791&partnerID=40&md5=05138fa730828e8dd53aefb119bb2786","Department of Industrial Engineering and Engineering Management, University of Sharjah, Sharjah, United Arab Emirates; Benha Faculty of Engineering, Benha University, Benha, Egypt; Applied Engineering and Technology Management Department, Indiana State University, Terre Haute, 47809, IN, United States","Alsibaei M., Department of Industrial Engineering and Engineering Management, University of Sharjah, Sharjah, United Arab Emirates; Haridy S., Department of Industrial Engineering and Engineering Management, University of Sharjah, Sharjah, United Arab Emirates, Benha Faculty of Engineering, Benha University, Benha, Egypt; Badar M.A., Applied Engineering and Technology Management Department, Indiana State University, Terre Haute, 47809, IN, United States","This work aimed to investigate the effect of various factors on cost, customer satisfaction and cycle time with respect to same day delivery (SDD). Using survey and Pareto chart, four factors were identified as the most important: logistics resources ownership, operations management, IT infrastructure, and facility location. Analysis of variance (ANOVA) revealed that all the four factors were significant for cost. For customer satisfaction and cycle time, all factors except logistics resources ownership were found to be significant. Correlation between cost, customer satisfaction and cycle time was studied and regression models were developed. A multi-objective optimisation model was used to find the best levels of the significant factors to optimise SDD. Analytic hierarchy process (AHP) was used to determine the relative weights for the cost, customer satisfaction and cycle time. The findings would help e-retailers in decision-making. Since the survey was conducted in UAE, the result would be limited to UAE. Copyright © 2022 Inderscience Enterprises Ltd.","e-commerce; logistics management; multi-criteria decision making; multi-objective optimisation; same day delivery; SDD; supply chain management; UAE; United Arab Emirates",{"$nulls":7},"Al-Odeh M., Smallwood J., Badar M.A., A framework for implementing sustainable supply chain management, International Journal of Advanced Operations Management, 13, 3, pp. 212-233, (2021); Alsibaei M., Haridy S., Badar M.A., Factors affecting same day delivery in the UAE, 2019 8th International Conference on Modeling Simulation and Applied Optimization (ICMSAO), (2019); Alsibaei M.W., Same Day Delivery in B2C E-Commerce Systems in the Context of the UAE, (2019); Anastasiou S., Critical human resources management functions for efficient logistics and supply chain management, 2nd International Conference on Supply Chains, (2012); Arnold F., Cardenas I., Sorensen K., Dewulf W., Simulation of B2C e-commerce distribution in Antwerp using cargo bikes and delivery points, European Transport Research Review, 10, 2, (2018); Azi N., Gendreau M., Potvin J., A dynamic vehicle routing problem with multiple delivery routes, Annals of Operations Research, 199, 1, pp. 103-112, (2012); Bader B.H., Badar M.A., A study on production breaks in gynecological examination table cover paper rolls processed on a Schultz Rewinder, Engineering Science and Technology, An International Journal, 20, 1, pp. 364-371, (2017); Baruch Y., Holtom B., Survey response rate levels and trends in organizational research, Human Relations, 61, 8, pp. 1139-1160, (2008); Bent R., Van Hentenryck P., Scenario-based planning for partially dynamic vehicle routing with stochastic customers, Operations Research, 52, 6, pp. 977-987, (2004); Bhayana N., Gandhi K., Jain A., Darbari J., Jha P.C., An integrated grey-based multi-criteria optimisation approach for sustainable supplier selection and procurement-distribution planning, International Journal of Advanced Operations Management, 13, 1, pp. 39-91, (2021); Boysen N., de Koster R., Weidinger F., Warehousing in the e-commerce era: a survey, European Journal of Operational Research, 277, 2, pp. 396-411, (2019); Carr R., Retailers Seek New Distribution Channels for Same-Day Deliveries, National Real Estate Investor, (2014); Chaurasia B., Study of Select Issues in Lean Manufacturing, (2018); Chen C., A fuzzy approach to select the location of the distribution center, Fuzzy Sets and Systems, 118, 1, pp. 65-73, (2001); Cleophas C., Ehmke J., When are deliveries profitable?, Business & Information Systems Engineering, 6, 3, pp. 153-163, (2014); Croxton K.L., The order fulfillment process, The International Journal of Logistics Management, 14, 1, pp. 19-32, (2003); Services for Business, (2021); Dweiri F., Kumar S., Khan S.A., Jain V., Designing an integrated AHP based decision support system for supplier selection in automotive industry, Expert Systems with Applications, 62, pp. 273-283, (2016); Galankashi M., Helmi S., Hashemzahi P., Supplier selection in automobile industry: a mixed balanced scorecard-fuzzy AHP approach, Alexandria Engineering Journal, 55, 1, pp. 93-100, (2016); Ghezzi A., Mangiaracina R., Perego A., Shaping the e-commerce logistics strategy: a decision framework, International Journal of Engineering Business Management, 4, (2012); Gleissner H., Femerling J.C., IT in Logistics. Logistics, pp. 189-223, (2013); Goyal S., Sergi B., Esposito M., Literature review of emerging trends and future directions of e-commerce in global business landscape, World Review of Entrepreneurship, Management and Sust. Development, 14, 1, pp. 312-332, (2017); Gu J., Goetschalckx M., McGinnis L., Research on warehouse design and performance evaluation: a comprehensive review, European Journal of Operational Research, 203, 3, pp. 539-549, (2010); Hamdan S., Cheaitou A., Supplier selection and order allocation with green criteria: an MCDM and multi-objective optimization approach, Computers & Operations Research, 81, pp. 282-304, (2017); Hisrich R., Ramadani V., E-commerce challenges and entrepreneurial manager, Effective Entrepreneurial Management, pp. 159-178, (2017); Ishii H., Lee Y.L., Yeh K.Y., Fuzzy facility location problem with preference of candidate sites, Fuzzy Sets and Systems, 158, 1, pp. 1922-1930, (2007); Joshi R., Banwet D., Shankar R., A Delphi-AHP-TOPSIS based benchmarking framework for performance improvement of a cold chain, Expert Systems with Applications, 38, 8, pp. 10170-10182, (2011); Kao D., Decou J., A strategy‐based model for e‐commerce planning, Industrial Management & Data Systems, 103, 4, pp. 238-252, (2003); Kawa A., Fulfillment service in e-commerce logistics, LogForum, 13, 4, pp. 429-438, (2017); Kembro J.H., Norrman A., Eriksson E., Adapting warehouse operations and design to omni-channel logistics, International Journal of Physical Distribution & Logistics Management, 48, 9, pp. 890-912, (2018); Kim T., Lee H., Delivery management system using the clustering based multiple ant colony algorithm: Korean home appliance delivery, International Journal of Industrial Engineering: Theory, Applications and Practice, 21, 2, pp. 53-65, (2014); Klapp M., Erera A., Toriello A., The Dynamic Dispatch Waves Problem for Same-Day Delivery, (2017); Lau H., Jiang Z., Ip W., Wang D., A credibility-based fuzzy location model with Hurwicz criteria for the design of distribution systems in B2C e-commerce, Computers & Industrial Engineering, 59, 4, pp. 873-886, (2010); Lee A., Kang H., Chang C., Fuzzy multiple goal programming applied to TFT-LCD supplier selection by downstream manufacturers, Expert Systems with Applications, 36, 3, pp. 6318-6325, (2009); Li Z., Wong W., Kwong C., An integrated model of material supplier selection and order allocation using fuzzy extended AHP and multiobjective programming, Mathematical Problems in Engineering, 2013, pp. 1-14, (2013); Mafakheri F., Breton M., Ghoniem A., Supplier selection-order allocation: a two-stage multiple criteria dynamic programming approach, International Journal of Production Economics, 132, 1, pp. 52-57, (2011); Montgomery D.C., Runger G.C., Applied Statistics and Probability for Engineers, (2014); Ngai E., Chau D., Chan T., Information technology, operational, and management competencies for supply chain agility: findings from case studies, The Journal of Strategic Information Systems, 20, 3, pp. 232-249, (2011); Nusair K., Hua N., Comparative assessment of structural equation modeling and multiple regression research methodologies: e-commerce context, Tourism Management, 31, 3, pp. 314-324, (2008); Onal S., Zhang J., Das S., Product flows and decision models in internet fulfillment warehouses, Production Planning & Control, 29, 10, pp. 791-801, (2018); Perez J.M., Vega J.M., Verdegay J.L., Fuzzy location problems on networks, Fuzzy Sets and Systems, 142, 1, pp. 393-405, (2004); Rao J., Saraswati K., Facility location problem on network under multiple criteria fuzzy set theoretic approach, International Journal of Systems Science, 19, 1, pp. 2555-2559, (1988); Saaty R., The analytic hierarchy process – what it is and how it is used, Mathematical Modelling, 9, 3–5, pp. 161-176, (1987); Samizadeh R., Aghagoli S., Vatankhah S., The effect of IT integration on improving agility, integration and performance of supply chain, International Journal of Advanced Operations Management, 11, 1, pp. 126-141, (2019); Siddayao G., Valdez S., Fernandez P., Analytic hierarchy process (AHP) in spatial modeling for floodplain risk assessment, International Journal of Machine Learning and Computing, 4, 5, pp. 450-457, (2014); Taber K., The use of Cronbach’s alpha when developing and reporting research instruments in science education, Research in Science Education, 48, 6, pp. 1273-1296, (2017); Ulmer M., Delivery deadlines in same-day delivery, Logistics Research, 10, 3, pp. 1-15, (2017); Ulmer M., Thomas B., Enough waiting for the cable guy – estimating arrival times for service vehicle routing, Transportation Science, 53, 3, pp. 897-916, (2019); Voccia S.A., Campbell A.M., Thomas B., The same-day delivery problem for online purchases, Transportation Science, 53, 1, pp. 167-184, (2017); Witkowski K., Koralewska M., Huk K., Logistics models in e-commerce, Research Papers Faculty of Materials Science and Technology Slovak University of Technology, 28, 46, pp. 90-97, (2020); Wouter V., E-commerce deliveries 2.0: towards a sustainable e-commerce, Scientific Conference on Economic and Social Development – ‘The Legal Challenges of Modern World, (2016); Yang L., Ji Y., Gao Z., Li K., Logistics distribution centers location problem and algorithm under fuzzy environment, Journal of Computational and Applied Mathematics, 208, 1, pp. 303-315, (2007)","M.A. Badar; Applied Engineering and Technology Management Department, Indiana State University, Terre Haute, 47809, United States; email: m.affan.badar@indstate.edu",null,"Inderscience Publishers",{"$nulls":5},"1758938X",null,null,null,"English","Int. J. Adv. Oper. Manag.","Article","Final","All Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85147749012"]
["Jiang Y.","Jiang, Yaping (57909669300)",5.79096693E10,"Procurement Volume Prediction of Cross-Border E-Commerce Platform Based on BP-NN",2022.0,"Wireless Communications and Mobile Computing",2022.0,null,7596819.0,null,null,null,0.0,"10.1155/2022/7596819","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85138945318&doi=10.1155%2f2022%2f7596819&partnerID=40&md5=86bfccc47e77c49a0b33b55f0735c5b2","School of Business, Shanghai Normal University Tianhua College Jiading District, Shanghai, China","Jiang Y., School of Business, Shanghai Normal University Tianhua College Jiading District, Shanghai, China","For logistics management, predictive analysis has never been more crucial than it is now, thanks to the vast number of deal data generated every second by electronic commerce. In an effort to enhance customer service and supply control, e-commerce businesses are progressively utilizing machine learning technologies to enhance projections. The back-propagation neural network (BP-NN) model is used to develop a C-A-BP forecasting model that considers commodity sales characteristics and the data series' trend. In order to predict each cluster, a C-BP-NN model is first created, adding sales information as influencing elements into the C-BP-NN model. An A-BP-NN model is used in combination with the ARIMA that is employed for the linear component. These two forecasting models are merged to provide the final results. By comparing the results of the ARIMA, BP-NN, A-BP-NN, and C-BP-NN using the information provided by Jollychic's cross-border platform, the A-C-BPNN was shown to be the best.  © 2022 Yaping Jiang.",null,"Backpropagation; Electronic commerce; Forecasting; Sales; Back-propagation neural networks; Commerce platforms; Cross-border; Customer-service; Forecasting models; Logistic management; Neural network model; Service control; Supply control; Volume predictions; Neural network models",{"$nulls":6},"Irina V., Blockchain technology in the international supply chains, Communication, 1, 1, pp. 16-25, (2020); Ellinger A., Shin H., Northington W.M., Adams F.G., Hofman D., O'Marah K., The influence of supply chain management competency on customer satisfaction and shareholder value, Supply Chain Management: An International Journal, 17, 3, pp. 249-262, (2012); Ji S., Wang X., Zhao W., Guo D., An application of a three-stage XGBoost-based model to sales forecasting of a cross-border e-commerce enterprise, Mathematical Problems in Engineering, 2019, (2019); Gilbert K., An ARIMA supply chain model, Management Science, 51, 2, pp. 305-310, (2005); Carter P.L., Carter J.R., Monczka R.M., Slaight T.H., Swan A.J., The future of purchasing and supply: a ten-year forecast 1, Journal of Supply Chain Management, 36, 1, pp. 14-26, (2000); Cai X., Qian Y., Bai Q., Liu W., Exploration on the financing risks of enterprise supply chain using back propagation neural network, Journal of Computational and Applied Mathematics, 367, (2020); Camilleri M.A., The rationale for responsible supply chain management and stakeholder engagement, Journal of Global Responsibility, 8, 1, pp. 111-126, (2017); Zhao X., A study on the applications of big data in cross-border E-commerce, pp. 280-284; Mahmoodzadeh A., Mohammadi M., M Gharrib Noori K., Khishe M., Hashim Ibrahim H., Farid Hama Ali H., Nariman Abdulhamid S., Presenting the best prediction model of water inflow into drill and blast tunnels among several machine learning techniques, Automation in Construction, 127, (2021); Mahmoodzadeh A., Mohammadi M., Hashim Ibrahim H., Nariman Abdulhamid S., Farid Hama Ali H., Mohammed Hasan A., Khishe M., Mahmud H., Machine learning forecasting models of disc cutters life of tunnel boring machine, Automation in Construction, 128, (2021); Mosavi M.R., Khishe M., The use of radial basis function networks based on leader mass gravitational search algorithm for sonar dataset classification, Journal of Electronic and Cyber Defence, 4, 2, pp. 39-52, (2020); Mosavi M.R., Kaveh M., Khishe M., Sonar data set classification using MLP NN trained by nonlinear migration rates BBO, pp. 1-5; Saffari A., Zahiri S.H., Khishe M., Mosavi S.M., Design of a fuzzy model of control parameters of chimp algorithm optimization for automatic sonar targets recognition, IJMT, 9, 1, pp. 1-44, (2020); Khishe M., Mosavi M.R., Moridi A., Chaotic fractal walk trainer for sonar data set classification using multi-layer perceptron NN and its hardware implementation, Applied Acoustics, 137, pp. 121-139, (2018); Mosavi M.R., Kaveh M., Khishe M., Aghababaie M., Design and implementation a sonar data set classifier using multi-layer perceptron NN trained by elephant herding optimization, IJMT, 5, 1, pp. 1-12, (2018); Wang Y., Yuan L.P., Khishe M., Moridi A., Mohammadzade F., Training RBF NN using sine-cosine algorithm for sonar target classification, Archives of Acoustics, 45, (2020); Kaveh M., Khishe M., Mosavi M.R., Design and implementation of a neighborhood search biogeography-based optimization trainer for classifying sonar dataset using multi-layer perceptron neural network, Analog Integrated Circuits and Signal Processing, 100, 2, pp. 405-428, (2019); Wu C., Khishe M., Mohammadi M., Karim S.H.T., Rashid T.A., Evolving deep convolutional neutral network by hybrid sine-cosine and extreme learning machine for real-time COVID19 diagnosis from X-ray images, Soft Computing, pp. 1-20, (2021); Hu T., Khishe M., Mohammadi M., Parvizi G.-R., Karim S.H.T., Rashid T.A., Real-time COVID-19 diagnosis from X-Ray images using deep CNN and extreme learning machines stabilized by chimp optimization algorithm, Biomedical Signal Processing and Control, 68, (2021); Khishe M., Mosavi M.R., Chimp optimization algorithm, Expert Systems with Applications, 149, (2020); Khishe M., Nezhadshahbodaghi M., Mosavi M.R., Martin D., A weighted chimp optimization algorithm, IEEE Access, 9, pp. 158508-158539, (2021); Kaidi W., Khishe M., Mohammadi M., Dynamic levy flight chimp optimization, Knowledge-Based Systems, 235, (2021); Khishe M., Safari A., Classification of sonar targets using an MLP NN trained by dragonfly algorithm, Wireless Personal Communications, 108, 4, pp. 2241-2260, (2019); Alon I., Qi M., Sadowski R.J., Forecasting aggregate retail sales: a comparison of artificial neural networks and traditional methods, Journal of Retailing and Consumer Services, 8, 3, pp. 147-156, (2001); Di Pillo G., Latorre V., Lucidi S., Procacci E., An application of support vector machines to sales forecasting under promotions, 4OR, 14, 3, pp. 309-325, (2016); Luo X., Sun J., Wang L., Wang W., Zhao W., Wu J., Wang J.H., Zhang Z., Short-term wind speed forecasting via stacked extreme learning machine with generalized correntropy, IEEE Trans. Ind. Informatics, 14, 11, pp. 4963-4971, (2018); Lu C.-J., Kao L.-J., A clustering-based sales forecasting scheme by using extreme learning machine and ensembling linkage methods with applications to computer server, Engineering Applications of Artificial Intelligence, 55, pp. 231-238, (2016); Dai W., Chuang Y.-Y., Lu C.-J., A clustering-based sales forecasting scheme using support vector regression for computer server, Procedia Manufacturing, 2, pp. 82-86, (2015); Chen I.-F., Lu C.-J., Sales forecasting by combining clustering and machine-learning techniques for computer retailing, Neural Computing and Applications, 28, 9, pp. 2633-2647, (2017); Freij A., Walid K., Mustafa M., Deep learning model for digital sales increasing and forecasting: towards smart E-commerce, Journal of Cybersecurity and Information Management, 8, 1, pp. 26-34, (2021); Zhang T., Ramakrishnan R., Livny M., BIRCH: a new data clustering algorithm and its applications, Data Mining and Knowledge Discovery, 1, 2, pp. 141-182, (1997)","Y. Jiang; School of Business, Shanghai Normal University Tianhua College Jiading District, Shanghai, China; email: jyp2186@sthu.edu.cn",null,"Hindawi Limited",{"$nulls":5},1.5308669E7,null,null,null,"English","Wireless Commun. Mobile Comput.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85138945318"]
["Cheng Z.","Cheng, Zhaozhao (57887079700)",5.78870797E10,"E-COMMERCE LOGISTICS TERMINAL DISTRIBUTION OPTIMISATION OF ENVIRONMENTAL PROTECTION ENTERPRISES UNDER THE BACKGROUND OF BIG DATA",2022.0,"Journal of Environmental Protection and Ecology",23.0,5.0,null,2133.0,2139.0,6.0,1.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137812057&partnerID=40&md5=0db74d10774ecf2499f4cfd65bf120c1","Jiangxi Modern Polytechnic College, Jiangxi, Nanchang, 330 095, China","Cheng Z., Jiangxi Modern Polytechnic College, Jiangxi, Nanchang, 330 095, China","In recent years, thanks to the rapid development of Internet, Internet of things and other technologies, e-commerce has risen rapidly and occupied a large number of markets. This is accompanied by changes in the way people sell and shop. Environmental protection products, as a part of them and an inevitable daily consumable, have also been favoured by people, but we should know that the shelf life of environmental protection products is limited. Therefore, it has also been limited by online sales for a long time. However, the emergence of environmental protection products has found a way out for online sales of environmental protection products. Excellence has always been our pursuit and expectation, so how to further shorten the distribution time of environmental protection product logistics has become a problem that we pay more and more attention to and think about. The emergence of big data has made a breakthrough in this idea. Therefore, based on the overview of the concept of environmental protection product logistics and terminal distribution, this paper analyses the current development status and existing problems of environmental protection product logistics terminal distribution in China. Then with the help of big data related technology, this paper puts forward some opinions and views on the optimisation of logistics terminal distribution of environmental protection products, hoping to provide some reference for the optimisation of logistics terminal distribution of environmental protection products. © 2022, Scibulcom Ltd.. All rights reserved.","big data; e-commerce; environmental protection enterprises; logistics terminal distribution","China; data set; electronic commerce; environmental management; environmental protection; Internet; optimization",{"$nulls":6},"KIM D., JACOME G., LEE S. C., Et al., Vulnerability Assessment Index at Process-level for the Identification of Adaptive Strategies in Wastewater Treatment Plants under Climate Change, Korean J Chem Eng, 34, 12, (2017); HAMZA S. M., AHSAN A., IMTEAZ M. A., Et al., GIS-based FRASTIC Model for Pollution Vulnerability Assessment of Fractured-rock Aquifer Systems, Environ Earth Sci, 76, 5, (2017); TAPIA C., ABAJO B., FELIU E., Et al., Profiling Urban Vulnerabilities to Climate Change: an Indicator-based Vulnerability Assessment for European Cities, Ecol Indic, 78, (2017); LI S., SUN Z., TAN M., Et al., Changing Patterns in Farming-pastoral Ecotones in China between 1990 and 2010, Ecol Indic, 89, (2018); VELLAITHURAI C., SRIVASTAVA A., ZONOUZ S., Et al., CPIndex: Cyber-physical Vulnerability Assessment for Power-Grid Infrastructures, IEEE T Smart Grid, 6, 2, (2015); HUSSEIN M., DIEZ ROUX A. V., MUJAHID M. S., Et al., Unequal Exposure or Unequal Vulnerability? Contributions of Neighborhood Conditions and Cardiovascular Risk Factors to Socioeconomic Inequality in Incident Cardiovascular Disease in the Multi-ethnic Study of Atherosclerosis, Am J Epidemiol, 187, 7, (2018); BRANDT L. A., BUTLER P. R., HANDLER S. D., Et al., Integrating Science and Management to Assess Forest Ecosystem Vulnerability to Climate Change, J For, 115, 3, (2017); DESMIT Z., ELHABASHY A. E., WELLS L. J., Et al., An Approach to Cyber-physical Vulnerability Assessment for Intelligent Manufacturing Systems, J Manuf Syst, 43, 2, (2017); IVAN V., VERONIKA J., MÁDL-SZŐNYI: State of the Art of Karst Vulnerability Assessment: Overview, Evaluation and Outlook, Environ Earth Sci, 76, 3, (2017); PATTERSON S. A., APOSTOLAKIS G. E., Identification of Critical Locations across Multiple Infrastructures for Terrorist Actions, Reliab Eng Syst Saf, 92, 9, (2007)","Z. Cheng; Jiangxi Modern Polytechnic College, Nanchang, Jiangxi, 330 095, China; email: 027044@jxxdxy.edu.cn",null,"Scibulcom Ltd.",{"$nulls":5},1.3115065E7,null,null,null,"English","J. Environ. Prot. Ecol.","Article","Final",null,"Scopus","2-s2.0-85137812057"]
["Chen Q.","Chen, Qiaoping (57869284000)",5.7869284E10,"Analysis and Prediction of Cross-Border e-Commerce Scale of China Based on the Machine Learning Model",2022.0,"Computational Intelligence and Neuroscience",2022.0,null,7906135.0,null,null,null,2.0,"10.1155/2022/7906135","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137106244&doi=10.1155%2f2022%2f7906135&partnerID=40&md5=d6c2b39d9204cc9afc275e19080762ea","School of Foreign Studies, Yiwu Industrial and Commercial College, Zhejiang, Yiwu, 322000, China","Chen Q., School of Foreign Studies, Yiwu Industrial and Commercial College, Zhejiang, Yiwu, 322000, China","In the context of the rapid development of Internet technology, the integration of the world economy has been strengthened, and the continuous innovation of technology and foreign trade business forms has promoted the rapid development of cross-border e-commerce. Due to the lack of relevant data on cross-border logistics empirical research, this paper conducts a prediction study on the scale of China's cross-border e-commerce market based on machine learning models and combines the relevant financial reports of listed companies to determine the proportion of performance costs to turnover. Forecast of the scale of cross-border e-commerce in China. Combined with the total economic volume, industrial structure, domestic and foreign trade, online shopping development, people's life, and express development, the index system is established, and 11 indicators are initially established with reference to the selection principle of indicators. Combined with the research object, multiple regression and gray prediction methods are established. The relevant prediction model is tested, and the established model is tested to ensure the prediction accuracy. The forecast results show that by 2027, the size of China's cross-border e-commerce market will reach 30.8133 trillion yuan.  © 2022 Qiaoping Chen.",null,"China; Commerce; Humans; Industry; Machine Learning; Technology; Electronic commerce; Forecasting; Machine learning; Continuous innovation; Cross-border; E- commerces; Empirical research; Financial reports; Internet technology; Machine learning models; On-machines; Performance costs; World economy; China; commercial phenomena; human; industry; machine learning; technology; International trade",{"$nulls":6},"Makridakis W., Forecasting freight transportation demand with the space-time multinomial pro ait model, Transportation Research Part A, 34, pp. 403-418, (1983); Terasvirta T., Van Dijk D., Medeiros M.C., Linear models, smooth transition autoregressions, and neural networks for forecasting macroeconomic time series: A re-examination, International Journal of Forecasting, 21, 4, pp. 755-774, (2005); Aburto L., Weber R., Improved supply chain management based on hybrid demand forecasts, Applied Soft Computing, 7, 1, pp. 136-144, (2007); Sheu J.B., Kundu T., Forecasting time-varying logistics distribution flows in the One Belt-One Road strategic context[J], Transportation Research Part e Logistics & Transportation Review, 117, pp. 5-22, (2017); Gomez-Herrera E., Martens B., Turlea G., The drivers and impediments for cross-border e-commerce in the EU, Information Economics and Policy, 28, 1, pp. 83-96, (2014); Asosheh A., Shahidi-Nejad H., Khodkari H., A model of a localized cross-border E-commerce, IBusiness, 4, 2, pp. 136-145, (2012); Davis D.F., Friske W., The role of public-private partnerships in facilitating cross-border logistics: A case study at the U.S./Canadian border, Journal of Business Logistics, 34, 4, pp. 347-359, (2013); Wong D.W.C., Choy K.L., Chow H.K.H., Lin C., Assessing a cross-border logistics policy using a performance measurement system framework: The case of Hong Kong and the Pearl River Delta region, International Journal of Systems Science, 45, 6, pp. 1306-1320, (2014); Ai W., Yang J., Wang L., Revelation of cross-border logistics performance for the manufacturing industry development, International Journal of Mobile Communications, 14, 6, (2016); Coase R.H., The nature of the firm, Economica, 4, 16, pp. 386-405, (1937); Erenguc S., Simpson N.C., Vakharia A.J., Integrated production/distribution planning in supply chains: An invited review, European Journal of Operational Research, 115, 2, pp. 219-236, (1999); Wang L., Yang J., Yin S., Electronic commerce international logistics performance influence factor analysis, International Journal of Mobile Communications, 13, 5, (2015); Moodley S., Steering in uncertain territory: E-Business, globalisation and the South African automotive components industry, South African Journal of Economic and Management Sciences, 5, 1, pp. 123-153, (2002); Moodley S., Morris M., Does e-commerce fulfil its promise for developing country (South African) garment export producers?, Oxford Development Studies, 32, 2, pp. 155-178, (2004); Sutanonpaiboon J., Pearson A.M., E-commerce adoption: Perceptions of managers/owners of small- and medium-sized enterprises (SMEs) in Thailand, Journal of Internet Commerce, 5, 3, pp. 53-82, (2006); Chatzoglou P., Chatzoudes D., Kipraios N., The impact of ISO 9000 certification on firms' financial performance, International Journal of Operations & Production Management, 35, 1, pp. 145-174, (2015); Nan C., Yang Y., The impact of customer experience on consumer purchase intention in cross-border E-commerce - - taking network structural embeddedness as mediator variable [J], Journal of Retailing and Consumer Services, 59, (2021)","Q. Chen; School of Foreign Studies, Yiwu Industrial and Commercial College, Yiwu, Zhejiang, 322000, China; email: chenqiaoping@ywicc.edu.cn",null,"Hindawi Limited",{"$nulls":5},1.6875265E7,null,null,3.6052048E7,"English","Comput. Intell. Neurosci.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85137106244"]
["Ting L.P.-Y.; Teng S.-Y.; Wu S.-C.; Chuang K.-T.","Ting, Lo Pang-Yun (57201747309); Teng, Shan-Yun (56438926900); Wu, Szu-Chan (57210570627); Chuang, Kun-Ta (7101644378)","57201747309; 56438926900; 57210570627; 7101644378","Interactive planning of revisiting-free itinerary for signed-for delivery",2022.0,"International Journal of Data Science and Analytics",{"$nulls":6},0.0,"10.1007/s41060-022-00333-0","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85130727067&doi=10.1007%2fs41060-022-00333-0&partnerID=40&md5=5bfcebe22c40d8fd39e7fd0c532af71b","Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan City, Taiwan","Ting L.P.-Y., Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan City, Taiwan; Teng S.-Y., Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan City, Taiwan; Wu S.-C., Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan City, Taiwan; Chuang K.-T., Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan City, Taiwan","The trend of online shopping has given rise to the growth of signed-for delivery services. Signed-for delivery is a reliable way of getting proof of delivery that ensures your parcel must be signed for upon its arrival with the recipient. However, due to the unknown of recipient occupancy, general signed-for delivery is not very effective for delivery drivers. Once the recipients are not available upon drivers’ arrival, drivers have to arrange revisiting the recipients, causing the resource waste and being overworked. In this paper, we address an important issue on the revisiting-free itinerary planning and propose a novel interactive planning system, called COKI, to interactively plan the effective delivery itineraries with a round-by-round strategy. The flow enables delivery drivers to take a shorter itinerary without revisiting any recipient. Our experimental studies on real data show that, without properly considering the issues in revisiting-free paradigm, the extension of state-of-the-art routing algorithms can only achieve sub-optimal results. Furthermore, the COKI framework can efficiently discover better revisiting-free itinerary for signed-for delivery in an interactive fashion. © 2022, The Author(s), under exclusive licence to Springer Nature Switzerland AG.","Interactive planning; Occupancy detection; Optimal delivery routing; Road network",{"$nulls":5},"Ministry of Science and Technology, Taiwan, MOST, (109-2221-E-006-187-MY3, 110-2221-E-006-001, 111AT16B)","This work was supported in part by Ministry of Science and Technology, R.O.C., under Contract 109-2221-E-006-187-MY3, 110-2221-E-006-001 and 111AT16B. ","Google or-tools; Abou-Rjeili A., Karypis G., Multilevel algorithms for partitioning power-law graphs, Proceedings of the IEEE International Parallel and Distributed Processing Symposium, (2006); Alabas-Uslu C., Dengiz B., A self-adaptive local search algorithm for the classical vehicle routing problem, Expert Syst. 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Ind. Eng., 90, pp. 390-401, (2015); Su J.-R., Improved particle swarm optimization for multi-object traveling salesman problems, : Proceedings of International Conference on Natural Computation, pp. In-pp, (2011); Sutton R.S., Barto A.G., Reinforcement Learning: An Introduction. Adaptive Computation and Machine Learning, (1998); Suykens J.A., Vandewalle J., Least squares support vector machine classifiers, Neural Process. Lett., 9, 3, pp. 293-300, (1999); Teng S.-Y., Wu S.-C., Chuang K.-T., Optimal delivery routing in road network with occupancy detection, Proceedings of International Conference on Mobile Data Management (MDM), pp. 575-580, (2019); van Hasselt H., Guez A., Silver D., Deep reinforcement learning with double q-learning, Proceedings of Of AAAI Conference on Artificial Intelligence, pp. 2094-2100, (2016); Wang C., Lin M., Zhong Y., Zhang H., Solving travelling salesman problem using multiagent simulated annealing algorithm with instance-based sampling, Int. J. Comput. Sci. Math., 6, 4, pp. 336-353, (2015); Wang C., Lin M., Zhong Y., Zhang H., Swarm simulated annealing algorithm with knowledge-based sampling for travelling salesman problem, Int. J. Intell. Syst. Technol. Appl., 15, pp. 74-94, (2016); Wei L., Zhang Z., Zhang D., Leung S.C., A simulated annealing algorithm for the capacitated vehicle routing problem with two-dimensional loading constraints, Eur. J. Oper. Res., 265, 3, pp. 843-859, (2018); Xu D., Weise T., Wu Y., Lassig J., Chiong R., An investigation of hybrid tabu search for the traveling salesman problem, Proceedings of International on Bio-Inspired Computing-Theories and Applications, pp. 523-537, (2015); Xu Z., Rodrigues B., An extension of the christofides heuristic for the generalized multiple depot multiple traveling salesmen problem, Eur. J. Oper. Res., 257, 3, pp. 735-745, (2017)","K.-T. Chuang; Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan City, Taiwan; email: ktchuang@mail.ncku.edu.tw",null,"Springer Science and Business Media Deutschland GmbH",{"$nulls":5},"2364415X",null,null,null,"English","Int. J. Data Sci. Anal.","Article","Article in press",null,"Scopus","2-s2.0-85130727067"]
["Sun J.; Luo N.","Sun, Jiahui (57783946400); Luo, Ning (57784234500)","57783946400; 57784234500","Research on Innovative Development of Crossborder e-Commerce under the Background of Wireless Communication and Internet of Things",2022.0,"Wireless Communications and Mobile Computing",2022.0,null,1803276.0,null,null,null,1.0,"10.1155/2022/1803276","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85145800842&doi=10.1155%2f2022%2f1803276&partnerID=40&md5=9c6fc65a08c1f855f1a123240213b42e","School of Business and Finance, Shanghai Normal University, Shanghai, 200234, China; Harbin Institute of Technology, Harbin, 150001, China","Sun J., School of Business and Finance, Shanghai Normal University, Shanghai, 200234, China; Luo N., Harbin Institute of Technology, Harbin, 150001, China","After the epidemic has entered the normalization stage, people's demand for online shopping and transactions has gradually increased, crossborder e-commerce has also developed more rapidly, and wireless communication and Internet of Things technologies have also been further upgraded with the update of electronic equipment. Technology has increased the smoothness of communication between overseas and domestic, and the Internet of Things has provided technical support for crossborder e-commerce trade traceability, trade security, and supply chain management. However, at present, crossborder e-commerce still has imperfect logistics systems and passive transactions, low income, etc. In order to solve the existing problems, this paper takes Shenzhen as an example, through a combination of literature analysis and practical investigation, and on the basis of analyzing the existing problems of crossborder e-commerce, an innovative scheme of crossborder e-commerce combining wireless communication and Internet of Things technology is proposed. The test results of the innovative scheme show that, compared with the unimproved scheme, this scheme greatly improves the income of e-commerce enterprises.  © 2022 Jiahui Sun and Ning Luo.",null,"Electronic commerce; Oscillators (electronic); Supply chain management; Cross-border; E- commerces; Existing problems; Internet of things technologies; Normalisation; Online shopping; Online transaction; Technical support; Wireless communications; Wireless internet; Internet of things",{"$nulls":6},"Goldman S.P., Van Herk H., Verhagen T., Weltevreden J.W., Strategic orientations and digital marketing tactics in cross-border e-commerce: Comparing developed and emerging markets, International Small Business Journal: Researching Entrepreneurship, 39, 4, pp. 350-371, (2021); Electronic Commerce F., Study data from South China University of Technology update knowledge of electronic commerce (product plus logistics bundling sale and co-delivery in cross-border E-commerce), Internet Business Newsweekly, 88, (2020); Zhu W., Yan R., Ding Z., Analysing impulse purchasing in cross-border electronic commerce, Industrial Management & Data Systems, 120, 10, pp. 1959-1974, (2020); Haoran F., Li H., Li Z., Analysis on cross-border e-commerce marketing strategy of small and micro-enterprises in China, World Scientific Research Journal, 6, 6, pp. 134-142, (2020); Zhang Q., Liu R., Research on the reform of talent cultivation mode of higher vocational cross-border electronic commerce based on modern apprenticeship, International Journal of Education and Economics, 3, (2020); Commerce F., Recent findings from Nanjing University of Aeronautics and Astronautics provides new insights into electronic commerce (entity name recognition of cross-border e-commerce commodity titles based on TWs-LSTM), Internet Business Newsweekly, 76, (2020); Qingsheng C., Research based on B2C cross-border e-commerce model, China Business Theory, 2021, 13, pp. 34-36, (2021); Commerce F., Study results from School of Management and Economics update understanding of electronic commerce (customs classification for cross-border e-commerce based on text-image adaptive convolutional neural network), Internet Weekly News, 65, (2019); Commerce F., Findings from South China University of Technology update understanding of electronic commerce (product + logistics bundling sale and co-delivery in cross-border e-commerce), Internet Weekly News, 59, (2019); He W., Xu Y., Cross-border electronic commerce development present situation and the innovation research in China, American Journal of Industrial and Business Management, 8, (2018); Yanna L., Yanfang G., The development and improvement of the online resolution mechanism for cross-border e-commerce disputes in my country, Journal of Yanshan University (Philosophy and Social Sciences Edition), 23, 1, pp. 72-79, (2022); Yan X., Education, obstetrics, science and innovation, students-oriented: An analysis of the blockchain-based training model for cross-border e-commerce talents, Foreign Economic and Trade, 12, pp. 145-148, (2021); Yinping C., Shuqing Y., Research on sustainable development strategy of Changzhou cross-border e-commerce industry, Modernization of Shopping Malls, 24, pp. 15-17, (2021); Guangqiang L., The current situation and optimization strategy of cross-border e-commerce and logistics integration, Modernization of Shopping Malls, 24, pp. 23-25, (2021); Xuejuan X., Qian G., Research on the high-quality development of Caofeidian cross-border e-commerce industry, Industrial Technology and Vocational Education, 19, 4, pp. 109-111, (2021); Aiping X., Zhi L., Exploration and practice of practical cross-border e-commerce talent training based on the integration of production and education, Journal of Hubei Radio and Television University, 41, 6, pp. 39-42, (2021); Jie G., Exploration of the optimal path for cross-border e-commerce \"government, school, business and enterprise\" collaborative education from an international perspective, Journal of Anhui Electronic Information Vocational and Technical College, 20, 6, pp. 100-103, (2021); Jieting L., Innovation in e-commerce operation management based on the rise of the Internet of Things, Information and Computer (Theory Edition), 33, 19, pp. 211-213, (2021); Kaixin M., Reflections on the development of cross-border e-commerce in my country under the background of the rise of the Internet of Things, Investment and Entrepreneurship, 31, 19, pp. 47-49, (2020); Huiling Z., Xueqing Y., Yanfeng S., Bottlenecks, models and countermeasures of the development of cross-border e-commerce logistics under the new retail perspective, China Storage and Transportation, 10, pp. 87-90, (2020); Jinling C., Yang P., The development strategy of cross-border e-commerce in Henan Province under the background of intelligence, Innovation and Technology, 19, 11, pp. 17-22, (2019); Jinhui Z., The application and research of Internet of things in cross-border e-commerce comprehensive service system, Electronic World, 18, pp. 61-62, (2019); Lingling Z., Donghua C., Research on the transformation and upgrading path and countermeasures of traditional industries based on value chain innovation - - taking Ningbo City as an example, Modern Marketing (Latest Issue), 6, pp. 98-101, (2019); Zimo S., Cross-border e-commerce development is heading for the Blue Ocean, Shenzhen Special Economic Zone News, 68, (2016); Yinyin T., Research on the Development of Cross-border E-Commerce in Shenzhen Qianhaiwan Free Trade Port Area, (2015)","J. Sun; School of Business and Finance, Shanghai Normal University, Shanghai, 200234, China; email: sunjiahui_vip@outlook.com",null,"Hindawi Limited",{"$nulls":5},1.5308669E7,null,null,null,"English","Wireless Commun. Mobile Comput.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85145800842"]
["Jing W.","Jing, Weijuan (58290563800)",5.82905638E10,"Construction of an E-Commerce System Based on 5G and Internet of Things Technology",2022.0,"International Journal of Information Systems and Supply Chain Management",15.0,2.0,{"$nulls":4},2.0,"10.4018/IJISSCM.287630","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85138447303&doi=10.4018%2fIJISSCM.287630&partnerID=40&md5=d376fdd7313d6706ef370e77c46c81de","Zhengzhou Vocational University of Information and Technology, China","Jing W., Zhengzhou Vocational University of Information and Technology, China","In order to improve the comprehensive performance of the e-commerce system, this paper combines 5G communication technology and the internet of things technology to improve the e-commerce system and conduct end-point analysis on the e-commerce client data analysis system and smart logistics system. Moreover, this paper uses 5G technology to improve machine learning algorithms to process e-commerce back-end data and improve the efficiency of e-commerce client data processing. In addition, this paper combines the internet of things to build an e-commerce smart logistics system model to improve the overall efficiency of the logistics system. Finally, this paper combines the demand analysis to construct the functional module structure of the e-commerce system and verifies the practical functions of the system through experimental research. From the experimental research results, it can be seen that the e-commerce system based on 5G communication technology and internet of things technology constructed in this paper is very reliable. © 2022 IGI Global. All rights reserved.","5G Communication; E-Commerce; Internet of Things; System Construction","5G mobile communication systems; Data handling; Efficiency; Electronic commerce; Engineering education; Learning algorithms; Machine learning; 5g communication; Communicationtechnology; Comprehensive performance; E- commerces; E-commerce systems; End-points; Experimental research; Internet of things technologies; Logistics system; System construction; Internet of things",{"$nulls":6},"Abd-Elmagid M. A., Pappas N., Dhillon H. S., On the role of age of information in the Internet of Things, IEEE Communications Magazine, 57, 12, pp. 72-77, (2019); Alalwan A. A., Rana N. P., Dwivedi Y. K., Algharabat R., Social media in marketing: A review and analysis of the existing literature, Telematics and Informatics, 34, 7, pp. 1177-1190, (2017); Batra R., Keller K. L., Integrating marketing communications: New findings, new lessons, and new ideas, Journal of Marketing, 80, 6, pp. 122-145, (2016); Cattaruzza D., Absi N., Feillet D., Gonzalez-Feliu J., Vehicle routing problems for city logistics, EURO Journal on Transportation and Logistics, 6, 1, pp. 51-79, (2017); Dobkin B. H., A rehabilitation-internet-of-things in the home to augment motor skills and exercise training, Neurorehabilitation and Neural Repair, 31, 3, pp. 217-227, (2017); Erevelles S., Fukawa N., Swayne L., Big Data consumer analytics and the transformation of marketing, Journal of Business Research, 69, 2, pp. 897-904, (2016); Feng H., Morgan N. A., Rego L. L., Marketing department power and firm performance, Journal of Marketing, 79, 5, pp. 1-20, (2015); Germann F., Ebbes P., Grewal R., The chief marketing officer matters, Journal of Marketing, 79, 3, pp. 1-22, (2015); Grabara J., Kolcun M., Kot S., The role of information systems in transport logistics, International Journal of Education and Research, 2, 2, pp. 1-8, (2014); Harmeling C. M., Moffett J. W., Arnold M. J., Carlson B. D., Toward a theory of customer engagement marketing, Journal of the Academy of Marketing Science, 45, 3, pp. 312-335, (2017); Homburg C., Jozic D., Kuehnl C., Customer experience management: Toward implementing an evolving marketing concept, Journal of the Academy of Marketing Science, 45, 3, pp. 377-401, (2017); Kannan P. K., Li H. A., Digital marketing: A framework, review and research agenda, International Journal of Research in Marketing, 34, 1, pp. 22-45, (2017); Leeflang P. S. H., Verhoef P. C., Dahlstrom P., Freundt T., Challenges and solutions for marketing in a digital era, European Management Journal, 32, 1, pp. 1-12, (2014); Martin K. D., Murphy P. E., The role of data privacy in marketing, Journal of the Academy of Marketing Science, 45, 2, pp. 135-155, (2017); Mayer M., Baeumner A. J., A megatrend challenging analytical chemistry: Biosensor and chemosensor concepts ready for the internet of things, Chemical Reviews, 119, 13, pp. 7996-8027, (2019); Moorman C., Day G. S., Organizing for marketing excellence, Journal of Marketing, 80, 6, pp. 6-35, (2016); Qadri Y. A., Nauman A., Zikria Y. B., Vasilakos A. V., Kim S. W., The future of healthcare internet of things: A survey of emerging technologies, IEEE Communications Surveys and Tutorials, 22, 2, pp. 1121-1167, (2020); Rust R. T., Huang M. H., The service revolution and the transformation of marketing science, Marketing Science, 33, 2, pp. 206-221, (2014); Siboni S., Sachidananda V., Meidan Y., Bohadana M., Mathov Y., Bhairav S., Shabtai A., Elovici Y., Security testbed for Internet-of-Things devices, IEEE Transactions on Reliability, 68, 1, pp. 23-44, (2019); Siegel J. E., Kumar S., Sarma S. E., The future internet of things: Secure, efficient, and model-based, IEEE Internet of Things Journal, 5, 4, pp. 2386-2398, (2017); Tiago M. T. P. M. B., Verissimo J. M. C., Digital marketing and social media: Why bother?, Business Horizons, 57, 6, pp. 703-708, (2014); Tofighi S., Torabi S. A., Mansouri S. A., Humanitarian logistics network design under mixed uncertainty, European Journal of Operational Research, 250, 1, pp. 239-2500, (2016); Wedel M., Kannan P. K., Marketing analytics for data-rich environments, Journal of Marketing, 80, 6, pp. 97-121, (2016); Yao J., Ansari N., Caching in energy harvesting aided Internet of Things: A game-theoretic approach, IEEE Internet of Things Journal, 6, 2, pp. 3194-3201, (2018); Zhang J. Z., Watson G. F., Palmatier R. W., Dant R. P., Dynamic relationship marketing, Journal of Marketing, 80, 5, pp. 53-75, (2016)",null,null,"IGI Global",{"$nulls":5},1.9355726E7,null,null,null,"English","Int. J. Inf. Syst. Supply Chain Manage.","Article","Final","All Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85138447303"]
["Li H.; Lu L.; Yang L.","Li, Huipeng (57735917000); Lu, Lin (55474691700); Yang, Liguo (57210317148)","57735917000; 55474691700; 57210317148","Study on the extension evaluation of smart logistics distribution of fresh agricultural products based on the perspective of customers",2022.0,"Journal of Intelligent and Fuzzy Systems",43.0,1.0,null,615.0,626.0,11.0,2.0,"10.3233/JIFS-212362","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85131764931&doi=10.3233%2fJIFS-212362&partnerID=40&md5=503b6266e55d3e0486ac1db7db3dc04d","College of Economics and Management, Guangxi Normal University, Guilin, China; Hohai University, Nanjing, China","Li H., College of Economics and Management, Guangxi Normal University, Guilin, China; Lu L., College of Economics and Management, Guangxi Normal University, Guilin, China; Yang L., Hohai University, Nanjing, China","The rapid development of the Internet has accelerated the expansion of e-commerce sacle of fresh agricultural products. The actual audience of smart logistics distribution of fresh agricultural products is customers, and customers enjoy the process and results of distribution services. However, the current research mainly selects indicators from the aspects of enterprise performance, cost and technical level based on the perspective of managers and technicians, which make it difficult to truly reflect customers' feelings in the evaluation results. At the same time, the evaluation methods mainly focus on the comprehensive evaluation method and fuzzy evaluation method. These evaluation methods are greatly affected by subjective factors in the evaluation grade distribution, and the assignment is often relatively complete and inaccurate. To solve these problems, this paper constructs the evaluation index system of intelligent logistics distribution of fresh agricultural products from the perspective of customers, so that the selection of indicators is more in line with the real wishes of customers. And we use the extension function to construct the correlation function for multi-level extension evaluation to ensure the accuracy of the evaluation results. Taking X logistics enterprise as an example, this paper verifies the scientificity of the evaluation index system of intelligent logistics distribution of fresh agricultural products through empirical research, which has reference significance for further improving the intelligent logistics distribution of fresh agricultural products.  © 2022 - IOS Press. All rights reserved.","customer perspective; extenics; fresh agricultural products; Smart logistics distribution","Agricultural products; Function evaluation; Customer perspectives; E- commerces; Evaluation indices system; Evaluation methods; Evaluation results; Extenics; Extension evaluations; Fresh agricultural products; Logistic distributions; Smart logistic distribution; Sales",{"$nulls":4},"Guangxi Philosophy and Social Science Research Project, (21FYJ055)","This study was supported by Guangxi Philosophy and Social Science Research Project: Research on the transformation and upgrading path and countermeasures of Guangxi manufacturing industry under the Internet business ecological environment (21FYJ055). We would like to express our sincere gratitude to the anonymous reviewers, and the editors for their truly valuable comments.","He F., Wei P., Research on fault diagnosis of thermodynamic system based on the network model of internet of things, Thermal Science, 23, (2019); Liu J., Mao J., Liao J., Hu H., Zhou A., SCLPD: Smart Cargo Loading Plan Decision Framework, 2020 IEEE 36th International Conference on Data Engineering (ICDE), (2020); Pan C.H., Construction of Intelligent Logistics Model Based on Big Data, Journal of Physics: Conference Series, 1648, (2020); Liu P., Yang L., Gao Z., Huang Y., Li D., Gao Y., Energyefficient train timetable optimization in the subway system with energy storage devices, IEEE Transactions on Intelligent Transportation Systems, 19, 12, pp. 3947-3963, (2018); Wang Y., Ma X., Xu M., Liu Y., Wang Y., Two-echelon logistics distribution region partitioning problem based on a hybrid particle swarm optimization-genetic algorithm, Expert Systems with Applications an International Journal, 42, 12, pp. 5019-5031, (2015); Issaoui Y., Khiat A., Bahnasse A., Hassan O., Smart logistics: Study of the application of blockchain technology, Procedia Computer Science, 160, pp. 217-267, (2019); Hasan M.Z., Al-Rizzo H., Task scheduling in Internet of Things cloud environment using a robust particle swarm optimization, Concurrency and Computation: Practice and Experience, 32, 2, (2020); Sun R., Liu M., Zhao L., Research on logistics distribution path optimization based on PSO and IoT. International Journal of Wavelets, Multiresolution and Information Processing, 17, 6, (2019); Hu W., An improved flower pollination algorithm for optimization of intelligent logistics distribution center, Advances in Production Engineering & Management, 14, 2, pp. 177-188, (2019); Wang D., Zhu J., Wei X., Cheng T.C.E., Yin Y., Wang Y., Integrated production and multiple trips vehicle routing with time windows and uncertain travel times, Computers & Operations Research, 103, pp. 1-12, (2019); Anderluh A., Nolz P.C., Hemmelmayr V.C., Crainic T.G., Multi-objective optimization of a two-echelon vehicle routing problem with vehicle synchronization and \"grey zone\" customers arising in urban logistics, European Journal of Operational Research, 289, 3, pp. 940-958, (2021); Vishal S., Ilsun Y., Giovanni P., Mario C., Jae L., Jeong K., LoRaWAN-Based Energy-Efficient Surveillance by Drones for Intelligent Transportation Systems, Energies, 11, 3, (2018); Chen X.Z., Chen R.L., Yang C.R., Research and design of fresh agricultural product distribution service model and framework using IoT technology, Journal of Ambient Intelligence and Humanized Computing, 25, pp. 1-17, (2021); Liu S., Zhang Y., Liu Y., Wang L., Wang X.V., An 'Internet of Things' enabled dynamic optimization method for smart vehicles and logistics tasks, Journal of Cleaner Production, 215, 1, pp. 806-820, (2019); Prasanna K.R., Hemalatha M., RFID GPS and GSM based logistics vehicle load balancing and tracking mechanism, Procedia Engineering, 30, 23, pp. 726-729, (2012); Lai K.H., Supply Chain Performance in Transport Logistics: An Assessment by Service Providers, International Journal of Logistics, 6, 3, pp. 151-164, (2004); Montreuil B., Toward a Physical Internet: meeting the global logistics sustainability grand challenge, Logistics Research, 3, 3, pp. 71-87, (2011); Govindan K., Cheng T.C.E., Mishra N., Shukla N., Big data analytics and application for logistics and supply chain management, Transportation Research Part E: Logistics and Transportation Review, 114, pp. 343-349, (2018); Guerrero-Ibanez J., Zeadally S., Contreras-Castillo J., Integration challenges of intelligent transportation systems with connected vehicle, cloud computing, and internet of things technologies, IEEE Wireless Communications, 22, 6, pp. 122-128, (2015); Liu Z., Wang X., Ma X.Q., Building intelligent logistics system based on internet of things RFID in platform of cloud computing, Journal of Chemical & Pharmaceutical Research, 6, 6, pp. 772-778, (2014); Gao Y.W., Wang X.F., Research on Optimization Model of Dynamic Distribution Path Based on Intelligent Logistics, Journal of Physics: Conference Series, 1650, 3, (2020); Wang H., Li W., Zhao Z.Z., Wang Z.F., Li M.H., Li D.F., Intelligent Distribution of Fresh Agricultural Products in Smart City, IEEE Transactions on Industrial Informatics, 18, 2, pp. 1220-1230, (2020); Nathanail E., Gogas M., Papoutsis K., Investigation of stakeholders' viewtowards the introduction of ICT in supply chain using Analytic Hierarchy Process, Journal of Traffic and Logistics Engineering, 2, 2, pp. 113-119, (2014); Bozorgi-Amiri A., Khorsi M., A dynamic multiobjective location-routing model for relief logistic planning under uncertainty on demand, travel time, and cost parameters, The International Journal of Advanced Manufacturing Technology, 85, 5, pp. 1633-1648, (2016); Xiong Q.Q., Yang H., Liang Q., Research on the Application of Smart Logistics in Trunk Transportation, Scientific Journal of Economics and Management Research, 2, 8, pp. 146-149, (2020); Wang X.L., Application of Fuzzy Set Theroy in Evalution of the Logistics Distribution Center, Procedings of the Third International Conference on Machine Learning and Cybernetics, 4, pp. 190-194, (2004); Zhang Q.Y., Research on the City Logistics Development Evaluation System Based on Fuzzy Mathematics, International Conference on Management and Service Science, 5, pp. 1-4, (2009); Li C.M., Guo L.H., Li Z.X., Design of Decision-Making System of Emergency Logistics Information System Based on Data Mining, Journal of Digital Information Management, 12, 6, pp. 383-386, (2014); Pan J.N., Nguyen H.T.N., Achieving customer satisfaction through service systems, European Journal of Operational Research, 247, 1, pp. 179-190, (2015)","L. Lu; College of Economics and Management, Guangxi Normal University, Guilin, 541000, China; email: lulin355@163.com",null,"IOS Press BV",{"$nulls":5},1.0641246E7,null,null,null,"English","J. Intelligent Fuzzy Syst.","Article","Final",null,"Scopus","2-s2.0-85131764931"]
["Yang L.","Yang, Li (57700528000)",5.7700528E10,"Research on Logistics Distribution Vehicle Path Optimization Based on Simulated Annealing Algorithm",2022.0,"Advances in Multimedia",2022.0,null,7363279.0,null,null,null,1.0,"10.1155/2022/7363279","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85130367053&doi=10.1155%2f2022%2f7363279&partnerID=40&md5=ab0d44dffe6d89502d550046af47cf6a","School Of Economics And Trade Management, Henan Institute Of Industry And Technology, Nanyang, 473000, China","Yang L., School Of Economics And Trade Management, Henan Institute Of Industry And Technology, Nanyang, 473000, China","With the continuous development of Internet technology, e-commerce has gradually become a popular field. As an important part of China's tertiary industry, the rapid development of e-commerce has played a huge role in promoting the development of the domestic economy. At the same time, e-commerce has also greatly contributed to the development of the logistics industry. Hence, with the rapid growth of the economy and the rapid development of e-commerce, the construction of logistics and distribution systems plays an essential role in the process of urban development. A perfect logistics and distribution system can promote the overall economic efficiency of the city and facilitate people's daily lives. In addition, the development of logistics systems can meet the escalating needs of consumers and the increasingly competitive market environment, thus promoting the transformation of e-commerce retail enterprises to high-quality development. The simulated annealing algorithm is an effective approximation algorithm for solving optimization problems, and the application of this algorithm to path optimization problems can be of practical value in solving problems in urban road traffic and logistics distribution. Therefore, exploring logistics distribution vehicle route optimization is of great practical significance to optimize the allocation of resources in cities, improve the economic efficiency of enterprises, and solve the problems of urban traffic congestion and can provide reference for relevant departments in their decision-making. This paper focuses on how to optimize vehicle paths in the logistics distribution process and constructs a path optimization model that satisfies the multiobjective premise. The path problem is solved using the simulated annealing algorithm, and the results are analyzed.  © 2022 Li Yang.",null,"Behavioral research; Decision making; Economic and social effects; Efficiency; Electronic commerce; Simulated annealing; Traffic congestion; Urban growth; Vehicles; Annealing algorithm; Continuous development; Distribution systems; Distribution vehicles; E- commerces; Economic efficiency; Logistic distributions; Logistics system; Optimization problems; Path optimizations; Approximation algorithms",{"$nulls":6},"Khrais L.T., Role of artificial intelligence in shaping consumer demand in E-commerce, Future Internet, 12, 12, (2020); Zhang D., Pee L.G., Cui L., Artificial intelligence in E-commerce fulfillment: a case study of resource orchestration at Alibaba's Smart Warehouse, International Journal of Information Management, 57, (2021); Li Q., E-commerce, free-trade zones, and the linkage effect to China's foreign trade, The Chinese Economy, 54, 6, pp. 441-449, (2021); Biagi F., Falk M., The impact of ICT and e-commerce on employment in Europe, Journal of Policy Modeling, 39, 1, pp. 1-18, (2017); Barykin S.Y., Smirnova E., Sharapaev P., Mottaeva A., Development of the Kazakhstan digital retail chains within the eaeu e-commerce market, Academy of Strategic Management Journal, 20, pp. 1-18, (2021); Chen H., Jin Y., Huo B., Understanding logistics and distribution innovations in China, International Journal of Physical Distribution & Logistics Management, 50, 3, pp. 313-322, (2020); Birasnav M., Kalaivanan S., Ramesh A., Tibrewala R., Routing vehicles through cross-docking facility for third party logistics service providers, International Journal of Operational Research, 38, 2, pp. 255-277, (2020); Buldeo Rai H., Verlinde S., Merckx J., MacHaris C., Crowd logistics: an opportunity for more sustainable urban freight transport?, European Transport Research Review, 9, 3, pp. 39-13, (2017); Ouyang F., Research on port logistics distribution route planning based on artificial fish swarm algorithm, Journal of Coastal Research, 115, SP1, pp. 78-80, (2020); Jiang X., Guo X., Evaluation of performance and technological characteristics of battery electric logistics vehicles: China as a case study, Energies, 13, 10, (2020); Yaxu Y., Comprehensive evaluation of logistics enterprise competitiveness based on SEM model, Journal of Intelligent and Fuzzy Systems, 40, 4, pp. 6469-6479, (2021); Andiyappillai N., Latest developments in logistics and supply chain systems implementations, International Research Journal on Advanced Science Hub, 2, 3, pp. 12-17, (2020); Zheng K., Zhang Z., Song B., E-commerce logistics distribution mode in big-data context: a case analysis of JD.COM, Industrial Marketing Management, 86, pp. 154-162, (2020); Konstantakopoulos G.D., Gayialis S.P., Kechagias E.P., Vehicle routing problem and related algorithms for logistics distribution: a literature review and classification, Operational Research, pp. 1-30, (2020); Satar N.S.M., Dastane O., Yusnorizam M., Customer value proposition for E-Commerce: a case study approach, International Journal of Advanced Computer Science and Applications, 10, 2, pp. 454-458, (2019); Klumpp M., Zijm H., Logistics innovation and social sustainability: how to prevent an artificial divide in human-computer interaction, Journal of Business Logistics, 40, 3, pp. 265-278, (2019); Cichosz M., Goldsby T.J., Knemeyer A.M., Taylor D.F., Innovation in logistics outsourcing relationship-in the search of customer satisfaction, LogForum, 13, 2, pp. 209-219, (2017); Orji I.J., Kusi-Sarpong S., Gupta H., Okwu M., Evaluating challenges to implementing eco-innovation for freight logistics sustainability in Nigeria, Transportation Research Part A: Policy and Practice, 129, pp. 288-305, (2019); Zhikang L., Research on development strategy of automobile reverse logistics based on SWOT analysis, Procedia Engineering, 174, pp. 324-330, (2017); Sun L., Song G., Current state and future potential of logistics and supply chain education: a literature review, Journal of International Education in Business, 11, 2, pp. 124-143, (2018); Lizbetinova L., Nedeliakova E., Sousek R., Gregus M., Keeping talents in the transport and logistics enterprises: case study from the Czech Republic, Acta Polytechnica Hungarica, 17, 9, pp. 199-219, (2020); Golembska E., Golembski M., A new model of the personnel function delivery in the logistics of polish firms, Logistics, 4, 3, (2020); Cheng B., Lu K., Li J., Chen H., Luo X., Shafique M., Comprehensive assessment of embodied environmental impacts of buildings using normalized environmental impact factors, Journal of Cleaner Production, 334, (2022); Twrdy E., Zanne M., Improvement of the sustainability of ports logistics by the development of innovative green infrastructure solutions, Transportation Research Procedia, 45, pp. 539-546, (2020); Wang K., Shao Y., Zhou W., Matheuristic for a two-echelon capacitated vehicle routing problem with environmental considerations in city logistics service, Transportation Research Part D: Transport and Environment, 57, pp. 262-276, (2017); Ali Abumalloh R., Ibrahim O., Nilashi M., Loyalty of young female Arabic customers towards recommendation agents: a new model for B2C E-commerce, Technology in Society, 61, (2020); Roudposhti V., Nilashi M., Mardani A., Streimikiene D., Samad S., Ibrahim O., A new model for customer purchase intention in e-commerce recommendation agents, Journal of International Studies, 11, 4, pp. 237-253, (2018); Keshavarz Ghorabaee M., Amiri M., Olfat L., Khatami Firouzabadi S.M.A., Designing a multi-product multi-period supply chain network with reverse logistics and multiple objectives under uncertainty, Technological and Economic Development of Economy, 23, 3, pp. 520-548, (2017); Miao C., Liu H., Zhu G.G., Chen H., Connectivity-based optimization of vehicle route and speed for improved fuel economy, Transportation Research Part C: Emerging Technologies, 91, pp. 353-368, (2018); Pamucar D., Cirovic G., Cirovic G., Vehicle route selection with an adaptive neuro fuzzy inference system in uncertainty conditions, Decision Making: Applications in Management and Engineering, 1, 1, pp. 13-37, (2018); Ho S.C., Szeto W.Y., A hybrid large neighborhood search for the static multi-vehicle bike-repositioning problem, Transportation Research Part B: Methodological, 95, pp. 340-363, (2017); Wang F., Liao F., Li Y., Yan X., Chen X., An ensemble learning based multi-objective evolutionary algorithm for the dynamic vehicle routing problem with time windows, Computers & Industrial Engineering, 154, (2021); Zhang W., Maleki A., Rosen M.A., Liu J., Optimization with a simulated annealing algorithm of a hybrid system for renewable energy including battery and hydrogen storage, Inside Energy, 163, pp. 191-207, (2018)","L. Yang; School Of Economics And Trade Management, Henan Institute Of Industry And Technology, Nanyang, 473000, China; email: 2006095@hnpi.edu.cn",null,"Hindawi Limited",{"$nulls":5},1.687568E7,null,null,null,"English","Adv. Multimedia","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85130367053"]
["Han X.; Wang J.","Han, Xiao (57918009600); Wang, Jingyi (57215508269)","57918009600; 57215508269","Logistics Supply Chain Management Mode of Chinese E-Commerce Enterprises under the Background of Big Data and Internet of Things",2022.0,"Journal of Sensors",2022.0,null,7818944.0,null,null,null,1.0,"10.1155/2022/7818944","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85139427787&doi=10.1155%2f2022%2f7818944&partnerID=40&md5=428f88f8557c036534bc96edb6c63b6d","Free Trade Office, Administrative Committee of Chongqing Liangjiang New Area, Chongqing, 401122, China; Economic Operation Bureau, Administrative Committee of Chongqing Liangjiang New Area, Chongqing, 401122, China","Han X., Free Trade Office, Administrative Committee of Chongqing Liangjiang New Area, Chongqing, 401122, China; Wang J., Economic Operation Bureau, Administrative Committee of Chongqing Liangjiang New Area, Chongqing, 401122, China","With the development of information technology, the logistics supply chain of Chinese E-commerce enterprises still has the problem of backward industrial model and low product quality. It is necessary to deeply integrate the logistics supply chain with big data and Internet technology and develop a logistics intelligent supply chain management model in order to meet the needs of Chinese E-commerce enterprises for logistics supply chain. The management mode of the logistics supply chain of Chinese E-commerce enterprises will show the development trend of diversification and simplification, standardization and normalization, and intelligence and efficiency in the future.  © 2022 Xiao Han and Jingyi Wang.",null,"Electronic commerce; Information management; Internet of things; Supply chain management; Data technologies; Development trends; E-commerce enterprise; Industrial modeling; Internet technology; Logistics supply chain managements; Logistics supply chains; Management Model; Management modes; Products quality; Big data",{"$nulls":6},"Qian P., Discussion on the management mode and construction of international logistics supply chain from the perspective of cross-border e-commerce, Mall Modernization, 17, pp. 46-47, (2018); Rui L., Research on supply chain management of logistics enterprises in the era of big data, China Market, 6, pp. 179-180, (2021); Yue H., The impact of big data technology on supply chain management, Chinese Business Theory, 2, pp. 108-109, (2021); Shuo J., Research on the construction of intelligent logistics supply chain system based on Internet of things, Computer Products and Circulation, 11, (2020); Juanjuan C., Innovation of enterprise logistics and supply chain management under the environment of e-commerce, Modernization of Shopping Malls, 18, pp. 66-67, (2020); Le Z., Management and science and technology of small and medium-sized enterprises (mid-issue), Contemporary Economy, 24, pp. 40-41, (2019); Le H., Discussion on the innovation of enterprise logistics and supply chain management under the environment of electronic commerce, Management and Technology of Small and Medium-sized Enterprises (First Ten Days), 12, (2019); Xinyi C., Probe into the risk generation mechanism and early warning mode of agricultural product logistics supply chain, Modernization of Shopping Malls, 18, pp. 66-67, (2020); Mei H., Discussion on the innovation of enterprise logistics and supply chain management under the environment of electronic commerce, Economic Forum, 12, pp. 55-59, (2019); Xiangyu C., Research on the development and innovation path of China's cross-border E-commerce under the background of big data, Management and Technology of Small and Medium-sized Enterprises (First Ten Days), 12, (2018); Xiaoping Z., Rational view of enterprise supply chain management under the environment of e-commerce, Management and Technology of Small and Medium-sized Enterprises (First Ten Days), 12, (2019); Changyu S., Supply chain management and its innovation under the environment of electronic commerce, Contemporary Economy, 20, pp. 40-41, (2019); Wang L., The financing mode of enterprises making use of third-party e-commerce platform, Journal of East China University, 19, 4, pp. 101-104, (2002); Rui Z., Research on the application of big data technology in cross-border E-commerce industry chain, Science and Technology Entrepreneurship Weekly, 4, pp. 92-93, (2020); Jiahao B., The reform of supply chain management under the environment of e-commerce, Modernization of Shopping Malls, 18, pp. 66-67, (2020); Hui H., Cross-border e-commerce based on the background of big data, Business Economics and Management, 20, pp. 89-99, (2018); Li Y., Analysis on the coordinated development of cross-border E-commerce and logistics in the era of big data, Science and Technology and Management, 4, (2021); Huan S., Supply chain management and its innovation in E-commerce environment, Science and Technology Entrepreneurship Weekly, 4, pp. 92-93, (2020)","X. Han; Free Trade Office, Administrative Committee of Chongqing Liangjiang New Area, Chongqing, 401122, China; email: 19403590@masu.edu.cn",null,"Hindawi Limited",{"$nulls":5},"1687725X",null,null,null,"English","J. Sensors","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85139427787"]
["Yan S.; Huang L.","Yan, Shenghua (58068253700); Huang, Lei (57226040263)","58068253700; 57226040263","Research on the optimisation of logistics parcel intelligent sorting and conveying chain combined with variable clustering mathematical method",2022.0,"Applied Mathematics and Nonlinear Sciences",{"$nulls":6},0.0,"10.2478/amns.2021.2.00259","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85146383440&doi=10.2478%2famns.2021.2.00259&partnerID=40&md5=ec1f2a62510e12ace1a4f196299c0ee9","School of Mechanical and Electrical Engineering, Hubei Polytechnic University, Huangshi, Hubei, 435003, China","Yan S., School of Mechanical and Electrical Engineering, Hubei Polytechnic University, Huangshi, Hubei, 435003, China; Huang L., School of Mechanical and Electrical Engineering, Hubei Polytechnic University, Huangshi, Hubei, 435003, China","The rapid development of China's economy, especially the rapid rise of the logistics and distribution industry in recent years, coupled with the rise of e-commerce in recent years, has created a huge impact on the traditional logistics industry. Aiming at the sorting system of small and medium-sized logistics distribution centrer, this paper proposes an item allocation strategy based on customer demand in combination with practical application requirements and adopts the direct dynamic clustering algorithm based on hierarchical clustering. As a clustering index, all items in the distribution centre are clustered and the final clustering result is obtained. The results show that the maximum value of segmentation using the single connection method is 5.8, reflecting that the distribution distance is more advantageous; the maximum value of the segmentation method using the median method is 2.94, and the minimum value is 2.35, which reflects that the result of the algorithm is relatively uniform. A reasonable item allocation strategy has a certain positive effect and influence on the development of modern logistics and the service quality of the logistics industry. © 2022 Shenghua Yan et al., published by Sciendo 2022.","Direct dynamic clustering; Fisher distance; Hierarchical clustering; Item assignment; Sorting system","Conveying; Warehouses; Allocation strategy; Direct dynamic clustering; Direct dynamics; Dynamic clustering; Fisher distance; Hier-archical clustering; Hierarchical Clustering; Item assignment; Logistics industry; Sorting system; Clustering algorithms",{"$nulls":4},"Hubei Provincial Department of Education, (B2020204)","Guiding project of Scientific Research Plan of Hubei Provincial Department of Education. (B2020204). Scientific research project of Hubei Polytechnic University. (20xjz10Q)","Liu P., Li Y., Multiattribute decision method for comprehensive logistics distribution center location selection based on 2-dimensional linguistic information, Information Sciences, 538, (2020); Zhu X., A Flexsim-based Optimization for the Operation Process of Cold-Chain Logistics Distribution Centre, Journal of applied research and technology, 12, 2, (2014); Yang L., Logistics distribution centers location problem and algorithm under fuzzy environment, Journal of Computational and Applied Mathematics, 208, 2, (2007); Hua X., Hu X., Yuan W., Research optimization on logistics distribution center location based on adaptive particle swarm algorithm, Optik, 127, 20, (2016); Holzapfel A., Kuhn H., Sternbeck M.G., Product allocation to different types of distribution center in retail logistics networks, European Journal of Operational Research, 264, 3, (2018); Liu W., Intelligent logistics transformation problems in efficient commodity distribution, Transportation Research Part E: Logistics and Transportation Review, 163, (2022); Kostrzewski M., Filina-Dawidowicz L., Walusiak S., Modern technologies development in logistics centers: the case study of Poland, Transportation Research Procedia, 55, (2021); Boysen N., Automated sortation conveyors: A survey from an operational research perspective, European Journal of Operational Research, 276, 3, (2019); Schenk L., Klabjan D., Intra market optimization for express package carriers with station to station travel and proportional sorting, Computers & operations research, 37, 10, (2010); Tan Z., Li H., He X., Optimizing parcel sorting process of vertical sorting system in e-commerce warehouse, Advanced Engineering Informatics, 48, (2021); Leung K.H., Lee C.K.M., Choy K.L., An integrated online pick-to-sort order batching approach for managing frequent arrivals of B2B e-commerce orders under both fixed and variable time-window batching, Advanced Engineering Informatics, 45, (2020); He X., Meng S., Liang J., Analysis of cross-border E-Commerce logistics model based on embedded system and genetic algorithm, Microprocessors and Microsystems, 82, (2021); Sisman S., Aydinoglu A.C., Improving performance of mass real estate valuation through application of the dataset optimization and Spatially Constrained Multivariate Clustering Analysis, Land Use Policy, 119, (2022); Park J., Lee T., Kim D., Improving PMF source reconciliation with cluster analysis for PM2.5 hourly data from Seoul, Korea, Atmospheric Pollution Research, 13, 5, (2022); Govender P., Sivakumar V., Application of k-means and hierarchical clustering techniques for analysis of air pollution: A review (1980-2019), Atmospheric pollution research, 11, 1, (2020); Jiang Z., Comparison of adverse events between cluster and conventional immunotherapy for allergic rhinitis patients with or without asthma: A systematic review and meta-analysis, American Journal of Otolaryngology, 40, 6, (2019); Grabowski J., Smolinski A., The application of hierarchical clustering to analyzing ashes from the combustion of wood pellets mixed with waste materials, Environmental Pollution, 276, (2021); Dong L., Wind power day-ahead prediction with cluster analysis of NWP, Renewable and Sustainable Energy Reviews, 60, (2016); Ahmad A., Khan S.S., initKmix-A novel initial partition generation algorithm for clustering mixed data using k-means-based clustering, Expert Systems with Applications, 167, (2021); Dobrykh F., Muravyov S., Ilyasova O., Ensemble Clustering Algorithm Development for Tabular Data by a Given Partition Quality Measure, Procedia Computer Science, 193, (2021); Xu N., Coal elemental (compositional) data analysis with hierarchical clustering algorithms, International Journal of Coal Geology, 249, (2022); Habib A., Akram M., Kahraman C., Minimum spanning tree hierarchical clustering algorithm: A new Pythagorean fuzzy similarity measure for the analysis of functional brain networks, Expert Systems with Applications, 201, (2022); Varshney A.K., Muhuri P.K., Lohani Q.M.D., PIFHC: The Probabilistic Intuitionistic Fuzzy Hierarchical Clustering Algorithm, Applied Soft Computing, 120, (2022); Zhang R., Adaptive density-based clustering algorithm with shared KNN conflict game, Information Sciences, 565, (2021); Cen L., Application of density-based clustering algorithm and capsule network to performance monitoring of antimony flotation process, Minerals Engineering, 184, (2022); Hu L., KR-DBSCAN: A density-based clustering algorithm based on reverse nearest neighbor and influence space, Expert Systems with Applications, 186, (2021); Deng X., Tang G., Wang Q., A novel fast classification filtering algorithm for LiDAR point clouds based on small grid density clustering, Geodesy and Geodynamics, 13, 1, (2022); Cheng M., Adaptive grid-based forest-like clustering algorithm, Neurocomputing, 481, (2022); Li B., DNC: A Deep Neural Network-based Clustering-oriented Network Embedding Algorithm, Journal of Network and Computer Applications, 173, (2021); Sun Y., Uncertain data stream algorithm based on clustering RBF neural network, Microprocessors and Microsystems, 81, (2021)","S. Yan; School of Mechanical and Electrical Engineering, Hubei Polytechnic University, Hubei, Huangshi, 435003, China; email: ysh201008@163.com",null,"Sciendo",{"$nulls":5},2.4448656E7,null,null,null,"English","Appl. Math. Nonlinear Sci.","Article","Article in press","All Open Access; Gold Open Access","Scopus","2-s2.0-85146383440"]
["Jiao J.; Liu Y.; Xie C.","Jiao, Jianhong (57682251200); Liu, Yong (57372073400); Xie, Cuijie (57681691900)","57682251200; 57372073400; 57681691900","The Optimization Model of E-Commerce Logistics Distribution Path Based on GIS Technology",2022.0,"Advances in Multimedia",2022.0,null,4303863.0,null,null,null,1.0,"10.1155/2022/4303863","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85131306310&doi=10.1155%2f2022%2f4303863&partnerID=40&md5=99579baa3223e3aa09efaadbe9e6ef93","Department of Logistics Management, Hebei Jiaotong Vocational and Technical College, Shijiazhuang, 050035, China","Jiao J., Department of Logistics Management, Hebei Jiaotong Vocational and Technical College, Shijiazhuang, 050035, China; Liu Y., Department of Logistics Management, Hebei Jiaotong Vocational and Technical College, Shijiazhuang, 050035, China; Xie C., Department of Logistics Management, Hebei Jiaotong Vocational and Technical College, Shijiazhuang, 050035, China","The optimization of the e-commerce logistics distribution path has always been an important research object in intelligent control. Based on the geographic information system (GIS) platform, this paper proposes an improved ant colony algorithm for the logistics distribution path optimization model based on the GIS platform. Firstly, ArcGIS software is used to solve the problem of complex networks and realize the selection and output of optional routes. Secondly, the basic ant colony algorithm is improved, and a dynamic path planning method combining global planning information and local planning is proposed. It mainly includes the improvement of the heuristic function and the improvement of the update method of pheromone. Finally, through simulation experiments and case validation experiments, it is concluded that the improved algorithm outperforms the traditional ant colony algorithm. In the case validation part, a local area of Beijing is selected to simulate a natural distribution environment, and the path optimization experiments are validated by building an actual road network model. The results show that the model can plan the optimal path for logistics distribution according to the road congestion. The data analysis shows that the route optimization model proposed in this paper can effectively reduce the distribution cost of enterprises, increase vehicle loading, and increase the profit and industry competitiveness of logistics enterprises.  © 2022 Jianhong Jiao et al.",null,"Ant colony optimization; Competition; Complex networks; Electronic commerce; Geographic information systems; Heuristic methods; Roads and streets; E- commerces; Improved ant colony algorithm; Logistic distributions; Optimisations; Optimization models; Path optimizations; Path-based; Research object; System platforms; Motion planning",{"$nulls":6},"Xiong G., Multimodal transportation planning of low carbon logistics, Computer Simulation, 33, 6, pp. 149-153+222, (2016); Yonetani R., Taniai T., Barekatain M., Nishimura M., Kanezaki A., Path planning using neural A∗ search, International Conference on Machine Learning, 139, pp. 12029-12039, (2021); Mohanty P.K., Kodapurath A.A., Singh R.K., A hybrid artificial Immune system for mobile robot navigation in unknown environments, Iranian Journal of Science and Technology, Transactions of Electrical Engineering, 44, 4, pp. 1619-1631, (2020); Liu L., Airplane trajectory planning using artificial Immune algorithm, Advances in 3D Image and Graphics Representation, Analysis, Computing and Information Technology, pp. 245-251, (2020); Liu X.-h., Zhang D.J.T.H., A path planning method based on the particle swarm optimization trained fuzzy neural network algorithm, Cluster Computing, 24, 3, pp. 1901-1915, (2021); Chen X., Gao P., Path planning and control of soccer robot based on genetic algorithm, Journal of Ambient Intelligence and Humanized Computing, 11, 12, pp. 6177-6186, (2020); Thangiah S., Nygard K., A genetic algorithm system for vehicle routing with time windows, pp. 322-328, (1990); Joe L., Blanton J., Multiple vehicle routing problem with time and capacity constraints using genetic algorithms, Morgan Kaufman Publishers Inc, 26, pp. 452-459, (1993); Ebadinezhad S., DEACO: adopting dynamic evaporation strategy to enhance ACO algorithm for the traveling salesman problem, Engineering Applications of Artificial Intelligence, 92, (2020); Got A., Moussaoui A., Zouache D., A guided population archive whale optimization algorithm for solving multiobjective optimization problems, Expert Systems with Applications, 141, MAR, (2020); Rajeev G., Raman M., A hybrid of Ant Colony and firefly algorithms (HAFA) for solving vehicle routing problems, Journal of Computational Science, 25, 3, pp. 25-38, (2018); Dorigo M., Maniezzo V., Colorni A., Ant system: optimization by a colony of cooperating agents, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 26, 1, pp. 29-41, (1996); Stutzle T., Hoos H.H., - ant system, Future Generation Computer Systems, 16, 8, pp. 889-914, (2000); Gaertner D., Clark K.L., On optimal parameters for ant colony optimization algorithms, pp. 83-89; Liang Y., Wang L., Applying genetic algorithm and ant colony optimization algorithm into marine investigation path planning model, Soft Computing, 24, 11, pp. 8199-8210, (2020); Gupta A., Srivastava S., Comparative analysis of ant colony and particle swarm optimization algorithms for distance optimization, Procedia Computer Science, 173, pp. 245-253, (2020); Campbell A., Both A., Sun Q., Detecting and mapping traffic signs from Google Street View images using deep learning and GIS, Computers, Environment and Urban Systems, 77, (2019); Sulaiman M., Liu X., Binalhaj M., Liou W.W., Abudayyeh O., GIS-based automatic flight planning of camera-equipped uavs for fire emergency response, pp. 139-144; Gyabeng B.A., Bernard A., Selection of optimum petroleum pipeline routes using A multi-criteria decision analysis and GIS least-cost path approach, International Journal of Scientific and Research Publications (IJSRP), 10, 6, pp. 572-579, (2020); Meena D.K., Tripathi R., Agrawal S., GIS based multi-parameter optimal path analysis for rural schools, ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 452, pp. 67-74, (2019); Jiao Z., Ma K., Rong Y., Wang P.H.S., A path planning method using adaptive polymorphic ant colony algorithm for smart wheelchairs, Journal of Computational Science, 25, pp. 50-57, (2018)","C. Xie; Department of Logistics Management, Hebei Jiaotong Vocational and Technical College, Shijiazhuang, 050035, China; email: xiecuijie@hejtxy.edu.cn",null,"Hindawi Limited",{"$nulls":5},1.687568E7,null,null,null,"English","Adv. Multimedia","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85131306310"]
["Arora A.; Kesari J.","Arora, Abhishek (57204044490); Kesari, Janardan (6602665848)","57204044490; 6602665848","Design and Development of a Solar Electric Delivery Pod",2022.0,"International Journal of Electrical and Electronics Research",10.0,3.0,null,429.0,437.0,8.0,1.0,"10.37391/ijeer.100304","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135971966&doi=10.37391%2fijeer.100304&partnerID=40&md5=d22c87a3449c8028f91b7d1dfbd0f333","Department of Mechanical Engineering, Delhi Technological University, Delhi, India","Arora A., Department of Mechanical Engineering, Delhi Technological University, Delhi, India; Kesari J., Department of Mechanical Engineering, Delhi Technological University, Delhi, India","Use of autonomous solar electric vehicles for road delivery purposes in India remains highly unexplored area. The aim of these research paper is to cover major design aspects and develop a prototype solar electric delivery vehicle with autonomous drive for city logistic purposes. The vehicle design is constructed using the locally available raw materials and is aerodynamically tested. CAD modelling on SolidWorks’20 has been used to build a virtual physical model of the vehicle and aerodynamic testing is performed. MATLAB Simulink has been used to develop a mathematical simulation model with various subsystems like battery, motor, vehicle dynamics and PV charging module. Vehicle has been tested for 2 major drive cycles and results are plotted. The vehicle operates with a wheel hub BLDC motor by rechargeable Li-ion battery pack charged with the help of PV panel. © 2022, Forex Publication. All rights reserved.","Autonomous vehicles; E-commerce; Electric Vehicle; Industry 4.0; Solar Vehicle; Urban Freight",{"$nulls":7},"Prajapati Mamta L, Et al., IOP Conf. Ser.: Mater. Sci. Eng, 937, (2020); Waseem Mohammad, Et al., SN Applied Sciences, 1, (2019); J. Renewable Sustainable Energy, 12, (2020); Iwan S., Et al., Sustainable Cities and Society, 74, (2021); de Mello Bandeira R.A., Et al., Transportation Research Part D, 67, pp. 491-502, (2019); Mirhedayatian S.M., Yan S., Transportation Research Part D, 58, pp. 22-38, (2018); Mobarak Muhammad Hosnee, Et al., IEEE Transactions on Transportation Electrification; Rizet Christophe, Et al., Transportation Research Procedia, 12, pp. 500-507, (2016); Teoh Tharsis, Et al., Sustainability, 10, (2018); Patyal V.S., Kumar R., Kushwah S., Energy, 237, (2021); Kumar Ashish, Prasad Lal Bahadur, International Conference on Computing, Power and Communication Technologies (GUCON) Galgotias University, (2018); Kaloko Bambang Sri, Et al., International Journal of Computer Applications (0975 – 8887), 24, 6, (2011); Ashok J., Mirajkar Pradnya P., Lakesar Archana L., International Journal of Mechanical and Production Engineering Research and Development (IJMPERD), 8, 4, pp. 133-146, (2018); Taha Zahari, Et al., Proceedings of the IASTED International Conference Solar Energy (SOE 2009), (2009); Jennings D., Figliozzi M., Study of road autonomous delivery robots and their potential impacts on freight efficiency and travel, Forthcoming Transportation Research Record, (2020); Paterson, Et al., Proc IMechE Part D: J Automobile Engineering; Lg M50 Rechargeable Battery; Ceat Zoom XL 80/100-17 46P Tubeless Bike Tyre, Rear: Amazon.in: Car & Motorbike; Buy Luminous 330W 24V Polycrystalline Solar Panel; BLDC Motors – Tech Imperial","A. Arora; Department of Mechanical Engineering, Delhi Technological University, Delhi, India; email: abhiarora4567@gmail.com",null,"Forex Publication",{"$nulls":5},"2347470X",null,null,null,"English","Int. J. Electr. Electron. Res.","Article","Final","All Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85135971966"]
["Macioszek E.; Jurdana I.","Macioszek, Elżbieta (36662343300); Jurdana, Irena (24437943900)","36662343300; 24437943900","ANALYSIS OF THE DEVELOPMENT OF E-COMMERCE IN POLAND FROM 2010-2020 AND ITS IMPACT ON THE TRANSPORT SECTOR",2022.0,"Scientific Journal of Silesian University of Technology. Series Transport",116.0,null,null,197.0,209.0,12.0,0.0,"10.20858/sjsutst.2022.116.12","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137183280&doi=10.20858%2fsjsutst.2022.116.12&partnerID=40&md5=9fce8ae46e09be4cc0b8aeb82a8c00f4","Faculty of Transport and Aviation Engineering, The Silesian University of Technology, Krasińskiego 8 Street, Katowice, 40-019, Poland; Faculty of Maritime Studies, University of Rijeka, Studentska Ulica 2, Rijeka, HR-51000, Croatia","Macioszek E., Faculty of Transport and Aviation Engineering, The Silesian University of Technology, Krasińskiego 8 Street, Katowice, 40-019, Poland; Jurdana I., Faculty of Maritime Studies, University of Rijeka, Studentska Ulica 2, Rijeka, HR-51000, Croatia","Trade with the use of internet technology (e-commerce) provides new opportunities for expansion on a larger scale for already existing business entities and offers prospects for rapid development for new companies. This is possible due to the low entry barriers that encourage the sale of products. Online retail trade is gaining increased popularity in Poland. This article aims to analyze e-commerce development in Poland from 2010-2020. This analysis is based on data from the Central Statistical Office. The results of the analysis clearly show that the share of purchases made via the internet has been systematically growing from year to year. This growth contributes to the faster development of transport logistics, as well as the transport of the goods itself. © 2022 Cristobal Balbontin. All rights reserved.","e-commerce; logistics of transport; online store logistics; transport company",{"$nulls":5},"Silesian University of Technology, SUT, (12/040/RGJ22/0047)","Acknowledgments: This publication is supported by the Rector’s Pro-Quality Grant, Silesian University of Technology, under grant number 12/040/RGJ22/0047.","Thihas Ali Mohammed, Thangavelan R., E-commerce, International Journal of Management, 6, 1, pp. 169-172, (2018); How has e-commerce changed logistics?; Nils Boysen, de Koster Rene, Weidinger Felix, Warehousing in the e-commerce era: A survey, European Journal of Operational Research, 277, 2, pp. 396-411, (2019); Felicjan Bylok, Examining the impact of trust on the e-commerce purchase intentions of young consumers in Poland, Journal of Internet Commerce, 21, 3, (2021); Gonzalez-Feliu J., Ambrosini C., Routhier J-L., New trend on urban goods movement: modelling and simulation of e-commerce distribution, European Transport / Trasporti Europei, 20, pp. 1-23, (2012); Gunasekaran A., Marri H.B., McGaughey R.E., Nedhwani M.D., E-commerce and its impact on operations management, International Journal of Production Economics, 75, 1-2, pp. 185-197, (2002); Adrian Januszkiewicz, E-commerce and the future of urban mobility, (2021); Moutaz Khouja, The evaluation of drop shipping option for e-commerce retailers, Computers & Industrial Engineering, 41, 2, pp. 109-126, (2001); Leung K.H., Choy K.L., Siu Paul K.Y., Ho G.T.S., Lam H.Y., Lee Carman K.M., A B2C e-commerce intelligent system for reengineering the e-order fulfilment process, Expert Systems with Applications, 91, pp. 386-401, (2018); Xiaolin Lin, Xuequn Wang, Nick Hajli, Building E-Commerce satisfaction and boosting sales: the role of social commerce trust and its antecedents, International Journal of Electronic Commerce, 23, 3, pp. 328-363, (2019); The impact of the E-commerce market on the TSL industry; Pawel Morawski, Logistics of online stores, Entrepreneurship and Management. Logistics management, pp. 125-140, (2011); Baozhuang Niu, Fengfeng Xie, Lei Chen, Xin Xu, Join logistics sharing alliance or nor? Incentive analysis of comnpeting E-commerce firms with promised-delivery-time, International Journal of Production Economics, 224, pp. 1-37, (2020); Hafaz Ngah Abdul, Mohamed Anuar Marhana, Nohd Rozar Nor Linda, Antonio Ariza-Montes, Luis Araya-Castillo, Jenny Kim Jinkyung, Heesup Hun, Online Sellers' Reuse behaviour for third-party logistics services: an innovative model development and E-commerce, Sustainability, 13, 14, pp. 1-15, (2021); System of Competence Councils: Identification of support instruments for the development of the trade sector, (2020); The World's Largest Market Research Store.,,Road Freight Transportation Market in Europe 2020-2024; The Polish e-commerce market will grow by a third this year. It will double in value by 2023; We check the domestic market; Nebojsa Vasic, Kilibarda Milorad, Andrejic Milan, Jovic Srdan, Satisfaction is a function of users of logistics services in e-commerce, Technology Analysis & Strategic Management, 33, 7, pp. 813-828, (2019); Wang Ying, Dayong Sang, Multi-agent framework for third party logistics in E-commerce, Expert Systems with Applications, 29, 2, pp. 431-436, (2005)",null,null,"Faculty of Transport and Aviation Engineering, Silesian University of Technology",{"$nulls":5},2093324.0,null,null,null,"English","Sci. J. Sil. Univ. Technol., Series Transp.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85137183280"]
["Chen Y.; Lan H.; Wang C.; Jia X.","Chen, Youhua (57211520159); Lan, Hongjie (25930863400); Wang, Chuan (57212467431); Jia, Xiaoqiong (57205576895)","57211520159; 25930863400; 57212467431; 57205576895","Integrated Online Order Picking and Vehicle Routing of Food Cold Chain with Demand Surge",2022.0,"Mathematical Problems in Engineering",2022.0,null,4485376.0,null,null,null,4.0,"10.1155/2022/4485376","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85134519949&doi=10.1155%2f2022%2f4485376&partnerID=40&md5=21a5565744db2ed734b68701421a2c4f","Beijing Jiaotong University, Haidian District, Beijing, 100044, China; China Mobile Group Beijing Co., Ltd, Xicheng District, Beijing, 100032, China","Chen Y., Beijing Jiaotong University, Haidian District, Beijing, 100044, China; Lan H., Beijing Jiaotong University, Haidian District, Beijing, 100044, China; Wang C., Beijing Jiaotong University, Haidian District, Beijing, 100044, China; Jia X., China Mobile Group Beijing Co., Ltd, Xicheng District, Beijing, 100032, China","This paper focuses on the effect of demand surge on the food cold chain, where orders arrive online. The demand surge has successively affected the order batching, batch sequencing, and route planning, compared to regular demand. This research studies the integrated optimization of food cold chain order picking and vehicle routing of online orders, where mixed integer programming model is formulated to minimize time-consuming and cost. We firstly use K-means++ algorithm to cluster all customers, and then an online batch processing algorithm is designed in each region. Finally, a genetic algorithm is used to complete the joint optimization of the picking and delivery. We use X enterprise's e-commerce platform as a case to collect actual operating data to verify the effectiveness of the model and algorithm. And comparing the analysis results between phased optimization and integrated optimization, reasonable suggestions are put forward for management decisions.  © 2022 Youhua Chen et al.",null,"Batch data processing; Genetic algorithms; Integer programming; K-means clustering; Chain ordering; Food cold chains; Integrated optimization; K-mean algorithms; Mixed integer programming model; Online orders; Order batching; Order-picking; Research studies; Route planning; Vehicle routing",{"$nulls":6},"Cui S., Chen H., Xu J., The research on disruption commodity distribution based on explosive demand of e-commerce promotion, Chinese Journal of Management Science, 21, 11, (2013); Ren T., Huang J., Liu Y., Zhu Y., He B., Research on the problems and countermeasures of regional logistics terminal distribution under explosive demnd of e-commerce promotion-basing on the analysis of consumers demands, Logistics Engineering and Management, 40, 9, (2018); Thompson S., Nunez M., Garfinkel R., Dean M.D., Or practice-efficient short-Term allocation and reallocation of patients to floors of a hospital during demand surges, Operations Research, 57, 2, pp. 261-273, (2009); Liu S., Hua G., Cheng T., Dong J., Unmanned vehicle distribution capacity sharing with demand surge under option contracts, Transportation Research Part e Logistics and Transportation Review, 149, 3, (2021); Roni M.S., Jin M., Eksioglu S.D., A hybrid inventory management system responding to regular demand and surge demand, Omega, 52, 4, pp. 190-200, (2015); Chen S.H., Jian-Hua J.I., Bao X., Capability management model based on capability sharing after the disruption, Science Technology and Engineering, 9, 1, pp. 63-69, (2009); Acimovic J., Graves S.C., Mitigating spillover in online retailing via replenishment, Manufacturing & Service Operations Management, 19, 3, pp. 419-436, (2017); Bao S., Research on Two-Echelon Routing Problem Based on Demand Blowout, (2019); Juliang Z., Shouting Z., Edwin C.T.C., Guowei H., Optimisation of online retailer pricing and carrier capacity expansion during low-price promotions with coordination of a decentralised supply chain, International Journal of Production Research, 57, 9, pp. 1-19, (2018); Li J., Liu X., Wu J., Yang F., Coordination of supply chain with a dominant retailer under demand disruptions, Mathematical Problems in Engineering, 2014, 8, pp. 1-10, (2014); Snyder L.V., Atan Z., Peng P., Rong Y., Schmitt A.J., Sinsoysal B., Or/ms models for supply chain disruptions: A review, IIE Transactions, 48, 2, pp. 89-109, (2016); Huang L., Song J.S., Tong J., Supply chain planning for random demand surges: Reactive capacity and safety stock, Manufacturing & Service Operations Management, 18, 4, pp. 509-524, (2016); Arora H., Raghu T.S., Vinze A., Resource allocation for demand surge mitigation during disaster response, Decision Support Systems, 50, 1, pp. 304-315, (2010); Bukchin Y., Khmelnitsky E., Yakuel P., Optimizing a dynamic order-picking process, European Journal of Operational Research, 219, 2, pp. 335-346, (2012); Henn S., Algorithms for on-line order batching in an order-picking warehouse, Computers & Operations Research, 39, 11, pp. 2549-2563, (2012); Giannikas V., Lu W., Robertson B., McFarlane D., An interventionist strategy for warehouse order picking: Evidence from two case studies, International Journal of Production Economics, 189, 7, pp. 63-76, (2017); Leung K.H., Lee C., Choy K.L., An integrated online pick-To-sort order batching approach for managing frequent arrivals of b2b e-commerce orders under both fixed and variable time-window batching-sciencedirect, Advanced Engineering Informatics, 45, (2017); Bent R.W., Van Hentenryck P., Scenario-based planning for partially dynamic vehicle routing with stochastic customers, Operations Research, 52, 6, pp. 977-987, (2004); Flatberg T., Hasle G., Kloster O., Nilssen E.J., Riise A., Dynamic and Stochastic Vehicle Routing in Practice, (2007); Hvattum L.M., Lokketangen A., Laporte G., Solving a dynamic and stochastic vehicle routing problem with a sample scenario hedging heuristic, Transportation Science, 40, 4, pp. 421-438, (2006); Ghiani G., Manni E., Quaranta A., Triki C., Anticipatory algorithms for same-day courier dispatching, Transportation Research Part e Logistics and Transportation Review, 45, 1, pp. 96-106, (2009); Ulmer M.W., Brinkmann J., Mattfeld D.C., Anticipatory Planning for Courier, Express and Parcel Services, (2015); Wang Z., Tingyu L.I., Yue C., Online schedulingfor the instant delivery problem in a city based on multiple prediction scenarios, Systems Engineering-Theory and Practice, 38, 12, pp. 3197-3211, (2018); Osvald A., Stirn L.Z., A vehicle routing algorithm for the distribution of fresh vegetables and similar perishable food, Journal of Food Engineering, 85, 2, pp. 285-295, (2008); Yao B., Chen C., Song X., Yang X., Fresh seafood delivery routing problem using an improved ant colony optimization, Annals of Operations Research, 273, 1-2, pp. 163-186, (2019); Sebastian, Henn, Integrated Production and Distribution Operations: Taxonomy, Models, and Review, (2004); Henn S., Henn, Order batching and sequencing for the minimization of the total tardiness in picker-To-part warehouses, Flexible Services and Manufacturing Journal, 27, 1, pp. 86-114, (2015); Cheng C.Y., Chen Y.Y., Chen T.L., Jung-Woon Yoo J., Using a hybrid approach based on the particle swarm optimization and ant colony optimization to solve a joint order batching and picker routing problem, International Journal of Production Economics, 170, 10, pp. 805-814, (2015); Schubert D., Scholz A., Wascher G., Integrated order picking and vehicle routing with due dates, Spectrum, 40, 4, pp. 1109-1139, (2018); Moons S., Braekers K., Ramaekers K., Caris A., Arda Y., The value of integrating order picking and vehicle routing decisions in a b2c e-commerce environment, International Journal of Production Research, 57, 20, pp. 6405-6423, (2019); Li J., Huang R., Dai J.B., Dai B., Joint optimisation of order batching and picker routing in the online retailer's warehouse in China, International Journal of Production Research, 55, 2, pp. 447-461, (2016); Zhang J., Liu F., Tang J., Li Y., The online integrated order picking and delivery considering pickers' learning effects for an o2o community supermarket, Transportation Research Part E: Logistics and Transportation Review, 123, 3, pp. 180-199, (2019); Zhang J., Zhang X., Zhang Y., A study on online scheduling problem of integrated order picking and delivery with multizone vehicle routing method for online-To-offline supermarket, Mathematical Problems in Engineering, 2021, pp. 1-9, (2021); Kuhn H., Schubert D., Holzapfel A., Integrated order batching and vehicle routing operations in grocery retail-a general adaptive large neighborhood search algorithm-sciencedirect, European Journal of Operational Research, 294, (2021); Devapriya P., Ferrell W., Geismar N., Integrated production and distribution scheduling with a perishable product, European Journal of Operational Research, 259, 3, pp. 906-916, (2017); Ju Hai J.I., Zhang X., Optimization model and algorithm of the vehicle routing problem of perishable food with pickup and delivery, Chinese Journal of Systems Science, 27, 1, pp. 130-135, (2019); Li L., Yang Y., Qin G., Optimization of integrated inventory routing problem for cold chain logistics considering carbon footprint and carbon regulations, Sustainability, 11, 17, (2019)","Y. Chen; Beijing Jiaotong University, Beijing, Haidian District, 100044, China; email: 17113142@bjtu.edu.cn",null,"Hindawi Limited",{"$nulls":5},"1024123X",null,null,null,"English","Math. Probl. Eng.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85134519949"]
["Zhou K.; Zhao W.; Zhou H.","Zhou, Kai (57222088839); Zhao, Weibin (57325540800); Zhou, Huiyan (57326112100)","57222088839; 57325540800; 57326112100","Research on model mechanism of B2B transaction based on delivery means of blockchain",2022.0,"International Journal of Technology, Policy and Management",22.0,"2024-02-01",null,114.0,140.0,26.0,0.0,"10.1504/IJTPM.2022.122560","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85130305572&doi=10.1504%2fIJTPM.2022.122560&partnerID=40&md5=7e2bf29e34c4e5fa05a5fdc468781c97","School of Cyber Security, Changchun University, Changchun, 130022, China","Zhou K., School of Cyber Security, Changchun University, Changchun, 130022, China; Zhao W., School of Cyber Security, Changchun University, Changchun, 130022, China; Zhou H., School of Cyber Security, Changchun University, Changchun, 130022, China","The security of customer information, business information and payment information pool is a problem in the process of transaction payment under traditional B2B e-commerce mode. To solve this security problem, a B2B e-commerce transaction payment mode based on block chain technology is constructed. This study integrates the technical characteristics of decentralisation in blockchain algorithm, point-to-point distributed computing network, distributed storage of data and security and credibility of data encryption into the system architecture of B2B e-commerce transaction payment, and explores the feasibility of blockchain payment model architecture from the perspective of demand and supply of system products, then a secure payment model mechanism based on blockchain technology is constructed, which provides an effective model architecture solution to solve the problems of payment security and information security in the traditional B2B e-commerce transaction payment system. Copyright © 2022 Inderscience Enterprises Ltd.","B2B e-commerce business model; blockchain technology; demand; information security; payment security; supply","Blockchain; Computer architecture; Digital storage; Electronic commerce; Network architecture; Network security; B2B e-commerce; B2B e-commerce business model; Block-chain; Blockchain technology; Business models; Demand; E-commerce business; E-commerce transactions; Payment security; Supply; Cryptography",{"$nulls":4},"Digital Economy enabling Jilin Province; Humanities and Social Science Research Project of Education Department of Jilin Province; Social Science Research Planning Project of Ed ucation Department of Jilin Province, (JJKH20210638SK); Social Science Research Planning Project of Education Department of Jilin Province","Funding text 1: This work is supported by Humanities and Social Science Research Project of Education Department of Jilin Province 2022 (Research on “One Master and Six Pairs” high-quality development strategy of Digital Economy enabling Jilin Province), and Social Science Research Planning Project of Education Department of Jilin Province (JJKH20210638SK) Research on the security of network economy in the process of urban rural integration in the new era.; Funding text 2: This work is supported by Humanities and Social Science Research Project of Education Department of Jilin Province 2022 (Research on “One Master and Six Pairs” high-quality development strategy of Digital Economy enabling Jilin Province), and Social Science Research Planning Project of Ed ucation Department of Jilin Province (JJKH20210638SK) Research on the security of network economy in the process of urban rural integration in the new era.","Ahn J., Park M., Shin H., Paek J., A model for deriving trust and reputation on blockchain-based e-payment system, Applied Sciences, 9, 24, pp. 1431-1436, (2019); Cao L., Blockchain smart contract and thinking on the development of banking business, Financial Technology Time, 29, pp. 40-43, (2021); Chin S-H., Lu C., Ho P-T., Shiao Y-F., Wu T-J., Commodity anti-counterfeiting decision in e-commerce trade based on machine learning and internet of things, Computer Standards and Interfaces, 76, pp. 1-7, (2021); Cui F., Hu H., Xie Y., An intelligent optimization method of E-commerce product marketing, Neural Computing and Applications, pp. 1-14, (2021); Du Y., Xu J., Zhong L., Hou Y., Shen J.A., Visualization of multi-dimensional characteristics of network public opinion situation and emotion – taking the epidemic situation of Cowid-19 as an example, Journal of Earth Information Science, 23, 2, pp. 1-13, (2021); Haidong Z., Zhang J., Zhang S., Zheng W., Zhang C., Study on spatial imbalance and determinants of E-commerce development in Zhejiang, China, Mathematical Problems in Engineering, pp. 1-12, (2021); He C., Discussion on the application of computer network security technology in E-commerce, Digital Space, 12, pp. 255-256, (2020); Huang W., Zhou W., Luo F., Coopetition between B2C E-commerce companies: price competition and logistics service cooperation, Journal of Systems Science and Systems Engineering, 29, 6, pp. 730-749, (2020); Jin N., Yan J., Research on ‘Mobile short video + E-commerce’ marketing mode, Chinese Market, 36, pp. 122-128, (2020); Li D., Zhang E., Wang L., Research on the development status and prospects of blockchain technology, China Management Information Technology, 23, 20, pp. 181-182, (2020); Li M., Shen L., Huang G.Q., Blockchain-enabled workflow operating system for logistics resources sharing in E-commerce logistics real estate service, Computers and Industrial Engineering, 135, pp. 950-969, (2019); Li X., Research on financial risk of E-commerce enterprises under mobile payment mode, China Logistics and Procurement, pp. 51-52, (2020); Liang X., Zhang H., An analysis of the application mode of blockchain technology in international payment, Friends of Accounting, pp. 115-117, (2021); Makhdoom I., Zhou I., Abolhasan M., Lipman J., Ni W., PrivySharing: A blockchain-based framework for privacy-preserving and secure data sharing in smart cities, Computers and Security, 88, pp. 1-24, (2020); Marjaneh J.L., Wang S., Urbanski M., Egorova M., Sustainable B2B E-commerce and blockchain-based supply chain finance, Sustainability, 12, 10, pp. 1-14, (2020); Wang S., Explore mobile E-commerce mode supported by cloud computing, Shang Xun, pp. 152-153, (2021); Wang Y., Li Y., Li N., Research on network culture information security communication mechanism and path based on blockchain technology, Information Science, 38, 10, pp. 35-40, (2020); Xie J., Wang L., Collaborative innovation of E-commerce enterprises based on FPGA and convolutional neural network, Microprocessors and Microsystems, 80, pp. 1-6, (2021); Xu G., Yi S., Research on the integrated development path of blockchain technology and modern circulation industry – based on suggestions for the 14th five-year plan, Price: Theory and Practice, pp. 21-26, (2020); Xu S., Chen J., Wu M., Zhao C., E-commerce supply chain process optimization based on whole-process sharing of internet of things identification technology, Computer Modeling in Engineering and Sciences, 126, 2, pp. 843-854, (2021); Zeng Y., Zhao Y., Liu K., Research on the development path of digital currency based on the background of blockchain technology, Market Modernization, 24, pp. 155-160, (2020)","K. Zhou; School of Cyber Security, Changchun University, Changchun, 130022, China; email: zhouk82@ccu.edu.cn",null,"Inderscience Publishers",{"$nulls":5},1.4684322E7,null,null,null,"English","Int. J. Technol. Policy Manage.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85130305572"]
["Campisi T.; Severino A.; Al-Rashid M.A.","Campisi, Tiziana (56866098200); Severino, Alessandro (57200646754); Al-Rashid, Muhammad Ahmad (57208389593)","56866098200; 57200646754; 57208389593","Introducing the Benefits of Autonomous Vehicles to Logistics During the COVID-19 Era",2022.0,"International Review of Civil Engineering",13.0,2.0,null,83.0,90.0,7.0,2.0,"10.15866/irece.v13i2.21161","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85131574603&doi=10.15866%2firece.v13i2.21161&partnerID=40&md5=6981053683b558476c4b76604588f212","Faculty of Engineering and Architecture, Kore University of Enna, Cittadella Universitaria, Enna, 94100, Italy; Department of Civil Engineering and Architecture, University of Catania, Catania, 95123, Italy; Department of City and Regional Planning, School of Architecture and Planning, University of Management and Technology, Lahore, 54770, Pakistan","Campisi T., Faculty of Engineering and Architecture, Kore University of Enna, Cittadella Universitaria, Enna, 94100, Italy; Severino A., Department of Civil Engineering and Architecture, University of Catania, Catania, 95123, Italy; Al-Rashid M.A., Department of City and Regional Planning, School of Architecture and Planning, University of Management and Technology, Lahore, 54770, Pakistan","– Recent years have seen an evolution in automation and logistics technologies, especially with the recent growth of the e-commerce industry. The current COVID-19 pandemic and the spread of smart cities have made it necessary to rethink this sector regarding sustainability and resilience. There is a widespread need to redesign some of the steps that lead goods to our homes, encouraging decarbonization policies, reducing contacts between people for possible contagions and at the same time ensuring that products arrive intact and on time. Currently, there is only limited research on the impact of autonomous vehicles on the logistics industry. This paper reviews the literature by analyzing which autonomous systems have been integrated into long, medium, and short-distance logistics. It is clear that the adoption of Autonomous Vehicles (AVs) stimulates possible innovation in mobility management and transportation logistics and provides the impetus for many unexplored research opportunities. The research investigates the main theoretical and practical benefits related to the use of autonomous vehicles in logistics, differentiating four areas of action (i.e., indoor and outdoor environments, long-distance and first and last-mile logistics). © 2022 Praise Worthy Prize S.r.l.-All rights reserved.","Autonomous Vehicle; CO2 Emissions; COVID-19; First and Last Mile; Logistics; Long-haul Trucking",{"$nulls":7},"Torrisi V., Campisi T., Inturri G., Ignaccolo M., Tesoriere G., Continue to share? An overview on italian travel behavior before and after the COVID-19 lockdown, AIP Conference Proceedings, 2343, 1, (2021); Ortego J., Andara R., Navas L. M., Vasquez C. L., Ramirez-Pisco R., Impact of the Covid-19 Pandemic on Traffic Congestion in Latin American Cities: An Updated Five-Month Study, Cham, 2021: Springer International Publishing, pp. 216-229; Shanker R., Jonas A., Devitt S., Huberty K., Flannery S., Greene W., Swinburne B., Locraft G., Wood A., Weiss K., Moore J., Autonomous cars: Self-driving the new auto industry paradigm, Morgan Stanley blue paper, pp. 1-109, (2013); Arena F., Pau G., Severino A., An Overview on the Current Status and Future Perspectives of Smart Cars, Infrastructures, 5, 7, (2020); Moraci F., Errigo M. F., Fazia C., Campisi T., Castelli F., Cities under Pressure: Strategies and Tools to Face Climate Change and Pandemic, Sustainability, 12, 18, (2020); Campisi T., Basbas S., Skoufas A., Akgun N., Ticali D., Tesoriere G., The Impact of COVID-19 Pandemic on the Resilience of Sustainable Mobility in Sicily, Sustainability, 12, 21, (2020); Severino A., Curto S., Barberi S., Arena F., Pau G., Autonomous Vehicles: An Analysis Both on Their Distinctiveness and the Potential Impact on Urban Transport Systems, Applied Sciences, 11, 8, (2021); Liu W., Liang Y., Bao X., Qin J., Lim M. K., China's logistics development trends in the post COVID-19 era, International Journal of Logistics Research and Applications, pp. 1-12, (2020); Liu T., hai Liao Q., Gan L., Ma F., Cheng J., Xie X., Wang Z., Chen Y., Zhu Y., Zhang S., Chen Z., The Role of the Hercules Autonomous Vehicle During the COVID-19 Pandemic: An Autonomous Logistic Vehicle for Contactless Goods Transportation, IEEE Robotics & Automation Magazine, 28, 1, pp. 48-58, (2021); Toapanta A., Zea D., Tasiguano C., Anangano G., Prado A., Camacho O., A review of autonomous vehicle technology and its use for the COVID-19 contingency, Ciencia E Ingenieria, pp. 43-51, (2021); Campisi T., Severino A., Al-Rashid M. A., Pau G., The Development of the Smart Cities in the Connected and Autonomous Vehicles (CAVs) Era: From Mobility Patterns to Scaling in Cities, Infrastructures, 6, 7, (2021); Seuwou P., Banissi E., Ubakanma G., The Future of Mobility with Connected and Autonomous Vehicles in Smart Cities, Digital Twin Technologies and Smart Cities, pp. 37-52, (2020); Flamig H., Autonomous Vehicles and Autonomous Driving in Freight Transport, Autonomous Driving: Technical, Legal and Social Aspects, pp. 365-385, (2016); Ohnemus M., Perl A., Shared autonomous vehicles: Catalyst of new mobility for the last mile?, Built Environment, 42, 4, pp. 589-602, (2016); Christine L.-C., Automated Guided Vehicles: Behind the Swift Business of a Heavy Industry; Van Meldert B., De Boeck L., Introducing autonomous vehicles in logistics: a review from a broad perspective, (2016); Piekenbrock P., Autonomous vehicles in goods transport, (2014); De La Torre G., Rad P., Choo K.-K. R., Driverless vehicle security: Challenges and future research opportunities, Future Generation Computer Systems, 108, pp. 1092-1111, (2020); Stanek D., Milam R. T., Huang E., Wang Y. A., Measuring autonomous vehicle impacts on congested networks using simulation, (2018); Metz D., Developing Policy for Urban Autonomous Vehicles: Impact on Congestion, Urban Science, 2, 2, (2018); Fagnant D. J., Kockelman K., Preparing a nation for autonomous vehicles: opportunities, barriers and policy recommendations, Transportation Research Part A: Policy and Practice, 77, pp. 167-181, (2015); Tsakalidis A., Gkoumas K., Pekar F., Digital Transformation Supporting Transport Decarbonisation: Technological Developments in EU-Funded Research and Innovation, Sustainability, 12, 9, (2020); Canale A., Tesoriere G., Campisi T., The MAAS development as a mobility solution based on the individual needs of transport users, AIP Conference Proceedings, 2186, 1, (2019); Abdelrhim M., Elsayed A., The Effect of COVID-19 Spread on the e-commerce market: The case of the 5 largest e-commerce companies in the world, (2020); Gruzauskas V., Baskutis S., Navickas V., Minimizing the trade-off between sustainability and cost effective performance by using autonomous vehicles, Journal of Cleaner Production, 184, pp. 709-717, (2018); Buchegger A., Lassnig K., Loigge S., Muhlbacher C., Steinbauer G., An Autonomous Vehicle for Parcel Delivery in Urban Areas, 2018 21st International Conference on Intelligent Transportation Systems (ITSC), pp. 2961-2967, (2018); Allie C., Rio Tinto talks up autonomous trucks, innovation cred; Carlo H. J., Vis I. F. A., Roodbergen K. J., Transport operations in container terminals: Literature overview, trends, research directions and classification scheme, European Journal of Operational Research, 236, 1, pp. 1-13, (2014); Vivaldini K. C. T., Tamashiro G., Martins Junior J., Becker M., Communication Infrastructure in the Centralized Management System for Intelligent Warehouses, pp. 127-136, (2013); Preliminary Statement of Policy Concerning Automated Vehicles, (2013); Moller A., Kranz M., Huitl R., Diewald S., Roalter L., A mobile indoor navigation system interface adapted to vision-based localization, Proceedings of the 11th International Conference on Mobile and Ubiquitous Multimedia, (2012); Julius Fusic S., Kanagaraj G., Hariharan K., Autonomous Vehicle in Industrial Logistics Application: Case Study, Industry 4.0 and Hyper-Customized Smart Manufacturing Supply Chains, pp. 182-208, (2019); Preparing for the Future of Transportation: Automated Vehicles 3.0 (AV 3.0), (2018); Logistics Trend Radar; Gao P., Kaas H.-W., Mohr D., Wee D., Automotive revolution–perspective towards 2030: How the convergence of disruptive technology-driven trends could transform the auto industry, (2016); Grahle A., Song Y. W., Bruske K., Bender B., Gohlich D., Autonomous shuttles for urban mobility on demand applications-Ecosystem dependent requirement elicitation, Proceedings of the Design Society: DESIGN Conference, 1, pp. 887-896, (2020); Bagloee S. A., Tavana M., Asadi M., Oliver T., Autonomous vehicles: challenges, opportunities, and future implications for transportation policies, Journal of Modern Transportation, 24, 4, pp. 284-303, (2016); Poczter S. L., Jankovic L. M., The google car: driving toward a better future?, Journal of Business Case Studies (JBCS), 10, 1, pp. 7-14, (2014); Morando M. M., Tian Q., Truong L. T., Vu H. L., Studying the Safety Impact of Autonomous Vehicles Using Simulation-Based Surrogate Safety Measures, Journal of Advanced Transportation, (2018); VISSIM 9 User Manual; Taniguchi E., Thompson R. G., Yamada T., Visions for City Logistics, Logistics Systems for Sustainable Cities, pp. 1-16, (2004)",null,null,"Praise Worthy Prize S.r.l",{"$nulls":5},2.0369913E7,null,null,null,"English","Int. Rev. Civ. Eng.","Article","Final",null,"Scopus","2-s2.0-85131574603"]
["Kapadia M.; Melachrinoudis E.; Zaarour N.","Kapadia, Moulik (57815749300); Melachrinoudis, Emanuel (7004681176); Zaarour, Nizar (53869755900)","57815749300; 7004681176; 53869755900","Optimal collection policies for returned products in the reverse supply chain",2022.0,"International Journal of Logistics Systems and Management",42.0,2.0,null,240.0,272.0,32.0,0.0,"10.1504/IJLSM.2022.124155","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85134739863&doi=10.1504%2fIJLSM.2022.124155&partnerID=40&md5=0d133c0e98b5ce4371cef220eb0a979b","Department of Mechanical and Industrial Engineering, Snell Engineering Center, Northeastern University, Boston, 02115, MA, United States; D’Amore-Mckim School of Business, Northeastern University, Boston, 02115, MA, United States","Kapadia M., Department of Mechanical and Industrial Engineering, Snell Engineering Center, Northeastern University, Boston, 02115, MA, United States; Melachrinoudis E., Department of Mechanical and Industrial Engineering, Snell Engineering Center, Northeastern University, Boston, 02115, MA, United States; Zaarour N., D’Amore-Mckim School of Business, Northeastern University, Boston, 02115, MA, United States","The emergence of e-commerce and increasing customer service expectations have pushed a growing number of firms to adopt liberal return policies, this results however in skyrocketing return delivery costs. To reduce this impact of product returns on a firm’s baseline, we develop and compare different collection models by leveraging economies of scale and optimising the collection period across multiple initial collection points (ICPs) in a three-echelon network before transshipping the returned products to a centralised return centre (CRC). Collection policies are developed for the case of multiple ICPs and a single type of product: 1) individual shipment policy; 2) combined shipment policy; 3) hybrid shipment policy. Mathematical models are developed for calculating the combined inventory and transportation costs for these policies, and an optimisation approach is designed to minimise the number of computations required to reach the optimal collection period. The results are then presented with an experimental dataset. Copyright © 2022 Inderscience Enterprises Ltd.","closed-loop supply chain; multiple collection points; operations research; optimisation; product returns; reverse logistics; reverse supply chain",{"$nulls":7},"Agrawal S., Singh R.K., Murtaza Q., A literature review and perspectives in reverse logistics, Resources, Conservation and Recycling, 97, 1, pp. 76-92, (2015); Al-Anzi F.S., Allahverdi A., A self-adaptive differential evolution heuristic for two-stage assembly scheduling problem to minimize maximum lateness with setup times, European Journal of Operational Research, 182, 1, pp. 80-94, (2007); Consumer Returns in the Retail Industry Report, (2017); Barros A.I., Dekker R., Scholten V., A two-level network for recycling sand: a case study, European Journal of Operational Research, 110, 2, pp. 199-214, (1998); Budijati S.M., Subagyo B., Wibisono M.A., Masruroh N.A., The influence of environmental attitude on consumers’ intentions to participate in a take back program, International Journal of Logistics Systems and Management, 26, 4, pp. 421-452, (2017); Caliskan A., Kalkan M., Ozturkoglu Y., City logistics: problems and recovery proposals, International Journal of Logistics Systems and Management, 26, 2, pp. 145-162, (2017); Carter C.R., Ellram L.M., Reverse logistics: a review of the literature and framework for future investigation, Journal of Business Logistics, 19, 1, (1998); Chanintrakul P., Coronado Mondragon A.E., Lalwani C., Wong C.Y., Reverse logistics network design: a state-of-the-art literature review, International Journal of Business Performance and Supply Chain Modelling, 1, 1, pp. 61-81, (2009); Coccola M., Mendez C.A., Dondo R.G., A branch-and-price approach to evaluate the role of cross-docking operations in consolidated supply chains, Computers & Chemical Engineering, 80, 1, pp. 15-29, (2015); Del Castillo E., Cochran J.K., Optimal short horizon distribution operations in reusable container systems, Journal of the Operational Research Society, 47, 1, pp. 48-60, (1996); Diabat A., Kannan D., Kaliyan M., Svetinovic D., An optimization model for product returns using genetic algorithms and artificial immune system, Resources, Conservation and Recycling, 74, 1, pp. 156-169, (2013); Du F., Evans G.W., A bi-objective reverse logistics network analysis for post-sale service, Computers & Operations Research, 35, 8, pp. 2617-2634, (2008); Ellili W., Samet M., Kachouri A., Logistics reverse chain optimization based on genetic algorithms, International Journal of Computer Science and Information Security, 14, 7, (2016); Fleischmann M., Kuik R., On optimal inventory control with independent stochastic item returns, European Journal of Operational Research, 151, 1, pp. 25-37, (2003); Fleischmann M., Krikke H.R., Dekker R., Flapper S.D.P., A characterisation of logistics networks for product recovery, Omega, 28, 6, pp. 653-666, (2000); Gecker R., Vigoroso M.W., Industry Best Practices in Reverse Logistics–Benchmarking the Success Strategies of top Industry Performers, (2007); Ghezavati V., Nia N.S., Development of an optimization model for product returns using genetic algorithms and simulated annealing, Soft Computing, 19, 11, pp. 3055-3069, (2015); Gomes I.V.S., Rosa R.D.A., Musso C.K., Cinelli L.V., Rodrigues V.O., Silva D.S., Planning the reverse logistic for recyclable solid waste by a mathematical model and a simulated annealing metaheuristic, International Journal of Logistics Systems and Management, 26, 2, pp. 181-202, (2017); 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Jayaraman V., Patterson R.A., Rolland E., The design of reverse distribution networks: models and solution procedures, European Journal of Operational Research, 150, 1, pp. 128-149, (2003); Kaboudani Y., Ghodsypour S.H., Kia H., Shahmardan A., Vehicle routing and scheduling in cross docks with forward and reverse logistics, Operational Research, pp. 1-34, (2018); Kaebernick H., Kara S., Sun M., Sustainable product development and manufacturing by considering environmental requirements, Robotics and Computer-Integrated Manufacturing, 19, 6, pp. 461-468, (2003); Kannan D., Diabat A., Alrefaei M., Govindan K., Yong G., A carbon footprint based reverse logistics network design model, Resources, Conservation and Recycling, 67, 1, pp. 75-79, (2012); Kannan G., Haq A.N., Devika M., Analysis of closed loop supply chain using genetic algorithm and particle swarm optimisation, International Journal of Production Research, 47, 5, pp. 1175-1200, (2009); Kannan G., Pokharel S., Kumar P.S., A hybrid approach using ISM and fuzzy TOPSIS for the selection of reverse logistics provider, Resources, Conservation and Recycling, 54, 1, pp. 28-36, (2009); Kheirkhah A., Rezaei S., Using cross-docking operations in a reverse logistics network design: a new approach, Production Engineering, 10, 2, pp. 175-184, (2016); Khorshidian H., Shirazi M.A., Ghomi S.F., An intelligent truck scheduling and transportation planning optimization model for product portfolio in a cross-dock, Journal of Intelligent Manufacturing, 30, 1, pp. 163-184, (2016); Kroon L., Vrijens G., Returnable containers: an example of reverse logistics, International Journal of Physical Distribution & Logistics Management, 25, 2, pp. 56-68, (1995); Kwak M., Kim H., Design for life-cycle profit with simultaneous consideration of initial manufacturing and end-of-life remanufacturing, Engineering Optimization, 47, 1, pp. 18-35, (2015); Lee D.H., Dong M., Dynamic network design for reverse logistics operations under uncertainty, Transportation Research Part E: Logistics and Transportation Review, 45, 1, pp. 61-71, (2009); Li J., Wang J., Hu Z., A reverse logistics network design method using genetic algorithm, 2006 6th World Congress on Intelligent Control and Automation, IEEE, 2, pp. 7287-7291, (2006); 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Zaarour N., Melachrinoudis E., Solomon M.M., Min H., The optimal determination of the collection period for returned products in the sustainable supply chain, International Journal of Logistics Research and Applications, 17, 1, pp. 35-45, (2014); Zhou G., Min H., Designing a closed-loop supply chain with stochastic product returns: a genetic algorithm approach, International Journal of Logistics Systems and Management, 9, 4, pp. 397-418, (2011)","M. Kapadia; Department of Mechanical and Industrial Engineering, Snell Engineering Center, Northeastern University, Boston, 02115, United States; email: kapadia.m@husky.neu.edu",null,"Inderscience Publishers",{"$nulls":5},1.7427967E7,null,null,null,"English","Int. J. Logist. Syst. Manage.","Article","Final",null,"Scopus","2-s2.0-85134739863"]
["Shen J.","Shen, Jianjun (57934082000)",5.7934082E10,"Research on the International Trade Performance Evaluation of Cross-Border e-Commerce Based on the Deep Neural Network Model",2022.0,"Journal of Sensors",2022.0,null,3006907.0,null,null,null,1.0,"10.1155/2022/3006907","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85140218862&doi=10.1155%2f2022%2f3006907&partnerID=40&md5=11ff97dd2793132b2d7a82ed5ce9acdb","Business School of Sanda University, Shanghai, 201209, China","Shen J., Business School of Sanda University, Shanghai, 201209, China","The rapid development of e-commerce international trade has driven the rapid growth of the economic system of international trade enterprises. This also means that industry competition is gradually intensifying, which also makes performance evaluation the key to cross-border e-commerce international trade. At present, my country's research on the performance evaluation of cross-border e-commerce international trade is in a blank state. Therefore, this paper takes the international trade performance evaluation of cross-border e-commerce as the research object and, based on the deep neural network model, develops a cross-border international trade performance evaluation model, changes trade strategies, and improves trade performance. This paper first analyzes various neural network models, such as artificial neural network, \"BP\"neuron model, and LSTM neural network. This paper summarizes a deep neural network model that is conducive to the development of cross-border e-commerce and points out the problems in the current performance evaluation of cross-border e-commerce international trade: The e-commerce market supervision system is not perfect; the second is the inconsistent evaluation indicators; the third is the evaluation system. There are some differences with the actual. Finally, this paper puts forward relevant suggestions for the performance evaluation of cross-border e-commerce international trade and points out the advantages and disadvantages of various neural networks, as well as their roles in cross-border e-commerce performance evaluation, and compares these neural networks through experiments. Experiments show that among these neural network models, the deep neural network model is the best and has the highest accuracy and stability in e-commerce trade performance evaluation. In the later stage, we will improve the global logistics system, strengthen the application of big data technology, and improve the overall performance of global operations. First, a set of indicators is designed to evaluate the performance of e-commerce systems, using the enterprise key factor model concept. In addition, this evaluation method is different from the commonly used expert evaluation method and physical evaluation method in evaluating the construction quality, cost, education and growth ability, and performance level of the international business system of cross-border e-commerce.  © 2022 Jianjun Shen.",null,"Competition; Deep neural networks; Electronic commerce; Long short-term memory; Neural network models; Quality control; Cross-border; E- commerces; Economic system; Evaluation methods; Neural network model; Neural-networks; Performance; Performances evaluation; Rapid growth; Trade enterprise; International trade",{"$nulls":6},"Choie J., Jin W.M., Han J.H., Development of a deep neural network model for estimating joint location of occupant indoor activities for providing thermal comfort, Energies, 14, 3, pp. 696-786, (2021); Wu J., Mao H., Sun Q., Analysis on dynamic mold of spindle of internal grinder based on BP neural network, Journal of Nanjing University of Aeronautics & Astronautics, 9, 6, pp. 47-75, (2003); Giovannangeli L., Lalanne F., Auber D., Deep Neural Network for DrawiNg Networks, DNN2, 2, 4, (2021); Gomez-Herrera E., Martens B., Turlea G., The drivers and impediments for cross-border e-commerce in the EU, Information Economics and Policy, 28, 1, pp. 83-96, (2014); Martens B., What does economic research tell us about cross-border E-commerce in the EU digital single market, Jrc Working Papers on Digital Economy, 4, 5, pp. 635-691, (2013); Fang J.I., Zhang X., University C., Innovation and development trend of cross-border E-commerce logistics, China Business and Market, 9, 5, pp. 23-78, (2015); Krugman P.R., Increasing returns, monopolistic competition, and international trade, Journal of International Economics, 9, 4, pp. 469-479, (1979); Ethier W.J., National and international returns to scale in the modern theory of international trade, Journal of Yanbian University, 72, 3, pp. 389-405, (1982); Ba Ier S.L., Bergstrand J.H., Do free trade agreements actually increase members' international trade, Journal of International Economics, 71, 1, pp. 72-95, (2005); Dixit A.K., Norman V.D., Theory of International Trade, 8, 3, (1980); Peng G.F., Value orientation is the deep structure of the performance evaluation system of local governments, Chinese Public Administration, 5, 1, pp. 26-38, (2004); Cao Q., Hoffman J.J., A case study approach for developing a project performance evaluation system, International Journal of Project Management, 29, 2, pp. 155-164, (2011); Iregren A., Gamberale F., Kjellberg A., SPES: A psychological test system to diagnose environmental hazards. Swedish performance evaluation system, Neurotoxicology and Teratology, 18, 4, pp. 485-491, (1996); Nuti S., Seghieri C., Vainieri M., Assessing the effectiveness of a performance evaluation system in the public health care sector: Some novel evidence from the Tuscany region experience, Journal of Management & Governance, 17, 1, pp. 59-69, (2013)","J. Shen; Business School of Sanda University, Shanghai, 201209, China; email: jjshen@sandau.edu.cn",null,"Hindawi Limited",{"$nulls":5},"1687725X",null,null,null,"English","J. Sensors","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85140218862"]
["Koshta N.; Devi Y.; Chauhan C.","Koshta, Nitin (57218632464); Devi, Yashoda (57223217370); Chauhan, Chetna (57204944385)","57218632464; 57223217370; 57204944385","Evaluating Barriers to the Adoption of Delivery Drones in Rural Healthcare Supply Chains: Preparing the Healthcare System for the Future",2022.0,"IEEE Transactions on Engineering Management",null,null,null,1.0,13.0,12.0,8.0,"10.1109/TEM.2022.3210121","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85139871549&doi=10.1109%2fTEM.2022.3210121&partnerID=40&md5=685d73c721108cab9c145873a28a554b","Operations Management, Alliance University Alliance School of Business, Bangalore, India; Operations Management, Amrita Vishwa Vidyapeetham Amrita School of Business - Campus Bengaluru, Bengaluru, India; Universidad de los Andes, Bogota, CO, USA","Koshta N., Operations Management, Alliance University Alliance School of Business, Bangalore, India; Devi Y., Operations Management, Amrita Vishwa Vidyapeetham Amrita School of Business - Campus Bengaluru, Bengaluru, India; Chauhan C., Universidad de los Andes, Bogota, CO, USA","Emerging technologies, such as delivery drones have enormous potential to revolutionize the rural healthcare supply chain (RHSC) and assist the countries in achieving sustainable development goal 3: good health and well-being. The advantages of delivery drones include faster delivery, high responsiveness, and a lack of dependence on road infrastructure. Given these advantages, prior literature on drone delivery has extensively explored their applicability in last-mile delivery from the e-commerce or retailer&#x0027;s perspective. However, their applicability in RHSC from an academic as well as practical perspective is still at a nascent stage. The present study fills this gap by examining the barriers inhibiting the adoption of delivery drones in RHSC using the Grey Decision-Making Trial and Evaluation Laboratory technique. The results suggest that &#x201C;lack of government regulations&#x201D; is the most critical barrier. The study findings indicate that seven barriers are causal, and six are the effect barriers. &#x201C;Limited load carrying capacity,&#x201D; &#x201C;low flight range,&#x201D; and &#x201C;difficulty in flying in adverse weather conditions&#x201D; are the most prominent cause barriers. Moreover, &#x201C;lack of skilled manpower,&#x201D; &#x201C;limited accuracy of navigation system,&#x201D; and &#x201C;lack of leadership commitment&#x201D; are the most prominent effect barriers. We also perform sensitivity analysis to prove the robustness of the study output. The study results provide an in-depth understanding to the decision-makers and policymakers to help pave the way for the successful adoption of delivery drones in RHSC. IEEE","Barriers; Costs; COVID-19; delivery drones; Drones; Electronic commerce; Grey Decision-Making Trial and Evaluation Laboratory (grey-DEMATEL); Medical services; rural healthcare supply chain (RHSC); Supply chains; sustainable development goals (SDGs); Vaccines","Competition; Decision making; Drones; Electronic commerce; Health care; Laws and legislation; Navigation systems; Planning; Sensitivity analysis; Supply chains; Sustainable development; Barrier; Delivery drone; Emerging technologies; Gray decision-making trial and evaluation laboratory; Grey decision making; Healthcare systems; Medical services; Rural healthcare supply chain; Sustainable development goal; Well being; COVID-19",{"$nulls":9},"Institute of Electrical and Electronics Engineers Inc.",{"$nulls":5},189391.0,null,"IEEMA",null,"English","IEEE Trans Eng Manage","Article","Article in press",null,"Scopus","2-s2.0-85139871549"]
["Zhu Y.","Zhu, Yanjie (57909252800)",5.79092528E10,"Research on Real-Time Tracking Algorithm of E-Commerce Logistics Information Based on Blockchain Technology",2022.0,"Computational Intelligence and Neuroscience",2022.0,null,7006506.0,null,null,null,2.0,"10.1155/2022/7006506","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85138875921&doi=10.1155%2f2022%2f7006506&partnerID=40&md5=2c95726a3288f043a964b057a7dfdaef","School of Business, Xuchang University, Henan, Xuchang, 461000, China","Zhu Y., School of Business, Xuchang University, Henan, Xuchang, 461000, China","In order to solve the problem of distrust of a large number of nodes under the overly centralized and centralized information transfer mode, a research method of real-time tracking algorithm of e-commerce logistics information based on blockchain technology is proposed. The application background of blockchain technology in real-time tracking algorithm of e-commerce logistics information is firstly described. Also, the blockchain technology, logistics information real-time tracking algorithm, cryptography technology, blockchain consensus algorithm, blockchain application scenarios, and other related technologies are analyzed in detail. Then, the blockchain model of real-time tracking of e-commerce logistics information is established, and it is found that data will be stored on the chain only when more than 51% of the nodes in the distributed system confirm that the data are valid. Otherwise, the data on the chain cannot be affected. Finally, the model description and hypothesis of real-time tracking of e-commerce logistics information based on blockchain technology are verified to provide guarantee for improving real-time tracking of e-commerce logistics information. © 2022 Yanjie Zhu.",null,"Algorithms; Blockchain; Commerce; Computer Security; Technology; Electronic commerce; Tracking (position); Block-chain; Centralised; Centralized informations; E- commerces; Information transfers; Logistics information; Real time tracking; Research method; Tracking algorithm; Transfer modes; algorithm; commercial phenomena; computer security; technology; Blockchain",{"$nulls":6},"Ma X., Li W., Wu J., Li W., Wu J., Research on the operation of e-commerce enterprises based on blockchain technology and bilateral platforms, Wireless Communications and Mobile Computing, 2021, 1, (2021); Sharma K., Chaurasia B.K., Trust Based Location Finding Mechanism in VANET Using DST, pp. 763-766; Chen C., Li D., Research on the detection and tracking algorithm of moving object in image based on computer vision technology, Wireless Communications and Mobile Computing, 2021, 4, (2021); Su X., Liu Y., Choi C., A blockchain-based p2p transaction method and sensitive data encoding for e-commerce transactions, IEEE Consumer Electronics Magazine, 9, 4, pp. 56-66, (2020); Huang Y., Li X., Zhang G., The impact of technology perception and government support on e-commerce sales behavior of farmer cooperatives: Evidence from liaoning province, China, Sage Open, 11, 2, (2021); Li Y., Zhang Y., Wang L., Guan X., Research on potential ground risk regions of aircraft crashes based on ads-b flight tracking data and gis, Journal of Transportation Safety & Security, 14, 1, pp. 152-176, (2020); Jayakumar J., Nagaraj B., Chacko S., Ajay P., Conceptual implementation of artificial intelligent based E-mobility controller in smart city environment, Wireless Communications and Mobile Computing, 2021, pp. 1-8, (2021); Li X., Huang D., Research on value integration mode of agricultural e-commerce industry chain based on internet of things and blockchain technology, Wireless Communications and Mobile Computing, 2020, 5, (2020); Hongmei Z., A cross-border e-commerce approach based on blockchain technology, Mobile Information Systems, 2021, 4, (2021); Cao K., Xu Y., Wu Q., Wang J., Liu C., Optimal channel and logistics service selection strategies in the e-commerce context, Electronic Commerce Research and Applications, 48, (2021); Muller R., Proposal for an automated real-time vat collection mechanism in b2c ecommerce using blockchain technology, International VAT Monitor, 31, 3, (2020); Zhang H., Dong J., Prediction of repeat customers on e-commerce platform based on blockchain, Wireless Communications and Mobile Computing, 2020, 12, (2020); Ghanbary H., Fathian M., Combination swot-ahp analysis for using blockchain in e-commerce, Journal of Engineering and Applied Sciences, 3, 1, pp. 237-253, (2021); Huang R., Yan P., Yang X., Knowledge map visualization of technology hotspots and development trends in China's textile manufacturing industry, IET Collaborative Intelligent Manufacturing, 3, 3, pp. 243-251, (2021); Peng H., Yao Y., Zhu X., Zhou R., Zi X., Research on intelligent transportation and logistics tracking of long billet based on machine vision, Journal of Electronic Imaging, 31, (2022); Li S., Structure optimization of e-commerce platform based on artificial intelligence and blockchain technology, Wireless Communications and Mobile Computing, 2020, 12, (2020); Fan Y., Zhao L., Qin J., Jiang Z., Cao Z., Liu S., An Q., Research and verification on real-time interpolated timing algorithm based on waveform digitization, IEEE Transactions on Nuclear Science, 67, 10, pp. 2246-2254, (2020); Xu Z., Zhu G., Metawa N., Zhou Q., Machine learning based customer meta-combination brand equity analysis for marketing behavior evaluation, Information Processing & Management, 59, 1, (2022); Ding W., Wu L., Research on the selection of supply chain marketing models based on e-commerce service levels, Proceedings of Business and Economic Studies, 4, 4, pp. 197-207, (2021); Zuo J., Analysis of e-commerce characteristics based on edge algorithm and cox model, Wireless Communications and Mobile Computing, 2021, 6, (2021); Susilo R.D., Daniawan B., Wijaya A., Suwitno, The acceptance study of e-commerce customers based on tam, Bit-Tech, 3, 3, pp. 124-138, (2021); Liu J., Pan B., Zhang X., Li D., Mobile e-commerce information system based on industry cluster under edge computing, Mobile Information Systems, 2021, 1, (2021); Zhang S., Fu L., Chen R., Mei Y., Optimizing the cargo location assignment of retail e-commerce based on an artificial fish swarm algorithm, Mathematical Problems in Engineering, 2020, 5, (2020)","Y. Zhu; School of Business, Xuchang University, Xuchang, Henan, 461000, China; email: 12006023@xcu.edu.cn",null,"Hindawi Limited",{"$nulls":5},1.6875265E7,null,null,3.6238677E7,"English","Comput. Intell. Neurosci.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85138875921"]
["Zhao J.; Zhou L.; Wang F.; Liu H.; Yang J.","Zhao, Junhui (57226239181); Zhou, Li (57164286500); Wang, Fan (57427678200); Liu, Huwei (58842682800); Yang, Jianglong (57222724504)","57226239181; 57164286500; 57427678200; 58842682800; 57222724504","Multibox Three-Dimensional Packing Problems for Heterogeneous Extrudable Items",2022.0,"Mathematical Problems in Engineering",2022.0,null,1497148.0,null,null,null,2.0,"10.1155/2022/1497148","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85142428530&doi=10.1155%2f2022%2f1497148&partnerID=40&md5=4ca0359cb8415f6d662e24a0be587008","School of Information, Beijing Wuzi University, Beijing, 101149, China; School of Management and Engineering, Capital University of Economics and Business, Beijing, 100070, China","Zhao J., School of Information, Beijing Wuzi University, Beijing, 101149, China; Zhou L., School of Information, Beijing Wuzi University, Beijing, 101149, China; Wang F., School of Information, Beijing Wuzi University, Beijing, 101149, China; Liu H., School of Information, Beijing Wuzi University, Beijing, 101149, China, School of Management and Engineering, Capital University of Economics and Business, Beijing, 100070, China; Yang J., School of Information, Beijing Wuzi University, Beijing, 101149, China","Aiming at the multibox 3D packing problem of heterogeneous extrudable items in e-commerce retail department stores, the optimization goal is to select appropriate packaging materials for packing all items in the order. On this basis, the number of packaging materials used is the least and the space utilization rate is high. A heuristic algorithm is designed. Firstly, the items are sorted in descending order according to volume, and then the items are boxed according to the rule of \"layer generation.\"In order to verify the feasibility and effectiveness of the algorithm, the data provided by a large domestic e-commerce platform are used to analyse and compare the space utilization of packaging materials under the conditions of no extrusion operation and extrusion operation. The feasibility and effectiveness of the algorithm in the packaging and delivery link in the storage field of e-commerce retail department stores are proved.  © 2022 Junhui Zhao et al.",null,"Digital storage; Electronic commerce; Extrusion; Heuristic algorithms; Packaging; Retail stores; 3D packing problem; E- commerces; Extrusion operation; Heuristics algorithm; Layer generation; Optimization goals; Packing problems; Space utilization; Three-dimensional packing; Utilization rates; Packaging materials",{"$nulls":6},"Erbayrak S., Ozkir V., Mahir Yildirim U., Multi-objective 3D bin packing problem with load balance and product family concerns, Computers & Industrial Engineering, 159, (2021); Elhedhli S., Gzara F., Yildiz B., Three-dimensional bin packing and mixed-case palletization, INFORMS Journal on Optimization, 1, 4, pp. 323-352, (2019); Huang Y.H., Hwang F.J., Lu H.C., An effective placement method for the single container loading problem, Computers & Industrial Engineering, 97, pp. 212-221, (2016); Su Y., Ye Y., Chen S., Yang W., A hybrid chemical reaction optimisation algorithm for solving 3D packing problem, International Journal of Autonomous and Adaptive Communications Systems, 14, 12, pp. 117-131, (2021); Correcher J.F., Alonso M.T., Parreno F., Alvarez-Valdes R., Solving a large multi-container loading problem in the car manufacturing industry, Computers & Operations Research, 82, pp. 139-152, (2017); Zhao H., Zhu C., Xu X., Huang H., Xu K., Learning practically feasible policies for online 3D bin packing, Science China Information Sciences, 65, pp. 1-17, (2022); de Carvalho P.R.V., Elhedhli S., A data-driven approach for mixed-case palletization with support, Optimization and Engineering, 23, 3, pp. 1587-1610, (2021); Liu S., Shen D., Shang X., Hong-Xia Z.H., Xi-Song D.O., Fei-Yue A., A multi-level tree search algorithm for three-dimensional container loading problem, Acta Automatica Sinica, 46, pp. 1178-1187, (2020); Gzara F., Elhedhli S., Yildiz B.C., The pallet loading problem: three-dimensional bin packing with practical constraints, European Journal of Operational Research, 287, 3, pp. 1062-1074, (2020); Wang N., Lim A., Zhu W., A multi-round partial beam search approach for the single container loading problem with shipment priority, International Journal of Production Economics, 145, 2, pp. 531-540, (2013); Tresca G., Cavone G., Carli R., Cerviotti A., Dotoli M., Automating bin packing: a layer building matheuristics for cost effective logistics, IEEE Transactions on Automation Science and Engineering, 19, 3, pp. 1599-1613, (2022); Mauro D., Furini F., Iori M., A branch-and-price algorithm for the temporal bin packing problem, Computers & Operations Research, 114, pp. 104825-104916, (2020); Ren J., Tian Y., Sawaragi T., A priority-considering approach for the multiple container loading problem, International Journal of Metaheuristics, 1, 4, pp. 298-349, (2011); Toffolo T.A., Esprit E., Wauters T., Vanden Berghe G., A two-dimensional heuristic decomposition approach to a three-dimensional multiple container loading problem, European Journal of Operational Research, 257, 2, pp. 526-538, (2017); Nguyen T.H., Tran V.T., Doan P.Q., Mac T.T., A novel heuristic algorithm for online 3D bin packing, Proceedings of the 2021 21st International Conference on Control, Automation and Systems (ICCAS), (2021); Agarwal M., Biswas S., Sarkar C., Paul S., Paul H.S., Jampacker: an efficient and reliable robotic bin packing system for cuboid objects, IEEE Robotics and Automation Letters, 6, 2, pp. 319-326, (2021); Li D., Gu Z., Wang Y., Ren C., Lau F.C., One model packs thousands of items with recurrent conditional Query learning, Knowledge-Based Systems, 235, (2022); Silva E.F., Toffolo T.A.M., Wauters T., Exact methods for three-dimensional cutting and packing: a comparative study concerning single container problems, Computers & Operations Research, 109, pp. 12-27, (2019); Iwasawa H., Hu Y., Hashimoto H., Imahori S., Yagiura M.A., A heuristic algorithm for the container loading problem with complex loading constraints, Journal of Advanced Mechanical Design Systems and Manufacturing, 10, 3, (2016); Ramos A.G., Silva E., Oliveira J.F., A new load balance methodology for container loading problem in road transportation, European Journal of Operational Research, 266, 3, pp. 1140-1152, (2018); Paquay C., Schyns M., Limbourg S., A mixed integer programming formulation for the three-dimensional bin packing problem deriving from an air cargo application, International Transactions in Operational Research, 23, 1-2, pp. 187-213, (2016); Ngoi B.K.A., Tay M.L., Chua E.S., Applying spatial representation techniques to the container packing problem, International Journal of Production Research, 32, 1, pp. 111-123, (1994); Fanslau T., Bortfeldt A., A tree search algorithm for solving the container loading problem, INFORMS Journal on Computing, 22, 2, pp. 222-235, (2010); Zhao X., Bennell J.A., Bektas T., Dowsland K., A comparative review of 3D container loading algorithms, International Transactions in Operational Research, 23, 1-2, pp. 287-320, (2016); Paquay C., Limbourg S., Schyns M., A tailored two-phase constructive heuristic for the three-dimensional multiple bin size bin packing problem with transportation constraints, European Journal of Operational Research, 267, 1, pp. 52-64, (2018); Jamrus T., Chien C.F., Extended priority-based hybrid genetic algorithm for the less-than-container loading problem, Computers & Industrial Engineering, 96, pp. 227-236, (2016); Alonso M.T., Alvarez-Valdes R., Iori M., Parreno F., Mathematical models for multi container loading problems with practical constraints, Computers & Industrial Engineering, 127, pp. 722-733, (2019); Borges Y.G., Miyazawa F.K., Schouery R.C., Xavier E.C., Exact algorithms for class-constrained packing problems, Computers & Industrial Engineering, 144, (2020); Liu Q., Cheng H., Tian T., Wang Y., Leng J., Zhao R., Zhang H., Wei L., Algorithms for the variable-sized bin packing problem with time windows, Computers & Industrial Engineering, 155, (2021); Wu H., Leung S.C., Si Y.W., Zhang D., Lin A., Three-stage heuristic algorithm for three-dimensional irregular packing problem, Applied Mathematical Modelling, 41, pp. 431-444, (2017); Sato A.K., Martins T.C., Gomes A.M., Tsuzuki M.S.G., Raster penetration map applied to the irregular packing problem, European Journal of Operational Research, 279, 2, pp. 657-671, (2019); Luo Q., Rao Y., Peng D., GA and GWO algorithm for the special bin packing problem encountered in field of aircraft arrangement, Applied Soft Computing, 114, (2022); Zhang H., Liu Q., Wei L., Zeng J., Leng J., Yan D., An iteratively doubling local search for the two-dimensional irregular bin packing problem with limited rotations, Computers & Operations Research, 137, (2022); Wang Z., Chang D., Man X., Optimization of two-dimensional irregular bin packing problem considering slit distance and free rotation of pieces, International Journal of Industrial Engineering Computations, 13, 4, pp. 491-506, (2022); Leng J., Wang D., Shen W., Li X., Liu Q., Chen X., Digital twins-based smart manufacturing system design in Industry 4.0: a review, Journal of Manufacturing Systems, 60, pp. 119-137, (2021); Leng J., Chen Z., Sha W., Lin Z., Lin J., Liu Q., Digital twins-based flexible operating of open architecture production line for individualized manufacturing, Advanced Engineering Informatics, 53, (2022); Marmolejo-Saucedo J.A., Digital twin framework for large-scale optimization problems in supply chains: a case of packing problem, Mobile Networks and Applications, 27, pp. 1-17, (2021); Leng J., Yan D., Liu Q., Zhang H., Zhao G., Wei L., Zhang D., Yu A., Chen X., Digital twin-driven joint optimisation of packing and storage assignment in large-scale automated high-rise warehouse product-service system, International Journal of Computer Integrated Manufacturing, 34, 7-8, pp. 783-800, (2021)","H. Liu; School of Information, Beijing Wuzi University, Beijing, 101149, China; email: darion8@163.com",null,"Hindawi Limited",{"$nulls":5},"1024123X",null,null,null,"English","Math. Probl. Eng.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85142428530"]
["Li J.","Li, Jiaolong (57698124400)",5.76981244E10,"E-Commerce Fraud Detection Model by Computer Artificial Intelligence Data Mining",2022.0,"Computational Intelligence and Neuroscience",2022.0,null,8783783.0,null,null,null,2.0,"10.1155/2022/8783783","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85130287513&doi=10.1155%2f2022%2f8783783&partnerID=40&md5=98cb1611d3465ebf5a15052026b81478","Purchasing Department, Sinosteel Xingtai Machinery & Mill Roll Co., Ltd., Xingtai, 054000, China","Li J., Purchasing Department, Sinosteel Xingtai Machinery & Mill Roll Co., Ltd., Xingtai, 054000, China","This study aims to identify e-commerce fraud, solve the financial risks of e-commerce enterprises through big data mining (BDM), further explore more effective solutions through Information fusion technology (IFT), and create an e-commerce fraud detection model (FDM) based on IFT (namely, computer technology (CT), artificial intelligence (AI), and data mining (DM). Meanwhile, BDM technology, support vector machine (SVM), logistic regression model (LRM), and the proposed IFT-based FDM are comparatively employed to study e-commerce fraud risks deeply. Specifically, the LRM can effectively solve data classification problems. The proposed IFT-based FDM fuses different information sources. The experimental findings corroborate that the proposed Business-to-Business (B2B) e-commerce enterprises-oriented IFT-based FDM presents significantly higher fraud identification accuracy than SVM and LRM. Therefore, the IFT-based FDM is superior to SVM and LRM; it can process and calculate e-commerce enterprises' financial risk data from different sources and obtain higher accuracy. BDM technology provides an important research method for e-commerce fraud identification. The proposed e-commerce enterprise-oriented FDM based on IFT can correctly analyze enterprises' financial status and credit status, obtaining the probability of fraudulent behaviors. The results are of great significance to B2B e-commerce fraud identification and provide good technical support for promoting the healthy development of e-commerce. © 2022 JiaoLong Li.",null,"Artificial Intelligence; Commerce; Computers; Data Mining; Fraud; Data mining; Electronic commerce; Finance; Logistic regression; Support vector machines; Data mining technology; Detection models; E- commerces; E-commerce enterprise; Financial risks; Fraud detection; Information fusion technology; Logistic Regression modeling; Model-based OPC; Technology-based; artificial intelligence; commercial phenomena; computer; data mining; fraud; Crime",{"$nulls":6},"Pentzold C., Brantner C., Folsche L., Imagining big data: Illustrations of \"big data\" in US news articles, 2010-2016, New Media & Society, 21, 1, pp. 139-167, (2019); Johnson S., Samsel F., Abram G., Olson D., Solis A.J., Herman B., Wolfram P.J., Lenglet C., Keefe D.F., Artifact-based rendering: Harnessing natural and traditional visual media for more expressive and engaging 3D visualizations, IEEE Transactions on Visualization and Computer Graphics, 26, 1, (2019); Suresh A., Rani N.J., Consumer perception towards artificial intelligence in E-commerce with reference to Chennai city, India, Journal of Information Technology and Economic Development, 11, 1, pp. 1-14, (2020); Ingaldi M., Ulewicz R., How to make e-commerce more successful by use of Kano's model to assess customer satisfaction in terms of sustainable development, Sustainability, 11, 18, (2019); Leung K.H., Luk C.C., Choy K.L., Lam H.Y., Lee C.K.M., A B2B flexible pricing decision support system for managing the request for quotation process under e-commerce business environment, International Journal of Production Research, 57, 20, pp. 6528-6551, (2019); Karimi Zandian Z., Mefuasn M.R.K., A helpful method to extract features using analyzing social network for fraud detection, Journal of AI and Data Mining, 7, 2, pp. 213-224, (2019); Oliveira M.M., Cruz-Tirado J.P., Barbin D.F., Nontargeted analytical methods as a powerful tool for the authentication of spices and herbs: A review, Comprehensive Reviews in Food Science and Food Safety, 18, 3, pp. 670-689, (2019); Dennis S.A., Goodson B.M., Pearson C., Online worker fraud and evolving threats to the integrity of MTurk data: A discussion of virtual private servers and the limitations of IP-based screening procedures, Behavioral Research in Accounting, 32, 1, pp. 119-134, (2020); Itoo F., Meenakshi S., Comparison and analysis of logistic regression, Naïve Bayes and KNN machine learning algorithms for credit card fraud detection, International Journal of Information Technology, 13, 4, pp. 1503-1511, (2021); Fan W., Liu J., Zhu S., Pardalos P.M., Investigating the impacting factors for the healthcare professionals to adopt artificial intelligence-based medical diagnosis support system (AIMDSS), Annals of Operations Research, 294, 1-2, pp. 567-592, (2020); Bechmann A., Bowker G.C., Unsupervised by any other name: Hidden layers of knowledge production in artificial intelligence on social media, Big Data & Society, 6, 1, (2019); Han W., The analysis on Chinese e-commerce tax losses based on the perspective of information asymmetry, Electronic Commerce Research, 20, 3, pp. 651-677, (2020); Choi D., Chung C.Y., Young J., Sustainable online shopping logistics for customer satisfaction and repeat purchasing behavior: Evidence from China, Sustainability, 11, 20, (2019); Tran V.D., The relationship among product risk, perceived satisfaction and purchase intentions for online shopping, The Journal of Asian Finance, Economics, and Business, 7, 6, pp. 221-231, (2020); Yan S., The perception difference analysis of the influence of coastal residents of big data mining technology on marine tourism development, Journal of Coastal Research, 115, 1, pp. 265-267, (2020); Triguero I., Garcia-Gil D., Maillo J., Luengo J., Garcia S., Herrera F., Transforming big data into smart data: An insight on the use of the k-nearest neighbors algorithm to obtain quality data, WIREs Data Mining and Knowledge Discovery, 9, 2, (2019); Ryu K.D., Park J.P., Kim Y., Dong-Hoon L., Development of AI-based real time agent advisor system on call center-focused on N bank call center, Journal of the Korea Academia-Industrial Cooperation Society, 20, 2, pp. 750-762, (2019); 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Zagorac D., Muller H., Ruehl S., Zagorac J., Rehme S., Recent developments in the Inorganic Crystal Structure Database: Theoretical crystal structure data and related features, Journal of Applied Crystallography, 52, 5, pp. 918-925, (2019); Sheng J., Amankwah-Amoah J., Khan Z., Wang X., COVID-19 pandemic in the new era of big data analytics: Methodological innovations and future research directions, British Journal of Management, 32, 4, pp. 1164-1183, (2021); Yu C., Zuo Y., Feng B., Chen B., An individual-group-merchant relation model for identifying fake online reviews: An empirical study on a Chinese e-commerce platform, Information Technology and Management, 20, 3, pp. 123-138, (2019)","J. Li; Purchasing Department, Sinosteel Xingtai Machinery & Mill Roll Co., Ltd., Xingtai, 054000, China; email: 20160121@ayit.edu.cn",null,"Hindawi Limited",{"$nulls":5},1.6875265E7,null,null,3.5586101E7,"English","Comput. Intell. Neurosci.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85130287513"]
["Wang Q.; Gu B.; Fu Y.","Wang, Quanli (55864746200); Gu, Bojun (53263598500); Fu, Yufang (57189371582)","55864746200; 53263598500; 57189371582","Optimization of Pricing and Freshness-Keeping Effort in Fresh e-Commerce Supply Chain considering Online Comments",2022.0,"Mathematical Problems in Engineering",2022.0,null,1473331.0,null,null,null,2.0,"10.1155/2022/1473331","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85131202407&doi=10.1155%2f2022%2f1473331&partnerID=40&md5=1a10b652409114daf463e6ce139ee692","School of Economics and Management, Zhejiang Ocean University, Zhoushan, China","Wang Q., School of Economics and Management, Zhejiang Ocean University, Zhoushan, China; Gu B., School of Economics and Management, Zhejiang Ocean University, Zhoushan, China; Fu Y., School of Economics and Management, Zhejiang Ocean University, Zhoushan, China","Considering that online comments play an important role in operational decisions of a fresh e-commerce supply chain, we construct single-stage and two-stage models for fresh produce supply chain consisting of a supplier and a fresh e-commerce platform. Utilizing the Stackelberg game and two-stage repeated game, the profit functions of the supplier and platform are established, and then, the optimal retail price and freshness-keeping effort are derived. In addition, to improve the accuracy of models in describing practical problems, we construct an extended two-stage model and a third-party logistics model. Furthermore, we compare the optimal strategies under different models. Our results show that, firstly, the optimal retail price and freshness-keeping effort of supplier and platform vary in different models and online comments play a positive effect on supplier and platform's profits. Secondly, compared with the single-stage model, the fresh e-commerce supply chain grabs more market share and profits under the two-stage model. Lastly, online comments vary in different dominance scenarios and may cause competition between supplier and platform for supply chain dominance. © 2022 Quanli Wang et al.",null,"Competition; Costs; Electronic commerce; Outsourcing; Profitability; Commerce platforms; E- commerces; Fresh produce; Freshness-keeping; Operational decisions; Optimal retail price; Optimisations; Produce supply chains; Single stage; Two stage model; Supply chains",{"$nulls":4},"Fundamental Research Funds for Zhejiang Provincial Universities and Research Institutes, (2019J00055)","This work was partly supported by the Fundamental Research Funds for Zhejiang Provincial Universities and Research Institutes (2019J00055)","Research Report on China Fresh E-Commerce Industry in, (2021); Zhang G., Liu Z.Y., Effects of influential factors on consumer perceptions of uncertainty for online shopping, Nankai Business Review, 13, 5, pp. 99-106, (2010); Singh J.P., Irani S., Rana N.P., Dwivedi Y.K., Saumya S., Kumar Roy P., Predicting the \"helpfulness\" of online consumer reviews, Journal of Business Research, 70, pp. 346-355, (2017); 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Fu; School of Economics and Management, Zhejiang Ocean University, Zhoushan, China; email: yufangcat@163.com",null,"Hindawi Limited",{"$nulls":5},"1024123X",null,null,null,"English","Math. Probl. Eng.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85131202407"]
["Zhang M.; Xiong G.; Bao S.; Meng C.","Zhang, Min (57215730928); Xiong, Guowen (57215826555); Bao, Shanshan (57197762312); Meng, Chao (55075986900)","57215730928; 57215826555; 57197762312; 55075986900","A TIME-DIVISION DISTRIBUTION STRATEGY FOR THE TWO-ECHELON VEHICLE ROUTING PROBLEM WITH DEMAND BLOWOUT",2022.0,"Journal of Industrial and Management Optimization",18.0,4.0,null,2847.0,2872.0,25.0,0.0,"10.3934/jimo.2021094","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85132339946&doi=10.3934%2fjimo.2021094&partnerID=40&md5=2fba6b305adbb44b98e318a70600ac75","School of Mechanical Engineering, Southwest Jiaotong University, Chengdu, 610031, China; Technology and Equipment of Rail Transit Operation and Maintenance Key Laboratory of Sichuan Province, Chengdu, 610031, China; Avic Chengdu Aircraft Industrial (Group)Co.,Ltd, Chengdu, 610031, China; School of Marketing, University of Southern Mississippi, Hattiesburg, 39406, MS, United States","Zhang M., School of Mechanical Engineering, Southwest Jiaotong University, Chengdu, 610031, China, Technology and Equipment of Rail Transit Operation and Maintenance Key Laboratory of Sichuan Province, Chengdu, 610031, China; Xiong G., School of Mechanical Engineering, Southwest Jiaotong University, Chengdu, 610031, China, Avic Chengdu Aircraft Industrial (Group)Co.,Ltd, Chengdu, 610031, China, School of Marketing, University of Southern Mississippi, Hattiesburg, 39406, MS, United States; Bao S., School of Mechanical Engineering, Southwest Jiaotong University, Chengdu, 610031, China, Avic Chengdu Aircraft Industrial (Group)Co.,Ltd, Chengdu, 610031, China, School of Marketing, University of Southern Mississippi, Hattiesburg, 39406, MS, United States; Meng C., School of Mechanical Engineering, Southwest Jiaotong University, Chengdu, 610031, China, Avic Chengdu Aircraft Industrial (Group)Co.,Ltd, Chengdu, 610031, China, School of Marketing, University of Southern Mississippi, Hattiesburg, 39406, MS, United States","Based on the rapid development of e-commerce, major promotional events and holidays can lead to explosive growth in market demand and place significant pressure on distribution systems. In this study, we considered a distribution system in which products are first transported to transfer satellites from a central depot and then delivered to customers from the transfer satellites. We modeled this distribution problem as a two-echelon vehicle routing problem with demand blowout (2E-VRPDB). We adopt a time-division distribution strategy to address massive delivery demand in two phases by offering incentives to customers who accept flexible delivery dates. We propose a hybrid fireworks algorithm (HFWA) to solve the 2E-VRPDB model. This model fuses an optimal cutting algorithm with an improved fireworks algorithm. To demonstrate the effectiveness and efficiency of the proposed HFWA, we conducted comparative analysis on a genetic algorithm and ant colony algorithm using a VRP example set. Finally, we applied the proposed model and HFWA to solve a distribution problem for the Jingdong Mall in Chengdu, China. The computational results demonstrate that the proposed approach can effectively reduce logistical costs and maintain a high service level. © 2022. Journal of Industrial and Management Optimization. All Rights Reserved.","Demand blowout; Hybrid fireworks algorithm; Time-division distribution; Two-echelon vehicle routing problem","Ant colony optimization; Blowouts; Explosives; Routing algorithms; Vehicle routing; Vehicles; Demand blowout; Distribution problem; Distribution strategies; Distribution systems; Fireworks algorithms; Hybrid firework algorithm; Time division; Time-division distribution; Two-echela vehicle routing problem; Vehicle Routing Problems; Genetic algorithms",{"$nulls":4},"Sichuan Province Science and Technology Support Program, (2020JDTD 0012); National Natural Science Foundation of China, NSFC, (51675450); Ministry of Education of the People's Republic of China, MOE, (18YJC630255); China Postdoctoral Science Foundation, (2020M673279)","Funding text 1: Acknowledgments. This work is partially supported by China Postdoctoral Science Foundation (No.2020M673279), National Natural Science Foundation of China (NSFC) (No. 51675450), Sichuan Science and Technology Program (No. 2020JDTD 0012) and MOE (Ministry of Education in China) Project of Humanities and Social Sciences (No. 18YJC630255).; Funding text 2: 2020 Mathematics Subject Classification. Primary: 90B06, 62K05; Secondary: 68T37. Key words and phrases. Two-echelon vehicle routing problem, demand blowout, time-division distribution, hybrid fireworks algorithm. The first author is supported by China Postdoctoral Science Foundation (No.2020M673279), National Natural Science Foundation of China (NSFC) (No.51675450), Sichuan Science and Technology Program (No.2020JDTD0012) and MOE (Ministry of Education in China) Project of Humanities and Social Sciences (No.18YJC630255). ∗ Corresponding author: Chao Meng.","Baldacci R., Mingozzi A., Roberti R., Clavo R. 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M., Bektas T., The time-dependent two-echelon capacitated vehicle routing problem with environmental considerations, International Journal of Production Economics, 164, pp. 366-378, (2015); Swilley E., Goldsmith R. E., Black Friday and Cyber Monday: Understanding consumer intentions on two major shopping days, Journal of Retailing and Consumer Services, 20, pp. 43-50, (2013); Tan Y., Zhu Y., Fireworks algorithm for optimization, International Conference in Swarm Intelligence, pp. 355-364; Tirkolaee E. B., Goli A., Faridnia A., Soltani M., Weber G.-W., Multi-objective optimization for the reliable pollution-routing problem with cross-dock selection using Pareto-based algorithms, Journal of Cleaner Production, 276, (2020); Tirkolaee E. B., Goli A., Pahlevan M., Kordestanizadeh R. M., A robust bi-objective multi-trip periodic capacitated arc routing problem for urban waste collection using a multiobjective invasive weed optimization, Waste Management and Research, 37, pp. 1089-1101, (2019); Tirkolaee E. B., Hadian S., Golpra H., A novel multi-objective model for two-echelon green routing problem of perishable products with intermediate depots, Journal of Industrial Engineering and Management Studies, 6, pp. 196-213, (2019); Tirkolaee E. B., Hadian S., Weber G.-W., Mahdavi I., A robust green traffic-based routing problem for perishable products distribution, Computational Intel ligence, 36, pp. 80-101, (2020); Wang K., Lan S., Zhao Y., A genetic-algorithm-based approach to the two-echelon capacitated vehicle routing problem with stochastic demands in logistics service, Journal of the Operational Research Society, 68, pp. 1409-1421, (2017); Yan X. M., Hao Z. F., Huang H., Li B, Jiang S., Assignment-preference ant colony optimization for the two-echelon vehicle routing problem, Indian Pulp and Paper Technical Association, 30, pp. 484-494, (2018); Zhang T. T., Liu Z. F., Fireworks algorithm for mean-VaR/CVaR models, Physica A: Statistical Mechanics and its Applications, 483, pp. 1-8, (2017)","C. Meng; School of Mechanical Engineering, Southwest Jiaotong University, Chengdu, 610031, China; email: meng5656@gmail.com",null,"American Institute of Mathematical Sciences",{"$nulls":5},1.5475816E7,null,null,null,"English","J. Ind. Manage. Optim.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85132339946"]
["Li X.; Zheng C.; Wang T.","Li, Xinxin (57560990900); Zheng, Chunfang (15844969400); Wang, Tongtong (57225192506)","57560990900; 15844969400; 57225192506","Modelling the Coupled and Coordinated Development between China's Cross-border E-commerce Supply Chain and Economic System",2022.0,"Discrete Dynamics in Nature and Society",2022.0,null,9547413.0,null,null,null,3.0,"10.1155/2022/9547413","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85127535130&doi=10.1155%2f2022%2f9547413&partnerID=40&md5=f2f9686487aff021629aae3a6990fd8d","Business College of Beijing Union University, Beijing, China","Li X., Business College of Beijing Union University, Beijing, China; Zheng C., Business College of Beijing Union University, Beijing, China; Wang T., Business College of Beijing Union University, Beijing, China","This study constructs a coupling model and establishes an index system for the coupled and coordinate development between cross-border e-commerce supply chain system and economic system. The index system adopts supply chain, foreign trade, e-commerce, e-commerce logistics, economic development, social consumption, talent environment, and technological innovation as sequential covariates. The calculation shows that the first three batches of 35 cross-border e-commerce comprehensive pilot areas (CBECCPA in brief) in China, in 2017, are classified into three degrees of the coupled and coordinated development: superior, good, and moderate. The study provides useful recommendations for promoting cross-border e-commerce supply chain, such as to pursue high-quality balanced development, to cultivate professional composite talents, to encourage innovation and entrepreneurship, and to create a favorable economic environment.  © 2022 Xinxin Li et al.",{"$nulls":8},"Balakrishnan A., Geunes J., Collaboration and coordination in supply chain management and E-commerce, Production and Operations Management, 13, pp. 1-2, (2010); Anderson W.P., Chatterjee L., Lakshmanan A.T.R., E-commerce, Transportation and E-commerce geography, Growth and Change, 34, 4, pp. 415-432, (2010); Davidaviciene V., Markus O., Davidavicius S., Identification of the opportunities to improve customer's experience in E-commerce, Journal of Logistics, Informatics and Service Science, 7, pp. 42-57, (2020); Li F., Yang L.H., Liang H., A study on the mechanism and path of synergistic development of Cross-border E-commerce and industrial clusters in China, International Trade Issues, 2, pp. 9-13, (2019); Xu M., Wang X., Wang H., A review of regional diversification entry patterns of enterprises based on the institutional base view, Foreign Economics and Management, 9, (2010); Quang H.N., Huu T.D., Factors preventing the way to success of the retail supply chain, Journal of System and Management Sciences, 9, 2, pp. 114-122, (2019); Lu J., Analysis of the elements and relationships affecting the efficiency of Cross-border E-commerce supply chain, Business Economics Research, 22, pp. 153-155, (2020); Nazifa T.H., Ramachandran K.K., Exploring the role of information sharing in supply chain management: A case study, Journal of System and Management Sciences, 8, pp. 13-37, (2018); Zhou F., Research on the development path of regional Cross-border E-commerce under the perspective of industrial competitiveness, Business Economic Research, 19, (2018); Zhang W.-N., Lu X.-J., Li M.-H., Study on the influencing factors of cross-border e-commerce development in China, Journal of Hainan University (Humanities and Social Sciences Edition), 37, 3, pp. 57-63, (2019); Qian H., He J., Analysis of influencing factors of Cross-border E-commerce and cross-border logistics synergy based on rooted theory model, Industry and Economics Review, 6, pp. 8-11, (2017); Zhang S., Exploring the collaborative network and evolutionary path of Cross-border E-commerce based on concordance theory, Business Economics Research, 3, (2018); Liu Y., Chen D., Synergistic evaluation analysis of Cross-border E-commerce and modern logistics based on composite system synergy model, China Circulation Economy, 5, pp. 3-7, (2016); Cao Y., Wang M., Research on the synergistic development of Cross-border E-commerce and logistics industry based on the perspective of industrial chain, Price Monthly, 2, pp. 3-4, (2017)","C. Zheng; Business College of Beijing Union University, Beijing, China; email: chunfang.zheng@buu.edu.cn",null,"Hindawi Limited",{"$nulls":5},1.0260226E7,null,null,null,"English","Discrete Dyn. Nat. Soc.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85127535130"]
["Barykin S.E.; Smirnova E.A.; Chzhao D.; Kapustina I.V.; Sergeev S.M.; Mikhalchevsky Y.Y.; Gubenko A.V.; Kostin G.A.; De La Poza Plaza E.; Saychenko L.; Moiseev N.","Barykin, Sergey Evgenievich (57202814691); Smirnova, Elena Aleksandrovna (57205202070); Chzhao, Dan (57382357100); Kapustina, Irina Vasilievna (57194710660); Sergeev, Sergey Mikhailovich (57200788956); Mikhalchevsky, Yuri Yurievich (57381476100); Gubenko, Alexander Viktorovich (56964049000); Kostin, Gennady Aleksanrovich (57802912100); De La Poza Plaza, Elena (57382357200); Saychenko, Lilya (57190739330); Moiseev, Nikita (56699755300)","57202814691; 57205202070; 57382357100; 57194710660; 57200788956; 57381476100; 56964049000; 57802912100; 57382357200; 57190739330; 56699755300","Digital echelons and interfaces within value chains: End-to-end marketing and logistics integration",2021.0,"Sustainability (Switzerland)",13.0,24.0,13929.0,null,null,null,17.0,"10.3390/su132413929","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121498270&doi=10.3390%2fsu132413929&partnerID=40&md5=518db4ed931e36f0fd1ce19f2088c023","Graduate School of Service and Trade, Peter the Great St. Petersburg Polytechnic University, St. Petersburg, 195251, Russian Federation; Department of Logistics and Supply Chain Management, St. Petersburg State University of Economics, St. Petersburg, 191023, Russian Federation; Graduate School of Industrial Management, Peter the Great St. Petersburg Polytechnic University, St. Petersburg, 195251, Russian Federation; Top Management Department, Saint Petersburg State University of Civil Aviation, St. Petersburg, 196210, Russian Federation; Center for Economic Engineering (INECO), Universitat Politècnica de València, Valencia, 46022, Spain; Department of Development and Exploration of Oil and Gas Wells, St. Petersburg Mining University, St. Petersburg, 199106, Russian Federation; Department of Mathematical Methods in Economics, Plekhanov Russian University of Economics, Moscow, 117997, Russian Federation","Barykin S.E., Graduate School of Service and Trade, Peter the Great St. Petersburg Polytechnic University, St. Petersburg, 195251, Russian Federation; Smirnova E.A., Department of Logistics and Supply Chain Management, St. Petersburg State University of Economics, St. Petersburg, 191023, Russian Federation; Chzhao D., Department of Logistics and Supply Chain Management, St. Petersburg State University of Economics, St. Petersburg, 191023, Russian Federation; Kapustina I.V., Graduate School of Service and Trade, Peter the Great St. Petersburg Polytechnic University, St. Petersburg, 195251, Russian Federation; Sergeev S.M., Graduate School of Industrial Management, Peter the Great St. Petersburg Polytechnic University, St. Petersburg, 195251, Russian Federation; Mikhalchevsky Y.Y., Top Management Department, Saint Petersburg State University of Civil Aviation, St. Petersburg, 196210, Russian Federation; Gubenko A.V., Top Management Department, Saint Petersburg State University of Civil Aviation, St. Petersburg, 196210, Russian Federation; Kostin G.A., Top Management Department, Saint Petersburg State University of Civil Aviation, St. Petersburg, 196210, Russian Federation; De La Poza Plaza E., Center for Economic Engineering (INECO), Universitat Politècnica de València, Valencia, 46022, Spain; Saychenko L., Department of Development and Exploration of Oil and Gas Wells, St. Petersburg Mining University, St. Petersburg, 199106, Russian Federation; Moiseev N., Department of Mathematical Methods in Economics, Plekhanov Russian University of Economics, Moscow, 117997, Russian Federation","The goals of real business in the context of the digital transformation of international logistics networks and marketing channels have necessitated the application of a scientifically based theoretical approach to the development of a formalized description acceptable for predictive planning based on leading indicators. In the context of globalization and interstate and regional economic unions, this will lead to achieving the maximum end-to-end integration of digital platforms. Based on the analysis, the article presents the integration of digital logistics and marketing approaches with the mathematical models of the ecosystem organization of economic relations. The features of the organization of economic relations between contractors involved in the execution of virtual transactions and the material movement of resources were analyzed. The researchers considered prerequisites for the analytical description of interconnections between the participants of digital platforms in cross border e-commerce. The authors’ approach is based on the idea of both a sales funnel in marketing and a conversion funnel in digital transformation. Considering the integration of logistics and marketing, authors offer the definition of business echelons as stages of the consumer value creation. The theoretical contribution of this article consists in constructing a mathematical description of business echelons along the entire value chain. The developed analytical description of business echelons is acceptable both for embedding a digital management support system into various software products, and for conducting in-depth analysis and finding optimal solutions. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.","Business interaction; Cross-border e-commerce; Digital logistics; Digital marketing; Digital platforms; Sustainable digital ecosystem","business; economic relations; integrated approach; marketing; mass movement; movement",{"$nulls":4},"Ministry of Education and Science of the Russian Federation, Minobrnauka, (075-15-2021-1333)","Funding: The research of S.E.B., S.M.S. and I.V.K. is partially funded by the Ministry of Science and Higher Education of the Russian Federation under the strategic academic leadership program ‘Priority 2030’ (Agreement 075-15-2021-1333 dated 30 September 2021).","Porter M.E., Competitive Advantage: Creating and Sustaining Superior Performance, (1985); Porter M.E., Competitive Strategy: Techniques for Analysing Industries and Competitors, (1980); Porter M.E., Kramer M.R., Creating Shared Value, Managing Sustainable Business, pp. 323-346, (2019); Shmatko A., Barykin S., Sergeev S., Thirakulwanich A., Modeling a Logistics Hub Using the Digital Footprint Method—The Implication for Open Innovation Engineering, J. Open Innov. Technol. Mark. Complex, 7, (2021); Barykin S.Y., Kapustina I.V., Sergeev S.M., Yadykin V.K., Algorithmic foundations of economic and mathematical modeling of network logistics processes, J. Open Innov. Technol. Mark. Complex, 6, (2020); Borisoglebskaya L.N., Sergeev S.M., Provotorova E.N., Zaslavskiy A.A., Digital algorithms for supply chain automation of mechanical engineering production, IOP Conf. Ser. Mater. Sci. Eng, 862, (2020); Pilipenko O.V., Provotorova E.N., Sergeev S.M., Rodionov O.V., Automation engineering of adaptive industrial warehouse, J. Phys. Conf. Ser, 1399, (2019); Yue D., You F., Game-theoretic modeling and optimization of multi-echelon supply chain design and operation under Stackelberg game and market equilibrium, Comput. Chem. Eng, 71, pp. 347-361, (2014); Popovic T., Barbosa-Povoa A., Kraslawski A., Carvalho A., Quantitative indicators for social sustainability assessment of supply chains, J. Clean. Prod, 180, pp. 748-768, (2018); Ullah M., Asghar I., Zahid M., Omair M., AlArjani A., Sarkar B., Ramification of remanufacturing in a sustainable three-echelon closed-loop supply chain management for returnable products, J. Clean. Prod, 290, (2021); Sarkar B., Guchhait R., Sarkar M., Pareek S., Kim N., Impact of safety factors and setup time reduction in a two-echelon supply chain management, Robot. Comput. Integr. Manuf, 55, pp. 250-258, (2019); Mitra S., Inventory management in a two-echelon closed-loop supply chain with correlated demands and returns, Comput. Ind. Eng, 62, pp. 870-879, (2012); Zhang Y., Huang G.H., He L., A multi-echelon supply chain model for municipal solid waste management system, Waste Manag, 34, pp. 553-561, (2014); Gumus A.T., Guneri A.F., A multi-echelon inventory management framework for stochastic and fuzzy supply chains, Expert Syst. Appl, 36, pp. 5565-5575, (2009); Ryu K., Moon I., Oh S., Jung M., A fractal echelon approach for inventory management in supply chain networks, Int. J. Prod. Econ, 143, pp. 316-326, (2013); Burke R., Mussomeli A., Laaper S., Hartigan M., Sniderman B., The Smart Factory. Responsive, Adaptive, Connected Manufacturing, (2017); Barykin S.Y., Smirnova E.A., Sharapaev P.A., Mottaeva A.B., Development of the Kazakhstan digital retail chains within the EAEU E-commerce, Acad. Strateg. Manag. J, 20, pp. 1-18, (2021); Scherbakov V., Silkina G., Conceptual model of Logistics Vocational Education in the Digital Economy, Proceedings of the International Conference on Digital Technologies in Logistics and Infrastructure (ICDTLI 2019), 1, pp. 120-125, (2019); Scherbakov V., Silkina G., Logistics of smart supply chains, Proceedings of the International Conference on Digital Technologies in Logistics and Infrastructure (ICDTLI 2019), 1, pp. 66-71, (2019); Bu L., Wang J., Wei Wang K., Zipser D., China Digital Consumer Trends: Discovering the Next Wave of Growth; Wu P., Xiao-chuan Weng C., Joseph S.-A., Crossing the Rubicon? The implications of RCEP on anti-monopoly enforcement on dominant E-commerce platforms in China, Comput. Law Secur. Rev, 42, (2021); HSE-Skolkovo Institute for Law and Development, (2019); Aslam H., Khan A.Q., Rashid K., Rehman S., Achieving supply chain resilience: The role of supply chain ambidexterity and supply chain agility, J. Manuf. Technol. Manag, 31, pp. 1185-1204, (2020); Frederico G., Garza-reyes J.A., Supply Chain Strategy Reboot—Supply Chain Management Review; Bag S., Wood L.C., Mangla S.K., Luthra S., Procurement 4.0 and its implications on business process performance in a circular economy, Resour. Conserv. Recycl, 152, (2020); Giordano G., A Hybrid Supply Chain, Plast. Eng, 76, pp. 9-11, (2020); Gao X., Wang Y., Chen X., Gao S., Interface, interaction, and intelligence in generalized brain–computer interfaces, Trends Cogn. Sci, 25, pp. 671-684, (2021); Nguyen Q.N., Sidorova A., Torres R., User interactions with chatbot interfaces vs. Menu-based interfaces: An empirical study, Comput. Hum. Behav, (2021); Ngai E.W.T., Lee M.C.M., Luo M., Chan P.S.L., Liang T., An intelligent knowledge-based chatbot for customer service, Electron. Commer. Res. Appl, 50, (2021); Borisoglebskaya L.N., Provotorov V.V., Sergeev S.M., Kosinov E.S., Mathematical aspects of optimal control of transference processes in spatial networks, IOP Conf. Ser. Mater. Sci. Eng, 537, (2019); Borisoglebskaya L.N., Provotorova E.N., Sergeev S.M., Commercial software engineering under the digital economy concept, J. Phys. Conf. Ser, 1399, (2019); Zhabko A.P., Shindyapin A.I., Provotorov V.V., Stability of weak solutions of parabolic systems with distributed parameters on the graph, Vestn. Sankt-Peterbg. Univ. Prikl. Mat. Inform. Protsessy Upr, 15, pp. 457-471, (2019); Krasnov S., Sergeev S., Zotova E., Grashchenko N., Algorithm of optimal management for the efficient use of energy resources, E3S Web Conf, 110, (2019); Barykin S.E., Borisoglebskaya L.N., Provotorov V.V., Kapustina I.V., Sergeev S.M., De La Poza Plaza E., Saychenko L., Sustainability of Management Decisions in a Digital Logistics Network, Sustainability, 13, (2021); Barykin S.Y., Kapustina I.V., Sergeev S.M., Kalinina O.V., Vilken V.V., De La Poza Plaza E., Putikhin Y.Y., Volkova L.V., Developing the physical distribution digital twin model within the trade network, Acad. Strateg. Manag. J, 20, pp. 1-18, (2021); Silkina G.Y., Shevchenko S.Y., Sharapaev P.A., Digital innovation in process management, Acad. Strateg. Manag. J, 20, pp. 1-25, (2021); Shabalov M.Y., Zhukovskiy Y.L., Buldysko A.D., Gil B., Starshaia V.V., The influence of technological changes in energy efficiency on the infrastructure deterioration in the energy sector, Energy Rep, 7, pp. 2664-2680, (2021); Litvinenko V., Meyer B., Syngas Production: Status and Potential for Implementation in Russian Industry, (2017); Filser M., Kraus S., Roig-Tierno N., Kailer N., Fischer U., Entrepreneurship as catalyst for sustainable development: Opening the black box, Sustainability, 11, (2019); Gupta R., Mejia C., Kajikawa Y., Business, innovation and digital ecosystems landscape survey and knowledge cross sharing, Technol. Forecast. Soc. Chang, 147, pp. 100-109, (2019); Kuckertz A., Bioeconomy transformation strategies worldwide require stronger focus on entrepreneurship, Sustainability, 12, (2020); An J., Mikhaylov A., Jung S.-U., A Linear Programming Approach for Robust Network Revenue Management in the Air-line Industry, J. Air Transp. Manag, 91, (2021); Mikhaylov A., Development of Friedrich von Hayek’s theory of private money and economic implications for digital currencies, Terra Econ, 19, pp. 53-62, (2021); An J., Mikhaylov A., Richter U.H., Trade War Effects: Evidence from Sectors of Energy and Resources in Africa, Heliyon, 6, (2020)","S.E. Barykin; Graduate School of Service and Trade, Peter the Great St. Petersburg Polytechnic University, St. Petersburg, 195251, Russian Federation; email: sbe@list.ru; S.M. Sergeev; Graduate School of Industrial Management, Peter the Great St. Petersburg Polytechnic University, St. Petersburg, 195251, Russian Federation; email: sergeev2@yandex.ru",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85121498270"]
["Ou T.-Y.; Cheng C.-Y.; Lai C.H.; Fu H.-P.","Ou, Tsung-Yin (57226676192); Cheng, Chen-Yang (24342947000); Lai, Chun Hsiung (57288430000); Fu, Hsin-Pin (7402948206)","57226676192; 24342947000; 57288430000; 7402948206","A Coordination-Based Algorithm for Dedicated Destination Vehicle Routing in B2B E-Commerce",2021.0,"Computer Systems Science and Engineering",40.0,3.0,null,895.0,911.0,16.0,2.0,"10.32604/CSSE.2022.018432","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85116709286&doi=10.32604%2fCSSE.2022.018432&partnerID=40&md5=d90ab09b284739debbbba55d8ca18729","Department of Marketing and Distribution Management, National Kaohsiung University of Science and Technology, Taiwan; Department of Industrial Engineering and Management, Taipei University of Technology, Taiwan; Department of Enterprise Information and Industrial Engineering, Tunghai University, Taiwan","Ou T.-Y., Department of Marketing and Distribution Management, National Kaohsiung University of Science and Technology, Taiwan; Cheng C.-Y., Department of Industrial Engineering and Management, Taipei University of Technology, Taiwan; Lai C.H., Department of Enterprise Information and Industrial Engineering, Tunghai University, Taiwan; Fu H.-P., Department of Marketing and Distribution Management, National Kaohsiung University of Science and Technology, Taiwan","This paper proposes a solution to the open vehicle routing problem with time windows (OVRPTW) considering third-party logistics (3PL). For the typical OVRPTW problem, most researchers consider time windows, capacity, routing limitations, vehicle destination, etc. Most researchers who previously investigated this problem assumed the vehicle would not return to the depot, but did not consider its final destination. However, by considering 3PL in the B2B e-commerce, the vehicle is required back to the nearest 3PL location with available space. This paper formulates the problem as a mixed integer linear programming (MILP) model with the objective of minimizing the total travel distance. A coordinate representation particle swarm optimization (CRPSO) algorithm is developed to obtain the best delivery sequencing and the capacity of each vehicle. Results of the computational study show that the proposed method provides solution within a reasonable amount of time. Finally, the result compared to PSO also indicates that the CRPSO is effective. © 2021 CRL Publishing. All rights reserved.","Dedicated destination; Open vehicle routing problem with time windows; Third-party logistics","Electronic commerce; Integer programming; Outsourcing; Particle swarm optimization (PSO); Vehicles; B2B e-commerce; Coordinate representations; Dedicated destination; Open vehicle routing problem with time window; Open vehicle routing problems; Routings; Third party logistics (3PL); Third-party logistics; Time windows; Vehicle routing problem with time windows; Vehicle routing",{"$nulls":6},"Hertz S., Alfredsson M., Strategic development of third-party logistics providers, Industrial Marketing Management, 32, 2, pp. 139-149, (2003); Quinn J. B., Strategic outsourcing: Leveraging knowledge capabilities, Sloan Management Review, 40, 4, pp. 9-21, (1999); Christopher M., Logistics & supply chain management, (2016); Dantzig G. B., Ramser J. H., The truck dispatching problem, Management Science, 6, 1, pp. 80-91, (1959); Leung K. H., Lee C. K., Choy K. L., An integrated online pick-to-sort order batching approach for managing frequent arrivals of B2B e-commerce orders under both fixed and variable time-window batching, Advanced Engineering Informatics, 45, pp. 101-125, (2020); Bell J. E., McMullen P. R., Ant colony optimization techniques for the vehicle routing problem, Advanced Engineering Informatics, 18, 1, pp. 41-48, (2004); Repoussis P. P., Tarantilis C. D., Ioannou G., The open vehicle routing problem with time windows, Journal of the Operational Research Society, 58, 3, pp. 355-367, (2007); Repoussis P. P., Paraskevopoulos D. C., Zobolas G., Tarantilis C. D., Ioannou G., A web-based decision support system for waste lube oils collection and recycling, European Journal of Operational Research, 195, 3, pp. 676-700, (2009); Baykasoglu A., Kaplanoglu V., A multi-agent approach to load consolidation in transportation, Advances in Engineering Software, 42, 7, pp. 477-490, (2011); Amorim P., Gunther H.-O., Almada-Lobo B., Multi-objective integrated production and distribution planning of perishable products, International Journal of Production Economics, 138, 1, pp. 89-101, (2012); Moon I., Lee J.-H., Seong J., Vehicle routing problem with time windows considering overtime and outsourcing vehicles, Expert Systems with Applications, 39, 18, pp. 13202-13213, (2012); Dorigo M., Maniezzo V., Colorni A., Ant system: optimization by a colony of cooperating agents, IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 26, 1, pp. 29-41, (1996); Schrage L., Formulation and structure of more complex/realistic routing and scheduling problems, Networks, 11, 2, pp. 229-232, (1981); Sariklis D., Powell S., A heuristic method for the open vehicle routing problem, Journal of the Operational Research Society, 51, 5, pp. 564-573, (2000); Li X., Tian P., Leung S. C., An ant colony optimization metaheuristic hybridized with tabu search for open vehicle routing problems, Journal of the Operational Research Society, 60, 7, pp. 1012-1025, (2009); Fleszar K., Osman I. H., Hindi K. S., A variable neighbourhood search algorithm for the open vehicle routing problem, European Journal of Operational Research, 195, 3, pp. 803-809, (2009); Ai T. J., Kachitvichyanukul V., Particle swarm optimization and two solution representations for solving the capacitated vehicle routing problem, Computers & Industrial Engineering, 56, 1, pp. 380-387, (2009); Ai T. J., Kachitvichyanukul V., A particle swarm optimization for the vehicle routing problem with simultaneous pickup and delivery, Computers & Operations Research, 36, 5, pp. 1693-1702, (2009); Eberhart R., Kennedy J., A new optimizer using particle swarm theory. Paper presented at the MHS’95, Proceedings of the Sixth International Symposium on Micro Machine and Human Science, (1995); Clarke J., McLay L., McLeskey J. T., Comparison of genetic algorithm to particle swarm for constrained simulation-based optimization of a geothermal power plant, Advanced Engineering Informatics, 28, 1, pp. 81-90, (2014); Elbir A., Ilhan H., Aydin N., The implementation of optimization methods for contrast enhancement, Computer Systems Science and Engineering, 34, 2, pp. 101-107, (2019); Wang X., Liu S., Zhang L., Highway cost prediction based on LSSVM optimized by initial parameters, Computer Systems Science and Engineering, 36, 1, pp. 259-269, (2021); Nguyen S., Ai T. J., Kachitvichyanukul V., Object library for evolutionary techniques ETLib: User’s guide, (2010); Solomon M. M., Algorithms for the vehicle routing and scheduling problems with time window constraints, Operations Research, 35, 2, pp. 254-265, (1987); Chen T.-L., Lin J.-T., Fang S.-C., A shadow-price based heuristic for capacity planning of TFT-LCD manufacturing, Journal of Industrial and Management Optimization, 6, 1, pp. 209-241, (2010)","H.-P. Fu; Department of Marketing and Distribution Management, National Kaohsiung University of Science and Technology, Taiwan; email: hpfu@nkust.edu.tw",null,"Tech Science Press",{"$nulls":5},2676192.0,null,"CSSEE",null,"English","Comput Syst Sci Eng","Article","Final","All Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85116709286"]
["Xue C.; Wen W.; Li S.","Xue, Chaogai (55558112800); Wen, Wen (57666390100); Li, Shumin (58604464600)","55558112800; 57666390100; 58604464600","Enterprise strategy analysis of synergy between cross-border e-commerce and logistics in a dynamic environment",2022.0,"Systems Science and Control Engineering",10.0,1.0,null,459.0,467.0,8.0,1.0,"10.1080/21642583.2022.2063200","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85129367932&doi=10.1080%2f21642583.2022.2063200&partnerID=40&md5=989dc0b44176f8b0f912d680d4962f61","School of Management Engineering, Zhengzhou University, Zhengzhou, China","Xue C., School of Management Engineering, Zhengzhou University, Zhengzhou, China; Wen W., School of Management Engineering, Zhengzhou University, Zhengzhou, China; Li S., School of Management Engineering, Zhengzhou University, Zhengzhou, China","In order to explore how cross-border e-commerce and logistics companies make decisions during synergy in a dynamic environment, this paper first establishes an evolutionary game model to study the influencing factors of enterprises’ strategies in the process of synergy in a dynamic environment. Then the study uses sensitivity analysis and numerical simulation to analyse the impact of different enterprises’ strategies on synergy. Finally, the synergistic strategies of enterprises in different dynamic environments are discussed. We found that: (1) capital and labour input of cross-border e-commerce platforms will affect the synergy. In a highly dynamic environment, the influences are greater. (2) There is a positive correlation between the technical level of the platform and synergistic degree, while the high technical level of logistics enterprises will inhibit synergy. However, in an unstable environment, the positive effect still exists, and the change in the logistics enterprise technology level has little effect on synergy. (3) The technical level of the cross-border e-commerce platform has the greatest impact on the benefits of both parties, and then is the lower cost of labour and capital input, while the technical level of logistics companies has little impact. © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.","Cross-border e-commerce; dynamic environment; evolutionary game; synergy","Sensitivity analysis; Cross-border; Cross-border e-commerce; Dynamic environments; E- commerces; e-Logistics; Enterprise strategies; Evolutionary games; Logistics company; Synergy; Technical levels; Electronic commerce",{"$nulls":4},"Humanities and Social Science Fund of Ministry of Education of China, (19YJA630096)","This work was supported by the Ministry of Education of Humanities and Social Science project [grant number 19YJA630096].","Bannova K., Aktaev N., Mathematical modelling of optimal tax trajectory within the framework of Cobb-Douglas model, Applied Economics Letters, pp. 1-7, (2019); Giuffrida M., Mangiaracina R., Perego A., Tumino A., Cross-border B2C e-commerce to China: An evaluation of different logistics solutions under uncertainty, International Journal of Physical Distribution & Logistics Management, 50, 3, pp. 355-378, (2019); Huo B., Ye Y., Zhao X., Wei J., Hua Z., Environmental uncertainty, specific assets, and opportunism in 3PL relationships: A transaction cost economics perspective, International Journal of Production Economics, 203, pp. 154-163, (2018); Li X., Zhao R., Research on optimization of cross-border e-commerce logistics chain based on the perspective of supply chain, Business Economic Research, 38, 12, pp. 76-79, (2019); Li Y., Guo H., Cooper S., Wang H., The influencing factors of the technology standard alliance collaborative innovation of emerging industry, Sustainability, 11, 24, (2019); Liu X., Zhao Z., An evolutionary game analysis on relational capital investment strategies of tourism supply chain alliance enterprises in an uncertain environment, Tourism Science, 33, 2, pp. 42-58, (2019); Ma S., Pan G., From cross-border e-commerce to global digital trading: A reexamination perspective from global transmission of Covid-2019, Journal of Hubei University (Philosophy and Social Science), 47, 5, pp. 119-132+169, (2020); Qian H., He J., Factors influencing synergy of cross-border e-commerce and cross-border logistics: An exploratory study based on ground theory, Industrial Economic Review, pp. 110-122, (2017); Qiu R., Dong H., Yuan H., Robust optimization model for multiple markets with uncertain discrete demand probability, Journal of Systems And Management, 25, 3, pp. 563-570, (2016); Seo E., Kim C., Kim K., A study on the mechanisms linking environmental dynamism to innovation performance, Sustainability, 12, 23, (2020); Sharma A., Adhikary A., Borah S., COVID-19’s impact on supply chain decisions: Strategic insights from NASDAQ 100 firms using twitter data, Journal of Business Research, 117, pp. 443-449, (2020); Yuan Q., The construction mechanism and algorithm of cross border E-commerce export logistics mode from the perspective of value chain, Journal of Intelligent and Fuzzy Systems, 37, 11, pp. 1-8, (2019); Zhang G., Wang W., Wang Q., (2018); Zhang X., Endogenous mechanism and development path of synergism of cross-border E-commerce and cross-border logistics from the perspective of global value chain, Contemporary Economic Management, 40, 8, pp. 14-18, (2018); Zhang X., Cross-border e-commerce and cross-border logistics synergy evaluation and improvement strategies, Business Economic Research, pp. 111-113, (2020)","W. Wen; School of Management Engineering, Zhengzhou University, Zhengzhou, China; email: ww425973@163.com",null,"Taylor and Francis Ltd.",{"$nulls":5},2.1642583E7,null,null,null,"English","Syst. Sci. Control Eng.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85129367932"]
["Yadav N.; Goyal S.","Yadav, Nidhi (57605871400); Goyal, Sonu (57209162143)","57605871400; 57209162143","Regaining partner trust in the food delivery business: case of Zomato",2022.0,"Emerald Emerging Markets Case Studies",12.0,2.0,null,1.0,32.0,31.0,1.0,"10.1108/EEMCS-10-2021-0341","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85128510282&doi=10.1108%2fEEMCS-10-2021-0341&partnerID=40&md5=bc7a59f63eec23da3b19707500d021d1","International Management Institute, New Delhi, India","Yadav N., International Management Institute, New Delhi, India; Goyal S., International Management Institute, New Delhi, India","Learning outcomes: The learning outcomes are as follows: to understand and examine the strategies that help platforms fight competition and manage networks; to analyse the role of platform governance in the management of the networks and partners’ trust; and to evaluate the strategic risks of disintermediation and multi-homing firms face while trying to sustain profits and capture value. Case overview/synopsis: The case presents the dilemma faced by Deepinder Goyal, the young founder and CEO of Zomato in formulating the growth strategy for its food delivery platform, struggling to retain its market leadership position amid intensifying competition and other challenges during the COVID-19 pandemic. Zomato has become a public company with an IPO announced in mid of July 2021. Therefore, there is growing expectation for profitability among its shareholders and investors considering tailwinds of COVID-19 crisis, which have given the push towards adoption of food delivery among the customers. This has also resulted in increased competition in the industry. On other hand, there is growing dissatisfaction among its restaurant partners who have been hit hard by COVID-19 and struggling for survival. CEO Deepinder has to find how he will ensure the long-term growth for Zomato to tap the growing food delivery market in India and regain its restaurant partner’s trust. Complexity Academic Level: The case is intended for post-graduate courses (MBA, PGDM) on digital business strategy or strategic management of technology-oriented businesses. The case can be used to understand the nature of competition and different strategies for platform-based businesses in the digital world. The case can also be used to study the role governance can play in efficient value creation and capture on the platform by the partner entities. Finally, the case also highlights how are platform businesses are coping with the Covid challenge. There are no specific prerequisites but knowledge on basic strategy concepts and platform business concepts will be good for better understanding. Level of difficulty is medium. Supplementary materials: Teaching notes are available for educators only. Subject code: CSS 11: Strategy. © 2022, Emerald Publishing Limited.","Competitive strategy; Digital strategy; E-commerce; Food delivery platform; Governance guidelines; Partner trust; Platform governance; Stakeholder management; Strategic management; Trust",{"$nulls":7},"Abbas M., India's growing data usage, smartphone adoption to boost digital India initiatives, (2021); Alam T., How restaurants in India are bypassing the duopoly of Zomato and Swiggy, (2021); Arora A., Indian food delivery market -evolution and road ahead, (2020); Bhushan R., Restaurants are looking beyond Swiggy, Zomato for food delivery, (2021); India online food delivery market to 2026 by delivery type, city, ordering platform, cuisine, ordering frequency & major Players - ResearchAndMarkets.com, (2021); Chadda R., Swiggy vs Zomato: Battle of India’s biggest food aggregator, (2020); Chandrasekaran K., Restaurants decry Zomato cancellation rules, (2021); Chengappa S., Amazon food’s reduced commission rate may hurt Swiggy, Zomato’s growth, (2021); Gosh D., Is Zomato running low on cash, (2019); Goyal D., Summary of all of Zomato’s COVID-19 related initiatives, (2020); Dey A., Zomato’s new survival plan in absence of food orders faces threat from JioMart, Kirana stores, (2020); I don't underestimate amazon. I don't fear them either: Zomato's Deepinder Goyal, (2021); NRAI seeks CCI intervention into Swiggy, Zomato ‘anti-competitive’ practices, (2021); What sets Swiggy apart from Zomato, Tinyowl, Foodpanda: All you want to know in 5 pts, (2015); Goyal D., A snapshot of our international presence, (2016); Future of Indian food and beverage industry post pandemic, (2020); What’s the story of Zomato?, (2019); Who leads the food delivery race between Zomato and Swiggy in India, (2021); Mittal A., Zomato makes its takeaway service available to restaurants at zero commission, (2020); Mittal A., Swiggy, Zomato back to discounting to attract new users, (2021); Online food delivery market - India (part 1, (2018); Parmar N., Foodpanda business model: Check everything to have insight into is its working & revenue model, (2022); Patwa P., Why more restaurants are preferring to go digital, and away from third-party aggregators, (2021); Peerzada A., Swiggy revenue jumps 115% to Rs 2,776 cr and losses up 61% to Rs 3,768 cr, (2021); Pengonda P., Why covid-19 has been a shot in the arm for online food delivery firms, (2021); Food delivery volumes in India reach pre-COVID-19 peaks: Deepinder Goyal, CEO, Z, (2020); Zomato FY20 revenue jumps over two-fold to Rs 2,960 crore, (2020); Qadri M., The three business pillars that drive Zomato’s revenue, (2020); Raman P., Zomato: a shining armour in the foodtech sector, Journal of Information Technology Case and Application Research, 20, 3-4, (2018); Sahay P., Restaurants look for alternatives as Swiggy, Zomato serve them raw deal, (2021); Sahay P., Swiggy goes the Peppo, DotPe way; pilots ‘order direct’ in Mumbai, (2021); Sharma S., Mittal A., ETtech exclusive: Zomato may invest $100 million in Grofers as e-grocer shelves US IPO plan, (2021); Shrivastava A., Peermohamed A., Orders go down as Zomato & Swiggy raise delivery fees, (2020); Singh M., Uber sold its food delivery business in India to Zomato for $206M, (2020); Soni Y., Weak last mile delivery may hurt amazon’s ambitions in India’s food delivery market, (2021); (2020); Revenue of Zomato from financial year 2016 to 2020, (2020); Suresh H., Ranipeta S.S., Why 1,200+ restaurants are choosing to log off food apps like Zomato and Dineout, (2019); Annual report; Zomato red herring prospectus, (2021); Financial statement Q1, Q2 FY22, (2021); NRAI approaches CCI against 'anti-competitive practices' by Zomato, Swiggy, (2021); Soni S., NRAI files more info with CCI on exorbitant commission, delayed payment, against IPO-bound Zomato, Swiggy, (2021); Zomato success story, (2019)","N. Yadav; International Management Institute, New Delhi, India; email: nidhi.f18@imi.edu",null,"Emerald Group Holdings Ltd.",{"$nulls":5},2.0450621E7,null,null,null,"English","Emerald Emerg. Mark. Case Stud.","Article","Final",null,"Scopus","2-s2.0-85128510282"]
["Javaid K.; Siddiqa A.; Naqvi S.A.Z.; Ditta A.; Ahsan M.; Khan M.A.; Mahmood T.; Khan M.A.","Javaid, Kumail (57221926160); Siddiqa, Ayesha (57200932715); Naqvi, Syed Abbas Zilqurnain (57203482225); Ditta, Allah (57193528024); Ahsan, Muhammad (57212940288); Khan, M.A. (57215096761); Mahmood, Tariq (57208210697); Khan, Muhammad Adnan (57226797214)","57221926160; 57200932715; 57203482225; 57193528024; 57212940288; 57215096761; 57208210697; 57226797214","Explainable Artificial Intelligence Solution for Online Retail",2022.0,"Computers, Materials and Continua",71.0,2.0,null,4425.0,4442.0,17.0,2.0,"10.32604/cmc.2022.022984","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85122747754&doi=10.32604%2fcmc.2022.022984&partnerID=40&md5=980b506ceadc33d9ce6dd07476debd4a","Department of Computer Science, University of South Asia, Lahore, 54000, Pakistan; Department of Mechatronics and Control Engineering, University of Engineering and Technology, Lahore, 54000, Pakistan; Department of Information Sciences, Division of Science and Technology, University of Education, Lahore, 54000, Pakistan; Riphah School of Computing and Innovation, Faculty of Computing, Riphah International University, Lahore Campus, Lahore, 54000, Pakistan; Division of Science and Technology, University of Education, Lahore, 54000, Pakistan; Pattern Recognition and Machine Learning Lab, Department of Software, Gachon University, Seongnam, 13557, South Korea","Javaid K., Department of Computer Science, University of South Asia, Lahore, 54000, Pakistan; Siddiqa A., Department of Mechatronics and Control Engineering, University of Engineering and Technology, Lahore, 54000, Pakistan; Naqvi S.A.Z., Department of Mechatronics and Control Engineering, University of Engineering and Technology, Lahore, 54000, Pakistan; Ditta A., Department of Information Sciences, Division of Science and Technology, University of Education, Lahore, 54000, Pakistan; Ahsan M., Department of Mechatronics and Control Engineering, University of Engineering and Technology, Lahore, 54000, Pakistan; Khan M.A., Riphah School of Computing and Innovation, Faculty of Computing, Riphah International University, Lahore Campus, Lahore, 54000, Pakistan; Mahmood T., Division of Science and Technology, University of Education, Lahore, 54000, Pakistan; Khan M.A., Pattern Recognition and Machine Learning Lab, Department of Software, Gachon University, Seongnam, 13557, South Korea","Artificial intelligence (AI) and machine learning (ML) help in making predictions and businesses to make key decisions that are beneficial for them. In the case of the online shopping business, it’s very important to find trends in the data and get knowledge of features that helps drive the success of the business. In this research, a dataset of 12,330 records of customers has been analyzed who visited an online shopping website over a period of one year. The main objective of this research is to find features that are relevant in terms of correctly predicting the purchasing decisions made by visiting customers and build ML models which could make correct predictions on unseen data in the future. The permutation feature importance approach has been used to get the importance of features according to the output variable (Revenue). Five ML models i.e., decision tree (DT), random forest (RF), extra tree (ET) classifier, Neural networks (NN), and Logistic regression (LR) have been used to make predictions on the unseen data in the future. The performance of each model has been discussed in detail using performance measurement techniques such as accuracy score, precision, recall, F1 score, and ROC-AUC curve. RF model is the best model among all five chosen based on accuracy score of 90% and F1 score of 79% followed by extra tree classifier. Hence, our study indicates that RF model can be used by online retailing businesses for predicting consumer buying behaviour. Our research also reveals the importance of page value as a key feature for capturing online purchasing trends. This may give a clue to future businesses who can focus on this specific feature and can find key factors behind page value success which in turn will help the online shopping business. © 2022 Tech Science Press. All rights reserved.","Explainable artificial intelligence; Neural network; Online retail; Random forest regression","Decision trees; Digital storage; Electronic commerce; Neural networks; Random forests; Sales; Explainable artificial intelligence; Extra-trees; F1 scores; Machine learning models; Neural-networks; Online retails; Online shopping; Random forest regression; Random forests; Tree classifiers; Forecasting",{"$nulls":6},"Saxena A., Rani U., Agarwal I., Sreedharan S. M., Introduction to machine learning, Big Data and Artificial Intelligence for Healthcare Applications, 1, pp. 23-66, (2021); Ahmeda R. A. E. D., Shehaba M. E., Morsya S., Mekawiea N., Performance study of classification algorithms for consumer online shopping attitudes and behavior using data mining, 5th IEEE Int. Conf. Communication Systems and Network Technologies, pp. 1344-1349, (2015); Morton A., Marzban E., Giannoulis G., Patel A., Aparasu R., Et al., A comparison of supervised machine learning techniques for predicting short-term in-hospital length of stay among diabetic patients, 13th Int. Conf. on Machine Learning and Applications, pp. 1-5, (2014); Joshi R., Gupte R., Saravanan P., A random forest approach for predicting online buying behavior of Indian customers, Theoretical Economics Letters, 8, 3, pp. 448-456, (2018); Effendy V., Baizal Z. A., Handling imbalanced data in customer churn prediction using combined sampling and weighted random forest, 2nd IEEE Int. Conf. on Information and Communication Technology, pp. 325-330, (2014); Boyer K. K., Hult G. T. M., Customer behavior in an online ordering application: A decision scoring model, Decision Sciences, 36, 4, pp. 569-598, (2005); Hadden J., Tiwari A., Roy R., Ruta D., Churn prediction: Does technology matter, International Journal of Intelligent Technology, 1, 2, pp. 104-110, (2006); Xie Y., Li X., Ngai E., Ying W., Customer churn prediction using improved balanced random forests, Expert Systems with Applications, 36, 3, pp. 5445-5449, (2009); Islam M. M., Lam A., Fukuda H., Kobayashi Y., Kuno Y. J. R. J., An intelligent shopping support robot: Understanding shopping behavior from 2d skeleton data using gru network, Robomech Journal, 6, 1, pp. 1-10, (2019); Sharma A., Shafiq M. O., Predicting purchase probability of retail items using an ensemble learning approach and historical data, 19th IEEE Int. Conf. on Machine Learning and Applications, pp. 723-728, (2020); Hafez M. M., Vilas A. F., Redondo R. P. D., Pazo H. O., Classification of retail products: From probabilistic ranking to neural networks, Applied Sciences, 11, 9, (2021); Roshan S., Online shopper’s intention, Kaggle, (2019); Sakar O., Polat S. O., Katircioglu M., Kastro Y., Real-time prediction of online shoppers’ purchasing intention using multilayer perceptron and LSTM recurrent neural networks, Neural Computing Applications, 31, 10, pp. 6893-6908, (2019); Baati K., Mohsil M., Real-time prediction of online shoppers’ purchasing intention using random forest, IFIP Advances in Information and Communication Technology, pp. 43-51, (2020); Liu H., Lang B., Machine learning and deep learning methods for intrusion detection systems: A survey, Applied Sciences, 9, 20, pp. 4396-4406, (2019); Chiang W. Y. K., Zhang D., Zhou L., Predicting and explaining patronage behavior toward web and traditional stores using neural networks: A comparative analysis with logistic regression, Decision Support Systems, 41, 2, pp. 514-531, (2006); Charbuty B., Abdulazeez A., Classification based on decision tree algorithm for machine learning, Journal of Applied Science Technology Trends, 2, 1, pp. 20-28, (2021); Liaw A., Wiener M., Classification and regression by random Forest, R News, 2, 3, pp. 18-22, (2002); Sharaff A., Gupta H., Extra-tree classifier with metaheuristics approach for email classification, Int. Conf. on Artificial Intelligence, Soft Computing, pp. 189-197, (2019); Ziboon H. T., Thabit A. A., A new proposed adaptive cognitive radio detection system based on MLP neural network for different modulation schemes, ARPN Journal of Engineering Applied Sciences, 12, 2, pp. 521-527, (2017); Jiao Y., Du P., Performance measures in evaluating machine learning based bioinformatics predictors forclassifications, Quantitative Biology, 4, 4, pp. 320-330, (2016); Tolosi Altmann L., Sander O., Lengauer T. J. B., Permutation importance: A corrected feature importance measure, Bioinformatics, 26, 10, pp. 1340-1347, (2010)","M.A. Khan; Pattern Recognition and Machine Learning Lab, Department of Software, Gachon University, Seongnam, 13557, South Korea; email: adnan@gachon.ac.kr",null,"Tech Science Press",{"$nulls":5},1.5462218E7,null,null,null,"English","Comput. Mater. Continua","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85122747754"]
["Duong Q.H.; Zhou L.; Meng M.; Nguyen T.V.; Ieromonachou P.; Nguyen D.T.","Duong, Quang Huy (57306075200); Zhou, Li (57204687859); Meng, Meng (34771609000); Nguyen, Truong Van (57194854988); Ieromonachou, Petros (15728987900); Nguyen, Duy Tiep (57217776073)","57306075200; 57204687859; 34771609000; 57194854988; 15728987900; 57217776073","Understanding product returns: A systematic literature review using machine learning and bibliometric analysis",2022.0,"International Journal of Production Economics",243.0,null,108340.0,null,null,null,25.0,"10.1016/j.ijpe.2021.108340","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85117717957&doi=10.1016%2fj.ijpe.2021.108340&partnerID=40&md5=ffb58fbd5a2052f346f36df86b11cfcd","Faculty of Business, University of Greenwich, London, SE10 9LS, UK, United Kingdom; School of Management, University of Bath, Bath, BA2 7AY, UK, United Kingdom; Brunel Business School, Brunel University London, Uxbridge, UB8 3PH, UK, United Kingdom","Duong Q.H., Faculty of Business, University of Greenwich, London, SE10 9LS, UK, United Kingdom; Zhou L., Faculty of Business, University of Greenwich, London, SE10 9LS, UK, United Kingdom; Meng M., School of Management, University of Bath, Bath, BA2 7AY, UK, United Kingdom; Nguyen T.V., Brunel Business School, Brunel University London, Uxbridge, UB8 3PH, UK, United Kingdom; Ieromonachou P., Faculty of Business, University of Greenwich, London, SE10 9LS, UK, United Kingdom; Nguyen D.T., Faculty of Business, University of Greenwich, London, SE10 9LS, UK, United Kingdom","Product Returns (PR) are an inevitable yet costly process in business, especially in the online marketplace. How to deal with the conundrums has attracted a great deal of attention from both practitioners and researchers. This paper aims to synthesise research developments in the PR domain in order to provide an insightful picture of current research and explore future directions for the research community. To ensure research rigour, we adapt a six-step framework - defining the topic, searching databases, cleaning and clustering data, paper selection, content analysis, and discussion. A hybrid approach is adopted for clustering and identifying the distribution and themes in a large number of publications collected from academic databases. The hybrid approach combines machine learning topic modelling and bibliometric analysis. The machine learning results indicate that the overall research can be clustered into three groups: (1) operations management of PR, covering (re)manufacturing network design, product recovery, reverse distribution, and quality of cores; (2) retailer and (re)manufacturer issues including return policy, channel, inventory, pricing, and information strategies; and (3) customer's psychology, experience, and perception on marketing-operation interface. Furthermore, from the content analysis, five potential future directions are discussed, namely digitalisation in the context of PR; globalisation versus localisation in the context of PR; multi-layer (i.e., retailer, manufacturer, logistics provider, online platform) and multi-channel (i.e., online, offline, dual and omni channel) oriented bespoke return policy; understanding and predicting customer return behaviour via online footprints; and customer return perception across the marketing–operations interface. © 2021 Elsevier B.V.","Bibliometric analysis; Framework; Literature review; Machine learning; Product returns; Topic modelling","Electronic commerce; Industrial research; Information management; Machine learning; Product design; Quality control; Bibliometrics analysis; Content analysis; Framework; Hybrid approach; Literature reviews; Marketing-operations interfaces; Product returns; Return policy; Systematic literature review; Topic Modeling; Sales",{"$nulls":6},{"$cut":{"chars":32535,"head":"Abdulla H., Ketzenberg M., Abbey J.D., Taking stock of consumer returns: a review and classification of the literature, J. Oper. Manag., 65, pp. 560-605, (2019); Ai X., Chen J., Zhao H., Tang X., Competition among supply chains: implications of full returns policy, Int. J. Prod. Econ., 139, pp. 257-265, (2012); AJG, Academic Journal Guide, (2018); Akcay Y., Boyacbox T., Zhang D., Selling with money-back guarantees: the impact on prices, quantities, and retail profitability, Prod. Oper. Manag., 22, pp. 777-791, (2013); Akturk M.S., Ketzenberg M., Yildiz B., Managing consumer returns with technology-enabled countermeasures, Omega (United Kingdom) 102, (2021); Alumur S.A., Nickel S., Saldanha-Da-Gama F., Verter V., Multi-period reverse logistics network design, Eur. J. Oper. Res., 220, pp. 67-78, (2012); Ambilkar P., Dohale V., Gunasekaran A., Bilolikar V., Product returns management: a comprehensive review and future research agenda, Int. J. Prod. Res., (2021); Anderson E.T., Hansen K., Simester D., The option value of returns: theory and empirical evidence, Mark. Sci., 28, pp. 405-423, (2009); Aras N., Boyaci T., Verter V., The effect of categorizing returned products in remanufacturing, IIE Trans. (Institute Ind. Eng., 36, pp. 319-331, (2004); Assid M., Gharbi A., Hajji A., Production control of failure-prone manufacturing-remanufacturing systems using mixed dedicated and shared facilities, Int. J. Prod. Econ., 224, (2020); Autry C.W., Formalization of reverse logistics programs: a strategy for managing liberalized returns, Ind. Market. Manag., 34, pp. 749-757, (2005); Bandyopadhyay S., Paul A.A., Equilibrium returns policies in the presence of supplier competition, Mark. Sci., 29, pp. 846-857, (2010); Barclaycard, Return to Sender: Retailers Face a ‘Phantom Economy’ of £7bn Each Year as Shopper Returns Continue to Rise [WWW Document]. Barclay, (2018); Bastian M., Heymann S., Jacomy M., Gephi: an open source software for exploring and manipulating networks, International AAAI Conference on Weblogs and Social Media, (2009); Why Some Countries Are Shipping Back Plastic Waste, (2019); Bechwati N.N., Siegal W.S., The impact of the prechoice process on product returns, J. Market. Res., 42, pp. 358-367, (2005); Bijmolt T.H.A., Broekhuis M., de Leeuw S., Hirche C., Rooderkerk R.P., Sousa R., Zhu S.X., Challenges at the marketing–operations interface in omni-channel retail environments, J. Bus. Res., 122, pp. 864-874, (2021); Blei D.M., Ng A.Y., Jordan M.I., Latent dirichlet allocation, J. Mach. Learn. Res., (2003); Bonifield C., Cole C., Schultz R.L., Product returns on the Internet: a case of mixed signals?, J. Bus. Res., 63, pp. 1058-1065, (2010); Borenich A., Dickbauer Y., Reimann M., Souza G.C., Should a manufacturer sell refurbished returns on the secondary market to incentivize retailers to reduce consumer returns?, Eur. J. Oper. Res., 282, pp. 569-579, (2020); Borner K., Chen C., Boyack K.W., Visualizing knowledge domains, Annu. Rev. Inf. Sci. Technol., (2003); Bower A.B., Maxham J.G., Return shipping policies of online retailers: normative assumptions and the long-term consequences of fee and free returns, J. Mark., 76, pp. 110-124, (2012); Boyack K.W., Klavans R., Co-citation analysis, bibliographic coupling, and direct citation: which citation approach represents the research front most accurately?, J. Am. Soc. Inf. Sci. Technol., (2010); Casalin F., Dia E., Information and reputation mechanisms in auctions of remanufactured goods, Int. J. Ind. Organ., 63, pp. 185-212, (2019); Chae B., Olson D., A topical exploration of the intellectual development of decision sciences 1975–2016, Decision Sciences, pp. 543-566, (2021); Che Y.-K., Customer return policies for experience goods, J. Ind. Econ., 44, (1996); Chen B., Chen J., When to introduce an online channel, and offer money back guarantees and personalized pricing?, Eur. J. Oper. Res., 257, pp. 614-624, (2017); Chen J., The impact of sharing customer returns information in a supply chain with and without a buyback policy, Eur. J. Oper. Res., 213, pp. 478-488, (2011); Ch"}},"L. Zhou; Faculty of Business, University of Greenwich, London, SE10 9LS, United Kingdom; email: Li.Zhou@gre.ac.uk",null,"Elsevier B.V.",{"$nulls":5},9255273.0,null,"IJPCE",null,"English","Int J Prod Econ","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85117717957"]
["Shaopeng H.; Lee O.; Ahn J.","Shaopeng, Hou (35332856500); Lee, Ook (7103020210); Ahn, Jongchang (55319971300)","35332856500; 7103020210; 55319971300","A STUDY on the INFLUENCING FACTORS of CONSUMERS' WILLINGNESS to BUY LARGE MUSICAL INSTRUMENTS ONLINE",2021.0,"Journal of Theoretical and Applied Information Technology",99.0,24.0,null,5748.0,5761.0,13.0,0.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85122230719&partnerID=40&md5=63ff0e2af49a623f4ea3a6975c9ba129","Department of Information Systems, Hanyang University, South Korea","Shaopeng H., Department of Information Systems, Hanyang University, South Korea; Lee O., Department of Information Systems, Hanyang University, South Korea; Ahn J., Department of Information Systems, Hanyang University, South Korea","Along with the fast development of the Internet and the continuous improvement of e-commerce platforms, Chinese consumption has dramatically changed. Online shopping is gaining wider popularity among consumers. In recent years, as the upstream and downstream industries relevant to e-commerce continue to develop, the types of online shopping have once again been widened. Large musical instruments such as pianos and guitars are also sold on e-commerce platforms. Their market share is gradually expanded by under more reasonable and transparent prices and lower logistics costs. Compared with the fast-growing market scale, we have few theoretical literatures concerning online shopping. At present, most of the study mainly focuses on the development of information technology and customer behaviors on the whole platform, and slightly ignores specific theoretical research on the art industry. Based on previous information systems theory, seven hypotheses about the behavior willingness for musical instruments online were put forward. A reasonable structural equation model is constructed; an empirical analysis on the collected valid 364 data is carried out; and six hypotheses are tested by analyzing the relation between path coefficient and variables. Moreover, perceived trust and perceived risk are two independent variables in the same dimension. The hypothesis that the result was not accepted is elaborated, and management and marketing suggestions are provided for managers of the online shopping platform. © 2021 Little Lion Scientific","Behavior willingness; Influencing factors; Information systems; Musical instrument sales; Online shopping; Structural equation model",{"$nulls":7},"People's Daily, the scale of online retail continues to grow, the number of online shopping users nationwide increased by 100 million over the previous year, (2020); 2020 E-commerce Industry Enterprise Data Report; Krylov P. A., Volodin O. B., Malyshev A. 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E., Marketing manag ement: Analysis, planning, implementation, and control, 9, (1997); Wood C. M., Schecr L. K., Incorporating Perceived Risk into Models of Consumer Deal Assessment and Purchase Intent, Advances in consumer research, 23, 1, pp. 399-404, (1996); Kovacich G., Electronic internet business and security, Computer and Security, 17, 2, pp. 129-135, (1998); Liao Z., Cheung M. T., Internet-based e-shopping and consumer attitudes: an empirical study, Information & Management, 38, 5, pp. 299-306, (2001); Hong I. B., Cha H. S., The mediating role of consumer trust in an online merchant in predicting purchase intention, International Journal of Information Management, 33, 6, pp. 927-939, (2013); Meng F., The influence factors of opinion leaders on consumers' purchasing intention under the socialized business environment, (2012); Jarvenpaa S. L., Tractinsky N., Consumer L., Trust in an Internet Store: A Cross-Cultural Validation, Journal of Computer Mediated Communication, 12, pp. 21-36, (1999); Davis F. D., Perceived usefulness, perceived ease of use, and user acceptance of informationtechnologies, MIS Quarterly, 13, 2, pp. 319-340, (1989); Davis F. D., Viswanath V., A critical assessment of potential measurement biases in the technology acceptance model: three experiments, International Journal of Human-Computer Studies, 45, 1, pp. 19-45, (1996); Igbaria M., Zinatelli N., Cragg P., Personal Computing Acceptance Factors in Small Firms: A StructuralEquation Model, Mis Quarterly, 21, 3, pp. 279-305, (1997); Arning K., Ziefle M., Understanding age differences in PDA acceptance and performance, Computers in Human Behavior, 23, 6, pp. 2904-2927, (2007); Djamasbi S., Strong D. M., Dishaw M., Affect and acceptance: Examining the effects of positive moodon the technology acceptance model, Decision Support Systems, 48, 2, pp. 383-394, (2010); Chew A. A., The adoption of M-commerce in the United States, (2006); Legris P., Ingham J., Collerette P., Why do people use information technology? A critical review of the technology acceptance model, Information & Management, 40, 3, pp. 191-204, (2003); Venkatesh V., Davis F. D., A Theoretical Extension of the Technology Acceptance Model: FourLongitudinal Field Studies, Management Science, 46, 2, pp. 186-204, (2000); Davis F. D., A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal FieldStudies, Management Science, 46, 2, pp. 186-204, (2000); Ajzen I., The theory of planned behavior. Organizational Behavior and Human Decision Processes, Organizational Behavior and Human Decision Processes, 50, 2, pp. 179-211, (1991); Fishbein M., Ajzen I., Beliefs, attitudes, intention, and behavior: An introduction of theory andresearch, Addison-Wesley, 82, 2, (1975); Taylor S., Todd P. A., Understanding information technology usage: A test of competingmodels, Information Systems Research, 6, 2, pp. 144-176, (1995); Karahanna E., Straub D. W., Chervany N. L., Information technology adoption across time: A cross-sectional comparison of pre-adoption and postadoption beliefs, MIS Quarterly, 23, 2, pp. 183-213, (1999); Bandura A., Self-efficacy: Toward a unifying theory of behavioral change, Psychological Review, 84, (1977); Lee M. K., Turban E., A trust model for consumer internet shopping, International Journal of Electronic Commerce, 6, 1, pp. 75-91, (2001); Jeyaraj A., Rottman J. W., Lacity M. 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Y., On the network effect in Web 2.0 applications, Electronic Commerce Research and Applications, 11, 2, pp. 142-151, (2012); Straub D., Boudreau M.C., Gefen D., Validation guidelines for IS positivist research, Communications of the Association for Information Systems, 13, pp. 380-427, (2004); Carmines E. G., Zeller R. A., Reliability and Validity Assessment, (1979); Eisinga R., Grotenhuis M. T., Pelzer B., The reliability of a two-item scale: Pearson, Cronbach, or Spearman-Brown?, International Journal of Public Health, 58, 4, pp. 637-642, (2013); Straub D., Boudreau M. C., Gefen D., Validation guidelines for IS positivist research, Communications of the Association for Information Systems, 13, pp. 380-427, (2004); Manson E., Bramble W., Understanding and conducting research, (1989); Hair J. F., Black W. C., Babin B. J., Anderson R. E., Tatham R. L., Multivariate data analysis, (2006); Mcdonald G. 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["Liu H.; Liu T.","Liu, Hongqing (57682800200); Liu, Ting (57217014155)","57682800200; 57217014155","The Application of Artificial Intelligence Oriented to the Internet of Things Technology in the Complexity of Digital Crossborder Trade",2022.0,"Wireless Communications and Mobile Computing",2022.0,null,2339399.0,null,null,null,1.0,"10.1155/2022/2339399","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85129977014&doi=10.1155%2f2022%2f2339399&partnerID=40&md5=3ae7397c65a02409e150239abdb5d9c8","College of Finance and Economics, Sichuan International Studies University, Chongqing, 400031, China; Business School, Hunan International Economics University, Changsha, 410205, China","Liu H., College of Finance and Economics, Sichuan International Studies University, Chongqing, 400031, China; Liu T., Business School, Hunan International Economics University, Changsha, 410205, China","With the continuous update of technologies such as cloud computing, big data, AI, and 5G, various IoT services have also been developed. Various IoT terminals have emerged one after another, and the number of access terminals has also risen sharply. With the development and popularization of a new generation of artificial intelligence technology, the Internet of Things mainly connects various objects to each other in an agreed manner through various sensing devices and conducts wireless communication and data exchange to achieve object-to-object communication, positioning, traceability, intelligent identification, and management. The Internet of Things has broad application prospects in many aspects such as intelligent robots, transportation, and intelligent buildings. Accurate node positioning is considered to be the focus of the application of the Internet of Things in geographic and network location services. More and more experts and scholars have begun to worry about the future development of artificial intelligence technology. While artificial intelligence technology provides convenience to the society, it may also cause huge hidden dangers to the public safety of the entire society. Therefore, it is necessary to make decisions about the technical risks of artificial intelligence. Philosophical analysis has certain historical, practical significance, and theoretical value. Internet technology innovation and digital technology innovation continue to emerge. Digital trade has become a typical feature of the current economic structural transformation, and it is also a new driving force for countries to participate in the division of labor in the global value chain. At present, the scale of global digital trade continues to expand, but there are still many restrictions on digital trade rules. Digital trade tariff barriers and nontariff barriers in digital trade such as crossborder data flow restrictions, intellectual property infringements, and personal information protection are bound to have an impact on the global value chain division of labor system. IoT technology-oriented artificial intelligence accelerates the logistics speed and tracking efficiency of digital cross-border trade, improves consumers' willingness to spend, and promotes the development of the entire e-commerce trade field.  © 2022 Hongqing Liu and Ting Liu.",null,"5G mobile communication systems; Artificial intelligence; Big data; Electronic data interchange; Ethical technology; Information management; Intelligent buildings; Intelligent robots; Access terminals; Artificial intelligence technologies; Cloud-computing; Continuous updates; Cross-border trades; Division of labor; Global value chain; Internet of things technologies; Sensing devices; Wireless communications; Internet of things",{"$nulls":6},"Chinthapalli U.R., Bommisetti R.K., Kondamudi B.R., Bagale G., Satyanarayana R., Isolated stakeholders' behavior towards fintech assisted by artificial intelligence technology, Annals of Operations Research, (2021); Fasee U., Zaka U., Sheeraz A., Ihtesham U., Saeed U., Javed I., Traffic priority based delay-aware and energy efficient path allocation routing protocol for wireless body area network, Journal of Ambient Intelligence and Humanized Computing, 10, 10, pp. 3775-3794, (2019); 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Liu; Business School, Hunan International Economics University, Changsha, 410205, China; email: liuting_vip@outlook.com",null,"Hindawi Limited",{"$nulls":5},1.5308669E7,null,null,null,"English","Wireless Commun. Mobile Comput.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85129977014"]
["Liu X.","Liu, Xia (57545234800)",5.75452348E10,"E-Commerce Precision Marketing Model Based on Convolutional Neural Network",2022.0,"Scientific Programming",2022.0,null,4000171.0,null,null,null,5.0,"10.1155/2022/4000171","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85126960423&doi=10.1155%2f2022%2f4000171&partnerID=40&md5=c0ab925f0b142e515fae72208dace1b4","Shandong University of Finance and Economics, Jinan, Shandong, China","Liu X., Shandong University of Finance and Economics, Jinan, Shandong, China","With the rapid development of network and informatization of the consumer market in my country, the application and maturity of technologies such as the Internet, terminal equipment, logistics, and payment and the continuous improvement of people's consumption concepts, online shopping has gradually become the mainstream purchase method for Chinese consumers, and e-commerce has gradually become one of the important driving forces to promote the sustained and vigorous development of China's economy. Under the traditional marketing model, companies do not fully understand the needs of users. The sales staff's thinking is only how to sell products to users. They do not know the specific consumer needs, so they can only focus on the product. Based on these foundations, this research uses convolutional neural networks and applies this model to precision marketing to obtain accurate portraits of consumers, thereby increasing the company's turnover. After comparing different models and conducting some experiments, it is concluded that (1) through the collection and analysis of W enterprise data, the training and testing conditions of the CNN model, LSTM model, LSTM attention model, and CNN + LSTM attention model are compared. It is concluded that the CNN + LSTM attention model and the LSTM attention model perform better, and the accuracy of testing and training is higher. (2) Through the fitting of the model, it is found that Sn(%) = 70.71, Sp(%) = 86.25, Acc(%) = 81.07, and MCC = 0.752 of the CNN + LSTM attention model are the best fitting models. The men and women stratification and gender stratification of users are predicted, and it is found that men in the W company are the main purchasing power, and in the age stratification, it is found that the population of 41-50 accounts for the highest proportion. (3) The average accuracy rate of the LSTM attention model is as high as 66.6%, the average recall rate is 82.3%, and the F1 score is 73.1%. This model has met expectations for precision marketing forecasts. (4) Using the CNN + LSTM attention model to predict the marketing input for the next year, it is found that the use of precision marketing will increase the profit of W company. The average annual data show that the monthly revenue of precision marketing has increased by 73.5%.  © 2022 Xia Liu.",null,"Convolution; Convolutional neural networks; Electronic commerce; Forecasting; Sales; Attention model; Consumer market; Continuous improvements; Convolutional neural network; Equipment logistics; Informatization; Marketing models; Model-based OPC; Precision marketings; Terminal equipment; Long short-term memory",{"$nulls":6},"Xian-Ming X.I., Wang L., The era of E-commerce marketing development, Journal of Harbin University of Commerce(Social Science Edition), 93, 5, pp. 58-67, (2006); Sawhney M., Precision marketing: The new rules for attracting, retaining, and leveraging profitable customers, Akuntansi Pegawai, 93, 3, pp. 158-165, (2004); Liu Z.Y., Study on precision marketing method, Journal of Shanghai Jiaotong University, 56, 65, pp. 32-45, (2007); Zhuo Z., Chen S., Chau K.Y., A new model of manufacturer's optimal product supply strategy in the context of precision marketing: Based on real demand pattern, Mathematical Problems in Engineering, 59, 2, pp. 62-98, (2020); 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Chen G., Li S., Research on location fusion of spatial geological disaster based on fuzzy SVM, Computer Communications, 153, pp. 538-544, (2020); Sun G., Chen C.-C., Bin S., Study of cascading failure in multisubnet composite complex networks, Symmetry, 13, 3, (2021); Kang K., Li H., Yan J., T-CNN: Tubelets with convolutional neural networks for object detection from videos, IEEE Transactions on Circuits and Systems for Video Technology, 28, 10, pp. 2896-2907, (2018); Li S., Chan A.B., 3D human pose estimation from monocular images with deep convolutional neural network, Asian Conference on Computer Vision, 12, 15, pp. 56-72, (2014); Lakhani P., Sundaram B., Deep learning at chest radiography: Automated classification of pulmonary tuberculosis by using convolutional neural networks, Radiology, 3, 5, pp. 23-51, (2017)","X. Liu; Shandong University of Finance and Economics, Shandong, Jinan, China; email: 20088532@sdufe.edu.cn",null,"Hindawi Limited",{"$nulls":5},1.0589244E7,null,"SCIPE",null,"English","Sci. Program","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85126960423"]
["Sanabria-Rey J.G.; Solano-Charris E.L.; Vega-Mejía C.A.; Quintero-Araújo C.L.","Sanabria-Rey, José G. (57223089491); Solano-Charris, Elyn L. (35238939800); Vega-Mejía, Carlos Alberto (36807370500); Quintero-Araújo, Carlos L. (55888087100)","57223089491; 35238939800; 36807370500; 55888087100","Solving Last-Mile Deliveries for Dairy Products Using a Biased Randomization-Based Spreadsheet. A Case Study",2022.0,"American Journal of Mathematical and Management Sciences",41.0,1.0,null,51.0,69.0,18.0,1.0,"10.1080/01966324.2021.1910886","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85104781682&doi=10.1080%2f01966324.2021.1910886&partnerID=40&md5=22ab75b3003747ce675edac49a64ab9c","Alumni of the Master Program in Operations Management, International School of Economics and Administrative Sciences, Universidad de La Sabana, Chia, Colombia; Operations & Supply Chain Management Research Group, International School of Economics and Administrative Sciences, Universidad de La Sabana, Chia, Colombia","Sanabria-Rey J.G., Alumni of the Master Program in Operations Management, International School of Economics and Administrative Sciences, Universidad de La Sabana, Chia, Colombia; Solano-Charris E.L., Operations & Supply Chain Management Research Group, International School of Economics and Administrative Sciences, Universidad de La Sabana, Chia, Colombia; Vega-Mejía C.A., Operations & Supply Chain Management Research Group, International School of Economics and Administrative Sciences, Universidad de La Sabana, Chia, Colombia; Quintero-Araújo C.L., Operations & Supply Chain Management Research Group, International School of Economics and Administrative Sciences, Universidad de La Sabana, Chia, Colombia","During recent years, Last-mile deliveries (LMD) have become relevant due to its application in e-commerce, urban logistics, and food delivery among others. This work addresses an LMD denoted as a Vehicle Routing Problem with time windows (VRPTW) and aims to minimize total time of the distribution process (i.e., makespan). The LMD is an NP-Hard problem that refers to the delivery of goods from a consolidation center to a destination. For solving the problem, a spreadsheet-based solution that employs a multi-start algorithm based on the biased-randomized version of the nearest neighbor heuristic is introduced. Real historical data of last-mile deliveries for dairy products in Bogotá (Colombia) was considered for evaluating our proposed method. Computational experiments are carried out to show the competitiveness of our method in terms of makespan, number of vehicles, average vehicle occupancy, average load and costs. Some insights for future works are also provided. © 2021 Taylor & Francis Group, LLC.","Last-mile deliveries; multi-start algorithm; nearest neighbor; spreadsheet; VRPTW","Contracts; Dairies; NP-hard; Spreadsheets; Vehicle routing; Vehicles; Average vehicle occupancies; Computational experiment; Delivery of goods; Distribution process; ITS applications; Nearest neighbors; Number of vehicles; Vehicle routing problem with time windows; Dairy products",{"$nulls":4},"Universidad de La Sabana, (EICEA-114-2018)","This work has been partially supported by Universidad de La Sabana and its General Direction of Research under grant EICEA-114-2018.","Almouhanna A., Quintero-Araujo C.L., Panadero J., Juan A.A., Khosravi B., Ouelhadj D., The location routing problem using electric vehicles with constrained distance, Computers & Operations Research, 115, (2020); Braekers K., Ramaekers K., Van Nieuwenhuyse I., The vehicle routing problem: State of the art classification and review, Computers & Industrial Engineering, 99, pp. 300-313, (2016); Cordeau J.-F., Desaulniers G., Desrosiers J., Soumis F., The VRP with time windows, The vehicle routing problem. SIAM Monographs on Discrete Mathematics and its Applications, pp. 157-193, (2002); Dantzig G.B., Ramser J.H., The truck dispatching problem, Management Science, 6, 1, pp. 80-91, (1959); Dominguez O., Guimarans D., Juan A.A., de la Nuez I., A biased-randomised large neighbourhood search for the two-dimensional vehicle routing problem with backhauls, European Journal of Operational Research, 255, 2, pp. 442-462, (2016); Dominguez O., Juan A.A., Barrios B., Faulin J., Agustin A., Using biased randomization for solving the two-dimensional loading vehicle routing problem with heterogeneous fleet, Annals of Operations Research, 236, 2, pp. 383-404, (2016); Dominguez O., Juan A.A., de la Nuez I., Ouelhadj D., An ILS-biased randomization algorithm for the two-dimensional loading HFVRP with sequential loading and items rotation, Journal of the Operational Research Society, 67, 1, pp. 37-53, (2016); Dominguez O., Juan A.A., Faulin J., A biased-randomized algorithm for the two-dimensional vehicle routing problem with and without item rotations, International Transactions in Operational Research, 21, 3, pp. 375-398, (2014); Elshaer R., Awad H., A taxonomic review of metaheuristic algorithms for solving the vehicle routing problem and its variants, Computers & Industrial Engineering, 140, pp. 106219-106242, (2020); Erdogan G., An open source spreadsheet solver for vehicle routing problems, Computers & Operations Research, 84, pp. 62-72, (2017); Feo T.A., Resende M.G.C., Greedy randomized adaptive search procedures, Journal of Global Optimization, 6, 2, pp. 109-133, (1995); Goeke D., Schneider M., Routing a mixed fleet of electric and conventional vehicles, European Journal of Operational Research, 245, 1, pp. 81-99, (2015); Grasas A., Juan A.A., Faulin J., Armas J.D., Ramalhinho H., Biased randomization of heuristics using skewed probability distributions: A survey and some applications, Computers & Industrial Engineering, 110, pp. 216-228, (2017); Gruler A., Quintero-Araujo C.L., Calvet L., Juan A.A., Waste collection under uncertainty: A simheuristic based on variable neighbourhood search, European J. of Industrial Engineering, 11, 2, pp. 228-255, (2017); Guimarans D., Dominguez O., Juan A.A., Martinez E., A multi-start simheuristic for the stochastic two-dimensional vehicle routing problem, 2016 Winter Simulation Conference (WSC), pp. 2326-2334, (2016); Hashimoto H., Yagiura M., Ibaraki T., An iterated local search algorithm for the time-dependent vehicle routing problem with time windows, Discrete Optimization, 5, 2, pp. 434-456, (2008); Hokama P., Miyazawa F.K., Xavier E.C., A branch-and-cut approach for the vehicle routing problem with loading constraints, Expert Systems with Applications, 47, pp. 1-13, (2016); Irnich S., Toth P., Vigo D., The family of vehicle routing problems, Vehicle routing: Problems, Methods, and Applications. MOS-SIAM Series on Optimization, pp. 1-33, (2014); Juan A.A., Faulin J., Ferrer A., Lourenco H.R., Barrios B., MIRHA: multi-start biased randomization of heuristics with adaptive local search for solving non-smooth routing problems, TOP, 21, 1, pp. 109-132, (2013); Juan A.A., Pascual I., Guimarans D., Barrios B., Combining biased randomization with iterated local search for solving the multidepot vehicle routing problem, International Transactions in Operational Research, 22, 4, pp. 647-667, (2015); Laporte G., Fifty years of vehicle routing, Transportation Science, 43, 4, pp. 408-416, (2009); Li H., Yuan J., Lv T., Chang X., The two-echelon time-constrained vehicle routing problem in linehaul-delivery systems considering carbon dioxide emissions, Transportation Research Part D: Transport and Environment, 49, pp. 231-245, (2016); Liao T.-Y., On-line vehicle routing problems for carbon emissions reduction, Computer-Aided Civil and Infrastructure Engineering, 32, 12, pp. 1047-1063, (2017); Lin C., Choy K.L., Ho G.T.S., Chung S.H., Lam H.Y., Survey of green vehicle routing problem: Past and future trends, Expert Systems with Applications, 41, 4, pp. 1118-1138, (2014); Manikas A.S., Kroes J.R., Gattiker T.F., Metro meals on wheels treasure valley employs a low-cost routing tool to improve deliveries, Interfaces, 46, 2, pp. 154-167, (2016); Mester D., Braysy O., Active guided evolution strategies for large-scale vehicle routing problems with time windows, Computers & Operations Research, 32, 6, pp. 1593-1614, (2005); Montoya-Torres J.R., Lopez Franco J., Nieto Isaza S., Felizzola Jimenez H., Herazo-Padilla N., A literature review on the vehicle routing problem with multiple depots, Computers & Industrial Engineering, 79, pp. 115-129, (2015); Nagata Y., Braysy O., Dullaert W., A penalty-based edge assembly memetic algorithm for the vehicle routing problem with time windows, Computers & Operations Research, 37, 4, pp. 724-737, (2010); Nataraj S., Ferone D., Quintero-Araujo C., Juan A.A., Festa P., Consolidation centers in city logistics: A cooperative approach based on the location routing problem, International Journal of Industrial Engineering Computations, 3, 10, pp. 393-404, (2019); Quintero-Araujo C.L., Applications of simheuristics and horizontal cooperation concept in rich vehicle routing problems, (2017); Quintero-Araujo C.L., Guimarans D., Juan A.A., A simheuristic algorithm for the capacitated location routing problem with stochastic demands, Journal of Simulation, pp. 1-18, (2019); Sicilia J.A., Quemada C., Royo B., Escuin D., An optimization algorithm for solving the rich vehicle routing problem based on variable neighborhood search and tabu search metaheuristics, Journal of Computational and Applied Mathematics, 291, pp. 468-477, (2016); Solano Charris E.L., Montoya-Torres J.R., Guerrero-Rueda W., A decision support system for technician routing with time windows: A case study of a Colombian public utility company, Academia Revista Latinoamericana de Administración, 32, 2, pp. 138-158, (2019); Tas D., Jabali O., van Woensel T., A vehicle routing problem with flexible time windows, Computers & Operations Research, 52, pp. 39-54, (2014); Tsao Y.-C., Lu J.-C., A supply chain network design considering transportation cost discounts, Transportation Research Part E: Logistics and Transportation Review, 48, 2, pp. 401-414, (2012); Vega-Mejia C.A., Montoya-Torres J.R., Islam S.M.N., Consideration of triple bottom line objectives for sustainability in the optimization of vehicle routing and loading operations: a systematic literature review, Annals of Operations Research, 273, 1-2, pp. 311-375, (2019); Yang H., Yang S., Xu Y., Cao E., Lai M., Dong Z., Electric vehicle route optimization considering time-of-use electricity price by learnable partheno-genetic algorithm, IEEE Transactions on Smart Grid, 6, 2, pp. 657-666, (2015); Yin P.Y., Chuang Y.L., Adaptive memory artificial bee colony algorithm for green vehicle routing with cross-docking, Applied Mathematical Modelling, 40, 21-22, pp. 9302-9315, (2016); Zhang J., Lam W.H.K., Chen B.Y., On-time delivery probabilistic models for the vehicle routing problem with stochastic demands and time windows, European Journal of Operational Research, 249, 1, pp. 144-154, (2016); Zolfagharinia H., Haughton M.A., Operational flexibility in the truckload trucking industry, Transportation Research Part B: Methodological, 104, pp. 437-460, (2017)","C.L. Quintero-Araújo; Operations Supply Chain Management Research Group, International School of Economics and Administrative Sciences, Universidad de La Sabana, Chia, Colombia; email: carlosqa@unisabana.edu.co",null,"Taylor and Francis Ltd.",{"$nulls":5},1966324.0,null,"AMMSD",null,"English","Am J Math Manage Sci","Article","Final",null,"Scopus","2-s2.0-85104781682"]
["Cherif N.; Jaafar W.; Yanikomeroglu H.; Yongacoglu A.","Cherif, Nesrine (57190405030); Jaafar, Wael (24479408700); Yanikomeroglu, Halim (6603917247); Yongacoglu, Abbas (7004741750)","57190405030; 24479408700; 6603917247; 7004741750","3D Aerial Highway: The Key Enabler of the Retail Industry Transformation",2021.0,"IEEE Communications Magazine",59.0,9.0,null,65.0,71.0,6.0,16.0,"10.1109/MCOM.010.2100072","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85117239560&doi=10.1109%2fMCOM.010.2100072&partnerID=40&md5=51858264964515ca87c6ea3707b2f397","University of Ottawa, Canada; Carleton University, Canada","Cherif N., University of Ottawa, Canada; Jaafar W., Carleton University, Canada; Yanikomeroglu H., Carleton University, Canada; Yongacoglu A., University of Ottawa, Canada","The retail industry is facing an inevitable transformation worldwide, which is accelerating with the current pandemic situation. Indeed, consumer habits are shifting from brick-and-mortar stores to online shopping. The bottleneck in the online shopping experience remains efficient and fast delivery to consumers. In this context, unmanned aerial vehicle (UAV) technology is seen as a potential solution to address cargo delivery issues. Hence, the number of cargo UAVs is expected to increase in the next few decades and the airspace to become crowded. To successfully deploy UAVs for mass cargo delivery, seamless and reliable cellular connectivity for cargo UAVs is required. Thus, organized and 'connected' routes in the sky are needed. Like highways for vehicles, 3D routes in the airspace should be designed to fulfill cargo UAV operations safely and efficiently. We refer to these routes as '3D aerial highways.' In this article, we investigate the feasibility of the aerial highways paradigm. First, we discuss the related motivations and concerns. Then we present our aerial highways paradigm design. Finally, we present linked connectivity issues and potential solutions.  © 1979-2012 IEEE.",null,"Antennas; Electronic commerce; Highway planning; 'current; Cargo delivery; Cellular connectivity; Connected routes; Online shopping; Retail industry; Vehicle operations; Vehicle technology; Unmanned aerial vehicles (UAV)",{"$nulls":6},"Mozaffari M., Et al., A tutorial on UAVs for wireless networks: Applications, challenges, and open problems, IEEE Commun. Surveys & Tutorials, 21, 3, pp. 2334-2360, (2019); Peng K., Et al., A hybrid genetic algorithm on routing and scheduling for vehicle-assisted multidrone parcel delivery, IEEE Access, 7, pp. 191-200, (2019); Stolaroff J.K., Et al., Energy use and life cycle greenhouse gas emissions of drones for commercial package delivery, Nature Commun., 9, 1, pp. 1-13, (2018); Sudbury A.W., Hutchinson E.B., A cost analysis of amazon prime air (drone delivery), J. Eco. Educ., 16, 1, pp. 1-12, (2016); Hamnanaka M., Optimum design for drone highway network, Proc. Int'l. Conf. UAS, pp. 923-929, (2019); Majd A., Troubitsyna E., Integrating safety-aware route optimisation and run-time safety monitoring in controlling swarms of drones, Proc. Int'l. Symp. Soft. Relia. Eng. Wksps., Toulouse, pp. 94-95, (2017); Zeng G., Et al., An airport airspace flow control method for drones, Proc. Int'l. Conf. Unmanned Sys., pp. 178-182, (2019); Azari M.M., Et al., Coexistence of terrestrial and aerial users in cellular networks, Proc. IEEE GLOBECOM Wksps., pp. 1-6, (2017); Cherif N., Et al., Downlink coverage analysis of an aerial user in vertical heterogeneous networks, Proc. IEEE GLOBECOM, pp. 1-6, (2019); Cherif N., Et al., On the optimal 3D placement of a uav base station for maximal coverage of UAV users, Proc. IEEE GLOBECOM, pp. 1-6, (2020); Fotouhi A., Et al., Survey on UAV cellular communications: Practical aspects, standardization advancements, regulation, and security challenges, IEEE Commun. Surveys & Tutorials., 21, 4, pp. 3417-3442, (2019); Clothier R.A., Et al., Risk perception and the public acceptance of drones, Risk Analysis, 35, 6, pp. 1167-1183, (2015); Alam M.S., Et al., High altitude platform station based super macro base station constellations, IEEE Commun. Mag., 59, 1, pp. 103-109, (2021); Kurt G.K., Et al., A vision and framework for the high altitude platform station (haps) networks of the future, IEEE Commun. Surveys & Tutorials, 23, 2, pp. 729-779, (2021); Rappaport T.S., Et al., Wideband millimeter-wave propagation measurements and channel models for future wireless communication system design, IEEE Trans. Commun., 63, 9, pp. 3029-3056, (2015)",null,null,"Institute of Electrical and Electronics Engineers Inc.",{"$nulls":5},1636804.0,null,"ICOMD",null,"English","IEEE Commun Mag","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85117239560"]
["Lin Y.; Wang Y.; Lee L.H.; Chew E.P.","Lin, Yunhui (57216781261); Wang, Yuan (57079310600); Lee, Loo Hay (55667526300); Chew, Ek Peng (7102013740)","57216781261; 57079310600; 55667526300; 7102013740","Profit-maximizing parcel locker location problem under threshold Luce model",2022.0,"Transportation Research Part E: Logistics and Transportation Review",157.0,null,102541.0,null,null,null,22.0,"10.1016/j.tre.2021.102541","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85120630831&doi=10.1016%2fj.tre.2021.102541&partnerID=40&md5=e27712ddc1c747f335c055159c2d72be","Department of Industrial Systems Engineering and Management, National University of Singapore, Singapore; School of Business, Singapore University of Social Sciences, Singapore","Lin Y., Department of Industrial Systems Engineering and Management, National University of Singapore, Singapore; Wang Y., School of Business, Singapore University of Social Sciences, Singapore; Lee L.H., Department of Industrial Systems Engineering and Management, National University of Singapore, Singapore; Chew E.P., Department of Industrial Systems Engineering and Management, National University of Singapore, Singapore","The growth of e-commerce has created increasing complexity in logistics services. To remain competitive, logistics and e-commerce companies are exploring new modes as supplements to traditional home delivery, one of which is the self-service parcel locker. This paper studies a parcel locker location problem where a company plans to introduce the locker service by locating locker facilities to attract customers. The objective is to maximize the profit, accounting for the revenue and the cost of facilities, under the competition of other delivery modes. To estimate the revenue, we use the threshold Luce model (TLM) to predict customers’ likelihood of using the locker service. We then propose a combinatorial optimization model and develop exact solution methodologies that are practically implementable according to our extensive computational experiments. In effect, our modeling framework generalizes the traditional facility location problems based on the binomial logit model (BNL) and the multinomial logit model (MNL), both of which impose strong and strict assumptions on the customer's choice sets. That is, they assume that the choice set will either contain only one facility or all facilities. In our numerical experiment, we demonstrate that using the BNL and the MNL could lead to, respectively, pessimistic and optimistic revenue estimation. Consequently, the suggested location decisions will be either conservative or aggressive. Our proposed model, by contrast, can effectively relax these assumptions. Our results also reveal that the aggressive decision due to the use of the MNL will incur an unnecessarily high facility cost that cannot be compensated by the additional revenue, leading to profit loss that could be significant in various scenarios. Finally, we conduct sensitivity analysis to shed light on how the relative attraction of locker services (compared to other delivery options) affects the location decisions and highlight the importance of calibrating the input parameters in TLM. © 2021 Elsevier Ltd","Choice set restriction; Discrete choice model; Facility location; Last-mile delivery; Parcel locker","Combinatorial optimization; Electronic commerce; Location; Locks (fasteners); Sales; Sensitivity analysis; Choice set restriction; Discrete choice models; E- commerces; Facilities locations; Last mile; Last-mile delivery; Location problems; Logit models; Multinomial logit model; Parcel locker; discrete choice analysis; electronic commerce; facility location; modeling; Profitability",{"$nulls":4},"Agency for Science, Technology and Research, A*STAR, (A1895a0033)","The authors have been supported by Singapore A*STAR IAF-PP fund (Grant No. A1895a0033 ) under the project ”Digitial Twin for Next Generation Warehouse”.","Aboolian R., Berman O., Krass D., Competitive facility location and design problem, European J. Oper. Res., 182, 1, pp. 40-62, (2007); Ahumada A., Ulku L., Luce rule with limited consideration, Math. Social Sci., 93, pp. 52-56, (2018); Biesinger B., Hu B., Raidl G., Models and algorithms for competitive facility location problems with different customer behavior, Ann. Math. Artif. Intell., 76, 1-2, pp. 93-119, (2016); Chen D.S., Batson R.G., Dang Y., Applied Integer Programming: Modeling and Solution, (2010); Chernev A., Bockenholt U., Goodman J., Choice overload: A conceptual review and meta-analysis, J. Consumer Psychol., 25, 2, pp. 333-358, (2015); Deutsch Y., Golany B., A parcel locker network as a solution to the logistics last mile problem, Int. J. Prod. Res., 56, 1-2, pp. 251-261, (2018); Dieke A.K., Bender C., Campbell J.I., Cohen R.H., Muller C., Niederprum A., de Streel A., Thiele S., Zanker C., Main developments in the postal sector (2010–2013), Bad Honnef: WIK Consulting, (2013); Drezner T., Derived attractiveness of shopping malls, IMA J. Manag. 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Res., 79, pp. 12-18, (2017); Flores A., Berbeglia G., Van Hentenryck P., Assortment and price optimization under the two-stage luce model, (2017); Gentile J., Pessoa A.A., Poss M., Roboredo M.C., Integer programming formulations for three sequential discrete competitive location problems with foresight, European J. Oper. Res., 265, 3, pp. 872-881, (2018); Gul F., Natenzon P., Pesendorfer W., Random choice as behavioral optimization, Econometrica, 82, 5, pp. 1873-1912, (2014); Gunawan H., Kusuma A., Abdullah S., Et al., Parcel locker as the alternative of parcel delivery service of online shopping, J. Comput. Theor. Nanosci., 17, 2, pp. 1311-1317, (2020); Haase K., Muller S., A comparison of linear reformulations for multinomial logit choice probabilities in facility location models, European J. Oper. Res., 232, 3, pp. 689-691, (2014); Hagberg A., Schult D., Swart P., Exploring network structure, dynamics, and function using networkx, Proceedings of the 7th Python in Science Conference, SciPy, (2008); Hakimi S.L., Locations with spatial interactions: competitive locations and games, Discrete Location Theory, (1990); Hodgson M.J., A location—allocation model maximizing consumers’ welfare, Reg. Stud., 15, 6, pp. 493-506, (1981); Hong J., Lee M., Cheong T., Lee H.C., Routing for an on-demand logistics service, Transp. Res. C, 103, pp. 328-351, (2019); Kucukaydin H., Aras N., Altinel I., A discrete competitive facility location model with variable attractiveness, J. Oper. Res. Soc., 62, 9, pp. 1726-1741, (2011); Lachapelle U., Burke M., Brotherton A., Leung A., Parcel locker systems in a car dominant city: Location, characterisation and potential impacts on city planning and consumer travel access, J. Transp. Geogr., 71, pp. 1-14, (2018); Lancinskas A., Fernandez P., Pelegin B., Zilinskas J., Improving solution of discrete competitive facility location problems, Optim. Lett., 11, 2, pp. 259-270, (2017); Lemke J., Iwan S., Korczak J., Usability of the parcel lockers from the customer perspective–the research in polish cities, Transp. Res. Procedia, 16, pp. 272-287, (2016); Lin Y.H., Tian Q., Branch-and-cut approach based on generalized benders decomposition for facility location with limited choice rule, European J. Oper. Res., 293, 1, pp. 109-119, (2021); Lin Y.H., Tian Q., Generalized benders decomposition for competitive facility location with concave demand and zone-specialized variable attractiveness, Comput. Oper. Res., 130, (2021); Lin Y.H., Wang Y., He D., Lee L.H., Last-mile delivery: Optimal locker location under multinomial logit choice model, Transp. Res. E: Logist. Transp. Rev., 142, (2020); Ljubic I., Moreno E., Outer approximation and submodular cuts for maximum capture facility location problems with random utilities, European J. Oper. Res., 266, 1, pp. 46-56, (2018); Lyu G., Teo C.P., Last mile innovation: The case of the locker alliance network, (2019); Mai T., Lodi A., A multicut outer-approximation approach for competitive facility location under random utilities, European J. Oper. Res., 284, 3, pp. 874-881, (2020); Mallozzi L., D'Amato E., Pardalos P.M., Spatial Interaction Models, (2017); McFadden D., Econometric models of probabilistic choice, Struct. Anal. Discrete Data Econom. Appl., (1981); Morganti E., Dablanc L., Fortin F., Final deliveries for online shopping: The deployment of pickup point networks in urban and suburban areas, Res. Transp. Bus. Manag., 11, pp. 23-31, (2014); Orenstein I., Raviv T., Sadan E., Flexible parcel delivery to automated parcel lockers: models, solution methods and analysis, EURO J. Transp. Logist., 8, 5, pp. 683-711, (2019); Punakivi M., Yrjola H., Holmstrom J., Solving the last mile issue: reception box or delivery box?, Int. J. Phys. Distrib. Logist. Manage., 31, 6, pp. 427-439, (2001); Rusmevichientong P., Shen Z.M., Shmoys D.B., Dynamic assortment optimization with a multinomial logit choice model and capacity constraint, Oper. Res., 58, 6, pp. 1666-1680, (2010); Schwerdfeger S., Boysen N., Optimizing the changing locations of mobile parcel lockers in last-mile distribution, European J. Oper. Res., 285, 3, pp. 1077-1094, (2020); Song L., Guan W., Cherrett T., Li B., Quantifying the greenhouse gas emissions of local collection-and-delivery points for last-mile deliveries, Transp. Res. Rec., 2340, 1, pp. 66-73, (2013); Suarez-Vega R., Santos-Penate D.R., Dorta-Gonzalez P., Competitive multifacility location on networks: the (r|xp)-medianoid problem, J. Reg. Sci., 44, 3, pp. 569-588, (2004); Suhara Y., Bahrami M., Bozkaya B., Pentland A.S., Validating gravity-based market share models using large-scale transactional data, Big Data, (2021); Vakulenko Y., Hellstrom D., Hjort K., What's in the parcel locker? Exploring customer value in e-commerce last mile delivery, J. Bus. Res., 88, pp. 421-427, (2018); Yuen K.F., Wang X., Ng L.W., Wong Y.D., An investigation of customers’ intention to use self-collection services for last-mile delivery, Transp. Policy, 66, pp. 1-8, (2018); Zhou M., Zhao L., Kong N., Campy K.S., Xu G., Zhu G., Cao X., Wang S., Understanding consumers’ behavior to adopt self-service parcel services for last-mile delivery, J. Retailing Consumer Services, 52, (2020)","Y. Wang; School of Business, Singapore University of Social Sciences, Singapore, 463 Clementi Road, 599494, Singapore; email: wangyuan@suss.edu.sg",null,"Elsevier Ltd",{"$nulls":5},1.3665545E7,null,null,null,"English","Transp. Res. Part E Logist. Transp. Rev.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85120630831"]
["Wong C.Y.","Wong, Chee Yew (55894542500)",5.58945425E10,"Celebrating IJPDLM's 50th anniversary: a reflection on its contributions and future directions",2021.0,"International Journal of Physical Distribution and Logistics Management",51.0,10.0,null,1049.0,1064.0,15.0,6.0,"10.1108/IJPDLM-10-2021-0427","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85118988970&doi=10.1108%2fIJPDLM-10-2021-0427&partnerID=40&md5=17b359191e860fce5dd5e6f49c541730","Leeds University Business School, University of Leeds, Leeds, United Kingdom","Wong C.Y., Leeds University Business School, University of Leeds, Leeds, United Kingdom","Purpose: This article celebrates the 50th anniversary of IJPDLM, reflects on the contribution of IJPDLM to the field of logistics and supply chain management (LSCM) and discusses future directions for the journal. Design/methodology/approach: Descriptive analysis of manuscripts received and accepted by IJPDLM during 2015–2019 is used to provide an overview of the journal. Content analysis of selected articles is used to highlight important contributions of the journal. Changes made since 2020 are highlighted to inform future directions of IJPDLM. Invited articles are discussed and used to clarify future directions. Findings: IJPDLM has made tremendous progress in informing and shaping the field of LSCM. Key issues addressed include sustainability and reverse logistics, omni-channel, e-commerce, retail logistics, risk, resilience, volatility, and complexity and digital technology innovation. The journal has expanded the use of methods beyond the typical qualitative and quantitative methods to explore the use of design science, experiment, conjoint analysis, qualitative comparative analysis, narrative analysis. The invited articles provide (1) a historical reflection of the purpose of the journal when it was launched, (2) new guidance on how to develop theories using literature review and grounded theories and (3) understanding of startups and supply chain ecosystems. Practical implications: Some exemplar articles are highlighted to explain how IJPDLM informs LSCM managers, companies and policy makers. Originality/value: This article explains the recent development and sets future directions for the LSCM field. © 2021, Emerald Publishing Limited.","Logistics management; Physical distribution; Supply chain management; Theoretical contribution",{"$nulls":7},"Asmussen J.N., Kristensen J., Steger-Jensen K., Waehrens B.V., When to integrate strategic and tactical decisions? Introduction of an asset/inventory ratio guiding fit for purpose production planning, International Journal of Physical Distribution and Logistics Management, 48, 5, pp. 545-568, (2018); Bhattacharjya J., Ellison A., Tripathi S., An exploration of logistics-related customer service provision on Twitter: the case of e-retailers, International Journal of Physical Distribution and Logistics Management, 46, 6-7, pp. 659-680, (2016); Busse C., Schleper M.C., Niu M., Wagner S.M., Supplier development for sustainability: contextual barriers in global supply chains, International Journal of Physical Distribution and Logistics Management, 46, 5, pp. 442-468, (2016); Busse C., Schleper M.C., Weilenmann J., Wagner S.M., Extending the supply chain visibility boundary: utilizing stakeholders for identifying supply chain sustainability risks, International Journal of Physical Distribution and Logistics Management, 47, 1, pp. 18-40, (2017); Carbone V., Rouquet A., Roussat C., A typology of logistics at work in collaborative consumption, International Journal of Physical Distribution and Logistics Management, 48, 6, pp. 570-585, (2018); Durach C.F., Wieland A., Machuca J.A.D., Antecedents and dimensions of supply chain robustness: a systematic literature review, International Journal of Physical Distribution and Logistics Management, 45, 1-2, pp. 118-137, (2015); Durach C.F., Kembro J., Wieland A., A new paradigm for systematic literature reviews in supply chain management, Journal of Supply Chain Management, 53, 4, pp. 67-85, (2017); Durach C.F., Kembro J.H., Wieland A., How to advance theory through literature reviews in logistics and supply chain management, International Journal of Physical Distribution and Logistics Management, 51, 10, (2021); Ellinger A.E., Chapman K., IJPDLM's 45th anniversary: a retrospective bibliometric analysis and future directions, International Journal of Physical Distribution and Logistics Management, 46, 1, pp. 2-18, (2016); Fan Y., Stevenson M., A review of supply chain risk management: definition, theory, and research agenda, International Journal of Physical Distribution and Logistics Management, 48, 3, pp. 205-230, (2018); Filbeck G., Kumar S., Liu J., Zhao X., Supply chain finance and financial contagion from disruptions - evidence from the automobile industry, International Journal of Physical Distribution and Logistics Management, 46, 4, (2016); Foerstl K., Kirchoff J.F., Bals L., Reshoring and insourcing: drivers and future research directions, International Journal of Physical Distribution and Logistics Management, 46, 5, pp. 492-515, (2016); Fratocchi L., Ancarani A., Barbieri P., Di Mauro C., Nassimbeni G., Sartor M., Vignoli M., Zanoni A., Motivations of manufacturing reshoring: an interpretative framework, International Journal of Physical Distribution and Logistics Management, 46, 2, pp. 98-127, (2016); Garcia-Arca J., Prado-Prado J.C., Fernandez-Gonzalez A.J., Integrating KPIs for improving efficiency in road transport, International Journal of Physical Distribution and Logistics Management, 48, 9, pp. 931-951, (2018); Gawor T., Hoberg K., Customers' valuation of time and convenience in e-fulfillment, International Journal of Physical Distribution and Logistics Management, 49, 1, pp. 75-98, (2019); Gelsomino L.M., Mangiaracina R., Perego A., Tumino A., Supply chain finance: a literature review, International Journal of Physical Distribution and Logistics Management, 46, 4, (2016); Hideg I., DeCelles K.A., Tihanyi L., From the editors – publishing practical and responsible research in AMJ, Academy of Management, 63, 6, pp. 1681-1686, (2020); Hohenstein N.O., Feisel E., Hartmann E., Giunipero L., Research on the phenomenon of supply chain resilience: a systematic review and paths for further investigation, International Journal of Physical Distribution and Logistics Management, 45, 1-2, pp. 90-117, (2015); Holweg C., Teller C., Kotzab H., Unsaleable grocery products, their residual value and instore logistics, International Journal of Physical Distribution and Logistics Management, 46, 6-7, pp. 634-658, (2016); Hubner A., Wollenburg J., Holzapfel A., Retail logistics in the transition from multi-channel to omni-channel, International Journal of Physical Distribution and Logistics Management, 46, 6-7, pp. 562-583, (2016); Ishfaq R., Defee C.C., Gibson B.J., Raja U., Realignment of the physical distribution process in omni-channel fulfillment, International Journal of Physical Distribution and Logistics Management, 46, 6-7, pp. 543-561, (2016); Kirchoff J.F., Tate W.L., Mollenkopf D.A., The impact of strategic organizational orientations on green supply chain management and firm performance, International Journal of Physical Distribution and Logistics Management, 46, 3, pp. 269-292, (2016); Li C., Wong C.W.Y., Yang C.-C., Shang K.C., Lirn T.C., Value of supply chain resilience: roles of culture, flexibility, and integration, International Journal of Physical Distribution and Logistics Management, 50, 1, pp. 80-100, (2020); Meixell M.J., Luoma P., Stakeholder pressure in sustainable supply chain management: a systematic review, International Journal of Physical Distribution and Logistics Management, 45, 1-2, pp. 69-89, (2015); Mello J.E., Manuj I., Flint D.J., Leveraging grounded theory in supply chain research: a researcher and reviewer guide, International Journal of Physical Distribution and Logistics Management, 51, 10, (2021); Morenza-Cinos M., Casamayor-Pujol V., Pous R., Stock visibility for retail using an RFID robot, International Journal of Physical Distribution and Logistics Management, 49, 10, pp. 1020-1042, (2019); Murfield M., Boone C.A., Rutner P., Thomas R., Investigating logistics service quality in omni-channel retailing, International Journal of Physical Distribution and Logistics Management, 47, 4, pp. 263-296, (2017); Richey R.G., Morgan T.R., Lindsey-Hall K., Adams F.G., A global exploration of Big Data in the supply chain, International Journal of Physical Distribution and Logistics Management, 46, 8, pp. 710-739, (2016); Russo I., Confente I., Gligor D., Cobelli N., A roadmap for applying qualitative comparative analysis in supply chain research: the reverse supply chain case, International Journal of Physical Distribution and Logistics Management, 49, 1, pp. 99-120, (2019); Sasson A., Johnson J.C., The 3D printing order: variability, supercenters and supply chain reconfigurations, International Journal of Physical Distribution and Logistics Management, 46, 1, pp. 82-94, (2016); Stevens G.C., Johnson M., Integrating the supply chain … 25 years on, International Journal of Physical Distribution and Logistics Management, 46, 1, pp. 19-42, (2016); Su S.-L., Fan X., Shou Y., A design science-based case study of retail chain delivery operations and its implications, International Journal of Physical Distribution and Logistics Management, 51, 3, pp. 212-235, (2021); Timmer S., Kaufmann L., Conflict minerals traceability – a fuzzy set analysis, International Journal of Physical Distribution and Logistics Management, 47, 5, pp. 344-367, (2017); Touboulic A., Walker H., Theories in sustainable supply chain management: a structured literature review, International Journal of Physical Distribution and Logistics Management, 45, 1-2, pp. 16-42, (2015); Tranfield D., Denyer D., Smart P., Towards a methodology for developing evidence informed management knowledge by means of systematic review, British Journal of Management, 14, pp. 207-222, (2003); Tsvetkova A., Human actions in supply chain management: the interplay of institutional work and institutional logics in the Russian Arctic, International Journal of Physical Distribution and Logistics Management, 51, 8, pp. 837-858, (2021); Van Hoek R., Retrospective on the launch of IJPDLM – lessons for the future of logistics and supply chain management research International, Journal of Physical Distribution and Logistics Management, 51, 10, (2021); van Hoek R., Lessons from CSCMP Supply Chain Hall of Famer Henry Ford and the research that they call for in modern supply chains, International Journal of Physical Distribution and Logistics Management, (2021); van Hoek R., Loseby D., Wong C.Y., Editorial: new section, International Journal of Physical Distribution and Logistics Management, 50, 9-10, pp. 769-774, (2020); Wagner S.F., Startups in the supply chain ecosystem: an organizing framework and research opportunities, International Journal of Physical Distribution and Logistics Management, 51, 10, (2021); Williams Z., Garver M.S., Richey R.G., Security capability and logistics service provider selection: an adaptive choice study, International Journal of Physical Distribution and Logistics Management, 49, 4, pp. 330-335, (2019); Wong C.Y., Editorial – can a descriptive literature review advance knowledge?, International Journal of Physical Distribution and Logistics Management, 51, 3, pp. 205-211, (2021); Wong C.Y., Wong C.W., Boon-itt S., Integrating environmental management into supply chains: a systematic literature review and theoretical framework, International Journal of Physical Distribution and Logistics Management, 45, 1-2, pp. 43-68, (2015); Zomorrodi M., Fayezi S., Lau K.H., McMurray A., Supply chain adaptations for the base-of-the-pyramid business: towards a theoretical model, International Journal of Physical Distribution and Logistics Management, 49, 5, pp. 599-624, (2019)","C.Y. Wong; Leeds University Business School, University of Leeds, Leeds, United Kingdom; email: c.y.wong@leeds.ac.uk",null,"Emerald Group Holdings Ltd.",{"$nulls":5},9600035.0,null,null,null,"English","Int. J. Phys. Distrib. Logist. Manage.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85118988970"]
["Sachan R.K.; Kushwaha D.S.","Sachan, Rohit Kumar (57170217300); Kushwaha, Dharmender Singh (12790371400)","57170217300; 12790371400","A Multi-objective anti-predatory nia for e-commerce logistics optimization problem",2021.0,"International Journal of Applied Metaheuristic Computing",12.0,4.0,null,1.0,27.0,26.0,1.0,"10.4018/IJAMC.2021100101","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85115652364&doi=10.4018%2fIJAMC.2021100101&partnerID=40&md5=935c7d118891844964113695d96a92a5","Motilal Nehru National Institute of Technology, India","Sachan R.K., Motilal Nehru National Institute of Technology, India; Kushwaha D.S., Motilal Nehru National Institute of Technology, India","Nature-inspired algorithms (NIAs) have established their promising performance to solve both singleobjective optimization problems (SOOPs) and multi-objective optimization problems (MOOPs). Anti-predatory NIA (APNIA) is one of the recently introduced single-objective algorithm based on the self-defense behavior of frogs. This paper extends APNIA as multi-objective algorithm and presents the first proposal of APNIA to solve MOOPs. The proposed algorithm is a posteriori version of APNIA, which is named as multi-objective anti-predatory NIA (MO-APNIA). It uses the concept of Pareto dominance to determine the non-dominated solutions. The performance of the MO-APNIA is established through the experimental evaluation and statistically verified using the Friedman rank test and Holm-Sidak test. MO-APNIA is also employed to solve a multi-objective variant of hub location problem (HLP) from the perspective of the e-commerce logistics. Results indicate that the MO-APNIA is also capable to finds the non-dominated solutions of HLP. This finds immense use in logistics industry. Copyright © 2021, IGI Global.","Anti-Predatory NIA; E-Commerce Logistics; Hub Location Problem; Multi-Objective Optimization; Non- Dominated Sorting; Pareto Front; Transportation; Warehouse",{"$nulls":7},"Akbari R., Hedayatzadeh R., Ziarati K., Hassanizadeh B., A multi-objective artificial bee colony algorithm, Swarm and Evolutionary Computation, 2, pp. 39-52, (2012); Blount J. D., Speed M. P., Ruxton G. D., Stephens P. A., Warning displays may function as honest signals of toxicity, Proceedings. Biological Sciences, 276, 1658, pp. 871-877, (2008); Broom D. M., Broom D., Biology of behaviour: Mechanisms, functions and applications, (1981); Calder J., Continuum limit for non-dominated sorting, (2018); Coello C. A. C., Lamont G. B., Van Veldhuizen D. A., Evolutionary algorithms for solving multiobjective problems, 5, (2007); Coello C. A. C., Pulido G. T., Lechuga M. 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T., Hammond G., Antipredator behaviors of newly metamorphosed green frogs (Rana clamitans) and leopard frogs (R. pipiens) in encounters with eastern garter snakes (Thamnophis s. sirtalis), American Midland Naturalist, 137, 1, pp. 136-144, (1997); Holm S., A simple sequentially rejective multiple test procedure, Scandinavian Journal of Statistics, pp. 65-70, (1979); Li B., Li J., Tang K., Yao X., Many-objective evolutionary algorithms: A survey, ACM Computing Surveys, 48, 1, (2015); Michalis C., Scott-Samuel N. E., Gibson D. P., Cuthill I. C., Optimal background matching camouflage, Proceedings of the Royal Society B: Biological Sciences, 284, 1858, (2017); Mostaghim S., Teich J., Strategies for finding good local guides in multi-objective particle swarm optimization (MOPSO), Proceedings of the 2003 IEEE Swarm Intelligence Symposium. SIS'03 (Cat. No. 03EX706), pp. 26-33, (2003); Nishiumi N., Mori A., Distance-dependent switching of anti-predator behavior of frogs from immobility to fleeing, Journal of Ethology, 33, 2, pp. 117-124, (2015); Patel V. K., Savsani V. J., Heat transfer search (HTS): A novel optimization algorithm, Information Sciences, 324, pp. 217-246, (2015); Qin Z., Gao Y., Uncapacitated p-hub location problem with fixed costs and uncertain flows, Journal of Intelligent Manufacturing, 28, 3, pp. 705-716, (2017); Rao R., Rai D. P., Ramkumar J., Balic J., A new multi-objective Jaya algorithm for optimization of modern machining processes, Advances in Production Engineering & Management, 11, 4, pp. 271-286, (2016); Sachan R. K., Kushwaha D. S., A Generalized and Robust Anti-Predatory Nature-Inspired Algorithm for Complex Problems, International Journal of Applied Metaheuristic Computing, 10, 1, pp. 75-91, (2019); Sachan R. K., Kushwaha D. S., Anti-Predatory NIA for Unconstrained Mathematical Optimization Problems, International Journal of Swarm Intelligence Research, 11, 1, pp. 1-23, (2020); Sachan R. K., Kushwaha D. S., Inspirations from Nature for Meta-heuristic Algorithms: A Survey, Recent Advances in Computer Science and Communications, 14, 6, pp. 1708-1720, (2021); Sachan R. K., Kumar T., Kushwaha D. S., Solving E-Commerce Logistics Problem using Anti- Predatory NIA, International Journal of Intelligent Engineering Informatics, 8, 1, pp. 54-76, (2020); Sachan R. K., Kushwaha D. S., Anti-Predatory NIA based Approach for optimizing basic COCOMO Model, 2019 9th International Conference on Cloud Computing, Data Science & Engineering (Confluence), pp. 716-721, (2020); Sachan R. K., Kushwaha D. S., Warehouse Setup Problem in Logistics: A Truck Transportation Cost Model, Science and Information Conference, pp. 43-62, (2020); Sachan R. K., Kushwaha D. 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G., No free lunch theorems for optimization, IEEE Transactions on Evolutionary Computation, 1, 1, pp. 67-82, (1997); Xue F., Sanderson A. C., Graves R. J., Pareto-based multi-objective differential evolution, The 2003 Congress on Evolutionary Computation, 2003. CEC'03, 2, pp. 862-869, (2003); Yang X. S., Multiobjective firefly algorithm for continuous optimization, Engineering with Computers, 29, 2, pp. 175-184, (2013); Yang X. 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Appl. Metaheuristic Computing","Article","Final",null,"Scopus","2-s2.0-85115652364"]
["Chotigo J.; Kadono Y.","Chotigo, Jankit (57223039370); Kadono, Yasuo (26664699500)","57223039370; 26664699500","Are there any key factors that encourage food delivery applications use during the COVID-19 pandemic in Thailand and the role of HRM?",2022.0,"Human Systems Management",41.0,2.0,null,177.0,198.0,21.0,5.0,"10.3233/HSM-201140","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85128685286&doi=10.3233%2fHSM-201140&partnerID=40&md5=4344a4365cac3f431c177ae00a0cf778","Graduate School of Technology Management, Ritsumeikan University, Osaka, Japan","Chotigo J., Graduate School of Technology Management, Ritsumeikan University, Osaka, Japan; Kadono Y., Graduate School of Technology Management, Ritsumeikan University, Osaka, Japan","BACKGROUND: Recently, because of the COVID-19 pandemic, customer sentiment has evolved as the new 'normal' for food consumption - as it affects customer behavioral change, including the way customers eat. Therefore, understanding customer demands and needs will help food delivery aggregators and retailers produce sustainable, competitive advantage and drive profitability. OBJECTIVE: This paper aims to investigate the determinant factors of Thai consumers' intention to use on-demand food delivery applications. METHODS: Convenient random sampling was used to gather data from 250 participants who have used food delivery applications in Thailand and Amos version 23 to test model validity and the hypotheses. RESULTS: The results show that satisfaction is critical for the intention to use food delivery applications. Social influence, trust, convenience, and application quality were found to play an essential role in meeting the needs of satisfaction toward the intention to use, and application quality is the most important. However, habit showed a negative relationship, and price value was found to have a nonsignificant impact on satisfaction. CONCLUSIONS: Food delivery aggregators should ensure the quality of application updates and efficiency and that users have the best quality experience to maintain customer satisfaction. However, customers are also concerned about their health and safety, which has altered their purchasing behavior. Therefore, restaurant players should add a third delivery system that optimize online ordering and delivery.  © 2022 - IOS Press. 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Food delivery business booms amid Covid-19 outbreak, (2020)","J. Chotigo; Ritsumeikan University, Osaka, Japan; email: ch.janekit@outlook.com",null,"IOS Press BV",{"$nulls":5},1672533.0,null,"HSMAD",null,"English","Hum Syst Manage","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85128685286"]
["Jovčić S.; Průša P.","Jovčić, Stefan (57210358662); Průša, Petr (55822151600)","57210358662; 55822151600","A hybrid mcdm approach in third-party logistics (3pl) provider selection",2021.0,"Mathematics",9.0,21.0,2729.0,null,null,null,12.0,"10.3390/math9212729","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85118255343&doi=10.3390%2fmath9212729&partnerID=40&md5=820e776bffaf252e9c5b045b3eab1d78","Department of Transport Management, Marketing and Logistics, Faculty of Transport Engineering, University of Pardubice, Studentská 95, Pardubice, 532 10, Czech Republic","Jovčić S., Department of Transport Management, Marketing and Logistics, Faculty of Transport Engineering, University of Pardubice, Studentská 95, Pardubice, 532 10, Czech Republic; Průša P., Department of Transport Management, Marketing and Logistics, Faculty of Transport Engineering, University of Pardubice, Studentská 95, Pardubice, 532 10, Czech Republic","Third-party logistics (3PL) is becoming more and more popular because of globalization, e-commerce development, and increasing customer demand. More and more companies are trying to move away from their own account transportation to third-party accounts. One reason for using 3PLs is that the company can focus more on its core activities, while the 3PL service provider can provide distribution activities in a more professional way, save costs and time, and increase the level of customer satisfaction. An emerging issue for companies in the logistics industry is how they can decide on the 3PL evaluation and selection process for outsourcing activities. For the first time, the entropy and the criteria importance through intercriteria correlation (CRITIC) methods were coupled in order to obtain hybrid criteria weights that are of huge importance to decide on the 3PL provider evaluation and selection process. The obtained criteria weights were further utilized within the additive ratio assessment (ARAS) method to rank the alternatives from the best to the worst. The introduced hybrid–ARAS approach can be highly beneficial, since combining two methods gives more robust solutions on one hand, while on the other hand eliminating subjectivity. Comparative and sensitivity analyses showed the high reliability of the proposed hybrid–ARAS method. A hypothetical case study is presented to illustrate the potentials and applicability of the hybrid–ARAS method. The results showed that 3PL-2 was the best possible solution for our case. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.","3PL logistics; ARAS; CRITIC; Decision making; Entropy",{"$nulls":7},"Simic V., Lazarevic D., Dobrodolac M., Picture fuzzy WASPAS method for selecting last-mile delivery mode: A case study of Belgrade, Eur. Transp. Res. Rev, 13, (2021); Lazarevic D., Dobrodolac M., Svadlenka L., Stanivukovic B., A model for business performance improvement: A case of the postal company, J. Bus. Econ. 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Dev. Econ, 16, pp. 159-172, (2010); Alinezhad A., Khalili J., WASPAS Method, New Methods and Applications in Multiple Attribute Decision Making (MADM); International Series in Operations Research & Management Science, pp. 93-98, (2019); Ghorabaee M.K., Zavadskas E.K., Olfat L., Turskis Z., Multi-Criteria Inventory Classification Using a New Method of Evaluation Based on Distance from Average Solution (EDAS), Informatica, 26, pp. 435-451, (2015)","S. Jovčić; Department of Transport Management, Marketing and Logistics, Faculty of Transport Engineering, University of Pardubice, Pardubice, Studentská 95, 532 10, Czech Republic; email: stefan.jovcic@upce.cz",null,"MDPI",{"$nulls":5},2.227739E7,null,null,null,"English","Mathematics","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85118255343"]
["Song Z.","Song, Zhouying (55220246100)",5.52202461E10,"The geography of online shopping in China and its key drivers",2022.0,"Environment and Planning B: Urban Analytics and City Science",49.0,1.0,null,259.0,274.0,15.0,12.0,"10.1177/23998083211002189","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85103127406&doi=10.1177%2f23998083211002189&partnerID=40&md5=be8cae3cf0efbc07fcd545d6dde82946","Chinese Academy of Sciences, China","Song Z., Chinese Academy of Sciences, China","Many studies shed light on online shopping adoption and its determinants, most of which were conducted in developed countries and focused on sociodemographic factors. However, the influence of spatial attributes remains unclear or underestimated, especially in emerging economies. China is the largest e-commerce market in terms of the number of e-shoppers and the volume of online retail sales, with a distinctive geographical pattern of e-shopping usage. This study developed a conceptual model of China’s e-shopping adoption, examined the spatial characteristics of the e-shopping usage across 1918 counties, and explored its key drivers. The findings indicate a digital divide of e-shopping in China, with counties in metropolitan areas having a relatively high online shopping index (SI) value. The counties’ online shopping levels in China decrease from the eastern coastal regions to the rural-mountainous regions in west China. This study also found that the key drivers of e-shopping adoption are the rate of urbanization, local delivery systems, and the internet connection, which indicates that geographical attributes, rather than socioeconomic problems, have to be solved for improving online shopping adoption. © The Author(s) 2021.","China; digital divide; e-shopping; geographical factor; sociodemographic factor","China; developing world; electronic commerce; metropolitan area; retailing; shopping activity; socioeconomic conditions; spatial analysis",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (41371006, 41871120)","The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was primarily funded by Program of the Natural Science Foundation of China (No. 41871120 and No. 41371006). 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How the internet changes city Centre shopping, Journal of Retailing and Consumer Services, 14, 3, pp. 192-207, (2007); Weltevreden J.W., Atzema O., Frenken K., Et al., The geography of internet adoption by independent retailers in The Netherlands, Environment and Planning B: Planning and Design, 35, 3, pp. 443-460, (2008); Weltevreden J.W., Van Rietbergen T., The implications of e-shopping for in-store shopping at various shopping locations in The Netherlands, Environment and Planning B: Planning and Design, 36, 2, pp. 279-299, (2009); Yang Z., Geographies of Click-Consumption Power in China, Environment Andplanning A, 49, 1, pp. 6-8, (2017); Yang Y., Hu X., Qu Q., Et al., Roots of tomorrow's digital divide: Documenting computer use and internet access in China's elementary schools today, China & World Economy, 21, 3, pp. 61-79, (2013); Zhai Q., Cao X., Zhen F., Relationshipbetween Online Shopping and Store Shopping in the Shopping Process: EmpiricalStudy for Search Goods and Experience Goods in Nanjing, China, Transportation Research Record, 2673, 11, pp. 38-47, (2019); Zhen F., Du X., Cao J., Theassociation between Spatial Attributes and e-Shopping in the Shopping Processfor Search Goods and Experience Goods: Evidence from Nanjing, Journal Oftransport Geography, 66, pp. 291-299, (2018); Zhou Y., Wang X., Explore the relationship between online shopping and shopping trips: An analysis with the 2009 NHTS data, Transportation Research Part A: Policy and Practice, 70, pp. 1-9, (2014); Zhu S., Chen J., The digital divide in individual e-commerce utilization in China: Results from a national survey, Information Development, 29, 1, pp. 69-80, (2016)","Z. Song; Chinese Academy of Sciences, China; email: songzy@igsnrr.ac.cn",null,"SAGE Publications Ltd",{"$nulls":5},2.3998083E7,null,null,null,"English","Environ. Plann.","Article","Final",null,"Scopus","2-s2.0-85103127406"]
["Mancini S.; Gansterer M.","Mancini, Simona (36477249900); Gansterer, Margaretha (55078355500)","36477249900; 55078355500","Vehicle routing with private and shared delivery locations",2021.0,"Computers and Operations Research",133.0,null,105361.0,null,null,null,36.0,"10.1016/j.cor.2021.105361","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85105339028&doi=10.1016%2fj.cor.2021.105361&partnerID=40&md5=4d7a900923aecb33fe04cffb8e3454e0","University of Klagenfurt, Department of Operations, Energy, and Environmental Management, Universitätsstraße 65–67, Klagenfurt, 9020, Austria; Università di Cagliari, Department of Mathematics and Computers Science, Via Ospedale 72, Cagliari, 09124, Italy; University of Vienna, Department of Business Decisions and Analytics, Oskar-Morgenstern-Platz 1, Vienna, 1090, Austria","Mancini S., University of Klagenfurt, Department of Operations, Energy, and Environmental Management, Universitätsstraße 65–67, Klagenfurt, 9020, Austria, Università di Cagliari, Department of Mathematics and Computers Science, Via Ospedale 72, Cagliari, 09124, Italy; Gansterer M., University of Klagenfurt, Department of Operations, Energy, and Environmental Management, Universitätsstraße 65–67, Klagenfurt, 9020, Austria, University of Vienna, Department of Business Decisions and Analytics, Oskar-Morgenstern-Platz 1, Vienna, 1090, Austria","The rapid growth of e-commerce has led to an increase of home delivery requests. Providing efficient distribution systems for services on the last mile has become a challenging issue for logistics companies, where a trade-off between the classical approaches, attended home delivery (AHD) and usage of shared delivery locations (SDLs) has been identified. AHD provides a higher quality of service but implies very high costs for the company, while usage of SDL requires customers to perform the very last mile by themselves. For companies, this bears the risk of a decrease in the perceived service quality. However, due to consolidation effects, transportation costs can be considerably mitigated. We propose a mixed delivery approach, which combines AHD and SDL usage in an innovative way. Customers can either be served at home during their preferred time window, or they can be asked to pick up their parcel at one of the SDLs. For each customer served using an SDL, the company pays a compensation price in order to reduce the perceived decrease in service quality. The newly introduced decision problem is formulated mathematically. We propose two matheuristics to efficiently solve large instances. In an extensive numerical study, we show that the new approach clearly outperforms standard ones. We observe an increase in solution quality of up to 40%, while customers’ perceived quality of service is not affected. Additionally, the results reveal that the obtained improvements are robust for different customer-specific time-window preferences, accepted travel times needed to reach an SDL, and different compensation schemes. © 2021 Elsevier Ltd","Last-mile delivery; Locker boxes; Matheuristics; Routing; Sharing","Economic and social effects; Sales; Telecommunication services; Travel time; Vehicle routing; Classical approach; Compensation scheme; Decision problems; Distribution systems; Logistics company; Perceived quality; Perceived service qualities; Transportation cost; Quality of service",{"$nulls":4},"Austrian Science Fund, FWF, (P 34151-N, P 34502-N)","This work is supported by FWF Austrian Science Fund : P 34502-N and P 34151-N .","Agatz N., Campbell A., Fleischmann M., Savelsbergh M., The vehicle routing problem: Latest advances and new challenges, Challenges and Opportunities in Attended Home Delivery, pp. 379-396, (2008); Agatz N., Campbell A., Fleischmann M., Savelsbergh M., Time slot management in attended home delivery, Transp. 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Procedia, 4, pp. 178-190, (2014); Orenstein I., Raviv T., Sadan E., Flexible parcel delivery to automated parcel lockers: models, solution methods and analysis, Eur. J. Transp. Logist., 8, pp. 683-711, (2019); Pan H., Lin H., Research on optimization of intelligent express locker: In the case of the intelligent express locker in s university, Manag. Sci. Eng., 11, pp. 23-30, (2017); Reyes D., Savelsbergh M., Toriello A., Vehicle routing with roaming delivery locations, Transp. Res. C, 80, pp. 71-91, (2017); Saha S., Zhuang G., Li S., Will consumers pay more for efficient delivery? an empirical study of what affects e-customers’ satisfaction and willingness to pay on online shopping in Bangladesh, Sustainability, 12, pp. 11-21, (2020); Sitek P., Wikarek J., Capacitated vehicle routing problem with pick-up and alternative delivery (CVRPPAD): Model and implementation using hybrid approach, Ann. Oper. Res., 273, pp. 257-277, (2019); Vakulenko Y., Hellstrom D., Hjort K., What's in the parcel locker? Exploring customer value in e-commerce last mile delivery, J. Bus. Res., 88, pp. 421-427, (2018); Yang X., Strauss A., An approximate dynamic programming approach to attended home delivery management, European J. Oper. Res., 263, pp. 935-945, (2017); Yuen K.F., Wang X., Ng L., Wong Y.D., An investigation of customers’ intention to use self-collection services for last-mile delivery, Transp. Policy, 66, pp. 1-8, (2018); Zhang S., Lee C., (2016); Zhou L., Baldacci R., Vigo D., Wang X., A multi-depot two-echelon vehicle routing problem with delivery options arising in the last mile distribution, European J. Oper. Res., 265, pp. 765-778, (2018)","M. Gansterer; University of Vienna, Department of Business Decisions and Analytics, Vienna, Oskar-Morgenstern-Platz 1, 1090, Austria; email: margaretha.gansterer@aau.at",null,"Elsevier Ltd",{"$nulls":5},3050548.0,null,"CMORA",null,"English","Comp. Oper. Res.","Article","Final",null,"Scopus","2-s2.0-85105339028"]
["Jiang L.; Zang X.; Alghoul I.I.Y.; Fang X.; Dong J.; Liang C.","Jiang, Li (57194833199); Zang, Xiaoning (26422646700); Alghoul, Ibrahim I.Y. (57277364800); Fang, Xiang (35602972800); Dong, Junfeng (55478035600); Liang, Changyong (10038789900)","57194833199; 26422646700; 57277364800; 35602972800; 55478035600; 10038789900","Scheduling the covering delivery problem in last mile delivery",2022.0,"Expert Systems with Applications",187.0,null,115894.0,null,null,null,11.0,"10.1016/j.eswa.2021.115894","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85115924373&doi=10.1016%2fj.eswa.2021.115894&partnerID=40&md5=cd502e16c5019137cfdb4e48521fb81b","School of Management, Hefei University of Technology, Hefei, 230009, Anhui, China; Key Laboratory of Process Optimization and Intelligent Decision-making, Ministry of Education, Hefei, China; Emirates College of Technology, Abu Dhabi, 999041, United Arab Emirates; Sheldon B. Lubar School of Business, University of Wisconsin‐Milwaukee, 3202 N Maryland Ave, Milwaukee, 53201, WI, United States","Jiang L., School of Management, Hefei University of Technology, Hefei, 230009, Anhui, China, Key Laboratory of Process Optimization and Intelligent Decision-making, Ministry of Education, Hefei, China; Zang X., School of Management, Hefei University of Technology, Hefei, 230009, Anhui, China, Key Laboratory of Process Optimization and Intelligent Decision-making, Ministry of Education, Hefei, China; Alghoul I.I.Y., Emirates College of Technology, Abu Dhabi, 999041, United Arab Emirates; Fang X., Sheldon B. Lubar School of Business, University of Wisconsin‐Milwaukee, 3202 N Maryland Ave, Milwaukee, 53201, WI, United States; Dong J., School of Management, Hefei University of Technology, Hefei, 230009, Anhui, China, Key Laboratory of Process Optimization and Intelligent Decision-making, Ministry of Education, Hefei, China; Liang C., School of Management, Hefei University of Technology, Hefei, 230009, Anhui, China, Key Laboratory of Process Optimization and Intelligent Decision-making, Ministry of Education, Hefei, China","This study proposes a covering delivery problem (CDP), which has practical applications in last mile parcel delivery in online shopping. A set of vertices are considered, including depot, facilities, customers that must be covered, customers that must be visited, and customers that can be visited or covered. The goal is to construct a Hamiltonian cycle with minimum total costs over a subset of vertices, in which each customer is visited by the cycle or covered by a facility on the cycle. Flow-based and bilevel programming models are proposed to formulate the problem. Essentially, the bilevel programming formulations consist of one leader and one follower subproblems. On the basis of the bilevel programming ideas, a hybrid biogeography-based optimization (HBBO) is developed to solve the problem. In HBBO, BBO and 3-opt are used to solve the leader and follower problems, respectively. Lastly, computational experiments on a set of randomly generated and benchmark instances indicate the effectiveness of the proposed method. © 2021 Elsevier Ltd","Bilevel programming; Biogeography-based optimization; Covering delivery problem; Last mile delivery","Benchmarking; Ecology; Hamiltonians; Heuristic algorithms; Bi-level programming; Biogeography-based optimizations; Covering delivery problem; Delivery problems; Flow based; Hamiltonian cycle; Last mile; Last mile delivery; Online shopping; Parcel delivery; Sales",{"$nulls":4},"Humanities and Social Science Fund; National Natural Science Foundation of China, NSFC, (71601061, 71771075); Ministry of Education of the People's Republic of China, MOE, (17YJA630037); Natural Science Foundation of Anhui Province, (1808085QG229); Fundamental Research Funds for the Central Universities, (JS2021ZSPY0037)","This research was supported by the Humanities and Social Science Fund of the Ministry of Education of China (Grant Number 17YJA630037), National Natural Science Foundation of China (Grant Numbers 71601061 , 71771075 ), Fundamental Research Funds for the Central Universities (Grant Number. JS2021ZSPY0037), and Natural Science Foundation of Anhui Province in China (Grant Number. 1808085QG229 ).","Aziez I., Cote J.-F., Coelho L.C., Exact algorithms for the multi-pickup and delivery problem with time windows, European Journal of Operational Research, 284, pp. 906-919, (2020); Baldacci R., Dell'Amico M., Gonzalez J.S., The capacitated m-ring-star problem, Operations Research, 55, pp. 1147-1162, (2007); Baldacci R., Hill A., Hoshino E.A., Lim A., Pricing strategies for capacitated ring-star problems based on dynamic programming algorithms, European Journal of Operational Research, 262, pp. 879-893, (2017); Bard J.F., Practical bilevel optimization, algorithms and applications, (1998); Bektas T., A note on the lifted Miller-Tucker-Zemlin subtour elimination constraints for the capacitated vehicle routing problem, European Journal of Operational Research, 158, pp. 793-795, (2004); Bergmann F.M., Wagner S.M., Winkenbach M., Integrating first-mile pickup and last-mile delivery on shared vehicle routes for efficient urban e-commerce distribution, Transportation Research Part B: Methodological, 131, pp. 26-62, (2020); Yogesh C.K., Hariharan M., Ngadiran R., Adom A.H., Yaacob S., Berkai C., Polat K., pp. 149-158, (2017); Calvete H.I., Gale C., Iranzo J., (2015); Colson B., Marcotte P., Savard G., An overview of bilevel optimization, Annals of Operations Research, 153, pp. 235-256, (2007); Current J.R., Schilling D.A., The covering salesman problem, Transportation Science, 23, pp. 208-213, (1989); Dempe S., Foundations of bilevel programming, (2002); Desrochers M., Laporte G., Improvements and extensions to the Miller-Tucker-Zemlin subtour elimination constraints, Operations Research Letters, 10, pp. 27-36, (1991); Deutsch Y., Golany B., A parcel locker network as a solution to the logistics last mile problem, International Journal of Production Research, 56, pp. 251-261, (2018); Gendreau M., Laporte G., Semet F., The covering tour problem, Operations Research, 45, pp. 568-576, (1997); Glize E., Roberti R., Jozefowiez N., Ngueveu S.U., Exact methods for mono-objective and Bi-Objective Multi-Vehicle Covering Tour Problems, European Journal of Operational Research, 283, pp. 812-824, (2020); Golden B., Naji-Azimi Z., Raghavan S., Salari M., Toth P., The generalized covering salesman problem, Informs Journal on Computing, 24, pp. 534-553, (2012); Hachicha M., Hodgson M.J., Laporte G., Semet F., Heuristics for the multi-vehicle covering tour problem, Computers Operations Research, 27, pp. 29-42, (2000); Helsgaun K., An effective implementation of the Lin-Kernighan traveling salesman heuristic, European Journal of Operational Research, 126, pp. 106-130, (2000); Jiang L., Dhiaf M., Dong J., Liang C., Zhao S., A traveling salesman problem with time windows for the last mile delivery in online shopping, International Journal of Production Research, (2020); Labbe M., Laporte G., Martin I.R., Gonzalez J.J.S., The ring star problem: Polyhedral analysis and exact algorithm, Networks, 43, pp. 177-189, (2004); Laporte G., Nobert Y., Arpin D., An exact algorithm for solving a capacitated location-routing problem, Annals of Operations Research, 6, pp. 291-310, (1986); Lemke J., Iwan S., Korczak J., Usability of the parcel lockers from the customer perspective – The research in Polish Cities, Transportation Research Procedia, 16, pp. 272-287, (2016); 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Niu Q., Zhang L., Li K., A biogeography-based optimization algorithm with mutation strategies for model parameter estimation of solar and fuel cells, Energy Conversion and Management, 86, pp. 1173-1185, (2014); Pan Q.K., Tasgetiren M.F., Liang Y.C., A discrete particle swarm optimization algorithm for the no-wait flowshop scheduling problem, Computers Operations Research, 35, pp. 2807-2839, (2008); Pan Q.K., Wang L., Zhao B.H., An improved iterated greedy algorithm for the no-wait flow shop scheduling problem with makespan criterion, International Journal of Advanced Manufacturing Technology, 38, pp. 778-786, (2008); Perez J.A.M., Moreno-Vega J.M., Martin I.R., Variable neighborhood tabu search and its application to the median cycle problem, European Journal of Operational Research, 151, pp. 365-378, (2003); Reinelt G., TSPLIB—A traveling salesman problem library, ORSA Journal on Computing, 3, pp. 376-384, (1991); Salari M., Naji-Azimi Z., An integer programming-based local search for the covering salesman problem, Computers & Operations Research, 39, pp. 2594-2602, (2012); Salari M., Reihaneh M., Sabbagh M.S., Combining ant colony optimization algorithm and dynamic programming technique for solving the covering salesman problem, Computers Industrial Engineering, 83, pp. 244-251, (2015); Schwerdfeger S., Boysen N., Optimizing the changing locations of mobile parcel lockers in last-mile distribution, European Journal of Operational Research, 285, pp. 1077-1094, (2020); Shaelaie M.H., Salari M., Naji-Azimi Z., The generalized covering traveling salesman problem, Applied Soft Computing, 24, pp. 867-878, (2014); Simon D., Biogeography-based optimization, IEEE Transactions on Evolutionary Computation, 12, pp. 702-713, (2008); Venkatesh P., Singh A., An artificial bee colony algorithm with variable degree of perturbation for the generalized covering traveling salesman problem, Applied Soft Computing, 78, pp. 481-495, (2019); Wang L., Xu Y., An effective hybrid biogeography-based optimization algorithm for parameter estimation of chaotic systems, Expert Systems with Applications, 38, pp. 15103-15109, (2011); Yang G., Liu Y., Optimizing an equilibrium supply chain network design problem by an improved hybrid biogeography based optimization algorithm, Applied Soft Computing, 58, pp. 657-668, (2017); Zhang J., Chen B., Ye Y., A Multiexchange Local Search Algorithm for the Capacitated Facility Location Problem, Mathematics of Operations Research, 30, pp. 389-403, (2005); Zhao F., Qin S., Zhang Y., Ma W., Zhang C., Song H., A hybrid biogeography-based optimization with variable neighborhood search mechanism for no-wait flow shop scheduling problem, Expert Systems with Applications, 126, pp. 321-339, (2019); Zhao Y., Leng L., Zhang C., A novel framework of hyper-heuristic approach and its application in location-routing problem with simultaneous pickup and delivery, Operational Research, (2019); Zhu W., Duan H., Chaotic predator-prey biogeography-based optimization approach for UCAV path planning, Aerospace Science and Technology, 32, pp. 153-161, (2014)","X. Zang; School of Management, Hefei University of Technology, Hefei, 230009, China; email: xnzang123@126.com",null,"Elsevier Ltd",{"$nulls":5},9574174.0,null,"ESAPE",null,"English","Expert Sys Appl","Article","Final",null,"Scopus","2-s2.0-85115924373"]
["Davidavičienė V.; Al Majzoub M.","Davidavičienė, Vida (35368051300); Al Majzoub, Mohamad (57226436675)","35368051300; 57226436675","Performance of reverse logistics in electronic commerce: a case study from Lebanon and Syria",2021.0,"Transport",36.0,3.0,null,260.0,282.0,22.0,2.0,"10.3846/transport.2021.14956","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85116132418&doi=10.3846%2ftransport.2021.14956&partnerID=40&md5=9e3441f27cdafd74b6dd655c1c151433","Dept of Business Technologies and Entrepreneurship, Vilnius Gediminas Technical University, Lithuania","Davidavičienė V., Dept of Business Technologies and Entrepreneurship, Vilnius Gediminas Technical University, Lithuania; Al Majzoub M., Dept of Business Technologies and Entrepreneurship, Vilnius Gediminas Technical University, Lithuania","The technological advancements facilitated the progress of the Business-To-Consumer (B2C) e-commerce business tremendously. B2C e-commerce has several benefits such as saving costs by decreasing the use of resources, increasing profits, and competitive advantage, especially in the pandemic context. However, this opportunity comes with challenges, and one of such is related to a significant number of products that are returned to the vendor or manufacturer. These challenges in the Reverse Logistics' (RL) in the context of e-commerce become a new phenomenon – Reverse E-Logistics' (REL), because the product in the e-commerce is physical goods or electronic ones like videos, music, books, etc. This study focuses on identifying the most critical factors that impact REL performance and discusses how REL can affect its performance. The methodology used is mainly a literature review, synthesis, survey methods, and Structural Equation Modelling (SEM). This study is done in Lebanon and Syria with a sample of 412 companies that perform B2C e-commerce and are faced with REL' . The results showed that out of the ten factors identified during the literature review, eight factors (management, employees, IT and technology, return policy and procedures/guarantee, infrastructure, organizational structure and culture, customer services/satisfaction, and quality management) have a positive correlation with REL performance. Moreover, improved REL performance results increase in companies' performances. The business research model was created based on performed REL performance in Lebanon and Syria, and this gives new scientific insights and knowledge about REL specificity in developing countries. © 2021 The Author(s). Published by Vilnius Gediminas Technical University.","E-commerce; E-logistics; Performance measurement; Reverse e-logistics; Reverse e-logistics' performance; Reverse logistics; Supply chain","Competition; Developing countries; Electronic commerce; Human resource management; Quality management; E-logistic; e-Logistics; Lebanon; Logistic performance; Performance; Performance measurements; Reverse e-logistic; Reverse e-logistic’ performance; Reverse logistics; Supply chains",{"$nulls":6},"Abebe G. K., Bahn R. A., Chalak A., Yehya A. A. K., Drivers for the implementation of market‐based food safety management systems: Evidence from Lebanon, Food Science & Nutrition, 8, 2, pp. 1082-1092, (2020); Agarwal V., Govindan K., Darbari J. D., Jha P. C., An optimization model for sustainable solutions towards implementation of reverse logistics under collaborative framework, International Journal of System Assurance Engineering and Management, 7, 4, pp. 480-487, (2016); Agrawal S., Singh R. K., Murtaza Q., Triple bottom line performance evaluation of reverse logistics, Competitiveness Review, 26, 3, pp. 289-310, (2016); Al Majzoub M., Davidaviciene V., Comparative analysis of reverse e-logistics' solution in Asia and Europe, International Scientific Conference “Contemporary Issues in Business, Management and Economics Engineering 2019, pp. 890-899, (2019); Al Majzoub M., Davidaviciene V., Meidute-Kavaliauskiene I., Measuring the impact of factors affecting reverse elogistics' performance in the electronic industry in Lebanon and Syria, Independent Journal of Management & Production, 11, 6, pp. 1969-1990, (2020); Alamir I., Ayoubi R. M., Massoud H., Hallak L. A., Transformational leadership, organizational justice and organizational outcomes: A study from the higher education sector in Syria, Leadership & Organization Development Journal, 40, 7, pp. 749-763, (2019); Alsaeed A., Adams C., E-service adoption in developing countries with instability status: the case of e-government in Syria, ECEG 2015 – Proceedings of the 15th European Conference on e-Government, pp. 376-385, (2015); Anderson P., Aleppo in Asia: mercantile networks between Syria, China and post-Soviet Eurasia since 1970, History and Anthropology, 29, 1, pp. S67-S83, (2018); Ardila Gamboa C. D., Ballesteros Riveros F. A., Data envelopment analysis to measure relative performance based on key indicators from a supply network with reverse logistics, INGE CUC, 14, 2, pp. 137-146, (2018); Asian S., Pool J. K., Nazarpour A., Tabaeeian R. A., On the importance of service performance and customer satisfaction in third-party logistics selection: an application of Kano model, Benchmarking: an International Journal, 26, 5, pp. 1550-1564, (2019); Bahn R. A., Abebe G. K., Analysis of food retail patterns in urban, peri-urban and rural settings: a case study from Lebanon, Applied Geography, 87, pp. 28-44, (2017); Bai C., Sarkis J., Integrating and extending data and decision tools for sustainable third-party reverse logistics provider selection, Computers & Operations Research, 110, pp. 188-207, (2019); Bal A., Satoglu S. I., A goal programming model for sustainable reverse logistics operations planning and an application, Journal of Cleaner Production, 201, pp. 1081-1091, (2018); Batarfi R., Jaber M. Y., Aljazzar S. M., A profit maximization for a reverse logistics dual-channel supply chain with a return policy, Computers & Industrial Engineering, 106, pp. 58-82, (2017); Bouzon M., Spricigo R., Rodriguez C. M. T., De Queiroz A. A., Cauchick Miguel P. A., Reverse logistics drivers: empirical evidence from a case study in an emerging economy, Production Planning & Control: the Management of Operations, 26, 16, pp. 1368-1385, (2015); Cannella S., Bruccoleri M., Framinan J. M., Closed-loop supply chains: what reverse logistics factors influence performance?, International Journal of Production Economics, 175, pp. 35-49, (2016); Chen L., Li W., Zhai H., The analysis of reverse logistics model in the e-commerce models, International Journal of Grid and Distributed Computing, 9, 9, pp. 173-184, (2016); Chileshe N., Rameezdeen R., Hosseini M. R., Martek I., Li H. X., Panjehbashi-Aghdam P., Factors driving the implementation of reverse logistics: a quantified model for the construction industry, Waste Management, 79, pp. 48-57, (2018); Chinda T., Examination of factors influencing the successful implementation of reverse logistics in the construction industry: pilot study, Procedia Engineering, 182, pp. 99-105, (2017); Choi Y., Mai D. Q., The sustainable role of the e-trust in the B2C e-commerce of Vietnam, Sustainability, 10, 1, (2018); Cooper A. L., Huscroft J. R., Overstreet R. E., Hazen B. T., Knowledge management for logistics service providers: the role of learning culture, Industrial Management & Data Systems, 116, 3, pp. 584-602, (2016); Da Silveira Guimaraes J. L., Salomon V. A. P., ANP applied to the evaluation of performance indicators of reverse logistics in footwear industry, Procedia Computer Science, 55, pp. 139-148, (2015); Daugherty P. J., Bolumole Y., Grawe S. J., The new age of customer impatience: An agenda for reawakening logistics customer service research, International Journal of Physical Distribution & Logistics Management, 49, 1, pp. 4-32, (2019); Davidaviciene V., Raudeliuniene J., Tvaronaviciene M., Kausinis J., The importance of security aspects in consumer preferences in electronic environment, Journal of Security and Sustainability Issues: International Entrepreneurial Perspectives and Innovative Outcomes, 8, 3, pp. 399-411, (2019); El Rassi M. A. 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J., Huang C.-J., Salient task environment, reverse logistics and performance, International Journal of Physical Distribution & Logistics Management, 45, 9, pp. 979-1006, (2015); Ibeh K., Kasem L., The network perspective and the internationalization of small and medium sized software firms from Syria, Industrial Marketing Management, 40, 3, pp. 358-367, (2011); Jianu Iu, Jianu Io, Turlea C., Measuring the company's real performance by physical capital maintenance, Economic Computation and Economic Cybernetics Studies and Research, 51, 1, pp. 37-57, (2017); Keshavarz Ghorabaee M., Amiri M., Olfat L., Khatami Firouzabadi S. M. A., Designing a multi-product multi-period supply chain network with reverse logistics and multiple objectives under uncertainty, Technological and Economic Development of Economy, 23, 3, pp. 520-548, (2017); Li Y.-L., Ying C.-S., Chin K.-S., Yang H.-T., Xu J., Thirdparty reverse logistics provider selection approach based on hybrid-information MCDM and cumulative prospect theory, Journal of Cleaner Production, 195, pp. 573-584, (2018); Mahindroo A., Samalia H. V., Verma P., Moderated influence of return frequency and resource commitment on information systems and reverse logistics strategic performance, International Journal of Productivity and Performance Management, 67, 3, pp. 550-570, (2018); Morgan T. R., Tokman M., Richey R. G., Defee C., Resource commitment and sustainability: a reverse logistics performance process model, International Journal of Physical Distribution & Logistics Management, 48, 2, pp. 164-182, (2018); Mouchawar R., Souq.com's CEO on building an e-commerce powerhouse in the Middle East, Harvard Business Review, 5, pp. 35-38, (2017); Mouselli S., Khalifa B., Entrepreneurship in crisis: the determinants of Syrian students' entrepreneurial intentions, Business, Management and Education, 15, 2, pp. 159-173, (2017); Nisar T. M., Prabhakar G., What factors determine e satisfaction and consumer spending in e-commerce retailing?, Journal of Retailing and Consumer Services, 39, pp. 135-144, (2017); Ochocka J., Mobile technologies in logistic customer service as a tool for winning customers' satisfaction, LogForum: Scientific Journal of Logistics, 15, 3, pp. 403-411, (2019); Pandian G. R. 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Q., Efficient intermodal transportation auctions for B2B e-commerce logistics with transaction costs, Transportation Research Part B: Methodological, 80, pp. 322-337, (2015); Xu Y., Zhang X., Cao J., Chen Y., Ye X., Collaboration and evolution of e-commerce and express delivery industry supply chain, Discrete Dynamics in Nature and Society, 2016, (2016); Yadav D. K., Barve A., Analysis of critical success factors of humanitarian supply chain: an application of interpretive structural modeling, International Journal of Disaster Risk Reduction, 12, pp. 213-225, (2015); Yu H., Solvang W. D., A carbon-constrained stochastic optimization model with augmented multi-criteria scenariobased risk-averse solution for reverse logistics network design under uncertainty, Journal of Cleaner Production, 164, pp. 1248-1267, (2017); Zaidan E., Analysis of ICT usage patterns, benefits and barriers in tourism SMEs in the Middle Eastern countries: the case of Dubai in UAE, Journal of Vacation Marketing, 23, 3, pp. 248-263, (2017)","V. Davidavičienė; Dept of Business Technologies and Entrepreneurship, Vilnius Gediminas Technical University, Lithuania; email: vida.davidaviciene@vilniustech.lt",null,"Vilnius Gediminas Technical University",{"$nulls":5},1.6484142E7,null,null,null,"English","Transport","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85116132418"]
["Álvarez-Miranda E.; Pereira J.","Álvarez-Miranda, Eduardo (39260996600); Pereira, Jordi (55426276000)","39260996600; 55426276000","A districting application with a quality of service objective",2022.0,"Mathematics",10.0,1.0,13.0,null,null,null,2.0,"10.3390/math10010013","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121610877&doi=10.3390%2fmath10010013&partnerID=40&md5=eda9c71771bc1520fea5478483840868","School of Economics and Business, Universidad de Talca, Talca, 3460000, Chile; Faculty of Engineering and Sciences, Universidad Adolfo Ibáñez, Av. Padre Hurtado 750, Viña del Mar, 2520000, Chile; UPF Barcelona School of Management, Universitat Pompeu Fabra, C. Balmes 132-134, Barcelona, 08008, Spain","Álvarez-Miranda E., School of Economics and Business, Universidad de Talca, Talca, 3460000, Chile; Pereira J., Faculty of Engineering and Sciences, Universidad Adolfo Ibáñez, Av. Padre Hurtado 750, Viña del Mar, 2520000, Chile, UPF Barcelona School of Management, Universitat Pompeu Fabra, C. Balmes 132-134, Barcelona, 08008, Spain","E-commerce sales have led to a considerable increase in the demand for last-mile delivery companies, revealing several problems in their logistics processes. Among these problems, are not meeting delivery deadlines. For example, in Chile, the national consumer service (SERNAC) indicated that in 2018, late deliveries represented 23% of complaints in retail online sales and were the second most common reason for complaints. Some of the causes are incorrectly designed delivery zones because in many cases, these delivery zones do not account for the demographic growth of cities. The result is an imbalanced workload between different zones, which leads to some resources being idle while others fail to meet their workload in satisfactory conditions. The present work proposes a hybrid method for designing delivery zones with an objective based on improving the quality of express delivery services. The proposed method combines a preprocess based on the grouping of demand in areas according to the structure of the territory, a heuristic that generates multiple candidates for the distribution zones, and a mathematical model that combines the different distribution zones generated to obtain a final territorial design. To verify the applicability of the proposed method, a case study is considered based on the real situation of a Chilean courier company with low service fulfillment in its express deliveries. The results obtained from the computational experiments show the applicability of the method, highlighting the validity of the aggregation procedure and improvements in the results obtained using the hybrid method compared to the initial heuristic. The final solution improves the ability to meet the conditions associated with express deliveries, compared with the current situation, by 12 percentage points. The results also allow an indicative sample of the critical service factors of a company to be obtained, identifying the effects of possible changes in demand or service conditions. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.","Districting; Hybrid heuristics; Last-mile delivery",{"$nulls":5},"National Agency of Research and Development; Fondo Nacional de Desarrollo Científico y Tecnológico, FONDECYT, (1180670); Instituto de Sistemas Complejos de Ingeniería, ISCI, (ANID PIA/BASAL AFB180003)","Funding: E. Álvarez-Miranda acknowledges the support of the National Agency of Research and Development (ANID), Chile, through the grant FONDECYT N.1180670 and through the Complex Engineering Systems Institute ANID PIA/BASAL AFB180003. J. Pereira acknowledges the support of ANID through the grant FONDECYT N.1180670.","Gevaers R., Van de Voorde E., Vanelslander T., Characteristics and Typology of Last-mile Logistics from an Innovation Perspective in an Urban Context, City Distribution and Urban Freight Transport, pp. 56-71, (2011); Retail e-Commerce Sales Worldwide from 2014 to 2024; Chopra S., Designing the Distribution Network in a Supply Chain, Transp. Res. Part E, 39, pp. 123-140, (2003); Cho J., Ozment J., Sink H., Logistics Capability, Logistics Outsourcing and Firm Performance in an E-commerce Market, Int. J. Phys. Distrib. 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Sci, 33, pp. 269-290, (2019); Caro F., Shirabe T., Guignard M., Weintraub A., School redistricting: Embedding GIS tools with integer programming, J. Oper. Res. Soc, 55, pp. 836-849, (2004); Rios-Mercado R., Bard J., An exact algorithm for designing optimal districts in the collection of waste electric and electronic equipment through an improved reformulation, Eur. J. Oper. Res, 276, pp. 259-271, (2019); Lin H., Kao J., Subregion districting analysis for municipal solid waste collection privatization, J. Air Waste Manag. Assoc, 58, pp. 104-111, (2008); Cortinhal M., Mourao M., Nunes A., Local search heuristics for sectoring routing in a household waste collection context, Eur. J. Oper. Res, 255, pp. 68-79, (2016); Jarrah A., Bard J., Large-scale pickup and delivery work area design, Comput. Oper. Res, 39, pp. 3102-3118, (2012); Gonzalez-Ramirez R., Smith N., Askin R., Camacho-Vallejo J., Gonzalez-Velarde J., A GRASP-Tabu Heuristic Approach to Territory Design for Pickup and Delivery Operations for Large-Scale Instances, Math. Probl. Eng, 2017, (2017); Kalcsics J., Nickel S., Schroder M., Towards a unified territorial design approach—Applications, algorithms and GIS integration, TOP, 13, pp. 1-56, (2005); Salazar-Aguilar M., Rios-Mercado R., Gonzalez-Velarde J., GRASP strategies for a bi-objective commercial territory design problem, J. Heuristics, 19, pp. 179-200, (2013); Moreno S., Pereira J., Yushimito W., A hybrid K-means and integer programming method for commercial territory design: A case study in meat distribution, Ann. Oper. Res, 286, pp. 87-117, (2020); Novaes A., Graciolli O., Designing multi-vehicle delivery tours in a grid-cell format, Eur. J. Oper. 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Res, 243, pp. 588-598, (2015); Galvao L., Novaes A., Cursi E., Souza J., A multiplicatively-weighted Voronoi diagram approach to logistics districting, Comput. Oper. Res, 33, pp. 93-114, (2006); Rios-Mercado R., Fernandez E., A reactive GRASP for a commercial territory design problem with multiple balancing requirements, Comput. Oper. Res, 36, pp. 755-776, (2009); Fernandez E., Kalcsics J., Nickel S., A novel maximum dispersion territory design model arising in the implementation of the WEEE-directive, J. Oper. Res. Soc, 61, pp. 503-514, (2010); Gonzalez-Ramirez R., Smith N., Askin R., Kalashnikov V., A heuristic approach for a logistics districting problem, Int. J. Innov. Comput. Inf. Control, 6, pp. 3551-3562, (2010); Lei H., Wang R., Laporte G., Solving a multi-objective dynamic stochastic districting and routing problem with a co-evolutionary algorithm, Comput. Oper. Res, 67, pp. 12-24, (2016); Bozkaya B., Erkut E., Laporte G., A tabu search heuristic and adaptive memory procedure for political districting, Eur. J. Oper. Res, 144, pp. 12-26, (2003); Tavares-Pereira F., Figueira J., Mousseau V., Roy B., Multiple criteria districting problems: The public transportation network pricing system of the Paris region, Ann. Oper. Res, 154, pp. 69-92, (2007); Ricca F., Scozzari A., Simeone B., Weighted Voronoi region algorithms for political districting, Math. Comput. Model, 48, pp. 1468-1477, (2007); Hopcroft J., Tarjan R., Algorithm 447: Efficient algorithms for graph manipulation, Commun. ACM, 16, pp. 372-378, (1973); Garey M., Johnson D., Computers and Intractability: A Guide to the Theory of NP-Completeness (Series of Books in the Mathematical Sciences), (1979); Resende M., Ribeiro C., Path-relinking, Optimization by GRASP, pp. 167-188, (2016); Hollander M., Wolfe D., Chicken E., Nonparametric Statistical Methods, (2014)","E. Álvarez-Miranda; School of Economics and Business, Universidad de Talca, Talca, 3460000, Chile; email: ealvarez@utalca.cl",null,"MDPI",{"$nulls":5},2.227739E7,null,null,null,"English","Mathematics","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85121610877"]
["Wei L.; Kapuscinski R.; Jasin S.","Wei, Lai (57226684610); Kapuscinski, Roman (6602219108); Jasin, Stefanus (55226201500)","57226684610; 6602219108; 55226201500","Shipping consolidation across two warehouses with delivery deadline and expedited options for E-commerce and Omni-channel Retailers",2021.0,"Manufacturing and Service Operations Management",23.0,6.0,null,1634.0,1650.0,16.0,12.0,"10.1287/msom.2020.0903","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85120429709&doi=10.1287%2fmsom.2020.0903&partnerID=40&md5=ef50fb6567b5b93581de0774b23a0c3c","Wallace E. Carroll School of Management, Boston College, Chestnut Hill, 02467, MA, United States; Stephen M. Ross School of Business, University of Michigan, Ann Arbor, 48109, MI, United States","Wei L., Wallace E. Carroll School of Management, Boston College, Chestnut Hill, 02467, MA, United States; Kapuscinski R., Stephen M. Ross School of Business, University of Michigan, Ann Arbor, 48109, MI, United States; Jasin S., Stephen M. Ross School of Business, University of Michigan, Ann Arbor, 48109, MI, United States","Problem definition: Shipment consolidation (i.e., shipping multiple orders together instead of shipping them separately) is commonly used to decrease total shipping costs. However, when the delivery of some orders is delayed, so they can be consolidated with future orders, a more expensive expedited shipment may be needed to meet shorter deadlines. In this paper, we study the optimal consolidation policy focusing on the tradeoff between economies of scale due to combining orders and expedited shipping costs, in the setting of two warehouses. Academic/practical relevance: Our work is motivated by the application of fulfillment consolidation in e-commerce and omni-channel retail, especially with the rise of so-called on-demand logistics services. Sellers have the flexibility to take advantage of consolidation by deciding when to ship the orders and from which warehouse to fulfill the orders, as long as the orders’ deadlines are met. Methodology: We use Dynamic Programming to study the optimal policy and its structure. We also conduct extensive simulation tests to evaluate the performance of heuristics that are based on structures of the optimal policies. Results: The optimal policies and their structures are characterized. Using the insights of these structural properties, we propose two easily implementable heuristics that perform within 1%–2% of the optimal solution and outperform other benchmark consolidation methods in numerical tests. Managerial implications: Consolidation is shown to significantly reduce the outbound shipping costs. Retailers can take advantage of it to effectively improve the standard policies by simply applying the threshold-form heuristics we propose. © 2020 INFORMS.","Consolidation; Deadline-driven logistics; Expedited shipment","Dynamic programming; Electronic commerce; Heuristic methods; Numerical methods; Sales; Structural optimization; Warehouses; Deadline-driven logistic; Delivery deadlines; E- commerces; Economy of scale; Expedited shipment; Multiple orders; Optimal policies; Problem definition; Shipping cost; Two-warehouse; Ships",{"$nulls":4},"National Science Foundation, NSF, (1561791)","Funding: This work was supported by that National Science Foundation [award 1561791]. Supplemental Material: The e-companion is available at https://doi.org/10.1287/msom.2020.0903.","Acimovic J, Graves SC, Making better fulfillment decisions on the fly in an online retail environment, Manufacturing Service Oper. Management, 17, 1, pp. 34-51, (2015); Annual Report, (2018); Personal communication with a co-founder of one of the largest online retailer in China, (2017); Caggiano KE, Muckstadt JA, Rappold JA, Integrated real-time capacity and inventory allocation for reparable service parts in a two-echelon supply system, Manufacturing Service Oper. Management, 8, 3, pp. 292-319, (2006); Cetinkaya S, Coordination of inventory and shipment consolidation decisions: A review of premises, models, and justification, Applications of Supply Chain Management and e-Commerce Research, pp. 3-51, (2005); Cetinkaya S, Tekin E, Lee CY, A stochastic model for integrated inventory replenishment and outbound shipment release decisions, IIE Trans, 40, 8, pp. 324-340, (2008); Daganzo CF, Shipment composition enhancement at a consolidation center, Transportation Res. Part B: Methodology, 22, 2, pp. 103-124, (1988); Fell J, Five tips for saving money on shipping, (2011); Gil R, Korkmaz E, Sahin O, Optimal pricing of access and secondary goods with repeat purchases: Evidence from online grocery shopping and delivery fees, (2014); Gosavi A, Simulation-Based Optimization: Parametric Optimization Techniques and Reinforcement Learning, (2003); Gupta YP, Bagchi PK, Inbound freight consolidation under just-in-time procurement: application of clearing models, J. Bus. Logist, 8, 2, pp. 74-94, (1987); Hausmann L, Herrmann NA, Krause J, Netzer T, Same-day delivery: The next evolutionary step in parcel logistics, (2014); Higginson JK, Bookbinder JH, Policy recommendations for a shipment consolidation program, J. Bus. Logist, 15, 1, pp. 87-112, (1994); Huggins EL, Olsen TL, Supply chain management with guaranteed delivery, Management Sci, 40, 9, pp. 1154-1167, (2003); Jasin S, Sinha A, An LP-based correlated rounding scheme for multi-item ecommerce order fulfillment, Oper. Res, 63, 6, pp. 1336-1351, (2015); Lei Y, Jasin S, Sinha A, Joint dynamic pricing and order fulfillment for e-commerce retailers, Manufacturing Service Oper. Management, 20, 2, pp. 269-284, (2018); Lewis M, Singh V, Fay S, An empirical study of the impact of nonlinear shipping and handling fees on purchase incidence and expenditure decisions, Marketing Sci, 25, 1, pp. 51-64, (2006); Lovasz L, Combinatorial Problems and Exercises, 361, (1993); Qi L, Lee K, Supply chain risk mitigations with expedited shipping, Omega, 57, pp. 98-113, (2015); Xu PJ, Allgor R, Graves SC, Benefits of reevaluating real-time order fulfillment decisions, Manufacturing Service Oper. Management, 11, 2, pp. 340-355, (2009); Zhou SX, Chao X, Newsvendor bounds and heuristics for serial supply chains with regular and expedited shipping, Naval Res. Logist, 57, 1, pp. 71-87, (2010)",null,null,"INFORMS Inst.for Operations Res.and the Management Sciences",{"$nulls":5},1.5234614E7,null,"MSOMF",null,"English","Manuf. Serv. Oper. Manage.","Article","Final",null,"Scopus","2-s2.0-85120429709"]
["Yu B.; Zhao A.","Yu, Baojun (57212346974); Zhao, Anni (57223344562)","57212346974; 57223344562","Development of internet finance industry with the core of e-commerce platform services optimised by the edge computing of the internet of things based on artificial intelligence",2022.0,"International Journal of Ad Hoc and Ubiquitous Computing",39.0,4.0,null,192.0,200.0,8.0,3.0,"10.1504/IJAHUC.2022.121651","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85127724135&doi=10.1504%2fIJAHUC.2022.121651&partnerID=40&md5=f476ce1824a153d8bdc959b26e0d43e6","Department of Management Science and Engineering, School of Management, Jilin University, Changchun, 130022, China; School of Management, Jilin University, Changchun, 130022, China","Yu B., Department of Management Science and Engineering, School of Management, Jilin University, Changchun, 130022, China; Zhao A., School of Management, Jilin University, Changchun, 130022, China","This article mainly discusses how to use internet edge computing to optimise IoT logistics services. This article conducted face-to-face interviews with 178 online shoppers and invited them to fill out a structured questionnaire. Finally, the data was analysed using Pearson correlation and multiple regression models. The results show that service recovery, delivery service and customer service are positive factors affecting customer satisfaction. The internet of things optimised based on artificial intelligence edge computing is of great significance to the service optimisation of e-commerce platforms. © 2022 Inderscience Enterprises Ltd.. All rights reserved.","e-commerce platform; edge computing; internet of things; IOT; logistics services","Artificial intelligence; Correlation methods; Customer satisfaction; Edge computing; Electronic commerce; Regression analysis; Surveys; Commerce platforms; E- commerces; E-commerce platform; Edge computing; Face-to-face interview; Finance industries; IOT; Logistics services; Online shops; Pearson correlation; Internet of things",{"$nulls":4},"Jilin University, JLU, (2019QY017)","This research was supported by The Frontier and Innovative Project of Philosophy, Social Science and Interdisciplinary in the Jilin University (Grant No. 2019QY017).","Amin M., Internet banking service quality and its implication on e-customer satisfaction and e-customer loyalty, International Journal of Bank Marketing, 34, 3, pp. 280-306, (2016); Bellavista P., Chessa S., Foschini L., Et al., Human-enabled edge computing: exploiting the crowd as a dynamic extension of mobile edge computing, IEEE Communications Magazine, 56, 1, pp. 145-155, (2018); Biswas S., Devi D., Chakraborty M., A hybrid case based reasoning model for classification in internet of things (IoT) environment, Journal of Organizational and End User Computing, 30, 4, pp. 104-122, (2018); The internet of things, Communications of the ACM, 60, 5, pp. 18-19, (2017); Camarinhamatos L., Tomic S., Graca P., Technological innovation for the internet of things, IFIP Advances in Information & Communication Technology, 25, 2, pp. 617-622, (2016); Chamberlain A., Crabtree A., Haddadi H., Et al., Special theme on privacy and the internet of things, Personal & Ubiquitous Computing, 22, 8, pp. 289-292, (2018); Chen H., Chen Y., Yang L., Intelligent early structural health prognosis with nonlinear system identification for RFID signal analysis, Computer Communications, 157, pp. 150-161, (2020); Chen Y., Lee G.M., Shu L., Et al., Industrial internet of things-based collaborative sensing intelligence: framework and research challenges, Sensors, 16, 2, (2016); Chiang M., Zhang T., Fog and IoT: an overview of research opportunities, IEEE Internet of Things Journal, 3, 6, pp. 854-864, (2016); Corcoran P., Datta S.K., Mobile-edge computing and the internet of things for consumers: extending cloud computing and services to the edge of the network, IEEE Consumer Electronics Magazine, 5, 4, pp. 73-74, (2016); Durresi M., Subashi A., Durresi A., Et al., Secure communication architecture for internet of things using smartphones and multi-access edge computing in environment monitoring, Journal of Ambient Intelligence & Humanized Computing, 10, 4, pp. 1-10, (2018); Elsayed W., Elhoseny M., Sabbeh S., Riad A., Self-maintenance model for wireless sensor networks, Computers & Electrical Engineering, 70, pp. 799-812, (2018); Fan Q., Ansari N., Application aware workload allocation for edge computing based IoT, IEEE Internet of Things Journal, 5, 3, pp. 2146-2153, (2018); Glazener M., The internet of things, Scientific American, 4, 1, pp. 20-25, (2017); Gu F., Guo J., Zhang W., Summers P.A., Hall P., From waste plastics to industrial raw materials: a life cycle assessment of mechanical plastic recycling practice based on a real-world case study, Science of the Total Environment, 601-602, pp. 1192-1207, (2017); Hida I., Takamaeda-Yamazaki S., Ikebe M., Et al., A high performance and energy efficient microprocessor with a novel restricted dynamically reconfigurable accelerator, Circuits & Systems, 8, 5, pp. 134-147, (2017); Himstedt M., Maehle E., Online semantic mapping of logistic environments using RGB-D cameras, International Journal of Advanced Robotic Systems, 14, 4, pp. 1-8, (2017); Hosseinabadi A.A.R., Vahidi J., Saemi B., Sangaiah A.K., Elhoseny M., Extended genetic algorithm for solving open-shop scheduling problem, Soft Computing, 23, 13, pp. 5099-5116; Huang Z., Nie J., Tsai S-B., Dynamic collection strategy and coordination of a remanufacturing closed-loop supply chain under uncertainty, Sustainability, 9, 5, (2017); Joseph N., Kar A.K., Ilavarasan P.V., Ganesh S., Review of discussions on internet of things (IoT): insights from Twitter analytics, Journal of Global Information Management, 25, 2, pp. 38-51, (2017); Kaur J., Kaur K., Internet of things: a review on technologies, architecture, challenges, applications, future trends, International Journal of Computer Network & Information Security, 9, 4, pp. 57-70, (2017); Kavun S., Topicality investigation of economic definitions in the cash flow area by the tools of internet-analysis, Decisions in Economics & Finance, 4, 2, pp. 48-53, (2016); Li C., Yang H.J., Sun F., Cioffi J.M., Yang L., Multiuser overhearing for cooperative two-way multiantenna relays, IEEE Transactions on Vehicular Technology, 65, 5, pp. 3796-3802, (2016); Lv Z., The security of internet of drones, Computer Communications, 148, 2, pp. 208-214, (2019); Lv Z., Security of internet of things edge devices, Softw.: Pract. Exper, 3, pp. 1-11, (2020); Lv Z., Song H., Mobile internet of things under data physical fusion technology, IEEE Internet of Things Journal, 7, 5, pp. 4616-4624, (2019); Lv Z., Hu B., Lv H., Infrastructure monitoring and operation for smart cities based on IoT system, IEEE Transactions on Industrial Informatics, 16, 3, pp. 1957-1962, (2020); Lv Z., Yang H.A.N., Singh A.K., Manogaran G., Lv H., Trustworthiness in industrial IoT systems based on artificial intelligence, IEEE Transactions on Industrial Informatics, (2020); Lv Z., Qiao L., Song H., Analysis of the security of internet of multimedia things, ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), (2020); Margaris D., Vassilakis C., Exploiting internet of things information to enhance venues' recommendation accuracy, Service Oriented Computing & Applications, 11, 1, pp. 393-409, (2017); Metawa N., Elhoseny M., Hassan M.K., Hassanien A.E., Loan portfolio optimization using genetic algorithm: a case of credit constraints, Proceedings of 12th International Computer Engineering Conference, ICENCO 2016: Boundless Smart Societies, pp. 59-64, (2016); Moskvitch K., Internet of things heads for home [news briefing], Engineering & Technology, 10, 9, (2016); Mulatu M.A., Chang L-C., Han Y.S., Mengistu F.G., Tseng D-F., Threshold-based cooperative communication of energy harvesting active networked tags, International Journal of Ad Hoc and Ubiquitous Computing, 24, 4, pp. 225-236, (2017); Munoz R., Et al., Integration of IoT, transport SDN, and edge/cloud computing for dynamic distribution of IoT analytics and efficient use of network resources, Journal of Lightwave Technology, 36, 7, pp. 1420-1428, (2018); Murphy M., The internet of things and the threat it poses to DNS, Network Security, 2017, 7, pp. 17-19, (2017); Qu Q., Chen K.Y., Wei Y.M., Liu Y., Tsai S.B., Dong W., Using hybrid model to evaluate performance of innovation and technology professionals in marine logistics industry, Mathematical Problems in Engineering, (2015); Satyanarayanan M., Edge computing, Computer, 50, 10, pp. 36-38, (2017); Shahzadi S., Iqbal M., Dagiuklas T., Et al., Multi-access edge computing: open issues, challenges and future perspective, Journal of Cloud Computing Advances Systems & Applications, 6, 1, (2017); Shi W., Et al., Edge computing: vision and challenges, IEEE Internet of Things Journal, 3, 5, pp. 637-646, (2016); Singh E., Meyyappan M., Nalwa H.S., Flexible graphene-based wearable gas and chemical sensors, ACS Applied Materials & Interfaces, 9, 40, (2017); Sivieri A., Mottola L., Cugola G., Building internet of things software with ELIoT, Computer Communications, 89, 2, pp. 141-153, (2016); Strang K.D., Vajjhala N.R., Student resistance to a mandatory learning management system in online supply chain courses, Journal of Organizational and End User Computing, 29, 3, pp. 49-67, (2017); Tsai S-B., Huang C-Y., Yu C., Chen Q., Et al., Using a mixed model to evaluate job satisfaction in high-tech industries, Plos One, 11, 5, (2016); Wan S., Zhao Y., Wang T., Gu Z., Abbasi Q.H., Choo K.K.R., Multi-dimensional data indexing and range query processing via Voronoi diagram for internet of things, Future Generation Computer Systems, 91, 2, pp. 382-391, (2019); Wang B., Chen L.L., New results on the control for a kind of uncertain chaotic systems based on fuzzy logic, Complexity, pp. 1-8, (2019); Wright A., Mapping the internet of things, Communications of the ACM, 60, 1, pp. 16-18, (2016); Xiao F., Multi-sensor data fusion based on the belief divergence measure of evidences and the belief entropy, Information Fusion, 46, pp. 23-32, (2019); Yang C., Yang Z., Deng Z., Robust weighted state fusion Kalman estimators for networked systems with mixed uncertainties, Information Fusion, 45, pp. 246-265, (2019); Yu P., Zhou F., Zhang X., Qiu X., Kadoch M., Cheriet M., Deep learning-based resource allocation for 5G broadband TV service, IEEE Transactions on Broadcasting, 66, 4, pp. 800-813, (2020); Zhang H., Chen Z., Wu J., Et al., Energy-efficient online resource management and allocation optimization in multi-user multi-task mobile-edge computing systems with hybrid energy harvesting, Sensors, 18, 9, (2018); Zhang Y., He Q., Chen G., Zhang X., Xiang Y., A low-overhead, confidentiality-assured, and authenticated data acquisition framework for IoT, IEEE Transactions on Industrial Informatics, (2019); Zou Y., Liu W., Wu K., Et al., Wi-Fi radar: recognizing human behavior with commodity Wi-Fi, IEEE Communications Magazine, 55, 10, pp. 105-111, (2017)","B. Yu; Department of Management Science and Engineering, School of Management, Jilin University, Changchun, 130022, China; email: baojunyu1978@163.com",null,"Inderscience Publishers",{"$nulls":5},1.7438225E7,null,null,null,"English","Int. J. Ad Hoc Ubiquitous Comput.","Article","Final",null,"Scopus","2-s2.0-85127724135"]
["Sari A.; Ramelan M.R.; Safitri D.; Inas N.","Sari, Aida (57469977900); Ramelan, Mudji Rachmat (57469611400); Safitri, Dina (57469611500); Inas, Nuzul (57469124200)","57469977900; 57469611400; 57469611500; 57469124200","Trust Perception and Payment Method on Marketplace in Indonesia (Study on Shopee)",2022.0,"WSEAS Transactions on Business and Economics",19.0,null,null,62.0,73.0,11.0,1.0,"10.37394/23207.2022.19.7","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85125389006&doi=10.37394%2f23207.2022.19.7&partnerID=40&md5=7306395bb6edec8a31a82df5ff426649","Department of Management, Faculty of Economics and Business, Universitas Lampung, Indonesia","Sari A., Department of Management, Faculty of Economics and Business, Universitas Lampung, Indonesia; Ramelan M.R., Department of Management, Faculty of Economics and Business, Universitas Lampung, Indonesia; Safitri D., Department of Management, Faculty of Economics and Business, Universitas Lampung, Indonesia; Inas N., Department of Management, Faculty of Economics and Business, Universitas Lampung, Indonesia","The rapid development of e-commerce in Indonesia has led to the emergence of competition. One of the e-commerce platforms that is aggressive in promoting and widely used by Indonesian consumers is Shopee. Shopee conducts promotions in Indonesia to bring new shopping experiences to facilitate easy sales and provide shoppers with secure payment processes and integrated logistics arrangements.The research purpose is to determine reputation’s effect, privacy, size, safeguard, web familiarity, and ease in creating a positive effect on confidence; and trust variable will have a positive effect on payment methods using the electronic payment system (EPS), credit cards and cash on delivery on product purchases at online shops in Indonesia. The research methodology uses quantitative methods with a cross-sectional research design by distributing questionnaires online with a Google Form, with 248 respondents. The study led to the findings of the perceptions of trust significantly influenced by security, benefits, and convenience, while reputation, privacy, size, and web familiarization do not affect trust. Furthermore, trust affects the electronic payment method (EPS), credit card, and cash on delivery. The limitation of the study is in the sampling method which covers not all regions in Indonesia. Contribution: as a company, Shopee should maintain security, the benefits, and convenience to develop strategies using electronic payment methods. © 2022, World Scientific and Engineering Academy and Society. All rights reserved.","E-commerce; Online Shop; Trust and method of payment",{"$nulls":7},"Abbad M., Abbad R., Saleh M., Limitations of e-commerce in developing countries: Jordan case, Education, Business and Society: Contemporary Middle Eastern Issues, 4, 4, pp. 280-291, (2011); Al-Debei M.M., Al-Lozi E., Explaining and predicting the adoption intention of mobile data services: a value-based approach, Computers in Human Behavior, 35, pp. 326-338, (2014); Josang Audun., Trust and Reputation System, The International Journal of Management Science, pp. 725-737, (2007); Belanger France, Et al., Trustworthiness in Electronic Commerce: The Role of Privacy, Security, and Site Attributes, Journal of Strategic Information Systems, 11, (2002); Karahanna E., Straub D.W., Trust and TAM in online shopping: an integrated model, MIS Quarterly, 27, 1, pp. 51-90, (2003); Doney P.M, Cannon J.P., An Examination of the nature of trust in buyer-seller relationships, Journal of Marketing, 30, 2, (1997); Developing a customer value-based theory of the firm, Journal of the Academy of Marketing Science, 25, pp. 162-167, (1997); Gefen D., E-commerce: The Role of Familiarity and Trust, The International Journal of Management Science, 28, pp. 725-737, (2000); Gefen D., Straub D.W., Managing user trust in B2C e-services, E-service journal, 2, 2, pp. 7-24, (2003); Gotsi M., Wilson A., Corporate reputation: seeking a definition, Corporate Communications: An International Journal, 6, 1, pp. 24-30, (2001); Hsiao K., Lin J., Wang X., Lu H., Yu H., Antecedents and consequences of trust in online product recommendations: an empirical study in social shopping, Online Information Review, 34, 6, pp. 935-953, (2010); Jarvenpaa S. L., Consumer trust in an internet store, Information Technology and Management, 1, pp. 45-71, (2000); Kim C., Tao W., Shin N., Kim K.S., An Empirical Study of Customers’ Perceptions of Security and Trust in E-Payment Systems. Electronic Commerce Research and Applications, 9, 84-95. use mobile payment, (2010); Lee I., Kim J., Choi B., Hong S.J., Measurement development for cultural characteristics of mobile internet users at the individual level, Computers in Human Behavior, 26, 6, pp. 1355-1368, (2010); Lin H.F., An empirical investigation of mobile banking adoption: the effect of innovation attributes and knowledge-based trust, International Journal of Information Management, 31, 3, pp. 252-260, (2011); Mangin Jean. P. L., Bourgault N., dan Guerrero M. M., Modelling Perceived Usefulness on Adopting Online Banking Through the TAM Model in A Canadian Banking Environment, Journal of Internet Banking and Commerce. (online), 16, 1, (2008); McKnight D.H., Choudhury V., Kacmar C., Developing and validating trust measures for e-commerce: an integrative typology, Information Systems Research, 13, 3, pp. 334-359, (2002); Nyengerai Sarah, Jaravaza Divaries, Mukucha Paul, Chirimubwe Ranganai, Manjoro Evans, Determinants of Perception towards Private Label Brands in Zimbabwe: The Role of Familiarity, Store Image, Demographic Factors and Consumer Characteristics, Greener Journal of Business and Management Studies, 3, 5, pp. 224-230, (2013); Sumanjeet S., Emergence of Payment Systems in the Age of Electronic Commerce: The State of Art, Global Journal of International Business Research, pp. 17-36, (2009); Tsiakis T., Sthephanides G., The concept of security and trust in electronic payments, Computers & Security, 24, 1, pp. 10-11, (2005); Faqih K.M.S., Integrating perceived risk and trust with technology acceptance model: an empirical assessment of customers’ acceptance of online shopping in Jordan, 2011 International Conference on Research and Innovation in Information Systems (ICRIIS), pp. 1-5, (2011); Nuri H., A Study of Role of the Factors Influencing the Acceptance of E-Banking, 3, pp. 521-525, (2014); Hoffman L.D., Novak T.P., Building Consumer Trust in Online Environment: The Case for Information’s Security, (1998); Zhang Sun, Optimal VAr planning in area power system, International Conference on Power System Technology, (2011); Ackerman Marks S., Davis Donald T., Privacy and Security Issues in E-Commerce, The New Economy Handbook; Almuntaha Eska, Faktor-Faktor yang Mempengaruhi Pengadopsian Teknologi Internet Banking oleh Nasabah di Indonesia, (2008); Laudon C., Kenneth, Laudon Jane, System Information Management, (2005); Sistem Informasi Keperilakuan, (2008); Maqableh M., Analysis and Design Security Primitives Based on Chaotic Systems for eCommerce, (2012)",null,null,"World Scientific and Engineering Academy and Society",{"$nulls":5},1.1099526E7,null,null,null,"English","WSEAS Trans. Busi. Econ.","Article","Final",null,"Scopus","2-s2.0-85125389006"]
["Wang M.; Yang W.","Wang, Mengmeng (57221049253); Yang, Wenjie (57356914400)","57221049253; 57356914400","What drives rural consumers to change e-commerce attitude and adopt e-commerce through the moderating role of corporate social responsibility in an emerging market? An empirical investigation in the chinese context",2021.0,"Sustainability (Switzerland)",13.0,23.0,13148.0,null,null,null,1.0,"10.3390/su132313148","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85120171887&doi=10.3390%2fsu132313148&partnerID=40&md5=de8d95b3d98c085309d2cfb71e0f13d7","College of Business, Gachon University, Seongnam, 13120, South Korea","Wang M., College of Business, Gachon University, Seongnam, 13120, South Korea; Yang W., College of Business, Gachon University, Seongnam, 13120, South Korea","The present study aims to introduce a comprehensive framework that may help to better understand how to make rural consumers hold a favorable attitude and enhance their willingness to adopt e-commerce. To empirically assess the hypotheses posited in this paper, we started by conducting a qualitative interview-based study of 104 rural consumers. This analysis elucidates new problems or challenges faced by rural consumers in impoverished areas after several years of experience in e-commerce. To further understand the service quality and cultural context effects, we conducted a quantitative study in 434 rural consumers in relatively underdeveloped areas of China. Using a partial least squares of structural equation modeling (SEM) approach through smart PLS, this study empirically tested the hypotheses posited in the paper. The SEM results demonstrate a positive relationship between logistics and training service quality, subjective norms, self-efficiency sense, and rural consumers’ attitudes toward e-commerce platforms, which in turn positively con-tributes to their willingness to engage in word-of-mouth e-commerce promotion. In addition, it is shown empirically that corporate social responsibility positively moderates the effects of logistics and training services, subjective norms, and attitudes toward the use of e-commerce platforms. The findings from these two studies contribute to a better understanding of, and have major implications for, successful e-commerce entrepreneurial practices in areas undergoing the process of transition to an important emerging e-commerce marketplace. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.","Attitude; Corporate social responsibility; Elaboration likelihood model; Logistics service; Self-efficiency sense; Subjective norms; Training service; Word-of-mouth","China; corporate social responsibility; electronic commerce; logistics; public attitude; rural area; service quality",{"$nulls":6},{"$cut":{"chars":18458,"head":"Roser M., Ortiz O.E., Global Extreme Poverty. Our World in Data, (2019); Ending Poverty; Newell P., Frynas J.G., Beyond CSR? Business, poverty and social justice: An introduction, Third World Q, 28, pp. 669-681, (2007); Moggi S., Bonomi S., Ricciardi F., Against food waste: CSR for the social and environmental impact through a network-based organizational model, Sustainability, 10, (2018); Kao T.Y., Chen J.C.H., Wu J.T.B., Yang M.H., Poverty reduction through empowerment for sustainable development: A pro-active strategy of corporate social responsibility, Corp. Soc. Responsib. Environ. Manag, 23, pp. 140-149, (2016); Obrenovic B., Du J., Godinic D., Tsoy D., Khan M.A.S., Jakhongirov I., Sustaining enterprise operations and productivity during the COVID-19 pandemic: Enterprise effectiveness and sustainability model, Sustainability, 12, (2020); Jha S.K., Pinsonneault A., Dube L., The evolution of an ICT platform-enabled ecosystem for poverty alleviation: The case of eKutir, MIS Q, 40, pp. 431-445, (2016); Li Y., Su B., Liu Y., Realizing targeted poverty alleviation in China: People’s voices, implementation challenges and policy implications, China Agric. Econ. Rev, 8, pp. 443-454, (2016); Li L., Du K., Zhang W., Mao J., Poverty alleviation through government-led e-commerce development in rural China: An activity theory perspective, Inf. Syst. J, 29, pp. 914-952, (2019); Leong C., Pan S.L., Newell. S.; Cui, L. The emergence of self-organizing e-commerce ecosystems in remote villages of China: A tale of digital empowerment for rural development, MIS Q, 40, pp. 475-484, (2016); Petty R.E., Cacioppo J.T., Communication and Persuasion: Central and Peripheral Routes to Attitude Change, (1986); Sussman S.W., Siegal W.S., Informational influence in organizations: An integrated approach to knowledge adoption, Inf. Syst. Res, 14, pp. 47-65, (2003); Tam K.Y., Ho S.Y., Web personalization as a persuasion strategy: An elaboration likelihood model perspective, Inf. Syst. Res, 16, pp. 271-291, (2005); Cheung C.M., Sia C., Kuan K.K., Is This review believable? A study of factors affecting the credibility of online consumer reviews from an ELM perspective, J. Assoc. Inf. Syst, 13, (2012); Petty R.E., Wegener D.T., The elaboration likelihood model: Current status and controversies, Dual-Process Theories in Social Psychology, pp. 37-72, (1999); Avcikurt C., Altay H., Ilban M.O., Critical success factors for small hotel businesses in turkey: An exploratory study, Cornell Hosp. Q, 52, pp. 153-164, (2011); Kim Y., Kim S., Myoung H., Lee H.R., Perceived service quality and its influence on behavioral intention in South Korean public dental hospitals, Asia Pac. J. Public Health, 24, pp. 391-405, (2012); Gracia E., Bakker A.B., Grau R.M., Positive emotions: The connection between customer quality and evaluations and loyalty, Cornell Hosp. Q, 52, pp. 458-465, (2011); Cao X., Liu Y., Zhu Z., Hu J., Chen X., Online selection of a physician by patients: Empirical study from elaboration likelihood perspective, Comput. Hum. Behav, 73, pp. 403-412, (2017); Wixom B.H., Todd P.A., A theoretical integration of user satisfaction and technology acceptance, Inf. Syst. Res, 16, pp. 85-102, (2005); Ayo C.K., Oni A.A., Adewoye O.J., Eweoya I.O., E-banking users’ behaviour: E-service quality, attitude, and customer satis-faction, Int. J. Bank Mark, 34, pp. 347-367, (2016); Guo X., Chen S., Zhang X., Ju X., Wang X., Exploring patients’ intentions for continuous usage of health services: Elaboration-likelihood perspective Study, JMIR Mhealth Uhealth, 84, (2020); Kulkarni P.P.A., Literature review on training and development and quality of work life, Res. World J. Arts Sci. Commer, 4, pp. 136-143, (2013); Zumrah A.R., How to enhance the impact of training on service quality? Evidence from malaysian public sector context, J. Workplace Learn, 27, pp. 514-529, (2015); Mathe K., Slevitch L., An exploratory examination of supervisor undermining, employee involvement climate, and the effects on customer perceptions of service quality in quick-service restaurants, J. Hosp."}},"W. Yang; College of Business, Gachon University, Seongnam, 13120, South Korea; email: wenjieyang000@gmail.com",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85120171887"]
["Mishra A.; Alzoubi Y.I.; Gill A.Q.; Anwar M.J.","Mishra, Alok (7201441575); Alzoubi, Yehia Ibrahim (36348354800); Gill, Asif Qumer (53979600700); Anwar, Memoona Javeria (57210843875)","7201441575; 36348354800; 53979600700; 57210843875","Cybersecurity Enterprises Policies: A Comparative Study",2022.0,"Sensors",22.0,2.0,538.0,null,null,null,18.0,"10.3390/s22020538","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85122706665&doi=10.3390%2fs22020538&partnerID=40&md5=b5db0e842108d27a3dfc9366ea4a801b","Informatics and Digitalization, Molde University College—Specialized University in Logistics, Molde, 6410, Norway; Department of Software Engineering, Atilim University, Ankara, 06830, Turkey; Management Information Systems Department, College of Business, American University of the Middle East, Egaila, 15453, Kuwait; School of Computer Science, The University of Technology Sydney, 15 Broadway, Ultimo, 2007, NSW, Australia","Mishra A., Informatics and Digitalization, Molde University College—Specialized University in Logistics, Molde, 6410, Norway, Department of Software Engineering, Atilim University, Ankara, 06830, Turkey; Alzoubi Y.I., Management Information Systems Department, College of Business, American University of the Middle East, Egaila, 15453, Kuwait; Gill A.Q., School of Computer Science, The University of Technology Sydney, 15 Broadway, Ultimo, 2007, NSW, Australia; Anwar M.J., School of Computer Science, The University of Technology Sydney, 15 Broadway, Ultimo, 2007, NSW, Australia","Cybersecurity is a critical issue that must be prioritized not just by enterprises of all kinds, but also by national security. To safeguard an organization’s cyberenvironments, information, and communication technologies, many enterprises are investing substantially in cybersecurity these days. One part of the cyberdefense mechanism is building an enterprises’ security policies library, for consistent implementation of security controls. Significant and common cybersecurity policies of various enterprises are compared and explored in this study to provide robust and comprehensive cybersecurity knowledge that can be used in various enterprises. Several significant common security policies were identified and discussed in this comprehensive study. This study identified 10 common cybersecurity policy aspects in five enterprises: healthcare, finance, education, aviation, and e-commerce. We aimed to build a strong infrastructure in each business, and investigate the security laws and policies that apply to all businesses in each sector. Furthermore, the findings of this study reveal that the importance of cybersecurity requirements differ across multiple organizations. The choice and applicability of cybersecurity policies are determined by the type of information under control and the security requirements of organizations in relation to these policies. © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).","Cybersecurity (CS); Cybersecurity polices; Cyberspace; Enterprise(s); Information and communication technology (ICT)","Commerce; Computer Security; Delivery of Health Care; Policy; National security; Security systems; Cyber security; Cybersecurity; Cybersecurity police; Cyberspaces; Enterprise IS; Enterprise(s); Information and Communication Technologies; Information and communication technology; Security policy; commercial phenomena; computer security; health care delivery; policy; Cybersecurity",{"$nulls":4},"Molde University College-Specialized Univ.","Funding: Authors thanks to the Molde University College-Specialized Univ. in Logistics, Norway for the support of Open access fund.",{"$cut":{"chars":25909,"head":"Tissir N., El Kafhali S., Aboutabit N., Cybersecurity management in cloud computing: Semantic literature review and conceptual framework proposal, J. Reliab. Intell. Environ, 7, pp. 69-84, (2021); Senol M., Karacuha E., Creating and Implementing an Effective and Deterrent National Cyber Security Strategy, J. Eng, 2020, (2020); Haddad C., Binder C., Governing through cybersecurity: National policy strategies, globalized (in-) security and sociotechnical visions of the digital society, Osterr. Z. Für Soziol, 44, pp. 115-134, (2019); Paananen H., Lapke M., Siponen M., State of the art in information security policy development, Comput. Secur, 88, (2020); Weiss M., Biermann F., Cyberspace and the protection of critical national infrastructure, J. Econ. Policy Reform, pp. 1-18, (2021); Hatcher W., Meares W.L., Heslen J., The cybersecurity of municipalities in the United States: An exploratory survey of policies and practices, J. Cyber Policy, 5, pp. 302-325, (2020); Alzoubi Y.I., Al-Ahmad A., Jaradat A., Fog computing security and privacy issues, open challenges, and blockchain solution: An overview, Int. J. Electr. Comput. Eng, 11, pp. 5081-5088, (2021); Alotaibi M., Furnell S., Clarke N., Information security policies: A review of challenges and influencing factors, Proceedings of the 11th International Conference for Internet Technology and Secured Transactions (ICITST), pp. 352-358, (2016); Knapp K.J., Morris R.F., Marshall T.E., Byrd T.A., Information security policy: An organizational-level process model, Comput. Secur, 28, pp. 493-508, (2009); Mthunzi S.N., Benkhelifa E., Bosakowski T., Guegan C.G., Barhamgi M., Cloud computing security taxonomy: From an atomistic to a holistic view, Future Gener. Comput. Syst, 107, pp. 620-644, (2020); Tchernykh A., Schwiegelsohn U., Talbi E.-G., Babenko M., Towards understanding uncertainty in cloud computing with risks of confidentiality, integrity, and availability, J. Comput. Sci, 36, (2019); Von Solms R., Van Niekerk J., From information security to cyber security, Comput. Secur, 38, pp. 97-102, (2013); Barr J.R., D'Auria D., Persia F., Telemedicine, Homecare in the Era of COVID-19 & Beyond, Proceedings of the Third International Conference on Artificial Intelligence for Industries (AI4I), pp. 48-51, (2020); Granja C., Janssen W., Johansen M.A., Factors determining the success and failure of eHealth interventions: Systematic review of the literature, J. Med. Internet Res, 20, (2018); Herzig T., Walsh T., Implementing Information Security in Healthcare: Building a Security Program, (2020); Alzoubi Y.I., Osmanaj V.H., Jaradat A., Al-Ahmad A., Fog computing security and privacy for the Internet of Thing applications: State-of-the-art, Secur. Priv, 4, (2021); Peltier T.R., Information Security Policies, Procedures, and Standards: Guidelines for Effective Information Security Management, (2016); AlJaafreh A., Al-Adaileh R., Gill A., Al-Ani A., Alzoubi Y., A review of literature of initial trust in e-services: The case of internet banking services in Jordanian context, J. Electron. Bank. Syst, 2014, (2014); Auta E.M., E-banking in developing economy: Empirical evidence from Nigeria, J. Appl. Quant. Methods, 5, pp. 212-222, (2010); Crane B.E., Online Teaching and Learning: A Practical Guide for Librarians, 29, (2016); Herrera A.V., Ron M., Rabadao C., National cyber-security policies oriented to BYOD (bring your own device): Systematic review, Proceedings of the 2017 12th Iberian Conference on Information Systems and Technologies (CISTI), pp. 644-648, (2017); Bandara I., Ioras F., Maher K., Cyber security concerns in e-learning education, Proceedings of the ICERI2014 Conference, pp. 728-734, (2014); Buja A.G., Cyber Security Featuresfor National E-Learning Policy, Turk. J. Comput. Math. Educ. (TURCOMAT), 12, pp. 1729-1735, (2021); Yang P., Xiong N., Ren J., Data security and privacy protection for cloud storage: A survey, IEEE Access, 8, pp. 131723-131740, (2020); Kania D.D., The Ethical Issues of Aviation Business in Indonesia, J. Manaj. Transp. Logist, 5, pp. 1-10, (2018); Wang H., He"}},"A. Mishra; Informatics and Digitalization, Molde University College—Specialized University in Logistics, Molde, 6410, Norway; email: alok.mishra@himolde.no",null,"MDPI",{"$nulls":5},1.424822E7,null,null,3.5062504E7,"English","Sensors","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85122706665"]
["Büttgen A.; Turan B.; Hemmelmayr V.","Büttgen, Anne (57381658600); Turan, Belma (57381658700); Hemmelmayr, Vera (23097964200)","57381658600; 57381658700; 23097964200","Evaluating distribution costs and co2-emissions of a two-stage distribution system with cargo bikes: A case study in the city of innsbruck",2021.0,"Sustainability (Switzerland)",13.0,24.0,13974.0,null,null,null,11.0,"10.3390/su132413974","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121512001&doi=10.3390%2fsu132413974&partnerID=40&md5=b7ba6a24dfae2b2ee3e312e1ce32dbb4","Department of Global Business and Trade, Vienna University of Economics and Business, Vienna, 1020, Austria","Büttgen A., Department of Global Business and Trade, Vienna University of Economics and Business, Vienna, 1020, Austria; Turan B., Department of Global Business and Trade, Vienna University of Economics and Business, Vienna, 1020, Austria; Hemmelmayr V., Department of Global Business and Trade, Vienna University of Economics and Business, Vienna, 1020, Austria","During the last years, e-commerce has grown rapidly. As a result, the number of parcel deliveries in urban areas is increasing, which affects the inner-city traffic and leads to congestion and air pollution, thereby decreasing the quality of life in cities. City administrators and logistic service providers have been working on the optimization of parcel distribution in order to alleviate congestion and reduce the negative impact on the environment. One of the solutions for environmentally friendly parcel distribution are two-stage distribution systems with city hubs. City hubs are facilities located close to the delivery area which are used as an enabling infrastructure to store and consolidate the parcels. For the last mile delivery from the city hub to final customers, zero emission vehicles, such as cargo bikes, can be used. Many studies have been conducted on this topic in recent years. This paper contributes to this research area by evaluating the implementation of such a two-stage distribution system with a city hub and cargo bikes in Innsbruck, Austria. The goal is to determine the best location for a city hub and the composition of the delivery fleet by minimizing the total distribution and CO2-emission cost. E-vans are used for the first and cargo bikes for the second stage of the parcel delivery. The problem is modeled as a vehicle routing problem with multiple trips and is solved in ArcGIS Pro, using the built-in routing solver. The analysis shows that all hub candidates provide comparably good results, with one potential station, the main station, showing the highest improvement compared to the basic system, with delivery by conventional vans. Savings in distribution costs of up to 30% can be achieved. Furthermore, by taking into account both indirect and direct emissions with a well-to-wheel approach, CO2-emissions can be reduced by 96%. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.","ArcGIS Pro; Cargo bike; City hub; City logistics; Environmental sustainability; Vehicle routing problem","Austria; Innsbruck; Tyrol; ArcGIS; carbon emission; cost analysis; distribution system; electronic commerce; emission control; quality of life; traffic congestion; traffic emission; urban pollution",{"$nulls":4},"Österreichische Forschungsförderungsgesellschaft, FFG, (877701)","Funding: This research was funded by FFG project INNS’PAKET grant number 877701.","Supply Chain Decarbonization: The Role of Logistics and Transport in Reducing Supply Chain Carbon Emissions, (2009); Oliveira C.M., Albergaria De Mello Bandeira R., Vasconcelos Goes G., Schmitz Goncalves D.N., D'Agosto M.D., Sustainable Vehicles-Based Alternatives in Last Mile Distribution of Urban Freight Transport: A Systematic Literature Review, Sustainability, 9, (2017); Sheth M., Butrina P., Goodchild A., McCormack E., Measuring delivery route cost trade-offs between electric-assist cargo bicycles and delivery trucks in dense urban areas, Eur. Transp. Res. Rev, 11, pp. 1-12, (2019); Anderluh A., Hemmelmayr V., Nolz P., Synchronizing vans and cargo bikes in a city distribution network, Cent. Eur. J. Oper. Res, 25, pp. 345-376, (2017); Leonardi J., Browne M., Allen J., Before-After Assessment of a Logistics Trial with Clean Urban Freight Vehicles: A Case Study in London, Procedia-Soc. Behav. Sci, 39, pp. 146-157, (2012); Statistische Stadtteile in Innsbruck, (2019); Zählsprengel in Innsbruck, (2019); Pfaffenbichler P., Umweltbelastung und Ressourcenverbrauch als Mögliche Auswirkung der Zunehmenden Nutzung des Onlinehandels durch die EinwohnerInnen der Stadt Wien (URANOS): Endbericht v1.0, (2018); Savelsbergh M., van Woensel T., City Logistics: Challenges and Opportunities: 50th Anniversary Invited Article, Transp. Sci, 50, pp. 579-590, (2016); Paddeu D., Sustainable Solutions for Urban Freight Transport and Logistics: An Analysis of Urban Consolidation Centers, Sustainable Freight Transport: Theory, Models, and Case Studies, pp. 121-137, (2018); Dolati Neghabadi P., Evrard Samuel K., Espinouse M.L., Systematic literature review on city logistics: overview, classification and analysis, Int. J. Prod. Res, 57, pp. 865-887, (2019); Enthoven D.L., Jargalsaikhan B., Roodbergen K.J., uit het Broek M.A.J., Schrotenboer A.H., The two-echelon vehicle routing problem with covering options: City logistics with cargo bikes and parcel lockers, Comput. Oper. Res, 118, (2020); Ehmke J.F., Routing in City Logistics, Integration of Information and Optimization Models for Routing in City Logistics, pp. 119-156, (2012); Arnold F., Cardenas I., Sorensen K., Dewulf W., Simulation of B2C e-commerce distribution in Antwerp using cargo bikes and delivery points, Eur. Transp. Res. Rev, 10, pp. 1-13, (2018); Quak H., Tavasszy L., Customized Solutions for Sustainable City Logistics: The Viability of Urban Freight Consolidation Centres, Transitions Towards Sustainable Mobility: New Solutions and Approaches for Sustainable Transport Systems, pp. 213-233, (2011); Crainic T.G., Ricciardi N., Storchi G., Models for Evaluating and Planning City Logistics Systems, Transp. Sci, 43, pp. 432-454, (2009); Nocera S., Cavallaro F., A two-step method to evaluate the Well-To-Wheel carbon efficiency of Urban Consolidation Centres, Res. Transp. Econ, 65, pp. 44-55, (2017); Melo S., Baptista P., Evaluating the impacts of using cargo cycles on urban logistics: integrating traffic, environmental and operational boundaries, Eur. Transp. Res. Rev, 9, (2017); Quak H., van Duin R., Hendriks B., Running an urban consolidation centre: Binnenstadservice 10 years back and forth, Transp. Res. Procedia, 46, pp. 45-52, (2020); Anderluh A., Hemmelmayr V., Wakolbinger T., Einsatz von Lastenfahrrädern zur innerstädtischen Güterlieferung: Ein Städtevergleich und Best Practice Empfehlungen für die Stadt Wien, (2016); Ranieri L., Digiesi S., Silvestri B., Roccotelli M., A Review of Last Mile Logistics Innovations in an Externalities Cost Reduction Vision, Sustainability, 10, (2018); Assmann T., Lang S., Muller F., Schenk M., Impact Assessment Model for the Implementation of Cargo Bike Transshipment Points in Urban Districts, Sustainability, 12, (2020); Gruber J., Narayanan S., Travel Time Differences between Cargo Cycles and Cars in Commercial Transport Operations, Transp. Res. Rec. J. Transp. Res. Board, 2673, pp. 623-637, (2019); Blazejewski L., Sherriff G., Davies N., Harnessing the potential of e-cargo bikes, Logist. Transp. 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Environ, 82, (2020); Weidemann T., Warum Paketboten Immer Seltener Klingeln und Was du Dagegen tun Kannst, (2018); Perboli G., Rosano M., Parcel delivery in urban areas: Opportunities and threats for the mix of traditional and green business models, TRansportation Res. Part C Emerg. Technol, 99, pp. 19-36, (2019); Eigenbauer A., Urbantschitsch W., Stromkennzeichnungsbericht 2020: Unsere Energie. Für klare Kennzeichnung; Koning M., Conway A., The good impacts of biking for goods: Lessons from Paris city, Case Stud. Transp. Policy, 4, pp. 259-268, (2016); Kosten einer Tonne CO2, (2021); Grundlage für CO2-Preis Steht, (2020); Thomasson E., Alkousaa R., FACTBOX-In Germany, Competition Heats Up between Two Logistics Giants, (2019); Wachotsch U., Kolodziej A., Specht B., Kohlmeyer R., Petrikowski F., E-Rad Macht Mobil: Potenziale von Pedelecs und deren Umweltwirkung, (2014)","B. Turan; Department of Global Business and Trade, Vienna University of Economics and Business, Vienna, 1020, Austria; email: belma.turan@wu.ac.at",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85121512001"]
["Wagner L.; Pinto C.; Amorim P.","Wagner, Laura (57208060787); Pinto, Catarina (57072726800); Amorim, Pedro (55429654100)","57208060787; 57072726800; 55429654100","On the Value of Subscription Models for Online Grocery Retail",2021.0,"European Journal of Operational Research",294.0,3.0,null,874.0,894.0,20.0,14.0,"10.1016/j.ejor.2020.05.011","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85086023785&doi=10.1016%2fj.ejor.2020.05.011&partnerID=40&md5=003dad29a0ac55588cf735b090edd736","Catolica Lisbon School of Business and Economics, Palma de Cima, Lisboa, 1649-023, Portugal; INESC TEC, Faculdade de Engenharia da Universidade do Porto, R. Dr. Roberto Frias, Porto, 4200-465, Portugal","Wagner L., Catolica Lisbon School of Business and Economics, Palma de Cima, Lisboa, 1649-023, Portugal; Pinto C., INESC TEC, Faculdade de Engenharia da Universidade do Porto, R. Dr. Roberto Frias, Porto, 4200-465, Portugal; Amorim P., INESC TEC, Faculdade de Engenharia da Universidade do Porto, R. Dr. Roberto Frias, Porto, 4200-465, Portugal","Omnichannel retailers are increasingly introducing subscription-based delivery services. By subscribing to this service and paying fees upfront, customers are entitled to have orders delivered to their home for a given period without paying any extra delivery charge. We analyze the resulting changes in customer behavior from two perspectives:(i) ordering behavior and (ii) delivery preferences. The model is estimated from the online transactional data of a grocery retailer and combines matching and difference-in-differences approaches. We confirm that subscription customers spend more per month and purchase more frequently online than customers without subscriptions. However, this outcome is compromised by shifts towards narrower time slots in the mornings and at night, where slots are requested with less advance notice. When weighing the increased revenue and higher operational costs, we show that subscriptions have a negative impact on a retailer's incremental profit. This remains valid for a wide range of assumptions about (i) the cannibalisation of sales from the retailer's offline business, (ii) picking cost and (iii) delivery cost. To mitigate the impact of subscriptions on retailer profits, we develop a data-driven algorithm that predicts whether certain customers should receive promotions for the subscription plan, rather than it being advertised to all customers. As an extension, we also study whether the addition of a minimum order threshold to subscription plans changes consumer behaviour. We find that this introduction encourages customers to seek more variety and increase their basket size, but does not reduce their order frequency, a phenomena which may be ascribed to cross-selling. © 2020 Elsevier B.V.","difference-in-differences; E-commerce; online retail; subscription models","Profitability; Customer behavior; Data-driven algorithm; Delivery costs; Delivery service; Difference-in-differences; Grocery retailer; Subscription models; Transactional data; Sales",{"$nulls":4},"Fundação para a Ciência e a Tecnologia, FCT, (PD/BD/128468/2017)","The authors would like to thank two anonymous referees for their helpful comments and insights. Catarina Pinto acknowledges FCT for her PhD grant (PD/BD/128468/2017).","Agatz N., Campbell A., Fleischmann M., Savelsbergh M., Time slot management in attended home delivery, Transportation Science, 45, 3, pp. 435-449, (2011); Agatz N., Campbell A.M., Fleischmann M., Savels M., Challenges and opportunities in attended home delivery, The vehicle routing problem: Latest advances and new challenges, pp. 379-396, (2008); (2019); Autor D.H., Outsourcing at will: The contribution of unjust dismissal doctrine to the growth of employment outsourcing, Journal of labor economics, 21, 1, pp. 1-42, (2003); Belavina E., Girotra K., Kabra A., Online Grocery Retail: Revenue Models and Environmental Impact Online Grocery Retail: Revenue Models and Environmental Impact, Management Science, (2016); Bell D., Gallino S., Moreno A.; Boyer K.K., Prud'homme A.M., Chung W., The last mile challenge: evaluating the effects of customer density and delivery window patterns, Journal of business logistics, 30, 1, pp. 185-201, (2009); Cachon G., Feldman P., Pricing Services Subject to Congestion: Charge Per-Use Fees or Sell Subscriptions?, Manufacturing & Service Operations Management, 13, 2, pp. 244-260, (2011); Cachon G., Gallino S., Xu J., Free shipping is not free: A data-driven model to design free-shipping threshold policies., Available at SSRN: https://ssrn.com/abstract=3250971, (2018); Cachon G., Swinney R., The value of fast fashion: Quick response, enhanced design, and strategic consumer behavior, Management Science, 57, 4, pp. 778-795, (2011); Calvo E., Cui R., Wagner L.; Campbell A.M., Savelsbergh M., Incentive schemes for attended home delivery services, Transportation Science, 40, 3, pp. 327-341, (2006); Chen C., Ngwe D., Shipping fees and product assortment in online retail, HBS Working Paper, (2018); Cochran W., The effectiveness of adjustment by subclassification in removing bias in observational studies, Biometrics, pp. 295-313, (1968); Gallino S., Moreno A., Stamatopoulos I., Channel integration, sales dispersion, and inventory management, Management Science, 63, 9, pp. 2813-2831, (2016); Gaur V., Fisher M.L., Raman A., An econometric analysis of inventory turnover performance in retail services, Management science, 51, 2, pp. 181-194, (2005); Gourville J., Soman D., Pricing and the psychology of consumption., Harvard Business Review, 80, 9, pp. 90-96, (2002); Guo L., Capturing consumption flexibility in assortment choice from scanner panel data, Management Science, 56, 10, pp. 1815-1832, (2010); Harris F., How many parts to make at once, Factory,The Magazine of Management, 10, pp. 135-136, (1913); Imai K., King G., Stuart E.A., Misunderstandings between experimentalists and observationalists about causal inference, Journal of the Royal Statistical Society: Series A (statistics in society), 171, 2, pp. 481-502, (2008); Kennedy P.E., Estimation with correctly interpreted dummy variables in semilogarithmic equations, American Economic Review, 71, (1981); Klein R., Neugebauer M., Ratkovitch D., Steinhardt C., Differentiated time slot pricing under routing considerations in attended home delivery, Transportation Science, 53, 1, pp. 236-255, (2017); Lantz B., Hjort K., Real e-customer behavioural responses to free delivery and free returns, Electronic Commerce Research, 13, 2, pp. 183-198, (2013); Lewis M., The effect of shipping fees on customer acquisition, customer retention, and purchase quantities, Journal of Retailing, 82, 1, pp. 13-23, (2006); Li J., Granados N., Netessine S., Are consumers strategic? structural estimation from the air-travel industry, Management Science, 60, 9, pp. 2114-2137, (2014); Li Y.P., Propert K.J., Rosenbaum P.R., Balanced risk set matching, Journal of the American Statistical Association, 96, 455, pp. 870-882, (2001); Mackert J., Choice-based dynamic time slot management in attended home delivery, Computers & Industrial Engineering, 129, pp. 333-345, (2019); Rosenbaum P.R., Design of observational studies, 10, (2010); Sainathan A., Customer differentiation with shipping as an ancillary service? free service, prioritization, and strategic delay, Decision Sciences, 49, 4, pp. 690-727, (2018); Simonson I., The effect of purchase quantity and timing on variety-seeking behavior, Journal of Marketing Research, 27, 2, pp. 150-162, (1990); Thaler R., Toward a positive theory of consumer choice, Journal of Economic Behavior & Organization, 1, 1, pp. 39-60, (1980); Yang X., Strauss A., Currie C., Eglese R., Choice-based demand management and vehicle routing in e-fulfillment, Transportation Science, 50, 2, pp. 473-488, (2014)","L. Wagner; Catolica Lisbon School of Business and Economics, Lisboa, Palma de Cima, 1649-023, Portugal; email: lwagner@ucp.pt",null,"Elsevier B.V.",{"$nulls":5},3772217.0,null,"EJORD",null,"English","Eur J Oper Res","Article","Final",null,"Scopus","2-s2.0-85086023785"]
["Cai L.; Yuen K.F.; Xie D.; Fang M.; Wang X.","Cai, Lanhui (57219317060); Yuen, Kum Fai (56581269200); Xie, Diancen (57300983800); Fang, Mingjie (57223433827); Wang, Xueqin (57196484178)","57219317060; 56581269200; 57300983800; 57223433827; 57196484178","Consumer's usage of logistics technologies: Integration of habit into the unified theory of acceptance and use of technology",2021.0,"Technology in Society",67.0,null,101789.0,null,null,null,30.0,"10.1016/j.techsoc.2021.101789","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85117373694&doi=10.1016%2fj.techsoc.2021.101789&partnerID=40&md5=ba1af60a2e934c67f6c61adda2dd7623","Department of International Logistics, Chung-Ang University, Seoul, South Korea; School of Civil and Environmental Engineering, Nanyang Technological University, Singapore; Department of Logistics, Service & Operations Management, Korea University Business School, Seoul, South Korea","Cai L., Department of International Logistics, Chung-Ang University, Seoul, South Korea; Yuen K.F., School of Civil and Environmental Engineering, Nanyang Technological University, Singapore; Xie D., Department of International Logistics, Chung-Ang University, Seoul, South Korea; Fang M., Department of Logistics, Service & Operations Management, Korea University Business School, Seoul, South Korea; Wang X., Department of International Logistics, Chung-Ang University, Seoul, South Korea","Different logistics technologies are emerging to improve the delivery efficiency and service standard of last-mile logistics. This study aims to understand consumer's usage behaviour of logistics technologies focussing on three representative logistics technologies: buy-online-and-pickup-in-store (BOPS), smart locker and drone delivery. A theoretical model is proposed by integrating the factors of habit and attitude into the unified theory of acceptance and use of technology (UTAUT). A total of 450 valid questionnaires are collected, and the data are analysed using structural equation modelling. The results suggest that (1) rational factors (i.e. performance expectancy, effort expectancy, facilitating conditions and attitude) and irrational factor (habit) collectively determine consumers' usage of logistics technologies; and (2) the key driving factors of consumers' usage behaviour of three logistics technologies do vary. The findings enrich the theoretical research on last-mile logistics and provide managerial implications for retail and logistics service providers. © 2021 Elsevier Ltd","Drone delivery; E-commerce delivery innovations; Habit; Last-mile logistics; Logistics technology; Smart locker; Structural equation modelling; UTAUT","Drones; Drone delivery; E-commerce delivery innovation; Habit; Last mile; Last-mile logistic; Logistics technologies; Smart locker; Structural equation models; Technology Integration; The unified theory of acceptance and use of technology(UTAUT); consumption behavior; innovation; logistics; numerical model; regression analysis; technology adoption; Surveys",{"$nulls":4},"UTAUT, (51,52, H5?H8); Ministry of Oceans and Fisheries, MOF","Funding text 1: This research was supported by the 4th Educational Training Program for the Shipping, Port and Logistics from the Ministry of Oceans and Fisheries .; Funding text 2: Table 2 summarises the theories applied in this paper. Firstly, UTAUT provides a general framework explaining consumers' behavioural intentions to use technology. The four antecedents (e.g. PE, EE, SI, FC) from UTAUT reflect technologies' inherent characteristics, external support conditions and social impact as perceived by technology users. Secondly, attitude theories conceptualise the formation of behavioural intentions into two stages characterised by the association of ?belief?attitude?intention?. To illustrate, the first stage involves consumers' cognition and beliefs that contribute to the attitude formation, and the second stage is that the attitude leads to the generation of behavioural intentions. Here, we propose that the four variables in UTAUT, as consumers' beliefs of technologies, affect their attitudes (H5?H8), and their attitudes promote behavioural intentions (H9).Moreover, FC refer to the personal perception of the extent to which the organisational and technical infrastructure support the usage of the system [28]. Theoretically, consumers having a certain degree of knowledge and resource compatible with the technology would be more willing to utilize it [51,52]. Consumers' needs, preferences, lifestyles and shopping preferences will affect consumers? attitude towards using BOPS, making it easier for consumers to use BOPS. Therefore, a detailed description of the in-store pickup process should be added. Unlike traditional delivery, consumers must consider whether such deliveries fit their lifestyles, which may influence their attitudes towards drone deliveries. If consumers perceive logistics technology as accessible and useable, they may be more receptive to the system and expect to exhibit positive attitudes. Therefore, the following hypothesis is proposed.This research was supported by the 4th Educational Training Program for the Shipping, Port and Logistics from the Ministry of Oceans and Fisheries.","Mangiaracina R., Perego A., Seghezzi A., Tumino A., Innovative solutions to increase last-mile delivery efficiency in B2C e-commerce: a literature review, Int. J. Phys. Distrib. Logist. Manag., 49, 9, pp. 901-920, (2019); Gasparin-isa I., Azevedo J.B., Slongo L.A., Buy-Online-and-Pick-up-In-Store: Review and Insights from Adopting a Cross-Channel Strategy, (2019); Wang X., Yuen K.F., Wong Y.D., Teo C.-C., Consumer participation in last-mile logistics service: an investigation on cognitions and affects, Int. J. Phys. Distrib. Logist. 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Syst., 27, 1, (2010); White C.S., The Impact of Structured Activities with a Computer-Based File-Management Program on Selected Information-Processing Skills (Social Studies, Database, Problem-Solving, Social Sciences, Software), (1985); Chen Y., Yu J., Yang S., Wei J., Consumer's intention to use self-service parcel delivery service in online retailing, Internet Res., 28, 2, pp. 500-519, (2018); Wang X., Wong Y.D., Liu F., Yuen K.F., A push–pull–mooring view on technology-dependent shopping under social distancing: When technology needs meet health concerns, Technol. Forecast. Soc. Change, 173, (2021)","X. Wang; Department of International Logistics, Chung-Ang University, Seoul, South Korea; email: xueqinwang@cau.ac.kr",null,"Elsevier Ltd",{"$nulls":5},"0160791X",null,null,null,"English","Technol. Soc.","Article","Final",null,"Scopus","2-s2.0-85117373694"]
["Alkhalifah A.; Alorini F.; Alturki R.","Alkhalifah, Ali (37080092000); Alorini, Fadwa (57383928500); Alturki, Reef (57383497900)","37080092000; 57383928500; 57383497900","Enhancement of E-commerce Service by Designing Last Mile Delivery Platform",2022.0,"Computer Systems Science and Engineering",42.0,1.0,null,49.0,67.0,18.0,4.0,"10.32604/CSSE.2022.021326","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121596634&doi=10.32604%2fCSSE.2022.021326&partnerID=40&md5=0cc48a9138a0311b45d508af96b33584","Department of Information Technology, College of Computer, Qassim University, Buraydah, 52211, Saudi Arabia","Alkhalifah A., Department of Information Technology, College of Computer, Qassim University, Buraydah, 52211, Saudi Arabia; Alorini F., Department of Information Technology, College of Computer, Qassim University, Buraydah, 52211, Saudi Arabia; Alturki R., Department of Information Technology, College of Computer, Qassim University, Buraydah, 52211, Saudi Arabia","The revolution of technology and the rapid evolution of the digital world had a significant effect on the development and expansion of e-commerce. Last mile delivery, for which different app-based delivery services have recently emerged, is a new area of research that is not thoroughly addressed. Delivery service is one of the supporting platforms of e-commerce. One of the delivery issues is that many customers experience difficulties in communicating and coordinating with the logistics companies responsible for the delivery service. This challenge is emphasized in this study which introduces a new system to facilitate communication and coordination between customers and logistics companies by using one identity and one interface. This paper is a programming-based study, as the proposed system evaluates a website to serve logistics companies as well as designs an application (app) to serve the customers of logistics companies. Swift, a powerful open-source and object-oriented programming language, and the mark-up language (HTML) were used to build the last mile delivery system. In addition, Firebase, a cloud-hosted real-time database built on Google infrastructure, were used to develop the system. By increasing the level of customer satisfaction and reducing delivery failure rates, this system will eventually increase the prosperity of e-commerce. © This work is licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.","E-commerce; Last mile delivery; Logistics companies","Customer satisfaction; Electronic commerce; Failure analysis; Object oriented programming; Open source software; Open systems; Customer experience; Delivery service; Digital world; E- commerces; E-commerce services; Last mile; Last mile delivery; Logistics company; Open-source; Supporting platform; Sales",{"$nulls":4},"Qassim University, QU","Acknowledgement: The authors thank Qassim University and the Deanship of Scientific Research for their support and funding the publication for this project.","Hwangbo H., Kim Y. S., Cha K. J., Recommendation system development for fashion retail e-commerce, Electronic Commerce Research and Applications, 28, 1, pp. 94-101, (2018); Turban E., King D., Lee J. K., Liang T., Turban D. C., Electronic Commerce, pp. 7-564, (2015); Bharucha J., Issues in the home delivery model in India, International Journal of Supply Chain Management (IJSCM), 6, 3, pp. 145-151, (2017); Autonomous last mile delivery market size 2021-2030, (2021); Joerss M., Schroder J., Neuhaus F., Klink C., Mann F., Parcel Delivery: The Future of Last Mile, pp. 142-149, (2016); Hepp S. B., Innovation in last mile delivery: Meeting evolving customer demands: The case of In-Car Delivery, (2018); Kiba-Janiak M., Marcinkowski J., Jagoda A., Skowronska A., Sustainable last mile delivery on e-commerce market in cities from the perspective of various stakeholders. Literature review, Sustainable Cities and Society, 71, (2021); Pourrahmani E., Jaller M., Crowdshipping in last mile deliveries: Operational challenges and research opportunities, Socio-Economic Planning Sciences, 10, (2021); Kapser S., Abdelrahman M., Acceptance of autonomous delivery vehicles for last-mile delivery in Germany-Extending UTAUT2 with risk perceptions, Transportation Research Part C: Emerging Technologies, 111, 2, pp. 210-225, (2020); Huang K., Ardiansyah M. N., A decision model for last-mile delivery planning with crowd-sourcing integration, Computers & Industrial Engineering, 135, 1, pp. 898-212, (2019); Bhat S. A., Kansana K., Majid J., A review paper on e-commerce, Proc. of the TIMS Int. Conf, (2016); Ohene-Djan J., Introducing electronic commerce, Electronic Commerce, pp. 8-15, (2008); Nanehkaran Y. A., An introduction to electronic commerce, International Journal of Scientific & Technology Research, 2, 4, pp. 190-193, (2013); Tiwari R., Buse S., The Concept of Mobile Commerce, The Mobile Commerce Prospects: A Strategic Analysis of Opportunities in the Banking Sector, pp. 26-36, (2007); Huang L., Exploring consumers' intention to urge to buy in mobile commerce: The perspective of pleasure-arousal-dominance, Proc. of the Pacific Asia Conf. on Information Systems (PACIS), (2017); Petrova K., Mobile commerce adoption: End-user/customer views, Proc. of the Global Business and Technology Association (GBATA) Int. Conf, pp. 604-615, (2004); Reddy K. S. L., Jayalaxmi S., A comparative study of traditional shopping vs. online shopping, ANNQUEST, 3, 1, pp. 37-51, (2014); Arora I. S., Customer perception towards online shopping, International Journal of Management, Technology and Engineering, 9, 5, pp. 5885-5897, (2019); Heutger M., Kuckelhaus M., Self-driving vehicles in logistics-A DHL perspective on implications and use cases for the logistics industry, DHL Trend Research, DHL Customers Solutions and Innovation, pp. 3-11, (2014); Corrocher N., Fontana R., Malerba F., Perrrone V., Poste Italiane: Innovation a Winning Strategy, (2012); Doan C. N., Location based services, (2015); Josang A., Pope S., User centric identity management, Proc. of the AusCERT Asia Pacific Information Technology Security Conf, (2005); Mangiaracina R., Perego A., Seghezzi A., Tumino A., Smart home devices and B2C e-commerce: A way to reduce failed deliveries, Proc. of the 24th Int. Sym. on Logistics, pp. 189-192, (2019); Nasreen A., Purohit S. K., Working conditions and social security issues of e-commerce delivery workers in India: Understanding from Marxian perspectives, International Journal of Social Science and Economic Research, 3, 3, pp. 1049-1067, (2018); Ghajargar M., Zenezini G., Montanaro T., Home delivery services: Innovations and emerging needs, IFACPapersOnLine, 49, 12, pp. 1371-1376, (2016); Bhattacharya S., Anand S., Are e-commerce companies leaking revenue?, SAMVAD, 18, pp. 102-109, (2019); Unni S., Nair V. S., Gunasekar S., E-retail and online customer satisfaction: Differential impact of delivery time in Indian metros, Proc. of the 2015 IEEE Int. Conf. on Computational Intelligence and Computing Research (ICCIC), pp. 1-4, (2015); Miquel-Romero M., Frasquet-Deltoro M., Molla-Descals A., Consumer motivations for click-and-collect and home delivery in online shopping, Advances in National Brand and Private Label Marketing, pp. 115-122, (2018); Swift - Apple, (2019); Swift, About swift-The swift programming language (swift 5.1), (2019); Robbins J. N., Where do I start?, Learning web design: A beginner's guide to HTML, CSS, JavaScript, and web graphics, pp. 12-13, (2012); Firebase, (2019); Jacob P. M., Ilyas H. M., Jose J., Jose J., An analytical approach on DFD to UML model transformation techniques, Proc. of the 2016 Int. Conf. on Information Science (ICIS), pp. 12-17, (2016); Valacich J. S., George J. F., System implementation, Modern Systems Analysis and Design, pp. 460-464, (2017); Sommerville I., Software processes, Software Engineering, pp. 48-59, (2016); Venkatesh V., Morris M. G., Davis G. B., Davis F. D., User acceptance of information technology: Toward a unified view, Management Information Systems (MIS) Quarterly, 27, 3, pp. 425-478, (2003); Davis F. D., Perceived usefulness, perceived ease of use, and user acceptance of information technology, Management Information Systems (MIS) Quarterly, 13, 3, pp. 319-340, (1989); Barnes S., Vidgen R., WebQual: An exploration of website quality, Proc. of European Conf. on Information Systems (ECIS), (2000)","A. Alkhalifah; Department of Information Technology, College of Computer, Qassim University, Buraydah, 52211, Saudi Arabia; email: a.alkhalifah@qu.edu.sa",null,"Tech Science Press",{"$nulls":5},2676192.0,null,"CSSEE",null,"English","Comput Syst Sci Eng","Article","Final","All Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85121596634"]
["Rimélé A.; Gamache M.; Gendreau M.; Grangier P.; Rousseau L.-M.","Rimélé, Adrien (57212454717); Gamache, Michel (6603926521); Gendreau, Michel (7005646783); Grangier, Philippe (57217601458); Rousseau, Louis-Martin (7005245914)","57212454717; 6603926521; 7005646783; 57217601458; 7005245914","Robotic mobile fulfillment systems: a mathematical modelling framework for e-commerce applications",2022.0,"International Journal of Production Research",60.0,11.0,null,3589.0,3605.0,16.0,12.0,"10.1080/00207543.2021.1926570","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85106240397&doi=10.1080%2f00207543.2021.1926570&partnerID=40&md5=72b45822734fcb95f22d67bf1732c4cc","Department of Mathematics and Industrial Engineering, Polytechnique Montreal, Montreal, QC, Canada; CIRRELT, Interuniversity Research Centre on Enterprise Networks, Logistics and Transportation, Montreal, QC, Canada; GERAD, Group for Research in Decision Analysis, Montreal, QC, Canada; IVADO Labs, Montreal, QC, Canada","Rimélé A., Department of Mathematics and Industrial Engineering, Polytechnique Montreal, Montreal, QC, Canada, CIRRELT, Interuniversity Research Centre on Enterprise Networks, Logistics and Transportation, Montreal, QC, Canada; Gamache M., Department of Mathematics and Industrial Engineering, Polytechnique Montreal, Montreal, QC, Canada, GERAD, Group for Research in Decision Analysis, Montreal, QC, Canada; Gendreau M., Department of Mathematics and Industrial Engineering, Polytechnique Montreal, Montreal, QC, Canada, CIRRELT, Interuniversity Research Centre on Enterprise Networks, Logistics and Transportation, Montreal, QC, Canada; Grangier P., IVADO Labs, Montreal, QC, Canada; Rousseau L.-M., Department of Mathematics and Industrial Engineering, Polytechnique Montreal, Montreal, QC, Canada, CIRRELT, Interuniversity Research Centre on Enterprise Networks, Logistics and Transportation, Montreal, QC, Canada","Robotic Mobile Fulfillment Systems (RMFSs) are a recent type of automated warehouse deployed in e-commerce. In this parts-to-picker system, a fleet of small robots is tasked with retrieving and storing shelves of items in the warehouse. Due to the nature of the e-commerce market, and the high flexibility of RMFSs, there are many opportunities to improve the productivity of the warehouse by optimising operational decisions. Online retailers promise extremely fast deliveries, which requires that new orders be included in the set of requests to fulfil as soon as they are revealed. For this reason, and because of the very dynamic nature of the robots' cycles, decision-making needs to be done in real time, in an uncertain environment. Because such a problem often lacks a formal description, we propose a mathematical framework that models the operational decisions taking place in an RMFS as a stochastic dynamic program. Our objective is to formalise optimisation opportunities, to allow researchers to develop more advanced methods in a well-defined environment. Embedded in a discrete event simulator, this model is illustrated by simulations to compare against standard storage decision rules. © 2021 Informa UK Limited, trading as Taylor & Francis Group.","e-commerce; mathematical modelling; robotic mobile fulfillment system; simulations; stochastic dynamic programming; warehouse","Decision making; Discrete event simulation; Robotics; Robots; Stochastic models; Stochastic systems; Warehouses; Automated warehouse; Discrete-event simulators; E-Commerce applications; Formal Description; Mathematical frameworks; Operational decisions; Stochastic dynamic program; Uncertain environments; Mobile commerce",{"$nulls":4},"Mitacs","We are grateful to the Mitacs Accelerate Program for providing funding for this project. We also wish to gratefully acknowledge the support and valuable insights of our industrial partners, JDA Software and Element AI.","Azadeh K., De Koster R., Roy D., Robotized Warehouse Systems: Developments and Research Opportunities, ERIM report series research in management Erasmus Research Institute of Management, ERS-2017-009-LIS, (2017); Banker S., Forbes Business, (2016); Banker S., Forbes Business, (2018); Boysen N., Briskorn D., Emde S., Parts-to-picker Based Order Processing in a Rack-moving Mobile Robots Environment, European Journal of Operational Research, 262, 2, pp. 550-562, (2017); Boysen N., De Koster R., Weidinger F., Warehousing in the E-commerce Era: A Survey, European Journal of Operational Research, 277, 2, pp. 396-411, (2019); Boysen N., Stephan K., Weidinger F., Manual Order Consolidation with Put Walls: the Batched Order Bin Sequencing Problem, EURO Journal on Transportation and Logistics, 8, 2, pp. 169-193, (2019); Bozer Y.A., Aldarondo F.J., A Simulation-based Comparison of Two Goods-to-person Order Picking Systems in An Online Retail Setting, International Journal of Production Research, 56, 11, pp. 3838-3858, (2018); D'Andrea R., Wurman P., 2008 IEEE International Conference on Technologies for Practical Robot Applications, TePRA, (2008); Davarzani H., Norrman A., Toward a Relevant Agenda for Warehousing Research: Literature Review and Practitioners' Input, Logistics Research, 8, 1, (2015); De Koster R., Le-Duc T., Roodbergen K.J., Design and Control of Warehouse Order Picking: A Literature Review, European Journal of Operational Research, 182, 2, pp. 481-501, (2007); Enright J.J., Wurman P.R., AAAI Workshop–Technical Report (WS-11-09), (2011); Gagliardi J.-P., Renaud J., Ruiz A., A Simulation Modeling Framework for Multiple-aisle Automated Storage and Retrieval Systems, Journal of Intelligent Manufacturing, 25, 1, pp. 193-207, (2014); Gagliardi J.-P., Renaud J., Ruiz A., On Sequencing Policies for Unit-load Automated Storage and Retrieval Systems, International Journal of Production Research, 52, 4, pp. 1090-1099, (2014); Gu J., Goetschalckx M., McGinnis L.F., Research on Warehouse Operation: A Comprehensive Review, European Journal of Operational Research, 177, 1, pp. 1-21, (2007); Guan M., Li Z., Genetic Algorithm for Scattered Storage Assignment in Kiva Mobile Fulfillment System, American Journal of Operations Research, 8, 6, pp. 474-485, (2018); Hausman W., Schwarz L., Graves S., Optimal Storage Assignment in Automatic Warehousing Systems, Management Science, 22, 6, pp. 629-638, (1976); Kirks T., Stenzel J., Kamagaew A., ten Hompel M., Cellular Transport Vehicles for Flexible and Changeable Facility Logistics Systems, Logistics Journal, 2192, 9084, (2012); Lamballais T., Roy D., De Koster R., Estimating Performance in a Robotic Mobile Fulfillment System, European Journal of Operational Research, 256, 3, pp. 976-990, (2017); Lamballais T., Roy D., De Koster R., Inventory Allocation in Robotic Mobile Fulfillment Systems, IISE Transactions, 52, 1, pp. 1-17, (2020); Merschformann M., Lamballais T., De Koster R., Suhl L., Decision Rules for Robotic Mobile Ful Fi Llment Systems, Operations Research Perspectives, 6, Mar., (2019); Merschformann M., Xie L., Li H., RAWSim-O: A Simulation Framework for Robotic Mobile Fulfillment Systems, Logistics Research, 11, 1, pp. 1-11, (2018); Powell W.B., A Unified Framework for Stochastic Optimization, European Journal of Operational Research, 275, 3, pp. 795-821, (2019); Ramanathan R., The Moderating Roles of Risk and Efficiency on the Relationship Between Logistics Performance and Customer Loyalty in E-commerce, Transportation Research Part E: Logistics and Transportation Review, 46, 6, pp. 950-962, (2010); Roodbergen K.J., Vis I.F.A., A Survey of Literature on Automated Storage and Retrieval Systems, European Journal of Operational Research, 194, 2, pp. 343-362, (2009); Shah B., Khanzode V., A Comprehensive Review of Warehouse Operational Issues, International Journal of Logistics Systems and Management, 26, 3, pp. 346-378, (2017); Tompkins J.A., Smith J.D., The Warehouse Management Handbook, (1998); van den Berg J.P., Gademann A.J.R.M., Simulation Study of An Automated Storage/retrieval System, International Journal of Production Research, 38, 6, pp. 1339-1356, (2000); Weidinger F., Boysen N., Briskorn D., Storage Assignment with Rack-moving Mobile Robots in KIVA Warehouses, Transportation Science, 52, 6, pp. 1479-1495, (2018); Wurman P.R., D'Andrea R., Mountz M., Coordinating Hundreds of Cooperative, Autonomous Vehicles in Warehouses, AI Magazine, 29, 1, (2008); Yuan R., Graves S., Cezik T., Velocity-Based Storage Assignment in Semi-Automated Storage Systems, Production and Operations Management, 28, 2, pp. 354-373, (2018); Zou B., Gong Y., Xu X., Yuan Z., Assignment Rules in Robotic Mobile Fulfilment Systems for Online Retailers, International Journal of Production Research, 55, 20, pp. 6175-6192, (2017)","A. Rimélé; Department of Mathematics and Industrial Engineering, Polytechnique Montreal, Montreal, Canada; email: adrien.rimele@polymtl.ca",null,"Taylor and Francis Ltd.",{"$nulls":5},207543.0,null,"IJPRB",null,"English","Int J Prod Res","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85106240397"]
["Maus B.; Olsson C.M.; Salvi D.","Maus, Benjamin (57219555493); Olsson, Carl Magnus (7103312820); Salvi, Dario (16176012000)","57219555493; 7103312820; 16176012000","Privacy Personas for IoT-Based Health Research: A Privacy Calculus Approach",2021.0,"Frontiers in Digital Health",3.0,null,675754.0,null,null,null,1.0,"10.3389/fdgth.2021.675754","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85131240250&doi=10.3389%2ffdgth.2021.675754&partnerID=40&md5=82cae890c9b8aa98a9e3119c1a878d38","Internet of Things and People Research Centre, University of Malmö, Malmö, Sweden","Maus B., Internet of Things and People Research Centre, University of Malmö, Malmö, Sweden; Olsson C.M., Internet of Things and People Research Centre, University of Malmö, Malmö, Sweden; Salvi D., Internet of Things and People Research Centre, University of Malmö, Malmö, Sweden","The reliance on data donation from citizens as a driver for research, known as citizen science, has accelerated during the Sars-Cov-2 pandemic. An important enabler of this is Internet of Things (IoT) devices, such as mobile phones and wearable devices, that allow continuous data collection and convenient sharing. However, potentially sensitive health data raises privacy and security concerns for citizens, which research institutions and industries must consider. In e-commerce or social network studies of citizen science, a privacy calculus related to user perceptions is commonly developed, capturing the information disclosure intent of the participants. In this study, we develop a privacy calculus model adapted for IoT-based health research using citizen science for user engagement and data collection. Based on an online survey with 85 participants, we make use of the privacy calculus to analyse the respondents' perceptions. The emerging privacy personas are clustered and compared with previous research, resulting in three distinct personas which can be used by designers and technologists who are responsible for developing suitable forms of data collection. These are the 1) Citizen Science Optimist, the 2) Selective Data Donor, and the 3) Health Data Controller. Together with our privacy calculus for citizen science based digital health research, the three privacy personas are the main contributions of this study. Copyright © 2021 Maus, Olsson and Salvi.","citizen science; IoT-based health research; privacy calculus; privacy personas; survey","Article; comorbidity; global health; health care delivery; human; pandemic; prediction; public health; systematic review; telehealth; trust",{"$nulls":6},"Liu H.Y., Dorler D., Heigl F., Grossberndt S., “Citizen science platforms, The Science of Citizen Science, (2021); Lane N.D., Miluzzo E., Lu H., Peebles D., Choudhury T., Campbell A.T., A survey of mobile phone sensing, IEEE Commun Mag, 48, pp. 140-150, (2010); Dang L.M., Piran M., Han D., Min K., Moon H., Et al., A survey on internet of things and cloud computing for healthcare, Electronics, 8, (2019); Ceccaroni L., Woods S.M., Sprinks J., Wilson S., Faustman E.M., Bonn A., Et al., Citizen science, health, and environmental justice, The Science of Citizen Science, (2021); Menni C., Valdes A.M., Freidin M.B., Sudre C.H., Nguyen L.H., Drew D.A., Et al., Real-time tracking of self-reported symptoms to predict potential COVID-19, Nat Med, 26, pp. 1037-1040, (2020); 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Beldad A.D., Hegner S.M., Expanding the technology acceptance model with the inclusion of trust, social influence, and health valuation to determine the predictors of German users' willingness to continue using a fitness app: a structural equation modeling approach, Int J Hum Comput Interact, 34, pp. 882-893, (2018); Prasad A., Sorber J., Stablein T., Anthony D., Kotz D., Understanding sharing preferences and behavior for mHealth devices, Proceedings of the 2012 ACM Workshop on Privacy in the Electronic Society, pp. 117-128, (2012); Albrecht U.V., Transparency of health-apps for trust and decision making, J Med Internet Res, 15, (2013); Wykes T., Schueller S., Why reviewing apps is not enough: transparency for trust (T4T) principles of responsible health app marketplaces, J Med Internet Res, 21, (2019); Kumaraguru P., Cranor L.F., Privacy Indexes: A Survey of Westin's Studies, (2005); Krane D., Light L., Gravitch D., Privacy on and off the internet: what consumers want, Harris Interact, (2002); 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Selective disclosure of data among citizen scientists, Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, pp. 1-11, (2019); Bietz M., Patrick K., Bloss C., Data donation as a model for citizen science health research, Citizen Sci Theory Pract, 4, (2019); Xu H., Gupta S., Rosson M.B., Carroll J.M., Measuring mobile users' concerns for information privacy, (2012); Wiggins A., Wilbanks J., The rise of citizen science in health and biomedical research, Am J Bioethics, 19, pp. 3-14, (2019); Maronick T.J., Do consumers read terms of service agreements when installing software?-a two-study empirical analysis, Int J Bus Soc Res, 4, pp. 137-145, (2014); Nebeker C., Gholami M., Kareem D., Kim E., Applying a digital health checklist and readability tools to improve informed consent for digital health research, Front Digit Health, 3, (2021); Lupton D., “Sharing Is Caring:” Australian self-trackers' concepts and practices of personal data sharing and privacy, Front Digit Health, 3, (2021); Meyer M.N., Practical tips for ethical data sharing, Adv Methods Pract Psychol Sci, 1, pp. 131-144, (2018); Connelly K., Khalil A., Liu Y., Do I do what I say?: Observed versus stated privacy preferences, IFIP Conference on Human-Computer Interaction, pp. 620-623, (2007)","B. Maus; Internet of Things and People Research Centre, University of Malmö, Malmö, Sweden; email: benjamin.maus@mau.se",null,"Frontiers Media SA",{"$nulls":5},"2673253X",null,null,null,"English","Front. Digit. Health","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85131240250"]
["Tang Y.M.; Chau K.Y.; Xu D.; Liu X.","Tang, Yuk Ming (55231482700); Chau, Ka Yin (57192810298); Xu, Duo (57225106244); Liu, Xiaoyun (57221969964)","55231482700; 57192810298; 57225106244; 57221969964","Consumer perceptions to support IoT based smart parcel locker logistics in China",2021.0,"Journal of Retailing and Consumer Services",62.0,null,102659.0,null,null,null,44.0,"10.1016/j.jretconser.2021.102659","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85109169244&doi=10.1016%2fj.jretconser.2021.102659&partnerID=40&md5=0e23da761620df73001a5afa24a26ed8","Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong; Hunan First Normal University, Changsha, Hunan, China; Faculty of Business, City University of Macau, Taipa, Macao","Tang Y.M., Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong, Faculty of Business, City University of Macau, Taipa, Macao; Chau K.Y., Faculty of Business, City University of Macau, Taipa, Macao; Xu D., Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong; Liu X., Hunan First Normal University, Changsha, Hunan, China, Faculty of Business, City University of Macau, Taipa, Macao","In recent years, the adoption of Internet of Things (IoT) based smart parcel lockers has developed very rapidly in Asia due to the wider applications from retailers, e-commerce companies, logistics companies, and consumers. The revolution of smart technologies has transformed the traditional way of last-mile delivery from logistics outlets to IoT-based parcel lockers due to the flexibility, convenience, and 24/7 accessibility. However, there are still many obstacles affecting the transformation of last-mile delivery especially in consumers perceptions towards the smart technologies. Therefore, in this study, we performed research based on the theory of service quality and customer satisfaction in the adoption of relevant technologies. This article divides the smart parcel lockers' service quality into five dimensions: service price, service reliability, convenience, fault handling capability, and service diversity. In this study, 272 valid questionnaires were collected from China to investigate consumer satisfaction with the smart parcel locker services. Statistical analysis, including the reliability and validity, was performed, followed by confirmatory factor analysis (CFA). The correlation between variables and the degree of influence on customer satisfaction and regression analysis was also undertaken in this study. The results revealed that the service price does not positively affect consumer satisfaction, and the other four underlying factors have a positive effect on consumer satisfaction. This research has significant impacts by determining the parcel lockers' core factors so as to foster the further development of last-mile services in the future. © 2021","Consumer behavior; Internet of things; Last-mile delivery; Service quality; Smart parcel locker","China; consumption behavior; electronic commerce; logistics; price dynamics; regression analysis; service quality; statistical analysis; technological development",{"$nulls":4},"Department of Industrial and Systems Engineering; University of Warwick; Hong Kong Polytechnic University, PolyU","The authors would like to acknowledge the support of the University of Warwick , United Kingdom, and the Department of Industrial and Systems Engineering from the Hong Kong Polytechnic University , the Hong Kong Special Administrative Region . This research study was conducted to support the Master of Science (MSc) programme under the Integrated Graduate Development Scheme (IGDS). We also thank Melissa Leffler, MBA, freelance language editor, for proofreading a draft of this manuscript.","Aldatmaz B., Sever C., Pehriz B., Caliskan A., Cetiner B., Parcel Delivery Service Quality Assessment, (2020); Arora P., Srivastava S., Majumder S., Using Automation Technology and IOT Based Data Capturing to Ensure High Quality Last Mile Logistics, (2017); Bai S., Wang H., Research on transporting logistics customer's satisfaction degree based on fuzzy entropy, Journal of Harbin University of Commerce(Social Science Edition), 1, pp. 7-10, (2008); Berry L.L., Seiders K., Grewal D., Understanding service convenience, J. Market., 66, 3, pp. 1-17, (2002); Bhatti A., Akram H., Basit H.M., Khan A.U., Raza S.M., Naqvi M.B., E-commerce trends during COVID-19 Pandemic, Int. J. Future Generat. Commun. 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Chau; Faculty of Business, City University of Macau, Taipa, Macao; email: gavinchau@cityu.mo",null,"Elsevier Ltd",{"$nulls":5},9696989.0,null,null,null,"English","J. Retail. Consum. Serv.","Article","Final",null,"Scopus","2-s2.0-85109169244"]
["Xia X.; Hou T.; Liu X.; Zong C.; Mu S.","Xia, Xiufeng (15047230100); Hou, Tingting (57568167900); Liu, Xiangyu (13605814400); Zong, Chuanyu (56012963400); Mu, Shengsheng (57567567700)","15047230100; 57568167900; 13605814400; 56012963400; 57567567700","Protecting Check-In Data Privacy in Blockchain Transactions with Preserving High Trajectory Pattern Utility",2022.0,"Wireless Communications and Mobile Computing",2022.0,null,9358531.0,null,null,null,0.0,"10.1155/2022/9358531","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85127845776&doi=10.1155%2f2022%2f9358531&partnerID=40&md5=d505a66a5d5e1e7135a0dce0ca2cb33f","School of Computer Science, Shenyang Aerospace University, Shenyang, 110136, China","Xia X., School of Computer Science, Shenyang Aerospace University, Shenyang, 110136, China; Hou T., School of Computer Science, Shenyang Aerospace University, Shenyang, 110136, China; Liu X., School of Computer Science, Shenyang Aerospace University, Shenyang, 110136, China; Zong C., School of Computer Science, Shenyang Aerospace University, Shenyang, 110136, China; Mu S., School of Computer Science, Shenyang Aerospace University, Shenyang, 110136, China","Because the blockchain is secure and untamperable, it has been widely used in many industries, such as the financial industry, digital tokens, and e-commerce logistics. The remarkable security feature of the blockchain is that the blockchain verifies the transaction initiated on each block through the node, and its process is broadcast throughout the whole network to let everyone know. On the one hand, this ensures the security of every transaction, but on the other hand, it is easy to cause privacy disclosure problems for transaction users. Therefore, under the premise of ensuring the security of the blockchain, it has become a hot issue to protect the sensitive information of transaction users. A check-in privacy protection (CPP) algorithm based on check-in location generalization is proposed in this paper, which can be applied to blockchain transactions to solve the privacy leakage problem of transaction users' sensitive information. CPP algorithm not only protects the privacy of check-in data but also keeps the high utility of trajectory pattern data. Firstly, location types are recommended in the sensitive check-in location generalization based on the user's trajectory pattern by using Markov chain technology. Secondly, to make sure that the generalized locations can be scattered as much as possible to prevent the attacker from deducing back, a heuristic rule is designed to select the generalized location based on the recommended location types, and at the same time, the similarity between the anonymous trajectory and the original trajectory is maintained. In addition, a generalized location search strategy is designed to improve the efficiency of the algorithm. Based on the real spatial-temporal check-in data, the results of the experiment indicate that our algorithm can effectively protect the privacy of sensitive check-in while ensuring the high utility of trajectory pattern data. © 2022 Xiufeng Xia et al.",null,"Location; Markov processes; Privacy-preserving techniques; Trajectories; Block-chain; Check-in; Digital tokens; Financial industry; Generalisation; Pattern datum; Privacy protection; Protection algorithms; Sensitive informations; Trajectory pattern; Blockchain",{"$nulls":6},"Liu L., Feng J., Pei Q., Chen C., Ming Y., Shang B., Dong M., Blockchain-enabled secure data sharing scheme in mobile-edge computing: An asynchronous advantage actor-critic learning approach, IEEE Internet of Things Journal, 8, 4, pp. 2342-2353, (2021); Tan L., Keping Y., Shi N., Yang C., Wei W., Huimin L., Towards secure and privacy-preserving data sharing for COVID-19 medical records: A blockchain-empowered approach, IEEE Transactions on Network Science and Engineering, 9, 1, pp. 271-281, (2022); 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Zhao L., Li H., Lin N., Lin M., Fan C., Shi J., Intelligent content caching strategy in autonomous driving toward 6G, IEEE Transactions on Intelligent Transportation Systems, pp. 1-11, (2021); Liu L., Zhao M., Yu M., Jan M.A., Lan D., Taherkordi A., Mobility-aware multi-hop task offloading for autonomous driving in vehicular edge computing and networks, IEEE Transactions on Intelligent Transportation Systems, pp. 1-14, (2022); Wang M., Lin Y., Tian Q., Si G., Transfer learning promotes 6G wireless communications: Recent advances and future challenges, IEEE Transactions on Reliability, 70, 2, pp. 790-807, (2021); Wang L., Meng X.F., Location privacy preservation in big data era: A survey, Journal of Software, 25, 4, pp. 693-712, (2014); Sweeney L., K-anonymity: A model for protecting privacy, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 10, 5, pp. 557-570, (2002); Dwork C., Differential privacy, Proc of the 33rd International Colloquium on Automata, Languages and Programming, pp. 1-12, (2006); Feng Z., Research on Location Privacy-Preserving Nearest Neighbor Query Based PIR, (2017); Feng Z., Wei-Wei N., Pseudo-random number encryption based on location privacy preserving nearest neighbor querying, Journal of East China Normal University, 2015, 5, pp. 128-142, (2015); Deldar F., Abadi M., PDP-SAG: Personalized privacy protection in moving objects databases by combining differential privacy and sensitive attribute generalization, IEEE Access, 7, pp. 85887-85902, (2019); Kido H., Yanagisawa Y., Satoh T., An Anonymous Communication Technique Using Dummies for Location-based Services, pp. 88-97; Gruteser M., Grunwald D., Anonymous Usage of Location-based Services Through Spatial and Temporal Cloaking, pp. 31-42; Gruteser M., Liu X., Protecting privacy in continuous location trajectorying applications, IEEE Security and Privacy, 2, 2, pp. 28-34, (2004); Gedik B., Ling L., Protecting location privacy with personalized k-anonymity: Architecture and algorithms, IEEE Transactions on Mobile Computing, 7, 1, pp. 1-18, (2008); Jie W., Chunru W., Jianfeng M.A., Dummy location selection algorithm based on location semantics and query probability, Journal on Communications, 41, 3, pp. 53-61, (2020); Niu B., Li Q., Zhu X., Achieving K-anonymity in Privacy-aware Location-based Services; Lu H., Jensen C.S., Yiu M.L., PAD: Privacy-area Aware, Dummy-based Location Privacy in Mobile Services, pp. 16-23; Xiong P., Zhang L., Zhu T., Reward-based spatial crowdsourcing with differential privacy preservation, Enterprise Information Systems, 11, 10, pp. 1500-1517, (2017); Qiyuan X., Zhenping C., Baochuan F., Hybrid location privacy protection based on differential privacy, Computer Applications and Software, 36, 6, pp. 296-301, (2019); Ping X., Zhu T., Lei P., Privacy Preserving in Location Data Release: A Differential Privacy Approach, Pacific Rim International Conference on Artificial Intelligence, pp. 183-195, (2014); Papadopoulos S., Bakiras S., Papadias D., Nearest neighbor search with strong location privacy, Proceedings of the VLDB Endowment, 3, 1-2, pp. 619-629, (2010)","T. Hou; School of Computer Science, Shenyang Aerospace University, Shenyang, 110136, China; email: 192106074080@email.sau.edu.cn",null,"Hindawi Limited",{"$nulls":5},1.5308669E7,null,null,null,"English","Wireless Commun. Mobile Comput.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85127845776"]
["Qin Z.","Qin, Zhidan (57426320900)",5.74263209E10,"The Inventory Control System of Reverse Logistics for E-Commerce Packaging Recovery Based on BP Neural Network",2022.0,"International Journal of Circuits, Systems and Signal Processing",16.0,null,51.0,413.0,425.0,12.0,0.0,"10.46300/9106.2022.16.51","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85123454454&doi=10.46300%2f9106.2022.16.51&partnerID=40&md5=fa95871ab48d0abf55bbbc820a08c1d1","Research Center for Infant Products and Services Supply Chain, Chongqing University of Education, Chongqing, 400067, China","Qin Z., Research Center for Infant Products and Services Supply Chain, Chongqing University of Education, Chongqing, 400067, China","The paper combines BP neural network to optimize the control system of e-commerce packaging and reverse logistics inventory. Through improving the hardware configuration structure of the system, the system can be improved and the operation effect of the system can be improved. The software flow and operation algorithm of the storage control system of e-commerce packaging recycling reverse logistics are optimized step by step, and the logistics is delivered by following the vehicle on the spot and visiting the logistics The distribution personnel collect the relevant data and data in the process of logistics and transportation, draw the reverse logistics business flow chart, point out the situation of reverse logistics before and after the goods distribution and distribution due to the cancellation of orders or transactions by customers, and the application for return of goods after the transaction. Meanwhile, it points out that the sales return operation site in the reverse logistics management process is chaotic and not formed the clear business process specification and other problems can effectively control the reverse logistics inventory of e-commerce packaging recovery. Finally, the experiment proves that the e-commerce packaging recycling reverse logistics inventory control system is more practical in the practical application process, and fully meets the research requirements. © 2022, North Atlantic University Union NAUN. All rights reserved.","BP neural network; E-commerce packaging; Reverse logistics","Control systems; Digital storage; Electronic commerce; Inventory control; Logistics; Packaging; Recycling; BP neural networks; E- commerces; E-commerce packaging; Flow algorithm; Hardware configurations; Inventory-control systems; On the spots; Operation algorithm; Reverse logistics; Storage control; Neural networks",{"$nulls":6},"Liu W., Route optimization for last-mile distribution of rural e-commerce logistics based on ant colony optimization, IEEE Access, 8, pp. 12179-12187, (2020); Dutta P, Mishra A, Khandelwal S, Et al., A multiobjective optimization model for sustainable reverse logistics in Indian E-commerce market, Journal of Cleaner Production, 249, (2020); Wang C N, Dang T T, Nguyen N A T., Outsourcing reverse logistics for e-commerce retailers: A two-stage fuzzy optimization approach, Axioms, 10, 1, (2021); Zennyo Y., Strategic contracting and hybrid use of agency and wholesale contracts in e-commerce platforms, European Journal of Operational Research, 281, 1, pp. 231-239, (2020); Wang Y, Fan R, Shen L, Et al., Recycling decisions of low-carbon e-commerce closed-loop supply chain under government subsidy mechanism and altruistic preference, Journal of Cleaner Production, 259, 10, (2020); Abumalloh R A, Ibrahim O, Nilashi M., Loyalty of young female Arabic customers towards recommendation agents: A new model for B2C E-commerce, Technology in Society, 61, 11, (2020); Collier Z A, Lambert J H., Evaluating management actions to mitigate disruptive scenario impacts in an e-commerce systems integration project, IEEE Systems Journal, 13, 1, pp. 593-602, (2019); Alsaad A, Taamneh A., The effect of international pressures on the cross-national diffusion of business-to-business e-commerce, Technology in Society, 59, 7, (2019); Kargar S, Pourmehdi M, Paydar M M., Reverse logistics network design for medical waste management in the epidemic outbreak of the novel coronavirus (COVID-19), Science of the Total Environment, 746, 8, (2020); Zarbakhshnia N, Wu Y, Govindan K, Et al., A novel hybrid multiple attribute decision-making approach for outsourcing sustainable reverse logistics, Journal of Cleaner Production, 242, (2020); Ma Y, Li Z, Fang Y, Et al., A hybrid priority-based genetic algorithm for simultaneous pickup and delivery problems in reverse logistics with time windows and multiple decision-makers, Soft Computing, 23, 15, pp. 6697-6714, (2019); Wang J, Li H, Lu H, Et al., Integrating offline logistics and online system to recycle e-bicycle battery in China, Journal of Cleaner Production, 247, 10, pp. 119095-119099, (2020); Wang Y, Shi Q., Spare parts closed-loop logistics network optimization problems: Model formulation and meta-heuristics solution, IEEE Access, 7, 10, pp. 45048-45060, (2019); Afra A P, Behnamian J., Lagrangian heuristic algorithm for green multi-product production routing problem with reverse logistics and remanufacturing, Journal of Manufacturing Systems, 58, pp. 33-43, (2020); Dutta P, Talaulika R S, Xavier V, Et al., Fostering reverse logistics in India by prominent barrier identification and strategy implementation to promote circular economy, Journal of Cleaner Production, 294, 5, (2021); Safdar N, Khalid R, Ahmed W, Et al., Reverse logistics network design of e-waste management under the triple bottom line approach, Journal of Cleaner Production, 272, 9, (2020); Oyola-Cervantes J, Amaya-Mier R., Reverse logistics network design for large off-the-road scrap tires from mining sites with a single shredding resource scheduling application, Waste Management, 100, pp. 219-229, (2019); Oliveira C D, Luna M, Campos L., Understanding the Brazilian expanded polystyrene supply chain and its reverse logistics towards circular economy, Journal of Cleaner Production, 235, pp. 562-573, (2019); Chen D, Ignatius J, Sun D, Et al., Reverse logistics pricing strategy for a green supply chain: A view of customers’ environmental awareness, International Journal of Production Economics, 217, pp. 197-210, (2019); Trochu J, Chaabane A, Ouhimmou M., A two-stage stochastic optimization model for reverse logistics network design under dynamic suppliers’ locations, Waste Management, 95, 9, pp. 569-583, (2019); Pramono Christopher Allen, Manurung Adler Haymans, Heriyati Pantri, Kosasih Wibowo, Analysis of The Influence of Entrepreneurship Capability, Agility, Business Transformation, Opportunity on Start-Up Behavior In E-Commerce Companies In Indonesia During The Covid 19 Pandemic, WSEAS Transactions on Business and Economics, 18, pp. 1103-1112, (2021); Alomari Saleh Ali, Salaimeh Safwan Al, Jarrah Emran Al, Alzboon Mowafaq Salem, Enhanced logistics information service systems performance: Using theoretical model and cybernetics? Principles, WSEAS Transactions on Business and Economics, 17, pp. 278-287, (2020); Zhang M, Pratap S, Zhao Z, Et al., Forward and reverse logistics vehicle routing problems with time horizons in B2C e-commerce logistics, International Journal of Production Research, 59, 20, pp. 6291-6310, (2021); Chen T., Simulation of E-Commerce Logistics Terminal Distribution Route Planning During the Express Delivery Period, Computer Simulation, 38, 3, pp. 355-359, (2021); Yang X, Han M, Tang H, Et al., Detecting Defects with Support Vector Machine in Logistics Packaging Boxes for Edge Computing, IEEE Access, 8, pp. 64002-64010, (2020)","Z. Qin; Research Center for Infant Products and Services Supply Chain, Chongqing University of Education, Chongqing, 400067, China; email: qinzd@cque.edu.cn",null,"North Atlantic University Union NAUN",{"$nulls":5},1.9984464E7,null,null,null,"English","Int. J. Circuit Syst. Signal Process.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85123454454"]
["Cortes J.D.; Suzuki Y.","Cortes, Juan David (56417109900); Suzuki, Yoshinori (7407203699)","56417109900; 7407203699","Last-mile delivery efficiency: en route transloading in the parcel delivery industry",2022.0,"International Journal of Production Research",60.0,9.0,null,2983.0,3000.0,17.0,8.0,"10.1080/00207543.2021.1907628","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85103623563&doi=10.1080%2f00207543.2021.1907628&partnerID=40&md5=94ad00835a56a960ae64c53b9c28c29e","Department of Finance, School of Business, Providence College, Providence, RI, United States; Department of Supply Chain Management, Debbie and Jerry Ivy College of Business, Iowa State University, Ames, IA, United States","Cortes J.D., Department of Finance, School of Business, Providence College, Providence, RI, United States; Suzuki Y., Department of Supply Chain Management, Debbie and Jerry Ivy College of Business, Iowa State University, Ames, IA, United States","In the last few years, many consumers have shifted their shopping locations from traditional brick-and-mortar stores to online shopping sites to take advantage of larger product selections and convenient delivery services. This has forced parcel delivery service providers, such as UPS and FedEx, to handle large amounts of shipments with complex delivery needs in a time-efficient manner. Given this challenge, parcel delivery companies are looking for faster, more cost-efficient ways to distribute parcels. Based on expert opinions, obtained through a series of interviews with practitioners, this study presents a decision tool to improve the operational efficiency of last-mile delivery for parcel delivery companies. This decision tool extends previous works on Vehicle Routing Problem with Split Deliveries by allowing shipment transloading to take place between vehicles at select points (other than the depot) in the logistics network, within pre-specified time windows. © 2021 Informa UK Limited, trading as Taylor & Francis Group.","metaheuristics; optimisation; Package delivery; urban logistics; vehicle routing","Efficiency; Ships; Decision tool; Delivery company; Delivery service; En-route; Last mile; Metaheuristic; Optimisations; Package delivery; Parcel delivery; Urban logistics; Vehicle routing",{"$nulls":6},"Ala-Risku T., Karkkainen M., Holmstrom J., Evaluating the Applicability of Merge-in-Transit, The International Journal of Logistics Management, 14, 2, pp. 67-82, (2003); Archetti C., Campbell A.M., Speranza M.G., Multicommodity vs. Single-Commodity Routing, Transportation Science, pp. 1-12, (2014); Archetti C., Savelsbergh M.W.P., Speranza M.G., To Split or Not to Split: That is the Question, Transportation Research Part E: Logistics and Transportation Review, 44, 1, pp. 114-123, (2008); 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Castrellon-Torres J.P., Talero Chaparro J.S., Manosalva Barrera N.E., Torres Acosta J.H., Adarme Jaimes W., Information Technology in City Logistics: A Decision Support System for Off-Hour Delivery Programs, (2018); Cortes J.D., (2017); Crainic T.G., Perboli G., Mancini S., Tadei R., Two-Echelon Vehicle Routing Problem: A Satellite Location Analysis, Procedia-Social and Behavioral Sciences, 2, 3, pp. 5944-5955, (2010); Croxton K.L., Gendron B., Magnanti T.L., Models and Methods for Merge-in-Transit Operations, Transportation Science, 37, 1, (2003); Cruz-Mejia O., Vilalta-perdomo E.L., Monsreal M., (2016); Dantzig G., Ramser J., The Truck Dispatching Problem, Management Science, 6, 1, pp. 80-91, (1959); Drexl M., Synchronization in Vehicle Routing–A Survey of VRPs with Multiple Synchronization Constraints, Transportation Science, 46, 3, pp. 297-316, (2012); Dror M., Trudeau P., Savings by Split Delivery Routing, Transportation Science, 23, 2, pp. 141-145, (1989); Dror M., Trudeau P., Split Delivery Routing, Naval Research Logistics, 37, 3, pp. 383-402, (1990); 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Novack R.A., Gibson B.J., Suzuki Y., Coyle J.J., Transportation: A Global Supply Chain Perspective, (2019); Ovide S., The New York Times, (2020); Perboli G., Tadei R., Vigo D., The Two-Echelon Capacitated Vehicle Routing Problem: Models and Math-Based Heuristics, Transportation Science, 45, 3, pp. 364-380, (2011); Peres I.T., Repolho H.M., Martinelli R., Monteiro N.J., Optimization in Inventory-Routing Problem with Planned Transshipment: A Case Study in the Retail Industry, International Journal of Production Economics, 193, pp. 748-756, (2017); Praet S., Martens D., Efficient Parcel Delivery by Predicting Customers’ Locations, Decision Sciences, 51, 5, pp. 1202-1231, (2020); Rais A., Alvelos F., Carvalho M.S., New Mixed Integer-Programming Model for the Pickup-and-Delivery Problem with Transshipment, European Journal of Operational Research, 235, 3, pp. 530-539, (2014); Rhodes K., Nehring R., Wilk B., Patel N., 2007 IEEE Systems and Information Engineering Design Symposium, (2007); Robinson S., Simulation: The Practice of Model Development and Use, (2014); Sankaran J.K., Ubgade R.R., Routing Tankers for Dairy Milk Pickup, Interfaces, 24, 5, pp. 59-66, (1994); Singh S., Kumar R., Panchal R., Tiwari M.K., Impact of COVID-19 on Logistics Systems and Disruptions in Food Supply Chain, International Journal of Production Research, pp. 1-16, (2020); Solomon M.M., Algorithms for the Vehicle Routing and Scheduling Problems with Time Window Constraints, Operation Research, 35, 2, pp. 254-265, (1987); Solomon M.M., Desrosiers J., Survey Paper–Time Window Constrained Routing and Scheduling Problems, Transportation Science, 22, 1, pp. 1-13, (1988); Toth P., Vigo D., Models, Relaxations and Exact Approaches for the Capacitated Vehicle Routing Problem, Discrete Applied Mathematics, 123, 1-3, pp. 487-512, (2002); Toth P., Vigo D., The Vehicle Routing Problem, (2002); Toth P., Vigo D., Vehicle Routing: Problems, Methods, and Applications, 18, (2014); Wade A.C., Salhi S., An Investigation Into a New Class of Vehicle Routing Problem with Backhauls, Omega, 30, 6, pp. 479-487, (2002); Xiao Y., Chen J., Supply Chain Management of Fresh Products with Producer Transportation, Decision Sciences, 43, 5, pp. 785-815, (2012); Zhou L., Baldacci R., Vigo D., Wang X., A Multi-Depot Two-Echelon Vehicle Routing Problem with Delivery Options Arising in the Last Mile Distribution, European Journal of Operational Research, 265, 2, pp. 765-778, (2018)","J.D. Cortes; Department of Finance, School of Business, Providence College, Providence, 1 Cunningham Square, United States; email: david.cortes@providence.edu",null,"Taylor and Francis Ltd.",{"$nulls":5},207543.0,null,"IJPRB",null,"English","Int J Prod Res","Article","Final",null,"Scopus","2-s2.0-85103623563"]
["Wang L.; Song H.","Wang, Lina (57421459300); Song, Hui (57421251700)","57421459300; 57421251700","E-Commerce Credit Risk Assessment Based on Fuzzy Neural Network",2022.0,"Computational Intelligence and Neuroscience",2022.0,null,3088915.0,null,null,null,4.0,"10.1155/2022/3088915","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85123235127&doi=10.1155%2f2022%2f3088915&partnerID=40&md5=3b4ff21c998c3935aa7e2a546ab2b136","School of Finacial Technology, Hebei Finance University, Baoding, Hebei, 071051, China; School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Haidian, Beijing, 100876, China","Wang L., School of Finacial Technology, Hebei Finance University, Baoding, Hebei, 071051, China; Song H., School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Haidian, Beijing, 100876, China","In this paper, we propose a cooperative strategy-based self-organization mechanism to reconstruct the network. The mechanism includes a comprehensive evaluation algorithm and structure adjustment mechanism. The self-organization mechanism can be carried out simultaneously with the parameter optimization process. By calculating the similarity and independent contribution of normative neurons, the effectiveness of fuzzy rules can be jointly evaluated, and effective structural changes can be realized. Moreover, this mechanism should not set the threshold in advance in practical application. In order to optimize the parameters of SC-IR2FNN, we developed a parameter optimization mechanism based on an interaction strategy. The parameter optimization mechanism based on a joint strategy, namely multilayer optimization engine, can split SC-IR2FNN parameters into nonlinear and linear parameters for joint optimization. The nonlinear parameters are optimized by an advanced two-level algorithm, and the linear parameters are updated with the minimum biological multiplication. Two parameter optimization algorithms optimize nonlinear and linear parameters, reduce the computational complexity of SC-IR2FNN, and improve the learning rate. Using the principal component factor analysis method, seven representative common factors are selected to replace the original variables, which include the profitability factor of the financing enterprise, the solvency factor of the financing enterprise, the profitability factor of the core enterprise, the operation guarantee factor, and the growth ability of the financing enterprise. Factors, supply chain online degree factors, financing enterprise quality, and cooperation factors, can well measure the credit risk of online supply chains. The logistic model shows that the profitability factor of the financing company, the debt repayment factor of the financing company, and the profitability of the core company are three factors that have a significant impact on the credit risk of online supply chain finance. Based on the improved credit calculation model, we developed an online clue risk calculation. This method is based on site conditions and can evaluate credit risk. From the test results, the improved credit scoring system is the result of facing speculative and circular credit fraud and implies that the traders of risk commentators are in a leading position in each electronic device. The results show that risk analysis is effective in any case.  © 2022 Lina Wang and Hui Song.",null,"Algorithms; Commerce; Neural Networks, Computer; Risk Assessment; Factor analysis; Fuzzy inference; Fuzzy neural networks; Genetic algorithms; Parameter estimation; Principal component analysis; Profitability; Risk analysis; Risk assessment; Supply chains; Credit risk assessment; Credit risks; E-commerce credit risks; Fuzzy-neural-networks; Linear parameters; Mechanism-based; Non-linear parameters; Online supplies; Parameter optimization; Self-organization mechanisms; algorithm; commercial phenomena; risk assessment; Finance",{"$nulls":6},"Wei C., Yu Z.J., Chen X.N., Research on social e-commerce reputation formation and state-introduced model, Kybernetes, 46, 6, pp. 1021-1038, (2017); Wu P.J., Lin K.C., Unstructured big data analytics for retrieving e-commerce logistics knowledge, Telematics and Informatics, 35, 1, pp. 237-244, (2018); Zhang Y., Building China EU cross border e-commerce ecosystem with blockchain technology, China's Circulation Economy, 2, 2, pp. 66-72, (2018); Hao Y., Usama M., Yang J., Hossain M.S., Liu Q., Ghoneim A., Recurrent convolutional neural network based multimodal disease risk prediction, Future Generation Computer Systems, 92, 1, pp. 76-83, (2019); Sulikowski P., Zdziebko T., Turzynski D., Kantoch E., Human-website interaction monitoring in recommender systems, Procedia Computer Science, 126, pp. 1587-1596, (2018); Dong N., Zhu X., Blockchain technology evolution and industrial application prospect, Information Security Research, 3, pp. 200-210, (2017); Mohammed S., Bankruptcy prediction by using the altman Z-score model in Oman: A case study of raysut cement company SAOG and its subsidiaries, Australasian Accounting Business and Finance Journal, 10, 4, pp. 70-80, (2016); Fan C., Wang J., Gang W., Li S., Assessment of deep recurrent neural network-based strategies for short-term building energy predictions, Applied Energy, 236, pp. 700-710, (2019); Wu Q., Zhu Q., Li P., A neural network based reputation bootstrapping approach for service selection, Enterprise Information Systems, 9, 7, pp. 768-784, (2015); Braunlich K., Seger C.A., Jentink K.G., Buard I., Kluger B.M., Thaut M.H., Rhythmic auditory cues shape neural network recruitment in parkinson's disease during repetitive motor behavior, European Journal of Neuroscience, 49, 6, pp. 849-858, (2019); Li H., Using blockchain technology to promote the development of cross border e-commerce in China, Monthly Finance and Accounting, 3, pp. 66-146, (2019); Liu Z.F., Analysis on the construction of cross-border E-commerce credit evaluation system under the background of big data, China Business and Market, 30, 6, pp. 58-64, (2016); Shen S., Han S.X., Aberle D.R., Bui A.A., Hsu W., An interpretable deep hierarchical semantic convolutional neural network for lung nodule malignancy classification, Expert Systems with Applications, 128, pp. 84-95, (2019); Tibermacine O., Tibermacine C., Cherif F., Estimating the reputation of newcomer web services using a regression-based method, Journal of Systems and Software, 145, pp. 112-124, (2018); Bortko K., Bartkow P., Jankowski J., Kuras D., Sulikowski P., Multi-criteria evaluation of Recommending Interfaces towards habituation reduction and limited negative impact on user experience, Procedia Computer Science, 159, pp. 2240-2248, (2019); Lu Z., Ge X., Research on the application of blockchain in cross border payment, Southwest Finance, 2, pp. 23-28, (2018); Zhou T., Thung K.H., Zhu X., Shen D., Effective feature learning and fusion of multimodality data using stage-wise deep neural network for dementia diagnosis, Human Brain Mapping, 40, 3, pp. 1001-1016, (2019); Yao B., Hagras H., Alhaddad M.J., Alghazzawi D., A fuzzy logic-based system for the automation of human behavior recognition using machine vision in intelligent environments, Soft Computing, 19, 2, pp. 499-506, (2015); Ahirwadkar B., Deshmukh S.N., Deep neural networks for recommender systems, International Journal of Innovative Technology and Exploring Engineering, 8, 12, pp. 4838-4842, (2019); Tian Y., Zhao G., Shen L., Blockchain transportation: A case study of freight logistics and its market governance, China's Circulation Economy, 2, pp. 50-56, (2018); Zhu W., Beroza G.C., PhaseNet: A deep-neural-network-based seismic arrival-time picking method, Geophysical Journal International, 216, 1, pp. 261-273, (2019); Goswami A., Parashari G.S., Gupta R., Evolutionary stability of reputation-based incentive mechanisms in P2P systems, IEEE Communication Letter, 22, 2, pp. 268-271, (2017); Akuma S., Iqbal R., Jayne C., Doctor F., Comparative analysis of relevance feedback methods based on two user studies, Computers in Human Behavior, 60, pp. 138-146, (2016); Wei W., Wong Y., Du Y., Hu Y., Kankanhalli M., Geng W., A multi-stream convolutional neural network for sEMG-based gesture recognition in muscle-computer interface, Pattern Recognition Letters, 119, pp. 131-138, (2019); Oliveira T., Alhinho M., Rita P., Dhillon G., Modelling and testing consumer trust dimensions in e-commerce, Computers in Human Behavior, 71, pp. 153-164, (2017); Rouhani S., Ashrafi A., Zare Ravasan A., Afshari S., The impact model of business intelligence on decision support and organizational benefits, Journal of Enterprise Information Management, 29, 1, pp. 19-50, (2016); Lodhi S., Manzar M.A., Raja M.A.Z., Fractional neural network models for nonlinear riccati systems, Neural Computing and Applications, 31, 1, pp. 359-378, (2019); Fang H., Xu L., Huang X., Self-adaptive trust management based on game theory in fuzzy large-scale networks, Soft Computing, 21, 4, pp. 907-921, (2017); Singraber A., Behler J., Dellago C., Library-based LAMMPS Implementation of high-dimensional neural network potentials, Journal of Chemical Theory and Computation, 15, 3, pp. 1827-1840, (2019); Li B., Li Y., Wang H., Ma Y., Hu Q., Ge F., Compensation of automatic weighing error of belt weigher based on BP neural network, Measurement, 129, pp. 625-632, (2018)","L. Wang; School of Finacial Technology, Hebei Finance University, Hebei, Baoding, 071051, China; email: wanglina@hbfu.edu.cn",null,"Hindawi Limited",{"$nulls":5},1.6875265E7,null,null,3.5035456E7,"English","Comput. Intell. Neurosci.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85123235127"]
["Musa R.; Nasaratnam S.; Rethinam K.; Varatharajoo P.M.; Shanmugam A.","Musa, Rusnifaezah (57189292442); Nasaratnam, Selvamalar (57203202440); Rethinam, Kalaiselvee (57561553900); Varatharajoo, Parteeban M. (57562140700); Shanmugam, Arunagiri (57560383900)","57189292442; 57203202440; 57561553900; 57562140700; 57560383900","A Study of Factors Influenced Online Shopping Behavior in Malaysia: A Structural Approach",2022.0,"WSEAS Transactions on Business and Economics",19.0,null,null,531.0,541.0,10.0,3.0,"10.37394/23207.2022.19.48","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85127583431&doi=10.37394%2f23207.2022.19.48&partnerID=40&md5=8f177b3e0e4e5970d5662d9bad295afb","Faculty of Business and Management, AIMST University, Kedah, Bedong, Malaysia","Musa R., Faculty of Business and Management, AIMST University, Kedah, Bedong, Malaysia; Nasaratnam S., Faculty of Business and Management, AIMST University, Kedah, Bedong, Malaysia; Rethinam K., Faculty of Business and Management, AIMST University, Kedah, Bedong, Malaysia; Varatharajoo P.M., Faculty of Business and Management, AIMST University, Kedah, Bedong, Malaysia; Shanmugam A., Faculty of Business and Management, AIMST University, Kedah, Bedong, Malaysia","-Online shopping becomes a key tool as the business landscape is modifying. Thus, the behavior of consumer will change accordingly towards online shopping. This study aimed to determine factors influence the online shopping behavior in Malaysia. Six independent factors and one mediator were tested to the dependent variable, online shopping behavior: customer satisfaction, security, site design, convenience, delivery, product brand, perceived usefulness. The questionnaire was adopted in accordance with previous research. Data were collected using survey method. About 352 data were collected from 400 questionnaires distributed through convenience sampling to respondent who want to consume green product. The data was analyzed using statistical packages for the social sciences (SPSS) version 27 and SMART PLS version 3.3.7. Findings postulates delivery, customer satisfaction, and perceived usefulness were significant towards online shopping behavior in Malaysia. Meanwhile, convenience, delivery, and site design were found significant with customer satisfaction. In other findings, customer satisfaction also mediates the relationship between convenience, delivery, design with online shopping behavior. The R2 (40%) of the study indicates the model have a moderate fit of model. In order to build engagement of the audience in social media, the business or marketing manager needs to share valuable and informative content in social media. The social media marketers also need to post high-quality, unique content to drive the reach of the post or videos of their business. This will create a strong relationship between the business and customers through social media platform. © 2022, World Scientific and Engineering Academy and Society. All rights reserved.","convenience; customer satisfaction; delivery; Online shopping behavior; site design; structural model",{"$nulls":7},"Wu W. Y., Ke C. C., Nguyen P. 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Busi. Econ.","Article","Final",null,"Scopus","2-s2.0-85127583431"]
["Zennaro I.; Finco S.; Calzavara M.; Persona A.","Zennaro, Ilenia (57190737200); Finco, Serena (57200245353); Calzavara, Martina (56305128800); Persona, Alessandro (6602705789)","57190737200; 57200245353; 56305128800; 6602705789","Implementing E-Commerce from Logistic Perspective: Literature Review and Methodological Framework",2022.0,"Sustainability (Switzerland)",14.0,2.0,911.0,null,null,null,23.0,"10.3390/su14020911","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124345540&doi=10.3390%2fsu14020911&partnerID=40&md5=8aef4a4350e8816b7ed5c758b5ec7cc6","Department of Management and Engineering, University of Padua, Stradella San Nicola 3, Vicenza, 36100, Italy","Zennaro I., Department of Management and Engineering, University of Padua, Stradella San Nicola 3, Vicenza, 36100, Italy; Finco S., Department of Management and Engineering, University of Padua, Stradella San Nicola 3, Vicenza, 36100, Italy; Calzavara M., Department of Management and Engineering, University of Padua, Stradella San Nicola 3, Vicenza, 36100, Italy; Persona A., Department of Management and Engineering, University of Padua, Stradella San Nicola 3, Vicenza, 36100, Italy","E-commerce is always more diffused as a selling channel around the whole world market, and its importance has increased and continues to increase with the COVID-19 pandemic emergency. It provides enterprises a lot of opportunities, as the importance of physical stores to sell goods is bypassed. However, it has also changed the role of logistics in the supply chain. For this reason, this work aims to identify the main logistics research areas related to e-commerce implementation and the factors and key performance indicators, which should be taken into account for each logistics research area, with particular attention to sustainable aspects. For doing this, a structured and comprehensive literature analysis is carried out. Keywords associated with e-commerce and logistics areas are matched to identify the most interesting works related to its implementation. From the analysis, five main research areas are identified: Supply Chain Network Design (SCND); Outbound Logistics (OL); Reverse Logistics (RL); Warehousing (WR); and IT and data management (E-IT). For each area, key factors, strategies and performance indicators have been identified. Finally, a methodological framework that summarizes the results of the analysis is presented; this is a useful tool for managers to implement or expand their e-commerce business. Many works are focused on one research area, carrying out critical factors, models, and methods to implement that topic. Instead, the methodological framework presented here summarizes multiple research areas from a logistic point of view, identifying for each one input and output variables and how they influence each other. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.","COVID-19; E-commerce; Last-mile logistics; Logistics and supply chain; Reverse logistics; Supply chain network design; Warehouse","business; COVID-19; design; electronic commerce; epidemic; information technology; literature review; logistics; supply chain management; sustainability",{"$nulls":6},{"$cut":{"chars":32601,"head":"Wigand R.T., Electronic Commerce: Definition, Theory, and Context, Inf. Soc, 13, pp. 1-16, (1997); Global Retail E-Commerce Market Size 2014–2023|Statista, (2021); Santarelli E., D'Altri S., The Diffusion of E-commerce among SMEs: Theoretical Implications and Empirical Evidence, Small Bus. Econ, 21, pp. 273-283, (2003); Jedrzejczak-Gas J., Barska A., Sinicakova M., Level of development of e-commerce in EU countries, Managagement, 23, pp. 209-224, (2019); Boysen N., de Koster R., Weidinger F., Warehousing in the e-commerce era: A survey, Eur. J. Oper. Res, 277, pp. 396-411, (2019); Melacini M., Perotti S., Rasini M., Tappia E., E-fulfilment and distribution in omni-channel retailing: A systematic literature review, Int. J. Phys. Distrib. Logist. Manag, 48, pp. 391-414, (2018); Taylor D., Brockhaus S., Knemeyer A.M., Murphy P., Omnichannel fulfillment strategies: Defining the concept and building an agenda for future inquiry, Int. J. Logist. Manag, 30, pp. 863-891, (2019); Hubner A., Wollenburg J., Holzapfel A., Retail logistics in the transition from multi-channel to omni-channel, Int. J. Phys. Distrib. Logist. Manag, 46, pp. 562-583, (2016); Agatz N., Fleischmann M., van Nunen J.A., E-fulfillment and multi-channel distribution—A review, Eur. J. Oper. Res, 187, pp. 339-356, (2008); Ghezzi A., Mangiaracina R., Perego A., Shaping the E-Commerce Logistics Strategy: A Decision Framework Regular Paper, Int. J. Eng. Bus. Manag, 4, pp. 4-13, (2012); Marchet G., Melacini M., Perotti S., Rasini M., Tappia E., Business logistics models in omni-channel: A classification framework and empirical analysis, Int. J. Phys. Distrib. Logist. Manag, 48, pp. 439-464, (2018); Chen Q., Zhang N., Does E-Commerce Provide a Sustained Competitive Advantage? An Investigation of Survival and Sustainability in Growth-Oriented Enterprises, Sustainability, 7, pp. 1411-1428, (2015); Chang Y., Wong S.F., Libaque-Saenz C.F., Lee H., E-Commerce Sustainability: The Case of Pinduoduo in China, Sustainability, 11, (2019); Neumann W.P., Dul J., Human factors: Spanning the gap between OM and HRM, Int. J. Oper. Prod. Manag, 30, pp. 923-950, (2010); Kembro J.H., Norrman A., Eriksson E., Adapting warehouse operations and design to omni-channel logistics A literature review and research agenda, Int. J. Phys. Distrib. Logist. Manag, 48, pp. 890-912, (2018); Lafkihi M., Pan S., Ballot E., Freight transportation service procurement: A literature review and future research opportunities in omnichannel E-commerce, Transp. Res. Part E Logist. Transp. Rev, 125, pp. 348-365, (2019); Mangiaracina R., Marchet G., Perotti S., Tumino A., A review of the environmental implications of B2C e-commerce: A logistics perspective, Int. J. Phys. Distrib. Logist. Manag, 45, pp. 565-591, (2015); Jaghbeer Y., Hanson R., Johansson M.I., Automated order picking systems and the links between design and performance: A systematic literature review, Int. J. Prod. Res, 58, pp. 4489-4505, (2020); Tate M., Coker B., Hope B., Coker B., Moving to Multi-Channel E-Commerce: Lessons Learned from a Case Study of an Apparel and Home-Ware Catalogue Company, J. Internet Commer, 4, pp. 3-32, (2008); Yee A., Chong L., Ooi K.B., Tak Y.K., Shuyang Z., Factors Affecting the Adoption of E-commerce: A Study of the Textile Industry in Wujin, China, Int. J. Bus. Manag. Sci, 2, pp. 117-130, (2009); Sarkar A., E-Commerce Adoption and Implementation in Automobile Industry: A Case Study, World Acad. Sci. Eng. Technol, 58, pp. 7-94, (2009); Paris D.L., Iahad N.A., Bahari M., Exploring Implementation Factors Influencing Business-to-Customer (B2C) e-Commerce, Adv. Sci. Lett, 21, pp. 1455-1459, (2015); Walker J.H., Saffu K., Mazurek M., An Empirical Study of Factors Influencing E-Commerce Adoption/Non-Adoption in Slovakian SMEs, J. Internet Commer, 15, pp. 189-213, (2016); Ye Y., Lau K.H., Kok L., Teo Y., Drivers and barriers of omni-channel retailing in China A case study of the fashion and. apparel industry, Int. J. Retail. Distrib. Manag, 46, pp. 657-689, (2018); Cai Y.-J., Lo C.K., Omni-channel management in the new ret"}},"I. Zennaro; Department of Management and Engineering, University of Padua, Vicenza, Stradella San Nicola 3, 36100, Italy; email: ilenia.zennaro@unipd.it",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85124345540"]
["Rajendran S.D.; Wahab S.N.","Rajendran, Salini Devi (57205628130); Wahab, Siti Norida (57204971443)","57205628130; 57204971443","Investigating last-mile delivery options on online shoppers experience and repurchase intention",2022.0,"International Journal of Electronic Marketing and Retailing",13.0,2.0,null,224.0,241.0,17.0,5.0,"10.1504/IJEMR.2022.121826","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85128746226&doi=10.1504%2fIJEMR.2022.121826&partnerID=40&md5=9cc92accc59de8ba3eb606a28ec88116","School of Food Studies and Gastronomy, Faculty of Social Sciences and Leisure Management, Taylor's University, 1, Jalan Taylors, Subang Jaya, Selangor, 47500, Malaysia; Faculty of Business and Management, Universiti Teknologi MARA Cawangan Selangor, Kampus Puncak Alam, Bandar Puncak Alam, Selangor, 42300, Malaysia","Rajendran S.D., School of Food Studies and Gastronomy, Faculty of Social Sciences and Leisure Management, Taylor's University, 1, Jalan Taylors, Subang Jaya, Selangor, 47500, Malaysia; Wahab S.N., Faculty of Business and Management, Universiti Teknologi MARA Cawangan Selangor, Kampus Puncak Alam, Bandar Puncak Alam, Selangor, 42300, Malaysia","Last-mile delivery is considered an imperative element in online trading. As technology is expanding and accelerating, the need to make sure that online shoppers in Malaysia experienced on-time and reliable online shopping delivery services has become vital. Hence, e-retailers play a major part in investigating the challenges faced by online shoppers during delivery services and identifying their most preferred delivery options. This paper aims to investigate the influence of last-mile delivery options on the online shopper's experience and its effect on the intention to repurchase with e-retailers. The study was carried out among 150 experienced online shoppers. Data were analysed using structural equation modelling via SmartPLS 3. Findings revealed that time-slot delivery and unattended delivery significantly influence online shoppers' experience and repurchase intention. Hence, this paper provides useful insights for online retailers to improve their current and future last-mile delivery services to customers. Copyright © 2022 Inderscience Enterprises Ltd.","delivery options; e-retailers; last-mile delivery; online shopping",{"$nulls":7},"Agatz N., Campbell A., Fleischmann M., Savelsbergh M., Time slot management in attended home delivery, Transportation Science, 45, 3, pp. 435-449, (2011); Ahn T., Ryu S., Han I., The impact of the online and offline features on the user acceptance of internet shopping malls, Electronic Commerce Research and Applications, 3, 4, pp. 405-420, (2014); Allen J., Piecyk M., Piotrowska M., Mcleod F., Cherrett T., Ghali K., Austwick M., Understanding the impact of e-commerce on last-mile light goods vehicle activity in urban areas: the case of London, Transportation Research Part D: Transport and Environment, Part B, 61, pp. 325-338, (2017); Atzori L., Itera A., Morabito G., The internet of things: a survey, Computer Network, 54, 15, pp. 2787-2805, (2010); Brewster M., An L., From mall to mobile: adjusting to new consumer habits, Global Consumer Insights Survey 2018, (2018); Browne M., Rizet C., Allen J., A comparative assessment of the light goods vehicle fleet and the scope to reduce its CO2 emissions in the UK and France, Procedia - Social and Behavioral Sciences, 125, pp. 334-344, (2014); Byrne B.M., Structural Equation Modelling with AMOS: Basic Concepts, Application and Programming, (2010); Caputo F., Carrubbo L., Sarno D., The influence of cognitive dimensions on the consumer-SME relationship: a sustainability-oriented view, Sustainability, 10, 9, (2018); Castle J., Parcel delivery and postal problems, CHOICE, (2016); Charlton G., Which ecommerce delivery options do customers want?, SaleCycle Blog, (2018); de Vos K., Ecommerce delivery trends: what contributes to a positive experience?, MyCustomer, (2016); Dessart L., Veloutsou C., Morgan-Thomas A., Consumer engagement in online brand communities: a social media perspective, Journal of Product & Brand Management, 24, 1, pp. 28-42, (2015); Malaysia Digital Marketing Statistics 2017, (2017); Edwards J., McKinnon A., Cherrett T., McLeod F., Song L., The CO2 benefits of using collection/delivery points for failed home deliveries, Transportation Research Record, 10, 1901, pp. 136-143, (2010); Door-to-Door Courier Service in Europe, (2018); Ferguson D., Online shopping: which supermarket really delivers?, The Guardian, (2015); Hair J., Hult G.T.M., Ringle C., Sarstedt M., A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM), (2017); Han S., Zhao L., Chen K., Luo Z., Mishra D., Appointment scheduling and routing optimization of attended home delivery system with random customer behavior, European Journal of Operational Research, 262, 3, pp. 966-980, (2017); Henseler J., Ringle C.M., Sarstedt M., A new criterion for assessing discriminant validity in variance-based structural equation modeling, Journal of the Academy of Marketing Science, 43, 1, pp. 115-135, (2015); Holdorf S., Haasis H., Last mile delivery concepts in e-commerce an empirical approach, The 8th International Conference on Software, Knowledge, Information Management and Applications, (2014); Huang Z., The Last Mile Delivery in China: Adoption of Last Mile Delivery Modes by Customers, (2015); Hungerlander P., Rendl A., Truden C., On the slot optimization problem in on-line vehicle routing, Transportation Research Procedia, 27, pp. 492-499, (2017); Janjevic M., Winkenbach M., Merchan D., Integrating collection-and-delivery points in the strategic design of urban last-mile e-commerce distribution networks, Transportation Research Part E: Logistics and Transportation Review, 131, pp. 37-67, (2019); Joerss M., Schroder J., Neuhaus F., Klink C., Mann F., Parcel delivery the future of last mile, McKinsey & Company, (2016); Khalifa M., Liu V., Online consumer retention: contingent effects of online shopping habit and online, shopping experience, European Journal of Information Systems, 16, 6, pp. 780-792, (2007); Kim H-R., Developing an index of online customer satisfaction, Journal of Financial Services Marketing, 10, pp. 49-64, (2004); Kline R.B., Principles and Practice of Structural Equation Modeling, (2010); Delivering Consumer Choice: 2015 State of eCommerce Delivery, (2015); Online Retailing - UK, (2016); Morganosky M., Cude B., Consumer demand for online food retailing: is it really a supply side issue?, International Journal of Retail & Distribution Management, 30, 10, pp. 451-458, (2015); Morganti E., Seidel S., Blanquart C., Dablanc L., Lenz B., The impact of e-commerce on final deliveries: alternative parcel delivery services in France and Germany, Transportation Research Procedia, 4, pp. 178-190, (2014); Moynagh M., Worsley R., Tomorrow's consumer - the shifting balance of power, Journal of Consumer Behaviour, 1, 3, pp. 293-301, (2002); Murfield M., Boone C.A., Rutner P., Thomas R.G., Investigating logistics service quality in omni-channel retailing, International Journal of Physical Distribution & Logistics Management, 4, 47, pp. 263-296, (2017); Pallant J., SPSS Survival Manual, (2016); Pandey S., Chawla D., Online customer experience (OCE) in clothing e-retail, International Journal of Retail & Distribution Management, 3, 46, pp. 323-346, (2018); Pappas I., Pateli A., Giannakos M., Chrissikopoulos V., Moderating effects of online shopping experience on customer satisfaction and repurchase intentions, International Journal of Retail & Distribution Management, 42, 3, pp. 187-204, (2014); Rai H.B., Verlinde S., Macharis C., The 'next day, free delivery' myth unravelled: possibilities for sustainable last mile transport in an omnichannel environment, International Journal of Retail & Distribution Management, 47, 1, pp. 39-54, (2019); Rajendran S.D., Wahab S.N., Ling Y.W., Yun L.S., The impact of logistics services on the e-shoppers' satisfaction, International Journal of Supply Chain Management, 7, 5, pp. 461-469, (2018); Rose S., Hair N., Clark M., Online customer experience: a review of the business-to-consumer online purchase context, International Journal of Management Reviews, 13, 1, pp. 24-39, (2011); Scherr Y.O., Neumann-Saavedra B.A., Hewitt M., Mattfeld D.C., Service network design for same day delivery with mixed autonomous fleets, Transportation Research Procedia, 30, pp. 23-32, (2018); Last Mile Services: Customer Demand from Retailers 2017 | Statistic, (2017); The 2016 State of Shipping in Commerce Report, (2016); Visser J., Nemoto T., Browne M., Home delivery and the impacts on urban freight transport: a review, Procedia - Social and Behavioral Sciences, 125, pp. 15-27, (2014); Viu-Roig M., Alvarez-Palau E.J., The impact of e-commerce-related last-mile logistics on cities: a systematic literature review, Sustainability, 12, 6492, pp. 1-19, (2020); Xu M., Ferrand B., Roberts M., The last mile of e-commerce - unattended delivery from the consumers and eTailers' perspectives, International Journal of Electronic Marketing and Retailing, 2, 1, pp. 20-38, (2008); Zhang P., Li T., Understanding Consumer Preferences for Logistics Services within Online Retailing of Fresh Products: a Research Conducted on Swedish Consumers, (2018)","S.D. Rajendran; School of Food Studies and Gastronomy, Faculty of Social Sciences and Leisure Management, Taylor's University, Selangor, 1, Jalan Taylors, Subang Jaya, 47500, Malaysia; email: Salini.Rajendran@taylors.edu.my",null,"Inderscience Publishers",{"$nulls":5},1.7411025E7,null,null,null,"English","Int. J. Electron. Mark. Retail.","Article","Final",null,"Scopus","2-s2.0-85128746226"]
["Xuan L.","Xuan, Liyuan (57210158859)",5.7210158859E10,"Computer aided optimization of picking system in logistics distribution center",2022.0,"Computer-Aided Design and Applications",19.0,"S4",null,46.0,55.0,9.0,4.0,"10.14733/cadaps.2022.S4.46-55","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85111758142&doi=10.14733%2fcadaps.2022.S4.46-55&partnerID=40&md5=0500351fcce4e5b1bddf651ea61c9b70","College of Economics and Management, Zhejiang University of Technology, Hangzhou, 310032, China","Xuan L., College of Economics and Management, Zhejiang University of Technology, Hangzhou, 310032, China","With the development of information technology and the improvement of scientific and technological level, the e-commerce industry has begun to enter the stage of large-scale development and operation. Especially with the continuous expansion of the scale of the online shopping market, the order structure of e-commerce enterprises is increasingly showing the development trend of \"small batch, multi-batch and diversified\", which increases the difficulty of short delivery in the logistics distribution center of e-commerce and becomes one of the bottlenecks restricting the rapid development of e-commerce enterprises. In this paper, C.V analysis method to establish SLP system logistics distribution center and new business model, effectively control the total inventory and end customer satisfaction. In order to solve the problems of insufficient receiving capacity of the main body and low utilization rate of personnel and equipment in the picking operation, a Petri net model of picking operation in the distribution center is established by using Petri net tool. The influencing factors of the model are analyzed and the optimization scheme of picking operation is put forward. The simulation platform is used to convert the Petri net model into a simulation model. By running the simulation model and comparing the simulation results before and after optimization, the feasibility and effectiveness of the optimization scheme are discussed in detail, so as to improve the utilization rate of personnel and equipment and operation efficiency. © 2022 CAD Solutions, LLC,.","Computer Aided; Distribution Center; Logistics Distribution; Picking System; System Optimization","Customer satisfaction; Personnel; Petri nets; Warehouses; Computer-aided optimizations; Distribution centers; E-commerce enterprise; Large-scale development; Logistics distribution centers; Online shopping market; Operation efficiencies; Technological level; Electronic commerce",{"$nulls":6},"Klumpp M., Hesenius M., Meyer O., Production logistics and human-computer interaction-state-of-the-art, challenges and requirements for the future, The International Journal of Advanced Manufacturing Technology, 105, 9, pp. 3691-3709, (2019); Dobransky J., Baron P., Vojnova E., Optimization of the production and logistics processes based on computer simulation tools, Key engineering materials, 669, pp. 532-540, (2016); Klumpp M., Zijm H., Logistics innovation and social sustainability: How to prevent an artificial divide in Human–Computer Interaction, Journal of Business Logistics, 40, 3, pp. 265-278, (2019); Vavrik V., Gregor M., Grznar P., Computer simulation as a tool for the optimization of logistics using automated guided vehicles, Procedia engineering, 192, pp. 923-928, (2017); Ali S.-M., Arafin A., Moktadir M.-A., Barriers to reverse logistics in the computer supply chain using interpretive structural model, Global journal of flexible systems management, 19, 1, pp. 53-68, (2018); Vanderroost M., Ragaert P., Verwaeren J., The digitization of a food package’s life cycle: Existing and emerging computer systems in the logistics and post-logistics phase, Computers in Industry, 87, pp. 15-30, (2017); Buckova M., Krajcovic M., Edl M., Computer simulation and optimization of transport distances of order picking processes, Procedia engineering, 192, pp. 69-74, (2017); Grznar P., Gregor M., Mozol S., Optimization of logistics process in context of smart logistics by using computer simulation-case study, Proceedings of CBU in Economics and Business, 1, pp. 84-90, (2020); Kamrani A., Nasr E.-A., Al-Ahmari A., Feature-based design approach for integrated CAD and computer-aided inspection planning, International Journal of Advanced Manufacturing Technology, 76, pp. 2159-2183, (2015); Landschutzer C., Ehrentraut F., Jodin D., Containers for the Physical Internet: requirements and engineering design related to FMCG logistics, Logistics Research, 8, 1, pp. 1-22, (2015)","L. Xuan; College of Economics and Management, Zhejiang University of Technology, Hangzhou, 310032, China; email: hxszq002@163.com",null,"CAD Solutions, LLC",{"$nulls":5},1.686436E7,null,null,null,"English","Comput.-Aided Des. Appl.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85111758142"]
["Muñoz-Villamizar A.; Velázquez-Martínez J.C.; Mejía-Argueta C.; Gámez-Pérez K.","Muñoz-Villamizar, Andrés (55886287800); Velázquez-Martínez, Josué C. (56032402100); Mejía-Argueta, Christopher (56401891700); Gámez-Pérez, Karla (57194041982)","55886287800; 56032402100; 56401891700; 57194041982","The impact of shipment consolidation strategies for green home delivery: a case study in a Mexican retail company",2022.0,"International Journal of Production Research",60.0,8.0,null,2443.0,2460.0,17.0,10.0,"10.1080/00207543.2021.1893852","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85102574658&doi=10.1080%2f00207543.2021.1893852&partnerID=40&md5=2098a574cb33b7483916ca01ca9fd4b5","Center for Transportation & Logistics, Massachusetts Institute of Technology, Cambridge, MA, United States; School of Economics and Management Sciences, Universidad de La Sabana, Chía, Colombia; Science and Engineering School, Tecnológico de Monterrey, Leon, Mexico","Muñoz-Villamizar A., Center for Transportation & Logistics, Massachusetts Institute of Technology, Cambridge, MA, United States, School of Economics and Management Sciences, Universidad de La Sabana, Chía, Colombia; Velázquez-Martínez J.C., Center for Transportation & Logistics, Massachusetts Institute of Technology, Cambridge, MA, United States; Mejía-Argueta C., Center for Transportation & Logistics, Massachusetts Institute of Technology, Cambridge, MA, United States; Gámez-Pérez K., Center for Transportation & Logistics, Massachusetts Institute of Technology, Cambridge, MA, United States, Science and Engineering School, Tecnológico de Monterrey, Leon, Mexico","The growth of e-commerce has increased the number of home deliveries that need to be made in retail operations. Strategies such as reducing routing distance using optimisation models have been the most popular approaches to enhancing the efficiency of the delivery process and reducing its environmental burden. However, recently, customer purchasing behaviour has become relevant in understanding demand trends and increasing the effectiveness of the supply chain process. Customers are subject to different incentives to drive them to wait longer for their home deliveries. These incentives allow companies to pool and ship in more cost-efficient and energy-friendly alternatives. In this article, we present a methodology that uses a mixed-integer-linear programming model to evaluate the impact of extending delivery slots. We use real data from one of the largest retail companies in Mexico to analyse the impact of different time slot extensions for three different criteria: distance, transport costs and CO2 emissions. Our results show that the common approach of minimising distance is not recommended for any of the scenarios under study. On average, having up to 4 days for deliveries leads to savings of 57% in total distance, 61% in total costs and 56% in fuel consumption and/or CO2 emissions. © 2021 Informa UK Limited, trading as Taylor & Francis Group.","emerging markets; environmental impact; Last-mile operations; optimisation; shipment pooling; urban distribution","Carbon dioxide; Digital storage; Integer programming; Sales; Ships; Supply chains; Delivery process; Environmental burdens; Mixed integer linear programming model; Optimisation models; Retail operations; Routing distance; Supply chain process; Transport costs; Costs",{"$nulls":6},"Aljohani K., Thompson R., A Multi-Criteria Spatial Evaluation Framework to Optimise the Siting of Freight Consolidation Facilities in Inner-City Areas, Transportation Research Part A: Policy And Practice, 138, pp. 51-69, (2020); Anand N., van Duin R., Quak H., Tavasszy L., Relevance of City Logistics Modelling Efforts: A Review, Transport Reviews, 35, 6, pp. 701-719, (2015); Archetti C., Fernandez E., Huerta-Munoz D., The Flexible Periodic Vehicle Routing Problem, Computers & Operations Research, 85, pp. 58-70, (2017); Archetti C., Jabali O., Speranza M., Multi-period Vehicle Routing Problem with due Dates, Computers & Operations Research, 61, pp. 122-134, (2015); Avila M.A., Larco J.A., Antonini C., Ortiz M.B., Mejia Argueta C., A Discrete Choice Model for Retailer Selection in Emerging Markets, Supply Chain Management and Logistics in Emerging Markets, pp. 299-318, (2020); Barth M., Younglove T., Scora G., (2005); Bektas T., Ehmke J., Psaraftis H., Puchinger J., The Role of Operational Research in Green Freight Transportation, European Journal of Operational Research, (2018); Bektas T., Laporte G., The Pollution-Routing Problem, Transportation Research Part B: Methodological, 45, pp. 1232-1250, (2011); Ben Mohamed I., Klibi W., Labarthe O., Deschamps J., Babai M., Modelling and Solution Approaches for the Interconnected City Logistics, International Journal of Production Research, 55, 9, pp. 2664-2684, (2017); Bozorgi A., Pazour J., Nazzal D., A New Inventory Model for Cold Items That Considers Costs and Emissions, International Journal Of Production Economics, 155, pp. 114-125, (2014); Braekers K., Ramaekers K., Van Nieuwenhuyse I., The Vehicle Routing Problem: State of the art Classification and Review, Computers & Industrial Engineering, 99, pp. 300-313, (2016); Bravo J.J., Vidal C.J., Freight Transportation Function in Supply Chain Optimization Models: a Critical Review of Recent Trends, Expert Systems with Applications, 40, 17, pp. 6742-6757, (2018); Browne M., Piotrowska M., Woodburn A., Allen J., Literature Review WM9: Part I-Urban Freight Transport. 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Montoya-Torres J.R., Munoz-Villamizar A., Vega-Mejia C.A., On the Impact of Collaborative Strategies for Goods Delivery in City Logistics, Production Planning & Control, 27, 6, pp. 443-455, (2016); Munoz-Villamizar A., Quintero-Araujo C., Montoya-Torres J., Faulin J., Short- and mid-Term Evaluation of the use of Electric Vehicles in Urban Freight Transport Collaborative Networks: A Case Study, International Journal of Logistics Research and Applications, 22, 3, pp. 229-252, (2019); Munoz-Villamizar A., Santos J., Montoya-Torres J.R., Jaca C., Using OEE to Evaluate the Effectiveness of Urban Freight Transportation Systems: A Case Study, Journal of Production Economics, 197, pp. 232-242, (2018); Road Cargo Transport., (2019); Pan S., Ballot E., Fontane F., The Reduction of Greenhouse gas Emissions from Freight Transport by Pooling Supply Chains, International Journal of Production Economics, 143, 1, pp. 86-94, (2013); Ranieri L., Digiesi S., Silvestri B., Roccotelli M., A Review of Last Mile Logistics Innovations in an Externalities Cost Reduction Vision, Sustainability, 10, 3, (2018); 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Network Modelling and Intelligent Transport Systems, (2001); Thompson R.G., Taniguchi E., City Logistics and Freight Transport, Handbook of Logistics and Supply-Chain Management (Handbooks in Transport, Volume 2), 550, pp. 393-405, (2017); Toth P., Vigo D., Vehicle Routing: Problems, Methods, and Applications, (2014); Tsang Y., Wu C., Lam H., Choy K., Ho G., Integrating Internet of Things and Multi-Temperature Delivery Planning for Perishable Food E-Commerce Logistics: A Model and Application, International Journal Of Production Research, pp. 1-23, (2020); Ubeda S., Arcelus F., Faulin J., Green Logistics at Eroski: A Case Study, International Journal of Production Economics, 131, 1, pp. 44-51, (2011); Ulmer M.W., Mattfeld D.C., Soeffker N., (2016); Velazquez-Martinez J., Fransoo J., Blanco E., Valenzuela-Ocana K., A new Statistical Method of Assigning Vehicles to Delivery Areas for CO 2 Emissions Reduction, Transportation Research Part D: Transport and Environment, 43, pp. 133-144, (2016); Velazquez-Martinez J., Yoshizaki H., Mejia-Argueta C., Introduction to Supply Chain Management and Logistics in Latin America, Supply Chain Management and Logistics in Latin America, pp. 1-5, (2018); Visser J., Nemoto T., Browne M., Home Delivery and the Impacts on Urban Freight Transport: A Review, Procedia - Social and Behavioral Sciences, 125, pp. 15-27, (2014); Yin R.K., Case Study Research. Design and Methods, (2013); Zhang Y., Sun L., Hu X., Zhao C., Order Consolidation for the Last-Mile Split Delivery in Online Retailing, Transportation Research Part E: Logistics and Transportation Review, 122, pp. 309-327, (2019)","A. Muñoz-Villamizar; Center for Transportation & Logistics, Massachusetts Institute of Technology, Cambridge, United States; email: andresmunvi@unisabana.edu.co",null,"Taylor and Francis Ltd.",{"$nulls":5},207543.0,null,"IJPRB",null,"English","Int J Prod Res","Article","Final",null,"Scopus","2-s2.0-85102574658"]
["Ogunjimi A.; Rahman M.; Islam N.; Hasan R.","Ogunjimi, Ayotunde (57257385100); Rahman, Mizan (8716301500); Islam, Nazrul (57210939883); Hasan, Rajibul (58124006100)","57257385100; 8716301500; 57210939883; 58124006100","Smart mirror fashion technology for the retail chain transformation",2021.0,"Technological Forecasting and Social Change",173.0,null,121118.0,null,null,null,22.0,"10.1016/j.techfore.2021.121118","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85114830977&doi=10.1016%2fj.techfore.2021.121118&partnerID=40&md5=9f1919dc56822c30ccd10a3199fa7dbe","University of Wales Trinity Saint David, UK, United Kingdom; Lincoln International Business School, University of Lincoln, UK, United Kingdom; Department of Science, Innovation, Technology and Entrepreneurship, University of Exeter Business School, UK, United Kingdom; School of Business, Maynooth University, Ireland","Ogunjimi A., University of Wales Trinity Saint David, UK, United Kingdom; Rahman M., Lincoln International Business School, University of Lincoln, UK, United Kingdom; Islam N., Department of Science, Innovation, Technology and Entrepreneurship, University of Exeter Business School, UK, United Kingdom; Hasan R., School of Business, Maynooth University, Ireland","As the digitalisation of businesses continues to change customers’ purchasing habits, brick-and-mortar retail SMEs (Small and Medium Enterprises) are confronted with unprecedented challenges. The proliferation of e-commerce and digital businesses is not only changing the rules of business but disrupting them by introducing new possibilities, especially with the integration of new technology. Studies that have attempted to measure technology-based service quality in retail settings are limited to online service experiences, creating a significant gap in the literature. The primary purpose of this paper is to explore how the service quality of brick-and-mortar clothing retail chains can be improved using innovative technology such as smart mirror fashion technology (SMFT), something academic research has not yet specifically addressed. This study used a qualitative approach with Soft System Methodology (SSM), based upon interviews triangulated with observations and field notes. It focused on the top five UK clothing retail chains, measured by market capitalisation. We found that the quality of service received is currently perceived as low when compared to customers’ expectations; however, use of technology enhanced service quality and influenced customer satisfaction. There was a positive relationship between service quality, customer satisfaction and the use of SMFT. The contribution of this study lies in the development of a new framework that integrates SMFT with traditional in-store transaction processes, resulting in improvements in service delivery and managerial practices of the offline clothing retail service providers. The study concludes that embracing SMFT can help provide high-quality service, creating value for customers. © 2021","Brick-and-mortar store; Innovation; Offline retail; Service quality; Smart mirror fashion technology","United Kingdom; Brick; Customer satisfaction; Mirrors; Mortar; Quality of service; Brick-and-mortar store; Customers' satisfaction; Enterprise IS; Innovation; Offline; Offline retail; Retail chains; Service Quality; Small-and-medium enterprise; Smart mirror fashion technology; clothing industry; consumption behavior; innovation; qualitative analysis; retailing; service quality; small and medium-sized enterprise; Sales",{"$nulls":6},"Acquila-Natale E., Iglesias-Pradas S., A matter of value? Predicting channel preference and multichannel behaviours in retail, Techno. Forecast. Soc. Chang., 162, 2021, (2020); Alam S.S., Susmit S., Lin C.Y., Masukujjaman M., Ho Y.H., Factors affecting augmented reality adoption in the retail industry, J. 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["Chen L.; Chen Y.; Langevin A.","Chen, Lu (55739185200); Chen, Yuyi (57223049731); Langevin, André (7004486817)","55739185200; 57223049731; 7004486817","An inverse optimization approach for a capacitated vehicle routing problem",2021.0,"European Journal of Operational Research",295.0,3.0,null,1087.0,1098.0,11.0,7.0,"10.1016/j.ejor.2021.03.031","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85104668317&doi=10.1016%2fj.ejor.2021.03.031&partnerID=40&md5=fc7ad884671b22d69a1e2ce9d12c0dd0","School of Mechanical Engineering, Shanghai Jiao Tong University, China; École Polytechnique de Montréal and CIRRELT, H3C 3A7, Canada","Chen L., School of Mechanical Engineering, Shanghai Jiao Tong University, China; Chen Y., School of Mechanical Engineering, Shanghai Jiao Tong University, China; Langevin A., École Polytechnique de Montréal and CIRRELT, H3C 3A7, Canada","The capacitated vehicle routing problem studied in this paper stems from an e-commerce company in China. Efficient delivery is crucial for the logistic service of the company. It was observed that experienced drivers (experts) planned better delivery routes than those from optimization tools. This is largely due to the fact that the objectives (or the cost matrices) in real life are highly complicated and the experts use more practical objectives while making decisions. In this paper, we propose an inverse optimization formulation to derive a proper cost matrix by learning from the experts experience. Thus, the routing model with respect to the learned cost matrix could provide solutions as good as those given by experts. A multiplicative weights updates algorithm is applied to achieve a fast and convergent learning process. Experimental analyses based on randomly generated instances and real-world instances demonstrate the effectiveness of the approach. © 2021 Elsevier B.V.","Inverse optimization; Last-mile delivery; On-line learning; Routing","E-learning; Inverse problems; Learning algorithms; Learning systems; Matrix algebra; Optimization; Capacitated vehicle routing problem; Cost matrices; Delivery routes; E- commerces; Inverse optimization; Last-mile delivery; Logistics services; Online learning; Optimization approach; Routings; Vehicle routing",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (51775347)","This work was supported by National Nature Science Foundation of China (project number: 51775347). And we thank the referees for their valuable comments. 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Chen; School of Mechanical Engineering, Shanghai Jiao Tong University, China; email: chenlu@sjtu.edu.cn",null,"Elsevier B.V.",{"$nulls":5},3772217.0,null,"EJORD",null,"English","Eur J Oper Res","Article","Final",null,"Scopus","2-s2.0-85104668317"]
["Iwan S.; Nürnberg M.; Jedliński M.; Kijewska K.","Iwan, Stanisław (36477426300); Nürnberg, Mariusz (57203995099); Jedliński, Mariusz (57194193121); Kijewska, Kinga (36477275100)","36477426300; 57203995099; 57194193121; 36477275100","Efficiency of light electric vehicles in last mile deliveries – Szczecin case study",2021.0,"Sustainable Cities and Society",74.0,null,103167.0,null,null,null,31.0,"10.1016/j.scs.2021.103167","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85111502889&doi=10.1016%2fj.scs.2021.103167&partnerID=40&md5=198be64a8471f50960776e8e4b41a559","Maritime University of Szczecin, Faculty of Transport Economics and Engineering, 11 Pobożnego Str., Szczecin, 70-515, Poland","Iwan S., Maritime University of Szczecin, Faculty of Transport Economics and Engineering, 11 Pobożnego Str., Szczecin, 70-515, Poland; Nürnberg M., Maritime University of Szczecin, Faculty of Transport Economics and Engineering, 11 Pobożnego Str., Szczecin, 70-515, Poland; Jedliński M., Maritime University of Szczecin, Faculty of Transport Economics and Engineering, 11 Pobożnego Str., Szczecin, 70-515, Poland; Kijewska K., Maritime University of Szczecin, Faculty of Transport Economics and Engineering, 11 Pobożnego Str., Szczecin, 70-515, Poland","City users gladly apply comfortable and time-saving e-commerce solutions as an alternative to traditional purchase. The present pandemic crisis made this issue even more important. It significantly increased the number of transport operations within the city area, as each order has to be delivered directly to the purchaser. Consequently, city authorities are confronted with the important challenge: how to fulfil the expectations and needs of city users in the context of transport system functioning in view of reducing the negative impacts of urban freight transport in terms of safety, air pollution or noise. This is one of the most important elements of social sustainability in cities. One of the solutions that help reduce the negative environmental impacts of urban freight transport is making use of vehicles that produce less air pollution, such as electric vans. It proved to be very effective in decreasing transportation footprint by reducing local emissions of e.g. PM or NOx. However, one of the key limitations is the potential short driving range of such vehicles, which results from the battery capacity and charging infrastructure availability. In recent years, some analyses related to that issue have been made. Nevertheless, the studies have taken into account passenger cars only. This paper presents the results of the research study aimed at verification of electric vans energy efficiency in real-life conditions, i.e. when delivering courier consignments. The electric van used for the purposes of the experiment was Nissan eNV200. This paper fulfils the important knowledge gap and could be helpful from both theoretical and practical perspectives. It should be emphasised that the experiment was carried out in real-life conditions, i.e. in the course of performing business processes in one of the worldwide known CEP companies. The research study was carried out under the EUFAL international project, funded under the Electric Mobility Europe programme. The results of the research shown high potential of electric vehicles and usefulness of electromobility in last mile deliveries. The business partner of the research is now on the stage of electric freight vehicles implementation into vehicles fleets. © 2021","City logistics; city sustainability; City users’ needs; Electric freight vehicles; Electro-mobility; Transport system impact; Urban freight transport","Poland [Central Europe]; Szczecin [Zachodniopomorskie]; Zachodniopomorskie; Air pollution; Electric automobiles; Energy efficiency; Freight transportation; Trucks; Urban transportation; City logistics; City sustainability; City user’ need; Condition; Electric freight vehicle; Electro mobilities; Last mile; Research studies; Transport system impact; Urban freight transport; efficiency measurement; electric vehicle; freight transport; logistics; sustainability; transportation system; urban transport; Sustainable development",{"$nulls":4},"European Commission within the research and innovation framework programme Horizon 2020, (723977)","The research introduced in the paper has been realized under the project EUFAL (Electric urban freight and logistics), co-funded by the ERA-NET Cofund Electric Mobility Europe (EMEurope) and national funding organisations. EMEurope is co-funded by the European Commission within the research and innovation framework programme Horizon 2020 (Project No. 723977 ).","Adnan N., Nordin S.M., Rahman I., Vasant P., Noor M.A., An overview of electric vehicle technology: a vision towards sustainable transportation, Intelligent transportation and planning: Breakthroughs in research and practice, pp. 292-309, (2018); Allen J., Browne M., Cherrett T., Investigating relationships between road freight transport, facility location, logistics management and urban form, Journal of Transport Geography, 24, (2012); (2019); Davis B.A., Figliozzi M.A., A methodology to evaluate the competitiveness of electric delivery trucks, Transportation Research Part E: Logistics and Transportation Review, 49, 1, pp. 8-23, (2013); Deb S., Tammi K., Kalita K., Mahanta P., Review of recent trends in charging infrastructure planning for electric vehicles, Wiley Interdisciplinary Reviews Energy and Environment, 7, 6, (2018); Lee D.-Y., Thomas V.M., Marilyn A., Brown electric urban delivery trucks: energy use, Greenhouse Gas Emissions, and Cost-Effectiveness Environmental Science & Technology, 47, 14, (2013); Ducret R., Using urban modelling and geographical analyses to tackle emergent urban logistics issues, Computational Science and Its Applications –ICCSA 2014, Lecture Notes in Computer Science, (2014); Duin van J.H.R., Tavasszy L.A., Quak H.J., Towards E(lectric)-urban freight: First promising steps in the electronic vehicle revolution, European Transport-Trasporti Europei, (2013); (2018); Giordano A., Fischbeck P., Scott M.H., Environmental and economic comparison of diesel and battery electric delivery vans to inform city logistics fleet replacement strategies, Transportation Research Part D: Transport and Environment, (2017); Granovetter M., Economic action and social structure: The problem of embeddedness, American Journal of Sociology, 91, 3, pp. 481-510, (1985); Huo M.Q., Sato K., Ohizumi T., Akimoto H., Takahashi K., Characteristics of carbonaceous components in precipitation and atmospheric particle at Japanese sites, Atmospheric Environment, 146, pp. 164-173, (2016); Iwan S., Kijewska K., Johansen B.G., Eidhammer O., Malecki K., Konicki W., Thompson R.G., Analysis of the environmental impacts of unloading bays based on cellular automata simulation, Transportation Research Part D: Transport and Environment, 61, pp. 104-117, (2018); Iwan S., Kijewska K., Kijewski D., Possibilities of applying electrically powered vehicles in urban freight transport, Procedia - Social and Behavioral Sciences, 151, pp. 87-101, (2014); Juan A.A., Mendez C.A., Fauli J., de Armas J., Grasman S.E., Electric vehicles in logistics and transportation: A survey on emerging environmental, strategic, and operational challenges, Energies, 9, 7, (2016); Khalkhali H., Hosseinia S.H., Multi-class EV charging and performance-based regulation service in a residential smart parking lot, Sustainable Energy Grids and Networks, 22, (2020); Kijewska K., Konicki W., Iwan S., Freight transport pollution propagation at urban areas based on Szczecin example, Transportation Research Procedia, 14, pp. 1543-1552, (2016); Larcher D., Tarascon J.M., Towards greener and more sustainable batteries for electric energy storage, Nature Chemistry, 7, pp. 19-29, (2015); Lebeau P., Macharis C., Van Mierlo J., Exploring the choice of battery electric vehicles in city logistics: A conjoint-based choice analysis, Transportation Resources Part E: Logistics and Transportation Review, 91, pp. 245-258, (2016); MacQueen J.B., Some methods for classification and analysis of multivariate observations, Proceeding of 5-th Berkeley Symposium on Mathematical Statistics and Probability, pp. 281-297, (1967); Mozafar M.R., Moradi M.H., Hadi Amini M., A simultaneous approach for optimal allocation of renewable energy sources and electric vehicle charging stations in smart grids based on improved GA-PSO algorithm, Sustainable Cities and Society, 32, pp. 627-637, (2017); Nesterova N., Quak H., Balm S., Roche-Cerasi I., Tretvik T., FREVUE 2.1 final report D1.3: State of the art city logistics and EV, European Commission Seventh framework programme, FP7-TRANSPORT-2012-MOVE-1, Demonstration of Urban freight Electric Vehicles for clean city logistics (theme: GC.SST.2012.1-7), (2013); Notter D.A., Gauch M., Widmer R., Wager P., Stamp A., Zah R., Et al., Contribution of Li-ion batteries to the environmental impact of electric vehicles, Environmental Science & Technology, 44, pp. 6550-6556, (2010); Onat N.C., Kucukvar M., Tatari O., Conventional, hybrid, plug-in hybrid or electric vehicles? 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Sci., 39, pp. 61-73, (2012); Sulabh S., Deb S., Singh S.N., Different charging infrastructures along with smart charging strategies for electric vehicles, Sustainable Cities and Society, 60, (2020); Taef T.T., Stutz S., Fink A., Assessing the cost-optimal mileage of medium-duty electric vehicles with a numeric simulation approach, Transportation Research Part D: Transport and Environment, 56, pp. 271-285, (2017); Thompson R.G., Vehicle related innovations for improving the environmental performance of urban freight systems, Green logistics and transportation: A sustainable supply chain perspective, 7, pp. 119-129, (2015); Watrobski J., Malecki K., Kijewska K., Iwan S., Karczmarczyk A., Thompson R.G., Multi-Criteria analysis of electric vans for city logistics, Sustainability, 9, 8, (2017); Wu D., Lin J.C., Oda T., Kort E.A., Space-based quantification of per capita CO2 emissions from cities, Environmental Research Letters, 15, (2020); Zou Y., Zhao J., Ding D., Miao F., Sobhani B., Solving dynamic economic and emission dispatch in power system integrated electric vehicle and wind turbine using multi-objective virus colony search algorithm, Sustainable Cities and Society Volume, 67, (2021)","S. Iwan; Maritime University of Szczecin, Faculty of Transport Economics and Engineering, Szczecin, 11 Pobożnego Str., 70-515, Poland; email: s.iwan@am.szczecin.pl",null,"Elsevier Ltd",{"$nulls":5},2.2106707E7,null,null,null,"English","Sustainable Cities Soc.","Article","Final","All Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85111502889"]
["Pu M.; Chen X.; Zhong Y.","Pu, Mingzhe (56957853300); Chen, Xi (57217077974); Zhong, Yu (57207823747)","56957853300; 57217077974; 57207823747","Overstocked agricultural produce and emergency supply system in the covid-19 pandemic: Responses from china",2021.0,"Foods",10.0,12.0,3027.0,null,null,null,9.0,"10.3390/foods10123027","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121354038&doi=10.3390%2ffoods10123027&partnerID=40&md5=bdf6a0c1af4896c2a1de002cef5c4dfc","Institute of Agricultural Economics and Development, Chinese Academy of Agricultural Sciences, Beijing, 100082, China","Pu M., Institute of Agricultural Economics and Development, Chinese Academy of Agricultural Sciences, Beijing, 100082, China; Chen X., Institute of Agricultural Economics and Development, Chinese Academy of Agricultural Sciences, Beijing, 100082, China; Zhong Y., Institute of Agricultural Economics and Development, Chinese Academy of Agricultural Sciences, Beijing, 100082, China","The spread of COVID-19 has affected not only public health but also agriculture, raising global concerns regarding the food system. As an immediate impact of COVID-19, farmers around the globe have had difficulties with sales, resulting in large amounts of overstocked agricultural products and food loss. This further threatens the livelihood of rural, poor farmers and impacts sustainable production. To provide a better understanding of the overstocking situation after the outbreak of the pandemic, this study depicts the distribution characteristics of overstocked agricultural products in China. After analyzing a nationwide data set collected from 3482 individuals/organizations by the Chinese Agri-products Marketing Association after the outbreak of the pandemic, we found that some of the initial prevention and control measures disrupted sales channels, and in turn, caused the farmers to suffer losses. The impact was more severe in perishable products and their production areas, as well as in poverty-stricken regions. Then, we identified China’s quick and effective actions to match the supply and demand. These findings suggest that emergency responses should coordinate the relationship between emergency actions and the necessary logistics of agricultural production. To prepare for the possibility of such shock in the future, the government should take actions to clear logistics obstacles for necessary transportation, keep enhancing the fundamental infrastructure and effective mechanism of the food supply chain, and actively include innovative techniques to build a more resilient food system. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.","China; COVID-19; E-commerce; Food loss; Food system; Online data; Overstocked agricultural products",{"$nulls":5},"Agricultural Science and Technology Collaborative Innovation Key Program, (CAAS-ZDRW202012); National Natural Science Foundation of China, NSFC, (71903187); Chinese Academy of Agricultural Sciences, CAAS; National Office for Philosophy and Social Sciences, NPOPSS, (21BJY131, 21ZDA056); Agricultural Science and Technology Innovation Program, ASTIP, (ASTIP-IAED-2021-01)","Funding: This research was funded by the National Natural Science Foundation of China (grant number 71903187), the National Social Science Foundation of China (grant number 21ZDA056, 21BJY131), the Agricultural Science and Technology Collaborative Innovation Key Program (grant number CAAS-ZDRW202012) and the Agricultural Science and Technology Innovation Program (grant number ASTIP-IAED-2021-01) from Chinese Academy of Agricultural Sciences.","Torero M., Prepare Food Systems for a Long-Haul Fight against COVID-19, IFPRI Blog, (2020); Global Report on Food Crises; Impact of the COVID-19 Pandemic on Food Security and Food Systems, (2020); Stephens E.C., Martin G., Wijk M., Timsina J., Snow V., Editorial: Impacts of COVID-19 on agricultural and food systems worldwide and on progress to the sustainable development goals, Agric. Syst, 183, (2020); Gralak S., Spajic L., Blom I.M., El Omrani O., Bredhauer J., Uakkas S., Mattijsen J., Ali A.O., Iturregui R.S., Ezzine T., Et al., COVID-19 and the future of food systems at the UNFCCC, Lancet Planet. Health, 4, pp. e309-e311, (2020); Carducci B., Keats E.C., Ruel M., Haddad L., Osendarp S.J.M., Bhutta Z.A., Food systems, diets and nutrition in the wake of COVID-19, Nat. Food, 2, pp. 68-70, (2021); Dixon J.M., Weerahewa J., Hellin J., Rola-Rubzen M.F., Huang J., Kumar S., Das A., Qureshi M.E., Krupnik T.J., Shideed K., Et al., Response and resilience of Asian agrifood systems to COVID-19: An assessment across twenty-five countries and four regional farming and food systems, Agric. Syst, 193, (2021); Davila F., Bourke R., McWilliam A., Crimp S., Robins L., van Wensveen M., Alders R.G., Butler J.R., COVID-19 and food systems in Pacific Island Countries, Papua New Guinea, and Timor-Leste: Opportunities for actions towards the sustainable development goals, Agric. 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Agric. Econ, 103, pp. 1595-1611, (2021); Wang Y., Wang J., Wang X., COVID-19, supply chain disruption and China’s hog market: A dynamic analysis, China Agric. Econ. Rev, 12, pp. 427-443, (2020); Zhang Y., Diao X.S., Chen K.Z., Robinson S., Fan S., Impact of COVID-19 on China’s macroeconomy and agri-food system—An economy-wide multiplier model analysis, China Agric. Econ. Rev, 12, pp. 387-407, (2020); Deaton B.J., Food security and Canada’s agricultural system challenged by COVID-19: One year later, Can. J. Agric. Econ, 69, pp. 161-166, (2021)","Y. Zhong; Institute of Agricultural Economics and Development, Chinese Academy of Agricultural Sciences, Beijing, 100082, China; email: zhongyu@caas.cn",null,"MDPI",{"$nulls":5},2.3048158E7,null,null,null,"English","Foods","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85121354038"]
["Duan R.; Wang S.","Duan, Ruifang (57825898600); Wang, Sujuan (57826409800)","57825898600; 57826409800","Research on Agricultural Products E-Commerce, bio technological ethics and Supply Chain Scheduling Based On Weight Template Matching",2021.0,"Journal of Commercial Biotechnology",26.0,4.0,null,75.0,85.0,10.0,1.0,"10.5912/jcb1058","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135220323&doi=10.5912%2fjcb1058&partnerID=40&md5=db7eeffe573e40cd634c40f225b2063c","Shijiazhuang Information Engineering Vocational College, Shijiazhuang, 050000, China","Duan R., Shijiazhuang Information Engineering Vocational College, Shijiazhuang, 050000, China; Wang S., Shijiazhuang Information Engineering Vocational College, Shijiazhuang, 050000, China","The main reason behind the defaulted decision making model of e-commerce agriculture supply chain is the huge cost of supply chain. The operative method for product designing, maintaining, and distribution is based on the e-commerce techniques, the use of FS algorithm for improving the services of agricultural product is common. The optimization of agricultural problems is made by decision making model. Formulation is done by sequencing the events. Scheduling mode is set up with the help of weighing templates. Plan that targets the distribution route are made on the basis of workable model. Example analysis results: the values of costs of different supply chain mentioned in the paper are 578494.6 yuan and 577983.2 yuan respectively. These values indicate the betterment of the weight matching template model. Although global agriculture has grown more efficient, recent decades have seen an increase in the competition for natural resources due to population expansion, changing food habits, industrial development, urbanization, and climate change. Deforestation, water scarcity, and other environmental problems are all direct results of this unsustainable competitiveness. Bio ethics present a vital role in agricultural products through E-commerce its shows that positive and significant relation between them. Land and water resources have become more competitive as a result of certain initiatives to reduce greenhouse gas (GHG) emissions. As an alternative to using readily accessible and more environmentally friendly energy sources, nations such as these have opted to produce bioenergy, which is very resource-intensive. © 2021 ThinkBiotech LLC. All rights reserved.","agriculture products; bio ethics; logistics services; online retailers; scheduling method; supply chain; weight template matching","Agricultural products; Climate change; Competition; Cost benefit analysis; Decision making; Electronic commerce; Gas emissions; Greenhouse gases; Philosophical aspects; Product design; Scheduling; Template matching; Water resources; Agriculture products; Bio ethic; Decision-making modeling; E- commerces; Logistics services; Online retailer; Optimisations; Scheduling methods; Supply chain scheduling; Weight template matching; agriculture; article; bioenergy; bioethics; climate change; competition; deforestation; electronic commerce; energy resource; ethics; feeding behavior; greenhouse gas emission; industrialization; natural resource; urbanization; water availability; water insecurity; webshop; Supply chains",{"$nulls":6},"Alsaad A., Taamneh A., Sila I., Elrehail H., Understanding the global diffusion of b2b e-commerce (b2b ec): an integrated model, Journal of Information Technology, 4, (2021); Liang B. 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K., Bhuniya S., Sarkar B., Involvement of controllable lead time and variable demand for a smart manufacturing system under a supply chain management, Expert Systems with Applications, 2, (2021); Dobrescu R., Mocanu S., Chenaru O., Nicolae M., Florea G., Versatile edge gateway for improving manufacturing supply chain management via collaborative networks, International Journal of Computer Integrated Manufacturing, 34, 4, pp. 1-15, (2021); Epping J., Laibach N., An underutilized orphan tuber crop-Chinese yam: a review, Planta, 252, 4, (2020); Gkalp E., Gkalp M. O., Oban S., Block chain-based supply chain management: understanding the determinants of adoption in the context of organizations, Information Systems Management, 3, pp. 1-22, (2020); Huang J. J., The latest generation of sezs: consumer-oriented unilateralism in china's e-commerce trade, Journal of International Economic Law, 2, (2021); JIA Qiang-fa, Simulation of Back-End Centralized Redundant Supply Chain Decision Model, Computer Simulation, 37, 12, pp. 345-348, (2020); Jung H. G., K-center algorithm for hierarchical binary template matching, Pattern recognition letters, 125, pp. 584-590, (2019); Kummer S., Herold D. M., Dobrovnik M., Mikl J., Schfer N., A systematic review of blockchain literature in logistics and supply chain management: identifying research questions and future directions, Future Internet, 12, 3, (2020); Li H., Zhang X., Yao S., Zhu B., Fatikow S., An improved template-matching-based pose tracking method for planar Nano positioning stages using enhanced correlation coefficient, IEEE Sensors Journal, 99, (2020); Linnartz M., Leckel A., Data sharing im supply-chain-management: ein assistenzsystem für die bewertung und gestaltung der offenheit und des vertrauensniveaus zwischen supply-chainpartnern, ZWF Zeitschrift fuer Wirtschaftlichen Fabrikbetrieb, 115, 9, pp. 563-566, (2020); Nguyen T., Qin X., Dinh A., Bui F., Low resource complexity r-peak detection based on triangle template matching and moving average filter, Sensors, 19, 18, (2019); Roth S., Nikolla A., Vorgehen zur erstellung einer digitalisierungsroadmap für das supply-chain-management, ZWF Zeitschrift fuer Wirtschaftlichen Fabrikbetrieb, 115, 9, pp. 634-640, (2020); Tiwari S., Chandra A., Praveen T., Toshi S., e-commerce' for India in a developing world: an int'1 trade law perspective, Journal of world trade, 54, 1, pp. 59-79, (2020); Vandana, Singh S. R., Yadav D., Sarkar B., Sarkar M., Impact of energy and carbon emission of a supply chain management with two-level trade-credit policy, Energies, 14, 6, (2021); Liu X, Dou Z., Yang W., Research on influencing factors of cross border ecommerce supply chain resilience based on integrated fuzzy dematel-ism, IEEE Access, 99, (2021); Friedman Y., Building biotechnology in India-Drugs are not the answer, Journal of Commercial Biotechnology, 20, 2, pp. 3-4, (2014)",null,null,"ThinkBiotech LLC",{"$nulls":5},1.4628732E7,null,"JCBOA",null,"English","J. Commer. Biotechnol.","Article","Final",null,"Scopus","2-s2.0-85135220323"]
["Fang D.; Zhang X.","Fang, Da (57265281600); Zhang, Xiaoke (57226822232)","57265281600; 57226822232","The protective effect of digital financial inclusion on agricultural supply chain during the covid-19 pandemic: Evidence from china",2021.0,"Journal of Theoretical and Applied Electronic Commerce Research",16.0,7.0,null,3202.0,3217.0,15.0,18.0,"10.3390/JTAER16070174","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85120314864&doi=10.3390%2fJTAER16070174&partnerID=40&md5=5041e489212f4f608403989525f6042f","School of Economics, Peking University, Beijing, 100871, China","Fang D., School of Economics, Peking University, Beijing, 100871, China; Zhang X., School of Economics, Peking University, Beijing, 100871, China","Financial inclusion plays a positive role in protecting agriculture during or after disaster. This paper focuses on the protective effect of digital financial inclusion on the agricultural supply chain and analyzes three mechanisms of the protective effect: financial widening, financial deepening, and financial services digitization. Based on the Gravity Equation, we conduct an empirical study using agricultural logistics and digital financial inclusion data from China. The regression results indicate that a 1% increase in the digital financial inclusion, measured by the Peking University Digital Inclusion Index, increases agricultural trade during the COVID-19 pandemic by approximately 1.6%. Furthermore, heterogeneous protective effects exist between regions in China. Digital financial inclusion is more effective in the Eastern regions in protecting the ASC than in other regions. This paper enriches the understanding of financial inclusion in helping agriculture supply chain recovery. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.","Agricultural trade; COVID-19; Digital financial inclusion; Rural e-commerce",{"$nulls":7},"Novel Coronavirus (COVID-19), (2020); Nayal K., Raut R.D., Queiroz M.M., Yadav V.S., Narkhede B.E., Are artificial intelligence and machine learning suitable to tackle the COVID-19 impacts? An agriculture supply chain perspective, Int. J. Logist. Manag, (2021); Sharma R., Shishodia A., Kamble S., Gunasekaran A., Belhadi A., Agriculture supply chain risks and COVID-19: Mitigation strategies and implications for the practitioners, Int. J. Logist. Res. Appl, (2020); Altieri M.A., Clara I.N., Agroecology and the reconstruction of a post-COVID-19 agriculture, J. Peasant Stud, 47, pp. 881-898, (2020); William A.K., The COVID-19 pandemic and agriculture: Short-and long-run implications for international trade relations, Can. J. Agric. Econ.-Rev. Can. 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J, 9, pp. 253-271, (2016); Guo F., Wang J.Y., Wang F., Kong S.T., Zhang X., Cheng Z.Y., Measuring China’s Digital Financial Inclusion: Index Compilation and Spatial Characteristics, China Econ. Q, 19, pp. 1401-1418, (2020); Liu Y., Liu C., Zhou M., Does digital inclusive finance promote agricultural production for rural households in China? Research based on the Chinese family database (CFD), China Agric. Econ. Rev, 13, pp. 475-494, (2021)","X. Zhang; School of Economics, Peking University, Beijing, 100871, China; email: pkufd95@pku.edu.cn",null,"MDPI",{"$nulls":5},7181876.0,null,null,null,"English","J. Theor. Appl. Electron. Commer. Res.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85120314864"]
["Ren J.; Li H.; Zhang M.; Wu C.","Ren, Jiajia (57226016099); Li, Hongxin (36655964500); Zhang, Mengmeng (57218950765); Wu, Cong (57225991418)","57226016099; 36655964500; 57218950765; 57225991418","Massive-scale graph mining for e-commerce cold chain analysis and optimization",2021.0,"Future Generation Computer Systems",125.0,null,null,526.0,531.0,5.0,12.0,"10.1016/j.future.2021.06.057","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85110220108&doi=10.1016%2fj.future.2021.06.057&partnerID=40&md5=184be41081699dcd9fc8c616a83fbae7","School of Management Science and Engineering, Dongbei University of Finance and Economics, Liaoning, 116023, Dalian, China; School of Logistics and E-commerce, Henan University of Animal Husbandry and Economy, Zhengzhou, Hennan, 450044, China; College of Business Administration, University of the Cordilleras, Baguio City, 2600, Philippines; Institute for Optimization and Decision Analytics, Liaoning Technical University, FuXin, Liaoning, 123000, China","Ren J., School of Management Science and Engineering, Dongbei University of Finance and Economics, Liaoning, 116023, Dalian, China, School of Logistics and E-commerce, Henan University of Animal Husbandry and Economy, Zhengzhou, Hennan, 450044, China; Li H., School of Management Science and Engineering, Dongbei University of Finance and Economics, Liaoning, 116023, Dalian, China; Zhang M., School of Logistics and E-commerce, Henan University of Animal Husbandry and Economy, Zhengzhou, Hennan, 450044, China, College of Business Administration, University of the Cordilleras, Baguio City, 2600, Philippines; Wu C., School of Management Science and Engineering, Dongbei University of Finance and Economics, Liaoning, 116023, Dalian, China, Institute for Optimization and Decision Analytics, Liaoning Technical University, FuXin, Liaoning, 123000, China","Presently, the development of fresh agricultural products e-commerce is constrained by the cold chain logistics. There are shortcomings such as the incomplete comprehensive supporting system, lacking of logistics technology and low effective infrastructure in cold chain logistics. Scientific and optimal selection of distribution mode is crucial to the operation of fresh e-commerce and urban circulation efficiency. Owing to the problem that urban logistics distribution limits the cold chain logistics of fresh agricultural products, we propose the distribution mode and synergistic mechanism of cold chain logistics of urban fresh agricultural products. By leveraging the theory of logistics and supply chain management, we explore the high logistics cost of fresh e-commerce, inconsistent cold chain logistics standards, and poor consumer viscosity. We introduce the self-established logistics, third-party logistics, self-established logistics, third-party logistics and other three main logistics distribution modes. Due to the impact of cold chain logistics distribution on the existing urban transportation, an integrated mode of self-established logistics/third-party logistics + joint distribution is designed. In order to promote the collaborative development of cold chain logistics distribution and fresh electricity, it is significant to establish three collaborative mechanisms from the perspective of government, enterprises and third-party logistics According to the green logistics, the carbon tax cost and cargo damage cost in the process of cold chain logistics distribution are discovered by a graphical model. The graphical model is constructed under the optimization objective of minimizing each cost. In order to avoid the problem that basic artificial fish swarm algorithm is prone to local optimum, a global artificial fish swarm algorithm is designed and solved. Extensive experimental results have shown the usefulness and effectiveness of our proposed method. © 2021","Cold chain; E-commerce; Fish swarm; Graph mining; Massive-scale","Agricultural products; Costs; Data mining; Graphic methods; Supply chain management; Urban transportation; Cold chain; Cold chain logistics; Distribution modes; E- commerces; Fish swarm; Fresh agricultural products; Graph mining; Logistic distributions; Massive-scale; Third-party logistics; Electronic commerce",{"$nulls":4},"Henan Province's key R&D and promotion projects-key scientific and technological projects; Henan Province’s key R&D and promotion projects-key scientific and technological projects, China, (192102310265); Key discipline construction project of ?; Key discipline construction project of “Enterprise Management, (2019-202); Research and innovation team construction project of ?; Research and innovation team construction project of “Fresh e-commerce channel innovation research team, (2018KYTD02); channel innovation research team?","Funding text 1: The study was supported by Henan Province’s key R&D and promotion projects-key scientific and technological projects, China (No: 192102310265 ), Research and innovation team construction project of “Fresh e-commerce channel innovation research team” in Henan university of animal husbandry and economy, China (No: 2018KYTD02 ), and Key discipline construction project of “Enterprise Management” in Henan university of animal husbandry and economy, China (No: 2019-202 ).; Funding text 2: The study was supported by Henan Province's key R&D and promotion projects-key scientific and technological projects, China (No:192102310265), Research and innovation team construction project of ?Fresh e-commerce channel innovation research team? in Henan university of animal husbandry and economy, China (No: 2018KYTD02), and Key discipline construction project of ?Enterprise Management? in Henan university of animal husbandry and economy, China (No: 2019-202).","Dalal N., Triggs B., Histograms of oriented gradients for human detection, CVPR, (2005); Hong P., Huang T., Spatial pattern discovery by learning a probabilistic parametric model from multiple attributed relational graphs, Discrete Appl. 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Rev., pp. 1-31, (2012); Jiang H., Ngo C.-W., Image mining using inexact maximal common subgraph of multiple args, (2003); Kim G., Faloutsos C., Hebert M., Unsupervised modeling of object categories using link analysis techniques, pp. 1-8, (2008); Kolmogorov V., Convergent tree-reweighted message passing for energy minimization, IEEE PAMI, 28, 10, pp. 1568-1583, (2006); Leordeanu M., Hebert M., A spectral technique for correspondence problems using pairwise constraints, ICCV, (2005); Leordeanu M., Hebert M., Smoothing-based optimization, CVPR, (2008); Leordeanu M., Hebert M., Unsupervised learning for graph matching, CVPR, (2009); Leordeanu M., Hebert M., Sukthankar R., Beyond local appearance: category recognition from pairwise interactions of simple features, CVPR, (2007); Liu H., Yan S., Common visual pattern discovery via spatially coherent correspondences, CVPR, (2010); Parikh D., Zitnick C., Chen T., Unsupervised learning of hierarchical spatial structures in images, CVPR, (2009); Poonthalir G., Nadarajan R., A fuel efficient greenvehicle routing problem with varying speed constraint (f-GVRP), Expert Syst. Appl., 100, 1, pp. 131-144, (2018); Ottmar R.D., Wildland fire emissions, carbon and climate:modeling fuel consumption, Forest Ecol. Manag., 317, 2, pp. 41-50, (2014); Wulan H., Tao Z., Researchon VRPSPDTW based on improved global artificial fish swarm algorithm, Comput. Eng. Appl., 52, 21, pp. 21-29, (2016); Ruyun Z., Qing L., CO2 emission minimizing for thetime-dependent VRP in urban area, Ind. Eng. Manag., 20, 4, pp. 29-34, (2015)","J. Ren; School of Management Science and Engineering, Dongbei University of Finance and Economics, Liaoning, 116023, China; email: renjiajia@hnuahe.edu.cn",null,"Elsevier B.V.",{"$nulls":5},"0167739X",null,"FGCSE",null,"English","Future Gener Comput Syst","Article","Final",null,"Scopus","2-s2.0-85110220108"]
["Shih D.-H.; Huang F.-C.; Chieh C.-Y.; Shih M.-H.; Wu T.-W.","Shih, Dong-Her (9335419500); Huang, Feng-Chuan (57194947248); Chieh, Chia-Yi (57247912700); Shih, Ming-Hung (36747047700); Wu, Ting-Wei (57202985540)","9335419500; 57194947248; 57247912700; 36747047700; 57202985540","Preventing return fraud in reverse logistics—A case study of espres solution by ethereum",2021.0,"Journal of Theoretical and Applied Electronic Commerce Research",16.0,6.0,null,2170.0,2191.0,21.0,12.0,"10.3390/jtaer16060121","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85114352722&doi=10.3390%2fjtaer16060121&partnerID=40&md5=f64609e36ab4a25d360c678af7a69df4","Department of Information Management, National Yunlin University of Science and Technology, Douliu, Yunlin, 64002, Taiwan; Department of Electrical and Computer Engineering, Iowa State University, 2520 Osborn Drive, Ames, 50011, IA, United States","Shih D.-H., Department of Information Management, National Yunlin University of Science and Technology, Douliu, Yunlin, 64002, Taiwan; Huang F.-C., Department of Information Management, National Yunlin University of Science and Technology, Douliu, Yunlin, 64002, Taiwan; Chieh C.-Y., Department of Information Management, National Yunlin University of Science and Technology, Douliu, Yunlin, 64002, Taiwan; Shih M.-H., Department of Electrical and Computer Engineering, Iowa State University, 2520 Osborn Drive, Ames, 50011, IA, United States; Wu T.-W., Department of Information Management, National Yunlin University of Science and Technology, Douliu, Yunlin, 64002, Taiwan","With the rapid development of e-commerce services, online retail has evolved from multi-channel to omni-channel in order to provide customers with more services. However, reverse logistics services (returns and exchanges) have become the target of many fraudulent activities, causing a lot of economic losses for many online retail companies. The current challenge of the traditional countermeasure is it requires a lot of manpower and training resources. In this study, we propose ESPRES, a system that adopts blockchain technology to prevent fraudulent behavior in the process of returns and exchanges with the smart contract and multi-attribute decision-support method to help consumers choose a suitable payment program. A practical implication of this study is that by adopting blockchain technology, a great amount of manpower used on determining whether each return or exchange is fraudulent can be reduced since merchants can check the product ownership. In addition, due to the fact that the footprint of goods cannot be forged, it can also prevent counterfeit or parallel imports of goods. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.","Blockchain; E-commerce; Ethereum; Omnichannel logistics; Return fraud prevention; Reverse logistics",{"$nulls":5},"Ministry of Science and Technology, Taiwan, MOST, (MOST 109-2410-H-224-022, MOST 110-2410-H-224-010)","Funding: This work was partially supported by the Taiwan Ministry of Science and Technology grant MOST 109-2410-H-224-022 and MOST 110-2410-H-224-010. The funder has no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.","Verhoef P.C., Kannan P.K., Inman J.J., From multi-channel retailing to omni-channel retailing: Introduction to the special issue on multi-channel retailing, J. 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Analysis of Functional Needs, Sustainability, 11, (2019)","D.-H. Shih; Department of Information Management, National Yunlin University of Science and Technology, Douliu, Yunlin, 64002, Taiwan; email: shihdh@yuntech.edu.tw",null,"MDPI",{"$nulls":5},7181876.0,null,null,null,"English","J. Theor. Appl. Electron. Commer. Res.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85114352722"]
["Rasmi S.A.B.; Wang Y.; Charkhgard H.","Rasmi, Seyyed Amir Babak (57195546183); Wang, Yuan (57079310600); Charkhgard, Hadi (54392796500)","57195546183; 57079310600; 54392796500","Wave order picking under the mixed-shelves storage strategy: A solution method and advantages",2022.0,"Computers and Operations Research",137.0,null,105556.0,null,null,null,13.0,"10.1016/j.cor.2021.105556","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85115011639&doi=10.1016%2fj.cor.2021.105556&partnerID=40&md5=2cd34d62619330bc0acd71087b753bb5","School of Electrical Engineering, Computing and Mathematical Sciences, Curtin University, Perth, Australia; School of Business, Singapore University of Social Sciences, Singapore, 599494, Singapore; Department of Industrial & Management Systems Engineering, University of South Florida, Tampa, 33620, FL, United States","Rasmi S.A.B., School of Electrical Engineering, Computing and Mathematical Sciences, Curtin University, Perth, Australia; Wang Y., School of Business, Singapore University of Social Sciences, Singapore, 599494, Singapore; Charkhgard H., Department of Industrial & Management Systems Engineering, University of South Florida, Tampa, 33620, FL, United States","Order picking (OP) is a time and cost consuming operation in many warehouses. The optimization of order picking planning is crucial to speed up customers’ delivery process and reduce warehouse expenses. A commonly adopted strategy is called mixed-shelves storage strategy (MSSS) that is highly recommended for e-commerce warehouses. Applying this, the units of the same stock keeping unit (SKU) are scattered to various storage locations which provides more improvement room for OP. However, consolidated methods have not been sufficiently discussed when OP is under the MSSS. In this paper, we study the problem of wave picking systems to jointly address order batching, batch assignment, and picker routing (BAR) in a MSSS-based warehouse. We propose the decomposition of OP into BAR subproblems (DOPBAR) for solving such a wave OP problem. We examine our approach on a large set of instances, validate the effectiveness of our method, and point out the advantages of the MSSS in OP. Moreover, we analyze the trade-offs between two conflicting objectives that practitioners aim to optimize: customer service level (makespan) and workforce level (labor cost). Finally, a few insightful managerial recommendations are proposed that support the decision making in choosing a storage location assignment strategy. © 2021 Elsevier Ltd","Bi-objective MILP; Makespan minimization; Mixed-shelves storage strategy; Multiple pickers’ routing; Order batching; Order picking","Decision making; Economic and social effects; Wages; Conflicting objectives; Customer service levels; Delivery process; Order batching; Solution methods; Stock keeping unit; Storage location; Storage location assignments; Warehouses",{"$nulls":4},"Agency for Science, Technology and Research, A*STAR, (A1895a0033)","The authors have been supported by Singapore A*STAR IAF-PP fund (Grant No. A1895a0033 ) under the project “Digital Twin for Next Generation Warehouse”. 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Rasmi; School of Electrical Engineering, Computing and Mathematical Sciences, Curtin University, Perth, Australia; email: babak.rasmi@curtin.edu.au",null,"Elsevier Ltd",{"$nulls":5},3050548.0,null,"CMORA",null,"English","Comp. Oper. Res.","Article","Final",null,"Scopus","2-s2.0-85115011639"]
["Siragusa C.; Tumino A.; Mangiaracina R.; Perego A.","Siragusa, Chiara (57204969259); Tumino, Angela (25929706400); Mangiaracina, Riccardo (35325033800); Perego, Alessandro (7004535933)","57204969259; 25929706400; 35325033800; 7004535933","Electric vehicles performing last-mile delivery in B2C e-commerce: An economic and environmental assessment",2022.0,"International Journal of Sustainable Transportation",16.0,1.0,null,22.0,33.0,11.0,37.0,"10.1080/15568318.2020.1847367","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85096319408&doi=10.1080%2f15568318.2020.1847367&partnerID=40&md5=6a47274fe3ce038d85f4a1c31f45d9ff","Department of Management, Economics and Industrial Engineering, Politecnico di Milano, Milano, Italy","Siragusa C., Department of Management, Economics and Industrial Engineering, Politecnico di Milano, Milano, Italy; Tumino A., Department of Management, Economics and Industrial Engineering, Politecnico di Milano, Milano, Italy; Mangiaracina R., Department of Management, Economics and Industrial Engineering, Politecnico di Milano, Milano, Italy; Perego A., Department of Management, Economics and Industrial Engineering, Politecnico di Milano, Milano, Italy","The proliferation of e-commerce in the recent years has been recognized to have a huge impact on transportation owing to the increasing need for last-mile deliveries in urban areas. Further, it is claimed to be responsible for the rising number of vans moving in cities, considerably impacting environmental sustainability. In this context, electric vehicles (EVs) could substitute internal combustion engine vehicles (ICEVs) to mitigate their harmful impact on the environment. This work aims to provide a comparison between the EVs and the ICEVs used to perform last-mile deliveries in business-to-consumers (B2C) e-commerce, considering both economic and environmental perspectives. The life cycle assessment method is adopted for the evaluation of environmental impact. However, economic assessment is based on the total cost of ownership analysis, which allows the comparison between the two types of vehicles throughout the ownership period. The analysis was conducted considering an Italian city (Milan). The use of EVs proved to be economically beneficial when an 8-year timeframe was considered. Even if the initial investment for EVs is high, owing to a purchasing price that is nearly double when compared to ICEVs, the lower operating expenditure makes EVs a competitive option. Considering the environmental perspective, EVs turned out to be the best option in all the scenarios assumed. In particular, EVs lead to a decrease in greenhouse gas (GHG) emissions by 17% (in the 20 km/day case) to by 54% (in the 120 km/day case), or even more if a higher daily mileage is considered. © 2020 Taylor & Francis Group, LLC.","B2C e-commerce; electric vehicle; environmental sustainability; last-mile delivery; life cycle assessment; total cost of ownership","Italy; Lombardy; Milan [Milano]; Milano [Lombardy]; Electronic commerce; Environmental impact; Gas emissions; Greenhouse gases; Life cycle; Sustainable development; Trucks; Urban transportation; Economic and environmental assessments; Economic assessments; Electric Vehicles (EVs); Environmental sustainability; Impact on the environment; Internal combustion engine vehicles; Life Cycle Assessment (LCA); Total-cost-of-ownership analysis; car ownership; comparative study; economic analysis; electric vehicle; electronic commerce; environmental assessment; environmental economics; life cycle analysis; sustainability; travel behavior; urban transport; Costs",{"$nulls":6},"Al-Alawi B.M., Bradley T.H., Total cost of ownership, payback, and consumer preference modeling of plug-in hybrid electric vehicles, Applied Energy, 103, pp. 488-506, (2013); Allen J., Browne M., Holguin-Veras J., Sustainability strategies for city logistics, Green Logistics: Improving the Environmental Sustainability of Logistics, (2010); (2020); (2016); Breetz H.L., Salon D., Do electric vehicles need subsidies? 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A total cost of ownership analysis, European Journal of Transport & Infrastructure Research, 15, 4, (2015); Letmathe P., Suares M., A consumer-oriented total cost of ownership model for different vehicle types in Germany, Transportation Research Part D: Transport and Environment, 57, pp. 314-335, (2017); Levay P.Z., Drossinos Y., Thiel C., The effect of fiscal incentives on market penetration of electric vehicles: A pairwise comparison of total cost of ownership, Energy Policy, 105, pp. 524-533, (2017); Lieb K.J., Lieb R.C., Environmental sustainability in the third-party logistics (3PL) industry, International Journal of Physical Distribution & Logistics Management, 40, 7, pp. 524-533, (2010); Lieb R., The North American third-party logistics industry in 2007: the provider CEO perspective, Transportation Journal, 47, 2, pp. 39-53, (2008); Lin C.Y., Ho Y.H., An empirical study on logistics service providers’ intention to adopt green innovations, Journal of Technology Management & Innovation, 3, 1, pp. 17-26, (2008); Mearig T., Coffee N., Morgan M., Life Cycle Cost Analysis Handbook, (1999); Mills G., MacGill I., Assessing greenhouse gas emissions from electric vehicle operation in Australia using temporal vehicle charging and electricity emission characteristics, International Journal of Sustainable Transportation, 11, 1, pp. 20-30, (2017); Morrison G., Stevens J., Joseck F., Relative economic competitiveness of light-duty battery electric and fuel cell electric vehicles, Transportation Research Part C: Emerging Technologies, 87, pp. 183-196, (2018); Palmer K., Tate J.E., Wadud Z., Nellthorp J., Total cost of ownership and market share for hybrid and electric vehicles in the UK, Applied Energy, 209, pp. 108-119, (2018); Pieralice E., & Trepiedi L., (2016); Quak H., Urban freight transport: the challenge of sustainability, City Distribution and Urban Freight Transport: Multiple Perspectives, (2011); Quak H., Nesterova N., van Rooijen T., Dong Y., Zero emission city logistics: Current practices in freight electromobility and feasibility in the near future, Transportation Research Procedia, 14, pp. 1506-1515, (2016); Rafique S., Town G.E., Potential for electric vehicle adoption in Australia, International Journal of Sustainable Transportation, 13, 4, pp. 245-254, (2019); Schoder D., Ding F., Campos J.K., The impact of e-commerce development on urban logistics sustainability, Open Journal of Social Sciences, 4, 3, pp. 1-6, (2016); Thiel C., Perujo A., Mercier A., Cost and CO2 aspects of future vehicle options in Europe under new energy policy scenarios, Energy Policy, 38, 11, pp. 7142-7151, (2010); Topal O., Nakir I., Total cost of ownership based economic analysis of diesel, CNG and electric bus concepts for the public transport in Istanbul City, Energies, 11, 9, (2018); Van Mierlo J., Maggetto G., Fuel cell or battery: Electric cars are the future, Fuel Cells, 7, 2, pp. 165-173, (2007); Werber M., Fischer M., Schwartz P.V., Batteries: Lower cost than gasoline?, Energy Policy, 37, 7, pp. 2465-2468, (2009); Wu G., Inderbitzin A., Bening C., Total cost of ownership of electric vehicles compared to conventional vehicles: A probabilistic analysis and projection across market segments, Energy Policy, 80, pp. 196-214, (2015); Wu Z., Wang M., Zheng J., Sun X., Zhao M., Wang X., Life cycle greenhouse gas emission reduction potential of battery electric vehicle, Journal of Cleaner Production, 190, pp. 462-470, (2018); Yu A., Wei Y., Chen W., Peng N., Peng L., Life cycle environmental impacts and carbon emissions: A case study of electric and gasoline vehicles in China, Transportation Research Part D: Transport and Environment, 65, pp. 409-420, (2018); Zachariadis T., On the baseline evolution of automobile fuel economy in Europe, Energy Policy, 34, 14, pp. 1773-1785, (2006); Zhang S., Wu Y., Liu H., Huang R., Yang L., Li Z., Fu L., Hao J., Real-world fuel consumption and CO2 emissions of urban public buses in Beijing, Applied Energy, 113, pp. 1645-1655, (2014)","C. Siragusa; Dipartimento di Ingegneria Gestionale, Politecnico di Milano, Milano, Via Lambruschini, 4B 20156, Italy; email: chiara.siragusa@polimi.it",null,"Taylor and Francis Ltd.",{"$nulls":5},1.5568318E7,null,null,null,"English","Intl. J. Sustainable Transp.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85096319408"]
["Issaoui Y.; Khiat A.; Haricha K.; Bahnasse A.; Ouajji H.","Issaoui, Yassine (57214777513); Khiat, Azeddine (57193027037); Haricha, Karim (57221704694); Bahnasse, Ayoub (57189848864); Ouajji, Hassan (57188879248)","57214777513; 57193027037; 57221704694; 57189848864; 57188879248","An Advanced System to Enhance and Optimize Delivery Operations in a Smart Logistics Environment",2022.0,"IEEE Access",10.0,null,null,6175.0,6193.0,18.0,10.0,"10.1109/ACCESS.2022.3141311","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85122859907&doi=10.1109%2fACCESS.2022.3141311&partnerID=40&md5=638f07e4be01c2b15d093457eaa235dd","2IACS Laboratory, ENSET of Mohammedia, University Hassan II of Casablanca, Casablanca, 20670, Morocco; ISPS2I Laboratory, Ensam Casablanca, University Hassan II of Casablanca, Casablanca, 20670, Morocco","Issaoui Y., 2IACS Laboratory, ENSET of Mohammedia, University Hassan II of Casablanca, Casablanca, 20670, Morocco; Khiat A., 2IACS Laboratory, ENSET of Mohammedia, University Hassan II of Casablanca, Casablanca, 20670, Morocco; Haricha K., 2IACS Laboratory, ENSET of Mohammedia, University Hassan II of Casablanca, Casablanca, 20670, Morocco; Bahnasse A., ISPS2I Laboratory, Ensam Casablanca, University Hassan II of Casablanca, Casablanca, 20670, Morocco; Ouajji H., 2IACS Laboratory, ENSET of Mohammedia, University Hassan II of Casablanca, Casablanca, 20670, Morocco","Optimization of order dispatch operations and delivery time prediction is a major concern in supply chains, mainly for e-commerce, which requires the implementation of advanced solutions to reduce delivery time, minimize costs and maximize customer satisfaction. In practice, they fail to warrant scalable and sustainable solutions as the numbers of orders become larger. For that, proper prediction and optimization for delivery operations are required for optimal logistics management. This paper presents an advanced logistics service, which warrants dynamic coordination among all the actors in the smart logistics environment. The proposed advanced shipping system consists of two main parts: the delivery prediction model to compute the expected arrival time, and a hybrid optimization model to tackle path issues. We demonstrate that the advanced system consistently outperforms conventional standard dispatching methods, which means that the proposed approach effectively contributes to optimizing the distribution chain and reducing costs.  © 2013 IEEE.","Deep learning; Intelligent systems; LSTM; Multi-objective optimization; Smart logistics","Cost reduction; Customer satisfaction; Deep learning; Electronic commerce; Forecasting; Logistics; Multiobjective optimization; Supply chains; Advanced systems; Deep learning; Delivery time; Dispatching; LSTM; Multi-objectives optimization; Operation time; Optimisations; Smart logistic; Vehicle's dynamics; Intelligent systems",{"$nulls":6},"Lipsman A., Global ecommerce 2019, EMarketer, Etats-Unis, 1, pp. 1-5, (2019); Orendorff A., Global Ecommerce Statistics and Trends to Launch Your Bus. beyond Borders, (2019); Kharpal A., Alibaba Breaks Singles Day Record with More Than $38 Billion in Sales, (2019); The Marketplace of the European Innovation Partnership on Smart Cities and Communities, (2019); Summary G., General Assembly-Towards a Joint Investment Programme for Smart Cities, (2017); Urban Agenda, (2018); Hofmann E., Rtisch M., Industry 4.0 and the current status as well as future prospects on logistics, Comput. 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Soft Comput., 24, 2, pp. 367-376, (2018); Zhang F., Lei T., Li J., Cai X., Shao X., Chang J., Tian F., Realtime calibration and registration method for indoor scene with joint depth and color camera, Int. J. Pattern Recognit. Artif. Intell., 32, 7, (2018); Zhou Y., Li T., Shi J., Qian Z., A CEEMDAN and XGBOOST-based approach to forecast crude oil prices, Complexity, 2019, pp. 1-15, (2019); Soesanti I., Syahputra R., Batik production process optimization using particle swarm optimization method, J. Theor. Appl. Inf. Technol., 86, 2, pp. 271-278, (2016); Dorigo M., Gambardella L.M., Ant colonies for the travelling salesman problem, Biosystems, 43, 2, pp. 73-81, (1997)","Y. Issaoui; 2IACS Laboratory, ENSET of Mohammedia, University Hassan II of Casablanca, Casablanca, 20670, Morocco; email: issaouiyassine818@gmail.com",null,"Institute of Electrical and Electronics Engineers Inc.",{"$nulls":5},2.1693536E7,null,null,null,"English","IEEE Access","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85122859907"]
["Ariansyah K.; Sirait E.R.E.; Nugroho B.A.; Suryanegara M.","Ariansyah, Kasmad (57202162180); Sirait, Emyana Ruth Eritha (57193699692); Nugroho, Badar Agung (57192412470); Suryanegara, Muhammad (57205093129)","57202162180; 57193699692; 57192412470; 57205093129","Drivers of and barriers to e-commerce adoption in Indonesia: Individuals’ perspectives and the implications",2021.0,"Telecommunications Policy",45.0,8.0,102219.0,null,null,null,24.0,"10.1016/j.telpol.2021.102219","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85110371032&doi=10.1016%2fj.telpol.2021.102219&partnerID=40&md5=077be60283656f1b46a1d87031fdd823","Centre for Research and Development on Resources, Equipment, and Operations of Posts and Informatics, Ministry of Communications and Informatics, Medan Merdeka Barat 9, Jakarta, 10110, Indonesia; Center of Research and Development of Informatic Application, Information and Public Communication, Ministry of Communications and Informatics, Medan Merdeka Barat 9, Jakarta, 10110, Indonesia; Graduate Program in Telecommunications Management, Department of Electrical Engineering, Universitas Indonesia, Depok, Indonesia","Ariansyah K., Centre for Research and Development on Resources, Equipment, and Operations of Posts and Informatics, Ministry of Communications and Informatics, Medan Merdeka Barat 9, Jakarta, 10110, Indonesia; Sirait E.R.E., Center of Research and Development of Informatic Application, Information and Public Communication, Ministry of Communications and Informatics, Medan Merdeka Barat 9, Jakarta, 10110, Indonesia; Nugroho B.A., Center of Research and Development of Informatic Application, Information and Public Communication, Ministry of Communications and Informatics, Medan Merdeka Barat 9, Jakarta, 10110, Indonesia; Suryanegara M., Graduate Program in Telecommunications Management, Department of Electrical Engineering, Universitas Indonesia, Depok, Indonesia","This study aims to investigate the underlying factors affecting Indonesian individuals' decision to make online purchases. Primary data were collected through a nationwide survey in 2019 covering all 34 Indonesian provinces. Secondary data regarding Indonesian villages' potential (PODES) are utilized to provide information about the availability of infrastructure at the village level. The standard utility/net gain maximization framework is adopted, and a binary logistic regression model is employed. A total of 8854 useable samples are analyzed. The results suggest that the probability of using e-commerce to make online purchases increases if an individual is male, young, married, highly educated, and an entrepreneur, as well as has access to the Internet, can easily find logistic and financial services, has sufficient digital skills, and has not been exposed to harmful content. These results produce several findings: the relative advantages of e-commerce over traditional commerce and the compatibility of e-commerce with individuals' needs and values can drive its adoption; digital skills and the ubiquitous related infrastructures are an essential requirements to expand e-commerce diffusion; exposure to harmful content is empirically discovered to be a barrier to e-commerce adoption. These findings lead the authors to provide recommendations to promote more inclusive e-commerce adoption and optimize the e-commerce sector's contribution to the national economy. © 2021 Elsevier Ltd","Developing countries; e-commerce adoption; Indonesian individuals; Online buyer; Online shopping","Digital storage; Logistic regression; Rural areas; Binary logistic regression models; Digital skills; E-commerce adoption; Financial service; National economy; Secondary datum; Traditional commerce; Underlying factors; Electronic commerce",{"$nulls":4},"Agency for Research and Human Resources Development on Communications and Informatics , Ministry of Communications and Informatics; Agency for Research and Human Resources Development on Communications and Informatics, Ministry of Communications and Informatics","Funding text 1: This work was financially supported by the Agency for Research and Human Resources Development on Communications and Informatics, Ministry of Communications and Informatics, the Republic of Indonesia. The authors would like to thank the survey team for their assitance with data collection.; Funding text 2: This work was financially supported by the Agency for Research and Human Resources Development on Communications and Informatics , Ministry of Communications and Informatics , the Republic of Indonesia. The authors would like to thank the survey team for their assitance with data collection.","Peta E-commerce Indonesia. 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DataReportal – global digital insights, (2020); Williams R., Using the margins command to estimate and interpret adjusted predictions and marginal effects, The Stata Journal: Promoting Communications on Statistics and Stata, 12, 2, pp. 308-331, (2012); The promise of education in Indonesia, (2019); GDP (current US$), (2020); GDP growth (annual %)—Indonesia, (2020)","K. Ariansyah; Centre for Research and Development on Resources, Equipment, and Operations of Posts and Informatics, Ministry of Communications and Informatics, Jakarta, Medan Merdeka Barat 9, 10110, Indonesia; email: kasmad.ariansyah@kominfo.go.id",null,"Elsevier Ltd",{"$nulls":5},3085961.0,null,"TEPOD",null,"English","Telecommun Policy","Article","Final",null,"Scopus","2-s2.0-85110371032"]
["Xu Z.; Ge Z.; Wang X.; Skare M.","Xu, Zeshui (55502698400); Ge, Zijing (57221283052); Wang, Xinxin (57204520948); Skare, Marinko (6506322858)","55502698400; 57221283052; 57204520948; 6506322858","Bibliometric analysis of technology adoption literature published from 1997 to 2020",2021.0,"Technological Forecasting and Social Change",170.0,null,120896.0,null,null,null,43.0,"10.1016/j.techfore.2021.120896","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85107129565&doi=10.1016%2fj.techfore.2021.120896&partnerID=40&md5=9db6b08cb4d33107a69bbdc2b0c3849f","Business School, Sichuan University, Chengdu, 610064, China; Juraj Dobrila Univ Pula, Fac Econ & Tourism Dr Mijo Mirkovic, Preradoviceva 1-1, Pula, 52100, Croatia","Xu Z., Business School, Sichuan University, Chengdu, 610064, China; Ge Z., Business School, Sichuan University, Chengdu, 610064, China; Wang X., Business School, Sichuan University, Chengdu, 610064, China; Skare M., Juraj Dobrila Univ Pula, Fac Econ & Tourism Dr Mijo Mirkovic, Preradoviceva 1-1, Pula, 52100, Croatia","With the rapid development of emerging technologies, research on technology adoption is valuable for improving the reception efficiency of new technologies. This paper uses bibliometric analysis methods and visualization software to explore the research stages, the hot issues, the limitations of the research and the future fronts. A total of 11,706 documents were collected as the original data using the retrieval formulas. Sorted by the numbers of citations, the top 10% of the documents are extracted as the top-cited documents. First, combining software and bibliometric analysis, we obtain the annual development trends and identify the productive countries/regions, the influential institutions and the high-yielding authors. In addition, we overview the representative authors and their works in the development of technology adoption. Then, we conduct keyword analysis and burstiness analysis to identify the academic hotspots, research fronts and limitations in this field. The results show that increasingly more researches have shifted from theories to applications. Technology adoption has multiple applications in the fields of online shopping, mobile learning, mobile banking, e-learning and health care delivery. Finally, we draw conclusions on the bibliometric findings and forecast the future research trends of technology adoption. In the future, more researches will focus on the impacts of age, gender, culture, and the environment on technology adoption. © 2021","Bibliometric analysis; Novel technology; Technology adoption; Top-cited papers","academic research; computer simulation; efficiency measurement; innovation; research and development; software; technology adoption; visualization",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (71771155, 72071135); Ministry of Education of the People's Republic of China, MOE; Fundamental Research Funds for the Central Universities, (SXYPY202146, YJ202063)","Funding text 1: The work was supported by the National Natural Science Foundation of China (Nos. 72071135 and 71771155 ) and the Fundamental Research Funds for the Central Universities ( YJ202063 and SXYPY202146 ). ; Funding text 2: Zeshui Xu received the Ph.D. degree in management science and engineering from Southeast University, Nanjing, China, in 2003. From October 2005 to December 2007, he was a Postdoctoral Researcher with School of Economics and Management, Tsinghua University, Beijing, China. He was a Distinguished Young Scholar of the National Natural Science Foundation of China and the Chang Jiang Scholar of the Ministry of Education of China. He is currently a Professor with the Business School, Sichuan University, Chengdu. He has been elected as Academician of IASCYS (International academy for systems and cybernetic sciences), Fellow of IEEE (Institute of Electrical and Electronics Engineers), Fellow of IFSA (International Fuzzy Systems Association), Fellow of RSA (Royal Society of Arts), Fellow of IET (Institution of Engineering and Technology), Fellow of BCS (British Computer Society), Fellow of VEBLEO , Fellow of IAAM (International Association of Advanced Materials), and ranked 431th among World's Top 100,000 Scientists in 2019. He has contributed more than 600 SCI/SSCI articles to professional journals, and is among the world's top 1% most highly cited researchers with about 64,000 citations, his h-index is 126. He is currently the Co-Editor of Economic Research-Ekonomska Istraživanja ; the Associate Editor-in-Chief of Applied Intelligence , the Senior Editor of IEEE Access, and the Associate Editors of IEEE Transactions on Cybernetics, IEEE Transactions on Fuzzy Systems, Information Sciences, Artificial Intelligence Review, Fuzzy Optimization and Decision Making, Journal of the Operational Research Society, etc. His current research interests include decision making, information fusion, data analysis, fuzzy systems and applications. ORCID identifier : 0000-0003-3547-2908 ","Ajjan H., Hartshorne R., Investigating faculty decisions to adopt Web 2.0 technologies: theory and empirical tests, Internet High. Educ., 11, pp. 71-80, (2008); Ajzen I., The Theory of planned behavior, Organ. Behav. Hum. Decis. 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Change, 78, pp. 386-407, (2011); Ye J.H., Zheng J.Q., Yi F.B., A study on users’ willingness to accept mobility as a service based on UTAUT model, Technol. Forecast. Soc. Change, 157, (2020); Yeo W., Kim S., Park H., Kang J., A bibliometric method for measuring the degree of technological innovation, Technol. Forecast. Soc. Change, 95, pp. 152-162, (2015); Yu D.J., Xu Z.S., Saparauskas J., The evolution of “Technological and Economic Development of Economy”: a bibliometric analysis, Technol. Econ. Dev. Econ., 25, 3, pp. 369-385, (2019); Zupic I., Cater T., Bibliometric methods in management and organization, Organ. Res. Methods, 18, pp. 429-472, (2015)","X. Wang; Business School, Sichuan University, Chengdu, 610064, China; email: wangxinxin_cd@163.com",null,"Elsevier Inc.",{"$nulls":5},401625.0,null,null,null,"English","Technol. Forecast. Soc. Change","Article","Final",null,"Scopus","2-s2.0-85107129565"]
["Chen X.","Chen, Xianhui (57546772400)",5.75467724E10,"E-Commerce Logistics Inspection System Based on Artificial Intelligence Technology in the Context of Big Data",2022.0,"Security and Communication Networks",2022.0,null,3418466.0,null,null,null,9.0,"10.1155/2022/3418466","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85126953816&doi=10.1155%2f2022%2f3418466&partnerID=40&md5=06b1c10da04a6d015542020f236c44ed","Hunan Post and Telecommunication College, Hunan, Changsha, 410015, China","Chen X., Hunan Post and Telecommunication College, Hunan, Changsha, 410015, China","With the development of science and technology, the logistics industry has generally introduced information technology, and the construction of intelligent warehouse management is the development trend of the logistics industry. In order to improve the operation efficiency of intelligent warehouse and make full use of freight resources, this paper proposes an intelligent logistics inspection system based on big data. The system takes the platform data of unmanned monitoring points with multiple data sources as the research object and also uses a deep learning-based method for parcel detection and tracking in order to overcome the defects of traditional parcel detection and tracking technology. The role of the system is to obtain the parcel flow data of each unmanned monitoring point and then upload these important data to the scheduling system of the warehouse to realize the intelligent management of the warehouse.  © 2022 Xianhui Chen.",null,"Deep learning; Information management; Inspection; Inspection equipment; Monitoring; Scheduling; Warehouses; Artificial intelligence technologies; Detection and tracking; Development of science and technologies; Development trends; Inspection system; Intelligent warehouse; Logistics industry; Management IS; Monitoring points; Warehouse management; Big data",{"$nulls":6},"Szaruga E., Zaloga E., Global network economy society: Information needs on the ethical framework and trust in transportation and logistics business among users of the google search engine, European Research Studies, 24, 2 B, pp. 835-849, (2021); Mikl J., Herold D.M., Pilch K., Cwiklicki M., Kummer S., Understanding disruptive technology transitions in the global logistics industry: The role of ecosystems, Review of International Business and Strategy, 31, 1, pp. 62-79, (2021); Kolarovszki P., Vaculik J., Intelligent storage system based on automatic identification, Transport and Telecommunication Journal, 15, 3, pp. 185-195, (2014); Pandian A.P., Artificial intelligence application in smart warehousing environment for automated logistics, Journal of Artificial Intelligence, 1, 2, pp. 63-72, (2019); Lee C.K.M., Lv Y., Ng K.K.H., Ho W., Choy K.L., Design and application of Internet of things-based warehouse management system for smart logistics, International Journal of Production Research, 56, 8, pp. 2753-2768, (2018); Pei J., Zhong K., Li J., Jiyuan X., Xinyi W., ECNN: Evaluating a cluster-neural network model for city innovation capability, Neural Computing & Applications, (2021); Hinkka V., Tatila J., RFID tracking implementation model for the technical trade and construction supply chains, Automation in Construction, 35, pp. 405-414, (2013); Yang P., PRLS-INVES: A general experimental investigation strategy for high accuracy and precision in passive RFID location systems, IEEE Internet of Things Journal, 2, 2, pp. 159-167, (2014); Abad I., Cerrada C., Cerrada J.A., Heradio R., Valero E., Managing RFID sensors networks with a general purpose RFID middleware, Sensors, 12, 6, pp. 7719-7737, (2012); Golparvar-Fard M., Bohn J., Teizer J., Savarese S., Pena-Mora F., Evaluation of image-based modeling and laser scanning accuracy for emerging automated performance monitoring techniques, Automation in Construction, 20, 8, pp. 1143-1155, (2011); Abosuliman S.S., Almagrabi A.O., Computer vision assisted human computer interaction for logistics management using deep learning, Computers & Electrical Engineering, 96, (2021); Yang M., Mahmood M., Zhou X., Shafaq S., Zahid L., Design and implementation of cloud platform for intelligent logistics in the trend of intellectualization, China Communications, 14, 10, pp. 180-191, (2017); Hossain S., Lee D., Deep learning-based real-time multiple-object detection and tracking from aerial imagery via A flying robot with GPU-based embedded devices, Sensors, 19, 15, (2019); Schroder P., Schmidt T.T., Blankenburg F., Neural basis of somatosensory target detection independent of uncertainty, relevance, and reports, Elife, 8, (2019); Hu J., Zhi X., Zhang W., Ren L., Bruzzone L., Salient ship detection via background prior and foreground constraint in remote sensing images, Remote Sensing, 12, 20, (2020); Pang Y., Wu Y., Wu C., Zhang M., Salient object detection via effective background prior and novel graph, Multimedia Tools and Applications, 79, 35, pp. 25679-25695, (2020); Liang D., Pan J., Sun H., Zhou H., Spatio-temporal attention model for foreground detection in cross-scene surveillance videos, Sensors, 19, 23, (2019); Ullah I., Fayaz M., Kim D., Improving accuracy of the kalman filter algorithm in dynamic conditions using ANN-based learning module, Symmetry, 11, 1, (2019); Wang C., Xu Y., Liu H., Jing X., Retrogression of correlation filters for discriminative visual object tracking, Journal of Electronic Imaging, 27, 6, (2018); Farhadi A., Redmon J., Yolov3: An Incremental Improvement, pp. 1804-2767; Huang Z., Wang J., Fu X., Yu T., Guo Y., Wang R., DC-SPP-YOLO: Dense connection and spatial pyramid pooling based YOLO for object detection, Information Sciences, 522, pp. 241-258, (2020)","X. Chen; Hunan Post and Telecommunication College, Changsha, Hunan, 410015, China; email: 201904217319@stu.zjsru.edu.cn",null,"Hindawi Limited",{"$nulls":5},1.9390114E7,null,null,null,"English","Secur. Commun. Networks","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85126953816"]
["Chaudhary S.; Suri P.K.","Chaudhary, Sanjay (57204717749); Suri, P.K. (36883866200)","57204717749; 36883866200","Ranking the Factors Influencing e-Trading Usage in Agricultural Marketing",2021.0,"Global Journal of Flexible Systems Management",22.0,3.0,null,233.0,249.0,16.0,4.0,"10.1007/s40171-021-00276-8","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85110057089&doi=10.1007%2fs40171-021-00276-8&partnerID=40&md5=8429caa0a58214f8890c75b1cb4ef074","Delhi School of Business, Vivekananda Institute of Professional Studies, AU Block, Outer Ring Road, Pitampura, Delhi, India; Delhi School of Management, Delhi Technological University, Shahabad Daulatpur, Main Bawana Road, Delhi, India","Chaudhary S., Delhi School of Business, Vivekananda Institute of Professional Studies, AU Block, Outer Ring Road, Pitampura, Delhi, India; Suri P.K., Delhi School of Management, Delhi Technological University, Shahabad Daulatpur, Main Bawana Road, Delhi, India","This research article attempts to rank the factors influencing continued e-Trading usage in Indian agriculture marketing. The ranking process is the first of its kind application in agricultural e-trading. A review of published literature has helped in identifying key factors influencing e-trading usage in agricultural marketing. The factors are ranked using the efficient Interpretive Ranking Process (IRP) methodology adopted in the context of agricultural marketing. Sixteen expert members, grouped into three different expert panels, have helped generate ranks and validation besides giving suggestions for improving e-trading usage in the context of the National Agriculture Market project (eNAM) in India. It has been found that the top factors influencing e-trading usage are 'Trust', 'Cost', 'Perceived Ease of Use', and 'Facilitating Conditions', respectively. These factors need to be supported with adequate resources to strengthen eNAM in terms of improved usage among the beneficiaries. It is further revealed that immediate attention is needed on aspects such as transparency, quick information dissemination, adequate quality assurance, uniformity in taxes and market fee, improvement in marketing infrastructure, inter-market trade logistics, conflict resolution, mobility and training. Further, the e-trading system's flexibility needs to be enhanced by incorporating modular design options, configurable new features, open-source innovation, cloud computing, and progressive artificial intelligence application. © 2021, Global Institute of Flexible Systems Management.","Agriculture; Digitalization; E-commerce; E-trading; Flexibility; IRP; Marketing; Supply chain",{"$nulls":7},{"$cut":{"chars":17495,"head":"The long road to the transformation of agricultural markets in India: Lessons from Karnataka. India, Indira Gandhi Institute of Development Research, (2016); Ajzen I., The Theory of Planned Behaviour, Organizational Behaviour and Human Decision Processes, 50, 2, pp. 179-211, (1991); Aravindh K.S., Karthikeyan C., The eminence of mobile agricultural apps in the worldwide Mobile network, International Journal of Development Extension, 9, 1, pp. 26-38, (2018); Astalin P.K., Qualitative research designs: A conceptual framework, International Journal of Social Science & Interdisciplinary Research, 2, 1, pp. 118-125, (2013); Aulkemeier F., Iacob M.E., Hillegersberg J.V., Platform-based collaboration in digital ecosystems, Electronic Markets, 29, pp. 597-608, (2019); Auramo J., Kauremaa J., Tanskanen K., Benefits of IT in supply chain management: An explorative study of progressive companies, International Journal of Physical Distribution & Logistics Management, 35, 2, pp. 82-100, (2005); Bender P.S., Debunking five supply chain myths, Supply Chain Management Review, 4, 1, pp. 52-58, (2000); Berg B.L., Qualitative Research Methods for the Social Sciences, (2001); Bichler M., Kalagnanam J., Katircioglu K., King A.J., Lawrence R.D., Lee H.S., Applications of flexible pricing in business-to-business electronic commerce, IBM Systems Journal, 41, 2, pp. 287-302, (2002); Bisen J., Kumar R., Agricultural marketing reforms and national agriculture market (e-NAM) in India: A review, Agricultural Economics Research Review, 31, pp. 167-176, (2018); Bryman A., Social Research Methods, (2008); Casalo L.V., Flavian C., Guinaliu,, The generation of trust in online services and product distribution: The case of Spanish electronic commerce, Journal of Electronic Commerce Research, 12, 3, pp. 199-2015, (2011); Chaudhary S., Suri P.K., Modeling the Enablers of e-Trading Adoption in Agricultural Marketing: A TISM-Based Analysis of eNAM, (2021); Chen R.S., Sun C.M., Helms M.M., Jih W.J., Factors influencing information system flexibility: An interpretive flexibility perspective, International Journal of Enterprise Information Systems, 5, 1, pp. 32-43, (2009); Chircu A.M., Kauffman R.J., A framework for performance and value assessment of e-business systems in corporate travel distribution, Working Paper, (2000); Chordia T., Roll R., Subrahmanyam A., Liquidity and market efficiency, Journal of Financial Economics, 87, 2, pp. 249-268, (2008); Clasen M., Mueller R.A.E., Success factors of agribusiness digital marketplaces, Electronic Markets, 16, 4, pp. 349-360, (2006); Creswell J.W., Qualitative inquiry and research design: Choosing among five approaches, (2007); Davis F.D., Perceived usefulness, perceived ease-of-use, and user acceptance of information technology, MIS Quarterly, 13, 3, pp. 318-340, (1989); Dejen A., Solomon N., Mobile information system for small-scale rural farmers, IEEE Technological Innovation in ICT for Agriculture and Rural Development (TIAR), pp. 79-83, (2015); Directorate of Economics and Statistics. Ministry of Agriculture and Farmers Welfare, (2018); Dey K., National agricultural market-rationale rollout and ramifications, Economic & Political Weekly, 51, 19, pp. 35-39, (2016); Dhaygude M., Chakraborty D., Rethinking design of digital platforms for emergent users: Findings from a study with rural Indian farmers, . India HCI '20: Proceedings of the 11Th Indian Conference on Human-Computer Interaction., (2020); Dodds W.B., Monroe K.B., Grewal D., Effects of price, brand, and store information on buyers, Journal of Marketing Research, 28, 3, pp. 307-319, (1991); Dwivedi Y.K., Rana N.P., Jeyaraj A., Marc C., Michael D.W., Re-examining the unified theory of acceptance and use of technology (UTAUT): Towards a revised theoretical model, Information System Frontiers, 21, pp. 719-734, (2019); Engotoit B., Musa B., Moya K.G., Abima B., A Mobile-based communication adoption model for agricultural market information dissemination in Uganda, Global Journal of Computers & Technology, 5, 1, pp. 249-265, (2016); Engstrom A., Salehi-Sangari"}},"S. Chaudhary; Delhi School of Business, Vivekananda Institute of Professional Studies, Delhi, AU Block, Outer Ring Road, Pitampura, India; email: one.sanjay@gmail.com",null,"Springer",{"$nulls":5},9722696.0,null,null,null,"English","Global J. Flexible Syst. Manage.","Article","Final",null,"Scopus","2-s2.0-85110057089"]
["Peng Z.; Chen M.","Peng, Zikang (57205559007); Chen, Miaochao (57460399400)","57205559007; 57460399400","New Media Marketing Strategy Optimization in the Catering Industry Based on Deep Machine Learning Algorithms",2022.0,"Journal of Mathematics",2022.0,null,5780549.0,null,null,null,0.0,"10.1155/2022/5780549","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124964489&doi=10.1155%2f2022%2f5780549&partnerID=40&md5=ad100ef8294c0cb875f3ee85c11cb71c","School of Marxism Henan, Finance University, Henan, Zhengzhou, 450046, China","Peng Z., School of Marxism Henan, Finance University, Henan, Zhengzhou, 450046, China; Chen M., School of Marxism Henan, Finance University, Henan, Zhengzhou, 450046, China","With the in-depth development of new-generation network technologies such as the Internet, big data, and cloud intelligence, people can obtain massive amounts of information on mobile phones or mobile platforms. The era of unreachable big data has arrived, which raises questions for the development of corporate marketing. With the development of Internet technology, people use mobile terminals for longer and longer periods of time. New media has gradually become the mainstream of the media arena. It has distinctive features such as freedom to find audiences, diverse content forms, and timeliness of information release, which has changed the traditional. The marketing model has a profound impact on the development of the market. This article uses relevant theories, such as new media, marketing, and catering industry marketing strategies, studies the related concepts and characteristics of new media, clarifies the impact of the development of new media on the catering industry and audience groups, and studies the impact of the catering industry from multiple dimensions. Based on the development factors in the new media environment, combined with marketing theory, it puts forward suggestions for catering companies to use new media to carry out marketing planning in product innovation, improving information channels, creating network events and topics, and promoting innovation and health in the catering industry. And a marketing strategy is proposed based on deep machine learning algorithms; including a cloud server, the cloud server communicates with the e-commerce software platform and the input of physical sales is recorded. The adopted cloud server is connected with data collection, data processing, and communication module. The communication module is connected with a deep machine learning algorithm system; that is, deep machine learning algorithm system is connected with a sales platform in communication. The sales platform is connected with advertising settings and advertising, and the advertising is electrically connected with an algorithm of advertising delivery methods. Advertisement delivery method algorithm communication is connected to the cloud server. This article uses deep machine learning algorithms to process the data information to make the data information easy to view and clear. The advertisement delivery method algorithm calculates the best way of advertising and then calculates the advertisement to deliver. Copyright © 2022 Zikang Peng.",{"$nulls":8},"He K., Zhang X., Ren S., Sun J., Deep residual learning for image recognition, pp. 770-778; Yun M., Zhao J., Zhao J., Weng X., Yang X., Impact of in-vehicle navigation information on lane-change behavior in urban expressway diverge segments, Accident Analysis & Prevention, 106, 1, pp. 53-66, (2017); Kumar Dwivedi S., Amin R., Satyanarayana V., Blockchain-based secured event-information sharing protocol in internet of vehicles for smart cities, Computers & Electrical Engineering, 86, 1, pp. 1-9, (2020); Khan Z., Amin S., Bottleneck model with heterogeneous information, Transportation Research Part B: Methodological, 112, 1, pp. 157-190, (2018); Cairney J.M., Rajan K., Haley D., Mining information from atom probe data, Ultramicroscopy, 159, 1, pp. 324-337, (2020); Yu J., Lu P., Learning traffic signal phase and timing information from low-sampling rate taxi GPS trajectories, Knowledge-Based Systems, 110, 1, pp. 275-292, (2016); Wijayaratna K.P., V Dixit V., Denant-Boemont L., An experimental study of the Online Information Paradox: does en-route information improve road network performance?, PLoS ONE, 12, 9, pp. 184-191, (2017); Wang Z., Ren H., Shen Q., Sui W., Zhang X., Seismic performance evaluation of a steel tubular bridge pier in a five-span continuous girder bridge system, Structures, 31, 1, pp. 909-920, (2021); Nakayama S., Takayama J., Traffic network equilibrium model for uncertain demands; Shao H., Lam W.H.K., Tam M.L., A reliability-based stochastic traffic assignment model for network with multiple user classes under uncertainty in demand, Networks and Spatial Economics, 6, 3, pp. 173-204, (2019); Chen A., Kim J., Lee S., Stochastic multi-objective models for network design problem[J], Expert Systems with Applications, 37, 2, pp. 1608-1619, (2020); Wang H., Lam W.H.K., Zhang X., Shao H., Sustainable transportation network design with stochastic demands and chance constraints, International Journal of Sustainable Transportation, 9, 2, pp. 126-144, (2015); Hosseininasab S.-M., Shetab-Boushehri S.-N., Integration of selecting and scheduling urban road construction projects as a time-dependent discrete network design problem, European Journal of Operational Research, 246, 3, pp. 762-771, (2015); Hosseininasab S.-M., Shetab-Boushehri S.-N., Hejazi S.R., Karimi H., A multi-objective integrated model for selecting, scheduling, and budgeting road construction projects, European Journal of Operational Research, 271, 1, pp. 262-277, (2018); Johnson M., Schuster M., Le Q.V., Krikun M., Wu Y., Chen Z., Thorat N., Viegas F., Wattenberg M., Corrado G., Hughes M., Dean J., Google's multilingual neural machine translation system: enabling zero-shot translation, Transactions of the Association for Computational Linguistics, 5, 1, pp. 339-351, (2017); Moreno M.D., Translation quality gained through the implementation of the iso en 17100:2015 and the usage of the blockchain, Babel, 1, 2, pp. 1-9, (2020); Wang X., Yu X., Guo L., Liu F., Xu L., Student performance prediction with short-term sequential campus behaviors, Information, 11, 4, (2020); Guo Q., Zhu Z., Lu Q., Zhang D., Wu W., A dynamic emotional session generation model based on Seq2Seq and a dictionary-based attention mechanism, Applied Sciences, 10, 6, pp. 1-10, (2020); Ren H., Mao X.i., Ma W., Wang J., Wang L., An English-Chinese machine translation and evaluation method for geographical names, ISPRS International Journal of Geo-Information, 9, 3, pp. 193-201, (2020); Arus-Pous J., Blaschke T., Ulander S., Reymond J.-L., Chen H., Engkvist O., Exploring the GDB-13 chemical space using deep generative models, Journal of Cheminformatics, 11, 1, pp. 20-29, (2019); Moon T., In Ahn T., Jung E., Long short-term memory for a model-free estimation of macronutrient ion concentrations of root-zone in closed-loop soilless cultures, Plant Methods, 15, 1, pp. 1-12, (2019); Pourdamghani N., Knight K., Neighbors helping the poor: improving low-resource machine translation using related languages, Machine Translation, 33, 3, pp. 239-258, (2019); Bote-Curiel L., Munoz-Romero S., Gerrero-Curieses A., Luis Rojo-Alvarez J., Deep learning and big data in healthcare: a double review for critical beginners, Applied Sciences, 9, 11, pp. 1-11, (2019); Zhang J., Matsumoto T., Corpus augmentation for neural machine translation with Chinese-Japanese parallel corpora, Applied Sciences, 9, 10, pp. 1-12, (2019); Chen Y., Ma Y., Mao X., Li Q., Multi-task learning for abstractive and extractive summarization, Data Science and Engineering, 4, 1, pp. 14-23, (2019); Zhou P., Jiang Z., Self-organizing map neural network (SOM) downscaling method to simulate daily precipitation in the Yangtze and Huaihe River Basin, Climatic and Environmental Research, 21, 5, pp. 512-524, (2016); Xiao X., Analysis on the employment psychological problems and adjustment of retired athletes in the process of career transformation, Modern Vocational Education, 5, 12, pp. 216-217, (2018); Sahoo S., Jha M.K., Pattern recognition in lithology classification: modeling using neural networks, self-organizing maps and genetic algorithms, Hydrogeology Journal, 25, 2, pp. 311-330, (2016); Zhou Y., Yang B., Sports video athlete detection using convolutional neural network, Journal of Natural Science of Xiangtan University, 39, 1, pp. 95-98, (2017); Pang J., Research on the evaluation model of sports training adaptation based on self-organizing neural network, Journal of Nanjing Institute of Physical Education, 16, 1, pp. 74-77, (2017); Querzola G., Lovati C., Mariani C., Pantoni L., A semi-quantitative sport-specific assessment of recurrent traumatic brain injury: the TraQ questionnaire and its application in American football, Neurological Sciences, 40, 9, pp. 1909-1915, (2019); Wang J., Luo X., Yan H., Correlation analysis between injuries and functional movement screening for athletes of the National Shooting Team, Journal of Capital Institute of Physical Education, 5, 4, pp. 352-355, (2016)","Z. Peng; School of Marxism Henan, Finance University, Zhengzhou, Henan, 450046, China; email: pengzikang@hafu.edu.cn",null,"Hindawi Limited",{"$nulls":5},2.3144629E7,null,null,null,"English","J. Math.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85124964489"]
["Huang S.-H.; Huang Y.-H.; Blazquez C.A.; Chen C.-Y.","Huang, Shan-Huen (35368427300); Huang, Ying-Hua (15729146800); Blazquez, Carola A. (7004004521); Chen, Chia-Yi (57429938600)","35368427300; 15729146800; 7004004521; 57429938600","Solving the vehicle routing problem with drone for delivery services using an ant colony optimization algorithm",2022.0,"Advanced Engineering Informatics",51.0,null,101536.0,null,null,null,41.0,"10.1016/j.aei.2022.101536","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85123587242&doi=10.1016%2fj.aei.2022.101536&partnerID=40&md5=81f3da42e60fff4b614187e60db9ae9c","Department of Logistics Management, National Kaohsiung University of Science and Technology, No. 1, University Rd., Yanchao Dist., Kaohsiung City, 824, Taiwan; Department of Civil and Construction Engineering, National Yunlin University of Science and Technology, 123 University Road, Sec. 3, Douliu, 64002, Yunlin, Taiwan; Department of Engineering Sciences, Universidad Andres Bello, Quillota 980, Viña del Mar, Chile","Huang S.-H., Department of Logistics Management, National Kaohsiung University of Science and Technology, No. 1, University Rd., Yanchao Dist., Kaohsiung City, 824, Taiwan; Huang Y.-H., Department of Civil and Construction Engineering, National Yunlin University of Science and Technology, 123 University Road, Sec. 3, Douliu, 64002, Yunlin, Taiwan; Blazquez C.A., Department of Engineering Sciences, Universidad Andres Bello, Quillota 980, Viña del Mar, Chile; Chen C.-Y., Department of Logistics Management, National Kaohsiung University of Science and Technology, No. 1, University Rd., Yanchao Dist., Kaohsiung City, 824, Taiwan","E-commerce and logistics companies are facing important challenges to satisfy the rapid growth of customer demands. Unmanned aerial vehicles such as drones are an emerging technology that are very useful to cope with rising customer expectations of fast, flexible, and reliable delivery services. Drones work in tandem with trucks to perform parcel delivery, which have proven to reduce costs, CO2 emissions, and delivery times. This research proposes a mixed integer programming formulation to address the Vehicle Routing Problem with Drone (VRPD) by assigning customers to drone-truck pairs, determining the number of dispatching drone-truck units, and obtaining optimal service routes while the fixed and travel costs of both vehicles are minimized. Given the NP-hard nature of the VRPD, an ant colony optimization (ACO) algorithm is elaborated to solve this problem. Two novel methods are proposed to investigate the efficiency of the drone-truck combination by allowing the drones to perform additional delivery services to only one feasible customer and also multiple feasible customers while the truck waits at a customer location. Experimental results show that the proposed ACO algorithm can effectively solve the VRDP for different size instances and different customer location distributions, and is successful in providing timely solutions for small test instances within 1% of the optimal solutions. Finally, experimentation also reveals that the ACO algorithm outperforms the classical VRP by obtaining cost-savings of over 30% for large instances. © 2022 Elsevier Ltd","Heuristic; Optimization; Unmanned aerial vehicle; Urban delivery; Vehicle routing problem","Ant colony optimization; Antennas; Artificial intelligence; Customer satisfaction; Drones; Integer programming; Sales; Trucks; Ant Colony Optimization algorithms; Customer demands; Delivery service; Emerging technologies; Heuristic; Logistics company; Optimisations; Rapid growth; Urban delivery; Vehicle Routing Problems; Vehicle routing",{"$nulls":4},"Ministry of Science and Technology, Taiwan, MOST, (109-2221-E-992-005)","Funding text 1: This work was supported by the Ministry of Science and Technology , Taiwan [Project No. 109-2221-E-992-005 ]. ; Funding text 2: The authors would like to thank the editor and the anonymous reviewers for their valuable comments and suggestions to improve the quality of the paper. Dr. Shan-Huen Huang would like to thank the Ministry of Science and Technology, Taiwan for the financial support (Project No. 109-2221-E-992-005). ","IMARC Group, (2020); Huang Y.H., Blazquez C.A., Huang S.H., Paredes-Belmar G., Latorre-Nunez G., Solving the feeder vehicle routing problem using ant colony optimization, Comput. Ind. Eng., 127, pp. 520-535, (2019); Li J., Rombaut E., Vanhaverbeke L., A systematic review of agent-based models for autonomous vehicles in urban mobility and logistics: Possibilities for integrated simulation models, Comput. Environ. Urban Syst., 89, (2021); Rabta B., Wankmuller C., Reiner G., A drone fleet model for last-mile distribution in disaster relief operations, Int. J. Disaster Risk Reduct., 28, pp. 107-112, (2018); Scott J., Scott C., Drone Delivery Models for Healthcare, (2017); Murray C., Chu A., The flying sidekick traveling salesman problem: Optimization of drone-assisted parcel delivery, Transp. Res. 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Blazquez; Department of Engineering Sciences, Universidad Andres Bello, Viña del Mar, Quillota 980, Chile; email: cblazquez@unab.cl",null,"Elsevier Ltd",{"$nulls":5},1.4740346E7,null,null,null,"English","Adv. Eng. Inf.","Article","Final",null,"Scopus","2-s2.0-85123587242"]
["Ahmad N.H.; Teoh M.F.; Ramayah T.; Halim H.A.","Ahmad, Noor Hazlina (35777347300); Teoh, Ming Fang (57462545500); Ramayah, T. (57222416490); Halim, Hasliza Abdul (36172546800)","35777347300; 57462545500; 57222416490; 36172546800","DIGITAL BUSINESS MODEL INNOVATION IN SMEs: THE ROLES OF ENTREPRENEURIAL LEADERSHIP AND GOVERNMENT SUPPORT",2022.0,"Journal of Applied Structural Equation Modeling",6.0,1.0,{"$nulls":4},2.0,"10.47263/JASEM.6(1)04","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85130261519&doi=10.47263%2fJASEM.6%281%2904&partnerID=40&md5=1c4d418d3f3a65899d94ded37dd7e21f","Universiti Sains Malaysia, Pulau Pinang, Malaysia","Ahmad N.H., Universiti Sains Malaysia, Pulau Pinang, Malaysia; Teoh M.F., Universiti Sains Malaysia, Pulau Pinang, Malaysia; Ramayah T., Universiti Sains Malaysia, Pulau Pinang, Malaysia; Halim H.A., Universiti Sains Malaysia, Pulau Pinang, Malaysia","Digital business model innovation (DBMI) is a new business model domain which is increasingly attracting interest in an attempt to resolve challenges to digital transformation. It is known as a crucial research field of business model. However, the empirical studies on SMEs focusing on digital business model innovation in a developing country are relatively scant. Previous studies have concentrated mostly on any two or three elements of DBMI. Thus, this research attempts to bridge the knowledge gap by focusing on all elements of DBMI to reveal valuable insights. Grounded in upper echelon and institutional theories, this study investigates the relationship between entrepreneurial leadership, government support with digital business model innovation (DBMI). Preliminary interviews were conducted with four members of top management from different SMEs in Malaysia to determine whether the literature and anecdotal evidence can reflect real-life business circumstances. The empirical data were collected from 132 Malaysian small and medium-sized enterprises (SMEs) using the purposive sampling technique. As predicted, the empirical findings show that entrepreneurial leadership and government support positively affect DBMI (value creation innovation, value proposition innovation, value delivery innovation, and value capture innovation). This research is novel as it the first study unravelling the pivotal role of entrepreneurial leadership and government support in promoting DBMI adoption to achieve superior performance in the digital sphere. It bridges the literature gaps on the driving factors of DBMI adoption. Present study contributes to the DBMI literature with the empirical evidence from SMEs. This study would complement prior findings on the role of entrepreneurial leadership and government support in business model innovation, e-business and e-commerce. The findings of the present study have various implications for SMEs and practitioners that plan to adopt DBMI in various industries. This model can be incorporated as a strategy by SMEs in both developing and developed countries to increase their competitiveness. Future studies could examine other factors that may contribute to DBMI and its associated outcomes in other contexts. © 2022, Sarawak Research Society. All rights reserved.","Digital business model innovation; entrepreneurial leadership; government support; SMEs",{"$nulls":5},"SFDT; SIDEC; SMERF; SMEs; FP7 Research for the Benefit of SMEs, SME; Ministry of Higher Education, Malaysia, MOHE, (FRGS/1/2018/SS03/USM/01/1)","Funding text 1: In terms of government support, there is a minor discrepancy from the inputs of respondents. Respondents A and D perceived financial support from the government, such as matching grant, and ‘Penjana’ loans can assist the business to transform some of the traditional systems/platforms to digital ones. However, respondent B argues that due to the influence of Covid-19, government financial support has been used to support business sustainability and not DBMI. Respondent C asserts that the business does not receive government financial assistance due to the rigid terms and bureaucratic processes. Nonetheless, he believed that government support played an important role to help SMEs to adopt DBMI during the Covid-19 pandemic. Non-financial government support that includes training were mentioned by respondents B and D. Respondent D depicts that some of the digital-related training was useful for the business in DBMI adoption.; Funding text 2: Furthermore, government support has been seen to exert a positive impact on value capture innovation. Government financial support, which includes soft financing scheme for automation and modernisation (SFSAM), soft financing scheme for digital and technology (SFDT), SME revitalisation financing (SMERF), SME digitalisation grants, smart automation grants, and the Selangor digitalisation grant (SIDEC), have reduced the financial burden of SMEs and support them to transform the business model at a lower cost structure and earn higher profit. The nonfinancial government support such as educational workshops was believed can guide SMEs to create the new cost structure and identify the new sources of revenues.","Ansong E., Boateng R., Surviving in the digital era – business models of digital enterprises in a developing economy, Digital Policy, Regulation and Governance, 21, 2, pp. 164-178, (2019); Awa H.O., Awara N.F., Lebari E.D., Critical factors inhibiting electronic commerce (EC) adoption in nigeria: A study of operators of SMEs, Journal of Science and Technology Policy Management, 6, 2, pp. 143-164, (2015); Blaschke M., Cigaina M., Riss U.V., Shoshan I., Designing Business Models for the Digital Economy, In, (2017); Boojihawon D.K., Ngoasong Z.M., Emerging digital business models in developing economies: The case of Cameroon, Strategic Change, 27, 2, pp. 129-137, (2018); Bouncken R.B., Kraus S., Roig-Tierno N., Knowledge-and innovation-based business models for future growth: Digitalized business models and portfolio considerations, Review of Managerial Science, 12, (2019); Cai W., Lysova E.I., Khapova S.N., Bossink B.A.G., Does Entrepreneurial Leadership Foster Creativity Among Employees and Teams? 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Teoh; Universiti Sains Malaysia, Pulau Pinang, Malaysia; email: mfteoh88@gmail.com",null,"Sarawak Research Society",{"$nulls":5},2.5904221E7,null,null,null,"English","J. Appl. Struct. Equ. Model.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85130261519"]
["Schadler M.; Schedler M.; Knödl M.; Prims D.; Landschützer C.; Katterfeld A.","Schadler, Michael (57202048211); Schedler, Michael (57220862659); Knödl, Martin (57203487635); Prims, Domenik (57197750302); Landschützer, Christian (36863782600); Katterfeld, André (57203694781)","57202048211; 57220862659; 57203487635; 57197750302; 36863782600; 57203694781","Characteristics of ‘polybags’ used for low-value consignments in the mail, courier, express and parcel industry",2022.0,"Logistics Journal",2022.0,1.0,{"$nulls":4},1.0,"10.2195/lj_Rev_schadler_en_202201_01","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85123595943&doi=10.2195%2flj_Rev_schadler_en_202201_01&partnerID=40&md5=2aa751dfd4802897ac79e199de10e3fd","Institute of Logistics Engineering (ITL), Faculty of Mechanical Engineering and Economic Sciences, Graz University of Technology, Austria; Siemens Logistics GmbH, Research & Development Department, Constance, Germany; Chair of Material Handling-Institute of Logistics and Material Handling Systems, Faculty of Mechanical Engineering, Otto-von-Guericke University Magdeburg, Germany","Schadler M., Institute of Logistics Engineering (ITL), Faculty of Mechanical Engineering and Economic Sciences, Graz University of Technology, Austria; Schedler M., Institute of Logistics Engineering (ITL), Faculty of Mechanical Engineering and Economic Sciences, Graz University of Technology, Austria; Knödl M., Institute of Logistics Engineering (ITL), Faculty of Mechanical Engineering and Economic Sciences, Graz University of Technology, Austria; Prims D., Siemens Logistics GmbH, Research & Development Department, Constance, Germany; Landschützer C., Institute of Logistics Engineering (ITL), Faculty of Mechanical Engineering and Economic Sciences, Graz University of Technology, Austria; Katterfeld A., Chair of Material Handling-Institute of Logistics and Material Handling Systems, Faculty of Mechanical Engineering, Otto-von-Guericke University Magdeburg, Germany","With the continuous growth of shipment volumes in the courier, express and parcel (CEP) market, mainly driven by e-commerce, the usage of so-called polybags as packaging material for low-value goods is increasingly replacing conventional cardboard boxes or kraft paper envelopes. Especially in the Asian region the usage of polybags as packaging material can be considered as status quo. Despite their advantages regarding costs, durability or tampering protection, the flexible shape and the material properties of polybags lead to major challenges when being processed with automated material handling technology in logistics distribution centers. Depending on one’s point of view the usage of polybags in the CEP industry can be seen as boon or bane. Another dilemma in conjunction with this kind of packaging material is that there is no precise definition of the term polybag neither in literature, nor in the packaging branch or in the CEP industry. This often leads to wrong interpretations and misunderstandings. The aim of this paper is to define polybags based on their physical characteristics and to analyze the behavior of polybags as they can be found in today’s shipments. This paper especially focuses on the evaluation of the limpness/rigidity and the static and dynamic coefficients of friction (COF) of polybags in comparison to cardboard and kraft paper. The paper also discusses other influencing factors such as weight, velocity and lift. © 2022 Logistics Journal:.","CEP; Low-value consignment; Mixed mail; Polybag; Small packet",{"$nulls":7},"How to Prep Products; Anton Paar GmbH: Rutschwinkelprüfer RWP; Arnold D., Einleitung des Herausgebers, Intralogistik. 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Connecting Buyers with Chinese Suppliers; Fritz M., Beitrag zur Simulation des Bewegungsverhaltens von Stückgütern im Pulk im Kontext der Vereinzelung, (2016); Fritz M., Wolfschluckner A., Jodin D., Simulation von Paketen im Pulk, (2013); Hafner F., Prozess zur Beschreibung des Fly-Out Verhaltens von Polybags innerhalb eines Sortiersystems, (2021); Hompel M. ten, Schmidt T., Dregger J., Teilfunktionen in Materialflusssystemen, Materialflusssysteme, pp. 247-338, (2018); UPU Convention Manual, (2018); Cross-border e-comerce shopper survey 2019, (2019); Cross-border e-comerce shopper survey 2020, (2020); Jodin D., Hompel M., ten: Sortier-und Verteilsysteme. Grundlagen, Aufbau, Berechnung und Realisierung, (2012); Katterfeld A., Prims D., SIMPPL-Simulation of the motion behaviour of filled parcels and load carriers in bulk mode, Project description; Landschutzer C., Wolfschluckner A., Fritz M., EAGLE – Innovatice technical solution for automated parcel unloading, Poster Abstract: IPIC 2017, 4th International Physical Internet Conference, (2017); McCloughan P., Study of Online Consumer Sales: The Economic Impacts of Online Consumer Sales on Additional Packaging and Its Cost in Ireland, (2019); Global Summery Report, (2018); Parcu P.L., Brennan T.J., Glass V., Hrsg.: The contribution of the postal and delivery sector, Between e-commerce and e-substitution, (2018); Prims D., Katterfeld A., Anwendung der Diskrete Elemente Methode zur Senkung der Beschädigungsrate von Maschinen für den Umschlag von Paketen im Pulk, Logistics Journal: Proceedings, 2017, (2017); Prims D., Et al., Validation of Flow Models as New Simulation Approach for Parcel Handling in Bulk Mode, Wissenschaftliche Gesellschaft für Technische Logistik, (2019); Saucke R., Technische und wirtschaftliche Bewertung von Konzepten zur Sortierung von (asiatischen) Kleinstsendungen, (2019); Siemens Logistics GmbH: Creating new business with mixed-mail automation, Integrating small parcel processing into mail sorting centers; Soroka W., Illustrated glossary of packaging terminology, (2008); Saucke R., Prims D., ECommerce-Handling-Fluch und Segen zugleich, Logistik Werkstatt: Solution day-\"update, pp. 45-76, (2019); Universal Post Union; World Customs Organization: WCO-UPU Postal Customs Guide, (2018); Sorting and distribution systems for parcel goods; Verband der Wellpappen-Industrie e.V.: Zahlen und Fakten. Daten für die Wellpapenindustrie, (2021); Wend R., Startschuss in Bochum, Postforum. Informationen für politische Entscheider, (2021); Development of Cross-border E-commerce through Parcel Delivery. A study for DG GROW, Delivering for the Future III: Workshop on Developments in the Postal Sector, (2019); Yang L., Hanneke S., Carbonell J., A theory of transfer learning with applications to active learning, Machine Learning, 90, pp. 161-189, (2013)",null,null,"Wissenschaftliche Gesellschaft fur Technische Logistik",{"$nulls":5},1.8607977E7,null,null,null,"English","Logist. J.","Article","Final",null,"Scopus","2-s2.0-85123595943"]
["Lan L.","Lan, Lan (57421547700)",5.74215477E10,"Research on e-commerce logistics distribution path planning based on Improved Genetic Algorithm",2022.0,"International Journal of Circuits, Systems and Signal Processing",16.0,null,24.0,202.0,208.0,6.0,0.0,"10.46300/9106.2022.16.24","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85123241189&doi=10.46300%2f9106.2022.16.24&partnerID=40&md5=9417e694f58f0a6732e70d1596867575","Henan Polytechnic Institute, Nanyang, 473000, China","Lan L., Henan Polytechnic Institute, Nanyang, 473000, China","—With the rapid development of the Internet, e-commerce business has gradually emerged. However, its logistics distribution route planning method has problems such as redundancy of logistics data, which cannot achieve centralized planning of distribution paths, resulting in low e-commerce logistics distribution efficiency and long distribution distances, higher cost. Therefore, in order to improve the ability of logistics distribution path planning, this paper designs an e-commerce logistics distribution path planning method based on improved genetic algorithm. Optimize the analysis of e-commerce logistics distribution nodes, establish a modern logistics distribution system, and optimize the total transportation time and transportation cost under the location model of the logistics distribution center. Using hybrid search algorithm and improved genetic algorithm parameters, an improved genetic algorithm distribution path planning model is established to select the optimal path of logistics distribution, and realize e-commerce logistics distribution path with high accuracy, low error and good convergence. planning. According to the experimental results, the method in this paper can effectively shorten the distance of e-commerce logistics distribution path, reduce the number of distribution vehicles, reduce distribution costs, improve distribution efficiency, and effectively achieve centralized planning of logistics distribution. Therefore, the e-commerce logistics distribution route planning method based on improved genetic algorithm has high practical application value. © 2022, North Atlantic University Union NAUN. All rights reserved.","E-commerce; Genetic algorithm; Logistics distribution; Path planning","Cost benefit analysis; Efficiency; Electronic commerce; Genetic algorithms; Centralised; Distribution efficiency; Distribution route; E- commerces; E-commerce business; High costs; Logistic distributions; Path planning method; Planning method; Route planning; Motion planning",{"$nulls":6},"Wang Y., Shi Q., Spare parts closed-loop logistics network optimization problems: model formulation and meta-heuristics solution, IEEE Access, 7, 11, pp. 45048-45060, (2019); Mardaneh E., Loxton R., Meka S., Et al., A decision support system for grain harvesting, storage, and distribution logistics, Knowledge-Based Systems, 223, 1, (2021); Alomari S., Salaimeh S., Jarrah E. A., Et al., Enhanced logistics information service systems performance: using theoretical model and cybernetics' principles, WSEAS Transactions on Business and Economics, 17, 29, pp. 278-287, (2020); Pramono C. A., Manurung A. H., Heriyati P., Et al., Analysis of the influence of entrepreneurship capability, agility, business transformation, opportunity on start-up behavior in e-commerce companies in Indonesia during the Covid 19 pandemic, WSEAS Transactions on Business and Economics, 18, pp. 1103-1112, (2021); Wan G. H., E-commerce logistics distribution path optimization based on improved ant colony optimization algorithm, Electronic Design Engineering, 29, pp. 25-28, (2021); Eisenhandler O., Tzur M., A segment-based formulation and a matheuristic for the humanitarian pickup and distribution problem, Transportation Science, 53, 5, pp. 1389-1408, (2019); Auliani F., Hertini E., Nahar J., Determination distribution route of beverage products with the application of the vehicle routing problem model and sensitivity analysis, Journal of Physics: Conference Series, 1722, 1, (2021); Febriandini I. F., Yuniaristanto, and W. Sutopo, “Multi-compartment vehicle routing problem to find the alternative distribution route of petroleum product delivery, IOP Conference Series: Materials Science and Engineering, 943, 1, (2020); Liu P., Ye S., Wang C., Et al., Spark-based parallel genetic algorithm for simulating a solution of optimal deployment of an underwater sensor network, Sensors, 19, 12, pp. 2717-2718, (2019); Zheng F., Liu X., Zuylen H. V., A methodological framework of travel time distribution estimation for urban signalized arterial roads, Operations Research, 59, 1-2, pp. 115-117, (2019); Yousefi R., Talebbeydokhti N., Afzali S. H., Et al., Stress–strain analysis by genetic algorithm-based integration of long-term subsidence time series from different synthetic aperture radar platforms in Darab, Iran. Journal of Applied Remote Sensing, 13, 2, (2019); Tomasz T., Lemu H. G., Improving prediction of springback in sheet metal forming using multilayer perceptron-based genetic algorithm, Materials, 13, 14, (2020); Wang Y., Yuan Y., Guan X., Et al., Collaborative two-echelon multicenter vehicle routing optimization based on state–space–time network representation, Journal of Cleaner Production, 258, 11, (2020); Wan S. P., Chen Z. H., Dong J. Y., Bi-objective trapezoidal fuzzy mixed integer linear program-based distribution center location decision for large-scale emergencies, Applied Soft Computing, 110, (2021); Melkonyan A., Gruchmann T., Lohmar F., Et al., Sustainability assessment of last-mile logistics and distribution strategies: The case of local food networks, International Journal of Production Economics, 228, 11, (2020); Xu R., Guo R., Jia Q., A novel hybrid metaheuristic for solving automobile part delivery logistics with clustering customer distribution, IEEE Access, 7, pp. 106075-106091, (2019); Ouyang F., Research on port logistics distribution route planning based on artificial fish swarm algorithm, Journal of Coastal Research, 115, sp1, (2020); Li D. L., Cao Q., Xu F., Delivery route optimization of chain convenience stores based on improved genetic algorithm, Computer Engineering and Science, 42, 11, pp. 2096-2102, (2020); Chu Z., Yu P., Innovation of e-commerce terminal express cooperative distribution based on big data platform, International Journal of Performability Engineering, 15, 3, pp. 977-986, (2019); Ozkan B., Ozceylan E., Mete S., Planning of vehicle routes for the exam booklet distribution: A GIS-based solution approach, IFAC-Papers on Line, 53, 2, pp. 11225-11230, (2020); Chi R., Su Y., Qu Z., Et al., A hybridization of cuckoo search and differential evolution for the logistics distribution center location problem, Mathematical Problems in Engineering, 29, 1, pp. 1-16, (2019); Liu P., Li Y., Multiattribute decision method for comprehensive logistics distribution center location selection based on 2-dimensional linguistic information, Information Sciences, 538, 12, pp. 209-244, (2020)","L. Lan; Henan Polytechnic Institute, Nanyang, 473000, China; email: jqisn04@163.com",null,"North Atlantic University Union NAUN",{"$nulls":5},1.9984464E7,null,null,null,"English","Int. J. Circuit Syst. Signal Process.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85123241189"]
["Huang L.; Xie G.; Huang R.; Li G.; Cai W.; Apostolidis C.","Huang, Lijuan (55324150500); Xie, Guojie (57194012125); Huang, Raoyi (57209858463); Li, Guokai (57203590408); Cai, Weiwei (57215898790); Apostolidis, Chrysostomos (57204930232)","55324150500; 57194012125; 57209858463; 57203590408; 57215898790; 57204930232","Electronic commerce for sustainable rural development: Exploring the factors influencing bops’ entrepreneurial intention",2021.0,"Sustainability (Switzerland)",13.0,19.0,10604.0,null,null,null,18.0,"10.3390/su131910604","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85115815830&doi=10.3390%2fsu131910604&partnerID=40&md5=cf9b865e701736cb48772c350c2f66ad","School of Management, Guangzhou University, Guangzhou, 510000, China; Faculty of Engineering, The Hong Kong Polytechnic University, 37075, Hong Kong; Department of Civil, Environmental and Architectural Engineering (DICEA), University of Padua, Padua, 35131, Italy; Graduate School, Northern Arizona University, Flagstaff, 86011, AZ, United States; Durham University Business School, Durham University, Millhill Ln, Durham, DH1 3LB, United Kingdom","Huang L., School of Management, Guangzhou University, Guangzhou, 510000, China; Xie G., School of Management, Guangzhou University, Guangzhou, 510000, China; Huang R., Faculty of Engineering, The Hong Kong Polytechnic University, 37075, Hong Kong; Li G., Department of Civil, Environmental and Architectural Engineering (DICEA), University of Padua, Padua, 35131, Italy; Cai W., Graduate School, Northern Arizona University, Flagstaff, 86011, AZ, United States; Apostolidis C., Durham University Business School, Durham University, Millhill Ln, Durham, DH1 3LB, United Kingdom","Rural e‐commerce entrepreneurship is an effective and credible means to alleviate poverty and promote sustainable social development, particularly in the Base of the Pyramid (BoP). Understanding how to encourage BoPs’ entrepreneurial intention in the rural e‐commerce market has become a key issue for private enterprises and local governments. Based on the entrepreneurial event model, we constructed a research framework to evaluate the factors influencing BoPs’ entrepreneurial intention in rural e‐commerce. We conducted an online survey of rural e‐commerce practitioners from Jieyang and Chaozhou in Guangdong Province, China, and empirically analyzed the survey results using SmartPLS software. The results show that professional knowledge, resource endowment, information and communication technology, and logistics infrastructure have a significant positive impact on BoP entrepreneurship in rural e‐commerce, while previous market channels had a significant negative impact. Based on the findings, we recommend that BoPs should focus more on cultivating professional knowledge in e‐commerce entrepreneurship and capitalize on local resource advantage. E‐commerce enterprises and local governments should strengthen and improve information communication technology and logistics infrastructure among BoP communities. Policymakers should support BoP entrepreneurship in rural e‐commerce by creating a favorable environment. © 2021 by the authors.","BoP community; Entrepreneurship; Factors; Intention; Rural e‐commerce","Chaozhou; China; Guangdong; Jieyang; electronic commerce; entrepreneur; exploration; factor analysis; information and communication technology; local government; policy making; psychology; rural development; sustainable development",{"$nulls":4},"National Office for Philosophy and Social Sciences, NPOPSS, (19BGL177)","This research was funded by the NATIONAL SOCIAL SCIENCE FOUNDATION OF CHINA, grant number 19BGL177.","Chao P., Biao B., Chen Z.C., Poverty Alleviation through E‐Commerce: Village Involvement and Demonstration Policies in Rural China, J. Integr. 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Rural Stud, 81, pp. 159-169, (2021); Alibaba Jingdong Pinduoduo to Promote the Development of Rural E‐Commerce; The Annual Transaction Volume of Rural E‐Commerce in China has Exceeded One Trillion Yuan; Muller S., Korsgaard S., Resources and Bridging: The role of Spatial Context in Rural Entrepreneurship, Entrep. Reg. Dev, 30, pp. 1-32, (2018); Borch O.J., Forde A., Ronning L., Vestrum I.K., Alsos G.A., Resource Configuration and Creative Practices of Community Entrepreneurs, J. Enterprising Communities People Places Glob. Econ, 2, pp. 100-123, (2008); Zhou Y.H., Liu C.Y., Analysis on the Aggregation of Farmers’ E‐commerce and Influencing Factors in “China’s Taobao Villages”: A Survey of Shaji Town and Yanji Town in Jiangsu Province, South China J. Econ, 37, pp. 62-84, (2018); Zhang C., Zhang G.S., Wang Y.L., Co‐evolution and Policy Optimization of Rural E‐commerce and Rural Logistics under Government Poverty Alleviation, J. Beijing Jiaotong Univ, 19, pp. 98-105, (2020); Adelson J.L., Mccoach D.B., Measuring the Mathematical Attitudes of Elementary Students: The Effects of a 4‐Point or 5‐Point Likert‐Type Scale, Educ. Psychol. Meas, 70, pp. 796-807, (2010); Huang L.J., Xie G.J., Blenkinsopp J., Huang R., Bin H., Crowdsourcing for Sustainable Urban Logistics: Exploring the Factors Influencing Crowd Workers’ Participative Behavior, Sustainability, 12, (2020); Kautonen T., Marco V.G., Matthias F., Robustness of the theory of planned behavior in predicting entrepreneurial intentions and actions, Entrep. Theory Pract, 39, pp. 655-674, (2015); Chen L.P., Build the Development Pole of the less Developed Coastal Areas in Eastern Guangdong, Learn. 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Sci, 12, pp. 942-942, (2004); Jieyang to Promote Express Logistics Industry Development Program; Chaozhou Municipal Government Held the 20th Executive Meeting of 2019 to Study the Construction of Rural Logistics Network and Other Matters; Fonseca R, Lopez-Garcia P., Pissarides C.A., Entrepreneurship, start‐up costs and employment, Eur. Econ. Rev, 45, pp. 692-705, (2001); Amoros J.E., Ciravegna L., Mandakovic V., Stenholm P., Necessity or opportunity? The effects of state fragility and economic development on entrepreneurial efforts, Entrep. Theory Pract, 43, pp. 725-750, (2019); Korsgaard S., Muller S., Tanvig H.W., Rural entrepreneurship or entrepreneurship in the rural—Between place and space, Int. J. Entrep. Behav. Res, 21, pp. 5-26, (2015)","G. Xie; School of Management, Guangzhou University, Guangzhou, 510000, China; email: 1111965003@e.gzhu.edu.cn",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85115815830"]
["Gee I.M.; Faust K.M.; Webber M.E.","Gee, Isabella M (57209851467); Faust, Kasey M (55803401200); Webber, Michael E (7103355833)","57209851467; 55803401200; 7103355833","A framework for determining energy use in rural food delivery services: capturing system interdependencies through an agent-based discrete-event approach",2021.0,"Environmental Research: Infrastructure and Sustainability",1.0,3.0,35002.0,null,null,null,1.0,"10.1088/2634-4505/ac2b10","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85130366894&doi=10.1088%2f2634-4505%2fac2b10&partnerID=40&md5=1cb14b0d3a472483639bc5c2b2784e3f","Civil, Architectural, and Environmental Engineering, University of Texas at Austin, 301 E Dean Keeton St C1700, Austin, 78712, TX, United States; Mechanical Engineering, University of Texas at Austin, 1 University Station C2200, Austin, 78712, TX, United States","Gee I.M., Civil, Architectural, and Environmental Engineering, University of Texas at Austin, 301 E Dean Keeton St C1700, Austin, 78712, TX, United States; Faust K.M., Civil, Architectural, and Environmental Engineering, University of Texas at Austin, 301 E Dean Keeton St C1700, Austin, 78712, TX, United States; Webber M.E., Mechanical Engineering, University of Texas at Austin, 1 University Station C2200, Austin, 78712, TX, United States","Food e-commerce has seen significant growth over the past decade that accelerated after the onset of the COVID-19 pandemic. Last-mile transportation and logistics are widely considered the most expensive and least efficient portion of the supply chain and have multiple important energy trade-offs such as cargo capacity and consumer density. Last-mile transportation energy use in rural areas is underrepresented in the literature. This study proposes a hybrid agent-based and discrete event model framework for evaluating the last-mile transportation energy use of van- and car-based food delivery services in a rural community, based on meal-kit and grocery delivery operations, respectively. This framework quantifies last-mile energy use in rural areas, and is demonstrated here using a neighborhood outside of Austin, TX as an analytical testbed. The study focuses on the effects of consumer density, cargo limitations, and vehicle speed. For the conditions examined with this framework, diesel delivery vans use more total energy than passenger cars for the same trip, though a van delivering four orders uses less energy per-order than a car delivering one order. However, there are trade-offs between vehicle type and mileage, cargo capacity, route density, and speed that are particularly important for delivery services operating in rural areas. This framework can be used by service providers to assess route-specific trade-offs for each vehicle and gauge which is preferable for given operating conditions or to evaluate the energy, and thus also cost, impact of expanding their services to rural areas. © 2021 The Author(s). Published by IOP Publishing Ltd.","e-commerce; energy; food delivery; last-mile; rural; transportation",{"$nulls":5},"George Mitchell Foundation","This work was funded by the Cynthia and George Mitchell Foundation. ",{"$cut":{"chars":17636,"head":"Albert A, Schafer A, Demand for freight transportation in the U.S.: a high-level view, 54th Annual Transportation Research Forum, (2013); Allen J, Understanding the impact of e-commerce on last-mile light goods vehicle activity in urban areas: the case of London, Transport. Res. D, 61, pp. 325-338325, (2018); Alternative Fuels Data Center 2014 Fuel Properties Comparison Department of Energy; Anagnostou A, Nouman A, Taylor S J E, Distributed hybrid agent-based discrete event emergency medical services simulation, Proc. 2013 Winter Simulation Conf.: Simulation: Making Decisions in a Complex World, 1625 1636, pp. 1625-1636, (2013); An Analysis of the Operational Costs of Trucking: 2019 Update American Transportation Research Institute, (2019); Ballare S, Lin J, Investigating the use of microhubs and crowdshipping for last mile delivery Transport, Res. Procedia, 46, pp. 277-284277, (2020); Bogage J, Push to Electrify Mail Trucks Gains Wide Support, an Unlikely Win for Both DeJoy and Biden, (2021); Borggren C, Moberg A, Finnveden G, Books from an environmental perspective-part 1: environmental impacts of paper books sold in traditional and internet bookshops, Int. J. Life Cycle Assess, 16, pp. 138-147138, (2011); Boyer K K, Prud'homme A M, Chung W, The last mile challenge: evaluating the effects of customer density and delivery window patterns, J. Bus. Logist, 30, pp. 185-201185, (2009); Brandt E J, Silvestri D M, Mande J R, Holland M L, Ross J S, Availability of grocery delivery to food deserts in states participating in the online purchase pilot, JAMA Netw. Open, 2, (2019); Carey N, UPS Partners with Workhorse to Build Electric Delivery Vans (Reuters), (2018); Chang W-R, Hwang J-J, Wu W, Environmental impact and sustainability study on biofuels for transportation applications, Renew. Sustain. Energy Rev, 67, pp. 277-288277, (2017); Chen P, Chankov S M, Crowdsourced delivery for last-mile distribution: an agent-based modelling and simulation approach, IEEE Int. Conf. Industrial Engineering and Engineering Management 2017 December, 1271 1275, pp. 1271-1275, (2018); Secrets of better fuel economy: the physics of MPG, (2018); Doering C, Peeking inside the Pod: A Deep Look inside Peapod’s Grocery Delivery Business (Food Dive), (2018); Edwards J B, McKinnon A C, Cullinane S L, Carbon auditing the ‘last mile’: modelling the environmental impacts of conventional and online non-food shopping, (2009); Edwards J B, Mckinnon A C, Cullinane S L, Comparative analysis of the carbon footprints of conventional and online retailing, Int. J. Phys. Distrib. Logist. Manage, 40, pp. 103-123103, (2010); Ehmke J F, Mattfeld D C, Vehicle routing for attended home delivery in city logistics, The 7th Int. Conf. City Logistics, 39, pp. 622-632622, (2012); Elgart Z, Miller K, Tan S, Warner J, Updated Guidebook: Using Public Transportation to Facilitate Last Mile Package Delivery Texas A&M Transportation Institute, (2019); Fakhimi M, Anagnostou A, Stergioulas L, Taylor S J E, A hybrid agent-based and discrete event simulation approach for sustainable strategic planning and simulation analytics, Proc. 2014 Winter Simulation Conf, 1573, 1584, pp. 1573-1584, (2014); Fan Y V, Klemes J J, Walmsley T G, Perry S, Minimising energy consumption and environmental burden of freight transport using a novel graphical decision-making tool, Renew. Sustain. Energy Rev, 114, (2019); The role of cities in the transformation of food systems: sharing lessons from Milan Pact cities, (2018); Fenton K, Unpacking the Sustainability of Meal Kit Delivery: A Comparative Analysis of Energy Use, Carbon Emissions, and Related Costs for Meal Kit Services and Grocery Stores University of Texas at Austin, (2017); Filippini R, Mazzocchi C, Corsi S, The contribution of urban food policies toward food security in developing and developed countries: a network analysis approach, Sustain. Cities Soc, 47, (2019); The Digitally Engaged Food Shopper The Food Industry Association, (2017); Frey H C, Trends in onroad transportation energy and emissions, J. Air Waste Manage. Assoc, 68, pp. 514-5635"}},"I.M. Gee; Civil, Architectural, and Environmental Engineering, University of Texas at Austin, Austin, 301 E Dean Keeton St C1700, 78712, United States; email: Isabella.gee@utexas.edu; K.M. Faust; Civil, Architectural, and Environmental Engineering, University of Texas at Austin, Austin, 301 E Dean Keeton St C1700, 78712, United States; email: faustk@utexas.edu; M.E. Webber; Mechanical Engineering, University of Texas at Austin, Austin, 1 University Station C2200, 78712, United States; email: webber@mail.utexas.edu",null,"Institute of Physics",{"$nulls":5},2.6344505E7,null,null,null,"English","Environ. Res. Infrastruct. Sustain.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85130366894"]
["Elkhattat D.; Medhat M.","Elkhattat, Dina (57223971960); Medhat, Mervat (57218450081)","57223971960; 57218450081","Creativity in packaging design as a competitive promotional tool",2022.0,"Information Sciences Letters",11.0,1.0,19.0,135.0,148.0,13.0,4.0,"10.18576/isl/110115","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121858080&doi=10.18576%2fisl%2f110115&partnerID=40&md5=f9f86e0c9b271d430df756c2e3ccac4c","Department of Public Relations at the College of Mass Communication, Ajman University, Ajman, United Arab Emirates; Department of Media and Mass Communication, Faculty of Arts, Ain Shams University, Cairo, Egypt; Department of Graphic Design at the College of Mass Communication, Ajman University, Ajman, United Arab Emirates; Department of Art & Design, Academy Higher Institution of Applied Art, Cairo, 6th of October, Egypt","Elkhattat D., Department of Public Relations at the College of Mass Communication, Ajman University, Ajman, United Arab Emirates, Department of Media and Mass Communication, Faculty of Arts, Ain Shams University, Cairo, Egypt; Medhat M., Department of Graphic Design at the College of Mass Communication, Ajman University, Ajman, United Arab Emirates, Department of Art & Design, Academy Higher Institution of Applied Art, Cairo, 6th of October, Egypt","In line with the vast technology, and challenging competition among organizations in the field of industry, recently the food companies recognized the importance of innovative Packaging design as a vital solution and a competitive element among competitors, as it should be unique, adding value to consumers, and well reflects the brand’s identity. In that context, the study of factors affecting consumer attraction and intentions and behaviors will be very beneficial for food companies that tend to produce creative packaging to enhance their brand’s positioning by attracting consumers’ attention towards their products and influence the final purchase intentions. Hence, analyzing the creative food packages will help companies to maintain the integration between innovation and creativity as parallel with the design appealing and functionality, through implementing new technologies to support consumers’ experience and enhancing the ease of use, and the concepts of social responsibility towards the environment. In this Regard, packages are developing all the time by using creative ideas, different printing materials, technologies, and smart solutions that are integrated with communication through digital media for a better experience in communicating with the target audience and to match their changing needs and lifestyles. The study through its analytical descriptive approach of food packaging samples aimed to identify, elaborate, analyze, and discuss factors that lead to a unique food packaging to have a great influence on consumer experience and preferences toward products, and to highlights the recent trends in creative packaging of the food industry, to specify the most significant elements in the food packaging nowadays. The study results concluded that adopting creative and innovative design ideas and utilizing different technologies could help the package promotion in unique impressive experience to enhance the consumers’ purchasing decision, and researchers stressed the recommendations regarding applying “eco-friendly and sustainable packages” to achieve mutual benefits for both consumers and the environment. Additionally, Food companies should be careful about the package functionality especially with the vast spreading of e-commerce and the long shipping period, and in times of crisis and pandemics like Covid-19, as packaging material should be protected during shipping till delivery to consumers. © 2022 NSP Natural Sciences Publishing Cor.","Consumer Behavior; Creativity and Innovation; Package Design; Promotion; Smart Package",{"$nulls":7},"Drago E., Campardelli R., Pettinato M., Perego P., Innovations in Smart Packaging Concepts for Food: An Extensive Review, MDPI, Foods 2020, 9, (2020); Arens W., Contemporary Advertising, European Journal of Marketing, 25, 3, (2007); Louw A., Kimber M., The Power of Packaging: The Customer Equity Company is a wholly-owned subsidiary of TNS (UK), (2007); Copley P., Marketing Communications Management: concepts and theories, cases and practices, (2004); Asadollahi A., Givee M., The role of graphic design in packaging and sales of production in Iran, Contemporary Marketing Review, 1, 5, pp. 30-34, (2011); Silayoi P., Speece M., Packaging and purchase decisions: An exploratory study on the impact of involvement level and time pressure, British Food Journal, (2004); Pilditch J., The silent salesman: How to Develop Packaging That Sells, (1973); Elkhattat D., Medhat M., Using Technology in Smart and Intelligent Food Packages as a Communicational Tool with Consumers, 2021 World Conference on Computing and Communication Technologies (WCCCT), (2020); Vyas H., Bhuvanesh v., packaging design elements, and users perception: a context in fashion branding and communication, Journal of Applied Packaging Research, pp. 95-107, (2015); Ahmad N., MohibBillo, Lakhan A., Effect of Product Packaging in Consumer Buying Decision, Journal of Business Strategies, 6, 2, pp. 1-10, (2012); Silayoi P, Packaging and Purchase Decisions, British Food Journal, 106, 8, pp. 607-608, (2006); Kuvykaite R., Dovaliene A., Navickiene L., Impact of Consumer Package Communication on Consumer Decision Making Process, Economics & Management, 14, (2009); Jugger S., The power of packaging, Admap Magzine, (2008); Rundh B., Packaging design: creating a competitive advantage with product packaging, British Food Journal, (2009); Stewart B., Packaging Design Strategy, (2004); Steenkamp J.E.M., Conceptual model of the quality perception process, Journal of Business Research, 21, pp. 309-333, (1990); Murphy I.P., Study: packaging important in trial purchase, Marketing News, (1997); Grunert K.G., Food quality and safety: consumer perception and demand, Eur. 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A preliminary study, Journal of Sensory Studies, (2020); Athena Chen Y.S., Does outward appearance appeal to the inward mind? The impact of packaging finishes on brand impressions and the subsequent behavior of consumers, Journal of Product & Brand Management, 30, 5, pp. 768-778, (2021); Brewer C., The Verbal and Visual Components of Package Design, Journal of product and brand management, 9, 1, pp. 56-70, (2006); Kauppinen-Raisanen H., Luomala H. T., Exploring consumers' product-specific color meanings, Qualitative Market Research: An International Journal, 13, 3, pp. 287-308, (2010); Meyers H., Gerstman R., The visionary package: using packaging to build effective brands, (2005); Pride W.M., Farrell O.C., Marketing, (2010); Wu P., Bao Z., Song W., Hu Z., Research on semantics of packaging design, Computer-Aided Industrial Design & Conceptual Design, 2009. CAID & CD 2009.IEEE 10th International Conference on, pp. 316-318, (2009); Sousa M.M, Carvalho F.M., Pereira R. G. F. A., Colour and shape of design elements of the packaging labels influence consumer expectations and hedonic judgments of specialty coffee, Food Quality and Preference, 83, 2020, (2020); Klein N. M., Burke R. R., Packaging communication: attentional effects of product imagery, Journal of Product &Brand Management, 10, 7, pp. 403-422, (2001); Assavagomenkul N., Graphic design project for medicinal products MHerb, (2008); Tongrungroj S., Packaging Design, (2012); Dantas M, Nakajima V, Rosa D, Andrade F, Canzian C, Martino H, Guava jam packaging determinant attributes in consumer buying decision, Ciênc Tecnol Aliment, 31, 3, pp. 567-570, (2011); Fadzil M. I., Khamis K. A., Wan Muhammad W. 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The role of market orientation and organizational learning, European Journal of innovation management, 11, 3, pp. 389-412, (2008); Spiridon I, Ursu RG, Spiridon IAC, New polylactic acid composites for packaging applications: Mechanical properties, thermal behavior, and antimicrobial activity, Int J Polym Anal Ch, 20, pp. 681-692, (2015); Cammarelle A., Lombardi M., Viscecchia R., Packaging Innovations to Reduce Food Loss and Waste: Are Italian Manufacturers Willing to Invest?, MDPI Sustainability 2021, 13, (2021); Schoorman J.P.L., Robben H.S.J., The effect of new package design on product attention, categorization and evaluation, Journal of Economic Physiology, 18, 2-3, pp. 271-287, (1997); Vyas H., Bhuvanesh v., packaging design elements and users perception: a context in fashion branding and communication, Journal of Applied Packaging Research, (2015); Lee D., Yam K., Piergiovanni L., Food Packaging Science and Technology, (2008); Westerman S.J., Sutherland E.J., Gardner P.H., Baig N., Critchley C., Hickey C., Mehigan S., Solway A., Zervos Z., The design of consumer packaging: Effects of manipulations of shape, orientation, and alignment of graphical forms on consumer’s assessments, Food Quality and Preference, 27, pp. 8-17, (2013); Royte E., Eat Your Food, and the Package Too, Science & Innovationfuture of Food, (2018); Albright M.B., Food Packaging: Have Your Cake and Eat the Wrapper, (2015); Bloch P. 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Postharvest Technology and Innovation, 7, 2, pp. 109-117, (2020); Kuswandi B, Freshness sensors for food packaging, Research Gate, (2017); New coffee cup lid alerts consumers to temperature, (2006); SATO RFID white paper, (2004); Mohamed N., Development of Innovative structural solid packaging design for special occasion products in Arabic Area, Conference: Graphic Design professionalism and message, (2014); Tehrani B.K, Cook B.S, Tentzeris M.M., Inkjet-printed 3D interconnects for millimeter-wave system-on-package solutions, the IEEE MTT-S International Microwave Symposium Digest, (2016); Park E.S, Jeon J., Subramanian V., Liu T.J.K., Inkjet-printed micro-shell encapsulation: A new zero-level packaging technology, 2012 IEEE 25th International Conference on Micro Electro Mechanical Systems (MEMS), pp. 357-360, (2012); Mantysalo M., Mansikkamaki P., Miettinen J., Kaija K., Evaluation of Inkjet Technology for Electronic Packaging and System Integration, Proceedings 57th Electronic Components and Technology Conference, pp. 89-94, (2007); Aspar G., Goubault B., Lebaigue O., Souriau J.C, Simon G., Di Cioccio L., Brechet Y., 3D printing as a new packaging approach for MEMS and Electronic devices, IEEE 67th Electronic Components and Technology Conference, (2017)","M. Medhat; Department of Graphic Design at the College of Mass Communication, Ajman University, Ajman, United Arab Emirates; email: mervat.m@ajman.ac.ae",null,"Natural Sciences Publishing",{"$nulls":5},2.0909551E7,null,null,null,"English","Inf. Sci. Lett.","Article","Final",null,"Scopus","2-s2.0-85121858080"]
["Moshref-Javadi M.; Winkenbach M.","Moshref-Javadi, Mohammad (55911808200); Winkenbach, Matthias (57189308132)","55911808200; 57189308132","Applications and Research avenues for drone-based models in logistics: A classification and review",2021.0,"Expert Systems with Applications",177.0,null,114854.0,null,null,null,138.0,"10.1016/j.eswa.2021.114854","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85104139743&doi=10.1016%2fj.eswa.2021.114854&partnerID=40&md5=0f49e20f9033efec41e42cafdada3ca4","Northeastern University, 360 Huntington Ave., Boston, 02115, MA, United States; Center for Transportation and Logistics, Massachusetts Institute of Technology, 77 Massachusetts Ave., Cambridge, 02139, MA, United States","Moshref-Javadi M., Northeastern University, 360 Huntington Ave., Boston, 02115, MA, United States; Winkenbach M., Center for Transportation and Logistics, Massachusetts Institute of Technology, 77 Massachusetts Ave., Cambridge, 02139, MA, United States","The operational design and planning of drone-based logistics models is a rapidly growing area of scientific research. In this paper, we present a structured, comprehensive, and scalable framework for classifying drone-based delivery systems and their associated routing problems along with a comprehensive review and synthesis of the extant academic literature in this domain. While our proposed classification defines the boundaries and facilitates the comparison between a wide variety of possible drone-based logistics systems, our comprehensive literature review helps to identify and prioritize research gaps that need to be addressed by future work. Our review shows that the extant research reasonably considers some relevant real-world operational constraints. Although the multi-visit multi-drone Pure-play Drone-based (PD) delivery models are popular, the majority of the Synchronized Multi-modal (SM) delivery models focus on formulating and evaluating single-truck, single-drone models. Moreover, the Resupply Multi-modal (RM) models have not received the due attention for research compared to other drone-based delivery models. Our comprehensive review of use cases of drones for delivery indicates that most of the reviewed models are designed for applications in e-commerce and healthcare/emergency services. Other applications, such as food and mail deliveries are still underrepresented in the academic discussion. © 2021 Elsevier Ltd","Drone logistics; Last-mile delivery; Routing optimization; Unmanned aerial vehicle","Drones; Aerial vehicle; Delivery models; Design and planning; Drone logistic; Last-mile delivery; Logistic modelling; Multi-modal; Operational design; Operational planning; Routing optimization; Logistics",{"$nulls":6},{"$cut":{"chars":21571,"head":"Ackerman E., Strickland E., (2018); Afrati F., Cosmadakis S., Papadimitriou C.H., Papageorgiou G., Papakostantinou N., The complexity of the travelling repairman problem, RAIRO Informatique théorique, 20, 1, pp. 79-87, (1986); Agatz N., Bouman P., Schmidt M., Optimization approaches for the traveling salesman problem with drone, Transportation Science, 52, 4, pp. 965-981, (2018); (2013); Amin H., (2020); Aurambout J.-P., Gkoumas K., Ciuffo B., Last mile delivery by drones: an estimation of viable market potential and access to citizens across European cities, European Transport Research Review, 11, 1, (2019); Baker A., (2017); Bakir I., Tinic G.O., (2020); Blum A., Chalasani P., Coppersmith D., Pulleyblank B., Raghavan P., Sudan M., The minimum latency problem, The twenty-sixth annual ACM symposium on the theory of computing, pp. 163-171, (1994); Boland N., Hewitt M., Marshall L., Savelsbergh M., The continuous-time service network design problem, Operations Research, 65, 5, pp. 1303-1321, (2017); Bouman P., Agatz N., Schmidt M., Dynamic programming approaches for the traveling salesman problem with drone, Networks, 72, 4, pp. 528-542, (2018); Boutilier J.J., Brooks S.C., Janmohamed A., Byers A., Buick J.E., Zhan C., Schoellig A.P., Cheskes S., Morrison L.J., Chan T.C.Y., Optimizing a drone network to deliver automated external defibrillators, Circulation, 135, 25, pp. 2454-2465, (2017); Boysen N., Briskorn D., Fedtke S., Schwerdfeger S., Drone delivery from trucks: Drone scheduling for given truck routes, Networks, 72, 4, pp. 506-527, (2018); Campbell J.F., Sweeney Ii D.C., Zhang J., Strategic design for delivery with trucks and drones, Supply Chain Analytics Report SCMA, 4, 1, pp. 1-38, (2017); Carlsson J.G., Song S., Coordinated logistics with a truck and a drone, Management Science, 64, 9, pp. 4052-4069, (2018); Chan T.F., (2017); Chang Y.S., Lee H.J., Optimal delivery routing with wider drone-delivery areas along a shorter truck-route, Expert Systems with Applications, 104, pp. 307-317, (2018); Chauhan D., Unnikrishnan A., Figliozzi M., Maximum coverage capacitated facility location problem with range constrained drones, Transportation Research Part C: Emerging Technologies, 99, pp. 1-18, (2019); Cheng C., Adulyasak Y., Rousseau L.M., Drone routing with energy function: Formulation and exact algorithm, Transportation Research Part B: Methodological, 139, pp. 364-387, (2020); Chiang W.C., Li Y., Shang J., Urban T.L., Impact of drone delivery on sustainability and cost: Realizing the UAV potential through vehicle routing optimization, Applied Energy, 242, pp. 1164-1175, (2019); Choudhury S., Solovey K., Kochenderfer M.J., Pavone M., (2019); Chowdhury S., Emelogu A., Marufuzzaman M., Nurre S.G., Bian L., Drones for disaster response and relief operations: A continuous approximation model, International Journal of Production Economics, 188, pp. 167-184, (2017); Chung S.H., Sah B., Lee J., Optimization for drone and drone-truck combined operations: A review of the state of the art and future directions, Computers and Operations Research, 123, (2020); Claesson A., Backman A., Ringh R.N., Svensson L., Nordberg P., Djarv T., Hollenberg J., Time to delivery of an automated external defibrillator using a drone for simulated out-of-hospital cardiac arrests vs emergency medical services, JAMA – Journal of the American Medical Association, 317, 22, pp. 2332-2334, (2017); Clarke G., Wright J.W., Scheduling of vehicles from a central depot to a number of delivery points, Operations Research, 12, 4, pp. 568-581, (1964); Coelho B.N., Coelho V.N., Coelho I.M., Ochi L.S., Haghnazar K., 88, pp. 306-315, (2017); Columbus C., (2017); Cordeau J.F., Laporte G., The dial-a-ride problem: Models and algorithms, Annals of Operations Research, 153, 1, pp. 29-46, (2007); Coutinho W.P., Nascimento R., pp. 752-765, (2016); Daknama R., Kraus E., (2017); Das D.N., Sewani R., Wang J., Tiwari M.K., Synchronized truck and drone routing in package delivery logistics, IEEE Transactions on Intelligent Transportation Systems, pp. 1-11, (2020); Dayarian I.,"}},"M. Moshref-Javadi; Northeastern University, Boston, 360 Huntington Ave., 02115, United States; email: m.moshref@northeastern.edu",null,"Elsevier Ltd",{"$nulls":5},9574174.0,null,"ESAPE",null,"English","Expert Sys Appl","Article","Final",null,"Scopus","2-s2.0-85104139743"]
["Qiao P.","Qiao, Pengliang (57580178100)",5.75801781E10,"Simulation of Logistics Delay in Bayesian Network Control Based on Genetic em Algorithm",2022.0,"Computational Intelligence and Neuroscience",2022.0,null,6981450.0,null,null,null,1.0,"10.1155/2022/6981450","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85128429248&doi=10.1155%2f2022%2f6981450&partnerID=40&md5=c8308f95ce499b78ebfc5352e0c06e5f","School of Management, Guangzhou College of Technology and Business, Guangdong, Foshan, 528138, China; School of Economics and Management, Beibu Gulf University, Guangxi, Qinzhou, 535011, China","Qiao P., School of Management, Guangzhou College of Technology and Business, Guangdong, Foshan, 528138, China, School of Economics and Management, Beibu Gulf University, Guangxi, Qinzhou, 535011, China","With the continuous development of e-commerce, the logistics industry is thriving, and logistics delays have become an issue that deserves more and more attention. Genetic EM algorithm is a genetic EM algorithm that is an iterative optimization strategy algorithm that can be used to solve the high-quality algorithm of travel problems with many nodes. Bayesian network (BN) is a network model based on probabilistic uncertainty. This article aims to study the probability of many factors that cause logistics delays to construct an algorithm model to control or reduce logistics delays. This paper constructs an EY model (That is the abbreviation of BN model based on genetic EM algorithm) based on the genetic EM algorithm, and conducts related simulation experiments based on the model to verify the accuracy and feasibility of the model. The experimental results of this paper show that the calculation efficiency of the EY model is significantly improved, and the actuarial accuracy is as high as 98%, which can effectively control logistics delays. © 2022 Pengliang Qiao.",null,"Algorithms; Bayes Theorem; Commerce; Computer Simulation; Uncertainty; Bayesian networks; Iterative methods; Bayesia n networks; Continuous development; E- commerces; EM algorithms; High quality; Iterative Optimization; Logistics industry; Model-based OPC; Network-control; Optimization strategy; algorithm; Bayes theorem; commercial phenomena; computer simulation; uncertainty; Genetic algorithms",{"$nulls":6},"Chaudhary S., Indu S., Chaudhury S., Video-based road traffic monitoring and prediction using dynamic bayesian networks, IET Intelligent Transport Systems, 12, 3, pp. 169-176, (2017); Chaturvedi I., Ragusa E., Gastaldo P., Zunino R., Cambria E., Bayesian network based extreme learning machine for subjectivity detection, Journal of the Franklin Institute, 355, 4, pp. 1780-1797, (2017); Bolt J.H., Van Der Gaag L.C., Balanced sensitivity functions for tuning multi-dimensional Bayesian network classifiers, International Journal of Approximate Reasoning, 80, pp. 361-376, (2017); Liang X.F., Wang H.D., Yi H., Li D., Warship reliability evaluation based on dynamic bayesian networks and numerical simulation, Ocean Engineering, 136, pp. 129-140, (2017); Zhang Z., Dong F., Xie L., Data-Driven Fault Prognosis Based on Incomplete Time Slice Dynamic Bayesian Network, IFAC-PapersOnLine, 51, 18, pp. 239-244, (2018); Kawabe R., Ito H., Yamashita H., Goto M., Hierarchical Structure Learning in a Bayesian Network for the Analysis of Purchasing Behavior, Total Quality Science, 4, 3, pp. 99-108, (2019); Jacob D.E., Fenton N.E., Noguchi T., Lagnado D., Resolving the so-called \"probabilistic paradoxes in legal reasoning\" with Bayesian networks, Science & Justice: Journal of the Forensic Science Society, 59, 4, pp. 367-379, (2019); Luo Y., McShan D., Ray D., Matuszak M., Jolly S., Lawrence T., Kong F.-M., Ten Haken R., El Naqa I., Development of a Fully Cross-Validated Bayesian Network Approach for Local Control Prediction in Lung Cancer, IEEE Transactions on Radiation and Plasma Medical Sciences, 3, 2, pp. 232-241, (2019); Mirhosseini A.M., Adib Nazari S., Maghsoud Pour A., Etemadi Haghighi S., Zareh M., Probabilistic failure analysis of hot gas path in a heavy-duty gas turbine using Bayesian networks, International Journal of System Assurance Engineering and Management, 10, 5, pp. 1173-1185, (2019); Yazdi M., A review paper to examine the validity of Bayesian network to build rational consensus in subjective probabilistic failure analysis, International Journal of System Assurance Engineering and Management, 10, 1, pp. 1-18, (2019); Wu H.-D., Han L., A novel reasoning model for credit investigation system based on Fuzzy Bayesian Network, Procedia Computer Science, 183, 19, pp. 281-287, (2021); Dairy B., Valverde-Rebaza J., Moura M.F., Lopes A.D.A., A survey of the applications of Bayesian networks in agriculture, Engineering Applications of Artificial Intelligence, 65, pp. 29-42, (2017); Ramos-Lopez D., Masegosa A.R., MAP inference in dynamic hybrid Bayesian networks, Progress in Artificial Intelligence, 6, 2, pp. 133-144, (2017); Gheisari S., Meybodi M.R., A new reasoning and learning model for Cognitive Wireless Sensor Networks based on Bayesian networks and learning automata cooperation, Computer Networks, 124, pp. 11-26, (2017); Qian S.S., Stow C.A., Comparative analysis of discretization methods in Bayesian networks, Environmental Modelling & Software, 87, pp. 64-71, (2017); Javadi M., Saeedi G., Shahriar K., Fuzzy Bayesian Network Model for Roof Fall Risk Analysis in Underground Coal Mines, Journal of Applied Sciences, 17, 3, pp. 103-115, (2017); Kobayashi S., Shirayama S., Selecting data adaptive learner from multiple deep learners using Bayesian networks, Neural Computing and Applications, 33, 9, pp. 4229-4241, (2021); Andrews B., Ramsey J., Cooper G.F., Scoring Bayesian networks of mixed variables, International Journal of Data Science & Analytics, 6, 1, pp. 1-16, (2018); Sachdeva K., Aggarwal S., Aggarwal S., A Hybrid Approach for Neural Network in Pattern Storage, Fusion: Practice and Applications, 6, 2, pp. 43-49, (2021); Lessan J., Fu L., Wen C., A hybrid bayesian network model for predicting delays in train operations, Computers & Industrial Engineering, 127, pp. 1214-1222, (2018); Butz C.J., Oliveira J.S., Dos Santos A.E., Madsen A.L., An empirical study of Bayesian network inference with simple propagation, International Journal of Approximate Reasoning, 92, pp. 198-211, (2018); Freire A., Perkusich M., Saraiva R., Almeida H., Perkusich A., A Bayesian networks-based approach to assess and improve the teamwork quality of agile teams, Information and Software Technology, 100, pp. 119-132, (2018); Zsolt Z., Huang W., Matthew S., Michael L., Multivariable and bayesian network analysis of outcome predictors in acute aneurysmal subarachnoid hemorrhage: Review of a pure surgical series in the postinternational subarachnoid aneurysm trial era, Operative Neurosurgery, 12, 6, pp. 603-610, (2018); Petitjean F., Buntine W., Webb G.I., Zaidi N., Accurate parameter estimation for Bayesian network classifiers using hierarchical Dirichlet processes, Machine Learning, 107, 8-10, pp. 1303-1331, (2018); Dennis D.-M.K., Williams M.R., Sigman M.E., Investigative probabilistic inferences of smokeless powder manufacturers utilizing a Bayesian network, Forensic Chemistry, 3, pp. 41-51, (2017); Abedallah Z.A., Ali A., Alwan, multi-objective chaotic butterfly optimization with deep neural network based sustainable healthcare management systems, American Journal of Business and Operations Research, 4, pp. 39-48, (2021); Ramirez-Noriega A., Juarez-Ramirez R., Martinez-Ramirez Y., Evaluation module based on bayesian networks to intelligent tutoring systems, International Journal of Information Management, 37, 1, pp. 1488-1498, (2017)","P. Qiao; School of Management, Guangzhou College of Technology and Business, Foshan, Guangdong, 528138, China; email: qpliang@gzgs.edu.cn",null,"Hindawi Limited",{"$nulls":5},1.6875265E7,null,null,3.5432508E7,"English","Comput. Intell. Neurosci.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85128429248"]
["Prajapati D.; Kumar M.M.; Pratap S.; Chelladurai H.; Zuhair M.","Prajapati, Dhirendra (57215023349); Kumar, M. Manoj (57714148900); Pratap, Saurabh (56667217800); Chelladurai, H. (24075425500); Zuhair, Mohd (56341258100)","57215023349; 57714148900; 56667217800; 24075425500; 56341258100","Sustainable Logistics Network Design for Delivery Operations with Time Horizons in B2B E-Commerce Platform",2021.0,"Logistics",5.0,3.0,61.0,null,null,null,10.0,"10.3390/logistics5030061","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85129033274&doi=10.3390%2flogistics5030061&partnerID=40&md5=f2fd079db9f1f3ee7045b5b2b86df3e9","Department of Mechanical Engineering, Indian Institute of Information Technology, Jabalpur, 482005, India; Department of Mechanical Engineering, Indian Institute of Technology (BHU), Varanasi, 221005, India; Department of Computer Science and Engineering, Institute of Technology, Nirma University, Ahmedabad, 382481, India","Prajapati D., Department of Mechanical Engineering, Indian Institute of Information Technology, Jabalpur, 482005, India; Kumar M.M., Department of Mechanical Engineering, Indian Institute of Information Technology, Jabalpur, 482005, India; Pratap S., Department of Mechanical Engineering, Indian Institute of Technology (BHU), Varanasi, 221005, India; Chelladurai H., Department of Mechanical Engineering, Indian Institute of Information Technology, Jabalpur, 482005, India; Zuhair M., Department of Computer Science and Engineering, Institute of Technology, Nirma University, Ahmedabad, 382481, India","In the recent era, the rapidly increasing trend of e-commerce business creates opportunities for logistics service providers to grow globally. With this growth, the concern regarding the implementation of sustainability in logistic networks has received attention in recent years. Thus, in this work, we have focused on the vehicle routing problem (VRP) to deliver the products in a lesser time horizon with driver safety concern considerations in business (B2B) e-commerce platforms. We proposed a sustainable logistics network that captures the complexities of suppliers, retailers, and logistics service providers. A mixed-integer nonlinear programming (MINLP) approach is applied to formulate a model to minimize total time associated with order processing, handling, packaging, shipping, and vehicle maintenance. Branch-and-bound algorithms in the LINGO optimization tool and genetic algorithm (GA) are used to solve the formulated mathematical model. The computational experiments are performed in eight different case scenarios (small-sized problem to large-sized problem) to validate the model. © 2021 by the authors.","B2B e-commerce logistics; exact optimization; metaheuristic approaches; sustainability; time horizons; VRP",{"$nulls":7},"Huang Y.H., Blazquez C.A., Huang S.H., Paredes-Belmar G., Latorre-Nunez G., Solving the Feeder Vehicle Routing Problem using ant colony optimization, Comput. Ind. Eng, 127, pp. 520-535, (2019); Li J., Wang D., Zhang J., Heterogeneous fixed fleet vehicle routing problem based on fuel and carbon emissions, J. Clean. Prod, 201, pp. 896-908, (2018); Rincon-Garcia N., Waterson B., Cherrett T.J., Salazar-Arrieta F., A metaheuristic for the time-dependent vehicle routing problem considering driving hours regulations—An application in city logistics, Transp. Res. Part A Policy Pract, 137, pp. 429-446, (2020); Ali A.H., Melkonyan A., Noche B., Gruchmann T., Developing a Sustainable Logistics Service Quality Scale for Logistics Service Providers in Egypt, Logistics, 5, (2021); Chen H.K., Chou H.W., Hsu C.Y., The linehaul-feeder vehicle routing problem with virtual depots and time windows, Math. Probl. Eng, 2011, (2011); Chen T.L., Cheng C.Y., Chen Y.Y., Chan L.K., An efficient hybrid algorithm for integrated order batching, sequencing and routing problem, Int. J. Prod. Econ, 159, pp. 158-167, (2015); Subramanyam A., Wang A., Gounaris C.E., A scenario decomposition algorithm for strategic time window assignment vehicle routing problems, Transp. Res. Part B Methodol, 117, pp. 296-317, (2018); Prajapati D., Zhou F., Cheikhrouhou N., Pratap S., Minimizes the Time Window for Delivery of Orders in B2B E-commerce, Proceedings of the 5th International Conference on Industrial Engineering (ICIE), pp. 1-6; Molina J.C., Salmeron J.L., Eguia I., Racero J., The heterogeneous vehicle routing problem with time windows and a limited number of resources, Eng. Appl. Artif. Intell, 94, (2020); Munoz-Villamizar A., Solano-Charris E.L., Reyes-Rubiano L., Faulin J., Measuring Disruptions in Last-Mile Delivery Operations, Logistics, 5, (2021); Asefi H., Shahparvari S., Chhetri P., Lim S., Variable fleet size and mix VRP with fleet heterogeneity in Integrated Solid Waste Management, J. Clean. Prod, 230, pp. 1376-1395, (2019); Su Y., Jin S., Zhang X., Shen W., Eden M.R., Ren J., Stakeholder-oriented multi-objective process optimization based on an improved genetic algorithm, Comput. Chem. Eng, 132, (2020); Attari M.Y.N., Torkayesh A.E., Malmir B., Jami E.N., Robust possibilistic programming for joint order batching and picker routing problem in warehouse management, Int. J. Prod. Res, 59, pp. 4434-4452, (2021); Gu W., Cattaruzza D., Ogier M., Semet F., Adaptive large neighborhood search for the commodity constrained split delivery VRP, Comput. Oper. Res, 112, (2019); Sabar N.R., Bhaskar A., Chung E., Turky A., Song A., An Adaptive Memetic Approach for Heterogeneous Vehicle Routing Problems with two-dimensional loading constraints, Swarm Evol. Comput, 58, (2020); Araee E., Manavizadeh N., Bosjin S.A., Designing a multi-objective model for a hazardous waste routing problem considering flexibility of routes and social effects, J. Ind. Prod. Eng, 37, pp. 33-45, (2020); Ancele Y., Ha M., Lersteau C., Matellini D.B., Nguyen T.T., Toward a more flexible VRP with pickup and delivery allowing consolidations, Transp. Res. Part C Emerg. Technol, 128, (2021); Tirkolaee E.B., Goli A., Pahlevan M., Kordestanizadeh R.M., A robust bi-objective multi-trip periodic capacitated arc routing problem for urban waste collection using a multi-objective invasive weed optimization, Waste Manag. Res, 37, pp. 1089-1101, (2019); Lu J., Chen Y., Hao J.K., He R., The Time-dependent Electric Vehicle Routing Problem: Model and solution, Expert Syst. Appl, 161, (2020); Fachini R.F., Armentano V.A., Logic-based Benders decomposition for the heterogeneous fixed fleet vehicle routing problem with time windows, Comput. Ind. Eng, 148, (2020); Keskin M., Catay B., Laporte G., A simulation-based heuristic for the electric vehicle routing problem with time windows and stochastic waiting times at recharging stations, Comput. Oper. Res, 125, (2021); Neves-Moreira F., Amorim-Lopes M., Amorim P., The multi-period vehicle routing problem with refueling decisions: Traveling further to decrease fuel cost?, Transp. Res. Part E Logist. Transp. Rev, 133, (2020); Nejad Attari M.Y., Torkayesh A.E., Jami E.N., Ant Colony Optimization for Multiple Pickup and Multiple Delivery Vehicle Routing Problem with Time Window and Heterogeneous Fleets, Logistics, 59, (2021); Prajapati D., Zhou F., Zhang M., Chelladurai H., Pratap S., Sustainable logistics network design for multi-products delivery operations in B2B e-commerce platform, Sādhanā, 46, (2021); Cheng C.Y., Chen Y.Y., Chen T.L., Yoo J.J., Using a hybrid approach based on the particle swarm optimization and ant colony optimization to solve a joint order batching and picker routing problem, Int. J. Prod. Econ, 170, pp. 805-814, (2015); Dwivedi A., Jha A., Prajapati D., Sreenu N., Pratap S., Meta-heuristic algorithms for solving the sustainable agro-food grain supply chain network design problem, Mod. Supply Chain Res. Appl, (2020); Gutierrez A., Dieulle L., Labadie N., Velasco N., A multi-population algorithm to solve the VRP with stochastic service and travel times, Comput. Ind. Eng, 125, pp. 144-156, (2018); Wu W., Zhou W., Lin Y., Xie Y., Jin W., A hybrid metaheuristic algorithm for location inventory routing problem with time windows and fuel consumption, Expert Syst. Appl, 166, (2021); Tirkolaee E.B., Hosseinabadi A.A.R., Soltani M., Sangaiah A.K., Wang J., A Hybrid genetic algorithm for multi-trip green capacitated Arc routing problem in the scope of urban services, Sustainability, 10, (2018); Tirkolaee E.B., Mahdavi I., Esfahani M.M.S., Weber G.W., A hybrid augmented ant colony optimization for the multi-trip capacitated arc routing problem under fuzzy demands for urban solid waste management, Waste Manag. Res, 38, pp. 156-172, (2020); Hamdia K.M., Zhuang X., Rabczuk T., An efficient optimization approach for designing machine learning models based on genetic algorithm, Neural Comput. Appl, 33, pp. 1923-1933, (2021); Goodarzian F., Kumar V., Ghasemi P., A set of efficient heuristics and meta-heuristics to solve a multi-objective pharmaceutical supply chain network, Comput. Ind. Eng, 158, (2021); Goodarzian F., Kumar V., Abraham A., Hybrid. Meta-Heuristic Algorithms for a Supply Chain Network Considering Different Carbon Emission Regulations Using Big Data Characteristics, (2021); Daultani Y., Cheikhrouhou N., Pratap S., Prajapati D., Designing Forward and Reverse Supply Chain Network for Refurbished Products, Proceedings of the 9th International Conference on Operations and Supply Chain Management, pp. 1-7; Zhang M., Pratap S., Zhao Z., Prajapati D., Huang G.Q., Forward and reverse logistics vehicle routing problems with time horizons in B2C e-commerce logistics, Int. J. Prod. Res, pp. 1-20, (2020); Prajapati D., Harish A.R., Daultani Y., Singh H., Pratap S., A Clustering Based Routing Heuristic for Last-Mile Logistics in Fresh Food E-Commerce, Glob. Bus. Rev, (2020)","S. Pratap; Department of Mechanical Engineering, Indian Institute of Technology (BHU), Varanasi, 221005, India; email: s.pratapiitkgp@gmail.com",null,"MDPI",{"$nulls":5},2.305629E7,null,null,null,"English","Logist.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85129033274"]
["Coppola P.; Silvestri F.","Coppola, Pierluigi (7003282386); Silvestri, Fulvio (57207925739)","7003282386; 57207925739","ASSESSING THE IMPACTS OF E-COMMERCE ON FUTURE URBAN LOGISTICS SCENARIOS: CASE STUDY OF THE CITY OF ROME",2021.0,"International Journal of Transport Economics",48.0,"2024-04-03",null,339.0,358.0,19.0,4.0,"10.19272/202106704003","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85139798381&doi=10.19272%2f202106704003&partnerID=40&md5=d19a7131151f4eec37ddcad294149e90","Politecnico di Milano, Department of Mechanical Engineering, Campus Bovisa Sud, Via La Masa 1, Milano, 20156, Italy; University of Rome Tor Vergata, Department of Enterprise Engineering, Via del Politecnico 1, Roma, 00133, Italy","Coppola P., Politecnico di Milano, Department of Mechanical Engineering, Campus Bovisa Sud, Via La Masa 1, Milano, 20156, Italy; Silvestri F., University of Rome Tor Vergata, Department of Enterprise Engineering, Via del Politecnico 1, Roma, 00133, Italy","The goal of essentially CO2-free city logistics in major urban centers by 2030 remains one of the most ambitious challenges that still seems very difficult to achieve. The efforts made so far by local governments have barely managed to counteract the freight demand growth in recent years. In this domain, the increasing penetration of the e-commerce (and vehicle flows) can further afflict air quality, traffic congestion, road safety and life quality in urban centers or can be guided by regulation to seize the opportunity to develop more livable cities. This paper aims at assessing the sustainability of future urban logistics developments, with an application to the case study of the city of Rome. Future exploratory scenarios are simulated through an aggregate multi-stage urban freight model and are assessed according to the measurement methodologies recommended by the joint European Monitoring and Evaluation Programme (EMEP)/European Environment Agency (EEA) inventory guidebook. The results show that the e-commerce penetration growth, which mainly implies a fragmentation of deliveries over space and time and an increase of smaller operating Light Goods Vehicles (LGVs), leads to an increase in overall vehicular mileage. This outcome, combined with forecasts on commercial vehicles distributions by fuel and eco-standards highlights that the transition to the latest petrol and diesel engines is already effective for reducing pollutant emissions, but not enough to reduce GHG emissions and energy consumption; for a significant reduction of the latter, a shift towards more eco-sustainable alternative fuels and the optimization of the distances traveled by LGVs appears necessary. © COPYRIGHT BY FABRIZIO SERRA EDITORE, PISA · ROMA.","City Logistics; E-Commerce; Freight Models; Future Scenarios; Last-Mile Deliveries; Sustainability","Europe; assessment method; demand analysis; electronic commerce; freight transport; future prospect; scenario analysis; sustainability; urban development",{"$nulls":6},"ALVES R., LIMA R. D., DE SENA D. C., PINHO D., FERREIRA A., HOLGUIN-VERAS J., Agent-Based Simulation Model for Evaluating Urban Freight Policy to E-Commerce, Sustainability, 11, (2019); CASCETTA E., Transportation Systems Analysis. Models and Applications, (2009); COMI A., DONNELLY R., RUSSO F., Urban Freight Models, Modelling Freight Transport, pp. 163-200, (2014); COPPOLA P., SILVESTRI F., Autonomous vehicles and future mobility solutions, Autonomous Vehicles and Future Mobility, (2019); COPPOLA P., SILVESTRI F., Future mobility and land use scenarios: impact assessment with an urban case study, TransportationResearchProcedia, 42, pp. 53-63, (2020); CRAINIC T. G., RICCIARDI N., STORCHI G., Models for Evaluating and Planning City Logistics Systems, Transportation Science, 43, 4, pp. 432-454, (2009); Roadmap to a Single European Transport Area - Towards a competitive and resource efficient transport system, (2011); The European Green Deal, (2019); EMEP/EEA air pollutant emission inventory guidebook 2019, (2019); ELBERT R., FRIEDRICH C., BOLTZE M., PFOHL H.-C., Urban Freight Transportation Systems: current trends and prospects for the future, pp. 265-276, (2020); Topic Guide. Sustainable Urban Logistics Planning, (2019); Guidelines. 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La transizione verso una mobilità sostenibile, (2019)","F. Silvestri; University of Rome Tor Vergata, Department of Enterprise Engineering, Roma, Via del Politecnico 1, 00133, Italy; email: fulvio.silvestri@uniroma2.it",null,"Fabrizio Serra Editore Srl",{"$nulls":5},3035247.0,null,null,null,"English","Int. J. Transp. Econ.","Article","Final",null,"Scopus","2-s2.0-85139798381"]
["Ouyang J.; Chen X.","Ouyang, Ju (57458835200); Chen, Xianping (57458380200)","57458835200; 57458380200","Personal Information Two-dimensional Code Encryption Technology in the Process of E-commerce Logistics Transportation",2022.0,"SAIEE Africa Research Journal",113.0,1.0,null,52.0,57.0,5.0,3.0,"10.23919/SAIEE.2022.9695425","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124883542&doi=10.23919%2fSAIEE.2022.9695425&partnerID=40&md5=84a32362c13d5b2eafaff246c8ce1c67","Zhejiang Yuying College of Vocational Technology, Zhejiang, Hangzhou, 310018, China","Ouyang J., Zhejiang Yuying College of Vocational Technology, Zhejiang, Hangzhou, 310018, China; Chen X., Zhejiang Yuying College of Vocational Technology, Zhejiang, Hangzhou, 310018, China","The popularity of the Internet has given birth to e-commerce and promoted the development of logistics industry. Traditional logistics is frail in personal information confidentiality, and it is easy to leak privacy information in the process of logistics. This paper briefly introduced the channels of privacy information disclosure in the process of e-commerce logistics and the privacy information encryption system based on two-dimensional code. Then, the privacy protective effect of the system was tested on the laboratory server. The results showed that mobile terminals with different permissions only obtained some necessary logistics information within their respective permissions in the normal process; the mobile terminals distinguished two-dimensional codes that did not belong to express mails, and only meaningless error codes were obtained after the mobile terminal without permissions scanned the code in the abnormal process. In conclusion, the encryption technology of personal information based on two-dimensional code can effectively protect the privacy information in the process of logistics. © 2022 South African Institute of Electrical Engineers. All rights reserved.","E-commerce; Logistics; Personal information encryption; Two-dimensional code","Computer terminals; Data privacy; Electronic commerce; Mobile telecommunication systems; Code encryption; E- commerces; Encryption technologies; Information disclosure; Logistics industry; Logistics transportations; Personal information; Personal information encryption; Privacy information; Two-dimensional codes; Cryptography",{"$nulls":6},"Qian J., Du X., Zhang B., Fan B., Yang X., Optimization of QR code readability in movement state using response surface methodology for implementing continuous chain traceability, Comput. Electron. Agr, 139, pp. 56-64, (2017); Xiao X., Fu Z., Zhang Y., Peng Z., Zhang X., SMS-CQ: A Quality and Safety Traceability System for Aquatic Products in Cold-Chain Integrated WSN and QR Code, J. Food Process Eng, 40, 1, (2017); Di Y. J., Shi J. P., Mao G. Y., A QR code identification technology in package auto-sorting system, Mod. Phys. Lett. B, 31, 19-21, (2017); Zhang X., Li H., Yang Y., Sun G., Chen G., LIPPS: Logistics Information Privacy Protection System Based on Encrypted QR Code, 2016 IEEE Trustcom/BigDataSE/I SPA, (2016); Han Q., Du C., Yao Y., Lei L., A New Express Management System Based on Encrypted QR Code, International Conference on Intelligent Computation Technology & Automation, (2016); Lin P. Y., Distributed Secret Sharing Approach with Cheater Prevention based on QR Code, IEEE T. Ind. Inform, 12, 1, pp. 384-392, (2016); Jiang B., Prater E., Distribution and logistics development in China, Int. J. Phys. Distr. Log, 32, 9, pp. 783-798, (2015); Xiang H., Xiao H., Yuan W., Research optimization on logistics distribution center location based on adaptive particle swarm algorithm, Optik - Int. J. Light Electr. Opt, 127, 20, pp. 8443-8450, (2016); Kumar R., Bhaduri B., Hennelly B., QR code-based non-linear image encryption using Shearlet transform and spiral phase transform, J. Mod. Optic, pp. 1-10, (2017); Fimiani G., Supporting Privacy in a Cloud-Based Health Information System by Means of Fuzzy Conditional Identity-Based Proxy Re-encryption (FCI-PRE), International Conference on Advanced Information Networking & Applications Workshops, pp. 569-572, (2018); Hua Z., Zhou Y., Pun C. M., Chen C. L. P., 2D Sine Logistic modulation map for image encryption, Inform. Sciences, 297, C, pp. 80-94, (2015); Yang L., Tang S., Ran L., Zhang L., Ma Z., Secure and robust digital image watermarking scheme using logistic and RSA encryption, Expert Syst. Appl, 97, pp. 95-105, (2018); Aono Y., Hayashi T., Le T. P., Wang L., Privacy-Preserving Logistic Regression with Distributed Data Sources via Homomorphic Encryption, IEICE T. Inf. Syst, E99.D, 8, pp. 2079-2089, (2016); Sujatha M., Noronha V. C., Monteiro A. T., Johar R., Roja M. M., Dual-Layer Video Encryption using RSA Algorithm, Int. J. Comput. Appl, 116, 1, pp. 3-40, (2015); Iovane G., Amorosia A., Benedetto E., Lamponi G., An Information Fusion approach based on prime numbers coming from RSA algorithm and Fractals for secure coding, J. Discrete Math. Sci. C, 18, 5, (2015)","X. Chen; Zhejiang Yuying College of Vocational Technology, Hangzhou, Zhejiang, 310018, China; email: p7939x@yeah.net",null,"South African Institute of Electrical Engineers",{"$nulls":5},1.9911696E7,null,null,null,"English","SAIEE Afr. Res. J.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85124883542"]
["Ding Y.; Guo B.; Zheng L.; Lu M.; Zhang D.; Wang S.; Son S.H.; He T.","Ding, Yi (57223811516); Guo, Baoshen (57219246087); Zheng, Lin (57196081413); Lu, Mingming (55276383700); Zhang, Desheng (54685570200); Wang, Shuai (57251375100); Son, Sang Hyuk (7202529973); He, Tian (14019293900)","57223811516; 57219246087; 57196081413; 55276383700; 54685570200; 57251375100; 7202529973; 14019293900","A City-Wide Crowdsourcing Delivery System with Reinforcement Learning",2021.0,"Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies",5.0,3.0,3478117.0,null,null,null,16.0,"10.1145/3478117","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85115197698&doi=10.1145%2f3478117&partnerID=40&md5=3b6bf685f56cb338f73b2f25fd2f102e","Alibaba Group, Shanghai, China; University of Minnesota, Minneapolis, United States; Southeast University, Nanjing, China; Central South University, Changsha, China; Rutgers University, United States; Dgist, South Korea","Ding Y., Alibaba Group, Shanghai, China, University of Minnesota, Minneapolis, United States; Guo B., Southeast University, Nanjing, China; Zheng L., Central South University, Changsha, China; Lu M., Central South University, Changsha, China; Zhang D., Rutgers University, United States; Wang S., Southeast University, Nanjing, China; Son S.H., Dgist, South Korea; He T., Alibaba Group, Shanghai, China, University of Minnesota, Minneapolis, United States","The revolution of online shopping in recent years demands corresponding evolution in delivery services in urban areas. To cater to this trend, delivery by the crowd has become an alternative to the traditional delivery services thanks to the advances in ubiquitous computing. Notably, some studies use public transportation for crowdsourcing delivery, given its low-cost delivery network with millions of passengers as potential couriers. However, multiple practical impact factors are not considered in existing public-transport-based crowdsourcing delivery studies due to a lack of data and limited ubiquitous computing infrastructures in the past. In this work, we design a crowdsourcing delivery system based on public transport, considering the practical factors of time constraints, multi-hop delivery, and profits. To incorporate the impact factors, we build a reinforcement learning model to learn the optimal order dispatching strategies from massive passenger data and package data. The order dispatching problem is formulated as a sequential decision making problem for the packages routing, i.e., select the next station for the package. A delivery time estimation module is designed to accelerate the training process and provide statistical delivery time guarantee. Three months of real-world public transportation data and one month of package delivery data from an on-demand delivery platform in Shenzhen are used in the evaluation. Compared with existing crowdsourcing delivery algorithms and widely used baselines, we achieve a 40% increase in profit rates and a 29% increase in delivery rates. Comparison with other reinforcement learning algorithms shows that we can improve the profit rate and the delivery rate by 9% and 8% by using time estimation in action filtering. We share the data used in the project to the community for other researchers to validate our results and conduct further research.1 [1]. © 2021 ACM.","Crowdsourced Labor; Crowdsourcing; Reinforcement Learning; Sharing Economy","Crowdsourcing; Decision making; Learning systems; Profitability; Reinforcement learning; Ubiquitous computing; Dispatching problem; Optimal order dispatching; Package delivery; Public transportation; Reinforcement learning models; Sequential decision making; Time constraints; Ubiquitous computing infrastructure; Learning algorithms",{"$nulls":4},"China National Key R&D Program, (2018YFB2100302); National Natural Science Foundation of China, NSFC, (61902066); Natural Science Foundation of Jiangsu Province, (BK20190336); Fundamental Research Funds for the Central Universities, (2242021R41068)","The authors would like to thank anonymous reviewers for their valuable comments and suggestions. Prof. Shuai Wang is partially supported by the National Natural Science Foundation of China under Grant No. 61902066, Natural Science Foundation of Jiangsu Province under Grant No. BK20190336, China National Key R&D Program 2018YFB2100302 and Fundamental Research Funds for the Central Universities under Grant No. 2242021R41068.","Local Service BU. 2021. 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ACM Interact. Mob. Wearable Ubiquitous Technol.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85115197698"]
["Yang Y.","Yang, Ying (57463781000)",5.7463781E10,"Selection Method of Cross-Border e-Commerce Export Logistics Mode Based on Collaborative Filtering Algorithm",2022.0,"Journal of Mathematics",2022.0,null,6885432.0,null,null,null,8.0,"10.1155/2022/6885432","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85125122337&doi=10.1155%2f2022%2f6885432&partnerID=40&md5=53e0e52471b33a13d11f208282526fff","School of Economics, Henan Institute of Technology, Henan, Xinxiang, 453003, China","Yang Y., School of Economics, Henan Institute of Technology, Henan, Xinxiang, 453003, China","The combination of the Internet and foreign trade has promoted the rapid development of cross-border e-commerce, and cross-border e-commerce logistics has risen due to the development of cross-border e-commerce. However, the costs incurred by enterprises in the operation of intermediate logistics links have remained high for many years. Considering the cross-border electricity export logistics mode selection, the author of this paper tackles the main existing problems, using literature study, field survey method, case analysis and the collaborative filtering method of major consumer goods export logistics mode, and the advantages and disadvantages in the enterprise' internal and external environmental analysis and evaluation, and puts forward a scientific logistics coordination mechanism and new export logistics mode. Firstly, the development background of cross-border e-commerce logistics is sorted out, and the research content, research method, and research framework are proposed based on the theoretical research of relevant scholars. Secondly, several logistics modes of cross-border e-commerce export are summarized, including international postal parcel, international express, international special line, etc., and the indicator system of logistics mode selection is determined through comparative analysis of application scope and advantages and disadvantages. Secondly, a logistics selection model based on collaborative filtering algorithm is constructed, and the model is verified by a practical case of a specific export cross-border e-commerce company. Finally, the research conclusions and application strategies of this paper are proposed, so as to provide the most appropriate logistics mode and guarantee suggestions for cross-border e-commerce enterprises and provide ideas and methods for cross-border e-commerce enterprises to choose international logistics mode for different types of import and export goods. The significance of this study was aimed at the current cross-border electricity development mainly by restricting factors, planning the most suitable for the development of China's cross-border electronic business logistics mode, to some extent, and it has enriched the cross-border electricity business related research in the field of logistics, to inspire transformation of foreign trade enterprises, so as to better promote the cross-border electricity business healthy and orderly development and export logistics mode optimization selection. © 2022 Ying Yang.",{"$nulls":8},"Hsiao Y.H., Chen M.C., Logistics service design for cross-border e-commerce using kansei engineering with text-mining-based online content analysis, Telematics and Informatics, 13, 11, pp. 11-18, (2016); Ribadu M.B., Wan N.W., An integrated approach towards Sharia compliance E-commerce trust, Applied Computing and Informatics, 15, pp. 1-6, (2019); Van Asch T., Dewulf W., Ivan F.K., Eddy C., De Voorde V., Cross-border e-commerce logistics-Strategic success factors for airports, Research in Transportation Economics, 3, pp. 167-192, (2017); 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Nan J., Tao J., Juan D., Personalized recommendation based on customer preference mining and sentiment assessment from a Chinese e-commerce website, Electronic Commerce Research, 1, pp. 1-21, (2018); Isinkaye F.O., Folajimi Y.O., Ojokoh B.A., Recommendation systems: Principles, methods and evaluation, Egyptian Informatics Journal, 16, 3, pp. 261-273, (2015); Yan H., Jiang Y., Gao Z., Exploring Hidden Factors behind Online Food Shopping from Amazon Reviews: A Topic Mining Approach, pp. 1-26; Sondur S., Chigadani A., Nayak S., Similarity measures for recommender systems: A comparative study, Journal of Research, 2, 3, pp. 76-80, (2016); Dafedar F., Bharati K.F., A Fast Collaborative Filtering Approach for Web Personalized Recommendation System, pp. 1-7; Almutairi F.M., Sidiropoulos N.D., Karypis G., Context-aware recommendation-based learning analytics using tensor and coupled matrix factorization, IEEE Journal of Selected Topics in Signal Processing, 11, 5, pp. 729-741, (2016)","Y. Yang; School of Economics, Henan Institute of Technology, Xinxiang, Henan, 453003, China; email: yangying@hait.edu.cn",null,"Hindawi Limited",{"$nulls":5},2.3144629E7,null,null,null,"English","J. Math.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85125122337"]
["Kawa A.; Światowiec-Szczepańska J.","Kawa, Arkadiusz (23090707300); Światowiec-Szczepańska, Justyna (55308169900)","23090707300; 55308169900","Logistics as a value in e-commerce and its influence on satisfaction in industries: a multilevel analysis",2021.0,"Journal of Business and Industrial Marketing",36.0,13.0,null,220.0,235.0,15.0,14.0,"10.1108/JBIM-09-2020-0429","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85108174736&doi=10.1108%2fJBIM-09-2020-0429&partnerID=40&md5=01a9e5b7a93ac3697aaeba7f5fb8dde5","Poznan University of Economics, Poznan, Poland","Kawa A., Poznan University of Economics, Poznan, Poland; Światowiec-Szczepańska J., Poznan University of Economics, Poznan, Poland","Purpose: The purpose of this paper is to identify the components of logistics value and examine their influence on customer satisfaction in e-commerce. This study investigates the moderation effect between those two variables using the overall service level in the different industries of e-commerce. Design/methodology/approach: A total of 592 correctly filled questionnaires from telephone and web interviews (computer-assisted telephone interviews and computer-assisted web interviews) were scrutinized. Hierarchical linear modeling (as a part of a wider group of multilevel modeling studies) was used to verify the dependencies between variables from an organization and industry levels. Findings: The logistics factors indicated and described in the paper differently affect the value for the customer. This value is subjective and dynamic. For this reason, the online seller should develop a system to create a sustainable value proposition. It is plausible due to the possibility of choosing the type of delivery, date of collection and change thereof, as well as that of returning the product. Because of all this, the customer decides on the way of the order execution and creates the value chain. Research limitations/implications: The developed model is aimed at identifying universal relationships that create the customer satisfaction mechanism for the logistics value. However, this may result in other aspects of customer satisfaction being neglected. The authors are aware that the creation of value by a company in e-commerce must be approached in a systematic manner. Practical implications: The results obtained and the representativeness of the surveyed sample of companies lead to the formulation of implications for business practice. The conclusions of the research definitely indicate a need to build awareness of logistics value and its influence on customer satisfaction through the service level in the industry. Because of the identified components of the logistics value and industry characteristics, managers of online retailers can better run their businesses, increase customer satisfaction, and thus improve their performance. Originality/value: It is the first study that concerns e-commerce in individual industries, with particular emphasis on logistics and its impact on customer satisfaction. © 2021, Arkadiusz Kawa and Justyna Światowiec-Szczepańska.","E-commerce; HLM; Industries; Logistics value; Multilevel analysis",{"$nulls":7},"Antipov E.A., An HLM-model of online price premia, Economics Bulletin, 34, 2, pp. 892-900, (2014); Chen Q., Zhang N., Does e-commerce provide a sustained competitive advantage? 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["Strauss A.; Gülpınar N.; Zheng Y.","Strauss, Arne (36648125000); Gülpınar, Nalan (6507170240); Zheng, Yijun (57216351028)","36648125000; 6507170240; 57216351028","Dynamic pricing of flexible time slots for attended home delivery",2021.0,"European Journal of Operational Research",294.0,3.0,null,1022.0,1041.0,19.0,28.0,"10.1016/j.ejor.2020.03.007","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85083249830&doi=10.1016%2fj.ejor.2020.03.007&partnerID=40&md5=21ca2a30c3ef997ecaed7b34d7fbdd89","Mercator Endowed Chair of Demand Management & Sustainable Transport, WHU – Otto Beisheim School of Management, Vallendar, 56179, Germany; Warwick Business School, University of Warwick, Coventry, CV4 7AL, United Kingdom","Strauss A., Mercator Endowed Chair of Demand Management & Sustainable Transport, WHU – Otto Beisheim School of Management, Vallendar, 56179, Germany; Gülpınar N., Warwick Business School, University of Warwick, Coventry, CV4 7AL, United Kingdom; Zheng Y., Warwick Business School, University of Warwick, Coventry, CV4 7AL, United Kingdom","In e-commerce, customers are usually offered a menu of home delivery time windows of which they need to select exactly one, even though at least some customers may be more flexible. To exploit the flexibility of such customers, we propose to introduce flexible delivery time slots, defined as any combination of such regular time windows (not necessarily adjacent). In selecting a flexible time slot (out of a set of windows that form the flexible product), the customer agrees to be informed only shortly prior to the dispatching of the delivery vehicle in which regular time window the goods will arrive. In return for providing this flexibility, the company may offer the customer a reduced delivery charge and/or highlight the environmental benefits. Our framework also can accommodate customized flexible slots where customers can self-select a set of regular slots in which a delivery may take place. The vehicle routing problem (VRP) in the presence of flexible time slots bookings corresponds to a VRP with multiple time windows. We build on literature on demand management and vehicle routing for attended home delivery, as well as on flexible products. These two concepts have not yet been combined, and indeed the results from the flexible products literature do not carry over directly because future expected vehicle routing implications need to be taken into account. The main methodological contribution is the development of a tractable linear programming formulation that links demand management decisions and routing cost implications, whilst accounting for customer choice behavior. The output of this linear program provides information on the (approximate) opportunity cost associated with specific orders and informs a tractable dynamic pricing policy for regular and flexible slots. Numerical experiments, based on realistically-sized scenarios, indicate that expected profit may increase significantly depending on demand intensity when adding flexible slots rather than using only regular slots. © 2020 Elsevier B.V.","Dynamic programming; E-commerce; Flexible product; Revenue management","Linear programming; Sales; Vehicle routing; Vehicles; Dynamic pricing policies; Environmental benefits; Linear programming formulation; Management decisions; Methodological contributions; Multiple time windows; Numerical experiments; Vehicle routing problem; Costs",{"$nulls":6},"Agatz N., Campbell A., Fleischmann M., Savelsbergh M., Time slot management in attended home delivery, Transportation Science, 45, 3, pp. 435-449, (2011); Agatz N., Campbell A.M., Fleischmann M., Van Nunen J., Savelsbergh M., Revenue management opportunities for Internet retailers, Journal of Revenue and Pricing Management, 12, 2, pp. 128-138, (2013); Agatz N., Fleischmann M., Van Nunen J.A.E.E., E-fulfillment and multi-channel distribution–A review, European Journal of Operational Research, 187, 2, pp. 339-356, (2008); Asdemir K., Jacob V.S., Krishnan R., Dynamic pricing of multiple home delivery options, European Journal of Operational Research, 196, 1, pp. 246-257, (2009); Belhaiza S., Hansen P., Laporte G., A hybrid variable neighborhood tabu search heuristic for the vehicle routing problem with multiple time windows, Computers & Operations Research, 52, pp. 269-281, (2014); Buhler D., Klein R., Neugebauer M., Model-based delivery cost approximation in attended home services, Computers & Industrial Engineering, 98, pp. 78-90, (2016); Campbell A.M., Savelsbergh M., Incentive schemes for attended home delivery services, Transportation Science, 40, 3, pp. 327-341, (2006); Campbell A.M., Savelsbergh M.W.P., Decision support for consumer direct grocery initiatives, Transportation Science, 39, 3, pp. 313-327, (2005); Cleophas C., Ehmke J.F., When Are Deliveries Profitable?, Business & Information Systems Engineering, 6, 3, pp. 153-163, (2014); Daganzo C.F., Modeling distribution problems with time windows. 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Strauss; Mercator Endowed Chair of Demand Management & Sustainable Transport, WHU – Otto Beisheim School of Management, Vallendar, 56179, Germany; email: arne.strauss@whu.edu",null,"Elsevier B.V.",{"$nulls":5},3772217.0,null,"EJORD",null,"English","Eur J Oper Res","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85083249830"]
["Sadati M.E.H.; Akbari V.; Çatay B.","Sadati, Mir Ehsan Hesam (57219624631); Akbari, Vahid (57073546700); Çatay, Bülent (6505945515)","57219624631; 57073546700; 6505945515","Electric vehicle routing problem with flexible deliveries",2022.0,"International Journal of Production Research",60.0,13.0,null,4268.0,4294.0,26.0,20.0,"10.1080/00207543.2022.2032451","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124736060&doi=10.1080%2f00207543.2022.2032451&partnerID=40&md5=7927926309a2d382a4c37dc7e6a88297","Faculty of Engineering and Natural Sciences, Sabanci University, Istanbul, Turkey; Smart Mobility and Logistics Lab, Sabanci University, Istanbul, Turkey; Nottingham University Business School, University of Nottingham, Jubilee Campus, Nottingham, United Kingdom","Sadati M.E.H., Faculty of Engineering and Natural Sciences, Sabanci University, Istanbul, Turkey, Smart Mobility and Logistics Lab, Sabanci University, Istanbul, Turkey; Akbari V., Nottingham University Business School, University of Nottingham, Jubilee Campus, Nottingham, United Kingdom; Çatay B., Faculty of Engineering and Natural Sciences, Sabanci University, Istanbul, Turkey, Smart Mobility and Logistics Lab, Sabanci University, Istanbul, Turkey","Growing concerns about the climate change have forced governments to initiate tighter environmental regulations and tougher emission reduction targets, increasing the interest on electromobility. Logistics operators started employing electric vehicles (EVs) and must face new operational planning challenges. Moreover, with an ever-growing interest in e-commerce, parcel delivery is taking new shapes by offering flexible delivery options to the customers. To mitigate these issues, we introduce the Electric Vehicle Routing Problem with Flexible Deliveries (EVRP-FD), where the customers are served using a fleet of EVs that can recharge their batteries along their routes. In this problem, a customer may specify different delivery locations for different time windows. Our objective is to serve the customers while minimising the total travelled distance using minimum number of vehicles. We first give the mathematical model and then develop a hybrid Variable Neighbourhood Search coupled with Tabu Search by proposing new mechanisms to solve the problem effectively. Then, we verify the performance of our algorithm on instances from the literature. We also introduce new instances for the EVRP-FD and perform an extensive computational study to investigate the trade-offs associated with different operational factors. Finally, we present a case study in Nottingham, UK to provide further insights. © 2022 Informa UK Limited, trading as Taylor & Francis Group.","Electric vehicle routing problem; flexible deliveries; granular tabu search; recharging; variable neighbourhood search","Climate change; Economic and social effects; Electric vehicles; Emission control; Environmental regulations; Finite difference method; Fleet operations; International trade; Sales; Vehicle routing; E- commerces; Electric vehicle routing problem; Electromobility; Emission reduction targets; Flexible delivery; Granular tabu search; Operational planning; Recharging; Variable neighborhood search; Vehicle Routing Problems; Tabu search",{"$nulls":6},"Abbasi B., Niaki S.T.A., Khalife M.A., Faize Y., A Hybrid Variable Neighborhood Search and Simulated Annealing Algorithm to Estimate the Three Parameters of the Weibull Distribution, Expert Systems with Applications, 38, 1, pp. 700-708, (2011); Aras N., Aksen D., Tekin M.T., Selective Multi-Depot Vehicle Routing Problem with Pricing, Transportation Research Part C: Emerging Technologies, 19, 5, pp. 866-884, (2011); Baker R., Cochran L.K., Norboge N.D., Moran M.M., Wagner J.A., Storey B.J., (2016); Baniamerian A., Bashiri M., Tavakkoli-Moghaddam R., Modified Variable Neighborhood Search and Genetic Algorithm for Profitable Heterogeneous Vehicle Routing Problem with Cross-Docking, Applied Soft Computing, 75, pp. 441-460, (2019); Beheshti A.K., Hejazi S.R., Alinaghian M., The Vehicle Routing Problem with Multiple Prioritized Time Windows: A Case Study, Computers & Industrial Engineering, 90, pp. 402-413, (2015); Belhaiza S., Hansen P., Laporte G., A Hybrid Variable Neighborhood Tabu Search Heuristic for the Vehicle Routing Problem with Multiple Time Windows, Computers & Operations Research, 52, pp. 269-281, (2014); Bortfeldt A., Hahn T., Mannel D., Monch L., Hybrid Algorithms for the Vehicle Routing Problem with Clustered Backhauls and 3D Loading Constraints, European Journal of Operational Research, 243, 1, pp. 82-96, (2015); Bruglieri M., Mancini S., Pezzella F., Pisacane O., A New Mathematical Programming Model for the Green Vehicle Routing Problem, Electronic Notes in Discrete Mathematics, 55, pp. 89-92, (2016); Bruglieri M., Pezzella F., Pisacane O., Suraci S., A Variable Neighborhood Search Branching for the Electric Vehicle Routing Problem with Time Windows, Electron. 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Çatay; Nottingham University Business School, University of Nottingham, Nottingham, Jubilee Campus, United Kingdom; email: catay@sabanciuniv.edu",null,"Taylor and Francis Ltd.",{"$nulls":5},207543.0,null,"IJPRB",null,"English","Int J Prod Res","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85124736060"]
["Khan S.; Alourani A.; Mishra B.; Ali A.; Kamal M.","Khan, Shahnawaz (57203386251); Alourani, Abdullah (57189035657); Mishra, Bharavi (57210470615); Ali, Ashraf (57395594800); Kamal, Mustafa (57193871087)","57203386251; 57189035657; 57210470615; 57395594800; 57193871087","Developing a Credit Card Fraud Detection Model using Machine Learning Approaches",2022.0,"International Journal of Advanced Computer Science and Applications",13.0,3.0,null,411.0,418.0,7.0,7.0,"10.14569/IJACSA.2022.0130350","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85129730934&doi=10.14569%2fIJACSA.2022.0130350&partnerID=40&md5=3a68579e7fbaf6c26688d901ba4964b9","Faculty of Engineering, Design and Information & Communications Technology, Bahrain Polytechnic, Isa Town, Bahrain; Department of Computer Science and Information, College of Science in Zulfi, Majmaah University, Al-Majmaah, 11952, Saudi Arabia; Department of Computer Science & Engineering, The LNM Institute of Information Technology, Rajasthan, Jaipur, India; Faculty of Computer Studies, Arab Open University, Bahrain; College of Science & Theoretical Studies, Saudi Electronic University, Dammam, Saudi Arabia","Khan S., Faculty of Engineering, Design and Information & Communications Technology, Bahrain Polytechnic, Isa Town, Bahrain; Alourani A., Department of Computer Science and Information, College of Science in Zulfi, Majmaah University, Al-Majmaah, 11952, Saudi Arabia; Mishra B., Department of Computer Science & Engineering, The LNM Institute of Information Technology, Rajasthan, Jaipur, India; Ali A., Faculty of Computer Studies, Arab Open University, Bahrain; Kamal M., College of Science & Theoretical Studies, Saudi Electronic University, Dammam, Saudi Arabia","The growing application and usage of e-commerce applications have given an exponential rise to the number of online transactions. Though there are several methods for completing online transactions, however, credit cards are most commonly used. The increased number of transactions has given the opportunity to the fraudsters to mislead the customers and make them execute fraudulent transactions. Therefore, there is a need for such a method that can automatically classify detect fraudulent transactions. This research study aims to develop a credit-card fraud detection model that can effectively classify an online transaction as fraudulent or genuine. Three supervised machine learning approaches have been applied to develop a credit-card fraud classifier. These techniques include logistic regression, artificial intelligence and support vector machine. The classification accuracy achieved by all the classifiers is almost similar. This research has used the confusion matrix and area under the curve to demonstrate the score of the different performance measures and evaluate the overall performance of the classifiers. Several performance measures such as accuracy, precision, recall, F1-measure, Matthews correlation coefficient, receiver operating characteristic curve have been computed and analysed to evaluate the performance of the credit-card fraud detection classifiers. The analysis demonstrates that the support vector machine-based classifier outperforms the other classifiers. © 2022. International Journal of Communication Networks and Information Security. All Rights Reserved.","Credit card fraud detection; Logistic regression; Neural network; Performance measures; Support vector machine","Crime; Logistic regression; Credit card fraud detections; Detection models; E-Commerce applications; Fraudulent transactions; Machine learning approaches; Neural-networks; Online transaction; Performance; Performance measure; Support vectors machine; Support vector machines",{"$nulls":6},"Altyeb A. A., Malebary S. 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L., A customized classification algorithm for credit card fraud detection, Engineering Applications of Artificial Intelligence, 72, pp. 21-29, (2018); Fiore U., De Santis A., Perla F., Zanetti P., Palmieri F., Using generative adversarial networks for improving classification effectiveness in credit card fraud detection, Information Sciences, (2017); Jurgovsky J., Granitzer M., Ziegler K., Calabretto S., Portier P.-E., He-Guelton L., Caelen O., Sequence classification for creditcard fraud detection, Expert Systems with Applications, 100, pp. 234-245, (2018); Khan S. N., Usman I., Amodel for english to urdu and hindi machine translation system using translation rules and artificial neural network, Int. Arab J. Inf. Technol, 16, 1, pp. 125-131, (2019); Khan S., Mishra R. B., Translation rules and ANN based model for English to Urdu machine translation, INFOCOMP Journal of Computer Science, 10, 3, pp. 36-47, (2011); Khan S., Mishra R. B., A neural network based approach for English to Hindi machine translation, (2012); Khan S., Thirunavukkarasu K., Hammad R., Bali V., Qader M. R., Convolutional neural network based SARS-CoV-2 patients detection model using CT images, International Journal of Intelligent Engineering Informatics, 9, 2, pp. 211-228, (2021); Kumar M. S., Soundarya V., Kavitha S., Keerthika E. S., Aswini E., Credit Card Fraud Detection Using Random Forest Algorithm, 2019 3rd International Conference on Computing and Communications Technologies (ICCCT), (2019); Le Borgne Yann-A., Bontempi Gianluca, Machine Learning for Credit Card Fraud Detection - Practical Handbook, (2021); Lucas Y., Portier P. E., Laporte L., He-Guelton L., Caelen O., Granitzer M., Calabretto S., Towards automated feature engineering for credit card fraud detection using multi-perspective HMMs, Future Generation Computer Systems, 102, pp. 393-402, (2020); Lusted L. B., Signal detectability and medical decision-making, Science, 171, 3977, pp. 1217-1219, (1971); Makki S., Assaghir Z., Taher Y., Haque R., Hacid M.-S., Zeineddine H., An Experimental Study with Imbalanced Classification Approaches for Credit Card Fraud Detection, IEEE Access, (2019); Maniraj S. P., Saini A., Ahmed S., Sarkar S., Credit card fraud detection using machine learning and data science, International Journal of Engineering Research and, 8, (2019); Matthews B. W., Comparison of the predicted and observed secondary structure of T4 phage lysozyme, Biochimica et Biophysica Acta (BBA) - Protein Structure, 405, 2, pp. 442-451, (1975); Pumsirirat A., Yan L., Credit card fraud detection using deep learning based on auto-encoder and restricted boltzmann machine, International Journal of advanced computer science and applications, 9, 1, pp. 18-25, (2018); Qader M. 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R., ANN and rule based model for English to Urdu-Hindi machine translation system, Proceedings of National Conference on Artificial Intelligence and agents: Theory& Application, AIAIATA, pp. 115-121, (2011); Szmigiera M., Value of fraudulent card transactions worldwide 2021-2027, (2021); Xuan S., Liu G., Li Z., Zheng L., Wang S., Jiang C., Random forest for credit card fraud detection, 2018 IEEE 15th International Conference on Networking, Sensing and Control (ICNSC), (2018); Zhang X., Han Y., Xu W., Wang Q., HOBA: A Novel Feature Engineering Methodology for Credit Card Fraud Detection with a Deep Learning Architecture, Information Sciences, (2019)",null,null,"Science and Information Organization",{"$nulls":5},"2158107X",null,null,null,"English","Intl. J. Adv.  Comput. Sci. Appl.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85129730934"]
["Yu V.F.; Susanto H.; Jodiawan P.; Ho T.-W.; Lin S.-W.; Huang Y.-T.","Yu, Vincent F. (24330397100); Susanto, Hadi (57457309200); Jodiawan, Panca (57213266350); Ho, Tsai-Wei (57482915400); Lin, Shih-Wei (7407153943); Huang, Yu-Tsung (57457681200)","24330397100; 57457309200; 57213266350; 57482915400; 7407153943; 57457681200","A Simulated Annealing Algorithm for the Vehicle Routing Problem With Parcel Lockers",2022.0,"IEEE Access",10.0,null,null,20764.0,20782.0,18.0,21.0,"10.1109/ACCESS.2022.3152062","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124813706&doi=10.1109%2fACCESS.2022.3152062&partnerID=40&md5=3e805c1f19a504712c7226359ca591e7","Department of Industrial Management, National Taiwan University of Science and Technology, Taipei, 106, Taiwan; Center for Cyber-Physical Innovation, National Taiwan University of Science and Technology, Taipei, 106, Taiwan; Universal Global Scientific Industrial Company Ltd., Nantou, 542, Taiwan; Department of Information Management, Chang Gung University, Taoyuan, 333, Taiwan; Department of Industrial Engineering and Management, Ming Chi University of Technology, New Taipei City, 243, Taiwan; Department of Neurology, Linkou Chang Gung Memorial Hospital, Taoyuan, 333, Taiwan; Kerry TJ Logistics Company Ltd., Taipei, 100, Taiwan","Yu V.F., Department of Industrial Management, National Taiwan University of Science and Technology, Taipei, 106, Taiwan, Center for Cyber-Physical Innovation, National Taiwan University of Science and Technology, Taipei, 106, Taiwan; Susanto H., Department of Industrial Management, National Taiwan University of Science and Technology, Taipei, 106, Taiwan; Jodiawan P., Department of Industrial Management, National Taiwan University of Science and Technology, Taipei, 106, Taiwan; Ho T.-W., Universal Global Scientific Industrial Company Ltd., Nantou, 542, Taiwan; Lin S.-W., Department of Information Management, Chang Gung University, Taoyuan, 333, Taiwan, Department of Industrial Engineering and Management, Ming Chi University of Technology, New Taipei City, 243, Taiwan, Department of Neurology, Linkou Chang Gung Memorial Hospital, Taoyuan, 333, Taiwan; Huang Y.-T., Kerry TJ Logistics Company Ltd., Taipei, 100, Taiwan","Due to the growth in e-commerce, city logistics needs to cope with the rise of customers' demand. Consequently, it adds to the complexity of the last-mile delivery process. Moreover, this process often contributes significantly to the distribution cost of companies. An alternative to alleviate the problem is the utilization of parcel lockers. It allows the delivery to be extended not only for home delivery but also for locker delivery, which brings several advantages in terms of cost-saving. However, considering multiple delivery options means adding new complexity to the delivery system. In the previous works, vehicle routing problem with time windows (VRPTW) has been widely dealt by only considering home delivery. This research proposes a new VRPTW variant by adding locker delivery as one of the delivery options. The developed problem is called the vehicle routing problem with parcel lockers (VRPPL). The goal of VRPPL is to minimize the total traveling cost. In this research, we formulate a new mathematical programming model and develop a simulated annealing (SA) algorithm to deal with VRPPL. A newly generated set of instances was developed from the well-known Solomon's VRPTW instances. The performance of the proposed algorithm is also presented.  © 2013 IEEE.","delivery options; parcel locker; simulated annealing; time window; Vehicle routing problem","Locks (fasteners); Logistics; Mathematical programming; Vehicle routing; Vehicles; Annealing algorithm; Delivery option; E- commerces; Home delivery; Metaheuristic; Parcel locker; Routings; Time windows; Vehicle routing problem with time windows; Vehicle Routing Problems; Simulated annealing",{"$nulls":6},"Global Retail E-Commerce Market Size 2014-2021. Statista, (2014); Wang Y., Zhang D., Liu Q., Shen F., Lee L.H., Towards enhancing the last-mile delivery: An effective crowd-tasking model with scalable solutions, Transp. Res. E, Logistics Transp. Rev., 93, pp. 279-293, (2016); Behnke M., Recent trends in last mile delivery: Impacts of fast fulfillment, parcel lockers, electric or autonomous vehicles, and more, Logistics Management. Cham, Switzerland: Springer, pp. 141-156, (2019); Deutsch Y., Golany B., A parcel locker network as a solution to the logistics last mile problem, Int. J. Prod. Res., 56, 1-2, pp. 251-261, (2018); Fang J., The Spatial Dynamics of Amazon Lockers, (2019); Bengtsson C., Vikingson A., Exploring and evaluating the parcel locker-A Swedish consumer perspective, M.S. Thesis, Dept. Des. Sci., Lund Univ., Lund, Sweden, (2015); Lin S.-W., Yu V.F., Solving the team orienteering problem with time windows and mandatory visits by multi-start simulated annealing, Comput. Ind. Eng., 114, pp. 195-205, (2017); Yu V.F., Redi A.A.N.P., Hidayat Y.A., Wibowo O.J., A simulated annealing heuristic for the hybrid vehicle routing problem, Appl. Soft Comput., 53, pp. 119-132, (2017); Zhou L., Baldacci R., Vigo D., Wang X., A multi-depot twoechelon vehicle routing problem with delivery options arising in the last mile distribution, Eur. J. Oper. Res., 265, 2, pp. 765-778, (2018); Sitek P., Wikarek J., Capacitated vehicle routing problem with pickup and alternative delivery (CVRPPAD): Model and implementation using hybrid approach, Ann. Oper. Res., 273, 1-2, pp. 257-277, (2019); Tilk C., Olkis K., Irnich S., The last-mile vehicle routing problem with delivery options, OR Spectr., 43, 4, pp. 877-904, (2021); Enthoven D.L.J.U., Jargalsaikhan B., Roodbergen K.J., Uit Het Broek M.A.J., Schrotenboer A.H., The two-echelon vehicle routing problem with covering options: City logistics with cargo bikes and parcel lockers, Comput. Oper. Res., 118, (2020); Dantzig G.B., Ramser J.H., The truck dispatching problem, Man-age. 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Rev., 42, 2, pp. 254-267, (2012); Moradi B., The new optimization algorithm for the vehicle routing problem with time windows using multi-objective discrete learnable evolution model, Soft Comput., 24, pp. 6741-6769, (2019); Pang K.-W., An adaptive parallel route construction heuristic for the vehicle routing problem with time Windows constraints, Expert Syst. Appl., 38, 9, pp. 11939-11946, (2011); Nagata Y., Braysy O., Dullaert W., A penalty-based edge assembly memetic algorithm for the vehicle routing problem with time Windows, Comput. Oper. Res., 37, 4, pp. 724-737, (2010); Banos R., Ortega J., Gil C., Fernandez A., De Toro F., A simulated annealing-based parallel multi-objective approach to vehicle routing problems with time Windows, Expert Syst. Appl., 40, 5, pp. 1696-1707, (2013); Cordeau J.-F., Maischberger M., A parallel iterated Tabu search heuristic for vehicle routing problems, Comput. Oper. Res., 39, 9, pp. 2033-2050, (2012); Xu Z., Cai Y., Variable neighborhood search for consistent vehicle routing problem, Expert Syst. Appl., 113, pp. 66-76, (2018); Wang H.-F., Chen Y.-Y., A genetic algorithm for the simultaneous delivery and pickup problems with time window, Comput. Ind. Eng., 62, 1, pp. 84-95, (2012); Baran B., Schaerer M., A multiobjective ant colony system for vehicle routing problem with time windows, Appl. Informat., pp. 97-102, (2003); Qi Y., Hou Z., Li H., Huang J., Li X., Adecomposition based memetic algorithm for multi-objective vehicle routing problem with time windows, Comput. Oper. Res., 62, pp. 61-77, (2015); Yassen E.T., Ayob M., Nazri M.Z.A., Sabar N.R., Meta-harmony search algorithm for the vehicle routing problem with time windows, Inf. Sci., 325, pp. 140-158, (2015); Blum C., Puchinger J., Raidl G.R., Roli A., Hybrid metaheuristics in combinatorial optimization: A survey, J. Appl. Soft Comput., 11, 6, pp. 4135-4151, (2011); Jeon G., Leep H.R., Shim J.Y., A vehicle routing problem solved by using a hybrid genetic algorithm, Comput. Ind. Eng., 53, 4, pp. 680-692, (2007); Subramanian A., Penna P.H.V., Uchoa E., Ochi L.S., A hybrid algorithm for the heterogeneous fieet vehicle routing problem, Eur. J. Oper. Res., 221, 2, pp. 285-295, (2012); Marinakis Y., Marinaki M., A hybrid genetic-Particle swarm optimization algorithm for the vehicle routing problem, Expert Syst. Appl., 37, 2, pp. 1446-1455, (2010); Marinakis Y., Marinaki M., Dounias G., A hybrid particle swarm optimization algorithm for the vehicle routing problem, Eng. Appl. Artif. Intell., 23, 4, pp. 463-472, (2010); Yu V.F., Lin S.-W., Lee W., Ting C.-J., A simulated annealing heuristic for the capacitated location routing problem, Comput. Ind. Eng., 58, 2, pp. 288-299, (2010); Jeong C.-S., Kim M.-H., Fast parallel simulated annealing for traveling salesman problem on SIMD machines with linear interconnections, Parallel Comput., 17, 2-3, pp. 221-228, (1991); Soflanopoulou S., Simulated annealing applied to the process allocation problem, Eur. J. Oper. Res., 60, 3, pp. 327-334, (1992); Seckiner S.U., Kurt M., A simulated annealing approach to the solution of job rotation scheduling problems, Appl. Math. Comput., 188, 1, pp. 31-45, (2007); Wang C., Mu D., Zhao F., Sutherland J.W., A parallel simulated annealing method for the vehicle routing problem with simultaneous pickupfidelivery and time Windows, Comput. Ind. Eng., 83, pp. 111-122, (2015); Laporte G., Nobert Y., Exact algorithms for the vehicle routing problem, North-Holland Math. Stud., 132, 1, pp. 147-184, (1987); Normasari N.M.E., Yu V.F., Bachtiyar C., Sukoyo, A simulated annealing heuristic for the capacitated green vehicle routing problem, Math. Problems Eng., 2019, pp. 1-18, (2019); Chiang W.-C., Russell R.A., Simulated annealing metaheuristics for the vehicle routing problem with timeWindows, Ann. Oper. Res., 63, 1, pp. 3-27, (1996); Kuo Y., Using simulated annealing to minimize fuel consumption for the time-dependent vehicle routing problem, Comput. Ind. Eng., 59, 1, pp. 157-165, (2010); Karagul K., Sahin Y., Aydemir E., Oral A., A simulated annealing algorithm based solution method for a green vehicle routing problem with fuel consumption, Lean and Green Supply Chain Management (International Series in Operations Research & Management Science), 273, (2019); Zhang D., Cai S., Ye F., Si Y.-W., Nguyen T.T., A hybrid algorithm for a vehicle routing problem with realistic constraints, Inf. Sci., 394-395, pp. 167-182, (2017); Wolpert D.H., What the No Free Lunch Theorems Really Mean; How to Improve Search Algorithms, 4, (2012); Rabbouch B., Saadaoui F., Mraihi R., Empirical-type simulated annealing for solving the capacitated vehicle routing problem, J. Experim. Theor. Artif. Intell., 32, 3, pp. 437-452, (2020); Walpole R.E., Myers R.H., Myers S.L., Ye K., Probability&Statistics for Engineers& Scientists, 9th Ed, (2011); Yu V.F., Winarno, Maulidin A., Redi A.A.N.P., Lin S.-W., Yang C.-L., Simulated annealing with restart strategy for the path cover problem with time Windows, Mathematics, 9, 14, (2021)","S.-W. Lin; Department of Information Management, Chang Gung University, Taoyuan, 333, Taiwan; email: swlin@mail.cgu.edu.tw",null,"Institute of Electrical and Electronics Engineers Inc.",{"$nulls":5},2.1693536E7,null,null,null,"English","IEEE Access","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85124813706"]
["Wang X.C.; Kim W.; Holguín-Veras J.; Schmid J.","Wang, Xiaokun (Cara) (55482185200); Kim, Woojung (57226057810); Holguín-Veras, José (6701659951); Schmid, Joshua (57203141853)","55482185200; 57226057810; 6701659951; 57203141853","Adoption of delivery services in light of the COVID pandemic: Who and how long?",2021.0,"Transportation Research Part A: Policy and Practice",154.0,null,null,270.0,286.0,16.0,32.0,"10.1016/j.tra.2021.10.012","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85118487713&doi=10.1016%2fj.tra.2021.10.012&partnerID=40&md5=001638b873d28b406a89316db0a24d90","Department of Civil and Environmental Engineering, Rensselaer Polytechnic Institute, 110 8th Street, 4032 JEC Building, Troy, 12180, NY, United States; VREF Center of Excellence for Sustainable Urban Freight Systems, Rensselaer Polytechnic Institute, 110 8th St, Room JEC 4030, Troy, 12180, NY, United States","Wang X.C., Department of Civil and Environmental Engineering, Rensselaer Polytechnic Institute, 110 8th Street, 4032 JEC Building, Troy, 12180, NY, United States; Kim W., Department of Civil and Environmental Engineering, Rensselaer Polytechnic Institute, 110 8th Street, 4032 JEC Building, Troy, 12180, NY, United States; Holguín-Veras J., VREF Center of Excellence for Sustainable Urban Freight Systems, Rensselaer Polytechnic Institute, 110 8th St, Room JEC 4030, Troy, 12180, NY, United States; Schmid J., Department of Civil and Environmental Engineering, Rensselaer Polytechnic Institute, 110 8th Street, 4032 JEC Building, Troy, 12180, NY, United States","A significant growth in demand for online shopping in light of the Coronavirus Disease (COVID) crisis has received attention from transportation practitioners, policy-makers, and researchers. However, an important question arises in this increase in online shopping and resulting deliveries: How long will this last? Very little is known whether this popularity would last a long time. To address this question, the authors conducted a survey of 915 individuals residing in the U.S. and classified them into the four distinctive consumer types (i.e., the prior adopter, temporary adopter and permanent new adopter, and non-adopter) depending on their usage of delivery services before, during, and after (expected) the COVID crisis. This research aims to gain behavioral insight by exploring the differences between the four consumer types and investigating factors affecting the initial adoption and continuance intention of using delivery services. The descriptive analysis revealed that there are clear differences not only between the four types of consumers but also between the four product types (i.e., grocery, food, home goods, and other packages) considered in the survey. The models found that factors affecting the initial adoption and continuance intention are different from the previous studies conducted before the COVID pandemic. Implications for planning and policymaking are also discussed. © 2021 Elsevier Ltd","Continuance intention; COVID; Delivery; Pandemic; Technology adoption","United States; Coronavirus; Electronic commerce; Surveys; Adoption intention; Continuance intentions; Coronavirus disease; Coronaviruses; Delivery; Delivery service; Initial adoption; Online shopping; Pandemic; Technology adoption; consumption behavior; COVID-19; epidemic; Internet; technology adoption; transportation system; Coronavirus",{"$nulls":4},"COE-SUFS; VREF Center of Excellence for Sustainable Urban Freight Systems; U.S. Department of Energy, USDOE, (DE-EE0008259)","This research was partially supported by the VREF Center of Excellence for Sustainable Urban Freight Systems (COE-SUFS) and the U.S. Department of Energy (DOE) project \"Collaborative Public-Private Sector Approaches to Foster Energy Efficient Logistics at the NYC-Albany Corridor\" (project number: DE-EE0008259). Their support is acknowledged and appreciated. The authors appreciate the anonymous reviewers for their valuable comments and suggestions.","Alemi F., Circella G., Handy S., Mokhtarian P., What influences travelers to use Uber? Exploring the factors affecting the adoption of on-demand ride services in California, Travel Behaviour and Society, 13, July 2017, pp. 88-104, (2018); (2020); Baig A., Hall B., Jenkins P., Lamarre E., McCarthy B., The COVID-19 recovery will be digital: A plan for the first 90 days, McKinsey Digital., (2020); Bergmann M., IPFWEIGHT: Stata module to create adjustment weights for surveys, (2011); Bhattacherjee A., Understanding information systems continuance: an expectation-confirmation model, MIS Quarterly, 25, 3, pp. 351-370, (2001); (2020); Brown D., (2020); Cao X., E-shopping, spatial attributes, and personal travel: A review of empirical studies, Transportation Research Record, 2135, 1, pp. 160-169, (2009); Carpenter S., (2020); Chen C.Y., Lee L., Yap A.J., Control deprivation motivates acquisition of utilitarian products, Journal of Consumer Research, 43, 6, pp. 1031-1047, (2017); Chen Q., Conway A., Cheng J., Parking for residential delivery in New York City: Regulations and behavior, Transport Policy, 54, pp. 53-60, (2017); (2021); (2020); Davis F.D., A technology acceptance model for empirically testing new end-user information systems: Theory and results, (1985); Davis F.D., Perceived usefulness, perceived ease of use, and user acceptance of information technology, MIS Quarterly, 13, 3, (1989); (2020); Dias F.F., Lavieri P.S., Sharda S., Khoeini S., Bhat C.R., Pendyala R.M., Pinjari A.R., Ramadurai G., Srinivasan K.K., A comparison of online and in-person activity engagement: The case of shopping and eating meals, Transportation Research Part C: Emerging Technologies, 114, pp. 643-656, (2020); Farag S., Weltevreden J., van Rietbergen T., Dijst M., van Oort F., E-shopping in the Netherlands: Does geography matter?, Environment and Planning B: Planning and Design, 33, 1, pp. 59-74, (2006); (2017); Goger A., (2020); Grashuis J., Skevas T., Segovia M.S., Grocery Shopping Preferences during the COVID-19 Pandemic, Sustainability, 12, 13, (2020); Hand C., Riley F.D.O., Harris P., Singh J., Rettie R., Online grocery shopping: The influence of situational factors, European Journal of Marketing, 43, 9, pp. 1205-1219, (2009); Hiser J., Nayga R.M., Capps O., An exploratory analysis of familiarity and willingness to use online food shopping services in a local area of texas, Journal of Food Distribution Research, 30, 1, pp. 78-90, (1999); Huang Y., Oppewal H., Why consumers hesitate to shop online: An experimental choice analysis of grocery shopping and the role of delivery fees, International Journal of Retail and Distribution Management, 34, 4-5, pp. 334-353, (2006); Jaller M., Pahwa A., Evaluating the environmental impacts of online shopping: A behavioral and transportation approach, Transportation Research Part D: Transport and Environment, 80, (2020); Lappeman J., (2020); Lee R.J., Sener I.N., Mokhtarian P.L., Handy S.L., Relationships between the online and in-store shopping frequency of Davis, California residents, Transportation Research Part A: Policy and Practice, 100, pp. 40-52, (2017); Lewis M., The effect of shipping fees on customer acquisition, customer retention, and purchase quantities, Journal of Retailing, 82, 1, pp. 13-23, (2006); Liao C., Palvia P., Chen J.-L., Information technology adoption behavior life cycle: Toward a Technology Continuance Theory (TCT), International Journal of Information Management, 29, 4, pp. 309-320, (2009); Lin J., Zhou W., Du L., Is on-demand same day package delivery service green?, Transportation Research Part D: Transport and Environment, 61, pp. 118-139, (2018); Lin Z., Filieri R., Airline passengers’ continuance intention towards online check-in services: The role of personal innovativeness and subjective knowledge, Transportation Research Part E: Logistics and Transportation Review, 81, pp. 158-168, (2015); Lufkin B., (2020); Marcucci E., Gatta V., (2021); Matherly D., Bye P., Benini J., (2020); Mokhtarian P.L., A conceptual analysis of the transportation impacts of B2C e-commerce, Transportation, 31, 3, pp. 257-284, (2004); (2020); NYC D.O.T.; NYC D.O.T.; Pandise E., (2020); Peng C., OuYang Z., Liu Y., Understanding bike sharing use over time by employing extended technology continuance theory, Transportation Research Part A: Policy and Practice, 124, pp. 433-443, (2019); Ren F., Kwan M.P., The impact of geographic context on e-shopping behavior, Environment and Planning B: Planning and Design, 36, 2, pp. 262-278, (2009); (2020); Rivoli D., (2020); (2020); Schmid J., Wang X.C., Conway A., Commercial vehicle parking duration in New York City and its implications for planning, Transportation Research Part A: Policy and Practice, 116, March, pp. 580-590, (2018); Schmid J., Wang X.C., Holguin-veras J., (2020); (2020); (2020); Shabanpour R., Shamshiripur A., Rahimi E., Mohammadian A., (2020); Shamshiripour A., Rahimi E., Shabanpour R., Mohammadian Kouros A., How is COVID-19 reshaping activity-travel behavior? Evidence from a comprehensive survey in Chicago, Transportation Research Interdisciplinary Perspectives, 7, (2020); Spurlock C.A., Todd-Blick A., Wong-Parodi G., Walker V., Children, Income, and the Impact of Home Delivery on Household Shopping Trips, Transportation Research Record: Journal of the Transportation Research Board., 2674, 10, pp. 335-350, (2020); Taylor S., The psychology of pandemics: Preparing for the next global outbreak of infectious disease, (2019); Thomas L., (2020); Tierney K.J., Businesses and disasters: Vulnerability, impacts, and recovery, Handbook of disaster research, pp. 275-296, (2007); (2020); Unnikrishnan A., Figliozzi M.A., (2020); (2016); Venkatesh V., Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model, Information Systems Research, 11, 4, pp. 342-365, (2000); Venkatesh V., Bala H., Technology acceptance model 3 and a research agenda on interventions, Decision Sciences, 39, 2, pp. 273-315, (2008); Venkatesh V., Davis F.D., A theoretical extension of the technology acceptance model: Four longitudinal field studies, Management Science, 46, 2, pp. 186-204, (2000); Venkatesh V., Morris M.G., Davis G.B., Davis F.D., User acceptance of information technology: Toward a unified view, MIS Quarterly, pp. 425-478, (2003); Wang X.C., Zhou Y., Deliveries to residential units: A rising form of freight transportation in the U.S, Transportation Research Part C: Emerging Technologies, 58, pp. 46-55, (2015); Washington S., Karlaftis M.G., Mannering F., Anastasopoulos P., Statistical and econometric methods for transportation data analysis, (2020); (2020); Weng G.S., Zailani S., Iranmanesh M., Hyun S.S., Mobile taxi booking application service's continuance usage intention by users, Transportation Research Part D: Transport and Environment, 57, October, pp. 207-216, (2017); Xi G., Cao X., Zhen F., The impacts of same day delivery online shopping on local store shopping in Nanjing, China, Transportation Research Part A: Policy and Practice, 136, February, pp. 35-47, (2020); Zhou T., An empirical examination of continuance intention of mobile payment services, Decision Support Systems, 54, 2, pp. 1085-1091, (2013); Zou W., Wang X.C., Conway A., Chen Q., Empirical analysis of delivery vehicle on-street parking pattern in Manhattan area, Journal of Urban Planning and Development, 142, 2, (2016)","W. Kim; Department of Civil and Environmental Engineering, Rensselaer Polytechnic Institute, Troy, 110 8th Street, 4032 JEC Building, 12180, United States; email: kimw6@rpi.edu",null,"Elsevier Ltd",{"$nulls":5},9658564.0,null,null,null,"English","Transp. Res. Part A Policy Pract.","Article","Final","All Open Access; Bronze Open Access; Green Open Access","Scopus","2-s2.0-85118487713"]
["Farchi F.; Touzi B.; Farchi C.; Mabrouki C.","Farchi, Fadwa (57416120000); Touzi, Badr (57416120100); Farchi, Chayma (57415856800); Mabrouki, Charif (55830333600)","57416120000; 57416120100; 57415856800; 55830333600","Optimal Urban Logistics - Through the Choice of Sustainable Axes",2021.0,"International Journal of Sustainable Development and Planning",16.0,8.0,null,1541.0,1549.0,8.0,2.0,"10.18280/ijsdp.160815","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85123021265&doi=10.18280%2fijsdp.160815&partnerID=40&md5=01bd5d51d4042b7fb9c9d2bf093a448d","Department of Mechanical and Electrical Engineering, Hassan 1er University of Settat, Settat, 26000, Morocco; Department of Economics and Management Sciences, Mohammed V University of Rabat, Rabat, 10170, Morocco","Farchi F., Department of Mechanical and Electrical Engineering, Hassan 1er University of Settat, Settat, 26000, Morocco; Touzi B., Department of Economics and Management Sciences, Mohammed V University of Rabat, Rabat, 10170, Morocco; Farchi C., Department of Mechanical and Electrical Engineering, Hassan 1er University of Settat, Settat, 26000, Morocco; Mabrouki C., Department of Mechanical and Electrical Engineering, Hassan 1er University of Settat, Settat, 26000, Morocco","In a world where urbanization is becoming more and more widespread, big figures can be seen around internal urban migration further aggravating the environmental urban situation, which results from several previous factors. This is the case with globalization, online shopping, or polluting industrial and human sources. The major solutions are centered primarily on the concern for urban mobility, the involvement of the stakeholders concerned, the optimization of journeys, the use of lanes and roads, the choice of vehicles as well as the zoning or choice of logistics locations. Sustainability is one of the primary elements of flow management; it is one of the most important pillars of the concept of \"urban logistics\". Indeed, the final goal goes beyond the delivery of goods, going so far as to place the environment as an essential support for urban logistics. In this paper we present a literature review on sustainable logistics, we will try to answer the following problem: Urban logistics: Where are we? To respond to this problem, we are taking the following approach: Presentation of the basic concepts, choice of articles to be used for the study which will induce us to determine the axes and the main actors, with the aim of specifying the most predominant aspects which must be treated and prioritized in order to make urban logistics more optimal. © 2021 WITPress. All rights reserved.","Digitization; Literature review; Smart city; Stakeholders; Sustainable urban logistics; Urban logistics","globalization; Internet; literature review; logistics; mobility; optimization; population migration; shopping activity; smart city; stakeholder; sustainability; urbanization",{"$nulls":6},"Kull T.J., Boyer K., Calantone R., Last‐mile supply chain efficiency: an analysis of learning curves in online ordering, International Journal of Operations & Production Management, 27, 4, pp. 409-434, (2007); Macharis C., Melo S., City Distribution and Urban Freight Transport, (2011); Dundar H., Omurgonulsen M., Soysal M., A review on sustainable urban vehicle routing, Journal of Cleaner Production, 285, (2021); Navarro C., Roca-Riu M., Furio S., Estrada M., Designing new models for energy efficiency in urban freight transport for smart cities and its application to the Spanish case, Transportation Research Procedia, 12, pp. 314-324, (2016); Schliwa G., Armitage R., Aziz S., Evans J., Rhoades J., Sustainable city logistics - Making cargo cycles viable for urban freight transport, Research in Transportation Business & Management, 15, pp. 50-57, (2015); Nurnberg M., Analysis of using cargo bikes in urban logistics on the example of Stargard, Transportation Research Procedia, 39, pp. 360-369, (2019); Ruesch M., Todesco P., Hegi P., A positive planning approach to secure logistics facilities in urban areas, Transportation Research Procedia, 46, pp. 69-76, (2020); Gatta V., Marcucci E., Le Pira M., Smart urban freight planning process: integrating desk, living lab and modelling approaches in decision-making, European Transport Research Review, 9, 3, (2017); Tian Z., Zhong R.Y., Vatankhah Barenji A., Wang Y.T., Li Z., Rong Y., A blockchain-based evaluation approach for customer delivery satisfaction in sustainable urban logistics, International Journal of Production Research, 59, 7, pp. 2229-2249, (2020); Giret A., Smart and sustainable urban logistic applications aided by intelligent techniques, Service Oriented Computing and Applications, 13, 3, pp. 185-186, (2019); Kauf S., City logistics – A Strategic Element of Sustainable Urban Development, Transportation Research Procedia, 16, pp. 158-164, (2016); Quak H., Lindholm M., Tavasszy L., Browne M., From freight partnerships to city logistics living labs – giving meaning to the elusive concept of living labs, Transportation Research Procedia, 12, pp. 461-473, (2016); Morfoulaki M., Kotoula K., Stathacopoulos A., Mikiki F., Aifadopoulou G., Evaluation of specific policy measures to promote sustainable urban logistics in small-medium sized cities: The case of Serres, Greece, Transportation Research Procedia, 12, pp. 667-678, (2016); Cossu P., Clean last mile transport and logistics management for smart and efficient local governments in Europe, Transportation Research Procedia, 14, pp. 1523-1532, (2016); Lagorio A., Pinto R., Golini R., Urban Logistics Ecosystem: a system of system framework for stakeholders in urban freight transport projects, IFACPapersOnLine, 50, 1, pp. 7284-7289, (2017); Pimentel C., Alvelos F., Integrated urban freight logistics combining passenger and freight flows – mathematical model proposal, Transportation Research Procedia, 30, pp. 80-89, (2018); Bergmann F.M., Wagner S.M., Winkenbach M., Integrating first-mile pickup and last-mile delivery on shared vehicle routes for efficient urban e-commerce distribution, Transportation Research Part B: Methodological, 131, pp. 26-62, (2020); Yue S., Wang Y., Zhao M., Liu Y., Research on the Feasibility and distribution mode of urban logistics distribution by Rail Transit, Journal of Physics: Conference Series, 1827, 1, (2021); Ruggieri R., Ruggeri M., Vinci G., Poponi S., Electric mobility in a smart city: European overview, Energies, 14, 2, (2021); Farvaresh H., Shahmansouri S., A coalition structure algorithm for large-scale collaborative pickup and delivery problem, Computers & Industrial Engineering, 149, (2020); Kumar S., Bharj R.S., Solar hybrid e-cargo rickshaw for urban transportation demand in India, Transportation Research Procedia, 48, pp. 1998-2005, (2020); Lin Y.H., Wang Y., He D., Lee L.H., Last-mile delivery: Optimal locker location under multinomial logit choice model, Transportation Research Part E: Logistics and Transportation Review, 142, (2020); Jiang B., Fan Z.P., Optimal allocation of shared parking slots considering parking unpunctuality under a platform-based management approach, Transportation Research Part E: Logistics and Transportation Review, 142, (2020); Drop N., Garlinska D., Evaluation of intelligent transport systems used in urban agglomerations and intercity roads by professional truck drivers, Sustainability, 13, 5, (2021); Szymczyk K., Kadlubek M., Challenges in general cargo distribution strategy in urban logistics – comparative analysis of the biggest logistics operators in EU, Transportation Research Procedia, 39, pp. 525-533, (2019); Tahami H., Rabadi G., Haouari M., Exact approaches for routing capacitated electric vehicles, Transportation Research Part E: Logistics and Transportation Review, 144, (2020); Crainic T.G., Gendreau M., Jemai L., Planning hyperconnected, urban logistics systems, Transportation Research Procedia, 47, pp. 35-42, (2020); Nathanail E., Gogas M., Adamos G., Smart interconnections of interurban and urban freight transport towards achieving sustainable city logistics, Transportation Research Procedia, 14, pp. 983-992, (2016); Zhang Z., Tafreshian A., Masoud N., Modular transit: Using autonomy and modularity to improve performance in public transportation, Transportation Research Part E: Logistics and Transportation Review, 141, (2020); Russo F., Comi A., Behavioural simulation of urban goods transport and logistics: The integrated choices of end consumers, Transportation Research Procedia, 46, pp. 165-172, (2020); Schoder D., Ding F., Campos J.K., The Impact of E-Commerce Development on Urban Logistics Sustainability, Open Journal of Social Sciences, pp. 1-6, (2016); Wolbertus R., Jansen S., Kroesen M., Stakeholders’ perspectives on future electric vehicle charging infrastructure developments, Futures, 123, (2020); Bhasker A., Sarmah S.P., Kim T., Collaborative last-mile delivery and pick-up in city logistics, International Journal of Logistics Systems and Management, 34, 4, (2019); Gusmao A, Ribeiro P.C.M., Guidelines for the efficiency of urban goods distribution: The Brazilian case, Case Studies on Transport Policy, 8, 4, pp. 1478-1488, (2020); Karakikes I., Nathanail E., Simulation techniques for evaluating smart logistics solutions for sustainable urban distribution, Procedia Engineering, 178, pp. 569-578, (2017); He P., He Y., Xu H., Buy-online-and-deliver-from-store strategy for a dual-channel supply chain considering retailer’s location advantage, Transportation Research Part E: Logistics and Transportation Review, 144, (2020); Fredriksson A., Janne M., Nolz P., de Radigues de Chenneviere P., van Lier T., Macharis C., Creating stakeholder awareness in construction logistics by means of the MAMCA, City and Environment Interactions, 11, (2021); Liang T., Wang H., Consumer decision-making and smart logistics planning based on FPGA and convolutional neural network, Microprocessors and Microsystems, 80, (2021); Leyerer M., Sonneberg M.O., Heumann M., Breitner M.H., Shortening the last mile in urban areas: optimizing a smart logistics concept for e-grocery operations, Smart Cities, 3, 3, pp. 585-603, (2020); Mor A., Speranza M.G., Viegas J.M., Efficient loading and unloading operations via a booking system, Transportation Research Part E: Logistics and Transportation Review, 141, (2020); Yang F., Dai Y., Ma Z.J., A cooperative rich vehicle routing problem in the last-mile logistics industry in rural areas, Transportation Research Part E: Logistics and Transportation Review, 141, (2020); Gogas M., Adamos G., Nathanail E., Assessing the performance of intermodal city logistics terminals in Thessaloniki, Transportation Research Procedia, 24, pp. 17-24, (2017); Goncalves L.A.P.J., Ribeiro P.J.G., Resilience of urban transportation systems. Concept, characteristics, and methods, Journal of Transport Geography, 85, (2020); Gross P.O., Ehmke J.F., Mattfeld D.C., Interval travel times for robust synchronization in city logistics vehicle routing, Transportation Research Part E: Logistics and Transportation Review, 143, (2020); Hammami F., The impact of optimizing delivery areas on urban traffic congestion, Research in Transportation Business & Management, 37, (2020); He M., Sun L., Zeng X., Liu W., Tao S., Node layout plans for urban underground logistics systems based on heuristic Bat algorithm, Computer Communications, 154, pp. 465-480, (2020); Hu W., Dong J., Hwang B., Ren R., Chen Z., Hybrid optimization procedures applying for two-echelon urban underground logistics network planning: A case study of Beijing, Computers & Industrial Engineering, 144, (2020); Ke J., Yang H., Zheng Z., On ride-pooling and traffic congestion, Transportation Research Part B: Methodological, 142, pp. 213-231, (2020); Lozano A., Cantillo V., Holguin-Veras J., Special issue on “Urban transportation sustainability: Experiences and innovative approaches, Transportation Research Part A: Policy and Practice, 137, (2020); Masik G., Sagan I., Scott J.W., Smart Smart City strategies and new urban development policies in the Polish context, Cities, 108, (2021); Matusiewicz M., SULP (Sustainable Urban Logistics Plan) as a tool for shaping sustainable urban logistics: A review of European projects supporting the creation of SULP, Transport Economics and Logistics, 84, pp. 71-78, (2019); Alho A., Bhavathrathan B.K., Stinson M., Gopalakrishnan R., Le D.T., Ben-Akiva M., A multi-scale agent-based modelling framework for urban freight distribution, Transportation Research Procedia, 27, pp. 188-196, (2017); Chu X., Liu J., Ren L., Gong D., Optimal contract design with a common agency in last-mile logistics, Transportation Research Part E: Logistics and Transportation Review, 139, (2020); De Bok M., Tavasszy L., Thoen S., Application of an empirical multi-agent model for urban goods transport to analyze impacts of zero emission zones in The Netherlands, Transport Policy, (2020); Gerlach J., Richter N., Becker U.J., Mobility indicators put to test – German strategy for sustainable development needs to be revised, Transportation Research Procedia, 14, pp. 973-982, (2016)","F. Farchi; Department of Mechanical and Electrical Engineering, Hassan 1er University of Settat, Settat, 26000, Morocco; email: f.farchi@uhp.ac.ma",null,"International Information and Engineering Technology Association",{"$nulls":5},1.7437601E7,null,null,null,"English","Int. J. Sustainable Dev. Plann.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85123021265"]
["PAVLOVA V.; MUROVANA T.; SARAI N.; VELYCHKO V.; ILLYASHENKO K.; HRYSHYNA H.","PAVLOVA, VALENTYNA (57211334374); MUROVANA, TETIANA (57200968744); SARAI, NATALIIA (57302119600); VELYCHKO, VIKTORIIA (57308849300); ILLYASHENKO, KOSTYANTYN (57303070900); HRYSHYNA, HANNA (57302914000)","57211334374; 57200968744; 57302119600; 57308849300; 57303070900; 57302914000","Crisis phenomena as an incentive to intensify e-commerce of the enterprise",2021.0,"Journal of Theoretical and Applied Information Technology",99.0,19.0,null,4646.0,4657.0,11.0,5.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85117521980&partnerID=40&md5=c7121a3d0cf573889c77f9ac59b4d478","Department of International Trade and Entrepreneurship, Alfred Nobel University, Dnipro, Ukraine; Department of Environmental Management and Entrepreneurship, Taras Shevchenko National University of Kyiv, Ukraine; Department of Entrepreneurship, Trade and Exchange Activities, Khmelnytskyi Cooperative Trade and Economic Institute, Khmelnytskyi, Ukraine; Department of Entrepreneurship and Business Administration, O.M. Beketov National University of Urban Economy in Kharkiv, Kharkiv, Ukraine; Department of Finance and Entrepreneurship, Sumy State University, Sumy, Ukraine","PAVLOVA V., Department of International Trade and Entrepreneurship, Alfred Nobel University, Dnipro, Ukraine; MUROVANA T., Department of Environmental Management and Entrepreneurship, Taras Shevchenko National University of Kyiv, Ukraine; SARAI N., Department of Entrepreneurship, Trade and Exchange Activities, Khmelnytskyi Cooperative Trade and Economic Institute, Khmelnytskyi, Ukraine; VELYCHKO V., Department of Entrepreneurship and Business Administration, O.M. Beketov National University of Urban Economy in Kharkiv, Kharkiv, Ukraine; ILLYASHENKO K., Department of Finance and Entrepreneurship, Sumy State University, Sumy, Ukraine; HRYSHYNA H., Department of International Trade and Entrepreneurship, Alfred Nobel University, Dnipro, Ukraine","The latest global crisis has negatively affected the global economy as a whole, but it has had a stimulating effect on e-commerce. Electronic commerce around the world has intensified with a breakthrough in sales and transactions. While virtually the entire world has imposed restrictions to contain the spread of the pandemic, Internet technology and e-commerce have helped many enterprises stay afloat and the impetus for a massive transition to online. Today, global digitalization allows you to make purchases without leaving your home. At the same time, customers get a complete picture of the product using modern IT technologies, such as AR & Video Consultations, Voice robots and Assistants, make payments using new payment systems, and receive the goods as soon as possible. At the same time, e-commerce faced several challenges. The article examines the trends in the development of e-commerce in the world and the correction of the share of e-commerce in total retail sales in connection with the crisis. Changes in the structure of the e-commerce market of enterprises under the influence of the crisis phenomena are noted. The article identifies the main problems that e-commerce enterprises faced during the last global crisis and the ways to solve them. Technological trends in the global e-commerce market are noted, such as chatbots, blockchain, artificial intelligence, mobile commerce, etc. The article also indicates the main trends in the development of e-commerce under the influence of the crisis. These tendencies are aimed at creating conditions that will quickly or even automatically close the questions and doubts of the user regarding the purchase of goods in the online store and at attracting the most \"hot\" visitors. The surge in e-commerce due to the crisis has led to increased online businesses and increased competition. Each salesperson fights for a customer, and searching for solutions to win customers generates new trends in online sales. The article highlights the following trends that are necessary to maintain positions in e-commerce: Process automation; focus on m-commerce; the use of voice assistants and robots; the use of new different payment methods, including new ones; organization of fast delivery, etc. © 2021 Little Lion Scientific. All rights reserved.","Chatbots; Crisis; Customer Data Platform; E-Commerce; Online Scam",{"$nulls":7},"Goncharuk I., Review of Research on the Impact of the COVID-19 Pandemic on the Development of Global and Russian E-commerce, Customs policy, 1, 94, pp. 66-82, (2021); Jain V., Malviya B., Arya S., An Overview of Electronic Commerce (e-Commerce), Journal of Contemporary Issues in Business and Government, 27, 3, pp. 665-670, (2021); Tran H., From E-Commerce to M-Commerce, Journal of Textile Science & Fashion Technology, 6, 1, (2020); Bondar I., Gumenyuk T., Udris-Borodavko N., Penchuk O., Entrepreneurship model for creation of designer competences in the process of professional training, Journal of Entrepreneurship Education, 22, 6, (2019); Bashynska I., Lytovchenko I., Kharenko D., Sales tunnels in messengers as new technologies for effective Internet-marketing in tourism and hospitality, International Journal of Innovative Technology and Exploring Engineering, 8, 12, pp. 594-598, (2019); Dobina T., Haidukevych K., Panchenko S., Petrova I., Sabadash J., Effectiveness analysis of entrepreneurship model of development qualities of future managers, Journal of Entrepreneurship Education, 22, 3, (2019); Prokopenko O., Shmorgun L., Kushniruk V., Prokopenko M., Slatvinska M., Huliaieva L., Business process efficiency in a digital economy, International Journal of Management, 11, 3, pp. 122-132; Arora S., Devising e-commerce and green e-commerce sustainability, International Journal of Engineering Development and Research, 7, 2, pp. 206-210, (2021); Tran H.D., From E-Commerce to M-Commerce, Journal of Textile Science & Fashion Technology, 6, 1, (2020); Nguyen H.T., Et al., Current Development of E-commerce Enterprises in Vietnam, Journal of Critical Reviews, 8, 1, pp. 748-754; Khmara D. S., Samotuga V. N., Development of E-Commerce in the Field of Small and Medium Enterprises, Economics and Management, 27, 6, pp. 426-436; Nivas S., E-commerce: Role of E-commerce in Today's Business, Computing Trendz - The Journal of Emerging Trends in Information Technology, 6, 1, (2021); Hrytsenko S., Activation of electronic commerce as a factor of economic modernization of internet business processes, Marketing in Ukraine, 2, pp. 34-39, (2012); Tereshchenko E., The development of e-commerce in the modern business environment, Efficient economy, 9, (2019); Almeghari H., Attracting International Audience Through Website's Multilingualism. Finnish e-retailing industry, (2018); E-commerce share of total global retail sales from 2015 to 2024; Coppola D., E-commerce worldwide - Statistics & Facts, (2021); The Future of E-commerce: 9 Trends in the Evolution of the Global E-Commerce Market; Prokopenko O., Toktosunova C., Sharsheeva N., Zablotska R., Mazurenko V., Halaz L., Prospects for the reorientation of investment flows for sustainable development under the influence of the covid-19 pandemic, Problemy Ekorozwoju, 16, 2, pp. 7-17, (2021); COVID-19 and e-commerce: A global review, United Nations Conference on Trade and Development; Alfonso V., Boar C., Frost J., Gambacorta L., Liu J., E-commerce in the pandemic and beyond, BIS Bulletin, 36, (2021); Palmer A., More brands are leaving Amazon, but the strategy could backfire, (2020); Bashynska I., Malanchuk M., Zhuravel O., Olinichenko K., Smart Solutions: Risk Management of Crypto-Assets and Blockchain Technology, International Journal of Civil Engineering and Technology, 10, 2, pp. 1121-1131, (2019); The future of e-commerce: 10 current trends in the development of the e-commerce market in the world; TOP 10 E-commerce Trends in 2021; Dykha M., Ustik T., Krasovska O., Pilevych D., Shatska Z., Iankovets T., Marketing tools for the development and enhance the efficiency of e-commerce in the context of digitalization, Estudios de Economia Aplicada, 39, 5, (2021); E-commerce trends - what to expect in 2021?","K. ILLYASHENKO; Department of Finance and Entrepreneurship, Sumy State University, Sumy, Ukraine; email: iva179@ukr.net",null,"Little Lion Scientific",{"$nulls":5},1.9928645E7,null,null,null,"English","J. Theor. Appl. Inf. Technol.","Article","Final",null,"Scopus","2-s2.0-85117521980"]
["Straubert C.","Straubert, Christian (57218449947)",5.7218449947E10,"A theoretical framework for the logistics strategies of B2C e-commerce retailers based on current trends in the industry",2022.0,"International Journal of Shipping and Transport Logistics",14.0,"2024-02-01",null,78.0,93.0,15.0,3.0,"10.1504/IJSTL.2022.120673","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124832467&doi=10.1504%2fIJSTL.2022.120673&partnerID=40&md5=c4aecceb8c26102a24dc1ab9ab2a7e0b","University of Bamberg, Feldkirchenstraße 21, Bamberg, 96052, Germany","Straubert C., University of Bamberg, Feldkirchenstraße 21, Bamberg, 96052, Germany","In B2C e-commerce, logistics is highly visible and very important to customers. It is therefore important that e-tailers have a strategy for the type of logistics services they want to offer, i.e., how they position themselves compared to their competitors. This paper aims to develop a theoretical framework for logistics strategies within the B2C e-commerce market. The theoretical framework developed in this paper is based on two sources of information: extensive quantitative data concerning the current and future trends in B2C e-commerce logistics and well-known models concerning competitive strategy. We find that B2C e-commerce logistics can be categorised into three main strategies: the 'logistics industry leaders' strategy, the 'logistics efficiency seekers' strategy, and the 'logistics niche concepts' strategy. We argue that because of the strong economies of scale in B2C e-commerce, logistics industry leaders are in a disproportionately strong position, especially compared to logistics efficiency seekers. The emphasis on competitive advantages and market positioning based on the logistics services offered by e-tailers is a new perspective that has not yet been discussed in the literature. © 2022 Inderscience Enterprises Ltd.","B2C e-commerce electric commerce; Competition; Logistics strategy; Theoretical framework; Trends",{"$nulls":7},"Ariguzo G.C., Mallach E.G., White D.S., The first decade of e-commerce, International Journal of Business Information Systems, 1, 3, (2006); Bakos Y., The emerging landscape for retail e-commerce, Journal of Economic Perspectives, 15, 1, pp. 69-80, (2001); Bask A., Lipponen M., Tinnila M., E-commerce logistics: a literature research review and topics for future research, International Journal of E-Services and Mobile Applications, 4, 3, pp. 1-22, (2012); Besanko D., Economics of Strategy, (2013); Cho J.J-K., Ozment J., Sink H., Logistics capability, logistics outsourcing and firm performance in an e‐commerce market, International Journal of Physical Distribution and Logistics Management, 38, 5, pp. 336-359, (2008); Jeff Bezos 1999 Interview on Amazon before the Dotcom Bubble Burst, (1999); Gawor T., Hoberg K., Customers' valuation of time and convenience in e-fulfillment, International Journal of Physical Distribution and Logistics Management, 49, 1, pp. 75-98, (2019); Ghezzi A., Mangiaracina R., Perego A., Shaping the e-commerce logistics strategy: a decision framework, International Journal of Engineering Business Management, 4, 2, pp. 1-13, (2012); Gupta A., Su B.C., Walter Z., An empirical study of consumer switching from traditional to electronic channels: a purchase-decision process perspective, International Journal of Electronic Commerce, 8, 3, pp. 131-161, (2004); Hsiao M.H., Shopping mode choice: physical store shopping versus e-shopping, Transportation Research Part E: Logistics and Transportation Review, 45, 1, pp. 86-95, (2009); Krippendorff K., Content Analysis: An Introduction to its Methodology, (2013); Lardner J., Yang D.J., A Flea Market for Webheads, U.S. News and World Report, 127, 14, (1999); Mahadevan B., Business models for internet-based e-commerce: an anatomy, California Management Review, 42, 4, pp. 55-69, (2000); Mangiaracina R., Marchet G., Perotti S., Tumino A., A review of the environmental implications of B2C e-commerce: a logistics perspective, International Journal of Physical Distribution and Logistics Management, 45, 6, pp. 565-591, (2015); Morris M., Schindehutte M., Allen J., The entrepreneur's business model: toward a unified perspective, Journal of Business Research, 58, 6, pp. 726-735, (2005); Oster S.M., Modern Competitive Analysis, (1999); Osterwalder A., Clarifying business models: origins, present, and future of the concept, Communications of the Association for Information Systems, 16, 1, (2005); Porter M.E., Competitive Advantage: Creating and Sustaining Superior Performance, (1985); Porter M.E., Competitive Strategy: Techniques for Analyzing Industries and Competitors, (1998); Schmitz S.W., Latzer M., Competition in B2C e-commerce: analytical issues and empirical evidence, Electronic Markets, 12, 3, pp. 163-174, (2002); Smith M.D., Brynjolfsson E., Consumer decision‐making at an internet shopbot: brand still matters, The Journal of Industrial Economics, 49, 4, pp. 541-558, (2001); Straubert C., Asdecker B., Zitzmann I., A content analysis on current technological trends in B2C e-commerce logistics, Proceedings of the 7th IEEE International Conference on Advanced Logistics and Transport (ICALT), pp. 117-122, (2019); Justice Department Reviewing the Practices of Market-Leading Online Platforms, Review Focuses on Practices that Create or Maintain Structural Impediments to Greater Competition and User Benefits, (2019); Treacy M., Wiersema F.D., The Discipline of Market Leaders: Choose your Customers, Narrow your Focus, Dominate your Market, (2006); Responses to Questions for the Record Following the July 16, 2019, Hearing of the Subcommittee on Antitrust, Commercial, and Administrative Law, Committee on the Judiciary, Entitled 'Online Platforms and Market Power, Part 2: Innovation and Entrepreneurship, (2019)","C. Straubert; University of Bamberg, Bamberg, Feldkirchenstraße 21, 96052, Germany; email: Christian.Straubert@Uni-Bamberg.de",null,"Inderscience Publishers",{"$nulls":5},1.7566517E7,null,null,null,"English","Int. J. Shipp. Transp. Logist.","Article","Final",null,"Scopus","2-s2.0-85124832467"]
["Addo P.C.; Akpatsa S.K.; Nukpe P.; Ohemeng A.A.; Kulbo N.B.","Addo, Prince Clement (57191376933); Akpatsa, Samuel Kofi (57218228847); Nukpe, Philip (57221108276); Ohemeng, Asare Andy (57382339400); Kulbo, Nora Bakabbey (57216484136)","57191376933; 57218228847; 57221108276; 57382339400; 57216484136","Digital analytics approach to understanding short video advertising in digital marketing",2022.0,"Journal of Marketing Theory and Practice",30.0,3.0,null,405.0,420.0,15.0,6.0,"10.1080/10696679.2022.2056487","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85130010531&doi=10.1080%2f10696679.2022.2056487&partnerID=40&md5=e9e583382073af14e82f80c9a8f3f648","Faculty of Applied Sciences and Mathematical Education, Akenten Appiah-Menka University of Skills Training and Entrepreneurial Development, Kumasi, Ghana; Department of Business and Marketing, Academic City University College, Accra, Ghana; School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, China; School of Business, George Brown College, Toronto, ON, Canada","Addo P.C., Faculty of Applied Sciences and Mathematical Education, Akenten Appiah-Menka University of Skills Training and Entrepreneurial Development, Kumasi, Ghana, Department of Business and Marketing, Academic City University College, Accra, Ghana; Akpatsa S.K., School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, China; Nukpe P., Department of Business and Marketing, Academic City University College, Accra, Ghana; Ohemeng A.A., School of Business, George Brown College, Toronto, ON, Canada; Kulbo N.B., School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, China","This study relied on datasets from global B2C and C2C to investigate the relationship between short video advertising (SV), customer satisfaction, price, quality signals, and sales in digital marketing. Using the web-scraping mining technique, the results from over twenty-three thousand online shops indicate that logistics service quality overrides the relevance of location in digital marketing. SV directly impacts sales and increases the shops’ dynamic scores, including quality of service and customer satisfaction. We identified actual online data to justify why SV adoption is essential in digital marketing and recommend logistic service quality and price fairness to improve sales in e-commerce. © 2022 Taylor & Francis Group, LLC.",{"$nulls":8},"AbuKausar M., Dhaka V.S., Kumar Singh S., Web Crawler: A Review, International Journal of Computer Applications, 63, 2, pp. 31-36, (2013); Adam L., The 7 Largest E-Commerce Companies in the World, (2019); Addo P.C., Dorgbefu M., Kulbo N.B., Akpatsa S.K., Asare A.O., Dagadu J.C., Boansi O.K., Kofi Frimpong A.N., Video ads in digital marketing and sales: A big data analytics using scrapy web crawler mining technique, Asian Journal of Research in Computer Science, 114, pp. 52-71, (2021); Addo P.C., Fang J., Asare A.O., Kulbo N.B., Clement A.P., Jiaming F., Li L., Customer engagement and purchase intention in live-streaming digital marketing platforms, The Service Industries Journal, 31, 2, pp. 1-20, (2021); Addo P.C., Fang J., Liangqiang L., Green advertising and purchase decisions in live-streaming B2C and C2C interactive marketing, International Journal of Information and Management Sciences, 31, 2, pp. 191-212, (2020); Addo P.C., Jiaming F., Kulbo N.B., Liangqiang L., COVID-19: Fear appeal favoring purchase behavior towards personal protective equipment, The Service Industries Journal, 40, 7-8, pp. 471-490, (2020); Afshari H., Peng Q., Gu P., Meng W., Reducing effects of design uncertainties on product sustainability, Cogent Engineering, 3, 1, pp. 1-17, (2016); Akdeniz M.B., Calantone R.J., Voorhees C.M., Signaling quality: An examination of the effects of marketing- and nonmarketing-controlled signals on perceptions of automotive brand quality, Journal of Product Innovation Management, 31, 4, pp. 728-743, (2014); Amazon Video in Search Ads (Beta), (2019); Ampomah E.K., Nyame G., Qin Z., Addo P.C., Gyamfi E.O., Gyan M., Stock market prediction with Gaussian Naïve Bayes machine learning algorithm, Informatica, 45, 2, (2021); Arias-Bolzmann L., Chakraborty G., Mowen J.C., Effects of absurdity in advertising: The moderating role of product category attitude and the mediating role of cognitive responses, Journal of Advertising, 29, 1, pp. 35-48, (2000); Arnold M.J., Reynolds K.E., Hedonic shopping motivations, Journal of Retailing, 79, 2, pp. 77-95, (2003); Bapna R., Jank W., Shmueli G., Consumer surplus in online auctions, Information Systems Research, 19, 4, pp. 400-416, (2008); Barigozzi F., Garella P.G., Peitz M., Advertising and prices as signals of quality: competing against a renown brand, (2006); Bellini S., Cardinali M.G., Grandi B., A structural equation model of impulse buying behaviour in grocery retailing, Journal of Retailing and Consumer Services, 36, January, pp. 164-171, (2017); Bienstock C.C., Mentzer J.T., Bird M.M., Measuring physical distribution service quality, Journal of the Academy of Marketing Science, 25, 1, pp. 31-44, (1997); Bolton L.E., Warlop L., Alba J.W., Consumer perceptions of price (Un)fairness, Journal of Consumer Research, 29, 4, pp. 474-491, (2003); Boone G., Secci J., Gallant L., Emerging trends in online advertising, Doxa Comunicación: Revista Interdisciplinar de Estudios de Comunicación y Ciencias Sociales, (2007); Breuer R., Brettel M., Engelen A., Incorporating long-term effects in determining the effectiveness of different types of online advertising, Marketing Letters, 22, 4, pp. 327-340, (2011); Briggs R., ‘A road map for online marketing strategy, Admap, pp. 27-31, (1998); Brundl S., Thomas H., Why do users broadcast? 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Empirical evidence from the financial services industry, European Management Journal, 32, 3, pp. 499-508, (2014); Van Der Wiele T., Boselie P., Hesselink M., Empirical evidence for the relationship between customer satisfaction and business performance, Managing Service Quality: An International Journal, 12, 3, pp. 184-193, (2002); Yeung M.C.H., Ging L.C., Ennew C.T., Customer satisfaction and profitability: A reappraisal of the nature of the relationship, Journal of Targeting, Measurement and Analysis for Marketing, 11, 1, pp. 24-33, (2002); Yeung R.M.W., Yee W.M.S., Chinese new year festival: Exploring consumer purchase intention at the flower market in Macau, International Journal of Hospitality Management, 29, 2, pp. 291-296, (2010); Yim M.Y.C., Yoo S.-C., Till B.D., Eastin M.S., In-store video advertising effectiveness, Journal of Advertising Research, 50, 4, pp. 386-402, (2010); Zeithaml V.A., Service quality, profitability, and the economic worth of customers: What we know and what we need to learn, Journal of the Academy of Marketing Science, 28, 1, pp. 67-85, (2000)","P.C. Addo; Faculty of Applied Sciences and Mathematical Education, Akenten Appiah-Menka University of Skills Training and Entrepreneurial Development, Kumasi, Ghana; email: prince@std.uestc.edu.cn",null,"Routledge",{"$nulls":5},1.0696679E7,null,null,null,"English","J. Mark. Theory Pract.","Article","Final",null,"Scopus","2-s2.0-85130010531"]
["Tandon U.; Mittal A.; Manohar S.","Tandon, Urvashi (57190029593); Mittal, Amit (57210989478); Manohar, Sridhar (56597608300)","57190029593; 57210989478; 56597608300","Examining the impact of intangible product features and e-commerce institutional mechanics on consumer trust and repurchase intention",2021.0,"Electronic Markets",31.0,4.0,null,945.0,964.0,19.0,18.0,"10.1007/s12525-020-00436-1","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85090967714&doi=10.1007%2fs12525-020-00436-1&partnerID=40&md5=0a070c81d38028a75d00dc6320e0f349","Chitkara Business School, Chitkara University, Chandigarh-Patiala National Highway (NH- 64), Rajpura, 140401, Punjab, India; Amity School of Business, Amity University, AUUP, Sector: 125, Pin- 201 303, Noida, Uttar Pradesh, India","Tandon U., Chitkara Business School, Chitkara University, Chandigarh-Patiala National Highway (NH- 64), Rajpura, 140401, Punjab, India; Mittal A., Chitkara Business School, Chitkara University, Chandigarh-Patiala National Highway (NH- 64), Rajpura, 140401, Punjab, India; Manohar S., Amity School of Business, Amity University, AUUP, Sector: 125, Pin- 201 303, Noida, Uttar Pradesh, India","The present study examines virtual try-on technology (VTO), return policies, pay-on-delivery (POD) mode of payment, vendor-specific guarantees, and free shipping policy of online retailers as antecedents of trust. The study also examines the role of perceived effectiveness of e-commerce institutional mechanisms (PEEIM) as a moderator between repurchase intention and trust. Data were collected through an online survey. The link to the questionnaire for the online survey was shared on different social media platforms and social networking sites. A total of 614 responses were considered for the study. Results revealed that return policies, POD mode of payment, free shipping policy, and VTO technology emerged significant predictors of trust. Surprisingly, vendor-specific guarantee had a negative relationship with trust. Trust, in turn, influenced repurchase intention. Considering the trust and survey responses, the results confirmed that PEEIM negatively moderates the relationship between trust and repurchase intention. This study contributes to the literature by empirically validating the impact of return policies, VTO technology, POD mode of payment, free shipping policies, and vendor-specific guarantees on trust. Most of these constructs have been analyzed as solitary constructs. In this study, the impact of these constructs is measured collectively, thereby indicating their importance as compared with other policies implemented by an online retailer. This is a first-of-its-kind study that validates the policies of online retailers in the Indian context. © 2020, Institute of Applied Informatics at University of Leipzig.","Free shipping policy; India; Online shopping; Pay-on-delivery (POD) mode of payment; PEEIM; Return policies; Vendor-specific guarantees; Virtual try-on technology (VTO)",{"$nulls":7},{"$cut":{"chars":20793,"head":"Akroush M.N., Al-Debei M.M., An integrated model of factors affecting consumer attitudes towards online shopping, Business Process Management Journal, 21, 6, pp. 1353-1376, (2015); Al-Debei M.M., Akroush M.N., Ashouri I., Consumer attitudes towards online shopping: The effects of trust, perceived benefits, and perceived web quality, Internet Research, 25, 5, pp. 707-733, (2015); Altug M.S., Aydinliyim T., Counteracting strategic purchase deferrals: The impact of online retailers’ return policy decisions, Manufacturing & Service Operations Management, 18, 3, pp. 376-392, (2016); Andrews D., Nonnecke B., Preece J., Electronic survey methodology: A case study in reaching hard-to-involve internet users, International journal of human-computer interaction, 16, 2, pp. 185-210, (2003); Armstrong J.S., Overton T.S., Estimating nonresponse bias in mail surveys, Journal of Marketing Research, 14, 3, pp. 396-402, (1977); Bagozzi R.P., Yi Y., On the evaluation of structural equation models, Journal of the Academy of Marketing Science, 16, 1, pp. 74-94, (1988); Bagozzi R.P., Yi Y., Multitrait-multimethod matrices in consumer research, Journal of Consumer Research, 17, 4, pp. 426-439, (1991); Can Augmented Reality Help E-shoppers Make Informed Purchases on Apparel Fit, Size, and Product Performance?, International Textile and Apparel Association Annual Conference Proceedings, 73, 1, pp. 1-2, (2016); Becerril-Arreola R., Leng M., Parlar M., Online retailers’ promotional pricing, free-shipping threshold, and inventory decisions: A simulation-based analysis, European Journal of Operational Research, 230, 2, pp. 272-283, (2013); Beck M., Crie D., I virtually try it … I want it! Virtual fitting room: A tool to increase on-line and off-line exploratory behavior, patronage and purchase intentions, Journal of Retailing and Consumer Services, 40, pp. 279-286, (2018); Blumler J.G., Katz E., The uses of mass communication Newbury Park, (1974); Bonifield C., Cole C., Schultz R.L., Product returns on the internet: A case of mixed signals?, Journal of Business Research, 63, 9-10, pp. 1058-1065, (2010); Boone T., Ganeshan R., Exploratory analysis of free shipping policies of online retailers, International Journal of Production Economics, 143, 2, pp. 627-632, (2013); Boulding W., Kalra A., Staelin R., Zeithaml V.A., A dynamic process model of service quality: From expectations to behavioral intentions, Journal of Marketing Research, 30, 1, pp. 7-27, (1993); Chang M.K., Cheung W., Tang M., Building trust online: Interactions among trust building mechanisms, Information & Management, 50, 7, pp. 439-445, (2013); Chiejina C., Olamide S.E., Investigating the significance of the ‘pay on delivery’ option in emerging prosperity of the Nigerian e-commerce sector, Journal of Marketing and Management, 5, 1, pp. 120-135, (2014); Chong A.Y.L., Lacka E., Boying L., Chan H.K., The role of social media in enhancing guanxi and perceived effectiveness of E-commerce institutional mechanisms in online marketplace, Information & Management, 55, 5, pp. 621-632, (2018); Clemes M.D., Gan C., Zhang J., An empirical analysis of online shopping adoption in Beijing, China, Journal of Retailing and Consumer Services, 21, 3, pp. 364-375, (2014); Connelly I.L., Certo S.T., Ireland R.D., Reutzel C.R., Signaling theory: A review and assessment, Journal of Management, 37, 1, pp. 39-67, (2011); Das G., Antecedents and consequences of trust: an e-tail branding perspective, International Journal of Retail & Distribution Management, 44, 7, pp. 713-730, (2016); de Leeuw E.D., Hox J.J., Dillman D.A., Mixed-mode surveys: When and why, International Handbook of Survey Methodology, pp. 299-316, (2008); Dennis C., Morgan A., Wright L.T., Jayawardhena C., The influences of social e-shopping in enhancing young women's online shopping behaviour, Journal of Customer Behaviour, 9, 2, pp. 151-174, (2010); Dwivedi Y.K., Rana N.P., Jeyaraj A., Clement M., Williams M.D., Re-examining the unified theory of acceptance and use of technology (UTAUT): Towards a revised theoretical model, Information System"}},"U. Tandon; Chitkara Business School, Chitkara University, Rajpura, Chandigarh-Patiala National Highway (NH- 64), 140401, India; email: urvashi.tandon@chitkara.edu.in",null,"Springer Science and Business Media Deutschland GmbH",{"$nulls":5},1.0196781E7,null,null,null,"English","Electron. Mark.","Article","Final",null,"Scopus","2-s2.0-85090967714"]
["Alam M.R.; Sadri A.M.; Jin X.","Alam, Md Rakibul (58694357900); Sadri, Arif Mohaimin (55673568000); Jin, Xia (35722440500)","58694357900; 55673568000; 35722440500","Identifying Public Perceptions toward Emerging Transportation Trends through Social Media-Based Interactions",2021.0,"Future Transportation",1.0,3.0,null,794.0,813.0,19.0,2.0,"10.3390/futuretransp1030044","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85133413824&doi=10.3390%2ffuturetransp1030044&partnerID=40&md5=47018586b3b3c17be5b7dd60baa5efcb","Department of Civil and Environmental Engineering, Florida International University, 10555 W Flagler St., EC 3680, Miami, 33174, FL, United States; School of Civil Engineering and Environmental Science, University of Oklahoma, 202 W. Boyd St, Norman, 73019, OK, United States","Alam M.R., Department of Civil and Environmental Engineering, Florida International University, 10555 W Flagler St., EC 3680, Miami, 33174, FL, United States; Sadri A.M., School of Civil Engineering and Environmental Science, University of Oklahoma, 202 W. Boyd St, Norman, 73019, OK, United States; Jin X., Department of Civil and Environmental Engineering, Florida International University, 10555 W Flagler St., EC 3680, Miami, 33174, FL, United States","The objective of this study is to mine and analyze large-scale social media data (rich spatio-temporal data unlike traditional surveys) and develop comparative infographics of emerging transportation trends and mobility indicators by adopting natural language processing and data-driven techniques. As such, first, around 13 million tweets for about 20 days (16 December 2019–4 January 2020) from North America were collected, and tweets closely aligned with emerging transportation and mobility trends (such as shared mobility, vehicle technology, built environment, user fees, telecommuting, and e-commerce) were identified. Data analytics captured spatio-temporal differences in social media user interactions and concerns about such trends, as well as topics of discussions formed through such interactions. California, Florida, Georgia, Illinois, New York are among the highly visible cities discussing such trends. Being positive overall, people carried more positive views on shared mobility, vehicle technology, telecommuting, and e-commerce, while being more negative on user fees, and the built environment. Ride-hailing, fuel efficiency, trip navigation, daily as well as shopping and recreational activities, gas price, tax, and product delivery were among the emergent topics. The social media data-driven framework would allow real-time monitoring of transportation trends by agencies, researchers, and professionals. © 2021 by the authors.","e-commerce; shared mobility; social media; trend; user fees; vehicle technology",{"$nulls":5},"Florida Department of Transportation, FDOT, (BDV29 977-53)","This research is funded by Florida Department of Transportation (BDV29 977-53). The opinions, findings, and conclusions expressed in this publication are those of the authors and not necessarily those of the Florida Department of Transportation or the U.S. Department of Transportation. 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Technol, 2, pp. 1-27, (2011); Huynh T., Fritz M., Schiele B., Discovery of Activity Patterns Using Topic Models, Proceedings of the UbiComp ‘08: The 10th International Conference on Ubiquitous Computing, pp. 10-19; Sun L., Yin Y., Discovering Themes and Trends in Transportation Research Using Topic Modeling, Transp. Res. Part C Emerg. Technol, 77, pp. 49-66, (2017); Griffiths T.L., Steyvers M., Finding Scientific Topics, Proc. Natl. Acad. Sci. USA, 101, pp. 5228-5235, (2004); Ahmed M.A., Sadri A.M., Pradhananga P., Elzomor M., Pradhananga N., Social Media Communication Patterns of Construction Industry in Major Disasters, Construction Research Congress 2020: Computer Applications-Selected Papers from the Construction Research Congress 2020, pp. 678-687, (2020); Howard P.N., Kollanyi B., Bots, #Strongerin, and #Brexit: Computational Propaganda During the UK-EU Referendum, SSRN Electron. J, (2017); Chu Z., Gianvecchio S., Wang H., Jajodia S., Who Is Tweeting on Twitter: Human, Bot, or Cyborg?, Proceedings of the 26th Annual Computer Security Applications Conference, pp. 21-30; Clark E.M., Williams J.R., Jones C.A., Galbraith R.A., Danforth C.M., Dodds P.S., Sifting Robotic from Organic Text: A Natural Language Approach for Detecting Automation on Twitter, J. Comput. Sci, 16, pp. 1-7, (2016); Dickerson J.P., Kagan V., Subrahmanian V.S., Using Sentiment to Detect Bots on Twitter: Are Humans More Opinionated than Bots?, Proceedings of the 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014), pp. 620-627; Sikder S.K., Behnisch M., Herold H., Koetter T., Geospatial Analysis of Building Structures in Megacity Dhaka: The Use of Spatial Statistics for Promoting Data-Driven Decision-Making, J. Geovisualization Spat. Anal, 3, (2019)","A.M. Sadri; School of Civil Engineering and Environmental Science, University of Oklahoma, Norman, 202 W. Boyd St, 73019, United States; email: sadri@ou.edu",null,"Multidisciplinary Digital Publishing Institute (MDPI)",{"$nulls":5},2.673759E7,null,null,null,"English","Future. Transp.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85133413824"]
["Diaz-Cachinero P.; Muñoz-Hernandez J.I.; Contreras J.","Diaz-Cachinero, Pablo (57203852206); Muñoz-Hernandez, Jose Ignacio (26026043200); Contreras, Javier (7201916928)","57203852206; 26026043200; 7201916928","Integrated operational planning model, considering optimal delivery routing, incentives and electric vehicle aggregated demand management",2021.0,"Applied Energy",304.0,null,117698.0,null,null,null,17.0,"10.1016/j.apenergy.2021.117698","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85114183046&doi=10.1016%2fj.apenergy.2021.117698&partnerID=40&md5=0b78d8804651c12686673c02f6c067e3","Power and Energy Analysis and Research Laboratory (PEARL), Escuela Técnica Superior de Ingeniería Industrial, University of Castilla-La Mancha, Ciudad Real, 13001, Spain; Power and Energy Analysis and Research Laboratory (PEARL), Escuela Técnica Superior de Ingenieros Industriales, University of Castilla-La Mancha, Albacete, 02071, Spain","Diaz-Cachinero P., Power and Energy Analysis and Research Laboratory (PEARL), Escuela Técnica Superior de Ingeniería Industrial, University of Castilla-La Mancha, Ciudad Real, 13001, Spain; Muñoz-Hernandez J.I., Power and Energy Analysis and Research Laboratory (PEARL), Escuela Técnica Superior de Ingenieros Industriales, University of Castilla-La Mancha, Albacete, 02071, Spain; Contreras J., Power and Energy Analysis and Research Laboratory (PEARL), Escuela Técnica Superior de Ingeniería Industrial, University of Castilla-La Mancha, Ciudad Real, 13001, Spain","The use of electric vehicles is being promoted to address emerging concerns about global warming associated with emissions from fossil fuels. Besides, in the context of parcel delivery deep growth related to e-commerce, electric vehicle is becoming an alternative to conventional fossil fuel technology. Intrinsically, the charging process implies the interdependence between the transportation and electric power systems. This paper presents a new multistage optimization-based approach that allows linking delivery routing and aggregated demand management in the transportation and electric power systems, respectively. For the routing and charging of each independent electric vehicle, battery degradation, acceleration- and speed-dependent power consumption, penalty for delivery delay, tolls, fixed charging prices and incentives for availability time are considered. An electric vehicle demand aggregator is used to guarantee the synergy between systems. Incentives are included to motivate electric vehicles to remain at charging intersections. However, attractive incentives can create electric power system congestion due to simultaneous charges on nodes. Thus, an iterative decongestion methodology is developed. The resulting model is divided into three stages: delivery allocation, delivery routing for each independent electric vehicle and optimal energy management by electric vehicle demand aggregator. The resulting optimization problem is cast as a mixed-integer linear programming model for the first two stages and a linear programming model for the third stage. Numerical results demonstrate the effectiveness of the proposed model on a real 284-intersection map with a set of 100 electric vehicles, showing that incentives allow electric vehicle demand aggregator to achieve cost savings of 8.5%. © 2021 The Author(s)","Electric vehicle demand aggregator; Incentives for availability time; Mixed-integer linear programming; Power system decongestion methodology; Routing problem","Availability; Charging (batteries); Costs; Electric vehicles; Fossil fuels; Global warming; Iterative methods; Traffic congestion; Electric vehicle demand aggregator; Incentive for availability time; Integer Linear Programming; Mixed integer linear; Mixed-integer linear programming; Operational planning; Power; Power system decongestion methodology; Routing problems; Routings; detection method; electric vehicle; global warming; integrated approach; methodology; model; Integer programming",{"$nulls":4},"Ministerio de Ciencia, Innovación y Universidades, MCIU, (RTI2018-096108-A-I00, RTI2018-098703-B-I00); Universidad de Castilla-La Mancha, UCLM, (2021-GRIN-30952)","This work was supported in part by the Ministry of Science, Innovation and Universities of Spain, under Projects RTI2018-096108-A-I00 and RTI2018-098703-B-I00 (MCIU/AEI/FEDER, UE), and in part by the University of Castilla-La Mancha, under Grant 2021-GRIN-30952 . ","Kester J., Noel L., de Rubens G.Z., Sovacool B.K., Policy mechanisms to accelerate electric vehicle adoption: A qualitative review from the Nordic Region, Renew Sustain Energy Rev, 94, pp. 719-731, (2018); Biresselioglu M.E., Kaplan M.D., Yilmaz B.K., Electric mobility in Europe: A comprehensive review of motivators and barriers in decision making processes, Transp Res A, 109, pp. 1-13, (2018); Joerss M., Schroder J., Neuhaus F., Klink C., Mann F., Parcel delivery: The future of last mile, (2016); Zhou C., Qian K., Allan M., Zhou W., Modeling of the cost of EV battery wear due to V2G application in power systems, IEEE Trans Energy Convers, 26, 4, pp. 1041-1050, (2011); Hannan M.A., Lipu M.H., Hussain A., Mohamed A., A review of lithium-ion battery state of charge estimation and management system in electric vehicle applications: Challenges and recommendations, Renew Sustain Energy Rev, 78, pp. 834-854, (2017); Marmaras C., Xydas E., Cipcigan L., Simulation of electric vehicle driver behaviour in road transport and electric power networks, Transp Res C, 80, pp. 239-256, (2017); Van Haaren R., Assessment of electric cars’ range requirements and usage patterns based on driving behavior recorded in the National Household Travel Survey of 2009, 51, (2011); Sundstrom O., Guzzella L., Soltic P., Optimal hybridization in two parallel hybrid electric vehicles using dynamic programming, IFAC Proc Vol, 41, 2, pp. 4642-4647, (2008); Wei W., Danman W., Qiuwei W., Shafie-Khah M., Catalao J.P., Interdependence between transportation system and power distribution system: A comprehensive review on models and applications, J Mod Power Syst Clean Energy, 7, 3, pp. 433-448, (2019); Nour M., Chaves-Avila J.P., Magdy G., Sanchez-Miralles A., Review of positive and negative impacts of electric vehicles charging on electric power systems, Energies, 13, 18, (2020); Kumar R.R., Alok K., Adoption of electric vehicle: A literature review and prospects for sustainability, J Clean Prod, 253, (2020); Goeke D., Schneider M., Routing a mixed fleet of electric and conventional vehicles, European J Oper Res, 245, 1, pp. 81-99, (2015); Miao H., Chen G., Li C., Dong Z.Y., Wong K.P., Operating expense optimization for EVs in multiple depots and charge stations environment using evolutionary heuristic method, IEEE Trans Smart Grid, 9, 6, pp. 6599-6611, (2017); Montoya A., Gueret C., Mendoza J.E., Villegas J.G., The electric vehicle routing problem with nonlinear charging function, Transp Res B, 103, pp. 87-110, (2017); Shao S., Guan W., Bi J., Electric vehicle-routing problem with charging demands and energy consumption, IET Intell Transp Syst, 12, 3, pp. 202-212, (2018); Kosmanos D., Maglaras L.A., Mavrovouniotis M., Moschoyiannis S., Argyriou A., Maglaras A., Et al., Route optimization of electric vehicles based on dynamic wireless charging, IEEE Access, 6, pp. 42551-42565, (2018); Cerna F.V., Pourakbari-Kasmaei M., Romero R.A., Rider M.J., Optimal delivery scheduling and charging of EVs in the navigation of a city map, IEEE Trans Smart Grid, 9, 5, pp. 4815-4827, (2018); Yu J.J.Q., Two-stage request scheduling for autonomous vehicle logistic system, IEEE Trans Intell Transp Syst, 20, 5, pp. 1917-1929, (2019); Cerna F.V., Pourakbari-Kasmaei M., Lehtonen M., Contreras J., Efficient automation of an HEV heterogeneous fleet using a two-stage methodology, IEEE Trans Veh Technol, 68, 10, pp. 9494-9506, (2019); Doppstadt C., Koberstein A., Vigo D., The hybrid electric vehicle-traveling salesman problem with time windows, European J Oper Res, 284, 2, pp. 675-692, (2020); Diaz-Cachinero P., Munoz-Hernandez J.I., Contreras J., Munoz-Delgado G., An enhanced delivery route operational planning model for electric vehicles, IEEE Access, 8, pp. 141762-141776, (2020); Huang S., Wu Q., Oren S.S., Li R., Liu Z., Distribution locational marginal pricing through quadratic programming for congestion management in distribution networks, IEEE Trans Power Syst, 30, 4, pp. 2170-2178, (2015); Amini M.H., Karabasoglu O., Optimal operation of interdependent power systems and electrified transportation networks, Energies, 11, 1, (2018); Liu Z., Wu Q., Oren S.S., Huang S., Li R., Cheng L., Distribution locational marginal pricing for optimal electric vehicle charging through chance constrained mixed-integer programming, IEEE Trans Smart Grid, 9, 2, pp. 644-654, (2018); Clairand J.-M., Rodriguez-Garcia J., Alvarez-Bel C., Smart charging for electric vehicle aggregators considering users’ preferences, IEEE Access, 6, pp. 54624-54635, (2018); Wei W., Wu L., Wang J., Mei S., Network equilibrium of coupled transportation and power distribution systems, IEEE Trans Smart Grid, 9, 6, pp. 6764-6779, (2018); Zhou Y., Kumar R., Tang S., Incentive-based distributed scheduling of electric vehicle charging under uncertainty, IEEE Trans Power Syst, 34, 1, pp. 3-11, (2019); Sun Y., Chen Z., Li Z., Tian W., Shahidehpour M., EV charging schedule in coupled constrained networks of transportation and power system, IEEE Trans Smart Grid, 10, 5, pp. 4706-4716, (2019); Geng L., Lu Z., He L., Zhang J., Li X., Guo X., Smart charging management system for electric vehicles in coupled transportation and power distribution systems, Energy, 189, (2019); Ding Z., Lu Y., Lai K., Yang M., Lee W.-J., Optimal coordinated operation scheduling for electric vehicle aggregator and charging stations in an integrated electricity-transportation system, Int J Electr Power Energy Syst, 121, (2020); Lv S., Wei Z., Chen S., Sun G., Wang D., Integrated demand response for congestion alleviation in coupled power and transportation networks, Appl Energy, 283, (2021); Mohsenian-Rad A.-H., Wong V.W., Jatskevich J., Schober R., Leon-Garcia A., Autonomous demand-side management based on game-theoretic energy consumption scheduling for the future smart grid, IEEE Trans Smart Grid, 1, 3, pp. 320-331, (2010); OPTIMIZATION-DIRECT, The ODH-CPLEX website, (2020); IBM, The IBM ILOG CPLEX website, (2020); Hochba D.S., Approximation algorithms for NP-hard problems, (1997); Diaz-Cachinero P., Munoz Hernandez J.I., Contreras J., Munoz-Delgado G., Electronic companion – An enhanced delivery route operational planning model for electric vehicles, (2020); Teoh T., Kunze O., Teo C.-C., Wong Y.D., Decarbonisation of urban freight transport using electric vehicles and opportunity charging, Sustainability, 10, 9, (2018); Han T.T.G., Suitability of battery electric vehicles and opportunity charging for urban freight transport: An evaluation framework, (2018); Diaz-Cachinero P., Munoz Hernandez J.I., Contreras J., Electronic companion – Integrated operational planning model, considering optimal delivery routing, incentives and electric vehicle aggregated demand management, (2021); GAMS, The GAMS development corporation website, (2020); Floudas C.A., Nonlinear and mixed-integer optimization: Fundamentals and Applications, (1995)","J. Contreras; Power and Energy Analysis and Research Laboratory (PEARL), Escuela Técnica Superior de Ingeniería Industrial, University of Castilla-La Mancha, Ciudad Real, 13001, Spain; email: javier.contreras@uclm.es",null,"Elsevier Ltd",{"$nulls":5},3062619.0,null,"APEND",null,"English","Appl. Energy","Article","Final","All Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85114183046"]
["Settey T.; Gnap J.; Synák F.; Skrúcaný T.; Dočkalik M.","Settey, Tomáš (57204825945); Gnap, Jozef (6505759592); Synák, František (57194465038); Skrúcaný, Tomáš (58026568500); Dočkalik, Marek (57223323459)","57204825945; 6505759592; 57194465038; 58026568500; 57223323459","Research into the impacts of driving cycles and load weight on the operation of a light commercial electric vehicle",2021.0,"Sustainability (Switzerland)",13.0,24.0,13872.0,null,null,null,12.0,"10.3390/su132413872","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121545573&doi=10.3390%2fsu132413872&partnerID=40&md5=9858f565d85551b4d24ab5889db8ed77","Department of Road and Urban Transport, Faculty of Operation and Economics of Transport and Communications, University of Zilina, Žilina, 010 26, Slovakia","Settey T., Department of Road and Urban Transport, Faculty of Operation and Economics of Transport and Communications, University of Zilina, Žilina, 010 26, Slovakia; Gnap J., Department of Road and Urban Transport, Faculty of Operation and Economics of Transport and Communications, University of Zilina, Žilina, 010 26, Slovakia; Synák F., Department of Road and Urban Transport, Faculty of Operation and Economics of Transport and Communications, University of Zilina, Žilina, 010 26, Slovakia; Skrúcaný T., Department of Road and Urban Transport, Faculty of Operation and Economics of Transport and Communications, University of Zilina, Žilina, 010 26, Slovakia; Dočkalik M., Department of Road and Urban Transport, Faculty of Operation and Economics of Transport and Communications, University of Zilina, Žilina, 010 26, Slovakia","The European Parliament has adopted Directive 2019/1161 on the promotion of environmentally friendly and energy-efficient road transport vehicles, which also defines the obligations and forms of support for the procurement of environmentally friendly vehicles in urban logistics. The increase in the number of shipments delivered within e-commerce, which is also the result of the COVID-19 pandemic, requires a transition to a sustainable logistics system. New research questions are being raised in the preparation of new projects for the introduction of small electric commercial vehicles in particular. One of the main research questions about deployment itself is whether light commercial electric vehicles are able to fully replace conventionally powered vehicles. What operating conditions are optimal for the operation of them? How does load weight affect the energy efficiency of operating a light commercial electric vehicle? The authors decided to carry out research into the impacts of weight and the nature of a driving cycle under laboratory conditions to eliminate all external factors that could distort individual measurements and their results. In order to simulate driving cycles, an urban driving cycle was designed on the basis of the course of speed, acceleration, deceleration and slope conditions of roads in the selected regional city of Žilina (Slovakia). In the case of the operation of an electrically powered light commercial vehicle, the impact of load weight on the range of the vehicle is low, and is below the level of the theoretical maximum range of the vehicle in urban logistics applications. The operation of electrically powered vehicles in hilly terrains with relatively longer gradients and steeper slopes increases electricity consumption and, thereby, reduces their range. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.","Electric vehicle; Sustainable city logistics; Urban driving cycle","Slovakia; Zilina; Zilinsky; electric vehicle; energy efficiency; environmental impact; operations technology; research work",{"$nulls":4},"European Regional Development Fund, ERDF","Funding: This research was facilitated by the support under the Operational Program Integrated Infrastructure for the following project: Identification and possibilities of the implementation of new technological measures in transport to achieve safe mobility during a pandemic caused by COVID-19 (ITMS code: 313011AUX5), co-financed by the European Regional Development Fund.","Directive (EU) 2019/1161 of the European Parliament and of the Council of 20 June 2019 Amending Directive 2009/33/EC on the Promotion of Clean and Energy-Efficient Road Transport Vehicles; Central Register of Vehicles of the Slovak Republic; Vehicles in Use Europe, (2021); Light Commercial Vehicles (Up to 3.5t) New Registrations by Fuel Type in the European Union; Merchan A.L., Leonard A., Limbourg S., Mostert M., Life cycle externalities versus external costs: The case of inland freight transport in Belgium, Transp. 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Econ, 85, (2021); Juvvala R., Sarmah S.P., Evaluation of policy options supporting electric vehicles in city logistics: A case study, Sustain. Cities Soc, 74, (2021); Napoli G., Polimeni A., Micari S., Dispenza G., Antonucci V., Andaloro L., Freight distribution with electric vehicles: A case study in Sicily. Delivery van development, Transp. Eng, 3, (2021); Moolenburgh E.A., Van Duin J.H.R., Balm S., Van Altenburg M., Van Amstel W.P., Logistics concepts for light electric freight vehicles: A multiple case study from the Netherlands, Transp. Res. Procedia, 46, pp. 301-308, (2020); Carrese F., Colombaroni C., Fusco G., Accessibility analysis for Urban Freight Transport with Electric Vehicles, Transp. Res. Procedia, 52, pp. 3-10, (2021); Fiori C., Arcidiacono V., Fontaras G., Makridis M., Mattas K., Marzano V., Thiel C., Ciuffo B., The effect of electrified mobility on the relationship between traffic conditions and energy consumption, Transp. Res. Part D Transp. 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Procedia, 46, pp. 3-12, (2020); Kretzschmar J., Gebhardt K., Theiss C., Schau V., Range prediction models for e-vehicles in urban freight logistics based on machine learning, International Conference on Data Mining and Big Data, pp. 175-184, (2016); Wei C., Sun X., Chen Y., Zang L., Bai S., Comparison of architecture and adaptive energy management strategy for plug-in hybrid electric logistics vehicle, Energy, 230, (2021); Khalfi J., Boumaaz N., Soulmani A., Laadissi E.M., An electric circuit model for a lithium-ion battery cell based on automotive drive cycles measurements, Int. J. Electr. Comput. Eng, 11, pp. 2088-8708, (2021); Shaobo X., Qiankun Z., Xiaosong H., Yonggang L., Xianke L., Battery sizing for plug-in hybrid electric buses considering variable route lengths, Energy, 226, (2021); Tong H.Y., Ng K., Development of bus driving cycles using a cost effective data collection approach, Sustain. Cities Soc, 69, (2021); Komorska I., Puchalski A., Niewczas A., Slezak M., Szczepanski T., Adaptive Driving Cycles of EVs for Reducing Energy Consumption, Energies, 14, (2021); Hu T., Li Y., Zhang Z., Zhao Y., Liu D., Energy Management Strategy of Hybrid Energy Storage System Based on Road Slope Information, Energies, 14, (2021); Serrano-Hernandez A., Ballano A., Faulin J., Selecting Freight Transportation Modes in Last-Mile Urban Distribution in Pamplona (Spain): An Option for Drone Delivery in Smart Cities, Energies, 14, (2021); Arrieta-Prieto M., Ismael A., Rivera-Gonzalez C., Mitchell J., Location of Urban Micro-consolidation Centers to Reduce Social Cost of Last-Mile Deliveries of Cargo: A Heuristic Approach, Networks, pp. 1-22, (2021); Soica A., Budala A., Monescu V., Sommer S., Owczarzak W., Method of estimating the rolling resistance coefficient of vehicle tyre using the roller dynamometer, Proc. Inst. Mech. Eng. Part D J. Automob. 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Veh. J, 6, pp. 373-379, (2013); Masood K., Zoppi M., Fremont V., Molfino R.M., From Drive-By-Wire to Autonomous Vehicle: Urban Freight Vehicle Perspectives, Sustainability, 13, (2021); Amaya J., Delgado-Lindeman M., Arellana J., Allen J., Urban freight logistics: What do citizens perceive?, Transp. Res. Part E Logist. Transp. Rev, 152, (2021)","J. Gnap; Department of Road and Urban Transport, Faculty of Operation and Economics of Transport and Communications, University of Zilina, Žilina, 010 26, Slovakia; email: jozef.gnap@fpedas.uniza.sk",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85121545573"]
["Prajapati D.; Chan F.T.S.; Daultani Y.; Pratap S.","Prajapati, Dhirendra (57215023349); Chan, Felix T. S. (7202586517); Daultani, Yash (56677743400); Pratap, Saurabh (56667217800)","57215023349; 7202586517; 56677743400; 56667217800","Sustainable vehicle routing of agro-food grains in the e-commerce industry",2022.0,"International Journal of Production Research",60.0,24.0,null,7319.0,7344.0,25.0,20.0,"10.1080/00207543.2022.2034192","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85125260341&doi=10.1080%2f00207543.2022.2034192&partnerID=40&md5=80ce7a8d2737e583d893e8b240b2ea69","Indian Institute of Information Technology, Jabalpur, India; Department of Decision Sciences, Macau University of Science and Technology, Taipa, Macao; Operations Management Group, Indian Institute of Management Lucknow, Lucknow, India; Department of Mechanical Engineering, Indian Institute of Technology (IIT BHU), Varanasi, India","Prajapati D., Indian Institute of Information Technology, Jabalpur, India; Chan F.T.S., Department of Decision Sciences, Macau University of Science and Technology, Taipa, Macao; Daultani Y., Operations Management Group, Indian Institute of Management Lucknow, Lucknow, India; Pratap S., Department of Mechanical Engineering, Indian Institute of Technology (IIT BHU), Varanasi, India","As a result of rapid industrialisation, rising food demand globally, and, increasing concerns associated with food safety and quality, the implementation of sustainable supply chain concepts is becoming critically important to the agro-food sector. This paper introduces an integrated first-mile pickup and last-mile delivery logistics problem, where agro-food grains are available at multiple farmer’s locations and are in demand by businesses like e-retailers, supermarkets, grocery shops, restaurants, hotels, etc. In addition, this work addresses a sustainable framework for agro-food grains supply chain (AFGSC) in urban and rural areas for e-commerce in developing countries. The proposed optimisation model considers costs related to first-mile pickup, transportation with last-mile delivery, carbon emission tax, inventory holding, vehicle and food damage due to accidents, and penalties on late pickup and delivery. This model also takes environmental and social (due to accidents) sustainability aspects into consideration, along with the economic aspects of sustainability. To solve the large complex practical scenarios by using four nature-inspired algorithms. The obtained results of this study are used to recommend significant managerial insights for implementing AFGSC in the e-commerce industry in considering practical conditions. Moreover, policy implications in terms of economic, social, and environmental aspects of sustainability are also discussed. © 2022 Informa UK Limited, trading as Taylor & Francis Group.","agro-food grains supply chain; E-commerce; metaheuristic; sustainability; triple-bottom line","Accidents; Biomimetics; Developing countries; Electronic commerce; Pickups; Public policy; Supply chains; Vehicle routing; Agro foods; Agro-food grain supply chain; E- commerces; Economic aspects; First mile; Food grain; Industrialisation; Last mile; Metaheuristic; Triple Bottom Line; Sustainable development",{"$nulls":6},"Allaoui H., Guo Y., Choudhary A., Bloemhof J., Sustainable Agro-Food Supply Chain Design Using Two-Stage Hybrid Multi-Objective Decision-Making Approach, Computers and Operations Research, 89, pp. 369-384, (2018); Allen J., Piecyk M., Piotrowska M., McLeod F., Cherrett T., Ghali K., Nguyen T., Et al., Understanding the Impact of E-Commerce on Last-Mile Light Goods Vehicle Activity in Urban Areas: The Case of London, Transportation Research Part D: Transport and Environment, 61, pp. 325-338, (2018); 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Zhang Y., Sun L., Hu X., Zhao C., Order Consolidation for the Last-Mile Split Delivery in Online Retailing, Transportation Research Part E: Logistics and Transportation Review, 122, pp. 309-327, (2019); Zhu Z., Chu F., Dolgui A., Chu C., Zhou W., Piramuthu S., Recent Advances and Opportunities in Sustainable Food Supply Chain: A Model-Oriented Review, International Journal of Production Research, 56, 17, pp. 5700-5722, (2018); Zhu L., Hu D., Study on the Vehicle Routing Problem Considering Congestion and Emission Factors, International Journal of Production Research, 57, 19, pp. 6115-6129, (2019)","F.T.S. Chan; Department of Decision Sciences, Macau University of Science and technology, Taipa, Macao; email: felix1202.chan@connect.polyu.hk",null,"Taylor and Francis Ltd.",{"$nulls":5},207543.0,null,"IJPRB",null,"English","Int J Prod Res","Article","Final",null,"Scopus","2-s2.0-85125260341"]
["Chen H.; Hu Z.; Solak S.","Chen, Heng (56201833000); Hu, Zhangchen (57195997423); Solak, Senay (24588050300)","56201833000; 57195997423; 24588050300","Improved delivery policies for future drone-based delivery systems",2021.0,"European Journal of Operational Research",294.0,3.0,null,1181.0,1201.0,20.0,21.0,"10.1016/j.ejor.2021.02.039","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85103007115&doi=10.1016%2fj.ejor.2021.02.039&partnerID=40&md5=a0a8852bf9c1dcc224aa8a5282031192","College of Business, University of Nebraska-Lincoln, United States; Isenberg School of Management, University of Massachusetts Amherst, United States","Chen H., College of Business, University of Nebraska-Lincoln, United States; Hu Z., Isenberg School of Management, University of Massachusetts Amherst, United States; Solak S., Isenberg School of Management, University of Massachusetts Amherst, United States","It is expected that commercial use of drones in the near future will involve delivery service operations by e-commerce companies. We consider relevant strategic and tactical decisions that these retailers will face in drone-based delivery operations, and derive policies on when to offer drone delivery, what delivery capacity to maintain, and what amount to charge for such deliveries. To this end, we develop a Markov decision process (MDP) framework, and introduce two heuristic procedures, through which near-optimal closed-form solutions can be obtained. The results are aimed at helping online retailers to determine in real time whether and to what extent to offer drone-based delivery for given product categories in different service zones. In addition, we study delivery fee structures and identify drone-based delivery pricing strategies under two widely used delivery pricing schemes. For capacity planning decisions, we describe an algorithm to identify the fleet size to utilize to fulfill uncertain demand in a given service region. We also identify structural characteristics on how these decisions and the expected profit are affected by changes in various problem parameters, which can generate generic insights on drone-based delivery operations for e-commerce companies. We find that retailers should prioritize more profitable items when allocating drone delivery capacity, and invest in adding more drones when per order opportunity costs are higher and promised delivery time thresholds are shorter. Retailers can potentially boost their net profits by increasing the effective promised delivery time threshold and/or decreasing the effective delivery delay costs and per order opportunity costs. © 2021 Elsevier B.V.","Capacity management; Delivery fee; Drone-based delivery; E-commerce; Stochastic dynamic programming","Costs; Drones; Electronic commerce; Heuristic methods; Markov processes; Profitability; Reinforcement learning; Sales; Stochastic systems; Capacity management; Delivery capacity; Delivery fee; Delivery systems; Delivery time; Drone-based delivery; E- commerces; Opportunity costs; Stochastic dynamic programming; Time thresholds; Dynamic programming",{"$nulls":6},"Agatz N., Bouman P., Schmidt M., Optimization approaches for the traveling salesman problem with drone, Transportation Science, 52, 4, pp. 965-981, (2018); Alidaee B., Wang H., Landram F., On the flexible demand assignment problems: Case of unmanned aerial vehicles, IEEE Transactions on Automation Science and Engineering, 8, 4, pp. 865-868, (2011); Allon G., Federgruen A., Pierson M., How much is a reduction of your customers’ wait worth? 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Chen; College of Business, University of Nebraska-Lincoln, United States; email: heng@unl.edu",null,"Elsevier B.V.",{"$nulls":5},3772217.0,null,"EJORD",null,"English","Eur J Oper Res","Article","Final",null,"Scopus","2-s2.0-85103007115"]
["Jafarzadeh H.; Tafti M.; Intezari A.; Sohrabi B.","Jafarzadeh, Hamed (56299420900); Tafti, Mahdi (57223650455); Intezari, Ali (57189179363); Sohrabi, Babak (56016849700)","56299420900; 57223650455; 57189179363; 56016849700","All's well that ends well: Effective recovery from failures during the delivery phase of e-retailing process",2021.0,"Journal of Retailing and Consumer Services",62.0,null,102602.0,null,null,null,13.0,"10.1016/j.jretconser.2021.102602","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85105971646&doi=10.1016%2fj.jretconser.2021.102602&partnerID=40&md5=e8bc6f054fdbe912f74b914e0db6a387","School of Management, Massey University, New Zealand; Faculty of Management, University of Tehran, Iran; UQ Business School, University of Queensland, Australia","Jafarzadeh H., School of Management, Massey University, New Zealand; Tafti M., Faculty of Management, University of Tehran, Iran; Intezari A., UQ Business School, University of Queensland, Australia; Sohrabi B., Faculty of Management, University of Tehran, Iran","E-commerce retail has been on an exponential growth since late-1990s and now with COVID-19 crisis it is more popular and prevalent than ever before. But failures during the e-retailing process, specially when the business is under pressure, is a severe challenge with deteriorative impacts on customers' attitude and behavioral intention. While the majority of failures during e-retail process takes place at the ‘product delivery phase’ (the last phase of e-commerce process), little attention has been paid towards investigating how e-retailers can effectively recover from service failure encounters during the delivery phase. Seeking to address this gap, the present study draws on cognitive dissonance theory to examine the determinants of effective recovery from service failure encounters during the delivery phase of e-retailing. In doing so, a scenario-based experiment was conducted to collect data from 320 online customers. The findings provide empirical insights on how perceived recovery endeavor interacts with criticality of situation and brand equity to mitigate the negative consequences of service failure at delivery phase. The theoretical and managerial implications of the findings are discussed along with avenues for future research. © 2021 Elsevier Ltd","ANOVA; Brand strength; Compensation; Criticality; Delivery failure; Delivery recovery; Hypothetical scenario-based experiment; Recovery endeavor; Service failure in delivery phase; Service recovery; Time","compensation system; consumption behavior; electronic commerce; experiment; marketing; retailing; service sector; variance analysis",{"$nulls":6},"Aaker D., Brand extensions: the good, the bad, and the ugly, MIT Sloan Manag. Rev., 31, 4, (1990); Ahmadi A., Thai Airways: key influencing factors on customers' word of mouth, Int. J. Qual. Reliab. Manag., (2019); Akter S., D'ambra J., Ray P., Service quality of mhealth platforms: development and validation of a hierarchical model using Pls, Electron. Mark., 20, pp. 209-227, (2010); Babin B.J., Zhuang W., Borges A., Managing service recovery experience: effects of the forgiveness for older consumers, J. 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Sci., 38, pp. 654-675, (2010); Zhou Y., Tsang A.S., Huang M., Zhou N., Does delaying service-failure resolution ever make sense?, J. Bus. Res., 67, pp. 159-166, (2014)","H. Jafarzadeh; School of Management, Massey University, New Zealand; email: H.Jafarzadeh@massey.ac.nz",null,"Elsevier Ltd",{"$nulls":5},9696989.0,null,null,null,"English","J. Retail. Consum. Serv.","Article","Final",null,"Scopus","2-s2.0-85105971646"]
["Asdecker B.","Asdecker, Björn (35848337500)",3.58483375E10,"Building the E-Commerce Supply Chain of the Future: What Influences Consumer Acceptance of Alternative Places of Delivery on the Last-Mile",2021.0,"Logistics",5.0,4.0,90.0,null,null,null,6.0,"10.3390/logistics5040090","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85136067692&doi=10.3390%2flogistics5040090&partnerID=40&md5=e5c414bb88e371b30378092e0d630f5a","Department of Business Administration, University of Bamberg, Bamberg, 96045, Germany","Asdecker B., Department of Business Administration, University of Bamberg, Bamberg, 96045, Germany","Background: To cope with the expected further growth in e-commerce and to be able to continue delivering at low costs, new concepts for the last-mile are needed. This paper reviews the literature and qualitatively investigates which factors influence the acceptance of four alternative place-of-delivery innovations in a business-to-consumer (B2C) context: (1) parcel lockers, (2) reception boxes, (3) trunk delivery, and (4) home access systems; Methods: The available literature was reviewed. Furthermore, 37 interviews were conducted and analyzed using the deductive category development method. In the following, abductive reasoning can derive detailed research models that may form the basis for future confirmative studies; Results: The research gains more detailed insights into how consumers perceive innovative last-mile place-of-delivery concepts. The study provides a clearer picture of what factors influence the intention to use such alternative services; Conclusions: The results can be used by logistics service providers and e-tailers through targeted communication efforts and lay the groundwork for further confirmatory research. © 2021 by the author.","customer acceptance; e-commerce; home-access systems; last-mile; parcel lockers; place of delivery; reception boxes; trunk delivery",{"$nulls":7},"KEP-Studie 2019; Kulkarni S.R., Barge P., Effect of COVID-19 on the Shift in Consumer Preferences with Respect to Shopping Modes (Offline/Online) for Groceries: An Exploratory Study, Int. J. 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Opportunities and challenges for smart locks from a consumer perspective, Res. Transp. Econ, 87, (2019); Musolino G., Rindone C., Vitetta A., Passengers and freight mobility with electric vehicles: A methodology to plan green transport and logistic services near port areas, Transp. Res. Procedia, 37, pp. 393-400, (2019); Fishbein M., Ajzen I., Predicting and Changing Behavior: The Reasoned Action Approach, (2010); Patton M.Q., Qualitative Research & Evaluation Methods: Integrating Theory and Practice, (2015); Eisenhardt K.M., Building Theories from Case Study Research, Acad. Manag. Rev, 14, pp. 532-550, (1989); Howland D., How Retail’s Gender Gap Affects Retailers; Jezerc G., Mind the Gap: The Gender Effect on Shopping Habits and Technology Disruptors, (2018); Mayring P., Qualitative Content Analysis, Forum Qual. Soc. Res, 1, pp. 1-10, (2000); Ajzen I., The theory of planned behavior, Organ. Behav. Hum. Decis. 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Rev, 14, pp. 490-495, (1989); Venkatesh V., Morris M.G., Davis G.B., Davis F.D., User Acceptance of Information Technology: Toward a Unified View, MIS Q, 27, pp. 425-478, (2003)","B. Asdecker; Department of Business Administration, University of Bamberg, Bamberg, 96045, Germany; email: bjoern.asdecker@uni-bamberg.de",null,"MDPI",{"$nulls":5},2.305629E7,null,null,null,"English","Logist.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85136067692"]
["Xie C.; Wang H.; Jiao J.","Xie, Cuijie (57681691900); Wang, Haijuan (57681415900); Jiao, Jianhong (57682251200)","57681691900; 57681415900; 57682251200","Cross-Border E-Commerce Logistics Collaboration Model Based on Supply Chain Theory",2022.0,"Security and Communication Networks",2022.0,null,1498765.0,null,null,null,3.0,"10.1155/2022/1498765","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85129977950&doi=10.1155%2f2022%2f1498765&partnerID=40&md5=07c5fa1453a9e45dd4dda5d076424619","Department of Logistics Management, Hebei Jiaotong Vocational and Technical College, Hebei, Shijiazhuang, 050035, China","Xie C., Department of Logistics Management, Hebei Jiaotong Vocational and Technical College, Hebei, Shijiazhuang, 050035, China; Wang H., Department of Logistics Management, Hebei Jiaotong Vocational and Technical College, Hebei, Shijiazhuang, 050035, China; Jiao J., Department of Logistics Management, Hebei Jiaotong Vocational and Technical College, Hebei, Shijiazhuang, 050035, China","With the rapid development of cross-border e-commerce, however, logistics has become a bottleneck in the development of cross-border electricity traders. The results of studies on cross-border e-commerce logistics are still less, and the relevant theoretical studies are not yet mature enough. As cross-border e-commerce occupies a share of foreign trade in foreign trade increases, so does their influence. In order to eliminate bottlenecks in the cross-border logistics of an electric enterprise, it is of great importance to systematically study the issues of synergy in the logistics of the supply chain of a cross-border electric enterprise and validate how cross-border traders and cross-border logistics work together using cross-border discussion based on the perspective of cross-border e-commerce ecosystem. At the same time, an analysis of the need for cross-border logistics collaboration electricity traders and cross-border logistics is being carried out, as well as an in-depth study of synergy mechanisms between cross-border electricity traders and cross-border logistics based on a cross-border ecosystem perspective. The empirical results show that cross-border logistics is available function service capability; cross-border logistics information sharing level, cross-border logistics resource optimization and allocation capability, and the opening level of cross-border logistics environment have different contributions to the impact on the efficiency of cross-border e-commerce logistics. Among them, the level of cross-border logistics information exchange has the most significant influence on the logistics efficiency of cross-border traders, followed by cross-border logistics functional services capabilities, again the level of openness of the cross-border logistics environment, and finally, the ability to optimally distribute cross-border logistics resources.  © 2022 Cuijie Xie et al.",null,"Ecosystems; Efficiency; Electronic commerce; Information dissemination; International trade; Chain theory; Collaboration models; Cross-border; E- commerces; Enterprise IT; Logistics information; Logistics resources; Model-based OPC; Service capability; Theoretical study; Supply chains",{"$nulls":6},"Di C., Research on the product logistics cost control strategy based on the multi-source supply chain theory, Intelligent Automation & Soft Computing, 26, 3, pp. 557-567, (2020); Ghalehkhondabi I., Maihami R., Sustainable municipal solid waste disposal supply chain analysis under price-sensitive demand: A game theory approach, Waste Management & Research, 38, 3, pp. 300-311, (2019); Matsui K., Optimal bargaining timing of a wholesale price for a manufacturer with a retailer in a dual-channel supply chain, European Journal of Operational Research, 287, 1, pp. 225-236, (2020); Guan S., Smart e-commerce logistics construction model based on big data analytics, Journal of Intelligent and Fuzzy Systems, 40, 2, pp. 1-9, (2020); Rasti Borazjani Faghat E., Khani N., Alemtabriz A., A paradigmatic model for shared value innovation management in the supply chain, International Journal of Innovation Science, 12, 1, pp. 142-166, (2020); Baier C., Beckmann M., Heidingsfelder J., Hidden allies for value chain responsibility? a system theory perspective on aligning sustainable supply chain management and trade compliance, International Journal of Physical Distribution & Logistics Management, 50, 4, pp. 439-456, (2020); Perdana Y.R., Ciptono W.S., Setiawan K., Broad span of supply chain integration: Theory development, International Journal of Retail & Distribution Management, 47, 2, pp. 186-201, (2019); Zatta F.N., Tambosi Filho E., Freitas R.R., Goncalves W., Oliveira R.R., Segura L.C., Formigoni H., Schirrmeister R., Operational competencies rooted in resource theory: Operations strategy and supply chain performance, Independent Journal of Management & Production, 12, 2, pp. 756-780, (2021); Zhang X., Sun B., Chen X., Chu X., Yang J., An approach to evaluating sustainable supply chain risk management based on bwm and linguistic value soft set theory, Journal of Intelligent and Fuzzy Systems, 39, 11, pp. 1-14, (2020); Lopatin A., Use of rough set theory and neural networks methods in supply chain management, Modern Economics, 22, 1, pp. 44-49, (2020); Tarigan Z.J.H., Siagian H., Sebayang P., The impact of implementing enterprise resources planning (erp) project on firm performance and organizational citizenship behavior as a moderating, Journal of Project Management, 5, 4, pp. 227-236, (2020); Guo J., Cao J., Yang Y., Chao L.U., Hua H., User demand oriented research framework of value morphology for rei and its application analysis, Power System Technology, 44, 2, pp. 493-504, (2020); Jafarzadehghoushchi S., Hushyar I., Designing a closed-loop supply chain network and providing a multi-objective mathematical model to select a third-party logistics company and supplier simultaneously, The International Journal of Industrial Engineering: Theory, Applications and Practice, 27, 2, pp. 245-275, (2020); Sun P., Gu L., Optimization of cross-border e-commerce logistics supervision system based on internet of things technology, Complexity, 2021, 4, pp. 1-11, (2021); Feng J., Liu B., Decision analysis of cooperative advertising for competitive supply chain considering long-term effects, Xitong Gongcheng Lilun Yu Shijian/System Engineering Theory and Practice, 39, 1, pp. 126-140, (2019); Ma J., Zhang D., Dong J., Tu Y., A supply chain network economic model with time-based competition, European Journal of Operational Research, 280, 3, pp. 889-908, (2020); Prasad S., Shankar R., Roy S., Impact of bargaining power on supply chain profit allocation: A game-theoretic study, Journal of Advances in Management Research, 16, 3, pp. 398-416, (2019); Wu Z., Liu G.-P., Hu J., An optimal control method to coordination of pricing and advertising for a supply chain: The consignment mode, IFAC-PapersOnLine, 53, 2, (2020); Zhang Z., An optimization model for logistics distribution network of cross-border e-commerce based on personalized recommendation algorithm, Security and Communication Networks, 2021, 4, pp. 1-11, (2021); Wang C., Analyzing the effects of cross-border e-commerce industry transfer using big data, Mobile Information Systems, 2021, 8, (2021); Yuan Q., The construction mechanism and algorithm of cross border e-commerce export logistics mode from the perspective of value chain, Journal of Intelligent and Fuzzy Systems, 37, 11, pp. 1-8, (2019); Xia L., Liu S., Intelligent iot-based cross-border e-commerce supply chain performance optimization, Wireless Communications and Mobile Computing, 2021, 121, pp. 1-13, (2021); Xiang D., Zhang Z., Cross-border e-commerce personalized recommendation based on fuzzy association specifications combined with complex preference model, Mathematical Problems in Engineering, 2020, 4, pp. 1-9, (2020); Garcia A., Pehanick K., Malley B., How shippers and 3pls can better manage the global cargo chain's first mile to last mile, Inbound Logistics, 39, 1, (2019)","J. Jiao; Department of Logistics Management, Hebei Jiaotong Vocational and Technical College, Shijiazhuang, Hebei, 050035, China; email: jiaojianhong@hejtxy.edu.cn",null,"Hindawi Limited",{"$nulls":5},1.9390114E7,null,null,null,"English","Secur. Commun. Networks","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85129977950"]
["Iannaccone G.; Marcucci E.; Gatta V.","Iannaccone, Gabriele (57222727120); Marcucci, Edoardo (6602255083); Gatta, Valerio (35109007100)","57222727120; 6602255083; 35109007100","What Young E-Consumers Want? Forecasting Parcel Lockers Choice in Rome",2021.0,"Logistics",5.0,3.0,57.0,null,null,null,26.0,"10.3390/logistics5030057","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121588369&doi=10.3390%2flogistics5030057&partnerID=40&md5=f1b564172091d5fb001662152ee283a6","Department of Political Science, Roma Tre University, Via Gabriello Chiabrera 199, Rome, 00145, Italy; Department of Logistics, Molde University College, P.O. Box 2110, Molde, 6402, Norway","Iannaccone G., Department of Political Science, Roma Tre University, Via Gabriello Chiabrera 199, Rome, 00145, Italy; Marcucci E., Department of Political Science, Roma Tre University, Via Gabriello Chiabrera 199, Rome, 00145, Italy, Department of Logistics, Molde University College, P.O. Box 2110, Molde, 6402, Norway; Gatta V., Department of Political Science, Roma Tre University, Via Gabriello Chiabrera 199, Rome, 00145, Italy","Surges in e-commerce sales represent a huge challenge for urban freight transport. Parcel lockers constitute a valid solution for addressing the challenges home deliveries imply. In fact, eliminating courier–consumer contact (also relevant for health-related issues, as made evident by the COVID-19 pandemic) and delivering in fewer predefined places might help coping mechanisms for missed deliveries substantially. Furthermore, this option enables consolidated shipping and reduced delivery trip costs. This paper analyses and compares consumer preferences for alternative collection strategies. It investigates home delivery vs. parcel locker use and forecasts their future market shares. This is performed based on both customer socio-economic variables and the attributes characterising these alternative logistic fulfilment strategies. The case study considered tests upon a stated preference survey deployed in the city of Rome. The investigation specifically targeted young people (i.e., population under 30 years) since they represent early adopters. Discrete choice models allow both quantifying the monetary value of parcel lockers attributes (i.e., willingness to pay measures) and estimating the potential demand for this innovative delivery scheme. Results show that distance and accessibility are the main choice determinants. Furthermore, there is an overall high propensity to adopt parcel lockers. This research can support policymakers when implementing such solutions. © 2021 by the authors.","channel choice; city logistics; collection points; consumer behavior; discrete choice modelling; e-commerce; home delivery; last mile delivery; parcel locker; stated preference; urban freight transport",{"$nulls":7},"Liscia R., Netcomm Focus LOGISTICA & PACKAGING per l’ e -Commerce Il Ruolo Della Logistica Nell’e -Commerce, (2020); Global 2020 Ecommerce Report. November 2020. No. 6–8; THE 2020 RETAILX EUROPE GROWTH 3000, (2020); Pernot D., Internet Shopping for Everyday Consumer Goods: An Examination of the Purchasing and Travel Practices of Click and Pickup Outlet Customers, Res. Transp. 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Econ, 64, pp. 13-25, (2017); Vieira J., Frade R., Ascenso R., Prates I., Martinho F., Generation Z and Key-Factors on E-Commerce: A Study on the Portuguese Tourism Sector, Adm. Sci, 10, (2020); Online Shopping Statistics You Need to Know in 2021; Cagliano A.C., Mangano G., Zenezini G., Technological Trends in Last-Mile Contexts: A European Perspective Technological Trends in Last-Mile Contexts, Proceedings of the 8th International Conference on Information Systems, Logistics and Supply Chain: Interconnected Supply Chains in an Era of Innovation, ILS 2020, pp. 356-364; Kelli L., Oliveira D., Morganti E., Dablanc L., Lucia R., Analysis of the Potential Demand of Automated Delivery Stations for E-Commerce Deliveries in Belo Horizonte, Brazil, Res. Transp. Econ, 65, pp. 34-43, (2017); Iwan S., Kijewska K., Lemke J., Analysis of Parcel Lockers’ Efficiency as the Last Mile Delivery Solution—The Results of the Research in Poland, Transp. Res. 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Part A Policy Pract, 82, pp. 169-192, (2015); Pacelli V., E-Commerce e Distribuzione Urbana Delle Merci: Parcel Locker Come Soluzione Ultimo Miglio, (2018); Beckers J., Verhetsel A., The Sustainability of the Urban Layer of E- Commerce Deliveries: The Belgian Collection and Delivery Point Networks, Eur. Plan. Stud, pp. 1-20, (2021); PUMS—Piano Urbano Della Mobilità Sostenibile. 2019, 2; Polinori P., Marcucci E., Bollino C.A., Bigerna S., Gatta V., Eco-Labeling and Sustainable Urban Freight Transport: How Much Are People Willing to Pay for Green Logistics?, Int. J. Transp. Econ, 45, pp. 631-658, (2018); Gatta V., Marcucci E., Nigro M., Serafini S., Sustainable Urban Freight Transport Adopting Public Transport-Based Crowdshipping for B2C Deliveries, Eur. Transp. Res. Rev, 11, (2019)","G. Iannaccone; Department of Political Science, Roma Tre University, Rome, Via Gabriello Chiabrera 199, 00145, Italy; email: gabriele.iannaccone@uniroma3.it",null,"MDPI",{"$nulls":5},2.305629E7,null,null,null,"English","Logist.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85121588369"]
["Figliozzi M.; Unnikrishnan A.","Figliozzi, Miguel (6507854711); Unnikrishnan, Avinash (24072608000)","6507854711; 24072608000","Exploring the impact of socio-demographic characteristics, health concerns, and product type on home delivery rates and expenditures during a strict COVID-19 lockdown period: A case study from Portland, OR",2021.0,"Transportation Research Part A: Policy and Practice",153.0,null,null,1.0,19.0,18.0,26.0,"10.1016/j.tra.2021.08.012","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85114827024&doi=10.1016%2fj.tra.2021.08.012&partnerID=40&md5=0a315611967f9984c3cd310067769413","Department of Civil and Environmental Engineering, Transportation Technology and People Lab, Portland State University, P.O. Box 751-CEE, Portland, 97207, OR, United States","Figliozzi M., Department of Civil and Environmental Engineering, Transportation Technology and People Lab, Portland State University, P.O. Box 751-CEE, Portland, 97207, OR, United States; Unnikrishnan A., Department of Civil and Environmental Engineering, Transportation Technology and People Lab, Portland State University, P.O. Box 751-CEE, Portland, 97207, OR, United States","E-commerce volumes and home deliveries have experienced steady growth in the last two decades. Strict COVID-19 lockdowns made home delivery an essential service and a lifeline for many households that, for travel restrictions or health concerns, were not able to utilize traditional shopping methods. This research studies the impact of socio-demographic variables and e-commerce attitudes on household deliveries for seven product categories (groceries, meals, electronics, household and office goods, recreational items, and fashion, beauty and personal care products, and medicine/health-related products) during the lockdown period in the greater Portland metropolitan region. To understand these impacts, exploratory factor analysis and choice models with latent variables are estimated utilizing data collected from an online survey representing the population in the greater Portland metropolitan region. The results indicate that each factor has a unique profile in terms of significant socio-demographic variables. A novel contribution of this research is to study the impact on home deliveries of non-traditional variables like health and safety concerns and the presence of household members with disabilities during a pandemic. The results show that health concerns are very influential and that there are substantial differences across factors on delivery rate and expenditure levels. Key findings and perspectives regarding future delivery rates and implications for transportation agencies and logistics companies are discussed. © 2021","COVID-19; Delivery rate; Expenditures; Health and safety concerns; Home deliveries; Product type","Oregon; Portland [Oregon]; United States; Factor analysis; Health; Population statistics; COVID-19; Delivery rate; Expenditure; Health and safety; Health concerns; Home delivery; Metropolitan regions; Product types; Safety concerns; Socio-demographic variables; COVID-19; demography; electronic commerce; expenditure; health risk; logistics; safety; Electronic commerce",{"$nulls":6},"(2020); Alemi F., Circella G., Mokhtarian P., Handy S., What drives the use of ridehailing in California? Ordered probit models of the usage frequency of Uber and Lyft, Transp. Res. Part C: Emerg. 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Med., 57, 6, pp. 749-756, (2019); Zhen F., Cao X., Mokhtarian P.L., Xi G., Associations between online purchasing and store purchasing for four types of products in Nanjing, China, Transp. Res. Rec., 2566, 1, pp. 93-101, (2016); Zhen F., Du X., Cao J., Mokhtarian P.L., The association between spatial attributes and e-shopping in the shopping process for search goods and experience goods: Evidence from Nanjing, J. Transp. Geogr., 66, pp. 291-299, (2018); Zhou Y., Wang X.C., Explore the relationship between online shopping and shopping trips: An analysis with the 2009 NHTS data, Transp. Res. Part A: Policy Pract., 70, pp. 1-9, (2014)","M. Figliozzi; Department of Civil and Environmental Engineering, Transportation Technology and People Lab, Portland State University, Portland, P.O. Box 751-CEE, 97207, United States; email: figliozzi@pdx.edu",null,"Elsevier Ltd",{"$nulls":5},9658564.0,null,null,null,"English","Transp. Res. Part A Policy Pract.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85114827024"]
["Lee K.H.; Kim B.","Lee, Kyoung Hee (57257377600); Kim, Boyoung (57199940011)","57257377600; 57199940011","Brand effects of omnichannel-based pickup service on consumption value and service satisfaction",2021.0,"Innovative Marketing",17.0,3.0,null,124.0,134.0,10.0,1.0,"10.21511/im.17(3).2021.10","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85114792392&doi=10.21511%2fim.17%283%29.2021.10&partnerID=40&md5=85863c7c799209ca80f2bff26bfedd13","Seoul Business School, aSSIST University, South Korea","Lee K.H., Seoul Business School, aSSIST University, South Korea; Kim B., Seoul Business School, aSSIST University, South Korea","As an online and offline integrated service of refund, replacement, and after-sales service, omnichannel is placing itself as a major service used in the online shopping market, as efficiency and an integrated operation system develop according to channel integration due to ICT development. Centered on young people who have recently put importance on in-store experience and direct experience, offline pickup service is reinforced beyond online delivery. This study aims to analyze the effects of a distribution company's brand factors on customer consumption value and satisfaction targeting the omnichannel-based pickup service. The research model was designed to find out whether brand image, identity, attachment, and trust factors affect consumption satisfaction factors through the intervention of emotional and functional consumption value factors. This study targeted 324 consumers using Korea's omnichannel-based pickup service and carried out a questionnaire survey. According to the analysis result, the brand image and brand identity had a positive (+) effect on the emotional value and functional value. Brand attachment and brand trust positively affected emotional value but the hypothesis on functional value was rejected. Hence, brand factors were confirmed to work on improving a consumer's emotional value effectively. © 2021 LLC CPC Business Perspectives. All rights reserved.","Consumption value; Customer satisfaction; Distribution channel; Service brand",{"$nulls":7},"Aaker D. A., Capitalizing on the value of a brand name, Managing Brand Equity, (1991); Digital Economy Index, (2020); Anderson E. W., Fornell C., Foundations of the American customer satisfaction index, Total Quality Management, 11, 7, pp. 869-882, (2000); Arslanagic-Kalajdzic M., Kadic-Maglajlic S., Miocevic D., The power of emotional value: Moderating customer orientation effect in professional business services relationships, Industrial Marketing Management, 88, 1, pp. 12-21, (2020); Bell D., Gallino S., Moreno A., Showrooms and information provision in omni-channel retail, Production and Operations Management, 24, 3, pp. 360-362, (2015); Bidmon S., How does attachment style influence the brand attachment - brand trust and brand loyalty chain in adolescents?, International Journal of Advertising, 36, 1, pp. 164-189, (2017); Bilgicer T., Jedidi K., Lehmann D. R., Neslin S. 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W., Dixon A., Omni-channel research framework in the context of personal selling and sales management: A review and research extensions, Journal of Research in Interactive Marketing, 10, 1, pp. 2-16, (2016); Fan M., Kohli R., Antecedents of B2C channel satisfaction and preference: Validating e-commerce metrics, Information Systems Research, 13, 3, pp. 316-333, (2002); Dolbec P. Y., Chebat J. C., The impact of a flagship vs. a brand store on brand attitude, brand attachment and brand equity, Journal of Retailing, 89, 4, pp. 460-466, (2013); Dorman A. J., Omnichannel retail and the new age consumer: An empirical analysis of direct to-consumer channel interaction in the retail industry, (2013); Faircloth J. B., Capella L. M., Alford B. L., The effect of brand attitude and brand image on brand equity, Journal of Marketing Theory and Practice, 9, 3, pp. 61-75, (2001); Fei L. I., Connation, cause and countermeasures of omni channel retailing: Further discussion on how to meet China multi channel retailing revolution storm, Journal of Beijing Technology and Business University, 2, 2, pp. 23-34, (2013); Frazer M., Stiehler B. E., Omnichannel retailing: The merging of the online and off-line environment, Global Conference on Business & Finance Proceedings, 9, 1, (2014); Fulgoni G. M., Omnichannel retail insights and the consumer's path-to-purchase: How digital has transformed the way people make purchasing decisions, Journal of Advertising Research, 54, 4, pp. 377-380, (2014); Gao F., Su X., Omnichannel retail operations with buy online and pick up in store, Management Science, 63, 8, pp. 2478-2492, (2016); Gensler S., Verhoef P. C., Bohm M., Understanding consumers' multichannel choices across the different stages of the buying process, Marketing Letters, 23, 4, pp. 987-1003, (2012); Ha H., Factors influencing consumer perceptions of brand trust online, Journal of Product & Brand Management, 13, 5, pp. 329-342, (2004); Holbrook M. B., Consumption experience, customer value, and subjective personal introspection: An illustrative photographic essay, Journal of Business Research, 59, 6, pp. 714-725, (2006); Japutra A., Ekinci Y., Simkin L., Exploring brand attachment, its determinants and outcomes, Journal of Strategic Marketing, 22, 7, pp. 616-630, (2014); Keller K. L., Strategic brand management: Building, measuring and managing brand equity, (2001); Keng J. C., Huang T. L., Zheng L. J., Modeling service encounters and customer experiential value in retailing, International Journal of Service Industry Management, 18, 4, pp. 349-367, (2007); Kotler P., Kartajaya H., Setiawan I., Marketing 4.0: Moving from traditional to digital, (2016); Lee S. Y., A study on omni channel case and strategy in domestic large-scale distributors, Journal of the Korean Society of Design Culture, 21, 4, pp. 477-488, (2015); Levenburg N. M., Delivering customer value online: An analysis of practices, applications, and performance, Journal of Retailing and Consumer Services, 12, 5, pp. 319-331, (2005); Lewis J., Whysall P., Foster C., Drivers and technology related obstacles in moving to multichannel retailing, International Journal of Electronic Commerce, 18, 4, pp. 43-68, (2014); Lim H., Dubinsky A. J., Consumers' perceptions of e-shopping characteristics: An expectancy-value approach, Journal of Services Marketing, 18, 7, pp. 500-513, (2004); Lim S. H., Kim S. H., A study on factors affecting use intention of omnichannel servicefocusing on self- efficacy and personal innovativeness, Journal of consumption culture, 21, 1, pp. 45-73, (2018); Madhavaram S., Badrinarayanan V., McDonald R. E., Integrated marketing communication and brand identity as critical components of brand equity strategy: A conceptual framework and research propositions, Journal of Advertising, 34, 4, pp. 69-80, (2005); Min D., The effect of psychological disposition on omni-channel shopping in the age of digital convergence: Focusing on extraversion-introversion and variety-seeking tendency, Journal of Digital Convergence, 14, 1, pp. 91-97, (2016); Napolitano M., Omnichannel distribution: Moving at the speed of now, Logistics Management, 52, 6, pp. 42-46, (2013); Pauwels K., Leeflang P. S., Teerling M. L., Huizingh K. 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Y., Effects of brand personality on brand trust and brand affect, Psychology and Marketing, 27, 7, pp. 639-661, (2010); Sung Y., Campbell W., Brand commitment in consumer-brand relationships: An investment model approach, Journal of Brand Management, 17, pp. 97-113, (2009); Um S. H., Yun J. Y., Kim J. W., Identifying the relationships among visitors u-tourism service experiences on site, satisfaction, and attitude change of the smart phone application, Journal of Tourism Sciences, 36, 9, pp. 295-313, (2012); Verhoef P. C., Kannan P. K., Inman J. J., From multichannel retailing to omni-channel retailing: Introduction to the special issue on multi-channel retailing, Journal of Retailing, 91, 2, pp. 174-181, (2015); Verhoef P. C., Neslin S. A., Vroomen B., Multichannel customer management: Understanding the research-shopper phenomenon, International Journal of Research in Marketing, 24, 2, pp. 129-148, (2007); Wang H. Y., Liao C., Yang L. H., What affects mobile application use? The roles of consumption values, International Journal of Marketing Studies, 5, 2, pp. 11-22, (2013); Wang R. J. H., Malthouse E. C., Krishnamurthi L., On the go: How mobile shopping affects customer purchase behavior, Journal of Retailing, 91, 2, pp. 217-234, (2015)",null,null,"LLC CPC Business Perspectives",{"$nulls":5},1.8142427E7,null,null,null,"English","Innov. Mark.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85114792392"]
["Wang H.-D.; Zheng C.-F.; Xiao X.","Wang, Hong-Dou (57477802200); Zheng, Chun-Fang (15844969400); Xiao, Xu (57477929100)","57477802200; 15844969400; 57477929100","An AMOS Model for Examining the Factors Influencing the Development of China Cross-Border E-Commerce Comprehensive Pilot Areas",2022.0,"Discrete Dynamics in Nature and Society",2022.0,null,1889589.0,null,null,null,6.0,"10.1155/2022/1889589","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85125761329&doi=10.1155%2f2022%2f1889589&partnerID=40&md5=c54565a2eb60a23336864e780d5e29bc","Business College of Beijing Union University, Beijing, China; Zhejiang Financial College, Hangzhou, China","Wang H.-D., Business College of Beijing Union University, Beijing, China; Zheng C.-F., Business College of Beijing Union University, Beijing, China; Xiao X., Zhejiang Financial College, Hangzhou, China","Cross-border e-commerce has greatly promoted the development of China's foreign trade, and the cross-border e-commerce comprehensive pilot area (CBECCPA, in brief) is the main form for promoting the development of cross-border e-commerce. The study aims to find out what factors and to what extent these factors affect the development of the CBECCPAs. Adopting the structural equation model analysis (AMOS) method and the data in 2017 of the 35 CBECCPAs set in the former three batches in China, the paper studies the effects of four main factors, including economic foundation, telecommunication network foundation, e-commerce logistics, and scientific and technological innovation, on the development of the CBECCPAs. The empirical results show that the economic foundation of the city where a CBECCPA locates has a vital impact, scientific and technological innovation has a quite important effect, e-commerce logistics has an important impact, and telecommunications network foundation has a slight influence on the development of CBECCPA. On the basis of empirically analysis results, it is suggested to strive to develop the cities' economy, increase investment in scientific and technological development, attach importance to scientific and technological innovation, and perfect the urban logistics system. Some suggestions are put forward, such as to make great efforts to develop the economy sustainably, to encourage to scientific and technological innovation, and to improve the logistics system. It is meaningful for the construction and development of the fourth and fifth batches of CBECCPAs.  © 2022 Hong-Dou Wang et al.",{"$nulls":8},"Zhang X., The coupling and coordinated development of cross-border e-commerce and economic system: An empirical study based on 35 comprehensive pilot zones of cross-border e-commerce, Journal of Business Economics, 38, 10, pp. 121-129, (2019); Liu J., Ren L., Chu X., Gong D., The effects of robots on the long-run economic growth, Tehnički Vjesnik-Technical Gazette, 27, 1, pp. 73-80, (2020); Li Y., Development, potential measurement and economic impact of regional logistics supply chain in China: A case study of cities in integrated pilot zones for cross-border e-commerce, Journal of Business Economics, 20, pp. 115-118, (2020); Burinskiene A., Pharma supply chain: Efficiency modelling Approach, Journal of System and Management Sciences, 8, 2, pp. 65-73, (2018); Wang R., Gu Q., Zhong B., What trade facilitation is needed for cross-border e-commerce? - Evidence from integrated pilot zones for cross-border e-commerce in 35 Cities in China, Zhejiang Journal, 4, pp. 100-110, (2020); Nie S., The impact of trade facilitation on the development of Cross-border e-commerce in China - Based on panel data analysis of 59 comprehensive cross-border e-commerce pilot zones, Foreign Trade and Economic Cooperation, 3, pp. 31-34, (2021); Zhang X., Chen Y., Research on the operational performance evaluation of integrated pilot zones for cross-border E-commerce, China Circulation Economy, 33, 9, pp. 73-82, (2019); Pei D., Performance evaluation and promotion strategy of Cross-border e-commerce operation in China - Based on the analysis of sample data in comprehensive pilot area of cross-border e-commerce, Journal of Business Economics, 6, pp. 145-148, (2020); Oyekunle R.A., E-business prospect and status in Nigerian universities, Journal of Logistics, Informatics and Service Science, 6, 2, pp. 43-75, (2019); Shim S.W., Jung L.S., The impacts of Experiential factors on Satisfaction and Behavioral Intention: An empirical study in the 6th industry, Journal of System and Management Sciences, 11, 1, pp. 54-68, (2021)","C.-F. Zheng; Business College of Beijing Union University, Beijing, China; email: chunfang.zheng@buu.edu.cn",null,"Hindawi Limited",{"$nulls":5},1.0260226E7,null,null,null,"English","Discrete Dyn. Nat. Soc.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85125761329"]
["Li N.; Yu Y.","Li, Ning (57608474600); Yu, Yanliang (57219715723)","57608474600; 57219715723","Design and Application of Improved Ant Colony Algorithm in E-Commerce System",2022.0,"Wireless Communications and Mobile Computing",2022.0,null,9467095.0,null,null,null,2.0,"10.1155/2022/9467095","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85128651489&doi=10.1155%2f2022%2f9467095&partnerID=40&md5=9d8bebf0686839cc0757756ad25b1b40","Economics School of Jilin University, Jilin, Changchun, 130000, China; Zhuhai College of Science and Technology, Guangdong, Zhuhai, 519041, China; School of Urban Economics and Public Administration, Capital University of Economics and Business, Beijing, 10070, China","Li N., Economics School of Jilin University, Jilin, Changchun, 130000, China, Zhuhai College of Science and Technology, Guangdong, Zhuhai, 519041, China; Yu Y., School of Urban Economics and Public Administration, Capital University of Economics and Business, Beijing, 10070, China","Since the 21st century, artificial intelligence and e-commerce have taken the lead. The two are close to life. Data show that, in the digital economy era, the two have developed rapidly and are widely used; however, they also have some problems. E-commerce logistics system has always been the first problem mentioned by relevant personnel and users. The continuous increase in transaction volume is worth celebrating, but the logistics efficiency continues to be flat or even declining, which has become a serious problem. This shows that, for the e-commerce platform, the investment in science and technology is not comprehensive and in depth, and the artificial intelligence technology has not been deeply applied for the logistics industry. Understanding needs, finding problems, and solving them in time are the way to develop this industry. Pareto is chosen by most logistics systems, but in fact, its efficiency is not as high as imagined. In view of this, this paper proposes an innovative algorithm, based on ant colony algorithm, with optimization mechanism to strengthen the shortcomings, thus improving the premature problem of ant colony algorithm, and at the same time, a series of performances such as convergence speed, accuracy, and stability have been strengthened because of this improvement. Experiments show that the optimization ability of this algorithm is better than the other two. © 2022 Ning Li and Yanliang Yu.",null,"Ant colony optimization; Artificial intelligence; Efficiency; Ant colonies algorithm; Commerce platforms; Design and application; Digital economy; E- commerces; E-commerce systems; Improved ant colony algorithm; Logistics efficiency; Logistics system; Science and Technology; Electronic commerce",{"$nulls":4},"Beijing Social Science Fund, (19ZDA03)","This work was sponsored in part by the Major Project of Beijing Social Science Foundation Research on building ecological civilization system (19ZDA03)","Bench-Capon T., Dunne P.E., Argumentation in artificial intelligence, Artificial Intelligence, 171, 10-15, pp. 619-641, (2007); Weidong J., Legal arguments in the age of artificial intelligence [J], Legal research, 41, 6, pp. 32-49, (2019); Pettorossi A., Proietti M., Transformation of logic programs, Handbook of Logic in Artificial Intelligence and Logic Programming, 5, pp. 697-787, (1998); Li D., Liu C., Yi D., Xu H., Artificial intelligence with uncertainty [J], Journal of Software, 15, 11, (2004); Kalogirou S.A., Artificial intelligence for the modeling and control of combustion processes: a review, Progress in Energy and Combustion Science, 29, 6, pp. 515-566, (2003); Vercauteren T., Unberath M., Padoy N., Navab N., CAI4CAI: the rise of contextual artificial intelligence in computer-assisted interventions, Proceedings of the IEEE, 108, 1, pp. 198-214, (2020); Chen G., Li S., Research on location fusion of spatial geological disaster based on fuzzy SVM, Computer Communications, 153, pp. 538-544, (2020); Hongjun G., Aiwu Z., The research on security technology of logistics system under e-commerce environment [C], Proceedings of the 6th International Conference on Material Handling ICMH, 2008, pp. 229-233, (2008); Chen G., Li S., Network on chip for enterprise information management and integration in intelligent physical systems, Enterprise Information Systems, 15, 7, pp. 935-950, (2021); Chen X., Hua L., Research on e-commerce logistics system informationization in chain [J], Procedia-Social and Behavioral Sciences, 96, 1, pp. 838-843, (2013); Liu B., Hua H., Li J., Research on commodity collaborative logistics service system under e-commerce environment, 4, 4, pp. 61-71, (2014); Wang Y., Sun L., Subramani S., CAB: classifying arrhythmias based on imbalanced sensor data, KSII Transactions on Internet and Information Systems, 15, 7, pp. 2304-2320, (2021); Yang J.P., Yang C.C., Yao X.X., Research on the \"last-mile\"issue in the e-commerce logistics system [J], Journal of Business Economics, 4, pp. 16-22, (2014); Li G., Chen Z., Study on the construction of agricultural products e-commerce logistics system in Jiangxi province [C], Proceedings of 2017 9th International Economics, Management and Education Technology Conference (IEMETC 2017), pp. 315-318, (2017); Wang H.W., Yan Y.S., Duan H.W., Measuring the performance of e-commerce logistics system based on fuzzy-AHP, Applied Mechanics and Materials, 505-506, pp. 898-901, (2014)","Y. Yu; School of Urban Economics and Public Administration, Capital University of Economics and Business, Beijing, 10070, China; email: yyl3039@email.poe.edu.pl",null,"Hindawi Limited",{"$nulls":5},1.5308669E7,null,null,null,"English","Wireless Commun. Mobile Comput.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85128651489"]
["Tilk C.; Olkis K.; Irnich S.","Tilk, Christian (44462320100); Olkis, Katharina (57224924414); Irnich, Stefan (22985527700)","44462320100; 57224924414; 22985527700","The last-mile vehicle routing problem with delivery options",2021.0,"OR Spectrum",43.0,4.0,null,877.0,904.0,27.0,29.0,"10.1007/s00291-021-00633-0","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85108620967&doi=10.1007%2fs00291-021-00633-0&partnerID=40&md5=241923aa056a79b27275e3375c5dbf66","Chair of Logistics Management, Gutenberg School of Management and Economics, Johannes Gutenberg University Mainz, Jakob-Welder-Weg 9, Mainz, D-55128, Germany","Tilk C., Chair of Logistics Management, Gutenberg School of Management and Economics, Johannes Gutenberg University Mainz, Jakob-Welder-Weg 9, Mainz, D-55128, Germany; Olkis K., Chair of Logistics Management, Gutenberg School of Management and Economics, Johannes Gutenberg University Mainz, Jakob-Welder-Weg 9, Mainz, D-55128, Germany; Irnich S., Chair of Logistics Management, Gutenberg School of Management and Economics, Johannes Gutenberg University Mainz, Jakob-Welder-Weg 9, Mainz, D-55128, Germany","The ongoing rise in e-commerce comes along with an increasing number of first-time delivery failures due to the absence of the customer at the delivery location. Failed deliveries result in rework which in turn has a large impact on the carriers’ delivery cost. In the classical vehicle routing problem (VRP) with time windows, each customer request has only one location and one time window describing where and when shipments need to be delivered. In contrast, we introduce and analyze the vehicle routing problem with delivery options (VRPDO), in which some requests can be shipped to alternative locations with possibly different time windows. Furthermore, customers may prefer some delivery options. The carrier must then select, for each request, one delivery option such that the carriers’ overall cost is minimized and a given service level regarding customer preferences is achieved. Moreover, when delivery options share a common location, e.g., a locker, capacities must be respected when assigning shipments. To solve the VRPDO exactly, we present a new branch-price-and-cut algorithm. The associated pricing subproblem is a shortest-path problem with resource constraints that we solve with a bidirectional labeling algorithm on an auxiliary network. We focus on the comparison of two alternative modeling approaches for the auxiliary network and present optimal solutions for instances with up to 100 delivery options. Moreover, we provide 17 new optimal solutions for the benchmark set for the VRP with roaming delivery locations. © 2021, The Author(s).","Branch-price-and-cut; City logistics; Routing; Service level; Vehicle routing",{"$nulls":5},"Deutsche Forschungsgemeinschaft, DFG, (IR 122/8-1)","We thank the anonymous reviewers for their helpful comments and, in particular, for pointing us to some recent and relevant literature. This research was supported by the Deutsche Forschungsgemeinschaft (DFG) under grant IR 122/8-1. This support is gratefully acknowledged. ","Achterberg T., Constraint Integer Programming. 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IEEE, (2016); Zhou L., Baldacci R., Vigo D., Wang X., A multi-depot two-echelon vehicle routing problem with delivery options arising in the last mile distribution, Eur J Op Res, 265, 2, pp. 765-778, (2018)","C. Tilk; Chair of Logistics Management, Gutenberg School of Management and Economics, Johannes Gutenberg University Mainz, Mainz, Jakob-Welder-Weg 9, D-55128, Germany; email: tilk@uni-mainz.de",null,"Springer Science and Business Media Deutschland GmbH",{"$nulls":5},1716468.0,null,null,null,"English","OR Spectrum","Article","Final","All Open Access; Green Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85108620967"]
["Amiri A.M.; Ferguson M.R.; Razavi S.","Amiri, Amir Mohammadian (57205513538); Ferguson, Mark R. (7402593242); Razavi, Saiedeh (36070789400)","57205513538; 7402593242; 36070789400","Adoption patterns of autonomous technologies in Logistics: evidence for Niagara Region",2022.0,"Transportation Letters",14.0,7.0,null,685.0,696.0,11.0,11.0,"10.1080/19427867.2021.1923305","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85105229360&doi=10.1080%2f19427867.2021.1923305&partnerID=40&md5=601c1ca852c95b97971c3cefc2836397","McMaster Institute for Transportation and Logistics, McMaster University, Hamilton, ON, Canada; McMaster Institute for Transportation and Logistics, McMaster University, Hamilton, ON, Canada; Civil Engineering Department McMaster Institute for Transportation and Logistics, McMaster University, Hamilton, ON, Canada","Amiri A.M., McMaster Institute for Transportation and Logistics, McMaster University, Hamilton, ON, Canada; Ferguson M.R., McMaster Institute for Transportation and Logistics, McMaster University, Hamilton, ON, Canada; Razavi S., Civil Engineering Department McMaster Institute for Transportation and Logistics, McMaster University, Hamilton, ON, Canada","Despite the well-known benefits that autonomous technologies bring to supply chain and logistics, the adoption of such technologies remains a challenging task. This study seeks to investigate how firms that are associated with the generation of freight movements in Niagara Region (Canada) will respond to new autonomous technologies. Structural Equation Modeling was used to extract meaningful features from the dataset obtained from an extensive and in-depth survey. The survey was designed to help better understand firms’ views regarding autonomous technologies. The results showed that firms with a higher percentage of e-commerce sales are more likely to adopt autonomous technologies. Results also showed that third-party logistics providers are likely to play an important role in facilitating a path to adoption. The number of product lines, the number of transportation assets, and the number of import countries are other important contributing factors that can affect firms’ levels of interest in autonomous technologies. © 2021 Informa UK Limited, trading as Taylor & Francis Group.","Autonomous technologies; Logistics operations; SMEs; technology adoption","Supply chains; Adoption patterns; Autonomous technology; Contributing factor; Freight movement; Logistics providers; Product-lines; Structural equation modeling; Third parties; Surveys",{"$nulls":4},"Autonomous Vehicle Innovation Network of Ontario; Niagara Region Economic Development; Transport Canada","The researchers would like to acknowledge the support received from the Autonomous Vehicle Innovation Network of Ontario (AVIN), Transport Canada, and the Niagara Region Economic Development for conducting this study. ","Cooper R.B., Zmud R.W., Information Technology Implementation Research: A Technological Diffusion Approach, Management Science, 36, 2, pp. 123-139, (1990); Curran J.M., Meuter M.L., Self‐service Technology Adoption: Comparing Three Technologies, Journal of Services Marketing, 19, 2, pp. 103-113, (2005); Ferguson M., Exploring Goods Movement and Export Diversification for Niagara Region Firms, McMaster Institute for Transportation and Logistics Website, (2020); Frambach R.T., Schillewaert N., Organizational Innovation Adoption: A Multi-level Framework of Determinants and Opportunities for Future Research, Journal of Business Research, 55, 2, pp. 163-176, (2002); Golob T.F., Structural Equation Modeling for Travel Behavior Research. 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I, 37, 5, pp. 972-987, (2009); Tobbin P., Kuwornu J.K., Adoption of Mobile Money Transfer Technology: Structural Equation Modeling Approach, European Journal of Business and Management, 3, 7, pp. 59-77, (2011); Tornatzky L.G., Klein K.J., Innovation Characteristics and Innovation Adoption-implementation: A Meta-analysis of Findings, IEEE Transactions on Engineering Management, EM-29, 1, pp. 28-45, (1982); Washington S., Karlaftis M.G., Mannering F., Anastasopoulos P., Statistical and Econometric Methods for Transportation Data Analysis, (2020); Xue Q.L., Introduction to Path Analysis, Statistics for Psychosocial Research II: Structural Models, (2006); Yoon C., Lim D., Park C., Factors Affecting Adoption of Smart Farms: The Case of Korea, Computers in Human Behavior, 108, (2020); Zhu K., Kraemer K.L., Post-adoption Variations in Usage and Value of E-business by Organizations: Cross-country Evidence from the Retail Industry, Information Systems Research, 16, 1, pp. 61-84, (2005)","A.M. Amiri; McMaster University, Hamilton, 1280 Main St. West, General Science Building Rm 206, L8S 4K1, Canada; email: amiria7@mcmaster.ca",null,"Taylor and Francis Ltd.",{"$nulls":5},1.9427867E7,null,null,null,"English","Transp. Lett.","Article","Final",null,"Scopus","2-s2.0-85105229360"]
["Yu B.; Yu H.; Yu Y.","Yu, Bilin (57217089238); Yu, Hu (57205610040); Yu, Yugang (14822788000)","57217089238; 57205610040; 14822788000","Within-aisle or across-aisle? Optimisation and comparison of two class-based storage policies in multi-dock unit-load warehouses",2022.0,"International Journal of Production Research",60.0,8.0,null,2572.0,2597.0,25.0,6.0,"10.1080/00207543.2021.1898060","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85102811403&doi=10.1080%2f00207543.2021.1898060&partnerID=40&md5=cc9ad9f624b6846c99944e1ff99af7fe","Anhui Province Key Laboratory of Contemporary Logistics and Supply Chain, School of Management, University of Science and Technology of China, Hefei, China","Yu B., Anhui Province Key Laboratory of Contemporary Logistics and Supply Chain, School of Management, University of Science and Technology of China, Hefei, China; Yu H., Anhui Province Key Laboratory of Contemporary Logistics and Supply Chain, School of Management, University of Science and Technology of China, Hefei, China; Yu Y., Anhui Province Key Laboratory of Contemporary Logistics and Supply Chain, School of Management, University of Science and Technology of China, Hefei, China","As E-Commerce develop, customers' tight delivery requirements are driving warehouses to operate more efficiently. This paper studies two types of class-based storage policies for a multi-dock unit-load warehouse: the within-aisle policy and the across-aisle policy. The aim is to determine the optimal class boundary and explore the dominance situation (i.e. which policy performs better in which situation). We first develop an expected response distance model for each policy based on a general layout of multiple docks. Then, closed-form optimal first zone boundary and warehouse dimension are given for the across-aisle policy. For within-aisle policy, an efficient algorithm is developed (based on the proved unimodality property) for obtaining its optimal first zone boundary. Besides, each policy's dominance situation is analysed for two typical situations. Numerical results show that both policies can bring up to 60% performance improvement compared with the random storage policy. Impacts of docks layout and warehouse dimensions on each policy's dominance situations are illustrated. It shows that the across-aisle policy performs better in the situation where the docks' and wall's centrelines are adjacent, and in the situation where the warehouse is narrow and deep. Managerial insights on policy selection and dock layout design are presented for warehouse managers. © 2021 Informa UK Limited, trading as Taylor & Francis Group.","class-based storage; Logistics; multi-docks; unit-load warehouse; within-aisle and across-aisle","Docks; Hydraulic structures; Managers; Class based storage; Class boundary; Layout designs; Numerical results; Optimisations; Policy selection; Random storage; Zone boundaries; Warehouses",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (71991464, 72001200); National Key Research and Development Program of China, NKRDPC, (2018YFB1601401)","This work was supported by the National Key R&D Program of China [grant no. 2018YFB1601401] and the National Natural Science Foundation of China [grant no's 71991464 and 72001200].","Aldarondo F.J., Bozer Y.A., Expected Distances and Alternative Design Configurations for Automated Guided Vehicle-based Order Picking Systems, International Journal of Production Research, pp. 1-18, (2020); 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Proceedings, (2015); Tutam M., White J.A., A Multi-dock, Unit-Load Warehouse Design, IISE Transactions, 51, 3, pp. 232-247, (2019); Tutam M., White J.A., Multi-dock Unit-Load Warehouse Designs with a Cross-aisle, Transportation Research Part E: Logistics and Transportation Review, 129, 1, pp. 247-262, (2019); Yang P., Yang K., Qi M., Miao L., Ye B., Designing the Optimal Multi-deep AS/RS Storage Rack Under Full Turnover-Based Storage Policy Based on Non-Approximate Speed Model of S/R Machine, Transportation Research Part E: Logistics and Transportation Review, 104, pp. 113-130, (2017); Yu Y., de Koster R.B.M., Guo X., Class-Based Storage with a Finite Number of Items: Using More Classes is Not Always Better, Production and Operations Management, 24, 8, pp. 1235-1247, (2015); Yu Y., Koster R.D., Optimal Zone Boundaries for Two-Class-Based Compact Three-dimensional Automated Storage and Retrieval Systems, IIE Transactions, 41, 3, pp. 194-208, (2009); Zaerpour N., Yu Y., de Koster R.B.M., Response Time Analysis of a Live-cube Compact Storage System with Two Storage Classes, IISE Transactions, 49, 5, pp. 461-480, (2017)","H. Yu; Anhui Province Key Laboratory of Contemporary Logistics and Supply Chain, School of Management, University of Science and Technology of China, Hefei, China; email: yuhu0421@ustc.edu.cn",null,"Taylor and Francis Ltd.",{"$nulls":5},207543.0,null,"IJPRB",null,"English","Int J Prod Res","Article","Final",null,"Scopus","2-s2.0-85102811403"]
["Özarık S.S.; Veelenturf L.P.; Woensel T.V.; Laporte G.","Özarık, Sami Serkan (57213819474); Veelenturf, Lucas P. (36667703700); Woensel, Tom Van (12781314700); Laporte, Gilbert (7101734278)","57213819474; 36667703700; 12781314700; 7101734278","Optimizing e-commerce last-mile vehicle routing and scheduling under uncertain customer presence",2021.0,"Transportation Research Part E: Logistics and Transportation Review",148.0,null,102263.0,null,null,null,25.0,"10.1016/j.tre.2021.102263","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85101814226&doi=10.1016%2fj.tre.2021.102263&partnerID=40&md5=1295e030563ad9a5404909603402ee82","School of Industrial Engineering and Innovation Sciences, Eindhoven University of Technology, P.O. Box 513, MB Eindhoven, 5600, Netherlands; Rotterdam School Management, Erasmus University Rotterdam, Burgemeester Oudlaan 50, PA Rotterdam, 3062, Netherlands; Department of Decision Sciences, HEC Montréal, Montréal, H3T 2A7, Canada; School of Management, University of Bath, Bath, B2A 2AY, United Kingdom","Özarık S.S., School of Industrial Engineering and Innovation Sciences, Eindhoven University of Technology, P.O. Box 513, MB Eindhoven, 5600, Netherlands; Veelenturf L.P., Rotterdam School Management, Erasmus University Rotterdam, Burgemeester Oudlaan 50, PA Rotterdam, 3062, Netherlands; Woensel T.V., School of Industrial Engineering and Innovation Sciences, Eindhoven University of Technology, P.O. Box 513, MB Eindhoven, 5600, Netherlands; Laporte G., Department of Decision Sciences, HEC Montréal, Montréal, H3T 2A7, Canada, School of Management, University of Bath, Bath, B2A 2AY, United Kingdom","The recent increase in online orders in e-commerce leads to logistical challenges such as low hit rates (proportion of successful deliveries). We consider last-mile vehicle routing and scheduling problems in which customer presence probability data are taken into account. The aim is to reduce the expected cost resulting from low hit rates by considering both routing and scheduling decisions simultaneously in the planning phase. We model the problem and solve it by the means of an adaptive large neighborhood search metaheuristic which iterates between the routing and scheduling components of the problem. Computational experiments indicate that using customer-related presence data significantly can yield savings as large as 40% in system-wide costs compared with those of traditional vehicle routing solutions. © 2021 The Author(s)","Adaptive large neighborhood search; Customer availability profiles; E-commerce; Last-mile delivery; Vehicle routing","Electronic commerce; Optimization; Sales; Vehicles; Adaptive large neighborhood searches; Customer availability profile; E- commerces; Hit rate; Last mile; Last-mile delivery; Online orders; Routing and scheduling; Vehicle routing and scheduling; Vehicle Routing Problems; electronic commerce; optimization; routing; transport vehicle; Vehicle routing",{"$nulls":4},"Natural Sciences and Engineering Research Council of Canada, NSERC, (2015-06189); Nederlandse Organisatie voor Wetenschappelijk Onderzoek, NWO, (628.009.013)","This research was partly funded by the Canadian Natural Sciences and Engineering Research Council under grant 2015-06189 . This research was also funded by The Dutch Research Council (NWO) Data2Move project under grant 628.009.013 . These supports are greatly acknowledged. ","Abell M.L., Braselton J.P., Chapter 8 - Introduction to the Laplace transform, Introductory Differential Equations, pp. 399-460, (2014); Barenji A.V., Wang W., Li Z., Guerra-Zubiaga D.A., Intelligent e-commerce logistics platform using hybrid agent based approach, Transport. Res. Part E: Logist. Transport. Rev., 126, pp. 15-31, (2019); Campbell A.M., Savelsbergh M.W.P., Incentive schemes for attended home delivery services, Transport. Sci., 40, pp. 327-341, (2006); Dabia S., Ropke S., Van Woensel T., De Kok T., Branch and price for the time-dependent vehicle routing problem with time windows, Transport. Sci., 47, pp. 380-396, (2013); Florio A.M., Feillet D., Hartl R.F., The delivery problem: Optimizing hit rates in e-commerce deliveries, Transport. Res. Part B: Methodol., 117, pp. 455-472, (2018); Francois V., Arda Y., Crama Y., Adaptive large neighborhood search for multitrip vehicle routing with time windows, Transport. Sci., 53, pp. 1706-1730, (2019); Gevaers R., pp. 56-71, (2011); He L., 29, pp. 186-194, (2019); Hoogeboom M., Dullaert W., Lai D., Vigo D., Efficient neighborhood evaluations for the vehicle routing problem with multiple time windows, Transport. Sci., 54, pp. 400-416, (2020); Lowe R., Rigby M., (2014); (2018); Mitrovic-Minic S., Laporte G., The pickup and delivery problem with time windows and transshipment, INFOR: Informat. Syst. Oper. Res., 44, pp. 217-227, (2006); Morganti E., Seidel S., Blanquart C., Dablanc L., Lenz B., The impact of e-commerce on final deliveries: alternative parcel delivery services in France and Germany, Transport. Res. Proc., 4, pp. 178-190, (2014); Ozbaygin G., Karasan O.E., Savelsbergh M.W.P., Yaman H., A branch-and-price algorithm for the vehicle routing problem with roaming delivery locations, Transport. Res. Part B: Methodol., 100, pp. 115-137, (2017); Pan S., Giannikas V., Han Y., Grover-Silva E., Qiao B., Using customer-related data to enhance e-grocery home delivery, Ind. Manage. Data Syst., 117, pp. 1917-1933, (2017); Ponce D., Contreras I., Laporte G., E-commerce shipping through a third-party supply chain, Transport. Res. Part E: Logist. Transport. Rev., 140, (2020); Potvin J.-Y., Rousseau J.-M., A parallel route building algorithm for the vehicle routing and scheduling problem with time windows, Eur. J. Oper. Res., 66, pp. 331-340, (1993); Punakivi M., Tanskanen K., Increasing the cost efficiency of e-fulfilment using shared reception boxes, Int. J. Retail Distrib. Manage., 30, pp. 498-507, (2002); Ropke S., Pisinger D., An adaptive large neighborhood search heuristic for the pickup and delivery problem with time windows, Transport. Sci., 40, pp. 455-472, (2006); Savelsbergh M.W.P., Van Woensel T., 50th anniversary invited article–city logistics: Challenges and opportunities, Transport. Sci., 50, pp. 579-590, (2016); Solomon M.M., Algorithms for the vehicle routing and scheduling problems with time window constraints, Oper. Res., 35, pp. 254-265, (1987); Tang C.S., Veelenturf L.P., The strategic role of logistics in the industry 4.0 era, Transport. Res. Part E: Logist. Transport. Rev., 129, pp. 1-11, (2019); Toth P., Vigo D.; Van Duin J., De Goffau W., Wiegmans B., Tavasszy L., Saes M., Improving home delivery efficiency by using principles of address intelligence for B2C deliveries, Transport. Res. Proc., 12, pp. 14-25, (2016); Vanelslander T., Deketele L., Van Hove D., Commonly used e-commerce supply chains for fast moving consumer goods: comparison and suggestions for improvement, Int. J. Logist. Res. Appl., 16, pp. 243-256, (2013); Visser T.R., Spliet R., Efficient move evaluations for time-dependent vehicle routing problems, Transport. Sci., 54, pp. 1091-1112, (2020); Yrjola H., Physical distribution considerations for electronic grocery shopping, Int. J. Phys. Distrib. Logist. Manage., 31, pp. 746-761, (2001)","S.S. Özarık; School of Industrial Engineering and Innovation Sciences, Eindhoven University of Technology, MB Eindhoven, P.O. Box 513, 5600, Netherlands; email: s.s.ozarik@tue.nl",null,"Elsevier Ltd",{"$nulls":5},1.3665545E7,null,null,null,"English","Transp. Res. Part E Logist. Transp. Rev.","Article","Final","All Open Access; Green Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85101814226"]
["Zhou Y.; Huang J.; Shi J.; Wang R.; Huang K.","Zhou, Yuzhen (57210931585); Huang, Jincai (9337816300); Shi, Jianmai (36139107000); Wang, Rui (56510490800); Huang, Kuihua (35775536600)","57210931585; 9337816300; 36139107000; 56510490800; 35775536600","The electric vehicle routing problem with partial recharge and vehicle recycling",2021.0,"Complex and Intelligent Systems",7.0,3.0,null,1445.0,1458.0,13.0,31.0,"10.1007/s40747-021-00291-3","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85128731831&doi=10.1007%2fs40747-021-00291-3&partnerID=40&md5=e1595381f2188156afdba22840009458","College of System Engineering, National University of Defense Technology, Changsha, 410073, China","Zhou Y., College of System Engineering, National University of Defense Technology, Changsha, 410073, China; Huang J., College of System Engineering, National University of Defense Technology, Changsha, 410073, China; Shi J., College of System Engineering, National University of Defense Technology, Changsha, 410073, China; Wang R., College of System Engineering, National University of Defense Technology, Changsha, 410073, China; Huang K., College of System Engineering, National University of Defense Technology, Changsha, 410073, China","In this paper, a new variant of the electric vehicle (EV) routing problem, which considers heterogeneous EVs, partial recharge, and vehicle recycling, is investigated based on logistic companies' practical operation. A mixed integer linear programming (MILP) model is proposed to formulate the problem. For small-scale scenarios, commercial solver, e.g., CPLEX, is leveraged. For large-scale instances faced by practical applications, a hybrid metaheuristic is designed through integrating a modified Greedy Algorithm with the Variable Neighborhood Search (VNS). The proposed algorithm was tested by real-world instances from JD, an e-commerce enterprise in China. Computational results indicate that partial recharge and vehicle recycling can save costs effectively. It also shows that the number of charging stations is an important factor for the application of EVs. © 2021, The Author(s).","Electric vehicle; Heterogeneous vehicles; Partial recharge; Routing problem; Vehicle recycling",{"$nulls":5},"Natural Science Fund of Distinguished Young Scholars in Hunan, (2018JJ1035); National Natural Science Foundation of China, NSFC, (71771215)","The research is supported by the National Natural Science Foundation of China (Grant no. 71771215) and the Natural Science Fund of Distinguished Young Scholars in Hunan (Grant no. 2018JJ1035). ","A European Strategy for Low-Emission Mobility. Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions, (2016); Ou S., Lin Z., Wu Z., Zheng J., Lyu R., Przesmitzki S., He X., A study of China’s explosive growth in the plug-in electric vehicle market, pp. 37831-46283, (2017); Nesterova N., Quak H., Balm S., Roche-Cerasi I., Tretvik T., State of the art of the electric freight vehicles implementation in city logistics, (2013); Erdelic T., Caric T., A survey on the electric vehicle routing problem: variants and solution approaches, J Adv Transp, 2019, pp. 1-48, (2019); Conrad R.G., Figliozzi M.A., The recharging vehicle routing problem, Proceedings of the 2011 Industrial Engineering Research Conference, (2011); Erdogan S., Miller-Hooks E., A green vehicle routing problem, Transp Res Part E Logist Transp Rev, 48, 1, pp. 100-114, (2012); Koc C., Karaoglan I., The green vehicle routing problem: a heuristic based exact solution approach, Appl Soft Comput, 39, pp. 154-164, (2016); Bahrami S., Nourinejad M., Amirjamshidi G., Roorda M.J., The Plugin Hybrid Electric Vehicle routing problem: a power-management strategy model, Transp Res Part C Emerg Technol, 111, pp. 318-333, (2020); Montoya A., Gueret C., Mendoza J.E., Villegas J.G., A multi-space sampling heuristic for the green vehicle routing problem, Transp Res Part C Emerg Technol, 70, pp. 113-128, (2016); Andelmin J., Bartolini E., An exact algorithm for the green vehicle routing problem, Transp Sci, 51, 4, pp. 1288-1303, (2017); Schneider M., Stenger A., Goeke D., The electric vehicle-routing problem with time windows and recharging stations, Transp Sci, 48, 4, pp. 500-520, (2014); Keskin M., Catay B., Partial recharge strategies for the electric vehicle routing problem with time windows, Transp Res Part C Emerg Technol, 65, pp. 111-127, (2016); Felipe A., Ortuno M.T., Righini G., Tirado G., A heuristic approach for the green vehicle routing problem with multiple technologies and partial recharges, Transp Res Part E Logist Transp Rev, 71, pp. 111-128, (2014); Ding N., Batta R., Kwon C., Conflict-Free Electric Vehicle Routing Problem with Capacitated Charging Stations and Partial Recharge, (2015); Keskin M., Catay B., A matheuristic method for the electric vehicle routing problem with time windows and fast chargers, Comput Oper Res, 100, pp. 172-188, (2018); Desaulniers G., Errico F., Irnich S., Schneider M., Exact algorithms for electric vehicle-routing problems with time windows, Oper Res, 64, 6, pp. 1388-1405, (2016); Schiffer M., Walther G., The electric location routing problem with time windows and partial recharging, Eur J Oper Res, 260, 3, pp. 995-1013, (2017); Mao H., Shi J., Zhou Y., Zhang G., The electric vehicle routing problem with time windows and multiple recharging options, IEEE Access, 8, pp. 114864-114875, (2020); Goeke D., Schneider M., Routing a mixed fleet of electric and conventional vehicles, Eur J Oper Res, 245, 1, pp. 81-99, (2015); Hiermann G., Puchinger J., Ropke S., Hartl R.F., The electric fleet size and mix vehicle routing problem with time windows and recharging stations, Eur J Oper Res, 252, 3, pp. 995-1018, (2016); Hiermann G., Hartl R.F., Puchinger J., Vidal T., Routing a mix of conventional, plug-in hybrid, and electric vehicles, Eur J Oper Res, 272, 1, pp. 235-248, (2019); Lebeau P., De Cauwer C., Van Mierlo J., Macharis C., Verbeke W., Coosemans T., Conventional, hybrid, or electric vehicles: which technology for an urban distribution centre?, Sci World J, 2015, pp. 1-11, (2015); Kopfer H., Vornhusen B., Energy vehicle routing problem for differently sized and powered vehicles, J Bus Econ, 89, pp. 1-29, (2017); Sassi O., Cherif W.R., Oulamara A., Vehicle Routing Problem with Mixed Fleet of Conventional and Heterogenous Electric Vehicles and Time-Dependent Charging Costs, (2014); Macrina G., Pugliese L.D.P., Guerriero F., Laporte G., The green mixed fleet vehicle routing problem with partial battery recharging and time windows, Comput Oper Res, 101, pp. 183-199, (2019); Montoya A., Gueret C., Mendoza J.E., Villegas J.G., The electric vehicle routing problem with nonlinear charging function, Transp Res Part B Methodol, 103, pp. 87-110, (2017); Koc C., Jabali O., Mendoza J.E., Laporte G., The electric vehicle routing problem with shared charging stations, Int Trans Oper Res, 26, 4, pp. 1211-1243, (2019); Froger A., Mendoza J.E., Ola J., Laporte G., New Formulations for the Electric Vehicle Routing Problem with Nonlinear Charging Functions, (2017)","J. Shi; College of System Engineering, National University of Defense Technology, Changsha, 410073, China; email: jianmaishi@gamil.com",null,"Springer International Publishing",{"$nulls":5},2.1994536E7,null,null,null,"English","Complex Intell. Syst.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85128731831"]
["Nahiduzzaman K.M.; Holland M.; Sikder S.K.; Shaw P.; Hewage K.; Sadiq R.","Nahiduzzaman, Kh Md (56129207800); Holland, Mark (57196043882); Sikder, Sujit K. (56781202400); Shaw, Pamela (35086955200); Hewage, Kasun (8384286700); Sadiq, Rehan (7003604679)","56129207800; 57196043882; 56781202400; 35086955200; 8384286700; 7003604679","Urban Transformation Toward a Smart City: An E-Commerce-Induced Path-Dependent Analysis",2021.0,"Journal of Urban Planning and Development",147.0,1.0,4020060.0,null,null,null,16.0,"10.1061/(ASCE)UP.1943-5444.0000648","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85097895563&doi=10.1061%2f%28ASCE%29UP.1943-5444.0000648&partnerID=40&md5=891ae3b66a9356107ca7f6280e2014c9","School of Engineering, Univ. of British Columbia (UBC) Okanagan, 1137 Alumni Ave, Kelowna, V1V1V7, BC, Canada; Community Planning, Vancouver Island Univ., 900 Fifth St., Nanaimo, V9R5S5, BC, Canada; Monitoring of Settlement and Open Space Development, Leibniz Institute of Ecological Urban and Regional Development, Weberplatz 1, Dresden, 01217, Germany","Nahiduzzaman K.M., School of Engineering, Univ. of British Columbia (UBC) Okanagan, 1137 Alumni Ave, Kelowna, V1V1V7, BC, Canada; Holland M., Community Planning, Vancouver Island Univ., 900 Fifth St., Nanaimo, V9R5S5, BC, Canada; Sikder S.K., Monitoring of Settlement and Open Space Development, Leibniz Institute of Ecological Urban and Regional Development, Weberplatz 1, Dresden, 01217, Germany; Shaw P., Community Planning, Vancouver Island Univ., 900 Fifth St., Nanaimo, V9R5S5, BC, Canada; Hewage K., School of Engineering, Univ. of British Columbia (UBC) Okanagan, 1137 Alumni Ave, Kelowna, V1V1V7, BC, Canada; Sadiq R., School of Engineering, Univ. of British Columbia (UBC) Okanagan, 1137 Alumni Ave, Kelowna, V1V1V7, BC, Canada","Making cities smart is an inherent goal and challenge for contemporary cities. This phenomenon becomes more complicated when there is an urgent need to adopt smart city principles against the backdrop of visible and invisible factors that cause urban transformations with varying magnitudes. One type of visibly invisible factor is e-commerce and its expanding operation that is understood to cause changes to a city's conventional spatial structure. However, very limited research exists about its momentum and pervasive magnitude of impact. Current literature predominantly focuses on the relationship and effect of e-commerce on transportation studies-notably, the influence of e-commerce on the direction and volume of traffic flow, the changing dynamics of logistics, and operational strategies. As a transitory variable, how e-commerce is going to influence a city's conventional spatial structure, the interwoven relationship between the city core, fringe, and rural areas, and in building smart cities remains unclear. This paper will attempt to explore the changing dynamics of a city's spatial structure with a specific focus on e-commerce induced changes in the retail landscape. Specifically, this paper aims to theoretically gauge the nature of these changes, which include division and fragmentation, reconceptualization, and relocation of retail stores and conceptually capturing the scenarios through critical analysis. Contemporary evidence further substantiates the need to account for e-commerce induced influence on contemporary thoughts on smart cities. Essentially, this stems from the requirement for a systemic analysis that explains the path-dependency framework of the complex relationship between e-commerce and shifts in a city's changing spatial structure. Based on the requirement for a path-dependent analysis, this paper calls for an ideological shift in the conceptualization of a smart city definition from a concept to a process. It argues that such a shift has a critical impact that determines what makes cities truly smart.  © 2020 American Society of Civil Engineers.","E-Commerce; Path-dependent analysis; Smart city; Spatial structure; Systemic framework","Retail stores; Smart city; Changing dynamics; Complex relationships; Critical analysis; Induced paths; Operational strategies; Path dependency; Spatial structure; Systemic analysis; conceptual framework; smart city; spatial analysis; strategic approach; urban development; urban planning; Electronic commerce",{"$nulls":4},"Green Construction Research and Training Centre at the University of British Columbia; University of British Columbia, UBC","The authors gratefully acknowledge the funding and support provided by the Green Construction Research and Training Centre at the University of British Columbia (UBC) to conduct this research.","Ahmed S., Nahiduzzaman K.M., Bramley G., From a town to a megacity: 400 years of growth, Dhaka Megacity: Geospatial Perspectives on Urbanisation, Environment and Health, pp. 23-43, (2014); Ahmed S., Nahiduzzaman K.M., Hasan M.M.U., Dhaka, Bangladesh: Unpacking challenges and reflecting on unjust transitions, Cities, 77, pp. 142-157, (2018); Anthopoulos L., Janssen M., Weerakkody V., A Unified Smart City Model (USCM) for smart city conceptualization and benchmarking, Smart Cities and Smart Spaces: Concepts, Methodologies, Tools, and Applications, pp. 247-264, (2019); Ashworth W., The Four Rs of Investing in Retail Investopia, (2019); Balduini M., Brambilla M., Della Valle E., Marazzi C., Arabghalizi T., Rahdari B., Vescovi M., Models and practices in urban data science at scale, Big Data Res., 17, pp. 66-84, (2019); Bartholomae F., Woon Nam C., Schoenberg A., Urban shrinkage and resurgence in Germany, Urban Stud., 54, pp. 2701-2718, (2017); Batty M., Axhausen K.W., Giannotti F., Pozdnoukhov A., Bazzani A., Wachowicz M., Ouzounis G., Portugali Y., Smart cities of the future, Eur. 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Evidence from China, Sustainable Cities Soc., 50, (2019); Zubizarreta I., Seravalli A., Arrizabalaga S., Smart city concept: What it is and what it should be, J. Urban Plann. Dev., 142, (2015)","K.M. Nahiduzzaman; School of Engineering, Univ. of British Columbia (UBC) Okanagan, Kelowna, 1137 Alumni Ave, V1V1V7, Canada; email: kh.nahiduzzaman@ubc.ca",null,"American Society of Civil Engineers (ASCE)",{"$nulls":5},7339488.0,null,null,null,"English","J. Urban Plann. Dev.","Article","Final",null,"Scopus","2-s2.0-85097895563"]
["Giannikas V.; McFarlane D.","Giannikas, Vaggelis (53463493700); McFarlane, Duncan (7006198499)","53463493700; 7006198499","Examining the value of flexible logistics offerings",2021.0,"European Journal of Operational Research",290.0,3.0,null,968.0,981.0,13.0,12.0,"10.1016/j.ejor.2020.08.056","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85091037757&doi=10.1016%2fj.ejor.2020.08.056&partnerID=40&md5=bea286b10a8451dc2bb835d7806c5693","School of Management, University of Bath, Claverton Down, Bath, BA2 7AY, United Kingdom; Institute for Manufacturing, University of Cambridge, 17 Charles Babbage Road, Cambridge, CB3 0FS, United Kingdom","Giannikas V., School of Management, University of Bath, Claverton Down, Bath, BA2 7AY, United Kingdom; McFarlane D., Institute for Manufacturing, University of Cambridge, 17 Charles Babbage Road, Cambridge, CB3 0FS, United Kingdom","In the order fulfilment and retail industry, the provision of fast and low cost delivery services has received significant focus over the last decade. What is often neglected is other factors that contribute to a customer's overall experience like customisation and flexibility of deliveries, especially in cases when a customer's needs and plans change between order placement and order delivery. This paper explores the value of a flexible type of logistics offering in which the customer is able to change the order requirements (such as delivery date) after the order has been placed. In particular, we focus on the interactions between a retailer and a customer in agreeing and executing such logistics orders. We examine the benefits of this type of flexible logistics offerings because flexibility and customisation are critical factors for the success of omni-channel commerce. Such offerings are clearly connected with recent developments in digital technologies as these technologies are essential for the implementation. Our results indicate that flexible logistics offerings can be beneficial both for retailers and for customers. They also highlight the importance of receiving orders that do not fully meet the requirements of a customer. © 2020 Elsevier B.V.","e-commerce; Flexibility; Logistics; Omni-channel; Retailing","Sales; Service industry; Critical factors; Customisation; Delivery dates; Delivery service; Digital technologies; Low costs; Retail industry; Costs",{"$nulls":4},"NSRF; European Social Fund, ESF","The authors are grateful to James and James Fulfilment Ltd. for their valuable contribution to this study. This study has been funded via the “Individual Assessment Scholarship Programme of the State Scholarship Foundation of Greece 2011–2012” using funds from the “Education and Lifelong Learning” Operational Programme of the European Social Fund (ESF) and the NSRF, 2007–2013. 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(2019); Thome A.M.T., Scavarda L.F., Pires S.R., Ceryno P., Klingebiel K., A multi-tier study on supply chain flexibility in the automotive industry, International Journal of Production Economics, 158, pp. 91-105, (2014); Tian Y., Ellinger A.E., Chen H., Third-party logistics provider customer orientation and customer firm logistics improvement in china, International Journal of Physical Distribution & Logistics Management, 40, 5, pp. 356-376, (2010); (2017); Vakulenko Y., Shams P., Hellstrom D., Hjort K., Online retail experience and customer satisfaction: the mediating role of last mile delivery, The International Review of Retail, Distribution and Consumer Research, 29, 3, pp. 306-320, (2019); Wollenburg J., Holzapfel A., Hubner A., Kuhn H., Configuring retail fulfillment processes for omni-channel customer steering, International Journal of Electronic Commerce, 22, 4, pp. 540-575, (2018); Wong C., McFarlane D., Zaharudin A., Agarwal V., The intelligent product driven supply chain, Proceedings of the IEEE international conference on systems, man and cybernetics, 4, (2002); Zhang Q., Vonderembse M.A., Lim J.-S., Logistics flexibility and its impact on customer satisfaction, International Journal of Logistics Management, 16, 1, pp. 71-95, (2005)","V. Giannikas; School of Management, University of Bath, Bath, Claverton Down, BA2 7AY, United Kingdom; email: v.giannikas@bath.ac.uk",null,"Elsevier B.V.",{"$nulls":5},3772217.0,null,"EJORD",null,"English","Eur J Oper Res","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85091037757"]
["Galkin A.; Zaytsev V.; Shyshkin V.; Obolentseva L.; Popova Y.","Galkin, Andrii (57194199918); Zaytsev, Vitaliy (56728021900); Shyshkin, Viktor (57006716800); Obolentseva, Larysa (57202442326); Popova, Yuliia (57211468598)","57194199918; 56728021900; 57006716800; 57202442326; 57211468598","Patterns of the Distribution of the Demand of End-Consumers among Retailers in the Zone of their Residence",2021.0,"Foundations of Management",13.0,1.0,null,145.0,158.0,13.0,5.0,"10.2478/fman-2021-0011","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85117121977&doi=10.2478%2ffman-2021-0011&partnerID=40&md5=841f935b1b130037bb75d09e554f23b3","O.M. Beketov National University of Urban Economy in Kharkiv, Faculty of Transport System and Technologies, Kharkiv, Ukraine; Kharkiv University of Technology STEP, Kharkiv, Ukraine; Zaporizhzhia National University, Department of Entrepreneurship, Organization Management and Logistics, Zaporizhia, Ukraine; O.M. Beketov National University of Urban Economy in Kharkiv, Department of Tourism and Hospitality, Kharkiv, Ukraine; State University of Infrastructure and Technologies, Department of Business Logistics and Transportation Technologies, Kyiv, Ukraine","Galkin A., O.M. Beketov National University of Urban Economy in Kharkiv, Faculty of Transport System and Technologies, Kharkiv, Ukraine; Zaytsev V., Kharkiv University of Technology STEP, Kharkiv, Ukraine; Shyshkin V., Zaporizhzhia National University, Department of Entrepreneurship, Organization Management and Logistics, Zaporizhia, Ukraine; Obolentseva L., O.M. Beketov National University of Urban Economy in Kharkiv, Department of Tourism and Hospitality, Kharkiv, Ukraine; Popova Y., State University of Infrastructure and Technologies, Department of Business Logistics and Transportation Technologies, Kyiv, Ukraine","The rapid development of retail and e-commerce is forcing marketing and logistics to be competitive and adapt to the demands of end-customers. At the same time, accurately determining the demand for goods allows to better understand customers and plan deliveries. The purpose of this article is to study the change in patterns of probability of choosing the option to purchase goods among end-consumers with and without the presence of e-commerce. The study consisted of research buyers, determining the probability of purchasing goods from \"consumer basket\"in the traditional way and over the Internet, which is considered for the example of one of the Kharkiv districts. The results develop e-commerce potential in Ukraine and are intended to determine the motives of consumers when choosing a shopping option.  © 2021 Andrii Galkin et al., published by Sciendo.","end-consumers; logistics; nonlinearity factor; service; slope factor; zone",{"$nulls":7},"Ainsworth B.E., Haskell W.L., Whitt M.C., Irwin M.L., Swartz A.M., Strath S.J., O'Brien W.L., Bassett D.R., Schmitz K.H., Emplaincourt P.O., Jacobs D.R., Leon A.S., Compendium of Physical Activities: An Update of Activity Codes and MET Intensities, Medicine & Science in Sports & Exercise, 32, 9, pp. 498-504, (2000); Bajdor P., Starostka-Patyk M., Smart City: A Bibliometric Analysis of Conceptual Dimensions and Areas, Energies, 14, 14, (2021); Balandina I.S., Obolentseva L.V., Aleksandrova S.A., Polyakova Y.O., Dulfan S.B., Assessing Corporate Culture of an Enterprise-based on Competing Values Framework Design, J. Advanced Res. L. & Econ., 9, (2018); Chornopyska N., Bolibrukh L., The Influence of the Covid-19 Crisis on the Formation of Logistics Quality, Intellectualization of Logistics and Supply Chain Management, 2, pp. 88-98, (2020); Chortok Y., Yevdokymova A., Serpeninova Y., Formation of the Mechanism of Corporate Social and Environmental Responsibility of the Trading Company, Journal of Environmental Management & Tourism, 9, 5, pp. 1011-1018, (2018); Comi A., A Modelling Framework to Forecast Urban Goods Flows, Research in Transportation Economics, 80, (2020); Fatoki O., Factors Influencing the Purchase of Energy-Efficient Appliances by Young Consumers in South Africa, Foundations of Management, 12, 1, pp. 151-166, (2020); Fesenko T., Shakhov A., Fesenko G., Bibik N., Tupchenko V., Modeling of Customer Oriented Construction Project Management Using the Gender Logic Systems, Eastern-European Journal of Enterprise Technologies, 1, 3, pp. 91-59, (2018); Galkin A., Dolia C., Davidich N., The Role of Consumers in Logistics Systems, Transportation Research Procedia, 27, pp. 1187-1194, (2017); Galkin A., Mykola K., Balandina I., Anton R., Litomin I., Davidich N., Kumar C., Assessing the Impact of Population Mobility on Consumer Expenditures while Shopping, Transportation Research Procedia, 48, pp. 2187-2196, (2020); Galkin A., Obolentseva L., Balandina I., Kush E., Karpenko V., Bajdor P., Last-Mile delivery for consumer driven logistics, Transportation Research Procedia, 39, pp. 74-83, (2019); Galkin A., Popova Y., Bodnaruk O., Zaika Y., Chuprina E., Shapovalenko D., Kolonataievskyi O., Attractiveness Modeling of Retail on Emotional Fatigue of Consumers, The South East European Journal of Economics and Business, 14, 2, pp. 106-116, (2019); Gorokhova T., Mamatova L., The Impact of e-Commerce Development on Logistic Service in Ukraine: Perspectives and Challenges, Intellectualization of Logistics and Supply Chain Management, 1, pp. 76-90, (2020); Halkin A., Emotional State of Consumer in the Urban Purchase: Processing Data, Foundations of Management, 10, 1, pp. 99-112, (2018); Halkin A., Assessing the Utility of Retailer Based on Generalized Costs of End-Consumers, Foundations of Management, 12, 1, pp. 31-41, (2020); Halkin A., Bliumska-Danko K., Smihunova O., Dudnyk E., Balandina I., Investigation Influence of Store Type on Emotional State of Consumer in the Urban Purchase, Foundations of Management, 11, 1, pp. 7-22, (2019); Jette M., Sidney K., Blumchen G., Metabolic Equivalents (METS) in Exercise Testing, Exercise Prescription, and Evaluation of Functional Capacity, Clinical Cardiology, 13, 8, pp. 555-565, (1990); Kolodii S., Correlation-regression Analysis of GDP and Average Wage Indicators in Ukraine, Bulletin of the Cherkasy Bohdan Khmelnytsky National University. Economic Sciences, 1, pp. 82-89, (2020); Koval L., Tserklevych V., Popovich O., Bukhta S., Hurman O., Komarnitskyi I., Gender Targeting of Restaurants' Visitors - Representatives of Generation Z., International Journal of Management (IJM), 11, 6, pp. 155-162, (2020); Lusch R.F., Serpkenci R.R., Orvis B.T., Determinants of Retail Store Performance: A Partial Examination of Selected Elements of Retailer Conduct, Proceedings of the 1995 World Marketing Congress, pp. 495-504, (2015); Mifflin M.D., St Jeor S.T., Hill L.A., Scott B.J., Daugherty S.A., Koh Y.O., A New Predictive Equation for Resting Energy Expenditure in Healthy Individuals, The American Journal of Clinical Nutrition, 51, 2, pp. 241-247, (1990); Mixed-Use Properties: A Convenient Option for Shoppers, (2019); Pursky O., Selivanova A., Dubovyk T., Herasymchuk T., Software Implementation of e-Trade Business Process Management Information System, In CEUR Workshop Proceedings, 2546, pp. 171-181, (2019); Russo F., Comi A., City Characteristics and Urban Goods Movements: A Way to Environmental transportation System in a Sustainable City, Procedia-Social and Behavioral Sciences, 39, pp. 61-73, (2012); Selivanova A., Pursky O., Yurchenko Y., Samoylenko H., Dubovyk T., Agent Modeling of Online Store Activities, pp. 227-236, (2020); Sharma P., Chen I.S., Luk S.T., Tourist Shoppers' Evaluation of Retail Service: A Study of Cross-border Versus International Outshoppers, Journal of Hospitality & Tourism Research, 42, 3, pp. 392-419, (2018); Verroios V., Efstathiou V., Delis A., Reaching Available Public Parking Spaces in Urban Environments Using Ad Hoc Networking, 1, pp. 141-151, (2011); Wodecki A., The Reserve Price Optimization for Publishers on Real-Time Bidding on-Line Marketplaces with Time-Series Forecasting, Foundations of Management, 12, 1, pp. 167-180, (2020); Zatonatska T., Dluhopolskyi O., Chyrak I., Kotys N., The Internet and e-Commerce Diffusion in European Countries (modeling at the example of Austria, Poland and Ukraine), Innovative Marketing, 15, 1, pp. 66-75, (2019)",null,null,"Sciendo",{"$nulls":5},2.0807279E7,null,null,null,"English","Found. Manag.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85117121977"]
["Boysen N.; Fedtke S.; Schwerdfeger S.","Boysen, Nils (16201940600); Fedtke, Stefan (57190967668); Schwerdfeger, Stefan (57188827390)","16201940600; 57190967668; 57188827390","Last-mile delivery concepts: a survey from an operational research perspective",2021.0,"OR Spectrum",43.0,1.0,{"$nulls":4},184.0,"10.1007/s00291-020-00607-8","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85091234095&doi=10.1007%2fs00291-020-00607-8&partnerID=40&md5=bbdb5dd259ede121596eac95d26d9a5b","Lehrstuhl für Operations Management, Friedrich-Schiller-Universität Jena, Carl-Zeiß-Straße 3, Jena, 07743, Germany; Lehrstuhl für Management Science, Friedrich-Schiller-Universität Jena, Carl-Zeiß-Straße 3, Jena, 07743, Germany","Boysen N., Lehrstuhl für Operations Management, Friedrich-Schiller-Universität Jena, Carl-Zeiß-Straße 3, Jena, 07743, Germany; Fedtke S., Lehrstuhl für Operations Management, Friedrich-Schiller-Universität Jena, Carl-Zeiß-Straße 3, Jena, 07743, Germany; Schwerdfeger S., Lehrstuhl für Operations Management, Friedrich-Schiller-Universität Jena, Carl-Zeiß-Straße 3, Jena, 07743, Germany, Lehrstuhl für Management Science, Friedrich-Schiller-Universität Jena, Carl-Zeiß-Straße 3, Jena, 07743, Germany","In the wake of e-commerce and its successful diffusion in most commercial activities, last-mile distribution causes more and more trouble in urban areas all around the globe. Growing parcel volumes to be delivered toward customer homes increase the number of delivery vans entering the city centers and thus add to congestion, pollution, and negative health impact. Therefore, it is anything but surprising that in recent years many novel delivery concepts on the last mile have been innovated. Among the most prominent are unmanned aerial vehicles (drones) and autonomous delivery robots taking over parcel delivery. This paper surveys established and novel last-mile concepts and puts special emphasis on the decision problems to be solved when setting up and operating each concept. To do so, we systematically record the alternative delivery concepts in a compact notation scheme, discuss the most important decision problems, and survey existing research on operations research methods solving these problems. Furthermore, we elaborate promising future research avenues. © 2020, The Author(s).","City logistics; Last-mile delivery; Survey; Transportation",{"$nulls":7},{"$cut":{"chars":32565,"head":"Agatz N., Bouman P., Schmidt M., Optimization approaches for the traveling salesman problem with drone, Transp Sci, 52, pp. 965-981, (2018); Agatz N., Campbell A.M., Fleischmann M., Savelsbergh M.W.P., Challenges and opportunities in attended home delivery, The Vehicle Routing Problem: Latest Advances and New Challenges. Operations Research/Computer Science Interfaces, 43, (2008); Agatz N., Campbell A.M., Fleischmann M., Savelsbergh M.W.P., Time slot management in attended home delivery, Transp Sci, 45, pp. 435-449, (2011); Akeb H., Moncef B., Durand B., Building a collaborative solution in dense urban city settings to enhance parcel delivery: an effective crowd model in Paris, Transp Res Part E, 119, pp. 223-233, (2018); Albiach J., Sanchis J.M., Soler D., An asymmetric TSP with time windows and with time-dependent travel times and costs: an exact solution through a graph transformation, Eur J Oper Res, 189, pp. 789-802, (2008); Allahviranloo M., Baghestani A., A dynamic crowdshipping model and daily travel behavior, Transp Res Part E, 128, pp. 175-190, (2019); Allen J., Bektaks T., Cherrett T.J., Bates O., Friday A., McLeod F.N., Piecyk M., Piotrowska M., Nguyen T., Wise S., The scope for pavement porters: addressing the challenges of last-mile parcel delivery in London, Transp Res Rec, 2672, pp. 184-193, (2018); Allen J., Piecyk M., Piotrowska M., McLeod F.N., Cherrett T.J., Ghali K., Nguyen T., Bektaxks T., Bates O., Friday A., Wise S., Understanding the impact of e-commerce on last-mile light goods vehicle activity in urban areas: the case of London, Transp Res Part D, 61, pp. 325-338, (2018); Online-Händler: Amazon will Mini-Drohnen einsetzen (digital image), (2013); (2020); (2019); Key by Amazon Smart Lock Kit, (2020); Amazon Flex Website, (2020); Anderluh A., Hemmelmayr V.C., Nolz P.C., Synchronizing vans and cargo bikes in a city distribution network, Central Eur J Oper Res, 25, pp. 345-376, (2017); Archetti C., Savelsbergh M.W.P., Speranza M.G., The vehicle routing problem with occasional drivers, Eur J Oper Res, 254, pp. 472-480, (2016); Arigliano A., Ghiani G., Grieco A., Guerriero E., Plana I., Time-dependent asymmetric traveling salesman problem with time windows: properties and an exact algorithm, Discrete Appl Math, 261, pp. 28-39, (2019); Arnold F., Cardenas I., Sorensen K., Dewulf W., Simulation of B2C e-commerce distribution in Antwerp using cargo bikes and delivery points, Eur Transp Res Rev, 10, (2018); Arslan A.M., Agatz N., Kroon L., Zuidwijk R., Crowdsourced Delivery: A dynamic pickup and delivery problem with ad-hoc drivers, Transp Sci, 53, (2019); Ascheuer N., Fischetti M., Grotschel M., A polyhedral study of the asymmetric traveling salesman problem with time windows, Networks, 36, pp. 69-79, (2000); Ascheuer N., Fischetti M., Grotschel M., Solving the asymmetric travelling salesman problem with time windows by branch-and-cut, Math Program, 90, pp. 475-506, (2001); Azi N., Gendreau M., Potvin J.-Y., A dynamic vehicle routing problem with multiple delivery routes, Ann Oper Res, 199, pp. 103-112, (2012); Bakach I., Campbell A.M., Ehmke J.F., A two-tier urban delivery network with robot-based deliveries, (2020); Baldacci R., Mingozzi A., Roberti R., New state-space relaxations for solving the traveling salesman problem with time windows, INFORMS J Comput, 24, pp. 356-371, (2012); Baloch G., Gzara F., Strategic network design for parcel delivery with drones under competition, Transp Sci, 54, pp. 204-228, (2020); Alibaba Begins Drone Delivery Trials in China., (2015); Beckman B.C., Bjone N., Ground-based mobile maintenance facilities for unmanned aerial vehicles, United States Patent, 9, 718, (2017); Behrend M., Meisel F., The integration of item-sharing and crowdshipping: Can collaborative consumption be pushed by delivering through the crowd?, Transp Res Part B, 111, pp. 227-243, (2018); Behrend M., Meisel F., Fagerholt K., Andersson H., An exact solution method for the capacitated item-sharing and crowdshipping problem, Eur J Oper Res, 279, pp. 589-604, (2019); Berg P.W., Isaacs S., Blodgett K.L."}},"N. Boysen; Lehrstuhl für Operations Management, Friedrich-Schiller-Universität Jena, Jena, Carl-Zeiß-Straße 3, 07743, Germany; email: nils.boysen@uni-jena.de",null,"Springer Science and Business Media Deutschland GmbH",{"$nulls":5},1716468.0,null,null,null,"English","OR Spectrum","Article","Final","All Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85091234095"]
["Akram U.; Fülöp M.T.; Tiron-Tudor A.; Topor D.I.; Căpușneanu S.","Akram, Umair (57190977435); Fülöp, Melinda Timea (56168879500); Tiron-Tudor, Adriana (36057720300); Topor, Dan Ioan (56955851400); Căpușneanu, Sorinel (24721054900)","57190977435; 56168879500; 36057720300; 56955851400; 24721054900","Impact of digitalization on customers’ well-being in the pandemic period: Challenges and opportunities for the retail industry",2021.0,"International Journal of Environmental Research and Public Health",18.0,14.0,7533.0,null,null,null,69.0,"10.3390/ijerph18147533","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85110106932&doi=10.3390%2fijerph18147533&partnerID=40&md5=3addd0ae1d0d7db60415c8394dd98eae","School of Management, Jiangsu University, Zhenjiang, 212013, China; Faculty of Economics and Business Administration, Babeş-Bolyai University of Cluj-Napoca, Cluj-Napoca, 400591, Romania; Faculty of Economic Sciences, 1 Decembrie 1918 University, Alba-Iulia, 510009, Romania; Faculty of Finance-Banking, Accounting and Business Administration, Titu Maiorescu University, Bucharest, 040051, Romania","Akram U., School of Management, Jiangsu University, Zhenjiang, 212013, China; Fülöp M.T., Faculty of Economics and Business Administration, Babeş-Bolyai University of Cluj-Napoca, Cluj-Napoca, 400591, Romania; Tiron-Tudor A., Faculty of Economics and Business Administration, Babeş-Bolyai University of Cluj-Napoca, Cluj-Napoca, 400591, Romania; Topor D.I., Faculty of Economic Sciences, 1 Decembrie 1918 University, Alba-Iulia, 510009, Romania; Căpușneanu S., Faculty of Economic Sciences, 1 Decembrie 1918 University, Alba-Iulia, 510009, Romania, Faculty of Finance-Banking, Accounting and Business Administration, Titu Maiorescu University, Bucharest, 040051, Romania","Order increases, supply chain disruptions, changing customer behavior, store closures, and more that have been caused by the coronavirus epidemic (COVID-19) will undoubtedly affect the online commerce forms of business. The coronavirus pandemic has a significant impact on digitalization and customer experience and well-being in mobile commerce. Since the beginning of the coronavirus pandemic, online sales and the number of online shoppers using wireless internet-enabled devices have increased tremendously. The article develops, an experimental study that captures COVID-19 and digital commerce’s impact in terms of customers’ experience and well-being during the pandemic period. The study explores the synergy between technology evolution and the effects of the COVID-19 pandemic on customers’ behavior based on survey data collection and the technology acceptance model (TAM). The results reveal that, for millennials, digital commerce seems to be the typical way of shopping and paying in the pandemic period since the oldest generations adopted in a smaller proportion the use of mobile devices for shopping and payments. Besides, retailers are confronted with great challenges raised by millennials’ expectations. The result confirms four of the six hypotheses based on the technology acceptance model (TAM). As a result, it shows that the easiness of use, trust, mobility, and customer involvement influences the behavioral intention of the customer to use mobile commerce, and that usefulness and customization does not influence the behavioral intention. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.","COVID-19; Customer wellbeing; M-commerce; Online; Pandemic","Commerce; Consumer Behavior; COVID-19; Humans; Pandemics; SARS-CoV-2; Surveys and Questionnaires; Coronavirus; consumption behavior; COVID-19; electronic commerce; experimental study; pandemic; retailing; shopping activity; technological development; Article; behavior; commercial phenomena; conceptual framework; consumer protection; coronavirus disease 2019; electronic commerce; expectation; home delivery; human; human experiment; hypothesis; information model; internet access; mobile application; online shopping; pandemic; patient satisfaction; perception; reliability; social status; technology acceptance model; trust; wellbeing; consumer attitude; questionnaire",{"$nulls":6},{"$cut":{"chars":22755,"head":"Kleemann F.C., Glas A.H., Einkauf 4.0: Digitale Transformation der Beschaffung—2 Auflage, (2020); Bendel O., Die Industrie 4.0 aus Sicht der Ethik, Industrie 4.0 Herausforderungen, Konzepte und Praxisbeispiele, pp. 161-172, (2017); Carroll N., Conboy K., Normalising the “new normal”: Changing tech-driven work practices under pandemic time pressure, Int. J. Inf. Manag, 55, (2020); Chong A.Y.-L., Chan F.T.S., Ooi K.-B., Predicting consumer decisions toadopt mobile commerce: Cross country empirical examination between Chinaand Malaysia, Decis. Support Syst, 53, pp. 34-43, (2012); Gardan D.A., Dumitru I., Gardan I.P., Pastiu C.A., Touristic SME’s Competitiveness in the Light of Present Challenges—A Qualitative Approach, Sustainability, 12, (2020); Williams S.N., Armitage C.J., Tampe T., Dienes K., Public perceptions and experiences of social distancing and social isolation during the COVID-19 pandemic: A UK-based focus group study, BMJ Open, 10, (2020); Oliveira T., Alhinho M., Rita P., Dhillon G., Modelling and Testing Consumer Trust Dimensions in E-Commerce, Comput. Human Behav, 71, pp. 153-164, (2017); Stanescu S.G., Cucui I., Ionescu C.A., Paschia L., Coman M.D., Nicolau N.L.G., Uzlau M.C., Lixandru M.L., Conceptual Model forIntegrating Environmental Impact in Managerial Accounting Information Systems, Int. J. Environ. Res. Public Health, 18, (2021); Sheth J., Impact of Covid-19 on consumer behavior: Will the old habits return or die?, J. Bus. Res, 117, pp. 280-283, (2020); Chong A.Y.-L., Predicting m-commerce adoption determinants: A neural network approach, Expert Syst. Appl, 40, pp. 523-530, (2013); Barry M., Jan M., Factors influencing the use of m-commerce: An extended technology acceptance model perspective, Int. J. Econ. Manag. Account, 26, pp. 157-183, (2018); Grewal D., Bart Y., Spann M., Zubcsek P.P., Mobile advertising: A framework and research agenda, J. Interact. Mark, 34, pp. 3-14, (2016); Shankar V., Venkatesh A., Hofacker C., Naik P., Mobile marketing in the retailing environment: Current insights, and future research avenues, J. Interact. Market, 24, pp. 111-120, (2010); Omar S., Mohsen K., Tsimonis G., Oozeerally A., Hsu J.H., M-commerce: The nexus between mobile shopping service quality and loyalty, J. Retail. Consum. Serv, 60, (2021); Dumitrascu L.M., Feleaga L., Ionescu B.S., Time Management and Time Utilization for Urology Surgeons, a Step in Implementing Social Responsibility, a Theoretical and a Practical Approach, Business Revolution in a Digital Era, pp. 319-329, (2021); Kovacs G., Combination of Lean value-oriented conception and facility layout design for even more significant efficiency improvement and cost reduction, Int. J. Prod. Res, 58, pp. 2916-2936, (2020); Gurau C., A Life-Stage Analysis of Consumer Loyalty Profile: Comparing Generation X and Millennial Consumers, J. Consum. Mark, 29, pp. 103-113, (2012); Lissitsa S., Kol O., Generation X vs. Generation Y: A decade of online shopping, J. Retail. Consum. Serv, 31, pp. 304-312, (2016); Siminica M., Avram M., Roxana L.P., Avram L., The adoption of national green procurement plans from the perspective of circular economy, Amfiteatru Econ, 22, pp. 15-27, (2020); Romanian Association of Online Stores; Neto R.D.C.S., Maia J.S., de Silva Neiva S., Scalia M.D., de Andrade J.B.S.O., The fourth industrial revolution and the coronavirus: A new era catalyzed by a virus, Res. Glob, 2, (2020); Rodriguez-Ardura I., Meseguer-Artola A., Toward a Longitudinal Model of e-Commerce: Environmental, Technological, and Organizational Drivers of B2C Adoption, Inf. Soc, 26, pp. 209-227, (2010); Zheng H., A Study on the Usability of e-Commerce Websites Between China and Thailand, Int. J. Simul, 17, (2016); Thatcher S.M., Foster W., Zhu L., B2B e-commerce adoption decisions in Taiwan: The interaction of cultural and other institutional factors, Electron. Commer. Res. Appl, 5, pp. 92-104, (2006); Zhang X., Wang T., Understanding Purchase Intention in O2O E-Commerce: The Effects of Trust Transfer and Online Contents, J. Theor. Appl. Electron. Commer. Res, 16, pp. 10"}},"D.I. Topor; Faculty of Economic Sciences, Alba-Iulia, 1 Decembrie 1918 University, 510009, Romania; email: dan.topor@uab.ro",null,"MDPI",{"$nulls":5},1.6617827E7,null,null,3.4299984E7,"English","Int. J. Environ. Res. Public Health","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85110106932"]
["Jo W.; Kim J.; Choi J.","Jo, Wooyong (57214895492); Kim, Jikyung (Jeanne) (57191899877); Choi, Jeonghye (49862944700)","57214895492; 57191899877; 49862944700","Who are the multichannel shoppers and how can retailers use them? Evidence from the French apparel industry",2021.0,"Asia Pacific Journal of Marketing and Logistics",33.0,1.0,null,250.0,274.0,24.0,25.0,"10.1108/APJML-05-2019-0317","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85082945858&doi=10.1108%2fAPJML-05-2019-0317&partnerID=40&md5=504922742702061f8667919ee32b0111","Emory University, Atlanta, United States; IE University, Madrid, Spain; Yonsei University, Seoul, South Korea","Jo W., Emory University, Atlanta, United States; Kim J., IE University, Madrid, Spain; Choi J., Yonsei University, Seoul, South Korea","Purpose: This study aims to identify, within the context of the French fashion industry, the characteristics of multichannel shoppers, that is, consumers who use more than one channel in a single shopping trip. We especially investigate whether consumers' focus on quality versus price affects their multichannel shopping tendency and their flexibilities in their shopping lists (basket flexibility). Design/methodology/approach: We surveyed a representative sample of 400 French shoppers regarding fashion apparel purchasing. We use a logistic regression framework to measure the probability of a shopper becoming a multichannel shopper based on the key constructs and a battery of control variables. Findings: The analysis shows that, in fashion buying, shoppers focused on quality and those with high basket flexibility have a higher probability of becoming multichannel shoppers. The probability becomes even greater when a shopper is both quality oriented and has basket flexibility. Research limitations/implications: We focus on the fashion apparel market for a deeper understanding of multichannel usage of products with both experience and search features. Future research can investigate other industries for higher generalizability. Practical implications: Our research provides insights into multichannel fashion companies whose managements aim to effectively manage high-value customers who tend to use more channels when shopping. Specifically, an omnichannel marketing strategy should focus on capturing the quality-oriented and highly basket-flexible segment of consumers. Originality/value: Our study provides evidence that for products having high experiential as well as search features, quality-oriented and highly flexible shoppers engage more in multichannel shopping. Because these characteristics are related to the long-term value of customers, we provide the link between multichannel marketing and firm profitability in the context of the fashion industry. © 2020, Emerald Publishing Limited.","Basket flexibility; Multichannel shopping; Omni-channel; Online shopping; Price consciousness; Quality consciousness; Showrooming; Webrooming",{"$nulls":5},"Yonsei University; Ministry of Education, MOE; National Research Foundation of Korea, NRF, (NRF-2017S1A3A2066788)","Funding text 1: The authors gratefully acknowledge insightful comments and suggestions from the two anonymous reviewers and the editor of APJML. This paper streams from work started during the first author’s undergraduate studies at Yonsei University. This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea [Grant NRF-2017S1A3A2066788]. ; Funding text 2: The authors gratefully acknowledge insightful comments and suggestions from the two anonymous reviewers and the editor of APJML. This paper streams from work started during the first author?s undergraduate studies at Yonsei University. This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea [Grant NRF-2017S1A3A2066788].",{"$cut":{"chars":22285,"head":"Abendroth L.J., Diehl K., Now or never: effects of limited purchase opportunities on patterns of regret over time, Journal of Consumer Research, 90, 3, pp. 342-351, (2006); Aiken L.S., West S.G., Reno R.R., Multiple Regression: Testing and Interpreting Interactions, (1991); Ajzen I., The theory of planned behavior, Organizational Behavior and Human Decision Processes, 50, 2, pp. 179-211, (1991); Anderson-Connell L.J., Ulrich P.V., Brannon E.L., A consumer-driven model for mass customization in the apparel market, Journal of Fashion Marketing and Management, 6, 3, pp. 240-258, (2002); Ansari A., Mela C.F., Neslin S.A., Customer channel migration, Journal of Marketing Research, 45, 1, pp. 60-76, (2008); Arora S., Sahney S., Consumer's webrooming conduct: an explanation using the theory of planned behavior, Asia Pacific Journal of Marketing and Logistics, 30, 4, pp. 1040-1063, (2018); Arora S., Singha K., Sahney S., Understanding consumer's showrooming behaviour: extending the theory of planned behaviour, Asia Pacific Journal of Marketing and Logistics, 29, 2, pp. 409-431, (2017); Ataman M.B., Mela C.F., Van Heerde H.J., Consumer packaged goods in France: national brands, regional chains, and local branding, Journal of Marketing Research, 44, 1, pp. 14-20, (2007); Avery J., Steenburgh T.J., Deighton J., Caravella M., Adding bricks to clicks: predicting the patterns of cross-channel elasticities over time, Journal of Marketing, 76, 3, pp. 96-111, (2012); Bakos J.Y., Reducing buyer search costs: implications for electronic marketplaces, Management Science, 43, 12, pp. 1676-1692, (1997); Baumeister R.F., Yielding to temptation: self-control failure, impulsive purchasing, and consumer behavior, Journal of Consumer Research, 28, 4, pp. 670-676, (2002); Bei L., Chen E., Widdows R., Consumers' online information search behavior and the phenomenon of search vs. experience products, Journal of Family and Economic Issues, 25, 4, pp. 449-467, (2004); Bell D.R., Gallino S., Moreno A., How to win in an omnichannel world, MIT Sloan Management Review, 56, 1, pp. 45-53, (2014); Bellenger D.N., Korgaonkar P.K., Profiling the recreational shopper, Journal of Retailing, 56, 3, pp. 77-92, (1980); Bertrandias L., Goldsmith R.E., Some psychological motivations for fashion opinion leadership and fashion opinion seeking, Journal of Fashion Marketing and Management, 10, 1, pp. 25-40, (2006); Birtwistle G., Tsim C., Consumer purchasing behaviour: an investigation of the UK mature women's clothing market, Journal of Consumer Behaviour, 4, 6, pp. 453-464, (2005); Blattberg R., Buesing T., Peacock P., Sen S., Identifying the deal prone segment, Journal of Marketing Research, 15, 3, pp. 369-377, (1978); Blattberg R., Malthouse E.C., Neslin S.A., Customer lifetime value: empirical generalizations and some conceptual questions, Journal of Interactive Marketing, 23, 2, pp. 157-168, (2009); Boatwright P., Dhar S., Rossi P.E., The role of retail competition, demographics and account retail strategy as drivers of promotional sensitivity, Quantitative Marketing and Economics, 2, 2, pp. 169-190, (2004); Boehm M., Determining the impact of internet channel use on a customer's lifetime, Journal of Interactive Marketing, 22, 3, pp. 2-22, (2008); Brun A., Castelli C., Supply chain strategy in the fashion industry: developing a portfolio model depending on product, retail channel and brand, International Journal of Production Economics, 116, 2, pp. 169-181, (2008); Castanier C., Deroche T., Woodman T., Theory of planned behaviour and road violations: the moderating influence of perceived behavioural control, Transportation Research Part F: Traffic Psychology and Behaviour, 18, pp. 148-158, (2013); Chandon P., Morwitz V.G., Reinartz W.J., The short-and long-term effects of measuring intent to repurchase, Journal of Consumer Research, 31, 3, pp. 566-572, (2004); Cheng J.M., Wang E.S., Lin J.Y., Vivek S.D., Why do customers utilize the internet as a retailing platform?, Asia Pacific Journal of Marketing and Logistics, 21, 1, pp. 144-160, (2009); Chiu W., Leng H.K., Con"}},"J. Choi; Yonsei University, Seoul, South Korea; email: jeonghye@yonsei.ac.kr",null,"Emerald Group Holdings Ltd.",{"$nulls":5},1.3555855E7,null,null,null,"English","Asia Pac. J. Mark. Logist.","Article","Final",null,"Scopus","2-s2.0-85082945858"]
["Pfoser S.; Brandner M.; Herman K.; Steinbach E.; Brandtner P.; Schauer O.","Pfoser, Sarah (56584701300); Brandner, Manuela (57357922400); Herman, Katharina (57357541900); Steinbach, Elisabeth (57357670400); Brandtner, Patrick (55415699500); Schauer, Oliver (56073831100)","56584701300; 57357922400; 57357541900; 57357670400; 55415699500; 56073831100","Sustainable Transport Packaging: Evaluation and Feasibility for Different Use Cases",2021.0,"LOGI - Scientific Journal on Transport and Logistics",12.0,1.0,null,159.0,170.0,11.0,4.0,"10.2478/logi-2021-0015","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85120349679&doi=10.2478%2flogi-2021-0015&partnerID=40&md5=8a6c1ec681bfdbc83f92e7ce895d4798","University of Applied Sciences Upper Austria, Roseggerstraße 15, Wels, 4600, Austria","Pfoser S., University of Applied Sciences Upper Austria, Roseggerstraße 15, Wels, 4600, Austria; Brandner M., University of Applied Sciences Upper Austria, Roseggerstraße 15, Wels, 4600, Austria; Herman K., University of Applied Sciences Upper Austria, Roseggerstraße 15, Wels, 4600, Austria; Steinbach E., University of Applied Sciences Upper Austria, Roseggerstraße 15, Wels, 4600, Austria; Brandtner P., University of Applied Sciences Upper Austria, Roseggerstraße 15, Wels, 4600, Austria; Schauer O., University of Applied Sciences Upper Austria, Roseggerstraße 15, Wels, 4600, Austria","The continuous increase in e-commerce shipping is causing a critical amount of transport packaging waste. The aim of this paper is a comprehensive presentation of different types of innovations for sustainable transport packaging. Within the paper, classification and evaluation of 37 sustainable packaging solutions are presented, including customized on-demand packaging, alternative materials and closed-loop systems. A multi-criteria evaluation scheme covering a wide range of economic, ecological, operational and social indicators was used to assess the feasibility of the packaging options in different cases. Depending on the degree of innovation and implementation risk, packaging options are proposed as a \"Quick Win\", \"Go Green\"or \"Thought Leadership\"solution. In the conclusion chapter of this paper, recommendations are made for three different use cases, namely grocery, fashion and textiles and electronic goods.  © 2021 Sarah Pfoser et al., published by Sciendo.","logistics; Packaging; sustainability; transport",{"$nulls":7},"Tencati A., Pogutz S., Moda B., Brambilla M., Cacia C., Prevention policies addressing packaging and packaging waste: Some emerging trends, Waste Management, 56, pp. 35-45, (2016); De Jaeger S., Rogge N., Cost-efficiency in packaging waste management: The case of belgium, Resources, Conservation and Recycling, 85, pp. 106-115, (2014); Meherishi L., Narayana S.A., Ranjani K.S., Sustainable packaging for supply chain management in the circular economy: A review, Journal of Cleaner Production, 237, (2019); Franken R., Franken S., Integrated knowledge and innovation management, With Case Studies and Examples from Company Practice (In German), (2011); Disselkamp M., Types of innovations, Innovation Management (In German), pp. 21-30, (2012); Esurrsell S., Llorach-Massana P., Blanca R.M., Sustainability in e-commerce packaging: A review, Journal of Cleaner Production, 280, (2021); Coelho P.M., Corona B., Klooster R., Worrell E., Sustainability of reusable packaging-current situation and trends, Ressources, Conservation & Recycling, 6, (2020); Licciardello F., Packaging, blessing in disguise. review on its diverse contribution to food sustainability, Trends in Food Science & Technology, 65, pp. 32-39, (2017); Narayanan M., Loganathan S., Valapa R.B., Thomas S., Varghese T.O., Uv protective poly(lactic acid)/rosin films for sustainable packaging, International Journal of Biological Macromolecules, 99, pp. 37-45, (2017); Paptic.com. With Assistance of Paptic, (2021); Egger J., Grass paper packaging (in german), With Assistance of Egger, (2021); Peck P., Richter J.L., Dalhammar C., Peck D., Orlov D., MacHacek E., Voytenko Palgan Y., A Compendium by the International Institute for Industrial Environmental Economics (IIIEE) at Lund University, (2019); Michel V., Siegfried P., Digitale Speditionen in der Lebensmittellogistik-Digital freight forwarders in food logistics, Logistics Journal: Logistics Journal : Referierte Veröffentlichungen, 2, (2021); Larsen J., Moxness T., Environmental Report (In Swedish), (2021); Korzeniowski A., Jasiczak J., Accomplishment of selected package functions in e-commerce, Log Forum, 1, 1-2, (2005); Massimo A., Enabling the Internet of Things, (2017); Freichel S., Wollenburg J., Wortge J., The role of packaging in omni-channel fashion retail supply chains-how can packaging contribute to logistics efficiency, Logistics Research, 13, 1, (2020)","S. Pfoser; University of Applied Sciences Upper Austria, Wels, Roseggerstraße 15, 4600, Austria; email: Sarah.Pfoser@fh-steyr.at",null,"De Gruyter Open Ltd",{"$nulls":5},2.3363037E7,null,null,null,"English","LOGI Sci. J. Trans. Log.","Article","Final","All Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85120349679"]
["Cao Q.; Zhang X.; Ren X.","Cao, Qingkui (13612418700); Zhang, Xuefei (57361568600); Ren, Xiangyang (24832240900)","13612418700; 57361568600; 24832240900","Path Optimization of Joint Delivery Mode of Trucks and UAVs",2021.0,"Mathematical Problems in Engineering",2021.0,null,4670997.0,null,null,null,1.0,"10.1155/2021/4670997","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85120529457&doi=10.1155%2f2021%2f4670997&partnerID=40&md5=44d0d0af610d9af49fab0251dac63faa","School of Management Engineering and Business, Hebei University of Engineering, Handan, 056038, China; School of Economics and Management, Langfang Normal University, Langfang, 065000, China","Cao Q., School of Management Engineering and Business, Hebei University of Engineering, Handan, 056038, China, School of Economics and Management, Langfang Normal University, Langfang, 065000, China; Zhang X., School of Management Engineering and Business, Hebei University of Engineering, Handan, 056038, China; Ren X., School of Management Engineering and Business, Hebei University of Engineering, Handan, 056038, China","With the development of e-commerce and information technology, new modes of distribution are emerging. A new type of distribution tool, UAV (unmanned aerial vehicle), has entered into the public's field of vision. In the background of growing e-commerce, this paper proposes a new delivery mode of joint delivery of trucks and UAVs which particularly has been popular in recent years, with the advantages of prompt delivery, low cost, and independence from terrain restrictions, while traditional transportation tools such as trucks have more advantages in terms of flight distance and load capacity. Therefore, the joint delivery mode of trucks and UAVs proposed in this paper can well realize the complementary advantages of trucks and UAVs in the distribution process and consequently optimize the distribution process. Moreover, the growing e-commerce promotes customers' higher needs for delivery efficiency and the integrity of the delivered goods which urges companies to pay more attention to customers' satisfaction. This paper analyzes the joint delivery mode of trucks and UAVs, aims to minimize total delivery cost and maximize customer satisfaction, and builds a multiobjective optimization model for joint delivery. Furthermore, an improved ant colony algorithm is proposed in order to solve the mode in this paper. In order to effectively avoid prematurity of the ant colony algorithm, the limited pheromone concentration and the classification idea of the artificial bee colony algorithm are introduced to improve the ant colony algorithm. Finally, some experiments are simulated by MATLAB software, and the comparison shows that the joint delivery of trucks and UAVs has more advantages, and the improved ant colony algorithm is more efficient than the traditional ant colony.  © 2021 Qingkui Cao et al.",null,"Ant colony optimization; Antennas; Automobiles; Electronic commerce; MATLAB; Multiobjective optimization; Sales; Trucks; Unmanned aerial vehicles (UAV); Customers' satisfaction; Delivery modes; Distribution process; Distribution tools; E- commerces; Improved ant colony algorithm; Load capacity; Low-costs; Path optimizations; Customer satisfaction",{"$nulls":4},"Social Science Grand Research of Hebei Education Department, (ZD202105)","This paper was supported by Social Science Grand Research of Hebei Education Department (ZD202105).","Ren X., Huang H., Yu S.-W., Feng S., Liang G.-Q., Review on vehicle-UAV combined delivery problem, Control and Decision, 10, pp. 2313-2327, (2021); Wu Y., Wu S.-B., Hu X.-T., Cooperative Path Planning of UAVs & UGVs for a persistent surveillance task in urban environments, Ieee Internet of Things Journal, 99, pp. 1-14, (2020); 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Zhang X.-M., Hu Y.-J., Li W.-G., Pang Q.-W., Yuan G.-G., Multi-UAV fire fighting mission planning based on improved artificial bee colony algorithm, Journal of Chinese Inertial Technology, 28, pp. 528-536, (2020); Kim J., Song B.D., Morrison J.R., On the scheduling of systems of UAVs and fuel service stations for long-term mission fulfillment, Journal of Intelligent & Robotic Systems, 70, 1-4, pp. 347-359, (2013); Maini P., Sundar K., Singh M., Rathinam S., Sujit P.B., Cooperative aerial-ground vehicle route Planning with fuel constraints for coverage applications, Ieee Transactions on Aerospace and Electronic Systems, 55, 6, pp. 3016-3028, (2019); Hu Z.-F., Chen Y., Zheng X.-J., Wu H.-Y., Cooperative patrol path planning method for air-ground heterogeneous robot system, Control Theory & Applications, 10, pp. 1-13, (2021); Murray C.C., Chu A.G., The flying sidekick traveling salesman problem: Optimization of drone-assisted parcel delivery, Transportation Research Part C: Emerging Technologies, 54, pp. 86-109, (2015); Ham A.M., Integrated scheduling of m-truck, m-drone, and m-depot constrained by time-window, drop-pickup, and m-visit using constraint programming depot constrained by time-window, drop-pickup, and m-visit using constraint programming, Transportation Research Part C: Emerging Technologies, 91, pp. 1-14, (2018); Agatz N., Bouman P., Schmidt M., Optimization approaches for the traveling salesman Problem with drone, Transportation Science, 52, 4, pp. 965-981, (2018); Mario M., Leonardo C., Michele O., Mauro D., En route truck-drone parcel delivery for optimal vehicle routing strategies, Transport Systems, 4, pp. 253-261, (2018); Poikonen S., Wang X., Golden B., The vehicle routing problem with drones: Extended models and connections, Networks, 70, 1, pp. 34-43, (2017); Chu Y.-C., Wang X.-T., Zhang N., Rural e-commerce logistics transportation path planning of truck combined with UAV, Logistics Technology, 9, pp. 82-88, (2020); Han M., Wang Y.-B., Ding L.-Y., Vehicle +UAV distribution path optimization based on CTDEA algorithm, Journal of Weapon Equipment Engineering, 11, pp. 149-154, (2019); Garey M.R., Johnson D.S., Computers and Intractability: A Guide to the Theory of NP-Completeness, (1979); William H.A., George T.S., Ho B., Ping J.B., Henry C.W., A hybrid genetic algorithm for the multi-depot vehicle routing problem, Engineering Applications of Artificial Intelligence, 21, pp. 548-557, (2008); Shim J.Y., A vehicle routing problem solved by using a hybrid genetic algorithm, Computers & Industrial Engineering, 53, pp. 2959-2986, (2007); Tarantilis C.D., Kiranoudis C.T., Vassiliadis V.S., A threshold accepting metaheuristic for the heterogeneous fixed fleet vehicle routing problem, European Journal of Operational Research, 152, 1, pp. 148-158, (2004); Osman I.H., Metastrategy simulated annealing and tabu search algorithms for the vehicle routing problem, Annals of Operations Research, 41, 4, pp. 421-451, (1993); Li Y., Fan H.-M., Zhang X.-N., Periodic optimization model and solution of vehicle routing problem under dynamic demand, Chinese Journal of Management Science, 10, pp. 1-23, (2021); Pei X.-B., Yu X.-Y., Research on Perishable Product distribution Problem based on improved artificial bee colony algorithm, Journal of Lanzhou University (Natural Sciences), 2, pp. 261-266, (2019); Li L., Liu S.-X., Tang J.-F., Improved ant colony algorithm for solving vehicle routing problem with time windows, Control and Decision, 25, pp. 1379-1383, (2010); Fu Z.-H., Liu C.-S., Research on the opentime-dependent vehicle routing problem of fresh food e-commerce distribution, Computer Engineering and Applications, 20, pp. 1-12, (2021); Hu Z.-A., Jia Y.-Z., Li B.-W., Study on vehicle routing optimization considering customer satisfaction, Industrial Engineering, 1, pp. 100-107, (2019); Hou Y.-C., Bai Y.-P., Hu H.-P., Multi objective fresh food distribution path optimization based on elite ant colony algorithm, Practice and Understanding of Mathematics, 20, pp. 50-57, (2018); Ren T., Chen Y., Xiang Y.-C., Low carbon cold chain vehicle routing optimization considering customer satisfaction, Computer Integrated Manufacturing System, 4, pp. 1108-1117, (2020); Dorigo M., Maniezzo V., Colorni A., Ant system: Optimization by a colony of cooperating agents, Ieee Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 26, 1, pp. 29-41, (1996); Karaboga D., Basturk B., A powerful and efficient algorithm for numerical function optimization: Artificial bee colony (ABC) algorithm, Journal of Global Optimization, 39, 3, pp. 459-471, (2007); Li S.D., You X.M., Liu S., Double ant colony algorithm based on ABC algorithm, Computer Engineering and Application, 12, pp. 37-46, (2020); Yu B., Yang Z.-Z., Xie J.-X., A parallel improved ant colony optimization for multi-depot vehicle routing problem, Journal of the Operational Research Society, 62, 1, pp. 183-188, (2011)","X. Ren; School of Management Engineering and Business, Hebei University of Engineering, Handan, 056038, China; email: xiangyangren@hebeu.edu.cn",null,"Hindawi Limited",{"$nulls":5},"1024123X",null,null,null,"English","Math. Probl. Eng.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85120529457"]
["Dalal A.; Chattopadhyay S.","Dalal, Arunava (57226151526); Chattopadhyay, Subrata (57223365463)","57226151526; 57223365463","Introspecting e-commerce platform for arts and crafts of Bengal",2021.0,"Indian Journal of Ecology",48.0,null,null,73.0,79.0,6.0,0.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85113775466&partnerID=40&md5=468ce8df26642d6bbc3cfae7f4ab1516","University of Engineering and Management University Area, Kolkata, 700 160, India","Dalal A., University of Engineering and Management University Area, Kolkata, 700 160, India; Chattopadhyay S., University of Engineering and Management University Area, Kolkata, 700 160, India","Arts and crafts form an inevitable lineage of culture and tradition. The artisans and craftsmen of West Bengal, an eastern state of India, are highly skilled and their finesse of artwork is adored all over the world. This is envisaged by the huge demand for their creation in the Trade Fairs nationally and internationally. However, there is no comprehensive e-commerce platform that can provide an online marketplace and promote their artistry to the world in a digital environment. Hence the need for a sustainable marketplace for these artisans belonging to the weaker socio-economic strata of the society. The paper explores the feasibility of the same, the opportunities and challenges therein, the demand perspective, logistics, pricing, and promotion parameters. It tries to formulate a viable logistics model and tries to explore the business channels which can result in a seamless connection of the skilled yet unprivileged and unrepresented to those who have a good admiration and fascination for their creation. The study strives to find out the aggregator model which would be apt for putting the brilliant creations on the global platform. © 2021 Ecological Society of India. All rights reserved.","Bottom of the pyramid; E-Commerce; Online market Place; Sustainable marketing",{"$nulls":7},"Banik S, A study on financial analysis of rural artisans in India: Issues and challenges, International Journal of Creative Research Thoughts (IJCRT), 5, 4, pp. 2294-2298, (2017); Corbin J, Strauss A, Basics of qualitative research, (2008); Dhar PP, Indian Art History: Changing Perspectives, (2011); Flick U, An introduction to qualitative research, (2014); Hsieh HF, Shannon SE, Three approaches to qualitative content analysis, Qualitative Health Research, 15, 9, pp. 1277-1288, (2005); Jena PK, Orissan Handicrafts in the age of globalization: Challengesandopportunities, OrissaReview, 64, 4, (2007); Khan AH, Arya D, People perceptions of climate change and its Impacts on phyto-diversity and livelihood of the inhabitants of Almora Kumaun Himalaya, Uttarakhand (India), Indian Journal of Ecology, 44, 4, pp. 735-740, (2017); Crafting culture: The importance of craftsmanship for the world of the arts and the economy at large; Kumari G, Srivasatava AR, Role of e-tailing in boostong the Indian handicraft, International Journal of Marketing & Financial Management, 4, 4, pp. 27-36, (2016); Manias E, McNamara T, Standard setting in specific-purpose language testing: What can a qualitative study add?, Language Testing, 33, 2, pp. 235-249, (2016); Pathak R, Sharma M, Sujatha R, RC2@ Craftsvilla. Com craftsvilla is revolutionizing through co-creation: Creating value for stakeholders, Journal of Business and Retail Management Research, 12, 1, (2017); Richardson A J, Paradigms, theory and management accounting practice: A comment on Parker (forthcoming) “Qualitative management accounting research: Assessing deliverables and relevance, Critical Perspectives on Accounting, 23, 1, pp. 83-88, (2012); India's handicrafts exports from FY 2011 to FY 2019, (2019); Tiwari A, Dutta B, Indian Handicrafts Industry: Evaluating Inclusivity of Current Business Models, (2013); Tsushima R, Methodological diversity in language assessment research: The role of mixed methods in classroom-based language assessment studies, International Journal of Qualitative Methods, 14, 2, pp. 104-121, (2015); Venkataramanaiah S, Kumar NG, Building competitiveness: A case of handicrafts manufacturing cluster units, Indore Management Journal, 3, 2, pp. 27-37, (2011); Working group report on handicrafts for 12th five year plan, (2011)","A. Dalal; University of Engineering and Management University Area, Kolkata, 700 160, India; email: arunava.dalal@gmail.com",null,"Ecological Society of India",{"$nulls":5},3045250.0,null,null,null,"English","Indian J. Ecol.","Article","Final",null,"Scopus","2-s2.0-85113775466"]
["Liu J.; Liew S.-Y.; Ooi B.Y.; Qin D.","Liu, Jialei (57221054603); Liew, Soung-Yue (7102903278); Ooi, Boon Yaik (24366995700); Qin, Donghong (50262744900)","57221054603; 7102903278; 24366995700; 50262744900","Dynamic Order-Based Scheduling Algorithms for Automated Retrieval System in Smart Warehouses",2021.0,"IEEE Access",9.0,null,null,158340.0,158352.0,12.0,7.0,"10.1109/ACCESS.2021.3129585","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85120079226&doi=10.1109%2fACCESS.2021.3129585&partnerID=40&md5=ed9dc232ba36121b527b9ee5da61b28b","Faculty of Information and Communication Technology, Universiti Tunku Abdul Rahman, Kampar, 31900, Malaysia; Faculty of Artificial Intelligence, Guangxi University for Nationalities, Nanning, 530000, China","Liu J., Faculty of Information and Communication Technology, Universiti Tunku Abdul Rahman, Kampar, 31900, Malaysia; Liew S.-Y., Faculty of Information and Communication Technology, Universiti Tunku Abdul Rahman, Kampar, 31900, Malaysia; Ooi B.Y., Faculty of Information and Communication Technology, Universiti Tunku Abdul Rahman, Kampar, 31900, Malaysia; Qin D., Faculty of Artificial Intelligence, Guangxi University for Nationalities, Nanning, 530000, China","In typical e-commerce warehouse operations, upon receiving the orders from customers, the purchased items need to be retrieved from shelves and then packaged accordingly for delivery. To automate and speed up the item retrieval process, a Smart Warehouse usually employs a management system, called the Automated Retrieval System (ARS), to control and schedule the retrieval jobs. The working principle of ARS is crucial to the Smart Warehouse because it will have a great impact on the subsequent downstream processes. In short, all the items in a particular order should be considered as an integral part; if one of these items encounters a much larger retrieval delay than others do, then the entire order may experience an unnecessary latency. In the past, the integrality of order has not received much attention for the parallel retrieval process of multiple stackers. To take this into account, this paper proposes using an Order Tag to label all the items that belong to the same order for retrieval job scheduling. The way of calculating the Order Tags will then determine the scheduling discipline of the ARS. With the objectives of minimizing the average delay and ensuring the fairness, two algorithms are proposed. They are named as Dynamic Order-Based (DOB) and Dynamic Order-Based with Threshold (DOBT) Scheduling Algorithms, respectively. Compared with the First-Come-First-Serve and other approaches, the simulation results show that DOB and DOBT are able to reduce the average order retrieval delay by at least 30%, and generate less backlog pressure to the downstream operations. © 2013 IEEE.","Algorithm design and analysis; Automated retrieval system; Job scheduling; Order integrality; Warehouse automation","Automation; Heuristic algorithms; Job shop scheduling; Scheduling algorithms; Warehouses; Algorithm design and analysis; Automated retrieval system; Delay; Heuristics algorithm; Jobs scheduling; License; Order integrality; Retrieval systems; Sequential analysis; Warehouse automation; Information retrieval",{"$nulls":4},"UTAR Research Fund; Universiti Tunku Abdul Rahman, UTAR, (IPSR/RMC/UTARRF/2019-C2/L05); Natural Science Foundation of Guangxi Province, (2018GXNSFAA281269)","This work was supported in part by the UTAR Research Fund through the Universiti Tunku Abdul Rahman, Malaysia, under Grant IPSR/RMC/UTARRF/2019-C2/L05; and in part by the Natural Science Foundation of Guangxi Province, China, under Grant 2018GXNSFAA281269.","Boysen N., De Koster R., Weidinger F., Warehousing in the ecommerce era: A survey, Eur. J. Oper. Res., 277, 2, pp. 396-411, (2019); Yu Y., Wang X., Zhong R.Y., Huang G.Q., E-commerce logistics in supply chain management: Practice perspective, Proc. CIRP, 52, pp. 179-185, (2016); Larsson A.D.T., Selection of Automated Order Picking Systems, (2016); Aggarwal V., Chen Y.-F.R., Lan T., Xiang Y., Sprout: A functional caching approach to minimize service latency in erasure-coded storage, IEEE/ACM Trans. Netw., 25, 6, pp. 3683-3694, (2017); Culler D., Long J., A prototype smart materials warehouse application implemented using custom mobile robots and open source vision technology developed using EmguCV, Proc. Manuf., 5, pp. 1092-1106, (2016); Lemon K.N., Verhoef P.C., Understanding customer experience throughout the customer journey, J. Marketing, 80, 6, pp. 69-96, (2016); He Z., Aggarwal V., Nof S.Y., Differentiated service policy in smart warehouse automation, Int. J. Prod. Res., 56, 22, pp. 6956-6970, (2018); De Koster R.B., Johnson A.L., Roy D., Warehouse design and management, Int. J. Prod. Res., 55, 21, pp. 6327-6330, (2017); Zhang H., Guo Z., Zhang W., Cai H., Wang C., Yu Y., Li W., Wang J., Layout design for intelligent warehouse by evolution with fitness approximation, IEEE Access, 7, pp. 166310-166317, (2019); Tejesh B.S.S., Neeraja S., Warehouse inventory management system using IoT and open source framework, Alexandria Eng. J., 57, 4, pp. 3817-3823, (2018); Gilya-Zetinov A., Demianova D., Khelvas A., Palletizing for fullautomated warehouses on the genetics algorithm base, Proc. Int. Conf. Eng. Telecommun. (EnT), pp. 1-5, (2019); Jiang X., Zhao D., Xu H., Analysis and reconstruction of pharmaceutical warehouse logistics delivery system, Proc. IEEE Int. Conf. Smart Manuf., Ind. Logistics Eng. (SMILE), pp. 226-229, (2019); Sun X., Ma Z., Wang Z., Ai C., The development of stereoscopic warehouse stacker control system based on motion controller, Proc. MATEC Web Conf., 139, pp. 38-43, (2017); Li S., Qin N., Huang D., Huang D., Ke L., Damage localization of stacker's track based on EEMD-EMD and DBSCAN cluster algorithms, IEEE Trans. Instrum. Meas., 69, 5, pp. 1981-1992, (2020); Rams H., Schoberl M., Schlacher K., Optimal motion planning and energy-based control of a single mast stacker crane, IEEE Trans. Control Syst. Technol., 26, 4, pp. 1449-1457, (2018); Kung Y., Kobayashi Y., Higashi T., Sugi M., Ota J., Order scheduling of multiple stacker cranes on common rails in an automated storage/ retrieval system, Int. J. Prod. Res., 52, 4, pp. 1171-1187, (2014); Khojasteh Y., Son J.-D., A travel time model for order picking systems in automated warehouses, Int. J. Adv. Manuf. Technol., 86, 5-8, pp. 2219-2229, (2016); Yang X., Xu Z., Jin W., Shu F., Optimization of automatic stacker picking sequence under the mixed picking strategy, Comput. Integr. Manuf. Syst., 27, 3, pp. 933-942, (2021); Pang K.W., Chan H.L., Data mining-based algorithm for storage location assignment in a randomisedwarehouse, Int. J. Prod. Res., 55, 14, pp. 4035-4052, (2017); Wang Y., Mou S., Wu Y., Task scheduling for multi-tier shuttle warehousing systems, Int. J. Prod. Res., 53, 19, pp. 5884-5895, (2015); Kong X.T.R., Yang X., Peng K.L., Li C.Z., Cyber physical systemenabled synchronization mechanism for pick-and-sort ecommerce order fulfilment, Comput. Ind., 118, (2020); Hu H., Li L., Lv Z., A novel hybrid algorithm for order picking optimization in automated warehouse, Proc. 37th Chin. Control Conf. (CCC), pp. 3216-3220, (2018); Nastasi G., Colla V., Cateni S., Campigli S., Implementation and comparison of algorithms for multi-objective optimization based on genetic algorithms applied to the management of an automated warehouse, J. Intell. Manuf., 29, pp. 1545-1557, (2016); Yang X.M., Xu Z.Q., Jin W., Shu F., The optimization problem of stacker operation sequence under compound picking strategy, Comput. Integr. Manuf. Syst., 27, pp. 933-942, (2021); Liu K., Niu J., Shen Y., Li S., Stacker job path optimization based on genetic particle swarm, J. Shijiazhuang Tiedao Univ. (Natural Sci. Ed.), 29, 2, pp. 67-71, (2016); Wencan L., Xuli H., Yanggao X., Yu L., Research on strategies and algorithms for intelligent scheduling of tobacco industry stackers, Proc. 4th Int. Conf. Electron Device Mech. Eng. (ICEDME), pp. 279-286, (2021); Yu X., Liao X., Li W., Liu X., Tao Z., Logistics automation control based on machine learning algorithm, Cluster Comput., 22, S6, pp. 14003-14011, (2019); Chen F., Wei Y., Wang H., A heuristic based batching and assigning method for online customer orders, Flexible Services Manuf. J., 30, 4, pp. 640-685, (2018); Zhang J., Wang X., Huang K., Integrated on-line scheduling of order batching and delivery under B2C e-commerce, Comput. Ind. Eng., 94, pp. 280-289, (2016); Nagendra Guptha C.K., Bhaskar M.G., Meghasree V., Design of IoT architecture for order picking in a typical warehouse, Proc. 3rd Int. Conf. Comput. Syst. Inf. Technol. Sustain. Solutions (CSITSS), pp. 50-53, (2018); Guo J., Jiang Z., Chu Y., Geng N., Study of scheduling of parallel multitask picking based on limited working area, Ind. Eng. Manage., 17, 3, pp. 102-107, (2012); Liu J., Liew S.-Y., Ooi B.Y., Qin D., Efficient order-based scheduling algorithms for automated retrieval system (ARS) in smart warehouses, Proc. 20th Int. Conf. Control, Autom. Syst. (ICCAS), pp. 839-844, (2020); Yoshitake H., Kamoshida R., Nagashima Y., New automated guided vehicle system using real-time holonic scheduling for warehouse picking, IEEE Robot. Autom. Lett., 4, 2, pp. 1045-1052, (2019); Tang H., Cheng X., Jiang W., Chen S., Research on equipment configuration optimization of AGV unmanned warehouse, IEEE Access, 9, pp. 47946-47959, (2021); Zhang Z., Guo Q., Chen J., Yuan P., Collision-free route planning for multiple AGVs in an automated warehouse based on collision classification, IEEE Access, 6, pp. 26022-26035, (2018); Guo K., Zhu J., Shen L., An improved acceleration method based on multi-agent system for AGVs conict-free path planning in automated terminals, IEEE Access, 9, pp. 3326-3338, (2021); Liu S., Research on scheduling policy of automated warehouse system, Proc. 2nd Int. Conf. Comput. Sci. Appl. Eng. (CSAE), pp. 1-5, (2018); Sun B., Zhang X., Qiao H., Li G., Chen Y., Multi-type resources collaborative scheduling in automated warehouse with fuzzy processing time, J. Intell. Fuzzy Syst., 39, 1, pp. 899-910, (2020)","S.-Y. Liew; Faculty of Information and Communication Technology, Universiti Tunku Abdul Rahman, Kampar, 31900, Malaysia; email: syliew@utar.edu.my",null,"Institute of Electrical and Electronics Engineers Inc.",{"$nulls":5},2.1693536E7,null,null,null,"English","IEEE Access","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85120079226"]
["Emde S.; Tahirov N.; Gendreau M.; Glock C.H.","Emde, Simon (35810166700); Tahirov, Nail (57160299400); Gendreau, Michel (7005646783); Glock, Christoph H. (26867716500)","35810166700; 57160299400; 7005646783; 26867716500","Routing automated lane-guided transport vehicles in a warehouse handling returns",2021.0,"European Journal of Operational Research",292.0,3.0,null,1085.0,1098.0,13.0,3.0,"10.1016/j.ejor.2020.11.038","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85097803030&doi=10.1016%2fj.ejor.2020.11.038&partnerID=40&md5=68a047099d9dc51ab72cb9a5eb298be0","CORAL - Cluster for Operations Research, Analytics, and Logistics, Department of Economics and Business Economics, Aarhus University, Fuglesangs Allé 4, Aarhus, V DK-8210, Denmark; Institute of Production and Supply Chain Management, Technische Universität Darmstadt, Hochschulstraße 1, Darmstadt, 64289, Germany; CIRRELT and Département de Mathématiques et de Génie Industriel, École Polytechnique de Montréal, Montreal, H3C 3A7, Canada","Emde S., CORAL - Cluster for Operations Research, Analytics, and Logistics, Department of Economics and Business Economics, Aarhus University, Fuglesangs Allé 4, Aarhus, V DK-8210, Denmark; Tahirov N., Institute of Production and Supply Chain Management, Technische Universität Darmstadt, Hochschulstraße 1, Darmstadt, 64289, Germany; Gendreau M., CIRRELT and Département de Mathématiques et de Génie Industriel, École Polytechnique de Montréal, Montreal, H3C 3A7, Canada; Glock C.H., Institute of Production and Supply Chain Management, Technische Universität Darmstadt, Hochschulstraße 1, Darmstadt, 64289, Germany","Faced with high return rates, many e-commerce retailers are considering novel technical solutions to expedite the processing of returned items in their warehouses. One such solution consists of lane-guided transport (LGT) vehicles. These small, electric vehicles follow optical markers on the floor, picking up boxes of returned items at a depot and dropping them off at workstations, releasing the logistics workers to focus on the productive task of actually processing the items instead of carrying them through the warehouse. These types of systems are simple to set up from a technical perspective; however, the routes on the warehouse floor still need to be carefully planned. This gives rise to the following routing problem. Given a set of stations to be served from multiple depots by a fleet of LGT vehicles, which stations doing what type of work should be visited on what route? Only one route per depot is allowed, but multiple vehicles may use the same route. Moreover, since routes cannot be changed on short notice, we consider an infinite planning horizon where the demand rate of the stations depends on the type of work they are assigned to do (e.g., handling defective items or refurbishing). We develop a decomposition heuristic, which solves instances derived from industry data to near-optimality in less than a minute. We also show that the depot location is rather unimportant for the overall system performance, but that the depot count can have a significant influence. © 2020 Elsevier B.V.","Mobile robots; Returns handling; Routing; Warehousing","Automatic guided vehicles; Floors; Warehouses; Defective items; Infinite planning horizons; Near optimality; Optical markers; Routing problems; Technical solutions; Transport vehicles; Warehouse floor; Fleet operations",{"$nulls":6},"Asef-Vaziri A., Laporte G., Loop based facility planning and material handling, European Journal of Operational Research, 164, 1, pp. 1-11, (2005); Azadeh K., De Koster R., Roy D., Robotized and automated warehouse systems: Review and recent developments, Transportation Science, 53, 4, pp. 917-945, (2019); Bektas T., The multiple traveling salesman problem: an overview of formulations and solution procedures, Omega, 34, 3, pp. 209-219, (2006); Boysen N., de Koster R., Weidinger F., Warehousing in the e-commerce era: A survey, European Journal of Operational Research, 277, 2, pp. 396-411, (2019); De Brito M.P., De Koster M., Product and material returns: handling and warehousing issues, Reverse logistics, pp. 135-153, (2004); De Brito M.P., De Koster M., van de Vendel M.A., Return handling: an exploratory study with nine retailer warehouses, International Journal of Retail & Distribution Management, 30, 8, pp. 407-421, (2002); De Koster R., Le-Duc T., Roodbergen K.J., Design and control of warehouse order picking: A literature review, European Journal of Operational Research, 182, 2, pp. 481-501, (2007); Dennis S., The ticking time bomb of e-commerce returns, Forbes, (2018); Emde S., Schneider M., Just-in-time vehicle routing for in-house part feeding to assembly lines, Transportation Science, 52, 3, pp. 657-672, (2018); Fazlollahtabar H., Saidi-Mehrabad M., Methodologies to optimize automated guided vehicle scheduling and routing problems: a review study, Journal of Intelligent & Robotic Systems, 77, 3-4, pp. 525-545, (2015); Ferrara A., Gebennini E., Grassi A., Fleet sizing of laser guided vehicles and pallet shuttles in automated warehouses, International Journal of Production Economics, 157, pp. 7-14, (2014); Garey M.R., Johnson D.S., Computers and intractability: a guide to NP-completeness, (1979); Glover F., Tabu searchpart I, ORSA Journal on computing, 1, 3, pp. 190-206, (1989); Glover F., Tabu searchpart ii, ORSA Journal on Computing, 2, 1, pp. 4-32, (1990); Gu J., Goetschalckx M., McGinnis L.F., Research on warehouse design and performance evaluation: A comprehensive review, European Journal of Operational Research, 203, 3, pp. 539-549, (2010); Helsgaun K., An effective implementation of the Lin–Kernighan traveling salesman heuristic, European Journal of Operational Research, 126, 1, pp. 106-130, (2000); Helsgaun K., General k-opt submoves for the Lin–Kernighan tsp heuristic, Mathematical Programming Computation, 1, 2-3, pp. 119-163, (2009); Helsgaun K., An extension of the Lin-Kernighan-Helsgaun tsp solver for constrained traveling salesman and vehicle routing problems, Roskilde: Roskilde University, (2017); Jeon S.M., Kim K.H., Kopfer H., Routing automated guided vehicles in container terminals through the q-learning technique, Logistics Research, 3, 1, pp. 19-27, (2011); Lin S., Kernighan B.W., An effective heuristic algorithm for the traveling-salesman problem, Operations research, 21, 2, pp. 498-516, (1973); Miyamoto T., Inoue K., Local and random searches for dispatch and conflict-free routing problem of capacitated agv systems, Computers & Industrial Engineering, 91, pp. 1-9, (2016); Petersen C.G., Aase G., A comparison of picking, storage, and routing policies in manual order picking, International Journal of Production Economics, 92, 1, pp. 11-19, (2004); Qiu L., Hsu W.-J., Huang S.-Y., Wang H., Scheduling and routing algorithms for agvs: a survey, International Journal of Production Research, 40, 3, pp. 745-760, (2002); Raa B., Fleet optimization for cyclic inventory routing problems, International Journal of Production Economics, 160, pp. 172-181, (2015); Raa B., Dullaert W., Route and fleet design for cyclic inventory routing, European Journal of Operational Research, 256, 2, pp. 404-411, (2017); Schrijver A., Combinatorial optimization: polyhedra and efficiency, (2003); Schrotenboer A.H., Wruck S., Roodbergen K.J., Veenstra M., Dijkstra A.S., Order picker routing with product returns and interaction delays, International Journal of Production Research, 55, 21, pp. 6394-6406, (2017); Schrotenboer A.H., Wruck S., Vis I.F., Roodbergen K., (2019); Taillard E.D., Helsgaun K., Popmusic for the travelling salesman problem, European Journal of Operational Research, 272, 2, pp. 420-429, (2019); Toth P., Vigo D., Vehicle routing: problems, methods, and applications, (2014); Trottmann M., Zhang S., The trend towards warehouse automation, White paper, (2017); Umar U.A., Ariffin M., Ismail N., Tang S., Hybrid multiobjective genetic algorithms for integrated dynamic scheduling and routing of jobs and automated-guided vehicle (agv) in flexible manufacturing systems (fms) environment, The International Journal of Advanced Manufacturing Technology, 81, 9-12, pp. 2123-2141, (2015); Vaidyanathan B.S., Matson J.O., Miller D.M., Matson J.E., A capacitated vehicle routing problem for just-in-time delivery, IIE Transactions, 31, 11, pp. 1083-1092, (1999); Van Den Berg J.P., A literature survey on planning and control of warehousing systems, IIE Transactions, 31, 8, pp. 751-762, (1999); Vis I.F., Survey of research in the design and control of automated guided vehicle systems, European Journal of Operational Research, 170, 3, pp. 677-709, (2006); Vivaldini K., Rocha L.F., Martarelli N.J., Becker M., Moreira A.P., Integrated tasks assignment and routing for the estimation of the optimal number of agvs, The International Journal of Advanced Manufacturing Technology, 82, 1-4, pp. 719-736, (2016); Vivaldini K.C., Rocha L.F., Becker M., Moreira A.P., Comprehensive review of the dispatching, scheduling and routing of agvs, Controlo014–Proceedings of the 11th portuguese conference on automatic control, pp. 505-514, (2015); Wruck S., Vis I.F., Boter J., Time-restricted batching models and solution approaches for integrated forward and return product flow handling in warehouses, Journal of the Operational Research Society, 64, 10, pp. 1505-1516, (2013); Zenker M., Emde S., Boysen N., Cyclic inventory routing in a line-shaped network, European Journal of Operational Research, 250, 1, pp. 164-178, (2016)","S. Emde; CORAL - Cluster for Operations Research, Analytics, and Logistics, Department of Economics and Business Economics, Aarhus University, Aarhus, Fuglesangs Allé 4, V DK-8210, Denmark; email: siem@econ.au.dk",null,"Elsevier B.V.",{"$nulls":5},3772217.0,null,"EJORD",null,"English","Eur J Oper Res","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85097803030"]
["Li L.; He X.; Keoleian G.A.; Kim H.C.; De Kleine R.; Wallington T.J.; Kemp N.J.","Li, Luyao (57234968600); He, Xiaoyi (57190579582); Keoleian, Gregory A. (7004102663); Kim, Hyung Chul (55739549800); De Kleine, Robert (38761199500); Wallington, Timothy J. (7102358724); Kemp, Nicholas J. (57225456923)","57234968600; 57190579582; 7004102663; 55739549800; 38761199500; 7102358724; 57225456923","Life Cycle Greenhouse Gas Emissions for Last-Mile Parcel Delivery by Automated Vehicles and Robots",2021.0,"Environmental Science and Technology",55.0,16.0,null,11360.0,11367.0,7.0,14.0,"10.1021/acs.est.0c08213","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85113639761&doi=10.1021%2facs.est.0c08213&partnerID=40&md5=0c2ac75660c84a0cc0a29cc3e7d55d29","Center for Sustainable Systems, School for Environment and Sustainability, University of Michigan, 440 Church Street, Ann Arbor, 48109, MI, United States; Research and Innovation Center, Ford Motor Company, Dearborn, 48121, MI, United States","Li L., Center for Sustainable Systems, School for Environment and Sustainability, University of Michigan, 440 Church Street, Ann Arbor, 48109, MI, United States; He X., Center for Sustainable Systems, School for Environment and Sustainability, University of Michigan, 440 Church Street, Ann Arbor, 48109, MI, United States; Keoleian G.A., Center for Sustainable Systems, School for Environment and Sustainability, University of Michigan, 440 Church Street, Ann Arbor, 48109, MI, United States; Kim H.C., Research and Innovation Center, Ford Motor Company, Dearborn, 48121, MI, United States; De Kleine R., Research and Innovation Center, Ford Motor Company, Dearborn, 48121, MI, United States; Wallington T.J., Research and Innovation Center, Ford Motor Company, Dearborn, 48121, MI, United States; Kemp N.J., Center for Sustainable Systems, School for Environment and Sustainability, University of Michigan, 440 Church Street, Ann Arbor, 48109, MI, United States","Increased E-commerce and demand for contactless delivery during the COVID-19 pandemic have fueled interest in robotic package delivery. We evaluate life cycle greenhouse gas (GHG) emissions for automated suburban ground delivery systems consisting of a vehicle (last-mile) and a robot (final-50-feet). Small and large cargo vans (125 and 350 cubic feet; V125 and V350) with an internal combustion engine (ICEV) and battery electric (BEV) powertrains were assessed for three delivery scenarios: (i) conventional, human-driven vehicle with human delivery; (ii) partially automated, human-driven vehicle with robot delivery; and (iii) fully automated, connected automated vehicle (CAV) with robot delivery. The robot's contribution to life cycle GHG emissions is small (2-6%). Compared to the conventional scenario, full automation results in similar GHG emissions for the V350-ICEV but 10% higher for the V125-BEV. Conventional delivery with a V125-BEV provides the lowest GHG emissions, 167 g CO2e/package, while partially automated delivery with a V350-ICEV generates the most at 486 g CO2e/package. Fuel economy and delivery density are key parameters, and electrification of the vehicle and carbon intensity of the electricity have a large impact. CAV power requirements and efficiency benefits largely offset each other, and automation has a moderate impact on life cycle GHG emissions.  © 2021 American Chemical Society.","autonomous vehicle; greenhouse gas emissions; last-mile ground delivery; life cycle assessment; robot","Automation; Fuel economy; Gas emissions; Life cycle; Robots; Trucks; fuel; Automated vehicles; Carbon intensity; Delivery systems; Efficiency benefits; Life-cycle GHG emissions; Life-cycle greenhouse gas emissions; Package delivery; Power requirement; emission control; greenhouse gas; life cycle analysis; robotics; traffic emission; Article; automation; carbon footprint; cargo van; combustion; cost control; energy conservation; human; life cycle assessment; model; motor vehicle; parcel delivery; pollution transport; postal mail; robotics; suburban area; Greenhouse gases",{"$nulls":4},"Ford University, (N024420); Ford University of Michigan, (N028450)","This research was supported by the Ford University of Michigan Alliance Program (N028450) and the Ford University Research Program (N024420). The authors wish to thank James Gawron at Ford Motor Company, Grace Hsia at UPS, and Boris Kort-Packard at FedEx for their input. While this article is believed to contain correct information, Ford Motor Company (Ford) does not expressly or impliedly warrant, nor assume any responsibility, for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, nor represent that its use would not infringe the rights of third parties. Reference to any commercial product or process does not constitute its endorsement. This article does not provide financial, safety, medical, consumer product, or public policy advice or recommendation. Readers should independently replicate all experiments, calculations, and results. The views and opinions expressed are of the authors and do not necessarily reflect those of Ford. This disclaimer may not be removed, altered, superseded, or modified without prior Ford permission.","Olsson J., Hellstrom D., Palsson H., Framework of Last Mile Logistics Research: A Systematic Review of the Literature, Sustain., 11, pp. 1-25, (2019); Brown J.R., Guiffrida A.L., Carbon Emissions Comparison of Last Mile Delivery versus Customer Pickup, Int. J. Logist. Res. 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Ai, 5, pp. 1-13, (2018); Smart Mobility Connected and Automated Vehicles Capstone Report; Kim H.C., Wallington T.J., Life Cycle Assessment of Vehicle Lightweighting: A Physics-Based Model to Estimate Use-Phase Fuel Consumption of Electrified Vehicles, Environ. Sci. Technol., 50, pp. 11226-11233, (2016); Jasinski D., Meredith J., Kirwan K., A Comprehensive Framework for Automotive Sustainability Assessment, J. Cleaner Prod., 135, pp. 1034-1044, (2016); Cooney G., Hawkins T.R., Marriott J., Life Cycle Assessment of Diesel and Electric Public Transportation Buses, J. Ind. Ecol., 17, pp. 689-699, (2013); Barkenbus J., Eco-Driving N., An Overlooked Climate Change Initiative, Energy Policy, 38, pp. 762-769, (2010); Orozco J.C., Analysis of Energy Efficiency in Truck-Drone \"last Mile\" Delivery Systems, (2019); Lohn A., What's the Buzz? The City-Scale Impacts of Drone Delivery, (2017)","G.A. Keoleian; Center for Sustainable Systems, School for Environment and Sustainability, University of Michigan, Ann Arbor, 440 Church Street, 48109, United States; email: gregak@umich.ed.u",null,"American Chemical Society",{"$nulls":5},"0013936X",null,"ESTHA",3.4328327E7,"English","Environ. Sci. Technol.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85113639761"]
["Park H.; Son D.; Koo B.; Jeong B.","Park, Hyungbin (57201488261); Son, Dongmin (57197734563); Koo, Bonwoo (7101738301); Jeong, Bongju (7102237921)","57201488261; 57197734563; 7101738301; 7102237921","Waiting strategy for the vehicle routing problem with simultaneous pickup and delivery using genetic algorithm",2021.0,"Expert Systems with Applications",165.0,null,113959.0,null,null,null,67.0,"10.1016/j.eswa.2020.113959","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85090570843&doi=10.1016%2fj.eswa.2020.113959&partnerID=40&md5=9144bed36a5e83bb8868bdd533a8f769","Department of Industrial Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, South Korea; Department of Management Sciences, University of Waterloo, 200 University Avenue W, Waterloo, N2L 3G1, ON, Canada","Park H., Department of Industrial Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, South Korea; Son D., Department of Industrial Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, South Korea; Koo B., Department of Management Sciences, University of Waterloo, 200 University Avenue W, Waterloo, N2L 3G1, ON, Canada; Jeong B., Department of Industrial Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, South Korea","With the development of information and telecommunication technology and the wide adoption of smartphones, consumers gradually change their purchase pattern toward online shopping. They can order products from their smartphones at any moment from any place, and the volume and variety of products delivered to consumers are increasing explosively. Companies in this industry need to set up the operational strategies to accommodate the increasing demand for delivery and return of products, and their focus should be the real-world vehicle routing problems with an additional consideration of the dynamic orders placed over time. This study proposes a waiting strategy for the vehicle routing problem with simultaneous pickup and delivery. This strategy implements an index called the rerouting indicator, which functions as a decision-making threshold to determine the rerouting point for real-time demands. For the most real-world-cases with complex problems, this study proposes a genetic algorithm to solve and validate its accuracy and performance by comparing the computational results. The significance and application of the waiting strategy are validated through several experiments, and the appropriate discretion by a decision maker can demonstrate the value of the proposed strategy. © 2020 Elsevier Ltd","Genetic algorithm; Rerouting indicator; Vehicle routing problem with simultaneous pickup and delivery; Waiting strategy","Decision making; Pickups; Routing algorithms; Smartphones; Vehicle routing; Vehicles; Complex problems; Computational results; Online shopping; Operational strategies; Simultaneous pickup and deliveries; Telecommunication technologies; Vehicle Routing Problems; Waiting strategy; Genetic algorithms",{"$nulls":4},"Ministry of Science, ICT and Future Planning, MSIP, (NRF-2019R1F1A1061349); National Research Foundation of Korea, NRF","This work was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (NRF-2019R1F1A1061349).","Ai T.J., Kachitvichyanukul V., A particle swarm optimization for the vehicle routing problem with simultaneous pickup and delivery, Computers & Operations Research, 36, 5, pp. 1693-1702, (2009); Al Chami Z., Manier H., Manier M.A., Fitouri C., A hybrid genetic algorithm to solve a multi-objective pickup and delivery problem, IFAC-PapersOnLine, 50, 1, pp. 14656-14661, (2017); Anbuudayasankar S.P., Ganesh K., Koh S.L., Ducq Y., Modified savings heuristics and genetic algorithm for bi-objective vehicle routing problem with forced backhauls, Expert Systems with Applications, 39, 3, pp. 2296-2305, (2012); Avci M., Topaloglu S., A hybrid metaheuristic algorithm for heterogeneous vehicle routing problem with simultaneous pickup and delivery, Expert Systems with Applications, 53, pp. 160-171, (2016); Barbucha D., Influence of the waiting strategy on the performance of the multi-agent approach to the DVRPTW, pp. 464-473, (2016); Barma P.S., Dutta J., Mukherjee A., A 2-opt guided discrete antlion optimization algorithm for multi-depot vehicle routing problem, Decision Making: Applications in Management and Engineering, 2, 2, pp. 112-125, (2019); Belgin O., Karaoglan I., Altiparmak F., Two-echelon vehicle routing problem with simultaneous pickup and delivery: Mathematical model and heuristic approach, Computers & Industrial Engineering, 115, pp. 1-16, (2018); Bevan L., (2019); Biswas P., Pal B.B., A fuzzy goal programming method to solve congestion management problem using genetic algorithm, Decision Making: Applications in Management and Engineering, 2, 2, pp. 36-53, (2019); Branke J., Middendorf M., Noeth G., Dessouky M., Waiting strategies for dynamic vehicle routing, Transportation Science, 39, 3, pp. 298-312, (2005); Catay B., A new saving-based ant algorithm for the vehicle routing problem with simultaneous pickup and delivery, Expert Systems with Applications, 37, 10, pp. 6809-6817, (2010); Chen R.M., Shen Y.M., Hong W.Z., Neural-like encoding particle swarm optimization for periodic vehicle routing problems, Expert Systems with Applications, 138, (2019); Cordeau J.F., Gendreau M., Laporte G., Potvin J.Y., Semet F., A guide to vehicle routing heuristics, Journal of the Operational Research society, 53, 5, pp. 512-522, (2002); Dantzig G.B., Ramser J.H., The truck dispatching problem, Management Science, 6, 1, pp. 80-91, (1959); Escuin D., Larrode E., Millan C., A cooperative waiting strategy based on elliptical areas for the Dynamic Pickup and Delivery Problem with Time Windows, Journal of Advanced Transportation, 50, 8, pp. 1577-1597, (2016); Garey M.R., Johnson D.S., Computers and intractability, 29, (2002); Ghiani G., Laporte G., Manni E., Musmanno R., Waiting strategies for the dynamic and stochastic traveling salesman problem, International Journal of Operations Research, 5, 4, pp. 233-241, (2008); Goksal F.P., Karaoglan I., Altiparmak F., A hybrid discrete particle swarm optimization for vehicle routing problem with simultaneous pickup and delivery, Computers & Industrial Engineering, 65, 1, pp. 39-53, (2013); Ho W., Ho G.T., Ji P., Lau H.C., A hybrid genetic algorithm for the multi-depot vehicle routing problem, Engineering Applications of Artificial Intelligence, 21, 4, pp. 548-557, (2008); Kalayci C.B., Kaya C., An ant colony system empowered variable neighborhood search algorithm for the vehicle routing problem with simultaneous pickup and delivery, Expert Systems with Applications, 66, pp. 163-175, (2016); Karami F., Vancroonenburg W., Vanden Berghe G., (2018); Karaoglan I., Altiparmak F., (2010); Liu R., Xie X., Augusto V., Rodriguez C., Heuristic algorithms for a vehicle routing problem with simultaneous delivery and pickup and time windows in home health care, European Journal of Operational Research, 230, 3, pp. 475-486, (2013); Ma Y., Li Z., Yan F., Feng C., A hybrid priority-based genetic algorithm for simultaneous pickup and delivery problems in reverse logistics with time windows and multiple decision-makers, Soft Computing, 23, 15, pp. 6697-6714, (2019); Mahmud N., Haque M.M., Solving multiple depot vehicle routing problem (MDVRP) using genetic algorithm, pp. 1-6, (2019); Mitrovic-Minic S., Laporte G., Waiting strategies for the dynamic pickup and delivery problem with time windows, Transportation Research Part B: Methodological, 38, 7, pp. 635-655, (2004); Park W., (2016); Polat O., Kalayci C.B., Kulak O., Gunther H.O., A perturbation based variable neighborhood search heuristic for solving the vehicle routing problem with simultaneous pickup and delivery with time limit, European Journal of Operational Research, 242, 2, pp. 369-382, (2015); Pureza V., Laporte G., Waiting and buffering strategies for the dynamic pickup and delivery problem with time windows, INFOR: Information Systems and Operational Research, 46, 3, pp. 165-175, (2008); Roy A., Manna A., Maity S., A novel memetic genetic algorithm for solving traveling salesman problem based on multi-parent crossover technique, Decision Making: Applications in Management and Engineering, 2, 2, pp. 100-111, (2019); Shi Y., Boudouh T., Grunder O., A hybrid genetic algorithm for a home health care routing problem with time window and fuzzy demand, Expert Systems with Applications, 72, pp. 160-176, (2017); Subramanian A., Drummond L.M.D.A., Bentes C., Ochi L.S., Farias R., A parallel heuristic for the vehicle routing problem with simultaneous pickup and delivery, Computers & Operations Research, 37, 11, pp. 1899-1911, (2010); Sun B., Yang Y., Shi J., Zheng L., Dynamic pick-up and delivery optimization with multiple dynamic events in real-world environment, IEEE Access, 7, pp. 146209-146220, (2019); Tasan A.S., Gen M., A genetic algorithm based approach to vehicle routing problem with simultaneous pick-up and deliveries, Computers & Industrial Engineering, 62, 3, pp. 755-761, (2012); Velasco N., Dejax P., Gueret C., Prins C., A non-dominated sorting genetic algorithm for a bi-objective pick-up and delivery problem, Engineering Optimization, 44, 3, pp. 305-325, (2012); Wang H.F., Chen Y.Y., A genetic algorithm for the simultaneous delivery and pickup problems with time window, Computers & Industrial Engineering, 62, 1, pp. 84-95, (2012); Zhang Z., Cheang B., Li C., Lim A., Multi-commodity demand fulfillment via simultaneous pickup and delivery for a fast fashion retailer, Computers & Operations Research, 103, pp. 81-96, (2019)","B. Jeong; Department of Industrial Engineering, Yonsei University, Seoul, 50 Yonsei-ro, Seodaemun-gu, 03722, South Korea; email: bongju@yonsei.ac.kr",null,"Elsevier Ltd",{"$nulls":5},9574174.0,null,"ESAPE",null,"English","Expert Sys Appl","Article","Final",null,"Scopus","2-s2.0-85090570843"]
["Li J.; Zhao Z.; Cheng T.","Li, Jiali (37017388800); Zhao, Zhijie (15023782600); Cheng, Tao (57203547768)","37017388800; 15023782600; 57203547768","Research on LRP Integration of E-Commerce Logistics under the Background of Integration of Collection and Distribution",2021.0,"Discrete Dynamics in Nature and Society",2021.0,null,6038947.0,null,null,null,1.0,"10.1155/2021/6038947","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85122177911&doi=10.1155%2f2021%2f6038947&partnerID=40&md5=39386b9d8fd2f36c71ac5ba09f55cb1b","Northeast Asia Service Outsourcing Research Center, Harbin University of Commerce, Heilongjiang, Harbin, 150028, China; College of Economics and Management, Heilongjiang Institute of Technology, Heilongjiang, Harbin, 150050, China","Li J., Northeast Asia Service Outsourcing Research Center, Harbin University of Commerce, Heilongjiang, Harbin, 150028, China, College of Economics and Management, Heilongjiang Institute of Technology, Heilongjiang, Harbin, 150050, China; Zhao Z., Northeast Asia Service Outsourcing Research Center, Harbin University of Commerce, Heilongjiang, Harbin, 150028, China; Cheng T., Northeast Asia Service Outsourcing Research Center, Harbin University of Commerce, Heilongjiang, Harbin, 150028, China","The distribution network composed of location and route is an important part of e-commerce logistics. With the continuous improvement of e-commerce requirements for logistics level, the practice of planning logistics network only from the perspective of the network location or the vehicle route can no longer meet the actual demand. In addition to the comprehensive consideration of the location-routing problem, the reverse logistics caused by customers' returning goods should be taken into account. In this paper, the destruction and reorganization strategy of adaptive large-scale neighborhood search algorithm was introduced into the traditional genetic algorithm, so as to conduct research on the logistics location-routing problem under the background of integration of collection and distribution. Finally, the effectiveness of the optimized genetic algorithm was verified by Matlab tools and the existing bench-marking data set of the location-routing problem, which provided reference for the planning and decision-making of logistics enterprises.  © 2021 Jiali Li et al.",{"$nulls":8},"Sureka G., Mahinda Y., Wickramarachchi D., Factors affecting the efficiency and effectiveness of reverse logistics process, Journal of International Logistics and Trade, 16, 2, pp. 74-87, (2018); Wang H., Tian Q., Li J., Li X., Stochastic frontier analysis of logistics efficiency and its influencing factors in provinces along the \"belt and road, Journal of Highway and Transportation Research and Development, 37, 10, pp. 151-158, (2020); Weber A., Uber Den Standort der Industrien, (1929); Tang Z., Multi-level logistics center location based on harmony search algorithm, Logistics Technology, 38, 11, pp. 89-92, (2019); Xu X., Yang Z., Liu L., SMA for solving the location problem of logistics distribution center, Computer Engineering and Applications, 56, 1, pp. 150-157, (2020); Xiao Z., Zhang X., The location model of cold chain logistics distribution center that meets the JUSDA limitations, Statistics & Decisions, 36, 12, pp. 185-188, (2020); Shu X., Analysis on the location of logistics center based on fuzzy comprehensive evaluation method, Neijiang Science and Technology, 42, 3, pp. 43-44, (2021); Dantzig G.B., Ramser J.H., The truck dispatching problem, Management Science, 6, 1, pp. 80-91, (1959); Xu C., Yu X., Modeling and simulation analysis of optimal choice of transportation route for intelligent transportation platform, Computer Simulation, 36, 3, pp. 175-178, (2019); Ma G., Pan F., Research on logistics transportation route based on improved ant colony algorithm, Computer Engineering and Science, 42, 3, pp. 523-528, (2020); Xia Q., Zhou J., Research on optimization of transportation route based on MATLAB software, Logistics Technology, 43, 10, pp. 97-100, (2020); Pu M., Zhang Y., Optimization method of logistics distribution vehicle route based on improved ant colony algorithm, Journal of Jilin Institute of Chemical Technology, 38, 5, pp. 90-94, (2021); Maranzana F.E., On the location of supply points to minimize transport costs, Journal of the Operational Research Society, 15, 3, pp. 261-270, (1964); Wang S., Zhao Y., Leng L., Zhang C., Jiang H., Low-carbon location-routing problem based on ant colony selection hyper-heuristic algorithm, Computer Integrated Manufacturing Systems, 26, 6, pp. 1702-1716, (2020); Wang C., Zheng Y., Yilong H., Hongtao H., Research on location selection of fresh food logistics distribution network-route optimization, Mathematics in Practice and Knowledge, 50, 10, pp. 33-43, (2020); Guo F., Huang Z., Huang W., Research on delivery vehicle routing problem while considering the location and service strategy of the front warehouse, System Engineering Theory and Practice, 41, 4, pp. 962-978, (2021); Liu D., Zhang H., Zhang L., Simultaneous delivery and pickup location-routing problem and hybrid immune algorithm, Application Research of Computers, 1-7, (2021); Barreto S.S., Analysis and Modeling of Location-routing Problems, (2004); Prins C., Prodhon C., Calvo R.W., Solving the capacitated location-routing problem by a GRASP complemented by a learning process and a path relinking, 4OR, 4, 3, pp. 221-238, (2006)","T. Cheng; Northeast Asia Service Outsourcing Research Center, Harbin University of Commerce, Harbin, Heilongjiang, 150028, China; email: 6885854@qq.com",null,"Hindawi Limited",{"$nulls":5},1.0260226E7,null,null,null,"English","Discrete Dyn. Nat. Soc.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85122177911"]
["Marcucci E.; Gatta V.; Le Pira M.; Chao T.; Li S.","Marcucci, Edoardo (6602255083); Gatta, Valerio (35109007100); Le Pira, Michela (56780165600); Chao, Ting (57220862349); Li, Shengnan (57220864177)","6602255083; 35109007100; 56780165600; 57220862349; 57220864177","Bricks or clicks? Consumer channel choice and its transport and environmental implications for the grocery market in Norway",2021.0,"Cities",110.0,null,103046.0,null,null,null,43.0,"10.1016/j.cities.2020.103046","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85097767075&doi=10.1016%2fj.cities.2020.103046&partnerID=40&md5=6307b4a398d782aab3559dea15eb4064","Molde University College, Molde, Norway; Roma Tre University, Rome, Italy; University of Catania, Italy","Marcucci E., Molde University College, Molde, Norway, Roma Tre University, Rome, Italy; Gatta V., Molde University College, Molde, Norway, Roma Tre University, Rome, Italy; Le Pira M., University of Catania, Italy; Chao T., Molde University College, Molde, Norway; Li S., Molde University College, Molde, Norway","E-grocery is the fastest growing e-commerce segment, while still a niche market. Notwithstanding the channel choice when buying groceries might have relevant transport and environmental implications, little attention is paid to demand analysis. The paper fills this research gap, by using stated preferences to estimate market shares for e-grocery, distinguishing between home deliveries and click&pick, using the in-store option as a reference, and by considering a case study in Norway. It investigates the role of various purchase characteristics (i.e. product price, service cost, lead-time, time window, travel time and product range) when choosing which purchase channel to use. Results suggest that the most important characteristics for consumers are related to price, in particular product price, but there is also significant heterogeneity in preferences within the sample. Scenario simulations allow estimating transport and environmental impacts deriving from channel market share changes. This information can be useful for developing both managerial strategies to increase e-grocery market share and public policy interventions to minimize negative externalities. © 2020 Elsevier Ltd","Channel choice; City logistics; E-commerce; E-groceries; Stated preference","Norway; consumption behavior; electronic commerce; information and communication technology; Internet; market conditions; preference behavior; shopping activity",{"$nulls":4},"Sharing Economy in a Living Lab; Università degli Studi Roma Tre, (0000957); Norges Forskningsråd, (283331)","This work was supported by the Norwegian Research Council project: “Digitalisation and mobility: Smart and sustainable transport in large urban agglomerations (DIGMOB)”, grant # 283331 . This work was also supported by the Roma Tre University research project: SHARELAB – Sharing Economy in a Living Lab, (Research Development Plan: Action 4), # 0000957. 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["Chatterjee S.; Goyal D.; Prakash A.; Sharma J.","Chatterjee, Swagato (57194601412); Goyal, Divesh (57219657202); Prakash, Atul (57219650550); Sharma, Jiwan (57219650835)","57194601412; 57219657202; 57219650550; 57219650835","Exploring healthcare/health-product ecommerce satisfaction: A text mining and machine learning application",2021.0,"Journal of Business Research",131.0,null,null,815.0,825.0,10.0,60.0,"10.1016/j.jbusres.2020.10.043","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85094580555&doi=10.1016%2fj.jbusres.2020.10.043&partnerID=40&md5=1d01aa505731f096e8401e6e5e5a6d13","Vinod Gupta School of Management, Indian Institute of Technology, Kharagpur, Kharagpur, 721302, West Bengal, India; Indian Institute of Technology, Kharagpur, Kharagpur, 721302, West Bengal, India","Chatterjee S., Vinod Gupta School of Management, Indian Institute of Technology, Kharagpur, Kharagpur, 721302, West Bengal, India; Goyal D., Indian Institute of Technology, Kharagpur, Kharagpur, 721302, West Bengal, India; Prakash A., Indian Institute of Technology, Kharagpur, Kharagpur, 721302, West Bengal, India; Sharma J., Indian Institute of Technology, Kharagpur, Kharagpur, 721302, West Bengal, India","In the digital era, online channels have become an inevitable part of healthcare services making healthcare/health-product e-commerce an important area of study. However, the reflections of customer-satisfaction and their difference in various subgroups of this industry is still unexplored. Additionally, extant literature has majorly focused on consumer surveys for customer-satisfaction research ignoring the huge data available online. The current study fills these gaps. With 186,057 reviews on 619 e-commerce firms from 29 subcategories of healthcare/health-product industry posted in a review-website between 2008 and 2018, we used text-mining, machine-learning and econometric techniques to find which core and augmented service aspects and which emotions are more important in which service contexts in terms of reflecting and predicting customer satisfaction. Our study contributes towards the healthcare/health-product marketing and services literature in suggesting an automated and machine-learning-based methodology for insight generation. It also helps healthcare/health-product e-commerce managers in better e-commerce service design and delivery. © 2020 Elsevier Inc.","Customer satisfaction; Emotion; Health-product ecommerce; Online reviews; Sentiment; Text mining",{"$nulls":7},"Ahani A., Nilashi M., Yadegaridehkordi E., Sanzogni L., Tarik A.R., Knox K., Ibrahim O., Revealing customers' satisfaction and preferences through online review analysis: The case of Canary Islands hotels, Journal of Retailing & Consumer Services, 51, pp. 331-343, (2019); Ajorlou A., Jadbabaie A., Kakhbod A., Dynamic pricing in social networks: The word-of-mouth effect, Management Science, 64, 2, pp. 971-979, (2016); Anderson E.W., Fornell C., Lehmann D.R., Customer satisfaction, market share, and profitability: Findings from Sweden, The Journal of marketing, 53-66, (1994); Anderson E.W., Sullivan M.W., The antecedents and consequences of customer satisfaction for firms, Marketing Science, 12, 2, pp. 125-143, (1993); Asghar M.Z., Khan A., Ahmad S., Kundi F.M., A review of feature extraction in sentiment analysis, Journal of Basic and Applied Scientific Research, 4, 3, pp. 181-186, (2014); 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You Y., Bhatnagar A., Ghose S., Customer satisfaction with E-Retailers: The role of product type in the relative importance of attributes, Journal of Internet Commerce, 15, 3, pp. 274-291, (2016); Zeithaml V.A., Parasuraman A., Malhotra A., Service quality delivery through web sites: A critical review of extant knowledge, Journal of the Academy of Marketing Science, 30, Fall, pp. 362-375, (2002)","S. Chatterjee; Vinod Gupta School of Management, Indian Institute of Technology, Kharagpur, Kharagpur, 721302, India; email: swagato@vgsom.iitkgp.ac.in",null,"Elsevier Inc.",{"$nulls":5},1482963.0,null,"JBRED",null,"English","J. Bus. Res.","Article","Final",null,"Scopus","2-s2.0-85094580555"]
["Phiboonbanakit T.; Horanont T.; Huynh V.-N.; Supnithi T.","Phiboonbanakit, Thananut (57189692820); Horanont, Teerayut (36598530800); Huynh, Van-Nam (7003274638); Supnithi, Thepchai (25032210400)","57189692820; 36598530800; 7003274638; 25032210400","A Hybrid Reinforcement Learning-Based Model for the Vehicle Routing Problem in Transportation Logistics",2021.0,"IEEE Access",9.0,null,null,163325.0,163347.0,22.0,6.0,"10.1109/ACCESS.2021.3131799","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85120555108&doi=10.1109%2fACCESS.2021.3131799&partnerID=40&md5=cf4193097cc26f105764e970a665a9f5","School of Knowledge Science, Japan Advanced Institute of Science and Technology, Ishikawa, Nomi, 923-1292, Japan; School of Information Computer and Communication Technology, Sirindhorn International Institute of Technology, Thammasat University, Pathum Thani, 12000, Thailand; National Electronics and Computer Technology Center (NECTEC), National Science and Technology Development Agency, Pathum Thani, 12000, Thailand","Phiboonbanakit T., School of Knowledge Science, Japan Advanced Institute of Science and Technology, Ishikawa, Nomi, 923-1292, Japan, School of Information Computer and Communication Technology, Sirindhorn International Institute of Technology, Thammasat University, Pathum Thani, 12000, Thailand; Horanont T., School of Information Computer and Communication Technology, Sirindhorn International Institute of Technology, Thammasat University, Pathum Thani, 12000, Thailand; Huynh V.-N., School of Knowledge Science, Japan Advanced Institute of Science and Technology, Ishikawa, Nomi, 923-1292, Japan; Supnithi T., National Electronics and Computer Technology Center (NECTEC), National Science and Technology Development Agency, Pathum Thani, 12000, Thailand","Currently, the number of deliveries handled by transportation logistics is rapidly increasing because of the significant growth of the e-commerce industry, resulting in the need for improved functional vehicle routing measures for logistic companies. The effective management of vehicle routing helps companies reduce operational costs and increases its competitiveness. The vehicle routing problem (VRP) seeks to identify optimal routes for a fleet of vehicles to deliver goods to customers while simultaneously considering changing requirements and uncertainties in the transportation environment. Due to its combinatorial nature and complexity, conventional optimization approaches may not be practical to solve VRP. In this paper, a new optimization model based on reinforcement learning (RL) and a complementary tree-based regression method is proposed. In our proposed model, when the RL agent performs vehicle routing optimization, its state and action are fed into the tree-based regression model to assess whether the current route is feasible according to the given environment, and the response received is used by the RL agent to adjust actions for optimizing the vehicle routing task. The procedure repeats iteratively until the maximum iteration is reached, then the optimal vehicle route is returned and can be utilized to assist in decision making. Multiple logistics agency case studies are conducted to demonstrate the application and practicality of the proposed model. The experimental results indicate that the proposed technique significantly improves profit gains up to 37.63% for logistics agencies compared with the conventional approaches.  © 2013 IEEE.","Freight; intelligent transportation; logistics; policy; reinforcement learning; vehicle routing problem","Decision making; Fleet operations; Iterative methods; Regression analysis; Reinforcement learning; Vehicles; Adaptation models; Freight; Intelligent transportation; Logistics agencies; Optimisations; Reinforcement learning agent; Transportation-logistics; Tree-based regression; Uncertainty; Vehicle Routing Problems; Vehicle routing",{"$nulls":6},"Musolino G., Polimeni A., Vitetta A., Freight vehicle routing with reliable link travel times: A method based on network fundamental diagram, Transp. Lett., 10, 3, pp. 159-171, (2018); Polimeni A., Vitetta A., Vehicle routing in urban areas: An optimal approach with cost function calibration, Transportmetrica B, Transp. Dyn., 2, 1, pp. 1-19, (2014); Sutton R.S., Barto A.G., Reinforcement Learning: An Introduction, 2nd Ed, (2017); Braekers K., Ramaekers K., Van Nieuwenhuyse I., The vehicle routing problem: State of the art classification and review, Comput. Ind. Eng., 99, pp. 300-313, (2016); Helal N., Pichon R., Porumbel D., Mercier D., Lefevre E., The capacitated vehicle routing problem with evidential demands, Int. J. Approx. Reasoning, 95, pp. 124-151, (2018); Hottung A., Tierney K., Neural large neighborhood search for the capacitated vehicle routing problem, Proc. Frontiers Artif. Intell. Appl., 325, pp. 443-450, (2020); Lin C., Choy K.L., Ho G.T.S., Chung S.H., Lam H.Y., Survey of green vehicle routing problem: Past and future trends, Expert Syst. Appl., 41, 4, pp. 1118-1138, (2014); Xiao Y., Zhao Q., Kaku I., Xu Y., Development of a fuel consumption optimization model for the capacitated vehicle routing problem, Comput. Oper. 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(ICEB), 2020, pp. 421-429; Drori I., Krishnamurthy Y., Lourenco R., Rampin R., Cho K., Silva C., Freire J., Automatic machine learning by pipeline synthesis using model-based reinforcement learning and a grammar, Proc. 6th Icml Workshop Automated Mach. Learn., pp. 1-8, (2019); Drori I., Krishnamurthy Y., Rampin R., De R., Lourenco P., Ono J.P., Cho K., Silva C., Freire J., AlphaD3M: Machine learning pipeline synthesis, Proc. AutoML Workshop Icml, pp. 1-8, (2018); Mao C., Shen Z., A reinforcement learning framework for the adaptive routing problem in stochastic time-dependent network, Transp. Res. C, Emerg. Technol., 93, pp. 179-197, (2018); Mazyavkina N., Sviridov S., Ivanov S., Burnaev E., Reinforcement Learning for Combinatorial Optimization: A Survey, (2020); Bengio Y., Lodi A., Prouvost A., Machine learning for combinatorial optimization: A methodological tour d'horizon, Eur. J. Oper. Res., 290, 2, pp. 405-421, (2021); Haj-Ali A., Ahmed N.K., Willke T., Gonzalez J., Asanovic K., Stoica I., A View on Deep Reinforcement Learning in System Optimization, (2019); Ulmer M.W., Goodson J.C., Mattfeld D.C., Thomas B.W., On modeling stochastic dynamic vehicle routing problems, Euro J. Transp. Logistics, 9, 2, (2020); Cruciol L.L.B.V., De Arruda A.C., Weigang L., Li L., Crespo A.M.F., Reward functions for learning to control in air traffic flow management, Transp. Res. C, Emerg. Technol., 35, pp. 141-155, (2013); Lombardi M., Milano M., Boosting combinatorial problem modeling with machine learning, Proc. 27th Int. Joint Conf. Artif. Intell. (IJCAI), pp. 5472-5478, (2018); Russell S., Norvig P., Artificial Intelligence: A Modern Approach, 3rd Ed, (2010); Frazelle E., Supply Chain: The Logistics of Supply Chain Management, (2002); Christopher M., Logistics and Supply Chain Management, 41, (2005); Phiboonbanakit T., Huynh V.-N., Horanont T., Supnithi T., Detecting abnormal behavior in the transportation planning using long short term memories and a contextualized dynamic threshold, Proc. Acm Int. Joint Conf. Pervasive Ubiquitous Comput., Acm Int. Symp. Wearable Comput, pp. 996-1007, (2019); Insa-Cabrera J., Dowe D.L., Hernandez-Orallo J., Evaluating a reinforcement learning algorithm with a general intelligence test, Proc. Conf. Spanish Assoc. Artif. Intell., in Lecture Notes in Computer Science, 7023, pp. 1-11, (2011); Poole D.L., MacKworth A.K., Artificial Intelligence: Foundations of Computational Agents, 2nd Ed, (2017); Taylor M.E., Kulis B., Sha F., Metric learning for reinforcement learning agents, Proc. 10th Int. Conf. Auton. Agents Multiagent Syst. (AAMAS), 2, pp. 729-736, (2011); Kotz S., Johnson N.L., Read C.B., Encyclopedia of Statistical Sciences, 1st Ed, (2006); Everitt B.S., Skrondal A., The Cambridge Dictionary of Statistics, 4th Ed, (2010); Google OR-Tools, (2019)","V.-N. Huynh; School of Knowledge Science, Japan Advanced Institute of Science and Technology, Nomi, Ishikawa, 923-1292, Japan; email: huynh@jaist.ac.jp; T. Horanont; School of Information Computer and Communication Technology, Sirindhorn International Institute of Technology, Thammasat University, Pathum Thani, 12000, Thailand; email: teerayut@siit.tu.ac.th",null,"Institute of Electrical and Electronics Engineers Inc.",{"$nulls":5},2.1693536E7,null,null,null,"English","IEEE Access","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85120555108"]
["Xiao J.; Wang W.; Tsai S.-B.","Xiao, Jing (57325164500); Wang, Wenlan (57324603100); Tsai, Sang-Bing (55910203400)","57325164500; 57324603100; 55910203400","Coupling of Agricultural Product Marketing and Agricultural Economic Development Based on Big Data Analysis and \"internet+\"",2021.0,"Mobile Information Systems",2021.0,null,3702064.0,null,null,null,11.0,"10.1155/2021/3702064","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85118549992&doi=10.1155%2f2021%2f3702064&partnerID=40&md5=c341877428114fdf5ef76977d33d0b9f","Jinshan College, Fujian Agriculture and Forestry University, Fujian, Fuzhou, 350002, China; School of Economics and Management, Fujian Agriculture and Forestry University, Fujian, Fuzhou, 350002, China; Regional Green Economy Development Research Center, School of Business, WUYI University, Nanping, China","Xiao J., Jinshan College, Fujian Agriculture and Forestry University, Fujian, Fuzhou, 350002, China; Wang W., School of Economics and Management, Fujian Agriculture and Forestry University, Fujian, Fuzhou, 350002, China; Tsai S.-B., Regional Green Economy Development Research Center, School of Business, WUYI University, Nanping, China","In the era of \"Internet+,\"the increase of agricultural products sales can be achieved by creating and joining e-commerce platforms. Most of the farmers in China are self-employed and cannot form an industrial scale. With the rise of \"Internet+\"background research, the combination of this technology and the marketing of agricultural products has become a new marketing model under the deep integration of different fields. Based on the marketing of products under the background of \"Internet+\"and using marketing theories, this paper reviews the development of marketing of agricultural products under the background of \"Internet+,\"including the Internet infrastructure, the establishment of logistics system, the formation of branding, and the deep processing of agricultural products. The paper reviews the development of agricultural marketing under the background of \"Internet+,\"including the Internet infrastructure, establishment of logistics system, branding, and deep processing of agricultural products. The marketing mode of agricultural products under the background of \"Internet+\"is proved, and the development of agricultural products marketing under the background of \"Internet+\"is discussed from various angles, and insights into how to improve it are proposed from five aspects. After excluding the influence of environmental factors through the improved three-stage SE-DEA model, the mean value of TE of comprehensive efficiency of agricultural information allocation increases from 0.773 to 0.832, the mean value of SE of scale efficiency increases from 0.844 to 0.9219, and the mean value of PTE of pure technical efficiency adjusts from 0.9087 to 0.9058. The mean value of pure technical efficiency (PTE) was adjusted from 0.9087 to 0.9058. Compared with the parametric method, DEA does not require a specific production function to be set in advance, and it is also difficult to select a suitable production function in advance for complex problems.  © 2021 Jing Xiao et al.",null,"Big data; Commerce; Efficiency; Marketing; Deep processing; E- commerces; Economic development; Internet infrastructure; Logistics system; Mean values; Product marketing; Product sales; Production function; Pure technical efficiencies; Agricultural products",{"$nulls":6},"Schaak H., Musshoff O., Understanding the adoption of grazing practices in German dairy farming, Agricultural Systems, 165, pp. 230-239, (2018); Stellian R., Danna-Buitrago J.P., Colombian agricultural product competitiveness under the free trade agreement with the United States: Analysis of the comparative advantages, CEPAL Review, 2017, 122, pp. 127-149, (2018); Harder R., Wielemaker R., Larsen T.A., Zeeman G., Oberg G., Recycling nutrients contained in human excreta to agriculture: Pathways, processes, and products, Critical Reviews in Environmental Science and Technology, 49, 8, pp. 695-743, (2019); Ghisi R., Vamerali T., Manzetti S., Accumulation of perfluorinated alkyl substances (PFAS) in agricultural plants: A review, Environmental Research, 169, pp. 326-341, (2019); Bhagwat A., Agricultural product marketing based on ratings and reviews (APMRR), International Journal for Research in Applied Science and Engineering Technology, 7, 5, pp. 1548-1554, (2019); Hadi F., Diana Y., Penerapan UML sebagai alat perancang website dinas pertanian kota payakumbuh, Indonesian Journal of Computer Science, 8, 1, pp. 11-21, (2019); Teluguntla P., Thenkabail P.S., Oliphant A., Xiong J., Gumma M.K., Congalton R.G., Yadav K., Huete A., A 30 m landsat-derived cropland extent product of Australia and China using random forest machine learning algorithm on google earth engine cloud computing platform, ISPRS Journal of Photogrammetry and Remote Sensing, 144, pp. 325-340, (2018); Nkeiruka U.L., Umar T.I., Commodity marketing and services systems' relationship with spacio-economic interactions in Akure city and its' inner towns and villages, Journal of Environment and Earth Science, 8, 8, pp. 55-65, (2018); Bondarenko A.M., Lipkovich E.I., Kachanova L.S., Control of technological processes of organic fertilizers application as a tool to ensure food safety, Journal of Environmental Management and Tourism, 9, 1, pp. 5-11, (2018); Wang C., Jiang P., Farmers' willingness to participate in agricultural product safety cogovernance and self-governance in Jiangsu, China: A gender perspective, Journal of Food Protection, 83, 5, pp. 736-744, (2020); Zurinani S., Rodiyah N., Rodiyah N., Prastyo D.T., Zuhri M.Y.A., Development strategy of brau edufarm tourism in batu, Journal of Indonesian Tourism and Development Studies, 7, 2, pp. 100-110, (2019); Williams G.W., Capps O., Hanselka D., U.S. National economic contribution of generic food and agricultural product advertising, Journal of International Food & Agribusiness Marketing, 30, 2, pp. 191-210, (2018); Comi M., Other agricultures of scale: Social and environmental insights from Yakima valley hop growers, Journal of Rural Studies, 80, pp. 543-552, (2020); Mbum P.A., Ederewhevbe I.G., Economic recovery, growth paradox and agricultural product marketing in Nigeria, Lwati: A Journal of Contemporary Research, 16, 3, pp. 125-148, (2019); Syahza A., Savitri E., Asmit B., Meiwanda G., Small-scale agricultural product marketing innovation through BUMDes and MSMEs empowerment in coastal areas, Management Science Letters, 11, 8, pp. 2291-2300, (2021); Mahardika C.B.D.P., Pello W.Y., Pallo M., Performa usaha kemitraan ayam ras pedaging, Partnerberatung, 25, 1, pp. 1270-1281, (2020); Li J.-F., Wang Z.-X., Research on coordination of multi-product \"agricultural super-docking\" supply chain, Procedia Manufacturing, 30, pp. 560-566, (2019); Bantis F., Smirnakou S., Ouzounis T., Koukounaras A., Ntagkas N., Radoglou K., Current status and recent achievements in the field of horticulture with the use of light-emitting diodes (LEDs), Scientia Horticulturae, 235, pp. 437-451, (2018); Ushachev I.G., Maslova V.V., Chekalin V.S., Import substitution and ensuring food security of Russia, Vegetable Crops of Russia, 2, 2, pp. 3-8, (2019); Guo J., Bao Y., Wang M., Steel slag in China: Treatment, recycling, and management, Waste Management, 78, pp. 318-330, (2018); Jinbo C., Yu Z., Lam A., Research on monitoring platform of agricultural product circulation efficiency supported by cloud computing, Wireless Personal Communications, 102, 4, pp. 3573-3587, (2018); Shim H.R., Kim B.G., The effect of customer value on user satisfaction with dialogue characteristics of apple's intelligent agent siri, Journal of Organizational and End User Computing, 32, 1, pp. 62-74, (2020); Zaher M., Shehab A., Elhoseny M., Farahat F.F., Unsupervised model for detecting plagiarism in internet-based handwritten Arabic documents, Journal of Organizational and End User Computing, 32, 2, pp. 42-66, (2020); Verkijika S.F., Assessing the role of simplicity in the continuous use of mobile apps, Journal of Organizational and End User Computing, 32, 4, pp. 26-42, (2020)","W. Wang; School of Economics and Management, Fujian Agriculture and Forestry University, Fuzhou, Fujian, 350002, China; email: wzg916@163.com; S.-B. Tsai; Regional Green Economy Development Research Center, School of Business, WUYI University, Nanping, China; email: sangbing@hotmail.com",null,"Hindawi Limited",{"$nulls":5},"1574017X",null,null,null,"English","Mob. Inf. Sys.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85118549992"]
["Minfang H.; Ludi L.; Xiangpei H.","Minfang, Huang (57421525900); Ludi, LI (57420874300); Xiangpei, HU (15926624300)","57421525900; 57420874300; 15926624300","Time-space network optimization method for split order consolidation on sorting center of large-scale online supermarket",2021.0,"Journal of Industrial Engineering and Engineering Management",35.0,5.0,null,163.0,172.0,9.0,3.0,"10.13587/j.cnki.jieem.2021.05.015","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85123246045&doi=10.13587%2fj.cnki.jieem.2021.05.015&partnerID=40&md5=e39dbce6af56dd069d79ab7f4e045dee","School of Economics and Management, North China Electric Power University, Beijing, 102206, China; School of Management, Zhejiang University, Hangzhou, 310058, China; Institute of Systems Engineering, Dalian University of Technology, Dalian, 116024, China","Minfang H., School of Economics and Management, North China Electric Power University, Beijing, 102206, China; Ludi L., School of Economics and Management, North China Electric Power University, Beijing, 102206, China; Xiangpei H., School of Management, Zhejiang University, Hangzhou, 310058, China, Institute of Systems Engineering, Dalian University of Technology, Dalian, 116024, China","Large-scale online supermarket is a new model of online retailing. Multiple stakeholders (e. g., business managers, customers, government) of large online supermarkets have been suffering from high costs, high disturbances and high pollution caused by multiple shipments due to order splitting fulfillment for one order. Thus, split-order consolidation under a multi-warehouse inventory network has become a key issue for the development of online supermarket. Various split-order consolidating strategies will be required for different combinations of the layout of the warehouses, the inventory structures of warehouses and specific items in the orders. Split orders could be consolidated on warehouse, sorting center or delivery station. This paper presents a split-order consolidation approach through transshipping suborders' stock-keeping units (SKUs) among sorting centers. With the goal of reducing the consolidated cost of split-order packages in sorting centers in large online supermarkets, this paper studies the operational process that the split-order parcels flow and the split-order consolidation among multiple sorting centers through transshipment taken by vehicle circulating departure. The time-space network is utilized to model and optimize the split-order consolidation problem of large-scale online supermarket on the base of the calculation of all types of costs. This paper further applies the classification of orders to reduce solution space and proposes the Genetic Algorithm based on multi-fragment to optimize the consolidation sequence of split-order parcels. The results show that the method is more efficient than the traditional first-come-first-served order fulfillment method. The contributions of this study are as follows: (1) Aiming at solving the problem of split-order consolidating fulfillment, with the characteristics of complicated commodity composition in one order and large numbers of split parcels, the strategy of split-order consolidation among multiple sorting centers by transshipment is proposed. This strategy is a supplement to the strategy of consolidation at warehouses for bulk ordinary orders and the strategy of consolidation at delivery stations for customers' urgent orders. It provides a new way to fulfill the split-order consolidation problem caused by high order splitting rates. (2) The time-space network, an efficient modeling approach, is applied to model and optimize the split-order consolidation problem of large-scale online supermarkets. The physical flow of the split-order parcels is extended to a two-dimensional network from the dimension of the time. Meanwhile, the mathematical model is simplified by using decision variables to represent the time correlation constraints in the classic planning models, in order to decrease the number of the constraints by increasing the number of decision variables. It brings convenience to the model and solution of the complex dynamic network flow planning problem oflarge scale split-order consolidation. It provides a new modeling method for other split-order consolidations based on different strategies. (3) In order to decrease the solution space while solving the problem, it classifies the split orders into batches according to two factors: specific assignment of split orders to sorting centers and the latest delivery time of the orders. And then the consolidating sequence of split orders is transferred to the consolidating sequence of batches of split orders. It makes it possible to utilize the Genetic Algorithm based on multi-fragment orders to solve the problem. From the numerical results, it shows the method is effective in terms of solution quality and time. This study provides a new modeling method for the optimal decision-making for split-order consolidation, which improves the practicability and adaptability of order consolidation. It also is conducive to the development of online supermarkets, a new e-commerce model. In practice, the theoretical results can be used for guiding the workers for their operations in sorting-centers of large online supermarkets or other B2C e-commerce businesses, which are confronted with high order splitting and complicated order fulfillment processing. And finally, it is beneficial to improve the efficiency and customer service levels of large-scale B2C businesses © 2021. All Rights Reserved.","Genetic Algorithm; Large-scale online supermarket; Order consolidation; Order splitting; Time-space network",{"$nulls":5},"National Natural Science Foundation of China, NSFC, (71421001, 71571067); National Key Research and Development Program of China, NKRDPC, (71931009)","Received Date: 2019-10-15　 　 　 Funded Project: Supported by the Innovative Research Group Program of the National Natural Science Foundation of China (71421001), the National Key Project of National Natural Science Foundation of China (71931009) and the Natural Science Foundation of China (71571067). ∗Corresponding author","Zhang Y, Huang M, Package consolidation approach to the split order fulfillment problem of online supermarkets[J], Journal of the Operational Research Society, 69, 1, pp. 127-141, (2018); Zhang Y K, Huang M F, Hu X P., Integrated optimization approach to order allocation and delivery problem of online supermarket, Journal of Systems Engineering, pp. 251-258; Co H C, Miller R H, Xu X., Clustering of SKUs to reduce split delivery cost and improve on-time delivery in online merchandising, California Journal of Operations Management, 6, 1, pp. 45-51, (2007); Zhao F, Wu D, Liang L, Et al., Lateral inventory transshipment problem in online-to-offline supply chain, International Journal of Production Research, 54, 7, pp. 1951-1963, (2016); Chen J X, Wang G H, Liang L., Managing demand disruption with lateral transshipment, Journal of Management Science in China, 17, 12, pp. 27-37, (2014); Ali Ulku M., Dare to care: Shipment consolidation reduces not only costs, but also environmental damage [J], International Journal of Production Economics, 139, 2, pp. 438-446, (2012); Glock C H, Kim T, Shipment consolidation in a multiple-vendor single-buyer integrated inventory model [J], Computers & Industrial Engineering, 70, pp. 31-42, (2014); Nguyen C, Dessouky M, Toriello A., Consolidation strategies for the delivery of perishable products [J], Transportation Research Part E: Logistics and Transportation Review, 69, pp. 108-121, (2014); Lei Y, Jasin S, Sinha A., Joint dynamic pricing and order fulfillment for ecommerce retailers [J], Manufacturing & Service Operations Management, 20, 2, pp. 269-284, (2018); 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Zhang Y, Sun L, Hu X, Et al., Order consolidation for the last-mile split delivery in online retailing, Transportation Research Part E: Logistics and Transportation Review, 122, pp. 309-327, (2019); Kok A G, Fisher M L, Vaidyanathan R., Assortment planning: Review of literature and industry practice [J], pp. 175-236, (2015); Catalan A, Fisher M., Assortment allocation to distribution centers to minimize split customer orders [J], (2013); Acimovic J, Graves S C., Mitigating spillover in online retailing via replenishment [J], Manufacturing & Service Operations Management, 19, 3, pp. 419-436, (2017); Jiang Y P., Dynamic emergency relief resource allocation & distribution scheduling approach in large scale disaster context [D], (2013); Le M L, Huang W X., Airline fleet assignment model based on time-space network, Journal of Transportation Systems Engineering and Information Technology, 14, 1, pp. 81-87, (2014); Li J., Research on multiple depot vehicle scheduling problem if urban bus system based on the time-space network[D], (2012); Hao C L., Model and algorithm for integrated railway blocking and timetabling problem based on complexed time-space network [D], (2017); Zhang D, Yu C, Desai J, Et al., A time-space network flow approach to dynamic repositioning in bicycle sharing systems, Transportation Research Part B: Methodological, 103, pp. 188-207, (2016); Chen S W, Liu M., The optimization for dynamic allocation container storage space for express site based on time-space network [J], China Journal of Management Science, 21, pp. 63-69, (2013); Liu M, Cao J., Optimization of logistics scheduling for hospital pharmacy trusteeship under hybrid uncertainty, Systems Engineering-Theory & Practice, 37, 12, pp. 3160-3169, (2017); Ding X Q., Research on dynamic optimization of coal transport based on the time-space network [D], (2016); Yuan Y, Tang L., Novel time-space network flow formulation and approximate dynamic programming approach for the crane scheduling in a coil warehouse [J], European Journal of Operational Research, 262, 2, pp. 424-437, (2017); Lu P., Research on the system of generating test paper based on subsection integer encoding adaptive genetic algorithm [D], (2016)",null,null,"Zhejiang University",{"$nulls":5},1.0046062E7,null,null,null,"English","J. Industrial Eng. Eng. Management","Article","Final",null,"Scopus","2-s2.0-85123246045"]
["Guo X.; Chen R.; Du S.; Yu Y.","Guo, Xiaolong (35755796400); Chen, Ran (57224580156); Du, Shaofu (25930733800); Yu, Yugang (14822788000)","35755796400; 57224580156; 25930733800; 14822788000","Storage assignment for newly arrived items in forward picking areas with limited open locations",2021.0,"Transportation Research Part E: Logistics and Transportation Review",151.0,null,102359.0,null,null,null,12.0,"10.1016/j.tre.2021.102359","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85107969712&doi=10.1016%2fj.tre.2021.102359&partnerID=40&md5=9f4e21d2322f04e3f461dc5112b93b9d","Anhui Province Key Laboratory of Contemporary Logistics and Supply Chain, International Institute of Finance, School of Management, University of Science and Technology of China, 96 Jinzhai Road, Hefei, 230026, Anhui, China","Guo X., Anhui Province Key Laboratory of Contemporary Logistics and Supply Chain, International Institute of Finance, School of Management, University of Science and Technology of China, 96 Jinzhai Road, Hefei, 230026, Anhui, China; Chen R., Anhui Province Key Laboratory of Contemporary Logistics and Supply Chain, International Institute of Finance, School of Management, University of Science and Technology of China, 96 Jinzhai Road, Hefei, 230026, Anhui, China; Du S., Anhui Province Key Laboratory of Contemporary Logistics and Supply Chain, International Institute of Finance, School of Management, University of Science and Technology of China, 96 Jinzhai Road, Hefei, 230026, Anhui, China; Yu Y., Anhui Province Key Laboratory of Contemporary Logistics and Supply Chain, International Institute of Finance, School of Management, University of Science and Technology of China, 96 Jinzhai Road, Hefei, 230026, Anhui, China","In e-commerce warehouses, replenishment operations involve the transportation of ordered items from reserve areas to forward picking areas. In this paper, we study where to store these items (called newly arrived items) in open storage locations in forward picking areas prior to picking to minimize the total travel distance for given picking orders. The locations occupied by items previously stored in the forward area are not available. The problem is formulated as an integer program and proved to be NP-hard. We propose a two-stage decomposition algorithm, showing that it provides high-quality solutions quickly. Compared with methods proposed in the literature and used in practice, the travel distance is substantially reduced. Also, our numerical study shows that considering the constraint that items have previously been stored, which has often been ignored in previous research, can improve the picking performance by more than 5%. We apply our proposed algorithm to real data from a Chinese 3PL retailer to show that it significantly outperforms the policy the company currently uses. © 2021 Elsevier Ltd","Forward picking area; Storage assignment; Warehouse","China; Digital storage; Integer programming; Location; Decomposition algorithm; E- commerces; Forward picking area; High-quality solutions; Integer program; NP-hard; Performance; Storage assignment; Storage location; Travel distance; algorithm; decomposition analysis; electronic commerce; logistics; retailing; storage; Warehouses",{"$nulls":4},"Top-Notch Young Talents Program of China; National Natural Science Foundation of China, NSFC, (71871207, 71921001, 71991464/71991460, 72071193, 72091215/72091210); Fundamental Research Funds for the Central Universities","This research is supported by the National Natural Science Foundation of China (NSFC) through grants 71991464/71991460, 71871207, 72071193, 72091215/72091210, 71921001; the Top-Notch Young Talents Program of China; and the Fundamental Research Funds for the Central Universities. ","Accorsi R., Baruffaldi G., Manzini R., Picking efficiency and stock safety: A bi-objective storage assignment policy for temperature-sensitive products, Comput. Ind. Eng., 115, pp. 240-252, (2018); Ang M., Lim Y.F., Sim M., Robust storage assignment in unit-load warehouses, Manage. Sci., 58, 11, pp. 2114-2130, (2012); Bahrami B., Aghezzaf E.H., Limre V., Enhancing the order picking process through a new storage assignment strategy in forward-reserve area, Int. J. Prod. Res., 57, 21, pp. 6593-6614, (2019); Bartholdi J.J., Hackman S.T., Allocating space in a forward pick area of a distribution center for small parts, IIE Trans., 40, 11, pp. 1046-1053, (2008); Bottani E., Cecconi M., Vignali G., Montanari R., Optimisation of storage allocation in order picking operations through a genetic algorithm, Int. J. Logist.-Res. Appl., 15, 2, pp. 127-146, (2012); Boysen N., De Koster R., Weidinger F., Warehousing in the e-commerce era: A survey, Eur. J. Oper. 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Res., 43, 17, pp. 3561-3581, (2005); Lee M.K., A storage assignment policy in a man-on-board automated storage/retrieval system, Int. J. Prod. Res., 30, 10, pp. 2281-2292, (1992); Leung K.H., Choy K.L., Siu P.K., Ho G.T., Lam H.Y., Lee C.K., A B2C e-commerce intelligent system for re-engineering the e-order fulfilment process, Expert Syst. Appl., 91, pp. 386-401, (2018); Leung K.H., Lee C.K., Choy K.L., An integrated online pick-to-sort order batching approach for managing frequent arrivals of B2B e-commerce orders under both fixed and variable time-window batching, Adv. Eng. Inform., 45, (2020); Li J., Huang R., Dai J.B., Joint optimisation of order batching and picker routing in the online retailers warehouse in China, Int. J. Prod. Res., 55, 2, pp. 447-461, (2017); Pan J.C.H., Shih P.H., Wu M.H., Lin J.H., A storage assignment heuristic method based on genetic algorithm for a pick-and-pass warehousing system, Comput. Ind. 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Econ., 170, pp. 741-762, (2015); Tsamis N., Giannikas V., McFarlane D., Lu W., Strachan J., pp. 271-279, (2015); Van Oudheusden D.L., Zhu W., Storage layout of AS/RS racks based on recurrent orders, Eur. J. Oper. Res., 58, 1, pp. 48-56, (1992); Velez-Gallego M.C., Smith A.E., (2018); Walter R., Boysen N., Scholl A., The discrete forward reserve problem: Allocating space, selecting products, and area sizing in forward order picking, Eur. J. Oper. Res., 229, 3, pp. 585-594, (2013); Weidinger F., Boysen N., Scattered storage: How to distribute stock keeping units all around a mixed-shelves warehouse, Transp. Sci., 52, 6, pp. 1412-1427, (2018); Wutthisirisart P., Noble J.S., Chang C.A., A two-phased heuristic for relation-based item location, Comput. Ind. Eng., 82, pp. 94-102, (2015); Xiao J., Zheng L., A correlated storage location assignment problem in a single-block-multi-aisles warehouse considering BOM information, Int. J. Prod. Res., 48, 5, pp. 1321-1338, (2010); Yang P., Zhao Z., Guo H., Order batch picking optimization under different storage scenarios for e-commerce warehouses, Transp. Res. Part E: Logist. Transp. Rev., 136, (2020); Yu Y., De Koster R., Designing an optimal turnover-based storage rack for a 3D compact automated storage and retrieval system, Int. J. Prod. Res., 47, 6, pp. 1551-1571, (2009); Yu M., De Koster R., Enhancing performance in order picking processes by dynamic storage systems, Int. J. Prod. Res., 48, 16, pp. 4785-4806, (2010); Yu Y., De Koster R., Guo X., Class-based storage with a finite number of items: Using more classes is not always better, Prod. Operat. Manage., 24, 8, pp. 1235-1247, (2015); Yuan R., Graves S.C., Cezik T., Velocity-based storage assignment in semi-automated storage systems, Prod. Operat. Manage., 28, 2, pp. 354-373, (2019); Zhang R.Q., Wang M., Pan X., New model of the storage location assignment problem considering demand correlation pattern, Comput. Ind. Eng., 129, pp. 210-219, (2019)","Y. Yu; Anhui Province Key Laboratory of Contemporary Logistics and Supply Chain, International Institute of Finance, School of Management, University of Science and Technology of China, Hefei, 96 Jinzhai Road, 230026, China; email: ygyu@ustc.edu.cn",null,"Elsevier Ltd",{"$nulls":5},1.3665545E7,null,null,null,"English","Transp. Res. Part E Logist. Transp. Rev.","Article","Final",null,"Scopus","2-s2.0-85107969712"]
["Makhitha K.M.; Ngobeni K.M.","Makhitha, Khathutshelo M. (56399307200); Ngobeni, Kate M. (57371646600)","56399307200; 57371646600","The impact of risk factors on south african consumers’ attitude towards online shopping",2021.0,"Acta Commercii",21.0,1.0,"a922",null,null,null,2.0,"10.4102/ac.v21i1.922","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121105821&doi=10.4102%2fac.v21i1.922&partnerID=40&md5=9f35283ea175f7ad8125dd2bac55eb6b","Department of Marketing and Retail Management, College of Economics and Management Sciences, University of South Africa, Pretoria, South Africa","Makhitha K.M., Department of Marketing and Retail Management, College of Economics and Management Sciences, University of South Africa, Pretoria, South Africa; Ngobeni K.M., Department of Marketing and Retail Management, College of Economics and Management Sciences, University of South Africa, Pretoria, South Africa","Orientation: The advances in technology have resulted in an increasing number of people choosing to shop online, globally. Despite the growing number of those shopping online and online retailers, most customers continue to avoid shopping online. This could be because of risks inherent in online shopping that have resulted in some consumers opting not to shop online. Research purpose: The main aim of the research study is to identify the risks influencing consumers’ attitude towards online purchases. Motivation for the study: The study was driven by the need to determine the risks associated with online shopping that influence whether consumers will shop online or not. Research design, approach and method: A survey, using the non-probability convenience sampling method, was used to reach respondents (207 consumers in South Africa who visited two shopping malls) in Gauteng, South Africa. Data were collected from consumers at the two shopping malls from March 2019 to April 2019. Structural equation modelling (SEM) was used to test the conceptual model for the study. Main findings: The results showed that product risk and privacy risk influence consumer attitude in online shopping positively and that delivery risk does not to have a great influence on attitude towards online shopping. The attitude towards online shopping was also found to positively influence their intention to shop online. Practical/managerial implications: The practical implications for this study would be that retail owners and marketers would understand and manage product and privacy as risks that inhibit consumers from shopping online. Retailers should formulate appropriate marketing and retail strategies that address these risks to change consumers’ perceptions about online shopping and reduce the level of risks related to online shopping. Contribution/value-add: Marketing and retail strategies should include strategies on how product risk and privacy risks will be managed and reduced to ensure they do not influence consumer’s attitude against online shopping. © 2021. The Authors. Licensee: AOSIS. This work.","Attitude, consumer behaviour; Online shopping; Purchase intention; Risk factors",{"$nulls":7},"Aghekyan-Simonian M., Forsythe S., Kwon W.S., Chattaraman V., The role of product brand image and online store image on perceived risks and online purchase intentions for apparel, Journal of Retailing and Consumer Services, 19, 3, pp. 325-331, (2012); Ariff M.S.M., Sylvester M., Zakuan N., Ismail K., Ali K.M., Consumer perceived risk, attitude and online shopping behaviour; empirical evidence from Malaysia, IOP Conference Series: Materials Science and Engineering, 58, 1, pp. 29-31, (2014); Ariffin H., Mohan T., Goh Y., Influence of consumers’ perceived risk on consumers’ online purchase intention, Journal of Research in Interactive Marketing, 12, 3, pp. 309-327, (2018); Arora N., Rahul M., The role of perceived risk in influencing online shopping attitude among women in India, International Journal of Public Sector Performance Management, 4, 1, pp. 98-113, (2018); Arora S., Sahney S., Consumer’s webrooming conduct: An explanation using the theory of planned behavior, Asia Pacific Journal of Marketing and Logistics, 30, 4, pp. 1040-1063, (2018); Bhatti A., Saad S., Gbadebo S.M., Convenience risk, product risk, and perceived risk influence on online shopping: Moderating effect of attitude, Science Arena Publications International Journal of Business Management, 3, 2, pp. 1-11, (2018); South Africans are expected to spend R45 billion shopping online this year, (2018); Chang M.-L., Wu W.-Y., Revisiting perceived risk in the context of online shopping: An alternative perspective of decision-making styles, Psychology & Marketing, 29, 5, pp. 378-400, (2012); Child D., The essentials of factor analysis, (2006); Dai H., Chen Y., Effects of exchange benefits, security concerns and situational privacy concerns on mobile commerce adoption, Journal of International Technology and Information Management, 24, 3, pp. 41-56, (2015); (2018); Farhana N, Khan T., Noor S., Factors affecting the attitude towards online shopping: An empirical study on urban youth in Bangladesh, Australian Academy of Business and Economics Review, 3, 4, pp. 224-234, (2017); Field A., Miles J., Discovering statistics using SAS, (2010); Forsythe S., Shi B., Consumer patronage and risk perceptions in Internet shopping, Journal of Business Research, 56, 11, pp. 867-876, (2003); Fortes N., Rita P, Privacy concerns and online purchasing behaviour: Towards an integrated model, European Research on Management and Business Economics, 22, 3, pp. 167-176, (2016); Hair J.F., Black. 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Makhitha; Department of Marketing and Retail Management, College of Economics and Management Sciences, University of South Africa, Pretoria, South Africa; email: makhikm@unisa.ac.za",null,"AOSIS (pty) Ltd",{"$nulls":5},2.4131903E7,null,null,null,"English","Acta. Commercii.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85121105821"]
["Saphores J.-D.; Xu L.","Saphores, Jean-Daniel (6602154152); Xu, Lu (57216862316)","6602154152; 57216862316","E-shopping changes and the state of E-grocery shopping in the US - Evidence from national travel and time use surveys",2021.0,"Research in Transportation Economics",87.0,null,100864.0,null,null,null,51.0,"10.1016/j.retrec.2020.100864","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85084969380&doi=10.1016%2fj.retrec.2020.100864&partnerID=40&md5=d969fe93678864872a798349a0165dfe","Departments of Civil and Environmental Engineering, Economics, and Urban Planning & Public Policy, Institute of Transportation Studies, University of California, Irvine, 92617, CA, United States; Department of Civil and Environmental Engineering, Institute of Transportation Studies, University of California, Irvine, 92617, CA, United States","Saphores J.-D., Departments of Civil and Environmental Engineering, Economics, and Urban Planning & Public Policy, Institute of Transportation Studies, University of California, Irvine, 92617, CA, United States; Xu L., Department of Civil and Environmental Engineering, Institute of Transportation Studies, University of California, Irvine, 92617, CA, United States","In spite of the popularity of e-shopping, only 16% of US adults have ordered groceries online, and 7 out of 10 of those who currently buy groceries online do so at most twice a month. Understanding the determinants of e-grocery shopping is important for grocers, supply chain managers, and urban planners. In this context, we first explore how deliveries from online shopping have been changing over time. From our analysis of the 2009 and 2017 National Household Travel Surveys, we found that online shopping has been embraced by increasingly diverse households, although income, education, and some racial/ethnic differences persist. Our analysis of the 2017 American Time Use Survey shows that Americans are 24 times more likely to shop for groceries in stores than online. Moreover, in-store grocery shoppers are more likely to be female and unemployed, but less likely to belong to younger generations, to have less than a college degree, or to be African American. The gender imbalance in grocery shopping is larger online than in stores, but e-grocery shoppers do not otherwise differ from the general population. Future travel and e-shopping surveys (especially for e-grocery) should combine time use and travel questions with retrospective questions about online purchases. © 2020 Elsevier Ltd","American Time use survey; e-grocery; National household travel survey; Online shopping",{"$nulls":7},"Agatz N., Campbell A.M., Fleischmann M., Van Nunen J., Savelsbergh M., Revenue management opportunities for Internet retailers, Journal of Revenue and Pricing Management, 12, 2, pp. 128-138, (2013); Andersson P., Ivehammar P., Benefits and costs of autonomous trucks and cars, Journal of Transportation Technologies, 9, 2, pp. 121-145, (2019); Anckar B., Walden P., Jelassi T., Creating customer value in online grocery shopping, International Journal of Retail & Distribution Management, 30, 4, pp. 211-220, (2002); Beaulac J., Kristjansson E., Cummins S., A systematic review of food deserts, 1966-2007, Preventing Chronic Disease, 6, 3, (2009); Blumberg S.J., Luke J.V., Wireless substitution: Early release of estimates from the national health Interview survey, (2017); Brashear T.G., Kashyap V., Musante M.D., Donthu N., A profile of the Internet shopper: Evidence from six countries, Journal of Marketing Theory and Practice, 17, 3, pp. 267-282, (2009); Bressolles G., Durrieu F., Senecal S., A consumer typology based on e-service quality and e-satisfaction, Journal of Retailing and Consumer Services, 21, 6, pp. 889-896, (2014); Burroughs R.E., Sabherwal R., Determinants of retail electronic purchasing: A multi-period Investigation1, INFOR: Information Systems and Operational Research, 40, 1, pp. 35-56, (2002); Calderwood E., Freathy P., Consumer mobility in the Scottish isles: The impact of internet adoption upon retail travel patterns, Transportation Research Part A: Policy and Practice, 59, pp. 192-203, (2014); Cherrett T., Dickinson J., McLeod F., Sit J., Bailey G., Whittle G., Logistics impacts of student online shopping–Evaluating delivery consolidation to halls of residence, Transportation Research Part C: Emerging Technologies, 78, pp. 111-128, (2017); Conover W.J., Practical nonparametric statistics, (1999); Conway J., Share of grocery stores that offered home delivery/store pickup of online orders in the United States from 2017 to 2019, (2020); Crocco F., Eboli L., Mazzulla G., Individual attitudes and shopping mode characteristics affecting the use of e-shopping and related travel, Transport and Telecommunication, 14, 1, pp. 45-56, (2013); Dost F., Maier E., E‐Commerce effects on energy consumption: A multi‐year ecosystem‐level assessment, Journal of Industrial Ecology, 22, 4, pp. 799-812, (2018); (2019); Farag S., Schwanen T., Dijst M., Faber J., Shopping online and/or in-store? 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It wasn't as creepy as I expected. CNET, (2018); Zhou Y., Wang X.C., Explore the relationship between online shopping and shopping trips: An analysis with the 2009 NHTS data, Transportation Research Part A: Policy and Practice, 70, pp. 1-9, (2014)","J.-D. Saphores; Departments of Civil and Environmental Engineering, Economics, and Urban Planning & Public Policy, Institute of Transportation Studies, University of California, Irvine, 92617, United States; email: saphores@uci.edu",null,"Emerald Group Holdings Ltd.",{"$nulls":5},7398859.0,null,null,null,"English","Res. Transp. Econ.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85084969380"]
["Settey T.; Gnap J.; Beňová D.; Pavličko M.; Blažeková O.","Settey, Tomáš (57204825945); Gnap, Jozef (6505759592); Beňová, Dominika (57204834094); Pavličko, Michal (57223138026); Blažeková, Ol’Ga (57210808657)","57204825945; 6505759592; 57204834094; 57223138026; 57210808657","The growth of e-commerce due to COVID-19 and the need for urban logistics centers using electric vehicles: Bratislava case study",2021.0,"Sustainability (Switzerland)",13.0,10.0,5357.0,null,null,null,28.0,"10.3390/su13105357","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85106611856&doi=10.3390%2fsu13105357&partnerID=40&md5=b1402016e10c10630562021fa8386a69","Department of Road and Urban Transport, Faculty of Operation and Economics of Transport and Communications, University of Zilina, Žilina, 010 26, Slovakia; Department of Quantitative Methods and Economic Informatics, Faculty of Operation and Economics of Transport and Communications, University of Zilina, Žilina, 010 26, Slovakia","Settey T., Department of Road and Urban Transport, Faculty of Operation and Economics of Transport and Communications, University of Zilina, Žilina, 010 26, Slovakia; Gnap J., Department of Road and Urban Transport, Faculty of Operation and Economics of Transport and Communications, University of Zilina, Žilina, 010 26, Slovakia; Beňová D., Department of Road and Urban Transport, Faculty of Operation and Economics of Transport and Communications, University of Zilina, Žilina, 010 26, Slovakia; Pavličko M., Department of Quantitative Methods and Economic Informatics, Faculty of Operation and Economics of Transport and Communications, University of Zilina, Žilina, 010 26, Slovakia; Blažeková O., Department of Quantitative Methods and Economic Informatics, Faculty of Operation and Economics of Transport and Communications, University of Zilina, Žilina, 010 26, Slovakia","Before the COVID-19 pandemic there had already been an increase in individual shipment transportation including inner-city areas. During the pandemic and implementation of adopted pre-ventive measures, it has increased by more than 100% in some cities. This presents an unsustainable development, particularly in terms of urban environment. The above-mentioned development has accelerated the research related to optimal allocation of logistics centres considering the last-mile distribution. Unfortunately, the theoretical mathematical model that finds an optimal urban logistics centre location based on the matrix of distance, number, and weight of shipments is not applicable in most cities. Therefore, the following research methodology was chosen in accordance with the approved territorial plan. The authors considered those locations in Bratislava—the capital of Slovak Republic—which are designated, or suitable for building up of an urban logistics centre. These localities were afterwards evaluated in a real-world case study employing methods of mathematical programming (linear programming), the nearest neighbour method, and the Clarke-Wright method. The presented methodology can be applied not only when deciding on the appropriate location of the city logistics centre, but also at optimizing the vehicle routing problem. Taking into account the urban logistics sustainability and the e-commerce growth, it was analysed whether the suggested location of urban logistics centre is feasible to provision examined facilities using electric vehicles. The range of considered electric vehicles of N2 category present in the market tends to be at the limits of distribution routes length for the given case study. Therefore, the article also deals with the fast-charging possibilities of vehicles during handling operations and the use of hybrid freight vehicles in city logistics. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.","Distribution; Electric vehicle; Logistics centre; Sustainable city logistics","Bratislava; Bratislavsky; Slovakia; COVID-19; electric vehicle; electronic commerce; epidemic; logistics; sustainable development; transportation system; trend analysis; urban area",{"$nulls":4},"European Regional Development Fund, ERDF","Funding: This research was created thanks to support under the Operational Program Integrated Infrastructure for the project: Identification and possibilities of implementation of new technological measures in transport to achieve safe mobility during a pandemic caused by COVID-19 (ITMS code: 313011AUX5), co-financed by the European Regional Development Fund.","Archetti C., Bertazzi L., Recent challenges in Routing and Inventory Routing: E-commerce and last-mile delivery, Networks, 77, pp. 255-268, (2020); Giret A., Carrascosa C., Julian V., Rebollo M., Botti V., A Crowdsourcing Approach for Sustainable Last Mile Delivery, Sustainability, 10, (2018); Raicu S., Costescu D., Burciu S., Distribution System with Flow Consolidation at the Boundary of Urban Congested Areas, Sustainability, 12, (2020); Aljohani K., Thompson R.G., A Stakeholder-Based Evaluation of the Most Suitable and Sustainable Delivery Fleet for Freight Consolidation Policies in the Inner-City Area, Sustainability, 11, (2019); Tolentino-Zondervan F., Bogers E., van de Sande L., A Managerial and Behavioral Approach in Aligning Stakeholder Goals in Sustainable Last Mile Logistics: A Case Study in the Netherlands, Sustainability, 13, (2021); Aljohani K., Thompson R.G., An Examination of Last Mile Delivery Practices of Freight Carriers Servicing Business Receivers in Inner-City Areas, Sustainability, 12, (2020); Wang F., Zhu Y., Wang F., Liu J., Ma X., Fan X., Car4Pac: Last Mile Parcel Delivery Through Intelligent Car Trip, IEEE Trans. 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Geogr, 74, pp. 173-180, (2019); Lin J., Zhou W., Wolfson O., Electric vehicle routing problem, Proceedings of the 9th International Conference on City Logistics, (2015); Bi X., Tang W.K.S., Logistical Planning for Electric Vehicles Under Time-Dependent Stochastic Traffic, IEEE Trans. Intell. Transp. Syst, 20, pp. S3771-S3781, (2019); Schaub J., Pieper M., Klopstein S., Ubbing M., Electrified efficiency–Diesel hybrid powertrain concepts for light commercial vehicles, Proceedings of the Internationaler Motorenkongress 2020; Taniguchi E., Thompson R.G., Qureshi A.G., Modelling city logistics using recent innovative technologies, Transp. Res. Procedia, 46, pp. 3-12, (2020); Seghezzi A., Mnagiaracina R., Investigating multi-parcel crowdsourcing logistics for B2C e-commerce last-mile deliveries, Int. J. Logist. Res. Appl, 14, (2021); Culik K., Kalasova A., Statistical Evaluation of BIS-11 and DAQ Tools in the Field of Traffic Psychology, Mathematics, 9, (2021)","J. Gnap; Department of Road and Urban Transport, Faculty of Operation and Economics of Transport and Communications, University of Zilina, Žilina, 010 26, Slovakia; email: jozef.gnap@fpedas.uniza.sk",null,"MDPI AG",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85106611856"]
["Kharfan M.; Chan V.W.K.; Firdolas Efendigil T.","Kharfan, Majd (57217216423); Chan, Vicky Wing Kei (57217217552); Firdolas Efendigil, Tugba (23033918000)","57217216423; 57217217552; 23033918000","A data-driven forecasting approach for newly launched seasonal products by leveraging machine-learning approaches",2021.0,"Annals of Operations Research",303.0,"2024-02-01",null,159.0,174.0,15.0,27.0,"10.1007/s10479-020-03666-w","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85086776289&doi=10.1007%2fs10479-020-03666-w&partnerID=40&md5=181c69b2ab5111f6c63788a455fb15ae","Converse Inc., 1 Lovejoy Wharf, Boston, 02114, MA, United States; Google Hong Kong Ltd, Suites 2501, Tower 2, Times Square, 1 Matheson St, Causeway Bay, Hong Kong; Massachusetts Institute of Technology (MIT), Center for Transportation and Logistics, 77 Massachusetts Avenue, E40, Cambridge, 02139, MA, United States","Kharfan M., Converse Inc., 1 Lovejoy Wharf, Boston, 02114, MA, United States; Chan V.W.K., Google Hong Kong Ltd, Suites 2501, Tower 2, Times Square, 1 Matheson St, Causeway Bay, Hong Kong; Firdolas Efendigil T., Massachusetts Institute of Technology (MIT), Center for Transportation and Logistics, 77 Massachusetts Avenue, E40, Cambridge, 02139, MA, United States","Companies in the fashion industry are struggling with forecasting demand due to the short-selling season, long lead times between the operations, huge product variety and ambiguity of demand information. The forecasting process is becoming more complicated by virtue of evolving retail technology trends. Demand volatility and speed are highly affected by e-commerce strategies as well as social media usage regards to varying customer preferences, short product lifecycles, obsolescence of the retail calendar, and lack of information for newly launched seasonal items. Consumers have become more demanding and less predictable in their purchasing behavior that expects high quality, guaranteed availability and fast delivery. Meeting high expectations of customers’ initiates with proper demand management. This study focuses on demand prediction with a data-driven perspective by both leveraging machine learning techniques and identifying significant predictor variables to help fashion retailers achieve better forecast accuracy. Prediction results obtained were compared to present the benefits of machine learning approaches. The proposed approach was applied by a leading fashion retail company to forecast the demand of newly launched seasonal products without historical data. © 2020, Springer Science+Business Media, LLC, part of Springer Nature.","Fashion retailer; Forecasting; Machine learning; Newly launched products",{"$nulls":7},"Intelligent demand forecasting systems for fast fashion (pp, 145–161, (2016); Breiman L., Random forests, Machine Learning, 45, 1, pp. 5-32, (2001); Carbonneau R., Laframboise K., Vahidov R., Application of machine learning techniques for supply chain demand forecasting, European Journal of Operational Research, 184, 3, pp. 1140-1154, (2008); Chase C.W., Machine learning is changing demand forecasting, Journal of Business Forecasting, 35, 4, pp. 43-45, (2016); Choi T.M., Hui C.L., Liu N., Ng S.F., Yu Y., Fast fashion sales forecasting with limited data and time, Decision Support Systems, 59, pp. 84-92, (2014); Das P., Chaudhury S., Prediction of retail sales of footwear using feedforward and recurrent neural networks, Neural Computing and Applications, 16, 4, pp. 491-502, (2007); Guyon I., Elisseeff A., An introduction to variable and feature selection, Journal of Machine Learning Research, 3, pp. 1157-1182, (2003); ). 5-Using artificial neural networks to improve decision making in apparel supply chain systems, Information Systems for the Fashion and Apparel Industry. Woodhead Publishing Series in Textiles (Pp. 97–107). New York: Woodhead Publishing., (2016); James G., Witten D., Hastie T., Tibshirani R., An introduction to statistical learning: With applications in R, (2014); Kaya M., Yesil E., Dodurka M.F., Siradag S., Fuzzy forecast combining for apparel demand forecasting, pp. 123-146, (2014); Kogan K., Herbon A., Production under periodic demand update prior to a single selling season: A decomposition approach, European Journal of Operational Research, 184, 1, pp. 133-146, (2008); Loureiro A., Migueis V., da Silva L.F., Exploring the use of deep neural networks for sales forecasting in fashion retail, Decision Support Systems, 114, pp. 81-93, (2018); Lu C.J., Sales forecasting of computer products based on variable selection scheme and support vector regression, Neurocomputing, 128, pp. 491-499, (2014); van der Maaten L., Hinton G., Visualizing data using t-SNE, Journal of Machine Learning Research, 9, pp. 2579-2605, (2008); Mostard J., Teunter R., de Koster R., Forecasting demand for single-period products: A case study in the apparel industry, European Journal of Operational Research, 211, 1, pp. 139-147, (2011); Pillo G.D., Latorre V., Lucidi S., Procacci E., An application of support vector machines to sales forecasting under promotions, 4OR, 14, pp. 309-325, (2016); Rousseeuw P.J., Silhouettes: A graphical aid to the interpretation and validation of cluster analysis, Journal of Computational and Applied Mathematics, 20, pp. 53-65, (1987); Sun Z.L., Choi T.M., Au K.F., Yu Y., Sales forecasting using extreme learning machine with applications in fashion retailing, Decision Support Systems, 46, 1, pp. 411-419, (2008); Thomassey S., Sales forecasts in clothing industry: The key success factor of the supply chain management, International Journal of Production Economics, 128, 2, pp. 470-483, (2010); Thomassey S., Happiette M., Castelain J.M., A short and mean-term automatic forecasting system-application to textile logistics, European Journal of Operational Research, 161, 1, pp. 275-284, (2005); Wong W., Guo Z., A hybrid intelligent model for medium-term sales forecasting in fashion retail supply chains using extreme learning machine and harmony search algorithm, International Journal of Production Economics, 128, 2, pp. 614-624, (2010); Xia M., Zhang Y., Weng L., Ye X., Fashion retailing forecasting based on extreme learning machine with adaptive metrics of inputs, Knowledge-Based Systems, 36, pp. 253-259, (2012); Zhang G.P., Time series forecasting using a hybrid ARIMA and neural network model, Neurocomputing, 50, pp. 159-175, (2003)","T. Firdolas Efendigil; Massachusetts Institute of Technology (MIT), Center for Transportation and Logistics, Cambridge, 77 Massachusetts Avenue, E40, 02139, United States; email: tugbae@mit.edu",null,"Springer",{"$nulls":5},2545330.0,null,null,null,"English","Ann. Oper. Res.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85086776289"]
["Hehua M.","Hehua, Mao (57412937000)",5.7412937E10,"Application of Passive Wireless RFID Asset Management in Warehousing of Cross-Border E-Commerce Enterprises",2021.0,"Journal of Sensors",2021.0,null,6438057.0,null,null,null,6.0,"10.1155/2021/6438057","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85122893085&doi=10.1155%2f2021%2f6438057&partnerID=40&md5=75941b4cadfd6e45f63f6cdf8982e5a0","Shazhou Professional Institute of Technology, Jiangsu, Zhangjiagang, 215600, China","Hehua M., Shazhou Professional Institute of Technology, Jiangsu, Zhangjiagang, 215600, China","As an important part of modern logistics, warehousing provides a guarantee for the sustainable stability of enterprises, so as to realize the economy of enterprise production and transportation and so as to realize the economy of enterprise production and transportation. With the advent of the information age, the traditional logistics management model has been difficult to adapt to the current increasingly fierce market competition environment. In the management of cross-border e-commerce enterprises, warehouse management must establish a systematic and information-based logistics warehouse management system to improve the level of logistics management. Passive wireless RFID asset management provides a new idea for the construction of warehousing management system of cross-border e-commerce enterprises. Through the application of RFID technology, the warehousing design scheme and process of cross-border e-commerce enterprises can be optimized and controlled to the greatest extent, so as to strengthen the optimization and integration of supply chain and improve the market competitiveness of logistics enterprises. Based on the wireless passive RFID asset management technology, this paper analyses the construction and optimization of the logistics warehouse management system of cross-border e-commerce enterprises. The simulation results show that after the application of wireless passive RFID asset management technology, the warehouse operation efficiency of cross-border e-commerce enterprises is improved, the employee utilization rate is relatively reduced, and at the same time, it can also save a lot of manpower and reduce the labour cost.  © 2021 Mao Hehua.",null,"Asset management; Electronic commerce; Information management; Supply chains; Wages; Asset management technology; Assets management; Cross-border; E-commerce enterprise; Enterprise production; Logistic management; Optimisations; Passive RFID; Production and transportations; Warehouse management systems; Competition",{"$nulls":6},"Ling-Li Y., Application of RFID technology in warehouse management of SMS cross border e-businesses: In the case of Zhejiang, Logistics Technology, 35, 8, pp. 122-125, (2016); Zhu-Ni X., Cheng-Li H., Application of RFID in intelligent warehousing and logistics, Electronic Technology and Software Engineering, 11, 3, pp. 177-178, (2021); Yi-Jun M., Research on the application of RFID technology in logistics warehousing, China Business Theory, 15, 3, pp. 34-35, (2020); Chun-Ning P., Research on the application of simulation technology in warehouse management, Modern Marketing, 12, 4, pp. 204-205, (2020); Jia-Qi W., Application of RFID technology in warehouse management, Logistics Technology, 43, 4, pp. 161-163, (2020); Hai L., Application of RFID technology in intelligent storage, Modern Industrial Economy and Informatization, 10, 3, pp. 50-51, (2020); Lei S., Application analysis and prospect of internet of things technology in warehousing and logistics, Communication World, 27, 1, pp. 155-156, (2020); Guo-Qing S., Application analysis of internet of things technology in warehousing and logistics, Value Engineering, 38, 35, pp. 258-259, (2019); Lei Y., Ling Z., Rui W., Application of RFID technology in logistics warehousing, China New Communications, 21, 4, pp. 101-103, (2019); Yong-Quang Z., Xin-Tong Z., Bao L., Exploring the application of RFID technology in warehouse management process, Logistics Engineering and Management, 40, 12, pp. 76-78, (2018); Li-Fang J., Application of UHF RFID technology in warehouse management, Modern Information Technology, 2, 11, pp. 191-193, (2018); Xiu-Min L., Research on the application of RFID based internet of things technology in intelligent storage, Journal of Shangqiu Vocational and Technical College, 17, 4, pp. 85-88, (2018); Ren-Yu F., Application of radio frequency identification technology in warehouse management system, Petrochemical Technology and Economy, 34, 3, pp. 14-16, (2018); Jing Z., Discussion on the application of RFID technology in warehouse management in the logistics laboratory of Shenzhen institute of technology, Educational Modernization, 4, 51, pp. 345-346, (2017); Meng-Ke C., Ling-Li Y., Application of RFID technology in warehousing of cross-border e-commerce enterprises, Logistics Engineering and Management, 39, 2, pp. 59-60, (2017); Yong-Qiang W., Research on the application of RFID technology in intelligent storage, Modern Industrial Economy and Informatization, 6, 18, pp. 84-85, (2016); Shou-Hai W., Application of RFID in heavy truck logistics warehouse management, Logistics Technology, 39, 8, pp. 144-148, (2016); Shan-Chao D., Application of RFID and UAV in warehouse management informatization, China New Communications, 18, 8, pp. 45-46, (2016); Shou-Kun X., Zhong-Peng Z., Yin-Qi L., Research on the application of RFID positioning technology in warehouse management, Value Engineering, 35, 5, pp. 97-99, (2016); Jie C., Ming-Kai L., Research on the application of RFID in warehouse management, Science and Technology Outlook, 25, 13, pp. 172-173, (2015); Xin Z., Warehouse management informatization and application of RFID indoor positioning technology, China Market, 11, 6, pp. 211-212, (2017); Si-Yu C., Lu-Lu B., Research on the application of RFID technology in intelligent storage, China High Tech Enterprise, 12, 5, pp. 76-77, (2017); Xiao-Zhou W., Xi-Bin G., Research on the application of RFID technology in warehouse management, Wireless Internet Technology, 17, 5, pp. 21-22, (2016); Mohammed A., Qiang W., Alyahya S., Bennett N., Design and optimization of an RFID-enabled automated warehousing system under uncertainties: A multi-criterion fuzzy programming approach, The International Journal of Advanced Manufacturing Technology, 91, 5-8, pp. 1661-1670, (2017); Kai-Ming H., Research on the application of RFID radio frequency technology in warehouse logistics management, Electronic Technology and Software Engineering, 16, 7, pp. 46-49, (2015)","M. Hehua; Shazhou Professional Institute of Technology, Zhangjiagang, Jiangsu, 215600, China; email: maohehua@szit.edu.cn",null,"Hindawi Limited",{"$nulls":5},"1687725X",null,null,null,"English","J. Sensors","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85122893085"]
["Zu E.; Shu M.-H.; Huang J.-C.; Hsu B.-M.; Hu C.-M.","Zu, Enhou (57218628600); Shu, Ming-Hung (7005890144); Huang, Jui-Chan (57194635224); Hsu, Bi-Min (8100365000); Hu, Chien-Ming (57217596456)","57218628600; 7005890144; 57194635224; 8100365000; 57217596456","Management Problems of Modern Logistics Information System Based on Data Mining",2021.0,"Mobile Information Systems",2021.0,null,5241921.0,null,null,null,4.0,"10.1155/2021/5241921","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85116651674&doi=10.1155%2f2021%2f5241921&partnerID=40&md5=f70a7b7c3454fb28025cea22bff62c8f","School of Management, Henan University of Science and Technology, Luoyang City Kaiyuan Avenue, Luoyang, 471023, China; Department of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung City, 80778, Taiwan; Department of Healthcare Administration and Medical Informatics, Kaohsiung Medical University, Kaohsiung City, 80708, Taiwan; Yango University, Fuzhou, 350015, China; Department of Industrial Engineering and Management, Cheng Shiu University, Kaohsiung City, 83347, Taiwan","Zu E., School of Management, Henan University of Science and Technology, Luoyang City Kaiyuan Avenue, Luoyang, 471023, China; Shu M.-H., Department of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung City, 80778, Taiwan, Department of Healthcare Administration and Medical Informatics, Kaohsiung Medical University, Kaohsiung City, 80708, Taiwan; Huang J.-C., Yango University, Fuzhou, 350015, China; Hsu B.-M., Department of Industrial Engineering and Management, Cheng Shiu University, Kaohsiung City, 83347, Taiwan; Hu C.-M., Department of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung City, 80778, Taiwan","With the development of technology, the data stored by humans is growing geometrically. Especially in the logistics industry, the rise of online e-commerce has created a huge data flow in the informatized logistics network. How to collect, analyze, and organize this information in time and analyze the meaning of this information from it is a difficult problem. The paper aims to learn the management of logistics systems from the perspective of statistics. This article uses random analysis of 1,000 customers' logistics records from the logistics enterprise information system, uses mathematical analysis and matrix theory to analyze the correlation among them, and analyzes customer types and shopping. The information on habits, daily consumption patterns, and brand preferences is classified and summarized using mathematical statistics. The experimental results show that the results of the study can well reflect customers' daily habits and consumption habits. The experimental data show that mining effective and accurate information from massive information can help companies to quickly make decisions, formulate scientific logistics management programs, improve operating efficiency, reduce operating costs, and obtain good benefits.  © 2021 Enhou Zu et al.",null,"Data mining; Information management; Information systems; Information use; Operating costs; Statistics; Dataflow; E- commerces; Learn+; Logistic information system; Logistics industry; Logistics network; Logistics system; Management problems; Modern logistics; Random analysis; Sales",{"$nulls":6},"Peter B., Review: Managing information technology in secondary schools, Computer Bulletin, 39, 6, (2018); Theis T.N., Wong H.S.P., The end of moore's law: A new beginning for information technology, Computing in Science & Engineering, 19, 2, pp. 41-50, (2017); Sawesi S., Rashrash M., Phalakornkule K., Carpenter J.S., Jones J.F., The impact of information technology on patient engagement and health behavior change: A systematic review of the literature, JMIR Medical Informatics, 4, 1, (2016); Tawalbeh L.A., Mehmood R., Benkhelifa E., Mobile cloud computing model and big data analysis for healthcare applications, IEEE Access, 6, pp. 6171-6180, (2016); Yuan W., Deng P., Taleb T., Wan J., Bi C., An unlicensed taxi identification model based on big data analysis, IEEE Transactions on Intelligent Transportation Systems, 17, 6, pp. 1703-1713, (2016); Alipbeki O., Kabzhanova G., Kurmanova G., Alipbekova C., Application of GIS technologies to monitor secondary radioactive contamination in the delegen mountain massif, IOP Conference Series: Earth and Environmental Science, 37, 1, (2016); Xiao J.L., Zhang X.B., Liu Y.C., Quality of schisandrae chinensis fructus regionalization based on GIS technology, Zhongguo Zhong Yao Za Zhi, 42, 22, pp. 4408-4413, (2017); Mei X., Lu Y., Development of implantable medical device traceability management information system, Chinese Journal of Medical Instrumentation, 40, 5, pp. 359-362, (2016); Guo Q., Nan P., Nan P., Wan J., Signal classification method based on data mining for multi-mode radar, Journal of Systems Engineering and Electronics, 27, 5, pp. 1010-1017, (2016); Abdelnour A., Kaddour D., Tedjini S., Transformation of barcode into RFID tag, design, and validation, IEEE Microwave & Wireless Components Letters, 28, pp. 398-400, (2018); Ren J.M., Ashfaq M., Hu X.N., Ma J., Liang F., Hebert P.D.N., Lin L., Germain J.F., Ahmed M.Z., Barcode index numbers expedite quarantine inspections and aid the interception of nonindigenous mealybugs (Pseudococcidae), Biological Invasions, 20, 2, pp. 449-460, (2018); Mor Cases S., Jianwattananukul K., Saenyot K., Lekchaum S., Locharoenrat K., Portable laser 1-D barcode scanner for material identification, Materials Today: Proceedings, 5, 7, pp. 15143-15148, (2018); Dong S., Yuan Z., Gu C., Research on intelligent agricultural machinery control platform based on multi-discipline technology integration, Transactions of the Chinese Society of Agricultural Engineering, 33, 8, pp. 1-11, (2017); Jing H., Research on the intelligent control applied in induction motor vector control, Journal of Computational & Theoretical Nanoscience, 13, 3, pp. 2102-2113, (2016); Zamula A., Kavun S., Complex systems modeling with intelligent control elements, International Journal of Modeling Simulation & Scientific Computing, 8, 1, pp. 111-132, (2016); Vogel C., Ntani G., Inskip H., Barker M., Cummins S., Cooper C., Moon G., Baird J., Education moderates the association between supermarket environment and diet, American Journal of Preventive Medicine, 51, 2, pp. e27-e34, (2016); Warwick H., Hutyra C., Politzer C., Francis A., Risoli T., Green C., Verma N., Huettel S., Mather R.C., Small social incentives did not improve the survey response rate of patients who underwent orthopaedic surgery: A randomized trial, Clinical Orthopaedics and Related Research, 477, 7, pp. 1648-1656, (2019); Jia J., Exploring the relationship between entrepreneurial orientation and corporate performance the role of competency of executives in entrepreneurial-oriented corporations Nankai, Business Review International, 5, 3, pp. 326-344, (2016); Fathian M., Hoseinpoor Y., Minaei-Bidgoli B., Offering a hybrid approach of data mining to predict the customer churn based on bagging and boosting methods, Kybernetes, 45, 5, pp. 732-743, (2016); Chernyavskiy A.M.C., Edemskiy A.G.E., Chernyavskiy M.A.C., Efimenko V.G.E., Tarkova A.R.T., Ivanov S.N.I., Efficiency of operation trombendarterektomy from pulmonary artery Branches depending on the degree of pulmonary hypertension and duration of disease, Kardiologiia, 56, 5, pp. 56-59, (2016); Xia X., Zhang L., Industrial energy systems in view of energy efficiency and operation control, Annual Reviews in Control, 42, pp. 299-308, (2016); Deng X., Xu J.X., Wang J., Wang G.Y., Chen Q.S., Biological modeling the undulatory locomotion of C. elegans, using dynamic neural network approach, Neurocomputing, 186, C, pp. 207-217, (2016); Gharehbaghi A., Linden M., A deep machine learning method for classifying cyclic time series of biological signals using time-growing neural network, IEEE Transactions on Neural Networks & Learning Systems, 29, pp. 4102-4115, (2017); Fernandez De Canete J., Del Saz-Orozco P., Baratti R., Mulas M., Ruano A., Garcia-Cerezo A., Soft-sensing estimation of plant effluent concentrations in a biological wastewater treatment plant using an optimal neural network, Expert Systems with Applications, 63, pp. 8-19, (2016); Cattaneo G., Chiaselotti G., Ciucci D., Gentile T., On the connection of hypergraph theory with formal concept analysis and rough set theory, Information Sciences, 330, 2, pp. 342-357, (2016); Lv Z., Lou R., Li J., Singh A.K., Song H., Big data analytics for 6G-enabled massive internet of things, IEEE Internet of Things Journal, 8, pp. 5350-5359, (2021); Grubljesic T., Coelho P.S., Jaklic J., The shift to socio-organizational drivers of business intelligence and analytics acceptance, Journal of Organizational and End User Computing, 31, 2, pp. 37-64, (2019); Hamidi H., Jahanshahifard M., The role of the internet of things in the improvement and expansion of business, Journal of Organizational and End User Computing, 30, 3, pp. 24-44, (2018); Tsai S.B., Wang K., Using a novel method to evaluate the performance of human resources in green logistics enterprises, Ecological Chemistry and Engineering S, 26, 4, pp. 629-640, (2019)","C.-M. Hu; Department of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung City, 80778, Taiwan; email: i108143101@nkust.edu.tw",null,"Hindawi Limited",{"$nulls":5},"1574017X",null,null,null,"English","Mob. Inf. Sys.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85116651674"]
["Song Y.; Hua X.","Song, Yanan (56703835000); Hua, Xiaolong (57300318000)","56703835000; 57300318000","Innovation Path of Leasing Trade under Smart Logistics Technology by Big Data Analysis",2021.0,"Mobile Information Systems",2021.0,null,8347904.0,null,null,null,2.0,"10.1155/2021/8347904","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85117324005&doi=10.1155%2f2021%2f8347904&partnerID=40&md5=6aa4e7806f2e5930d357434d18052938","School of Business, Macau University of Science and Technology, Macao, Macao; School of Finance, Inner Mongolia University of Finance and Economics, Huhhot, China","Song Y., School of Business, Macau University of Science and Technology, Macao, Macao; Hua X., School of Finance, Inner Mongolia University of Finance and Economics, Huhhot, China","With the continuous development of big data and the increasing maturity of e-commerce, people's requirements for modern logistics are becoming increasingly diversified. Conventional modern logistics service level is insufficient to meet the needs of consumers. Therefore, research on the innovative path of big data analysis of leasing trade under smart logistics technology is increasingly important. Smart logistics pays much attention to the integration of the Internet of Things, sensor networks, and the existing internet and realizes the automation, visualization, controllability, intelligence, and networking of logistics through sophisticated, dynamic, and scientific management, thereby improving resource utilization rate and productivity level, creating a more comprehensive connotation of social value. This work aimed to study the use of smart logistics technology to make electric car leasing to a higher level and to innovate the promotion and use mode of leasing trade. A shared business model of electric vehicles was proposed based on the internet and smart logistics technology. The experimental results showed that smart logistics technology contributes to exploring and expanding the role of electric vehicles in solving group users' short-distance travel and improving an urban transportation system. It could offer a basis for nationwide promotion, thus promoting the development of the new energy vehicle industry and testing the practicability of the model. Regarding the improvement of the sample information system, the experimental results showed that the user's full satisfaction is approximately 50%, while there remain the customers who would ask for further improvements. Besides, most customers believe that the accuracy and sensitivity of the existing in-vehicle information display need to be enhanced. © 2021 Yanan Song and Xiaolong Hua.",null,"Commerce; Customer satisfaction; Data handling; Electric vehicles; Information analysis; Information management; Sensor networks; Urban transportation; Continuous development; Dynamic management; E- commerces; Logistics services; Logistics technologies; Modern logistics; Resources utilizations; Scientific management; Sensors network; Service levels; Big data",{"$nulls":6},"Kirch M., Poenicke O., Richter K., RFID in logistics and production-Applications, research and visions for smart logistics zones, Procedia Engineering, 178, pp. 526-533, (2017); Lee S.H., Study on RFID based smart cold chain system, Journal of Platform Technology, 5, 1, pp. 23-32, (2017); Agyabeng-Mensah Y., Ahenkorah E., Korsah G., The mediating roles of supply chain quality integration and green logistics management between information technology and organisational performance, Journal of Supply Chain Management Systems, 8, 4, pp. 1-17, (2019); Webber G., Tough\" 2017 for charter market due to new alliances, Container Shipping & Trade, 6, 2, pp. 10-11, (2017); Lacourbe P., Durable goods leasing in the presence of exporting used products to an international secondary market, European Journal of Operational Research, 250, 2, pp. 448-456, (2016); Kutlu M., Elsayed T., Lease M., Intelligent topic selection for low-cost information retrieval evaluation: A new perspective on deep vs. shallow judging, Information Processing & Management, 54, 1, pp. 37-59, (2018); Knowler G., Port of melbourne lease fetches USD 9.7 billion, Fairplay, 387, 6888, pp. 26-27, (2016); Baldwin A.C.W., Mallidi H.R., Baldwin J.C., Sandoval E., Cohn W.E., Frazier O.H., Singh S.K., Through the looking glass: Real-Time video using \"smart\" technology provides enhanced intraoperative logistics, World Journal of Surgery, 40, 1, pp. 242-244, (2016); Michel R., Wearables come in for a refit: Technologies including smart glasses and real-Time locating are shaking up industrial wearable computers, while more traditional wearables like forearm-mounted terminals evolve to take advantage of android, touchscreens and other technology, Logistics Management, 56, 4, pp. 44-48, (2017); Baek S.I., Shin H.R., Park M.H., Doo I.C., A study on the management of drug logistics using beacon technology, Advanced Science Letters, 24, 3, pp. 1979-1985, (2018); Thoben K.-D., Wiesner S., Wiesner S., Wuest T., Industrie 4.0\" and smart manufacturing-a review of research issues and application examples, International Journal of Automation Technology, 11, 1, pp. 4-16, (2017); Li Y.Y., Huang Y.S., Research and application of cold chain logistics technology of medical supplies based on IOT, Basic and Clinical Pharmacology and Toxicology, 119, S4, (2016); Schmidtke N., Glistau E., Behrendt F., Magdeburg logistics model-the smart logistics zone as a concept for enabling logistics 4.0 technologies, Advanced Logistic Systems-Theory and Practice, 13, 1, pp. 7-16, (2019); Humayun M., Jhanjhi N., Hamid B., Ahmed G., Emerging smart logistics and transportation using IoT and blockchain, Ieee Internet of Things Magazine, 3, 2, pp. 58-62, (2020); King L., Teknowlogi launches A.I. platform for smart logistics decisions, Air Cargo World, 107, 7, (2017); Roll I., Wylie R., Evolution and revolution in artificial intelligence in education, International Journal of Artificial Intelligence in Education, 26, 2, pp. 582-599, (2016); Jeavons A., What is artificial intelligence?, Research World, 2017, 65, (2017); Lu H., Li Y., Min C., Kim H., Serikawa S., Brain intelligence: Go beyond artificial intelligence, Mobile Networks and Applications, 23, 7553, pp. 368-375, (2017); Hassabis D., Kumaran D., Summerfield C., Botvinick M., Neuroscience-inspired artificial intelligence, Neuron, 95, 2, pp. 245-258, (2017); Raedt L.D., Kersting K., Natarajan S., Poole D., Statistical relational artificial intelligence: Logic, probability, and computation, Synthesis Lectures on Artificial Intelligence and Machine Learning, 10, 2, pp. 1-189, (2016); Ma Y., Lee E., Yuen R., An artificial intelligence-based approach for simulating pedestrian movement, Ieee Transactions on Intelligent Transportation Systems, 17, 11, pp. 1-12, (2016); Lubonja F., Gjylameti B., Kurti S., Financial leasing in albania and the impact that internal factors of a SME would have on the probability to be financed by lease, Central European Economic Journal, 6, 53, pp. 189-198, (2020); Liu R., Yang B., Zio E., Chen X., Artificial intelligence for fault diagnosis of rotating machinery: A review, Mechanical Systems and Signal Processing, 108, pp. 33-47, (2018); Thrall J.H., Li X., Li Q., Cruz C., Do S., Dreyer K., Brink J., Artificial intelligence and machine learning in radiology: Opportunities, challenges, pitfalls, and criteria for success, Journal of the American College of Radiology, 15, 3, pp. 504-508, (2018)","X. Hua; School of Finance, Inner Mongolia University of Finance and Economics, Huhhot, China; email: hxl@imufe.edu.cn",null,"Hindawi Limited",{"$nulls":5},"1574017X",null,null,null,"English","Mob. Inf. Sys.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85117324005"]
["Han J.; Lin N.; Ruan J.; Wang X.; Wei W.; Lu H.","Han, Jiliang (57217130195); Lin, Na (57204103900); Ruan, Junhu (25652148000); Wang, Xuping (35273544600); Wei, Wei (57198566861); Lu, Huimin (57209823396)","57217130195; 57204103900; 25652148000; 35273544600; 57198566861; 57209823396","A Model for Joint Planning of Production and Distribution of Fresh Produce in Agricultural Internet of Things",2021.0,"IEEE Internet of Things Journal",8.0,12.0,9257374.0,9683.0,9696.0,13.0,37.0,"10.1109/JIOT.2020.3037729","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85098776034&doi=10.1109%2fJIOT.2020.3037729&partnerID=40&md5=49fb832660710851beee7bad0481ce2c","School of Economics and Management, Northwest AF University, Yangling, China; School of Economics and Management, Dalian University of Technology, Dalian, China; School of Computer Science and Engineering, Xi'An University of Technology, Xi'an, China; Department of Mechanical and Control of Engineering, Kyushu Institute of Technology, Kitakyushu, Japan","Han J., School of Economics and Management, Northwest AF University, Yangling, China; Lin N., School of Economics and Management, Dalian University of Technology, Dalian, China; Ruan J., School of Economics and Management, Northwest AF University, Yangling, China; Wang X., School of Economics and Management, Dalian University of Technology, Dalian, China; Wei W., School of Computer Science and Engineering, Xi'An University of Technology, Xi'an, China; Lu H., Department of Mechanical and Control of Engineering, Kyushu Institute of Technology, Kitakyushu, Japan","The production and distribution planning of fresh produce is a complex optimization problem, which is affected by many factors, including its perishable characteristics. Farmers cannot guarantee the efficiency and accuracy of production and distribution decisions. Given the close relationship between the production and distribution of annual fresh produce, the intention of our research is to solve the two-stage joint planning problem and maximize the revenue of farmers ultimately. The internal relationship matrix between the two links of production and distribution is established. On this basis, we propose a mixed-integer programming (MIP) model, which covers the constraints of labor and capital. The decisions obtained are not only based on price estimation and resource availability but also on the impact of the agricultural Internet-of-Things technology and the special requirements of each distribution channel. Numerical experiments demonstrate that when the planting area is 1, 4, and 6 ha, the proposed joint planning model can improve the distribution revenue of farmers by 7.92%, 4.15%, and 4.94%, respectively, compared with the traditional separate decision-making approach of distribution. According to different decision scenarios, management insights have been obtained. For example, farmers should carefully sort and package products as well as choose a timely and safe third-party express delivery company. Additionally, the proposed strategy can evaluate the impact of distribution channels on farmers' revenue.  © 2014 IEEE.","Fresh e-commerce; fresh produce; Internet of Things (IoT); production and distribution planning","Agricultural robots; Decision making; Integer programming; Internet of things; Complex optimization problems; Distribution channel; Internal relationships; Mixed integer programming model; Numerical experiments; Price estimation; Production and distribution planning; Resource availability; Agriculture",{"$nulls":4},"Annual Social Science Foundation Project of Shaanxi Province, (2020R002); National Natural Science Foundation of China, NSFC, (71531002, 71602096, 71703122, 71703123, 71973106); Natural Science Foundation of Shaanxi Province, (2020JQ-281); Northwest A and F University, NWAFU, (2452019167, 2452020068); National Key Research and Development Program of China, NKRDPC, (2019YFD1101103); Shanxi Provincial Key Research and Development Project, (2019ZDLNY07-02-01)","Manuscript received June 27, 2020; revised August 13, 2020 and October 14, 2020; accepted November 2, 2020. Date of publication November 16, 2020; date of current version June 7, 2021. This work was supported in part by the National Key Research and Development Program of China under Grant 2019YFD1101103; in part by the National Natural Science Foundation of China under Grant 71973106, Grant 71602096, Grant 71703122, Grant 71703123, and Grant 71531002; in part by the Key Research and Development Program of Shaanxi under Grant 2019ZDLNY07-02-01; in part by the Annual Social Science Foundation Project of Shaanxi Province under Grant 2020R002; in part by the Natural Science Foundation Research Project of Shaanxi Province under Grant 2020JQ-281; in part by the Scientific Research Startup Foundation of Northwest A&F University under Grant 2452019167; and in part by the Basic Operating Expense under Humanities and Social Sciences Program of Northwest A&F University under Grant 2452020068. (Corresponding author: Junhu Ruan.) Jiliang Han and Junhu Ruan are with the School of Economics and Management, Northwest A&F University, Yangling 712100, China (e-mail: xnhjl@nwsuaf.edu.cn; rjh@nwsuaf.edu.cn).","Ahumada O., Villalobos J.R., A tactical model for planning the production and distribution of fresh produce, Ann. Oper. Res., 190, 1, pp. 339-358, (2011); Zhang H., Nagarajan M., Sosic' G., Dynamic supplier contracts under asymmetric inventory information, Oper. Res., 58, 5, pp. 1380-1397, (2010); Giri B.C., Roy B., Maiti T., Coordinating a three-echelon supply chain under price and quality dependent demand with sub-supply chain and RFM strategies, Appl. Math. Model., 52, pp. 747-769, (2017); Panda S., Modak N.M., Basu M., Disposal cost sharing and bargaining for coordination and profit division in a three-echelon supply chain, Int. J. Eng. Sci., 9, 4, pp. 276-285, (2014); Ekman S., Tillage system selection: A mathematical programming model incorporating weather variability, J. Agr. Eng. 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["Mehlawat M.K.; Gupta P.; Khaitan A.","Mehlawat, Mukesh K. (23035630900); Gupta, Pankaj (57193233548); Khaitan, Anisha (57217107039)","23035630900; 57193233548; 57217107039","Multiobjective fuzzy vehicle routing using Twitter data: Reimagining the delivery of essential goods",2021.0,"International Journal of Intelligent Systems",36.0,7.0,null,3566.0,3595.0,29.0,15.0,"10.1002/int.22427","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85104242269&doi=10.1002%2fint.22427&partnerID=40&md5=9cf2f9c89785d4ce0e49f5ab3e12fcf1","Department of Operational Research, University of Delhi, Delhi, India","Mehlawat M.K., Department of Operational Research, University of Delhi, Delhi, India; Gupta P., Department of Operational Research, University of Delhi, Delhi, India; Khaitan A., Department of Operational Research, University of Delhi, Delhi, India","The world faced a major disruption in the form of the coronavirus disease (COVID-19) pandemic, which caused many countries to impose severe restrictions on movement, popularly known as “lockdown.” These lockdowns impacted transportation adversely, leading to massive disruptions in global and local supply chains. As the local markets were shut down, more people started turning to e-commerce logistics platforms offering doorstep deliveries of essential items (food and medicines). This resulted in an explosion in demand for such services, and businesses struggled to complete their deliveries. Additionally, the volume of real-time text data suddenly increased, as these customers started sharing their feedback on social media platforms. The availability of real-time raw text data and its popularity for solving complex business problems motivated the development of the approach proposed herein to address last-mile delivery issues. Thus, this paper suggests the use of Twitter data to identify the various grievances of customers about e-commerce logistics platforms. Natural language processing, a popular tool for text analytics, is employed to extract consumer tweets from the Twitter profiles of such businesses and subsequently to clean, process, and analyse them. Issues are categorized and used as objectives in a multiobjective fuzzy vehicle routing problem (VRP). An integrated hybrid fuzzy VRP is developed and coded to solve last-mile delivery issues. Experimental results and comparative analyses highlight the benefits of the novel approach. Managerial insights and scope for future research assist in the further development of the idea. © 2021 Wiley Periodicals LLC","fuzzy simulation; genetic algorithm; natural language processing; text analytics; vehicle routing problem","Electronic commerce; Natural language processing systems; Supply chains; Vehicle routing; Business problems; Comparative analysis; Fuzzy vehicle routing problems; Logistics platforms; Multi objective; NAtural language processing; Social media platforms; Text analytics; Social networking (online)",{"$nulls":6},"Corning P.A., Biological adaptation in human societies: a ‘basic needs’ approach, J Bioeconomics, 2, 1, pp. 41-86, (2000); Nikolopoulos K., Punia S., Schafers A., Tsinopoulos C., Vasilakis C., Forecasting and planning during a pandemic: COVID-19 growth rates, supply chain disruptions, and governmental decisions, Eur J Oper Res, 290, 1, pp. 99-115, (2020); Aggarwal C.C., Zhai C., Mining text data, (2012); Greco F., Polli A., Emotional text mining: customer profiling in brand management, Int J Inf Manage, 51, (2020); Antons D., Grunwald E., Cichy P., Salge T.O., The application of text mining methods in innovation research: current state, evolution patterns, and development priorities, R D Manag, 50, 3, pp. 329-351, (2020); Gupta P., Mehlawat M.K., Khaitan A., Pedrycz W., Sentiment analysis for driver selection in fuzzy capacitated vehicle routing problem with simultaneous pick-up and drop in shared transportation, IEEE Trans Fuzzy Syst, (2020); Manders T., Klaassen E., Unpacking the smart mobility concept in the Dutch context based on a text mining approach, Sustainability, 11, 23, (2019); Dantzig G.B., Ramser J.H., The truck dispatching problem, Manage Sci, 6, 1, pp. 80-91, (1959); Lenstra J.K., Kan A.H.G.R., Complexity of vehicle routing and scheduling problems, Networks, 11, 2, pp. 221-227, (1981); Konstantakopoulos G.D., Gayialis S.P., Kechagias E.P., Vehicle routing problem and related algorithms for logistics distribution: a literature review and classification, Oper Res, pp. 1-30, (2020); Elshaer R., Awad H., A taxonomic review of metaheuristic algorithms for solving the vehicle routing problem and its variants, Comput Ind Eng, 140, (2020); Zadeh L.A., Fuzzy sets, Inf Control, 8, 3, pp. 338-353, (1965); Teodorovic D., Pavkovic G., The fuzzy set theory approach to the vehicle routing problem when demand at nodes is uncertain, Fuzzy Sets Syst, 82, 3, pp. 307-317, (1996); Mehlawat M.K., Gupta P., Khaitan A., Pedrycz W., A hybrid intelligent approach to integrated fuzzy multiple depot capacitated green vehicle routing problem with split delivery and vehicle selection, IEEE Trans Fuzzy Syst, 28, 6, pp. 1155-1166, (2020); Wang R., Zhou J., Yi X., Pantelous A.A., Solving the green-fuzzy vehicle routing problem using a revised hybrid intelligent algorithm, J Ambient Intell Humaniz Comput, 10, 1, pp. 321-332, (2019); Shi Y., Boudouh T., Grunder O., A hybrid genetic algorithm for a home health care routing problem with time window and fuzzy demand, Expert Syst. 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Paper presentation at: The Workshop on Intelligent Metaheuristics for Logistic Planning (CAEPIA-TTIA 2009), (2009); Gupta P., Mehlawat M.K., Aggarwal U., Charles V., An integrated AHP-DEA multiobjective optimization model for sustainable transportation in mining industry, Resour Policy, (2018); Hwang C.L., Yoon K., Lecture notes in economics and mathematical systems, Multiple attribute decision making: methods and applications, a state-of-the-art survey, pp. 58-191, (1981); Gaskell T.J., Bases for vehicle fleet scheduling, J Oper Res Soc, 18, 3, pp. 281-295, (1967)","P. Gupta; Department of Operational Research, University of Delhi, Delhi, India; email: pankajgpta@gmail.com",null,"John Wiley and Sons Ltd",{"$nulls":5},8848173.0,null,"IJISE",null,"English","Int J Intell Syst","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85104242269"]
["Klumpp M.; Loske D.","Klumpp, Matthias (37087477300); Loske, Dominic (57200620979)","37087477300; 57200620979","Order picking and e-commerce: introducing non-parametric efficiency measurement for sustainable retail logistics",2021.0,"Journal of Theoretical and Applied Electronic Commerce Research",16.0,4.0,null,846.0,858.0,12.0,12.0,"10.3390/jtaer16040048","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85103074390&doi=10.3390%2fjtaer16040048&partnerID=40&md5=fb53604fbb7499c5b689f1c7e9c4d942","Fraunhofer Institute for Material Flow and Logistics IML, J.-v.-Fraunhofer-Str. 2-4, Dortmund, 44227, Germany; Institute for Logistics and Service Management, FOM University of Applied Sciences Essen, Leimkugelstr. 6, Essen, 45141, Germany; Department of Business Administration, Georg-August-University of Göttingen, Platz der Göttinger Sieben 3, Göttingen, 37073, Germany; Faculty of Business and Law, UCAM Universidad Católica San Antonio de Murcia, Av. de los Jerónimos, 135, Guadalupe, 30107, Spain","Klumpp M., Fraunhofer Institute for Material Flow and Logistics IML, J.-v.-Fraunhofer-Str. 2-4, Dortmund, 44227, Germany, Institute for Logistics and Service Management, FOM University of Applied Sciences Essen, Leimkugelstr. 6, Essen, 45141, Germany, Department of Business Administration, Georg-August-University of Göttingen, Platz der Göttinger Sieben 3, Göttingen, 37073, Germany; Loske D., Institute for Logistics and Service Management, FOM University of Applied Sciences Essen, Leimkugelstr. 6, Essen, 45141, Germany, Faculty of Business and Law, UCAM Universidad Católica San Antonio de Murcia, Av. de los Jerónimos, 135, Guadalupe, 30107, Spain","Order picking is a crucial but labor-and cost-intensive activity in the retail logistics and e-commerce domain. Comprehensive changes are implemented in this field due to new technologies like AI and automation. Nevertheless, human worker’s activities will be required for quite some time in the future. This fosters the necessity of evaluating manual picker-to-part operations. We apply the non-parametric Data Envelopment Analysis (DEA) to evaluate the efficiency of n = 23 order pickers processing 6109 batches with 865,410 stock keeping units (SKUs). We use distance per location, picks per location, as well as volume per SKU as inputs and picks per hour as output. As the convexity axiom of standard DEA models cannot be fully satisfied when using ratio measures with different denominators, we apply the Free Disposal Hull (FDH) approach that does not assume convexity. Validating the efficiency scores with the company’s efficiency assessment, operationalized by premium payments shows a 93% goodness=of-fit for the proposed model. The formulated non-parametric approach and its empirical application are promising ways forward in implementing empirical efficiency measurements for order picking operations within e-commerce operations. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.","Data envelopment analysis; E-commerce; FDH; Order picking; Retail logistics",{"$nulls":7},"Bach M.P., Editorial: Electronic Commerce in the Time of Covid-19—Perspectives and Challenges, J. Theor. Appl. Electron. Commer. Res, 16, (2021); Bozer Y.A., Aldarondo F.J., A simulation-based comparison of two goods-to-person order picking systems in an online retail setting, Int. J. Prod. Res, 56, pp. 3838-3858, (2018); Boysen N., Fussler D., Stephan K., See the light. Optimization of put-to-light order picking systems, Naval Res. Logist, 67, pp. 3-20, (2020); De Koster R., Le-Duc T., Roodbergen K.J., Design and control of warehouse order picking. A literature review, Eur. J. Oper. 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Agric, 151, pp. 226-237, (2018); Calzavara M., Sgarbossa F., Persona A., Vertical Lift Modules for small items order picking: An economic evaluation, Int. J. Prod. Econ, 210, pp. 199-210, (2019); Fager P., Hanson R., Medbo L., Johansson M.I., Kit preparation for mixed model assembly—Efficiency impact of the picking information system, Comput. Ind. Eng, 129, pp. 169-178, (2019); Lee H.-Y., Murray C.C., Robotics in order picking: Evaluating warehouse lay-outs for pick, place, and transport vehicle routing systems, Int. J. Prod. Res, 57, pp. 5821-5841, (2019); Zhou L., Liu J., Fan X., Zhu D., Wu P., Cao N., Design of V-Type Warehouse Layout and Picking Path Model Based on Internet of Things, IEEE Access, 7, pp. 58419-58428, (2019); D'Avella S., Tripicchio P., Avizzano C.A., A study on picking objects in cluttered environments: Exploiting depth features for a custom low-cost universal jamming gripper, Robot. Comput. 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Anal, 16, pp. 129-147, (2001); Klumpp M., Zijm H., Logistics Innovation and Social Sustainability: How to Prevent an Artificial Divide in Human–Computer Interaction, J. Bus. Logist, 40, pp. 265-278, (2019); Klumpp M., de Leeuw S., Regattieri A., de Souza R., Humanitarian Logistics and Sustainability, (2015); Centobelli P., Cerchione R., Esposito E., Oropallo E., Surfing blockchain wave, or drowning? Shaping the future of distributed ledgers and decentralized technologies, Technol. Forecast. Soc. Chang, 165, (2021); Di Nardo M., Clericuzio M., Murino T., Sepe C., An Economic Order Quantity Stochastic Dynamic Optimization Model in a Logistic 4.0 Environment, Sustainability, 12, (2020); Di Nardo M., Forino D., Murino T., The evolution of man–machine interaction: The role of human in Industry 4.0 paradigm, Prod. Manuf. Res, 8, pp. 20-34, (2020); Raut R.D., Mangla S.K., Narwane V.S., Dora M., Liu M., Big Data Analytics as a mediator in Lean, Agile, Resilient, and Green (LARG) practices effects on sustainable supply chains, Transp. Res. Part E Logist. Transp. Rev, 145, (2021)","M. Klumpp; Fraunhofer Institute for Material Flow and Logistics IML, Dortmund, J.-v.-Fraunhofer-Str. 2-4, 44227, Germany; email: matthias.klumpp@uni-goettingen.de; M. Klumpp; Institute for Logistics and Service Management, FOM University of Applied Sciences Essen, Essen, Leimkugelstr. 6, 45141, Germany; email: matthias.klumpp@uni-goettingen.de; M. Klumpp; Department of Business Administration, Georg-August-University of Göttingen, Göttingen, Platz der Göttinger Sieben 3, 37073, Germany; email: matthias.klumpp@uni-goettingen.de",null,"MDPI AG",{"$nulls":5},7181876.0,null,null,null,"English","J. Theor. Appl. Electron. Commer. Res.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85103074390"]
["Tianzhuo L.; Rong H.; Feng Y.; Manman W.","Tianzhuo, Liu (57306026300); Rong, Huang (57306026400); Feng, Yang (55925588400); Manman, Wang (57221728124)","57306026300; 57306026400; 55925588400; 57221728124","The optimal logistics service strategy choices between the platform and e-retailers",2021.0,"Journal of University of Science and Technology of China",51.0,4.0,null,259.0,274.0,15.0,2.0,"10.52396/JUST-2021-0081","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85117692918&doi=10.52396%2fJUST-2021-0081&partnerID=40&md5=484080d4ac3e63fd92f7054bee01c24f","School of Management, University of Science and Technology of China, Hefei, 230026, China; International Institute of Finance, University of Science and Technology of China, Hefei, 230601, China","Tianzhuo L., School of Management, University of Science and Technology of China, Hefei, 230026, China, International Institute of Finance, University of Science and Technology of China, Hefei, 230601, China; Rong H., School of Management, University of Science and Technology of China, Hefei, 230026, China, International Institute of Finance, University of Science and Technology of China, Hefei, 230601, China; Feng Y., School of Management, University of Science and Technology of China, Hefei, 230026, China, International Institute of Finance, University of Science and Technology of China, Hefei, 230601, China; Manman W., School of Management, University of Science and Technology of China, Hefei, 230026, China, International Institute of Finance, University of Science and Technology of China, Hefei, 230601, China","In the e-commerce market, the success of the hybrid online platform is well proven. The platform is not only an e-retailer but also provides online logistics services for other e-retailers in the platform. Logistics service is an indispensable link in e-commerce, and it also plays a vital role in promoting the online shopping. In our research, we analyze the impacts of logistics service sharing between the platform and the e-retailer and investigate the optimal strategy in two models. The study found that when the third-party logistics provider’ s logistics service level coordinates with logistics service fees and both are in the middle range, the platform and the e-retailer can achieve a logistics service sharing agreement, forming a win-win scenario. When the logistics service fee charged by the third-party logistics provider is too low, or the third-party logistics provider’ s logistics service is too high, both the platform and the e-retailer will choose the strategic mode of not sharing logistics service. Simultaneously, the third-party logistics provider’ s logistics service level promotes the logistics service level of the platform. Finally, numerical analysis is carried out to verify the equilibrium model and analyze the impacts of the equilibrium model’s main parameters. Our study contributes to the growing body of research on the platform operation and provides management insights on firms’ logistic service strategy choices. © 2021, Editorial Department of Journal of University of Science and Technology of China. All rights reserved.","Coopetition; E-commerce; Logistics service; Platform",{"$nulls":5},"National Natural Science Foundation of China, NSFC, (71631006, 71921001, 71991464 / 71991460)","Acknowledgments This work is supported by the National Natural Science Foundation of China ( 71991464 / 71991460, 71631006 and 71921001).","Gao B.J., Chan W.K., Chi L., Et al., Size and Growth Dynamics of Online Stores: A Case of China’s Taobao. Com. 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COM, Industrial Marketing Management, 86, 1, (2020); Hua W., Jing Z., An empirical study on e-commerce logistics service quality and customer satisfaction, WHICEB Proceeding, 16, 3, (2015); Hu M., Fang H., Hou H., Et al., Customized logistics service and online shoppers ’ satisfaction: An empirical study, Internet Research, 26, 2, (2016); Huang G., The relationship between customer satisfaction with logistics service quality and customer loyalty of China e-commerce market: A case of SF express, Journal of Rangsit Graduate Studies in Business and Social Sciences, 5, 1, (2019); Sohn J.I., Woo S.H., Kim T.W., Assessment of logistics service quality using the Kano model in a logistics-triadic relationship, The International Journal of Logistics Management, 28, 2, pp. 680-698, (2017); Yu Y., Wang X., Zhong R.Y., Et al., E-commerce logistics in supply chain management, Industrial Management & Data Systems, 117, 10, pp. 2263-2286, (2017); Wang P., Hao W.J., Dong L.Y., Comparative analysis of customer satisfaction of the self-operated logistics and third-party logistics of JD. com, E-Commerce Letters, 7, 1, (2018); Sun L., Lyu G., Yu Y., Et al., Fulfillment by Amazon versus fulfillment by seller: An interpretable risk-adjusted fulfillment model, Naval Research Logistics, 67, 8, pp. 627-645, (2020); Zhu F., Liu Q., Competing with complementors: An empirical look at Amazon. com, Strategic Management Journal, 39, 10, (2018); He P., Zhang S.S., He C., Impacts of logistics resource sharing on B2C E-commerce companies and customers, Electronic Commerce Research and Applications, 34, (2019); Rai R.K., A co-opetition-based approach to value creation in interfirm alliances: Construction of a measure and examination of its psychometric properties, Journal of Management, 42, 6, pp. 1663-1699, (2016); Yang Z.B., Hu X., Gurnani H., Et al., Multichannel distribution strategy: Selling to a competing buyer with limited supplier capacity, Management Science, 64, 5, pp. 2199-2218, (2018); He Z., Huang D., He S.G., Design of extended warranty service in a dual supply channel, Total Quality Management & Business Excellence, 29, 9, pp. 1089-1107, (2018); Chen X., Luo Z., Wang X.J., Compete or cooperate: Intensity, dynamics, and optimal strategies, Omega, 86, 10, (2019); Peng T.A., Bourne M., The coexistence of competition and cooperation between networks: Implications from two Taiwanese healthcare networks, British Journal of Management, 20, 3, pp. 377-400, (2009); Ritala P., Coopetition strategy: When is it successful? Empirical evidence on innovation and market performance, British Journal of Management, 23, 2, (2012); Gnyawali D.R., Park B.J.R., Co-opetition between giants: Collaboration with competitors for technological innovation, Research Policy, 40, 5, (2011); Wilhelm M., Managing coopetition through horizontal supply chain relations: Linking dyadic and network levels of analysis, Journal of Operations Management, 29, 7-8, pp. 663-676, (2011); Kim J., Parkhe A., Competing and cooperating similarity in global strategic alliances: An exploratory examination, British Journal of Management, 20, 3, pp. 363-376, (2009); Bello D.C., Katsikeas C.S., Robson M.J., Does accommodating a self-serving partner in an international marketing alliance pay off?, Journal of Marketing, 74, 6, pp. 77-93, (2010); Luo X., Slotegraaf R.J., Pan X., Cross-functional “coopetition”: The simultaneous role of cooperation and competition within firms, Journal of Marketing, 70, 2, pp. 67-80, (2006); Abhishek V., Jerath K., Zhang Z., Agency selling or reselling? 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Feng; School of Management, University of Science and Technology of China, Hefei, 230026, China; email: fengyang@ustc.edu.cn",null,"Editorial Department of Journal of University of Science and Technology of China",{"$nulls":5},2532778.0,null,null,null,"English","J. Univ. Sci. Technol. China","Article","Final",null,"Scopus","2-s2.0-85117692918"]
["Borgström B.; Hertz S.; Jensen L.-M.","Borgström, Benedikte (54787281200); Hertz, Susanne (14024445300); Jensen, Leif-Magnus (35117745700)","54787281200; 14024445300; 35117745700","Strategic development of third-party logistics providers (TPLs): “Going under the floor” or “raising the roof”?",2021.0,"Industrial Marketing Management",97.0,null,null,183.0,192.0,9.0,11.0,"10.1016/j.indmarman.2021.07.008","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85111530428&doi=10.1016%2fj.indmarman.2021.07.008&partnerID=40&md5=8ea1570722177101ba92ba64b6eee62b","Malmö University, Malmö, 205 06, Sweden; Jönköping International Business School, Jönköping, 551 11, Sweden; School of Engineering at Jönköping University, Jönköping, 551 11, Sweden","Borgström B., Malmö University, Malmö, 205 06, Sweden; Hertz S., Jönköping International Business School, Jönköping, 551 11, Sweden; Jensen L.-M., School of Engineering at Jönköping University, Jönköping, 551 11, Sweden","Contemporary (third-party logistics providers) TPLs are in danger of being stuck in the middle, unable to perform customer adaptation as well as before and unable to achieve sufficient economies of scale. This conceptual paper aims to explore challenges facing the strategic development of TPLs within a context of increased digitalization, e-commerce and servitization. There are two apparent strategic paths. Under circumstances of strong price pressure, there is demand for standardized TPL services offering simplicity, minimalism and functionality based on digitalization, e-commerce and servitization. Alternatively, with market developments responsive to supply chain complexity, digitalization, e-commerce and servitization enable development towards innovation and change. We conclude that these developments do not invalidate existing frameworks for TPL strategies but contribute alternative strategies. We formulate three propositions for each strategic path. To avoid being stuck in the middle, TPLs are encouraged to either develop efficient services through servitized logistics chains and digital solutions or develop advanced solutions to integrate the consumer into the logistics network system through competencies to control increased levels of complexity. © 2021","Digitalization; E-commerce; Servitization; Strategic development; Third party logistics (TPL)",{"$nulls":7},"Aggarwal R., Lim M.K., Increasing competitiveness of third party logistics with RFID, 2011 IEEE international conference on RFID-technologies and applications, 15–16 Sept 2011, Sitges, Spain, (2011); Berglund M., van Laarhoven P., Sherman G., Wandel S., Third party logistics: is there a future?, International Journal of Logistics Management, 10, 1, pp. 59-70, (1999); Bohm E., Eggert A., Thiesbrummel C., Service transition: A viable option for manufacturing companies with deteriorating financial performance?, Industrial Marketing Management, 60, pp. 101-111, (2017); Borgstrom B., Towards a methodology for studying supply chain practice, International Journal of Physical Distribution and Logistics Management, 42, 8-9, pp. 843-862, (2012); Boysen N., Koster R.D., Weidinger F., Warehousing in the e-commerce era: A survey, European Journal of Operational Research, 277, 2, pp. 396-411, (2019); Brekalo L., Albers S., Delfmann W., Logistics alliance management capabilities: Where are they?, International Journal of Physical Distribution and Logistics Management, 43, 7, pp. 529-543, (2013); Busse C., Wallenburg C.M., Innovation management of logistics service providers foundations, review, and research agenda, International Journal of Physical Distribution and Logistics Management, 41, 2, pp. 187-218, (2011); Caniato F., Henke M., Zsidisin G.A., Supply chain finance: Historical foundations, current research, future developments, Journal of Purchasing and Supply Management, 25, 2, pp. 99-104, (2019); Coreynen W., Matthyssens P., Van Bockhaven W., Boosting servitization through digitization: Pathways and dynamic resource configurations for manufacturers, Industrial Marketing Management, 60, pp. 42-53, (2017); Cruijssen F., Dullaert W., Fleuren H., Horizontal cooperation in transport and logistics: A literature review, Transportation Journal, 46, 3, pp. 22-39, (2007); Cui L., Hertz S., Networks and capabilities as characteristics of logistics firms, Industrial Marketing Management, 40, 6, pp. 1004-1011, (2011); Cui L., Su S.-I.I., Feng Y., Hertz S., Causal or effectual? Dynamics of decision making logics in servitization, Industrial Marketing Management, (2019); Fabbe-Costes N., Jahre M., Supply chain integration improves performance: The Emperor's new suit?, International Journal of Physical Distribution and Logistics Management, 37, pp. 835-855, (2007); Fadile L., El Oumami M., Beidouri Z., Logistics outsourcing: A review of basic concepts, International Journal of Supply Chain Management, 7, 3, pp. 53-69, (2018); Hagberg J., Sundstrom M., Egels-Zanden N., The digitalization of retailing: An exploratory framework, International Journal of Retail & Distribution Management, 44, 7, pp. 694-712, (2016); Hertz S., Alfredsson M., Strategic development of third party logistics providers, Industrial Marketing Management, 32, pp. 139-149, (2003); Hertz S., Macquet M., Customer coordination as a base for third party logistics providers - effectiveness and efficiency, Third party logistics Finnish and Swedish experiences, (2006); Hingley M.K., Power to all our friends? Living with imbalance in supplier-retailer relationships, Industrial Marketing Management, 34, 8, pp. 848-858, (2005); Hingley M., Lindgreen A., Grant D., Kane C., Using fourth-party logistics management to improve horizontal collaboration among grocery retailers, Supply Chain Management: An International Journal, 16, pp. 316-327, (2011); Hosie P.J., Sundarakani B., Tan A., Kozlak A., Determinants of fight party logistics (5PL): Service providers for supply chain management, International Journal of Logistics Systems and Management, 13, 3, pp. 287-316, (2012); Hubner A., Holzapfel A., Kuhn H., Distribution systems in omnichannel retailing, Business Research, 9, pp. 255-296, (2016); Hubner A., Kuhn H., Wollenberg J., Last mile fulfilment and distribution in omni-channel grocery retailing: A strategy planning framework, International Journal of Retail & Distribution Management, 44, 3, pp. 228-247, (2016); Ishfaq R., Defee C.C., Gibson B.J., Raja U., Realignment of the physical distribution process in omni-channel fulfillment, International Journal of Physical Distribution and Logistics Management, 46, 6-7, pp. 543-561, (2016); Jocevski M., Arvidsson N., Miragliotta G., Ghezzi A., Mangiaracina R., Transitions towards omni-channel retailing strategies: a business model perspective, International Journal of Retail & Distribution Management, 47, 2, pp. 78-93, (2019); Jonsson A., Hagberg J., Egels-Zanden N., Lammgard C., Sundstrom M., Handelns digitalisering och förändrade affärsmodeller, (2016); Kembro J., Norrman A., Eriksson E., Adapting warehouse operations and design to omni-channel logistics: A literature review and research agenda, International Journal of Physical Distribution and Logistics Management, 48, 9, pp. 890-912, (2018); Kindstrom D., Kowalkowski C., Service innovation in product centric firms: A multidimentional business model perspective, Journal of Business & Industrial Marketing, 29, 2, pp. 96-111, (2014); Konig C., Caldwell N.D., Ghadge A., Service provider boundaries in competitive markets: The case of the logistics industry, International Journal of Production Research, 57, 18, pp. 5624-5639, (2018); Kovacs Z., Szabo L., Pato B.S.G., Characteristics of logistics service providers and their services, Studia Universitatis Babeș-Bolyai Oeconomica, 61, 1, (2016); Lagorio A., Pinto R., Golini R., Research in urban logistics: A systematic literature review, International Journal of Physical Distribution and Logistics Management, 46, 10, pp. 908-931, (2016); Lim S.F.W.T., Winkenbach M., Configuring the last-mile in business-to-consumer e-retailing, California Management Review, 61, 2, pp. 132-154, (2019); Lim S.F.W., Jin X., Srai J.S., Consumer-driven e-commerce: A literature review, design framework, and research agenda on last-mile logistics models, International Journal of Physical Distribution and Logistics Management, 48, 3, pp. 308-332, (2018); Lindgreen A., Di Benedetto C.A., Citation classics from Industrial Marketing Management: Celebrating forty-seven years of publications on business-to-business marketing management, Industrial Marketing Management, 73, pp. 1-6, (2018); Mangiaracina R., Perego A., Seghezzi A., Tumino A., Innovative solutions to increase last-mile delivery efficiency in B2C e-commerce: A literature review, International Journal of Physical Distribution and Logistics Management, 49, 9, pp. 901-920, (2019); Marasco A., Third-party logistics: A literature review, International Journal of Production Economics, 113, 1, pp. 127-147, (2008); Marchet G., Melacini M., Perotti S., Sassi C., Tappia E., Value creation models in the 3PL industry: What 3PL providers do to cope with shipper requirements, International Journal of Physical Distribution and Logistics Management, 47, 6, pp. 472-494, (2017); Marchet G., Melacini M., Sassi C., Tappia E., Assessing efficiency and innovation in the 3PL industry: an empirical analysis. [Article], International Journal of Logistics Research and Applications, 20, 1, pp. 53-72, (2017); Melacini M., Perotti S., Rasini M., Tappia E., E-fulfilment and distribution in omni-channel retailing: A systematic literature review, International Journal of Physical Distribution and Logistics Management, 48, 4, pp. 391-414, (2018); Moretto A., Gelsimo L.M., Caniato F., de Boer R., Business models for supply chain finance: The perspective of logistics service providers, Conference procedings IPSERA 2018, Athens, (2018); Naslund D., Logistics needs qualitative research - especially action research, International Journal of Physical Distribution and Logistics Management, 32, pp. 321-338, (2002); Nilsson F., Gammelgaard B., Moving beyond the systems approach in SCM and logistics research, International Journal of Physical Distribution and Logistics Management, 42, pp. 764-783, (2012); Olah J., Karmazin G., Peto K., Popp J., Information technology developments of logistics service providers in Hungary, International Journal of Logistics Research and Applications, 21, 3, pp. 332-344, (2018); Oliva R., Kallenberg R., Managing the transition from products to services, International Journal of Service Industry Management, 14, pp. 160-172, (2003); Prockl G., Pflaum A., Kotzab H., 3PL factories or lernstatts? Value-creation models for 3PL service providers, International Journal of Physical Distribution and Logistics Management, 42, 6, pp. 544-561, (2012); Qiu X., Luo H., Xu G., Zhong R., Huang G.Q., Physical assets and service sharing for IoT-enabled Supply Hub in Industrial Park (SHIP), International Journal of Production Economics, 159, pp. 4-15, (2015); Raddats C., Kowalkowski C., Benedettini O., Burton J., Gebauer H., Servitization: A contemporary thematic review of four major research streams, Industrial Marketing Management, (2019); Rai H.B., Verlinde S., Macharis C., Schoutteet P., Vanhaverbeke L., Logistics outsourcing in omnichannel retail: State of practice and service recommendations, International Journal of Physical Distribution and Logistics Management, 49, 3, pp. 267-286, (2019); Rajahonka M., Bask A., Lipponen M., Modularity and customisation in LSPs’ service strategies, International Journal of Services and Operations Management, 16, 2, pp. 174-204, (2013); Sabourn S., Avram-Pop B., Zima L.A., The impact of problem faced by online customers on ecommerce, Studia universitatis Babes-Bolyal: Oeconomica, 62, 2, pp. 77-88, (2017); Saglietto L., Towards a classification of fourth party logistics (4PL), Universal Journal of Industrial and Business Management, 1, pp. 104-116, (2013); Selviaridis K., Spring M., Third party logistics: A literature review and research agenda, The International Journal of Logistics Management, 18, 1, pp. 125-150, (2007); Selviaridis K., Spring M., Araujo L., Provider involvement in business service definition: A typology, Industrial Marketing Management, 42, 8, pp. 1398-1410, (2013); Skjott-Larsen T., Third party logistics – from an interorganizational point of view, International Journal of Physical Distribution and Logistics Management, 30, 2, pp. 112-127, (2000); Sodero A., Jin Y., Barratt M., The social process of Big Data and predictive analytics use for logistics and supply chain management, International Journal of Physical Distribution and Logistics Management, 49, 7, pp. 706-726, (2019); Stefansson G., Collaborative logistics management and the role of third-party service provider, International Journal of Physical Distribution and Logistics Management, 36, 2, pp. 76-92, (2006); Sundtoft Hald K., Kinra A., How the blockchain enables and constrains supply chain performance, International Journal of Physical Distribution and Logistics Management, 49, 4, pp. 376-397, (2019); Ulaga W., Reinartz W., Hybrid offering: How manufacturing firms combine goods and service successfully, Journal of Marketing, 75, 6, pp. 5-23, (2011); Wang X., Persson G., Huemer L., Logistics service providers and value creation through collaboration: A case study, Long Range Planning, 49, 1, pp. 117-128, (2016); Wollenburg J., Hubner A.H., Kuhn H., Trautrims A., From bricks-and-mortar to bricks-and-clicks: Logistics networks in omni-channel grocery retailing, International Journal of Physical Distribution and Logistics Management, 48, 4, pp. 415-438, (2018)","S. Hertz; Jönköping International Business School, Jönköping, 551 11, Sweden; email: Susanne.hertz@ju.se",null,"Elsevier Inc.",{"$nulls":5},198501.0,null,"IMMAD",null,"English","Ind. Mark. Manage.","Article","Final",null,"Scopus","2-s2.0-85111530428"]
["Meng F.; Ji Q.; Zheng H.; Wang H.; Chu D.","Meng, Fanchao (55426658300); Ji, Qingran (57221563688); Zheng, Hongzhen (7403440798); Wang, Huihui (57205731196); Chu, Dianhui (9733764400)","55426658300; 57221563688; 7403440798; 57205731196; 9733764400","Modeling and solution algorithm for optimization integration of express terminal nodes with a joint distribution mode",2021.0,"Journal of Organizational and End User Computing",33.0,4.0,null,1.0,27.0,26.0,7.0,"10.4018/JOEUC.20210701.oa7","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85107649294&doi=10.4018%2fJOEUC.20210701.oa7&partnerID=40&md5=ee3c276877a8ea77850b058d499d1613","School of Computer Science and Technology, Harbin Institute of Technology, Weihai, China","Meng F., School of Computer Science and Technology, Harbin Institute of Technology, Weihai, China; Ji Q., School of Computer Science and Technology, Harbin Institute of Technology, Weihai, China; Zheng H., School of Computer Science and Technology, Harbin Institute of Technology, Weihai, China; Wang H., School of Computer Science and Technology, Harbin Institute of Technology, Weihai, China; Chu D., School of Computer Science and Technology, Harbin Institute of Technology, Weihai, China","The rapid development of e-commerce has led to increased pressure on the express delivery industry to transport products to customers in a timely manner. The problem of how to deliver an increasing volume of express orders to customer clusters in a timely manner and at low cost with the joint distribution mode is becoming urgent. In this study, an express terminal node optimization and integration model is presented with an option to detach single customer clusters. In addition, the simulated annealing algorithm (SAA) based on neighborhood search that includes four rules is proposed to solve the problem. Contrast experiments are performed with SAA, the immune genetic algorithm (IGA), and the CPLEX solver. The experimental results indicate that IGA is less effective than SAA, and the running time of the IGA is longer. The CPLEX solver is less effective than the SAA, too. Additionally, the experimental results also show that every neighborhood rule proposed in this study plays a role in the optimization process. © 2021 IGI Global. All rights reserved.","Detachable customer business; Express terminal nodes integration; Immune genetic algorithm; Minimum cost; Neighborhood search rules; Simulated annealing algorithm","Sales; Simulated annealing; Contrast experiment; Customer cluster; Immune genetic algorithms; Integration models; Joint distributions; Neighborhood search; Simulated annealing algorithm(SAA); Solution algorithms; Genetic algorithms",{"$nulls":4},"Key R&D Plan Project of China, (2018YFB1403104); Key R&D Plan Project of Shandong Province, (GG201703130116)","This research was supported by the Key R&D Plan Project of China [grant number 2018YFB1403104]; and the Key R&D Plan Project of Shandong Province, China [grant number GG201703130116].","Drozdziel P., Winska M., Madlenak R., Szumski P., Optimization of the post logistics network and location of the local distribution center in selected area of the Lublin province, Procedia Engineering, 192, pp. 130-135, (2017); Duan H., Song G., Qu S., Dong X., Xu M., Post-consumer packaging waste from express delivery in China, Resources, Conservation and Recycling, 144, pp. 137-143, (2019); Guastaroba G., Speranza M. G., A heuristic for BILP problems: The single source capacitated facility location problem, European Journal of Operational Research, 238, 2, pp. 438-450, (2014); Hakimi S. L., Optimum locations of switching centers and the absolute centers and medians of a graph, Operations Research, 12, 3, pp. 450-459, (1964); Hazlewood W. R., Coyle L., On ambient information systems: challenges of design and evaluation, International Journal of Ambient Computing & Intelligence, 1, 2, pp. 1-12, (2009); He Y., Wang X., Lin Y., Zhou F., Zhou L., Sustainable decision making for joint distribution center location choice, Transportation Research Part D, Transport and Environment, 55, pp. 202-216, (2017); Hua X., Hu X., Yuan W., Research optimization on logistics distribution center location based on adaptive particle swarm algorithm, Optik (Stuttgart), 127, 20, pp. 8443-8450, (2016); Jaramillo J. H., Bhadury J., Batta R., On the use of genetic algorithms to solve location problems, Computers & Operations Research, 29, 6, pp. 761-779, (2002); Ji Y., Yang H., Zhang Y., Zhong W., Location optimization model of regional express distribution center, Procedia: Social and Behavioral Sciences, 96, pp. 1008-1013, (2013); Joerss M., Schroder J., Neuhaus F., Klink C., Mann F., Parcel delivery: The future of last mile, (2016); Kirkpatrick S., Gelatt C. D., Vecchi M. P., Optimization by simulated annealing, Science, 220, 4598, pp. 671-680, (1983); Klose A., Gortz S., A branch-and-price algorithm for the capacitated facility location problem, European Journal of Operational Research, 179, 3, pp. 1109-1125, (2007); Lai M. C., Sohn H. S., Tseng T. L. B., Chiang C., A hybrid algorithm for capacitated plant location problem, Expert Systems with Applications, 37, 12, pp. 8599-8605, (2010); Liu Y., Fan L., Wang Y., Dong Q., Optimization of Logistics Nodes in Dynamic Location with a Multi-objective Evolutionary Algorithm, 2009 International Conference on Computational Intelligence and Security, 1, pp. 133-137, (2009); Melkote S., Daskin M. S., Capacitated facility location/network design problems, European Journal of Operational Research, 129, 3, pp. 481-495, (2001); Nozick L. K., The fixed charge facility location problem with coverage restrictions, Transportation Research Part E, Logistics and Transportation Review, 37, 4, pp. 281-296, (2001); Pal M., Tardos T., Wexler T., Facility location with nonuniform hard capacities, Proceedings 42nd IEEE Symposium on Foundations of Computer Science, pp. 329-338, (2001); Sun H., Gao Z., Wu J., A bi-level programming model and solution algorithm for the location of logistics distribution centers, Applied Mathematical Modelling, 32, 4, pp. 610-616, (2008); Sun L., Karwan M. H., Gemici-Ozkan B., Pinto J. M., Estimating the long-term cost to serve new customers in joint distribution, Computers & Industrial Engineering, 80, pp. 1-11, (2015); Ting C. J., Chen C. H., A multiple ant colony optimization algorithm for the capacitated location routing problem, International Journal of Production Economics, 141, 1, pp. 34-44, (2013); Venables H., Moscardini A., An adaptive search heuristic for the capacitated fixed charge location problem, International Workshop on Ant Colony Optimization and Swarm Intelligence, pp. 348-355, (2006); Venables H., Moscardini A., Ant based heuristics for the capacitated fixed charge location problem, International Conference on Ant Colony Optimization and Swarm Intelligence, pp. 235-242, (2008); Wang W., Rahman M. A., Kurniawan I. F., Asyhari A. T., Sadat S. N., Yao L., Immune Genetic Algorithm Optimization and Integration of Logistics Network Terminal Resources, 2019 Third IEEE International Conference on Robotic Computing (IRC), pp. 435-436, (2019); Wang Y., Ma X., Liu M., Gong K., Liu Y., Xu M., Wang Y., Cooperation and profit allocation in two-echelon logistics joint distribution network optimization, Applied Soft Computing, 56, pp. 143-157, (2017); Wu L. Y., Zhang X. S., Zhang J. L., Capacitated facility location problem with general setup cost, Computers & Operations Research, 33, 5, pp. 1226-1241, (2006); Xu Y., Xu D., Du D., Zhang D., Approximation algorithm for squared metric facility location problem with nonuniform capacities, Discrete Applied Mathematics, 264, pp. 208-217, (2019); Yamin M., Sen A. A. A., Improving privacy and security of user data in location based services, International Journal of Ambient Computing and Intelligence, 9, 1, pp. 19-42, (2018); Yang W., Wang X., Song X., Yang Y., Patnaik S., Design of intelligent transportation system supported by new generation wireless communication technology, International Journal of Ambient Computing and Intelligence, 9, 1, pp. 78-94, (2018); Zhang J., Chen B., Ye Y., A multiexchange local search algorithm for the capacitated facility location problem, Mathematics of Operations Research, 30, 2, pp. 389-403, (2005)",null,null,"IGI Global",{"$nulls":5},1.5462234E7,null,null,null,"English","J. Organ. End User Comput.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85107649294"]
["Minh N.T.","Minh, Nguyen Tien (57246179200)",5.72461792E10,"Factors affecting logistics performance in e-commerce: evidence from vietnam",2021.0,"Uncertain Supply Chain Management",9.0,4.0,null,957.0,962.0,5.0,0.0,"10.5267/j.uscm.2021.7.005","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85114244320&doi=10.5267%2fj.uscm.2021.7.005&partnerID=40&md5=60f9e9754e4f49609f13d564631df514","VNU University of Economics & Business, Hanoi, Viet Nam","Minh N.T., VNU University of Economics & Business, Hanoi, Viet Nam","The objective of the study is to determine the factors affecting logistics performance in e-commerce in Vietnam. Vietnam's logistics industry with an estimated total value of USD 50-60 billion is currently growing rapidly (20-25%/year) and is forecast to maintain double-digit growth for at least the next 5-10 years, due to the breakthrough of the retail industry with the high penetration of the internet and the trend of online shopping. Research has shown 6 factors that have an impact on logistics performance: customer perception, technology and security, customer protection, electronic payment system, human resources, organization and administration. Analysis of factors affecting logistics performance to propose solutions to improve supply chain quality in e-commerce. © 2021 Growing Science Ltd. All rights reserved.","E-logistics; Logistics performance E-commerce",{"$nulls":7},"Brosch T., Pourtois G., Sander D., The perception and categorisation of emotional stimuli: A review, Cognition and Emotion, 24, 3, pp. 377-400, (2010); Cakir S. Y., EGINLI A. T., E-service Quality Factors that Web Sites should have in Creating Electronic Customer Satisfaction: A Research on Online (Clothing) Shopping Sites, International Journal of Business and Management Studies, 5, 1, pp. 474-484, (2013); Chakraborty R., Lee J., Bagchi-Sen S., Upadhyaya S., Rao H. R., Online shopping intention in the context of data breach in online retail stores: An examination of older and younger adults, Decision Support Systems, 83, pp. 47-56, (2016); Fiske S. T., Lin M., Neuberg S. L., The continuum model: Ten years later, Social cognition, pp. 41-75, (2018); Glover S., Benbasat I., A model of e-commerce transaction perceived risk, International Journal of Electronic Commerce, 15, 2, pp. 47-78, (2011); Hohenstein N. O., Feisel E., Hartmann E., Human resource management issues in supply chain management research, International Journal of Physical Distribution & Logistics Management, 44, 6, pp. 434-463, (2014); Jing Y., On-line Payment and Security of E-commerce, Proceedings. The 2009 International Symposium on Web Information Systems and Applications (WISA 2009), (2009); Menon S. T., Human resource practices, supply chain performance, and wellbeing, International Journal of Manpower, 33, 7, pp. 769-785, (2012); Metzger M. J., Making sense of credibility on the Web: Models for evaluating online information and recommendations for future research, Journal of the American Society for Information Science and Technology, 58, 13, pp. 2078-2091, (2007); Okifo J., Igbunu R., Electronic Payment System in Nigeria: Its Economic Benefits and Challenges, Journal of Education and practice, 6, 16, pp. 56-62, (2015); Panarello A., Tapas N., Merlino G., Longo F., Puliafito A., Blockchain and iot integration: A systematic survey, Sensors, 18, 8, (2018); Petronio S., Boundaries of privacy: Dialectics of disclosure, (2002); Sharma K., An Evaluation of Consumer Privacy Protection in E-Commerce Websites: A Comparative Study of Six E-Stores: Part II, EDPACS, 42, 2, pp. 1-19, (2010); Singh P. R. I. Y. A. N. K. A., Supriya N., Joshna M. S., Issues and challenges of electronic payment systems, International Journal for Research in Management and Pharmacy, 2, 9, pp. 25-30, (2013); Smith-Doerflein K. A., Tracey M., Tan C. L., Human resource management and supply chain effectiveness: an exploratory study, International Journal of Integrated Supply Management, 6, 3-4, pp. 202-232, (2011); Solvi A. S., Foss K., von Soest T., Roald H. E., Skolleborg K. C., Holte A., Motivational factors and psychological processes in cosmetic breast augmentation surgery, Journal of Plastic, Reconstructive & Aesthetic Surgery, 63, 4, pp. 673-680, (2010); Wong WPM, Tan KL, Ida AK, Lim BCY, The Effect of Technology Trust on Customer E-Loyalty in Online Shopping and The Mediating Effect of Trustworthiness, Journal of Marketing Advances and Practices, 1, 2, pp. 38-51, (2019); Yakup D., DIYARBAKIRLIOGLU I., A theoritical approach to the role of perception on the consumer buying decision process, Asian Journal of Business and Management Sciences, 1, 4, pp. 217-221, (2011); Yuniar A. D., Fibrianto A. S., The Affect of Technical Familiarity and Consumer Protection Behavior in Using E-Commerce as Platform Online Shopping, 2019 International Seminar on Application for Technology of Information and Communication (iSemantic), pp. 300-305, (2019); Yu H. C., Hsi K. H., Kuo P. J., Electronic payment systems: an analysis and comparison of types, Technology in Society, 24, 3, pp. 331-347, (2002)","N.T. Minh; VNU University of Economics & Business, Hanoi, Viet Nam; email: tiennguyenm306@gmail.com",null,"Growing Science",{"$nulls":5},2.2916822E7,null,null,null,"English","Uncertain Supply Chain Manag.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85114244320"]
["Makhmudov M.; Lee G.M.; Ko C.S.","Makhmudov, Muzaffar (57208503525); Lee, Gyu M. (57363735900); Ko, Chang Seong (7202596739)","57208503525; 57363735900; 7202596739","Fair profit distribution in delivery service collaboration considering service quality",2021.0,"International Journal of Industrial Engineering : Theory Applications and Practice",28.0,2.0,null,228.0,238.0,10.0,3.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85120652027&partnerID=40&md5=d958894d40d0c9d090d862c7932db90a","Department of Industrial and Management Engineering, Kyungsung University, Busan, South Korea; Department of Industrial and Management Engineering, Pusan National University, Busan, South Korea","Makhmudov M., Department of Industrial and Management Engineering, Kyungsung University, Busan, South Korea; Lee G.M., Department of Industrial and Management Engineering, Pusan National University, Busan, South Korea; Ko C.S., Department of Industrial and Management Engineering, Kyungsung University, Busan, South Korea","Electronic commerce (e-commerce) transactions have become quite prevailing over the last decade. Due to the COVID-19 pandemic, consumers have started to make more online purchases, using fast electronic payment and transaction methods. This trend has led to a surge in sales-to-consumers (B2C) and inter-enterprise (B2B) e-commerce. The express or last-mile parcel delivery business of large companies such as Amazon, Alibaba, or Coupang has grown fast, and their market share has risen while the small and medium-sized delivery companies continue to struggle to survive. While anticipation of further growth in e-commerce at rapid rates is still there, small and medium-sized delivery companies shall always look for ways to remain competitive. Collaboration with other companies is a way of their survival in rapid market competition. In general, parcel delivery companies handle and deliver various types of items or products, which are usually mixed in volume, and some require special facilities. Additionally, there are unforeseen troubles during the delivery process, such as loss, damage, or delay, which may quickly reflect the delivery company's reputation and service reliability. When a collaborative delivery system is in place, the frequency of delivery troubles may increase due to differences in delivery processes among participating delivery companies, especially when these participants handle different types of items: Regular, oversized/overweighted, and refrigerated items. This study aims to consider defective rates in the delivery service of participating companies and impose a penalty for such defects if any. The multi-objective programming model is proposed to describe the problem considering the delivery by types, defective rate, and penalty) while the collaboration group's profit and individual incremental profit of each participating delivery company can be maximized. The max-sum criterion, max-min criterion, Shapley value allocation, and nucleolus-based allocation methods are used to find an optimal solution and fair profit distribution for the collaboration group. Finally, the effectiveness of the proposed model is demonstrated through an illustrative numerical example. © 2021 University of Cincinnati. All rights reserved.","Collaboration model; Express delivery service; Max-min criterion; Max-sum criterion; Multi-objective programming model; Nucleolus-based allocation; Shapley value allocation; The defective rate in the delivery service","Competition; Defects; Game theory; Multiobjective optimization; Profitability; Sales; Collaboration models; Defective rates; Delivery service; Express delivery service; Max-min criteria; Max-sum criteria; Max/min; Multi-objective programming model; Nucleolus-based allocation; Shapley value; Shapley value allocation; The defective rate in the delivery service; Electronic commerce",{"$nulls":4},"Kyungsung University; National Research Foundation of Korea, NRF; Ministry of Education, Science and Technology, MEST, (NRF-2018R1D1A3A03000944)","This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science, and Technology (NRF-2018R1D1A3A03000944). This research was also supported by Kyungsung University research grants in 2020.","Agranoff R., Inside collaborative networks: Ten lessons for public managers, Public Administration Review, 66, pp. 56-60, (2006); Alizadeh A. Z., Nasseri S. H., Mahdavi I., A Fuzzy Stochastic Multi-Objective Optimization Model to Configure a Supply Chain Considering New Product Development, Applied Mathematical Modelling, 40, pp. 7545-7570, (2016); Bardach E., Getting Agencies to Work Together: The Practice and Theory of Managerial Craftsmanship, Brookings Institution Press, 4, 2, (2001); Chung K. H., Ko H. J., Ferdinand F. N., A fuzzy set-theoretic approach to the weak strategic alliance for the survival of multiple service center in express courier services, ICIC Express Letters: International Journal of Research and Surveys, 5, 2, pp. 385-389, (2011); Chung K. H., Ko S. Y., Ko C. S., A Cooperative Game Theoretic Network Design for Collaborative Operation of Service Centers and Consolidation Terminals in Delivery Services, The International Journal of Industrial Engineering: Theory, Applications and Practice, 25, 1, pp. 18-28, (2018); Chung K. H., Ko S. Y., Lee C. U., Sustainable Collaboration Model with Monopoly of Service Centers in Express Delivery Services Based on Shapley Value Allocation, The International Journal of Industrial Engineering: Theory, Applications and Practice, 23, 3, pp. 166-173, (2016); Chung K. H., Rho J. J., Ko C. S., A Strategic Alliance Model with Regional Monopoly of Service Centres in Express Courier Services, International Journal Services and Operations Management, 5, 6, pp. 774-786, (2009); Eliyan A., Elomri A., Kerbache L., The last-mile delivery challenge: Evaluating the efficiency of smart parcel stations, Supply Chain Forum: An International Journal, 67, pp. 91-120, (2021); Etemadnia H., Goetz S. J., Canning P., Tavallali, M.S. Optimal Wholesale Facilities Location Within the Fruit and Vegetables Supply Chain with Bimodal Transportation Options: An LP-MIP Heuristic Approach, European Journal of Operational Research, 244, 2, pp. 648-661, (2015); Entwistle T., Martin S., From Competition to Collaboration in Public Service Delivery: A New Agenda for Research, Public Administration, 83, 1, pp. 14-23, (2005); Farahani R. Z., Rezapour S., Drezner T., Fallah S., Competitive Supply Chain Network Design: An Overview of Classifications, Models, Solution Techniques and Applications, Omega, 45, pp. 92-118, (2014); Ferdinand F. N., Chung K. H., Ko H. J., Ko C.S., Genetic Algorithm-Based Approach to Multi-Objective Decision Making Model for Strategic Alliances in Express Courier Services, ICIC Express Letters, 6, 4, pp. 929-934, (2012); Keizer M., Akkerman R., Grunow M., Bloemhof J. M., Haijema R., van der Vorst J.G.A.J., Logistics Network Design for Perishable Products with Heterogeneous Quality Decay, European Journal of Operational Research, 262, 2, pp. 535-549, (2017); Ko S. Y., Sari R. P., Makhmudov M. M., Ko C. S., Collaboration Model for Service Clustering in Last-Mile Delivery, Sustainability, 12, 14, (2020); Kut C. S., Price and Time Competition for Service Delivery, Manufacturing & Service Operations Management, 2, 4, pp. 392-409, (2000); Mangiaracina R., Perego A., Seghezzi A., Innovative Solutions to Increase Last-Mile Delivery Efficiency in B2C E-Commerce, a Literature Review, International Journal of Physical Distribution & Logistics Management, 49, 9, pp. 901-920, (2019); Morganti E., Seidel S., Blanquart C., The Impact of E-Commerce on Final Deliveries: Alternative Parcel Delivery Services in France and Germany, Transportation Research Procedia, 4, pp. 178-190, (2014); Simonin B. L., The importance of collaborative know-how: An empirical test of the learning organization, Academy of Management Journal, 40, 5, pp. 1150-1174, (1997); Wang C. N., Nhieu N. L., Chung Y. C., Pham H. T., Multi-Objective Optimization Models for Sustainable Perishable Intermodal Multi-Product Networks with Delivery Time Window, Mathematics, 9, (2021); Wang Y., Zhang J., Assogba K., Collaboration and Transportation Resource Sharing in Multiple Centers Vehicle Routing Optimization with Delivery and Pickup, Knowledge-Based Systems, 160, pp. 296-310, (2018); Zahir S., Sarker R., Optimising Multi-Objective Location Decisions In A Supply Chain Using An AHP-Enhanced Goal-Programming Model, International Journal of Logistics Systems and Management, 6, 3, pp. 249-266, (2010)","C.S. Ko; Department of Industrial and Management Engineering, Kyungsung University, Busan, South Korea; email: csko@ks.ac.kr",null,"University of Cincinnati",{"$nulls":5},1.0724761E7,null,"IJIEF",null,"English","Int J Ind Eng Theory Appl Pract","Article","Final",null,"Scopus","2-s2.0-85120652027"]
["Burlando C.; Vella A.","Burlando, Claudia (6507894623); Vella, Andrea (57759263500)","6507894623; 57759263500","E-COMMERCE AND THE LAST MILE IN URBAN GOODS DISTRIBUTION : CRITICALITIES AND THE NEED FOR CHANGE",2021.0,"International Journal of Transport Economics",48.0,2.0,null,141.0,161.0,20.0,0.0,"10.19272/202106702001","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85132507454&doi=10.19272%2f202106702001&partnerID=40&md5=6199c5c04a54fa958d59eb28bf526c15","University of Genoa, Department of Economics and Business Studies, C.I.E.L.I., the Italian Center of Excellence on Logistics Transports and Infrastructures, Italy; Sennder Italia, Italy","Burlando C., University of Genoa, Department of Economics and Business Studies, C.I.E.L.I., the Italian Center of Excellence on Logistics Transports and Infrastructures, Italy; Vella A., Sennder Italia, Italy","The disruptive innovation of e-commerce on incoming and outgoing flows has led to a marked increase in traffic volumes over the so-called last mile. This increase has inevitably impacted urban infrastructures ill prepared for such higher flows and related negative externalities. Moreover, fierce competition and ever more complex customer demand weigh on firms' logistic chains in the form of increased delivery charges and operational inefficiencies simply to preserve market share. This situation is likely to worsen as e-commerce continues to expand and uncertainty over Covid 19 persists. The last mile is a rapidly changing yet problematic link in the logistic chain since : - customers expect free and fast delivery ; - logistic companies need to satisfy increasingly demanding customer delivery needs ; - urban roads, already overloaded with flows of people and traditional goods, face significant increases in the size of these flows together with the rapid speed of change ; - these complex changes are not a priority on policy makers' agenda. All these changes will transform the concept of the city. The purpose of this paper is to provide an updated overview of the current condition for urban deliveries as well as to analyse challenges and identify opportunities for future improvements. This paper reviews recent developments in e-commerce and the urban freight transport solutions used. Specifically, the work provides a complete overview of the critical factors affecting e-Commerce's last mile (failed deliveries, returns, packaging, role of customer satisfaction). The paper also highlights gaps in current research on the topic (i.e. data collection on load factors, externalities, warehousing space and related impacts) as well as within the political agenda (i.e. regulation for efficiency in delivery, planning of collection points and their accessibility, green urban policies, consumer environmental awareness). © 2021 Fabrizio Serra Editore Srl. All rights reserved.","e-Commerce; Last-mile Logistics; Sustainable Development; Urban Externalities; Urban Freight Transport","electronic commerce; freight transport; innovation; logistics; sustainable development; urban transport",{"$nulls":6},"Allen J., Austwick M., Bates O., Bektas T., McLeod F., Piecyk M., Piotrowska M., Wise S., Friday A., Understanding the Impact of E-commerce on Last-Mile Light Goods Vehicle, Transportation Research Part D Transport and Environment, 61, pp. 325-338, (2017); Observatoire annuel des activités postales en France, (2012); Bardi A., Dallara A., Luppino G., Tengattini S., Sinossi delle condizioni per lo sviluppo della ciclologistica urbana, Rivista Scientifica della Società Italiana di Economia dei Trasporti e della Logistica, 5, 1, (2018); New E-Commerce Checkout Research - Why 68% of Users Abandon Their Cart, (2016); Bhatti A., Akram H., Basit H., Khan A., Naqvi S., Bilal M., E-commerce trends during COVID-19 Pandemic, International Journal of Future Generation Communication and Networking, 13, 2, pp. 1449-1452, (2020); Blanquart C., Dablanc L., Lenz B., Morganti E., Sidel S., The impact of e-commerce on final deliveries : alternative parcel delivery services in France and Germany, Transportation Research Procedia, 4, pp. 178-190, (2014); Bolzacchini E., Effetto della Zona a Traffico Limitato di Milano (Area C) sulla composizione chimica del PM, (2016); Borbon-Galvez Y., Barbosa I. 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R., Mobility effects of B2C and C2C e-commerce : A literature review and assessment, Journal of Transport Geography, 17, 2, pp. 83-92, (2009); Weltevreden J. W., B2c e-commerce logistics : the rise of collection-and-delivery points in The Netherlands, International Journal of Retail & Distribution Management, 36, 8, pp. 638-661, (2008); Wygonik E., Goodchild A., Evaluating the impacts of the density on urban goods movement externalities, International Research on Placemaking and Urban Sustainability, 10, 4, pp. 487-499, (2017); Yang H., Wang X., Managing network mobility with tradable credits, Transportation Research Part B : Methodological, 45, 3, pp. 580-594, (2011); Zaarour N., Melachrinoudis E., Solomon M., Min H., A Reverse Logistics Network Model for Handling Returned Products, International Journal of Engineering Business Management, 6, 13, (2014)","C. Burlando; University of Genoa, Department of Economics and Business Studies, C.I.E.L.I., the Italian Center of Excellence on Logistics Transports and Infrastructures, Italy; email: burlando@economia.unige.it",null,"Fabrizio Serra Editore Srl",{"$nulls":5},3035247.0,null,null,null,"English","Int. J. Transp. Econ.","Article","Final",null,"Scopus","2-s2.0-85132507454"]
["Zhu W.; Shi M.","Zhu, Wangli (57243510900); Shi, Meixia (57191250923)","57243510900; 57191250923","Research on the Development Path of a Cross-European e-Commerce Logistics Mode under the Background of \"internet Plus\"",2021.0,"Wireless Communications and Mobile Computing",2021.0,null,6964302.0,null,null,null,3.0,"10.1155/2021/6964302","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85116653742&doi=10.1155%2f2021%2f6964302&partnerID=40&md5=b45fdd3023cb223ed29244f13f487641","School of Economics and Management, Beijing Jiaotong University, Beijing, China","Zhu W., School of Economics and Management, Beijing Jiaotong University, Beijing, China; Shi M., School of Economics and Management, Beijing Jiaotong University, Beijing, China","Cross-border e-commerce and the logistics industry are interrelated in specific economic and circulation fields. Based on the development of cross-border e-commerce in China and Europe, this paper analyzes the economic development of China's cross-border e-business logistics providers in the context of Internet plus and analyzes the development trend of cross-border e-commerce in China and gives suggestions for optimization, with a view to providing cross-border e-commerce for the future. In-depth cooperation provides reference.  © 2021 Wangli Zhu and Meixia Shi.",null,"Business logistics; Cross-border; Development path; E- commerces; eBusiness; Economic development; Logistics industry; Logistics modes; Logistics providers; Paper analysis; Electronic commerce",{"$nulls":6},"Valarezo A., Perez-Amaral T., Garin-Munoz T., Garcia I.H., Lopez R., Drivers and barriers to cross-border e-commerce: Evidence from Spanish individual behavior, Telecommunications Policy, 42, 6, pp. 464-473, (2018); Ji S., Wang X., Zhao W., Guo D., An application of a three-stage XGBoost-based model to sales forecasting of a cross-border E-commerce enterprise, Mathematical Problems in Engineering, 2019, (2019); Liu Y., Zhang X., Zhou Q., VR technology online classroom mode in cross border E-commerce teaching in colleges and universities, IEEE Access, (2020); Song B., Yan W., Zhang T., Cross-border e-commerce commodity risk assessment using text mining and fuzzy rule-based reasoning, Advanced Engineering Informatics, 40, pp. 69-80, (2019); Wang X., Xie J., Fan Z.P., B2C cross-border E-commerce logistics mode selection considering product returns, International Journal of Production Research, 42, 1, (2021); Xie H., Ma R.T.B., Lui J.C.S., Enhancing reputation via price discounts in E-commerce systems, ACM Transactions on Knowledge Discovery from Data, 12, 3, pp. 1-29, (2018); Giuffrida M., Mangiaracina R., Perego A., Tumino A., Cross-border B2C e-commerce to China, International Journal of Physical Distribution & Logistics Management, 50, 3, pp. 355-378, (2020); Wu P.J., Lin K.C., Unstructured big data analytics for retrieving e-commerce logistics knowledge, Telematics and Informatics, 35, 1, pp. 237-244, (2018); Kawa A., Supply Chains of Cross-Border E-Commerce//Asian Conference on Intelligent Information and Database Systems, (2017); Zhang H.Z., Hsieh C.M., Luo Y.L., An Investigation of Cross-border E-commerce Logistics and Develop Strategies through SCCOM Framework and Logistic Service Riskanalysis//transdisciplinary Engineering: A Paradigm Shift: Proceedings of the 24th ISPE Inc; Giuffrida M., Mangiaracina R., Perego A., Logistics Solutions to Support Cross Border E-Commerce towards China: The Case of the Apparel Industry//Workshop on Business Models and ICT Technologies for the Fashion Supply Chain, (2016); Giuffrida M., Mangiaracina R., Perego A., Tumino A., Cross-border B2C e-commerce to Greater China and the role of logistics: A literature review, International Journal of Physical Distribution & Logistics Management, 47, 9, pp. 772-795, (2017); Assi K.J., Nahiduzzaman K.M., Ratrout N.T., Aldosary A.S., Mode choice behavior of high school goers: Evaluating logistic regression and MLP neural networks, Case Studies on Transport Policy, 6, 2, pp. 225-230, (2018); Gnap J., Poliak M., Semanova S., The issue of a transport mode choice from the perspective of enterprise logistics, Open Engineering, 9, 1, pp. 374-383, (2019); Cano J.A., Correa-Espinal A.A., Solución del Problema de Conformación de Lotes en Almacenes utilizando Algoritmos Genéticos, Informacion Tecnologica, 29, 6, pp. 235-244, (2018); Larranaga A.M., Arellana J., Senna L.A., Encouraging intermodality: A stated preference analysis of freight mode choice in Rio Grande do sul, Transportation Research Part A: Policy and Practice, 102, pp. 202-211, (2017); Phiophuead T., Kunsuwan N., Logistic regression analysis of factors affecting travel mode choice for disaster evacuation, Engineering Journal, 23, 6, pp. 399-417, (2019); Shin S., Roh H.S., Hur S.H., Characteristics analysis of freight mode choice model according to the introduction of a new freight transport system, Sustainability, 11, 4, (2019); Henning E., Ferreira Schubert T., Ceccatto M.A., Modelling of university student transport mode choice in Joinville: A binary logistic model for active modes, Journal of Sustainable Development of Energy, Water and Environment Systems, 8, 4, pp. 678-691, (2020); Combes F., Tavasszy L.A., Inventory theory, mode choice and network structure in freight transport, European Journal of Transport and Infrastructure Research, 16, 1, pp. 1567-7141, (2016); Hagenauer J., Helbich M., A comparative study of machine learning classifiers for modeling travel mode choice, Expert Systems with Applications, 78, pp. 273-282, (2017); Calastri C., Hess S., Choudhury C., Daly A., Gabrielli L., Mode choice with latent availability and consideration: Theory and a case study, Transportation Research Part B: Methodological, 123, pp. 374-385, (2019); Pirra M., Diana M., A study of tour-based mode choice based on a support vector machine classifier, Transportation Planning and Technology, 42, 1, pp. 23-36, (2019); Brito T.B., Botter R.C., A cross-paradigm simulation framework for complex logistics systems, In Proceedings of the 2017 Winter Simulation Conference (WSC '17), pp. 1-12, (2017); Meena S., Patil G.R., Mondal A., Understanding mode choice decisions for shopping mall trips in metro cities of developing countries, Transportation Research Part F: Traffic Psychology and Behaviour, 64, pp. 133-146, (2019)","W. Zhu; School of Economics and Management, Beijing Jiaotong University, Beijing, China; email: 15113183@bjtu.edu.cn",null,"Hindawi Limited",{"$nulls":5},1.5308669E7,null,null,null,"English","Wireless Commun. Mobile Comput.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85116653742"]
["Jain P.K.; Pamula R.; Ansari S.","Jain, Praphula Kumar (57202970970); Pamula, Rajendra (37015729600); Ansari, Sarfraj (57216269709)","57202970970; 37015729600; 57216269709","A Supervised Machine Learning Approach for the Credibility Assessment of User-Generated Content",2021.0,"Wireless Personal Communications",118.0,4.0,null,2469.0,2485.0,16.0,15.0,"10.1007/s11277-021-08136-5","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85100720759&doi=10.1007%2fs11277-021-08136-5&partnerID=40&md5=da39f4b67bd909891ca65a824fbf20e7","Department of Computer Science and Engineering, Indian Institute of Technology (ISM), Dhanbad, 826004, Jharkhand, India","Jain P.K., Department of Computer Science and Engineering, Indian Institute of Technology (ISM), Dhanbad, 826004, Jharkhand, India; Pamula R., Department of Computer Science and Engineering, Indian Institute of Technology (ISM), Dhanbad, 826004, Jharkhand, India; Ansari S., Department of Computer Science and Engineering, Indian Institute of Technology (ISM), Dhanbad, 826004, Jharkhand, India","Consumers increasingly rely on online reviews to assist them in their buying decisions. The rising popularity of e-commerce websites, hotel reviews, and social media has become a relevant research field in recent years. Online reviews affect people’s decisions in their day-to-day life; the fake review impacts both consumers and business organizations. They need to know how different types of consumers prefer consumer feedback, which influences their opinion. Automatic detection of such reviews is a difficult job, provided that the author writes in such a way that it seems like a real review. Previous work has tackled the identification of fake reviews in many fields, including food reviews or company reviews in a restaurant and hotels. In this study, we proposed a fully supervised approach to distinguish opinion spammers in online reviews. In this work, we have used labeled data that can be useful to classify real and fake reviews. We have also implemented various machine learning algorithms for classification on two different datasets (Yelp hotel review dataset, Yelp restaurant review dataset). We have performed the classification task on the features engineered dataset. Our experiment’s measured results show that Logistic regression performs better than other algorithms on most occasions. We may conclude that the presented study contributes to the existing literature with better accuracy from the obtained results. © 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature.","Fake review; Machine learning; Natural language processing; Online review; Opinion spam","Behavioral research; Classification (of information); Hotels; Learning systems; Logistic regression; Supervised learning; Technology transfer; Automatic Detection; Business organizations; Classification tasks; Credibility assessment; E-commerce websites; Restaurant reviews; Supervised machine learning; User-generated content; Learning algorithms",{"$nulls":6},"Chen Y., Xie J., Online consumer review: Word-of-mouth as a new element of marketing communication mix, Management Science, 54, 3, pp. 477-491, (2008); Ha S.H., Bae S., Son L.K., Impact of online consumer reviews on product sales: Quantitative analysis of the source effect, Applied Mathematics and Information Sciences, 9, 2L, pp. 373-387, (2015); Filieri R., McLeay F., E-wom and accommodation: An analysis of the factors that influence travelers’ adoption of information from online reviews, Journal of Travel Research, 53, 1, pp. 44-57, (2014); Sotiriadis M.D., Van Zyl C., Electronic word-of-mouth and online reviews in tourism services: The use of twitter by tourists, Electronic Commerce Research, 13, 1, pp. 103-124, (2013); Hernandez-Nieves E., Hernandez G., Gil-Gonzalez A.-B., Rodriguez-Gonzalez S., Corchado J.M., Fog computing architecture for personalized recommendation of banking products, Expert Systems with Applications, 140, (2020); Opinion spam and analysis, In Proceedings of the 2008 International Conference on Web Search and Data Mining, pp. 219-230, (2008); Mukherjee A., Detecting deceptive opinion spam using linguistics, behavioral and statistical modeling, Proceedings of the 53Rd Annual Meeting of the Association for Computational Linguistics and the 7Th International Joint Conference on Natural Language Processing: Tutorial Abstracts, pp. 21-22, (2015); Reducing permission requests in mobile apps, Proceedings of the Internet Measurement Conference, pp. 259-266, (2019); Rudolph S., The Impact of Online Reviews on customers’ Buying Decisions; Alothali E., Zaki N., Mohamed E.A., Alashwal H., Detecting social bots on twitter: A literature review, In 2018 International Conference on Innovations in Information Technology (IIT), IEEE, 2018 (Pp, pp. 175-180, (2018); Gillum E.C., Ke Q., Xie Y., Yu F., Zhao Y., Graph based bot-user detection, uS Patent 8,069,210 (Nov, 29), (2011); Kudugunta S., Ferrara E., Deep neural networks for bot detection, Information Sciences, 467, pp. 312-322, (2018); Ott M., Choi Y., Cardie C., Hancock J.T., Finding deceptive opinion spam by any stretch of the imagination. 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Effects of verbal and nonverbal behaviors on detection of fake online reviews, Journal of Management Information Systems, 33, 2, pp. 456-481, (2016); Keiningham T.L., Cooil B., Andreassen T.W., Aksoy L., A longitudinal examination of net promoter and firm revenue growth, Journal of Marketing, 71, 3, pp. 39-51, (2007); Jang S., Prasad A., Ratchford B.T., How consumers use product reviews in the purchase decision process, Marketing Letters, 23, 3, pp. 825-838, (2012); Mudambi S.M., Schuff D., Research note: What makes a helpful online review? a study of customer reviews on amazon. com, MIS Quarterly, pp. 185-200, (2010); Ye Q., Law R., Gu B., Chen W., The influence of user-generated content on traveler behavior: An empirical investigation on the effects of e-word-of-mouth to hotel online bookings, Computers in Human behavior, 27, 2, pp. 634-639, (2011); Yin D., Bond S.D., Zhang H., Anxious or angry? effects of discrete emotions on the perceived helpfulness of online reviews, MIS Quarterly, 38, 2, pp. 539-560, (2014); Reichheld F.F., The one number you need to grow, Harvard Business Review, 81, 12, pp. 46-55, (2003); Ding X., Liu B., Yu P.S., A holistic lexicon-based approach to opinion mining, In Proceedings of the 2008 International Conference on Web Search and Data Mining, pp. 231-240, (2008); Mukherjee A., Kumar A., Liu B., Wang J., Hsu M., Castellanos M., Ghosh R., Spotting opinion spammers using behavioral footprints, In Proceedings of the 19Th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 632-640, (2013); Wang G., Xie S., Liu B., Philip S.Y., Review graph based online store review spammer detection. In 2011 IEEE 11th international conference on data mining, IEEE, pp. 1242-1247, (2011); Xie S., Wang G., Lin S., Yu P.S., Review spam detection via temporal pattern discovery, In Proceedings of the 18Th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 823-831, (2012); Fei G., Mukherjee A., Liu B., Hsu M., Castellanos M., Ghosh R., Seventh international AAAI conference on weblogs and social media, Exploiting Burstiness in Reviews for Review Spammer Detection, (2013); Lim E.-P., Nguyen V.-A., Jindal N., Liu B., Lauw H.W., Detecting product review spammers using rating behaviors, In Proceedings of the 19Th ACM International Conference on Information and Knowledge Management, pp. 939-948, (2010); Ott M., Cardie C., Hancock J., Estimating the prevalence of deception in online review communities, In Proceedings of the 21St International Conference on World Wide Web, pp. 201-210, (2012); Mukherjee A., Venkataraman V., Liu B., Glance N., What yelp fake review filter might be doing?, In Seventh International AAAI Conference on Weblogs and Social Media, (2013); Fornaciari T., Poesio M., Identifying fake amazon reviews as learning from crowds; Dewang R.K., Singh A., Identification of fake reviews using new set of lexical and syntactic features, Proceedings of the Sixth International Conference on Computer and Communication Technology, 2015, pp. 115-119, (2015); Fusilier D.H., Montes-y Gomez M., Rosso P., Cabrera R.G., Detecting positive and negative deceptive opinions using pu-learning, Information Processing & Management, 51, 4, pp. 433-443, (2015); Li Y., Feng X., Zhang S., Detecting fake reviews utilizing semantic and emotion model, In 2016 3Rd International Conference on Information Science and Control Engineering (ICISCE), IEEE (Pp, pp. 317-320, (2016); Albitar S., Fournier S., Espinasse B., An Effective Tf/Idf-Based Text-To-Text Semantic Similarity Measure for Text Classification, pp. 105-114, (2014); Dwoskin E., Timberg C., How Merchants Use Facebook to Flood Amazon with Fake Reviews, Washington Post; Martin-Fuentes E., Mateu C., Fernandez C., Does verifying uses influence rankings? analyzing booking. com and tripadvisor, Tourism Analysis, 23, 1, pp. 1-15, (2018); McNamee R., Zucked: Waking up to the Facebook catastrophe, (2020)","P.K. Jain; Department of Computer Science and Engineering, Indian Institute of Technology (ISM), Dhanbad, 826004, India; email: praphulajn1@gmail.com",null,"Springer",{"$nulls":5},9296212.0,null,"WPCOF",null,"English","Wireless Pers Commun","Article","Final",null,"Scopus","2-s2.0-85100720759"]
["Dong Y.; Xiao C.; Chen H.; Yu J.X.; Takeoka K.; Oyamada M.; Kitagawa H.","Dong, Yuyang (57190569998); Xiao, Chuan (7202240345); Chen, Hanxiong (9433858500); Yu, Jeffrey Xu (57203435589); Takeoka, Kunihiro (57218799401); Oyamada, Masafumi (56335818200); Kitagawa, Hiroyuki (7402625746)","57190569998; 7202240345; 9433858500; 57203435589; 57218799401; 56335818200; 7402625746","Continuous top-k spatial–keyword search on dynamic objects",2021.0,"VLDB Journal",30.0,2.0,null,141.0,161.0,20.0,8.0,"10.1007/s00778-020-00627-4","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85090317106&doi=10.1007%2fs00778-020-00627-4&partnerID=40&md5=18afb9cb7c83ba933bcf7aa694415efe","NEC Corporation, Tokyo, Japan; Osaka University, Osaka, Japan; Nagoya University, Nagoya, Japan; University of Tsukuba, Tsukuba, Japan; Chinese University of Hong Kong, Hong Kong","Dong Y., NEC Corporation, Tokyo, Japan; Xiao C., Osaka University, Osaka, Japan, Nagoya University, Nagoya, Japan; Chen H., University of Tsukuba, Tsukuba, Japan; Yu J.X., Chinese University of Hong Kong, Hong Kong; Takeoka K., NEC Corporation, Tokyo, Japan; Oyamada M., NEC Corporation, Tokyo, Japan; Kitagawa H., University of Tsukuba, Tsukuba, Japan","As the popularity of SNS- and GPS-equipped mobile devices rapidly grows, numerous location-based applications have emerged. A common scenario is that a large number of users change location and interests from time to time; e.g., a user watches news, blogs, and videos while moving outside. Many online services have been developed based on continuously querying spatial–keyword objects. For instance, Twitter adjusts advertisements based on the location and the content of the message a user has just tweeted. In this paper, we investigate the case of dynamic spatial–keyword objects whose locations and keywords change over time. We study the problem of continuously tracking top-k dynamic spatial–keyword objects for a given set of queries. Answering this type of queries benefits many location-aware services such as e-commerce potential customer identification, drone delivery, and self-driving stores. We develop a solution based on a grid index. To deal with the changing locations and keywords of objects, our solution first finds the set of queries whose results are affected by the change and then updates the results of these queries. We propose a series of indexing and query processing techniques to accelerate the two procedures. We also discuss batch processing to cope with the case when multiple objects change locations and keywords in a time interval and top-k results are reported afterward. Experiments on real and synthetic datasets demonstrate the efficiency of our method and its superiority over alternative solutions. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature.","Dynamic object; Spatial–keyword search; Spatio-temporal databases; Top-k retrieval","Batch data processing; Indexing (materials working); Location; Mobile telecommunication systems; Search engines; Alternative solutions; Dynamic spatial; Location aware services; Location-based applications; Multiple objects; Potential customers; Query processing techniques; Synthetic datasets; Object tracking",{"$nulls":4},"Japan Society for the Promotion of Science, KAKEN, (17H06099, 18H04093, 19K11979, 19K12114); Research Grants Council, University Grants Committee, RGC, UGC, (14202919, 14203618, 19H04114)","Chuan Xiao was supported by JSPS Kakenhi 17H06099, 18H04093, and 19K11979. Hanxiong Chen was supported by JSPS Kakenhi 19K12114. Jeffrey Xu Yu was supported by the Research Grants Council of Hong Kong, China, Nos. 14203618 and 14202919. Hiroyuki Kitagawa was supported by JSPS Kakenhi 19H04114. ","Agrawal P., Arasu A., Kaushik R., On indexing error-tolerant set containment, SIGMOD, pp. 927-938, (2010); Ahuja R., Armenatzoglou N., Papadias D., Fakas G.J., Geo-social keyword search, SSTD, Pp. 431–450, (2015); Bayardo R.J., Ma Y., Srikant R., Scaling up all pairs similarity search, WWW, pp. 131-140, (2007); Chaudhuri S., Ganti V., Kaushik R., A primitive operator for similarity joins in data cleaning, ICDE, (2006); Chen L., Cong G., Cao X., An efficient query indexing mechanism for filtering geo-textual data, SIGMOD, pp. 749-760, (2013); Chen L., Cong G., Cao X., Tan K., Temporal spatial-keyword top-k publish/subscribe, ICDE, pp. 255-266, (2015); Chen L., Cong G., Jensen C.S., Wu D., Spatial keyword query processing: an experimental evaluation, PVLDB, 6, 3, pp. 217-228, (2013); Chen L., Shang S., Zhang Z., Cao X., Jensen C.S., Kalnis P., Location-aware top-k term publish/subscribe, ICDE, pp. 749-760, (2018); Cong G., Jensen C.S., Querying geo-textual data: Spatial keyword queries and beyond, SIGMOD, pp. 2207-2212, (2016); Cong G., Jensen C.S., Wu D., Efficient retrieval of the top-k most relevant spatial web objects, PVLDB, 2, 1, pp. 337-348, (2009); Dong Y., Chen H., Kitagawa H., Continuous search on dynamic spatial keyword objects, ICDE, pp. 1578-1581, (2019); Duntgen C., Behr T., Guting R.H., Berlinmod: a benchmark for moving object databases, VLDB J., 18, 6, pp. 1335-1368, (2009); Foursquare Check-In Dataset, (2019); Gao Y., Qin X., Zheng B., Chen G., Efficient reverse top-k boolean spatial keyword queries on road networks, IEEE Trans. Knowl. Data Eng., 27, 5, pp. 1205-1218, (2015); Guo L., Shao J., Aung H.H., Tan K., Efficient continuous top-k spatial keyword queries on road networks, Geoinformatica, 19, 1, pp. 29-60, (2015); Guo L., Zhang D., Li G., Tan K., Bao Z., Location-aware pub/sub system: When continuous moving queries meet dynamic event streams, SIGMOD, pp. 843-857, (2015); Huang W., Li G., Tan K., Feng J., Efficient safe-region construction for moving top-k spatial keyword queries, CIKM, pp. 932-941, (2012); Li G., Wang Y., Wang T., Feng J., Location-aware publish/subscribe, KDD, Pp. 802–810, (2013); Lu Y., Cong G., Lu J., Shahabi C., Efficient algorithms for answering reverse spatial-keyword nearest neighbor queries, SIGSPATIAL/GIS, pp. 1-82, (2015); Lu Y., Lu J., Cong G., Wu W., Shahabi C., Efficient algorithms and cost models for reverse spatial-keyword k-nearest neighbor search, ACM Trans. Database Syst., 39, 2, pp. 13:1-13:46, (2014); Mahmood A.R., Aref W.G., Query processing techniques for big spatial-keyword data, SIGMOD, pp. 1777-1782, (2017); Mann W., Augsten N., Bouros P., An empirical evaluation of set similarity join techniques, PVLDB, 9, 9, pp. 636-647, (2016); Mouratidis K., Bakiras S., Papadias D., Continuous monitoring of top-k queries over sliding windows, SIGMOD, pp. 635-646, (2006); Mouratidis K., Hadjieleftheriou M., Papadias D., Conceptual partitioning: An efficient method for continuous nearest neighbor monitoring, SIGMOD, pp. 634-645, (2005); Open Data: Green Taxi Trip Data, (2016); Rocha-Junior J.B., Gkorgkas O., Jonassen S., Norvag K., Efficient processing of top-k spatial keyword queries, SSTD, pp. 205-222, (2011); Twitter. Geotagged Tweets from the Us., (2016); Wang J., Li G., Feng J., Can we beat the prefix filtering?, An Adaptive Framework for Similarity Join and Search, pp. 85-96, (2012); Wang P., Xiao C., Qin J., Wang W., Zhang X., Ishikawa Y., Local similarity search for unstructured text, SIGMOD, pp. 1991-2005, (2016); Wang X., Qin L., Lin X., Zhang Y., Chang L., Leveraging set relations in exact and dynamic set similarity join, VLDB J., 28, 2, pp. 267-292, (2019); Wang X., Zhang Y., Zhang W., Lin X., Huang Z., SKYPE: top-k spatial-keyword publish/subscribe over sliding window, PVLDB, 9, 7, pp. 588-599, (2016); Wang X., Zhang Y., Zhang W., Lin X., Wang W., Ap-tree: efficiently support location-aware publish/subscribe, VLDB J., 24, 6, pp. 823-848, (2015); Wu D., Yiu M.L., Jensen C.S., Moving spatial keyword queries: Formulation, methods, and analysis, ACM Trans. Database Syst., 38, 1, pp. 1-7, (2013); Xiao C., Wang W., Lin X., Yu J.X., Wang G., Efficient similarity joins for near-duplicate detection, ACM Trans. Database Syst., 36, 3, pp. 15:1-15:41, (2011); Xiong X., Mokbel M.F., Aref W.G., SEA-CNN: Scalable processing of continuous k-nearest neighbor queries in spatio-temporal databases, ICDE, pp. 643-654, (2005); Yang D., Zhang D., Zheng V.W., Yu Z., Modeling user activity preference by leveraging user spatial temporal characteristics in lbsns, IEEE Trans. Syst. Man Cybern. Syst., 45, 1, pp. 129-142, (2015); Yao Z., Fu Y., Liu B., Liu Y., Xiong H., POI recommendation: A temporal matching between POI popularity and user regularity, ICDM, pp. 549-558, (2016); Yelp, Yelp Dataset., (2019); Yi K., Yu H., Yang J., Xia G., Chen Y., Efficient maintenance of materialized top-k views, ICDE, pp. 189-200, (2003); Young N.E., Greedy set-cover algorithms, Encyclopedia of Algorithms., (2008); Yu X., Pu K.Q., Koudas N., Monitoring k-nearest neighbor queries over moving objects, ICDE, pp. 631-642, (2005); Zhao J., Gao Y., Chen G., Jensen C.S., Chen R., Cai D., Reverse top-k geo-social keyword queries in road networks, ICDE, pp. 387-398, (2017); Zheng B., Zheng K., Xiao X., Su H., Yin H., Zhou X., Li G., Keyword-aware continuous kNN query on road networks, ICDE, pp. 871-882, (2016)","C. Xiao; Osaka University, Osaka, Japan; email: chuanx@ist.osaka-u.ac.jp",null,"Springer Science and Business Media Deutschland GmbH",{"$nulls":5},1.0668888E7,null,null,null,"English","VLDB J.","Article","Final",null,"Scopus","2-s2.0-85090317106"]
["Miler R.K.; Kuriata A.; Brzozowska A.; Akoel A.; Kalinichenko A.","Miler, Ryszard K. (56288717200); Kuriata, Andrzej (57219313902); Brzozowska, Anna (56009729100); Akoel, Akram (57226559566); Kalinichenko, Antonina (56328180300)","56288717200; 57219313902; 56009729100; 57226559566; 56328180300","The algorithm of a game-based system in the relation between an operator and a technical object in management of e-commerce logistics processes with the use of machine learning",2021.0,"Sensors",21.0,15.0,5244.0,null,null,null,0.0,"10.3390/s21155244","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85112005555&doi=10.3390%2fs21155244&partnerID=40&md5=78b72451eb8a54b50f5d6ca3581a198c","Faculty of Management and Finance, WSB University in Gdańsk, Gdańsk, 80-266, Poland; Faculty of Management, Czestochowa University of Technology, Częstochowa, 42-201, Poland; The Briese Schiffahrts GmbH and Co. KG, Hafenstraße 12, Leer, 26789, Germany; Institute of Environmental Engineering and Biotechnology, University of Opole, Opole, 45-040, Poland; Department of Information System and Technology, Poltava State Agrarian Academy, Poltava, 36003, Ukraine","Miler R.K., Faculty of Management and Finance, WSB University in Gdańsk, Gdańsk, 80-266, Poland; Kuriata A., Faculty of Management and Finance, WSB University in Gdańsk, Gdańsk, 80-266, Poland; Brzozowska A., Faculty of Management, Czestochowa University of Technology, Częstochowa, 42-201, Poland; Akoel A., The Briese Schiffahrts GmbH and Co. KG, Hafenstraße 12, Leer, 26789, Germany; Kalinichenko A., Institute of Environmental Engineering and Biotechnology, University of Opole, Opole, 45-040, Poland, Department of Information System and Technology, Poltava State Agrarian Academy, Poltava, 36003, Ukraine","Machine learning (ML) is applied in various logistic processes utilizing innovative techniques (e.g., the use of drones for automated delivery in e-commerce). Early challenges showed the insufficient drones’ steering capacity and cognitive gap related to the lack of theoretical foundation for controlling algorithms. The aim of this paper is to present a game-based algorithm of controlling behaviours in the relation between an operator (OP) and a technical object (TO), based on the assumption that the game is logistics-oriented and the algorithm is to support ML applied in e-commerce optimization management. Algebraic methods, including matrices, Lagrange functions, systems of differential equations, and set-theoretic notation, have been used as the main tools. The outcome is a model of a game-based optimization process in a two-element logistics system and an algorithm applied to find optimal steering strategies. The algorithm has been initially verified with the use of simulation based on a Bayesian network (BN) and a structured set of possible strategies (OP/TO) calculated with the use of QGeNie Modeller, finally prepared for Python. It has been proved the algorithm at this stage has no deadlocks and unforeseen loops and is ready to be challenged with the original big set of learning data from a drone-operating company (as the next stage of the planned research). © 2021 by the authors. Licensee MDPI, Basel, Switzerland.","A game-based system; A logistics zero-sum game; Bayesian network; E-commerce; Machine learning algorithms","Algorithms; Bayes Theorem; Commerce; Computer Simulation; Humans; Machine Learning; Algebra; Bayesian networks; Computer software; Differential equations; Drones; Electronic commerce; Learning algorithms; Innovative techniques; Lagrange functions; Logistics process; Operating companies; Optimization managements; Systems of differential equations; Technical objects; Theoretical foundations; algorithm; Bayes theorem; commercial phenomena; computer simulation; human; machine learning; Machine learning",{"$nulls":6},"Clarke R., Electronic Commerce Definition, (1999); Wang B., Liu Y., Parker K.S., How does the use of information communication technology affect individuals? A work design perspective, Annals, 14, pp. 695-725, (2020); Zwass V., Electronic commerce: Structure and issues, Int. J. Electron. Commer. 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Res, 16, pp. 937-958, (2021); Du X., Gao Y., Chang L., Lang X., Xue X., Bi D., Assessing the application of big data technology in platform business model: A hierarchical framework, PLoS ONE, 15, (2020); Pabian A., Pabian B., Reformat B., E-Customer Security as a Social Value in the Sphere of Sustainability, Sustainability, 12, (2020); Jiang Y., Lai P., Chang C.-H., Yuen K.F., Li S., Wang X., Sustainable Management for Fresh Food E-Commerce Logistics Services, Sustainability, 136, (2021); Khrais L.T., Alghamdi A.M., The Role of Mobile Application Acceptance in Shaping E-Customer Service, Future Internet, 13, (2021); Hussain A., Shahzad A., Hassan R., Organizational and Environmental Factors with the Mediating Role of E-Commerce and SME Performance, J. Open Innov. Technol. Mark. Complex, 6, (2020); Wang C.N., Dang T.T., Nguyen N.A.T., Outsourcing Reverse Logistics for E-Commerce Retailers. 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Teoria Oraz Praktyczne Zastosowania, (2019); Kordel Z., Kuriata A., Logistyka i Transport w Ujęciu Systemowym, (2018); Massimino B., Accessing Online Data: Web-Crawling and Information-Scraping Techniques to Automate the Assembly of Research Data, J. Busin. Logist, 37, pp. 34-42, (2016); Raj A., Biswas I., Srivastava K.S., Designing supply contracts for the sustainable supply chain using game theory, J. Clean Prod, 185, pp. 275-284, (2018); Hamister J., Magazine M., Polak G., Integrating Analytics through the Big Data Information Chain: A Case from Supply Chain Management, J. Busin. Logist, (2018); Beyerer J., Nagel M., Richter M., Pattern Recognition, (2017); Chena Y.-W., Larbani M., Two-person zero-sum game approach for fuzzy multiple attribute decision making problems, Fuzzy Sets Syst, 157, pp. 34-51, (2006); Haller G., Lagrangian Coherent Structures, Ann. Rev. Fluid Mechan, 47, pp. 137-162, (2015); Goldsby T.J., Zinn W., Technology Innovation and New Business Models: Can Logistics and Supply Chain Research Accelerate the Evolution?, J. Busin. Logist, 37, pp. 80-81, (2016); Sanders N.R., Boone T., Ganeshan R., Wood J.D., Sustainable Supply Chains in the Age of AI and Digitization: Research Challenges and Opportunities, J. Busin. Logist, 40, pp. 229-240, (2019); Teschendorff A.E., Avoiding common pitfalls in machine learning omic data science, Nat. Mater, 18, pp. 422-427, (2019); Klumpp M., Zijm W.H.M., Logistics Innovation and Social Sustainability: How to Prevent an Artificial Divide in Human-Computer Interaction, J. Busin. Logist, 40, pp. 265-278, (2019); Hong P., Schoenherr T., Hult G.T.M., Zinn W., Goldsby T., Cross-functional Management and Base-of-Pyramid Issues in Logistics and Supply Chain Management, J. Busin. Logist, 40, pp. 76-80, (2019); Miller J., Ganster D., Griffis S., Leveraging Big Data to Develop Supply Chain Management Theory: The Case of Panel Data, J. Busin. Logist, 39, pp. 182-202, (2018); Kopishynska O., Utkin Y., Kalinichenko A., Jelonek D., Efficacy of the cloud computing technology in the management of communication and business processes of the companies, Pol. J. Manag. Stud, 14, pp. 104-114, (2016); Larranaga P., Atienza D., Diaz-Rozo J., Ogbechie A., Puerto-Santana C., Bielza C., Industrial Applications of Machine Learning, (2018)","A. Kalinichenko; Institute of Environmental Engineering and Biotechnology, University of Opole, Opole, 45-040, Poland; email: akalinichenko@uni.opole.pl",null,"MDPI AG",{"$nulls":5},1.424822E7,null,null,3.437248E7,"English","Sensors","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85112005555"]
["Yoon Y.L.; Yoon Y.; Nam H.; Choi J.","Yoon, Yeo Lim (57221760250); Yoon, Yeohong (57205513693); Nam, Hyoryung (56486921300); Choi, Jeonghye (49862944700)","57221760250; 57205513693; 56486921300; 49862944700","Buyer-supplier matching in online B2B marketplace: An empirical study of small- and medium-sized enterprises (SMEs)",2021.0,"Industrial Marketing Management",93.0,null,null,90.0,100.0,10.0,23.0,"10.1016/j.indmarman.2020.12.010","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85100124156&doi=10.1016%2fj.indmarman.2020.12.010&partnerID=40&md5=0f57cff5d25852b04686c595ff225750","School of Business, Yonsei University, Seoul, South Korea; Department of Marketing, Whitman School of Management, Syracuse University, Syracuse, New York, 13244, United States","Yoon Y.L., School of Business, Yonsei University, Seoul, South Korea; Yoon Y., School of Business, Yonsei University, Seoul, South Korea; Nam H., Department of Marketing, Whitman School of Management, Syracuse University, Syracuse, New York, 13244, United States; Choi J., School of Business, Yonsei University, Seoul, South Korea","Mitigating perceived uncertainty and risk is critical for successful exchanges in an online B2B marketplace. However, scant empirical research has been devoted to the topic, and even less to small- and medium-sized enterprises (SMEs). We investigate the use of quality signals and recommendations to foster buyer-supplier matching in an online B2B marketplace of SMEs. Unique proprietary data from a leading B2B e-commerce platform suggest that such a matching is significantly related to signals of SME buyers' quality and credibility embedded in how projects are described. Moreover, appropriately designed recommendation system can increase the matching rate because it helps reduce buyers' information overload. This research highlights the importance of integrating online channel data with traditional offline channel data to accurately assess the drivers of buyer-supplier matching. Our findings provide valuable insights into how to design and manage an online B2B marketplace for SMEs to yield more successful matches. © 2020","B2B e-commerce; Buyer-supplier matching; Digital platform; Multinomial logistic regression; SMEs",{"$nulls":5},"Yonsei University; Ministry of Education, MOE; National Research Foundation of Korea, NRF, (NRF-2020S1A3A2A02093277)","The authors are grateful to the B2B e-commerce platform company for generously sharing data. This work was supported by the Yonsei University Research Grant of 2020. This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea ( NRF-2020S1A3A2A02093277 ).","Alderete M.V., Do information and communication technology access and innovation increase outsourcing in small and medium enterprises?, Journal of Information Systems and Technology Management, 10, 2, pp. 303-322, (2013); Allocca M.A., Kessler E.H., Innovation speed in small and medium-sized enterprises, Creativity and Innovation Management, 15, 3, pp. 279-295, (2006); Bakos J.Y., Brynjolfsson E., Information technology, incentives, and the optimal number of suppliers, Journal of Management Information Systems, 10, 2, pp. 37-53, (1993); Balakrishnan S., Koza M.P., Information asymmetry, adverse selection and joing venture, Journal of Economic Behavior and Organization, 20, 1, pp. 99-117, (1993); Barthelemy J., Geyer D., The determinants of total IT outsourcing: An empirical investigation of French and German firms, Journal of Computer Information Systems, 44, 3, pp. 91-97, (2004); 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Li J., Netessine S., Higher market thickness reduces matching rate in online platforms: Evidence from a quasiexperiment, Management Science, 66, 1, pp. 271-289, (2020); Malaska M., Saraniemi S., Tahtinen J., Network actors’ participation in B2B SME branding, Industrial Marketing Management, 40, 7, pp. 1144-1152, (2011); McIvor R., How the transaction cost and resource-based theories of the firm inform outsourcing evaluation, Journal of Operations Management, 27, 1, pp. 45-63, (2009); Merrilees B., Fenech T., From catalog to web: B2B multi-channel marketing strategy, Industrial Marketing Management, 36, 1, pp. 44-49, (2007); Merrilees B., Rundle-Thiele S., Lye A., Marketing capabilities: Antecedents and implications for B2B SME performance, Industrial Marketing Management, 40, 3, pp. 368-375, (2011); Mo J.P.T., Chan A.M.S., Strategy for the successful implementation of ISO 9000 in small and medium manufacturers, The TQM Magazine, 9, 2, pp. 135-145, (1997); Morgan R.M., Hunt S.D., The commitment-trust theory of relationship marketing, Journal of Marketing, 58, 3, (1994); 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Choi; School of Business, Yonsei University, Seoul, South Korea; email: jeonghye@yonsei.ac.kr",null,"Elsevier Inc.",{"$nulls":5},198501.0,null,"IMMAD",null,"English","Ind. Mark. Manage.","Article","Final",null,"Scopus","2-s2.0-85100124156"]
["Buldeo Rai H.","Buldeo Rai, Heleen (57195135422)",5.7195135422E10,"The net environmental impact of online shopping, beyond the substitution bias",2021.0,"Journal of Transport Geography",93.0,null,103058.0,null,null,null,22.0,"10.1016/j.jtrangeo.2021.103058","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85104445943&doi=10.1016%2fj.jtrangeo.2021.103058&partnerID=40&md5=716a66b0cfbd72a56fbac37fa241fd45","Univ Gustave Eiffel, Logistics City Chair, France","Buldeo Rai H., Univ Gustave Eiffel, Logistics City Chair, France","Internet, digitalisation and access to technology have transformed contemporary consumption patterns and habits. Whether or not these changes hold beneficial or detrimental implications for society is subject to ongoing debate. Specifically concerning the environmental impacts of online and omnichannel retail, claims have been made on both sides: crediting the efficiency of home deliveries versus individual shopping trips on the one hand and pointing out complex consumer behaviour on the other hand. Despite intensive research efforts, a solid consensus lacks. The disperse and contradicting scientific knowledge base that is currently available prevents policymakers and practitioners from implementing sustainability improving measures and from steering consumers towards sustainable practices. Supported by a systematic review of the literature, this article presents a framework for understanding the net environmental sustainability of shopping. The debate is broken down in three impact categories that need to be considered simultaneously: individual purchases, consumer behaviour and consumption geography. The majority of research articles focus on the environmental impact of purchasing a single item or a basket of items, in which in-store purchases are substituted by purchases online. Such studies conclude in favour of e-commerce. The balance shifts when taking changes in behaviour and geography into consideration. While behavioural reflections are on the rise, hardly any empirical work takes the spatial (re)organisation of businesses and consumers into account. The article surpasses the case-study approach and in doing so comprises the body of literature in a solid framework that is able to guide future discussions and research in more sustainable directions. © 2021 Elsevier Ltd","Conceptual framework; E-commerce; Environmental sustainability; Mobility; Omnichannel retail; Online shopping; Transport","conceptual framework; consumption behavior; electronic commerce; environmental impact; Internet; retailing; shopping activity",{"$nulls":6},"Belavina E., Girotra K., Kabra A., Online grocery retail: revenue models and environmental impact, Manag. Sci., 63, pp. 1781-1799, (2016); Bjorgen A., Bjerkan K.Y., Hjelkrem O.A., E-groceries: sustainable last mile distribution in city planning, Res. Transp. Econ., (2019); Borggren C., Moberg A., Finnveden G., Books from an environmental perspective-part 1: environmental impacts of paper books sold in traditional and internet bookshops, Int. J. Life Cycle Assess., 16, pp. 138-147, (2011); Brown J.R., Guiffrida A.L., Carbon emissions comparison of last mile delivery versus customer pickup, Int J Log Res Appl, 17, pp. 503-521, (2014); Buldeo Rai H., Mommens K., Verlinde S., Macharis C., How does Consumers’ Omnichannel shopping behaviour translate into travel and transport impacts? Case-Study of a Footwear Retailer in Belgium, Sustainability, 11, (2019); Cairns S., Delivering supermarket shopping: more or less traffic?, Transp. Rev., 25, pp. 51-84, (2005); Cullinane S., From bricks to clicks: the impact of online retailing on transport and the environment, Transp. Rev., 29, pp. 759-776, (2009); Durand B., Gonzalez-Feliu J., Impacts of proximity deliveries on e-grocery trips, Supply Chain Forum An Int. J., 13, pp. 10-19, (2012); Edwards J., McKinnon A., Cullinane S., Comparative analysis of the carbon footprints of conventional and online retailing: a “last mile” perspective, Int. J. Phys. Distrib. Logist. Manag., 40, pp. 103-123, (2010); European Commission, A European Retail Sector Fit for the 21st Century, (2018); Fernie J., Sparks L., Logistics & Retail Management. Emerging Issues and New Challenges in the Retail Supply Chain, (2009); Figliozzi M.A., Carbon emissions reductions in last mile and grocery deliveries utilizing air and ground autonomous vehicles, Transp. Res. Part D Transp. Environ., 85, (2020); Frick V., Matthies E., Everything is just a click away. Online shopping efficiency and consumption levels in three consumption domains, Sustain. Prod. Consum., 23, pp. 212-223, (2020); Gee I.M., Davidson F.T., Speetles B.L., Webber M.E., Deliver me from food waste: model framework for comparing the energy use of meal-kit delivery and groceries, J. Clean. Prod., 236, (2019); Goodchild A., Wygonik E., Mayes N., An analytical model for vehicle miles traveled and carbon emissions for goods delivery scenarios, Eur. Transp. Res. Rev., 10, (2018); Guy C., ‘Sustainable transport choices’ in consumer shopping: a review of the UK evidence, Int. J. Consum. Stud., 33, pp. 652-658, (2009); Hagberg J., Holmberg U., Travel modes in grocery shopping, Int. J. Retail Distrib. Manag., 45, pp. 991-1010, (2017); Hardi L., Wagner U., Grocery delivery or customer pickup — influences on energy consumption and CO2 emissions in Munich, Sustain., 11, (2019); Heard B.R., Bandekar M., Vassar B., Miller S.A., Comparison of life cycle environmental impacts from meal kits and grocery store meals, Resour. Conserv. Recycl., 147, pp. 189-200, (2019); Hischier R., Car vs. packaging—a first, simple (environmental) sustainability assessment of our changing shopping behaviour, Sustainability, 10, (2018); Jaller M., Pahwa A., Evaluating the environmental impacts of online shopping: a behavioral and transportation approach, Transp. Res. Part D Transp. Environ., 80, (2020); Jiao J., Vernez Moudon A., Drewnowski A., Grocery shopping how individuals and built environments influence choice of travel mode, Transp. Res. Rec. J. Transp. Res. Board, 2230, pp. 85-95, (2011); Karbassi S., Tehrani A., Application of E-commerce in local home shopping and its consequences on energy consumption and air pollution reduction, J. Environ. Health Sci. Eng., 2, pp. 247-250, (2005); Kellner F., Igl J., Estimating the effect of changing retailing structures on the greenhouse gas performance of FMCG distribution networks, Logist. Res., 4, pp. 87-99, (2012); Kim J., Xu M., Kahhat R., Allenby B., Williams E., Designing and assessing a sustainable networked delivery (SND) system: hybrid business-to-consumer book delivery case study, Environ. Sci. Technol., 43, pp. 181-187, (2009); Laghaei J., Faghri A., Li M., Impacts of home shopping on vehicle operations and greenhouse gas emissions: multi-year regional study, Int. J. Sustain. Dev. World Ecol., 4509, pp. 1-11, (2015); Lagorio A., Pinto R., Golini R., Research in urban logistics: a systematic literature review, Int. J. Phys. Distrib. Logist. Manag., 46, pp. 908-931, (2016); Lazaris C., Vrechopoulos A., From multichannel to “Omnichannel” retailing: Review of the literature and calls for research, 2nd International Conference on Contemporary Marketing Issues, (2013); Mangiaracina R., Marchet G., Perotti S., Tumino A., A review of the environmental implications of B2C e-commerce: a logistics perspective, Int. J. Phys. Distrib. Logist. Manag., 45, pp. 565-591, (2015); Mangiaracina R., Perego A., Perotti S., Tumino A., Assessing the environmental impact of logistics in online and offline B2C purchasing processes in the apparel industry, Int. J. Logist. Syst. Manag., 23, (2016); Matustik J., Koci V., A comparative life cycle assessment of electronic retail of household products, Sustainability, 12, pp. 1-13, (2020); Melacini M., Tappia E., A critical comparison of alternative distribution configurations in Omni-Channel retailing in terms of cost and greenhouse gas emissions, Sustainability, 10, pp. 1-15, (2018); OECD, OECD Guide to Measuring the Information Society, (2011); Palsson H., Pettersson F., Winslott Hiselius L., Energy consumption in e-commerce versus conventional trade channels - insights into packaging, the last mile, unsold products and product returns, J. Clean. 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Empirical evidence from Chengdu, China, Transp. Res. Part A., (2019); Van Loon P., Deketele L., Dewaele J., McKinnon A., Rutherford C., A comparative analysis of carbon emissions from online retailing of fast moving consumer goods, J. Clean. Prod., 106, pp. 478-486, (2015); Verhoef P.C., Kannan P.K., Inman J.J., From Multi-Channel retailing to Omni-Channel retailing. Introduction to the special issue on multi-channel retailing, J. Retail., 91, pp. 174-181, (2015); WHO, Health in the Green Economy: Health Co-Benefits of Climate Change Mitigation – Transport Sector. Geneva, Switzerland, (2011); Wiese A., Toporowski W., Zielke S., Transport-related CO2 effects of online and brick-and-mortar shopping: a comparison and sensitivity analysis of clothing retailing, Transp. Res. Part D Transp. Environ., 17, pp. 473-477, (2012); Wygonik E., Goodchild A., Evaluating the efficacy of shared-use vehicles for reducing greenhouse gas emissions: A U.S. case study of grocery delivery, J. Transp. Res. Forum, (2012); Wygonik E., Goodchild A., Urban form and last-mile goods movement: factors affecting vehicle miles travelled and emissions, Transp. Res. Part D, 61, pp. 217-229, (2016); Zhang L., Zhang Y., A comparative study of environmental impacts of two delivery systems in the business-to-customer book retail sector, J. Ind. Ecol., 17, pp. 407-417, (2013)",null,null,"Elsevier Ltd",{"$nulls":5},9666923.0,null,null,null,"English","J. Transp. Geogr.","Article","Final","All Open Access; Bronze Open Access; Green Open Access","Scopus","2-s2.0-85104445943"]
["Yang S.; Zhang Y.; Ma L.; Song Y.; Zhou P.; Shi G.; Chen H.","Yang, Shujun (57218685290); Zhang, Yichuan (36645402000); Ma, Lianbo (35117920700); Song, Yan (57217222093); Zhou, Ping (57222904205); Shi, Gang (58592462400); Chen, Hanning (56068384200)","57218685290; 36645402000; 35117920700; 57217222093; 57222904205; 58592462400; 56068384200","A Novel Maximin-Based Multi-Objective Evolutionary Algorithm Using One-by-One Update Scheme for Multi-Robot Scheduling Optimization",2021.0,"IEEE Access",9.0,null,9514575.0,121316.0,121328.0,12.0,10.0,"10.1109/ACCESS.2021.3105102","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85113233336&doi=10.1109%2fACCESS.2021.3105102&partnerID=40&md5=3258a286371f63a167bed354319b4c24","Software College, Northeastern University, Shenyang, China; School of Physics, Liaoning University, Shenyang, China; Chinese Academy of Sciences, Shenyang Institute of Automation, Shenyang, China; School of Computer Science and Technology, Tiangong University, Tianjin, China","Yang S., Software College, Northeastern University, Shenyang, China; Zhang Y., Software College, Northeastern University, Shenyang, China; Ma L., Software College, Northeastern University, Shenyang, China; Song Y., School of Physics, Liaoning University, Shenyang, China; Zhou P., Software College, Northeastern University, Shenyang, China; Shi G., Chinese Academy of Sciences, Shenyang Institute of Automation, Shenyang, China; Chen H., School of Computer Science and Technology, Tiangong University, Tianjin, China","With the continuous development of E-commerce, warehouse logistics is also facing emerging challenges, including more batches of orders and shorter order processing cycles. When more orders need to be processed simultaneously, some existing task scheduling methods may not be able to give a suitable plan, which delays order processing and reduces the efficiency of the warehouse. Therefore, the intelligent warehouse system that uses autonomous robots for automated storage and intelligent order scheduling is becoming mainstream. Based on this concept, we propose a multi-robot cooperative scheduling system in the intelligent warehouse. The aim of the multi-robot cooperative scheduling system of the intelligent storage is to drive many robots in an intelligent warehouse to perform the distributed tasks in an optimal (e.g., time-saving and energy-conserved) way. In this paper, we propose a multi-robot cooperative task scheduling model in the intelligent warehouse. For this model, we design a maximin-based multi-objective algorithm, which uses a one-by-one update scheme to select individuals. In this algorithm, two indicators are devised to discriminate the equivalent individuals with the same maximin fitness value in the environmental selection process. The results on benchmark test suite show that our algorithm is indeed a useful optimizer. Then it is applied to settle the multi-robot scheduling problem in the intelligence warehouse. Simulation experiment results demonstrate the efficiency of the proposed algorithm on the real-world scheduling problem. © 2013 IEEE.","Many-objective optimization; maximin fitness function; multi-objective optimization; multi-robot scheduling optimization; one-by-one update scheme","Benchmarking; Evolutionary algorithms; Industrial robots; Multipurpose robots; Multitasking; Scheduling; Warehouses; Continuous development; Cooperative scheduling; Intelligent storage; Intelligent warehouse; Multi objective algorithm; Multi objective evolutionary algorithms; Real-world scheduling; Scheduling optimization; Intelligent robots",{"$nulls":4},"Yan Song; National Natural Science Foundation of China, NNSFC, (61773103, 61803367, 61872075); National Key Research and Development Program of China, NKRDPC, (2018YFB1700103); Fundamental Research Funds for the Central Universities, (N2117005)","Corresponding authors: Lianbo Ma (malb@swc.neu.edu.cn), Yan Song (profsongyan@163.com), and Hanning Chen (chenhanning@tjpu.edu.cn) This work was supported in part by the National Key Research and Development Program of China under Grant 2018YFB1700103; in part by the National Natural Science Foundation of China under Grant 61773103, Grant 61803367, and Grant 61872075; and in part by the Fundamental Research Funds for the Central Universities under Grant N2117005.","Alavidoost M., Tarimoradi M., Zarandi M.F., Bi-objective mixedinteger nonlinear programming for multi-commodity tri-echelon supply chain networks, J. 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Cybern., 49, 2, pp. 542-555, (2019); While L., Hingston P., Barone L., Huband S., A faster algorithm for calculating hypervolume, IEEE Trans. Evol. Comput., 10, 1, pp. 29-38, (2006)","L. Ma; Software College, Northeastern University, Shenyang, China; email: malb@swc.neu.edu.cn",null,"Institute of Electrical and Electronics Engineers Inc.",{"$nulls":5},2.1693536E7,null,null,null,"English","IEEE Access","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85113233336"]
["Zhengyang F.","Zhengyang, Fang (57420303400)",5.74203034E10,"INNOVATIVE DEVELOPMENT OF CROSS-BORDER E-COMMERCE BASED ON GREEN SUPPLY CHAIN MANAGEMENT",2021.0,"Journal of Environmental Protection and Ecology",22.0,6.0,null,2718.0,2726.0,8.0,5.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85123218141&partnerID=40&md5=ef3bc2fb67ef5ec4f5d0f62bf910c538","Business School of Zhengzhou Vocational College of Information Engineering, Henan, Zhengzhou, 450 121, China; Colleges of Industrial Education, Technological University of the Philippines, Manila, 0900, Philippines","Zhengyang F., Business School of Zhengzhou Vocational College of Information Engineering, Henan, Zhengzhou, 450 121, China, Colleges of Industrial Education, Technological University of the Philippines, Manila, 0900, Philippines","With the continuous expansion of the scale of China’s logistics industry, green logistics has become the transformation and development goal of logistics enterprises. Under the traditional logistics industry model, there have been many problems, such as high cost, information asymmetry and resource waste. Starting with the concept and application principles of green supply chain, this paper analyses how to integrate green supply chain into all links of logistics industry chain and the problems in the operation of green logistics. This paper explores the path of innovative development of e-commerce enterprises from the perspective of green supply chain, and puts forward the method of introducing the concept of green environmental protection into the management decision-making of logistics industry. E-commerce enterprises can promote e-commerce enterprise innovation with the help of green logistics management talents with the goal of realising both economic benefits and efficient resource allocation from product production to product recycling. Vulnerable e-commerce enterprises are encouraged to enter the low-end cross-border market and bypass the technical barriers of highly competitive enterprises. E-commerce enterprises should use new information technology to realise green and intelligent innovation of cross-border logistics, and optimise the service process from product production to consumption, so as to solve the inherent problems existing in the traditional logistics industry chain. © 2021, Scibulcom Ltd.. All rights reserved.","Cross-border e-commerce; Environmental protection; Green logistics; Green supply chain","China; cross-border relations; electronic commerce; environmental protection; innovation; recycling; resource allocation; supply chain management",{"$nulls":6},"GUO J., YU H., GEN M., Research on Green Closed-Loop Supply Chain with the Consideration of Double Subsidy in e-Commerce Environment, Comput Ind Eng, 149, (2020); LEE P. M., Behavioral Model of Online Purchasers in e-Commerce Environment, Electron Commer Res, 2, 1–2, (2002); LV J., WANG T., WANG H., YU J., WANG Y., The Impact of Information Dissemination on Purchasing Behavior in Social e-Commerce Environment, Front Comput Sci (print), 14, 6, (2020); Al-SENAFY M., ABRAHAM J., Vulnerability of Groundwater Resources from Agricultural Activities in Southern Kuwait, Agric Water Manage, 64, 1, (2004); BRENKERT A. L., MALONE E. L., Modeling Vulnerability and Resilience to Climate Change: a Case Study of India and Indian States, Clim Change, 72, 1–2, (2005); POPESCU L. R., IORDACHE M., PASCU L. F., UNGUREANU E.-M., BUICA G.-O., Applications of the Mathematical Model ANOVA in the Area of an Industrial Platform for Assessment of Groundwater Quality, J Environ Prot Ecol, 17, 1, (2016); JACKSON D., How Personal Trainers Can Use Self-efficacy Theory to Enhance Exercise Behavior in Beginning Exercisers, Strength Cond J, 32, 3, (2010); UZEL G., GURLUK S., Water Resources Management, Allocation and Pricing Issues: the Case of Turkey, J Environ Prot Ecol, 17, 1, (2016); AXELSON J. N., SAUCHYN D. J., BARICHIVICH J., New Reconstructions of Streamflow Variability in the South Saskatchewan River Basin from a Network of Tree Ring Chronologies, Alberta, Canada, Water Resour Res, 45, 9, (2009); MANNING M., FLEMING C. M., AMBREY C. L., Life Satisfaction and Individual Willingness to Pay for Crime Reduction, Reg Stud, 50, (2016); BORGOMEO E., PFLUG G., HALL J. W., HOCHRAINER-STIGLER S., Assessing Water Resource System Vulnerability to Unprecedented Hydrological Drought Using Copulas to Characterize Drought duration and Deficit, Water Resour Res, 51, 11, (2015)","F. Zhengyang; Business School of Zhengzhou Vocational College of Information Engineering, Zhengzhou, Henan, 450 121, China; email: cocofang926@126.com",null,"Scibulcom Ltd.",{"$nulls":5},1.3115065E7,null,null,null,"English","J. Environ. Prot. Ecol.","Article","Final",null,"Scopus","2-s2.0-85123218141"]
["Qiu Y.; Zhou D.; Du Y.; Liu J.; Pardalos P.M.; Qiao J.","Qiu, Yuzhuo (36683161900); Zhou, Dan (57221617166); Du, Yanan (57197854983); Liu, Jie (57221617391); Pardalos, Panos M. (7005330875); Qiao, Jun (55977812700)","36683161900; 57221617166; 57197854983; 57221617391; 7005330875; 55977812700","The two-echelon production routing problem with cross-docking satellites",2021.0,"Transportation Research Part E: Logistics and Transportation Review",147.0,null,102210.0,null,null,null,18.0,"10.1016/j.tre.2020.102210","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85099623942&doi=10.1016%2fj.tre.2020.102210&partnerID=40&md5=34f638550b08efbdfd6b5e4e90fcc78f","School of Management Science and Engineering, Nanjing University of Information Science and Technology, Nanjing, 210044, China; Jiangsu Key Laboratory of Modern Logistics, School of Marketing and Logistics Management, Nanjing University of Finance and Economics, Nanjing, 210023, China; Department of Industrial and Systems Engineering, Faculty of Engineering, University of Florida, Gainesville, 32611, United States","Qiu Y., School of Management Science and Engineering, Nanjing University of Information Science and Technology, Nanjing, 210044, China, Department of Industrial and Systems Engineering, Faculty of Engineering, University of Florida, Gainesville, 32611, United States; Zhou D., Jiangsu Key Laboratory of Modern Logistics, School of Marketing and Logistics Management, Nanjing University of Finance and Economics, Nanjing, 210023, China; Du Y., Jiangsu Key Laboratory of Modern Logistics, School of Marketing and Logistics Management, Nanjing University of Finance and Economics, Nanjing, 210023, China; Liu J., Jiangsu Key Laboratory of Modern Logistics, School of Marketing and Logistics Management, Nanjing University of Finance and Economics, Nanjing, 210023, China; Pardalos P.M., Department of Industrial and Systems Engineering, Faculty of Engineering, University of Florida, Gainesville, 32611, United States; Qiao J., Jiangsu Key Laboratory of Modern Logistics, School of Marketing and Logistics Management, Nanjing University of Finance and Economics, Nanjing, 210023, China","This paper introduces a mixed integer programming model for the two-echelon production routing problem with cross-docking satellites. This problem is important in e-commerce, home delivery services, and city logistics. To solve this problem, we propose a branch-and-cut algorithm with proved valid inequalities and a matheuristic that can provide feasible initial solutions. Extensive computational results are reported, which are obtained on instances derived from benchmarks for the production routing problems and two echelon vehicle routing problems. Management insights on dynamic balance among handling costs, inventory costs, and routing costs are also drawn from the sensitivity analysis. © 2021 Elsevier Ltd","Material handling; Production planning; Two-echelon networks; Vehicle routing","Satellites; logistics; routing; satellite data; satellite imagery; sensitivity analysis; transportation development; transportation planning",{"$nulls":4},"Six Peaks of Top Talents” in Jiangsu Province, (JY-076); Colleges and Universities in Jiangsu Province; Priority Academic Program Development of Jiangsu Higher Education Institutions, PAPD; Major Projects for Natural Science Research in Colleges and Universities of Jiangsu Province, (19KJA520002); Priority Academic Program Development of Jiangsu Higher Education Institutions, PAPD; National Natural Science Foundation of China, NSFC, (71571092)","We thank the anonymous reviewers for their constructive and insightful suggestions on the earlier versions of this paper. This work is supported by NSFC under Grant No. 71571092. This work is also supported in part by the High-level Talent Project from “Six Peaks of Top Talents” in Jiangsu Province under Grant No. JY-076, Young and Middle-aged Academic Leaders from “Green–Blue Project” of Colleges and Universities in Jiangsu Province, Major Projects for Natural Science Research in Colleges and Universities of Jiangsu Province under Grant No. 19KJA520002, and the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD). ","Absi N., Archetti C., Dauzere-Peres S., Feillet D., A two-phase iterative heuristic approach for the production routing problem, Transport. Sci., 49, 4, pp. 784-795, (2015); Adulyasak Y., Cordeau J.-F., Jans R., Formulations and branch-and-cut algorithms for multivehicle production and inventory routing problems, INFORMS J. 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Res., 87, pp. 114-124, (2017); Zhang Q., Sundaramoorthy A., Grossmann I.E., Pinto J.M., Multiscale production routing in multicommodity supply chains with complex production facilities, Comput. Oper. Res., 79, pp. 207-222, (2017)","Y. Qiu; School of Management Science and Engineering, Nanjing University of Information Science and Technology, Nanjing, 210044, China; email: jadeqyz@gmail.com",null,"Elsevier Ltd",{"$nulls":5},1.3665545E7,null,null,null,"English","Transp. Res. Part E Logist. Transp. Rev.","Article","Final",null,"Scopus","2-s2.0-85099623942"]
["Sujatha R.; Karthikeyan M.S.","Sujatha, R. (57395955100); Karthikeyan, M.S. (57237621300)","57395955100; 57237621300","Determinants of e-commerce adoption: Evidence from small and medium-sized enterprises in india",2021.0,"International Journal of Business and Society",22.0,2.0,null,574.0,590.0,16.0,5.0,"10.33736/ijbs.3740.2021","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85117334273&doi=10.33736%2fijbs.3740.2021&partnerID=40&md5=5cea880f76ec1e480d2565699dc785bf","PSG Institute of Management, India","Sujatha R., PSG Institute of Management, India; Karthikeyan M.S., PSG Institute of Management, India","Information technology (IT) is driving the business world in contemporary times. Large, medium, and small organisations in developed and developing countries are trying to adopt electronic commerce (e-commerce). Small and medium-sized enterprises (SMEs) are abundant in India, which is a rapidly developing country. Despite enormous efforts to adopt e-commerce, SMEs must address many hurdles. The major objective of this paper is to investigate the determinant factors that influence the adoption of e-commerce in SMEs. In this study, three categories and a three-stage model were used to demonstrate the various factors and stages that are involved in the adoption of e-commerce. A structured survey was conducted and data was collected from 148 firms in Coimbatore, a major industrial city in India. The data was analysed using binomial logistic regression to determine a significant relationship between a set of independent variables and the dependent variable. The results indicated that Top Management Support, Learning Orientation, Receptivity towards Change, Strategic Orientation, IT Readiness, Cost, and Relative Advantage as statistically significant determinants of e-commerce adoption. This study provides insight to the managers of organisations who are responsible for implementing e-commerce, and it will help to spread e-commerce use across SMEs in India. © 2021, Universiti Malaysia Sarawak. All rights reserved.","Developing country; E-commerce adoption; Internet; Small and medium-sized enterprises",{"$nulls":7},"Ahmad S. Z., Bakar A. R. A., Faziharudean T. M., Zaki K. A. M., An empirical study of factors affecting e-commerce adoption among small and medium-sized enterprises in a developing country: Evidence from Malaysia, Information Technology for Development, 21, 4, pp. 555-572, (2015); Al-Alawi A. I., Al-Ali F. M., Factors affecting e-commerce adoption in SMEs in the GCC: An empirical study of Kuwait, Research Journal of Information Technology, 7, 1, pp. 1-21, (2015); Alam S. S., Khatibi A., Ahmad M. I. S., Ismail H. B., Factors affecting e-commerce adoption in the electronic manufacturing companies in Malaysia, International Journal of Commerce and Management, 17, 1, pp. 125-139, (2008); Al-Qirim N., An empirical investigation of an e‐commerce adoption‐capability model in small businesses in New Zealand, Electronic Markets, 15, 4, pp. 263-28, (2005); Al-Somali S. A., Gholami R., Clegg B., A stage-oriented model (SOM) for e-commerce adoption: A study of Saudi arabian Organisation, Journal of Manufacturing Technology Management, 22, 1, pp. 2-35, (2015); Awiagah R., Kang J., Lim J. I., Factors affecting e-commerce adoption among SMEs in Ghana, Information Development, 32, 4, pp. 815-836, (2016); Belkhamza Z., Wafa S., The effect of perceived risk on the intention to use e-commerce: The case of Algeria, Journal of Internet Banking and Commerce, 14, 1, pp. 1-10, (2009); Why Coimbatore hums with industrial energy, (2018); Chaudhury A., Kuilboer J. P., E-Business and Infrastructure, (2002); Chong S., Success in electronic commerce implementation-a cross-country study of small and medium-sized enterprises, Journal of Enterprise Information Management, 21, 5, pp. 468-492, (2008); Cooper R. B., Zmud R. W., Information technology implementation research: A technological diffusion approach, Management Science, 36, 2, pp. 123-139, (1990); Ghobakhloo M., Tang S. H., The role of owner/manager in adoption of electronic commerce in small businesses, Journal of Small Business and Enterprise Development, 20, 4, pp. 754-787, (2013); Globerman S., Roehl T. W., Standifird S., Globalization and electronic commerce, Journal of International Business Studies, 32, 4, pp. 749-768, (2001); Annual Report 2017-18, (2018); Hair J. F., Anderson R. E., Tatham R. L., Black W. C., Multivariate Data Analysis, (2010); Hartman A., Sifonis J., Kador J., Net Ready: Strategies for Success in the Economy, (2000); Hussein A., Baharudin A. S., A case study of e-commerce adoption in Jordanian small and medium enterprises (SMEs), International Journal of Business and Management, 6, 9, pp. 88-93, (2017); Huy L. E. V., Rowe F., Truex D., An empirical study of determinants of e-commerce adoption in SMEs in Vietnam an economy in transition, Journal of Global Information Management, 20, 3, pp. 23-54, (2012); Jon K., Lai T. L., Khoon C. H., Dennis N. C., Meng T. S., Electronic commerce adoption by SMEs in Singapore, Proceedings of the 34th International Conference on System Sciences, (2001); Kreiser P. M., Marina L. D., Dickson P., Weaver K. M., Cultural influences on entrepreneurial orientation: The impact of national culture on risk taking and pro-activeness in SMEs, Entrepreneurship theory and practice, 34, 5, pp. 959-984, (2010); Li P., Xie W., A strategic framework for determining e-commerce adoption, Journal of Technology Management in China, 7, 1, pp. 22-35, (2012); Marasini R., Ions K., Ahmad M., Assessment of e-business adoption in SMEs: a study of manufacturing industry in the UK north east region, Journal of Manufacturing Technology Management, 19, 5, pp. 627-644, (2008); Masarweh M. A., Al-Masaeed J. S., Al-Qaisi J. L., Hunaiti J. Z., E-commerce adoption at customer level in Jordan: An empirical study of Philadelphia general supplies, International Journal of Advanced Computer Science and Applications, 7, 11, pp. 196-205, (2016); Moghavvemi S., Hakimian F., Feissal T., Competitive advantage through it innovation adoption by SMEs, Social Technologies, 2, 1, pp. 24-39, (2012); Molla A., Licker P.S., Ecommerce adoption in developing countries: A model and instrument, Information and Management, 42, 6, pp. 877-899, (2005); Molla A., Licker P. S., Perceived e-readiness factors in e-commerce adoption: An empirical investigation in a developing country, International Journal of Electronic Commerce, 10, 1, pp. 83-110, (2005); Research and Intelligence, Quarterly Industry Review, (2018); Ndayizigamiye P., A unified approach towards e-commerce adoption by SMEs in South Africa, International Journal of Information Technology and Business Management, 16, 1, pp. 92-101, (2012); Nezakati H., Jofreh M., Liong G., Asgari O., Assessing e-commerce adoption by small and medium enterprises in Malaysia, Singapore and Thailand, World Applied Sciences Journal, 19, 10, pp. 1406-1411, (2012); Nikolaeva R., E-commerce adoption in the retail sector: Empirical insights, International Journal of Retail & Distribution Management, 34, 4, pp. 369-387, (2006); Nunnally J. C., Psychometric Theory, (1978); Oliveira T., Martins M. F., Understanding e-business adoption across industries in European countries, Industrial Management & Data Systems, 110, 9, pp. 1337-1354, (2010); Parker C. M., Castleman T., Small firm e-business adoption: A critical analysis of theory, Journal of Enterprise Information Management, 22, 1, pp. 167-182, (2009); Rahayu R., Day J., Determinant factors of e-commerce adoption by SMEs in developing country: Evidence from Indonesia, Procedia-Social and Behavioral Sciences, 195, 3, pp. 142-150, (2015); Rahayu R., Day J., E-commerce adoption by SMEs in developing countries: Evidence from Indonesia, Eurasian Business Review, 7, 1, pp. 25-41, (2017); Ramdansyah A. D., Adoption model of e-commerce from SMEs perspective in developing country evidence – case study for Indonesia, European Research Studies Journal, 20, 4B, pp. 227-24, (2017); Rogers E. M., Diffusion of Innovations, (1995); Saffu K., Walker J. H., Hinson R., Strategic value and electronic commerce adoption among small and medium-sized enterprises in a transitional economy, Journal of Business & Industrial Marketing, 23, 6, pp. 395-404, (2008); Schulze C., Baumgartner J., Don’t panic, do e-commerce, a beginner’s guide to European law affecting ecommerce, European commission’s electronic commerce team, (2000); Seyal A. H., Rahman M. N. A., Yussof H. A., Mohammad H. A., A quantitative analysis of factors contributing electronic data interchange adoption among Bruneian SMEs, Business Process Management Journal, 13, 5, pp. 728-746, (2007); Terzi N., The impact of e-commerce on international trade and employment, Procedia Social and Behavioral Sciences, 24, 1, pp. 745-753, (2011); Titi K. M., The impact of adoption electronic commerce in small to medium enterprises Jordanian companies, Proceedings of the 1st International Conference on e-Business and E-Learning, pp. 159-178, (2005); Turban E., King D., Lee J., Warkentin M., Chung H. M., Electronic Commerce, (2002); Xiaoxia D., Deng H., Corbitt B., Evaluating the critical determinants for adopting e-market in Australian small and medium sized enterprises, Management Research Review, 35, 3, pp. 289-308, (2012); Zaied A. N. H., Barriers to e-commerce adoption in Egyptian SMEs, International Journal of Information Engineering and Electronic Business, 3, 1, pp. 9-18, (2012); Zaltman G., Duncan R., Holbek J., Innovations and Organizations, (1973); Zhao J., Huang W. V., Zhu Z., An empirical study of e-business implementation process in China, IEEE Transactions on Engineering Management, 55, 1, pp. 134-147, (2008)","R. Sujatha; PSG Institute of Management, Coimbatore, Tamil Nadu, Post Box No. 1668, Peelamedu, 641 004, India; email: sujatha@psgim.ac.in",null,"Universiti Malaysia Sarawak",{"$nulls":5},1.511667E7,null,null,null,"English","Int. J. Bus. Soc.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85117334273"]
["Zhang J.","Zhang, Jing (55720170400)",5.57201704E10,"Research on airfreight loading optimization of e-commerce logistics based on improved genetic algorithm",2021.0,"International Journal of Mechatronics and Applied Mechanics",1.0,9.0,null,45.0,50.0,5.0,1.0,"10.17683/IJOMAM/ISSUE9.6","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85112409334&doi=10.17683%2fIJOMAM%2fISSUE9.6&partnerID=40&md5=12f0b2d4fe9502499c69aacd4387e438","Changsha Aeronautical Vocational and Technical College, Hunan, Changsha, 410124, China","Zhang J., Changsha Aeronautical Vocational and Technical College, Hunan, Changsha, 410124, China","At present, more and more e-commerce logistics use airfreight. To further optimize the freight loading problem, this study first established the freight loading optimization model, improved the genetic algorithm to solve the model, and made an example analysis. It was found that the load utilization rate was 96.63%, and the space utilization rate was 92.95% in the scheme obtained by the algorithm proposed in this study, which was higher than those of the other two algorithms. In the aspect of calculation time, the method proposed in this study could obtain the optimal scheme in 56.78 s. The experimental results show that the proposed algorithm performs better in the loading optimization problem and can be further promoted and applied. © 2021, Cefin Publishing House. All rights reserved.","Air logistics; E-commerce logistics; Genetic algorithm; Loading optimization","Electronic commerce; Genetic algorithms; Calculation time; Loading optimization; Loading problem; Optimal scheme; Space utilization; Utilization rates; Loading",{"$nulls":6},"Ha H T H, Nananukul N., Air Cargo Optimization Models for Logistics Forwarders, Advanced Science Letters, 23, 5, pp. 4162-4167, (2017); Chu Y L, Gong Z G, Yang Z Z., The Spatial Pattern of China Air Cargo Transportation in 21~(st) Century, Scientia Geographica Sinica, 36, 3, pp. 335-341, (2016); Ashwini R, Manoj E., Review on Cargo Space Optimization Methodologies, International Journal of Computer Applications, 162, 3, pp. 31-34, (2017); Kulak O, Genc A, Taner M E., A decision making tool considering risk assessment of subcontracting agents for an air cargo shipment planning problem, Journal of Air Transport Management, 69, pp. 123-136, (2018); Peng Y, Wang P, Zhao X, Chen M, Zhang J, Zhang F., A data-driven air cargo redistribution model based on multiple programming, International Journal of Modern Physics B, 33, 17, (2019); Paquay C, Schyns M, Limbourg S., A mixed integer programming formulation for the three-dimensional bin packing problem deriving from an air cargo application, International Transactions in Operational Research, 23, 1-2, pp. 187-213, (2016); Roesener A G, Barnes J W., An advanced tabu search approach to the airlift loading problem, Logs Research, 9, 1, pp. 1-18, (2016); Nance R L, Moore A R., Special Issue: Heuristic Optimisation || An advanced tabu search for solving the mixed payload airlift loading problem, Journal of the Operational Research Society, 62, 2, pp. 337-347, (2011); Liu Y T, Yang Z B, Deng J X, Zhu J J., Investigation of fuel savings for an aircraft due to optimization of the center of gravity, Materials Science & Engineering Conference Series, (2018); Bookbinder J H, Elhedhli S, Li Z., The air-cargo consolidation problem with pivot weight: Models and solution methods, Computers & Operations Research, 59, pp. 22-32, (2015); Zhang C, Xie F, Huang K, Wu T, Liang Z., MIP models and a hybrid method for the capacitated air-cargo network planning and scheduling problems, Transportation Research Part E: Logs and Transportation Review, 103, pp. 158-173, (2017); Volkanovski A, Mavko B, Bosevski T, Chaushevski A, Cepin M., Genetic algorithm optimisation of the maintenance scheduling of generating units in a power system, Reliability Engineering & System Safety, 93, 6, pp. 779-789, (2017); Zhang H, Lennox B, Goulding PR, Leung AYT., A float-encoded genetic algorithm technique for integrated optimization of piezoelectric actuator and sensor placement and feedback gains, Smart Materials & Structures, 9, 4, (2016); Ross J., Airfreight awakenings, American Shipper, 59, 12, pp. 11-11, (2017); Budiarto S, Putro H P, Pradono P, Yudoko G., Revenue management of air cargo service in theory and practice, IoP Conference, 158, (2018)","J. Zhang; Changsha Aeronautical Vocational and Technical College, Changsha, Hunan, 410124, China; email: jingzzhangj@yeah.net",null,"Cefin Publishing House",{"$nulls":5},2.5596497E7,null,null,null,"English","Int. J. Mech. Appl. Mech.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85112409334"]
["Lemardelé C.; Estrada M.; Pagès L.; Bachofner M.","Lemardelé, Clément (57222744565); Estrada, Miquel (7102245693); Pagès, Laia (15036490900); Bachofner, Mónika (57222744362)","57222744565; 7102245693; 15036490900; 57222744362","Potentialities of drones and ground autonomous delivery devices for last-mile logistics",2021.0,"Transportation Research Part E: Logistics and Transportation Review",149.0,null,102325.0,null,null,null,68.0,"10.1016/j.tre.2021.102325","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85103988567&doi=10.1016%2fj.tre.2021.102325&partnerID=40&md5=898935058ac1064729180ea34a61221b","Civil Engineering School of Barcelona. Universitat Politècnica de Catalunya – Barcelona TECH, C. Jordi Girona 1-3, Edificio Omega, Planta 0 Oficina 05, Barcelona, 08034, Spain; Civil Engineering School of Barcelona, Universitat Politècnica de Catalunya – Barcelona TECH, C. Jordi Girona 1-3, Barcelona, B1-110 08034, Spain; CARNET Barcelona. C. Jordi Girona 1-3, Edificio Omega, Planta 0 Oficina 05, Barcelona, 08034, Spain","Lemardelé C., Civil Engineering School of Barcelona. Universitat Politècnica de Catalunya – Barcelona TECH, C. Jordi Girona 1-3, Edificio Omega, Planta 0 Oficina 05, Barcelona, 08034, Spain; Estrada M., Civil Engineering School of Barcelona, Universitat Politècnica de Catalunya – Barcelona TECH, C. Jordi Girona 1-3, Barcelona, B1-110 08034, Spain; Pagès L., CARNET Barcelona. C. Jordi Girona 1-3, Edificio Omega, Planta 0 Oficina 05, Barcelona, 08034, Spain; Bachofner M., CARNET Barcelona. C. Jordi Girona 1-3, Edificio Omega, Planta 0 Oficina 05, Barcelona, 08034, Spain","The e-commerce boom has increased the complexity of last-mile logistics operations in urban environments. In this context, unmanned aerial vehicles (UAVs), also known as delivery drones, and ground autonomous delivery devices (GADDs) show great potentialities. The objective of this paper is to provide strategic insights to adequately match these autonomous technologies with some given characteristics of cities and help define relevant decision variables. Using continuous approximation equations, the operations costs as well as the externalities induced by a) GADDs in association with an urban consolidation center (UCC) and b) truck-launched UAVs are estimated. Then, the developed mathematical formulations are applied in two different use cases: a part of the Paris suburbs (France) and the historical center of Barcelona (Spain). In less dense and larger service regions such as the Paris suburbs, truck-launched delivery drones seem more suitable to reduce the carriers’ operations costs. In denser neighborhoods such as the Barcelona historical center, GADDs are expected to be more economically profitable. In both use cases, GADDs would generate less externalities. Finally, considering the high uncertainty of some input parameters, a sensitivity analysis of the models is done. © 2021 Elsevier Ltd","Autonomous delivery robot; Barcelona (Spain); Continuous approximation; Delivery drones; E-commerce; Externalities; Last-mile logistics; Operation costs; Parcel lockers; Paris (France)","Barcelona [Barcelona (PRV)]; Barcelona [Catalonia]; Catalonia; France; Ile de France; Paris; Spain; Ville de Paris; decision analysis; electronic commerce; neighborhood; profitability; robotics; sensitivity analysis; shipping; unmanned vehicle; urban area",{"$nulls":4},"CARNET Barcelona","The first author would like to personally acknowledge CARNET Barcelona for the funding of this research article, developed in the framework of his PhD thesis. ","(2020); (2019); (2018); Barthuly D., (2019); Boysen N., Schwerdfeger S., Weidinger F., Scheduling last-mile deliveries with truck-based autonomous robots, Eur. J. Oper. 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Sci., 54, 1, pp. 229-249, (2020); Dieke A., (2018); Ducret R., Parcel deliveries and urban logistics: Changes and challenges in the courier express and parcel sector in Europe—The French case, Res. Transp. Bus. Manage., 11, pp. 15-22, (2014); Ellingsen L.A.W., Singh B., Stromman A.H., The size and range effect: lifecycle greenhouse gas emissions of electric vehicles, Environ. Res. Lett., 11, 5, (2016); Estrada M., Campos-Cacheda J.M., Robuste F., Night deliveries and carrier-led consolidation strategies to improve urban goods distribution, Transport, 33, 4, pp. 930-947, (2018); Estrada M., Roca-Riu M., Stakeholder's profitability of carrier-led consolidation strategies in urban goods distribution, Transp. Res. Part E: Logist. Transp. Rev., 104, pp. 165-188, (2017); (2019); (2019); (2019); (2020); Feng W., Figliozzi M., An economic and technological analysis of the key factors affecting the competitiveness of electric commercial vehicles: a case study from the USA market, Transp. Res. Part C: Emerg. Technol., 26, pp. 135-145, (2013); Figliozzi M.A., Lifecycle modeling and assessment of unmanned aerial vehicles (Drones) CO2 emissions, Transp. Res. Part D: Transp. Environ., 57, October, pp. 251-261, (2017); Giordano A., Fischbeck P., Matthews H.S., Environmental and economic comparison of diesel and battery electric delivery vans to inform city logistics fleet replacement strategies, Transp. Res. Part D: Transp. Environ., 64, pp. 216-229, (2018); Goodchild A., Toy J., Delivery by drone: an evaluation of unmanned aerial vehicle technology in reducing CO2 emissions in the delivery service industry, Transp. Res. Part D: Transp. Environ., 61, pp. 58-67, (2018); Hoffmann T., Prause G., On the regulatory framework for last-mile delivery robots, Machines, 6, 3, pp. 6-8, (2018); Holguin-Veras J., Amaya-Leal J., Wojtowicz J., Jaller M., Gonzalez-Calderon C., Sanchez-Diaz I., Browne M., (2015); Holguin-Veras J., Wang C., Browne M., Hodge S.D., Wojtowicz J., The New York city off-hour delivery project: lessons for city logistics, Proc. – So. Behav. Sci., 125, pp. 36-48, (2014); Jennings D., Figliozzi M., Study of sidewalk autonomous delivery robots and their potential impacts on freight efficiency and travel, Transp. Res. Rec., 2673, 6, pp. 317-326, (2019); Keen K., (2020); Keeney T., (2015); Kirschstein T., Comparison of energy demands of drone-based and ground-based parcel delivery services, Transp. Res. Part D: Transp. Environ., 78, (2020); Lee H.L., Chen Y., Gillai B., Rammohan S., (2016); Li Y., Zhang G., Pang Z., Li L., Continuum approximation models for joint delivery systems using trucks and drones, Enterprise Inf. Syst., pp. 1-30, (2018); Macharis C., Milan L., Verlinde S., Balm S., Quak H., Estrada M., Roca-Riu M., (2012); Marks M., Robots in space: sharing our world with autonomous delivery vehicles, SSRN Electronic J., (2019); Mazareanu E., (2020); Morganti E., Seidel S., Blanquart C., Dablanc L., Lenz B., The impact of e-commerce on final deliveries: alternative parcel delivery services in France and Germany, Transp. Res. Procedia, 4, pp. 178-190, (2014); Morganti E., Browne M., Technical and operational obstacles to the adoption of electric vans in France and the UK: an operator perspective, Transp. Policy, 63, pp. 90-97, (2018); Moshref-Javadi M., Hemmati A., Winkenbach M., A truck and drones model for last-mile delivery: a mathematical model and heuristic approach, Appl. Math. Model., 80, pp. 290-318, (2020); Murray C.C., Chu A.G., The flying sidekick traveling salesman problem: optimization of drone-assisted parcel delivery, Transp. Res. Part C: Emerg. 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Procedia, 12, (2016); Roca-Riu M., Menendez M., (2019); (2020); Samadi S., The social costs of electricity generation - categorising different types of costs and evaluating their respective relevance, Energies, 10, 3, (2017); Stolaroff J.K., Samaras C., O'Neill E.R., Lubers A., Mitchell A.S., Ceperley D., Energy use and life cycle greenhouse gas emissions of drones for commercial package delivery, Nat. Commun., 9, 1, pp. 1-13, (2018); Sudbury A.W., Hutchinson E.B., A cost analysis of amazon prime air (drone delivery), J. Econ. Educ., 16, 1, pp. 1-12, (2016); Ulmer M.W., Streng S., Same-Day delivery with pickup stations and autonomous vehicles, Comput. Oper. Res., 108, pp. 1-19, (2019); Ulmer M.W., Thomas B.W., Same-day delivery with heterogeneous fleets of drones and vehicles, Networks, 72, 4, pp. 475-505, (2018); Van Duin J.H.R., De Goffau W., Wiegmans B., Tavasszy L.A., Saes M., Improving home delivery efficiency by using principles of address intelligence for B2C deliveries, Transp. Res. Procedia, 12, pp. 14-25, (2016); (2013); Van Duin J.H.R., Wiegmans B.W., van Arem B., van Amstel Y., From home delivery to parcel lockers: a case study in Amsterdam, Transp. Res. Procedia, 46, pp. 37-44, (2020); Wang D., Hu P., Du J., Zhou P., Deng T., Hu M., Routing and scheduling for hybrid truck-drone collaborative parcel delivery with independent and truck-carried drones, IEEE Internet Things J., 6, 6, (2019); (2020); (2020); Zenezini G., Lagorio A., Pinto R., De Marco A., Golini R., The collection-and-delivery points implementation process from the courier, express and parcel operator's perspective, IFAC-PapersOnLine, 51, 11, pp. 594-599, (2018); Zhang J., Campbell J.F., Sweeney D.C., Hupman A.C., Energy consumption models for delivery drones: a comparison and assessment, Transp. Res. Part D: Transp. Environ., 90, (2021)","C. Lemardelé; Civil Engineering School of Barcelona. Universitat Politècnica de Catalunya – Barcelona TECH, Barcelona, C. Jordi Girona 1-3, Edificio Omega, Planta 0 Oficina 05, 08034, Spain; email: clement.lemardele@upc.edu",null,"Elsevier Ltd",{"$nulls":5},1.3665545E7,null,null,null,"English","Transp. Res. Part E Logist. Transp. Rev.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85103988567"]
["Shiau J.-Y.; Huang M.-K.; Chou S.-W.; Liao T.-C.","Shiau, Jiun-Yan (9244076700); Huang, Ming-Kung (57202354153); Chou, Shih-Wei (36747802900); Liao, Tzu-Ching (55902378300)","9244076700; 57202354153; 36747802900; 55902378300","A delivery oriented order picking policy with batching for a randomised storage warehouse",2021.0,"International Journal of Logistics Systems and Management",40.0,4.0,null,443.0,465.0,22.0,1.0,"10.1504/IJLSM.2021.120490","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124096085&doi=10.1504%2fIJLSM.2021.120490&partnerID=40&md5=3d7520f67c4c8cedecc5d251850faaf3","Department of Logistics Management, National Kaohsiung University of Science and Technology, Kaohsiung, Taiwan; College of Management, National Kaohsiung University of Science and Technology, Kaohsiung, Taiwan; Department of Information Management, National Kaohsiung University of Science and Technology, Kaohsiung, Taiwan","Shiau J.-Y., Department of Logistics Management, National Kaohsiung University of Science and Technology, Kaohsiung, Taiwan; Huang M.-K., College of Management, National Kaohsiung University of Science and Technology, Kaohsiung, Taiwan; Chou S.-W., Department of Information Management, National Kaohsiung University of Science and Technology, Kaohsiung, Taiwan; Liao T.-C., Department of Logistics Management, National Kaohsiung University of Science and Technology, Kaohsiung, Taiwan","One of the most crucial tasks of a warehouse management system is order picking, which is also the most expensive cost of warehouse operations in a distribution centre. Improving picking efficiency can thus be highly beneficial for distribution centre operations. In this study, a 24-hour express shipping online shopping case was investigated. The theory of order picking is reviewed and summarised to assist researchers to develop methods to improve upon deficiencies identified in the case study. A mixed integer programming model that integrates order picking operations and order packing operations was developed to improve the performance of warehouse operations. A conceptual system with a simplified example of the proposed order picking function was implemented to demonstrate the merits of our idea and is reported herein. Copyright © 2021 Inderscience Enterprises Ltd.","Order picking problem; Packing problems; Warehouse management system; WMS",{"$nulls":5},"National Science Council of Republic of China, (NSC 101-2221-E-327-028)","This work was supported in part by the National Science Council of Republic of China under the grant NSC 101-2221-E-327-028.","Altarazi S.A., Ammouri M.M., Concurrent manual-order-picking warehouse design: a simulation-based design of experiments approach, International Journal of Production Research, 56, 23, pp. 1-19, (2018); Bansal N., Sviridenko M., Two-dimensional bin packing with one-dimensional resource augmentation, Discrete Optimization, 4, 2, pp. 143-153, (2007); Bask A., Et al., E-commerce logistics: a literature research review and topics for future research, International Journal of E-Services and Mobile Applications (IJESMA), 4, 3, pp. 1-22, (2012); Boysen N., Et al., Warehousing in the e-commerce era: a survey, European Journal of Operational Research, 277, 2, pp. 396-411, (2019); Burinskiene A., Order picking process at warehouses, International Journal of Logistics Systems and Management, 6, 2, pp. 162-178, (2010); Chen T-L., Et al., An efficient hybrid algorithm for integrated order batching, sequencing and routing problem, International Journal of Production Economics, 159, pp. 158-167, (2015); de Koster R., Warehouse assessment in a single tour, Warehousing in the Global Supply Chain: Advanced Models, Tools and Applications for Storage Systems, (2008); de Koster R., Et al., When to apply optimal or heuristic routing of orderpickers, Advances in Distribution Logistics, (1998); Dewa P.K., Et al., Human errors in warehouse operations: an improvement model, International Journal of Logistics Systems and Management, 27, 3, pp. 298-317, (2017); Epstein L., Two-dimensional online bin packing with rotation, Theoretical Computer Science, 411, 31, pp. 2899-2911, (2010); Fischetti M., Et al., Mixed-integer linear programming heuristics for the prepack optimization problem, Discret. Optim, 22, pp. 195-205, (2016); Heady R.B., Et al., Evaluation of carton packing rules for high volume operations, Journal of Operations Management, 13, 1, pp. 59-66, (1995); Henn S., Wascher G., Tabu search heuristics for the order batching problem in manual order picking systems, European Journal of Operational Research, 222, 3, pp. 484-494, (2012); Hsieh L-F., Huang Y-C., New batch construction heuristics to optimise the performance of order picking systems, International Journal of Production Economics, 131, 2, pp. 618-630, (2011); Kang K., Et al., A hybrid genetic algorithm with a new packing strategy for the three-dimensional bin packing problem, Applied Mathematics and Computation, 219, 3, pp. 1287-1299, (2012); Kaur J., Awasthi A., A systematic literature review on barriers in green supply chain management, International Journal of Logistics Systems and Management, 30, 3, pp. 330-348, (2018); Li X., Zhang K., A hybrid differential evolution algorithm for multiple container loading problem with heterogeneous containers, Computers & Industrial Engineering, 90, pp. 305-313, (2015); Najlae A., Et al., Product driven system for the optimal assignment of warehouse locations, International Journal of Logistics Systems and Management, 33, 3, pp. 322-352, (2019); Pang K-W., Chan H-L., Data mining-based algorithm for storage location assignment in a randomized warehouse, International Journal of Production Research, 55, 14, pp. 4035-4052, (2017); Park B.C., Order picking: issues, systems and models, Warehousing in the Global Supply Chain, (2012); Petersen C.G., An evaluation of order picking routeing policies, International Journal of Operations & Production Management, 17, 11, pp. 1098-1111, (1997); Petersen C.G., Aase G., A comparison of picking, storage, and routing policies in manual order picking, International Journal of Production Economics, 92, 1, pp. 11-19, (2004); Reis A., Et al., Internal logistics management: Brazilian warehouse best practices based on lean methodology, International Journal of Logistics Systems and Management, 26, 3, pp. 329-345, (2017); Shah B., Khanzode V., A comprehensive review of warehouse operational issues, International Journal of Logistics Systems and Management, 26, 3, pp. 346-378, (2017); Shiau J-Y., Lee M-C., A warehouse management system with sequential picking for multi-container deliveries, Computers & Industrial Engineering, 58, 3, pp. 382-392, (2010); Tompkins J.A., Facilities Planning, (1996); van Gils T., Et al., Designing efficient order picking systems by combining planning problems: state-of-the-art classification and review, European Journal of Operational Research, 267, 1, pp. 1-15, (2018); Won J., Olafsson S., Joint order batching and order picking in warehouse operations, International Journal of Production Research (Int. J. Prod. Res.), 43, 7, pp. 1427-1442, (2005)","J.-Y. Shiau; Department of Logistics Management, National Kaohsiung University of Science and Technology, Kaohsiung, Taiwan; email: sho@nkust.edu.tw",null,"Inderscience Publishers",{"$nulls":5},1.7427967E7,null,null,null,"English","Int. J. Logist. Syst. Manage.","Article","Final",null,"Scopus","2-s2.0-85124096085"]
["Sanchez-Diaz I.; Altuntas Vural C.; Halldórsson Á.","Sanchez-Diaz, Ivan (55365754800); Altuntas Vural, Ceren (57062354700); Halldórsson, Árni (6701805551)","55365754800; 57062354700; 6701805551","Assessing the inequalities in access to online delivery services and the way COVID-19 pandemic affects marginalization",2021.0,"Transport Policy",109.0,null,null,24.0,36.0,12.0,19.0,"10.1016/j.tranpol.2021.05.007","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85107920381&doi=10.1016%2fj.tranpol.2021.05.007&partnerID=40&md5=e664c8b7fb7eb1c82667c7361e8d7b92","Service Management and Logistics, Technology Management and Economics, Chalmers University of Technology, Vera Sandbergs Allé 8, Gothenburg, 41296, Sweden","Sanchez-Diaz I., Service Management and Logistics, Technology Management and Economics, Chalmers University of Technology, Vera Sandbergs Allé 8, Gothenburg, 41296, Sweden; Altuntas Vural C., Service Management and Logistics, Technology Management and Economics, Chalmers University of Technology, Vera Sandbergs Allé 8, Gothenburg, 41296, Sweden; Halldórsson Á., Service Management and Logistics, Technology Management and Economics, Chalmers University of Technology, Vera Sandbergs Allé 8, Gothenburg, 41296, Sweden","This paper discusses the importance of incorporating online home delivery services (OHDS) into the concept of accessibility and marginalization. The authors propose a method to quantify access to OHDS and assess levels of inequalities in access to OHDS using data from OHDS providers in the pharmaceutical and food sectors, as well as from transport operators delivering parcels. The Västra Götaland Region in the West coast of Sweden is used as a case study. The results show significant inequalities in access to OHDS. Moreover, there are segments of population under a compound marginalization during the COVID-19 pandemic due to (i) limited accessibility to OHDS services, (ii) high incidence of COVID-19 cases in their area that makes physical visits to a store a risk activity, and (iii) high vulnerability (e.g., high share of individuals older than 65). These results reveal a need for the public sector to prioritize innovations in services that target specific clusters of the population that are vulnerable and marginalized, but also shows the imminent risk for some of these segments during the pandemic. © 2021 The Author(s)","Accessibility; COVID-19; Digital divide; e-commerce; Marginalization","Sweden; Vastra Gotaland; accessibility; assessment method; COVID-19; electronic commerce; epidemic; innovation; marginalization; service quality; service sector",{"$nulls":4},"Area of Advance Transport at Chalmers","We would like to thank Rakshith B. Ramakrishna Subramanya and Sumanth Mikkilineni for their contribution to the extensive data collection effort that was necessary to conduct this research. We would also like to acknowledge the funding from the Area of Advance Transport at Chalmers through the project “ Logistics for the Marginalized ”.","Allen J., Browne M., Holguin-Veras J., Sustainability Strategies for City Logistics. Green logistics: Improving the Environmental Sustainability of Logistics, pp. 282-305, (2010); Altuntas-Vural C., Sanchez-Diaz I., Halldorsson A., (2020); Behrends S., Recent developments in urban logistics research – A review of the, Transport Res. Proc., 12, pp. 278-287, (2016); Bocarejo S J.P., Oviedo H D.R., Transport accessibility and social inequities: a tool for identification of mobility needs and evaluation of transport investments, J. Transport Geogr., 24, pp. 142-154, (2012); Borenstein S., Saloner G., Economics and electronic commerce, J. Econ. Perspect., 15, 1, pp. 3-12, (2001); Brannigan C., Et al., Study on Urban Mobility–Assessing and Improving the Accessibility of Urban Areas, (2017); Brown J.R., Goolsbee A., Does the Internet make markets more competitive? Evidence from the life insurance industry, J. Polit. Econ., 110, 3, pp. 481-507, (2002); Brynjolfsson E., Hu Y., Smith M.D., Consumer surplus in the digital economy: estimating the value of increased product variety at online booksellers, Manag. Sci., 49, 11, pp. 1580-1596, (2003); Cardenas I., Beckers J., Vanelslander T., E-commerce last-mile in Belgium: developing an external cost delivery index, Res. Transport. Buisness Manag., 24, pp. 123-129, (2017); Cascetta E., Carteni A., Montanino M., A behavioral model of accessibility based on the number of available opportunities, J. Transport Geogr., 51, pp. 45-58, (2016); Church A., Frost M., Sullivan K., Transport and social exclusion in London, Transport Pol., 7, 3, pp. 195-205, (2000); Dablanc L., Et al., CITYLAB Deliverable 2.1, Observatory of Strategic Developments Impacting Urban Logistics (2018 version), (2018); Dalvi M.Q., Martin K., The measurement of accessibility: some preliminary results, Transportation, 5, 1, pp. 17-42, (1976); Eurostat, E-shopping: Biggest increase Among You Internet Users, (2020); Geurs K., Accessibility, Land Use and Transport: Accessibility Evaluation of Land-Use and Transport Developments and Policy Strategy, (2006); Geurs K.T., Ritsema van Eck J.R., Accessibility Measures: Review and Applications. Evaluation of accessibility Impacts of Land-use Transportation Scenarios, and related Social and Economic Impact, (2001); Geurs K.T., Van Wee B., Accessibility evaluation of land-use and transport strategies: review and research directions, J. Transport Geogr., 12, 2, pp. 127-140, (2004); Gevaers R., Van de Voorde E., Vanelslander T., Characteristics and Typology of Last-Mile Logistics from an Innovation Perspective in an Urban Context. City Distribution and Urban Freight Transport: Multiple Perspectives, pp. 56-71, (2011); Gonzalez-Feliu J., Mercier A., A Combined People-Freight Accessibility Approach for Urban Retailing and Leisure Planning at Strategic Level, (2013); Gonzalez-Feliu J., Semet F., Routhier J.-L., Sustainable Urban Logistics: Concepts, Methods and Information Systems, (2014); Grieco M., Poverty mapping and sustainable transport: a neglected dimension, Res. Transport. Econ., 51, pp. 3-9, (2015); Gutierrez J., Garcia-Palomares J.C., Transport and Accessibility, (2020); Guzman L.A., Oviedo D., Rivera C., Assessing equity in transport accessibility to work and study: the Bogotá region, J. Transport Geogr., 58, pp. 236-246, (2017); Hansen W.G., How accessibility shapes land use, J. Am. Inst. Plan., 25, 2, pp. 73-76, (1959); Hesse M., Location matters, ACCESS Magazine, 1, 21, pp. 22-26, (2002); Huschebeck M., Leonardi J., Approaching delivery as a service, Transport Res. Proc., 46, pp. 61-68, (2020); Business Region Göteborg, (2020); Keeling K., Macaulay L.A., McGoldrick P., DiTV and e-commerce among disadvantaged community groups, Behav. Inf. Technol., 26, 6, pp. 545-560, (2007); Kenyon S., Lyons G., Rafferty J., Transport and social exclusion: investigating the possibility of promoting inclusion through virtual mobility, J. Transport Geogr., 10, 3, pp. 207-219, (2002); Kitchin R., Thrift N., International Encyclopedia of Human Geography, (2009); Klimberg R., McCullough B.D., Fundamentals of Predictive Analytics with JMP, (2016); Lim S.F.W., Jin X., Srai J.S., Consumer-driven E-Commerce, (2018); Litman T., Evaluating transportation equity, World Transport Pol. Pract., 8, 2, pp. 50-65, (2002); Litman T., Evaluating Transportation Diversity, (2017); Lucas K., A Critical Assessment of Accessibility Planning for Social Inclusion, in Accessibility Analysis and Transport Planning, (2012); Lucas K., Van Wee B., Maat K., A method to evaluate equitable accessibility: combining ethical theories and accessibility-based approaches, Transportation, 43, 3, pp. 473-490, (2016); Mena C., Et al., Realignment of the physical distribution process in omni-channel fulfillment, Int. J. Phys. Distrib. Logist. Manag., (2016); Morris A., E-literacy and the grey digital divide: a review with recommendations, J. Inform. Literacy, 1, 3, pp. 13-28, (2007); SAS Institute Inc., JMP(R) 14 Multivariate Methods, (2018); Postnord, The e-barometer Annual Report 2019, (2020); Roos J.M., Et al., The Consumption Report (rig. Konsumptionsrapporten 2019), (2019); Rosenbaum M.S., Seger-Guttmann T., Giraldo M., Commentary: vulnerable consumers in service settings, J. Serv. Market., (2017); Rust R.T., Lemon K.N., E-service and the consumer, Int. J. Electron. Commer., 5, 3, pp. 85-101, (2001); Which Grocery Delivery Company Offers the Best Service for Foreigners in Sweden?, in Thelocal.Se, (2020); Sverigesradio, Swedish Coronavirus Deaths Increase, with Concerns about Somali-Swedes in Particular, in Sverigesradio.Se, (2020); Taniguchi E., Thompson R., Yamada T., Recent Advances in Modelling City Logistics. City Logistics II, pp. 3-34, (2001); Thomopoulos N., Grant-Muller S., Tight M., Incorporating equity considerations in transport infrastructure evaluation: current practice and a proposed methodology, Eval. Progr. Plann., 32, 4, pp. 351-359, (2009); Van Wee B., The Traffic and Transport System and Effects on Accessibility, the Environment and Safety: an Introduction. The Transport System and Transport Policy, pp. 4-18, (2013); Van Wee B., Geurs K., Discussing equity and social exclusion in accessibility evaluations, Eur. J. Transport Infrastruct. Res., 11, 4, (2011); Van Wee B., Hagoort M., Annema J.A., Accessibility measures with competition, J. Transport Geogr., 9, 3, pp. 199-208, (2001); Weber J., Kwan M.-P., Evaluating the effects of geographic contexts on individual accessibility: a multilevel Approach1, Urban Geogr., 24, 8, pp. 647-671, (2003); Statista, Worldwide Retail e-commerce Sales, (2020)","I. Sanchez-Diaz; Service Management and Logistics, Technology Management and Economics, Chalmers University of Technology, Gothenburg, Vera Sandbergs Allé 8, 41296, Sweden; email: sanchez@chalmers.se",null,"Elsevier Ltd",{"$nulls":5},"0967070X",null,null,null,"English","Transp. Policy","Article","Final","All Open Access; Green Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85107920381"]
["Reardon T.; Heiman A.; Lu L.; Nuthalapati C.S.R.; Vos R.; Zilberman D.","Reardon, Thomas (7006621542); Heiman, Amir (7007018227); Lu, Liang (56895417800); Nuthalapati, Chandra S.R. (57191310778); Vos, Rob (7005330526); Zilberman, David (35578894000)","7006621542; 7007018227; 56895417800; 57191310778; 7005330526; 35578894000","“Pivoting” by food industry firms to cope with COVID-19 in developing regions: E-commerce and “copivoting” delivery intermediaries",2021.0,"Agricultural Economics (United Kingdom)",52.0,3.0,null,459.0,475.0,16.0,62.0,"10.1111/agec.12631","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85104826108&doi=10.1111%2fagec.12631&partnerID=40&md5=0ec37a08dda670e5b40ead8e15e8e0fb","Department of Agricultural, Food, and Resource Economics, Michigan State University, East Lansing, MI, United States; Department of Environmental Economics and Management and the Center for Agricultural Economics Research, Robert H. Smith Faculty of Agriculture, Food, and Environment, Hebrew University of Jerusalem, Rehovot, Israel; Department of Agricultural Economics and Rural Sociology, University of Idaho, Moscow, ID, United States; Institute of Economic Growth, Delhi, India; Markets, Trade, and Institutions Division, International Food Policy Research Institute, Washington, DC, United States; Department of Agricultural and Resource Economics, University of California, Berkeley, CA, United States","Reardon T., Department of Agricultural, Food, and Resource Economics, Michigan State University, East Lansing, MI, United States; Heiman A., Department of Environmental Economics and Management and the Center for Agricultural Economics Research, Robert H. Smith Faculty of Agriculture, Food, and Environment, Hebrew University of Jerusalem, Rehovot, Israel; Lu L., Department of Agricultural Economics and Rural Sociology, University of Idaho, Moscow, ID, United States; Nuthalapati C.S.R., Institute of Economic Growth, Delhi, India; Vos R., Markets, Trade, and Institutions Division, International Food Policy Research Institute, Washington, DC, United States; Zilberman D., Department of Agricultural and Resource Economics, University of California, Berkeley, CA, United States","Coronavirus disease 2019 and related lockdown policies in 2020 shocked food industry firms’ supply chains in developing regions. Firms “pivoted” to e-commerce to reach consumers and e-procurement to reach processors and farmers. “Delivery intermediaries” copivoted with food firms to help them deliver and procure. This was crucial to the ability of the food firms to pivot. The pandemic was a “crucible” that induced this set of fast-tracking innovations, accelerating the diffusion of e-commerce and delivery intermediaries, and enabling food industry firms to redesign, at least temporarily, and perhaps for the long term, their supply chains to be more resilient, and to weather the pandemic, supply consumers, and contribute to food security. We present a theoretical model to explain these firm strategies, and then apply the framework to classify firms’ practical strategies. We focus on cases in Asia and Latin America. Enabling policy and infrastructural conditions allowed firms to pivot and copivot fluidly. © 2021 International Association of Agricultural Economists","COVID-19; delivery intermediaries; developing region food supply chains; e-commerce; pivoting","Asia; Latin America; Coronavirus; COVID-19; developing world; electronic commerce; firm size; food industry; spatiotemporal analysis; strategic approach; viral disease",{"$nulls":4},"Godrej's own venture capital fund; Michigan AgBioResearch; United States Department of Agriculture National Institute of Food and Agriculture; North Dakota Agricultural Experiment Station, NDAES; Indian Council of Social Science Research, ICSSR","Funding text 1: We are thankful for funding from the United States Department of Agriculture National Institute of Food and Agriculture and Michigan AgBioResearch, as well as the Indian Council of Social Science Research and the Idaho Agricultural Experiment Station. We appreciate the extremely useful comments of Johan Swinnen as Guest Editor and to the reviewers.; Funding text 2: In India, Godrej (discussed above) partnered with several start‐up B2B firms to source intermediate inputs. These start‐ups were funded by Godrej's own venture capital fund (Omnivore, with additional funding from U.S. firm Sequoia Capital) started in 2010. Two illustrative start‐ups are DeHaat (meaning marketplace in Hindi) and Stellaps. These start‐ups functioned like Ninjacart and source crops and dairy, respectively, for Godrej, as well as for retailers, such as Reliance Fresh, and other delivery intermediaries, such as Zomato and Udaan (Mitter, 2020 ; Singh, 2020c ). Britannia, another large processing firm, used the B2B Agribazaar, as well as various local logistics firms during COVID‐19 to avoid the overcrowded, and hence, unsafe regular wholesale markets (Mathew, 2020 ). Moreover, ITC (discussed above) used its digital advisory application “e‐choupal” more intensively during the pandemic. E‐choupal provided information to farmers about prices via a mobile platform (Anand, 2020 ) and transport of crops from farms to their train network and coastal container shipments to ensure uninterrupted movement of grain and soy inputs during and right after the lockdown period (Kurmanath, 2020 ). 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Reardon; Department of Agricultural, Food, and Resource Economics, Michigan State University, East Lansing, United States; email: reardon@msu.edu",null,"Blackwell Publishing Ltd",{"$nulls":5},1695150.0,null,"AECNB",null,"English","Agric. Econ.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85104826108"]
["Zhu S.; Hu X.; Huang K.; Yuan Y.","Zhu, Shan (57218880410); Hu, Xiangpei (24481299300); Huang, Kai (55238241400); Yuan, Yufei (7402708857)","57218880410; 24481299300; 55238241400; 7402708857","Optimization of product category allocation in multiple warehouses to minimize splitting of online supermarket customer orders",2021.0,"European Journal of Operational Research",290.0,2.0,null,556.0,571.0,15.0,17.0,"10.1016/j.ejor.2020.08.024","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85090580165&doi=10.1016%2fj.ejor.2020.08.024&partnerID=40&md5=18224f3e816e22e344e8c791935056ec","Institute of Systems Engineering, Dalian University of Technology, Dalian, 116024, China; School of Management, Zhejiang University, Hangzhou, 310058, China; DeGroote School of Business, McMaster University, Hamilton, L8S 4L8, Canada","Zhu S., Institute of Systems Engineering, Dalian University of Technology, Dalian, 116024, China; Hu X., School of Management, Zhejiang University, Hangzhou, 310058, China; Huang K., DeGroote School of Business, McMaster University, Hamilton, L8S 4L8, Canada; Yuan Y., DeGroote School of Business, McMaster University, Hamilton, L8S 4L8, Canada","In an online supermarket, people may purchase multiple items in a single order for convenience or to obtain free delivery. Multi-item customer orders often need to be split into multiple shipments because the ordered items may be stored in different warehouses. Order splitting results in higher shipping costs. One way to reduce splitting is to store and retrieve all the items in a single warehouse. However, due to the vast volume of items sold by online supermarkets, it is difficult to build and operate such a warehouse. Another way is to optimize the allocation of products in multiple warehouses to reduce order splitting. In this paper, we propose a K-links heuristic clustering algorithm to optimize the product category allocation among multiple warehouses based on the distribution of multi-item orders to minimize the total number of order splits. Using online order and inventory data from a large Chinese online supermarket, we demonstrate that our algorithm performs well and dramatically reduces order splitting. © 2020 Elsevier B.V.","E-commerce order fulfillment; Heuristic clustering algorithm; Logistics; Order splitting; Warehouse products distribution","Clustering algorithms; Optimization; Retail stores; Sales; Ships; Customer orders; Inventory data; Multiple items; Multiple shipments; Online orders; Online supermarkets; Order splitting; Product categories; Warehouses",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (71421001, 71571067)","We are grateful for the careful and detailed feedback provided by three anonymous referees which improve our paper greatly. This work was supported by the Innovative Research Groups Program of the NSFC [ 71421001 , 2015–2020]; and the National Natural Science Foundation of China (NSFC) [ 71571067 , 2016–2019].","Acimovic J.A., Lowering outbound shipping costs in an online retail environment by making better fulfillment and replenishment decisions, (2012); Acimovic J., Graves S.C., Making better fulfillment decisions on the fly in an online retail environment, Manufacturing & Service Operations Management, 17, 1, pp. 34-51, (2014); Acimovic J., Graves S.C., Mitigating spillover in online retailing via replenishment, Manufacturing & Service Operations Management, 19, 3, pp. 419-436, (2017); Bebitoglu B., Sen A., Kaminsky P., Multi-location assortment optimization under capacity constraints, SSRN Electronic Journal, (2018); Becerril-Arreola R., Leng M., Parlar M., Online retailers’ promotional pricing, free-shipping threshold, and inventory decisions: A simulation-based analysis, European Journal of Operational Research, 230, 2, pp. 272-283, (2013); Benati S., Puerto J., Rodriguez-Chia A.M., Clustering data that are graph connected, European Journal of Operational Research, 261, 1, pp. 43-53, (2017); Boysen N., de Koster R., Weidinger F., Warehousing in the e-commerce era: A survey, European Journal of Operational Research, 277, 2, pp. 396-411, (2019); Bruglieri M., Ehrgott M., Hamacher H.W., Maffioli F., An annotated bibliography of combinatorial optimization problems with fixed cardinality constraints, Discrete Applied Mathematics, 154, 9, pp. 1344-1357, (2006); Carrizosa E., Mladenovic N., Todosijevic R., Variable neighborhood search for minimum sum-of-squares clustering on networks, European Journal of Operational Research, 230, 2, pp. 356-363, (2013); Catalan A., Fisher M., Assortment allocation to distribution centers to minimize split customer orders, SSRN Electronic Journal, (2012); Chuang Y.F., Lee H.T., Lai Y.C., Item-associated cluster assignment model on storage allocation problems, Computers & Industrial Engineering, 63, 4, pp. 1171-1177, (2012); Chuang Y.F., Lee H.T., Tan S.W., A robust heuristic method on the clustering-assignment problem model, Computers & Industrial Engineering, 98, pp. 63-67, (2016); DeValve L., Wei Y., Wu D., Yuan R., Understanding the value of fulfillment flexibility in an online retailing environment, SSRN Electronic Journal, (2018); Feige U., Langberg M., Approximation algorithms for maximization problems arising in graph partitioning, Journal of Algorithms, 41, 2, pp. 174-211, (2001); Goncalves G.M., Lourenco L.L., Mathematical formulations for the K clusters with fixed cardinality problem, Computers & Industrial Engineering, 135, pp. 593-600, (2019); Herran A., Colmenar J.M., Duarte A., A Variable neighborhood Search approach for the Vertex Bisection problem, Information Sciences, (2018); Hsieh L.F., Huang Y.C., New batch construction heuristics to optimise the performance of order picking systems, International Journal of Production Economics, 131, 2, pp. 618-630, (2011); Huang Z., Extensions to the k-means algorithm for clustering large data sets with categorical values, Data Mining and Knowledge Discovery, 2, 3, pp. 283-304, (1998); 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Santi E., Aloise D., Blanchard S.J., A model for clustering data from heterogeneous dissimilarities, European Journal of Operational Research, 253, 3, pp. 659-672, (2016); Savelsbergh M.W., The vehicle routing problem with time windows: Minimizing route duration, Journal On Computing, 4, 2, pp. 146-154, (1992); Torabi S.A., Hassini E., Jeihoonian M., Fulfillment source allocation, inventory transshipment, and customer order transfer in e-tailing, Transportation Research Part E: Logistics and Transportation Review, 79, pp. 128-144, (2015); (2019); Wu X., Che A., Energy-efficient no-wait permutation flow shop scheduling by adaptive multi-objective variable neighborhood search, Omega, (2019); Xu P.J., Order fulfillment in online retailing: What goes where, (2005); Xu P.J., Allgor R., Graves S.C., Benefits of reevaluating real-time order fulfillment decisions, Manufacturing & Service Operations Management, 11, 2, pp. 340-355, (2009); Zhang Y., Huang M., Hu X., Sun L., Package consolidation approach to the split-order fulfillment problem of online supermarkets, Journal of the Operational Research Society, 69, 1, pp. 127-141, (2018); Zhang Y., Lin W.H., Huang M., Hu X., Multi-warehouse package consolidation for split orders in online retailing, European Journal of Operational Research, (2019)","X. Hu; School of Management, Zhejiang University, Hangzhou, 310058, China; email: drhxp@dlut.edu.cn",null,"Elsevier B.V.",{"$nulls":5},3772217.0,null,"EJORD",null,"English","Eur J Oper Res","Article","Final",null,"Scopus","2-s2.0-85090580165"]
["Mishra K.N.; Pandey S.C.","Mishra, Kamta Nath (57192188286); Pandey, Subhash Chandra (36865743600)","57192188286; 36865743600","Fraud Prediction in Smart Societies Using Logistic Regression and k-fold Machine Learning Techniques",2021.0,"Wireless Personal Communications",119.0,2.0,null,1341.0,1367.0,26.0,11.0,"10.1007/s11277-021-08283-9","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85101816961&doi=10.1007%2fs11277-021-08283-9&partnerID=40&md5=77b6349cc6716f632a600917da1ad46d","Department of Computer Science and Engineering, Birla Institute of Technology, Mesra, India","Mishra K.N., Department of Computer Science and Engineering, Birla Institute of Technology, Mesra, India; Pandey S.C., Department of Computer Science and Engineering, Birla Institute of Technology, Mesra, India","The credit/debit card deceit detection is an enormously difficult task. However, it is a well known problem of our cloud based mobile internet society and it must be solved by technocrats in the welfare of societal mental harassments. The main problem in executing credit/debit card fraud detection technique is the availability of limited amount of fraud related data like transaction amount, transaction date, transaction time, address, and vendor category code related to the frauds. It is the truth of mobile internet world that there are billions of potential places and e-commerce websites where a credit/debit card can be used by fraudulent people for online transactions and payments which make it exceedingly thorny to trace the pattern of frauds. Moreover, the problem of fraud detection in cloud— Internet of Things (IoT) based smart societies has numerous constraints like continuous change in the behavior of normal and fraudulent persons, the fraudulent people try to develop and use new method for executing frauds, and very little availability of frauds related bench mark data sets. In this research article, the authors have presented logistic regression based k-fold machine learning technique (MLT) for fraud detection and prevention in cloud-IoT based smart societal environment. The k-fold method creates multiple folds of bank transactions related data before implementing logistic regression and MLT. The logistic regression performs logic based regression analysis and the intelligent machine learning approach performs registration, classification, clustering, dimensionality reduction, deep learning, training, and reinforcement learning steps on the received bank transactions data. The implementation of proposed methodology and its further analysis using intelligent machine learning tools like ROC (Receiver Operating Characteristic) curve, confusion matrix, mean-recall score value, and precision recall curves for European banks day-to-day transactions related bench mark data set reveal that the proposed methodology is efficient, accurate, and reliable for detecting frauds in cloud-IoT based smart societal environment. © 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature.","Cloud-IoT based distributed environment; Confusion matrix; Fraud detection; Fraudulent; Logistic regression; Machine learning; Mean-recall-score; ROC curve","Crime; Deep learning; Dimensionality reduction; Internet of things; Logistic regression; Mobile commerce; Predictive analytics; Reinforcement learning; Bank transactions; Confusion matrices; E-commerce websites; Intelligent machine; Internet of Things (IOT); Machine learning techniques; Online transaction; Receiver operating characteristics; Learning systems",{"$nulls":4},"Birla Institute of Scientific Research, BISR, (0012)",null,"Aleskerov E., Freisleben B., Rao B., CARDWATCH: A neural network-based database mining system for credit card fraud detection, In Proceedings of the IEEE/IAFE on Computational Intelligence for Financial Engineering, pp. 220-226, (1997); Anderson R., The credit scoring toolkit: Theory and practice for retail credit risk management and decision automation, (2007); Card Fraud Facts and Figures; Bellis M., Who Invented Credit Cards-The History of Credit Cards.; Mena J., Investigate data mining for security and criminal detection, pp. 1-272, (2003); Ray S., Mishra K.N., Dutta S., Big data security issues from the perspective of IoT and cloud computing: a review, Recent Advances in Computer Science and Communications, Benthem Science Journal, 13, pp. 1-25, (2020); Chen R., Chiu M., Huang Y., Chen L., Detecting credit card fraud by using questionnaire responded transaction model based on SVMs, In Proceedings of IDEAL2004, pp. 800-806, (2004); 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Pandey S.C., Mind, Machine, and Image Processing, Deep Learning and Image Processing, pp. 1-26, (2018); Pandey S.C., Recent developments in big data analysis tools using apache spark, book on big data processing using spark in cloud, pp. 217-236, (2019); Pandey S.C., Nandi G.C., TSD based framework for mining the induction rules, Journal of Computational Science, 5, pp. 184-195, (2015); Mishra K.N., Chakraborty C., A novel approach towards enhancing the quality of life in smart cities using clouds and iot based technologies, a book on digital twins technologies and smart cities, pp. 19-35, (2020); Mishra K.N., Importance of AADhar based smartcard systems’s implementation in developing countries, a book on advances in soft computing and machine learning in image processing, pp. 443-457, (2018); Mishra K.N., A novel mechanism for cloud data management in distributed environment, a book on data intensive computing applications for big data, pp. 386-413, (2018); Mishra K.N., AAdhar based smartcard system for security management in South Asia, 2Nd IEEE International Conference on Control Computing Communication and Materials (IEEE ICCCCM—2016), pp. 106-111, (2016); 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Acad. Sci. Lett., 43, 1-6, (2020)","K.N. Mishra; Department of Computer Science and Engineering, Birla Institute of Technology, Mesra, India; email: mishrakn@yahoo.com",null,"Springer",{"$nulls":5},9296212.0,null,"WPCOF",null,"English","Wireless Pers Commun","Article","Final",null,"Scopus","2-s2.0-85101816961"]
["Archetti C.; Bertazzi L.","Archetti, Claudia (6506478737); Bertazzi, Luca (6602103396)","6506478737; 6602103396","Recent challenges in Routing and Inventory Routing: E-commerce and last-mile delivery",2021.0,"Networks",77.0,2.0,null,255.0,268.0,13.0,49.0,"10.1002/net.21995","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85092113282&doi=10.1002%2fnet.21995&partnerID=40&md5=cc16a3baef91c505488d7b03eef8188a","Department of Information Systems, Decision Sciences and Statistics, ESSEC Business School of Paris, Paris, France; Department of Economics and Management, University of Brescia, Brescia, Italy","Archetti C., Department of Information Systems, Decision Sciences and Statistics, ESSEC Business School of Paris, Paris, France; Bertazzi L., Department of Economics and Management, University of Brescia, Brescia, Italy","In the e-commerce era, vendors have to satisfy a large number of on-line orders, mainly from private customers, with low weight and volume, reduced delivery time, and overlap of customers' time windows. Production is made available all day long. New strategies and new technologies are emerging for deliveries. The processing time of the orders is reduced. These new features generate interesting challenges in formulating and solving Routing and Inventory Routing problems. After discussing these features and the corresponding challenges, we recall the relevant literature in Routing and Inventory Routing and provide future research directions, mainly related to routing problems with release dates, routing problems with crowdshipping, and inventory routing problems in the e-commerce era. © 2020 Wiley Periodicals LLC.","crowdshipping; e-commerce; inventory routing; last-mile delivery; release dates; routing problems","Customer satisfaction; Delivery time; Future research directions; Inventory routing; Inventory routing problems; Private customers; Processing time; Routing problems; Time windows; Electronic commerce",{"$nulls":6},"Adulyasak Y., Cordeau J.F., Jans R., Formulations and branch-and-cut algorithms for multivehicle production and inventory routing problems, INFORMS J. Comput., 26, pp. 103-120, (2013); Agatz N., Bouman P., Schmidt M., Optimization approaches for the traveling salesman problem with drone, Transp. 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Bertazzi; Department of Economics and Management, University of Brescia, Brescia, Italy; email: luca.bertazzi@unibs.it",null,"Wiley-Liss Inc.",{"$nulls":5},283045.0,null,null,null,"English","Networks","Article","Final",null,"Scopus","2-s2.0-85092113282"]
["Issaoui Y.; Khiat A.; Bahnasse A.; Ouajji H.","Issaoui, Yassine (57214777513); Khiat, Azeddine (57193027037); Bahnasse, Ayoub (57189848864); Ouajji, Hassan (57188879248)","57214777513; 57193027037; 57189848864; 57188879248","An Advanced LSTM Model for Optimal Scheduling in Smart Logistic Environment: E-Commerce Case",2021.0,"IEEE Access",9.0,null,null,126337.0,126356.0,19.0,10.0,"10.1109/ACCESS.2021.3111306","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85114737133&doi=10.1109%2fACCESS.2021.3111306&partnerID=40&md5=27d64671ba172ad995e402536dd9df67","SSDIA Laboratory, Hassan II University of Casablanca, Casablanca, Morocco; Ensam Casablanca, Hassan II University of Casablanca, Casablanca, Morocco","Issaoui Y., SSDIA Laboratory, Hassan II University of Casablanca, Casablanca, Morocco; Khiat A., SSDIA Laboratory, Hassan II University of Casablanca, Casablanca, Morocco; Bahnasse A., Ensam Casablanca, Hassan II University of Casablanca, Casablanca, Morocco; Ouajji H., SSDIA Laboratory, Hassan II University of Casablanca, Casablanca, Morocco","At present, most logistics systems, especially those dedicated to e-commerce, are based on artificial intelligence techniques to offer better services and increase outcomes. However, the variety and complexity of resource allocation, as well as task scheduling, denote that dynamic environments have still great challenges to overcome. So advanced models based on strong algorithms are required. Introducing advanced models into scheduling solutions is a promising way to enhance logistics efficiency. As a result, managing system resources remain essential to optimize task scheduling respecting the interactive impacts, and logistics systems requirements. In response to these challenges, in this paper, a powerful solution based on a Long short-term memory (LSTM) model is proposed to optimize resource allocation and to enhance task scheduling in a smart logistics framework. This paper explores some of the most important scheduling techniques and hypothesizes that deep learning techniques might be able to afford accurate approaches. The proposed smart logistics model lays on strong techniques, for that, experimental simulations were conducted using various project instances. The validation tests demonstrated competitive results with important performance rates i.e.: accuracy of 92,44% with a precision of 93,83, a recall of 95.18%, F1-score of 94,92%, and an AUC of 88,17%. These results reveal the proof-of-principle for using LSTM models for effective and truthful logistics operations. © 2013 IEEE.","Artificial intelligence; deep learning; LSTM; optimization; smart logistics; task management; task scheduling","Deep learning; Electronic commerce; Multitasking; Resource allocation; Scheduling; Artificial intelligence techniques; Dynamic environments; Experimental simulations; Learning techniques; Logistics efficiency; Logistics operations; Proof of principles; Scheduling techniques; Long short-term memory",{"$nulls":6},"Szymaska O., Adamczak M., Cyplik P., Logistics 4.0-A new paradigm or set of known solutions?, Res. 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["Ansari S.; Gupta S.","Ansari, Sana (58710661400); Gupta, Sumeet (55495227700)","58710661400; 55495227700","Customer perception of the deceptiveness of online product reviews: A speech act theory perspective",2021.0,"International Journal of Information Management",57.0,null,102286.0,null,null,null,41.0,"10.1016/j.ijinfomgt.2020.102286","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85097788420&doi=10.1016%2fj.ijinfomgt.2020.102286&partnerID=40&md5=1e8c8dcb77e62b9e666c6bf602ee3410","Department of IT & Systems, Indian Institute of Management Raipur, Atal Nagar, P.O. - Kurru (Abhanpur), Raipur, 493 661, Chhattisgarh, India","Ansari S., Department of IT & Systems, Indian Institute of Management Raipur, Atal Nagar, P.O. - Kurru (Abhanpur), Raipur, 493 661, Chhattisgarh, India; Gupta S., Department of IT & Systems, Indian Institute of Management Raipur, Atal Nagar, P.O. - Kurru (Abhanpur), Raipur, 493 661, Chhattisgarh, India","With the presence of fake reviews on e-commerce platforms, the reliability of reviews becomes questionable. The extant literature demonstrates the impact of fake reviews on product sales and proposes several algorithms to prevent fake reviews from being displayed on the platform. However, what has largely remained uninvestigated is how customers perceive reviews present on the e-commerce platform. Based on the speech act theory, we develop a theoretical framework that explains how the linguistic style (both at the word and the structural level) acts as a cue for assessing a reviewer's (in)sincere intentions. We evaluate the framework on a corpus of 120 online product reviews – each examined by at least 50 customers – using the fractional logit model. Results suggest that the communication style of a speaker reflects his/her intention. Reviews with less contextual embedding, argument structuring, and flattering through non-verbal cues trigger customers towards perceiving a review as deceptive. © 2020 Elsevier Ltd","Customers perception; Fake reviews; Linguistic cues; Review manipulation; Speech act theory","Electronic commerce; Linguistics; Logistic regression; Communication styles; Customer perceptions; Linguistic styles; Logit modeling; Online product reviews; Speech act theory; Structural levels; Theoretical framework; Sales",{"$nulls":6},"Anderson E.T., Simester D.I., Reviews without a purchase: Low ratings, loyal customers, and deception, Journal of Marketing Research, 51, 3, pp. 249-269, (2014); Antioco M., Coussement K., Misreading of consumer dissatisfaction in online product reviews: Writing style as a cause for bias, International Journal of Information Management, 38, 1, pp. 301-310, (2018); Aulakh G., Flipkart sells $200 million worth of mobile phones during’ Big Billion’ sale, (2015); Austin J.L., How to do things with words, 88, (1975); Bower G.H., Morrow D.G., Mental models in narrative comprehension, Science, 247, 4938, pp. 44-48, (1990); Chevalier J.A., Mayzlin D., The effect of word of mouth on sales: Online book reviews, Journal of Marketing Research, 43, 3, pp. 345-354, (2006); Cui G., Lui H.-K., Guo X., The effect of online consumer reviews on new product sales, International Journal of Electronic Commerce, 17, 1, pp. 39-58, (2012); del Pilar Salas-Zarate M., Paredes-Valverde M.A., Rodriguez-Garcia M.A., Valencia-Garcia R., Alor-Hernandez G., Automatic detection of satire in Twitter: A psycholinguistic-based approach, Knowledge-Based Systems, 128, pp. 20-33, (2017); Dellarocas C., Strategic manipulation of internet opinion forums: Implications for consumers and firms, Management Science, 52, 10, pp. 1577-1593, (2006); Dellarocas C., Zhang X.M., Awad N.F., Exploring the value of online product reviews in forecasting sales: The case of motion pictures, Journal of Interactive Marketing, 21, 4, pp. 23-45, (2007); DePaulo B.M., Lindsay J.J., Malone B.E., Muhlenbruck L., Charlton K., Cooper H., Cues to deception, Psychological Bulletin, 129, 1, (2003); DePaulo B.M., Rosenthal R., Green C.R., Rosenkrantz J., Diagnosing deceptive and mixed messages from verbal and nonverbal cues, Journal of Experimental Social Psychology, 18, 5, pp. 433-446, (1982); Dwivedi Y.K., Ismagilova E., Hughes D.L., Carlson J., Filieri R., Jacobson J., Krishen A.S., Setting the future of digital and social media marketing research: Perspectives and research propositions, International Journal of Information Management, (2020); Ekman P., Telling lies: Clues to deceit in the marketplace, politics, and marriage, (1991); Ekman P., Friesen W.V., O'Sullivan M., Smiles when lying. 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Gupta; Department of IT & Systems, Indian Institute of Management Raipur, Raipur, Atal Nagar, P.O. - Kurru (Abhanpur), 493 661, India; email: sumeetgupta@iimraipur.ac.in",null,"Elsevier Ltd",{"$nulls":5},2684012.0,null,"IJMAE",null,"English","Int J Inf Manage","Article","Final",null,"Scopus","2-s2.0-85097788420"]
["Perkumiene D.; Osamede A.; Andriukaitiene R.; Beriozovas O.","Perkumiene, Dalia (56355264500); Osamede, Agbonmere (57406692000); Andriukaitiene, Regina (56405579500); Beriozovas, Olegas (57406512700)","56355264500; 57406692000; 56405579500; 57406512700","The impact of COVID-19 on the transportation and logistics industry",2021.0,"Problems and Perspectives in Management",19.0,4.0,null,458.0,469.0,11.0,13.0,"10.21511/ppm.19(4).2021.37","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85122570155&doi=10.21511%2fppm.19%284%29.2021.37&partnerID=40&md5=b2046064ec0abd787d86b278608211f4","Kazimieras Simonavičius University, Vytautas Magnus University, Lithuania; Vytautas Magnus University Agriculture Academy, Lithuania; Department of Management of Sports and Tourism, Lithuanian Sports University, Lithuania; Kazimieras Simonavičius University, Lithuania","Perkumiene D., Kazimieras Simonavičius University, Vytautas Magnus University, Lithuania; Osamede A., Vytautas Magnus University Agriculture Academy, Lithuania; Andriukaitiene R., Department of Management of Sports and Tourism, Lithuanian Sports University, Lithuania; Beriozovas O., Kazimieras Simonavičius University, Lithuania","In this present age of globalization, the logistics and transportation industry has become an integral part of most businesses/firms as it is aimed at ensuring the effective movement of people, distribution of goods and services from one location to another on time. Therefore, this paper aims to analyze the impact of COVID-19 on the logistics and transportation sectors. The qualitative research approach was adopted using analysis and synthesis of scientific literature, data from news reports, organizational sites, and a case study of data contents. The paper presented the analysis of negative and positive effects of COVID-19 on the logistics and transportation industry. The study also discusses possible strategies and further steps for improvement of the logistics and transportation sector, including the automation and introduction of other technologies, a sustainable and flexible transportation system, cooperation of logistics and transportation business. Findings regarding the positive implications of COVID-19 show noticeable advancements in the logistics and transportation sector, such as the rise of e-commerce businesses with efficient delivery options, and the development of 3rd party logistics services as more companies outsource supply chain operations. The study revealed the importance of strategic planning with a joint effort from the research centers, public sector, private sector, and educational institutions as one of the proposed solutions for the logistics and transportation industry. © Dalia Perkumiene, Agbonmere Osamede, Regina Andriukaitiene, Olegas Beriozovas, 2021","Economic sectors; Globalization; Logistics; Pandemic; Strategy; Transportation",{"$nulls":7},"Borca B., Putz L. 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N., Reimagining the post-pandemic city, (2020); Lin Y., Fan D., Shi X., Fu M., The effects of supply chain diversification during the COVID-19 crisis: Evidence from Chinese manufacturers, Transportation Research Part E: Logistics and Transportation Review, 155, (2021); Loske D., The impact of COVID-19 on transport volume and freight capacity dynamics: An empirical analysis in German food retail logistics, Transportation Research Interdisciplinary Perspectives, 6, (2020); Luman R., Soroka O., Konings J., ING’s transport and logistics sector outlook, (2021); Mishra K., Rampal J., The COVID-19 pandemic and food insecurity: A viewpoint on India, World Development, 135, (2020); Mitrega M., Choi T-M., How small-and-medium transportation companies handle asymmetric customer relationships under COVID-19 pandemic: A multi-method study, Transportation Research Part E: Logistics and Transportation Review, 148, (2021); Mouratidis K., Peters S., van Wee B., Transportation technologies, sharing economy, and tele activities: Implications for built environment and travel, Transportation Research Part D: Transport and Environment, 92, (2021); Okeleke U., Aponjolosun M., A study on the effects of COVID–19 pandemic on Nigerian seafarers, Journal Of Sustainable Development Of Transport And Logistics, 5, 2, pp. 135-142, (2020); Perkumiene D., Pranskuniene R., Vienazindiene M., Grigiene, The Right to A Clean Environment: Considering Green Logistics and Sustainable Tourism, International Journal of Environmental Research and Public Health, 17, 9, (2020); Pranskuniene R., Perkumiene D., Public Perceptions on City Landscaping during the Outbreak of Coronavirus Disease: The Case of Vilnius Pop-Up Beach, Lithuania, Land, 10, 1, (2021); Rudmin F. W., The Consumer Science of Sharing: A Discussant’s Observations, Journal of the Association for Consumer Research, 1, 2, pp. 198-209, (2016); Shihui X., Saad R., Yong H., Kamran J., Tasawar J., Artene A. E., Effect of COVID-19 Pandemic on Service Sector Sustainability and Growth, Frontiers in Psychology, 12, (2021); Subramanya K., Kermanshachi S., Impact of COVID-19 on transportation industry: Comparative analysis of road, air, and rail transportation modes, International Conference on Transportation and Development, 2021, (2021); Tan L., Ma C., Choice behavior of commuters’ rail transit mode during the COVID-19 pandemic based on logistic model, Journal of Traffic and Transportation Engineering (English Edition), 8, 2, pp. 186-195, (2021); Tseng Y., Yue W. L., Taylor M. A. P., The role of transportation in logistics chain, Proceedings of the Eastern Asia Society for Transportation Studies, 5, pp. 1657-1672, (2005); Vidya C. T., Prabheesh K. P., Implications of COVID-19 pandemic on the global trade networks, Emerging Market Finance and Trade, 56, 10, pp. 2408-2421, (2020); Vienazindiene M., Tamuliene V., Zaleckiene J., Green logistics practices seeking Development of Sustainability: Evidence from Lithuanian Transportation and Logistics Companies, Energies, 14, 22, (2021); Analysis: Impact of COVID-19 on Logistics Industry; Vveinhardt J., Andriukaitiene R., Social Responsibility Discourse in Empirical and Theoretical Lithuanian Scientific Studies, Inžinerinė Ekonomika – Engineering Economics, 25, 5, pp. 578-588, (2014); WHO Coronavirus (COVID-19) dashboard, (2021); Yu Z., Xiao Y., Li Y., The response of the labor force participation rate to an epidemic: Evidence from a cross-country analysis, Emerging Markets Finance and Trade, 56, 10, pp. 2390-2407, (2020); Wang T., Leung R., Woo L. F., Lee A., 2021 Risk Radar: Transport and Logistics Sector, KPMG China’s Transport and Logistics practice, (2021); Zeng Z., Chen P. J., Lew A. A., From high-touch to high-tech: COVID-19 drives robotics adoption, Tourism Geographies, 22, 3, pp. 724-734, (2020)",null,null,"LLC CPC Business Perspectives",{"$nulls":5},1.7277051E7,null,null,null,"English","Probl. Perspect. Manage.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85122570155"]
["Wang C.-N.; Dang T.-T.; Nguyen N.-A.-T.","Wang, Chia-Nan (57757351100); Dang, Thanh-Tuan (57218565464); Nguyen, Ngoc-Ai-Thy (57218570813)","57757351100; 57218565464; 57218570813","Outsourcing reverse logistics for e-commerce retailers: A two-stage fuzzy optimization approach",2021.0,"Axioms",10.0,1.0,34.0,null,null,null,47.0,"10.3390/axioms10010034","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85103249500&doi=10.3390%2faxioms10010034&partnerID=40&md5=9646e000cfd30ad563540cf4cc3f7d13","Department of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung, 80778, Taiwan; Department of Logistics and Supply Chain Management, Hong Bang International University, Ho Chi Minh, 723000, Viet Nam","Wang C.-N., Department of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung, 80778, Taiwan; Dang T.-T., Department of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung, 80778, Taiwan, Department of Logistics and Supply Chain Management, Hong Bang International University, Ho Chi Minh, 723000, Viet Nam; Nguyen N.-A.-T., Department of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung, 80778, Taiwan","On the heels of the online shopping boom during the Covid-19 pandemic, the electronic commerce (e-commerce) surge has many businesses facing an influx in product returns. Thus, relevant companies must implement robust reverse logistics strategies to reflect the increased importance of the capability. Reverse logistics also plays a radical role in any business’s sustainable development as a process of reusing, remanufacturing, and redistributing products. Within this context, outsourcing to a third-party reverse logistics provider (3PRLP) has been identified as one of the most important management strategies for today’s organizations, especially e-commerce players. The objective of this study is to develop a decision support system to assist businesses in the selection and evaluation of different 3PRLPs by a hybrid fuzzy multicriteria decision-making (MCDM) approach. Relevant criteria concerning the economic, environmental, social, and risk fac-tors are incorporated and taken into the models. For obtaining more scientific and accurate ranking results, linguistic terms are adopted to reduce fuzziness and uncertainties of criteria weights in the natural decision-making process. The fuzzy analytic hierarchy process (FAHP) is applied to meas-ure the criteria’s relative significance over the evaluation process. The fuzzy technique for order preference by similarity to an ideal solution (FTOPSIS) is then used to rank the alternatives. The prescribed method was adopted for solving a case study on the 3PRLP selection for an online mer-chant in Vietnam. As a result, the most compatible 3PRLP was determined. The study also indicated that “lead time,” “customer’s voice,” “cost,” “delivery and service,” and “quality” are the most dominant drivers when selecting 3PLRLs. This study aims to provide a more complete and robust evaluation process to e-commerce businesses and any organization that deals with supply chain management in determining the optimized reverse logistics partners. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.","Decision making; E-commerce; FAHP; FTOPSIS; Outsource; Recycling; Reverse logistics; Sustainability; Triangular fuzzy number",{"$nulls":5},"National Kaohsiung University of Science and Technology, (MOST 109-2622-E-992-026); National Kaohsiung University of Science and Technology, Ministry of Sciences and Technology in Taiwan; Ministry of Science and Technology, Taiwan, MOST","Funding text 1: Acknowledgments: The authors appreciate the support from the National Kaohsiung University of Science and Technology, Ministry of Sciences and Technology in Taiwan.; Funding text 2: Funding: This research was partly supported by the National Kaohsiung University of Science and Technology, and MOST 109-2622-E-992-026 from the Ministry of Sciences and Technology in Taiwan.","Sahay B.S., Srivastava S.K., Srivastava R.K., Managing Product Returns for Reverse Logistics, Int. J. Phys. Distrib. Logist. 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Appl, 36, pp. 4387-4398, (2009); Moberg C.R., Speh T.W., Third–Party Warehousing Selection: A Comparison of National and Regional Firms, Am. J. Bus, 19, pp. 71-76, (2004); Sinkovics R.R., Roath A.S., Strategic Orientation, Capabilities, and Performance in Manufacturer—3PL Relationships, J. Bus. Logist, 25, pp. 43-64, (2004); Yang J., Wang J., Wong C.W., Lai K.H., Relational Stability and Alliance Performance in Supply Chain, Omega, 36, pp. 600-608, (2008); Saaty T.L., The Analytic Hierarchy Process, (1980); Tzeng G.H., Huang J.J., Multiple Attribute Decision Making: Methods and Applications, (2011); Spencer M.S., Rogers D.S., Daugherty P.J., JIT Systems and External Logistics Suppliers, Int. J. Oper. Prod. Manag, 14, pp. 60-74, (1994); Tsai M.C., Wen C.H., Chen C.S., Demand Choices of High-Tech Industry for Logistics Service Providers—an Empirical Case of an Offshore Science Park in Taiwan, Ind. Mark. Manag, 36, pp. 617-626, (2007); Mavi R.K., Goh M., Zarbakhshnia N., Sustainable Third-Party Reverse Logistic Provider Selection with Fuzzy SWARA and Fuzzy MOORA in Plastic Industry, Int. J. Adv. Manuf. Technol, 91, pp. 2401-2418, (2017); Efendigil T., Onut S., Kongar E., A Holistic Approach for Selecting a Third-Party Reverse Logistics Provider in the Presence of Vagueness, Comput. Ind. Eng, 54, pp. 269-287, (2008); Goebel P., Reuter C., Pibernik R., Sichtmann C., The Influence of Ethical Culture on Supplier Selection in the Context of Sustainable Sourcing, Int. J. Prod. Econ, 140, pp. 7-17, (2012); Ni J., Chu L.K., Yen B.P., Coordinating Operational Policy with Financial Hedging for Risk-Averse Firms, Omega, 59, pp. 279-289, (2016); Da Silveira Guimaraes J.L., Salomon V.A.P., ANP Applied to the Evaluation of Performance Indicators of Reverse Logistics in Footwear Industry, Procedia Comput. Sci, 55, pp. 139-148, (2015); Mitra S., Karathanasopoulos A., Sermpinis G., Dunis C., Hood J., Operational Risk: Emerging Markets, Sectors and Measure-ment, Eur. J. Oper. Res, 241, pp. 122-132, (2015); Zadeh L.A., Fuzzy Sets, Inf. Control, 8, pp. 338-358, (1965); Sun C.C., A Performance Evaluation Model by Integrating Fuzzy AHP and Fuzzy TOPSIS Methods, Expert Syst. Appl, 37, pp. 7745-7754, (2010); Chen C.T., Extensions of the TOPSIS for Group Decision-Making Under Fuzzy Environment, Fuzzy Sets Syst, 114, pp. 1-9, (2000); Wang C.-N., Dang T.-T., Nguyen N.-A.-T., Le T.-T.-H., Supporting Better Decision-Making: A Combined Grey Model and Data Envelopment Analysis for Efficiency Evaluation in E-Commerce Marketplaces, Sustainability, 12, (2020); Chou Y.C., Yen H.Y., Dang V.T., Sun C.C., Assessing the Human Resource in Science and Technology for Asian Countries: Application of Fuzzy AHP and Fuzzy TOPSIS, Symmetry, 11, (2019); Buckley J.J., Ranking Alternatives Using Fuzzy Numbers, Fuzzy Sets Syst, 15, pp. 21-31, (1985); Wang C.-N., Dang T.-T., Le T.Q., Kewcharoenwong P., Transportation Optimization Models for Intermodal Networks with Fuzzy Node Capacity, Detour Factor, and Vehicle Utilization Constraints, Mathematics, 8, (2020); E-Commerce Logistics: Emerging Opportunities in Vietnam; Tang Y.-C., Beynon M.J., Application and Development of a Fuzzy Analytic Hierarchy Process within a Capital Investment Study, J. Econ. Manag, 1, pp. 207-230, (2005); Shekhovtsov A., Kozlov V., Nosov V., Salabun W., Efficiency of Methods for Determining the Relevance of Criteria in Sustainable Transport Problems: A Comparative Case Study, Sustainability, 12, (2020); Wang C.-N., Nhieu N.-L., Chung Y.-C., Pham H.-T., Multi-Objective Optimization Models for Sustainable Perishable Inter-modal Multi-Product Networks with Delivery Time Window, Mathematics, 9, (2021)","C.-N. Wang; Department of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung, 80778, Taiwan; email: cn.wang@nkust.edu.tw; T.-T. Dang; Department of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung, 80778, Taiwan; email: tuandang.ise@gmail.com; T.-T. Dang; Department of Logistics and Supply Chain Management, Hong Bang International University, Ho Chi Minh, 723000, Viet Nam; email: tuandang.ise@gmail.com; N.-A.-T. Nguyen; Department of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung, 80778, Taiwan; email: thy.logistics@gmail.com",null,"MDPI AG",{"$nulls":5},2.075168E7,null,null,null,"English","Axioms","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85103249500"]
["Ileberi E.; Sun Y.; Wang Z.","Ileberi, Emmanuel (57387530900); Sun, Yanxia (35180292400); Wang, Zenghui (7410034341)","57387530900; 35180292400; 7410034341","Performance Evaluation of Machine Learning Methods for Credit Card Fraud Detection Using SMOTE and AdaBoost",2021.0,"IEEE Access",9.0,null,null,165286.0,165294.0,8.0,43.0,"10.1109/ACCESS.2021.3134330","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121800267&doi=10.1109%2fACCESS.2021.3134330&partnerID=40&md5=3279a3305e63674ca1e01aaf98892742","Department of Electrical and Electronic Engineering Science, University of Johannesburg, Johannesburg, 2094, South Africa; Department of Electrical Engineering, University of South Africa, Florida, 1709, South Africa","Ileberi E., Department of Electrical and Electronic Engineering Science, University of Johannesburg, Johannesburg, 2094, South Africa; Sun Y., Department of Electrical and Electronic Engineering Science, University of Johannesburg, Johannesburg, 2094, South Africa; Wang Z., Department of Electrical Engineering, University of South Africa, Florida, 1709, South Africa","The advance in technologies such as e-commerce and financial technology (FinTech) applications have sparked an increase in the number of online card transactions that occur on a daily basis. As a result, there has been a spike in credit card fraud that affects card issuing companies, merchants, and banks. It is therefore essential to develop mechanisms that ensure the security and integrity of credit card transactions. In this research, we implement a machine learning (ML) based framework for credit card fraud detection using a real world imbalanced datasets that were generated from European credit cardholders. To solve the issue of class imbalance, we re-sampled the dataset using the Synthetic Minority over-sampling TEchnique (SMOTE). This framework was evaluated using the following ML methods: Support Vector Machine (SVM), Logistic Regression (LR), Random Forest (RF), Extreme Gradient Boosting (XGBoost), Decision Tree (DT), and Extra Tree (ET). These ML algorithms were coupled with the Adaptive Boosting (AdaBoost) technique to increase their quality of classification. The models were evaluated using the accuracy, the recall, the precision, the Matthews Correlation Coefficient (MCC), and the Area Under the Curve (AUC). Moreover, the proposed framework was implemented on a highly skewed synthetic credit card fraud dataset to further validate the results that were obtained in this research. The experimental outcomes demonstrated that using the AdaBoost has a positive impact on the performance of the proposed methods. Further, the results obtained by the boosted models were superior to existing methods.  © 2013 IEEE.","Credit card fraud; machine learning; predictive modeling","Adaptive boosting; Crime; Decision trees; Engineering education; Boosting; Credit card fraud detections; Credit card frauds; Credit cards; Europe; Machine learning methods; Machine-learning; Predictive models; Radiofrequencies; Support vectors machine; Support vector machines",{"$nulls":4},"National Research Foundation, NRF, (114911, 132797, 137951)","This work was supported in part by the South African National Research Foundation under Grant 114911, Grant 137951, and Grant 132797, and in part by the Eskom Tertiary Education Support Programme Grants.","Thennakoon A., Bhagyani C., Premadasa S., Mihiranga S., Kuruwitaarachchi N., Real-time credit card fraud detection using machine learning, Proc. 9th Int. Conf. Cloud Comput., Data Sci. Eng. (Confluence), pp. 488-493, (2019); Maniraj S.P., Saini A., Ahmed S., Sarkar S., Credit card fraud detection using machine learning and data science, Int. J. Res. Appl. Sci. Eng. Technol., 8, 9, pp. 3788-3792, (2021); The Nilson Report, (2021); The Nilson Report, (2021); Elreedy D., Atiya A.F., A comprehensive analysis of synthetic minority oversampling technique (SMOTE) for handling class imbalance, Inf. Sci., 505, pp. 32-64, (2019); Chawla N.V., Bowyer K.W., Hall L.O., Kegelmeyer W.P., SMOTE: Synthetic minority over-sampling technique, J. Artif. Intell. Res., 16, 1, pp. 321-357, (2002); Imalanced Learn, (2021); Pandas, (2021); Khatri S., Arora A., Agrawal A.P., Supervised machine learning algorithms for credit card fraud detection: A comparison, Proc. 10th Int. Conf. Cloud Comput., Data Sci. Eng. (Confluence), pp. 680-683, (2020); Rajora S., Li D.L., Jha C., Bharill N., Patel O.P., Joshi S., Puthal D., Prasad M., A comparative study of machine learning techniques for credit card fraud detection based on time variance, Proc. Ieee Symp. Comput. Intell. (SSCI), pp. 1958-1963, (2018); Trivedi N.K., Simaiya S., Lilhore U.K., Sharma S.K., An efficient credit card fraud detection model based on machine learning methods, Int. J. Adv. Sci. Technol., 29, 5, pp. 3414-3424, (2020); Sailusha R., Gnaneswar V., Ramesh R., Rao G.R., Credit card fraud detection using machine learning, Proc. 4th Int. Conf. Intell. Comput. Control Syst. (ICICCS), pp. 967-972, (2020); El Hlouli F.Z., Riffi J., Mahraz M.A., El Yahyaouy A., Tairi H., Credit card fraud detection based on multilayer perceptron and extreme learning machine architectures, Proc. Int. Conf. Intell. Syst. Comput. Vis. (ISCV), pp. 1-5, (2020); Randhawa K., Loo C.K., Seera M., Lim C.P., Nandi A.K., Credit card fraud detection using AdaBoost and majority voting, Ieee Access, 6, pp. 14277-14284, (2018); Schapire R.E., Explaining adaboost, Empirical Inference, pp. 37-52, (2013); Li X., Wang L., Sung E., AdaBoost with SVM-based component classifiers, Eng. Appl. Artif. Intell., 21, 5, pp. 785-795, (2008); Kirasich K., Smith T., Sadler B., Random forest vs logistic regression: Binary classification for heterogeneous datasets, Smu Data Sci. Rev., 1, 3, (2018); Feng J., Xu H., Mannor S., Yan S., Robust logistic regression and classification, Proc. Adv. Neural Inf. Process. Syst., 27, pp. 253-261, (2014); Chern C.-C., Chen Y.-J., Hsiao B., Decision treefibased classifier in providing telehealth service, Bmc Med. Informat. Decis. Making, 19, 1, pp. 1-15, (2019); Hengl T., Nussbaum M., Wright M.N., Heuvelink G.B.M., Graler B., Random forest as a generic framework for predictive modeling of spatial and spatio-temporal variables, PeerJ, 6, (2018); Pisner D.A., Schnyer D.M., Support vector machine, Machine Learning, pp. 101-121, (2020); Tharwat A., Parameter investigation of support vector machine classifier with kernel functions, Knowl. Inf. Syst., 61, 3, pp. 1269-1302, (2019); Ensemble Trees, (2021); Wong T.T., Yeh P.Y., Reliable accuracy estimates from k-fold cross validation, Ieee Trans. Knowl. Data Eng., 32, 8, pp. 1586-1594, (2019); Credit Card Fraud Detection, (2021); Google Colab, (2021); Scikit-learn: Machine Learning in Python, (2021); Chicco D., Jurman G., The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation, Bmc Genomics, 21, 1, pp. 1-13, (2020); Boughorbel S., Jarray F., El-Anbari M., Optimal classifier for imbalanced data using Matthews correlation coefficient metric, PLoS One, 12, 6, (2017); Norton M., Uryasev S., Maximization of AUC and buffered AUC in binary classification, Math. Program., 174, 1, pp. 575-612, (2019); Luque A., Carrasco A., Martin A., Heras Las A.De, The impact of class imbalance in classification performance metrics based on the binary confusion matrix, Pattern Recognit., 91, pp. 216-231, (2019); Altman E.R., Synthesizing Credit Card Transactions, (2019)","Z. Wang; Department of Electrical Engineering, University of South Africa, Florida, 1709, South Africa; email: wangzengh@gmail.com",null,"Institute of Electrical and Electronics Engineers Inc.",{"$nulls":5},2.1693536E7,null,null,null,"English","IEEE Access","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85121800267"]
["Hao H.; Guo J.; Xin Z.; Qiao J.","Hao, Huicheng (57298580800); Guo, Jialin (57298780500); Xin, Zhichao (57298780600); Qiao, Jinyou (36449643500)","57298580800; 57298780500; 57298780600; 36449643500","Research on e-Commerce Distribution Optimization of Rice Agricultural Products Based on Consumer Satisfaction",2021.0,"IEEE Access",9.0,null,null,135304.0,135315.0,11.0,6.0,"10.1109/ACCESS.2021.3114409","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85117192051&doi=10.1109%2fACCESS.2021.3114409&partnerID=40&md5=338556bbc94b1961bfa840bde0d724a6","College of Engineering, Management Science and Engineering, Northeast Agricultural University, Harbin, 150030, China","Hao H., College of Engineering, Management Science and Engineering, Northeast Agricultural University, Harbin, 150030, China; Guo J., College of Engineering, Management Science and Engineering, Northeast Agricultural University, Harbin, 150030, China; Xin Z., College of Engineering, Management Science and Engineering, Northeast Agricultural University, Harbin, 150030, China; Qiao J., College of Engineering, Management Science and Engineering, Northeast Agricultural University, Harbin, 150030, China","With the continuous development of agricultural product e-commerce platforms and the rapid growth of trading volume, conducting in-depth mining and analysis of online review data to improve consumer satisfaction is of considerable importance. This paper uses JingDong's self-run online reviews of rice agricultural products as the research object and analyzes the logistics factors that affect consumer satisfaction through text mining technology. A multi-objective model for logistics center distribution path optimization under a soft time window was constructed. The model used the results of online review analysis, namely, packaging integrity, delivery timeliness, and logistics cost, as the goals, and the model used ant colony algorithm (ACO) and genetic algorithm (GA) to solve the optimal distribution solution to minimize the penalty cost and transportation cost. Through examples to solve the optimal distribution vehicle number and shipping routes, in addition, a comparison of the two types of algorithm performance of the model under different node number indicated that the number of nodes affects algorithm performance. With a node number below 50, the ant ACO has high precision and a better distribution path. With a node number above 50, GA has more comprehensive performance. The average efficiency of the GA is 12.28% higher than that of ACO.  © 2013 IEEE.","ant colony algorithm; Consumer satisfaction; genetic algorithm; logistics distribution; soft time window","Ant colony optimization; Artificial intelligence; Cost benefit analysis; Data mining; Electronic commerce; Genetic algorithms; Algorithm performance; Ant colonies algorithm; Consumer satisfactions; Distribution optimization; E- commerces; Logistic distributions; Nodes number; Online reviews; Optimal distributions; Soft time windows; Agricultural products",{"$nulls":6},"Beyari H., Abareshi A., Consumer satisfaction in social commerce: An exploration of its antecedents and consequences, J. Develop. Areas, 52, 2, pp. 55-72, (2018); Cao S.H., A novel optimal selection algorithm for agricultural trade export in blockchain-enabled Internet of Things, Wireless Commun. Mobile Comput, 2021, (2021); Jarupan L., Hunsa-Udom R., Bumbudsanpharoke N., Potential use of oil palm fronds for papermaking and application as molded pulp trays for fresh product under simulated cold chain logistics, J. Natural Fibers, 4, pp. 1-13, (2021); Van Duin J.H.R., Goffau W.D., Wiegmans B., Tavasszy L.A., Saes M., Improving home delivery efficiency by using principles of address intel- ligence for B2C deliveries, ', Proc. 9th Int. Conf. City Logistics, 12, pp. 14-25, (2016); Su Y., Fan Q.-M., The green vehicle routing problem from a smart logistics perspective, Ieee Access, 8, pp. 839-846, (2020); Paul J., Sankaranarayanan K.G., Mekoth N., Consumer satisfaction in retail stores: Theory and implications, Int. J. Consum. Stud., 40, 6, pp. 635-642, (2016); Li M., Ma Y., Cao P., Revealing customer satisfaction with hotels through multi-site online reviews:Amethod based on the evidence theory, Ieee Access, 8, pp. 225226-225239, (2020); Alnawas I., Aburub F., The effect of bene-ts generated from inter- acting with branded mobile apps on consumer satisfaction and purchase intentions, J. Retailing Consum. Services, 31, pp. 313-322, (2016); Medina-Merodio J.-A., De-Pablos-Heredero C., Jimenez-Rodriguez L., Fernandez-Sanz L., Robina-Ramirez R., Andres-Jimenez J., Aframe- work to support the process of measurement of customer's satisfaction according to ISO 9001, Ieee Access, 8, pp. 102554-102569, (2020); Handayani S.M., Sugiharti M.H., Jamhari, Lestari R.W., Jangkung H.M., Consumer satisfaction on wetland rice agro-tourism in Daerah Istimewa Yogyakarta (DIY), ', Iop Conf. Ser., Earth Environ. Sci., 518, 1, (2020); Brandtner P., Darbanian F., Falatouri T., Udokwu C., Impact of COVID-19 on the customer end of retail supply chains: A big data anal- ysis of consumer satisfaction, Sustainability, 13, 3, (2021); Yuksel M.E., Fidan H., A decision support system using text min- ing based grey relational method for the evaluation of written exams, Symmetry, 11, 11, (2019); Shaq M., Tian Z., Bashir A.K., Jolfaei A., Yu X., `Data mining and machine learning methods for sustainable smart cities traf-c classi-cation: A survey, Sustain. Cities Soc, 60, (2020); Wang P., Yan Y., Si Y., Zhu G., Zhan X., Wang J., Pan R., Clas- sification of proactive personality: Text mining based on Weibo text and short-answer questions text, Ieee Access, 8, pp. 97370-97382, (2020); Bicquelet A., Using online mining techniques to inform formative eval- uations: An analysis of Youtube video comments about chronic pain, Evaluation, 23, 3, pp. 323-338, (2017); Zhao Y., Xu X., Wang M., Predicting overall customer satisfaction: Big data evidence from hotel online textual reviews, ', Int. J. 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Sci, 53, 1, pp. 256-281, (2019); Li M., Lu J., Ma W., A hybrid multi-objective genetic algorithm for bi-objective time window assignment vehicle routing problem, ', Traffic Transp., 31, 5, pp. 513-525, (2019); Dai X., Long S., Zhang Z., Gong D., Mobile robot path planning based on ant colony algorithm with A∗ heuristic method, Frontiers Neu- Rorobot, 13, (2019); Chen Y., Zhou X., Path planning of robot based on improved ant colony algorithm in computer technology, J. Phys., Conf. ser, 1744, 4, (2021); Sahu C., Parhi D.R., B.kumar P., An approach to optimize the path of humanoids using adaptive ant colony optimization, J. Bionic Eng., 15, 4, pp. 623-635, (2018); Cruz-Chavez M.A., Rosales M.H.C., Zavala-Diaz J.C., Aguilar J.A.H., Rodriguez-Leon A., Avelino J.C.P., Ortiz M.E.L., Salinas O.H., Hybrid micro genetic multi-population algorithm with collective com- munication for the job shop scheduling problem, Ieee Access, 7, pp. 82358-82376, (2019); Sivaramkumar V., Thansekhar M., Saravanan R., Amali S.M., Multi- objective vehicle routing problem with time windows: Improving customer satisfaction by considering gap time, Proc. Inst. Mech. Eng., B, J. Eng. Manuf., 231, 7, pp. 1248-1263, (2017); Xiaoqiang S., Zhichao L., Xuan Z., Xinchao N., `Research on robot path planning based on improved adaptive ant colony algorithm, , Proc. Chin. Control Decis. Conf. (CCDC), pp. 506-510, (2019); Mohammed M.A., Ghani M.K.A., Hamed R.I., Mostafa S.A., Ahmad M.S., Ibrahim D.A., `Solving vehicle routing problem by using improved genetic algorithm for optimal solution, J. Comput. Sci., 21, pp. 255-262, (2017); Bertrand B.A.P., Moustapha D., Etienne S., Souleymane O., Boko A., Agenetic algorithm for overall designing and planning of a long term evo- lution advanced network, ', Amer. J. Oper. Res., 6, 4, pp. 355-370, (2016)","J. Qiao; College of Engineering, Management Science and Engineering, Northeast Agricultural University, Harbin, 150030, China; email: qiaojiniyou@163.com",null,"Institute of Electrical and Electronics Engineers Inc.",{"$nulls":5},2.1693536E7,null,null,null,"English","IEEE Access","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85117192051"]
["Zagurskiy O.M.","Zagurskiy, O.M. (56607287000)",5.6607287E10,"MODERN TRENDS IN DEVELOPMENT OF LOGISTICS MARKET",2021.0,"Machinery and Energetics",12.0,1.0,null,17.0,24.0,7.0,0.0,"10.31548/machenergy2021.01.017","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85179934740&doi=10.31548%2fmachenergy2021.01.017&partnerID=40&md5=9561ff70ac311c9e6a00416270e1ec76","National University of Life and Environmental Sciences of Ukraine, Ukraine","Zagurskiy O.M., National University of Life and Environmental Sciences of Ukraine, Ukraine","In logistics, analytical, technological and marketing paradigms are being replaced by an integrated (logistics) paradigm, which goes beyond the problems of optimizing the business processes of an individual enterprise and involves the integration of individual enterprises into supply chains to improve management processes and increase the overall efficiency of their business. The article provides a theoretical and methodological justification for the influence of institutional and technological factors on the transformation of the logistics market in modern conditions. It defines that the mutual influence of institutional and technological factors forms in logistics the specifics of multi-channel supply networks, which have a fundamentally different more complex market mechanics, and also form a new institutional framework of trade and logistics infrastructure of multi-channel supply of modern consumer market. It has been proven that the development of e-commerce creates new institutional conditions and encourages changes in corporate governance strategies and consumer behavior, and the dominant type of institutional agreements imposes certain restrictions on determining the needs, preferences and choices of agents, thus stimulating the development of even more modern technologies. © 2021, National University of Life and Environmental Sciences of Ukraine. All rights reserved.","e-commerce; institutional environment; logistics market; multi-channel networks; supply chain",{"$nulls":7},"Internet of Things (Fleet Management, Real-Time Supply Chain Visibility) – 17%. 2. Artificial Intelligence (Demand Forecasting, Process Optimization) – 14. 3. Robotics (Collaborative Robots Cobots work collaboratively with human workers, Robotic Process Automation) – 11%. 4. Last-Mile Delivery (Drones, Smart Lockers) –; Bauersoks D., Kloss D., Logistics: an integrated supply chain, (2001); Bubnova G. B., Levin B. A., Digital logistics – innovative mechanism for development and efficient functioning of transport and logistics systems and complexes, International Journal of Open Information Technologies, 5, 3, pp. 72-78, (2017); Zagurskiy O. M., Competitiveness of transport and logistics systems in the minds of globalization: institutional analysis, (2019); Govindan К., Soleimani Н., A review of reverse logistics and closed-loop supply chains, Journal of Cleaner Production, 142, 1, pp. 371-384, (2017); Gy К., Sebastian К., New logistics and production trends as the effect of global economy changes, Polish Journal of Management Studies, 14, pp. 115-126, (2016); Hamalainen T. J., National competitiveness and economic growth, The Changing Determinants of Economic Performance in the World Economy, (2003); Irtyshcheva I., Ishchenko O., Barabanova J., Organizational and economic mechanisms of transport system development based on logistics, Journal of Vasyl Stefanyk Precarpathian National University, 6, pp. 37-45, (2019); Kabashkin I., Bazaras D., Ciziuniene K., Palsaitis R., Competence and capacity-building requirements in transport and logistics market, Transport and Telecommunication, 17, pp. 1-8, (2016); Karatas-Cetin C., Denktas-Sakar G., Logistics research beyond 2000: theory, method and relevance, The Asian Journal of Shipping and Logistics, 29, 2, pp. 125-144, (2013); Kozlenkova І., Hult G., Lund D., Mena J., Kekec P., The role of marketing channels in supply chain management, Journal of Retailing, 91, 4, pp. 586-609, (2015); Macurova P., Juraskova K., The trends in development of full logistics services, Journal of Applied Economic Sciences, 9, pp. 65-75, (2014); Marasco А., Third-party logistics: a literature review, International Journal of Production Economics, 113, 1, pp. 127-147, (2008); Monios J., Lambert B., The heartland intermodal corridor: public private partnerships and the transformation of institutional settings, Journal of Transport Geography, 27, pp. 36-45, (2013); Neirotti P., De Marco A., Cagliano А., Mangano G., Scorrano F., Current trends in Smart City initiatives: some stylised facts, Cities, 38, pp. 25-36, (2014); Raimbault N., From regional planning to port regionalization and urban logistics. The inland port and the governance of logistics development in the Paris region, Journal of Transport Geography, 78, pp. 205-213, (2019); Rauch Е., Dallasega Р., Matt D., Sustainable production in emerging markets through Distributed Manufacturing Systems (DMS), Journal of Cleaner Production, 135, pp. 127-138, (2016); Schliwa G., Armitage R., Aziz S., Evans J., Rhoades J., Sustainable city logistics – making cargo cycles viable for urban freight transport, Research in Transportation Business & Management, 15, pp. 50-57, (2015); Sumets O. M., Factors of logistics development at the present stage of market transformations, Bulletin of the National University \"Lviv Polytechnic\", 779, pp. 106-112, (2014); Tijan E., Aksentijevic S., Ivanic K., Jardas M., Blockchain technology implementation in logistics, Sustainability, 11, pp. 1-13, (2019); Ye F., Zhao Х., Prahinski С., Li Y., The impact of institutional pressures, top managers' posture and reverse logistics on performance – evidence from China, International Journal of Production Economics, 143, 1, pp. 132-143, (2013); Zagurskiy О., Ohiienko M., Pokusa Т., Zagurska S., Pokusa F., Titova L., Rogovskii І., Study of efficiency of transport processes of supply chains management under uncertainty, (2020); Zagurskiy О., Titova L., Problems and prospects of blockchain technology usage in supply chains, Journal of Automation and Information Sciences, 11, pp. 63-74, (2019); Zagurskiy O. M., Zhurakovska T. S., Optimization of transport processes in supply chains of epicenter hypermarket network. Machinery & Energetics, Journal of Rural Production Research. Kyiv. Ukraine, 11, 3, pp. 55-60, (2020); Zagurskiy О., Rogach S., Titova L., Rogovskii І., Pokusa Т., Green» supply chain as a path to sustainable development. Mechanisms of stimulation of socio-economic development of regions in conditions of transformation, pp. 199-213, (2019)","O.M. Zagurskiy; National University of Life and Environmental Sciences of Ukraine, Ukraine; email: zagurskiy_oleg@ukr.net",null,"National University of Life and Environmental Sciences of Ukraine",{"$nulls":5},2.6631334E7,null,null,null,"English","Mach. Energ.","Article","Final",null,"Scopus","2-s2.0-85179934740"]
["Gaudenzi B.; Mola L.; Rossignoli C.","Gaudenzi, Barbara (26029807500); Mola, Lapo (36008960100); Rossignoli, Cecilia (25645376500)","26029807500; 36008960100; 25645376500","Hitting or missing the target: Resources and capabilities for alternative e-commerce pathways in the fashion industry",2021.0,"Industrial Marketing Management",93.0,null,null,124.0,136.0,12.0,19.0,"10.1016/j.indmarman.2020.12.016","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85100135332&doi=10.1016%2fj.indmarman.2020.12.016&partnerID=40&md5=e73e850f67c290962584972d11ca51af","Department of Business Administration, University of Verona, Italy; SKEMA Business School, Université Côte d'Azur (GREDEG), France","Gaudenzi B., Department of Business Administration, University of Verona, Italy; Mola L., Department of Business Administration, University of Verona, Italy, SKEMA Business School, Université Côte d'Azur (GREDEG), France; Rossignoli C., Department of Business Administration, University of Verona, Italy","This exploratory and longitudinal research investigates how firms may succeed in implementing an e-commerce strategy and move from perceived needs to e-supply chain configurations. The study investigated four Italian companies in the fashion industry, through in-depth interviews with 35 interviewees collected over 2011–2019. The companies were examined from the perspective of Resource-Based View and Dynamic Capabilities to address the links between antecedents, e-supply chain configuration resources, capabilities, and alternative paths of evolution. A theoretical framework and three relevant propositions are also provided. Results indicate two key resources – namely, network structure and flows and service architecture – and four key capabilities – namely, relationship governance capabilities, exploitation of information asymmetry, core logistics capabilities and e-CRM and digital capabilities – which determine the alternative pathways of evolution. The pathways have been finally identified and described. © 2021 Elsevier Inc.","Dynamic capabilities; E-commerce; E-supply chain; Fashion industry; Resource-based view",{"$nulls":7},"Adaileh M.J., Elrehail H., E-business supply chain collaboration measurement scale: A confirmatory approach, International Journal of Supply Chain Management, 7, 5, pp. 22-34, (2018); Alvesson M., Karreman D., Constructing mystery: Empirical matters in theory development, Academy of Management Review, 32, pp. 1265-1281, (2007); Amit R., Zott C., Value creation in e-business, Strategic Management Journal, 22, pp. 493-520, (2001); Barney J., Firm resources and sustained competitive advantage, Journal of Management, 17, pp. 99-120, (1991); Benbasat I., Goldstein D.K., Mead M., The case research strategy in studies of information systems, MIS Quarterly, 11, pp. 369-386, (1987); Bernard R.H., Social research methods: Qualitative and quantitative approaches, (2012); Brax S.A., Visintin F., Meta-model of servitization: The integrative profiling approach, Industrial Marketing Management, 60, pp. 17-32, (2017); 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Gaudenzi; Department of Business Administration, University of Verona, Italy; email: barbara.gaudenzi@univr.it",null,"Elsevier Inc.",{"$nulls":5},198501.0,null,"IMMAD",null,"English","Ind. Mark. Manage.","Article","Final",null,"Scopus","2-s2.0-85100135332"]
["Liu B.","Liu, Binbin (55558078200)",5.55580782E10,"Logistics Distribution Route Optimization Model Based on Recursive Fuzzy Neural Network Algorithm",2021.0,"Computational Intelligence and Neuroscience",2021.0,null,3338840.0,null,null,null,7.0,"10.1155/2021/3338840","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121991084&doi=10.1155%2f2021%2f3338840&partnerID=40&md5=c4541ae8348abf120750a95213ac6b91","Department of Business Administration, Suqian University, Suqian, 223800, China; Department of Business Administration, Jeonbuk National University, Jeonju, 54896, South Korea","Liu B., Department of Business Administration, Suqian University, Suqian, 223800, China, Department of Business Administration, Jeonbuk National University, Jeonju, 54896, South Korea","In recent years, more and more attention has been paid to the utilization of data and information in the logistics distribution path optimization system of e-commerce, but it is difficult to have scientific guarantee in the process of determining the optimal distribution path scheme of e-commerce. How to realize the optimization and adaptive setting of distribution path by using intelligent algorithm has become a hot spot. To battle these issues, this paper studies the logistics distribution path optimization model based on recursive fuzzy neural network algorithm. This paper analyses the research status of logistics distribution path determination scheme and applies the recursive fuzzy neural network algorithm in the selection of e-commerce logistics distribution path scheme. The experimental results show that the recursive fuzzy neural network algorithm can realize the optimization of e-commerce logistics distribution path, and the best distribution route can be made according to the characteristic difference of logistics distribution route, and its distribution accuracy can reach more than 97%. Copyright © 2021 Binbin Liu. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.",null,"Algorithms; Commerce; Neural Networks, Computer; Electronic commerce; Fuzzy inference; Optimization; Distribution route; E- commerces; Fuzzy-neural-networks; Logistic distributions; Model-based OPC; Neural networks algorithms; Optimization models; Path optimizations; Route optimization; algorithm; commercial phenomena; Fuzzy neural networks",{"$nulls":4},"Social Science Applied Research Excellent Project of Jiangsu Province, (19SYB-140); Jiangsu Provincial Department of Education, JPDE, (2020SJA2172)","is study was supported by the University Philosophy and Social Science Research Project of Department of Education of Jiangsu Province (Research on emergency logistics mode based on blockchain application in public health emergencies) (2020SJA2172), Social Science Applied Research Excellent Project of Jiangsu Province (Function layout and operation analysis of smart logistics park in big data environment) (19SYB-140), and Applied Research Project of","Chen Y., Intelligent algorithms for cold chain logistics distribution optimization based on big data cloud computing analysis, Journal of Cloud Computing, 9, 1, pp. 1-12, (2020); 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Choudhury S., Dutta A., Ray D., Chaos and complexity from quantum neural network. A study with diffusion metric in machine learning, Journal of High Energy Physics, 2021, 4, pp. 1-33; Roy P., Mahapatra G.S., Dey K.N., Neuro-genetic approach on logistic model based software reliability prediction, Expert Systems with Applications, 42, 10, pp. 4709-4718, (2015); Rout M., Koudjonou K.M., Satapathy S.C., Analysis of net asset value prediction using low complexity neural network with various expansion techniques, Evolutionary Intelligence, 14, 2, pp. 643-655, (2021); Deng W., Shang S., Cai X., Zhao H., Song Y., Xu J., An improved differential evolution algorithm and its application in optimization problem, Soft Computing, 25, 7, pp. 5277-5298, (2021); Zheng K., Zhang Q., Hu Y., Wu B., Design of fuzzy system-fuzzy neural network-backstepping control for complex robot system, Information Sciences, 546, pp. 1230-1255; Jafari R., Razvarz S., Gegov A., A novel technique for solving fully fuzzy nonlinear systems based on neural networks, Vietnam Journal of Computer Science, pp. 93-107, (2020); Varol Altay E., Alatas B., Intelligent optimization algorithms for the problem of mining numerical association rules, Physica A: Statistical Mechanics and Its Applications, 540; Kang X., Zhang Y., Zhang H., Li S., Gao W., Research on neural network model for new energy industry economy based on particle swarm optimization, Journal of Intelligent and Fuzzy Systems, 38, 6, pp. 7267-7277, (2020); Bianchini M., Scarselli F., On the complexity of neural network classifiers: A comparison between shallow and deep architectures, IEEE Transactions on Neural Networks and Learning Systems, 25, 8, pp. 1553-1565, (2014); Hippert H.S., Taylor J.W., An evaluation of Bayesian techniques for controlling model complexity and selecting inputs in a neural network for short-term load forecasting, Neural Networks, 23, 3, pp. 386-395, (2010); Paul A., Saravanan V., Thangaiah P.R., Data mining analytics to minimize logistics cost, International Journal of Advances in Science and Technology, 2, 3, pp. 89-107, (2011); Zu E., Shu M.H., Huang J.C., Management problems of modern logistics information system based on data mining, Mobile Information Systems, 2021, (2021); Lin J.C.-W., Djenouri Y., Srivastava G., Efficient closed high-utility pattern fusion model in large-scale databases, Information Fusion, 76, pp. 122-132; Kumar T.S., Data mining based marketing decision support system using hybrid machine learning algorithm, Journal of Artificial Intelligence, 2, 3, pp. 185-193, (2020)","B. Liu; Department of Business Administration, Suqian University, Suqian, 223800, China; email: 22062@squ.edu.cn",null,"Hindawi Limited",{"$nulls":5},1.6875265E7,null,null,3.4777491E7,"English","Comput. Intell. Neurosci.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85121991084"]
["Ehrler V.C.; Schöder D.; Seidel S.","Ehrler, Verena Ch (55479848500); Schöder, Dustin (57211938412); Seidel, Saskia (57072699100)","55479848500; 57211938412; 57072699100","Challenges and perspectives for the use of electric vehicles for last mile logistics of grocery e-commerce – Findings from case studies in Germany",2021.0,"Research in Transportation Economics",87.0,null,100757.0,null,null,null,30.0,"10.1016/j.retrec.2019.100757","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85075430586&doi=10.1016%2fj.retrec.2019.100757&partnerID=40&md5=b4d65d3e8b3f3f9601a56d607da0d7c4","DLR German Aerospace Centre, Institute of Transport Research, Rutherfordstr. 2, Berlin, 12489, Germany; Hellmann Worldwide Logistics Road & Rail GmbH & Co.KG, Elbestrasse 1, Osnabrueck, 49090, Germany","Ehrler V.C., DLR German Aerospace Centre, Institute of Transport Research, Rutherfordstr. 2, Berlin, 12489, Germany; Schöder D., Hellmann Worldwide Logistics Road & Rail GmbH & Co.KG, Elbestrasse 1, Osnabrueck, 49090, Germany; Seidel S., DLR German Aerospace Centre, Institute of Transport Research, Rutherfordstr. 2, Berlin, 12489, Germany","Purpose: More and more cities struggle to provide acceptable air quality and noise levels for their inhabitants. At the same time, urbanization is continuing, as is the need for supply with groceries in cities. Another ongoing trend is the growth of online shopping of groceries. Increase of online shopping in other areas, e.g. clothing, has resulted in augmented transport demand due to deliveries and returns. Therefore, an approach is needed to uncouple grocery supply related transport demand from emissions augmentation. This is only possible though, if transportation efficiency is further improved and if lower emission technologies (noise and fumes) are applied, e.g. electric vehicles. With limited data available on urban commercial transport as well as on e-mobility, it is difficult for both logistics providers and politics to prepare for these developments and understand their implications. Focusing on the German market and using the test case of a renowned logistics service provider who trialed e-vehicles for commercial transport, this paper discusses potential shifts in grocery shopping habits, maps out perspectives, prerequisites and challenges for a shift to electric vehicles for their distribution and derives recommendations for industry and politics based on the findings. Research approach: The data basis of the research is as follows: Whereas the analysis of online grocery shopping had to be based mainly on secondary data, analysis of the potential and prerequisites for the use of electric vehicles for their distribution are based on real-life test cases. This is due to the fact that primary data on commercial transport and on logistics structures of groceries in particular is difficult to obtain in general, and especially in Germany. This is due to the tight data protection in Germany, not allowing to trace employees unless union representatives and employees have agreed. Furthermore, businesses do not want to disclose their logistics structures. The real-life test cases of electric vehicles for grocery deliveries were piloted by Hellmann Worldwide Logistics in Germany and were accompanied by the researchers. The synthesis of the insights gained build the basis for a discussion, whether e-mobility is the right approach to cope with the impact of the trends of urbanization and online grocery shopping and which further developments are needed for reducing grocery-logistics related emissions. Findings: The analysis reflects the following aspects and findings: status-quo and trends of online groceries sales in Germany motivation for and experiences made within a real-life test case of use of electric vehicles by a renown logistics service provider in Germany implications from the findings of the test cases and their relation to online grocery sales identification of perspectives, prerequisites and challenges for the successful introduction of electric vehicles for the distribution of online sales, in particular online grocery sales Research impact: Limitations experienced during the research and challenges encountered build the basis for the identification of further research fields needed in order to be able to develop and conceive sustainable urban logistics concepts. Practical impact: Findings are included in the logistics service provider's involved endeavors to further reduce their emissions. In particular, in the context of an upcoming trial phase for innovative urban distribution structures in Bremen, Germany. © 2019 Elsevier Ltd","E-commerce; E-grocery; Electric vehicles; Emission reduction; Online distribution; Online grocery sales; Urban logistics",{"$nulls":7},"Caussil J.-N., Les 10 mesures principales du plan Carrefour 2022; LSA Commerce et Conomation, (2018); Durand B., Gonzales-Feliu J., Urban Logistics and e-Grocery: Have Proximity Delivery Services a Positive Impact on Shopping Trips?, Procedia – social and behavioral sciences, 39, pp. 510-520, (2012); Ehrler V., Hebes P., Electromobility for city logistics–the solution to urban transport collapse? An analysis beyond theory, Procedia - Social and Behavioral Sciences, 48, pp. 786-795, (2012); Ehrler V., Lobig A., Einsatzmöglichkeiten und Grenzen von e-Mobilität im urbanen Wirtschaftsverkehr, (2016); EU, European commission air quality standards, (2018); Eurostat, Population density by metropolitan regions, (2018); Forrester, Online sales in Europe are growing 10 times faster than the retail market; update of the forrester western European online retail forecast for 2017 to 2022, (2018); Hacker F., Et al., Elektromobilität – faktencheck, (2017); HDE, Lebensmittel online – Hoffnung oder Hype; report on grocery sales online by the German Retail Federation on, (2018); Hebes P., Et al., Service Traffic. 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A comparison of food retail and distribution structures in France and Germany, Case Study Transport Policy, 2015, (2015); Seidel S., Et al., Innovations in e-grocery and logistics solutions for cities, Published in: Transportation research Procedia, 2016, (2016); Seidel S., Blanquart C., E-commerce in France and Germany a comparative analysis, Recherche Transports Sécurité, (2019); Statista, Share of global online grocery sales based on value in leading European Union (EU) countries, (2017); Stuttgart, Masterplan 100% Klimaschutz, (2018); UN, 68% of the world population projected to live in urban areas by 2050, says UN, (2018); UN, World health organization global ambient air pollution, (2018); Statista, Retail e-commerce sales as share of retail trade in selected countries from 2014 to 2018, (2019)","V.C. Ehrler; DLR German Aerospace Centre, Institute of Transport Research, Berlin, Rutherfordstr. 2, 12489, Germany; email: verena.ehrler@dlr.de",null,"Emerald Group Holdings Ltd.",{"$nulls":5},7398859.0,null,null,null,"English","Res. Transp. Econ.","Article","Final",null,"Scopus","2-s2.0-85075430586"]
["Du J.; Yu Z.","Du, Jie (57318025200); Yu, Zhaoyan (55488389800)","57318025200; 55488389800","Building a Cross-Border E-Commerce Ecosystem Model Based on Block Chain + Internet of Things",2021.0,"Security and Communication Networks",2021.0,null,6451721.0,null,null,null,7.0,"10.1155/2021/6451721","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85118314140&doi=10.1155%2f2021%2f6451721&partnerID=40&md5=bfc3a7ee8387fd0e7edd3fd5f0d14b28","School of Business, Liaocheng University, Shandong, Liaocheng, 252000, China","Du J., School of Business, Liaocheng University, Shandong, Liaocheng, 252000, China; Yu Z., School of Business, Liaocheng University, Shandong, Liaocheng, 252000, China","With the development of Internet technology, cross-border e-commerce in the form of \"Internet + foreign trade\"has come into being. However, in recent years, scholars have continuously raised the problem that the cross-border e-commerce ecosystem with cross-border e-commerce platform as the core and the new Internet technology has not been developed sympathetically. Therefore, by establishing a model of cross-border e-commerce ecosystem and new Internet technology (block chain + Internet of Things), this paper analyzes the stable evolution strategy of both for convergence development and proposes countermeasures for the convergence development of new Internet technology and cross-border e-commerce platform ecosystem of RFID technology logistics tracking + block chain authentic product traceability, taking vertical class cross-border e-commerce platform as an example. The simulation experiment results show that the solution proposed in this paper is feasible compared with traditional and has obvious advantages in data theft prevention, multiparty authentication, and saving system overhead to solve the calculation method of e-commerce sharing problem. Reference is provided for solving the e-commerce cyberculture problem. The process takes advantage of block chain decentralization and auditability from the relevant data analysis from the theoretical concept of big data, the current situation of cross-border e-commerce, and how big data can be applied and developed for cross-border e-commerce, in three major dimensions. © 2021 Jie Du and Zhaoyan Yu.",null,"Big data; Ecosystems; Electronic commerce; Engineering education; International trade; Block-chain; Commerce platforms; Cross-border; E- commerces; E-commerce ecosystems; Ecosystem model; Evolution strategies; Internet technology; Model-based OPC; Paper analysis; Internet of things",{"$nulls":6},"Zhang Z., Yuan Z., Ni G., Lin H., Lu Y., The quality traceability system for prefabricated buildings using blockchain: An integrated framework, Frontiers of Engineering Management, 7, 4, pp. 528-546, (2020); Zhang T., Tan C., Research on the impact of block chain technology on China's e-commerce, Proceedings of the 2018 8th International Conference on Applied Science, Engineering and Technology (ICASET 2018), pp. 122-125, (2018); 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Wu L., Yang Z., Wang Q., Jian M., Zhao B., Yan J., Chen C.W., Fusing motion patterns and key visual information for semantic event recognition in basketball videos, Neurocomputing, 413, pp. 217-229, (2020); Liu L., Objects detection toward complicated high remote basketball sports by leveraging deep CNN architecture, Future Generation Computer Systems, 119, pp. 31-36, (2021); Trinidad-Fernandez M., Beckwee D., Cuesta-Vargas A., Gonzalez-Sanchez M., Moreno F.-A., Gonzalez-Jimenez J., Joos E., Vaes P., Differences in movement limitations in different low back pain severity in functional tests using an RGB-D camera, Journal of Biomechanics, 116, (2021); Chen X., Marine transport efficiency evaluation of cross-border e-commerce logistics based on analytic hierarchy process, Journal of Coastal Research, 94, SI, pp. 682-686, (2019)","J. Du; School of Business, Liaocheng University, Liaocheng, Shandong, 252000, China; email: dujie@lcu.edu.cn",null,"Hindawi Limited",{"$nulls":5},1.9390114E7,null,null,null,"English","Secur. Commun. Networks","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85118314140"]
["Wang X.; Wong Y.D.; Yuen K.F.","Wang, Xueqin (57196484178); Wong, Yiik Diew (57218910096); Yuen, Kum Fai (56581269200)","57196484178; 57218910096; 56581269200","Does covid-19 promote self-service usage among modern shoppers? An exploration of pandemic-driven behavioural changes in self-collection users",2021.0,"International Journal of Environmental Research and Public Health",18.0,16.0,8574.0,null,null,null,16.0,"10.3390/ijerph18168574","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85112372435&doi=10.3390%2fijerph18168574&partnerID=40&md5=6a123b8eff320accb4bbec38d2829391","Department of International Logistics, Chung-Ang University, Seoul, 06974, South Korea; School of Civil and Environmental Engineering, Nanyang Technological University, Singapore, 639798, Singapore","Wang X., Department of International Logistics, Chung-Ang University, Seoul, 06974, South Korea; Wong Y.D., School of Civil and Environmental Engineering, Nanyang Technological University, Singapore, 639798, Singapore; Yuen K.F., School of Civil and Environmental Engineering, Nanyang Technological University, Singapore, 639798, Singapore","Due to health concerns related to COVID-19, shoppers have learned to minimise social contact by adopting various contactless self-service technologies to fulfil their consumption needs. This study explores shoppers’ behavioural changes in relation to self-service, using the special research context of e-commerce self-collection services. By synthesising insights from the health psychology literature, this study proposes an affective-cognitive-social perspective to explain the pandemic-driven behavioural changes of self-collection users. The survey instrument is used for online data collection (n = 500), and a combined (descriptive and quantitative) method is adopted for data analysis. Our results suggest that, although with a relatively weak predictive power, the affective and cognitive appraisals of health risks lead to the reinforced usage of self-collection service. This also applies to the factors of action/coping planning and subjective norm. This study theoretically contributes to the self-service literature and creates managerial implications for retailers and logistics operators. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.","COVID-19; E-commerce delivery; Last-mile logistics; Pandemic-driven behavioural change; Self-collection locker; Self-service","Adaptation, Psychological; COVID-19; Humans; Pandemics; SARS-CoV-2; Surveys and Questionnaires; cognition; consumption behavior; coping strategy; COVID-19; electronic commerce; health risk; affect; Article; behavior change; coping behavior; coronavirus disease 2019; electronic commerce; health care planning; health hazard; information processing; mathematical phenomena; pandemic; prediction; quantitative analysis; social aspect; human; questionnaire",{"$nulls":4},"Nanyang Technological University, NTU","Funding: This research was funded by Nanyang Technological University, CEE internal seed fund (2019).","Sheth J., Impact of Covid-19 on consumer behavior: Will the old habits return or die?, J. Bus. 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Yuen; School of Civil and Environmental Engineering, Nanyang Technological University, Singapore, 639798, Singapore; email: kumfai.yuen@ntu.edu.sg",null,"MDPI",{"$nulls":5},1.6617827E7,null,null,3.4444323E7,"English","Int. J. Environ. Res. Public Health","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85112372435"]
["Shrivastava M.; Kumar S.","Shrivastava, Mayank (35119398300); Kumar, Shishir (55464037600)","35119398300; 55464037600","A pragmatic and intelligent model for sarcasm detection in social media text",2021.0,"Technology in Society",64.0,null,101489.0,null,null,null,27.0,"10.1016/j.techsoc.2020.101489","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85098938836&doi=10.1016%2fj.techsoc.2020.101489&partnerID=40&md5=b7b3471b007c18705aebabdcde39a58d","Department of Computer Science and Engineering, Jaypee University of Engineering and Technology, Guna, India","Shrivastava M., Department of Computer Science and Engineering, Jaypee University of Engineering and Technology, Guna, India; Kumar S., Department of Computer Science and Engineering, Jaypee University of Engineering and Technology, Guna, India","The world has now become an ecumenical village because of the Internet. Online platforms like e-commerce sites, search engines, social media have convoluted with the general routine of daily life. Social sites such as Twitter and Facebook have a user population larger than most of the countries, due to which communication is now largely shifted to text-based communication from verbal communication. This research investigates a common yet crucial problem of sarcasm detection in text-based communication. To prevent this problem a novel model has been proposed based on Google BERT (Bidirectional Encoder Representations from Transformers) that can handle volume, velocity and veracity of data. The performance of the model is compared with other classical and contemporary approaches such as Support Vector Machine, Logistic Regression, Long Short Term Memory and Convolutional Neural Network, BiLSTM and attention-based models which have been reported to be used for such tasks. The proposed model establishes its competence by evaluation on different parameters such as precision, recall, F1 score and accuracy. The model is built with the hope that it may help not only the government but also the general public to build a safer and technologically advanced society. © 2020 Elsevier Ltd","BERT; Computational; Intelligent; Irony; Sarcasm; Text analysis","Convolution; Convolutional neural networks; Logistic regression; Search engines; Support vector machines; Support vector regression; E-commerce sites; General publics; Intelligent modeling; Online platforms; Social media; Social sites; Text-based communication; Verbal communications; detection method; information and communication technology; social media; support vector machine; World Wide Web; Social networking (online)",{"$nulls":6},"Koetsier J., Why 2020 Is A Critical Global Tipping Point for Social Media, Forbes.Com, (2020); Vlastos G., Socratic irony, class, Far E. 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Notes bioinformatics), (2017); Ghosh A., Veale T., Magnets for sarcasm: making sarcasm detection timely, contextual and very personal, in: proc. 2017 conf. Empir. Methods nat. Lang, Process., pp. 482-491, (2017); Abulaish M., Kamal A., Zaki M.J., A survey of figurative Language and its computational detection in online social networks, ACM Trans. Web, 14, pp. 1-52, (2020)","S. Kumar; Department of Computer Science and Engineering, Jaypee University of Engineering and Technology, Guna, India; email: dr.shishir@yahoo.com",null,"Elsevier Ltd",{"$nulls":5},"0160791X",null,null,null,"English","Technol. Soc.","Article","Final",null,"Scopus","2-s2.0-85098938836"]
["Kandula S.; Krishnamoorthy S.; Roy D.","Kandula, Shanthan (57223230523); Krishnamoorthy, Srikumar (24450494400); Roy, Debjit (25522771400)","57223230523; 24450494400; 25522771400","A prescriptive analytics framework for efficient E-commerce order delivery",2021.0,"Decision Support Systems",147.0,null,113584.0,null,null,null,20.0,"10.1016/j.dss.2021.113584","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85105336231&doi=10.1016%2fj.dss.2021.113584&partnerID=40&md5=1c662f699d2986628e610412480b640a","Indian Institute of Management Ahmedabad, 380015, Gujarat, India; Rotterdam School of Management, Erasmus University, Rotterdam, 3062, PA, Netherlands","Kandula S., Indian Institute of Management Ahmedabad, 380015, Gujarat, India; Krishnamoorthy S., Indian Institute of Management Ahmedabad, 380015, Gujarat, India; Roy D., Indian Institute of Management Ahmedabad, 380015, Gujarat, India, Rotterdam School of Management, Erasmus University, Rotterdam, 3062, PA, Netherlands","Achieving timely last-mile order delivery is often the most challenging part of an e-commerce order fulfillment. Effective management of last-mile operations can result in significant cost savings and lead to increased customer satisfaction. Currently, due to the lack of customer availability information, the schedules followed by delivery agents are optimized for the shortest tour distance. Therefore, orders are not delivered in customer-preferred time periods resulting in missed deliveries. Missed deliveries are undesirable since they incur additional costs. In this paper, we propose a decision support framework that is intended to improve delivery success rates while reducing delivery costs. Our framework generates delivery schedules by predicting the appropriate delivery time periods for order delivery. In particular, the proposed framework works in two stages. In the first stage, order delivery success for every order throughout the delivery shift is predicted using machine learning models. The predictions are used as an input for the optimization scheme, which generates delivery schedules in the second stage. The proposed framework is evaluated on two real-world datasets collected from a large e-commerce platform. The results indicate the effectiveness of the decision support framework in enabling savings of up to 10.2% in delivery costs when compared to the current industry practice. © 2021 Elsevier B.V.","Analytics; Data-driven delivery; E-commerce; Machine learning; Vehicle routing","Customer satisfaction; Electronic commerce; Large dataset; Sales; Decision support framework; Delivery schedules; Effective management; Industry practices; Machine learning models; Optimization scheme; Order fulfillment; Real-world datasets; Decision support systems",{"$nulls":4},"Flipkart India Pvt. Ltd.; Ministry of Electronics & IT; Nederlandse Organisatie voor Wetenschappelijk Onderzoek, NWO; Ministry of Electronics and Information technology, Meity","Funding text 1: This work was supported by the Indo-Dutch Grant [grant number 13(4)/2018-CC&BT ] provided by the Ministry of Electronics & IT (MeitY) , India, in collaboration with the Netherlands Organization for Scientific Research (NWO) . ; Funding text 2: This work was supported by the Indo-Dutch Grant [grant number 13(4)/2018-CC&BT] provided by the Ministry of Electronics & IT (MeitY), India, in collaboration with the Netherlands Organization for Scientific Research (NWO). We thank Flipkart India Pvt. Ltd. for providing necessary data for the research work. In particular, we thank Chandrasekhar K, Shailendra Kumar, Sreeparna Chatterjee, Muthusamy Chelliah for providing advice and sharing the data.","Clement J., E-commerce Share of Total Global Retail Sales from 2015 to 2023, (2019); Mikko P., Hannu Y., Jan H., Solving the last mile issue: reception box or delivery box?, Int. J. Phys. Distrib. Logist. Manag., 31, pp. 427-439, (2001); Gevaers R., Van de Voorde E., Vanelslander T., Characteristics and typology of last-mile logistics from an innovation perspective in an urban context, City Distribution and Urban Freight Transport, pp. 56-71, (2011); Rao S., Rabinovich E., Raju D., The role of physical distribution services as determinants of product returns in Internet retailing, J. Oper. Manag., 32, pp. 295-312, (2014); Arnold F., Cardenas I., Sorensen K., Dewulf W., Simulation of B2C e-commerce distribution in Antwerp using cargo bikes and delivery points, Eur. Transp. Res. 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["Xiong C.; Wu L.","Xiong, Chunyan (57240423500); Wu, Liusan (55681679900)","57240423500; 55681679900","Prediction of China's Express Business Volume Based on FGM (1, 1) Model",2021.0,"Journal of Mathematics",2021.0,null,8585238.0,null,null,null,6.0,"10.1155/2021/8585238","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85113986073&doi=10.1155%2f2021%2f8585238&partnerID=40&md5=4fde76c19266ad288baf4fd567a3e630","College of Information Management, Nanjing Agricultural University, Nanjing, 210031, China; School of Information Management, Nanjing University, Nanjing, 210023, China","Xiong C., College of Information Management, Nanjing Agricultural University, Nanjing, 210031, China, School of Information Management, Nanjing University, Nanjing, 210023, China; Wu L., College of Information Management, Nanjing Agricultural University, Nanjing, 210031, China","With the continuous development of the economy, people's lifestyle has changed greatly, online shopping has become a better choice for many people, and the express business volume is also increasing. Forecasting express business volume is of benefit to the healthy development of the logistics industry. Based on the data of China's express business volume from 2015 to 2019, this paper uses the improved Particle Swarm Optimization algorithm to calculate the fractional-order r of the FGM (1, 1) model and forecasts China's express business volume from 2020 to 2023. The results indicate that in the next few years, China's express business volume will show a large growth trend, indicating that the express delivery industry still has a lot of room for development.  © 2021 Chunyan Xiong and Liusan Wu.",{"$nulls":8},"Li P., Zhang R., Analysis and forecast of RBF-SVR monthly express business volume based on TSCI change, Statistics & Decisions, 37, 5, pp. 184-188, (2021); Zhou Y., Gan L., Jin L., Prediction of daily express business scale by R programming language-based SARIMA sliding window model, Logistics Technology, 39, 10, pp. 103-108, (2020); Tang S., Deng G., Based on the theory of grey system to forecast China's business volume of express services, Modern Economy, 6, 2, pp. 283-288, (2015); Deng J., Properties of grey forecasting models GM (1, 1), Journal of Huazhong University of Science and Tedimelogy, 15, 5, pp. 1-6, (1987); Wang Y., Chen Z., Gao Z., A generalization of the GM (1, 1) direct modeling method with a step-by-step optimizing grey derivative's whiten values and its applications, Kybernetes, 33, 2, pp. 382-389, (2004); Wang Z.-X., Dang Y.-G., Liu S.-F., Optimization of background value in GM (1, 1) model, Systems Engineering-Theory & Practice, 28, 2, pp. 61-67, (2008); Song J., Liu Y., Prediction of polycyclic aromatic hydrocarbons from vehicle exhaust emission and coal combustion based on grey model GM (1, 1), Journal of Computational and Theoretical Nanoscience, 13, 9, pp. 6377-6381, (2016); Wang Y., Wei F., Sun C., Li Q., The research of improved grey GM (1, 1) model to predict the postprandial glucose in type 2 diabetes, BioMed Research International, 2016, (2016); Wu L., Fractional Order Grey Forecasting Models and Their Application, (2015); Wu L., Liu S., Yao L., Discrete grey model based on fractional-order accumulates, System Engineering-Theory & Practice, 34, 7, pp. 1822-1827, (2014); Tong Y., Chen Y., Chen H., Forecast of Tianjin municipal solid waste disposal volume based on FGM (1, 1) model, Mathematics in Practice and Theory, 50, 8, pp. 67-72, (2020); Tong Y., Chen H., Zhang X., Forecast of Beijing natural gas consumption based on FGM (1, 1) model, Mathematics in Practice and Theory, 50, 3, pp. 79-83, (2020); Zhao G., Tong Y., Chen H., Forecast of added value of high-tech industries in Hebei Province based on FGM (1, 1) model, Mathematics in Practice and Theory, 51, 6, pp. 313-317, (2021); Kennedy J., Eberhart R., Particle Swarm Optimization, pp. 1942-1948; Eberhart R., Kennedy J., A New Optimizer Using Particle Swarm Theory, pp. 39-43; Shin J.-J., Bang H., UAV path planning under dynamic threats using an improved PSO algorithm, International Journal of Aerospace Engineering, 2020, 10, (2020); Guo L., Yang X., Wang J., Design of nonlinear observer of dynamic positioning based on particle swarm optimization algorithm, Computing Technology and Automation, 39, 4, pp. 1-6, (2020); Yang L., Hu X., Li K., A vector angles-based many-objective particle swarm optimization algorithm using archive, Applied Soft Computing, 106, (2021); Hou Z., Lv Z., Particle swarm optimization with application based on MATLAB, Computer Simulation, 20, 10, pp. 68-70, (2003); Tu L., Chen Y., An unequal adjacent grey forecasting air pollution urban model, Applied Mathematical Modelling, 99, pp. 260-275, (2021)","L. Wu; College of Information Management, Nanjing Agricultural University, Nanjing, 210031, China; email: wuls@njau.edu.cn",null,"Hindawi Limited",{"$nulls":5},2.3144629E7,null,null,null,"English","J. Math.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85113986073"]
["Ren T.; Jiang Z.; Cai X.; Yu Y.; Xing L.; Zhuang Y.; Li Z.","Ren, Teng (55659417000); Jiang, Zhuo (57222173590); Cai, Xiangyu (57222170067); Yu, Yongzhuo (57222169574); Xing, Lining (13403466100); Zhuang, Yuan (57222165014); Li, Zhenping (55647884900)","55659417000; 57222173590; 57222170067; 57222169574; 13403466100; 57222165014; 55647884900","A dynamic routing optimization problem considering joint delivery of passengers and parcels",2021.0,"Neural Computing and Applications",33.0,16.0,null,10323.0,10334.0,11.0,7.0,"10.1007/s00521-021-05794-1","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85101785586&doi=10.1007%2fs00521-021-05794-1&partnerID=40&md5=573d5e2b61535886fdb32d28ba068d1e","School of Logistics and Transportation, Central South University of Forestry and Technology, Changsha, 410004, China; College of Systems Engineering, National University of Defense Technology, Changsha, 410073, China; State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China; School of Information, Beijing Wuzi University, Beijing, 101149, China","Ren T., School of Logistics and Transportation, Central South University of Forestry and Technology, Changsha, 410004, China; Jiang Z., School of Logistics and Transportation, Central South University of Forestry and Technology, Changsha, 410004, China; Cai X., School of Logistics and Transportation, Central South University of Forestry and Technology, Changsha, 410004, China; Yu Y., School of Logistics and Transportation, Central South University of Forestry and Technology, Changsha, 410004, China; Xing L., School of Logistics and Transportation, Central South University of Forestry and Technology, Changsha, 410004, China, College of Systems Engineering, National University of Defense Technology, Changsha, 410073, China, State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China; Zhuang Y., School of Logistics and Transportation, Central South University of Forestry and Technology, Changsha, 410004, China; Li Z., School of Information, Beijing Wuzi University, Beijing, 101149, China","With the rapid development of e-commerce, last-mile delivery optimization is important for reduction in logistics cost of e-business enterprises. However, the complex road network structure in various cities makes the last-mile delivery more difficult, which shows high research value. To this end, this paper proposes a special kind of share-a-ride problem (SARP), which uses online car-hailing as a carrier to transport passengers to the distribution centre and courier points to pick up and deliver parcels. The dynamics of the problem is described by designing the key points to update the delivery information; by using an improved genetic algorithm (GA), the problem is solved to realize the goal of minimizing the total cost of three participants (i.e. drivers, passengers and courier companies) and the time penalty costs. Eventually, through simulation example and comparison tests based on three sets of data of different scales, the economic applicability of the problem and the effectiveness of the algorithm are validated. © 2021, The Author(s), under exclusive licence to Springer-Verlag London Ltd. part of Springer Nature.","Genetic algorithm; Last mile; Passengers and parcels sharing; Share-a-ride; Vehicles booked on-line","Dynamic routing algorithms; Electronic commerce; Genetic algorithms; Comparison test; Complex road networks; Distribution centres; Dynamic routing; Logistics costs; Penalty cost; Simulation example; Transport passengers; Costs",{"$nulls":4},"Hunan Key Laboratory of Intelligent Logistics Technology, (2019TP1015); Innovation Team of Guangdong Provincial Department of Education, (2018KCXTD031); Opening Foundation of Beijing Intelligent Logistics Collaborative Innovation Centre, (BILSCIC-2019KF-25); National Natural Science Foundation of China, NSFC, (61773120, 71771028); State Key Lab of Digital Manufacturing Equipment and Technology, (DMETKF2020030)","This work was supported by the National Natural Science Foundation, China (No. 61773120, No.71771028), the Opening Foundation of Beijing Intelligent Logistics Collaborative Innovation Centre (No. BILSCIC-2019KF-25), the Innovation Team of Guangdong Provincial Department of Education (2018KCXTD031), Hunan Key Laboratory of Intelligent Logistics Technology (2019TP1015) and State Key Laboratory of Digital Manufacturing Equipment and Technology (DMETKF2020030). 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AbdAllah A.M.F., Essam D.L., Sarker R.A., On solving periodic re-optimization dynamic vehicle routing problems[J], Appl Soft Comput, 55, pp. 1-12, (2017); Houming F., Jiaxin W., Jing G., Et al., Vehicle routing problem with fuzzy demand and time window and hybrid genetic algorithm [J], J Syst Manag, 1, pp. 107-118, (2020); Yulei Y., Jin Z., Vehicle Routing Problem with Soft Time Windows Based on Dynamic Demands, 2019 4Th International Conference on Intelligent Transportation Engineering (ICITE), Singapore, 2019, pp. 222-226, (2019); Golpayegani F., Clarke S., Co-Ride: Collaborative preference-based taxi-sharing and taxi-dispatch, 2018 IEEE 30Th International Conference on Tools with Artificial Intelligence (ICTAI), Volos, pp. 864-871, (2018); Wang F., Zhu Y., Wang F., Liu J., Ma X., Fan X., Car4Pac: Last mile parcel delivery through intelligent car trip sharing, IEEE Transactions on Intelligent Transportation Systems; Wang F., Wang F., Ma X., Liu J., Demystifying the crowd intelligence in last mile parcel delivery for smart cities, IEEE Netw, 33, 2, pp. 23-29, (2019); Xijun Z., Qirui Z., Lijuan Z., Et al., Research on taxi shared route planning based on improved genetic algorithm, Transportation System Engineering and Information, 6, pp. 127-132, (2019); Huang H., Savkin A.V., Huang C., Optimal Control of a Hybrid UAV/Train Parcel Delivery System, 2019 Chinese Control Conference (CCC), Guangzhou, China, pp. 6606-6609, (2019); Huang H., Savkin A.V., Huang C., Control of a novel parcel delivery system consisting of a UAV and a Public Train, 2019 IEEE 17Th International Conference on Industrial Informatics (INDIN), Helsinki, Finland, pp. 1047-1050, (2019); Zhu H., Dou S., Qiu Y., Joint model for last-mile delivery service selection in China: evidence from a cross-nested logit study, IEEE Access, 7, pp. 137668-137679, (2019); Wang F., Li Y.X., Zhou A.M., Tang K., An estimation of distribution algorithm for mixed-variable newsvendor problems, IEEE Trans Evol Comput, 24, 3, pp. 479-493, (2020)","L. Xing; School of Logistics and Transportation, Central South University of Forestry and Technology, Changsha, 410004, China; email: xln_2002@nudt.edu.cn; Z. Li; School of Information, Beijing Wuzi University, Beijing, 101149, China; email: lizhenping@bwu.edu.cn",null,"Springer Science and Business Media Deutschland GmbH",{"$nulls":5},9410643.0,null,null,null,"English","Neural Comput. Appl.","Article","Final",null,"Scopus","2-s2.0-85101785586"]
["Muñoz-Villamizar A.; Solano-Charris E.L.; Reyes-Rubiano L.; Faulin J.","Muñoz-Villamizar, Andrés (55886287800); Solano-Charris, Elyn L. (35238939800); Reyes-Rubiano, Lorena (57195726657); Faulin, Javier (6506670477)","55886287800; 35238939800; 57195726657; 6506670477","Measuring Disruptions in Last-Mile Delivery Operations",2021.0,"Logistics",5.0,1.0,17.0,null,null,null,9.0,"10.3390/logistics5010017","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85145800738&doi=10.3390%2flogistics5010017&partnerID=40&md5=004cc12aa5a22432e171f5e0ebca9d05","International School of Economic and Administrative Sciences, Universidad de La Sabana, Chía, 140013, Colombia; Department of Statistics, Computer Science, and Mathematics, Institute of Smart Cities, Public University of Navarra, Pamplona, 31006, Spain","Muñoz-Villamizar A., International School of Economic and Administrative Sciences, Universidad de La Sabana, Chía, 140013, Colombia; Solano-Charris E.L., International School of Economic and Administrative Sciences, Universidad de La Sabana, Chía, 140013, Colombia; Reyes-Rubiano L., International School of Economic and Administrative Sciences, Universidad de La Sabana, Chía, 140013, Colombia; Faulin J., Department of Statistics, Computer Science, and Mathematics, Institute of Smart Cities, Public University of Navarra, Pamplona, 31006, Spain","The rapid growth of urbanisation and e-commerce has increased the number of home deliveries that need to be made in retail operations. Consequently, there is also an increase in unexpected incidents, such as adverse traffic, unavailability of parking space, and vehicle breakdowns. These disruptions result in delays, higher costs, and lower service levels in the last-mile delivery operation. Motivated by free, innovative, and efficient tools, such as the Google application programming interface (API) and Google OR, we built a model to measure the impact of disruptions in the last-mile delivery operation. Our model considers customers’ geographic information, speed estimation between nodes, routing optimisation, and disruption evaluation. Disruptions are considered here as external factors such as accidents and road works that imply the closure of or slow access to certain roads. Computational experiments, based on a set of real data from three different cities around the world, which contrast in size and characteristics (i.e., Boston, US; Bogotá, Colombia; and Pamplona, Spain), were conducted to validate our approach. The tests consider 50 different instances of up to 100 customers per city and analyse the impact of disruptions in terms of travelled time and distance. Our results provide managerial insights for key stakeholders (i.e., carriers, consumers, and government) to define policies and development plans that improve the resilience and capabilities of cities’ transportation systems. © 2021 by the authors.","disruptions; Google API; Google OR; last-mile delivery",{"$nulls":5},"Ministerio de Ciencia, Innovación y Universidades, MCIU, (PID2019-111100RB-C22/AEI/10.13039/501100011033, RED2018-102642-T); Erasmus+, (2018-1-ES01-KA103-049767)","This work has been partially supported by the Spanish Ministry of Science, Innovation, and Universities (RED2018-102642-T; PID2019-111100RB-C22/AEI/10.13039/501100011033). Moreover, we appreciate the financial support of the Erasmus+ Program (2018-1-ES01-KA103-049767). ","Pronello C., Camusso C., Valentina R., Last mile freight distribution and transport operators’ needs: Which targets and challenges?, Transp. Res. Procedia, 25, pp. 888-899, (2017); Antun J.P., Reis V., Macario R., Strategies to Improve Urban Freight Logistics in Historical Centers: The Cases of Lisbon and Mexico City, City Logistics 3, pp. 349-366, (2018); Aljohani K., Thompson R.G., Impacts of logistics sprawl on the urban environment and logistics: Taxonomy and review of literature, J. Transp. Geogr, 57, pp. 255-263, (2016); Marcucci E., Gatta V., Scaccia L., Urban freight, parking and pricing policies: An evaluation from a transport providers’ perspective, Transp. Res. Part A Policy Pract, 74, pp. 239-249, (2015); Teo J.S.E., Taniguchi E., Qureshi A.G., Evaluating City Logistics Measure in E-Commerce with Multiagent Systems, Procedia Soc. Behav. 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Manag, 48, pp. 308-332, (2018); Bosona T., Urban Freight Last Mile Logistics—Challenges and Opportunities to Improve Sustainability: A Literature Review, Sustainability, 12, (2020); Hu W., Dong J., Hwang B., Ren R., Chen Z., A Scientometrics Review on City Logistics Literature: Research Trends, Advanced Theory and Practice, Sustainability, 11, (2019); Marei N., Savy M., Global South countries: The dark side of city logistics. Dualisation vs Bipolarisation, Transp. Policy, 100, pp. 150-160, (2021); Holguin-Veras J., Kalahasthi L., Campbell S., Gonzalez-Calderon C.A., Wang X., Freight mode choice: Results from a nationwide qualitative and quantitative research effort, Transp. Res. Part A Policy Pract, 143, pp. 78-120, (2021); Zenezini G., Marco A., De City logistics policy evaluation with system dynamics, Transp. Res. Procedia, 46, pp. 253-260, (2020); Juhasz J., Banyai T., Last mile logistics: An integrated view, IOP Conf. Ser. Mater. Sci. Eng, 448, (2018); Bell M.G.H., City logistics and the urban environment, Urban Form and Accessibility, pp. 359-378, (2021); Ullah Z., Al-Turjman F., Mostarda L., Gagliardi R., Applications of Artificial Intelligence and Machine learning in smart cities, Comput. Commun, 154, pp. 313-323, (2020); Meire S., Derudder B., A bimodal accessibility analysis of Australia through application programming interfaces, Transp. A Transp. Sci, 16, pp. 695-715, (2020); Richardson D.B., Real-Time Space–Time Integration in GIScience and Geography, Ann. Assoc. Am. Geogr, 103, pp. 1062-1071, (2013); Chen P.-H., Nguyen T.C., Integrating web map service and building information modeling for location and transportation analysis in green building certification process, Autom. Constr, 77, pp. 52-66, (2017); Socharoentum M., Karimi H.A., A comparative analysis of routes generated by Web Mapping APIs, Cartogr. Geogr. Inf. Sci, 42, pp. 33-43, (2015); Weiss D.J., Nelson A., Gibson H.S., Temperley W., Peedell S., Lieber A., Hancher M., Poyart E., Belchior S., Fullman N., Et al., A global map of travel time to cities to assess inequalities in accessibility in 2015, Nature, 553, pp. 333-336, (2018); May T.H.N., Win Z.H., Design and Construction of Navigation Based Auto Self Driving Vehicle using Google Map API with GPS, Int. J. Trend Sci. Res. Dev, 39, pp. 65-68, (2019); Park Y., Mount J., Liu L., Xiao N., Miller H.J., Assessing public transit performance using real-time data spatiotemporal patterns of bus operation enhanced Reader, J. Int. J. Geogr. Inf. Sci, 34, pp. 367-392, (2019); Wang F., Xu Y., Estimating O–D travel time matrix by Google Maps API: Implementation, advantages, and implications, Ann. GIS, 17, pp. 199-209, (2011); Viergutz K., Krajzewicz D., Analysis of the Travel Time of Various Transportation Systems in Urban Context, Transp. Res. 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Technol, 121, (2020); Gendreau M., Laporte G., Potvin J.-Y., Metaheuristics for the Capacitated VRP, The Vehicle Routing Problem, pp. 129-154, (2002); Juan A.A., David Kelton W., Currie C.S.M., Faulin J., Simheuristics applications: Dealing with uncertainty in logistics, transportation, and other supply chain areas, Proceedings of the 2018 Winter Simulation Conference (WSC), pp. 3048-3059; Dettenbach A.M.C., Ubber S., Managing Disruptions in Last Mile Distribution, Proceedings of the 2015 48th Hawaii International Conference on System Sciences, pp. 1078-1087; Verlinden T., Van de Voorde E., Dewulf W., Ho.Re.Ca. logistics and European medieval structured cities: A search for cost generators, Transp. Policy, 99, pp. 419-429, (2020); Beghelli S., Guastella G., Pareglio S., Governance fragmentation and urban spatial expansion: Evidence from Europe and the United States, Rev. Reg. Res, 40, pp. 13-32, (2020)","A. Muñoz-Villamizar; International School of Economic and Administrative Sciences, Universidad de La Sabana, Chía, 140013, Colombia; email: andresmunvi@unisabana.edu.co",null,"MDPI",{"$nulls":5},2.305629E7,null,null,null,"English","Logist.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85145800738"]
["Lu Q.; Li S.; Yang T.; Xu C.","Lu, Qiao (57297962300); Li, Silin (57298766300); Yang, Tuo (57298766400); Xu, Chenheng (57226320388)","57297962300; 57298766300; 57298766400; 57226320388","An adaptive hybrid XdeepFM based deep Interest network model for click-through rate prediction system",2021.0,"PeerJ Computer Science",7.0,null,null,1.0,22.0,21.0,5.0,"10.7717/PEERJ-CS.716","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85117171257&doi=10.7717%2fPEERJ-CS.716&partnerID=40&md5=b6dec9174566c6e75b1a641d8888f589","Taicu Music co Ltd Shenzhen China, Shenzhen, United Kingdom; School of Economics, Tianjin University of Commerce, Tianjin, China","Lu Q., Taicu Music co Ltd Shenzhen China, Shenzhen, United Kingdom; Li S., Taicu Music co Ltd Shenzhen China, Shenzhen, United Kingdom; Yang T., Taicu Music co Ltd Shenzhen China, Shenzhen, United Kingdom; Xu C., School of Economics, Tianjin University of Commerce, Tianjin, China","Recent advances in communication enable individuals to use phones and computers to access information on the web. E-commerce has seen rapid development, e.g., Alibaba has nearly 12 hundred million customers in China. Click-Through Rate (CTR) forecasting is a primary task in the e-commerce advertisement system. From the traditional Logistic Regression algorithm to the latest popular deep neural network methods that follow a similar embedding and MLP, several algorithms are used to predict CTR. This research proposes a hybrid model combining the Deep Interest Network (DIN) and eXtreme Deep Factorization Machine (xDeepFM) to perform CTR prediction robustly. The cores of DIN and xDeepFM are attention and feature cross, respectively. DIN follows an adaptive local activation unit that incorporates the attention mechanism to adaptively learn user interest from historical behaviors related to specific advertisements. xDeepFM further includes a critical part, a Compressed Interactions Network (CIN), aiming to generate feature interactions at a vectorwise level implicitly. Furthermore, a CIN, plain DNN, and a linear part are combined into one unified model to form xDeepFM. The proposed end-to-end hybrid model is a parallel ensemble of models via multilayer perceptron. CIN and xDeepFM are trained in parallel, and their output is fed into a multilayer perceptron. We used the e-commerce Alibaba dataset with the focal loss as the loss function for experimental evaluation through online complex example mining (OHEM) in the training process. The experimental result indicates that the proposed hybrid model has better performance than other models. © 2021. Lu et al. All Rights Reserved.","Agents and Multi-Agent Systems; Algorithms and Analysis of Algorithms; Artificial Intelligence; Brain-Computer Interface; Click-Through Rate Prediction; Computational Linguistics; Deep Interest Network; Deep Learning; Hybrid model; Machine Learning; Neural Networks; OHEM; Parallel ensemble; XDeepFM","Behavioral research; Brain computer interface; Deep neural networks; Forecasting; Intelligent agents; Multi agent systems; Multilayer neural networks; Multilayers; Agent and multi-agent system; Algorithm and analyse of algorithm; Analysis of algorithms; Click-through rate prediction; Clickthrough rates (CTR); Deep interest network; Deep learning; Hybrid model; Machine-learning; Neural-networks; OHEM; Parallel ensemble; Rate predictions; XDeepFM; Electronic commerce",{"$nulls":6},"Albahli S, Rauf HT, Algosaibi A, Balas VE., Ai-driven deep cnn approach for multilabel pathology classification using chest X-rays, PeerJ Computer Science, 7, (2021); Amodei D, Ananthanarayanan S, Anubhai R, Bai J, Battenberg E, Case C, Casper J, Catanzaro B, Cheng Q, Chen G, Chen J, Chen J, Chen Z, Chrzanowski M, Coates A, Diamos G, Ding K, Du N, Elsen E, Engel J, Fang W, Fan L, Fougner C, Gao L, Gong C, Hannun A, Han T, Johannes L, Jiang B, Ju C, Jun B, LeGresley P, Lin L, Liu J, Liu Y, Li W, Li X, Ma D, Narang S, Ng A, Ozair S, Peng Y, Prenger R, Qian S, Quan Z, Raiman J, Rao V, Satheesh S, Seetapun D, Sengupta S, Srinet K, Sriram A, Tang H, Tang L, Wang C, Wang J, Wang K, Wang Y, Wang Z, Wang Z, Wu S, Wei L, Xiao B, Xie W, Xie Y, Yogatama D, Yuan B, Zhan J, Zhu Z., Deep speech 2: end-to-end speech recognition in english and mandarin, (2016); 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Zhou G, Mou N, Fan Y, Pi Q, Bian W, Zhou C, Zhu X, Gai K., Deep interest evolution network for click-through rate prediction, Proceedings of the AAAI conference on artificial intelligence, 33, pp. 5941-5948, (2019); Zhou G, Zhu X, Song C, Fan Y, Zhu H, Ma X, Yan Y, Jin J, Li H, Gai K., Deep interest network for click-through rate prediction, Proceedings of the 24th ACM SIGKDD international conference on knowledge discovery & data mining, pp. 1059-1068, (2018)","C. Xu; School of Economics, Tianjin University of Commerce, Tianjin, China; email: 8322275281@163.com",null,"PeerJ Inc.",{"$nulls":5},2.3765992E7,null,null,null,"English","PeerJ Comput. Sci.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85117171257"]
["Srivatsa Srinivas S.; Marathe R.R.","Srivatsa Srinivas, S. (56816990200); Marathe, Rahul R. (8519236300)","56816990200; 8519236300","Moving towards “mobile warehouse”: Last-mile logistics during COVID-19 and beyond",2021.0,"Transportation Research Interdisciplinary Perspectives",10.0,null,100339.0,null,null,null,67.0,"10.1016/j.trip.2021.100339","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85102899549&doi=10.1016%2fj.trip.2021.100339&partnerID=40&md5=d827824bfb3b2b2f0da41d13a68c1f3c","Production & Quantitative Methods Area, Indian Institute of Management Ahmedabad, Ahmedabad, Gujarat, India; Department of Management Studies, Indian Institute of Technology Madras, Chennai, 600036, India","Srivatsa Srinivas S., Production & Quantitative Methods Area, Indian Institute of Management Ahmedabad, Ahmedabad, Gujarat, India; Marathe R.R., Department of Management Studies, Indian Institute of Technology Madras, Chennai, 600036, India","Supply chains in general and last-mile logistics in particular, have been disrupted due to COVID-19. Though several innovative last-mile logistics solutions have been proposed in the past, they possess certain limitations, especially during COVID-19 motivating the need for an alternative last-mile logistics solution. We present a review of literature related to last-mile logistics and supply chain disruptions to identify the limitations of existing last-mile delivery practices during COVID-19. Using a stylized analytical model, we then propose that “mobile warehouse” can be an effective solution to last-mile logistics issues faced during COVID-19 and beyond under certain conditions. A mobile warehouse is a truck dedicated to a particular geographical location and carries the inventory of various products based on the estimated demand requirements for these products in that geographical location. We provide the condition under which the B2C e-commerce providers find it profitable to adopt a truck as a mobile warehouse to sell high demand items quickly. © 2021 The Authors","COVID-19; E-commerce; Innovation; Last-mile logistics; Mobile warehouse; Supply chain management",{"$nulls":7},"Akeb H., Moncef B., Durand B., Building a collaborative solution in dense urban city settings to enhance parcel delivery: an effective crowd model in Paris, Transp. Res. E Logist. Transp. Rev., 119, pp. 223-233, (2018); Arslan A.M., Agatz N., Kroon L., Zuidwijk R., Crowdsourced delivery—aa dynamic pickup and delivery problem with ad hoc drivers, Transp. Sci., 53, 1, pp. 222-235, (2019); Asdemir K., Jacob V.S., Krishnan R., Dynamic pricing of multiple home delivery options, Eur. J. Oper. 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J. Retail Distrib. Manag., 36, 8, pp. 638-660, (2008); Xu Z., Elomri A., Kerbache L., El Omri A., Impacts of COVID-19 on global supply chains: facts and perspectives, IEEE Eng. Manage. Rev., 48, 3, pp. 153-166, (2020); Yuen K.F., Wang X., Ng L.T.W., Wong Y.D., An investigation of customers’ intention to use self-collection services for last-mile delivery, Transp. Policy, 66, pp. 1-8, (2018); Yuen K.F., Wang X., Ma F., Wong Y.D., The determinants of customers’ intention to use smart lockers for last-mile deliveries, J. Retail. nd Consumer Serv., 49, pp. 316-326, (2019); Zhang Y., Sun L., Hu X., Zhao C., Order consolidation for the last-mile split delivery in online retailing, Transp. Res. E Logist. Transp. Rev., 122, pp. 309-327, (2019)","R.R. Marathe; Department of Management Studies, Indian Institute of Technology Madras, Chennai, 600036, India; email: rrmarathe@iitm.ac.in",null,"Elsevier Ltd",{"$nulls":5},2.5901982E7,null,null,null,"English","Transp.  Res.  Interdiscip.  Perspect.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85102899549"]
["Grant D.B.; Banomyong R.; Gibson B.J.","Grant, David B. (55545862384); Banomyong, Ruth (24921269800); Gibson, Brian J. (7202976303)","55545862384; 24921269800; 7202976303","A brave new world for retail logistics and SCM in the 2020s and beyond",2021.0,"International Journal of Logistics Research and Applications",{"$nulls":6},9.0,"10.1080/13675567.2021.1986477","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85116385297&doi=10.1080%2f13675567.2021.1986477&partnerID=40&md5=98ca0416db714f6226a774dade2d3e0b","Hanken School of Economics, Helsinki, Finland; Thammasat University, Bangkok, Thailand; Auburn University, Auburn, AL, United States","Grant D.B., Hanken School of Economics, Helsinki, Finland, Thammasat University, Bangkok, Thailand; Banomyong R., Thammasat University, Bangkok, Thailand; Gibson B.J., Hanken School of Economics, Helsinki, Finland, Auburn University, Auburn, AL, United States","This perspective paper considers the current state of retail and retail logistics and supply chain management to discuss what the future may hold for it through four important issues: changing consumer expectations, the impact of e-commerce, and the relationship with the natural environment all of which are influenced by the economic environment. These issues apply to retailing globally and have been exacerbated by events such as the global COVID-19 pandemic, and examples are provided from various retail markets to illustrate them. Retailers will need to think strategically how to adapt their business models to address these issues by recognising the needs of new consumer segments, focussing on niche service and products to avoid direct clashes with larger physical store and Internet retailers, embracing more fully opportunities in e-commerce, and ensuring their activities are sustainable economically, socially and ecologically. © 2021 Informa UK Limited, trading as Taylor & Francis Group.","consumer expectations; E-commerce; economy; environment; Perspective; retailing",{"$nulls":7},"Ali F., (2020); (2021); Anderson L., Analytic Autoethnography, Journal of Contemporary Ethnography, 35, 4, pp. 373-395, (2006); (2021); (2021); Blechingberg-Kilpi P., Grant D.B., Corporate and Social Responsibility Perspectives of Finnish Fashion Retailers and Consumers, Essential Issues in Corporate Social Responsibility: New Insights and Recent Issues, pp. 55-71, (2020); Caro F., Kok A.G., Martinez-de-Albeniz V., The Future of Retail Operations, Manufacturing & Service Operations Management, 22, 1, pp. 47-58, (2019); Chambers S., (2021); Cheung M.-C., (2021); Dabija D.-C., Bejan B.M., Grant D.B., The Impact of Consumer Green Behaviour on Green Loyalty among Retail Formats: A Romanian Case Study, Moravian Geographical Reports, 26, 3, pp. 173-185, (2018); Danziger P.N., (2020); The Future of High Streets: Progress Since the Portas Review, (2013); (2019); (2020); Dickinson H., (2014); (2020); Eger L., Komarkova L., Egerova D., Micik M., The Effect of COVID-19 on Consumer Shopping Behaviour: Generational Cohort Perspective, Journal of Retailing and Consumer Services, 61, (2021); Esper T.L., Castillo V.E., Ren K., Sodero A., Wan X., Croxton K.L., Knemeyer A.M., DeNunzio S., Zinn W., Goldsby T.J., Everything is old Again: The age of Consumer-Centric Supply Chain Management, Journal of Business Logistics, 41, 4, pp. 286-293, (2020); Fernie J., Grant D.B., Fashion Logistics, (2019); Fry R., (2020); Gauri D.K., Jindal R.P., Ratchford B., Fix E., Bhatnagar A., Pandey A., Navallo J.R., Fogarty J., Carr S., Howerton E., Evolutions of Retail Formats: Past, Present, and Future, Journal of Retailing, 97, 1, pp. 42-61, (2021); Gibson B.J., Ishfaq R., Logistics 2030 Navigating a Disruptive Decade: Year 2–Warehousing and Distribution, (2020); Gibson B.J., Ishfaq R., Davis-Sramek B., 2022 State of the Retail Supply Chain, (2020); Gibson B.J., Ishfaq R., Defee C., Davis-Sramek B., 2018 State of the Retail Supply Chain, (2018); Gibson B.J., Thornton L., Davis-Sramek B., Logistics 2030 Navigating a Disruptive Decade: Year 1–Freight Transportation, (2019); Gold S., Trautrims A., Trodd Z., Modern Slavery Challenges to Supply Chain Management, Supply Chain Management: An International Journal, 20, 5, pp. 485-494, (2015); (2020); Grandval S., Nimtrakool K., Grant D.B., Factors of Adoption Governing the Emergence of Urban Consolidation Centres, Supply Chain Forum: An International Journal, 20, 4, pp. 247-256, (2019); Grant D.B., Logistics Management, (2012); Grant D.B., Fulfilling Customer Needs in the 2020s with Marketing and Logistics, Global Logistics: New Directions in Supply Chain Management, pp. 79-94, (2021); Grant D.B., Dabija D.-C., Colicchia C., Creazza A., Philipp B., Spens K., Babut R., Expectations of Millennial Consumers Regarding Online Shopping and Fulfilment, Proceedings of the 22nd Annual Logistics Research Network (LRN) Conference - Southampton Solent University, pp. 356-363, (2017); Grant D.B., Menachof D., Bovis C., The ‘Deglobalisation’ of Logistics and Supply Chains in an Increasingly Nationalistic and Risky World, Global Logistics: New Directions in Supply Chain Management, pp. 427-446, (2021); Grant D.B., Shaw S., Environmental or Sustainable Supply Chain Performance Measurement Standards and Certifications, Handbook on the Sustainable Supply Chain, pp. 357-376, (2019); Grant D.B., Trautrims A., Wong C.Y., Sustainable Logistics and Supply Chain Management, (2017); Harvey F., (2021); Herrera S., (2021); Hingley M., Lindgreen A., Grant D.B., Kane C., Using Fourth Party Logistics Management to Improve Horizontal Collaboration among Grocery Retailers, Supply Chain Management: An International Journal, 16, 5, pp. 316-327, (2011); (2020); Jacobs M., (2021); Larsen A.S., Enlund M., (2021); McArthur E., Weaven S., Dant R., The Evolution of Retailing: A Meta Review of the Literature, Journal of Macromarketing, 36, 3, pp. 272-286, (2016); McKinnon A., Browne M., Piecyk M., Whiteing A., Green Logistics, (2015); (2020); Mesure S., (2013); Meyer L., (2016); Morgan B., (2018); O'Carroll L., (2021); Olsen N., From Choice to Welfare: The Concept of the Consumer in the Chicago School of Economics, Modern Intellectual History, 14, 2, pp. 507-535, (2017); O'Neil L., (2021); Pagano M., (2013); Popa I.D., Dabija D.-C., Grant D.B., Exploring Omnichannel Retailing Differences and Preferences among Consumer Generations, Applied Ethics for Entrepreneurial Success: Recommendations for the Developing World, pp. 129-146, (2019); Prateepsawangwong N., Luo C., (2018); Price C.C., Edwards K.A., Trends in Income from 1975 to 2018, (2020); Rafi-Ul-Shan P.M., Grant D.B., Perry P., Are Fashion Supply Chains Capable of Coopetition? An Exploratory Study in the UK, International Journal of Logistics: Research and Applications, (2020); Ralls A., (2021); Roggeveen A.L., Sethuraman R., Editorial: How the COVID-19 Pandemic may Change the World of Retailing, Journal of Retailing, 96, 2, pp. 169-171, (2020); Scurria A., Sebastian D., (2021); Sharma R., (2014); Souiden N., Ladhari R., Chiadmi N.-E., Editorial: New Trends in Retailing and Services, Journal of Retailing and Consumer Services, 50, pp. 286-288, (2019); (2019); (2019); (2019); Stephens D., (2020); Suba C., (2019); (2021); Vadakkepatt G.G., Winterich K.P., Mittal V., Zinn W., Beitelspacher L., Aloysius J., Ginger J., Reilman J., Sustainable Retailing, Journal of Retailing, 97, 1, pp. 62-80, (2021); Verhoef P.C., Kannan P.K., Inman J.J., From Multi-Channel Retailing to Omni-Channel Retailing, Introduction to the Special Issue on Multi-Channel Retailing. Journal of Retailing, 21, 2, pp. 174-181, (2015); Yawar S.A., Seuring S., Management of Social Issues in Supply Chains: A Literature Review Exploring Social Issues, Actions and Performance Outcomes, Journal of Business Ethics, 141, 3, pp. 621-643, (2017)","D.B. Grant; Hanken School of Economics, Helsinki, Finland; email: david.grant@hanken.fi",null,"Taylor and Francis Ltd.",{"$nulls":5},1.3675567E7,null,null,null,"English","Int. J. Logist. Res. Applic.","Article","Article in press",null,"Scopus","2-s2.0-85116385297"]
["Villa R.; Monzón A.","Villa, Rafael (57223124517); Monzón, Andrés (35782062100)","57223124517; 35782062100","A metro-based system as sustainable alternative for urban logistics in the era of e-commerce",2021.0,"Sustainability (Switzerland)",13.0,8.0,4479.0,null,null,null,26.0,"10.3390/su13084479","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85104989206&doi=10.3390%2fsu13084479&partnerID=40&md5=b76bc720f98a2321a28c3dda05ec010e","School of Technology and Science, Camilo José Cela University, Madrid, 28692, Spain; Transport Research Centre (TRANSyT), Universidad Politécnica de Madrid, Madrid, 28040, Spain","Villa R., School of Technology and Science, Camilo José Cela University, Madrid, 28692, Spain; Monzón A., Transport Research Centre (TRANSyT), Universidad Politécnica de Madrid, Madrid, 28040, Spain","Business to consumer e-commerce (B2C) has increased sharply in recent years driven by a growing online population and changes in consumer behavior. In metropolitan areas, the “Amazon effect” (online retailers’ vast selection, fast shipping, free returns, and low prices) has led to an increased use of light goods vehicles. This is affecting the rational functioning of the transport system, including a high degree of fragmentation, low load optimization, and, among other externalities, higher traffic congestion. This paper investigates the potential of a metro system, in a big city like Madrid, to provide delivery services by leveraging its existing carrying capacity and using the metro stations to collect parcels in lockers. It would be a new mixed distribution model for last-mile deliveries associated with e-commerce. To that end, the paper evaluates the cost and impacts of two alternative scenarios for managing the unused space in rolling stock (shared trains) or specific full train services (dedicated trains) on existing lines. The external costs of the proposed scenarios are compared with current e-commerce delivery scenario (parcel delivery by road). The results show that underground transport of parcels could significantly reduce congestion costs, accidents, noise, GHG emissions, and air pollution. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.","City logistics; E-commerce; Externality; Last-mile innovation; Sustainable development; Urban rail freight","Madrid [Spain]; Spain; carrying capacity; cost analysis; electronic commerce; logistics; metropolitan area; sustainability; traffic congestion",{"$nulls":6},"Sanchez-Diaz I., Browne M., Accommodating urban freight in city planning, Eur. Transp. Res. Rev, 10, (2018); Eurostat Digital Economy and Society Statistics—Households and Individuals—Statistics Explained; Rai H.B., Verlinde S., Merckx J., Macharis C., Crowd logistics: An opportunity for more sustainable urban freight transport?, Eur. Transp. Res. Rev, 9, (2017); Macharis C., Nocera S., The future of freight transport, Eur. Transp. Res. Rev, 11, (2019); Greenhouse Gas Emissions from Transport in Europe—European Environment Agency; Dablanc L., Goods transport in large European cities: Difficult to organize, difficult to modernize, Transp. Res. Part A Policy Pract, 41, pp. 280-285, (2007); Urban Freight. Research & Innovation Roadmap, (2015); Gonzalez-Feliu J., Costs and Benefits of Railway Urban Logistics: A Prospective Social Cost Benefit Analysis; Browne M., Allen J., Woodburn A., Piotrowska M., The Potential for Non-road Modes to Support Environmentally Friendly Urban Logistics, Procedia Soc. Behav. Sci, 151, pp. 29-36, (2014); Statista COVID-19 Impact on Global Retail e-Commerce Site Traffic 2019–2020; Crainic T.G., Ricciardi N., Storchi G., Advanced freight transportation systems for congested urban areas, Transp. Res. Part C Emerg. Technol, 12, pp. 119-137, (2004); Cardenas I., Borbon-Galvez Y., Verlinden T., Van De Voorde E., Vanelslander T., Dewulf W., City logistics, urban goods distribution and last mile delivery and collection, Compet. Regul. Netw. Ind, 18, pp. 22-43, (2017); Lebeau P., Macharis C., Freight transport in Brussels and its impact on road traffic?, Bruss. Stud, (2014); Morganosky M.A., Cude B.J., Consumer demand for online food retailing: Is it really a supply side issue?, Int. J. Retail. Distrib. Manag, 30, pp. 451-458, (2002); Same-Day Delivery. Not Ready for Prime Time, (2013); The Future of Last Mile; Travel, Transport and Logistics, (2016); Ringing in the Retail, (2018); The Last-Mile Delivery Challenge. Giving Retail and Consumer Product Customers a Superior Delivery Experience without Impacting Profitability, (2019); Allen J., Thorne G., Browne M., Good Practice Guide on Urban Freight Transport, (2007); Lemmens N., Gijsbrechts J., Boute R., Synchromodality in the Physical Internet—Dual sourcing and real-time switching between transport modes, Eur. Transp. Res. Rev, 11, (2019); Arvidsson N., Browne M., A Review of the Success and Failure of Tram Systems to Carry Urban Freight: The Implications for a Low Emission Intermodal Solution Using Electric Vehicles on Trams, Eur. Transp, 54, (2013); Marinov M., Giubilei F., Gerhardt M., Ozkan T., Stergiou E., Papadopol M., Cabecinha L., Urban freight movement by rail, J. Transp. Lit, 7, pp. 87-116, (2013); Strale M., The Cargo Tram: Current Status and Perspectives, the Example of Brussels, Transport and Sustainability, 6, pp. 245-263, (2014); Oishi R., Taniguchi E., Effects and Profitability of Constructing the New Underground Freight Transport System, Proceedings of the 1st International Conference on City Logistics, (1999); Robinson A.M., Mortimer P.N., Logistics & Transport Focus, (2004); Kikuta J., Ito T., Tomiyama I., Yamamoto S., Yamada T., New Subway-Integrated City Logistics Szystem, Procedia Soc. Behav. Sci, 39, pp. 476-489, (2012); Dampier A., Marinov M., A Study of the Feasibility and Potential Implementation of Metro-Based Freight Transportation in Newcastle upon Tyne, Urban Rail Transit, 1, pp. 164-182, (2015); Behiri W., Belmokhtar-Berraf S., Chu C., Urban freight transport using passenger rail network: Scientific issues and quantitative analysis, Transp. Res. Part E Logist. Transp. Rev, 115, pp. 227-245, (2018); Gatta V., Marcucci E., Nigro M., Serafini S., Sustainable urban freight transport adopting public transport-based crowdshipping for B2C deliveries, Eur. Transp. Res. Rev, 11, (2019); Li Q., Lai Y., Wang Q., Lu Z., Mechanical Structure Design of Underground Logistics System Based on Passenger and Freight Transportation, IOP Conf. Ser. Mater. Sci. Eng, 688, (2019); Leung L., Cheung W., Van Hai Y., A framework for a logistics e-commerce community network: The Hong Kong air cargo industry, IEEE Trans. Syst. Man Cybern. Part A Syst. Hum, 30, pp. 446-455, (2000); Okholm H.B., Thelle M.H., Moller A., Basalisco B., Rolmer S., Copenhagen Economics E-Commerce and Delivery: A Study of the State of Play of EU Parcel Markets with Particular Emphasis on e-Commerce, (2013); Kotler P., Keller K., Marketing Management, (2012); Essen H., van Wijngaarden L., van Schroten A., Sutter D., Bieler C., Maffii S., Brambilla M., Fiorello D., Fermi F., Parolin R., Et al., Handbook on the External Costs of Transport, (2019); Padrón Municipal de Habitantes; Plan de Calidad de Aire de la Ciudad de Madrid y Cambio Climático (PLAN A)—Ayuntamiento de Madrid; Cambio Climático—Inventario de emisiones—Ayuntamiento de Madrid; Metro de Madrid Proyectos y Datos; Edwards J., McKinnon A., Cherrett T., Song L., The Impact of Failed Home Delivery on Carbon Emissions: Are Collection/Delivery Points Environmentally-Friendly Alternatives, (2009); Lemke J., Iwan S., Korczak J., Usability of the Parcel Lockers from the Customer Perspective—The Research in Polish Cities, Transp. Res. Procedia, 16, pp. 272-287, (2016); Bart D.M., Ecological and Economic Impact of Automated Parcel Lockers vs. Home Delivery, (2017); Gevaers R., Van de Voorde E., Vanelslander T., Cost Modelling and Simulation of Last-mile Characteristics in an Innovative B2C Supply Chain Environment with Implications on Urban Areas and Cities, Procedia Soc. Behav. Sci, 125, pp. 398-411, (2014); Van Duin J., De Goffau W., Wiegmans B., Tavasszy L., Saes M., Improving Home Delivery Efficiency by Using Principles of Address Intelligence for B2C Deliveries, Transp. Res. Procedia, 12, pp. 14-25, (2016); Van Duin J., Wiegmans B., van Arem B., van Amstel Y., From home delivery to parcel lockers: A case study in Amsterdam, Transp. Res. Procedia, 46, pp. 37-44, (2020); Edición del Estudio Sobre Logística del eCommerce y Marketplaces; IPC Cross-Border E-Commerce Shopper Survey, (2019); (2019); CNMCData—Comision Nacional de Los Mercados y La Competencia; Handbook on the External Costs of Transport: Version 2019-1.1; Padrón Municipal—Portal de Datos Abiertos del Ayuntamiento de Madrid","R. Villa; School of Technology and Science, Camilo José Cela University, Madrid, 28692, Spain; email: rvilla@ucjc.edu",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85104989206"]
["Maheshbhai P.V.; Shaileshbhai P.N.; Mohanlal P.V.","Maheshbhai, Patel Venci (57327684800); Shaileshbhai, Patel Nehal (57326974000); Mohanlal, Prajapati Viral (57327399000)","57327684800; 57326974000; 57327399000","E-commerce accompanied by errand mechanism for user convenience",2021.0,"Journal of Engineering Research (Kuwait)",2021.0,{"$nulls":5},0.0,"10.36909/jer.ICETET.14987","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85118746390&doi=10.36909%2fjer.ICETET.14987&partnerID=40&md5=21600b0363ce4f98d23ec4d22d7d42be","Department of Information Technology, Laxmi Institute of Technology, Valsad, Gujarat, Sarigam, India","Maheshbhai P.V., Department of Information Technology, Laxmi Institute of Technology, Valsad, Gujarat, Sarigam, India; Shaileshbhai P.N., Department of Information Technology, Laxmi Institute of Technology, Valsad, Gujarat, Sarigam, India; Mohanlal P.V., Department of Information Technology, Laxmi Institute of Technology, Valsad, Gujarat, Sarigam, India","Nowadays many families are dealing with the problem of fast and energy-saving delivery of groceries. Also, they can't purchase products from different sellers of their choice in a single buy. Thus, to overcome these problems, we are going to make an application called \"SAHAYAK-Simplicity of life\". It is providing solutions based on vocal for local and errand methods. SAHAYAK is trying to connect local vendors & buyers on a single platform and to implement an errand method for any normal person who wants to deliver their nearest ones' ordered products can deliver. They earn credit points for such delivery which can be helpful for them in their future shopping. In SAHAYAK, the customer has a choice to select various products from their selected vendors and pay for them all together, the system will request those items to the respective sellers and collect & deliver them all together. Easy process to buy the groceries which customers want, don't have to pay extra or pay differently at all places. © 2021 University of Kuwait. All rights reserved.","Delivery service; Errand; Essentials; Traders",{"$nulls":7},"(2019); Prakash Prarthana, The Rise of the Online Grocery Market in India, (2020); Dashnov Sanchita, Online grocery may become a $10 billion industry by 2023 but even then, only one in 100 Indians will be buying, (2019)","P.V. Mohanlal; Department of Information Technology, Laxmi Institute of Technology, Sarigam, Valsad, Gujarat, India; email: viral_itworld@hotmail.com",null,"University of Kuwait",{"$nulls":5},2.3071885E7,null,null,null,"English","J. Eng. Res. (Kuwait)","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85118746390"]
["Serrano-Hernandez A.; Ballano A.; Faulin J.","Serrano-Hernandez, Adrian (57215653301); Ballano, Aitor (57226612593); Faulin, Javier (6506670477)","57215653301; 57226612593; 6506670477","Selecting freight transportation modes in last-mile urban distribution in pamplona (Spain): An option for drone delivery in smart cities",2021.0,"Energies",14.0,16.0,4748.0,null,null,null,18.0,"10.3390/en14164748","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85112066881&doi=10.3390%2fen14164748&partnerID=40&md5=daf49b3a4390db46736aa7e597b3642e","Department of Statistics, Computer Science, and Mathematics, Institute of Smart Cities, Public University of Navarre, Pamplona, 31006, Spain; Aerospace Systems and Transport Research Group, European Institute for Aviation Training and Accreditation (EIATA), Rey Juan Carlos University, Fuenlabrada, 28943, Spain","Serrano-Hernandez A., Department of Statistics, Computer Science, and Mathematics, Institute of Smart Cities, Public University of Navarre, Pamplona, 31006, Spain; Ballano A., Department of Statistics, Computer Science, and Mathematics, Institute of Smart Cities, Public University of Navarre, Pamplona, 31006, Spain, Aerospace Systems and Transport Research Group, European Institute for Aviation Training and Accreditation (EIATA), Rey Juan Carlos University, Fuenlabrada, 28943, Spain; Faulin J., Department of Statistics, Computer Science, and Mathematics, Institute of Smart Cities, Public University of Navarre, Pamplona, 31006, Spain","Urban distribution in medium-sized cities faces a major challenge, mainly when deliveries are difficult in the city center due to: an increase of e-commerce, weak public transportation system, and the promotion of urban sustainability plans. As a result, private cars, public transportation, and freight transportation compete for the same space. This paper analyses the current state for freight logistics in the city center of Pamplona (Spain) and proposes alternative transportation routes and transportation modes in the last-mile city center distribution according to different criteria evaluated by residents. An analytic hierarchy process (AHP) was developed. A number of alternatives have been assessed considering routes and transportation modes: the shortest route criterion and avoiding some city center area policies are combined with traditional van-based, bike, and aerial (drone) distribution protocols for delivering parcels and bar/restaurant supplies. These alternatives have been evaluated within a multicriteria framework in which economic, environmental, and social objectives are considered at the same time. The point in this multicriteria framework is that the criteria/alternative AHP weights and priorities have been set according to a survey deployed in the city of Pamplona (Navarre, Spain). The survey and AHP results show the preference for the use of drone or bike distribution in city center in order to reduce social and environmental issues. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.","Analytic hierarchy process; Drones; Energy optimization; Freight urban transportation","Analytic hierarchy process; Antennas; Drones; Geographical distribution; Hierarchical systems; Smart city; Surveys; Sustainable development; Targeted drug delivery; Transportation routes; Urban transportation; Analytic hierarchy process (ahp); Distribution protocols; Public transportation; Public transportation systems; Social and environmental; Transportation mode; Urban distribution; Urban sustainability; Freight transportation",{"$nulls":4},"“la Caixa” Foundation, (LCF/PR/PR15/51100007); Ministerio de Ciencia, Innovación y Universidades, MCIU, (PID2019-111100RB-C22/AEI/10.13039/501100011033, RED2018-102642-T); Erasmus+, (2018-1-ES01-KA103-049767)","This work has been partially supported by the Spanish Ministry of Science, Innovation, and Universities (PID2019-111100RB-C22/AEI/10.13039/501100011033; RED2018-102642-T), and the “la Caixa” Foundation (LCF/PR/PR15/51100007) project. Moreover, we appreciate the financial support of the Erasmus+ Program (2018-1-ES01-KA103-049767). Similarly, we would like to thank Jose Carlos Velasco and Ulrich Recalde for their support with the development of survey depicted in this article.","Perez-Martinez P., Miranda R., Andrade M., Kumar P., Air quality and fossil fuel driven transportation in the Metropolitan Area of São Paulo, Transp. Res. Interdiscip. Perspect, 5, (2020); Wang T., Lin B., Fuel consumption in road transport: A comparative study of China and OECD countries, J. Clean. Prod, 206, pp. 156-170, (2019); Denant-Boemont L., Faulin J., Hammiche S., Serrano-Hernandez A., Valuations of Transport Nuisances and Cognitive Biases: A Survey Laboratory Experiment in the Pyrenees Region, Environ. Model. Assess, pp. 1-16, (2021); Corlu C., De La Torre R., Serrano-Hernandez A., Juan A., Faulin J., Optimizing energy consumption in transportation: Literature review, insights, and research opportunities, Energies, 13, (2020); Faulin J., Grasman S.E., Juan A.A., Hirsch P., Sustainable transportation: Concepts and current practices, Sustainable Transportation and Smart Logistics, pp. 3-23, (2019); Visser J., Nemoto T., Browne M., Home Delivery and the Impacts on Urban Freight Transport: A Review, Procedia Soc. Behav. Sci, 125, pp. 15-27, (2014); Li Y., Zhao R., Liu T., Zhao J., Does urbanization lead to more direct and indirect household carbon dioxide emissions? Evidence from China during 1996–2012, J. Clean. Prod, 102, pp. 103-114, (2015); Li L., Liu Y., Spatial-Temporal Patterns and Driving Forces of Sustainable Urbanization in China since 2000, J. Urban Plan. 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Consum. Serv, 49, pp. 186-197, (2019); Comi A., Nuzzolo A., Exploring the Relationships between e-shopping Attitudes and Urban Freight Transport, Transp. Res. Procedia, 12, pp. 399-412, (2016); The Last-Mile Delivery Challenge, (2019); Faulin J., Sarobe P., Simal J., The DSS LOGDIS optimizes delivery routes for FRILAC’s frozen products, Interfaces, 35, pp. 202-214, (2005); He Y., Wang X., Zhou F., Lin Y., Dynamic vehicle routing problem considering simultaneous dual services in the last mile delivery, Kybernetes, 49, pp. 1267-1284, (2019); Archetti C., Bertazzi L., Recent challenges in Routing and Inventory Routing: E-commerce and last-mile delivery, Networks, 77, pp. 255-268, (2020); Serrano-Hernandez A., Hirsch P., Faulin J., Fikar C., The role of horizontal cooperation to improve service quality in last-mile distribution, Int. J. Simul. Process Model, 13, pp. 299-309, (2018); Serrano-Hernandez A., Faulin J., Hirsch P., Fikar C., Agent-based simulation for horizontal cooperation in logistics and transportation: From the individual to the grand coalition, Simul. Model. Pract. Theory, 85, pp. 47-59, (2018); Quintero-Araujo C.L., Gruler A., Juan A.A., Faulin J., Using horizontal cooperation concepts in integrated routing and facility-location decisions, Int. Trans. Oper. Res, 26, pp. 551-576, (2019); Paddeu D., Parkhurst G., Fancello G., Fadda P., Ricci M., Multi-stakeholder collaboration in urban freight consolidation schemes: Drivers and barriers to implementation, Transport, 33, pp. 913-929, (2018); Allen J., Bektas T., Cherrett T., Friday A., McLeod F., Piecyk M., Piotrowska M., Zaltz Austwick M., Enabling a freight traffic controller for collaborative multidrop urban logistics: Practical and theoretical challenges, Transp. Res. Rec, 2609, pp. 77-84, (2017); Salama M., Srinivas S., Joint optimization of customer location clustering and drone-based routing for last-mile deliveries, Transp. Res. Part C Emerg. Technol, 114, pp. 620-642, (2020); Jackson A., Srinivas S., A Simulation-Based Evaluation of Drone Integrated Delivery Strategies for Improving Pharmaceutical Service, Supply Chain Management in Manufacturing and Service Systems. International Series in Operations Research and Management Science, 304, pp. 185-204, (2021); Erdogan S., Miller-Hooks E., A Green Vehicle Routing Problem, Transp. Res. Part E Logist. Transp. Rev, 48, pp. 100-114, (2012); Moghdani R., Salimifard K., Demir E., Benyettou A., The green vehicle routing problem: A systematic literature review, J. Clean. Prod, 279, (2021); Liu C., Wang Q., Susilo Y., Assessing the impacts of collection-delivery points to individual’s activity-travel patterns: A greener last mile alternative?, Transp. Res. Part E Logist. Transp. Rev, 121, pp. 84-99, (2019); Wygonik E., Goodchild A., Urban form and last-mile goods movement: Factors affecting vehicle miles travelled and emissions, Transp. Res. Part D Transp. Environ, 61, pp. 217-229, (2018); Ranieri L., Digiesi S., Silvestri B., Roccotelli M., A review of last mile logistics innovations in an externalities cost reduction vision, Sustainability, 10, (2018); Klompmaker J., Janssen N., Bloemsma L., Gehring U., Wijga A., van den Brink C., Lebret E., Brunekreef B., Hoek G., Residential surrounding green, air pollution, traffic noise and self-perceived general health, Environ. Res, 179, (2019); Lu X., Kang J., Zhu P., Cai J., Guo F., Zhang Y., Influence of urban road characteristics on traffic noise, Transp. Res. Part D Transp. Environ, 75, pp. 136-155, (2019); Morillas J., Gozalo G., Gonzalez D., Moraga P., Vilchez-Gomez R., Noise Pollution and Urban Planning, Curr. Pollut. Rep, 4, pp. 208-219, (2018); Sanchez M., Lopez-Mosquera N., Lera-Lopez F., Faulin J., An Extended Planned Behavior Model to Explain the Willingness to Pay to Reduce Noise Pollution in Road Transportation, J. Clean. Prod, 177, pp. 144-154, (2018); Demir E., Huang Y., Scholts S., Van Woensel T., A selected review on the negative externalities of the freight transportation: Modeling and pricing, Transp. Res. Part E Logist. Transp. Rev, 77, pp. 95-114, (2015); Pathak D., Thakur L., Rahman S., Performance evaluation framework for sustainable freight transportation systems, Int. J. Prod. Res, 57, pp. 6202-6222, (2019); Reyes-Rubiano L., Faulin J., Calvet L., Juan A., A simheuristic approach for freight transportation in smart cities, Proceedings of the 2017 Winter Simulation Conference (WSC), pp. 3346-3357, (2017); Boschmann E., Kwan M.P., Toward socially sustainable urban transportation: Progress and potentials, Int. J. Sustain. 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Res, 77, pp. 95-114, (2020); Saaty T., How to make a decision: The analytic hierarchy process, Interfaces, 24, pp. 19-43, (1994); Alvarez P., Serrano-Hernandez A., Faulin J., Juan A., Using Modelling Techniques to Analyze Urban Freight Distribution. A Case Study in Pamplona (Spain), Transp. Res. Procedia, 33, pp. 37-74, (2018); Juan A., Mendez C., Faulin J., De Armas J., Grasman S., Electric vehicles in logistics and transportation: A survey on emerging environmental, strategic, and operational challenges, Energies, 9, (2016); Figliozzi M.A., Carbon emissions reductions in last mile and grocery deliveries utilizing air and ground autonomous vehicles, Transp. Res. Part D Transp. Environ, 85, (2020); Reyes-Rubiano L., Voegl J., Rest K.D., Faulin J., Hirsch P., Exploration of a disrupted road network after a disaster with an online routing algorithm, OR Spectr, 43, pp. 289-326, (2021); Macrina G., Pugliese L.D.P., Guerriero F., Laporte G., Drone-aided routing: A literature review, Transp. Res. Part C Emerg. Technol, 120, (2020); Lemardele C., Estrada M., Pages L., Bachofner M., Potentialities of drones and ground autonomous delivery devices for last-mile logistics, Transp. Res. Part E Logist. Transp. Rev, 149, (2021); Aurambout J.P., Gkoumas K., Ciuffo B., Last mile delivery by drones: An estimation of viable market potential and access to citizens across European cities, Eur. Transp. Res. Rev, 11, (2019)","A. Serrano-Hernandez; Department of Statistics, Computer Science, and Mathematics, Institute of Smart Cities, Public University of Navarre, Pamplona, 31006, Spain; email: adrian.serrano@unavarra.es",null,"MDPI AG",{"$nulls":5},1.9961073E7,null,null,null,"English","Energies","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85112066881"]
["Cals B.; Zhang Y.; Dijkman R.; van Dorst C.","Cals, Bram (57219692276); Zhang, Yingqian (57189904037); Dijkman, Remco (36794162100); van Dorst, Claudy (57219686557)","57219692276; 57189904037; 36794162100; 57219686557","Solving the online batching problem using deep reinforcement learning",2021.0,"Computers and Industrial Engineering",156.0,null,107221.0,null,null,null,7.0,"10.1016/j.cie.2021.107221","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85103798816&doi=10.1016%2fj.cie.2021.107221&partnerID=40&md5=4ec63c1c0733975fc77c668ff1bd007a","Eindhoven University of Technology, School of Industrial Engineering, P.O. Box 513, MB Eindhoven, 5600, Netherlands; Vanderlande Industries B.V., P.O. Box 18, AA Veghel, 5460, Netherlands","Cals B., Eindhoven University of Technology, School of Industrial Engineering, P.O. Box 513, MB Eindhoven, 5600, Netherlands; Zhang Y., Eindhoven University of Technology, School of Industrial Engineering, P.O. Box 513, MB Eindhoven, 5600, Netherlands; Dijkman R., Eindhoven University of Technology, School of Industrial Engineering, P.O. Box 513, MB Eindhoven, 5600, Netherlands; van Dorst C., Vanderlande Industries B.V., P.O. Box 18, AA Veghel, 5460, Netherlands","In e-commerce markets, on-time delivery is of great importance to customer satisfaction. In this paper, we present a Deep Reinforcement Learning (DRL) approach, together with a heuristic, for deciding how and when arrived orders should be batched and picked in a warehouse to minimize the number of tardy orders. In particular, the technique facilitates making decisions on whether an order should be picked individually (pick-by-order) or picked in a batch with other orders (pick-by-batch), and if so, with which other orders. We approach the problem by formulating it as a semi-Markov decision process and developing a vector-based state representation that includes the characteristics of the warehouse system. This allows us to create a deep reinforcement learning solution that learns a strategy by interacting with the environment and solve the problem with a proximal policy optimization algorithm. We evaluate the performance of the proposed DRL approach by comparing it with several batching and sequencing heuristics in different problem settings. The results show that the DRL approach can develop a strategy that produces consistent, good solutions and performs better than the proposed heuristics in most of the tested cases. We show that the strategy learned by DRL is different from the hand-crafted heuristics. In this paper, we demonstrate that the benefits from recent advancements of Deep Reinforcement Learning can be transferred to solve sequential decision-making problems in warehousing operations. © 2021 The Author(s)","Deep reinforcement learning; E-commerce; Machine learning; Order batching; Sequential decision making; Warehousing","Behavioral research; Customer satisfaction; Deep learning; E-learning; Electronic commerce; Learning algorithms; Markov processes; Reinforcement learning; Warehouses; Batching problem; Customers' satisfaction; E- commerces; Machine-learning; On-time delivery; Order batching; Reinforcement learning approach; Reinforcement learnings; Sequential decision making; Warehousing; Decision making",{"$nulls":6},"Ardjmand E., Shakeri H., Singh M., Bajgiran O.S., Minimizing order picking makespan with multiple pickers in a wave picking warehouse, International Journal of Production Economics, 206, pp. 169-183, (2018); Azadeh K., (2017); Bartholdi J., Hackman S., (2014); Bello I., Pham H., Le Q.V., Norouzi M., Bengio S., (2017); Boysen N., de Koster R., Weidinger F., Warehousing in the e-commerce era: A survey, European Journal of Operational Research, 277, pp. 396-411, (2019); Bustillo M., Menendez B., Pardo E.G., Duarte A., An algorithm for batching, sequencing and picking operations in a warehouse, 2015 International Conference on Industrial Engineering and Systems Management (IESM), pp. 842-849, (2015); Cergibozan C., Tasan A.S., Order batching operations: an overview of classification, solution techniques, and future research, Journal of Intelligent Manufacturing, 30, pp. 335-349, (2019); Chen F., Wei Y., Wang H., A heuristic based batching and assigning method for online customer orders, Flexible Services and Manufacturing Journal, 30, pp. 640-685, (2018); Chen M.C., Wu H.-P., An association-based clustering approach to order batching considering customer demand patterns, Omega, 33, pp. 333-343, (2005); (2020); De Koster D., Le-Duc T., Roodbergen K.J., Design and control of warehouse order picking: A literature review, European Journal of Operational Research, 182, pp. 481-501, (2007); Elsayed E.A., Order sequencing in automated storage/retrieval systems with due dates, Part of the Progress in Material Handling and Logistics, 2, pp. 245-267, (1991); Elsayed E.A., Lee M.-K., Order processing in automated storage/retrieval systems with due dates, IIE Transactions, 28, pp. 567-577, (1996); Elsayed E.A., Lee M.-K., Kim S., Scherer E., Sequencing and batching procedures for minimizing earliness and tardiness penalty of order retrievals, The International Journal of Production Research, 31, pp. 727-738, (1993); Gademann N., Velde S., Order batching to minimize total travel time in a parallel-aisle warehouse, IIE Transactions, 37, pp. 63-75, (2005); Gijsbrechts J., Boute R.N., Van Mieghem J.A., Zhang D., Can deep reinforcement learning improve inventory management? Performance and implementation of dual sourcing-mode problems, SSRN Electronic Journal, (2018); Gil-Borras S., Pardo E.G., Alonso-Ayuso A., Duarte A., Et al., Grasp with variable neighborhood descent for the online order batching problem, Journal of Global Optimization, pp. 1-31, (2020); van Gils T., Caris A., Ramaekers K., Braekers K., Formulating and solving the integrated batching, routing, and picker scheduling problem in a real-life spare parts warehouse, European Journal of Operational Research, 277, pp. 814-830, (2019); Grosse E.H., Glock C.H., Jaber M.Y., Neumann W.P., Incorporating human factors in order picking planning models: Framework and research opportunities, International Journal of Production Research, 53, pp. 695-717, (2015); Henn S., Algorithms for on-line order batching in an order picking warehouse, Computers & Operations Research, 39, pp. 2549-2563, (2012); Henn S., Order batching and sequencing for the minimization of the total tardiness in picker-to-part warehouses, Flexible Services and Manufacturing Journal, 27, pp. 86-114, (2015); Henn S., Schmid V., Metaheuristics for order batching and sequencing in manual order picking systems, Computers & Industrial Engineering, 66, pp. 338-351, (2013); Heuillet A., Couthouis F., (2020); Hutter F., Kotthoff L., Vanschoren J., Automated machine learning: methods, systems, challenges, (2019); Kingma D.P., Ba J., (2014); Kool W., (2018); Lee M.-K., Kim S.-Y., Scheduling of storage/retrieval orders under a just-in-time environment, International Journal of Production Research, 33, pp. 3331-3348, (1995); Li, Huang R., Dai J.B., Joint optimisation of order batching and picker routing in the online retailer's warehouse in china, International Journal of Production Research, 55, pp. 447-461, (2017); Menendez B., Bustillo M., Pardo E.G., Duarte A., General variable neighborhood search for the order batching and sequencing problem, European Journal of Operational Research, 263, pp. 82-93, (2017); Mnih V., Badia A.P., Mirza M., Graves A., Lillicrap T., Harley T., Silver D., Kavukcuoglu K., Asynchronous methods for deep reinforcement learning, International conference on machine learning, pp. 1928-1937, (2016); Mnih V., Kavukcuoglu K., Silver D., Graves A., Antonoglou I., Wierstra D., Riedmiller M., (2013); Mnih V., Kavukcuoglu K., Silver D., Rusu A.A., Veness J., Bellemare M.G., Graves A., Riedmiller M., Fidjeland A.K., Ostrovski G., Et al., Human-level control through deep reinforcement learning, Nature, 518, (2015); Oroojlooyjadid A., Nazari M., Snyder L., (2017); Peer E., Menkovski V., Zhang Y., (2018); Petersen C.G., An evaluation of order picking routeing policies, International Journal of Operations & Production Management, 17, pp. 1098-1111, (1997); Petersen C.G., Schmenner R.W., An evaluation of routing and volume-based storage policies in an order picking operation, Decision Sciences, 30, pp. 481-501, (1999); Refaei Afshar R., Zhang Y., Firat M., Kaymak U., A state aggregation approach for solving knapsack problem with deep reinforcement learning, pp. 81-96, (2020); Rummukainen H., Nurminen J.K., Practical reinforcement learning-experiences in lot scheduling application, IFAC-PapersOnLine, 52, pp. 1415-1420, (2019); Samek W., Binder A., Montavon G., Lapuschkin S., Muller K.-R., Evaluating the visualization of what a deep neural network has learned, IEEE Transactions on Neural Networks and Learning Systems, 28, pp. 2660-2673, (2016); Scholz A., Schubert D., Wascher G., Order picking with multiple pickers and due dates–simultaneous solution of order batching, batch assignment and sequencing, and picker routing problems, European Journal of Operational Research, 263, pp. 461-478, (2017); Schulman J., Wolski F., Dhariwal P., Radford A., Klimov O., (2017); Sutton R.S., Barto A.G., Et al., Introduction to reinforcement learning, 135, (1998); Tsai C.-Y., Liou J.J., Huang T.-M., Using a multiple-ga method to solve the batch picking problem: considering travel distance and order due time, International Journal of Production Research, 46, pp. 6533-6555, (2008); Valle C.A., Beasley J.E., da Cunha A.S., Optimally solving the joint order batching and picker routing problem, European Journal of Operational Research, 262, pp. 817-834, (2017); Waschneck B., Reichstaller A., Belzner L., Altenmuller T., Bauernhansl T., Knapp A., Kyek A., Deep reinforcement learning for semiconductor production scheduling, 2018 29th Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC), pp. 301-306, (2018); Zhang Z., Zheng L., Li N., Wang W., Zhong S., Hu K., Minimizing mean weighted tardiness in unrelated parallel machine scheduling with reinforcement learning, Computers & Operations Research, 39, pp. 1315-1324, (2012)","Y. Zhang; Eindhoven University of Technology, School of Industrial Engineering, MB Eindhoven, P.O. Box 513, 5600, Netherlands; email: yqzhang@tue.nl",null,"Elsevier Ltd",{"$nulls":5},3608352.0,null,"CINDD",null,"English","Comput Ind Eng","Article","Final","All Open Access; Green Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85103798816"]
["Abhishek; Legros B.; Fransoo J.C.","Abhishek (57298309000); Legros, Benjamin (55819341000); Fransoo, Jan C. (6602253532)","57298309000; 55819341000; 6602253532","Performance Evaluation of Stochastic Systems with Dedicated Delivery Bays and General On-Street Parking",2021.0,"Transportation Science",55.0,5.0,null,1070.0,1087.0,17.0,5.0,"10.1287/TRSC.2021.1065","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85117178611&doi=10.1287%2fTRSC.2021.1065&partnerID=40&md5=b2decde192e781b043383147537d7617","Department of Logistics, Kuehne Logistics University, Hamburg, 20457, Germany; Laboratoire Métis, EM Normandie, Paris, 75016, France; Tilburg School of Economics and Management, Tilburg University, Tilburg, 5000 LE, Netherlands","Abhishek, Department of Logistics, Kuehne Logistics University, Hamburg, 20457, Germany; Legros B., Laboratoire Métis, EM Normandie, Paris, 75016, France; Fransoo J.C., Tilburg School of Economics and Management, Tilburg University, Tilburg, 5000 LE, Netherlands","As freight deliveries in cities increase due to retail fragmentation and e-commerce, parking is becoming a more and more relevant part of transportation. In fact, many freight vehicles in cities spend more time parked than they are moving. Moreover, part of the public parking space is shared with passenger vehicles, especially cars. Both arrival processes and parking and delivery processes are stochastic in nature. In order to develop a framework for analysis, we propose a queueing model for an urban parking system consisting of delivery bays and general on-street parking spaces. Freight vehicles may park both in the dedicated bays and in general on-street parking, whereas passenger vehicles only make use of general on-street parking. Our model allows us to create parsimonious insights into the behavior of a delivery bay parking stretch as part of a limited length of curbside. We are able to find explicit expressions for the relevant performance measures, and formally prove a number of monotonicity results. We further conduct a series of numerical experiments to show more intricate properties that cannot be shown analytically. The model helps us shed light onto the effects of allocating scarce urban curb space to dedicated unloading bays at the expense of general on-street parking. In particular, we show that allocating more space to dedicated delivery bays can also make passenger cars better off. © 2021 INFORMS Inst.for Operations Res.and the Management Sciences. All rights reserved.","Bay parking; Loss system; Parking system; Street parking; Urban logistics","Automobiles; Freight transportation; Queueing theory; Sales; Unloading; Bay parking; Freight vehicle; Loss system; On-street parking; Parking spaces; Parking systems; Passengers vehicles; Performances evaluation; Street parking; Urban logistics; Stochastic systems",{"$nulls":6},"Bassamboo A, Harrison JM, Zeevi A, Design and control of a large call center: Asymptotic analysis of an LP-based method, Oper. Res, 54, 3, pp. 419-435, (2006); Bhulai S, Brooms AC, Spieksma FM, On structural properties of the value function for an unbounded jump Markov process with an application to a processor sharing retrial queue, Queueing Systems, 76, 4, pp. 425-446, (2014); Caliskan M, Barthels A, Scheuermann B, Mauve M, Predicting parking lot occupancy in vehicular ad hoc networks, Proc. IEEE 65th Vehicular Tech. Conf, pp. 277-281, (2007); Cassady CR, Kobza JE, A probabilistic approach to evaluate strategies for selecting a parking space, Transportation Sci, 32, 1, pp. 30-42, (1998); Crainic TG, Ricciardi N, Storchi G, Models for evaluating and planning city logistics systems, Transportation Sci, 43, 4, pp. 432-454, (2009); Daley D, Queueing output processes, Adv. Appl. Probab, 8, 2, pp. 395-415, (1976); Dalla Chiara G, Cheah L, Data stories from urban loading bays, Eur. Transport Res. Rev, 9, 4, (2017); Dalla Chiara G, Goodchild A, Do commercial vehicles cruise for parking? 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Board 95th Annual Meeting Compendium of Papers, (2016); Goodchild A, Ivanov B, The final 50 feet of the urban goods delivery system, (2017); Green L, Kolesar P, The pointwise stationary approximation for queues with nonstationary arrivals, Management Sci, 37, 1, pp. 84-97, (1991); Gurvich I, Perry O, Overflow networks: Approximations and implications to call center outsourcing, Oper. Res, 60, 4, pp. 996-1009, (2012); Hauer E, Templeton JGC, Queuing in lanes, Transportation Sci, 6, 3, pp. 247-259, (1972); Jaller M, Holguin-Veras J, Hodge SD, Parking in the city: Challenges for freight traffic, Transportation Res. Rec, 2379, 1, pp. 46-56, (2013); Jennings O, Mandelbaum A, Massey W, Whitt W, Server staffing to meet time-varying demand, Management Sci, 42, 10, pp. 1383-1394, (1996); Kladeftiras M, Antoniou C, Simulation-based assessment of double-parking impacts on traffic and environmental conditions, Transportation Res. 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Part A: Policy Practice, 64, pp. 54-64, (2014); Puterman ML, Markov Decision Processes: Discrete Stochastic Dynamic Programming, (2014); Ross SM, Introduction to Probability Models, (2014); Savelsbergh M, Van Woensel T, 50th anniversary invited article—City logistics: Challenges and opportunities, Transportation Sci, 50, 2, pp. 579-590, (2016); Shoup DC, Cruising for parking, Transport Policy, 13, 6, pp. 479-486, (2006); Smirnov N, Table for estimating the goodness of fit of empirical distributions, Ann. Math. Statist, 19, 2, pp. 279-281, (1948); Takacs L, On the limiting distribution of the number of coincidences concerning telephone traffic, Ann. Math. Statist, 30, 1, pp. 134-142, (1959); Taniguchi E, Thompson RG, City Logistics 1: New Opportunities and Challenges, (2018); Vieira JGV, Fransoo JC, How logistics performance of freight operators is affected by urban freight distribution issues, Transport Policy, 44, pp. 37-47, (2015); Ward A, Kumar S, Asymptotically optimal admission control of a queue with impatient customers, Math. Oper. Res, 33, 1, pp. 167-202, (2008); Wigan MR, Broughton J, Descriptive models of parking to complement transport planning studies, Transportation Res. Part A: General, 14, 3, pp. 159-171, (1980); Xiao J, Lou Y, Frisby J, How likely am I to find parking? A practical model-based framework for predicting parking availability, Transportation Res. Part B: Methodological, 112, pp. 19-39, (2018); Xu K, Necessity of future information in admission control, Oper. Res, 63, 5, pp. 1213-1226, (2015)","Abhishek; Department of Logistics, Kuehne Logistics University, Hamburg, 20457, Germany; email: abhishek.abhishek@the-klu.org; B. Legros; Laboratoire Métis, EM Normandie, Paris, 75016, France; email: blegros@em-normandie.fr; J.C. Fransoo; Tilburg School of Economics and Management, Tilburg University, Tilburg, 5000 LE, Netherlands; email: jan.fransoo@tilburguniversity.edu",null,"INFORMS Inst.for Operations Res.and the Management Sciences",{"$nulls":5},411655.0,null,"TRSCB",null,"English","Transp Sci","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85117178611"]
["Suguna M.; Shah B.; Raj S.K.; Suresh M.","Suguna, M. (57200289073); Shah, Bhavin (57209161080); Raj, S. Karthik (57224598577); Suresh, M. (56684483100)","57200289073; 57209161080; 57224598577; 56684483100","A study on the influential factors of the last mile delivery projects during Covid-19 era",2021.0,"Operations Management Research",{"$nulls":6},29.0,"10.1007/s12063-021-00214-y","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85114817903&doi=10.1007%2fs12063-021-00214-y&partnerID=40&md5=56d4ebbaf01cbb995342244d63711a6c","Department of Information Science and Engineering, Kumaraguru College of Technology, Coimbatore, India; Indian Institute of Management, Sirmaur, India; Amrita School of Business, Amrita Vishwa Vidyapeetham, Coimbatore, India","Suguna M., Department of Information Science and Engineering, Kumaraguru College of Technology, Coimbatore, India; Shah B., Indian Institute of Management, Sirmaur, India; Raj S.K., Amrita School of Business, Amrita Vishwa Vidyapeetham, Coimbatore, India; Suresh M., Amrita School of Business, Amrita Vishwa Vidyapeetham, Coimbatore, India","The Covid-19 has shifted the face of many markets including e-commerce and online business with many bottlenecks to be cleared. The last-mile delivery project has the greatest effect on all types of e-commerce companies because it has many consumer touchpoints as well as the Covid-19 pain points. Due to these interconnected issues, the delivery projects itself requires modern solutions. The purpose of this paper is to identify, analyse and categorize the major factors that affect the last mile delivery projects in e-commerce, food sector, retail sector and so on using total ınterpretive structural modelling approach during the Covid-19. Ten major factors are identified from literature review, and expert opinions are collected from multiple organizations that are involved in the last mile delivery projects. The results indicate that types of goods, achieving routing efficiency and meeting fulfilment timeline are the key factors for last mile delivery projects during the time of Covid-19. This study helps the managers to identify the key factors and to focus on these factors for the successful implementation of last mile delivery project. © 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.","Covid-19 influence; Delivery projects; Distribution projects; Last mile delivery; Logistics; Project success factors; Total interpretive structural modelling (TISM)",{"$nulls":7},"Agarwal N., Seth N., Analysis of supply chain resilience barriers in Indian automotive company using total interpretive structural modelling, J Adv Manage Res, (2021); Ayers J.B., Supply chain project management: a structured collaborative and measurable approach, (2003); Bag S., Green strategy, supplier relationship building and supply chain performance: total interpretive structural modelling approach, IJPM, 9, 4, pp. 398-426, (2016); Ballare S., Lin J., Investigating the use of microhubs and crowdshipping for last mile delivery, Trans Res Procedia, 46, pp. 277-284, (2020); Bauer R., Hoster B., Nadel M., Rose J., Rutledge K., Williams H., Differentiating with Last-Mile Delivery., (2020); Bopage G., Nanayakkara J., Vidanagamachchi K., A strategic model to improve the last mile delivery performance in e-commerce parcel delivery, Proceedings of the International Conference on Industrial Engineering and Operations Management, 2019, (2019); Bushuyev S., Bushuiev D., Bushuieva V., Project management during Infodemic of the COVID-19 pandemic, Innov Technol Sci Sol Ind, 2, 12, pp. 13-21, (2020); Chaudhary H., Analyzing the paradigm shift of consumer behavior towards e-Commerce during pandemic lockdown, SSRN J, (2020); Corbin J.M., Strauss A., Grounded theory research: procedures, canons, and evaluative criteria, Qual Sociol, 13, 1, pp. 3-21, (1990); Dell'Amico M., Hadjidimitriou S., Innovative logistics model and containers solution for efficient last mile delivery, Procedia Soc Behav Sci, 48, pp. 1505-1514, (2012); Deloison T., Hannon E., Huber A., Heid B., Klink C., Sahay R., Christoph Wolff C., The future of the last-mile ecosystem, World Economic Forum., (2020); Dubey R., Gunasekaran A., Sushil, Singh T., Building theory of sustainable manufacturing using total interpretive structural modelling, Int J Syst Sci, 2, 4, pp. 231-247, (2015); Dubey R., Gunasekaran A., Papadopoulos T., Green supply chain management: theoretical framework and further research directions, BIJ, 24, 1, pp. 184-218, (2017); Galkin A., Obolentseva L., Balandina I., Kush E., Karpenko V., Bajdor P., Last-mile delivery for consumer driven logistics, Trans Res Procedia, 39, pp. 74-83, (2019); Gevaers R., van De Voorde E., Vanelslander T., Characteristics and typology of last-mile logistics from an innovation perspective in an urban context, City Distribution and Urban Freight Transport. 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Macioszek E., First and last mile delivery–problems and issues, Scientific and technical conference transport systems theory and practice, pp. 147-154, (2017); Mangiaracina R., Perego A., Seghezzi A., Tumino A., Innovative solutions to increase last-mile delivery efficiency in B2C e-commerce: a literature review, Int J Phys Distrib Logist Manag, 49, 9, pp. 901-920, (2019); Market Study Report, (2021); Mathivathanan D., Mathiyazhagan K., Rana N.P., Khorana S., Dwivedi Y.K., Barriers to the adoption of blockchain technology in business supply chains: a total interpretive structural modelling (TISM) approach, Int J Prod Res, 59, 11, pp. 3338-3359, (2021); Menon S., Suresh M., Total interpretive structural modelling: evolution and applications, International conference on innovative data communication technologies and application, pp. 257-265, (2019); Menon S., Suresh M., Factors influencing organizational agility in higher education, BIJ, 28, 1, pp. 307-332, (2021); Menon S., Suresh M., Enablers of workforce agility in engineering educational institutions, J Appl Res High Educ, 13, 2, pp. 504-539, (2021); 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Yu Z., Rehman Khan S.A., Evolutionary game analysis of green agricultural product supply chain financing system: COVID-19 pandemic, Int J Log Res Appl, (2021)","B. Shah; Indian Institute of Management, Sirmaur, India; email: bhavin.shah@iimsirmaur.ac.in",null,"Springer",{"$nulls":5},1.9369735E7,null,null,null,"English","Oper. Manage. Res.","Article","Article in press","All Open Access; Bronze Open Access","Scopus","2-s2.0-85114817903"]
["Chen C.-L.; Deng Y.-Y.; Weng W.; Zhou M.; Sun H.","Chen, Chin-Ling (57214694244); Deng, Yong-Yuan (25932019800); Weng, Wei (36640955900); Zhou, Ming (57218297764); Sun, Hongyu (55729312000)","57214694244; 25932019800; 36640955900; 57218297764; 55729312000","A blockchain-based intelligent anti-switch package in tracing logistics system",2021.0,"Journal of Supercomputing",77.0,7.0,null,7791.0,7832.0,41.0,28.0,"10.1007/s11227-020-03558-7","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85099217428&doi=10.1007%2fs11227-020-03558-7&partnerID=40&md5=34708e9805165d95143e69bdd3561b1f","School of Computer and Information Engineering, Xiamen University of Technology, Xiamen, 361024, China; School of Information Engineering, Changchun Sci-Tech University, Changchun, 130600, Jilin, China; Department of Computer Science and Information Engineering, Chaoyang University of Technology, Taichung, 41349, Taiwan; Department of Computer Science, Jilin Normal University, Changchun, China","Chen C.-L., School of Computer and Information Engineering, Xiamen University of Technology, Xiamen, 361024, China, School of Information Engineering, Changchun Sci-Tech University, Changchun, 130600, Jilin, China, Department of Computer Science and Information Engineering, Chaoyang University of Technology, Taichung, 41349, Taiwan; Deng Y.-Y., Department of Computer Science and Information Engineering, Chaoyang University of Technology, Taichung, 41349, Taiwan; Weng W., School of Computer and Information Engineering, Xiamen University of Technology, Xiamen, 361024, China; Zhou M., School of Computer and Information Engineering, Xiamen University of Technology, Xiamen, 361024, China; Sun H., Department of Computer Science, Jilin Normal University, Changchun, China","In recent years, with the rapid development of e-commerce and network technologies, many people do online shopping through the Internet. If a physical product is bought by a client, the store will entrust their logistics to deliver the goods to the client. However, there have been many cases of switched goods which were purchased by clients recently. Some scholars proposed a security mechanism with a subliminal channel for E-cash and digital content previously. Only the designated sender and the designated receiver know the subliminal message which was hidden in the signature. Thus, it can be applied to solve the switched package issue. According to the WTO (World Trade Organization) forum, blockchain-related logistics applications have gradually emerged in recent days. Blockchain technology is essentially a decentralized database maintained by the collective. It has the characteristics of high reliability and high confidentiality and has a good prospect in effectively solving the trust problem between the two parties. In short, blockchain information will be publicly verifiable and cannot be tampered with, which provides solutions for traditional logistics. It realizes trust and cooperation between multiple entities, and create a modernized logistics environment. In this paper, we attach a sensor to monitor the situation of the delivery object and tag on the package to be an IoT object. The proposed scheme is a blockchain-based intelligent anti-switch package in tracing the logistics system. The client can check the GPS (Global Positioning System) location, the temperature, and humidity sensing data of the package any time during the delivery process, and the IoT-related intelligent logistics can be achieved. The proposed scheme also achieves data integrity, resisting replay attack, forward and backward secrecy, non-repudiation, and mutual authentication. © 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature.","Anti-switch package; BAN logic; Blockchain; Intelligent logistics; Mutual authentication; Package tracking; Sensor; Subliminal channel","Blockchain; Electronic commerce; Global positioning system; Humidity sensors; International trade; Network security; Decentralized database; Designated receivers; Forward and backward secrecy; Gps (global positioning system); Mutual authentication; Network technologies; Publicly verifiable; World Trade Organizations; Internet of things",{"$nulls":4},"Ministry of Science and Technology of the People's Republic of China, MOST, (108-2221-E-324-013); Ministerio de Ciencia y Tecnología, MICYT","Funding text 1: This study is supported by the Ministry of Science and Technology (MOST), Taiwan, Republic of China, under the Grants of MOST 108-2221-E-324-013. ; Funding text 2: This study is supported by the Ministry of Science and Technology (MOST), Taiwan, Republic of China, under the Grants of MOST 108-2221-E-324-013.","Whitmore A., Agarwal A., Da Xu L., The internet of things: a survey of topics and trends, Inf Syst Front, 17, 2, pp. 261-274, (2015); Ray B.R., Abawajy J., Chowdhury M., Alelaiwi A., Universal and secure object ownership transfer protocol for the Internet of Things, Fut Gener Comput Syst, 78, 2, pp. 838-849, (2018); Liang K., Susilo W., Searchable attribute-based mechanism with efficient data sharing for secure cloud storage, IEEE Trans Inf Forensics Secur, 10, 9, pp. 1981-1992, (2015); Yao X., Chen Z., Tian Y., A lightweight attribute-based encryption scheme for the internet of things, Fut Gener Comput Syst, 49, pp. 104-112, (2015); Han J., Susilo W., Mu Y., Improving privacy and security in decentralized ciphertext-policy attribute-based encryption, IEEE Trans Inf Forensics Secur, 10, pp. 665-678, (2015); Zhao S., Aggarwal A., Frost R., Bai X., A survey of applications of identity-based cryptography in mobile ad-hoc networks, IEEE Commun Surv Tutor, 14, 2, pp. 380-400, (2012); 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Banerjee S., Odelu V., Das A.K., Srinivas J., Kumar N., Chattopadhyay S., Choo K.K.R., A provably secure and lightweight anonymous user authenticated session key exchange scheme for the Internet of Things deployment, IEEE Internet Things J, 6, 5, pp. 8739-8752, (2019); Shuai M., Yu N., Wang H., Xiong L., Anonymous authentication scheme for smart home environment with provable security, Comput Secur, 86, pp. 132-146, (2019); Islam S.H., Vijayakumar P., Bhuiyan M.Z.A., Amin R., Balusamy B., A provably secure three-factor session initiation protocol for multimedia big data communications, IEEE Internet Things J, 5, 5, pp. 3408-3418, (2017); Global Trade and Blockchain Forum, (2020); Who Will Win the Race to Blockchain Supply Chain Supremacy?; Simplicio M.A., Silva M.V.M., Alves R.C.A., Shibata T.K.C., Lightweight and escrow-less authenticated key agreement for the Internet of Things, Comput Commun, 98, pp. 43-51, (2017); Simplicio M., Oliveira B., Barreto P., Margi C., Carvalho T., Naslund M., Comparison of authenticated-encryption schemes in wireless sensor networks, Proceedings of the 36Th IEEE Conference on Local Computer Networks (LCN), 2011, pp. 454-461, (2011); 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Simmons G.J., Subliminal communication is easy using the DSA, Proceedings of Eurocrypt’93, pp. 218-232, (1993); Simmons G.J., The history of subliminal channels, IEEE J Sel Areas Commun, 16, pp. 452-462, (1998); Chang S.E., Chen Y.C., Lu M.F., Supply chain re-engineering using blockchain technology: a case of smart contract based tracking process, Technol Forecast Soc Change, 144, pp. 1-11, (2019); Li C.T., Wu T.Y., Chen C.L., Lee C.C., Chen C.M., An efficient user authentication and user anonymity scheme with provably security for IoT-based medical care system, Sensors, (2017); Das A.K., Goswami A., A robust anonymous biometric-based remote user authentication scheme using smart cards, J King Saud Univ Comput Inf Sci, 27, pp. 193-210, (2015); Speranza M.G., Trends in transportation and logistics, Eur J Oper Res, 264, pp. 830-836, (2018); Odelu V., Das A.K., Goswami A., An efficient ECC-based privacy-preserving client authentication protocol with key agreement using smart card, J Inf Secur Appl, 21, pp. 1-19, (2015); 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Weng; School of Computer and Information Engineering, Xiamen University of Technology, Xiamen, 361024, China; email: wwweng@xmut.edu.cn; M. Zhou; School of Computer and Information Engineering, Xiamen University of Technology, Xiamen, 361024, China; email: mzhou@xmut.edu.cn; Y.-Y. Deng; Department of Computer Science and Information Engineering, Chaoyang University of Technology, Taichung, 41349, Taiwan; email: allen.nubi@gmail.com",null,"Springer",{"$nulls":5},9208542.0,null,"JOSUE",null,"English","J Supercomput","Article","Final",null,"Scopus","2-s2.0-85099217428"]
["Wang C.-N.; Nguyen N.-A.-T.; Dang T.-T.; Lu C.-M.","Wang, Chia-Nan (57757351100); Nguyen, Ngoc-Ai-Thy (57218570813); Dang, Thanh-Tuan (57218565464); Lu, Chen-Ming (57223038928)","57757351100; 57218570813; 57218565464; 57223038928","A compromised decision-making approach to third-party logistics selection in sustainable supply chain using fuzzy ahp and fuzzy vikor methods",2021.0,"Mathematics",9.0,8.0,886.0,null,null,null,81.0,"10.3390/math9080886","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85104659804&doi=10.3390%2fmath9080886&partnerID=40&md5=e6d911a8459e41a88523addf65a4f124","Department of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung, 80778, Taiwan; Department of Logistics and Supply Chain Management, Hong Bang International University, Ho Chi Minh, 723000, Viet Nam; Shanghai Jiao Tong University, Shanghai, 200081, China","Wang C.-N., Department of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung, 80778, Taiwan; Nguyen N.-A.-T., Department of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung, 80778, Taiwan; Dang T.-T., Department of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung, 80778, Taiwan, Department of Logistics and Supply Chain Management, Hong Bang International University, Ho Chi Minh, 723000, Viet Nam; Lu C.-M., Shanghai Jiao Tong University, Shanghai, 200081, China","With the effects of the COVID-19 pandemic, the e-commerce trend is driving faster, significantly impacting supply chains around the world. Thus, the importance of logistics and supply chain functions has been amplified in almost every business that ships physical goods. In Vietnam, the logistics service sector has seen rapid expansion. Since more and more businesses are seeking third-party logistics (3PL) providers to outsource the logistics functions, this article aims to offer decision-makers an integrated and consistent model for evaluating and selecting the most efficient 3PLs. To this end, the authors exploit a hybrid multi-criteria method which is fuzzy analytic hierarchy process (FAHP) and fuzzy vlsekriterijumska optimizacija i kompromisno resenje (FVIKOR) while examining the most influential and conflicting criteria regarding economic, service level, environmental, social, and risk aspects. Fuzzy information in the natural decision-making process is considered, linguistic variables are used to mitigate the uncertain levels in the criteria weights. First, FAHP (the weighting method) is adopted to evaluate and calculate each criterion’s relative significant fuzzy weight. FVIKOR (the compromised ranking method) is then used to rank the alternatives. The combination of FAHP and FVIKOR methods provides more accurate ranking results. As a result, reliability and delivery time, voice of customer, logistics cost, network management, and quality of service are the most impactful factors to the logistics outsourcing problem. Eventually, the optimized 3PLs were determined that fully meet the criteria of sustainable development. The developed integrated model offers the complete and robust 3PLs evaluation and selection process and can also be a powerful decision support tool for other industries. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.","3PL; Decision-making; FAHP; FVIKOR; Logistics outsourcing; Supply chain; Triangular fuzzy number",{"$nulls":5},"National Kaohsiung University of Science and Technology, (MOST 109-2622-E-992-026); Shanghai Gen‐ eral Hospital; Ministry of Science and Technology of the People's Republic of China, MOST; Ministry of Science and Technology, Taiwan, MOST; National Taiwan University of Science and Technology, NTUST","Funding text 1: This research was partly supported by the National Kaohsiung University of Science and Technology and project number MOST 109-2622-E-992-026 from the Ministry of Sciences and Technology in Taiwan.; Funding text 2: Acknowledgments: The authors appreciate the support from the National Kaohsiung University of Science and Technology, Taiwan; Ministry of Sciences and Technology; Taiwan; and Shanghai Gen‐ eral Hospital, China.","Pamucar D., Chatterjee K., Zavadskas E.K., Assessment of third-party logistics provider using multi-criteria decision-making approach based on interval rough numbers, Comput. 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Model, 54, pp. 2802-2815, (2011); Shekhovtsov A., Kozlov V., Nosov V., Salabun W., Efficiency of Methods for Determining the Relevance of Criteria in Sustainable Transport Problems: A Comparative Case Study, Sustainability, 12, (2020); Wang C.-N., Dang T.-T., Tibo H., Duong D.-H., Assessing Renewable Energy Production Capabilities Using DEA Window and Fuzzy TOPSIS Model, Symmetry, 13, (2021); Salabun W., Urbaniak K., A new coefficient of rankings similarity in decision-making problems, International Conference on Computational Science, pp. 632-645, (2020)","N.-A.-T. Nguyen; Department of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung, 80778, Taiwan; email: i109143106@nkust.edu.tw; T.-T. Dang; Department of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung, 80778, Taiwan; email: i108143106@nkust.edu.tw; C.-M. Lu; Shanghai Jiao Tong University, Shanghai, 200081, China; email: cheng.ml1092@gmail.com",null,"MDPI AG",{"$nulls":5},2.227739E7,null,null,null,"English","Mathematics","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85104659804"]
["Zhuansun F.; Chen J.; Chen W.; Sun Y.","Zhuansun, Fengqin (57402235700); Chen, Jiaojiao (57402523600); Chen, Wenlong (57402235800); Sun, Yan (57401954400)","57402235700; 57402523600; 57402235800; 57401954400","The Mechanism of Evolution and Balance for e-Commerce Ecosystem under Blockchain",2021.0,"Scientific Programming",2021.0,null,5984306.0,null,null,null,6.0,"10.1155/2021/5984306","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85122355049&doi=10.1155%2f2021%2f5984306&partnerID=40&md5=4284412a525a8b16cc759c527c5cdd4e","School of Management, Wuxi Institute of Technology, Wuxi, 214000, China","Zhuansun F., School of Management, Wuxi Institute of Technology, Wuxi, 214000, China; Chen J., School of Management, Wuxi Institute of Technology, Wuxi, 214000, China; Chen W., School of Management, Wuxi Institute of Technology, Wuxi, 214000, China; Sun Y., School of Management, Wuxi Institute of Technology, Wuxi, 214000, China","With the development of society, e-commerce competition has become increasingly intense and has ascended to the level of the ecosystem. Therefore, it is extremely significant to study the mechanism of evolution and balance for the e-commerce ecosystem. Simultaneously, blockchain technology is essentially a consensus mechanism, the core idea of which is decentralization, but it is actually the deconstruction of privileges and authority. Especially, the influence on the e-commerce ecosystem cannot be underestimated. Blockchain technology ultimately changes not only technology, but a comprehensive reconstruction of various industries. Building an e-commerce information ecosystem based on blockchain can promote the healthy and sustainable development of e-commerce information ecology. This work combines the definition and technical characteristics of blockchain, discusses the blockchain-based e-commerce information ecosystem model, and discusses how to achieve the ecological balance and system evolution of e-commerce under the background of blockchain. According to the internal problems of the e-commerce ecosystem, three evolutionary paths are proposed in this work. First, consider the timeliness of the information and construct a full-process information channel. Second, remove central nodes and build a safe and efficient block payment. Third, solve the blind zone in the field of logistics and create efficient and transparent intelligent logistics. This work can provide an effective reference for the development of e-commerce. © 2021 Fengqin ZhuanSun et al.",null,"Blockchain; Ecosystems; Block-chain; Decentralisation; E- commerces; E-commerce ecosystems; Ecological balance; Ecological systems; Ecosystem model; Information ecology; Information ecosystems; System evolution; Electronic commerce",{"$nulls":6},"Zheng S., Lv Q., The evolution of E-commerce in twenty years in China, Journal of Business Economics, 11, 265, pp. 5-16, (2013); Piggott S., Internet commerce and knowledge management-the next megatrends, Business Information Review, 14, 4, pp. 169-172, (1997); Levikangas P., Rni R., From business models to value networks and business ecosystems-what does it mean for the economics and governance of the transport system?, Utilities Policy, 64, (2020); Meyer M., Utterback J., James M., The product family and the dynamics of core capability, MIT Sloan Management Review, 34, pp. 77-92, (1992); Veenstra V.S., Halman J.I.M., Voordijk J.T., A methodology for developing product platforms in the specific setting of the housebuilding industry, Research in Engineering Design, 17, 3, pp. 157-173, (2006); Pei J., Solving the Problem of Charging and Discharging of Electric Vehicles Based on Particle Swarm Algorithm, pp. 534-538; Liu J., Sun C., Yuan Y., Blockchain hotspot field and frontier path in China: Based on CiteSpace measurement analysis, Journal of Chongqing University of Posts and Telecommunications, 32, 6, pp. 121-129, (2020); Rochet J.-C., Tirole J., Platform competition in two-sided markets, Journal of the European Economic Association, 1, 4, pp. 990-1029, (2003); Muegge S., Business ecosystems as institutions of participation: A systems perspective on community-developed platforms, Technology Innovation Management Review, 27, 4, (2011); Metso L., Kans M., An ecosystem perspective on asset management information, Management Systems in Production Engineering, 25, 3, (2017); Pei J., Big data mining in the control of epidemic, Basic and Clinical Pharmacology and Toxicology, 126, pp. 428-430, (2020); Normann R., Ramirez R., From value chain to value constellation: Designing interactive strategy, Harvard Business Review, 7, 4, pp. 65-77, (1993); Moore J.F., Predators and prey: A new ecology of competition, Harvard Business Review, 71, 3, pp. 75-86, (1993); Sviokla J., Expert Systems and Their Impact on the Firm: The Effects of Planpower Use on the Information-processing Capacity of the Financial Collaborative; Gummesson E., Mele C., Marketing as value Co-creation through network interaction and resource integration, Journal of Business Market Management, 4, 4, pp. 181-198, (2010); Tay N.S.P., Lusch R.F., A preliminary test of hunt's general theory of competition: Using artificial adaptive agents to study complex and ill-defined environments, Journal of Business Research, 58, 9, pp. 1155-1168, (2005); Zhang H., Xu Z., Research on the structure and evolution of cross-border E-commerce ecosystem based on the perspective of symbiosis, Journal of Social Sciences, 19, 928, pp. 44-46, (2020); Pei J., Li J., Zhou B., A Recommendation Algorithm about Choosing Travel Means for Urban Residents in Intelligent Traffic System, pp. 2553-2556; Gawer A., Cusumano M., How Companies Become Platform Leaders, (2008); Mei S., Xu J., Research on collaborative B2B E-business model and value creation, Journal of Management Science in China, 16, 5, pp. 55-68, (2013); Wang X., Research on the Internal Coordination Mechanism of E-Commerce Ecosystem Based on Evolutionary Game, (2019); Zhang Y., Blockchain to lead to new changes in E-commerce, Contemporary Economic Management, 39, 10, (2017); Bilgihan A., Gen Y., Customer loyalty in online shopping: An integrated model of trust, user experience and branding, Computers in Human Behavior, 61, pp. 103-113, (2016); Yu W., Ding Z., Liu L., Wang X., Crossley R.D., Petri net-based methods for analyzing structural security in E-commerce business processes, Future Generation Computer Systems, 109, pp. 611-620, (2020); Min H., Blockchain technology for enhancing supply chain resilience, Business Horizons, 62, 1, pp. 35-45, (2019); Robert J., Kubler S., Ghatpande S., Enhanced lightning network (off-chain)-based micropayment in IoT ecosystems, Future Generation Computer Systems, 112, pp. 283-296, (2020); Angelis J., Ribeiro Da Silva E., Blockchain adoption: A value driver perspective, Business Horizons, 62, 3, pp. 307-314, (2019); Dennis R., Owenson G., Rep on the roll: A peer to peer reputation system based on a rolling blockchain, International Journal of Digital Society, 7, 1, pp. 1123-1134, (2016); Schaub A., Bazin R., Hasan O., Brunie L., A T Privacy-preserving Reputation System, pp. 398-411; Wang S., Research on blockchain of legal tender system, Economist, 9, pp. 77-85, (2016); Zhang B., The application of foreign blockchain technology and related enlightenment, Financial Technology Time, 24, 5, pp. 35-38, (2016); Li Q., Zhang X., Blockchain: A technology to win open and trust in education, The Journal of Distance Education, 35, 1, pp. 36-44, (2017); Zhang N., Wang Y., Kang C., Cheng J., He D., Blockchain technique in the energy Internet: Preliminary research framework and typical applications, Proceedings of the CSEE, 36, 15, pp. 4011-4022, (2016); Dan M., Analysis of blockchain technology's reconstruction of E-commerce ecosystem, Chinese Commerce, 14, pp. 26-27, (2020); Zhang T., Li B., Analysis of the value-added tax collection of E-commerce model under the background of blockchain, Chinese Commerce, 14, pp. 28-29, (2020); Chen Y., Research on Enterprise Credit Information Sharing Model Based on Blockchain Technology, (2019); Liu J., Research on Cooperative Evolution of Cross-Border E-Commerce Ecosystem, (2018); Zhang L., Li Z., Wang J., User perception model of E-business ecosystem, Information Science, 38, 8, (2020); Zhang L., Wang X., Li J., Dynamic evolutionary game of credit mechanism among core populations in E-commerce ecosystem, Operations Research Management Science, 29, 4, pp. 93-101, (2020); Wu T., Zhao Z., Anti-monopoly law on the \"choose one from two\" action of E-commerce platform: On the insufficient application of the theory of abuse of superior bargaining position, Journal of Chongqing University of Posts and Telecommunications, 32, 6, pp. 59-68, (2020); Guo H., Internet enterprise data identification antitrust legal supervision regulation, Journal of Chongqing University of Posts and Telecommunications, 31, 2, pp. 37-46, (2019)","F. Zhuansun; School of Management, Wuxi Institute of Technology, Wuxi, 214000, China; email: zhsfq@wxit.edu.cn",null,"Hindawi Limited",{"$nulls":5},1.0589244E7,null,"SCIPE",null,"English","Sci. Program","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85122355049"]
["Qu Q.; Liu C.; Bao X.","Qu, Qiao (58448612500); Liu, Cheng (57191676709); Bao, Xinzhong (36083956100)","58448612500; 57191676709; 36083956100","Financial Security Analysis of E-Commerce Platform Based on Supply Chain for Heterogeneous Network Location Verification",2021.0,"Journal of Sensors",2021.0,null,7952123.0,null,null,null,0.0,"10.1155/2021/7952123","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85122337852&doi=10.1155%2f2021%2f7952123&partnerID=40&md5=4068fbdf09136d6e4569b4708edfe1c4","School of Economics and Management, University of Science and Technology Beijing, Beijing, 100083 , China; School of Management, Beijing Union University, Beijing, 100101 , China","Qu Q., School of Economics and Management, University of Science and Technology Beijing, Beijing, 100083 , China; Liu C., School of Economics and Management, University of Science and Technology Beijing, Beijing, 100083 , China; Bao X., School of Management, Beijing Union University, Beijing, 100101 , China","The development of supply chain finance, its pricing strategy for bilateral business cooperation between e-commerce, banking institutions, and fourth-party logistics services providers has gained the attention of researchers. This paper combines the heterogeneous network location verification technology, starting from information asymmetry and Rubens bargaining game ideas, and combines it with game theory methods to provide a reference for bilateral cooperation decision-making on e-commerce platforms. The experiment results indicated the pricing decisions of e-commerce platforms which are affected by the efforts of the other party and the ability of bargaining. The quoted price increases with the decrease of the bank's ability and the increase of the service provider's ability. The pricing decisions of banks and service providers are only affected by the direct proportion of their respective business costs. When considering the introduction of incentive mechanism conditions, it is found that appropriate incentive conditions can increase the quotation of the e-commerce platform. The price quoted by the e-commerce platform that chooses to bargain with the bank is higher than the price quoted by the bank after negotiating with the service provider, which will help to better realize the benefits. Finally, the paper numerically analyzes the results of the bargaining game between e-commerce platforms and banks and fourth-party logistics service providers, and the numerical results verify the better performance.  © 2021 Qiao Qu et al.",null,"Costs; Decision making; Decision theory; Game theory; Heterogeneous networks; Internet service providers; Supply chains; Bargaining game; Commerce platforms; Condition; E- commerces; Fourth party logistics; Location verification; Logistics service provider; Network location; Pricing decision; Service provider; Electronic commerce",{"$nulls":6},"Nagurney A., Daniele P., Shukla S., A supply chain network game theory model of cybersecurity investments with nonlinear budget constraints, Annals of Operations Research, 248, 1-2, pp. 405-427, (2017); Hu Q., Xu Z., Dinev T., Ling H., Does deterrence work in reducing information security policy abuse by employees?, Communications of the ACM, 54, 6, pp. 54-60, (2011); Johnstone R.W., Not safe enough: Fixing transportation security, Issues in Science and Technology, 23, 2, pp. 51-60, (2007); Rowan N.J., Galanakis C.M., Unlocking challenges and opportunities presented by COVID-19 pandemic for cross-cutting disruption in agri-food and green deal innovations: Quo Vadis?, Science of the Total Environment, 748, (2020); Zhao C., Chen B., China's oil security from the supply chain perspective: A review, Applied Energy, 136, pp. 269-279, (2014); Wang X., Wu Y., Liang L., Huang Z., Service outsourcing and disaster response methods in a relief supply chain, Annals of Operations Research, 240, 2, pp. 471-487, (2016); Song H., Yu K., Ganguly A., Turson R., Supply chain network, information sharing and SME credit quality, Industrial Management & Data Systems, 116, 4, pp. 740-758, (2016); Heng M.S., Research note: Implications of e-commerce for banking and finance, SSRN Electronic Journal, 12, 7, pp. 392-401, (2006); Bhatti R.S., Kumar P., Kumar D., Analytical modeling of third party service provider selection in lead logistics provider environments, Journal of Modelling in Management, 5, 3, pp. 275-286, (2010); Tang G.-S., Supply chain governance level, bank's perception of the seller and bank credit, pp. 1333-1338; Francis E., Blumenstock J., Robinson J., Digital Credit: A Snapshot of the Current Landscape and Open Research Questions, (2017); Wikner J., Towill D.R., Naim M., Smoothing supply chain dynamics, International Journal of Production Economics, 22, 3, pp. 231-248, (1991); Amid A., Ghodsypour S., O'Brien C., A weighted max-min model for fuzzy multi-objective supplier selection in a supply chain, International Journal of Production Economics, 131, 1, pp. 139-145, (2011); Iyer A.V., Bergen M.E., Quick response in manufacturer-retailer channels, Management Science, 43, 4, pp. 559-570, (1997); Triulzi I., Di Pasquale F., Antonel A., Rossi E., Turchetti G., PP155 demand side and supply side of healthcare supply chain, International Journal of Technology Assessment in Health Care, 35, S1, pp. 66-67, (2019); Ferguson M.E., When to commit in a serial supply chain with forecast updating, Naval Research Logistics (NRL), 50, 8, pp. 917-936, (2003); Mazzetto F., Ortiz-Gutierrez R.A., Manca D., Bezzo F., Strategic design of bioethanol supply chains including commodity market dynamics, Industrial & Engineering Chemistry Research, 52, 30, pp. 10305-10316, (2013); Lanier D., Wempe W.F., Zacharia Z.G., Concentrated supply chain membership and financial performance: Chain- A nd firm-level perspectives, Journal of Operations Management, 28, 1, pp. 1-16, (2010); Du M., Chen Q., Xiao J., Yang H., Ma X., Supply chain finance innovation using blockchain, IEEE Transactions on Engineering Management, 67, 4, pp. 1045-1058, (2020); Qureshi K.N., Hussain R., Jeon G., A distributed software defined networking model to improve the scalability and quality of services for flexible green energy internet for smart grid systems, Computers Electrical Engineering, 841, (2020); Marques M., Da Costa M.F., Mayorga M.I.D.O., Pinheiro P.R.C., Water environments: Anthropogenic pressures and ecosystem changes in the Atlantic drainage basins of Brazil, Environment, 33, 1, pp. 68-77, (2004); Manne J., Snively C.S., Levy M.Z., Reich M.R., Supply chain problems for Chagas disease treatment, The Lancet Infectious Diseases, 12, 3, pp. 173-175, (2012); Qureshi K.N., Kaiwartya O., Jeon G., Piccialli F., Neurocomputing for internet of things: Object recognition and detection strategy, Neurocomputing, 8, 22, pp. 623-635, (2021); Kim Y.-W., Han S.-H., Yi J.-S., Chang S., Supply chain cost model for prefabricated building material based on time-driven activity-based costing, Canadian Journal of Civil Engineering, 43, 4, pp. 287-293, (2016); Hasan A., Qureshi K., Internet of things device authentication scheme using hardware serialization, pp. 109-114; Yang T.-J., Financial performance analysis of e-collaboration supply chain under transportation disruptions, 2, pp. 435-439; Paz A., El Boussaidi G., Hafedh M., checsdm: A method for ensuring consistency in heterogeneous safety-critical system design, IEEE Transactions on Software Engineering, 5, 23, pp. 226-234, (2020); Filippov A., Shkirskaya S., Verification of the cell (heterogeneous) model of an ion-exchange membrane and its comparison with the homogeneous model, Colloid Journal, 81, 5, pp. 597-606, (2019); Riad K., Cheng J., Adaptive XACML access policies for heterogeneous distributed IoT environments, Information Sciences, 548, pp. 135-152, (2021); Jayne R.S., Wu H., Pollyea R.M., Geologic CO<sub>2</sub>sequestration and permeability uncertainty in a highly heterogeneous reservoir, International Journal of Greenhouse Gas Control, 83, pp. 128-139, (2019); Yang E., Kang D.-K., Youn C.-H., BOA: Batch orchestration algorithm for straggler mitigation of distributed DL training in heterogeneous GPU cluster, The Journal of Supercomputing, 76, 1, pp. 47-67, (2020); Xie G., Ma W., Peng H., Li R., Li K., Price performance-driven hardware cost optimization under functional safety requirement in large-scale heterogeneous distributed embedded systems, IEEE Transactions on Industrial Electronics, 68, 5, pp. 4485-4497, (2019); Yu Y., Li Z., Zhang D., Xing L., Peng H., Simulation studies of time reversal-based protoacoustic reconstruction for range and dose verification in proton therapy, Medical Physics, 46, 8, pp. 3649-3662, (2019)","Q. Qu; School of Economics and Management, University of Science and Technology Beijing, Beijing, 100083 , China; email: qq0069aa@163.com",null,"Hindawi Limited",{"$nulls":5},"1687725X",null,null,null,"English","J. Sensors","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85122337852"]
["Li Q.; Xiao R.","Li, Qiubo (57223011867); Xiao, Ru (57223015249)","57223011867; 57223015249","The use of data mining technology in agricultural e-commerce under the background of 6G Internet of things communication",2021.0,"International Journal of System Assurance Engineering and Management",12.0,4.0,null,813.0,823.0,10.0,14.0,"10.1007/s13198-021-01108-9","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85104397225&doi=10.1007%2fs13198-021-01108-9&partnerID=40&md5=60d0c45f3dfc57b29e38ad22594c95bd","Business School, Fuyang Normal University, Fuyang, China; Finanical Department, Fuyang Normal University, Fuyang, China","Li Q., Business School, Fuyang Normal University, Fuyang, China; Xiao R., Finanical Department, Fuyang Normal University, Fuyang, China","In view of the particularity of agricultural products and the shortcomings of existing agricultural products logistics distribution system, to reduce the cost of agricultural e-commerce logistics distribution and improve customer satisfaction, in this exploration, data mining technology in the field of artificial intelligence is used. Based on the analysis of the distribution efficiency of the current mainstream agricultural products logistics distribution mode, the logistics mode is optimized and improved, and the agricultural e-commerce common delivery mode is proposed. The logistics cost and customer satisfaction under the logistics mode are tested and analyzed through genetic algorithm and MATLAB software. The results show that the timely distribution rate of three modes of self-operated distribution, third-party logistics and common delivery decreases with the increase of orders; the timely distribution rate of common delivery mode fluctuates the most, followed by the third-party logistics mode; the timely distribution rate of self-operated distribution mode is the stablest, but it is relatively low. The calculation of genetic algorithm reveals that the optimized common delivery mode of agricultural products logistics has a significant effect on oil consumption, damage cost and other aspects. By implementing the common delivery mode, the oil consumption cost, the penalty cost, the refrigeration cost, and the damage cost are optimized by 26.7%, 31.7%, 30.3% and 19.6%, respectively. Moreover, 95% of customers are totally satisfied. In this exploration, the data mining technology is used to optimize the agricultural products distribution mode, which makes a beneficial exploration for solving the logistics bottleneck problem in the e-commerce environment, enriches the research of e-commerce logistics distribution system, and provides reference for promoting the development of agricultural products e-commerce logistics system and improving the efficiency of agricultural products logistics distribution. © 2021, The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden.","Agricultural e-commerce; Data mining; Internet of things; Logistics distribution system","Agricultural products; Agricultural robots; Artificial intelligence; Costs; Customer satisfaction; Efficiency; Electronic commerce; Genetic algorithms; Internet of things; MATLAB; Outsourcing; Petroleum prospecting; Sales; Software testing; Agricultural products logistics; Bottleneck problem; Data mining technology; Distribution efficiency; Distribution modes; Logistics distribution; Products distributions; Third party logistics; Data mining",{"$nulls":4},"Anhui Province Philosophy and Social Science Planning Project, (AHSKQ2019D019); Fuyang Normal University, (2017WLGH01ZD)","This research was supported by the following fundings: 1. Humanities and Social Sciences Project of Fuyang Normal University (Grant No. 2017WLGH01ZD); 2. Anhui Province Philosophy and Social Science Planning Project (Grant No. AHSKQ2019D019). ","Ardito L., Carrillo-Hermosilla J., del Rio P., Et al., Corporate social responsibility and environmental management invites contributions for a special issue on 'sustainable innovation: processes, strategies, and outcomes, Corp Soc Respons Environ Manag, 25, 1, pp. 106-109, (2018); Banker R.D., Mitra S., Procurement models in the agricultural supply chain: a case study of online coffee auctions in India, Electron Commer Res Appl, 6, 3, pp. 309-321, (2007); Beaman L., Dillon A., Diffusion of agricultural information within social networks: evidence on gender inequalities from Mali, J Dev Econ, 7, 5, pp. 113-116, (2018); Bladek I., Krawiec K., Swan J., Counterexample-driven genetic programming: heuristic program synthesis from formal specifications, Evol Comput, 26, 3, pp. 441-469, (2018); Burch D., Lawrence G.A., Supermarket own brands, supply chains and the transformation of the agri-food system, Int J Sociol Agric Food, 13, 1, pp. 1-18, (2005); Campbell S.T., The dynamics of handcart as a means of informal transportation in support of logistics and tourism, Worldwide Hosp Tourism Themes, 12, 1, pp. 48-55, (2020); Cherrez-Ojeda I., Plaza K., Cano J.A., Et al., Does Ecuadorians with asthma has preferences in the use of information and communication technologies? Pilot study, Rev Alerg Mex, 64, 4, pp. 403-414, (2017); Chettri L., Bera R., A comprehensive survey on Internet of Things (IoT) toward 5G wireless systems, IEEE Internet Things J, 7, 1, pp. 16-32, (2019); Dai M., Liu L., Risk assessment of agricultural supermarket supply chain in big data environment, Sustain Comput Inf Syst, 28, (2020); Desai V.S., Conway D.G., Crook J.N., Et al., Credit-scoring models in the credit-union environment using neural networks and genetic algorithms, IMA J Manag Math, 1, 4, pp. 323-346, (2018); Essougong U.P.K., Fouepe G.H.F., Degrande A., Can community-based organisations deliver adequate agricultural information to farmers? Evidence from rural resources centres in Cameroon, Inf Dev, 35, 3, pp. 435-446, (2019); Hajiheidari S., Wakil K., Badri M., Et al., Intrusion detection systems in the Internet of things: a comprehensive investigation, Comput Netw, 160, 4, pp. 165-191, (2019); Kakarountas A., the internet of things: trends, threats, and applications, IEEE Potentials, 38, 2, pp. 10-11, (2019); Liu D., Study on supplier selection of fresh e-commerce enterprises based on entropy weight TOPSIS, Manag Eng, 8, 1, pp. 1-6, (2019); Liu L., Wang H., Xing S., Optimization of distribution planning for agricultural products in logistics based on degree of maturity, Comput Electron Agric, 160, pp. 1-7, (2019); Monteiro E., Parmiggiani E., Synthetic knowing: the politics of the internet of things, MIS Q, 43, 1, pp. 167-184, (2019); Navicelli A., Carlo F.D., Third-party logistics as a competitive advantage in utilities spare parts management, IFAC-PapersOnLine, 51, 11, pp. 600-605, (2018); Perdana Y.R., Logistics information system for supply chain of agricultural commodity, Procedia Soc Behav Sci, 65, pp. 608-613, (2012); Rong A., Akkerman R., Grunow M., An optimization approach for managing fresh food quality throughout the supply chain, Int J Prod Econ, 131, 1, pp. 421-429, (2011); Saad W., Bennis M., Chen M., A vision of 6G wireless systems: applications, trends, technologies, and open research problems, IEEE Netw, 34, 3, pp. 134-142, (2019); Sohaiba O., Naderpourab M., Hussaina W., Martinezc L., Cloud computing model selection for e-commerce enterprises using a new 2-tuple fuzzy linguistic decision-making method, Comput Ind Eng, 132, pp. 47-58, (2019); Soukarieh B., El Hawari K., El Husseini M., Et al., Impact of Lebanese practices in industry, agriculture and urbanization on soil toxicity evaluation of the polycyclic aromatic hydrocarbons (PAHs) levels in soil, Chemosphere, 2, 10, pp. 85-92, (2018); Surabhi M., Subash S.P., Anurag A., Agricultural information and knowledge network in rural India: a case of Bihar, J Agric Educ Ext, 10, 20, pp. 1-26, (2018); Udoh I.S., Kotonya G., Developing IoT applications: challenges and frameworks, IET Cyber-Phys Syst Theory Appl, 3, 2, pp. 65-72, (2018); Wang Z., Willingness of agricultural workers to conduct e-commerce of agricultural products based on GEM Model, Asian Agric Res, 10, 5, pp. 26-30, (2018); Wang Z., Willingness of agricultural workers to conduct e-commerce of agricultural products based on GEM Model, Agric Res Asia, 10, 5, pp. 22-26, (2018); Wen W., A knowledge-based intelligent electronic commerce system for selling agricultural products, Comput Electron Agric, 57, 1, pp. 33-46, (2007); Yoshida S., Izumi S., Kajihara K., Et al., Energy-efficient spectral analysis method using autoregressive model-based approach for internet of things, Circuits Syst I Regul Pap IEEE Trans, 1, 9, pp. 1-10, (2019); Zhang Z., Xiao Y., Ma Z., Et al., 6G wireless networks: vision, requirements, architecture, and key technologies, IEEE Veh Technol Mag, 14, 3, pp. 28-41, (2019); Zhu J., Zhou L., Huang S., A hybrid drought index combining meteorological, hydrological, and agricultural information based on the entropy weight theory, Arab J Geosci, 11, 5, pp. 1-12, (2018)","Q. Li; Business School, Fuyang Normal University, Fuyang, China; email: 201507014@fynu.edu.cn",null,"Springer",{"$nulls":5},9756809.0,null,null,null,"English","Intl. J. Syst. Assur. Eng. Manage.","Article","Final",null,"Scopus","2-s2.0-85104397225"]
["Zhao Y.; Jia W.","Zhao, Yanan (57404932400); Jia, Wei (57405250600)","57404932400; 57405250600","Considering the Sales Method and Logistics Service Strategy, Which Operating Mode Is the Best under Different Power Structures?",2021.0,"Mathematical Problems in Engineering",2021.0,null,7653068.0,null,null,null,1.0,"10.1155/2021/7653068","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85122540936&doi=10.1155%2f2021%2f7653068&partnerID=40&md5=d62cdbfb482d71fee57621b105a2ddaa","School of Economics and Management, Liaoning Petrochemical University, Fushun, China","Zhao Y., School of Economics and Management, Liaoning Petrochemical University, Fushun, China; Jia W., School of Economics and Management, Liaoning Petrochemical University, Fushun, China","When merchants enter hybrid e-commerce platforms (such as JD.com and Amazon), they will face issues such as which sales methods to choose and whether to use platform logistics under different power structures. Different sales methods and logistics service strategies have resulted in three operating modes: (a) resale mode, marked as A, (b) agency + no-platform logistics, marked as B, and (c) agency + platform logistics, marked as C. This paper constructs an analysis framework composed of an e-commerce platform and a merchant to explore the optimal operating mode. The game models of the three modes are first constructed, and then, the equilibrium results are compared and analysed. Based on the results of comparative analysis and considering the dynamic game between the e-commerce platform and the merchant regarding sales methods and logistics service strategies, the optimal operating mode is determined. The results show that when the platform has absolute power, mode C is optimal for it. When the logistics service sensitivity coefficient and market size are both large, the best for the merchant with absolute power is mode B. In addition, if neither of them has absolute power, only when the merchant first decides the logistics service strategy, then the platform decides the sales method; the best for both parties is mode B; otherwise, the best is mode A. This research has generated new insights and has practical management significance, which can provide guidance for merchant and platform decision-making. Copyright © 2021 Yanan Zhao and Wei Jia.",null,"Decision making; Electronic commerce; Absolute power; AM modes; Analysis frameworks; Commerce platforms; E- commerces; Game models; Logistics services; Operating modes; Power structures; Service strategy; Sales",{"$nulls":6},"Liu W., Yan X., Li X., Wei W., The impacts of market size and data-driven marketing on the sales mode selection in an Internet platform based supply chain, Transportation Research Part E: Logistics and Transportation Review, 136, (2020); Hagiu A., Wright J., Marketplace or reseller?, Management Science, 61, 1, pp. 184-203, (2015); Deng W., Shang S., Cai X., Zhao H., Zhou Y., Chen H., Deng W., Quantum differential evolution with cooperative coevolution framework and hybrid mutation strategy for large scale optimization, Knowledge-Based Systems, 224, (2021); Yu Y., Wang X., Zhong R.Y., Huang G.Q., E-commerce logistics in supply chain management: practice perspective, Procedia CIRP, 52, pp. 179-185, (2016); Deng W., Xu J., Gao X.-Z., Zhao H., An enhanced msiqde algorithm with novel multiple strategies for global optimization problems, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 98, pp. 1-10, (2020); He P., Wen J., Ye S., Li Z., Logistics service sharing and competition in a dual-channel e-commerce supply chain, Computers & Industrial Engineering, 149, (2020); Deng W., Shang S., Cai X., Zhao H., Song Y., Xu J., An improved differential evolution algorithm and its application in optimization problem, Soft Computing, 25, 7, pp. 5277-5298, (2021); Jiang B., Jerath K., Srinivasan K., Firm strategies in the \"mid tail\" of platform-based retailing, Marketing Science, 30, 5, pp. 757-775, (2011); Kwark Y., Chen J., Raghunathan S., Platform or wholesale? A strategic tool for online retailers to benefit from third-party information, Social Science Electronic Publishing, 41, 3, pp. 763-786, (2013); Mantin B., Krishnan H., Dhar T., The strategic role of third-party marketplaces in retailing, Production and Operations Management, 23, 11, pp. 1937-1949, (2015); Abhishek V., Jerath K., Zhang Z.J., Agency selling or reselling? Channel structures in electronic retailing, Management Science, 62, 8, pp. 2259-2280, (2016); Chen L., Nan G., Li M., Wholesale pricing or agency pricing on online retail platforms: the effects of customer loyalty, International Journal of Electronic Commerce, 22, 4, pp. 576-608, (2018); Zennyo Y., Strategic contracting and hybrid use of agency and wholesale contracts in e-commerce platforms, European Journal of Operational Research, 281, 1, pp. 231-239, (2020); Yan Y., Zhao R., Xing T., Strategic introduction of the marketplace channel under dual upstream disadvantages in sales efficiency and demand information, European Journal of Operational Research, 273, 3, pp. 968-982, (2019); Li Q., Wang Q., Song P., The effects of agency selling on reselling on hybrid retail platforms, International Journal of Electronic Commerce, 23, 4, pp. 524-556, (2019); Zhang S., Zhang J., Agency selling or reselling: E-tailer information sharing with supplier offline entry, European Journal of Operational Research, 280, 1, pp. 134-151, (2020); Chen P., Zhao R., Yan Y., Li X., Promotional pricing and online business model choice in the presence of retail competition, Omega, 94, (2020); Xu X., He P., Zhang S., Channel addition from marketplace or reselling under regional carbon cap-and-trade regulation, International Journal of Production Economics, 236; Pu X., Zhang S., Ji B., Han G., Online channel strategies under different offline channel power structures, Journal of Retailing and Consumer Services, 60, (2021); Zhang X., Hou W., The impacts of e-tailer’s private label on the sales mode selection: from the perspectives of economic and environmental sustainability, European Journal of Operational Research, 296, 2, pp. 601-614, (2022); Chen C., Zhuo X., Li Y., Online channel introduction under contract negotiation: reselling versus agency selling, Managerial and Decision Economics, 23, (2021); Pu X., Sun S., Shao J., Direct selling, reselling, or agency selling? Manufacturer's online distribution strategies and their impact, International Journal of Electronic Commerce, 24, 2, pp. 232-254, (2020); Yang M., Zhang T., Wang C.-X., The optimal e-commerce sales mode selection and information sharing strategy under demand uncertainty, Computers & Industrial Engineering, 162, (2021); Li D., Liu Y., Fan C., Hu J., Chen X., Logistics service strategies under different selling modes, Computers & Industrial Engineering, 162, (2021); He P., Zhang S., He C., Impacts of logistics resource sharing on B2C E-commerce companies and customers, Electronic Commerce Research and Applications, 34, (2019); Niu B., Xie F., Chen L., Xu X., Join logistics sharing alliance or not? Incentive analysis of competing E-commerce firms with promised-delivery-time, International Journal of Production Economics, 224, (2020); Qin X., Liu Z., Tian L., The strategic analysis of logistics service sharing in an e-commerce platform, Omega, 92, (2020); Qin X., Liu Z., Tian L., The optimal combination between selling mode and logistics service strategy in an e-commerce market, European Journal of Operational Research, 289, 2, pp. 639-651, (2021); Cao K., Xu Y., Wu Q., Wang J., Liu C., Optimal channel and logistics service selection strategies in the e-commerce context, Electronic Commerce Research and Applications, 48, (2021); Pan K., Lai K.K., Leung S.C.H., Xiao D., Revenue-sharing versus wholesale price mechanisms under different channel power structures, European Journal of Operational Research, 203, 2, pp. 532-538, (2010); Wu C.-H., Chen C.-W., Hsieh C.-C., Competitive pricing decisions in a two-echelon supply chain with horizontal and vertical competition, International Journal of Production Economics, 135, 1, pp. 265-274, (2012); Gao J., Han H., Hou L., Wang H., Pricing and effort decisions in a closed-loop supply chain under different channel power structures, Journal of Cleaner Production, 112, pp. 2043-2057, (2016); Luo Z., Chen X., Chen J., Wang X., Optimal pricing policies for differentiated brands under different supply chain power structures, European Journal of Operational Research, 259, 2, pp. 437-451, (2017); Luo Z., Chen X., Kai M., The effect of customer value and power structure on retail supply chain product choice and pricing decisions, Omega, 77, pp. 115-126, (2018); Li C., Liu Q., Zhou P., Huang H., Optimal innovation investment: the role of subsidy schemes and supply chain channel power structure, Computers & Industrial Engineering, 157, (2021); Jin L., Zheng B., Huang S., Pricing and coordination in a reverse supply chain with online and offline recycling channels: a power perspective, Journal of Cleaner Production, 298, (2021); Hu Y., Qu S., Li G., Sethi S.P., Power structure and channel integration strategy for online retailers, European Journal of Operational Research, 294, 3, pp. 951-964, (2021)","Y. Zhao; School of Economics and Management, Liaoning Petrochemical University, Fushun, China; email: zhao3226870051@163.com",null,"Hindawi Limited",{"$nulls":5},"1024123X",null,null,null,"English","Math. Probl. Eng.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85122540936"]
["Kolte A.; Sangvikar B.; Pawar A.; Singh J.","Kolte, Ashutosh (57204614937); Sangvikar, Balkrishan (57211453074); Pawar, Avinash (57211460055); Singh, Jagbir (57208617122)","57204614937; 57211453074; 57211460055; 57208617122","Investigation of applied criteria for selecting online retailers: implications from the Indian market",2021.0,"International Journal of Enterprise Network Management",12.0,4.0,null,297.0,311.0,14.0,2.0,"10.1504/IJENM.2021.119660","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85122023504&doi=10.1504%2fIJENM.2021.119660&partnerID=40&md5=f564edea42ad0ee1ae8916dca83aa38a","Department of Management Sciences, Savitribai Phule Pune University, India; Swami Shraddhanand College, University of Delhi, India","Kolte A., Department of Management Sciences, Savitribai Phule Pune University, India; Sangvikar B., Department of Management Sciences, Savitribai Phule Pune University, India; Pawar A., Department of Management Sciences, Savitribai Phule Pune University, India; Singh J., Swami Shraddhanand College, University of Delhi, India","Today, online retail businesses focused on the adoption of customer centric approaches. Since the last few decades, information and internet technologies are providing new opportunities to businesses in market. Many retailers have started their online format of retailing called as e-retailing. This paper identifies the factors and criteria used by consumers to select online retailers for their consumption needs. The collected data of retailers is analysed using the statistical technique of interval estimates of the proportion. The outcome of the paper deliberates on the consumer factors for selecting online retailers which includes price range and quality, offers and discounts, payment methods and delivery options, and transparent return policy. Moreover, retailer image and trust, website, social media reports and customer reviews, privacy and security of data are crucial. Furthermore, a model of online retailing with criteria is proposed, which can help the retailers to operate in the Indian retail environment. Copyright © 2021 Inderscience Enterprises Ltd.","Consumerism in India; E-commerce; E-customers; E-retail business; E-retailing; Online retailer selection model; Online retailers; Retail consumer; Retail consumer influence; Retail management; Retail modelling; Retail strategy; Retail technology; Retailer selection criteria",{"$nulls":7},"AlGhamdi R., Drew S., AlFaraj O., Issues influencing Saudi customers' decisions to purchase from online retailers in the KSA: a qualitative analysis, European Journal of Scientific Research, 55, 4, pp. 580-593, (2011); Baji A., Sekhar N.D.C., Consumer behavior towards buying of electronic goods, Abhinav, 2, 1, pp. 20-27, (2013); Bonera M., The propensity of e-commerce usage: the influencing variables, Management Research Review, 34, 7, pp. 821-837, (2011); Burman B., Evans J., Retail Management: A Strategic Approach, (2006); Cai S., Jun M., Internet users' perceptions of online service quality: a comparison of online buyers and information searchers, Managing Service Quality: An International Journal, 13, 6, pp. 504-519, (2003); Cattani K.D., Gilland W.G., Swaminathan J.M., Coordinating traditional and internet supply chains, Handbook of Quantitative Supply Chain Analysis, pp. 643-677, (2004); Doherty N.F., Ellis-Chadwick F., Internet retailing: the past, the present and the future, International Journal of Retail & Distribution Management, 38, 11, pp. 943-965, (2010); Doherty N.F., Ellis-Chadwick F.E., Hart C.A., Cyber retailing in the UK: the potential of the internet as a retail channel, International Journal of Retail & Distribution Management, 27, 1, pp. 22-36, (1999); Goswami S., Mathur M., Retail goes online-an Indian perspective, International Journal of Management and Tourism, 19, 2, pp. 1-11, (2011); Hoffman L., Novak T.P., Marketing in hypermedia computer‐mediated environments: conceptual foundations, Journal of Marketing, 60, 3, pp. 50-68, (1996); Kim S., Noh M.J., Determinants influencing consumers' trust and trust performance of social commerce and moderating effect of experience, Information Technology Journal, 11, 10, pp. 1369-1380, (2012); Kolesar M.B., Wayne R.G., A services-marketing perspective on eretailing: implications for e-retailers and directions for further research, Internet Research, 10, 5, pp. 424-438, (2000); Kolte A., Siggia D., Veer N., Daryani A., Critical exploration of indian economic reforms of 1991: a lesson for developing economies, International Journal of Engineering and Advanced Technology, 8, pp. 490-500, (2019); Kouki P., Fountalis I., Vasiloglou N., Yan N., Ahsan U., Jadda K.A., Qu H., Product collection recommendation in online retail, Proceedings of the 13th ACM Conference on Recommender Systems, pp. 486-490, (2019); Lal R., Matutes C., Retail pricing and advertising strategies, Journal of Business, 67, 3, pp. 345-371, (1994); Lee M.K., Turban E., A trust model for consumer internet shopping, International Journal of Electronic Commerce, 6, 1, pp. 75-91, (2001); Levy M., Weitz B.A., Retailing Management, (2006); Limbu Y.B., Jensen R.W., The determinants and consequences of website credibility in e-retailing: examining the roles of ethical issues, Int. J. Electronic Marketing and Retailing, 9, 1, pp. 89-108, (2018); Loureiro S.M.C., Bilro R.G., Be or not be online engaged: exploring the flow from stimuli to e-WOM on online retail consumers, Exploring the Power of Electronic Word-of-Mouth in the Services Industry, pp. 18-34, (2020); Mishra S., Mathew P.M., Analyzing perceived risks and website attributes in eretailing: a study from India, Journal of Internet Banking and Commerce, 18, 2, pp. 1-14, (2013); Monsuwe T.P., Dellaert B.G.C., Ruyter K.D., What drives consumers to shop online: A literature review, International Journal of Service Industry Management, 15, 1, pp. 102-121, (2004); Park C., Kim Y., Identifying key factors affecting consumer purchase behavior in an online shopping context, International Journal of Retail & Distribution Management, 31, 1, pp. 16-29, (2003); Park J., Stoel L., Effect of brand familiarity, experience and information on online apparel purchase, International Journal of Retail & Distribution Management, 33, 2, pp. 148-160, (2005); Pentina I., Amialchuk A., Taylor D.G., Exploring effects of online shopping experiences on browser satisfaction and e-tail performance, International Journal of Retail & Distribution Management, 39, 10, pp. 742-758, (2011); Prasad A., Analysing Online Retail Transactions using Big Data Framework, pp. 1-6, (2019); Punj G., Srinivasan N., Influence of problem recognition on search and other decision process variables: a framework for analysis, Advances in Consumer Research, 19, 1, pp. 491-497, (1992); Pyle R., Electronic commerce and the internet, Communications of the ACM, 39, 6, pp. 22-24, (1996); Rosenbloom B., Marketing Channels: A Management View, (1999); Sangvikar B., Kolte A., Pawar A., Competitive strategies for unorganised retail business: understanding structure, operations, and profitability of small mom and pop stores in India, International Journal on Emerging Technologies, 10, 3, pp. 253-259, (2019); Sangvikar B., Pawar A., Pahurkar R., Survival from the balance of payment crisis: implications from the challenges faced by India, International Journal of Recent Technology and Engineering, 8, pp. 3769-3775, (2019); Sangvikar B., Pawar A., Kolte A., Mainkar A., Sawant P., How does green marketing influence consumers? The market trend examination towards environmentally sustainable products in emerging Indian cities, International Journal of Recent Technology and Engineering, 8, 3S, pp. 561-571, (2019); Schaupp L.C., Belanger F., A conjoint analysis of online consumer satisfaction, Journal of Electronic Commerce Research, 6, 2, pp. 95-111, (2005); Sinha P.K., Banerjee A., Store choice behavior in an evolving market, International Journal of Retail & Distribution Management, 32, 10, pp. 482-494, (2004); Solomon M.R., Consumer Behavior. Buying, Having and Being, (1996); Sorce P., Perotti V., Widrick S., Attitude and age differences in online buying, International Journal of Retail & Distribution Management, 33, 21, pp. 122-132, (2005); Srinivasan S., Anderson R., Kishore P., Customer loyalty in e‐commerce: an exploration of its antecedents and consequences, Journal of Retailing, 78, 1, pp. 41-50, (2002); Trabold L.M., Heim G.R., Field J.M., Comparing e-service performance across industry sectors, International Journal of Retail & Distribution Management, 34, 4, pp. 240-257, (2006); Veer N., Pawar A., Kolte A., Store preference criteria and its attributes, Journal of Advanced Research in Dynamical and Control Systems, 10, 14, pp. 1920-1930, (2018); Veer N., Pawar P., Kolte A., Effectiveness of social media tools and it's impact on promotions, International Journal of Innovative Technology and Exploring Engineering, 8, pp. 224-230, (2019); Verhagen T., Van Dolen W., The influence of online store beliefs on consumer online impulse buying: a model and empirical application, Information & Management, 48, 8, pp. 320-327, (2011); Wang Y., Multi channel integration of online and offline two-way docking of retail enterprises in the internet era, Caribbean Journal of Science, 52, 4, pp. 1821-1823, (2019); Zhang T., Zhuang G., Huang Y., A literature review on the studies of internet retailing management, Technology and Investment, 1, 1, pp. 19-25, (2010)","A. Kolte; Department of Management Sciences, Savitribai Phule Pune University, India; email: ashutoshkolte@gmail.com",null,"Inderscience Publishers",{"$nulls":5},1.7481252E7,null,null,null,"English","Int. J. Enterp. Network Manage.","Article","Final",null,"Scopus","2-s2.0-85122023504"]
["Cokyasar T.","Cokyasar, Taner (57196022283)",5.7196022283E10,"Optimization of battery swapping infrastructure for e-commerce drone delivery",2021.0,"Computer Communications",168.0,null,null,146.0,154.0,8.0,32.0,"10.1016/j.comcom.2020.12.015","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85099790730&doi=10.1016%2fj.comcom.2020.12.015&partnerID=40&md5=80c965c3033de21e4bc61e189b281973","Energy Systems Division, Argonne National Laboratory, 9700 Cass Avenue, Lemont, IL, United States","Cokyasar T., Energy Systems Division, Argonne National Laboratory, 9700 Cass Avenue, Lemont, IL, United States","Drone delivery is widely-researched to alter the current e-commerce delivery convention for providing short delivery lead times. Yet, flight range of drones, constrained by the available battery technology, sets a milestone toward realizing the sole-drone delivery. To tackle with the flight range limitation, locating automated battery swapping machines (ABSM) have been proposed and a few studies modeled the problem. Using the ABSMs, drones can be loaded with fully-charged batteries along the route to a demand location. In this study, we introduce a mixed-integer nonlinear program to model the problem. The objective of the program is to optimally select ABSM locations, determine the delivery-mode choices (drone-only, truck-only, and mixed delivery) of demand locations, find drone delivery routes, and approximate the baseline requirements for the number of drones and batteries needed. The program minimizes the overall delivery system costs including: ABSM, delivery, drone ownership, battery inventory, and service congestion. A cutting-plane method is developed to find exact solutions in finite iterations. Computational experiments showed that the method quickly yields the optimal solution to instances with less than 60 ABSM candidates and 20 demand locations. A case study shows that the optimal drone delivery infrastructure can save almost 20% cost compared to the conventional truck-only delivery. Sensitivity analyses were conducted to reveal the impact of key parameters in the decision-making and found that a decrease in the ABSM and drone costs highly affect the system cost. Code to solve the case study is publicly available at https://gitlab.com/tcokyasar/optimization-of-battery-swapping. © 2020 Elsevier B.V.","Battery swapping for drones; Drone delivery; Optimization","Cost benefit analysis; Decision making; Electric batteries; Electronic commerce; Integer programming; Location; Nonlinear programming; Sensitivity analysis; Trucks; Battery swapping; Battery technology; Computational experiment; Cutting plane methods; Delivery routes; Delivery systems; Mixed integer nonlinear program; Optimal solutions; Drones",{"$nulls":4},"U.S. Department of Energy, USDOE; Office of Energy Efficiency and Renewable Energy, EERE; Argonne National Laboratory, ANL, (DE-AC02-06CH11357)","Funding text 1: The submitted manuscript has been created by UChicago Argonne, LLC, Operator of Argonne National Laboratory (“Argonne”). Argonne, a U.S. Department of Energy Office of Science laboratory, is operated under Contract No. DE-AC02-06CH11357. The U.S. Government retains for itself, and others acting on its behalf, a paid-up nonexclusive, irrevocable worldwide license in said article to reproduce, prepare derivative works, distribute copies to the public, and perform publicly and display publicly, by or on behalf of the Government. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan. http://energy.gov/downloads/doe-public-access-plan .; Funding text 2: This material is based upon work supported by the U.S. Department of Energy, Vehicle Technologies Office, under the Systems and Modeling for Accelerated Research in Transportation Mobility Laboratory Consortium, an initiative of the Energy Efficient Mobility Systems Program. David Anderson, a Department of Energy, Office of Energy Efficiency and Renewable Energy manager, played an important role in establishing the project concept, advancing implementation, and providing ongoing guidance. The submitted manuscript has been created by UChicago Argonne, LLC, Operator of Argonne National Laboratory (?Argonne?). Argonne, a U.S. Department of Energy Office of Science laboratory, is operated under Contract No. DE-AC02-06CH11357. The U.S. Government retains for itself, and others acting on its behalf, a paid-up nonexclusive, irrevocable worldwide license in said article to reproduce, prepare derivative works, distribute copies to the public, and perform publicly and display publicly, by or on behalf of the Government. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan. http://energy.gov/downloads/doe-public-access-plan.; Funding text 3: This material is based upon work supported by the U.S. Department of Energy, Vehicle Technologies Office , under the Systems and Modeling for Accelerated Research in Transportation Mobility Laboratory Consortium, an initiative of the Energy Efficient Mobility Systems Program. David Anderson, a Department of Energy, Office of Energy Efficiency and Renewable Energy manager, played an important role in establishing the project concept, advancing implementation, and providing ongoing guidance. ","Amazon prime air, (2020); Elliot D., DHL testing delivery drones, (2013); Madrigal A.C., Inside Google's secret drone-delivery program, (2014); Berminghman F., FedEx researching drone delivery but not for widespread use, (2014); Aitken R., What do China's delivery drones look like? – JD.com spotlight, (2017); Summary of Small Unmanned Aircraft Rule (Part 107), (2016); Curlander J.C., Gilboa-Amir A., Kisser L.M., Koch R.A., Welsh R.D., (2017); Cokyasar T., Dong W., Jin M., Network optimization for hybrid last-mile delivery with trucks and drones, (2019); Cokyasar T., Dong W., Jin M., Verbas I.O., Designing a drone delivery network with automated battery swapping machines, Comput. Oper. Res., (2020); Hong I., Kuby M., Murray A.T., A range-restricted recharging station coverage model for drone delivery service planning, Transp. Res. C, 90, pp. 198-212, (2018); Huang H., Savkin A.V., A method of optimized deployment of charging stations for drone delivery, IEEE Trans. Transp. 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Commun., 149, pp. 270-299, (2020); Bacanli S.S., Turgut D., Energy-efficient unmanned aerial vehicle scanning approach with node clustering in opportunistic networks, Comput. Commun., 161, pp. 76-85, (2020); Grippa P., Behrens D.A., Wall F., Bettstetter C., Drone delivery systems: Job assignment and dimensioning, Auton. Robots, 43, pp. 261-274, (2019); Kirschstein T., Comparison of energy demands of drone-based and ground-based parcel delivery services, Transp. Res. D, 78, pp. 102209-102227, (2020); Madan K.C., Saleh M.F., On M/D/1 queue with general server vacations, Internat. J. Inform. Management Sci., 12, pp. 25-38, (2001); Mak H.-Y., Rong Y., Shen Z.-J.M., Infrastructure planning for electric vehicles with battery swapping, Manage. Sci., 59, pp. 1557-1575, (2013); Gurobi Optimization, LLC, Gurobi optimizer reference manual, (2020); Auld J., Hope M., Ley H., Sokolov V., Xu B., Zhang K., POLARIS: Agent-based modeling framework development and implementation for integrated travel demand and network and operations simulations, Transp. Res. C, 64, pp. 101-116, (2016)",null,null,"Elsevier B.V.",{"$nulls":5},1403664.0,null,"COCOD",null,"English","Comput Commun","Article","Final","All Open Access; Bronze Open Access; Green Open Access","Scopus","2-s2.0-85099790730"]
["He X.; Meng S.; Liang J.","He, Xijin (57221378948); Meng, Shuxia (57221372126); Liang, Juanjuan (56402213300)","57221378948; 57221372126; 56402213300","Analysis of cross-border E-Commerce logistics model based on embedded system and genetic algorithm",2021.0,"Microprocessors and Microsystems",82.0,null,103827.0,null,null,null,11.0,"10.1016/j.micpro.2021.103827","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85098979082&doi=10.1016%2fj.micpro.2021.103827&partnerID=40&md5=8317ece6830382d8bd5125d2bc91a7b4","School of Economics and Trade, Xingtai University, Xingtai, 054000, Hebei, China","He X., School of Economics and Trade, Xingtai University, Xingtai, 054000, Hebei, China; Meng S., School of Economics and Trade, Xingtai University, Xingtai, 054000, Hebei, China; Liang J., School of Economics and Trade, Xingtai University, Xingtai, 054000, Hebei, China","Cross-border e-commerce is a challenge in the logistics sector because of this dynamic market. It means hiring sea and air cargo partners, customs brokers, warehousing operators, regional logistics partners, and all other stakeholders at the Operations Department. Refers to online transactions between cross-border e-commerce companies (retailers and brands) and consumers, both companies, often brands and wholesalers, or between two individuals. Using embedded system to design can achieve the balance of software and hardware.In solving combinatorial optimization problems, we often use genetic algorithm.In order to solve the practical problems, we need to consider both the software part and the hardware part.Genetic algorithm mainly simulates the evolution process of organisms through natural selection. On the one hand, it can solve some constrained problems, on the other hand, it can also optimize some unconstrained problems.In this study, based on genetic algorithm, we optimize the distribution efficiency in the real world, and propose the optimized algorithm and improve it.We have changed the parameters of the traditional genetic algorithm to realize the optimization of e-commerce. We can also see from the experimental results that we have achieved certain results.The improved genetic algorithm can play a certain role in the distribution process of e-commerce, improve the efficiency of transportation, and meet the requirements of reality. © 2021","Cross-border e-commerce; Embedded system; Genetic algorithm; Logistics model","Biodiversity; Combinatorial optimization; Efficiency; Electronic commerce; Embedded systems; Freight transportation; Combinatorial optimization problems; Constrained problem; Distribution efficiency; Distribution process; Online transaction; Optimized algorithms; Regional logistics; Traditional genetic algorithms; Genetic algorithms",{"$nulls":6},"Chen H., Liu S., Su T., The study for refurbishing process of packaging material in E-commerce logistics, 2018 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI), Singapore, pp. 80-84, (2018); Pan Y., Wang Z., Hu Q., Integration of RFID Technique and E-commerce Logistics, 2009 International Conference on Networking and Digital Society, Guiyang,Guizhou, pp. 152-155, (2009); Yang Y., Hao-yu W., Mechanism of Logistics information in reverse tracking system under E-commerce, Proceedings of 2011 IEEE International Conference on Service Operations, Logistics and Informatics, Beijing, pp. 177-181, (2011); Jianyu W.A., Runtong Z.H., Jun W.A., Research on the distribution system in E-commerce logistics based on gridding management, 2015 International Conference on Logistics, Informatics and Service Sciences (LISS), Barcelona, pp. 1-5, (2015); Yang L.A., Wu S.I., Study of a logistics management model, based on e-commerce, 2010 3rd International Conference on Advanced Computer Theory and Engineering (ICE), Chengdu, (2010); Lixin Z.H., Faliang S.H., An analysis on the relationship between modern logistics and e-commerce, 2008 IEEE International Conference on Service Operations and Logistics, and Informatics, Beijing, pp. 1381-1384, (2008); Zhang D., Zhang J., The enterprises logistics information platform framework based on E-Commerce, 2007 IEEE International Conference on Automation and Logistics, Jinan, pp. 880-883, (2007); Zhi-Qiang L., Bao-ling Y., Competitiveness analysis method for logistics enterprises in E-commerce, 2010 International Conference on E-Business and E-Government, Guangzhou, pp. 3212-3214, (2010); Guo F., Zhong Y., Zhang Q., Study on logistics outsourcing strategy of E-Commerce based on revenue sharing contract, 2016 12th International Conference on Computational Intelligence and Security (CIS), Wuxi, pp. 370-373, (2016); Yang L., Zhang Y., Application of fuzzy-AHP method in the evaluation of logistics capability in E-Commerce environment, 2010 International Conference on Communications and Intelligence Information Security, Nanning, pp. 228-231, (2010); Zheng S., Zhang Y., He T., The application of genetic algorithm in embedded system hardware-software partitioning, 2009 International Conference on Electronic Computer Technology, Macau, pp. 219-222, (2009); Vudatha C.P., Nalliboena S., Jammalamadaka S.K., Duvvuri B.K.K., Reddy L.S.S., Automated generation of test cases from output domain of an embedded system using Genetic algorithms, 2011 3rd International Conference on Electronics Computer Technology, Kanyakumari, pp. 216-220, (2011); Talbi E., Muntean T., Designing embedded parallel systems with parallel genetic algorithms, IEE Colloquium on Genetic Algorithms for Control Systems Engineering, London, UK, (1993); Ali M.S., Mahajan A., Choudhari N.V., Compiled code compression for embedded systems using evolutionary computing, Fifth International Conference on Information Technology: New Generations (itng 2008), Las Vegas, NV, pp. 1173-1174, (2008); Conner J., Xie Y., Kandemir M., Link G., Dick R., FD-HGAC: a hybrid heuristic/genetic algorithm hardware/software co-synthesis framework with fault detection, Proceedings of the ASP-DAC 2005. Asia and South Pacific Design Automation Conference, 2005, Shanghai, pp. 709-712, (2005); Anguraj S., Kumaresan K., A structured system of embedded based on artificial intelligence by incorporating genetic algorithm, 2010 International Conference on Communication Control and Computing Technologies, Ramanathapuram, pp. 451-454, (2010); Bao J., Zhou B., Yan Y., A genetic-algorithm-based weight discretization paradigm for neural networks, 2009 WRI World Congress on Computer Science and Information Engineering, Los Angeles, CA, pp. 655-659, (2009); Yu J., Solution for virtual network embedding problem based on Simulated Annealing genetic algorithm, 2012 2nd International Conference on Consumer Electronics, Communications and Networks (CECNet), Yichang, (2012); Niu X.I., Yuan X.A., Zhou Y.O., Fan H., UAV track planning based on evolution algorithm in embedded system, Microprocess Microsyst, 75, (2020); Sanaj M.S., Joe Prathap P.M., An infrastructure for embedded systems using task scheduling, Microprocess Microsyst, 77, (2020)","X. He; School of Economics and Trade, Xingtai University, Xingtai, 054000, China; email: hexijin123456@163.com",null,"Elsevier B.V.",{"$nulls":5},1419331.0,null,"MIMID",null,"English","Microprocessors Microsyst","Article","Final",null,"Scopus","2-s2.0-85098979082"]
["Gao T.","Gao, Tiange (57396635300)",5.73966353E10,"Study on the Intention of Foreign Trade Driven by Cross-Border E-Commerce Based on Blockchain Technology",2021.0,"Security and Communication Networks",2021.0,null,9623672.0,null,null,null,8.0,"10.1155/2021/9623672","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85122249073&doi=10.1155%2f2021%2f9623672&partnerID=40&md5=bfb92382c94f2f44ed4bec94361c4bb1","School of International Business and Trade, Zhejiang Industry and Trade Vocational College, Zhejiang, Wenzhou, 325000, China","Gao T., School of International Business and Trade, Zhejiang Industry and Trade Vocational College, Zhejiang, Wenzhou, 325000, China","Cross-border e-commerce is also facing the problems of cross-border goods selling counterfeit, long delivery time of cross-border logistics, and high cross-border payment fee in the process of development. Blockchain technology, with its characteristics of high trustworthiness, traceability, and information immutability, can be applied to the field of cross-border e-commerce, providing a new direction for cross-border e-commerce to solve these problems. At the present stage, scholars at home and abroad mainly study how blockchain technology is applied in cross-border e-commerce, explore the specific mode of combining blockchain technology with cross-border e-commerce, and lay the theoretical foundation for the application of blockchain technology in cross-border e-commerce, while less research is conducted on the application effect of blockchain technology in cross-border e-commerce. Based on this, this paper researches the influence mechanism of the application of blockchain technology in cross-border e-commerce on consumers' willingness to purchase, explains the current situation of the application of blockchain technology in various fields of cross-border e-commerce, and on this basis, divides the quality of the blockchain system of cross-border e-commerce into three dimensions of commodity information quality, logistics service quality, and payment security.  © 2021 Tiange Gao.",null,"Blockchain; International trade; Network security; Application effect; Block-chain; Cross-border; Current situation; Delivery time; E- commerces; Influence mechanism; Paper research; Present stage; Theoretical foundations; Electronic commerce",{"$nulls":6},"Hua Z., Be K., Shi Q., Research on the information tracing model for cross-border e-commerce products based on blockchain, E3S Web of Conferences, 235, 4, (2021); Liu X., Walsh J., Development of cross-border e-commerce in the context of China's foreign trade strategy, City University Research Journal, 9, 4, pp. 776-787, (2019); Wang Y., Jia F., Schoenherr T., Gong Y., Chen L., Cross-border e-commerce firms as supply chain integrators: The management of three flows, Industrial Marketing Management, 89, pp. 72-88, (2020); Lin C.Y., Knowledge mapping analysis of research frontiers and hotspots from the perspective of China-ASEAN cross-border e-commerce, pp. 556-561; Liao Q., Wang Y., Prospect and challenges of cross-border payment posed by digital currency-from the perspective of blockchain coalition; Hallikainen H., Laukkanen T., Trustworthiness in e-commerce: A replication study of competing measures, Journal of Business Research, 126, pp. 644-653, (2021); Goutam D., Gopalakrishna B.V., Ganguli S., Determinants of customer loyalty dimensions, Journal of Electronic Commerce in Organizations, 19, 1, pp. 1-23, (2021); Shen X.-D., Chen X., Ji R., Wu R.-H., The new ecosystem of cross-border e-commerce among Korea, China and Japan based on blockchain, Journal of Korea Trade, 24, 5, pp. 87-105, (2020); Zhou X., He Y., Study on application of arcs motivational model on cross-border e-commerce course design, pp. 288-293; Dutta P., Choi T.-M., Somani S., Butala R., Blockchain technology in supply chain operations: Applications, challenges and research opportunities, Transportation Research Part E: Logistics and Transportation Review, 142, (2020); Xie T., Zhang C., Zhang Z., Yang K., Utilizing active sensor nodes in smart environments for optimal communication coverage, IEEE Access, 7, (2018); Liu Z., Li Z., A blockchain-based framework of cross-border e-commerce supply chain, International Journal of Information Management, 52, (2019); Liu Z., Li Z., A blockchain-based framework of cross-border e-commerce supply chain, International Journal of Information Management, 52, (2020); Li S., Structure optimization of e-commerce platform based on artificial intelligence and blockchain technology, Wireless Communications and Mobile Computing, 2020, 12, (2020); Liao Q., Shao M., Discussion on payment application in cross-border e-commerce platform from the perspective of blockchain, E3S Web of Conferences, 235, 2, (2021); Niu B., Mu Z., Cao B., Gao J., Should multinational firms implement blockchain to provide quality verification?, Transportation Research Part E: Logistics and Transportation Review, 145, (2021); Fernandes M., Verschoore J.R., How blockchain affects the technological strategy of the financial Industry: An analysis based on knowledge discovery in text, Future Studies Research Journal Trends and Strategies, 12, 2, pp. 311-334, (2020); Zhang C., Xie T., Yang K., Ma H., Xie Y., Xu Y., Luo P., Positioning optimisation based on particle quality prediction in wireless sensor networks, IET Networks, 8, 2, pp. 107-113, (2019); Qiu T., Zhang R., Gao Y., Ripple vs. SWIFT: Transforming cross border remittance using blockchain technology, Procedia Computer Science, 147, pp. 428-434, (2019); Esmaeilzadeh P., Consumers' perceptions of using health information exchanges (HIEs) for research purposes, Information Systems Management, 36, 1-2, pp. 57-77, (2019); Wang L., Zhang C., Chen Q., Liu Z., Liu S., Yang Z., Li H., A communication strategy of proactive nodes based on loop theorem in wireless sensor networks, pp. 160-167; Rahman M.S., Omar A.A., Bhuiyan M., Basu A., Kiyomoto S., Wang G., Accountable cross-border data sharing using blockchain under relaxed trust assumption, IEEE Transactions on Engineering Management, 67, 99, pp. 1-11, (2020); Perri A., Andersson U., Nell P.C., Santangelo G.D., Balancing the trade-off between learning prospects and spillover risks: MNC subsidiaries' vertical linkage patterns in developed countries, Journal of World Business, 48, 4, pp. 503-514, (2013); Li H., Zeng D., Chen L., Chen Q., Wang M., Zhang C., Immune multipath reliable transmission with fault tolerance in wireless sensor networks, pp. 513-517; Shen S.L., Lee M.C., Lin C.Y., The influence of brand image and perceived value of cross-border E-commerce businesses on consumer purchase intention with Thailand's baggo serving as the study object, International Journal of Uncertainty and Innovation Research, 2, 1, pp. 57-71, (2020); Aristovnik A., Matevz M., The Economic and Monetary Union's effect on (international) trade: The case of Slovenia before euro adoption, MPRA Paper, 79, 17445, pp. 26-37, (2009); Farrell D., Kalil T., A strategy for innovation: The administrations comprehensive approach includes research, education, infrastructure, a conducive market environment, and a quest to meet national needs, Research in Dance Education, 14, 3, pp. 201-215, (2010); Chung G.H., Du J., Choi J.N., How do employees adapt to organizational change driven by cross-border M&As? a case in China, Journal of World Business, 49, 1, pp. 78-86, (2014); Chapman D.W., Pekol A., Wilson E., Cross-border university networks as a development strategy: Lessons from three university networks focused on emerging pandemic threats, International Review of Education, 60, 5, pp. 619-637, (2014); Soman D., Zhao M., The fewer the better: Number of goals and savings behavior., Journal of Marketing Research, 48, 6, pp. 944-957, (2011)",null,null,"Hindawi Limited",{"$nulls":5},1.9390114E7,null,null,null,"English","Secur. Commun. Networks","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85122249073"]
["Dua T.R.","Dua, Tilak Raj (55937271500)",5.59372715E10,"Active Infrastructure Sharing – A Key Enabler of Wireless Networks",2021.0,"Journal of Mobile Multimedia",17.0,"2024-03-01",null,141.0,156.0,15.0,0.0,"10.13052/jmm1550-4646.17137","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85102495719&doi=10.13052%2fjmm1550-4646.17137&partnerID=40&md5=2a799725096df652f2e040de6f4961a0","TAIPA, New Delhi, India","Dua T.R., TAIPA, New Delhi, India","Innovations and dynamic technological developments motivated the era of Information and Communications. We have witnessed revolution in communication and pattern as well as in the need of connecting world. Telecom industry is always been the core of digitization. Current pandemic situation has reflected new business and connectivity models and huge dependency on the telecom sector. The telecom network enables virtual work and meetings, education, financial transaction, e commerce, health, social meetings, webinars etc. Apart from the common usage for entertainment in terms of OTT, social media – the telecom network has become fundamental to contactless transactions – telemedicine, contactless courier delivery, online shopping etc. This paper presents an overview of telecom infrastructure model, concept of infrastructure sharing and its advantages. It also discusses various factors affecting infrastructure sharing. © 2021 River Publishers","5G; Infrastructure; IoT; Sharing infrastructure; Telecom",{"$nulls":8},"T.R. Dua; TAIPA, New Delhi, India; email: tilakrajdua@gmail.com",null,"River Publishers",{"$nulls":5},1.5504646E7,null,null,null,"English","J.Mob. Multimedia","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85102495719"]
["Ngah A.H.; Anuar M.M.; Rozar N.N.; Ariza-Montes A.; Araya-Castillo L.; Kim J.J.; Han H.","Ngah, Abdul Hafaz (56074673600); Anuar, Marhana Mohamed (56541155400); Rozar, Norlinda Nohd (57205632205); Ariza-Montes, Antonio (57217331422); Araya-Castillo, Luis (36699152300); Kim, Jinkyung Jenny (57211615845); Han, Heesup (21233360400)","56074673600; 56541155400; 57205632205; 57217331422; 36699152300; 57211615845; 21233360400","Online sellers’ reuse behaviour for third-party logistics services: An innovative model development and E-Commerce",2021.0,"Sustainability (Switzerland)",13.0,14.0,7679.0,null,null,null,17.0,"10.3390/su13147679","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85111142051&doi=10.3390%2fsu13147679&partnerID=40&md5=c9812496e12cfa1270e1391f87585937","Department of Marketing, Faculty of Business, Economics and Social Development, Universiti Malaysia, Kuala Nerus, 21030, Malaysia; Faculty of Maritime Management, Universiti Malaysia Terengganu, Kuala Nerus, 21030, Malaysia; Social Matters Research Group, Universidad Loyola Andalucía C, Escritor Castilla Aguayo, 4, Córdoba, 14004, Spain; Facultad de Economía y Negocios, Universidad Andrés Bello, Santiago de Chile, 7591538, Chile; School of Hotel and Tourism Management, Youngsan University, 142 Bansong Beltway, Haeundae-Gu, Busan, 48015, South Korea; College of Hospitality and Tourism Management, Sejong University, 98 Gunja-Dong, Gwanjin-Gu, Seoul, 05006, South Korea","Ngah A.H., Department of Marketing, Faculty of Business, Economics and Social Development, Universiti Malaysia, Kuala Nerus, 21030, Malaysia; Anuar M.M., Department of Marketing, Faculty of Business, Economics and Social Development, Universiti Malaysia, Kuala Nerus, 21030, Malaysia; Rozar N.N., Faculty of Maritime Management, Universiti Malaysia Terengganu, Kuala Nerus, 21030, Malaysia; Ariza-Montes A., Social Matters Research Group, Universidad Loyola Andalucía C, Escritor Castilla Aguayo, 4, Córdoba, 14004, Spain; Araya-Castillo L., Facultad de Economía y Negocios, Universidad Andrés Bello, Santiago de Chile, 7591538, Chile; Kim J.J., School of Hotel and Tourism Management, Youngsan University, 142 Bansong Beltway, Haeundae-Gu, Busan, 48015, South Korea; Han H., College of Hospitality and Tourism Management, Sejong University, 98 Gunja-Dong, Gwanjin-Gu, Seoul, 05006, South Korea","The increase in customer complaints on the reliability of 3PL services among online sellers has become prominent in the industry, as confirmed by 3PL service providers in Malaysia. The increase in customer complaints increases the tendency to switch to other 3PL service providers. As Asian markets lead the growth of e-commerce, covering approximately 50% of the global e-commerce market, whether the customer will continue to shop online or not is no longer the issue. Although having the proper logistics provider to support online sellers’ business is crucial, most studies have focused on the online shopper’s perspective and employ the service quality theory. Observably, the satisfaction and reuse intention of the 3PL from the online retailer’s perspective is largely neglected. This study identified the factors influencing the satisfaction and reuse intention of 3PL services among online sellers in Malaysia by employing and expanding the stimulus-organism- response (SOR) theory. A purposive sampling method was employed, and the data were gathered via an online survey among online sellers. Additionally, smart partial least squares (SmartPLS) was applied to test the hypotheses. The results indicated that reliability had a positive effect on satisfaction, and satisfaction had a positive relationship with the reuse intention of certain 3PL services. Moreover, satisfaction mediated the relationship between reliability and reuse intention, whereas price fairness strengthened the positive relationship between satisfaction and reuse intention. The findings enhance studies that employed the SOR theory, particularly relating to online sellers’ behaviour on 3PL services. The findings also benefit online sellers and 3PL service providers to create attractive marketing strategies for business sustainability. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.","Mediator; Moderator; Online seller; Reuse intention of third-party logistics services; SOR theory","Malaysia; electronic commerce; human behavior; innovation; Internet; life satisfaction; logistics; market transition; numerical model; reliability analysis; service provision; service quality",{"$nulls":6},"Cichosz M., Wallenburg C.M., Knemeyer A.M., Digital transformation at logistics service providers: Barriers, success factors and leading practices, Int. J. Logist. Manag, 31, pp. 209-238, (2020); Parvin M., Bin Asimiran S.B., Ayub A.F.B.M., Impact of introducing e-commerce on small and medium enterprises—A case on logistics provider, Soc. Bus. Rev, (2021); (2020); (2021); Kamal S.M., Amid Complaints, Pos Malaysia Says Some Issues with “Intermittent System Accessibility” but Tracking Service Fine; Gidener N.G., Deveci D.A., An Analysis of Service Failures and Recovery Strategies in the Third Party Logistics Service Industry, Trans. Marit. Sci, 9, pp. 35-50, (2020); Nielsen V.R., As E-Commerce Start to Mature in Asian Market, Retailers Must Rise to a New Challenges, The end of the Beginning of E-Commerce, pp. 56-57, (2021); Vu T.P., Grant D.B., Menachof D.A., Exploring logistics service quality in Hai Phong, Vietnam, Asian J. Shipp. Logist, 36, pp. 54-64, (2020); Fernandes D.W., Moori R.G., Filho V.A.V., Logistic service quality as a mediator between logistics capabilities and customer satisfaction, Rev. Gestão, 25, pp. 358-372, (2018); Huma S., Ahmed W., Ikram M., Khawaja M.I., The effect of logistics service quality on customer loyalty: Case of logistics service industry, South. Asian J. Bus. Stud, 9, pp. 43-61, (2019); Wang X., Yuen K.F., Wong Y.D., Teo C.-C., Consumer participation in last-mile logistics service: An investigation on cognitions and affects, Int. J. Phys. Distrib. Logist. 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["de Sousa P.R.; Barbosa M.W.; de Oliveira L.K.; de Resende P.T.V.; Rodrigues R.R.; Moura M.T.; Matoso D.","de Sousa, Paulo Renato (55293126200); Barbosa, Marcelo Werneck (57193771373); de Oliveira, Leise Kelli (57194449016); de Resende, Paulo Tarso Vilela (55293019300); Rodrigues, Ricardo Ruiz (57221562731); Moura, Myrian Teixeira (57221563282); Matoso, Daniel (57225283749)","55293126200; 57193771373; 57194449016; 55293019300; 57221562731; 57221563282; 57225283749","Challenges, opportunities, and lessons learned: Sustainability in Brazilian omnichannel retail",2021.0,"Sustainability (Switzerland)",13.0,2.0,666.0,1.0,17.0,16.0,9.0,"10.3390/su13020666","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85099470184&doi=10.3390%2fsu13020666&partnerID=40&md5=1192ef2a2b6568bc88d41a747965bb59","Research and Development Center for Logistics, Supply Chain and Infrastructure, Fundação Dom Cabral, Nova Lima, Minas Gerais, 30140-083, Brazil; Facultad de Administración y Negocios, Universidad Autónoma de Chile, Santiago, 7500912, Chile; Department of Transport and Geotechnical Engineering, Universidade Federal de Minas Gerais, Belo Horizonte, 31270-901, Brazil","de Sousa P.R., Research and Development Center for Logistics, Supply Chain and Infrastructure, Fundação Dom Cabral, Nova Lima, Minas Gerais, 30140-083, Brazil; Barbosa M.W., Facultad de Administración y Negocios, Universidad Autónoma de Chile, Santiago, 7500912, Chile; de Oliveira L.K., Department of Transport and Geotechnical Engineering, Universidade Federal de Minas Gerais, Belo Horizonte, 31270-901, Brazil; de Resende P.T.V., Research and Development Center for Logistics, Supply Chain and Infrastructure, Fundação Dom Cabral, Nova Lima, Minas Gerais, 30140-083, Brazil; Rodrigues R.R., Research and Development Center for Logistics, Supply Chain and Infrastructure, Fundação Dom Cabral, Nova Lima, Minas Gerais, 30140-083, Brazil; Moura M.T., Research and Development Center for Logistics, Supply Chain and Infrastructure, Fundação Dom Cabral, Nova Lima, Minas Gerais, 30140-083, Brazil; Matoso D., Research and Development Center for Logistics, Supply Chain and Infrastructure, Fundação Dom Cabral, Nova Lima, Minas Gerais, 30140-083, Brazil","This paper reports the focus group results administered with top executives of the Brazilian retailers regarding their omnichannel strategies. This study aimed at analyzing the process of implementing omnichannel strategies and identifying contributions omnichannel has to sustainability. Using qualitative exploratory and a case study design to assess three large Brazilian retailers, we collected information concerning omnichannel implementation associated with processes, technologies, and organizational structure. This study was conducted with top executives in Brazil. Results suggest that the most viable solution, given a company’s investment capacity, is implementing an e-commerce platform that results in greater integration, profitability, and sustainability of the whole chain. A discussion on the benefits and outcomes related to the sustainable performance of such companies is also presented. This study answers calls for more research on the retail sector in Latin American countries. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.","Information technology; Logistics; Omnichannel; Supply chain; Sustainability",{"$nulls":7},"Cottet P., Lichtle M.C., Plichon V., The role of value in services: A study in a retail environment, J. Consum. Mark, 23, pp. 219-227, (2006); Von Briel F., The future of omnichannel retail: A four-stage Delphi study, Technol. Forecast. Soc. Chang, 132, pp. 217-229, (2018); Grewal D., Roggeveen A.L., Nordfalt J., The Future of Retailing, J. Retail, 93, pp. 1-6, (2017); Zhang J., Farris P.W., Irvin J.W., Kushwaha T., Steenburgh T.J., Weitz B.A., Crafting integrated multichannel retailing strategies, J. Interact. Mark, 24, pp. 168-180, (2010); Li Y., Liu H., Lim E.T.K., Mein J., Yang F., Lee M.K.O., Customer’s reaction to cross-channel integration in omnichannel retailing: The mediating roles of retailer uncertainty, identity attractiveness, and switching costs, Decis. 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Manag, 55, (2020)","P.R. de Sousa; Research and Development Center for Logistics, Supply Chain and Infrastructure, Fundação Dom Cabral, Nova Lima, Minas Gerais, 30140-083, Brazil; email: paulorenato@fdc.org.br",null,"MDPI AG",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85099470184"]
["Tang X.","Tang, Xiuli (56327181400)",5.63271814E10,"Notice of Violation of IEEE Publication Principles: Research on Logistics Information Collection Based on Image Recognition",2021.0,"IEEE Access",{"$nulls":6},1.0,"10.1109/ACCESS.2020.3000038","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85172602699&doi=10.1109%2fACCESS.2020.3000038&partnerID=40&md5=16855e4de87172a801a91647e65251e5","School of Logistics, Beijing Wuzi University, Beijing,101149, P. R. China. (e-mail: xianyu9186900@163.com)","Tang X., School of Logistics, Beijing Wuzi University, Beijing,101149, P. R. China. (e-mail: xianyu9186900@163.com)","The logistics industry is an important part of the national economy and social life. With the rapid rise of e-commerce, the logistics industry is developing rapidly, and there are many problems due to the low level of automation in the sorting process. Therefore, improving the level of automation in the express sorting process is crucial to improving the efficiency of express sorting. In view of the above problems, this paper builds a logistics information collection model based on image recognition based on logistics information collection, combined with convolutional neural network for logistics image recognition. First, the current application status of information collection and image recognition in the logistics industry is described. Secondly, based on the existing image recognition technology, the convolutional neural network algorithm is used to quickly identify and collect information on logistics images. Finally, the case analysis and performance test results illustrate the superiority of the realized logistics information collection technology. This method can provide a scientific reference and basis for the modern logistics industry to adopt image recognition technology. Author",null,"Convolution; Neural networks; Convolutional neural network; E- commerces; Image recognition technology; Information collections; Levels of automation; Logistics industry; Logistics information; National economy; Social life; Sorting process; Image recognition",{"$nulls":9},"Institute of Electrical and Electronics Engineers Inc.",{"$nulls":5},2.1693536E7,null,null,null,"English","IEEE Access","Article","Article in press","All Open Access; Gold Open Access","Scopus","2-s2.0-85172602699"]
["Zandi G.; Torabi R.; Mohammad M.A.; Dan X.Y.","Zandi, GholamReza (55091974300); Torabi, Rezvan (57221541878); Mohammad, Mohammad Amin (57206934238); Dan, Xu Yi (57367400900)","55091974300; 57221541878; 57206934238; 57367400900","Customer’s Satisfaction via Online Shopping Environment: The Case of China",2021.0,"Journal of Information Technology Management",13.0,3.0,null,16.0,32.0,16.0,2.0,"10.22059/JITM.2021.83110","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85120882563&doi=10.22059%2fJITM.2021.83110&partnerID=40&md5=1233103bc17fd7a8294c7324cf7c7bc6","University Kuala Lumpur (UniKL) Business School, Malaysia; Graduate School of Business, SEGi University, Malaysia","Zandi G., University Kuala Lumpur (UniKL) Business School, Malaysia; Torabi R., Graduate School of Business, SEGi University, Malaysia; Mohammad M.A., University Kuala Lumpur (UniKL) Business School, Malaysia; Dan X.Y., University Kuala Lumpur (UniKL) Business School, Malaysia","The increase in Internet technology popularity due to the advancement of information technology is bound to rise at an unprecedented pace in China. The development of E-commerce has become an important part of people everyday lives in certain sectors of business activities such as online advertising, online shopping, online promotional advisory and service. This study examines critical factors in online shopping that affect customer satisfaction. The philosophy of positivism was used to evaluate the online shopping behaviour in a Chinese context. The philosophy defines a structural method that combines logical deduction with accurate and well-known observation of personal character and behaviour. The data on the level of customer satisfaction collected by E-mail and survey. The results of the validity and reliability test, Pearson's correlation and Multiple Linear Regression analyses suggested that online shopping websites’ privacy, delivery system and service quality would improve customer satisfaction in China. The Companies must carefully develop the E-commerce environment in terms of customer behaviour in China, emphasizing the factors that have a significant impact on their online customer satisfaction. Copyright © 2021, GholamReza Zandi, Rezvan Torabi, Mohammad Mohammad Amin, Xu Yi Dan","Chinese context; Customer Satisfaction; E-commerce; Internet; Technology",{"$nulls":7},"Abojeib M., Habib F., Blockchain for Islamic social responsibility institutions, Fintech as a Disruptive Technology for Financial Institutions, pp. 221-240, (2019); Akamai online retail performance report: Milliseconds are critical, (2017); Aslam W., Hussain A., Farhat K., Arif I., Underlying Factors Influencing Consumers’ Trust and Loyalty in E-commerce, Business Perspectives and Research, (2019); Bachrach D. G., Ogilvie J., Rapp A., Calamusa J., More than a showroom: Strategies for winning back on-line shoppers, (2016); Chaing, Dholakia, Factor Driving Consumer Intention to Shop Online: An Empirical Investigation, Journal of Consumer Psychology, 13, pp. 177-183, (2014); Chen Yan, Fan, Phosphorus-doped carbon derived from cellulose phosphate as efficient catalyst for air-cathode in microbial fuel cells, (2015); The 33rd Statistical Report on Internet Development in China, (2014); Delone W. H., McLean E. R., (2003) and Hu, M., Rabinovich, E., & Hou, H. (2015), Information system success - The quest for the dependent variable, Information Systems Research, 3, 1, pp. p60-p97; Ecommerce growth fell 26% in 2017: Forrester Research - The Economic Times, (2018); Gerbing D.W., Anderson, (2015) Structure Equation Modelling in Practice: A Review and Recommended Two-Step Approach, Psychological Bulletin, 103, pp. 411-423, (1988); Gibbs Graham R.; Giese J. L., Cote J. A., Defining consumer satisfaction, Academy of Marketing Science Review, (2016); Goldstuck, Steyn 2The Intrauterine Device in Women with Diabetes Mellitus Type I and II: A Systematic Review, (2013); Hong W., Zheng C., Wu L., Pu X., Analyzing the Relationship between Consumer Satisfaction and Fresh E-Commerce Logistics Service Using Text Mining Techniques, Sustainability, 11, 13, (2019); Hsieh, Et al., Online Shopping-A Literature Review Sanjay Kumar Assistant ProfessorBRCMCET, (2013); Number of Internet Users (2015) - Internet Live Stats, (2015); Ammari, Radicalising the marketing of higher education: learning from student-generated social media data, (2016); King W., He J., A Meta-Analysis of the Technology Acceptance Model, Information and Management, 43, pp. 740-755, (2006); Khairudin S. M. H. H. S., Amin M., TOWARDS ECONOMIC GROWTH: THE IMPACT OF INFORMATION TECHNOLOGY ON PERFORMANCE OF SMES, Journal of Security & Sustainability Issues, 9, 1, (2019); Malhotra N., Review of marketing research, (2013); Mathewson J., Moran M, Outside-In Marketing: Using Big Data to guide your content, (2016); Mohammed A., Determinants of young consumers' online shopping intention, International Journal of Academic Research, 6, 1, pp. 475-482, (2014); Hasim Muhammad Asyraf, Shabi Khairul shahida, Shamsudin Mohd Farid, Ali Aeshah Mohd, The Relationship between Sales Promotions and Online Impulse Buying in Malaysia, Opcion, 34, 16, pp. 295-308, (2018); Nair R. P., Will Indian e-commerce ever match up to the Chinese dragon?, (2017); Rahman Nik Khadijah Nik Abdul, Zandi GholamReza, Yuan Liang, The Repurchase Intention Development: The Case of Birds Nest Market Consumers in China, International Journal of Engineering & Technology, 7, 4, (2018); Okeke T., Customer Satisfaction with Online Retail Transactions, Customer Relationship Management and IT, (2019); Rajah R. K., Customer Satisfaction towards Online Shopping, (2018); Iyer Rajesh, Jacqueline Eastman, The Elderly and Their Attitude Toward s the Internet: The Impact of Internet use, Purchases, and Comparison Shopping, Journal of Marketing Theory and Practice, 14, 1, (2014); Rita P., Oliveira T., Farisa A., The impact of e-service quality and customer satisfaction on customer behavior in online shopping, Heliyon, 5, 10, (2019); Why eCommerce in India is diminutive when compared to countries like China & Brazil, (2016); Smith H.K., Roberts I.J.H., Allen M.J., Connolly J.B., Moffat K.G., O'Kane C.J., (1996); Sopadjieva E., Dholakia U., Benjamin B., A study of 46,000 shoppers shows that omnichannel retailing works, Harvard Business Review, 3, (2017); Sushma U. N., Morgan Stanley explains why India’s e-commerce market is a hot investment opportunity, (2017); Sushma U. N., Morgan Stanley explains why India’s e-commerce market is a hot investment opportunity, (2017); Team C., Moda, Tmall Virtual Dressing Room Debuted, (2015); Venkatesh Michael G. Morris, Davis Gordon B., Davis Fred D., MIS Quarterly, 27, 3, pp. 425-478, (2003); Wang B., Alibaba insider explains why Amazon lost in China and how it applies to India’s current ecommerce rise, (2017); Wilson N., Christella R., An empirical research of factors affecting customer satisfaction: A case of the Indonesian e-commerce industry, DeReMa Jurnal Manajemen, 14, 1, pp. 21-44, (2019); GholamReza Zandi, Aslam Ayesha, Nasir Muhammad Umar, Zhang Yajing, Smart Phones and Brand Equity: A Study of Malaysian Consumer Buying Behavior, International Journal of Engineering & Technology, 7, 4, (2018); GholamReza Zandi, Mansori Shaheen, Hai Ong Boon, The Effect of Demographic Variables and Ownership on Credit Card Market in Malaysia, International Journal of Financial Research (IJFR), 10, 5, (2019)","R. Torabi; Graduate School of Business, SEGi University, Malaysia; email: torabi.economic@gmail.com",null,"University of Tehran",{"$nulls":5},2.0085893E7,null,null,null,"English","J. Inf. Technol. Manag.","Article","Final",null,"Scopus","2-s2.0-85120882563"]
["Ali S.; Khalid N.; Javed H.M.U.; Islam D.M.Z.","Ali, Saqib (57207793882); Khalid, Nadeem (57190303279); Javed, Hafiz Muhammad Usama (57221205336); Islam, Dewan Md. Zahurul (9637465300)","57207793882; 57190303279; 57221205336; 9637465300","Consumer adoption of online food delivery ordering (Ofdo) services in pakistan: The impact of the covid-19 pandemic situation",2021.0,"Journal of Open Innovation: Technology, Market, and Complexity",7.0,1.0,10.0,1.0,23.0,22.0,105.0,"10.3390/joitmc7010010","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85099411986&doi=10.3390%2fjoitmc7010010&partnerID=40&md5=df114fd27a0af54728e69b2caa3a61a9","Department of Management Sciences, COMSATS University Islamabad, Sahiwal, 5700, Pakistan; Executive Education Center, KIMEP University, Almaty, 050010, Kazakhstan; Bang College of Business, KIMEP University, Almaty, 050010, Kazakhstan","Ali S., Department of Management Sciences, COMSATS University Islamabad, Sahiwal, 5700, Pakistan; Khalid N., Executive Education Center, KIMEP University, Almaty, 050010, Kazakhstan; Javed H.M.U., Department of Management Sciences, COMSATS University Islamabad, Sahiwal, 5700, Pakistan; Islam D.M.Z., Bang College of Business, KIMEP University, Almaty, 050010, Kazakhstan","Evolving internet technology has brought about changes in consumer lifestyle and in-creased online shopping. Grounded in the theory of technology readiness (TR), this study aims to examine the effect of factors such as optimism, innovativeness, insecurity, and discomfort that may motivate consumers’ adoption intentions towards online food delivery ordering (OFDO) services. Ad-ditionally, this study intends to investigate the moderating role of situational influences (COVID-19) in affecting such an online behavior. By using survey methods, a total of 439 usable responses were gathered through an online survey. Data were analyzed by using Partial least square (PLS) and multigroup analysis (MGA) techniques. The results revealed that optimism and innovativeness have positive influences on adoption intentions while insecurity and discomfort have negative influences on adoption intentions in the use of OFDO services. The results also supported the moderating role of situational influences such as the COVID-19 pandemic. Furthermore, the PLS-MGA results indicate that the effects of optimism and innovativeness are stronger in demographic variables, i.e., young, male, high income, high education, etc. On the contrary, the effects of insecurity and discomfort are stronger for the opposite, i.e., elder, female, low income, low education, etc. Finally, this paper depicts remarkable insights for researchers, practitioners, service providers, and marketers. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.","Online food delivery ordering (OFDO) services; Situational influences COVID-19; Technology readiness (TR) model",{"$nulls":7},{"$cut":{"chars":21185,"head":"Suhartanto D., Helmi Ali M., Tan K.H., Sjahroeddin F., Kusdibyo L., Loyalty toward online food delivery service: The role of e-service quality and food quality, J. Foodserv. Bus. Res, 22, pp. 81-97, (2019); Sjahroeddin F., The Role of E-S-Qual and Food Quality on Customer Satisfaction in Online Food Delivery Service, (2018); Retail E-Commerce Sales Worldwide from 2014 to 2023. 2020; Abramovich G., 15 Mind-Blowing Stats about Online Shopping in 2019, (2019); Rahman M.A., Islam M.A., Esha B.H., Sultana N., Chakravorty S., Consumer buying behavior towards online shopping: An empirical study on Dhaka city, Bangladesh, Cogent Bus. Manag, 5, pp. 1-22, (2018); Bauboniene Z., Guleviciute G., E-commerce factors influencing consumers ‘online shopping decision, Soc. Technol, 5, pp. 74-81, (2015); Wen C., Prybutok V.R., Xu C., An integrated model for customer online repurchase intention, J. Comput. Inf. Syst, 52, pp. 14-23, (2011); Jusoh Z.M., Ling G.H., Factors influencing consumers’ attitude towards e-commerce purchases through online shopping, Int. J. Humanit. Soc. Sci, 2, pp. 223-230, (2012); Roh M., Park K., Adoption of O2O food delivery services in South Korea: The moderating role of moral obligation in meal preparation, Int. J. Inf. Manag, 47, pp. 262-273, (2019); Gao S., Tang O., Wang H., Yin P., Identifying competitors through comparative relation mining of online reviews in the restaurant industry, Int. J. Hosp. Manag, 71, pp. 19-32, (2018); Yeo V.C.S., Goh S.K., Rezaei S., Consumer experiences, attitude and behavioral intention toward online food delivery (OFD) services, J. Retail. Consum. Serv, 35, pp. 150-162, (2017); Dospinescu N., Dospinescu O., Tatarusanu M., Analysis of the Influence Factors on the Reputation of Food-Delivery Companies: Evidence from Romania, Sustainability, 12, (2020); Online Food Delivery, (2020); Gunden N., Morosan C., DeFranco A., Consumers’ intentions to use online food delivery systems in the USA, Int. J. Contemp. Hosp. Manag, 32, pp. 1325-1345, (2020); Wei L.H., Osman M.A., Zakaria N., Bo T., Adoption of e-commerce online shopping in Malaysia, Proceedings of the IEEE 7th International Conference on E-Business Engineering, pp. 140-143; Digital 2020: Pakistan—DataReportal–Global Digital Insights, (2020); How did you order/deliver food at home, (2020); Belanche D., Flavian M., Perez-Rueda A., Mobile Apps Use and WOM in the Food Delivery Sector: The Role of Planned Behavior, Perceived Security and Customer Lifestyle Compatibility, Sustainability, 12, (2020); Ali S., Ullah H., Akbar M., Akhtar W., Zahid H., Determinants of Consumer Intentions to Purchase Energy-Saving Household Products in Pakistan, Sustainability, 11, (2019); Parasuraman A., Colby C.L., An Updated and Streamlined Technology Readiness Index, J. Serv. Res, 18, pp. 59-74, (2015); Annaraud K., Berezina K., Predicting satisfaction and intentions to use online food delivery: What really makes a difference?, J. Foodserv. Bus. Res, 23, pp. 305-323, (2020); Ray A., Dhir A., Bala P.K., Kaur P., Why do people use food delivery apps (FDA)? A uses and gratification theory perspective, J. Retail. Consum. Serv, 51, pp. 221-230, (2019); Sultan P., Tarafder T., Pearson D., Henryks J., Intention-behaviour gap and perceived behavioural control-behaviour gap in theory of planned behaviour: Moderating roles of communication, satisfaction and trust in organic food consumption, Food Qual. Prefer, 81, (2020); Hassan L.M., Shiu E., Shaw D., Who says there is an intention–behaviour gap? Assessing the empirical evidence of an intention–behaviour gap in ethical consumption, J. Bus. Ethics, 136, pp. 219-236, (2016); Tan B., Understanding consumer ethical decision making with respect to purchase of pirated software, J. Consum. Mark, 19, pp. 96-111, (2002); Belk R., Situation Variables and Consumer Behavior, J. Consum. Res, 2, pp. 157-164, (1975); Chocarro R., Cortinas M., Villanueva M.L., Situational variables in online versus offline channel choice, Electron. Commer. Res. Appl, 12, pp. 347-361, (2013); Hand C., Riley F.D.O., Harris P., Singh J., Rettie R., O"}},"H.M.U. Javed; Department of Management Sciences, COMSATS University Islamabad, Sahiwal, 5700, Pakistan; email: usamajaved943@gmail.com",null,"Multidisciplinary Digital Publishing Institute (MDPI)",{"$nulls":5},2.1998531E7,null,null,null,"English","J. Open Innov.: Technol. Mark. Complex.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85099411986"]
["Schoeman A.; Bick G.; Barnardo C.","Schoeman, Aldi (57226666170); Bick, Geoff (24376346900); Barnardo, Claire (57215501362)","57226666170; 24376346900; 57215501362","Cape union mart: digital transformation and customer experience during a crisis",2021.0,"Emerald Emerging Markets Case Studies",11.0,3.0,null,1.0,47.0,46.0,1.0,"10.1108/EEMCS-04-2021-0116","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85112297605&doi=10.1108%2fEEMCS-04-2021-0116&partnerID=40&md5=36412e7312655b768a109f9ce5faaa53","Graduate School of Business, University of Cape Town, Cape Town, South Africa; Case Writing Centre, Graduate School of Business, University of Cape Town, Cape Town, South Africa","Schoeman A., Graduate School of Business, University of Cape Town, Cape Town, South Africa; Bick G., Graduate School of Business, University of Cape Town, Cape Town, South Africa; Barnardo C., Case Writing Centre, Graduate School of Business, University of Cape Town, Cape Town, South Africa","Learning outcomes: The learning outcomes of this paper are as follows: to define the scope of digital customer experience, why it is important and how it can be used to create a competitive advantage, to evaluate the various challenges for traditional retail businesses that undertake a digital transformation strategy, to critically assess a chosen digital transformation strategy, to identify the key features of a successful digital transformation strategy and to develop a crisis communication strategy. Case overview/synopsis: The Cape Union Mart Group is a typical apparel retail company faced with the challenge of improving the digital customer experience and accelerating digital transformation in the wake of the Covid-19 pandemic. Due to the pandemic, the demand for e-commerce increased dramatically. However, strict lockdown regulations forbade the delivery of clothing. When the lockdown was lifted, there was an order backlog of four weeks. To add to this challenge, the Group was in the midst of a technology update. They moved their entire information technology (IT) backbone to three clouds and, just a week before the lockdown, launched five new websites for its five different retail chains. The ultimate goal with the technology update was to give the company a competitive advantage by improving the customer experience. However, having to do this at an accelerated pace due to the pandemic posed a number of challenges. The case provides a vivid description of how the crisis unfolded and how Grant De Waal-Dubla, the executive of e-commerce and IT at the Group and his team responded to the challenges, together with the marketing team. Based on the success of e-commerce during the lockdown, the owners of the business then tasked Grant with new, aggressive growth targets. Whilst dealing with the aftermath of the lockdown, Grant’s main challenge is to develop a strategy to reach those targets. Complexity academic level: The primary target audience for this case are postgraduate students enrolled on programmes such as Master of Business Administration or specialist masters in a business field such as marketing or strategy and also for Executive Education courses. Supplementary materials: Teaching notes are available for educators only. Subject code: CSS 11: Strategy. © 2021, Emerald Publishing Limited.","Crisis management; Digital marketing; E-commerce; Marketing; Strategy",{"$nulls":7},"Ahlfelt J., Personal communication, (2020); Erasmus M., Really dissapointed [sic] with the service I’m getting ffron [sic] your courier company. I’ve been on the phone 4 times yesterday….holding [comment], (2020); Ferreira E., I have the same issue – I asked to remove a non essential [sic] item so I can get my boots and [comment], (2020); Gonsalves N., I have been trying to get hold of someone from your customer services department. I have sent 3 mails but [comment], (2020); Gonsalves N., I got my “first lockdown” delivery today, from all the way back in April, I really appreciate a gift to [comment], (2020); Hi sphephelo shange – Thanks for your inquiry! We can’t wait to get our baby clothes into the hands of our [comment], (2020); Littlewood K., Personal communication, (2020); Rhodes M., So dissappointed [sic]. placed an order weeks ago, and people who have placed an order a few days ago have already [comment], (2020); Shange S., Hi will your store be opened Monday?, (2020); Shange S., Thanks keedo my 24months old baby needs winter clothes, this is sad hopefully the covid 19 will end soon [comment], (2020); Van der Westhuizen J., So disappointed with your customer service! it’s one thing having a backlog on orders but you are blatantly ignoring your [comment], (2020)","C. Barnardo; Case Writing Centre, Graduate School of Business, University of Cape Town, Cape Town, South Africa; email: claire.barnardo@gsb.uct.ac.za",null,"Emerald Group Holdings Ltd.",{"$nulls":5},2.0450621E7,null,null,null,"English","Emerald Emerg. Mark. Case Stud.","Article","Final",null,"Scopus","2-s2.0-85112297605"]
["Kim W.; Wang X.C.","Kim, Woojung (57226057810); Wang, Xiaokun (Cara) (55482185200)","57226057810; 55482185200","To be online or in-store: Analysis of retail, grocery, and food shopping in New York city",2021.0,"Transportation Research Part C: Emerging Technologies",126.0,null,103052.0,null,null,null,26.0,"10.1016/j.trc.2021.103052","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85104502874&doi=10.1016%2fj.trc.2021.103052&partnerID=40&md5=f7131e94115a37fae5f2725d494ac2ef","Department of Civil and Environmental Engineering, Rensselaer Polytechnic Institute, 110 8th Street, 5304 JEC Building, Troy, 12180, NY, United States; Department of Civil and Environmental Engineering, Rensselaer Polytechnic Institute, 110 8th Street, 4032 JEC Building, Troy, 12180, NY, United States","Kim W., Department of Civil and Environmental Engineering, Rensselaer Polytechnic Institute, 110 8th Street, 5304 JEC Building, Troy, 12180, NY, United States; Wang X.C., Department of Civil and Environmental Engineering, Rensselaer Polytechnic Institute, 110 8th Street, 4032 JEC Building, Troy, 12180, NY, United States","With advances in information technology, online shopping for a parcel (retail), grocery, and food (i.e. prepared meal) have become a part of daily life and they are expected to continue to grow in the future. Accordingly, shopping behaviors, i.e. shopping channels, are becoming more complex than ever. However, the current research focus is still mainly on traditional parcel delivery and little is known for food and grocery deliveries and their impacts on transportation systems. To have a better understanding of deliveries and their impacts on transportation systems, using the survey data from NYC DOT Citywide Mobility Survey in 2018, this paper investigated (a) factors affecting the three types of deliveries (retail, grocery, and food) by developing a seemingly unrelated model, and (b) the relationships between deliveries and in-store shopping trips by different modes using multiple simultaneous equations models. The results showed that factors affecting deliveries vary by the type of delivery, and the three deliveries are positively correlated by common unobserved factors. In addition, the relationships between delivery and shopping trip vary not only by delivery type but also by trip mode (driving/walking). The findings would provide valuable insights into travel demand modeling and curbside management. © 2021 Elsevier Ltd","Food delivery; Grocery delivery; In-store trip; Online shopping; Parcel delivery; Shopping behavior","New York [New York (STT)]; New York [United States]; United States; Sales; Surveys; Daily lives; Food delivery; Grocery delivery; In-store trip; New York city; Online shopping; Parcel delivery; Shopping behaviour; Shopping trip; Transportation system; food market; information technology; Internet; mobility; retailing; shopping activity; survey; transportation system; Electronic commerce",{"$nulls":6},"Alho A.R., Silva J.D.A., Modeling retail establishments’ freight trip generation: a comparison of methodologies to predict total weekly deliveries, Transportation, 44, 5, pp. 1195-1212, (2017); Baum C., (2016); Barrett G., Hamermesh D., Labor supply elasticities: overcoming nonclassical measurement error using more accurate hours data, J. Human Resour., 54, 1, pp. 255-265, (2019); Bound J., Brown C., Mathiowetz N., Measurement error in survey data, Handbook of econometrics, 5, pp. 3705-3843, (2001); (2014); Campbell S., Holguin-Veras J., Ramirez-Rios D.G., Gonzalez-Calderon C., Kalahasthi L., Wojtowicz J., Freight and service parking needs and the role of demand management, Eur. Transp. Res. Rev., 10, 2, (2018); Cao X., Douma F., Cleaveland F., Influence of E-shopping on shopping travel: evidence from Minnesota's Twin Cities, Transp. Res. Record, 2157, pp. 147-154, (2010); Cao X., Xu Z., Douma F., The interactions between e-shopping and traditional in-store shopping: an application of structural equations model, Transportation, 39, 5, pp. 957-974, (2012); Chen Q., Conway A., Cheng J., Parking for residential delivery in New York City: regulations and behavior, Transp. Policy, 54, pp. 53-60, (2017); Cohen L., curbFlow’ s Curb Management Program in Washington, (2019); Cuba J., (2019); Cuba J., NYPD: Bike Injuries Are Up 43 Percent During Coronavirus Crisis, Streetsblog NYC, (2020); Dias F.F., Lavieri P.S., Sharda S., Khoeini S., Bhat C.R., Pendyala R.M., Pinjari A.R., Ramadurai G., Srinivasan K.K., A comparison of online and in-person activity engagement: the case of shopping and eating meals, Transp. Res. Part C: Emerg. Technol., 114, pp. 643-656, (2020); Escand P., Chen Q., Conway A., Parking conditions for residential delivery in New York City: a case study analysis, Transportation Research Board 97th Annual Meeting, (2018); Fabusuyi T., Twumasi-Boakye R., Broaddus A., Fishelson J., Hampshire R.C., Estimating small area demand for online package delivery, Transportation Research Board 99th Annual Meeting, (2020); Farag S., Krizek K.J., Dijst M., E-shopping and its relationship with in-store shopping: empirical evidence from the Netherlands and the USA, Transp. Rev., 26, 1, pp. 43-61, (2006); Farag S., Schwanen T., Dijst M., Empirical investigation of online searching and buying and their relationship to shopping trips, Transp. Res. Rec., 1926, pp. 242-251, (2005); Farag S., Schwanen T., Dijst M., Faber J., Shopping online and/or in-store? A structural equation model of the relationships between e-shopping and in-store shopping, Transp. Res. Part A: Policy Pract., 41, 2, pp. 125-141, (2007); Farag S., Weltevreden J., van Rietbergen T., Dijst M., van Oort F., E-shopping in the Netherlands: does geography matter?, Environ. Plann. B: Plann. Design, 33, 1, pp. 59-74, (2006); (2017); Ferrell C.E., Home-based teleshoppers and shopping travel: do teleshoppers travel less?, Transp. Res. Rec., 1894, pp. 241-248, (2004); Han L., Chin S.-M., Franzese O., Hwang H., Estimating the impact of pickup- and delivery-related illegal parking activities on traffic, Transp. Res. Rec.: J. Transp. Res. Board, 1906, pp. 49-55, (2005); Hand C., Riley F.D.O., Harris P., Singh J., Rettie R., Online grocery shopping: the influence of situational factors, Eur. J. Market., 43, 9, pp. 1205-1219, (2009); Henao A., Marshall W.E., The impact of ride-hailing on vehicle miles traveled, Transportation, 46, 6, pp. 2173-2194, (2019); Hiser J., Nayga R.M., Capps O., An exploratory analysis of familiarity and willingness to use online food shopping services in a local area of texas, J. Food Distrib. Res., 30, 1, pp. 78-90, (1999); Holguin-Veras J., Jaller M., Destro L., Ban X., Lawson C., Levinson H.S., Freight generation, freight trip generation, and perils of using constant trip rates, Transp. Res. 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Technol., 58, pp. 46-55, (2015); White G.K., Factors Influencing Consumers’ Likelihood of Purchasing Specialty Food and Drink Products On-line: Results of Consumer Reviews of 12 Selected Sites, J. Food Distrib. Res., (1996); Zellner A., An efficient method of estimating seemingly unrelated regressions and tests for aggregation bias, J. Am. Stat. Assoc., 57, 298, (1962); Zhen F., Cao X., Mokhtarian P.L., Xi G., Associations between online purchasing and store purchasing for four types of products in Nanjing, China, Transp. Res. Rec., 2566, 2566, pp. 93-101, (2016); Zhou Y., Wang X.C., Explore the relationship between online shopping and shopping trips: an analysis with the 2009 NHTS data, Transp. Res. Part A: Policy Pract., 70, pp. 1-9, (2014)","X.C. Wang; Department of Civil and Environmental Engineering, Rensselaer Polytechnic Institute, Troy, 110 8th Street, 4032 JEC Building, 12180, United States; email: wangx18@rpi.edu",null,"Elsevier Ltd",{"$nulls":5},"0968090X",null,null,null,"English","Transp. Res. Part C Emerg. Technol.","Article","Final",null,"Scopus","2-s2.0-85104502874"]
["Xu S.; Chen J.; Wu M.; Zhao C.","Xu, Shiyan (57217128533); Chen, Jun (57221655126); Wu, Maoguo (56920995500); Zhao, Chenyang (57217134463)","57217128533; 57221655126; 56920995500; 57217134463","E-Commerce supply chain process optimization based on whole-process sharing of internet of things identification technology",2021.0,"CMES - Computer Modeling in Engineering and Sciences",126.0,2.0,null,843.0,854.0,11.0,12.0,"10.32604/cmes.2021.014265","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85101076333&doi=10.32604%2fcmes.2021.014265&partnerID=40&md5=89e5155b22e976fe39220be94d124f05","School of Economics and Management, Tongji University, Shanghai, 200092, China; SILC Business School, Shanghai University, Shanghai, 201800, China","Xu S., School of Economics and Management, Tongji University, Shanghai, 200092, China; Chen J., SILC Business School, Shanghai University, Shanghai, 201800, China; Wu M., SILC Business School, Shanghai University, Shanghai, 201800, China; Zhao C., SILC Business School, Shanghai University, Shanghai, 201800, China","With in-depth development of the Internet of Things (IoT) in various industries, the informatization process of various industries has also entered the fast lane. This article aims to solve the supply chain process problem in e-commerce, focusing on the specific application of Internet of Things technology in e-commerce. Warehousing logistics is an important link in today's e-commerce transactions. This article proposes a distributed analysis method for RFID-based e-commerce warehousing process optimization and an e-commerce supply chain management process based on Internet of Things technology. This article first introduces the advantages and disadvantages of shared IoT identification technology and the IoT resource sharing platform based on the three-layer abstract data model and representational state transfer (REST) style. Combining actual IoT applications and the characteristics of an existing platform, a REST-based IoT resource sharing platform is proposed. Combined with actual projects, a REST-based IoT resource sharing platform was built, and key technology experiments were conducted for verification. Finally, optimizing the e-commerce supply chain management process under Internet of Things technology and explaining the advantages of optimized e-commerce supply chain management are discussed. Research on this subject provides a theoretical basis for the application of the Internet of Things in e-commerce and has practical significance and practical value for managing service capabilities and service levels in e-commerce. © This work is licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.","E-commerce; Optimization; Shared IoT identification technology; Supply chain process","Electronic commerce; Optimization; Process control; Supply chain management; Warehouses; Distributed analysis; E-commerce transactions; Identification technology; Internet of thing (IOT); Internet of things technologies; Representational state transfer; Service capability; Supply chain process; Internet of things",{"$nulls":6},"Jin M., Wang H., Zhang Q., Zeng Y., Supply chain optimization based on chain management and mass customization, Information Systems and e-Business Management, 2, 1, pp. 647-664, (2020); Li D., Perspective for smart factory in petrochemical industry, Computers & Chemical Engineering, 9, 1, pp. 136-148, (2016); Liu L., Geng K., Intelligent storage system architecture research based on the Internet of Things, International Conference on Industrial IoT Technologies and Applications, pp. 247-256, (2016); Liu C., Feng Y., Lin D., Wu L., Guo M., IoT based laundry services: An application of big data analytics, intelligent logistics management, and machine learning techniques, International Journal of Production Research, 58, 17, pp. 5113-5131, (2020); Shang X., Zhang R., Zhu X., Zhou Q., Design theory, modelling and the application for the Internet of Things service, Enterprise Information Systems, 10, 3, pp. 249-267, (2016); Ruan J., Shi Y., Monitoring and assessing fruit freshness in IoT-based e-commerce delivery using scenario analysis and interval number approaches, Information Sciences, 373, 3, pp. 557-570, (2016); He Y., Zhou F., Qi M., Wang X., Joint distribution: Service paradigm, key technologies and its application in the context of Chinese express industry, International Journal of Logistics Research and Applications, 23, 3, pp. 211-227, (2020); Wang J., Lim M. K., Zhan Y., Wang X., An intelligent logistics service system for enhancing dispatching operations in an IoT environment, Transportation Research Part E: Logistics and Transportation Review, 13, 5, pp. 101-105, (2020); Li B., Ling Y., Tian M., Zheng S., Design and implementation of sugarcane growth monitoring system based on RFID and ZigBee, International Journal of Online and Biomedical Engineering, 14, 3, pp. 96-106, (2018); Zhou Z., Pei J., Liu X., Fu H., Pardalos P. M., Effects of resource occupation and decision authority decentralisation on performance of the IoT-based virtual enterprise in central China, International Journal of Production, 2, 1, pp. 1-17, (2020); Zhang J., The integration of technology and the publishing industry in China, Publishing Research Quarterly, 33, 2, pp. 173-182, (2017); Ping H., Wang J., Ma Z., Du Y., Mini-review of application of IoT technology in monitoring agricultural products quality and safety, International Journal of Agricultural and Biological Engineering, 11, 5, pp. 35-45, (2018); Qi Q., Tao F., Digital twin and big data towards smart manufacturing and industry 4.0:360 degree comparison, IEEE Access, 6, 1, pp. 3585-3593, (2018); Wu W., Cheung C., Lo S. Y., Zhong R. Y., Huang G. Q., An IoT-enabled real-time logistics system for a third party company: A case study, Procedia Manufacturing, 4, 9, pp. 16-23, (2020); Zheng Z., Xie S., Dai H. N., Chen X., Wang H., Blockchain challenges and opportunities: A survey, International Journal of Web and Grid Services, 14, 4, pp. 352-375, (2018); Li Z., A data classification algorithm of internet of things based on neural network, International Journal of Online and Biomedical Engineering, 13, 9, pp. 28-37, (2017); Yang A., Li Y., Liu C., Li J., Zhang Y., Et al., Research on logistics supply chain of iron and steel enterprises based on block chain technology, Future Generation Computer Systems, 10, 1, pp. 635-645, (2019); Ding Y., Brief analysis about digital twin supply chain model and application, Industrial Engineering and Innovation Management, 2, 1, pp. 14-23, (2019); Kang P., Chen S., Zhao Y., Shang X., Investigation and analysis of demand for intelligent logistics system with light intelligent packages, Management Science and Engineering, 12, 4, pp. 39-43, (2018); Zhou Q., Zhang Z., Wang Y., Research on safety management system optimization of B2C e-commerce intelligent logistics information system based on data cube, Journal of Intelligent & Fuzzy Systems, 38, 2, pp. 1585-1592, (2020)","J. Chen; SILC Business School, Shanghai University, Shanghai, 201800, China; email: chenjun1@shu.edu.cn",null,"Tech Science Press",{"$nulls":5},1.5261492E7,null,null,null,"English","CMES Comput. Model. Eng. Sci.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85101076333"]
["Hu X.; Zhang X.; Lovrich N.P.","Hu, Xiaochen (57202875403); Zhang, Xudong (57194536061); Lovrich, Nicholas P. (6603765188)","57202875403; 57194536061; 6603765188","Forecasting Identity Theft Victims: Analyzing Characteristics and Preventive Actions through Machine Learning Approaches",2021.0,"Victims and Offenders",16.0,4.0,null,465.0,494.0,29.0,10.0,"10.1080/15564886.2020.1806161","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85089529537&doi=10.1080%2f15564886.2020.1806161&partnerID=40&md5=162d89c6af03b82a59ca323def05bf6f","Department of Criminal Justice, Fayetteville State University, Fayetteville, NC, United States; Department of Computer Science, Graduate Center of the City University of New York, New York City, United States; School of Politics, Philosophy and Public Affairs, Washington State University, Pullman, WA, United States","Hu X., Department of Criminal Justice, Fayetteville State University, Fayetteville, NC, United States; Zhang X., Department of Computer Science, Graduate Center of the City University of New York, New York City, United States; Lovrich N.P., School of Politics, Philosophy and Public Affairs, Washington State University, Pullman, WA, United States","Researchers in criminology and criminal justice have been making increasing use of the machine learning approach to investigate questions involving large amounts of digital data. We make use here of survey data on over 220,000 respondents drawn from three waves of the National Crime Victimization Survey Identity Theft Supplement (NCVS-ITS) conducted by the Bureau of Justice Statistics (BJS) in 2012, 2014, and in 2016. We use three distinct machine learning algorithms to analyze these data: 1) logistic regression; 2) decision tree; and, 3) random forest. We assess the efficacy of these approaches against these evaluative criteria: the overall percentage of correct classification, receiver operating characteristics (ROC), the area under the ROC curve (AUC), and feature criticality. Our findings indicate that the logistic regression algorithm performs best in predicting overall identity theft victimization, misuse of credit cards, misuse of financial accounts of other types, and the opening of new accounts; the random forest algorithm performs best in predicting misuse of checking/saving accounts. Our findings suggest that the respondent’s age, educational level, and online shopping frequency are significantly related to identity theft victimization. Additionally, frequently checking credit reports and changing passwords of financial accounts are strong predictors of identity theft victimization. We draw out the implications of our work for our collective understanding of identity theft, and for informing our judgment as to the potential utility of the use of machine learning approaches in criminology and criminal justice. © 2020 Taylor & Francis Group, LLC.","criminal justice; criminology; decision tree; Identity theft; machine learning; random forest; victimization",{"$nulls":7},"Allison S.F., Schuck A.M., Lersch K.M., Exploring the crime of identity theft: Prevalence, clearance rates, and victim/offender characteristics, Journal of Criminal Justice, 33, 1, pp. 19-29, (2005); Amit Y., Geman D., Wilder K., Joint induction of shape features and tree classifiers, IEEE Transactions on Pattern Analysis and Machine Intelligence, 19, 11, pp. 1300-1305, (1997); Anderson K.B., Who are the victims of identity theft? 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An empirical comparison of supervised learning algorithms to predict recidivism, Criminal Justice Policy Review, 28, 6, pp. 570-600, (2017); Fawcett T., An introduction to ROC analysis, Pattern Recognition Letters, 27, 8, pp. 861-874, (2006); Consumer sentinel network, Federal Trade Commission, (2019); Foster B.P., Zurada J., Barney D.K., Could decision trees help improve farm service agency lending decisions?, Academy of Information and Management Sciences Journal, 13, 1, pp. 69-91, (2010); Friedl M.A., Brodley C.E., Decision tree classification of land cover from remotely sensed data, Remote Sensing of Environment, 61, 3, pp. 399-409, (1997); Golladay K., Holtfreter K., The consequences of identity theft victimization: An examination of emotional and physical health outcomes, Victims & Offenders, 12, 5, pp. 741-760, (2017); Golladay K.A., Reporting behaviors of identity theft victims: An empirical test of Black’s theory of law, Journal of Financial Crime, 24, 1, pp. 101-117, (2017); Harrell E., Victims of identity theft, 2014, US Department of Justice, Office of Justice Programs, Bureau of Justice Statistics, (2015); Harrell E., Victims of identity theft, 2016, US Department of Justice, Office of Justice Programs, Bureau of Justice Statistics, (2019); Harrell E., Langton L., Victims of identity theft, 2012, U.S. Department of Justice, Office of Justice Programs, Bureau of Justice Statistics, (2013); Holtfreter K., Reisig M.D., Pratt T.C., Low self‐control, routine activities, and fraud victimization, Criminology, 46, 1, pp. 189-220, (2008); Holtfreter K., Reisig M.D., Pratt T.C., Holtfreter R.E., Risky remote purchasing and identity theft victimization among older Internet users, Psychology, Crime & Law, 21, 7, pp. 681-698, (2015); Hosmer J.D., Lemeshow W., Sturdivant R.X., Applied logistic regression, 398, (2013); Hu X., Wu J., DeValve M.J., Fisher B.S., Exploring violent crime reporting among school-age victims: Findings from NCVS SCS 2005-2015, Victims & Offenders, 15, 2, pp. 141-158, (2020); Kleinbaum D.G., Dietz K., Gail M., Klein M., Klein M., Logistic regression, (2002); Liaw A., Wiener M., Classification and regression by randomForest, R News, 2, 3, pp. 18-22, (2002); Manning M., Wong G.T., Graham T., Ranbaduge T., Christen P., Taylor K., Wortley R., Makkai T., Skorich P., Towards a ‘smart’cost–benefit tool: Using machine learning to predict the costs of criminal justice policy interventions, Crime Science, 7, 1, (2018); Morgan R.E., Oudekerk B.A., Criminal victimization, 2018, Bureau of Justice Statistics. NCJ, 253043, (2019); Neuilly M.A., Zgoba K.M., Tita G.E., Lee S.S., Predicting recidivism in homicide offenders using classification tree analysis, Homicide Studies, 15, 2, pp. 154-176, (2011); Ngo F.T., Stalking: An examination of the correlates of subsequent police responses, Policing: An International Journal, 42, 3, pp. 362-375, (2019); Nguyen K., Yuan Y., McNeeley S., School security measures, school environment, and avoidance behaviors, Victims & Offenders, 15, 1, pp. 43-59, (2020); Piquero N.L., Cohen M.A., Piquero A.R., How much is the public willing to pay to be protected from identity theft?, Justice Quarterly, 28, 3, pp. 437-459, (2011); Pontell H., Pleased to meet you … won’t you guess my name: Identity fraud, cyber-crime, and white-collar delinquency, Adelaide Law Review, 23, 2, pp. 305-328, (2002); Powers D.M., Evaluation: From precision, recall and F-measure to ROC, informedness, markedness and correlation, Journal of Machine Learning Technologies, 2, 1, pp. 37-63, (2011); Pratt T.C., Holtfreter K., Reisig M.D., Routine online activity and internet fraud targeting: Extending the generality of routine activity theory, Journal of Research in Crime and Delinquency, 47, 3, pp. 267-296, (2010); Randa R., Reyns B.W., The physical and emotional toll of identity theft victimization: A situational and demographic analysis of the national crime victimization survey, Deviant Behavior, (2019); Rebovich D.J., Examining identity theft: Empirical explorations of the offense and the offender, Victims & Offenders, 4, 4, pp. 357-364, (2009); Reisig M.D., Holtfreter K., Shopping fraud victimization among the elderly, Journal of Financial Crime, 20, 3, pp. 324-337, (2013); Reisig M.D., Pratt T.C., Holtfreter K., Perceived risk of internet theft victimization: Examining the effects of social vulnerability and financial impulsivity, Criminal Justice and Behavior, 36, 4, pp. 369-384, (2009); Reyns B.W., Online routines and identity theft victimization: Further expanding routine activity theory beyond direct-contact offenses, Journal of Research in Crime and Delinquency, 50, 2, pp. 216-238, (2013); Russell S.J., Norvig P., Artificial intelligence: A modern approach, (2016); Safavian S.R., Landgrebe D., A survey of decision tree classifier methodology, IEEE Transactions on Systems, Man, and Cybernetics, 21, 3, pp. 660-674, (1991); Shmueli G., To explain or to predict?, Statistical Science, 25, 3, pp. 289-310, (2010); Slosarik K., Identity theft: An overview of the problem, The Justice Professional, 15, 4, pp. 329-343, (2002); Stehman S.V., Selecting and interpreting measures of thematic classification accuracy, Remote Sensing of Environment, 62, 1, pp. 77-89, (1997); Takieddine S., Andoh-Baidoo F.K., An exploratory analysis of internet banking adoption using decision tree induction, International Journal of Electronic Finance, 8, 1, pp. 1-20, (2014); Warner R.M., Applied statistics: From bivariate through multivariate techniques, (2013); White M.D., Fisher C., Assessing our knowledge of identity theft: The challenges to effective prevention and control efforts, Criminal Justice Policy Review, 19, 1, pp. 3-24, (2008); Ylang N., Capable guardianship against identity theft: Demographic insights based on a national sample of US adults, Journal of Financial Crime, 27, 1, pp. 130-142, (2020); Zeng J., Ustun B., Rudin C., Interpretable classification models for recidivism prediction, Journal of the Royal Statistical Society: Series A (Statistics in Society), 180, 3, pp. 689-722, (2017); Zurada J., Kunene N., Guan J., The classification performance of multiple methods and datasets: Cases from the loan credit scoring domain, Journal of International Technology and Information Management, 23, 1, pp. 57-82, (2014)","X. Hu; Fayetteville State University, Fayetteville, Lauretta Taylor 3101200 Murchison Road, 28301,, United States; email: xhu@uncfsu.edu",null,"Routledge",{"$nulls":5},1.5564886E7,null,null,null,"English","Victims Offenders","Article","Final",null,"Scopus","2-s2.0-85089529537"]
["Frei R.; Jack L.; Brown S.","Frei, Regina (7103231288); Jack, Lisa (8276658700); Brown, Steve (55479568600)","7103231288; 8276658700; 55479568600","Product returns: a growing problem for business, society and environment",2020.0,"International Journal of Operations and Production Management",40.0,10.0,null,1613.0,1621.0,8.0,31.0,"10.1108/IJOPM-02-2020-0083","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85086179212&doi=10.1108%2fIJOPM-02-2020-0083&partnerID=40&md5=ae9740c66b4a93593de947f350a57794","Business School, University of Southampton, Southampton, United Kingdom; Business School, University of Portsmouth, Portsmouth, United Kingdom","Frei R., Business School, University of Southampton, Southampton, United Kingdom; Jack L., Business School, University of Portsmouth, Portsmouth, United Kingdom; Brown S., Business School, University of Southampton, Southampton, United Kingdom","Purpose: This article sheds light onto the increasing problem of product returns, which is exacerbated by growing e-commerce. Many retailers and academics are oblivious to the nature and scale of this challenge. Interdisciplinary research is needed to develop supporting theory, and cross-functional teams are required to implement measures addressing economic, ecological and social sustainability issues. Design/methodology/approach: The initial project adopted a multi-case study approach, whereby returns processes were mapped, vulnerabilities identified and a returns cost calculator was developed. Findings: Product returns processes are usually complicated, prone to internal and external fraud, inefficient and lack sustainability. They can generate considerable losses to the business, especially as returns data are often not systematically collected, monitored or reported to senior management. There are important implications for strategic and operational management, namely the need to develop a concept for Lean returns systems. Originality/value: Product returns are a unique and understudied but growing field in academic research, with only few publications over the last two decades. Yet the phenomenon is causing increasing problems in business and society. Robust solutions could achieve great financial and non-financial impacts. © 2020, Emerald Publishing Limited.","Business strategy; Operations strategy; Retail sector; Reverse logistics; Supply chain management; Sustainability",{"$nulls":7},"Lean reverse logistics, (2018); Frei R., Jack L., Krzyzaniak S.A., Sustainable reverse supply chains and circular economy in multichannel retail returns, Business Strategies and the Environment, (2020); Tackling over-consumption: a key challenge for the European green deal, (2019); Jack L., Frei R., Krzyzaniak S.A., Buy online, return to store; the challenges and opportunities of product returns in a multichannel environment, (2019); Ram A., UK retailers count the cost of returns, Financial Times, 27, January, (2016); Rogers D., Lambert D., Croxton K., Garcia-Dastugue S., The returns management process, International Journal of Logistics Management, 13, 2, pp. 1-18, (2002); Schiffer J., The unsustainable cost of free returns, Vogue Business, (2019); Speights D., Return rate miscalculations impact retail chains nationwide, White paper, Appriss Retail, (2013)","R. Frei; Business School, University of Southampton, Southampton, United Kingdom; email: work@reginafrei.ch",null,"Emerald Group Holdings Ltd.",{"$nulls":5},1443577.0,null,null,null,"English","Int. J. Oper. Prod. Manage.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85086179212"]
["Koch S.; Klein R.","Koch, Sebastian (57198210293); Klein, Robert (57199458980)","57198210293; 57199458980","Route-based approximate dynamic programming for dynamic pricing in attended home delivery",2020.0,"European Journal of Operational Research",287.0,2.0,null,633.0,652.0,19.0,23.0,"10.1016/j.ejor.2020.04.002","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85086509890&doi=10.1016%2fj.ejor.2020.04.002&partnerID=40&md5=4b4095cdcaf60eac69af020455aed8cf","Chair of Analytics and Optimization, University of Augsburg, Universitätsstraße 16, Augsburg, D-86159, Germany","Koch S., Chair of Analytics and Optimization, University of Augsburg, Universitätsstraße 16, Augsburg, D-86159, Germany; Klein R., Chair of Analytics and Optimization, University of Augsburg, Universitätsstraße 16, Augsburg, D-86159, Germany","Attended home delivery describes the delivery of goods by e-grocers or e-tailers to customers within an agreed time window. Because customers expect narrow time windows, offering such services may lead to expensive fulfillment operations. This has led to research on how to influence customers’ bookings using time window pricing or slotting. In this paper, we reconsider the problem of demand management through dynamic pricing for attended home delivery services. This problem is usually modeled as a stochastic dynamic program, but even small instances cannot be solved to optimality due to the curses of dimensionality. The major challenges consist of finding feasible time windows for an incoming customer, estimating the opportunity costs, i.e., the future monetary loss due to accepting a booking, and optimizing the time window prices in real time. In this paper, we propose a route-based approximate dynamic programming approach to tackle these challenges. The approach carefully combines and partially extends state-of-the-art methods in attended home delivery, dynamic pricing, and dynamic vehicle routing. In an extensive simulation study, we compare its performance with state-of-the-art benchmark heuristics. The results indicate a superior performance of our approach in terms of both profit and number of customers served. © 2020 Elsevier B.V.","Approximate dynamic programming; Attended home delivery; Dynamic pricing; E-commerce; Revenue management","Benchmarking; Contracts; Costs; Economics; Sales; Stochastic systems; Vehicle routing; Approximate dynamic programming; Dynamic Vehicle Routing; Extensive simulations; Home delivery services; Number of customers served; Opportunity costs; State-of-the-art methods; Stochastic dynamic program; Dynamic programming",{"$nulls":6},"Agatz N.A.H., Campbell A.M., Fleischmann M., Savelsbergh M.W.P., Time slot management in attended home delivery, Transportation Science, 45, 3, pp. 435-449, (2011); Agatz N.A.H., Campbell A.M., Fleischmann M., van Nunen J.A.E.E., Savelsbergh M.W.P., Revenue management opportunities for internet retailers, Journal of Revenue and Pricing Management, 12, 2, pp. 128-138, (2013); Agatz N.A.H., Fleischmann M., van Nunen J.A.E.E., E-fulfillment and multi-channel distribution – A review, European Journal of Operational Research, 187, 2, pp. 339-356, (2008); Asdemir K., Jacob V.S., Krishnan R., Dynamic pricing of multiple home delivery options, European Journal of Operational Research, 196, 1, pp. 246-257, (2009); Bent R.W., van Hentenryck P., Scenario-based planning for partially dynamic vehicle routing with stochastic customers, Operations Research, 52, 6, pp. 977-987, (2004); Berbeglia G., Garassino A., Vulcano G., A comparative empirical study of discrete choice models in retail operations, (2018); Bertsimas D., Popescu I., Revenue management in a dynamic network environment, Transportation Science, 37, 3, pp. 257-277, (2003); Birge J.R., Louveaux F., Introduction to stochastic programming, (2011); Braysy O., Gendreau M., Vehicle routing problem with time windows, part I: Route construction and local search algorithms, Transportation Science, 39, 1, pp. 104-118, (2005); Breidert C., Hahsler M., Reutterer T., A review of methods for measuring willingness-to-pay, Innovative Marketing, 2, 4, pp. 8-32, (2006); Bruck B.P., Cordeau J.F., Iori M., A practical time slot management and routing problem for attended home services, Omega, 81, December 2018, pp. 208-219, (2018); Buhler D., Klein R., Neugebauer M., Model-based delivery cost approximation in attended home services, Computers & Industrial Engineering, 98, August 2016, pp. 78-90, (2016); Campbell A.M., Savelsbergh M.W.P., Efficient insertion heuristics for vehicle routing and scheduling problems, Transportation Science, 38, 3, pp. 369-378, (2004); Campbell A.M., Savelsbergh M.W.P., Decision support for consumer direct grocery initiatives, Transportation Science, 39, 3, pp. 313-327, (2005); Campbell A.M., Savelsbergh M.W.P., Incentive schemes for attended home delivery services, Transportation Science, 40, 3, pp. 327-341, (2006); Chen K.D., Hausman W.H., Technical note: Mathematical properties of the optimal product line selection problem using choice-based conjoint analysis, Management Science, 46, 2, pp. 327-332, (2000); Cleophas C., Ehmke J.F., When are deliveries profitable? Considering order value and transport capacity in demand fulfillment for last-mile deliveries in metropolitan areas, Business & Information Systems Engineering, 6, 3, pp. 153-163, (2014); Daganzo C.F., Modeling distribution problems with time windows: Part I, Transportation Science, 21, 3, pp. 171-179, (1987); Dalmeijer K., Spliet R., A branch-and-cut algorithm for the time window assignment vehicle routing problem, Computers & Operations Research, 89, January 2018, pp. 140-152, (2018); Davis J.M., Topaloglu H., Williamson D.P., Pricing problems under the nested logit model with a quality consistency constraint, INFORMS Journal on Computing, 29, 1, pp. 54-76, (2017); Desaulniers G., Madsen O.B.G., Ropke S., The vehicle routing with time windows, Vehicle routing: Problems, methods, and applications, (2014); Dong L., Kouvelis P., Tian Z., Dynamic pricing and inventory control of substitute products, Manufacturing & Service Operations Management, 11, 2, pp. 317-339, (2009); Ehmke J.F., Campbell A.M., Customer acceptance mechanisms for home deliveries in metropolitan areas, European Journal of Operational Research, 233, 1, pp. 193-207, (2014); 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Koch S., Least squares approximate policy iteration for learning bid prices in choice-based revenue management, Computers & Operations Research, 77, January 2017, pp. 240-253, (2017); Kohler C., Ehmke J.F., Campbell A.M., Flexible time window management for attended home deliveries, To appear in: Omega, (2020); Kok A.G., Fisher M.L., Vaidyanathan R., Assortment planning: Review of literature and industry practice, Retail supply chain management: Quantitative models and empirical studies, (2009); Kraus U.G., Yano C.A., Product line selection and pricing under a share-of-surplus choice model, European Journal of Operational Research, 150, 3, pp. 653-671, (2003); Kunze O., A new interactive approach on route planning with tight delivery time windows: A comparison of the obtained planning results to other approaches, Logistics systems for sustainable cities: Proceedings of the third international Conference on City Logistics (Madeira, Portugal), (2004); Liu Q., van Ryzin G., On the choice-based linear programming model for network revenue management, Manufacturing & Service Operations Management, 10, 2, pp. 288-310, (2008); Lu Q., Dessouky M.M., A new insertion-based construction heuristic for solving the pickup and delivery problem with time windows, European Journal of Operational Research, 175, 2, pp. 672-687, (2006); Mackert J., Choice-based dynamic time slot management in attended home delivery, Computers & Industrial Engineering, 129, March 2019, pp. 333-345, (2019); Meisel S., Anticipatory optimization for dynamic decision making, (2011); Miranda Bront J.J., Mendez-Diaz I., Vulcano G., A column generation algorithm for choice-based network revenue management, Operations Research, 57, 3, pp. 769-784, (2009); Powell W.B., Approximate dynamic programming: Solving the curses of dimensionality, (2011); Rosenkrantz D.J., Stearns R.E., Lewis P.M., Approximate algorithms for the traveling salesperson problem, proceedings of the fifteenth annual symposium on switching and automata theory, (1974); Savelsbergh M.W.P., Local search in routing problems with time windows, Annals of Operations Research, 4, 1, pp. 285-305, (1985); 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Train K., Discrete choice methods with simulation, (2009); Ulmer M.W., On modeling stochastic dynamic vehicle routing problems. 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To appear in: EURO Journal on Transportation and Logistics, (2020); Ulmer M.W., Mattfeld D.C., Koster F., Budgeting time for dynamic vehicle routing with stochastic customer requests, Transportation Science, 52, 1, pp. 20-37, (2018); Ulmer M.W., Thomas B.W., Meso-parametric value function approximation for dynamic customer acceptances in delivery routing, European Journal of Operational Research, 285, 1, pp. 183-195, (2019); Ulmer M.W., Thomas B.W., Mattfeld D.C., Preemptive depot returns for dynamic same-day delivery, EURO Journal on Transportation and Logistics, 199, 1, pp. 1-35, (2018); Varian H.R., Intermediate microeconomics: A modern approach, (2014); Voccia S.A., Campbell A.M., Thomas B.W., The same-day delivery problem for online purchases, Transportation Science, 53, 1, pp. 167-184, (2019); Yang X., Strauss A.K., An approximate dynamic programming approach to attended home delivery management, European Journal of Operational Research, 263, 3, pp. 935-945, (2017); Yang X., Strauss A.K., Currie C.S.M., Eglese R., Choice-based demand management and vehicle routing in e-fulfillment, Transportation Science, 50, 2, pp. 473-488, (2016)","R. Klein; Chair of Analytics and Optimization, University of Augsburg, Augsburg, Universitätsstraße 16, D-86159, Germany; email: robert.klein@wiwi.uni-augsburg.de",null,"Elsevier B.V.",{"$nulls":5},3772217.0,null,"EJORD",null,"English","Eur J Oper Res","Article","Final",null,"Scopus","2-s2.0-85086509890"]
["Wei Q.; Sun D.; Gou X.; Bai C.","Wei, Qiang (57204766918); Sun, Daguang (57225195348); Gou, Xinyu (57204774709); Bai, Chunguang (24485581400)","57204766918; 57225195348; 57204774709; 24485581400","Sharing Economy for Cost Reduction and Efficiency Increase: The Case of Sharing E-Commerce Logistics",2021.0,"Complexity",2021.0,null,5573422.0,null,null,null,4.0,"10.1155/2021/5573422","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85109451077&doi=10.1155%2f2021%2f5573422&partnerID=40&md5=a12210de77e0dc3e8274a62f900e42c9","School of Management and Economics, University of Electronic Science and Technology of China, Chengdu, 611731, China; Southwestern University of Finance and Economics, Chengdu, 611130, China; School of Business Administration, Southwestern University of Finance and Economics, Chengdu, 611130, China","Wei Q., School of Management and Economics, University of Electronic Science and Technology of China, Chengdu, 611731, China; Sun D., Southwestern University of Finance and Economics, Chengdu, 611130, China; Gou X., School of Business Administration, Southwestern University of Finance and Economics, Chengdu, 611130, China; Bai C., School of Management and Economics, University of Electronic Science and Technology of China, Chengdu, 611731, China","In the real business environment, due to unpredictable market demand or high prediction difficulty and low prediction accuracy, there will be inevitably operational loss in the field of e-commerce logistics caused by undersupply or oversupply of express service capabilities. At present, China is deepening the supply-side structural reforms. Confronted with the growing demand for e-commerce logistics express delivery, especially the urgent demand for tackling orders piling up to 1 billion pieces during the recent \"Double 11\"shopping carnival, it is very important and practical for us to study how to make scientific decisions on the supply side in the field of e-commerce express delivery. Therefore, in this paper, we design a sharing logistics cooperation mechanism considering both the undersupply and oversupply of express delivery service capabilities under stochastic demand. By comparing the earnings data of several listed express companies, we analyze four types of optimization strategies: the order flow proportion revenue sharing strategy (RE-OFP), the combined factors revenue sharing strategy (RE-RSF), the order flow proportion risk sharing strategy (RS-OFP), and the combined factors risk sharing strategy (RS-RSF). The research results demonstrate that the four optimization strategies of RE-OFP, RE-RSF, RS-OFP, and RS-RSF could achieve Pareto improvements in the operational performance of e-commerce express service. The performance of four revenue sharing and risk sharing strategies varies with different revenue sharing or risk sharing factors. Under some certain combined factors, the revenue sharing contract could help realize the supply chain coordination of the sharing logistics service. The sharing logistics cooperation mechanism based on equity investment proposed hereafter provides a feasible solution to solve the problems of high empty driving rate and operational cost of e-commerce express delivery service in urban areas.  © 2021 Qiang Wei et al.",null,"Cost reduction; Risk management; Stochastic systems; Supply chains; Business environments; Cost reduction and efficiencies; Logistics cooperations; Operational performance; Optimization strategy; Revenue sharing contracts; Scientific decisions; Supply chain coordination; Electronic commerce",{"$nulls":4},"Fundamental Research Funds for the Central Universities, (JBK1507105)","This research was supported by Fundamental Research Funds for the Central Universities (JBK1507105).","Catherine C., Caitlin C., Jan F.E., Kevin T., Collaborative urban transportation: Recent advances in theory and practice, European Journal of Operational Research, 273, 3, pp. 801-816, (2019); Giannoccaro I., Pontrandolfo P., Negotiation of the revenue sharing contract: An agent-based systems approach, International Journal of Production Economics, 122, 2, pp. 558-566, (2009); Liu W., Liu C., Ge M., An order allocation model for the two-echelon logistics service supply chain based on cumulative prospect theory, Journal of Purchasing and Supply Management, 19, 1, pp. 39-48, (2013); Liu W., Wang Q., Mao Q., Wang S., Zhu D., A scheduling model of logistics service supply chain based on the mass customization service and uncertainty of FLSP's operation time, Transportation Research Part E: Logistics and Transportation Review, 83, pp. 189-215, (2015); Liu W., Liang Z., Ye Z., Liu L., The optimal decision of customer order decoupling point for order insertion scheduling in logistics service supply chain, International Journal of Production Economics, 175, pp. 50-60, (2016); Bektas T., Crainic T.G., Van Woensel T., From managing urban freight to smart city logistics networks, Network Design and Optimization for Smart Cities, pp. 143-188, (2017); Savelsbergh M., Van Woensel T., 50th anniversary invited article-city logistics: Challenges and opportunities, Transportation Science, 50, 2, pp. 579-590, (2016); Thompson R.G., Hassall K.P., A collaborative urban distribution network, Procedia - Social and Behavioral Sciences, 39, pp. 230-240, (2012); Browne M., Allen J., Nemoto T., Patier D., Visser J., Reducing social and environmental impacts of urban freight transport: A review of some major cities, Procedia - Social and Behavioral Sciences, 39, pp. 19-33, (2012); Cattaruzza D., Absi N., Feillet D., Gonzalez-Feliu J., Vehicle routing problems for city logistics, Euro Journal on Transportation and Logistics, 6, 1, pp. 51-79, (2015); Narasimhan C., Papatla P., Ravula P., Preference Segmentation Induced by Tariff Schedules and Availability in Ride-sharing Markets, (2016); Wu C., Wang Y., Zhu T., Mobile Hailing Technology, Worker Productivity and Digital Inequality: a Case of the Taxi Industry, (2016); Zervas G., Proserpio D., Byers J.W., The rise of the sharing economy: Estimating the impact of Airbnb on the hotel industry, Journal of Marketing Research, 54, 5, pp. 687-705, (2017); Cohen P., Hahn R.W., Hall J., Levitt S.D., Metcalfe R.D., Using Big Data to Estimate Consumer Surplus: The Case of Uber, (2016); Tian L., Jiang B., Effects of consumer-to-consumer product sharing on distribution channel, Production & Operations Management, 27, 3, (2018); Guda H., Subramanian U., Strategic Surge Pricing and Forecast Communication on On-Demand Service Platforms, (2017); Belk R., Sharing, Journal of Consumer Research, 36, 5, pp. 715-734, (2010); Ranchordas S., Does sharing mean caring: Regulating innovation in the sharing economy, Minnesota Journal of Law, Science and Technology, 16, 1, (2015); He P., He Y., Shi C., Xu H., Zhou L., Cost-sharing contract design in a low-carbon service supply chain, Computers & Industrial Engineering, 139, (2020); Cachon G.P., Lariviere M.A., Supply chain coordination with revenue-sharing contracts: Strengths and limitations, Management Science, 51, 1, pp. 30-44, (2005); Wang Y.-Y., Lau H.-S., Hua Z.-S., Three revenue-sharing variants: Their significant performance differences under system-parameter uncertainties, Journal of the Operational Research Society, 63, 12, pp. 1752-1764, (2012); Wei Q., Li S., Gou X., Huo B., Joint optimal decision of the shared distribution system through revenue-sharing and cooperative investment contracts, Industrial Management & Data Systems, 119, 3, pp. 578-612, (2019); Zhang J., Liu G., Zhang Q., Bai Z., Coordinating a supply chain for deteriorating items with a revenue sharing and cooperative investment contract, Omega, 56, pp. 37-49, (2015); Bai Q., Chen M., Xu L., Revenue and promotional cost-sharing contract versus two-part tariff contract in coordinating sustainable supply chain systems with deteriorating items, International Journal of Production Economics, 187, pp. 85-101, (2017); Hu B., Xu D., Meng C., Inconsistency of a retailer's optimal policies and channel performance under revenue sharing contracts, International Journal of Production Economics, 183, pp. 53-65, (2017); Yang H., Luo J., Wang H., The role of revenue sharing and first-mover advantage in emission abatement with carbon tax and consumer environmental awareness, International Journal of Production Economics, 193, pp. 691-702, (2017); Song H., Gao X., Green supply chain game model and analysis under revenue-sharing contract, Journal of Cleaner Production, 170, pp. 183-192, (2018); Yang H., Chen W., Retailer-driven carbon emission abatement with consumer environmental awareness and carbon tax: Revenue-sharing versus Cost-sharing, Omega, 78, pp. 179-191, (2018); Li T., Zhang R., Zhao S., Liu B., Low carbon strategy analysis under revenue-sharing and cost-sharing contracts, Journal of Cleaner Production, 212, pp. 1462-1477, (2019); Yu B., Wang J., Lu X., Yang H., Collaboration in a low-carbon supply chain with reference emission and cost learning effects: Cost sharing versus revenue sharing strategies, Journal of Cleaner Production, 250, (2010); He Y., Zhou F., Qi M., Wang X., Joint distribution: Service paradigm, key technologies and its application in the context of Chinese express industry, International Journal of Logistics Research and Applications, 23, 3, pp. 211-227, (2020); Xiao D., Wang J., Lu Q., Stimulating sustainability investment level of suppliers with strategic commitment to price and cost sharing in supply chain, Journal of Cleaner Production, 252, (2020); Yun F.L., Wang Y., Wu Y., Consignment contracts with revenue sharing for a capacitated retailer and multiple manufacturers, Manufacturing & Service Operations Management, 17, 4, pp. 527-537, (2012); Luo Y., Wei Q., Gou X., Dai D., Zhou Y., Sharing logistics service supply chain with revenue-sharing vs. cost-sharing contracts, Mathematical Problems in Engineering, 2021, (2021); Cepolina E.M., Farina A., A new urban freight distribution scheme and an optimization methodology for reducing its overall cost, European Transport Research Review, 7, 1, pp. 1-14, (2015)","C. Bai; School of Management and Economics, University of Electronic Science and Technology of China, Chengdu, 611731, China; email: cbai@uestc.edu.cn",null,"Hindawi Limited",{"$nulls":5},1.0762787E7,null,null,null,"English","Complexity","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85109451077"]
["Wang X.","Wang, Xiaoming (57219396608)",5.7219396608E10,"Location Selection of Marine Product E-commerce Distribution Centers Based on Effective Covering Model",2020.0,"Journal of Coastal Research",110.0,"sp1",null,15.0,19.0,4.0,3.0,"10.2112/JCR-SI110-004.1","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85092522029&doi=10.2112%2fJCR-SI110-004.1&partnerID=40&md5=837f5e4cbc52c0faf5134ce9d6f2afda","School of Economics and Management, Yiwu Industrial and Commercial College, Yiwu, 322000, China","Wang X., School of Economics and Management, Yiwu Industrial and Commercial College, Yiwu, 322000, China","The location selection of marine product e-commerce distribution centers affects the transportation costs and transportation efficiency of the products, and the effective covering model is an efficient way to solve this problem. Based on the product features, this paper first analyzes the marine product e-commerce operation modes and the influencing factors of the location selection of distribution centers; then it explores the demand conditions of marine product e-commerce and the logistics distribution systems, and applies the effective covering model to conduct an empirical analysis on the location selection problem of marine product e-commerce distribution centers. The research results show that the marine product e-commerce platforms have several operation modes such as O2O and B2B. The external influencing factors of the location selection of marine product e-commerce distribution centers mainly include 3 categories: surrounding environment, public facilities and population. On the e-commerce platforms, the demand for marine products is quite considerable; the distribution mode adopted by most of these e-commerce platforms or the logistics enterprises is based on the technology of multimodal transportation and main-branch line transportation distribution; the effective covering model can be divided into Location Set Covering Model (LSCM) and Maximum Covering Location Model (MCLM), and the specific planning of the model could be conducted according to the actual situation of the distribution centers. The study in this paper aims to play a promotive role in the scientific location selection of distribution centers of marine product e-commerce enterprises.  © Coastal Education and Research Foundation, Inc. 2020.","distribution center; e-commerce; effective covering model; location selection; Marine products",{"$nulls":5},"Yiwu Industrial and Commercial College; Yiwu Mobile Ecommerce Research Center; Zhejiang Province Higher Education Teaching Reform Project, (jg20160349); Zhejiang philosophy and Social Sciences Development Planning Leading Group, (20NDJC344YBM)","This work is supported by Yiwu Industrial and Commercial College. Additionally, supported by the Yiwu Mobile Ecommerce Research Center, Zhejiang Province Higher Education Teaching Reform Project (jg20160349), Zhejiang philosophy and Social Sciences Development Planning Leading Group (20NDJC344YBM).","Bowers A.J., Toward addressing the issues of site selection in district effectiveness research: A two-level hierarchical linear growth model, Educational Administration Quarterly, 46, 3, pp. 395-425, (2010); Caro J.J., MoLler J., Decision-analytic models: Current methodological challenges, Pharmacoeconomics, 32, 10, pp. 943-950, (2014); Goomas D.T., The impact of wireless technology on order selection audits at an auto parts distribution center, Journal of Organizational Behavior Management, 32, 2, pp. 131-139, (2012); Hopp T., Barker V., Investigating the influence of age, social capital affinity, and flow on positive outcomes reported by e-commerce site users, Behaviour and Information Technology, 35, 5, pp. 1-14, (2016); Hua N., E-commerce performance in hospitality and tourism, International Journal of Contemporary Hospitality Management, 28, 9, pp. 2052-2079, (2016); Huang A., A risk detection system of e-commerce: Researches based on soft information extracted by affective computing web texts, Electronic Commerce Research, 18, 22, pp. 1-15, (2018); Julia-Igual J.F., Cervello-Royo R., Berne-Lafuente I., Market value analysis of a Chinese e-commerce holding group: a multicriteria approach, Service Business, 11, 3, pp. 475-490, (2016); Li X.L., Li Z., A hybrid prediction model for e-commerce customer churn based on logistic regression and extreme gradient boosting algorithm, Ingénierie des Systèmes d'Information, 24, 5, pp. 525-530, (2019); Lin X., Wang X., Hajli N., Building e-commerce satisfaction and boosting sales: The role of social commerce trust and its antecedents, International Journal of Electronic Commerce, 23, 3, pp. 328-363, (2019); Lupu Y., The informative power of treaty commitment: Using the spatial model to address selection effects, American Journal of Political Science, 57, 4, pp. 912-925, (2013); Qian Q.L., Chen Y.B., Li Y., Mo X., Spatial distribution of logistics enterprises in Guangzhou and its influencing factors, Geographical Research, 30, 7, pp. 1254-1261, (2011); Shi L.L., Liu S.H., Petrovic S., Cryptanalysis of a pseudorandom generator for cross-border E-commerce, Ingénierie des Systèmes d'Information, 24, 4, pp. 361-365, (2019); Shu J., Li Z., Huang L., Demand selection decisions for a multi-echelon inventory distribution system, Journal of the Operational Research Society, 64, 9, pp. 1307-1313, (2013)","X. Wang; School of Economics and Management, Yiwu Industrial and Commercial College, Yiwu, 322000, China; email: 461412091@qq.com",null,"Coastal Education Research Foundation Inc.",{"$nulls":5},7490208.0,null,"JCRSE",null,"English","J. Coast. Res.","Article","Final",null,"Scopus","2-s2.0-85092522029"]
["Figliozzi M.A.","Figliozzi, Miguel A. (6507854711)",6.507854711E9,"Carbon emissions reductions in last mile and grocery deliveries utilizing air and ground autonomous vehicles",2020.0,"Transportation Research Part D: Transport and Environment",85.0,null,102443.0,null,null,null,110.0,"10.1016/j.trd.2020.102443","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85087506193&doi=10.1016%2fj.trd.2020.102443&partnerID=40&md5=237a19ca620db1df81bbca74d5e11ad1","Civil and Environmental Engineering, Portland State University, United States","Figliozzi M.A., Civil and Environmental Engineering, Portland State University, United States","The rapid growth of e-commerce and package deliveries across the globe is demanding new solutions to meet customers’ desire for more and faster deliveries. New driverless air and ground vehicles are being launched and tested to deliver products or services in the areas of retail, groceries, and healthcare. This research focuses on the efficiency of autonomous (driverless) air and ground delivery vehicles in terms of vehicle-miles, energy consumption, and CO2 emissions. Three types of autonomous vehicle are analyzed: drones or unmanned aerial vehicles (UAVs), sidewalk autonomous delivery robots (SADRs), and road autonomous delivery robots (RADRs). The CO2 emissions of these autonomous vehicles are compared against emissions from an electric van (e-van), a conventional internal combustion engine van, and driving to a store utilizing electric and conventional vehicles. The impacts of vehicle capacity, range, and time constraints are analyzed as well as the impacts of number of deliveries, service time, area of service, and depot-service area distance. Novel results are found regarding the efficiency of each vehicle type and tradeoffs between driving to a store and store delivery as a function of order size and type of vehicle driven by consumers. © 2020 Elsevier Ltd","Air drone; Autonomous vehicles; Carbon emissions; Delivery industry; Energy; Grocery shopping; Ground robot; Travel distance","Antennas; Autonomous vehicles; Carbon; Carbon dioxide; Energy utilization; Unmanned aerial vehicles (UAV); Carbon emissions reductions; Delivery vehicle; New solutions; Package delivery; Research focus; Time constraints; Vehicle capacity; Vehicle types; aircraft; carbon dioxide; carbon emission; electronic commerce; emission control; energy efficiency; robotics; Ground vehicles",{"$nulls":4},"Freight Mobility Research Institute; U.S. DOT University Transportation Center","This research project was funded by the Freight Mobility Research Institute (FMRI), a U.S. DOT University Transportation Center.","Aljohani K., Thompson R.G., Impacts of logistics sprawl on the urban environment and logistics: taxonomy and review of literature, J. 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Econ., (2019); Slowik P., Sharpe B., pp. 1-30, (2018); Song L., Guan W., Cherrett T., Li B., Quantifying the greenhouse gas emissions of local collection-and-delivery points for last-mile deliveries, Transp. Res. Rec., 2340, 1, pp. 66-73, (2013); Sorensen H., Bogomolova S., Anderson K., Trinh G., Sharp A., Kennedy R., Page B., Wright M., Fundamental patterns of in-store shopper behavior, J. Retailing Consumer Services, 37, pp. 182-194, (2017); Stolaroff J.K., Samaras C., O'Neill E.R., Lubers A., Mitchell A.S., Ceperley D., Energy use and life cycle greenhouse gas emissions of drones for commercial package delivery, Nat. Commun., 9, 1, (2018); Suel E., Le Vine S., Polak J., Empirical application of expenditure diary instrument to quantify relationships between in-store and online grocery shopping: case study of Greater London, Transp. Res. Rec., 2496, 1, pp. 45-54, (2015); Talebian A., Mishra S., Predicting the adoption of connected autonomous vehicles: a new approach based on the theory of diffusion of innovations, Transp. Res. Part C: Emerg. Technol., 95, pp. 363-380, (2018); pp. 1-3, (2020); (2018); Verger R., (2018); Vleeshouwer T., Duin R.V., Verbraeck A., (2017); Wygonik E., Goodchild A., Evaluating the efficacy of shared-use vehicles for reducing greenhouse gas emissions: a US case study of grocery delivery, J. Transp. Res. Forum, 51, 2, (2012)",null,null,"Elsevier Ltd",{"$nulls":5},1.3619209E7,null,"TRDTF",null,"English","Transp. Res. Part D Transp. Environ.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85087506193"]
["Sallnäs U.; Björklund M.","Sallnäs, Uni (57173225000); Björklund, Maria (36080373400)","57173225000; 36080373400","Consumers' influence on the greening of distribution – exploring the communication between logistics service providers, e-tailers and consumers",2020.0,"International Journal of Retail and Distribution Management",48.0,11.0,null,1177.0,1193.0,16.0,28.0,"10.1108/IJRDM-07-2019-0213","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85087061212&doi=10.1108%2fIJRDM-07-2019-0213&partnerID=40&md5=6bb9186cb0d219d78f92c4e2d843394f","Department of Management and Engineering, Linköping University, Linköping, Sweden","Sallnäs U., Department of Management and Engineering, Linköping University, Linköping, Sweden; Björklund M., Department of Management and Engineering, Linköping University, Linköping, Sweden","Purpose: This paper takes its starting point in the possibilities consumers have to influence the greening of distribution. It focuses on three key actors who can facilitate consumer influence, namely e-tailers, logistics service providers (LSPs) and the consumers themselves. The purpose is to illuminate consumers' possibilities to influence the greening of distribution by exploring the communication between LSPs, e-tailers and consumers. Design/methodology/approach: Website scans of the 40 largest Swedish e-tailers and ten LSPs were combined with interviews of three e-tailers and three LSPs. Findings: The findings suggest that consumers at present have limited possibilities to influence the greening of distribution. One reason for this is the limited communication between LSPs, e-tailers and consumers. A gap in communication arises because e-tailers determine how to promote distribution alternatives on their websites, while it is the LSPs who develop and offer green distribution services. Research limitations/implications: This paper provides a first step in our understanding of what is needed in order to facilitate green distribution decisions from e-consumers. Practical implications: E-tailers can gain an increased understanding of their important role as facilitators of environmentally sound decisions for consumers through their design of websites. This study also highlights the need for LSPs to support e-tailers in this work. Social implications: The study contributes to the societal striving towards zero greenhouse gas emission by focussing on decreasing environmental effects by using suitable logistics. Originality/value: In contrast with previous research into the environmental impact of e-commerce distribution, this study investigates the possibilities consumers have to influence green logistics within e-commerce. © 2020, Emerald Publishing Limited.","Communication; E-commerce distribution; E-tailers; Environmental logistics; Green supply chain management; Last mile",{"$nulls":5},"Handelsrådet; Familjen Kamprads Stiftelse","The authors would like to thank The Swedish Retail and Wholesale Council and the Kamprad Family Foundation for funding this research.","Abbasi M., Nilsson F., Themes and challenges in making supply chains environmentally sustainable, Supply Chain Management, 17, 5, pp. 517-530, (2012); Allen J., Piecyk M., Piotrowska M., Analysis of Online Shopping and Home Delivery in the UK, (2017); Bask A., Halme M., Kallio M., Kuula M., Consumer preferences for sustainability and their impact on supply chain management: the case of mobile phones, International Journal of Physical Distribution and Logistics Management, 5-6, pp. 380-406, (2013); Bjorklund M., Forslund H., Persdotter Isaksson M., Exploring logistics-related environmental sustainability in large retailers, International Journal of Retail and Distribution Management, 44, 1, pp. 38-57, (2016); Browne M., Rizet C., Anderson S., Allen J., Keita B., Life cycle assessment in the supply chain: a review and case study, Transport Reviews, 25, 6, pp. 761-782, (2005); Bryman A., Bell E., Business Research Methods, (2011); Buldeo Rai H., Mommens K., Verlinde S., Macharis C., How does consumers' omnichannel shopping behaviour translate into travel and transport impacts? case-study of a footwear retailer in Belgium, Sustainability, 11, 9, (2019); Buldeo Rai H., Verlinde S., Macharis C., The ‘next day, free delivery’ myth unravelled: possibilities for sustainable last mile transport in an omnichannel environment, International Journal of Retail and Distribution Management, 47, 1, pp. 39-54, (2019); Buldeo Rai H., Environmental Sustainability of the Last Mile in Omnichannel Retail, (2019); Cambra-Fierro J.J., Polo-Redondo Y., Creating satisfaction in the demand‐supply chain: the buyers' perspective, Supply Chain Management: International Journal, 13, 3, pp. 211-224, (2008); Colicchia C., Marchet G., Melacini M., Perotti S., Building environmental sustainability: empirical evidence from logistics service providers, Journal of Cleaner Production, 59, pp. 197-209, (2013); Edwards J.B., McKinnon A.C., Cullinane S.L., Comparative analysis of the carbon footprints of conventional and online retailing: a ‘last mile’ perspective, International Journal of Physical Distribution and Logistics Management, 40, 1-2, pp. 103-123, (2010); Ehandelsindex, Topplista: topp 100 största nätbutikerna i Sverige, (2018); Eurostat, E-commerce statistics for individuals - statistics explained, (2020); Evangelista P., Environmental sustainability practices in the transport and logistics service industry: an exploratory case study investigation, Research in Transportation Business and Management, 12, pp. 63-72, (2014); Evans D., Welch D., Swaffield J., Constructing and mobilizing ‘the consumer’: responsibility, consumption and the politics of sustainability, Environment and Planning A, 49, 6, pp. 1396-1412, (2017); Hubner A., Kuhn H., Wollenburg J., Last mile fulfilment and distribution in omni-channel grocery retailing: a strategic planning framework, International Journal of Retail and Distribution Management, 44, 3, pp. 228-247, (2016); Kembro J., Naslund D., Information sharing in supply chains, myth or reality? 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Sallnäs; Department of Management and Engineering, Linköping University, Linköping, Sweden; email: uni.sallnas@liu.se",null,"Emerald Group Holdings Ltd.",{"$nulls":5},9590552.0,null,null,null,"English","Int. J. Retail Disrtib. Manage.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85087061212"]
["Liu C.; Feng Y.; Lin D.; Wu L.; Guo M.","Liu, Chang (57191678019); Feng, Yongfu (57215024819); Lin, Dongtao (56189551600); Wu, Liang (56454554100); Guo, Min (57215036299)","57191678019; 57215024819; 56189551600; 56454554100; 57215036299","Iot based laundry services: an application of big data analytics, intelligent logistics management, and machine learning techniques",2020.0,"International Journal of Production Research",58.0,17.0,null,5113.0,5131.0,18.0,86.0,"10.1080/00207543.2019.1677961","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85079716591&doi=10.1080%2f00207543.2019.1677961&partnerID=40&md5=6a8ea9a24751ea1cbae4ab2141d014f9","Southwestern University of Finance and Economics, Chengdu, China; School of Language and Culture, Sichuan University, Chengdu, China; School of Economics, Sichuan University, Chengdu, China; China Great Wall Asset Management Co., Ltd., Chengdu, China","Liu C., Southwestern University of Finance and Economics, Chengdu, China; Feng Y., Southwestern University of Finance and Economics, Chengdu, China; Lin D., School of Language and Culture, Sichuan University, Chengdu, China; Wu L., School of Economics, Sichuan University, Chengdu, China; Guo M., China Great Wall Asset Management Co., Ltd., Chengdu, China","The authors propose an innovative Internet of Things (IoT) based E-commerce business model Cloud Laundry for mass scale laundry services. The model utilises big data analytics, intelligent logistics management, and machine learning techniques. Using GPS and real-time update of big data, it calculates the best transportation path and update and re-route the logistic terminals quickly and simultaneously. Cloud laundry intelligently and dynamically provides the best laundry solutions based on the current state spaces of the laundry terminals through the user's specifications and thus offers local hotel customers with convenient, efficient, and transparent laundry services. Taking advantage of the rapid development of the big data industry, user interest modelling, and information security and privacy considerations, cloud laundry uses smartphone terminal control and big data models to maintain customers’ security needs. Different from the traditional laundry industry, cloud laundry companies have higher capital turnover, more liquidity, and stronger profitability. Therefore, this new generation of smart laundry business model could be of interest to not only academic researchers, but E-commerce entrepreneurs as well. © 2020 Informa UK Limited, trading as Taylor & Francis Group.","big data analytics; intelligent manufacturing systems; machine learning; performance measures; real time scheduling","Advanced Analytics; Big data; Cleaning; Data Analytics; Electronic commerce; Learning algorithms; Learning systems; Machine learning; Real time systems; Security of data; Transportation routes; Business modeling; E-commerce business; Intelligent manufacturing system; Internet of Things (IOT); Logistics management; Machine learning techniques; Performance measure; Real - time scheduling; Internet of things",{"$nulls":4},"Sichuan County Economic Development Research Center, (xy2018023); Sichuan petroleum and natural gas development research center, (SKB18-02); National Natural Science Foundation of China, NSFC, (18BJL075, 71473204, 71673226); Fundamental Research Funds for the Central Universities, (2020YJG065, JBK1902054, JBK2002051)","This study is funded by Fundamental Research Funds for the Central Universities [grant numbers  JBK1902054, JBK2002051 and 2020YJG065]; China National Natural Science Foundation [grant numbers  71673226 and 71473204]; the Sichuan petroleum and natural gas development research center [grant number SKB18-02]; China National Social Science Foundation [grant number 18BJL075]; Sichuan County Economic Development Research Center [grant number xy2018023].","Alberto C., Dirk S., Cloud Manufacturing as a New Type of Product-Service System, International Journal of Computer Integrated Manufacturing, (2018); Andrews K.R., A Concept of Corporate Strategy, (1971); Cecil J., Albuhamood S., Ramanathan P., Gupta A., An Internet-of-Things (IoT) Based Cyber Manufacturing Framework for the Assembly of Microdevices, International Journal of Computer Integrated Manufacturing, 32, 4-5, pp. 430-440, (2019); Chen H., Chiang R.H.L., Storey V.C., Business Intelligence and Analytics: From Big Data to Big Impact, MIS Quarterly, 36, pp. 1165-1188, (2012); Chen C.L.P., Zhang C.Y., Data-Intensive Applications, Challenges, Techniques and Technologies: A Survey on Big Data, Information Sciences, 275, 11, pp. 314-347, (2014); 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Kumar P.M., Gandhi U., Varatharajan R., Manogaran G.R.J., Vadivel T., Intelligent Face Recognition and Navigation System Using Neural Learning for Smart Security in Internet of Things, Cluster Computing, pp. 1-12, (2017); Liu F., Hirano M., Autonomous Decentralized Enterprise Model–A New Wave in Web 2.0 Type E-Commerce, E-commerce, (2010); Liu C., Li Y., Tang J., Next Generation Integrated Smart Manufacturing Based on Big Data Analytics, Reinforced Learning, and Optimal Routes Planning Methods, International Journal of Computer Integrated Manufacturing, 32, 9, pp. 820-831, (2019); Liu N., Zhang J., Yang X., Research on “Internet + Washing” Model, Rural Economy and Technology, 29, 11, pp. 179-180, (2008); Lytras M.D., Raghavan V., Damiani E., Big Data and Data Analytics Research: From Metaphors to Value Space for Collective Wisdom in Human Decision Making and Smart Machines, International Journal on Semantic Web and Information Systems, 13, 1, pp. 1-10, (2017); Manogaran G., Thota C., Kumar M.V., MetaCloudDataStorage Architecture for Big Data Security in Cloud Computing, Procedia Computer Science, 87, pp. 128-133, (2016); Naisa M.A.K., Usman B., The Impact of Information Technology on Entrepreneurship: A Case Study of Technology Incubation Center Kano Nigeria, British Journal of Surgery, 56, 5, pp. 21-33, (2016); Poel M., Renda A., Ballon P., Business Model Analysis as a New Tool for Policy Evaluation: Policies for Digital Content Platforms, info, 9, 5, pp. 86-100, (2007); Rasouli M., An Architecture for IoT-Enabled Intelligent Process-Aware Cloud Production Platform: A Case Study in a Networked Cloud Clinical Laboratory, International Journal of Production Research, (2019); Rathore M.M., Paul A., Ahmad A., Jeon G., IoT-Based Big Data: From Smart City towards Next Generation Super City Planning, International Journal on Semantic Web and Information Systems, 13, 1, pp. 28-47, (2017); Song W., Zhang H., Tong L., C-W Algorithm for Vehicle Routing Problem of Non-Full Loads with Time Windows, Journal of Northeastern University, (2006); Steven J., Samuel F., Shahriar A., Rameshwar D., Stephen J., Modelling Quality Dynamics, Business Value and Firm Performance in a Big Data Analytics Environment, International Journal of Production Research, 55, 17, pp. 5011-5026, (2017); Sven W., Eric H., Logistics 4.0: A Systematic Review towards a New Logistics System, International Journal of Production Research, (2019); Tong Z., How to Understand “Internet + Life Service” in the Transformation and Upgrading of Traditional Household Management Enterprises Under the Community O2O Wave?, Family Services, 4, pp. 54-55, (2016); Tucker S.-P., E-Commerce Standard Users Interface: Design and Implementation, (2018); Wang J., Zhang J., Big Data Analytics for Forecasting Cycle Time in Semiconductor Wafer Fabrication System, International Journal of Production Research, 54, 23, pp. 7231-7244, (2016); Zhang J., Fang W., Improved Genetic Algorithm for Vehicle Routing Problem with Time Window, Computer Engineering and Applications, (2010); Zhong R., Xu C., Chen C., Huang H., Big Data Analytics for Physical Internet-Based Intelligent Manufacturing Shop Floors, International Journal of Production Research, 55, 9, pp. 2610-2621, (2017)","L. Wu; School of Economics, Sichuan University, Chengdu, China; email: LiangWu@scu.edu.cn",null,"Taylor and Francis Ltd.",{"$nulls":5},207543.0,null,"IJPRB",null,"English","Int J Prod Res","Article","Final",null,"Scopus","2-s2.0-85079716591"]
["Goutam D.; Gopalakrishna B.V.; Ganguli S.","Goutam, Doddahulugappa (57203891324); Gopalakrishna, B.V. (57193438956); Ganguli, Shirshendu (36469988700)","57203891324; 57193438956; 36469988700","Determinants of customer satisfaction and loyalty in e-commerce settings: An emerging economy perspective",2021.0,"International Journal of Internet Marketing and Advertising",15.0,3.0,null,327.0,348.0,21.0,13.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85108013633&partnerID=40&md5=5b597bbc59c01b7fd28e2ceaaeeca892","School of Management, National Institute of Technology Karnataka, Surathkal, NH-66, Srinivasnagar, Mangalore, Karnataka, 575025, India; T A Pai Management Institute, Badagabettu Road, Manipal, Karnataka, 576104, India","Goutam D., School of Management, National Institute of Technology Karnataka, Surathkal, NH-66, Srinivasnagar, Mangalore, Karnataka, 575025, India; Gopalakrishna B.V., School of Management, National Institute of Technology Karnataka, Surathkal, NH-66, Srinivasnagar, Mangalore, Karnataka, 575025, India; Ganguli S., T A Pai Management Institute, Badagabettu Road, Manipal, Karnataka, 576104, India","E-commerce is one of the rapidly mushrooming industries in the world. The rapid development of information technology has granted numerous opportunities for e-commerce players as well as online shoppers. In this era of digital-marketing, satisfying customers becomes one of the fundamental goals of the e-retailers. Specifically, earning the satisfaction and loyalty of consumers and sustaining in the business is an arduous challenge for e-retailers in this competitive market. Additionally, the influencing factors that drive the customers' purchase decisions in the e-commerce platform are also an essential consideration. This study explores the determinants of consumer satisfaction and loyalty in an e-commerce environment. The researchers propose website service quality, privacy, product quality, price, and timely delivery as predominant determinants of e-satisfaction and e-loyalty. The final sample size was a total of 230 online buyers. Hypotheses were tested using structural equation modelling (SEM). The findings indicate that the price, product quality and timely delivery have a positive effect on e-satisfaction as well as e-loyalty. However, website service quality does not affect e-satisfaction and e-loyalty. The study infers that privacy affect only e-satisfaction. Correspondingly, the study reveals that there is a direct and significant impact of e-satisfaction on e-loyalty. © 2021 Inderscience Enterprises Ltd.. All rights reserved.","e-commerce; e-loyalty; e-satisfaction; SEM.; structural equation modelling",{"$nulls":7},"Agrawal M., Sandhir V., Gupta G., Emerging profile of online apparel shoppers in India and comparison with the US Online shoppers: A few marketing implications?, Advances in Consumer Research, 8, 6, (2009); Alexander B., Hess T., The signaling role of IT features in influencing trust and participation in online communities?, International Journal of Electronic Commerce, 15, 4, pp. 7-56, (2011); Anderson R.E., Srinivasan S.S., E-satisfaction and e-loyalty: A contingency framework?, Psychology and Marketing, 20, 2, pp. 123-138, (2003); Asubonteng P., Mccleary K.J., Swan J.E., SERVQUAL revisited: A critical review of service quality?, Journal of Services Marketing, 10, 6, pp. 62-81, (1996); Azam A., Investigation of psychological dimensions of trust on e-loyalty: A case of Saudi Arabian consumers?, Journal of Islamic Marketing, 6, 2, pp. 224-249, (2015); Bansal G., Gaurav F., Zahedi M., Gefen D., Trust violation and repair: The information privacy perspective?, Decision Support Systems, 1, 71, pp. 62-77, (2015); Cao Y., Gruca T.S., Klemz B.R., Internet pricing, price satisfaction, and customer satisfaction?, International Journal of Electronic Commerce, 8, 2, pp. 31-50, (2003); Chao Y., Lee G.Y., Ho Y.C., Customer loyalty in virtual environments: An empirical study in e-bank?, AIP Conference Proceedings, 148, 1, pp. 497-500, (2009); Chiu C.M., Lin H.Y., Sun S.Y., Hsu M.H., Understanding customers? loyalty intentions towards online shopping: An integration of technology acceptance model and fairness theory?, Behaviour and Information Technology, 28, 4, pp. 347-360, (2009); Chou S., Chen C.W., Lin J.Y., Female online shoppers: examining the mediating roles of e-satisfaction and e-Trust on e-loyalty development?, Internet Research, 25, 4, pp. 542-561, (2015); Crosby L.A., Stephens N., Effects of relationship marketing on satisfaction retention, and prices in the life insurance industry?, Journal of Marketing Research, 24, 4, pp. 404-411, (1987); Devaraj S., Fan M., Kohli R., Antecedents of B2C channel satisfaction and preference: validating e-commerce metrics?, Information Systems Research, 13, 3, pp. 316-333, (2002); Fang Y.H., Chiu C.M., Wang E.T.G., Understanding customers? satisfaction and repurchase intentions?, Internet Research, 21, 4, (2011); Flavian C., Guinaliu M., Consumer trust, perceived security and privacy policy: Three basic elements of loyalty to a web site?, Industrial Management and Data Systems, 106, 5, pp. 601-620, (2006); Fornell C., Larcker D.F., Evaluating structural equation models with unobservable variables and measure?, Journal of Marketing Research, 18, 1, pp. 39-50, (1981); Gefen D., E-commerce: The role of familiarity and trust?, Omega, 28, 6, pp. 725-737, (2000); Gefen D., Customer loyalty in e-commerce?, Journal of the Association for Information Systems, 3, 27, (2002); Goutam D., Gopalakrishna B.V., Customer loyalty development in online shopping: An integration of e-service quality model and commitment-Trust theory?, Management Science Letters, 8, 11, pp. 1149-1158, (2018); Greenaway K.E., Chan Y.E., Crossler R.E., Company information privacy orientation: A conceptual framework?, Information Systems Journal, 25, 6, pp. 579-606, (2015); Gronroos C., Strategic Management and Marketing in the Service Sector, (1983); Grosso M., Castaldo S., How store attributes impact shoppers? loyalty: do different national cultures follow the same loyalty building process, The International Review of Retail, Distribution and Consumer Research, 25, 5, pp. 503-515, (2015); Ha H.Y., Factors influencing consumer perceptions of brand trust online?, Journal of Product and Brand Management, 13, 5, pp. 329-342, (2004); Hair J.F., Black W.C., Babin B.J., Anderson R.E., Tatham L.R., Multivariate Data Analysis, (2006); Handa M., Gupta N., A study of the relationship between shopping orientation and online shopping behavior among Indian youth?, Journal of Internet Commerce, 13, 1, pp. 22-44, (2014); Huffmire D., Improving customer satisfaction, loyalty, and profit: An integrated measurement and management system?, Choice, 38, 5, pp. 946-947, (2001); Iglesias M.P., Guillen M.J.Y., Perceived quality and price: Their impact on the satisfaction of restaurant customers?, International Journal of Contemporary Hospitality Management, 16, 6, pp. 373-379, (2006); Jayachandran S., Sharma S., Kaufman P., Raman P., The role of relational information processes and technology use in customer relationship management?, Journal of Marketing, 69, 4, pp. 177-192, (2005); Jin B., Park J.Y., Kim J., Cross-cultural examination of the relationships among firm reputation, e-satisfaction, e-Trust, and e-loyalty?, International Marketing Review, 25, 3, pp. 324-337, (2008); Kalia P., Demographic profile of online shoppers: An overview?, Indian Journal of Economics and Development, 12, 1a, pp. 37-41, (2016); Kaura V., Ch S., Prasad D., Sharma S., Service quality, service convenience, price and fairness, customer loyalty, and the mediating role of customer satisfaction?, International Journal of Bank Marketing, 33, 4, pp. 404-422, (2015); Kim D.J., A study of the multilevel and dynamic nature of trust in e-commerce from a cross-stage perspective?, International Journal of Electronic Commerce, 19, 1, pp. 11-64, (2014); Fulfilled: Indian?s E-Commerce Retail Logistics Growth Story, (2015); Kumar V., Dange U., E-retailing in India-A study of consumers? Internet usage pattern, their profile and their shopping pattern?, Ujwala, E-Retailing in India-A Study of Consumers?, (2014); Kumar V., Petersen J.A., Customer Relationship Management, (2012); Lai C.S., Chen C.S., Lin P.J., The effects of service quality on customer relational benefits in a travel website?, Portland International Center for Management of Engineering and Technology, Proceedings-Management of Converging Technologies, 1, 6, pp. 1133-1140, (2007); Lehtinen U., Lehtinen J.R., Service Quality: A Study of Quality Dimensions, (1982); Lin G.T.R., Sun C.C., Factors influencing satisfaction and loyalty in online shopping: An integrated model?, Online Information Review, 33, 3, pp. 458-475, (2009); Mazhar F., Jam F.A., Anwar F., Consumer trust in e-commerce: A study of consumer perceptions in Pakistan?, African Journal of Business Management, 6, 7, pp. 2516-2528, (2012); Miceli G.N., Raimondo M.A., Farace S., Customization and brand in customer identity communication?, Association for Consumer Research European Advances, 10, 1, pp. 283-284, (2013); Milne G.R., Culnan M.J., Using the content of online privacy notices to inform public policy: A longitudinal analysis of the 1998-2001 US Web surveys?, The Information Society, 18, 5, pp. 345-359, (2002); Milne G.R., Culnan M.J., Strategies for reducing online privacy risks: why consumers read (or don?t read) online privacy notices?, Journal of Interactive Marketing, 18, 3, pp. 15-29, (2004); Nayyar R., Gupta S.L., Impact of changing demographic profiles of Indian customers on their internet shopping behaviour?, Viewpoint, 51, 3, pp. 17-24, (2010); Oliver R., A cognitive model of the antecedents and consequences of satisfaction decisions?, Journal of Marketing Research, 17, 4, pp. 460-469, (1980); Pandey S., Chawla D., Using qualitative research for establishing content validity of e-lifestyle and website quality constructs?, Qualitative Market Research: An International Journal, 19, 3, pp. 339-356, (2016); Parasuraman A., Zeithaml V.A., Berry L.L., A conceptual model of service quality and its implications for future research?, Journal of Marketing, 49, 4, pp. 41-50, (1985); Pereira H.G., De M., Salgueiro F., Rita P., Online purchase determinants of loyalty: The mediating effect of satisfaction in tourism?, Journal of Retailing and Consumer Services, 30, 1, pp. 279-291, (2016); Pfeifer P.E., Ovchinnikov A., A note on willingness to spend and customer lifetime value for firms with limited capacity?, Journal of Interactive Marketing, 25, 3, pp. 178-189, (2011); Phelps J., Nowak G., Ferrell E., Privacy concerns and consumer willingness to provide personal information?, Journal of Public Policy and Marketing, 19, 1, pp. 27-41, (2000); Prashar S., Sai Vijay T., Parsad C., Effects of online shopping values and website cues on purchase behaviour: A study using S-O-R framework?, Vikalpa, 42, 1, pp. 1-18, (2017); Rastogi A.K., A study of Indian online consumers & their buying behaviour?, International Research Journal, 1, 10, pp. 80-82, (2010); Ribbink D., Riel A.C.R.V., Liljander V., Streukens S., Comfort your online customer: quality, trust and loyalty on the internet?, Managing Service Quality, An International Journal, 14, 6, pp. 446-456, (2004); Richards K.A., Jones E., Customer relationship management: finding value drivers?, Industrial Marketing Management, 37, 2, pp. 120-130, (2008); Schoenbachler D.D., Gordon G.L., Trust and customer willingness to provide information in database- driven relationship marketing?, Journal of Interactive Marketing, 16, 3, pp. 2-16, (2002); Shih H.P., An empirical study on predicting user acceptance of e-shopping on the web?, Information Management, 41, 3, pp. 351-369, (2004); Su Q., Li Z., Song Y.T., Chen T., Conceptualizing consumers? perceptions of e-commerce quality?, International Journal of Retail and Distribution Management, 36, 5, pp. 360-374, (2007); Swartz T.A., Brown S.W., Consumer and provider expectations and experience in evaluating professional service quality?, Journal of the Academy of Marketing Science, 17, 2, pp. 189-195, (1989); Szymanski D.M., Hise R.T., E-satisfaction: An initial examination?, Journal of Retailing, 76, 3, pp. 309-322, (2000); Tsao W.C., Hsieh M.T., eWOM persuasiveness: Do eWOM platforms and product type matter?, Electronic Commerce Research, 15, 4, pp. 509-541, (2015); Verhoef P.C., Kannan P.K., Inman J.J., From multi-channel retailing to Omni-channel retailing: introduction to the special issue on multi-channel retailing?, Journal of Retailing, 91, 2, pp. 174-181, (2015); White T.B., Consumer disclosure and disclosure avoidance: A motivational frame work?, Journal of Consumer Psychology, 14, 1-2, pp. 41-51, (2004); White T.B., Novak T.P., Hoffman D.L., No strings attached: when giving it away versus making them pay reduces consumer information disclosure?, Journal of Interactive Marketing, 28, 3, pp. 184-195, (2014)","S. Ganguli; T A Pai Management Institute, Manipal, Karnataka, Badagabettu Road, 576104, India; email: shirshenduganguli@tapmi.edu.in",null,"Inderscience Publishers",{"$nulls":5},1.4775212E7,null,null,null,"English","Int. J. Internet Mark. Advert.","Article","Final",null,"Scopus","2-s2.0-85108013633"]
["Zimmermann T.; Bliklen R.","Zimmermann, Till (55279306900); Bliklen, Rebecca (57219841829)","55279306900; 57219841829","Single-use vs. reusable packaging in e-commerce: Comparing carbon footprints and identifying break-even points",2020.0,"GAIA - Ecological Perspectives for Science and Society",29.0,3.0,null,176.0,183.0,7.0,17.0,"10.14512/GAIA.29.3.8","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85095707709&doi=10.14512%2fGAIA.29.3.8&partnerID=40&md5=b41c6a10ad59804ceef5e1935cfdaef9","Ökopol Institute for Environmental Strategies, Nernstweg 32-34, Hamburg, 22765, Germany","Zimmermann T., Ökopol Institute for Environmental Strategies, Nernstweg 32-34, Hamburg, 22765, Germany; Bliklen R., Ökopol Institute for Environmental Strategies, Nernstweg 32-34, Hamburg, 22765, Germany","In Germany, the revenue of e-commerce amounted to over 68 billion euros in 2018 with over two billion shipments being delivered. Up to 30 percent of online retail's carbon footprint comes from the use of shipping packaging. Reusable packaging could make a significant contribution to resource savings and waste avoidance. Few valid findings exist as to the environmental performance of reusable packaging systems in online retail. It is also difficult to ascertain which factors influence these results most (such as material, weight, number of cycles). Against this backdrop, we examined two types of reusable shipping packaging in terms of their CO2eq emissions: A reusable PP box and a reusable shipping bag. Both were then compared with single-use alter - natives. Compared to a single-use LDPE bag, the reusable shipping bag offered an environmental advantage after a few cycles, with the absolute carbon footprint of both bags depending on whether recycled material was used. For the reusable PP box, the break-even point was between 32 and 81 cycles, depending on which assumptions were made. For a broader application of reusable shipping packaging, further challenges arise, such as the cost-efficient design of return logistics or the optimization of the packaging design. © 2020 Oekom Verlag. All rights reserved.","Carbon footprint; E-commerce; Packaging waste; Reusable packaging",{"$nulls":5},"German Ministry for Research and Education; Bundesministerium für Bildung und Forschung, BMBF, (033R243A)","This work is part of the project praxPACK and has been funded by the German Ministry for Research and Education (BMBF; grant number 033R243A).","Interaktiver Handel in Deutschland: Ergebnisse 2018, (2019); Clever verpackt -effizient zugestellt: KEP-Studie 2019 - Analyse des Marktes in Deutschland, (2019); Cooper D. R., Gutowski T. G., The environmental impacts of reuse: A review, Journal of Industrial Ecology, 21, 1, pp. 38-56, (2017); Klimafreundlich einkaufen. Eine vergleichende Betrachtung von Onlinehandel und stationärem Einzelhandel, (2015); Edwards J. B., McKinnon A. C., Cullinane S. L., Comparative analysis of the carbon footprints of conventional and online retailing, International Journal of Physical Distribution and Logistics Management, 40, 1-2, pp. 103-123, (2010); Edwards J., McKinnon A., Cullinane S., Comparative carbon auditing of conventional and online retail supply chains: A review of methodological issues, Supply Chain Management, 16, 1, pp. 57-63, (2011); Waste reduction model WARM, (2015); Comparative life cycle assessment of reusable plastic containers and display and non-display ready corrugated containers used for fresh produce applications, (2017); Associates Franklin, Life cycle impacts for postconsumer recycled resins: PET, HDPE, and PP, pp. 119-124, (2018); Online Monitor 2019, (2019); Hischier R., Car vs. Packaging: A first, simple (environmental) sustainability assessment of our changing shopping behaviour, Sustainability, 10, 9, (2018); Jepsen D., Spengler L., Reihlen A., Vollmer A., Themenbereich B: Methoden. Themenblock 1: Ökodesign-Prinzipien. B1.1 Langlebigkeit, (2016); Jepsen D., Zimmermann T., Rodig L., Eco Design von Kunststoff-Verpackungen. Der Management-Leitfaden des Runden Tisches, (2019); Kahlenborn W., Keppner B., Uhle C., Richter S., Jetzke T., Die Zukunft im Blick: Konsum 4.0: Wie Digitalisierung den Konsum verändert. Trendbericht zur Abschätzung der Umweltwirkungen, (2018); Keith J., Methodology for assessing the climate change impacts of packaging optimisation under the Courtauld Commitment Phase 2, (2010); Mangiaracina R., Marchet G., Perotti S., Tumino A., A review of the environmental implications of B2C e-commerce: A logistics perspective, International Journal of Physical Distribution and Logistics Management, 45, 6, pp. 565-591, (2015); The great consumer shift: Ten charts that show how US shopping behavior is changing, (2020); Mottschall M., Online shoppen oder beim lokalen Händler?, (2015); Olah J., Kitukutha N., Haddad H., Pakurar M., Mate D., Popp J., Achieving sustainable e-commerce in environmental, social and economic dimensions by taking possible trade-offs, Sustainability, 11, 1, (2019); Group Otto, Geschäftsbericht 2018/2019: Hallo Mensch. Wie wir die digitale Zukunft gemeinsam gestalten können, (2019); Eco-profiles, (2005); Carton Pro, The Carbon footprint of carton packaging 2019: Executive summary, (2019); Carbon-Footprint-Report-2019-Exec-Summary-English-1.pdf; Raugei M., Fullana Palmer P., Puig Vidal R., Torres A., Single-use vs reusable transport packaging: A comparative life cycle analysis, Packaging Technology and Science, 22, 8, pp. 443-450, (2009); Reitz A., Versandverpackungen. Bestandsaufnahme von Mengen und Materialdaten, (2020); Nachhaltigkeitsbilanz 2015, (2016); Teststart mit Mehrwegversandtaschen bei Tchibo, Otto und Avocado store, (2020); ProBas - Prozessorientierte Basisdaten für Umweltmanagementsysteme, (2015); Emissionskennzahlen Datenbasis 2017: Emissionsfaktoren bezogen auf Personen-/Tonnenkilometer, (2019); Entwicklung der spezifischen Kohlendioxid-Emissionen des deutschen Strommix in den Jahren 1990-2018, (2019); van Loon P., Deketele L., Dewaele J., McKinnon A., Rutherford C., A comparative analysis of carbon emissions from online retailing of fast moving consumer goods, Journal of Cleaner Production, 106, pp. 478-486, (2015); Weber C. L., Hendrickson C.T., Matthews H. S., Nagengast A., Nealer R., Jaramillo P., Life cycle comparison of traditional retail and e-commerce logistics for electronic products: A case study of buy.com, 2009 IEEE International Symposium on Sustainable Systems and Tech nology, (2008); Wiese A., Sustainability in retailing: Environmental effects of transport processes, shopping trips and related consumer behaviour, (2013); Wood G., Sturges M., Single trip or reusable packaging: Considering the right choice for the environment, (2010); Geschäftsbericht 2018, (2019)",null,null,"Oekom Verlag",{"$nulls":5},9405550.0,null,null,null,"English","GAIA - Ecological Perspectives for Science and Society","Article","Final",null,"Scopus","2-s2.0-85095707709"]
["Dutta P.; Choi T.-M.; Somani S.; Butala R.","Dutta, Pankaj (16244453500); Choi, Tsan-Ming (7202769936); Somani, Surabhi (57219222450); Butala, Richa (57219221553)","16244453500; 7202769936; 57219222450; 57219221553","Blockchain technology in supply chain operations: Applications, challenges and research opportunities",2020.0,"Transportation Research Part E: Logistics and Transportation Review",142.0,null,102067.0,null,null,null,581.0,"10.1016/j.tre.2020.102067","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85091753252&doi=10.1016%2fj.tre.2020.102067&partnerID=40&md5=da3898d055c533d51a72d1813eca4d78","Faculty of Decision Sciences, Shailesh J. Mehta School of Management, Indian Institute of Technology Bombay, Powai, Mumbai, 400076, India; Institute of Textiles and Clothing, The Hong Kong Polytechnic University, 11 Yuk Choi Road, Kowloon, Hong Kong; Shailesh J. Mehta School of Management, Indian Institute of Technology Bombay, Powai, Mumbai, 400076, India","Dutta P., Faculty of Decision Sciences, Shailesh J. Mehta School of Management, Indian Institute of Technology Bombay, Powai, Mumbai, 400076, India; Choi T.-M., Institute of Textiles and Clothing, The Hong Kong Polytechnic University, 11 Yuk Choi Road, Kowloon, Hong Kong; Somani S., Shailesh J. Mehta School of Management, Indian Institute of Technology Bombay, Powai, Mumbai, 400076, India; Butala R., Shailesh J. Mehta School of Management, Indian Institute of Technology Bombay, Powai, Mumbai, 400076, India","Blockchain is a technology with unique combination of features such as decentralized structure, distributed notes and storage mechanism, consensus algorithm, smart contracting, and asymmetric encryption to ensure network security, transparency and visibility. Blockchain has immense potential to transform supply chain (SC) functions, from SC provenance, business process reengineering to security enhancement. More and more studies exploring the use of blockchain in SCs have appeared in recent years. In this paper, we consider a total of 178 articles and examine all the relevant research done in the field associated with the use of blockchain integration in SC operations. We highlight the corresponding opportunities, possible societal impacts, current state-of-the-art technologies along with major trends and challenges. We examine several industrial sectors such as shipping, manufacturing, automotive, aviation, finance, technology, energy, healthcare, agriculture and food, e-commerce, and education among others that can be successfully revamped with blockchain based technologies through enhanced visibility and business process management. A future research agenda is established which lays the solid foundation for further studies on this important emerging research area. © 2020 Elsevier Ltd","Applications; Blockchain; Integration; Literature review; Logistics; Supply chain","Cryptography; Engineering education; Network security; Reengineering; Supply chains; Visibility; Asymmetric encryption; Block-chain; Consensus algorithms; Decentralized structures; Literature reviews; Networks security; Research opportunities; Storage mechanism; Supply chain functions; Supply chain operation; decentralization; Internet; literature review; research work; supply chain management; technology adoption; trend analysis; Blockchain",{"$nulls":4},"Hong Kong Polytechnic University, PolyU, (P0009192)","The authors sincerely thank the guest editor and three reviewers for their critical comments which led to significant improvement of this paper. Tsan-Ming Choi's research is partially supported by The Hong Kong Polytechnic University (Project no.: P0009192 ). ",{"$cut":{"chars":32577,"head":"Al-Jaroodi J., Mohamed N., Blockchain in Industries: A survey, IEEE Access, 7, pp. 36500-36515, (2019); Al-Saqaf W., Seidler N., Blockchain technology for social impact: opportunities and challenges ahead, J. Cyber Policy, 2, 3, pp. 338-354, (2017); Alkhodre A., Jan S., Khusro S., Ali T., Alsaawy Y., Yasar M., A blockchain-based value added tax (VAT) system: Saudi Arabia as a use-case, Int. J. Adv. Comput. Sci. Appl., 10, 9, pp. 708-716, (2019); Allen D.W., Berg C., Davidson S., Novak M., Potts J., International policy coordination for blockchain supply chains, Asia Pacific Policy Stud., 6, 3, pp. 367-380, (2019); Arza O., Choi T.M., Olson D., Salman S., Role of analytics for operational risk management in the era of big data, Decision Sci., published online, (2020); Astarita V., Giofre V.P., Mirabelli G., Solina V., A review of blockchain-based systems in transportation, Information, 11, 1, (2020); Astill J., Dara R.A., Campbell M., Farber J.M., Fraser E.D., Sharif S., Yada R.Y., Transparency in food supply chains: A review of enabling technology solutions, Trends Food Sci. Technol., 91, pp. 240-247, (2019); Azzi R., Chamoun R.K., Sokhn M., The power of a blockchain-based supply chain, Comput. Ind. Eng., 135, pp. 582-592, (2019); Babich V., Hilary G., Distributed ledgers and operations: What operations management researchers should know about blockchain technology, Manuf. Service Oper. Manage., (2019); Behnke K., Janssen M.F.W.H.A., Boundary conditions for traceability in food supply chains using blockchain technology, Int. J. Inf. Manage., (2019); Bencic F.M., Skocir P., Zarko I.P., DL-Tags: DLT and smart tags for decentralized, privacy-preserving, and verifiable supply chain management, IEEE Access, 7, pp. 46198-46209, (2019); Betti Q., Khoury R., Halle S., Montreuil B., Improving hyperconnected logistics with blockchains and smart contracts, IT Prof., 21, 4, pp. 25-32, (2019); Bogucharskov A.V., Pokamestov I.E., Adamova K.R., Tropina Z.N., Adoption of blockchain technology in trade finance process, J. Rev. Global Econ., 7, pp. 510-515, (2018); Bumblauskas D., Mann A., Dugan B., Rittmer J., A blockchain use case in food distribution: Do you know where your food has been?, Int. J. Inf. Manage., (2019); Cachon G.P., Supply chain coordination with contracts, Handbooks Oper. Res. Manage. Sci., 11, pp. 227-339, (2003); Cai Y., Choi T.M., Zhang J., Platform supported supply chain operations in the blockchain era: supply contracting and moral hazards, Decision Sci., (2020); Casino F., Dasaklis T.K., Patsakis C., A systematic literature review of blockchain-based applications: Current status, classification and open issues, Telematics Inform., 36, pp. 55-81, (2019); Chan K.Y., Abdullah J., Khan A.S., A Framework for traceable and transparent supply chain management for agri-food sector in Malaysia using blockchain technology, Int. J. Adv. Comput. Sci. Appl., 10, 11, pp. 149-156, (2019); Chang S.E., Chen Y.-C., Lu M.-F., Supply chain re-engineering using blockchain technology: A case of smart contract based tracking process, Technol. Forecast. Soc. Chang., 144, pp. 1-11, (2019); Chang Y., Iakovou E., Shi W., Blockchain in global supply chains and cross border trade: a critical synthesis of the state-of-the-art, challenges and opportunities, Int. J. Prod. Res., pp. 1-18, (2019); Chavez-Dreyfuss G., (2019); Chen T., Wang D., Combined application of blockchain technology in fractional calculus model of supply chain financial system, Chaos, Solitons Fractals, 131, (2020); Cho S.H., Park S.Y., Lee S.R., Blockchain consensus rule based dynamic blind voting for non-dependency transaction, Int. J. Grid Distrib. Comput., 10, 12, pp. 93-106, (2017); Choi T.M., Blockchain-technology-supported platforms for diamond authentication and certification in luxury supply chains, Transport. Res. Part E: Logist. Transport. Rev., 128, pp. 17-29, (2019); Choi T.M., Creating all-win by blockchain technology in supply chains: Impacts of agents’ risk attitudes towards cryptocurrency, J. Oper. Res. Soc., (2020); Choi T.M., Innovative “Bring-Service-Near"}},"P. Dutta; Faculty of Decision Sciences, Shailesh J. Mehta School of Management, Indian Institute of Technology Bombay, Mumbai, Powai, 400076, India; email: pdutta@iitb.ac.in",null,"Elsevier Ltd",{"$nulls":5},1.3665545E7,null,null,null,"English","Transp. Res. Part E Logist. Transp. Rev.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85091753252"]
["Chen J.; Dan B.; Shi J.","Chen, Jiumei (23134762700); Dan, Bin (7004780554); Shi, Jing (55485966800)","23134762700; 7004780554; 55485966800","A variable neighborhood search approach for the multi-compartment vehicle routing problem with time windows considering carbon emission",2020.0,"Journal of Cleaner Production",277.0,null,123932.0,null,null,null,31.0,"10.1016/j.jclepro.2020.123932","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85090580996&doi=10.1016%2fj.jclepro.2020.123932&partnerID=40&md5=dcbf2b79a9a00a88a4c88177e84e982f","Chongqing Engineering Research Center for Processing, Storage and Transportation of Characterized Agro-Products, Chongqing, 400067, China; Chongqing Key Laboratory of Electronic Commerce and Supply Chain System, Chongqing Technology and Business University, Chongqing, 400067, China; Collaborative Innovation Center for Chongqing's Modern Trade Logistics & Supply Chain, Chongqing Technology and Business University, Chongqing, 400067, China; School of Economics & Business Administration Chongqing University, Chongqing, 400044, China; Department of Mechanical & Materials Engineering College of Engineering and Applied Science University of Cincinnati, Cincinnati, 45221, OH, United States","Chen J., Chongqing Engineering Research Center for Processing, Storage and Transportation of Characterized Agro-Products, Chongqing, 400067, China, Chongqing Key Laboratory of Electronic Commerce and Supply Chain System, Chongqing Technology and Business University, Chongqing, 400067, China, Collaborative Innovation Center for Chongqing's Modern Trade Logistics & Supply Chain, Chongqing Technology and Business University, Chongqing, 400067, China; Dan B., School of Economics & Business Administration Chongqing University, Chongqing, 400044, China; Shi J., Department of Mechanical & Materials Engineering College of Engineering and Applied Science University of Cincinnati, Cincinnati, 45221, OH, United States","In recent years, fresh food e-commerce has developed rapidly and become a new strategic field for traditional e-commerce firms. Logistics is one of the bottlenecks in its development. Each type of fresh food has its own temperature requirements during transportation. In this paper, the multi-compartment vehicle routing problem with time window (MCVRPTW) arising in fresh food e-commerce is proposed to include the consideration of carbon emission. A variable neighborhood search (VNS) approach with the key steps of local search and shaking is proposed to solve the MCVRPTW formulation. For the VNS approach, three operators are used in the local search phase, and two kinds of operators based on path relinking are adopted in the shaking phase. Extensive efforts are made to verify the proposed approach. Firstly, the parameters are tuned based on Taguchi method. Secondly, the approach is compared with representative algorithms in the literature to solve VRPTW instances and MCVRPTW instances. For the VRPTW cases, VNS outperforms a well-known benchmark algorithm by 4–7%, and the overall average gap between the VNS solutions and the known best solutions is only 1.93%. For the MCVRPTW instances, VNS produces the same or improved “best solution” in the majority of the 24 instances with less than 30% of running time, compared with two existing MCVRPTW algorithms. Finally, VNS is employed to solve a real-world case, and the results show that the total cost of the solution is 36.38% lower than the actual operation. Overall, this study takes the minimum total of travel cost, fixed cost, refrigeration cost and carbon emission cost as the optimization objective, and the findings are conducive to reducing energy consumption and carbon emission in the fresh e-commerce delivery process. © 2020 Elsevier Ltd","Carbon emission; Fresh food E-commerce; Multi-compartment vehicle routing problem with time windows; Path relinking; Variable neighborhood search","Carbon; Electronic commerce; Energy utilization; Local search (optimization); Taguchi methods; Actual operation; Carbon emissions; Delivery process; Path relinking; Reducing energy consumption; Running time; Variable neighborhood search; Vehicle routing problem with time windows; Vehicle routing",{"$nulls":4},"National Social Science Foundation of China; Natural Science Foundation of Chongqing, (cstc2019jcyj-msxmX0569); National Office for Philosophy and Social Sciences, NPOPSS, (15ZDB169)","The first and the second authors acknowledge that the research was partly supported by the Major Program of the National Social Science Foundation of China (Grant number: 15ZDB169) and the Chongqing Natural Science Foundation of China (Grant number: cstc2019jcyj-msxmX0569).","Alzaqebah M., Abdullah S., Jawarneh S., Modified artificial bee colony for the vehicle routing problems with time windows, SpringerPlus, 5, 1, (2016); Amous M., Toumi S., Jarboui B., Eddaly M., A variable neighborhood search algorithm for the capacitated vehicle routing problem, Electron. 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Sci., 4, 2, pp. 166-176, (2019); Romero Ocano A.D., Cosio Leon M.D.L.A., Valenzuela Alcaraz V.M., Aviles Rodriguez G.J., Martinez Vargas A., Effect of parameters tuned by a Taguchi Design L_9 3^ 4 in the GRASP algorithm to solve the vehicle routing problem with time windows, Comput. Sist., 22, 2, pp. 657-673, (2018); Sanchez-Oro J., Lopez-Sanchez A.D., Colmenar J.M., A general variable neighborhood search for solving the multi-objective open vehicle routing problem, J. Heuristics, pp. 1-30, (2017); Solomon M.M., Algorithms for the vehicle routing and scheduling problems with time window and constraints, Oper. Res., 35, 2, pp. 254-266, (1987); Thuan N.D., Phat N.T., Nghia N.T., Improved Tabu Search Algorithm for Vehicle Routing Problem with Time Windows, pp. 283-291, (2019); Yassen E.T., Ayob M., Ahmad Nazri M.Z., Sabar N.R., A hybrid meta-heuristic algorithm for vehicle routing problem with time windows, Int. J. Artif. Intell. Tool., 24, 6, pp. 1-23, (2015); Zhang L.Y., Tseng M.L., Wang C.H., Et al., Low-carbon cold chain logistics using ribonucleic acid-ant colony optimization algorithm, J. Clean. Prod., 233, pp. 169-180, (2019)","J. Shi; Department of Mechanical & Materials Engineering College of Engineering and Applied Science University of Cincinnati, Cincinnati, 45221, United States; email: jing.shi@uc.edu",null,"Elsevier Ltd",{"$nulls":5},9596526.0,null,"JCROE",null,"English","J. Clean. Prod.","Article","Final",null,"Scopus","2-s2.0-85090580996"]
["Eliyan A.; Elomri A.; Kerbache L.","Eliyan, Afnan (56441616500); Elomri, Adel (56915869700); Kerbache, Laoucine (6602694753)","56441616500; 56915869700; 6602694753","The last-mile delivery challenge: evaluating the efficiency of smart parcel stations",2021.0,"Supply Chain Forum",22.0,4.0,null,360.0,369.0,9.0,4.0,"10.1080/16258312.2021.1918532","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85104851890&doi=10.1080%2f16258312.2021.1918532&partnerID=40&md5=761ce354f026a249ed35edacbd4b4d14","College of Engineering, Qatar University, Doha, Qatar; College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar; HEC Paris, France","Eliyan A., College of Engineering, Qatar University, Doha, Qatar, College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar; Elomri A., College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar; Kerbache L., College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar, HEC Paris, France","With recent advances in technology, e-commerce has significantly increased over the last decade. In response to higher customer expectations, last-mile delivery strategies need to be redesigned for companies to remain competitive in the market. In this setting, smart parcel stations (SPS) have been widely deployed in several countries as evidence and proof of concept for their viability in last mile delivery. Nevertheless, little empirical research has been done on wide logistic implications of the use of SPS in parcel delivery. To the best of our knowledge, this research work is among the first attempts to analysis the deployment of smart parcel stations as solution to the last mile delivery problem. We propose three different mathematical formulations to model a two-stage delivery problem where a retailer delivers parcels to set of customers via a set of SPS. The models were designed to capture many key performance indicators and efficiency measures including travelled distance, carbon emissions, customer service level, and smart parcel occupancy and utilisation. © 2021 Kedge Business School.","E-commerce; last mile; parcel delivery; smart parcel stations; supply chainmanagement",{"$nulls":5},"Qatar National Library","Open Access funding provided by the Qatar National Library.","Agatz N.A., Fleischmann M., Van Nunen J.A., E-fulfillment and Multi-channel Distribution–A Review, European Journal of Operational Research, 187, 2, pp. 339-356, (2008); Bayles D.L., Bhatia H., E-Commerce Logistics & Fulfillment: Delivering the Goods, (2000); Crainic T.G., Hewitt M., Toulouse M., Vu D.M., Service Network Design with Resource Constraints, Transportation Science, (2016); Deutsch Y., Golany B., A Parcel Locker Network as A Solution to the Logistics Last Mile Problem, International Journal of Production Research, 56, 1-2, pp. 251-261, (2018); Ehmke J.F., Mattfeld D.C., Vehicle Routing for Attended Home Delivery in City Logistics, Procedia - Social and Behavioral Sciences, 39, pp. 622-632, (2012); ‘Greenhouse Gases Equivalencies Calculator - Calculations and References’, (2020); Esper T.L., Jensen T.D., Turnipseed F.L., Burton S., The Last Mile: An Examination of Effects of Online Retail Delivery Strategies on Consumers, Journal of Business Logistics, 24, 2, pp. 177-203, (2003); Gevaers R., De Voorde E.V., Vanelslander T., Characteristics and Typology of Last-mile Logistics from an Innovation Perspective in an Urban Context, (2011); Ghajargar M., Zenezini G., Montanaro T., Home Delivery Services Innovations and Emerging Needs, IFAC-PapersOnLine, 49, 12, pp. 1371-1376, (2016); Huang Y.A.Y.K., The Evaluation of Logistics Service Quality on Home Delivery Service for On- Line Auction, ‘2008 IEEE International Conference on Service Operations and Logistics, and Informatics’, 1, (2008); Iwan S., Kijewska K., Lemke J., Analysis of Parcel Lockers’ Efficiency as the Last Mile Delivery Solution–The Results of the Research in Poland, Transportation Research Procedia, 12, pp. 644-655, (2016); Janjevic M., Winkenbach M., Characterizing Urban Last-mile Distribution Strategies in Mature and Emerging E-commerce Markets, Transportation Research Part A: Policy and Practice, 133, pp. 164-196, (2020); Jiang L., Dhiaf M., Dong J., Liang C., Zhao S., A Traveling Salesman Problem with Time Windows for the Last Mile Delivery in Online Shopping, International Journal of Production Research, 58, 16, pp. 5077-5088, (2020); Kollmann T., Kuckertz A., Kayser I., Cannibalization or Synergy? Consumers’ Channel Selection in Online–offline Multichannel Systems, Journal of Retailing and Consumer Services, 19, 2, pp. 186-194, (2012); Kull T., Boyer K., Calantone R., Last-mile Supply Chain Efficiency: An Analysis of Learning Curves in Online Ordering, International Journal of Operations & Production Management, 27, 4, pp. 409-434, (2007); Lemke J., Iwan S., Korczak J., Usability of the Parcel Lockers from the Customer Perspective–The Research in Polish Cities, Transportation Research Procedia, 16, pp. 272-287, (2016); Miller C.E., Tucker A.W., Zemlin R.A., Integer Programming Formulation of Traveling Salesman Problems, Journal of the ACM, 7, 4, pp. 326-329, (1960); Morganti E., Dablanc L., Fortin F., Final Deliveries for Online Shopping: The Deployment of Pickup Point Networks in Urban and Suburban Areas, Research in Transportation Business & Management, 11, pp. 23-31, (2014); Morganti E., Seidel S., Blanquart C., Dablanc L., Lenz B., The Impact of E- Commerce on Final Deliveries: Alternative Parcel Delivery Services in France and Germany, Transportation Research Procedia, 4, pp. 178-190, (2014); Orendorff A., ‘Global Ecommerce Statistics and Trends to Launch Your Business beyond Borders’, (2019); Patil H., Divekar B.R., ‘Inventory Management Challenges for B2C E-commerce Retailers’, Procedia Economics and Finance, 11, pp. 561-571, (2014); Ribas I., Lusa A., Corominas A., ‘A Framework for Designing a Supply Chain Distribution Network’, International Journal of Production Research, 57, 7, pp. 2104-2116, (2019); Savelsbergh M.W.P., Woensel T.V., ‘50th Anniversary Invited article—City Logistics: Challenges and Opportunities’, Transportation Science, 50, 2, pp. 579-590, (2016); Schwerdfeger S., Boysen N., ‘Optimizing the Changing Locations of Mobile Parcel Lockers in Last-mile Distribution’, European Journal of Operational Research, 285, 3, pp. 1077-1094, (2020); Uchoa E., Pecin D., Pessoa A., Poggi M., Vidal T., Subramanian A., ‘New Benchmark Instances for the Capacitated Vehicle Routing Problem’, European Journal of Operational Research, 257, 3, pp. 845-858, (2017); Visser J., Nemoto T., Browne M., ‘Home Delivery and the Impacts on Urban Freight Transport: A Review’, Procedia - Social and Behavioral Sciences, 125, pp. 15-27, (2014); Wang Y., Zhang D., Liu Q., Shen F., Lee L.H., Towards Enhancing the Last-mile Delivery: An Effective Crowd-tasking Model with Scalable Solutions, Transportation Research Part E: Logistics and Transportation Review, 93, pp. 279-293, (2016); Wu H., Shao D., Ng W.S., Locating Self-collection Points for Last-mile Logistics Using Public Transport Data, Advances in Knowledge Discovery and Data Mining, pp. 498-510, (2015); Yu Y., Wang X., Zhong R.Y., Huang G.Q., ‘E-commerce Logistics in Supply Chain Management: Practice Perspective’, Procedia CIRP, 52, pp. 179-185, (2016)","A. Elomri; College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar; email: aelomri@hbku.edu.qa",null,"Taylor and Francis Ltd.",{"$nulls":5},1.6258312E7,null,null,null,"English","Supply Chain Forum","Article","Final",null,"Scopus","2-s2.0-85104851890"]
["Ma P.; Yao N.; Yang X.","Ma, Panpan (57209135043); Yao, Ni (35194829600); Yang, Xuedong (57226285529)","57209135043; 35194829600; 57226285529","Service Quality Evaluation of Terminal Express Delivery Based on an Integrated SERVQUAL-AHP-TOPSIS Approach",2021.0,"Mathematical Problems in Engineering",2021.0,null,8883370.0,null,null,null,15.0,"10.1155/2021/8883370","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85111073455&doi=10.1155%2f2021%2f8883370&partnerID=40&md5=cb69ef514934667834e330382cf9e7ae","College of Computer and Communication Engineering, Zhengzhou University of Light Industry, Zhengzhou, China","Ma P., College of Computer and Communication Engineering, Zhengzhou University of Light Industry, Zhengzhou, China; Yao N., College of Computer and Communication Engineering, Zhengzhou University of Light Industry, Zhengzhou, China; Yang X., College of Computer and Communication Engineering, Zhengzhou University of Light Industry, Zhengzhou, China","With the rapid development of e-commerce and information technology, the express package volume in the Chinese market keeps an explosively increasing tendency. Terminal delivery plays a significant role on the business and reputation promotion of express brand. To identify the service quality of delivery service, an integrated SERVUQAL-AHP-TOPSIS approach is developed to evaluate the quality of service (QoS) of the city express industry. Firstly, the QoS criteria system is established through SERVQUAL-based dimensions. Secondly, the AHP method is employed to derive the relative weights of criteria. Then, the two stages are embedded into the TOPSIS steps to evaluate the service quality of the express alternative. An application case study is conducted following the detailed steps of the proposed integrated decision-making framework, and results demonstrate the effectiveness and validity of the proposed approach on the QoS of terminal delivery evaluation problem.  © 2021 Panpan Ma et al.",null,"Decision making; Hierarchical systems; Quality control; Service industry; Chinese markets; Criteria systems; Delivery service; Evaluation problems; Express industries; Integrated decision makings; Relative weights; Service quality evaluation; Quality of service",{"$nulls":6},"Qin X., Liu Z., Tian L., The strategic analysis of logistics service sharing in an e-commerce platform, Omega-International Journal of Management Science, 92, (2020); Rai A., Pavlou P.A., Im G., Du S., Interfirm IT capability profiles and communications for cocreating relational value: Evidence from the logistics industry, MIS Quarterly, 36, 1, pp. 233-262, (2012); He Y., Zhou F., Qi M., Wang X., Joint distribution: Service paradigm, key technologies and its application in the context of Chinese express industry, International Journal of Logistics Research and Applications, 54, pp. 1-17, (2019); Tillman F.A., The multiple terminal delivery problem with probabilistic demands, Transportation Science, 3, 3, pp. 192-204, (1969); He Y., Qi M., Zhou F., Su J., An effective metaheuristic for the last mile delivery with roaming delivery locations and stochastic travel times, Computers and Industrial Engineering, 145, (2020); Li L., Wang X., Lin Y., Zhou F., Chen S., Cooperative game-based profit allocation for joint distribution alliance under online shopping environment, Asia Pacific Journal of Marketing and Logistics, 31, 2, pp. 302-326, (2019); He Y., Wang X., Zhou F., Lin Y., Dynamic vehicle routing problem considering simultaneous dual services in the last mile delivery, Kybernetes, 10, (2019); Zhou F., He Y., Zhou L., Last mile delivery with stochastic travel times considering dual services, IEEE Access, 7, pp. 159013-159021, (2019); Zhou L., Lin Y., Wang X., Zhou F., Model and algorithm for bilevel multisized terminal location-routing problem for the last mile delivery, International Transactions in Operational Research, 26, 1, pp. 131-156, (2019); 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Grew B., Schneider C.R., Mirzaei A., Carter S.R., Validation of a questionnaire for consumers' perception of service quality in community pharmacy, Research in Social and Administrative Pharmacy, 15, 6, pp. 673-681, (2019); Eboli L., Forciniti C., Mazzulla G., Spatial variation of the perceived transit service quality at rail stations, Transportation Research Part A: Policy and Practice, 114, pp. 67-83, (2018); Yang Y., Huang C., DC fault location in multi-terminal DC distribution network based on voltage similar triangle principle, Electric Power Systems Research, 184, (2020); Zhou F.-L., Wang X., Lin Y., He Y.-D., Wu N., Influence research of multi-dimensional tech-innovation behavior on tech-innovation performance, International Journal of Innovation Science, 8, 2, pp. 148-160, (2016); Buyukozkan G., Cifci G., A novel hybrid MCDM approach based on fuzzy DEMATEL, fuzzy ANP and fuzzy TOPSIS to evaluate green suppliers, Expert Systems with Applications, 39, 3, pp. 3000-3011, (2012); Mangla S.K., Kumar P., Barua M.K., Risk analysis in green supply chain using fuzzy AHP approach: A case study, Resources, Conservation and Recycling, 104, pp. 375-390, (2015); Zhou F., Lin Y., Wang X., Zhou L., He Y., ELV recycling service provider selection using the hybrid MCDM method: A case application in China, Sustainability, 8, 5, (2016); Prajapati D., Zhou F., Zhang M., Chelladurai H., Pratap S., Sustainable logistics network design for multi-products delivery operations in B2B e-commerce platform, Sādhanā, 46, 2, pp. 1-13, (2021); He Y., Wang X., Lin Y., Zhou F., Zhou L., Sustainable decision making for joint distribution center location choice, Transportation Research Part D: Transport and Environment, 55, pp. 202-216, (2017); Opricovic S., Tzeng G.-H., Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS, European Journal of Operational Research, 156, 2, pp. 445-455, (2004); Zhou F., Wang X., Lim M.K., He Y., Li L., Sustainable recycling partner selection using fuzzy DEMATEL-AEW-FVIKOR: A case study in small-and-medium enterprises (SMEs), Journal of Cleaner Production, 196, pp. 489-504, (2018)","P. Ma; College of Computer and Communication Engineering, Zhengzhou University of Light Industry, Zhengzhou, China; email: mapanpan128@163.com",null,"Hindawi Limited",{"$nulls":5},"1024123X",null,null,null,"English","Math. Probl. Eng.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85111073455"]
["Zhang Z.","Zhang, Zhongqiang (57223122769)",5.7223122769E10,"An Optimization Model for Logistics Distribution Network of Cross-Border E-Commerce Based on Personalized Recommendation Algorithm",2021.0,"Security and Communication Networks",2021.0,null,5510481.0,null,null,null,14.0,"10.1155/2021/5510481","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85104912857&doi=10.1155%2f2021%2f5510481&partnerID=40&md5=bad5cd5ac8868d40fec5fa4d6a0ce8c6","School of Management, Xuzhou University of Technology, Xuzhou, 221018, China","Zhang Z., School of Management, Xuzhou University of Technology, Xuzhou, 221018, China","In order to solve the problems of poor timeliness and high service cost caused by international logistics of cross-border e-commerce and to realize the localization of cross-border trade and improve consumers' shopping experience, much cross-border e-commerce has introduced overseas warehouse business. Because the optimization model for the logistics distribution network of cross-border e-commerce cannot solve the problem of high operation cost, the optimization model for the logistics distribution network of cross-border e-commerce based on a personalized recommendation algorithm is designed. Through the analysis of the logistics distribution network of cross-border e-commerce structure and the construction of logistics distribution network of cross-border e-commerce model and multiobjective optimization of logistics distribution network of cross-border e-commerce, the construction process of the logistics distribution network optimization model is completed. The simulation results verify the effectiveness of the model. By comparison, this model can effectively solve the problems that the original model cannot solve and reduce the operation cost of the logistics distribution network. © 2021 Zhongqiang Zhang.",null,"Electronic commerce; International trade; Multiobjective optimization; Operating costs; Construction process; Cross-border trades; E-commerce model; Logistics distribution networks; Operation cost; Optimization modeling; Original model; Personalized recommendation; Costs",{"$nulls":6},"Mou J., Cui Y., Kurcz K., Trust, risk and alternative website quality in B-buyer acceptance of cross-border E-commerce, Journal of Global Information Management, 28, 1, pp. 167-188, (2020); Wingreen S.C., Mazey N.C.H.L., Baglione S.L., Transfer of electronic commerce trust between physical and virtual environments: Experimental effects of structural assurance and situational normality, Electronic Commerce Research, 19, 2, pp. 339-371, (2019); Xueli C., Liang M., Fan B., Ant colony algorithm for vehicle routing problem (VRP), Systems Engineering, 19, 4, pp. 418-422, (2004); Lijun S., Xiangpei H., Zheng W., Research progress on vehicle path planning problems and solving methods, Systems Engineering, 24, pp. 31-36, (2006); Yufeng L., Li J., Dynamic programming heuristic algorithm for solving time-varying vehicle scheduling problems, Systems Engineering Theory and Practice, 32, pp. 1712-1718, (2012); Xiang L., Yanhui L., Cross-regional VRP model for e-commerce distribution and its heuristic algorithm, Journal of Tsinghua University, 46, Z1, pp. 1014-1018, (2006); Ratliff H D., Rosenthal A.S., ―order picking in a rectangular warehouse: A solvable case of the traveling sa leman problem, Operations Research, 2, 31, pp. 507-521, (2002); Dingwei W., Modeling and Optimization in E-Commerce, (2008); Jian Y., Jin L., Houqing L., ‖annealing network solution for VRP in stochastic demand situation‖, Systems Engineering Theory and Practice, 22, 3, pp. 109-114, (2002); Jiali L., Zujun M., There are vehicle rental and sharing and there are time windows and multiple distribution centers open loop VRP, Systems Engineering Theory and Practice, 33, 3, pp. 666-672, (2013); Yuqin L., Peiru W., Research on the Traditional Storage Picking Path of Logistics Center‖, Supplementary City Name, (2005); Chen S., Huang L., Lei Z., Wang S., Research on personalized recommendation hybrid algorithm for interactive experience equipment, Computational Intelligence, 36, 3, pp. 1348-1373, (2020); Yang C., Fan Q., Wang T., RepoLike: Amulti-feature-based personalized recommendation approach for open-source repositories, Frontiers of Information Technology & Electronic Engineering, 20, 2, pp. 222-237, (2019); Zhou W., Han W., Personalized recommendation via user preference matching, Information Processing & Management, 56, 3, pp. 955-968, (2019); Pourya P., Oh K.K., Lim H., Integrating sustainability into the optimization of fuel logistics networks, Korean Society of Civil Engineers, 23, 3, pp. 1369-1383, (2019); Dai Z., Zhou H., Wen F., Efficient predictability of stock return volatility: The role of stock market implied volatility, The North American Journal of Economics and Finance, 52, (2019); Yu J.J., Average case constant factor time and distance optimal multi-robot path planning in well-connected environments, Autonomous Robots, 44, 5, pp. 469-483, (2020); Guitian D. F.R.M., Casas-Mendez B., Routing problems in agricultural cooperatives: A model for optimization of transport vehicle logistics, IMA Journal of Management Mathematics, 30, 4, pp. 387-412, (2019); He Z., Zhou F., Xia X., Wen F., Huang Y., Interaction between oil price and investor sentiment: Nonlinear causality, time- varying influence, and asymmetric effect, Emerging Markets Finance and Trade, 55, 12, pp. 2756-2773, (2019); Priscila P.S.C., Ricardo A.K., Jorge L.M.R., Interactions among stakeholders in the processes of city logistics: A systematic review of the literature, Scientometrics, 20, 2, pp. 567-607, (2019); Abdullah A., Suresh S., Revisiting Norm Optimization for Multi-Objective Black-Box Problems: A Finite-Time Analysis, 73, 3, pp. 659-673, (2019); Izabela D.G., Miguel A.G.G., Guillermo H.G., Mineralization of cyanide originating from gold leaching effluent using electro-oxidation: Multi-objective optimization and kinetic study, Journal of Applied Electrochemistry, 50, 2, pp. 217-230, (2020); Slawomir K., Anna P.D., Rapid multi-objective optimization of antennas using nested kriging surrogates and single-fidelity em simulation models, Engineering Computations, 37, 4, pp. 1491-1512, (2019); Es-Saidi S., Blaize S., Macias D., Meta-model-based multi-objective optimization for robust color reproduction using hybrid diffraction gratings, Optics Express, 28, 3, pp. 3388-3400, (2020); McDonald N., Yuan Q., Naumann R., Urban freight and road safety in the era of e-commerce, Traffic Injury Prevention, 20, 7, pp. 764-770, (2019); Xiang D., Zhang Z., Cross-border E-commerce personalized recommendation based on fuzzy association specifications combined with complex preference model, Mathematical Problems in Engineering, 2020, 4, pp. 1-9, (2020); Liu F., Shi Y., A study on artificial intelligence IQ and standard intelligent model, Computer Science, 180, 20, pp. 118-191, (2015)","Z. Zhang; School of Management, Xuzhou University of Technology, Xuzhou, 221018, China; email: zzq@xzit.edu.cn",null,"Hindawi Limited",{"$nulls":5},1.9390114E7,null,null,null,"English","Secur. Commun. Networks","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85104912857"]
["Luo Y.; Yang Z.; Liang Y.; Zhang X.; Xiao H.","Luo, Yuyan (55743656500); Yang, Zheng (57219722505); Liang, Yuan (57219148580); Zhang, Xiaoxu (57219727475); Xiao, Hong (57226083758)","55743656500; 57219722505; 57219148580; 57219727475; 57226083758","Exploring energy-saving refrigerators through online e-commerce reviews: an augmented mining model based on machine learning methods",2021.0,"Kybernetes",{"$nulls":6},7.0,"10.1108/K-11-2020-0788","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85110316804&doi=10.1108%2fK-11-2020-0788&partnerID=40&md5=4fd13cd453a5563130919a63e8970647","College of Management Science, Chengdu University of Technology, Chengdu, China","Luo Y., College of Management Science, Chengdu University of Technology, Chengdu, China; Yang Z., College of Management Science, Chengdu University of Technology, Chengdu, China; Liang Y., College of Management Science, Chengdu University of Technology, Chengdu, China; Zhang X., College of Management Science, Chengdu University of Technology, Chengdu, China; Xiao H., College of Management Science, Chengdu University of Technology, Chengdu, China","Purpose: Based on climate issues and carbon emissions, this study aims to promote low-carbon consumption and compel consumers to actively shift to energy-saving appliances. In this big data era, online reviews in social and electronic commerce (e-commerce) websites contain valuable product information, which can facilitate firm business strategies and consumer comparison shopping. This study is designed to advance existing research on energy-saving refrigerators by incorporating machine learning models in the analysis of online reviews to provide valuable suggestions to e-commerce platform managers and manufacturers to effectively understand the psychological cognition of consumers. Design/methodology/approach: This study proposes an online e-commerce review mining and management strategy model based on “data acquisition and cleaning, data mining and analysis and strategy formation” through multiple machine learning methods, namely, Bayes networks, support vector machine (SVM), latent Dirichlet allocation (LDA) and importance–performance analysis (IPA), to help managers. Findings: Based on a case study of one of the largest e-commerce platforms in China, this study linguistically analyzes 29,216 online reviews of energy-saving refrigerators. Results indicate that the energy-saving refrigerator features that consumers are generally satisfied with are, in sequential order, logistics, function, price, outlook, after-sales service, brand, quality and space. This study also identifies ten topics with 100 keywords by analyzing 18 different refrigerator models. Finally, based on the IPA, this study allocates different priorities to the features and provides suggestions from the perspective of consumers, the government and manufacturers. Research limitations/implications: In terms of limitations, future research may focus on the following points. First, the topics identified in this study derive from specific points in time and reviews; thus, the topics may change with the text data. A machine learning-based online review analysis platform could be developed in the future to dynamically improve consumer satisfaction. Moreover, given that consumers' needs may change over time, e-commerce platform types and consumer characteristics, such as user profiles, can be incorporated into the model to effectively analyze trends in consumers' perceived dimensions. Originality/value: This study fills the gap in previous research in this field, which uses small-sample data for qualitative analysis, while integrating management ideas and proposes an online e-commerce review mining and management strategy model based on machine learning methods. Moreover, this study considers how consumers' emotional and thematic preferences for products affect their purchase decision-making from the perspective of their psychological perception and linguistically analyzes online reviews of energy-saving refrigerators using the proposed mining model. Through the improved IPA model, this study provides optimizing strategies to help e-commerce platform managers and manufacturers. © 2021, Emerald Publishing Limited.","Energy-saving refrigerator; Low-carbon consumption; Online review; Sentiment analysis; Text mining","Bayesian networks; Behavioral research; Carbon; Data acquisition; Data mining; Decision making; E-learning; Electronic commerce; Electronics industry; Energy conservation; Linguistics; Managers; Manufacture; Refrigerators; Statistics; Support vector machines; Turing machines; After-sales services; Consumer satisfactions; Design/methodology/approach; Latent dirichlet allocations; Low-carbon consumption; Machine learning models; Management strategies; Performance analysis; Learning systems",{"$nulls":4},"China's Post-doctoral Science Fund Project, (2018M631069); Philosophy and Social Science Research Foundation of Chengdu University of Technology, (10800-00009824, YJ2019-NS004); Ministry of Education of the People's Republic of China, MOE, (20YJC630095); Chengdu University of Technology, CDUT, (2019KY37-04203)","This research was funded by the Humanities and Social Sciences Program of the Ministry of Education of the People's Republic of China (Grant No. 20YJC630095), China's Post-doctoral Science Fund Project (Grant No. 2018M631069), the Funding Program for Middle-aged Core Teachers at Chengdu University of Technology (Grant No. 2019KY37-04203), Philosophy and Social Science Research Foundation of Chengdu University of Technology (Grant No. YJ2019-NS004) and the special funding for post-doctoral research projects on Sichuan in 2017 named “Dynamic evolution of multi-system coupling in resource-oriented cities of western China from a technology innovation-driven perspective”, the Program of Graduate Education Reform Program at Chengdu University of Technology (Grant Nos. 10800-00009824).","Abubakar A.M., Ilkan M., Impact of online WOM on destination trust and intention to travel: a medical tourism perspective, Journal of Destination Marketing and Management, 5, pp. 192-201, (2016); 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Luo; College of Management Science, Chengdu University of Technology, Chengdu, China; email: luoyuyan.cdut@qq.com",null,"Emerald Group Holdings Ltd.",{"$nulls":5},"0368492X",null,null,null,"English","Kybernetes","Article","Article in press",null,"Scopus","2-s2.0-85110316804"]
["Zhu A.; Bian B.; Jiang Y.; Hu J.","Zhu, Anqi (57219352839); Bian, Bei (57211803986); Jiang, Yiping (55965631200); Hu, Jiaxiang (55499383200)","57219352839; 57211803986; 55965631200; 55499383200","Integrated tomato picking and distribution scheduling based on maturity",2020.0,"Sustainability (Switzerland)",12.0,19.0,7934.0,null,null,null,5.0,"10.3390/SU12197934","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85092408128&doi=10.3390%2fSU12197934&partnerID=40&md5=dbf58c5cee699098b986e537f2a32a69","School of Information Management, Nanjing Agricultural University, Nanjing, 210031, China; College of Economics and Management, Nanjing Agricultural University, Nanjing, 210095, China; China Center for Food Security Studies, Nanjing Agricultural University, Nanjing, 210095, China","Zhu A., School of Information Management, Nanjing Agricultural University, Nanjing, 210031, China; Bian B., School of Information Management, Nanjing Agricultural University, Nanjing, 210031, China; Jiang Y., School of Information Management, Nanjing Agricultural University, Nanjing, 210031, China; Hu J., College of Economics and Management, Nanjing Agricultural University, Nanjing, 210095, China, China Center for Food Security Studies, Nanjing Agricultural University, Nanjing, 210095, China","Agriproducts have the characteristics of short lifespan and quality decay due to the maturity factor. With the development of e-commerce, high timelines and quality have become a new pursuit for agriproduct online retailing. To satisfy the new demands of customers, reducing the time from receiving orders to distribution and improving agriproduct quality are significantly needed advancements. In this study, we focus on the joint optimization of the fulfillment of online tomato orders that integrates picking and distribution simultaneously within the context of the farm-to-door model. A tomato maturity model with a firmness indicator is proposed firstly. Then, we incorporate the tomato maturity model function into the integrated picking and distribution schedule and formulate a multiple-vehicle routing problem with time windows. Next, to solve the model, an improved genetic algorithm (the sweep-adaptive genetic algorithm, S-AGA) is addressed. Finally, we prove the validity of the proposed model and the superiority of S-AGA with different numerical experiments. The results show that significant improvements are obtained in the overall tomato supply chain efficiency and quality. For instance, tomato quality and customer satisfaction increased by 5% when considering the joint optimization, and the order processing speed increased over 90% compared with traditional GA. This study could provide scientific tomato picking and distribution scheduling to satisfy the multiple requirements of consumers and improve agricultural and logistics sustainability. © 2020 by the authors.","Farm-to-door distribution; Joint optimization; Maturity; Picking; Sweep-adaptive genetic algorithm; Tomato","Lycopersicon esculentum; food processing; food quality; numerical model; optimization; supply chain management; sustainability",{"$nulls":4},"Humanity and Social Science Youth Foundation; National Natural Science Foundation of China, NSFC, (71803084); Ministry of Education of the People's Republic of China, MOE, (17YJC630048); Nanjing Agricultural University, NAU, (1930A77); Fundamental Research Funds for the Central Universities, (SKCX2020009); Priority Academic Program Development of Jiangsu Higher Education Institutions, PAPD","Funding: This research was funded by the National Natural Science Foundation of China, grant number 71803084, Fundamental Research Funds for the Central Universities, grant number NAU: SKCX2020009; the Humanity and Social Science Youth Foundation of the Ministry of Education of China, grant number 17YJC630048; the Students’ Research Training Program of Nanjing Agricultural University, grant number 1930A77; and Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD).","Behzadi G., Osullivan M.J., Olsen T.L., Zhang A., Agribusiness supply chain risk management: A review of quantitative decision models, Omega, 79, pp. 21-42, (2018); Maul F., Sargent S.A., Sims C.A., Baldwin E.A., Huber D.J., Tomato flavor and aroma quality as affected by storage temperature, J. Food Sci., 65, pp. 1228-1237, (2000); Osvald A., Stirn L.Z., A vehicle routing algorithm for the distribution of fresh vegetables and similar perishable food, J. Food Eng., 85, pp. 285-295, (2008); Ahumada O., Villalobos J.R., Application of planning models in the agri-food supply chain: A review, Eur. J. Oper. Res., 196, pp. 1-20, (2009); Ahumada O., Villalobos J.R., Mason A.N., Tactical planning of the production and distribution of fresh agricultural products under uncertainty, Agric. Syst., 112, pp. 17-26, (2012); Amalia U., Torsten R., Amir H.A., Optimisation of agricultural routing planning in field logistics with evolutionary hybrid neighbourhood search, Biosyst. Eng., 184, pp. 166-180, (2019); Javier E.G.-L., Marcela C.G.-A., Wladimir E.S.-S., Masly M.R.-M., Optimizing tactical harvest planning for multiple fruit orchards using a metaheuristic modeling approach, Eur. J. Oper. Res., (2020); Graf P.M., Coupling of crop assignment and vehicle routing for harvest planning in agriculture, Artif. Intell. Agric., 2, pp. 99-109, (2019); Ali O., Verlinden B., Oudheusden D.V., Infield logistics planning for crop-harvesting operations, Eng. Optimiz., 41, pp. 183-197, (2009); Kamal L., Philip C.J., Barrett W.T., Harvest logistics in agricultural systems with multiple, independent producers and no on-farm storage, Comput. Ind. Eng., 91, pp. 129-138, (2016); Liu H., Zhang J., Zhou C., Optimal purchase and inventory retrieval policies for perishable seasonal agricultural products, Omega, 79, pp. 133-145, (2018); Wang X., Wang M., Ruan J., Zhan H., The multi-objective optimization for perishable food distribution route considering temporal-spatial distance, Procedia Comput. Sci., 96, pp. 1211-1220, (2016); Fan J., The vehicle routing problem with simultaneous pickup and delivery based on customer satisfaction, Procedia Eng., 15, pp. 5284-5289, (2011); Li J.Y., Fan L.N., Dong D.Y., A new route optimization approach of cold chain logistics distribution based on fresh agricultural products, In Proceedings of the 30th China Conference on Control and Decision-Making, pp. 1118-1123, (2018); Wan P., Toudeshki A., Tan H., Ehsani R., A methodology for fresh tomato maturity detection using computer vision, Comput. Electron. Agric., 146, pp. 43-50, (2018); Mohammed M., Wilson L.A., Gomes P.I., Postharvest sensory and physiochemical attributes of processing and nonprocessing tomato cultivars, J. Food. Qual., 22, pp. 167-182, (1999); Shanna M., Julia V., Paxton P., Jim G., Use of genomics tools to isolate key ripening genes and analyse fruit maturation in tomato, J. Exp. Bot., 53, pp. 2023-2030, (2002); Zhang L., McCarthy M.J., Measurement and evaluation of tomato maturity using magnetic resonance imaging, Postharvest Biol. Technol., 76, pp. 37-43, (2012); Wan S.L., Gao Y., Nie J.Q., Cai Y.P., The changes of characters to fruit firmness of tomato during fruit ripening, China Veg., 4, pp. 20-23, (2008); Holt C.B., Measurement of tomato firmness with a universal testing machine, J. Texture Stud., 19, pp. 491-501, (1970); Patrick L., Marie F.D., Measurement of tomato firmness by using a non-destructive mechanical sensor, Postharvest Biol. Technol., 8, pp. 45-55, (1996); Zsom M.V., Zsom T., Felfoldi J., In-Vivo measurement of tomato firmness, Acta Hortic., 801, pp. 677-684, (2008); Liu L., Wang H., Xing S.H., Optimization of distribution planning for agricultural products in logistics based on degree of maturity, Comput. Electron. Agric., 160, pp. 1-7, (2019); Cao Q., Shao J.P., Sun Y.A., Multi-objective fresh agricultural product distribution path optimization based on improved genetic algorithm, Ind. Eng. J., 15, pp. 71-76, (2015); Choi K., Lee G., Han Y.J., Bunn J.M., Tomato maturity evaluation using color image analysis, Trans. ASAE, 38, pp. 171-176, (1995); Shiue Y.C., An inventory model for perishable items in a lot-size system with quantity discounts, Eur. J. Oper. Res., 45, pp. 260-264, (1990); Savelsbergh M.W.P., Local search for routing problem with time windows, Ann. Oper. Res., 35, pp. 254-265, (1985); Zheng J., Research on food vehicle routing problem based on improved genetic algorithm, J. Food. Sci. Technol., 8, pp. 219-222, (2015); Wang K., Lan S., Zhao Y., A genetic-algorithm-based approach to the two-echelon capacitated vehicle routing problem with stochastic demands in logistics service, J. Oper. Res. Soc., 68, pp. 1409-1421, (2017); Yang B., Hu Z.H., Wei C., Li S.Q., Zhao L., Jia S., Routing with time-windows for multiple environmental vehicle types, Comput. Ind. Eng., 89, pp. 150-161, (2015); Pierre D.M., Zakaria N., Stochastic partially optimized cyclic shift crossover for multi-objective genetic algorithms for the vehicle routing problem with time-windows, Soft Comput., 52, pp. 863-876, (2016); Holland J.H., Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence, (1992)","Y. Jiang; School of Information Management, Nanjing Agricultural University, Nanjing, 210031, China; email: ypjiang@njau.edu.cn",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85092408128"]
["Simoni M.D.; Kutanoglu E.; Claudel C.G.","Simoni, Michele D. (57195106271); Kutanoglu, Erhan (6602818791); Claudel, Christian G. (23391776600)","57195106271; 6602818791; 23391776600","Optimization and analysis of a robot-assisted last mile delivery system",2020.0,"Transportation Research Part E: Logistics and Transportation Review",142.0,null,102049.0,null,null,null,66.0,"10.1016/j.tre.2020.102049","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85089343255&doi=10.1016%2fj.tre.2020.102049&partnerID=40&md5=29e03c0674bd501610fde1ca12624332","Dept. of Civil, Architectural, and Environmental Engineering, University of Texas at Austin, 301E Dean Keeton, St., Austin, 78712, TX, United States; Operations Research and Industrial Engineering, University of Texas at Austin, 204E Dean Keeton, St., Austin, 78712, TX, United States; Division of Systems Analysis and Economics, KTH Royal Institute of Technology, Stockholm, Sweden","Simoni M.D., Dept. of Civil, Architectural, and Environmental Engineering, University of Texas at Austin, 301E Dean Keeton, St., Austin, 78712, TX, United States, Division of Systems Analysis and Economics, KTH Royal Institute of Technology, Stockholm, Sweden; Kutanoglu E., Operations Research and Industrial Engineering, University of Texas at Austin, 204E Dean Keeton, St., Austin, 78712, TX, United States; Claudel C.G., Dept. of Civil, Architectural, and Environmental Engineering, University of Texas at Austin, 301E Dean Keeton, St., Austin, 78712, TX, United States","The last mile of freight distribution is a critical part of the supply chain because of its significant costs and customers’ increasing expectations from e-commerce and same-day delivery services. Automated technologies in freight transportation represent an opportunity to develop more efficient systems characterized by the integration of different and complementary modes. In this study, we focus on the possibility of implementing an integrated truck-robot system for the last-mile delivery. This typology of problem shares similarities with truck-drone problems, although robots are characterized by much slower speeds and can perform several consecutive deliveries. Based on these particular features, a heuristic that efficiently identifies solutions based on initial truck tours and corresponding joint robot operations is presented. This solution approach leverages a special version of the “Weighted Interval Scheduling Problem,” which allows for a very efficient Dynamic Programming solution. The developed solution approach is adopted to analyze the influence on efficiency of different features concerning the robot's design and operation, and the surrounding environment. The results show that robot-assisted last-mile delivery systems are quite efficient if robots are employed in heavily congested areas and appropriately retrofitted to accommodate several compartments in the robot's storage. © 2020 Elsevier Ltd","City logistics; Integrated truck-robot delivery; Last-mile delivery; Local search with adaptive perturbation; Traveling salesman with robot","Dynamic programming; Freight transportation; Local search (optimization); Machine design; Supply chains; Traveling salesman problem; Trucks; Vehicle routing; City logistics; Delivery systems; Integrated truck-robot delivery; Last mile; Last-mile delivery; Local search; Local search with adaptive perturbation; Robot operations; Traveling salesman with robot; Travelling salesman; cost analysis; electronic commerce; freight transport; logistics; optimization; robotics; supply chain management; trucking; typology; Robots",{"$nulls":4},"National Science Foundation, NSF, (1739964)",null,"Agatz N., Bouman P., Schmidt M., Optimization approaches for the traveling salesman problem with drone, Transport. Sci., 52, 4, pp. 965-981, (2018); Allen J., Piecyk M., Piotrowska M., McLeod F., Cherrett T., Ghali K., Wise S., Understanding the impact of e-commerce on last-mile light goods vehicle activity in urban areas: the case of London, Transport. Res. D: Transp. Environ., 61, pp. 325-338, (2017); Benlic U., Hao J.K., (2013); Bishop C., (2016); Boysen N., Schwerdfeger S., Weidinger F., Scheduling last-mile deliveries with truck-based autonomous robots, Eur. J. Oper. Res., 271, 3, pp. 1085-1099, (2018); Burns J., (2016); Carlsson J.G., Song S., Coordinated logistics with a truck and a drone, Manage. Sci., 64, 9, pp. 4052-4069, (2017); Chao I.M., A tabu search method for the truck and trailer routing problem, Comput. Oper. Res., 29, 1, pp. 33-51, (2002); Coldewey D.; Conway A., Wang X., Chen Q., Schmid J., (2016); Cuda R., Guastaroba G., Speranza M.G., A survey on two-echelon routing problems, Comput. Oper. Res., 55, pp. 185-199, (2015); (2017); Derigs U., Pullmann M., Vogel U., Truck and trailer routing—problems, heuristics and computational experience, Comput. Oper. Res., 40, 2, pp. 536-546, (2013); Desjardins J.; Drexl M., Synchronization in vehicle routing—a survey of VRPs with multiple synchronization constraints, Transport. Sci., 46, 3, pp. 297-316, (2012); Drexl M., Branch-and-cut algorithms for the vehicle routing problem with trailers and transshipments, Networks, 63, 1, pp. 119-133, (2014); Ha Q.M., Deville Y., Pham Q.D., Ha M.H., On the min-cost traveling salesman problem with drone, Transport. Res. Part C: Emerg. Technol., 86, pp. 597-621, (2018); Halzack S., (2016); Hern A., (2014); Jennings D., Figliozzi M., Study of Sidewalk Autonomous Delivery Robots and Their Potential Impacts on Freight Efficiency and Travel, Transp. Res. Rec., (2019); Joerss M., Schroder J., Neuhaus F., Klink C., Mann F., (2016); Kleinberg J., Tardos E., Algorithm design, (2006); Knoblauch R., Pietrucha M., Nitzburg M., Field studies of pedestrian walking speed and start-up time, Transport. Res. Rec.: J. Transport. Res. Board, 1538, pp. 27-38, (1996); Lin S.W., Vincent F.Y., Chou S.Y., Solving the truck and trailer routing problem based on a simulated annealing heuristic, Comput. Oper. Res., 36, 5, pp. 1683-1692, (2009); Murray C.C., Chu A.G., The flying sidekick traveling salesman problem: optimization of drone-assisted parcel delivery, Transport. Res. C: Emerg. Technol., 54, pp. 86-109, (2015); Nicas J., (2018); Otto A., Agatz N., Campbell J., Golden B., Pesch E., Optimization approaches for civil applications of unmanned aerial vehicles (UAVs) or aerial drones: a survey, Networks, 72, 4, pp. 411-458, (2018); Poeting M., Schaudt S., Clausen U., pp. 1-19, (2019); Reed T., Kidd J., (2019); Rodrigue J.P., Comtois C., Slack B., The “Last Mile” in Freight Distribution, The Geography of Transport Systems, (2009); Savelsbergh M., Van Woensel T., 50th anniversary invited article – city logistics: challenges and opportunities, Transportation Science, 50, 2, pp. 579-590, (2016); Scheuerer S., A tabu search heuristic for the truck and trailer routing problem, Comput. Oper. Res., 33, 4, pp. 894-909, (2006); Sonneberg M.O., Leyerer M., Kleinschmidt A., Knigge F., Breitner M.H., (2019); Scott S., (2019); (2019); Villegas J.G., Prins C., Prodhon C., Medaglia A.L., Velasco N., A GRASP with evolutionary path relinking for the truck and trailer routing problem, Comput. Oper. Res., 38, 9, pp. 1319-1334, (2011); Villegas J.G., Prins C., Prodhon C., Medaglia A.L., Velasco N., A matheuristic for the truck and trailer routing problem, Eur. J. Oper. Res., 230, 2, pp. 231-244, (2013); Wang X., Poikonen S., Golden B., The vehicle routing problem with drones: several worst-case results, Optimiz. Lett., 11, 4, pp. 679-697, (2017)","M.D. Simoni; Dept. of Civil, Architectural, and Environmental Engineering, University of Texas at Austin, Austin, 301E Dean Keeton, St., 78712, United States; email: micheles@kth.se",null,"Elsevier Ltd",{"$nulls":5},1.3665545E7,null,null,null,"English","Transp. Res. Part E Logist. Transp. Rev.","Article","Final",null,"Scopus","2-s2.0-85089343255"]
["Wang C.","Wang, Cuimin (57223026350)",5.722302635E10,"Analyzing the Effects of Cross-Border E-Commerce Industry Transfer Using Big Data",2021.0,"Mobile Information Systems",2021.0,null,9916304.0,null,null,null,12.0,"10.1155/2021/9916304","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85108955780&doi=10.1155%2f2021%2f9916304&partnerID=40&md5=b6c19733e3d6b733c65be1f590dbcce0","School of Economics and Management, Hebei Chemical and Pharmaceutical College, Shijiazhuang, 050026, China","Wang C., School of Economics and Management, Hebei Chemical and Pharmaceutical College, Shijiazhuang, 050026, China","With the increasing diversification and personalization of consumer demand in the international market, coupled with the rapid development of the internet, the many advantages of cross-border e-commerce as an emerging trading model have become more apparent. When the hybrid system synergy model is based on the effective combination of the systems, the overall performance is greater than the sum of various elements' simple superposition. As the upstream chain of modern logistics, cross-border e-commerce requires its virtual characteristics to develop in the direction of informationization, automation, and intelligence. Only when they are interdependent and mutually promoted can they achieve greater synergy. The regional difference measurement theory is often used to measure the effect of cross-border e-commerce industry transfer. First, build a cross-border e-commerce industry transfer effect measurement model to analyze the development level of China's cross-border e-commerce, for example, the measurement model of commercial industry transfer effects from 2001 to 2016. It is mainly because the development of modern logistics lags behind cross-border e-commerce, resulting in the inability of cross-border e-commerce and modern logistics to form an orderly coupling in the system structure and function. Therefore, to better promote the coordinated development of cross-border e-commerce and modern logistics, it is necessary to stimulate the functions of various subsystems and promote the synergy and deep integration of multiparty entities such as government, enterprises, and industry associations.  © 2021 Cuimin Wang.",null,"Big data; Hybrid systems; International trade; Measurement theory; Effect measurements; Industry association; Industry transfers; Informationization; International markets; Measurement model; Regional differences; System structures; Electronic commerce",{"$nulls":6},"Falk M., Hagsten E., E-commerce trends and impacts across Europe, International Journal of Production Economics, 170, pp. 357-369, (2015); Mathews S., Bianchi C., Perks K.J., Healy M., Wickramasekera R., Internet marketing capabilities and international market growth, International Business Review, 25, 4, pp. 820-830, (2016); Schu M., Morschett D., Swoboda B., Internationalization speed of online retailers: a resource-based perspective on the influence factors, Management International Review, 56, 5, pp. 733-757, (2016); Wang Y., Wang Y., Lee S., The effect of cross-border E-commerce on China's international trade: an empirical study based on transaction cost analysis, Sustainability, 9, 11, (2017); Watson G.F., Weaven S., Perkins H., Sardana D., Palmatier R.W., International market entry strategies: relational, digital, and hybrid approaches, Journal of International Marketing, 26, 1, pp. 30-60, (2018); Theophilou G., Morais C.L., Halliwell D.E., Synchrotron-and focal plane array-based Fourier-transform infrared spectroscopy differentiates the basalis and functionalis epithelial endometrial regions and identifies putative stem cell regions of human endometrial glands, Analytical and Bioanalytical Chemistry, 410, pp. 1-14, (2018); Huo D., Ouyang R., Hung K., Sun B., Effect of cross-border E-business policy on the export trade of an emerging market: a dynamic study of institutional support to cross-border E-business at Chinese pilot cities, Emerging Markets Finance and Trade, 54, pp. 1-15, (2018); Leonidou L.C., Katsikeas C.S., Samiee S., Aykol B., International marketing research: a state-of-the-art review and the way forward, Advances in Global Marketing, pp. 3-33, (2018); 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Yang H., Yu J., Zo H., Choi M., User acceptance of wearable devices: an extended perspective of perceived value, Telematics and Informatics, 33, 2, pp. 256-269, (2016); Yang H., Lee H., Zo H., User acceptance of smart home services: an extension of the theory of planned behavior, Industrial Management & Data Systems, 117, 1, pp. 68-89, (2017); Yu J., Lee H., Ha I., Zo H., User acceptance of media tablets: an empirical examination of perceived value, Telematics and Informatics, 34, 4, pp. 206-223, (2017); Liang H., Zou J., Zuo K., Khan M.J., An improved genetic algorithm optimization fuzzy controller applied to the wellhead back pressure control system, Mechanical Systems and Signal Processing, 142, (2020); Zheng H., Guo W., Xiong N., A kernel-based compressive sensing approach for mobile data gathering in wireless sensor network systems, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 48, 12, pp. 2315-2327, (2017); Liang H., Zou J., Li Z., Khan M.J., Lu Y., Dynamic evaluation of drilling leakage risk based on fuzzy theory and PSO-SVR algorithm, Future Generation Computer Systems, 95, pp. 454-466, (2019); Zhang Y., Zhu R., Chen Z., Gao J., Xia D., Evaluating and selecting features via information theoretic lower bounds of feature inner correlations for high-dimensional data, European Journal of Operational Research, 290, 1, (2020); Liang H., Xian A., Mao M., Ni P., Wu H., A research on remote fracturing monitoring and decision-making method supporting smart city, Sustainable Cities and Society, 62, (2020); Zhou Y., Zhang D., Xiong N., Post-cloud computing paradigms: a survey and comparison, Tsinghua Science and Technology, 22, 6, pp. 714-732, (2017); Al-Momani A.M., Mahmoud M.A., Ahmad M.S., Factors that influence the acceptance of Internet of things services by customers of telecommunication companies in Jordan, Journal of Organizational and End User Computing, 30, 4, pp. 51-63, (2018); Reddy M.R., Srinivasa K.G., Reddy B.E., Smart vehicular system based on the Internet of things, Journal of Organizational and End User Computing, 30, 3, pp. 45-62, (2018); Singh P., Agrawal R., A customer centric best connected channel model for heterogeneous and IoT networks, Journal of Organizational and End User Computing, 30, 4, pp. 32-50, (2018); Chen C.-H., Song F., Hwang F.-J., Wu L., A probability density function generator based on neural networks, Physica A: Statistical Mechanics and Its Applications, 541, (2020); Chu W., MOOCS curriculum model: contribution and dilemma, Foreign Language Audio-Visual Teaching, 3, 4, pp. 39-40, (2014)","C. Wang; School of Economics and Management, Hebei Chemical and Pharmaceutical College, Shijiazhuang, 050026, China; email: wcm001@stu.ahu.edu.cn",null,"Hindawi Limited",{"$nulls":5},"1574017X",null,null,null,"English","Mob. Inf. Sys.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85108955780"]
["Hamed S.; El-Deeb S.","Hamed, Sara (55748487100); El-Deeb, Sara (57216130170)","55748487100; 57216130170","Cash on Delivery as a Determinant of E-Commerce Growth in Emerging Markets",2020.0,"Journal of Global Marketing",33.0,4.0,null,242.0,265.0,23.0,15.0,"10.1080/08911762.2020.1738002","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85082623998&doi=10.1080%2f08911762.2020.1738002&partnerID=40&md5=9dee2319415d4c2fad75fcca48dd21ed","Marketing Department, Faculty of Management Technology, The German University in Cairo (GUC), Cairo, Egypt","Hamed S., Marketing Department, Faculty of Management Technology, The German University in Cairo (GUC), Cairo, Egypt; El-Deeb S., Marketing Department, Faculty of Management Technology, The German University in Cairo (GUC), Cairo, Egypt","Buyers have values and risks affecting their online purchase behavior. This study captures cash on delivery, an online payment method found in emerging markets, as a moderator between utilitarian and hedonic value, perceived risks, and online purchase intention. A survey on a sample of 365 respondents from Egypt is utilized. Results show that cash on delivery increases hedonic value, yet does not affect utilitarian value or risks. Understanding consumers in different regions helps practitioners develop correct strategies for survival in global markets. Marketing researchers would benefit by developing models that are more comprehensive of consumer behavior in diverse regions. © 2020 Taylor & Francis Group, LLC.","Cash on delivery; hedonic value; perceived risks; perceived value; utilitarian value",{"$nulls":7},"Bezes C., Definition and psychometric validation of ameasurement index common to website and store images, Journal of Business Research, 67, 12, pp. 2559-2578, (2014); Bezes C., Comparing online and in-store risks in multichannel shopping, International Journal of Retail & Distribution Management, 44, 3, pp. 284-300, (2016); Chiejina C., Olamide S.E., Investigating the significance of the ‘pay on delivery’ option in the emerging prosperity of the Nigerian e-commerce sector, Journal of Marketing and Management, 5, 1, pp. 120-135, (2014); Chiu C., Wang E.T.G., Fang Y., Huang H., Understanding customers’ repeat purchase intentions in B2C e-commerce: The roles of utilitarian value, hedonic value and perceived risk, Information Systems Journal, 24, 1, pp. 85-114, (2014); Choi J., Lee K., Risk perception and e‐shopping: a cross‐cultural study, Journal of Fashion Marketing and Management: An International Journal, 7, 1, pp. 49-64, (2003); Coker B.L.S., Ashill N.J., Hope B., Measuring Internet product purchase risk, European Journal of Marketing, 45, 7-8, pp. 1130-1151, (2011); Cretu A., Brodie R., Chapter 7 Brand image, corporate reputation, and customer value, Business-To-Business Brand Management: Theory, Research and Executive Case Study Exercises (Advances in Business Marketing and Purchasing, Vol. 15), pp. 263-387, (2009); Forsythe S., Liu C., Shannon D., Gardner L.C., Development of a scale to measure the perceived benefits and risks of online shopping, Journal of Interactive Marketing, 20, 2, pp. 55-75, (2006); Frasquet M., Miquel M., Do channel integration efforts pay-off in terms of online and offline customer loyalty?, International Journal of Retail & Distribution Management, 45, 7-8, pp. 859-873, (2017); Gawor T., Hoberg K., Customers’ valuation of time and convenience in e-fulfillment, International Journal of Physical Distribution & Logistics Management, 49, 1, pp. 75-98, (2019); 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Hsieh T., Yang K., Yang C., Yang C., Urban and rural differences: Multilevel latent class analysis of online activities and e-payment behavior patterns, Internet Research, 23, 2, pp. 204-228, (2013); Hussain Z., Wallace J., Tassabehji R., Khan O., E-business in the developing world: An empirical study of payment methods and their implications, International Journal of Electronic Business, 5, 3, pp. 315-335, (2007); Javadi M.H.M., Dolatabadi H.R., Nourbakhsh M., Poursaeedi A., Asadollahi A.R., An analysis of factors affecting on online shopping behavior of consumers, International Journal of Marketing Studies, 4, 5, pp. 81-98, (2012); Jones C., Kim S., Influences of retail brand trust, off-line patronage, clothing involvement and website quality on online apparel shopping intention, International Journal of Consumer Studies, 34, 6, pp. 627-637, (2010); Kahneman D., Tversky A., Prospect theory: An analysis of decision under risk, Econometrica, 47, 2, pp. 263-292, (1979); Kamel S., Hussein M., The development of e-commerce: The emerging virtual context within Egypt, Logistics Information Management, 14, 1-2, pp. 119-126, (2001); 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An empirical study of two trust-building strategies, Journal of Management Information Systems, 23, 2, pp. 233-266, (2006); Liu M.T., Brock J.L., Shi G.C., Chu R., Tseng T., Perceived benefits, perceived risk, and trust: Influences on consumers’ group buying behavior, Asia Pacific Journal of Marketing and Logistics, 25, 2, pp. 225-248, (2013); Malhotra N.K., Marketing research–An applied orientation, (2010); Martin S.S., Camarero C., How perceived risk affects online buying, Online Information Review, 33, 4, pp. 629-654, (2009); Martin S.S., Camarero C., Jose R.S., Dual effect of perceived risk on cross-national e-commerce, Internet Research, 21, 1, pp. 46-66, (2011); Masoud E.Y., The effect of perceived risk on online shopping in Jordan, European Journal of Business and Management, 5, 6, pp. 76-87, (2013); Mathwick C., Malhotra N., Rigdon E., Experiential value: Conceptualization, measurement and application in the catalog and Internet shopping environment, Journal of Retailing, 77, 1, pp. 39-56, (2001); (2017); (2017); Omar M., Bathgate I., Nwankwo S., Internet marketing and customer satisfaction in emerging markets: The case of Chinese online shoppers, Competitiveness Review, 21, 2, pp. 224-237, (2011); Pallant J., SPSS survival manual: A step by step guide to data analysis using SPSS for Windows, (2005); Rahman S., Khan M.A., Iqbal N., Motivations and barriers to purchasing online: Understanding consumer responses, South Asian Journal of Business Studies, 7, 1, pp. 111-128, (2018); Raman P., Understanding female consumers’ intention to shop online: The role of trust, convenience and customer service, Asia Pacific Journal of Marketing and Logistics, 31, 4, pp. 1138-1160, (2019); Rathee R., Rajain P., Online shopping environments and consumer’s need for touch, Journal of Advances in Management Research, 16, 5, pp. 814-826, (2019); Sahney S., Ghosh K., Shrivastava A., Buyer’s motivation for online buying: An empirical case of railway eticketing in Indian context, Journal of Asia Business Studies, 8, 1, pp. 43-64, (2013); San-Martin S., Gonzalez-Benito O., Martos-Partal M., To what extent does need for touch affect online perceived quality?, International Journal of Retail & Distribution Management, 45, 9, pp. 950-968, (2017); Tandon U., Kiran R., Sah A.N., The influence of website functionality, drivers and perceived risk on customer satisfaction in online shopping: An emerging economy case, Information Systems and e-Business Management, 16, 1, pp. 57-91, (2018); Tauber E.M., Why do people shop?, Journal of Marketing, 36, 4, pp. 46-49, (1972); Taylor E., Mobile payment technologies in retail: A review of potential benefits and risks, International Journal of Retail & Distribution Management, 44, 2, pp. 159-177, (2016); Teoh W.M., Chong S.C., Lin B., Chua J.W., Factors affecting consumers’ perception of electronic payment: An empirical analysis, Internet Research, 23, 4, pp. 465-485, (2013); Thakur R., Srivastava M., A study on the impact of consumer risk perception and innovativeness on online shopping in India, International Journal of Retail & Distribution Management, 43, 2, pp. 148-166, (2015); Turban E., King D., Lee J.K., Liang T., Turban D.C., Electronic commerce: A managerial and social networks perspective, (2015); Wu W., Huang V., Chen X., Davison R.M., Hua Z., Social value and online social shopping intention: the moderating role of experience, Information Technology & People, 31, 3, pp. 688-711, (2018); Zhang M., Zhu M., Liu X., Yang J., Why should I pay for e-books?: An empirical study to investigate Chinese readers’ purchase behavioural intention in the mobile era, The Electronic Library, 35, 3, pp. 472-493, (2017)","S. Hamed; Marketing Department, Faculty of Management Technology, The German University in Cairo (GUC), Cairo, The 5th District, 11432, Egypt; email: sara.m.m.hamed@gmail.com",null,"Routledge",{"$nulls":5},8911762.0,null,null,null,"English","J. Global Mark.","Article","Final",null,"Scopus","2-s2.0-85082623998"]
["Lv Y.; Xiang S.; Zhu T.; Zhang S.","Lv, Yaqiong (36185734400); Xiang, Shangjia (57218853946); Zhu, Tianyi (57218853159); Zhang, Shuzhu (56244760100)","36185734400; 57218853946; 57218853159; 56244760100","Data-driven design and optimization for smart logistics parks: Towards the sustainable development of the steel industry",2020.0,"Sustainability (Switzerland)",12.0,17.0,7034.0,null,null,null,16.0,"10.3390/su12177034","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85090442198&doi=10.3390%2fsu12177034&partnerID=40&md5=ac58bed594ccaf2a0f51fb73a171334a","School of Logistics Engineering, Wuhan University of Technology, Wuhan, Hubei, 430070, China; Department of Information Management and Artificial Intelligence, Zhejiang University of Finance and Economics, Hangzhou, Zhejiang, 310018, China","Lv Y., School of Logistics Engineering, Wuhan University of Technology, Wuhan, Hubei, 430070, China; Xiang S., School of Logistics Engineering, Wuhan University of Technology, Wuhan, Hubei, 430070, China; Zhu T., School of Logistics Engineering, Wuhan University of Technology, Wuhan, Hubei, 430070, China; Zhang S., Department of Information Management and Artificial Intelligence, Zhejiang University of Finance and Economics, Hangzhou, Zhejiang, 310018, China","The design of steel logistics parks acts as fundamental infrastructure supporting the operations of storage, allocation, and distribution of steel products in the steel logistics industry, which actually lags behind the development of other logistics industries, such as e-commerce logistics, due to its large lot bulk storage, low turnover rate, and costly transportation and operations. This research proposes a data-driven approach for a specific steel logistics park, aiming to improve its operational efficiency in terms of product layout and allocation in multiple yards. The entry and delivery order data are analyzed comprehensively so as to determine the products with high operational frequency and the corresponding relevancy among them. Experimental results show that, among the 69 steel specifications, 14 high-frequency products are identified, and the correlation among the 14 identified high-frequency products possesses evident distribution characteristics concerning their brands and specifications. The identified frequency and correlation among various products can not only facilitate the product layout and allocation in steel logistics parks, but also advance the vehicle scheduling efficiency for product pick-up and delivery. Moreover, the research methodology and framework can provide managerial insights for other industries with mass data processing requirements. © 2020 by the authors.","Data-driven design; FP-growth; Layout planning; Smart logistics","design method; electronic commerce; iron and steel industry; optimization; sustainable development",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (71902171); Natural Science Foundation of Zhejiang Province, ZJNSF, (LY19G010003); Humanities and Social Science Fund of Ministry of Education of China, (19YJC630216, 20YJC630096)","Funding: This work was supported in part by the National Natural Science Foundation of China, grant number 71902171; in part by the Humanities and Social Science Foundation of Ministry of Education of China, grant number 19YJC630216 and 20YJC630096; in part by the Natural Science Foundation of Zhejiang Province, China, grant number LY19G010003.","Pinto J.T., Morales M.E., Fedoruk M., Kovaleva M., Diemer A., Sensitization in support of sustainable cities: What are steel's contributions and challenges?, Sustainability, 11, (2019); Branca T.A., Fornai B., Colla V., Murri M.M., Streppa E., Schroder A., The challenge of digitalization in the steel sector, Metals, 10, (2020); Tang J., Tang L., Wang X., Solution method for the location planning problem of logistics park with variable capacity, Comput. 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Appl, 42, pp. 7768-7780, (2015); Palominos P., Pertuze D., Quezada L., Sanchez L., An extension of the systematic layout planning system using QDF: Its application to service oriented physical distribution, EM]-Eng. Manag. J, 31, pp. 284-302, (2019); He Q., Xue X., A Research on Layout Planning of Regional Logistics Park Based on Fuzzy Clustering, pp. 907-909, (2009); Hsieh L.F., Huang Y.C., New batch construction heuristics to optimise the performance of order picking systems, Int. J. Prod. Econ, 131, pp. 618-630, (2011); Kulak O., Sahin Y., Taner M.E., Joint order batching and picker routing in single and multiple-cross-aisle warehouses using cluster-based tabu search algorithms, Flex. Serv. Manuf. J, 24, pp. 52-80, (2011); Chiang D.M.H., Lin C.P., Chen M.C., Data mining based storage assignment heuristics for travel distance reduction, Expert Syst, 31, pp. 81-90, (2012); Pang K.W., Chan H.L., Data mining-based algorithm for storage location assignment in a randomised warehouse, Int. J. Prod. Res, 55, pp. 1-18, (2016); Han J., Pei J., Yin Y., In Mining frequent patterns without candidate generation, pp. 1-12, (2000); Han J.-W., Pei J., Yin Y., Mao R., Mining frequent patterns without candidate generation: A frequent-pattern tree approach, Data Min. Knowl. Discov, 8, pp. 53-87, (2004); Agrawal R., Imielinski T., Swami A., Mining association rules between sets of items in large databases, pp. 207-216, (1993); Kuo R., Pai C., Lin R., Chu H., The integration of association rule mining and artificial immune network for supplier selection and order quantity allocation, Appl. Math. Comput, 250, pp. 958-972, (2015); Feng W., Zhu Q., Zhuang J., Yu S., An expert recommendation algorithm based on Pearson correlation coefficient and FP-growth, Clust. Comput, 22, pp. 7401-7412, (2018); Wu Y., Zhang J., Building the electronic evidence analysis model based on association rule mining and FP-growth algorithm, Soft Comput, 24, pp. 7925-7936, (2019)","S. Zhang; Department of Information Management and Artificial Intelligence, Zhejiang University of Finance and Economics, Hangzhou, Zhejiang, 310018, China; email: shuzhu.zhang@connect.polyu.hk",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85090442198"]
["Chen J.; Wu H.; Zhou X.; Wu M.; Zhao C.; Xu S.","Chen, Jun (57221655126); Wu, Huan (57223025117); Zhou, Xi (57223027477); Wu, Maoguo (56920995500); Zhao, Chenyang (57217134463); Xu, Shiyan (57217128533)","57221655126; 57223025117; 57223027477; 56920995500; 57217134463; 57217128533","Optimization of internet of things e-commerce logistics cloud service platform based on mobile communication",2021.0,"Complexity",2021.0,null,5542914.0,null,null,null,5.0,"10.1155/2021/5542914","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85104542478&doi=10.1155%2f2021%2f5542914&partnerID=40&md5=69f71a0e3c152054f325d2bd12d046d1","Silc Business School, Shanghai University, Shanghai, 201800, China","Chen J., Silc Business School, Shanghai University, Shanghai, 201800, China; Wu H., Silc Business School, Shanghai University, Shanghai, 201800, China; Zhou X., Silc Business School, Shanghai University, Shanghai, 201800, China; Wu M., Silc Business School, Shanghai University, Shanghai, 201800, China; Zhao C., Silc Business School, Shanghai University, Shanghai, 201800, China; Xu S., Silc Business School, Shanghai University, Shanghai, 201800, China","E-commerce conceivable future trade, consumption, and service is a new digital employer mode. Therefore, in order to decorate the customary natural environment of operation, it is quintessential to get rid of the preferred desktop in the true field, create a social logistics and transportation administration computing device with commodity agents and distributors as the key features, and mix freight logistics, business enterprise approach waft and data waft advertising and marketing, and advertising and marketing organically. The notion of e-commerce logistics looks alongside the enchantment vogue of neighborhood technological knowledge and social demand. It is an integral part of ending e-commerce authentic economic value. All kinds of cell networks clear up the problem of data flow communication; in the technological know-how of telephone network, digital cost solves the bother of capital flow; at present, logistics is however a long-standing problem of e-commerce. Logistics has grown to be the last and entirely bottleneck of e-commerce. If logistics cannot adapt to the enchantment of e-commerce, it may also additionally lead to the slow enchantment of e-commerce. The purpose of this paper is to supply an Internet of things (IoT) e-commerce logistics cloud provider platform based totally absolutely on cell communication, which can be combined with e-commerce and beautify the transport tempo of e-commerce. 'is paper moreover optimizes the e-commerce logistics system, so that it can combine with e-commerce to increase out the distribution of goods, the distribution tempo of e-commerce is doubled, and e-commerce can in a similar fashion develop rapidly. © 2021 Jun Chen et al.",null,"Distribution of goods; Freight transportation; Internet of things; Marketing; Technology transfer; Business enterprise; Cell communication; Internet of Things (IOT); Logistics and transportations; Mobile communications; Natural environments; Technological knowledge; Telephone networks; Mobile commerce",{"$nulls":6},"Chen L.L., Huang J., Design and implementation of public bicycle rental system service platform based on IOCP and JSON, Advanced Materials Research, 998-999, 8, pp. 1100-1103, (2014); Ma L., Jin C., Huo Y., Selection of logistics service modes in e-commerce based on multi-oligopolies Cournot competition, International Journal of Shipping and Transport Logistics, 11, 4, pp. 354-383, (2019); Ying Z., Simulation of public art communication in colleges based on smart cloud platform and artificial intelligence algorithm, Journal of Intelligent and Fuzzy Systems, 12, 3, pp. 1-11, (2020); Ping P., Petrenko Y.N., Mobile robot navigation path algorithm in 3d industrial internet of thing (iot) environment based on 5 g mobile communication, System Analysis and Applied Information Science, 9, 1, pp. 16-24, (2019); Pop F., Dobre C., Mocanu B.C., Citoteanu O.M., Xhafa F., Trust models for efficient communication in mobile cloud computing and their applications to e-commerce, Enterprise Information Systems, 10, 7, pp. 982-1000, (2015); Paolo F., Alessandra F., Stefano R., Sisinni E., Maffei D., Malara M., Impact of quality of service on cloud based industrial iot applications with OPCUA, Electronics, 7, 7, pp. 109-112, (2018); Wei W., Fan X., Song H., Fan X., Yang J., Imperfect information dynamic stackelberg game based resource allocation using hidden Markov for cloud computing, Ieee Transactions on Services Computing, 11, 1, pp. 78-89, (2016); Li W., Santos I., Delicato F.C., Et al., System modelling and performance evaluation of a three-tier cloud of things, Future Generation Computer Systems, 70, pp. 104-125, (2017); Filev R., Lurbe C.B., Baniya A.A., Hornbuckle H., IRRISENS: An IoT Platform based on microservices applied in commercial-scale crops working in a multi-cloud environment, Sensors, 20, 24, pp. 63-71, (2020); Chen J.X., Based on the digital library mobile service platform construction and mobile reading, Journal of Library & Information Sciences in Agriculture, 26, 10, pp. 29-32, (2014); Samsudin A., Cui H., Optimization of digitalized document verification using e-governance service delivery platform, International Journal of Computational Intelligence Research, 14, 8, pp. 619-639, (2018); Cellary W., Strykowski S., E-government based on cloud computing and service-oriented architecture, Proceedings of the 3rd International Conference on 1eory and Practice of Electronic Governance, (2009); Chen F., The automatic positioning method for defect data of 5g mobile communication based on cloud computing, International Journal of Autonomous and Adaptive Communications Systems, 14, 4, pp. 12-16, (2021); Jung S.Y., Yu S.M., Kim S.-L., Optimization of spectrum allocation and subsidization in mobile communication services, Ieee Transactions on Vehicular Technology, 65, 10, pp. 8432-8443, (2016); Kang H.-W., Koh S.-J., Lim S.-K., Kang T.-G., TAC reconfiguration for paging optimization in LTE-based mobile communication systems, Computer Science and Its Applications, 33, 10, pp. 677-682, (2015); Lee S., Han J., Kwon J., Kim J., Design and validation of service composition based on microservices architecture for cloud-native IoT-cloud services, Kiise Transactions on Computing Practices, 26, 3, pp. 123-134, (2020); Ramasamy R.K., Chua F.F., Haw S.C., Adaptive and dynamic service composition for cloud-based mobile application, Lecture Notes in Electrical Engineering, 31, 5, pp. 963-973, (2016); Aulkemeier F., Paramartha M.A., Iacob M.-E., Van Hillegersberg J., A pluggable service platform architecture for e-commerce, Information Systems and E-Business Management, 14, 3, pp. 469-489, (2016); Liu P., He W., Research on the E-commerce operation performance of SMEs based on cloud computing service platform, Revista de la Facultad de Ingenieria, 32, 3, pp. 500-509, (2017); Zhe Z., Xu J.H., Design and implementation logistics cloud platform based on SOA, Applied Mechanics and Materials, 610, 1, pp. 775-780, (2014); Li C., Shen J., Liu Y., Study on architecture and implementation of port logistics information service platform based on cloud computing, New Journal of Chemistry, 27, 3, pp. 1078-1083, (2015); Shen Y.Y., Qian Y., A study of new E-commerce logistics mode based on cloud computing technology, Advanced Materials Research, 1049-1050, 4, pp. 1848-1852, (2014); Li J., Feng G., Wei W., Et al., PSOTrack: A RFID-based system for random moving objects tracking in unconstrained indoor environment, Ieee Internet of 1ings Journal, 5, 6, pp. 4632-4641, (2018); Ando B., Baglio S., Marletta V., Crispino R., Pistorio A., A measurement strategy to assess the optimal design of an RFID-based navigation aid, Ieee Transactions on Instrumentation and Measurement, 68, 7, pp. 2356-2362, (2018)","H. Wu; Silc Business School, Shanghai University, Shanghai, 201800, China; email: wuhuan@shu.edu.cn",null,"Hindawi Limited",{"$nulls":5},1.0762787E7,null,null,null,"English","Complexity","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85104542478"]
["Nahry N.; Ayu T.","Nahry, Nahry (7409936161); Ayu, Talitha (57222430896)","7409936161; 57222430896","Green last mile distribution system: Heterogeneous fleet vehicle routing problem with time window and external cost",2021.0,"Journal of Applied Engineering Science",19.0,1.0,null,154.0,161.0,7.0,0.0,"10.5937/jaes0-27922","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85102704965&doi=10.5937%2fjaes0-27922&partnerID=40&md5=2a8dd77755e82429af8d4c3ece5962a4","Universitas Indonesia, Faculty of Engineering, Department of Civil Engineering, Depok, Indonesia","Nahry N., Universitas Indonesia, Faculty of Engineering, Department of Civil Engineering, Depok, Indonesia; Ayu T., Universitas Indonesia, Faculty of Engineering, Department of Civil Engineering, Depok, Indonesia","The development of e-commerce business in Jakarta, Indonesia, in recent years has made the Last Mile Delivery (LMD) business sector develop rapidly. Increased demand for LMD makes the resulting kilometer trips even greater, resulting in negative externalities. On the other hand, logistics costs in Indonesia are only affected by vehicle operating costs and no external cost component. Optimization of LMD services that take into account internal and external costs is needed to minimize the total cost of LMD and in reducing the impact of negative externalities. The purpose of this paper is to optimize the LMD distribution system on the Heterogeneous Fleet Vehicle Routing Problem with Time Window and External Costs (HFVRPTW-EC) models. The optimization is done by applying the HFVRPTW-EC model using data from one of the parcel deliveries companies in Jakarta and then doing a simulation by forming several operational scenarios. The results show that the optimization of LMD has reduced internal and external costs by more than 50% compared to existing conditions. The detailed results show that, for the short-term program, a scenario with a one-tier distribution system and type of motorcycle vehicle can reduce total costs compared to existing conditions by 66.22% on a peak day and 59.41% on off-peak day. Whereas for long-term program optimization, scenarios with multiple tier distribution systems and types of motorized vehicles for drop mileage and pick up truck for stem mileage can reduce total costs by 69.23% on a peak day and 60.24% on off-peak day. © 2021 Institut za Istrazivanja. All rights reserved.","External cost; Last mile delivery; Logistic distribution system; Vehicle routing problem",{"$nulls":7},"Report On Indonesia ECommerce, Metamorphosis in a Post Covid World, (2020); Ozan Sahiner, E-Commerce Impact On Logistics, More Than Shipping; Lindner J., Last Mile Logistics Capability: A Multidimensional System Requirements Analysis for a General Modelling and Evaluation Approach, (2011); Taniguchi E., Kakimoto Y., Modelling effects of e-commerce on urban freight transport, Logist. Syst. suistanable cities, 1, pp. 35-46, (2004); Brons M., Christidis P., External Cost Calculator for Marco Polo Freight Transport Project Proposals, (2012); Demir E, Huang Y, Scholts S, Van Woensel T., A selected review on the negative externalities of the freight transportation: Modeling and pricing, Transp Res Part E Logist Transp, 77, pp. 95-114, (2015); Cardenas I, Beckers J, Vanelslander T., E-commerce last-mile in Belgium: Developing an external cost delivery index, Res Transp Bus Manag, 24, 12, pp. 3-9, (2017); Yudha SW., Air Pollution And Its Implications For Indonesia: Challenges And Imperatives For Change, (2017); Biaya Logistik Agregat; Serrano-hernandez A, Alvarez P, Lerga I, Reyes-rubiano L., Pricing and Internalizing Noise Externalities in Road Freight Transportation, Transp Res, 27, 3, pp. 25-32, (2017); Janjevic M, Winkenbach M, Merchan D., Integrating collection-and-delivery points in the strategic design of urban last-mile e-commerce distribution networks, Transp Res Part E, 131, pp. 37-67, (2019); Irnich S., Toth P., Vigo D., Chapter 1 The Family of Vehicle Routing Problems, Vehicle routing: Problems, methods, and applications, (2014); Erdogan Gunes, An open source Spreadsheet Solver for Vehicle Routing Problems, Comput Oper Res, 84, pp. 62-72, (2017); Toth P., Vigo D., Vehicle routing: Problems, methods, and applications, (2014); Inovasi Logistik E-Commerce; Why Last Mile Logistic; Handbook on The External Costs of Transport, (2019); Pisinger D, Ropke S., A general heuristic for vehicle routing problems, Comput Oper Res, 34, pp. 24-35, (2007); Subramanian A, Drummond LMA, Bentes C, Ochi LS, Farias R., A parallel heuristic for the Vehicle Routing Problem with Simultaneous Pickup and Delivery, Comput Oper Res, 37, 18, pp. 99-111, (2010); Vidal T, Crainic TG, Gendreau M, Prins C., A unified solution framework for multi-attribute vehicle routing problems, Eur J Oper Res, 234, 6, pp. 58-73, (2014); Niu Y, Yang Z, Chen P, Xiao J., Optimizing the green open vehicle routing problem with time windows by minimizing comprehensive routing cost, J Clean Prod, 171, 9, pp. 62-71, (2018); Martins-turner K, Nagel K, Martins-turner K, Nagel K., How Driving Multiple Tours A ff ects the Results of Last Mile How Driving Delivery Multiple Vehicle Tours A ff ects the Results of Last Mile Routing Problems Delivery Vehicle Routing Problems, Procedia Comput Sci, 151, 84, pp. 0-5, (2019)","N. Nahry; Universitas Indonesia, Faculty of Engineering, Department of Civil Engineering, Depok, Indonesia; email: nahry@eng.ui.ac.id",null,"Institut za Istrazivanja",{"$nulls":5},1.4514117E7,null,null,null,"English","J. Appl. Eng. Sci.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85102704965"]
["Lu B.; Zhang S.","Lu, Baozhou (50561752000); Zhang, Song (57196100819)","50561752000; 57196100819","A conjoint approach to understanding online buyers’ decisions towards online marketplaces",2020.0,"Journal of Theoretical and Applied Electronic Commerce Research",15.0,3.0,null,69.0,83.0,14.0,10.0,"10.4067/S0718-18762020000300106","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85083709172&doi=10.4067%2fS0718-18762020000300106&partnerID=40&md5=c9a76bc0cd2a0069ae010700f11cc6b5","Qingdao University, Business School, Qingdao, China","Lu B., Qingdao University, Business School, Qingdao, China; Zhang S., Qingdao University, Business School, Qingdao, China","The marketplace-based e-commerce is the dominant type so far. Therefore, it is important to understand the decisional attributes and their relevance for online consumers when choosing marketplaces. However, little research is devoted to this issue. This paper outlines seven attributes of marketplace based on three theories, including ease of use, usefulness, logistics service quality, effectiveness of feedback mechanisms, effectiveness of escrow service, effectiveness of information security services, and effectiveness of dispute resolution mechanisms. Via conjoint analysis methodology, we find that for the whole sample effectiveness of dispute resolution is the most important attribute, whereas logistics service quality is the least important one. The results further reveal gender has impacts on the relative strength of each attribute: while male buyers think some attributes (i.e., effectiveness of dispute resolution mechanisms and effectiveness of information security services) are more important than others (i.e., logistics service quality), female buyers consider that each attribute is equally important. This study suggests that institutional theory and technology adoption model offer more relevant theoretical perspective than the logistics service theory for marketplace choice. Though having limitations including focusing on young users in one region, this paper offers several theoretical contributions to research and some insights for practice. © 2020 Universidad de Talca-Chile.","Conjoint analysis; Decisional attribute; Institutional mechanisms; Marketplace choice; Online purchase decision",{"$nulls":5},"National Office for Philosophy and Social Sciences, NPOPSS, (16BGL075); Humanities and Social Science Fund of Ministry of Education of China, (19YJA630115)","This work is supported by the National Social Science Fund of China (Grant No. 16BGL075) and the Ministry of Education of Humanities and Social Science project (Grant No. 19YJA630115). The authors are also extremely grateful to the editors and the three anonymous reviewers for their insightful comments on this paper.","Angriawan A., Thakur R., A parsimonious model of the antecedents and consequence of online trust: An uncertainty perspective, Journal of Internet Commerce, 7, 1, pp. 74-94, (2008); Ba S., Pavlou P.A., Evidence of the effect of trust buliding technology in electronic markets: Price premiums and buyer behavior, MIS Quarterly, 26, 3, pp. 243-268, (2002); Bauer H.H., Grether M., Virtual community: Its contribution to customer relationships by providing social capital, Journal of Relationship Marketing, 4, 1-2, pp. 91-109, (2005); Bienstock C.C., Royne M.B., Technology acceptance and satisfaction with logistics services, International Journal of Logistics Management, 21, 2, pp. 271-292, (2010); Blanchard A., Horan T., Virtual communities and social capital, Social Science Computer Review, 16, 3, pp. 293-307, (1998); Bouzaabia R., Bouzaabia O., Capatina A., Retail logistics service quality: A crosscultural survey on customer perceptions, International Journal of Retail & Distribution Management, 41, 8, pp. 627-647, (2013); Bulut Z.A., Karabulut A.N., Examining the role of two aspects of ewom in online repurchase intention: An integrated trust-loyalty perspective, Journal of Consumer Behaviour, 17, 4, pp. 407-417, (2018); Chong A.Y.L., Lacka E., Boying L., Chan H.K., The role of social media in enhancing guanxi and perceived effectiveness of e-commerce institutional mechanisms in online marketplace, Information and Management, 55, 5, pp. 621-632, (2018); China Internet Purchase Market Research Report, (2015); Collier J., Bienstock C., Measuring service quality in e-retailing, Journal of Service Research, 8, 3, pp. 260-275, (2006); Crusciel D., Zahedi F.M., Seller-based vs. Buyer-based Internet intermediaries: A research design, Proceedings of 4Th Americas Conf. 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An explanation based on self-determination theory, Behaviour & Information Technology, 37, 8, pp. 786-799, (2018); Gefen D., Karahanna E., Straub D.W., Trust and TAM in online shopping: An integrated model, MIS Quarterly, 27, 1, pp. 51-90, (2003); Gefen D., Straub D.W., Consumer trust in B2C e-commerce and the importance of social presence: Experiments in e-products and e-services, Omega, 32, 6, pp. 407-424, (2004); Gefen D., Pavlou P.A., The boundaries of trust and risk: The quadratic moderating role of institutional structures, Information Systems Research, 23, 3-2, pp. 940-959, (2012); Green P.E., Srinivasan V., Conjoint analysis in marketing: New developments with implications for research and practice, Journal of Marketing, 54, 4, pp. 3-19, (1990); Green P.E., Krieger A.M., Wind Y., Thirty years of conjoint analysis: Reflections and prospects, Interfaces, 31, pp. 56-73, (2001); Grover V., Teng J.T.C., E-commerce and the information market, Communications of the ACM, 44, 4, pp. 79-86, (2001); 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Theor. Appl. Electron. Commer. Res.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85083709172"]
["Agus A.A.; Yudoko G.; Mulyono N.; Imaniya T.","Agus, Anna Amalyah (57215328810); Yudoko, Gatot (55899413800); Mulyono, Nurbudi (54891988000); Imaniya, Taliya (57215306756)","57215328810; 55899413800; 54891988000; 57215306756","E-Commerce Performance, Digital Marketing Capability and Supply Chain Capability within E-Commerce Platform: Longitudinal Study Before and After COVID-19",2021.0,"International Journal of Technology",12.0,2.0,null,360.0,370.0,10.0,24.0,"10.14716/ijtech.v12i2.4122","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85110251732&doi=10.14716%2fijtech.v12i2.4122&partnerID=40&md5=30f2865a64305b4d48c06121c6c0c169","School of Business and Management, Bandung Institute of Technology, Jl. Ganesha 10, Bandung, 40132, Jawa Barat, Indonesia; Department of Management, Faculty of Economics and Business, Universitas Indonesia, Kampus UI Depok, 16424, Jawa Barat, Indonesia","Agus A.A., School of Business and Management, Bandung Institute of Technology, Jl. Ganesha 10, Bandung, 40132, Jawa Barat, Indonesia; Yudoko G., School of Business and Management, Bandung Institute of Technology, Jl. Ganesha 10, Bandung, 40132, Jawa Barat, Indonesia; Mulyono N., School of Business and Management, Bandung Institute of Technology, Jl. Ganesha 10, Bandung, 40132, Jawa Barat, Indonesia; Imaniya T., Department of Management, Faculty of Economics and Business, Universitas Indonesia, Kampus UI Depok, 16424, Jawa Barat, Indonesia",". The Corona Virus Disease (COVID)-19 pandemic has disrupted the business and industry landscape and changed consumers’ behavior. The purpose of this paper was to explore how the behavior of online shoppers and sellers changed because of the COVID-19 outbreak. The originality of this paper lies in combining four main constructs: digital promotion capability, supply chain capability, customer experience, and performance of the e-commerce platform. It incorporates intervening factors like seasonal pricing and logistics outsourcing in the context of COVID 19. The main findings were that, before the pandemic, customer review ratings had a significant positive effect on the performance of the e-commerce platform, but not after the outbreak. Meanwhile, logistics outsourcing does not intervene in the relationship between perceived supply chain capability and (relative) e-commerce platform performance, unlike before the pandemic. This research is a longitudinal study before and after the COVID 19 pandemic, with a call-back sample size of 88 end customer respondents and 55 seller respondents. Data gathered from previous and current e-commerce research were processed by multivariate regression using SPSS software. © 2021, International Journal of Technology. All Rights Reserved.","COVID-19; Customer review rating; Digital marketing; E-commerce performance; Supply chain capability",{"$nulls":7},"Channel Shift: Prioritizing Digital Commerce, Navigating the Human and Business Impact Of COVID-19, pp. 1-26; Respond, Reset and Renew. Navigating the Impact of COVID-19 in Consumer Goods, pp. 1-17, (2020); Agus A.A, Yudoko G., Mulyono N.B, Imaniya T., E-commerce Platform Performance, Digital Marketing and Supply Chain Capability, International Research Journal of Business Studies, 13, 1, pp. 63-80, (2020); Bakker E., Zheng J., Knight L., Harland C., Putting E-Commerce Adoption in a Supply Chain Context, International Journal of Operations and Production Management, 28, 4, pp. 313-330, (2008); Bao H., Li B., Shen J., Hou F., Industrial Management & Data Systems Article Information: Repurchase Intention in Chinese E-Marketplace: Roles of Interactivity, Trust and Perceived Effectiveness of E-commerce Institutional Mechanisms, Industrial Management & Data Systems, 116, 8, pp. 1759-1778, (2016); Belch G.E., Belch M.A., Advertising and Promotion: An Integrated Marketingcommunications Perspective, (2009); Berawi M.A, Suwartha N., Kusrini E., Yuwono A.H., Harwahyu R., Setiawan E.A., Yatmo Y.A., Atmodiwirjo P., Zagloel Y.T., Suryanegara M., Putra N., Budiyarnto M.A, Whulanza Y., Tackling the COVID-19 Pandemic: Managing the Cause, Spread and Impact, International Journal of Technology, 11, 2, pp. 209-214, (2020); Gong W., National Culture and Global Diffusion of Business-to-Consumer E-Commerce, Cross Cultural Management: An International Journal, 16, 1, pp. 83-101, (2009); Gudigantala N., Bicen P., Eom M., An Examination of Antecedents of Conversion Rates of E-Commerce Retailers, Management Research Review, 39, pp. 82-114, (2016); Hartmann E., Herb S., Opportunism Risk in Service Triads – A Social Capital Perspective, International Journal of Physical Distribution and Logistics Management, 44, 3, pp. 242-256, (2014); Karjaluoto H., Mustonen N., Ulkuniemi P., The Role of Digital Channels in Industrial Marketing Communications, Journal of Business and Industrial Marketing, 30, 6, pp. 703-710, (2015); Malhotra N., Marketing Research: An Applied Orientation, (2019); Race Against the Virus: Indonesian Consumer’s Response towards COVID-19, (2020); Pentina I., Hasty R.W., Effects of Multichannel Coordination and E-Commerce Outsourcing on Online Retail Performance, Journal of Marketing Channels, 4, pp. 359-374, (2009); Sahney S., Ghosh K., Shrivastava A., Buyer’s Motivation” for Online Buying: An Empirical Case of Railway E-Ticketing in Indian Context, Journal of Asia Business Studies, 8, 1, pp. 43-64, (2013); Tunjung N., Kreshanti P., Saharman Y.R., Whulanza Y., Supriadi S., Chalid M., Anggraeni M.I., Hamid A.R.A.H., Sukasah C.L., Clinical Evaluation of Locally Made Flocked Swabs in Response to the COVID-19 Pandemic in a Developing Country, International Journal of Technology, 11, 5, pp. 878-887, (2020); Whulanza Y., Supriadi S., Chalid M., Kreshanti P., Agus A.A., Napitupulu P., Supriyanto J.W., Rivai E., Purnomo A., Setting Acceptance Criteria for a National Flocked Swab for Biological Specimens during the COVID-19 Pandemic, International Journal of Technology, 11, 5, pp. 888-899, (2020); Yu Y., Wang X., Zhong R.Y., Huang G.Q., E-Commerce Logistics in Supply Chain Management Implementations and Future Perspective in Furniture Industry, Industrial Management and Data Systems, 117, pp. 2263-2286, (2017); Zhou S., Sun B., Ma W., Chen X., The Pricing Strategy for Fuji Apple in Shaanxi of Chain under the E-Commerce Environment, Kybernetes, 47, pp. 208-221, (2018)","A.A. Agus; School of Business and Management, Bandung Institute of Technology, Bandung, Jl. Ganesha 10, 40132, Indonesia; email: anna_amalyah@sbm-itb.ac.id",null,"Faculty of Engineering, Universitas Indonesia",{"$nulls":5},2.0869614E7,null,null,null,"English","Int. J. Technol.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85110251732"]
["Sun Q.; Jiang L.; Xu H.","Sun, Qi (57190947157); Jiang, Liwen (57216289077); Xu, Haitao (57221722760)","57190947157; 57216289077; 57221722760","Expectation-Maximization Algorithm of Gaussian Mixture Model for Vehicle-Commodity Matching in Logistics Supply Chain",2021.0,"Complexity",2021.0,null,9305890.0,null,null,null,13.0,"10.1155/2021/9305890","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85099953293&doi=10.1155%2f2021%2f9305890&partnerID=40&md5=b8797604cf867134aaabc2d689ea4c93","Antai College of Economics and Management, Shanghai Jiao Tong University, Shanghai, China; College of Economics and Management, Shandong University of Science and Technology, Qingdao, China; Department of Electrical Engineering and Computer Science, Cleveland State University, Cleveland, OH, United States","Sun Q., Antai College of Economics and Management, Shanghai Jiao Tong University, Shanghai, China; Jiang L., College of Economics and Management, Shandong University of Science and Technology, Qingdao, China; Xu H., Antai College of Economics and Management, Shanghai Jiao Tong University, Shanghai, China, Department of Electrical Engineering and Computer Science, Cleveland State University, Cleveland, OH, United States","A vehicle-commodity matching problem (VCMP) is presented for service providers to reduce the cost of the logistics system. The vehicle classification model is built as a Gaussian mixture model (GMM), and the expectation-maximization (EM) algorithm is designed to solve the parameter estimation of GMM. A nonlinear mixed-integer programming model is constructed to minimize the total cost of VCMP. The matching process between vehicle and commodity is realized by GMM-EM, as a preprocessing of the solution. The design of the vehicle-commodity matching platform for VCMP is designed to reduce and eliminate the information asymmetry between supply and demand so that the order allocation can work at the right time and the right place and use the optimal solution of vehicle-commodity matching. Furthermore, the numerical experiment of an e-commerce supply chain proves that a hybrid evolutionary algorithm (HEA) is superior to the traditional method, which provides a decision-making reference for e-commerce VCMP.  © 2021 Qi Sun et al.",null,"Decision making; Electronic commerce; Evolutionary algorithms; Gaussian distribution; Integer programming; Maximum principle; Numerical methods; Supply chains; Vehicles; Expectation-maximization algorithms; Gaussian Mixture Model; Hybrid evolutionary algorithm; Information asymmetry; Logistics supply chains; Non-linear mixed integer programming; Numerical experiments; Vehicle classification; Image segmentation",{"$nulls":6},"Andersson D., A novel approach to calculate individuals' carbon footprints using financial transaction data-app development and design, Journal of Cleaner Production, 256, (2020); Beisland L.A., Djan K.O., Mersland R., Randoy T., Measuring social performance in social enterprises: A global study of microfinance institutions, Journal of Business Ethics, pp. 1-21, (2020); 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Garg H., A hybrid GSA-GA algorithm for constrained optimization problems, Information Sciences, 478, pp. 499-523, (2019); Garg H., A hybrid PSO-GA algorithm for constrained optimization problems, Applied Mathematics and Computation, 274, pp. 292-305, (2016); Janjevic M., Winkenbach M., Characterizing urban last-mile distribution strategies in mature and emerging e-commerce markets, Transportation Research Part A: Policy and Practice, 133, pp. 164-196, (2020); Garg H., Exponential operational laws and new aggregation operators for intuitionistic multiplicative set in multiple-attribute group decision making process, Information Sciences, 538, pp. 245-272, (2020); Moghaddam K.S., Fuzzy multi-objective model for supplier selection and order allocation in reverse logistics systems under supply and demand uncertainty, Expert Systems with Applications, 42, 15-16, pp. 6237-6254, (2015); Cont R., Stoikov S., Talreja R., A stochastic model for order book dynamics, Operations Research, 58, 3, pp. 549-563, (2010); Bayraktar E., Ludkovski M., Liquidation in limit order books with controlled intensity, Mathematical Finance, 24, 4, pp. 627-650, (2014); Mafakheri F., Breton M., Ghoniem A., Supplier selection-order allocation: A two-stage multiple criteria dynamic programming approach, International Journal of Production Economics, 132, 1, pp. 52-57, (2011); Kannan D., Khodaverdi R., Olfat L., Diabat A., Integrated fuzzy multi criteria decision making method and multi-objective programming approach for supplier selection and order allocation in a green supply chain, Journal of Cleaner Production, 47, pp. 355-367, (2013); Azadnia A.H., Saman M.Z.M., Wong K.Y., Sustainable supplier selection and order lot-sizing: An integrated multi-objective decision-making process, International Journal of Production Research, 53, 2, pp. 383-408, (2015); Torfi F., Farahani R.Z., Mahdavi I., Fuzzy MCDM for weight of object's phrase in location routing problem, Applied Mathematical Modelling, 40, 1, pp. 526-541, (2016); Marinakis Y., An improved particle swarm optimization algorithm for the capacitated location routing problem and for the location routing problem with stochastic demands, Applied Soft Computing, 37, pp. 680-701, (2015); Macedo R., Alves C., Hanafi S., Skewed general variable neighborhood search for the location routing scheduling problem, Computers & Operations Research, 61, pp. 143-152, (2015); Foreman J., Gallien J., Alspaugh J., Implementing supply-routing optimization in a make-to-order manufacturing network, Manufacturing & Service Operations Management, 12, 4, pp. 547-568, (2010); Yue J., Xia Y., Tran T., Selecting sourcing partners for a make-to-order supply chain, Omega, 38, 3-4, pp. 136-144, (2010); Sawik T., Single vs. multiple objective supplier selection in a make to order environment, Omega, 38, 3-4, pp. 203-212, (2010); Sawik T., Selection of a dynamic supply portfolio in make-to-order environment withrisks, Computers & Operations Research, 38, 4, pp. 782-796, (2011); Sawik T., Joint supplier selection and scheduling of customer orders under disruption risks: Single vs. dual sourcing, Omega, 43, pp. 83-95, (2014); Sawik T., Selection of supply portfolio under disruption risks, Omega, 39, 2, pp. 194-208, (2011); Ren Y., Croson R., Overconfidence in newsvendor orders: An experimental study, Management Science, 59, 11, pp. 2502-2517, (2013); Pan W., Wang X., Zhong Y.-G., A fuzzy multi-objective model for capacity allocation and pricing policy of provider in data communication service with different QoS levels, International Journal of Systems Science, 43, 6, pp. 1054-1063, (2012); Hall N., Liu Z., Capacity allocation and scheduling in supply chains, Operations Research, 58, 6, pp. 1711-1725, (2010); Moghaddam K.S., Supplier selection and order allocation in closed-loop supply chain systems using hybrid Monte Carlo simulation and goal programming, International Journal of Production Research, 53, 20, pp. 6320-6338, (2015)","L. Jiang; College of Economics and Management, Shandong University of Science and Technology, Qingdao, China; email: jiangliwen@sdust.edu.cn",null,"Hindawi Limited",{"$nulls":5},1.0762787E7,null,null,null,"English","Complexity","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85099953293"]
["Subashanthini S.; Pounambal M.","Subashanthini, S. (56071189700); Pounambal, M. (36873503100)","56071189700; 36873503100","Three stage hybrid encryption of cloud data with penta-layer security for online business users",2020.0,"Information Systems and e-Business Management",18.0,3.0,null,379.0,404.0,25.0,4.0,"10.1007/s10257-019-00419-6","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85070772575&doi=10.1007%2fs10257-019-00419-6&partnerID=40&md5=b642b96b80833df3fd7eb5ca20a9b8e0","School of Information Technology, Vellore Institute of Technology, Vellore, India","Subashanthini S., School of Information Technology, Vellore Institute of Technology, Vellore, India; Pounambal M., School of Information Technology, Vellore Institute of Technology, Vellore, India","Interactive media applications in smart electronic business (e-business), for example, web based exchanging and Internet advertising, dependably face security issues in storing and retrieval of text, images, audio and video. The proposed work addresses the problem of security in e-commerce and proposes a unified framework to secure the image data that are stored in the third party cloud. A three-stage image encryption procedure is proposed in this paper, which combines integer wavelet transform (IWT), chaotic maps and deoxyribose nucleic acid (DNA) encoding rule. The proposed technique uses five levels of security by generating five key sequences through five different chaotic maps. A grayscale image is partitioned as 8 × 8 blocks. Key 1 is generated using logistic map to select an 8 × 8 block randomly. Line map is utilized to create Key 2, in order to scramble the selected 8 × 8 block. Tent map derives Key 3 to randomize the choice of IWTs between Haar or 5/3. Approximation coefficients are scrambled using Key 4 derived from Henon map. The resultant scrambled block is encrypted by selecting a DNA rule using Key 5 that is generated using sine map. The proposed methodology is validated through several performance analysis metrics, and the algorithm achieves an entropy of 7.99, PSNR of 9 dB and near-zero correlation. The algorithm is also resistant to differential attacks and brute force with the key space greater than 2128. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature.","Chaotic maps; Cloud storage; DNA encoding; E-commerce; Image encryption; Integer wavelet transform",{"$nulls":7},"Belazi A., Abd El-Latif A.A., Diaconu A., Rhouma R., Belghith S., Chaos-based partial image encryption scheme based on linear fractional and lifting wavelet transforms, Opt Lasers Eng, 88, pp. 37-50, (2017); Cai S., Huang L., Chen X., Xiong X., A symmetric plaintext-related color image encryption system based on bit permutation, Entropy, 20, 4, (2018); Goldstein A., Frank U., Components of a multi-perspective modeling method for designing and managing IT security systems, Inf Syst E-Bus Manag, 14, (2016); Huang X., Ye G., An efficient self-adaptive model for chaotic image encryption algorithm, Commun Nonlinear Sci Numer Simul, 19, 12, pp. 4094-4104, (2014); Khajouei H., Kazemi M., Moosavirad S.H., Ranking information security controls by using fuzzy analytic hierarchy process, Inf Syst E-Bus Manag, 15, (2017); Khanzadi H., Eshghi M., Borujeni S.E., Image encryption using random bit sequence based on chaotic maps, Arab J Sci Eng, 39, 2, pp. 1039-1047, (2014); Li S., Yin B., Ding W., Zhang T., Ma Y., A nonlinearly modulated logistic map with delay for image encryption, Electronics (Switzerland), 7, 11, (2018); Liu L., Zhang Q., Wei X., A RGB image encryption algorithm based on DNA encoding and chaos map, Comput Electr Eng, 38, 5, pp. 1240-1248, (2012); Liu H., Wang X., Kadir A., Image encryption using DNA complementary rule and chaotic maps, Appl Soft Comput J, 12, 5, pp. 1457-1466, (2012); Praveenkumar P., Amirtharajan R., Thenmozhi K., Balaguru Rayappan J.B., Medical data sheet in safe havens: a tri-layer cryptic solution, Comput Biol Med, 62, pp. 264-276, (2015); Praveenkumar P., Amirtharajan R., Thenmozhi K., Rayappan J.B.B., Fusion of confusion and diffusion: a novel image encryption approach, Telecommun Syst, 65, 1, pp. 65-78, (2017); Ramalingam B., Rengarajan A., Rayappan J.B.B., Hybrid image crypto system for secure image communication: a VLSI approach, Microprocess Microsyst, 50, pp. 1-13, (2017); Ravichandran D., Praveenkumar P., Balaguru Rayappan J.B., Amirtharajan R., Chaos based crossover and mutation for securing DICOM image, Comput Biol Med, 72, pp. 170-184, (2016); Ravichandran D., Praveenkumar P., Rayappan J.B.B., Amirtharajan R., DNA chaos blend to secure medical privacy, IEEE Trans Nanobiosci, 16, 8, pp. 850-858, (2017); Seyedzadeh S.M., Norouzi B., Mosavi M.R., Mirzakuchaki S., A novel color image encryption algorithm based on spatial permutation and quantum chaotic map, Nonlinear Dyn, 81, 1-2, pp. 511-529, (2015); Tedmori S., Al-Najdawi N., Image cryptographic algorithm based on the Haar wavelet transform, Inf Sci, 269, pp. 21-34, (2014); Wang X., Liu C., A novel and effective image encryption algorithm based on chaos and DNA encoding, Multimed Tools Appl, 76, 5, pp. 6229-6245, (2017); Wang Y., Wong K., Liao X., Chen G., A new chaos-based fast image encryption algorithm, Appl Soft Comput J, 11, 1, pp. 514-522, (2011); Wang X., Gu S., Zhang Y., Novel image encryption algorithm based on cycle shift and chaotic system, Opt Lasers Eng, 68, pp. 126-134, (2015); Wu X., Wang D., Kurths J., Kan H., A novel lossless color image encryption scheme using 2D DWT and 6D hyperchaotic system, Inf Sci, 349-350, pp. 137-153, (2016); Xiao G., Lu M., Qin L., Lai X., New field of cryptography: DNA cryptography, Chin Sci Bull, 51, 12, pp. 1413-1420, (2006); Xu L., Gou X., Li Z., Li J., A novel chaotic image encryption algorithm using block scrambling and dynamic index based diffusion, Opt Lasers Eng, 91, pp. 41-52, (2017); Ye G., Huang X., A feedback chaotic image encryption scheme based on both bit-level and pixel-level, JVC J Vib Control, 22, 5, pp. 1171-1180, (2016); Younas I., Khan M., A new efficient digital image encryption based on inverse left almost semi group and Lorenz chaotic system, Entropy, 20, 12, (2018); Zhang Q., Guo L., Wei X., Image encryption using DNA addition combining with chaotic maps, Math Comput Model, 52, 11-12, pp. 2028-2035, (2010); Zhang Q., Liu L., Wei X., Improved algorithm for image encryption based on DNA encoding and multi-chaotic maps, AEU Int J Electron Commun, 68, 3, pp. 186-192, (2014)","M. Pounambal; School of Information Technology, Vellore Institute of Technology, Vellore, India; email: mpounambal@vit.ac.in",null,"Springer Science and Business Media Deutschland GmbH",{"$nulls":5},1.6179846E7,null,null,null,"English","Inf. Syst. e-Bus. Manage.","Article","Final",null,"Scopus","2-s2.0-85070772575"]
["Sarfo C.A.; Song H.","Sarfo, Christian Agyapong (57221854044); Song, Hayeon (8909051200)","57221854044; 8909051200","E-commerce adoption within SME's in Ghana, a tool for growth?",2021.0,"International Journal of Electronic Business",16.0,1.0,null,32.0,51.0,19.0,4.0,"10.1504/IJEB.2021.112764","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85100421210&doi=10.1504%2fIJEB.2021.112764&partnerID=40&md5=24bed4bcf86786baa2ae13fdc666519c","Division of Commerce, Otago University, New Zealand; School of Business, Sungkyunkwan University, South Korea","Sarfo C.A., Division of Commerce, Otago University, New Zealand; Song H., School of Business, Sungkyunkwan University, South Korea","Electronic commerce presents small and medium enterprises (SMEs) in developing economies the opportunity to compete on a global stage. With theoretical underpinning of the technology acceptance model (TAM) and technology-organisation-environment (TOE), this study investigated e-commerce adoption among SMEs in Ghana. Managers and owners of SMEs participated in both survey (n = 152) and interview (n = 38). Partial least squares regression analysis indicates that the introduction of point of sale (POS) machines for SMEs will improve offline cashless trading, which must necessarily precede online trading for an effective payment system to exist. An increased internet penetration rate would enable nationwide e-commerce participation rather than the current skewed practice with e-commerce dominance within southern Ghana. For the private investor, there exists a market for logistics services. The Ghana postal service must, however, take the lead to serve as a blueprint as well as a source of data for private investors. Copyright © 2021 Inderscience Enterprises Ltd.","E-commerce; Ghana; Net benefits; SMEs","Least squares approximations; Privatization; Developing economies; E-commerce adoption; Logistics services; Partial least squares regression analysis; Penetration rates; Private investors; Small and medium enterprise; Technology acceptance model; Electronic commerce",{"$nulls":6},"Adaji I., Vassileva J., Perceived effectiveness, credibility and continuance intention in e-commerce: a study of Amazon, International Conference on Persuasive Technology, pp. 293-306, (2017); Al-Alawi A.I., Al-Ali F.M., Factors affecting e-commerce adoption in SMEs in the GCC: an empirical study of Kuwait, Research Journal of Information Technology, 7, 1, pp. 1-21, (2015); Ali A., Rasool G., Pathania A., Antecedents for success of e-commerce platforms: an investigative approach, International Journal of Information Technology and Management, 16, 4, pp. 376-390, (2017); Al-Qirim N., The adoption of ecommerce communications and applications technologies in small businesses in New Zealand, Electronic Commerce Research and Applications, 6, 4, pp. 462-473, (2007); Awa H.O., Ojiabo O.U., Emecheta B.C., Integrating TAM, TPB and TOE frameworks and expanding their characteristic constructs for e-commerce adoption by SMEs, Journal of Science & Technology Policy Management, 6, 1, pp. 76-94, (2015); Awiagah R., Kang J., Lim J.I., Factors affecting e-commerce adoption among SMEs in Ghana, Information Development, 32, 4, pp. 815-836, (2016); Awiagah R., Kang J., Lim J.I., Factors affecting e-commerce adoption among SMEs in Ghana, Information Development, 32, 4, pp. 815-836, (2016); Brynjolfsson E., Smith M.D., Frictionless commerce? A comparison of internet and conventional retailers, Management Science, 46, 4, pp. 563-585, (2000); Ghana - Telecoms, Mobile, Broadband and Forecasts, (2013); Davis F.D., Perceived usefulness, perceived ease of use, and user acceptance of information technology, MIS Quarterly, 3, 3, pp. 319-340, (1989); Delone W.H., Mclean E.R., Measuring e-commerce success: applying the DeLone & McLean information systems success model, International Journal of Electronic Commerce, 9, 1, pp. 31-47, (2004); Deshmukh S.P., Naware A.M., Mobile money: M-payment system for India, International Journal of Computer Science & Information Technologies, 5, 2, (2014); Dong J., Hu Z., Liang C., E-commerce supply chain coordination under demand influenced by historical sales rate, 2017 3rd International Conference on Information Management (ICIM), pp. 61-71, (2017); Dowuona-Hammond C., Consumer law and policy in Ghana, Journal of Consumer Policy, 41, 4, pp. 333-354, (2018); Edward T., E-Commerce in Ghana, Where Are We?, (2015); Frempong G., Trends in ICT usage by small and medium scale enterprises in Ghana, ATDF Journal, 4, 1, pp. 3-10, (2007); Gan L., Liu L., The development and status of automobile e-commerce in China, Research and Practical Issues of Enterprise Information Systems II, pp. 1535-1544, (2008); Gefen D., Straub D.W., The relative importance of perceived ease of use in IS adoption: a study of e-commerce adoption, Journal of the association for Information Systems, 1, 1, pp. 1-30, (2000); Ghorishi M., E-Commerce Adoption Model in Iranian SME's: Investigating the Causal Link between Perceived Strategic Value of e-Commerce & Factor of Adoption, (2009); Ghose A., Sundararajan A., Evaluating pricing strategy using e-commerce data: evidence and estimation challenges, Statistical Science, 1, 2, pp. 131-142, (2006); Golubova S., E-commerce Adoption and Implementation Strategy for a High-Tech Firm, (2012); Grandon E., Pearson J.M., Strategic value and adoption of electronic commerce: an empirical study of Chilean small and medium businesses, Journal of Global Information Technology Management, 6, 3, pp. 22-43, (2003); Henseler J., Dijkstra T.K., Sarstedt M., Ringle C.M., Diamantopoulos A., Straub D.W., Calantone R.J., Common beliefs and reality about PLS: comments on Rönkkö and Evermann (2013), Organizational Research Methods, 17, 2, pp. 182-209, (2014); World Information Society Report 2017, (2017); Ivanov D., The impact of e-commerce on small-size companies in Sweden, (2012); Li X., Zheng Y., Zhou Z., Zheng Z., Demand prediction, predictive shipping, and product allocation for large-scale e-commerce, Predictive Shipping, and Product Allocation for Large-Scale E-Commerce, (2018); Olusola A.A., Motunrayo O.A., Comparative analysis of e-commerce in Nigeria: problems, solutions and efficacy, Journal of Emerging Trends in Computing and Information Sciences, 6, 1, pp. 68-75, (2015); Quarshie H.O., Ami-Narh J., The growth and usage of internet in Ghana, Journal of Emerging Trends in Computing and Information Sciences, 3, 9, pp. 1302-1308, (2012); Rahayu R., Day J., Determinant factors of e-commerce adoption by SMEs in developing country: evidence from Indonesia, Procedia-Social and Behavioral Sciences, 195, pp. 142-150, (2015); Rosen J.W., Ghana's last mile, Technology Review, 120, 1, pp. 74-87, (2017); Shih T.H., Fan X., Comparing response rates from web and mail surveys: a meta-analysis, Field Methods, 20, 3, pp. 249-271, (2008); Singh P., Keswani S., Singh S., Sharma S., A study of adoption behavior for online shopping: an extension of tam model, IJASSH, 4, 7, pp. 11-22, (2018); Tenenhaus M., Vinzi V.E., Chatelin Y.M., Lauro C., PLS path modeling, Computational Statistics & Data Analysis, 48, 1, pp. 159-205, (2005); Tornatzky L.G., Fleischer M., Chakrabarti A.K., Processes of Technological Innovation, (1990); Trautman L.J., E-commerce, cyber, and electronic payment system risks: lessons from PayPal, UC Davis Bus. LJ, 16, 1, pp. 261-307, (2015); Uljala L., Scupola A., Motivators and inhibitors of e-residency adoption for globale-entrepreneurship, Services, Experiences and Innovation, (2018); Information Economy Report: Unlocking the Potential of E-commerce for Developing Countries, (2015); Venkatesh V., Davis F.D., A theoretical extension of the technology acceptance model: four longitudinal field studies, Management Science, 46, 2, pp. 186-204, (2000); Venkatesh V., Morris M.G., Davis G.B., Davis F.D., User acceptance of information technology: toward a unified view, MIS Quarterly, 27, 3, pp. 425-478, (2003); Wang Y.S., Wang Y.M., Lin H.H., Tang T.I., Determinants of user acceptance of internet banking: an empirical study, International Journal of Service Industry Management, 14, 5, pp. 501-519, (2003); World Development Indicators: Power and Communications, (2016); Yaseen H., Dingley K., Alhusban M.D., Alhosban A., E-commerce adoption model for traditional retailers in developing countries, Int. J. Infonomics, 10, 2, pp. 1296-1304, (2017)","C.A. Sarfo; Division of Commerce, Otago University, New Zealand; email: owurananakwaku@gmail.com",null,"Inderscience Publishers",{"$nulls":5},1.4706067E7,null,null,null,"English","Int. J. Electron. Bus.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85100421210"]
["Klapp M.A.; Erera A.L.; Toriello A.","Klapp, Mathias A. (57189397260); Erera, Alan L. (7801316807); Toriello, Alejandro (26634454600)","57189397260; 7801316807; 26634454600","Request acceptance in same-day delivery",2020.0,"Transportation Research Part E: Logistics and Transportation Review",143.0,null,102083.0,null,null,null,23.0,"10.1016/j.tre.2020.102083","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85091381907&doi=10.1016%2fj.tre.2020.102083&partnerID=40&md5=4504a732e1f4a00949bfd530dc613782","Engineering School, Pontificia Universidad Católica de Chile, Santiago, Chile; H. Milton Stewart School of Industrial and Systems Engieering, Georgia Institute of Technology, Atlanta, 30332, Georgia","Klapp M.A., Engineering School, Pontificia Universidad Católica de Chile, Santiago, Chile; Erera A.L., H. Milton Stewart School of Industrial and Systems Engieering, Georgia Institute of Technology, Atlanta, 30332, Georgia; Toriello A., H. Milton Stewart School of Industrial and Systems Engieering, Georgia Institute of Technology, Atlanta, 30332, Georgia","We study request acceptance dynamics in same-day delivery systems by formulating the Dynamic Dispatch Waves Problem with Immediate Acceptance, which models integrated management and distribution for dynamically arriving customer requests. We consider an e-commerce platform that attempts to serve most customers with same-day delivery service. When a shopper attempts to place an order, a decision is made immediately to offer same-day delivery service (accept the request) or to deny service. Accepted requests are not available for immediate dispatch; they must be processed (picked and packed) before they are loaded for delivery. Vehicle routes are updated dynamically and serve each accepted delivery request no later than the end of the service day. In this work, we limit the study to the case of a single vehicle serving requests, potentially using multiple trips from the distribution center. The objective is to make request acceptance and distribution decisions that minimize the expected sum of vehicle travel costs and penalties for service denials. We develop a framework for dynamic decision policies over continuous time for such systems, where a feasible vehicle dispatch plan is redesigned and used to guide decisions over time. We design methods for determining an initial optimal a priori plan and for updating the plan using a heuristic roll-out procedure. Our methods are tested on a family of simulated instances against two common-sense benchmarks and an infeasible relaxed policy that allows the dispatcher to delay the acceptance or rejection of a request until the end of the service day. We demonstrate in our computational study that the cost-per-request of the best benchmark policy is on average 9.7% higher than our proposed dynamic policy and furthermore that the dynamic policy leads to only a 4.4% cost increase over the infeasible relaxed policy lower bound. © 2020 Elsevier Ltd","Approximate dynamic porgramming; Same-day delivery; Vehicle routing","Continuous time systems; Heuristic methods; Vehicles; Approximate dynamic porgramming; Commerce platforms; Delivery service; Delivery systems; Dynamic dispatch; Dynamic policy; E- commerces; Integrated management; Same-day delivery; Wave problems; consumption behavior; cost analysis; electronic commerce; integrated approach; logistics; management; policy approach; policy development; Vehicle routing",{"$nulls":4},"Fondo Nacional de Desarrollo Científico y Tecnológico, FONDECYT, (11190392); Agencia Nacional de Investigación y Desarrollo, ANID","Mathias Klapp thanks ANID (Agencia Nacional de Investigación y Desarrollo), Chile, for its support through the FONDECYT Iniciación Project number 11190392.","Agatz N., Campbell A.M., Fleischmann M., Savelsbergh M.W.P., Time slot management in attended home delivery, Transp. 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Res., 42, 3, pp. 543-549, (1994); Larsen A., Madsen O.B.G., Solomon M.M., pp. 199-218, (2008); Pillac V., Gendreau M., Gueret C., Medaglia A., A review of dynamic vehicle routing problems, Eur. J. Oper. Res., 225, 1, pp. 1-11, (2013); Powell W., Approximate Dynamic Programming: Solving the Curses of Dimensionality, (2007); Puterman M., Markov Decision Processes: Discrete Stochastic Dynamic Programming, (2009); Savelsbergh M.W.P., Sol M., The general pickup and delivery problem, Transp. Sci., 29, 1, pp. 17-29, (1995); Savelsbergh M.W.P., Van Woensel T., 50th anniversary invited article – city logistics: challenges and opportunities, Transp. Sci., 50, 2, pp. 579-590, (2016); Secomandi N., Margot F., Reoptimization approaches for the vehicle-routing problem with stochastic demands, Oper. 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Res., 269, 3, pp. 883-899, (2018); Ulmer M.W., Thomas B.W., Mattfeld D.C., Preemptive depot returns for a dynamic same-day delivery problem, EURO J. Transp. Logist., pp. 1-35, (2018); pp. 1-3, (2018); pp. 1-19, (2017); Voccia S., Campbell A.M., Thomas B.W., The probabilistic traveling salesman problem with time windows, EURO J. Transp. Logist., pp. 1-19, (2012); Voccia S., Campbell A.M., Thomas B.W., pp. 1-18, (2015); Wen M., Cordeau J.-F., Laporte G., Larsen J., The dynamic multi-period vehicle routing problem, Comput. Oper. Res., 37, 9, pp. 1615-1623, (2010)","M.A. Klapp; Engineering School, Pontificia Universidad Católica de Chile, Santiago, Chile; email: maklapp@ing.puc.cl",null,"Elsevier Ltd",{"$nulls":5},1.3665545E7,null,null,null,"English","Transp. Res. Part E Logist. Transp. Rev.","Article","Final",null,"Scopus","2-s2.0-85091381907"]
["Rachana Harish A.; Liu X.L.; Zhong R.Y.; Huang G.Q.","Rachana Harish, Arjun (57220854460); Liu, X.L. (57204569405); Zhong, Ray Y. (55353690000); Huang, George Q. (7403425048)","57220854460; 57204569405; 55353690000; 7403425048","Log-flock: A blockchain-enabled platform for digital asset valuation and risk assessment in E-commerce logistics financing",2021.0,"Computers and Industrial Engineering",151.0,null,107001.0,null,null,null,50.0,"10.1016/j.cie.2020.107001","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85097778325&doi=10.1016%2fj.cie.2020.107001&partnerID=40&md5=908a4e3c167ce082ec2898787c5994d8","HKU-ZIRI Laboratory for Physical Internet, Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong","Rachana Harish A., HKU-ZIRI Laboratory for Physical Internet, Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong; Liu X.L., HKU-ZIRI Laboratory for Physical Internet, Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong; Zhong R.Y., HKU-ZIRI Laboratory for Physical Internet, Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong; Huang G.Q., HKU-ZIRI Laboratory for Physical Internet, Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong","E-commerce retail sales have seen significant growth in the past decade with its proliferation into the consumer markets at unprecedented rates. This has led to the rise of logistics companies (LC) and the advent of Logistics financing as a tool used by them to attain business expansion. The current climate in e-commerce that is characterized by an upswing in sales requires the LCs to equip themselves with sufficient capital to elevate or modernize their operational capabilities. But, these small and medium-sized enterprises tend to overlook their business expansion opportunities due to the unfavorable financing environment created due to their: (i) limited tangible assets (ii) lack of clarity on operating capability, and (iii) lack of reliable information-sharing mechanism. To address these problems, this study aims to utilize the digital assets of the LC to aid logistics financing. This study introduces a logistics financing platform (Log-Flock), that leverages the abilities of the Internet of Things (IoT), cyber-physical system (CPS), and blockchain technologies to support the utilization of digital assets of the LC for logistics financing. The IoT and CPS are combined to support the generation of the digital assets whereas the core constructs of blockchain technology, such as the tokens and smart contracts, are used to (i) introduce incentivized rewarding mechanisms to motivate the engagement of users and, (ii) to perform the digital asset valuation and risk assessment in logistics financing. Some of the expected benefits from the study include: (i) This novel platform if implemented, would significantly reduce the time for financing. (ii) It communicates the operating capability of the LCs in the form of credit rating which is easily comprehensible for the financing institutions. © 2020 Elsevier Ltd","Blockchain; Digital asset; E-commerce logistics financing; Internet of things; Risk-assessment; Valuation","Blockchain; Electronic commerce; Embedded systems; Expansion; Finance; Internet of things; Sales; Business expansion; Cyber-physical systems (CPS); Information sharing mechanism; Internet of thing (IOT); Logistics financings; Operating capability; Operational capabilities; Small and medium sized enterprise; Risk assessment",{"$nulls":4},"2018 Guangzhou Leading Innovation Team Program, (201909010006); Guangdong Special Support Talent Program – Innovation and Entrepreneurship Leading Team, (2019BT02S593); Innovation and Entrepreneurship Leading Team; RGC, (17203518, ITP/021/20LP)","Funding text 1: The authors would like to acknowledge partial financial supports from funding sources, including HKSAR RGC GRF Project (17203518), HKSAR ITC (LSCM) Project (ITP/021/20LP), the 2019 Guangdong Special Support Talent Program – Innovation and Entrepreneurship Leading Team (China) (2019BT02S593), and 2018 Guangzhou Leading Innovation Team Program (201909010006).; Funding text 2: The authors would like to acknowledge partial financial supports from funding sources, including HKSAR RGC GRF Project (17203518), HKSAR ITC (LSCM) Project (ITP/021/20LP), the 2019 Guangdong Special Support Talent Program ? Innovation and Entrepreneurship Leading Team (China) (2019BT02S593), and 2018 Guangzhou Leading Innovation Team Program (201909010006).","Abe M., Troilo M., Batsaikhan O., Financing small and medium enterprises in Asia and the Pacific, Journal of Entrepreneurship and Public Policy, 4, 1, pp. 2-32, (2015); Al-Doghman F., Chaczko Z., (2017); Ali Z., Gongbing B., Mehreen A., Does supply chain finance improve SMEs performance? The moderating role of trade digitization, Business Process Management Journal, 26, 1, pp. 150-167, (2018); Alyoubi A.A., E-commerce in developing countries and how to develop them during the introduction of modern systems, Procedia Computer Science, 65, pp. 479-483, (2015); Aydiner A.S., Tatoglu E., Bayraktar E., Zaim S., Information system capabilities and firm performance: Opening the black box through decision-making performance and business-process performance, International Journal of Information Management, 47, July 2018, pp. 168-182, (2019); Beck T., Demirguc-Kunt A., Small and medium-size enterprises: Access to finance as a growth constraint, Journal of Banking and Finance, 30, 11, pp. 2931-2943, (2006); Berger A.N., Udell G.F., A more complete conceptual framework for SME finance, Journal of Banking and Finance, 30, 11, pp. 2945-2966, (2006); Best P.J., Rikhardsson P., Best P.J., (2009); (2016); Chen M.C., Wu P.J., Hsu Y.H., An effective pricing model for the congestion alleviation of e-commerce logistics, Computers and Industrial Engineering, 129, pp. 368-376, (2019); Choda J., Inventory, risk shifting, and trade credit, Management Science, 63, 10, pp. 3207-3225, (2017); Davidson S., De Filippi P., Potts J., Economics of Blockchain, SSRN Electronic Journal, 1-23, (2016); (2019); (2014); Evans J., (2020); Hasan H., AlHadhrami E., AlDhaheri A., Salah K., Jayaraman R., Smart contract-based approach for efficient shipment management, Computers and Industrial Engineering, 136, July, pp. 149-159, (2019); Hassan M.U., Rehmani M.H., Chen J., Privacy preservation in blockchain based IoT systems: Integration issues, prospects, challenges, and future research directions, Future Generation Computer Systems, 97, pp. 512-529, (2019); Helo P., Hao Y., Blockchains in operations and supply chains: A model and reference implementation, Computers and Industrial Engineering, 136, July, pp. 242-251, (2019); Janjevic M., Winkenbach M., Characterizing urban last-mile distribution strategies in mature and emerging e-commerce markets, Transportation Research Part A: Policy and Practice, 133, January, pp. 164-196, (2020); Jiang P., Cai C.X., Keasey K., Wright M., Zhang Q., The role of venture capitalists in small and medium-sized enterprise initial public offerings: Evidence from China, International Small Business Journal: Researching Entrepreneurship, 32, 6, pp. 619-643, (2014); Junior O.C.A., Rabelo R.J., A KPI model for logistics partners’ search and suggestion to create virtual organisations, International Journal of Networking and Virtual Organisations, 12, 2, pp. 149-177, (2013); Krauth E., Moonen H., Popova V., (2005); Lee C.K.M., Lv Y., Ng K.K.H., Ho W., Choy K.L., Design and application of internet of things-based warehouse management system for smart logistics, International Journal of Production Research, 56, 8, pp. 2753-2768, (2018); Lee J., Lapira E., Bagheri B., Kao H.A., Recent advances and trends in predictive manufacturing systems in big data environment, Manufacturing Letters, 1, 1, pp. 38-41, (2013); Lee S., Kang Y., Prabhu V.V., Smart logistics: Distributed control of green crowdsourced parcel services, International Journal of Production Research, 54, 23, pp. 6956-6968, (2016); Leenheer J., van Heerde H.J., Bijmolt T.H.A., Smidts A., Do loyalty programs really enhance behavioral loyalty? An empirical analysis accounting for self-selecting members, International Journal of Research in Marketing, 24, 1, pp. 31-47, (2007); Li M., Shen L., Huang G.Q., Blockchain-enabled workflow operating system for logistics resources sharing in E-commerce logistics real estate service, Computers and Industrial Engineering, 135, July, pp. 950-969, (2019); Li Z., Barenji A.V., Huang G.Q., Toward a blockchain cloud manufacturing system as a peer to peer distributed network platform, Robotics and Computer-Integrated Manufacturing, 54, July, pp. 133-144, (2018); Lin S., (2015); Liu X.L., Wang W.M., Guo H., Barenji A.V., Li Z., Huang G.Q., (2020); Lu Q., Gu J., Huang J., Supply chain finance with partial credit guarantee provided by a third-party or a supplier, Computers and Industrial Engineering, 135, October 2017, pp. 440-455, (2019); Moin S., Karim A., Safdar Z., Safdar K., Ahmed E., Imran M., Securing IoTs in distributed blockchain: Analysis, requirements and open issues, Future Generation Computer Systems, 100, pp. 325-343, (2019); (2019); Perboli G., Musso S., Rosano M., Blockchain in logistics and supply chain: A lean approach for designing real-world use cases, IEEE Access, 6, pp. 62018-62028, (2018); Qu T., Lei S.P., Wang Z.Z., Nie D.X., Chen X., Huang G.Q., IoT-based real-time production logistics synchronization system under smart cloud manufacturing, International Journal of Advanced Manufacturing Technology, 84, 1-4, pp. 147-164, (2016); Radovic D., Stevic Z., Evaluation and selection of Kpi in transport using swara method, Transport & Logistics, 18, 44, pp. 60-68, (2018); Reyna A., Martin C., Chen J., Soler E., Diaz M., On blockchain and its integration with IoT. Challenges and opportunities, Future Generation Computer Systems, 88, 2018, pp. 173-190, (2018); (2019); (2014); Schleich B., Anwer N., Mathieu L., Wartzack S., Shaping the digital twin for design and production engineering, CIRP Annals - Manufacturing Technology, 66, 1, pp. 141-144, (2017); Sharma P.K., Park J.H., Blockchain based hybrid network architecture for the smart city, Future Generation Computer Systems, 86, 2018, pp. 650-655, (2018); Wamba S.F., Boeck H., Enhancing information flow in a retail supply chain using RFID and the EPC network: A proof-of concept approach, Journal of Theoretical and Applied Electronic Commerce Research, 3, 1, pp. 92-105, (2008); Wang X., Zha X., Ni W., Liu R.P., Guo Y.J., Niu X., (2019); White M., (2020); Xiang H., Yang Z., Investment timing and capital structure with loan guarantees, Finance Research Letters, 13, pp. 179-187, (2015); Xu L.D., He W., Li S., Internet of things in industries: A survey, IEEE Transactions on Industrial Informatics, 10, 4, pp. 2233-2243, (2014); Xu X., Chen X., Jia F., Brown S., Gong Y., Xu Y., Supply chain finance: A systematic literature review and bibliometric analysis, International Journal of Production Economics, 204, September 2016, pp. 160-173, (2018); Yang B., Construction of logistics financial security risk ontology model based on risk association and machine learning, Safety Science, 123, (2020); Zacharias J., Zhang B., Local distribution and collection for environmental and social sustainability - tricycles in central Beijing, Journal of Transport Geography, 49, pp. 9-15, (2015); Zhang Y., Guo Z., Lv J., Liu Y., A framework for smart production-logistics systems based on CPS and industrial IoT, IEEE Transactions on Industrial Informatics, 14, 9, pp. 4019-4032, (2018); Zhang Y., Qu T., Ho O.K., Huang G.Q., Agent-based Smart Gateway for RFID-enabled real-time wireless manufacturing, International Journal of Production Research, 49, 5, pp. 1337-1352, (2011); Zhang Y., Ren S., Liu Y., Si S., A big data analytics architecture for cleaner manufacturing and maintenance processes of complex products, Journal of Cleaner Production, 142, pp. 626-641, (2017); Zhang Y., Zhang P., Tao F., Liu Y., Zuo Y., Consensus aware manufacturing service collaboration optimization under blockchain based Industrial Internet platform, Computers and Industrial Engineering, 135, May, pp. 1025-1035, (2019); Zhong R.Y., Peng Y., Xue F., Fang J., Zou W., Luo H., Huang G.Q., Prefabricated construction enabled by the Internet-of-Things, Automation in Construction, 76, pp. 59-70, (2017); Zhu X., Shi J., Huang S., Zhang B., Consensus-oriented cloud manufacturing based on blockchain technology: An exploratory study, Pervasive and Mobile Computing, 62, (2020); Zhu Y., Zhou L., Xie C., Wang G.J., Nguyen T.V., Forecasting SMEs’ credit risk in supply chain finance with an enhanced hybrid ensemble machine learning approach, International Journal of Production Economics, 211, January, pp. 22-33, (2019)","G.Q. Huang; HKU-ZIRI Laboratory for Physical Internet, Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong; email: gqhuang@hku.hk",null,"Elsevier Ltd",{"$nulls":5},3608352.0,null,"CINDD",null,"English","Comput Ind Eng","Article","Final",null,"Scopus","2-s2.0-85097778325"]
["Tseng S.-M.","Tseng, Shu-Mei (36024537700)",3.60245377E10,"Understanding the impact of the relationship quality on customer loyalty: the moderating effect of online service recovery",2021.0,"International Journal of Quality and Service Sciences",13.0,2.0,null,300.0,320.0,20.0,9.0,"10.1108/IJQSS-07-2020-0115","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85107509936&doi=10.1108%2fIJQSS-07-2020-0115&partnerID=40&md5=ec9cc6e216a1a585fc32162b838efdc1","Department of Hospitality Management, I-Shou University, Kaohsiung, Taiwan","Tseng S.-M., Department of Hospitality Management, I-Shou University, Kaohsiung, Taiwan","Purpose: The purpose of this study is to examine the impact of the relationship quality on customer loyalty. The moderating role played by online service recovery in this study is further discussed. Design/methodology/approach: A quantitative Web-based survey study was conducted to statistically test these relationships among relationship quality, service recovery and customer loyalty. Data collected from 183 respondents were taken for analysis through partial least squares. Findings: The findings reveal that relationship quality has significant influence on customer loyalty, whereas service recovery has moderated effect on the relationship between relationship quality and customer loyalty. Research limitations/implications: The respondents of this study were recruited from online panels; thus, a purposive sample could be a biased indication of the characteristics of the actual population. Therefore, it is suggested that future researchers enroll subjects from a statistical population that accurately represents the entire population and, in addition, that they collect more responses to increase the generalizability of the findings. Practical implications: Because failures in service delivery are inevitable, recovery of such encounters thus represents a significant challenge for service firms. Hence, this study proposes concrete suggestions for firms to manage and operate e-commerce websites, as well as to enhance relationship quality and customer loyalty. Originality/value: Service failures have been the bane of e-commerce, compelling customers to either abandon transactions entirely or switch to a physical competitor. Many firms have realized the importance of maintaining strong relationships with customers to enhance their loyalty. However, previous literature has a few studies conducted on the relationships among service recovery, relationship quality and customer loyalty in the e-commerce context. Therefore, it is meaningful to identify these relationships. © 2021, Emerald Publishing Limited.","Customer loyalty; Relationship quality; Service failures; Service recovery",{"$nulls":5},"Ministry of Science and Technology, Taiwan, MOST, (106-2410-H-214-002)","This research is supported by Ministry of Science and Technology, Taiwan, R.O.C. under Grant no. MOST 106-2410-H-214-002-.",{"$cut":{"chars":22479,"head":"Abdul-Rahman M., Kamarulzaman Y., The influence of relationship quality and switching costs on customer loyalty in the Malaysian hotel industry, Procedia - Social and Behavioral Sciences, 62, pp. 1023-1027, (2012); Alejandro T.B., Souza D.V., Boles J.S., Ribeiro A.H.P., Monteiro P.R.R., The outcome of company and account manager relationship quality on loyalty, relationship value and performance, Industrial Marketing Management, 40, 1, pp. 36-43, (2011); Ali Abumalloh R., Ibrahim O., Nilashi M., Loyalty of young female Arabic customers towards recommendation agents: a new model for B2c e-commerce, Technology in Society, 61, (2020); Ambrose M., Hess R.L., Ganesar S., The relationship between justice and attitudes: an examination of justice effects on event and system-related attitudes, Organizational Behavior and Human Decision Processes, 103, 1, pp. 21-36, (2007); Bacile T.J., Wolter J.S., Allen A.M., Xu P., The effects of online incivility and consumer-to-consumer interactional justice on complainants, observers, and service providers during social media service recovery, Journal of Interactive Marketing, 44, pp. 60-81, (2018); Baliga A.J., Chawla V., Sunder M.V., Ganesh L.S., Sivakumaran B., Service failure and recovery in B2B markets – a morphological analysis, Journal of Business Research, (2020); Barroso C., Carrion G.C., Roldan J.L., Applying maximum likelihood and pls on different sample sizes: studies on servqual model and employee behavior model, Handbook of Partial Least Squares, (2010); Bejou D., Palmer A., Service failure and loyalty: an exploratory empirical study of airline customers, Journal of Services Marketing, 12, 1, pp. 7-22, (1998); Berry L.L., Relationship marketing of services: growing interest, emerging perspectives, Journal of the Academy of Marketing Science, 23, 4, pp. 236-245, (1995); Bilgihan A., Bujisic M., The effect of website features in online relationship marketing: a case of online hotel booking, Electronic Commerce Research and Applications, 14, 4, pp. 222-232, (2015); Bitner M.J., Brown S.W., Meuter M.L., Technology infusion in service encounters, Journal of the Academy of Marketing Science, 28, 1, pp. 138-149, (2000); Bougoure U.S., Russell-Bennett R., Fazal-E-Hasan S., Mortimer G., The impact of service failure on brand credibility, Journal of Retailing and Consumer Services, 31, pp. 62-71, (2016); Bouranta N., Psomas E., Vouzas F., The effect of service recovery on customer loyalty: the role of perceived food safety, International Journal of Quality and Service Sciences, 11, 1, pp. 69-86, (2019); Bowen J.T., Shoemaker S., Loyalty: a strategic commitment, Cornell Hotel and Restaurant Administration Quarterly, 44, 5-6, pp. 31-46, (2003); Boyer K.K., Hallowell R., Roth A.V., E-services: operating strategy – a case study and a method for analyzing operational benefits, Journal of Operations Management, 20, 2, pp. 175-188, (2002); Buttle F., Burton J., Does service failure influence customer loyalty?, Journal of Consumer Behaviour, 1, 3, (2002); Cater T., Cater B., Product and relationship quality influence on customer commitment and loyalty in B2b manufacturing relationships, Industrial Marketing Management, 39, 8, pp. 1321-1333, (2010); Chang C.C., Choice, perceived control, and customer satisfaction: the psychology of online service recovery, Cyberpsychology and Behavior, 11, 3, pp. 321-328, (2008); Chang H.H., Lai M.K., Hsu C.H., Recovery of online service: perceived justice and transaction frequency, Computers in Human Behavior, 28, 6, pp. 2199-2208, (2012); Cheng B.L., Gan C.C., Imrie B.C., Mansori S., Service recovery, customer satisfaction and customer loyalty: evidence from Malaysia’s hotel industry, International Journal of Quality and Service Sciences, 11, 2, pp. 187-203, (2019); Cheng X., Gu Y., Shen J., An integrated view of particularized trust in social commerce: an empirical investigation, International Journal of Information Management, 45, pp. 1-12, (2019); Cheng F.F., Wu C.S., Chen Y.C., Creating customer loyalty in online brand communities, Computers in Human Behavi"}},"S.-M. Tseng; Department of Hospitality Management, I-Shou University, Kaohsiung, Taiwan; email: y97576@isu.edu.tw",null,"Emerald Group Holdings Ltd.",{"$nulls":5},"1756669X",null,null,null,"English","Int. J. Qual. Serv. Sci.","Article","Final",null,"Scopus","2-s2.0-85107509936"]
["Gee I.M.; Heard B.R.; Webber M.E.; Miller S.A.","Gee, Isabella M. (57209851467); Heard, Brent R. (57189870365); Webber, Michael E. (7103355833); Miller, Shelie A. (57201191523)","57209851467; 57189870365; 7103355833; 57201191523","The Future of Food: Environmental Lessons from E-Commerce",2020.0,"Environmental Science and Technology",54.0,23.0,null,14776.0,14784.0,8.0,17.0,"10.1021/acs.est.0c01731","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85096624963&doi=10.1021%2facs.est.0c01731&partnerID=40&md5=0d9d05424feafce3e87e294df86c384b","Walker Department of Mechanical Engineering, University of Texas at Austin, Austin, 78712, TX, United States; School for Environment and Sustainability, University of Michigan, Ann Arbor, 48109, MI, United States","Gee I.M., Walker Department of Mechanical Engineering, University of Texas at Austin, Austin, 78712, TX, United States; Heard B.R., School for Environment and Sustainability, University of Michigan, Ann Arbor, 48109, MI, United States; Webber M.E., Walker Department of Mechanical Engineering, University of Texas at Austin, Austin, 78712, TX, United States; Miller S.A., School for Environment and Sustainability, University of Michigan, Ann Arbor, 48109, MI, United States","Our food system is experiencing dramatic changes as the expansion of e-commerce, introduction of new products, and innovations in supply chain structures all pose to transform how we buy, sell, and distribute food. However, the environmental impacts of these transformations remain unclear. This feature reviews existing literature on environmental implications of e-commerce, discusses relevant trade-offs, and identifies pressing gaps in research. Some trade-offs discussed are those between centralized and decentralized delivery service types, those unique to a rural landscape, and those within the interplay of transportation and consumer behavior. The impacts of fulfillment centers, of refrigerated logistics, of e-commerce on consumer shopping and food waste habits, and of e-commerce services in rural regions are identified as pressing knowledge gaps.  © ",null,"Commerce; Food; Food Supply; Refuse Disposal; Transportation; Economic and social effects; Electronic commerce; Food waste; Supply chains; Consumer shopping; Delivery service; E-commerce services; Environmental implications; Knowledge gaps; Rural landscapes; Rural regions; Supply chain structures; electronic commerce; environmental impact; food availability; food waste; innovation; supply chain management; article; consumer attitude; environmental impact; food waste; habit; human; shopping; catering service; commercial phenomena; food; traffic and transport; waste disposal; Consumer behavior",{"$nulls":4},"National Science Foundation, NSF, (1804287, CBET 1804287)","We acknowledge the University of Michigan Rackham Graduate School and the Cynthia and George Mitchell foundation. This work was partially supported by the National Science Foundation Environmental Sustainability program under Grant No. CBET 1804287. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. We also thank the reviewers of this feature for their thoughtful feedback. The authors have no conflicts of interest to declare.","Springmann M., Clark M., Mason-D'Croz D., Wiebe K., Bodirsky B.L., Lassaletta L., De Vries W., Vermeulen S.J., Herrero M., Carlson K.M., Jonell M., Troell M., Declerck F., Gordon L.J., Zurayk R., Scarborough P., Rayner M., Loken B., Fanzo J., Godfray H.C.J., Tilman D., Rockstrom J., Willett W., Options for Keeping the Food System within Environmental Limits, Nature, 562, 7728, pp. 519-525, (2018); Poore J., Nemecek T., Reducing Food's Environmental Impacts through Producers and Consumers, Science (Washington, DC, U. 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In towards Life Cycle Sustainability Management, Towards Life Cycle Sustainability Management, pp. 359-370, (2011); State of Grocery, (2017); Jilcott Pitts S.B., Wen Ng S., Blitstein J.L., Gustafson A., Niculescu M., Online Grocery Shopping: Promise and Pitfalls for Healthier Food and Beverage Purchases, Public Health Nutr., 21, pp. 3360-3376, (2018); Heard B.R., Taiebat M., Xu M., Miller S.A., Sustainability Implications of Connected and Autonomous Vehicles for the Food Supply Chain, Resour. Conserv. Recycl., 128, pp. 22-24, (2018); Stolaroff J.K., Samaras C., O'Neill E.R., Lubers A., Mitchell A.S., Ceperley D., Energy Use and Life Cycle Greenhouse Gas Emissions of Drones for Commercial Package Delivery, Nat. Commun., 9, (2018); HelloFresh Sustainability Report 2019, (2019); Lee S.Y., Lee S.J., Choi D.S., Hur S.J., Current Topics in Active and Intelligent Food Packaging for Preservation of Fresh Foods, J. Sci. Food Agric., 95, 14, pp. 2799-2810, (2015)","I.M. Gee; Walker Department of Mechanical Engineering, University of Texas at Austin, Austin, 78712, United States; email: Isabella.gee@utexas.edu",null,"American Chemical Society",{"$nulls":5},"0013936X",null,"ESTHA",3.3186012E7,"English","Environ. Sci. Technol.","Article","Final",null,"Scopus","2-s2.0-85096624963"]
["Zhang H.; Sun Y.; Zhao M.; Chow T.W.S.; Wu Q.M.J.","Zhang, Haijun (57188929355); Sun, Yanfang (57203638915); Zhao, Mingbo (55143406500); Chow, Tommy W. S. (55505516700); Wu, Q. M. Jonathan (55613291700)","57188929355; 57203638915; 55143406500; 55505516700; 55613291700","Bridging User Interest to Item Content for Recommender Systems: An Optimization Model",2020.0,"IEEE Transactions on Cybernetics",50.0,10.0,8663339.0,4268.0,4280.0,12.0,33.0,"10.1109/TCYB.2019.2900159","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85091543053&doi=10.1109%2fTCYB.2019.2900159&partnerID=40&md5=c43b8af6463228ea17c40af55f996aa3","Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen, China; College of Information Sciences and Technology, Donghua University, Shanghai, China; Department of Electronic Engineering, City University of Hong Kong, Hong Kong, Hong Kong; Department of Electrical and Computer Engineering, University of Windsor, Windsor, ON, Canada","Zhang H., Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen, China; Sun Y., Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen, China; Zhao M., College of Information Sciences and Technology, Donghua University, Shanghai, China; Chow T.W.S., Department of Electronic Engineering, City University of Hong Kong, Hong Kong, Hong Kong; Wu Q.M.J., Department of Electrical and Computer Engineering, University of Windsor, Windsor, ON, Canada","Recommender systems are currently utilized widely in e-commerce for product recommendations and within content delivery platforms. Previous studies usually use independent features to represent item content. As a result, the relationship hidden among the content features is overlooked. In fact, the reason that an item attracts a user may be attributed to only a few set of features. In addition, these features are often semantically coupled. In this paper, we present an optimization model for extracting the relationship hidden in content features by considering user preferences. The learned feature relationship matrix is then applied to address the cold-start recommendations and content-based recommendations. It could also easily be employed for the visualization of feature relation graphs. Our proposed method was examined on three public datasets: 1) hetrec-movielens-2k-v2; 2) book-crossing; and 3) Netflix. The experimental results demonstrated the effectiveness of our method in comparison to the state-of-the-art recommendation methods.  © 2013 IEEE.","Content based; optimization; recommendation; relation learning; user preference","Optimization; Recommender systems; Cold-start Recommendations; Content delivery; Content-based recommendation; Optimization modeling; Product recommendation; Recommendation methods; Relationship matrix; State of the art; article; cold stress; comparative effectiveness; intermethod comparison; Electronic commerce",{"$nulls":4},"Shenzhen Science and Technology Program, (JCYJ20170413105929681, JCYJ20170811161545863); National Natural Science Foundation of China, NSFC, (61572156, 61832004); National Key Research and Development Program of China, NKRDPC, (2018YFB1003800, 2018YFB1003805)","Manuscript received August 22, 2018; revised November 3, 2018 and December 27, 2018; accepted February 11, 2019. Date of publication March 8, 2019; date of current version September 23, 2020. This work was supported in part by the National Key Research and Development Program of China under Grant 2018YFB1003800 and Grant 2018YFB1003805, in part by the National Natural Science Foundation of China under Grant 61572156 and Grant 61832004, and in part by the Shenzhen Science and Technology Program under Grant JCYJ20170413105929681 and Grant JCYJ20170811161545863. This paper was recommended by Associate Editor S. Ozawa. (Corresponding author: Mingbo Zhao.) H. Zhang and Y. Sun are with the Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen 518055, China (e-mail: hjzhang@hit.edu.cn; ahongsun1993@gmail.com).","Van Setten M., Supporting People in Finding Information: Hybrid Recommender Systems and Goal-based Structuring, (2005); Rich E., User modeling via stereotypes, Cogn. Sci. Multidiscipl. 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Cybern., 47, 12, pp. 4049-4061, (2017); Wu Z., HPSD: A hybrid PU-learning-based spammer detection model for product reviews, IEEE Trans. Cybern.",null,null,"Institute of Electrical and Electronics Engineers Inc.",{"$nulls":5},2.1682267E7,null,null,3.0869636E7,"English","IEEE Trans. Cybern.","Article","Final",null,"Scopus","2-s2.0-85091543053"]
["Tsakalidis A.; Krause J.; Julea A.; Peduzzi E.; Pisoni E.; Thiel C.","Tsakalidis, Anastasios (56237225500); Krause, Jette (24483341000); Julea, Andreea (22234501500); Peduzzi, Emanuela (55341264700); Pisoni, Enrico (15926005400); Thiel, Christian (13605737400)","56237225500; 24483341000; 22234501500; 55341264700; 15926005400; 13605737400","Electric light commercial vehicles: Are they the sleeping giant of electromobility?",2020.0,"Transportation Research Part D: Transport and Environment",86.0,null,102421.0,null,null,null,46.0,"10.1016/j.trd.2020.102421","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85087587869&doi=10.1016%2fj.trd.2020.102421&partnerID=40&md5=8afcfff7929cfd8785b6d149e8d61c5a","European Commission, Joint Research Centre (JRC), Ispra, Italy","Tsakalidis A., European Commission, Joint Research Centre (JRC), Ispra, Italy; Krause J., European Commission, Joint Research Centre (JRC), Ispra, Italy; Julea A., European Commission, Joint Research Centre (JRC), Ispra, Italy; Peduzzi E., European Commission, Joint Research Centre (JRC), Ispra, Italy; Pisoni E., European Commission, Joint Research Centre (JRC), Ispra, Italy; Thiel C., European Commission, Joint Research Centre (JRC), Ispra, Italy","Transport emissions need to be drastically decreased in order to put Europe on a path towards a long-term climate neutrality. Commercial transport, and especially last mile delivery is expected to grow because of the rise of e-commerce. In this frame, electric light commercial vehicles (eLCVs) can be a promising low-emission solution. Literature holistically analysing the potential of eLCVs as well as related support policies is sparse. This paper attempts to close this research gap. To this aim, the total cost of ownership (TCO) comparisons for eLCVs and benchmark vehicles are performed and support measures that target the improvement of the eLCV TCO are analysed. Various eLCV deployment scenarios until 2030 are explored and their impact on carbon dioxide (CO2) and other pollutant emissions as well as pollutant concentrations are calculated. It is found that while in several European Union (EU) countries eLCVs are already cost competitive, because of fiscal support, some remaining market barriers need to be overcome to pave the way to mass market deployment of eLCVs. High penetration of eLCVs alone can lead to a reduction of total transport CO2 emissions by more than 3% by 2030. For pollutant emissions, such as nitrogen oxide (NOx) and particulate matter (PM), the reduction would be equal or even higher. In the case of PM, this can translate to reductions in concentrations by nearly 2% in several urban areas by 2030. Carefully designed support policies could help to ensure that the potential of eLCVs as a low-emission alternative is fully leveraged in the EU. © 2020 The Authors","eLCV; Electric vehicles; Emissions mitigation; Incentives; Last mile delivery; Total cost of ownership","Europe; Automobiles; Carbon dioxide; Commerce; Electric lighting; Light weight vehicles; Nitrogen oxides; Pollution; Commercial transport; Deployment scenarios; European Union countries; Light commercial vehicles; Particulate Matter; Pollutant concentration; Total cost of ownership; Transport emissions; air quality; atmospheric pollution; benchmarking; carbon dioxide; carbon emission; concentration (composition); electric vehicle; European Union; numerical model; traffic emission; transportation system; Commercial vehicles",{"$nulls":4},"Barbara Realini; European Commission, EC","The views expressed here are purely those of the authors and may not, under any circumstances, be regarded as an official position of the European Commission. The authors would like to thank Barbara Realini for proofreading the manuscript and for her linguistic improvements to the manuscript.","ACEA, ACEA Tax Guide 2019, (2019); (2014); Camilleri P., Dablanc L., An assessment of present and future competitiveness of electric commercial vans, J. Earth Sci. Geotech. Eng., 7, pp. 337-364, (2017); Christensen L., Klauenberg J., Kveiborg O., Rudolph C., Suitability of commercial transport for a shift to electric mobility with Denmark and Germany as use cases, Res. Transp. Econ., 64, pp. 48-60, (2017); Clappier A., Pisoni E., Thunis P., A new approach to design source–receptor relationships for air quality modelling, Environ. Model. Softw., 74, pp. 66-74, (2015); Dablanc L., Morganti E., Arvidsson N., Woxenius J., Browne M., Saidi N., The rise of on-demand ‘Instant Deliveries’ in European cities, Supply Chain Forum An Int. 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Procedia, 12, pp. 157-169, (2016); Quak H., Nesterova N., Van Rooijen T., Dong Y., Zero emission city logistics: current practices in freight electromobility and feasibility in the near future, Transp. Res. Procedia, 14, pp. 1506-1515, (2016); Sierzchula W., Factors influencing fleet manager adoption of electric vehicles, Transp. Res. Part D Transp. Environ., 31, pp. 126-134, (2014); Taefi T.T., Kreutzfeldt J., Held T., Fink A., Supporting the adoption of electric vehicles in urban road freight transport – a multi-criteria analysis of policy measures in Germany, Transp. Res. Part A Policy Pract., 91, pp. 61-79, (2016); (2018); Thiel C., Drossinos Y., Krause J., Harrison G., Gkatzoflias D., Donati A.V., Modelling electro-mobility: an integrated modelling platform for assessing European policies, Transp. Res. Procedia, 14, pp. 2544-2553, (2016); Thiel C., Julea A., Acosta Iborra B., De Miguel Echevarria N., Peduzzi E., Pisoni E., Gomez Vilchez J.J., Krause J., Assessing the impacts of electric vehicle recharging infrastructure deployment efforts in the European Union, Energies, 12, (2019); Thiel C., Nijs W., Simoes S., Schmidt J., van Zyl A., Schmid E., The impact of the EU car CO2 regulation on the energy system and the role of electro-mobility to achieve transport decarbonisation, Energy Policy, 96, pp. 153-166, (2016); Thiel C., Tsakalidis A., Jager-Waldau A., Will electric vehicles be killed (again) or are they the next mobility killer app?, Energies, 13, (2020); Thunis P., Degraeuwe B., Pisoni E., Ferrari F., Clappier A., On the design and assessment of regional air quality plans: the SHERPA approach, J. Environ. Manage., 183, pp. 952-958, (2016); Tsakalidis A., Julea A., Thiel C., The role of infrastructure for electric passenger car uptake in Europe, Energies, 12, (2019); Tsakalidis A., Thiel C., (2018); Tsakalidis A., (2018); (2017); Wolff S., Madlener R., Driven by change: Commercial drivers’ acceptance and efficiency perceptions of light-duty electric vehicle usage in Germany, Transp. Res. Part C Emerg. Technol., 105, pp. 262-282, (2019)","A. Tsakalidis; European Commission, Joint Research Centre (JRC), Ispra, Italy; email: anastasios.tsakalidis@ec.europa.eu",null,"Elsevier Ltd",{"$nulls":5},1.3619209E7,null,"TRDTF",null,"English","Transp. Res. Part D Transp. Environ.","Article","Final","All Open Access; Green Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85087587869"]
["Zhou C.; Stephen A.; Cao X.; Wang S.","Zhou, Chenhao (56809928400); Stephen, Aloisius (57201456092); Cao, Xinhu (57201029577); Wang, Shuhong (57214888978)","56809928400; 57201456092; 57201029577; 57214888978","A data-driven business intelligence system for large-scale semi-automated logistics facilities",2021.0,"International Journal of Production Research",59.0,8.0,null,2250.0,2268.0,18.0,7.0,"10.1080/00207543.2020.1727048","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85079432028&doi=10.1080%2f00207543.2020.1727048&partnerID=40&md5=5bd67653e41af9ee9d3191e47218d3da","Department of Industrial Systems Engineering and Management, National University of Singapore, Singapore, Singapore","Zhou C., Department of Industrial Systems Engineering and Management, National University of Singapore, Singapore, Singapore; Stephen A., Department of Industrial Systems Engineering and Management, National University of Singapore, Singapore, Singapore; Cao X., Department of Industrial Systems Engineering and Management, National University of Singapore, Singapore, Singapore; Wang S., Department of Industrial Systems Engineering and Management, National University of Singapore, Singapore, Singapore","With the proliferation of e-commerce, the regional hub of a large-scale logistics company is required to sort and load a large number of packages into different delivery vehicles by dawn and deliver them to customers by noon on a daily basis. The efficiency of the sorting operation is thus a competitive advantage which directly impacts the company's service level. In this study, a data-driven business intelligence system for the semi-automated sorting facility is proposed for real-world implementation. To determine the cargo handling sequence, an information-based approach with a multi-criteria index function is developed. Then a simulation-based optimisation framework, which integrates a multi-objective search algorithm with a simulation model, is employed to fine-tune the parameters of the index function to perform optimally. The results of the numerical experiment show that the proposed technique is able to reduce 20% of the sorting operation duration, which equals a reduction of about 3600 man-hours per year. The study is a good example of applying emerging technologies in the logistics industry. © 2020 Informa UK Limited, trading as Taylor & Francis Group.","data-driven business intelligence system; heuristics; information-based approach; logistics; semi-automated sorting facility; simulation optimisation","Competition; Decision support systems; Information analysis; Logistics; Optimization; Sorting; Automated sorting; Business intelligence systems; heuristics; information-based approach; Simulation optimisation; Automation",{"$nulls":6},"Bahrami B., Aghezzaf E.-H., Limere V., Enhancing the Order Picking Process through a New Storage Assignment Strategy in Forward-Reserve Area, International Journal of Production Research, 57, 21, pp. 6593-6614, (2019); Boysen N., Briskorn D., Emde S., Parts-to-Picker Based Order Processing in a Rack-Moving Mobile Robots Environment, European Journal of Operational Research, 262, 2, pp. 550-562, (2017); Boysen N., Briskorn D., Fedtke S., Schmickerath M., Automated Sortation Conveyors: A Survey from an Operational Research Perspective, European Journal of Operational Research, 276, 3, pp. 796-815, (2019); Calzavara M., Glock C.H., Grosse E.H., Sgarbossa F., An Integrated Storage Assignment Method for Manual Order Picking Warehouses Considering Cost, Workload and Posture, International Journal of Production Research, 57, 8, pp. 2392-2408, (2019); Choy K.L., Chow H.K.H., Poon T.C., Ho G.T.S., Cross-Dock Job Assignment Problem in Space-Constrained Industrial Logistics Distribution Hubs with a Single Docking Zone, International Journal of Production Research, 50, 9, pp. 2439-2450, (2012); Crainic T.G., Perboli G., Rosano M., Simulation of Intermodal Freight Transportation Systems: A Taxonomy, European Journal of Operational Research, 270, 2, pp. 401-418, (2018); De Koster R., Le-Duc T., Roodbergen K.J., Design and Control of Warehouse Order Picking: A Literature Review, European Journal of Operational Research, 182, 2, pp. 481-501, (2007); (2019); Ding H., Benyoucef L., Xie X., Stochastic Multi-Objective Production-Distribution Network Design Using Simulation-Based Optimization, International Journal of Production Research, 47, 2, pp. 479-505, (2009); 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Hong S., Zhang D., Lau H.C., Zeng X., Si Y.-W., A Hybrid Heuristic Algorithm for the 2D Variable-Sized Bin Packing Problem, European Journal of Operational Research, 238, 1, pp. 95-103, (2014); Kang J., Park S., Algorithms for the Variable Sized bin Packing Problem, European Journal of Operational Research, 147, 2, pp. 365-372, (2003); Kleijnen J.P.C., Simulation and Optimization in Production Planning: A Case Study, Decision Support Systems, 9, 3, pp. 269-280, (1993); Layeb S.B., Jaoua A., Jbira A., Makhlouf Y., A Simulation-Optimization Approach for Scheduling in Stochastic Freight Transportation, Computers & Industrial Engineering, 126, pp. 99-110, (2018); Lee S.-D., Kuo Y.-C., Exact and Inexact Solution Procedures for the Order Picking in an Automated Carousal Conveyor, International Journal of Production Research, 46, 16, pp. 4619-4636, (2008); Li H., Lee L.H., Chew E.P., Lendermann P., MO-COMPASS: A Fast Convergent Search Algorithm for Multi-Objective Discrete Optimization via Simulation, IIE Transactions, 47, 11, pp. 1153-1169, (2015); 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Pasupathy R., Ghosh S., Simulation Optimization: A Concise Overview and Implementation Guide, Theory Driven by Influential Applications, pp. 122-150, (2013); Pedrielli G., Alfieri A., Matta A., Integrated Simulation–Optimisation of Pull Control Systems, International Journal of Production Research, 53, 14, pp. 4317-4336, (2015); Revillot-Narvaez D., Perez-Galarce F., Alvarez-Miranda E., Optimising the Storage Assignment and Order-Picking for the Compact Drive-in Storage System, International Journal of Production Research, (2019); Roodbergen K.J., Vis I.F.A., A Survey of Literature on Automated Storage and Retrieval Systems, European Journal of Operational Research, 194, 2, pp. 343-362, (2009); Tako A.A., Robinson S., The Application of Discrete Event Simulation and System Dynamics in the Logistics and Supply Chain Context, Decision Support Systems, 52, 4, pp. 802-815, (2012); (2018); Wang H.-M., Solving Single Batch-Processing Machine Problems Using an Iterated Heuristic, International Journal of Production Research, 49, 14, pp. 4245-4261, (2011); Wei L., Oon W.-C., Zhu W., Lim A., A Goal-Driven Approach to the 2D bin Packing and Variable-Sized bin Packing Problems, European Journal of Operational Research, 224, 1, pp. 110-121, (2013); Winkelhaus S., Grosse E.H., Logistics 4.0: A Systematic Review towards a New Logistics System, International Journal of Production Research, 58, 1, pp. 18-43, (2020); Xu J., Huang E., Chen C.-H., Lee L.H., Simulation Optimization: A Review and Exploration in the New Era of Cloud Computing and Big Data, Asia-Pacific Journal of Operational Research, 32, 3, (2015); Yu Y., De Koster R.B.M., Sequencing Heuristics for Storing and Retrieving Unit Loads in 3D Compact Automated Warehousing Systems, IIE Transactions, 44, 2, pp. 69-87, (2012); Yu W., Egbelu P.J., Scheduling of Inbound and Outbound Trucks in Cross Docking Systems with Temporary Storage, European Journal of Operational Research, 184, 1, pp. 377-396, (2008); Zhou C., Chew E.P., Lee L.H., Information-Based Allocation Strategy for Grid-Based Transshipment Automated Container Terminal, Transportation Science, 52, 3, pp. 707-721, (2018); Zhou C., Li H., Liu W., Stephen A., Lee L.H., Chew E.P., (2018); Zhou C., Stephen A., Li H., Lee L.H., Chew E.P., (2017)","A. Stephen; Department of Industrial Systems Engineering and Management, National University of Singapore, Singapore, Singapore; email: aloisius.s@u.nus.edu",null,"Taylor and Francis Ltd.",{"$nulls":5},207543.0,null,"IJPRB",null,"English","Int J Prod Res","Article","Final",null,"Scopus","2-s2.0-85079432028"]
["Ha N.T.; Nguyen T.L.H.; Pham T.V.; Nguyen T.H.T.","Ha, Ngoc Thang (57209173446); Nguyen, Thi Lien Huong (57209175415); Pham, Thanh Van (57222314362); Nguyen, Thi Hong Tham (57225934562)","57209173446; 57209175415; 57222314362; 57225934562","Factors Influencing Online Shopping Intention: An Empirical Study in Vietnam",2021.0,"Journal of Asian Finance, Economics and Business",8.0,3.0,null,1257.0,1266.0,9.0,18.0,"10.13106/jafeb.2021.vol8.no3.1257","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85102312621&doi=10.13106%2fjafeb.2021.vol8.no3.1257&partnerID=40&md5=eabb49465ba844be166e4c919e6f3849","National Economics University, Viet Nam; National Economics University, Hanoi, Viet Nam","Ha N.T., National Economics University, Viet Nam; Nguyen T.L.H., National Economics University, Hanoi, Viet Nam; Pham T.V., National Economics University, Hanoi, Viet Nam; Nguyen T.H.T., National Economics University, Hanoi, Viet Nam","The study examines factors that influence shopping intention of online consumers in Vietnam. Studied factors include consumers’ attitude, subjective norms, perception of behavioral control, perception of usefulness, perceived risks and trust. The expansion of Theory of Planned Behavior (TPB) and Technology Acceptance Model (TAM) are used as basic theories. We have surveyed people who have experiences on online shopping. There are 836 selected questionnaires that are qualified for data processing. The collected data are analyzed through a process which starts from scale reliability test to exploratory factor analysis (EFA), correlation analysis and regression analysis. The results show that shopping intention of online consumers are positively affected by their attitude, subjective norms, perception of behavioral control, perception of usefulness and trust. In contrast, online shopping intention is negatively affected by the perceived risks that online shopping could bring. Among those factors, the perception of risk is shown to have the strongest influence to online shopping intention. The findings of this study suggest that managers and retailers can apply cash-on-delivery method and design their website with user-friendly interface to enhance online shopping intention of consumers. The Government is also recommended to fulfill the law system to reduce customers’ perception of financial risks. © The Author(s) This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.","Attitude; Behavioral Control; Ease of Use; Online Shopping Intention; Subjective Norm",{"$nulls":7},"Abbad M., Abbad R., Saleh M., Limitations of e-commerce in developing countries: Jordan case, Education, Business and Society: Contemporary Middle Eastern Issues, 4, 4, pp. 280-291, (2011); Ajzen I., The theory of planned behavior, Organizational Behavior and Human Decision Processes, 50, 2, pp. 179-211, (1991); Akbar W., Hassan S., Khurshid S., Niaz M., Rizwan M., Antecedents Affecting Customer’s Purchase Intentions towards Green Products, Journal of Sociological Research, 5, 1, pp. 273-289, (2014); Aziz N. 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D., Miniard P. W., Engel J. F., Consumer behavior, (2001); Bonera M., The propensity of e-commerce usage: the influencing variables, Management Research Review, 34, 7, pp. 821-837, (2011); Chen Y. T., Chou T. Y., Exploring the continuance intentions of consumers for B2C online shopping: Perspectives of fairness and trust, Online Information Review, 36, 1, pp. 104-125, (2012); Choi J., Park J., Multichannel retailing in Korea: Effects of shopping orientations and information seeking patterns on channel choice behavior, International Journal of Retail & Distribution Management, 34, 8, pp. 577-596, (2006); Vietnam Net Citizens Report 2012, (2012); Corbitt B. J., Thanasankit T., Yi H., Trust and e-commerce: a study of consumer perceptions, Electronic Commerce Research and Applications, 2, 3, pp. 203-215, (2003); Davis F. D., Perceived usefulness, perceived ease of use, and user acceptance of information technology, MIS quarterly, pp. 319-340, (1989); Davis F. D., Bagozzi R. P., Warshaw P. 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W., Trust and TAM in online shopping: an integrated model, MIS Quarterly, 27, 1, pp. 51-90, (2003); Gefen D., Karahanna E., Straub D. W., Inexperience and experience with online stores: the importance of TAM and trust, Engineering Management, IEEE Transactions on, 50, 3, pp. 307-321, (2003); George J. F., The theory of planned behavior and Internet purchasing, Internet Research, 14, 3, pp. 198-212, (2004); Giao H. N. K, Customer satisfaction at Tiki. vn E-commerce Platform, The Journal of Asian Finance, Economics and Business, 7, 4, pp. 173-183, (2020); Ha N. T., The impact of perceived risk on consumers’ online shopping intention: An integration of TAM and TPB, Management Science Letters, 10, 9, pp. 2029-2036, (2020); Ha N. T., Nguyen T. D., The factors drive customers to shop online in Vietnam, Journal of Economics and Development, pp. 91-96, (2013); Ha N. T., Nguyen T. D., Factors that prevent customers from online shopping in Vietnam, Journal of Economics and Development, 203, pp. 61-69, (2014); Ha N. T., Nguyen T. D., The influence of perceived risk, reputation and reference group on Vietnamese consumers’ trust in online shopping, Journal of Economics and Development, 217, pp. 16-23, (2015); Ha N. T., Nguyen T. L. H., Factors influencing Vietnamese consumers’ online shopping intention: An integration of TAM and TPB with risk and trust, International conference: The economy of Vietnam in the integration period: opportunities and challenges, pp. 737-749, (2016); Ha N. T., Nguyen T. L. H., Nguyen T. P. L., Nguyen T. D., The effect of trust on consumers’ online purchase intention: An integration of TAM and TPB, Management Science Letters, 9, 9, pp. 1451-1460, (2019); Hair J. F., Black W. C., Babin B. J., Anderson R. E., Tatham R. L., Multivariate data analysis, (2010); Hanafizadeh P., Behboudi M., Koshksaray A. A., Tabar M. J. 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M., Loyd D., Internet shopping and buying behavior of college students, Services Marketing Quarterly, 27, 2, pp. 123-138, (2005); Lim Y. J., Osman A., Salahuddin S. N., Romle A. R., Abdullah S., Factors influencing online shopping behavior: the mediating role of purchase intention, Procedia Economics and Finance, 35, 5, pp. 401-410, (2016); Lin H. F., Predicting consumer intentions to shop online: An empirical test of competing theories, Electronic Commerce Research and Applications, 6, 4, pp. 433-442, (2007); Lohse G. L., Bellman S., Johnson E. J., Consumer buying behavior on the Internet: Findings from panel data, Journal of Interactive Marketing, 14, 1, pp. 15-29, (2000); Malaquias R. F., Hwang Y., An empirical study on trust in mobile banking: A developing country perspective, Computers in Human Behavior, 54, pp. 453-461, (2016); Mayer R. C., Davis J. H., Schoorman F. D., An integrative model of organizational trust, Academy of Management Review, 20, 3, pp. 709-734, (1995); McKnight D. H., Choudhury V., Kacmar C., Developing and validating trust measures for e-commerce: an integrative typology, Information Systems Research, 13, 3, pp. 334-359, (2002); Vietnamese e-Commerce Report 2012, (2012); Vietnamese e-Commerce Report 2015, (2015); Morganosky M. A., Cude B. J., Consumer response to online grocery shopping, International Journal of Retail & Distribution Management, 28, 1, pp. 17-26, (2000); Ozen H., Engizek N., Shopping online without thinking: being emotional or rational?, Asia Pacific Journal of Marketing and Logistics, 26, 1, pp. 78-93, (2014); Pavlou P. A., Consumer acceptance of electronic commerce: integrating trust and risk with the technology acceptance model, International Journal of Electronic Commerce, 7, 3, pp. 69-103, (2003); Pavlou P. 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B, Perceived Risk factors affecting consumers’ online shopping behavior, The Journal of Asian Finance, Economics and Business, 6, 4, pp. 249-260, (2019); Tran V. D., The relationship among product risk, perceived satisfaction and purchase intentions for online shopping, The Journal of Asian Finance, Economics and Business, 7, 6, pp. 221-231, (2020); Tran V. H., E-Commerce, (2008); Verhagen T., Meents S., Tan Y. H., Perceived risk and trust associated with purchasing at electronic marketplaces, European Journal of Information Systems, 15, 6, pp. 542-555, (2006); Walsh J., Godfrey S., The Internet: a new era in customer service, European Management Journal, 18, 1, pp. 85-92, (2000); Winch G., Joyce P., Exploring the dynamics of building, and losing, consumer trust in B2C eBusiness, International Journal of Retail & Distribution Management, 34, 7, pp. 541-555, (2006); Wu L., Cai Y., Liu D., Online shopping among Chinese customers: an exploratory investigation of demographics and value orientation, International Journal of Customer Studies, 35, pp. 458-469, (2011); Y Monsuwe T. P., Dellaert B. G., De Ruyter K., What drives consumers to shop online? A literature review, International Journal of Service Industry Management, 15, 1, pp. 102-121, (2004); Yoh E., Damhorst M. L., Sapp S., Laczniak R., Consumer adoption of the internet: the case of apparel shopping, Psychology & Marketing, 20, 12, pp. 1095-1118, (2003)","N.T. Ha; National Economics University, Viet Nam; email: hangocthang@yahoo.com",null,"Korea Distribution Science Association (KODISA)",{"$nulls":5},2.2884637E7,null,null,null,"English","J. Asian Financ. Econ. Bus.","Article","Final",null,"Scopus","2-s2.0-85102312621"]
["Li M.; Shao S.; Ye Q.; Xu G.; Huang G.Q.","Li, Ming (57196402801); Shao, Saijun (56414109100); Ye, Qiwen (57202189702); Xu, Gangyan (55361785800); Huang, George Q. (7403425048)","57196402801; 56414109100; 57202189702; 55361785800; 7403425048","Blockchain-enabled logistics finance execution platform for capital-constrained E-commerce retail",2020.0,"Robotics and Computer-Integrated Manufacturing",65.0,null,101962.0,null,null,null,88.0,"10.1016/j.rcim.2020.101962","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85082867988&doi=10.1016%2fj.rcim.2020.101962&partnerID=40&md5=cae93089e39d7b540de4e36ac65ca4ed","School of Intelligent Systems Science and Engineering, Jinan University (Zhuhai Campus), Zhuhai, Guangdong, China; Institute of Physical Internet, Jinan University (Zhuhai Campus), Zhuhai, Guangdong, China; Department of Transportation Economics and Logistics Management, College of Economics, Shenzhen University, Shenzhen, China; School of Economics & Management, South China Normal University, Guangzhou, Guangdong, China; School of Architecture, Harbin Institute of Technology, Shenzhen, Guangdong, China; Intelligent Transportation Lab, Shenzhen Key Laboratory of Urban Planning and Decision Making, Harbin Institute of Technology, Shenzhen, Guangdong, China; HKU-ZIRI Lab for Physical Internet, Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong","Li M., School of Intelligent Systems Science and Engineering, Jinan University (Zhuhai Campus), Zhuhai, Guangdong, China, Institute of Physical Internet, Jinan University (Zhuhai Campus), Zhuhai, Guangdong, China; Shao S., Department of Transportation Economics and Logistics Management, College of Economics, Shenzhen University, Shenzhen, China; Ye Q., School of Economics & Management, South China Normal University, Guangzhou, Guangdong, China; Xu G., School of Architecture, Harbin Institute of Technology, Shenzhen, Guangdong, China, Intelligent Transportation Lab, Shenzhen Key Laboratory of Urban Planning and Decision Making, Harbin Institute of Technology, Shenzhen, Guangdong, China; Huang G.Q., HKU-ZIRI Lab for Physical Internet, Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong","As one of the most prevailing retail channels, E-commerce has nowadays facilitated retailers to sell goods to customers worldwide and tremendously increased the supply chain efficiency by removing most intermediate links. The broaden business scope and accelerated goods circulation, nevertheless, have generally led to capital shortages for retailers, especially small and medium enterprises (SMEs). Given the SMEs’ difficulty in acquiring capital from financial institutions such as banks, logistics finance (LF) has emerged as an alternative, which is the combination of logistics and financial service. However, the frequent order fulfillment and diversity of pledges in E-commerce hinder SMEs in meeting LF's financing requirements. Furthermore, the current LF relies more on large and reputable third-party logistics (3PLs) to alleviate financing risks, which in turn raises the entry threshold for other 3PLs. Hence, this paper has proposed a blockchain-enabled logistics finance execution platform (BcLFEP) as an integrated solution to facilitate LF for E-commerce retail. A cross-layered architecture is proposed to organize and manage involved resources, workflows and decisions based on the object-oriented methodology (OOM). A hybrid finite state machine-based smart contract (HFSM-SC) is designed to associate and coordinate with all kinds of agents for LF operations throughout its lifecycle. Moreover, blockchain is integrated with agent technology to construct a blockchain-enabled multi-agent system (BcMAS), providing a trusted runtime environment to more autonomously and efficiently execute smart contract. Finally, a case study is conducted to implement BcLFEP-enabled dynamic pledge management for verification and evaluation. © 2020 Elsevier Ltd","Blockchain agent; E-commerce retail; Logistics finance; Multi-agent system","Agricultural robots; Blockchain; Electronic commerce; Fintech; Life cycle; Multi agent systems; Outsourcing; Sales; Supply chains; Financial institution; Layered architecture; Logistics finances; Object-oriented methodology; Runtime environments; Small and medium enterprise; Supply chain efficiency; Third party logistics; Autonomous agents",{"$nulls":4},"Hangzhou Municipal and Lin'an City Governments; National Key R&D Program of China; National Natural Science Foundation of China, NSFC, (71901146); National Key Research and Development Program of China, NKRDPC, (2019YFB1705401)","Funding text 1: This research is supported by National Natural Science Foundation of China under Grant No. 71901146, and National Key R&D Program of China under Grant No. 2019YFB1705401. Acknowledgments are also given to Zhejiang Provincial, Hangzhou Municipal and Lin'an City Governments for partial financial supports.; Funding text 2: This research is supported by National Natural Science Foundation of China under Grant No. 71901146 , and National Key R&D Program of China under Grant No. 2019YFB1705401 . Acknowledgments are also given to Zhejiang Provincial, Hangzhou Municipal and Lin'an City Governments for partial financial supports.","Jing B., Chen X., Cai G., Equilibrium financing in a distribution channel with capital constraint, Prod. Oper. Manag, 21, pp. 1090-1101, (2012); Hanedar E.Y., Broccardo E., Bazzana F., Collateral requirements of SMEs: the evidence from less-developed countries, J. Bank. Financ., 38, pp. 106-121, (2014); Chen X., Cai G.G., Joint logistics and financial services by a 3PL firm, Eur. J. Oper. 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Econ., 5, pp. 60-66, (2012); Sun X.H., Chu X.J., Researches on mitigation of risks of logistics finance caused by information not fully shared, Adv. Mater. Res., pp. 663-667, (2014); Wang L., Xu T., Zhu S., Supply chain decision-making based on warehouse receipt pledge and risk consideration under twice ordering mode, Math. Probl. Eng., pp. 1-15, (2018); Jia F., Blome C., Sun H., Yang Y., Zhi B., Towards an integrated conceptual framework of supply chain finance: an information processing perspective, Int. J. Prod. Econ., 219, pp. 18-30, (2020); Cong L., Research on risk control of logistics finance, DEStech Trans. Soc. Sci. Educ. Hum. Sci., pp. 289-293, (2018); Abbasi W.A., Wang Z., Abbasi D.A., Supply chain finance: generation and growth of new financing approach, J. Finance, 5, pp. 50-57, (2017); Fellenz M.R., Augustenborg C., Brady M., Greene J., Requirements for an evolving model of supply chain finance: a technology and service providers perspective, Commun. 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Agents Multi-Agent Syst., pp. 110-126, (2018); Coad P., Yourdon E., (1991); Rumbaugh J., Blaha M., Premerlani W., Eddy F., Lorensen W.E., Object-oriented Modeling and Design, (1991); Li M., Xu G., Lin P., Huang G.Q., Cloud-based mobile gateway operation system for industrial wearables, Robot. Comput. Integr. Manuf, 58, pp. 43-54, (2019); Li M., Lin P., Xu G., Huang G.Q., Cloud-based ubiquitous object sharing platform for heterogeneous logistics system integration, Adv. Eng. Informatics, 38, pp. 343-356, (2018); Fang J., Qu T., Li Z., Xu G., Huang G.Q., Agent-based gateway operating system for RFID-enabled ubiquitous manufacturing enterprise, Robot. Comput. Integr. Manuf., 29, pp. 222-231, (2013)","S. Shao; Department of Transportation Economics and Logistics Management, College of Economics, Shenzhen University, Shenzhen, China; email: aaron.shaosj@gmail.com",null,"Elsevier Ltd",{"$nulls":5},7365845.0,null,"RCIME",null,"English","Rob Comput Integr Manuf","Article","Final",null,"Scopus","2-s2.0-85082867988"]
["Shen X.-D.; Chen X.; Ji R.; Wu R.-H.","Shen, Xiang-Dong (57222115475); Chen, Xi (57225125600); Ji, Ran (57221441460); Wu, Ren-Hong (57211134547)","57222115475; 57225125600; 57221441460; 57211134547","The new ecosystem of cross-border e-commerce among Korea, China and Japan based on blockchain",2020.0,"Journal of Korea Trade",24.0,5.0,null,87.0,105.0,18.0,12.0,"10.35611/jkt.2020.24.5.87","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85099158838&doi=10.35611%2fjkt.2020.24.5.87&partnerID=40&md5=02e599992ab2a7628c4928aa535ab613","Business School, Changshu Institute of Technology, China; Business School, Shandong Jianzhu University, China; College of Tourism, Hebei University of Economics and Business, China; College of Economics, Guangdong Ocean University, China","Shen X.-D., Business School, Changshu Institute of Technology, China; Chen X., Business School, Shandong Jianzhu University, China; Ji R., College of Tourism, Hebei University of Economics and Business, China; Wu R.-H., College of Economics, Guangdong Ocean University, China","Purpose - The purpose of the study is to propose a theoretical framework of cross-border e-commerce ecosystems based on blockchain technology. The ecosystem includes five systems, namely, crossborder supply chain intelligent system, cross-border logistics system, cross-border payment system, cross-border product quality traceability system and cross-border customs supervision system. Design/methodology - This study firstly derived the main improvement factors for the new ecosystem based on blockchain through prior research and expert interviews on cross-border e-commerce. Then explored the use of virtue of decentralization, anti-counterfeiting traceability, consensus mechanism, smart contract and other means of the core technology of blockchain to overcome the bottleneck of cross-border e-commerce development among Korea, China, and Japan. Finally, proposed valuable implications in both theoretical and practical perspectives. Findings - As a result, we combined with the problems existing in cross-border e-commerce among Korea, China and Japan, this paper proposes a solution based on blockchain. On this basis, it constructs a cross-border e-commerce ecosystem among these three countries, including five systems. In addition, we discuss the main problems existing in the current blockchain, such as low transaction concurrency, security loopholes, and inconsistent standards, the corresponding countermeasures are proposed from the technical level, security level and industry standards. Originality/value - This study is the first to apply the blockchain technology to solve the cross-border e-commerce problems in Korea, China and Japan, which is of pioneering significance in both literature and practice. Block chain technology is in the ascendency. This study provides technical solutions for promoting the development of cross-border e-commerce import and export trade between Korea, China and Japan. © 2020 Korea Trade Research Association.","Blockchain; China and japan; Cross-border e-commerce; Ecosystem; Korea",{"$nulls":7},"Antonopoulos A. 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J., Christopher M., Jatinder S., Blockchain Demystified: An Introduction to Blockchain Technology and its Legal Implications, pp. 1-53, (2017); Chen Si, Shi Rui, Ren Zhuang-Yu, Yan Jia-Qi, Shi Ya-Ni, Zhang Jin-Yu, A Blockchain-based Supply Chain Quality Management Framework, 2017 IEEE 14th International Conference on e-Business Engineering (ICEBE), (2017); Data Monitoring Report of China’s Cross-border E-commerce Market in 2018, (2019); Choi Hyuk-Jun, Jung Hyun-Jae, Lee Dong-Hyon, A Study on Port Improvement with the Activation of Cross-Border E-Commerce: A Study of Pyeongtaek Port, Journal of Korea Trade, 23, 7, pp. 34-44, (2019); Huckle S., Bhattacharya R., White M., Beloff N., Internet of Things, Blockchain and Shared Economy Applications, Procedia Computer Science, 98, pp. 461-466, (2016); Ding Qing-Yang, Zhu Jian-Ming, The Product Information Traceability and Security Model of B2C E-Platform from the Perspective of Blockchain, China Business and Market, 31, 12, pp. 41-49, (2017); Han Xuan, Zhu Yong, Wang Fei-Yue, Security Problems on Blockchain: The State of the Art and Future Trends, ACTA AUTOMATICA SINICA, 45, 1, pp. 206-225, (2019); He Jiang, Qian Hui-Wen, Research on Synergy Strategies of Cross-border E-commerce and Cross-border Logistics, Logistics Sci-Tech, 7, pp. 1-6, (2017); La Jung-Joo, Shin Won-Kyu, Assessment of the Korean-Chinese Exports Competition in Sophisticated Markets, Journal of Korea Trade, 23, 2, pp. 1-13, (2019); La Kong-Woo, Song Jin-Gu, An Empirical Study on the Effects of Export Promotion on Korea-China-Japan Using Logistics Performance Index (LPI), Journal of Korea Trade, 23, 7, pp. 96-112, (2019); Li Hai-Bo, Research on the Problems and Measures of Cross-border E-commerce Based on the Block Chain Technology, China Business and Market, 32, 11, pp. 41-48, (2018); Liu Tao, Lu Dong, Woo W. T., Trade, finance and international currency, Journal of Economic Behavior and Organization, 16, 3, pp. 14-23, (2019); Liu Xue-Chun, Zheng Ya-Qin, Application of Block Chain Technology in Cross-border Import E-Commerce: A Case Study of Tmall International, Journal of WuHan Business University, 33, 4, pp. 25-30, (2019); 2018 China Blockchain Industry White Paper, (2018); Morkunaa V J., Paschen J., Boon E., How Blockchain Technologies Impact Your Business Model, Business Horizons, 62, 3, pp. 295-306, (2019); Peters G. W., Panayi E., Understanding Modern Banking Ledgers through Blockchain Technologies: Future of Transaction Processing and Smart Contracts on the Internet of Money, Banking Beyond Banks and Money, 11, pp. 239-278, (2016); Qiu Tianyi, Zhang Rui-Dong, Gao Yuan, Ripple vs. SWIFT: Transforming Cross-broder Remittance Using Blockchain Technology, Procedia Computer Science, 147, pp. 428-434, (2019); Rajput U., Abbas F., Heekuck O., A Solution towards Eliminating Transaction Malleability in Bitcoin, Journal of Information Processing Systems, 14, 2, pp. 837-850, (2018); Richard D., Gareth O., Rep on the Roll: A Peer to Peer Reputation System based on a Rolling Blockchain, International Journal of Digital Society, 7, 1, pp. 1123-1134, (2016); Satoshi N., Bitcoin: A Peer-to-Peer Electronic Cash System, (2008); Song Sang-Hwa, The Future of Blockchain and Logistics, Logistics Insight, 1, pp. 1-36, (2018); Wang Juan-Juan, Qin Wei, Explore the New Normal of E-commerce in the ‘One Belt and One Road Strategic Area, China Business and Market, 29, 5, pp. 46-54, (2015); Wu Jia-Ni, Nguyen K. T., Application of Blockchain Technology in Sustainable Energy Systems: An Overview, Sustainability, 10, pp. 1-22, (2018); Wei Li-Ping, Xing Wen-Xiang, Research on the Impact of Cross-border E-commerce Export on Brand Internationalization in China, Intertrade, 12, pp. 19-26, (2019); Korea, China and Japan Launched the First Cross-border Authentic Product Traceability Platform to Help the Development of Cross-border E-commerce, (2016); Yang Jung-Ho, Applicability of Blockchain based Bill of Lading under the Rotterdam Rules and UNCITRAL Model Law on Electronic Transferable Records, Journal of Korea Trade, 23, 6, pp. 113-130, (2019); Yang Ke-Yan, Research on Information Ecosystem Construction about E-business, Information Science, 32, 3, pp. 37-41, (2014); Yuan Yong, Wang Fei-Yue, Blockchain: The State of the Art and Future Trends, ACTA AUTOMATICA SINICA, 42, 4, pp. 481-494, (2016); Zeng Shi-Qin, Huo Ru, Huang Tao, Liu Jiang, Liu Shuo, Feng Wei, Survey of Blockchain: Principle, Progress and Application, Journal of Communications, 41, 1, pp. 134-151, (2020); Zhang Hao, Zhu Pei-Feng, Business Model Innovation Based on Block Chain Technology: Value Proposition and Application Scenarios, Science & Technology Progress and Policy, 37, 2, pp. 19-25, (2020); Zhang Yan-Bin, The New Ecosystem of Cross-border E-commerce between EU and China based on Blockchain, China Business and Market, 32, 2, pp. 66-72, (2018)","X. Chen; Business School, Shandong Jianzhu University, China; email: chenxi0801@naver.com",null,"Korea Trade Research Association",{"$nulls":5},"1229828X",null,null,null,"English","J. Korea Trade","Article","Final",null,"Scopus","2-s2.0-85099158838"]
["Zhang M.; Pratap S.; Zhao Z.; Prajapati D.; Huang G.Q.","Zhang, Mengdi (56204508000); Pratap, Saurabh (56667217800); Zhao, Zhiheng (57192180873); Prajapati, D. (57215023349); Huang, George Q. (7403425048)","56204508000; 56667217800; 57192180873; 57215023349; 7403425048","Forward and reverse logistics vehicle routing problems with time horizons in B2C e-commerce logistics",2021.0,"International Journal of Production Research",59.0,20.0,null,6291.0,6310.0,19.0,24.0,"10.1080/00207543.2020.1812749","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85090304796&doi=10.1080%2f00207543.2020.1812749&partnerID=40&md5=c14dbfe40ad84c2bea1d8a9248b4f614","School of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing, China; Department of Mechanical Engineering, Indian Institute of Information Technology, Design & Manufacturing, Jabalpur, India; HKU-ZIRI Lab for Physical Internet, Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong, Hong Kong","Zhang M., School of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing, China; Pratap S., Department of Mechanical Engineering, Indian Institute of Information Technology, Design & Manufacturing, Jabalpur, India; Zhao Z., School of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing, China; Prajapati D., Department of Mechanical Engineering, Indian Institute of Information Technology, Design & Manufacturing, Jabalpur, India; Huang G.Q., HKU-ZIRI Lab for Physical Internet, Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong, Hong Kong","This research addresses a vehicle routing problem with simultaneous pickup and delivery with time windows from multiple depots (MVRPSPDTW) over a time horizon in the B2C e-commerce logistics system. We consider an e-commerce logistics system with a multi-period, which consists of customers, logistics service providers (LSPs), suppliers, and a decision-making platform. A mixed-integer non-linear programming (MINLP) model is developed and tested on small- and large-scale instances. To handle more realistic large-scale problems, we have used two approaches (i) exact optimisation approach using (i.e. CPLEX tool) and metaheuristic algorithms (i.e. Differential Evolutionary Algorithm (DE), Parallel Differential Evolutionary Algorithm (Par-DE), Genetic Algorithm (GA), and Block-based Genetic Algorithm (BBGA)) to minimise the total transportation cost and penalty due to the delay by logistics service providers. The computation experiment is conducted on the real practical scenario data and the comparative result is demonstrated. © 2020 Informa UK Limited, trading as Taylor & Francis Group.","CPLEX; differential evolutionary algorithm; E-commerce logistics; meta-heuristic; reverse logistics; vehicle routing problem","Decision making; Electronic commerce; Integer programming; Nonlinear programming; Vehicle routing; Differential evolutionary algorithm; Large-scale problem; Logistics service provider; Meta heuristic algorithm; Mixed-integer nonlinear programming; Simultaneous pickup and deliveries; Transportation cost; Vehicle Routing Problems; Genetic algorithms",{"$nulls":4},"Nanjing University of Post and Telecommunications research start-up fund, (NY218125, NY218126); National Natural Science Foundation of China, NSFC, (NY219112); Natural Science Foundation of Jiangsu Province, (BK20180749); Natural Science Research of Jiangsu Higher Education Institutions of China, (19KJB580016)","This research was supported, in part, by Natural Science Foundation of the Jiangsu Higher Education Institutions of China (grant number 19KJB580016), Nanjing University of Post and Telecommunications research start-up fund (grant numbers NY218125, NY218126), NSFC Incubation fund (grant number NY219112) and Natural Science Foundation of Jiangsu Province (grant number BK20180749).","Alshamrani A., Mathur K., Ballou R.H., Reverse Logistics: Simultaneous Design of Delivery Routes and Returns Strategies, Computers & Operations Research, 34, 2, pp. 595-619, (2007); 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Ehmke J.F., Campbell A.M., Thomas B.W., Optimizing for Total Costs in Vehicle Routing in Urban Areas, Transportation Research Part E: Logistics and Transportation Review, 116, pp. 242-265, (2018); Erbao C., Mingyong L., A Hybrid Differential Evolution Algorithm to Vehicle Routing Problem with Fuzzy Demands, Journal of Computational and Applied Mathematics, 231, 1, pp. 302-310, (2009); Govindan K., Soleimani H., Kannan D., Reverse Logistics and Closed-Loop Supply Chain: A Comprehensive Review to Explore the Future, European Journal of Operational Research, 240, 3, pp. 603-626, (2015); Grewal D., Iyer G.R., Levy M., Internet Retailing: Enablers, Limiters and Market Consequences, Journal of Business Research, 57, 7, pp. 703-713, (2004); Griffis S.E., Rao S., Goldsby T.J., Niranjan T.T., The Customer Consequences of Returns in Online Retailing: An Empirical Analysis, Journal of Operations Management, 30, 4, pp. 282-294, (2012); Guo J., Wang X., Fan S., Gen M., Forward and Reverse Logistics Network and Route Planning Under the Environment of Low-Carbon Emissions: A Case Study of Shanghai Fresh Food E-Commerce Enterprises, Computers & Industrial Engineering, 106, pp. 351-360, (2017); Hassini E., Surti C., Searcy C., A Literature Review and a Case Study of Sustainable Supply Chains with a Focus on Metrics, International Journal of Production Economics, 140, 1, pp. 69-82, (2012); Iassinovskaia G., Limbourg S., Riane F., The Inventory-routing Problem of Returnable Transport Items With Time Windows and Simultaneous Pickup and Delivery in Closed-loop Supply Chains, International Journal of Production Economics, 183, pp. 570-582, (2017); Khanduzia R., Sangaiah A.K., A Fast Genetic Algorithm for a Critical Protection Problem in Biomedical Supply Chain Networks, Applied Soft Computing, 75, pp. 162-179, (2019); Kokkinaki A.I., Dekker R., de Koster R., Pappis C., (2001); Kumar V.N.S.A., Kumar V., Brady M., Garza-Reyes J.A., Simpson M., Resolving Forward-reverse Logistics Multi-period Model Using Evolutionary Algorithms, International Journal of Production Economics, 183, pp. 458-469, (2017); Kuo R.J., Wibowo B.S., Zulvia F.E., Application of a Fuzzy Ant Colony System to Solve the Dynamic Vehicle Routing Problem with Uncertain Service Time, Applied Mathematical Modelling, 40, 23-24, pp. 9990-10001, (2016); Leung K.H., Luk C.C., Choy K.L., Lam H.Y., Lee C.K.M., A B2B Flexible Pricing Decision Support System for Managing the Request for Quotation Process Under E-commerce Business Environment, International Journal of Production Research, 57, 20, pp. 6528-6551, (2019); Li J., Pardalos P.M., Sun H., Pei J., Zhang Y., Iterated Local Search Embedded Adaptive Neighborhood Selection Approach for the Multi-Depot Vehicle Routing Problem with Simultaneous Deliveries and Pickups, Expert Systems with Applications, 42, 7, pp. 3551-3561, (2015); Mingyong L., Erbao C., An Improved Differential Evolution Algorithm for Vehicle Routing Problem with Simultaneous Pickups and Deliveries and Time Windows, Engineering Applications of Artificial Intelligence, 23, 2, pp. 188-195, (2010); Moons S., Braekers K., Ramaekers K., Caris A., Arda Y., The Value of Integrating Order Picking and Vehicle Routing Decisions in a B2C E-commerce Environment, International Journal of Production Research, 57, 20, pp. 6405-6423, (2019); 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Tasan A.S., Gen M., A Genetic Algorithm Based Approach to Vehicle Routing Problem with Simultaneous Pick-up and Deliveries, Computers & Industrial Engineering, 62, 3, pp. 755-761, (2012); Wang X., Xie J., Fan Z.-P., B2C Cross-border E-commerce Logistics Mode Selection Considering Product Returns, International Journal of Production Research, (2020); Wang J., Zhou Y., Wang Y., Zhang J., Chen C.P., Zheng Z., Multiobjective Vehicle Routing Problems with Simultaneous Delivery and Pickup and Time Windows: Formulation, Instances, and Algorithms, IEEE Transactions on Cybernetics, 46, 3, pp. 582-594, (2016); Winkelhaus S., Grosse E.H., Logistics 4.0: A Systematic Review Towards a New Logistics System, International Journal of Production Research, 58, 3, pp. 18-43, (2020); Wu X., Che A., A Memetic Differential Evolution Algorithm for Energy-efficient Parallel Machine Scheduling, Omega, 82, pp. 155-165, (2019); Zhang M., (2017); Zhang M., Wang N., He Z., Yang Z., Guan Y., Bi-Objective Vehicle Routing for Hazardous Materials Transportation With Actual Load Dependent Risks and Considering the Risk of Each Vehicle, IEEE Transactions on Engineering Management, 66, 3, pp. 429-442, (2018); Zhao Z., Fang J., Huang G.Q., Zhang M., Location Management of Cloud Forklifts in Finished Product Warehouse, International Journal of Intelligent Systems, 32, 4, pp. 342-370, (2017); Zhou S., Li X., Du N., Pang Y., Chen H., A Multi-Objective Differential Evolution Algorithm for Parallel Batch Processing Machine Scheduling Considering Electricity Consumption Cost, Computers & Operations Research, 96, pp. 55-68, (2018)","S. Pratap; Department of Mechanical Engineering, Indian Institute of Information Technology, Design & Manufacturing, Jabalpur, India; email: s.pratapiitkgp@gmail.com",null,"Taylor and Francis Ltd.",{"$nulls":5},207543.0,null,"IJPRB",null,"English","Int J Prod Res","Article","Final",null,"Scopus","2-s2.0-85090304796"]
["Yang G.; Zhao L.; Kong N.","Yang, Ge (57221539909); Zhao, Lindu (7404455064); Kong, Nan (7005055833)","57221539909; 7404455064; 7005055833","\"order-online-and-pickup-offline\" strategy for online direct sale of time-sensitive commodities",2021.0,"RAIRO - Operations Research",55.0,null,null,"S999","S1011",12.0,2.0,"10.1051/ro/2020019","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85102063572&doi=10.1051%2fro%2f2020019&partnerID=40&md5=4e911111cf16ecdde72bbd131804f8e0","School of Economics and Management, Southeast University, No. 2 Sipailou, Nanjing, 210096, China; Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, United States","Yang G., School of Economics and Management, Southeast University, No. 2 Sipailou, Nanjing, 210096, China; Zhao L., School of Economics and Management, Southeast University, No. 2 Sipailou, Nanjing, 210096, China; Kong N., Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, United States","Although recent decades have witnessed rapid development of e-commerce, direct sale of time-sensitive commodities on e-commerce platforms still faces significant challenges due to the dilemma between short delivery time and high delivery costs. To alleviate these challenges, manufacturers with online retailing operations have attempted to cooperate with offline retailers by using an \"order-online, pickup-offline\"(OOPO) strategy. To study the problem of effectively implementing the OOPO strategy for time-sensitive commodities, we consider a mechanism under which the manufacturer pays the retailers a cooperative service fee to ensure delivery coordination between the online and offline channels. We develop Stackelberg game-theoretic models to compare the profits of both delivery channels before and after the implementation of the OOPO strategy. By analyzing the models, we derive a feasible range on the cooperative service fee such that both channels are more profitable with the implementation. We further examine the plausibility of implementing the strategy when both channels are required to charge the same price on the commodities, which can lead to both channel coordination and pricing coordination. © EDP Sciences, ROADEF, SMAI 2021.","Cooperative pricing; Dual-channel; Stackelberg game theory; Time-sensitive","Electronic commerce; Game theory; Manufacture; Pickups; Profitability; Channel coordination; Cooperative services; Delivery channels; Offline channel; Offline retailers; Online retailing; Short delivery time; Stackelberg Games; Costs",{"$nulls":4},"Key R & D Plans of Jiangsu Province, (BE2017156); National Natural Science Foundation of China, NSFC, (71661147004, 71671039)","Acknowledgements. This work was supported by the National Natural Science Foundation of China (Grant No. 71661147004, 71671039), the Key R & D Plans of Jiangsu Province, China (No. BE2017156).","Ashcraft D., The multichannel pricing challenge-managing customer service in stores and on the internet-brief article, Dsn Retail. Today, 1, (2001); Boute R.N., Disney S.M., Lambrecht M.R., Coordinating lead times and safety stocks under auto correlated demand, Eur. J. Oper., 232, pp. 52-63, (2014); Chen H., Chen J., Chen Y.F., A coordination strategy for a supply chain with demand information updating, Int. J. Prod. Econ., 103, pp. 347-361, (2006); Chen K.Y., Kaya M., Ozer O., Dual sale channel management with service competition, M & SOM-Manuf. Serv. Oper., 10, pp. 654-675, (2008); Fa D., Xu Q., Fan T., Inventory optimization model considering consumer shift and inventory transshipment in dual-channel supply chains, RAIRO: Or, 53, pp. 59-79, (2019); Fan C., Liu Y., Yang X., Online and offline cooperation under buy-online, pick-up-in-store: Pricing and inventory decisions, J. Ind. Manage. Optim., 15, pp. 1455-1472, (2019); Hong I.H., Hsu H.M., Wu Y.M., Equilibrium pricing and lead time decisions in a competitive industry, Int. J. Prod. Econ., 139, pp. 586-595, (2012); Hu Y., Guan Y., Liu T., Lead-time hedging and coordination between manufacturing and sale departments using Nash and Stackelberg games, Eur. J. Oper. Res., 210, pp. 231-240, (2011); Hua G., Wang S., Cheng T.C.E., Price and lead time decisions in dual channel supply chains, Eur. J. Oper. Res., 205, pp. 113-126, (2010); Jap S.D., Mohr J.J., Leveraging internet technologies in B2B relationships, Calif. Manage. Rev., 44, pp. 24-38, (2002); Jin Z., Average Profit Margin of Medical E-commerce Is 5.5%, (2016); Leng M., Parlar M., Lead-time reduction in a two-level supply chain: Non-cooperative equilibria vs, Coordination with a Profit-sharing Contract. Int. J. Prod. Econ., 118, pp. 521-544, (2009); Li Y., Lin Q., Ye F., Pricing and promised delivery lead time decisions with a risk-averse agent, Int. J. Prod. Res., 52, pp. 3518-3537, (2014); Li Y.B., Lin C.P., Wu T.J., The study on price and lead time decisions in retailer-dominated dual-channel supply chain, J. Interd. Math., 20, pp. 805-819, (2017); Liu L., Parlar M., Zhu S.X., Pricing and lead time decisions in decentralized supply chains, Manage. Sci., 53, pp. 713-725, (2007); Ma J.Z., Yi X.X., Many Fresh Food E-commerce Companies Have Closed down, (2016); Neslin S.A., Grewal D., Leghorn R., Challenges and opportunities in multichannel customer management, J. Ser. Res., 19, pp. 95-112, (2006); Pekgun P., Grifin P.M., Keskinocak P., Coordination of marketing and production for price and leadtime decisions, Iie Trans., 40, pp. 12-30, (2008); Qing N., Tmall Sets up 540 Courier Collection Points in Wenzhou, (2013); Ray S., Jewkes E.M., Customer lead time management when both demand and price are lead time sensitive, Eur. J. Oper. Res., 153, pp. 769-781, (2004); Saha S., Modak N.M., Panda S., Managing a retailers dual-channel supply chain under price-and delivery time-sensitive demand, J. Model. Manage., 13, pp. 351-374, (2018); Tang F.F., Xing X., Will the growth of multi-channel retailing diminish the pricing efficiency of the web?, J. Retail., 73, pp. 319-333, (2001); Tersin R.J., Hummingbird E.A., Lead-time reduction: The search for competitive advantage, Int. J. Oper. Prod. Manage., 15, pp. 8-18, (1995); Tsay A.A., Agrawal N., Channel conict and coordination in the e-commerce age, Oper. Manage., 13, pp. 93-110, (2004); Uthayakumar R., Kumar M.G., Constrained integrated inventory model for multi-item under mixture of distributions, RAIRO: Or, 52, pp. 849-893, (2018); Webster S., Dynamic pricing and lead-time policies for make-to-order systems, Decis. Sci., 33, pp. 579-600, (2002); Wu C.X., Guo J., Xu C.Y., Price competition between a dual-channel retailer and a pure online retailer, J. Emerg. Trends Econ. Manage. Sci., 5, pp. 120-127, (2014); Xiao T., Qi X., A two-stage supply chain with demand sensitive to price delivery time, and reliability of delivery, Ann. Oper. Res., 241, pp. 475-496, (2016); Xiao T., Yang D., Shen H., Coordinating a supply chain with a quality assurance policy via a revenue-sharing contract, Int. J. Prod. Res., 49, pp. 90-120, (2011); Xu H., Liu Z.Z., Zhang S.H., A strategic analysis of dual channel supply chain design with price and delivery lead time considerations, Int. J. Prod. Econ., 139, pp. 654-663, (2012); Zhai Y., Zhong R.Y., Li Z., Production lead-time hedging and coordination in prefabricated construction supply chain management, Int. J. Prod. Res., 55, pp. 3984-4002, (2017); Zhu S.X., Integration of capacity, pricing, and lead-time decisions in a decentralized supply chain, Int. J. Prod. Econ., 164, pp. 14-23, (2015)","L. Zhao; School of Economics and Management, Southeast University, Nanjing, No. 2 Sipailou, 210096, China; email: ldzhao@seu.edu.cn",null,"EDP Sciences",{"$nulls":5},2.8047303E7,null,null,null,"English","RAIRO Oper. Res.","Article","Final","All Open Access; Bronze Open Access; Green Open Access","Scopus","2-s2.0-85102063572"]
["Kumar A.; Sikdar P.; Saha R.","Kumar, Amresh (57221101812); Sikdar, Pallab (56825574700); Saha, Raiswa (57204290207)","57221101812; 56825574700; 57204290207","Seller experience assessment in online marketplace: a scale development study",2021.0,"Benchmarking",28.0,7.0,null,2315.0,2342.0,27.0,4.0,"10.1108/BIJ-06-2020-0305","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85100240165&doi=10.1108%2fBIJ-06-2020-0305&partnerID=40&md5=2a4f256de11798f350243cd262a3853e","Indian Institute of Management (IIM), Bodh Gaya, India; Institute of Management (BULMIM), New Delhi, India; SRM University, Haryana Campus, Sonepat, India","Kumar A., Indian Institute of Management (IIM), Bodh Gaya, India; Sikdar P., Institute of Management (BULMIM), New Delhi, India; Saha R., SRM University, Haryana Campus, Sonepat, India","Purpose: Recent decade has witnessed exponential growth in e-commerce segment, leading to emergence of various online selling platforms catering to diverse product requirements of customers. Such a development has provided impetus to both existing businesses and newly established ventures to make available their offerings through online selling platforms with a view to improve the reach of their products. This study is an attempt to identify the experience of registered vendors with the online marketplaces. It aims to develop and validate a scale to measure vendor's experience with e-commerce platforms. Design/methodology/approach: As a part of the scale development process, relevant literature sources were scanned to spot the precise knowledge gap and to put in place a sound theoretical background for the study. Thereafter, a scientific approach was adopted for scale creation. First, the scale items were identified through interviews of vendors registered with major online selling platforms and other academic experts pertaining to the marketing domain. Subsequently, major dimensions of seller experience were identified through exploratory factor analysis (EFA) applied on data collected from active vendors by the means of a structured survey instrument. The final data set was subjected to confirmatory factor analysis (CFA) in a bid to validate the scale. Findings: The study’s outcomes reveal that seller experience in an online marketplace can be best captured by a multidimensional scale characterized by six major dimensions. These are “Registration,”; “Product Listing”; “Pricing Autonomy”; “Ease of Pick-up and Delivery”; “Credit of Receivables” and “Vendor Assistance.” A proper emphasis to continually improve upon these dimensions by the e-commerce platforms is expected to enhance the utility and overall experience of vendors from such platforms. Existence of a mutually beneficial relationship between vendors and online marketplaces will help marketplaces to mitigate concerns like nonfulfillment of orders and dispatch of substandard products. Originality/value: Sustainable long-term relations between vendors and online marketplaces hold the key for such marketplaces to render error-free and delightful service on each individual order received. Seller experience of registering and operating on such e-marketplaces inspite of playing a defining role in vendor–marketplace relations has received scant attention of researchers, both in academia and industry till date. The present research is a seminal attempt to address this gap in marketing literature and offer additional know-how. © 2021, Emerald Publishing Limited.","E-commerce; Online marketplace; Scale development; Vendors",{"$nulls":7},"Anderson S.T., Friedman D., Milam G., Singh N., Seller strategies on eBay: does size matter?, International Journal of Electronic Business, 5, 6, pp. 643-669, (2007); Bagdare S., Jain R., Measuring retail customer experience, International Journal of Retailing and Distribution Management, 41, 10, pp. 790-804, (2013); Bapna R., Goes P., Gupta A., Replicating online Yankee auctions to analyze auctioneers' and bidders' strategies, Information Systems Research, 14, 3, pp. 244-268, (2003); Bartezzaghi E., Ronchi S., E-sourcing in a buyer-operator-seller perspective: benefits and criticalities, Production Planning and Control, 16, 4, pp. 405-412, (2005); Becherer R.C., Halstead D., Characteristics and internet marketing strategies of online auction sellers, International Journal of Internet Marketing and Advertising, 1, 1, pp. 24-36, (2004); Beyma J., The Complete Guide to Selling on the Walmart Marketplace in 2019, (2019); Blocker C.P., Cannon J.P., Panagopoulos N.G., Sager J.K., The role of the sales force in value creation and appropriation: new directions for research, Journal of Personal Selling and Sales Management, 32, 1, pp. 15-27, (2012); Boles J.S., Brashear T., Bellenger D., Barksdale H.C.J., Relationship selling behaviours: antecedents and relationship with performance, Journal of Business and Industrial Marketing, 15, 2, pp. 141-153, (2000); Bolton G., Greiner B., Ockenfels A., Engineering trust: reciprocity in the production of reputation information, Management Science, 59, pp. 265-285, (2013); Bowen N.K., Guo S., Structural Equation Modeling (Pocket Guide to Social Work Research Methods), (2012); Braun V., Clarke V., Using thematic analysis in psychology, Qualitative Research in Psychology, 3, 2, pp. 77-101, (2006); Cannon J.P., Perreault W.D., Buyer–seller relation-ships in business markets, Journal of Marketing Research, 36, 4, pp. 439-460, (1999); Carmines E.G., Zeller R.A., Reliability and Validity Assessment, 17, (1979); Che X., Katayama H., Lee P., Shi N., Warranty, seller reputation, and buyer experience: evidence from ebay used car auctions, The Journal of Industrial Economics, 67, 3-4, pp. 593-627, (2019); Chevalier M., Gutsatz M., Luxury Retail Management: How the World's Top Brands Provide Quality Product and Service Support, (2012); Churchill G.A., A paradigm for developing better measures of marketing constructs, Journal of Marketing Research, 16, 1, pp. 64-73, (1979); Costello A.B., Osborne J.W., Best practices in exploratory factor analysis: four recommendations for getting the most from your analysis, Practical Assessment, Research and Evaluation, 10, 1, (2005); How to Attract Sellers on Your Virtual Multi Vendor Marketplace, (2019); Daly J., Kellehear A., Gliksman M., The Public Health Researcher: A Methodological Guide, (1997); Dann S., Dann S., Strategic Internet Marketing, (2001); DeVellis R.F., Factor analysis. 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Saha; SRM University, Sonepat, Haryana Campus, India; email: raiswasaha5@gmail.com",null,"Emerald Group Holdings Ltd.",{"$nulls":5},1.4635771E7,null,"BQMTF",null,"English","Benchmarking","Article","Final",null,"Scopus","2-s2.0-85100240165"]
["Jiang Z.-Z.; Wan M.; Pei Z.; Qin X.","Jiang, Zhong-Zhong (9335480600); Wan, Mingzhong (57208086581); Pei, Zhi (36773534100); Qin, Xuwei (8724410800)","9335480600; 57208086581; 36773534100; 8724410800","Spatial and temporal optimization for smart warehouses with fast turnover",2021.0,"Computers and Operations Research",125.0,null,105091.0,null,null,null,12.0,"10.1016/j.cor.2020.105091","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85091638132&doi=10.1016%2fj.cor.2020.105091&partnerID=40&md5=7040c38c09cf1eed4f84000a41f9f71a","School of Business Administration & Institute of Behavioral and Service Operations Management, Northeastern University, Shenyang, 110167, China; Key Laboratory of Data Analytics and Optimization for Smart Industry (Northeastern University), Ministry of Education, Shenyang, 110819, China; College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou, 310023, China","Jiang Z.-Z., School of Business Administration & Institute of Behavioral and Service Operations Management, Northeastern University, Shenyang, 110167, China, Key Laboratory of Data Analytics and Optimization for Smart Industry (Northeastern University), Ministry of Education, Shenyang, 110819, China; Wan M., School of Business Administration & Institute of Behavioral and Service Operations Management, Northeastern University, Shenyang, 110167, China; Pei Z., College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou, 310023, China; Qin X., School of Business Administration & Institute of Behavioral and Service Operations Management, Northeastern University, Shenyang, 110167, China","With the rapid development of e-commerce and the new retail, the same-day or even same-half day delivery service is provided to compete for market share. Recently, an increased number of e-commerce companies implement the unmanned smart warehouses to improve the logistics efficiency. In order to further reduce the demand response time, a novel picking strategy is designed to firstly split the orders, and then assign the partial orders to different pickers. After all the order segments have been collected, it is shipped to the customer. Due to the inherent complexity of the problem, a two stage optimization model is introduced. In the first stage, an order splitting and batching strategy based on spatial measure is proposed. And a MIP model is constructed to minimize the total picking distance, which is then solved via a column generation based algorithm. In the second stage, the newly formed batches are considered as a priori inputs, which are then assigned to automatic pickers. The picking process is modeled as a special parallel machine scheduling problem with multiple due dates for a single item, which could reduce to a customer order scheduling problem on parallel machines, and it is unary NP-complete. A heuristic method is proposed to obtain an approximate solution. Although the order splitting technique is not new in the logistics industry, the split orders are picked according to a vehicle routing problem, which fails to address the kitting issue for fast turnovers. In the numerical analysis section, the proposed algorithm is validated through extensive testing on various scales of instances. It is observed that the optimality gap for our algorithm is within 9%, and the computation time is around 5 min. Also, the average turnover rate increases by approximately 50% in comparison with the no-splitting policy. In most cases, the average order tardiness decreases by 90% compared with order splitting and no-kitting policy. © 2020 Elsevier Ltd","Column generation; Order kitting; Order splitting; Smart warehouse; Spatial and temporal heuristic","Competition; Electronic commerce; Linear programming; Sales; Scheduling; Vehicle routing; Warehouses; Approximate solution; Customer order scheduling; Inherent complexity; Logistics efficiency; Multiple due dates; Parallel machine-scheduling problems; Two-stage optimization models; Vehicle Routing Problems; Heuristic methods",{"$nulls":4},"Project of Promoting Talents in Liaoning Province, (XLYC1807252); National Natural Science Foundation of China, NSFC, (51305400, 52005447, 71520107004, 71621061, 71671033, 71871203, 71971052, 72071037, L1924063); Natural Science Foundation of Zhejiang Province, ZJNSF, (LY18G010017); Fundamental Research Funds for the Central Universities, (N2006006); Higher Education Discipline Innovation Project, (B16009)","This work is supported by the National Natural Science Foundation of China ( 71671033, 71971052 , 71871203 , 51305400 , L1924063 , 52005447 , 72071037 ), the Fund for Innovative Research Groups of the National Natural Science Foundation of China ( 71621061 ), the Major International Joint Research Project of the National Natural Science Foundation of China ( 71520107004 ), Zhejiang Provincial Natural Science Foundation of China under Grant No. LY18G010017 , the Fundamental Research Funds for the Central Universities ( N2006006 ), the Project of Promoting Talents in Liaoning Province (XLYC1807252) and the 111 Project (B16009).","Azizoglu M., Kirca O., Tardiness minimization on parallel machines, International Journal of Production Economics, 55, pp. 163-168, (1998); Boysen N., de Koster R., Weidinger F., Warehousing in the e-commerce era: A survey, European Journal of Operational Research, 277, pp. 396-411, (2019); Briant O., Cambazard H., Cattaruzza D., Catusse N., Ladier A.-L., Ogier M., An efficient and general approach for the joint order batching and picker routing problem, European Journal of Operational Research, (2020); Cergibozan C., Tasan A.S., Order batching operations: an overview of classification, solution techniques, and future research, Journal of Intelligent Manufacturing, 30, pp. 335-349, (2019); Ceven E., Gue K.R., Optimal wave release times for order fulfillment systems with deadlines, Transportation Science, 51, pp. 52-66, (2017); Chen T.-L., Cheng C.-Y., Chen Y.-Y., Chan L.-K., An efficient hybrid algorithm for integrated order batching, sequencing and routing problem, International Journal of Production Economics, 159, pp. 158-167, (2015); De Koster R.B., Le-Duc T., Zaerpour N., Determining the number of zones in a pick-and-sort order picking system, International Journal of Production Research, 50, pp. 757-771, (2012); 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Wu T.-H., A note on a global approach for general 0–1 fractional programming, European Journal of Operational Research, 101, pp. 220-223, (1997); Xu X., Ma Y., Zhou Z., Zhao Y., Customer order scheduling on unrelated parallel machines to minimize total completion time, IEEE Transactions on Automation Science and Engineering, 12, pp. 244-257, (2013); Yang J., The complexity of customer order scheduling problems on parallel machines, Computers & Operations Research, 32, pp. 1921-1939, (2005); Yu M., De Koster R.B., The impact of order batching and picking area zoning on order picking system performance, European Journal of Operational Research, 198, pp. 480-490, (2009)","Z. Pei; College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou, 310023, China; email: peizhi@zjut.edu.cn",null,"Elsevier Ltd",{"$nulls":5},3050548.0,null,"CMORA",null,"English","Comp. Oper. Res.","Article","Final",null,"Scopus","2-s2.0-85091638132"]
["Foo Y.J.; A-Jalil E.E.; Wan Mustaffa W.S.","Foo, Yee Jing (57218671986); A-Jalil, Emy E (56225882500); Wan Mustaffa, Wan Salmuni (57000513400)","57218671986; 56225882500; 57000513400","What's Up Omni? The relationship between omni-channel supply chain and logistics service quality in influencing online purchasing behaviour",2020.0,"International Journal of Supply Chain Management",9.0,4.0,null,643.0,650.0,7.0,4.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85089972696&partnerID=40&md5=7d847be987d9f2f2ddf1819413131bb3","School of Technology Management and Logistics, UUM College of Business, Universiti Utara Malaysia, UUM Sintok, Kedah, 06010, Malaysia; Technology Supply Chain Excellence Institute, School of Technology Management and Logistics, UUM College of Business, Universiti Utara Malaysia, UUM Sintok, Kedah, 06010, Malaysia; Faculty of Management and Economics, Universiti Pendidikan Sultan Idris, Malaysia","Foo Y.J., School of Technology Management and Logistics, UUM College of Business, Universiti Utara Malaysia, UUM Sintok, Kedah, 06010, Malaysia; A-Jalil E.E., Technology Supply Chain Excellence Institute, School of Technology Management and Logistics, UUM College of Business, Universiti Utara Malaysia, UUM Sintok, Kedah, 06010, Malaysia; Wan Mustaffa W.S., Faculty of Management and Economics, Universiti Pendidikan Sultan Idris, Malaysia","Consumer behavior had been affected by the evolution of digital technologies and the internet. Online shopping is becoming more popular, with e-commerce market growth that encourages the involvement of retailers. However, consumers' satisfaction is still the same as they request for a seamless and frictionless shopping experience, an 'Omni-channel supply chain.' Retailers need to understand the new phenomenon and how the concept is influencing customer purchasing behavior, especially online shopping. Several types of research had highlighted the importance of logistics service quality in predicting online purchasing behavior. Thus, this study investigates the relationship between the Omni-channel supply chain and logistics service quality in influencing online purchasing behavior. A survey-based approach is used to collect data from consumers about their perceptions. Overall, the study had enhanced the understanding of the relationship between the Omni-channel supply chain and logistics service quality with online purchasing behavior. Besides, the knowledge of online purchasing behavior in the Omni-channel context has enabled a retailer to allocate resources in designing new strategies. © ExcelingTech Pub, UK.","Logistics service quality; Omni-channel; Online purchasing behavior; Supply chain",{"$nulls":7},"Ma S., Fast or Free Shipping Options in Online and Omni-channel Retail? 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Ali M., Ahmed T., Absar S., Urban Youth Attitude toward Online Shopping: Evidence from Dhaka City, International Journal of Entrepreneurial Research, 19, 3, pp. 33-40, (2020); Sun I., Yoo D.K., Yang H.C., The Empirical Study of Logistics Service Quality Factors influencing Service Satisfaction on Supplying the Industrial Goods in the Tourism and Leisure Industry: Focusing on the Moderating Effects of Job Types, International Journal of u-and e-Service, Science and Technology, 9, 4, pp. 203-212, (2016); Akroush M.N., Mahadin B., ElSamen A.A., Shoter A., An empirical model of mobile shopping attitudes and intentions in an emerging market, International Journal of Web Based Communities, 16, 2, pp. 150-179, (2020); Weiland D., Omnichannel as a new challenge for logistics, Torun Business Review, 15, 4, pp. 69-78, (2016); Kasuma J., Kanyan A., Khairol M., Sa'ait N., Panit G., Factors Influencing Customers Intention for Online Shopping, International Journal of Modern Trends in Business Research;, 3, 11, pp. 31-41, (2020); Faisal A.S., Haque R., Pang A.K., Rahman A., Connie G., The Influence of e-Service Quality Dimensions on Customer Satisfaction and Purchase Intention: An Indian e-Market Perspective, Asian Journal of Technology & Management Research, (2020)",null,null,"ExcelingTech",{"$nulls":5},2.0513771E7,null,null,null,"English","Int. J. Supply Chain Manag.","Article","Final",null,"Scopus","2-s2.0-85089972696"]
["Liu Z.-Y.; Guo P.-T.","Liu, Zi-Yu (55550457400); Guo, Peng-Tao (57226442704)","55550457400; 57226442704","Supply Chain Decision Model Based on Blockchain: A Case Study of Fresh Food E-Commerce Supply Chain Performance Improvement",2021.0,"Discrete Dynamics in Nature and Society",2021.0,null,5795547.0,null,null,null,11.0,"10.1155/2021/5795547","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85111567072&doi=10.1155%2f2021%2f5795547&partnerID=40&md5=efa0d5947984c80f717e44a3e55c4fc9","School of Economics and Management, Hebei University of Science and Technology, Hebei, Shijiazhuang, 050018, China","Liu Z.-Y., School of Economics and Management, Hebei University of Science and Technology, Hebei, Shijiazhuang, 050018, China; Guo P.-T., School of Economics and Management, Hebei University of Science and Technology, Hebei, Shijiazhuang, 050018, China","Aiming at the problems in the performance improvement of the fresh food e-commerce supply chain, in this article, the author defines the constraints on the performance improvement of the fresh food e-commerce supply chain and determines the demand to improve performance in quality and safety, logistics traceability, resource integration, and benefit distribution. In addition, this article conducts coupling analysis on the characteristics of blockchain technology, such as intelligent contract, information sharing, traceability, and performance improvement requirements. The author embeds the alliance chain in the fresh food e-commerce supply chain and designs the blockchain information platform model from four levels: application layer, contract layer, network layer, and data layer, with the purpose of optimizing and improving the performance of the fresh food e-commerce supply chain. What is more, the Stackelberg game model between the supplier and the e-commerce platform was constructed to study and compare the profit changes of the fresh food e-commerce supply chain before and after the application of the blockchain information platform. Finally, the result of Stackelberg game is numerically simulated by Matlab software. The results show that blockchain technology is a booster for the development of the fresh food e-commerce supply chain to a higher stage of the whole industry chain management, coordination, and integration. Investing in the blockchain system within a certain budget range can not only improve the reliability of products, but also improve the performance of each main component of the fresh food e-commerce supply chain, as well as the overall performance. Results can offer a theoretical guidance for producer and retailer in investing in BIP, pricing decision, and supply chain coordination after applying BIP. © 2021 Zi-Yu Liu and Peng-Tao Guo.",{"$nulls":8},"Liu W., Study on consumers, Food Safety Risk Perception and Purchasing Behavior under Fresh E-Commerce, (2019); Shang J., Ji X., Optimization of ecological agricultural supply chain based on block chain application, Journal of South China Agricultural University (Social Science Edition), 19, 4, pp. 67-75, (2020); Zhou X., Influencing factors and optimization measures of supply chain overall performance, Journal of South-Central University for Nationalities (Humanities and Social Sciences), 1, pp. 41-42, (2004); Wu J., Research on supply chain management of autonomous fresh food E-commerce based on blockchain, Journal of Dali University, 5, 1, pp. 123-128, (2020); Van Der Vorst J.G.A.J., Beulens A.J.M., Van Beek P., Modelling and simulating multi-echelon food systems, European Journal of Operational Research, 122, 2, pp. 354-366, (2000); Joby George V., Pillai M., A study of factors affecting supply chain performance, ICAME, 2, pp. 018018-012018, (2019); Zan M., Chen G., Wang Z., Development of E-commerce of fresh agricultural products in China: Progress, Difficulties and Strategies on Economic Problems, 12, pp. 68-74, (2020); Moazzam M., Akhtar P., Garnevska E., Marr N.E., Measuring agri-food supply chain performance and risk through a new analytical framework: A case study of New Zealand dairy, Production Planning & Control, 29, 15, pp. 1258-1274, (2018); Odongo W., Dora M., Molnar A., Ongeng D., Gellynck X., Performance perceptions among food supply chain members, British Food Journal, 118, 7, pp. 1783-1799, (2016); Yadav S., Garg D., Luthra S., Development of IoT based data-driven agriculture supply chain performance measurement framework, Journal of Enterprise Information Management, 34, 1, pp. 292-327, (2020); Yadav S., Garg D., Implementing technology to improve stakeholder fairness perception, 18th International Symposium on Horticultural Economics and Management, 1132, pp. 105-112, (2016); Kaipia R., Dukovska-Popovska I., Loikkanen L., Creating sustainable fresh food supply chains through waste Reduction, International Journal of Physical Distribution & Logistics Management, 43, 3, pp. 262-276, (2013); Yeh T.-M., Pai F.-Y., Wu L.-C., Relationship stability and supply chain performance for SMEs: From internal, supplier, and customer integration perspectives, Mathematics, 8, 11, (2020); Saberi S., Kouhizadeh M., Sarkis J., Shen L., Blockchain technology and its relationships to sustainable supply chain management, International Journal of Production Research, 57, 7, pp. 2117-2135, (2019); Sikorski J.J., Haughton J., Kraft M., Blockchain technology in the chemical industry: Machine to machine electricity market, Applied Energy, 195, pp. 234-246, (2017); Zhou X., Zheng F., A research on the construction of agricultural product quality and safety traceability system based on the blockchain technology, Journal of Fujian Provincial Committee Party School of CPC (Fujian Academy of Governance), 1, 3, pp. 113-117, (2019); Salah K., Nizamuddin N., Jayaraman R., Omar M., Blockchain-based soybean traceability in agricultural supply chain, IEEE Access, 7, pp. 73295-73305, (2019); Alzahrani N., Blockchain-based intelligent contract for factoring business in supply chains, Annals of Operations Research, 1, (2020); Li P., Research on the circulation safety of fresh agricultural products in my country from the perspective of blockchain, Journal of Commercial Economics, 10, pp. 146-149, (2020); Park K.O., A study on sustainable usage intention of blockchain in the big data era: Logistics and supply chain management companies, Sustainability, 12, 24, (2020); Mei B., China's agricultural product cold chain logistics model and development countermeasures based on blockchain technology, Journal of Commercial Economics, 5, pp. 97-100, (2020); Tang D., Zhuang X., Decision-making of supply chain finance based on blockchain accounts receivables transfer platform, Systems Engineering, 37, 6, pp. 58-66, (2019); Gauthier J., Blockchain-based intelligent contract for factoring business in supply chains, Annals of Operations Research, 1, 1, (2020); Nandi M.L., Nandi S., Moya H., Kaynak H., Blockchain technology-enabled supply chain systems and supply chain performance: A resource-based view, Supply Chain Management: An International Journal, 25, 6, pp. 841-862, (2020); Hald K.S., Kinra A., How the blockchain enables and constrains supply chain performance, International Journal of Physical Distribution & Logistics Management, 49, 4, pp. 376-397, (2019); Chen H., Jia X., Jiang M., Research on deision-making of fresh agricultural supply chain with blockchain under behavior of misreportin, Computer Engineering and Applications, 55, 16, pp. 265-270, (2019); Zeng Y., Yuan P., Zhang Y., Decision-making analysis of fresh E-commerce supply chain with different dominant powers from the perspective of game theory, Journal of Nanjing Audit University, 16, 5, pp. 55-64, (2019); Liu P., Long Y., Song H.-C., He Y.-D., Investment decision and coordination of green agri-food supply chain considering information service based on blockchain and big data, Journal of Cleaner Production, 277, 1, (2020); Fu Y., Zhu J., Operation mechanism for G2B system based on blockchain, Tehnički Glasnik, 26, 6, pp. 1841-1852, (2019); Karamachoski J., Marina N., Jovan T.P., Blockchain-based application for certification management, Tehnički Glasnik, 14, 4, pp. 488-492, (2020)","Z.-Y. Liu; School of Economics and Management, Hebei University of Science and Technology, Shijiazhuang, Hebei, 050018, China; email: purpleyuliu@163.com",null,"Hindawi Limited",{"$nulls":5},1.0260226E7,null,null,null,"English","Discrete Dyn. Nat. Soc.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85111567072"]
["Wang Y.; Lei L.; Zhang D.; Lee L.H.","Wang, Yuan (57079310600); Lei, Linfei (57217164627); Zhang, Dongxiang (34267886900); Lee, Loo Hay (55667526300)","57079310600; 57217164627; 34267886900; 55667526300","Towards delivery-as-a-service: Effective neighborhood search strategies for integrated delivery optimization of E-commerce and static O2O parcels",2020.0,"Transportation Research Part B: Methodological",139.0,null,null,38.0,63.0,25.0,24.0,"10.1016/j.trb.2020.06.003","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85086593917&doi=10.1016%2fj.trb.2020.06.003&partnerID=40&md5=e280a7957a3844e4d11abfbf808c6f26","Department of Industrial Systems Engineering and Management, National University of Singapore, Singapore; School of Computer Science and Engineering, University of Electronic Science and Technology of China, China; School of Computer Science and Technology, Zhejiang University, China","Wang Y., Department of Industrial Systems Engineering and Management, National University of Singapore, Singapore; Lei L., School of Computer Science and Engineering, University of Electronic Science and Technology of China, China; Zhang D., School of Computer Science and Technology, Zhejiang University, China; Lee L.H., Department of Industrial Systems Engineering and Management, National University of Singapore, Singapore","In this paper, we investigate a new variant of last-mile delivery that integrates the scheduling of static E-commerce parcels and Online-to-Offline(O2O) parcels. The O2O parcels, such as flowers and cakes, are often delivered intra city with a time window constraint. It is driven by the concept of delivery-as-a-service, which targets at building consolidated infrastructure and using the same fleet of vehicles to provide standardized delivery services for different types of merchants. We formulate it as an integration of Multi-Depot Multi-Trip Vehicle Routing Problem (MDMTVRP) and Paired Pickup and Delivery Problem with Time Window (PPDPTW). To solve the mixed problem of MDMTVRP and PPDPTW, we present its Mixed-Integer Programming (MIP) model to obtain the optimal solution for small-scale instances. To solve large-scale problems, we propose a hybrid neighborhood search strategy to effectively combine the merits of ALNS and tabu search. We also present a two-level pruning strategy that can significantly accelerate the local search procedure. We conduct extensive numeric experiments on multiple datasets, and results showed that our hybrid approach achieved near-optimal performance and established clear superiority over ALNS and tabu search. © 2020","Hybrid local search; Multi-depot multi-trip VRP; Pickup-and-delivery with time window; Space pruning","Electronic commerce; Fleet operations; Tabu search; Vehicle routing; Large-scale problem; Mixed integer programming model; Multiple data sets; Near-optimal performance; Neighborhood search; Pickup and delivery problem with time windows; Time window constraint; Vehicle Routing Problems; data set; electronic commerce; integrated approach; methodology; optimization; performance assessment; service sector; transportation infrastructure; travel behavior; Integer programming",{"$nulls":6},"Azadian F., Murat A., Chinnam R.B., An unpaired pickup and delivery problem with time dependent assignment costs: application in air cargo transportation, Eur. J. Oper. 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Sci., 47, 1, pp. 64-80, (2013); Taillard E., Badeau P., Gendreau M., Guertin F., Potvin J.-Y., A tabu search heuristic for the vehicle routing problem with soft time windows, Transp. Sci., 31, 2, pp. 170-186, (1997); Vinsensius A., Wang Y., Chew E.P., Lee L.H., Dynamic incentive mechanism for delivery slot management in e-commerce attended home delivery, Transp. Sci., 54, 3, pp. 567-587, (2020); Wang Y., Zhang D., Liu Q., Shen F., Lee L.H., Towards enhancing the last-mile delivery: an effective crowd-tasking model with scalable solutions, Transp. Res. Part E, 93, pp. 279-293, (2016); Wang Y., Zhang D., Liu Y., Dai B., Lee L.H., Enhancing transportation systems via deep learning: asurvey, Transp. Res. Part C, 99, pp. 144-163, (2019); Yu B., Yang Z.-Z., Xie J.-X., A parallel improved ant colony optimization for multi-depot vehicle routing problem, J. Oper. Res. Soc., 62, 1, pp. 183-188, (2011); Zhang Y., Sun L., Hu X., Zhao C., Order consolidation for the last-mile split delivery in online retailing, Transp. Res. Part E, 122, pp. 309-327, (2019); Zulj I., Kramer S., Schneider M., A hybrid of adaptive large neighborhood search and tabu search for the order-batching problem, Eur. J. Oper. Res., 264, 2, pp. 653-664, (2018)","D. Zhang; School of Computer Science and Technology, Zhejiang University, China; email: zhangdongxiang@zju.edu.cn",null,"Elsevier Ltd",{"$nulls":5},1912615.0,null,null,null,"English","Transp. Res. Part B Methodol.","Article","Final",null,"Scopus","2-s2.0-85086593917"]
["Buldeo Rai H.; Verlinde S.; Macharis C.","Buldeo Rai, Heleen (57195135422); Verlinde, Sara (55970308800); Macharis, Cathy (6507193118)","57195135422; 55970308800; 6507193118","Who is interested in a crowdsourced last mile? A segmentation of attitudinal profiles",2021.0,"Travel Behaviour and Society",22.0,null,null,22.0,31.0,9.0,44.0,"10.1016/j.tbs.2020.08.004","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85089524049&doi=10.1016%2fj.tbs.2020.08.004&partnerID=40&md5=bc06cf6d1b4f2b9bee257cfd3dd0e0b9","Vrije Universiteit Brussel, Research Group MOBI, Pleinlaan 2, Brussels, 1050, Belgium","Buldeo Rai H., Vrije Universiteit Brussel, Research Group MOBI, Pleinlaan 2, Brussels, 1050, Belgium; Verlinde S., Vrije Universiteit Brussel, Research Group MOBI, Pleinlaan 2, Brussels, 1050, Belgium; Macharis C., Vrije Universiteit Brussel, Research Group MOBI, Pleinlaan 2, Brussels, 1050, Belgium","Online and omnichannel retail developments placed logistics at the front-end of consumers’ purchase journeys. Particularly the last mile of the supply chain increasingly affects consumer satisfaction, while its financial and environmental impact is critical. “Crowd logistics” is introduced as a promising solution. As consumers are increasingly driving innovation and initiatives in the last mile, it is important to know their preferences and perceptions. Our objective is to identify which type of consumer is interested in a crowdsourced last mile and which particular crowd logistics services are considered interesting. To this end, we set up a survey among a sample of one-thousand consumers that represent the Belgian population. The survey is analysed using descriptive statistics and two-step cluster analysis. Analysis shows that consumers support neighbour relays and delivery by retailers’ employees, but general interest is low. A cluster analysis identifies four attitudinal profiles. One segment, labelled the “trailblazers”, are most likely to adopt crowdsourced last mile services: they strongly prefer delivery at home and rely on their community of neighbours when a delivery fails. They are more interested in last mile innovations and sustainability enhancements. The research contributes by taking a consumer perspective on the last mile and by including three types of services and four types of crowd. Three recommendations for retailers are formulated, to focus on a crowdsourcing solution that combines collection and delivery among their employees’ local network, to target consumers that fit the identified profile and to accentuate crowd logistics’ quality of enhancing information transparency. © 2020 Hong Kong Society for Transportation Studies","Consumer preferences; Crowdsourcing; E-commerce; Last mile delivery; Omnichannel retail; Sharing economy",{"$nulls":5},"Innoviris Anticipate; Innoviris","This work is supported by the Innoviris Anticipate programme: prospective research for Brussels-Capital Region, and the retail group. The authors would like to thank the retail group for the opportunity to carry out this research.","Ailawadi K.L., Farris P.W., Managing multi- and omni-channel distribution: metrics and research directions, J. Retail., 93, 1, pp. 120-135, (2017); Akeb H., Moncef B., Durand B., Building a collaborative solution in dense urban city settings to enhance parcel delivery: An effective crowd model in Paris, Transp. Res. Part E: Logist. Transp. Rev., 119, pp. 223-233, (2018); Archetti C., Savelsbergh M., Speranza M.G., The vehicle routing problem with occasional drivers, Eur. J. Oper. Res., 254, 2, pp. 472-480, (2016); Benkler Y., Sharing Nicely: On shareable goods and the emergence of sharing as a modality of economic production, Yale Law J., 114, 2, (2004); Borsenberger C., The Sharing Economy and the ‘Uberization’ Phenomenon: What Impacts on the Economy in General and for the Delivery Operators in Particular, The Changing Postal and Delivery Sector: Towards A Renaissance, pp. 191-203, (2017); Botsman R., Crowdshipping: Using the crowd to transform delivery, AFR Boss Magazine, (2014); Buldeo Rai H., Verlinde S., Macharis C., Shipping outside the box. Environmental impact and stakeholder analysis of a crowd logistics platform in Belgium, J. Cleaner Prod., 202, pp. 806-816, (2018); Buldeo Rai H., Verlinde S., Macharis C., The “next day, free delivery” myth unravelled: Possibilities for sustainable last mile transport in an omnichannel environment, Int. J. Retail. Distrib. Mgt., 47, 1, pp. 39-54, (2019); Buldeo Rai H., Verlinde S., Macharis C., City logistics in an omnichannel environment. The case of Brussels, Case Stud. Transport Policy, 7, 2, pp. 310-317, (2019); Buldeo Rai H., Verlinde S., Merckx J., Macharis C., Crowd logistics: an opportunity for more sustainable urban freight transport?, Eur. Transp. Res. Rev., 9, 3, (2017); Buldeo Rai H., Verlinde S., Merckx J., Macharis C., City Logistics 3: Towards Sustainable and Liveable Cities, pp. 89-108, (2018); Carbone V., Rouquet A., Roussat C., The rise of crowd logistics: A new way to co-create logistics value, J. 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Log Manage, 49, 2, pp. 217-238, (2019); Wang X., Yuen K.F., Wong Y.D., Teo C.-C., E-consumer adoption of innovative last-mile logistics services: A comparison of behavioural models, Total Quality Manage. Business Excellence, 31, 11-12, pp. 1381-1407, (2018); Wang X., Yuen K.F., Wong Y.D., Teo C.C., An innovation diffusion perspective of e-consumers’ initial adoption of self-collection service via automated parcel station, Int. J. Logist. Manage., 29, 1, pp. 237-260, (2018); Wang Y., Zhang D., Liu Q., Shen F., Lee L.H., Towards enhancing the last-mile delivery: An effective crowd-tasking model with scalable solutions, Transp. Res. Part E: Logist. Transport. Rev., 93, pp. 279-293, (2016); Yuen K.F., Wang X., Ma F., Wong Y.D., The determinants of customers’ intention to use smart lockers for last-mile deliveries, J. Retail. Consumer Services, 49, pp. 316-326, (2019); Zhang M., Xia Y., Li S., Wu W., Wang S., “Crowd logistics platform's informative support to logistics performance: Scale development and empirical examination.”, Sustainability, 11, 2, (2019)","H. Buldeo Rai; Vrije Universiteit Brussel, Research Group MOBI, Brussels, Pleinlaan 2, 1050, Belgium; email: heleen.buldeo.rai@vub.be",null,"Elsevier Ltd",{"$nulls":5},"2214367X",null,null,null,"English","Travel Behav. Soc.","Article","Final",null,"Scopus","2-s2.0-85089524049"]
["Tandon U.; Ertz M.; Sakshi K.","Tandon, Urvashi (57190029593); Ertz, Myriam (56816944900); Sakshi, Khanna (57219474677)","57190029593; 56816944900; 57219474677","POD Mode of Payment, Return Policies and Virtual-Try-on Technology as Predictors of Trust: An Emerging Economy Case",2021.0,"Journal of Promotion Management",27.0,6.0,null,832.0,855.0,23.0,17.0,"10.1080/10496491.2021.1888174","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85101858361&doi=10.1080%2f10496491.2021.1888174&partnerID=40&md5=ed5fb072893ea5c120729c4ca2c138b0","Chitkara University, Punjab, India; LaboNFC, Université du Québec à Chicoutimi, Chicoutimi, QC, Canada; Fortune Institute of International Business, New Delhi, India","Tandon U., Chitkara University, Punjab, India; Ertz M., LaboNFC, Université du Québec à Chicoutimi, Chicoutimi, QC, Canada; Sakshi K., Fortune Institute of International Business, New Delhi, India","This study examines virtual-try-on technology (VTO), return policy, and pay-on-delivery (POD) mode of payment as predictors of trust in an online context. The study further investigates trust as an influencer of repurchase intentions while positing habit as a moderator of the relationship between trust and repurchase intention. Data was collected through a self-administered and structured questionnaire targeting online shoppers in North Indian states. A sample of 424 online shoppers was considered in this research. Structural Equation Modeling (SEM) was used to evaluate the constructs. CFA was applied to calculate validity and composite reliability. To examine the hypothesized relationships, path analysis was carried out. The results confirmed that both return policies and POD are significant predictors of trust. Interestingly, VTO has no significant effect on trust, while habit strengthens the positive relationship between trust and repurchase intentions. © 2021 Taylor & Francis Group, LLC.","habit; online shopping; POD mode of payment (POD); return policy; Trust; virtual-try-on technology",{"$nulls":7},"Agag G., El-Masry A.A., Understanding the determinants of hotel booking intentions and moderating role of habit, International Journal of Hospitality Management, 54, pp. 52-67, (2016); Almousa M., Consumer experience of 3D body scanning technology and acceptance of related e-commerce market applications in Saudi Arabia, The Journal of the Textile Institute, 111, 9, pp. 1300-1307, (2020); Anjum S., Chai J., Drivers of cash-on-delivery method of payment in e-commerce shopping: Evidence from Pakistan, SAGE Open, 10, 3, (2020); Armstrong J.S., Overton T.S., Estimating nonresponse bias in mail surveys, Journal of Marketing Research, 14, 3, pp. 396-402, (1977); Baytar F., Chung T.L.D., Shin E., Can augmented reality help e-shoppers make informed purchases on apparel fit, size, and product performance?, International Textile and Apparel Association Annual Conference Proceedings, 73, 1, pp. 1-2, (2016); (1988); Beck M., Crie D., I virtually try it…Iwantit! 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A cross-cultural comparison study between China and the United States, Journal of Promotion Management, 23, 5, pp. 748-768, (2017); Zhang T., Wang W.Y.C., Cao L., Wang Y., The role of virtual try-on technology in online purchase decision from consumers’ aspect, Internet Research, 29, 3, pp. 529-551, (2019)",null,null,"Routledge",{"$nulls":5},1.0496491E7,null,null,null,"English","J. Promot. Manage.","Article","Final",null,"Scopus","2-s2.0-85101858361"]
["Vasić N.; Kilibarda M.; Andrejić M.; Jović S.","Vasić, Nebojša (57220121925); Kilibarda, Milorad (35368337500); Andrejić, Milan (55251649500); Jović, Srđan (57204096420)","57220121925; 35368337500; 55251649500; 57204096420","Satisfaction is a function of users of logistics services in e-commerce",2021.0,"Technology Analysis and Strategic Management",33.0,7.0,null,813.0,828.0,15.0,26.0,"10.1080/09537325.2020.1849610","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85096968213&doi=10.1080%2f09537325.2020.1849610&partnerID=40&md5=7756a3f5dcec7eaa2930a6e68cca5084","Department of road traffic, Technical College of Applied Sciences Uroševac, Leposavić, Serbia; Faculty of Transport and Traffic Engineering, Department of logistics, University of Belgrade, Belgrade, Serbia; Faculty of Technical Sciences in Kosovska Mitrovica, University of Pristina, Kosovska Mitrovica, Serbia","Vasić N., Department of road traffic, Technical College of Applied Sciences Uroševac, Leposavić, Serbia; Kilibarda M., Faculty of Transport and Traffic Engineering, Department of logistics, University of Belgrade, Belgrade, Serbia; Andrejić M., Faculty of Transport and Traffic Engineering, Department of logistics, University of Belgrade, Belgrade, Serbia; Jović S., Faculty of Technical Sciences in Kosovska Mitrovica, University of Pristina, Kosovska Mitrovica, Serbia","Customer satisfaction in e-commerce directly depends on diverse dimensions of logistics services. In the market, there is a constant dilemma which logistics service dimensions affect customer satisfaction in e-commerce. The aim of the paper is to determine how certain dimensions of logistics services affect customer satisfaction in e-commerce. Thus, a methodological approach has been developed, as well as an original measuring instrument with eight dimensions: availability, delivery time, shipping costs, delivery reliability, product quality and condition, consumer complaints and return policy, information quality, and e-customers’ perception and satisfaction, with 31 items in total. The model is based on Confirmatory Factor Analysis (CFA) and Partial Least Squares method (PLS) and has been applied on the market of Serbia. A web survey was conducted on a sample of 425 respondents, i.e. final consumers who have used e-commerce services significantly in recent years. The obtained results clearly indicate that the satisfaction of e-commerce consumers directly depends on the observed dimensions of logistics service. The developed procedure and measuring instrument represent a concrete scientific contribution to better understanding of the dimensions of logistics service and customer satisfaction in e-commerce. The measuring instrument can be used to increase the satisfaction of e-commerce clients. © 2020 Informa UK Limited, trading as Taylor & Francis Group.","confirmatory factor analysis (CFA); Customer satisfaction; E-commerce; logistics service dimensions; SmartPLS 3","Serbia; consumption behavior; electronic commerce; factor analysis; information and communication technology; logistics; market conditions; reliability analysis; service quality",{"$nulls":4},"Ministarstvo Prosvete, Nauke i Tehnološkog Razvoja, MPNTR, (TR 36006)","This paper was supported by the Ministry of Education, Science and Technological development of the Republic of Serbia, through the project TR 36006.","Armstrong G., Kotler P., Marketing an Introduction, (2009); Armstrong J.S., Overton T.S., Estimating Nonresponse Bias in Mail Surveys, Journal of Marketing Research, 14, 3, pp. 396-402, (1977); Bagozzi R.P., Yi Y., On the Evaluation of Structural Equation Models, Journal of the Academy of Marketing Science, 16, 1, pp. 74-94, (1988); 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Xing Y., Grant D.B., McKinnon A.C., Fernie J., The Interface Between Retailers and Logistics Service Providers in the Online Market, European Journal of Marketing, 45, 3, pp. 334-357, (2011); Zeithaml V.A., Parasuraman A., Malhotra A., Service Quality Delivery Through web Sites: a Critical Review of Extant Knowledge, Journal of the Academy of Marketing Science, 30, 4, pp. 362-375, (2002); Ziaullah M., Feng Y., Akhter S.N., E-Loyalty: The Influence of Product Quality and Delivery Services on e-Trust and e-Satisfaction in China, International Journal of Advancements in Research & Technology, 3, 10, pp. 20-31, (2014)","S. Jović; Faculty of Technical Sciences in Kosovska Mitrovica, University of Pristina, Kosovska Mitrovica, Kneza Milosa 7, 38 220, Serbia; email: srdjanjovic2016@hotmail.com",null,"Routledge",{"$nulls":5},9537325.0,null,null,null,"English","Technol. Anal. Strateg. Manage.","Article","Final",null,"Scopus","2-s2.0-85096968213"]
["Raviya K.; Mary Vennila S.","Raviya, K. (57217538188); Mary Vennila, S. (20436157700)","57217538188; 20436157700","An Implementation of Hybrid Enhanced Sentiment Analysis System using Spark ML Pipeline: A Big Data Analytics Framework",2021.0,"International Journal of Advanced Computer Science and Applications",12.0,5.0,null,323.0,329.0,6.0,5.0,"10.14569/IJACSA.2021.0120540","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85107606856&doi=10.14569%2fIJACSA.2021.0120540&partnerID=40&md5=65ae0492425d56d7a509d2f3b4a968c1","Research Scholar, PG and Research Department of Computer Science, Presidency College, Chennai, India; Associate Professor and Research Supervisor, PG & Research Department of Computer Science Presidency College, Chennai, India","Raviya K., Research Scholar, PG and Research Department of Computer Science, Presidency College, Chennai, India; Mary Vennila S., Associate Professor and Research Supervisor, PG & Research Department of Computer Science Presidency College, Chennai, India","Today, we live in the Big Data age. Social networks, online shopping, mobile data are main sources generating huge text data by users. This \"text data\" will provide companies with useful insight on how customers view their brand and encourage them to make business strategies actively in order to maintain their trade. Hence, it is essential for the enterprises to analyse the sentiments of social media big data to make predictions. Because of the variety and existence of data, the study of sentiment on broad data has become difficult. However, it includes opensource Big Data platforms and machine learning techniques to process large text information in real-time. The advancement in fields including Big Data and Deep Learning technology has influenced and overcome the traditional restrictions of distributed computing. The primary aim is to perform sentiment analysis on the pipelined architecture of Apache Spark ML to speed upward the computations and improve machine efficiency in different environments. Therefore, the Hybrid CNN-SVM model is designed and developed. Here, CNN is pipeline with SVM for sentiment feature extraction and classification in ML to improve the accuracy. It is more flexible, fast and scalable. In addition, Naive Bayes, Support Vector Machines (SVM), Random Forest, Logistic Regression classifiers have been used to measure the efficiency of the proposed system on multi-node environment. The experimental results demonstrate that in terms of different evaluation metrics, the hybrid sentiment analysis model outperforms the conventional models. The proposed method makes it convenient for effective handling of big sentiment datasets. It would be more beneficial for corporations, government and individuals to improve their great value. © 2021. All Rights Reserved.","apache spark; Big data; machine learning; ML pipeline; sentiment analysis","Big data; Decision trees; Deep learning; Efficiency; Logistic regression; Random forests; Sentiment analysis; Support vector machines; Analysis system; Apache spark; Business strategy; ML pipeline; Mobile data; Online shopping; Sentiment analysis; Social media; Support vectors machine; Text data; Pipelines",{"$nulls":6},"Lenka Venkata S., A Survey on Challenges and Advantages in Big Data, 8491, pp. 115-119, (2015); Ramesh R, Divya G, Divya D, Kurian Merin K, Vishnuprabha V, Big Data Sentiment Analysis using Hadoop, IJIRST, 1, 11, pp. 92-98, (2015); Guller Mohammed, Big Data Analytics with Spark, (2015); Zainuddin Nurulhuda, Selamat Ali, Sentiment Analysis Using Support Vector Machine, IEEE International Conference on Computer, Communication, and Control Technology (I4CT 2014), pp. 333-337, (2014); Mehta Rajat, Big Data Analytics with Java, (2017); Al-Barznji Kamal, Atanassov Atanas, A Framework for Cloud Based Hybrid Recommender System for Big Data Mining, a journal of \"Science, Engineering & Education, 2, 1, pp. 58-65, (2017); Bell Jason, Machine Learning: Hands-On for Developers and Technical Professionals, (2015); Baltas A., Kanavos A., Tsakalidis A. K., An apache spark implementation for sentiment analysis on twitter data, International Workshop of Algorithmic Aspects of Cloud Computing, pp. 15-25; Kaluza Bostjan, Machine Learning in Java, (2016); Pentreath Nick, Machine Learning with Spark, (2015); Sayed Hend, Abdel-Fattah Manal A., Kholief Sherif, Predicting Potential Banking Customer Churn using Apache Spark ML and MLlib Packages“, A Comparative Study, IJACSA) International Journal of Advanced Computer Science and Applications, 9, pp. 674-677, (2018); Al-Saqqaa b, Al-Naymata Ghazi, Awajan Arafat, A Large-Scale Sentiment Data Classification for Online Reviews Under Apache Spark, The 9th International Conference on Emerging Ubiquitous Systems and Pervasive Networks, (2018); Al-Barznji Kamal, Atanassov Atanas, Big Data Sentiment Analysis Using Machine Learning Algorithms, Proceedings of 26th International Symposium \"Control of Energy, Industrial and Ecological Systems, (2018); Hochreiter S., Schmidhuber J., Long short-term memory, Neural computation, 9, 8, pp. 1735-1780, (1997); Almuqren L., Cristea A., Framework for sentiment analysis of Arabic text, Proceedings of the 27th ACM Conference on Hypertext and Social Media, pp. 315-317, (2016); Al-Horaibi L., Khan M., Sentiment Analysis of Arabic Tweets Using Semantic Resources, International Journal of Computing and Information Sciences, 13, 1, pp. 9-18, (2017); Alsheikh M.A., Niyato D., Lin S., Tan H.-P., Han Z., Mobile Big Data Analytics Using Deep Learning and ApacheSpark, pp. 22-29, (2016)",null,null,"Science and Information Organization",{"$nulls":5},"2158107X",null,null,null,"English","Intl. J. Adv.  Comput. Sci. Appl.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85107606856"]
["Ünver Ş.; Alkan Ö.","Ünver, Şeyda (57217095264); Alkan, Ömer (55759376500)","57217095264; 55759376500","Determinants of e-Commerce Use at Different Educational Levels: Empirical Evidence from Turkey e-Commerce Use at Different Educational Levels",2021.0,"International Journal of Advanced Computer Science and Applications",12.0,3.0,null,40.0,49.0,9.0,8.0,"10.14569/IJACSA.2021.0120305","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85103699990&doi=10.14569%2fIJACSA.2021.0120305&partnerID=40&md5=732270750ac4400e308a9c32a7532ba0","Department of Econometrics Ataturk University, Erzurum, Turkey","Ünver Ş., Department of Econometrics Ataturk University, Erzurum, Turkey; Alkan Ö., Department of Econometrics Ataturk University, Erzurum, Turkey","Rapid spread of internet has made e-commerce an essential and effective tool for commercial transactions. The purpose of this study is to investigate e-commerce use differences between individuals in Turkey according to their educational levels and to specify the relationship between demographic characteristics of individuals and e-commerce use. In this study, the cross-sectional data obtained by Household Information Technologies Usage Survey were used. Binary logistic regression analysis was utilized to determine the factors associated with the e-commerce use of individuals. This study has concluded that the variables of income level, age, gender, occupation, region, social media use, use of internet banking, use of e-government, number of information equipment in a household and the number of people in a household have relationships with e-commerce use. In addition, it has been found out that the variables in e-commerce use showed differences according to educational levels of individuals. It has been determined as a result of this study that as the education level of the individuals increased, their tendency towards online shopping increased. Higher education level refers to higher income level at both state and private institutions and more perception towards innovations. This has naturally a positive effect on online shopping behaviors of individuals. © 2021","binary logistic regression; e-commerce; educational level; Electronic commerce; online shopping; Turkey","e-government; E-learning; Logistic regression; Binary logistic regression; Commercial transactions; Demographic characteristics; E- commerces; Educational levels; Effective tool; Income levels; Information technology usages; Online shopping; Turkey; Electronic commerce",{"$nulls":4},"Turkish Statistical Institute","The authors would like to thank the Turkish Statistical Institute for the data. 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The moderating role of subjective and objective knowledge, British Food Journal, 11, 2, pp. 275-288, (2019); Duroy D., Gorse P., Lejoyeux M., Characteristics of online compulsive buying in Parisian students, Addictive Behaviors, 39, 12, pp. 1827-1830, (2014); Akman I., Et al., E-Gov: A global perspective and an empirical assessment of citizens’ attributes, Government Information Quarterly, 22, 2, pp. 239-257, (2005); Hossein K.M., Et al., Factors Associated to Online Shopping at the BoP Community in Rural Bangladesh, International Journal of Advanced Computer Science and Applications, 8, 10, pp. 46-51, (2017); Stranahan H., Kosiel D., E ‐ tail spending patterns and the importance of online store familiarity, Internet Research, 17, 4, pp. 421-434, (2007); Leong L.-Y., Jaafar N.I., Ainin S., Understanding Facebook Commerce (F-Commerce) Actual Purchase from an Artificial Neural Network Perspective, Journal of Electronic Commerce Research, 19, 1, pp. 75-103, (2018)",null,null,"Science and Information Organization",{"$nulls":5},"2158107X",null,null,null,"English","Intl. 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["Garg C.P.","Garg, Chandra Prakash (57038581800)",5.70385818E10,"A robust hybrid decision model to evaluate critical factors of reverse logistics implementation using Grey-DEMATEL framework",2020.0,"OPSEARCH",57.0,3.0,null,837.0,873.0,36.0,11.0,"10.1007/s12597-020-00453-w","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85085278236&doi=10.1007%2fs12597-020-00453-w&partnerID=40&md5=98ffc3a8a036eb81d8f0c34c78e85a72","Department of Operations Management, Indian Institute of Management Rohtak, Rohtak, 124010, Haryana, India","Garg C.P., Department of Operations Management, Indian Institute of Management Rohtak, Rohtak, 124010, Haryana, India","The rising electronics waste (e-waste), increased pollution, disposal issues and exploitation of natural resources have augmented ecological and resource scarcity problems. These problems can be abate by adopting reverse logistics (RL) implementation so, the environmental protection and resource recovery options such as reuse, refurbish, recycle, remanufacturing and proper disposal can be executed to deal and manage with the e-waste. The goal of this research work is to identifies, evaluate and analyze the factors for successful implementation of RL practices. Fifteen critical RL factors are recognized from pertinent literature and endorsed by industry professionals. This paper utilized Grey based Decision Making Trial and Evaluation Laboratory (DEMATEL) approach to sort the identified factors into cause and effect clusters. Grey DEMATEL resolves the problem of data uncertainty and impreciseness involves in decision making in analyzing the factors. The results of the study found that 11 RL factors came into causal cluster as vital factors and 4 RL factors into the effect cluster as fundamental problems factors. Among causal cluster, the highest ranked four influential factors are Top management commitment (RLF1) with weightage value 0.7604, RLF2 i.e. enforced government regulations with weightage value 0.6549, RLF6 i.e. environmental/green concerns factor with weightage value 0.5678 and RLF8 i.e. Waste minimization (especially e-waste) factor with weightage value 0.5113 are respectively. Similarly, among effect cluster, the most easily influenced two factors are “Market and competition factors” (RLF15) with weightage value (− 1.1207) and “Increased e-commerce” (RLF13) with weightage value (− 1.2855) respectively. A case example of an Indian electronics firm is taken to showcase the application of the proposed model. This paper can help supply chain managers and analysts in superior understanding of critical factors and increase the chances of practicing more effective and successful RL implementation in electronics industry. At the end, few key country and industry-specific recommendations are offered to support major decision for management and policy makers to embrace and successfully accomplish the reverse supply chain practices in India. © 2020, Operational Research Society of India.","Decision Making Trial and Evaluation Laboratory (DEMATEL); Electronics industry; Grey set theory; India; Reverse logistics factors (RLFs); Supply chain (SC)",{"$nulls":5},"Indian Institute of Management Rohtak","The author would like to thank the Editor-in-chief, Managing Editor and two anonymous referees for their valuable suggestions, which have been of great help in improving the quality of this paper. This research does not involve any financial support. Author acknowledges thanks for the support to the research facilities provided by the employer, Indian Institute of Management Rohtak, Management City NH-10 Southern Bypass, Sunaria, Rohtak-124010, Haryana, India. 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["Brand C.; Schwanen T.; Anable J.","Brand, Christian (23018199200); Schwanen, Tim (6603601123); Anable, Jillian (23007448200)","23018199200; 6603601123; 23007448200","‘Online Omnivores’ or ‘Willing but struggling’? Identifying online grocery shopping behavior segments using attitude theory",2020.0,"Journal of Retailing and Consumer Services",57.0,null,102195.0,null,null,null,43.0,"10.1016/j.jretconser.2020.102195","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85086505804&doi=10.1016%2fj.jretconser.2020.102195&partnerID=40&md5=e0db1a6516ca40a8c3c2f93aaa3fddab","Transport Studies Unit, University of Oxford, South Parks Road, Oxford, OX1 3QY, United Kingdom; Institute for Transport Studies, University of Leeds, 34-40 University Road, Leeds, LS2 9JT, United Kingdom","Brand C., Transport Studies Unit, University of Oxford, South Parks Road, Oxford, OX1 3QY, United Kingdom; Schwanen T., Transport Studies Unit, University of Oxford, South Parks Road, Oxford, OX1 3QY, United Kingdom; Anable J., Institute for Transport Studies, University of Leeds, 34-40 University Road, Leeds, LS2 9JT, United Kingdom","The landscape of grocery shopping is changing fast. Online retailing via home delivery or ‘click and collect’, convenience stores and various hybrid shopping channels are gaining popularity with some consumers, but not with others. The central premise of this paper is that focusing on the ‘average grocery shopper’ is not very helpful if the objective is to understand recent and future changes in grocery shopping. There are few recent studies that have identified groups of individuals using online and multi-channel shopping by considering both observable behavior and associated attitudes – feelings, beliefs, opinions and behavioral dispositions – and by drawing explicitly on attitude theories from social psychology. The current paper thus aims to identify and describe groups of grocery shoppers using a psychographic segmentation approach that is explicitly grounded in the Theory of Planned Behavior (TPB) (Ajzen, 1991) and its close cousin, the Technology Acceptance Model (TAM) (Davis et al., 1989). Primary data were collected through a self-completion questionnaire that produced a largely representative study sample of 2032 grocery shoppers across the United Kingdom, Europe's largest market for online grocery shopping. A principal component and two stage cluster analysis methodology was implemented to identify five well-defined and highly interpretable segments according to their attitudes, norms, perceptions and beliefs, then profiled by their socio-economic and grocery shopping characteristics. The segments reveal a range of different grocery shopping preference levels, from those ‘super-shoppers’ (Flynn and Goldsmith, 2016) who are clearly attracted to the online experience and want more (‘Intensive Urbanites’, ‘Online Omnivores’) to those who appear resistant and socially responsible towards the adoption of online shopping services (‘Resisting and Responsible’). The key distinguishing features of these segments suggest that shoppers might be attracted to or repelled from online shopping for reasons of convenience, perceived benefits, costs and risks, technology affect, time pressures and fit into daily schedules (perceived behavioral control), as well as social and environmental dimensions of personal norms and beliefs. © 2020 Elsevier Ltd","Attitude theory; Consumer segmentation; Grocery shopping; Psychographic segmentation; Technology acceptance framework","computer simulation; innovation; Internet; retailing; social media; supermarket; technological development; technology adoption",{"$nulls":4},"Engineering and Physical Sciences Research Council, EPSRC, (EP/K00915X/1, EP/L024756/1); Research Councils UK, RCUK","The research supporting this paper was undertaken for the UK Centre for Sustainable Road Freight and UK Energy Research Centre . CB and TS received funding by the UK Research Councils ( EPSRC grant number EP/K00915X/1 ). CB and JA received funding by the UK Research Councils ( EPSRC grant number EP/L024756/1 ). The authors acknowledge the helpful input of the editor, associate editor and reviewers. In addition, the authors thank the many participants of the online panel survey and Accent Marketing & Research Limited for administering the survey. ","Ajzen I., The theory of planned behavior, Organ. Behav. Hum. Decis. Process., 50, 2, pp. 179-211, (1991); Anable J., Complacent Car Addicts' or 'Aspiring Environmentalists'? Identifying travel behavior segments using attitude theory, Transport Pol., 12, 1, pp. 65-78, (2005); Asger Nielsen N., Ramus K., Online grocery retailing: what do consumers think?, Internet Res., 15, 3, pp. 335-352, (2005); Atkins K.G., Kumar A., Kim Y.-K., Smart grocery shopper segments, J. Int. Consum. Market., 28, 1, pp. 42-53, (2016); Babin B.J., Darden W.R., Griffin M., Work and/or fun: measuring hedonic and utilitarian shopping value, J. Construct. 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["Praet S.; Martens D.","Praet, Stiene (57208554920); Martens, David (14034052100)","57208554920; 14034052100","Efficient Parcel Delivery by Predicting Customers’ Locations*",2020.0,"Decision Sciences",51.0,5.0,null,1202.0,1231.0,29.0,12.0,"10.1111/deci.12376","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85065102016&doi=10.1111%2fdeci.12376&partnerID=40&md5=f16b933bef9d0f21b4fcfc19e91596ae","Department of Engineering Management, University of Antwerp, Prinsstraat 13, Antwerp, 2000, Belgium","Praet S., Department of Engineering Management, University of Antwerp, Prinsstraat 13, Antwerp, 2000, Belgium; Martens D., Department of Engineering Management, University of Antwerp, Prinsstraat 13, Antwerp, 2000, Belgium","An important aspect of the growing e-commerce sector involves the delivery of tangible goods to the end customer, the so-called last mile. This final stage of the logistics chain remains highly inefficient due to the problem of failed deliveries. To address this problem, delivery service providers can apply data science to determine the optimal, customer-centered location and time window for handover. In this article, we present a three-step approach for location prediction, based on mobile location data, in order to support delivery planning. The first step is identifying a user's locations of interest through density-based clustering. Next, the semantics (home or work) of the user's locations of interest are discovered, based on temporal assumptions. Finally, we predict future locations with a decision tree model that is trained on each user's historical location data. Though the problem of location prediction is not new, this work is the first to apply it to the field of parcel delivery with its corresponding implications. Moreover, we provide a novel and detailed evaluation on real-world data from a parcel delivery service. The promising results indicate that our approach has the potential to help delivery service providers to gain insights into their customers’ optimal delivery time and location in order to support delivery planning. Eventually this will decrease last-mile delivery costs and boost customer satisfaction. © 2019 Decision Sciences Institute","Data Science; e-Commerce; Location Prediction; Parcel Delivery",{"$nulls":7},"Arnold F., Cardenas I., Sorensen K., Dewulf W., Simulation of b2c e-commerce distribution in antwerp using cargo bikes and delivery points, European Transport Research Review, 10, 1, pp. 2-14, (2017); Asahara A., Maruyama K., Sato A., Seto K., Pedestrian-movement prediction based on mixed markov-chain model. Proceedings of the 19th ACM Sigspatial International Conference on Advances in Geographic Information Systems. 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Proceedings of the 10th International Conference on Mobile Data Management: Systems, Services and Middleware. Washington, DC: IEEE, pp. 1-10, (2009); Zhou C., Frankowski D., Ludford P., Shekhar S., Terveen L., Discovering personally meaningful places: An interactive clustering approach, ACM Transactions on Information Systems (TOIS), 25, 3, (2007)","S. Praet; Department of Engineering Management, University of Antwerp, Antwerp, Prinsstraat 13, 2000, Belgium; email: stiene.praet@uantwerp.be",null,"Blackwell Publishing Ltd",{"$nulls":5},117315.0,null,null,null,"English","Decis. Sci.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85065102016"]
["Tsang Y.P.; Wu C.H.; Lam H.Y.; Choy K.L.; Ho G.T.S.","Tsang, Y.P. (57191666025); Wu, C.H. (55506191100); Lam, H.Y. (57201769414); Choy, K.L. (7005477047); Ho, G.T.S. (8348673600)","57191666025; 55506191100; 57201769414; 7005477047; 8348673600","Integrating Internet of Things and multi-temperature delivery planning for perishable food E-commerce logistics: a model and application",2021.0,"International Journal of Production Research",59.0,5.0,null,1534.0,1556.0,22.0,59.0,"10.1080/00207543.2020.1841315","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85096086696&doi=10.1080%2f00207543.2020.1841315&partnerID=40&md5=a9ea0266d82fb5cb02a9f797d29edeea","Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong; Department of Supply Chain and Information Management, The Hang Seng University of Hong Kong, Shatin, Hong Kong","Tsang Y.P., Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong; Wu C.H., Department of Supply Chain and Information Management, The Hang Seng University of Hong Kong, Shatin, Hong Kong; Lam H.Y., Department of Supply Chain and Information Management, The Hang Seng University of Hong Kong, Shatin, Hong Kong; Choy K.L., Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong; Ho G.T.S., Department of Supply Chain and Information Management, The Hang Seng University of Hong Kong, Shatin, Hong Kong","With the rapid growth of perishable food e-commerce businesses, there is a definite need for logistics services providers to manage parcel shipments with multi-temperature requirements. E-commerce characteristics, including time-critical delivery, fragmented orders, and high product variety, should be further considered to extend the ontology of multi-temperature joint distribution. However, traditional delivery route planning is insufficient because it merely minimises the cost of travelling between customer locations. Factors related to food quality and arrival time windows should also be considered. In addition, handling dynamic incident management, such as violations of handling requirements during delivery, is lacking. This leads to the likelihood of food deteriorating before it reaches the consumers, thereby impacting customer satisfaction. This paper proposes an Internet of Things–based multi-temperature delivery planning system (IoT-MTDPS), embedding a two-phase multi-objective genetic algorithm optimiser (2PMGAO). The formulation of delivery routing mainly considers product-dependent multi-temperature characteristics, service level, transportation cost, and number of trucks. Once there are unexpected incidents which are detected by Internet of Things technologies, 2PMGAO can optimise the membership functions of fuzzy logic for re-routing the e-commerce delivery plan. With using IoT-MTDPS, the capability of handling e-commerce orders is enhanced, while customer satisfaction can be maintained at a designated level. © 2020 Informa UK Limited, trading as Taylor & Francis Group.","fuzzy logic; Internet of Things; optimisation; Perishable food e-commerce; routing","Customer satisfaction; Electronic commerce; Fuzzy logic; Genetic algorithms; Membership functions; Sales; E-commerce business; Incident Management; Internet of things technologies; Joint distributions; Multi-objective genetic algorithm; Temperature characteristic; Transportation cost; Unexpected incidents; Internet of things",{"$nulls":4},"ABC Holdings Limited; Hang Seng University of Hong Kong; Hong Kong Polytechnic University, PolyU","The authors would like to thank the Research Office of the Hong Kong Polytechnic University, ABC Holdings Limited (alias), and the Hang Seng University of Hong Kong for supporting the project. (Project Code: RUDV). 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Wang F., Wang F., Ma X., Liu J., Demystifying the Crowd Intelligence in Last Mile Parcel Delivery for Smart Cities, IEEE Network, 33, 2, pp. 23-29, (2019); Wang X., Wang M., Ruan J., Zhan H., The Multi-Objective Optimization for Perishable Food Distribution Route Considering Temporal-Spatial Distance, Procedia Computer Science, 96, pp. 1211-1220, (2016); Winkelhaus S., Grosse E.H., Logistics 4.0: A Systematic Review Towards a new Logistics System, International Journal of Production Research, 58, 1, pp. 18-43, (2020); Xu W.J., He L.J., Zhu G.Y., Many-Objective Flow Shop Scheduling Optimisation with Genetic Algorithm Based on Fuzzy Sets, International Journal of Production Research, (2019); Yu Y., Wang X., Zhong R.Y., Huang G.Q., E-commerce Logistics in Supply Chain Management, Industrial Management & Data Systems, 117, 10, pp. 2263-2286, (2017); Zdravkovic M., Zdravkovic J., Aubry A., Moalla N., Guedria W., Sarraipa J., Domain Framework for Implementation of Open IoT Ecosystems, International Journal of Production Research, 56, 7, pp. 2552-2569, (2018); Zhang M., Pratap S., Huang G.Q., Zhao Z., Optimal Collaborative Transportation Service Trading in B2B e-Commerce Logistics, International Journal of Production Research, 55, 18, pp. 5485-5501, (2017); Zhao S., Li S., Qi L., Da Xu L., Computational Intelligence Enabled Cybersecurity for the Internet of Things, IEEE Transactions on Emerging Topics in Computational Intelligence, 4, 5, pp. 666-674, (2020); Zhu Z., Chu F., Dolgui A., Chu C., Zhou W., Piramuthu S., Recent Advances and Opportunities in Sustainable Food Supply Chain: A Model-Oriented Review, International Journal of Production Research, 56, 17, pp. 5700-5722, (2018)","K.L. Choy; Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong; email: kl.choy@polyu.edu.hk",null,"Taylor and Francis Ltd.",{"$nulls":5},207543.0,null,"IJPRB",null,"English","Int J Prod Res","Article","Final",null,"Scopus","2-s2.0-85096086696"]
["Yang K.L.; Sha D.Y.; Jou Y.-T.","Yang, Kuang Li (57221418751); Sha, D.Y. (7006750130); Jou, Yung-Tsan (23090928700)","57221418751; 7006750130; 23090928700","Use the service gap model to improve the level of service (LOS) of e-commerce physical home logistic in Taiwan area",2020.0,"Journal of Quality",27.0,5.0,null,319.0,330.0,11.0,0.0,"10.6220/joq.202010_27(5).0003","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85099098672&doi=10.6220%2fjoq.202010_27%285%29.0003&partnerID=40&md5=f6724cfb588e6360836f07ae6b003d0a","Department of Industrial and Systems Engineering, Chung Yuan Christian University, Taiwan; Department of Industrial Engineering and Management, National Chiao Tung University, Taiwan","Yang K.L., Department of Industrial and Systems Engineering, Chung Yuan Christian University, Taiwan; Sha D.Y., Department of Industrial Engineering and Management, National Chiao Tung University, Taiwan; Jou Y.-T., Department of Industrial and Systems Engineering, Chung Yuan Christian University, Taiwan","The purpose of this empirical study is to examine management issues that Taiwan’s distribution industry is facing due to the popularity of E-commerce. We use the service gap model to understand the entire service field of the physical home-delivery service system needed for improving. The questionnaire includes the use experience in the past six months, as well as another 25 questions about the expectation and perceived service quality of physical home delivery. A survey based on the service quality (SERVQUAL) questionnaire and user’s E-commerce experience was distributed by email and i-message to totally 350 selected college students and research and design (R&D) personnel of a research institute. The empirical data was collected electronically and a result of 91 valid copies was analyzed by using the importance-satisfaction (I-S) mode to determine the quality attributes and improvement coefficient (Ii) to determine the items and order of improvement. Service indicators included: reliability, responsiveness, empathy, and introducing a communication interface that is important and will affect the level of service (LOS) of E-commerce physical home logistic in Taiwan area, and also could set the basis for business innovation and formation of new business to propose refined customer value. © 2020, Chinese Society for Quality. All rights reserved.","I-S model; Level of service (LOS); Physical home logistic; SERVQUAL","Quality of service; Students; Surveys; Business innovation; Communication interface; Home delivery services; Improvement coefficients; Management issues; Perceived service qualities; Quality attributes; Research institutes; Electronic commerce",{"$nulls":6},"Arvis J.-F., Saslavsky D., Ojala L., Shepherd B., Busch C., Raj A., Naula T., Connecting to Compete 2016: Trade Logistics in the Global economy—the Logistics Performance Index and Its Indicators, (2016); Athanasopoulou P., Relationship quality: A critical literature review and research agenda, European Journal of Marketing, 43, 5-6, pp. 583-610, (2009); Overview of E-Commerce Development in the Retail Industry in Major Countries, (2018); Dieke K.A., Arnold R., Bender C., Hillebrand A., Niederprum A., Tas S., Et al., Development of Cross-Border E-Commerce through Parcel Delivery: Appendix B WIK Consumer Survey, (2019); Eboli L., Mazzulla G., Service quality attributes affecting customer satisfaction for bus transit, Journal of Public Transportation, 10, 3, pp. 21-34, (2007); Franceschini F., Galetto M., Turina E., Service quality monitoring by performance indicators: A proposal for a structured methodology, International Journal of Services and Operations Management, 5, 2, pp. 251-273, (2009); Gajewska T., Grigoroudis E.G., Importance of logistics services attributes influencing customer satisfaction, Paper Presented at the 2015 4Th IEEE International Conference on Advanced Logistics and Transport, (2015); Gulc A., Models and methods of measuring the quality of logistic service, Procedia Engineering, 182, pp. 255-264, (2017); Lin C.K., Planning for the White Paper on National Freight Development Policy, 2002, (2016); Martilla J., James J., Importance-performance analysis, Journal of Marketing, 41, 1, pp. 77-79, (1977); Mentzer J.T., Flint D.J., Hult T.M., Logistics service quality as a segment—customized process, Journal of Marketing, 65, 4, pp. 82-104, (2001); The White Book on National Freight Development Policy, Ministry of Transportation and Communications, (2004); Morganti E., Seidel S., Blanquart C., Dablanc L., Lenz B., The impact of E-commerce on final deliveries: Alternative parcel delivery services in France and Germany, Transportation Research Procedia, 4, pp. 178-190, (2014); Parasuraman A., Zeithaml V.A., Berry L.L., A conceptual model of service quality and its implications for future research, Journal of Marketing, 49, 4, pp. 41-50, (1985); Parasuraman A., Zeithaml V.A., Berry L.L., SERVQUAL: A multiple-item scale for measuring consumer perceptions of service quality, Journal of Retailing, 64, 1, pp. 12-40, (1988); Prentkovskis O., Erceg Z., Stevic Z., Tanackov I., Vasiljevic M., Gavranovic M., A new methodology for improving service quality measurement: Delphi-FUCOM-SERVQUAL model, Symmetry, 10, 12, (2018); Sohn J.-I., Woo S.-H., Kim T.-W., Assessment of logistics service quality using the Kano model in a logistics-triadic relationship, The International Journal of Logistics Management, 28, 2, pp. 680-698, (2017); Thomas C., Ecommerce Delivery: How Your Delivery Strategy Can Increase Your Sales, (2014); Yang C.-C., The application of two-dimensional quality model on service quality, Quality Control Monthly, 29, 5, pp. 27-33, (1993); Yang C.-C., Establishment and applications of the integrated model of service quality measurement, Managing Service Quality: An International Journal, 13, 4, pp. 310-324, (2003); Yuan X., Shi L., Li H., Research on the relationship between the logistics service quality and customer loyalty in C2C E-commerce, Wuhan International Conference on E-Business 2014 Proceedings, pp. 104-113, (2014); Zeithaml V.A., Parasuraman A., Berry L.L., Delivering Quality Service: Balancing Customer Perceptions and Expectations, (1990)","Y.-T. Jou; Department of Industrial and Systems Engineering, Chung Yuan Christian University, Taiwan; email: ytjou@cycu.edu.tw",null,"Chinese Society for Quality",{"$nulls":5},1.022069E7,null,null,null,"English","J Qual.","Article","Final",null,"Scopus","2-s2.0-85099098672"]
["Shen Y.; Qian Y.; Li S.; Wu X.","Shen, Yuyan (37018778600); Qian, Yan (37018685300); Li, Shufang (57197708956); Wu, Xudong (57224679771)","37018778600; 37018685300; 57197708956; 57224679771","Cloud logistics and risk assessment design platform based on service modularisation",2021.0,"International Journal of Wireless and Mobile Computing",20.0,3.0,null,272.0,280.0,8.0,0.0,"10.1504/IJWMC.2021.115655","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85108174602&doi=10.1504%2fIJWMC.2021.115655&partnerID=40&md5=9632f63f1f1abdd0106772e6da817a15","Qianjiang College, Hangzhou Normal University, Hangzhou, 310018, China; Hangzhou Normal University, Hangzhou, 310018, China; Zhejiang Business College, Zhejiang University, Xihu, Hangzhou, 310053, China; Hangzhou Chipshare Technology Co., Ltd., Hangzhou, 310016, China","Shen Y., Qianjiang College, Hangzhou Normal University, Hangzhou, 310018, China, Hangzhou Normal University, Hangzhou, 310018, China; Qian Y., Qianjiang College, Hangzhou Normal University, Hangzhou, 310018, China; Li S., Zhejiang Business College, Zhejiang University, Xihu, Hangzhou, 310053, China; Wu X., Hangzhou Chipshare Technology Co., Ltd., Hangzhou, 310016, China","This paper is intended to develop a cloud logistics service model from the three dimensions of service modularisation, namely design structure, interface and standards. A case study research method was employed to analyse the service modularisation of Star Express’s cloud logistic platform based on service process modularisation, service function modularisation and service object modularisation and to propose the realisation method of the modularisation service mode of the logistics service of the e-commerce platform. Further, this study conducted a risk assessment of the modularisation service quality of the cloud logistics platform, through the cloud logistics platform risk assessment model based on the OWA operator. Research findings revealed that cloud logistics service model and risk assessment analysis leads to decreasing the maintenance costs, and improves the service quality and optimise the modularisation service of the cloud logistics platform. Copyright © 2021 Inderscience Enterprises Ltd.","Cloud logistics; Modularisation design; Risk assessment; Service modularisation; Star express","Quality of service; Risk analysis; Case study research; Design structure; Logistics platforms; Logistics services; Maintenance cost; Risk assessment models; Service functions; Three dimensions; Risk assessment",{"$nulls":4},"Hangzhou Leading Geese Plan; Zhejiang Provincial Soft Science Research Program, (2021C35122); Humanities and Social Science Fund of Ministry of Education of China, (19YJA630040)","The Zhejiang Provincial Soft Science Research Program (2021C35122). The Ministry of Education of Humanities and Social Science Project (19YJA630040). The Hangzhou Leading Geese Plan (2019)","Baldwin C.Y., Clark K.B., Managing in an age of modularity, Harvard Business Review, 75, 5, pp. 84-93, (1997); Baldwin C.Y., Clark K.B., Design Rules, Volume 1, the Power of Modularity, (2000); Chen P., New franchise model promotes faster development of e-commerce logistics, Logistics Technology and Application, 1, pp. 67-69, (2010); Chen X., Research on cloud logistics model of private express industry based on long tail theory, Southeast Academic, 6, pp. 81-89, (2012); Di H., Liu F., Cloud logistics development model & upgrade path based on big data background, Business Economics Research, 21, pp. 67-70, (2019); Hao B., Ren H., Modularization organization association interface: form mechanism & effectiveness mechanism, Scientific Research Management, 6, pp. 120-127, (2010); Hao B., Ren H., Analysis of problem of modularization organization leading rule design based on SBC Paradigm, Foreign Economy and Management, 6, pp. 28-35, (2009); Huang S., Li X., Analysis of fresh logistics problems & analysis of solutions under background of “New Retail, Modern Marketing (Late Issue), 12, pp. 154-155, (2019); Lei R., Et al., Comparative study on organization model based on modularization & efficiency, China Industrial Economy, 10, pp. 83-91, (2004); Li X., Et al., Research on organizational governance path of li service modularized network: from the perspective of risk Paradox, Science and Technology Management Research, 13, pp. 217-228, (2019); Li D., Research on aquatic Product supply chain safety risk management, (2011); Gong X., Yang R., Application of “Cloud Computing” & “Cloud Logistics” in logistics, China Circulation Economy, 10, pp. 29-35, (2012); Sanchez R., Modular architectures in the marketing process, The Journal of Marketing, 63, pp. 92-111, (1999); Sundbo J., Modulization of service production and a thesis of convergence between service and manufacturing organizations, Scandinavian Journal of Management, 10, 3, pp. 245-266, (1994); Sun G., Zhu Y., Research on risk generation mechanism of modular network organization, Business Studies, 1, pp. 86-91, (2013); Wang X., Research on Benefit Distribution of Logistics Service Providers under Cloud Logistics Model, (2013); Wang Q., Research on service innovation model of logistics industry cluster based on cloud logistics, Logistics Technology, 2, pp. 24-28, (2013); Wang Z., Research on cloud logistics model & transformation path in era of big data, Technology Economics and Management Research, 3, pp. 15-20, (2019); Yin R.K., Case Study Research: Design and Methods, (2003); Yu C., Wu Z., Modularization operation of civil aviation services from perspective of value creation-based on perspective of exploratory case analysis, China Industrial Economy, 12, pp. 141-153, (2012); Zhang J., Luo W., Research on cooperative innovation coupling mechanism of technology & service model based on cloud logistics platform, Journal of Dalian University of Technology (Social Science Edition), 40, pp. 24-33, (2019)","Y. Shen; Qianjiang College, Hangzhou Normal University, Hangzhou, 310018, China; email: shenyy225@sina.cn",null,"Inderscience Publishers",{"$nulls":5},1.7411084E7,null,null,null,"English","Int. J. Wireless Mobile Comput.","Article","Final",null,"Scopus","2-s2.0-85108174602"]
["Wu Y.; Ding Y.; Ding S.; Savaria Y.; Li M.","Wu, Yuzhan (57222517112); Ding, Yuanhao (57222517422); Ding, Susheng (57222516113); Savaria, Yvon (7006575013); Li, Meng (56804068000)","57222517112; 57222517422; 57222516113; 7006575013; 56804068000","Autonomous Last-Mile Delivery Based on the Cooperation of Multiple Heterogeneous Unmanned Ground Vehicles",2021.0,"Mathematical Problems in Engineering",2021.0,null,5546581.0,null,null,null,11.0,"10.1155/2021/5546581","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85102967963&doi=10.1155%2f2021%2f5546581&partnerID=40&md5=4e5ac5497b48024dd808b26c441b512c","Beihang University, Beijing, China; School of Information Science and Technology, Zhejiang Sci-Tech University, Hangzhou, China; Department of Electrical Engineering, Polytechnique Montreal, Montreal, QC, Canada; College of Big Data and Internet, Shenzhen Technology University, Shenzhen, China","Wu Y., Beihang University, Beijing, China; Ding Y., School of Information Science and Technology, Zhejiang Sci-Tech University, Hangzhou, China; Ding S., School of Information Science and Technology, Zhejiang Sci-Tech University, Hangzhou, China; Savaria Y., Department of Electrical Engineering, Polytechnique Montreal, Montreal, QC, Canada; Li M., College of Big Data and Internet, Shenzhen Technology University, Shenzhen, China","With the development of e-commerce, the last-mile delivery has become a significant part of customers' shopping experience. In this paper, an autonomous last-mile delivery method using multiple unmanned ground vehicles is investigated. Being a smart logistics service, it provides a promising solution to reduce the delivery cost, improve efficiency, and avoid the spread of airborne diseases, such as SARS and COVID-19. By using a cooperation strategy with multiple heterogeneous robots, contactless parcel delivery can be carried out within apartment complexes efficiently. In this paper, the last-mile delivery with heterogeneous UGVs is formulated as an optimization problem aimed at minimizing the maximum makespan to complete all tasks. Then, a heuristic algorithm combining the Floyd's algorithm and PSO algorithm is proposed for task assignment and path planning. This algorithm is further realized in a distributed scheme, with all robots in a swarm working together to obtain the best task schedule. A good solution with an optimized makespan is achieved by considering the constraints of various robots in terms of speed and payload. Simulations and experiments are carried out and the obtained results confirm the validity and applicability of the developed approaches. © 2021 Yuzhan Wu et al.",null,"Heuristic algorithms; Intelligent vehicle highway systems; Particle swarm optimization (PSO); Robots; Apartment complexes; Co-operation strategy; Distributed schemes; Floyd's algorithm; Logistics services; Multiple heterogeneous robots; Optimization problems; Unmanned ground vehicles; Ground vehicles",{"$nulls":6},"Wei M., Wang S., Zheng J., Chen D., UGV navigation optimization aided by reinforcement learning-based path tracking, IEEE Access, 6, pp. 57814-57825, (2018); Curiel-Ramirez L.A., Ramirez-Mendoza R.A., Bautista-Montesano R., End-to-end automated guided modular vehicle, Applied Sciences, 10, 12, (2020); Kato T., Kamoshida R., Multi-Agent simulation environment for logistics warehouse design based on self-contained agents, Applied Sciences, 10, 21, (2020); Wang X., Choi T.-M., Liu H., Yue X., Novel ant colony optimization methods for simplifying solution construction in vehicle routing problems, IEEE Transactions on Intelligent Transportation Systems, 17, 11, pp. 3132-3141, (2016); 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Wu J., Ahn S., Zhou Y., Liu P., Qu X., The cooperative sorting strategy for connected and automated vehicle platoons, Transportation Research Part C: Emerging Technologies, 123, (2021); Sedighi K.H., Ashenayi K., Manikas T.W., Wainwright R.L., Tai H.-M., Autonomous local path planning for a mobile robot using a genetic algorithm, Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No. 04TH8753), 2, pp. 1338-1345, (2004); Bremermann H.J., The Evolution of Intelligence: The Nervous System As A Model of Its Environment, (1958); Shibata T., Fukuda T., Intelligent Motion Planning by Genetic Algorithm with Fuzzy Critic, pp. 565-570; Xiao J., Michalewicz Z., Zhang L., Trojanowski K., Adaptive evolutionary planner/navigator for mobile robots, IEEE Transactions on Evolutionary Computation, 1, pp. 18-28, (1997); Kennedy J., Eberhart R., Particle Swarm Optimization, pp. 1942-1948; Tang X.-L., Li L.-M., Jiang B.-J., Mobile robot SLAM method based on multi-agent particle swarm optimized particle filter, The Journal of China Universities of Posts and Telecommunications, 21, 6, pp. 78-86, (2014); Masehian E., Sedighizadeh D., Multi-objective PSO- And NPSO-based algorithms for robot path planning, Advances in Electrical and Computer Engineering, 10, 4, pp. 69-76, (2010); Wang Y., Bai P., Liang X., Wang W., Zhang J., Fu Q., Reconnaissance mission conducted by UAV swarms based on distributed PSO path planning algorithms, IEEE Access, 7, pp. 105086-105099, (2019); Yan Z., Li J., Wu Y., Zhang G., A real-time path planning algorithm for AUV in unknown underwater environment based on combining PSO and waypoint guidance, Sensors, 19, (2019); Dorigo M., Maniezzo V., Colorni A., The ant system: An 5 autocatalytic optimizing process, Technical Report 91-016, pp. 1-27, (1991); Dorigo M., Gambardella L.M., Ant colony system: A cooperative learning approach to the traveling salesman problem, IEEE Transactions on Evolutionary Computation, 1, 1, pp. 53-66, (1997); Zhang Y., Wang H.L., Li X., Zhang Y.H., Wang H., Parallel ant system based on OpenMP, Advanced Materials Research, 765-767, pp. 658-661, (2013); Stutzle T., Hoos H.H., MAX-MIN- ant system, Future Generation Computer Systems, 16, 8, pp. 889-914, (2000); Bullnheimer B., Hartl R.F., Strauss C., A new rank based version of the Ant system-a computational study, Central European Journal of Operations Research, 7, 1, pp. 25-38, (1999); Ji X.F., Pan J.S., Chu S.C., Hu P., Chai Q.W., Zhang P., Adaptive Cat swarm optimization algorithm and its applications in vehicle routing problems, Mathematical Problems in Engineering, 2020, (2020)","M. Li; College of Big Data and Internet, Shenzhen Technology University, Shenzhen, China; email: limeng2@sztu.edu.cn",null,"Hindawi Limited",{"$nulls":5},"1024123X",null,null,null,"English","Math. Probl. Eng.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85102967963"]
["Zani B.","Zani, Beatrice (57204284307)",5.7204284307E10,"WeChat, we sell, we feel: Chinese women’s emotional petit capitalism",2020.0,"International Journal of Cultural Studies",23.0,5.0,null,803.0,820.0,17.0,10.0,"10.1177/1367877920923360","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85089152047&doi=10.1177%2f1367877920923360&partnerID=40&md5=9601f2e62cbcc73ae134661d4f16fc14","Sciences Po Lyon. TRIANGLE, France","Zani B., Sciences Po Lyon. TRIANGLE, France","Through multi-situated and virtual ethnography, this article investigates the link between mobilities, subalternity, emotions and digital economies. Drawing on the case study of Chinese migrant women’s digital labour and e-commerce in Taiwan, it elucidates the social and emotional construction of translocal virtual markets, which connect online and offline the different temporalities, spatialities and emotions of women’s mobilities. In Taiwan, Chinese migrants contest a local condition of social, economic and cultural subalternity by exploring physical and digital, material and emotional markets. Setting sail through local consumption and translocal logistics, through the online application WeChat an emotional petit capitalism is socially and emotionally produced within women’s daily microcosmos of experiences and practices. © The Author(s) 2020."," WeChat; China-Taiwan; digital markets; e-commerce; emotions; mobilities; subalternity; virtual ethnography",{"$nulls":7},"Abdelnour S., Moi, petite entreprise: Les auto-entrepreneurs, de l’utopie à la réalité, (2016); Ambrosini M., Irregular Immigration in Southern Europe: Actors, Dynamics and Governance, (2018); Appadurai A., Introduction: Commodities and the politics of value, The Social Life of Things, pp. 2-45, (1986); Appadurai A., Modernity at Large: The Cultural Consequences of Globalisation, (1999); Boccagni P., Baldassar L., Emotions on the move: Mapping the emergent field of emotion and migration, Emotion, Space and Society, 16, pp. 73-80, (2015); Bondi L., Davidson J., Emotional Geographies, (2007); Butler J., Undoing Gender, (2004); Callon M., The economy of qualities, Economy and Society, 31, 2, pp. 194-217, (2002); Casilli A., Is there a global digital labour culture?, The Information Society, 32, 1, pp. 117-129, (2016); Chang K.-S., South Korea Under Compressed Modernity, (2010); Cheng I., Making foreign women the mother of our nation: The exclusion and assimilation of immigrant women in Taiwan, Asian Ethnicity, 14, 2, pp. 157-169, (2013); Diminescu D., The connected migrant: An epistemological manifesto, Social Science Information, 47, 4, pp. 565-579, (2008); Diminescu D., Researching the connected migrant, The Sage Handbook of Media and Migration, pp. 74-78, (2020); Flichy M., Les Nouvelles Frontières du travail à l’ère numérique, (2017); Fligstein N., Social skills and the theory of fields, Sociological Theory, 19, 2, pp. 1-37, (2001); Glick Schiller N., Salazar N.B., Regimes of mobility across the globe, Journal of Ethnic and Migratory Studies, 39, 2, pp. 183-200, (2013); Goffman E., On fieldwork, Journal of Contemporary Ethnography, 18, 2, pp. 123-132, (1989); Granovetter M., Business group, The Handbook of Economic Sociology, pp. 453-475, (1994); Guarnizo L.E., Smith M.P., The location of transnationalism, Transnationalism from Below: Comparative Urban and Community Research, pp. 3-34, (2008); Hine C., Ethnography for the Internet: Embedded, Embodied and Every Day, (2015); Illouz E., Cold Intimacies: The Making of Emotional Capitalism, (2007); Illouz E., Emodities or the making of emotional commodities, Emotions as Commodities: Capitalism, Consumption and Authenticity, pp. 1-30, (2018); Ingold T., The Perception of the Environment, (2000); Kloosterman R., Rath J., Immigrant entrepreneurs in advanced economies: Mixed embeddedness further explored, Journal of Ethnic and Migration Studies, 27, 2, pp. 189-201, (2001); Lau T., Swatter business: Commodity exchange and the mediation of agency in the Tibetan itinerant sweater trade in India, Moving Subjects, Moving Objects: Transnationalism, Cultural Production and Emotions, pp. 96-116, (2014); Li H.F.A., E-commerce and Taobao villages, China Perspectives, 2017, 3, pp. 57-62, (2017); Li P., The world’s largest labour force migration, China’s Internal and International Migration, pp. 20-25, (2013); Lin Y., E-urbanism: E-commerce, migration and the transformation of Taobao villages in urban China, Cities, 91, pp. 202-219, (2019); Lutz C., Abu-Lughod L., Language and the Politics of Emotion, (1990); Marcus G.E., Ethnography in/of the world system: The emergence of multi-sited ethnography, Annual Review of Anthropology, 24, pp. 95-117, (1995); Marcus G.E., Fischer M., Anthropology as Cultural Critique: An Experimental Moment in the Human Sciences, (1986); Miller D., Stuff, (2010); Polanyi K., La Grande Transformation: Aux origines politiques et économiques de notre temps, (1983); Ponzanesi S., Migration and mobility in a digital age: (Re)mapping connectivity and belonging, Television and New Media, 20, 6, pp. 547-557, (2019); Portes A., Theoretical convergences and empirical evidence in the study of immigrant transnationalism, International Migration Review, 37, pp. 814-892, (2003); Portes A., Guarnizo L., Landolt P., The study of transnationalism: Pitfalls and promise of an emergent research field, Ethnic and Racial Studies, 22, pp. 200-217, (1999); Pun N., Made in China, (2005); Rosenwein B.H., Emotional Communities in the Early Middle Ages, (2006); Roulleau-Berger L., In commemoration of the legacy of Ulrich Beck: Theory of migration and methodological cosmopolitanism, Development and Society, 46, 2, pp. 227-250, (2017); Roulleau-Berger L., Temporalities, space and compressed individual in China, Temporalités, 26, (2018); Sassen S., The Global City: New York, London and Tokyo, (1995); Steiner P., The market according to economic sociology, Revue Européenne des Sciences Sociales, 2, 1, pp. 45-68, (2005); Svasek M., Introduction. Affective moves: Transit, transition and transformation, Moving Subjects, Moving Objects: Transnationalism, Cultural Production and Emotions, pp. 1-40, (2014); Tarrius A., Les Nouveaux Cosmopolitismes: mobilités, identités, territoires, (2000); Waldinger R., Aldrich H., Ward R., Opportunities, groups’ characteristics, and strategies, Ethnic Entrepreneurs, 1, pp. 13-48, (1990); Zani B., Gendered transnational ties and multipolar economies: Chinese migrant women’s WeChat commerce in Taiwan, International Migration, 57, 4, pp. 232-246, (2018); Zani B., In-between: Re-migration, emotional circulations and new cosmopolitan biographies, Asia Pacific Viewpoint, (2020)","B. Zani; Sciences Po Lyon. TRIANGLE, France; email: beatrice.zani92@gmail.com",null,"SAGE Publications Ltd",{"$nulls":5},1.3678779E7,null,null,null,"English","Int. J. Cult. Stud.","Article","Final",null,"Scopus","2-s2.0-85089152047"]
["Yu R.; Wu Z.; Qu S.","Yu, Rong (57223270739); Wu, Zhong (56167556300); Qu, Shaojian (15136760000)","57223270739; 56167556300; 15136760000","Distribution Service Competition with the Consideration of Different Consumer Behaviors",2021.0,"Discrete Dynamics in Nature and Society",2021.0,null,9417675.0,null,null,null,0.0,"10.1155/2021/9417675","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85108539699&doi=10.1155%2f2021%2f9417675&partnerID=40&md5=aa2805db49e936e4038a3d2dce3e52ba","Business School, University of Shanghai for Science and Technology, Shanghai, 200093, China","Yu R., Business School, University of Shanghai for Science and Technology, Shanghai, 200093, China; Wu Z., Business School, University of Shanghai for Science and Technology, Shanghai, 200093, China; Qu S., Business School, University of Shanghai for Science and Technology, Shanghai, 200093, China","Logistics distribution plays an important role in the operation of e-commerce firms. This paper considers two logistics distribution modes with service competition: the e-commerce platform self-distribution (SDL) mode and third-party logistics (TPL) mode. By introducing consumer behavior into the model, we examine the competition between two firms with the same functionalities in the context of e-commerce. According to the real scene, we build the corresponding mathematical optimization model. Each firm needs to decide a logistics distribution mode and a corresponding price for the selected logistics mode. We first analyze the two firms chosen logistics modes and prices simultaneously and then extend it to Stackelberg game situation. We find out the optimal strategy for two firms. Finally, we propose numerical analysis to identify our models and provide a series of managerial insights.  © 2021 Rong Yu et al.",{"$nulls":8},"Shu J., Sun J., Designing the distribution network for an integrated supply chain, Journal of Industrial and Management Optimization, 2, 3, pp. 339-349, (2006); Ellinger A.E., Lynch D.F., Andzulis J.K., Smith R.J., B-To-B E-commerce: A content analytical assessment of motor carrier websites, Journal of Business Logistics, 24, 1, pp. 199-220, (2011); Yu Y., Wang X., Zhong R.Y., Huang G.Q., E-commerce logistics in supply chain management: Practice perspective, Procedia CIRP, 52, pp. 179-185, (2016); Lee H., Whang S., Winning the last mile of E-commerce, Mit Sloan Management Review, 42, 4, pp. 54-62, (2001); Chen F., Yong L., Xue Y., Online and offline cooperation under buy-online, pick-up-in-store: Pricing and inventory decisions, Journal of Industrial and Management Optimization, 15, 3, pp. 1455-1472, (2019); Wang Y., Sang D., Multi-Agent Framework for Third Party Logistics in E-Commerce, 29, 2, pp. 431-436, (2005); Choudhary V., Ghose A., Mukhopadhyay T., Rajan U., Personalized pricing and quality differentiation, Management Science, 51, 7, pp. 1120-1130, (2005); Robert H., The value chain and e-business in exporting: Case studies from Ghana's non-traditional export (NTE) sector, Telematics and Informatics, 27, 3, pp. 323-340, (2010); Qu S., Yang H., Ji Y., Low-carbon supply chain optimization considering warranty period and carbon emission reduction level under cap-and-trade regulation, Environment, Development and Sustainability, (2021); Peral T., Ecem B., Seyhan T., Mustafa A., The impact of barriers and benefits of e-procurement on its adoption decision: An empirical analysis, International Journal of Production Economics, 158, pp. 77-90, (2014); Hong-Oanh N., Critical factors in e-business adoption: Evidence from Australian transport and logistics companies, International Journal of Production Economics, 146, 1, pp. 300-312, (2013); Mu C., Pei J., Yu H., An effective pricing model for the congestion alleviation of e-commerce logistics, Computers and Industrial Engineering, 129, pp. 368-376, (2019); Chen D., Ignatius J., Sun D., Reverse logistics pricing strategy for a green supply chain: A view of customers' environmental awareness, International Journal of Production Economics, 3, pp. 366-385, (2018); Chu Z., Feng B., Lai F., Logistics service innovation by third party logistics providers in China: Aligning guanxi and organizational structure, Transportation Research Part E: Logistics and Transportation Review, 118, pp. 291-307, (2018); Veena G., Gopinath P., Optimal information policy in discrete-time queues with strategic customers, Journal of Industrial and Management Optimization, 15, 2, pp. 689-703, (2019); Tong W., Mu D., Zhao F., Mendis G.P., Sutherland J.W., The impact of cap-and-trade mechanism and consumers' environmental preferences on a retailer-led supply Chain, Resources, Conservation and Recycling, 142, pp. 88-100, (2019); Qu S., Li Y., Ji Y., The mixed integer robust maximum expert consensus models for large-scale GDM under uncertainty circumstances, Applied Soft Computing Journal, 107, (2021); Shin H.K., Kim A., Lee C.W., Relationship between consumer's preference and service attributes in mobile telecommunication service, Expert Systems with Applications, 38, 4, pp. 3522-3527, (2011); Cai J., Hu X., Tadikamalla P.R., Shang J., Flexible contract design for VMI supply chain with service-sensitive demand: Revenue-sharing and supplier subsidy, European Journal of Operational Research, 261, 1, pp. 143-153, (2017); Zheng L., Xu C., Ming K., The effect of customer value and power structure on retail supply chain product choice and pricing decisions, Omega, 77, pp. 115-126, (2018); Hu X., Su P., The Newsvendor's Joint Procurement and pricing problem under price-sensitive stochastic demand and purchase price uncertainty, Omega, 79, pp. 81-90, (2018); Kogan K., El Ouardighi F., Autonomous and include production learning under price and quality competition, Applied Mathematical Modelling, 67, pp. 74-84, (2018); Hua G., Wang S., Cheng T.C.E., Price and lead time decisions in dual-channel supply chains, European Journal of Operational Research, 205, 1, pp. 113-126, (2010); Eltoukhy A.E.E., Wang Z.X., Chan F.T.S., Fu X., Data analytics in managing aircraft routing and maintenance staffing with price competition by a Stackelberg-Nash game model, Transportation Research Part E: Logistics and Transportation Review, 122, C, pp. 143-168, (2019); Qu S., Jiang G., Ji Y., Newsvendor's optimal decisions under stochastic demand and cap-and-trade regulation, Environment, Development and Sustainability, (2021); Feng L., Govindan K., Li C., Strategic planning: Design and coordination for dual-recycling channel reverse supply chain considering consumer behavior, European Journal of Operational Research, 260, 2, pp. 601-612, (2017)","Z. Wu; Business School, University of Shanghai for Science and Technology, Shanghai, 200093, China; email: wuzhong_1968@163.com",null,"Hindawi Limited",{"$nulls":5},1.0260226E7,null,null,null,"English","Discrete Dyn. Nat. Soc.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85108539699"]
["Sampaio A.; Savelsbergh M.; Veelenturf L.P.; Van Woensel T.","Sampaio, Afonso (57215836142); Savelsbergh, Martin (6701542933); Veelenturf, Lucas P. (36667703700); Van Woensel, Tom (12781314700)","57215836142; 6701542933; 36667703700; 12781314700","Delivery systems with crowd-sourced drivers: A pickup and delivery problem with transfers",2020.0,"Networks",76.0,2.0,null,232.0,255.0,23.0,32.0,"10.1002/net.21963","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85087689695&doi=10.1002%2fnet.21963&partnerID=40&md5=db7169507608c0774b24725d51f8c684","School of Industrial Engineering, Eindhoven University of Technology, Eindhoven, Netherlands; H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA, United States","Sampaio A., School of Industrial Engineering, Eindhoven University of Technology, Eindhoven, Netherlands; Savelsbergh M., H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA, United States; Veelenturf L.P., School of Industrial Engineering, Eindhoven University of Technology, Eindhoven, Netherlands; Van Woensel T., School of Industrial Engineering, Eindhoven University of Technology, Eindhoven, Netherlands","Rapid urban growth, the increasing importance of e-commerce and high consumer service expectations have given rise to new and innovative models for freight delivery within urban environments. Crowdsourced solutions—where drivers are not employed by a carrier but occasionally offer their services through on-line platforms and are contracted as required by carriers—are receiving growing attention from industry. We consider a crowdsourced system where drivers express their availability to perform delivery tasks for a given period of time and the platform communicates a schedule with requests to serve. We investigate the potential benefits of introducing transfers to support driver activities. At transfer locations, drivers can drop off packages for pick up by other drivers at a later time. We frame the problem as a multidepot pickup and delivery problem with time windows and transfers, and propose an adaptive large neighborhood search algorithm that effectively identifies beneficial transfer opportunities and synchronizes driver operations. Computational experiments indicate that introducing transfer options can significantly reduce system-wide travel distance as well as the number of drivers required to serve a given set of requests, especially when drivers have short availability and requests have high service requirements. © 2020 The Authors. Networks published by Wiley Periodicals LLC.","crowdshipping; large neighborhood search; pickup and delivery; transfers","Optimization; Pickups; Service industry; Urban growth; Adaptive large neighborhood searches; Computational experiment; Crowdsourced systems; Freight deliveries; Pickup and delivery problem with time windows; Pickup and delivery problems; Potential benefits; Service requirements; Crowdsourcing",{"$nulls":4},"DATAS; Netherlands Organization for Scientific Research; Nederlandse Organisatie voor Wetenschappelijk Onderzoek, NWO, (438‐15‐507, 439‐17‐703)","Funding text 1: This research was supported by the DATAS for Cities, Grant/Award Number: 438‐15‐507; Physical Internet Reisbeurzenprogramma, Grant/Award Number: 439‐17‐703 Funding information ; Funding text 2: information This research was supported by the DATAS for Cities, Grant/Award Number: 438-15-507; Physical Internet Reisbeurzenprogramma, Grant/Award Number: 439-17-703Funding for this research was provided by Netherlands Organization for Scientific Research (NWO), via the project DATAS for Cities (No. 438-15-507) and the Physical Internet Reisbeurzenprogramma (No. 439-17-703). The authors gratefully acknowledge the grants received to support their work.; Funding text 3: Funding for this research was provided by Netherlands Organization for Scientific Research (NWO), via the project DATAS for Cities (No. 438‐15‐507) and the Physical Internet Reisbeurzenprogramma (No. 439‐17‐703). The authors gratefully acknowledge the grants received to support their work.","Archetti C., Savelsbergh M., Grazia Speranza M., The vehicle routing problem with occasional drivers, Eur. J. Oper. Res., 254, pp. 472-480, (2016); Arslan A., Agatz N., Kroon L., Zuidwijk R., Crowdsourced delivery—A dynamic pickup and delivery problem with ad hoc drivers, Transp. Sci., 53, 1, pp. 222-235, (2019); Behrend M., Meisel F., The integration of item-sharing and crowdshipping: Can collaborative consumption be pushed by delivering through the crowd?, Transp. Res. B: Methodol., 111, pp. 227-243, (2018); Berbeglia G., Cordeau J.-F., Gribkovskaia I., Laporte G., Static pickup and delivery problems: A classification scheme and survey, TOP, 15, pp. 1-31, (2007); Berbeglia G., Cordeau J.-F., Laporte G., Dynamic pickup and delivery problems, Eur. J. Oper. Res., 202, pp. 8-15, (2010); Rai H.B., Verlinde S., Merckx J., Macharis C., Crowd logistics: An opportunity for more sustainable urban freight transport?, Eur. Transp. Res. Rev., 9, (2017); Chen C., Pan S., Using the crowd of taxis to last mile delivery in e-commerce: A methodological research, Service Orientation in Holonic and Multi-Agent Manufacturing, pp. 61-70, (2016); Chen C., Pan S., Zhu W., Zhong R.Y., Using taxis to collect citywide e-commerce reverse flows: A crowdsourcing solution, Int. J. Prod. Res., 55, pp. 1833-1844, (2017); Chen W., Mes M., Schutten M., Multi-hop driver-parcel matching problem with time windows, Flexible Serv. Manuf. J., 30, pp. 517-553, (2017); Cortes C.E., Matamala M., Contardo C., The pickup and delivery problem with transfers: Formulation and a branch-and-cut solution method, Eur. J. Oper. Res., 200, pp. 711-724, (2010); Dahle L., Andersson H., Christiansen M., Grazia Speranza M., The pickup and delivery problem with time windows and occasional drivers, Comput. Oper. Res., 109, pp. 122-133, (2019); Dayarian I., Savelsbergh M., Crowdshipping and same-day delivery: Employing in-store customers to deliver online orders, Optim. Online, (2017); Ghilas V., Demir E., Van Woensel T., An adaptive large neighborhood search heuristic for the pickup and delivery problem with time windows and scheduled lines, Comput. Oper. Res., 72, pp. 12-30, (2016); Guastaroba G., Grazia Speranza M., Vigo D., Intermediate facilities in freight transportation planning: A survey, Transp. Sci., 50, pp. 763-789, (2016); Kafle N., Zou B., Lin J., Design and modeling of a crowdsource-enabled system for urban parcel relay and delivery, Transp. Res. B: Methodol., 99, pp. 62-82, (2017); Li B., Krushinsky D., Reijers H.A., Van Woensel T., The share-a-ride problem: People and parcels sharing taxis, Eur. J. Oper. Res., 238, pp. 31-40, (2014); Maknoon Y., Laporte G., Vehicle routing with cross-dock selection, Comput. Oper. Res., 77, pp. 254-266, (2017); Masson R., Lehuede F., Peton O., An adaptive large neighborhood search for the pickup and delivery problem with transfers, Transp. Sci., 47, pp. 344-355, (2013); Masson R., Lehuede F., Peton O., The dial-a-ride problem with transfers, Comput. Oper. Res., 41, pp. 12-23, (2014); Mitrovic S., Laporte G., The pickup and delivery problem with time windows and transshipment, INFOR: Inform. Syst. Oper. Res., 44, pp. 217-227, (2006); Nakao Y., Nagamochi H., Worst case analysis for pickup and delivery problems with transfer, IEICE Trans. Fundam. Electron. Commun. Comput. Sci., E91-A, pp. 2328-2334, (2008); Pisinger D., Ropke S., A general heuristic for vehicle routing problems, Comput. Oper. Res., 34, pp. 2403-2435, (2007); Yuan Q., Bard J.F., A GRASP with adaptive large neighborhood search for pickup and delivery problems with transshipment, Comput. Oper. Res., 39, pp. 2439-2456, (2012); Rais A., Alvelos F., Carvalho M., New mixed integer-programming model for the pickup-and-delivery problem with transshipment, Eur. J. Oper. Res., 235, pp. 530-539, (2014); Ropke S., Pisinger D., An adaptive large neighborhood search heuristic for the pickup and delivery problem with time windows, Transp. Sci., 40, pp. 455-472, (2006); Sampaio A., Savelsbergh M., Veelenturf L., Van Woensel T., Crowd-based city logistics, Sustainable Transportation and Smart Logistics: Decision-Making Models and Solutions, Chapter 15, pp. 382-398, (2018); Savelsbergh M., Sol M., The general pickup and delivery problem, Transp. Sci., 29, 1, pp. 17-29, (1995); Stenger A., Vigo D., Enz S., Schwind M., An adaptive variable neighborhood search algorithm for a vehicle routing problem arising in small package shipping, Transp. Sci., 47, pp. 64-80, (2013)","A. Sampaio; School of Industrial Engineering, Eindhoven University of Technology, Eindhoven, Netherlands; email: a.h.sampaio.oliveira@tue.nl",null,"Wiley-Liss Inc.",{"$nulls":5},283045.0,null,null,null,"English","Networks","Article","Final","All Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85087689695"]
["Serrano-Hernandez A.; de la Torre R.; Cadarso L.; Faulin J.","Serrano-Hernandez, Adrian (57215653301); de la Torre, Rocio (57191334574); Cadarso, Luis (6508150537); Faulin, Javier (6506670477)","57215653301; 57191334574; 6508150537; 6506670477","Urban e-grocery distribution design in pamplona (Spain) applying an agent-based simulation model with horizontal cooperation scenarios",2021.0,"Algorithms",14.0,1.0,20.0,null,null,null,3.0,"10.3390/a14010020","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85099785446&doi=10.3390%2fa14010020&partnerID=40&md5=d0bb183abc23557e65943d863fd2cda1","Institute of Smart Cities, Public University of Navarre, Pamplona, 31006, Spain; Aerospace Systems and Transport Research Group, EIATA Institute, Rey Juan Carlos University, Fuenlabrada, 28942, Spain; INARBE Institute, Public University of Navarre, Pamplona, 31006, Spain","Serrano-Hernandez A., Institute of Smart Cities, Public University of Navarre, Pamplona, 31006, Spain, Aerospace Systems and Transport Research Group, EIATA Institute, Rey Juan Carlos University, Fuenlabrada, 28942, Spain; de la Torre R., INARBE Institute, Public University of Navarre, Pamplona, 31006, Spain; Cadarso L., Aerospace Systems and Transport Research Group, EIATA Institute, Rey Juan Carlos University, Fuenlabrada, 28942, Spain; Faulin J., Institute of Smart Cities, Public University of Navarre, Pamplona, 31006, Spain","E-commerce has boosted in the last decades because of the achievements of the information and telecommunications technology along with the changes in the society life-style. More recently, the groceries online purchase (or e-grocery), has also prevailed as a way of making the weekly shopping, particularly, the one including fresh vegetables and fruit. Furthermore, this type of virtual shopping in supermarkets is gaining importance as the most efficient delivery system in cost and time. Thus, we have evaluated in this study the influence of the cooperation-based policies on costs and service quality among different supermarkets in Pamplona, Spain. Concerning methodology, first of all, we carried out a survey in Pamplona having the purpose of modelling the demand patterns about e-grocery. Second, we have developed an agent-based simulation model for generating scenarios in non-cooperative, limited cooperation, and full cooperation settings, considering the real data obtained from the survey analysis. At this manner, Vehicle Routing Problems (VRP) and Multi Depot VRPs (MDVRP) are dynamically generated and solved within the simulation framework using a biased-randomization algorithm. Finally, the results show significant reductions in distance driven and lead times when employing horizontal cooperation in e-grocery distribution. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.","Agent-based simulation; E-groceries; Horizontal cooperation; Optimization","Electronic commerce; Retail stores; Surveys; Telecommunication industry; Vehicle routing; Agent-based simulation models; Cooperation based; Fresh vegetables; Horizontal cooperations; Information and Telecommunications Technology; Randomization algorithm; Simulation framework; Vehicle routing problem; Quality control",{"$nulls":4},"CAN Foundation in Navarre, Spain, (ID 903 100010434, LCF/PR/PR15/51100007); SEPIE Erasmus+, (2019-I-ES01-KA103-062602); Ministerio de Ciencia, Innovación y Universidades, MCIU, (PID2019-111100RB-C22/AEI/10.13039/501100011033, RED2018-102642-T)","Funding: This work has been partially supported by the Spanish Ministry of Science, Innovation, and Universities (RED2018-102642-T; PID2019-111100RB-C22/AEI/10.13039/501100011033) and the SEPIE Erasmus+ Program (2019-I-ES01-KA103-062602). We also want to acknowledge the support received from the CAN Foundation in Navarre, Spain (Grant ID 903 100010434 under the agreement LCF/PR/PR15/51100007).","Kamarainen V., Punakivi M., Developing cost-effective operations for the e-grocery supply chain, Int. J. Logist, 5, pp. 285-298, (2002); Olsson J., Hellstrom D., Palsson H., Framework of last mile logistics research: A systematic review of the literature, Sustainability, 11, (2019); Fredriksson A., Liljestrand K., Capturing food logistics: A literature review and research agenda, Int. J. Logist. Res. Appl, 18, pp. 16-34, (2015); Williams J., Memery J., Megicks P., Morrison M., Ethics and social responsibility in Australian grocery shopping, Int. J. Retail. Distrib. Manag, 38, pp. 297-316, (2010); Teller C., Holweg C., Reiner G., Kotzab H., Retail store operations and food waste, J. Clean. Prod, 185, pp. 981-997, (2018); Fikar C., A decision support system to investigate food losses in e-grocery deliveries, Comput. Ind. 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Res, 22, pp. 647-667, (2015); Serrano-Hernandez A., Juan A., Faulin J., Perez-Bernabeu E., Horizontal collaboration in freight transport: Concepts, benefits, and environmental challenges, Stat. Oper. Res. Trans, 41, pp. 1-22, (2017)","A. Serrano-Hernandez; Institute of Smart Cities, Public University of Navarre, Pamplona, 31006, Spain; email: adrian.serrano@unavarra.es",null,"MDPI AG",{"$nulls":5},1.9994893E7,null,null,null,"English","Algorithms","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85099785446"]
["Chen Y.-H.","Chen, Yi-hua (57217874706)",5.7217874706E10,"Intelligent algorithms for cold chain logistics distribution optimization based on big data cloud computing analysis",2020.0,"Journal of Cloud Computing",9.0,1.0,37.0,null,null,null,39.0,"10.1186/s13677-020-00174-x","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85087745127&doi=10.1186%2fs13677-020-00174-x&partnerID=40&md5=40694c7c77403415bdbc9dd5e5e13cbe","School of software, South China Normal University, Nanhai, 528225, Guangdong, China","Chen Y.-H., School of software, South China Normal University, Nanhai, 528225, Guangdong, China","In recent years, the rapid development of fresh food e-commerce in China has brought about more development opportunities for the cold chain logistics industry but has also presented new challenges. With the development of cloud computing and big data technology, it is increasingly important to study the application of big data and cloud computing technology in cold chain logistics. The purpose of this paper is to study the intelligent algorithm of cold chain logistics distribution optimization based on big data cloud computing analysis. Based on the constituent elements of the cold chain distribution problem and using cloud computing technology to obtain real-time traffic information in the transportation system through a unified access interface, this article analyses the distribution time and cost of refrigerated vehicles, thereby establishing a cold chain distribution vehicle path optimization model. By analysing the parallel programming mode of cloud computing, the parallel design and analysis of a coarse-grained genetic algorithm are used to solve the simulation model of the established optimization model. The experimental results show that the method of optimizing cold chain logistics vehicle routing using cloud computing is effective. When comparing 1, 2, 4, and 8 processors, the execution times are 19.89, 14.52, 8.12, and 6.41, respectively. It can be seen that the more processors there are, the shorter the calculation time. © 2020, The Author(s).","Big data; Cloud computing; Cold chain logistics; Distribution optimization","Big data; Genetic algorithms; Parallel processing systems; Parallel programming; Vehicle routing; Vehicles; Cloud computing technologies; Coarse-grained genetic algorithms; Cold chain logistics; Constituent elements; Intelligent Algorithms; Optimization modeling; Real-time traffic information; Transportation system; Cloud computing",{"$nulls":4},"Han nationality","The authors thank the editor and anonymous reviewers for their helpful comments and valuable suggestions. Yi-hua Chen (1965.08--), male, the Han nationality, born in Shaoyang, Hunan, Master, Associate Professor, engaged in information technology research of the electronic & computer.","Lv Y., Duan Y., Kang W., Traffic flow prediction with big data: a deep learning approach, IEEE Trans Intell Transp Syst, 16, 2, pp. 865-873, (2015); Boru D., Kliazovich D., Granelli F., Energy-efficient data replication in cloud computing datacenters, Clust Comput, 18, 1, pp. 385-402, (2015); Lailossa G.W., The new paradigm of cold chain management systems and it’s logistics on tuna fishery sector in Indonesia, Aacl Bioflux, 8, 3, pp. 381-389, (2015); Andreu-Perez J., Poon C.C.Y., Merrifield R.D., Big data for health[J], IEEE J Biomed Health Inf, 19, 4, pp. 1193-1208, (2015); Zaharia M., Xin R.S., Wendell P., Apache spark: a unified engine for big data processing, Commun ACM, 59, 11, pp. 56-65, (2016); Hashem I.A.T., Chang V., Anuar N.B., The role of big data in smart city, Int J Inf Manag, 36, 5, pp. 748-758, (2016); Liu K., Sheng W., Zhang D., Big data application requirements and scenario analysis in smart distribution network, Proc Csee, 35, 2, pp. 287-293, (2015); Jiang D., Wu S., Chen G., epiC: an extensible and scalable system for processing Big Data, Proc Vldb Endowment, 7, 7, pp. 541-552, (2015); Zheng K., Yang Z., Zhang K., Big data-driven optimization for mobile networks toward 5G, IEEE Netw, 30, 1, pp. 44-51, (2016); Zhou S., Xu Q., Qi Q., Big data in mobile social networks: a QoE-oriented framework, IEEE Netw, 30, 1, pp. 52-57, (2016); Bera S., Misra S., Rodrigues J.J.P.C., Cloud computing applications for smart grid: a survey, Parallel Distributed Syst IEEE Trans, 26, 5, pp. 1477-1494, (2015); Mcgilvary G.A., Barker A., Atkinson M., Ad hoc cloud computing: from concept to realization, Comput Sci, 265, 11, pp. 1063-1068, (2015); Zhong Z., Chen K., Zhai X., Virtual machine-based task scheduling algorithm in a cloud computing environment[J], Tsinghua Sci Technol, 21, 6, pp. 660-667, (2016); Kaur T., Chana I., Energy efficiency techniques in cloud computing- a survey and taxonomy[J], ACM Comput Surv, 48, 2, pp. 1-46, (2015); Barsoum A.F., M, Anwar Hasan. Provable multicopy dynamic data possession in cloud computing systems, IEEE Trans Inf Forensics Security, 10, 3, pp. 485-497, (2015); Cao Z., Lin J., Wan C., Optimal cloud computing resource allocation for demand side Management in Smart Grid, IEEE Trans Smart Grid, 8, 4, pp. 1943-1955, (2017); Shen J., Member I.E.E.E., Anonymous and traceable group data sharing in cloud computing, IEEE Trans Inf Forensics Security, 13, 4, pp. 912-925, (2018); Sabi H.M., Uzoka F.-M.E., Langmia K., Conceptualizing a model for adoption of cloud computing in education, Int J Inf Manag, 36, 2, pp. 183-191, (2016); Wang J., Chen X., Huang X., Verifiable auditing for outsourced database in cloud computing, IEEE Trans Comput, 64, 11, (2015); Cai H., Xu B., Jiang L., IoT-based big data storage systems in cloud computing: perspectives and challenges, IEEE Internet Things J, 4, 1, pp. 75-87, (2017); Bo C.H.E.N., Ao Z.H.O.U., An analysis of the cold chain logistics concerning agricultural products in Chongqing City, Asian Agric Res, 8, 1, pp. 19-21, (2016); Zhang H., Qiu B., Zhang K., A new risk assessment model for agricultural products cold chain logistics, Ind Manag Data Syst, 117, 9, pp. 1800-1816, (2017); Ebing L., Mintian Z., The new Gsp pharmaceutical cold chain logistics present situation and the suggestions of the development of quality management, J Liaoning Univ Tradit Chin Med, 18, 4, pp. 519-533, (2015); Xi-Chuan Z.H.A.I., Yong-Feng L.I.U., Ye W.A.N.G., Application of modeling techniques based on CFD in food cold chain logistics, J Food Saf Qual, 1, pp. 207-211, (2015); Wang Y., Li J., Wang H.H., Cluster and cloud computing framework for scientific metrology in flow control, Clust Comput, 22, 1, pp. 1-10, (2019)","Y.-H. Chen; School of software, South China Normal University, Nanhai, 528225, China; email: cy89aa@163.com",null,"Springer",{"$nulls":5},"2192113X",null,null,null,"English","J. Cloud Comput.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85087745127"]
["Shen J.","Shen, J. (56562136100)",5.65621361E10,"An e-commerce facility location problem under uncertainty",2021.0,"Scientia Iranica",28.0,"1 E",null,412.0,423.0,11.0,0.0,"10.24200/sci.2019.50437.1692","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85102480761&doi=10.24200%2fsci.2019.50437.1692&partnerID=40&md5=ccbfed41a754a260eba3d19ca2e99fd0","Department of Public Basic Courses, Nanjing Institute of Industry Technology, Nanjing, Jiangsu, 210023, China","Shen J., Department of Public Basic Courses, Nanjing Institute of Industry Technology, Nanjing, Jiangsu, 210023, China","Facility location problem is a branch of operations research and computational geometry. It covers the best allocation of facilities to minimize transportation costs by considering the factors involved (e.g., avoiding the placement of dangerous materials near the premises and the facilities of competitors). Given the unique customer characteristics and the erce market competition of business-to-consumer e-commerce, the expected value model and chance-constrained model for uncertain facility location problems were constructed. Owing to the intricacies of the competitive market, supply capacity, delivery cost, and customer demand were assumed as uncertain variables. The deterministic equivalent forms of the models were discussed using the inverse uncertainty distribution method. A hybrid algorithm was proposed to solve these models. Some numerical experiments were used to verify the e ectiveness of the proposed models and method. © 2021 Sharif University of Technology. All rights reserved.","Chance-constrained; Expected value; Facility location; Supply chain network; Uncertain environment","Competition; Computational geometry; Electronic commerce; Location; Materials handling; Numerical methods; Operations research; Business to consumer E commerces; Chance-constrained model; Competitive markets; Deterministic equivalents; Expected value model; Facility location problem; Numerical experiments; Uncertainty distributions; business; competition (economics); computer simulation; demand analysis; electronic commerce; facility location; market system; research work; uncertainty analysis; Inverse problems",{"$nulls":4},"Research Foundation of NIIT, (YK18-10-03, YK18-10-02); National Natural Science Foundation of China, NSFC, (61673011)","I am grateful to the editor and the anonymous reviewers for their helpful suggestions on an earlier version of this paper. This work is supported by the National Natural Science Foundation of China (No. 61673011) and Research Foundation of NIIT (YK18-10-02, YK18-10-03).","Cao M., Zhang Q.Y., Seydel J., B2C e-commerce web site quality: an empirical examination, Industrial Management & Data Systems, 105, 5, pp. 645-661, (2005); Chiu C.M., Wang E.T.G., Fang Y.H., Huang H.Y., Understanding customers' repeat purchase intentions in B2C e-commerce: the roles of utilitarian value, hedonic value and perceived risk, Information Systems Journal, 24, 1, pp. 85-114, (2014); Gefen D., Straub D.W., Consumer trust in B2C e-commerce and the importance of social presence: experiments in e-products and e-services, Omega, 32, 6, pp. 407-424, (2004); Klose A., Drexl A., Facility location models for distribution system design, European Journal of Operational Research, 162, 1, pp. 4-29, (2005); Manzini R., Gebennini E., Optimization models for the dynamic facility location and allocation problem, International Journal of Production Research, 46, 8, pp. 2061-2086, (2008); 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Zhou J., Liu B.D., Modeling capacitated location-allocation problem with fuzzy demands, Computers & Industrial Engineering, 53, 3, pp. 454-468, (2007); Liu B.D., Uncertainty Theory, (2007); Liu B.D., Uncertainty Theory: A Branch of Mathematics for Modeling Human Uncertainty, (2010); Shen J.Y., Zhu Y.G., Uncertain exible ow shop scheduling problem subject to breakdowns, Journal of Intelligent & Fuzzy Systems, 32, 1, pp. 207-214, (2017); Shen J.Y., Zhu K., An uncertain single machine scheduling problem with periodic maintenance, Knowledge-Based Systems, 144, pp. 32-41, (2018); Shen J.Y., Zhu Y.G., An uncertain programming model for single machine scheduling problem with batch delivery, Journal of Industrial and Management Optimization, 15, 2, pp. 577-593, (2019); Wen M.L., Qin Z.F., Kang R., The -cost minimization model for capacitated facility location-allocation problem with uncertain demands, Fuzzy Optimization and Decision Making, 13, 3, pp. 345-356, (2014); Chen Z.H., Lan Y.F., Zhao R.Q., Impacts of risk attitude and outside option on compensation contracts under di erent information structures, Fuzzy Optimization and Decision Making, 17, 1, pp. 13-47, (2018); Liu Y.H., Ralescu D.A., Value-at-risk in uncertain random risk analysis, Information Sciences, 391, 1, pp. 1-8, (2017); Zhou J., Liu Y.Y., Zhang X.X., Gu X., Wang D., Uncertain risk aversion, Journal of Intelligent Manufacturing, 28, 3, pp. 615-624, (2017); Chen X.W., Uncertain calculus with nite variation processes, Soft Computing, 19, 10, pp. 2905-2912, (2015); Yang X.F., Gao J.W., Kar S., Uncertain calculus with Yao process, IEEE Transactions on Fuzzy Systems, 24, 6, pp. 1578-1585, (2016); Yao K., Multi-dimensional uncertain calculus with Liu process, Journal of Uncertain Systems, 8, 4, pp. 244-254, (2014); Liu H.J., Fei W.Y., Neutral uncertain delay di erential equations, Information: An International Interdisciplinary Journal, 16, 2, pp. 1225-1232, (2013); Wang Z.R., Analytic solution for a general type of uncertain di erential equation, Information: An International Interdisciplinary Journal, 16, 2, pp. 1003-1010, (2013); Yao K., Gao J.W., Gao Y., Some stability theorems of uncertain di erential equation, Fuzzy Optimization and Decision Making, 12, 1, pp. 3-13, (2013); Liu B.D., Some research problems in uncertainty theory, Journal of Uncertain Systems, 3, 1, pp. 3-10, (2009); Jiang Z.Z., Wang D.W., Ip W.H., Fuzzy programming model and algorithm for optimal design of distribution centers for B2C e-commerce, Proceedings of 2007 IEEE International Conference on Automation and Logistics, pp. 1533-1539, (2007)","J. Shen; Department of Public Basic Courses, Nanjing Institute of Industry Technology, Nanjing, Jiangsu, 210023, China; email: fjcyue007@126.com",null,"Sharif University of Technology",{"$nulls":5},1.0263098E7,null,null,null,"English","Sci. Iran.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85102480761"]
["Nali M.C.; Purushothaman V.; Xu Q.; Cuomo R.E.; Mackey T.K.","Nali, Matthew C. (57220921834); Purushothaman, Vidya (57219703630); Xu, Qing (57209582523); Cuomo, Raphael E. (55814198900); Mackey, Timothy K. (30067646600)","57220921834; 57219703630; 57209582523; 55814198900; 30067646600","Characterizing and assessing compliance of online vendors to the state of Massachusetts ENDS product sales ban",2021.0,"Tobacco Induced Diseases",19.0,{"$nulls":5},3.0,"10.18332/TID/131199","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85100768996&doi=10.18332%2fTID%2f131199&partnerID=40&md5=1117e34526a1dc62fd96209b6e3d62b1","Global Health Policy Institute, San Diego, United States; Department of Anesthesiology, University of California San Diego School of Medicine, San Diego, United States; Master’s Program in Public Health, University of California San Diego School of Medicine, San Diego, United States; Department of Healthcare Research and Policy, University of California San Diego - Extension, San Diego, United States; Division of Infectious Diseases and Global Public Health, Department of Medicine, University of California San Diego School of Medicine, San Diego, United States","Nali M.C., Global Health Policy Institute, San Diego, United States, Department of Anesthesiology, University of California San Diego School of Medicine, San Diego, United States; Purushothaman V., Department of Anesthesiology, University of California San Diego School of Medicine, San Diego, United States, Master’s Program in Public Health, University of California San Diego School of Medicine, San Diego, United States; Xu Q., Global Health Policy Institute, San Diego, United States, Department of Healthcare Research and Policy, University of California San Diego - Extension, San Diego, United States; Cuomo R.E., Global Health Policy Institute, San Diego, United States, Department of Anesthesiology, University of California San Diego School of Medicine, San Diego, United States, Department of Healthcare Research and Policy, University of California San Diego - Extension, San Diego, United States; Mackey T.K., Global Health Policy Institute, San Diego, United States, Department of Anesthesiology, University of California San Diego School of Medicine, San Diego, United States, Department of Healthcare Research and Policy, University of California San Diego - Extension, San Diego, United States, Division of Infectious Diseases and Global Public Health, Department of Medicine, University of California San Diego School of Medicine, San Diego, United States","INTRODUCTION Recent reports of lung injury associated with Electronic Nicotine Delivery System (ENDS) products precipitated by increasing vaping prevalence and interest in flavors among adolescents has led to policies that restrict the sale, distribution, and accessibility of ENDS products. This study assessed compliance of online ENDS vendors to the Massachusetts temporary sales ban. METHODS The study involved structured web surveillance for online ENDS vendors using keyword searches on Google search engine (October to November 2019.) Once vendors were identified, we conducted simulated online purchases, defined as placing an order for an ENDS product by putting it in the website shopping cart without finalizing payment. Simulated purchases and content analysis of websites was conducted to determine compliance characteristics. Fisher’s exact test was used to identify associations between compliance and website characteristics such as location and age verification requirements. RESULTS Simulated online purchases from 50 identified ENDS vendors yielded 72% (n=36) stores that were non-compliant and allowed placement of ENDS product orders, without restrictions, to a Massachusetts address. The remaining 14 websites had processes in place to prevent orders from buyers located in Massachusetts. Other characteristics of interest, including use of age verification, location data, and web registrar/registrant data were collected and reported. CONCLUSIONS The September 2019 Massachusetts executive order was a comprehensive ban on selling ENDS products both online and offline. However, our study found that close to three-fourths of the vendors appeared to be non-compliant, indicating that implementation and enforcement are ongoing challenges for future tobacco control efforts on the internet. Policymaking needs to be specifically tailored to address the unique challenges of online environments, particularly in the context of identifying non-compliant sites, ensuring age verification, and addressing non-US sellers. © 2021 Nali M.C. et al.",null,"age; Article; commercial phenomena; Massachusetts; online shopping; online system; priority journal; risk factor; sales ban; simulation",{"$nulls":4},"University of California Tobacco-related Disease Research Program, (T29IP0384)","The authors have each completed and submitted an ICMJE form for disclosure of potential conflicts of interest. The authors declare that they have no competing interests, financial or otherwise, related to the current work. M.C. Nali, Q. Xu, and T.K. Mackey report funding from S-3 Research LLC, outside the submitted work.","Declaration of a Public Health Emergency, (2019); States and Localities that Have Restricted The Sale of Flavored Tobacco Products; Dai H, Leventhal AM., Prevalence of e-Cigarette Use among Adults in the United States, 2014-2018, JAMA, 322, 18, pp. 1824-1827, (2019); Miech R, Johnston L, O'Malley PM, Bachman JG, Patrick ME., Trends in Adolescent Vaping, 2017–2019, N Engl J Med, 381, 15, pp. 1490-1491, (2019); Ghinai I, Pray IW, Navon L, Et al., E-cigarette Product Use, or Vaping, Among Persons with Associated Lung Injury — Illinois and Wisconsin, April–September 2019, MMWR Morb Mortal Wkly Rep, 68, 39, pp. 865-869, (2019); Moritz ED, Zapata LB, Lekiachvili A, Et al., Update: Characteristics of Patients in a National Outbreak of E-cigarette, or Vaping, Product Use–Associated Lung Injuries — United States, October 2019, MMWR Morb Mortal Wkly Rep, 68, 43, pp. 985-989, (2019); Siegel DA, Jatlaoui TC, Koumans EH, Et al., Update: Interim Guidance for Health Care Providers Evaluating and Caring for Patients with Suspected E-cigarette, or Vaping, Product Use Associated Lung Injury — United States, October 2019, MMWR Morb Mortal Wkly Rep, 68, 41, pp. 919-927, (2019); Outbreak of Lung Injury Associated with the Use of E-Cigarette, or Vaping, Products; E-Cigarettes and Liquid Nicotine; Rules Committee Print 116–44: Text of the House Amendment to the Senate Amendment to H.R. 1865; FDA finalizes enforcement policy on unauthorized flavored cartridge-based e-cigarettes that appeal to children, including fruit and mint; Axelrod T., New York bans flavored e-cigarettes, The Hill, (2019); Health Code - Restricting the Sale, Manufacture, and Distribution of Tobacco Products, Including Electronic Cigarettes, (2019); Ravikumar V., Smokers, beware: Beverly Hills says it is the first US city to ban tobacco sales; Murga T., City Council: New sales of flavored tobacco temporarily banned, The Santa Clarita Valley Signal, (2019); Cohen J, Sarabia V, Ashley MJ., Tobacco commerce on the internet: A threat to comprehensive tobacco control, Tob Control, 10, 4, pp. 364-367, (2001); Samuel KA, Ribisl KM, Williams RS., Internet cigarette sales and Native American sovereignty: Political and public health contexts, J Public Health Policy, 33, 2, pp. 173-187, (2012); Williams RS, Derrick J, Liebman AK, LaFleur K., Content analysis of e-cigarette products, promotions, prices and claims on Internet tobacco vendor websites, 2013-2014, Tob Control, 27, e1, pp. e34-e40, (2018); Williams RS, Derrick J, Liebman AK, LaFleur K, Ribisl KM., Content analysis of age verification, purchase and delivery methods of internet e-cigarette vendors, 2013 and 2014, Tob Control, 27, 3, pp. 287-293, (2018); Williams RS, Derrick J, Ribisl KM., Electronic cigarette sales to minors via the internet, JAMA Pediatr, 169, 3, (2015); Ribisl KM, Kim AE, Williams RS., Web sites selling cigarettes: How many are there in the USA and what are their sales practices?, Tob Control, 10, 4, pp. 352-359, (2001); Williams RS, Derrick JC., Internet little cigar and cigarillo vendors: Surveillance of sales and marketing practices via website content analysis, Prev Med (Baltim), 109, pp. 51-57, (2018); Bryant JA, Cody MJ, Murphy ST., Online sales: Profit without question, Tob Control, 11, 3, pp. 226-227, (2002); Mackey TK, Miner A, Cuomo RE., Exploring the e-cigarette e-commerce marketplace: Identifying Internet e-cigarette marketing characteristics and regulatory gaps, Drug Alcohol Depend, 156, pp. 97-103, (2015); Chriqui JF, Ribisl KM, Wallace RM, Williams RS, O'Connor JC, el Arculli R., A comprehensive review of state laws governing Internet and other delivery sales of cigarettes in the United States, Nicotine Tob Res, 10, 2, pp. 253-265, (2008); Child-Resistant Packaging for Liquid Nicotine: Are Current State and Federal Policy Responses Adequate?; Sales Restrictions; (2019); Ineligible businesses; Braak DC, Cummings MK, Nahhas GJ, Et al., Where do vapers buy their vaping supplies? Findings from the international tobacco control (ITC) 4 country smoking and vaping survey, Int J Environ Res Public Health, 16, 3, (2019); Nguyen H, Dennehy CE, Tsourounis C., Violation of US regulations regarding online marketing and sale of e-cigarettes: FDA warnings and retailer responses, Tob Control, (2020); Outbreak of Lung Injury Associated with the Use of E-Cigarette, or Vaping, Products","T.K. Mackey; Global Health Policy Institute, San Diego, 8950 Villa La Jolla Drive, Suite A124, 92037, United States; email: tmackey@ucsd.edu",null,"International Society for the Prevention of Tobacco Induced Diseases",{"$nulls":5},1.6179625E7,null,null,null,"English","Tob. Induced Dis.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85100768996"]
["Barykin S.Y.; Smirnova E.; Sharapaev P.; Mottaeva A.","Barykin, Sergey Yevgenievich (57202814691); Smirnova, Elena (57205202070); Sharapaev, Petr (57224518188); Mottaeva, Angela (57221193402)","57202814691; 57205202070; 57224518188; 57221193402","Development of the kazakhstan digital retail chains within the eaeu e-commerce market",2021.0,"Academy of Strategic Management Journal",20.0,"SpecialIssue2",null,1.0,18.0,17.0,39.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85107790741&partnerID=40&md5=f03a622327515c545f578b24888ee732","Peter the Great St. Petersburg Polytechnic University, Russian Federation; St. Petersburg State University of Economics, Russian Federation; Mazhilis of the Parliament of the Republic of Kazakhstan, Russian Federation; Moscow State University of Civil Engineering, Russian Federation","Barykin S.Y., Peter the Great St. Petersburg Polytechnic University, Russian Federation; Smirnova E., St. Petersburg State University of Economics, Russian Federation; Sharapaev P., Mazhilis of the Parliament of the Republic of Kazakhstan, Russian Federation; Mottaeva A., Moscow State University of Civil Engineering, Russian Federation","The article covers the theoretical and practical experience which could be implemented for the designing of Kazakhstan digital retail chains. The lack of the studies in the field of the operation of digital retail chains in Kazakhstan’s e-commerce market within the EAEU could be defined as a research gap. The authors consider the research task as studying the features of the digital retail chains of the Republic of Kazakhstan and the potential of its development in the e-commerce market within the EAEU. The article aims in investigating the advantages and disadvantages of the infrastructure for the development of the digital retail chains and in general e-commerce in Kazakhstan. The authors explore the product distribution system in the sphere of trade, promoting growth in the country’s retail chains, particularly, in the field of online commerce. The research methods include both the system analysis and PEST method, as well as the comparative analysis and synthesis, allowing to trace the main trends in the development of the Kazakhstan’s digital retail chains in the e-commerce market. As we have established, the main findings include the specific drivers of the development of Kazakhstan’s digital retail chains. The most significant advantage of the infrastructure for the digital retail chains could be observed from the active introduction of digital technologies, influencing the development of e-commerce and leading to a shift in emphasis when configuring the network structure of physical retail chains, as well as the development of new models of interaction between counterparties. The topics of further research on Kazahkstan’s e-commerce market could be developing recommendations for building an integrated digital platform that will allow to perform trade and logistics operations quickly, safely and with minimal costs. © 2021","Digital Retail Chains; Digital Trading Platforms; E-commerce; Eurasian Economic Union; Republic of Kazakhstan",{"$nulls":7},"Abdunurova A., Surapbergenova Z., Digital consumer behavior in tourism: A cross-national analysis in Asian countries, Conference Proceedings, pp. 201-224, (2019); Akhmetova Z., Baimukhanbetova E., Belgozhakyzy M., Alikbaeva A., Tulebaeva N., The development of e-commerce infrastructure in modern conditions, E3S Web of Conferences, 159, (2020); Alimkhanova S.K., Legal aspects of harmonization of labor legislation of kazakhstan and the eurasian economic union countries (EAEU), Journal of Advanced Research in Law and Economics, 11, 4, pp. 1080-1086, (2020); Atkinson J., Managing change and embedding innovation in academic libraries and information services, New Review of Academic Librarianship. Routledge, 9, 1, pp. 25-41, (2003); Bayadyan A., Baghdasaryan A., Problems of development and integration of the securities market in the countries of the eaeu, International Organisations Research Journal, 12, 4, pp. 91-108, (2017); Bogers M., Chesbrough H., Heaton S., Teece D.J., Strategic management of open innovation: A dynamic capabilities perspective, California Management Review, 62, 1, pp. 77-94, (2019); Bogers M., Chesbrough H., Moedas C., Open innovation: Research, practices, and policies, California Management Review, 60, 2, pp. 5-16, (2018); Bril A., Kalinina O., Levina A., Two-stage commercial evaluation of engineering systems production projects for high-rise buildings, E3S Web of Conferences, 33, (2018); Bril A., Kalinina O., Valebnikova O., Innovation venture financing projects in information technology. in internet of things, smart spaces, and Next generation networks and Systems, 9870, pp. 766-775, (2016); Bukharbayeva A.Z., Nauryzbayev A.Z., Jrauova K.S., Oralbayeva K., Aimagambetova A.D., Formation of the transport and logistics system as the basis for rice production development in the Kazakhstan Aral Sea region in the context of the EAEU economic integration, Academy of Strategic Management Journal, 19, 3, pp. 1-7, (2020); Chesbrough H., Vanhaverbeke W., West J., Chapter 13 Open innovation in value networks, Open Innovation: Researching a New Paradigm, (2006); Christensen C.M., McDonald R., Altman E.J., Palmer J.E., Disruptive innovation: An intellectual history and directions for future research, Journal of Management Studies, 55, 7, pp. 1043-1078, (2018); Christensen J.F., Olesen M.H., Kjaer J.S., The industrial dynamics of Open Innovation - Evidence from the transformation of consumer electronics, Research Policy, 34, 10, pp. 1533-1549, (2005); Chung K.C., Mobile (shopping) commerce intention in central Asia: The impact of culture, innovation characteristics and concerns about order fulfilment, Asia-Pacific Journal of Business Administration, 11, 3, pp. 251-266, (2019); Cox J., The higher education environment driving academic library strategy: A political, economic, social and technological (PEST) analysis, Journal of Academic Librarianship. 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Elsevier B.V, 43, 5, pp. 805-811, (2014); Yemelina N., Omarova A., Anara K., Analysis and forecast of prices of the housing market, Journal of Applied Economic Sciences, 13, 3, pp. 843-851, (2018); Yun J.J., Kim D., Yan MR., Open innovation engineering—preliminary study on new entrance of technology to market, Electronics (Switzerland), 9, 5, pp. 1-10, (2020); Zaurbekova Z., Role of global supply chain strategy in control of transfer pricing in the EAEU countries, International Journal of Supply Chain Management, 9, 4, pp. 1046-1054, (2020); Zhekenov D., Darkenbaev A., Zhunisov Z., The ‘Nurly Zhol’ and the ‘One Belt, One Road’ projects: Juxtaposition of an idea, The challenge of change for the legal and political systems of Eurasia: The impact of the new silk road, pp. 131-140, (2020)",null,null,"Allied Business Academies",{"$nulls":5},1.5441458E7,null,null,null,"English","Acad. Strateg. Manage. J","Article","Final",null,"Scopus","2-s2.0-85107790741"]
["Weingarten J.; Spinler S.","Weingarten, Jennifer (57219352835); Spinler, Stefan (7006502092)","57219352835; 7006502092","Shortening Delivery Times by Predicting Customers’ Online Purchases: A Case Study in the Fashion Industry",2021.0,"Information Systems Management",38.0,4.0,null,287.0,308.0,21.0,8.0,"10.1080/10580530.2020.1814459","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85092355941&doi=10.1080%2f10580530.2020.1814459&partnerID=40&md5=caa32bf775108beef1e85f0fc4528547","WHU – Otto Beisheim School of Management, Kühne Institute for Logistics Management, Vallendar, Germany","Weingarten J., WHU – Otto Beisheim School of Management, Kühne Institute for Logistics Management, Vallendar, Germany; Spinler S., WHU – Otto Beisheim School of Management, Kühne Institute for Logistics Management, Vallendar, Germany","Limited research exists that investigates how big data can be used to optimize delivery times for customers. The goal of this paper is to develop a prediction model for anticipatory shipping, which predicts customers’ online purchases with the aim of shipping products in advance, and subsequently minimizing delivery times. Results indicate that customer purchases are, to a certain extent, predictable, but anticipatory shipping comes at a high cost due to wrongly sent products. © 2020 Taylor & Francis.","Anticipatory shipping; big data analytics; e-commerce; online purchases; prediction","Electronic commerce; Predictive analytics; Ships; Delivery time; Fashion industry; High costs; Prediction model; Sales",{"$nulls":6},"Akter S., Wamba S.F., Big data analytics in e-commerce: A systematic review and agenda for future research, Electronic Markets, 26, 2, pp. 173-194, (2016); Baesens B., Van Gestel T., Viaene S., Stepanova M., Suykens J., Vanthienen J., Benchmarking state-of-the-art classification algorithms for credit scoring, Journal of the Operational Research Society, 54, 6, pp. 627-635, (2003); Bergmann H., Versand- und Retourenmanagement im E-Commerce 2018 (Report No. VER16493), (2018); Breiman L., Random forests, Machine Learning, 45, 1, pp. 5-32, (2001); Chang P.C., Liu C.H., Fan C.Y., Data clustering and fuzzy neural network for sales forecasting: A case study in printed circuit board industry, Knowledge-Based Systems, 22, 5, pp. 344-355, (2009); Chen I., Lu C., Sales forecasting by combining clustering and machine-learning techniques for computer retailing, Neural Computing & Applications, 28, 9, pp. 2633-2647, (2017); Chen Z.Y., Fan Z.P., Sun M., A hierarchical multiple kernel support vector machine for customer churn prediction using longitudinal behavioral data, European Journal of Operational Research, 223, 2, pp. 461-472, (2012); Choi Y., Lee H., Irani Z., Big data-driven fuzzy cognitive map for prioritising IT service procurement in the public sector, Annals of Operations Research, 270, 1-2, pp. 75-104, (2018); Cirqueira D., Hofer M., Nedbal D., Helfert M., Bezbradica M., Customer purchase behavior prediction in e-commerce: A conceptual framework and research agenda, New frontiers in mining complex patterns. 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Sismeiro C., Bucklin R.E., Modeling purchase behavior at an e-commerce web site: A task-completion approach, Journal of Marketing Research, 41, 3, pp. 306-323, (2004); Spiegel J.R., McKenna M.T., Lakshman G.S., Nordstrom P.G., Method and system for anticipatory package shipping (U.S. Patent No. 8,615,473), U.S. Patent and Trademark Office, (2013); Tax D.M., Duin R.P., Support vector data description, Machine Learning, 54, 1, pp. 45-66, (2004); Thomassey S., Fiordaliso A., A hybrid sales forecasting system based on clustering and decision trees, Decision Support Systems, 42, 1, pp. 408-421, (2006); Tiwari S., Wee H.M., Daryanto Y., Big data analytics in supply chain management between 2010 and 2016: Insights to industries, Computers & Industrial Engineering, 115, pp. 319-330, (2018); Van den Poel D., Buckinx W., Predicting online-purchasing behaviour, European Journal of Operational Research, 166, 2, pp. 557-575, (2005); Verbeke W., Dejaeger K., Martens D., Hur J., Baesens B., New insights into churn prediction in the telecommunication sector: A profit driven data mining approach, European Journal of Operational Research, 218, 1, pp. 211-229, (2012); Viet N.Q., Behdani B., Bloemhof J., Data-driven process redesign: Anticipatory shipping in agro-food supply chains, International Journal of Production Research, 58, 5, pp. 1302-1318, (2020); Voccia S.A., Campbell A.M., Thomas B.W., The same-day delivery problem for online purchases, Transportation Science, 53, 1, pp. 167-184, (2019); Wang G., Gunasekaran A., Ngai E.W., Papadopoulos T., Big data analytics in logistics and supply chain management: Certain investigations for research and applications, International Journal of Production Economics, 176, pp. 98-110, (2016); Xu L., Duan J.A., Whinston A., Path to purchase: A mutually exciting point process model for online advertising and conversion, Management Science, 60, 6, pp. 1392-1412, (2014); Yang Y., Pan B., Song H., Predicting hotel demand using destination marketing organization’s web traffic data, Journal of Travel Research, 53, 4, pp. 433-447, (2014); Zhao Q., Zhang Y., Friedman D., Tan F., E-commerce recommendation with personalized promotion, Proceedings of the 9th ACM Conference on Recommender Systems, Vienna, pp. 219-226, (2015)","J. Weingarten; Cologne, 50933, Germany; email: jennifer.weingarten@whu.edu",null,"Taylor and Francis Ltd.",{"$nulls":5},1.058053E7,null,null,null,"English","Inf. Syst. Manage.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85092355941"]
["Li T.","Li, Tao (57202353954)",5.7202353954E10,"A SWOT analysis of China's air cargo sector in the context of COVID-19 pandemic",2020.0,"Journal of Air Transport Management",88.0,null,101875.0,null,null,null,51.0,"10.1016/j.jairtraman.2020.101875","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85088946857&doi=10.1016%2fj.jairtraman.2020.101875&partnerID=40&md5=d1ce19dfb3a6ee30dd15852ca81f3b20","Hebei University of Economics and Business, Law School, Xuefu Road No.47, Shijiazhuang, China","Li T., Hebei University of Economics and Business, Law School, Xuefu Road No.47, Shijiazhuang, China","This paper discusses the situation of China's air cargo sector facing the COVID-19 pandemic. Based on the expectation that it can go out of recession more easily than China's air passenger sector, this paper analyzes four aspects that are favorable and unfavorable for its further development: (1) strengths (China's sustainable economic basis and proliferating cargo suppliers), (2) weaknesses (insufficient cargo capacity and less business internationalization), (3) opportunities (top authority support, rising e-commerce demand, and new technological momentum), and (4) challenges (uncertain trade environment and increasing profitability pressure). Then this paper suggests strategies for China's air cargo suppliers to adapt to the pandemic. © 2020 Elsevier Ltd","Air cargo capacity; COVID-19; Digital logistics; e-commerce; Integrated supply chain","China; air transportation; cargo; demand analysis; electronic commerce; sustainable development",{"$nulls":4},"Ministry of Science and Technology of the People's Republic of China, MOST, (2018YFC0831800); Ministerio de Ciencia y TecnologÃ­a, MICYT","Funding text 1: This wok was supported by the Ministry of Science and Technology of PRC [grant number 2018YFC0831800].; Funding text 2: This wok was supported by the Ministry of Science and Technology of PRC [grant number 2018YFC0831800 ]. ","Budd L., Ison S., The role of dedicated freighter aircraft in the provision of global airfreight services, J. Air Transport. Manag., 61, pp. 34-40, (2017); Chow C.K.W., Measuring the productivity changes of Chinese airlines: the impact of the entries of non-state-owned carriers, J. Air Transport. Manag., 16, 6, pp. 320-324, (2010); Chow C.K.W., Fung M.K.Y., Measuring the effects of China's airline mergers on the productivity of state-owned carriers, J. Air Transport. Manag., 25, pp. 1-4, (2012); Doganis R., The Airline Business, (2006); Jiang H., Et al., Market and infrastructure analysis of future air cargo demand in China, AIAA's 3rd Annual Aviation Technology, Integration, and Operations Forum, (2003); Kasarda J.D., Green J.D., Air cargo as an economic development engine: a note on opportunities and constraints, J. Air Transport. Manag., 11, 6, pp. 459-462, (2005); Kupfer F., Et al., The underlying drivers and future development of air cargo, J. Air Transport. Manag., 61, pp. 6-14, (2017); Merkert R., Et al., Making or breaking - key success factors in the air cargo market, J. Air Transport. Manag., 61, pp. 1-5, (2017); Tijan E., Et al., Blockchain technology implementation in logistics, Sustainability, 11, 4, (2019); Wang H., China's approach to the belt and road initiative: scope, character and sustainability, J. Int. Econ. Law, 22, 1, pp. 29-55, (2019); Wang K., Et al., Benchmarking the performance of Chinese airlines: an investigation of productivity, yield and cost competitiveness, J. Air Transport. Manag., 38, pp. 3-14, (2014); Wu Y., Et al., The impact of environmental variables on the efficiency of Chinese and other non-Chinese airlines, J. Air Transport. Manag., 29, pp. 35-38, (2013); Zhang A., Industrial reform and air transport development in China, J. Air Transport. Manag., 4, 3, pp. 155-164, (1998); Zhang Y., Et al., Exploring the roles of high-speed train, air and coach services in the spread of covid-19 in China, Transport Pol., 94, pp. 34-42, (2020)",null,null,"Elsevier Ltd",{"$nulls":5},9696997.0,null,null,null,"English","J. Air Transp. Manage.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85088946857"]
["Abdallah A.A.","Abdallah, Abdallah A. (20336956300)",2.03369563E10,"Simulated Six Sigma: A multi response optimization",2020.0,"Quality Engineering",32.0,4.0,null,583.0,594.0,11.0,8.0,"10.1080/08982112.2019.1694151","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85080147943&doi=10.1080%2f08982112.2019.1694151&partnerID=40&md5=1136d68aae9d2591245569866a222924","Graduate School of Business Administration, The German Jordanian University, Amman, Jordan","Abdallah A.A., Graduate School of Business Administration, The German Jordanian University, Amman, Jordan","Six Sigma is widely used in many industries for the purpose of improving process performance. Typical improvements sought in Six Sigma projects include decreased operational cost, increased customer satisfaction, decreased cycle time, and enhanced profits, but regardless of the nature of the improvement, all projects follow the “Define-Measure-Analyze-Improve-Control” (DMAIC) methodology. This paper proposes the use of simulation and multi response optimization in addition to other typical Six Sigma tools in order to arrive at optimum performance at the end of each project through an established optimization framework. The framework is used in a real case study performed at a global logistics company. The case study is concerned with an e-commerce logistics station located at John F. Kennedy airport (JFK) in New York; a station that suffers from low on-time delivery performance and high operational cost. As result, a Six Sigma project was implemented and the process was simulated to reveal various scenarios suggested by the Six Sigma team in order to optimize the process. The project resulted in 65 percent reduction in labor, 41 percent reduction in work in process (WIP) and 55 percent reduction in average time packages spend at the station. These improvements highly support the effectiveness of implementing Six Sigma projects in the format suggested. © 2020 Taylor & Francis Group, LLC.","desirability index; logistics; optimization; simulation; Six Sigma","Customer satisfaction; Logistics; Optimization; Process monitoring; Silicon; Six sigma; Work simplification; desirability index; Multiresponse optimization; On-time delivery performance; Optimization framework; Optimum performance; Process performance; simulation; Six sigma project; Process engineering",{"$nulls":6},"Antony J., Banuelas R., Six Sigma: A strategy for survival, Manufacturing Engineering, 80, 3, pp. 119-121, (2001); Banks J., John S.C., Barry L.N., David M.N., Discrete-event system simulation, (2010); Bowie B., Air freighting of perishable agribusiness products: Process and issues, (2018); Cudney E.A., Kestle R., Implementing Lean Six Sigma throughout the supply chain: The comprehensive and transparent case study, (2018); Del Castillo E., Montgomery D.C., McCarville D.R., Modified desirability functions for multiple response optimization, Journal of Quality Technology, 28, 3, pp. 337-345, (1996); Derringer G., Suich R., Simultaneous optimization of several response variables, Journal of Quality Technology, 12, 4, pp. 214-219, (1980); Folaron J., The evolution of Six Sigma, Six Sigma Forum Magazine, 2, 4, pp. 38-44, (2003); Goldsby T., Martichenko R., Lean Six Sigma logistics, (2005); Gutierrez-Gutierrez L., Sander L., Ruud D., Logistics services and Lean Six Sigma implementation: A case study, International Journal of Lean Six Sigma, 7, 3, pp. 324-342, (2016); Jeong I.J., Kim K.J., An interactive desirability function method to multiresponse optimization, European Journal of Operational Research, 195, 2, pp. 412-426, (2009); Kelton W.D., Randall P.S., David T.S., Simulation with arena, (2007); Kovacs G., Kot S., New logistics and production trends as the effect of global economy changes, Polish Journal of Management Studies, 14, 2, pp. 115-126, (2016); Kwak Y.H., Anbari F.T., Benefits, obstacles, and future of Six Sigma approach, Technovation, 26, 5-6, pp. 708-715, (2006); Olga M.F., Carvalho W., Edson P.P., Lean Six Sigma in Brazil: A literature Review, International Journal of Lean Six Sigma, 10, 1, pp. 435-472, (2019); Park Y., Choi J.K., Zhang A., Evaluating competitiveness of air cargo express services, Transportation Research Part E: Logistics and Transportation Review, 45, 2, pp. 321-334, (2009); Pyzdek T., Keller P., The Six Sigma handbook, (2014); Qatawneh L., Abdallah A., Zalloum S., Six Sigma application in healthcare logistics: A framework and a case study, Journal of Healthcare Engineering, 2019, 1, pp. 1-12, (2019); Schroeder R.G., Linderman K., Liedtke C., Choo A.S., Six Sigma: Definition and underlying theory, Journal of Operations Management, 26, 4, pp. 536-554, (2008); Shankar R., Process improvement using Six Sigma: A DMAIC guide, (2009); Shengli Z., Zeping L., Li Z., Construction of logistics network system based on internet, Journal of Physics: Conference Series Proceedings, 1176, pp. 22-27, (2019); Singh M., (2017); Stacy A.V., Ann M.C., Barrett W.T., The same-day delivery problem for online purchases, Transportation Science, 53, 1, pp. 167-184, (2017); Wu F.C., Optimization of correlated multiple quality characteristics using desirability function, Quality Engineering, 17, 1, pp. 119-126, (2004); Zhang A., Lou W., Shi Y., Chia S., Sim Z., Lean and Six Sigma in logistics: A pilot survey study in Singapore, International Journal of Operations & Production Management, 36, 1, pp. 1625-1643, (2016); Zu X., Fredendall L.D., Douglas T.J., The evolving theory of quality management: The role of Six Sigma, Journal of Operations Management, 26, 5, pp. 630-650, (2008)","A.A. Abdallah; Graduate School of Business Administration, The German Jordanian University, Amman, Madaba Street, P.O. Box 35247, 11180, Jordan; email: Abdallah.abdallah@gju.edu.jo",null,"Bellwether Publishing, Ltd.",{"$nulls":5},8982112.0,null,"QUENE",null,"English","Qual Eng","Article","Final",null,"Scopus","2-s2.0-85080147943"]
["Guan S.","Guan, Shuai (57221905569)",5.7221905569E10,"Smart E-commerce logistics construction model based on big data analytics",2021.0,"Journal of Intelligent and Fuzzy Systems",40.0,2.0,null,3015.0,3023.0,8.0,20.0,"10.3233/JIFS-189340","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85100574566&doi=10.3233%2fJIFS-189340&partnerID=40&md5=ea1fd19b69096529d292eabdbbf7b97b","School of Management, Henan University of Science and Technology, Luoyang, Henan, China","Guan S., School of Management, Henan University of Science and Technology, Luoyang, Henan, China","With the continuous implementation of the Belt and Road Initiative of China, cross-border e-commerce is gradually becoming one of the main ways of trade. The smart operation of cross-border logistics has become an important factor affecting the quality of cross-border e-commerce transactions by its characteristics of high-efficiency, high-quality, and low-cost. As China's first smart city in China with the theme of the aviation economy, the top priority for developing cross-border e-commerce in the Zhengzhou Airport Economic Zone is to construct cross-border e-commerce smart logistics. This paper expounds on the significance of applying big data technology on the construction of the intelligent logistics, analyzing its important roles not only in further promoting the cross-border e-commerce development in the Zhengzhou Airport Economy Zone but also during the process of the entire national economic transformation and escalation. The smart logistics constructing strategy in the Zhengzhou Airport Economy Zone is expected to provide ideas and support for the Zhengzhou Airport Economy Zone making continuous improvement in leading and pushing the Henan regional economy to achieve sustainable development in the future. © 2021-IOS Press. All rights reserved.","big data; cross-border e-commerce; Smart logistics construction; the Zhengzhou airport economy zone","Advanced Analytics; Airports; Big data; Data Analytics; Electronic commerce; Metadata; Planning; Regional planning; Construction model; Continuous improvements; Data technologies; E-commerce development; E-commerce transactions; Economic transformation; High-efficiency; Regional economy; Costs",{"$nulls":4},"China National Social Science Fund, (19BJY179); Henan Universities Applied Research of Philosophy and Social Sciences’ Major Project, (2018-YYZD-05); Henan Universities Philosophy and Social Sciences Innovative Team Support Program, (2019-CXTD-05)","It is supported by 2019 China National Social Science Fund (19BJY179, Research on Global Economic Rebalancing, Value Chain Restructuring and China’s Foreign Trade Transformation and Upgrading), Henan Universities Philosophy and Social Sciences Innovative Team Support Program (2019-CXTD-05), Henan Universities Applied Research of Philosophy and Social Sciences’ Major Project (2018-YYZD-05).","Yu L., Eight key words about the internet in the government work report, China?s Foreign Trade, 572, 2, pp. 46-47, (2019); Chen J., Wang X., Chu Z., Capacity Sharing Product Differentiation and Welfare, Economic Research-Ekonomska Istrazivanja, 33, 1-2020, pp. 107-123; Gang Gang L., Hanwen Z., An Ontology Constructing Technology Oriented on Massive Social Security Policy Documents, Cognitive Systems Research, 60, 2020, pp. 97-105; Jiuru Z., Influential factors and strategic analysis on the development of cross-border e-commerce between China and Russia under the belt and road initiative, The 30th China Conference on Control and Decision, (2018); Qu Q., Chen K.Y., Wei Y.M., Liu Y., Tsai S.B., Dong W., Using a hybrid model to evaluate the performance of innovation and technology professionals in the marine logistics industry, Mathematical Problems in Engineering, (2015); Niu B., Wang J., Lee C.K.M., Et al., Product+logistics\" bundling sale and co-delivery in cross-border e-commerce, Electronic Commerce Research, 2019; Lv Z., Singh A.K., Big Data Analysis of Internet of Things System, Acm Transactions on Internet Technology (TOIT), (2020); Kerdprasop N., Chansilp K., Kerdprasop K., Et al., Anomaly Detection with Machine Learning Technique to Support Smart Logistics Computational Science and Its Applications-ICCSA, (2019); Tsai S.-B., Lee Y.-C., Wuand C.-H., Guo J.-J., Examining How Manufacturing Corporations Win Orders, South African Journal of Industrial Engineering, 24, 3, pp. 112-124, (2013); Jinming W., Li H., Fumin Z., Swarm robotics control and communications: Imminent challenges for next-generation smart logistics, Ieee Communications Magazine, 56, 7, pp. 102-107, (2018); Ke Z., Zh Y., ZhouYang G., Research on the efficiency of the aviation logistics industry in Zhengzhou Airport Economy Zone, Regional Research and Development, 2, pp. 76-79, (2018); Zhou S., Luo P., Jain D.K., Lan X., Zhang Y., Double-Domain Imaging and Adaption for Person Re-Identification, Ieee Access, 7, 2019, pp. 103336-103345; El-Hasnony I.M., Barakat S., Elhoseny M., Mostafa R.R., Improved Feature Selection Model for Big Data Analytics, Ieee Access, 8, 1, pp. 66989-67004, (2020); McAfee A., Brynjolfsson E., Big Data the management revolution, Harvard Business Review, 90, 10, pp. 60-668128, (2012); Borgi T., Zoghlami N., Abed M., Big data for transport and logistics: A review, 2017 International Conference on Advanced Systems and Electric Technologies (IC Aset, (2017); Nannan T., Revolution in data management ideas in the Era of big data: From the result to the process, Information Studies: Theory & Application, (2017); Wan S., Gu Z., Ni Q., Cognitive computing and wireless communications on the edge for healthcare service robots, Computer Communications; Tamas D.P., P. Illes B., Et al., Application possibilities of the Big Data concept in Industry 4.0, Iop Conference Series Materials Science and Engineering, 2018; Lv Z., Yang H.A.N., Singh A.K., Manogaran G., Lv H., Trustworthiness in Industrial IoT Systems Based on Artificial Intelligence, Ieee Transactions on Industrial Informatics, (2020); Lade P., Ghosh R., Srinivasan S., Manufacturing analytics and industrial internet of things, Ieee Intelligent Systems, 32, 3, pp. 74-79, (2017); Yingying S., Lianjuan H., Jianan W., Quantumbehaved RS-PSO-LSSVM method for Quality Prediction in Parts Production Processes, Concurrency and Computation-Practice & Experience; Hou R., Kong Y., Cai B., Et al., Unstructured big data analysis algorithm and simulation of Internet of Things based on machine learning, Neural Comput & Applic, 32, pp. 5399-5407, (2020); Bates O., Knowles B., Friday A., Are people the key to enabling collaborative smart logistics?, Proceedings of the 2017 Chi Conference Extended Abstracts on Human Factors in Computing Systems, pp. 1494-1499, (2017); Yang Y., Research on the optimization of the supplier intelligent management system for cross-border e-commerce platforms based on machine learning, Information Systems and E-Business Management, (2019); Wei-Hua S.U., Yu-Ying W., Statistical research on the development level of china?s cross-border e-commerce in comprehensive pilot areas, Journal of Business Economics, (2017); Zhao J., Zeng D.-L., Zhou T.-W., Zhu Z.-C., Data mining of urban new energy vehicles in an intelligent government subsidy environment using a closed-loop supply chain pricing model, Comput Syst Sci Eng, 35, 3; Liu W., Shi H.B., Zhang Z., Tsai S.B., Zhai Y., Chen Q., Wang J., The Development Evaluation of Economic Zones in China, Int J Environ Res Public Health, 15, (2018); Gaber T., Abdelwahab S., Elhoseny M., Hassanien A.E., Trust-based secure clustering in WSN-based intelligent transportation systems, Computer Networks, 146, 2018, pp. 151-158; Rizk-Allah R.M., Hassanien A.E., Elhoseny M., A Multi-Objective Transportation Model under Neutrosophic Environment, Computers and Electrical Engineering, 69, 2018, pp. 705-719; Saracevic M., Adamovic S., MacEk N., Elhoseny M., Sarhan S., Cryptographic Keys Exchange Model for Smart City Applications, Iet Intelligent Transport Systems, (2020); Lv Z., Zhang S., Xiu W., Solving the Security Problem of Intelligent Transportation System with Deep Learning, Ieee Transactions on Intelligent Transportation Systems; Liu Z., Feng J., Liu B., Pricing and service level decisions under a sharing product and consumers? variety-seeking behavior, Sustainability (Switzerland), 11, 24, (2019); El-Hasnony I.M., Barakat S., Elhoseny M., Mostafa R.R., Improved Feature Selection Model for Big Data Analytics, Ieee Access, 8, 1, pp. 66989-67004, (2020); Liu B., Li T., Tsai S.B., Low carbon strategy analysis of competing supply chains with different power structures, Sustainability, 9, 2017; Elsayed W., Elhoseny M., Sabbeh S., Riad A., Self-maintenance model for wireless sensor networks, Computers & Electrical Engineering, 70, pp. 799-812, (2018); Wan S., Li X., Xue Y., Et al., Efficient computation offloading for the Internet of Vehicles in edge computing-Assisted 5G networks, J Supercomput, (2019); Degha H.E., Laallam F.Z., Said B., Intelligent contextawareness system for energy efficiency in the smart building based on ontology, Sustain Comput Informatics Syst, 21, 2019, pp. 212-233; Mukherjee A., Mukherjee P., De N.D.D., Panigrahi B.K., Lightweight sustainable intelligent load forecasting platform for smart grid applications, Sustain Comput Informatics Syst, 25, 2020; Ji Q., Guo J.F., Oil Price Volatility Oil-Related Events An Internet Concern Study Perspective, Applied Energy, 137, 1, pp. 256-264, (2015)","S. Guan; School of Management, Henan University of Science and Technology, Luoyang, Henan, China; email: guanshuai@haust.edu.cn",null,"IOS Press BV",{"$nulls":5},1.0641246E7,null,null,null,"English","J. Intelligent Fuzzy Syst.","Article","Final",null,"Scopus","2-s2.0-85100574566"]
["Ponce D.; Contreras I.; Laporte G.","Ponce, Diego (57189064426); Contreras, Ivan (17533856100); Laporte, Gilbert (7101734278)","57189064426; 17533856100; 7101734278","E-commerce shipping through a third-party supply chain",2020.0,"Transportation Research Part E: Logistics and Transportation Review",140.0,null,101970.0,null,null,null,21.0,"10.1016/j.tre.2020.101970","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85086744762&doi=10.1016%2fj.tre.2020.101970&partnerID=40&md5=3934c48ff861e2d6309b7eb3bd52c5a7","Concordia University, Montréal, Canada; Interuniversity Research Centre on Enterprise Networks, Logistics and Transportation (CIRRELT), Montréal, Canada; Institute of Mathematics of the University of Seville (IMUS), Sevilla, Spain; HEC Montréal, Montréal, Canada; School of Management, University of Bath, Bath, United Kingdom","Ponce D., Concordia University, Montréal, Canada, Interuniversity Research Centre on Enterprise Networks, Logistics and Transportation (CIRRELT), Montréal, Canada, Institute of Mathematics of the University of Seville (IMUS), Sevilla, Spain; Contreras I., Concordia University, Montréal, Canada, Interuniversity Research Centre on Enterprise Networks, Logistics and Transportation (CIRRELT), Montréal, Canada; Laporte G., Interuniversity Research Centre on Enterprise Networks, Logistics and Transportation (CIRRELT), Montréal, Canada, HEC Montréal, Montréal, Canada, School of Management, University of Bath, Bath, United Kingdom","We consider an e-commerce retailer who must ship orders from a warehouse to a set of customers with delivery deadlines. As is often the case, the retailer uses a third-party service provider to ensure its distribution. The retailer can enter the supply chain of the service provider at various levels. Entering it at a higher level entails lower sorting costs for the retailer, but higher delivery costs, and longer delivery times. The customer orders arrive at various moments over a rolling planning horizon. This means that the retailer must also make consolidation decisions. We model and solve the static and dynamic cases of this problem. The static case is modeled as an integer linear program and solved by CPLEX. We develop and compare four shipping policies for the dynamic case. Extensive computational results based on real location data from California and Texas are reported. © 2020 Elsevier Ltd","Dynamic shipping policies; E-commerce; Supply chain; Third-party logistics","California; Texas; United States; cost analysis; decision making; electronic commerce; policy approach; retailing; shipping; supply chain management",{"$nulls":4},"Horizon Postdoctoral Fellowship; Natural Sciences and Engineering Research Council of Canada, NSERC, (2015-06189, 2018-06704); Concordia University, CU","This work was partly funded by the Horizon Postdoctoral Fellowship, Concordia University and by the Canadian Natural Sciences and Engineering research Council under grants 2018-06704 and 2015-06189 . This support is gratefully acknowledged.","Aguezzoul A., Third-party logistics selection problem: A literature review on criteria and methods, Omega, 49, pp. 69-78, (2014); Albareda-Sambola M., Fernandez E., Laporte G., The dynamic multiperiod vehicle routing problem with probabilistic information, Comput. Oper. Res., 48, pp. 31-39, (2014); Angelelli E., Bianchessi N., Mansini R., Speranza M.G., Short term strategies for a dynamic multi-period routing problem, Transp. Res. Part C: Emerg. Technol., 17, pp. 106-119, (2009); Archetti C., Jabali O., Speranza M.G., Multi-period vehicle routing problem with due dates, Comput. Oper. Res., 61, pp. 122-134, (2015); Ayanso A., Diaby M., Nair S.K., Inventory rationing via drop-shipping in Internet retailing: A sensitivity analysis, Eur. J. Oper. Res., 171, pp. 135-152, (2006); Berbeglia G., Cordeau J.-F., Laporte G., Dynamic pickup and delivery problems, Eur. J. Oper. Res., 202, pp. 8-15, (2010); Buldeo Rai H., Verlinde S., Merckx J., Macharis C., Crowd logistics: an opportunity for more sustainable urban freight transport?, Eur. Transp. Res. Rev., 9, (2017); Chen A., Large-scale optimization in online-retail inventory management, (2017); Chen Y.-K., Chiu F.-R., Lin W.-H., Huang Y.-C., An integrated model for online product placement and inventory control problem in a drop-shipping optional environment, Comput. Industr. Eng., 117, pp. 71-80, (2018); Cheng X., Gou Q., Yue J., Zhang Y., Equilibrium decisions for an innovation crowdsourcing platform, Transp. Res. Part E: Logist. Transp. Rev., 125, pp. 241-260, (2019); Clement J., (2014); Cohen R., How Amazon's delivery logistics redefined retail supply chains, J. Supply Chain Manage. Logist. Procurement, 1, pp. 75-86, (2018); Daganzo C.F., The length of tours in zones of different shapes, Transp. Res. 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Contreras; Concordia University, Montréal, H3G 1M8, Canada; email: icontrer@encs.concordia.ca",null,"Elsevier Ltd",{"$nulls":5},1.3665545E7,null,null,null,"English","Transp. Res. Part E Logist. Transp. Rev.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85086744762"]
["Sun P.; Gu L.","Sun, Pingping (57221920804); Gu, Lingang (57221914139)","57221920804; 57221914139","Optimization of Cross-Border e-Commerce Logistics Supervision System Based on Internet of Things Technology",2021.0,"Complexity",2021.0,null,4582838.0,null,null,null,21.0,"10.1155/2021/4582838","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85107576260&doi=10.1155%2f2021%2f4582838&partnerID=40&md5=2b8a1b53ba8ae26596c5d44fb1db1922","Business and Tourism Institute, Hangzhou Vocational and Technical College, Hangzhou, Zhejiang, 310018, China; Special Equipment Institute, Hangzhou Vocational and Technical College, Hangzhou, Zhejiang, 310018, China","Sun P., Business and Tourism Institute, Hangzhou Vocational and Technical College, Hangzhou, Zhejiang, 310018, China; Gu L., Special Equipment Institute, Hangzhou Vocational and Technical College, Hangzhou, Zhejiang, 310018, China","Based on the Internet of Things technology, this paper proposes building a cross-border e-commerce logistics supervision system and determines the evaluation index system from the overall framework design of the system, supply chain supervision process optimization, risk supervision optimization, and system order degree optimization. First of all, the framework adopts the national certification center to supervise the logistics service platform and logistics service platform to supervise the logistics participants of the secondary supervision system. Then, functions such as swarm intelligence contract, legal anonymous identity authentication, intelligent transaction matching, abnormal data analysis and detection, privacy protection, and traceability are realized under the framework of the supervision system. Then, the security analysis and transaction supervision component software are used to verify the security, control, and operating efficiency of the transaction supervision framework. Finally, in a real crowd sourcing logistics enterprise platform to run on the software component, the actual measurement, the measured results show that the proposed cross-border supervision system is safe and controllable, and electronic business logistics protects users and data privacy, prevents forgery and fraud, and realizes the user behavior and user data in addition to auditability and traceability.  © 2021 Pingping Sun and Lingang Gu.",null,"Behavioral research; Electronic commerce; Electronics industry; Optimization; Privacy by design; Supply chains; Actual measurements; Electronic business; Evaluation index system; Identity authentication; Internet of things technologies; Logistics enterprise; Logistics service platforms; Operating efficiency; Internet of things",{"$nulls":6},"Liu Z., Li Z., A blockchain-based framework of cross-border e-commerce supply chain, International Journal of Information Management, 52, (2020); Lai J., Research on Cross-border E-commerce Logistics Supply under Block Chain, pp. 214-218; Ma S., Chai Y., Zhang H., Rise of cross-border E-commerce exports in China, China & World Economy, 26, 3, pp. 63-87, (2018); Li M., Guan S.P., Du R.R., Research on the Application of Customs Supervision on Cross-border Import E-commerce Retail Business from the Perspective of Block Chain, pp. 74-78; Xie J., SWOT Analysis of Cross-Border E-Commerce Development in China under the Background of Internet plus, pp. 210-213, (2017); Zhang X., Zhou G., Cao J., Wu A., Evolving strategies of e-commerce and express delivery enterprises with public supervision, Research in Transportation Economics, 80, (2020); Sun D., Fang L., Li J., Research on the Development of Cross-border E-commerce in Port Cities-A Case of Manzhouli City, pp. 589-596; Porambage P., Okwuibe J., Liyanage M., Ylianttila M., Taleb T., Survey on multi-access edge computing for internet of things realization, IEEE Communications Surveys & Tutorials, 20, 4, pp. 2961-2991, (2018); Mohammed S., Fiaidhi J., Ramos C., Kim T.-H., Fang W.C., Abdelzaher T., Blockchain in eCommerce, ACM Transactions on Internet Technology, 21, 1, pp. 11-55, (2021); 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Li M., Shao S., Ye Q., Xu G., Huang G.Q., Blockchain-enabled logistics finance execution platform for capital-constrained E-commerce retail, Robotics and Computer-Integrated Manufacturing, 65, (2020); Sun X., Research on Cross-Border E-Commerce and Financial Services Supervision, pp. 498-502, (2018); Jiangsheng S., The Coordinated Development of Cross Border E-commerce and Cross Border Logistics, pp. 16-18; Guan S., Smart E-commerce logistics construction model based on big data analytics, Journal of Intelligent & Fuzzy Systems (Preprint), 1, 4, pp. 1-9, (2019); Liu J., Research on Strategies of Logistics Talents Training in Higher Vocational Education under the Background of Intelligent Logistics, pp. 932-936, (2018); Zhang J., Qu G., Physical unclonable function-based key sharing via machine learning for IoT security, IEEE Transactions on Industrial Electronics, 67, 8, pp. 7025-7033, (2019); Zhang J., Shen C., Su H., Arafin M.T., Qu G., Voltage over-scaling-based lightweight Authentication for IoT security, IEEE Transactions on Computers, (2021); Yang J., Zhang J., Wang H., Urban traffic control in software defined internet of things via a multi-agent deep reinforcement learning approach, IEEE Transactions on Intelligent Transportation Systems, pp. 1-13, (2020); Li X., Huang D., Research on value integration mode of agricultural E-commerce industry chain based on internet of things and blockchain technology, Wireless Communications and Mobile Computing, 2020, (2020); Wei W., Ke Q., Nowak J., Korytkowski M., Scherer R., Wozniak M., Accurate and fast URL phishing detector: A convolutional neural network approach, Computer Networks, 178, (2020); Li Y., Yang J., Meta-learning baselines and database for few-shot classification in agriculture, Computers and Electronics in Agriculture, 182, (2021); Wang W., Kumar N., Chen J., Realizing the potential of the internet of things for smart tourism with 5G and AI, IEEE Network, 34, 6, pp. 295-301, (2020); Kang N., An overview of \"optimal input-output planning model and cross-boundary economic management information system\" -combinations between optimal input-output planning model, big data, new cloud computing technologies and internet of things or new internet industry, American Journal of Industrial and Business Management, 9, 9, pp. 1800-1830, (2019); Yang C.S., Adoption of software testing in internet of things: A systematic literature mapping, Computing Reviews, 61, 2, pp. 72-73, (2020)","L. Gu; Special Equipment Institute, Hangzhou Vocational and Technical College, Hangzhou, Zhejiang, 310018, China; email: 1999010004@hzvtc.edu.cn",null,"Hindawi Limited",{"$nulls":5},1.0762787E7,null,null,null,"English","Complexity","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85107576260"]
["Pourhejazy P.","Pourhejazy, Pourya (57191925773)",5.7191925773E10,"Destruction decisions for managing excess inventory in e-commerce logistics",2020.0,"Sustainability (Switzerland)",12.0,20.0,8365.0,1.0,12.0,11.0,16.0,"10.3390/su12208365","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85093089477&doi=10.3390%2fsu12208365&partnerID=40&md5=4ec46487038721651f6dfea2ce03669a","Department of Industrial Engineering and Management, National Taipei University of Technology, Taipei, 10608, Taiwan","Pourhejazy P., Department of Industrial Engineering and Management, National Taipei University of Technology, Taipei, 10608, Taiwan","The Internet has brought about new possibilities for innovation and radically changed business activities. Internet shopping is a prime example of increasing popularity, which is exacerbated due to the recent pandemic. It is expected that e-commerce will accommodate more than a quarter of the total retail sales worldwide in the next few years. Given the characteristics of e-commerce, inventory management is of paramount importance for an effective and timely response to the online customers’ demand. Despite its relevance, the issue of warehouse excess inventory is not sufficiently studied in the operations management literature. This study explores the factors, including sustainability and strategic considerations, that influence the inventory destruction decisions as one of the alternatives for managing excess inventory. Applying the Fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) method, the interrelationships between the decision factors are investigated and the decisive considerations are identified. Overall, the outcomes provide insights for the e-commerce practitioners and offer directions for modeling and managing inventory destruction decisions. © 2020 by the author. Licensee MDPI, Basel, Switzerland.","Decision analysis; E-commerce; Excess inventory; Inventory destruction; Inventory management","business; decision making; electronic commerce; fuzzy mathematics; innovation; Internet; inventory; sustainability",{"$nulls":6},"Askin J., Asif A., Suhee Vimalesh S., Kumaresan S., Kirubakaran V., Study on Solid Waste Management System in Dindigul Corporation of Tamilnadu and Feasibility Analysis on Waste-to-Energy Projects, 1, (2020); Gbale B.H.A., Aristondo L.A., Idrissi S., Drop Shipping, the New Age of Doing Business: Arbery United States, (2020); Dannenberg P., Fuchs M., Riedler T., Wiedemann C., Digital transition by COVID-19 pandemic? The German food online retail, Tijdschr. Econ. Soc. Geogr, 111, pp. 543-560, (2020); Kim R.Y., The Impact of COVID-19 on Consumers: Preparing for Digital Sales, IEEE Eng. Manag. 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Res, 16, pp. 122-141, (1968); Reike D., Vermeulen W.J.V., Witjes S., The circular economy: New or refurbished as CE 3.0?— Exploring controversies in the conceptualization of the circular economy through a focus on history and resource value retention options, Resour. Conserv. Recycl, 135, pp. 246-264, (2018); Patriarca R., Hu T., Costantino F., Di Gravio G., Tronci M., A System-Approach for Recoverable Spare Parts Management Using the Discrete Weibull Distribution, Sustainability, 11, (2019)","P. Pourhejazy; Department of Industrial Engineering and Management, National Taipei University of Technology, Taipei, 10608, Taiwan; email: pourya@ntut.edu.tw",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85093089477"]
["Wang F.; Zhu Y.; Wang F.; Liu J.; Ma X.; Fan X.","Wang, Fangxin (57201917282); Zhu, Yifei (57227645300); Wang, Feng (36065073900); Liu, Jiangchuan (8969748600); Ma, Xiaoqiang (36930770600); Fan, Xiaoyi (56460611200)","57201917282; 57227645300; 36065073900; 8969748600; 36930770600; 56460611200","Car4Pac: Last Mile Parcel Delivery through Intelligent Car Trip Sharing",2020.0,"IEEE Transactions on Intelligent Transportation Systems",21.0,10.0,8861125.0,4410.0,4424.0,14.0,26.0,"10.1109/TITS.2019.2944134","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85092557467&doi=10.1109%2fTITS.2019.2944134&partnerID=40&md5=153be38e660a67b56453ef80425dff6c","School of Computing Science, Simon Fraser University, Burnaby, V5A 1S6, BC, Canada; Department of Computer and Information Science, University of Mississippi, Oxford, 38677, MS, United States; School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan, 430074, China; Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, V6T 1Z4, BC, Canada","Wang F., School of Computing Science, Simon Fraser University, Burnaby, V5A 1S6, BC, Canada; Zhu Y., School of Computing Science, Simon Fraser University, Burnaby, V5A 1S6, BC, Canada; Wang F., Department of Computer and Information Science, University of Mississippi, Oxford, 38677, MS, United States; Liu J., School of Computing Science, Simon Fraser University, Burnaby, V5A 1S6, BC, Canada; Ma X., School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan, 430074, China; Fan X., Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, V6T 1Z4, BC, Canada","The explosion of online shopping brings great challenges to traditional logistics industry, where the massive parcels and tight delivery deadline impose a large cost on the delivery process, in particular the last mile parcel delivery. On the other hand, modern cities never lack transportation resources such as the private car trips. Motivated by these observations, we propose a novel and effective last mile parcel delivery mechanism through car trip sharing, to leverage the available private car trips to incidentally deliver parcels during their original trips. To achieve this, the major challenges lie in how to accurately estimate the parcel delivery trip cost and assign proper tasks to suitable car trips to maximize the overall performance. To this end, we develop Car4Pac, an intelligent last mile parcel delivery system to address these challenges. Leveraging the real-world massive car trip trajectories, we first build up a 3D (time-dependent, driver-dependent and vehicle-dependent) landmark graph that accurately predicts the travel time and fuel consumption of each road segment. Our prediction method considers not only traffic conditions of different times, but also driving skills of different people and fuel efficiencies of different vehicles. We then develop a two-stage solution towards the parcel delivery task assignment, which is optimal for one-to-one assignment and yields high-quality results for many-to-one assignment. Our extensive real-world trace driven evaluations further demonstrate the superiority of our Car4Pac solution. © 2000-2011 IEEE.","Intelligent transportation system; route planning; trajectory data mining; travel cost prediction","Behavioral research; Traffic control; Travel time; Delivery deadlines; Delivery process; Intelligent cars; Logistics industry; Online shopping; Prediction methods; Traffic conditions; Transportation resources; Cost benefit analysis",{"$nulls":4},"Canada NSERC; Natural Sciences and Engineering Research Council of Canada, NSERC; National Natural Science Foundation of China, NSFC, (61702204)","Manuscript received December 1, 2017; revised March 13, 2018, September 19, 2018, and April 5, 2019; accepted September 6, 2019. Date of publication October 7, 2019; date of current version October 2, 2020. This work was supported by the Canada Technology Demonstration Program (TDP) Grant and the Canada NSERC Discovery Grant. The work of X. Ma was supported in part by the National Natural Science Foundation of China under Grant 61702204. The work of X. Fan was supported in part by the NSERC Postdoctoral Fellowship. The Associate Editor for this article was Y. Song. (Corresponding author: Jiangchuan Liu.) F. Wang, Y. Zhu, and J. Liu are with the School of Computing Science, Simon Fraser University, Burnaby, BC V5A 1S6, Canada (e-mail: fangxinw@sfu.ca; yza323@sfu.ca; jcliu@sfu.ca).","Retail E-Commerce Sales in the United States, (2019); 1.5 Billion Packages to Be Shipped during China's Singles, (2019); Argos Customers Have Been Left Furious by Long Delays to Deliveries after Black Friday, (2019); Wang F., Wang F., Ma X., Liu J., Demystifying the crowd intelligence in last mile parcel delivery for smart cities, Ieee Netw., 33, 2, pp. 23-29, (2019); Aized T., Srai J.-S., Hierarchical modelling of Last Mile logistic distribution system, Int. J. Adv. Manuf. 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["Yang D.; Wu P.","Yang, Dong (57223027827); Wu, Peijian (57223029579)","57223027827; 57223029579","E-commerce logistics path optimization based on a hybrid genetic algorithm",2021.0,"Complexity",2021.0,null,5591811.0,null,null,null,10.0,"10.1155/2021/5591811","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85104561970&doi=10.1155%2f2021%2f5591811&partnerID=40&md5=f2ecf2258199d5cebcad5be7cee3170e","School of Management Science and Engineering, Dongbei University of Finance and Economics, Dalian, Liaoning, 116025, China; School of Business Administration, Anhui University of Finance and Economics, Bengbu, Anhui, 233030, China","Yang D., School of Management Science and Engineering, Dongbei University of Finance and Economics, Dalian, Liaoning, 116025, China, School of Business Administration, Anhui University of Finance and Economics, Bengbu, Anhui, 233030, China; Wu P., School of Business Administration, Anhui University of Finance and Economics, Bengbu, Anhui, 233030, China","Based on the problem of e-commerce logistics and distribution network optimization, this paper summarizes the solution ideas and solutions proposed by domestic and foreign scholars and designs a method to optimize the B2C e-commerce logistics and distribution network by taking into account the special traffic conditions in the city. The logistics network optimization model is established and solved by combining various methods. Taking into account the new target requirements constantly proposed in the modern logistics environment, the vehicle path problem under the generalized objective function is studied, and the multidimensional impact maximization problem in this type of problem is proposed and modeled. The problem follows from the path planning for emergency material delivery. Given locations, roads, and multiple classes of supplies in a map, each road allows vehicles to deliver each class of supplies with a certain probability. The goal of the problem is how to select a finite number of locations in the map as centers of supplies so that the number of locations that can be effectively covered by vehicle paths from them is maximized with the desired probability. For the first time, we used a hybrid genetic algorithm to optimize the e-commerce logistics path, and the optimized results are more reasonable than other algorithms.  © 2021 Dong Yang and Peijian Wu.",null,"Electronic commerce; Location; Motor transportation; Vehicles; Emergency material; Hybrid genetic algorithms; Logistics network; Maximization problem; Modern logistics; Objective functions; Path optimizations; Traffic conditions; Genetic algorithms",{"$nulls":6},"Victor A., Ghalib M.R., Detection of skin cancer cells-A review, Research Journal of Pharmacy and Technology, 10, 11, pp. 4093-4098, (2017); Sudra M.N., Selvarajan S., Hybrid approach towards feature selection for breast tumor classification from screening mammograms, International Journal of Biomedical Engineering and Technology, 29, 4, pp. 309-326, (2019); Worker M., Akare A., Classification of stages of lung cancer using genetic candidate group search approach, Iosr Journal of Computer Engineering, 18, 5, pp. 7-13, (2016); Yang L., Xu Z., Feature extraction by PCA and diagnosis of breast tumors using SVM with DE-based parameter tuning, International Journal of Machine Learning and Cybernetics, 10, 3, pp. 591-601, (2019); Chan Y.-K., Chang M.-J., Hung Y.-W., Et al., Tissue section image-based liver scar detection, Journal of Medical and Biological Engineering, 38, 6, pp. 857-866, (2018); Paul R.V., Sannakki S., Rajpurohit V.S., A survey on classification of liver diseases using image processing and data mining techniques, International Journal of Computer Sciences and Engineering, 5, 3, pp. 29-34, (2017); Liu T., Zhang W., McLean P., Ueland M., Forbes S.L., Su S.W., Electronic nose-based odor classification using genetic algorithms and fuzzy support vector machines, International Journal of Fuzzy Systems, 20, 4, pp. 1309-1320, (2018); Das A., Das P., Panda S.S., Sabut S., Adaptive fuzzy clustering-based texture analysis for classifying liver cancer in abdominal CT images, International Journal of Computational Biology and Drug Design, 11, 3, pp. 192-208, (2018); Ralph J., Singh A., Bhadauria H.S., Computer assisted classification framework for prediction of acute lymphoblastic and acute megaloblastic leukemia, Biocybernetics and Biomedical Engineering, 37, 4, pp. 637-654, (2017); Allan M., Nandhini M., A study on optimization techniques in feature selection for medical image analysis, International Journal of Computer Science and Engineering (IJCSE), 9, 3, pp. 75-82, (2017); Manda R., Walsh M.J., Bhargava R., Selecting optimal features from Fourier transform infrared spectroscopy for discrete-frequency imaging, Analyst, 143, 5, pp. 1147-1156, (2018); Kaur P., Singh G., Kaur P., An intelligent validation system for diagnostic and prognosis of ultrasound fetal growth analysis using neuro-fuzzy based on genetic algorithm, Egyptian Informatics Journal, 20, 1, pp. 55-87, (2019); Wang C., Li Z., Dey N., Et al., Histogram of oriented gradient based plantar pressure image feature extraction and classification employing fuzzy support vector machine, Journal of Medical Imaging and Health Informatics, 8, 4, pp. 842-854, (2018); Nanda N., Kakkar P., Nagpal S., Computer-Aided segmentation of liver lesions in CT scans using cascaded convolutional neural networks and genetically optimised classifier, Arabian Journal for Science and Engineering, 44, 4, pp. 4049-4062, (2019); Anguish I., Kumar A.V.A., Improving medical diagnosis performance using hybrid feature selection via relief and entropy based genetic search (RF-EGA) approach: Application to breast cancer prediction, Cluster Computing, 22, 3, pp. 6899-6906, (2019); Salem C., Azar D., Tokajian S., Image processing and genetic algorithm-based approach for the detection of melanoma in patients, Methods of Information in Medicine, 57, pp. 74-80, (2018); Aarhus S.L., Prabu S., Tri-texture feature extraction and region growing-level set segmentation in breast cancer diagnosis, International Journal of Biomedical Engineering and Technology, 26, 3-4, pp. 279-303, (2018); Lakshmi A., Arivoli T., Pallikonda Rajasekaran M., A novel M-ACA-based tumor segmentation and DAPP feature extraction with PPCSO-PKC-based MRI classification, Arabian Journal for Science and Engineering, 43, 12, pp. 7095-7111, (2018); Ronald S., Asadi S., An evolutionary deep belief network extreme learning-based for breast cancer diagnosis, Soft Computing, 23, 24, pp. 13139-13159, (2019); Tomaz R.D.L., Carneiro P.C., Bonin J.E., MacEdo T.A.A., Patrocinio A.C., Soares A.B., Novel Mahalanobis-based feature selection improves one-class classification of early hepatocellular carcinoma, Medical & Biological Engineering & Computing, 56, 5, pp. 817-832, (2018); Seth G., Saini B.S., Computer aided diagnosis system for abdomen diseases in computed tomography images, Biocybernetics and Biomedical Engineering, 36, 1, pp. 42-55, (2016); Chroma H., Abdulkareem S., Herawan T., Evolutionary Neural Network model for West Texas Intermediate crude oil price prediction, Applied Energy, 142, pp. 266-273, (2015); Laing C., Schlick T., Computational approaches to RNA structure prediction, analysis, and design, Current Opinion in Structural Biology, 21, 3, pp. 306-318, (2011); Oh H., Lee S., Bovik A.C., Stereoscopic 3D visual discomfort prediction: A dynamic accommodation and vergence interaction model, Ieee Transactions on Image Processing, 25, 2, pp. 615-629, (2015); Wang W., Carr M., Xu W., Kobbacy K., A model for residual life prediction based on Brownian motion with an adaptive drift, Microelectronics Reliability, 51, 2, pp. 285-293, (2011); Gordon N., A genetic algorithm approach for SMEs bankruptcy prediction: Empirical evidence from Italy, Expert Systems with Applications, 41, 14, pp. 6433-6445, (2014); Baum G., Blangiardo M., Hierarchical layered model for the prediction of football results, Journal of Applied Statistics, 37, 2, pp. 253-264, (2010)","P. Wu; School of Business Administration, Anhui University of Finance and Economics, Bengbu, Anhui, 233030, China; email: 120100001@aufe.edu.cn",null,"Hindawi Limited",{"$nulls":5},1.0762787E7,null,null,null,"English","Complexity","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85104561970"]
["Liu W.; Zhang J.; Wei S.; Wang D.","Liu, Weihua (56456762900); Zhang, Jiahui (57216414370); Wei, Shuang (57216674322); Wang, Di (57193765483)","56456762900; 57216414370; 57216674322; 57193765483","Factors influencing organisational efficiency in a smart-logistics ecological chain under e-commerce platform leadership",2021.0,"International Journal of Logistics Research and Applications",24.0,4.0,null,364.0,391.0,27.0,33.0,"10.1080/13675567.2020.1758643","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85084261710&doi=10.1080%2f13675567.2020.1758643&partnerID=40&md5=584bf8da3c3d73e78dedfb24ebb1ac09","College of Management and Economics, Tianjin University, Tianjin, China","Liu W., College of Management and Economics, Tianjin University, Tianjin, China; Zhang J., College of Management and Economics, Tianjin University, Tianjin, China; Wei S., College of Management and Economics, Tianjin University, Tianjin, China; Wang D., College of Management and Economics, Tianjin University, Tianjin, China","In smart-logistics ecological chains led by e-commerce platforms, the organisational efficiency has become an important indicator to measure the ecological chain’s development. However, no scientific theoretical framework exists regarding the factors affecting such organisational efficiency. This paper adopts a multi-case study method to research four e-commerce platforms in China and investigate the current situation and development of smart-logistics ecological chains. Through interviews and analysis, the research proposes a theoretical framework of factors influencing the organisational efficiency about smart-logistics ecological chains led by an e-commerce platform. First, it reveals that under e-commerce platform leadership, the smart-logistics ecological chain’s organisational efficiency directly relates to two factors: the eco-chain’s technological innovation capability and contract fulfilment. Second, national policies, consumer demands, the competition among ecological chains, and Information-sharing will indirectly affect the smart-logistics ecological chain’s organisational efficiency. Third, enhancing the smart-logistics ecological chain’s technological innovation capability positively impacts its contract fulfilment. © 2020 Informa UK Limited, trading as Taylor & Francis Group.","contract fulfilment; E-commerce platform; multi-case study; organisational efficiency; smart logistics ecological chain; technological innovation capability",{"$nulls":5},"National Key Research and Development Program of China, NKRDPC, (2018YFB1601400); National Office for Philosophy and Social Sciences, NPOPSS, (18ZDA060)","This research was funded by National Key R&D Program of China (grant number No. 2018YFB1601400). It also was funded by Major Program of the National Social Science Foundation of China (grant number No. 18ZDA060). The reviewers’ comments are also highly appreciated. 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Zhang N., Smart Logistics Path for Cyber-Physical Systems with Internet of Things, IEEE Access, 6, pp. 70808-70819, (2018); Zhao X., Technological Innovation and Acquisitions, Management Science, 55, 7, pp. 1170-1183, (2009); Zhong X., Yang X., Science and Technology Policy Reform and Its Impact on China's National Innovation System, Technology in Society, 29, 3, pp. 317-325, (2007)","W. Liu; College of Management and Economics, Tianjin University, Tianjin, China; email: lwhliu888@163.com",null,"Taylor and Francis Ltd.",{"$nulls":5},1.3675567E7,null,null,null,"English","Int. J. Logist. Res. Applic.","Article","Final",null,"Scopus","2-s2.0-85084261710"]
["Zhang X.; Xu D.; Xiao L.","Zhang, Xiaheng (57201496312); Xu, Dongpeng (57225128527); Xiao, Lin (57225127689)","57201496312; 57225128527; 57225127689","Intelligent Perception System of Big Data Decision in Cross-Border e-Commerce Based on Data Fusion",2021.0,"Journal of Sensors",2021.0,null,7021151.0,null,null,null,8.0,"10.1155/2021/7021151","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85109209062&doi=10.1155%2f2021%2f7021151&partnerID=40&md5=f3c0757f54b6aba3af0a1f50a5a910f5","College of Business and Trade, Nanchang Institute of Science and Technology, Jiangxi, Nanchang, 330108, China; Management School, Northwest University of Political Science and Law, Shaanxi, Xi'an, 710122, China; Faculty of Finance, City University of Macau, 999078, Macao","Zhang X., College of Business and Trade, Nanchang Institute of Science and Technology, Jiangxi, Nanchang, 330108, China, Management School, Northwest University of Political Science and Law, Shaanxi, Xi'an, 710122, China; Xu D., Faculty of Finance, City University of Macau, 999078, Macao; Xiao L., Management School, Northwest University of Political Science and Law, Shaanxi, Xi'an, 710122, China","There is a gap between supply and demand in cross-border e-trading platforms. The so-called supply and demand gap refers to the existing good companies that cannot meet the needs of buyers. Cross-border e-commerce, the buyer's purchase demand is often included in the buyer's behavior, such as searching for goods by pressing buttons, clicking price, category and other means, and on-site delivery time. It is important for CBEC to analyze the buyer's needs to protect the procurement and provide the seller with reference to supply, so as to solve the supply and demand gap between the buyer and the seller. This paper mainly studies the CBEC big data decision intelligent perception system based on data fusion. It is the same as the innovation process of better application of data fusion to the e-commerce business model. At the same time, the key technologies of data extraction, conversion, data warehouse, and front-end display in the system construction are analyzed and designed. This paper mainly uses data fusion algorithm, data fusion network model, quaternion method, big data decision intelligent sensing system framework design experiment, and CBEC user experiment to study the CBEC big data decision intelligent sensing system based on data fusion, and also with the development of CBEC, I hope more people can participate in CBEC practice. The results show that with the increase of data volume of the CBEC platform from 2016 to 2020, the construction of the CBEC platform business of big data production intelligent perception system considers the situation of users from seven aspects. With the increase of consumption, domestic consumers are increasingly pursuing a better life, cross-border import e-commerce ushered in a great development era.  © 2021 Xiaheng Zhang et al.",null,"Big data; Data fusion; Data handling; Electronic commerce; Sales; Data fusion algorithm; Data fusion networks; E-commerce business; Innovation process; Intelligent perception; Intelligent sensing; Quaternion methods; System construction; Data warehouses",{"$nulls":6},"Liao W., Huang X., Van Coillie F., Gautama S., Pizurica A., Philips W., Liu H., Zhu T., Shimoni M., Moser G., Tuia D., Processing of multiresolution thermal hyperspectral and digital color data: Outcome of the 2014 IEEE GRSS data fusion contest, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 8, 6, pp. 2984-2996, (2017); Semmens K.A., Anderson M.C., Kustas W.P., Gao F., Alfieri J.G., McKee L., Prueger J.H., Hain C.R., Cammalleri C., Yang Y., Xia T., Sanchez L., Mar Alsina M., Velez M., Monitoring daily evapotranspiration over two California vineyards using Landsat 8 in a multi-sensor data fusion approach, Remote Sensing of Environment, 185, 185, pp. 155-170, (2016); Bareinboim E., Pearl J., Causal inference and the data-fusion problem, Proceedings of the National Academy of Sciences of the United States of America, 113, 27, pp. 7345-7352, (2016); Berkow M., Monsere C.M., Koonce P., Bertini R.L., Wolfe M., Prototype for data fusion using stationary and mobile data: Sources for improved arterial performance measurement, Transportation Research Record: Journal of the Transportation Research Board, 2099, 1, pp. 102-112, (2018); Schmitt M., Zhu X.X., Data fusion and remote sensing: An ever-growing relationship, IEEE Geoscience and Remote Sensing Magazine, 4, 4, pp. 6-23, (2016); Liu K., Huang S., Integration of data fusion methodology and degradation modeling process to improve prognostics, IEEE Transactions on Automation Science and Engineering, 13, 1, pp. 344-354, (2016); Yokoya N., Grohnfeldt C., Chanussot J., Hyperspectral and multispectral data fusion: A comparative review of the recent literature, IEEE Geoscience and Remote Sensing Magazine, 5, 2, pp. 29-56, (2017); Mou L., Zhu X., Vakalopoulou M., Karantzalos K., Paragios N., Le Saux B., Moser G., Tuia D., Multitemporal very high resolution from space: Outcome of the 2016 IEEE GRSS data fusion contest, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10, 8, pp. 3435-3447, (2017); Tuia D., Moser G., Le Saux B., Bechtel B., See L., 2017 IEEE GRSS data fusion contest: Open data for global multimodal land use classification [technical committees], IEEE Geoscience and Remote Sensing Magazine, 5, 1, pp. 70-73, (2017); Pradhan B., Jebur M.N., Shafri H.Z.M., Tehrany M.S., Data fusion technique using wavelet transform and Taguchi methods for automatic landslide detection from airborne laser scanning data and QuickBird satellite imagery, IEEE Transactions on Geoscience and Remote Sensing, 54, 3, pp. 1610-1622, (2016); Chen F.C., Jahanshahi R., NB-CNN: Deep learning-based crack detection using convolutional neural network and Naïve Bayes data fusion, IEEE Transactions on Industrial Electronics, 65, 5, pp. 4392-4400, (2018); Bijarbooneh F.H., Du W., Ngai E.C.-H., Fu X., Liu J., Cloud-assisted data fusion and sensor selection for internet-of-things, IEEE Internet of Things Journal, 3, 3, pp. 257-268, (2017); Zhou D., Zhang K., Ravey A., Gao F., Miraoui A., On-line estimation of lithium polymer batteries state-of-charge using particle filter based data fusion with multi-models approach, IEEE Transactions on Industry Applications, 52, 3, pp. 2582-2595, (2016); Tao Z., Bonnifait P., Sequential data fusion of GNSS pseudoranges and Dopplers with map-based vision systems, IEEE Transactions on Intelligent Vehicles, 1, 3, pp. 254-265, (2017); Alofi A., Alghamdi A., Alahmadi R., Aljuaid N., Hemalatha M., A review of data fusion techniques, International Journal of Computer Applications, 167, 7, pp. 37-41, (2017); Kawa A., Zdrenka W., Conception of integrator in CBEC, Logforum, 12, 121, pp. 63-73, (2016); Hsiao Y.H., Chen M.C., Liao W.C., Logistics service design for cross-border E-commerce using Kansei engineering with text-mining-based online content analysis, Telematics & Informatics, 34, 4, pp. 284-302, (2017); Qian H., Status of cross border e-commerce development against the background of \"silk Road Economic Belt\" and measures%, Journal of Urumqi Vocational University, 25, 3, pp. 44-48, (2016); Wang Y.K., Model for evaluating the logistics service quality of cross-border E-commerce enterprises with intuitionistic fuzzy information, Journal of Computational and Theoretical Nanoscience, 14, 2, pp. 1136-1139, (2017); Fan Q., An empirical study on cross border e-commerce promoting regional economic i nnovation: Taking Taicang City as an example, Jiangsu Science and Technology Information, 36, 15, pp. 1-3, (2019); Zhou M., Li Y., Tahir M.J., Geng X., Wang Y., He W., Integrated statistical test of signal distributions and access point contributions for Wi-Fi indoor localization, IEEE Transactions on Vehicular Technology, 70, 5, pp. 5057-5070, (2021); Zhou M., Wang Y., Liu Y., Tian Z., An information-theoretic view of WLAN localization error bound in GPS-denied environment, IEEE Transactions on Vehicular Technology, 68, 4, pp. 4089-4093, (2019)","D. Xu; Faculty of Finance, City University of Macau, 999078, Macao; email: f20092100138@cityu.mo",null,"Hindawi Limited",{"$nulls":5},"1687725X",null,null,null,"English","J. Sensors","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85109209062"]
["Wu Y.; Wang Q.; Zhou Y.; Huang M.","Wu, Yongzhong (55707413300); Wang, Qiran (57218346254); Zhou, Yongwu (7405366443); Huang, Mianmian (57201552469)","55707413300; 57218346254; 7405366443; 57201552469","Strategic decisions on the establishment of an offshore warehouse for manufacturers with an e-commerce channel",2021.0,"International Journal of Industrial and Systems Engineering",38.0,2.0,null,239.0,262.0,23.0,3.0,"10.1504/IJISE.2021.115323","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85106867276&doi=10.1504%2fIJISE.2021.115323&partnerID=40&md5=a702eb4599e98039e615a15ed6887fe3","School of Business Administration, South China University of Technology, 381 Wushan Road, Tianhe District, Guangzhou, Guangdong, 510641, China","Wu Y., School of Business Administration, South China University of Technology, 381 Wushan Road, Tianhe District, Guangzhou, Guangdong, 510641, China; Wang Q., School of Business Administration, South China University of Technology, 381 Wushan Road, Tianhe District, Guangzhou, Guangdong, 510641, China; Zhou Y., School of Business Administration, South China University of Technology, 381 Wushan Road, Tianhe District, Guangzhou, Guangdong, 510641, China; Huang M., School of Business Administration, South China University of Technology, 381 Wushan Road, Tianhe District, Guangzhou, Guangdong, 510641, China","While Chinese manufacturers increasingly use cross-border e-commerce platforms to sell products to overseas customers, international express delivery is commonly used to meet the requirement of short order-to-delivery time for the online end customers. In order to reduce the logistics cost while meeting the service level, many manufacturers are considering renting or constructing an offshore warehouse. Goods are shipped in bulk to the offshore warehouse in advance and the daily customer orders are fulfilled by the warehouse inventory. Strategic decisions arise regarding the need for as well as the location and capacity of an offshore warehouse. This paper establishes a dedicate discrete-event simulation model to analyse these strategic decisions with considerations of key variables in different scenarios, including the order arrival rate, inventory cost and warehouse costs. The optimal inventory policy of the offshore warehouse is obtained via a metaheuristic method embedded in the simulation model. Experiments and sensitivity analysis are conducted to evaluate the impact of the key variables on the strategic decisions. The established model provides a systematic method for the decision-making regarding the optimal design of offshore warehouses for the fast-growing cross-border e-commerce industry. Copyright © 2021 Inderscience Enterprises Ltd.","Discrete-event simulation; E-commerce; Offshore warehouse; Order-to-delivery time","Decision making; Discrete event simulation; Electronic commerce; Manufacture; Offshore oil well production; Optimization; Sales; Sensitivity analysis; Systems engineering; Chinese manufacturers; Discrete-event simulation model; International express; Inventory policies; Meta-heuristic methods; Simulation model; Strategic decisions; Systematic method; Warehouses",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (71571071)","This work was supported by the National Natural Science Foundation of China under Grants <71571071>, <71520107001>.","Avci M.G., Selim H., A multi-objective, simulation-based optimization framework for supply chains with premium freights, Expert Systems with Applications, 67, pp. 95-106, (2017); Badri M.A., Davis D.L., Davis D., Decision support models for the location of firms in industrial sites, International Journal of Operations & Production Management, 15, 15, pp. 50-62, (1995); Baumol W.J., Wolfe P., A warehouse-location problem, Operations Research, 6, 2, pp. 252-263, (1958); Bhutta K.S., Huq F., Frazier G., Mohamed Z., An integrated location, production, distribution and investment model for a multinational corporation, International Journal of Production Economics, 86, 3, pp. 201-216, (2003); Bookbinder J.H., Bayley T., Logistics and transportation in global supply chains: review, critique, and prospects, INFORMS Tutorials in Operations Research, pp. 182-211, (2009); Bugert N., Lasch R., Effectiveness of responsive pricing in the face of supply chain disruptions, Computers & Industrial Engineering, 124, pp. 304-315, (2018); Campbell J.F., O'Kelly M.E., Twenty-five years of hub location research, Transportation Science, 46, 2, pp. 153-169, (2012); Canel C., Khumawala B.M., A mixed-integer programming approach for the international facilities location problem, International Journal of Operations & Production Management, 16, 4, pp. 49-68, (1996); Canel C., Khumawala B.M., International facilities location: a heuristic procedure for the dynamic uncapacitated problem, International Journal of Production Research, 39, 17, pp. 3975-4000, (2001); Carvalho H., Barroso A.P., Machado V.H., Azevedo S., CzuzMachado V., Supply chain redesign for resilience using simulation, Computers & Industrial Engineering, 62, 1, pp. 329-341, (2012); Chang H-JC., Hsieh C-M., A new model for selecting sites for chain stores in China, International Journal of Industrial and Systems Engineering, 28, 3, pp. 346-359, (2018); Chatfield D.C., Hayya J.C., Harrison T.P., A multi-formalism architecture for agent-based, order-centric supply chain simulation, Simulation Modelling Practice & Theory, 15, 2, pp. 153-174, (2007); Chen Y.J., Chen Y.M., An XML-based modular system analysis and design for supply chain simulation, Robotics and Computer Integrated Manufacturing, 25, 2, pp. 289-302, (2009); Cigolini R., Pero M., Rossi T., Sianesi A., Linking supply chain configuration to supply chain performance: a discrete event simulation model, Simulation Modelling Practice and Theory, 40, pp. 1-11, (2014); Dorigatti M., Guarnaschelli A., Chiotti O., Salomone H.E., A service-oriented framework for agent-based simulations of collaborative supply chains, Computers in Industry, 83, pp. 92-107, (2016); Fanti M.P., Iacobellis G., Ukovich W., Boschian V., Georgoulas G., Stylios C., A simulation-based decision support system for logistics management, Journal of Computational Science, 10, pp. 86-96, (2015); Felix T.S.C., Zhang T., The impact of collaborative transportation management on supply chain performance: a simulation approach, Expert Systems with Applications, 38, 3, pp. 2319-2329, (2011); Fuchs E., Kirchain R., Design for location? The impact of manufacturing offshore on technology competitiveness in the optoelectronics industry, Management Science, 56, 12, pp. 2323-2349, (2010); Ge H., Nolan J., Gray R., Goetz S., Han Y., Supply chain complexity and risk mitigation – a hybrid optimization–simulation model, International Journal of Production Economics, 179, pp. 228-238, (2016); Gelareh S., Pisinger D., Fleet deployment, network design and hub location of liner shipping companies, Transportation Research Part E: Logistics and Transportation Review, 47, 6, pp. 947-964, (2011); Gourdin K.N., Global Logistics Management: A Competitive Advantage for the 21st Century, (2006); Hamad R., Gualda N.D.F., Model for facilities or vendors location in a global scale considering several echelons in the chain, Networks & Spatial Economics, 8, 2–3, pp. 297-307, (2008); Hung W.Y., Samsatli N.J., Shah N., Object-oriented dynamic supply-chain modelling incorporated with production scheduling, European Journal of Operational Research, 169, 3, pp. 1064-1076, (2006); Iannone R., Miranda S., Riemma S., Supply chain distributed simulation: an efficient architecture for multi-model synchronization, Simulation Modelling Practice and Theory, 15, 3, pp. 221-236, (2007); iiMedia Research, (2018); Ivanov D., Disruption tails and revival policies: a simulation analysis of supply chain design and production-ordering systems in the recovery and post-disruption periods, Computers & Industrial Engineering, 127, pp. 558-570, (2018); Kouvelis P., Rosenblatt M.J., Munson C.L., A mathematical programming model for global plant location problems: analysis and insights, IIE Transactions, 36, 2, pp. 127-144, (2004); Li J., Sheng Z., Liu H., Multi-agent simulation for the dominant players’ behavior in supply chains, Simulation Modelling Practice and Theory, 18, 6, pp. 850-859, (2010); Long Q., Zhang W., An integrated framework for agent-based inventory–production–transportation modelling and distributed simulation of supply chains, Information Sciences, 277, 2, pp. 567-581, (2014); Lu L.X., Van M.J.A., Multimarket facility network design with offshoring applications, Manufacturing & Service Operations Management, 11, 1, pp. 90-108, (2009); Mohanavelu T., Krishnaswamy R., Marimuthu P., Simulation modelling and development of analytic hierarchy process-based priority dispatching rule for a dynamic press shop, International Journal of Industrial and Systems Engineering, 27, 3, pp. 340-364, (2017); Oum T.H., Park J.H., Multinational firms’ location preference for regional distribution centers: focus on the Northeast Asian region, Transportation Research Part E: Logistics and Transportation Review, 40, 2, pp. 101-121, (2004); Ouzi, (2017); Pinho T.M., Coelho J.P., Oliveira P.M., Oliveira B., Marques A., Rasinmaki J., Moreira A.P., Veiga G., Boaventura-Cunha J., Routing and schedule simulation of a biomass energy supply chain through SimPy simulation package, Applied Computing and Informatics, (2018); Robinson A.G., Bookbinder J.H., NAFTA supply chains: facilities location and logistics, International Transactions in Operational Research, 14, 2, pp. 179-199, (2010); Sahin M., Ko H.S., Lee H.F., Azambuja M., A simulation case study on supply chain management of a construction firm adopting cloud computing and RFID, International Journal of Industrial and Systems Engineering, 27, 2, pp. 233-254, (2017); Sajadi S.M., Ghasemi S., Vahdani H., Simulation optimisation for nurse scheduling in a hospital emergency department (case study: Shahid Beheshti Hospital), International Journal of Industrial and Systems Engineering, 23, 4, pp. 405-419, (2016); Serrano A., Faulin J., Hirsch P., Fikar C., Agent-based simulation for horizontal cooperation in logistics and transportation: from the individual to the grand coalition, Simulation Modelling Practice & Theory, 85, pp. 47-59, (2018); Sharma P., Singhal S., A review of objectives and solution approaches for facility layout problems, International Journal of Industrial and Systems Engineering, 24, 4, pp. 469-489, (2016); Wu H.H., Chen C.P., Tsai C.H., Tsai T.P., A study of an enhanced simulation model for TOC supply chain replenishment system under capacity constraint, Expert Systems with Applications, 37, 9, pp. 6435-6440, (2010); Wu S., Yang Z., Locating manufacturing industries by flow-capturing location model – case of Chinese steel industry, Transportation Research Part E: Logistics and Transportation Review, 112, pp. 1-11, (2018); Yoo T., Cho H., Yucesan E., Hybrid algorithm for discrete event simulation based supply chain optimization, Expert Systems with Applications, 37, 3, pp. 2354-2361, (2010); Zheng J., Qi J., Sun Z., Li F., Community structure based global hub location problem in liner shipping, Transportation Research Part E: Logistics and Transportation Review, 118, pp. 1-19, (2018)","Y. Zhou; School of Business Administration, South China University of Technology, Guangzhou, Guangdong, 381 Wushan Road, Tianhe District, 510641, China; email: zyw_666@hotmail.com",null,"Inderscience Publishers",{"$nulls":5},1.7485037E7,null,null,null,"English","Int. J. Ind. Syst. Eng.","Article","Final",null,"Scopus","2-s2.0-85106867276"]
["Alhaddad M.J.; Alkinani M.H.; Atoum M.S.; Alarood A.A.","Alhaddad, Mohammed J. (6508021649); Alkinani, Monagi H. (57190278212); Atoum, Mohammed Salem (57908540600); Alarood, Alaa Abdulsalm (57188661907)","6508021649; 57190278212; 57908540600; 57188661907","Evolutionary detection accuracy of secret data in audio steganography for securing 5G-enabled internet of things",2020.0,"Symmetry",12.0,12.0,2071.0,1.0,18.0,17.0,9.0,"10.3390/sym12122071","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85097806557&doi=10.3390%2fsym12122071&partnerID=40&md5=5840b062b76a543cafb6dc3c397cf084","Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, 21441, Saudi Arabia; College of Computer Science and Engineering, University of Jeddah, Jeddah, 21959, Saudi Arabia; Department of Computer Science, Irbid National University, Irbid, 21162, Jordan","Alhaddad M.J., Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, 21441, Saudi Arabia; Alkinani M.H., College of Computer Science and Engineering, University of Jeddah, Jeddah, 21959, Saudi Arabia; Atoum M.S., Department of Computer Science, Irbid National University, Irbid, 21162, Jordan; Alarood A.A., College of Computer Science and Engineering, University of Jeddah, Jeddah, 21959, Saudi Arabia","With the unprecedented growing demand for communication between Internet of Things (IoT) devices, the upcoming 5G and 6G technologies will pave the path to a widespread use of ultra-reliable low-latency applications in such networks. However, with most of the sensitive data being transmitted over wireless links, security, privacy and trust management are emerging as big challenges to handle. IoT applications vary, from self-driving vehicles, drone deliveries, online shopping, IoT smart cities, e-healthcare and robotic assisted surgery, with many applications focused on Voice over IP (VoIP) and require securing data from potential eavesdroppers and attackers. One well-known technique is a hidden exchange of secret data between the devices for which security can be achieved with audio steganography. Audio steganography is an efficient, reliable and low-latency mechanism used for securely communicating sensitive data over wireless links. MPEG-1 Audio Layer 3’s (MP3’s) bit rate falls within the acceptable sound quality required for audio. Its low level of noise distortion does not affect its sound quality, which makes it a good carrier medium for steganography and watermarking. The strength of any embedding technique lies with its undetectability measure. Although there are many detection techniques available for both steganography and watermarking, the detection accuracy of secret data has been proven erroneous. It has yet to be confirmed whether different bit rates or a constant sampling rate for embedding eases detection. The accuracy of detecting hidden information in MP3 files drops with the influence of the compression rate or increases. This drop or increase is caused by either the increase in file track size, the sampling rate or the bit rate. This paper presents an experimental study that evaluates the detection accuracy of the secret data embedded in MP3. Training data were used for the embedding and detection of text messages in MP3 files. Several iterations were evaluated. The experimental results show that the used approach was effective in detecting the embedded data in MP3 files. An accuracy rate of 97.92% was recorded when detecting secret data in MP3 files under 128-kbps compression. This result outperformed the previous research work. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.","5G technology; Audio steganography; Embedding; Internet of things; Least significant bit; Security and privacy; Steganalysis detection accuracy",{"$nulls":5},"Deanship of Scientific Research; King Abdulaziz University, KAU, (G-481-611-37)","Acknowledgments: This project was funded by the Deanship of Scientific Research (DSR) at King Abdulaziz University, Jeddah, under grant no. G-481-611-37. The authors, therefore, acknowledge with thanks DSR for technical and financial support.","Goudos S.K., Dallas P.I., Chatziefthymiou S., Kyriazakos S.A., A Survey of IoT Key Enabling and Future Technologies: 5G, Mobile IoT, Sematic Web and Applications, Wirel. Pers. Commun, 97, pp. 1645-1675, (2017); Saxena N., Roy A., Sahu B.J.R., Kim H., Efficient iot gateway over 5g wireless: A new design with prototype and implementation results, IEEE Commun. Mag, 55, pp. 97-105, (2017); Chettri L., Bera R., A Comprehensive Survey on Internet of Things (IoT) Toward 5G Wireless Systems, IEEE Internet Things J, 7, pp. 16-32, (2020); Balgurgi P.P., Jagtap S.K., Audio steganography used for secure data transmission, Proceedings of the International Conference on Advances in Computing, (2013); Chandini M.S., An Overview about a Milestone in Information Security: Steganography, Int. J. Progress. Res. Sci. Eng, 1, pp. 33-35, (2020); Das R., Tuithung T., A novel steganography method for image based on Huffman Encoding, Proceedings of the 3rd National Conference on Emerging Trends and Applications in Computer Science, (2012); Hu D., Wang L., Jiang W., Zheng S., Li B., A Novel Image Steganography Method via Deep Convolutional Generative Adversarial Networks, IEEE Access, 6, pp. 38303-38314, (2018); Westfeld A., Detecting low embedding rates, International Workshop on Information Hiding, pp. 324-339, (2002); Wan W., Zhao X., Huang W., Sheng R., Steganalysis of mp3stego based onhu_man table distribution and recording, J. Grad. Univ. Chin. Acad. Sci, 29, pp. 118-124, (2012); Chhikara R., Singh L., A review on digital image steganalysis techniques categorised by features extracted, Int. J. Eng. Innov. Technol, 3, pp. 203-213, (2013); Alarood A., Abdulmanaf A., Ibrahim S., Alhaddad M.J., Mp3 steganalysis based on neural networks, Int. J. Eng. Technol, 15, pp. 74-78, (2015); Lopez-Hernandez J., Martinez-Noriega R., Nakano-Miyatake M., Yamaguchi K., Detection of bpcs-steganography using smwcf steganalysis and svm, Proceedings of the International Symposium on Information Theory and Its Applications, pp. 1-5; Usha B., Srinath N., Cauvery N., Data embedding technique in image steganography using neural network, Int. J. Adv. Res. Comput. Commun. Eng, 2, pp. 2319-5940, (2013); Gomez-Coronel S.L., Escalante-Ramirez B., Acevedo-Mosqueda M.A., Mosqueda M.E.A., Steganography in audio files by hermite transform, Appl. Math. Inf. Sci, 8, (2014); Kesavaraj G., Sukumaran S., A study on classi_cation techniques in data mining, Proceedings of the Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT), pp. 1-7; Ker A.D., Bas P., Bohme R., Cogranne R., Craver S., Filler T., Fridrich J., Pevny T., Moving steganography and steganalysis from the laboratory into the real world, Proceedings of the First ACM Workshop on Information Hiding and Multimedia Security, pp. 45-58; V Holub J.F., Designing steganographic distortion using directional filters, Proceedings of the IEEE International Workshop on Information Forensics and Security (WIFS), pp. 234-239; Qiao M., Sung A.H., Liu Q., MP3 audio steganalysis, Inf. Sci, 231, pp. 123-134, (2013); Jan-Ti Y., Yu J.-M., A Novel Hardware Implementation of MP3 Decoder for Low Power and Minimum Chip Size, Proceedings of the 6th International Conference on ASIC, 2, pp. 1085-1088, (2005); Jin C., Wang R., Diqun Y., Steganalysis of MP3Stego with low embedding-rate using Markov feature, Multimed. Tools Appl, 76, pp. 6143-6158, (2016); Kodovsky J., Pevny T., Fridrich J.J., Modern steganalysis can detect YASS, Media Forensics and Security II, 7541, (2010); Pevny T., Fridrich J., Novelty detection in blind steganalysis, Proceedings of the 10th ACM Workshop on Multimedia and Security, pp. 167-176; Fridrich J., Feature-based steganalysis for jpeg images and its implications for future design of steganographic schemes, Proceedings of the International Workshop on Information Hiding, pp. 67-81; Hernandez-Castro J., Estevez-Tapiador J., Palomar E., Romero-Gonzalex A., Blind steganalysis of mp3stego, J. Inf. Sci. Eng, 26, pp. 1787-1799, (2010); Chandramouli R., Memon N.D., A distributed detection framework for steganalysis, Proceedings of the 2000 ACM Workshops on Multimedia, pp. 123-126, (2000); Fridrich J., Goljan M., Practical steganalysis of digital images: State of the art, Security and Watermarking of Multimedia Contents IV, 4675, pp. 1-13, (2002); Cox I., Miller M., Bloom J., Fridrich J., Kalker T., Digital Watermarking and Steganography, (2007); Hou Y., Ni R., Zhao Y., Steganalysis to adaptive pixel pair matching using two-group subtraction pixel adjacency model of covers, Proceedings of the 12th International Conference on Signal Processing (ICSP), pp. 1864-1867; Provos N., Defending against statistical steganalysis, Proceedings of the Usenix Security Symposium, 10, pp. 323-336, (2001); Bohme R., Assessment of steganalytic methods using multiple regression models, Proceedings of the International Workshop on Information Hiding, pp. 278-295; Kodovsky J., Fridrich J., Holub V., Ensemble classifiers for steganalysis of digital media, IEEE Trans. Inf. Forensics Secur, 7, pp. 432-444, (2011); Fridrich J., Kodovsky J., Rich models for steganalysis of digital images, IEEE Trans. Inf. Forensics Secur, 7, pp. 868-882, (2012); Homburg H., Mierswa I., Moller B., Morik K., Wurst M., A benchmark dataset for audio classification and clustering, Proceedings of the 6th International Conference on Music Information Retrieval (ISMIR), 2005, pp. 528-531; Atoum M.S., New mp3 steganography data set, Proceedings of the 2015 5th International Conference on IT Convergence and Security (ICITCS), pp. 1-7; Shahzad M., Liu A.X., Samuel A., Secure unlocking of mobile touch screen devices by simple gestures: You can see it but you can not do it, Proceedings of the 19th Annual International Conference on Mobile Computing & Networking, pp. 39-50, (2013); Diqun Y., Wang R., Yu X., Zhu J., Steganalysis for MP3Stego using differential statistics of quantization step, Digit. Signal Process, 23, pp. 1181-1185, (2013)","A.A. Alarood; College of Computer Science and Engineering, University of Jeddah, Jeddah, 21959, Saudi Arabia; email: alaa.alarood@gmail.com",null,"MDPI AG",{"$nulls":5},2.0738994E7,null,null,null,"English","Symmetry","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85097806557"]
["Kosovac A.; Muharemovic E.","Kosovac, Amel (55913615900); Muharemovic, Ermin (57216899452)","55913615900; 57216899452","Pickup and delivery costs- A proposed outsourcing model based on the number of stops",2021.0,"Journal of Applied Engineering Science",19.0,2.0,null,270.0,274.0,4.0,1.0,"10.5937/jaes0-28450","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85108519917&doi=10.5937%2fjaes0-28450&partnerID=40&md5=4dfa6de49c348b2ebdc405177d3d9f38","Faculty of Traffic and Communications, University of Sarajevo, Sarajevo, Bosnia and Herzegovina","Kosovac A., Faculty of Traffic and Communications, University of Sarajevo, Sarajevo, Bosnia and Herzegovina; Muharemovic E., Faculty of Traffic and Communications, University of Sarajevo, Sarajevo, Bosnia and Herzegovina","The active introduction and modern technologies application in the transport market greatly affect all transport branches and the ways of their business. Availability and mass usage of the internet and web services create a new ambiance of trade through online sales and e-commerce. The increase in internet sales has a direct effect on the business of courier companies. The number of shipments in the B2C (Business-to-Consumer) segment is growing and putting an increasing pressure on costs for companies that perform pickup and delivery. Companies are trying to adapt their business to the new challenges and conditions that prevail in the transport market through different cost management models. One way to manage costs is to outsource costs. This paper proposes a model cost calculation in outsourcing services for pickup and delivery shipments based on the number of stops. © 2021 Institut za Istrazivanja. All rights reserved.","Costs; Delivery; Model; Outsourcing; Pickup; Stop",{"$nulls":7},"Ko S. Y., Cho S. W., Lee C., Pricing and Collaboration in Last Mile Delivery Services, Sustainability, 10, 12, pp. 1-20, (2018); Tiwapat N., Pomsing C., Jomthong P., Last Mile Delivery: Modes, Efficiencies, Sustainability, and Trends, 2018 3rd IEEE International Conference on Intelligent Transportation Engineering, ICITE 2018, pp. 313-317, (2018); Duan H., Et al., Post-consumer packaging waste from express delivery in China, Resources, Conservation and Recycling, 144, pp. 137-143, (2019); Ding Z., Evaluating Different Last Mile Logistics Solutions, (2014); Tibor K., Outsourcing decision support: A survey of benefits, risks, and decision factors, Supply Chain Management: An International Journal, 11, 6, pp. 467-482, (2006); Sahay B. S., Mohan R., 3PL practices: An Indian perspective, International Journal of Physical Distribution &Logistics Management, 36, 9, pp. 666-689, (2006); Kosovac A., Muharemovic E., Trubint N., A Cost Calculation Model for Outsourcing in Parcel Pick-up and Delivery by Commercial Postal Services Operators, TEM JOURNAL-TECHNOLOGY EDUCATION MANAGEMENT INFORMATICS. NOVI PAZAR, ASSOC INFORMATION COMMUNICATION TECHNOLOGY EDUCATION & SCIENCE, 9, 1, pp. 216-220, (2020); Boyer K. K., Prud'homme A. M., Chung W., THE LAST MILE CHALLENGE: EVALUATING THE EFFECTS OF CUSTOMER DENSITY AND DELIVERY WINDOW PATTERNS, Journal of Business Logistics, 30, 1, pp. 185-201, (2009); Kin B., Et al., Modelling alternative distribution set-ups for fragmented last mile transport: Towards more efficient and sustainable urban freight transport', Case Studies on TransportPolicy, World Conference on Transport Research Society, 6, 1, pp. 125-132, (2018); Thakur R. K., MIT Global SCALE Network, (2016); Deljanin A., Colakovic A., Muharemovic E., Rationalization of Transport of Postal Shipment using GPS/RFID Technologies in Bosnia and Herzegovina, Suvremeni Promet-Modern Traffic, 34, 1-2, pp. 26-31, (2014); Deljanin A., Kosovac A., Muharemovic E., Use of ITS System as a Track&Trace in Express Delivery in Bosnia and Herzegovina, Suvremeni Promet-Modern Traffic, 37, 1-2, pp. 30-35, (2017); Jung H., Lee K., Chun W., Integration of GIS, GPS, and optimization technologies for the effective control of parcel delivery service, Computers and Industrial Engineering, 51, 1, pp. 154-162, (2006); Causevic S., Et al., Potentials and advantages of applying geographic information systems in various fields of traffic engineering, Road and Rail Infrastructure V, pp. 1285-1290, (2018)","E. Muharemovic; Faculty of Traffic and Communications, University of Sarajevo, Sarajevo, Bosnia and Herzegovina; email: ermin.muharemovic@fsk.unsa.ba",null,"Institut za Istrazivanja",{"$nulls":5},1.4514117E7,null,null,null,"English","J. Appl. Eng. Sci.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85108519917"]
["Wang K.; Bae K.-H.","Wang, Kun (58366594400); Bae, Ki-Hyung (57203764524)","58366594400; 57203764524","In-Depth Learning Layout and Path Optimization of Energy Service Urban Distribution Sites under e-Commerce Environment",2021.0,"Complexity",2021.0,null,6665610.0,null,null,null,3.0,"10.1155/2021/6665610","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85101573752&doi=10.1155%2f2021%2f6665610&partnerID=40&md5=32dbf9ea57ad59c0def529a955e26124","Department of Economics, Sejong University, Seoul, 05000, South Korea; College of Foreign Language and Tourism, Henan Institute of Economics and Trade, Zhengzhou, 450018, China","Wang K., Department of Economics, Sejong University, Seoul, 05000, South Korea, College of Foreign Language and Tourism, Henan Institute of Economics and Trade, Zhengzhou, 450018, China; Bae K.-H., Department of Economics, Sejong University, Seoul, 05000, South Korea","This article uses a research method that combines theoretical research and empirical analysis. It first introduces the relevant theories of energy service city distribution sites in the context of e-commerce and then the types of energy service city distribution sites and the composition of energy service city distribution systems. The network layout of the service city distribution site and the location objectives, principles, and processes of the model is studied to determine the network layout plan of the energy service city distribution system in this paper. This paper fully considers the characteristics of the network operation mode of the energy service city distribution site and establishes an optimization model for the location selection and vehicle routing of the distribution center with the lowest total system cost under the simultaneous delivery service mode; based on the hierarchical solution strategy, a combination of deep learning is designed. Algorithms mainly include two-stage hybrid heuristic algorithm of cluster analysis, maximum coverage and genetic algorithm; simulation analysis is conducted to verify the effectiveness of the model and algorithm by data simulation, finally get the integrated optimization plan of distribution center location and routing, and put forward the operation strategy through the result expansion analysis. This paper studies the planning model based on the network layout planning of the energy service city distribution system under the e-commerce environment, aiming to promote the breakthrough development of urban smart logistics and prove the importance of the energy service city distribution station network layout planning. The purpose and results of the research are to reduce traffic and environmental pressures, achieve joint direct distribution, improve the efficiency of urban logistics and distribution, and solve the problem of the last mile of the city.  © 2021 Kun Wang and Ki-Hyung Bae.",null,"Cluster analysis; Clustering algorithms; Deep learning; Electronic commerce; Genetic algorithms; Heuristic algorithms; Location; Urban growth; Vehicle routing; Warehouses; Distribution centers; Environmental pressures; Hybrid heuristic algorithms; Integrated optimization; Model and algorithms; Optimization modeling; Simulation analysis; Theoretical research; Location based services",{"$nulls":6},"Chen Z., Dong J., Ren R., Urban underground logistics system in China: opportunities or challenges?, Underground Space, 2, 3, pp. 195-208, (2017); Savelsbergh M., Van Woensel T., 50th anniversary invited article-city logistics: challenges and opportunities, Transportation Science, 50, 2, pp. 579-590, (2016); Sachs J., Andersson L.A.A., Araujo J., Adaptive 5G low-latency communication for Tactile Internet services, Proceedings of the IEEE, 107, 2, pp. 325-349, (2018); Willing C., Brandt T., Neumann D., Electronic mobility market platforms - a review of the current state and applications of business analytics, Electronic Markets, 27, 3, pp. 267-282, (2017); Paffumi E., De Gennaro M., Martini G., European-wide study on big data for supporting road transport policy, Case Studies on Transport Policy, 6, 4, pp. 785-802, (2018); Chen X., Wang H.H., Tian B., Visualization model of big data based on self-organizing feature map neural network and graphic theory for smart cities[J, ]. Cluster Computing, 22, 6, pp. 13293-13305, (2019); Zhang J., Fan J., Shen H., A study of the development framework of the travel application of public information service for urban tourism[J], Tourism, Leisure and Global Change, 1, 1, pp. 161-182, (2016); Klaine P.V., Imran M.A., Onireti O., Souza R.D., A survey of machine learning techniques applied to self-organizing cellular networks, IEEE Communications Surveys and Tutorials, 19, 4, pp. 2392-2431, (2017); Onstein A.T.C., Ektesaby M., Rezaei J., Tavasszy L.A., van Damme D.A., Importance of factors driving firms' decisions on spatial distribution structures, International Journal of Logistics Research and Applications, 23, 1, pp. 24-43, (2020); Krivy M., Towards a critique of cybernetic urbanism: The smart city and the society of control, Planning Theory, 17, 1, pp. 8-30, (2018); Wiig A., The empty rhetoric of the smart city: From digital inclusion to economic promotion in Philadelphia, Urban Geography, 37, 4, pp. 535-553, (2016); Raven R., Sengers F., Spaeth P., Xie L., Cheshmehzangi A., de Jong M., Urban experimentation and institutional arrangements, European Planning Studies, 27, 2, pp. 258-281, (2019); Verrest H., Pfeffer K., Elaborating the urbanism in smart urbanism: distilling relevant dimensions for a comprehensive analysis of Smart City approaches, Information, Communication & Society, 22, 9, pp. 1328-1342, (2019); Hashem I.A.T., Chang V., Anuar N.B., The role of big data in smart city, International Journal of Information Management, 36, 5, pp. 748-758, (2016); Barns S., Cosgrave E., Acuto M., Mcneill D., Digital infrastructures and urban governance, Urban Policy and Research, 35, 1, pp. 20-31, (2017); Gagliardi D., Schina L., Sarcinella M.L., Mangialardi G., Niglia F., Corallo A., Information and communication technologies and public participation: interactive maps and value added for citizens, Government Information Quarterly, 34, 1, pp. 153-166, (2017); Eckhoff D., Wagner I., Privacy in the smart city - applications, technologies, challenges, and solutions, IEEE Communications Surveys and Tutorials, 20, 1, pp. 489-516, (2017); Sandulli F.D., Ferraris A., Bresciani S., How to select the right public partner in smart city projects, R&D Management, 47, 4, pp. 607-619, (2017); Rossi U., The variegated economics and the potential politics of the smart city, Territory, Politics, Governance, 4, 3, pp. 337-353, (2016); Kumar N., Vasilakos A.V., Rodrigues J.J.P.C., A multi-tenant cloud-based DC nano grid for self-sustained smart buildings in smart cities, IEEE Communications Magazine, 55, 3, pp. 14-21, (2017); Sookhak M., Tang H., He Y., Security and privacy of smart cities: a survey, research issues and challenges, IEEE Communications Surveys and Tutorials, 21, 2, pp. 1718-1743, (2018); Kitchin R., The realtimeness of smart cities, TECNOSCIENZA: Italian Journal of Science and Technology Studies, 8, 2, pp. 19-42, (2018); Wang J., Jiang C., Zhang K., Vehicular sensing networks in a smart city: principles, technologies and applications, IEEE Wireless Communications, 25, 1, pp. 122-132, (2017); Vu K., Hartley K., Promoting smart cities in developing countries: policy insights from Vietnam, Telecommunications Policy, 42, 10, pp. 845-859, (2018); Pereira G.V., Macadar M.A., Luciano E.M., Testa M.G., Delivering public value through open government data initiatives in a Smart City context, Information Systems Frontiers, 19, 2, pp. 213-229, (2017); Gaffney C., Robertson C., Smarter than smart: rio de Janeiro's flawed emergence as a smart city, Journal of Urban Technology, 25, 3, pp. 47-64, (2018)","K.-H. Bae; Department of Economics, Sejong University, Seoul, 05000, South Korea; email: x201710729377@stu.ncwu.edu.cn",null,"Hindawi Limited",{"$nulls":5},1.0762787E7,null,null,null,"English","Complexity","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85101573752"]
["Zhen G.","Zhen, G. (57223815932)",5.7223815932E10,"Optimization of e-commerce logistics distribution network based on highway service areas",2021.0,"Advances in Transportation Studies",53.0,null,null,197.0,210.0,13.0,0.0,"10.4399/979128041434213","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85106174831&doi=10.4399%2f979128041434213&partnerID=40&md5=f00b477800277b8cda48a3b820262acf","College of Electronic commerce, Zhejiang Business College, Hangzhou, 310053, China","Zhen G., College of Electronic commerce, Zhejiang Business College, Hangzhou, 310053, China","With the fast growth of the transaction volume of e-commerce, the efficiency of logistics distribution has become an important factor affecting the economic benefits of related industries. To improve logistics efficiency and increase economic benefits, field scholars’ research focus has turned to the overall efficiency of the e-commerce logistics network under the new mode of “freight + operation”. For this purpose, this paper constructed an e-commerce logistics distribution network based on the highway service areas (HSAs) and optimized it with an improved genetic algorithm (GA). First, the paper gave an analysis on the process of e-commerce logistics distribution of HSAs and studied the problems of the site selection of multi-level HSAs and the path planning of e-commerce logistics distribution. Then, based on the fuzzy processing of consumer demand and the arrival time of logistics vehicles, a logistics distribution network model was constructed and optimized with the improved GA. At last, the stability and effectiveness of the model and the algorithm were verified by experimental results. © 2021, Aracne Editrice. All rights reserved.","E-commerce; Highway service area (HSA); Logistics distribution network","Economic and social effects; Efficiency; Electronic commerce; Highway service areas; Site selection; Economic benefits; Fuzzy processing; Logistics distribution; Logistics distribution networks; Logistics efficiency; Logistics network; Logistics vehicles; Overall efficiency; Genetic algorithms",{"$nulls":6},"Huang W.X., Zhou W.H., Luo F., Coopetition between B2C E-commerce Companies: Price Competition and Logistics Service Cooperation, Journal of Systems Science and Systems Engineering, 29, 6, pp. 730-749, (2020); Li H., Wu T., Ran J., Zhan J.J., Zhu Y.T., Spatial coupling between specialized production of fruits and vegetables and front-end cold-chain logistics, International Journal of Design & Nature and Ecodynamics, 15, 2, pp. 167-176, (2020); Gajewska T., Zimon D., Study of the logistics factors that influence the development of e-commerce services in the customer’s opinion, Archives of Transport, 45, 1, pp. 25-34, (2018); Giuffrida M., Mangiaracina R., Perego A., Tumino A., Logistics solutions to support cross border e-commerce towards China: The case of the apparel industry, Lecture Notes in Electrical Engineering, 413, pp. 163-177, (2017); Khan S.A.R., Chen J., Zhang Y., Golpira H., Effect of green purchasing, green logistics, and ecological design on organizational performance: A path analysis using structural equation modeling, Information Technology and Intelligent Transportation Systems, 314, pp. 183-190, (2019); Duan L.M., Path planning for batch picking of warehousing and logistics robots based on modified A algorithm, Academic Journal of Manufacturing Engineering, 16, 2, pp. 99-106, (2018); Mishra P., Pandey R.K., Mohan J., Computing shortest path for transportation logistics from high-resolution satellite imagery, Lecture Notes in Electrical Engineering, 490, pp. 59-66, (2018); Kong X.T.R., Huang G.Q., Du M.L., A physical emulation model of cellular warehousing for e-commerce logistics, Procedia CIRP, 83, pp. 339-344, (2019); Hurtado P.A., Dorneles C., Frazzon E., Big Data application for E-commerce’s Logistics: A research assessment and conceptual model, IFAC-PapersOnLine, 52, 13, pp. 838-843, (2019); Li D., Liu C.H., Li K., A remanufacturing logistics network model based on improved multi-objective ant colony optimization, Journal Européen des Systèmes Automatisés, 52, 4, pp. 391-395, (2019); Ho K., De Week O.L., Hoffman J.A., Shishko R., Campaign-level dynamic network modelling for spaceflight logistics for the flexible path concept, Acta Astronautica, 123, pp. 51-61, (2016); Cheng G.Z., Liu X.L., Xu L., Wang L.Z., Empirical estimation of the width of highway roadside clear zone, International Journal of Safety and Security Engineering, 10, 2, pp. 247-253, (2020); Hsiao Y.H., Chen M.C., Liao W.C., Logistics service design for cross-border E-commerce using Kansei engineering with text-mining-based online content analysis, Telematics and Informatics, 34, 4, pp. 284-302, (2017); Swamy L.N., Gorabal J.V., Logistic regression-based classification for reviews analysis on E-commerce based applications, Advances in Intelligent Systems and Computing, 1014, pp. 323-334, (2020); Dong B.K., Zhu X.N., Yan R., Zhang C.L., Evaluation of third-party reverse logistics providers based on extension superiority method, Ingenierie des Systemes d’Information, 24, 1, pp. 101-105, (2019); Hidayatno A., Destyanto A.R., Fadhil M., Model conceptualization on e-commerce growth impact to emissions generated from urban logistics transportation: A case study of Jakarta, Energy Procedia, 156, pp. 144-148, (2019); Jafari H., E-Commerce Logistics -Contemporary Literature, IEEE International Conference on Industrial Engineering and Engineering Management, pp. 1196-1200, (2018); Chen H., Liu S.C., Su T.S., The Study for Refurbishing Process of Packaging Material in E-commerce Logistics, Proceedings of the 2018 IEEE International Conference on Service Operations and Logistics, and Informatics, pp. 80-84, (2018); Li D., Liu C.H., Li K., A remanufacturing logistics network model based on improved multi-objective ant colony optimization, Journal Européen des Systèmes Automatisés, 52, 4, pp. 391-395, (2019); Sun G., Qiao F.J., Li Y.R., Research on logistics mode of cross border e-commerce in China, Boletin Tecnico/TechnicalBulletin, 55, 10, pp. 490-497, (2017); Burinskiene A., Pharma supply chain: Efficiency modelling approach, Journal of System and Management Sciences, 8, 2, pp. 65-73, (2018); Meincke P., Asmer L., Geike L., Wiarda H., Concepts for cargo ground handling of unmanned cargo aircrafts and their influence on the supply chain, Journal of System and Management Sciences, 8, 3, pp. 26-51, (2018); Fu P.H., Chen Y.F., Yin H.B., IUCstream: A novel increment update clustering algorithm for commodity stream data analysis in e-commerce and logistics, Journal of Computers (Finland), 8, 3, pp. 795-802, (2013); Seo Y., Seo U.J., Kim J.H., Economic feasibility of ground source heat pump system deployed in expressway service area, Geothermics, 76, pp. 220-230, (2018); Koo C., Hong T., Kim J., A decision support system for determining the optimal size of a new expressway service area: Focused on the profitability, Decision Support Systems, 67, pp. 9-20, (2014); Ito Y., Yamamoto K., Soeda M., Ohno R., An analysis of users’ behavior in the service areas of expressway by open/close log sensor attached to the toilet booth doors, AIJ Journal of Technology and Design, 20, 44, pp. 203-206, (2014); Daduna J.R., Developments in city logistics -the path between expectations and reality, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 3-21, (2019); Kawa A., Swiatowiec-Szczepanska J., Logistics Value and Perceived Customer Loyalty in E-commerce: Hierarchical Linear Modeling Analysis, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 417-427, (2020)","G. Zhen; College of Electronic commerce, Zhejiang Business College, Hangzhou, 310053, China; email: 371189942@qq.com",null,"Aracne Editrice",{"$nulls":5},1.8245463E7,null,null,null,"English","Adv. Transp. Stud.","Article","Final",null,"Scopus","2-s2.0-85106174831"]
["Islam J.","Islam, Jehirul (58555368900)",5.85553689E10,"Jurisprudence of Delivery in Consumer Contract in E-Commerce: A Critical Appraisal of The Consumer Protection Law in India",2020.0,"Indian Journal of Law and Justice",11.0,2.0,null,196.0,210.0,14.0,0.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85169155236&partnerID=40&md5=15e399620a3920db3157a3bdf8b1856f","United World School of Law, Karnavati University, Gandhinagar, India","Islam J., United World School of Law, Karnavati University, Gandhinagar, India","E-commerce market is growing tremendously due to the many advantages it provides to consumers and traders as well. On the other hand, concerns of consumer with respect to delayed delivery, wrong delivery, non-delivery and improper information pertaining to delivery of goods or services are also evident from the numbers of online consumer complaints. The Consumer Protection Act, 1986 and the Sale of Goods Act, 1930 may sufficiently protect consumers in traditional market; however, both the Acts fail to recognise the unique features of e-commerce, which have raised the new forms unease to consumers. The provisions of the newly enacted Consumer Protection Act, 2019 are structurally weak and inefficient to protect consumers in e-commerce. Classification Code: O Economic Development, Innovation, Technology Change, and Growth. © 2020, Department of Law, University of North Bengal. All rights reserved.","Consumer Protection; Delivery; E-Commerce; Law; Technology",{"$nulls":7},"United World School of Law; Barik Soumyarendra, National Consumer Helpline Registered 8,373 Complaints of Fraud in Online Shopping in 3 Years, Minister Reveals; Morgan Stanley expects ‘the size of the Indian Internet Market to rise from $ 11 bn in 2013 to $ 137 bn by 2020, making it fastest growing e-commerce market in the world; India has 350 million Internet users; Dominiquel Bosco, Teen orders laptop for 14,000 online, get brick; SambitSatpathy, 4 unexpected things Snapdeal delivered to buyers and one that Flipkart didn’t, BER India; Chengappa Sangeeta, Harmanissues legal notice to online retailer; Bose Adrija, The Big Snapdeal Screw up: Man orders smartphone, gets bar of soap instead, firstpost; Khan Nuzhat Parveen, Khan Parveen, Online Shopping in India: Issues and Challenges with Special Emphasis on the Consumer Protection Bill, 2015, JLJ, 3, (2018); Pathak Akhileshwar, E-Retailing and the Consumer Protection Bill, 2015: Drawing from the European Union Consumer Directive; Kaur Gagandeep, Jurisprudence of E-Commerce and Consumer Protection in India, 59, (2015); Khare Rajiv, GargiRajvanshi, E-commerce and Consumer Protection: A Critical Analysis of Legal Regulations, IJCLP, 1, (2013); Khan Nuzhat Parveen, Khan Parveen, Online Shopping in India: Issues and Challenges with Special Emphasis on the Consumer Protection Bill, 2015, JLJ, 3, (2018); Sharma Rama, Srivastava Vibha, Et al., Consumer Protection in the era of Ecommerce, IJR, 1, (2014); MANU/SF/0061, (2010); MANU/SF/0038, (2017); MANU/SA/0002, (2017); MANU/SG/0001, (2018); Khare Rajiv, Rajvanshi Gargi, E-commerce and Consumer Protection: A Critical Analysis of Legal Regulations, IJCLP, 1, (2013); The Sale of Goods Act, 1, (1930); Section 26 of the Sale of Goods Act, 1930 reads as; ’26. Risk prima facie passes with property.- unless otherwise agreed, the goods remain at the seller’s risk until the property therein is transferred to the buyer, but when the property therein is transferred to the buyer, the goods are at the buyer’s risk whether delivery has been made or not; The Sale of Goods Act, 2, (1930); J in Hartly v. Hymans, (1920); The Sale of Goods Act, (1930); The Sale of Goods Act, (1930); The Sale of Goods Act; Section 62 of the Sale of Goods Act, 1930 reads as ’62. Exclusion of implied terms and Conditions.- where any right, duty or liability would arise under a contract of sale by implication of law, it may be negatived or varied by express agreement or by the course of dealing between the parties, or by usage, if the usage is such as to bind both the parties to the contract; Gupta Sarla, Agrawal Beniprasad, Cyber Laws: Law Relating to Information Technology, Hacking, Intellectual Property Rights, Trade Marks, E-Commerce, Computers, Computer Software, Internet and Cyber Crimes etc, pp. 944-945, (2016); Pathak Akhileshwar, The Consumer Protection Bill, 2005: (Lack of) Rights of the Consumer to Terminate Sale Contract; Section 2 (47)(viii) of the Consumer Protection Act, 2019 recognise the following act of seller or service provider as ‘unfair trade practice’, which reads as ‘after selling such goods and rendering of such services, refuses to take back or withdraw the goods or withdraw or discontinue the service and refuses to refund the consideration thereof, if paid, within a period of thirty days after the receipt of goods or availing of services if it is so stipulated and requested by the consumer’; Pathak Akhileshwar, E-Retailing and the Consumer Protection Bill, 2015: Drawing from the European Union Consumer Directive; SC, (2005); Mail, Internet or Telephone Order Merchandise Rule; Mail, Internet or Telephone Order Merchandise Rule; The Consumer Rights Act, (2015); The Consumer Rights Act, (2015); Internet Sales Contract Harmonisation Template, 5, 3; Canadian Code of Practice for Consumer Protection in Electronic Commerce; Canadian Code of Practice for Consumer Protection in Electronic Commerce",null,null,"Department of Law, University of North Bengal",{"$nulls":5},9763570.0,null,null,null,"English","Indian. J. Law. Justice.","Article","Final",null,"Scopus","2-s2.0-85169155236"]
["Ma X.; Li W.; Wu J.","Ma, Xiaoye (57222639891); Li, Weina (58605299100); Wu, Jun (57849192800)","57222639891; 58605299100; 57849192800","Research on the Operation of e-Commerce Enterprises Based on Blockchain Technology and Bilateral Platforms",2021.0,"Wireless Communications and Mobile Computing",2021.0,null,8872689.0,null,null,null,7.0,"10.1155/2021/8872689","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85103571436&doi=10.1155%2f2021%2f8872689&partnerID=40&md5=d240c3532e6d0e4b2255f33942dd6223","Guilin University of Electronic Technology, Guilin, 541000, China; Tangshan Normal University, Tangshan, 063000, China","Ma X., Guilin University of Electronic Technology, Guilin, 541000, China; Li W., Tangshan Normal University, Tangshan, 063000, China; Wu J., Guilin University of Electronic Technology, Guilin, 541000, China","E-commerce platform enterprises have typical bilateral market characteristics. The e-commerce platform provides real-time communication services for buyers and sellers. Different buyers and sellers form crossnetwork characteristics. The formulation and implementation of bilateral strategies affect both the merchants and consumers' choice of platform and registration transactions. This impact will directly lead to the transaction value of the platform. Then, the article builds an econometric model and empirically analyses the impact of e-commerce platforms. The e-commerce chain is a complex structure that consists of logistics, information flow, and capital flow and connects suppliers, manufacturers, distributors, and users in the industry together. Blockchain technology can be used as a large-scale collaboration tool to adapt to supply chain management, the main factor that drives the market power of the enterprise. The research results show that the input costs of advertising, research and development, and employee training and the impact of long-term investment and taxation on market forces are quite different in different industries, both positive and negative, and subsidies, inventory, and state-owned holdings have a negative impact on the market power of companies in all industries. Finally, the competition strategy of e-commerce platform enterprises is summarized. On the basis of the conclusions of the theory and case study, the paper puts forward specific suggestions and countermeasures for the competition strategy of e-commerce platform enterprises in the bilateral network environment.  © 2021 Xiaoye Ma et al.",null,"Blockchain; Electronic commerce; Investments; Personnel training; Supply chain management; Taxation; Buyers and sellers; Competition strategy; E-commerce enterprise; Large-scale collaboration; Long-term investment; Network environments; Real-time communication service; Research and development; Competition",{"$nulls":6},"Nwaeze E.T., The adjustment process of accruals: Empirical evidence and implication for accrual research, Review of Quantitative Finance & Accounting, 17, 2, pp. 187-211, (2001); Proa C., Gradual wage-price adjustments, labor market frictions and monetary policy, Journal of Economic Behavior & Organization, 82, 1, pp. 220-235, (2012); Bauer S., Lazarev S., Molinari A., Breitenstein A., Leufke P., Kruk R., Hahn H., Baumbach T., The power of in situ pulsed laser deposition synchrotron characterization for the detection of domain formation during growth of Ba0.5Sr0.5TiO3 on MgO, Journal of Synchrotron Radiation, 21, 2, pp. 386-394, (2014); Teo T.S.H., Lin S., Lai K.H., Adopters and non-adopters of e-procurement in Singapore: An empirical study, Omega, 37, 5, pp. 972-987, (2009); Lee Y.-R., Jin X., Kim H.-J., Node localization based on neural network using semi-supervised learning in wireless sensor networks, The Journal of Korean Institute of Communications and Information Sciences, 44, 3, pp. 517-527, (2019); Cerny I., Veverkova A., Kovar M., Pacuta V., Molnarova J., Influence of temperature and moisture conditions of locality on the yield formation of sunflower (Helianthus annuus L.), Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, 59, 6, pp. 99-104, (2014); Hassan O., Salahddine K., Khaoula K., Lahoucine E., Salah-Ddine K., Secure data for wireless sensor network using detection malcious node method, Test Engineering and Management, 82, 1-2, pp. 4968-4982, (2020); Pinheiro J.P.V., Ahlke E., Nowak-Gottl U., Hempel G., Muller H.J., Lumkemann K., Schrappe M., Rath B., Fleischhack G., Mann G., Boos J., Pharmacokinetic dose adjustment of Erwiniaasparaginase in protocol II of the paediatric ALL/NHL-BFM treatment protocols, British Journal of Haematology, 104, 2, pp. 313-320, (2015); Wang L., Guo Q., Liu J.G., Measuring node importance based on weighted nonlinear method, Application Research of Computers, 35, 5, pp. 1426-1428, (2018); Cheng Y., Liu Q., Wang J., Wan S., Umer T., Distributed fault detection for wireless sensor networks based on support vector regression, Wireless Communications and Mobile Computing, 5, pp. 1-8, (2018); Dolha S., Negirla P., Alexa F., Silea I., Considerations about the signal level measurement in wireless sensor networks for node position estimation, Sensors, 19, 19, pp. 41-79, (2019); Liu G.Y., Tang S., Li D., Hu J., Self-adjustment of calcium phosphate coating on micro-arc oxidized magnesium and its influence on the corrosion behaviour in simulated body fluids, Corrosion Science, 79, 3, pp. 206-214, (2014); Cerny I., Veverková, Alexandra, Kovár, Marek, et al. Influence of temperature and moisture conditions of locality on the yield formation of sunflower (Helianthus annuus L.), Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, 59, 6, pp. 99-104, (2014); Barros Neto J.M., Anjos E.A., Silva S.E., Tavares C.M., Pedro A.N., The formation of the professional nurse and the labor market today, Revista Gestão& Saúde, 5, 1, pp. 176-193, (2014); Vieira Pinheiro J.P., Ahlke E., Nowak-Gottl U., Hempel G., Muller H.J., Lumkemann K., Schrappe M., Rath B., Fleischhack G., Mann G., Boos J., Pharmacokinetic dose adjustment of Erwinia asparaginase in protocol II of the paediatric ALL/NHL-BFM treatment protocols, British Journal of Haematology, 104, 2, pp. 313-320, (2015); Gavrin A., Kaiser B.N., Geiger D., Tyerman S.D., Wen Z., Bisseling T., Fedorova E.E., Adjustment of host cells for accommodation of symbiotic bacteria: Vacuole defunctionalization, HOPS suppression, and TIP1g retargeting in Medicago, Plant Cell, 26, 9, pp. 3809-3822, (2014); Guangyou Y., Chenbo X., Xiong G., Tuo Z., Energy efficient node deployment optimization for cts based on cooperative beamforming in single-hop wireless sensor networks, Automatic Control and Computer Sciences, 54, 2, pp. 147-155, (2020); Badir Y.F., O'Connor G.C., The formation of tie strength in a strategic alliance's first new product development project: The influence of project and partners' characteristics, Journal of Product Innovation Management, 32, 1, pp. 154-169, (2015)","W. Li; Tangshan Normal University, Tangshan, 063000, China; email: yuna-ada@hotmail.com",null,"Hindawi Limited",{"$nulls":5},1.5308669E7,null,null,null,"English","Wireless Commun. Mobile Comput.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85103571436"]
["Ulmer M.W.","Ulmer, Marlin W. (57147181500)",5.71471815E10,"Dynamic pricing and routing for same-day delivery",2020.0,"Transportation Science",54.0,4.0,null,1016.0,1033.0,17.0,43.0,"10.1287/TRSC.2019.0958","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85084577269&doi=10.1287%2fTRSC.2019.0958&partnerID=40&md5=5a0fe60a648345b25206a72491c569d8","Technische Universität Braunschweig, Braunschweig, 38106, Germany","Ulmer M.W., Technische Universität Braunschweig, Braunschweig, 38106, Germany","An increasing number of e-commerce retailers offers same-day delivery. To deliver the ordered goods, providers dynamically dispatch a fleet of vehicles transporting the goods from the warehouse to the customers. In many cases, retailers offer different delivery deadline options, from four-hour delivery up to next-hour delivery. Due to the deadlines, vehicles often only deliver a few orders per trip. The overall number of served orders within the delivery horizon is small and the revenue low. As a result, many companies currently struggle to conduct same-day delivery cost-efficiently. In this paper, we show how dynamic pricing is able to substantially increase both revenue and the number of customers we are able to serve the same day. To this end, we present an anticipatory pricing and routing policy (APRP) method that incentivizes customers to select delivery deadline options efficiently for the fleet to fulfill. This maintains the fleet's flexibility to serve more future orders. We model the respective pricing and routing problem as a Markov decision process (MDP). To apply APRP, the state-dependent opportunity costs per customer and option are required. To this end, we use a guided offline value function approximation (VFA) based on state space aggregation. The VFA approximates the opportunity cost for every state and delivery option with respect to the fleet's flexibility. As an offline method, APRP is able to determine suitable prices instantly when a customer orders. In an extensive computational study, we compare APRP with a policy based on fixed prices and with conventional temporal and geographical pricing policies. APRP outperforms the benchmark policies significantly, leading to both a higher revenue and more customers served the same day. © 2020 INFORMS","Dynamic pricing; Dynamic vehicle routing; Opportunity cost; Same-day delivery; Stochastic requests; Value function approximation","Economics; Fleet operations; Markov processes; Sales; Computational studies; Delivery deadlines; Fleet of vehicles; Markov Decision Processes; Opportunity costs; Routing problems; State dependent opportunity costs; Value function approximation; Costs",{"$nulls":4},"Martin Savelsbergh","There are several colleagues that helped tremendously with this work. The author especially thanks Warren Powell for his great support with the modeling of the problem. The author appreciates Warren's effort to bring clarity to the dynamic routing literature, and the author highly recommends studying his framework to everyone working in this field. The author also thanks Sebastian Koch for his valuable advice on revenue management and Ninja Soeffker for her helpful remarks in the preparation of this paper. Finally, the author would like to thank Martin Savelsbergh, the associate editor, and the referees for their very valuable support and constructive suggestions.","Adelman D, Dynamic bid prices in revenue management, Oper. Res, 55, 4, pp. 647-661, (2007); Agatz N, Campbell AM, Fleischmann M, Savelsbergh MWP, Time slot management in attended home delivery, Transportation Sci, 45, 3, pp. 435-449, (2011); Agatz N, Campbell AM, Fleischmann M, van Nunen J, Savelsbergh MWP, Revenue management opportunities for Internet retailers, J. Revenue Pricing Management, 12, 2, pp. 128-138, (2013); Anderson M, Amazon is offering a key benefit of traditional brick-and-mortar stores, Business Insider, (2015); Archetti C, Savelsbergh MWP, Speranza MG, The vehicle routing problem with occasional drivers, Eur. J. Oper. Res, 254, 2, pp. 472-480, (2016); Asdemir K, Jacob VS, Krishnan R, Dynamic pricing of multiple home delivery options, Eur. J. Oper. Res, 196, 1, pp. 246-257, (2009); Azi N, Gendreau M, Potvin J-Y, A dynamic vehicle routing problem with multiple delivery routes, Ann. Oper. Res, 199, 1, pp. 103-112, (2012); Birger N, Welt, (2016); Borenstein S, Dynamic pricing in retail gasoline markets, Rand J. Econom, 27, 3, pp. 429-451, (1996); Dong L, Kouvelis P, Tian Z, Dynamic pricing and inventory control of substitute products, Manufacturing Service Oper. Management, 11, 2, pp. 317-339, (2009); Do today's on-demand consumers want same-day delivery?, (2015); Figliozzi MA, Mahmassani HS, Jaillet P, Pricing in dynamic vehicle routing problems, Transportation Sci, 41, 3, pp. 302-318, (2007); Fuest B, Maass S, Zimmermann M, So funktioniert das neue Ein-Stunden-Amazon, Welt, (2016); Gawor T, Hoberg K, Customers' valuation of time and convenience in e-fulfillment, Internat. J. Phys. Distribution Logist. Management, 49, 1, pp. 75-98, (2018); Grosch T, Same-Day-Delivery gestartet: Online-Marktplatz LocaFox ermöglicht Lieferung am selben Tag in Berlin, (2016); McFadden D, Computing willingness-to-pay in random utility models, Trade, Theory and Econometrics, (1999); Powell WB, Approximate Dynamic Programming: Solving the Curses of Dimensionality, (2011); Punakivi M, Saranen J, Identifying the success factors in e-grocery home delivery, Internat. J. Retail Distribution Management, 29, 4, pp. 156-163, (2001); Ram A, UK retailers face high cost of online deliveries, (2015); Silver H, How important is same-day delivery to shoppers?, (2015); Soeffker N, Ulmer MW, Mattfeld DC, Problem-specific state space partitioning for dynamic vehicle routing problems, Proceedings of MKWI, pp. 229-240, (2016); Stevenson R, Black T, Amazon spurs delivery startups with shot at $300,000 profit, Bloomberg, (2018); Topaloglu H, Powell W, Incorporating pricing decisions into the stochastic dynamic fleet management problem, Transportation Sci, 41, 3, pp. 281-301, (2007); Ulmer MW, Delivery deadlines for same-day delivery, Logist. Res, 10, 1, (2017); Ulmer MW, Thomas BW, Meso-parametric value function approximation for dynamic customer acceptances in delivery routing, Eur. J. Oper. Res, (2019); Ulmer MW, Mattfeld DC, Koster F, Budgeting time for dynamic vehicle routing with stochastic customer requests, Transportation Sci, 52, 1, pp. 20-37, (2018); Ulmer MW, Thomas BW, Mattfeld DC, Preemptive depot returns for same-day delivery, EURO J. Transportation Logistics, 8, 4, pp. 327-361, (2019); Ulmer MW, Goodson JC, Mattfeld DC, Hennig M, Offline-online approximate dynamic programming for dynamic vehicle routing with stochastic requests, Transportation Sci, 53, 1, pp. 185-202, (2019); Vulcano G, Van Ryzin G, Ratliff R, Estimating primary demand for substitutable products from sales transaction data, Oper. Res, 60, 2, pp. 313-334, (2012); Increased value-added services expected to boost the same-day delivery market in the US, says Technavio, (2016); Yang X, Strauss AK, An approximate dynamic programming approach to attended home delivery management, Eur. J. Oper. Res, 263, 3, pp. 935-945, (2017); Yang X, Strauss AK, Currie CSM, Eglese R, Choice-based demand management and vehicle routing in e-fulfillment, Transportation Sci, 50, 2, pp. 473-488, (2014); You P-S, Dynamic pricing in airline seat management for flights with multiple flight legs, Transportation Sci, 33, 2, pp. 192-206, (1999)","M.W. Ulmer; Technische Universität Braunschweig, Braunschweig, 38106, Germany; email: m.ulmer@tu-braunschweig.de",null,"INFORMS Inst.for Operations Res.and the Management Sciences",{"$nulls":5},411655.0,null,"TRSCB",null,"English","Transp Sci","Article","Final",null,"Scopus","2-s2.0-85084577269"]
["Zhu X.; Pasch T.J.; Bergstrom A.","Zhu, Xun (57190868366); Pasch, Timothy J. (57202794491); Bergstrom, Aaron (56869103800)","57190868366; 57202794491; 56869103800","Understanding the structure of risk belief systems concerning drone delivery: A network analysis",2020.0,"Technology in Society",62.0,null,101262.0,null,null,null,20.0,"10.1016/j.techsoc.2020.101262","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85083877036&doi=10.1016%2fj.techsoc.2020.101262&partnerID=40&md5=4303a1f0e85f98e1f854c834bb348b55","Department of Communication, College of Arts & Sciences, University of North Dakota, United States; Division of Research & Economic Development, University of North Dakota, United States","Zhu X., Department of Communication, College of Arts & Sciences, University of North Dakota, United States; Pasch T.J., Department of Communication, College of Arts & Sciences, University of North Dakota, United States; Bergstrom A., Division of Research & Economic Development, University of North Dakota, United States","While e-commerce industries envision drones as a promising solution to the challenges associated with last-mile logistics of product delivery, there is increasing public concern over the risks of these airborne innovations. A growing number of studies seek to gauge the public's risk beliefs about drone delivery and inform policy development before its widespread uptake. Complicating these efforts is the fact that beliefs are interconnected and embedded in a cognitive system. This article argues that public outcomes are not based on atomized and isolated beliefs about risks involved in drone delivery, but instead emerge from the patterns in the relationships among these expressed beliefs. However, little is known about the structural characteristics of risk belief systems related to drone delivery, and the implications for risk communication and management. In an effort to fill this void, we conducted a network analysis of risk beliefs about drone delivery based on nationally representative data (N = 1465). The results revealed structural connections among 11 risk beliefs and explored structural variations in the risk belief system between people with different attitudes toward drone delivery. The simulation results showed that risk-mitigating messages instigated greater changes to the public's risk perceptions when they targeted structurally central, as opposed to peripheral, risk beliefs. The reported evidence adds new insights into how risks about drone delivery are configured in the public consciousness, and provides guidance into how practitioners may mobilize structural leverage to optimize the effectiveness and efficiency of risk communication strategies. © 2020","Belief system; Drones; Network analysis; Risk communication; Risk perceptions","Cognitive systems; Drones; Public risks; Risk assessment; Risk perception; Effectiveness and efficiencies; Policy development; Product delivery; Risk communication; Risk mitigating; Structural characteristics; Structural connections; Structural variations; electronic commerce; innovation; logistics; network analysis; risk perception; unmanned vehicle; Risk analysis",{"$nulls":6},"Federal Aviation Administration, Unmanned Aerial Systems, (2018); Amazon Unveils Futuristic Plan: Delivery by Drone, (2013); Joerss M., Schroder J., Neuhaus F., Klink C., Mann F., Parel Delivery: the Future of Last Mile, (2016); Clothier R.A., Greer D.A., Greer D.G., Mehta A.M., Risk perception and the public acceptance of drones: risk perception and the public acceptance of drones, Risk Anal., 35, pp. 1167-1183, (2015); Soffronoff J., Piscioneri P., Weaver A., Public Perception of Drone Delivery in the United States (RARC-WP-17-001), (2016); Zhu X., Segmenting the public's risk beliefs about drone delivery: a belief system approach, Telematics Inf., 40, pp. 27-40, (2019); Yoo W., Yu E., Jung J., Drone delivery: factors affecting the public's attitude and intention to adopt, Telematics Inf., 35, pp. 1687-1700, (2018); West J.P., Klofstad C.A., Uscinski J.E., Connolly J.M., Citizen support for domestic drone use and regulation, Am. 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["Hribernik M.; Zero K.; Kummer S.; Herold D.M.","Hribernik, Marko (57220816497); Zero, Kathrin (57220814639); Kummer, Sebastian (36731180700); Herold, David M. (56521172600)","57220816497; 57220814639; 36731180700; 56521172600","City logistics: Towards a blockchain decision framework for collaborative parcel deliveries in micro-hubs",2020.0,"Transportation Research Interdisciplinary Perspectives",8.0,null,100274.0,null,null,null,39.0,"10.1016/j.trip.2020.100274","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85097681154&doi=10.1016%2fj.trip.2020.100274&partnerID=40&md5=80bab759641f224e57b435b391027b18","Institute for Transport and Logistics Management, Vienna University of Economics and Business, Welthandelsplatz 1, Vienna, 1020, Austria; gredata IT-Solutions EU, Pramergasse 25/13, Wien, 1090, Austria; Department of Logistics, School of Management, Jilin University, No. 5988 Renmin Street, Changchun, Jilin Province, China; Department of Business, Strategy and Innovation, Griffith University, Gold Coast Campus, Southport, 4215, QLD, Australia","Hribernik M., Institute for Transport and Logistics Management, Vienna University of Economics and Business, Welthandelsplatz 1, Vienna, 1020, Austria, gredata IT-Solutions EU, Pramergasse 25/13, Wien, 1090, Austria; Zero K., gredata IT-Solutions EU, Pramergasse 25/13, Wien, 1090, Austria; Kummer S., Institute for Transport and Logistics Management, Vienna University of Economics and Business, Welthandelsplatz 1, Vienna, 1020, Austria, Department of Logistics, School of Management, Jilin University, No. 5988 Renmin Street, Changchun, Jilin Province, China; Herold D.M., Institute for Transport and Logistics Management, Vienna University of Economics and Business, Welthandelsplatz 1, Vienna, 1020, Austria, Department of Business, Strategy and Innovation, Griffith University, Gold Coast Campus, Southport, 4215, QLD, Australia","The growth in e-commerce has led to increased pressure within the courier, express and parcel (CEP) sector to tackle the ‘last-mile’ issue and come up with solutions that not only satisfy the customers, but also other stakeholders such as city councils and other regulatory bodies. Scholars have highlighted micro-hubs and the associated horizontal collaboration as a possible solution, which might help alleviate problems associated with last-mile logistics in inner-city centers. However, trust and data exchange issues are considerable barriers to the introduction of horizontal collaboration, in particular between CEP carriers. To address the lack of trust and the issue of data exchange between carriers, the use of blockchain technology may present a solution, but existing research so far is limited concerning frameworks that specifically discuss blockchain technology in the context of micro-hubs and last-mile deliveries. In response, this paper presents a blockchain decision framework for a horizontal collaboration between CEP carriers based on key characteristics of existing blockchain decision models and relevant related research in the area of logistics and last-mile distribution. This is the first study that specifically addresses the use of blockchain technology for horizontal collaboration in the context of micro-hubs and last-mile deliveries. © 2020 The Author(s)","Blockchain; Horizontal collaboration; Last-mile; Logistics; Micro-hubs",{"$nulls":5},"Österreichische Forschungsförderungsgesellschaft, FFG","This study is part of the research project “KoopHubs” funded by the Austrian Research Promotion Agency (Österreichische Forschungsförderungsgesellschaft/FFG). ","Allen J., Bektas T., Cherrett T., Friday A., McLeod F., Piecyk M., Et al., Enabling a freight traffic controller for collaborative multidrop urban logistics: practical and theoretical challenges, Transp. Res. 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["Alkan Ö.; Küçükoğlu H.; Tutar G.","Alkan, Ömer (55759376500); Küçükoğlu, Hasan (57221845659); Tutar, Gökhan (57221841035)","55759376500; 57221845659; 57221841035","Modeling of the Factors Affecting e-Commerce Use in Turkey by Categorical Data Analysis",2021.0,"International Journal of Advanced Computer Science and Applications",12.0,1.0,null,95.0,105.0,10.0,7.0,"10.14569/IJACSA.2021.0120113","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85100433076&doi=10.14569%2fIJACSA.2021.0120113&partnerID=40&md5=255540ce4f96e4e61ee0ed9ebd5e069f","Department of Econometrics, Ataturk University, Erzurum, Turkey; Department of Management Information Systems, Ataturk University, Erzurum, Turkey","Alkan Ö., Department of Econometrics, Ataturk University, Erzurum, Turkey; Küçükoğlu H., Department of Management Information Systems, Ataturk University, Erzurum, Turkey; Tutar G., Department of Management Information Systems, Ataturk University, Erzurum, Turkey","e-Commerce use is a subject of study that has been frequently discussed in recent years. The aim of this study was to detect the socio-demographic and economic factors affecting ecommerce use of individuals in Turkey. The micro dataset obtained from Information and Communication Technology (ICT) Usage Survey in Households performed by the Turkish Statistical Institute in 2014-2018 was employed in this study. Multinomial logistic and multinomial probit regression analyses were performed to detect the factors affecting e-commerce use of individuals in Turkey. The data of 129,643 individuals, who participated in ICT Usage Survey in Households in 2014-2018, were employed in the regression analyses. According to the analysis results, the variables of survey year, age, gender, educational level, occupation, income level, region and household size were detected to be effective on online shopping. The results of the study indicated that e-commerce use was gradually increasing. It was determined that more educated and young individuals and individuals living in relatively more developed regions were more inclined to online shopping. Policies should also be developed to increase e-commerce use of low educated individuals and individuals over middle age. In particular, small and medium-sized businesses (SMB) should pay more attention to the use of e-commerce in order to increase their activities by taking these situations into consideration. Indeed, how important e-commerce use is has been found out in epidemics/pandemics such as COVID-19, which causes people to lock themselves at home in the countries. © 2021. All rights reserved.","e-commerce; Electronic commerce; multinomial probit regression; online purchase; online shopping; Turkey","Electronic commerce; Factor analysis; Surveys; Categorical data; E- commerces; Information and Communication Technologies; Multinomial probit; Multinomial probit regression; Online shopping; Socio-demographic factors; Socio-economic factor; Technology usages; Turkey; Regression analysis",{"$nulls":4},"Turkish Statistical Institute","The authors would like to thank the Turkish Statistical Institute for the data. The views and opinions expressed in this manuscript are those of the authors only and do not necessarily represent the views, official policy, or position of the Turkish Statistical Institute.","Barnes S. J., Vidgen R. T., An integrative approach to the assessment of e-commerce quality, Journal of Electronic Commerce Research, 3, 3, pp. 114-127, (2002); Corbitt B. 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F., Hsueh-Shan C., Shopping-centre attributes affecting male shopping behaviour, Journal of Retail & Leisure Property, 4, 4, pp. 324-340, (2005); Stranahan H., Kosiel D., E‐tail spending patterns and the importance of online store familiarity, Internet research, 17, 4, pp. 421-434, (2007); Koyuncu C., Lien D., E-commerce and consumer' s purchasing behaviour, Applied Economics, 35, 6, pp. 721-726, (2003); Leong L.-Y., Jaafar N. I., Ainin S., Understanding facebook commerce (F-commerce) actual purchase from an artificial neural network perspective, Journal of Electronic Commerce Research, 19, 1, pp. 75-103, (2018); Bellman S., Lohse G. L., Johnson E. J., Predictors of online buying behavior, association for computing machinery, Communications of the ACM, 42, 12, pp. 32-38, (1999); Palvia P., The role of trust in e-commerce relational exchange: A unified model, Information & management, 46, 4, pp. 213-220, (2009); Aghdaie S. F. A., Piraman A., Fathi S., An analysis of factors affecting the consumer' s attitude of trust and their impact on internet purchasing behavior, International Journal of Business and Social Science, 2, 23, (2011); Fernandez A. M. G., Los valores personales en el comportamiento del consumidor: Revisión de diversas metodologías aplicadas al marketing, Esic Market, 107, pp. 9-36, (2000); Vicente M., Determinants of C2C e-commerce: an empirical analysis of the use of online auction websites among Europeans, Applied Economics Letters, 22, 12, pp. 978-981, (2015); Burkolter D., Kluge A., Online consumer behavior and its relationship with socio-demographics, shopping orientations, need for emotion, and fashion leadership, Journal of Business and Media Psychology, 2, 2, pp. 20-28, (2011); Cristobal-Fransi E., Martin-Fuentes E., Daries-Ramon N., Behavioural analysis of subjects interacting with information technology: categorising the behaviour of e-consumers, International Journal of Services Technology and Management, 21, 1-3, pp. 163-182, (2015); Akhter S. H., Digital divide and purchase intention: Why demographic psychology matters, Journal of Economic Psychology, 24, 3, pp. 321-327, (2003); Kumar V., Dange U., A study of factors affecting online buying behavior: A conceptual model, SSRN Electronic Journal, (2012); Rohm A. J., Swaminathan V., A typology of online shoppers based on shopping motivations, Journal of business research, 57, 7, pp. 748-757, (2004)",null,null,"Science and Information Organization",{"$nulls":5},"2158107X",null,null,null,"English","Intl. J. Adv.  Comput. Sci. Appl.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85100433076"]
["Hao N.; Wang H.H.; Zhou Q.","Hao, Na (56548380800); Wang, H. Holly (7501735135); Zhou, Qingjie (57204761790)","56548380800; 7501735135; 57204761790","The impact of online grocery shopping on stockpile behavior in Covid-19",2020.0,"China Agricultural Economic Review",12.0,3.0,null,459.0,470.0,11.0,89.0,"10.1108/CAER-04-2020-0064","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85089296982&doi=10.1108%2fCAER-04-2020-0064&partnerID=40&md5=94afdf63b99516528274f1cb7f32f2ed","School of Economics, Beijing Technology and Business University, Beijing, China; Department of Agricultural Economics, Purdue University, West Lafayette, IN, United States; Zhejiang University, Hangzhou, China","Hao N., School of Economics, Beijing Technology and Business University, Beijing, China; Wang H.H., Department of Agricultural Economics, Purdue University, West Lafayette, IN, United States, Zhejiang University, Hangzhou, China; Zhou Q., School of Economics, Beijing Technology and Business University, Beijing, China","Purpose: This research is to examine the impact of online channels on food stockpile behavior. Design/methodology/approach: In this study, we use bivariate probit models to empirically investigate the impact of online purchasing channels on Chinese urban consumer food hoarding behaviors with random survey samples. Findings: Results show that fresh food e-commerce channels are more likely to be associated with panic stockpile behaviors due to higher likelihood of supply shortages than offline channels with government assistance in logistic management. In contrast, community group buy, another format of e-commerce, appears superior in satisfying the consumer needs and easing the panic buying perception. Practical implications: It suggests that online channels may have diverse impacts on consumers' panic stockpiling behaviors during the extreme situations. Online channels need to develop efficient supply chains to be more resilient to extreme situations and the government shall recognize the increasing share of the online channels together with traditional offline channels when implementing supporting policies. Social implications: With ever increasing share of online channels, it is imperative in terms of policy implications to understand how would online channels affect hoarding behavior. Originality/value: We are the first study in online shopping's impact on food stockpile during pandemics using a random sample. Although food stockpile behavior at times of emergency have been investigated in many literature, there are no empirical studies on the impact of online channels on stockpile behaviors under extreme situations. Unlike disasters that immediately impact every entity in supply chains covering producers, vendors, distribution centers and retailers, pandemics did not render supply chains affected immediately, but rather increase consumers' willingness to shop online to avoid virus. Thus, Covid-19 provides a natural experiment to investigate the online channels' impact on stockpile behavior. © 2020, Emerald Publishing Limited.","Community group buy; Fresh food e-commerce; Pandemics; Stockpile",{"$nulls":5},"2017 Beijing high level group building program, (IDHT20170505); Beijing Municipal Commission of Education, (SM201810011002); Beijing Technology and Business University, BTBU, (PXM2018_014213_000033)","The authors thank Beijing Municipal Education Commission Social Science Funding, SM201810011002; Beijing Technology and Business University Young talent research funding, PXM2018_014213_000033; and 2017 Beijing high level group building program, IDHT20170505. ","Abe N., Moriguchi N., Inakura N., The Effects of Natural Disasters on Prices and Purchasing Behaviors: The Case of the Great East Japan Earthquake, (2014); Chen T., Community group buy – the next billion dollar e-commerce industry, Walkthechat, (2019); Guo H., Liu X., Kevin C., How to Battle against Pandemics Using E-Commerce Platforms, (2020); Ho J., Poh F., Zhou J., Zipser D., Chinese Consumer Survey Report 2020: The Diversity Faces of Chinese Consumers, (2019); Hori M., Iwamoto K., The run on daily foods and goods after the 2011 Tohoku earthquake, The Japanese Political Economy, 40, 1, pp. 69-113, (2014); Kabango C.M., Asa A.R., Factors influencing E-commerce development: implications for the developing countries, International Journal of Innovation and Economic Development, 1, 1, pp. 59-66, (2015); Lufkin B., Amid the Coronavirus Outbreak, People Are Flocking to Supermarkets Worldwide – but Are They Simply Preparing, or Irrationally Panicking? BBC Worklife, (2020); Stabilizing vegetable baskets supply in multiple areas and piloting pre-order facemask, (2020); Segerstrom S.C., Taylor S.E., Kemeny M.E., Fahey J.L., Optimism is associated with mood, coping, and immune change in response to stress, Journal of Perspective Social Psychology, 74, 10, pp. 1646-1655, (1998); Sheng J., An 167% Sale Increase on Shanghai Fresh Food E-Commerce Platforms, (2020); Shi R., How Covid-19 is changing grocery shopping in China. China, Mintel Blog, (2020); Yao J., Thoughts on e-commerce development under the pandemic, Sina Finance and Economics, (2020); Zheng Q., Chen J., Zhang R., Wang H.H., What factors affect Chinese consumers' online grocery shopping? Product attributes, e-vendor characteristics and consumer perceptions, China Agricultural Economic Review, 12, 2, pp. 193-213, (2020)","N. Hao; School of Economics, Beijing Technology and Business University, Beijing, China; email: nahao_7@163.com",null,"Emerald Group Holdings Ltd.",{"$nulls":5},"1756137X",null,null,null,"English","China Agric. Econ. Rev.","Article","Final",null,"Scopus","2-s2.0-85089296982"]
["Han C.; Pervez A.; Wu J.; Shen X.; Zhang D.","Han, Chunyang (57801209200); Pervez, Amjad (57203571001); Wu, Jingqiong (57850172700); Shen, Xiaojing (57207243292); Zhang, Dezhi (55321180100)","57801209200; 57203571001; 57850172700; 57207243292; 55321180100","Home-delivery-oriented agri-food supply chain alliance: Framework, management strategies, and cooperation stability control",2020.0,"Sustainability (Switzerland)",12.0,16.0,6547.0,null,null,null,9.0,"10.3390/su12166547","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85089981078&doi=10.3390%2fsu12166547&partnerID=40&md5=b707581cd7c80d92e4f3dddf7126bfbf","School of Traffic and Transportation Engineering, Central South University, Changsha, 410075, China; Faculty of Transportation Engineering, Kunming University of Science and Technology, Kunming, 650500, China; School of Logistics Management and Engineering, Nanning Normal University, Nanning, 530001, China","Han C., School of Traffic and Transportation Engineering, Central South University, Changsha, 410075, China; Pervez A., School of Traffic and Transportation Engineering, Central South University, Changsha, 410075, China; Wu J., Faculty of Transportation Engineering, Kunming University of Science and Technology, Kunming, 650500, China; Shen X., School of Logistics Management and Engineering, Nanning Normal University, Nanning, 530001, China; Zhang D., School of Traffic and Transportation Engineering, Central South University, Changsha, 410075, China","The high cost of operation and severe competition in the agri-food e-commerce market make it hard for the small and medium agri-food enterprises (A-SMEs) to operate cost-efficiently and in a sustainable manner. This paper seeks to organize A-SMEs to develop a cooperative organization via collaborative strategies and alliance structures, named as the home-delivery-oriented agri-food supply chain (HASC) alliance, to form a substantive relationship to gain a stable foothold in the emerging e-commerce market. A theoretical framework of the HASC alliance is built with its organizational structure and schematics of the process of implementation strategies that cover the aspects of last-mile chain extension, food transportation, and production/distribution control. Furthermore, a three-step analytical method is proposed to analyze the performance of the alliance with the aim to provide appropriate strategies to hedge against the potential risks of cooperation instability. A hypothetical case is conducted, and the results show that: (1) the performance of the hypothetical HASC alliance with time shows significant variation in the beginning, but it gains stability with the application of stability control strategies; (2) the cooperation stability of HASC alliance is very sensitive to the performance of the strategies that control the customer and environment variations; (3) the factors of trust and market fluctuation have higher effects on membership and environmental stability, respectively; (4) the minimum and maximum cost ranges of control strategies at which the alliance can maintain its stability and performance are 5% and 29%, respectively, of the total operation cost. © 2020 by the authors.","Agri-food e-commerce; Cooperation stability control; Hybrid push-pull strategy; Multi-temperature joint distribution (MTJD); Strategic alliance; Supply chain extension","agricultural cooperative; conceptual framework; control system; electronic commerce; food market; food supply; management practice; organizational framework; policy implementation; sustainability; sustainable development",{"$nulls":6},{"$cut":{"chars":23788,"head":"Agatz N., Campbell A., Savelsbergh M., Savelsbergh M., Time slot management in attended home delivery, Transp. Sci, 45, pp. 435-449, (2008); Duin J.H., Goffau W.D., Wiegmans B., Tavasszy L.A., Saes M., Improving home delivery efficiency by using principles of address intelligence for b2c deliveries, Transp. Res. Procedia, 12, pp. 14-25, (2016); Riccardo M., Gino M., Sara P., Angela T., A review of the environmental implications of B2C e-commerce: A logistics perspective, Int. J. Phys. Distrib. Logist. Manag, 45, pp. 565-591, (2015); Patricia J.D., Cornelia D., Organizational structure in divisional manufacturers: The potential for outsourcing logistical services, Int. J. Phys. Distrib. Logist. Manag, 21, pp. 22-29, (1997); Rotem-Mindali O., Weltevreden J.W., Transport effects of e-commerce: What can be learned after years of research, Transportation, 40, pp. 867-885, (2013); Lu Q., Meng F.W., Goh M., Choice of supply chain governance: Self-managing or outsourcing, Int. J. Prod. Econ, 154, pp. 32-38, (2014); Dean E., Yunus K., The effects of global outsourcing strategies on participants' attitudes and organizational effectiveness, Int. J. Manpow, 21, pp. 112-128, (2000); Kremic T., Oya I.T.L., Walter O., Outsourcing decision support: A survey of benefits, risks, and decision factors, Supply Chain Manag. Int. J, 11, pp. 467-482, (2006); Gandhi S.J., Gorod A., Sauser B., Prioritization of outsourcing risks from a systemic perspective, Strateg. Outsourc, 5, pp. 39-71, (2012); Shahani R., Good outsourcing requires good governance, Supply Chain Manag. Rev, 11, pp. 15-16, (2007); Das T.K., Teng B.S., Trust, control, and risk in strategic alliances: An integrated framework, Organ. Stud, 22, pp. 251-283, (2001); Christoffersen J., Plenborg T., Robson M.J., Measures of strategic alliance performance classified and assessed, Int. Bus. Rev, 23, pp. 479-489, (2014); Gomes E., Barnes B.R., Mahmood T., A 22-year review of strategic alliance research in the leading management journals, Int. Bus. Rev, 25, pp. 15-27, (2014); Albers S., Wohlgezogen F., Zajac E.J., Strategic alliance structures: An organization design perspective, J. Manag, 42, pp. 582-614, (2016); Angelo C., Evi H., Matthias S.F., Intra-industry strategic alliances for managing sustainability-related supplier risks: Motivation and outcome, Int. J. Phys. Distrib. Logist. Manag, 47, pp. 387-409, (2017); Kim D., John S., Eric D., An organization-level framework for the NZ food industry-Its development and application, Int. J. Phys. Distrib. Logist. Manag, 35, pp. 728-743, (2005); Zhang J., Frazier G.V., Strategic alliance via co-opetition: Supply chain partnership with a competitor, Decis. Support Syst, 51, pp. 853-863, (2011); Lo V.H.Y., Yeung A.H.W., Practical framework for strategic alliance in pearl river delta manufacturing supply chain: A total quality approach, Int. J. Prod. Econ, 87, pp. 231-240, (2004); Mellat-Parast M., Digman L.A., A framework for quality management practices in strategic alliances, Manag. Decis, 45, pp. 802-818, (2007); Sambasivan M., Siew L., Mohamed Z.A., Leong Y.C., Factors influencing strategic alliance outcomes in a manufacturing supply chain: Role of alliance motives, interdependence, asset specificity and relational capital, Int. J. Phys. Distrib. Logist. Manag, 141, pp. 339-351, (2013); Sambasivan M., Siew L., Mohamed Z.A., Leong Y.C., Impact of interdependence between supply chain partners on strategic alliance outcomes, Manag. Decis, 54, pp. 548-569, (2011); Fynes B., Burca S., Mangan J., The effect of relationship characteristics on relationship quality and performance, Int. J. Prod. Econ, 111, pp. 56-69, (2008); Patel T., The role of dynamic cultural theories in explaining the viability of international strategic alliances: A focus on Indo-French alliances, Manag. Rev, 45, pp. 1532-1559, (2007); Sambasivan M., Nget Y.C., Strategic alliances in a manufacturing supply chain: Influence of organizational culture from the manufacturer's perspective, Int. J. Phys. Distrib. Logist. Manag, 40, pp. 456-474, (2010); China Fresh E-Commerce Report"}},"A. Pervez; School of Traffic and Transportation Engineering, Central South University, Changsha, 410075, China; email: amjadpervez04@csu.edu.cn",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85089981078"]
["Feng X.","Feng, Xuan (57224222820)",5.722422282E10,"Economic and ecological optimization of the london urban logistics system considering infection risk during pandemic periods",2021.0,"International Journal of Supply and Operations Management",8.0,2.0,null,114.0,133.0,19.0,2.0,"10.22034/IJSOM.2021.2.2","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85107276009&doi=10.22034%2fIJSOM.2021.2.2&partnerID=40&md5=9757f99344403c9194556f582e1fe2f5","School of Strategy and Leadership, Coventry University, Coventry, United Kingdom","Feng X., School of Strategy and Leadership, Coventry University, Coventry, United Kingdom","Urban delivery, especially the last-mile delivery, has become an increasingly important area in the global supply chain along with the boom of e-commerce. Delivery companies and merchants can introduce some innovative solutions such as the equipment of autonomous vehicles (AVs) to decrease their operating costs, environmental impact, and social risks during the delivery process. This paper mainly develops a mathematical model to get the best allocation of AVs among city logistics centers (CLCs) as a mixed delivery method. The advantage of the presented model stems from considering the equipment cost, the delivery cost, and the CO2 emission, which is measured through social carbon cost (SCC). In addition, this paper establishes a risk model considering the impact of seasonal variations to evaluate the infection risk of delivery during pandemic periods for four potential delivery scenarios: customers going to CLCs, ordering online and picking-up at CLCs, delivering by traditional vehicles (TVs), and delivering by the mixed method with the optimal allocation of AVs. The research finds the optimal allocation for a London case, reveals the relationship between the nominal service capacity (NCpa) of CLCs and the optimal number of CLCs equipped with AVs, concludes that the more CLCs are equipped with AVs, the fewer CO2 emissions and the fewer citizens will be infected, and provides some managerial insights that may help delivery companies and merchants make appropriate decisions about the allocation of AVs. © 2021 Kharazmi University. All rights reserved.","CO2 emission; Cost optimization; Infection risk; Net Present value; Urban logistics",{"$nulls":7},"Abbasi M., Nilsson F., Developing environmentally sustainable logistics: Exploring themes and challenges from a logistics service providers' perspective, Transportation Research Part D: Transport and Environment, 46, pp. 273-283, (2016); Akeb H., Moncef B., Durand B., Building a collaborative solution in dense urban city settings to enhance parcel delivery: An effective crowd model in Paris, Transportation Research Part E: Logistics and Transportation Review, 119, pp. 223-233, (2018); Alho A., Silva J., Sousa J., Blanco E., Improving mobility by optimizing the number, location and usage of loading/unloading bays for urban freight vehicles, Transportation Research Part D: Transport and Environment, 61, pp. 3-18, (2018); Anderhofstadt B., Spinler S., Preferences for autonomous and alternative fuel-powered heavy-duty trucks in Germany, Transportation Research Part D: Transport and Environment, 79, (2020); 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A stated choice experiment with Swiss households, Transportation Research Part D: Transport and Environment, 71, pp. 265-282, (2019); Tsao Y., Thanh V., A multi-objective mixed robust possibilistic flexible programming approach for sustainable seaport-dry port network design under an uncertain environment, Transportation Research Part E: Logistics and Transportation Review, 124, pp. 13-39, (2019); Vahidia A., Sciarretta A., Energy saving potentials of connected and automated vehicles, Transportation Research Part C: Emerging Technologies, 95, pp. 822-843, (2018); Wang S., Zhao J., Risk preference and adoption of autonomous vehicles, Transportation Research Part A: Policy and Practice, 126, pp. 215-229, (2019); Wong E., Tai A., Zhou E., Optimising truckload operations in third-party logistics: A carbon footprint perspective in volatile supply chain, Transportation Research Part D: Transport and Environment, 63, pp. 649-661, (2018); Wu W., Zhang F., Liu W., Lodewijks G., Modelling the traffic in a mixed network with autonomous-driving expressways and non-autonomous local streets, Transportation Research Part E: Logistics and Transportation Review, 134, (2020); Xia H., Yang H., Is Last-Mile Delivery a 'Killer App' for Self-Driving Vehicles?, Communications of the ACM, 61, 11, pp. 70-75, (2018); Zhu F., Ukkusuri S.V., A linear programming formulation for autonomous intersection control within a dynamic traffic assignment and connected vehicle environment, Transportation Research Part C: Emerging Technologies, 55, pp. 363-378, (2015)","X. Feng; School of Strategy and Leadership, Coventry University, Coventry, United Kingdom; email: fengxuan1995@gmail.com",null,"Kharazmi University",{"$nulls":5},2.3831359E7,null,null,null,"English","Int. J. Supply Oper. Manag.","Article","Final",null,"Scopus","2-s2.0-85107276009"]
["Fang L.; Huang C.-C.","Fang, Lijie (57670191700); Huang, Chien-Chung (8135109100)","57670191700; 8135109100","Targeted poverty alleviation in China: Evidence from Jingdong e-commerce poverty alleviation",2020.0,"Poverty and Public Policy",12.0,4.0,null,386.0,396.0,10.0,4.0,"10.1002/pop4.292","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85099536285&doi=10.1002%2fpop4.292&partnerID=40&md5=f1ad10fe0df880df7f3851ce548a33f6","Institute of Sociology, Chinese Academy of Social Sciences, Beijing, China; School of Social Work, Huamin Research Center, Rutgers University, New Brunswick, NJ, United States","Fang L., Institute of Sociology, Chinese Academy of Social Sciences, Beijing, China; Huang C.-C., School of Social Work, Huamin Research Center, Rutgers University, New Brunswick, NJ, United States","Inequalities within and between countries continue to grow as a result of globalization. Although traditional anti-poverty efforts from governments and NGOs have had their respective successes, poverty continues to exist in every country, particularly in rural areas where there are fewer resources to support socioeconomic development. Private enterprises may use their strengths, including market knowledge and accessibility to various resources, to develop innovative business models that can provide viable and effective solutions to social problems such as poverty. This article examines a case study of a poverty alleviation initiative by Jingdong (JD). The results indicate that JD utilizes industrial poverty alleviation to empower local enterprises. Through the use of education and training, finance, and employment support, JD builds an ecosystem that provides local enterprises high-quality employees and reliable logistics with which to conduct business. As a result, the JD model enables local enterprises to compensate farmers with sufficient wages that can reduce poverty and improve their well-being, creating a mutually beneficial solution for all stakeholders. The findings demonstrate the potential of a private enterprise to reduce poverty in a way that might not be otherwise independently achieved by government and NGOs. © 2021 Policy Studies Organization","capital; collective sharing; e-commerce; enterprise; innovation; Jingdong; precise poverty alleviation; targeted poverty alleviation",{"$nulls":7},"Drucker P., The temptation to do good, (1984); Drucker P., Management challenges for 21st century, (1999); Gates B., (2008); Han J., (2016); (2018); (2019); Liu Y., (2017); Lu D., Capital and capital sharing: The theme of coordinated development, (2018); Lu S., Lin Y.T., Vikse J.H., Huang C.-C., Effectiveness of social welfare programmes on poverty reduction and income inequality in China, Journal of Asian Public Policy, 6, pp. 277-291, (2013); Porter M.E., Kramer M.R., Creating shared value, Harvard Business Review, 89, 1-2, pp. 62-77, (2011); Qu T., (2018); Notice of the 13th Five-Year Plan for poverty alleviation, (2016); Verschuere B., Brandsen T., Pestoff V., Co-production: The state of the art in research and the future agenda, Voluntas, 33, pp. 1083-1101, (2012)","C.-C. Huang; School of Social Work, Huamin Research Center, Rutgers University, New Brunswick, United States; email: huangc@ssw.rutgers.edu",null,"Blackwell Publishing Ltd",{"$nulls":5},1.9442858E7,null,null,null,"English","Poverty Public Policy","Article","Final",null,"Scopus","2-s2.0-85099536285"]
["Khandpur N.; Zatz L.Y.; Bleich S.N.; Taillie L.S.; Orr J.A.; Rimm E.B.; Moran A.J.","Khandpur, Neha (36903676700); Zatz, Laura Y. (56122012500); Bleich, Sara N. (22957224900); Taillie, Lindsey Smith (56711297700); Orr, Jennifer A. (57879613100); Rimm, Eric B. (56457771800); Moran, Alyssa J. (56799914400)","36903676700; 56122012500; 22957224900; 56711297700; 57879613100; 56457771800; 56799914400","Supermarkets in cyberspace: a conceptual framework to capture the influence of online food retail environments on consumer behavior",2020.0,"International Journal of Environmental Research and Public Health",17.0,22.0,8639.0,1.0,15.0,14.0,18.0,"10.3390/ijerph17228639","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85096359797&doi=10.3390%2fijerph17228639&partnerID=40&md5=85baded24a927e74548381ea771f86e6","University of São Paulo, Av. Dr. Arnaldo, 715 Cerqueira César, São Paulo, 01246-904, SP, Brazil; Harvard T.H. Chan School of Public Health, Harvard University, 677 Huntington Ave, Boston, 02115, MA, United States; Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 135 Dauer Dr, Chapel Hill, 27599, NC, United States; University of Pennsylvania, 423 Guardian Drive, Philadelphia, 19104-6021, PA, United States; Bloomberg School of Public Health, Johns Hopkins University, Baltimore, 21218, MD, United States","Khandpur N., University of São Paulo, Av. Dr. Arnaldo, 715 Cerqueira César, São Paulo, 01246-904, SP, Brazil, Harvard T.H. Chan School of Public Health, Harvard University, 677 Huntington Ave, Boston, 02115, MA, United States; Zatz L.Y., Harvard T.H. Chan School of Public Health, Harvard University, 677 Huntington Ave, Boston, 02115, MA, United States; Bleich S.N., Harvard T.H. Chan School of Public Health, Harvard University, 677 Huntington Ave, Boston, 02115, MA, United States; Taillie L.S., Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 135 Dauer Dr, Chapel Hill, 27599, NC, United States; Orr J.A., University of Pennsylvania, 423 Guardian Drive, Philadelphia, 19104-6021, PA, United States; Rimm E.B., Harvard T.H. Chan School of Public Health, Harvard University, 677 Huntington Ave, Boston, 02115, MA, United States; Moran A.J., Bloomberg School of Public Health, Johns Hopkins University, Baltimore, 21218, MD, United States","The rapid increase in online shopping and the extension of online food purchase and delivery services to federal nutrition program participants highlight the need for a conceptual framework capturing the influence of online food retail environments on consumer behaviors. This study aims to develop such a conceptual framework. To achieve this, mixed methods were used, including: (1) a literature review and development of an initial framework; (2) key informant interviews; (3) pilot testing and refinement of the draft framework; and (4) a group discussion with experts to establish content validity. The resulting framework captures both consumer-and retailer-level influences across the entire shopping journey, as well as the broader social, community, and policy context. It identifies important factors such as consumer demographic characteristics, preferences, past behaviors, and retailer policies and practices. The framework also emphasizes the dynamic nature of personalized marketing by retailers and customizable website content, and captures equity and transparency in retailer policies and practices. The framework draws from multiple disciplines, providing a foundation for understanding the impact of online food retail on dietary behaviors. It can be utilized to inform public health interventions, retailer practices, and governmental policies for creating healthy and equitable online food retail environments. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.","Conceptual framework; Consumer behavior; Food choices; Online food retail; Online shopping; Retailer policies","Commerce; Consumer Behavior; Food; Humans; Internet; Supermarkets; conceptual framework; consumption behavior; retailing; shopping activity; supermarket; article; conceptual framework; consumer attitude; content validity; controlled study; demography; diet; human; interview; marketing; public health; public policy; shopping; commercial phenomena; food; Internet",{"$nulls":4},"Robert Wood Johnson Foundation, RWJF","Funding: This research was supported by Healthy Eating Research, a national program of the Robert Wood Johnson Foundation.","Online Grocery Shopping Report 2020: Market Stats and Delivery Trends for Ecommerce Groceries, (2020); The Digitally Engaged Food Shopper, (2017); 70% of Consumers will be Grocery Shopping Online by 2024, (2018); Online Grocery Reaches New Heights in April. 2020; Online Grocery Sales Surge 37% in April to $5.3bn, Finds Brick Meets Click, (2020); Online Grocery Shopping Statistics: Pre and Post Covid-19. 2020; Supplemental Nutrition Assistance Program Online Purchasing Pilot, (2020); For Millions of Low-Income Seniors, Coronavirus Is a Food-Security Issue. 2020; SNAP Online Purchasing to Cover 90% of Households, (2020); WIC/EWIC Pickup and Delivery Options, (2020); Glanz K., Bader M.D., Iyer S., Retail grocery store marketing strategies and obesity: An integrative review, Am. J. Prev. Med, 42, pp. 503-512, (2012); Dawson J., Retailer activity in shaping food choice, Food Qual. Pref, 28, pp. 339-347, (2013); Hand C., Riley F.D.O., Harris P., Singh J., Rettie R., Online grocery shopping: The influence of situational factors, Eur. J. Mark, 43, pp. 1205-1219, (2009); Hansen T., Consumer adoption of online grocery buying: A discriminant analysis, Int. J. Retail Distrib. Manag, 33, pp. 101-121, (2005); Cetina I., Munthiu M.-C., Radulescu V., Psychological and social factors that influence online consumer behavior, Soc. Behav. Sci, 62, pp. 184-188, (2012); Zheng Q., Chen J., Zhang R., Wang H.H., What factors affect Chinese consumers’ online grocery shopping? Product attributes, e-vendor characteristics and consumer perceptions, China Agric. Econ. Rev, 12, pp. 193-213, (2020); Inman J.J., Nikolova H., Shopper-facing retail technology: A retailer adoption decision framework incorporating shopper attitudes and privacy concerns, J. Retail, 93, pp. 7-28, (2017); Pauzi S.F.F., Thoo A.C., Tan L.C., Muharam F.M., Talib N.A., Factors influencing consumers intention for online grocery shopping—A proposed framework, IOP Conf. Ser. Mater. Sci. Eng, 215, (2017); Esbjerg L., Jensen B.B., Bech-Larsen T., de Barcellos M.D., Boztug Y., Grunert K.G., An integrative conceptual framework for analyzing customer satisfaction with shopping trip experiences in grocery retailing, J. Retail. Cons. Serv, 19, pp. 445-456, (2012); Darley W.K., Blankson C., Luethge D.J., Toward an integrated framework for online consumer behavior and decision-making process. A review, Psychol. Mark, 27, pp. 94-116, (2010); Nguyen D.H., de Leeuw S., Dullaert W.E., Consumer behaviour and order fulfilment in online retailing: A systematic review, Int. J. Manag. Rev, 20, pp. 255-276, (2018); Jabareen Y., Building a conceptual framework: Philosophy, definitions, and procedure, Int. J. Qual. Methods, 8, pp. 49-62, (2009); Armstrong G., Adam S., Denize S., Kotler P., Principles of Marketing, (2014); Dominici G., From marketing mix to e-marketing mix: A literature overview and classification, Int. J. Bus. Manag, 4, pp. 17-24, (2009); Davis F.D., Perceived usefulness, perceived ease of use, and user acceptance of information technology, MIS Q, 13, pp. 319-340, (1989); Cheung C.M., Chan G.W., Limayem M., A critical review of online consumer behavior: Empirical research, J. Electron. Commerce Org, 3, pp. 1-19, (2005); Marreiros C., Ness M., A Conceptual Framework of Consumer Food Choice Behaviour, (2009); Penim J.M.C.D.S., Online Grocery Shopping: An Exploratory Study of Consumer Decision Making Processes, (2013); Kurnia S., Chien J.A.W., The Acceptance of The Online Grocery Shopping, Proceedings of the 16th Bled Electronic Commerce Conference, (2003); Glanz K., Johnson L., Yaroch A.L., Phillips M., Ayala G.X., Davis E.L., Measures of retail food store environments and sales: Review and implications for healthy eating initiatives, J. Nutr. Ed. Behav, 48, pp. 280-288, (2016); Bronfenbrenner U., The Ecology of Human Development, (1979); Choi Y.A., Structural Equation Model of the Determinants of Repeat Purchase Behaviour of Online Grocery Shoppers in the UK, (2013); Kumanyika S.K., A framework for increasing equity impact in obesity prevention, Am. J. Public Health, 109, pp. 1350-1357, (2019); USDA Online Buying Program for Snap Participants Threatens Their Privacy and Can Exacerbate Racial and Health Inequities, Says New Report, (2020); Increasing Disparities in Unhealthy Food Advertising Targeted to Hispanic and Black Youth, (2019)","N. Khandpur; University of São Paulo, São Paulo, Av. Dr. Arnaldo, 715 Cerqueira César, 01246-904, Brazil; email: neha.khandpur@usp.br; N. Khandpur; Harvard T.H. Chan School of Public Health, Harvard University, Boston, 677 Huntington Ave, 02115, United States; email: neha.khandpur@usp.br",null,"MDPI AG",{"$nulls":5},1.6617827E7,null,null,3.3233798E7,"English","Int. J. Environ. Res. Public Health","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85096359797"]
["Shi C.; Pei Y.; Li D.; Wu T.","Shi, Chunyang (57218304658); Pei, Yilei (23974792400); Li, Dandan (45161458700); Wu, Ting (57224682348)","57218304658; 23974792400; 45161458700; 57224682348","Influencing factors of catering o2o customer experience: an approach integrating big data analytics with grounded theory",2021.0,"Tehnicki Vjesnik",28.0,3.0,null,862.0,872.0,10.0,5.0,"10.17559/TV-20210124041130","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85108159371&doi=10.17559%2fTV-20210124041130&partnerID=40&md5=0f8c99b6e190e1ec7011cbb246d2f267","Institution: Management College, Beijing Union University, Postal address 97 North Fourth Ring East Road, 100101, China","Shi C., Institution: Management College, Beijing Union University, Postal address 97 North Fourth Ring East Road, 100101, China; Pei Y., Institution: Management College, Beijing Union University, Postal address 97 North Fourth Ring East Road, 100101, China; Li D., Institution: Management College, Beijing Union University, Postal address 97 North Fourth Ring East Road, 100101, China; Wu T., Institution: Management College, Beijing Union University, Postal address 97 North Fourth Ring East Road, 100101, China","In the era of digital economy, catering O2O is developing rapidly. Catering O2O (catering online to offline), namely catering takeout in the paper, means that customers place an order through online ordering platform, and delivery persons deliver the food provided by catering enterprises offline. Catering O2O conforms to the trend of the digital economy era, but exposes a variety of problems, such as lower feedback rate of the platform, lower timeliness of acceptance and handling, lower customer feedback satisfaction, and poorer customer experience. As China's leading e-commerce platform for life services, Meituan won the rating of not recommending to place an order in the report of \"2020 China E-commerce User Experience and Complaint Monitoring\". In order to improve customer experience and service satisfaction of catering O2O, this paper takes Meituan takeout as an example, integrates big data analytics and grounded theory to explore influencing factors of catering O2O customer experience. With the big data analytics method, the main influencing factors are obtained from 54250 customer reviews, and then the grounded theory method is used to conduct in-depth analysis on negative reviews, and influencing factors of O2O customer experience are verified and confirmed. The results show that the main influencing factors of catering O2O customer experience are catering food quality and delivery service quality and after-sale service quality. Catering food quality and delivery service quality have a significant impact on customer experience. Finally, from perspectives of catering O2O platforms and enterprises, the paper obtains management implications as follows: Catering O2O platforms should attach great importance on the service of contact points in distribution link, strengthen the last-mile delivery service quality, and improve the supervision and feedback mechanism; catering O2O enterprises should ensure the quality, portion and package of catering food, so as to improve customer experience and win electronic word-of-mouth and customer satisfaction. © 2021, Strojarski Facultet. All rights reserved.","Big data analytics; Customer experience; Customer reviews; Influencing factors; The grounded theory","Big data; Data Analytics; Electronic commerce; Quality of service; Sales; User experience; Customer experience; Customer feedback; Electronic word of mouths; Feedback mechanisms; Grounded theory methods; In-depth analysis; Management implications; Service satisfaction; Advanced Analytics",{"$nulls":4},"Premium Funding Project for Academic Human Resources Development in Beijing Union University, (BPHR2020CS05); Beijing Municipal Commission of Education, (SZ202111417021); Beijing Union University, BUU, (12205561107-132, JS10202006); Beijing Social Science Fund, (17GLC050)","The paper is supported by Beijing Social Science Fund (17GLC050), Premium Funding Project for Academic Human Resources Development in Beijing Union University (BPHR2020CS05), Key Projects of Scientific Research Plan of Beijing Municipal Education Commission (SZ202111417021), the Academic Research Projects of Beijing Union University (JS10202006) and Teaching Innovation Course Construction Project in Beijing Union University (12205561107-132).","Aaltojarvi I., Kontukoski M., Hopia A., Framing the local food experience: A case study of a Finnish pop-up restaurant, British Food Journal, 120, 1, pp. 133-145, (2018); Andaleeb S. 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B., Chan A., A conceptual framework of hotel experience and customer-based brand equity: some research questions and implications, International Journal of Contemporary Hospitality Management, 22, 2, (2010); Xu L. H., Xiang J. C., Yin H., Huang Z. Z., Research on the relationship between experience value and customer satisfaction of online booking in O2O mode, Consumer Economics, 31, pp. 46-50, (2015); Yao Y. G., He S. Y., Research on agricultural products cold chain logistics distribution path optimization based on traffic big data, Management Review, 31, 4, pp. 240-253, (2019); Yu B. H., Yang Y. Q., Sun J. L., Qin J., Xu Y., The Effects of Customer Offline Experience and Merchant Offline Presence on Customer Acceptance of Community 020 Ecommerce, Chinese Journal of Management, 12, 11, pp. 1658-1664, (2015); Yrjola M., Rintamakia T., Saarijarvia H., Joensuua J., Kulkarnib G., A customer value perspective to service experiences in restaurants, Journal of Retailing and Consumer Services, 51, pp. 91-101, (2019); Zhang Q., Zhao L., Research on the Influence Factors of Repeat Consumption Intention in O2O Takeaway Business Mode, Science and Technology Management Research, 34, 12, pp. 200-204, (2014); Zhao L., Lu S., Structural equation modelling of key factors influencing the development of catering 020, Finance and accounting monthly, 15, pp. 88-92, (2016)","Y. Pei; Institution: Management College, Beijing Union University, Postal address 97 North Fourth Ring East Road, 100101, China; email: peiyilei@126.com",null,"Strojarski Facultet",{"$nulls":5},1.3303651E7,null,null,null,"English","Teh. Vjesn.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85108159371"]
["Ho M.H.-W.; Chung H.F.L.; Kingshott R.; Chiu C.-C.","Ho, Mia Hsiao-Wen (56344183100); Chung, Henry F.L. (7404002296); Kingshott, Russel (23501593700); Chiu, Chun-Chen (57214931872)","56344183100; 7404002296; 23501593700; 57214931872","Customer engagement, consumption and firm performance in a multi-actor service eco-system: The moderating role of resource integration",2020.0,"Journal of Business Research",121.0,null,null,557.0,566.0,9.0,44.0,"10.1016/j.jbusres.2020.02.008","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85079542634&doi=10.1016%2fj.jbusres.2020.02.008&partnerID=40&md5=8ad3d83c0d6144790be43df8f0fcd128","National Sun Yat-Sen University, Department of Business Management, 70 Lien-Hai Road, Kaohsiung, 80424, Taiwan; School of Communication, Journalism and Marketing, College of Business, Massey University, Auckland, Private Bag 102 904, North Shore, 0745, Auckland, New Zealand; School of Marketing, Faculty of Business and Law, Curtin University, Kent Street, Bentley, Perth, 6102, WA, Australia","Ho M.H.-W., National Sun Yat-Sen University, Department of Business Management, 70 Lien-Hai Road, Kaohsiung, 80424, Taiwan; Chung H.F.L., School of Communication, Journalism and Marketing, College of Business, Massey University, Auckland, Private Bag 102 904, North Shore, 0745, Auckland, New Zealand; Kingshott R., School of Marketing, Faculty of Business and Law, Curtin University, Kent Street, Bentley, Perth, 6102, WA, Australia; Chiu C.-C., National Sun Yat-Sen University, Department of Business Management, 70 Lien-Hai Road, Kaohsiung, 80424, Taiwan","This study aims to understand how e-commerce firms can operate more effectively within the context of a multi-actor service eco-system by examining the factors contributing to their firms’ performance. Due to their multidirectional information and business exchanges through the worldwide internet cloud these firms are often characterized by network-based operations and collaborative systems. We investigate how multiple participants, namely employees, business partners, focal and fellow customers, social media communities and technology, interact with each other and how these multi-actor exchanges influence firms’ performance. Based on a total of 288 weekly data collected from a leading e-ticketing service provider from January 2013 to December 2018 in Taiwan, our empirical findings support the service-dominant logic that customer engagement across varied social media communities positively contribute to customer consumption in terms of new customer acquisition and existing customer retention, and further enhances the service firm's financial performance. Customer consumption is elevated when the firm successfully orchestrates its resource integration by providing better employee service, extending its business partnerships, and incorporating service innovation to improve its service delivery processes and customer database management. © 2020 Elsevier Inc.","Business partner collaboration; Customer engagement; Employee service; Firm performance; Network coordination; Service innovation",{"$nulls":7},"Alexander M.J., Jaakkola E., Hollebeek L.D., Zooming out: Actor engagement beyond the dyadic, Journal of Service Management, 29, 3, pp. 333-351, (2018); Arthur B.W., The nature of technology: What it is and how it evolves, (2009); Atuahene-Gima K., Market orientation and innovation, Journal of Business Research, 35, pp. 93-103, (1996); Balaji M.S., Jha S., Sengupta A.S., Krishnan B.C., Are cynical customers satisfied differently? 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Chung; School of Communication, Journalism and Marketing, College of Business, Massey University, North Shore, Auckland, Private Bag 102 904, 0745, New Zealand; email: H.Chung@massey.ac.nz",null,"Elsevier Inc.",{"$nulls":5},1482963.0,null,"JBRED",null,"English","J. Bus. Res.","Article","Final",null,"Scopus","2-s2.0-85079542634"]
["Manser Payne E.H.; Dahl A.J.; Peltier J.","Manser Payne, Elizabeth H. (57194785577); Dahl, Andrew J. (53063396700); Peltier, James (7006667934)","57194785577; 53063396700; 7006667934","Digital servitization value co-creation framework for AI services: a research agenda for digital transformation in financial service ecosystems",2021.0,"Journal of Research in Interactive Marketing",15.0,2.0,null,200.0,222.0,22.0,76.0,"10.1108/JRIM-12-2020-0252","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85100001965&doi=10.1108%2fJRIM-12-2020-0252&partnerID=40&md5=1706eb515e89655684edb622efa81a8f","Department of Marketing, University of South Dakota, Vermillion, SD, United States; Department of Marketing, College of Business and Economics, University of Wisconsin-Whitewater, Whitewater, WI, United States","Manser Payne E.H., Department of Marketing, University of South Dakota, Vermillion, SD, United States; Dahl A.J., Department of Marketing, College of Business and Economics, University of Wisconsin-Whitewater, Whitewater, WI, United States; Peltier J., Department of Marketing, College of Business and Economics, University of Wisconsin-Whitewater, Whitewater, WI, United States","Purpose: Innovative firms have rapidly developed artificial intelligence (AI) capabilities into their service ecosystems, essentially changing perceptions of what is service quality and service delivery in their respective industries. Nonetheless, the issues surrounding AI services remain relatively unknown. The purpose for this paper is to offer a digital servitization framework for understanding how AI services impact value perceptions, consumer engagement and firm performance measures. The authors use the financial service ecosystem to explore this topic. Design/methodology/approach: The authors explore relevant literature on digital servitization, service-dominant logic and AI/disruptive innovation. Next, a conceptual framework, organized by AI-Service Exchange Antecedents, Context of AI Usage and Digital Servitization Consequences, is developed. The authors conceptualize consequences for consumers and firms. Findings: The main findings suggest that the linkages between consumers, financial institutions and fintech companies with AI usage in a service ecosystem should be identified; how value is created among multiple SD Logic-AI network actors should be analyzed; and the effects of AI-consumer interactions (lower-level and higher levels of engagement) on firm performance measures should be explored. Research limitations/implications: The conceptual framework identifies gaps in the literature and suggests research questions for future studies. Practical implications: This paper may assist practitioners with the development of AI-enabled banking activities that involve direct consumer engagement. Originality/value: To the authors’ best knowledge, this research agenda is the first comprehensive framework for understanding value co-creation in the context of AI in financial services, linking antecedents, usage and consequences. © 2021, Emerald Publishing Limited.","Blogs; Consumer behaviour internet; Customer value; Digitalizations; e-commerce; Eservice quality; Financial services; Information technology; Online consumer behavior; Service quality; Services marketing",{"$nulls":7},{"$cut":{"chars":21709,"head":"Adapa S., Fazal-e-Hasan S.M., Makam S.B., Azeem M.M., Mortimer G., Examining the antecedents and consequences of perceived shopping value through smart retail technology, Journal of Retailing and Consumer Services, 52, 1, pp. 1-11, (2020); Akaka M.A., Vargo S.L., Technology as an operant resource in service (eco)systems, Information Systems and e-Business Management, 12, 3, pp. 367-384, (2014); Akbar P., Hoffmann S., Creating value in product service systems through sharing, Journal of Business Research, 121, 12, pp. 495-505, (2020); Akhter S.H., Impact of internet usage comfort and internet technical comfort on online shopping and online banking, Journal of International Consumer Marketing, 27, 3, pp. 207-219, (2015); Albashrawi M., Motiwalla L., An integrative framework on mobile banking success, Information Systems Management, 37, 1, pp. 16-32, (2020); Atkinson R.D., ‘It is going to kill us!’” and other myths about the future of artificial intelligence, IUP Journal of Computer Sciences, 12, 4, pp. 7-56, (2018); Banoun A., Dufour L., Andiappan M., Evolution of a service ecosystem: longitudinal evidence from multiple shared services centers based on the economies of worth framework, Journal of Business Research, 69, 8, pp. 2990-2998, (2016); Banwo A., Artificial intelligence and financial services: regulatory tracking and change management, Journal of Securities Operations and Custody, 10, 4, pp. 354-365, (2018); Baraldi E., Gressetvold E., Harrison D., Resource interaction in inter-organizational networks: foundations, comparison, and a research agenda, Journal of Business Research, 65, 2, pp. 266-276, (2012); Barney-McNamara B., Peltier J.W., Chennamaneni P.R., Niedermeier K.E., A conceptual framework for understanding the antecedents and consequences of social selling: a theoretical perspective and research agenda, Journal of Research in Interactive Marketing, (2021); Belanche D., Casalo L.V., Flavian C., Artificial intelligence in fintech: understanding robo-advisors adoption among customers, Industrial Management and Data Systems, 119, 7, pp. 1411-1430, (2019); Bendapudi N., Leone R.P., Psychological implications of customer participation in co-production, Journal of Marketing, 67, 1, pp. 14-28, (2003); Blut M., Wang C., Technology readiness: a meta-analysis of conceptualizations of the construct and its impact on technology usage, Journal of the Academy of Marketing Science, 48, 4, pp. 649-669, (2020); Boateng S.L., Online relationship marketing and customer loyalty: a signaling theory perspective, International Journal of Bank Marketing, 37, 1, pp. 226-240, (2019); Bock D.E., Mangus S.M., Folse J.A.G., The road to customer loyalty paved with service customization, Journal of Business Research, 69, 10, pp. 3923-3932, (2016); Bower J.L., Christensen C.M., Disruptive technologies: catching the wave, Harvard Business Review, 73, 1, pp. 43-53, (1995); Bruggen E.C., Hogreve J., Holmlund M., Kabadayi S., Lofgren M., Financial well-being: a conceptualization and research agenda, Journal of Business Research, 79, 10, pp. 228-237, (2018); Carida A., Edvardsson B., Colurcio M., Conceptualizing resource integration as an embedded process: matching, resourcing and valuing, Marketing Theory, 19, 1, pp. 65-84, (2019); Chandler J.D., Lusch R.F., Contextualization and value-in-context: how context frames exchange, Marketing Theory, 11, 1, pp. 35-49, (2011); Chandler J.D., Danatzis I., Wernicke C., Akaka M.A., Reynolds D., How does innovation emerge in a service ecosystem?, Journal of Service Research, 22, 1, pp. 75-89, (2019); Chen T., Dodds S., Finsterwalder J., Witell L., Cheung L., Falter M., Garry T., Snyder H., McColl-Kennedy J.R., Dynamics of wellbeing co-creation: a psychological ownership perspective, Journal of Service Management, ahead-of-print, ahead-of-print, (2020); Chepurna M., Rialp Criado J., Identification of barriers to co-create on-line: the perspectives of customers and companies, Journal of Research in Interactive Marketing, 12, 4, pp. 452-471, (2018); Choudhury V., Karahanna E., The relative advantage of ele"}},"J. Peltier; Department of Marketing, College of Business and Economics, University of Wisconsin-Whitewater, Whitewater, United States; email: peltierj@uww.edu",null,"Emerald Group Holdings Ltd.",{"$nulls":5},2.0407122E7,null,null,null,"English","J. Res. Interact. Mark.","Article","Final",null,"Scopus","2-s2.0-85100001965"]
["Wang X.; Yuen K.F.; Wong Y.D.; Teo C.-C.","Wang, Xueqin (57196484178); Yuen, Kum Fai (56581269200); Wong, Yiik Diew (57218910096); Teo, Chee-Chong (34267826000)","57196484178; 56581269200; 57218910096; 34267826000","E-consumer adoption of innovative last-mile logistics services: A comparison of behavioural models",2020.0,"Total Quality Management and Business Excellence",31.0,"2024-12-11",null,1381.0,1407.0,26.0,32.0,"10.1080/14783363.2018.1485484","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85087697284&doi=10.1080%2f14783363.2018.1485484&partnerID=40&md5=d32758a9a2228cca80475fbee2464294","School of Civil and Environmental Engineering, Nanyang Technological University, Singapore; Department of International Logistics, Chung-Ang University, Seoul, South Korea","Wang X., School of Civil and Environmental Engineering, Nanyang Technological University, Singapore; Yuen K.F., Department of International Logistics, Chung-Ang University, Seoul, South Korea; Wong Y.D., School of Civil and Environmental Engineering, Nanyang Technological University, Singapore; Teo C.-C., School of Civil and Environmental Engineering, Nanyang Technological University, Singapore","This paper investigates consumers’ behavioural responses to innovative last-mile delivery services (self-collection as an example) in the emerging e-commerce market of Singapore. Anchored on theoretical insights from attitude theories and Diffusion of Innovation (DOI) theory, the mediating role of the e-consumers’ attitude between their beliefs and their behavioural intention is examined in three competing models. A total of 209 valid survey responses are collected and the data are analysed using Structural Equation Modelling (SEM). Our study suggests an irreplaceable mediating role of attitude in determining the desirability of innovative last-mile delivery services. In particular, a sense of relative advantage and compatibility should be communicated to e-consumers. With an inter-disciplinary effort to integrate consumers’ behaviour in the management of last-mile logistics service innovations, this study contributes to the theoretical synthesis of these two streams of research. It also represents a unique angle to manage e-consumers’ service concerns from the perceptual and the behavioural perspectives. © 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group.","consumer adoption behaviour; consumer attitude; E-commerce; innovation diffusion; last-mile logistics; logistics service innovation; model comparison; self-collection",{"$nulls":7},{"$cut":{"chars":16786,"head":"Agarwal R., Prasad J., The role of innovation characteristics and perceived voluntariness in the acceptance of information technologies, Decision Sciences, 28, 3, pp. 557-582, (1997); Ajzen I., The theory of planned behavior, Organizational Behavior and Human Decision Processes, 50, pp. 179-211, (1991); Ajzen I., Fishbein M., Understanding attitudes and predicting social behavior, (1980); Akaike H., Factor analysis and AIC, Psychometrika, 52, 3, pp. 317-332, (1987); Aldas-Manzano J., Ruiz-Mafe C., Sanz-Blas S., Exploring individual personality factors as drivers of M-shopping acceptance, Industrial Management & Data Systems, 109, 6, pp. 739-757, (2009); Baek H., Oh S., Yang H.-D., Ahn J., Electronic word-of-mouth, box office revenue and social media, Electronic Commerce Research and Applications, 22, pp. 13-23, (2017); Baron R.M., Kenny D.A., The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations, Journal of Personality and Social Psychology, 51, 6, pp. 1173-1182, (1986); Bhattacharjya J., Ellison A., Tripathi S., An exploration of logistics- related customer service provision on twitter: The case of e-retailers, International Journal of Physical Distribution & Logistics Management, 46, 6-7, pp. 659-680, (2016); Bhattacherjee A., Understanding information systems continuance: An expectation-confirmation model, MIS Quarterly, 25, 3, pp. 351-370, (2001); Buettner R., Predicting user behavior in electronic markets based on personality-mining in large online social networks: A personality-based product recommender framework, Electronic Markets, 27, 3, pp. 247-265, (2017); Busse C., Marcus Wallenburg C., Innovation management of logistics service providers, International Journal of Physical Distribution & Logistics Management, 41, 2, pp. 187-218, (2011); Chen N.-H., Huang S., Domestic technology adoption: Comparison of innovation adoption models and moderators, Human Factors and Ergonomics in Manufacturing & Service Industries, 26, 2, pp. 177-190, (2016); Choo C., Master thesis: Impact of a delivery point network for urban E-commerce deliveries, (2016); Choudhury V., Karahanna E., The relative advantage of electronic channels: A multidimensional view, MIS Quarterly, 32, 1, pp. 179-200, (2008); Collier J.E., Kimes S.E., Only if it is convenient: Understanding how convenience influences self-service technology evaluation, Journal of Service Research, 16, 1, pp. 39-51, (2012); Collier J.E., Sherrell D.L., Examining the influence of control and convenience in a self-service setting, Journal of the Academy of Marketing Science, 38, pp. 490-509, (2010); Collier J.E., Sherrell D.L., Babakus E., Horky A.B., Understanding the differences of public and private self-service technology, Journal of Services Marketing, 28, October 2012, pp. 60-70, (2014); Collins A.T., Behavioural influences on the environmental impact of collection/delivery points, Green logistics and transportation: A sustainable supply chain perspective, pp. 15-34, (2015); Curran J.M., Meuter M.L., Self-service technology adoption: Comparing three technologies, Journal of Services Marketing, 19, 2, pp. 103-113, (2005); Dabholkar P.A., Bagozzi R.P., An attitudinal model of technology-based self-service: Moderating effects of consumer traits and situational factors, Journal of the Academy of Marketing Science, 30, 3, pp. 184-201, (2002); Dablanc L., Morganti E., Fortin F., Alternatives to home deliveries, final report, (2015); Da Mota Pedrosa A., Customer integration during innovation development: An exploratory study in the logistics service industry, Creativity and Innovation Management, 21, 3, pp. 263-276, (2012); Da Mota Pedrosa A., Blazevic V., Jasmand C., Logistics innovation development: A micro-level perspective, International Journal of Physical Distribution & Logistics Management, 45, 4, pp. 313-332, (2015); Davis F.D., Perceived usefulness, perceived ease of use, and user acceptance of information technology, MIS Quarterly, 13, 3, pp. 319-340, (1989); Davis F.D., Bagozzi R.P., Warshaw "}},"K.F. Yuen; Department of International Logistics, Chung-Ang University, Seoul, South Korea; email: Yuenkf@cau.ac.kr",null,"Routledge",{"$nulls":5},1.4783363E7,null,"TQMAE",null,"English","Total Qual. Manage. Bus. Excellence","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85087697284"]
["Maidiana K.; Hidayat Z.","Maidiana, Karilla (57226359273); Hidayat, Z. (57218270062)","57226359273; 57218270062","Distributing Goods and Information Flow: Factors Influencing Online Purchasing Behavior of Indonesian Consumers",2021.0,"Journal of Distribution Science",19.0,7.0,null,5.0,17.0,12.0,2.0,"10.15722/jds.19.7.202107.5","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85111277109&doi=10.15722%2fjds.19.7.202107.5&partnerID=40&md5=b12fa56da26e8b6bc00c73d6c13c6850","Communication Department, Master of Strategic Marketing Communication, Binus Graduate Program, Binus University, 11480, Indonesia","Maidiana K., Communication Department, Master of Strategic Marketing Communication, Binus Graduate Program, Binus University, 11480, Indonesia; Hidayat Z., Communication Department, Master of Strategic Marketing Communication, Binus Graduate Program, Binus University, 11480, Indonesia","Purpose: The distribution of goods and the flow of information, determined by consumer behavior toward online shopping, is drastically popular worldwide. This study examines some factors such as brand trust, online sales promotion, consumer personality, delivery service, quality assurance, information search, and online consumer satisfaction influence online shopping behavior. Research design, data, and methodology: A constructed questionnaire in an online survey was conducted with 241 random cluster respondents in the greater Jakarta Area. Structure equation model was utilized to analyze and verify all the data. Results: Research finding indicates online sales promotion, delivery service, quality assurance, and online consumer satisfaction positively influence information search. Meanwhile, brand trust, quality assurance, and information search positively influence online shopping behavior. However, the result illustrates that consumer personality negatively influences both information search and online shopping behavior. Conclusions: To influence online shopping behavior, the most important factors that need to be considered by marketplaces are quality assurance. It positively motivates Indonesia's citizens to collect information and make unplanned purchases. The study finding can be a reference for brands to maintain and build outstanding product quality, an informational website, and an excellent marketing strategy so that customers can meet their expectations. Besides, it also broadens both companies’ and individuals’ knowledge about the digital revolution on consumer behavior. © Copyright: The Author(s) This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://Creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original work is properly cited.","Consumer behavior; Distribution; Factors of online shopping; Indonesian consumers; Purchasing behavior",{"$nulls":5},"Binus University, BINUS","* This paper is supported by Binus University as an Independent Research.","Ahuja M., Gupta B., Raman P., An empirical investigation of online consumer purchasing behavior, Communications of the ACM, 46, 12, pp. 145-151, (2003); Alex D., Thomas S., Impact of product quality, service quality, and contextual Experience on customer perceived value and future buying intentions, European Journal of Business and Management, 3, 3, pp. 305-318, (2012); Amananah D., Harahap D. 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D., The impact of promotional tools on consumer buying behavior in the retail market, International Journal of Business and Social Science, 7, 1, pp. 75-85, (2016); Simanjuntak M., Musyifah I., Online shopping behavior on generation Y in Indonesia, Global Business & Finance Review, 2, 1, pp. 33-45, (2016); Sramova B., Pavelka J., Gender differences and wellbeing values in adolescent online shopping, International Journal of Retail & Distribution Management, 47, 6, (2018); Stoian C. L., Tugulea O., What are the dimensions of online satisfaction?, Review of Economics and Business Studies, 9, 2, pp. 45-59, (2016); Thaichon P., Consumer socialization process: The role of age in children's online, Journal of Retailing and Consumer Services, 34, pp. 38-47, (2017); Vasic N., Kilibarda M., Kaurin T., The influence of online shopping determinants on customer satisfaction in the Serbian market, Journal of Theoretical and Applied Electronic Commerce Research, 14, 2, pp. 70-89, (2019); Vinerean S., Luliana C., Dumitrescu L., Tichindelean M., The effect of social media marketing on online consumer behavior, International Journal of Business Management, 8, 14, pp. 65-79, (2013); Wu W., Ke C., Nguyen P., Online shopping behavior in electronic commerce: An integrative model from utilitarian and hedonic perspectives, International Journal of Entrepreneurship, 22, 3, pp. 1-16, (2018); Ye L.R., Zhang H., Sales promotion and purchasing intention: Applying the technology acceptance model in consumer-to-consumer marketplaces, International Journal of Business, Humanities, and Technology, 4, 3, pp. 1-5, (2014); Yoo K., Gretzel U., Influence of personality on travel-related consumer-generated media creation, Computers in Human Behavior, 27, pp. 609-621, (2011); Zhang B., Kim J., Luxury fashion consumption in china: Factors affecting attitude and purchase intent, Journal of Retailing and Consumer Services, 20, pp. 68-79, (2013)","Z. Hidayat; Communication Department, Master of Strategic Marketing Communication, Binus Graduate Program, Binus University, 11480, Indonesia; email: z.hidayat@binus.edu",null,"Korea Distribution Science Association (KODISA)",{"$nulls":5},1.738311E7,null,null,null,"English","J. Distribution Science","Article","Final",null,"Scopus","2-s2.0-85111277109"]
["Aktas E.; Bourlakis M.; Zissis D.","Aktas, Emel (14059584200); Bourlakis, Michael (6506844873); Zissis, Dimitris (57119852500)","14059584200; 6506844873; 57119852500","Collaboration in the last mile: evidence from grocery deliveries",2021.0,"International Journal of Logistics Research and Applications",24.0,3.0,null,227.0,241.0,14.0,17.0,"10.1080/13675567.2020.1740660","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85081715541&doi=10.1080%2f13675567.2020.1740660&partnerID=40&md5=0f2d9bb69402f51aa78fa7292645f828","Cranfield School of Management, Cranfield University, Cranfield, United Kingdom; Norwich Business School, University of East Anglia, Norwich, United Kingdom","Aktas E., Cranfield School of Management, Cranfield University, Cranfield, United Kingdom; Bourlakis M., Cranfield School of Management, Cranfield University, Cranfield, United Kingdom; Zissis D., Norwich Business School, University of East Anglia, Norwich, United Kingdom","The grocery sector has transitioned into an omnichannel operating mode, allowing consumers to buy online and have their order delivered to their chosen address. The last mile delivery service leads to avoidable inefficiencies such as low asset utilisation and repeated trips to nearby neighbourhoods, increasing vehicle emissions, traffic, and operational costs. Combining historical order and delivery data of an online grocery retailer with secondary data publicly available on other retailers, we employ Monte Carlo simulation to estimate grocery home delivery demand per 1-hour time windows. We use the simulation output as an input to daily vehicle routing problem instances under independent and collaborative last mile delivery operation to estimate the impact of collaboration. Our analyses show distance savings of around 17% and route reduction of around 22%. These results can support policies incentivising vehicle and infrastructure sharing settings and decoupling the last mile delivery from the core grocery retail services. © 2020 Informa UK Limited, trading as Taylor & Francis Group.","Collaboration; e-commerce; last mile delivery; Monte Carlo simulation; UK grocery sector; vehicle routing",{"$nulls":5},"Horizon 2020 Framework Programme, H2020; Horizon 2020, (635773)","Funding text 1:  This paper is an outcome of a project which has received funding from the European Union's Horizon 2020 research and innovation programme. ; Funding text 2: This work was supported by European Union Horizon 2020 [Grant Agreement No 635773]. This paper is an outcome of a project which has received funding from the European Union's Horizon 2020 research and innovation programme.","Abdulkader M., Gajpal Y., ElMekkawy T., Vehicle Routing Problem in Omni-Channel Retailing Distribution Systems, International Journal of Production Economics, 196, pp. 43-55, (2018); Accorsi R., Baruffaldi G., Manzini R., Tufano A., On the Design of Cooperative Vendors’ Networks in Retail Food Supply Chains: A Logistics-Driven Approach, International Journal of Logistics Research and Applications, 21, 1, pp. 35-52, (2018); Al Sunny S.M.N., Liu X.F., Shahriar M.R., An Integrated IoT Enabled On-Demand Grocery Shopping and Delivery Cloud System Using MTComm at the Edge, Proceedings–2019 IEEE International Conference on Edge Computing, EDGE 2019–Part of the 2019 IEEE World Congress on Services, pp. 51-55, (2019); Andelmin J., Bartolini E., A Multi-Start Local Search Heuristic for the Green Vehicle Routing Problem Based on a Multigraph Reformulation, Computers & Operations Research, 109, pp. 43-63, (2019); Asdemir K., Jacob V., Krishnan R., Dynamic Pricing of Multiple Home Delivery Options, European Journal of Operational Research, 196, 1, pp. 246-257, (2009); Belavina E., Girotra K., Kabra A., Online Grocery Retail: Revenue Models and Environmental Impact, Management Science, 63, 6, pp. 1781-1799, (2017); Breunig U., Baldacci R., Hartl R.F., Vidal T., The Electric Two-Echelon Vehicle Routing Problem, Computers and Operations Research, 103, pp. 198-210, (2019); Cachon G., Retail Store Density and the Cost of Greenhouse Gas Emissions, Management Science, 60, 8, pp. 1907-1925, (2014); Clarke G., Johnson A., Nankivell J., Van Travel Trends in Great Britain, (2014); Cleophas C., Ehmke J.F., When Are Deliveries Profitable?: Considering Order Value and Transport Capacity in Demand Fulfillment for Last-Mile Deliveries in Metropolitan Areas, Business and Information Systems Engineering, 6, 3, pp. 153-163, (2014); Cordeau J.-F., Laporte G., Savelsbergh M.W.P., Vigo D., Chapter 6 Vehicle Routing, Transportation, 14, pp. 367-428, (2007); de Kervenoael R., Yanik S., Bozkaya B., Palmer M., Hallsworth A., Trading-up on Unmet Expectations? Evaluating Consumers’ Expectations in Online Premium Grocery Shopping Logistics, International Journal of Logistics Research and Applications, 19, 2, pp. 83-104, (2016); Edwards J.B., McKinnon A.C., Cullinane S.L., Comparative Analysis of the Carbon Footprints of Conventional and Online Retailing, International Journal of Physical Distribution & Logistics Management, 40, 1-2, pp. 103-123, (2010); Emec U., Catay B., Bozkaya B., An Adaptive Large Neighborhood Search for an E-Grocery Delivery Routing Problem, Computers & Operations Research, 69, pp. 109-125, (2016); George E., Financial Times, (2019); Hackney R., Grant K., Birtwistle G., The UK Grocery Business: Towards a Sustainable Model for Virtual Markets, International Journal of Retail & Distribution Management, 34, 4-5, pp. 354-368, (2006); Hijmans R.J., Introduction to the “Geosphere” Package (Version 1.5-10), (2019); The Future of E-Commerce in FMCG, (2017); Kotzab H., Teller C., Value-Adding Partnerships and Co-opetition Models in the Grocery Industry, International Journal of Physical Distribution & Logistics Management, 33, 3, pp. 268-281, (2003); Lim S.F.W.T., Jin X., Srai J.S., Consumer-driven e-commerce: A Literature Review, Design Framework, and Research Agenda on Last-Mile Logistics Models, International Journal of Physical Distribution and Logistics Management, 48, 3, pp. 308-332, (2018); Lozano S., Moreno P., Adenso-Diaz B., Algaba E., Cooperative Game Theory Approach to Allocating Benefits of Horizontal Cooperation, European Journal of Operational Research, 229, 2, pp. 444-452, (2013); Online Grocery Retailing UK, March 2018 Executive Summary, (2018); Nathanail E., Adamos G., Gogas M., A Novel Approach for Assessing Sustainable City Logistics, Transportation Research Procedia, 25, pp. 1036-1045, (2017); O'Sullivan F., London’s Traffic Really Is Moving More Slowly, (2016); Paul J., Agatz N., Spliet R., Koster R.D., Shared Capacity Routing Problem − An Omni-Channel Retail Study, European Journal of Operational Research, 273, 2, pp. 731-739, (2019); Rogerson S., Santen V., Shippers’ Opportunities to Increase Load Factor: Managing Imbalances Between Required and Available Capacity, International Journal of Logistics Research and Applications, 20, 6, pp. 581-603, (2017); Teller C., Alexander A., Floh A., The Impact of Competition and Cooperation on the Performance of a Retail Agglomeration and its Stores, Industrial Marketing Management, 52, pp. 6-17, (2016); Tempelmeier N., Dietze S., Demidova E., Crosstown Traffic-Supervised Prediction of Impact of Planned Special Events on Urban Traffic, GeoInformatica, pp. 1-32, (2019); World Urbanization Prospects: The 2014 Revision, (2015); Zissis D., Aktas E., Bourlakis M., A New Process Model for Urban Transport of Food in the UK, Transportation Research Procedia, 22, pp. 588-597, (2017); Zissis D., Aktas E., Bourlakis M., Collaboration in Urban Distribution of Online Grocery Orders, The International Journal of Logistics Management, 29, 4, pp. 1196-1214, (2018); Zissis D., Saharidis G.K.D., Aktas E., Ioannou G., Emission Reduction via Supply Chain Coordination, Transportation Research Part D: Transport and Environment, 62, pp. 36-46, (2018)","E. Aktas; Cranfield School of Management, Cranfield University, Cranfield, United Kingdom; email: emel.aktas@cranfield.ac.uk",null,"Taylor and Francis Ltd.",{"$nulls":5},1.3675567E7,null,null,null,"English","Int. J. Logist. Res. Applic.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85081715541"]
["Li W.; Wu Y.; Kumar P.N.R.; Li K.","Li, Wenli (57195838344); Wu, Yong (56153285600); Kumar, P. N. Ram (57982161100); Li, Kunpeng (55894405000)","57195838344; 56153285600; 57982161100; 55894405000","Multi-trip vehicle routing problem with order release time",2020.0,"Engineering Optimization",52.0,8.0,null,1279.0,1294.0,15.0,14.0,"10.1080/0305215X.2019.1642880","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85070523246&doi=10.1080%2f0305215X.2019.1642880&partnerID=40&md5=1df4c901ed7f4b61c679b99170fa7d94","School of Management, Huazhong University of Science & Technology, Wuhan, China; Department of Business Strategy and Innovation, Griffith University, Queensland, Australia; Quantitative Methods & Operations Management Area, Indian Institute of Management Kozhikode, Kozhikode, India","Li W., School of Management, Huazhong University of Science & Technology, Wuhan, China; Wu Y., Department of Business Strategy and Innovation, Griffith University, Queensland, Australia; Kumar P.N.R., Quantitative Methods & Operations Management Area, Indian Institute of Management Kozhikode, Kozhikode, India; Li K., School of Management, Huazhong University of Science & Technology, Wuhan, China","This article studies a new variant of the vehicle routing problem known as the multi-trip vehicle routing problem with order release time. This problem frequently arises in the context of last-mile delivery in e-commerce. The order release time represents the time at which the customers’ goods become available at the depot for final distribution. Vehicles attached to the depot are used to perform multiple trips owing to the relatively short delivery distance. In this work, firstly, a mixed-integer linear programming (MILP) model is formulated. As the problem is a proven NP-hard problem, for solving large-sized instances quickly, an adaptive large neighbourhood search algorithm combined with a labelling procedure (ALNS-L) is proposed. The performance of the algorithm is further augmented by incorporating an optimal serving sequence property. The effectiveness of both the mathematical model and ALNS-L framework is verified by conducting extensive computational experiments on existing benchmark problems and real-life data. © 2019, © 2019 Informa UK Limited, trading as Taylor & Francis Group.","e-commerce; last-mile delivery; Multi-trip vehicle routing; order release time","Computational complexity; Electronic commerce; Integer programming; Vehicles; Bench-mark problems; Computational experiment; Large neighbourhood searches; Last mile; Mixed integer linear programming model; Multi trips; Order release; Vehicle Routing Problems; Vehicle routing",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (71372133, 71620107002, 71831007)","This work was supported by the National Natural Science Foundation of China [grant numbers 71372133, 71620107002, 71831007].","Alonso F., Alvarez M., Beasley J.E., A Tabu Search Algorithm for the Periodic Vehicle Routing Problem with Multiple Vehicle Trips and Accessibility Restrictions, Journal of the Operational Research Society, 59, 7, pp. 963-976, (2008); Archetti C., Feillet D., Andrea M., Speranza M.G., An Iterated Local Search for the Traveling Salesman Problem with Release Dates and Completion Time Minimization, Computers & Operations Research, 98, 10, pp. 24-37, (2018); Archetti C., Feillet D., Speranza M.G., Complexity of Routing Problems with Release Dates, European Journal of Operational Research, 247, 3, pp. 797-803, (2015); Arda Y., Crama Y., Kronus D., Pironet T., Hentenryck P.V., Multi Period Vehicle Loading with Stochastic Release Dates, EURO Journal on Transportation and Logistics, 3, 2, pp. 93-119, (2014); Azi N., Gendreau M., Potvin J.Y., An Exact Algorithm for a Single-vehicle Routing Problem with Time Windows and Multiple Routes, European Journal of Operational Research, 178, 3, pp. 755-766, (2007); Azi N., Gendreau M., Potvin J.Y., An Exact Algorithm for a Vehicle Routing Problem with Time Windows and Multiple use of Vehicles, European Journal of Operational Research, 202, 3, pp. 756-763, (2010); Azi N., Gendreau M., Potvin J.Y., An Adaptive Large Neighborhood Search for a Vehicle Routing Problem with Multiple Routes, Computers & Operations Research, 41, 1, pp. 167-173, (2014); Battarra M., Monaci M., Vigo D., An Adaptive Guidance Approach for the Heuristic Solution of a Minimum Multiple Trip Vehicle Routing Problem, Computers & Operations Research, 36, 11, pp. 3041-3050, (2009); Brandao J., Mercer A., A Tabu Search Algorithm for the Multi-trip Vehicle Routing and Scheduling Problem, European Journal of Operational Research, 100, 1, pp. 180-191, (1997); Cattaruzza D., Absi N., Feillet D., The Multi-Trip Vehicle Routing Problem with Time Windows and Release Dates, Transportation Science, 50, 2, pp. 676-693, (2016); Cattaruzza D., Absi N., Feillet D., Vidal T., A Memetic Algorithm for the Multi-Trip Vehicle Routing Problem, European Journal of Operational Research, 236, 3, pp. 833-848, (2014); Cattaruzza D., Absi N., Feillet D., Vidal T., An Iterated Local Search for the Multi-Commodity Multi-trip Vehicle Routing Problem with Time Windows, Computers & Operations Research, 51, 11, pp. 257-267, (2014); Cheikh M., Ratli M., Mkaouar O., Jarboui B., A Variable Neighborhood Search Algorithm for the Vehicle Routing Problem with Multiple Trips, Electronic Notes in Discrete Mathematics, 47, pp. 277-284, (2015); Fleischmann B., (1990); (2017); Hernandez F., Feillet D., Giroudeau R., Naud O., A new Exact Algorithm to Solve the Multi-trip Vehicle Routing Problem with Time Windows and Limited Duration, 4OR, 12, 3, pp. 235-259, (2014); Hernandez F., Feillet D., Giroudeau R., Naud O., Branch-and-price Algorithms for the Solution of the Multi-Trip Vehicle Routing Problem with Time Windows, European Journal of Operational Research, 249, 2, pp. 551-559, (2016); Liu L., Li K.P., Liu Z., A Capacitated Vehicle Routing Problem with Order Available Time in E-commerce Industry, Engineering Optimization, 49, 3, pp. 449-465, (2017); Macedo R., Alves C., Carvalho J.V., Clautiaux F., Hanafi S., Solving the Vehicle Routing Problem with Time Windows and Multiple Routes Exactly Using a Pseudo-Polynomial Model, European Journal of Operational Research, 214, 3, pp. 536-545, (2011); Mingozzi A., Roberti R., Toth P., An Exact Algorithm for the Multi-trip Vehicle Routing Problem, INFORMS Journal on Computing, 25, 2, pp. 193-207, (2013); Olivera A., Viera O., Adaptive Memory Programming for the Vehicle Routing Problem with Multiple Trips, Computers & Operations Research, 34, 1, pp. 28-47, (2007); Petch R.J., Salhi S., A Multi-Phase Constructive Heuristic for the Vehicle Routing Problem with Multiple Trips, Discrete Applied Mathematics, 133, 1-3, pp. 69-92, (2004); Pisinger D., Ropke S., A General Heuristic for Vehicle Routing Problems, Computers & Operations Research, 34, 8, pp. 2403-2435, (2007); Quan Z., Wu L., Cooperative Parallel Adaptive Neighborhood Search for the Disjunctively Constrained Knapsack Problem, Engineering Optimization, 49, 9, pp. 1541-1557, (2017); Reyes D., Erera A.L., Savelsbergh M.W., Complexity of Routing Problems with Release Dates and Deadlines, European Journal of Operational Research, 266, 1, pp. 29-34, (2018); Ropke S., Pisinger D., An Adaptive Large Neighborhood Search Heuristic for the Pickup and Delivery Problem with Time Windows, Transportation Science, 40, 4, pp. 455-472, (2006); Salhi S., Petch R., A GA Based Heuristic for the Vehicle Routing Problem with Multiple Trips, Journal of Mathematical Modelling and Algorithms, 6, 4, pp. 591-613, (2007); Shaw P., Using Constraint Programming and Local Search Methods to Solve Vehicle Routing Problems, Lecture Notes in Computer Science, 1520, pp. 417-431, (1998); Shelbourne B., Battarra M., Potts C., The Vehicle Routing Problem with Release and due Dates, INFORMS Journal on Computing, 29, 4, pp. 705-723, (2018); Taillard E.D., Laporte G., Gendreau M., Vehicle Routing with Multiple use of Vehicles, Journal of the Operational Research Society, 47, 8, pp. 1065-1070, (1996); Xiao Z.P., Wang J.J., Lenzer J., Sun Y.H., Understanding the Diversity of Final Delivery Solutions for Online Retailing: A Case of Shenzhen, China, Transportation Research Procedia, 25, pp. 985-998, (2017); Xiao Y.Y., Zhao Q.H., Kaku I., Mladenovic N., Variable Neighborhood Simulated Annealing Algorithm for Capacitated Vehicle Routing Problems, Engineering Optimization, 46, 4, pp. 562-579, (2014)","K. Li; School of Management, Huazhong University of Science & Technology, Wuhan, China; email: likp@mail.hust.edu.cn",null,"Taylor and Francis Ltd.",{"$nulls":5},"0305215X",null,"EGOPA",null,"English","Eng Optim","Article","Final","All Open Access; Bronze Open Access; Green Open Access","Scopus","2-s2.0-85070523246"]
["Ren S.; Choi T.-M.; Lee K.-M.; Lin L.","Ren, Shuyun (36618013100); Choi, Tsan-Ming (7202769936); Lee, Ka-Man (24468281700); Lin, Lei (55970736900)","36618013100; 7202769936; 24468281700; 55970736900","Intelligent service capacity allocation for cross-border-E-commerce related third-party-forwarding logistics operations: A deep learning approach",2020.0,"Transportation Research Part E: Logistics and Transportation Review",134.0,null,101834.0,null,null,null,90.0,"10.1016/j.tre.2019.101834","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85078560803&doi=10.1016%2fj.tre.2019.101834&partnerID=40&md5=7f32d12044d28ed13a877c1cb9d10136","Guangdong University of Technology, Guangzhou, China; Business Division, Institute of Textiles and Clothing, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong; Faculty of Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong; Goergen Institute for Data Science, University of Rochester, Rochester, 14623, NY, United States","Ren S., Guangdong University of Technology, Guangzhou, China; Choi T.-M., Business Division, Institute of Textiles and Clothing, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong; Lee K.-M., Faculty of Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong; Lin L., Goergen Institute for Data Science, University of Rochester, Rochester, 14623, NY, United States","With the rise of “cross-border-e-commerce”, the third-party-forwarding-logistics (3PFL) service becomes increasingly popular. Different from the traditional third-party-logistics (3PL) service, the 3PFL company provides forwarding services cost-effectively by consolidating orders from different e-tailers/platforms. The random arrivals of orders create a big challenge. Different from most of the existing studies, a deep learning based one-step integration optimal decision making approach S2SCL(Seq2Seq based CNN-LSTM) is proposed in this paper which intelligently integrates inventory optimization and demand-forecasting process. The Seq2Seq based forecasting architecture, which integrates CNN and LSTM network, is able to model the system dynamics and dependency-relations in varying demand for logistics services. Besides generating the point forecasting results, the proposed approach can quantify demand uncertainty via a dynamic distribution and make optimal decision on logistics service capacity allocation. Through a case-study analysis with real data obtained from a 3PFL company in China's Great Bay Area, we compare the proposed S2SCL with two benchmark models, including a one-step statistics based integration approach ARIMA and a two-step optimization based approach PSO-ELM, for two tasks: (1) point forecasting and (2) optimal logistic service capacity (LSC) allocation. Experimental results show that S2SCL outperforms the two benchmark models in both tasks significantly. © 2020 Elsevier Ltd","Cross-border e-commerce; Deep learning; Logistics service capacity (LSC) allocation; Multi-product newsvendor; Third-party forwarding logistics (3PFL)","China; artificial neural network; benchmarking; electronic commerce; forecasting method; logistics; optimization; travel demand",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (71801054); Innovation and Technology Fund, ITF, (ZM2K)","This research is supported by Innovation and Technology Fund (Project: ZM2K). Shuyun Ren's research is partially supported by National Natural Science Foundation of China (Project account: 71801054). The author sincerely thank Wah Tung Tai Company Ltd for providing industrial real data for this research.","Arabzad S.M., Ghorbani M., Tavakkoli-Moghaddam R., An evolutionary algorithm for a new multi-objective location-inventory model in a distribution network with transportation modes and third-party logistics providers, Int. J. Prod. Res., 53, 4, pp. 1038-1050, (2015); Barenji A.V., Wang W.M., Li Z., Guerra-Zubiaga D.A., Intelligent E-commerce logistics platform using hybrid agent based approach, Transport. Res. Part E: Logist. Transport. Rev., 126, pp. 15-31, (2019); Ban G.Y., Rudin C., The big data newsvendor: Practical insights from machine learning, Oper. Res., 67, 1, pp. 90-108, (2018); Chen F.Y., Hum S.H., Sun J., Analysis of third-party warehousing contracts with commitments, Eur. J. Oper. 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Technol., 100, pp. 372-385, (2019); Wang Y., Wallace S.W., Shen B., Choi T.M., Service supply chain management: A review of operational models, Eur. J. Oper. Res., 247, 3, pp. 685-698, (2015); Wang Y., Jia F., Schoenherr T., Gong Y., Chen L., Cross-border e-commerce firms as supply chain integrators: the management of three flows, Ind. Market. Manage., (2019); Yu Y., Choi T.M., Hui C.L., An intelligent fast sales forecasting model for fashion products, Expert Syst. Appl., 38, 6, pp. 7373-7379, (2011); Zhang S., Xiao K., Carranza E.J.M., Yang F., Zhao Z., Integration of auto-encoder network with density-based spatial clustering for geochemical anomaly detection for mineral exploration, Comput. Geosci., (2019)","K.-M. Lee; Faculty of Engineering, The Hong Kong Polytechnic University, Kowloon, Hung Hom, Hong Kong; email: ckm.lee@polyu.edu.hk",null,"Elsevier Ltd",{"$nulls":5},1.3665545E7,null,null,null,"English","Transp. Res. Part E Logist. Transp. Rev.","Article","Final",null,"Scopus","2-s2.0-85078560803"]
["Abdallah A.A.","Abdallah, Abdallah Ali (20336956300)",2.03369563E10,"Axiomatic six sigma, a simulation-based decision-making framework",2020.0,"Journal of Mechanical Engineering Research and Developments",43.0,7.0,null,119.0,136.0,17.0,2.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85095568538&partnerID=40&md5=bcd9558a4a4f88d8b268a5c1dd3f5903","Industrial engineering department, German Jordanian University, Madaba Street, P.O. Box 35247, Amman, 11180, Jordan","Abdallah A.A., Industrial engineering department, German Jordanian University, Madaba Street, P.O. Box 35247, Amman, 11180, Jordan","For the last few decades, companies used six sigma in almost all processes to improve performance. Typical improvements include decreased operational cost, increased customer satisfaction, decreased cycle time, and enhanced profits, but regardless of the nature of the improvement, all projects follow the \"Define-Measure-Analyze- Improve-Control\" methodology. This paper proposes the use of a decision framework that utilizes the use of axiomatic design in the analyze and improve phases in order to reach optimum performance at the end of each project through an established optimization framework. The framework includes the use of simulation and a managerial decisionmaking tool called \"alternative evaluation tool\". The author implemented the framework in a real case study performed at a global logistics company that has an e-commerce logistics station located at John F. Kennedy airport in New York; a station that suffers from low on-time delivery and high operational cost. As result, the author implemented a six-sigma project along with simulation to reveal various scenarios suggested by the six-sigma team in order to optimize the process. The project resulted in 65% reduction in labor, 41% reduction in work in process and 55% reduction in average time packages spend at the station. © 2020 Zibeline International Publishing Sdn. Bhd.. All rights reserved.","Axiomatic design; Logistics; Process optimization; Simulation; Six sigma",{"$nulls":7},"Abdallah A.A., Simulated Six Sigma: A multi response optimization, Quality Engineering; Shengli Z., Zeping L., Li Z., Construction of Logistics Network System Based on Internet, Journal of Physics, 1176, pp. 22-27, (2019); Stacy A.V., Ann M.C., Barrett W.T., The Same-Day Delivery Problem for Online Purchases, Transportation Science, 53, pp. 167-184, (2017); Park Y., Choi J.K., Zhang A., Evaluating competitiveness of air cargo express Services, Transportation Research, 45, pp. 321-334, (2009); Bowie B., Air freighting of perishable agribusiness products: Process and issues, (2018); Folaron J., The evolution of Six Sigma, S. S. Forum Magazine, 2, 4, pp. 38-44, (2003); Kwak Y.H., Anbari F.T., Benefits, obstacles, and future of Six Sigma approach, Technovation, 26, pp. 708-715, (2006); Antony J., Banuelas R., Six Sigma: A strategy for survival, Manufacturing Engingineering, 80, pp. 119-121, (2001); Zu X., Fredendall L. D., Douglas T. J., The evolving theory of quality management: The role of Six Sigma, Journal of Operation Management, 26, pp. 630-650, (2008); Schroeder R.G., Linderman K., Liedtke C., Choo A.S., Six Sigma: definition and underlying theory, Journal of operation Management, 26, pp. 536-554; Shankar R., Process improvement using Six Sigma: A DMAIC guide, (2009); Pyzdek T., Keller P., The Six Sigma Handbook, (2014); Qatawneh L., Abdallah A., Zalloum S., Six Sigma Application in Healthcare Logistics: A Framework and a Case Study, Journal of Health Care Engineering, 1, pp. 1-12, (2019); Arcidiacono G., Giorgetti A., Pugliese M., Axiomatic Design to improve PRM airport assistance, Proceedings of ICAD conference, (2015); Arcidiacono G., Yang K., Trewn J., Bucciarelli L., Application of Axiomatic Design for Project-Based Learning Methodology, Proceedings of the 10th International Conference on Axiomatic Design, (2016); Cudney E.A., Kestle R., Implementing Lean Six Sigma throughout the Supply Chain: The Comprehensive and Transparent Case Study, (2018); Olga M.F., Carvalho W., Edson P.P., Lean Six Sigma in Brazil: a literature Review, International Journal of Lean Six Sigma, 10, pp. 435-472, (2019); Goldsby T., Martichenko R., Lean Six Sigma Logistics, (2003); Singh M., Optimization of Food Commodity Supply Chain in Logistics Service Provider Business by Implementing Lean Management, Working Paper Series 2017-007, (2017); Gutierrez-Gutierrez L., Sander L., Ruud D., Logistics services and Lean Six Sigma implementation: a case study, International Journal of Lean Six Sigma, 7, pp. 324-342, (2016); Zhang A., Lou W., Shi Y., Chia S., Sim Z., Lean and Six Sigma in logistics: a pilot survey study in Singapore, International Journal of Operations & Production Management, 36, pp. 1625-1643, (2016); Jones E., Supply Chain Engineering and Logistics Handbook: Inventory and Production, (2019); Suh N.P., The principles of design, (1990); Suh N.P., Bell A.C., Gossard D.C., On an axiomatic approach to manufacturing and manufacturing systems, Journal of Engineering for Industry, 100, pp. 127-130, (1978); Brown C.A., Decomposition and Prioritization in Engineering Design, Proceedings of the 6th International Conference on Axiomatic Design, (2011); Banks J., John S.C., Barry L.N., David M.N., Discrete-event System Simulation, (2010); Kelton W.D., Randall P.S., David T.S., Simulation with Arena, (2010); Montgomery D.C., Runger G.C., Applied Statistics and Probability for Engineers, (2018); Kovacs G., Kot S., New logistics and production trends as the effect of global economy changes, Polish Journal of Management Studies, 14, pp. 115-126, (2016)","A.A. Abdallah; Industrial engineering department, German Jordanian University, Amman, Madaba Street, P.O. Box 35247, 11180, Jordan; email: abdallah.abdallah@gju.edu.jo",null,"Bangladesh University of Engineering and Technology",{"$nulls":5},1.0241752E7,null,"JERDF",null,"English","J Mech Eng Res Dev","Article","Final",null,"Scopus","2-s2.0-85095568538"]
["Lei X.-Q.; Yang J.-J.; Zou J.-B.; Zhuang M.-E.","Lei, Xiao-Qing (57219319297); Yang, Jia-Jia (57218489010); Zou, Jian-Bo (57219316600); Zhuang, Mei-Er (57217010252)","57219319297; 57218489010; 57219316600; 57217010252","Research on the Impact of Logistics Technology Progress on Employment Structure Based on DEA-Malmquist Method",2020.0,"Mathematical Problems in Engineering",2020.0,null,7064897.0,null,null,null,7.0,"10.1155/2020/7064897","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85092126714&doi=10.1155%2f2020%2f7064897&partnerID=40&md5=6a3f150d30c4dfdffef7e7cb7d27106a","School of Business, Guangdong University of Foreign Studies, Guangzhou, 510006, China; Department of Public Policy, King's College London, London, WC2R 2LS, United Kingdom; School of Business, Guangdong University of Foreign Studies, Guangzhou, 510000, China","Lei X.-Q., School of Business, Guangdong University of Foreign Studies, Guangzhou, 510006, China; Yang J.-J., Department of Public Policy, King's College London, London, WC2R 2LS, United Kingdom; Zou J.-B., School of Business, Guangdong University of Foreign Studies, Guangzhou, 510006, China; Zhuang M.-E., School of Business, Guangdong University of Foreign Studies, Guangzhou, 510000, China","In recent years, with the vigorous development of e-commerce, the logistics industry has also developed rapidly and has gradually become one of China's important industries. This paper takes 49 listed companies in the logistics industry in China as the research object and uses the DEA-Malmquist index method to measure the technology progress index of the logistics industry based on their panel data for a total of 10 years from 2008 to 2017. In this way, this article explores the impact of technological progress in the logistics industry and provides a reference for solving the contradiction of employment structure in China  © 2020 Xiao-qing Lei et al.",null,"Mathematical techniques; DEA-Malmquist; Logistics industry; Logistics technologies; Panel data; Research object; Structure-based; Technological progress; Technology progress; Engineering",{"$nulls":6},"Xiong S., Zhu Y., The experience of technological progress and employment growth in the eastern region, Contemporary Economy, 36, 12, pp. 100-101, (2008); Jiang M., Analysis of the impact of technological progress on employment, Science and Technology Management Research, 40, 1, pp. 70-73, (2007); Bo L., Wen J., The employment effect of technological progress in China's industrial sector, Economic Developments, 61, 10, pp. 34-37, (2010); Srour I., Taymaz E., Vivarelli M., Skill-Biased Technological Change and Skill-Enhancing Trade in Turkey: Evidence from Longitudinal Microdata, (2013); Rogerson R., Kaboski J.P., Buera F., Skill-biased Structural Change and the Skill Premium; Berman E., Bound J., MacHin S., Implications of skill-biased technological change: International evidence, The Quarterly Journal of Economics, 113, 4, pp. 1245-1279, (1998); Spitz-Oener A., Technical change, job tasks, and rising educational demands: Looking outside the wage structure, Journal of Labor Economics, 24, 2, pp. 235-270, (2006); Kaplan J., Humans Need Not Apply: A Guide to Wealth and Work in the Age of Artificial Intelligence, (2015); Zhu Q., Li M., Research on countermeasures for artificial intelligence, technological progress and labor structure optimization, Science and Technology Progress and Countermeasures, 35, 6, pp. 36-41, (2018); Mincer J., Danninger S., Technology, unemployment and inflation, Nber Working Paper, (2000); Acemoglu D., Changes in unemployment and wage inequality: An alternative theory and some evidence, American Economic Review, 89, 5, pp. 1259-1278, (1999); Katz L.F., Murphy K.M., Changes in relative wages, 1963-1987: Supply and demand factors, The Quarterly Journal of Economics, 107, 1, pp. 35-78, (1992)","X.-Q. Lei; School of Business, Guangdong University of Foreign Studies, Guangzhou, 510006, China; email: lei_xq@126.com",null,"Hindawi Limited",{"$nulls":5},"1024123X",null,null,null,"English","Math. Probl. Eng.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85092126714"]
["Juan S.","Juan, Shenyi (57220544970)",5.722054497E10,"Analysis on mechanical structure and automatic control of an intelligent logistics vehicle",2020.0,"International Journal of Mechatronics and Applied Mechanics",1.0,8.0,null,24.0,32.0,8.0,0.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85097340098&partnerID=40&md5=52a5848c4612fb7580447f3c9e502c99","Business School, Wuchang University of Technology, Wuhan, 430223, China","Juan S., Business School, Wuchang University of Technology, Wuhan, 430223, China","In order to solve the application of driving motor drive structure and sensor technology in logistics vehicles to make the logistics vehicles adapt to more complex road conditions, a research on logistics vehicle based on electronic differential speed is presented, and its mechanical structure and automatic control system are designed. Firstly, the hub motor, mechanical structure, automatic controller, electronic differential principle, and fuzzy PI control theory of intelligent logistics vehicle are introduced. Besides, the hub motor, mechanical structure and automatic controller are designed. For the design of hub motor, the drive motor is chosen as brushless direct current (DC) motor. In the mechanical structure, three kinds of wheel structure are introduced, and the four-wheel structure is selected. The Intelligent Power Module (IPM) of IKCM30F60GA driving circuit is designed for the automatic controller. Then, the vehicle control strategy based on electronic differential velocity model system master control module algorithm is constructed. Finally, an external hub motor is constructed for finite element simulation, and the experiment is carried out for no-load, load and electronic differential steering of the external rotor. The experimental results show that the brushless DC motor is in the form of four wheels. The mechanical structure of the wheel is that the first two wheels are driving wheels and the two rear wheels are directional wheels. According to the simulation experiment, fuzzy PI has a shorter response time, stronger anti-interference and stability than conventional PI. The logistics vehicle based on electronic differential speed designed in this research can adapt to more complex road conditions, and the degree of intelligence and automation has been improved. The research provides a good guiding ideology for the development of logistics vehicles in the e-commerce industry. © 2020, Cefin Publishing House. All rights reserved.","Automatic Controller; Electron Differential Model; Hub Motor; Mechanical Structure; Self-Guiding Vehicle","Automation; Brushless DC motors; Control system synthesis; Controllers; Electric motors; Fuzzy control; Process control; Road vehicles; Roads and streets; Water craft; Wheels; Automatic controllers; Brushless direct currents; Electronic differential; Finite element simulations; Intelligent power module; Logistics vehicles; Mechanical structures; Sensor technologies; Structural design",{"$nulls":6},"Li G., Lin R., Li M, Et al., A Master-Slave Separate Parallel Intelligent Mobile Robot Used for Autonomous Pallet Transportation [J], Applied Sciences, 9, 3, (2019); Yang Y., Zhong M., Yao H, Et al., Internet of things for smart ports: Technologies and challenges [J], IEEE Instrumentation & Measurement Magazine, 21, 1, pp. 34-43, (2018); Tran A. S., Ngo H. Q. T., Research and manufacture of automated guided vehicle for the service of storehouse [J], Science and Technology Development Journal-Engineering and Technology, 1, 1, pp. 5-12, (2018); Klosowski G., Gola A., Amila T., Computational intelligence in control of AGV multimodal systems [J], Ifac-papersonline, 51, 11, pp. 1421-1427, (2018); Kaliappan S., Lokesh J., Mahaneesh P, Et al., Mechanical Design and Analysis of AGV for Cost Reduction of Material Handling in Automobile Industries, International Research Journal of Automotive Technology, 1, 1, pp. 1-7, (2018); Gao Z., Du Y., Zhang Y, Et al., Design and Development on Automatic Guided Logistics Platform with Robotic Arm [J], Machinery Design & Manufacture, 8, (2015); Peng T., Qian J., Zi B, Et al., Mechanical design and control system of an omni-directional mobile robot for material conveying, Procedia CIRP, 56, pp. 412-415, (2016); Zhang J., Zhang H., Zhao Y, Et al., Design for Micro Intelligent Automatic Tracking AGV Based on Arduino Microcontroller [J], Machine Tool & Hydraulics, 3, (2018); Wu X., Wu J., Jin P, Et al., Genetic Algorithm-Based Structure Optimization and Load-Carrying Analysis for the Body Frame of Heavy-Duty AGVs [J], International Journal of Robotic Engineering, 3, 2, pp. 1-10, (2018); Li G., Lin R., Li M, Et al., A Master-Slave Separate Parallel Intelligent Mobile Robot Used for Autonomous Pallet Transportation [J], Applied Sciences, 9, 3, (2019); Tran A. S., Ngo H. Q. T., Research and manufacture of automated guided vehicle for the service of storehouse [J], Science and Technology Development Journal-Engineering and Technology, 1, 1, pp. 5-12, (2018); Jacobs L., De Preter A., Anthonis J, Et al., Trajectory tracking of AGVs by linear parameter-varying control: a case study, IFAC-Papers On Line, 51, 26, pp. 43-48, (2018); Yao J., Chen J., Wang Q., Design and realization of a three-dimensional garage control and management system based on agv carrier [J], Mechanical Engineering & Automation, 1, (2018); Mehami J., Nawi M., Zhong R. Y., Smart automated guided vehicles for manufacturing in the context of Industry 4.0[J], Procedia Manufacturing, 26, pp. 1077-1086, (2018); Wang H., Guan H., Wang P, Et al., Design of camera tracking car based on ROS system [J], Information Technology and Informatization, 2, (2019); Hang P., Chen X., Zhang B, Et al., Longitudinal velocity tracking control of a 4WID electric vehicle [J], IFAC-Papers On Line, 51, 31, pp. 790-795, (2018)","S. Juan; Business School, Wuchang University of Technology, Wuhan, 430223, China; email: juanshenyisywh@163.com",null,"Cefin Publishing House",{"$nulls":5},2.5596497E7,null,null,null,"English","Int. J. Mech. Appl. Mech.","Article","Final",null,"Scopus","2-s2.0-85097340098"]
["Suvittawat A.","Suvittawat, Adisak (56068116600)",5.60681166E10,"Logistics service innovation for business growth: A case study of logistics service entrepreneurs; [Innowacje usług logistycznych dla rozwoju biznesu: Studium przypadku przedsiębiorców usług logistycznych]",2020.0,"Polish Journal of Management Studies",21.0,1.0,null,394.0,407.0,13.0,1.0,"10.17512/pjms.2020.21.1.29","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85088278315&doi=10.17512%2fpjms.2020.21.1.29&partnerID=40&md5=3ef5b539f2eead7fe8e8b29e807518f6","Suranaree University of Technology, School of Management, Thailand","Suvittawat A., Suranaree University of Technology, School of Management, Thailand","The emerging of e-commerce creates the logistics industry to experience a new never before seen high. Logistics is a great opportunity for service innovations and business growth in this time and age. This objective of the study is to find out logistics service innovation in various dimensions such as customer satisfaction, service guarantee, service blueprint, pay by instalment, product testing trial and the offering of additional services. This research applied a quantitative method by using questionnaires focusing on 44 logistics service entrepreneurs. The results of this study reveal that logistics has become a service industry with a service mind and quality, and it provides a service blueprint, service guarantee and customer satisfaction guarantee. Those who do not adjust to the demands of the market and focus on customer satisfaction are left behind and miss out the business growth opportunity. The demand for new domestic logistic service like Grab and company like Kerry carry more than their market share focusing on service warranties and guaranties something new in industry, and country which usually passes on the blame whenever it can. But in this case, with logistics, the innovative companies take responsibility. © 2020, Czestochowa University of Technology. All rights reserved.","Business growth; Entrepreneurs; Logistics management; Service innovation",{"$nulls":7},"Ack N. J., Urthy D. N. P. M., Warranty servicing strategies to improve customer satisfaction, IMA Journal of Management Mathematics, 15, 2, pp. 111-124, (2004); Atarodian A., Service innovation-driven enterprises in Emerging markets: A contemporary new insight of firms in a dynamic global context, 26th Annual RESER Conference, pp. 1-19, (2016); Bogicevic V., Yang W., Bilgihan A., Bujisic M., Airport service quality drivers of passenger satisfaction, Tourism Review, 68, 4, pp. 3-18, (2013); Carvallho L., Goodyear P., Design, learning networks, and service innovation, Design Studies, pp. 1-27, (2018); Castano M. S., Mendez M. T., Galindo M. A., Innovation, internationalization and business-growth expectations among entrepreneurs in the services sector, Journal of Business Research, 69, 5, pp. 1690-1695, (2016); Chang W. L., Lin J. H., Optimal maintenance policy and length of extended warranty within the life cycle of products, Computers and Mathematics with Applications, 63, 1, pp. 144-150, (2012); Dobbs M., Hamilton R. T., Small business growth: Recent evidence and new directions, International Journal of Entrepreneurial Behaviour and Research, 13, 5, pp. 296-322, (2007); Gleissner H., Femerling C., Logistics: basics-exercises-case studies, (2013); Haksever C., Render B., Service management: An integrated approach to supply chain management and operations, (1995); Haugen M., Service Blueprints, pp. 1-15, (2014); Hendayana Y, Suryana, The Effect of Productivity and Innovation on the Competitiveness of Batik SMEs in West Java Indonesia, J. Mgt. Mkt. Review, 4, 1, pp. 19-26, (2019); Hossain M. Z., Enam F., Farhana S., Service Blueprint a Tool for Enhancing Service Quality in Restaurant Business, American Journal of Industrial and Business Management, 7, 7, pp. 919-926, (2017); Hsieh Y.-H., Chou Y.-H., Modeling the impact of service innovation for small and medium enterprises: A system dynamics approach, Simulation Modelling Practice and Theory, 82, pp. 84-102, (2018); Husaini, Pirzada K., Saiful, Risk Management, Sustainable Governance Impact on Corporate Performance, Journal of Security and Sustainability Issues, 9, 3, pp. 993-1004, (2020); Issac L., Adeyemo A., Ogunleye O., Impact Of After Sales Service On Consumer Satisfaction And Retention. A Study of LG Electronics in Ibadan, Nigeria, IOSR Journal of Business and ManagementJournal of Business and Management, 11, 4, pp. 54-58, (2013); Kotaskova A., Rozsa Z., The impact of selected factors on the quality of business environment assessment in the Czech Republic and the Slovak Republic, International Journal of Entrepreneurial Knowledge, 6, 2, pp. 71-80, (2018); Liu W., Shen X., Xie D., Decision method for the optimal number of logistics service providers with service quality guarantee and revenue fairness, Applied Mathematical Modelling, 48, pp. 53-69, (2017); Meidute-Kavaliauskiene A., Aranskis A., Litvinenko M., Consumer satisfaction with the quality of logistics services, Procedia-Social and Behavioral Sciences, 110, pp. 330-340, (2014); Micu C. C., Coulter R. A., Price L. L., How Product Trial Alters The Effects of Model Attractiveness, Journal of Advertising, 38, 2, pp. 69-82, (2009); Myerson A.P., Supply chain and logistics management made easy: Methods and application for planning, operations, integration, control and improvement and network design, (2015); Nedeliakova E., Sekulova J., Nedeliak I., Loch M., Methods of identification level of service quality in railway transport, Procedia-Social and Behavioral Sciences, 110, pp. 320-329, (2014); Onuferova E., Cabinova, Enterprise performance analysis of selected service sector by applying modern methods with an emphasis on the creation and application of the modified creditworthy model (MCWM), Journal of Tourism and Service, 9, 17, pp. 130-147, (2019); Paraman P., The impact of ultimate service guarantee on consumer decision making towards luxury hotel sectors in accordance to Malaysian consumer protection Act 1999 (Cpa), International Journal of In Multidisciplinary and Academic Research, 3, 6, pp. 1-35, (2014); Pekarcikova M., Trebuna P., Kliment M., Digitalization effects on the usability of lean tools, Acta logistica, 6, 1, pp. 9-13, (2019); Randhawa P., MiRan K., CiChy R., Service innovations: What the managers belive and what the customer say, Journal of Hospitality Marketing& Management, 26, 2, pp. 186-206, (2017); Rantala T., Ukko J., Saunila M., Havukainen J., The effect od sustainability in the adoption of technological, service, and business model innovation, Journal of Cleaner Production, 17, pp. 46-55, (2018); Sasongko G., Huruta A.D., Pirzada K., Why labor force participation rate rises? New empirical evidence from Indonesia, Entrepreneurship and Sustainability Issues, 7, 1, pp. 166-176, (2019); Shaw S., Chovancova M., Bejtkovsky J., Consumer behavior and warranty claim: A study on Czech consumers, Economics and Sociology, 10, 3, pp. 90-101, (2017); Silk A. J., Urban G. L., Pre-Test-Market Evaluation of New Packaged Goods: A Model and Measurement Methodology, Journal of Marketing Research, 15, 2, pp. 171-182, (1978); Simarmata J., Ikhsan R. B., Building customer retention in on-line, Polish Journal of Management Studies, 15, 2, pp. 229-239, (2017); Simarmata J., Keke Y., Veronica, Silalahi S. A., Benkova E., How To Establish Customer Trust and Retention in a Highly Competitive Airline Business, Polish Journal of Management Studies, 16, 1, pp. 202-214, (2017); Singh J., Crisafulli B., Managing online service recovery: procedures, justice, and customer satisfaction, Journal of Service Theory and Practice, 26, 6, pp. 764-787, (2016); Sousa-Zomer T., Miguel P., Sustainable business models as an innovation strategy in product-service systems, Journal of Clean Production, 171, pp. 119-129, (2018); Suvittawat A., Klichandeang N., Singchai K., Customer satisfaction evaluation by using service marketing mix model: A case study of budget hotel at Rayong province, Thailand, The Journal of Social Sciences Research, 2, pp. 104-109, (2018); Veraart I.C.J., International trade and port logistics, (2014); Witell L., Snyder H., Gustafsson A., Fombelle P., Kristensson P., Defining service innovation: A review and synthesis, Journal of Business Research, 69, 8, pp. 2863-2872, (2016); Yang C.-C., Marlow P., Lu C.-S., Assessing resources, logistics service capabilities, innovation capabilities and the performance of container shipping services in Taiwan, International Journal Production Economics, 122, pp. 4-20, (2009)","A. Suvittawat; Suranaree University of Technology, School of Management, Thailand; email: suvittawat.adisak@gmail.com",null,"Czestochowa University of Technology",{"$nulls":5},2.0817452E7,null,null,null,"English","Pol. J. Manag. Stud.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85088278315"]
["Feng Z.","Feng, Zhitan (57208741694)",5.7208741694E10,"Constructing rural e-commerce logistics model based on ant colony algorithm and artificial intelligence method",2020.0,"Soft Computing",24.0,11.0,null,7937.0,7946.0,9.0,20.0,"10.1007/s00500-019-04046-8","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85065669231&doi=10.1007%2fs00500-019-04046-8&partnerID=40&md5=c20f0b2b4b6abcea0381470267a60fcb","School of Commercial, Nantong Institute of Technology, Nan Tong, China","Feng Z., School of Commercial, Nantong Institute of Technology, Nan Tong, China","In order to study the application of ant colony algorithm in rural e-commerce logistics mode, the third-party distribution model was adopted as the logistics method with Xuzhou City’s fruit and vegetable agricultural products as the key research object. Through the model construction, the problem of the third-party distribution model is analyzed. Based on the ant colony algorithm, the shortest path and cost are calculated using MATLAB software. The cost and efficiency problems under different variables are analyzed and the model evaluation is carried out. Finally, the difficulties at the urban and rural end of the third-party distribution model are solved. The results show that the method improves the distribution efficiency and reduces the logistics cost. Therefore, it is conducive to the advancement of rural e-commerce. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature.","Ant colony algorithm; Artificial intelligence; e-commerce; Logistics model; Rural","Agricultural products; Artificial intelligence; Efficiency; Electronic commerce; MATLAB; Rural areas; Ant colony algorithms; Artificial intelligence methods; Distribution efficiency; Distribution models; Fruit and vegetables; Logistics model; Model construction; Model evaluation; Ant colony optimization",{"$nulls":4},"First Level Key Built Discipline Projects of the Business Administration, (SJY201609)","This project was supported by the First Level Key Built Discipline Projects of the Business Administration under Jiangsu Provincial “the 13th Five-Year Plan” (project number: SJY201609).","Cai H.Y., Xu Y.Z., Research on the development pattern and effect mechanism of logistics industry in the Yangtze River delta—based on the perspective of spatial economics, East China Econ Manag, 20, 10, pp. 15-23, (2016); Dai J., Xie L., Wang Q., The impact of the third party logistics integration on logistics service quality, partnership and corporate operational performance, Manag Rev, 27, 5, pp. 188-197, (2015); Farhan A., Bashir B.K., Salabat K., Et al., CACONET: Ant colony optimization (ACO) based clustering algorithm for VANET[J], PLoS ONE, 11, 5, (2016); Fathian M., Shiran G.R., Jafarian-Moghaddam A.R., Two new clustering algorithms for vehicular Ad-Hoc network based on ant colony system[J], Wirel Pers Commun, 83, 1, pp. 473-491, (2015); He X.H., Application research on quantum ant colony algorithm in grain logistics distribution path optimization, Electron Des Eng, 24, 9, pp. 39-41, (2016); Huang W.H., Amp N.T., University R., 4PL path optimization based on improved ant colony algorithm, J Ningbo Univ Technol, 28, 4, (2016); Jiao R., Yu X.Q., The problems and path thinking of China’s rural logistics development, Asian Agric Res, 3, 5, pp. 112-115, (2011); Khorram B., Yazdi M., A new optimized thresholding method using ant colony algorithm for MR Brain image segmentation[J], J Digit Imaging, 32, 1, pp. 162-174, (2019); Li J., One way logistics distribution route optimization based on ant colony optimization algorithm, Electron Des Eng, 24, 10, pp. 68-70, (2016); Li Z.L., University L.J., Transportation S.O., Robust optimization of route in emergency logistics dynamic network based on ant colony algorithm, Technol Econ Areas Commun, 18, 4, (2016); Li S.L., Zhao R., Chen L.H., Research and analysis on the influencing factors of logistics cost based on ANP, Ind Technol Econ, 37, 6, pp. 108-118, (2018); Lim S.F.W.T., Jin X., Srai J.S., Consumer-driven e-commerce: a literature review, design framework, and research agenda on last-mile logistics models, Int J Phys Distrib Logist Manag, 48, 3, pp. 308-332, (2018); Liu J.P.L., Chen W.Q., The last mile” dilemma and the mobilization of farmers—an analysis of the predicament of local governance in the context of resource to the countryside, Chin Public Adm, 3, pp. 49-51, (2016); Liu J., Liu G.R., Path planning of mobile robot based on improved ant colony algorithm, Control Eng China, 31, 5, pp. 531-533, (2010); Liu M., Zhang F., Ma Y., Et al., Evacuation path optimization based on quantum ant colony algorithm, Adv Eng Inform, 30, 3, pp. 259-267, (2016); Ma Y.N., Gong Y.J., Xiao C.F., Et al., Path planning for autonomous underwater vehicles: an ant colony algorithm incorporating alarm pheromone[J], IEEE Trans Veh Technol, 68, 1, pp. 141-154, (2019); Marchet G., Melacini M., Perotti S., Et al., Business logistics models in omni-channel: a classification framework and empirical analysis, Int J Phys Distrib Logist Manag, 48, 4, pp. 439-464, (2018); Mavrovouniotis M., Yang S., Training neural networks with ant colony optimization algorithms for pattern classification, Soft Comput, 19, 6, pp. 1511-1522, (2015); Mei Y., Xie K., Evacuation strategy of emergent event in metro station based on the ELECTRE method, Granul Comput, 3, pp. 1-10, (2018); Najafi M., Eshghi K., Dullaert W., A multi-objective robust optimization model for logistics planning in the earthquake response phase, Transp Res Part E Logist Transp Rev, 49, 1, pp. 217-249, (2013); Nie J.J., Logistics distribution based on ant colony algorithm, the optimal path[J], Autom Instrum, 5, pp. 3-5, (2016); Wang B.Y., A study on the developmental strategies for “the last-kilometer delivery” of e-commerce logistics—take “novice station” as an example, J Jilin Teach Inst Eng Technol, 32, 1, pp. 47-49, (2016); Wang N., Empirical analysis on the model of e-commerce logistics of hazardous chemical products based on SWOT, Chem Eng Trans, 71, pp. 1261-1266, (2018); Wang Z., Polytechnic T., Conception of fresh farm produce cold chain logistics industry development strategy, Logist Technol, 3, pp. 47-52, (2016); Wu P.J., Lin K.C., Unstructured big data analytics for retrieving e-commerce logistics knowledge, Telemat Inform, 35, 1, pp. 237-244, (2018); Xin H., Tobacco logistics distribution route optimization based on improved ant colony algorithm, Technol Dev Enterp, 35, 7, pp. 77-81, (2016); Zeng M.R., Xi L., Xiao A.M., The free step length ant colony algorithm in mobile robot path planning, Adv Robot, 30, 23, (2016); Zhang J.M., Zhang D.X., Wang S., Path planning of robot based on ant colony optimization algorithm, Appl Mech Mater, 614, pp. 199-202, (2016); Zhang Y., Yu Y., Zhang S., Et al., Ant colony optimization for Cuckoo search algorithm for permutation flow shop scheduling problem[J], Syst Sci Control Eng Open Access J, 7, 1, pp. 20-27, (2019); Zhou J.X., Wang Y., Research on the model of corporate’s procurement management with the involvement of 3PL[J], Chin J Manag Sci, 25, 3, pp. 121-129, (2017)","Z. Feng; School of Commercial, Nantong Institute of Technology, Nan Tong, China; email: 2115709912@qq.com",null,"Springer",{"$nulls":5},1.4327643E7,null,null,null,"English","Soft Comput.","Article","Final",null,"Scopus","2-s2.0-85065669231"]
["Stickle B.; Hicks M.; Stickle A.; Hutchinson Z.","Stickle, Ben (56600574600); Hicks, Melody (57214319680); Stickle, Amy (57214319364); Hutchinson, Zachary (57515007100)","56600574600; 57214319680; 57214319364; 57515007100","Porch pirates: examining unattended package theft through crime script analysis",2020.0,"Criminal Justice Studies",33.0,2.0,null,79.0,95.0,16.0,14.0,"10.1080/1478601X.2019.1709780","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85078605126&doi=10.1080%2f1478601X.2019.1709780&partnerID=40&md5=ab35c48b2775c8ce781dcecdcb0c88e6","Criminal Justice Administration, Middle Tennessee State University, Murfreesboro, TN, United States; University Studies, Middle Tennessee State University, Murfreesboro, TN, United States","Stickle B., Criminal Justice Administration, Middle Tennessee State University, Murfreesboro, TN, United States; Hicks M., Criminal Justice Administration, Middle Tennessee State University, Murfreesboro, TN, United States; Stickle A., University Studies, Middle Tennessee State University, Murfreesboro, TN, United States; Hutchinson Z., Criminal Justice Administration, Middle Tennessee State University, Murfreesboro, TN, United States","Package theft is an emerging crime type due to the tremendous growth in online shopping and the delivery of goods directly to a home. Unattended delivery creates an opportunity for thieves to steal packages after delivery and before the resident collects them. It is believed that these types of incidents are increasing dramatically, and media attention has amplified awareness and concern of ‘porch pirates.’ Currently, little is known about unattended package theft and the present study represents the first known scholarly examination of this crime. Using Video Data Analysis to examine 67 YouTube videos of porch pirates engaged in criminal activity, the authors develop a Crime Script Analysis and identify Situational Crime Prevention (SCP) practices that can interrupt porch piracy. Findings indicate porch piracy occurs during daylight hours, at homes closer to a roadway, and most often with packages that can be easily seen from the roadway which are of medium size and usually have brand names on the box. Further, traditional SCP techniques such as fences, cameras, and guardians appear to have little impact on the thieves. Prevention techniques are discussed with the most promising including: increasing the risks, concealing packages, and removing packages. Additional findings, prevention techniques, and limitations are discussed. © 2019, © 2019 Informa UK Limited, trading as Taylor & Francis Group.","crime script; delivery theft; last-mile delivery; Package theft; porch pirate; unattended home delivery; video data analysis",{"$nulls":7},"Borrion H., Quality assurance in crime scripting, Crime Science, 2, 1, pp. 6-11, (2013); Bramsen I., How violence happens (or not): Situational conditions of violence and nonviolence in Bahrain, Tunisia, and Syria, Psychology of Violence, 8, 3, pp. 305-315, (2018); Brayley H., Cockbain E., Laycock G., The value of crime scripting: Deconstructing internal child sex trafficking, Policing, 5, 2, pp. 132-143, (2011); 11 Million U.S. Homeowners Experienced Package Theft Within the Last Year, August Home Study Reveals, (2016); 2019 Package Theft Statistics Report, (2019); Campo C., Watch out for ‘porch pirates’ who want to steal your holiday gift packages, (2017); Chiu Y.N., Leclerc B., Townsley M., Crime script analysis of drug manufacturing in clandestine laboratories: Implications for prevention, The British Journal of Criminology, 51, 2, pp. 355-374, (2011); Clarke R.V., Introduction, Situational crime prevention. Successful case studies, pp. 1-44, (1997); Clarke R.V., Situational crime prevention, Environmental criminology and crime analysis, (2017); Clarke R.V., Mayhew P., The British gas suicide story and its criminological implications, Crime and Justice, 10, pp. 79-116, (1988); Cohen L.E., Felson M., Social change and crime rate trends: A routine activity approach, American Sociological Review, 44, 4, pp. 588-608, (1979); Cornish D.B., The procedural analysis of offending and its relevance for situational prevention, Crime prevention studies, Volume 3, pp. 151-196, (1994); Cornish D.B., Clarke R.V., Opportunities, precipitators and criminal dispositions: A reply to Wortley’s critique of situational crime prevention, Theory and practice in situational crime prevention volume 16, (2003); Dabney D.A., Hollinger R.C., Dugan L., Who actually steals? A study of covertly observed shoplifters, Justice Quarterly, 21, 4, pp. 693-728, (2004); Edwards R., These are the top ten major metros for package theft, (2019); E-commerce share of total global retail sales from 2015 to 2021, (2018); Fischer C., New Texas law makes stealing packages off porches a felony, (2019); Gilmour N., Understanding money laundering. A crime script approach, The European Review of Organized Crime, 1, 2, pp. 35-56, (2014); Guerette R.T., The pull, push, and expansion of situational crime prevention evaluation: An appraisal of thirty-seven years of research, Evaluating crime reduction initiatives, volume 24, (2009); Hu W., Haag M., 90,000 packages disappear daily in N.Y.C. Is help on the way?, (2019); Jacobs B.A., Dealing crack: The social world of streetcorner selling, (1999); Jacques S., Bernasco W., Drug dealing: Amsterdam’s red light district, Cognition and crime: Offender decision-making and script analysis. crime science, (2013); Jordan B., Henderson A., Interaction analysis: Foundations and practice, The Journal of the Learning Sciences, 4, 1, pp. 39-103, (1995); Landis J.R., Koch G.G., The measurement of observer agreement for categorical data, Biometrics, 33, 1, pp. 159-174, (1977); Leclerc B., Wortley R., Smallbone S., Getting into the script of adult child sex offenders and mapping out situational prevention measures, Journal of Research in Crime and Delinquency, 48, 2, pp. 209-237, (2011); Leclerc C., New developments in script analysis for situational crime prevention: Moving beyond offender scripts, Cognition and crime: Offender decision-making and script analysis. crime science, (2013); Legewie N., Nassauer A., YouTube, Google, Facebook: 21st-century online video research and research ethics, Forum Qualitative Sozialforschung/Forum: Qualitative Social Research, 19, 3, pp. 21-28, (2018); Liebst L.S., Heinskou M.B., Ejbye-Ernst P., On the actual risk of bystander intervention: A statistical study based on naturally occurring violent emergencies, Journal of Research in Crime and Delinquency, 55, 1, pp. 27-50, (2018); Lindegaard M.R., Bernasco W., Lessons learned from crime caught on camera, Journal of Research in Crime and Delinquency, 55, 1, pp. 155-186, (2018); Mayhew P., Hough M., Situational crime prevention. The home office origins, The reasoning criminologist: Essays in honor of Ronald V. Clarke, pp. 15-29, (2012); McKinnon A.C., Tallam D., Unattended delivery to the home: An assessment of the security implications, International Journal of Retail & Distribution Management, 31, 1, pp. 30-41, (2003); Moeller K., Video-recorded retail cannabis trades in a low-risk marketplace: Trade Value and temporal patterns, Journal of Research in Crime and Delinquency, 55, 1, pp. 103-124, (2018); Moreto W.D., Provoked poachers? Applying a situational precipitator framework to examine the nexus between human-wildlife conflict, retaliatory killings, and poaching, Criminal Justice Studies, 32, 2, pp. 63-80, (2019); Mosselman F., Weenink D., Lindegaard M.R., Weapons, body postures, and the quest for dominance in robberies: A qualitative analysis of video footage, Journal of Research in Crime and Delinquency, 55, 1, pp. 3-26, (2018); Nassauer A., From peaceful marches to violent clashes: A micro-situational analysis, Social Movement Studies, 15, 5, pp. 515-530, (2016); Nassauer A., How robberies succeed or fail: Analyzing crime caught on CCTV, Journal of Research in Crime and Delinquency, 55, 1, pp. 125-154, (2018); Nassauer A., Situational dynamics and the emergence of violence in protests, Psychology of Violence, 8, 3, pp. 293-304, (2018); Nassauer A., Legewie N.M., Video Data Analysis: A methodological frame for a novel research trend, Sociological Methods & Research, 10, 10, pp. 1-40, (2018); Natarajan M., Clarke R.C., Carcach C., Ponce C., de Sanfeliu M., Escobar Polanco D., Shi M., Situational prevention and public transport crime in El Salvador, Crime Science, 4, 1, pp. 1-15, (2015); Ogonowski P., 10 ecommerce average order value statistics [Updated 2019, (2019); Osborne J.R., Capellan J.A., Examining active shooter events through the rational choice perspective and crime script analysis, Security Journal, 30, 3, pp. 880-902, (2017); How it works, (2018); Poyner B., Webb B., Crime free housing, (1991); Punakivi M., Yrjola H., Holmstrom J., Solving the last mile issue: Reception box or delivery box?, International Journal of Physical Distribution & Logistics Management, 31, 6, pp. 427-439, (2001); The 2017 package theft report: Porch pirates, purchase habits, and privacy, (2017); Stickle B.F., Metal scrappers and thieves: Scavenging for survival and profit, (2017); Sytsma V.A., Piza E.L., Script analysis of open-air drug selling: A systematic social observation of CCTV footage, Journal of Research in Crime and Delinquency, 55, 1, pp. 78-102, (2018); Tedeschi J.T., Felson R.B., Violence, aggression, and coercive actions, (1994); Tompson L., Chainey S., Profiling illegal waste activity: Using crime scripts as a data collection and analytical strategy, European Journal on Criminal Policy and Research, 17, 3, pp. 179-201, (2011); Tunley M., Button M., Shepherd D., Blackbourn D., Preventing occupational corruption: Utilizing situational crime prevention techniques and theory to enhance organisational resilience, Security Journal, 31, 1, pp. 21-52, (2018); Willison R., Siponen M., Overcoming the insider: Reducing employee computer crime through Situational Crime Prevention, Communications of the ACM, 52, 9, pp. 133-137, (2009); Willits D.W., Makin D.A., Show me what happened: Analyzing use of force through analysis of body-worn camera footage, Journal of Research in Crime and Delinquency, 55, 1, pp. 51-77, (2018); Wortley R., McFarlane M., The role of territoriality in crime prevention: A field experiment, Security Journal, 24, 2, pp. 149-156, (2011); Wright R., Decker S.H., Armed robbers in action: Stickups and street culture, (1997); Wright R.T., Decker S.H., Burglars on the job: Streetlife and residential break-ins, (1994); Yanowitz K.L., Yanowitz J.L., The role of gender in the generation of stalking scripts, Sex Roles, 66, 5-6, pp. 366-377, (2012)","B. Stickle; Department of Criminal Justice Administration, Middle Tennessee State University, Murfreesboro, 37132, United States; email: Ben.stickle@mtsu.edu",null,"Routledge",{"$nulls":5},"1478601X",null,null,null,"English","Crim. Justice Stud.","Article","Final",null,"Scopus","2-s2.0-85078605126"]
["Zhang H.; Liu Y.; Zhang Q.; Cui Y.; Xu S.","Zhang, Hao (57189490560); Liu, Yu (57205764174); Zhang, Qian (55883655500); Cui, Yan (57205701133); Xu, Shensi (57189515360)","57189490560; 57205764174; 55883655500; 57205701133; 57189515360","A Bayesian network model for the reliability control of fresh food e-commerce logistics systems",2020.0,"Soft Computing",24.0,9.0,null,6499.0,6519.0,20.0,17.0,"10.1007/s00500-020-04666-5","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85077893894&doi=10.1007%2fs00500-020-04666-5&partnerID=40&md5=4265162d6a4ce42a34de919d0534873e","Business School, Beijing Technology and Business University, Beijing, China","Zhang H., Business School, Beijing Technology and Business University, Beijing, China; Liu Y., Business School, Beijing Technology and Business University, Beijing, China; Zhang Q., Business School, Beijing Technology and Business University, Beijing, China; Cui Y., Business School, Beijing Technology and Business University, Beijing, China; Xu S., Business School, Beijing Technology and Business University, Beijing, China","This paper focuses on the reliability of intelligent logistics for fresh food e-commerce. Based on the development of fresh food e-commerce, this paper analyses the factors that influence the reliability of fresh food logistics from the aspects of information technology, facilities and equipment, personnel operation and external environment. A Bayesian network is used to analyse the influence of each factor on system reliability, and the degree of importance of each factor is calculated. Based on the importance of each influential factor in fresh food e-commerce logistics systems, an intelligent logistics model for reliability control of fresh food is established. The purpose of this model is to improve the economic efficiency and the intelligent level of the fresh food e-commerce logistics system on the premise of meeting the system reliability requirements. Finally, simulation results show that the developed intelligent logistics reliability control model can significantly improve the reliability of fresh food e-commerce logistics systems, and provide practical suggestions for fresh food e-commerce enterprises. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature.","Bayesian network; e-commerce logistics; Fresh food; Reliability","Bayesian networks; Electronic commerce; Bayesian network models; E-commerce enterprise; Economic efficiency; External environments; Fresh food; Influential factors; Intelligent level; System reliability; Reliability",{"$nulls":4},"Beijing Project of Philosophy and Social Science, (17GLB013); Beijing Talents foundation of Organization Department of Beijing Municipal Committee; Business Administration, (19005902053); Precision and Advanced Discipline Construction (Municipal); National Key Research and Development Program of China, NKRDPC, (2017YFC1600605); National Office for Philosophy and Social Sciences, NPOPSS, (15BGL202)","This study was funded by a Project of the National Key R&D Program of China (2017YFC1600605), a Beijing Project of Philosophy and Social Science (17GLB013), a Project of the National Social Science Foundation of China (15BGL202), a Beijing's “High-grade, Precision and Advanced Discipline Construction (Municipal)-Business Administration” Project (No. 19005902053) and a project of Beijing Talents foundation of Organization Department of Beijing Municipal Committee of the CPC. ","Ameknassi L., Ait-Kadi D., Rezg N., Integration of logistics outsourcing decisions in a green supply chain design: a stochastic multi-objective multi-period multi-product programming model, Int J Prod Econ, 182, pp. 165-184, (2016); Chen C., Liu X., Chen H.H., A rear-end collision risk evaluation and control scheme using a Bayesian network model, IEEE Trans Intell Transp, 99, pp. 264-284, (2018); Ersel D., Icen D., Fuzzy probability calculation with confidence intervals in Bayesian networks, Soft Comput, 20, 2, pp. 819-829, (2016); Hackl J., Kohler J., Reliability assessment of deteriorating reinforced concrete structures by representing the coupled effect of corrosion initiation and progression by Bayesian networks, Struct Saf, 62, pp. 12-23, (2016); Kaipia R., Dukovska-Popovska I., Loikkanen L., Creating sustainable fresh food supply chains through waste reduction, Int J Phys Distrib Logist, 43, 3, pp. 262-276, (2013); Kim H., Kim P., Reliability redundancy allocation problem considering optimal redundancy strategy using parallel genetic algorithm, Reliab Eng Syst Saf, 159, pp. 153-160, (2017); Lam C.Y., Ip W.H., An improved spanning tree approach for the reliability analysis of supply chain collaborative network, Enterp Inf Syst, 6, 4, pp. 405-418, (2012); Lessan J., Fu L., Wen C., A hybrid Bayesian network model for predicting delays in train operations, Comput Ind Eng, 127, pp. 1214-1222, (2018); Luque J., Straub D., Reliability analysis and updating of deteriorating systems with dynamic Bayesian networks, Struct Saf, 62, pp. 34-46, (2016); Manning L., Soon J.M., GAP framework for fresh produce supply, Br Food J, 115, 6, pp. 796-820, (2013); Mkrtchyan L., Podofillini L., Dang V.N., Methods for building conditional probability tables of Bayesian belief network from limited judgment: an evaluation for human reliability application, Reliab Eng Syst Saf, 151, pp. 93-112, (2016); Mokhtar E.H.A., Chateauneuf A., Laggoune R., Bayesian approach for the reliability assessment of corroded interdependent pipe networks, Int J Press Vessels Pip, 148, pp. 46-58, (2016); Nahman J., Peric D., Path-set based optimal planning of new urban distribution networks, Int J Electr Power, 85, pp. 42-49, (2017); Nakandala D., Lau H., Zhang J.J., Cost-optimization modelling for fresh food quality and transportation, Ind Manag Data Syst, 116, 3, pp. 564-583, (2016); Nakandala D., Samaranayake P., Lau H., Et al., Modelling information flow and sharing matrix for fresh food supply chains, Bus Process Manag J, 23, 1, pp. 108-129, (2017); Okaro I.A., Tao L.B., Reliability analysis and optimisation of subsea compression system facing operational covariate stresses, Reliab Eng Syst Saf, 156, pp. 159-174, (2016); Oliveira S.C., Cobre J., Ferreira T.D.P., A Bayesian approach for the reliability of scientific co-authorship networks with emphasis on nodes, Soc Netw, 48, pp. 110-115, (2017); Rijpkema W.A., Rossi R., van der Vorst J.G.A.J., Effective sourcing strategies for perishable product supply chains, Int J Phys Distrib Logist, 44, 6, pp. 494-510, (2014); Sharma S., Pai S.S., Analysis of operating effectiveness of a cold chain model using Bayesian networks, Bus Process Manag J, 21, 4, pp. 722-742, (2015); Sharma S., Routroy S., Modeling information risk in supply chain using Bayesian networks, J Enterp Inf Manag, 29, 2, pp. 238-254, (2016); Srivastava S.K., Chaudhuri A., Srivastava R.K., Propagation of risks and their impact on performance in fresh food retail, Int J Logist Manag, 26, 3, pp. 568-602, (2015); Walter G., Aslett L.J.M., Coolen F.P.A., Bayesian nonparametric system reliability using sets of priors, Int J Approx Reason, 80, pp. 67-88, (2017); Xu X.F., Hao J., Deng Y., Wang Y., Design optimization of resource combination for collaborative logistics network under uncertainty, Appl Soft Comput, 560, 7, pp. 684-691, (2017); Xu X.F., Hao J., Yu L., Deng Y., Fuzzy optimal allocation model for task-resource assignment problem in collaborative logistics network, IEEE Trans Fuzzy Syst, 27, 5, pp. 1112-1125, (2019); Zhang H., Wang M., Tang M., Et al., The reliability measures model of multilayer urban distribution network, Soft Comput, (2017)","Q. Zhang; Business School, Beijing Technology and Business University, Beijing, China; email: ZHANG_Q_2018@163.com",null,"Springer",{"$nulls":5},1.4327643E7,null,null,null,"English","Soft Comput.","Article","Final",null,"Scopus","2-s2.0-85077893894"]
["Jat M.N.; Jajja M.S.S.","Jat, Mohsin Nasir (57200910536); Jajja, Muhammad Shakeel Sadiq (56102468700)","57200910536; 56102468700","TCS: ‘Hazir SubKuch’—Making Everything Present",2020.0,"Asian Journal of Management Cases",17.0,1.0,null,17.0,35.0,18.0,0.0,"10.1177/0972820119892738","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85078303279&doi=10.1177%2f0972820119892738&partnerID=40&md5=ba88e1bda74fbd4924415b40e9a29c15","Edwards School of Business, University of Saskatchewan, Saskatoon, SK, Canada; Suleman Dawood School of Business, Lahore University of Management Sciences, Lahore, Pakistan","Jat M.N., Edwards School of Business, University of Saskatchewan, Saskatoon, SK, Canada; Jajja M.S.S., Suleman Dawood School of Business, Lahore University of Management Sciences, Lahore, Pakistan","The case describes the journey of TCS as it became Pakistan’s leading logistics service provider. It highlights how and when TCS acquired different logistics and other value-adding capabilities and how these capabilities, in turn, complimented the diverse logistics services that TCS offered to a wide variety of businesses. TCS had been offering a top-notch Express and Logistics service around Pakistan for 30 years. TCS started as a company providing secure distribution of letters and packages. Customers perceived TCS as a shipping solution provider for all their goods transportation needs which included parcels, documents, E-commerce products and even their groceries. Table 1 of the case study highlights that TCS had taken up some unique and new initiatives. TCS handled four main clientele areas: Corporate, Consumer, International and E-commerce. For consumer wing, TCS oversaw bookings of documents and parcels at the express centres, door-to-door containerized shipments, domestic and international air ticketing, visa application drop box facility for various countries and financial services in the form of insurance plans. On the corporate side, TCS provided warehousing and distribution, digital printing and bulk mail solutions. International and e-commerce both catered consumer and corporate segments. Over the last decade, TCS had established a warehousing and distribution wing and a mail management and printing facility. Other ventures and services that TCS offered were Visatronix, Hazir, Home Movers, E-COM, TCS Aviation, Mail Management System, Warehouse and Distribution, Intiana, Sentiments express and Octra. The case focusses on the decision of whether or not to run an ambitious new logistics service, that is, Hazir SubKuch (HSK), meant to deliver anything non-prohibited that a customer wanted, on a crowdsourcing model. In the proposed crowdsourcing model, after training and evaluation, anyone could assume the role of a customer service provider by connecting to the system remotely. Similarly, pickup and delivery jobs could be performed under an Uber-like model by anyone who owned a ride and had smartphone connectivity. The service was a brainchild of the new CEO, hired by the founder and chairman as part of the new management team to bring a fresh dynamism in the company. © 2020 Lahore University of Management Sciences.","business model innovation; crowdsourcing architecture; last mile delivery; Logistics",{"$nulls":7},"Mehdi T., An overview of the 2008 general elections, Dawn, (2013)","M.S.S. Jajja; Suleman Dawood School of Business, Lahore University of Management Sciences, Lahore, Pakistan; email: ssj@lums.edu.pk",null,"Sage Publications India Pvt. Ltd",{"$nulls":5},9728201.0,null,null,null,"English","Asian J. Manage. Cases","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85078303279"]
["Van Asch T.; Dewulf W.; Kupfer F.; Cárdenas I.; Van de Voorde E.","Van Asch, Thomas (57211641368); Dewulf, Wouter (57191031550); Kupfer, Franziska (56010172500); Cárdenas, Ivan (57191038157); Van de Voorde, Eddy (6602230250)","57211641368; 57191031550; 56010172500; 57191038157; 6602230250","Cross-border e-commerce logistics – Strategic success factors for airports",2020.0,"Research in Transportation Economics",79.0,null,100761.0,null,null,null,23.0,"10.1016/j.retrec.2019.100761","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85074722984&doi=10.1016%2fj.retrec.2019.100761&partnerID=40&md5=83865de46ae53feb3aa43d9008ae074c","Department of Transport and Regional Economics, University of Antwerp, Prinsstraat 13, Antwerp, 2000, Belgium","Van Asch T., Department of Transport and Regional Economics, University of Antwerp, Prinsstraat 13, Antwerp, 2000, Belgium; Dewulf W., Department of Transport and Regional Economics, University of Antwerp, Prinsstraat 13, Antwerp, 2000, Belgium; Kupfer F., Department of Transport and Regional Economics, University of Antwerp, Prinsstraat 13, Antwerp, 2000, Belgium; Cárdenas I., Department of Transport and Regional Economics, University of Antwerp, Prinsstraat 13, Antwerp, 2000, Belgium; Van de Voorde E., Department of Transport and Regional Economics, University of Antwerp, Prinsstraat 13, Antwerp, 2000, Belgium","E-commerce has become a real game-changer in the air cargo industry and is forecasted to be the main growth driver in the following years. Airlines, forwarders, integrators and airports are trying to increase their market share in this growing market and hence develop strategies to attract as much e-commerce activities as possible. This paper investigates the cross-border e-commerce market from the airport's perspective. First, a market analysis is carried out and an overview of the air cargo industry is given. Moreover, the relevance of e-commerce for airports is highlighted. Second, by means of a literature review, the potential factors on which airports can focus to attract cross-border e-commerce are identified. Those factors are then verified by conducting structured interviews with different actors involved in the cross-border e-commerce air transport chain and as well as by performing an AHP analysis. As a result the following factors are identified as an absolute prerequisite to develop cross-border e-commerce at an airport: ability to pre-clear e-commerce goods, high airlift and land capacity. Furthermore, the e-commerce market should be facilitated by seamless data exchange. The outcome of this research will be relevant for the industry as it will enable airports to check whether their strategy is focusing on the right critical success factors to boost the local e-commerce cargo flows. © 2019 Elsevier Ltd","Air cargo; Airport competition; Airport competitiveness; Airport strategy; Cross-border e-commerce",{"$nulls":7},"Adenigbo J.A., Factors influencing cargo agents choice of operations in Abuja airport, Nigeria, Journal of Air Transport Management, 55, pp. 113-119, (2016); Adikariwattage V., de Barros A.G., Wirasinghe S.C., Ruwanpura J., Airport classification criteria based on passenger characteristics and terminal size, Journal of Air Transport Management, 24, pp. 36-41, (2012); Airbus, Global market Forecast. Toulouse, France, (2015); Alkaabi K.A., Debbage K.G., The geography of air freight: Connections to U.S. metropolitan economies, Journal of Transport Geography, 19, pp. 1517-1529, (2011); Amaruchkul K., Lorchirachoonkul V., Air-cargo capacity allocation for multiple freight forwarders, Transportation Research Part E Logist. Transp. Rev., 47, pp. 30-40, (2011); Ankersmit S., Rezaei J., Tavasszy L., The potential of horizontal collaboration in airport ground freight services, Journal of Air Transport Management, 40, pp. 169-181, (2014); Asosheh A., Shahidi-Nejad H., Khodkari H., A model of a localized cross-border E-commerce, iBusiness, 4, pp. 136-145, (2012); ATAG, Aviation: Benefits without borders 2018. Geneva, Switzerland, (2018); Bevilacqua M., Braglia M., The analytic hierarchy process applied to maintenance strategy selection, Reliability Engineering & System Safety, 70, pp. 71-83, (2000); Boeing, World air cargo Forecast 2018-2037. Seattle, USA, (2018); Boonekamp T., Burghouwt G., Measuring connectivity in the air freight industry, Journal of Air Transport Management, 61, pp. 81-94, (2017); Boujelbene Y., Derbel A., The performance analysis of public transport operators in Tunisia using AHP method, Procedia Computer Science, 73, pp. 498-508, (2015); Bowen J.T., The geography of freighter aircraft operations in the Pacific Basin, Journal of Transport Geography, 12, pp. 1-11, (2004); Budd L., Ison S., The role of dedicated freighter aircraft in the provision of global airfreight services, Journal of Air Transport Management, 61, pp. 34-40, (2017); Burghouwt G., Poort J., Ritsema H., Lessons learnt from the market for air freight ground handling at amsterdam airport schiphol, Journal of Air Transport Management, 41, pp. 56-63, (2014); Cardenas I., Beckers J., Vanelslander T., E-commerce last-mile in Belgium: Developing an external cost delivery index, Research in Transportation Business & Management, 24, pp. 123-129, (2017); Cardenas I., Borbon-Galvez Y., Verlinden T., Van De Voorde E., Vanelslander T., Dewulf W., City logistics, urban goods distribution and last mile delivery and collection, Competition and Regulation in Network Industries, 18, pp. 22-43, (2017); Cardenas I., Vanelslander T., Smet C., Dewulf W., Beckers J., The E-commerce parcel delivery market and the implications of home B2C deliveries, International Journal of Transport Economics, 44, pp. 235-256, (2017); Chu H.C., Exploring preference heterogeneity of air freight forwarders in the choices of carriers and routes, Journal of Air Transport Management, 37, pp. 45-52, (2014); Dewulf W., Meersman H., Van de Voorde E., From carpet sellers to cargo stars: Analyzing strategies of air cargo carriers, Journal of Air Transportation Studies, 5, pp. 96-119, (2014); Ecommerce Europe, European Ecommerce report 2018 edition - a word from Ecommerce Europe. Amsterdam, The Netherlands, (2018); Ecommerce Foundation, Global Ecommerce report 2017. 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The impact of air cargo operations on departure on-time performance for combination carriers, Transportation Research Part A, 1219, pp. 214-223, (2019); Larrode E., Muerza V., Villagrasa V., Analysis model to quantify potential factors in the growth of air cargo logistics in airports, Transportation Research Procedia, 33, pp. 339-346, (2018); Li Z., Bookbinder J.H., Elhedhli S., Optimal shipment decisions for an airfreight forwarder: Formulation and solution methods, Transportation Research Part C: Emerging Technologies, 21, pp. 17-30, (2012); Lieshout R., Malighetti P., Redondi R., Burghouwt G., The competitive landscape of air transport in Europe, Journal of Transport Geography, 50, pp. 68-82, (2016); Lotti R., Caetano M., The airport choice of exporters for fruit from Brazil, Journal of Air Transport Management, 70, pp. 104-112, (2018); Lo W.W.L., Wan Y., Zhang A., Empirical estimation of price and income elasticities of air cargo demand: The case of Hong Kong, Transportation Research Part A Policy Pract., 78, pp. 309-324, (2015); Malighetti P., Martini G., Redondi R., Scotti D., The geography of integrators' air transport networks in Europe, (2016); Matsumoto H., International urban systems and air passenger and cargo flows: Some calculations, Journal of Air Transport Management, 10, pp. 241-249, (2004); McKinsey & Company, McKinsey - future of air cargo 2025 - what are the latest global market developments and trends.pdf. 10th Air Cargo Handling Conference, Brussels, Belgium, (2018); Meersman H., Pauwels T., Struyf E., de Voorde E.V., Vanelslander T., Ground handling in a changing market. The case of Brussels Airport, Res. Transp. Bus. Manag., 1, pp. 128-135, (2011); Moertini V.S., Small Medium Enterprises: On Utilizing Business-to-Business e-Commerce to Go Global, Procedia Economic and Finance, 4, pp. 13-22, (2012); Njoya E.T., Niemeier H.M., Do dedicated low-cost passenger terminals create competitive advantages for airports?, Res. Transp. Bus. Manag., 1, pp. 55-61, (2011); Oosterlynck S., Swyngedouw E., Noise reduction: The postpolitical quandary of night flights at Brussels Airport, Environment & Planning A, 42, pp. 1577-1594, (2010); Park Y., Choi J.K., Zhang A., Evaluating competitiveness of air cargo express services, Transportation Research Part E Logist. Transp. Rev., 45, pp. 321-334, (2009); Popescu A., Keskinocak P., al Mutawaly I., The air cargo industry, Intermodal transportation: Moving freight in a global economy, pp. 208-237, (2011); Saaty T.L., Scenarios and priorities in transport planning: Application to the Sudan, Transportation Research, 11, pp. 343-350, (1977); WTO, E-commerce in developing countries - opportunities and challenges for small and medium-sized enterprises. Geneva, Switzerland, (2013); Zhang A., Zhang Y., A model of air cargo liberalization: Passenger vs. all-cargo carriers, Transportation Research Part E Logist. Transp. Rev., 38, pp. 175-191, (2002); Zhang A., Zhang Y., Issues on liberalization of air cargo services in international aviation, Journal of Air Transport Management, 8, pp. 275-287, (2002)","T. Van Asch; Department of Transport and Regional Economics, University of Antwerp, Antwerp, Prinsstraat 13, 2000, Belgium; email: Thomas.VanAsch@uantwerp.be",null,"Emerald Group Holdings Ltd.",{"$nulls":5},7398859.0,null,null,null,"English","Res. Transp. Econ.","Article","Final",null,"Scopus","2-s2.0-85074722984"]
["Mao J.; Hong D.; Ren R.; Li X.; Wang J.; Nasr E.S.A.","Mao, Jia (52763701500); Hong, Dou (57217392456); Ren, Runwang (57217392252); Li, Xiangyu (57192497349); Wang, Ju (35195033700); Nasr, Emad S. Abouel (23012625000)","52763701500; 57217392456; 57217392252; 57192497349; 35195033700; 23012625000","Driving Conditions of New Energy Logistics Vehicles Using Big Data Technology",2020.0,"IEEE Access",8.0,null,9130673.0,123891.0,123903.0,12.0,6.0,"10.1109/ACCESS.2020.3005529","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85088692527&doi=10.1109%2fACCESS.2020.3005529&partnerID=40&md5=aaa82ef1ee7376c18694e356e7316a21","School of Transportation, Jilin University, Changchun, China; College of Automotive Engineering, Jilin University, Changchun, China; Industrial Engineering Department, College of Engineering, King Saud University, Riyadh, Saudi Arabia","Mao J., School of Transportation, Jilin University, Changchun, China; Hong D., School of Transportation, Jilin University, Changchun, China; Ren R., School of Transportation, Jilin University, Changchun, China; Li X., College of Automotive Engineering, Jilin University, Changchun, China; Wang J., College of Automotive Engineering, Jilin University, Changchun, China; Nasr E.S.A., Industrial Engineering Department, College of Engineering, King Saud University, Riyadh, Saudi Arabia","With the development of e-commerce and trade, China's logistics transportation demand has increased significantly. To improve the operation efficiency of new energy trucks, logistics transportation companies need scientific management methods. They need to analyze a large number of real driving conditions for new energy trucks. Additionally, to reduce new energy trucks' energy consumption and pollutant emissions, automobile manufacturers have increased the research and development of new energy trucks, and the analysis of new energy truck driving conditions is the basis for the technical development and evaluation of new models. The research in this article is based on an actual project of an automobile manufacturing company, consulting a large amount of relevant domestic and foreign literature, summarizing the current status of driving conditions at home and abroad, explaining the principle of data collection for the driving conditions of new energy trucks, and developing in-vehicle data for driving conditions based on the principle transmission method and remote transmission method. Using the membership function and K-means clustering algorithm to determine the attribute characteristics of the new energy truck driving condition analysis, a truck driving condition analysis model is built, the software function of the model is designed, and a small amount of sample data is used to import the model instance to verify the model effectiveness. Finally, based on the constructed new energy truck driving condition analysis model, big data technology was used to perform a big data analysis experiment on the actual operation data of 200 trucks of an automobile manufacturing enterprise. The Spark big data calculation framework was used to perform stream calculation and offline analysis calculations on a large amount of data from the new energy trucks. The results show that the operating efficiency of the new energy truck driving condition analysis method using big data technology is significantly higher than that of traditional technology. This study provides a theoretical basis for controlling the energy consumption and pollutant emissions of new energy trucks in logistics transportation, and provides management and logistics support for transportation logistics companies. The technical development and evaluation of the company's new models provided data references.  © 2013 IEEE.","big data analysis; clustering algorithm; driving conditions; membership function; New energy trucks","Automobile manufacture; Automobiles; Automotive industry; Big data; Data streams; Energy utilization; Function evaluation; Industrial research; K-means clustering; Membership functions; Pollution; Trucks; Vehicle transmissions; Automobile manufacturers; Automobile manufacturing; Automobile manufacturing enterprise; Logistics transportations; Operation efficiencies; Research and development; Scientific management; Transportation-logistics; Data flow analysis",{"$nulls":4},"Education Department of Jilin Province, (JJKH20190239SK)","This work was supported by the Science and Technology Research Program of the Jilin Provincial Education Department under Grant JJKH20190239SK.","Xiaojuan Y., Jian W., Construction and research on driving conditions of heavy-duty passenger cars in Beijing, J. Environ. Eng. Technol., 5, 6, pp. 455-463, (2015); Kent J.H., Allen G.H., Rule G., A driving cycle for Sydney, Transp. Res., 12, 3, pp. 147-152, (1978); Tzirakis E., Pitsas K., Vehicle emissions and driving cycles: Comparison of the Athens driving cycle (ADC) with ECE-15 and European driving cycle (EDC), Global Nest J., 8, 3, pp. 282-290, (2006); Andre M., Joumard R., Vidon R., Tassel P., Perret P., Real-world European driving cycles, for measuring pollutant emissions from highand low-powered cars, Atmos. Environ., 40, 31, pp. 5944-5953, (2006); Nesamani K.S., Subramanian K.P., Development of a driving cycle for intra-city buses in Chennai, India, Atmos. Environ., 45, 31, pp. 5469-5476, (2011); Kudoh Y., Matsuhashi K., Kondo Y., Kobayashi S., Moriguchi Y., Yagita H., Statistical analysis on transition of actual fuel consumption by improvement of Japanese 10 15 mode fuel consumption, J. Jpn. Inst. Energy, 87, 11, pp. 930-937, (2008); Fuxing Z., Study on Driving Conditions of Urban Vehicles, pp. 89-97, (2005); Zhiyuan H., Yan Q., Yiqiang T., Diming L., Construction of driving conditions of Shanghai passenger cars based on large samples, Tongji Univ Nat. Sci., 43, 10, pp. 1523-1527, (2015); Dianyu Z., Xiaogang W., Han C., Yanyu D., Construction of driving conditions of passenger cars in Harbin city, J. Highw. Transp. Res. Dev., 34, 4, pp. 101-107, (2017); Brady J., O'Mahony M., Development of a driving cycle to evaluate the energy economy of electric vehicles in urban areas, Appl. Energy, 177, pp. 165-178, (2016); Hu X., Method for identifyingHEVdriving conditions based on historical data of operating conditions, M.S. Thesis, Dept. Automot. Eng., Dalian Univ. Technol., Dalian, China, (2015); Yaohua L., Peng L., Wei Y., Jingyu L., Study on driving conditions of Xi'an pure electric city bus, China Sci. 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Transp, 29, 4, pp. 130-137, (2016); Tang M., Li Z., Tian G., A Data-Driven-Based wavelet support vector approach for passenger fiow forecasting of the metropolitan hub, IEEE Access, 7, pp. 7176-7183, (2019); Taoying L., Research on Cluster Analysis Methods in the Field of Trans-portation, pp. 120-126, (2014); Tian G., Zhang H., Feng Y., Wang D., Peng Y., Jia H., Green decoration materials selection under interior environment characteristics: A grey-correlation based hybrid MCDM method, Renew. Sustain. Energy Rev., 81, pp. 682-692, (2018); Yihui W., Ying C., Yanning Z., Yuntao P., Review of K-means algorithm research, New Technol. Lib Inf. Ser., 5, 5, pp. 28-35, (2011); Yang Z., Li H., Haodong Z., An improved K-means dynamic clustering algorithm, J. Chongqing Norm. Univ., 33, 1, pp. 97-101, (2016); Tian G., Hao N., Zhou M., Pedrycz W., Zhang C., Ma F., Li Z., Fuzzy grey choquet integral for evaluation of multicriteria decision making problems with interactive and qualitative indices, IEEE Trans. Syst., Man, Cybern. Syst., Early Access, Apr. 12, (2020); Yong W., Jing T., Qinfei R., Chaoyan Y., Efficient algorithm for determining K-means optimal clustering number, J. Comput. Appl., 34, 5, pp. 1331-1335, (2014); Lili T., Method for text feature selection based on information entropy and dynamic clustering, Comput. Eng. Appl., 51, 19, pp. 152-157, (2015); Weizhong Z., Huifang M., Yanxiang F., Zhongzhi S., Design of parallel K-means clustering algorithm based on cloud computing platform Hadoop, Comput. Sci., 38, 10, pp. 166-168, (2011); Franks B., Hai H., Driving Big Data, pp. 103-114, (2013); Karau H., Daoyuan W., Spark's Fast Big Data Analysis, pp. 125-130, (2015); Jialin W., Yang X., Inside Analysis and Source Code of Spark Streaming Technology, pp. 89-93, (2017); Yan L., Parallelization of data mining algorithms based on distributed platforms Spark and YARN, M.S. Thesis, Dept. Electron. Eng., Sun Yatsen Univ., Guangzhou, China, (2014); Karau H., Daoyuan W., Spark's Fast Big Data Analysis, pp. 167-172, (2015)","J. Mao; School of Transportation, Jilin University, Changchun, China; email: maojia@jlu.edu.cn",null,"Institute of Electrical and Electronics Engineers Inc.",{"$nulls":5},2.1693536E7,null,null,null,"English","IEEE Access","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85088692527"]
["Olagunju T.; Oyebode O.; Orji R.","Olagunju, Tolulope (57217990695); Oyebode, Oladapo (57205718069); Orji, Rita (36802416800)","57217990695; 57205718069; 36802416800","Exploring Key Issues Affecting African Mobile eCommerce Applications Using Sentiment and Thematic Analysis",2020.0,"IEEE Access",8.0,null,9108261.0,114475.0,114486.0,11.0,21.0,"10.1109/ACCESS.2020.3000093","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85087836358&doi=10.1109%2fACCESS.2020.3000093&partnerID=40&md5=8519ea3d8d14a124065011152c253123","Faculty of Computer Science, Dalhousie University, Halifax, B3H 4R2, Canada","Olagunju T., Faculty of Computer Science, Dalhousie University, Halifax, B3H 4R2, Canada; Oyebode O., Faculty of Computer Science, Dalhousie University, Halifax, B3H 4R2, Canada; Orji R., Faculty of Computer Science, Dalhousie University, Halifax, B3H 4R2, Canada","Mobile eCommerce applications are increasingly becoming popular for shopping online in Africa, since the means of accessing the Internet is mostly through mobile devices. This presents an opportunity to explore and understand the key issues affecting African mobile eCommerce applications by performing sentiment analysis of users reviews from seven top African mobile eCommerce applications (i.e., Jiji Nigeria, Jumia, Jiji Kenya, Konga, Takealot, KiliMall and Jiji Uganda). We implement two sentiment analysis approaches, which are Linguistic Inquiry Word Count (LIWC) and Machine Learning (ML), to classify user reviews into positive or negative sentiment polarity. Specifically, we compare five ML algorithms and the LIWC with respect to their performance, and also conduct thematic analysis to uncover the positive and negative factors affecting African mobile eCommerce. Our results show that LIWC is the best performing method with 86.7% F1-score. Our thematic analysis reveals various business, legal, and technology issues, as well as positive factors such as ease of use, fast delivery time, and affordable items. Finally, we offer recommendations on how to tackle the negative issues. © 2013 IEEE.","Africa; eCommerce; lexicon-based approach; machine learning; mobile applications; sentiment analysis; user reviews","Electronic commerce; Sentiment analysis; Analysis approach; Delivery time; Ml algorithms; Mobile e-commerce; Negative sentiments; Technology issues; Thematic analysis; User reviews; Factor analysis",{"$nulls":4},"Natural Sciences and Engineering Research Council of Canada, NSERC","This work is supported by the NSERC Discovery Grant awarded to Dr. Rita Orji.","Godsay M., The process of sentiment analysis: A study, Int. J. Comput. Appl., 126, 7, pp. 26-30, (2015); Guzman E., Maalej W., How do users like this feature? A fine grained sentiment analysis of app reviews, Proc. Ieee 22nd Int. Requirements Eng. Conf. (RE), pp. 153-162, (2014); Oyebode O., Orji R., Deconstructing persuasive strategies in mental health Apps based on user reviews using natural language processing, Proc. Ceur Int. Work. Behav. Chang. Support Syst., pp. 1-13, (2020); Etzo S., Collender G., The mobile phone revolution' in Africa: Rhetoric or reality?, Afr. Affairs, 109, 437, pp. 659-668, (2010); James J., Versteeg M., Mobile phones in Africa: How much do we really know?, Social Indicators Res., 84, 1, pp. 117-126, (2007); (2020); Pennebaker J.W., Boyd R.L., Jordan K., Blackburn K., The Development and Psychometric Properties of LIWC2015, (2015); Nkwo M.S., Orji R., Nwokeji J.C., E-Commerce personalization in Africa: A comparative analysis of Jumia and Konga personalized persuasive strategies for behaviour change, Proc. Ppt Persuasive Conf., pp. 68-76, (2018); Okoli C., Mbarika V.A.W., A framework for assessing e-Commerce in sub-Saharan Africa, J. Global Inf. Technol. Manage., 6, 3, pp. 44-66, (2003); Oyebode O., Orji R., Social media and sentiment analysis: The Nigeria presidential election 2019, Proc. Ieee 10th Annu. Inf. Technol., Electron. Mobile Commun. Conf. (IEMCON), pp. 140-146, (2019); Oyebode O., Orji R., Detecting factors responsible for diabetes prevalence in Nigeria using social media and machine learning, Proc. 15th Int. Conf. Netw. Service Manage. (CNSM), pp. 1-4, (2019); Ji X., Chun S.A., Geller J., Monitoring public health concerns using Twitter sentiment classifications, Proc. Ieee Int. Conf. Healthcare Informat., pp. 335-344, (2013); Korkontzelos I., Nikfarjam A., Shardlow M., Sarker A., Ananiadou S., Gonzalez G.H., Analysis of the effect of sentiment analysis on extracting adverse drug reactions from tweets and forum posts, J. Biomed. Informat., 62, pp. 148-158, (2016); Yang L., Li Y., Wang J., Sherratt R.S., Sentiment analysis for e-Commerce product reviews in Chinese based on sentiment lexicon and deep learning, Ieee Access, 8, pp. 23522-23530, (2020); Kumar K.L.S., Desai J., Majumdar J., Opinion mining and sentiment analysis on online customer review, Proc. Ieee Int. Conf. Comput. Intell. Comput. Res. (ICCIC), pp. 1-4, (2016); Priyadharsini R.L., College B.H., Felciah M.L.P., Recommendation system in E-commerce using sentiment analysis, Int. J. Eng. Trends Technol., 49, 7, pp. 445-450, (2017); Cosma G., Acampora G., A computational intelligence approach to efficiently predicting review ratings in e-commerce, Appl. Soft Comput., 44, pp. 153-162, (2016); Sari P.K., Alamsyah A., Wibowo S., Measuring e-Commerce service quality from online customer review using sentiment analysis, J. Phys. Conf. Ser., 971, (2018); Peng Q., Zhong M., Detecting spam review through sentiment analysis, J. Softw., 9, 8, (2014); Del Pilar S.-Z.M., Lopez-Lopez E., Valencia-Garcia R., Aussenac-Gilles N., Almela A., Alor-Hernandez G., A study on LIWC categories for opinion mining in Spanish reviews, J. Inf. Sci., 40, 6, pp. 749-760, (2014); Miller G.A., WordNet: A lexical database for English, Commun. Acm, 38, 11, pp. 39-41, (1995); Powers D.M.W., Evaluation: From precision, recall and F-measure to ROC, informedness, markedness &correlation, J. Mach. Learn. Technol., 2, 1, pp. 37-63, (2011); Braun V., Clarke V., Using thematic analysis in psychology, Quali-tative Res. Psychol., 3, 2, pp. 77-101, (2006); Orji R., Oyibo K., Lomotey R.K., Orji F.A., Socially-driven persuasive health intervention design: Competition, social comparison, and cooperation, Health Informat. J., 25, 4, pp. 1451-1484, (2019); Kaasinen E., User acceptance of mobile services-value, ease of use, trust and ease of adoption, Proc. Dissertation. Tampere, Finland: Vtt Technical Research Centre of Finland, pp. 45-70, (2005); Gangeshwer D.K., E-commerce or Internet marketing:Abusiness review from Indian context, Int. J. U-e-Service, Sci. Technol., 6, 6, pp. 187-194, (2013); Baden S., Barber C., The Impact of the Second-Hand Clothing Trade on Developing Countries, pp. 1-37, (2005); Nayebi F., Desharnais J.-M., Abran A., The state of the art of mobile application usability evaluation, Proc. 25th Ieee Can. Conf. Electr. Comput. Eng. (CCECE), pp. 1-4, (2012); Olagunju K., Evaluating traffic congestion in developing countries-A case study of Nigeria, 2015 Chartered Institute of Logistics and Transport (CILT), (2015); Makokha B.E., Security strategies applicable in resolving Traffic congestion in cities, case of Jogoo road, Nairobi city county, Kenya, Kenyatta Univ., Nairobi, Kenya, Tech. Rep., pp. 1-91, (2018); Nakarada-Kordic I., Lobb B., Effect of perceived attractiveness of Web interface design on visual search of Web sites, Proc. Acm Int. Conf., 94, pp. 25-27, (2005); Cyr D., Head M., Ivanov A., Design aesthetics leading to m-loyalty in mobile commerce, Inf. Manage., 43, 8, pp. 950-963, (2006); Ilobinso I., Paving the path to an enhanced consumer protection for the Nigerian online market: Theories and concepts, Nnamdi Azikiwe Univ. J. Int.Law Jurisprudence, 8, 2, pp. 81-91, (2017); Jobodwana Z.N., E-commerce and mobile commerce in South Africa: Regulatory challenges, J. Int. Commercial Law Technol., 4, 4, pp. 287-298, (2009); Ndulue C., Orji R., Developing persuasive mobile games for African rural audiences, Proc. Adjunct Publication 27th Conf. User Modeling, Adaptation Personalization Umap Adjunct, pp. 179-184, (2019)","T. Olagunju; Faculty of Computer Science, Dalhousie University, Halifax, B3H 4R2, Canada; email: tolagunju@dal.ca",null,"Institute of Electrical and Electronics Engineers Inc.",{"$nulls":5},2.1693536E7,null,null,null,"English","IEEE Access","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85087836358"]
["Bayanova A.R.; Sivova I.V.; Kamasheva Y.L.; Popova O.V.; Semyanov E.V.; Shagieva R.V.; Yusupov I.M.","Bayanova, Almira R. (57204968815); Sivova, Irina V. (57211803408); Kamasheva, Yuliya L. (56518300200); Popova, Olga V. (56494433900); Semyanov, Evgeny V. (57211468619); Shagieva, Rozalina V. (56114745000); Yusupov, Il’Dar M. (57224113677)","57204968815; 57211803408; 56518300200; 56494433900; 57211468619; 56114745000; 57224113677","Student online services consumption: Routine practices or mistrust to digital service?",2020.0,"Contemporary Educational Technology",11.0,1.0,null,47.0,54.0,7.0,19.0,"10.30935/cet.641767","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85078317178&doi=10.30935%2fcet.641767&partnerID=40&md5=b054d790941f2b254a870cdece155dad","Kazan (Volga region) Federal University, Russian Federation; Kazan National Research Technical University named after A.N. Tupolev – KAI, Russian Federation; Gzhel State University, Russian Federation; Kazan Innovative University named after V. G. Timiryasov, Russian Federation; Financial University under the Government of the Russian Federation, Russian Federation; Russian New University (RosNOU), Russian Federation; Russian Customs Academy, Russian Federation","Bayanova A.R., Kazan (Volga region) Federal University, Russian Federation, Kazan National Research Technical University named after A.N. Tupolev – KAI, Russian Federation; Sivova I.V., Gzhel State University, Russian Federation; Kamasheva Y.L., Kazan Innovative University named after V. G. Timiryasov, Russian Federation; Popova O.V., Financial University under the Government of the Russian Federation, Russian Federation; Semyanov E.V., Russian New University (RosNOU), Russian Federation; Shagieva R.V., Russian Customs Academy, Russian Federation; Yusupov I.M., Kazan Innovative University named after V. G. Timiryasov, Russian Federation","The article aims to study the practices of students’ use of services in the conditions of digitalization. The leading methods for the study of this problem are the methods of questioning and testing, allowing to make a qualitative analysis of student consumption practices in the conditions of digitization of services. These methods allowed revealing the peculiarities of online consumption practices by students. The authors found that the majority of students who are not actively using online services, to some extent had experience using online services, but almost every tenth of them had negative result. It is established that students are distrustful of new methods to obtain services, especially when it comes to any operations related to money. It is shown that students who do not practice online services have a feeling that the provided online services are of poor quality, and informants are ready to experience some discomfort in exchange for the usual, guaranteed and high quality, in their opinion, service. In addition, students who are not actively using online services note that it is not easy for them to adapt to new technologically advanced things, but the rest of the students believe that they can adapt to innovations, but the way of providing services that is now perceived as traditional one is the most acceptable for them. It is established that the leader in the use of online services is a taxi. This service is used by all students to some extent, followed by the service of food delivery and only then online banking, online shopping and public services. The novelty and originality of the study lies in the fact that the features of consumption practices among students actively practicing online services and avoiding them are revealed. It is established that students who have little recourse to online services are wary of modern services, which is based either on the previous negative experience of use, or on the unsatisfactory experience of friends, believe that those techniques and applications that are now on the market are not optimal for them and the usual methods of obtaining services for them remain more comfortable and familiar, even though more time spent on obtaining a particular service. The practical significance lies in the fact that the data obtained in the work can be used in social psychology, age psychology, labor psychology, management, sociology, as well as for further theoretical development of this issue. © 2020, Anadolu University, Faculty of Communication Sciences. All rights reserved.","Consumption; E-Commerce; Internet; Students",{"$nulls":7},"Alisov E.A., Cherdymova E.I., Trubina G.F., Yakushev A.N., Zhdanov S.P., Popova O.V., Kobzar-Frolova M.N., Study of Dominant Type of Student Ecological Focus, Ekoloji, 27, 106, pp. 357-362, (2018); Belkin A.S., Success Situation: How to Create It, (1991); Bolshakova O.A., Modern Priorities in the Daily Life of Students: University Studies and Paid Work. Values of Daily Activities of Citizens, (2004); Bozhovich L.I., Personality and Its Formation in Childhood, (1968); Cherdymova E.I., Afanasjeva S.A., Parkhomenko A.G., Ponyavina M.B., Yulova E.S., Nesmeianova I.A., Skutelnik O.A., Student ecological consciousness as determining component of ecological-oriented activity, Eurasian Journal of Biosciences, 12, 2, pp. 167-174, (2018); Cherdymova E.I., Prokopyev A.I., Karpenkova T.V., Pravkin S.A., Ponomareva N.S., Kanyaeva O.M., Ryazapova L.Z., Anufriev A.F., EcoArt Therapy as a Factor of Students’ Environmental Consciousness Development, Ekoloji, 28, 107, pp. 687-693, (2019); Goroshko E.I., Communicative space of the Internet as an object of socio-cultural analysis, Bulletin of Odessa National University. Odessa, 15, 14, pp. 130-136, (2010); Gurov O.N., Baudrillard J., Approaches to the Study of Consumer Culture, (2003); Hague M., Fundamentals of E-Business, (2002); Ilyin V.I., Consumption as a Discourse, (2008); Kalugina O.A., Tarasevich N.A., Smart technology integration into EFL teaching at the non-linguistic higher school, Xlinguae, 11, 1XL, pp. 8-18, (2018); Khalin V.G., Chernova G.V., Digitalization and Its Impact on the Russian Economy and Society: Advantages, Challenges, Threats and Risks, (2018); Lazinin I.V., Consumption as a cultural phenomenon: Modern specific, Bulletin of Stavropol State University. Philosophy Science, 76, pp. 18-25, (2011); Ovrutsky A.V., Sociology of Consumption: Main Directions of Research, (2014); Ozhegov S.I., Dictionary of Russian Language, (2011); Pashkov A.S., The Way of Life of A Large City Population: A Comprehensive Social Studies, (1988); Pirogov S.V., E-Commerce. Moscow: Publishing House “Social relations”, Publishing House “Perspektiva”, (2003); Radaev V.V., Economic sociology in Russia: Formation and development, Economic Sociology, 5, 3, pp. 98-104, (2004); Radaev V.V., Sociology of consumption: Basic approaches, Sociological Research, NRU HSE, 1, pp. 12-25, (2005); Radaev V.V., Kotelnikova Z.V., Markin M.E., Development of Russian Retail: Measures of State Regulation and Their Consequences. Analytics of Laboratory for Studies in Economic Sociology, (2009); Schwab K., The Fourth Industrial Revolution, (2017); Sorokoumova E.A., Cherdymova E.I., Rezvantseva M.O., Kochneva L.V., Latysheva V.V., Perkova E.P., Environmental and Social Practices of Old Stuff Use and Disposal by Students, Ekoloji, 28, 107, pp. 5065-5069, (2019); Tatarintseva Y.O., Consumer Culture as a sociological category, Bulletin of TSU, Series of Social Sciences, 3, 7, pp. 66-76, (2016); Vasbieva D.G., Sokolova N.L., Masalimova A.R., Shinkaruk V.M., Kiva-Khamzina Y.L., Exploring the EFL teacher’s role in a smart learning environment – a review study, Xlinguae, 11, 2, pp. 265-274, (2018); Zhilina L.N., Frolova N.T., Problems of Consumption and Education of Personality, (1969)","A.R. Bayanova; Kazan National Research Technical University named after A.N. Tupolev – KAI, Kazan, Russian Federation; email: almira-djl@mail.ru",null,"Anadolu University, Faculty of Communication Sciences",{"$nulls":5},"1309517X",null,null,null,"English","Contemp. Edu. Tech.","Article","Final","All Open Access; Bronze Open Access; Green Open Access","Scopus","2-s2.0-85078317178"]
["Akkarakantrakorn S.","Akkarakantrakorn, Somkanae (58499340200)",5.84993402E10,"Guidelines for the Management of Digital Evidence Gathering Concerning Online Shopping Fraud",2020.0,"Thammasat Review",23.0,1.0,null,138.0,159.0,21.0,2.0,"10.14456/tureview.2020.7","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85108349589&doi=10.14456%2ftureview.2020.7&partnerID=40&md5=1be73d6f15412185b91f6a84df215843","Faculty of Social Science and Humanities, Mahidol University, Thailand","Akkarakantrakorn S., Faculty of Social Science and Humanities, Mahidol University, Thailand","Constant connectivity to the Internet has improved our quality of life by leaps and bounds. Convenience shopping is the ultimate game-changer which is fast becoming the norm. While globalization of the Internet is rapidly moving forward, online businesses and consumers are vulnerable towards online fraud due to increasing usage on online transactions. This mixed methods study aims to investigate the factors that contribute towards online purchases while gathering evidence to develop guidelines for collecting digital evidence. Quantitative samples from 95 police officers from the Technology Crime Suppression Division, whereas qualitative samples comprised of 6 police officers from the same division, and 13 senior executives in various agencies who had been coordinated work with the Public and State Agencies in coordinating work in digital data evidence collection. The study employed focus group discussion and in-depth interviews. Questionnaires, percentage, mean, standard deviation, t-test and ANOVA were also used for data collection and analysis. Research outcomes revealed that online shopping fraud was done in 3 ways: 1) buyer fraud 2) seller fraud 3) buyer and seller fraud. The Computer Crime Act B.E. 2550 (2007) empowered the police to request information from the service providers regarding the communication, financial, shipping and delivery trail. Problems and obstacles were related to poor knowledge management, delays, late delivery of evidence, scope of police power, incompetent personnel without ability to manage the flow of internal and external knowledge effectively, including a lack of public awareness. The main contribution of this study is to build public awareness to prevent and reduce the risk of online shopping fraud as well as providing a guideline for the Technology Crime Suppression Division to further operations. © 2020, Thammasat University. All rights reserved.","Buyer & Seller Fraud; Computer Crime Act B.E. 2550; Digital Evidence; Online Shopping Fraud; Technology Crime Suppression Division",{"$nulls":7},"Regarding the offence related to the Computer Crime Act B.E.2550, (2017); Albrecht W. S., Albrecht C. O., Albrecht C. C., Zimbelman M. F., Fraud Examination, (2009); Amornpinyokiet P, Explanations on the Computer Crime Act B.E. 2550, (2010); Arnusasananun V., The Investigation officers’ authority in collecting electronics evidence: A comparative Study between Thailand and U.S.A, (2007); Good Practice Guide for Computer-Based Electronic Evidence, (2009); Boonthum K., Social Sciences Research Methodology, (2002); Bunting S., Wei W., The OFFICIAL EnCE: EnCase Certified Examiner Study Guide, (2006); Chalermchai L., The Development of Evidence Collection and Storing Electronic Evidence (Master of Sciences), (2009); Clough J., Principles of cybercrime, (2010); Duffield G, Grabosky P, The psychology of fraud, Trends & Issues in Crime and Criminal Justice, 199, pp. 1-6, (2001); (Draft) Standard Practice in digital evidence validation, (2015); Jintasathien C., Overrule on non-admissible evidence acquired illegally based on Section 226/1 Code of Law on Criminal Procedures, (2010); Kasaemsaeng S., Problems and Obstacles in Performing Tasks of the police officials regarding the Suppression of Corruption and Misconduct among the officials, (2000); Kim D. J., Ferriny D. L., Rao H. R., A trust-based consumer decision-making model in electronic commerce: The role of trust, perceived risk, and their antecedents, Decision Support Systems, 44, 2, pp. 544-564, (2008); Kitpreedaborisut B., Social Sciences Research Methodology. Bangkok: Books Center, Chulalongkorn University Chadarat Pipatnun (2011), Computer Crime Act B.E. 2550 section related to the Office University of Thai Chamber of Commerce Journal, 31, 2, pp. 142-157, (2002); Kittisomboon N., Search of Evidence from private information from Electronics Data in Computer Crime (Unpublished Master of Law), (2006); Kittivarakul S., The Impacts of Freedom of Speech Concepts with the police arrest, A comparison between Thailand and the People Republic of China (Master of Laws), (2012); Kovacich G. L., Fighting fraud: how to establish and manage and anti-fraud program, (2008); Kruse W. G., Heiser J. G., Computer Forensics: Incident Response Essentials, (2002); Kulnithet N., Et al., Network and Knowledge Management in Computer Crime, (2013); Liu C., Marchewka J. T., Lu J., Yu C-S., Beyond concern: a privacy-trust-behavioral intention model of electronic commerce, Information & Management, 42, 2, pp. 289-304, (2005); Lu Y., Yang S., Chau P. Y. K., Cao Y., Dynamics between the trust transfer process and intention to use mobile payment service: a cross-environment perspective, Information & Management, 48, 8, pp. 393-403, (2011); Ma G., Wang Z., Zou L., Computer Forensics Model Based on Evidence Ring and Evidence Chain. The Central Institute for Correctional Police, Procedia Engineering, 15, 2011, pp. 3663-3667, (2011); Seecharoen M., Et al., Guidelines in developing higher education and Excellence in Police Career, (2010); Mandia K., Incident Response & Computer Forensics, pp. 200-206, (2003); Mukherjee A., Nath P., Role of electronic trust in online retailing: A re-examination of the commitment-trust theory, European Journal of Marketing, 41, 9, pp. 1173-1202, (2007); Na Na Korn K., Code of Conduct Law, (2006); Naetivanich V., Manual for Legal and Information Technology Communication, (2008); Survey of Household Use of Information Technology and Communication 2015, (2016); Newby T., Carroll O., Rethinking the Storage of Computer Evidence, (2008); Ngamsaeng N., Computer Crime: A Case Study on Factors affecting Internet Crime, (2004); Market Analysis on Thai Fixed Broadband Market, (2016); Pedneault S., Fraud 101: Techniques and Strategies for Understanding Fraud, (2009); Research for developing investigation and inquiry process of the Police Officers to combat computer crime, (2016); Ruijiravinijchai K., Developing Effectiveness in Administering Investigation of Metropolitan Bureau, Royal Thai Police, (2014); Silverstone H., Sheetz M., Forensic accounting and fraud investigation for non-experts, (2007); SWGDE Best Practices for Computer Forensics Version: 3.1, (2014); Computer Crime, (2015); Suksri S., Et al., Affects from the Computer Crime Act B.E. 2550 and the State Policies with the Freedom of Speech, Internet for the public (iLaw), (2012); Sukhum S., Factors Affecting Computer Crime Prevention of the police Office at the Economic Crime Suppression Division, (2000); Tung F-C., Chang S-C., Chou C-M., An extension of trust and TAM model with IDT in the adoption of the electronic logistics information system in HIS in the medical industry, International Journal of Medical Informatics, 77, pp. 324-335, (2008); Best Practices for Seizing Electronic Evidence v.3 A Pocket Guide for First Responders, (2006); Comprehensive Study on Cybercrime, (2013); Unsri V., Problems on collecting Electronics Evidence in the Criminal Case, (2001); Vichitcholchai P., Explanation for the Computer Crime Act B.E. 2550, (2007); Vithitanon V., Criminal Investigation, (2006); Yamane T., Statistics, an Introductory Analysis, (1967); Yungyuen S., Computer Crime, (2015)","S. Akkarakantrakorn; Faculty of Social Science and Humanities, Mahidol University, Thailand; email: somkanae@gmail.com",null,"Thammasat University",{"$nulls":5},8595747.0,null,null,null,"English","Thammasat. Rev.","Article","Final",null,"Scopus","2-s2.0-85108349589"]
["Xi G.; Cao X.; Zhen F.","Xi, Guangliang (57191755976); Cao, Xinyu (57999339800); Zhen, Feng (55586058900)","57191755976; 57999339800; 55586058900","The impacts of same day delivery online shopping on local store shopping in Nanjing, China",2020.0,"Transportation Research Part A: Policy and Practice",136.0,null,null,35.0,47.0,12.0,54.0,"10.1016/j.tra.2020.03.030","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85082852887&doi=10.1016%2fj.tra.2020.03.030&partnerID=40&md5=36936a43e77a81adc627a1a019934cd2","School of Architecture and Urban Planning, Nanjing University, Nanjing, 210093, China; Provincial Engineering Laboratory of Smart City Design Simulation & Visualization, Nanjing, 210093, China; Beijing Advanced Innovation Center for Big Data and Brain Computing, Beihang University, Beijing, 100191, China; Humphrey School of Public Affairs, University of Minnesota, Twin Cities, United States","Xi G., School of Architecture and Urban Planning, Nanjing University, Nanjing, 210093, China, Provincial Engineering Laboratory of Smart City Design Simulation & Visualization, Nanjing, 210093, China; Cao X., Beijing Advanced Innovation Center for Big Data and Brain Computing, Beihang University, Beijing, 100191, China, Humphrey School of Public Affairs, University of Minnesota, Twin Cities, United States; Zhen F., School of Architecture and Urban Planning, Nanjing University, Nanjing, 210093, China, Provincial Engineering Laboratory of Smart City Design Simulation & Visualization, Nanjing, 210093, China","Same Day Delivery (SDD) online shopping may generate different influences on physical store shopping from conventional online shopping, but few studies have explored this new and burgeoning channel and its impacts. Using retrospective survey data in Nanjing, this study investigates the impacts of SDD online shopping on local store shopping. Quasi-longitudinal analyses of the retrospective data show that SDD online shopping substitutes for local store shopping, and that changes in local shopping are associated with SDD online shopping frequency. These results suggest that SDD online shopping may change local shopping travel and alter the distribution of commercial land uses over time. Moreover, a comparison between quasi-longitudinal and cross-sectional analyses suggests that cross-sectional results are not reliable. Future studies should move beyond cross-sectional design. © 2020 Elsevier Ltd","E-shopping; Information and communication technology; Longitudinal design; Retrospective approach; Shopping travel","China; Jiangsu; Nanjing [Jiangsu]; Land use; Cross sectional analysis; Cross-sectional design; Information and Communication Technologies; Longitudinal analysis; Longitudinal designs; Retrospective approach; Retrospective surveys; Shopping travel; comparative study; design; electronic commerce; information and communication technology; shopping activity; survey; Electronic commerce",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (41571146, 41701178); Natural Science Foundation of Jiangsu Province, (BK20170639)","This study was funded by the National Natural Science Foundation of China (No. 41571146 ; 41701178 ) and the Natural Science Foundation of Jiangsu Province (No. BK20170639 ). 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Board, 2566, pp. 93-101, (2016); Zhou Y., Wang X., Explore the relationship between online shopping and shopping trips: an analysis with the 2009 NHTS data, Transp. Res. Part A: Policy Pract., 70, pp. 1-9, (2014)","X. Cao; Humphrey School of Public Affairs, University of Minnesota, Twin Cities, Minneapolis, 301 19th Ave S, 55455, United States; email: cao@umn.edu",null,"Elsevier Ltd",{"$nulls":5},9658564.0,null,null,null,"English","Transp. Res. Part A Policy Pract.","Article","Final",null,"Scopus","2-s2.0-85082852887"]
["Kerigan N.","Kerigan, Nick (57218138407)",5.7218138407E10,"The consumer in lockdown: Consumer– merchant payments in a mobility-constrained environment",2020.0,"Journal of Payments Strategy and Systems",14.0,2.0,null,113.0,119.0,6.0,4.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85088041406&partnerID=40&md5=18ae0a6ddafe24bf3800344b32007f21","Barclays Bank PLC, United Kingdom","Kerigan N., Barclays Bank PLC, United Kingdom","The COVID-19 pandemic has prompted a broad-ranging response from governments across the world. A common theme of those responses is to lock down consumers, largely confining them to their homes. This paper explores what the COVID-19 lockdown could mean for consumer behaviours, and therefore by implication, for payments. In this period of lockdown, consumer needs do not go away — but how those needs are met and how those solutions are accessed could change radically. This situation will favour digital business models with delivery services, over physical stores, restaurants and other venues. Payment providers are likely to see a rapid change in the mix of payments towards contactless and e/m-commerce payments. This paper argues that it is important not to lose sight of the strategic implications of what could be a profound change in how we live our lives and our relationship with digital technology. © Henry Stewart Publications, 1750-1806.","Behaviours; payments; Consumer; Contactless; Digital; E-commerce; Pandemic",{"$nulls":7},"Medium, (2020); Coronavirus (COVID-19): what you need to do, (2020); Davidson H., Around 20 per cent of global population under coronavirus lockdown, Guardian, (2020); Impact of non-pharmaceutical interventions (NPIs) to reduce COVID19 mortality and healthcare demand, (2020); Gardner B., Dirty banknotes may be spreading the coronavirus,WHO suggests, Daily Telegraph, (2020); Patel M., How coronavirus could lead to digital exclusion in a cashless society, Fintech Times, (2020); Gamio L., Coronavirus workers at risk, NewYork Times, (2020); Jagannathan M., World Health Organization: “We did NOT say that cash was transmitting coronavirus, (2020); There is no evidence that cash helps COVID-19 spread, (2020); Hall I., Governments quarantine banknotes as coronavirus puts “dirty” money in spotlight, Global Government Forum, (2020); Costa Coffee stores go cashless and remove seating areas in the UK, (2020); UK Payment Markets Review, (2019); COVID19 and cash — LINK update, (2020); Contactless limit in UK to be increased to £45, (2020); Dutch banks raise contactless limits for PIN entry, (2020); Netherlands and Norway banks raise contactless limits for PIN entry, (2020); Statement on consumer and payment issues in light of COVID19, (2020); The economic cost of coronavirus lockdowns, (2020); Evaluating the initial impact of COVID-19 containment measures on economic activity, (2020); Keffer P., This US consumer spending data by category (down 30%YOY as of 3/24) from @BankofAmerica is stunning, (2020); COVID-19 strategies and policies of the world’s largest companies, (2020); Global E-Commerce 2019, (2019); Navigating the COVID-19 Pandemic, (2020); Arora A., Cristiani P., Dreischmeier R., Libarikian A., Yegoryan H., Building an e-commerce business: Lessons on moving fast, (2020); Coronavirus: online shopping website Ocado suspends service, (2020); Duffy C., Amazon hiring 100,000 new distribution workers to keep up with online shopping surge caused by coronavirus, CNN Business, (2020); Lomas N., Techcrunch, (2020); Alexander J., Porter J., Disney Plus and Facebook are also reducing streaming quality in Europe, The Verge, (2020); Neichel D., When every other sport goes dark… and the entire world is stranded at home…, (2020); Cloete K., Universal becomes first studio to move theatrical releases to streaming, Critical Hit Entertainment, (2020); Knatchbull P., Amazingly #CurzonHomeCinema is up 50% today over yesterday.We are genuinely grateful for your support and I know the team is working day and night to bring you the best films available, (2020); Bjorson G., Met Opera is streaming free, iconic performances every night this week, (2020); Gompertz S., Plumber R., Coronavirus: Six things that are booming in sales, BBC News, (2020); Birch D., A friend of mine who works at Homebase (kind of like Home Depot, for US readers) confirms @profgalloway’s thinking: people working at home for the next three months are already spending on home improvement suppliers. I’ll finally going to get around to putting up that shelf, etc, (2020); Patel; Hearing A., Cardless in the coronavirus crisis, Financial Times, (2020)","N. Kerigan; Barclays Bank PLC, United Kingdom; email: nick.kerigan@gmail.com",null,"Henry Stewart Publications",{"$nulls":5},1.7501806E7,null,null,null,"English","J. Paym. Strateg. Syst.","Article","Final",null,"Scopus","2-s2.0-85088041406"]
["Jaller M.; Pahwa A.","Jaller, Miguel (36158256500); Pahwa, Anmol (57214588705)","36158256500; 57214588705","Evaluating the environmental impacts of online shopping: A behavioral and transportation approach",2020.0,"Transportation Research Part D: Transport and Environment",80.0,null,102223.0,null,null,null,100.0,"10.1016/j.trd.2020.102223","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85078144388&doi=10.1016%2fj.trd.2020.102223&partnerID=40&md5=75d8c00b7148c48651432bc1c8aade30","Department of Civil and Environmental Engineering, Sustainable Freight Research Center, Institute of Transportation Studies, University of California, Davis, One Shields Ave, 2001 Ghausi Hall, Davis, 95616, CA, United States","Jaller M., Department of Civil and Environmental Engineering, Sustainable Freight Research Center, Institute of Transportation Studies, University of California, Davis, One Shields Ave, 2001 Ghausi Hall, Davis, 95616, CA, United States; Pahwa A., Department of Civil and Environmental Engineering, Sustainable Freight Research Center, Institute of Transportation Studies, University of California, Davis, One Shields Ave, 2001 Ghausi Hall, Davis, 95616, CA, United States","Various fields and commercial sectors have witnessed a transformation with the advent of the internet. In the last decade, the retail sector in particular has witnessed the massive growth of e-commerce. This has also significantly altered our shopping experiences, influencing a range of decisions, from where, how, and how much to shop. With the consistent growth of e-commerce transactions, more trucks than ever before are entering cities today, bringing with them the negative externalities of increased congestion and pollution. This study first unravels underlying shopping behaviors–both in-store and online–using the 2016 American Time Use Survey (ATUS) data. The authors also develop an econometric behavioral model to understand the factors that affect shopping decisions. At a macro level, the disaggregate individual shopping behaviors are studied by implementing the model to synthetic populations to estimate potential vehicle miles traveled and environmental emissions in two metropolitan areas, Dallas and San Francisco (SF). Finally, the study estimates the impacts of rush deliveries, basket size, and consolidation levels by developing a breakeven analysis between in-store and online shopping. These results confirm the importance of managing the urban freight system, including delivery services and operations, to foster a more sustainable urban environment. © 2020 Elsevier Ltd","Consolidation level; Delivery tours; Environmental impacts; Online shopping; Shopping behaviors; Substitution and complementary","Electronic commerce; Traffic congestion; American time use surveys; Delivery tours; E-commerce transactions; Environmental emissions; Online shopping; Shopping behavior; Sustainable urban environments; Vehicle-miles traveled; electronic commerce; environmental impact; Internet; metropolitan area; shopping activity; transportation system; Environmental impact",{"$nulls":4},"CTECH; Center for Transportation, Environment and Community Health; National Center for Sustainable Transportation; California Department of Transportation, CT","The authors would also like to thank the National Center for Sustainable Transportation (NCST), the California Department of Transportation, the Sustainable Freight Research Center at the Institute of Transportation Studies, and the Center for Transportation, Environment and Community Health (CTECH). The authors would also like to thank Dr. Giovanni Circella for his suggestions during the behavioral modeling process.","Allen J., Piecyk M., Piotrowska M., McLeod F., Cherrett T., Ghali K., Nguyen T., Bektas T., Bates O., Friday A., Understanding the impact of e-commerce on last-mile light goods vehicle activity in urban areas: the case of London, Transport. Res. Part D: Transp. Environ. Plan., 61, pp. 325-338, (2018); Amadeo K., (2018); Bandeira R.A.D.M., Goes G.V., Goncalves D.N.S., D'Agosto M.D.A., Oliveira C.M.D., Electric vehicles in the last mile of urban freight transportation: A sustainability assessment of postal deliveries in Rio de Janeiro-Brazil, Transport. Res. Part D, 67, pp. 491-502, (2019); Barth M., Boriboonsomsin K., Energy and emissions impacts of a freeway-based dynamic eco-driving system, Transport. Res. Part D: Transp. 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Sci., 39, pp. 510-520, (2012); (2017); Farag S., Schwanen T., Dijst M., Empirical investigatiuon of online searching and buying and their relationshop to shopping trips, Transport. Res. Rec., 1926, pp. 242-251, (2005); Farag S., Schwanen T., Dijst M., Faber J., Shopping online and/or in-store? A structural equation model of the relationships between e-shopping and in-store shopping, Transport. Res. Part A, 41, pp. 125-141, (2007); Ferrel C.E., Home-based teleshoppers and shopping travel: do teleshoppers travel less?, Transport. Res. Rec., 1894, pp. 241-248, (2004); Gevaers R., Voorde E.V.D., Vanelslander T., Cost modelling and simulation of last-mile characteristics in an innovative B2C supply chain environment with implications on urban areas and cities, Proc. – Social Behav. Sci., 125, pp. 398-411, (2014); Goodchild A., Toy J., Delivery by drone: an evaluation of unmanned aerial vehicle technology in reducing CO<sub>2</sub> emissions in the delivery service industry, Transport. Res. Part D, 61, pp. 58-67, (2018); Hofferth S., Flood S.M., Sobek M., (2017); Holguin-Veras J., Xu N., Jaller M., Mitchell J., A dynamic spatial price equilibrium model of integrated urban production-transportation operations considering freight delivery tours, Transport. Sci., 50, 2, pp. 489-519, (2015); (2016); Jaller M., Otero-Palencia C., Yie-Pinedo R., Inventory and Fleet Purchase Decisions under a Sustainable Regulatory Environment, Supply Chain Forum. An International Journal, pp. 1-13, (2019); Jaller M., Pineda L., Ambrose H., Evaluating the use of zero-emission vehicles in last mile deliveries, UC Davis Institute of Transport Studies, (2018); Kuo M., How do experts like FedEx plan their routes?, Routific, (2018); Lee R.J., Sener I.N., Mokhatarian P.L., Handy S.L., Relationships between the online and in-store shopping frequency of Davis, California residents, Transport. Res. Part A, 100, pp. 40-52, (2017); Lewis P.H., Attention Shoppers: Internet Is Open, (1994); Lin J., Zhou W., Du L., Is on-demand same day package delivery service green?, Transport. Res. Part D, 61, pp. 118-139, (2018); Loon P.V., Deketele L., Dewaele J., McKinnon A., Rutherford C., A comparative analysis of carbon emissions from online retailing of fast moving consumer goods, J. Clean. Prod., 106, pp. 478-486, (2015); Mokhatarian P., A conceptual analysis of the transportation impacts of B2C e-commerce, Transportation, 31, pp. 257-284, (2004); Nicasio F., (2018); Rotem-Mindali O., Salomon I., The impacts of E-retail on the choice of shopping trips and delivery: some preliminary findings, Transp. Res. Part A, 41, pp. 176-189, (2007); Shang G., Pekgun P., Ferguson M., Galbreth M., How much do online consumers really value free product returns? Evidence from eBay, J. Operat. Manage., 53, 56, pp. 45-62, (2017); Siikavirta H., Punakivi M., Karkkainen M., Linnanen L., Effects of E-commerce on greenhouse gas emissions, J. Indust. Ecol., 6, 2, pp. 83-97, (2003); Srinivasan S., Bhat C.R., Modeling household interactions in daily in-home and out-of-home maintenance activity participation, Transportation, 32, pp. 523-544, (2005); Thirumalai S., Sinha K.K., Customer satisfaction with order fulfillment in retail supply chains: implications of product type in electronic B2C transaction, J. Operat. Manage., 23, pp. 291-303, (2005); Tipagornwong C., Figliozzi M., Analysis of competitiveness of freight tricycle delivery services in urban areas, Transp. Res. Rec., 2410, pp. 76-84, (2014); (2018); (2017); (2017); Weltevreden J.W.J., Rietbergen T.V., E-shopping versus city centre shopping: the role of perceived city centre attractiveness, J. Econ. Social Geogr., 98, 1, pp. 68-85, (2007); Wiese A., Toporowski W., Zielke S., Transport-related CO<sub>2</sub> effects of online and brick-and-mortar shopping: a comparison and sensitivity analysis of clothing retailing, Transport. Res. Part D, 17, pp. 473-477, (2012); Wygonik E., Goodchild A.V., Urban form and last-mile goods movement: factors affecting vehicle miles traveled and emissions, Transport. Res. Part D, (2016); Zhou Y., Wang X., Explore the relationship between online shopping and shopping trips: an analysis with the 2009 NHTS data, Transport. Res. Part A, 70, pp. 1-9, (2014)","M. Jaller; Department of Civil and Environmental Engineering, Sustainable Freight Research Center, Institute of Transportation Studies, University of California, Davis, Davis, One Shields Ave, 2001 Ghausi Hall, 95616, United States; email: mjaller@ucdavis.edu",null,"Elsevier Ltd",{"$nulls":5},1.3619209E7,null,"TRDTF",null,"English","Transp. Res. Part D Transp. Environ.","Article","Final",null,"Scopus","2-s2.0-85078144388"]
["Shui W.; Li M.","Shui, Wenbing (34877631600); Li, Mengxia (57218488771)","34877631600; 57218488771","Integrated Pricing and Distribution Planning for Community Group Purchase of Fresh Agricultural Products",2020.0,"Scientific Programming",2020.0,null,8839398.0,null,null,null,13.0,"10.1155/2020/8839398","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85089308011&doi=10.1155%2f2020%2f8839398&partnerID=40&md5=77b3f88270af9c2fb0edf017cfe82763","Faculty of Transportation Engineering, Kunming University of Science and Technology, Kunming, 650500, China","Shui W., Faculty of Transportation Engineering, Kunming University of Science and Technology, Kunming, 650500, China; Li M., Faculty of Transportation Engineering, Kunming University of Science and Technology, Kunming, 650500, China","As a new social e-commerce model, community group purchase of fresh agricultural products has been gradually welcomed by the public. However, its development and operation still face homogeneous competition problems. In order to enhance competitive advantages of operators, this paper proposes a collaborative optimization mechanism, including a new pricing model and a new cold chain vehicle route planning model. It aims to ensure the quality of fresh products, reduce logistics costs, and improve enterprise profitability. The model takes into account not only the quality of fresh products and their impact on price and demand but also the impact of quality changes on total distribution costs. A two-layer programming method is applied to realize the collaborative optimization mechanism, and then the upper and lower models are solved by mathematical derivation, proof methods, and optimization procedures, respectively. Finally, the feasibility and effectiveness of the model are verified by combining with specific examples, and the following conclusions are obtained: price, delivery quality, and total profit increase with the increase of potential market demand rate. The lower the refrigeration temperature of the vehicle we choose within a certain range, the higher the quality can be obtained. In order to obtain the highest profit, community group purchase operators can choose a higher distribution temperature on the premise that they can guarantee that the quality of fresh agricultural products can be at an appropriate level. © 2020 Wenbing Shui and Mengxia Li.",null,"Agricultural products; Agricultural robots; Competition; Profitability; Purchasing; Sales; Collaborative optimization; Competitive advantage; Development and operations; Distribution temperature; Fresh agricultural products; Mathematical derivation; Optimization procedures; Refrigeration temperatures; Costs",{"$nulls":6},"Zhang G., Shang J., Yildirim P., Optimal pricing for group buying with network effects, Omega, 63, 8, pp. 69-82, (2016); Kauffman R.J., Wang B., New buyers' arrival under dynamic pricing market microstructure: The case of group-buying discounts on the Internet, Journal of Management Information Systems, 18, 2, pp. 157-188, (2001); Chen J., Liu Y., Song X., A study of Single-vendor and multiple-retailers pricing-ordering strategy under group-buying online auction, pp. 19-23; Chen J., Chen X., Song X., Comparison of the group-buying auction and the fixed pricing mechanism, Decision Support Systems, 43, 2, pp. 445-459, (2007); Sharif Vaghefi M., Sharif Vaghefi M., Beheshti N., A pricing model for group-buying auction based on customers' waiting-time, Marketing Letters, 25, 4, pp. 425-434, (2014); Gu W., Cai X., Application of group buying pricing in two - echelon distribution systems, pp. 1-6; Tang F.C., Chi K.P., Research on pricing strategy of online group buying in two-sided network, Chinese Journal of Management Science, 21, 3, pp. 185-192, (2013); Qian D., Su H., Joint decision of pricing and advertising investment for online group-buying under intersecting demand regimes, Journal of Applied Sciences, 13, 22, pp. 4949-4954, (2013); Hsu C.-I., Hung S.-F., Li H.-C., Vehicle routing problem with time-windows for perishable food delivery, Journal of Food Engineering, 80, 2, pp. 465-475, (2007); Osvald A., Stirn L.Z., A vehicle routing algorithm for the distribution of fresh vegetables and similar perishable food, Journal of Food Engineering, 85, 2, pp. 285-295, (2008); Amorim P., Parragh S.N., Sperandio F., Almada-Lobo B., A rich vehicle routing problem dealing with perishable food: a case study, Top, 22, 2, pp. 489-508, (2014); Estrada-Moreno A., Fikar C., Angel A., Juan, A biased-randomized algorithm for redistribution of perishable food inventories in supermarket chains, International Transactions in Operational Research, 26, 6, pp. 2077-2095, (2019); Wang X., Wang M., Ruan J., Zhan H., The multi-objective optimization for perishable food distribution route considering temporal-spatial distance, Procedia Computer Science, 96, 1, pp. 1211-1220, (2016); Hsiao Y.-H., Chen M.-C., Chin C.-L., Distribution planning for perishable foods in cold chains with quality concerns: formulation and solution procedure, Trends in Food Science & Technology, 61, 1, pp. 80-93, (2017); Hsiao Y.-H., Chen M.-C., Lu K.-Y., Chin C.-L., Last-mile distribution planning for fruit-and-vegetable cold chains, The International Journal of Logistics Management, 29, 3, pp. 862-886, (2018); Zhen L., Modeling of yard congestion and optimization of yard template in container ports, Transportation Research Part B, 90, pp. 83-104, (2016); Zhen L., Tactical berth allocation under uncertainty, European Journal of Operational Research, 247, 3, pp. 928-944, (2015)",null,null,"Hindawi Limited",{"$nulls":5},1.0589244E7,null,"SCIPE",null,"English","Sci. Program","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85089308011"]
["Wang H.; Fang F.","Wang, Hui (57218524903); Fang, Fang (57217077857)","57218524903; 57217077857","Research on E-Commerce supply chain design based on MVC model and virtual image technology",2020.0,"IEEE Access",8.0,null,9098922.0,98295.0,98304.0,9.0,6.0,"10.1109/ACCESS.2020.2996675","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85086077317&doi=10.1109%2fACCESS.2020.2996675&partnerID=40&md5=d4b02319e7c834e335342893e92a7702","College of Economic and Management, Hunan University of Science and Engineering, Yongzhou, 425199, China; College of Business, Lyceum of the Philippines University, Batangas, 4200, Philippines","Wang H., College of Economic and Management, Hunan University of Science and Engineering, Yongzhou, 425199, China, College of Business, Lyceum of the Philippines University, Batangas, 4200, Philippines; Fang F., College of Economic and Management, Hunan University of Science and Engineering, Yongzhou, 425199, China, College of Business, Lyceum of the Philippines University, Batangas, 4200, Philippines","In order to improve the intelligence of procurement under cross-border e-commerce, an e-commerce procurement system based on MVC model and virtual image technology is proposed. The procurement system under e-commerce is divided into logistics layer, management layer, financial layer, warehouse layer and procurement system transactions. Under the layer audit signature, the order is sent to the supplier, the information exchange is carried out in the MVC mode, and the integrated framework of the information organization and procurement system under cross-border e-commerce is designed through the MVC mode. This paper takes the electronic commerce simulation system as the framework and the virtual image technology as the basis to study the key technology of updating massive terrain data in real time under the condition of general computer hardware. Using the XP (Extreme Programming) programming method in the agile development mode, the development efficiency and quality are effectively improved. The design process uses UML and Visio to establish requirements and system design, simulates geographic information with virtual image technology, and provides real-time traffic scene graphic image information. The system takes the order process as the main line, realizes the system under the network environment, realizes the integration of internal and external supply chains, and solves the drawbacks of high information level and large amount of information at the bottom of traditional procurement activities. The simulation results show that the intelligent e-commerce procurement system based on virtual image technology has good intelligent processing capabilities and strong online analysis and processing capabilities. © 2013 IEEE.","cross-border e-commerce; geographic image; government procurement system; MVCmodel J2EE framework; virtual reality; virtual technology","Computer hardware; Design; Electronic commerce; Supply chains; EXtreme Programming; Geographic information; Information exchanges; Information organization; Integrated frameworks; Intelligent processing; Network environments; Processing capability; Image enhancement",{"$nulls":4},"Construct Program of the Applied Characteristic Discipline in the Hunan University of Science and Engineering","This work was supported by the Construct Program of the Applied Characteristic Discipline in the Hunan University of Science and Engineering (Applied Economics).","Zhao Y.L., Nan H., Yu Z.H., Improved particle swarm optimiza-tion algorithm based on twice search, J. 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Appl., 37, 9, pp. 2536-2540, (2017); Patel H., Accelerated PSO swarm search feature selection with SVM for data stream mining big data, Int. J. Res. Eng., 3, 9, pp. 15761-15765, (2016); Li W.H., Ni H.Y., An improved Adaboost training algorithm, J. Jilin Univ. (Sci. Ed.), 49, 3, pp. 498-504, (2011); Li N., Yu Y., Zhou Z.H., Diversity regularized ensemble pruning, Proc. Joint Eur. Conf. Mach. Learn. Knowl. Discovery Databases (Lec-ture Notes in Computer Science), 13, 11, pp. 330-345, (2012); Parvin H., MirnabiBaboli M., Alinejad-Rokny H., Proposing a classifier ensemble framework based on classifier selection and decision tree, Eng. Appl. Artif. Intell., 37, pp. 34-42, (2015); Singal G., Laxmi V., Gaur M.S., Todi S., Rao V., Tripathi M., Kushwaha R., Multi-constraints link stable multicast routing protocol in MANETs, Ad Hoc Netw., 63, pp. 115-128, (2017); Jiang X.-L., Wang Q., He B., Chen S.-J., Li B.-L., Robust level set image segmentation algorithm using local correntropy-based fuzzy c-means clustering with spatial constraints, Neurocomputing, 207, pp. 22-35, (2016); Niu S., Chen Q., De Sisternes L., Ji Z., Zhou Z., Rubin D.L., Robust noise region-based active contour model via local similarity factor for image segmentation, Pattern Recognit., 61, pp. 104-119, (2017); Bi S., Ho C.K., Zhang R., Wireless powered communication: Oppor-tunities and challenges, IEEE Commun. Mag., 53, 4, pp. 117-125, (2015); Ulukus S., Yener A., Erkip E., Simeone O., Zorzi M., Grover P., Huang K., Energy harvesting wireless communications: A review of recent advances, IEEE J. Sel. Areas Commun., 33, 3, pp. 360-381, (2015); Seo D.-W., Lee J.-H., Lee H.-S., Optimal coupling to achieve max-imum output power in a WPT system, IEEE Trans. Power Electron., 31, 6, pp. 3994-3998, (2016); Khabbazibasmenj A., Hassanien A., Vorobyov S.A., Morency M.W., Efficient transmit beamspace design for search-free based DOA esti-mation in MIMO radar, IEEE Trans. Signal Process., 62, 6, pp. 1490-1500, (2014); Sammartino P.F., Baker C.J., Griffiths H.D., Frequency diverse MIMO techniques for radar, IEEE Trans. Aerosp. Electron. Syst., 49, 1, pp. 201-222, (2013); Wang W.-Q., Shao H., Range-angle localization of targets by a double-pulse frequency diverse array radar, IEEE J. Sel. Topics Signal Process., 8, 1, pp. 106-114, (2014)","H. Wang; College of Economic and Management, Hunan University of Science and Engineering, Yongzhou, 425199, China; email: youmao882127@163.com",null,"Institute of Electrical and Electronics Engineers Inc.",{"$nulls":5},2.1693536E7,null,null,null,"English","IEEE Access","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85086077317"]
["Bhattacharjee A.; Chakraborty S.","Bhattacharjee, Abhijit (58554255000); Chakraborty, Saikat (58554068500)","58554255000; 58554068500","Internet Banking-A transformation Based on Technology from Traditional to Virtual Banking",2020.0,"Indian Journal of Law and Justice",11.0,1.0,null,150.0,158.0,8.0,0.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85169036861&partnerID=40&md5=ca8bda6214ff4efa36c7cf5d99b91bff","Jalpaiguri Law College, Jalpaiguri, India; CoochbeharPanchananBarma University, Cooch Behar, India","Bhattacharjee A., Jalpaiguri Law College, Jalpaiguri, India; Chakraborty S., CoochbeharPanchananBarma University, Cooch Behar, India","Indian Banking has undergone a total transformation over the last decade. Moving seamlessly from a manual, scale constrained environment to a technological leading position, it has been a miracle. Such a transformation takes place as per the need of the hour within a short span of time with low cost. In the development of Indian economy, banking sector plays a very important and crucial role. With the use of technology there had been an increase in penetration, productivity and efficiency. It has not only increased the cost effectiveness but also has helped in making small value transaction viable. Electronic delivery channels, ATMs, variety of cards, web based banking, and mobile banking are names of few outcome of the process of automation and computerization in banking sector. Customer values and their preferences need to be recognized for the development of internet banking to ensure long term organization-customer relationship in the E-era. The advancement and development in technology and a concrete mix of these with the information technology have brought about a critical change in outlook in the banking sector from conventional to internet-based banking framework. IT and globalization have forced the latest banking system to embrace the fast-growing innovations and change the delivery channels of financial services provided by them. Apart from the various advantages of internet banking, there are many disadvantages also as everything has both pros and cons. It has some disadvantages which must be studied and taken care of. E Banking is not a separate business; it is Banking using E Channels. Banking is regulated by RBI under RBI Act Subject to licensing Law regarding Electronic documents is contained in Information Technology Act 2000 As amended by Information technology Act 2008. There are various provisions of law, which are applicable to traditional banking activities and, are also applicable to e-banking. However, this does not overcome many problems, hence there is need for introducing more stringent rules and regulations specifically to meet the problems of e-banking. The legal framework of Indian banking system is governed by a set of enactments, i.e., The Banking Regulation Act, 1949, the Reserve Bank of India Act, 1934 and Foreign Exchange Management Act, 1999, evidence act, contract act and so on. The Information Technology Act 2000 has attempted to address a number of e-commerce regulatory issues. Yet there exists a grey area, which has neither been spelt out properly nor has there been any workable modes of implementation suggested by Constitutional institutions. © 2020, Department of Law, University of North Bengal. All rights reserved.","Development and Social Transformatio; E-Banking; Implementation; Information Technology",{"$nulls":7},"Behar Cooch; SHARMA B.R., BANK FRAUDS PREVENTION AND DETECTION, (2009); The Banking Regulation Act, 10, (1949); TANNAN M. L., TANNAN, BANKING LAW AND PRACTICE IN INDIA, (2003); Information Technology Act, 21, (2000)",null,null,"Department of Law, University of North Bengal",{"$nulls":5},9763570.0,null,null,null,"English","Indian. J. Law. Justice.","Article","Final",null,"Scopus","2-s2.0-85169036861"]
["Enthoven D.L.J.U.; Jargalsaikhan B.; Roodbergen K.J.; uit het Broek M.A.J.; Schrotenboer A.H.","Enthoven, David L.J.U. (57219584755); Jargalsaikhan, Bolor (55925759500); Roodbergen, Kees Jan (6506018019); uit het Broek, Michiel A. J. (57194133278); Schrotenboer, Albert H. (57190299865)","57219584755; 55925759500; 6506018019; 57194133278; 57190299865","The two-echelon vehicle routing problem with covering options: City logistics with cargo bikes and parcel lockers",2020.0,"Computers and Operations Research",118.0,null,104919.0,null,null,null,82.0,"10.1016/j.cor.2020.104919","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85079890614&doi=10.1016%2fj.cor.2020.104919&partnerID=40&md5=28b3c7b63a869e383d51116313e9fa93","Department of Operations, Faculty of Economics and Business, University of Groningen, Netherlands","Enthoven D.L.J.U., Department of Operations, Faculty of Economics and Business, University of Groningen, Netherlands; Jargalsaikhan B., Department of Operations, Faculty of Economics and Business, University of Groningen, Netherlands; Roodbergen K.J., Department of Operations, Faculty of Economics and Business, University of Groningen, Netherlands; uit het Broek M.A.J., Department of Operations, Faculty of Economics and Business, University of Groningen, Netherlands; Schrotenboer A.H., Department of Operations, Faculty of Economics and Business, University of Groningen, Netherlands","We introduce the two-echelon vehicle routing problem with covering options (2E-VRP-CO). This problem arises in sustainable applications for e-commerce and city distribution. In the first echelon, trucks depart from a single depot and transport goods to two types of locations. At covering locations, such as parcel lockers, customers can pick up goods themselves. At satellite locations, goods are transferred to zero-emission vehicles (such as cargo bikes) that deliver to customers. If desired, customers can indicate their choice for delivery. The 2E-VRP-CO aims at finding cost-minimizing solutions by selecting locations and routes to serve all customers. We present a compact mixed integer programming formulation and an efficient and tailored adaptive large neighborhood search heuristic that provides high-quality, and often optimal, solutions to the 2E-VRP-CO. The 2E-VRP-CO has as special cases the two-echelon vehicle routing problem, and the simultaneous facility location and vehicle routing problem without duration constraints. On these special cases, for which our heuristic predominantly solves the established benchmark instances either to optimality or to the best-known solution, our heuristic finds three new best-known solutions. Moreover, we introduce a new set of benchmark instances for the 2E-VRP-CO and provide managerial insights when distribution via both satellite and covering locations is most beneficial. Our results indicate that customers in the same area are best-served either via cargo-bikes or parcel lockers (i.e., not both), and that the use of parcel lockers has a great potential to reduce driving distance. © 2020","Cargo bikes; City logistics; Location routing; Parcel lockers; Sustainable logistics; Two-echelon vehicle routing","Benchmarking; Bicycles; Heuristic algorithms; Integer programming; Location; Sales; Adaptive large neighborhood searches; Cargo bikes; City logistics; Location-routing; Mixed integer programming; Parcel lockers; Vehicle Routing Problems; Zero emission vehicles; Vehicle routing",{"$nulls":4},"Nederlandse Organisatie voor Wetenschappelijk Onderzoek, NWO, (438-13-216, 439-16-612)","This work was partly supported by the Netherlands Organisation for Scientific Research (NWO) through grants no 438-13-216 (Michiel A. J. uit het Broek and Albert H. Schrotenboer) and no 439-16-612 (Kees Jan Roodbergen and Bolor Jargalsaikhan).  ","Anderluh A., Hemmelmayr V.C., Nolz P.C., Synchronizing vans and cargo bikes in a city distribution network, Cent. Eur. J. Oper. Res., 25, 2, pp. 345-376, (2017); Arnold F., Cardenas I., Sorensen K., Dewulf W., Simulation of b2c e-commerce distribution in antwerp using cargo bikes and delivery points, Eur. Transp. Res. Rev., 10, 1, (2018); Breunig U., Baldacci R., Hartl R.F., Vidal T., The electric two-echelon vehicle routing problem, Comput. Oper. Res., 103, pp. 198-210, (2019); Breunig U., Schmid V., Hartl R.F., Vidal T., A large neighbourhood based heuristic for two-echelon routing problems, Comput. Oper. Res., 76, pp. 208-225, (2016); Cattaruzza D., Absi N., Feillet D., Gonzalez-Feliu J., Vehicle routing problems for city logistics, EURO J. Transp. Logist., 6, 1, pp. 51-79, (2017); Cuda R., Guastaroba G., Speranza M.G., A survey on two-echelon routing problems, Comput. Oper. Res., 55, pp. 185-199, (2015); Demir E., Huang Y., Scholts S., Van Woensel T., A selected review on the negative externalities of the freight transportation: modeling and pricing, Transp. Res. Part E, 77, pp. 95-114, (2015); Deutsch Y., Golany B., A parcel locker network as a solution to the logistics last mile problem, Int. J. Prod. Res., 56, 1-2, pp. 251-261, (2018); Franceschetti A., Demir E., Honhon D., Van Woensel T., Laporte G., Stobbe M., A metaheuristic for the time-dependent pollution-routing problem, Eur. J. Oper. Res., 259, 3, pp. 972-991, (2017); Grangier P., Gendreau M., Lehuede F., Rousseau L.-M., An adaptive large neighborhood search for the two-echelon multiple-trip vehicle routing problem with satellite synchronization, Eur. J. Oper. Res., 254, 1, pp. 80-91, (2016); Guastaroba G., Speranza M.G., Vigo D., Intermediate facilities in freight transportation planning: a survey, Transp. Sci., 50, 3, pp. 763-789, (2016); Hemmelmayr V.C., Cordeau J.-F., Crainic T.G., An adaptive large neighborhood search heuristic for two-echelon vehicle routing problems arising in city logistics, Comput. Oper. Res., 39, 12, pp. 3215-3228, (2012); Kirkpatrick S., Gelatt C.D., Vecchi M.P., Optimization by simulated annealing, Science, 220, 4598, pp. 671-680, (1983); Perboli G., Tadei R., New families of valid inequalities for the two-echelon vehicle routing problem, Electron. Notes Discret. Math., 36, pp. 639-646, (2010); Perboli G., Tadei R., Vigo D., The two-echelon capacitated vehicle routing problem: models and math-based heuristics, Transp. Sci., 45, 3, pp. 364-380, (2011); Pisinger D., Ropke S., A general heuristic for vehicle routing problems, Comput. Oper. Res., 34, 8, pp. 2403-2435, (2007); Prodhon C., Prins C., A survey of recent research on location-routing problems, Eur. J. Oper. Res., 238, 1, pp. 1-17, (2014); Ropke S., Pisinger D., An adaptive large neighborhood search heuristic for the pickup and delivery problem with time windows, Transp. Sci., 40, 4, pp. 455-472, (2006); Savelsbergh M., Van Woensel T., 50th anniversary invited articlecity logistics: challenges and opportunities, Transp. Sci., 50, 2, pp. 579-590, (2016); Schrotenboer A.H., Uit het Broek M.A.J., Jargalsaikhan B., Roodbergen K.J., Coordinating technician allocation and maintenance routing for offshore wind farms, Comput. Oper. Res., 98, pp. 185-197, (2018); Schrotenboer A.H., Wruck S., Vis I.F., Roodbergen K.J., (2019); Stenger A., Schneider M., Schwind M., Vigo D., Location routing for small package shippers with subcontracting options, Int. J. Prod. Econ., 140, 2, pp. 702-712, (2012); Veenstra M., Roodbergen K.J., Coelho L.C., Zhu S.X., A simultaneous facility location and vehicle routing problem arising in health care logistics in the netherlands, Eur. J. Oper. Res., 268, 2, pp. 703-715, (2018); Wang K., Shao Y., Zhou W., Matheuristic for a two-echelon capacitated vehicle routing problem with environmental considerations in city logistics service, Transp. Res. Part D, 57, pp. 262-276, (2017); Zhou L., Baldacci R., Vigo D., Wang X., A multi-depot two-echelon vehicle routing problem with delivery options arising in the last mile distribution, Eur. J. Oper. Res., 265, 2, pp. 765-778, (2018); Zhou L., Wang X., Ni L., Lin Y., Location-routing problem with simultaneous home delivery and customers pickup for city distribution of online shopping purchases, Sustainability, 8, 8, (2016)","M.A.J. uit het Broek; Department of Operations, Faculty of Economics and Business, University of Groningen, Netherlands; email: a.j.uit.het.broek@rug.nl",null,"Elsevier Ltd",{"$nulls":5},3050548.0,null,"CMORA",null,"English","Comp. Oper. Res.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85079890614"]
["Refaningati T.; Nahry; Tangkudung E.S.W.; Kusuma A.","Refaningati, Tuesta (57216344815); Nahry (7409936161); Tangkudung, Ellen S. W. (57193131716); Kusuma, Andyka (42461737000)","57216344815; 7409936161; 57193131716; 42461737000","Analysis of characteristics and efficiency of smart locker system (Case study: Jabodetabek)",2020.0,"Evergreen",7.0,1.0,null,111.0,117.0,6.0,12.0,"10.5109/2740966","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85083283577&doi=10.5109%2f2740966&partnerID=40&md5=354bc1ce3cb2c808717296f40f513e61","Civil Engineering Department, Faculty of Engineering, Universitas Indonesia, Indonesia","Refaningati T., Civil Engineering Department, Faculty of Engineering, Universitas Indonesia, Indonesia; Nahry, Civil Engineering Department, Faculty of Engineering, Universitas Indonesia, Indonesia; Tangkudung E.S.W., Civil Engineering Department, Faculty of Engineering, Universitas Indonesia, Indonesia; Kusuma A., Civil Engineering Department, Faculty of Engineering, Universitas Indonesia, Indonesia","Last mile delivery is the last trip of an item before it arrives at the final destination. The current increase of last mile delivery is the impact of increasing home delivery services in areas that see a growing development of e-commerce. There are several issues in the operational process, including the high number of trips taken from parcel delivery service. One of the innovations used to solve these issues is the smart locker system. The objective of this research is to analyze the characteristics and efficiency of the smart locker system that has been running in Jabodetabek to reduce the trips taken for home delivery service. Data analysis was performed using the travel diary data of a single smart locker operator. Results showed that the use of smart locker is not without faults and causes the performance of each transit hub (as a part of a trip chain of smart lockers) to significantly differ. One issue includes the variable of waiting time either at the pickup or at the delivery of shipments. Another issue is that the coverage area for each locker is not the same, thus affecting the performance of each transit hub. In terms of delivery trip length, the use of the smart locker is 30.65% more efficient when compared to parcel delivery service. In order to deliver 222 items, the total trip length for parcel delivery is 717.8 km, while using the smart locker requires a total trip length of 497.83 km. © 2020, Novel Carbon Resource Sciences. All rights reserved.","Efficiency; Home delivery service; Last mile delivery; Smart locker",{"$nulls":5},"Publikasi Terindeks Internasional Untuk Tugas Akhir Mahasiswa UI; Universitas Indonesia, UI","This research is supported by research funds made available through the Research Fund of PITTA (Publikasi Terindeks Internasional Untuk Tugas Akhir Mahasiswa UI) of Universitas Indonesia, 2019.","Perkembangan E-Commerce Di Indonesia, (2017); E-Commerce Di Indonesia Dan Perkembangannya, (2016); Boyer K.K., Prud'homme A.M., Chung W., The Last Mile Challenge: Evaluating the Effects of Customer Density and Delivery Window, pp. 185-199, (2009); What is Last Mile Delivery? Part 1: How Omnichannel Retail is Affecting Transportation & Logistics.; Gevaers R., van de Voorde E., Vanelslander T., Cost Modelling and Simulation of Last-Mile Characteristics in an Innovative B2C Supply Chain Environment with Implications on Urban Areas and Cities, pp. 398-411, (2014); Ghajargar M., Zenezini G., Montanaro T., Home Delivery Service: Innovation and Emerging Needs, pp. 1371-1376, (2016); Prinsip-Prinsip Statistik Untuk Teknik Dan Sains, (2005); Huang Y., Kuo Y., The Evaluation of Logistics Service Quality on Home Delivery Service for Online Auction, pp. 1343-1348, (2008); Iwan S., Kijewska K., Lemke J., Analysis of Parcel Lockers Efficiency as The Last Mile Delivery Solution: The Result of The Research in Poland, (2015); Janjevic M., Winkenbach M., Merchan D., Integrating Collection-And-Delivery Points in the Strategic Design of Urban Last-Mile E-Commerce Distribution Networks, pp. 37-67, (2019); Lemke J., Iwan S., Korczak J., Usability of The Parcel Lockers from The Customer Perspective: The Research in Polish Cities, (2016); Lestari N.A., Reduction of CO2 Emission by Integrated Biomass Gasification-Solid Oxide Fuel Cell Combined with Heat Recovery and In-Situ CO2 Utilization, pp. 254-261, (2019); Lindner J., Last Mile Logistics Capability: A Multidimensional System Analysis for A General Modelling and Evaluation Approach, (2011); Martono N., Metode Penelitian Kuantitatif, (2012); Morganti E., Seidel S., Blanquart C., The Impact of E-Commerce on Final Deliveries: Alternative Parcel Delivery Services in France and Germany, (2014); Pal A., Uddin K., Thu K., Saha B.B., Environmental Assessment and Characteristics of Next Generation Refrigerants, pp. 58-66, (2018); PT Paxelbox Digital Unggul (Paxel), (2019); Ramadhan S.G., Analisis Komparatif Dampak Emisi Karbon Dari Aktivitas Last Mile Delivery Belanja Online Dan Konvensional, (2018); Turner K.M., Nagel K., How Driving Multiple Tours Affects the Results of Last Mile Delivery Vehicle Routing Problems, pp. 840-845, (2019); Duin J., Goffau W., Wiegmans B., Tavasszy L., Saes M., Improving Home Delivery Efficiency by Using Principles of Address Intelligence for B2C Deliveries, (2015); Visse J., Nemoto T., Browne M., Home Delivery and the Impacts on Urban Freight Transport: A Review, (2014); Wardhani S., Perkembangan E-Commerce Di Indonesia (1), (2017); Yuen K.F., Wang X., Wendy Ng L.T., Wong Y.D., An Investigation of Customers' Intention to Use Self-Collection Services for Last-Mile Delivery, pp. 1-8, (2018); Zhang Y., Un L., Hu X., Zhao C., Order Consolidation for the Last-Mile Split Delivery in Online Retailing, (2019); Zhou M., Zhao L., Campy K.S., Et al., Understanding Consumers' Behavior to Adopt Self-Service Parcel Services for Last-Mile Delivery, (2019)","T. Refaningati; Civil Engineering Department, Faculty of Engineering, Universitas Indonesia, Indonesia; email: tuestarefaningati@gmail.com",null,"Novel Carbon Resource Sciences",{"$nulls":5},2.189042E7,null,null,null,"English","Evergreen","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85083283577"]
["Kaushik V.; Kumar A.; Gupta H.; Dixit G.","Kaushik, Vineet (58747871900); Kumar, Ashwani (58737729100); Gupta, Himanshu (7201692177); Dixit, Gaurav (57200161372)","58747871900; 58737729100; 7201692177; 57200161372","A hybrid decision model for supplier selection in Online Fashion Retail (OFR)",2020.0,"International Journal of Logistics Research and Applications",null,null,null,1.0,25.0,24.0,11.0,"10.1080/13675567.2020.1791810","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85087754586&doi=10.1080%2f13675567.2020.1791810&partnerID=40&md5=5f363824e8befe28e6ce9b78ca5182f7","Indian Institute of Management, Kashipur, India; Department of Operations, Jaipuria Institute of Management, Noida, India; Department of Management Studies, Indian Institute of Technology (Indian School of Mines), Dhanbad, India; Department of Management Studies, Indian Institute of Technology, Roorkee, India","Kaushik V., Indian Institute of Management, Kashipur, India; Kumar A., Department of Operations, Jaipuria Institute of Management, Noida, India; Gupta H., Department of Management Studies, Indian Institute of Technology (Indian School of Mines), Dhanbad, India; Dixit G., Department of Management Studies, Indian Institute of Technology, Roorkee, India","Multichannel retailing has caused significant disruption in the market. The major credit for this disruption belongs to online retailing, which is proliferating at a high pace. With the immense growth, the online fashion retail sector faces many challenges as well. The majority of these challenges are attributed to the inefficiency of suppliers to deliver the right products at the right time. Thus, supplier selection becomes an important parameter for the success of the online fashion retail industry. This study focused on supplier selection based on seven main criteria, which are Operational Competency, Product Attribute, Logistic Warehousing, Ethics, Status, Business Competencies, and Versatility. An integrated Best Worst Method (BWM)–VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) methodology was applied to prioritise the criteria and select the most feasible suppliers among available suppliers. Out of thirty-eight sub-criteria, those that got most preferences are Just in Time (JIT) Capabilities, Order Flexibility, Return Policies, Technical Soundness, Billing Flexibility. The results of the study disseminated theoretical and managerial implications that can be applied in online fashion retail. © 2020, © 2020 Informa UK Limited, trading as Taylor & Francis Group.","BWM; E-commerce; online fashion retail; Online shopping; supplier selection; VIKOR",{"$nulls":7},{"$cut":{"chars":19808,"head":"Abdel-Basset M., Manogaran G., Gamal A., Smarandache F., A Hybrid Approach of Neutrosophic Sets and DEMATEL Method for Developing Supplier Selection Criteria, Design Automation for Embedded Systems, 22, 3, pp. 257-278, (2018); Aboutorab H., Saberi M., Asadabadi M.R., Hussain O., Chang E., ZBWM: The Z-Number Extension of Best Worst Method and its Application for Supplier Development, Expert Systems with Applications, 107, pp. 115-125, (2018); Alimardani M., Hashemkhani Zolfani S., Aghdaie M.H., Tamosaitiene J., A Novel Hybrid SWARA and VIKOR Methodology for Supplier Selection in an Agile Environment, Technological and Economic Development of Economy, 19, 3, pp. 533-548, (2013); Arbuthnot J.J., Slama M., Sisler G., Selection Criteria and Information Sources in the Purchase Decisions of Apparel Buyers of Small Retailing Firms, Journal of Small Business Management, 31, 2, (1993); Awasthi A., Kannan G., Green Supplier Development Program Selection Using NGT and VIKOR Under Fuzzy Environment, Computers and Industrial Engineering, 91, pp. 100-108, (2016); Aziz K.A., Mansor Z., Vendor Assessment Method: A Review, Advanced Science Letters, 24, 7, pp. 5204-5207, (2018); Bashar A., Hasin M.A.A., Lean Manufacturing Awareness and its Implementation Status in the Apparel Industry in Bangladesh, International Journal of Lean Enterprise Research, 2, 3, pp. 202-217, (2018); Basnet C., Leung J.M., Inventory Lot-Sizing with Supplier Selection, Computers and Operations Research, 32, 1, pp. 1-14, (2005); Bayazit O., Use of Analytic Network Process in Vendor Selection Decisions, Benchmarking: An International Journal, 13, 5, pp. 566-579, (2006); Bayazit O., Karpak B., ISAHP, Honolulu, Hawaii, July, (2005); Beck B., Key Strategic Issues in Online Apparel Retailing, (2000); Benton W.C., Krajewski L., Vendor Performance and Alternative Manufacturing Environments, Decision Sciences, 21, 2, pp. 403-415, (1990); Bernard P., Managing Vendor Performance, Production and Inventory Management Journal, 30, 1, (1989); Bhardwaj V., Fairhurst A., Fast Fashion: Response to Changes in the Fashion Industry, The International Review of Retail, Distribution and Consumer Research, 20, 1, pp. 165-173, (2010); Bhutta M.K.S., Supplier Selection Problem: Methodology Literature Review, Journal of International Information Management, 12, 2, (2003); Bottani E., Rizzi A., A Fuzzy Multi-Attribute Framework for Supplier Selection in an e-Procurement Environment, International Journal of Logistics: Research and Applications, 8, 3, pp. 249-266, (2005); Brewer A., Sloan N., Landers T.L., Intelligent Tracking in Manufacturing, Journal of Intelligent Manufacturing, 10, 3-4, pp. 245-250, (1999); Chamodrakas I., Batis D., Martakos D., Supplier Selection in Electronic Marketplaces Using Satisficing and Fuzzy AHP, Expert Systems with Applications, 37, 1, pp. 490-498, (2010); Chan F.T., Chan H.K., An AHP Model for Selection of Suppliers in the Fast Changing Fashion Market, The International Journal of Advanced Manufacturing Technology, 51, 9-12, pp. 1195-1207, (2010); Chang M.K., Cheung W., Tang M., Building Trust Online: Interactions among Trust Building Mechanisms, Information and Management, 50, 7, pp. 439-445, (2013); Chapman S.N., Just-in-time Supplier Inventory: An Empirical Implementation Model, The International Journal of Production Research, 27, 12, pp. 1993-2007, (1989); Chen Z.L., Zhang Z.G., Hu F., When Should Internet Retailers Adopt Dropshipping Model, Industrial Engineering and Management, 7, pp. 57-61, (2008); Crow L.E., Olshavsky R.W., Summers J.O., Industrial Buyers’ Choice Strategies: A Protocol Analysis, Journal of Marketing Research, 17, 1, pp. 34-44, (1980); Davidrajuh R., Modeling and Implementation of Supplier Selection Procedures for e-Commerce Initiatives, Industrial Management and Data Systems, 103, 1, pp. 28-38, (2003); de Almeida A.T., Multicriteria Decision Model for Outsourcing Contracts Selection Based on Utility Function and ELECTRE Method, Computers and Operations Research, 34, 12, pp. 3569-3574, (2007); De Boer L., Labro E., Morlacchi P., A Revie"}},"H. Gupta; Department of Management Studies, Indian Institute of Technology (Indian School of Mines), Dhanbad, India; email: himanshuguptadoms@gmail.com",null,"Taylor and Francis Ltd.",{"$nulls":5},1.3675567E7,null,null,null,"English","Int. J. Logist. Res. Applic.","Article","Final",null,"Scopus","2-s2.0-85087754586"]
["Yang G.; Huang Y.; Fu Y.; Huang B.; Sheng S.; Mao L.; Huang S.; Xu Y.; Le J.; Ouyang Y.; Yin Q.","Yang, Gege (57218996653); Huang, Yin (37039479700); Fu, Ying (57426184900); Huang, Biao (57219001534); Sheng, Sishi (57212390696); Mao, Lisha (57219002131); Huang, Shumin (57209652180); Xu, Yan (57219001585); Le, Jia (57218997602); Ouyang, Yun (57219000631); Yin, Qian (57211885766)","57218996653; 37039479700; 57426184900; 57219001534; 57212390696; 57219002131; 57209652180; 57219001585; 57218997602; 57219000631; 57211885766","Parcel Locker Location Based on a Bilevel Programming Model",2020.0,"Mathematical Problems in Engineering",2020.0,null,5263689.0,null,null,null,17.0,"10.1155/2020/5263689","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85090970622&doi=10.1155%2f2020%2f5263689&partnerID=40&md5=37faf62eec7a8a8a26c9184ffb72d907","School of Logistics and Transportation, Central South University of Forestry and Technology, Changsha, 410004, China","Yang G., School of Logistics and Transportation, Central South University of Forestry and Technology, Changsha, 410004, China; Huang Y., School of Logistics and Transportation, Central South University of Forestry and Technology, Changsha, 410004, China; Fu Y., School of Logistics and Transportation, Central South University of Forestry and Technology, Changsha, 410004, China; Huang B., School of Logistics and Transportation, Central South University of Forestry and Technology, Changsha, 410004, China; Sheng S., School of Logistics and Transportation, Central South University of Forestry and Technology, Changsha, 410004, China; Mao L., School of Logistics and Transportation, Central South University of Forestry and Technology, Changsha, 410004, China; Huang S., School of Logistics and Transportation, Central South University of Forestry and Technology, Changsha, 410004, China; Xu Y., School of Logistics and Transportation, Central South University of Forestry and Technology, Changsha, 410004, China; Le J., School of Logistics and Transportation, Central South University of Forestry and Technology, Changsha, 410004, China; Ouyang Y., School of Logistics and Transportation, Central South University of Forestry and Technology, Changsha, 410004, China; Yin Q., School of Logistics and Transportation, Central South University of Forestry and Technology, Changsha, 410004, China","In order to improve delivery network efficiency and to solve consumer satisfaction problems, parcel locker location optimisation scheme is proposed based on the delivery demand under the e-commerce environment. In this paper, a bilevel programming (BLP) model is established to identify the optimal location for parcel lockers by considering benefits of consumers and logistics planning departments. The upper-level model is to determine the optimal location by minimising the planners' cost, and the lower one gives an equilibrium demand distribution by minimising the consumers' pick-up cost. On the special form of constraints, a bilevel genetic algorithm is proposed based on GIS data and a genetic algorithm. Finally, a numerical example is employed to demonstrate the application of the method, which indicates that the model can solve the problem of parcel locker location. © 2020 Gege Yang et al.",null,"Location; Numerical methods; Bi-level programming; Bilevel genetic algorithms; Bilevel programming models; Consumer satisfactions; Demand distribution; Logistics planning; Network efficiency; Optimal locations; Genetic algorithms",{"$nulls":6},"Wang J.Q., Zou E., Analysis of Application of Smart Express Parcel Cabinets in Online Shopping Endpoint Logistics, Logistics Technology, 34, 5, pp. 58-60, (2015); Punakivi M., Yrjola H., Holmstrom J., Solving the last mile issue: Reception box or delivery box?, International Journal of Physical Distribution & Logistics Management, 31, 6, pp. 427-439, (2001); Shi S., Huang Y.F., Yan W., Research on automatic Logistic terminal equipment application in campus express, Computer Simulation, 32, 9, pp. 421-424, (2015); Li J., Lu S., Research and application of site selection and planning of intelligent self-service Locker on campus, Logistics Engineering and Management, 40, 1, pp. 74-77, (2018); Liu X.T., Research on the Layout of Pick-Up Points of A Company in Beijing, (2015); Aikens C.H., Facility location models for distribution planning, European Journal of Operational Research, 22, 3, pp. 263-279, (1985); Holmberg K., Exact solution methods for uncapacitated location problems with convex transportation costs, European Journal of Operational Research, 114, 1, pp. 127-140, (1999); Barahona F., Jensen D., Plant location with minimum inventory, Mathematical Programming, 83, pp. 101-111, (1998); Owen S.H., Daskin M.S., Strategic facility location: A review, European Journal of Operational Research, 111, 3, pp. 423-447, (1998); Zhou G., Min H., Gen M., The balanced allocation of customers to multiple distribution centers in the supply chain network: A genetic algorithm approach, Computers & Industrial Engineering, 43, 1-2, pp. 251-261, (2002); Miller T.C., Friesz T.L., Tobin R.L., \"equilibrium Facility Location on Networks,\", (1996); Sun H., Gao Z., Wu J., A bi-level programming model and solution algorithm for the location of logistics distribution centers, Applied Mathematical Modelling, 32, 4, pp. 610-616, (2008); Hansen P., Jaumard B., Savard G., New branch-and-bound rules for Linear bilevel programming, Siam Journal on Scientific and Statistical Computing, 13, 5, pp. 1194-1217, (1992); Judice J.J., Faustino A.M., A sequential LCP method for bilevel Linear programming, Annals of Operations Research, 34, 1-4, (1992); Bard J.F., Moore J.T., A branch and bound algorithm for the bilevel programming problem, Siam Journal on Scientific and Statistical Computing, 11, 2, pp. 281-292, (1990); Zhao W., Penalty function method for bi-level multiobjective programming, Acta Automatica Sinica, 24, 3, pp. 331-337, (1998); Shimizu K., Lu M., A global optimization method for the stackelberg problem with convex functions via problem transformation and concave programming, Ieee Transactions on Systems, Man, and Cybernetics, 25, 12, pp. 1635-1640, (1995); White D.J., Anandalingam G., A penalty function approach for solving bi-level linear programs, Journal of Global Optimization, 3, 4, pp. 397-419, (1993); Mathieu R., Pittard L., Anandalingam G., Genetic algorithm based approach to Bi-level Linear programming, RAIRO-Operations Research, 28, 1, pp. 1-21, (1994); Anandalingam G., \"artificial Intelligence Based Approaches for Hierarchical Optimization: In Impact of Recent Computer Advances in Operations Research,\", (1989); Gendreau M., Marcotte P., Savard G., A hybrid tabu-ascent algorithm for the Linear bilevel programming problem, Journal of Global Optimization, 8, 3, pp. 217-233, (1996); Yin Y., Genetic-algorithms-based approach for bilevel programming models, Journal of Transportation Engineering, 126, 2, pp. 115-120, (2000); Bard J., \"practical Bilevel Optimization Algorithm and Applications: Nonconvex Optmization and Its Applications,\", (1998); Chen S.X., Lan H.J., Location of fresh product self-collection cabinet based on Bi-level programming, Industrial Engineering and Management, 23, 6, pp. 57-63, (2018); Ben-Ayed O., Boyce D.E., Blair C.E., A general bilevel linear programming formulation of the network design problem, Transportation Research Part B: Methodological, 22, 4, pp. 311-318, (1988); Oduguwa V., Roy R., Bi-level Optimisation Using Genetic Algorithm; Xia G.M., Zeng J.C., A stochastic particle swarm optimization algorithm based on the genetic algorithm of roulette wheel selection, Computer Engineering and Science, 29, 6, pp. 6-11, (2007)",null,null,"Hindawi Limited",{"$nulls":5},"1024123X",null,null,null,"English","Math. Probl. Eng.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85090970622"]
["Ligang C.; Haili R.; Jie D.; Yajun Z.","Ligang, Cui (36705662700); Haili, Ren (57421046900); Jie, Deng (57421267200); Yajun, Zhang (57420937200)","36705662700; 57421046900; 57421267200; 57420937200","A particle swarm algorithm for a novel B2C multi-item replenishment and delivery coordination model with fuzzy random demands",2020.0,"Journal of Industrial Engineering and Engineering Management",34.0,6.0,null,183.0,190.0,7.0,4.0,"10.13587/j.cnki.jieem.2020.06.019","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85123265749&doi=10.13587%2fj.cnki.jieem.2020.06.019&partnerID=40&md5=e48fd0a1cd52282703ed69c48902bf81","School of Economics and Management, Chongqing Jiaotong University, Chongqing, 400074, China; Intellectual Property Institution of Chongqing, Chongqing University of Technology, Chongqing, 400050, China; School of Business Administration, Guizhou University of Finance and Economics, Guiyang, 550025, China","Ligang C., School of Economics and Management, Chongqing Jiaotong University, Chongqing, 400074, China; Haili R., School of Economics and Management, Chongqing Jiaotong University, Chongqing, 400074, China; Jie D., Intellectual Property Institution of Chongqing, Chongqing University of Technology, Chongqing, 400050, China; Yajun Z., School of Business Administration, Guizhou University of Finance and Economics, Guiyang, 550025, China","The rapid development and extraordinary achievements of e-commerce in China in recent years have attracted worldwide attention. As more and more companies embrace e-commerce, the fierce competition between e-commerce companies and traditional companies or even e-commerce companies erupted in an unprecedented situation. In all e-commerce models, business-to-consumer (B2C) is characterized by providing high-quality goods and services, reflecting greater development potential and stronger competitive strength than its rivals. However, in the face of a wide range of commodity categories and various operations of replenishment-delivery processes, B2C e-commerce logistics operations are under tremendous pressure to solve the problem of how to reasonably characterize the needs of customers in small quantities and uncertain demands to achieve stable and efficient operation of replenishment-delivery processes. By assuming the fuzzy demands of customers, this paper studies the multi-product joint replenishment and delivery (JRD) coordination problem of B2C e-commerce enterprises. First of all, in order to better assess and predict customer demand for uncertainty, we define commodity demand as a triangular fuzzy variable based on subjective judgments of different experts. Secondly, considering that the fuzzy interval is obtained based on empirical knowledge data and the fuzzy variables may be judged by different experts when using fuzzy variables, this paper uses fuzzy expected value theory to construct a fuzzy random JRD model to minimize the total cost of the system change. Thirdly, considering that the JRD model is essentially an NP-hard problem, this paper designs a particle swarm optimization (PSO) algorithm to solve the model. For the PSO algorithm, this paper designs a real and integer mixed encoding scheme to represent the basic processing cycle, the replenishment-delivery frequencies of multi-items. Fourthly, through the numerical experiment for the parameter sensitivity analysis, the optimal parameter combination for the PSO algorithm for subsequent experiments is found. Finally, PSO and genetic algorithm (GA) based on the optimal parameter combination were compared and solved. The numerical calculation results show that PSO gives better performance in searching efficiency and effectiveness than GA, but the searching stability is slightly weaker. Based on the above analysis, our research found that: (1) Fuzzy random expectation value theory is a suitable and reasonable method to deal with the uncertainty demand and coordinate the cognitive disparities of different experts' knowledge in judging customer demands; (2) Compared with GA, PSO algorithm has certain advantages in solving JRD problems, but there is still room for improvement, especially in solving stability. In future research, we will focus on solving two types of the model under this theme. One is to continue to expand the existing JRD model by considering the waiting costs of customers' fuzzy random. The other one is to continue to improve the performance of PSO to solve different JRDs. © 2020. All Rights Reserved.","B2C; Fuzzy demands; Joint replenishment and delivery; Particle swarm optimization",{"$nulls":5},"Innovative scientific research program for postgraduates of Chongqing, (CYS17216); Department of Education of Guizhou Province; National Office for Philosophy and Social Sciences, NPOPSS, (71602015); Fundamental and Frontier Research Project of Chongqing, (cstc2016jcyjA0530); Humanities and Social Sciences Youth Foundation, Ministry of Education of the People's Republic of China, (16YJC630014)","Received Date: 2018-06-30 Accepted Date: 2019-01-01 Funded Project: Supported by the National Social Science Foundation of China (71602015), the Humanities and Social Sciences Foundation of the Chinese Ministry of Education (16YJC630014), the Fundamental and Frontier Research Project of Chongqing ( cstc2016jcyjA0530 ), the Project of Guizhou Provincial Education Department (Qian-Jiao-He KY Code [2018]159) and the Innovative scientific research program for postgraduates of Chongqing (CYS17216) — 190 —","Cui L, Deng J, Liu F, Et al., Investigation of RFID investment in a single retailer two-supplier supply chain with random demand to decrease inventory inaccuracy [J], Journal of Cleaner Production, 142, pp. 2028-2044, (2017); Li C Y, Xu X F, Zhan D C., Joint replenishment problem with fuzzy constraints, Computer Integrated Manufacturing Systems, 14, 1, pp. 113-117, (2008); Wang L, Qu H, Chen X X, Et al., Fuzzy joint replenishment model considering transportation capacity constraints and quantity discount based on differential evolution algorithm[J], Chinese Journal of Management, 11, 10, pp. 1507-1513, (2014); Bian W L, Ju S D, Xu J, Et al., An empirical research on online B2C customer perceptions[J], Journal of Industrial Engineering/ Engineering Management, 25, 2, pp. 14-20, (2011); Li C, Ma L, Liang C Y., DFM-IA: A multi-source user interest data fetching mechanism for business-to-customer E-commerce, Journal of Industrial Engineering/Engineering Management, 31, 1, pp. 58-70, (2017); Wang L, Chen C, Zeng Y R., Differential evolution algorithm for stochastic joint replenishment model with resource constraint[J], Computer Integrated Manufacturing Systems, 17, 7, pp. 1541-1546, (2011); Xiao D, Zhou Y W, Zhong Y G, Et al., Co-opetition game analysis of retailers' joint purchasing coalitions with inventory technology sharing under stochastic demand, Journal of Industrial Engineering/ Engineering Management, 31, 4, pp. 194-199, (2017); Zhou J, Wang Y., Research on the model of corporate's procurement management with the involvement of 3PL with partial information[J], Journal of Industrial Engineering/Engineering Management, 32, 1, pp. 171-177, (2018); Zeng Y R, Wang L, Feng Y T., Joint replenishment model under fuzzy costs and resource constraints-differential evolution algorithm approach, Application Research of Computers, 29, 3, (2012); Zhang S, Mi Y L, Xu J H, Et al., Research on joint replenishment problem of aircraft consumable items with fuzzy resource constraint[J], Ordnance Industry Automation, 34, 11, pp. 4-8, (2015); Dutta Chakraborty, Roy, Continuous review inventory model in mixed fuzzy and stochastic environment[J], Applied Mathematics & Computation, 188, 1, pp. 970-980, (2007); Dalman H, Guzel N, Sivri M., A fuzzy set-based approach to multi-objective multi-item solid transportation problem under uncertainty, International Journal of Fuzzy Systems, 18, 4, pp. 716-729, (2016); Goyal S K, Satir A T., Joint replenishment inventory control: Deterministic and stochastic models [J], European Journal of Operational Research, 38, 1, pp. 2-13, (2007); Moon I K, Cha B C, Lee C U., The joint replenishment and freight consolidation of a warehouse in a supply chain [J], International Journal of Production Economics, 133, 1, pp. 344-350, (2011); Cui L, Deng J, Wang L, Et al., A novel locust swarm algorithm for the joint replenishment problem considering multiple discounts simultaneously [J], Knowledge-Based Systems, 111, pp. 51-62, (2016); Wang W., A study on the delivery model portfolio selection for general merchandise B2C[D], (2014); Yang J M, Hou X P, Cui H H, Et al., Improved multi-objective particle swarm optimization algorithm based on integrating multiply strategies, Control and Decision, 2, pp. 226-234, (2018); Wang L, Chen C, Zhang J L, Et al., A study on the supplier selection and order quantity allocation problem based on improved particle swarm optimization algorithm, Chinese Journal of Management Science, 17, 6, pp. 98-103, (2009); Eberhart R, Kennedy J., A new optimizer using particle swarm theory [C], Proceedings of the Sixth International Symposium on Micromachine Machine & Human Science, pp. 39-43, (1995); Cui L., Research on the joint replenishment models with the investment of the RFID technology[D], (2014)",null,null,"Zhejiang University",{"$nulls":5},1.0046062E7,null,null,null,"English","J. Industrial Eng. Eng. Management","Article","Final",null,"Scopus","2-s2.0-85123265749"]
["Simoni M.D.; Marcucci E.; Gatta V.; Claudel C.G.","Simoni, Michele D. (57195106271); Marcucci, Edoardo (6602255083); Gatta, Valerio (35109007100); Claudel, Christian G. (23391776600)","57195106271; 6602255083; 35109007100; 23391776600","Potential last-mile impacts of crowdshipping services: a simulation-based evaluation",2020.0,"Transportation",47.0,4.0,null,1933.0,1954.0,21.0,62.0,"10.1007/s11116-019-10028-4","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85068825808&doi=10.1007%2fs11116-019-10028-4&partnerID=40&md5=472996c05f22e63033e9b6b23c3c0e40","Department of Civil, Architectural, and Environmental Engineering, University of Texas at Austin, 301E Dean Keeton, St., Austin, 78712, TX, United States; Department of Public Institutions Economics and Society, University of Roma Tre, Via G. Chiabrera, 199, Rome, 00145, Italy; Center for Transportation and Logistics, Massachusetts Institute of Technology, 1 Amherst Street, Cambridge, 02142, MA, United States","Simoni M.D., Department of Civil, Architectural, and Environmental Engineering, University of Texas at Austin, 301E Dean Keeton, St., Austin, 78712, TX, United States, Center for Transportation and Logistics, Massachusetts Institute of Technology, 1 Amherst Street, Cambridge, 02142, MA, United States; Marcucci E., Department of Public Institutions Economics and Society, University of Roma Tre, Via G. Chiabrera, 199, Rome, 00145, Italy; Gatta V., Department of Public Institutions Economics and Society, University of Roma Tre, Via G. Chiabrera, 199, Rome, 00145, Italy; Claudel C.G., Department of Civil, Architectural, and Environmental Engineering, University of Texas at Austin, 301E Dean Keeton, St., Austin, 78712, TX, United States","Crowdsourced delivery services (crowdshipping) represent a shipping alternative to traditional delivery systems, particularly suitable for e-commerce. Although some benefits in terms of reduced pollution and congestion could be obtained by replacing dedicated freight trips, the impacts of crowdshipping are unclear and depend on several factors such as the transport mode used, the match between supply and demand, length of detours, and possible induced demand. For example, private drivers could modify their existing routes or engage in new trips to pick up and drop off packages; similarly, public transport users could carry along packages on their trips and drop them off at lockers installed around the stations. In this paper, we analyze by means of a simulation-based approach the potential impacts of alternative implementation frameworks. In order to account more realistically for last-mile delivery operations, a hybrid dynamic traffic simulation is adopted such that the macroscopic features of traffic (triggering of congestion, queue spillbacks and interactions with traffic signals) are reproduced in combination with the microscopic features of delivery operations (delivery vehicles are tracked along their routes). The effects on traffic and emissions are investigated for the adoption of crowdshipping by carriers delivering parcels in the city center of Rome, Italy. Results show that not only is the mode employed by crowdshippers crucial for the sustainability of such a measure, but also operational aspects involving the length of detour, parking behavior, and daily traffic variations. Crowdsourced deliveries by car have generally higher negative impacts than corresponding deliveries by public transit. However, limiting the deviations of crowdshippers from the original trips, providing adequate parking options, and incentivizing off-peak deliveries, could significantly reduce crowdshipping externalities. © 2019, Springer Science+Business Media, LLC, part of Springer Nature.","City logistics; Crowdshipping; Crowdsourced delivery; Dynamic traffic simulation; External costs","Italy; Lazio; Roma [Lazio]; Rome; Crowdsourcing; Drops; Economics; Traffic signals; Transportation routes; City logistics; Crowdshipping; Crowdsourced delivery; Dynamic traffic; External costs; computer simulation; crowdsourcing; electronic commerce; parking; public transport; sustainability; Traffic congestion",{"$nulls":6},"Allen J., Piecyk M., Piotrowska M., McLeod F., Cherrett T., Ghali K., Wise S., Understanding the impact of e-commerce on last-mile light goods vehicle activity in urban areas: the case of London, Transp. Res. Part D Transp. Environ., 61, (2017); Amer A., Chow J.Y., A downtown on-street parking model with urban truck delivery behavior, Transp. Res. Part A Policy Pract., 102, pp. 51-67, (2017); Archetti C., Savelsbergh M., Speranza M.G., The vehicle routing problem with occasional drivers, Eur. J. Oper. Res., 254, 2, pp. 472-480, (2016); Arslan A.M., Agatz N., Kroon L., Zuidwijk R., Crowdsourced delivery—a dynamic pickup and delivery problem with ad hoc drivers, Transp. Sci., 53, 1, pp. 222-235, (2018); Baindur D., Macario R.M., Mumbai lunch box delivery system: A transferable benchmark in urban logistics?, Res. Transp. Econ., 38, pp. 110-121, (2013); Barth M., Boriboonsomsin K., Real-world carbon dioxide impacts of traffic congestion, Transp. Res. Rec. J. Transp. Res. Board, 2058, pp. 163-171, (2008); Boulter P.G., Barlow T.J., McCrae I.S., Emission factors 2009: Report 3-exhaust emission factors for road vehicles in the United Kingdom, (2009); Buldeo Rai H., Verlinde S., Macharis C., Shipping outside the box. Environmental impact and stakeholder analysis of a crowd logistics platform in Belgium, J. Clean. Prod., 202, (2018); Buldeo Rai H., Verlinde S., Merckx J., Macharis C., Crowd logistics: An opportunity for more sustainable urban freight transport?, Eur. Transp. Res. Rev., 9, 3, (2017); Cap Gemini: Evolving E-Commerce Market Dynamics. Cap Gemini, (2013); Cheu R.L., Jin X., Ng K.C., Ng Y.L., Srinivasan D., Calibration of FRESIM for Singapore expressway using genetic algorithm, J. Transp. Eng., 124, 6, pp. 526-535, (1998); Cleophas C., Cottrill C., Ehmke J.F., Tierney K., Collaborative urban transportation: recent advances in theory and practice, Eur. J. Oper. Res., 273, pp. 801-816, (2018); (2016); Dablanc L., Rodrigue J.P., The Geography of Urban Freight. The Geography of Urban Transportation, (2017); Dantzig G., Fulkerson R., Johnson S., Solution of a large-scale traveling-salesman problem, J. Oper. Res. Soc. Am., 2, 4, pp. 393-410, (1954); Dolan S., How crowdsourcing shipping through technology will make last mile delivery cheaper, Business Insider, (2018); Gatta V., Marcucci E., Nigro M., Serafini S., Sustainable urban freight transport adopting public transport-based crowdshipping for B2C deliveries, Eur. Transp. Res. Rev., 11, 1, (2019); Gatta V., Marcucci E., Nigro M., Patella S.M., Serafini S., Public transport-based crowdshipping for sustainable city logistics: assessing economic and environmental impacts, Sustainability, 11, 1, (2019); Gazis D.C., Herman R., The moving and “phantom” bottlenecks, Transp. Sci., 26, 3, pp. 223-229, (1992); Google Traffic: Google Traffic Map of Rome, (2018); Hawkins A.J., Parking Tickets: All in the Cost of Doing Business. the Bane of Many Companies, Tickets Defy Solutions, (2013); Design Manual for Roads and Bridges, 12; Kafle N., Zou B., Lin J., Design and modeling of a crowdsource-enabled system for urban parcel relay and delivery, Transp. Res. Part B Methodol., 99, pp. 62-82, (2017); Le Pira M., Marcucci E., Gatta V., Ignaccolo M., Inturri G., Pluchino A., Towards a decision-support procedure to foster stakeholder involvement and acceptability of urban freight transport policies, Eur. Transp. Res. Rev., 9, 4, (2017); Lighthill M.J., Whitham G.B., On kinematic waves. II. A theory of traffic flow on long crowded roads, Proceedings of the Royal Society of London A: Mathematical, Physical and Engineering Sciences, 229, pp. 317-345, (1955); Lozzi G., Gatta V., Marcucci E., European urban freight transport policies and research funding: Are priorities and Horizon 2020 calls aligned?, Region, 5, 1, pp. 53-71, (2018); Marcucci E., Delle Site P., Gatta V., Pompetti P., Ex-ante acceptability of road pricing and modal shift extimation: the case of Rome, Sci. Reg., 17, 3, pp. 477-504, (2018); Marcucci E., Gatta V., Investigating the potential for off-hour deliveries in the city of Rome: retailers’ perceptions and stated reactions, Transp. Res. Part A Policy Practice, 102, pp. 142-156, (2017); Marcucci E., Le Pira M., Gatta V., Inturri G., Ignaccolo M., Pluchino A., Simulating participatory urban freight transport policy-making: accounting for heterogeneous stakeholders’ preferences and interaction effects, Transp. Res. Part E Logist. Transp. Rev., 103, pp. 69-86, (2017); Marcucci E., Le Pira M., Carrocci C.S., Gatta V., Pieralice E., Connected shared mobility for passengers and freight: Investigating the potential of crowdshipping in urban areas, 2017 5Th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS), pp. 839-843, (2017); McKinnon A., Crowdshipping—A Communal Approach to Reducing Urban Traffic Levels? Kuehne Logistics University, (2016); Miller J., Nie Y., Stathopoulos A., Crowdsourced urban package delivery: modeling traveler willingness to work as crowdshippers, Transp. Res. Rec. J. Transp. Res. Board, 2610, 1, pp. 67-75, (2017); Munoz J.C., Daganzo C.F., Moving bottlenecks: A theory grounded on experimental observation, Transportation and Traffic Theory in the 21St Century: Proceedings of the 15Th International Symposium on Transportation and Traffic Theory, pp. 441-461, (2002); Newell G.F., A simplified theory of kinematic waves in highway traffic, part II: queueing at freeway bottlenecks, Transp. Res. Part B, 27, 4, pp. 289-303, (1993); Paloheimo H., Lettenmeier M., Waris H., Transport reduction by crowdsourced deliveries—a library case in Finland, J. Clean. Prod., 132, pp. 240-251, (2016); Papageorgiou M., Some remarks on macroscopic traffic flow modelling, Transp. Res. A Policy Pract., 32, 5, pp. 323-329, (1998); Punel A., Ermagun A., Stathopoulos A., Studying determinants of crowd-shipping use, Travel Behav. Soc., 12, pp. 30-40, (2018); Punel A., Stathopoulos A., Modeling the acceptability of crowdsourced goods deliveries: role of context and experience effects, Transp. Res. Part E Logist. Transp. Rev., 105, pp. 18-38, (2017); Qi W., Li L., Liu S., Shen Z.J.M., Shared mobility for Last-Mile delivery: design, operational prescriptions and environmental impact, Manuf. Serv. Oper. Manag., 20, 4, pp. 737-751, (2018); Richards P.I., Shock waves on the highway, Oper. Res., 4, 1, pp. 42-51, (1956); Sampaio A., Savelsbergh M., Veelenturf L., van Woensel T., Crowd-based city logistics, Sustainable Transportation and Smart Logistics, pp. 381-400, (2019); Savelsbergh M.W., Sol M., The general pickup and delivery problem, Transp. Sci., 29, 1, pp. 17-29, (1995); Serafini S., Nigro M., Gatta V., Marcucci E., Evaluating service’ scenarios for crowdshipping by public transport, Transp. Res. Procedia, 30, pp. 101-110, (2018); Simoni M.D., Claudel C.G., A simulation framework for modeling urban freight operations impacts on traffic networks, Simul. Model. Pract. Theory, 86, pp. 36-54, (2018); Simoni M.D., Claudel C.G., A Fast Lax–Hopf Formula to Solve the Lighthill–Whitham–Richards Traffic Flow Model on Networks, (2018); Stock S., Postal Service’s Big Delivery Edge: No Parking Tickets, (2014); Taniguchi E., Kakimoto T., Effects of e-commerce on urban distribution and the environment, J. East. Asia Soc. Transp. Stud., 5, pp. 2355-2366, (2003); Full Ranking 2018, (2018); Wang Y., Zhang D., Liu Q., Shen F., Lee L.H., Towards enhancing the last-mile delivery: an effective crowd-tasking model with scalable solutions, Transp. Res. Part E Logist. Transp. Rev., 93, pp. 279-293, (2016); Wang Y., Szeto W.Y., Han K., Friesz T.L., Dynamic traffic assignment: a review of the methodological advances for environmentally sustainable road transportation applications, Transp. Res. Part B Methodol., 111, pp. 370-394, (2018)","M.D. Simoni; Department of Civil, Architectural, and Environmental Engineering, University of Texas at Austin, Austin, 301E Dean Keeton, St., 78712, United States; email: msimoni@mit.edu",null,"Springer",{"$nulls":5},494488.0,null,null,null,"English","Transportation","Article","Final",null,"Scopus","2-s2.0-85068825808"]
["Vinsensius A.; Wang Y.; Chew E.P.; Lee L.H.","Vinsensius, Albert (57215366263); Wang, Yuan (57079310600); Chew, Ek Peng (7102013740); Lee, Loo Hay (55667526300)","57215366263; 57079310600; 7102013740; 55667526300","Dynamic Incentive Mechanism for Delivery Slot Management in E-Commerce Attended Home Delivery",2020.0,"Transportation Science",54.0,3.0,null,567.0,587.0,20.0,24.0,"10.1287/trsc.2019.0953","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85086590948&doi=10.1287%2ftrsc.2019.0953&partnerID=40&md5=d765ed33b8cd3abba5d358e7eb699f3a","Department of Industrial Systems Engineering and Management, National University of Singapore, Singapore, 117576, Singapore","Vinsensius A., Department of Industrial Systems Engineering and Management, National University of Singapore, Singapore, 117576, Singapore; Wang Y., Department of Industrial Systems Engineering and Management, National University of Singapore, Singapore, 117576, Singapore; Chew E.P., Department of Industrial Systems Engineering and Management, National University of Singapore, Singapore, 117576, Singapore; Lee L.H., Department of Industrial Systems Engineering and Management, National University of Singapore, Singapore, 117576, Singapore","In attended home delivery, challenges arise in practice because of the short strict time windows, stochastic customer requests, and varying customers’ preferences for delivery slots. In this study, we focus on integrating dynamic time slot incentives and order delivery with the intention of reducing overall delivery cost and improving profitability. The proposed incentive mechanism is able to exploit the variability in the marginal fulfillment cost of an order and the customers’ preferences to influence the customers’ selection of delivery slots. We present an approximate dynamic programming approach to estimate the marginal fulfillment cost using the operational vehicle routing cost while accounting for future orders. We demonstrate that the proposed incentive mechanism can achieve a high level of savings (of up to 70%) with respect to the benchmark customer-free-choice scenario. It is also noted that the proposed mechanism effectively exploits higher order density and vehicle availability to achieve a higher level of savings. © 2020 INFORMS","Approximate dynamic programming; Attended home delivery; Dynamic incentives","Dynamic programming; Dynamics; Sales; Stochastic systems; Vehicle routing; Approximate dynamic programming; Delivery costs; Dynamic time; Higher-order; Home delivery; Incentive mechanism; Time windows; Cost benefit analysis",{"$nulls":4},"Agency for Science, Technology and Research of Singapore, (A1895a0033)","History: This paper has been accepted for the Transportation Science Special Section on Urban Freight Transportation and Logistics. Funding: This work was partially supported by Agency for Science, Technology and Research of Singapore [Grant A1895a0033]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/trsc.2019.0953.","Agatz N, Campbell AM, Fleischmann M, Savels M, Challenges and opportunities in attended home delivery, The Vehicle Routing Problem: Latest Advances and New Challenges, Operations Research/Computer Science Interfaces Series, 43, pp. 379-396, (2008); Agatz N, Campbell A, Fleischmann M, Savelsbergh M, Time slot management in attended home delivery, Transportation Sci, 45, 3, pp. 435-449, (2011); Agatz N, Campbell AM, Fleischmann M, van Nunen J, Savelsbergh M, Revenue management opportunities for Internet retailers, J. Revenue Pricing Management, 12, 2, pp. 128-138, (2013); Archetti C, Jabali O, Speranza MG, Multi-period vehicle routing problem with due dates, Comput. Oper. Res, 61, pp. 122-134, (2015); Asdemir K, Jacob VS, Krishnan R, Dynamic pricing of multiple home delivery options, Eur. J. Oper. Res, 196, 1, pp. 246-257, (2009); Braysy O, Gendreau M, Vehicle routing problem with time windows, part I: Route construction and local search algorithms, Transportation Sci, 39, 1, pp. 104-118, (2005); Braysy O, Gendreau M, Vehicle routing problem with time windows, part II: Metaheuristics, Transportation Sci, 39, 1, pp. 119-139, (2005); Bruck BP, Cordeau JF, Iori M, A practical time slot management and routing problem for attended home services, Omega, 81, December, pp. 208-219, (2018); Buhler D, Klein R, Neugebauer M, Model-based delivery cost approximation in attended home services, Comput. Indust. Engrg, 98, August, pp. 78-90, (2016); Campbell AM, Savelsbergh MWP, Decision support for consumer direct grocery initiatives, Transportation Sci, 39, 3, pp. 313-327, (2005); Campbell AM, Savelsbergh M, Incentive schemes for attended home delivery services, Transportation Sci, 40, 3, pp. 327-341, (2006); Ehmke JF, Campbell AM, Customer acceptance mechanisms for home deliveries in metropolitan areas, Eur. J. Oper. Res, 233, 1, pp. 193-207, (2014); Elmaghraby W, Keskinocak P, Dynamic pricing in the presence of inventory considerations: Research overview, current practices, and future directions, Management Sci, 49, 10, pp. 1287-1309, (2003); Figliozzi MA, Mahmassani HS, Jaillet P, Pricing in dynamic vehicle routing problems, Transportation Sci, 41, 3, pp. 302-318, (2007); Francis P, Smilowitz K, Tzur M, The period vehicle routing problem with service choice, Transportation Sci, 40, 4, pp. 439-454, (2006); Hubner A, Kuhn H, Wollenburg J, Last mile fulfilment and distribution in omni-channel grocery retailing, Internat. J. Retail Distribution Management, 44, 3, pp. 228-247, (2016); Klein R, Neugebauer M, Ratkovitch D, Steinhardt C, Differentiated time slot pricing under routing considerations in attended home delivery, Transportation Sci, 53, 1, pp. 236-255, (2019); Laporte G, Fifty years of vehicle routing, Transportation Sci, 43, 4, pp. 408-416, (2009); Larsen A, Madsen OBG, Solomon MM, Partially dynamic vehicle routing—Models and algorithms, J. Oper. Res. Soc, 53, 6, pp. 637-646, (2002); Larsen A, Madsen OBG, Solomon MM, Recent developments in dynamic vehicle routing systems, The Vehicle Routing Problem: Latest Advances and New Challenges, Operations Research/Computer Science Interfaces Series, 43, pp. 199-218, (2008); Liu L, Li K, Liu Z, A capacitated vehicle routing problem with order available time in e-commerce industry, Engrg. Optim, 49, 3, pp. 449-465, (2017); Lu C, Interview with RedMart’s CEO on the operations backend, (2014); Pillac V, Gendreau M, Gueret C, Medaglia AL, A review of dynamic vehicle routing problems, Eur. J. Oper. Res, 225, 1, pp. 1-11, (2013); Pisinger D, Ropke S, A general heuristic for vehicle routing problems, Comput. Oper. Res, 34, 8, pp. 2403-2435, (2007); Powell WB, What you should know about approximate dynamic programming, Naval Res. Logist, 56, 3, pp. 239-249, (2009); Psaraftis HN, Wen M, Kontovas CA, Dynamic vehicle routing problems: Three decades and counting, Networks, 67, 1, pp. 3-31, (2015); Ritzinger U, Puchinger J, Hartl RF, A survey on dynamic and stochastic vehicle routing problems, Internat. J. Production Res, 54, 1, pp. 215-231, (2016); Ulmer MW, Approximate Dynamic Programming for Dynamic Vehicle Routing, Operations Research/Computer Science Interfaces Series, 61, (2017); Ulmer MW, Soeffker N, Mattfeld DC, Value function approximation for dynamic multi-period vehicle routing, Eur. J. Oper. Res, 269, 3, pp. 883-899, (2018); Ulmer MW, Goodson JC, Mattfeld DC, Hennig M, Offline–online approximate dynamic programming for dynamic vehicle routing with stochastic requests, Transportation Sci, 53, 1, pp. 1-318, (2019); Voccia SA, Campbell AM, Thomas BW, The same-day delivery problem for online purchases, Transportation Sci, 53, 1, pp. 167-184, (2017); Yang X, Strauss AK, An approximate dynamic programming approach to attended home delivery management, Eur. J. Oper. Res, 263, 3, pp. 935-945, (2017); Yang X, Strauss AK, Currie CSM, Eglese R, Choice-based demand management and vehicle routing in e-fulfillment, Transportation Sci, 50, 2, pp. 473-488, (2016)","A. Vinsensius; Department of Industrial Systems Engineering and Management, National University of Singapore, Singapore, 117576, Singapore; email: vinsensius.albert@u.nus.edu",null,"INFORMS Inst.for Operations Res.and the Management Sciences",{"$nulls":5},411655.0,null,"TRSCB",null,"English","Transp Sci","Article","Final",null,"Scopus","2-s2.0-85086590948"]
["Wang S.; Wu R.; Chu F.; Yu J.","Wang, Shijin (24472325200); Wu, Ruochen (57211600793); Chu, Feng (7201881008); Yu, Jianbo (16033533200)","24472325200; 57211600793; 7201881008; 16033533200","Variable neighborhood search-based methods for integrated hybrid flow shop scheduling with distribution",2020.0,"Soft Computing",24.0,12.0,null,8917.0,8936.0,19.0,22.0,"10.1007/s00500-019-04420-6","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85074575492&doi=10.1007%2fs00500-019-04420-6&partnerID=40&md5=6485e0d6adc4b905c5369e2841025f31","School of Economics and Management, Tongji University, Shanghai, 200092, China; Laboratoire IBISC, Univ-Évry, Université Paris-Saclay, Évry, 91025, France; School of Economics and Management, Fuzhou University, Fuzhou, 350116, China; School of Mechanical Engineering, Tongji University, Shanghai, 200092, China","Wang S., School of Economics and Management, Tongji University, Shanghai, 200092, China; Wu R., School of Economics and Management, Tongji University, Shanghai, 200092, China; Chu F., Laboratoire IBISC, Univ-Évry, Université Paris-Saclay, Évry, 91025, France, School of Economics and Management, Fuzhou University, Fuzhou, 350116, China; Yu J., School of Mechanical Engineering, Tongji University, Shanghai, 200092, China","With the rapid development of make-to-order pattern including E-commerce and takeout and catering service in restaurants, the study of integrated scheduling and distribution receives more and more attentions. Based on a practical order picking and distribution system, a three-stage hybrid flow shop scheduling problem with distribution is studied. Each order is processed on the hybrid flow shop which consists of identical parallel machines with sequence-dependent setup times at stage 1, identical parallel machines at stage 2 and dedicated machines at stage 3, followed by a multi-trip traveling salesman problem with capacitated vehicles for customers of different destination areas. A mixed-integer linear programming model is formulated to minimize the maximum delivery completion time. A variable neighborhood search (VNS)-based method, a four-layered constructive heuristic method (denoted by CHVNS) and a hybrid heuristic method (denoted by CONSVNS) which combines the VNS method and the CHVNS method are developed to solve the problems with practical size. Computational experiments show the effectiveness and efficiency of the proposed methods. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature.","Constructive heuristic; Hybrid flow shop; Parallel machines; Traveling salesman problem; Variable neighborhood search","Integer programming; Machine shop practice; Scheduling; Traveling salesman problem; Constructive heuristic; Effectiveness and efficiencies; Hybrid flow shop; Hybrid flow shop scheduling; Mixed integer linear programming model; Parallel machine; Sequence-dependent setup time; Variable neighborhood search; Heuristic methods",{"$nulls":4},"National Natural Science Foundation of China, NNSF, (71571135, 71971155); Fundamental Research Funds for the Central Universities"," This work was supported by the National Natural Science Foundation of China (Grant Nos. 71571135, 71971155). The work was also supported by the Fundamental Research Funds for the Central Universities. The authors would express appreciation to Miss Benyan Ye for helping in discussions on the algorithm development. ","Albrecht W., Steinrucke M., Continuous-time production, distribution and financial planning with periodic liquidity balancing, J Schedul, 20, 3, pp. 219-237, (2017); Albrecht W., Steinrucke M., Continuous-time scheduling of production, distribution and sales in photovoltaic supply chains with declining prices, Flex Serv Manuf J, (2019); Belo-Filho M.A.F., Amorim P., Almada-Lobo B., An adaptive large neighbourhood search for the operational integrated production and distribution problem of perishable products, Int J Prod Res, 53, 20, pp. 6040-6058, (2015); Bozer Y.A., Kile J.W., Order batching in walk-and-pick order picking systems, Int J Prod Res, 46, 7, pp. 1887-1909, (2008); Cakici E., Mason S.J., Geismar H.N., Fowler J.W., Scheduling parallel machines with single vehicle delivery, J Heuristics, 20, 5, pp. 511-537, (2014); Chang Y.C., Lee C.Y., Machine scheduling with job delivery coordination, Eur J Oper Res, 158, 2, pp. 470-487, (2004); Chen Z.L., Integrated production and distribution operations: taxonomy, models, and review, Handbook of quantitative supply chain analysis, pp. 711-745, (2004); Chen Z.L., Integrated production and outbound distribution scheduling: review and extensions, Oper Res, 58, 1, pp. 130-148, (2010); Chen Z.L., Vairaktarakis G.L., Integrated scheduling of production and distribution operations, Manag Sci, 51, 4, pp. 614-628, (2005); The 41Th China Statistical Report on Internet Development, Published by China Internet Network Information Center (CNNIC), (2018); Coelho I.M., Munhoz P.L.A., Ochi L.S., Souza M.J.F., Bentes C., Farias R., An integrated CPU–GPU heuristic inspired on variable neighbourhood search for the single vehicle routing problem with deliveries and selective pickups, Int J Prod Res, 54, 4, pp. 945-962, (2016); De Armas J., Lalla-Ruiz E., Expsito-Izquierdo C., Landa-Silva D., Melin-Batista B., A hybrid GRASP-VNS for ship routing and scheduling problem with discretized time windows, Eng Appl Artif Intell, 45, C, pp. 350-360, (2015); Devapriya P., Ferrell W., Geismar N., Integrated production and distribution scheduling with a perishable product, Eur J Oper Res, 259, 3, pp. 906-916, (2017); Fu L.L., Aloulou M.A., Triki C., Integrated production scheduling and vehicle routing problem with job splitting and delivery time windows, Int J Prod Res, 55, 20, pp. 5942-5957, (2017); Garcia J.M., Lozano S., Production and delivery scheduling problem with time windows, Comput Ind Eng, 48, pp. 733-742, (2005); Hansen P., Mladenovic N., Variable neighborhood search: principles and applications, Eur J Oper Res, 130, 3, pp. 449-467, (2001); Hong S., Johnson A.L., Peters B.A., Batch picking in narrow-aisle order picking systems with consideration for picker blocking, Eur J Oper Res, 221, 3, pp. 557-570, (2012); Karaoglan I., Kesen S.E., The coordinated production and transportation scheduling problem with a time-sensitive product: a branch-and-cut algorithm, Int J Prod Res, 55, 2, pp. 536-557, (2017); Kergosien Y., Gendreau M., Billaut J.-C., A benders decomposition-based heuristic for a production and outbound distribution scheduling problem with strict delivery constraints, Eur J Oper Res, 262, pp. 287-298, (2017); Kesen S.E., Bektas T., Integrated production scheduling and distribution planning with time windows, Lean and green supply chain management. 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Marandi F., Ghomi S.M.T.F., Integrated multi-factory production and distribution scheduling applying vehicle routing approach, Int J Prod Res, 57, 3, pp. 722-748, (2019); Menendez B., Pardo E.G., Alonso-Ayuso A., Molina E., Duarte A., Variable neighborhood search strategies for the order batching problem, Comput Oper Res, 78, pp. 500-512, (2017); Mladenovic N., Hansen P., Variable neighborhood search, Comput Oper Res, 24, 11, pp. 1097-1100, (1997); Mohammadi S., Mirzapour Al-e-Hashem S.M.J., Rekik Y., An integrated production scheduling and delivery route planning with multi-purpose machines: a case study from a furniture manufacturing company, Int J Prod Econ, 219, pp. 347-359, (2020); Moons S., Ramaekers K., Caris A., Arda Y., Integrating production scheduling and vehicle routing decisions at the operational decision level: a review and discussion, Comput Ind Eng, 104, pp. 224-245, (2017); Ng C.T., Lu L.F., On-line integrated production and outbound distribution scheduling to minimize the maximum delivery completion time, J Schedul, 15, 3, pp. 391-398, (2012); 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Wang D.J., Zhu J.Q., Wei X.W., Cheng T.C.E., Yin Y.Q., Wang Y.Z., Integrated production and multiple trips vehicle routing with time windows and uncertain travel times, Comput Oper Res, 103, pp. 1-12, (2019); Zhang B., Pan Q.K., Gao L., Zhang X.L., Chen Q.D., A hybrid variable neighborhood search algorithm for the hot rolling batch scheduling problem in compact strip production, Comput Ind Eng, 116, pp. 22-36, (2018); Zhong W.Y., Dosa G., Tan Z.Y., On the machine scheduling problem with job delivery coordination, Eur J Oper Res, 182, pp. 1057-1072, (2007); Zhong W.Y., Chen Z.L., Chen M., Integrated production and distribution scheduling with committed delivery dates, Oper Res Lett, 38, pp. 133-138, (2010); Zou X., Liu L., Li K., Li W., A coordinated algorithm for integrated production scheduling and vehicle routing problem, Int J Prod Res, 56, 15, pp. 5005-5024, (2018)","S. Wang; School of Economics and Management, Tongji University, Shanghai, 200092, China; email: shijinwang@tongji.edu.cn",null,"Springer",{"$nulls":5},1.4327643E7,null,null,null,"English","Soft Comput.","Article","Final",null,"Scopus","2-s2.0-85074575492"]
["Saha S.K.; Zhuang G.; Li S.","Saha, Swapan Kumar (57208663830); Zhuang, Guijun (7004628711); Li, Sihan (57213621837)","57208663830; 7004628711; 57213621837","Will consumers pay more for efficient delivery? An empirical study of what affects E-customers' satisfaction and willingness to pay on online shopping in Bangladesh",2020.0,"Sustainability (Switzerland)",12.0,3.0,1121.0,null,null,null,15.0,"10.3390/su12031121","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85081237902&doi=10.3390%2fsu12031121&partnerID=40&md5=c0b64980a0570b3d691345ce900e7342","School of Management, Xi'an Jiaotong University, Xi'an, 710049, China","Saha S.K., School of Management, Xi'an Jiaotong University, Xi'an, 710049, China; Zhuang G., School of Management, Xi'an Jiaotong University, Xi'an, 710049, China; Li S., School of Management, Xi'an Jiaotong University, Xi'an, 710049, China","The delivery of products to the end consumer has been widely considered in the e-commerce sector as new challenges to reach customers and provide them with timely and efficient delivery have surfaced. Less focus has been given to information about delivery efficiency that impacts online shoppers' relations with e-retailers. This study's research model builds on the extended unified theory of acceptance and use of technology (UTAUT-2) by adding the critical e-commerce variables of delivery efficiency, cost-saving efficiency, and online purchase experience (shopping satisfaction and subsequent willingness to pay). The conceptual model was tested, and samples were collected using an online survey hosted on Google Forms using e-mail in Bangladesh. The findings show that consumers' willingness to pay is enhanced by satisfaction with online shopping and delivery efficiency. The study also contributes insights into how cost-saving efficiency affects online customer satisfaction and the intention to repurchase. Also, by applying hierarchical regression analysis, this study contributes to understanding how e-retailers can provide a functional online experience for customers. Finally, our findings offer guidelines to e-retailers regarding increasing shopping satisfaction, the intention to repurchase, and the willingness to pay more. © 2020 by the authors.","Cost saving efficiency; Delivery efficiency; E-shopping satisfaction; Intention to repurchase; Online shopping experience; Willingness to pay","Bangladesh; conceptual framework; consumption behavior; cost analysis; electronic commerce; empirical analysis; Internet; shopping activity; willingness to pay",{"$nulls":4},"National Natural Science Foundation of China General program; National Natural Science Foundation of China key Program; Xi'an Jiaotong University; Xi’an Jiaotong University, XJTU; National Key Research and Development Program of China, NKRDPC, (71132005, 71472149)","Funding text 1: This work was supported by the National Natural Science Foundation of China General program (grant number 71472149) and the National Natural Science Foundation of China key Program (grant number 71132005). This work is also supported by Xi'an Jiaotong University, China.; Funding text 2: Funding: This work was supported by the National Natural Science Foundation of China General program (grant number 71472149) and the National Natural Science Foundation of China key Program (grant number 71132005). This work is also supported by Xi’an Jiaotong University, China.",{"$cut":{"chars":18881,"head":"EMarketer's Worldwide Retail and Ecommerce Sales: EMarketer's Updated Forecast and New Mcommerce Estimates for 2016-2021-eMarketer, (2020); Ramkumar B., Ellie Jin B., Examining pre-purchase intention and post-purchase consequences of international online outshopping (IOO): The moderating effect of E-tailer's country image, J. Retail. Consum. Serv, 49, pp. 186-197, (2019); Slap V., Online Shopping Getting Costlier for VAT slap[pipe]The Daily Star, (2020); (2017); Rahman M.A., Islam M.A., Esha B.H., Sultana N., Chakravorty S., Consumer buying behavior towards online shopping: An empirical study on Dhaka city, Bangladesh, Cogent Bus. Manag, 5, pp. 1-22, (2018); Al Mamun M.A., Griffiths M.D., The association between Facebook addiction and depression: A pilot survey study among Bangladeshi students, Psychiatry Res, 271, pp. 628-633, (2019); Siddiquee N.A., E-government and transformation of service delivery in developing countries, Transform. Gov People Process Policy, 10, pp. 368-390, (2016); Talukder M.S., Shen L., Hossain Talukder M.F., Bao Y., Determinants of user acceptance and use of open government data (OGD): An empirical investigation in Bangladesh, Technol. Soc, 56, pp. 147-156, (2019); Thirumalai S., Sinha K.K., Customer satisfaction with order fulfillment in retail supply chains: Implications of product type in electronic B2C transactions, J. Oper. Manag, 23, pp. 291-303, (2005); Visser J., Nemoto T., Browne M., Home Delivery and the Impacts on Urban Freight Transport: A Review, Procedia-Soc. Behav. Sci, 125, pp. 15-27, (2014); Chou S., Chen C.-W., Lin J.-Y., Female online shoppers, Internet Res, 25, pp. 542-561, (2015); Yu J., Subramanian N., Ning K., Edwards D., Product delivery service provider selection and customer satisfaction in the era of internet of things: A Chinese e-retailers' perspective, Int. J. Prod. Econ, 159, pp. 104-116, (2015); Jain N.K., Gajjar H., Shah B.J., Sadh A., E-fulfillment dimensions and its influence on customers in e-tailing: A critical review, Asia Pac. J. Mark. Logist, 29, pp. 347-369, (2017); Cao Y., Ajjan H., Hong P., Post-purchase shipping and customer service experiences in online shopping and their impact on customer satisfaction: An empirical study with comparison, Asia Pac. J. Mark. Logist, 30, pp. 400-416, (2018); Huang W.-H., Shen G.C., Liang C.-L., The effect of threshold free shipping policies on online shoppers' willingness to pay for shipping, J. Retail. Consum. Serv, 48, pp. 105-112, (2019); Vakulenko Y., Shams P., Hellstrom D., Hjort K., Service innovation in e-commerce last mile delivery: Mapping the e-customer journey, J. Bus. Res, 101, pp. 461-468, (2019); Loo W.H., Yeow P.H.P., Chong S.C., User acceptance of Malaysian government multipurpose smartcard applications, Gov. Inf. Q, 26, pp. 358-367, (2009); Venkatesh V., Morris M.G., Davis G.B., Davis F.D., User Acceptance of Information Technology: Toward a Unified View, MIS Q, 27, pp. 425-478, (2003); Moore G.C., Benbasat I., Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation, Inf. Syst. Res, 2, pp. 192-222, (1991); Fishbein M., Ajzen I., Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research;, (1975); Davis F.D., Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology, MIS Q, 13, pp. 319-340, (1989); Ajzen I., The theory of planned behavior, Organ. Behav. Hum. Decis. Process, 50, pp. 179-211, (1991); Thompson R.L., Higgins C.A., Howell J.M., Personal Computing: Toward a Conceptual Model of Utilization, MIS Q, 15, pp. 125-143, (2006); Taylor S., Todd P., Assessing IT Usage: The Role of Prior Experience, MIS Q, 19, pp. 561-570, (1995); Compeau D., Higgins C., Development of a Measure and Initial Test, Manag. Inf. Syst. Res. Center Univ. Minesota, 19, pp. 189-211, (1995); Davis F.D., Bagozzi R.P., Warshaw P.R., Extrinsic and Intrinsic Motivation to Use Computers in the Workplace1, J. Appl. Soc. Psychol, 22, pp. 1111-1132, (1992); Bigne E., Sanz S., Ruiz C., Aldas J., Why Some Internet Users Don't Buy Air"}},"S.K. Saha; School of Management, Xi'an Jiaotong University, Xi'an, 710049, China; email: swapan@iubat.edu",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85081237902"]
["Huang X.; Xie R.; Huang L.","Huang, Xiangrong (55500283600); Xie, Ruhe (7202459055); Huang, Lijuan (55324150500)","55500283600; 7202459055; 55324150500","Real-time emergency management mode of cold chain logistics for agricultural products under the background of 'Internet+'",2020.0,"Journal of Intelligent and Fuzzy Systems",38.0,6.0,null,7461.0,7473.0,12.0,19.0,"10.3233/JIFS-179819","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85088694937&doi=10.3233%2fJIFS-179819&partnerID=40&md5=efa88c0cc7142b95a427cdce6f00854b","School of Traffic and Transportation Engineering, Central South University, Changsha, China; School of Management, Guangzhou University, Guangzhou, China","Huang X., School of Traffic and Transportation Engineering, Central South University, Changsha, China, School of Management, Guangzhou University, Guangzhou, China; Xie R., School of Management, Guangzhou University, Guangzhou, China; Huang L., School of Management, Guangzhou University, Guangzhou, China","To solve the problems of the traditional cold chain logistics management mode of agricultural products, such as loose circulation, inaccurate information transmission, untimely processing, serious loss of fresh agricultural products, a real-time and accurate management of cold chain logistics is established to study the real-time emergency management mode of cold chain logistics for agricultural products under the background of 'Internet+'. Method: Under the background of 'Internet+', the e-commerce platform and the cold chain logistics network are combined, and the physical real-time emergency management mode of the cold chain of agricultural products is divided into the sub-mode of 'production warehouse+cold chain', the sub-mode of 'e-commerce+cold chain express+smart cabinet' and the sub-mode of 'cold chain storage+chain new retail'; through the circulation efficiency improvement algorithm of cold logistics supply chain, the circulation loss between nodes is reduced, to improve the circulation efficiency of the supply chain; The evaluation method of real-time emergency management mode for cold chain logistics, the entropy weight method and the analytic hierarchy process are selected to jointly determine the weight, and the fuzzy comprehensive evaluation method is used to comprehensively evaluate the emergency management effect of cold chain logistics for agricultural product. Results: The final score of the performance evaluation in enterprise SX's fresh agricultural product supply chain using the emergency management mode is 69.52 points, and the efficiency value of cold product logistics management in the enterprise C is 0.536. Conclusion: The real-time emergency management mode of cold chain logistics of agricultural products studied has certain feasibility, which can accurately analyze the advantages and disadvantages of cold chain logistics management of different enterprises. © 2020 - IOS Press and the authors. All rights reserved.","agricultural products; cold chain logistics; Internet+; management mode; supply chain","Agricultural products; Agricultural robots; Civil defense; Disasters; Efficiency; Electronic commerce; Risk management; Supply chains; Cold chain logistics; Efficiency improvement; Emergency management; Entropy weight method; Fresh agricultural products; Fuzzy comprehensive evaluation method; Inaccurate information; Logistics supply chains; Supply chain management",{"$nulls":4},"Ministry of Education of the People's Republic of China, MOE, (08JA630019); National Office for Philosophy and Social Sciences, NPOPSS, (15BGL201)","This work is supported by the Humanities and Social Sciences Research Project of the Ministry of Education of China (No. 08JA630019); the National Social Science Foundation of China (No. 15BGL201).","Yoo B., Oh K., Baek J.B., A study on improved emergency management system-focused on response to diffusion of oil spilled in marine, British Journal of Ophthalmology, 30, 2, pp. 83-89, (2015); Lei C., Lin W.H., Miao L., A stochastic emergency vehicle redeployment model for an effective response to traffic incidents, Ieee Transactions on Intelligent Transportation Systems, 16, 2, pp. 898-909, (2015); Jabbour C.J.C., Sobreiro V.A., Campos L.M.D.S., An analysis of the literature on humanitarian logistics and supply chain management: Paving the way for future studies, Annals of Operations Research, 5, 6, pp. 1-19, (2017); Kristensen D.D., Lorenson T., Bartholomew K., Can thermostable vaccines help address cold-chain challenges? Results from stakeholder interviews in six low-and middleincome countries, Vaccine, 34, 7, pp. 899-904, (2016); Akalin E., Yaka E., Yilmaz S., Compliance with the infectious diseases society of America guidelines for emergency management of febrile neutropenia in cancer patients, Acta Medica Mediterranea, 31, 4, pp. 785-792, (2015); Maria H.I., Wegner E.A., Practitioner-centered, Longterm Testing of An Ict-based Triage System for Emergency Management, Journal of Apicultural Research, 53, 2, pp. 269-278, (2015); Li J.F., Tuo X.G., Lin Y., Study on vehicle routing problems in logistics distribution, Computer Simulation, 33, 4, pp. 184-188, (2016); Albuquerque J.P.D., Fonte C.C., Almeida J.P.D., How volunteered geographic information can be integrated into emergency management practice? First lessons learned from an urban fire simulation in the city of Coimbra, Ieee Transactions on Biomedical Engineering, 52, 10, pp. 1625-1631, (2016); Brockow K., Schallmayer S., Beyer K., Effects of a structured educational intervention on knowledge and emergency management in patients at risk for anaphylaxis, Allergy, 70, 2, pp. 227-235, (2015); Cosme-Silva L., Moretti A.B.S., Lima D.C., Knowledge of parents from public and private school students on emergency management of avulsed permanent teeth, Journal of Public Health, 25, 2, pp. 1-5, (2016); Krishnamurti L., Smith-Packard B., Gupta A., Impact of individualized pain plan on the emergency management of children with sickle cell disease, Pediatric Blood &Cancer, 61, 10, pp. 1747-1753, (2015); Dixon M., Scutt P., Appleton J.P., PP18|Interim analysis of ambulance logistics and timings in patients recruited into the rapid intervention with glyceryl trinitrate in hypertensive stroke trial-2 (right-2), Emergency Medicine Journal, 34, 10, pp. e63-e67, (2017); Nguyentat M., Cornelius C., Hoffman A., The Manchester triage system (mts): A score for emergency management of patients with acute gastrointestinal bleeding, Zeitschrift fur Gastroenterologie, 56, 5, pp. 479-487, (2018); Singh R.K., Gunasekaran A., Kumar P., Third party logistics (3PL) selection for cold chain management: A fuzzy AHP and fuzzy TOPSIS approach, Annals of Operations Research, 267, 1-2, pp. 531-553, (2018); Curnin S., Owen C., Paton D., A theoretical framework for negotiating the path of emergency management multiagency coordination, Applied Ergonomics, 47, 47, pp. 300-307, (2015); Parris S., Planning for failure: A framework evaluation of Nova Scotia's environmental emergency management capacity in the context of tailings dam failure, Geophysical Journal International, 94, 1, pp. 21-34, (2015); Donker T., Blankers M., Hedman E., Economic evaluations of Internet interventions for mental health: A systematic review, Psychological Medicine, 45, 16, pp. 3357-3376, (2015); Gao W., Hosamani S., Distance learning techniques for ontology similarity measuring and ontology mapping, Cluster Computing-The Journal of Networks Software Tools and Applications, 20, 2 SI, pp. 959-968, (2017); Wu W., Peng Y., Extension of grey relational analysis for facilitating group consensus to oil spill emergency management, Annals of Operations Research, 238, 1-2, pp. 615-635, (2016); Xiao X., He Q., Fu Z., Applying cs and WSN methods for improving efficiency of frozen and chilled aquatic products monitoring system in cold chain logistics, Food Control, 60, 7, pp. 656-666, (2016); Xiao X., He Q., Li Z., Improving traceability and transparency of table grapes cold chain logistics by integrating WSN and correlation analysis, Food Control, 73, pp. 1556-1563, (2017); Ahmad Y., Ali U., Bilal M., Zafar S., Zahid Z., Some new standard graphs labeled by 3-total edge product cordial labeling, Applied Mathematics &Nonlinear Sciences, 2, 1, pp. 61-72, (2017); Sagna Y., Multidimensional BSDE with Poisson jumps of Osgood type, Applied Mathematics and Nonlinear Sciences, 4, 2, pp. 387-394, (2019); Yang Y., Postolache O., Internet of things for smart ports: Technologies and challenges, Ieee Instrumentation &Measurement Magazine, 21, 1, pp. 34-43, (2018); Liu Z., Wang J., Effects of the Sharing Economy on Sequential Innovation Products, Complexity, (2019)",null,null,"IOS Press",{"$nulls":5},1.0641246E7,null,null,null,"English","J. Intelligent Fuzzy Syst.","Article","Final",null,"Scopus","2-s2.0-85088694937"]
["Guo H.; Zhang Y.; Zhang C.; Liu Y.; Zhou Y.","Guo, Hao (57190736884); Zhang, Ying (58747574300); Zhang, Chunnan (57202380833); Liu, Yu (58611031700); Zhou, Yuan (58845936100)","57190736884; 58747574300; 57202380833; 58611031700; 58845936100","Location-inventory decisions for closed-loop supply chain management in the presence of the secondary market",2020.0,"Annals of Operations Research",291.0,"2024-02-01",null,361.0,386.0,25.0,9.0,"10.1007/s10479-018-3039-0","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85048127770&doi=10.1007%2fs10479-018-3039-0&partnerID=40&md5=6cae94781d2e966e0b9de24921a85121","School of Management, Jinan University, Guangzhou, 510632, Guangdong, China; Department of Industrial and Systems Engineering, The State University of New York at Buffalo, Buffalo, 14260, NY, United States; Department of Accounting, Temple University, Philadelphia, 19122, PA, United States; College of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan, 430081, China; Department of Industrial, Manufacturing and Systems Engineering, University of Texas at Arlington, Arlington, 76019, TX, United States","Guo H., School of Management, Jinan University, Guangzhou, 510632, Guangdong, China; Zhang Y., Department of Industrial and Systems Engineering, The State University of New York at Buffalo, Buffalo, 14260, NY, United States; Zhang C., Department of Accounting, Temple University, Philadelphia, 19122, PA, United States; Liu Y., College of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan, 430081, China; Zhou Y., Department of Industrial, Manufacturing and Systems Engineering, University of Texas at Arlington, Arlington, 76019, TX, United States","This paper studies a location-inventory problem in a closed-loop supply chain by considering the demand and sales in the primary and secondary markets. Based on a real business program in a big e-commerce company, we develop a mixed-integer nonlinear programming model with a single hybrid production-recovery center, multiple hybrid distribution-collection centers, and many customer zones. As a closed-loop system, forward and reverse logistics flows in each market are considered, and the logistics flows between the two markets are also captured. Moreover, a novel heuristic approach based on differential evolution is designed to solve the model efficiently, and its performance is also compared with other popular methods. Finally, research implications and managerial insights are provided to advance real-world practices. © 2018, Springer Science+Business Media, LLC, part of Springer Nature.","Closed-loop supply chain; Consumer returns; Differential evolution; Location-inventory problem; Reverse logistics; Secondary market",{"$nulls":5},"National Natural Science Foundation of China, NSFC, (61502359)","This work was supported by the National Natural Science Foundation of China (Grant Number 61502359).","Abdallah T., Diabat A., Simchi-Levi D., Sustainable supply chain design: A closed-loop formulation and sensitivity analysis, Production Planning & Control, 23, 2-3, pp. 120-133, (2012); Allevi E., Gnudi A., Konnov I.V., Oggioni G., Evaluating the effects of environmental regulations on a closed-loop supply chain network: A variational inequality approach, Annals of Operations Research, 261, 1-2, pp. 1-43, (2018); Angelus A., A multiechelon inventory problem with secondary market sales, Management Science, 57, 12, pp. 2145-2162, (2011); Consumers Choosing Refurbished Products to Be Environmentally Responsible, according to Liquidity Services’ Survey, (2014); Daskin M.S., Coullard C.R., Shen Z.J.M., An inventory-location model: Formulation, solution algorithm and computational results, Annals of Operations Research, 110, 1, pp. 83-106, (2002); Diabat A., Abdallah T., Henschel A., A closed-loop location-inventory problem with spare parts consideration, Computers & Operations Research, 54, pp. 245-256, (2015); Diabat A., Richard J.-P., Codrington C.W., A Lagrangian relaxation approach to simultaneous strategic and tactical planning in supply chain design, Annals of Operations Research, 203, 1, pp. 55-80, (2013); Diggins M.A., Chen C., Chen J., A review: Customer returns in fashion retailing, Analytical modeling research in fashion business, pp. 31-48, (2016); Eppen G., Effects of centralization on expected costs in a multi-location newsboy problem, Management Science, 25, 5, pp. 498-501, (1979); Farahani R.Z., Bajgan H.R., Fahimnia B., Kaviani M., Location-inventory problem in supply chains: A modelling review, International Journal of Production Research, 53, 12, pp. 3769-3788, (2015); Fattahi M., Govindan K., Integrated forward/reverse logistics network design under uncertainty with pricing for collection of used products, Annals of Operations Research, 253, 1, pp. 193-225, (2017); Ferguson M., Guide V.D.R., Souza G.C., Supply chain coordination for false failure returns, Manufacturing & Service Operations Management, 8, 4, pp. 376-393, (2006); Govindan K., Soleimani H., Kannan D., Reverse logistics and closed-loop supply chain: A comprehensive review to explore the future, European Journal of Operational Research, 240, pp. 603-626, (2015); Guo H., Li C., Zhang Y., Zhang C., Lu M., A location-inventory problem in a closed-loop supply chain with secondary market consideration, Sustainability, 10, 6, (2018); Guo H., Li C., Zhang Y., Zhang C., Wang Y., A nonlinear integer programming model for integrated location, inventory and routing decisions in a closed-loop supply chain, Complexity, (2018); Guo S., Shen B., Choi T.M., Jung S., A review on supply chain contracts in reverse logistics: Supply chain structures and channel leaderships, Journal of Cleaner Production, 144, pp. 387-402, (2017); Huang X., Gu J.W., Ching W.K., Siu T.K., Impact of secondary market on consumer return policies and supply chain coordination, Omega, 45, pp. 57-70, (2014); Worldwide Market for Used Smartphones Forecast to Grow to 222.6 Million Units in 2020, (2016); Jha A., Somani K., Tiwari M.K., Chan F.T., Fernandes K.J., Minimizing transportation cost of a joint inventory location model using modified adaptive differential evolution algorithm, The International Journal of Advanced Manufacturing Technology, 60, 1-4, pp. 329-341, (2012); Jung K.S., Dawande M., Geismar H.N., Guide V.D.R., Sriskandarajah C., Supply planning models for a remanufacturer under just-in-time manufacturing environment with reverse logistics, Annals of Operations Research, 240, 2, pp. 533-581, (2016); Kannan D., Garg K., Jha P.C., Diabat A., Integrating disassembly line balancing in the planning of a reverse logistics network from the perspective of a third party provider, Annals of Operations Research, 253, 1, pp. 353-376, (2017); Lee H., Whang S., The impact of the secondary market on the supply chain, Management Science, 48, 6, pp. 719-731, (2002); Leininger K., The U.S. pharmaceutical secondary market. White paper, (2007); Li Y., Guo H., Zhang Y., An integrated location-inventory problem in a closed-loop supply chain with third-party logistics, International Journal of Production Research, 56, 10, pp. 3462-3481, (2018); Liu H., Lei M., Huang T., Leong G.K., Refurbishing authorization strategy in the secondary market for electrical and electronic products, International Journal of Production Economics, 195, pp. 198-209, (2018); Masoudipour E., Amirian H., Sahraeian R., A novel closed-loop supply chain based on the quality of returned products, Journal of Cleaner Production, 151, pp. 344-355, (2017); Nahmias S., Production and operations analysis, (2013); Oraiopoulos N., Ferguson M.E., Toktay L.B., Relicensing as a secondary market strategy, Management Science, 58, 5, pp. 1022-1037, (2012); Prakash S., Kumar S., Soni G., Jain V., Rathore A.P.S., Closed-loop supply chain network design and modelling under risks and demand uncertainty: An integrated robust optimization approach, Annals of Operations Research, (2018); Shen Z.J.M., Integrated supply chain design models: A survey and future research directions, Journal of Industrial & Management Optimization, 3, 1, pp. 831-838, (2007); Shen Z.J.M., Coullard C., Daskin M.S., A joint location-inventory model, Transportation Science, 37, 1, pp. 40-55, (2003); Souza G.C., Closed-loop supply chains: A critical review, and future research, Decision Sciences, 44, 1, pp. 7-38, (2013); Storn R., Price K., Differential evolution-a simple and efficient heuristic for global optimization over continuous spaces, Journal of Global Optimization, 11, 4, pp. 341-359, (1997); Vahdani B., Soltani M., Yazdani M., Mousavi S.M., A three level joint location-inventory problem with correlated demand, shortages and periodic review system: Robust meta-heuristics, Computers & Industrial Engineering, 109, pp. 113-129, (2017); Vorasayan J., Ryan S.M., Optimal price and quantity of refurbished products, Production and Operations Management, 15, 3, pp. 369-383, (2006); Xiong Y., Zhao P., Xiong Z., Li G., The impact of product upgrading on the decision of entrance to a secondary market, European Journal of Operational Research, 252, 2, pp. 443-454, (2016); Zhang Z.H., Unnikrishnan A., A coordinated location-inventory problem in closed-loop supply chain, Transportation Research Part B: Methodological, 89, pp. 127-148, (2016)","Y. Zhang; Department of Industrial and Systems Engineering, The State University of New York at Buffalo, Buffalo, 14260, United States; email: yz29@buffalo.edu",null,"Springer",{"$nulls":5},2545330.0,null,null,null,"English","Ann. Oper. Res.","Article","Final",null,"Scopus","2-s2.0-85048127770"]
["Kapser S.; Abdelrahman M.","Kapser, Sebastian (57203634512); Abdelrahman, Mahmoud (55523598900)","57203634512; 55523598900","Acceptance of autonomous delivery vehicles for last-mile delivery in Germany – Extending UTAUT2 with risk perceptions",2020.0,"Transportation Research Part C: Emerging Technologies",111.0,null,null,210.0,225.0,15.0,154.0,"10.1016/j.trc.2019.12.016","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85077047606&doi=10.1016%2fj.trc.2019.12.016&partnerID=40&md5=5a72bf25826b87af53246ecf3e1514d2","Northumbria University Newcastle Business School, City Campus East, NE1 8ST, United Kingdom","Kapser S., Northumbria University Newcastle Business School, City Campus East, NE1 8ST, United Kingdom; Abdelrahman M., Northumbria University Newcastle Business School, City Campus East, NE1 8ST, United Kingdom","The inevitable need to develop new delivery practices in last-mile logistics arises from the enormously growing business to consumer (B2C) e-commerce and the associated challenges for logistics service providers. Autonomous delivery vehicles (ADVs) are believed to have the potential to revolutionise last-mile delivery in a way that is more sustainable and customer focused. However, if not widely accepted, the introduction of ADVs as a delivery option can be a substantial waste of resources. At present, the research on consumers’ receptivity of innovations in last-mile delivery, such as ADVs, is limited. This study is the first that investigates the users’ acceptance of ADVs in Germany by utilising an extended Unified Theory of Acceptance and Use of Technology (UTAUT2) and adapted it to the context of ADVs in last-mile delivery. Quantitative data was collected through an online survey approach (n = 501) and structural equation modelling was undertaken. The results indicate that price sensitivity is the strongest predictor of behavioural intention (i.e., user acceptance), followed by performance expectancy, hedonic motivation, perceived risk, social influence and facilitating conditions, whereas no effect could be found for effort expectancy. These findings have important theoretical and practical contributions in the areas of technology acceptance and last-mile delivery. © 2019","Germany; Home delivery; Last-mile transportation; Perceived risk; User acceptance; UTAUT2","Germany; Autonomous vehicles; Germany; Home delivery; Last mile; Perceived risk; User acceptance; UTAUT2; electronic commerce; perception; risk assessment; transportation system; Risk perception",{"$nulls":6},"Adell E., Acceptance of Driver Support Systems, Proceedings of the European Conference on Human Centred Design for Intelligent Transport Systems, pp. 475-486, (2010); Agarwal R., Prasad J., A conceptual and operational definition of personal innovativeness in the domain of information technology, Inf. Syst. Res., 9, 2, pp. 204-215, (1998); Ajzen I., The theory of planned behavior, Organ. Behav. Hum. Decis. 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Findings from a field experiment, Transport. Res. Part C: Emerg. Technol., 95, pp. 320-334, (2018); Zhu X., Xie X., Effects of knowledge on attitude formation and change toward genetically modified foods, Risk Analy. Off. Publica. Soc. Risk Analy., 35, 5, pp. 790-810, (2015); Zmud J., Sener I.N., Wagner J., Self-driving vehicles: determinants of adoption and conditions of usage, Transport. Res. Record: J. Transport. Res. Board, 2565, 1, pp. 57-64, (2016); Zmud J.P., Sener I.N., Towards an understanding of the travel behavior impact of autonomous vehicles, Transp. Res. Procedia, 25, pp. 2500-2519, (2017)","S. Kapser; Northumbria University Newcastle Business School, City Campus East, NE1 8ST, United Kingdom; email: sebastian.kapser@t-online.de",null,"Elsevier Ltd",{"$nulls":5},"0968090X",null,null,null,"English","Transp. Res. Part C Emerg. Technol.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85077047606"]
["Cohen N.; Fraser K.T.; Arnow C.; Mulcahy M.; Hille C.","Cohen, Nevin (35117574000); Fraser, Katherine Tomaino (57217134067); Arnow, Chloe (57217128304); Mulcahy, Michelle (57217133036); Hille, Christophe (57217133071)","35117574000; 57217134067; 57217128304; 57217133036; 57217133071","Online grocery shopping by NYC public housing residents using supplemental nutrition assistance program (SNAP) benefits: A service ecosystems perspective",2020.0,"Sustainability (Switzerland)",12.0,11.0,4694.0,null,null,null,24.0,"10.3390/su12114694","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85086387232&doi=10.3390%2fsu12114694&partnerID=40&md5=c58e4218eead889bbf4160bb7a1c9f1e","Department of Health Policy and Management, CUNY Graduate School of Public Health and Health Policy, New York, 10027, NY, United States; CUNY Urban Food Policy Institute, New York, 10027, NY, United States; Enterprise Community Partners, Inc., New York, 10004, NY, United States; Karen Karp and Partners, P.O. Box 515, Southold, 11971, NY, United States","Cohen N., Department of Health Policy and Management, CUNY Graduate School of Public Health and Health Policy, New York, 10027, NY, United States, CUNY Urban Food Policy Institute, New York, 10027, NY, United States; Fraser K.T., CUNY Urban Food Policy Institute, New York, 10027, NY, United States; Arnow C., Enterprise Community Partners, Inc., New York, 10004, NY, United States; Mulcahy M., Enterprise Community Partners, Inc., New York, 10004, NY, United States; Hille C., Karen Karp and Partners, P.O. Box 515, Southold, 11971, NY, United States","This paper examines adoption of online grocery shopping, and potential cost and time savings compared to brick and mortar food retailers, by New York City public housing residents using Supplemental Nutrition Assistance Program (SNAP) benefits. A mixed methods action research project involving the co-creation of an online shopping club, the Farragut Food Club (FFC), recruited 300 members who registered to shop online using SNAP, and received waivers on delivery minimums and provided technical assistance and centralized food delivery. We conducted a survey (n = 206) and focus groups to understand shopping practices; FFC members collected receipts of groceries over two weeks before and after the pilot to measure foods purchased, stores patronized, and prices. We interviewed FFC members to elicit experiences with the pilot, and estimated cost differences between products purchased in brick and mortar stores and equivalent products online, and transportation time and cost differences. Online shopping represented a small (2.4%) percentage of grocery spending. Unit prices for products purchased on Amazon ($0.28) were significantly higher than for equivalent products purchased in brick and mortar stores ($0.23) (p < 0.001.) Compatibility with existing routines, low relative advantage, and cost of online products limited the adoption of online shopping among SNAP users. © 2020 by the authors.","Food access; Food stamps; Innovation diffusion; Online grocery shopping; Supplemental nutrition assistance program (SNAP)","New York [New York (STT)]; cost analysis; food security; food supplementation; Internet; nutritional status; public spending; questionnaire survey; retailing; shopping activity",{"$nulls":4},"Farragut Food Club; Fund for Public Housing; NYC Housing Authority; Robin Hood Foundation","Funding text 1: This project received financial support from the Robin Hood Foundation and the Reinvestment Fund. The authors would like to acknowledge all project partners who supported this work: Enterprise Community Partners, Karen Karp & Partners, Brooklyn Community Services, the NYC Housing Authority, the Fund for Public Housing, and the Farragut Food Club, as well as all members of the Farragut Houses community.; Funding text 2: Funding: This project received financial support from the Robin Hood Foundation and the Reinvestment Fund.","US Online Grocery Survey 2019, (2020); The Online Grocery Report: The Market, Drivers, Key Players, and Opportunities in a Rising Segment of Ecommerce, (2020); Meena S., Swerdlow F., Kumar S., The State of Global Online Grocery Retail;, (2018); The Digitally Engaged Food Shopper: Developing Your Omnichannel Collaboration Model, (2020); Jones J.M., Kashanchi S., Online Grocery Shopping Still Rare in U.S. Gallup, (2020); SNAP FNS Launches the Online Purchasing Pilot, (2020); Healthful Foods Could Be Just a Click Away: FNS Works to Bring Online Shopping to Snap Purchases, (2020); Cohen N., SNAP at the Community Scale: How Neighborhood Characteristics Affect Participation and Food Access, Am. J. Public Health, 109, pp. 1646-1651, (2019); SNAP Online Purchasing to Cover 90% of Households. Press Release No. 0268.20. 20 May 2020, (2020); Martinez O., Tagliaferro B., Rodriguez N., Athens J., Abrams C., Elbel B., EBT payment for online grocery orders: A mixed-methods study to understand its uptake among SNAP recipients and the barriers to and motivators for its use, J. Nutr. Educ. Behav, 50, pp. 396-402, (2018); Rogus S., Guthrie J.F., Niculescu M., Mancino L., Online Grocery Shopping Knowledge, Attitudes, and Behaviors Among SNAP Participants, J. Nutr. Educ. Behav, 52, pp. 539-545, (2020); Brandt E.J., Silvestri D.M., Mande J.R., Holland M.L., Ross J.S., Availability of Grocery Delivery to Food Deserts in States Participating in the Online Purchase Pilot, JAMA Netw. Open, 2, (2019); Rogers E.M., Diffusion of Innovations, (1995); Vargo S.L., Wieland H., Akaka M.A., Innovation through institutionalization: A service ecosystems perspective, Ind. Mark. Manag, 44, pp. 63-72, (2015); Vargo S.L., Akaka M.A., Value Cocreation and Service Systems (Re)Formation: A Service Ecosystems View, Serv. Sci, 4, pp. 207-217, (2012); Vargo S.L., Akaka M.A., Wieland H., Rethinking the process of diffusion in innovation: A service-ecosystems and institutional perspective, J. Bus. Res, (2020); Taillard M., Peters L.D., Pels J., Mele C., The role of shared intentions in the emergence of service ecosystems, J. Bus. Res, 69, pp. 2972-2980, (2016); Colyvas J.A., Jeannette A., Ubiquity and legitimacy: Disentangling diffusion and institutionalization, Soc. Theory, 29, pp. 27-53, (2011); Lewin G.W., Resolving Social Conflicts, (1948); Carter G., Action research in community planning, J. Community Prac, 11, pp. 121-131, (2003); Baum F., MacDougall C., Smith D., Participatory action research, J. Epidemiol. Community Health, 60, (2006); Resident Characteristics Report, (2019); Community Health Survey 2017, (2019); The Value of Travel Time Savings: Departmental Guidance for Conducting Economic Evaluations Revision 2 (2016 Update), (2020); Hesse-Biber S., Qualitative Approaches to Mixed Methods Practice, Qual. Inc, 16, pp. 455-468, (2010)","N. Cohen; Department of Health Policy and Management, CUNY Graduate School of Public Health and Health Policy, New York, 10027, United States; email: nevin.cohen@sph.cuny.edu",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85086387232"]
["Sen B.; Ydyrys S.; Omarova A.; Munassipova M.; Kuralbayev A.","Sen, Bulent (57209715858); Ydyrys, Serikbay (57191893020); Omarova, Aizhan (57208482832); Munassipova, Malike (57209713463); Kuralbayev, Almas (57188842835)","57209715858; 57191893020; 57208482832; 57209713463; 57188842835","Supply chain management improvement in Kazakhstan E-commerce",2020.0,"International Journal of Supply Chain Management",9.0,3.0,null,331.0,337.0,6.0,1.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85087750662&partnerID=40&md5=3996586bc9c670f95217d8e91a4e4442","Management Department, Khoja Akhmet Yassawi International Kazakh-Turkish University, Turkestan, Kazakhstan; Economics Department, Khoja Akhmet Yassawi International Kazakh-Turkish University, Turkestan, Kazakhstan; Economics Department, Yessenov University, Aktau, Kazakhstan; Finance and Auditing Department, Khoja Akhmet Yassawi International Kazakh-Turkish University, Kazakhstan; Cabinet for the development and implementation of educational programs, Turkestan branch of the Academy of Public Administration under the President of Kazakhstan, Turkestan, Kazakhstan","Sen B., Management Department, Khoja Akhmet Yassawi International Kazakh-Turkish University, Turkestan, Kazakhstan; Ydyrys S., Economics Department, Khoja Akhmet Yassawi International Kazakh-Turkish University, Turkestan, Kazakhstan; Omarova A., Economics Department, Yessenov University, Aktau, Kazakhstan; Munassipova M., Finance and Auditing Department, Khoja Akhmet Yassawi International Kazakh-Turkish University, Kazakhstan; Kuralbayev A., Cabinet for the development and implementation of educational programs, Turkestan branch of the Academy of Public Administration under the President of Kazakhstan, Turkestan, Kazakhstan","Electronic commerce is widely considered as a part of electronic business and the result of digital transformation. This paper aims to evaluate the capabilities and development of digital technologies in supply chain management. The evaluation process is conducted on the example of Kazakhstan by comparing the country with logistics and digital adaptation leaders. The paper analyses the effectiveness of information, communication, and logistics technologies development in supply chain management (SCM). The analysis involves systematizing secondary information. This research uses statistics from open sources as a foundation for descriptive comparative analysis to achieve research goals. The indicators such as logistics performance and the spread of information and communication technologies are selected for the evaluation. The paper outlines that an effective supply chain is essential to country's development and integration into the world economy within the context of globalization and digital transformation. © ExcelingTech Pub.","Communication technologies; E-commerce; Electronic data; Kazakhstan; Logistics; Supply chain; Supply chain management",{"$nulls":7},"Pawar K., Driva H., Electronic trading in the supply chain: A holistic implementation framework, Logistics Information Management, 13, 1, pp. 21-32, (2000); Chen H., Kong L., An Analysis on the Implementation of Electronic Supply Chain in International Trade, Integration and Innovation Orient to E-Society, (2007); Ivanov D., Dolgui A., Sokolov B., The impact of digital technology and Industry 4.0 on the ripple effect and supply chain risk analytics, International Journal of Production Research, 57, 3, pp. 829-846, (2019); Agrawal P., Narain R., Digital supply chain management: An Overview, IOP Conference Series: Materials Science and Engineering, 455, (2018); Scuotto V., Caputo F., Villasalero M., Del Giudice M., A multiple buyer-supplier relationship in the context of SMEs' digital supply chain management, Production Planning and Control, 28, 16, pp. 1378-1388, (2017); Mussomeli A., Gish D., Laaper S., The Rise of the Digital Supply Chain, Deloitte Insights, 45, 3, pp. 20-21, (2016); Hanifan G., Sharma A., Newberry C., A New Paradigm for Supply Chain Management, pp. 1-8, (2014); Kayikci Y., Sustainability impact of digitization in logistics, In Procedia Manufacturing, 21, pp. 782-789, (2018); Farahani P., Meier C., Wilke J., Digital Supply Chain Management 2020 Vision, The Business Transformation Journal, 13, (2015); Klotzer C., Pflaum A., Toward the Development of a Maturity Model for Digitalization within the Manufacturing Industry's Supply Chain, Proceedings of the 50th Hawaii International Conference on System Sciences, (2017); Korpela K., Hallikas J., Dahlberg T., Digital Supply Chain Transformation toward Blockchain Integration, Proceedings of the 50th Hawaii International Conference on System Sciences, (2017); Swaminathan J.M., Tayur S.R., Models for supply chains in e-business, Management Science, 49, 10, pp. 1387-1406, (2003); Buyukozkan G., Gocer F., Digital Supply Chain: Literature review and a proposed framework for future research, Computers in Industry, 97, pp. 157-177, (2018); Saberi S., Kouhizadeh M., Sarkis J., Shen L., Blockchain technology and its relationships to sustainable supply chain management, International Journal of Production Research, 57, 7, pp. 2117-2135, (2019); Kache F., Seuring S., Challenges and opportunities of digital information at the intersection of Big Data Analytics and supply chain management, International Journal of Operations and Production Management, 37, 1, pp. 10-36, (2017); Tovma N.A., Shurenov N.B., Bimendiyeva L.A., Kozhamkulova Z.T., Akhmetova Z.B., Territorial marketing and its role in determining regional competitiveness. Evaluating supply chain management, Uncertain Supply Chain Management, 8, 1, pp. 1-16, (2020); Kalykova B., Kaiyrbayeva A., Nurmanbekova G., Yeltayeva K., Rakhimzhanova G., The agricultural supply chain systems in cooperation and integration of Agro-Industrial Complexes of Russia, International Journal of Supply Chain Management, 7, 6, pp. 500-505, (2018); Glushkova S., Lomakina O., Sakulyeva T., The economy of developing countries in the context of globalization: Global supply chain management, International Journal of Supply Chain Management, 8, 1, pp. 876-884, (2019); Kot S., Onyusheva I., Grondys K., Supply Chain Management in SMEs: Evidence from Poland and Kazakhstan, Engineering Management in Production and Services, 10, 3, pp. 23-36, (2018); Karkinbayeva S.I., Kirdasinova K.A., Adiyetova E.M., Kanatova A.Z., Korgan B.B., Topical issues surrounding supply chain management in developing food industry: Kazakhstan case study, International Journal of Supply Chain Management, 8, 4, pp. 743-750, (2019); (2020); (2020); (2020); (2018); Panfilova E., Dzenzeliuk N., Domnina O., Morgunova N., Zatsarinnaya E., The Impact of Cost Allocation on Key Decisions of Supply Chain Participants, International Journal of Supply Chain Management, 9, 1, pp. 552-558, (2020)",null,null,"ExcelingTech",{"$nulls":5},2.0513771E7,null,null,null,"English","Int. J. Supply Chain Manag.","Article","Final",null,"Scopus","2-s2.0-85087750662"]
["Guo H.; Liu Y.; Shi X.; Chen K.Z.","Guo, Hongdong (36978572900); Liu, Yehong (57218607762); Shi, Xinjie (57215655470); Chen, Kevin Z. (8343381000)","36978572900; 57218607762; 57215655470; 8343381000","The role of e-commerce in the urban food system under COVID-19: lessons from China",2020.0,"China Agricultural Economic Review",13.0,2.0,null,436.0,455.0,19.0,50.0,"10.1108/CAER-06-2020-0146","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85094652608&doi=10.1108%2fCAER-06-2020-0146&partnerID=40&md5=9e7145a0d262339b25d8ec87098bc0a8","China Academy for Rural Development, School of Public Affairs, Zhejiang University, Hangzhou, China; China Academy for Rural Development, Zhejiang University, Hangzhou, China; International Food Policy Research Institute, Beijing Office, Beijing, China","Guo H., China Academy for Rural Development, School of Public Affairs, Zhejiang University, Hangzhou, China; Liu Y., China Academy for Rural Development, School of Public Affairs, Zhejiang University, Hangzhou, China; Shi X., China Academy for Rural Development, School of Public Affairs, Zhejiang University, Hangzhou, China; Chen K.Z., China Academy for Rural Development, Zhejiang University, Hangzhou, China, International Food Policy Research Institute, Beijing Office, Beijing, China","Purpose: The purpose of this study is to investigate e-commerce as a new means to ensure that the urban demand for food can be met during the coronavirus disease 2019 (COVID-19) outbreak. Because a number of COVID-19 e-commerce models have emerged, this paper discusses whether and (if so) why and how e-commerce can ensure the food supply for urban residents if social distancing becomes a norm and the transport and logistics systems are hindered. Design/methodology/approach: This study used qualitative research methods following the lack of empirical data. The authors referred to relevant literature, statistical data and official reports and comprehensively described the importance of e-commerce in ensuring the safety of food supply to Chinese urban residents under the impact of the epidemic. Corresponding to the traditional case study, this study presented a Chinese case on ensuring food supply through e-commerce during an epidemic. Findings: The authors found that three e-commerce models played a substantial role in preventing the spread of the epidemic and ensuring the food supply for urban residents. The nationwide e-commerce platforms under market leadership played their roles by relying on the sound infrastructure of large cities and its logistics system was vulnerable to the epidemic. In the worst-affected areas, particularly in closed and isolated communities, the local e-commerce model was the primary model, supplemented by the unofficial e-commerce model based on social relations. Through online booking, centralized procurement and community distribution, the risk of cross infection could be effectively reduced and the food demand could be effectively satisfied. The theoretical explanation further verifies that, apart from e-commerce, a governance system that integrates the government, e-commerce platform, community streets and the unofficial guanxi also impels the success of these models. Originality/value: Lessons from China are drawn for other countries struggling to deliver food to those in need under COVID-19. The study not only provides a solution that will ensure constant food supply to urban residents under the COVID-19 epidemic but also provides some reference for the maintenance of the food system of urban residents under the impact of a globalization-related crisis in future. © 2020, Emerald Publishing Limited.","China; COVID-19; E-commerce; Urban food system",{"$nulls":5},"Zhejiang University-IFPRI Center for International Development Studies, (126000-541902); National Natural Science Foundation of China, NSFC, (71673244, 72003170); Fundamental Research Funds for the Central Universities, (2020QNA142)","The authors would like to thank for the financial supports by the National Natural Science Foundation of China (NSFC) (nos. 71673244, 72003170), Zhejiang University-IFPRI Center for International Development Studies (grant 126000-541902) and Fundamental Research Funds for the Central Universities (no. 2020QNA142). The authors are also grateful to the editor and the anonymous reviewers for their comments and suggestions to improve the quality of this paper. 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Evidence from a natural experiment in India's agriculture markets, Management Science, 62, 9, pp. 2481-2503, (2016); Qi J., Zheng X., Cao P., Zhu L., The effect of e-commerce agribusiness clusters on farmers' migration decisions in China, Agribusiness, 35, 1, pp. 20-35, (2019); Shieh L., Friedmann J., Restructuring urban governance: community construction in contemporary China, City, 12, 2, pp. 183-195, (2008); Teo T.S.H., Liu J., Consumer trust in E-commerce in the USA, Singapore and China, Omega, 35, 1, pp. 22-38, (2007); Verdouw C.N., Vucic N., Sundmaeker H., Beulens A., Future internet as a driver for virtualization, connectivity and intelligence of agri‐food supply chain networks, International Journal on Food System Dynamics, 4, 4, pp. 261-272, (2014); Wang J., Zhu X., Zhang C., Models of China's e-commerce in the agricultural sector: an exploratory study, International Journal of U- and e- Service, Science and Technology, 9, 4, pp. 389-400, (2016); Wang Y., Hong A., Li X., Gao J., Marketing innovations during a global crisis: a study of China firms' response to COVID-19, Journal of Business Research, 116, May, pp. 214-220, (2020); Wu J.T., Leung K., Leung G.M., Nowcasting and forecasting the potential domestic and international spread of the 2019-NCoV outbreak originating in wuhan, China: a modelling study, The Lancet, 395, 10225, pp. 689-697, (2020); Yang X., Chen X., Jiang Y., Jia F., Adoption of e-commerce by the agri-food sector in China: the case of minyu e-commerce company, International Food and Agribusiness Management Review, 23, 1, pp. 1-16, (2020); Yaoa Y., Jia F., Wenhui F., Guo H., How to become a system integrator streamlining vegetable supply chains: the case of Songxiaocai company, International Food and Agribusiness Management Review, 22, 4, pp. 621-634, (2019); Zeng Y., Jia F., Wan L., Guo H., E-Commerce in agri-food sector: a systematic literature review, International Food and Agribusiness Management Review, 20, 4, pp. 439-459, (2017); Zhang X., Investigation of e-commerce in China in a geographical perspective, Growth and Change, 50, 3, pp. 1062-1084, (2019)","X. Shi; China Academy for Rural Development, School of Public Affairs, Zhejiang University, Hangzhou, China; email: shixinjie1990@126.com",null,"Emerald Group Holdings Ltd.",{"$nulls":5},"1756137X",null,null,null,"English","China Agric. Econ. Rev.","Article","Final",null,"Scopus","2-s2.0-85094652608"]
["Lazarevic D.; Švadlenka L.; Radojicic V.; Dobrodolac M.","Lazarevic, Dragan (57212826595); Švadlenka, Libor (26322051800); Radojicic, Valentina (6507269511); Dobrodolac, Momcilo (56017397300)","57212826595; 26322051800; 6507269511; 56017397300","New express delivery service and its impact on CO2 emissions",2020.0,"Sustainability (Switzerland)",12.0,2.0,456.0,null,null,null,12.0,"10.3390/su12020456","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85079685340&doi=10.3390%2fsu12020456&partnerID=40&md5=eb79ab1ae226d45a990c48b94333af1d","Faculty of Transport and Traffic Engineering, University of Belgrade, Belgrade, 11000, Serbia; Jan Perner Transport Faculty, University of Pardubice, Pardubice, 532 10, Czech Republic","Lazarevic D., Faculty of Transport and Traffic Engineering, University of Belgrade, Belgrade, 11000, Serbia; Švadlenka L., Jan Perner Transport Faculty, University of Pardubice, Pardubice, 532 10, Czech Republic; Radojicic V., Faculty of Transport and Traffic Engineering, University of Belgrade, Belgrade, 11000, Serbia; Dobrodolac M., Faculty of Transport and Traffic Engineering, University of Belgrade, Belgrade, 11000, Serbia","A rapid development of Internet technologies creates new opportunities for e-commerce, which is one of the fastest-growing segments of the entire economy. For policymakers, the most important aspects of e-commerce are related to the cost reduction in transportation, facilitation of administration and communication, innovations at the market level, and environmental issues. An unavoidable part of the e-commerce production process is related to the postal service. New market expectations of modern society lead to the consideration of upgrading the traditional express delivery service in terms of time availability. In this paper, we propose a new 24-h availability of postal and courier service so-called \"post express nonstop\". To assess the potential demand for this kind of service, we propose a forecasting procedure based on the Bass diffusion model. In particular, the research is directed toward the examination of environmental issues, considering both types of services-traditional and the proposed new one. A comparison is done by analyzing CO2 emissions in the last-mile delivery of goods to the users' addresses. The experiment was carried out in the city of Belgrade, simulating the last-mile delivery under realistic conditions and controlling the fuel consumption and CO2 emissions. In accordance with the results of this experiment and the forecasted number of postal items, a projection of CO2 emissions for the new service from 2020 to 2025 was carried out. The results show a significant contribution of the proposed new express delivery service to environmental well-being and sustainability. © 2020 by the authors.","CO<sub>2</sub> emissions; Express delivery service; Fuel consumption; Postal items forecasting; Social change; Time availability","Belgrade; Serbia; carbon dioxide; carbon emission; electronic commerce; environmental impact assessment; environmental issue; forecasting method; fuel consumption; innovation; policy making; research work; service provision; social change; temporal analysis",{"$nulls":6},"Agronick G.S., Duncan L.E., Personality and social change: Individual differences, life path, and importance attributed to the women's movement, J. Personal. Soc. Psychol., 74, (1998); Glenn S.S., Individual behavior, culture, and social change, Behav. 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Power Sources, 226, pp. 272-288, (2013); Lopes J.A.P., Soares F.J., Almeida P.M.R., Integration of electric vehicles in the electric power system, Proc. IEEE, 99, pp. 168-183, (2010); Tzeng G.H., Lin C.W., Opricovic S., Multi-criteria analysis of alternative-fuel buses for public transportation, Energy Policy, 33, pp. 1373-1383, (2005); Carraretto C., Macor A., Mirandola A., Stoppato A., Tonon S., Biodiesel as alternative fuel: Experimental analysis and energetic evaluations, Energy, 29, pp. 2195-2211, (2004); Murugesan A., Umarani C., Subramanian R., Nedunchezhian N., Bio-diesel as an alternative fuel for diesel engines-A review, Renew. Sustain. Energy Rev., 13, pp. 653-662, (2009); Bozbas K., Biodiesel as an alternative motor fuel: Production and policies in the European Union, Renew. Sustain. Energy Rev., 12, pp. 542-552, (2008); Saboohi Y., Farzaneh H., Model for developing an eco-driving strategy of a passenger vehicle based on the least fuel consumption, Appl. 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Manag., 78, pp. 142-149, (2019); Stojmenovic M., Biddle R., Grundy J., Farrell V., The influence of textual and verbal word-of-mouth on website usability and visual appeal, J. Supercomput., 75, pp. 1783-1830, (2019); Fisher J.C., Pry R.H., A simple substitution model of technological change, Technol. Forecast. Soc. Chang., 3, pp. 75-88, (1971); Putsis W.P., Temporal aggregation in diffusion models of first-time purchase: Does choice of frequency matter?, Technol Forecast. Soc. Chang., 51, pp. 265-279, (1996); Lenk P.J., Rao A.G., New models from old: Forecasting product adoption by hierarchical Bayes procedures, Mark. Sci., 9, pp. 42-53, (1990); Sultan F., Farley J.U., Lehmann D.R., A meta-analysis of applications of diffusion models, J. Mark. Res., 27, pp. 70-77, (1990); Robinson B., Lakhani C., Dynamic price models for new-product planning, Manag. 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Jpn., 44, pp. 1-18, (2001); Khan M.I., Islam M.R., True Sustainability in Technological Development and Natural Resource Management, (2007); Batalla I., Knudsen M.T., Mogensen L., del Hierro O., Pinto M., Hermansen J.E., Carbon footprint of milk from sheep farming systems in northern Spain including soil carbon sequestration in grasslands, J. Clean. Prod., 104, pp. 121-129, (2015); Dobrodolac M., Ralevic P., Svadlenka L., Radojicic V., Impact of a new concept of universal service obligations on revenue increase in the post of Serbia, PROMET Traffic Transp., 28, pp. 235-244, (2016); Fildes R., Kumar V., Telecommunications demand forecasting-A review, Int. J. Forecast., 18, pp. 489-522, (2002); Meade N., Islam T., Modelling and forecasting the diffusion of innovation-A 25-year review, Int. J. Forecast., 22, pp. 519-545, (2006)","D. Lazarevic; Faculty of Transport and Traffic Engineering, University of Belgrade, Belgrade, 11000, Serbia; email: d.lazarevic@sf.bg.ac.rs",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85079685340"]
["Wang Y.; Zhai X.","Wang, Yichun (57219747175); Zhai, Xiaodong (57219743448)","57219747175; 57219743448","Research on B2C E-commerce and Logistics Optimization in Coastal Areas",2020.0,"Journal of Coastal Research",115.0,"sp1",null,461.0,464.0,3.0,0.0,"10.2112/JCR-SI115-128.1","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85095128754&doi=10.2112%2fJCR-SI115-128.1&partnerID=40&md5=9cd5c9aba27a07bd9f3fd6f0d8490452","Institute of Communication Studies, Communication University of China, Beijing, 100024, China; Business School, Qingdao University, Qingdao, 266071, China","Wang Y., Institute of Communication Studies, Communication University of China, Beijing, 100024, China; Zhai X., Business School, Qingdao University, Qingdao, 266071, China","Wang, Y.C. and Zhai, X.D., 2020. Research on B2C E-commerce and logistics optimization in coastal areas. In: Bai, X. and Zhou, H. (eds.), Advances in Water Resources, Environmental Protection, and Sustainable Development. Journal of Coastal Research, Special Issue No. 115, pp. 461-464. Coconut Creek (Florida), ISSN 0749-0208. This paper studies the optimization of logistics in coastal areas business processes for B2C E-commerce companies. First, it analyzes the main problems faced by B2C E-commerce companies in China. On the basis, it fully expounds the necessity of optimization, and finally focuses on three B2C enterprise logistics Corresponding optimization strategies and key points are presented for key business processes. This paper proposes that B2C enterprises should continue to optimize logistics business processes to reduce the distance of logistics links and achieve seamless connection between links, further improving the efficiency and efficiency of B2C enterprises. The level of customer service reduces unnecessary operating costs, thereby enhancing the core competitiveness of B2C companies and lying the foundation for the implementation of corporate strategies.  © 2020 Coastal Education Research Foundation Inc.. All rights reserved.","B2C E-commerce; coastal areas; logistics; optimization","Florida",{"$nulls":6},"Al-Momani A.M., Mahmoud M.A., Ahmad M.S., Factors that influence the acceptance of internet of things services by customers of telecommunication companies in Jordan, Journal of Organizational and End User Computing, 30, 4, pp. 51-63, (2018); Chen X.Y., Analysis and Optimization of Business Process of Baicheng Post EMS System, (2006); Chen Y., Jiang B., Logistics Basics, (2009); Du P.Q., Chen S.F., Optimization model and algorithm for site selection, Logistics Technology, pp. 40-43, (2008); Fang Y.J., Research on Logistics Distribution Vehicle Scheduling Method under E-commerce Environment, (2006); Guo Z.P., Research and Implementation of Logistics Distribution Optimization under Supply Chain Environment, (2006); Huang T.Y., Li Y.J., Management Information System (Third Edition), (2005); Li Q., Guo J.J., Liu W., Yue X.G., Duarte N., Pereira C., How knowledge acquisition diversity affects innovation performance during the technological catch-up in emerging economies: A moderated inverse U-shape relationship, Sustainability, 12, (2020); Li Z., Discussion on the E-commerce logistics distribution method based on B2C model, China E-commerce, 12, (2010); Liu W., Ma H.L., Annika W., Advance in photonic crystal solar cells, Renewable and Sustainable Energy Reviews, 116, (2019); Ma S.H., Supply Chain Management, (2000); Peng J.P., Quan J., Peng L., It application maturity, management institutional capability and process management capability, Journal of Organizational and End User Computing, 31, 1, pp. 61-85, (2019); Shen M.L., Chen M.J., Ma Y.X., Fundamentals of Electronic Commerce, (2010); Tian S., Organizational Forms, Methods and Strategies of E-commerce Logistics Distribution, (2000); Wang D.P., Bao X.Z., Supply Chain Management Tutorial Theory and Method, (2009); Wang L., Network-based business process optimization of storage and transportation of military material stations, Logistics Technology, pp. 15-18, (2003); Zhou K., A probe into E-commerce and logistics distribution, Modernization of Shopping Malls, pp. 80-83, (2000); Zhou S.S., Warehouse and Distribution Management, (2008)","X. Zhai; Business School, Qingdao University, Qingdao, 266071, China; email: qduzhai@163.com",null,"Coastal Education Research Foundation Inc.",{"$nulls":5},7490208.0,null,"JCRSE",null,"English","J. Coast. Res.","Article","Final",null,"Scopus","2-s2.0-85095128754"]
["Zhao Y.","Zhao, Yanan (57211027012)",5.7211027012E10,"Influencing Factors of Cross-Border E-Commerce Trade between China and \"belt and Road\" Coastal and Inland Countries",2020.0,"Journal of Coastal Research",103.0,"sp1",null,70.0,73.0,3.0,9.0,"10.2112/SI103-015.1","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85087159002&doi=10.2112%2fSI103-015.1&partnerID=40&md5=edffc2bc522318a764eaee224159c441","School of Economics, Shenyang University, Shenyang, 110043, China","Zhao Y., School of Economics, Shenyang University, Shenyang, 110043, China","Zhao, Y., 2020. Influencing factors of cross-border e-commerce trade between China and \"Belt and Road\" coastal and inland countries. In: Yang, Y.; Mi, C.; Zhao, L., and Lam, S. (eds.), Global Topics and New Trends in Coastal Research: Port, Coastal and Ocean Engineering. Journal of Coastal Research, Special Issue No. 103, pp. 70-73. Coconut Creek (Florida), ISSN 0749-0208. In context of building \"Belt and Road\", e-commerce has developed rapidly. Therefore, how to evaluate and measure its influential factors is worth exploring. This article uses an extended trade gravity model to empirically explain the influencing factors of CBEC volume scale between \"Belt and Road\" countries and China. This study results show that similar to traditional trade, per capita income, consumer groups, and additional factors affect the scale of CBEC signifigantly, especially geographical distance has a significant obstacle to the size of CBEC transactions. Additionally, the above estimated results of the newly added explanatory variables such as logistics performance index and Internet penetration are basically in line with expectations. In particular, the logistics performance index has the most obviously positive effect on CBEC exporting and CBEC importing. China would strengthen cooperating with Belt and Road countries in the aspect of e-commerce, create a good business environment, encourage infrastructure construction so as to develop the potential of CBEC markets. © Coastal Education and Research Foundation, Inc. 2020.","Belt and Road; cross border e-commerce (CBEC); e-commerce of Silk Road; extended gravity model; influncing factors",{"$nulls":5},"Liaoning Federation of Social Science Fund, (2020lslktjdyb-049); Liaoning Provincial Social Science Fund, (L19BJY032)","This paper is supported by the following projects: (1) Shenyang","Anderson J.E., Van Wincoop E., Gravity with Gravitas: A solution to the border puzzle, American Economic Review, 93, 1, pp. 170-192, (2003); Blum B.S., Goldfarb A., Does the in-ternet defy the law of gravity?, Journal of International Economics, 70, 2, pp. 384-405, (2006); Eikebrokk T., Olsen D., An empirical investigation of competency factors affecting e-business success in European SMEs, Information & Management, 44, pp. 364-384, (2007); Giuffrida M., Mangiaracina R., Perego A., Tumino A., Logistics solutions to support cross border e-commerce towards China: The case of the apparel industry, Lecture Notes in Electrical Engineering, 413, pp. 162-177, (2017); Gomez-Herrera E., Martens B., Turlea G., The drivers and impediments for cross-border e-commerce in the EU, Information Economics & Policy, 28, 1, pp. 83-96, (2014); Guo L., Sriyakul T., Nojavan S., Jermsittiparsert K., Risk-based traded demand response between consumers' aggregator and retailer using downside risk constraints technique, IEEE Access, (2020); Jiang B., Wang Z., Li J., Empirical test of trade gravity model in Chinese cross-border e-commerce, Business Economics Research, 10, pp. 32-34, (2017); Liu M.Y., Lin M.S., Research on the development path of cross-border e-commerce in the Asia-Pacific region from the perspective of trade gravity, Journal of the Party School of Fujian Province Committee of the CPC, 1, pp. 73-82, (2019); Liu Z., Feng J., Liu B., Pricing and service level decisions under a sharing product and consumers' variety-seeking behavior, Sustainability, 11, 24, (2019); Martin B., Zaki W., A model of a localized cross border e-commerce, IBusiness, 4, pp. 136-145, (2012); Sherah K., Alzougool B.A., Adoption of electronic commerce evaluation for SMEs, System Science, 51, 11, pp. 33-47, (2014); Valarezo A., Perez-Amaral T., Drivers and barriers to cross-bordere-commerce: Evidence from Spanish individual behavior, Telecommunications Policy, 3, pp. 1-10, (2018); Zhu B., Pang R., Chevallier J., Wei Y., Vo D., Including intangible costs into the cost-of-illness approach: A method refinement illustrated based on the PM2. 5 economic burden in China, The European Journal of Health Economics, 20, pp. 501-511, (2019)","Y. Zhao; School of Economics, Shenyang University, Shenyang, 110043, China; email: syuint@126.com",null,"Coastal Education Research Foundation Inc.",{"$nulls":5},7490208.0,null,"JCRSE",null,"English","J. Coast. Res.","Article","Final",null,"Scopus","2-s2.0-85087159002"]
["Suthamathi D.; Jeeva S.","Suthamathi, D. (57200580967); Jeeva, S. (57215081197)","57200580967; 57215081197","Online shopping vs offline shopping customer preference in Salem district",2020.0,"International Journal of Scientific and Technology Research",9.0,2.0,null,5394.0,5398.0,4.0,1.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85079838695&partnerID=40&md5=d7d1a0221299c2f2c24acbe4df5c37eb",null,null,"The study tries to recognize and progress a conceptual that addresses customer’s value opinion for using the internet shopping versus offline shopping. Observations of online and offline buyers or customers can be evaluated to see how value is constructed in both channels. It is either to recognize what factors influence online and offline choice progression. The factors affecting online shopping are risk of purchase; delivery product varied the buying product, delivery time very delay, quality. The factors affecting direct shopping are the bargaining; time spends for purchasing, less number of choice. The study showed that perceptions of price, service quality and threat strongly impact perceived value and purchase intents in the offline and online network. Main Objective of the study is to analyze the significant difference between the offline and online customers group in terms of demographic, technology use, availability and attitude of the customers. The research is based on primary information’s obtained from the customers of online and offline shopping. Overall, customers, however the respondent and purchasing for online and offline shopping. © 2020 IJSTR.","Buying Behaviour; Customer attitude; Customer satisfaction; Shopping preference",{"$nulls":7},"Ahn T., Ryu S., Han I., The effect of the web and offline capabilities on the person acceptance of internet shopping department shops, Electronic Commerce Studies and Application, 3, pp. 405-420, (2004); Bartelt A., Lamersdorf W., A multi requirements taxonomy of business enterprise fashions in digital commerce, Proceedings of IFIP/ACM International Conference WS on Electronic Commerce., (2001); Bhatnagar A., Misra S., Rao R.H., On chance, comfort and internet buying behavior, Association for Computing Machinery, (2000); Online Retailing in Europe, the U.S. and Canada 2015-2016, (2015); Dey S.K., Nabi M.N., Anwer M., Challenges in Building Trust in B2C E-Commerce and suggestion to mitigate them: Developing international locations perspective, Proceedings of 2009 Twelfth Worldwide Conference in Computer and Information Technology, pp. 21-23, (2009); Grewal D., Iyer G.R., Levy M., Internet retailing: Enablers, Limiters and Market consequences, Journal of Business Research, 5743, pp. 1-11, (2002); Gurau C., Ranchod A., Hackney R., Internet transactions and physical logistics: Conflict or Complimentary?, Logistic Information Management, 14, 1-2, pp. 33-40, (2007); Suhan J., Acceptance of Online Shopping in Bangladesh: Clients Perspective, Journal of Business and Management (IOS-JBM), 17, 1, pp. 14-24, (2015); Laisuzzaman I.M., Imran N., Nahid A.A., Amin M.Z., Alim M.A., The framework for implementing E-commerce: The feature of Bank and Telecom in Bangladesh, Journal of Telecommunication, 1, 1, pp. 57-60, (2010); Lee M.K.O., Turban E.L., A do not forget model for patron net buying, International Journal of Electronic Commerce, 6, pp. 75-90, (2001); Liu C., Arnett K.P., Exploring the factors related to net website fulfillment in the context of electronic commerce, Information & Management, 38, (2000); Swinyard W.R., Smith S.M., Why People (Don’t) Shop on-line: A life-style test of the net customer, Psychology & Marketing, 20, 7, pp. 567-597, (2003); Valariezeithaml A., Delivery of Service Quality, Journal of Marketing, Fifty two., (1998)",null,null,"International Journal of Scientific and Technology Research",{"$nulls":5},2.2778616E7,null,null,null,"English","Int. J. Sci. Technol. Res.","Article","Final",null,"Scopus","2-s2.0-85079838695"]
["Wang Y.","Wang, Yingkai (57194607090)",5.719460709E10,"Study on the optimization selection of cross-border E-commerce logistics distribution path under the O2O mode",2020.0,"Italian Journal of Pure and Applied Mathematics",44.0,null,null,952.0,964.0,12.0,0.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85090122624&partnerID=40&md5=e86ab7289ffa30d12395471c8ac966a5","International Economics and Trade Department, School of Economics, Law University of Science and Technology Liaoning, No. 185, Gaoxin District, Anshan City Liaoning Province, 114051, China","Wang Y., International Economics and Trade Department, School of Economics, Law University of Science and Technology Liaoning, No. 185, Gaoxin District, Anshan City Liaoning Province, 114051, China","The rapid development of cross-border e-commerce in online to offline (O2O) mode has brought more opportunities and challenges to the development of logistics industry. Aviation logistics is the most important way of cross-border logistics, the optimization of which plays an important role in e-commerce enterprises and logistics enterprises. This study studied the types of aircraft and the arrangement of air routes in the process of aviation logistics. The route optimization of passenger cabin and full cargo transportation was discussed respectively. A model was established and the optimization method was designed. Finally example analysis was performed. The results showed the designed method could achieve the maximum profit and the optimization of distribution routes. This study provides some references for the optimization of logistics distribution of cross-border e-commerce and is beneficial to the further development of the cross-border e-commerce logistics industry. © 2020 Forum-Editrice Universitaria Udinese SRL. All rights reserved.","Logistics distribution; O2O; Path optimization","Transportation routes; Cargo transportation; Distribution route; E-commerce enterprise; Logistics distribution; Logistics enterprise; Logistics industry; Optimization method; Route optimization; Electronic commerce",{"$nulls":6},"Lin L.F., Li Y.M., A social recommendation mechanism for enhancing O2O E-commerce, Iiai International Congress on Advanced Applied Informatics, IEEE Computer Society, pp. 401-406, (2017); Fan Z., Ma M., Research on the optimization of vehicle distribution routes in logistics enterprises, IOP Conference Series: Earth and Environmental Science. IOP Conference Series: Earth and Environmental Science, (2018); Lai M., Yang H., Yang S., Et al., Cyber-physical logistics system-based vehicle routing optimization, Journal of Industrial & Management Optimization, 10, pp. 701-715, (2017); Deng Y., Yao Z., Li J., Route optimization model in collaborative logistics network for mixed transportation problem considered cost discount based on GATS, Journal of Ambient Intelligence & Humanized Computing, pp. 1-8, (2018); Wang S.Y., Tao F.M., Shi Y.H., Optimization of location-routing problem for cold chain logistics considering carbon footprint, International Journal of Environmental Research and Public Health, 15, (2018); Jiang G., Pan Y., Hu F.Y., Et al., Research on logistics distribution route based on genetic algorithm and ant colony optimization algorithm, Computer Engineering & Applications, pp. 758-762, (2015); Chen X., Wang J., A novel hybrid cuckoo search algorithm for optimizing vehicle routing problem in logistics distribution system, Journal of Computational & Theoretical Nanoscience, 13, pp. 114-119, (2016); Rahman N.A.B.A., Mohammad M.F., Rahim S.A., Et al., Shipper’s perceptions of aviation logistics service quality (LSQ) of air freight provider, Journal of Engineering & Applied Science, 12, pp. 699-704, (2017); Yang J., Zheng B., Yang L., Research on cross-border E-commerce index system based on factor analysis, Finance & Trade Economics, 35, pp. 94-102, (2014); Chen N., Yang J., Mechanism of government policies in cross-border e-commerce on firm performance and implications on m-commerce, International Journal of Mobile Communications, 15, (2017); Wang Y., Avery W., Wang Y., Lee S.H., The effect of cross-border E-commerce on China’s international trade: an empirical study based on transaction cost analysis, Sustainability, 9, (2017); Gomez-Herrera E., Martens B., Turlea G., The drivers and impediments for cross-border e-commerce in the EU, Information Economics & Policy, 28, pp. 83-96, (2014); Zhang K., Qiu B., Mu D., Low-carbon logistics distribution route planning with improved particle swarm optimization algorithm, International Conference on Logistics, Informatics and Service Sciences. IEEE, pp. 1-4, (2017); Li X., Jianguo W., Yuan J., A New logistics distribution route optimization algorithm for fresh agricultural products based on the fusion of genetic algorithm and ant colony algorithm, C E Ca, 42, pp. 2428-2432, (2017); Wang J., Yang Y., Zhang N., Et al., Optimization of logistics collaborative distribution routing based on improved Ant Colony Algorithm, International Conference on Industrial Technology and Management, IEEE, pp. 36-40, (2017)","Y. Wang; International Economics and Trade Department, School of Economics, Law University of Science and Technology Liaoning, Anshan City Liaoning Province, No. 185, Gaoxin District, 114051, China; email: yingkwustl@126.com",null,"Forum-Editrice Universitaria Udinese SRL",{"$nulls":5},1.1268042E7,null,null,null,"English","Ital. J. Pure Appl. Math.","Article","Final",null,"Scopus","2-s2.0-85090122624"]
["Wang Z.; Zhu H.","Wang, Zhe (58690267900); Zhu, Hong (58691099200)","58690267900; 58691099200","Optimization of e-commerce logistics of marine economy by fuzzy algorithms",2020.0,"Journal of Intelligent and Fuzzy Systems",38.0,4.0,null,3813.0,3821.0,8.0,6.0,"10.3233/JIFS-179604","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124025273&doi=10.3233%2fJIFS-179604&partnerID=40&md5=f8fa93fc025c5823747f9a7fbe4c3b68","Qingdao Ocean Shipping Mariners College, Shandong, Qingdao, China; Shandong Academy of Governance, Shandong, Jinan, China","Wang Z., Qingdao Ocean Shipping Mariners College, Shandong, Qingdao, China; Zhu H., Shandong Academy of Governance, Shandong, Jinan, China","In order to achieve the improvement and optimization of e-commerce logistics, a fuzzy algorithm was built to optimize the e-commerce logistics in the marine economy. Through the construction of the fuzzy algorithm, a comparative analysis was made on the effects of logistics before the optimization of marine e-commerce, such as customer satisfaction, product arrival rate on time, logistics cost, number of routes, safety rate, work efficiency, and other aspects. The research shows that the fuzzy algorithm has a better performance in logistics cost than before. After optimization, the monthly mileage of logistics has also been significantly reduced, and the economic benefit is very significant. The algorithm in this paper has an excellent effect in customer satisfaction and product arrival rate on time, which has obvious improvement effect on the logistics network. The improvement of the customer satisfaction is of great value and significance to the follow-up development of marine e-commerce. The improvement and optimization of logistics path based on fuzzy algorithm has reference value for the development of logistics in other fields. Based on the fuzzy algorithm, the function of the algorithm is studied by analyzing the logistics optimization of marine e-commerce. The fuzzy algorithm used shows a comprehensive and excellent result in improving the marine logistics situation, and shows that the optimization and improvement of the algorithm is a process that needs to be improved in many ways. The research greatly improves the understanding of the fuzzy algorithm and the e-commerce logistics in the marine economy environment.  © 2020 - IOS Press and the authors. All rights reserved.","e-commerce logistics optimization; Fuzzy algorithm; marine economy","Cost benefit analysis; Electronic commerce; Fuzzy sets; Sales; Arrival rates; Comparative analyzes; Customers' satisfaction; E- commerces; E-commerce logistic optimization; Fuzzy algorithms; Logistic costs; Logistics optimization; Marine economy; Optimisations; Customer satisfaction",{"$nulls":6},"Xiao K., Hu X., Study on maritime logisticswarehousing center model and precision marketing strategy optimization based on fuzzy method and neural network model, Polish Maritime Research, 24, S2, pp. 30-38, (2017); Chen B., Wang B., Location selection of logistics center in e-commerce network environments, American Journal of Neural Networks and Applications, Science Publishing Group, 3, 4, pp. 40-48, (2017); Jiang J., Wang Y., Li Z., Al E., Optimal design method for a digital human-computer interface based on human reliability in a nuclear power plant. Part 3: Optimization method for interface task layout, Annals of Nuclear Energy, 94, pp. 750-758, (2016); Tan S., Tian D., The Optimization Model Research of Fuzzy Multi-objective in Transport Logistics, Logistics Sci-Tech, 2016, 5; Zhu Q., Li Y., Agricultural research recommendation algorithm based on consumer preference model of e-commerce, Future Generation Computer Systems, 88, pp. 151-155, (2018); Dan-Dan W., Ke-Bin L., Construction of urban vegetable retail distribution network under the environment of regional electricity suppliers Taking Hefei city as an example, Journal of Jiamusi Vocational Institute, 2016, 11; Abad E., Palacio F., Nuin M., Al E., Connpilation of References, Handbook of Research on Urban and Humanitarian Logistics, 93, 4, (2019); Akter S., Wamba S.F., Big data analytics in E-commerce: A systematic review and agenda for future research, Electronic Markets, 26, 2, pp. 173-194, (2016); Hu Z.H., Li X., Wei C., Al E., Examining collaborative filtering algorithms for clothing recommendation in e-commerce, Textile Research Journal, 89, 14, pp. 2821-2835, (2019); Abad E., Palacio F., Nuin M., Al E., Connpilation of References, Handbook of Research on Urban and Humanitarian Logistics, 93, 4, (2019); Jiao W., Li Q., Anomaly detection based on fuzzy rules, International Journal of Performability Engineering, 14, 2, (2018); Han H., Trimi S., A fuzzy TOPSIS method for performance evaluation of reverse logistics in social commerce platforms, Expert Systems with Applications, 103, pp. 133-145, (2018); Xu S.X., Huang G.Q., Efficient multi-attribute multi-unit auctions for B2B E-commerce logistics, Production and Operations Management, 26, 2, pp. 292-304, (2017); Chen H., Location Problem of Distribution Center Based on Baumer Walvar Model: Taking Jiaji Logistics as an Example, Open Journal of Business and Management, 7, 2, (2019); Ren X.Y., Kong Z.F., Liang W.C., Al E., Vehicle scheduling based on plant growth simulation algorithm and distribution staff behavior, Advances in Production Engineering & Management, 12, 2, (2017); Li Z., Zhang Y., Hierarchical evaluation algorithm of logistics carrying capacity based on transfer learning in multimedia environment, Multimedia Tools and Applications, 78, 4, pp. 4481-4501, (2019); Pourhejazy P., Kwon O., The new generation of operations research methods in supply chain optimization: A review, Sustainability, 8, 10, (2016); Jin Y., Li G., Zhang H., Evaluation of Regional Rural Information Environment Based on Fuzzy Method in the Era of the Internet of Things, IEEE Access, 6, pp. 78530-78541, (2018); Chen M., Yang B., Zhu X., Bi-objective optimization of overseas warehouse location for export cross-border e-commerce, Journal of Shanghai Maritime University, 2017, 2; Zhang L., Gao Y., Sun Y., Al E., Application on Cold Chain Logistics Routing Optimization Based on Improved Genetic Algorithm, Automatic Control and Computer Sciences, 53, 2, pp. 169-180, (2019)","Z. Wang; Qingdao Ocean Shipping Mariners College, Qingdao, Shandong, 266000, China; email: wang.zhe2@coscoshipping.com",null,"IOS Press BV",{"$nulls":5},1.0641246E7,null,null,null,"English","J. Intelligent Fuzzy Syst.","Article","Final",null,"Scopus","2-s2.0-85124025273"]
["Xu B.; Huang D.; Mi B.","Xu, Bing (57215094066); Huang, Darong (16177279000); Mi, Bo (14037723400)","57215094066; 16177279000; 14037723400","Smart city-based e-commerce security technology with improvement of SET network protocol",2020.0,"Computer Communications",154.0,null,null,66.0,74.0,8.0,7.0,"10.1016/j.comcom.2020.02.024","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85079836276&doi=10.1016%2fj.comcom.2020.02.024&partnerID=40&md5=b12d6d22831e828a49f3a0045b28f20d","School of Economics and Management, Chongqing Jiaotong University, Chongqing, China","Xu B., School of Economics and Management, Chongqing Jiaotong University, Chongqing, China; Huang D., School of Economics and Management, Chongqing Jiaotong University, Chongqing, China; Mi B., School of Economics and Management, Chongqing Jiaotong University, Chongqing, China","In this paper, we proposed an improvement of SET protocol for E-commerce transaction. We study the security technology and protocol flow of set protocol, and point out the shortcomings of SET protocol. Due to the lack of security and low scalability of the current protocol, this paper proposes a server e-wallet strategy, which divides the original client into e-wallet client and e-wallet server, and enhances the convenience and security of the transaction by transferring the client to the issuer or the third-party financial institution, while the scalability is stronger. In order to ensure the atomicity of goods and confirm the atomicity of delivery, this paper proposes a secure e-commerce payment protocol based on the fourth party, which includes master protocol, customer return protocol, customer exchange protocol and customer merchant transaction dispute resolution protocol. According to the efficiency of SET protocol, a security hierarchical control model is proposed, which can select different security levels to operate according to the actual needs of customers, and the principle and implementation of the model are analyzed. © 2020 Elsevier B.V.","Atomicity; E-commerce security; Server wallet; SET protocol","Electronic money; Network security; Sales; Scalability; Smart city; Atomicity; Dispute resolution protocols; E-commerce security; E-commerce transactions; Financial institution; Hierarchical control; Security technology; Set protocols; Network protocols",{"$nulls":4},"Chongqing Municipal Education Commission, CQMEC, (KJQN201900739)","The paper supported by Scientific and Technological ResearchProgram of Chongqing Municipal Education Commission ( KJQN201900739 ), Dynamic Option Pricing Mechanism Study on Highway Revenue Rights from Heterogeneity Perspective.   ","di X., Research on E-Commerce Network Information Security Technology, (2019); jingling H., Yan L., Improved payment model of secure E-commerce based on set protocol, Mod. Electr. Technol., 42, 6, pp. 65-68, (2019); Ying Z., Analysis of the shortcomings and improvement scheme of security electronic protocol set, Netw. Secur. Technol. Appl., 4, pp. 73-74, (2018); Junjie C., Analysis and research of E-commerce protocol SSL and set, Netw. Secur. Technol. Appl., 2, pp. 42-43, (2017); Nanqiang W., E-commerce security based on set protocol, Shandong Ind. Technol., 4, (2017); Lei Z., Analysis and design of electronic payment platform based on set protocol, Mech. Manag. Dev., 29, 6, pp. 11-13, (2014); Jianghong L., Design and implementation of E-commerce secure fair trading system, Commun. Technol., 46, 5, pp. 88-90 ＋ 94, (2013); Rui X., Research on E-Commerce Security Based on Set Protocol, (2013); Kaiti Z., Research on Network Electronic Payment System Based on Set Protocol, (2013); Liu T., Zhang M., Zhu J., Zheng R., Liu R., Wu Q., ACCP: adaptive congestion control protocol in named data networking based on deep learning, Neural Comput. Appl., 31, 9, pp. 4675-4683, (2019); Xiuqiong C., Research on the Improvement of Online Payment Model Based on SSL Protocol, (2012); Sakar C.O., Polat S.O., Katircioglu M., Kastro Y., Real-time prediction of online shoppers’ purchasing intention using multilayer perceptron and LSTM recurrent neural networks, Neural Comput. Appl., 31, 10, pp. 6893-6908, (2019); Tingting Y., Research on the Unified Payment Platform and Its Protocol Based on the Fourth Party E-Commerce, (2012); cungao M., Security issues and countermeasures of E-commerce, Wirel. Commun. Technol., 21, 1, pp. 54-58, (2012); Katarya R., Verma O.P., Recommender system with grey wolf optimizer and FCM, Neural Comput. Appl., 30, 5, pp. 1679-1687, (2018); Liang L., Analysis and comparison of SSL protocol and set protocol in E-commerce, Inf. Netw. Secur., 4, pp. 27-28, (2011); Ehikioya S.A., Olukunle A.A., A formal model of distributed security for electronic commerce transactions systems, IJNDC, 7, 2, pp. 68-84, (2019); Hu L., E-commerce trade consumption payment security and privacy based on improved B2C model, Int. J. Netw. Secur., 21, 4, pp. 545-550, (2019); Khan H.U., Alshare K.A., Violators versus non-violators of information security measures in organizations - A study of distinguishing factors, J. Org. Comput. Electron. Commer., 29, 1, pp. 4-23, (2019); Halim Barkatullah A., Djumadi K.A., Does self-regulation provide legal protection and security to E-commerce consumers?, Electron. Commer. Res. Appl., 30, pp. 94-101, (2018); Hopkins J., Kafali O., Alrayes B., Stathis K., Pirasa: strategic protocol selection for E-commerce agents, Electron. Mark., 29, 2, pp. 239-252, (2019); Thapliyal K., Pathak A., Quantum E-commerce: a comparative study of possible protocols for online shopping and other tasks related to E-commerce, Quantum Inf. Process., 18, 6, (2019); Hwang R.-J., Lai C.-H., Provable fair document exchange protocol with transaction privacy for E-commerce, Symmetry, 7, 2, pp. 464-487, (2015); Ruoyan Z., Xiaoxia L., Hong Z., Establishment of formal model and security analysis of set protocol, Comput. Appl. Softw., 26, 5, pp. 81-84, (2009); Tingting W., Research on the Unified Payment Platform and Its Agreement Based on the Fourth Party E-Commerce, (2012); Yuanhong C., Yudong L., Improved E-commerce secure transaction mode, Manag. Mod., 5, pp. 12-14, (2010); Xiajun D., Xiaodan J., Shuangxia H., Tieqiang P., E-commerce payment security research based on SSL protocol and set protocol, Sci. Technol. Inf., 28, pp. 18-19, (2010); (2013); Tao L., Research on SET Protocol Improvement Scheme and Payment Model, (2005); pp. 105-107, (2010)","B. Xu; School of Economics and Management, Chongqing Jiaotong University, Chongqing, China; email: xbing@cqjtu.edu.cn",null,"Elsevier B.V.",{"$nulls":5},1403664.0,null,"COCOD",null,"English","Comput Commun","Article","Final",null,"Scopus","2-s2.0-85079836276"]
["Yan Y.; Wang Y.; Du Z.; Zhang F.; Liu R.; Ye X.","Yan, Yiming (56888147800); Wang, Yuanyuan (57315767600); Du, Zhenhong (25929119800); Zhang, Feng (56434720200); Liu, Renyi (55809641900); Ye, Xinyue (36474249400)","56888147800; 57315767600; 25929119800; 56434720200; 55809641900; 36474249400","Where urban youth work and live: A data-driven approach to identify urban functional areas at a fine scale",2020.0,"ISPRS International Journal of Geo-Information",9.0,1.0,42.0,null,null,null,5.0,"10.3390/ijgi9010042","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85077997694&doi=10.3390%2fijgi9010042&partnerID=40&md5=c782dd11d219c8d2af4e32f8c23f3bcd","School of Earth Sciences, Zhejiang University, 38 Zheda Road, Hangzhou, 310027, China; Zhejiang Provincial Key Laboratory of Geographic Information Science, 148 Tianmushan Road, Hangzhou, 310028, China; Ocean Academy, Zhejiang University, 1 Zheda Road, Zhoushan, 316021, China; Department of Informatics, New Jersey Institute of Technology, Newark, 07102, NJ, United States","Yan Y., School of Earth Sciences, Zhejiang University, 38 Zheda Road, Hangzhou, 310027, China, Zhejiang Provincial Key Laboratory of Geographic Information Science, 148 Tianmushan Road, Hangzhou, 310028, China; Wang Y., School of Earth Sciences, Zhejiang University, 38 Zheda Road, Hangzhou, 310027, China, Ocean Academy, Zhejiang University, 1 Zheda Road, Zhoushan, 316021, China; Du Z., School of Earth Sciences, Zhejiang University, 38 Zheda Road, Hangzhou, 310027, China, Zhejiang Provincial Key Laboratory of Geographic Information Science, 148 Tianmushan Road, Hangzhou, 310028, China; Zhang F., School of Earth Sciences, Zhejiang University, 38 Zheda Road, Hangzhou, 310027, China, Zhejiang Provincial Key Laboratory of Geographic Information Science, 148 Tianmushan Road, Hangzhou, 310028, China; Liu R., School of Earth Sciences, Zhejiang University, 38 Zheda Road, Hangzhou, 310027, China, Ocean Academy, Zhejiang University, 1 Zheda Road, Zhoushan, 316021, China; Ye X., Department of Informatics, New Jersey Institute of Technology, Newark, 07102, NJ, United States","As a major labor force of cities, young people provide a huge driving force for urban innovation and development, and contribute to urban industrial upgrading and restructuring. In addition, with the acceleration of urbanization in China, the young floating population has increased rapidly, causing over-urbanization and creating certain social problems. It is important to analyze the demand of urban youth and promote their social integration. With the development of the mobile Internet and the improvement of the city express system, ordering food delivery has become a popular and convenient way to dine, especially in China. Food delivery data have a significant user attribute where the ages of most delivery customers are under 35 years old. In this paper, we introduce food delivery data as a new data source in urban functional zone detection and propose a time-series-based clustering approach to discover the urban hotspot areas of young people. The work and living areas were effectively identified according to the human behavioral characteristics of ordering food delivery. Furthermore, we analyzed the relationship between young people and the industry structure of Hangzhou and discovered that the geographical distribution of the identified work areas was similar to that of the Internet and e-commerce companies. The characteristics of the identified living areas were also analyzed in combination with the distribution of subway lines and residential communities, and it was found that the living areas were mainly distributed along subway lines and that urban villages appeared in the living hotspot regions, indicating that transportation and living cost were two important factors in the choice of residential location for young people. The findings of this paper can help urban industrial and residential planning and young population management. © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).","Food delivery data; Industrial structure; Urban hotspots; Urban village; Urban youth",{"$nulls":5},"National Key R&D Program of China; Open Fund of Laboratory of Target Microwave Properties; National Natural Science Foundation of China, NSFC, (41671391, 41701436); National Key Research and Development Program of China, NKRDPC, (2018KF05, 2018YFB0505000)","Funding text 1: This research was funded by the National Natural Science Foundation of China (Grant Nos. 41701436, 41671391), National Key R&D Program of China (Grant No. 2018YFB0505000), and the Open Fund of Laboratory of Target Microwave Properties (Grant No. 2018KF05).; Funding text 2: Funding: This research was funded by the National Natural Science Foundation of China (Grant Nos. 41701436, 41671391), National Key R&D Program of China (Grant No. 2018YFB0505000), and the Open Fund of Laboratory of Target Microwave Properties (Grant No. 2018KF05).","Tan S.K., Li Y.A., Song Y., Luo X., Zhou M., Zhang L., Kuang B., Influence factors on settlement intention for floating population in urban area: A China study, Qual. Quant., 51, pp. 147-176, (2017); Tao L., Hui E.C., Wong F.K., Chen T., Housing choices of migrant workers in China: Beyond the Hukou perspective, Habitat Int, 49, pp. 474-483, (2015); Li B., Floating population or urban citizens? Status, social provision and circumstances of rural-urban migrants in China, Soc. Policy Adm., 40, pp. 174-195, (2006); Frosch K.H., Workforce age and innovation: A literature survey, Int. J. Manag. Rev., 13, pp. 414-430, (2011); Chatman D.G., How density and mixed uses at the workplace affect personal commercial travel and commute mode choice, Transp. Res. Rec., 1831, pp. 193-201, (2003); Peng Z.-R., The jobs-housing balance and urban commuting, Urban Stud, 34, pp. 1215-1235, (1997); Wu W., Migrant intra-urban residential mobility in urban China, Hous. Stud., 21, pp. 745-765, (2006); Liu Y., Xiao Y., Gao S., Kang C.-G., Wang Y.-L., A review of human mobility research based on location aware devices, Geogr. Geo Inf. 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Sci., 28, pp. 1988-2007, (2014); Toole J.L., Ulm M., Gonzalez M.C., Bauer D., Inferring land use from mobile phone activity, Proceedings of the ACM SIGKDD International Workshop on Urban Computing, pp. 1-8, (2012); Yang X., Fang Z., Yin L., Li J., Zhou Y., Lu S., Understanding the spatial structure of urban commuting using mobile phone location data: A case study of Shenzhen, China, Sustainability, 10, (2018); Zhao Z., Shaw S.-L., Xu Y., Lu F., Chen J., Yin L., Understanding the bias of call detail records in human mobility research, Int. J. Geogr. Inf. Sci., 30, pp. 1738-1762, (2016); Mao F., Ji M., Liu T., Mining spatiotemporal patterns of urban dwellers from taxi trajectory data, Front. Earth Sci., 10, pp. 205-221, (2016); Tang J., Liu F., Wang Y., Wang H., Uncovering urban human mobility from large scale taxi GPS data, Phys. A Stat. Mech. 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Geogr., 41, pp. 175-183, (2014); Mohamed K., Come E., Oukhellou L., Verleysen M., Clustering smart card data for urban mobility analysis, IEEE Trans. Intell. Transp. Syst., 18, pp. 712-728, (2016); Long Y., Thill J.-C., Combining smart card data and household travel survey to analyze jobs-housing relationships in Beijing, Comput. Environ. Urban Syst., 53, pp. 19-35, (2015); Mazimpaka J.D., Timpf S., Trajectory data mining: A review of methods and applications, J. Spat. Inf. Sci., 2016, pp. 61-99, (2016); Hu Y., Han Y., Identification of urban functional areas based on POI data: A case study of the Guangzhou economic and technological development zone, Sustainability, 11, (2019); Yang X., Zhao Z., Lu S., Exploring spatial-temporal patterns of urban human mobility hotspots, Sustainability, 8, (2016); China Internet Local Life Services Blue Book, (2017); China Online Catering Food Market Research Report; China Delivery Development Research Report, (2017); Statistical Communique of Hangzhou on the 2018 National Economic and Social Development; Ord J.K., Getis A., Local spatial autocorrelation statistics: Distributional issues and an application, Geogr. Anal., 27, pp. 286-306, (1995); Makrai G., Efficient method for large-scale spatio-temporal hotspot analysis (GIS Cup), Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, pp. 1-18, (2016); Ray S., Turi R.H., Determination of number of clusters in k-means clustering and application in colour image segmentation, Proceedings of the 4th International Conference on Advances in Pattern Recognition and Digital Techniques, pp. 137-143, (1999); Zhang Y., Zhu Z., Research on mutual driving relationship between industrial agglomeration and talent gathering in Jiangsu, Proceedings of the Second International Conference on Economic and Business Management (FEBM 2017), (2017); Florida R., The economic geography of talent, Ann. Assoc. Am. Geogr., 92, pp. 743-755, (2002); Song Y., Zenou Y., Urban villages and housing values in China, Reg. Sci. Urban Econ., 42, pp. 495-505, (2012); Wehrhahn R., Bercht A.L., Krause C.L., Azzam R., Kluge F., Strohschon R., Wiethoff K., Baier K., Urban restructuring and social and water-related vulnerability in megacities-the example of the urban village of Xincun, Guangzhou (China), Die Erde, 139, pp. 227-249, (2008)","Y. Wang; School of Earth Sciences, Zhejiang University, Hangzhou, 38 Zheda Road, 310027, China; email: wangyuanyuanxy@zju.edu.cn",null,"MDPI AG",{"$nulls":5},2.2209964E7,null,null,null,"English","ISPRS Int. J. Geo-Inf.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85077997694"]
["Ziyadin S.; Yergobek D.; Kazhmuratova A.; Kuralova A.","Ziyadin, Sayabek (55339474600); Yergobek, Dimash (57216620199); Kazhmuratova, Aigerim (57212377491); Kuralova, Aigerim (57216617903)","55339474600; 57216620199; 57212377491; 57216617903","KAZAKHSTAN'S TRANSIT POTENTIAL DEVELOPMENT through TRANSFORMATION of LOGISTICS PROCESSES AS A PART of ECONOMIC GROWTH",2020.0,"Communications - Scientific Letters of the University of Žilina",22.0,4.0,null,56.0,62.0,6.0,1.0,"10.26552/com.C.2020.4.56-62","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85092258700&doi=10.26552%2fcom.C.2020.4.56-62&partnerID=40&md5=eeb1b48f540ade893bbc42108a2a70a4","Korkyt ata Kyzylorda State University, Kazakhstan; Al-Farabi Kazakh National University, Kazakhstan","Ziyadin S., Korkyt ata Kyzylorda State University, Kazakhstan; Yergobek D., Al-Farabi Kazakh National University, Kazakhstan; Kazhmuratova A., Al-Farabi Kazakh National University, Kazakhstan; Kuralova A., Al-Farabi Kazakh National University, Kazakhstan","The rapid development of transport, the widespread introduction of modern transport technologies, close cooperation with Russia, China and other neighboring countries, will allow Kazakhstan to become a serious player in the transportation market between Europe and Asia in the coming years. Such existing transport potential directly affects the economic growth of the country which will lead to high living standard. The global movement towards digitalization is transforming the logistics industry, as well. The \"digit\" changes the channels of movement of goods, delivery formats and management processes. Development of e - commerce and the increasing supply requirements - multichannel, responsiveness, transparency, accuracy - stimulate retailers and logistics operators to increase efficiency of processes and introduce new technologies. Therefore, the ways of prosperity of Kazakhstani economy, through digitalization of logistics processes is considered in this article. © 2 0 2 0 U N I V E R S I T Y O F Z I L I N A","Digitalization; E - commerce; Economic growth; Innovations; Logistics operations; New technologies; Transit potential",{"$nulls":7},"International Trade Statistics 2014 - World Trade Organization; LUTHRA S., MANGLA S. K., Evaluating challenges to Industry 4.0 initiatives for supply chain sustainability in emerging economies, Process Safety and Environmental Protection, 117, pp. 168-179, (2018); HORENBERG D., Applications within Logistics 4.0: a research conducted on the visions of 3PL service providers, (2017); JAHN C., KERSTEN W., RINGLE C. M., Logistics 4.0 and sustainable supply chain management: innovative solutions for logistics and sustainable supply chain management in the context of industry 4.0, Hamburg International Conference of Logistics (HICL): proceedings, 26, (2018); WAGENER N., Intermodal logistics centres and freight corridors-concepts and trends, LogForum, 13, 3, pp. 273-283, (2017); DOMINGO GALINDO L., The challenges of Logistics 4.0 for the supply chain management and the information technology, (2016); DONG C., BOUTE R., MCKINNON A., VERELST M., Investigating synchro-modality from a supply chain perspective, Transportation Research Part D: Transport and Environment, 61, pp. 42-57, (2018); QU W., REZAEI J., MAKNOON Y., TAVASSZY L., Hinterland freight transportation replanning model under the framework of synchromodality, Transportation Research Part E: Logistics and Transportation Review, 131, pp. 308-328, (2019); VURAL C. A., TUNA O., The prioritisation of service dimensions in logistics centres: a fuzzy quality function deployment methodology, International Journal of Logistics Research and Applications, 19, 3, pp. 159-180, (2016); GIUSTI R., MANERBA D., PERBOLI G., TADEI R., YUAN S., A new open-source system for strategic freight logistics planning: the SYNCHRO-NET optimization tools, Transportation Research Procedia, 30, pp. 245-254, (2018); GIUSTI R., MANERBA D., BRUNO G., TADEI R., Synchromodal logistics: an overview of critical success factors, enabling technologies, and open research issues, Transportation Research Part E: Logistics and Transportation Review, 129, pp. 92-110, (2019); Basler Vision Technologies - inspect World of Vision, (2016); SZYMANSKA O., ADAMCZAK M., CYPLIK P., Logistics 4.0-a new paradigm or set of known solutions?, Research in Logistics and Production, 7, 4, pp. 299-310, (2017); SCHLOTT S., Vehicle systems for Logistics 4.0, ATZ Worldwide [online], 119, 2, pp. 8-13, (2017); TANG C. S., VEELENTURF L. P., The Strategic role of logistics in the Industry 4.0 era, Transportation Research Part E: Logistics and Transportation Review, 129, pp. 1-11, (2019); BARRETO L., AMARAL A., PEREIRA T., Industry 4.0 implications in logistics: an overview, Procedia Manufacturing, 13, pp. 1245-1252, (2017); YAVAS V., OZKAN - OZEN Y. D., Logistics centers in the new industrial era: a proposed framework for logistics center 4.0, Transportation Research Part E: Logistics and Transportation Review, 135, (2020); Official foreign exchange rates for 2020 year - National Bank of Kazakhstan; Statistics for socio-economic indicators - Ministry of National Economy of the Republic of Kazakhstan, Statistics Committee","D. Yergobek; Al-Farabi Kazakh National University, Kazakhstan; email: Yedk2017@mail.ru",null,"University of Žilina",{"$nulls":5},1.3354205E7,null,null,null,"English","Commun. Sci. Lett. Univ. Zilina","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85092258700"]
["Shahmohammadi S.; Steinmann Z.J.N.; Tambjerg L.; Van Loon P.; King J.M.H.; Huijbregts M.A.J.","Shahmohammadi, Sadegh (57200016249); Steinmann, Zoran J. N. (56027056400); Tambjerg, Lau (57215867113); Van Loon, Patricia (56261985000); King, J. M. Henry (36468594300); Huijbregts, Mark A. J. (6701896825)","57200016249; 56027056400; 57215867113; 56261985000; 36468594300; 6701896825","Comparative Greenhouse Gas Footprinting of Online versus Traditional Shopping for Fast-Moving Consumer Goods: A Stochastic Approach",2020.0,"Environmental Science and Technology",54.0,6.0,null,3499.0,3509.0,10.0,34.0,"10.1021/acs.est.9b06252","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85082146855&doi=10.1021%2facs.est.9b06252&partnerID=40&md5=313a458e90a0303a84b62471f64bfa81","Department of Environmental Science, Institute for Water and Wetland Research, Faculty of Science, Radboud University Nijmegen, Nijmegen, 6525 AJ, Netherlands; Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Bedford, MK44 1LQ, United Kingdom; Chalmers Industriteknik, Sven Hultins Plats 1, Göteborg, 41258, Sweden; Department of Environmental Sciences, Wageningen University and Research, Roevendaalsesteeg 3, Wageningen, 6708PB, Netherlands; Environmental Modeling, Sensing and Analysis, TNO, Princetonlaan 6, Utrecht, 3584 CB, Netherlands","Shahmohammadi S., Department of Environmental Science, Institute for Water and Wetland Research, Faculty of Science, Radboud University Nijmegen, Nijmegen, 6525 AJ, Netherlands, Environmental Modeling, Sensing and Analysis, TNO, Princetonlaan 6, Utrecht, 3584 CB, Netherlands; Steinmann Z.J.N., Department of Environmental Science, Institute for Water and Wetland Research, Faculty of Science, Radboud University Nijmegen, Nijmegen, 6525 AJ, Netherlands, Department of Environmental Sciences, Wageningen University and Research, Roevendaalsesteeg 3, Wageningen, 6708PB, Netherlands; Tambjerg L., Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Bedford, MK44 1LQ, United Kingdom; Van Loon P., Chalmers Industriteknik, Sven Hultins Plats 1, Göteborg, 41258, Sweden; King J.M.H., Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Bedford, MK44 1LQ, United Kingdom; Huijbregts M.A.J., Department of Environmental Science, Institute for Water and Wetland Research, Faculty of Science, Radboud University Nijmegen, Nijmegen, 6525 AJ, Netherlands","Variability in consumer practices and choices is typically not addressed in comparisons of environmental impacts of traditional shopping and e-commerce. Here, we developed a stochastic model to quantify the variability in the greenhouse gas (GHG) footprints of product distribution and purchase of fast-moving consumer goods (FMCGs) via three prevalent retail channels in the United Kingdom (U.K.). We found that shopping via bricks and clicks (click and fulfillment via physical store delivery) most likely decreases the GHG footprints when substituting traditional shopping, while FMCGs purchased through pure players with parcel delivery often have higher GHG footprints compared to those purchased via traditional retail. The number of items purchased and the last-mile travel distance are the dominant contributors to the variability in the GHG footprints of all three retail channels. We further showed that substituting delivery vans with electric cargo bikes can lead to a GHG emission reduction of 26% via parcel delivery. Finally, we showed the differences in the \"last mile\" GHG footprint of traditional shopping in the U.K. compared to three other countries (China, Netherlands, and the United States), which are primarily caused by the different shares of modes of transport (walking and by car, bus, and bike). © 2020 American Chemical Society.",null,"China; Greenhouse Effect; Greenhouse Gases; Netherlands; United Kingdom; United States; China; Netherlands; United Kingdom; United States; Electric bikes; Emission control; Greenhouse gases; Purchasing; Sales; Stochastic models; Stochastic systems; Trucks; Bricks and clicks; Consumer practices; Fast moving consumer goods; Greenhouse gas (GHG); Physical stores; Product distributions; Stochastic approach; Travel distance; carbon footprint; cargo; commercial activity; comparative study; electronic commerce; environmental economics; greenhouse gas; shopping activity; stochasticity; article; carbon footprint; China; consumer; controlled study; human; human experiment; Netherlands; quantitative analysis; shopping; stochastic model; travel; United Kingdom; United States; walking; greenhouse effect; greenhouse gas; Distribution of goods",null,"Greenhouse Gases, ",null,null,"Horizon 2020 Framework Programme, H2020, (641459)","This project has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement no. 641459 (RELIEF).","Kenton W., Fast-Moving Consumer Goods (FMCG), (2019); THE FUTURE of E-COMMERCE in FMCG, (2017); Van Loon P., Deketele L., Dewaele J., McKinnon A., Rutherford C., A comparative analysis of carbon emissions from online retailing of fast moving consumer goods, J. Cleaner Prod., 106, pp. 478-486, (2015); Edwards J.B., McKinnon A.C., Shopping trip or home delivery: Which has the smaller carbon footprint?, Logistics and Transport Focus, (2009); Wygonik E., Goodchild A., Evaluating the efficacy of shared-use vehicles for reducing greenhouse gas emissions: A U.S. case study of grocery delivery, Journal of the Transportation Research Forum, (2012); Siikavirta H., Punakivi M., Karkkainen M., Linnanen L., Effects of E-Commerce on Greenhouse Gas Emissions: A Case Study of Grocery Home Delivery in Finland, J. Ind. Ecol., 6, pp. 83-97, (2002); Tiwari S., Singh P., E-commerce: Prospect or threat for environment, Int. J. Environ. Sci. Dev., 2, (2011); Boyer K.K., Prud'Homme A.M., Chung W., The last mile challenge: Evaluating the effects of customer density and delivery window patterns, J. Bus. 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Environ., 61, pp. 325-338, (2018); Driving Shopper Behavior in Grocery, (2014); Weber C.L., Hendrickson C.T., Matthews H.S., Nagengast A., Nealer R., Jaramillo P., Life cycle comparison of traditional retail and e-commerce logistics for electronic products: A case study of buy. com, Sustainable Systems and Technology, 2009. ISSST'09 IEEE International Symposium, pp. 1-6, (2009); Di Sorrentino E.P., Woelbert E., Sala S., Consumers and their behavior: State of the art in behavioral science supporting use phase modeling in LCA and ecodesign, Int. J. Life Cycle Assess., 21, pp. 237-251, (2016); Edwards J.B., McKinnon A.C., Cullinane S.L., Comparative analysis of the carbon footprints of conventional and online retailing: A \"last mile\" perspective, Int. J. Phys. Distrib. Logist. Manage., 40, pp. 103-123, (2010); Rushton A., Croucher P., Baker P., The Handbook of Logistics and Distribution Management: Understanding the Supply Chain, (2014); Jingzhu L., Electric 3-wheelers in Urban Delivery in China and Germany - A Bumpy Road Ahead?, (2018); Goodchild A., Toy J., Delivery by drone: An evaluation of unmanned aerial vehicle technology in reducing CO<sub>2</sub> emissions in the delivery service industry, Transp. Res. Part D: Transp. Environ., 61, pp. 58-67, (2018); Field M., World's first robot delivery service launched in Milton Keynes, The Telegraph, (2018); Reid C., Cargobikes Not Drones Are the Future for Urban Deliveries, (2018); Gruber J., Kihm A., Lenz B., A new vehicle for urban freight? An ex-ante evaluation of electric cargo bikes in courier services, Res. Transp. Bus. 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Rev., 10, (2018); Allen J., Piecyk M., Piotrowska M., An analysis of the parcels market and parcel carriers' operations in the UK, Freight Traffic Control, 2050, (2016); Huizer D., Oldenkamp R., Ragas A.M.J., Van Rooij J.G.M., Huijbregts M.A.J., Separating uncertainty and physiological variability in human PBPK modelling: The example of 2-propanol and its metabolite acetone, Toxicol. 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Blockchain Assoc., 1, (2018); Tian F., An agri-food supply chain traceability system for China based on RFID & blockchain technology, 2016 13th International Conference on Service Systems and Service Management (ICSSSM), pp. 1-6, (2016); Caro M.P., Ali M.S., Vecchio M., Giaffreda R., Blockchain-based traceability in Agri-Food supply chain management: A practical implementation, 2018 IoT Vertical and Topical Summit on Agriculture-Tuscany (IOT Tuscany), pp. 1-4, (2018); Barr A., E-tailers Embrace Same-day Delivery, but US Shoppers Shrug-survey, (2013); Utter D., Shop. Org Asks if Business Should Rush to Same-day Delivery, (2013); Brusch M., Stuber E., Developments and Classifications of Online Shopping Behavior in Germany, Int. J. Cyber Soc. Educ., 7, pp. 147-156, (2014); Hiselius L.W., Rosqvist L.S., Clark A., E-shopping and changed transport behavior, European Transport Conference 2012, (2012)","S. Shahmohammadi; Department of Environmental Science, Institute for Water and Wetland Research, Faculty of Science, Radboud University Nijmegen, Nijmegen, 6525 AJ, Netherlands; email: sadegh_shahmohammadi@yahoo.com",null,"American Chemical Society",{"$nulls":5},"0013936X",null,"ESTHA",3.2100529E7,"English","Environ. Sci. Technol.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85082146855"]
["Tebaldi L.; Murino T.; Bottani E.","Tebaldi, Letizia (57204497688); Murino, Teresa (6506833048); Bottani, Eleonora (14035135900)","57204497688; 6506833048; 14035135900","An adapted version of the water wave optimization algorithm for the capacitated vehicle routing problem with time windows with application to a real case using probe data",2020.0,"Sustainability (Switzerland)",12.0,9.0,3666.0,null,null,null,6.0,"10.3390/su12093666","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85085300365&doi=10.3390%2fsu12093666&partnerID=40&md5=de62476172e629de59365865f0d76326","Department of Engineering and Architecture, University of Parma, viale delle Scienze 181/A, Parma, 43124, Italy; Department of Chemical, Materials and Industrial Production Engineering, University of Naples 'Federico II', Piazzale Tecchio 80, Napoli, 80125, Italy","Tebaldi L., Department of Engineering and Architecture, University of Parma, viale delle Scienze 181/A, Parma, 43124, Italy; Murino T., Department of Chemical, Materials and Industrial Production Engineering, University of Naples 'Federico II', Piazzale Tecchio 80, Napoli, 80125, Italy; Bottani E., Department of Engineering and Architecture, University of Parma, viale delle Scienze 181/A, Parma, 43124, Italy","Customers' habits, as far as shipping requests are concerned, have changed in the last decade, due to the fast spread of e-commerce and business to consumer (B2C) systems, thus generating more and more vehicles on the road, traffic congestion and, consequently, more pollution. Trying to partially solve this problem, the operational research field dedicates part of its research to possible ways to optimize transports in terms of costs, travel times, full loads etc., with the aim of reducing inefficiencies and impacts on profit, planet and people, i.e., the well-known triple bottom line approach to sustainability, also thanks to new technologies able to instantly provide probe data, which can detail information as far as the vehicle behavior. In line with this, an adapted version of the metaheuristic water wave optimization algorithm is here presented and applied to the context of the capacitated vehicle routing problem with time windows. This latter one is a particular case of the vehicle routing problem, whose aim is to define the best route in terms of travel time for visiting a set of customers, given the vehicles capacity and time constraints in which some customers need to be visited. The algorithm is then tested on a real case study of an express courier operating in the South of Italy. A nearest neighbor heuristic is applied, as well, to the same set of data, to test the effectiveness and accuracy of the algorithm. Results show a better performance of the proposed metaheuristic, which could improve the journeys by reducing the travel time by up to 23.64%. © 2020 by the authors.","Logistics; Metaheuristic algorithm; Routing; Sustainability; Transport; Vehicle routing problem; Water wave optimization","Italy; accuracy assessment; consumption behavior; electronic commerce; heuristics; optimization; profitability; shipping; sustainability; traffic congestion; travel time",{"$nulls":6},"Singh R.K., Murty H.R., Gupta S.K., Dikshit A.K., An overview of sustainability assessment methodologies, Ecol. Indic., 15, pp. 281-299, (2012); Litman T., Burwell D., Issues in sustainable transportation, Int. J. Glob. Environ. Issues, 6, pp. 331-347, (2006); Banister D., Anderton K., Bonilla D., Givoni M., Schwanen T., Transportation and the, Environment. Annu. Rev. Environ. Resour., 36, pp. 247-270, (2011); Baldacci R., Mingozzi A., Roberti R., Recent exact algorithms for solving the vehicle routing problem under capacity and time window constraints, Eur. J. Oper. Res., 218, pp. 1-6, (2012); Dantzig G.B., Ramser J.H., The Truck Dispatching Problem, Manag. Sci., 6, pp. 80-91, (1959); Abbatecola L., Fanti M.P., Ukovich W., A Review of New Approaches for Dynamic Vehicle Routing Problem, Proceedings of the 2016 IEEE International Conference on Automation Science and Engineering (CASE), (2016); Drexl M., Rich Vehicle Routing in Theory and Practice, Fraunhofer Centre for Applied Research on Supply Chain Services, (2011); Solomon M.M., Algorithms for the vehicle routing and scheduling problem with time window constraints, Oper. 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Res., 55, pp. 1-11, (2015); Wu X.-B., Liao J., Wang Z.-C., Water Wave Optimization for the Traveling Salesman Problem, Intelligent Computing Theories and Methodologies; Huang, 9225, (2015); Bottani E., Rinaldi M., Montanari R., Murino T., Centobelli P., An adapted water wave optimization for routing order pickers in manual warehouses, Proceedings of the XXI Summer School \"Francesco Turco\"-Industrial Systems Engineering, (2016); Cover T., Hart P., Nearest neighbor pattern classification, IEEE Trans. Inf. Theory, 13, pp. 21-27, (1967); Layeb A., Ammi M., A GRASP algorithm based on new randomized heuristic for vehicle routing problem, J. Comput. Inf. Technol., 1, pp. 35-46, (2013); Li Y.H., Mao H.J., Qin Y.M., Vehicle Routing Problem with Multiple Time Windows and Batch Splitting Based on Inferior First Bidirectional Search Algorithm, J. Phys.:Conf. Ser., 1314, (2019); Liu J., Liu D., Liu M., He Y., An improved multiple ant colony system for the collection vehicle routing problems with intermediate facilities, Proceedings of the 8thWorld Congress on Intelligent Control and Automation, (2010); Soltanian A., Derakhshan F., Soleimanpour-Moghadam M., MWWO: ModifiedWaterWave Optimization, Proceedings of the 3rd Conference on Swarm Intelligence and Evolutionary Computation (CSIEC2018), (2018); Sathyanarayanan S., Suresh J., Jayakumar S.K.V., A hybrid population seeding technique based genetic algorithm for stochastic multiple depot vehicle routing problem, Proceedings of the International Conference of Computing and Communications Technologies, pp. 119-127, (2015); Braekers K., Ramaekers K., Van Nieuwenhuyse I., The vehicle routing problem: State of the art classification and review, Comput. Ind. Eng., 99, pp. 300-313, (2016)","E. Bottani; Department of Engineering and Architecture, University of Parma, Parma, viale delle Scienze 181/A, 43124, Italy; email: eleonora.bottani@unipr.it",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85085300365"]
["Qin X.; Liu Z.; Tian L.","Qin, Xuelian (57211914371); Liu, Zhixue (55656822100); Tian, Lin (57191291331)","57211914371; 55656822100; 57191291331","The strategic analysis of logistics service sharing in an e-commerce platform",2020.0,"Omega (United Kingdom)",92.0,null,102153.0,null,null,null,119.0,"10.1016/j.omega.2019.102153","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85075354821&doi=10.1016%2fj.omega.2019.102153&partnerID=40&md5=f7ea35294dfc72f24e36a7efc00c876b","School of Management, Huazhong University of Science and Technology, Wuhan, 430074, China; School of Management, Fudan University, Shanghai, 200433, China","Qin X., School of Management, Huazhong University of Science and Technology, Wuhan, 430074, China; Liu Z., School of Management, Huazhong University of Science and Technology, Wuhan, 430074, China; Tian L., School of Management, Fudan University, Shanghai, 200433, China","In e-commerce, the success of hybrid online platforms is well documented where the platform not only works as a retailer but also offers online marketplace services to sellers. Logistics service is one of the most expensive operations for e-commerce and plays a critical role in promoting online purchases. In most cases, the platform builds a self-supporting logistics service system to deliver its own products, and the seller outsources the logistics service to third-party logistics service providers (TPLPs). Recently, the e-commerce market has emerged with a new trend of business-to-business logistics service sharing—the platform shares its logistics service system with the seller. In this paper, we first analyze the strategic and economic impacts of logistics service sharing. Our analysis shows that whereas logistics service sharing will lead to a lose-win situation for the platform and the seller when the TPLP's logistics service level and the market potential are low, it will lead to a win-lose situation when the TPLP's logistics service level or the market potential is very high. Furthermore, a win-win situation can be achieved when the TPLP's logistics service level and the market potential are in the middle regions. Then, we examine the equilibrium mode by considering the strategic interactions between the platform and the seller. We find that when the TPLP's logistics service level and the market potential are relatively low, the equilibrium mode is No-Service-Sharing. As the TPLP's logistics service level, the market potential, or both increase, the equilibrium mode will evolve from No-Service-Sharing to Service-Sharing. © 2019 Elsevier Ltd","Coopetition; E-commerce; Hybrid platform; Logistics service sharing","Outsourcing; Co-opetition; E- commerces; Equilibrium modes; Hybrid platform; Logistic service sharing; Logistics services; Market potential; Service levels; Service systems; Service-sharing; article; Electronic commerce",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (71702093, 71922008, 71972081)","All authors have contributed equally to the paper. The authors gratefully acknowledge the editor, the associate editor, and two anonymous reviewers for helpful suggestions that have significantly improved the paper. Lin Tian is the corresponding author of this paper, which is supported in part by the National Natural Science Foundation of China [Grants 71972081 , 71922008 and 71702093 ].  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Tian; School of Management, Fudan University, Shanghai, 200433, China; email: tianlin@fudan.edu.cn",null,"Elsevier Ltd",{"$nulls":5},3050483.0,null,"OMEGA",null,"English","Omega","Article","Final",null,"Scopus","2-s2.0-85075354821"]
["Strang K.D.; Vajjhala N.R.","Strang, Kenneth David (57147570200); Vajjhala, Narasimha Rao (56106511000)","57147570200; 56106511000","Predictors of e-service consumption in a highly productive Brazil-Russia-India-China-South Africa region sample",2020.0,"International Journal of E-Services and Mobile Applications",12.0,1.0,null,39.0,56.0,17.0,1.0,"10.4018/IJESMA.2020010103","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85079768549&doi=10.4018%2fIJESMA.2020010103&partnerID=40&md5=95ae147b7125852c0b945f58f02a9d18","APPC Research, New York, United States; American University of Nigeria, Yola, Nigeria","Strang K.D., APPC Research, New York, United States; Vajjhala N.R., American University of Nigeria, Yola, Nigeria","The authors investigated consumer e-commerce behavior in a Brazil-Russia-India-China-South-Africa (BRICS) region from a socio-cultural perspective. BRICS countries are important to study because they have a large population representative of other global e-services markets, they account for 40% of the world's population, 26% of the world's land and approximately a third of the world's gross domestic economic e-commerce production, plus residents are habitual consumers of mobile technology like smartphones. A binary logistic regression model revealed that young educated consumer satisfaction with e-services, e-service happiness, positive feelings and e-service pleasant feelings, but not e-service excitement, could predict purchase behavior. The model correctly classified 87.3% of the e-commerce consumers using two factors and a second model with one factor correctly categorized 90.5% of them. These results are important for managers and academics to consider. Copyright © 2020, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.","Brazil-Russia-India-China-South-Africa; Empirical Predictive Model Study; Mobile E-Services; Online Purchase Behavior; Socio-Cultural Factors",{"$nulls":5},"American University, AU","This research was indirectly supported by American University.","Agarwal H., Dixit S., The encumbered growth of ecommerce in India: Can we help?, Aweshkar Research Journal, 23, 2, pp. 114-132, (2017); Ajzen I., Fishbein M., Understanding Attitude and Predicting Social Behavior, (1980); Babo G., Evaluating suburban New Jersey building principals using the ISLLC 2008 “functions” as a paradigm model, The International Journal of Educational Leadership Preparation, 3, 2, (2008); Beleites C., Geiger K., Kirsch M., Sobottka S.B., Schackert G., Salzer R., Raman spectroscopic grading of astrocytoma tissues: Using soft reference information, Annals of Bioanalysis Chemistry, 400, 1, pp. 2801-2816, (2011); Bremmer I., The mixed fortunes of the BRICS countries, in 5 facts, Time, (2017); Carter S., Yeo A.C.-M., From hedonism and utilitarianis, to anticipated actual behavior: Do UK and Malaysian postgraduate students behave differently to mobile apps?, Economics. 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["Amling A.; Daugherty P.J.","Amling, Alan (57205304348); Daugherty, Patricia J. (6604065239)","57205304348; 6604065239","Logistics and distribution innovation in China",2020.0,"International Journal of Physical Distribution and Logistics Management",50.0,3.0,null,323.0,332.0,9.0,20.0,"10.1108/IJPDLM-07-2018-0273","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85059461289&doi=10.1108%2fIJPDLM-07-2018-0273&partnerID=40&md5=5993c463e41ede9c0c66bfe948e99fc4","Corporate Strategy, United Parcel Service, Atlanta, GA, United States; Department of Supply Chain Management, Iowa State University College of Business, Ames, IA, United States","Amling A., Corporate Strategy, United Parcel Service, Atlanta, GA, United States; Daugherty P.J., Department of Supply Chain Management, Iowa State University College of Business, Ames, IA, United States","Purpose: The purpose of this paper is to explore how two mega-trends, e-commerce and urbanization, have the potential to reshape logistics practices around the world. Primary focus is on how Chinese business practices and logistics innovations are increasingly relevant to the USA and other western countries. Design/methodology/approach: Experience-based thought piece focusing on specific Chinese logistics innovations centering on speed, adaptability and new business models. Findings: The Chinese economy has played a key role in providing support and enabling logistics innovations in China. Key enablers include the ubiquitous connectivity and applications availability, the dynamic low-cost labor environment and government support for the Chinese logistics industry. Research limitations/implications: This study suggests new areas for research. Practical implications: This study provides insights into the potential value associated with adopting innovative Chinese logistics practices. Social implications: This study provides suggested areas of attention to help focus on logistics operations on key societal trends. Originality/value: Our paper provides insights into the potential value associated with adopting innovative Chinese logistics practices. We believe this represents a significant contribution as little coverage of the topics have been noted to date in leading logistics/supply chain journals. © 2018, Emerald Publishing Limited.","Chinese logistics practices; E-commerce; Logistics innovations; Logistics profit centres; Pan-industrial firms; Urbanization",{"$nulls":7},"Alibaba fully acquires Ele.me, (2018); 2017 Amazon Annual Report, (2018); Amazon orders 20,000 vans to bolster its delivery program, (2018); Belanger L., Amazon will let entrepreneurs start their own delivery business and earn up to $300,000 a year, Entrepreneur, (2018); Brozek M., Raising the bar: how gen Z expectations are reshaping brand experiences, (2017); Cainiao network overview, (2016); Cainiao in pursuit of advanced unmanned logistics networks, (2018); Chen J., Rapid urbanization in China: a real challenge to soil protection and food security, CATENA, 69, pp. 1-15, (2007); China tech briefings: Ling Shou Tong-Alibaba Leverages independent convenient store to gain a competitive advantage in new retail, (2018); D'Aveni R., Choosing scope over focus, MIT Sloan Management Review, 58, 4, pp. 22-26, (2017); Daugherty P.J., Stank T.P., Ellinger A.E., Leveraging logistics/distribution capabilities: the effect of logistics service on market share, Journal of Business Logistics, 19, 2, pp. 35-51, (1998); Flint D.J., Gammelgard B., Mentzer J.T., Logistics innovation: a customer value – oriented social process, Journal of Business Logistics, 26, 1, pp. 113-147, (2005); Giuffrida M., Mangiaracina R., Perego A., Tumino A., Cross-border B2C e-commerce to greater China and the role of logistics: a literature review, International Journal of Physical Distribution & Logistics Management, 47, 9, pp. 772-795, (2017); Grawe S.J., Logistics innovation: a literature-based conceptual framework, The International Journal of Logistics Management, 20, 3, pp. 360-377, (2009); Guan X., Wei H., Lu S., Dai Q., Su H., Assessment on the urbanization strategy in china: achievements, challenges and reflections, Habitat International, 71, pp. 97-109, (2018); Report on china’s O2O catering market, 2017-2018, (2018); Jiao Z., Development of e-commerce logistics in China, Contemporary Logistics in China, pp. 1-19, (2013); Liao S., How WeChat came to rule china, (2018); Lin L.Y.C.-W., Why Alibaba’s jack ma can’t seem to win over the US, Wall Street Journal, (2018); Ma J., Letter to Shareholders, (2017); Melnyk S.A., Stanton D.J., The customer-centric supply chain, Supply Chain Management Review, 20, 12, pp. 28-39, (2017); Melton J., Grocery chain Aldi will roll out instacard delivery nationwide, (2018); Schumpeter J., The Theory of Economic Development: An Inquiry into Profits, Capital, Credit, Interest, and the Business Cycle, (1934); Smith A., The Glasgow edition of the works and correspondence of Adam Smith, Life and Works of Adam Smith, 3, (1980); How does JD prepare for double 11?, (2017); Stambor Z., Walmart revamps Jet in a big to attract urban shoppers, (2018); Takada K., In china’s delivery market, smaller is better, (2012); Teo S., Yip C., Hu I., Liu A., China’s online retail sales may near US$1 trillion for 2017 after record shopping spree, (2017); Thompson A., Harry & David to open 20 pop-up stores for holiday season, (2017); Woodhouse A., JD.com raises $2.5B for logistics subsidiary, (2018); Yang B., Intelligent courier locker offers ‘last mile’ solution, (2017); Zhang Y., Supply chain in focus with new approach, (2017); Logistics T.I., Alibaba and Cainiao’s investment in ZTO express – more than what meets the eye, (2017)","P.J. Daugherty; Department of Supply Chain Management, Iowa State University College of Business, Ames, United States; email: pjd1@iastate.edu",null,"Emerald Group Holdings Ltd.",{"$nulls":5},9600035.0,null,null,null,"English","Int. J. Phys. Distrib. Logist. Manage.","Article","Final",null,"Scopus","2-s2.0-85059461289"]
["Lu S.; Yang L.; Liu W.; Jia L.","Lu, Shan (57215559005); Yang, Lin (57840066500); Liu, Wenqi (57215561707); Jia, Lin (56023246000)","57215559005; 57840066500; 57215561707; 56023246000","User preference for electronic commerce overpackaging solutions: Implications for cleaner production",2020.0,"Journal of Cleaner Production",258.0,null,120936.0,null,null,null,32.0,"10.1016/j.jclepro.2020.120936","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85081164823&doi=10.1016%2fj.jclepro.2020.120936&partnerID=40&md5=6028d5665b2e0cd1b2a2fcc0b22460cb","School of Management and Economics, Beijing Institute of Technology, China; Sustainable Development Research Institute for Economy and Society of Beijing, China","Lu S., School of Management and Economics, Beijing Institute of Technology, China; Yang L., School of Management and Economics, Beijing Institute of Technology, China; Liu W., School of Management and Economics, Beijing Institute of Technology, China; Jia L., School of Management and Economics, Beijing Institute of Technology, China, Sustainable Development Research Institute for Economy and Society of Beijing, China","The volume of express delivery has increased dramatically with the rapid development of electronic commerce (e-commerce) in China. This increase exacerbates overpackaging and challenges the sustainable development of our society. To solve the issue of overpackaging in e-commerce from the perspective of consumers, this study systematically summarizes the overpackaging solutions from the previous literature and obtains a list of 13 solutions. Then, we rank the user preference for these solutions by conducting a best–worst scaling experiment and analyze the data with the mixed logit model. The research demonstrates that the top three most accepted solutions are the optimization of the packaging strategy, the construction of a recycling system, and large-scale packaging. Results show that consumers have a pronounced preference for technologically improved solutions but a less evident preference for material improvements. This study identifies the overpackaging solutions that consumers prefer. In addition, it provides feasible recommendations for governments and enterprises in reducing packaging waste and promoting cleaner production. © 2020 Elsevier Ltd","Best–worst scaling; Cleaner production; Electronic commerce; Mix logit model; Overpackaging solutions; User preference","Pollution control; Cleaner production; Logit modeling; Mixed logit models; Packaging waste; Recycling systems; Scaling experiments; User preference; Electronic commerce",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (71572013, 71872013, NSFC 71602009); Beijing Municipal Commission of Education","This work was supported by the National Natural Science Foundation of China (Grant ID: NSFC 71602009 , 71872013 , 71572013 ); Special Fund for Joint Development Program of Beijing Municipal Commission of Education .","Agarwal G., Barari S., Tiwari M.K., A PSO-based optimum consumer incentive policy for WEEE incorporating reliability of components, Int. J. Prod. 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Prod., 246, (2020); Zhou G., Gu Y., Wu Y., Gong Y., Mu X., Han H., Chang T., A systematic review of the deposit-refund system for beverage packaging: operating mode, key parameter and development trend, J. Clean. Prod., (2019)","L. Jia; School of Management and Economics, Beijing Institute of Technology Beijing, 100081, China; email: jialin87@bit.edu.cn",null,"Elsevier Ltd",{"$nulls":5},9596526.0,null,"JCROE",null,"English","J. Clean. Prod.","Article","Final",null,"Scopus","2-s2.0-85081164823"]
["He Y.; Zhou F.; Qi M.; Wang X.","He, Yandong (55951616500); Zhou, Fuli (57189093462); Qi, Mingyao (23111610800); Wang, Xu (55951735500)","55951616500; 57189093462; 23111610800; 55951735500","Joint distribution: service paradigm, key technologies and its application in the context of Chinese express industry",2020.0,"International Journal of Logistics Research and Applications",23.0,3.0,null,211.0,227.0,16.0,26.0,"10.1080/13675567.2019.1667314","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85073983272&doi=10.1080%2f13675567.2019.1667314&partnerID=40&md5=0c2d3bc8a17c33d250df8af335bf7fc2","Research Center on Modern Logistics, Graduate School at Shenzhen, Tsinghua University, Shenzhen, China; School of Economics and Management, Zhengzhou University of Light Industry, Zhengzhou, China; College of Mechanical Engineering, Chongqing University, Chongqing, China","He Y., Research Center on Modern Logistics, Graduate School at Shenzhen, Tsinghua University, Shenzhen, China; Zhou F., School of Economics and Management, Zhengzhou University of Light Industry, Zhengzhou, China; Qi M., Research Center on Modern Logistics, Graduate School at Shenzhen, Tsinghua University, Shenzhen, China; Wang X., College of Mechanical Engineering, Chongqing University, Chongqing, China","To cope with the globalisation of online shopping, ecological environment deterioration and increasing traffic pressure, a novel logistics service paradigm–joint distribution (JD)–for tackling the bottlenecks in operational efficiency, quality of service and environment-friendly development is put forward under online shopping combining with the internet of things, service-oriented technologies and other advanced management methods and tools. Then, the concept of JD is defined under online shopping, the differences among JD, third-party express service system (TESS) and self-built logistics system (SLS) are discussed. JD architecture and typical characteristics and the key technologies for developing a JD service platform (JDSP) are introduced. Four core components, i.e. Management system, optimisation on resource service, operational strategies during the delivery, etc. are studied for developing the JDSP. Finally, we develop some key systems and integrate them into the JDSP, also the platform is applied to a joint distribution alliance, and future research directions are discussed. © 2019, © 2019 Informa UK Limited, trading as Taylor & Francis Group.","concept; joint distribution; joint distribution service platform; sharing economy; Urban logistics",{"$nulls":5},"Soft Science Research Project in Henan Province; National Natural Science Foundation of China, NSFC, (71772100); Zhengzhou University of Light Industry, ZZULI, (0140/13501050042); Science and Technology Department of Gansu Province, (192400410016); Shenzhen Municipal Science and Technology Innovation Council, (JCYJ20170412171044606)","This work is supported by the National Natural Science Foundation of China [grant number 71772100]; the Shenzhen Municipal Science and Technology Innovation Committee [grant number JCYJ20170412171044606]; the Soft Science Research Project in Henan Province from Henan Science and Technology Department [grant number 192400410016]; and the Scientific Research Starting Fund from Zhengzhou University of Light Industry [grant number 0140/13501050042]. We would like to thank the editors and anonymous reviewers for their suggestions on improving this paper, and we are also grateful to other researchers in the team of ‘City Joint Distribution for Online Shopping Logistics’.","Aized T., Srai J.S., Hierarchical Modelling of Last Mile Logistic Distribution System, International Journal of Advanced Manufacturing Technology, 70, pp. 1053-1061, (2014); (2015); Boyer K.K., Hult G.T.M., Extending the Supply Chain: Integrating Operations and Marketing in the Online Grocery Industry, Journal of Operations Management, 23, 6, pp. 642-661, (2005); Browne M., (2001); Brummelman H.J., Kuipers B., Vale N., Effecten van Packstations op Verkeersbewegingen, (2003); Chen C., Pan S., Wang Z., Zhong R.Y., Using Taxis to Collect Citywide E-commerce Reverse Flows: A Crowdsourcing Solution, International Journal of Production Research, 55, 7, pp. 1833-1844, (2017); Demir E., Van Woensel T., De Kok T., Multidepot Distribution Planning at Logistics Service Provider Nabuurs B.V, Interfaces, 44, 6, pp. 591-604, (2014); 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Zhou; School of Economics and Management, Zhengzhou University of Light Industry, Zhengzhou, China; email: deepbreath329@outlook.com",null,"Taylor and Francis Ltd.",{"$nulls":5},1.3675567E7,null,null,null,"English","Int. J. Logist. Res. Applic.","Article","Final",null,"Scopus","2-s2.0-85073983272"]
["Scaria A.; Antony M.; Antony M.; Anagha P.","Scaria, Anoop (57216964857); Antony, Milna (57216970593); Antony, Milana (57216970592); Anagha, P. (57216964468)","57216964857; 57216970593; 57216970592; 57216964468","A study on the factors effecting online shopping among young professionals",2020.0,"International Journal on Emerging Technologies",11.0,3.0,null,253.0,256.0,3.0,1.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85085581155&partnerID=40&md5=8f81ebfb125e2c7c256a3e54a3a80953","Vimal Jyothi Institute of Management and Research, Kannur, Chemperi, Kerala, India","Scaria A., Vimal Jyothi Institute of Management and Research, Kannur, Chemperi, Kerala, India; Antony M., Vimal Jyothi Institute of Management and Research, Kannur, Chemperi, Kerala, India; Antony M., Vimal Jyothi Institute of Management and Research, Kannur, Chemperi, Kerala, India; Anagha P., Vimal Jyothi Institute of Management and Research, Kannur, Chemperi, Kerala, India","Online shopping make provision for a new shopping dimension among the people. Online shopping is the process of buying and selling of goods through or over internet. There are many factors which influence the growth of online shopping. Increased number of smart phones and easy accessibility to internet are considered as the basic factors for the development of online shopping. With the help of online shopping, consumers can easily purchase accessories, gadgets, home decors, cosmetics, electronics etc. This study is an attempt to identify the factors which influence the online shopping among Yong professionals. For the analysis of data descriptive statistics have been applied. Chi square test and analysis of variance is used for statistical analysis. Research findings are not conclusive because samples from different professional backgrounds are not equal, and the results are based only on a small number of factors. Majority of respondents agrees that discount; latest trends, delivery time, quality, reputation of the brand, good description of goods, security, entertainment, etc are the important elements in online shopping. Fastest growth of online business will provide both opportunities and challenges to the retailers to attain advantage over competitors and to achieve sustainable growth. © 2020, Research Trend. All rights reserved.","Online shopping; Security issues; Website preference; Young professionals",{"$nulls":7},"Aruna S., William A.J., A Study of Consumer Behavior Towards Online Shopping in Coimbatore District, International Journal of Research in Business Management, 3, 7, pp. 51-62, (2015); Bashir R., Gaur B., Sharma B.K., An Analytical View of the Moderating Effect of Gender on Online Purchase Behavior, International Journal on Emerging Technologies, 1, 1, pp. 2-5, (2019); Dhanalakshmi M., Sakthivel M., Nandhini M., A Study on Customer Perception towards Online Shopping Salem, International Journal of Advanced Research, 5, 1, pp. 2468-2470, (2017); Hardia A., Sharma K., Empirical Study of factors Affecting Online Shopping Amongst Youth, Indian Journal of Retail Management, pp. 1-5, (2019); Kamaraj K., Vethirajan V., Vinayagamoorthy V., Consumer Perception Towards Online Household Products, Restaurant Business, 118, 7, pp. 1-5, (2019); Kansra P., Rajiva D., A Study of Perception of Young People Towards Online Shopping in Punjab. ELK's, International Journal of Marketing, 4, 1, pp. 1-9, (2013); Kinker M., Shukla N.K., An Analysis of Consumer Behaviours Towards Online Shopping of Electronics Goods with Special Reference to Bhopal and Jabalpur City. International Journal of Innovation and Applied, Studies, 14, 1, pp. 218-235, (2016); Nagra G., Gopal R., A Study of Factors Effecting on Online Shopping Behavior of Consumers, International Journal of Science and Research Publications, 3, 6, pp. 1-4, (2013); Rajan B.V., A Study on Consumer's Online Buying Behaviour with Reference to Home Appliances in Kerala, International Research Journal of Management Sociology & Humanities, 10, 8, pp. 17-28, (2019); Sharma R., Mehta K., Sharma S., Understanding online shopping behaviour of Indian shoppers, International Journal of Management and Business Studies, 4, 3, pp. 9-18, (2014); Sharma S.K., Chopra P., Predicting Factors Influencing Online Purchase Behavior Among Indian Youth, International Journal of Recent Technology and Engineering, 8, pp. 765-769, (2019)",null,null,"Research Trend",{"$nulls":5},9758364.0,null,null,null,"English","Int. J. Emerg. Technol.","Article","Final",null,"Scopus","2-s2.0-85085581155"]
["Yuanyuan J.; Zhihui L.; Zhifeng S.","Yuanyuan, Jiao (57421368500); Zhihui, LI (57421264100); Zhifeng, Shen (57420933500)","57421368500; 57421264100; 57420933500","A study on the mechanism of new product diffusion under online social network context: Based on the process of peer influence",2020.0,"Journal of Industrial Engineering and Engineering Management",34.0,5.0,null,105.0,113.0,8.0,2.0,"10.13587/j.cnki.jieem.2020.05.011","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85123241136&doi=10.13587%2fj.cnki.jieem.2020.05.011&partnerID=40&md5=d6c798d5e34a20a052a558a8e6fbc020","Business School, Nankai University, Tianjin, 300071, China; Management Engineering School, Zhengzhou University, Zhengzhou, 450001, China","Yuanyuan J., Business School, Nankai University, Tianjin, 300071, China; Zhihui L., Business School, Nankai University, Tianjin, 300071, China, Management Engineering School, Zhengzhou University, Zhengzhou, 450001, China; Zhifeng S., Management Engineering School, Zhengzhou University, Zhengzhou, 450001, China","Against the background of trade protectionism becoming more serious and the trade war upgrading among countries, innovation-driven development, as a new engine promoting economic structure transformation and upgrade, has gained widespread attention in the practical and theoretical circles. However, if an innovation is not widely applied, it will be difficult to have any real impact on the social economy. So only when an innovation diffused in the social system it can realize its true value. The diffusion of new products as an embodiment of innovation is the key to realize the value of innovation. It is also a basis for the innovation to have any influence on society. With the development of the Internet and Web2.0, social networks like WeChat, blogs, online community, and e-commerce's customer reviews that are characterized by user-generated content, have become more and more widely used. Social media increases interpersonal interdependence and makes interpersonal influence deeper and wider. The new product adopters, especially imitators, who account for 97.5% of all in the system (when innovation is fully diffused) adopt a new product because of interpersonal influence. Thus, interpersonal influence plays a vital role in the diffusion of a new product. Since information exchange occurs mainly among identical or similar individuals (peers), and this is the fundamental means of interpersonal communication, put it differently, individuals are more inclined to choose peers to communicate and interact. Hence, individuals are more influenced by peers than others, especially in the context of social networks; individuals can find and interact with peers who have the same interests or preferences more conveniently and efficiently. Therefore, peer influence on new product diffusion in social networks contexts is larger and deeper than in conventional contexts. How does peer influence play a role in the user's new product adoption intention formation? That is, what is the new product diffusion mechanism based on peer influence? The discussion of this question not only helps scholars to better grasp the cause and effect of the user's new product adoption but also helps the company to better implement the promotion and marketing strategies of new products based on peer influence. However, the existing researches either explore the process of new product diffusion in a certain social system from a macro perspective, such as the Bass model and its extension model or investigate influence factors of new product diffusion from a micro perspective, such as personal characteristics, external factors, and product innovation attributes. All of those have not explored the influence mechanism. For this reason, this study introduces peer influence, a concept from social psychology, into the field of innovation diffusion. Based on the relevant literature, and combined with the use gratification theory, this paper further perfects and supplements the formation process of peer influence, which is based on the influence process theory and the homogenization theory. Motivation drives the formation of peer influence. With peer interaction, peers are unnoticeably influenced to have homogeneous behaviors or opinions, or with interaction, mutual trust is formed, which results in homogeneous behaviors or opinions ultimately. Based on this process, a model was built to study new product diffusion under peer influence in the context of the social network. Data was acquired through the delivery on the network using the snowball method to test the model empirically. The model was revised based on the results of empirical analysis at last. The results show that for the new product diffusion, the information motivation and reward motivation of adopters are the antecedents. This conclusion shows that the new model used by the paper is a further improvement of the homogenization theory and the influence process theory. It shows that user-involved peer-to-peer communication about new products is not a purposeless behavior, but driven by the motivation to obtain more information or gain internal and external compensation to reduce the risk of adopting a new product and maximize the self-interest. Peer communication is the necessary link; the trust composing perceived similarity and benevolence plays a partial mediating role in peer communication and adaption intention and is the direct influence factor of new product diffusion. This conclusion further validates the explanatory power of homogenization theory in the new era, new situation, and new product diffusion field. The influence process theory is only a supplement to the homogenization theory. It cannot completely replace it, because perceived similarity and benevolence, as two dimensions of trust, play a partial mediating role in the new product diffusion, but not a fully mediating role. Peer communication does not influence adoption intention by a trust. In addition, the indirect effect value of the path of the mediating effect is relatively low. However, the trust established in communication plays an active role in the promoting users' willingness to adopt, is one of the direct influencing factors of the new product diffusion, and the higher the trust, the better the communication effect, and the greater the influence on the willingness to adopt. © 2020. All Rights Reserved.","Adoption intention; Peer influence; Social networks; The new product diffusion",{"$nulls":5},"National Natural Science Foundation of China, NSFC, (71672095)","Funded Project: Supported by the Natural Science Foundation of China (71672095)","Rogers E M, Et al., Diffusion of innovations, pp. 45-211, (2016); Dunne A, Lawlor M, Rowley J., Young people's use of online social networking sites-a uses and gratifications perspective, Journal of Research in Interactive Marketing, 4, 1, pp. 46-58, (2010); Kozlenkova IV, Palmatier RW, Fang E, Et al., Online relationship formation, Journal of Marketing a Quarterly Publication of the American Marketing Association, 81, 3, pp. 0-40, (2017); Zhang K, Pelechrinis K., Understanding spatial homophiles: the case of peer influence and social selection[J], Thames and Hudson, 57, 1, pp. 271-281, (2014); Hu X, Huang Q, Zhong X, Et al., The influence of peer characteristics and technical features of a social shopping website on a consumer purchase intention, International Journal of Information Management, 36, 6, pp. 1218-1230, (2016); 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Industrial Eng. Eng. Management","Article","Final",null,"Scopus","2-s2.0-85123241136"]
["Liu W.","Liu, Wei (57212676101)",5.7212676101E10,"Route Optimization for Last-Mile Distribution of Rural E-Commerce Logistics Based on Ant Colony Optimization",2020.0,"IEEE Access",8.0,null,8950401.0,12179.0,12187.0,8.0,40.0,"10.1109/ACCESS.2020.2964328","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85078694858&doi=10.1109%2fACCESS.2020.2964328&partnerID=40&md5=9139ca51e9b13eacb367f6e71aa05a3b","School of Information Engineering, Shaanxi Xueqian Normal University, Xi'an, China","Liu W., School of Information Engineering, Shaanxi Xueqian Normal University, Xi'an, China","This paper aims to solve the last-mile distribution of rural e-commerce logistics (RECL) for the survival of third-party logistics enterprise. Considering the features of the RECL (long transport chain and low consumption density), A route optimization model is constructed for RECL's last-mile distribution to maximize the profit of the logistics enterprise, which is subsidized by the government. To solve the model, the ant colony optimization (ACO) was improved to suit the RECL's last-mile distribution by modifying the heuristic information, the update rule of pheromone, and the solution construction. Next, the optimal combinations of the default parameters in the improved ACO were determined through Matlab tests on five test datasets in different sizes. The other parameters were configured according to the scale of the RECL. On this basis, the improved ACO was proved effective through example analysis on the said test datasets. The analysis results also reflect how the number of vehicles affects the maximum profit of the logistics enterprise and the coverage of the RECL logistics network. © 2013 IEEE.","ant colony optimization (ACO); last-mile distribution; route optimization; Rural e-commerce logistics (RECL)","Artificial intelligence; Electronic commerce; Outsourcing; Profitability; Ant Colony Optimization (ACO); Default parameters; Heuristic information; Last mile; Logistics enterprise; Optimal combination; Route optimization; Third party logistics enterprise; Ant colony optimization",{"$nulls":4},"Colleges and Universities Study Innovation Fund; Scientific Searching Plan Project of Shaanxi Province, Education Department, (16JK1184); Ministry of Education of the People's Republic of China, MOE, (2018A03024)","This work was supported in part by the Scientific Searching Plan Project of Shaanxi Province, Education Department under Grant 16JK1184, and in part by the Colleges and Universities Study Innovation Fund through the Science and Technology Development Center of the Ministry of Education under Grant 2018A03024.","Lim S., Wang L., Srai J., Walmart's omni-channel synergy, Supply Chain Manage. Rev., 32, 3, pp. 30-37, (2017); Lim S., Jin X., Srai J., Consumer-driven e-commerce: A literature review, design framework, and research agenda on last-mile logistics models, Int. J. Phys. Distrib. Logistics Manage., 48, 3, pp. 308-332, (2018); Hayel Y., Quadri D., Jimenez T., Brotcorne L., Decentralized optimization of last-mile delivery services with non-cooperative bounded rational customers, Ann. Oper. Res., 239, 2, pp. 451-469, (2016); Crainic T.G., Ricciardi N., Storchi G., Models for evaluating and planning city logistics systems, Transp. Sci., 43, 4, pp. 432-454, (2009); Boyer K.K., Prud'Homme A.M., Chung W., The last mile challenge: Evaluating the effects of customer density and delivery window patterns, J. Bus. Logistics, 30, 1, pp. 185-201, (2009); Punakivi M., Yrjola H., Holmstrom J., Solving the last mile issue: Reception box or delivery box?, Int. J. Phys. Distrib. 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Appl., 66, pp. 163-175, (2016); Papenhausen E., Mueller K., Coding ants: Optimization of GPU code using ant colony optimization, Comput. Lang., Syst. Struct., 54, pp. 119-138, (2018); Ranjbar M., Kazemi A., A generalized variable neighborhood search algorithm for the talent scheduling problem, Comput. Ind. Eng., 126, pp. 673-680, (2018); Vansteenwegen P., Souffriau W., Oudheusden D.V., The orienteering problem: A survey, Eur. J. Oper. Res., 209, 1, pp. 1-10, (2011); Ke L., Archetti C., Feng Z., Ants can solve the team orienteering problem, Comput. Ind. Eng., 54, 3, pp. 648-665, (2008); Fischetti M., Gonzalez J.J.S., Toth P., Solving the orienteering problem through branch-and-cut, INFORMS J. Comput., 10, 2, pp. 133-148, (1998); Ferreira J., Quintas A., Oliveira J.A., Pereira G.A.B., Dias L., Solving the team orienteering problem: Developing a solution tool using a genetic algorithm approach, Soft Computing in Industrial Applications, 223, pp. 365-375, (2014)","W. Liu; School of Information Engineering, Shaanxi Xueqian Normal University, Xi'an, China; email: liu_weei@163.com",null,"Institute of Electrical and Electronics Engineers Inc.",{"$nulls":5},2.1693536E7,null,null,null,"English","IEEE Access","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85078694858"]
["Jaghbeer Y.; Hanson R.; Johansson M.I.","Jaghbeer, Yasmeen (57194723484); Hanson, Robin (55075175500); Johansson, Mats Ingemar (7401997169)","57194723484; 55075175500; 7401997169","Automated order picking systems and the links between design and performance: a systematic literature review",2020.0,"International Journal of Production Research",null,null,null,4489.0,4505.0,16.0,56.0,"10.1080/00207543.2020.1788734","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85087632818&doi=10.1080%2f00207543.2020.1788734&partnerID=40&md5=0f84101bfb43a1987242926e5c82c047","Department of Technology Management and Economics, Chalmers University of Technology, Gothenburg, Sweden","Jaghbeer Y., Department of Technology Management and Economics, Chalmers University of Technology, Gothenburg, Sweden; Hanson R., Department of Technology Management and Economics, Chalmers University of Technology, Gothenburg, Sweden; Johansson M.I., Department of Technology Management and Economics, Chalmers University of Technology, Gothenburg, Sweden","With new market developments and e-commerce, there is an increased use of and interest in automation for order picking. This paper presents a systematic review and content analysis of the literature. It has the purpose of understanding the relevant performance aspects for automated, or partly automated, OPSs and identifying the studied links between design and performance, i.e. identifying which combinations of design aspects and performance aspects have been studied in previous research. For this purpose, 74 papers were selected and reviewed. From the review, it is clear that there has been an increased number of papers dealing with the performance of automated, or partly automated, OPSs in recent years. Moreover, there are differences between the different OPS types, but, overall, the performance categories of throughput, lead time, and operational efficiency have received the most attention in the literature. The paper identifies links between design and performance that have been studied, as well as links that appear to be under-researched. For academics, this paper synthesises the current knowledge on the performance of automation in OPSs and identifies opportunities for future research. For practitioners, the paper provides knowledge that can support the decision-making process of automation in OPSs. © 2020, © 2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.","automation; logistics; materials handling; Order picking; warehouse operations","Decision making; Content analysis; Decision making process; Market development; Operational efficiencies; Order-picking systems; Performance aspects; Systematic literature review; Systematic Review; Automation",{"$nulls":6},"Andriansyah R., De Koning W.W.H., Jordan R.M.E., Etman L.F.P., Rooda J.E., A Process Algebra Based Simulation Model of a Miniload-Workstation Order Picking System, Computers in Industry, 62, 3, pp. 292-300, (2011); Andriansyah R., Etman L.F.P., Adan I.J., Rooda J.E., Design and Analysis of an Automated Order-Picking Workstation, Journal of Simulation, 8, 2, pp. 151-163, (2014); Andriansyah R., Etman P., Rooda J., First International Conference on Advances in System Simulation, (2009); Andriansyah R., Etman L.F.P., Rooda J., Proceedings of the 2010 Winter Simulation Conference, (2010); Armstrong R.D., Cook W.D., Saipe A.L., Optimal Batching in a Semi-Automated Order Picking System, Journal of the Operational Research Society, 30, 8, pp. 711-720, (1979); 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Hanson; Department of Technology Management and Economics, Chalmers University of Technology, Gothenburg, 412 96, Sweden; email: robin.hanson@chalmers.se",null,"Taylor and Francis Ltd.",{"$nulls":5},207543.0,null,"IJPRB",null,"English","Int J Prod Res","Article","Final","All Open Access; Green Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85087632818"]
["Himela T.H.","Himela, Tanvir Hussain (57196416217)",5.7196416217E10,"Improving customer relationship management (CRM) through database systems and internet marketing - An analysis of online customers of Bangladesh",2020.0,"International Journal of Innovation, Creativity and Change",12.0,5.0,null,394.0,410.0,16.0,0.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85084391696&partnerID=40&md5=c9f6cc5be18752af18cb6e305bfedec8","Monash University, Australia","Himela T.H., Monash University, Australia","Customer relationship management (CRM) is an approach in order to establish interaction with existing and probable clients by using data analysis from a database system named CRM database system which covers all customers' data. These are collected, stored and analysed utilising a customer relationship program. Bangladesh is a developing country where internet marketing is widely used now-a-days; however, lack of proper implementation of the latest technology, lack of adept IT professionals, poor delivery timing, and a bad transportation system are some of the disablers for success in online shopping systems. Also, few pieces of research have been done up to now on the integration of internet marketing and database marketing for online shopping in Bangladesh, as this sector is still developing. This research contains both qualitative and quantitative research in order to discover the ways of improving CRM for online shopping through database and internet marketing in Bangladesh. Face to face interviews, along with questionnaires' distributions, have been taken from Bangladeshi online buyers (customers) in order to know the ways of improvement in CRM systems. Moreover, this research provides information about the paths of the integrated working environment between IT and marketing teams of companies. Furthermore, appropriate recommendations are given for future research according to the results of the research. © 2020 Primrose Hall Publishing Group.","Database marketing; Internet marketing; Online customers in Bangladesh",{"$nulls":7},"Ba S., Johansson W.C., An Exploratory Study of the Impact of e-service Process on Online Customer Satisfaction,\" Production and Operations Management, 17, 1, pp. 107-119, (2008); (2018); Berry M.J., Linoff G.S., Data mining techniques: for marketing, sales, and customer relationship management, (2004); Buttle F., Customer relationship management, (2004); Cravens D.W., Piercy N., Strategic marketing (Vol. 6), (2006); 5G internet by 2021: BTRC, (2019); (2019); Ellson S., 120 Ways To Market Your Business Hyper Locally: Tried and True Tips and Techniques (Vol. 3), (2016); Goldsmith R.E., Goldsmith E.B., Buying apparel over the Internet, Journal of Product & Brand Management, 11, 2, pp. 89-102, (2002); Hopson D.B., Keys K.S., Kroger Co, Online shopping system, (2006); Howladar M.H.R., Islam M.M., Developing Online Shopping Intention Among Bangladesh People: Bangladesh Perspective,\" Developing Countries Studies, 2, 9, (2012); Ishtiaque A.S., Sarwar A., \"E-commerce in Bangladesh\", (2017); McKim B., The differences between CRM and database marketing, Journal of Database Marketing & Customer Strategy Management, 9, 4, pp. 371-375, (2002); Moniruzzaman A.B.M., Hossain S.A., Nosql database: New era of databases for big data analytics-classification, characteristics and comparison, (2013); Ngai E.W., Customer relationship management research (1992-2002) An academic literature review and classification, Marketing intelligence & planning, 23, 6, (2005); O'Leary C., Rao S., Perry C., Improving customer relationship management through database/Internet marketing: A theory-building action research project\", European journal of marketing, 38, 3-4, pp. 338-354, (2004); Parvatiyar A., Sheth J.N., Customer relationship management: Emerging practice, process, and discipline\", Journal of Economic & Social Research, 3, 2, pp. 1-34, (2001); Parvez S., \"Shopping habits changing as online retailers spring up\", (2018); Payne A., Frow P., A strategic framework for customer relationship management, Journal of marketing, 69, 4, pp. 167-176, (2005); Rahman S.M., Optimizing digital marketing for generation Y: an investigation of developing online market in Bangladesh,\" International Business Research, 8, 8, pp. 150-163, (2015); Ramachandan T., \"E-commerce to drive growth in electronic payments\", (2016); Roberts M.L., Zahay D., \"Internet marketing: Integrating online and offline strategies\", (2012); Rosen A., \"The e-commerce question and answer book: a survival guide for business managers'', (2002); Shanthi R., Desti K., Consumers' perception on online shopping, Journal of Marketing and Consumer Research, 13, pp. 14-21, (2015); \"Individuals using the internet\", (2019)","T.H. Himela; Monash University, Australia; email: thhim1@student.monash.edu",null,"Primrose Hall Publishing Group",{"$nulls":5},2.2011315E7,null,null,null,"English","Int. J. Innov. Creat. Change","Article","Final",null,"Scopus","2-s2.0-85084391696"]
["Pato L.","Pato, Lúcia (57194449125)",5.7194449125E10,"THE IMPORTANCE OF ECO-LABELS CERTIFICATIONS AND ICT IN THE PROMOTION OF SUSTAINABLE TOURISM – CASE STUDY OF A RURAL TOURISM UNIT; [A IMPORTÂNCIA DAS CERTIFICAÇÕES ECOLÓGICAS E DAS TIC NA PROMOÇÃO DO TURISMO SUSTENTÁVEL – ESTUDO DE CASO DE UMA UNIDADE DE TURISMO RURAL]; [LA IMPORTANCIA DE LAS ECOCERTIFICACIONES Y LAS TIC EN LA PROMOCIÓN DEL TURISMO SOSTENIBLE – ESTUDIO DE CASO DE UNA UNIDAD DE TURISMO RURAL]",2020.0,"Millenium: Journal of Education, Technologies, and Health",2.0,"Especial 5",null,369.0,377.0,8.0,3.0,"10.29352/mill0205e.37.00242","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85159151778&doi=10.29352%2fmill0205e.37.00242&partnerID=40&md5=4cbeb8a75c2818f461bbb4dbdcd27336","Polytechnic Institute of Viseu, Agrarian School, CERNAS-IPV Research Centre, Viseu, Portugal","Pato L., Polytechnic Institute of Viseu, Agrarian School, CERNAS-IPV Research Centre, Viseu, Portugal","Introduction: In an era of increasing environmental problems, the sustainable conduct of tourism enterprises, particularly in rural tourism, is now of central importance. A good part of the market tends to look for an environmentally friendly and socially responsible enterprise. Hence, information and communication technologies (ICT) are fundamental for the transmission of these principles. Indeed, not only promoters but also e-commerce companies in the field of travel are aware of this reality and need, trying to skillfully communicate their respective sustainable tourism offer. A notable example that highlights the importance of environmental and social sustainability and the value of using information and communication technologies (ICT) is located in the Viseu Dão-Lafões Region (RVDL), more precisely in one of the most interior communities of the region. Objetives: Taking as a unit of analysis a rural tourism enterprise in VDLR, the purpose of this study is to explore the importance of sustainability strategies and ICT for delivery and promotion of the touristic product. Methods: In order to allow a deeper analysis, a case study methodology is used. In addition to a semi-structured interview with the entrepreneur of the unit, it was observed and analyzed the web page of the unit and other electronic documents. Results: In the genesis and development of this enterprise there was always a concern with the environment and with the community. Hence, the enterprise is in a process of certification by Biosphere and Green Key. Whether it is in the development and updating of the web page, social networks, response to evaluations on TripAdvisor / Booking and updating channels of disclosure when reservations are made, the promotion / communication of the most sustainable tourism offer through ICT, occupies the majority of the time that the promoter dedicates to the enterprise. Conclusions: The existence of an environmental conduct by the rural tourism enterprise, and the communication of this conduct, is assumed as a fundamental ingredient for the success of the tourist activity of the enterprise. Moreover, it is fundamental for the attraction of a new tourist more concerned with environmental issues. © 2020, Polytechnic Institute of Viseu. All rights reserved.","customer orientation; ICT; rural tourism; sustainability",{"$nulls":5},"CERNAS Research Centre; Fundação para a Ciência e a Tecnologia, FCT, (IDBU /00681/2020); Instituto Politécnico de Viseu, IPV","Funding text 1: This work is funded by National Funds through the FCT-Foundation for Science and Technology, I.P., within the scope of the project Refª UIDB/00681/2020. Furthermore we would like to thank the CERNAS Research Centre and the CI&DETS of the Polytechnic Institute of Viseu for their support.; Funding text 2: This ow rk is funded by National Funds through the FCT - Foundation for Science and Technology, I.P., project Refª IDBU /00681/2020. Furthermore ew ow uld like to thank the CERNAS Research Centre and the Polytechnic Institute of Viseu for their support.","Alvarez L. S., Martin A. M. D., Casielles R. V., Relationship Marketing and Information and Communication Technologies: Analysis of Retail Travel Agencies, Journal of Travel Research, 45, 4, pp. 453-463, (2007); Angelkovaa T., Koteskia C., Jakovleva Z., Mitrevskaa E., Sustainability and competitiveness of tourism, Procedia-Social and Behavioral Sciences, 2012, pp. 221-227, (2012); The definitive guide for sustainable tourism, (2019); Help us change the world At Biosphere we bet on sustainable tourism, (2019); Bowen G. A., Document analysis as a qualitative research method, Qualitative Research Journal, 9, 2, pp. 27-40, (2009); Erlingsson C., Brysiewicz P., A hands-on guide to doing content analysis, African Journal of Emergency Medicine, 7, pp. 93-99, (2017); Evans G., Parravicini P., Exploiation of ICT for Rural Tourism enterprise: the case of Aragon, Spain, Rural tourism and sustainable business, pp. 103-120, (2005); Figueiredo E., Mc Rural, No Rural or What Rural? Some refletions on rural reconfifuration processes based on the promotion of Schist Villages Network, Portugal, Shaping Rural Areas in Europe-Perceptions and Outcomes on the Present and the Future, pp. 129-146, (2013); Booking.com and Green Key start a collaboration, (2019); Unlocking sustainability in the hospitality industry, (2019); Hojeghan S. B., Esfangareh A. N., Digital economy and tourism impacts, influences and challenges, Procedia Social and Behavioral Sciences, 19, pp. 308-316, (2011); Kastenholz E., Management of demand\" as a tool in sustainable tourist destination, Journal of Sustainable Tourism, 12, 5, pp. 388-408, (2004); Kastenholz E., Turismo Rural-Reinventar para sustentar?, Reinventar o turismo rural em Portugal Cocriação de experiências turísticas sustentáveis, pp. 1-6, (2014); Kastenholz E., Eusebio C., Carneiro M. J., Segmenting the rural tourist market by sustainable travel behaviour: Insights from village visitors in Portugal, Journal of Destination Marketing & Management, 10, pp. 132-142, (2018); Keller K. L., Building strong brands in a modern marketing communications environment, Journal of marketing communications, 15, 2-3, pp. 139-155, (2009); Lane B., Sustainable rural tourism strategies: A tool for development and conservation, Journal of Sustainable Tourism, 2, 1, pp. 102-111, (1994); Mathieson A., Wall G., Tourism: economic, physical, and social impacts, (1982); Mittiga A., Silva B., Wernet F., Kow N., Kutschera S., Travel Trends Report 2019, (2018); Pato L., Dinâmicas do turismo rural-impactos em termos de Desenvolvimento Rural, (2012); Pato L., Comunicação em turismo rural e línguas estrangeiras entre o desejado e a realidade, Millenium journal of Education, Technologies, and Health, 2, 4, pp. 11-19, (2019); Pato L., A relação umbilical entre turismo rural e línguas estrangeiras, Millenium journal of Education, Technologies, and Health, 2, pp. 21-29, (2019); Pato L., Kastenholz E., Marketing of rural tourism-a study based on rural tourism lodgings in Portugal, Journal of Place Management and Development, 10, 2, pp. 121-130, (2017); Pena A. I. P., Jamilena D. M. F., The relationship between business characteristics and ICT deployment in the rural tourism sector. The case of Spain, International Journal of Tourism Research, 12, 1, pp. 34-48, (2010); Pena A. I. P., Jamilena D. M. F., Angel M., Molina R., Impact of Customer Orientation and ICT Use on the Perceived Performance of Rural Tourism Enterprises, Journal of Travel & Tourism Marketing, 30, 3, pp. 272-289, (2013); Penz E., Hofmann E., Hartl B., Fostering Sustainable Travel Behavior: Role of Sustainability Labels and Goal-Directed Behavior Regarding Touristic Services, Sustainability, 9, 6, (2017); Pesonen J., Komppula R., Rural wellbeing tourism: Motivations and expectations, Journal of Hospitality and Tourism Management, 17, pp. 150-158, (2010); Pulido-Fernandez J. I., Lopez-Sanchez Y., Are Tourists Really Willing to Pay More for Sustainable Destinations?, Sustainability, 8, 12, (2016); Romero A. B., Valiente G. C., Las tecnologías de la información y la comunicación en el desarrollo del turismo rural, Documents d’Anàlisi Geogràfica, 46, pp. 105-117, (2005); Roque V., Martins J. A., Lopes R., Análise exploratória de sítios web: o caso dos hotéis Portugueses de 4 e 5 estrelas, Inovação e Tecnologia em Turismo & Hotelaria, pp. 121-142, (2013); Sedmak G., Planinc T., Kociper T., Planinc S., Managers' perceptions of the role of ICT in rural tourism firms efficiency: The case of Slovenia, Tourism, 64, pp. 339-345, (2016); Report of the world Commission on Environment and Development \"Our Common Future\", (1987); Sustainable Development of Tourism, (2019); Yin R., Case Study Research: Design and Methods fith Editon, (2014)","L. Pato; Escola Superior Agrária de Viseu, Viseu, Quinta da Alagoa-Estrada de Nelas, Ranhados, 3500-606, Portugal; email: Pato-mljesus@esav.ipv.pt",null,"Polytechnic Institute of Viseu",{"$nulls":5},8733015.0,null,null,null,"English","Millenium","Article","Final",null,"Scopus","2-s2.0-85159151778"]
["Wang Y.; Jia F.; Schoenherr T.; Gong Y.; Chen L.","Wang, Ying (57210176338); Jia, Fu (55701204700); Schoenherr, Tobias (12752310000); Gong, Yu (57191418413); Chen, Lujie (55758032800)","57210176338; 55701204700; 12752310000; 57191418413; 55758032800","Cross-border e-commerce firms as supply chain integrators: The management of three flows",2020.0,"Industrial Marketing Management",89.0,null,null,72.0,88.0,16.0,70.0,"10.1016/j.indmarman.2019.09.004","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85072192269&doi=10.1016%2fj.indmarman.2019.09.004&partnerID=40&md5=3b79a59a2683c6356a6fde62f6389164","School of Economics and Management, Minjiang University, Fuzhou, China; The York Management School, University of York, Heslington, York, YO10 5DD, United Kingdom; Department of Supply Chain Management, Broad College of Business, Michigan State University, 632 Bogue St., Room N370, East Lansing, 48824, MI, United States; Southampton Business School, University of Southampton, Southampton, SO17 1BJ, United Kingdom; International Business School Suzhou, Xi'an Jiaotong-Liverpool University, Suzhou, China","Wang Y., School of Economics and Management, Minjiang University, Fuzhou, China; Jia F., The York Management School, University of York, Heslington, York, YO10 5DD, United Kingdom; Schoenherr T., Department of Supply Chain Management, Broad College of Business, Michigan State University, 632 Bogue St., Room N370, East Lansing, 48824, MI, United States; Gong Y., Southampton Business School, University of Southampton, Southampton, SO17 1BJ, United Kingdom; Chen L., International Business School Suzhou, Xi'an Jiaotong-Liverpool University, Suzhou, China","Cross-border e-commerce is becoming increasingly popular around the world. With the development of technology, competition has gradually shifted from commodity-based attributes, such as cost and quality, to a supply chain's service capacity for e-commerce. Within this context, the present paper delineates how cross-border e-commerce firms can generate supply chain service capabilities that yield improvements in supply chain relationship quality to e-tailors and other platform users. Insights are derived through data collected via a multiple case study approach based on four Chinese cross-border e-commerce enterprises (OSell, Zongteng, BizArk and Linca); data were collected from 41 semi-structured interviews, field visits and secondary data. Relying on the service-dominant logic as the theoretical foundation, we identify three supply chain resources (flows related to information, logistics and finance) and their interplay as being critical for the development of supply chain service capabilities, which in turn lead to an improvement in the quality of supply chain relationships (assessed by the dimensions of trust improvement/commitment, risk mitigation, and customer satisfaction). The results offer important insights into how to best manage supply chain resources in relation to the three flows by cross-border e-commerce firms in order to foster relationship quality, an attribute that has become so critical today for competitive differentiation. © 2019","Case studies; Cross-border e-commerce; Service supply chains; Service-dominant logic",{"$nulls":5},"National Social Science Foundation Project, (15CJY010)","This research was funded by National Social Science Foundation Project , grant number 15CJY010 .  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Wells J.R., Danskin D., Ellsworth G., Amazon.com, 2018, Harvard Business School Case, (2018); Xie K., Wu Y., Xiao J., Hu Q., Value co-creation between firms and customers: The role of big data-based cooperative assets, Information & Management, 53, 8, pp. 1034-1048, (2016); Xinhuanet, Cross-border E-commerce to boost Chinese foreign trade, (2016); Yin R., Case study research, (2013); Zeng A.Z., Rossetti C., Developing a framework for evaluating the logistics costs in global sourcing processes: An implementation and insights, International Journal of Physical Distribution & Logistics Management, 33, 9, pp. 785-803, (2003); Zhang X., Chen R., Examining the mechanism of the value co-creation with customers, International Journal of Production Economics, 116, 2, pp. 242-250, (2008)","L. Chen; International Business School Suzhou, Xi'an Jiaotong-Liverpool University, Suzhou, China; email: Lujie.Chen@xjtlu.edu.cn",null,"Elsevier Inc.",{"$nulls":5},198501.0,null,"IMMAD",null,"English","Ind. Mark. Manage.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85072192269"]
["Ge X.; Zhu Z.; Jin Y.","Ge, Xianlong (55647754300); Zhu, Ziqiang (57219284819); Jin, Yuanzhi (57219283180)","55647754300; 57219284819; 57219283180","Electric Vehicle Routing Problems with Stochastic Demands and Dynamic Remedial Measures",2020.0,"Mathematical Problems in Engineering",2020.0,null,8795284.0,null,null,null,10.0,"10.1155/2020/8795284","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85092043765&doi=10.1155%2f2020%2f8795284&partnerID=40&md5=4eecfa6224658b1ce71b636c8c5c7c4d","School of Economics and Management, Chongqing Jiaotong University, Chongqing, 400074, China; Key Laboratory of Intelligent Logistics Network, Chongqing Jiaotong University, Chongqing, 400074, China; Department of Computer Technology and Information Engineering, Sanmenxia Polytechnic, Sanmenxia, 472000, China","Ge X., School of Economics and Management, Chongqing Jiaotong University, Chongqing, 400074, China, Key Laboratory of Intelligent Logistics Network, Chongqing Jiaotong University, Chongqing, 400074, China; Zhu Z., School of Economics and Management, Chongqing Jiaotong University, Chongqing, 400074, China; Jin Y., School of Economics and Management, Chongqing Jiaotong University, Chongqing, 400074, China, Department of Computer Technology and Information Engineering, Sanmenxia Polytechnic, Sanmenxia, 472000, China","With the rapid development of e-commerce, logistic enterprises must better predict customer demand to improve distribution efficiency, so as to deliver goods in advance, which makes logistics stochastic and dynamic. In order to deal with this challenge and respond to the concept of \"green logistics,\"an electric vehicle routing problem with stochastic demands (EVRPSD) and proactive remedial measures is investigated, and an EVRPSD model with probability constraints is established. At the same time, a hybrid heuristic algorithm, combining a saving method and an improved Tabu search algorithm, is proposed to solve the model. Moreover, two insertion strategies with the greedy algorithm for charging stations and dynamic nodes are introduced. Finally, a large number of experimental data show that the heuristic algorithm proposed in this paper is feasible and effective. © 2020 Xianlong Ge et al.",null,"Distribution of goods; Heuristic algorithms; Heuristic methods; Stochastic models; Tabu search; Vehicle routing; Customer demands; Distribution efficiency; Greedy algorithms; Hybrid heuristic algorithms; Improved Tabu search algorithm; Probability constraints; Remedial measures; Stochastic demand; Stochastic systems",{"$nulls":6},"Stewart W.R., Golden B.L., Stochastic vehicle routing: a comprehensive approach, European Journal of Operational Research, 14, 4, pp. 371-385, (1983); Psaraftis H.N., A dynamic programming solution to the single vehicle many-to-many immediate request dial-a-ride problem, Transportation Science, 14, 2, pp. 130-154, (1980); Goncalves F., Cardoso S.R., Relvas S., Optimization of a distribution network using electric vehicles, pp. 18-20; Dror M., Laporte G., Trudeau P., Vehicle routing with stochastic demands: properties and solution frameworks, Transportation Science, 23, 3, pp. 166-176, (1989); Gauvin C., Desaulniers G., Gendreau M., A branch-cut-and-price algorithm for the vehicle routing problem with stochastic demands, Computers & Operations Research, 50, pp. 141-153, (2014); Gendreau M., Laporte G., Seguin R., An exact algorithm for the vehicle routing problem with stochastic demands and customers, Transportation Science, 29, 2, pp. 143-155, (1995); Lei H., Laporte G., Guo B., The capacitated Vehicle routing problem with stochastic demands and time windows, Computers & Operations Research, 38, 12, pp. 1775-1783, (2011); Bertazzi L., Secomandi N., Faster rollout search for the vehicle routing problem with stochastic demands and restocking, European Journal of Operational Research, 270, 2, pp. 487-497, (2018); Qureshi A.G., Taniguchi E., Yamada T., A microsimulation based analysis of exact solution of dynamic vehicle routing with soft time windows, Procedia-Social and Behavioral Sciences, 39, pp. 205-216, (2012); Abdallah A.M.F.M., Essam D.L., Sarker R.A., On solving periodic re-optimization dynamic vehicle routing problems, Applied Soft Computing, 55, pp. 1-12, (2017); Kuo R.J., Wibowo B.S., Zulvia F.E., Application of a fuzzy ant colony system to solve the dynamic vehicle routing problem with uncertain service time, Applied Mathematical Modelling, 40, 23-24, pp. 9990-10001, (2016); Ge X., Wang X., Deng L., Research on open and dynamic vehicle routing problems based on joint distribution, Journal of Industrial Engineering and Engineering Management, 27, 3, pp. 60-68, (2013); Okulewicz M., Mandziuk J., The impact of particular components of the PSO-based algorithm solving the dynamic vehicle routing problem, Applied Soft Computing, 58, pp. 586-604, (2017); Ghannadpour S.F., Noori S., Tavakkoli-Moghaddam R., Ghoseiri K., A multi-objective dynamic vehicle routing problem with fuzzy time windows: model, solution and application, Applied Soft Computing, 14, pp. 504-527, (2014); Ge X., Xue G., Wen P., Proactive two-level dynamic distribution routing optimization based on historical data, Mathematical Problems in Engineering, 2018, (2018); Conrad R.G., Figliozzi M.A., The recharging vehicle routing problem, pp. 21-25; Erdogan S., Miller-Hooks E., A green vehicle routing problem, Transportation Research Part E: Logistics and Transportation Review, 48, 1, pp. 100-114, (2012); Schneider M., Stenger A., Goeke D., The electric vehicle-routing problem with time windows and recharging stations, Transportation Science, 48, 4, pp. 500-520, (2014); Lin J., Zhou W., Wolfson O., Electric vehicle routing problem, Transportation Research Procedia, 12, pp. 508-521, (2016); Alejandro M., Christelle G., The electric vehicle routing problem with nonlinear charging function, Transportation Research Part B, 103, pp. 87-110, (2017); Goeke D., Schneider M., Routing a mixed fleet of electric and conventional vehicles, European Journal of Operational Research, 245, 1, pp. 81-99, (2015); Yang J., Sun H., Battery swap station location-routing problem with capacitated electric vehicles, Computers & Operations Research, 55, pp. 217-232, (2015); Hof J., Schneider M., Goeke D., Solving the battery swap station location-routing problem with capacitated electric vehicles using an AVNS algorithm for vehicle-routing problems with intermediate stops, Transportation Research Part B: Methodological, 97, pp. 102-112, (2017); Shao S., Guan W., Ran B., Electric vehicle routing problem with charging time and variable travel time, Mathematical Problems in Engineering, 2017, (2017); Su J., Yu Y., Zhang X., Knowledge transfer efficiency measurement with applications for open innovation networks, International Journal of Technology Management, 81, 1, pp. 118-142, (2019); Wang W., Ge X., Li L., Su J., Proactive and reactive multi-project scheduling in uncertain environment, IEEE Access, 7, pp. 88986-88997, (2019); Ge X., Ge X.B., Wang W., A path-based selection solution approach for the low carbon vehicle routing problem with a time-window constraint, Applied Science, 10, 4, (2020)","X. Ge; School of Economics and Management, Chongqing Jiaotong University, Chongqing, 400074, China; email: gexianlong@cqjtu.edu.cn",null,"Hindawi Limited",{"$nulls":5},"1024123X",null,null,null,"English","Math. Probl. Eng.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85092043765"]
["Li J.; Lee S.-C.; Jeong H.-E.","Li, Jian (57201395037); Lee, Sang-Chun (57221441906); Jeong, Ha-Eun (57221438191)","57201395037; 57221441906; 57221438191","Research on the relationship between social capital and enterprise performance in supply chain environment",2020.0,"Journal of Korea Trade",24.0,4.0,null,34.0,48.0,14.0,3.0,"10.35611/jkt.2020.24.4.34","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85099151199&doi=10.35611%2fjkt.2020.24.4.34&partnerID=40&md5=901b60b8f4537fee7def79c1b97ba16c","Department of Logistics, Yancheng Teachers University, China; Department of International Trade, Jungwon University, South Korea; Department of Trade, Halla University, South Korea","Li J., Department of Logistics, Yancheng Teachers University, China; Lee S.-C., Department of International Trade, Jungwon University, South Korea; Jeong H.-E., Department of Trade, Halla University, South Korea","Purpose - The rapid rise of e-commerce enterprises has led to the development of the logistics industry. At the same time, some enterprises are motivated by the interests to start reducing costs and inputs, which on the contrary leads to low quality of service, thus reducing customer satisfaction. In recent years, vicious competition, violent express delivery and lack of professionalism in the logistics market have led to high annual customer complaint rate, which has resulted in the company losing many loyal customers, but also unable to obtain new customers. Therefore, to pay attention to and understand the psychological needs of customers and improve the quality of logistics distribution service has become a pressing problem for Every express company. Design/methodology - By analyzing the problems existing in logistics distribution of express companies, this paper explores various factors affecting customer satisfaction and takes consumer sentiment as a mediating variable. Through questionnaires to collect relevant data, put forward hypotheses for empirical analysis, use two different software including SPSS 21.0 and AMOS 21.0 to analyze the information, draw conclusions and make recommendations. Findings - According to the above research results, the reliability, convenience, efficiency, professional can have a positive impact on customer satisfaction through the mediating effect of their sentiment, convenience and professional on consumer sentiment and satisfaction are more significant. Originality/value - This paper the establishment of distribution service indicators related to customer satisfaction and empirical analysis can not only enrich and supplement the distribution service quality indicator system studied by the former, but also provide a theoretical basis for future research. © 2020 Korea Trade Research Association.","Consumer response; Customer satisfaction; Questionnaire; Spss21.0 & amos21.0",{"$nulls":5},"Jiangsu University, JSU, (2019SJA1731)","This work was supported by the Jiangsu University Philosophy and Social Science Research Fund Project of 2019. Project No. 2019SJA1731.","Bao F. N., How does Relational Social Capital Affect Enterprise Innovation Performancea path Analysis Based on Knowledge Transfer, Enterprise Economy, 40, 1, pp. 129-135, (2020); Barratt M, Oke A., Antecedents of Supply Chain Visibility in Retail Supply Chains: A Resource-Based Theory Perspective, Journal of Operations Management, 25, 6, pp. 1217-1233, (2007); Bian Y., Qiu H., Social Capital and Efficiency of Enterprises, Chinese Social Sciences, 41, 2, pp. 87-99, (2000); Bo Q. W., Social Capital, Corporate Governance and Corporate Performance, Social Science Front, 43, 11, pp. 78-90, (2018); Burt V., Norms and Networks in Economic and Organizational Performance, American Economic Review, 88, 2, pp. 85-89, (1998); Brent L. J. N., Heilbronner S. R., Horvath J. E., Martinez J. G., Lambides A. R., Robinson A., Et al., Genetic Origins of Social Networks in Rhesus Macaques: Supplementary Information, Scientific Reports, 3, 1042, pp. 1-8, (2013); Garcia-Villaverde P. M, Rodrigo F. M. J., Ortega M. J. R., Requena G. F., The Role of Knowledge Absorptive Capacity on the Relationship Between Cognitive Social Capital and Entrepreneurial Orientation, Journal of Knowledge Management, 22, 5, pp. 1015-1036, (2018); Gligor D. M., Holcomb M. C., Antecedents and Consequences of Supply Chain Agility: Establishing the Link to Firm Performance, Journal of Business Logistics, 33, 4, pp. 295-308, (2012); Han C., Research on the Impact of Green Supply Chain Management on Enterprise Performance from the Perspective of Social Capital, (2015); Kolekofski K. E., Heminger A. R., Beliefs and Attitudes Affecting Intentions to Share Information in an Organizational Setting, Information & Management, 40, 6, pp. 521-532, (2003); Liu J., The Establishment of Agile Supply Chain Performance Evaluation System, Modern Management Science, 39, 6, pp. 79-82, (2006); Lucy K. W., The Influence of Structural Social Capital on Performance of Social Enterprises in Nairobi City County, Kenya, European Journal of Business and Management, 11, 7, pp. 131-139, (2019); Lummus R. R., Vokurka R. J., Duclos L. K., Delphi Study on Supply Chain Flexibility, International Journal of Production Research, 43, 13, pp. 2687-2708, (2005); Mai S., Zheng J., Corporate Social Responsibility and Corporate Social Capital, Friends of Accounting, 38, 2, pp. 13-19, (2020); Nahapiuet J., Ghoshal S., Social Capital, Intellectual Capital, and the Organizational Advantage, Academy of Management Review, 23, 2, pp. 242-266, (1998); Peng S., Huang J., Sheehy J. E., Laza R. C., Visperas R. M., Zhong X., Et al., Rice Yields Decline with Higher Night Temperature from Global Warming, Research Article, 101, 27, pp. 9971-9975, (2004); Smaros J., Lehtonen J. M., Appelqvist P., Holmstrom J., The Impact of Increasing Demand Visibility on Production and Inventory Control Efficiency, International Journal of Physical Distribution & Logistics Management, 33, 4, pp. 336-354, (2003); White A., Daniel E. M., Nohdzain M., The Role of Emergent Information Technologies and Systems in Enabling Supply Chain Agility, International Journal of Information Management, 25, 5, pp. 396-410, (2005); Xavier B., Does Supply Chain Visibility Enhance Agility?, International Journal of Production Economics, 171, 1, pp. 46-59, (2016); Yang Y., Tian Y., Research on the Influence of Supply Chain Management Practice and Supply Chain Agility on Enterprise Performance, Business Economics and Management, 40, pp. 13-96, (2015); Zeng Y., Zhang J., Social Capital and Accounting Earnings Quality, Economic Science, 3, pp. 93-104, (2011)","S.-C. Lee; Department of International Trade, Jungwon University, South Korea; email: sclee@jwu.ac.kr",null,"Korea Trade Research Association",{"$nulls":5},"1229828X",null,null,null,"English","J. Korea Trade","Article","Final",null,"Scopus","2-s2.0-85099151199"]
["Zhou Q.; Zhang Z.; Wang Y.","Zhou, Qingyuan (57109587900); Zhang, Zongming (57192943558); Wang, Yuancong (57211449405)","57109587900; 57192943558; 57211449405","Research on safety management system optimization of B2C e-commerce intelligent logistics information system based on data cube",2020.0,"Journal of Intelligent and Fuzzy Systems",38.0,2.0,null,1582.0,1592.0,10.0,15.0,"10.3233/JIFS-179522","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85084634920&doi=10.3233%2fJIFS-179522&partnerID=40&md5=b4ad1bcfd74a3e5e7a125c1ef64a0609","School of Economics and Management, Changzhou Vocational Institute of Mechatronic Technology, China; School of Economics and Management, Xidian University, Xi'an, China; Naveen Jindal School of Management, University of Texas at Dallas, Richardson, TX, United States; School of Public Administration, Sichuan University, Chengdu, China","Zhou Q., School of Economics and Management, Changzhou Vocational Institute of Mechatronic Technology, China; Zhang Z., School of Economics and Management, Xidian University, Xi'an, China, Naveen Jindal School of Management, University of Texas at Dallas, Richardson, TX, United States; Wang Y., School of Public Administration, Sichuan University, Chengdu, China","With the rapid popularization and rapid development of the Internet in the world, e-commerce has gradually become the mainstream trade mode. E-commerce has its own unique trading mode and brand-new global business opportunities. More and more people conduct online transactions through the Internet. According to the characteristics of data in B2C e-commerce system, data mining management module is designed in B2C e-commerce management system. Data mining technology is used to preprocess data, data mining and mining results. It is implemented using J2EE's B/S architecture. With the continuous growth of B2C e-commerce scale, logistics bottlenecks have become increasingly prominent, and e-commerce distribution model based on cloud logistics integrates IT information technology with traditional logistics information systems. Integrate logistics service demand and logistics distribution capabilities, and provide corresponding cloud logistics information and management platform system. It will help solve the problem of logistics and distribution of B2C e-commerce in China and promote the healthy and rapid development of e-commerce economy. © 2020 - IOS Press and the authors. All rights reserved","B2C E-Commerce; Data Cube; Intelligent Logistics","Data mining; Electronic commerce; Information systems; Information use; Management information systems; Data mining technology; Distribution models; Logistics distribution; Logistics information; Logistics information systems; Management platforms; Mining managements; Safety management systems; Information management",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (71502132); Ministry of Education of the People's Republic of China, MOE, (16JZDW019); Qinglan Project of Jiangsu Province of China","The authors acknowledge the financial support of the National Natural Science Foundation of China (71502132), Major Projects of the Ministry of Education of China (16JZDW019), and Qing Lan Project.","Zhao H., Morad B., From e-commerce to social commerce: A close look at design features, Electronic Commerce Research and Applications, 12, 4, pp. 246-259, (2013); Ziping W., Dong-Qing Y., Peiqing H., A new location-inventory policy with reverse logistics applied to B2C e-markets of China, International Journal of Production Economics, 107, 2, pp. 350-363, (2007); Chao-Min C., Wang Eric T.G., Yu-Hui F., Hsin-Yi H., Understanding customers' repeat purchase intentions in B2C e-commerce: The roles of utilitarian value, hedonic value and perceived risk, Information Systems Journal, 24, 1, pp. 85-114, (2014); Ling J., Minjoon J., Zhilin Y., Customer-perceived value and loyalty: How do key service quality dimensions matter in the context of B2C e-commerce?, Service Business, 10, 2, pp. 301-317, (2016); Bahador S., Rafsanjani M.K., A fuzzy system approach to multilateral automated negotiation in B2C e-commerce, Neural Computing and Applications, 25, 2, pp. 367-377, (2014); Soohyung K., Hyukki L., Dohn C.Y., Privacy-preserving data cube for electronic medical records: An experimental evaluation, International Journal of Medical Informatics, 97, pp. 33-42, (2017); Marek L., Cost effective storage space for data cubes, Journal of Intelligent Information Systems, 48, 2, pp. 243-261, (2017); Jinlou X., Jianjian L., Qingyuan Z., Data mining based quality analysis on informants involved applied research, Cluster Computing, 19, 4, pp. 1885-1893, (2016); Chinyao L., Yahsueh C., Mingchang W., Understanding the determinants of cloud computing adoption, Industrial Management & Data Systems, 111, 7, pp. 1006-1023, (2011); Hartono E., Holsapple C.W., Kim K.-Y., Na K.-S., Simpson J.T., Measuring perceived security in B2C electronic commerce website usage: A respecification and validation, Decision Support Systems, 62, pp. 11-21, (2014); Qingyuan Z., Jianjian L., The risk management using limit theory of statistics on extremes on the big data era, Journal of Computational and Theoretical Nanoscience, 12, 12, pp. 6237-6243, (2015); Qingyuan Z., Jianjian L., Artificial neural network based grid computing of E-government scheduling for emergency management, Computer Systems Science and Engineering, 30, 5, pp. 335-343, (2015); Karimov F.P., Brengman M., An examination of trust assurances adopted by top internet retailers: Unveiling some critical determinants, Electronic Commerce Research, 14, 4, pp. 459-496, (2014); Campbell D.E., Wells J.D., Valacich J.S., Breaking the ice in B2C relationships: Understanding pre-adoption e-commerce attraction, Information Systems Research, 24, 2, pp. 219-238, (2013); Wenming Z., Qiuping H., Chang F., Zhenpeng Z., Quality management of B2C e-commerce service based on human factors engineering, Electronic Commerce Research and Applications, 12, 5, pp. 309-320, (2013); Domenico R., Sarne G.M.L., Multi-agent technology and ontologies to support personalization in B2C E-Commerce, Electronic Commerce Research and Applications, 13, 1, pp. 13-23, (2014); Huang E.Y., Chia-Jung T., Assessing customer retention in B2C electronic commerce: An empirical study, Journal of Marketing Analytics, 4, 4, pp. 172-185, (2016); Kaplan S.E., Nieschwietz R.J., A Web assurance services model of trust for B2C e-commerce, International Journal of Accounting Information Systems, 4, 2, pp. 95-114, (2003); Mengxun H., Chunying R., Haijun Z., Intent-based recommendation for B2C e-commerce platforms, IBM Journal of Research and Development, 58, 5-6, pp. 51-510, (2014); Petra S., Ginsburg M., Virtual communities of transaction: The role of personalization in electronic commerce, Electronic Markets, 10, 1, pp. 45-55, (2000); Qingyuan Z., Research on heterogeneous data integration model of group enterprise based on cluster computing, Cluster Computing, 19, 3, pp. 1275-1282, (2016); Deng X., Jian Z., Differentiating the effects of Internet usage and wireless usage on business-to-business and business-to-consumer e-commerce, Journal of Internet Commerce, 13, 2, pp. 138-157, (2014); Bahador S., Rafsanjani M.K., A multi-agent based model for collective purchasing in electronic commerce, International Journal of Machine Learning and Cybernetics, 4, 4, pp. 409-417, (2013); Libu P.D., Bahari M., Noorminshah A., IAHAD, exploring implementation factors influencing business-to-customer (B2C) e-commerce, Advanced Science Letters, 21, 5, pp. 1455-1459, (2015); Zhou Q., Jianjian L., The study on evaluation method of urban network security in the big data era, Intelligent Automation & Soft Computing, 24, 1, pp. 133-138, (2018); Zhou Q., Ranran L., Strategy optimization of resource scheduling based on cluster rendering, Cluster Computing, 19, 4, pp. 2109-2117, (2016); Xiao-Nan Z., Hou-Ming F., Jian-Feng L.I., Bi-objective fuzzy location model and algorithm for the designoflogisticsdistributionnetworkinB2Ce-commerce, Systems Engineering-Theory & Practice, 35, 5, pp. 1202-1213, (2015); Qingyuan Z., Multi-layer affective computing model based on emotional psychology, Electronic Commerce Research, 18, 1, pp. 109-124, (2018); Geok P.L., Customer co-creation in B2C e-commerce: Does it lead to better new products?, Electronic Commerce Research, 16, 2, pp. 217-243, (2016)","Y. Wang; School of Public Administration, Sichuan University, Chengdu, 610065, China; email: zgsccd@scu.edu.cn",null,"IOS Press",{"$nulls":5},1.0641246E7,null,null,null,"English","J. Intelligent Fuzzy Syst.","Article","Final",null,"Scopus","2-s2.0-85084634920"]
["Wang X.; Zhang J.","Wang, Xue (58854649700); Zhang, Jun (55266463100)","58854649700; 55266463100","Factors Influencing Chinese Online Shopping Distributions of Fresh Agricultural Products",2020.0,"Journal of Distribution Science",18.0,10.0,null,53.0,64.0,11.0,8.0,"10.15722/jds.18.10.202010.53","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85102281718&doi=10.15722%2fjds.18.10.202010.53&partnerID=40&md5=35f71fba0b5e81f6a2a6a5c5c019aa25","Institution of Hangzhou Kaiyi Cultural Media, Hangzhou, China; Department of Global Business, Konkuk University, Seoul, South Korea","Wang X., Institution of Hangzhou Kaiyi Cultural Media, Hangzhou, China; Zhang J., Department of Global Business, Konkuk University, Seoul, South Korea","Purpose: With the emergence of high technology in China, online shopping distribution of fresh agricultural products have been developing rapidly. This study built a model to investigate how perceived quality of products and logistic services, perceived risk, and perceived cost affect intention to buy fresh agricultural products in an Internet environment. Especially, in the purchasing process, attitude may work as an important mediator. Research design, data and methodology: To achieve the objectives of this study, Chinese respondents were asked to fill in a questionnaire through the China online survey website. With 520 available data, regression analysis was used to test the hypotheses. Results: Results indicate that perceived quality of fresh agriculture products and perceived logistics service quality have a significant positive impact on attitude and purchase intention. Results also reveal that perceived risk and perceived cost affect attitude and purchase intention negatively. Finally, results imply that attitude has a positive effect on purchase intention, which is the unique mediator in the online shopping process. Conclusions: This study suggests that managers in the online shopping distributions of fresh agricultural products should improve the quality of products and logistics services along with the reduction of the perceived risk and cost to compete in the China market. ©Copyright: The Author(s) This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://Creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original work is properly cited.","Attitude; Perceived Cost; Perceived Quality; Perceived Risk; Purchase Intention",{"$nulls":7},"Abdul-Muhmin A. G., Repeat purchase intentions in online shopping: The role of satisfaction, attitude, and online retailers’ performance, Journal of International Consumer Marketing, 23, 1, pp. 5-20, (2010); Ahumada O., Villalobos J. R., Mason A. 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How website quality influences perceptions of product quality and purchase intentions, MIS Quarterly, 35, 2, pp. 373-396, (2011); Widodo K. H., Nagasawa H., Morizawa K., Ota M., A periodical flowering-harvesting model for delivering agricultural fresh products, European Journal of Operational Research, 170, 1, pp. 24-43, (2006); Won J., Kim B-Y., The effect of consumer motivations on purchase intention of online fashion-sharing platform, Journal of Asian Finance, Economics and Business, 7, 6, pp. 197-207, (2020); Wu L. Y., Chen K. Y., Chen P. Y., Cheng S. L., Perceived value, transaction cost, and repurchase-intention in online shopping: A relational exchange perspective, Journal of Business Research, 67, 1, pp. 2768-2776, (2014); Wu S. I., The relationship between consumer characteristics and attitude toward online shopping, Marketing Intelligence & Planning, 21, 1, pp. 37-44, (2003); Yan B., Chen X., Cai C., Guan S., Supply chain coordination of fresh agricultural products based on consumer behavior, Computers and Operation Research, 123, pp. 1-9, (2020); Zeithaml V. A., Consumer perceptions of price, quality, and value: A means-end model and synthesis of evidence, Journal of marketing, 52, 3, pp. 2-22, (1988); Zeithaml V. A., Berry L. L., Parasuraman A., The behavioral consequences of service quality, Journal of Marketing, 60, 2, pp. 31-46, (1996); Zeithaml V. A., Parasuraman A., Malhotra A., Service quality delivery through web sites: A critical review of extant knowledge, Journal of the Academy of Marketing Science, 30, 4, pp. 362-375, (2002)","X. Wang; Institution of Hangzhou Kaiyi Cultural Media, Hangzhou, China; email: wangxue9347@gmail.com; J. Zhang; Department of Global Business, Konkuk University, Seoul, South Korea; email: zhangjun@konkuk.ac.kr",null,"Korea Distribution Science Association (KODISA)",{"$nulls":5},1.738311E7,null,null,null,"English","J. Distribution Science","Article","Final",null,"Scopus","2-s2.0-85102281718"]
["Zhang H.; He J.; Shi X.; Hong Q.; Bao J.; Xue S.","Zhang, Hao (56926294900); He, Jie (54930944100); Shi, Xiaomeng (56505911200); Hong, Qiong (54405365600); Bao, Jie (36197972400); Xue, Shuqi (57190493293)","56926294900; 54930944100; 56505911200; 54405365600; 36197972400; 57190493293","Technology characteristics, stakeholder pressure, social influence, and green innovation: Empirical evidence from chinese express companies",2020.0,"Sustainability (Switzerland)",12.0,7.0,2891.0,null,null,null,25.0,"10.3390/su12072891","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85083573354&doi=10.3390%2fsu12072891&partnerID=40&md5=b1527687ce85b8f11896ce9879fcbab2","Jiangsu Key Laboratory of Urban ITS, Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, School of Transportation, Southeast University, Nanjing, 211189, China; School of Traffic Engineering, Huaiyin Institute of Technology, Huaian, 223003, China; Business School, Huaian Vocational College of Information Technology, Huaian, 223003, China; Civil Aviation College, Nanjing University of Aeronautics and Astronautics, Nanjing, 211106, China; School of Modern Posts, Xi'an University of Posts and Telecommunications, Xi'an, 710061, China","Zhang H., Jiangsu Key Laboratory of Urban ITS, Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, School of Transportation, Southeast University, Nanjing, 211189, China, School of Traffic Engineering, Huaiyin Institute of Technology, Huaian, 223003, China; He J., Jiangsu Key Laboratory of Urban ITS, Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, School of Transportation, Southeast University, Nanjing, 211189, China; Shi X., Jiangsu Key Laboratory of Urban ITS, Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, School of Transportation, Southeast University, Nanjing, 211189, China; Hong Q., Business School, Huaian Vocational College of Information Technology, Huaian, 223003, China; Bao J., Civil Aviation College, Nanjing University of Aeronautics and Astronautics, Nanjing, 211106, China; Xue S., School of Modern Posts, Xi'an University of Posts and Telecommunications, Xi'an, 710061, China","Over the past decade, the rapid development of e-commerce and express industries in China has resulted in huge environmental costs. Compared with manufacturing industries, the values of green innovation are less recognized in logistics industries. To promote the green practices in logistic enterprises, it is imperative to have a thorough understanding of the determinants of green innovation adoption. To this end, this paper performs an empirical investigation into the intentions to adopt green innovation from 196 Chinese express companies. The determinant variables were constructed from the perspective of technology characteristics (perceived green usefulness and perceived integration ease of use), stakeholder pressure (government, customer, and platform pressures), and social influence. Then, a 20-item scale was designed based on the literature review and expert opinions. The results revealed the significant positive effects of technology characteristics and social influence on the intentions to adopt green innovation. Meanwhile, only the platform pressure was significant with the adopting intentions among the variables from stakeholder pressure. Moreover, variables from technology characteristics were found to have meditation effects between social influence and adopting intentions. Based on the findings, theoretical and practical implications are proposed to promote the green and sustainable development of express companies in China. © 2020 by the authors.","E-commerce; Express companies; Green innovation; Technology adoption","China; cost analysis; empirical analysis; green economy; industrial enterprise; innovation; manufacturing; perception; stakeholder; sustainable development",{"$nulls":4},"Green and Blue Project\" fund of Jiangsu Province; Green and Blue Project” fund of Jiangsu Province, (2017SJB1641); Huaian Vocational College of Information Technology, (HXYC2017003); Natural Science Fund for Colleges in Jiangsu Province, (17KJB58001); Philosophy and Social Science fund for colleges in Jiangsu Province, (2018SJA1649); Six Industry Talent Peak Project\" fund of Jiangsu Province; Six Industry Talent Peak Project” fund of Jiangsu Province, (JNHB-115, RJFW-049); National Natural Science Foundation of China, NSFC, (51778141, 71874067); Humanities and Social Science Fund of Ministry of Education of China, (19YJA790070)","Funding text 1: Funding: This research is supported by the National Natural Science Foundation of China (71874067 & 51778141), the “Six Industry Talent Peak Project” fund of Jiangsu Province (RJFW-049 & JNHB-115), the “Green and Blue Project” fund of Jiangsu Province (2017SJB1641), the Philosophy and Social Science fund for colleges in Jiangsu Province (2017SJB1641 & 2018SJA1649), the Natural Science Fund for Colleges in Jiangsu Province (17KJB58001), the fund of Huaian Vocational College of Information Technology (HXYC2017003), and the Ministry of education of Humanities and Social Science Project (19YJA790070).; Funding text 2: This research is supported by the National Natural Science Foundation of China (71874067 & 51778141), the \"Six Industry Talent Peak Project\" fund of Jiangsu Province (RJFW-049 & JNHB-115), the \"Green and Blue Project\" fund of Jiangsu Province (2017SJB1641), the Philosophy and Social Science fund for colleges in Jiangsu Province (2017SJB1641 & 2018SJA1649), the Natural Science Fund for Colleges in Jiangsu Province (17KJB58001), the fund of Huaian Vocational College of Information Technology (HXYC2017003), and the Ministry of education of Humanities and Social Science Project (19YJA790070). The authors would like to thank the government agencies and logistic enterprises for their assistance and engagement in the survey.",{"$cut":{"chars":17547,"head":"Bernauer T., Stephanie Engels D., Seijas K., Seijas J., Explaining Green Innovation-Ten Years after Porter's Win-Win Proposition: How to Study the Effects of Regulation on Corporate Environmental Innovation, Politische Vierteljahresschrift, 39, pp. 323-341, (2007); Chiou T.-Y., Chan H.K., Lettice F., Chung S.H., The influence of greening the suppliers and green innovation on environmental performance and competitive advantage in Taiwan, Transp. Res. Part E Logist. Transp. Rev, 47, pp. 822-836, (2011); Yin J., Gong L., Wang S., Large-scale assessment of global green innovation research trends from 1981 to 2016: A bibliometric study, J. Clean. Prod, 197, pp. 827-841, (2018); Rossi S., Colicchia C., Cozzolino A., Christopher M., The logistics service providers in eco-effciency innovation: An empirical study, Supply Chain Manag. Int. J, 18, pp. 583-603, (2013); Huang X., Hu Z., Liu C., Yu D., Yu L., The relationships between regulatory and customer pressure, green organizational responses, and green innovation performance, J. Clean. Prod, 112, pp. 3423-3433, (2016); Du K., Li J., Towards a green world: How do green technology innovations affect total-factor carbon productivity, Energy Policy, 131, pp. 240-250, (2019); Abdullah M., Zailani S., Iranmanesh M., Jayaraman K., Barriers to green innovation initiatives among manufacturers: The Malaysian case, Rev. Manag. Sci, 10, pp. 683-709, (2016); Baldwin J., Lin Z., Impediments to advanced technology adoption for Canadian manufacturers, Res. Policy, 31, pp. 1-18, (2002); Kammerer D., The effects of customer benefit and regulation on environmental product innovation, Empirical evidence from appliance manufacturers in Germany. Ecol. Econ, 68, pp. 2285-2295, (2009); Wong S.K.S., Environmental requirements, knowledge sharing and green innovation: Empirical evidence from the electronics industry in China, Bus. Strategy Environ, 22, pp. 321-338, (2013); Chou C.J., Chen K.S., Wang Y.Y., Green practices in the restaurant industry from an innovation adoption perspective: Evidence from Taiwan, Int. J. Hosp. Manag, 31, pp. 703-711, (2012); Dai Y., Gao H.O., Energy consumption in China's logistics industry: A decomposition analysis using the LMDI approach, Transp. Res. Part D Transp. Environ, 46, pp. 69-80, (2016); Solis J.C., Sheinbaum C., Energy consumption and greenhouse gas emission trends in Mexican road transport, Energy Sustain. Dev, 17, pp. 280-287, (2013); Bastani P., Heywood J.B., Hope C., The effect of uncertainty on US transport-related GHG emissions and fuel consumption out to 2050, Transp. Res. Part A Policy Pract, 46, pp. 517-548, (2012); Bueno G., Analysis of scenarios for the reduction of energy consumption and GHG emissions in transport in the Basque Country, Renew. Sustain. Energy Rev, 16, pp. 1988-1998, (2012); He M., Shen J., Wu X., Luo J., Logistics Space: A Literature Review from the Sustainability Perspective, Sustainability, 10, (2018); SPBPRC State Post Bureau of the People's Republic of China, (2020); Giuliano G., O'Brien T., Dablanc L., Holliday K., Synthesis of Freight Research in Urban Transportation Planning, (2013); Yuan Q., Planning Matters: Institutional Perspectives on Warehousing Development and Mitigating Its Negative Impacts, J. Am. Plan. Assoc, 85, pp. 525-543, (2019); Zhang N., Wei X., Dynamic total factor carbon emissions performance changes in the Chinese transportation industry, Appl. Energy, 146, pp. 409-420, (2015); Baumgartner M., Leonardi J., Krusch O., Improving computerized routing and scheduling and vehicle telematics: A qualitative survey, Transp. Res. Part D Transp. Environ, 13, pp. 377-382, (2008); Roumboutsos A., Kapros S., Vanelslander T., Green city logistics: Systems of Innovation to assess the potential of E-vehicles, Res. Transp. Bus. Manag, 11, pp. 43-52, (2014); Zailani S., Iranmanesh M., Nikbin D., Jumadi H.B., Determinants and environmental outcome of green technology innovation adoption in the transportation industry in Malaysia, Asian J. Technol. Innov, 22, pp. 286-301, (2014); Zhu Q., Dou Y., Sarkis J., A portfolio-based anal"}},"J. He; Jiangsu Key Laboratory of Urban ITS, Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, School of Transportation, Southeast University, Nanjing, 211189, China; email: hejie@seu.edu.cn",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85083573354"]
["Liu Q.","Liu, Q. (57198642953)",5.7198642953E10,"Automated logistics management and distribution based on RFID positioning technology",2020.0,"Telecommunications and Radio Engineering (English translation of Elektrosvyaz and Radiotekhnika)",79.0,1.0,null,17.0,27.0,10.0,9.0,"10.1615/telecomradeng.v79.i1.20","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85081050234&doi=10.1615%2ftelecomradeng.v79.i1.20&partnerID=40&md5=1a30475604ad940690482589452613db","Zhengzhou Vocational College of Finance and Taxation, 18 Zhengwei Road, Zhengzhou, Henan, 450048, China","Liu Q., Zhengzhou Vocational College of Finance and Taxation, 18 Zhengwei Road, Zhengzhou, Henan, 450048, China","With the development of Internet technology, online shopping has gradually emerged. For logistics companies, the efficiency of the traditional warehouse management model has been difficult to meet the growing needs for logistics. In order to improve the efficiency of management, radio frequency identification (RFID) technology is combined with warehouse management. In this paper, RFID technology and RFID-based warehousing logistics distribution are briefly introduced, two experiments are carried out in the warehouse of Zhengzhou xx Logistics Company, i.e., the influence of the position of the electronic label of the goods on the recognition accuracy and the comparison experiment between traditional management mode and RFID-based management mode. The results show that the accuracy of recognition is the highest when the electronic label is at the bottom of the cargo, that is, when it is closest to the reader. The management accuracy of the RFID-based warehouse management is higher within one day, which is not subject to the peak of the throughput of cargoes. Within one month, the RFID-based warehouse management has a higher average inbound and outbound speed of the warehouse, the larger storage capacity of the warehouse, lower required labor cost and smaller loss rate of cargoes during the process of distribution. In summary, the use of RFID technology can effectively improve the efficiency of warehouse management. © 2020 by Begell House, Inc.","Automation; Logistics; Radio frequency identification; Warehouse management","Automation; Efficiency; Logistics; Radio frequency identification (RFID); Radio waves; Wages; Warehouses; Electronic labels; Internet technology; Logistics distribution; Logistics management; Radio frequency identification technology; Recognition accuracy; Traditional management; Warehouse management; Distribution of goods",{"$nulls":6},"Kim M.S., A Cost-benefit analysis of case-level radio frequency identification tagging-based system on logistics service, Adv. Sci. Lett., 21, 10, pp. 3324-3328, (2015); Jansen R., Krabs A., Automatic identification in packaging - Radio frequency identification in multiway systems, Packag. Technol. Sci., 12, 5, pp. 229-234, (2015); Barge P., Gay P., Merlino V., Tortia C., Radio frequency identification technologies for livestock management a, Can. J. Anim. Sci., 93, 1, pp. 23-33, (2017); Saygin C., Sarangapani J., Radio Frequency Identification (RFID) enabling lean manufacturing, Int. J. Manuf. Res., 6, 4, pp. 321-336, (2015); Li T.H., Hu H.B., Research on liquor warehousing and the anti-counterfeiting system based on radio frequency identification technology, J. Comput. Theor. Nanosci., 13, 9, pp. 6052-6055, (2016); Aviles J., Smith N.R., Vargasrosales C., A method for identifying multiple RFID tags in high electromagnetic interference environments, Can. J. Elect. Comput. E., 38, 4, pp. 346-352, (2015); Jia X.L., Feng Q.Y., An improved anti-collision protocol for radio frequency identification tag, Int. J. Commun. Syst., 28, 3, pp. 401-413, (2015); Pumpoung T., Phongcharoenpanich C., Design of wideband tag antenna for ultrahigh-frequency radio frequency identification system using modified t-match and meander-line techniques, Electromagnetics, 35, 5, pp. 340-354, (2015); Nayak R., Singh A., Padhye R., Wang L.J., RFID in textile and clothing manufacturing: Technology and challenges, Fashion Text, 2, 1, (2015); Sun X., Zhang X., Zhao B., Wang L., Wei L., Jia Q., Design, experiment and error analysis of impulse radio-ultra wide band indoor positioning system used in agricultural warehousing, Trans. Chin. Soc. Agricult. Eng., 33, pp. 23-29, (2017); Guo X.M., He Y., Ontology model of real-time inventory and hourglass-showing distribution in supply chain system, J. Zhejiang Univ. (Eng. Sci. Ed.), 49, 1, pp. 54-62, (2015); Mohammed A., Wang Q., Alyahya S., Bennett N., Design and optimization of an RFID-enabled automated warehousing system under uncertainties: A multi-criterion fuzzy programming approach, Int. J. Adv. Manuf. Tech., 91, 5-8, pp. 1661-1670, (2017); Kadlubek M., On analysis of RFID technology application in warehouses, Appl. Mech. Mater., 795, pp. 115-122, (2015); Liukkonen M., RFID technology in manufacturing and supply chain, Int. J. Computer Integr. Manuf., 28, 8, (2015); Dufour J.C., Reynier P., Boudjema S., Soto Aladro A., Giorgi R., Brouqui P., Evaluation of hand hygiene compliance and associated factors with a radio-frequency-identification-based real-time continuous automated monitoring system, J. Hosp. Infect., 95, 4, (2017)","Q. Liu; Zhengzhou Vocational College of Finance and Taxation, Zhengzhou, Henan, 18 Zhengwei Road, 450048, China; email: qinlliuq@yeah.net",null,"Begell House Inc.",{"$nulls":5},402508.0,null,"TCREA",null,"English","Telecommun Radio Eng","Article","Final",null,"Scopus","2-s2.0-85081050234"]
["Azmi F.R.; Abdullah A.; Musa H.; Wan Mahmood W.H.","Azmi, Fadhlur Rahim (57191516010); Abdullah, Abu (54983595300); Musa, Haslinda (57191251272); Wan Mahmood, Wan Hasrulnizzam (53867422100)","57191516010; 54983595300; 57191251272; 53867422100","Perception of food manufacturers towards adoption of halal food supply chain in Malaysia: Exploratory factor analysis",2020.0,"Journal of Islamic Marketing",11.0,3.0,null,571.0,589.0,18.0,15.0,"10.1108/JIMA-12-2018-0236","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85067060448&doi=10.1108%2fJIMA-12-2018-0236&partnerID=40&md5=5f563d07ab05841d6c67f6bf468369d3","Faculty of Technology Management and Technopreneurship, Universiti Teknikal Malaysia Melaka, Durian Tunggal, Malaysia; Faculty of Manufacturing Engineering, Universiti Teknikal Malaysia Melaka, Durian Tunggal, Malaysia; Faculty of Mechanical and Manufacturing Engineering Technology, Universiti Teknikal Malaysia Melaka, Durian Tunggal, Malaysia","Azmi F.R., Faculty of Technology Management and Technopreneurship, Universiti Teknikal Malaysia Melaka, Durian Tunggal, Malaysia; Abdullah A., Faculty of Manufacturing Engineering, Universiti Teknikal Malaysia Melaka, Durian Tunggal, Malaysia; Musa H., Faculty of Technology Management and Technopreneurship, Universiti Teknikal Malaysia Melaka, Durian Tunggal, Malaysia; Wan Mahmood W.H., Faculty of Mechanical and Manufacturing Engineering Technology, Universiti Teknikal Malaysia Melaka, Durian Tunggal, Malaysia","Purpose: Food industry players obtain the advantages of profits growth within the halal industry whereby the market is dynamic to generate profit. Hence, this study aims to analyse the perception of food manufacturers towards the adoption of the halal food supply chain (HFSC). Design/methodology/approach: For this study, 103 halal food manufacturers in Malaysia were selected as respondents. Perceptions of respondents towards HFSC were recorded using a five-point questionnaire. The questionnaire was designed by authors and adapted from a previous study. The questionnaire was circulated by two experts with proficiency in this filed. Findings: By conducting exploratory factor analysis, the study found the perception of food manufacturers, which is expected business benefits play an important role in the adoption of HFSC. Halal integrity becomes the second factor to lead the company to its adoption. Organizational readiness is the third factor that drives the company to adopt HFSC. Research limitations/implications: Majority of the sample was responded by Bumiputera companies. The study suggests focussing the study for non-Bumiputera companies to examine their influence towards HFSC. Furthermore, future studies should explore different sectors of halal, such as pharmaceuticals, cosmetics, travel and tourism, logistics, finance and e-commerce. Moreover, ensuring the status of halal should be more emphasized in food chains; thus, the source of risk in HFSC should be explored to secure the integrity of halal. Practical implications: The paper includes implications for the halal food industry, whereby the adoption of HFSC will contribute to the business benefits to create a more competitive advantage to the industry. Moreover, the implications of halal practice can create consumers’ trust on the halal product. Originality/value: This paper fulfils an analysed need to study specifically on upstream parties by adopting HFSC. © 2019, Emerald Publishing Limited.","Exploratory factor analysis; Halal adoption; Halal food; Halal food supply chain",{"$nulls":5},"Universiti Teknikal Malaysia Melaka, UTeM","The corresponding author would like to thank Universiti Teknikal Malaysia Melaka for the UTeM Zamalah Scheme for sponsorship.","Ab Talib M.S., Ai Chin T., Fischer J., Linking halal food certification and business performance, British Food Journal, 119, 7, pp. 1606-1618, (2017); Ab Talib M.S., Md. 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Health and supply chain risks and a proposed framework to address urgent analytical needs, The Analyst, 141, 1, pp. 24-35, (2016); White G.R., Samuel A., Fairtrade and halal food certification and labeling: commercial lessons and religious limitations, Journal of Macromarketing, 36, 4, pp. 388-399, (2016); Williams B., Onsman A., Brown T., Exploratory factor analysis: a five-step guide for novices, Australasian Journal of Paramedicine, 8, 3, pp. 1-11, (2010); Wilson J.A., The halal phenomenon: an extension or a new paradigm?, Social Business, 4, 3, pp. 255-271, (2014); Wilson J.A., Liu J., Shaping the halal into a brand?, Journal of Islamic Marketing, 1, 2, pp. 107-123, (2010); Zailani S., Kanapathy K., Iranmanesh M., Tieman M., Drivers of halal orientation strategy among halal food firms, British Food Journal, 117, 8, pp. 2143-2160, (2015); Zulfakar M.H., Anuar M.M., Ab Talib M.S., Conceptual framework on halal food supply chain integrity enhancement, Procedia-Social and Behavioral Sciences, 121, pp. 58-67, (2014); Wilson J.A., Liu J., The challenges of Islamic branding: navigating emotions and halal, Journal of Islamic Marketing, 2, 1, pp. 28-42, (2011)","F.R. Azmi; Faculty of Technology Management and Technopreneurship, Universiti Teknikal Malaysia Melaka, Durian Tunggal, Malaysia; email: fadhlurrahimazmi@gmail.com",null,"Emerald Group Holdings Ltd.",{"$nulls":5},1.7590833E7,null,null,null,"English","J. Islam. Mark.","Article","Final",null,"Scopus","2-s2.0-85067060448"]
["Nisenson L.","Nisenson, Lisa (23395176800)",2.33951768E10,"Rapidly changing e-commerce trends and technologies mean big changes for land-use and infrastructure planning.",2020.0,"Planning",86.0,4.0,null,26.0,33.0,7.0,0.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85094921577&partnerID=40&md5=d468c43c7c68689f8a7cb93d9be9a333",null,null,"Rapidly changing e-commerce trends and technologies mean big changes for land-use and infrastructure planning. With people staying at home all day, due to coronavirus pandemic, most stores and businesses temporarily shuttered, and restaurants closed to dine-in patrons, many Americans are turning to e-commerce and contactless delivery for groceries and other goods, including those who have not been online shoppers. For planners and local governments, experts offer a few pieces of advice. First, when it comes to permitting new technologies during the pandemic, planners must be careful to make those permits time-limited or associated specifically with an emergency declaration, so that they can make thoughtful decisions that carefully consider long-term impacts later.",null,"Coronavirus; Trachinotus falcatus; advanced technology; electronic commerce; infrastructure planning; land use planning; technological change",{"$nulls":9},"American Planning Association",{"$nulls":5},12610.0,null,null,null,"English","Planning","Article","Final",null,"Scopus","2-s2.0-85094921577"]
["Zhao Y.; Zhou Y.; Deng W.","Zhao, Yingyan (57216781569); Zhou, Yihong (57216789070); Deng, Wu (36343223500)","57216781569; 57216789070; 36343223500","Innovation mode and optimization strategy of B2C E-commerce logistics distribution under big data",2020.0,"Sustainability (Switzerland)",12.0,8.0,3381.0,null,null,null,21.0,"10.3390/SU12083381","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85084644329&doi=10.3390%2fSU12083381&partnerID=40&md5=3d8aedb4695ab4ea94a6c310e8d1d5dd","College of Business Administration, Ningbo Polytechnic, Ningbo, 315800, China; Office of Educational Administration, Ningbo Polytechnic, Ningbo, 315800, China; School of Software Engineering, Dalian Jiaotong University, Dalian, 116028, China","Zhao Y., College of Business Administration, Ningbo Polytechnic, Ningbo, 315800, China; Zhou Y., Office of Educational Administration, Ningbo Polytechnic, Ningbo, 315800, China; Deng W., School of Software Engineering, Dalian Jiaotong University, Dalian, 116028, China","With the advent of big data era and rapid development of Internet technology, e-commerce has had a strong development tendency that causes many problems, such as redundant and complex business processes, low efficiency and a high cost for e-commerce logistics in the distribution sector. It is not difficult to conclude that the key to improving logistics distribution efficiency-and reduce logistics distribution costs-is to optimize logistics distribution under big data. In this study, the management model, influence factors and development status of B2C e-commerce logistics distribution under big data are analyzed in detail. Then big data processing, business process and route optimization strategies for B2C e-commerce logistics distribution under big data are deeply studied. Furthermore, an optimization model of product sales and logistics distribution of B2C e-commerce by big data platform is discussed in order to propose an innovative optimization strategy for B2C e-commerce logistics distribution under big data. Big data technology is applied in B2C e-commerce logistics business management, which is studied in detail. These findings achieve the optimal distribution of B2C e-commerce, reduce the B2C e-commerce logistics distribution cost and improve the B2C e-commerce logistics distribution efficiency under big data. In addition, enhanced competitiveness of B2C e-commerce logistics distribution is examined in this study. This study provides a reference for follow-up big data studies in the field of e-commerce. © 2020 by the authors.","B2C e-commerce; Big data; Innovative model; Logistics distribution; Optimization strategy","business; competitiveness; complexity; data processing; electronic commerce; innovation; Internet; logistics; optimization; strategic approach",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (51605068, 61771087)","Funding: This research was funded by the National Natural Science Foundation of China, Grant Number 61771087, Grant Number 51605068.","Giuffrida M., Mangiaracina R., Perego A., Tumino A., Cross-border B2C E-commerce to China An evaluation of different logistics solutions under uncertainty, Int. J. Phys. Distrib. Logist. 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Manag, 17, pp. 285-318, (2019); Zhang B., Du Z., Wang B., Wang Z., Motivation and challenges for E-commerce in e-waste recycling under \"Big data\" context: A perspective from household willingness in China, Technol. Forecast. Soc. Chang, 144, pp. 436-444, (2019); Zhou H.J., Sun G., Fu S., A scalable approach for fraud detection in online E-commerce transactions with big data analytics, Comput. Mater. Contin, 60, pp. 179-192, (2019); Liu X., Liu X., Luo X., Fu H., Wang M., Li L., Impact of different policy instruments on diffusing energy consumption monitoring technology in public buildings: Evidence from Xi'an, China, J. Clean. Prod, 251, (2020); Wu J., Shi J., Li T.Y., A novel image encryption approach based on a hyperchaotic system, pixel-level filtering with variable kernels, and DNA-level diffusion, Entropy, 22, (2020)","W. Deng; School of Software Engineering, Dalian Jiaotong University, Dalian, 116028, China; email: dw7689@djtu.edu.cn",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85084644329"]
["Ko S.Y.; Sari R.P.; Makhmudov M.; Ko C.S.","Ko, Seung Yoon (57193687380); Sari, Ratna Permata (57208593321); Makhmudov, Muzaffar (57208503525); Ko, Chang Seong (7202596739)","57193687380; 57208593321; 57208503525; 7202596739","Collaboration model for service clustering in last-mile delivery",2020.0,"Sustainability (Switzerland)",12.0,14.0,5844.0,null,null,null,11.0,"10.3390/su12145844","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85088839007&doi=10.3390%2fsu12145844&partnerID=40&md5=e3b82a61ec7274e9a393c40fcf2a5544","Department of Industrial Engineering, Seoul National University, Gwanak-ro, Gwanak-gu, Seoul, 08826, South Korea; Department of Industrial and Management Engineering, Kyungsung University, 309 Suyeong-ro, Nam-gu, Busan, 48434, South Korea","Ko S.Y., Department of Industrial Engineering, Seoul National University, Gwanak-ro, Gwanak-gu, Seoul, 08826, South Korea; Sari R.P., Department of Industrial and Management Engineering, Kyungsung University, 309 Suyeong-ro, Nam-gu, Busan, 48434, South Korea; Makhmudov M., Department of Industrial and Management Engineering, Kyungsung University, 309 Suyeong-ro, Nam-gu, Busan, 48434, South Korea; Ko C.S., Department of Industrial and Management Engineering, Kyungsung University, 309 Suyeong-ro, Nam-gu, Busan, 48434, South Korea","As e-commerce is rapidly expanding, efficient and competitive product delivery system to the final customer is highly required. Recently, the emergence of a smart platform is leading the transformation of distribution, performance, and quality in express delivery services, especially in the last-mile delivery. The business to consumer (B2C) through smart platforms such as Amazon in America and Coupang in Korea utilizes the differentiated delivery rates to increase the market share. In contrast, the small and medium-sized express delivery companies with low market share are trying hard to expand their market share. In order to fulfill all customer needs, collaboration is needed. This study aims to construct a collaboration model to maximize the net profit by considering the market density of each company. A Baduk board game is used to derive the last-mile delivery time function of market density. All companies in collaboration have to specialize the delivery items into certain service clustering types, which consist of regular, big sized/weighted, and cold items. The multi-objective programming model is developed based on max-sum and max-min criteria. The Shapley value and nucleolus approaches are applied to find the profit allocation. Finally, the applicability of the proposed collaboration model is shown through a numerical example. © 2020 by the authors.","Baduk board game; Collaboration model; Express delivery service; Last-mile delivery; Nucleolus; Service clustering; Shapley value","Amazonia; Korea; business development; cluster analysis; consumption behavior; electronic commerce; emergence; market conditions; profitability",{"$nulls":4},"Kyungsung University; National Research Foundation of Korea, NRF; Ministry of Education, Science and Technology, MEST, (NRF-2018R1D1A3A03000944)","Funding: This research was supported by Basic Science Research Program though the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (NRF-2018R1D1A3A03000944). This research was also supported by Kyungsung University research grants in 2019.","Lim S.F.W., Jin X., Srai J.S., Consumer-Driven E-commerce: A literature Review, Design Framework, and Research Agenda on Last-mile Logistics Models, Int. J. Phys. Distrib. Logist. Manag., 48, pp. 308-332, (2018); Ko S.Y., Cho S.W., Lee C., Pricing and Collaboration in Last Mile Delivery Services, Sustainability, 10, (2018); Zerbino P., Aloini D., Dulmin R., Mininno V., Big Data-enabled Customer Relationship Management: A holistic approach, Inf. Process. Manag., 54, pp. 818-846, (2018); Lu W., McFarlane D., Giannikas V., Zhang Q., An Algorithm for Dynamic Order-picking in Warehouse Operations, Eur. J. Oper. Res., 248, pp. 107-122, (2016); Macioszek E., First and Last Mile Delivery-Problems and Issues, Advanced Solutions of Transport Systems for Growing Mobility, 631, pp. 147-154, (2018); Todeva E., Knock D., Strategic Alliances and Models of Collaboration, Manag. Decis., 43, pp. 1-22, (2005); Gevaers R., Voorde E.V.D., Vanelslander T., Cost Modelling and Simulation of Last-mile Characteristics in an Innovative B2C Supply Chain Environment with Implications on Urban Areas and Cities, Procedia Soc. Behav. Sci., 125, pp. 398-411, (2014); Duin J.H.R.V., Goffau W.D., Wiegmans B., Tavasszy L.A., Saes M., Improving Home Delivery Efficiency by using Principles of Address Intelligence for B2C Deliveries, Transp. Res. Procedia, 12, pp. 14-25, (2016); Agatz N.A.H., Fleischmann M., Nunen J.A.E.E.V., E-Fulfillment and Multi-Channel Distribution-A Review, Eur. J. Oper. Res., 187, pp. 339-356, (2008); Aized T., Srai J.S., Hierarchical Modeling of Last Mile Logistic Distribution System, Int. J. Adv. Manuf. Technol., 70, pp. 1053-1061, (2014); Belgin O., Karaoglan I., Altiparmak F., Two-Echelon Vehicle Routing Problem with Simultaneous Pickup and Delivery: Mathematical Model and Heuristic Approach, Comput. Ind. Eng., 115, pp. 1-16, (2018); Ozbaygin G., Karasan O.E., Savelsbergh M., Yaman H.A., Branch-And-Price Algorithm for the Vehicle Routing Problem with Roaming Delivery Locations, Transp. Res. Part B, 100, pp. 115-137, (2017); Tanash M., Contreras I., Vidyarthi N., An Exact Algorithm for the Modular Hub Location Problem with Single Assignments, Comput. Oper. Res., 85, pp. 32-44, (2017); Boyer K.K., Prud'homme A.M., Chung W., The Last Mile Challenge: Evaluating the Effects of Customer Density and Delivery Window Patterns, J. Bus. Logist., 30, pp. 185-200, (2009); Ferdinand F.N., Chung K.H., Ko H.J., Ko C.S., Genetic Algorithm-Based Approach to Multi-Objective Decision Making Model for Strategic Alliances in Express Courier Services, ICIC Express Lett., 6, pp. 929-934, (2012); Ferdinand F.N., Ko C.S., Coevolutionary Algorithm Based Approach to The Collaborative Network Design in Express Delivery Services using Coalitional Game Theory, ICIC Express Lett., 10, pp. 2711-2717, (2016); Chung K.H., Rho J.J., Ko C.S., A Strategic Alliance Model with Regional Monopoly of Service Centres in Express Courier Services, Int. J. Serv. Oper. Manag., 5, pp. 774-786, (2009); Chung K.H., Ko S.Y., Lee C.U., Ko C.S., Sustainable Collaboration Model with Monopoly of Service Centers in Express Delivery Services Based on Shapley Value Allocation, Int. J. Ind. Eng. Theory Appl. Pract., 23, pp. 166-173, (2016); Chung K.H., Ko S.Y., Ko C.S., A Cooperative Game Theoretic Network Design for Collaborative Operation of Service Centers and Consolidation Terminals in Delivery Services, Int. J. Ind. Eng. Theory Appl. Pract., 25, pp. 18-28, (2018); Dai B., Chen H., Profit Allocation Mechanisms for Carrier Collaboration in Pickup and Delivery Service, Comput. Ind. Eng., 62, pp. 633-643, (2012); Cachon G.P., Lariviere M.A., Capacity Choice and Allocation: Strategic Behavior and Supply Chain Performance, Manag. Sci., 45, pp. 1091-1108, (1999); Frisk M., Lundgren M.G., Jomsten K., Ronnqvist D., Cost Allocation in Collaborative Forest Transportation, Eur. J. Oper. Res., 205, pp. 448-458, (2010); Galkin A., Obolenseva L., Balandina I., Kush E., Karpenko V., Bajdor P., Last Mile Delivery for Consumer Driven Logistics, Transp. Res. Procedia, 39, pp. 74-83, (2019); Giret A., Carrascosa C., Julian V., Rebollo M., Botti V., Crowd sourcing Approach for Sustainable Last Mile Delivery, Sustainability, 10, (2018); Kanuri C., Venkata K., Maitia S., Mulukutla P., Leveraging Innovation for Last Mile Connectivity to Mass Transit, Transp. Res. Procedia, 41, pp. 655-669, (2019); Clausen U., Geiger C., Poting M., Hands-on Testing of Last mile Concepts, Transp. Res. Procedia, 14, pp. 1533-1542, (2016); Manerba D., Mansini R., Zanotti R., Attended Home Delivery: Reducing Last Mile Environmental Impact by Changing Customer Habits, Int. Fed. Autom. Control (IFAC), 51, pp. 55-60, (2018); Wang Y., Peng S., Assogba K., Liu Y., Wang H., Xu M., Wang Y., Implementation of Cooperation for Recycling Vehicle Routing Optimization in Two-Echelon Reverse Logistics Networks, Sustainability, 10, (2018); Gansterer M., Hartl R.F., Collaborative Vehicle Routing: A Survey, Eur. J. Oper. Res., 268, pp. 1-12, (2017); Yea M., Chung S., Cheong T., Kim D., The Sharing of Benefits from a Logistics Alliance Based on a Hub-Spoke Network: A Cooperative Game Theoretic Approach, Sustainability, 10, (2018); Timmer J., Michela Chessa M., Boucherie R.J., Cooperation and Game-Theoretic Cost Allocation in Stochastic Inventory Models with Continuous Review, Eur. J. Oper. Res., 231, pp. 567-576, (2013); Do W., Park H., Chung K., Park D., An Effects Analysis of Logistics Collaboration: The Case of Pharmaceutical Supplies in Seoul, Sustainability, 11, (2019); Villamizar A.M., Torres J.R.M., Mejia C.A.V., Non-Collaborative versus Collaborative Last Mile Delivery in Urban Systems with Stochastic Demands, Procedia CIRP, 30, pp. 263-268, (2015); Buyukozkan G., Feyzioglu O., Nebol E., Selection of the Strategic Alliance Partner in Logistics Value Chain, Int. J. Prod. Econ., 113, pp. 148-158, (2008); Parise S., Henderson J.C., Knowledge Resource Exchange in Strategic Alliances, IBM Syst. J., 40, pp. 908-924, (2001); Feng X., Moon I., Ryu K., Warehouse Capacity Sharing via Transshipment for an Integrated Two-Echelon Supply Chain, Transp. Res. Part E Logist. Transp. Rev., 104, pp. 17-35, (2017); Lozano S., Moreno P., Adenso-Diaz B., Algaba E., Cooperative Game Theory Approach to Allocating Benefits of Horizontal Cooperation, Eur. J. Oper. Res., 229, pp. 444-452, (2013); Moustakides G.V., Verykios V.S., A Max-min Approach for Hiding Frequent Item Sets, Data Knowl. Eng., 65, pp. 75-89, (2008); Gao J., Yang X., Liu D., Uncertain Shapley value of Coalitional Game with Application to Supply Chain Alliance, Appl. Soft Comput., 56, pp. 551-556, (2017)","C.S. Ko; Department of Industrial and Management Engineering, Kyungsung University, Nam-gu, Busan, 309 Suyeong-ro, 48434, South Korea; email: csko@ks.ac.kr",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85088839007"]
["P. D.; Babu S.; Vijayalakshmi Y.","P., Dijesh (57193055703); Babu, SuvanamSasidhar (57193057419); Vijayalakshmi, Yellepeddi (57195063470)","57193055703; 57193057419; 57195063470","Enhancement of e-commerce security through asymmetric key algorithm",2020.0,"Computer Communications",153.0,null,null,125.0,134.0,9.0,18.0,"10.1016/j.comcom.2020.01.033","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85078965145&doi=10.1016%2fj.comcom.2020.01.033&partnerID=40&md5=ce9e63b70085703aeae17b3b49b999cb","Department of Computer Science, Bharathiar University, Coimbatore, Tamilnadu, India; School of Computing and Information Technology, Reva University, Bengaluru, 560064, India; Department of CSE, Karpagam University, Coimbatore, Tamilnadu, India","P. D., Department of Computer Science, Bharathiar University, Coimbatore, Tamilnadu, India; Babu S., School of Computing and Information Technology, Reva University, Bengaluru, 560064, India; Vijayalakshmi Y., Department of CSE, Karpagam University, Coimbatore, Tamilnadu, India","Electronic commerce offers reduced transaction costs and much convenient mode of business to all over global consumers. This paper explains asymmetric methods which uses electronic commerce transactions and other assisted algorithms of cryptography that are important in set up of electronic commerce working. This study explains the essential security problems in electronic commerce. To avoid the issues of security certain secure conditions must be followed which offers sufficient security to transaction data for every entity in transaction of electronic commerce. In this study a multi-layer encryption algorithm namely RSA encryption algorithm and Fernet cipher encryption algorithm is proposed based on security. Multi-layer encryption algorithm is used to construct a sophisticated and complex approach of encryption. This algorithm integrates the strength of several techniques of encryption at the same time. This study reveals how much safe consumer and payment data order will be managed effectively by security-based approaches. Encryption technique discussed in this study is the major technique to make the transaction over internet secure. A better technology of encryption can decrease the fraudlent activities easily and effectively. This study proposes a multi-layer encryption algorithm and implemented it in order to enable delivery of messages through network in a secure way. This study will be helpful to control the decryption and encryption with the use of private and public key of receiver and sender. © 2020","Decryption; E-commerce security; Encryption; Fernet cipher algorithm; RSA algorithm","Costs; Electronic commerce; Network security; Cipher algorithms; Decryption; E-commerce security; Encryption algorithms; Encryption technique; RSA algorithms; Security problems; Transaction data; Cryptography",{"$nulls":6},"Chaudhary A., Ahmad K., Rizvi M.A., E-commerce security through asymmetric key algorithm, Communication Systems and Network Technologies, CSNT, 2014 Fourth International Conference on, pp. 776-781, (2014); Ritu A., Crytography based E-commerce security, Int. J. Adv. Res. Comput. Sci. Softw. Eng., 6, 7, pp. 359-362, (2016); Gupta M.P., Dubey A., E-commerce-study of privacy, trust and security from consumer's perspective, Transactions, 37, (2016); Rathi N.A., Gupta S.R., Analysis of security mechanism in E-commerce transaction, Int. J. Adv. Res. Comput. Eng. Technol., 5, 1, pp. 131-134, (2016); Patro S.P., Padhy N., Panigrahi R., Security issues over E-commerce and their solutions, Int. J. Adv. Res. Comput. Commun. Eng., 5, 12, pp. 81-85, (2016); Churi P., E-commerce security with secure electronic transaction protocol: A survey and implementation, (2017); Illayaraja M., Shankar K., Devika G., A modified symmetric key cryptography method for secure data transmission, Int. J. Pure Appl. Math., 116, 10, pp. 301-306, (2017); Suguna S., Dhanakoti V., Manjupriya R., A study on symmetric and asymmetric key encryption algorithms, Int. Res. J. Eng. Technol., 3, 4, pp. 27-31, (2016); Garg N., Yadav P., Comparison of asymmetric algorithms in cryptography, Int. J. Comput. Sci. Mob. Comput., 3, 4, pp. 1190-1196, (2014); Kaur K., Pathak A., Kaur P., Kaur K., E-commerce privacy and security system, Int. J. Eng. Res. Appl., 5, 5, pp. 63-73, (2015); Verma S., Garg D., An improved RSA variant, Int. J. Adv. Technol., 5, 2, pp. 161-169, (2014); Kumar C., Vincent P.D.R., Enhanced Diffie-Hellman algorithm for reliable key exchange, IOP Conference Series: Materials Science and Engineering, 263, (2017); Kak A., Certificates, digital signatures, and the Diffie-Hellman key exchange algorithm, (2018); Shi Y., Lin J., Xiong G., Wang X., Fan H., Key-insulated undetachable digital signature scheme and solution for secure mobile agents in electronic commerce, Mob. Inf. Syst., (2016); Kamalakannan V., Tamilselvan S., Security enhancement of text message based on matrix approach using elliptical curve cryptosystem, Procedia Mater. Sci., 10, pp. 489-496, (2015); Setiadi I., Kistijantoro A.I., Miyaji A., Elliptic curve cryptography: Algorithms and implementation analysis over coordinate systems, Advanced Informatics: Concepts, Theory and Applications, ICAICTA, 2015 2nd International Conference on, pp. 1-6, (2015); Kuppuswamy P., Al-Khalidi S.Q., Securing E-commerce business using hybrid combination based on new symmetric key and RSA algorithm, MIS Rev. Int. J., 20, 1, pp. 59-71, (2014); Shetty A., Shravya Shetty K., Krithika K., A review on asymmetric cryptography – RSA and El-Gamal algorithm, Int. J. Innov. Res. Comput. Commun. Eng., 2, 5, pp. 98-105, (2015); Arora S., Pooja K., Enhancing cryptographic security using novel approach based on enhanced-RSA and elamal: Analysis and comparison, Int. J. Comput. Appl. Technol., 112, 13, pp. 35-38, (2015); Kallam S., Diffie-Hellman: Key exchange and public key cryptosystems, (2015); Nwoye C.J., Design and development of an E-commerce security using RSA cryptosystem, Int.J. Innov. Res. Inf. Secur., 6, 2, pp. 6-17, (2015); Jain A., Kapoor V., Secure communication using RSA algorithm for network environment, Int. J. Comput. Appl., 118, 7, (2015); Jaju A.S., Chowhan S.S., Analytical study of modified RSA algorithms for digital signature, Int. J. Recent Innov. Trends Comput. Commun., 3, 3, pp. 944-949, (2015); Fernando A.D.N.M., Herath H.M.P.M.B., Senarathne M.L.R.K., Brandiwatta D.P., Kiroshan T., Madushika M.P., Senarathne P.A.D.A., Dharmmearatchi M.D., Biometric encryption: E-commerce security using cryptography techniques, Int. J. Sci. Res. Publ., 6, 10, (2016); Ahmad K., Alam M.S., E-commerce security through elliptic curve cryptography, Procedia Comput. Sci., 78, pp. 867-873, (2016); Rane Y.S., Study on services provided by digital signatures in E-commerce, Int. Res. J. Eng. Technol., 3, 5, pp. 3039-3041, (2016); Shaikh J.R., Kumar R., Nenova M., IIiev G., Singh H., Enhancing E-commerce security using elliptic curve cryptography, Int. J. Curr. Adv. Res., 6, 8, pp. 5338-5342, (2017); Halim M.A.A., Wen C.C., Rahmi I., Abdullah N.A., Rahman N.H.A., Email authentication using symmetric and asymmetric key algorithm encryption, AIP Conference Proceedings, 1891, (2017); Liu X., Lee W.B., Bui Q.A., Lin C.C., Wu H.L., Biometrics-based RSA cryptosystem for securing real-time communication, (2018); Matte S., Dubey A., Shirsat N., Kale A., Hybrid model for securing E-commerce transaction, Int. J. Sci. Eng. Res., 9, 4, pp. 25-26, (2018)","D. P.; Department of Computer Science, Bharathiar University, Coimbatore, India; email: dijeshtirur@gmail.com",null,"Elsevier B.V.",{"$nulls":5},1403664.0,null,"COCOD",null,"English","Comput Commun","Article","Final",null,"Scopus","2-s2.0-85078965145"]
["Wagener N.; Aritua B.; Zhu T.","Wagener, Norbert (57216296828); Aritua, Bernard (57816859600); Zhu, Tong (57216299930)","57216296828; 57816859600; 57216299930","The new silk road: Opportunities for global supply chains and challenges for further development; [Nowy jedwabny szlak: Możliwości globalnego łańcucha dostaw i wyzwania dla dalszego rozwoju]",2020.0,"Logforum",16.0,2.0,null,193.0,207.0,14.0,13.0,"10.17270/J.LOG.2020.403","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85083057969&doi=10.17270%2fJ.LOG.2020.403&partnerID=40&md5=9118658467c488b5744847bb4547f063","Poznan School of Logistics, Poznan, Poland; The World Bank Group, China","Wagener N., Poznan School of Logistics, Poznan, Poland; Aritua B., The World Bank Group, China; Zhu T., The World Bank Group, China","Background: Efforts to revive the New Silk Route from Europe to Asia have been on-going since the late 1970s. However, the launch of the Belt and Road Initiative (BRI) of the PR China in 2013 has given new impetus to Europe-Asia connectivity. Between 2014 and 2018 the number of block trains between China and Europe (including Russia) increased from 298 to 4,982 per year. Will this trend continue? Which bottlenecks and challenges appear? What are opportunities for respective countries, policy makers, shippers and logistics operators? The paper contributes to the scientific question of further and sustainable segmentation of intermodal transport markets in the context of global supply chains. Methods: Based on a literature review and interviews with logistics operators and shippers the authors analyze the present design and operational parameters of the intermodal land bridge traffic system, major challenges and bottlenecks and propose measure how to enable further growth and to improve the sustainability of this traffic. Results: Main issues of the further development of the New Silk Road Europe China are technological innovations, digitalization of supply chains, optimizing of intermodal transport and gateway concepts, corridor management and new trading patterns with e-commerce. Conclusions: Although this intermodal land bridge connection will likely continue to be a niche market, it offers considerable transit time and cost savings for specific types of freight where air freight is too expensive and maritime logistics is too slow. At higher freight costs compared with the sea freight and lower fares than air cargo this is especially interesting for high value cargo and the Northern provinces of China; also for opportunities in Central Asia, and the Caucasus. The new transport route promotes not only investments into production sites for export at locations in the Northern provinces but also opens new opportunities for European exports of industrial goods and FMCG for the growing middle class in China. The total logistics costs from the viewpoint of a shipper can be more competitive via land bridge than via sea. Both production and distribution networks of large companies (e.g. BASF, HP, BMW) and small and medium sized companies (here especially through e-commerce) can benefit from a further integration of markets and globalization of supply chains. © Wyższa Szkoła Logistyki, Poznań, Polska.","Belt and road initiative; Corridor Management; Digitalization; Global supply chains; Intermodal transport; New silk road",{"$nulls":5},"Poznan School of Logistics","Statutory fund of Poznan School of Logistics.","Aritua B.N.H., World Bank Policy Research Working Paper Series: The Belt and Road Initiative Connectivity and Infrastructure Gaps, Beijing: S.N, (2019); Beifert A., Sherbanin Y., Vinokurov E., Challenges and Opportunities of Economic Integration within a Wider European and Eurasian Space-Trans-Eurasian Land Transport Corridors: Assessment of Prospects and Barriers, (2018); Press Centre-Bmw., (2019); Belt and Road Portal, Six Years' Review of Belt and Road Initiative, (2019); China Business Journal, (2019); (2019); RETRACK WP 13: Potential for Eurasia Land Bridge Corridors & Logistics Developments along the Corridors, (2012); Neue Seidenstraße-Wie Österreichs Bahn Die europäische Konkur-Renz Im China-Geschäft abhängen Will, (2019); Hofmann S., BASF plant 10-Milliarden-Projekt in China, Handelsblatt, Issue, 9, 7, (2018); BMW Ramps up Investment in China, (2018); Jiaoe W., An organizational model and border port hinterlands for the China-Europe Railway Express, Journal of Geographical Sciences, 28, 9, (2018); Sibirische Zugroute Wird Zum Erfolgsmodell, (2016); Gleave S.D., Research for TRAN Committee: The New Silk Route-Opportunities and Challenges for EU Transport, (2018); First Blockchain Container Shipped to Rotterdam, (2019); Comprehensive Planning of Eurasian Transport Corridors to Strenghen the Intra-And Inter-Regional Transport Connectivity, (2017); Wagener N., Bamler N., Behrens R., Potenzialstudie für Den Intermodalen Güterverkehr in Der Wirtschaftsregion Lausitz, (2019); Belt and Road Economics-Opportunities and Risks of Transport Corridors, (2019)",null,null,"Poznan School of Logistics",{"$nulls":5},1.8952038E7,null,null,null,"English","Logforum","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85083057969"]
["Leung K.H.; Mo D.Y.; Ho G.T.S.; Wu C.H.; Huang G.Q.","Leung, K.H. (57328966600); Mo, Daniel Y. (14822088000); Ho, G.T.S. (8348673600); Wu, C.H. (55506191100); Huang, G.Q. (7403425048)","57328966600; 14822088000; 8348673600; 55506191100; 7403425048","Modelling near-real-time order arrival demand in e-commerce context: a machine learning predictive methodology",2020.0,"Industrial Management and Data Systems",120.0,6.0,null,1149.0,1174.0,25.0,31.0,"10.1108/IMDS-12-2019-0646","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85085085304&doi=10.1108%2fIMDS-12-2019-0646&partnerID=40&md5=fc9c5d802024259b569a0f45063472b9","Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong; Department of Supply Chain and Information Management, The Hang Seng University of Hong Kong, Hong Kong; HKU-ZIRI Lab for Physical Internet, Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong","Leung K.H., Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong; Mo D.Y., Department of Supply Chain and Information Management, The Hang Seng University of Hong Kong, Hong Kong; Ho G.T.S., Department of Supply Chain and Information Management, The Hang Seng University of Hong Kong, Hong Kong; Wu C.H., Department of Supply Chain and Information Management, The Hang Seng University of Hong Kong, Hong Kong; Huang G.Q., HKU-ZIRI Lab for Physical Internet, Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong","Purpose: Accurate prediction of order demand across omni-channel supply chains improves the management's decision-making ability at strategic, tactical and operational levels. The paper aims to develop a predictive methodology for forecasting near-real-time e-commerce order arrivals in distribution centres, allowing third-party logistics service providers to manage the hour-to-hour fast-changing arrival rates of e-commerce orders better. Design/methodology/approach: The paper proposes a novel machine learning predictive methodology through the integration of the time series data characteristics into the development of an adaptive neuro-fuzzy inference system. A four-stage implementation framework is developed for enabling practitioners to apply the proposed model. Findings: A structured model evaluation framework is constructed for cross-validation of model performance. With the aid of an illustrative case study, forecasting evaluation reveals a high level of accuracy of the proposed machine learning approach in forecasting the arrivals of real e-commerce orders in three different retailers at three-hour intervals. Research limitations/implications: Results from the case study suggest that real-time prediction of individual retailer's e-order arrival is crucial in order to maximize the value of e-order arrival prediction for daily operational decision-making. Originality/value: Earlier researchers examined supply chain demand, forecasting problem in a broader scope, particularly in dealing with the bullwhip effect. Prediction of real-time, hourly based order arrivals has been lacking. The paper fills this research gap by presenting a novel data-driven predictive methodology. © 2020, Emerald Publishing Limited.","Data driven predictive analytics; E-commerce supply chain management; Machine learning; Real-time demand forecasting; Time series modelling","Electronic commerce; Forecasting; Fuzzy inference; Fuzzy neural networks; Fuzzy systems; Machine learning; Outsourcing; Predictive analytics; Supply chains; Adaptive neuro-fuzzy inference system; Design/methodology/approach; Distribution centres; Forecasting problems; Machine learning approaches; Operational decision making; Real-time prediction; Third party logistics; Decision making",{"$nulls":4},"Research Grants Council, University Grants Committee, RGC, UGC, (UGC/FDS14/E05/16)","The authors would like to thank Research Grants Council of Hong Kong for supporting this research under the Grant UGC/FDS14/E05/16.","Bogue R., Growth in e-commerce boosts innovation in the warehouse robot market, Industrial Robot: International Journal, 43, 6, pp. 583-587, (2016); 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Colla E., Lapoule P., E-commerce: exploring the critical success factors, International Journal of Retail and Distribution Management, 40, 11, pp. 842-864, (2012); Ducret R., Parcel deliveries and urban logistics: changes and challenges in the courier express and parcel sector in Europe—the French case, Research in Transportation Business and Management, 11, pp. 15-22, (2014); Ekici B.B., Aksoy U.T., Prediction of building energy needs in early stage of design by using ANFIS, Expert Systems with Applications, 38, 5, pp. 5352-5358, (2011); GuNeri A.F., Ertay T., YuCel A., An approach based on ANFIS input selection and modeling for supplier selection problem, Expert Systems with Applications, 38, 12, pp. 14907-14917, (2011); Guresen E., Kayakutlu G., Daim T.U., Using artificial neural network models in stock market index prediction, Expert Systems with Applications, 38, 8, pp. 10389-10397, (2011); Hubner A., Kuhn H., Wollenburg J., Last mile fulfilment and distribution in omni-channel grocery retailing: a strategic planning framework, International Journal of Retail and Distribution Management, 44, 3, pp. 228-247, (2016); 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Xing Y., Grant D.B., McKinnon A.C., Fernie J., The interface between retailers and logistics service providers in the online market, European Journal of Marketing, 45, 3, pp. 334-357, (2011); Yu Y., Wang X., Zhong R.Y., Huang G.Q., E-commerce logistics in supply chain management: implementations and future perspective in furniture industry, Industrial Management and Data Systems, 117, 10, pp. 2263-2286, (2017)","K.H. Leung; Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong; email: leungekh@hku.hk",null,"Emerald Group Holdings Ltd.",{"$nulls":5},2635577.0,null,"IMDSD",null,"English","Ind Manage Data Sys","Article","Final",null,"Scopus","2-s2.0-85085085304"]
["Lee S.-H.; Kwak M.-K.; Cha S.-S.","Lee, Su-Han (56053168100); Kwak, Min-Kyu (55985166100); Cha, Seong-Soo (57194775194)","56053168100; 55985166100; 57194775194","Consumers' choice for fresh food at online shopping in the time of covid19",2020.0,"Journal of Distribution Science",18.0,9.0,null,45.0,53.0,8.0,7.0,"10.15722/jds.18.9.202009.45","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85092030391&doi=10.15722%2fjds.18.9.202009.45&partnerID=40&md5=ab82640820b9ac6f476dfaf41bd5f2c2","Dept. of Food Science and Service, College of Bio-Convergence, Eulji University, South Korea; Dept. of Food and Nutrition, College of Bio-Convergence, Eulji University, South Korea","Lee S.-H., Dept. of Food Science and Service, College of Bio-Convergence, Eulji University, South Korea; Kwak M.-K., Dept. of Food and Nutrition, College of Bio-Convergence, Eulji University, South Korea; Cha S.-S., Dept. of Food Science and Service, College of Bio-Convergence, Eulji University, South Korea","Purpose: This study aims at investigating consumers' choice in online food purchasing behavior and the impact on repurchase for fresh food delivery which has recently shown rapid growth in Korea. The study focuses on the user experience factors af fecting satisfaction and intention to continuously use the online food market. Research design, data and methodology: The survey was conducted by 309 people who had purchased fresh food online, and the analysis was conducted using SPSS and AMOS. Structural Equation Modeling was used for the analysis for the verification of hypotheses. The factors that consumers value when ordering fresh food delivery services were defined as system quality, service quality, commodity quality, brand characteristics, and economics from the preceding study and the relationship between satisfaction and willingness to repurchase was verified. Results: When consumers purchase fresh food online, system quality, product quality, brand characteristics, and economics have had a significant impact on satisfaction. Meanwhile, of the five optional attributes of consumers, only economic efficiency has been verified to have a statistically significant impact on repurchase intentions. Conclusions: The results of the study suggested factors that consumers consider important when ordering fresh food online, providing basic data for companies to develop related strategies. © The Author(s).","COVID19; Delivery; Fresh food; Online shopping",{"$nulls":5},"Eulji University","* This paper was supported by Eulji University in 2020.","Anderson E.W., Fornell C., Lehmann D.R., Customer satisfaction, market share, and profitability: Findings from Sweden, Journal of Marketing, 58, 3, pp. 53-66, (1994); Bagozzi R.P., Yi Y., On the evaluation of structural equation models, Journal of the Academy of Marketing Science, 16, 1, pp. 74-94, (1988); Bearden W.O., Sharma S., Teel J.E., Sample size effects on chi square and other statistics used in evaluating causal models, Journal of Marketing Research, 19, 4, pp. 425-430, (1982); Cha S.S., Lee S.H., The effects of HMR selection attributes on repurchase intention by shopping channels, The Journal of Distribution Science, 16, 3, pp. 13-21, (2018); 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Ryu M.H., Undergraduate consumers' information needs according to purchase intention toward convenience store private brand foods, Family and Environment Research, 51, 6, pp. 623-635, (2013); San Yang C., Effect relationship and satisfaction factor of satisfaction level of environmental-friendly organic food brand on purchase and continuous repurchase, Journal of Basic Design & Art, 16, 2, pp. 281-295, (2015); Seo M.S., Park S.W., Shin C., The influences of shopping motives and e-store attributes of Chinese consumers on re-purchase intention, Korea Industrial Economics Association, 22, 3, pp. 1487-1511, (2009); Seo Y.O., Kim J.S., A survey on the consumer's satisfaction factors in internet shopping of agricultural products, Journal of Agriculture & Life Science, 43, 2, pp. 65-78, (2009); Song Y.E., Jeon S.H., Jeon M.S., The effect of mobile food delivery application usage factors on customer satisfaction and intention to reuse, Culinary Science & Hospitality Research, 23, 1, pp. 37-47, (2017); Wang I.W., Kang C.D., The influential analysis for customer preferencein the perceived quality of hypermarket PB, Journal of Korea Academia-Industrial Cooperation Society, 12, 5, pp. 2099-2107, (2011)","S.-S. Cha; Dept. of Food Science and Service, College of Bio-Convergence, Eulji University, South Korea; email: sscha@eulji.ac.kr",null,"Korea Distribution Science Association (KODISA)",{"$nulls":5},1.738311E7,null,null,null,"English","J. Distribution Science","Article","Final",null,"Scopus","2-s2.0-85092030391"]
["Alhujaylan A.I.; Hosny M.I.","Alhujaylan, Abeer I. (57208797563); Hosny, Manar I. (19638353300)","57208797563; 19638353300","Hybrid clustering algorithms with GRASP to construct an initial solution for the MVPPDP",2020.0,"Computers, Materials and Continua",62.0,3.0,null,1025.0,1051.0,26.0,2.0,"10.32604/cmc.2020.08742","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85082176716&doi=10.32604%2fcmc.2020.08742&partnerID=40&md5=83f05d015c24ce6266bcd41d5c26b1ea","Computer Science Department, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia; College of Computer, Qassim University, Buraydah, Saudi Arabia","Alhujaylan A.I., Computer Science Department, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia, College of Computer, Qassim University, Buraydah, Saudi Arabia; Hosny M.I., Computer Science Department, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia","Mobile commerce (m-commerce) contributes to increasing the popularity of electronic commerce (e-commerce), allowing anybody to sell or buy goods using a mobile device or tablet anywhere and at any time. As demand for e-commerce increases tremendously, the pressure on delivery companies increases to organise their transportation plans to achieve profits and customer satisfaction. One important planning problem in this domain is the multi-vehicle profitable pickup and delivery problem (MVPPDP), where a selected set of pickup and delivery customers need to be served within certain allowed trip time. In this paper, we proposed hybrid clustering algorithms with the greedy randomised adaptive search procedure (GRASP) to construct an initial solution for the MVPPDP. Our approaches first cluster the search space in order to reduce its dimensionality, then use GRASP to build routes for each cluster. We compared our results with state-of-the-art construction heuristics that have been used to construct initial solutions to this problem. Experimental results show that our proposed algorithms contribute to achieving excellent performance in terms of both quality of solutions and processing time. © 2020 Tech Science Press. All rights reserved.","Ant colony optimisation; Greedy randomised adaptive search procedure; K-means clustering algorithm; Metaheuristic algorithms; Multi-vehicle profitable pickup and delivery problem","Ant colony optimization; Customer satisfaction; Mobile commerce; Pickups; Profitability; Sales; Adaptive search; Construction heuristics; Hybrid clustering algorithm; Meta heuristic algorithm; Mobile commerce (m-commerce); Pickup and delivery problems; Quality of solution; Transportation plans; K-means clustering",{"$nulls":4},"Department of Sport and Recreation, Government of Western Australia, DSR","Acknowledgment: The authors would like to thank Deanship of scientific research for funding and supporting this research through the initiative of DSR Graduate Students Research Support (GSR).","Alhujaylan A.I., Hosny M.I., A GRASP-based solution construction approach for the multi-vehicle profitable pickup and delivery problem, International Journal of Advanced Computer Science and Applications, 10, 4, pp. 111-120, (2019); Aras N., Aksen D., Tugrul T.M., Selective multi-depot vehicle routing problem with pricing, Transportation Research Part C: Emerging Technologies, 19, 5, pp. 866-884, (2011); Archetti C., Speranza M.G., Vigo D., Chapter 10: Vehicle routing problems with profits, Vehicle Routing: Problems, Methods, and Applications, pp. 273-297, (2014); Baniamerian A., Bashiri M., Tavakkoli-Moghaddam R., Modified variable neighborhood search and genetic algorithm for profitable heterogeneous vehicle routing problem with cross-docking, Applied Soft Computing, 75, pp. 441-460, (2019); Barnhart C., Jin H., Vance P.H., Railroad blocking: A network design application, Operations Research, 48, 4, pp. 603-614, (2000); Bell J.E., Patrick R.M., Ant colony optimization techniques for the vehicle routing problem, Advanced Engineering Informatics, 18, 1, pp. 41-48, (2004); Bruck B.P., dos Santos A.G., Arroyo J.E.C., Hybrid metaheuristic for the single vehicle routing problem with deliveries and selective pickups, IEEE Congress on Evolutionary Computation, pp. 1-8, (2012); Coelho I.M., Munhoz P.L., Haddad M.N., Souza M.J., Ochi L.S., A hybrid heuristic based on general variable neighborhood search for the single vehicle routing problem with deliveries and selective pickups, Electronic Notes in Discrete Mathematics, 39, pp. 99-106, (2012); Coelho I.M., Munhoz P.L., Ochi L.S., Souza M.J., Bentes C., Et al., An integrated CPU-GPU heuristic inspired on variable neighbourhood search for the single vehicle routing problem with deliveries and selective pickups, International Journal of Production Research, 54, 4, pp. 945-962, (2016); Colorni A., Dorigo M., Maniezzo V., Distributed optimization by ant colonies, Proceedings of the First European Conference on Artificial Life, 142, pp. 134-142, (1991); Cornillier F., Boctor F.F., Laporte G., Renaud J., An exact algorithm for the petrol station replenishment problem, Journal of the Operational Research Society, 59, 5, pp. 607-615, (2008); Dahan F., El Hindi K., Mathkour H., AlSalman H., Dynamic flying ant colony optimization (DFACO) for solving the traveling salesman problem, Sensors, 19, 8, (2019); Diaz-Parra O., Ruiz-Vanoye O., Bernabe J.A., Fuentes-Penna B., Fuentes-Penna A., Et al., A survey of transportation problems, Journal of Applied Mathematics, 2014, pp. 1-17, (2014); Du H., Data Mining Techniques and Applications. An Introduction, (2010); Duhamel C., Lacomme P., Prins C., Prodhon C., A GRASP×ELS approach for the capacitated location-routing problem, Computers & Operations Research, 37, 11, pp. 1912-1923, (2010); Feo T.A., Resende M.G., Greedy randomized adaptive search procedures, Journal of Global Optimization, 6, 2, pp. 109-133, (1995); Gansterer M., Hartl R., Vetschera R., The cost of incentive compatibility in auction-based mechanisms for carrier collaboration, Networks, 73, 4, pp. 490-514, (2019); Gansterer M., Kucuktepe M., Hartl R.F., The multi-vehicle profitable pickup and delivery problem, OR Spectrum, 39, 1, pp. 303-319, (2017); Gribkovskaia I., Laporte G., Shyshou A., The single vehicle routing problem with deliveries and selective pickups, Computers & Operations Research, 35, 9, pp. 2908-2924, (2008); Gutierrez-Jarpa G., Desaulniers G., Laporte G., Marianov V., A branch- and-price algorithm for the vehicle routing problem with deliveries, selective pickups and time windows, European Journal of Operational Research, 206, 2, pp. 341-349, (2010); Haddad M., An Efficient Heuristic for One-to-One Pickup and Delivery Problems, (2017); Ho S.C., Szeto W.Y., GRASP with path relinking for the selective pickup and delivery problem, Expert Systems with Applications, 51, pp. 14-25, (2016); Jafar O.M., Sivakumar R., Ant-based clustering algorithms: A brief survey, International Journal of Computer Theory and Engineering, 2, 5, (2010); Kucuktepe M., A General Variable Neighbourhood Search Algorithm for the Multi-Vehicle Profitable Pickup and Delivery Problem, (2014); Layeb A., Ammi M., Chikhi S., A GRASP algorithm based on new randomized heuristic for vehicle routing problem, Journal of Computing and Information Technology, 21, 1, pp. 35-46, (2013); Liao X.L., Ting C.K., An evolutionary approach for the selective pickup and delivery problem, IEEE Congress on Evolutionary Computation, pp. 1-8, (2010); Lin C., Choy K.L., Ho G.T., Chung S.H., Lam H.Y., Survey of green vehicle routing problem: Past and future trends, Expert Systems with Applications, 41, 4, pp. 1118-1138, (2014); MacQueen J., Some methods for classification and analysis of multivariate observations, Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability, pp. 281-297, (1967); Marinakis Y., Multiple phase neighborhood search-GRASP for the capacitated vehicle routing problem, Expert Systems with Applications, 39, 8, pp. 6807-6815, (2012); Prive J., Renaud J., Boctor F., Laporte G., Solving a vehicle-routing problem arising in soft-drink distribution, Journal of the Operational Research Society, 57, 9, pp. 1045-1052, (2006); Qiu X., Feuerriegel S., Neumann D., Making the most of fleets: A profit-maximizing multi-vehicle pickup and delivery selection problem, European Journal of Operational Research, 259, 1, pp. 155-168, (2017); Saha J., An algorithm for bus scheduling problems, Journal of the Operational Research Society, 21, 4, pp. 463-474, (1970); Talbi E.G., Metaheuristics: From Design to Implementation, (2009); Ting C.K., Liao X.L., The selective pickup and delivery problem: Formulation and a memetic algorithm, International Journal of Production Economics, 141, 1, pp. 199-211, (2013); Toth P., Vigo D., Vehicle routing: Problems, methods, and applications, Society for Industrial and Applied Mathematics, (2014); Wen M., Larsen J., Clausen J., Cordeau J.F., Laporte G., Vehicle routing with cross-docking, Journal of the Operational Research Society, 60, 12, pp. 1708-1718, (2009); Yan S., Wang S., Wu M.W., A model with a solution algorithm for the cash transportation vehicle routing and scheduling problem, Computers & Industrial Engineering, 63, 2, pp. 464-473, (2012); Zhu C., Hu J., Wang F., Xu Y., Cao R., On the tour planning problem, Annals of Operations Research, 192, 1, pp. 67-86, (2012)","A.I. Alhujaylan; Computer Science Department, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia; email: abeer.alhujaylan@gmail.com",null,"Tech Science Press",{"$nulls":5},1.5462218E7,null,null,null,"English","Comput. Mater. Continua","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85082176716"]
["Bowden Z.E.; Ragsdale C.T.","Bowden, Zachary E. (57201274036); Ragsdale, Cliff T. (7003885887)","57201274036; 7003885887","The general pickup and delivery problem with backtracking restrictions",2020.0,"International Journal of Operational Research",39.0,4.0,null,539.0,561.0,22.0,2.0,"10.1504/IJOR.2020.111342","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85096810600&doi=10.1504%2fIJOR.2020.111342&partnerID=40&md5=a65f7e4f99e0fb30652fc53d753dc057","Virginia Tech Transportation Institute, 3500 Transportation Research Plaza, Blacksburg, 24061, VA, United States; Department of Business Information Technology, Pamplin College of Business, Virginia Tech, Pamplin Hall, 880 West Campus Drive, Blacksburg, 24061, VA, United States","Bowden Z.E., Virginia Tech Transportation Institute, 3500 Transportation Research Plaza, Blacksburg, 24061, VA, United States; Ragsdale C.T., Department of Business Information Technology, Pamplin College of Business, Virginia Tech, Pamplin Hall, 880 West Campus Drive, Blacksburg, 24061, VA, United States","This paper introduces a model for the general pickup and delivery problem (GPDP) that provides a novel approach to limit the amount of backtracking allowed in the solution. This problem is motivated by the increase in peer-to-peer vehicle transactions via online marketplaces such as eBay and an associated increase in the direct consumer procurement of shipping services for transporting recently purchased vehicles. We approach this problem in the context of a profit seeking objective while considering the cognitive processes and behavioural preferences of the driver as important to the ultimate solution of the routing problem. We offer a method for producing a set of good solutions that are differentiated based on backtracking characteristics of the directional flow of the route. Copyright © 2020 Inderscience Enterprises Ltd.","Backtracking; Behavioural logistics; PDP; Profit maximisation; Vehicle routing",{"$nulls":7},"Abbes I., Abid C., Chabchoub H., Dhiaf M.M., Vehicle routing problem in real case application, International Journal of Operational Research, 20, 4, (2014); Amponsah S.K., Salhi S., The investigation of a class of capacitated arc routing problems: the collection of garbage in developing countries, Waste Management, 24, 7, pp. 711-721, (2004); Baldacci R., Mingozzi A., Roberti R., Recent exact algorithms for solving the vehicle routing problem under capacity and time window constraints, European Journal of Operational Research, 218, 1, pp. 1-6, (2012); Baraniuk R., Davenport M., Duarte M., Hedge C., An Introduction to Compressive Sensing, (2014); Berbeglia G., Cordeau J-F., Gribkovskaia I., Laporte G., Static pickup and delivery problems: a classification scheme and survey, TOP, 15, 1, pp. 1-31, (2007); Camm J.D., Raturi A.S., Tsubakitani S., Cutting big M down to size, Interfaces, 20, 5, pp. 61-66, (1990); Chen A-P., Hwang C-H., Tan G.L.H., Lin C-Y., Development of a decision support system for service delivery, Computational Economics, 6, 2, pp. 115-129, (1993); Chen K-P., Lai H., Yu Y-T., The seller’s listing strategy in online auctions: evidence from eBay, International Journal of Industrial Organization, 56, pp. 107-144, (2018); Christofides N., Mingozzi A., Toth P., The vehicle routing problem, Combinatorial Optimization, pp. 315-338, (1979); Cordeau J-F., Laporte G., Ropke S., Recent models and algorithms for one-to-one pickup and delivery problems, The Vehicle Routing Problem: Latest Advances and New Challenges, Operations Research/Computer Science Interfaces, pp. 327-357, (2008); Dantzig G.B., Ramser J.H., The truck dispatching problem, Management Science, 6, 1, pp. 80-91, (1959); eBay Marketplaces Fast Facts At-A-Glance (Q3 2014), (2015); El Hachemi N., Gendreau M., Rousseau L-M., A heuristic to solve the synchronized log-truck scheduling problem, Computers & Operations Research, Transport Scheduling, 40, 3, pp. 666-673, (2013); Estrada-Romeu M., Robuste F., Stopover and hub-and-spoke shipment strategies in less-than-truckload carriers, Transportation Research Part E: Logistics and Transportation Review, 76, pp. 108-121, (2015); Faiz S., Krichen S., Inoubli W., A DSS based on GIS and Tabu search for solving the CVRP: the Tunisian case, The Egyptian Journal of Remote Sensing and Space Science, 17, 1, pp. 105-110, (2014); Franzese O., Davidson D., Effect of Weight and Roadway Grade on the Fuel Economy of Class-8 Freight Trucks, (2011); Gino F., Pisano G., Toward a theory of behavioral operations, Manufacturing & Service Operations Management, 10, 4, pp. 676-691, (2008); Golden B.L., Raghavan S., Wasil E.A., The Vehicle Routing Problem: Latest Advances and New Challenges, (2008); Gounaris C.E., Wiesemann W., Floudas C.A., The robust capacitated vehicle routing problem under demand uncertainty, Operations Research, 61, 3, pp. 677-693, (2013); Hu X., Sun L., Liu L., A PAM approach to handling disruptions in real-time vehicle routing problems, Decision Support Systems, 54, 3, pp. 1380-1393, (2013); Katayama N., Yurimoto S., The load planning problem for less-than-truckload motor: carriers and a solution approach, Developments in Logistics and Supply Chain Management, pp. 240-249, (2016); Ke G.Y., Bookbinder J.H., Coordinating the discount policies for retailer, wholesaler, and less-than-truckload carrier under price-sensitive demand: a tri-level optimization approach, International Journal of Production Economics, 196, pp. 82-100, (2018); Krichen S., Faiz S., Tlili T., Tej K., Tabu-based GIS for solving the vehicle routing problem, Expert Systems with Applications, 41, 14, pp. 6483-6493, (2014); Mendoza J.E., Medaglia A.L., Velasco N., An evolutionary-based decision support system for vehicle routing: the case of a public utility, Decision Support Systems, Wireless in the Healthcare, 46, 3, pp. 730-742, (2009); Mourao M.C., Amado L., Heuristic method for a mixed capacitated arc routing problem: a refuse collection application, European Journal of Operational Research, Applications of Mathematical Programming Models, 160, 1, pp. 139-153, (2005); Naini S.G.J., Paydar M.M., Jouzdani J., Fathian M., Fuzzy stochastic linear programming-based approach for multiple departures single destination multiple travelling salesman problem, International Journal of Operational Research, 17, 4, (2013); Newberry P.W., The effect of competition on eBay, International Journal of Industrial Organization, 40, pp. 107-118, (2015); Nuortio T., Kytojoki J., Niska H., Braysy O., Improved route planning and scheduling of waste collection and transport, Expert Systems with Applications, 30, 2, pp. 223-232, (2006); Perrier N., Langevin A., Amaya C-A., Vehicle routing for urban snow plowing operations, Transportation Science, 42, 1, pp. 44-56, (2008); Perrier N., Langevin A., Campbell J.F., A survey of models and algorithms for winter road maintenance. Part IV: vehicle routing and fleet sizing for plowing and snow disposal, Computers & Operations Research, 34, 1, pp. 258-294, (2007); Ramaekers K., Caris A., Maes T., Janssens G., Pickup and delivery selection: problem formulation and extension to problem variants, Information Technology and Management Science, 18, 1, (2015); Ropke S., Cordeau J-F., Branch and cut and price for the pickup and delivery problem with time windows, Transportation Science, 43, 3, pp. 267-286, (2009); Salhi S., Nagy G., A cluster insertion heuristic for single and multiple depot vehicle routing problems with backhauling, The Journal of the Operational Research Society, 50, 10, pp. 1034-1042, (1999); Savelsbergh M.W.P., Sol M., The general pickup and delivery problem, Transportation Science, 29, 1, pp. 17-29, (1995); Savsar M., Alnaqi J., Atash M., Scheduling and routing of city buses for a public transport company, International Journal of Operational Research, 16, 3, (2013); Schonberger J., Kopfer H., Mattfeld D.C., A combined approach to solve the pickup and delivery selection problem, Operations Research Proceedings 2002, pp. 150-155, (2003); Stefanski M.M., Beulens A.J.M., Hoefnagels J.P., From Vehicle Routing Packages Towards Routing DSS, (1989); Sun Y., Decision Making Process and Factors Routing, (2013); Toledo T., Sun Y., Rosa K., Ben-Akiva M., Flanagan K., Sanchez R., Spissu E., Decision-making process and factors affecting truck routing, Freight Transport Modelling, pp. 233-248, (2013); Toth P., Vigo D., Vehicle Routing: Problems, Methods, and Applications, (2014); uShip.com – About, (2015); Wang X., Battarra M., Golden B., Wasil E., Vehicle routing and scheduling, Routledge Handbook of Transportation, pp. 238-256, (2016); Xiao Y., Zhao Q., Kaku I., Xu Y., Development of a fuel consumption optimization model for the capacitated vehicle routing problem, Computers & Operations Research, 39, 7, pp. 1419-1431, (2012); Zhang B., Yao T., Friesz T.L., Sun Y., A tractable two-stage robust winner determination model for truckload service procurement via combinatorial auctions, Transportation Research Part B: Methodological, 78, pp. 16-31, (2015)","Z.E. Bowden; Virginia Tech Transportation Institute, Blacksburg, 3500 Transportation Research Plaza, 24061, United States; email: zbowden@vt.edu",null,"Inderscience Publishers",{"$nulls":5},1.7457645E7,null,null,null,"English","Int. J. Oper. Res.","Article","Final",null,"Scopus","2-s2.0-85096810600"]
["Naughton B.","Naughton, Barry (7005513752)",7.005513752E9,"Chinese industrial policy and the digital silk road: The case of Alibaba in Malaysia",2020.0,"Asia Policy",15.0,1.0,null,23.0,39.0,16.0,14.0,"10.1353/asp.2020.0006","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85091207771&doi=10.1353%2fasp.2020.0006&partnerID=40&md5=dba47ff35501c0ca3542102f304348b5","University of California, San Diego, United States","Naughton B., University of California, San Diego, United States","This essay demonstrates how China's domestic industrial policies provide important indirect support for the Digital Silk Road, as shown by Alibaba's activities in Malaysia. main argument In recent years, China's domestic industrial policies have expanded dramatically. Three trends are especially important in shaping the impact of domestic policies on the Digital Silk Road. First, recent industrial policies have increasingly focused on technologies centered around artificial intelligence, 5G telecommunications, and smart networks. Second, while policies are still state-led, they rely on close partnerships with private firms such as Alibaba, Baidu, and Tencent. Third, a new wave of regional policies aims to create urban clusters that will be more efficient and less congested than regions dominated by single large cities. Each of these trends can be witnessed in the activities of Alibaba in Malaysia. Already a pioneer of smart city development in China, Alibaba has begun implementing its City Brain program in Kuala Lumpur, Malaysia, complementary to its e-commerce and logistics initiatives in Southeast Asia. While Malaysia is a front runner in these activities, similar dynamics are at work throughout the region. There are powerful complementarities created by dynamic private Chinese businesses, the large Chinese market, and the availability of finance for China-supported infrastructure programs. policy implications • The U.S. and other nations committed to open standards need to recognize that a few Chinese companies, like Alibaba, have already made substantial inroads into Southeast Asia and are purveying an attractive business model. • The U.S. and Japan need to improve the quality of their game in Southeast Asia. It cannot be presumed that a backlash will develop against Chinese government-dominated initiatives or corruption. On the contrary, attractive, concrete, low-cost alternatives must be offered to the countries, businesses, and people of Southeast Asia. • The ultimate shape of smart infrastructure is not yet known, and the potential for heightened transparency and more responsive systems is large. Many countries, and specifically those in Southeast Asia, have an interest in open systems that increase their options and do not tie them to a single business partner. The U.S. needs to develop a comprehensive program to strengthen the open global system and provide these countries with secure access to it. © The National Bureau of Asian Research, Seattle, Washington. © 2020 National Bureau of Asian Research.","Artificial intelligence; Industrial policy; Malaysia; Smart cities",{"$nulls":7},"Ling C., Naughton B., An Institutionalized Policy-making Mechanism: China's Return to Techno-industrial Policy, Research Policy, 45, 10, pp. 2138-2152, (2016); Lee K.-F., AI Superpowers: China, Silicon Valley, and the New World Order, (2018); Naughton B., The Financialisation of the State Sector in China, China's Economic Modernisation and Structural Changes: Essays in Honour of John Wong, pp. 167-185, (2019); Toh M., Erasmus L., Alibaba's 'City Brain' Is Slashing Congestion in Its Hometown, (2019); Linden G., China Standard Time: A Study in Strategic Industrial Policy, Business and Politics, 6, 3, pp. 1-26, (2004); Luo C., One Platform to Rule Them All: The Brains behind Cainiao Network (PI), (2016); Beall A., In China, Alibaba's Data-Hungry AI Is Controlling (and Watching) Cities, Wired, (2018); Zhou M., Mahathir: 'We Have to Go to the Chinese' for Infrastructure, Nikkei Asian Review, (2019)","B. Naughton; University of California, San Diego, United States; email: bnaughton@ucsd.edu",null,"National Bureau of Asian Research",{"$nulls":5},1.5590968E7,null,null,null,"English","Asia Policy","Article","Final",null,"Scopus","2-s2.0-85091207771"]
["Hood N.; Urquhart R.; Newing A.; Heppenstall A.","Hood, Nick (56971057800); Urquhart, Ryan (57214988418); Newing, Andy (55602621600); Heppenstall, Alison (9243300500)","56971057800; 57214988418; 55602621600; 9243300500","Sociodemographic and spatial disaggregation of e-commerce channel use in the grocery market in Great Britain",2020.0,"Journal of Retailing and Consumer Services",55.0,null,102076.0,null,null,null,44.0,"10.1016/j.jretconser.2020.102076","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85079683925&doi=10.1016%2fj.jretconser.2020.102076&partnerID=40&md5=fc46cf273747488b7d09f51d4cf4927a","School of Geography, University of Leeds, United Kingdom; Leeds Institute for Data Analytics, University of Leeds, United Kingdom; Alan Turing Institute, British Library, Euston Road, London, United Kingdom","Hood N., School of Geography, University of Leeds, United Kingdom, Leeds Institute for Data Analytics, University of Leeds, United Kingdom; Urquhart R., School of Geography, University of Leeds, United Kingdom, Leeds Institute for Data Analytics, University of Leeds, United Kingdom; Newing A., School of Geography, University of Leeds, United Kingdom; Heppenstall A., School of Geography, University of Leeds, United Kingdom, Leeds Institute for Data Analytics, University of Leeds, United Kingdom, Alan Turing Institute, British Library, Euston Road, London, United Kingdom","The UK Grocery e-commerce industry is amongst the most developed in the world with an estimated value of £11.4Billion in 2018. Assisted by technological developments, the market has experienced dramatic growth over the past two decades. Grocery retailers have invested in online infrastructure and home delivery networks. As a result, consumers have a range of options which enable them to shop interchangeably between in-store and online channels. The proliferation of new grocery shopping channels such as home delivery or ‘click and collect’ (collect in store or collection from a non-store collection point), coupled with changing consumer behaviour, provides new challenges for retailers in understanding consumer dynamics in this market. This paper explores consumer behaviour and preferences for e-commerce in the grocery retail industry in Great Britain (GB) using a survey of 19,033 respondents from the major market research company YouGov. Respondents were asked a range of questions around uptake and channel usage in the grocery e-commerce sector. The survey presents a novel opportunity to analyse self-reported consumer behaviour in GB, with survey responses attached to key sociodemographic and locational information. We find that sociodemographics are an important driver of groceries e-commerce usage and channel choice, with females, more affluent households and those in the 25–44 age group most likely to use home delivery, corroborating previous research. Contrasting previous research, we also find statistically significant evidence of relatively high values of home delivery use among over-55s. Whilst overall usage is lower, we find a particular affinity to collection facilities among males and skilled manual workers. Spatially, we find evidence of both the innovation-diffusion theory and the efficiency theory at both a national and local authority district level, using a brief case study of Yorkshire and the Humber. These insights can support grocery retailers as they further develop costly localised infrastructure to support e-commerce. It could also assist retailers in understanding the localised drivers of channel choice as they seek to shift demand from home delivery (with high costs faced by the retailer in relation to the ‘last mile’) to click and collect (in which the customer faces the costs associated with the last mile). © 2020","click and collect; consumer behaviour; e-commerce; grocery; home delivery; spatial analysis","United Kingdom; consumption behavior; electronic commerce; innovation; preference behavior; service sector; spatial analysis; supermarket; theoretical study",{"$nulls":4},"Consumer Data Research Centre; Economic and Social Research Council, ESRC, (CDRC 147, ES/L011840/1, ES/L011891/1)","The data for this research have been provided by the Consumer Data Research Centre, an ESRC Data Investment, under project ID CDRC 147, ES/L011840/1; ES/L011891/1. We are grateful for the valuable comments and suggestions raised by two anonymous reviewers.","Alexiou A., The Great British Geography of internet Use and engagement, (2018); Anderson W.P., Chatterjee L., Lakshmanan T.R., E-commerce, transportation, and economic geography, Growth Change, 34, 4, pp. 415-432, (2003); Armstrong A., Morrisons to roll out home deliveries nationwide after Ocado contract wrangling, The Telegraph, (2016); Aspray W., Royer G., Ocepek M.G., Anatomy of a dot-com failure: the case of online grocer Webvan, Food in the Internet Age, pp. 25-35, (2013); Batty E.N., Global Online FMCG Sales Grow by 13%, Kantar World Pannel, (2018); Beck N., Rygl D., Categorization of multiple channel retailing in multi-, cross-, and omni-channel for retailers and retailing, J. Retailing Consum. Serv., 27, pp. 170-178, (2015); Beckers J., Cardenas I., Verhetsel A., Identifying the geography of online shopping adoption in Belgium, J. Retailing Consum. 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Rec., 2383, 1, pp. 18-26, (2013); Clark T., Ping Chang S., A history of Tesco: the rise of Britain's biggest supermarket, The Telegraph, (2014); Clarke G., Eyre H., Guy C., Deriving indicators of access to food retail provision in British cities: studies of Cardiff, Leeds and Bradford, Urban Stud., 39, 11, pp. 2041-2060, (2002); Clarke G., Thompson C., Birkin M., The emerging geography of e-commerce in British retailing, Reg. Sci. Reg. Stud., 2, 1, pp. 371-391, (2015); Davies A., Dolega L., Arribas-Bel D., Buy online collect in-store: exploring grocery click & collect using a national case study, Int. J. Retail Distrib. Manag., 47, 3, pp. 278-291, (2019); Department for Environment, Food & Rural Affairs, 2011 Rural-Urban Classification of Local Authorities and other geographies, (2014); Doherty N.F., Ellis-Chadwick F., Hackney R., Grant K., Birtwistle G., The UK grocery business: towards a sustainable model for virtual markets, Int. J. Retail Distrib. Manag., 34, 4-5, pp. 354-368, (2006); Elms J., Kervenoael R., Hallsworth A., Internet or store? An ethnographic study of consumers' internet and store-based grocery shopping practices, J. Retailing Consum. Serv., 32, pp. 234-243, (2016); Eriksson E., Norrman A., Kembro J., Contextual adaptation of omni-channel grocery retailers’ online fulfilment centres, Int. J. Retail Distrib. Manag., 47, 12, pp. 1232-1250, (2019); Farag S., Weltevreden J., van Rietbergen T., Dijst M., van Oort F., E-shopping in The Netherlands: does geography matter?, Environ. Plann. Plann. Des., 33, 1, pp. 59-74, (2006); Fernie J., McKinnon A., The development of e-tail logistics, Kogan Page, London, Logistics and Retail Management: Emerging Issues and New Challenges in the Retail Supply Chain, pp. 207-232, (2009); Friendly M., Mosaic displays for multi-way contingency tables, J. Am. Stat. 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Introduction to the special issue on multi-channel retailing, J. Retailing, 91, 2, (2015); Vyt D., Jara M., Cliquet G., Grocery pickup creation of value: customers' benefits vs. spatial dimension, J. Retailing Consum. Serv., 39, pp. 145-153, (2017); Warf B., Segueways into cyberspace: multiple geographies of the digital divide, Environ. Plann. B, 28, pp. 3-19, (2010); Weltevreden J.W., Substitution or complementarity? How the Internet changes city centre shopping, J. Retailing Consum. Serv., 14, 3, pp. 192-207, (2007); Wollenburg J., From bricks-and-mortar to bricks-and-clicks, Int. J. Phys. Distrib. Logist. Manag., 48, 4, pp. 415-438, (2018); Wrigley N., Food deserts' in British cities: policy context and research priorities, Urban Stud., 39, 11, pp. 2029-2040, (2002); YouGov, Panel methodology, (2019); Zhou Y., Wang X.C., Explore the relationship between online shopping and shopping trips: an analysis with the 2009 NHTS data, Transport. Res. Pol. Pract., 70, pp. 1-9, (2014); Zissis D., Aktas E., Bourlakis M., Collaboration in urban distribution of online grocery orders, Int. J. Logist. Manag., 29, 4, pp. 1196-1214, (2018); Zook M.A., The web of production: the economic geography of commercial Internet content production in the United States, Environ. Plann., 44, pp. 1679-1696, (2000)","N. Hood; School of Geography, University of Leeds, United Kingdom; email: n.a.hood@leeds.ac.uk",null,"Elsevier Ltd",{"$nulls":5},9696989.0,null,null,null,"English","J. Retail. Consum. Serv.","Article","Final","All Open Access; Green Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85079683925"]
["Dragomirov N.","Dragomirov, Nikolay (57222158937)",5.7222158937E10,"E-Commerce Platforms and Supply Chain Management – Functionalities Study",2020.0,"Economic Alternatives",26.0,2.0,null,250.0,261.0,11.0,4.0,"10.37075/EA.2020.2.04","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85101674134&doi=10.37075%2fEA.2020.2.04&partnerID=40&md5=9fb3eb7ad38769355fa8208a8b231185","University of National and World Economy, Department of Logistics and Supply Chains, Sofia, Bulgaria","Dragomirov N., University of National and World Economy, Department of Logistics and Supply Chains, Sofia, Bulgaria","The rise of e-commerce worldwide represents an indisputable and sustainable process of transformation of previously known market relationships. It has led to the development and continuous improvement of a number of processes related to the efficient management of material flows in the supply chain. E-commerce platforms can in general be considered as specialised software solutions that, in addition to presenting products in digital space, can play a significant role in organising logistics, marketing and financial processes. This complex logistics management problem can be studied through several indicators related to integration of the inner supply chain and to the management of relationships with product suppliers, buyers and trade partners, and logistics services providers. The article outlines the results of a study of the logistics functionalities of some leading e-commerce platforms and reveals some trends in their evolution and their readiness for supporting some of the supply chain management processes. © 2020, University of National and World Economy. All rights reserved.","e-commerce; logistics; SCM",{"$nulls":7},"Atanasov B., Pricing in Omni-channels, Omni-channel trading and innovations, pp. 151-155, (2016); The Evolution of eCommerce Over the Last Decade [online], Augment News, (2016); (2019); What is logistics and how does it apply to ecommerce? 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Exploring customer value in e-commerce last mile delivery, Journal of Business Research, 88, pp. 421-427, (2018); Best Warehouse Management System, (2018); Wu P.-J., Lin K.-C., Unstructured big data analytics for retrieving e-commerce logistics knowledge, Telematics and Informatics, 35, 1, pp. 237-244, (2018); Yu Y., Et al., E-commerce Logistics in Supply Chain Management: Practice Perspective, Procedia CIRP, 52, pp. 179-185, (2016); Zeng L., Bolz T., Analysis of the logistics efficiency in e-commerce online vs. multichannel, BIT, 1, pp. 62-68, (2017); Zurek J., E-commerce influence on changes in logistics processes, Logforum, 11, 2, pp. 129-138, (2015)",null,null,"University of National and World Economy",{"$nulls":5},1.3127462E7,null,null,null,"English","Econ. Altern.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85101674134"]
["Pérez-Amaral T.; Valarezo A.; López R.; Garín-Muñoz T.; Herguera I.","Pérez-Amaral, Teodosio (6505954111); Valarezo, Angel (57200541703); López, Rafael (56672367900); Garín-Muñoz, Teresa (6507062892); Herguera, Iñigo (6506396448)","6505954111; 57200541703; 56672367900; 6507062892; 6506396448","E-commerce by individuals in Spain using panel data 2008–2016",2020.0,"Telecommunications Policy",44.0,4.0,101888.0,null,null,null,16.0,"10.1016/j.telpol.2019.101888","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85074402648&doi=10.1016%2fj.telpol.2019.101888&partnerID=40&md5=c0d075960ea1131958f398e32ec35044","Instituto Complutense de Análisis Económico, ICAE, Spain; Universidad Complutense de Madrid, UCM, Spain; Universidad Nacional de Educación a Distancia, UNED, Spain","Pérez-Amaral T., Instituto Complutense de Análisis Económico, ICAE, Spain, Universidad Complutense de Madrid, UCM, Spain; Valarezo A., Instituto Complutense de Análisis Económico, ICAE, Spain, Universidad Complutense de Madrid, UCM, Spain; López R., Instituto Complutense de Análisis Económico, ICAE, Spain, Universidad Complutense de Madrid, UCM, Spain; Garín-Muñoz T., Universidad Nacional de Educación a Distancia, UNED, Spain; Herguera I., Instituto Complutense de Análisis Económico, ICAE, Spain, Universidad Complutense de Madrid, UCM, Spain","Digital technologies sometimes create digital divides. One of the remedies for certain divides in Europe is the creation of the Digital Single Market, of which e-commerce is one of the main elements. The focus of this work is e-commerce in Spain. The current study improves on existing international literature by using a large and representative panel data set on individual consumers, with 133,420 observations for the period 2008–2016. Moreover, it uses economic models and employs a variety of panel techniques. This paper measures digital e-commerce divides and their evolution along time. Next, a model that incorporates previously neglected explanatory variables, at the individual level, such as income and digital skills, is formulated. Individual demand models are estimated using panel logistic regression techniques. This allows quantifying the impact of each of the socioeconomic and geographic characteristics on the adoption of the service. Newly incorporated variables are significant as well as age, education, gender and geographical and time variables. The results allow novel regional comparisons. Policy recommendations are derived, suggesting effective and affordable measures targeted at specific socio-demographic groups. © 2019 Elsevier Ltd","Dynamic model; E-commerce; E-commerce digital divide; Heckman selection model; ICT-H survey; Individual annual panel data; Individual consumers; Logistic regression","Dynamic models; Regression analysis; Digital divide; Individual consumers; Logistic regressions; Panel data; Selection model; Electronic commerce",{"$nulls":4},"Comunidad de Madrid, (PRODECON-CM HM S2015/HUM-3491)","Presented at the ITS European Conference, 2019, Helsinki. Research funded by the Autonomous Community of Madrid, Spain. Project: Finance, Innovation, and Strategies: Economic Analysis of Business Productivity and its Determinants (PRODECON-CM HM S2015/HUM-3491), 2016–2018.","Artle R., Averous C., The telephone system as a public good: Static and Dynamic Aspects, 4, pp. 89-100, (1973); Bach M.P., Zoroja J., Vuksic V.B., Determinants of firms' digital divide: A review of recent research, Procedia Technology, 9, pp. 120-128, (2013); Barzilai-Nahon K., Gaps & Bits: Conceptualizing Measurements for digital divide/s, The Information Society, 22, 5, pp. 269-278, (2006); Biagi F., Falk M., The impact of ICT and e-commerce on employment in Europe, Journal of Policy Modeling, 39, 1, pp. 1-18, (2017); Billon M., Lera-Lopez F., Marco R., ICT use by households and firms in the EU: Links and determinants from a multivariate perspective, Review of World Economics, 152, 4, pp. 629-654, (2016); Bose R., Luo X., Integrative framework for assessing firms' potential to undertake Green IT initiatives via virtualization – a theoretical perspective, The Journal of Strategic Information Systems, 20, 1, pp. 38-54, (2011); Burgos C., Cortes J.-C., Shaikhet L., Villanueva R.-J., A nonlinear dynamic age-structured model of e-commerce in Spain: Stability analysis of the equilibrium by delay and stochastic perturbations, Commun Nonlinear Sci Numer Simulat, 64, pp. 149-158, (2018); Cerno L., Perez-Amaral T., Demand for internet access and use in Spain, Governance of Communication Networks, connecting societies and markets with IT, (2006); Cerno L., Perez-Amaral T., E-commerce use in Spain, Telecommunication markets: Drivers and impediments (157–172), (2009); Correa M., Garcia J.R., Tabanera A., “Comercio electrónico y hábitos de consumo en España: La importancia de la banca on-line” BBVA research, (2015); Demoussis M., Giannakopoulos N., Facets of the digital divide in Europe: Determination and extent of internet use, Economics of Innovation and New Technology, 15, pp. 235-246, (2006); Digital economy and society index country profile (DESI) 2017: Profile of Spain, (2017); Digital economy and society index country profile (DESI) 2018: Profile of Spain, (2018); Human capital and digital skills, (2019); The digital economy and society index (DESI), (2019); Eurostat, ICT usage in households and by individuals from Eurostat, (2017); Fairlie R.W., Race and the digital divide, contributions to economic analysis and policy, The Berkeley Electronic Journals, 3, pp. 1-38, (2004); Fundacion B.B.V.A., “Uso de Internet en España y la Unión Europea” Esenciales IVIE 29/2018, (2018); Garin-Munoz T., Lopez R., Perez-Amaral T., Herguera I., Valarezo A., Models for individual adoption of eCommerce, eBanking and eGovernment in Spain, Telecommunications Policy, 43, pp. 100-111, (2019); Garin-Munoz T., Perez-Amaral T., “Factores determinantes del comercio electrónico en España”. Boletín económico de ICE, Información Comercial Española, 3016, pp. 51-65, (2011); Hacker K.L., Mason S.M., Ethical gaps in studies of the digital divide, Ethics and Information Technology, 5, 2, pp. 99-115, (2003); Hackl F., Kummer M.E., Winter-Ebmer R., Zulehner C., Market structure and market performance in E-commerce, European Economic Review, 68, pp. 199-218, (2014); Hilbert M., The end justifies the definition: The manifold outlooks on the digital divide and their practical usefulness for policy-making, Telecommunications Policy, 35, pp. 715-736, (2011); INE, Survey on equipment and use of information and communication technologies in households, Telecommunications Policy, 35, pp. 715-736, (2017); ICT facts and figures, (2016); Lera-Lopez F., Billon M., Gil M., Determinants of internet use in Spain, Economics of Innovation and New Technology, 20, 2, pp. 127-152, (2011); Limayem M., Khalifa M., Frini A., What makes consumers buy from internet? 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Valarezo; Instituto Complutense de Análisis Económico, ICAE, Spain; email: angel.valarezo.unda@ucm.es",null,"Elsevier Ltd",{"$nulls":5},3085961.0,null,"TEPOD",null,"English","Telecommun Policy","Article","Final",null,"Scopus","2-s2.0-85074402648"]
["Lahkani M.J.; Wang S.; Urbański M.; Egorova M.","Lahkani, Marjaneh Jahangiri (57217094159); Wang, Shouyang (35195168500); Urbański, Mariusz (57203835101); Egorova, Mariya (56613056000)","57217094159; 35195168500; 57203835101; 56613056000","Sustainable B2B E-commerce and blockchain-based supply chain finance",2020.0,"Sustainability (Switzerland)",12.0,10.0,3968.0,null,null,null,97.0,"10.3390/SU12103968","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85086163291&doi=10.3390%2fSU12103968&partnerID=40&md5=65a76b9ad0ce00a7dad2adfcacc6ef8a","School of Economics and Management, University of Chinese Academy of Sciences, Haidian District, Beijing, 100190, China; Faculty of Civil Engineering, Czestochowa University of Technology, Dabrowskiego 69, Czestochowa, 42-201, Poland; Department of Social Sciences and Humanities, National Research Tomsk Polytechnic University, Tomsk, 634050, Russian Federation","Lahkani M.J., School of Economics and Management, University of Chinese Academy of Sciences, Haidian District, Beijing, 100190, China; Wang S., School of Economics and Management, University of Chinese Academy of Sciences, Haidian District, Beijing, 100190, China; Urbański M., Faculty of Civil Engineering, Czestochowa University of Technology, Dabrowskiego 69, Czestochowa, 42-201, Poland; Egorova M., Department of Social Sciences and Humanities, National Research Tomsk Polytechnic University, Tomsk, 634050, Russian Federation","Information technology advancements integrated with the e-commerce supply chain allow participants in the business process to effectively work with large volumes of data and control transactions. To improve the profitability and competitiveness of e-commerce companies, a blockchain solution was incorporated into the global B2B (Business-to-Business) supply chain. This technology simplified the transaction process by providing all participants in the sustainable B2B buying process with the same data about the trade. Overall, the use of blockchain improved the efficiency of logistics and digital documentation which reached 74% and 75%, respectively. The main advantage of using blockchain is that it creates a decentralized database that is secure. In addition, it increases the speed of payment and the reliability and transparency of data transfer. Further research may focus on the use of blockchain in green logistics to improve environmental sustainability in the e-commerce supply chain. © 2020 by the authors.","B2B e-commerce; Blockchain; Supply chain finance; Sustainability; Transformation","business; competitiveness; decentralization; financial system; information technology; integrated approach; logistics; participatory approach; profitability; research work; supply chain management; sustainability",{"$nulls":4},"Tomsk Polytechnic University, TPU","Acknowledgments: The third author M.E. was supported by Tomsk Polytechnic University within the framework of Tomsk Polytechnic University Competitiveness Enhancement Program.","Khan A.G., Electronic commerce: A study on benefits and challenges in an emerging economy, GJMBR, 16, pp. 19-22, (2016); Zeng M., Alibaba and the Future of Business, Harv. Bus. 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Financ., 23, pp. 51-54, (2017); Imran M., Jian Z., Ul Haque A., Urbanski M., Nair S.L.S., Determinants of firm's export performance in China's automobile industry, Sustainability, 10, (2018)","M.J. Lahkani; School of Economics and Management, University of Chinese Academy of Sciences, Haidian District, Beijing, 100190, China; email: jahangirilahkani@yahoo.com; M. Urbański; Faculty of Civil Engineering, Czestochowa University of Technology, Czestochowa, Dabrowskiego 69, 42-201, Poland; email: mariusz.urbanski@pcz.pl",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85086163291"]
["Qi X.; Chan J.H.; Hu J.; Li Y.","Qi, Xiaoguang (57189996882); Chan, Jin Hooi (37010337500); Hu, Junyan (57214796435); Li, Yifan (57214808797)","57189996882; 37010337500; 57214796435; 57214808797","Motivations for selecting cross-border e-commerce as a foreign market entry mode",2020.0,"Industrial Marketing Management",89.0,null,null,50.0,60.0,10.0,62.0,"10.1016/j.indmarman.2020.01.009","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85079127391&doi=10.1016%2fj.indmarman.2020.01.009&partnerID=40&md5=c05eb35913bda9ed842c5a203539880b","Anshan Normal University, Anshan, Liaoning, China; Judge Business School, University of Cambridge, Cambridge, United Kingdom; Faculty of Business, University of Greenwich, United Kingdom; London School of Economics and Political Science, United Kingdom","Qi X., Anshan Normal University, Anshan, Liaoning, China, Judge Business School, University of Cambridge, Cambridge, United Kingdom; Chan J.H., Faculty of Business, University of Greenwich, United Kingdom; Hu J., Anshan Normal University, Anshan, Liaoning, China; Li Y., London School of Economics and Political Science, United Kingdom","This article is an in-depth case study examining a foreign firm deploying Cross-border E-commerce as an entry mode to the Chinese market, integrating services provided by a major technology provider and a leading marketplace platform. Selecting which foreign market entry mode is an important internationalization strategic decision of firms and could have a considerable impact on the firm's performance. The CBEC mode emerges as a plausible choice: e-commerce has grown rapidly in many markets, particularly in China. Additionally, foreign firms face high transaction costs due to unfamiliar consumer behavior and institutional barriers. It is especially difficult for SMEs. This study deploys transaction cost theory as the underpinning framework to explain the motivations for selecting a CBEC entry mode. The findings suggest that CBEC could reduce uncertainties and opportunistic behaviors, while increasing trust. Foreign firms could lower their asset investment in physical shops, staff requirements and training, logistics and warehousing: these supports are provided by marketplace platforms. This new entry mode also takes advantage of the involvement and the dependency of intermediaries. In addition to providing market knowledge, technology providers help to build trust and reduce risks and thereby transaction costs, despite the high transaction frequency of e-commerce. © 2020 Elsevier Inc.",{"$nulls":6},"Liaoning Province BaiQianWan Talents Program; Hanshan Normal University, HNU","This research is partly supported by Liaoning Province BaiQianWan Talents Program and Anshan Normal University, China. The authors would like to acknowledge the comments and proofreading works done by Bernard Lane and Zaw Lwin. Special thanks to the issue editors and anonymous reviewers for their invaluable comments on the earlier versions of this article.","AliResearch, The future of trade: Cross-border e-commerce connects the world, (2016); Anderson E., Gatignon H., Modes of foreign entry: A transaction cost analysis and propositions, Journal of International Business Studies, 17, 3, pp. 1-26, (1986); Azam R., Global taxation of cross-border e-commerce income, Virginia Tax Review, 31, 4, pp. 639-693, (2012); Biggs C., Chande A., Matthews E., Mercier P., Wang A., Zou L., (2017); Bradach J.L., Eccles R.G., Price, authority, and trust: From ideal types to plural form, Annual Review of Sociology, 15, 1, pp. 97-118, (1989); Brouthers K.D., Brouthers L.E., Acquisition or greenfield start-up? 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WHICEB 2016 Proceedings. Paper 53, (2016); Yin R.K., Case study research: Design and methods, (1994)","J.H. Chan; Faculty of Business, University of Greenwich, London, United Kingdom; email: jinhooi@cantab.net",null,"Elsevier Inc.",{"$nulls":5},198501.0,null,"IMMAD",null,"English","Ind. Mark. Manage.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85079127391"]
["Rao J.","Rao, Jing (57218197141)",5.7218197141E10,"Operation mode of electric business logistics based on the application of two-dimensional code technology",2020.0,"International Journal of Metrology and Quality Engineering",11.0,null,3.0,null,null,null,1.0,"10.1051/ijmqe/2020001","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85088261213&doi=10.1051%2fijmqe%2f2020001&partnerID=40&md5=86f94dc447a623ccf3b697304c6a599c","Department of Financial Management, Chongqing Youth Vocational and Technical College, Chongqing, 400712, China","Rao J., Department of Financial Management, Chongqing Youth Vocational and Technical College, Chongqing, 400712, China","In recent years, with the irresistible pace of e-commerce development, e-commerce logistics orders show blowout growth. For the logistics industry, it is both an opportunity and a difficult problem as there are many problems such as low technology content and poor distribution efficiency. Therefore, it is a challenge that needs to be tackled to integrate technology accurately with the operation mode of e-commerce logistics. In order to improve the effect of logistics operation, bring convenience to the management of business logistics, and ultimately realize the maximum profit of logistics enterprises, based on two-dimensional code technology, this study took the specific mode of logistics operation as the research subject, applied the corresponding two-dimensional code generated to three different logistics processes, put forward specific optimization schemes, and carried out the analysis of the application results. The results showed that the intervention of two-dimensional code could protect users' privacy, prevent channel conflict, and realize logistics tracing of product information, thus effectively improve the logistics operation mode.  © J. Rao, published by EDP Sciences, 2020.","Decoding; E-commerce; Logistics tracing; Two-dimensional code","Quality control; Distribution efficiency; E-commerce development; Integrate technologies; Logistics enterprise; Logistics operations; Optimization scheme; Technology contents; Two dimensional codes; Electronic commerce",{"$nulls":4},"Research Center for E-commerce Entrepreneurship Innovation of Chongqing Youth Vocational & Technical College, (CQY2018CXTDC03); Research Center for Ecommerce Entrepreneurship Innovation of Chongqing Youth Vocational & Technical College","Funding text 1: This study was supported by the Research Center for Ecommerce Entrepreneurship Innovation of Chongqing Youth Vocational & Technical College (CQY2018CXTDC03).; Funding text 2: This study was supported by the Research Center for E-commerce Entrepreneurship Innovation of Chongqing Youth Vocational & Technical College (CQY2018CXTDC03).","Zhang H., Et al., Comput. Optim. Appl., 72, pp. 827-848, (2019); Shan Y., Et al., Proc. Second Int. Conf. Innov. Comput. Cloud Comput. 222-224, (2013); Xiao X., Fu Z., Zhang Y., Peng Z., Zhang X., J. Food Process Eng., 40, (2015); Di Y.J., Shi J.P., Mao G.Y., Mod. Phys. Lett., 31, (2017); Kalkan Y., Et al., Efficiency and Logistics 253-260 (2013); Zhang X., Et al., 2016 Ieee Trustcom/BigDataSE/I Spa 996-1000, (2016); Lim S.F.W., Jin X., Srai J.S., Int. J. Phys. Distrib. Logist. Manag., 48, pp. 308-332, (2018); Yang J.P., Yang C.C., Yao X.X., J. Bus. Econ., pp. 16-22, (2014); Cheng Y., Fu Z., Yu B., Ieee Trans. Inf. Foren. Sec., pp. 1-1, (2018); Kulshreshtha R., Kamboj A., Singh S., Int. Conf. Comput. Sci., pp. 722-731, (2012); Somani U., Lakhani K., Mundra M., Int. Conf. Parallel Distrib. Grid Comput., pp. 211-216, (2010); Liu X.Q., Et al., J. Cent. South Univ., 42, pp. 1890-1898, (2011); Montero-Mayorga J., Queral C., Gonzalez-Cadelo J., Ann. Nucl. Energy, 75, pp. 87-100, (2015); Mackay D.J.C., Neal R.M., Electron. Lett., 32, pp. 457-458, (2013); Kenk K., Haldma T., Discuss Estonian Econ. Policy, 24, pp. 35-50, (2016)","J. Rao; Department of Financial Management, Chongqing Youth Vocational and Technical College, Chongqing, 400712, China; email: rj_jing@yeah.net",null,"EDP Sciences",{"$nulls":5},2.1076839E7,null,null,null,"English","Int. J. Metrol. Qual. Eng.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85088261213"]
["Mut-Puigserver M.; Cabot-Nadal M.A.; Payeras-Capella M.M.","Mut-Puigserver, MacIa (6508028014); Cabot-Nadal, Miquel A. (57205754150); Payeras-Capella, M. Magdalena (15061983000)","6508028014; 57205754150; 15061983000","Removing the Trusted Third Party in a Confidential Multiparty Registered eDelivery Protocol Using Blockchain",2020.0,"IEEE Access",8.0,null,9110560.0,106855.0,106871.0,16.0,13.0,"10.1109/ACCESS.2020.3000558","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85086991341&doi=10.1109%2fACCESS.2020.3000558&partnerID=40&md5=f9dd740651b27073817a11b084970acf","Departamento de Ciències Matemàtiques i Informàtica, Universitat de les Illes Balears, Palma, E-07122, Spain","Mut-Puigserver M., Departamento de Ciències Matemàtiques i Informàtica, Universitat de les Illes Balears, Palma, E-07122, Spain; Cabot-Nadal M.A., Departamento de Ciències Matemàtiques i Informàtica, Universitat de les Illes Balears, Palma, E-07122, Spain; Payeras-Capella M.M., Departamento de Ciències Matemàtiques i Informàtica, Universitat de les Illes Balears, Palma, E-07122, Spain","Recently several proposals of blockchain-based solutions for traditional e-commerce applications have been presented, taking advantage of the fact that blockchain is a technology that offers an immutable registry of data. Among these proposals we can find solutions for certified notifications, digital signature of contracts, escrow protocols, fair payments and registered deliveries. In order to execute fair exchanges, most solutions involve trusted third parties, known as TTP, supervising the exchanges in a way or another. Until now, two solutions have been presented for Registered electronic Delivery (eDelivery) services. This service allows a user to prove that he has sent some data to a set of receivers. These protocols differ in the properties achieved and also in the use of trusted third parties. The first protocol is a blockchain-based solution without TTP for the eDelivery of non-confidential data. The second protocol allows also the eDelivery of confidential data. However, this second proposal requires the involvement of a TTP in a non-mandatory resolution phase. In this paper we present a new protocol that achieves the best properties of the previous solutions at the same time. The new protocol doesn't require the involvement of a TTP at any moment while it allows the eDelivery of confidential data, satisfying the security requirements for this service. © 2013 IEEE.","Blockchain; confidentiality; cryptocurrencies; fairness; notification; smart contract","Confidential data; E-Commerce applications; Fair exchange; New protocol; Security requirements; Trusted third parties; Blockchain",{"$nulls":4},"European Regional Development Funds, (RTI2018-097763-B-I00); Ministerio de Economía y Competitividad, MINECO; Agencia Estatal de Investigación, AEI","This work was supported in part by the Ministerio de Economia, Industria y Competitividad (MINECO), in part by the Agencia Estatal de Investigacion (AEI), and in part by the European Regional Development Funds (ERDF) through the Project Fair Exchange, Loyalty and TIckets with blockCHAIN (FeltiCHAIN) under Grant RTI2018-097763-B-I00.","Asokan N., Shoup V., Waidner M., Asynchronous protocols for optimistic fair exchange, Proc. 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(PKC), in Lecture Notes in Computer Science, 1751, pp. 46-57, (2000); Transitions: Recommendation for the Transitioning of the Use of Crypto-graphic Algorithms and Key Lengths, DRAFT NIST Special Publication 800-131A, (2019); Digital Signature Standard (DSS). (U.S. Department of Commerce, Washington, D.C.), Federal Information Processing Standards Publi-cation (FIPS) 186-4, NIST, Gaithersburg, MD, USA, (2013); Secure Hash Standard (SHS), (2015); Standards for Efficient Cryptography (SEC) 2: Recom-mended Elliptic Curve Domain Parameters. Version 2.0, (2010); Esposito C., Palmieri F., Choo K.-K.R., Cloud message queueing and notification: Challenges and opportunities, IEEE Cloud Comput., 5, 2, pp. 11-16, (2018); Zupan N., Zhang K., Jacobsen H.-A., Hyperpubsub: A decentralized, permissioned, publish/subscribe service using blockchains, Proc. 18th ACM/IFIP/USENIX Middleware Conf., pp. 15-16, (2017)","M. Mut-Puigserver; Departamento de Ciències Matemàtiques i Informàtica, Universitat de les Illes Balears, Palma, E-07122, Spain; email: macia.mut@uib.cat",null,"Institute of Electrical and Electronics Engineers Inc.",{"$nulls":5},2.1693536E7,null,null,null,"English","IEEE Access","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85086991341"]
["Guerrero-Lorente J.; Gabor A.F.; Ponce-Cueto E.","Guerrero-Lorente, Javier (57216565382); Gabor, Adriana F. (15818957800); Ponce-Cueto, Eva (35222118000)","57216565382; 15818957800; 35222118000","Omnichannel logistics network design with integrated customer preference for deliveries and returns",2020.0,"Computers and Industrial Engineering",144.0,null,106433.0,null,null,null,28.0,"10.1016/j.cie.2020.106433","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85083901152&doi=10.1016%2fj.cie.2020.106433&partnerID=40&md5=685933d2c0ad916f2cfa22f3453444ed","Department of Management Engineering, Business Administration and Statistics, Technical University of Madrid, Madrid, Spain; Research Center of Digital Supply Chain and Operations and Department of Applied Mathematics, Khalifa University, Abu Dhabi, United Arab Emirates; MIT Center for Transportation and Logistics, Massachusetts Institute of Technology, Cambridge, MA, United States","Guerrero-Lorente J., Department of Management Engineering, Business Administration and Statistics, Technical University of Madrid, Madrid, Spain; Gabor A.F., Research Center of Digital Supply Chain and Operations and Department of Applied Mathematics, Khalifa University, Abu Dhabi, United Arab Emirates; Ponce-Cueto E., MIT Center for Transportation and Logistics, Massachusetts Institute of Technology, Cambridge, MA, United States","This paper proposes a mixed integer program (MIP) for the network design problem of a parcel carrier that manages online orders from omnichannel retailers. The network includes several types of facilities, such as city distribution centers, intermediary depots, parcel offices, as well as collect channel points, such as automated parcel stations (APS), stores or kiosks. The model formulation takes into account the influence of these collection points on consumer choice and the maximum distance customers are willing to walk to reach them. Realistic transportation costs are also considered, including detailed long haul costs and delivery costs in an area. The transportation costs inside an area are estimated via the Continuous Approximation proposed by Newell (1971) and Newell (1973), which results in a simpler problem than a location-routing problem, however, at the cost of losing linearity. For a special case of the problem, we propose a heuristic that, in our experimental setting, is on average 42.5 faster than the overall MIP and gives solutions within 1.02% of the optimum. Finally, we use the model to discuss the network design of a Spanish parcel carrier operating in Madrid. © 2020 Elsevier Ltd","Customer preference; E-commerce; Network design; Omnichannel logistics; Returns","Sales; City distribution; Continuous approximations; Customer preferences; Location routing problem; Mixed-integer programs; Model formulation; Network design problems; Transportation cost; Integer programming",{"$nulls":4},"Khalifa University of Science, Technology and Research, KU, (874000218); United Arab Emirates University, UAEU, (31B065); École Polytechnique Paris","Funding text 1: We thank Guillaume Crognier from École Polytechnique Paris, France, for his help with the computational experiments and insightful comments on the paper and to dr. Edgar Blanco for many insightful discussions on the topic. This publication is based upon work supported by the Khalifa University of Science and Technology under Award No. RC2 DSO and Grant 874000218, and United Arab Emirates University under Grant 31B065.; Funding text 2: We thank Guillaume Crognier from École Polytechnique Paris, France, for his help with the computational experiments and insightful comments on the paper and to dr. Edgar Blanco for many insightful discussions on the topic. This publication is based upon work supported by the Khalifa University of Science and Technology under Award No. RC2 DSO and Grant 874000218 , and United Arab Emirates University under Grant 31B065 . 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Yadav V.S., Tripathi S., Singh A., Exploring omnichannel and network design in omni environment, Cogent Engineering, 4, 1, (2017); Yadav V.S., Tripathi S., Singh A., Bi-objective optimization for sustainable supply chain network design in omnichannel, Journal of Manufacturing Technology Management, 30, 6, pp. 972-986, (2019); Yang X., Strauss A.K., Currie C.S.M., Eglese R., Choice-based demand management and vehicle routing in e-fulfillment, Transportation Science, 50, 2, pp. 473-488, (2016); Zhang S., Lee C.K.M., Wu K., Choy K.L., Multi-objective optimization for sustainable supply chain network design considering multiple distribution channels, Expert Systems with Applications, 65, pp. 87-99, (2016); Zhang S., Zhu H., Li X., Wang Y., Omni-channel product distribution network design by using the improved particle swarm optimization algorithm, Discrete Dynamics in Nature and Society, 2019, pp. 1-15, (2019)","A.F. Gabor; Research Center of Digital Supply Chain and Operations and Department of Applied Mathematics, Khalifa University, Abu Dhabi, United Arab Emirates; email: adriana.gabor@ku.ac.ae",null,"Elsevier Ltd",{"$nulls":5},3608352.0,null,"CINDD",null,"English","Comput Ind Eng","Article","Final",null,"Scopus","2-s2.0-85083901152"]
["Zhu L.","Zhu, Liwei (57219869014)",5.7219869014E10,"Optimization and Simulation for E-Commerce Supply Chain in the Internet of Things Environment",2020.0,"Complexity",2020.0,null,8821128.0,null,null,null,4.0,"10.1155/2020/8821128","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85095843969&doi=10.1155%2f2020%2f8821128&partnerID=40&md5=bfba23c10ee92ecb5709a2a3a6b5c157","College of Commerce, Guangdong Polytechnic of Science and Technology, Zhuhai, 519090, China","Zhu L., College of Commerce, Guangdong Polytechnic of Science and Technology, Zhuhai, 519090, China","The supply chain optimization of e-commerce is the optimization of the integrated linear management model for e-commerce enterprises based on manufacturers, suppliers, warehouses, distribution centers, and channels. The application of Internet of Things (IoT) technology to the optimization of e-commerce supply chain can help e-commerce enterprises to monitor each product in real time and manage logistics system reasonably; thus, the circulation process of e-commerce product in the supply chain can be monitored and shared, and the product information at each stage of the supply chain can be analyzed and predicted, helping e-commerce companies to estimate the future trends or accident probability. On the analysis of summarizing and analyzing previous works, this article expounded the research status and significance of e-commerce supply chain optimization, elaborated the development background, current status, and future challenges of the IoT technology, introduced the methods and principles of the node distribution model and constraint parameter analysis of logistics supply chain, constructed the IoT-based e-commerce supply chain linear and nonlinear model including competition and risk-control modules, performed the design of IoT-based e-commerce supply chain optimization, and discussed the solutions to procurement robustness optimization and management process optimization. The final simulation analysis showed that the proposed optimization model can effectively predict e-commerce product information in each stage of the supply chain; the IoT-based e-commerce supply chain optimization can enable each node company in the supply chain to improve the quality of information transmission and reduce the risk of information asymmetry in the process of e-commerce exchanges and can quickly and easily respond to the sudden changes of market and environment, thereby promoting them to cooperate with each other for establishing a supply chain network structure with closer business relationships, smoother logistics transportation, more reasonable benefit sharing, and stronger market competitiveness. © 2020 Liwei Zhu.",null,"Competition; Electronic commerce; Information management; Internet of things; Optimization; Quality control; Research and development management; Risk assessment; Supply chains; Warehouses; Business relationships; Internet of Things (IOT); Linear and nonlinear models; Logistics supply chains; Logistics transportations; Quality of information; Robustness optimizations; Supply chain optimization; Supply chain management",{"$nulls":6},"Abdel-Basset M., Manogaran G., Mohamed M., Internet of things (IoT) and its impact on supply chain: A framework for building smart, secure and efficient systems, Future Generation Computer Systems, 86, pp. 614-628, (2018); Manavalan E., Jayakrishna K., A review of internet of things (IoT) embedded sustainable supply chain for industry 4.0 requirements, Computers and Industrial Engineering, 127, pp. 925-953, (2019); Caro F., Sadr R., The internet of things (IoT) in retail: Bridging supply and demand, Business Horizons, 62, 1, pp. 47-54, (2019); Haddud A., DeSouza A.R., Khare A., Lee H., Examining potential benefits and challenges associated with the internet of things integration in supply chains, Journal of Manufacturing Technology Management, 28, 8, pp. 1055-1085, (2017); Zhang Y., Wen J., The IoT electric business model: Using blockchain technology for the internet of things, Peer-to-Peer Networking and Applications, 10, 4, pp. 983-994, (2017); Elijah O., Rahman T.A., Orikumhi I., Leow C.Y., Hindia M.N., An overview of internet of things (IoT) and data analytics in agriculture: Benefits and challenges, Ieee Internet of Things Journal, 5, 5, pp. 3758-3773, (2018); Shang X., Zhang R., Zhu X., Zhou Q., Design theory, modelling and the application for the internet of things service, Enterprise Information Systems, 10, 3, pp. 249-267, (2016); Liu S., Zhang Y., Liu Y., Wang L., Wang X.V., An \"internet of things\" enabled dynamic optimization method for smart vehicles and logistics tasks, Journal of Cleaner Production, 215, pp. 806-820, (2019); Javed F., Afzal M.K., Sharif M., Kim B.S., Internet of things (IoT) operating Systems support, networking technologies, applications, and challenges: A comparative review, Ieee Communications Surveys & Tutorials, 20, 3, pp. 2062-2100, (2018); Liu P., Yi S.P., Pricing policies of green supply chain considering targeted advertising and product green degree in the big data environment, Journal of Cleaner Production, 164, pp. 1614-1622, (2017); Hsu L.F., E-commerce model based on the internet of things, Advanced Science Letters, 22, 10, pp. 3089-3091, (2016); Kamble S.S., Gunasekaran A., Parekh H., Joshi S., Modeling the internet of things adoption barriers in food retail supply chains, Journal of Retailing and Consumer Services, 48, pp. 154-168, (2019); Musa A., Dabo A.A.A., A review of RFID in supply chain management: 2000-2015, Global Journal of Flexible Systems Management, 17, 2, pp. 189-228, (2016); Chung B.D., Kim S.I., Lee J.S., Dynamic supply chain design and operations plan for connected smart factories with additive manufacturing, Applied Sciences, 8, 4, (2018); Liu C., Xiao Y., Javangula V., Hu Q., Wang S., Cheng X., NormaChain: A blockchain-based normalized autonomous transaction settlement system for IoT-based E-commerce, Ieee Internet of Things Journal, 6, 3, pp. 4680-4693, (2018); Tiwari S., Wee H.M., Daryanto Y., Big data analytics in supply chain management between 2010 and 2016: Insights to industries, Computers & Industrial Engineering, 115, pp. 319-330, (2018); Boiko A., Shendryk V., Boiko O., Information systems for supply chain management: Uncertainties, risks and cyber security, Procedia Computer Science, 149, pp. 65-70, (2019); Tao Q., Gu C., Wang Z., Rocchio J., Hu W., Yu X., Big data driven agricultural products supply chain management: A trustworthy scheduling optimization approach, Ieee Access, 6, pp. 49990-50002, (2018); Zhang Y., Application of improved BP neural network based on e-commerce supply chain network data in the forecast of aquatic product export volume, Cognitive Systems Research, 57, pp. 228-235, (2019); Zhang M., Huang G.Q., Xu S.X., Zhao Z., Optimization based transportation service trading in B2B e-commerce logistics, Journal of Intelligent Manufacturing, 30, 7, pp. 2603-2619, (2019); Saif A., Elhedhli S., Cold supply chain design with environmental considerations: A simulation-optimization approach, European Journal of Operational Research, 251, 1, pp. 274-287, (2016); Huang J., Song J., Optimal inventory control with sequential online auction in agriculture supply chain: An agent-based simulation optimisation, International Journal of Production Research, 56, 6, pp. 2322-2338, (2018)","L. Zhu; College of Commerce, Guangdong Polytechnic of Science and Technology, Zhuhai, 519090, China; email: 11630019@zju.edu.cn",null,"Hindawi Limited",{"$nulls":5},1.0762787E7,null,null,null,"English","Complexity","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85095843969"]
["Zhang H.; Wang Z.; Tang M.; Lv X.; Luo H.; Liu Y.","Zhang, Hongguang (56482388100); Wang, Zan (57213687339); Tang, Mengzhen (57222468752); Lv, Xiusha (57222469161); Luo, Han (57205769379); Liu, Yuanan (8377051500)","56482388100; 57213687339; 57222468752; 57222469161; 57205769379; 8377051500","Dynamic memory memetic algorithm for VRPPD with multiple arrival time and traffic congestion constraints",2020.0,"IEEE Access",8.0,null,null,167537.0,167554.0,17.0,5.0,"10.1109/ACCESS.2020.3023090","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85102776641&doi=10.1109%2fACCESS.2020.3023090&partnerID=40&md5=de6eb2a7b11042002040ecaa061d7972","Beijing Key Laboratory of Work Safety Intelligent Monitoring, School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing, 100876, China","Zhang H., Beijing Key Laboratory of Work Safety Intelligent Monitoring, School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing, 100876, China; Wang Z., Beijing Key Laboratory of Work Safety Intelligent Monitoring, School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing, 100876, China; Tang M., Beijing Key Laboratory of Work Safety Intelligent Monitoring, School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing, 100876, China; Lv X., Beijing Key Laboratory of Work Safety Intelligent Monitoring, School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing, 100876, China; Luo H., Beijing Key Laboratory of Work Safety Intelligent Monitoring, School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing, 100876, China; Liu Y., Beijing Key Laboratory of Work Safety Intelligent Monitoring, School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing, 100876, China","With the new distribution demands emerging continuously in the last decade, the distribution mode is changing gradually in various applications, such as e-commerce, emergency relief supplies distribution, the last-mile delivery, and so on. We formulate vehicle routing problem with pickup and delivery (VRPPD), while simultaneously considering multiple arrival time and traffic congestion constraints. Our model focuses on the clear changes of the distribution mode to meet the fast-delivery requirements in the last decade, which is characterized by the multi-batch arrival of goods in 24 hours and time-varying congestion in various time windows. Besides, we propose dynamic memory memetic algorithm, which updates its dynamic memory by whether to promote populations to find new better solutions or not. This is an effective acceleration mechanism to promote the population progress. Meanwhile, dynamic memory memetic algorithm determines the serious congestion tasks in the delivery route and transforms them into normal congestion or even non-congestion tasks. Test sets with 30 test problems are constructed by using real distribution data from Alibaba Cloud and traffic congestion data from Baidu Map in Shanghai. By comparing with four compared algorithms, the effectiveness, efficiency, and robustness of our proposed algorithm in non-congestion and congestion tests are simultaneously demonstrated. © 2020 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.","Distribution mode; Dynamic memory; Pickup and delivery problem; The multi-batch arrival of goods; Traffic congestion; VRPPD","Distribution of goods; Motor transportation; Vehicle routing; Acceleration mechanisms; Delivery routes; Distribution modes; Emergency relief; Memetic algorithms; Pickup and delivery; Real distribution; Vehicle Routing Problems; Traffic congestion",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (61876199)","This work was supported by the National Natural Science Foundation of China under Grant 61876199.","Nanry W.P., Wesley Barnes J., Solving the pickup and delivery problem with time windows using reactive tabu search, Transp. Res. 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["Mehlawat M.K.; Gupta P.; Mahajan D.","Mehlawat, Mukesh Kumar (23035630900); Gupta, Pankaj (57193233548); Mahajan, Divya (57201530795)","23035630900; 57193233548; 57201530795","A multi-period multi-objective optimization framework for software enhancement and component evaluation, selection and integration",2020.0,"Information Sciences",523.0,null,null,91.0,110.0,19.0,6.0,"10.1016/j.ins.2020.02.076","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85082172225&doi=10.1016%2fj.ins.2020.02.076&partnerID=40&md5=afef96a25527b788158b32b7b762c111","Department of Operational Research, University of Delhi, Delhi, India; Department of Mathematics, ADGITM, Guru Gobind Singh Indraprastha University, Delhi, India","Mehlawat M.K., Department of Operational Research, University of Delhi, Delhi, India; Gupta P., Department of Operational Research, University of Delhi, Delhi, India; Mahajan D., Department of Mathematics, ADGITM, Guru Gobind Singh Indraprastha University, Delhi, India","Software can be delivered either after it has been entirely developed or it can be delivered in phases. When delivered in phases, software can be enhanced either by upgrading the existing modules in forthcoming phases or by modifying the modules that were developed in previous phases. An incorporated multi-period multiple objective optimization model for the enhancement and establishment of a software system is discussed in this paper. The software system's total cost is minimized, and the fitness evaluation score of the software components (commercial off-the-shelf and in-house) for modules that are not outsourced, along with vendors for modules that are outsourced, is maximized. The fitness evaluation of module alternatives (software components and vendors) is conducted based on many important qualitative attributes using the Technique for Order Preference by Similarity to Ideal Solution. The model is constrained to critical parameters, such as compatibility, delivery time and integration of alternatives, along with software reliability. To exemplify the applicability of the suggested framework for optimization, the development of e-commerce software is used as a case study. © 2020 Elsevier Inc.","Component integration; Incremental software development; Multi-phase optimization; Multiple criteria analysis; Software enhancement","Integration; Multiobjective optimization; Software design; Component integration; Incremental software development; Multi-phase optimization; Multiple criteria analysis; Software enhancements; Software reliability",{"$nulls":6},"Ahmed A.M., Zhu W., Outsourcing software testing activities: a case study for Eastern Ocean Solutions-China, Proceedings of the 3rd IEEE International Conference on Communication Software and Networks (ICCSN), Xi'an, China, pp. 742-744, (2011); Badampudi D., Wohlin C., Petersen K., Software component decision-making: in-house, OSS, COTS or outsourcing-a systematic literature review, J. Syst. 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Appl., 1, pp. 344-357, (2011); Tarawneh F., Baharom Y., Hj J., Zainol A., COTS software evaluation and selection: a pilot study based in Jordan firms, Proceedings of the International Conference on Electrical Engineering and Informatics, Bandung, Indonesia, (2011); Verma S., Mehlawat M.K., Multi-criteria optimization model integrated with AHP for evaluation and selection of COTS components, Optimization, 66, pp. 1879-1894, (2017); Verma S., Mehlawat M.K., Mahajan D., Software component evaluation and selection using TOPSIS and fuzzy interactive approach under multiple applications development, Ann. Oper. Res., (2018); Zachariah B., Rattihalli R.N., A multicriteria optimization model for quality of modular software systems, Asia Pacific J. Oper. Res., 24, pp. 797-811, (2007)","P. Gupta; Department of Operational Research, University of Delhi, Delhi, India; email: pankajgpta@gmail.com",null,"Elsevier Inc.",{"$nulls":5},200255.0,null,"ISIJB",null,"English","Inf Sci","Article","Final",null,"Scopus","2-s2.0-85082172225"]
["Moshref-Javadi M.; Hemmati A.; Winkenbach M.","Moshref-Javadi, Mohammad (55911808200); Hemmati, Ahmad (36473242800); Winkenbach, Matthias (57189308132)","55911808200; 36473242800; 57189308132","A truck and drones model for last-mile delivery: A mathematical model and heuristic approach",2020.0,"Applied Mathematical Modelling",80.0,null,null,290.0,318.0,28.0,110.0,"10.1016/j.apm.2019.11.020","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85076287414&doi=10.1016%2fj.apm.2019.11.020&partnerID=40&md5=687de0159aa6d33d90113d25c3e80f70","Massachusetts Institute of Technology, Cambridge, 02139, MA, United States; University of Bergen, Bergen, 5020, Norway","Moshref-Javadi M., Massachusetts Institute of Technology, Cambridge, 02139, MA, United States; Hemmati A., University of Bergen, Bergen, 5020, Norway; Winkenbach M., Massachusetts Institute of Technology, Cambridge, 02139, MA, United States","We present a mathematical formulation and a heuristic solution approach for the optimal planning of delivery routes in a multi-modal system combining truck and Unmanned Aerial Vehicle (UAV) operations. In this system, truck and UAV operations are synchronized, i.e., one or more UAVs travel on a truck, which serves as a mobile depot. Deliveries can be made by both UAVs and the truck. While the truck follows a multi-stop route, each UAV delivers a single shipment per dispatch. The presented optimization model minimizes the waiting time of customers in the system. The model determines the optimal allocation of customers to truck and UAVs, the optimal route sequence of the truck, and the optimal launch and reconvene locations of the UAVs along the truck route. We formulate the problem as a Mixed-Integer Linear Programming (MILP) model and conduct a bound analysis to gauge the maximum potential of the proposed system to reduce customer waiting time compared to a traditional truck-only delivery system. To be able to solve real-world problem size instances, we propose an efficient Truck and Drone Routing Algorithm (TDRA). The solution quality and computational performance of the mathematical model and the TDRA are compared together and with the truck-only model based on a variety of problem instances. Further, we apply the TDRA to a real-world case study for e-commerce delivery in São Paulo, Brazil. Our numerical results suggest significant reductions in customer waiting time to be gained from the proposed multi-modal delivery model. © 2019 Elsevier Inc.","Large neighborhood search; Last-mile delivery; Mixed-integer programming; UAV logistics","Antennas; Drones; Heuristic methods; Integer programming; Sales; Transportation routes; Computational performance; Heuristic solutions; Large neighborhood search; Last mile; Mathematical formulation; Mixed integer linear programming model; Mixed integer programming; Optimization modeling; Trucks",{"$nulls":6},"Goodman R., Whatever you call it, just don't think of last-mile logistics, last, Global Logist. 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Res., 113, 2, pp. 469-499, (1999); Gander W., Golub G.H., Strebel R., Least-squares fitting of circles and ellipses, BIT Numer. Math., 34, 4, pp. 558-578, (1994); (2019); (2019); Salehipour A., Sorensen K., Goos P., Braysy O., Efficient GRASP+ VND and GRASP+ VNS metaheuristics for the traveling repairman problem, 4OR, 9, 2, pp. 189-209, (2011); Silva M.M., Subramanian A., Vidal T., Ochi L.S., A simple and effective metaheuristic for the minimum latency problem, Eur. J. Oper. Res., 221, 3, pp. 513-520, (2012); (2018); Kharpal A., (2016); Yoon J.J., The traveling salesman problem with multiple drones: an optimization model for last-mile delivery, (2018)","M. Moshref-Javadi; Massachusetts Institute of Technology, Cambridge, 02139, United States; email: moshref@mit.edu",null,"Elsevier Inc.",{"$nulls":5},"0307904X",null,"AMMOD",null,"English","Appl. Math. Model.","Article","Final",null,"Scopus","2-s2.0-85076287414"]
["Li Z.; Barenji A.V.; Jiang J.; Zhong R.Y.; Xu G.","Li, Zhi (57189370824); Barenji, Ali Vatankhah (55616657900); Jiang, Jiazhi (57205120537); Zhong, Ray Y. (55353690000); Xu, Gangyan (55361785800)","57189370824; 55616657900; 57205120537; 55353690000; 55361785800","A mechanism for scheduling multi robot intelligent warehouse system face with dynamic demand",2020.0,"Journal of Intelligent Manufacturing",31.0,2.0,null,469.0,480.0,11.0,52.0,"10.1007/s10845-018-1459-y","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85058636275&doi=10.1007%2fs10845-018-1459-y&partnerID=40&md5=00fd81d1d1d30280077b3c4d3a948763","Guangdong Provincial Key Laboratory of Computer Integrated Manufacturing Systems, School of Electromechanical Engineering, Guangdong University of Technology, Guangzhou, Guangdong, China; Department of Mechatronics Engineering, Kennesaw State University, Kennesaw, United States; Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Pok Fu Lam, Hong Kong; School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore, Singapore","Li Z., Guangdong Provincial Key Laboratory of Computer Integrated Manufacturing Systems, School of Electromechanical Engineering, Guangdong University of Technology, Guangzhou, Guangdong, China; Barenji A.V., Guangdong Provincial Key Laboratory of Computer Integrated Manufacturing Systems, School of Electromechanical Engineering, Guangdong University of Technology, Guangzhou, Guangdong, China, Department of Mechatronics Engineering, Kennesaw State University, Kennesaw, United States; Jiang J., Guangdong Provincial Key Laboratory of Computer Integrated Manufacturing Systems, School of Electromechanical Engineering, Guangdong University of Technology, Guangzhou, Guangdong, China; Zhong R.Y., Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Pok Fu Lam, Hong Kong; Xu G., School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore, Singapore","Given the evolutionary journey of E-commerce, there have been emerging challenges confronting warehouse logistics, including smaller shipping units, more varieties and batches, and shorter cycles. These challenges are difficult to cope when using conventional scheduling with the robotic approach. Currently, automated storage and retrieval system are becoming preferred for warehouse companies with the help of mobile robots. However, when many orders are received simultaneously, the existing scheduling approach might make unreasonable decisions, leading to delayed packaging of entire orders and reducing the performance of the warehouse. Therefore, this paper addresses this problem and proposes a novel scheduling mechanism for multi-robot and tasks allocation problems which may arise in an intelligent warehouse system. This mechanism proposes into the intelligent warehouse troubled with simultaneous multiple customer demands. The mathematical model for the system is developed by considering a multitask robot facing dynamic customer demand. The proposed model’s approach is based on the particle swarm optimization heuristic. The result for this approach then compared with the genetic algorithm (GA). The simulation results demonstrate that the proposed solution is far superior to that of the GA for multi-robot scheduling and tasks allocation problems in the intelligent warehouse. © 2018, Springer Science+Business Media, LLC, part of Springer Nature.","Intelligent warehousing system; Multi-robot; Scheduling; Synchronized","Computer control systems; Dynamics; Genetic algorithms; Industrial robots; Multipurpose robots; Particle swarm optimization (PSO); Scheduling; Warehouses; Automated storage and retrieval system; Customer demands; Intelligent warehouse; Multirobots; Scheduling mechanism; Synchronized; Tasks allocations; Warehousing systems; Intelligent robots",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (51405089); China Postdoctoral Science Foundation, (2018M633008); Science and Technology Planning Project of Guangdong Province, (2015B010131008)","This work was supported by the National Natural Science Foundation of China (51405089), the Science and Technology Planning Project of Guangdong Province (2015B010131008) and China Postdoctoral Science Foundation under (2018M633008).","Alavidoost M., Tarimoradi M., Zarandi M.F., Bi-objective mixed-integer nonlinear programming for multi-commodity tri-echelon supply chain networks, Journal of Intelligent Manufacturing, 29, pp. 1-18, (2015); Bai Q., Analysis of particle swarm optimization algorithm, Computer and Information Science, 3, 1, (2010); Baker P., Canessa M., Warehouse design: A structured approach, European Journal of Operational Research, 193, 2, pp. 425-436, (2009); Barenji A.V., Barenji R.V., Roudi D., Hashemipour M., A dynamic multi-agent-based scheduling approach for SMEs, The International Journal of Advanced Manufacturing Technology, 89, 9-12, pp. 3123-3137, (2017); Barenji R.V., Barenji A.V., Hashemipour M., A multi-agent RFID-enabled distributed control system for a flexible manufacturing shop, The International Journal of Advanced Manufacturing Technology, 71, 9-12, pp. 1773-1791, (2014); Barenji R.V., Ozkaya B.Y., Barenji A.V., Quantifying the advantage of a kitting system using Petri nets: A case study in Turkey, modeling, analysis, and insights, The International Journal of Advanced Manufacturing Technology, 93, 9-12, pp. 3677-3691, (2017); Chen F., Wang H., Xie Y., Qi C., An ACO-based online routing method for multiple order pickers with congestion consideration in warehouse, Journal of Intelligent Manufacturing, 27, 2, pp. 389-408, (2016); Contreras-Cruz M.A., Ayala-Ramirez V., Hernandez-Belmonte U.H., Mobile robot path planning using artificial bee colony and evolutionary programming, Applied Soft Computing, 30, pp. 319-328, (2015); Costa A., Cappadonna F.A., Fichera S., A hybrid genetic algorithm for minimizing makespan in a flow-shop sequence-dependent group scheduling problem, Journal of Intelligent Manufacturing, 28, 6, pp. 1269-1283, (2017); Dias M.B., Zlot R., Kalra N., Stentz A., Market-based multirobot coordination: A survey and analysis, Proceedings of the IEEE, 94, 7, pp. 1257-1270, (2006); Dou J., Chen C., Yang P., Genetic scheduling and reinforcement learning in multirobot systems for intelligent warehouses, Mathematical Problems in Engineering, 2015, pp. 1-10, (2015); Elango M., Nachiappan S., Tiwari M.K., Balancing task allocation in multi-robot systems using K-means clustering and auction based mechanisms, Expert Systems with Applications, 38, 6, pp. 6486-6491, (2011); Foumani M., Moeini A., Haythorpe M., Smith-Miles K., A cross-entropy method for optimising robotic automated storage and retrieval systems, International Journal of Production Research, 56, pp. 1-23, (2018); Gautam A., Thakur A., Dhanania G., Mohan S., A distributed algorithm for balanced multi-robot task allocation, 2016 11Th International Conference on Paper Presented at the Industrial and Information Systems (ICIIS), (2016); Gu J., The forward reserve warehouse sizing and dimensioning problem, (2005); Gu J., Goetschalckx M., McGinnis L.F., Research on warehouse operation: A comprehensive review, European Journal of Operational Research, 177, 1, pp. 1-21, (2007); Gu J., Goetschalckx M., McGinnis L.F., Research on warehouse design and performance evaluation: A comprehensive review, European Journal of Operational Research, 203, 3, pp. 539-549, (2010); Hariga M.A., Jackson P.L., The warehouse scheduling problem: Formulation and algorithms, IIE Transactions, 28, 2, pp. 115-127, (1996); Hassan M.M.D., A framework for the design of warehouse layout, Facilities, 20, 13-14, pp. 432-440, (2002); Hassan R., Cohanim B., Weck O., Venter G., A comparison of particle swarm optimization and the genetic algorithm, Paper Presented at the 46Th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference, (2005); Heragu S.S., Du L., Mantel R.J., Schuur P.C., Mathematical model for warehouse design and product allocation, International Journal of Production Research, 43, 2, pp. 327-338, (2005); Huh J., Chae M.J., Park J., Kim K., A case-based reasoning approach to fast optimization of travel routes for large-scale AS/RSs, Journal of Intelligent Manufacturing, 28, pp. 1-14, (2017); Kennedy J., Particle swarm optimization, Encyclopedia of machine learning, pp. 760-766, (2011); Kulkarni R.V., Venayagamoorthy G.K., Particle swarm optimization in wireless-sensor networks: A brief survey, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), 41, 2, pp. 262-267, (2011); Liu M., Ma J., Lin L., Ge M., Wang Q., Liu C., Intelligent assembly system for mechanical products and key technology based on internet of things, Journal of Intelligent Manufacturing, 28, 2, pp. 271-299, (2017); Minner S., Transchel S., Periodic review inventory-control for perishable products under service-level constraints, OR Spectrum, 32, 4, pp. 979-996, (2010); Mohemmed A.W., Sahoo N.C., Geok T.K., Solving shortest path problem using particle swarm optimization, Applied Soft Computing, 8, 4, pp. 1643-1653, (2008); Nastasi G., Colla V., Cateni S., Campigli S., Implementation and comparison of algorithms for multi-objective optimization based on genetic algorithms applied to the management of an automated warehouse, Journal of Intelligent Manufacturing, 27, pp. 1-13, (2016); Nedic N., Stojanovic V., Djordjevic V., Optimal control of hydraulically driven parallel robot platform based on firefly algorithm, Nonlinear Dynamics, 82, 3, pp. 1457-1473, (2015); Onwubolu G.C., Mutingi M., A genetic algorithm approach for the cutting stock problem, Journal of Intelligent Manufacturing, 14, 2, pp. 209-218, (2003); Poli R., Analysis of the publications on the applications of particle swarm optimisation, Journal of Artificial Evolution and Applications, (2008); Ponnambalam S., Ramkumar V., Jawahar N., A multiobjective genetic algorithm for job shop scheduling, Production Planning & Control, 12, 8, pp. 764-774, (2001); Prsic D., Nedic N., Stojanovic V., A nature inspired optimal control of pneumatic-driven parallel robot platform, Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 231, 1, pp. 59-71, (2017); Rouwenhorst B., Reuter B., Stockrahm V., van Houtum G.-J., Mantel R., Zijm W.H., Warehouse design and control: Framework and literature review, European Journal of Operational Research, 122, 3, pp. 515-533, (2000); Stojanovic V., Nedic N., Prsic D., Dubonjic L., Djordjevic V., Application of cuckoo search algorithm to constrained control problem of a parallel robot platform, The International Journal of Advanced Manufacturing Technology, 87, 9-12, pp. 2497-2507, (2016); Venter G., Sobieszczanski-Sobieski J., Particle swarm optimization, AIAA Journal, 41, 8, pp. 1583-1589, (2003); Yalcin A., Koberstein A., Schocke K.O., An optimal and a heuristic algorithm for the single-item retrieval problem in puzzle-based storage systems with multiple escorts, International Journal of Production Research, 29, pp. 1-23, (2018); Yan B., Yan C., Long F., Tan X.C., Multi-objective optimization of electronic product goods location assignment in stereoscopic warehouse based on adaptive genetic algorithm, Journal of Intelligent Manufacturing, 26, pp. 1-13, (2015); Ye S., Ma H., Xu S., Yang W., Fei M., An effective fireworks algorithm for warehouse-scheduling problem, Transactions of the Institute of Measurement and Control, 39, 1, pp. 75-85, (2017); Zhang Y., Gong D.-W., Zhang J.-H., Robot path planning in uncertain environment using multi-objective particle swarm optimization, Neurocomputing, 103, pp. 172-185, (2013); Zhong R.Y., Huang G.Q., Dai Q.Y., Zhang T., Mining SOTs and dispatching rules from RFID-enabled real-time shopfloor production data, Journal of Intelligent Manufacturing, 25, 4, pp. 825-843, (2014); Zhou L., Shi Y., Wang J., Yang P., A balanced heuristic mechanism for multirobot task allocation of intelligent warehouses, Mathematical Problems in Engineering, 2014, pp. 15-25, (2014)","R.Y. Zhong; Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Pok Fu Lam, Hong Kong; email: zhongzry@gmail.com",null,"Springer",{"$nulls":5},9565515.0,null,"JIMNE",null,"English","J Intell Manuf","Article","Final",null,"Scopus","2-s2.0-85058636275"]
["Guo B.","Guo, Binbin (57219743387)",5.7219743387E10,"Research on the Construction of Logistics Information Platform for Coastal Ports under the Background of Electronic Commerce",2020.0,"Journal of Coastal Research",115.0,"sp1",null,120.0,122.0,2.0,4.0,"10.2112/JCR-SI115-036.1","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85095129878&doi=10.2112%2fJCR-SI115-036.1&partnerID=40&md5=af9a6f3563a30b035d3e3200d6dbc91a","Zhongshan Institute, University of Electronic Science and Technology of China, Zhongshan, 528402, China","Guo B., Zhongshan Institute, University of Electronic Science and Technology of China, Zhongshan, 528402, China","Guo, B., 2020. Research on the construction of logistics information platform for coastal ports under the background of electronic commerce. In: Bai, X. and Zhou, H. (eds.), Advances in Water Resources, Environmental Protection, and Sustainable Development. Journal of Coastal Research, Special Issue No. 115, pp.120-122. Coconut Creek (Florida), ISSN 0749-0208. The construction of e-commerce integrated information platform is the key to realize the informatization, individuation, high efficiency and sustainable development of port logistics park (Buntak et al., 2019). With the improvement of China's economic strength, many modern technologies, such as automatic identification technology and bar code technology, have been widely applied in the field of port logistics, making ports gradually develop from traditional labor-intensive to e-commerce of logistics operation mode. E-commerce, with its good information processing and transmission system, has become a very important condition for the logistics industry to provide good services. The realization of port logistics informatization is an inevitable requirement to enhance the comprehensive competitiveness of port logistics in the era of e-commerce. Without the guarantee of a perfect logistics system, e-commerce activities cannot be carried out smoothly. This paper discusses the development trend of coastal port logistics in the e-commerce environment and the competitiveness of e-commerce to enhance port logistics. On this basis, the conditions for the construction of port logistics information platform are described.  © Coastal Education and Research Foundation, Inc. 2020.","E-commerce; information platform; port logistics","Florida",{"$nulls":6},"Buntak K., Kovacic M., Mutavdzija M., Internet of Things and Smart Warehouses as the Future of Logistics, Tehnicki Glasnik-Technical Journal, 13, 3, pp. 248-253, (2019); He X.R., Liu Y.Y., Analysis and design of marine logistics e-commerce platform, Port Economics, 149, pp. 51-53, (2016); Hu B.Q., Zhao Y.P., Research on the joint development of port logistics industry cluster and cross-border e-commerce from the perspective of innovation, Commercial Economics Research, 699, pp. 104-105, (2016); Li X.G., The development direction of port logistics in the era of big data Internet, China Port, 0, pp. 46-47, (2016); Mu D.Q., Research on the development strategy of port logistics informatization under e-commerce model, Logistics Engineering and Management, 7, pp. 97-98, (2015); Sun Y.W., Talking about the development strategy of port logistics shipping agency service, China Economy and Trade, 3, pp. 48-49, (2016); Wang B.S., Zhao Y.F., Application of port logistics e-commerce platform based on private cloud, China Port, 0, pp. 56-58, (2018); Wu Y.S., Exploring the integrated management of port logistics enterprises, China Port, 0, pp. 49-50, (2015); Zhang L., Research on the application of big data governance model for port logistics services, E-commerce, 0, pp. 3-4, (2018)","B. Guo; Zhongshan Institute, University of Electronic Science and Technology of China, Zhongshan, 528402, China; email: jpugmo69@sina.com",null,"Coastal Education Research Foundation Inc.",{"$nulls":5},7490208.0,null,"JCRSE",null,"English","J. Coast. Res.","Article","Final",null,"Scopus","2-s2.0-85095129878"]
["Tanveer M.; Hassan S.; Bhaumik A.","Tanveer, Muhammad (57211168007); Hassan, Shafiqul (57200439502); Bhaumik, Amiya (57209775120)","57211168007; 57200439502; 57209775120","COVID-19 quarantine and consumer behavior that change the trends of business sustainability & development",2020.0,"Academy of Strategic Management Journal",19.0,4.0,null,1.0,11.0,10.0,8.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85091483823&partnerID=40&md5=77b5d8d7c00b9059ea1ed992157c37b9","Lincoln University College, Malaysia; Prince Sultan University, Saudi Arabia","Tanveer M., Lincoln University College, Malaysia; Hassan S., Prince Sultan University, Saudi Arabia; Bhaumik A., Lincoln University College, Malaysia","Introduction: The corona virus is all having an impact on all fields of life. In addition to the IT market, the manufacturing, retail and food markets, chemicals, electrical products, rubber and chemicals, and office equipment are often compromised. Many technological firms are experiencing storage and network constraints and are unable to satisfy consumer demand there now. Due to COVID-19 it is great concern for the organizations, firms to sustain their business and development is a question mark. Objective: The study tries to know the COVID-19 and quarantine has influenced the consumer behavior negatively or positively and similarly if these ultimately making the sustainability of Business Empire in Saudi Arabia go downwards or not? Methodology: In this study the researchers used quantitative and qualitative method to analyze the results and the reliability of the hypothesis were utilized. The questionnaire and interviews were conducted through by using email, phones and through by using social media. The analysis was carried out along with reliability and KMO test to check the certainty of the hypothesis and its impact on business sustainability, development and consumer behavior. Results: The customer behavior was found very poor towards the business development as the presumption has been believed, and this weakens the market world economy in the region. COVID-19 keeps the customers at home but the demands are continuously raising online purchasing and home delivery. Conversely Because of reduced of purchasing because of not having much experience of online shopping and home delivery. Due to COVID-19 people were very choosy to buy products that had great impact on business sustainability and development and consumer behavior were found negative. Conclusion: Despite this outbreak several imports are delayed, which has further weakened the country's economy. Here, the research paper highlights the reality that corona virus has destroyed the company. While evaluating, it is specifically known that COVID has negatively impacted Saudi Arabia's industry and customer base as a whole. Many plants became closed, which created shortages in the labor force now need to explore new trends, techniques and innovations to alive the market. So there is huge need of business to kick off again to fulfil the business requirements and cover the damages. © 2020.","Business management; Business sustainability; Consumer behavior; COVID-19; Quarantine",{"$nulls":7},"Coronavirus (COVID-19) business impact, (2020); GCC ministers discuss economic impact of COVID-19, (2020); Saudi Arabia Turns to E-Commerce during COVID-19 Outbreak, (2020); Harris K., Tracking the global impact of the coronavirus outbreak, (2020); Mehio R., Saudi Arabia cuts down 2020 budget due to unexpected covid-19 expenses, (2020); Ozili P.K., Arun T., Spillover of COVID-19: Impact on the Global Economy, (2020); Saudi Arabia requires lenders to help companies, (2020); Revert T., How is the Coronavirus affecting consumer behaviour?, (2020); Tanveer M., Hassan S., The role of new and creative ideas in developing industries of education, software and manufacturing in Pakistan, Journal of Entrepreneurship Education, 23, 3, (2020); Tanveer M., Bhaumik A., Hassan S., Covid-19 pandemic, outbreak educational sector and students online learning in Saudi Arabia, Journal of Entrepreneurship Education, 23, 3, (2020); How covid-19 will change the global business climate, (2020); Middle East and Africa: Coronavirus (COVID-19) Impact on Business Aviation, (2020); (2020)","S. Hassan; Prince Sultan University, Riyadh, Saudi Arabia; email: shassan@psu.edu.sa",null,"Allied Business Academies",{"$nulls":5},1.5441458E7,null,null,null,"English","Acad. Strateg. Manage. J","Article","Final",null,"Scopus","2-s2.0-85091483823"]
["Wang Q.; Liu X.; Liu W.; Liu A.-A.; Liu W.; Mei T.","Wang, Qi (57200857037); Liu, Xinchen (56431458100); Liu, Wu (55145372400); Liu, An-An (23480048200); Liu, Wenyin (22433292200); Mei, Tao (7005396035)","57200857037; 56431458100; 55145372400; 23480048200; 22433292200; 7005396035","MetaSearch: Incremental Product Search via Deep Meta-Learning",2020.0,"IEEE Transactions on Image Processing",29.0,null,9127791.0,7549.0,7564.0,15.0,57.0,"10.1109/TIP.2020.3004249","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85088301170&doi=10.1109%2fTIP.2020.3004249&partnerID=40&md5=28b1c3f31607f2c5bdf8429deb056397","Department of Computer, Guangdong University of Technology, Guangzhou, China; AI Research of JD.com, Beijing, China; School of Electrical and Information Engineering, Tianjin University, Tianjin, China","Wang Q., Department of Computer, Guangdong University of Technology, Guangzhou, China; Liu X., AI Research of JD.com, Beijing, China; Liu W., AI Research of JD.com, Beijing, China; Liu A.-A., School of Electrical and Information Engineering, Tianjin University, Tianjin, China; Liu W., Department of Computer, Guangdong University of Technology, Guangzhou, China; Mei T., Department of Computer, Guangdong University of Technology, Guangzhou, China","With the advancement of image processing and computer vision technology, content-based product search is applied in a wide variety of common tasks, such as online shopping, automatic checkout systems, and intelligent logistics. Given a product image as a query, existing product search systems mainly perform the retrieval process using predefined databases with fixed product categories. However, real-world applications often require inserting new categories or updating existing products in the product database. When using existing product search methods, the image feature extraction models must be retrained and database indexes must be rebuilt to accommodate the updated data, and these operations incur high costs for data annotation and training time. To this end, we propose a few-shot incremental product search framework with meta-learning, which requires very few annotated images and has a reasonable training time. In particular, our framework contains a multipooling-based product feature extractor that learns a discriminative representation for each product, and we also design a meta-learning-based feature adapter to guarantee the robustness of the few-shot features. Furthermore, when expanding new categories in batches during a product search, we reconstruct the few-shot features by using an incremental weight combiner to accommodate the incremental search task. Through extensive experiments, we demonstrate that the proposed framework achieves excellent performance for new products while still guaranteeing the high search accuracy of the base categories after gradually expanding new product categories without forgetting. © 1992-2012 IEEE.","Few-shot learning; Incremental search; Meta-learning; Multipooling; Product search","Database systems; Deep learning; Image processing; Online systems; Product design; Query processing; Image feature extractions; Image processing and computer vision; Incremental search; Online shopping; Product categories; Product database; Retrieval process; Search accuracy; Search engines",{"$nulls":4},"Tianjin New Generation Artificial Intelligence Major Program, (19ZXZNGX00110); Guangdong Province Introduction of Innovative R&D Team, (2014ZT05G157); National Natural Science Foundation of China, NSFC, (61902077, 91748107); Universiteit Hasselt, (BOF20BL01)","Manuscript received September 28, 2019; revised March 18, 2020 and May 14, 2020; accepted June 13, 2020. Date of publication June 29, 2020; date of current version July 13, 2020. This work was supported in part by the National Natural Science Foundation of China under Grant 91748107 and Grant 61902077, in part by the Guangdong Innovative Research Team Program under Grant 2014ZT05G157, in part by the Special Research Fund of Hasselt University under Grant BOF20BL01, and in part by the Grant of Tianjin New Generation Artificial Intelligence Major Program under Grant 19ZXZNGX00110. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Soma Biswas. (Corresponding authors: Wu Liu; Wenyin Liu.) Qi Wang is with the Department of Computer, Guangdong University of Technology, Guangzhou 510006, China, and also with the Faculty of Engineering Technology, Hasselt University, 3590 Hasselt, Belgium (e-mail: wangqi_6414@sina.com).","Arandjelovic R., Gronat P., Torii A., Pajdla T., Sivic J., NetVLAD: CNN architecture for weakly supervised place recognition, IEEE Trans. Pattern Anal. Mach. Intell., 40, 6, pp. 1437-1451, (2018); Babenko A., Lempitsky S.V., Aggregating local deep features for image retrieval, Proc. ECCV, pp. 1269-1277, (2015); Lee K., Maji S., Ravichandran A., Soatto S., Meta-learning with differentiable convex optimization, Proc. IEEE/CVF Conf. Comput. Vis. Pattern Recognit. (CVPR), pp. 10657-10665, (2019); Chaudhry A., Dokania P.K., Ajanthan T., Torr H.S.P., Riemannian walk for incremental learning: Understanding forgetting and intransigence, Proc. 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Pattern Recognit., pp. 7278-7286, (2018); Wei X.-S., Cui Q., Yang L., Wang P., Liu L., RPC: A large-scale retail product checkout dataset, CoRR, abs/1901.07249, (2019); Xie H., Mao Z., Zhang Y., Deng H., Yan C., Chen Z., Doublebit quantization and index hashing for nearest neighbor search, IEEE Trans. Multimedia, 21, 5, pp. 1248-1260, (2019); Yao T., Pan Y., Li Y., Mei T., Incorporating copying mechanism in image captioning for learning novel objects, Proc. IEEE Conf. Comput. Vis. Pattern Recognit. (CVPR), pp. 5263-5271, (2017); Zheng L., Wang S., Tian Q., Coupled binary embedding for largescale image retrieval, IEEE Trans. Image Process., 23, 8, pp. 3368-3380, (2014); Zheng L., Yang Y., Tian Q., SIFT meets CNN: A decade survey of instance retrieval, IEEE Trans. Pattern Anal. Mach. Intell., 40, 5, pp. 1224-1244, (2018)","W. Liu; Department of Computer, Guangdong University of Technology, Guangzhou, China; email: liuwy@gdut.edu.cn; X. Liu; AI Research of JD.com, Beijing, China; email: liuxinchen1@jd.com",null,"Institute of Electrical and Electronics Engineers Inc.",{"$nulls":5},1.0577149E7,null,"IIPRE",null,"English","IEEE Trans Image Process","Article","Final",null,"Scopus","2-s2.0-85088301170"]
["Çera G.; Phan Q.P.T.; Androniceanu A.; Çera E.","Çera, Gentjan (57204419608); Phan, Quyen Phu Thi (57208165938); Androniceanu, Armenia (35253283800); Çera, Edmond (57211300278)","57204419608; 57208165938; 35253283800; 57211300278","Financial capability and technology implications for online shopping",2020.0,"E a M: Ekonomie a Management",23.0,2.0,null,156.0,172.0,16.0,19.0,"10.15240/tul/001/2020-2-011","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85086468053&doi=10.15240%2ftul%2f001%2f2020-2-011&partnerID=40&md5=3f203d07646b2a4397113f762e0be212","Tomas Bata University in Zlin, Faculty of Management and Economics, Czech Republic; The University of Danang, University of Economics, Faculty of Marketing, Viet Nam; Bucharest University of Economic Studies, International Centre for Public Management, Romania; Tomas Bata University in Zlin, Faculty of Management and Economics, Czech Republic","Çera G., Tomas Bata University in Zlin, Faculty of Management and Economics, Czech Republic; Phan Q.P.T., The University of Danang, University of Economics, Faculty of Marketing, Viet Nam; Androniceanu A., Bucharest University of Economic Studies, International Centre for Public Management, Romania; Çera E., Tomas Bata University in Zlin, Faculty of Management and Economics, Czech Republic","To promote online shoppers’ long-term interest, consumers need to have the knowledge and ability to avoid problems with financial issues. Financial capability helps to put consumers on the path to a sustainable financial future. However, previous studies only focused on financial capability in a financial context. To handle personal finance systematically and successfully in an online setting, this study extends an enhanced understanding of how financial capability on online consumer behaviour. Based on the data of 690 respondents collected by a face-to-face from eight main regions in Albania, this study employed principal components analysis and logistic regression in order to investigate the effect of consumers’ financial capabilities and technology use on the decision to purchase online. The outcome of this study firstly identifies six dimensions of financial capabilities, namely, digital banking usage, financial service risk, financial advice, payment risk, risk tolerance, and financial attitude. Secondly, the finding revealed that individuals who use smartphones and administrate a social media account, are more likely to involve in purchasing through online channels. Moreover, the decision to purchase online is more prone for those individuals who manifest high levels in digital banking usage, financial advice, prior bank experience and technology usage, and low levels in attitude towards payment risk and attitude towards risk tolerance. This paper offers useful insights concerning the determinants of online purchasing by combining individuals’ financial capability, technology and social media usage along with its demographic characteristics. In term of practical contribution, this study provides a useful model by incorporating for measuring and managing consumers’ financial capability to enhance their involvement and to reduce their cognitive dissonance in the online shopping context. This study also contributes to the accumulated knowledge and encourages consumers to use digital banking and consult their financial issues when purchasing online. © 2020, Technical University of Liberec. All rights reserved.","Financial capability; Logistic regression; Online shopping; Prior bank experience; Smartphone; Social media",{"$nulls":7},"Ajzen I., The theory of planned behavior, Organizational Behavior and Human Decision Processes, 50, 2, pp. 179-211, (1991); Al-Debei M.M., Akroush M.N., Ashouri M.I., Consumer attitudes towards online shopping: The effects of trust, perceived benefits, and perceived web quality, Internet Research, 25, 5, pp. 707-733, (2015); Atkinson A., McKay S., Kempson E., Collard S., Levels of Financial Capability in the UK: Results of a Baseline Survey, (2006); The Retail Payment Costs and Savings in Albania, (2018); Homebanking Transactions 2005-2019., (2019); Barbaranelli C., Guidugli S.P., Di Giorgio D., Gramazio M., Personal determinants of purchasing of pharmaceutical products online. 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The challenges and opportunities of Social Media, Business Horizons, 53, 1, pp. 59-68, (2010); Karjaluoto H., Mattila M., Pento T., Factors underlying attitude formation towards online banking in Finland, International Journal of Bank Marketing, 20, 6, pp. 261-272, (2002); Katawetawaraks C., Wang C.L., Online Shopper Behavior: Influences of Online Shopping Decision, Asian Journal of Business Research, 1, 2, pp. 66-74, (2011); Kempson E., Collard S., Moore N., Measuring Financial Capability: An Exploratory Study (Consumer Research Report 37), (2005); Kim D.J., Ferrin D.L., Rao H.R., A trust-based consumer decision-making model in electronic commerce: The role of trust, perceived risk, and their antecedents, Decision Support Systems, 44, 2, pp. 544-564, (2008); Kim Y., Kim W., Yang T., The effect of the triple helix system and habitat on regional entrepreneurship: Empirical evidence from the U.S, Research Policy, 41, 1, pp. 154-166, (2012); Kramer M.M., Financial literacy, confidence and financial advice seeking, Journal of Economic Behavior & Organization, 131, A, pp. 198-217, (2016); Lam L.T., Lam M.K., The association between financial literacy and Problematic Internet Shopping in a multinational sample, Addictive Behaviors Reports, 6, pp. 123-127, (2017); Laroche M., Habibi M.R., Richard M.-O., To be or not to be in social media: How brand loyalty is affected by social media?, International Journal of Information Management, 33, 1, pp. 76-82, (2013); Lusardi A., Mitchell O.S., The Economic Importance of Financial Literacy: Theory and Evidence, Journal of Economic Literature, 52, 1, pp. 5-44, (2014); Marsden M., Zick C.D., Mayer R.N., The Value of Seeking Financial Advice, Journal of Family and Economic Issues, 32, 4, pp. 625-643, (2011); Mbama C.I., Ezepue P., Alboul L., Beer M., Digital banking, customer experience and financial performance, Journal of Research in Interactive Marketing, 12, 4, pp. 432-451, (2018); National Consumer and Financial Literacy Framework, (2011); McKay S., Understanding Financial Capability in Canada: Analysis of the Canadian Financial Capability Survey., (2011); Mehrabian A., Russell J., An Approach to Environmental Psychology., (1974); Mikalef P., Giannakos M., Pateli A., Shopping and Word-of-Mouth Intentions on Social Media, Journal of Theoretical and Applied Electronic Commerce Research, 8, 1, pp. 17-34, (2013); Mou J., Shin D.H., Cohen J.F., Trust and risk in consumer acceptance of e-services, Electronic Commerce Research, 17, 2, pp. 255-288, (2017); Naseri M.B., Elliott G., Role of demographics, social connectedness and prior internet experience in adoption of online shopping: Applications for direct marketing, Journal of Targeting, Measurement and Analysis for Marketing, 19, 2, pp. 69-84, (2011); Negash S., Meso P., Wiredu G., Mobile Banking Adoption in the United States: Adapting mobile banking features from lowincome countries, A Proceeding of SIG Globdev Fourth Annual Workshop, pp. 1-6, (2011); Nguyen T.A.N., Rozsa Z., Financial Literacy and Financial Advice Seeking for Retirement Investment Choice, Journal of Competitiveness, 11, 1, pp. 70-83, (2019); Financial Education in Europe: Trends and Recent Developments, (2016); Oertzen A.S., Odekerken-Schroder G., Achieving continued usage in online banking: A post-adoption study, International Journal of Bank Marketing, 37, 6, pp. 1394-1418, (2019); Oluwafemi O.J., Adebiyi S.O., Customer Loyalty and Integrated Marketing Communications among Subscribers of Telecommunication Firms in Lagos Metropolis, Nigeria. 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Manage.","Article","Final","All Open Access; Bronze Open Access; Green Open Access","Scopus","2-s2.0-85086468053"]
["Sun P.; Veelenturf L.P.; Hewitt M.; Van Woensel T.","Sun, Peng (57195053798); Veelenturf, Lucas P. (36667703700); Hewitt, Mike (34872009800); Van Woensel, Tom (12781314700)","57195053798; 36667703700; 34872009800; 12781314700","Adaptive large neighborhood search for the time-dependent profitable pickup and delivery problem with time windows",2020.0,"Transportation Research Part E: Logistics and Transportation Review",138.0,null,101942.0,null,null,null,50.0,"10.1016/j.tre.2020.101942","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85084660772&doi=10.1016%2fj.tre.2020.101942&partnerID=40&md5=217fbc18293c6d4eba071651a175e69b","Kühne Logistics University, Hamburg, Germany; School of Industrial Engineering, Eindhoven University of Technology, Eindhoven, Netherlands; Quinlan School of Business Loyola University Chicago, Chicago, IL, United States","Sun P., Kühne Logistics University, Hamburg, Germany, School of Industrial Engineering, Eindhoven University of Technology, Eindhoven, Netherlands; Veelenturf L.P., School of Industrial Engineering, Eindhoven University of Technology, Eindhoven, Netherlands; Hewitt M., Quinlan School of Business Loyola University Chicago, Chicago, IL, United States; Van Woensel T., School of Industrial Engineering, Eindhoven University of Technology, Eindhoven, Netherlands","The rise of e-commerce has increased the demands placed on pickup and delivery operations, as well as customer expectations regarding the quality of services provided by those operations. One strategy a logistics provider can employ for meeting these increases in demands and expectations is to complement and coordinate its fleet operations with those of for-hire, third-party logistics providers. Herein, we study an optimization problem for coordinating these operations: the time-dependent profitable pickup and delivery problem with time windows. In this problem, the logistics provider has the opportunity to use its fleet of capacitated vehicles to transport shipment requests, for a profit, from pickup to delivery locations. Owing to demographic and market trends, we focus on an urban setting, wherein road congestion is a factor. As a result, the problem explicitly recognizes that travel times may be time-dependent. The logistics provider seeks to maximize its profits from serving transportation requests, which we compute as the difference between the profits associated with transported requests and transportation costs. To solve this problem, we propose an adaptive large neighborhood search algorithm. The results of our extensive computational study show that the proposed algorithm can find high-quality solutions quickly on instances with up to 75 transportation requests. Furthermore, we study its impact on profits when explicitly recognizing traffic congestion during planning operations. © 2020","ALNS; Pickup and delivery problem; Profitable; Time-dependent travel time","Fleet operations; Outsourcing; Pickups; Traffic congestion; Travel time; Adaptive large neighborhood searches; ALNS; E- commerces; Logistics providers; Pickup and delivery problems; Pickup and delivery problems with time windows; Profitable; Time dependent; Time-dependent travel time; Travel-time; algorithm; electronic commerce; neighborhood; optimization; traffic congestion; Profitability",{"$nulls":4},"Deutsche Forschungsgemeinschaft, DFG, (GO 1841/5–1); China Scholarship Council, CSC, (201206160092)","The authors gratefully acknowledge funds provided by China Scholarship Council (CSC) under Grant No.201206160092 and the German Research Foundation (DFG, project GO 1841/5–1). Special thanks also due to Asvin Goel for his valuable comments. ","Ali F., (2019); Balseiro S.R., Loiseau I., Ramont J., An ant colony algorithm hybridized with insertion heuristics for the time dependent vehicle routing problem with time windows, Comput. Oper. Res., 38, pp. 954-966, (2011); (2020); Cordeau J.-F., Ghiani G., Guerriero E., Analysis and branch-and-cut algorithm for the time-dependent travelling salesman problem, Transport. Sci., 48, 1, pp. 46-58, (2014); Cordeau J.-F., Laporte G., A tabu search heuristic for the static multi-vehicle dial-a-ride problem, Transport. Res. Part B: Methodol., 37, 6, pp. 579-594, (2003); Cordeau J.-F., Laporte G., Ropke S., (2008); Cortes-Murcia D.L., Prodhon C., Afsar H.M., The electric vehicle routing problem with time windows, partial recharges and satellite customers, Transport. Res. Part E: Logist. Transport. Rev., 130, pp. 184-206, (2019); Dabia S., Ropke S., Van Woensel T., de Kok T., Branch and cut and price for the time dependent vehicle routing problem with time windows, Transport. 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Sci., (2019); Wang Z., Delivering meals for multiple suppliers: Exclusive or sharing logistics service, Transport. Res. Part E: Logist. Transport. Rev., 118, pp. 496-512, (2018); Xu M., Et al., (2017)","P. Sun; Eindhoven University of Technology, Eindhoven, Netherlands; email: p.sun@tue.nl",null,"Elsevier Ltd",{"$nulls":5},1.3665545E7,null,null,null,"English","Transp. Res. Part E Logist. Transp. Rev.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85084660772"]
["Yahya S.; Sugiyanto C.","Yahya, Syarifudin (58124521100); Sugiyanto, Catur (55351020800)","58124521100; 55351020800","Indonesian Demand for Online Shopping: Revisited",2020.0,"Journal of Indonesian Economy and Business",35.0,3.0,null,188.0,203.0,15.0,4.0,"10.22146/jieb.55358","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137411020&doi=10.22146%2fjieb.55358&partnerID=40&md5=6c7c60c817e020cedd273ca129230857","BPS Staf, Jl Dr Sutomo nà 5-8, Pasar Baru, Kec. Sawah Besar, DKI, Kota Jakarta Pusat, 10710, Indonesia; Department of Economics, Faculty of Economics and Business, Universitas Gadjah Mada, Yogyakarta, 55281, Indonesia","Yahya S., BPS Staf, Jl Dr Sutomo nà 5-8, Pasar Baru, Kec. Sawah Besar, DKI, Kota Jakarta Pusat, 10710, Indonesia; Sugiyanto C., Department of Economics, Faculty of Economics and Business, Universitas Gadjah Mada, Yogyakarta, 55281, Indonesia","Introduction/Main Objectives: This study aims to analyze the factors that influence online shopping. Data are aggregated at the national, island, and regional levels. The regions are categorized based on their level of demand for online shopping. Background Problems: The rapid development of information and communications technology contributes to the transformation of the digital economy. By using 281,185 internet users from the National Households Survey (Survei Sosial Ekonomi- Susenas) 2017 data, we found that the percentage of online shopping in Indonesia is 7.59%. Online shopping is concentrated on the island of Java, especially in the Greater Jakarta area (Jakarta, Bogor, Depok, Tangerang, and Bekasi). Novelty: This study analyzes online shopping from the point of view of economic development studies, especially related to the development of information technology and the digital economy. Research Methods: We used a binary logistic regression analysis to assess the effect of demographic, socio-economic, and spatial factors on an individual's decision to shop online. Finding/Results: The results indicate that individuals who have a greater tendency to shop online are those who have a high income, are women, can access the internet using mobile phones, they are the spouses of the heads of households, are 25 to30 years old, live in urban areas, have graduated from college (especially with a diploma), and work in the tertiary sector. The higher that the share of online shopping is in an area, the more intense the influence of individual characteristics will be on the tendency to shop online, according to the demographic and socio-economic factors, while the spatial factors will fade away. Conclusion: Income, gender, internet access, and the shopper's position in the household are factors that significantly influence individuals to shop online. © 2020 Gadjah Mada University. All right reserved.","female consumer; internet access; online shopping; urban consumer",{"$nulls":7},"Penetrasi dan perilaku pengguna internet Indonesia, (2017); Klasifikasi Baku Lapangan Usaha Indonesia 2015, (2015); Hasil Pendaftaran Usaha/Perusahaan Sensus Ekonomi 2016 Indonesia, (2017); Pedoman Pengawasan Survei Komuter Bandung Raya dan Gerbangkertosusila 2017, (2017); Statistik Kesejahteraan Rakyat 2017, (2017); Statistik Indonesia 2018, (2018); Beckers J., Cardenas I., Verhetsel A., Identifying the geography of online shopping adoption in Belgium, Journal of Retailing and Consumer Services, 45, pp. 33-41, (2018); Bellman S., Lohse G. L., Johnson E. J., Predictors of online buying behavior, Communications of the ACM, 42, 12, pp. 32-38, (1999); Bigne E., Ruiz C., Sanz S., The impact of internet user shopping patterns and demographics on consumer mobile buying behaviour, Journal of Electronic Commerce Research, 6, 3, (2005); Blackwell R. D., Miniard P. W., Engel J. 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Z., Effect of consumer demographic factors on purchasing herbal products online in Malaysia, International Journal of Economics and Management Engineering, 7, 8, pp. 2380-2386, (2013); Richa D., Impact of demographic factors of consumers on online shopping behaviour: A study of consumers in India, International journal of engineering and management sciences, 3, 1, pp. 43-52, (2012); Sin L., Tse A., Profiling internet shoppers in Hong Kong: demographic, psychographic, attitudinal and experiential factors, Journal of International Consumer Marketing, 15, 1, pp. 7-29, (2002); Smith A. D., Rupp W. T., Strategic online customer decision making: leveraging the transformational power of the Internet, Online information review, (2003); Swinyard W. R., Smith S. M., Why people (don't) shop online: A lifestyle study of the internet consumer, Psychology & marketing, 20, 7, pp. 567-597, (2003); Tsao W. C., Hsieh M. T., Lin T. M., Intensifying online loyalty! The power of website quality and the perceived value of consumer/seller relationship, Industrial Management & Data Systems, (2016); Valarezo A., Perez-Amaral T., Garin-Munoz T., Garcia I. H., Lopez R., Drivers and barriers to cross-border ecommerce: Evidence from Spanish individual behavior, Telecommunications Policy, 42, 6, pp. 464-473, (2018); Wang C. L., Zhang Y., Ye L. R., Nguyen D. D., Subscription to fee-based online services: What makes consumer pay for online content?, Journal of Electronic Commerce Research, 6, 4, (2005); Yang B., Lester D., Gender differences in e-commerce, Applied Economics, 37, 18, pp. 2077-2089, (2005); Yusmita F., Nik Kamariah Nik Mat, (2012); Yusoff Yuhainis Mohd, azhar Fitrisal, Behjati Saeed, Determinants of Online Purchasing Behavior in Nanggroe Aceh Darussalam, American Journal of Economics June, pp. 153-157, (2012); Zhou L., Dai L., Zhang D., Online shopping acceptance model-A critical survey of consumer factors in online shopping, Journal of Electronic commerce research, 8, 1, (2007)","C. Sugiyanto; Department of Economics, Faculty of Economics and Business, Universitas Gadjah Mada, Yogyakarta, 55281, Indonesia; email: catur@ugm.ac.id",null,"Gadjah Mada University",{"$nulls":5},2.0858272E7,null,null,null,"English","J. Indones. Econ. Bus.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85137411020"]
["Fraske T.; Bienzeisler B.","Fraske, Tim (57221008079); Bienzeisler, Bernd (55641097800)","57221008079; 55641097800","Toward smart and sustainable traffic solutions: a case study of the geography of transitions in urban logistics",2020.0,"Sustainability: Science, Practice, and Policy",16.0,1.0,null,353.0,366.0,13.0,8.0,"10.1080/15487733.2020.1840804","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85097992177&doi=10.1080%2f15487733.2020.1840804&partnerID=40&md5=cd67373a11e619bb6fe5c50b57002c64","Fraunhofer Institute for Industrial Engineering IAO, Research and Innovation Center for Cognitive Service Systems, Heilbronn, Germany; Department of Geography, Kiel University, Kiel, Germany","Fraske T., Fraunhofer Institute for Industrial Engineering IAO, Research and Innovation Center for Cognitive Service Systems, Heilbronn, Germany, Department of Geography, Kiel University, Kiel, Germany; Bienzeisler B., Fraunhofer Institute for Industrial Engineering IAO, Research and Innovation Center for Cognitive Service Systems, Heilbronn, Germany","City logistics as a research field offers a wide range of potential solutions and technologies for advancing toward modern and sustainable mobility. As societies demand environments that are more ecological and cities tackle the effects of growing e-commerce, innovative tools to regulate urban economic traffic become increasingly important. Based on the theoretical approach of the multi-level perspective, this case study combines findings from city-logistics research with evolutionary economics to gain a deeper understanding of the development of smart sustainable cities. The study strengthens the view on the geography of a transition with a focus on the interplay of changed practices, involved actors, and pathways. The analysis is based on qualitative social research, including interviews with various stakeholders. It examines the implementation of an app-based technology to regulate economic transport and delivery traffic in Barcelona. The municipal administration introduced the innovation in the Urban Mobility Plan and quickly integrated it across the city. The commitment of a software developer resulted in an enhanced version of the technology by a startup company. The development of the original innovation thus led to geographic diffusion of the upgraded technology through processing actors’ feedback and targeting new markets outside the city. © 2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group on behalf of the University of Stuttgart.","City logistics; economic geography; innovation studies; multi-level perspective; sustainable mobility",{"$nulls":5},"Fraunhofer Institute for Industrial Engineering IAO; German Federal Ministry of Education and Research; Bundesministerium für Bildung und Forschung, BMBF, (01UU1605A)","Funding text 1: This research was conducted with the support of the Fraunhofer Institute for Industrial Engineering IAO, Germany. The authors cordially thank all the anonymous respondents for their insights and reliable cooperation during our research project. We also thank the editors and reviewers for improving this article.; Funding text 2: The guest editors of the Special Issue thank the German Federal Ministry of Education and Research (BMBF) for supporting this Special Issue under grant number 01UU1605A. 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Five Tensions in the Visions and Practices of the Smart-Sustainable City, Technological Forecasting and Social Change, 133, pp. 269-278, (2018); Marvin S., Luque-Ayala A., McFarlane C., Smart Urbanism: Utopian Vision or False Dawn?, (2015); Marvin S., Bulkeley H., Mai L., McCormick K., Palgan Y., Urban Living Labs: Experimenting with City Futures, (2018); Nelson R., Winter S., In Search of a Useful Theory of Innovation, Research Policy, 6, 1, pp. 36-76, (1977); Nelson R., Winter S., An Evolutionary Theory of Economic Change, (1982); Nelson R., Winter S., Evolutionary Theorizing in Economics, Journal of Economic Perspectives, 16, 2, pp. 23-46, (2002); Raven R., Ghosh B., Wieczorek A., Stirling A., Ghosh D., Jolly S., Karjangtimapron E., Et al., Unpacking Sustainabilities in Diverse Transition Contexts: Solar Photovoltaic and Urban Mobility Experiments in India and Thailand, Sustainability Science, 12, 4, pp. 579-596, (2017); Roberts C., Geels F., Conditions for Politically Accelerated Transitions: Historical Institutionalism, the Multi-Level Perspective, and Two Historical Case Studies in Transport and Agriculture, Technological Forecasting and Social Change, 140, pp. 221-240, (2019); Rose W., Mollenkopf D., Autry C., Bell J., Exploring Urban Institutional Pressures on Logistics Service Providers, International Journal of Physical Distribution and Logistics Management, 46, 2, pp. 153-176, (2016); Shove E., Walker G., Governing Transitions in the Sustainability of Everyday Life, Research Policy, 39, 4, pp. 471-476, (2010); Smith A., Voss J.-P., Grin J., Innovation Studies and Sustainability Transitions: The Allure of the Multi-Level Perspective and Its Challenges, Research Policy, 39, 4, pp. 435-448, (2010); Thornbush M., Golubchikov O., Sustainable Urbanism in Digital Transitions: From Low Carbon to Smart Sustainable Cities, (2019); Trencher G., Towards the Smart City 2.0: Empirical Evidence of Using Smartness as a Tool for Tackling Social Challenges, Technological Forecasting and Social Change, 142, pp. 117-128, (2019); Truffer B., Coenen L., Environmental Innovation and Sustainability Transitions in Regional Studies, Regional Studies, 46, 1, pp. 1-21, (2012); Turnheim B., Kivimaa P., Berkhout F., Innovating Climate Governance: Moving beyond Experiments, (2018); Whittle C., Whitmarsh L., Haggar P., Morgan P., Parkhurst G., User Decision-Making in Transitions to Electrified, Autonomous, Shared or Reduced Mobility, Transportation Research Part D: Transport and Environment, 71, pp. 302-319, (2019); Yadav P., Malakar Y., Davies P., Multi-Scalar Energy Transitions in Rural Households: Distributed Photovoltaics as a Circuit Breaker to the Energy Poverty Cycle in India, Energy Research and Social Science, 48, pp. 1-12, (2019)",null,null,"Bellwether Publishing, Ltd.",{"$nulls":5},1.5487733E7,null,null,null,"English","Sustainability Sci. Pract. Policy","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85097992177"]
["Cobelli N.; Wilkinson G.","Cobelli, Nicola (36634054600); Wilkinson, Georgina (57196658945)","36634054600; 57196658945","Online wine purchasing: a comparison between South Africa and Italy",2020.0,"TQM Journal",32.0,4.0,null,837.0,847.0,10.0,6.0,"10.1108/TQM-10-2019-0242","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85079451484&doi=10.1108%2fTQM-10-2019-0242&partnerID=40&md5=23188ea5294297ff8a60d848ff9a2427","Department of Business Administration, The University of Verona, Verona, Italy; Vinifera Program, Montpellier SupAgro, Languedoc-Roussillon, Montpellier, France","Cobelli N., Department of Business Administration, The University of Verona, Verona, Italy; Wilkinson G., Vinifera Program, Montpellier SupAgro, Languedoc-Roussillon, Montpellier, France","Purpose: The purpose of this study is to explore South African and Italian consumers' attitude toward online wine purchasing. In detail, through the application of the technology acceptance model (TAM), this research intends to explain the antecedents of consumers actual online purchasing of wine in South Africa and Italy. Design/methodology/approach: Two questionnaire-based surveys were conducted, yielding a sample of 190 consumers in South Africa and 179 in Italy. Data were analyzed through several techniques including t-tests, principal component factor analyses, and binary logistic regressions. Findings: Overall, the findings show that South African and Italian online wine consumers are more similar than the offline wine consumers. However, perceived usefulness has an impact on the use of the online channel to purchase wine in Italy but not in South Africa, whereas perceived complexity has an effect in South Africa but not in Italy. Research limitations/implications: This study adopts a convenience sampling technique, suggesting that the used samples are not representative of the whole population. Moreover, TAM offers a simple and clear understanding of the actual use of wine e-commerce but overlooks other potential explanatory factors. Practical implications: Targeting online wine consumers in South Africa and Italy opens up the opportunity for using cross-national highly standardized product and communication strategies. However, different approaches are required to convert offline wine consumers to online wine consumers in South Africa and Italy. Originality/value: This is the first cross-national study investigating consumers' attitude toward online wine purchasing in South Africa and Italy. Moreover, it offers a comparison of online and offline wine consumers in the two countries. In addition, the research offers a new point of view over consumers of Italy and South Africa, two important countries in terms of wine production and consumption that can be very beneficial for wineries owners and managers. © 2019, Emerald Publishing Limited.","e-commerce; Industry 4.0; Italy; Online purchasing; South Africa; Wine; Wine marketing","Electronic commerce; Industry 4.0; Logistic regression; Sales; Surveys; Binary logistic regression; Communication strategy; Design/methodology/approach; Italy; Online purchasing; Principal component factor analysis; South Africa; Technology acceptance model; Wine",{"$nulls":6},"Ajami M.P., Navarro Elola L., Pastor J., Validation and improvement of the European customer satisfaction index for the Spanish wine sector, The TQM Journal, 30, 2, pp. 133-152, (2018); Allamani A., Voller F., Pepe P., Baccini M., Massini G., Cipriani F., Italy between drinking culture and control policies for alcoholic beverages, Substance Use and Misuse, 49, 12, pp. 1646-1664, (2014); Alonso A.D., Bressan A., O'Shea M., Krajsic V., Website and social media usage: implications for the further development of wine tourism, hospitality, and the wine sector, Tourism Planning and Development, 10, 3, pp. 229-248, (2013); Alreck P., Settle R.B., Gender effects on Internet, catalogue and store shopping, Journal of Database Marketing and Customer Strategy Management, 9, 2, pp. 150-162, (2002); Balestrini P., Gamble P., Country-of-origin effects on Chinese wine consumers, British Food Journal, 108, 5, pp. 396-412, (2006); Barber N., Almanza B.A., Donovan J.R., Motivational factors of gender, income and age on selecting a bottle of wine, International Journal of Wine Marketing, 18, 3, pp. 218-232, (2006); Begalli D., Codurri S., Gaeta D., Wine and web marketing strategies: the case study of Italian speciality wineries, British Food Journal, 111, 6, pp. 598-619, (2009); Brown A., Quality: where have we come from and what can we expect?, The TQM Journal, 25, 6, pp. 585-596, (2013); Cassia F., Ugolini M.M., Cobelli N., Gill L., Service-based vs. goods-based positioning of the product concept: effects on customer perceived value, The TQM Journal, 27, 2, pp. 247-255, (2015); Chaney I.M., External search effort for wine, International Journal of Wine Marketing, 12, 2, pp. 5-21, (2000); Corduas M., Cinquanta L., Ievoli C., The importance of wine attributes for purchase decisions: a study of Italian consumers' perception, Food Quality and Preference, 28, 2, pp. 407-418, (2013); Cox D.R., Snell E.J., Analysis of Binary Data, (1989); Davis F.D., Perceived usefulness, perceived ease of use, and user acceptance of information technology, MIS Quarterly, 13, 3, pp. 319-340, (1989); Dolan R., Conduit J., Fahy J., Goodman S., Facebook for wine brands: an analysis of strategies for Facebook posts and user engagement actions, Proceedings of the 9th AWBR International Conference, pp. 457-465, (2016); Fishbein M., Ajzen I., Belief, Attitude, Intention and Behavior: An Introduction to Theory and Research, (1975); Galloway G., Mitchell R., Getz D., Crouch G., Ong B., Sensation seeking and the prediction of attitudes and behaviours of wine tourists, Tourism Management, 29, 5, pp. 950-966, (2008); Goodman S., An international comparison of retail consumer wine choice, International Journal of Wine Business Research, 21, 1, pp. 41-49, (2009); Harrison-Walker L.J., If you build it, will they come? Barriers to international e-marketing, Journal of Marketing Theory and Practice, 10, 2, pp. 12-21, (2002); Herbst F., Von Arnim C., The role and influence of wine awards as perceived by the South African wine consumers, Acta Commercii, 9, 1, pp. 90-101, (2009); Higgins L.M., McGarry Wolf M., Bitter R., Amspacher W., Winery distribution choices and the online wine buyer, Journal of Food Distribution Research, 46, 3, pp. 32-49, (2015); Hollebeek L.D., Jaeger S.R., Brodie R.J., Balemi A., The influence of involvement on purchase intention for new world wine, Food Quality and Preference, 18, 8, pp. 1033-1049, (2007); Hosmer D.W., Lemeshow S., Applied Logistic Regression, (1989); Jiang L., Jun M., Yang Z., Customer-perceived value and loyalty: how do key service quality dimensions matter in the context of B2C e-commerce?, Service Business, 10, 2, pp. 301-317, (2016); Kahneman D., Thinking, Fast and Slow, (2011); Keown C., Casey M., Purchasing behaviour in the Northern Ireland wine market, British Food Journal, 97, 1, pp. 17-20, (1995); Kirkby, Wine e-commerce. A growing, yet challenging phenomenon, WineLand Magazine, (2014); Lee M.K., Cheung C.M., Chen Z., Acceptance of Internet-based learning medium: the role of extrinsic and intrinsic motivation, Information and Management, 42, 8, pp. 1095-1104, (2005); Limayem M., Khalifa M., Frini A., What makes consumers buy from Internet? A longitudinal study of online shopping, IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans, 30, 4, pp. 421-432, (2000); Lockshin L., Corsi A.M., Consumer behaviour for wine 2.0: a review since 2003 and future directions, Wine Economics and Policy, 1, 1, pp. 2-23, (2012); MarketLine, Wine in Italy, (2015); MarketLine, Wine in South Africa, (2015); Mason M., Gos L., Moretti A., The wine sector in the digital era: an empirical evaluation of E-quality opportunities, Journal of Internet Banking and Commerce, 20, 3, (2015); Menard S., Applied Logistic Regression Analysis, (2002); Mueller S., Szolnoki G., The relative influence of packaging, labelling, branding and sensory attributes on liking and purchase intent: consumers differ in their responsiveness, Food Quality and Preference, 21, 7, pp. 774-783, (2010); Nagelkerke N.J., A note on a general definition of the coefficient of determination, Biometrika, 78, 3, pp. 691-692, (1991); Ndanga L.Z., Louw A., Van Rooyen J., Increasing domestic consumption of South African wines: exploring the market potential of the “black diamonds, Agrekon, 49, 3, pp. 293-315, (2010); Ngwako S.M., Van Rooyen J., Janssens W., Bostyn F., D'Haese L., Exploring black economic empowerment in the South African wine industry: a case study, in International Food and Agribusiness Management Association, 18th Annual World Symposium, (2007); Notta O., Vlachvei A., Web Site utilization in SME business strategy: the case of Greek wine SMEs, World, 3, 5, pp. 131-141, (2013); Phillips R., A Short History of Wine, (2001); Qiu L., Li D., Applying TAM in B2C E-commerce research: an extended model, Tsinghua Science and Technology, 13, 3, pp. 265-272, (2008); South African wine industry statistics NR4, (2016); Sheridan M.J., Cazier J.A., May D.B., Leisure, wine and the internet: exploring the factors that impact the purchase of wine online, International Journal of Electronic Marketing and Retailing, 2, 3, pp. 284-297, (2008); Mid-year Population Estimates, 2014, (2014); Szymanski D.M., Bharadwaj S.G., Varadarajan P.R., Standardization versus adaptation of international marketing strategy: an empirical investigation, The Journal of Marketing, 57, 4, pp. 1-17, (1993); Yen Y.S., A comparison of quality satisfaction between transactional and relational customers in e-commerce, The TQM Journal, 26, 6, pp. 577-593, (2014)","N. Cobelli; Department of Business Administration, The University of Verona, Verona, Italy; email: nicola.cobelli@univr.it",null,"Emerald Group Holdings Ltd.",{"$nulls":5},1.7542731E7,null,null,null,"English","TQM J.","Article","Final","All Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85079451484"]
["Khare A.; Dixit S.; Sarkar S.","Khare, Arpita (36458467200); Dixit, Saumya (55340373500); Sarkar, Subhro (57196040457)","36458467200; 55340373500; 57196040457","Factors affecting website continuance intention: a study of Indian travel websites",2020.0,"Information Technology and Tourism",22.0,2.0,null,243.0,271.0,28.0,5.0,"10.1007/s40558-019-00162-1","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85077083541&doi=10.1007%2fs40558-019-00162-1&partnerID=40&md5=a7129f3bab1500aaead3bbfcd505b100","Indian Institute of Management Rohtak, Rohtak, India; Indian Institute of Technology Mandi, Mandi, India","Khare A., Indian Institute of Management Rohtak, Rohtak, India; Dixit S., Indian Institute of Technology Mandi, Mandi, India; Sarkar S., Indian Institute of Management Rohtak, Rohtak, India","Recent advancements in technology and changing consumer behaviour have presented several opportunities for companies. Companies are extensively using mobile apps to facilitate transactions and improve service delivery. The use of mobile apps has led to a shift from websites (desktop/mobile) enabled transactions to a mobile-based interface. However, from an organization’s viewpoint websites are crucial for branding and are perceived as cost-effective. Thus, to retain and attract consumers to websites, this research proposes inclusion of cultural and promotional dimensions into travel websites to make them more appealing to consumers. It implies customization of travel websites according to cultural and religious nuances for improving the service experience. Also, this study examines the role of network effect and website characteristics on website continuance intention. Data collected from 356 users of Indian travel websites was analyzed using structural equation modeling. The findings suggest that referent network size and perceived complementarity influence network benefits which have an impact on customers’ website continuance intention. Website characteristics like ease of information accessibility, interactivity, promotional and pilgrimage offers emerged as antecedents to website continuance intention. This research will create a better understanding of e-commerce system amongst managers of websites and guide them in designing strategy for retaining consumers. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature.","Continuance intention; India; Network effects; Travel website; Website characteristics",{"$nulls":7},{"$cut":{"chars":17250,"head":"Abdullah D., Jayaraman K., Kamal S.B.M., A conceptual model of interactive hotel website: the role of perceived website interactivity and customer perceived value toward website revisit intention, Proc Econ Financ, 37, pp. 170-175, (2016); Abou-Shouk M.A., Khalifa G.S., The influence of website quality dimensions on e-purchasing behavior and e-loyalty: a comparative study of Egyptian travel agents and hotels, J Travel Tour Mark, 34, 5, pp. 608-623, (2017); Agag G.M., El-Masry A.A., Why do consumers trust online travel websites? Drivers and outcomes of consumer trust toward online travel websites, J Travel Res, 56, 3, pp. 347-369, (2017); Ahrholdt D.C., Empirical identification of success-enhancing web site signals in e-tailing: an analysis based on known e-tailers and the theory of reasoned action, J Mark Theory Pract, 19, 4, pp. 441-458, (2011); Anderson J.C., Gerbing D.W., Structural equation modeling in practice: a review and recommended two-step approach, Psychol Bull, 103, 3, (1988); Digital Commerce Market Expected to Cross $50 Billion Mark in 2018: Study, (2017); Atchariyachanvanich K., Okada H., Sonehara N., What keeps online customers repurchasing through the internet?, ACM SIGecom Exch, 6, 2, pp. 47-57, (2007); Bhattacherjee A., Understanding information systems continuance: an expectation-confirmation model, MIS Q, 25, 3, pp. 351-370, (2001); Bonera M., The propensity of e-commerce usage: the influencing variables, Manag Res Rev, 34, 7, pp. 821-837, (2011); Buttner O.B., Goritz A.S., Perceived trustworthiness of online shops, J Consum Behav Int Res Rev, 7, 1, pp. 35-50, (2008); Byrne B.M., Structural equation modeling with LISREL, PRELIS, and SIMPLIS: basic concepts, applications, and programming, (2013); Campo S., Yague M.J., Tourist loyalty to tour operator: effects of price promotions and tourist effort, J Travel Res, 46, 3, pp. 318-326, (2008); Chen C., Identifying significant factors influencing consumer trust in an online travel site, Inf Technol Tour, 8, 3-4, pp. 197-214, (2006); Chu R., What online Hong Kong travelers look for on airline/travel websites?, Int J Hosp Manag, 20, 1, pp. 95-100, (2001); Clark R.A., Zboja J.J., Goldsmith R.E., Antecedents of coupon proneness: a key mediator of coupon redemption, J Promot Manag, 19, 2, pp. 188-210, (2013); Cyr D., Website design, trust and culture: an eight country investigation, Electron Commer Res Appl, 12, 6, pp. 373-385, (2013); Cyr D., Modeling web site design across cultures: relationships to trust, satisfaction, and e-loyalty, J Manag Inf Syst, 24, 4, pp. 47-72, (2014); Cyr D., Kindra G.S., Dash S., Web site design, trust, satisfaction, and e-loyalty: the Indian experience, Online Inf Rev, 32, 6, pp. 773-790, (2008); Cyr D., Head M., Larios H., Colour appeal in website design within and across cultures: a multi-method evaluation, Int J Human-Comput Stud, 68, 1-2, pp. 1-21, (2010); Davis L., Wang S., Lindridge A., Culture influences on emotional responses to on-line store atmospheric cues, J Bus Res, 61, 8, pp. 806-812, (2008); deAscaniis S., Cantoni L., Information and communication technologies in religious tourism and pilgrimage, Int J Relig Tour Pilgr, 4, 3, (2016); Degeratu A.M., Rangaswamy A., Wu J., Consumer choice behavior in online and traditional supermarkets: the effects of brand name, price, and other search attributes, Int J Res Mark, 17, 1, pp. 55-78, (2000); Dholakia U.M., What makes groupon promotions profitable for businesses?, (2011); Dholakia R.R., Zhao M., Dholakia N., Fortin D.R., Interactivity and revisits to websites: A theoretical framework, (2000); Doney P.M., Cannon J.P., An examination of the nature of trust in buyer–seller relationships, J Mark, 61, pp. 35-51, (1997); Evanschitzky H., Iyer G.R., Hesse J., Ahlert D., E-satisfaction: a re-examination, J Retail, 80, pp. 239-247, (2004); Field A., Discovering statistics using SPSS, (2009); Fink D., Laupase R., Perceptions of web site design characteristics: a Malaysian/Australian comparison, Internet Res, 10, 1, pp. 44-55, (2000); Flavian C., Guinaliu M., Gurrea R., The role pla"}},"S. Dixit; Indian Institute of Technology Mandi, Mandi, India; email: saumya.mgmt@gmail.com",null,"Springer",{"$nulls":5},1.0983058E7,null,null,null,"English","Inf. Technol. Tour.","Article","Final",null,"Scopus","2-s2.0-85077083541"]
["Liu Y.; Han D.; Wang L.; Xu C.-Z.","Liu, Yandong (57202943402); Han, Dong (57214752271); Wang, Lujia (35175084300); Xu, Cheng-Zhong (55600419500)","57202943402; 57214752271; 35175084300; 55600419500","HGHA: task allocation and path planning for warehouse agents",2020.0,"Assembly Automation",41.0,2.0,null,165.0,173.0,8.0,8.0,"10.1108/AA-10-2020-0152","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85098672200&doi=10.1108%2fAA-10-2020-0152&partnerID=40&md5=06dc5d7456c2221e6b07b64ff8e598b3","Center for Cloud Computing, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China; Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China; State Key Lab of IOTSC, Department of Computer and Information Science, University of Macau, Taipa, Macao; Shenzhen College of Advanced Technology, University of the Chinese Academy of Sciences, Beijing, China","Liu Y., Center for Cloud Computing, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China, Shenzhen College of Advanced Technology, University of the Chinese Academy of Sciences, Beijing, China; Han D., Center for Cloud Computing, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China, Shenzhen College of Advanced Technology, University of the Chinese Academy of Sciences, Beijing, China; Wang L., Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China; Xu C.-Z., State Key Lab of IOTSC, Department of Computer and Information Science, University of Macau, Taipa, Macao","Purpose: With the rapid development of e-commerce, logistics demand is increasing day by day. The modern warehousing with a multi-agent system as the core comes into being. This paper aims to study the task allocation and path-planning (TAPP) problem as required by the multi-agent warehouse system. Design/methodology/approach: The TAPP problem targets to minimize the makespan by allocating tasks to the agents and planning collision-free paths for the agents. This paper presents the Hierarchical Genetic Highways Algorithm (HGHA), a hierarchical algorithm combining optimization and multi-agent path-finding (MAPF). The top-level is the genetic algorithm (GA), allocating tasks to agents in an optimized way. The lower level is the so-called highways local repair (HLR) process, avoiding the collisions by local repairment if and only if conflicts arise. Findings: Experiments demonstrate that HGHA performs faster and more efficient for the warehouse scenario than max multi-flow. This paper also applies HGHA to TAPP instances with a hundred agents and a thousand storage locations in a customized warehouse simulation platform with MultiBots. Originality/value: This paper formulates the multi-agent warehousing distribution problem, TAPP. The HGHA based on hierarchical architecture solves the TAPP accurately and quickly. Verifying the HGHA by the large-scale multi-agent simulation platform MultiBots. © 2020, Emerald Publishing Limited.","Hierarchical Genetic Highways Algorithm; Multi-agent; Path planning; Task allocation","Genetic algorithms; Multi agent systems; Simulation platform; Warehouses; Collision-free paths; Design/methodology/approach; Distribution problem; Hierarchical algorithm; Hierarchical architectures; Multi agent simulation; Storage location; Warehouse systems; Software agents",{"$nulls":6},"Adhau S., Mittal M., Mittal A., A multi-agent system for distributed multi-project scheduling: an auction-based negotiation approach, Engineering Applications of Artificial Intelligence, 25, 8, pp. 1738-1751, (2012); Ayari A., Bouamama S., ACD 3 GPSO: automatic clustering-based algorithm for multi-robot task allocation using dynamic distributed double-guided particle swarm optimization, Assembly Automation, 40, 2, (2019); Barer M., Sharon G., Stern R., Felner A., Suboptimal variants of the conflict-based search algorithm for the multi-agent pathfinding problem, Seventh Annual Symposium on Combinatorial Search, (2014); Ferner C., Wagner G., Choset H., ODrM* optimal multirobot path planning in low dimensional search spaces, IEEE International Conference on Robotics and Automation (ICRA), pp. 3854-3859, (2013); FerriMunafoTesei G., Lepage K., A market-based task allocation framework for autonomous underwater surveillance networks, Oceans, (2017); Gerkey B.P., Mataric M.J., A formal analysis and taxonomy of task allocation in multi-robot systems, The International Journal of Robotics Research, 23, 9, pp. 939-954, (2004); Holland J.H., Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence, (1992); Liu Y., Wang L., Huang H., Liu M., Xu C.-Z., A novel swarm robot simulation platform for warehousing logistics, 2017 IEEE International Conference on Robotics and Biomimetics (ROBIO), pp. 2669-2674, (2017); Ma H., Koenig S., Optimal target assignment and path finding for teams of agents, International Foundation for Autonomous Agents and Multiagent Systems, pp. 1144-1152, (2016); Ma H., Tovey C.A., Sharon G., Kumar T.S., Koenig S., Multi-Agent Path Finding with Payload Transfers and the Package-Exchange Robot-Routing Problem, pp. 3166-3173, (2016); Morris R., Pasareanu C.S., Luckow K.S., Malik W., Ma H., Kumar T.S., Koenig S., Planning, Scheduling and Monitoring for Airport Surface Operations, (2016); Ohta Y., Sato H., Evolutionary multi-objective air-conditioning schedule optimization for office buildings, Proceedings of the Genetic and Evolutionary Computation Conference Companion, (2018); Rahimi M., Gibb S., Shen Y., La H.M., A Comparison of Various Approaches to Reinforcement Learning Algorithms for Multi-Robot Box Pushing, pp. 16-30, (2019); Sharon G., Stern R., Felner A., Sturtevant N.R., Conflict-based search for optimal multi-agent pathfinding, Artificial Intelligence, 219, pp. 40-66, (2015); Surynek P., Reduced time-expansion graphs and goal decomposition for solving cooperative path finding Sub-Optimally, IJCAI, pp. 1916-1922, (2015); Wang K.-H.C., Botea A., Fast and memory-efficient multi-agent pathfinding, ICAPS, pp. 380-387, (2008); Wang L., Liu M., Meng M.Q.-H., Real-time multisensor data retrieval for cloud robotic systems, IEEE Transactions on Automation Science and Engineering, 12, 2, pp. 507-518, (2015); Wang X., Li Z., Xu P., Xu Y., Gao X., Chen H.-H., Spectrum sharing in cognitive radio networks – an auction-based approach, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 40, pp. 587-596, (2010); Wu Y., Jiang B., Lu N., A descriptor system approach for estimation of incipient faults with application to high-speed railway traction devices, Systems, (2017); Wu Y., Jiang B., Wang Y., Incipient winding fault detection and diagnosis for squirrel-cage induction motors equipped on CRH trains, ISA Transactions, 99, pp. 488-495, (2020); Wurman P.R., D'Andrea R., Mountz M., Coordinating hundreds of cooperative, autonomous vehicles in warehouses, AI Magazine, 29, (2008); Xiao H., Cui R., Xu D., Cooperative multi-agent search using Bayesian approach with connectivity maintenance, Assembly Automation, 40, 1, (2019); Yu J., Lavalle S.M., Multi-agent path planning and network flow, Algorithmic Foundations of Robotics X, (2013); Yu J., Lavalle S.M., Planning optimal paths for multiple robots on graphs, 2013 IEEE International Conference on Robotics and Automation (ICRA), pp. 3612-3617, (2013); Yuxiang S., Ming L., Meng Q.-H., Motion removal for reliable RGB-D SLAM in dynamic environments, Robotics and Autonomous Systems, 108, pp. 115-128, (2018); Zelinsky A., A mobile robot exploration algorithm, IEEE Transactions on Robotics and Automation, 8, 6, pp. 707-717, (1992)","L. Wang; Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China; email: lj.wang1@siat.ac.cn",null,"Emerald Group Holdings Ltd.",{"$nulls":5},1445154.0,null,"ASAUD",null,"English","Assem. Autom.","Article","Final",null,"Scopus","2-s2.0-85098672200"]
["Wei C.; Asian S.; Ertek G.; Hu Z.-H.","Wei, Chen (56424564700); Asian, Sobhan (56335596700); Ertek, Gurdal (6508147381); Hu, Zhi-Hua (35279757500)","56424564700; 56335596700; 6508147381; 35279757500","Location-based pricing and channel selection in a supply chain: a case study from the food retail industry",2020.0,"Annals of Operations Research",291.0,"2024-02-01",null,959.0,984.0,25.0,29.0,"10.1007/s10479-018-3040-7","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85053427199&doi=10.1007%2fs10479-018-3040-7&partnerID=40&md5=fb06f2f33964a502419e90e6c71ad592","Logistics Research Center, Shanghai Maritime University, Shanghai, China; La Trobe Business School, La Trobe University, Melbourne, Australia; College of Business, Abu Dhabi University, Abu Dhabi, United Arab Emirates","Wei C., Logistics Research Center, Shanghai Maritime University, Shanghai, China; Asian S., La Trobe Business School, La Trobe University, Melbourne, Australia; Ertek G., College of Business, Abu Dhabi University, Abu Dhabi, United Arab Emirates; Hu Z.-H., Logistics Research Center, Shanghai Maritime University, Shanghai, China","Many retailers nowadays operate in an Internet-enabled dual-channel supply chain setting, referred to as “click and mortar”. In such a structure, products and services are delivered through both online B2C (business-to-consumer e-tail) and offline B2C (traditional brick and mortar retail) channels. In this paper, we develop and present a unified modeling approach that reflects a real-world dual-channel supply chain in the food retail industry. Motivated by the actual business operations of a case study, we incorporate the spatial locations of customers, as well as other logistics and operational costs, into the service provider’s pricing and the customers’ channel choice decisions. We develop two models, namely the benchmark and proposed models, and conduct extensive numerical experiments with parameter values centered on actual values. The results reveal that the ratio of online and offline profit to the total dual-channel profit vary significantly, depending on the locations of customers and the values of the logistics costs. In addition, our statistical and visual analysis suggest that by jointly optimizing the logistics and operational processes, the service provider can achieve a considerably high profit through both channels, without necessarily expanding the size of its geographical service areas. © 2018, Springer Science+Business Media, LLC, part of Springer Nature.","Channel selection; Dual-channel supply chains; E-commerce logistics; Food retail industry; Location-based pricing",{"$nulls":5},"Doctoral Innovation Foundation of Shanghai Maritime University, (2017ycx074); La Trobe University; National Natural Science Foundation of China, NSFC, (71471109); Science and Technology Commission of Shanghai Municipality, STCSM, (16040501800)","We sincerely thank the guest editors and anonymous reviewers for their valuable suggestions and comments. We thank the founding manager of Roza’s Kitchen for initiating the joint industry project and providing information, data, and continuous support throughout the study. This research was supported by the National Natural Science Foundation of China (71471109), the Doctoral Innovation Foundation of Shanghai Maritime University (No. 2017ycx074), and the Shanghai Science and Technology Commission (16040501800). This research was also supported by a Social Research Platform Grant from La Trobe University.","Amrouche N., Yan R., A manufacturer distribution issue: How to manage an online and a traditional retailer, Annals of Operations Research, 244, 2, pp. 257-294, (2016); Asian S., Nie X., Coordination in supply chains with uncertain demand and disruption risks: Existence, analysis, and insights, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 44, 9, pp. 1139-1154, (2014); State of the industry., (2017); Cai G., Channel selection and coordination in dual-channel supply chains, Journal of Retailing, 86, 1, pp. 22-36, (2010); Cai G., Zhang Z.G., Zhang M., Game theoretical perspectives on dual-channel supply chain competition with price discounts and pricing schemes, International Journal of Production Economics, 117, 1, pp. 80-96, (2009); Chen T.-H., Effects of the pricing and cooperative advertising policies in a two-echelon dual-channel supply chain, Computers & Industrial Engineering, 87, pp. 250-259, (2015); Chen J., Liang L., Yao D.-Q., Sun S., Price and quality decisions in dual-channel supply chains, European Journal of Operational Research, 259, 3, pp. 935-948, (2017); Chen X., Wang X., Chan H.K., Channel coordination through subsidy contract design in the mobile phone industry, International Journal of Production Economics, 171, pp. 97-104, (2016); Choi T.-M., Chow P.-S., Xiao T., Electronic price-testing scheme for fashion retailing with information updating, International Journal of Production Economics, 140, 1, pp. 396-406, (2012); Ertek G., Griffin P.M., Supplier-and buyer-driven channels in a two-stage supply chain, IIE transactions, 34, 8, pp. 691-700, (2002); de Kervenoael R., Yanik S., Bozkaya B., Palmer M., Hallsworth A., Trading-up on unmet expectations? 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Asian; La Trobe Business School, La Trobe University, Melbourne, Australia; email: s.asian@latrobe.edu.au",null,"Springer",{"$nulls":5},2545330.0,null,null,null,"English","Ann. Oper. Res.","Article","Final",null,"Scopus","2-s2.0-85053427199"]
["Dutta P.; Mishra A.; Khandelwal S.; Katthawala I.","Dutta, Pankaj (16244453500); Mishra, Anurag (57214672321); Khandelwal, Sachin (57213609472); Katthawala, Ibrahim (57213602022)","16244453500; 57214672321; 57213609472; 57213602022","A multiobjective optimization model for sustainable reverse logistics in Indian E-commerce market",2020.0,"Journal of Cleaner Production",249.0,null,119348.0,null,null,null,89.0,"10.1016/j.jclepro.2019.119348","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85077899509&doi=10.1016%2fj.jclepro.2019.119348&partnerID=40&md5=d19f05a485c133c0f5ac9abfe5650655","Shailesh J. Mehta School of Management, Indian Institute of Technology, Bombay, Powai, Mumbai, 400076, India; Flipkart Internet Pvt. Ltd., Embassy Tech Village, Devarabeesanahalli, Bellandur, Bengaluru, 560103, India","Dutta P., Shailesh J. Mehta School of Management, Indian Institute of Technology, Bombay, Powai, Mumbai, 400076, India; Mishra A., Shailesh J. Mehta School of Management, Indian Institute of Technology, Bombay, Powai, Mumbai, 400076, India; Khandelwal S., Flipkart Internet Pvt. Ltd., Embassy Tech Village, Devarabeesanahalli, Bellandur, Bengaluru, 560103, India; Katthawala I., Flipkart Internet Pvt. Ltd., Embassy Tech Village, Devarabeesanahalli, Bellandur, Bengaluru, 560103, India","A cleaner and sustainable environment is becoming a topmost priority for both owners and stakeholders involved in businesses. It could be achieved by adopting better sustainable practices like reduction in waste through process of recycling, recovery and remanufacturing which helps to minimize both the cost and environmental losses. With a recent surge in E-commerce market and online shopping in India there is a need for a more efficient, sustainable and reliable reverse logistics design by including cost, environmental and social factors into consideration. With the factors considered above this paper proposes a multi-objective logistics network model for the return products specifically pertaining to the Indian E-commerce market. The components of this multi-echelon supply chain considered are Customer Markets, Warehouses, Delivery Hubs, Landfills, Incineration Centres and Recycling Centres. The multi-objective optimization is done on the three fronts of sustainability, namely, economical, represented by cost, environmental, represented by environmental impact of different process, and social, which is represented by work days created and lost due to harms at work. Different technologies are considered in delivery hubs and mother warehouse which could result in a more efficient way of transferring and processing products. Weighted goal programming (WGP) technique is used by weighing different objectives to minimize cost, environment impact and maximize the social responsibility. Finally, - model is validated with a numerical example based on an online retail selling clothes. This study will help the managers in deciding the number of facility stores and warehouses needed to open and operate, technology to be adopted for a more efficient way of transferring and processing products. © 2019 Elsevier Ltd","E-commerce; India; Multi-objective; Reverse logistics; Sustainability","Economic and social effects; Electronic commerce; Environmental impact; Linear programming; Multiobjective optimization; Recycling; Sales; Social aspects; Supply chains; Sustainable development; Warehouses; Waste incineration; India; Logistics network model; Multi echelon supply chains; Multi objective; Multi-objective optimization models; Reverse logistics; Social responsibilities; Sustainable environment; Costs",{"$nulls":6},"Adler I., Monteiro R.D., A geometric view of parametric linear programming, Algorithmica, 8, 1-6, pp. 161-176, (1992); Alshamsi A., Diabat A., A reverse logistics network design, J. Manuf. 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Sci., 6, 1, pp. 73-79, (1959); Charnes A., Cooper W.W., Programming with linear fractional functionals, Nav. Res. Logist. Q., 9, 3-4, pp. 181-186, (1962); Charnes A., Cooper W.W., Goal programming and multiple objective optimizations: Part 1, Eur. J. Oper. Res., 1, 1, pp. 39-54, (1977); Charnes A., Cooper W.W., Ferguson R.O., Optimal estimation of executive compensation by linear programming, Manag. Sci., 1, 2, pp. 138-151, (1955); Das K., Chowdhury A.H., Designing a reverse logistics network for optimal collection, recovery and quality-based product-mix planning, Int. J. Prod. Econ., 135, 1, pp. 209-221, (2012); Dekker R., Zuidwijk R., Pappis C., Ryan S., Kokkinaki A., Ecommerce for reverse logistics, ECIS 2002 Proceedings, 23, (2002); Diabat A., Kannan D., Kaliyan M., Svetinovic D., An optimization model for product returns using genetic algorithms and artificial immune system, Resour. Conserv. 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Res., 111, 3, pp. 569-581, (1998); Tiwari R.N., Dharmar S., Rao J.R., Fuzzy goal programming—an additive model, Fuzzy Sets Syst., 24, 1, pp. 27-34, (1987); XiaoYan Q., Yong H., Qinli D., Stokes P., Reverse logistics network design model based on e-commerce, Int. J. Organ. Anal., 20, 2, pp. 251-261, (2012); Zarbakhshnia N., Soleimani H., Goh M., Razavi S.S., A novel multi-objective model for green forward and reverse logistics network design, J. Clean. Prod., 208, pp. 1304-1316, (2019); Zohal M., Soleimani H., Developing an ant colony approach for green closed-loop supply chain network design: a case study in gold industry, J. Clean. Prod., 133, pp. 314-337, (2016)","P. Dutta; Shailesh J. Mehta School of Management, Indian Institute of Technology, Mumbai, Bombay, Powai, 400076, India; email: pdutta@iitb.ac.in",null,"Elsevier Ltd",{"$nulls":5},9596526.0,null,"JCROE",null,"English","J. Clean. Prod.","Article","Final",null,"Scopus","2-s2.0-85077899509"]
["Damodharan P.; Ravichandran C.S.","Damodharan, P. (56084684000); Ravichandran, C.S. (55806907700)","56084684000; 55806907700","Applicability Evaluation of Web Mining in Healthcare E-Commerce towards Business Success and a derived Cournot Model",2019.0,"Journal of Medical Systems",43.0,8.0,268.0,null,null,null,2.0,"10.1007/s10916-019-1395-1","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85068799049&doi=10.1007%2fs10916-019-1395-1&partnerID=40&md5=6798124d2d3ac4f8fff544ad75caf292","Akshaya College of Engineering and Technology, Coimbatore, India; Sri Ramakrishna Engineering College, Coimbatore, India","Damodharan P., Akshaya College of Engineering and Technology, Coimbatore, India; Ravichandran C.S., Sri Ramakrishna Engineering College, Coimbatore, India","Internet has become integral part of day-to-day business to almost everybody, this result in diversified interests of customers. So as to catering to this intrinsic need, any E-Commerce firm to survive must be of cutting edge and competitive edge. The providers should not only to stay abreast with technologies where the life cycle of a technology is at its bare minimum and further dwindling They should also entertain the customers through inventively fine tuning the delicate parameters of website. This involves evaluating the usage pattern and trails of the customer left as a log, deriving pattern from click stream etc. However, the cutting edge technology applied by the big healthcare E-Commerce industries like private Cloud utilization (John et al., Optimization and Computing, 2012), web content mining enables them to attract and retain innumerable number of customers even during peak hours. According to the research carried out in this paper, there are two distinct types of online business based on web content promoted towards buy, they are classified as exhaustive promote and partial promote. Typically exhaustive promote website perform even complex web mining operations for identifying and enticing the potential customers to buy various healthcare products based on various factors such as buying habits, interests etc. However for the partial promote in the observed cases, they are not even aware of the existence of such techniques. Based on the analysis performed on various renounced online websites, if 60% and above of the web content leads the customer to perform the ‘buy, then it is exhaustive promote the rest is considered as partial promote. Moreover a huge gap is observed between Partial and exhaustive promote when it comes to the deployment of the web mining techniques. Consequently to understand the varying role of web mining in the online business successes, this paper models the web mining as a Game in Cournot Model. The results show that the model suits the economics behind the online businesses in both the cases and thus helps to identify or enhance the underlying web mining techniques towards business success. © 2019, Springer Science+Business Media, LLC, part of Springer Nature.","Cournot model; E-Commerce; Game theory; Healthcare; Web content mining; Web mining","Commerce; Competitive Behavior; Data Mining; Delivery of Health Care; Internet; Models, Organizational; article; case report; clinical article; economics; game; habit; mining; rest; commercial phenomena; competitive behavior; data mining; health care delivery; Internet; nonbiological model",{"$nulls":6},"Sujatha V., Punithavalli, Improved user Navigation Pattern Prediction Technique from Web Log Data, Procedia Engineering, 30, pp. 92-99, (2012); Alphy A., Prabakaran S., A Dynamic Recommender System for Improved Web Usage Mining and CRM Using Swarm Intelligence, Sci. World J., (2015); Lopes P., Roy B., Dynamic Recommendation System Using Web Usage Mining for E-commerce Users, International Conference on Advanced Computing Technologies and Applications (ICACTA), pp. 60-69, (2015); Ting I.-H., Chang P.S., Wang S.-L., Understanding Microblog Users for Social Recommendation Based on Social Networks Analysis, J. Univ. Comput. Sci., 18, 4, pp. 554-576, (2012); NAZAR N.B., SENTHILKUMAR R., An online approach for feature selection for classification in big data, TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES, 25, pp. 163-171, (2017); Gawali R.R., Mundhe S.D., Web Mining techniques, process and applications in Ecommerce, Proceedings of National Conference on Emerging Trends: Innovations and Challenges in IT, pp. 19-20, (2013); Jojo J., Sugana N., User profile creation based on navigation pattern for modeling user behaviour with personalised search, IEEE Xplore International Conference on Current Trends in Engineering and Technology (ICCTET), (2013); Somprasertsri G., Lalitrojwong P., Mining Feature-Opinion in Online Customer Reviews for Opinion Summarization, J. Univ. Comput. Sci., 16, 6, pp. 938-955, (2010); Wang Y., Integration of Data Mining with Game Theory, Knowledge Enterprise: Intelligent Strategies in Product Design, Manufacturing, and Management, 207, (2006); Devi B.N., Devi Y.R., Rani B.P., Rao R.R., Design and Implementation of Web Usage Mining Intelligent System in the Field of e-commerce, Procedia Engineering, 30, pp. 20-27, (2012); Trabold D., Horvath T., Mining Data Streams with Dynamic Confidence Intervals, Big Data Analytics and Knowledge Discovery, pp. 99-113, (2016); Trabold D., Horvath T., Mining Data Streams with Dynamic Confidence Intervals, Big Data Analytics and Knowledge Discovery, pp. 99-113, (2016); Niu N., Stroulia E., El-Ramly M., Understanding Web Usage for Dynamic Web-Site Adaptation: A Case Study, Proceedings of the Fourth International Workshop on Web Site Evolution (WSE’02), (2002); Lina Y., Shib X., Yimin Weib C., On computing PageRank via lumping the Google matrix, J. Comput. Appl. Math., 224, 2, pp. 702-708, (2009); Salah T., Tiun S., Focused crawling of online business Web pages using latent semantic indexing approach, ARPN Journal of Engineering and Applied Sciences, 11, 15, pp. 9229-9234, (2016); Harry T., Achsan Y., Wibowo W.C., A Fast Distributed Focused-web Crawling, Procedia Engineering, 69, pp. 492-499, (2014); Choi J., Lee G., Moon J., Web Context Classification Based on Information Quality Factors, J. Univ. Comput. Sci., 16, 16, pp. 2232-2251, (2010); Sabucedo L.A., Rifon L.A., Locating and Crawling e-Government Services A Light-weight Semantic Approach, J. Univ. Comput. Sci., 16, 8, pp. 1117-1137, (2010); Stathis P., Kavallieratou E., Papamarkos N., An Evaluation Technique for Binarization Algorithms, J. Univ. Comput. Sci., 14, 18, pp. 3011-3030, (2008); Abraham A., Business Intelligence from Web Usage Mining, Journal of Information & Knowledge Management, 2, 4, pp. 375-390, (2003); Ulvisimsek M., Ozdemir S., Analysis of the relation between Turkish twitter messages and stock market index, IEEE Xplore 6Th International Conference on Application of Information and Communication Technologies (AICT), pp. 17-19, (2012); Cui M., Hu S., Search Engine Optimization Research for Website Promotion, IEEE International Conference on Information Technology, Computer Engineering and Management Sciences (ICM), (2011); Attardi G., Di Marco S., Salvi D., Categorisation by Content, J. Univ. Comput. Sci., 4, 9, pp. 719-736, (1998); Safran C., Kappe F., Success Factors in a Weblog Community, J. Univ. Comput. Sci., 14, 4, pp. 546-556, (2008); Panniello U., Ardito L., Petruzzelli A.M., Does the Users’ Tendency to Seek Information Affect Recommender Systems’ Performance?, J. Univ. Comput. Sci., 23, 2, pp. 187-207, (2017); Velasquez J.D., Web mining and privacy concerns: Some important legal issues to be consider before applying any data and information extraction technique in web-based environments, Elsevier Expert Systems with Applications, 40, 13, pp. 5228-5239, (2013); Bravo C., Figueroa N., Weber R., Modeling pricing strategies using game theory and support vector machines. In Petra Pertner, editor, Advances in Data Mining. Applications and Theoretical Aspects, Lect. Notes Comput. Sci, 6171, pp. 323-337, (2010); Abolhassani M., Bateni M.H., Hajiaghayi M.T., Mahini H., Sawant A., Network Cournot Competition, (2014); Bimpikis K., Ehsani S., Ilkilic R., Modeling Pricing Strategies Using Game Theory and Support Vector Machines, Proceedings of the Fifteenth ACM Conference on Economics and Computation EC’14, (2014); Barry C., Markey R., Almquist E., Brahm C., Putting Social Media to Work, (2011); John J.M., Mini G.V., Arun E., User Profile Tracking by Web Usage Mining in Cloud Computing, Procedia Engineering, 38, pp. 3270-3277, (2012)","P. Damodharan; Akshaya College of Engineering and Technology, Coimbatore, India; email: damumtp_cse@yahoo.com",null,"Springer New York LLC",{"$nulls":5},1485598.0,null,"JMSYD",3.1273541E7,"English","J. Med. Syst.","Article","Final",null,"Scopus","2-s2.0-85068799049"]
["Jabeen S.A.; Prasanth Y.; Prasad G.S.","Jabeen, Shaik Anjumun (57209200547); Prasanth, Yalla (57198346938); Prasad, Gudapati Syam (58591788800)","57209200547; 57198346938; 58591788800","UDD based procedure for record deduplication over digital storage systems",2019.0,"International Journal of Engineering and Advanced Technology",8.0,4.0,null,1850.0,1856.0,6.0,0.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85066811478&partnerID=40&md5=935b63d9d2e40e91358fd6dd1f83e3f9","Department of CSE, Koneru Lakshmaiah Education Foundation, Vaddeswaram, A.P, India","Jabeen S.A., Department of CSE, Koneru Lakshmaiah Education Foundation, Vaddeswaram, A.P, India; Prasanth Y., Department of CSE, Koneru Lakshmaiah Education Foundation, Vaddeswaram, A.P, India; Prasad G.S., Department of CSE, Koneru Lakshmaiah Education Foundation, Vaddeswaram, A.P, India","Digital libraries, E-commerce brokers and similar vast information-oriented systems rely on consistent data to offer high-quality services. But presence of duplicates, quasi replicas, or near-duplicate entries (Dirty Data) in their repositories asperses their storage resources directly and delivery issues indirectly. Significant investments in this field from interested parties prompted the need for best methods for removing replicas from data repositories. Prior approaches involved using SVM classifiers, approaches to handle these dirty data. New distributed deduplication systems with higher reliability in which the data chunks are distributed across multiple cloud servers. The security requirements of data confidentiality and tag consistency are also achieved by introducing a deterministic secret sharing scheme in distributed storage systems, instead of using convergent encryption as in previous deduplication systems. So propose to use Unsupervised Duplicate Detection (UDD) Mechanism a query-dependent record matching method that requires no pre trained data set. UDD uses two cooperating classifiers that is, a weighted component similarity summing (WCSS) classifier and an SVM classifier that iteratively identifies duplicates in the query results from data sources. Achieves the same efficiency in terms of Deduplication results but significantly at a better performance rate (time) compared to GP systems. A practical implementation of the proposed approach validates the claim. © 2019, Blue Eyes Intelligence Engineering & Sciences Publication. All rights reserved.","Active learning; Cloud computing environment; Deduplication and cloud security; Genetic programming",{"$nulls":7},"Yuan J., Yu S., Secure and Constant Cost Public Cloud Storage Auditing with Deduplication, Trans. Inf. Theory, 22, 6, pp. 644-654, (2015); de Freitas J., Pappa G.L., da Silva A.S., Active Learning Genetic Programming for Record Deduplication, ICML '09: Proc. of the 26th Annual Int. Conf. on Machine Learning., pp. 49-56, (2009); Carvalho M.G., Laender A.H.F., Goncalves M.A., da Silva A.S., Replica identification using genetic programming, Proc. of the ACM Symposium on Applied computing, pp. 1801-1806, (2008); Gantz J., Reinsel D., The digital universe decade-are you ready?, (2010); Yuan J., Yu S., Proofs of retrievability with public verifiability and constant communication cost in cloud, Proceedings of the ACM ASIACCS-SCC’13, (2013); Shacham H., Waters B., Compact proofs of retrievability, Proceedings of the 14th International Conference on the Theory and Application of Cryptology and Information Security, pp. 90-107, (2008); Juels A., Kaliski B.S., Pors: Proofs of retrievability for large files, Proceedings of the 14th ACM conference on Computer and communications security, pp. 584-597, (2007); Dodis Y., Vadhan S., Wichs D., Proofs of retrievability via hardness amplification, Proceedings of the 6th Theory of Cryptography Conference on Theory of Cryptography, pp. 109-127, (2009); Ateniese G., Burns R., Curtmola R., Herring J., Kissner L., Peterson Z., Song D., Provable data possession at untrusted stores, Proceedings of the 14th ACM conference on Computer and communications security, pp. 598-609, (2007); Ateniese G., Di Pietro R., Mancini L.V., Tsudik G., Scalable and efficient provable data possession, Proceedings of the 4th international conference on Security and privacy in communication netowrks, (2008); Erway C., Kupcu A., Papamanthou C., Tamassia R., Dynamic provable data possession, Proceedings of the 16th ACM conference on Computer and communications security, pp. 213-222, (2009); Wang Q., Wang C., Ren K., Lou W., Li J., Enabling public auditability and data dynamics for storage security in cloud computing, IEEE Trans. Parallel Distrib. Syst., 22, 5, pp. 847-859, (2011); Halevi S., Harnik D., Pinkas B., Shulman-Peleg A., Proofs of ownership in remote storage systems, Proceedings of the 18th ACM conference on Computer and communications security, pp. 491-500, (2011); Di Pietro R., Sorniotti A., Boosting efficiency and security in proof of ownership for deduplication, Proceedings of the 7th ACM Symposium on Information, Computer and Communications Security, pp. 81-82, (2012); Zheng Q., Xu S., Secure and efficient proof of storage with deduplication, Proceedings of the second ACM conference on Data and Application Security and Privacy, pp. 1-12, (2012); Youngjoo Shin K.K., Hur J., Security weakness in the proof of storage with deduplication, Cryptology ePrint Archive, (2012); Boneh D., Boyen X., Short signatures without random oracles, EUROCRYPT, pp. 56-73, (2004); Reed I.S., Solomon G., Polynomial Codes Over Certain Finite Fields, Journal of the Society for Industrial and Applied Mathematics, 8, 2, pp. 300-304, (1960); Jia X., Ee-Chien C., Towards efficient provable data possession, Proceedings of the 7th ACM Symposium on Information, Computer and Communications Security, (2012); A Hybrid Cloud Approach for Secure Authorized Deduplication, IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEM, PP, 99, (2014); Goncalves, da Silva A.S., A Genetic Programming Approach to Record Deduplication, IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 24, 3, (2012); Bellare M., Keelveedhi S., Ristenpart T., Message-bolted encryption and secure deduplication, EUROCRYPT, pp. 296-312, (2013); Halevi S., Harnik D., Pinkas B., Shulman-Peleg A., Confirmations of proprietorship in remote stockpiling frameworks, ACM Conference on Computer and Communications Security, pp. 491-500, (2011); Li J., Chen X., Li M., Li J., Lee P., Lou W., Secure deduplication with proficient and solid merged key administration, IEEE Transactions on Parallel and Distributed Systems, (2013); Ng C., Lee P., Revdedup: A converse deduplication stockpiling framework advanced for peruses to most recent reinforcements, Proc. of APSYS, (2013)",null,null,"Blue Eyes Intelligence Engineering and Sciences Publication",{"$nulls":5},2.2498958E7,null,null,null,"English","Int. J. Eng. Adv. Technol.","Article","Final",null,"Scopus","2-s2.0-85066811478"]
["Ikuesan A.R.; Razak S.A.; Venter H.S.; Salleh M.","Ikuesan, Adeyemi Richard (57200145399); Razak, Shukor Abd (57202120585); Venter, Hein S. (7005841055); Salleh, Mazleena (36992863900)","57200145399; 57202120585; 7005841055; 36992863900","Polychronicity tendency-based online behavioral signature",2019.0,"International Journal of Machine Learning and Cybernetics",10.0,8.0,null,2103.0,2118.0,15.0,9.0,"10.1007/s13042-017-0748-7","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85069515490&doi=10.1007%2fs13042-017-0748-7&partnerID=40&md5=bd324431dcb0848e5440c52d735c9b1f","University of Pretoria, Pretoria, Gauteng, South Africa; Department of Computer Science, Universiti Teknologi Malaysia, Johor Bahru, Malaysia","Ikuesan A.R., University of Pretoria, Pretoria, Gauteng, South Africa; Razak S.A., Department of Computer Science, Universiti Teknologi Malaysia, Johor Bahru, Malaysia; Venter H.S., University of Pretoria, Pretoria, Gauteng, South Africa; Salleh M., Department of Computer Science, Universiti Teknologi Malaysia, Johor Bahru, Malaysia","The proliferation of ubiquitous and pervasive computing devices has led to the emergence of research areas like Internet of things, and the Big-Data, which has seen a rise in obfuscation of online identity thus fueling an increase in online anonymity. Online anonymity constitutes a major platform for the exploitation of the potentials of cyber-crime; at the same time, it also inhibits the potential economic power that can be harnessed from the surging Internet population. Methods of online identification, such as usage profiling, demographic profiling, cookie-based identification process, media fingerprinting as well as token-based identification processes, are limited to either system identification or one-to-one identification. Current one-to-one identification mechanisms require huge volume of templates of known users, and cannot be applied to novel users. This study proposed a psychosocial approach that integrates the composition of human Polyphasia tendency into online identification processes for a one-to-many identification process. To achieve this, the study administered a Polychronic-Monochronic tendency scale measurement instrument to staff members of a research unit in a university, and the server-side network traffic of each respondent was monitored and collected in eight-months duration. A logistic model tree—after an initial classifier exploration process—was adapted for the one-to-many classification model based on human intrinsic features extracted from the network traffic and Polyphasia dichotomy. High degree of reliable accuracy of > 80% was achieved which suggests a reliable model that supports the underlying hypothesis of the proposed model. Based on this accuracy, the approach finds practical relevance in online profiling process for online identification as well as online demographic profiling for e-commerce and e-learning. Furthermore, this approach can be applied to improve recommender systems in areas such as prediction and profile delivery through the extraction of the purpose of online surfing. © 2017, Springer-Verlag GmbH Germany, part of Springer Nature.","Digital time preference signature; Intrinsic network feature; Logistic model tree; One-to-many identification; Online psychosocial fingerprint; Polyphasia tendency","Electronic commerce; Forestry; Palmprint recognition; Population statistics; Ubiquitous computing; Logistic models; Network features; Online psychosocial fingerprint; Polyphasia tendency; Time preferences; Online systems",{"$nulls":4},"University of Pretoria, UP; Ministry of Higher Education, Malaysia, MOHE, (R.J130000.7813.4F193); Universiti Teknologi Malaysia, UTM","We would like to thank the Ministry of Education, Malaysia for sponsoring this research grant (Vote: R.J130000.7813.4F193), Universiti Teknologi Malaysia and University of Pretoria. The preliminary version of this article has been published in ASC 2017 in conjunction with BIGCOMP 2017 [31].","Miniwatts M.G., Internet usage statistics: The internet big picture, World Internet Users and 2015 Population Stats [Online, (2015); Tor: Anonymity Online, (2015); Padmanabhan B., Yang Y., Clickprints on the Web: Are There Signatures in Web Browsing Data?, (2007); Yang (Catherine) Y., Web user behavioral profiling for user identification, Decis Support Syst, 49, 3, pp. 261-271, (2010); Yang Y., Padmanabhan B., Toward user patterns for online security: Observation time and online user identification, Decis Support Syst, 48, 4, pp. 548-558, (2010); Herrmann D., Gerber C., Banse C., Federrath H., Espoo, Analyzing characteristic host access patterns for re-identification of web user sessions, ISBN: 978-., vol7127 LNCS, (2010); Abramson M., Aha D., User authentication from web browsing behavior, The Twenty-Sixth International FLAIRS Conference, pp. 268-273, (2013); Baggili I., Rogers M., Self-reported cyber crime: an analysis on the effects of anonymity and pre-employment integrity, Int J Cyber Criminol, 3, 2, pp. 536-549, (2009); Brown B., Lampe C., Rodden K., Ducheneaut N., Models, theories and methods of studying online behaviour, CHI’10 Extended Abstracts on Human Factors in Computing Systems, pp. 4449-4452, (2010); Amichai-Hamburger Y., Wainapel G., Fox S., ‘On the Internet no one knows I’m an introvert’: extroversion, neuroticism, and Internet interaction, Cyberpsychol Behav, 5, 2, pp. 125-128, (2002); Zhang Y., Goonetilleke R.S.R., Plocher T., Liang S.S.M.S.S.M., Time orientation and human performance, Hong Kong Univ Sci Technol Kowloon, 1999, pp. 247-252, (2004); Rose G.M., Evaristo R., Straub D., Culture and consumer responses to web download time: a four-continent study of mono and polychronism, IEEE Trans Eng Manag, 50, 1, pp. 31-44, (2003); Palmer D.K., Schoorman F.D., Unpackaging the multiple aspects of time in polychronicity, J Manag Psychol, 14, 3-4, pp. 323-345, (1999); Lee W., Tan T., Hameed S., Polychronicity, the internet, and the mass media: a Singapore study, J Comput Mediat Commun, 11, pp. 300-316, (2006); Kralisch A., Eisend M., Berendt B., The impact of culture on website navigation behaviour, The 11Th International Conference on Human–Computer Interaction (HCI International), pp. 1-9, (2005); Joshua D., Lee M.L.S., Yi M.Y., Time-user preference and technology acceptance: Measure development of computer polychronicity, Am J Bus, 24, 2, pp. 23-32, (2009); Capdeferro N., Romero M., Barbera E., Polychronicity: review of the literature and a new configuration for the study of this hidden dimension of online learning, Distance Educ, 35, 3, pp. 294-310, (2014); Lindquist J.D., Kaufman-Scarborough C., The Polychronic monochronic tendency model: PMTS scale development and validation, Time Soc, 16, 2-3, pp. 253-285, (2007); Kumar R., Tomkins A., A characterization of online browsing behavior, Proceedings of the 19Th International Conference World Wide Web, pp. 561-570, (2010); Adeyemi I.R., Razak A.S., Salleh M., A psychographic framework for online user identification, International Symposium on Biometrics and Security Technologies (ISBAST), pp. 198-203, (2014); Senin P., Lin J., Wang X., Oates T., GrammarViz 2.0: A tool for grammar-based pattern discovery in time series, The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, pp. 468-472, (2014); Barabasi A., The origin of bursts and heavy tails in human dynamics, Nature, 435, 7039, pp. 207-211, (2005); Zhou T., Han X., Wang B., Towards the Understanding of Human Dynamics, Sci Matters Humanit Complex Syst, 1, pp. 207-233, (2008); Nguyen T.T.T., Armitage G., A survey of techniques for internet traffic classification using machine learning, Commun Surv Tutorials, 10, 4, pp. 56-76, (2008); Kotsiantis S., Zaharakis I., Pintelas P., Supervised machine learning: A review of classification techniques, Informatical, 31, pp. 249-268, (2007); Othman F.M., Moh T., Yau S., Comparison of different classification techniques using WEKA for Breast cancer, 3Rd Kuala Lumpur International Conference on Biomedical Engineering, 15, pp. 520-523, (2007); Yang Y.C., Web user behavioral profiling for user identification, Decis Support Syst, 49, 3, pp. 261-271, (2010); Adeyemi I.R., Razak S.A., Salleh M., Venter H.S., Observing consistency in online communication patterns for user re-identification, PLoS One, 11, 12, pp. 1-27, (2016); Bauer E., Kohavi R., Chan P., Stolfo S., Wolpert D., An empirical comparison of voting classification algorithms: bagging, boosting, and variants, Mach Learn, 36, pp. 105-139, (1999); Dietterich T.G., An experimental Comparison of three methods for constructing ensembles of decision Trees, Mach Learn, 40, pp. 139-157, (2000); Adeyemi I.R., Razak S.A., Venter H.S., Salleh M., High-level online user attribution model based on human Polychronic-Monochronic tendency, 2017 IEEE International Conference on Big Data and Smart Computing, Bigcomp 2017, pp. 445-450, (2017); Li X., Xie H., Chen L., Wang J., Deng X., News impact on stock price return via sentiment analysis, Knowl Based Syst, 69, 1, pp. 14-23, (2014); Cambria E., Speer R., Havasi C., Hussain A., SenticNet: a publicly available semantic resource for opinion mining, Artif Intell, 10, pp. 14-18, (2010); Gu B., Sun X., Sheng V.S., Structural minimax probability machine, IEEE Trans Neural Netw Learn Syst, 28, 7, pp. 1646-1656, (2017)","A.R. Ikuesan; University of Pretoria, Pretoria, South Africa; email: rikuesan@hotmail.com",null,"Springer Verlag",{"$nulls":5},1.8688071E7,null,null,null,"English","Intl. J. Mach. Learn. Cybern.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85069515490"]
["Jeon A.-G.; Lee S.-H.","Jeon, An-Gyoon (56545446100); Lee, Sang-Hyun (49061211200)","56545446100; 49061211200","Design and development of logistic artificial neural network for electronic commerce",2019.0,"International Journal of Recent Technology and Engineering",7.0,6.0,null,1226.0,1230.0,4.0,0.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85066873279&partnerID=40&md5=ad6da5cc6a507167883ff0af7d9c2e95","Department of LINC+, Chonbuk National University, Chonbuk, South Korea; Department of Computer Engineering, Honam University, Gwangju, South Korea","Jeon A.-G., Department of LINC+, Chonbuk National University, Chonbuk, South Korea; Lee S.-H., Department of Computer Engineering, Honam University, Gwangju, South Korea","This study shows that logistic neural network can be a better alternative to diffusion modeling of technological innovation including electronic commerce in the neural network based integrated approach predicts and models the diffusion of technology innovation. Especially, diffusion model by logistic neural network shows better performance through discussion of different diffusion related dynamics such as internal and external influence of growth process and comparison of traditional diffusion theory. The results of this study can be applied to other similar technologies as well as e-commerce growth modeling. © BEIESP.","CAN communication; Logistic neural network; Mixed model; Real-Time Scheduling",{"$nulls":7},"Ali A., Haseeb M., Radio frequency identification (RFID) technology as a strategic tool towards higher performance of supply chain operations in textile and apparel industry of Malaysia, Uncertain Supply Chain Management, 7, 2, pp. 215-226, (2019); Awang Z., Ahmed U., Hoque A.S.M.M., Siddiqui B.A., Dahri A.S., Muda H., The Mediating Role of Meaningful Work in the Relationship Between Career Growth Opportunities and Work Engagement, International Academic Confernce on Business and Economics (IACBE 2017), (2017); Haseeb M., Abidin I.S.Z., Hye Q.M.A., Hartani N.H., The Impact of Renewable Energy on Economic Well-Being of Malaysia: Fresh Evidence from Auto Regressive Distributed Lag Bound Testing Approach, International Journal of Energy Economics and Policy, 9, 1, pp. 269-275, (2018); Haseeb H.Z.G., Hartani N.H., Pahi M.H., Nadeem H., Environmental Analysis of the Effect of Population Growth Rate on Supply Chain Performance and Economic Growth of Indonesia, Ekoloji, 28, 107, (2019); Yao J.T., Ecommerce Adoption of Insurance Companies in New Zealand, Journal of Electronic Commerce Research, 5, 1, pp. 54-61, (2004); Wang Y.C.W., Chang C.-W., Michael M.S.H., The Levels of Information Technology Adoption, Business Network, and a Strategic Position Model for Evaluating Supply Chain Integration, Journal of Electronic Commerce Research, 5, 2, pp. 85-98, (2004); Venkatraman N., Loh L., Koh J., The Adoption of Corporate Governance Mechanisms: A Test of Competing Diffusion Models, Management Science, 40, pp. 496-507, (1994); Mukhopadhyay S., Samaddar S., Nargundkar S., Predicting Electronic Commerce Growth: An Integration of Diffusion and Neural Network Models, Journal of Electronic Commerce Research; Armstrong J.S., Principles of Forecasting: A Handbook of Researchers and Practitioners, (2001); Adepoju A.T., Okunola O.A., Modeling and Optimization of Transesterification of Beniseed Oil to Beniseed Methylester: A Case of Artificial Neural Network versus Response Surface Methodology, International Journal of Chemical and Process Engineering Research, 2, 3, pp. 30-43, (2015); Adepoju T.F., Okunola A.A., Modeling and Optimization of Transesterification of Beniseed Oil to Beniseed Methylester: A Case of Artificial Neural Network versus Response Surface Methodology, International Journal of Chemical and Process Engineering Research, 2, 3, pp. 30-43, (2015); Suryanto T., Haseeb M., Hartani N.H., The Correlates of Developing Green Supply Chain Management Practices: Firms Level Analysis in Malaysia, International Journal of Supply Chain Management, 7, 5, (2018); Jalali R., Safari H., Momeni M., Moghadam M., Relocation of facility location based on the inactive defense approach in humanitarian aid logistics, Management Science Letters, 8, 5, pp. 259-270, (2018); Doktoralina C., Apollo A., The contribution of strategic management accounting in supply chain outcomes and logistic firm profitability, Uncertain Supply Chain Management, 7, 2, pp. 145-156, (2019); Erna E., Surachman S., Sunaryo S., Djajuli A., Integration between radical innovation and incremental innovation to expedite supply chain performance through collaboration and open-innovation: A case study of Indonesian logistic companies, Uncertain Supply Chain Management, 7, 2, pp. 191-202, (2019); Sadeghi M., Shafabakhsh G., Estimation of intercity freight origin-destination matrix using simulated annealing algorithm, Uncertain Supply Chain Management, 6, 1, pp. 13-24, (2018)",null,null,"Blue Eyes Intelligence Engineering and Sciences Publication",{"$nulls":5},2.2773878E7,null,null,null,"English","Int. J. Recent Technol. Eng.","Article","Final",null,"Scopus","2-s2.0-85066873279"]
["Arora A.; Singh S.","Arora, Ashish (57215497548); Singh, Surabhi (57195372121)","57215497548; 57195372121","Sustainability issues in freshfruggies: hyperlocal fruits and vegetables delivery model",2019.0,"Emerald Emerging Markets Case Studies",9.0,2.0,null,1.0,21.0,20.0,1.0,"10.1108/EEMCS-10-2018-0222","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85080980304&doi=10.1108%2fEEMCS-10-2018-0222&partnerID=40&md5=887da7723a2cf6c3557863972dc2af05","Faculty of Management, GNDU College, Jalandhar, India; PGDM, Institute of Management Studies Ghaziabad, Ghaziabad, India","Arora A., Faculty of Management, GNDU College, Jalandhar, India; Singh S., PGDM, Institute of Management Studies Ghaziabad, Ghaziabad, India","Learning outcomes: The learning outcomes are as follows: identify the challenges and opportunities in an ecommerce start-up B; understand the issues of operational sustainability of ecommerce start-up; evaluate the sustainability of hyperlocal models to ecommerce start up; and implement innovative solutions to address the issues of e-business models. Case overview/synopsis: It was the cold winter evening of December 2016 when Puja, a cofounder of freshfruggies, an e-commerce start-up company, made up her mind after meeting her cofounders of reviving the Venture “freshfruggies” as a Hyperlocal Fruits and Vegetables Delivery Company in a non-metro town of Jalandhar in Punjab province of India. She contemplated the poor performance of the company in the past which prepared her for the better planning and execution of operational sustainability of freshfruggies. Puja took the critical decision of revival as she planned to develop the right business strategy for ensuring continuity. freshfruggies had been experiencing constant losses since its inception, and the issues of its sustainability needed attention. It was a dream project for all the co-founders who started with the vision to make freshfruggies a popular ecommerce model of hyperlocal fruits and vegetables delivery in the happening city of Jalandhar. However, lack of trained manpower, weak digital marketing strategy and lack of operating efficiency emerged as major issues of operational sustainability in freshfruggies. The co-founders outlined the possible options to revive freshfruggies after deliberating upon the challenges faced. The choices were limited and time was running out along with finances. The options included either changing the business model to a hybrid retail model or to continue as an ecommerce company after sorting out demand and supply issues. There was an urgent need to take a decision in this regard. Complexity academic level: This case focuses on undergraduate and graduate courses in entrepreneurship and operations management courses. Supplementary materials: Teaching notes are available for educators only. Please contact your library to gain login details or email support@emeraldinsight.com to request teaching notes. © 2019, Emerald Publishing Limited.","Business Formation/Start ups; Emerging markets; Entrepreneurship; Institutional voids; Sustainability; Venture planning",{"$nulls":8},"S. Singh; PGDM, Institute of Management Studies Ghaziabad, Ghaziabad, India; email: surabhi777@gmail.com",null,"Emerald Group Publishing Ltd.",{"$nulls":5},2.0450621E7,null,null,null,"English","Emerald Emerg. Mark. Case Stud.","Article","Final",null,"Scopus","2-s2.0-85080980304"]
["Sumathi K.; Sujatha V.","Sumathi, K. (57211793404); Sujatha, V. (57215888878)","57211793404; 57215888878","Deep learning based-phishing attack detection",2019.0,"International Journal of Recent Technology and Engineering",8.0,3.0,null,8428.0,8432.0,4.0,5.0,"10.35940/ijrte.C6527.098319","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85074978154&doi=10.35940%2fijrte.C6527.098319&partnerID=40&md5=67d1755e09dd564c8b8830b4dfb445cc","Department of Computer Applications, CMS College of Science and Commerce, Coimbatore, Tamilnadu, India","Sumathi K., Department of Computer Applications, CMS College of Science and Commerce, Coimbatore, Tamilnadu, India; Sujatha V., Department of Computer Applications, CMS College of Science and Commerce, Coimbatore, Tamilnadu, India","Due to the rapid development of the communication technologies and global networking, lots of daily human life activities such as electronic banking, social networks, e-commerce, etc are transferred to the cyberspace. The anonymous, open and uncontrolled infrastructure of the internet enables an excellent platform for cyber attacks. Phishing is one of the cyber attacks in which attackers open some fraudulent websites similar to the popular and legal websites to steal the user’s sensitive information. Machine learning techniques such as J48, Support Vector Machine (SVM), Logistic Regression (LR), Naive Bayes (NB) and Artificial Neural Network (ANN) were widely to detect the phishing attacks. But, getting good-quality training data is one of the biggest problems in machine learning. So, a deep learning method called Deep Neural Network (DNN) is introduced to detect the phishing Uniform Resource Locators (URLs). Initially, a feature extractor is used to construct a 30-dimension feature vector based on URL-based features, HTML-based features and domain-based features. These features are given as input to the DNN classifier for phishing attack detection. It consists of one input layer, multiple hidden layers and one output layer. The multiple hidden layers in DNN try to learn high-level features in an incremental manner. Finally, the DNN returns a probability value which represent the phishing URLs and legitimate URLs. By using DNN the accuracy, precision and recall of phishing attack detection is improved. © BEIESP.","Artificial neural network; Deep learning; Deep neural network; Machine learning; Phishing",{"$nulls":7},"Rao R.S., Ali S.T., PhishShield: A desktop application to detect phishing webpages through heuristic approach, Procedia Comput. Sci., 54, pp. 147-156, (2015); Akanbi O.A., Amiri I.S., Fazeldehkordi E., Cyber security: A machine learning approach to phishing, (2014); Chin T., Xiong K., Hu C., Phishlimiter: A Phishing Detection and Mitigation Approach Using Software-Defined Networking, IEEE Access, 6, pp. 42516-42531, (2018); Li Y., Xiao R., Feng J., Zhao L., A semi-supervised learning approach for detection of phishing webpages, Optik, 124, 23, pp. 6027-6033, (2013); Moghimi M., Varjani A.Y., New rule-based phishing detection method, Expert syst. appl., 53, pp. 231-242, (2016); Montazer G.A., Arab Yarmohammadi S., Detection of phishing attacks in Iranian e-banking using a fuzzy-rough hybrid system, Appl. Soft Comput, 35, pp. 482-492, (2015); Hadi W.E., Aburub F., Alhawari S., A new fast associative classification algorithm for detecting phishing websites, Appl. Soft Comput, 48, pp. 729-734, (2016); Chiew K.L., Tan C.L., Wong K., Yong K.S., Tiong W.K., A new hybrid ensemble feature selection framework for machine learning-based phishing detection system, Inf. Sci., 484, pp. 153-166, (2019); Smadi S., Aslam N., Zhang L., Detection of online phishing email using dynamic evolving neural network based on reinforcement learning, Deci. Support Syst., 107, pp. 88-102, (2018); Zhu E., Chen Y., Ye C., Li X., Liu F., OFS-NN: An Effective Phishing Websites Detection Model Based on Optimal Feature Selection and Neural Network, IEEE Access, 7, pp. 73271-73284, (2019)",null,null,"Blue Eyes Intelligence Engineering and Sciences Publication",{"$nulls":5},2.2773878E7,null,null,null,"English","Int. J. Recent Technol. Eng.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85074978154"]
["Duong-Trung N.; Ha X.S.; Phan T.T.; Trieu P.N.; Nguyen Q.N.; Pham D.; Huynh T.T.; Le H.T.","Duong-Trung, Nghia (57191328820); Ha, Xuan Son (57193341872); Phan, Tan Tai (57211206155); Trieu, Phuong Nam (57211208886); Nguyen, Quoc Nghiep (57208798749); Pham, Duy (57211204795); Huynh, Thai Tam (57209173318); Le, Hai Trieu (57208802236)","57191328820; 57193341872; 57211206155; 57211208886; 57208798749; 57211204795; 57209173318; 57208802236","Multi-sessions mechanism for decentralized cash on delivery system",2019.0,"International Journal of Advanced Computer Science and Applications",10.0,9.0,null,553.0,560.0,7.0,23.0,"10.14569/ijacsa.2019.0100973","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85072958649&doi=10.14569%2fijacsa.2019.0100973&partnerID=40&md5=72164ce4759416b5f95d2b2789ecebcb","Can Tho University of Technology, Can Tho city, Viet Nam; FPT University, Can Tho city, Viet Nam; National Chiao Tung University, Taiwan; Hanoi University Science Technology, Ha Noi, Viet Nam; Transaction Technologies Pte. Ltd., Singapore","Duong-Trung N., Can Tho University of Technology, Can Tho city, Viet Nam, FPT University, Can Tho city, Viet Nam; Ha X.S., Can Tho University of Technology, Can Tho city, Viet Nam, FPT University, Can Tho city, Viet Nam; Phan T.T., National Chiao Tung University, Taiwan; Trieu P.N., Can Tho University of Technology, Can Tho city, Viet Nam, FPT University, Can Tho city, Viet Nam; Nguyen Q.N., Can Tho University of Technology, Can Tho city, Viet Nam, FPT University, Can Tho city, Viet Nam; Pham D., Hanoi University Science Technology, Ha Noi, Viet Nam; Huynh T.T., Transaction Technologies Pte. Ltd., Singapore; Le H.T., Can Tho University of Technology, Can Tho city, Viet Nam","To date, cash on delivery (COD) is one of the most popular payment methods in developing countries thanks to the blossom of customer-to-customer e-commerce. With the widespread of a very small business model and the Internet, online shopping has become part of people's daily activity. People browse for desirable products at the comfort of their homes and ask the online vendor that a shipper can deliver the merchandise at their doorstep. Then, COD allows customers to pay in cash when the product is delivered to their desired location. Since customers receive goods before making a payment, COD is, therefore, considered as a payment system. However, the crucial issue that previous research has not yet addressed is that their models only support single delivering session at a time. More precisely, if the current buyer is not available to receive the goods, the shipper has to wastefully wait for the complete payment and he/she cannot start shipping another merchandise. The tracking system seems to poorly handle this issue. In particular, we propose a multi-session mechanism, which consists of blockchain technology, smart contracts and hyperledger fabric platform to achieve distributed and transparent across delivering sessions in the decentralized markets. Our proposed mechanism ensure the efficiency of delivering process. The authors release our sources codes for further reproducibility and development. We conclude that the integration of multi-session mechanism and blockchain technology will cause significant efficiency across several disciplines. © 2018 The Science and Information (SAI) Organization Limited.","Blockchain; Cash on delivery; Decentralized system; Multi-sessions","Decentralized systems; Developing countries; Distributed ledger; Efficiency; Electronic commerce; Sales; Ships; Smart contract; Block-chain; Business models; Cash-on-delivery; Decentralised; Decentralized system; Delivery systems; E- commerces; Multi-session; Payment methods; Very small business; Blockchain",{"$nulls":6},"Halaweh M., Cash on delivery (cod) as an alternative payment method for e-commerce transactions: Analysis and implications, International Journal of Sociotechnology and Knowledge Development (IJSKD), 10, 4, pp. 1-12, (2018); Halaweh M., Intention to adopt the cash on delivery (cod) payment model for e-commerce transactions: An empirical study,, IFIP International Conference on Computer Information Systems and Industrial Management, pp. 628-637, (2017); Tandon U., Kiran R., Study on drivers of online shopping and significance of cash-on-delivery mode of payment on behavioural intention, International Journal of Electronic Business, 14, 3, pp. 212-237, (2018); Alie J.D., Vliek P.E., International cash-on-delivery system and method,, (2007); Asgaonkar A., Krishnamachari B., Solving the buyer and seller's dilemma: A dual-deposit escrow smart contract for provably cheat-proof delivery and payment for a digital good without a trusted mediator,, (2018); Hasan H.R., Salah K., Blockchain-based solution for proof of delivery of physical assets,, International Conference on Blockchain, pp. 139-152, (2018); Son H.X., Nguyen M.H., Phien N.N., Le H.T., Nguyen Q.N., Dinh V.D., Tru P.T., Nguyen P., Towards a mechanism for protecting seller's interest of cash on delivery by using smart contract in hyperledger, International Journal of Advanced Computer Science and Applications, 10, 4, (2019); Camp L.J., Tygar J.D., Harkavy M.R., Anonymous certified delivery,; Le N.T.T., Nguyen Q.N., Phien N.N., Duong-Trung N., Huynh T.T., Nguyen T.P., Son H.X., Assuring nonfraudulent transactions in cash on delivery by introducing double smart contracts, International Journal of Advanced Computer Science and Applications, 10, 5, (2019); AlTawy R., ElSheikh M., Youssef A.M., Gong G., Lelantos: A blockchain-based anonymous physical delivery system, in 2017 15th Annual Conference on Privacy, pp. 15-1509, (2017); Asgaonkar A., Krishnamachari B., Solving the buyer and seller's dilemma: A dual-deposit escrow smart contract for provably cheat-proof delivery and payment for a digital good without a trusted mediator,, 2019 IEEE International Conference on Blockchain and Cryptocurrency (ICBC), pp. 262-267, (2018); Halaweh M., Intention to Adopt the Cash on Delivery (COD) Payment Model for E-commerce Transactions: An Empirical Study, in 16th IFIP International Conference on Computer Information Systems and Industrial Management (CISIM), ser. Computer Information Systems and Industrial Management, pp. 628-637; Barkhordari M., Nourollah Z., Mashayekhi H., Mashayekhi Y., Ahangar M.S., Factors influencing adoption of e-payment systems: an empirical study on iranian customers, Information systems and ebusiness management, 15, 1, pp. 89-116, (2017); Sites like ebay or etsy but decentralized-our features.; Le N.T.T., Nguyen Q.N., Phien N.N., Duong-Trung N., Huynh T.T., Nguyen T.P., Son H.X., Assuring nonfraudulent transactions in cash on delivery by introducing double smart contracts, International Journal of Advanced Computer Science and Applications, 10, 5, (2019); Wood G., Et al., Ethereum: A secure decentralised generalised transaction ledger, Ethereum project yellow paper, 151, pp. 1-32, (2014); Ethereum.; Dannen C., Introducing Ethereum and Solidity, (2017); Hirai Y., Defining the ethereum virtual machine for interactive theorem provers,, International Conference on Financial Cryptography and Data Security, pp. 520-535, (2017); Wohrer M., Zdun U., Smart contracts: security patterns in the ethereum ecosystem and solidity,, 2018 International Workshop on Blockchain Oriented Software Engineering (IWBOSE), pp. 2-8, (2018); What is a dapp? decentralized application on the blockchain.; Raval S., Decentralized applications: harnessing Bitcoin's blockchain technology, (2016); Mougayar W., The business blockchain: promise, practice, and application of the next Internet technology, (2016); Wright A., De Filippi P., Decentralized blockchain technology and the rise of lex cryptographia,, (2015)",null,null,"Science and Information Organization",{"$nulls":5},"2158107X",null,null,null,"English","Intl. J. Adv.  Comput. Sci. Appl.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85072958649"]
["Ochocka J.","Ochocka, Jagoda (57211312472)",5.7211312472E10,"Mobile technologies in logistic customer service as a tool for winning customers’ satisfaction; [Technologie mobilne w obsłudze logistycznej klienta jako narzędzie zwiększające satysfakcję klientów]",2019.0,"Logforum",15.0,3.0,null,403.0,411.0,8.0,2.0,"10.17270/J.LOG.2019.338","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85073456756&doi=10.17270%2fJ.LOG.2019.338&partnerID=40&md5=34df827f8f41d12bbd16866b52a4357c","University of Lodz, Łódź, Poland","Ochocka J., University of Lodz, Łódź, Poland","Background: The extremely demanding and dynamic situation on the 21st-century market along with market trends such as globalization, product unification or the development of e-commerce and m-commerce make it harder for businesses to compete and lead to greater deployment of technologies. As customers’ expectations rise to an unbelievable level, all firms are searching for new means to succeed. Therefore, the aim of this paper is to present the importance of mobile technologies in logistics customer service and boosting customers’ satisfaction in the form of a two-perspective judgement concerning both the supplier and the end client. Methods: In order to acquire the dual perspective, the research includes two interviews with different companies from one supply chain and a survey. Both interviews were structured so as to compare each business’s comprehension of the importance of mobile technologies in the logistics supply chain. The survey was conducted among randomly chosen customers aged 20-30, who mostly use mobile technologies while shopping (gived their share in the number of mcommerce customers). This approach made the survey results realistic. Results: The results show an undoubtable synergy effect of the conscious use of mobile technologies in each linkin the supply chain. Moreover, the study confirms the growing popularity of this solution, as well as its contribution to constantly improving logistics customer service in terms of time, reliability, communication and comfort. Conclusions: Based on the study, the high level of general customers’ satisfaction of mobile technologies is incontestable proof of their overall benefits. Therefore, mobile technologies can be the key to gaining or keeping customers in the 21st-century marketplace. © 2019, Poznan School of Logistics. All rights reserved.","Logistics customer service; Mobile technologies; Omnichanneling; Satisfaction",{"$nulls":7},"Ashford R., QR Codes and Academic Libraries: Reaching Mobile Users, (2010); Cheremkhin P.A., Krasnov V.V., Rodin V.G., Starikov R.S., QR code optical encryption using spatially incoherent illumination, Laser Physics Letters, 14, (2017); (2017); Faulds D.J., Glynn Mangold W., Raju P.S., Valsalan S., The Mobile Shopping, 1449, pp. 1-16, (2017); Folwarski M., The impact of selected regulations on the development of payment systems in Poland, Marketing and Management of Innovations, 3, pp. 302-312, (2018); Grant D., Using Marketing and Services Strategies for Logistics Customer Service, In: Global Logistics, (2010); Landmark A.D., Sjobakk B., Tracking customer behaviour in fashion retail using RFID, International Journal of Retail & Distribution Management, 45, 7-8, pp. 844-858, (2018); Lanko A., Vatin N., Kaklauskas A., Application of RFID combined with blockchain technology in logistics of construction materials, MATEC Web of Conferences, 170, pp. 1-6, (2018); Melovic B., Mitrovic S., Djokaj A., Vatin N., Logistics in the Function of Customer Service - Relevance for the Engineering Management, Procedia Engineering, 117, pp. 802-807, (2015); Rezazadeh J., Subramanian R., Sandrasegaran K., Kong X., Moradi M., Khodamoradi F., Novel iBeacon Placement for Indoor Positioning in IoT, IEEE Sensors Journal, pp. 1-8, (2018); Wilson R., Hill A.V., Glazer H., Tools and Tactics for Operations Managers (Collection), (2013)","J. Ochocka; University of Lodz, Łódź, Poland; email: jagoda.ochocka@gmail.com",null,"Poznan School of Logistics",{"$nulls":5},1.8952038E7,null,null,null,"English","Logforum","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85073456756"]
["Dua A.; Sinha D.","Dua, Aman (57204355658); Sinha, Deepankar (57150177300)","57204355658; 57150177300","Assessment of Quality of Multimodal Transportation for Containerized Exports",2019.0,"IIM Kozhikode Society and Management Review",8.0,1.0,null,10.0,22.0,12.0,11.0,"10.1177/2277975218810613","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85081735945&doi=10.1177%2f2277975218810613&partnerID=40&md5=2a03fe0d89469c66ea8f220cc18d9c19","International Management Institute, Bhubaneswar, India; Indian Institute of Foreign Trade, Kolkata Campus, Kolkata, India","Dua A., International Management Institute, Bhubaneswar, India; Sinha D., Indian Institute of Foreign Trade, Kolkata Campus, Kolkata, India","The twin paradigm of e-commerce and just-in-time has impelled the global markets for door-to-door service. Shippers do not particularly seek special modes of transport but rather demand performance of transport such as door-to-door service from the multimodal transport service (MTS) operators. Door-to-door service has also led to shift in common terms of trade such as free on board (FOB) and cost insurance freight (CIF) to delivery at place (DAP) or delivery duty paid (DDP) International Commercial Terms (incoterms). In such a case, the sellers are required to plan end-to-end rather than concentrate on port-to-port leg of the delivery process. Multimodal transportation (MMT) includes multiple modes of transport, multiple nodes (terminals) and numerous stakeholders. So far, researchers have focused on the attributes of MTS providers that affect expectations of customers. The present study looks into factors affecting performance of MTS. The approach cuts across the spectrum of qualitative to quantitative assessment. The authors, here, propose opinion mining to decipher the sentiments of clients of logistics service providers followed by open discussion (in a semi-structured format) to collate the soft and hard aspects of MMT chain. The findings of these exercises are used to frame a structured questionnaire for quantitative analysis. Four dimensions affecting quality of MMT have been identified, and one of them is found to be significant only under certain conditions. This article suggests implementation of an integrated digital ecosystem to enhance the quality of MMT in emerging markets like India. © 2019 SAGE Publications.","confirmatory factor analysis; multimodal transportation; opinion mining; Quality; structural equation modelling",{"$nulls":7},"Anderson J.C., Gerbing D.W., Structural equation modeling in practice: A review and recommended two-step approach, Psychological Bulletin, 103, 3, pp. 411-423, (1988); Anthony T., Supply chain collaboration: Success in the new internet economy, Achieving Supply Chain Excellence through Technology, 2, pp. 41-44, (2000); Assadipour G., Ke G.Y., Verma M., Planning and managing intermodal transportation of hazardous materials with capacity selection and congestion, Transportation Research Part E: Logistics and Transportation Review, 76, pp. 45-57, (2015); Auramo J., Kauremaa J., Tanskanen K., Benefits of IT in supply chain management: An explorative study of progressive companies, International Journal of Physical Distribution & Logistics Management, 35, 2, pp. 82-100, (2005); Banomyong R., Beresford A.K.C., Multimodal transport corridors in South East Asia: A case study approach, (2000); Bienstock C.C., Mentzer J.T., Bird M.M., Measuring physical distribution service quality, Journal of the Academy of Marketing Science, 25, 1, pp. 31-44, (1997); Bruns F., Goerigk M., Knust S., Schobel A., Robust load planning of trains in intermodal transportation, OR Spectrum, 36, 3, pp. 631-668, (2014); Chao P., The impact of multimodal transport service value and relationships on business performance: The Thai shippers’ perspective, (2011); Choong S.T., Cole M.H., Kutanoglu E., Empty container management for intermodal transportation networks, Transportation Research Part E: Logistics and Transportation Review, 38, 6, pp. 423-438, (2002); Chopra S., Meindl P., Supply chain management. 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Hair J.F., Black W.C., Babin B.J., Anderson R.E., Multivariate data analysis, (2010); Hair J.F., Black W.C., Babin B.J., Anderson R.E., Tatham R.L., Multivariate data analysis, 5, pp. 207-219, (1998); Henstra D., Woxenius J., Intermodal transport in Europe, (1999); Hernandez S., Peeta S., A carrier collaboration problem for less-than-truckload carriers: Characteristics and carrier collaboration model, Transportmetrica A: Transport Science, 10, 4, pp. 327-349, (2014); Hoffman A.J., Lusanga K.P., Bhero E., A combined GPS/RFID system for improved cross-border management of freight consignments, Africon, pp. 1-8, (2013); Holguin-Veras J., Thorson E., Modeling commercial vehicle empty trips with a first order trip chain model, Transportation Research Part B: Methodological, 37, 2, pp. 129-148, (2003); Holweg M., Disney S., Holmstrom J., Smaros J., Supply chain collaboration: Making sense of the strategy continuum, European Management Journal, 23, 2, pp. 170-181, (2005); Iravani S.M., Van Oyen M.P., Sims K.T., Structural flexibility: A new perspective on the design of manufacturing and service operations, Management Science, 51, 2, pp. 151-166, (2005); 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Sinha; Indian Institute of Foreign Trade, Kolkata, Kolkata Campus, India; email: dsinha2000@gmail.com",null,"Sage Publications India Pvt. Ltd",{"$nulls":5},2.2779752E7,null,null,null,"English","IIM Kozhikode Soc. Manag. Rev.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85081735945"]
["Lee S.W.; Sung H.J.; Jeon H.M.","Lee, Suk Won (57209304427); Sung, Hye Jin (57209309310); Jeon, Hyeon Mo (57192394658)","57209304427; 57209309310; 57192394658","Determinants of continuous intention on food delivery apps: Extending UTAUT2 with information quality",2019.0,"Sustainability (Switzerland)",11.0,11.0,3141.0,null,null,null,176.0,"10.3390/su11113141","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85067313301&doi=10.3390%2fsu11113141&partnerID=40&md5=b150e14eb5354734378ce52ec2932a93","Department of Hotel, Tourism, and Foodservice Management, Dongguk University-Gyeonju, 123, Dongdae-ro, Gyeongju-si, Gyeongsangbuk-do, 38066, South Korea; Department of Foodservice Management, Pai Chai University, 155-40, Baejae-ro, Seo-gu, Daejeon-si, 35345, South Korea","Lee S.W., Department of Hotel, Tourism, and Foodservice Management, Dongguk University-Gyeonju, 123, Dongdae-ro, Gyeongju-si, Gyeongsangbuk-do, 38066, South Korea; Sung H.J., Department of Foodservice Management, Pai Chai University, 155-40, Baejae-ro, Seo-gu, Daejeon-si, 35345, South Korea; Jeon H.M., Department of Hotel, Tourism, and Foodservice Management, Dongguk University-Gyeonju, 123, Dongdae-ro, Gyeongju-si, Gyeongsangbuk-do, 38066, South Korea","This study empirically analyzes an extended Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model that augments information quality to identify the determinants of continuous use intention for food delivery software applications. A sample survey of 340 respondents who had ordered or purchased food through delivery apps was used for the analysis. The results indicate that habit had the strongest influence on continuous use intention, followed by performance expectancy and social influence. Furthermore, information quality had an indirect effect on continuous use intention via performance expectancy. Consequently, this study confirms the importance of information quality, performance expectancy, habit, and social influence as factors in inducing users' continuous use intention for food delivery apps. These findings expand previous research in online-to-offline business in the field of food services and suggest practical implications. Ultimately, the model proposed and validated in this study may be employed as a basis for future research on consumer behavior in the field of food e-commerce services. © 2019 by the authors.","Continuous intention; Food delivery app; Food service consumer; Information quality; O2O; UTAUT2","business development; food; food consumption; information; model validation; perception; performance assessment; software",{"$nulls":6},"Liu W., Batra R., Wang H., Product touch and consumers' online and offline buying: The role of mental representation, J. Retail, 93, pp. 369-381, (2017); Cho M.H., Bonn M.A., Li J., Differences in perceptions about food delivery apps between single-person and multi-person households, Int. J. Hosp. Manag, 77, pp. 108-116, (2019); Ji S.W., Sun X.Y., Liu D., Research on core competitiveness of Chinese retail industry based on O2O, Adv. Mater. Res, 834-836, pp. 2017-2020, (2014); Lyu S.O., Hwang J., Are the days of tourist information centers gone? 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Manag, 35, pp. 45-56, (2015); Singh M., Matsui Y., How long tail and trust affect online shopping behavior: An extension to UTAUT2 framework, Pac. Asia J. Assoc. Inf. Syst, 9, pp. 1-24, (2017); Shaw N., Sergueeva K., The non-monetary benefits of mobile commerce: Extending UTAUT2 with perceived value, Int. J. Inf. Manag, 45, pp. 44-55, (2019); Prasanna R., Huggins T.J., Factors affecting the acceptance of information systems supporting em ergency operations centres, Comput. Hum. Behav, 57, pp. 168-181, (2016); Escobar-Rodriguez T., Carvajal-Trujillo E., Online drivers of consumer purchase of website airline tickets, Air Transp. Manag, 32, pp. 58-64, (2013); Barnes S.J., Vidgen R.T., An integrative approach to the assessment of e-commerce quality, J. Electron. Commer. Res, 3, pp. 114-127, (2002); Hair J.F., Hult G.T.M., Ringle C., Sarstedt M., Primer on Partial Least Squares Structural Equation Modelling (PLS-SEM), (2016); Fornell C.R., Larcker D.F., Evaluating structural equation models with unobservable variables and measurement error, J. Mark. Res, 18, pp. 39-50, (1981); Wright K.B., Researching internet-based populations: Advantages and disadvantages of online survey research, online questionnaire authoring software packages, and web survey services, J. Comput.-Mediat. Commun, 10, (2005)","H.M. Jeon; Department of Hotel, Tourism, and Foodservice Management, Dongguk University-Gyeonju, Gyeongju-si, Gyeongsangbuk-do, 123, Dongdae-ro, 38066, South Korea; email: jhm010@dongguk.ac.kr",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85067313301"]
["Jannifer Rani N.; Bina Pani S.; Nimisha N.S.","Jannifer Rani, N. (57211398801); Bina Pani, S. (57211472775); Nimisha, N.S. (57211387196)","57211398801; 57211472775; 57211387196","A study on factors influencing to use online food apps",2019.0,"Journal of Advanced Research in Dynamical and Control Systems",11.0,"9 Special Issue",null,1325.0,1330.0,5.0,0.0,"10.5373/JARDCS/V11/20192744","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85078832228&doi=10.5373%2fJARDCS%2fV11%2f20192744&partnerID=40&md5=e74773ed3311381d62998a8cd033571c","Department of Commerce and Economics, Faculty of Arts and Science, BIHER, Bharath Institute of Higher Education & Research, Selaiyur, Chennai, India","Jannifer Rani N., Department of Commerce and Economics, Faculty of Arts and Science, BIHER, Bharath Institute of Higher Education & Research, Selaiyur, Chennai, India; Bina Pani S., Department of Commerce and Economics, Faculty of Arts and Science, BIHER, Bharath Institute of Higher Education & Research, Selaiyur, Chennai, India; Nimisha N.S., Department of Commerce and Economics, Faculty of Arts and Science, BIHER, Bharath Institute of Higher Education & Research, Selaiyur, Chennai, India","The current status and situation shows the growth in use of internet and mobile phones. Increasing use of mobile phones and internet leads to digital acting like online shopping, mobile payment, smart marketers use this opportunity and developed many new applications to serve the online customers. In food industry food delivery apps makes huge impact in the online services. This study shows the service strategies used by food delivery apps. The structured questionnaire was used as research tool for understanding the impact on customers. Data was collected from 50 respondents in south Chennai. Anova and descriptive analysis was used to analyze the responses. The main aim of the study was to analyze the service strategies and its impact on customers. And also to find out the most preferred food delivery app in south Chennai and also the factors which influence to use food delivery apps. © 2019, Institute of Advanced Scientific Research, Inc.. All rights reserved.","Food delivery apps; Online service; Service strategies",{"$nulls":7},"Udayakumar R., Khanaa V., Saravanan T., Analysis of polarization mode dispersion in fibers and its mitigation using an optical compensation technique, Indian Journal of Science and Technology, 6, pp. 4767-4771, (2013); Udayakumar R., Kumarave A., Rangarajan K., Introducing an efficient programming paradigm for object-oriented distributed systems, Indian Journal of Science and Technology, 6, pp. 4596-4603, (2013); Uma Mageswaran S., Guna Sekhar N.O., Reactive power contribution of multiple STATCOM using particle swarm optimization, International Journal of Engineering and Technology, 5, 1, pp. 122-126, (2013); Kumar Giri R., Saikia M., Multipath routing for admission control and load balancing in wireless mesh networks, International Review on Computers and Software, 8, 3, pp. 779-785, (2013); Padmapriya G., Manikandan A., Krishnasamy V., Jaganathan S.K., Antony S.A., Spinel NixZn1-xFe2O4 (0.0 ≤ x ≤ 1.0) nano-photocatalysts: Synthesis characterization and photocatalytic degradation of methylene blue dye, Journal of Molecular Structure, 1119, pp. 39-47, (2016); 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Teresita V.M., Manikandan A., Josephine B.A., Sujatha S., Antony S.A., Electromagnetic Properties and Humidity-Sensing Studies of Magnetically Recoverable LaMg x Fe 1-x O 3-δ Perovskites Nano-photocatalysts by Sol-Gel Route, Journal of Superconductivity and Novel Magnetism, 29, 6, pp. 1691-1701, (2016); Lydia Caroline M., Vasudevan S., Growth and characterization of pure and doped bis thiourea zinc acetate: Semiorganic nonlinear optical single crystals, Current Applied Physics, 9, 5, pp. 1054-1061, (2009); Jayalakshmi V., Gunasekar N.O., Implementation of discrete PWM control scheme on Dynamic Voltage Restorer for the mitigation of voltage sag /swell, 2013, International Conference on Energy Efficient Technologies for Sustainability, ICEETS, 2013, pp. 1036-1040, (2013); Udayakumar R., Khanaa V., Kaliyamurthie K.P., Optical ring architecture performance evaluation using ordinary receiver, Indian Journal of Science and Technology, 6, pp. 4742-4747, (2013); Udayakumar R., Khanaa V., Kaliyamurthie K.P., Performance analysis of resilient ftth architecture with protection mechanism, Indian Journal of Science and Technology, 6, pp. 4737-4741, (2013); 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Jannifer Rani; Department of Commerce and Economics, Faculty of Arts and Science, BIHER, Bharath Institute of Higher Education & Research, Chennai, Selaiyur, India; email: janniferrani.com@bharathuniv.ac.in",null,"Institute of Advanced Scientific Research, Inc.",{"$nulls":5},"1943023X",null,null,null,"English","J. Adv. Res. Dyn. Control. Syst.","Article","Final",null,"Scopus","2-s2.0-85078832228"]
["Gupta P.; Mehlawat M.K.; Mahajan D.","Gupta, Pankaj (57193233548); Mehlawat, Mukesh Kumar (23035630900); Mahajan, Divya (57201530795)","57193233548; 23035630900; 57201530795","Multi-objective optimization framework for software maintenance, component evaluation and selection involving outsourcing, redundancy and customer to customer relationship",2019.0,"Information Sciences",483.0,null,null,21.0,52.0,31.0,9.0,"10.1016/j.ins.2019.01.017","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85060243667&doi=10.1016%2fj.ins.2019.01.017&partnerID=40&md5=c19bfa2b227acde7e6c9c664ed2ef1be","Department of Operational Research, University of Delhi, Delhi, India","Gupta P., Department of Operational Research, University of Delhi, Delhi, India; Mehlawat M.K., Department of Operational Research, University of Delhi, Delhi, India; Mahajan D., Department of Operational Research, University of Delhi, Delhi, India","In this paper, we propose an integrated multi-objective optimization framework for the development and maintenance of a modular software system. From the perspective of development, other than the cost of a software system, the compatibility of the software components, software reliability, delivery time and execution time for the software, we also consider the evaluation of fitness (using TOPSIS) of software components (COTS and in-house) for non-outsourced modules and vendors for outsourced modules on the basis of many important qualitative attributes. On the other hand, from the perspective of maintenance, we consider the software maintenance cost, the evaluation of fitness (using TOPSIS) of maintenance teams (the outsourced teams and the in-house team) on the basis of many important qualitative attributes, and the interactions between maintenance teams, which we call as the customer to customer (C2C) relationship. Moreover, in order to ensure that the software development company may not prefer to interact with a large number of maintenance teams and that a single team is not always burdened with the maintenance of all the modules, we consider some new cardinality and load balancing constraints. The proposed optimization model is tested using a real-world case study involving e-commerce software development. © 2019 Elsevier Inc.","Component-based software development; Multiple criteria decision analysis; Optimization; Outsourcing; Software maintenance","Computer software selection and evaluation; Decision theory; Multiobjective optimization; Operations research; Optimization; Outsourcing; Public relations; Sales; Software design; Software reliability; Software testing; Component evaluation; Component-based software development; Customer to customer relationships; Evaluation of fitness; Multiple criteria decision analysis; Optimization modeling; Qualitative attributes; Software maintenance costs; Computer software maintenance",{"$nulls":6},"Ahmed A.M., Zhu W., Outsourcing software testing activities: a case study for eastern ocean solutions-china, Proceedings of the 3rd IEEE International Conference on Communication Software and Networks (ICCSN), Xi'an, China, pp. 742-744, (2011); Ahmed R.E., Software maintenance outsourcing: issues and strategies, Comput. Electr. Eng., 32, pp. 449-453, (2006); Badampudi D., Wohlin C., Petersen K., Software component decision-making: in-house, OSS, COTS or outsourcing-a systematic literature review, J. Syst. Softw., 121, pp. 105-124, (2016); Baharom F., Yahaya J.H., Tarawneh F., The Development of Software Evaluation and Selection Framework for Supporting COTS-Based Systems: The Theoretical Framework, Proceedings of the International Conference on Software Engineering and Computer Systems, Software Engineering and Computer Systems, pp. 133-143, (2011); Berman O., Ashrafi N., Optimization models for reliability of modular software systems, IEEE Trans. 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Eng., 18, pp. 573-595, (2011); Gupta P., Mehlawat M.K., Mittal G., Verma S., A hybrid approach for selecting optimal COTS products, Lect. Notes Comput. Sci., 5592, pp. 949-962, (2009); Hwang C.L., Yoon K., Multiple Attribute Decision making: Methods and Applications, (1981); Jha P.C., Arora R., Kumar U.D., An optimization framework for “build or buy” strategy for component selection in a fault tolerant modular software system under recovery block scheme, Ratio Math., 21, pp. 91-105, (2011); Jung H.W., Choi B., Optimization models for quality and cost of modular software systems, Eur. J. Oper. 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Intell., 42, pp. 353-368, (2015); Mittal S., Bhatia P.K., Software component quality models from ISO 9126 perspective: a review, IJMRS's Int. J. Eng. Sci., 2, pp. 6-13, (2013); Neubauer T., Stummer C., Interactive decision support for multiobjective COTS selection, Proceedings of the 40th Annual Hawaii International Conference on System Sciences, Big Island, 283b, (2007); Nunkaew W., Phruksaphanrat B., A multiobjective programming for transportation problem with the consideration of both depot to customer and customer to customer relationships, Proceedings of the International MultiConference of Engineers and Computer Scientists, IMECS, (2009); Pande J., Bisht R., Pant D., Pathak V., On some quality issues of component selection in CBSD, J. Software Eng. Appl., 3, pp. 556-560, (2010); Pressman, Roger S., Software engineering-a practitioner's approach, (2014); Rolland C., Requirement engineering for COTS based systems, Inf. Software Technol., 41, pp. 985-990, (1999); Saaty T.L., Fundamentals of decision making and priority theory with the analytic hierachy process, (1994); Tarawneh F., Baharom F., Yahaya J.H., Ahmad F., Evaluation and selection of COTS software process: the state of art, Int. J. New Comput. Archit. Appl., 1, pp. 344-357, (2011); Tarawneh F., Baharom F., Yahaya J.H., Zainol A., COTS software evaluation and selection: a pilot study based in jordan firms, Proceedings of the International Conference on Electrical Engineering and Informatics, Bandung, Indonesia, (2011); Verma S., Mehlawat M.K., Multi-criteria optimization model integrated with AHP for evaluation and selection of COTS components, Optimization, 66, pp. 1879-1894, (2017); Verma S., Mehlawat M.K., Mahajan D., Software component evaluation and selection using TOPSIS and fuzzy interactive approach under multiple applications development, Ann. Oper. Res., (2018); Zachariah B., Rattihalli R.N., A multicriteria optimization model for quality of modular software systems, Asia-Pacific J. Oper. Res., 24, pp. 797-811, (2007)","P. Gupta; Delhi, Flat No.-01, Kamayani Kunj, Plot No. 69, Indraprastha Extension, 110092, India; email: pgupta@or.du.ac.in",null,"Elsevier Inc.",{"$nulls":5},200255.0,null,"ISIJB",null,"English","Inf Sci","Article","Final",null,"Scopus","2-s2.0-85060243667"]
["Barenji A.V.; Wang W.M.; Li Z.; Guerra-Zubiaga D.A.","Barenji, Ali Vatankhah (55616657900); Wang, W.M. (8232186000); Li, Zhi (57189370824); Guerra-Zubiaga, David A. (23060428300)","55616657900; 8232186000; 57189370824; 23060428300","Intelligent E-commerce logistics platform using hybrid agent based approach",2019.0,"Transportation Research Part E: Logistics and Transportation Review",126.0,null,null,15.0,31.0,16.0,77.0,"10.1016/j.tre.2019.04.002","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85064005003&doi=10.1016%2fj.tre.2019.04.002&partnerID=40&md5=adaa5e33c4f57c145d95ba3398b781f8","Guangdong Provincial Key Laboratory of Computer Integrated Manufacturing System, School of Electromechanical Engineering, Guangdong University of Technology, Guangzhou, 510006, China; Mechatronics Engineering Department, Kennesaw State University, Marietta, GA, United States","Barenji A.V., Guangdong Provincial Key Laboratory of Computer Integrated Manufacturing System, School of Electromechanical Engineering, Guangdong University of Technology, Guangzhou, 510006, China; Wang W.M., Guangdong Provincial Key Laboratory of Computer Integrated Manufacturing System, School of Electromechanical Engineering, Guangdong University of Technology, Guangzhou, 510006, China; Li Z., Guangdong Provincial Key Laboratory of Computer Integrated Manufacturing System, School of Electromechanical Engineering, Guangdong University of Technology, Guangzhou, 510006, China; Guerra-Zubiaga D.A., Mechatronics Engineering Department, Kennesaw State University, Marietta, GA, United States","This paper proposes a hybrid agent-based approach for the scheduling and synchronization of e-commerce logistics parks (EcLP). This is accomplished by integrating intelligent distribution centers within the e-commerce environment. The proposed platform has been developed based on an agent technology, which not only serves for decentralization and synchronization purposes but also it has been optimized for the transportation and logistics of the overall system. Moreover, mobile agent-based communication mechanisms between the hardware agents and the software agents were developed, and the proposed hybrid agent-based platform was implemented and tested based on a case study. Following this, the results were compared to a conventional system based on four main indicators. © 2019","And control; E-commerce; E-commerce logistic park; Multi-agent system; Online to offline; Scheduling","Intelligent agents; Mobile agents; Mobile commerce; Software testing; Agent-based approach; And control; E- commerces; E-commerce logistic park; Hybrid agents; Logistics park; Logistics platforms; Offline; Online to offline; Scheduling; decentralization; electronic commerce; logistics; software; technological development; Multi agent systems",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (51405089); China Postdoctoral Science Foundation, (2018M630928, 2018M633008); Natural Science Foundation of Guangdong Province, (2018A0303130035)","This work was supported by the National Natural Science Foundation of China under Grant [ 51405089 ], the Natural Science Foundation of Guangdong Province [ 2018A0303130035 ], and China Postdoctoral Science Foundation under [ 2018M630928 ] and [ 2018M633008 ].  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["Hsiao W.-H.; Chang T.-S.","Hsiao, Wei-Hung (55378106000); Chang, Tsung-Sheng (8832869500)","55378106000; 8832869500","Exploring the opportunity of digital voice assistants in the logistics and transportation industry",2019.0,"Journal of Enterprise Information Management",32.0,6.0,null,1034.0,1050.0,16.0,17.0,"10.1108/JEIM-12-2018-0271","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85073200010&doi=10.1108%2fJEIM-12-2018-0271&partnerID=40&md5=b59fe34d73fedc64e4c8702a48ef29df","Department of Distribution Management, National Taichung University of Science and Technology, Taichung, Taiwan; Department of Information Management, Da-Yeh University, Changhua, Taiwan","Hsiao W.-H., Department of Distribution Management, National Taichung University of Science and Technology, Taichung, Taiwan; Chang T.-S., Department of Information Management, Da-Yeh University, Changhua, Taiwan","Purpose: The logistics industry has benefited hugely from the growth of e-commerce. The logistics and transportation industry operators have realized that higher-quality service and logistics management provides the competitive edge as the primary channel of communication with consumers. Digital voice assistants (DVA) is an information system based on an artificial intelligence framework that can interact through voice, such that a deliveryman can query for or use information in a relatively short time. The purpose of this paper is to explore the value of DVA in logistic service. Design/methodology/approach: This study aims to develop a framework for innovation and logistics service capabilities of logistics and transportation services to structure a model based on the analysis hierarchy process method to discuss the factors considered when adopting DVA. Findings: The results of this study implied that common problem and expectations of current operators in the delivery of goods and their expectations of DVA. Practical implications: Innovative operations and planning are possible with information technology-enabled logistic services. It is important to identify relevant DVA development avenues. Originality/value: The purpose of this study is to show which factors are significant to the logistics and transportation industry using DVA to aid the deliverymen, and it provides guidance for manager evaluating adopted DVA and its object. © 2019, Emerald Publishing Limited.","Analytic hierarchy process (AHP); Digital voice assistants (DVA); Innovation and logistics service capability; Smart logistic; Transport",{"$nulls":7},"Agrawal S., Singh R.K., Murtaza Q., Triple bottom line performance evaluation of reverse logistics, Competitiveness Review, 26, 3, pp. 289-310, (2016); AI Khalil M.I., Selecting the appropriate project delivery method using AHP, International Journal of Project Management, 20, 6, pp. 469-474, (2002); Athanasis N., Karagiannis F., Palaiologou P., Vasilakos C., Kalabokidis K., AEGIS app: wildfire information management for windows phone devices, Procedia Computer Science, 56, pp. 544-549, (2015); Azar G., Ciabuschi F., Organizational innovation, technological innovation, and export performance: the effects of innovation radicalness and extensiveness, International Business Review, 26, 2, pp. 324-336, (2017); Barata M., Salman A.G., Faahakhododo I., Kanigoro B., Android based voice assistant for blind people, Library Hi Tech News, 35, 6, pp. 9-11, (2018); Barney J.B., Resource-based theories of competitive advantage: a ten year retrospective on the resource-based view, Journal of Management, 27, 6, pp. 643-650, (2001); Benitez J., Delgado-Galvan X., Izquierdo J., Perez-Garcia R., An approach to AHP decision in a dynamic context, Decision Support Systems, 53, 3, pp. 499-506, (2012); Bertscher I., Erdsiek D., Trenz M., IT outsourcing—a source of innovation? 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Chang; Department of Information Management, Da-Yeh University, Changhua, Taiwan; email: china@mail.dyu.edu.tw",null,"Emerald Group Holdings Ltd.",{"$nulls":5},1.7410398E7,null,null,null,"English","J. Enterp. Inf. Manage.","Article","Final",null,"Scopus","2-s2.0-85073200010"]
["Alves R.; Lima R.S.; de Sena D.C.; de Pinho A.F.; Holguín-Veras J.","Alves, Roberta (55623213700); Lima, Renato da Silva (57219937996); de Sena, David Custódio (57188752227); de Pinho, Alexandre Ferreira (24586945600); Holguín-Veras, José (6701659951)","55623213700; 57219937996; 57188752227; 24586945600; 6701659951","Agent-based simulation model for evaluating urban freight policy to e-commerce",2019.0,"Sustainability (Switzerland)",11.0,15.0,4020.0,null,null,null,36.0,"10.3390/su11154020","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85070371623&doi=10.3390%2fsu11154020&partnerID=40&md5=7a35284611262e7c686dd140bbeb2320","Mechanical Department, Federal University of São João del Rei, Minas Gerais, 36307-353, Brazil; Industrial Engineering and Management Institute, Federal University of Itajubá, Minas Gerais, 37500-903, Brazil; Environmental Sciences and Engineering Department, Federal Rural University of Semi-Arid, Rio Grande do Norte, 59625-900, Brazil; Department of Civil and Environmental Engineering, Rensselaer Polytechnic Institute, Troy, 12180, NY, United States","Alves R., Mechanical Department, Federal University of São João del Rei, Minas Gerais, 36307-353, Brazil, Industrial Engineering and Management Institute, Federal University of Itajubá, Minas Gerais, 37500-903, Brazil; Lima R.S., Industrial Engineering and Management Institute, Federal University of Itajubá, Minas Gerais, 37500-903, Brazil; de Sena D.C., Environmental Sciences and Engineering Department, Federal Rural University of Semi-Arid, Rio Grande do Norte, 59625-900, Brazil; de Pinho A.F., Industrial Engineering and Management Institute, Federal University of Itajubá, Minas Gerais, 37500-903, Brazil; Holguín-Veras J., Department of Civil and Environmental Engineering, Rensselaer Polytechnic Institute, Troy, 12180, NY, United States","This study aims to assess delivery lockers as a last-mile solution, considering the behavior and interaction among e-commerce stakeholders. In Brazil, a large portion of deliveries are attended home. This results in a large number of failed deliveries and redelivery attempts, which can reach up to three delivery attempts. Delivery lockers (DL) represent a solution to reduce the number of re-deliveries and consolidate the delivery of goods. The implementation of DL and the exclusion of the third delivery attempt are evaluated in this study via an agent-based simulation model (ABSM) in the city of Belo Horizonte, Brazil. Four scenarios were simulated by varying delivery locker implementation and the exclusion of the third attempts, which allowed comparable results to be obtained for each agent, in terms of gains and operational and external costs (emission, noise, and congestion). The scenario that most closely resembles the current situation was the one that presented the worst results. The implementation of the lockers brings improvements to this scenario in terms of reducing re-deliveries and distances traveled by trucks. When the possibility of three delivery attempts is excluded, the benefits are even greater. The deployment of lockers also enables carriers to reduce the number of trucks required to make deliveries, thereby increasing their profits. © 2019 by the authors.","City logistics; Delivery lockers; Simulation","Belo Horizonte; Brazil; Minas Gerais; electronic commerce; freight transport; logistics; operations technology; simulation; stakeholder",{"$nulls":4},"Foundation for the Promotion of Science; Conselho Nacional de Desenvolvimento Científico e Tecnológico, CNPq; Fundação de Amparo à Pesquisa do Estado de Minas Gerais, FAPEMIG","Funding: The authors would like to acknowledge the Brazilian agencies FAPEMIG (Foundation for the Promotion of Science of the State of Minas Gerais) and CNPq (Brazilian National Council for Scientific and Technological Development) for the financial support provided to this research.","(2018); Morganti E., Seidel S., Blanquart C., Dablanc L., Lenz B., The impact of e-commerce on final deliveries: Alternative parcel delivery services in France and Germany, Transp. 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Simul, 7, pp. 12-24, (2013); (2015); (2012); Edwards J., Mckinnon A., Cherrett T., Mcleod F., Song L., Carbon Dioxide Benefits of Using Collection-Delivery Points for Failed Home Deliveries in the United Kingdom, Transp. Res. Rec, 2191, pp. 136-143, (2010); Bodin L., Routing and Acheduling of vehicles and crews, the state of the art, Comput. Oper. Res, 10, pp. 63-211, (1983); Esser K., Kurte J., Strategies for Optimizing Pick-up and Delivery Traffic of Internet Commerce-Packstations in Cologne (OPTIMAL)), (2007); Redução das deseconomias urbanas pela melhoria do transporte público, Rev. dos Transp. Públicos, 21, pp. 35-92, (1999); Planilhas Referenciais de Custo do Transporte Rodoviário de Cargas, (2018); Update of the Handbook on External Costs of Transport; PCAPredict Fixing Failed Deliveries: Improving Data Quality in Retail, (2018); Teoh T., Kunze O., Teo C.C., Wong Y.D., Decarbonisation of urban freight transport using electric vehicles and opportunity charging, Sustainability, 10, (2018); Aljohani K., Thompson R.G., A stakeholder-based evaluation of the most suitable and sustainable delivery fleet for freight consolidation policies in the inner-city area, Sustainability, 11, (2018)","R. Alves; Mechanical Department, Federal University of São João del Rei, Minas Gerais, 36307-353, Brazil; email: robertaalves@ufsj.edu.br",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85070371623"]
["Prabhu S.","Prabhu, Sandeep (57200120608)",5.7200120608E10,"Factors of service quality and service-recovery quality of online retailers",2019.0,"International Journal of Innovative Technology and Exploring Engineering",8.0,"11 Special Issue",null,356.0,361.0,5.0,2.0,"10.35940/ijitee.K1065.09811S19","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85073520167&doi=10.35940%2fijitee.K1065.09811S19&partnerID=40&md5=47205d22bb36be38d17cc2c8cd0b1c8f","Symbiosis Institute of Telecom Management, Constituent of Symbiosis International University, Pune, India","Prabhu S., Symbiosis Institute of Telecom Management, Constituent of Symbiosis International University, Pune, India","The purpose of this research is to explore factors of ‘service quality’ and ‘service-recovery quality’ of online retailers in India; and to suggests measurement constructs for ‘service quality’ and ‘service-recovery quality’ from customer’s perspective. Exploratory factor analysis (EFA) of customer responses of a survey of consumer attitudes is used for data analysis. In the first stage, concepts and constructs of the ‘service quality’ and ‘service-recovery quality’ for online retailers are identified through extensive literature review. In the second stage, survey of attitude measurement questionnaire was administered to customers, —who have experienced online shopping over a period of time. A 7-point Likert scale is used for capturing customer responses based on quota sampling technique. EFA is conducted using oblique rotation considering factor dependence. Factors thus identified are further studied for literature support, analyzed for validity and reliability. Exploratory factor analysis using principal component method, identified five factor structure of ‘service quality’ of online retailers as; e-reliability, e-servicescape, e-technology dissatisfiers, e-security and e-delivery. Research also explored factors of ‘service-recovery quality’ of online retailers as; e-support and e-compensation. The proposed factors of ‘service quality’ and ‘service recovery quality’ of online retailers can be useful in improving service product offers. The designed research constructs can be operationalized for better online shopping consumer experience. Considering retail customer channel shift from offline retail shops to online retail, this research is a latest consumer perspective towards online buying. Identified factors is useful inputs to design online retail service quality by improving retail operations. © BEIESP.","Consumer behavior; Exploratory factor analysis; Online retail; Service quality; Service recovery",{"$nulls":7},"Ahn T., Ryu S., Han I., The impact of Web quality and playfulness on user acceptance of online retailing, Information and Management, 44, 3, pp. 263-275, (2007); Carlson J., O'Cass A., Developing a framework for understanding e-service quality, its antecedents, consequences, and mediators, Managing Service Quality, 21, 3, pp. 264-286, (2011); (2011); Chiu C., Chang C., Cheng H., Fang Y., Determinants of customer repurchase intention in online shopping, Online Information Review, 33, 4, pp. 761-784, (2009); Cronin J.J., Taylor S.A., Measuring service quality: A re-examination and extension, Journal of Marketing, 56, 3, pp. 55-68, (1992); Dabholkar P.A., A Contingency Framework for Predicting Causality Between Customer Satisfaction and Service Quality, Advances in Consumer Research, 22, 1, pp. 101-108, (1995); Dabholkar P.A., Shepherd C.D., Thorpe D.I., A Comprehensive Framework for Service Quality: An investigation of Critical Conceptual and Measurement Issues Through a Longitudinal Study, Journal of Retailing, 76, pp. 139-173, (2000); Davis F.D., A technology acceptance model for empirically testing new end-user information systems: Theory and results, Management, (1986); Frost F.A., Kumar M., INTSERVQUAL – an internal adaptation of the GAP model in a large service organisation, Journal of Services Marketing, (2000); Gronroos C., A Service Quality Model and its Marketing Implications, European Journal of Marketing, (1984); Ha S., Stoel L., Online apparel retailing: Roles of e-shopping quality and experiential e-shopping motives, Journal of Service Management, 23, 2, pp. 197-215, (2012); Hsu S.H., Developing an index for online customer satisfaction: Adaptation of American Customer Satisfaction Index, Expert Systems with Applications, 34, 4, pp. 3033-3042, (2008); Kim J., Lennon S.J., Effects of reputation and website quality on online consumers’ emotion, perceived risk and purchase intention: Based on the stimulus-organism-response model, Journal of Research in Interactive Marketing, 7, 1, pp. 33-56, (2013); Kim M., Kim J.H., Lennon S.J., Online service attributes available on apparel retail web sites: An E-S-QUAL approach, Managing Service Quality, 16, 1, pp. 51-77, (2006); Long M., McMellon C., Exploring the determinants of retail service quality on the Internet, Journal of Services Marketing, 18, 1, pp. 78-90, (2004); Luk S., Layton R., Perception Gaps in customer expectations: Managers versus service providers and customers, Service Industries Journal, 22, 2, pp. 109-128, (2002); Nwabueze U., Reality check: The identification of service gaps in the NHS, Total Quality Management, 12, 6, pp. 757-771, (2001); Parasuraman A., SERVQUAL: A Multiple-Item Scale for Measuring Consumer Perceptions of Service Quality, Journal of Retailing, 64, 1, pp. 5-6, (1988); Parasuraman A., Zeithaml V.A., Berry L.L., A Conceptual Model of Service Quality and Its Implications for Future Research, Journal of Marketing, 49, Fall, pp. 41-50, (1985); Parasuraman A., Zeithaml V.A., Malhotra A., E-S-QUAL: A Multiple-Item Scale for Assessing Electronic Service Quality, Journal of Service Research, 7, pp. 1-21, (2005); Prabhu S., A Study of Retail Service Gaps with Specific Reference to Three Major Color Television Brands in Pune City, 1, pp. 1-266, (2016); Pune Muncipal Corporation Census 2011, Household Data., (2011); (2018); Trocchia P.J., Janda S., How do consumers evaluate Internet retail service quality?, Journal of Services Marketing, 17, 3, pp. 243-253, (2003)","S. Prabhu; Symbiosis Institute of Telecom Management, Constituent of Symbiosis International University, Pune, India; email: sprabhu@sitm.ac.in",null,"Blue Eyes Intelligence Engineering and Sciences Publication",{"$nulls":5},2.2783075E7,null,null,null,"English","Int. J. Innov. Technol. Explor. Eng.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85073520167"]
["Heshmati S.; Verstichel J.; Esprit E.; Vanden Berghe G.","Heshmati, Sam (35174484100); Verstichel, Jannes (50862194200); Esprit, Eline (57191899794); Vanden Berghe, Greet (57195924329)","35174484100; 50862194200; 57191899794; 57195924329","Alternative e-commerce delivery policies: A case study concerning the effects on carbon emissions",2019.0,"EURO Journal on Transportation and Logistics",8.0,3.0,null,217.0,248.0,31.0,8.0,"10.1007/s13676-018-0120-4","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85071639723&doi=10.1007%2fs13676-018-0120-4&partnerID=40&md5=9e61e50141a62b1a3c53da2884d56639","KU Leuven, Department of Computer Science, CODeS & imec, Gent, Belgium; INESC TEC, Faculty of Engineering, University of Porto, Porto, Portugal","Heshmati S., KU Leuven, Department of Computer Science, CODeS & imec, Gent, Belgium, INESC TEC, Faculty of Engineering, University of Porto, Porto, Portugal; Verstichel J., KU Leuven, Department of Computer Science, CODeS & imec, Gent, Belgium; Esprit E., KU Leuven, Department of Computer Science, CODeS & imec, Gent, Belgium; Vanden Berghe G., KU Leuven, Department of Computer Science, CODeS & imec, Gent, Belgium","Contemporary shopping habits are undergoing rapid change, with more and more consumers purchasing goods online. The rapid growth of the online retail sector provides great opportunities for both wholesalers and transporters in servicing this newly emergent type of customer. With both consumers and corporations acutely aware of the environmental impact of business activities, one of the most relevant research questions is how to organize the operations of a e-commerce delivery business while simultaneously minimizing its environmental impact. The present paper addresses the e-commerce delivery problem, a mathematical formulation and fast heuristics which enable the simulation of various e-commerce delivery scenarios. The effects of the scenarios regarding more environmentally friendly e-commerce concerns are tested upon real-world data. In particular, the impact of new green(er) technology (such as electric bicycles and cars), aggregated collection points, carrier bundling, and changing delivery times is investigated. The obtained results are suitable for implementation at an organizational or operational level within both e-commerce delivery companies and transporters. © 2018, Springer-Verlag GmbH Germany, part of Springer Nature and EURO - The Association of European Operational Research Societies.","E-commerce delivery problem; Mixed-fleet vehicle routing; Operational policies","Carbon; Electronic commerce; Fleet operations; Sales; Vehicle routing; Business activities; Carbon emissions; Delivery problems; Electric bicycles; Mathematical formulation; Operational level; Operational policy; Research questions; Environmental impact",{"$nulls":4},"Agentschap Innoveren en Ondernemen, VLAIO, (IWT 140002); Belgian Federal Science Policy Office, BELSPO; KU Leuven","Work commissioned by VIL, the innovation platform for the logistics cluster in Flanders, supported by VLAIO (Egreen IWT 140002) and the Belgian Science Policy Office (BELSPO) in the Interuniversity Attraction Pole COMEX. Editorial consultation provided by Luke Connolly (KU Leuven).","Archetti C., Savelsbergh M., Speranza M.G., The vehicle routing problem with occasional drivers, Eur J Oper Res, 254, 2, pp. 472-480, (2016); Bektas T., Laporte G., The pollution-routing problem, Trans Res Part B Methodol, 45, 8, pp. 1232-1250, (2011); Campbell A.M., Savelsbergh M., Incentive schemes for attended home delivery services, Transp Sci, 40, 3, pp. 327-341, (2006); Christiaens J., Vanden Berghe G., A fresh ruin & recreate implementation for the capacitated vehicle routing problem, (2016); Croes G.A., A method for solving traveling-salesman problems, Oper Res, 6, 6, pp. 791-812, (1958); Dekker R., Bloemhof J., Mallidis I., Operations research for green logistics—an overview of aspects, issues, contributions and challenges, Eur J Oper Res, 219, 3, pp. 671-679, (2012); Demir E., Bektas T., Laporte G., An adaptive large neighborhood search heuristic for the pollution-routing problem, Eur J Oper Res, 223, 2, pp. 346-359, (2012); 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Schrimpf G., Schneider J., Stamm-Wilbrandt H., Dueck G., Record breaking optimization results using the ruin and recreate principle, J Comput Phys, 159, 2, pp. 139-171, (2000); Shao J., Yang H., Xing X., Yang L., E-commerce and traffic congestion: an economic and policy analysis, Transp Res Part B Methodol, 83, pp. 91-103, (2016); Tasan A.S., Gen M., A genetic algorithm based approach to vehicle routing problem with simultaneous pick-up and deliveries, Comput Ind Eng, 62, 3, pp. 755-761, (2012); Vidal T., Crainic T.G., Gendreau M., Lahrichi N., Rei W., A hybrid genetic algorithm for multidepot and periodic vehicle routing problems, Oper Res, 60, 3, pp. 611-624, (2012); Vidal T., Crainic T.G., Gendreau M., Prins C., A hybrid genetic algorithm with adaptive diversity management for a large class of vehicle routing problems with time-windows, Comput Oper Res, 40, 1, pp. 475-489, (2013)","S. Heshmati; KU Leuven, Department of Computer Science, CODeS & imec, Gent, Belgium; email: sam.heshmati@kuleuven.be",null,"Springer Verlag",{"$nulls":5},2.1924376E7,null,null,null,"English","EURO J. Transp. Logist.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85071639723"]
["Ulmer M.W.","Ulmer, Marlin W. (57147181500)",5.71471815E10,"Anticipation versus reactive reoptimization for dynamic vehicle routing with stochastic requests",2019.0,"Networks",73.0,3.0,null,277.0,291.0,14.0,16.0,"10.1002/net.21861","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85054682902&doi=10.1002%2fnet.21861&partnerID=40&md5=2a551e854537e06358fe5460500934e0","Carl-Friedrich-Gauß-Fakultät, Technische Universität Braunschweig, Braunschweig, Germany","Ulmer M.W., Carl-Friedrich-Gauß-Fakultät, Technische Universität Braunschweig, Braunschweig, Germany","Due to new business models and technological advances, dynamic vehicle routing is gaining increasing interest. Especially solving dynamic vehicle routing problems with stochastic customer requests becomes increasingly important, for example, in e-commerce and same-day delivery. Solving these problems is challenging, because it requires optimization along two dimensions. First, as a reaction to new customer requests, current routing plans need to be reoptimized. Second, potential future requests need to be anticipated in current decision making. Decisions need to be derived in real-time. The limited time often prohibits extensive optimization in both dimensions and the question arises how to utilize the limited calculation time effectively. In this paper, we analyze the merits of reactive route reoptimization and anticipation for a dynamic vehicle routing problem with stochastic requests. To this end, we compare an existing method from each dimension as well a policy allowing for a tunable combination of the two approaches. We show how the appropriate optimization combination is strongly connected to the degree of dynamism, the percentage of unknown requests. We also show that our combination does not provide significant benefit compared to the respectively best optimization dimension. © 2018 Wiley Periodicals, Inc.","anticipation; approximate dynamic programming; degree of dynamism; dynamic vehicle routing; mixed-integer programming; reoptimization; stochastic requests","Decision making; Integer programming; Motor transportation; Problem solving; Stochastic systems; Vehicle routing; Vehicles; anticipation; Approximate dynamic programming; degree of dynamism; Dynamic Vehicle Routing; Mixed integer programming; Reoptimization; stochastic requests; Dynamic programming",{"$nulls":6},"Arslan A.M., Agatz N., Kroon L., Zuidwijk R., Crowdsourced delivery a dynamic pickup and delivery problem with ad hoc drivers, Transport. Sci., (2018); Bent R.W., Van Hentenryck P., Scenario-based planning for partially dynamic vehicle routing with stochastic customers, Oper. 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Sci., 41, 3, pp. 319-331, (2007); Ulmer M.W., Approximate dynamic programming for dynamic vehicle routing, Operations Research/Computer Science Interfaces Series, (2017); Ulmer M.W., Goodson J.C., Mattfeld D.C., Hennig M., Offline-online approximate dynamic programming for dynamic vehicle routing with stochastic requests, Transport. Sci., 52, pp. 20-37, (2018); Ulmer M.W., Heilig L., Voss S., On the value and challenge of real-time information in dynamic dispatching of service vehicles, Bus. Inform. Syst. Eng., 59, 3, pp. 161-171, (2017); Ulmer M.W., Mattfeld D.C., Koster F., Budgeting time for dynamic vehicle routing with stochastic customer requests, Transport. Sci., 52, 1, pp. 20-37, (2018); Ulmer M.W., Soeffker N., Mattfeld D.C., Value function approximation for dynamic multi-period vehicle routing, Eur. J. Oper. Res., 269, pp. 883-899, (2018); Voccia S.A., Campbell A.M., Thomas B.W., The same-day delivery problem for online purchases, Transport. Sci., (2018); Zhang S., Ohlmann J.W., Thomas B.W., Dynamic orienteering on a network of queues, Transport. Sci., 52, 3, pp. 691-706, (2018)","M.W. Ulmer; Carl-Friedrich-Gauß-Fakultät, Technische Universität Braunschweig, Braunschweig, Germany; email: m.ulmer@tu-braunschweig.de",null,"Wiley-Liss Inc.",{"$nulls":5},283045.0,null,null,null,"English","Networks","Article","Final",null,"Scopus","2-s2.0-85054682902"]
["Zagurskiy O.N.; Titova L.L.","Zagurskiy, O.N. (56607287000); Titova, L.L. (57213966497)","56607287000; 57213966497","Problems and prospects of blockchain technology usage in supply chains",2019.0,"Journal of Automation and Information Sciences",51.0,11.0,null,63.0,74.0,11.0,10.0,"10.1615/JAutomatInfScien.v51.i11.60","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85082760323&doi=10.1615%2fJAutomatInfScien.v51.i11.60&partnerID=40&md5=a974fdf71994f3bc902094d031ac0871","National University of Life and Environmental Sciences of Ukraine, Kiev, Ukraine","Zagurskiy O.N., National University of Life and Environmental Sciences of Ukraine, Kiev, Ukraine; Titova L.L., National University of Life and Environmental Sciences of Ukraine, Kiev, Ukraine","Global supply chains more and more depend on implementation of modern information technologies which contribute to expenses decrease, improvement of processes quality and increase of mutual transparency. Transition history tracking possibility between a sender and a consumer throughout the whole supply chain is a key factor especially if there is a distrust problem between chain members. This article studied principles of blockchain practical application and distributed ledger construction in addendums of blockchain. The main attention is paid to analysis of integration increase in supply chains between business partners based on digital data and web-transferred funds. The ways of application of blockchain technology to increase sustainability of agricultural product supply chain are determined. The application of blockchain technology in supply chain of agricultural product will provide a close connection between financial, logistic and commercial participants of trade and economic transactions with an opportunity of payments and supplies unification. The conducted analysis showed that blockchain technology concentrated around tangible and financial assets commerce is potentially the most interesting for both transactions and management processes inside organizations and between them. Processes, strategies and practice of blockchain technology application in supply chain indicate its vast potential and wide opportunities for development and increase of organizations efficiency. Blockchain technology application can increase competitive advantages of companies and decrease a risk by increasing a reliable information about supply chain members especially when two entities perform such operation for the first time. © 2019 by Begell House Inc.","Blockchain; Digital economy; E-commerce; Internet technologies; Supply chain; Transactions","Agricultural products; Agricultural robots; Commerce; Competition; Electronic commerce; Supply chains; Competitive advantage; Digital economy; Economic transactions; Global supply chain; Internet technology; Modern information technologies; Technology application; Transactions; Blockchain",{"$nulls":6},"Shin L., Bank Destroyers, Forbes, 2, pp. 86-91, (2016); Maier R., Passiante G., Zhang S., Creating value in networks, International Journal of Innovation and Technology Management, 8, 3, pp. 357-371, (2011); Aizekson V., Innovators: How a group of hackers, geniuses and geeks made the digital revolution, Vydavnytstvo “Nash Format, (2017); Alm E., Colliander N., Deforche F., Digitizing Europe: Why Northern European Frontrunners Must Drive Digitization of the EU Economy, (2016); Hukkinen T., Mattila J., Ilomaki J., Seppala T., A blockchain applicationin energy, ETLA Reports No, 71, (2017); Grant P., An entire real estate deal takes place online, using cryptocurrency technology, The Wall Street Journal, 26, (2017); Swan M., Blockchain: Blueprint for A New Economy, (2015); Tapscott D., Digital Economy. 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Logist, 36, pp. 69-87, (2015); Chae B., Yen H.R., Sheu C., Information technology and supply chain collaboration: Moderating effects of existing relationships between partners, IEEE Trans. Eng. Manag., 52, pp. 440-448, (2005); Kersten W., Seiter M., von See B., Hackius N., Maurer T., Trends and strategies in logistics and supply chain management, Digital Transformation Opportunities, pp. 1-70, (2017); Kupriyanovskiy V.P., Dobrynin A.P., Sinyagov S.A., Namiot D.E., An integral model of transformation in digital economy — How to become digital leader, International Journal of Open Information Technologies, 5, 1, pp. 26-33, (2017); Kuprijanovskij V.P., Sinjagov S.A., Klimov A.A., Petrov A.V., Namiot D.E., Digital supply chains and blockchain-based technologies in a collaborative economy, International Journal of Open Information Technologies, 5, 8, pp. 80-95, (2017); Smith J., Blockfreight™ the Blockchain for Global Freight. Version: Public Release, (2016); Prjanikov M.M., Chugunov A.V., Blockchain as a communication basis for digital economy formation: Advantages and problems, International Journal of Open Information Technologies, 5, 6, pp. 49-55, (2017); Deep Shift — Technology tipping points and societal impact, World Economic Forum, (2015); Tapscott D., Tapscott A., The Blockchain Revolution: How the Technology behind Bitcoin Is Changing Money, Business, and the World, (2016); Blockchain disruption in transport are you decentralised yet?, Concept Paper, (2018); Szabo N., Smart Contracts, (1994); Szabo N., The Idea of Smart Contracts, (1997); Popper N., Lohr S., Blockchain: A better way to track pork chops, bonds, bad peanut butter?, The New York Times, 4, (2017); Groenfeldt T., IBM and Maersk Apply Blockchain to Container Shipping, (2017)",null,null,"Begell House Inc.",{"$nulls":5},1.0642315E7,null,null,null,"English","J Autom Inform Sci","Article","Final",null,"Scopus","2-s2.0-85082760323"]
["Wang F.; Wang F.; Ma X.; Liu J.","Wang, Fangxin (57201917282); Wang, Feng (36065073900); Ma, Xiaoqiang (36930770600); Liu, Jiangchuan (8969748600)","57201917282; 36065073900; 36930770600; 8969748600","Demystifying the Crowd Intelligence in Last Mile Parcel Delivery for Smart Cities",2019.0,"IEEE Network",33.0,2.0,8675168.0,23.0,29.0,6.0,46.0,"10.1109/MNET.2019.1800228","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85063786760&doi=10.1109%2fMNET.2019.1800228&partnerID=40&md5=48cb859e2449031200aabe583510f8d8","Simon Fraser University, School of Computing Science, Canada; University of Mississippi, Department of Computer and Information Science, United Kingdom; Huazhong University of Science and Technology, China","Wang F., Simon Fraser University, School of Computing Science, Canada; Wang F., University of Mississippi, Department of Computer and Information Science, United Kingdom; Ma X., Simon Fraser University, School of Computing Science, Canada, Huazhong University of Science and Technology, China; Liu J., Simon Fraser University, School of Computing Science, Canada","Recent years have witnessed an explosive growth of online shopping, which has posted unprecedented pressure on the logistics industry, especially the last mile parcel delivery. Existing solutions mostly rely on dedicated couriers, which suffer from high cost and low elasticity when dealing with a massive amount of local addresses. Advances in the Internet of Things, however, have enabled vehicle information to be readily accessible anytime anywhere, forming an Internet of Vehicles (IoV), which further enables intelligent vehicle scheduling and management. New opportunities therefore arise toward efficient and elastic last mile delivery for smart cities. In this article, we seek novel solutions to improve the last mile parcel delivery with crowd intelligence. We first review the existing and emerging solutions for last mile parcel delivery. We then discuss the advances of the ride-sharing- based delivery mechanism, identifying the unique opportunities and challenges therein. We further present Car4Pac, an IoV-enabled intelligent ride-sharing-based delivery system for smart cities, and demonstrate its superiority with real trace-driven evaluations. © 2019 IEEE.",null,"Scheduling; Smart city; Vehicles; Delivery mechanism; Delivery systems; Explosive growth; Logistics industry; Novel solutions; Online shopping; Parcel delivery; Ride-sharing; Targeted drug delivery",{"$nulls":4},"Canada NSERC; National Natural Science Foundation of China; National Science Foundation, NSF, (1822104); National Natural Science Foundation of China, NSFC, (61702204)","Funding text 1: This research is supported by a Canada NSERC Discovery Grant. Feng's work is partly supported by an NSF I/UCRC Grant (1822104). Xiaoqiang's work is partly supported by the National Natural Science Foundation of China under Grant 61702204. The corresponding author is Xiaoqiang Ma.; Funding text 2: This research is supported by a Canada NSERC Discovery Grant. Feng’s work is partly supported by an NSF I/UCRC Grant (1822104). Xiao-qiang’s work is partly supported by the National Natural Science Foundation of China under Grant 61702204. The corresponding author is Xiao-qiang Ma.","Aized T., Srai J.S., Hierarchical modelling of last mile logistic distribution system, Int'l. J. Advanced Manufacturing Technology, 70, 5-8, pp. 1053-1061, (2014); Joerss M., Et al., Parcel Delivery - The Future of the Last Mile, (2016); Lam A.Y., Leung Y.-W., Chu X., Autonomous-vehicle public transportation system: Scheduling and admission control, IEEE Trans. Intelligent Transportation Systems, (2016); Yu J., Lam A.Y., Autonomous vehicle logistic system: Joint routing and charging strategy, IEEE Trans. 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Intelligent Transportation Systems, 18, 6, pp. 1478-1496, (2017); Abdelhamid S., Hassanein H., Takahara G., Vehicle as a resource (VAAR), IEEE Network, 29, 1, pp. 12-17, (2015)",null,null,"Institute of Electrical and Electronics Engineers Inc.",{"$nulls":5},8908044.0,null,"IENEE",null,"English","IEEE Network","Article","Final",null,"Scopus","2-s2.0-85063786760"]
["de Mello Bandeira R.A.; Goes G.V.; Schmitz Gonçalves D.N.; D'Agosto M.D.A.; Oliveira C.M.D.","de Mello Bandeira, Renata Albergaria (25121365300); Goes, George Vasconcelos (57195265249); Schmitz Gonçalves, Daniel Neves (57146830800); D'Agosto, Márcio de Almeida (25121417100); Oliveira, Cíntia Machado de (57205338764)","25121365300; 57195265249; 57146830800; 25121417100; 57205338764","Electric vehicles in the last mile of urban freight transportation: A sustainability assessment of postal deliveries in Rio de Janeiro-Brazil",2019.0,"Transportation Research Part D: Transport and Environment",67.0,null,null,491.0,502.0,11.0,75.0,"10.1016/j.trd.2018.12.017","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85059623295&doi=10.1016%2fj.trd.2018.12.017&partnerID=40&md5=ce3f56f2e29d29f712c2f52624f6c3e9","Program of Transportation Engineering COPPE/UFRJ, Technology Center, Building H – Room 117, University City – Rio de Janeiro, 21949-900, Brazil; Military Institute of Engineering, Praça General Tibúrcio 80, Praia Vermelha, Rio de Janeiro, Brazil; Federal Center of Technological Education Celso Suckow da Fonseca, Rio de Janeiro, Brazil","de Mello Bandeira R.A., Program of Transportation Engineering COPPE/UFRJ, Technology Center, Building H – Room 117, University City – Rio de Janeiro, 21949-900, Brazil, Military Institute of Engineering, Praça General Tibúrcio 80, Praia Vermelha, Rio de Janeiro, Brazil; Goes G.V., Program of Transportation Engineering COPPE/UFRJ, Technology Center, Building H – Room 117, University City – Rio de Janeiro, 21949-900, Brazil; Schmitz Gonçalves D.N., Program of Transportation Engineering COPPE/UFRJ, Technology Center, Building H – Room 117, University City – Rio de Janeiro, 21949-900, Brazil; D'Agosto M.D.A., Program of Transportation Engineering COPPE/UFRJ, Technology Center, Building H – Room 117, University City – Rio de Janeiro, 21949-900, Brazil; Oliveira C.M.D., Program of Transportation Engineering COPPE/UFRJ, Technology Center, Building H – Room 117, University City – Rio de Janeiro, 21949-900, Brazil, Federal Center of Technological Education Celso Suckow da Fonseca, Rio de Janeiro, Brazil","The growth of urban population and the rise of e-commerce activities increase the complexity of the last-mile of parcel deliveries and its impacts to the environment and quality of life. Despite the relevance, emerging countries have difficult to establish and implement alternatives to the conventional scope of fossil-based operations. This paper proposes a method to assess alternative strategies for the last-mile of parcel deliveries, in terms of social, environmental, and economic impacts and presents an application to assess the distribution strategy of a postal company located in the city of Rio de Janeiro, Brazil. Moreover, we developed a systematic literature review to develop realistic alternatives to the baseline scenario, which operates with diesel propelled light duty vehicles. Literature points to the reduction of the dimensions of vehicles, as well as to the migration of the propulsion source to electric energy, as sustainable alternatives for last mile deliveries in urban areas. For that reason, we opted to evaluate the use of electric vehicles of smaller dimensions, tricycle and LDV, in the last mile of parcel deliveries, assessing two alternative scenarios: one with the use of electric LDV type BEV; and the other with electric tricycles. Results indicated that the use electric tricycle is a more feasible alternative regarding the economic, environmental and social aspects, demanding no public incentives. © 2019 Elsevier Ltd","Electric mobility; Last mile; Urban freight; Vehicles","Brazil; Rio de Janeiro [Brazil]; Rio de Janeiro [Rio de Janeiro (STT)]; Electric vehicles; Freight transportation; Population statistics; Social aspects; Sustainable development; Urban growth; Vehicles; Distribution strategies; Electric mobility; Feasible alternatives; Last mile; Light duty vehicles; Sustainability assessment; Systematic literature review; Urban freight; electric vehicle; freight transport; literature review; mobility; sustainability; transportation development; urban transport; Urban transportation",{"$nulls":4},"Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, CAPES; Conselho Nacional de Desenvolvimento Científico e Tecnológico, CNPq","The authors wish to thank CAPES and CNPq for financial support. 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["Zheng B.","Zheng, Bichen (55869030600)",5.58690306E10,"Financial default payment predictions using a hybrid of simulated annealing heuristics and extreme gradient boosting machines",2019.0,"International Journal of Internet Technology and Secured Transactions",9.0,4.0,null,404.0,425.0,21.0,3.0,"10.1504/IJITST.2019.102796","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85073194068&doi=10.1504%2fIJITST.2019.102796&partnerID=40&md5=ec3c7fa795ab113032625ae6c9744ba5","Department of Systems Science and Industrial Engineering, State University of New York at Binghamton, Vestal, NY, United States; OwnerIQ Inc., Boston, MA, United States","Zheng B., Department of Systems Science and Industrial Engineering, State University of New York at Binghamton, Vestal, NY, United States, OwnerIQ Inc., Boston, MA, United States","Online peer-to-peer (P2P) lending platforms face multiple challenges in today's e-commerce, but one of the most outstanding concerns evaluating loan risk based on borrowers' financial status and histories. Traditionally, financial experts assess borrowers' risk of default payments manually, but this process is tedious and time consuming, which are not widely applicable concerns for online P2P platforms. This paper proposes a hybrid of the simulated annealing and the extreme gradient boosting machine models in order to predict the likelihood of default payments based on users' finance histories. Based on the experimental results, the proposed model demonstrates its predictability with high recall scores. The proposed model not only out-performs over conventional algorithms including logistic regressions, support vector machines, random forests, and artificial neural networks, but it also provides an efficient method for optimising hyper-parameters in the machine learning algorithms. Through the utilisation of the proposed data-driven models, the necessity of tedious and potentially inaccurate human labour can be significantly reduced, and service level agreements (SLAs) can be further improved by time reduction made possible through the introduction of advanced data mining approaches. © 2019 Inderscience Enterprises Ltd.","Big data; Credit risk; Credit scoring; Data mining; Extreme gradient boosting machines; Simulated annealing; XGBoost",{"$nulls":7},"Benkedjouh T., Medjaher K., Zerhouni N., Rechak S., Health assessment and life prediction of cutting tools based on support vector regression, Journal of Intelligent Manufacturing, 26, 2, pp. 213-223, (2015); Campos R., Ruiz F.J., Agell N., Angulo C., Financial credit risk measurement prediction using innovative soft-computing techniques, International Conference on Computational Finance & Its Applications, (2004); Chen T., Guestrin C., XGBoost: A scalable tree boosting system, Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 785-794, (2016); 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Tsai M.C., Lin S.P., Cheng C.C., Lin Y.P., The consumer loan default predicting model - An application of DEA-DA and neural network, Expert Systems with Applications, 36, 9, pp. 11682-11690, (2009); Tsaur S.H., Chiu Y.C., Huang C.H., Determinants of guest loyalty to international tourist hotels - A neural network approach, Tourism Management, 23, 4, pp. 397-405, (2002); West D., Neural network credit scoring models, Computers & Operations Research, 27, 11, pp. 1131-1152, (2000); Yeh I.-L., Lien C., The comparisons of data mining techniques for the predictive accuracy of probability of default of credit card clients, Expert Systems with Applications, 36, 2, pp. 2473-2480, (2009); Zheng B., Yoon S.W., Lam S.S., Breast cancer diagnosis based on feature extraction using a hybrid of K-means and support vector machine algorithms, Expert Systems with Applications, 41, 4, pp. 1476-1482, (2014); Zieba M., Tomczak S.K., Tomczak J.M., Ensemble boosted trees with synthetic features generation in application to bankruptcy prediction, Expert Systems with Applications, 58, 1, pp. 93-101, (2016)","B. Zheng; Department of Systems Science and Industrial Engineering, State University of New York at Binghamton, Vestal, United States; email: bzheng6@binghamton.edu",null,"Inderscience Publishers",{"$nulls":5},"1748569X",null,null,null,"English","Int. J. Internet Technol. Secured Trans.","Article","Final",null,"Scopus","2-s2.0-85073194068"]
["Gatta V.; Marcucci E.; Nigro M.; Serafini S.","Gatta, Valerio (35109007100); Marcucci, Edoardo (6602255083); Nigro, Marialisa (36158289300); Serafini, Simone (57204010144)","35109007100; 6602255083; 36158289300; 57204010144","Sustainable urban freight transport adopting public transport-based crowdshipping for B2C deliveries",2019.0,"European Transport Research Review",11.0,1.0,13.0,null,null,null,90.0,"10.1186/s12544-019-0352-x","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85061822868&doi=10.1186%2fs12544-019-0352-x&partnerID=40&md5=3d6bef7fafbe72f82b89ab6964edff03","Department of Political Science, Roma Tre University, Via Gabriello Chiabrera 199, Rome, 00145, Italy; Department of Logistics, Molde University College, PO.Box 2110, Molde, 6402, Norway; Department of Engineering, Roma Tre University, Via Vito Volterra 62, Rome, 00146, Italy","Gatta V., Department of Political Science, Roma Tre University, Via Gabriello Chiabrera 199, Rome, 00145, Italy; Marcucci E., Department of Logistics, Molde University College, PO.Box 2110, Molde, 6402, Norway; Nigro M., Department of Engineering, Roma Tre University, Via Vito Volterra 62, Rome, 00146, Italy; Serafini S., Department of Engineering, Roma Tre University, Via Vito Volterra 62, Rome, 00146, Italy","Cities crave innovative logistics solutions dealing with the requirements of the ‘on demand economy’. The paper estimates the willingness to act as a crowdshipper (supply) and to buy a crowdshipping service (demand) to get goods delivered/picked-up in the last mile B2C e-commerce situation. Specifically, it innovates by considering an environmental-friendly crowdshipping based on the use of the mass transit network of the city where parcels customers/crowdshippers pick-up/drop-off goods in automated parcel lockers located either inside the transit stations or in the surroundings. This issue is very important since “standard” crowdshipping is usually not able to reduce congestion and polluting emissions due to the dedicated trips performed using private motorized vehicles. The paper rests on an extensive stated preference survey. The hypothetical scenarios used to acquire both demand (customers’) and supply (crowdshippers’) preferences make use of the most relevant attributes emerging from a preliminary investigation performed in the study context. The investigation is performed in the city of Rome and the metro is the transit system considered. The results are useful in understanding and quantifying the potential of this freight transport strategy for e-commerce in an urban context and in providing local policy makers with a good knowledge base for its future development. © 2019, The Author(s).","City logistics; Crowdshipping; Discrete choice models; On demand economy; Stated preference; Urban freight transport","Electronic commerce; Knowledge based systems; Light rail transit; Traffic congestion; Urban planning; Urban transportation; City logistics; Crowdshipping; Discrete choice models; On demands; Stated preferences; Urban freight transport; Freight transportation",{"$nulls":4},"BNC-Foundation, (ICROWD4FR8); EU H2020; Università degli Studi Roma Tre; H2020 Transport, TRANSPORT, (635898)","Funding text 1: Not applicable This work was supported by the EU H2020 CITYLAB project (grant agreement no. 635898), by the BNC-Foundation ICROWD4FR8 project, and by the Roma Tre University SHARELAB project. Not applicable; Funding text 2: This work was supported by the EU H2020 CITYLAB project (grant agreement no. 635898), by the BNC-Foundation ICROWD4FR8 project, and by the Roma Tre University SHARELAB project.","Allen J., Piecyk M., Piotrowska M., McLeod F., Cherrett T., Nguyen T., Bektas T., Bates O., Friday A., Wise S., Austwick M., Understanding the impact of e-commerce on last-mile light goods vehicle activity in urban areas: The case of London, Transportation Research Part D: Transport and Environment, (2017); Archetti C., Savelsbergh M., Speranza M.G., The vehicle routing problem with occasional drivers, European Journal of Operational Research, 254, 2016, pp. 472-480, (2016); Bateman I.J., Carson R.T., Day B., Hanemann W.M., Hanley N., Hett T., Lee M.J., Loomes G., Mourato S., Ozdemiroglu E., Pearce D.W., Economic valuation with stated preference techniques: A manual, (2002); Behrend B., Meisel F., The integration of item-sharing and crowdshipping: Can collaborative consumption b e pushe d by delivering through the crowd?, Transportation Research Part B, 111, 2018, pp. 227-243, (2018); Luci e ombre del commercio online in Italia, Identikit Del Consumatore Online E Delle Imprese in Europa Rapporto sull’e-commerce 2017, (2017); Bensinger G., Amazon's next delivery drone: You, The Wall Street Journal, (2015); Bierlaire M., BIOGEME: A free package for the estimation of discrete choice models. In: Swiss Transport Research Conference, (2003); Briffaz M., Darvey C., Crowd-shipping in Geneva exploratory and descriptive study of Crowd-shipping, Master Thesis. 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Kwak N., Radler B., A comparison between mail and web surveys: Response pattern, respondent profile, and data quality, Journal of official statistics, 18, pp. 257-273, (2002); Le Pira M., Marcucci E., Gatta V., Ignaccolo M., Inturri G., Pluchino A., Towards a decision-support procedure to foster stakeholder involvement and acceptability of urban freight transport policies, European Transport Research Review, 9, 4, (2017); Le Pira M., Marcucci E., Gatta V., Inturri G., Ignaccolo M., Pluchino A., Integrating discrete choice models and agent-based models for ex-ante evaluation of stakeholder policy acceptability in urban freight transport, Research in Transportation Economics, 64, pp. 13-25, (2017); Lozzi G., Gatta V., Marcucci E., European urban freight transport policies and research funding: Are priorities and horizon 2020 calls aligned?, Region, 5, 1, pp. 53-71, (2018); Mak H., Peer-To-Peer Crowdshipping as an Omnichannel Retail Strategy, (2018); Marcucci E., Gatta V., Dissecting preference heterogeneity in consumer stated choices, Transportation Research Part E-Logistics and Transportation Review, 48, pp. 331-339, (2012); Marcucci E., Gatta V., Investigating the potential for off-hour deliveries in the city of Rome: Retailers’ perceptions and stated reactions, Transportation Research Part A: Policy and Practice, 102, pp. 142-156, (2017); Marcucci E., Gatta V., Le Pira M., Gamification design to foster stakeholder engagement and behavior change: An application to urban freight transport, Transportation Research Part A: Policy and Practice, 118, pp. 119-132, (2018); Marcucci E., Gatta V., Le Pira M., Carrocci C.S., Pieralice E., Connected shared mobility for passengers and freight: Investigating the potential of crowdshipping in urban areas, 5Th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2017 - Proceedings, pp. 839-843, (2017); Marcucci E., Gatta V., Marciani M., Cossu P., Measuring the effects of an urban freight policy package defined via a collaborative governance model, Research in Transportation Economics, 65, pp. 3-9, (2017); Marcucci E., Gatta V., Pieralice E., Pira M., Carrocci C.S., Analisi del crowdshipping come soluzione innovativa per promuovere la crescita e la sostenibilità delle aree urbane, Trasporti E Cultura, 47, (2017); 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Internet Conf., pp. 1-19, (2014); Savelsberghvan Woensel M.T., City Logistics: Challenges and Opportunities, (2016); Serafini S., Nigro M., Gatta V., Marcucci E., Sustainable crowdshipping using public transport: A case study evaluation in Rome, Transportation Research Procedia, 30, pp. 101-110, (2018); Slabinac M., Innovative solutions for a “last-mile” delivery – A European experience,                                   International Scientific Conference Business Logistics in Modern Management                             , pp. 111-129, (2015); La Pianificazione Dei Trasporti nell’area Metropolitana Di Roma, (2016); Taniguchi E., Thompson R.G., Yamada T., New opportunities and challenges for city logistics, Transportation Research Procedia, 12, 2016, pp. 5-13, (2016); Valeri E., Gatta V., Teobaldelli D., Polidori P., Barratt B., Fuzzi S., Kazepov Y., Sergi V., Williams M., Maione M., Modelling individual preferences for environmental policy drivers: Empirical evidence of Italian lifestyle changes using a latent class approach, Environmental Science & Policy, 65, pp. 65-74, (2016); Yildiz B., Savelsbergh M., Service and Capacity Planning in Crowd-Sourced Delivery, Transportation Research Part C: Emerging Technologies, 100, pp. 177-199, (2019); Zwerina K., The importance of utility balance and efficient choice designs, Journal of Marketing Research, 33, August, pp. 307-317, (1996)","V. Gatta; Department of Political Science, Roma Tre University, Rome, Via Gabriello Chiabrera 199, 00145, Italy; email: valerio.gatta@uniroma3.it",null,"Springer Verlag",{"$nulls":5},1.8670717E7,null,null,null,"English","Eur. Transp. Res. Rev.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85061822868"]
["Riley J.M.; Klein R.","Riley, Jason M. (57191486218); Klein, Richard (56583233600)","57191486218; 56583233600","How logistics capabilities offered by retailers influence millennials’ online purchasing attitudes and intentions",2019.0,"Young Consumers",22.0,1.0,null,131.0,151.0,20.0,15.0,"10.1108/YC-12-2018-0889","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85074012220&doi=10.1108%2fYC-12-2018-0889&partnerID=40&md5=3c347266a7bf6aa4e21a7b3030f178e5","Department of Management, Marketing and Information Systems, Sam Houston State University, Huntsville, TX, United States","Riley J.M., Department of Management, Marketing and Information Systems, Sam Houston State University, Huntsville, TX, United States; Klein R., Department of Management, Marketing and Information Systems, Sam Houston State University, Huntsville, TX, United States","Purpose: The purpose of this study is to understand consumers’ use of online retail channels. This study examines how tracking capabilities, delivery speed, trust, logistics carriers’ reputation, people important to the consumer and online reviews influence Millennials’ online purchasing attitudes and intentions. Design/methodology/approach: A survey was administered to 321 Millennials. Subsequently, it was used to test both direct and indirect hypotheses using structural equation modeling techniques. Findings: The study determined that tracking capabilities, trust, people important to the consumer and online reviews directly influence online purchase attitude and by extension intention formation. The results also revealed that logistics carrier reputation moderates the trust to online purchase attitude linkage. Research limitations/implications: This work improves the explanatory power of the theory of reasoned action by linking logistics factors to online shopping behavior. Further, it provides insight into the moderating influence of logistics carriers’ reputation. Practical implications: For retailers, the results provide information on how to better develop ecommerce service offerings. By providing information about logistics services and capabilities during the ecommerce transaction, retailers can improve the chance that consumers will complete online purchases. Originality/value: This research fills a gap in the literature regarding how to influence millennial consumers. Moreover, findings strengthen the understanding of online-purchasing attitudes and intentions formation, important to retailers developing new online shopping platforms and technologies. © 2019, Emerald Publishing Limited.","E-commerce; Millennials; Online reviews; Purchase intention; Theory of reasoned action",{"$nulls":7},"Acheampong P., Zhiwen L., Abubakar R., Antwi H., Akomeah M., Stimulants of online shopping behaviour among Chinese millennials in China, International Journal of Academic Research in Business & Social Sciences, 6, 5, pp. 331-349, (2016); Aiken L.S., West S.G., Reno R.R., Multiple Regression: Testing and Interpreting Interactions, (1991); Ajzen I., Nature and operation of attitudes, Annual Review of Psychology, 52, 1, pp. 27-58, (2001); Al-Jabari M.A., Othman S.N., Mat N.K., Actual online shopping behavior among Jordanian customers, American Journal of Economics, pp. 125-129, (2012); Order with prime FREE same-day delivery, (2017); Armstrong J.S., Overton T.S., Estimating nonresponse bias in mail surveys, Journal of Marketing Research, 14, 3, pp. 396-402, (1977); 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Riley; Department of Management, Marketing and Information Systems, Sam Houston State University, Huntsville, United States; email: jmr099@shsu.edu",null,"Emerald Group Holdings Ltd.",{"$nulls":5},1.7473616E7,null,null,null,"English","Young Consum.","Article","Final",null,"Scopus","2-s2.0-85074012220"]
["Micale R.; La Fata C.M.; La Scalia G.","Micale, R. (36548895700); La Fata, C.M. (55067526900); La Scalia, G. (24399361400)","36548895700; 55067526900; 24399361400","A combined interval-valued ELECTRE TRI and TOPSIS approach for solving the storage location assignment problem",2019.0,"Computers and Industrial Engineering",135.0,null,null,199.0,210.0,11.0,39.0,"10.1016/j.cie.2019.06.011","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85067030491&doi=10.1016%2fj.cie.2019.06.011&partnerID=40&md5=56bb24c36abc920cfcb7728ac70e56e6","Department of Engineering, Università degli Studi di Palermo, Viale delle Scienze Ed. 8, Palermo, 90128, Italy","Micale R., Department of Engineering, Università degli Studi di Palermo, Viale delle Scienze Ed. 8, Palermo, 90128, Italy; La Fata C.M., Department of Engineering, Università degli Studi di Palermo, Viale delle Scienze Ed. 8, Palermo, 90128, Italy; La Scalia G., Department of Engineering, Università degli Studi di Palermo, Viale delle Scienze Ed. 8, Palermo, 90128, Italy","Efficiency and effectiveness of logistic activities, in general, and of distribution networks, in particular, are largely influenced by the way warehouses operate as nodes of these networks. In recent years, warehouse management has undergone major changes due to the increase of e-commerce and competition in time-reduction. Despite that, logistic costs of warehouse processes (e.g. receiving, storage, order picking and shipping, etc.) are still often high. Referring to the order picking process, related activities may be optimized by a proper assignment of products to storage locations. In the literature, this problem is known as Storage Location Assignment Problem (SLAP). Due to the multi-criteria nature of SLAP, a combined ELECTRE TRI and TOPSIS based approach under an uncertain environment is designed in the present paper. Aiming at properly dealing with the uncertainty of the decision process, an interval extension of both ELECTRE TRI and TOPSIS is proposed. Therefore, ELECTRE TRI is firstly used to assign products to shelf levels whereas TOPSIS is afterwards applied to determine their storage locations within every level rather than using a random assignment policy. The whole methodology has been designed in cooperation with a Sicilian company that provides logistic services all over the Italian territory. © 2019 Elsevier Ltd","Interval-valued ELECTRE TRI; Interval-valued TOPSIS; Storage location assignment problem; Warehouse management","Combinatorial optimization; Industrial management; Location; ELECTRE TRI; Interval extension; Interval-valued; Logistic services; Random assignment; Storage location assignments; Uncertain environments; Warehouse management; Warehouses",{"$nulls":6},"Accorsi R., Manzini R., Bortolini M., A hierarchical procedure for storage allocation and assignment within an order-picking system. 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The A.N., Mousseau V., Using assignment examples to infer category limits for the ELECTRE TRI method, Journal of Multi-Criteria Decision Analysis, 11, 1, pp. 29-43, (2002); Xiao J., Zheng L., A correlated storage location assignment problem in a single-block-multi-aisles warehouse considering BOM information, International Journal of Production Research, 48, 5, pp. 1321-1338, (2010); Zardari N.H., Ahmed K., Shirazi S.M., Yusop Z., (2015)","C.M. La Fata; Department of Engineering, Università degli Studi di Palermo, Palermo, Viale delle Scienze Ed. 8, 90128, Italy; email: concettamanuela.lafata@unipa.it",null,"Elsevier Ltd",{"$nulls":5},3608352.0,null,"CINDD",null,"English","Comput Ind Eng","Article","Final",null,"Scopus","2-s2.0-85067030491"]
["Leyerer M.; Sonneberg M.-O.; Heumann M.; Breitner M.H.","Leyerer, Max (57202495351); Sonneberg, Marc-Oliver (57188998603); Heumann, Maximilian (57209069430); Breitner, Michael H. (6602910157)","57202495351; 57188998603; 57209069430; 6602910157","Decision support for sustainable and resilience-oriented urban parcel delivery",2019.0,"EURO Journal on Decision Processes",7.0,"2024-04-03",null,267.0,300.0,33.0,15.0,"10.1007/s40070-019-00105-5","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85077108862&doi=10.1007%2fs40070-019-00105-5&partnerID=40&md5=fcdf826a842afb71520bad73bf6eda1f","Information Systems Institute, Leibniz Universität Hannover, Königsworther Platz 1, Hannover, 30167, Germany","Leyerer M., Information Systems Institute, Leibniz Universität Hannover, Königsworther Platz 1, Hannover, 30167, Germany; Sonneberg M.-O., Information Systems Institute, Leibniz Universität Hannover, Königsworther Platz 1, Hannover, 30167, Germany; Heumann M., Information Systems Institute, Leibniz Universität Hannover, Königsworther Platz 1, Hannover, 30167, Germany; Breitner M.H., Information Systems Institute, Leibniz Universität Hannover, Königsworther Platz 1, Hannover, 30167, Germany","The worldwide trend of urbanization, the rising needs of individuals, and the continuous growth of e-commerce lead to increasing urban delivery activities, which are a substantial driver of traffic and pollution in cities. Due to rising public pressure, emission-reducing measures are increasingly likely to be introduced. Such measures can cover diesel bans or even entire car-free zones, causing drastic effects on delivery networks in urban areas. As an option to reduce the risk of a regulation-induced shock, we present a resilience-oriented network and fleet optimization. We propose an innovative parcel delivery concept for last mile delivery (LMD) operations and develop an optimization model to support tactical planning decisions. Our model minimizes overall operating costs by determining optimal locations for micro depots and it allocates transport vehicles to them. An adjustable CO2-threshold and external costs are included to consider potential regulatory restrictions by city authorities. We implement our model into a decision support system (DSS) that allows analyzing and comparing different scenarios. We provide a computational study by evaluating and discussing our DSS with an example of a mid-sized German city. Our results and findings demonstrate the trade-off between cost and emission minimization by quantifying the impacts of various fleet compositions. The proposed logistics concept represents an option to achieve environmentally friendly, cost-efficient, and resilient LMD of parcels. © EURO-The Association of European Operational Research Societies and Springer-Verlag GmbH Germany, part of Springer Nature 2019.","City logistics; Decision support system; Environmental sustainability; Last mile delivery; Resilience",{"$nulls":7},"Albareda-Sambola M., Fernandez E., Laporte G., Heuristic and lower bound for a stochastic location-routing problem, Eur J Oper Res, 179, pp. 940-955, (2007); Arnold F., Cardenas I., Sorensen K., Dewulf W., Simulation of B2C e-commerce distribution in Antwerp using cargo bikes and delivery points, Eur Trans Res Rev, 10, (2018); Awasthi A., Chauhan S.S., Goyal S.K., A multi-criteria decision making approach for location planning for urban distribution centers under uncertainty, Math Comput Model, 53, pp. 98-109, (2011); Barcelo J., Grzybowska H., Orozco J.A., City logistics, Handbook of Heuristics, pp. 887-930, (2018); Barone V., Crocco F., Mongelli D.W.E., Models of choice between shopping and e-shopping, Appl Mech Mater, 442, pp. 607-616, (2014); Baykasoglu A., Subulan K., Tasan A.S., Dudakli N., A review of fleet planning problems in single and multimodal transportation systems, Transportmetrica A, 15, 2, pp. 631-697, (2019); Behrends B., Lindholm M., Woxenius J., The impact of urban freight transport: A definition of sustainability from an actor’s perspective, Transp Plan Technol, 31, 6, pp. 693-713, (2008); Bielli M., Bielli A., Rossi R., Trends in models and algorithms for fleet management, Proc Soc Behav Sci, 20, pp. 4-18, (2011); Boccia M., Crainic T.G., Sforza A., Sterle C., Multi-commodity location-routing: Flow intercepting formulation and branch-and-cut algorithm, Comput Oper Res, 89, pp. 94-112, (2018); Bouhana A., Chabchoub H., Abed M., Fekih A., A multi-criteria decision making approach based on fuzzy theory and fuzzy preference relations for urban distribution centers’ location selection under uncertain environments, ICALT’2013, pp. 556-561, (2013); Castrellon-Torres J.P., Chaparro J.S.T., Barrera N.E.M., Acosta J.H.T., Jaimes W.A., Information technology in city logistics: A decision support system for off-hour delivery programs, Exploring Intelligent Decision Support Systems, pp. 221-238, (2018); Catturazza D., Absi N., Feillet D., Gonzalez-Feliu J., Vehicle routing problems for city logistics, Eur J Transp Log, 6, 1, pp. 51-79, (2017); Cepolina E.M., Farina A., Optimization of the FURBOT urban freight transport scheme, Transp Res Proc, 5, pp. 119-131, (2015); Chan Y., Carter W.B., Burnes M.D., A multiple-depot, multiple-vehicle, location-routing problem with stochastically processed demands, Comput Oper Res, 28, pp. 803-826, (2001); Cirovic G., Pamucar D., Bozanic D., Green logistic vehicle routing problem: Routing light delivery vehicles in urban areas using a neuro-fuzzy model, Expert Syst Appl, 41, 9, pp. 4245-4258, (2014); Car Free City Life in Oslo, (2019); Crainic T.G., Ricciardi N., Storchi G., Advanced freight transportation systems for congested urban areas, Transp Res Part C, 12, pp. 119-137, (2004); Cutter S.L., Ahearn J.A., Amadei B., Crawford P., Eide E.A., Galloway G.E., Goodchild M.F., Kunreuther H.C., Li-Vollmer M., Schoch-Spana M., Scrimshaw S.C., Stanley E.M., Whitney G., Zoback M.L., Disaster resilience: A national imperative, Environ Sci Policy Sustain Dev, 55, 2, pp. 25-29, (2013); Dantzig G.B., Ramser J.H., The truck dispatching problem, Manag Sci, 6, 1, pp. 80-91, (1959); de Oliveira L.M., Morganti E., Dablanc L., de Oliveira R.L.M., Analysis of the potential demand of automated delivery stations for e-commerce deliveries in Belo Horizonte, Brazil, Res Transp Econ, 65, pp. 34-43, (2017); Demir E., Bektas T., Laporte G., The bi-objective pollution-routing problem, Eur J Oper Res, 232, pp. 464-478, (2014); Deutsche Post A.G., Locations: Packstations and Paketboxes in Hannover., (2019); DHL Expands Green Urban Delivery with City Hub for Cargo Bicycles, (2017); Diabat A., Simchi-Levi D., A carbon-capped supply chain network problem, Proceeding of 2009 IEEE International Conference on Industrial Engineering and Engineering Management, pp. 523-527, (2009); Diaz-Madronero M., Peidro D., Mula J., A review of tactical optimization models for integrated production and transport routing planning decisions, Comput Ind Eng, 88, pp. 518-535, (2015); Digiesi S., Fanti M.P., Mummolo G., Silvestri B., Externalities reduction strategies in last mile logistics: A review, Proceeding of 2017 IEEE International Conference on Service Operations and Logistics, and Informatics, pp. 248-253, (2017); Drexl M., Rich vehicle routing in theory and practice, Logist Res, 5, 1-2, pp. 47-63, (2012); Ehrler V.C., Hebes P., Electromobility for city logistics—the solution to urban transport collaps? 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Leyerer; Information Systems Institute, Leibniz Universität Hannover, Hannover, Königsworther Platz 1, 30167, Germany; email: leyerer@iwi.uni-hannover.de",null,"Springer Science and Business Media Deutschland GmbH",{"$nulls":5},2.1939438E7,null,null,null,"English","EURO J.  Decis. Process.","Article","Final",null,"Scopus","2-s2.0-85077108862"]
["Alicia E.; Dubois T.D.","Alicia, E. (58147126300); Dubois, Thomas David (14919293600)","58147126300; 14919293600","China Eats—Innovation, E-Commerce and Food Safety at the Hangzhou Food Forum",2019.0,"Asia-Pacific Journal: Japan Focus",17.0,11.0,5286.0,null,null,null,0.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85150380119&partnerID=40&md5=d665d0a66eb25f5ce32e2da957f81020","Hewlett-Packard, Beijing, China; Fudan University Development Institute (FDDI), China","Alicia E., Hewlett-Packard, Beijing, China; Dubois T.D., Fudan University Development Institute (FDDI), China","Since 2000, the driving force behind China’s booming food industries has shifted from state planning to consumer demand. This shift has powered the growing importance of food branding, as consumers rely increasingly on known brands in the search for safe and wholesome food. While earlier eras of food branding strongly favored multinationals like Coca Cola and Nestlé, Chinese brands appear to be gradually regaining the trust of consumers, who increasingly rely on online ecosystems that seamlessly combine ecommerce, e-payment and home delivery into a self-contained purchasing environment. The 2019 Food and Beverage Innovation Forum suggests that future trends may include increasing reliance on data informatics, a domestic shift to focus on free spending GenZ consumers, and branded export of China’s unique strength in logistics. © 2019, Asia-Pacific Journal, Inc.. All rights reserved.","branding; China; consumption; food industry; multinationals",{"$nulls":7},"(2015); Zhang Qian Forrest, Donaldson John Andrew, The Rise of Agrarian Capitalism with Chinese Characteristics: Agricultural Modernization, Agribusiness and Collective Land Rights, The China Journal, 60, pp. 25-47, (2008); China Statistical Yearbook 2013: 11-2 Per Capita Annual Income and Engel’s Coefficient of Urban and Rural Households; 11-8 Per Capita Annual Purchases of Major Commodities of Urban Households. The drop in fresh vegetable consumption may derive from rising consumption of cooked meals, or decreased consumption of low value vegetables such as cabbage, (2013); DuBois Thomas David, Borden and Nestlé in East Asia, 1870-1929: Branding and retail strategy in the condensed milk trade, forthcoming in Business History; da Silva Lopes Teresa, Global Brands: The Growth of Multinationals in the Alcoholic Drinks Industry (New York: Cambridge University Press, 2007). Jones, G. (1994). Brands and Marketing, 52, 1, pp. 100-119; Consumerism Without Capitalism: Consumption and Brand Names in Late Imperial China, The Social Economy of Consumption: Monographs in Economic Anthropology, 6, pp. 253-279, (1989); Kirby William C., China Unincorporated: Company Law and Business Enterprise in Twentieth-Century China, The Journal of Asian Studies, 54, 1, pp. 43-63, (1995); Mercer John, A mark of distinction: Branding and trade mark law in the UK from the 1860s, Business History, 52, 1, pp. 17-42, (2010); Kazuko Furuta K., Imitation, Counterfeiting, and the Market in Early Twentieth Century Japan and China: Intra-Asian Trade in Modern Small Sundry Goods, Imitation, Counterfeiting and the Quality of Goods in Modern Asian History, (2017); Kim Chung Koo, Chung Jay Young, Brand popularity, country image and market share: An empirical study, Journal of International Business Studies, 28, pp. 361-386, (1997); Xiu Changbai, Klein K.K., Melamine in milk products in China: Examining the factors that led to deliberate use of the contaminant?, Food Policy, 35, pp. 463-470, (2010); Collantes Fernando, Food chains and the retailing revolution: supermarkets, dairy processors and consumers in Spain (1960 to the present), Business History, 58, 7, pp. 1055-1076, (2016); List of 139 organic farms available here",null,null,"Asia-Pacific Journal, Inc.",{"$nulls":5},1.557466E7,null,null,null,"English","Asia-Pacific J. Japan Focus","Article","Final",null,"Scopus","2-s2.0-85150380119"]
["Yao Y.; Zhu X.; Dong H.; Wu S.; Wu H.; Carol Tong L.; Zhou X.","Yao, Yu (57201189174); Zhu, Xiaoning (8051528100); Dong, Hongyu (57211025109); Wu, Shengnan (57211021028); Wu, Hailong (57211022984); Carol Tong, Lu (57211025397); Zhou, Xuesong (8246091000)","57201189174; 8051528100; 57211025109; 57211021028; 57211022984; 57211025397; 8246091000","ADMM-based problem decomposition scheme for vehicle routing problem with time windows",2019.0,"Transportation Research Part B: Methodological",129.0,null,null,156.0,174.0,18.0,66.0,"10.1016/j.trb.2019.09.009","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85072292117&doi=10.1016%2fj.trb.2019.09.009&partnerID=40&md5=e2fbdacdeca6cae85f0c926915b7ea14","School of Traffic and Transportation, Beijing Jiaotong University, Beijing, 100044, China; Logistics R&D Department, Beijing Jingdong Zhenshi Information Technology Co., Ltd, Beijing, 100176, China; Research Institute of Frontier Science, National Engineering Laboratory for Comprehensive Transportation Big Data Application Technology, Beihang University, Beijing, 100091, China; School of Sustainable Engineering and the Built Environment, Arizona State University, Tempe, 85281, AZ, United States","Yao Y., School of Traffic and Transportation, Beijing Jiaotong University, Beijing, 100044, China; Zhu X., School of Traffic and Transportation, Beijing Jiaotong University, Beijing, 100044, China; Dong H., Logistics R&D Department, Beijing Jingdong Zhenshi Information Technology Co., Ltd, Beijing, 100176, China; Wu S., Logistics R&D Department, Beijing Jingdong Zhenshi Information Technology Co., Ltd, Beijing, 100176, China; Wu H., Logistics R&D Department, Beijing Jingdong Zhenshi Information Technology Co., Ltd, Beijing, 100176, China; Carol Tong L., Research Institute of Frontier Science, National Engineering Laboratory for Comprehensive Transportation Big Data Application Technology, Beihang University, Beijing, 100091, China; Zhou X., School of Sustainable Engineering and the Built Environment, Arizona State University, Tempe, 85281, AZ, United States","Emerging urban logistics applications need to address various challenges, including complex traffic conditions and time-sensitive requirements. In this study, in the context of urban logistics, we consider a vehicle routing problem with time-dependent travel times and time windows (VRPTW), and the goal is to minimize the total generalized costs including the transportation, waiting time, and fixed costs associated with each vehicle. We adopt a high-dimensional space–time network flow model to formulate an underlying vehicle routing problem (VRP) with a rich set of criteria and constraints. A difficult issue, when solving VRPs, is how to iteratively improve both the primal and dual solution quality in general and how to break the symmetry generated by many identical solutions, particularly with homogeneous vehicles. Along this line, many coupling constraints, such as the consensus constraints across different agents or decision makers, need to be carefully addressed to find high-quality optimal or close-to-optimal solutions under medium- or large-scale instances. Currently, the alternating direction method of multipliers (ADMM) is widely used in the field of convex optimization, as an integration of the augmented Lagrangian relaxation and block coordinate descent methods, for machine learning and large-scale continuous systems optimization and control. In this work, we introduce the use of ADMM to solve the multi-VRP, which is a special case of integer linear programming, and demonstrate a manner to reduce the quadratic penalty terms used in ADMM into simple linear functions. In a broader context, a computationally reliable decomposition framework is developed to iteratively improve both the primal and dual solution quality. Essentially, the least-cost path subproblem or other similar subproblems involving binary decisions can be embedded into a sequential solution scheme with an output of both lower bound estimates and upper bound feasible solutions. We examine the performance of the proposed approach using classical Solomon VRP benchmark instances. We also evaluate our approach on a real-world instance based on a problem-solving competition by Jingdong Logistics, a major E-commerce company. © 2019 Elsevier Ltd","Alternating direction method of multipliers; Problem decomposition; Urban logistics; Vehicle routing problem with time windows","Benchmarking; Constrained optimization; Convex optimization; Cost benefit analysis; Decision making; Integer programming; Iterative methods; Problem solving; Travel time; Urban transportation; Vehicles; Alternating direction method of multipliers; Augmented Lagrangian relaxation; Block coordinate descents; Integer Linear Programming; Problem decomposition; Urban logistics; Vehicle routing problem with time windows; Vehicle Routing Problems; benchmarking; cost analysis; decision making; decomposition analysis; transportation planning; travel behavior; travel time; urban transport; Vehicle routing",{"$nulls":4},"National Science Foundation, NSF, (1663657, CMMI 1538105, CMMI 1663657); National Natural Science Foundation of China, NSFC, (71801006); National Key Research and Development Program of China, NKRDPC, (2018YFB1201403)","We thank Prof. Natashia Boland and Prof. Martin Savelsbergh at the Georgia Institute of Technology for their valuable comments. The first two authors of this paper are supported by the National Key R&D Program of China (2018YFB1201403). The second-to-last author is supported by National Natural Science Foundation of China (No. 71801006 ). The last author is partially funded by the National Science Foundation , United States, under the NSF Grant No. CMMI 1538105 , “Collaborative Research: Improving Spatial Observability of Dynamic Traffic Systems through Active Mobile Sensor Networks and Crowdsourced Data” and the NSF Grant No. CMMI 1663657, “Real-time Management of Large Fleets of Self-Driving Vehicles Using Virtual Cyber Tracks”. ","Altinkemer K., Gavish B., Parallel savings based heuristics for the delivery problem, Oper. Res., 39, 3, pp. 456-469, (1991); Barnhart C., Johnson E.L., Nemhauser G.L., Savelsbergh M.W., Vance P.H., Branch-and-price: column generation for solving huge integer programs, Oper. 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Dong; Logistics R&D Department, Beijing Jingdong Zhenshi Information Technology Co., Ltd, Beijing, 100176, China; email: donghongyu@jd.com",null,"Elsevier Ltd",{"$nulls":5},1912615.0,null,null,null,"English","Transp. Res. Part B Methodol.","Article","Final",null,"Scopus","2-s2.0-85072292117"]
["Nascimento D.C.; Barbosa B.; Perez A.M.; Caires D.O.; Hirama E.; Ramos P.L.; Louzada F.","Nascimento, Diego C. (57201673097); Barbosa, Bruno (57214576601); Perez, André M. (57211945672); Caires, Daniel O. (57211950624); Hirama, Edgar (57211944556); Ramos, Pedro L. (56430569600); Louzada, Francisco (54976304900)","57201673097; 57214576601; 57211945672; 57211950624; 57211944556; 56430569600; 54976304900","Risk management in e-commerce-a fraud study case using acoustic analysis through its complexity",2019.0,"Entropy",21.0,11.0,1087.0,null,null,null,4.0,"10.3390/e21111087","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85075483982&doi=10.3390%2fe21111087&partnerID=40&md5=5286adee04bf73be4e96ef0da08663d4","Institute of Mathematical Science and Computing, University of São Paulo, São Carlos, 13566-590, Brazil","Nascimento D.C., Institute of Mathematical Science and Computing, University of São Paulo, São Carlos, 13566-590, Brazil; Barbosa B., Institute of Mathematical Science and Computing, University of São Paulo, São Carlos, 13566-590, Brazil; Perez A.M., Institute of Mathematical Science and Computing, University of São Paulo, São Carlos, 13566-590, Brazil; Caires D.O., Institute of Mathematical Science and Computing, University of São Paulo, São Carlos, 13566-590, Brazil; Hirama E., Institute of Mathematical Science and Computing, University of São Paulo, São Carlos, 13566-590, Brazil; Ramos P.L., Institute of Mathematical Science and Computing, University of São Paulo, São Carlos, 13566-590, Brazil; Louzada F., Institute of Mathematical Science and Computing, University of São Paulo, São Carlos, 13566-590, Brazil","This work aimed to develop business intelligence towards fraud detection using buyer-placed information combined with the sound analysis from a confirmation purchase call. We used a dataset of 789 orders in 2018, provided by different e-commerce websites and calls fulfilled from every Brazilian state. Nine acoustic index features were used, through entropy in sound and vibration, summarizing the audio plus 6 extra features related, added by 12 customer features to compose two different classifiers (Logistic Regression and Random Forest). The acoustic indexes were, in fact, capable of providing better accuracy of the models, showing a probability associated with the voice characteristics, helping decision-making in credit card fraud. © 2019 by the authors.","Acoustic indexes; Entropy; Fraud detection; Sound analysis",{"$nulls":5},"Vitor Bonini; Fundação de Amparo à Pesquisa do Estado de São Paulo, FAPESP, (2013/07375-0, 2017/25971-0); Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, CAPES, (301976/2017-1); Conselho Nacional de Desenvolvimento Científico e Tecnológico, CNPq","The authors are also thankful for the helpful discussions with Paola Okuda, Erik Yang Yue, Clayton Sespedes, and Vitor Bonini. Research carried out using the computational resources of the Center for Mathematical Sciences Applied to Industry (CeMEAI) funded by FAPESP (grant 2013/07375-0).This study was partially financed by CNPq and CAPES of Brazil. Francisco Louzada acknowledges support from the CNPq grant Proc. 301976/2017-1. Pedro L. Ramos acknowledges support from the São Paulo State Research Foundation (FAPESP Proc. 2017/25971-0).","Bhatla T.P., Prabhu V., Dua A., Understanding Credit Card Frauds, Cards Business Review #2003-01, (2003); Jainl N., Khan V., Credit Card Fraud Detection using Recurrent Attributes, Int. Adv. Res. J. Sci. Eng. Technol, (2018); Sueur J., Sound Analysis and Synthesis with R, (2018); Kolmogorov A.N., Sur l'interpolation et extrapolation des suites stationnaires, CR Acad. Sci, 208, pp. 2043-2045, (1939); Whittle P., The analysis of multiple stationary time series, J. R. Stat. Soc. Ser. B Methodol, 15, pp. 125-139, (1953); Llanos F., Alexander J.M., Stilp C.E., Kluender K.R., Power spectral entropy as an information-theoretic correlate of manner of articulation in American English, J. Acoust. Soc. Am, 141, pp. EL127-EL133, (2017); Shannon C.E., Communication theory of secrecy systems, Bell Syst. Tech. 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["Jiang X.; Wang H.; Guo X.; Gong X.","Jiang, Xiaohong (57213018611); Wang, Huiying (57211431482); Guo, Xiucheng (25651339300); Gong, Xiaolin (55596167900)","57213018611; 57211431482; 25651339300; 55596167900","Using the FAHP, ISM, and MICMAC approaches to study the sustainability influencing factors of the last mile delivery of rural e-commerce logistics",2019.0,"Sustainability (Switzerland)",11.0,14.0,3937.0,null,null,null,36.0,"10.3390/su11143937","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85073897633&doi=10.3390%2fsu11143937&partnerID=40&md5=5a1dc689893d15189989f6f45f329322","College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing, 210037, China; School of Transportation, Southeast University, Nanjing, 210096, China","Jiang X., College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing, 210037, China; Wang H., College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing, 210037, China; Guo X., School of Transportation, Southeast University, Nanjing, 210096, China; Gong X., College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing, 210037, China","The development of rural e-commerce has rapidly driven the development of rural logistics in China. Improving the service quality of the last mile delivery is an important measure to promote the sustainable development of rural e-commerce logistics. However, such work is challenging because the current rural last mile delivery is inefficient and unsustainable and is influenced by a set of interacting factors. It is necessary to explore the relationships among the sustainability influencing factors of rural last mile delivery. A total of 15 sustainability influencing factors are selected. The improved fuzzy analytic hierarchy process (FAHP) is used to assign the weights of the factors and then the interpretative structural model (ISM) is used to determine the hierarchical structure of each factor. The driving force-dependency quadrant graph is constructed by cross-impact matrix multiplication (MICMAC). The research results show that four factors, including \"convenience of returning goods\", \"integrity of goods\", \"advance reservation of goods pickup\", and \"delivery costs\", are the most basic factors affecting the sustainability of rural last mile delivery and are the deepest and most indispensable factors. This research provides valuable information for decision makers to develop proactive strategies and reinforcement policies to improve the service quality of rural last mile delivery, which could promote the sustainable development of rural logistics. © 2019 by the authors.","Cross-impact matrix multiplication applied to classification (MICMAC); Fuzzy analytical hierarchy process (FAHP); Interpretative structural modeling (ISM); Last mile delivery; Rural e-commerce logistics; Sustainability influencing factors","analytical hierarchy process; classification; decision making; electronic commerce; fuzzy mathematics; logistics; rural area; service quality; sustainability",{"$nulls":4},"Research subject of China logistics association; Social Science Research Foundation of Jiangsu Province, (18WTA009); Southeast University, SEU; Social Science Foundation of Jiangsu Province","Funding text 1: This research was funded by Social Science Research Foundation of Jiangsu Province (grant no.18WTA009), and Research subject of China logistics association (grant no.2019CSLKT3-032)We gratefully acknowledge the experts who participated in the study and thank Zhenjun Zhu (Southeast University) for his valuable comments on early drafts.; Funding text 2: Funding: This research was funded by Social Science Research Foundation of Jiangsu Province (grant no.18WTA009), and Research subject of China logistics association (grant no.2019CSLKT3-032) Acknowledgments: We gratefully acknowledge the experts who participated in the study and thank Zhenjun Zhu (Southeast University) for his valuable comments on early drafts.","Mohanty M., Shankar R., Modelling uncertainty in sustainable integrated logistics using Fuzzy-TISM, Transp. 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["Kim J.-H.","Kim, Jung-Hwan (55720265900)",5.57202659E10,"Imperative challenge for luxury brands: Generation Y consumers’ perceptions of luxury fashion brands’ e-commerce sites",2019.0,"International Journal of Retail and Distribution Management",47.0,2.0,null,220.0,244.0,24.0,45.0,"10.1108/IJRDM-06-2017-0128","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85063577727&doi=10.1108%2fIJRDM-06-2017-0128&partnerID=40&md5=1531e6a0045e69e0c6183c84ba8d4c98","Department of Retailing, University of South Carolina, Columbia, SC, United States","Kim J.-H., Department of Retailing, University of South Carolina, Columbia, SC, United States","Purpose: The purpose of this paper is to examine whether any differences exist between high- and low/middle-income Generation Y luxury consumers in terms of their service quality perceptions on luxury fashion brands’ own official e-commerce sites. Design/methodology/approach: This study focused on actual luxury consumers who purchased luxury fashion items from luxury fashion brands’ e-commerce sites. An online survey asked participants to evaluate their perceptions of e-service attributes available on luxury fashion brands’ own official e-commerce sites based on their experience with the site. A total of 123 usable respondents obtained. Findings: Of the nine e-service quality dimensions identified, efficiency and web appearance were significant dimensions affecting high-income Generation Y luxury fashion consumers’ overall e-satisfaction. For low/middle-income Generation Y luxury fashion consumers, order/delivery management, personalization and trust were crucial factors that affected overall e-satisfaction. Originality/value: Despite the growth of luxury e-commerce sales and the increasing interest in luxury consumption by consumers from a variety of demographic groups, little research has focused on how luxury consumers perceive luxury brands’ own official e-commerce site and how luxury fashion brands develop their own e-commerce sites to meet demographically dissimilar customers’ necessities. The findings of the study provide valuable practical implications to luxury fashion brands by proving that luxury consumers are unalike and that their perceptions on e-service quality are dissimilar based on different income levels. © 2019, Emerald Publishing Limited.","E-commerce; Generation Y; Income; Luxury brands",{"$nulls":7},"Census data on income distribution reveal evidence of rising income levels for a rising share of American households, (2016); Aruna S., Santhi P., Impulse purchase behavior among Generation Y, The IUP Journal of Marketing Management, 14, 1, pp. 21-38, (2015); Luxury goods worldwide market study, Fall–Winter 2017, (2017); Barclay D.W., Higgins C.A., Thompson R., The partial least squares approach to causal modeling: personal computer adoption and use as illustration, Technology Studies, 2, 2, pp. 285-309, (1995); Bauer H.H., Falk T., Hammerschmidt M., eTransQual: a transaction process-based approach for capturing service quality in online shopping, Journal of Business Research, 59, 1, pp. 866-875, (2006); 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Kim; Department of Retailing, University of South Carolina, Columbia, United States; email: jhkim@mailbox.sc.edu",null,"Emerald Group Holdings Ltd.",{"$nulls":5},9590552.0,null,null,null,"English","Int. J. Retail Disrtib. Manage.","Article","Final",null,"Scopus","2-s2.0-85063577727"]
["Hong W.; Zheng C.; Wu L.; Pu X.","Hong, Wei (57206995406); Zheng, Changyuan (57209805547); Wu, Linhai (58257775000); Pu, Xujin (12762986900)","57206995406; 57209805547; 58257775000; 12762986900","Analyzing the relationship between consumer satisfaction and fresh e-commerce logistics service using text mining techniques",2019.0,"Sustainability (Switzerland)",11.0,13.0,3570.0,null,null,null,42.0,"10.3390/su11133570","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85068748032&doi=10.3390%2fsu11133570&partnerID=40&md5=393f4221829df80fc10a47a68fa24894","Food Safety Research Base of Jiangsu Province, Jiangnan University, Wuxi, 214122, China; School of Business, Jiangnan University, Wuxi, 214122, China; Institute for Food Safety Risk Management, Jiangnan University, Wuxi, 214122, China","Hong W., Food Safety Research Base of Jiangsu Province, Jiangnan University, Wuxi, 214122, China, School of Business, Jiangnan University, Wuxi, 214122, China, Institute for Food Safety Risk Management, Jiangnan University, Wuxi, 214122, China; Zheng C., School of Business, Jiangnan University, Wuxi, 214122, China; Wu L., Food Safety Research Base of Jiangsu Province, Jiangnan University, Wuxi, 214122, China, School of Business, Jiangnan University, Wuxi, 214122, China, Institute for Food Safety Risk Management, Jiangnan University, Wuxi, 214122, China; Pu X., Food Safety Research Base of Jiangsu Province, Jiangnan University, Wuxi, 214122, China, School of Business, Jiangnan University, Wuxi, 214122, China, Institute for Food Safety Risk Management, Jiangnan University, Wuxi, 214122, China","The rapid development of the Internet and the transformation of consumption patterns have prompted consumers to purchase fresh products online. For fresh e-commerce enterprises, logistics is an important aspect of customer satisfaction. Therefore, this study focused on online review information and used a convolutional neural network text mining model for its analysis. Logistics service elements concerned with customer satisfaction are convenience, communication, integrity, responsiveness, and reliability. Thereafter, comment information was converted to digital information using sentiment analysis. Finally, a correlation analysis was carried out to compare the significance of various influencing factors. The results confirm that convenience, communication, reliability, and responsiveness had a significant impact on customer satisfaction, whereas integrity had none. Fresh e-commerce logistic services need to improve for the development of the companies. © 2019 by the authors.","Convolutional neural network; Customer satisfaction; Fresh e-commerce; Logistics service; Sentiment analysis","artificial neural network; data mining; electronic commerce; Internet; life satisfaction; logistics; residential satisfaction; service sector",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (71303094, 71871105); Fundamental Research Funds for the Central Universities, (JUSRP51641A); National Office for Philosophy and Social Sciences, NPOPSS, (14ZDA069)","Funding: This work was supported by the National Natural Science Foundation of China (Project Approval No. 71303094), the Major Project of the National Social Science Fund of China (Project Approval No. 14ZDA069), the Fundamental Research Funds for the Central Universities (Project Approval No. JUSRP51641A), and the National Natural Science Foundation of China (Project Approval No. 71871105).","Chevalier J.A., Mayzlin D., The Effect of Word of Mouth on Sales: Online Book Reviews, J. 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Issues, 33, pp. 40-43, (2012); Li F., Han C., Huang M., Zhu X., Xia Y.J., Zhang S., Yu H., Structure aware Review Mining and Summarization, Proceedings of the International Conference on Computational Linguistics, pp. 653-661, (2010); Li C.W., Chuang H.C., Li S.T., Hedonic Analysis for Consumer Electronics Using Online Product Reviews, Proceedings of the IIAI International Congress on Advanced Applied Informatics, pp. 609-614, (2016); Ha M., The Impact of the Port Logistics Service Quality on Customer Satisfaction and Loyalty, Korea Int. Commer. Rev, 33, pp. 171-191, (2018); Park K., Logistics Service Quality and Customer Satisfaction in E-commerce, Asia Pac. J. Inf. Syst, 12, pp. 237-253, (2002); Kim B.I., The Relative Effects of Three Dimensions of Port Logistics Service Quality on Customer Satisfaction, J. Korea Port Econ. Assoc, 22, pp. 125-149, (2006)","W. Hong; Food Safety Research Base of Jiangsu Province, Jiangnan University, Wuxi, 214122, China; email: hongwei@jiangnan.edu.cn",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85068748032"]
["Gao H.","Gao, Han (57210379285)",5.7210379285E10,"A B2C agricultural products self-distribution system in E-commerce environment",2019.0,"International Journal of Mechatronics and Applied Mechanics",2019.0,5.0,null,37.0,44.0,7.0,1.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85070500112&partnerID=40&md5=48eb1afe1f8809984a1fd694b1fc384f","Department of Economic Management, Xi’an Vocational and Technical College, Xi’an, 710077, Shaanxi, China","Gao H., Department of Economic Management, Xi’an Vocational and Technical College, Xi’an, 710077, Shaanxi, China","With the advent of Internet plus age, agricultural products home delivery mode has been concerned more and more. In this study, an optimized e-commerce distribution system was designed against the problems existing in the traditional agricultural products distribution process. The distribution structure and technology, operation process and profit model were analyzed based on business to customer (B2C) mode. Moreover the self-distribution system was optimized. As to the problem of distribution route, the concept of time window was added for restriction, hypothesis was proposed, and the role of saving algorithm for distribution route was analyzed. An example was demonstrated to verify that adding time window constraint saving algorithm into B2C mode based self-distribution system could optimize distribution route and enhance distribution efficiency. The application of the algorithm can save distribution cost and improve economic benefits. © 2019, Cefin Publishing House. All rights reserved.","B2C mode; Distribution route; E-commerce environment; Time window","Agricultural products; Electronic commerce; B2c modes; Business to customers; Distribution costs; Distribution efficiency; Distribution route; Distribution systems; Products distributions; Time windows; Costs",{"$nulls":6},"Zhang J., Wang X., Huang K., Integrated on-line scheduling of order batching and delivery under B2C e-commerce, Computers & Industrial Engineering, 94, C, pp. 280-289, (2016); Hoglund M., Wikman I., Collaborative consumption-Business-to-consumer sharing and its economic impact on consumers, Göteborgs Universitetsbibliotek, 6, (2017); Li G., Wang D., Optimization for the Locations of B2C E-Commerce Distribution Network Based on an Improved Genetic Algorithm, Lecture Notes in Electrical Engineering, 236, pp. 223-232, (2013); Deng C., A Preliminary Study on the Application of Logistics Distribution Strategy in B2C E-commerce Enterprises, International Conference on Electronic, Mechanical, Information and Management Society, (2016); Naccache S., Montreuil B., Optimizing Consumer Order Delivery Consolidation in Drop-Ship Based B2C Distribution, IFAC Papersonline, 48, 3, pp. 1996-2001, (2015); Arnold F., Cardenas I., Sorensen K., Et al., Simulation of B2C e-commerce distribution in Antwerp using cargo bikes and delivery points, European Transport Research Review, 10, 1, (2018); Yan Q., Research on Fresh Produce Food Cold Chain Logistics Tracking System Based on RFID, Advance Journal of Food Science & Technology, 7, 3, pp. 191-194, (2015); Ding Z., Zhang R., Kan Z., Quality and Safety Inspection of Food and Agricultural Products by LabVIEW IMAQ Vision, Food Analytical Methods, 8, 2, pp. 290-301, (2015); Vale T., de Almeida E.S., Alves V., Et al., Software product lines traceability, Information & Software Technology, 84, pp. 1-18, (2017); Liu Z.Y., Liu Y., Wang Z.W., Study on the Influence Factors of On-line Shoppers Satisfaction Based on B2C, Technological Development of Enterprise, (2016); Qadir I., Ali A., Importance of Logistics Processes for Customer Service and Firm Performance: Evidence from Furniture Industry of Pakistan, 22, 3, (2017); Ding R., Huo Y., Wang H., Game analysis for logistics mode decision of B2C enterprises, Icic Express Letters, 11, 6, pp. 1153-1158, (2017); Veenstra M., Cherkesly M., Desaulniers G., Et al., The pickup and delivery problem with time windows and handling operations, Computers & Operations Research, 77, 7, pp. 127-140, (2017); Zare-Reisabadi E., Mirmohammadi S.H., Site dependent vehicle routing problem with soft time window: Modeling and solution approach, Computers & Industrial Engineering, 90, C, pp. 177-185, (2015); Tang L., Wang W., Wang Y., Et al., An Energy-Saving Algorithm with Joint User Association, Clustering and On/Off Strategies in Dense Heterogeneous Networks, IEEE Access, 99, (2017)","H. Gao; Department of Economic Management, Xi’an Vocational and Technical College, Xi’an, 710077, China; email: gaohan69xz@126.com",null,"Cefin Publishing House",{"$nulls":5},2.5596497E7,null,null,null,"English","Int. J. Mech. Appl. Mech.","Article","Final",null,"Scopus","2-s2.0-85070500112"]
["Liao W.; Wang T.","Liao, Wenzhu (23974947900); Wang, Tong (7405561755)","23974947900; 7405561755","A novel collaborative optimization model for job shop production-delivery considering time window and carbon emission",2019.0,"Sustainability (Switzerland)",11.0,10.0,2781.0,null,null,null,32.0,"10.3390/su11102781","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85067121539&doi=10.3390%2fsu11102781&partnerID=40&md5=96fb462dc9f7a5a63c92fb804812eb09","College of Mechanical Engineering, Chongqing University, Chongqing, 400044, China","Liao W., College of Mechanical Engineering, Chongqing University, Chongqing, 400044, China; Wang T., College of Mechanical Engineering, Chongqing University, Chongqing, 400044, China","The manufacturing industry is undergoing transformation and upgrading from traditional manufacturing to intelligent manufacturing, in which Internet of Things (IoT) technology plays a central role in promoting the development of intelligent manufacturing. In order to solve the problem that low production efficiency and machine utilization lead to serious pollution emissions in the workshop caused by untimely transmission of information in all links of the production and manufacturing process to whole supply chains, this study establishes an intelligent production scheduling and logistics delivery model with IoT technology to promote green and sustainable development of intelligent manufacturing. Firstly, an application framework of IoT technology in production-delivery supply chain systems was established to improve efficiency and achieve the integration of production and delivery. Secondly, an integrated production-delivery model was constructed, which takes into account time and low carbon constraints. Finally, a two-layer optimization algorithm was proposed to solve this integration problem. Through a case study, the results show this integration production-delivery model can reduce the cost of supply chains and improve customer satisfaction. Moreover, it proves that carbon emission cost is a major factor affecting total cost, and it could help enterprises to realize the profit and sustainable development of the environment. The production-delivery model could also support the last kilometer distribution problem and extension under E-commerce applications. © 2019 by the authors.","Green sustainable; Internet of Things; Logistic delivery; Scheduling; Time window","algorithm; carbon emission; emission; industrial production; Internet; logistics; manufacturing; numerical model; optimization; supply chain management; sustainable development",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (71301176); Specialized Research Fund for the Doctoral Program of Higher Education of China, SRFDP, (20130191120001)","Funding: The authors would like to thank anonymous referees for their remarkable comments and great support by National Natural Science Foundation of China (No. 71301176), Research fund for the Doctoral Program of Higher Education of China (20130191120001).","Modoni G.E., Trombetta A., Veniero M., Sacco M., Mourtzis D., An event-driven integrative framework enabling information notification among manufacturing resources, Int. 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Res, 39, pp. 1419-1431, (2012); Thammano A., Teekeng W., A modified genetic algorithm with fuzzy roulette wheel selection for job-shop scheduling problems, Int. J. Gen. Syst, 44, pp. 499-518, (2015); Kadri R.L., Boctor F.F., An efficient genetic algorithm to solve the resource-constrained project scheduling problem with transfer times: The single mode case, Eur. J. Oper. Res, 265, pp. 454-462, (2018); Lu R., An agent based approach for multi-objective optimization in production scheduling for turbine engine blade manufacturing, SAE Int. J. Mater. Manuf, 8, pp. 12-17, (2014)","W. Liao; College of Mechanical Engineering, Chongqing University, Chongqing, 400044, China; email: liaowz@cqu.edu.cn",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85067121539"]
["Leung K.H.; Choy K.L.; Ho G.T.S.; Lee C.K.M.; Lam H.Y.; Luk C.C.","Leung, K.H. (57328966600); Choy, K.L. (7005477047); Ho, G.T.S. (8348673600); Lee, Carman K.M. (24468281700); Lam, H.Y. (57201769414); Luk, C.C. (57204634952)","57328966600; 7005477047; 8348673600; 24468281700; 57201769414; 57204634952","Prediction of B2C e-commerce order arrival using hybrid autoregressive-adaptive neuro-fuzzy inference system (AR-ANFIS) for managing fluctuation of throughput in e-fulfilment centres",2019.0,"Expert Systems with Applications",134.0,null,null,304.0,324.0,20.0,17.0,"10.1016/j.eswa.2019.05.027","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85067457044&doi=10.1016%2fj.eswa.2019.05.027&partnerID=40&md5=d9fb31bf07ab6d348e5459f8da40ba96","Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong; Department of Supply Chain and Information Management, The Hang Seng University of Hong Kong, Sha Tin, New Territories, Hong Kong","Leung K.H., Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong; Choy K.L., Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong; Ho G.T.S., Department of Supply Chain and Information Management, The Hang Seng University of Hong Kong, Sha Tin, New Territories, Hong Kong; Lee C.K.M., Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong; Lam H.Y., Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong; Luk C.C., Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong","The complexity of today's e-commerce logistics environment compels practitioners to achieve a higher level of operating efficiency. As it is infeasible for operators to process a large number of discrete e-orders individually, warehouse postponement, that is, delaying the execution of a logistics process until the last possible moment, is essential. Yet the question remains as to how one can accurately identify the timing for consolidating e-orders, and subsequently releasing the grouped e-orders for batch order picking. This is a subject, lacking previous research, but is fundamentally crucial in today's e-commerce logistics environment. This paper introduces an integrated autoregressive-adaptive neuro-fuzzy inference system (AR-ANFIS) approach for forecasting e-commerce order arrivals. Two AR-ANFIS models are built for evaluating their prediction ability against ARIMA models. The experimental results confirm the suitability of the hybrid model for forecasting e-order arrivals. To make use of the model output, an algorithm is formulated to convert e-order arrival figures into cut-off time of order grouping. In this sense, this total solution, packaged as a decision support system, namely the E-order arrival prediction system, assists logistics practitioners in judging when to release the grouped e-orders for batch processing, and essentially improves their order handling capability. © 2019 Elsevier Ltd","Adaptive neuro-fuzzy inference system (ANFIS); Autoregressive (AR) model; E-commerce logistics; Order arrival prediction; Warehouse postponement applications","Batch data processing; Decision support systems; Electronic commerce; Forecasting; Fuzzy neural networks; Fuzzy systems; Warehouses; Adaptive neuro-fuzzy inference system; Auto regressive models; Auto-regressive; B2C e-commerce; Batch ordering; Logistics process; Operating efficiency; Prediction systems; Fuzzy inference",{"$nulls":4},"Hong Kong Polytechnic University, PolyU","The authors wish to thank the Research Office of The Hong Kong Polytechnic University for supporting the project (Project Code: RU5T and G-YBMS).  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Choy; Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong; email: kl.choy@polyu.edu.hk",null,"Elsevier Ltd",{"$nulls":5},9574174.0,null,"ESAPE",null,"English","Expert Sys Appl","Article","Final",null,"Scopus","2-s2.0-85067457044"]
["Tham K.W.; Dastane O.; Johari Z.; Ismail N.B.","Tham, Kok Wai (57215780462); Dastane, Omkar (57208015890); Johari, Zainudin (57215208176); Ismail, Nurlida Binti (57202035912)","57215780462; 57208015890; 57215208176; 57202035912","Perceived risk factors affecting consumers' online shopping behaviour",2019.0,"Journal of Asian Finance, Economics and Business",6.0,4.0,246.0,246.0,260.0,14.0,58.0,"10.13106/jafeb.2019.vol6.no4.246","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85081927911&doi=10.13106%2fjafeb.2019.vol6.no4.246&partnerID=40&md5=b17993ddd655c8d5a7921ad7742fbf32","Lord Ashcroft International Business School, Anglia Ruskin University, Cambridge, United Kingdom; School of Accounting and Business Management, FTMS College Malaysia, Block 3420, Persiaran Semarak Api, Cyber 4, Cyberjaya, 63000, Malaysia; School of Engineering and Information Systems, FTMS College Malaysia, Malaysia; Taylor's Business School, Taylor's University, Subang Jaya, Malaysia","Tham K.W., Lord Ashcroft International Business School, Anglia Ruskin University, Cambridge, United Kingdom; Dastane O., School of Accounting and Business Management, FTMS College Malaysia, Block 3420, Persiaran Semarak Api, Cyber 4, Cyberjaya, 63000, Malaysia; Johari Z., School of Engineering and Information Systems, FTMS College Malaysia, Malaysia; Ismail N.B., Taylor's Business School, Taylor's University, Subang Jaya, Malaysia","The study examines the impact of financial risk, convenience risk, non-delivery risk: return policy risk and product risk on online consumer behavior of Malaysian consumers. The research employed a self-administered survey to collect empirical data from 245 Malaysian online shoppers by using convenience sampling. Cronbach alpha was calculated to confirm the reliability of the data and then normality was assessed. Confirmatory Factor Analysis was then conducted to test the model using the goodness-of-fit tests. And finally, structural equation modeling is used to test the hypotheses and draw conclusions. IBM SPSS AMOS version 22.0 was utilized for data analysis. The research indicates that product risk, convenience risk, and return policy risk have a significant and positive impact on online shopping behavior. Financial risk is found to have insignificant and negative effects on consumer behavior, hi addition, the non-delivery risk is found to have a significant and negative impact on online shopping behavior. The findings provide a useful model for measuring and managing perceived risk in online shopping which may result in an increase in participation of Malaysian consumers and reduce their cognitive deficiencies in the e-commerce environment. 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The marketing strategies, Procedia-Social and Behavioral Sciences, 62, pp. 1265-1270, (2012); Wong S.W., Dastane O., Safie N., Maarif Y., What WeChat can learn from WhatsApp? Customer value proposition development for mobile social networking Apps: A case study approach, Journal of Theoretical and Applied Information Technology, 97, 4, pp. 1091-1117, (2019); Zeithaml V., Bitner M., Services marketing: Integrating customer focus across the firm, (2003); Zhang L., Tan W., Xu Y., Tan G., Dimensions of consumers perceived risk and their influences on online consumers purchasing behaviour, Communications in Information Science and Management Engineering, 2, 7, pp. 8-14, (2012); Zheng L., Favier M., Huang P., Coat F., Chinese consumer perceived risk and risk relievers in E-shopping for clothing, Journal of Electronic Commerce Research, 13, 3, pp. 255-274, (2012)","O. Dastane; School of Accounting and Business Management, FTMS College Malaysia, Cyberjaya, Block 3420, Persiaran Semarak Api, Cyber 4, 63000, Malaysia; email: omkar.dastane@gmail.com",null,"Korea Distribution Science Association (KODISA)",{"$nulls":5},2.2884637E7,null,null,null,"English","J. Asian Financ. Econ. Bus.","Article","Final",null,"Scopus","2-s2.0-85081927911"]
["Inoue Y.; Hashimoto M.; Takenaka T.","Inoue, Yuki (57077468300); Hashimoto, Masataka (36477221100); Takenaka, Takeshi (8636962500)","57077468300; 36477221100; 8636962500","Effectiveness of ecosystem strategies for the sustainability of marketplace platform ecosystems",2019.0,"Sustainability (Switzerland)",11.0,20.0,5866.0,null,null,null,9.0,"10.3390/su11205866","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85074264155&doi=10.3390%2fsu11205866&partnerID=40&md5=72c1f12dacae59edd9fde63f54eb91c9","Graduate School of Social Sciences, Hiroshima University, Higashi-senda, 1-1-89, Naka-ku, Hiroshima, 730-0053, Japan; Human Augmentation Research Center, National Institute of Advanced Industrial Science and Technology, 6-2-3, Kashiwanoha, Kashiwa, Chiba, 277-0882, Japan; Graduate School of Global Business, Meiji University, 1-1, Surugadai, Kanda, Chiyoda-ku, Tokyo, 101-8301, Japan","Inoue Y., Graduate School of Social Sciences, Hiroshima University, Higashi-senda, 1-1-89, Naka-ku, Hiroshima, 730-0053, Japan, Human Augmentation Research Center, National Institute of Advanced Industrial Science and Technology, 6-2-3, Kashiwanoha, Kashiwa, Chiba, 277-0882, Japan; Hashimoto M., Graduate School of Global Business, Meiji University, 1-1, Surugadai, Kanda, Chiyoda-ku, Tokyo, 101-8301, Japan; Takenaka T., Human Augmentation Research Center, National Institute of Advanced Industrial Science and Technology, 6-2-3, Kashiwanoha, Kashiwa, Chiba, 277-0882, Japan","Physical intermediary firms, such as logistics firms, are the foundation of marketplace platform ecosystems. This study introduces the case of a delivery crisis caused by the withdrawal of major logistics firms from the Japanese marketplace platform. To address such a problem, this study considers the application of an \"ecosystem strategy\". We define an ecosystem strategy in this situation, as \"the strategy by which the platform owner cooperates with logistics firms to standardize logistics services and provides a platform system to improve cooperation among them\". We constructed an agent-based simulation system customized by a dataset of Japanese platform-based markets to test the effectiveness of the proposed strategy. The results indicate that the introduction of the ecosystem strategy postponed the start of the collapse. It also increased the number of platform users by roughly 1.10 times and increased the total profits of logistics firms about 1.22 times. Additionally, it removed the trade-off relationship between platform users and the profits of logistics firms and allowed the maximization of both. This study contributed to the research stream of platform ecosystems by defining an ecosystem strategy, including physical intermediary firms, and verifying the effectiveness of the strategy for ecosystem evolution and sustainability. © 2019 by the authors.","Delivery crisis; E-commerce; Ecosystem strategy; Marketplace platform; Platform ecosystem; Platform-based market; Service open innovation","ecosystem service; electronic commerce; logistics; market conditions; service sector; sustainability; trade-off",{"$nulls":4},"Japan Society for the Promotion of Science, JSPS, (18K12874)","Funding: This work was funded by JSPS KAKENHI Grant Numbers 18K12874.","Tauscher K., Laudien S.M., Understanding platform business models: A mixed methods study of marketplaces, Eur. Manag. 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Methodological issues on agent-based models for analytical social science, J. Artif. Soc. Soc. Simul, 8, pp. 1-6, (2005); Monthly users of EC websites; Methods of Investigation and collection about amount of home deliveries in 2013; Abhishek V., Jerath K., Zhang Z.J., Agency selling or reselling?, Channel structures in electronic retailing. Manag. Sci, 62, pp. 2259-2280, (2016); Miron E.T., Purcarea A.A., Negotia O.D., Modelling perceived risks associated to the entry of complementors' in platform enterprises: A case study, Sustainability, 10, (2018); Wan X., Cenamor J., Parker G., Van Alstyne M., Unraveling platform strategies: A review from an organizational ambidexterity perspective, Sustainability, 9, (2017); Yun J.J., Won D., Park K., Dynamics from open innovation to evolutionary change, J. Open Innov. Technol. Mark. Complex, 2, (2016); Yun J.J., Liu Z., Micro-and macro-dynamics of open innovation with a quadruple-helix model, Sustainability, 11, (2019); Siu S., Inoue Y., Tsujimoto M., Erosion of complement portfolio sustainability: Uncovering adverse repercussions in steam's refund policy, J. Open Innov. Technol. Mark. Complex, 5, (2019)","Y. Inoue; Graduate School of Social Sciences, Hiroshima University, Naka-ku, Hiroshima, Higashi-senda, 1-1-89, 730-0053, Japan; email: yuinoue@hiroshima-u.ac.jp",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85074264155"]
["Chakraborty S.; Sharma A.; Vaidya O.S.","Chakraborty, Shuvabrata (57210999938); Sharma, Ankit (57211108689); Vaidya, Omkarprasad S. (8976444500)","57210999938; 57211108689; 8976444500","Achieving sustainable operational excellence through IT implementation in Indian logistics sector: An analysis of barriers",2020.0,"Resources, Conservation and Recycling",152.0,null,104506.0,null,null,null,25.0,"10.1016/j.resconrec.2019.104506","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85072684420&doi=10.1016%2fj.resconrec.2019.104506&partnerID=40&md5=3749142ab7010690a99945b90a02b99d","Indian Institute of Management Lucknow, India","Chakraborty S., Indian Institute of Management Lucknow, India; Sharma A., Indian Institute of Management Lucknow, India; Vaidya O.S., Indian Institute of Management Lucknow, India","Information Technology (IT) infrastructure has been integral to operational excellence approaches towards sustainable supply chains. The paper explores the crucial barriers to IT implementation in the largely unorganized logistics sector of an emerging economy, India. Through a comparative study using two separate expert-groups, representing the organized and unorganized logistics sectors respectively, the paper analyses their views on the criticality of barriers in each sector and highlights the sector-specific problems that hinder effective IT implementation. Considering the profiles of the expert groups used, the paper implements Fuzzy-ISM and Fuzzy-MICMAC analysis for one group and IRP for the other to capture and analyze their opinions appropriately. The results obtained from the analyses show that the barriers concerning IT implementation in the unorganized logistics sector (ULS) substantially differ from those concerning the organized logistics sector (OLS) as perceived by the corresponding sector experts. The study ranks the barriers in the two sectors and highlights the focus areas that require immediate attention to strengthen the IT infrastructure of Indian ULS, which suffers mainly from behavioral issues at the organizational level. Focused attention to unorganized sector's requirements can revive the sector and smoothen its transformation to an organized one as exceedingly demanded by the recent e-commerce boom. The work is perhaps the first to address the Indian ULS. It implements a unique approach: seeks inputs from two different expert groups, implements tools appropriate to the respective panel profiles, and compares their opinions to identify the specific and different requirements of the Indian ULS with respect to IT implementation. © 2019 Elsevier B.V.","Barriers; Fuzzy-Interpretive Structural Modelling (Fuzzy-ISM); India; Interpretive Ranking Process (IRP); IT implementation; Unorganized logistics","India; Economics; Natural resources management; Waste management; Barriers; India; IT implementation; Ranking process; Structural modelling; electronic commerce; implementation process; information technology; infrastructure; logistics; article; attention; controlled study; human; India; information technology; Supply chains",{"$nulls":6},"Agyemang M., Zhu Q., Adzanyo M., Antarciuc E., Zhao S., Evaluating barriers to green supply chain redesign and implementation of related practices in the West Africa cashew industry, Resour. Conserv. Recycl., 136, pp. 209-222, (2018); Baker P.M.A., Bellordre C., Adoption of Information and Communication Technologies: Key Policy Issues, Barriers and Opportunities for People with Disabilities, (2004); Beamon B.M., Measuring supply chain performance, Int. J. Oper. Prod. Manag., 19, 3, pp. 275-292, (1999); Biyani V., Decoding the Indian Transportation Industry and the Digital Opportunities, (2017); Bouzon M., Govindan K., Rodriguez C.M.T., Evaluating barriers for reverse logistics implementation under a multiple stakeholders’ perspective analysis using grey decision making approach, Resour. Conserv. Recycl., 128, pp. 315-335, (2018); Bowersox D.J., Daugherty P.J., Logistics paradigms: the impact of information technology, J. Bus. Logist., 16, (1995); Dawe R.L., An investigation of the pace and determination of information technology use in the manufacturing materials logistics system, J. Bus. 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Man Cybern., pp. 405-417, (1974); Yenradee P., Dangton R., Implementation sequence of engineering and management techniques for enhancing the effectiveness of production and inventory control system, Int. J. Prod. Res., 38, pp. 2689-2707, (2000); Zimmermann H.-J., Fuzzy Set Theory—and Its Applications, (2001)","S. Chakraborty; Indian Institute of Management Lucknow, India; email: fpm17010@iiml.ac.in",null,"Elsevier B.V.",{"$nulls":5},9213449.0,null,"RCREE",null,"English","Resour. Conserv. Recycl.","Article","Final",null,"Scopus","2-s2.0-85072684420"]
["Parker C.J.; Wenyu L.","Parker, Christopher J. (55303496400); Wenyu, Lu (57209256446)","55303496400; 57209256446","What influences Chinese fashion retail? Shopping motivations, demographics and spending",2019.0,"Journal of Fashion Marketing and Management",23.0,2.0,null,158.0,175.0,17.0,15.0,"10.1108/JFMM-09-2017-0093","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85067068214&doi=10.1108%2fJFMM-09-2017-0093&partnerID=40&md5=9f23b815cfeb1af098bf6da184021a85","School of Materials, The University of Manchester, Manchester, United Kingdom","Parker C.J., School of Materials, The University of Manchester, Manchester, United Kingdom; Wenyu L., School of Materials, The University of Manchester, Manchester, United Kingdom","Purpose: The purpose of this paper is to establish the influence of shopping motivations on Chinese fashion retail engagement relative to demographics, monthly spend on fashion items and high street/electronic commerce (e-commerce) preference. This is to determine how international fashion retailers should design more effective retails channels, expanding upon established theory in Hedonic and utilitarian motivations. While earlier research suggests shopping motivations associate with demographics while influencing retail channel preference and consumer spending, much of this exploration is Western focused, with all variables being influential. However, the degree to which these apply to China, and the unique fingerprint of influential motivations remains unknown. This paper answers these questions to allow international retailers to develop more efficient marketing strategies and design more effective retail channels. Design/methodology/approach: In all, 403 Chinese consumers generalisable to the broader population were surveyed on their hedonic and utilitarian motivations to shop for fashion apparel in high street and e-commerce environments. Statistical analysis was commenced through direct logistic regression and MANOVA. Findings: Demographics have limited association with shopping motivations, with gender and age only producing small effect sizes, while occupation, income and education has no significance. High street store preference is influenced by adventure and social shopping and e-commerce preference only by idea shopping. Spending over ¥1k per month on fashion apparel is influenced by gratification and idea shopping, and regular spending habits inspired by value shopping. Originality/value: This empirical paper characterises the fingerprint of shopping motivations’ influence as singular to China while proving their limitation and need for a wider plethora of influential factors to be recognised. © 2019, Emerald Publishing Limited.","China; Consumer behaviour; Demographics; International marketing; Motivation; Retailing",{"$nulls":7},"Alesina A., Giuliano P., Nunn N., On the origins of gender roles: women and the plough, The Quarterly Journal of Economics, 128, 2, pp. 469-530, (2013); Al-Somali S.A., Gholami R., Clegg B., An investigation into the acceptance of online banking in Saudi Arabia, Technovation, 29, 2, pp. 130-141, (2009); Arnold M.J., Reynolds K.E., Hedonic shopping motivations, Journal of Retailing, 79, 2, pp. 77-95, (2003); Arvidsson A., Niessen B., Creative mass. 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A study on Indian consumers, Siddhant – A Journal of Decision Making, 17, 2, (2017); Pearson E.S., Hartley H.O., Biometrika Tables for Statisticians, (1958); Phillips S., China’s Middle Income Consumers, (2016); Rahman O., Fung B.C.M., Chen Z., Chang W.-L., Gao X., A study of apparel consumer behaviour in China and Taiwan, International Journal of Fashion Design, Technology and Education, 11, 1, pp. 22-33, (2018); Riedl R., Hubert M., Kenning P., Are there neural gender differences in online trust? an fMRI study on the perceived trustworthiness of eBay offers, Management Information Systems Quarterly, 34, 2, pp. 397-428, (2010); Rocha M.A.V., Hammond L., Hawkins D., Age, gender and national factors in fashion consumption, Journal of Fashion Marketing and Management, 9, 4, pp. 380-390, (2005); Ruzeviciute R., Kamleitner B., Attracting new customers to loyalty programs: the effectiveness of monetary versus nonmonetary loyalty programs, Journal of Consumer Behaviour, 16, 6, pp. e113-e124, (2017); Scarpi D., Hedonic and utilitarian behaviour in specialty shops, The Marketing Review, 5, 1, pp. 31-44, (2005); Sender T., How Amazon is Disrupting the Fashion Sector – 29th June 2017, (2017); Seock Y.-K., Bailey L.R., The influence of college students’ shopping orientations and gender differences on online information searches and purchase behaviours, International Journal of Consumer Studies, 32, 2, pp. 113-121, (2008); Shaouf A., Lu K., Li X., The effect of web advertising visual design on online purchase intention: an examination across gender, Computers in Human Behavior, 60, pp. 622-634, (2016); Sharma P., Chen I.S.N., Luk S.T.K., Gender and age as moderators in the service evaluation process, Journal of Services Marketing, 26, 2, pp. 102-114, (2012); Sorce P., Perotti V., Widrick S., Attitude and age differences in online buying, International Journal of Retail & Distribution Management, 33, 2, pp. 122-132, (2005); Annual expenditure on clothing and footwear in the United Kingdom (UK) from 2005 to 2016, (2017); Average annual salary of an employee in urban China from 2006 to 2016 (in Yuan), (2018); Tabachnick B.G., Fidell L.S., Using Multivariate Statistics, (2001); Tang C., Xiong Y., Wu H., Xu J., Adaptation and assessments of the Chinese version of the ICECAP-A measurement, Health and Quality of Life Outcomes, 16, 1, (2018); Teo T.S.H., Demographic and motivation variables associated with Internet usage activities, Internet Research, 11, 2, pp. 125-137, (2001); To P.-L., Liao C., Lin T.-H., Shopping motivations on internet: a study based on utilitarian and hedonic value, Technovation, 27, 12, pp. 774-787, (2007); Tsai S., Utility, cultural symbolism and emotion: a comprehensive model of brand purchase value, International Journal of Research in Marketing, 22, 3, pp. 277-291, (2005); Tsai W.-H.S., Men L.R., Consumer engagement with brands on social network sites: a cross-cultural comparison of China and the USA, Journal of Marketing Communications, Routledge, 23, 1, pp. 2-21, (2017); Tynan C., McKechnie S., Experience marketing: a review and reassessment, Journal of Marketing Management, 25, 5-6, pp. 501-517, (2009); World Economic Situation and Prospects, (2016); Warnaby G., Synchronising retail and space: using urban squares for competitive place differentiation, Consumption Markets & Culture, 16, 1, pp. 25-44, (2013); Warnaby G., Parker C.J., Walking cities (or not): how walking impacts the city experience?, Mobility, Marketing, and the City: The Discovery of Experience, pp. 203-217, (2017); Wu L., Cai Y., Liu D., Online shopping among Chinese consumers: an exploratory investigation of demographics and value orientation, International Journal of Consumer Studies, 35, 4, pp. 458-469, (2011); Xiao L., Guo Z., D'Ambra J., Fu B., Building loyalty in e-commerce, Program, 50, 4, pp. 431-461, (2016); Xue L., Parker C.J., McCormick H., A virtual reality and retailing literature review: current focus, underlying themes and future directions, 4th International AR & VR Conference 2018: The Power of AR & VR for Business, Creative Augmented Virtual Reality Hub, (2018); Yang K., Kim H.-Y., Mobile shopping motivation: an application of multiple discriminant analysis, International Journal of Retail & Distribution Management, 40, 10, pp. 778-789, (2012); Zeng C., Xu D., Views on the development of e-commerce of Chinese clothing industry, International Journal of Business and Management, 5, 8, pp. 215-218, (2010)","C.J. Parker; School of Materials, The University of Manchester, Manchester, United Kingdom; email: c.parker@lboro.ac.uk",null,"Emerald Group Holdings Ltd.",{"$nulls":5},1.3612026E7,null,null,null,"English","J. Fash. Mark. Manage.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85067068214"]
["Li X.; Li Z.","Li, Xueling (57212678487); Li, Zhen (58742033300)","57212678487; 58742033300","A hybrid prediction model for e-commerce customer churn based on logistic regression and extreme gradient boosting algorithm",2019.0,"Ingenierie des Systemes d'Information",24.0,5.0,null,525.0,530.0,5.0,15.0,"10.18280/isi.240510","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85077319284&doi=10.18280%2fisi.240510&partnerID=40&md5=179f4d235f9cd57b7f6c93921a43ebdb","Computer and Software College, Jincheng College of Sichuan University, Chengdu, 611731, China","Li X., Computer and Software College, Jincheng College of Sichuan University, Chengdu, 611731, China; Li Z., Computer and Software College, Jincheng College of Sichuan University, Chengdu, 611731, China","Customer churn is an important problem in the field of e-commerce. Based on the real data of an e-commerce platform, this paper establishes a hybrid prediction model for customer churn based on logistic regress and extreme gradient boosting (XGBoost) algorithm. More than 20 key indices were selected through data mining of the real data, covering such dimensions as order information, customer profile, and aftersales situation. With these indices, the hybrid model was applied to predict the churn state of each customer in the sample data. The results show that our model achieved a greater-than-85% accuracy in the forecast of customer churn. The research findings provide an important guide for e-commerce enterprises to improve customer adhesiveness. © 2019 International Information and Engineering Technology Association. All rights reserved.","Customer churn; E-commerce; Empirical analysis; Extreme gradient boosting (XGBoost) algorithm; Logistic regression","Adhesives; Data mining; Electronic commerce; Forecasting; Regression analysis; Customer churns; Customer profiles; E-commerce enterprise; Empirical analysis; Gradient boosting; Hybrid model; Hybrid prediction models; Logistic regressions; Sales",{"$nulls":6},"Chen D., Sain S.L., Guo K., Data mining for the online retail industry: A case study of RFM model-based customer segmentation using data mining, Journal of Database Marketing & Customer Strategy Management, 19, 3, pp. 197-208, (2012); Chang H., Jamin S., Willinger W., Inferring AS-level Internet topology from router-level path traces, International Society for Optics and Photonics, Scalability and Traffic Control in IP Networks, 4526, pp. 196-207, (2001); Lee N., Kim J.M., Conversion of categorical variables into numerical variables via Bayesian network classifiers for binary classifications, Computational Statistics & Data Analysis, 54, 5, pp. 1247-1265, (2010); Shaker A., Senge R., Hullermeier E., Evolving fuzzy pattern trees for binary classification on data streams, Information Sciences, 220, pp. 34-45, (2013); Unler A., Murat A., A discrete particle swarm optimization method for feature selection in binary classification problems, European Journal of Operational Research, 206, 3, pp. 528-539, (2010); Ebenuwa S.H., Sharif M.S., Alazab M., Al-Nemrat A., Variance ranking attributes selection techniques for binary classification problem in imbalance data, IEEE Access, 7, pp. 24649-24666, (2019); Shao Y.H., Chen W.J., Deng N.Y., Nonparallel hyperplane support vector machine for binary classification problems, Information Sciences, 263, pp. 22-35, (2014); Xu Z., Watada J., Wu M., Ibrahim Z., Khalid M., Solving the imbalanced data classification problem with the particle swarm optimization based support vector machine, IEEJ Transactions on Electronics, Information and Systems, 134, 6, pp. 788-795, (2014); Huang Y., Wang Y., Decision tree classification based on naive Bayesian and ID3 algorithm, Computer Engineering, 38, 14, pp. 41-43, (2012); Ahmed M., Afzal H., Majeed A., Khan B., A survey of evolution in predictive models and impacting factors in customer churn, Advances in Data Science and Adaptive Analysis, 9, 3, (2017); Ju C.H., Lu Q.B., Guo F.P., E-commerce customer churn prediction model combined with individual activity, Systems Engineering-Theory & Practice, 33, 1, pp. 141-150, (2013); Chan K.K., Misra S., Characteristics of the opinion leader: A new dimension, Journal of Advertising, 19, 3, pp. 53-60, (1990); Carver T., Harris S.R., Berriman M., Parkhill J., McQuillan J.A., ArtemiS: An integrated platform for visualization and analysis of high-throughput sequence-based experimental data, Bioinformatics, 28, 4, pp. 464-469, (2011); Fathian M., Hoseinpoor Y., Minaei-Bidgoli B., Offering a hybrid approach of data mining to predict the customer churn based on bagging and boosting methods, Kybernetes, 45, 5, pp. 732-743, (2016); Sharma A., Panigrahi P.K., A neural network based approach for predicting customer churn in cellular network services, International Journal of Computer Applications, 27, 11, pp. 26-31, (2013); Keramati A., Azadeh A., Mohammadi M., Rostami H., Identification of customer churn determinants using censored log file data in the Iranian mobile telecommunications service industry, International Journal of Electronic Customer Relationship Management, 5, 2, pp. 111-129, (2011); Su Q., Shao P., Ye Q., The analysis on the determinants of mobile VIP customer churn: A logistic regression approach, International Journal of Services Technology and Management, 18, 1-2, pp. 61-74, (2012)","X. Li; Computer and Software College, Jincheng College of Sichuan University, Chengdu, 611731, China; email: lixueling@scujcc.edu.cn",null,"International Information and Engineering Technology Association",{"$nulls":5},1.6331311E7,null,null,null,"English","Ing. Syst. Inf.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85077319284"]
["Hjort K.; Hellström D.; Karlsson S.; Oghazi P.","Hjort, Klas (55480129900); Hellström, Daniel (6603092522); Karlsson, Stefan (57225388552); Oghazi, Pejvak (36195901200)","55480129900; 6603092522; 57225388552; 36195901200","Typology of practices for managing consumer returns in internet retailing",2019.0,"International Journal of Physical Distribution and Logistics Management",49.0,7.0,null,767.0,790.0,23.0,26.0,"10.1108/IJPDLM-12-2017-0368","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85070265839&doi=10.1108%2fIJPDLM-12-2017-0368&partnerID=40&md5=6ac931bbc839c23a9046e60db2968b38","Department of Design Sciences, Packaging Logistics, Lund University, Lund, Sweden; School of Social Sciences, Södertörn University, Stockholm, Sweden","Hjort K., Department of Design Sciences, Packaging Logistics, Lund University, Lund, Sweden; Hellström D., Department of Design Sciences, Packaging Logistics, Lund University, Lund, Sweden; Karlsson S., Department of Design Sciences, Packaging Logistics, Lund University, Lund, Sweden; Oghazi P., School of Social Sciences, Södertörn University, Stockholm, Sweden","Purpose: The purpose of this paper is to explore, describe and categorise practices of managing product returns empirically in internet retailing. Design/methodology/approach: A multiple case study was conducted involving 12 e-commerce firms and 4 logistics service providers. An integrative data collection approach of semi-structured interviews, documentation and observations was used to gain comprehensive managerial and operational descriptions of returns management (RM) processes. Findings: The findings show inconsistent RM processes, with a plethora of practices implemented and organised differently across firms. RM processes are ambiguous; their design is a result of incremental changes over time, lacking strategy and goals. There is a mismatch between how they are described and understood in the literature and how they are actually used. Practices in gatekeeping, avoidance and reverse logistics are defined and categorised. These serve as a typology of practices for managers to (re)consider, along with 15 propositions on how RM is practised. Research limitations/implications: The range of RM practices and the processes reflect a lack of scholarly attention and strategic view. Research is needed to develop clear goals on how the RM process can be better aligned with business strategies. Practical implications: The typology of practices is a benchmark for internet retailers in their design of efficient RM processes. Originality/value: Systematic and empirical research on RM is scarce compared to forward management. The study bridges this gap as one of the first to describe RM practices in depth, define service as a key activity, and identify a mismatch between theory and practice. © 2019, Emerald Publishing Limited.","Avoidance; Case study; Consumer returns; Gatekeeping; Internet retailing; Returns management; Reverse logistics; Service",{"$nulls":7},"Directive 2011/83/EU of the European Parliament and of the Council (Online), (2011); Consumer returns in the retail industry, (2017); Badenhorst A., What practice can learn from theory: the potential impact of disposition decision factors on organisational performance, Journal of Transport and Supply Chain Management, 12, a338, pp. 1-16, (2018); Barry J.B., William R.D., Mitch G., Work and/or fun: measuring hedonic and utilitarian shopping value, Journal of Consumer Research, 20, 4, pp. 644-656, (1994); Bernon M., Cullen J., Gorst J., Online retail returns management: integration within an omni-channel distribution context, International Journal of Physical Distribution and Logistics Management, 46, 6-7, pp. 584-605, (2016); Bernon M., Rossi S., Cullen J., Retail reverse logistics: a call and grounding framework for research, International Journal of Physical Distribution & Logistics Management, 41, 5, pp. 484-510, (2011); Bernon M., Upperton J., Bastl M., Cullen J., An exploration of supply chain integration in the retail product returns process, International Journal of Physical Distribution and Logistics Management, 43, 7, pp. 586-608, (2013); Blackburn J.D., Guide V.D.R., Souza G.C., Van Wassenhove L.N., Reverse supply chains for commercial returns, California Management Review, 46, 2, pp. 6-22, (2004); Bradley G.T., Lafleur E.K., Toward the development of hedonic-utilitarian measures of retail service, Journal of Retailing and Consumer Services, 32, 2016, pp. 3260-3266, (2016); Corbin J., Strauss A., Grounded theory research: procedures, canons, and evaluative criteria, Qualitative Sociology, 13, 1, pp. 3-21, (1990); de Brito M.P., Dekker R., A framework for reverse logistics (30 2003 5,), (2003); Doherty N.F., Ellis-Chadwick F., Internet retailing: the past, the present and the future, International Journal of Retail & Distribution Management, 38, 11-12, pp. 943-965, (2010); Eisenhardt K.M., Building theories from case study research, Academy of Management Review, 14, 4, pp. 532-550, (1989); Ellram L.M., The use of the case study method in logistics research, Journal of Business Logistics, 17, 2, pp. 93-138, (1996); Gammelgaard B., Schools in logistics research? 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Exploring the shopper service ecosystem, Journal of Business Logistics, 37, 2, pp. 185-197, (2016); Vocke R., Schrauf S., Van Ostaeyen L., Trzeschan T., Solving the online logistics dilemma: a practical guide toward profitability, (2017); Wang J.-J., Chen H., Rogers D.S., Ellram L.M., Grawe S.J., A bibliometric analysis of reverse logistics research (1992-2015) and opportunities for future research, International Journal of Physical Distribution & Logistics Management, 47, 8, pp. 666-687, (2017); Wang X., Retail return policy, endowment effect, and consumption propensity: an experimental study, The B.E. Journal of Economic Analysis & Policy, 9, 1, pp. 1-27, (2009); Wollenburg J., Hubner A., Kuhn H., Trautrims A., From bricks-and-mortar to bricks-and-clicks, International Journal of Physical Distribution & Logistics Management, 48, 4, pp. 415-438, (2018); Yin R.K., Case Study Research Design and Methods, (2014); Evans P.B., Wurster T.S., Strategy and the new economics of information, Harvard Business Review, 75, 5, pp. 70-82, (1997); Krikke H., Hofenk D., Wang Y., Revealing an invisible giant: a comprehensive survey into return practices within original (closed-loop) supply chains, Resources, Conservation and Recycling, 73, 2013, pp. 239-250, (2013); Norek C.D., Returns management making order out of chaos, Supply Chain Management Review, 6, 3, pp. 34-42, (2002); Van Wassenhove L.N., Zikopoulos C., On the effect of quality overestimation in remanufacturing, International Journal of Production Research, 48, 18, pp. 5263-5280, (2010)","K. Hjort; Department of Design Sciences, Packaging Logistics, Lund University, Lund, Sweden; email: klas.hjort@plog.lth.se",null,"Emerald Group Holdings Ltd.",{"$nulls":5},9600035.0,null,null,null,"English","Int. J. Phys. Distrib. Logist. Manage.","Article","Final",null,"Scopus","2-s2.0-85070265839"]
["Yuan Q.","Yuan, Qingwen (48862165900)",4.88621659E10,"The construction mechanism and algorithm of cross border E-commerce export logistics mode from the perspective of value chain",2019.0,"Journal of Intelligent and Fuzzy Systems",37.0,3.0,null,3393.0,3400.0,7.0,13.0,"10.3233/JIFS-179142","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85073744240&doi=10.3233%2fJIFS-179142&partnerID=40&md5=13cd1fbc3ea7b5c6329a537cf8898895","Department of Finance and Economics, Shandong University of Science and Technology, Jinan, China","Yuan Q., Department of Finance and Economics, Shandong University of Science and Technology, Jinan, China","Cross border logistics and cross-border e-commerce are complementary relations. On the one hand, cross-border logistics has promoted the development of cross-border e-commerce. On the other hand, the development of cross-border e-commerce brings more opportunities for the construction of cross-border logistics. With the continuous progress and innovation of technology, the new technology represented by AI (Artificial Intelligence) is relatively mature. The application of intelligent logistics system in cross border e-commerce logistics industry will become the trend of international logistics development. Based on this, the construction mechanism and algorithm of cross-border e-commerce export logistics mode are analyzed from the perspective of value chain. From the perspective of value chain, a BP neural network model based on logistics distribution center location is established to perfect the mechanism of cross-border e-commerce export logistics. Finally, the particle swarm optimization and the ant colony algorithm and the ELECTRE-II algorithm are proposed, with the effectiveness of this algorithm verified. The results prove the effectiveness of the proposed algorithm. © 2019-IOS Press and the authors. All rights reserved.","Algorithm; construction mechanism; export logistics mode; value chain","Algorithms; Ant colony optimization; International trade; Neural networks; Particle swarm optimization (PSO); Ant colony algorithms; BP neural network model; Complementary relation; Logistics development; Logistics distribution centers; Logistics industry; Logistics modes; Value chains; Electronic commerce",{"$nulls":6},"Hsiao Y.H., Chen M.C., Liao W.C., Logistics service design for cross-border E-commerce using Kansei engineering with text-mining-based online content analysis, Telematics & Informatics, 13, 11, pp. 11-18, (2016); Zhang X.H., Guo H.L., Cross-border e-commerce and cross-border logistics synergy: Mechanism and path, China Business & Market, 1, 2, pp. 91-95, (2016); Giuffrida M., Mangiaracina R., Perego A., Cross border B2C e-commerce to Greater China and the role of logistics: A literature review, International Journal of Physical Distribution & Logistics Management, 47, 6, (2017); Jia-Ting L.I., Fan C.J., Wang Y.S., Cross-border Ecommerce logistics models analysis and market study in China, Logistics Sci-Tech, 41, 2, (2016); Liu Y.S., Chen D.B., University F., The synergetic measurement of cross-border E-commerce and modern logistics based on the synergetic degree model of the compound system, China Business & Market, 47, 3, pp. 124-127, (2016); Liu X.J., Zhang B., University J., The study of collaborative development of cross-border E-commerce logistics in countries along the belt and road, China Business & Market, 42, 6, pp. 2428-2432, (2016); Yan M., Wang F., Han C., Nanowire templated semihollow bicontinuous graphene scrolls: Designed construction, mechanism, and enhanced energy storage performance, Journal of the American Chemical Society, 135, 48, pp. 18176-18182, (2013); Kim J.H., Chang B.J., Numerical construction of balanced state manifold for single-support legged mechanism in sagittal plane, Multibody System Dynamics, 31, 3, pp. 257-281, (2014); Quirk D.G., Shakerley A., Howe M.J., A mechanism for construction of volcanic rifted margins during continental breakup, Geology, 42, 12, pp. 1079-1082, (2014); 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Elhoseny M., Yuan X., El-Minir H.K., Riad A.M., Extending self-organizing network availability using genetic algorithm, 2014 International Conference on Computing, Communication and Networking Technologies (ICCCNT), pp. 11-13, (2014); Metawaa N., Kabir Hassana M., Elhoseny M., Genetic algorithm based model for optimizing bank lending decisions, Expert Systems with Applications, 80, pp. 75-82, (2017); Reza Boveiri H., Khayami R., Elhoseny M., Gunasekaran M., An efficient swarm-intelligence approach for task scheduling in cloud-based internet of things applications, Journal of Ambient Intelligence and Humanized Computing, 2018; Rao H., Shi X., Kouassi Rodrigue A., Feng J., Xia Y., Elhoseny M., Yuan X., Gu L., Feature selection based on artificial bee colony and gradient boosting decision tree, Applied Soft Computing, (2018)","Q. Yuan; Department of Finance and Economics, Shandong University of Science and Technology, Jinan, China; email: Tiger_yuan@163.com",null,"IOS Press",{"$nulls":5},1.0641246E7,null,null,null,"English","J. Intelligent Fuzzy Syst.","Article","Final",null,"Scopus","2-s2.0-85073744240"]
["Papagiannidis S.; Bourlakis M.; See-To E.","Papagiannidis, Savvas (8848778400); Bourlakis, Michael (6506844873); See-To, Eric (16403237500)","8848778400; 6506844873; 16403237500","Social media in supply chains and logistics: Contemporary trends and themes",2019.0,"International Journal of Business Science and Applied Management",14.0,1.0,null,17.0,34.0,17.0,3.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85088009254&partnerID=40&md5=7d62ff13e36afe8134ec7110b008e2ea","Department of Computing and Decision Sciences, Lingnan University, 8 Castle Peak Rd, Tuen Mun, Hong Kong; Procurement & Supply Chain Management Group, Cranfield School of Management, Cranfield University Bedford, Cranfield, MK43 0AL, United Kingdom; David Goldman Professor of Innovation and Enterprise, Newcastle University Business School, Newcastle University, 5 Barrack Road, Newcastle upon Tyne, NE1 4SE, United Kingdom","Papagiannidis S., David Goldman Professor of Innovation and Enterprise, Newcastle University Business School, Newcastle University, 5 Barrack Road, Newcastle upon Tyne, NE1 4SE, United Kingdom; Bourlakis M., Procurement & Supply Chain Management Group, Cranfield School of Management, Cranfield University Bedford, Cranfield, MK43 0AL, United Kingdom; See-To E., Department of Computing and Decision Sciences, Lingnan University, 8 Castle Peak Rd, Tuen Mun, Hong Kong","Although social media have been employed in various business and management scientific domains, their use and role in relation to supply chains has been scant. This paper addresses the gap and adds to this body of knowledge by providing new data and original insights and by showcasing emerging, contemporary trends and themes. Over a period of 4 months we downloaded tweets that contained the #supplychain and/or the #logistics hashtags. After cleaning the data and filtering tweets in English we analysed 76,378 posts, using different analytical techniques. Our work shows the key trends emerging where various supply chain management technologies play a dominant role. Blockchain is the leading technology followed by artificial intelligence. The increased role of last mile logistics is also shown which can be related to e-commerce and customer service. Supply chain technologies are also clustered and interlinked in a related dendrogram and, automation is linked to robots and robotics, analytics is linked to data, artificial intelligence is linked to IoT and machine learning. Similar interlinkages are illustrated for other trends impacting contemporary supply chains. This research provides direction to supply chain managers for the key trends and themes emerging in their profession, and a new graph-based measure to understand the topology of the social media mindset landscape. In turn, such trends can offer valuable insights as to how the industry is developing and help proactively identify areas of potential investment. © 2019, International Journal of Business Science and Applied Management. All rights reserved.","Contemporary trends and themes; Logistics; Social media; Supply chain management; Tweets",{"$nulls":7},"Aleahmad A., Karisani P., Rahgozar M., Oroumchian F., OLFinder: Finding opinion leaders in online social networks, Journal of Information Science, 42, 5, pp. 659-674, (2015); Ballou R. 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M., Trends in transportation and logistics, European Journal of Operational Research, 264, pp. 830-836, (2018); Storey J., Emberson C., Godsell J., Harrison A., Supply chain management: Theory, practice and future challenges, International Journal of Operations & Production Management, 26, 7, pp. 754-774, (2006); Tan K. H., Zhan Y., Ji G., Ye F., Chang C. M., Harvesting big data to enhance supply chain innovation capabilities: An analytic infrastructure based on deduction graph, International Journal of Production Economics, 165, pp. 223-233, (2015); Tapscott D., Tapscott A., How Blockchain Will Change Organizations, MIT Sloan Management Review, 58, 2, pp. 10-13, (2017); Treiblmaier H., The impact of the blockchain on the supply chain: a theory-based research framework and a call for action, Supply Chain Management: An International Journal, 23, 6, pp. 545-559, (2018); Waller M. A., Fawcett S. E., Data Science, Predictive Analytics, and Big Data: A Revolution That Will Transform Supply Chain Design and Management, Journal of Business Logistics, 34, 2, pp. 77-84, (2013); Wang G., Gunasekaran A., Ngai E. W. T., Papadopoulos T., Big data analytics in logistics and supply chain management: Certain investigations for research and applications, International Journal of Production Economics, 176, pp. 98-110, (2016)","S. Papagiannidis; David Goldman Professor of Innovation and Enterprise, Newcastle University Business School, Newcastle University, Newcastle upon Tyne, 5 Barrack Road, NE1 4SE, United Kingdom; email: savvas.papagiannidis@ncl.ac.uk",null,"International Journal of Business Science and Applied Management",{"$nulls":5},1.7530296E7,null,null,null,"English","Int. J. Bus. Sci. Appl. Manage.","Article","Final",null,"Scopus","2-s2.0-85088009254"]
["Vaziri S.; Etebari F.; Vahdani B.","Vaziri, Sh. (57202238045); Etebari, F. (55539892200); Vahdani, B. (26644463900)","57202238045; 55539892200; 26644463900","Development and optimization of a horizontal carrier collaboration vehicle routing model with multi-commodity request allocation",2019.0,"Journal of Cleaner Production",224.0,null,null,492.0,505.0,13.0,35.0,"10.1016/j.jclepro.2019.02.043","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85063433327&doi=10.1016%2fj.jclepro.2019.02.043&partnerID=40&md5=11eed2be20de6edec555f38a787982c2","Department of Industrial Engineering, Faculty of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran","Vaziri S., Department of Industrial Engineering, Faculty of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran; Etebari F., Department of Industrial Engineering, Faculty of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran; Vahdani B., Department of Industrial Engineering, Faculty of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran","This paper proposes a new Vehicle Routing Problem (VRP) with fair Carrier Collaboration (CC) which split multi-pickup and delivery services are considered for serving customers. This study has focused on VRP and serving customers with several commodity requirements from different geographically scattered suppliers subject to constraints on the vehicle capacity. A Mixed Integer Programming (MIP) model to maximize the total profit and the fair sharing of profit among the carriers by considering the travel time minimization is developed. Each carrier with its limited capacity can have reserved requests which must be served by itself and selective requests which can be served by itself or other vehicles or not served at all. There are various applications of the proposed model in the environment which can help reducing number of vehicles serving to the customers and eliminating empty back hauls. A Genetic Algorithm (GA) is proposed to solve this problem due to its Non-deterministic Polynomial-time hard (NP-hard) nature. In addition, Variable Neighbourhood Search (VNS) method is developed for improving the quality of initial solutions. Some instances are generated at different scales to evaluate the algorithm's performance by comparing the results of an exact optimal solution with that of the proposed algorithm. The obtained results demonstrate the efficiency of the proposed algorithm in providing reasonable solutions within an acceptable computational time. The algorithm is also tested for an online shopping website in Tehran, Iran. The test outcome shows that the proposed model returns a better benefit compared to the manual methods. The results of sensitivity analysis suggest that increasing the fairness coefficient among carries can led to a decrease in the total obtained profit. © 2019","Carrier collaboration; Fair sharing of profit; Multi-commodity service; Pickup and delivery; Variable neighbourhood search; Vehicle routing","Computational efficiency; Electronic commerce; Genetic algorithms; Pickups; Polynomial approximation; Profitability; Sales; Sensitivity analysis; Travel time; Vehicle routing; Vehicles; Carrier collaboration; Fair sharing; Multi-commodity; Pickup and delivery; Variable neighbourhood search; Integer programming",{"$nulls":6},"Azadian F., Murat A., Chinnam R.B., An unpaired pickup and delivery problem with time dependent assignment costs: application in air cargo transportation, Eur. J. Oper. Res., 263, 1, pp. 188-202, (2017); Baldacci R., Bartolini E., Mingozzi A., An exact algorithm for the pickup and delivery problem with time windows, Oper. 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Ind. Eng., 99, pp. 300-313, (2016); Chen H., Combinatorial clock-proxy exchange for carrier collaboration in less than truck load transportation, Transport. Res. E Logist. Transport. Rev., 91, pp. 152-172, (2016); Cherkesly M., Desaulniers G., Irnich S., Laporte G., Branch-price-and-cut algorithms for the pickup and delivery problem with time windows and multiple stacks, Eur. J. Oper. Res., 250, 3, pp. 782-793, (2016); Chu C.W., A heuristic algorithm for the truckload and less-than-truckload problem, Eur. J. Oper. Res., 165, 3, pp. 657-667, (2005); Cordeau J.F., Laporte G., Savelsbergh M.W.P., Vigo D., Chapter 6 vehicle routing, Handb. Oper. Res. Manag. Sci., 14, pp. 367-428, (2007); Cruijssen F., Cools M., Dullaert W., Horizontal cooperation in logistics: opportunities and impediments, Transport. Res. E Logist. Transport. Rev., 43, 2, pp. 129-142, (2007); Dai B., Chen H., A multi-agent and auction-based framework and approach for carrier collaboration, Logist. Res., 3, 2-3, pp. 101-120, (2011); Dai B., Chen H., Profit allocation mechanisms for carrier collaboration in pickup and delivery service, Comput. Ind. Eng., 62, 2, pp. 633-643, (2012); Dai B., Chen H., Yang G., Price-setting based combinatorial auction approach for carrier collaboration with pickup and delivery requests, Oper. Res., 14, 3, pp. 361-386, (2014); Dantzig G.B., Ramser J.H., The truck dispatching problem, Manag. Sci., 6, 1, pp. 80-91, (1959); Dror M., Trudeau P., Savings by split delivery routing, Transport. Sci., 23, 2, pp. 141-145, (1989); Dib O., Moalic L., Manier M.A., Caminada A., An advanced GA–VNS combination for multicriteria route planning in public transit networks, Expert Syst. Appl., 72, pp. 67-82, (2017); Eksioglu B., Vural A.V., Reisman A., The vehicle routing problem: a taxonomic review, Comput. Ind. Eng., 57, 4, pp. 1472-1483, (2009); Fernandez E., Roca-Riu M., Speranza M.G., The shared customer collaboration vehicle routing problem, Eur. J. Oper. 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["van der Gaast J.P.; de Koster R.B.M.; Adan I.J.B.F.","van der Gaast, J.P. (56160211600); de Koster, René B. M. (6603607097); Adan, Ivo J. B. F. (7004197715)","56160211600; 6603607097; 7004197715","Optimizing product allocation in a polling-based milkrun picking system",2019.0,"IISE Transactions",51.0,5.0,null,486.0,500.0,14.0,10.0,"10.1080/24725854.2018.1493758","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85060107818&doi=10.1080%2f24725854.2018.1493758&partnerID=40&md5=b9bb301d13831d92a1b4ca6b7fa478fe","Department of Operations, Faculty of Economics and Business, University of Groningen, Groningen, Netherlands; Department of Technology and Operations Management, Rotterdam School of Management, Erasmus University of Rotterdam, Rotterdam, Netherlands; Department of Operations Planning Accounting & Control, Industrial Engineering & Innovation Sciences, Eindhoven University of Technology, Eindhoven, Netherlands","van der Gaast J.P., Department of Operations, Faculty of Economics and Business, University of Groningen, Groningen, Netherlands; de Koster R.B.M., Department of Technology and Operations Management, Rotterdam School of Management, Erasmus University of Rotterdam, Rotterdam, Netherlands; Adan I.J.B.F., Department of Operations Planning Accounting & Control, Industrial Engineering & Innovation Sciences, Eindhoven University of Technology, Eindhoven, Netherlands","E-commerce fulfillment competition evolves around cheap, speedy, and time-definite delivery. Milkrun order picking systems have proven to be very successful in providing handling speed for a large, but highly variable, number of orders. In this system, an order picker picks orders that arrive in real-time during the picking process; by dynamically changing the stops on the picker’s current picking route. The advantage of milkrun picking is that it reduces order picking set-up time and worker travel time compared with conventional batch picking systems. This article is the first to study order throughput times of multi-line orders in a milkrun picking system. We model this system as a cyclic polling system with simultaneous batch arrivals, and determine the mean order throughput time for three picking strategies: exhaustive, locally-gated, and globally-gated. These results allow us to study the effect of different product allocations in an optimization framework. We show that the picking strategy that achieves the shortest order throughput times depends on the ratio between pick times and travel times. In addition, for a real-world application, we show that milkrun order picking significantly reduces the order throughput time compared with conventional batch picking. © 2019, © 2019 The Author(s). Published with license by Taylor & Francis Group, LLC.","facility logistics; optimization; queueing theory; stochastic models; Warehousing","Logistics; Optimization; Queueing theory; Stochastic systems; Throughput; Travel time; Warehouses; Batch arrivals; Cyclic polling; Facility logistics; Optimization framework; Order-picking systems; Product allocations; Throughput time; Warehousing; Stochastic models",{"$nulls":6},"Boon M.A.A., van der Mei R.D., Winands E.M.M., Applications of polling systems, Surveys in Operations Research and Management Science, 16, 2, pp. 67-82, (2011); Boon M.A.A., van Wijk A.C.C., Adan I.J.B.F., Boxma O.J., A polling model with smart customers, Queueing Systems, 66, 3, pp. 239-274, (2010); Bottani E., Cecconi M., Vignali G., Montanari R., Optimisation of storage allocation in order picking operations through a genetic algorithm, International Journal of Logistics Research and Applications, 15, 2, pp. 127-146, (2012); Bozer Y.A., Ciemnoczolowski D.D., Performance evaluation of small-batch container delivery systems used in lean manufacturing–Part 1: System stability and distribution of container starts, International Journal of Production Research, 51, 2, pp. 555-567, (2013); 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Garfinkel M., Minimizing multi-zone orders in the correlated storage assignment problem, (2005); Goldberg D.E., Lingle R., Alleles, loci, and the traveling salesman problem, Proceedings of the First International Conference on Genetic Algorithms and their Applications, pp. 154-159, (1985); Gong Y., de Koster M.B.M., A polling-based dynamic order picking system for online retailers, IIE Transactions, 40, 11, pp. 1070-1082, (2008); Gong Y., de Koster M.B.M., A review on stochastic models and analysis of warehouse operations, Logistics Research, 3, 4, pp. 191-205, (2011); Hanson R., Finnsgard C., Impact of unit load size on in-plant materials supply efficiency, International Journal of Production Economics, 147, A, pp. 46-52, (2014); Kilic H.S., Durmusoglu M.B., A mathematical model and a heuristic approach for periodic material delivery in lean production environment, The International Journal of Advanced Manufacturing Technology, 69, 5-8, pp. 977-992, (2013); Kim K.H., A joint determination of storage locations and space requirements for correlated items in a miniload automated storage-retrieval system, International Journal of Production Research, 31, 11, pp. 2649-2659, (1993); 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Van den Berg J.P., A literature survey on planning and control of warehousing systems, IIE Transactions, 31, 8, pp. 751-762, (1999); Van der Gaast J.P., Adan I.J.B.F., de Koster R.B.M., The analysis of batch sojourn-times in polling systems, Queueing Systems, 85, 3, pp. 313-335, (2017); Whitley L.D., Starkweather T., Scheduling problems and traveling salesmen: The genetic edge recombination operator, Proceedings of the Third International Conference on Genetic Algorithms, pp. 133-140, (1989); Wolff R.W., Poisson arrivals see time averages, Operations Research, 30, 2, pp. 223-231, (1982); Xiao J., Zheng L., Correlated storage assignment to minimize zone visits for BOM picking, The International Journal of Advanced Manufacturing Technology, 61, 5-8, pp. 797-807, (2011)","J.P. van der Gaast; Department of Operations, Faculty of Economics and Business, University of Groningen, Groningen, Netherlands; email: j.p.van.der.gaast@rug.nl",null,"Taylor and Francis Ltd.",{"$nulls":5},2.4725854E7,null,null,null,"English","IISE Trans.","Article","Final","All Open Access; Green Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85060107818"]
["Wei Q.; Li S.; Gou X.; Huo B.","Wei, Qiang (57204766918); Li, Sheng (58374692800); Gou, Xinyu (57204774709); Huo, Baofeng (24067029800)","57204766918; 58374692800; 57204774709; 24067029800","Joint optimal decision of the shared distribution system through revenue-sharing and cooperative investment contracts",2019.0,"Industrial Management and Data Systems",119.0,3.0,null,578.0,612.0,34.0,5.0,"10.1108/IMDS-07-2018-0285","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85057134151&doi=10.1108%2fIMDS-07-2018-0285&partnerID=40&md5=ef3c247fa810e8a380b4eb1df44bc8e4","School of Statistics, Southwestern University of Finance and Economics, Chengdu, China; School of Management, Chengdu University of Traditional Chinese Medicine, Chengdu, China; School of Business Administration, Southwestern University of Finance and Economics, Chengdu, China; College of Management and Economics, Tianjin University, Tianjin, China","Wei Q., School of Statistics, Southwestern University of Finance and Economics, Chengdu, China; Li S., School of Statistics, Southwestern University of Finance and Economics, Chengdu, China, School of Management, Chengdu University of Traditional Chinese Medicine, Chengdu, China; Gou X., School of Business Administration, Southwestern University of Finance and Economics, Chengdu, China; Huo B., College of Management and Economics, Tianjin University, Tianjin, China","Purpose: The rapid development of e-commerce has caused not only explosive growth of the express delivery industry, but also ever-greater operational pressures. Models from the sharing economy may provide new ideas for operational improvement. The purpose of this paper is to consider an optimization method that reduces costs and increases efficiency. The proposed method enables a shared distribution system based on revenue-sharing and cooperative investment contracts. Design/methodology/approach: The authors design a two-echelon supply chain (SC) of the shared distribution system with one shared distribution company and N express companies. In this SC, the express companies provide only inter-city transportation, and they outsource internal-city transportation to a shared distribution company. This distribution system differs from that of the traditional express delivery industry. The traditional system of delivery requires large numbers of empty trips (with no load to deliver), because the operating mode of urban distribution has been the franchise. To offer greater efficiency and performance, the authors introduce the sharing economy mode of express delivery. The authors examine the potential of a joint optimal decision-making strategy that involves revenue-sharing and cooperative investment contracts based on an order flow proportion (OFP) and a revenue-sharing factor (RSF). In this shared distribution system, the most important innovation is that all of the express companies jointly invest in and establish a shared distribution company based on OFP or RSF principles. Findings: The profitability of an SC with revenue-sharing contracts based on an OFP system is much higher than that of a decentralized SC, and it is very close to the profitability of a centralized SC. In SCs with revenue-sharing contracts that are based on RSFs, there are many possible combinations of RSFs that can increase the overall profitability. The analyses indicate that the OFP system offers the best solution in designing revenue-sharing contracts based on RSFs. Practical implications: This study indicates that revenue-sharing contracts based on both OFP and RSF principles can increase overall SC returns by 0.21 to 0.44 percent. In sum total, this improvement could mean a 0.84 to 1.76bn Yuan increase in revenues for the 400+ bn-Yuan express delivery industry. Originality/value: The authors find that a combination of equity investment and SC coordination contracts makes the cooperation between SC members much more stable. Through this kind of shared distribution system, the scale of economy can further reduce the costs and increase the efficiency of the express delivery industry. © 2018, Emerald Publishing Limited.","Cooperative investment; OFP; Revenue-sharing; RSF; Shared distribution system; Supply chain coordination","Cost reduction; Decision making; Efficiency; Profitability; Supply chains; Cooperative investments; Design/methodology/approach; Distribution systems; Efficiency and performance; Operational improvements; Revenue sharing contracts; Revenue-sharing; Supply chain coordination; Investments",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (71525005); Fundamental Research Funds for the Central Universities, (JBK1507105)","This research was supported by Fundamental Research Funds for the Central Universities ( JBK1507105) and National Natural Science Foundation of China (#71525005).","Agrawal S., Sengupta R.N., Shanker K., Impact of information sharing and lead time on bullwhip effect and on-hand inventory, European Journal of Operational Research, 192, 2, pp. 576-593, (2009); 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Wakolbinger T., Cruz J.M., Supply chain disruption risk management through strategic information acquisition and sharing and risk-sharing contracts, International Journal of Production Research, 49, 13, pp. 4063-4084, (2011); Wang Y., Jiang L., Shen Z.J., Channel performance under consignment contract with revenue sharing, Management Science, 50, 1, pp. 34-47, (2004); Wu C., Wang Y., Zhu T., Mobile hailing technology, worker productivity and digital inequality: a case of the taxi industry, (2016); Xiao T., Risk sharing and information revelation mechanism of a one-manufacturer and one-retailer supply chain facing an integrated competitor, European Journal of Operational Research, 196, 3, pp. 1076-1085, (2009); Yang H., Chen W., Retailer-driven carbon emission abatement with consumer environmental awareness and carbon tax: revenue-sharing versus cost-sharing, Omega, 78, C, pp. 179-191, (2017); Yungao M.A., Nengmin W., Ada C., Yufei H., Jinpeng X., The bullwhip effect under different information-sharing settings: a perspective on price-sensitive demand that incorporates price dynamics, International Journal of Production Research, 51, 10, pp. 3085-3116, (2013); Zervas G., Proserpio D., Byers J.W., The rise of the sharing economy: estimating the impact of Airbnb on the hotel industry, Journal of Marketing Research, 54, 5, pp. 687-705, (2017); Zhang J., Liu G., Zhang Q., Bai Z., Coordinating a supply chain for deteriorating items with a revenue sharing and cooperative investment contract, Omega, 56, 3, pp. 37-49, (2015); Zhang Y., Donohue K.L., Cui T.H., Contract preferences and performance for the loss-averse supplier: buyback versus revenue sharing, Management Science, 62, pp. 1734-1754, (2012)","B. Huo; College of Management and Economics, Tianjin University, Tianjin, China; email: baofeng@tju.edu.cn",null,"Emerald Group Holdings Ltd.",{"$nulls":5},2635577.0,null,"IMDSD",null,"English","Ind Manage Data Sys","Article","Final",null,"Scopus","2-s2.0-85057134151"]
["Huang K.; Ardiansyah M.N.","Huang, Kuancheng (17344127000); Ardiansyah, Muhammad Nashir (56369220300)","17344127000; 56369220300","A decision model for last-mile delivery planning with crowdsourcing integration",2019.0,"Computers and Industrial Engineering",135.0,null,null,898.0,912.0,14.0,48.0,"10.1016/j.cie.2019.06.059","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85068251927&doi=10.1016%2fj.cie.2019.06.059&partnerID=40&md5=2041acf17d5e4e5b67462ae99dc808b4","Department of Transportation and Logistics Management, National Chiao Tung University, 1001 Ta-Hsueh Road, Hsinchu, 30010, Taiwan","Huang K., Department of Transportation and Logistics Management, National Chiao Tung University, 1001 Ta-Hsueh Road, Hsinchu, 30010, Taiwan; Ardiansyah M.N., Department of Transportation and Logistics Management, National Chiao Tung University, 1001 Ta-Hsueh Road, Hsinchu, 30010, Taiwan","Crowdsourced transportation has been playing a more important role when faced with the growing demand for last-mile delivery, mainly due to the booming e-commerce. Crowdsourced delivery offers greater flexibility and requires less capital investment than traditional outsourcing approaches. This study deals with the planning of the last-mile delivery with partial crowdsourcing integration, in which crowdsourcing helps to manage the delivery from a transfer point to final customer locations. The decision involves several basic questions, including which customer is to be outsourced, by which outsourcing partner, and at which transfer point. The decision problem is formulated as a mixed integer programing (MIP) model. In addition, a heuristics algorithm has been designed to handle large-scale problems. Based on the numerical experiment, the heuristics algorithm can generate a good quality solution within an acceptable computation time. In general, this study shows that well-planned crowdsourcing integration can take advantage of the flexibility and cost saving of crowdsourcing for last-mile delivery. © 2019","Crowdsourced delivery; Last-mile delivery; Mixed integer programming; Tabu search heuristics; Two echelon routing problem","Decision theory; Heuristic algorithms; Integer programming; Integration; Investments; Tabu search; Crowdsourced delivery; Last mile; Mixed integer programming; Routing problems; Tabu search heuristics; Crowdsourcing",{"$nulls":6},"Akeb H., Moncef B., Durand B., Building a collaborative solution in dense urban city settings to enhance parcel delivery: An effective crowd model in Paris, Transportation Research Part E: Logistics and Transportation Review, 119, pp. 223-233, (2018); Allen A.J., Browne M., Jones P., A framework for considering policies to encourage sustainable urban freight traffic and goods/service flows: Summary report, (2000); Augerat P., Polyhedral approach of vehicle routing problem, (1995); Barbarosoglu G., Ozgur D., A tabu search algorithm for the vehicle routing problem, Computers & Operations Research, 26, pp. 255-270, (1999); Belgin O., Karaoglan I., Altiparmak F., Two-echelon vehicle routing problem with simultaneous pickup and delivery: Mathematical model and heuristic approach, Computer & Industrial Engineering, 115, pp. 1-16, (2018); Carbone V., Rouquet A., Roussat C., The rise of crowd logistics: A new way to co-create logistics value, Journal of Business Logistics, pp. 1-15, (2017); Cardenas I., Beckers J., Vanelslander T., E-commerce last-mile in Belgium: Developing an external cost delivery index, Research in Transportation Business & Management, 24, pp. 123-129, (2017); Chao I.M., A tahu search method for the truck and trailer routing problem, Computer & Operations Research, 29, 1, pp. 33-51, (2002); Chen C., Pan S., Using the crowd of taxis to last mile delivery in e-commerce: A methodological research, Service orientation in holonic and multi-agent manufacturing, pp. 61-70, (2016); Christofides N., Mingozzi A., Toth P., Sandi C., Combinatorial optimization, (1979); Cuda R., Guastaroba G., Speranza M., A survey on two-echelon routing problems, Computers & Operations Research, 55, pp. 185-199, (2015); Devari A., Nikolaev A.G., He Q., Crowdsourcing the last mile delivery of online orders by exploiting the social networks of retail store customers, Transportation Research Part E, pp. 105-122, (2017); (2018); Ghiani G., Laporte G., Musmanno R., Introductino to logistics system planning and control, (2004); Glover F., Future paths for integer programming and links to artificial intelligence, Computers & Operations Research, 13, 5, pp. 533-549, (1986); (2019); Huang K., Wu K.-F., Ardiansyah M.N., A stochastic dairy transportation problem considering collection and delivery phases, Transportation Research Part E, (2018); Hurkens C.O.A., Woeginger G.J., On the nearest neighbor rule for the traveling salesman problem, Operations Research Letters, 32, 1, pp. 1-4, (2004); Kafle N., Zou B., Lin J., Design and modeling of a crowdsource-enabled system for urban parcel relay and delivery, Transportation Research Part B, pp. 62-82, (2017); Nguyen V.-P., Prins C., Prodhon C., Solving the two-echelon location routing problem by a GRASP reinforced by a learning process and path relinking, European Journal of Operational Research, 216, pp. 113-126, (2012); Pichka K., Bajgiran A.H., Petering M.E.H., Jang J., Yue X., The two-echelon open location routing problem: Mathematical model and hybrid heuristic, Computer & Industrial Engineering, 121, pp. 97-112, (2018); Rouges J.-F., Montreuil B., Crowdsourcing delivery: New interconnected business models to reinvent delivery, 1st International physical internet conference. Quebec City, (2014); Scheuerer S., A tabu search heuristics for the truck and trailer routing problem, Computer & Operation Research, 33, 4, pp. 894-909, (2006); Slabinac M., Innovative solutions for a last-mile delivery - a European experience, 15th International scientific conference business logistics in modern management, Osijek, Croatia, pp. 111-130, (2015); Su H., Zhen K., Huang J., Jeung H., Chen L., Zhou X., CrowdPlanner: A crowd-based route recommendation system, (2014); Wang J., Jagannathan A.K.R., Zuo X., Murray C.C., Two-layer simulated annealing and tabu search heuristics for a vehicle routing problem with cross docks and split deliveries, Computers & Industrial Engineering, 112, pp. 84-98, (2017); Wang Y., Zhang D., Liu Q., Shen F., Lee L.H., Towards enhancing the last-mile delivery: An effective crowd-tasking model with scalable solutions, Transportation Research Part E, 93, pp. 279-293, (2016); Willard J., Vehicle routing using r-optimal tabu search. M.Sc. Dissertation, The management school, (1989)","K. Huang; Department of Transportation and Logistics Management, National Chiao Tung University, Hsinchu, 1001 Ta-Hsueh Road, 30010, Taiwan; email: kchuang@cc.nctu.edu.tw",null,"Elsevier Ltd",{"$nulls":5},3608352.0,null,"CINDD",null,"English","Comput Ind Eng","Article","Final",null,"Scopus","2-s2.0-85068251927"]
["Moksin H.; Fung K.I.; Ahmad S.N.B.; Nazri S.M.","Moksin, Hanifah (57211237792); Fung, Kong Ing (57211244424); Ahmad, Siti Nor Bayaah (57196197201); Nazri, Syahida Mohd (57211240585)","57211237792; 57211244424; 57196197201; 57211240585","Consumer's repurchase behavior intention in online shopping: A Malaysian perspective",2019.0,"International Journal of Innovation, Creativity and Change",6.0,3.0,null,339.0,350.0,11.0,1.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85073109028&partnerID=40&md5=604a0e37465de96947827554f7c40637","Faculty of Business and Technology, UNITAR International University, Malaysia; Faculty of Education and Humanities, UNITAR International University, Malaysia","Moksin H., Faculty of Business and Technology, UNITAR International University, Malaysia; Fung K.I., Faculty of Business and Technology, UNITAR International University, Malaysia; Ahmad S.N.B., Faculty of Business and Technology, UNITAR International University, Malaysia; Nazri S.M., Faculty of Education and Humanities, UNITAR International University, Malaysia","The retail industry is going through a transformation largely driven by the influence of digital technology on the shopping experience. The digital age has changed consumer's purchasing behavior, shifting them away from physical stores to online stores. E-commerce has gained popularity among consumers due to the rapid development of the internet. Earlier studies have shown that perceived risks namely product risk, financial risk, non-delivery risk and convenience risk influence consumers in shopping online. The objective of this study was to investigate the influence of perceived risks defined as Perceived Product Risk (PPR), Perceived Financial Risk (PFR), Perceived Convenience Risk (PCR) and Perceived Non-Delivery Risk (PNDR) in online consumer's repurchase behavior. The online survey using close-ended questionnaire was distributed to two Buy and Sell groups from a famous online social platform, Facebook. A total of 200 valid samples were collected using convenience sampling methodology. Data analysis was conducted using SPSS version 20.0. The findings indicate that Perceived Non-Delivery Risk and Perceived Financial Risk had a moderate impact on Malaysian online consumer's repurchase behavior while Perceived Product Risk and Perceived Convenience Risk did not have any significant impact on Malaysian online consumer repurchase behavior. © 2019 Primrose Hall Publishing Group.","Consumer's perceived risks; Consumer's repurchase behavior; E-commerce; Perceived convenience risk",{"$nulls":7},"Afthanorhan A., Awang Z., Rashid N., Foziah H., Ghazali P., Assessing the effects of service quality on customer satisfaction, Management Science Letters, 9, 1, pp. 13-24, (2019); Al Kailani M., Kumar R., Investigating Uncertainty Avoidance and Perceived Risk for Impacting Internet Buying: A Study in Three National Cultures, International Journal of Business and Management, 6, 5, pp. 76-92, (2011); Al-Mhasnah A., Salleh F., Afthanorhan A., Ghazali P., The relationship between services quality and customer satisfaction among Jordanian healthcare sector, Management Science Letters, 8, 12, pp. 1413-1420, (2018); Celik H., Influence of social norm, perceived playfulness and online shopping anxiety on customer's adoption of online retail shopping: an empirical study in the Turkish context, International Journal of Retail & Distribution Management, 39, 6, pp. 390-413, (2011); Chiu Y.B., Lin C.P., Tang L.L., Gender differs: assessing a model of online purchases intentions in e-tail service, Int. J. Service Industry Manag, 16, 5, (2005); Dick A.S., Basu K., Customer loyalty: Toward an integrated conceptual framework, Journal of the Academy of Marketing Science, 22, 2, pp. 99-113, (1994); Fishbein M., Ajzen I., Belief, Attitude, Intention and Behavior: An Introduction to Theory and Research, (1975); Forsythe S., Liu C.L., Shannon D., Gardner L.C., Development of a scale to measure the perceived benefits and riks of online shopping, Journal of Interactive Marketing, 20, 2, pp. 55-75, (2006); George J.F., The Theory of Planned Behavior and Internet Purchasing, Journal of Internet Research, 14, 3, pp. 198-212, (2004); Hanjun K., Jaemin J.K.J.Y.S.W.S., Cross-cultural differences in perceived risk of online shopping, Journal of Interactive Advertising, 4, 2, pp. 20-29, (2004); Huang, Oppewal, Why consumers hesitate to shop online: An experimental choice analysis of grocery shopping and the role of delivery fees, International Journal of Retail & Distribution Mangement, 13, 4-5, (2006); Hume M., Winzar, Exploring repurchase intention in a performing arts context: Who comes?. And why do they come back, International Journal of Non Profit & Voluntary Sector Marketing, (2007); Javadi M., Dolatabadi H., Nourbakhsh M., Poursaeedi A., Asodollahi A., An Analysis of Factors Affecting on Online Shopping Behavior of Consumers, International Journal of Marketing Studies, 4, 5, pp. 81-89, (2012); Jermsittiparsert K., Sriyakul T., Pamornmast C., Minimum Wage and Country's Economic Competitiveness: An Empirical Discourse Analysis, The Social Sciences, 9, 4, pp. 244-250, (2014); Khan R.E.A., Aslam I., Child immunization in Pakistan: Socio-institutional and regional aspects, Asian Journal of Economic Modelling, 5, 1, pp. 49-56, (2017); Khan Y., Hassan T., Yi W.M., Gulzar R., A Comparative Analysis Based on Economic Factors of Students Emigration from South Asia, Asian Journal of Economics and Empirical Research, 5, 2, pp. 201-208, (2018); Khalid N., Pahi M.H., Ahmed U., Loosing your best talent: Can leadership retain employees? The dilemma of the banking sector of Hyderabad Sindh, Pakistan: A mediation investigation, International Review of Management and Marketing, 6, 3, pp. 608-616, (2016); Khonamri F., Azizi M., Fallahpour S., The Effect of Focus of Strategic Planning on Accuracy and Complexity in Argumentative Writing of Intermediate L2 Learners, International Journal of Asian Social Science, 7, 6, pp. 489-496, (2017); Kim I., Consumers' rankings of risk reduction strategies in e-shopping, International Journal of Business Research, 10, 3, pp. 143-148, (2010); Law H., Zhao, Modeling repurchase frequency & customer satisfaction for fast food outlets, International Journal of Quality & Reliability Management, 21, 5, (2004); Masoud E.Y., The Effect of Perceived Risk on Online Shopping in Jordan, European Journal of Business and Management, 5, 6, pp. 76-87, (2013); Perner L., Consumer behavior and marketing strategy, (2008); Peyrot, Doren, Effect of a Class Action Suit on Consumer Repurchase Intentions, The Journal of Consumer Affairs, (1994); Saprikis V., Chouliara A., Vlachopoulou K.M., Perception towards online shopping: Analyzing the Greek University students' attitude, Communications of the IBIMA, 2010, pp. 1-13, (2010); Syed Z.H., Nilufar, Young consumer online shopping: An empirical study, Journal of Internet Business, 5, pp. 81-98, (2008); Tanadi T., Samadi B., Gharleghi B., The impact of perceived risks and perceived benefits to improve an online intention among Generation Y in Malaysia, Asian Social Science, 11, 26, pp. 226-237, (2015); Turban, Et al., Electronic Commerce A Managerial Perspective, (2008); Wu W.Y., Lee C.L., Fu C.S., Wang H.C., How can online store layout design and atmosphere influence consumer shopping intention on website, International Journal of Retail & Distribution Mangement, 42, 1, pp. 4-24, (2014); Yang B., Lester D., James S., Attitudes toward buying online as predictors of shopping online for British and American respondent, Cyber Psychology & Behavior 2007, 10, 2, pp. 198-203, (2007); Zhang L., Tan W., Xu Y., Tan G., Dimensions of consumers' perceived risk and their influences on online consumers' purchasing behavior, Communications in information science and management engineering, 2, 7, pp. 8-14, (2012)","H. Moksin; Faculty of Business and Technology, UNITAR International University, Malaysia; email: hanifahm@unitar.my",null,"Primrose Hall Publishing Group",{"$nulls":5},2.2011315E7,null,null,null,"English","Int. J. Innov. Creat. Change","Article","Final",null,"Scopus","2-s2.0-85073109028"]
["Jansi Rani K.; Catherine R.; Saillaja V.","Jansi Rani, K. (57211398285); Catherine, R. (57211395558); Saillaja, V. (57210440642)","57211398285; 57211395558; 57210440642","A study on service strategies used by online food apps and their impact on customers",2019.0,"Journal of Advanced Research in Dynamical and Control Systems",11.0,"9 Special Issue",null,1390.0,1395.0,5.0,0.0,"10.5373/JARDCS/V11/20192754","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85075695506&doi=10.5373%2fJARDCS%2fV11%2f20192754&partnerID=40&md5=ebd643dc24593ee011c1be86e12a157f","Department of Commerce and Economics, Faculty of Arts and Science, BIHER, Bharath Institute of Higher Education & Research, Selaiyur, Chennai, India","Jansi Rani K., Department of Commerce and Economics, Faculty of Arts and Science, BIHER, Bharath Institute of Higher Education & Research, Selaiyur, Chennai, India; Catherine R., Department of Commerce and Economics, Faculty of Arts and Science, BIHER, Bharath Institute of Higher Education & Research, Selaiyur, Chennai, India; Saillaja V., Department of Commerce and Economics, Faculty of Arts and Science, BIHER, Bharath Institute of Higher Education & Research, Selaiyur, Chennai, India","The current status and situation shows the growth in use of internet and mobile phones. Increasing use of mobile phones and internet leads to digital acting like online shopping, mobile payment, smart marketers use this opportunity and developed many new applications to serve the online customers. In food industry food delivery apps makes huge impact in the online services. This study shows the service strategies used by food delivery apps. The structured questionnaire was used as research tool for understanding the impact on customers. Data was collected from 50 respondents in south Chennai. Anova and descriptive analysis was used to analyze the responses. The main aim of the study was to analyze the service strategies and its impact on customers. And also to find out the most preferred food delivery app in south Chennai and also the factors which influence to use food delivery apps. © 2019, Institute of Advanced Scientific Research, Inc.. All rights reserved.","Food Delivery Apps; Online Service; Service Strategies",{"$nulls":7},"Udayakumar R., Khanaa V., Saravanan T., Analysis of polarization mode dispersion in fibers and its mitigation using an optical compensation technique, Indian Journal of Science and Technology, 6, pp. 4767-4771, (2013); Udayakumar R., Kumarave A., Rangarajan K., Introducing an efficient programming paradigm for objectoriented distributed systems, Indian Journal of Science and Technology, 6, pp. 4596-4603, (2013); Uma Mageswaran S., Guna Sekhar N.O., Reactive power contribution of multiple STATCOM using particle swarm optimization, International Journal of Engineering and Technology, 5, pp. 122-126, (2013); Kumar G.R., Saikia M., Multipath routing for admission control and load balancing in wireless mesh networks, International Review on Computers and Software, 8, 3, pp. 779-785, (2013); Padmapriya G., Manikandan A., Krishnasamy V., Jaganathan S.K., Antony S.A., Spinel NixZn1-xFe2O4 (0.0 ≤ x ≤ 1.0) nano-photocatalysts: Synthesis, characterization and photocatalytic degradation of methylene blue dye, Journal of Molecular Structure, 1119, pp. 39-47, (2016); Vijayaragavan S.P., Karthik B., Kiran Kumar T.V.U., Sundar Raj M., Analysis of chaotic DC-DC converter using wavelet transform, Middle-East Journal of Scientific Research, 16, pp. 1813-1819, (2013); Lokesh K., Kavitha G., Manikandan E., Mani G.K., Kaviyarasu K., Rayappan J.B.B., Ladchumananandasivam R., Aanand J.S., Jayachandran M., Maaza M., Effective ammonia detection using n-ZnO/p-NiO heterostructured nanofibers, IEEE Sensors Journal, 16, 8, pp. 2477-2483, (2016); Abraham A.G., Manikandan A., Manikandan E., Vadivel S., Jaganathan S.K., Baykal A., Renganathan P.S., Enhanced magneto-optical and photo-catalytic properties of transition metal cobalt (Co2+ ions) doped spinel MgFe2O4 ferrite nanocomposites, Journal of Magnetism and Magnetic Materials, 452, pp. 380-388, (2018); Kennedy J., Fang F., Futter J., Leveneur J., Murmu P.P., Panin G.N., Kang T.W., Manikandan E., Synthesis and enhanced field emission of zinc oxide incorporated carbon nanotubes, Diamond and Related Materials, 71, pp. 79-84, (2017); Teresita V.M., Manikandan A., Josephine B.A., Sujatha S., Antony S.A., Electromagnetic Properties and Humidity-Sensing Studies of Magnetically Recoverable LaMg x Fe 1−x O 3−δ Perovskites Nanophotocatalysts by Sol-Gel Route, Journal of Superconductivity and Novel Magnetism, 29, 6, pp. 1691-1701, (2016); Lydia Caroline M., Vasudevan S., Growth and characterization of pure and doped bis thiourea zinc acetate: Semiorganic nonlinear optical single crystals, Current Applied Physics, 9, 5, pp. 1054-1061, (2009); Jayalakshmi V., Gunasekar N.O., Implementation of discrete PWM control scheme on Dynamic Voltage Restorer for the mitigation of voltage sag /swell, 2013 International Conference on Energy Efficient Technologies for Sustainability, ICEETS 2013, pp. 1036-1040, (2013); Udayakumar R., Khanaa V., Kaliyamurthie K.P., Optical ring architecture performance evaluation using ordinary receiver, Indian Journal of Science and Technology, 6, pp. 4742-4747, (2013); Udayakumar R., Khanaa V., Kaliyamurthie K.P., Performance analysis of resilient ftth architecture with protection mechanism, Indian Journal of Science and Technology, 6, pp. 4737-4741, (2013); Saravanan T., Srinivasan V., Sandiya V.P., A two stage DC-DC converter with isolation for renewable energy applications, Indian Journal of Science and Technology, V-6, I-SUPPL.6, pp. 4824-4830, (2013); Sundarraj M., Study of compact ventilator, Middle-East Journal of Scientific Research, 16, 12, pp. 1741-1743, (2013); Thema F.T., Manikandan E., Gurib-Fakim A., Maaza M., Single phase Bunsenite NiO nanoparticles green synthesis by Agathosma betulina natural extract, Journal of Alloys and Compounds, 657, pp. 655-661, (2016); Sathyaseelan B., Manikandan E., Sivakumar K., Kennedy J., Maaza M., Enhanced visible photoluminescent and structural properties of ZnO/KIT-6 nanoporous materials for white light emitting diode (W-LED) application, Journal of Alloys and Compounds, 651, pp. 479-482, (2015); Gopalakrishnan K., Prem Jeya Kumar M., Sundeep Aanand J., Udayakumar R., Analysis of static and dynamic load on hydrostatic bearing with variable viscosity and pressure, Indian Journal of Science and Technology, V-6, I-SUPPL.6, pp. 4783-4788, (2013); Ramkumar Prabhu M., Reji V., Sivabalan A., Improved radiation and bandwidth of triangular and star patch antenna, Research Journal of Applied Sciences, Engineering and Technology, 4, pp. 1740-1748, (2012); Arumugam S., Ramareddy S., Simulation comparison of class D/ Class E inverter fed induction heating, Journal of Electrical Engineering, 12, 2, pp. 71-76, (2012); Udayakumar R., Khanaa V., Kaliyamurthie K.P., High data rate for coherent optical wired communication using DSP, Indian Journal of Science and Technology, 6, pp. 4772-4776, (2013); Nagarajan C., Madheswaran M., Experimental study and steady state stability analysis of CLL-T series parallel resonant converter with fuzzy controller using state space analysis, Iranian Journal of Electrical and Electronic Engineering, 8, 3, pp. 259-267, (2012); Gopalakrishnan K., Prem Jeya Kumar M., Sundeep Aanand J., Udayakumar R., Thermal properties of doped azopolyester and its application, Indian Journal of Science and Technology, 6, pp. 4722-4725, (2013); Thariniepandiyaraj V., Ant Colony Optimization based Latency Conscious Routing Protocol (ACO-LCRP) for Wireless Sensor Network, International Journal of Advances in Engineering and Emerging Technology, 8, 3, pp. 191-199, (2016); Chandran C., Arulgeetha G., Efficient User Revocation for Anonymity Control Cloud Data Access Privilege, International Journal of Advances in Engineering and Emerging Technology, 8, 3, pp. 209-222, (2016); Hariharan N., Karthikeyan K., Nelson M., Sangeetha K.S., Attribute based Encryption with Distributed System, International Journal of Advances in Engineering and Emerging Technology, 8, 3, pp. 223-227, (2016); Sumangala K., A Smart System for Indoor Plant Care, Journal of Computational Information Systems, 15, 1, pp. 61-64, (2019); Satheeshkumar R., Real Time Virtual Human Hand for Robotics, Journal of Computational Information Systems, 15, 1, pp. 82-89, (2019); Santhosh Kumar K., A Systematic Review on Finger Vein Recognition Techniques Based on Template Matching, Journal of Computational Information Systems, 15, 1, pp. 114-122, (2019); Priyadharshini M., Amsaveni R., Case Based Automatic Text Classification Using Semantic Relationship, International Journal of Advances in Engineering and Emerging Technology, 7, 9, pp. 586-596, (2015); Sivakumar R., Duraisamy S., Designing a Novel Framework of Load Balancing Cluster with Target Coverage Problem and Trust Evaluation for Military Wireless Sensor Networks, International Journal of Advances in Engineering and Emerging Technology, 7, 9, pp. 597-614, (2015); Yamuna B., Girija T., Enhanced Fully Distributed Load Rebalancing in Cloud Computing, International Journal of Advances in Engineering and Emerging Technology, 7, 10, pp. 615-626, (2015); Priya P., Mercy Gnana Rani A., An ANT Based Intelligent Routing Algorithm for MANET, International Journal of Advances in Engineering and Emerging Technology, 7, 10, pp. 627-639, (2015); Kumaravel A., Meetei O.N., An application of non-uniform cellular automata for efficient cryptography, Indian Journal of Science and Technology, 6, pp. 4560-4566, (2013); Kumaravel A., Pradeepa R., Layered approach for predicting protein subcellular localization in yeast microarray data, Indian Journal of Science and Technology, 6, pp. 4567-4571, (2013); Kaviyarasu K., Manikandan E., Kennedy J., Maaza M., Synthesis and analytical applications of photoluminescent carbon nanosheet by exfoliation of graphite oxide without purification, Journal of Materials Science: Materials in Electronics, 27, 12, pp. 13080-13085, (2016); Mathubala G., Manikandan A., Arul Antony S., Ramar P., Photocatalytic degradation of methylene blue dye and magneto-optical studies of magnetically recyclable spinel NixMn1-xFe2O4 (X = 0.0-1.0) nanoparticles, Journal of Molecular Structure, 1113, pp. 79-87, (2016); Manikandan E., Kennedy J., Kavitha G., Kaviyarasu K., Maaza M., Panigrahi B.K., Mudali U.K., Hybrid nanostructured thin-films by PLD for enhanced field emission performance for radiation micro-nano dosimetry applications, Journal of Alloys and Compounds, 647, pp. 141-145, (2015); Kumaravel A., Meetei O.N., An application of non-uniform cellular automata for efficient cryptography, 2013 IEEE Conference on Information and Communication Technologies, ICT 2013, pp. 1200-1205, (2013); Langeswaran K., Gowthamkumar S., Vijayaprakash S., Revathy R., Balasubramanian M.P., Influence of limonin on Wnt signalling molecule in HepG2 cell lines, Journal of Natural Science, pp. 126-133, (2013); Srinivasan V., Saravanan T., Analysis of harmonic at educational division using C.A. 8332, Middle-East, Journal of Scientific Research, 16, 12, pp. 1768-1773, (2013); Josephine B.A., Manikandan A., Teresita V.M., Antony S.A., Fundamental study of LaMg x Cr 1−x O 3−δ perovskites nano-photocatalysts: Sol-gel synthesis, characterization and humidity sensing, Korean Journal of Chemical Engineering, 33, 5, pp. 1590-1598, (2016); Saravanan T., Saritha G., Udayakumar R., A Robust H-infinity two degree of freedom control for electromagnetic suspension system, Middle-East Journal of Scientific Research, 18, 12, pp. 1827-1831, (2013); Rajasulochana P., Dhamotharan R., Murugakoothan P., Murugesan S., Krishnamoorthy P., Biosynthesis and characterization of gold nanoparticles using the alga kappaphycus alvarezii, International Journal of Nanoscience, 9, pp. 511-516, (2010); Slimani Y., Gungunes H., Nawaz M., Manikandan A., El Sayed H.S., Almessiere M.A., Sozeri H., Shirsath S.E., Ercan I., Baykal A., Magneto-optical and microstructural properties of spinel cubic copper ferrites with Li-Al co-substitution, Ceramics International, 44, 12, pp. 14242-14250, (2018); Kaviyarasu K., Manikandan E., Kennedy J., Jayachandran M., Maaza M., Rice husks as a sustainable source of high quality nanostructured silica for high performance Li-ion battery requital by sol-gel method a review, Advanced Materials Letters, 7, 9, pp. 684-696, (2016); Ilayaraja K., Ambica A., Spatial distribution of groundwater quality between injambakkam-thiruvanmyiur areas, south east coast of India, Nature Environment and Pollution Technology, 14, pp. 771-776, (2015); Sharmila S., Jeyanthi R.L., Das M.P., Saduzzaman M., Isolation and partial purification of protease from plant leaves, Journal of Chemical and Pharmaceutical Research, 4, pp. 3808-3812, (2012); Brintha R.S., Nalini C., An Efficient Cost Model for Data Storage with Horizontal Layout in the Cloud, Indian Journal of Science and Technology, V-7, PP:45-46, (2014)","K. Jansi Rani; Department of Commerce and Economics, Faculty of Arts and Science, BIHER, Bharath Institute of Higher Education & Research, Chennai, Selaiyur, India; email: jansirani.com@bharathuniv.ac.in",null,"Institute of Advanced Scientific Research, Inc.",{"$nulls":5},"1943023X",null,null,null,"English","J. Adv. Res. Dyn. Control. Syst.","Article","Final",null,"Scopus","2-s2.0-85075695506"]
["Khalyn V.G.","Khalyn, V.G. (57207889458)",5.7207889458E10,"The significance of logistics in servicing growing volumes of e-commerce",2019.0,"International Journal of Economics and Business Administration",7.0,null,null,185.0,194.0,9.0,3.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85079138124&partnerID=40&md5=5528b2503b9c5e1eefde6452b496542a","Department of Commerce and Logistics, Rostov State University of Economics, Russian Federation","Khalyn V.G., Department of Commerce and Logistics, Rostov State University of Economics, Russian Federation","Purpose: The article highlights the multi-task nature and prospects of the development of the transit potential of warehouse logistics systems, reveals the theoretical and methodological foundations of logistics in the storage and cargo handling system, indicates and confirms the importance of warehousing logistics in the context of servicing the growing volumes of electronic commerce. Design/Methodology/Approach: For the purposes of developing logistics in the storage and cargo handling system we study the technical and technological support and design developments that have significant potential for increasing the efficiency of logistics processes, and to study consumer behavior in the warehouse services market and transport market trends - warehouse activities. Findings: Automation significantly simplifies logistics processes, information exchange, remote control and management, optimizes costs by combining various market entities and objects, target groups and parameters of logistics processes on electronic platforms. Integration in modern logistics allows synchronizing the complex information component of electronic services and platforms and activating the formation of a system interface that is common for all elements of the logistics system of warehousing, cargo processing and inventory management. Practical implications: The results of the study can be implemented in the activities of Russian companies in order to develop the transit potential of warehouse logistics systems. Originality/value: The significance of this study lies in shifting the emphasis to the need to switch to improved customer service systems taking into account the needs and development of online retail and fulfillment of logistics operators (full-cycle operator: taking goods from the customer’s warehouse, responsible storage, packaging, delivery, work with returns), tied to the development of infrastructure, as the foundation for increasing the efficiency, speed and quality of logistics processes. © 2019 International Strategic Management Association. All rights reserved.","Development; E-commerce; Warehousing logistics",{"$nulls":7},"Bowersox D.J., Logistics. Integrated Supply Chain, (2017); Khalyn V.G., Restructuring of the information system of regional distribution complexes based on the use of innovative logistics tools, Terra Economicus, 1, pp. 2-11, (2011); Levikov G.A., Logistics, transport and forwarding, Brief Dictionary-Reference Book, (2017); Plokhikh Yu.V., Gubich M.E., Prospects and problems of transport and logistics services market development, Young Scientist, 9, 89, pp. 685-686, (2015); Volgin V.V., Storekeeper. Arrangement of warehouses., Warehouse Operations. Warehouse Management, (2016)","V.G. Khalyn; Department of Commerce and Logistics, Rostov State University of Economics, Russian Federation; email: vg@sklp.biz",null,"International Strategic Management Association",{"$nulls":5},2.2414754E7,null,null,null,"English","Int. J. Econ. Bus. Adm.","Article","Final",null,"Scopus","2-s2.0-85079138124"]
["Jacob A.M.; Sreedharan N.V.; Sreena K.","Jacob, Arji Mariam (57209503103); Sreedharan, N.V. (57209499532); Sreena, K. (57200934884)","57209503103; 57209499532; 57200934884","Consumer perception of online food delivery apps in Kochi",2019.0,"International Journal of Innovative Technology and Exploring Engineering",8.0,7.0,null,302.0,305.0,3.0,8.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85067994832&partnerID=40&md5=84dedda5ae46be1e755f7c8db31962a6","Department of Visual Media and Communication, Amrita School of Arts and Sciences, Amrita Vishwa Vidyapeetham, Kochi, India","Jacob A.M., Department of Visual Media and Communication, Amrita School of Arts and Sciences, Amrita Vishwa Vidyapeetham, Kochi, India; Sreedharan N.V., Department of Visual Media and Communication, Amrita School of Arts and Sciences, Amrita Vishwa Vidyapeetham, Kochi, India; Sreena K., Department of Visual Media and Communication, Amrita School of Arts and Sciences, Amrita Vishwa Vidyapeetham, Kochi, India","A single window for ordering from a wide range of restaurants, online food delivery mobile applications has become popular over these years. This trend has changed the mindset of customers, gratifying users of different age groups. There are wide varieties of restaurants now delivering online services at best offers and reasonable prices. This, indeed, has expanded their daily business, witnessing a boom in online food delivering system as well as popularizing it across the country. The online food ordering system sets up a food menu online with the help of mobile applications like Zomato, Swiggy and Uber Eats. Science and technology is developing day by day and undoubtedly, it can be said that the invention of internet has expanded the country’s online business enterprises. From booking tickets, paying bills, buying utensils and so on, internet has endorsed everyone in many ways and the recent development is food delivering applications where the desired food items are delivered at the user’s doorstep. It frees customers from visiting the eateries and also the long wait in restaurants. In this study, the main focus is to analyze the perception of consumer towards online food ordering services. The research takes both quantitative and qualitative approach to the study. © BEIESP.","Customer Perception; E-Commerce; Food delivery; Mobile application Swiggy; Online food; Restaurant; Uber eats; Zomato",{"$nulls":7},"Priyadharshini R., Consumer perception towards MNC fast food outlets in Coimbatore, International Journal of Applied Research, 3, 3, (2017); Samsudin N.A., Khalid S.K., Kohar M.F., Senin Z., Ihkasan M.N., A customizable wireless food ordering system with realtime customer feedback, 2011 IEEE Symposium on Wireless Technology and Applications (ISWTA), (2011); Rathore S.S., Chaudhary M., Consumer’s Perception on Online Food Ordering, International Journal of Management & Business Studies, 8, 4, (2018); Singh R.A., Pathan A.S., Kanade V., Online Food Ordering System, International Journal of Computer Applications, 180, 6, pp. 22-24, (2017)",null,null,"Blue Eyes Intelligence Engineering and Sciences Publication",{"$nulls":5},2.2783075E7,null,null,null,"English","Int. J. Innov. Technol. Explor. Eng.","Article","Final",null,"Scopus","2-s2.0-85067994832"]
["Lee H.-Y.; Wang N.-J.","Lee, Hsien-Yu (57205259690); Wang, Nai-Jian (9335220600)","57205259690; 9335220600","Cloud-based enterprise resource planning with elastic model–view–controller architecture for Internet realization",2019.0,"Computer Standards and Interfaces",64.0,null,null,11.0,23.0,12.0,20.0,"10.1016/j.csi.2018.11.005","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85059312687&doi=10.1016%2fj.csi.2018.11.005&partnerID=40&md5=52847ec201660bc3440bdd9a93e4f15e","Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei, 106, Taiwan; Department of Web Development, IT Division, Formosa Plastics Corporation, 07039, NJ, United States","Lee H.-Y., Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei, 106, Taiwan, Department of Web Development, IT Division, Formosa Plastics Corporation, 07039, NJ, United States; Wang N.-J., Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei, 106, Taiwan","Companies currently encounter obstacles in networking, integration, and global manufacturing as mobile devices as well as computers increasingly facilitate commercial activities. Accordingly, we propose a new web-based enterprise resource planning (e-ERP) system that can be rapidly migrated from conventional on-site ERP systems. In this paper, by referring to Internet technologies and several key web topics, we explore the evolution of e-Commerce and ERP. We also discuss the applications of the proposed method based on an elastic model–view–controller e-ERP and software-as-a-service delivery. On the basis of information system architecture evaluation and realization results, we discuss the application of web technologies and web engineering models for the effective hosting of a reliable cloud ERP. In addition, on the basis of a review of the literature and related emerging technologies, we comparatively discuss several holistic frameworks of web application development from the technical and business perspectives. As indicated by the implementation results, the proposed approach can be used to effectively host a secure cloud ERP. © 2018 Elsevier B.V.","Cloud computing; e-Business; Information system architecture evaluation; Interface; Web programming","Application programs; Cloud computing; Computer architecture; Electronic commerce; Information systems; Information use; Interfaces (materials); Resource allocation; Software as a service (SaaS); Controller architectures; eBusiness; Emerging technologies; Global manufacturing; Information system architecture; Web application development; Web engineering models; Web programming; Enterprise resource planning",{"$nulls":4},"Damien Watterson, of Wallace Academic Editing","The authors would like to thank the anonymous reviewers for their valuable comments, which helped to improve the paper. In addition, we also wish to gratefully acknowledge two anonymous referees from the editorial teams of Studies in Engineering and Technology and the International Journal of Advanced Computer Research for reading this article and providing suggestions, which improved the contents and composition substantially. Finally, this manuscript was edited by Christopher Law and Damien Watterson, of Wallace Academic Editing. Without their warm help, we could not have finished this paper.","Staehr L., Understanding the role of managerial agency in achieving business benefits from ERP systems, Inf. Syst. J., 20, 3, pp. 213-238, (2010); Hofmann P., ERP is dead, long live ERP, IEEE Internet Comput., 12, 4, pp. 84-88, (2008); Kiadehi E.F., Mohammadi S., Cloud ERP: implementation of enterprise resource planning using cloud computing technology, J. Basic Appl. Sci. 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Conf. e-Business e-Government (ICEE), May, pp. 1-4, (2011); Chung J.-Y., Lin K.-J., Shim S.S.Y., Beyond electronic commerce, Computer, 38, 8, pp. 92-93, (2005); Lin K.-J., e-Commerce technology: back to a prominent future, IEEE Internet Comput., 12, January/February (1), pp. 60-65, (2008); Garfinkel S., Abelson H., Architects of the Information Society, Thirty-Five Years of the Laboratoryfor Computer Science at MIT, (1999); Pulparambil S., Baghdadi Y., Service oriented architecture maturity models: a systematic literature review, Comput. Stand. Interfaces, 61, pp. 65-76, (2019); Raines G., Cloud Computing and SOA, (2009); Kress J., Et al., SOA and Cloud Computing, (2014)","H.-Y. Lee; Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei, 106, Taiwan; email: ebilllee@gmail.com",null,"Elsevier B.V.",{"$nulls":5},9205489.0,null,"CSTIE",null,"English","Comput Stand Interfaces","Article","Final",null,"Scopus","2-s2.0-85059312687"]
["Ramadan Z.B.; Farah M.F.; Daouk S.","Ramadan, Zahy B. (57191495384); Farah, Maya F. (26633914300); Daouk, Shireen (57211466231)","57191495384; 26633914300; 57211466231","The effect of e-retailers' innovations on shoppers' impulsiveness and addiction in web-based communities: The case of Amazon's Prime Now",2019.0,"International Journal of Web Based Communities",15.0,4.0,null,327.0,343.0,16.0,10.0,"10.1504/IJWBC.2019.103181","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85074060325&doi=10.1504%2fIJWBC.2019.103181&partnerID=40&md5=f34896c144d090591a9cb53b9c6087f7","Lebanese American University,Beirut, P.O. Box 13-5053, Chouran, Beirut, 1102-2801, Lebanon","Ramadan Z.B., Lebanese American University,Beirut, P.O. Box 13-5053, Chouran, Beirut, 1102-2801, Lebanon; Farah M.F., Lebanese American University,Beirut, P.O. Box 13-5053, Chouran, Beirut, 1102-2801, Lebanon; Daouk S., Lebanese American University,Beirut, P.O. Box 13-5053, Chouran, Beirut, 1102-2801, Lebanon","In the era of exponential growth of online shopping, e-commerce has accelerated consumers' shift from offline to online shopping, specifically in the FMCG industry. In 2015, Amazon launched the Amazon Prime Now service based on same-day delivery. The research objective is to understand the implications of this ordering tool on the consumer journey from the shopper web-based community, the retailer and brand perspectives. In order to investigate the usage of Amazon Prime Now and its impact on the overall consumer journey, a survey was devised and completed by 25 Prime users who reside in the UK. The findings show that clients' gratification is due to the outstanding customer service Amazon offers, which as a result established a trust and love relationship with the retailer. Moreover, the findings show that while the minimum order fees have reduced shoppers' impulsive behaviour in web-based communities, an overall addiction toward the use of Amazon Prime Now was taking place. © 2019 Inderscience Enterprises Ltd.","Amazon; Retailing; Shopper web-based community; UK","Sales; Websites; Amazon; Customer services; Exponential growth; Minimum order; Online shopping; Research objectives; Retailing; Web-based communities; Electronic commerce",{"$nulls":6},"Aitken R., Will Amazon's Internet of Things Device 'Dash' UK Supermarket Fortunes?, (2016); Annual Number of Worldwide Active Amazon Customer Accounts from 1997 to 2015 (In Millions), (2016); Armstrong A., Tesco Restores Dividend for First Time since Accounting Scandal, (2017); Ayadi N., Giraud M., Gonzalez C., An investigation of consumers' self-control mechanisms when confronted with repeated purchase temptations: Evidence from online private sales, Journal of Retailing and Consumer Services, 20, 3, pp. 272-281, (2013); Barone M.J., Roy T., Does exclusivity always pay off? 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Bus. Rev., pp. 18-37, (2016); Neslin S.A., Jerath K., Bodapati A., Bradlow E.T., Deighton J., Gensler S., Et al., The interrelationships between brand and channel choice, Marketing Letters, 25, pp. 319-330, (2014); Orford J., Community Psychology: Challenges, Controversies and Emerging Consensus, (2008); Parker G.G., Van Alstyne M.W., Two-sided network effects: A theory of information product design, Management Science, 51, 10, pp. 1494-1504, (2005); Piotrowicz W., Cuthbertson R., Introduction to the special issue information technology in retail: Toward omnichannel retailing, International Journal of Electronic Commerce, 18, 4, pp. 5-16, (2014); Prince R., Tesco Is Launching a 1-hour Delivery Service As It Goes to War with Amazon, (2017); Ramadan Z., Farah M.F., The advent of the' social moment of truth' in online communities, International Journal of Web Based Communities, 13, 3, pp. 364-378, (2017); Rigby D., The future of shopping, Harvard Business Review, 89, 12, pp. 65-76, (2011); Riquelme I.P., Roman S., The influence of consumers' cognitive and psychographic traits on perceived deception: A comparison between online and offline retailing contexts, Journal of Business Ethics, 119, 3, pp. 405-422, (2014); Rochet J.C., Tirole J., Platform competition in two-sided markets, Journal of European Economic Association, 1, 4, pp. 990-1029, (2003); Rook D.W., The buying impulse, Journal of Consumer Research, 14, 2, pp. 189-199, (1987); Rook D.W., Gardner M., In the mood: Impulse buying's affective antecedents, Research in Consumer Behavior, 6, 7, pp. 1-28, (1993); Rose S., Dhandayudham A., Towards An Understanding of Internet-based Problem Shopping Behaviour: The Concept of Online Shopping Addiction and Its Proposed Predictors, (2014); Ruvio A.A., Belk R.W., The Routledge Companion to Identity and Consumption, (2013); Shah D., Rust R.T., Parasuraman A., Staelin R., Day G.S., The path to customer centricity, Journal of Service Research, 9, pp. 113-124, (2006); Shi A., Amazon Prime Members Now Outnumber Non-Prime Customers, (2016); Stern H., The significance of impulse buying today, The Journal of Marketing, 26, 2, pp. 59-62, (1962); Sussman S., Lisha N., Griffiths M., Prevalence of the addictions: A problem of the majority or the minority?, Evaluation & the Health Professions, 34, 3, pp. 3-56, (2010); Thompson C.J., Locander W.B., Pollio H.R., The lived meaning of free choice: An existential-phenomenological description of everyday consumer experiences of contemporary married women, Journal of Consumer Research, 17, 3, pp. 346-361, (1990); Triandis H.C., Individualism and Collectivism, (1995); Verhoef P.C., Kannan P.K., Inman J.J., From multi-channel retailing to omni-channel retailing: Introduction to the special issue on multi-channel retailing, Journal of Retailing, 91, pp. 174-181, (2015); Yu U.J., Niehm L.S., Russell D.W., Exploring perceived channel price, quality, and value as antecedents of channel choice and usage in multichannel shopping, Journal of Marketing Channels, 18, 2, pp. 79-102, (2011); Zhang J., Farris P.W., Irvin J.W., Kushwaha T., Steenburgh T.J., Weitz B.A., Crafting integrated multichannel retailing strategies, Journal of Interactive Marketing, 24, 2, pp. 168-180, (2010); Zhu F., Liu Q., Competing with Complementors: An Empirical Look at Amazon.com, (2016)","Z.B. Ramadan; Lebanese American University,Beirut, Chouran, Beirut, P.O. Box 13-5053, 1102-2801, Lebanon; email: zahy.ramadan@lau.edu.lb",null,"Inderscience Publishers",{"$nulls":5},1.4778394E7,null,null,null,"English","Int. J. Web Based Communities","Article","Final",null,"Scopus","2-s2.0-85074060325"]
["Liu W.; Deng T.; Li J.","Liu, Weimiao (57208134029); Deng, Tianhu (56396164500); Li, Jianbin (57208131872)","57208134029; 56396164500; 57208131872","Product packing and stacking under uncertainty: A robust approach",2019.0,"European Journal of Operational Research",277.0,3.0,null,903.0,917.0,14.0,10.0,"10.1016/j.ejor.2019.03.040","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85063916699&doi=10.1016%2fj.ejor.2019.03.040&partnerID=40&md5=80afaf045e0c31e0149005837fb7731f","Department of Industrial Engineering, Tsinghua University, Beijing, China; 92942 Army, People's Liberation Army of China, Beijing, China","Liu W., Department of Industrial Engineering, Tsinghua University, Beijing, China; Deng T., Department of Industrial Engineering, Tsinghua University, Beijing, China; Li J., 92942 Army, People's Liberation Army of China, Beijing, China","China, the world's largest logistics market, is experiencing insatiable demand for logistics services. The boom in China's e-commerce has led to massive growth in the need for product shipping and warehouse storage. Some of China's largest retailers have invested tremendous amounts of money in warehouse development. Two important functions of a warehouse are packing and stacking: packing small products into medium-sized containers and stacking the containers on pallets. Often, the packing problem is solved independently from that of stacking or is ignored. Generally, the stacking problem is solved while treating the packing decisions as given. However, considering these two problems separately may result in suboptimal, i.e., less efficient operations. Therefore, we propose a mixed integer linear programming formulation that addresses these two problems as a whole and two relaxations for actual-size examples. Due to the inherent demand uncertainty, we present a two-stage robust model that employs interval-based and scenario-based uncertainty sets. We numerically verify that the integrated model achieves considerable economic benefits and efficient space utilization while exploiting spatial flexibility. The additional computational experiments suggest that two relaxations yield tiny optimality gaps of 0.3% on average (4.6% at maximum), and considerable computation time improvements of 207.9% on average (347.4% at maximum). Our numerical results also illustrate that the scenario-based robust approach outperforms the deterministic approach and interval-based robust approach. We verify the model with varying variability and sizes of containers. The computational results indicate that compared with single type of containers, two or three types would bring significant economic benefits. © 2019 Elsevier B.V.","OR in defense; Packing; Robust optimization; Stacking; Warehouse management","Containers; Integer programming; Packing; Warehouses; Computational experiment; Computational results; Deterministic approach; Mixed integer linear programming; OR in defense; Robust optimization; Stacking; Warehouse management; Economic and social effects",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (71822105); Tsinghua University, THU","The authors thank the editor and two anonymous referees for their constructive suggestions that have significantly improved this paper. This work was partially supported by the National Natural Science Foundation of China (Grant 71822105 ) and Tsinghua University Initiative Scientific Research Program.  ","Aldred S., Jim C., (2014); (2014); Awasthi P., Goyal V., Lu B.Y., On the adaptivity gap in two-stage robust linear optimization under uncertain packing constraints, Mathematical Programming, 173, 1-2, pp. 1-40, (2018); Barreto E., (2017); Basten R.J.I., Heijden M.C.V.D., Schutten J.M.J., Kutanoglu E., An approximate approach for the joint problem of level of repair analysis and spare parts stocking, Annals of Operations Research, 224, 1, pp. 121-145, (2015); Bortfeldt A., Wascher G., Constraints in container loading – A state-of-the-art review, European Journal of Operational Research, 229, 1, pp. 1-20, (2013); Bruns F., Knust S., Shakhlevich N.V., Complexity results for storage loading problems with stacking constraints, European Journal of Operational Research, 249, 3, pp. 1074-1081, (2016); Chan L.M.A., Simchi-Levi D., Bramel J., Worst-case analyses, linear programming and the bin-packing problem, Mathematical Programming, 83, 1-3, pp. 213-227, (1998); Cherri L.H., Mundim L.R., Andretta M., Toledo F.M., Oliveira J.F., Carravilla M.A., Robust mixed-integer linear programming models for the irregular strip packing problem, European Journal of Operational Research, 253, 3, pp. 570-583, (2016); Coffman E.G., Garey M.R., Johnson D.S., Approximation algorithms for bin packing: A survey, Approximation algorithms for NP-hard problems, pp. 46-93, (1997); Courcoubetis C., Weber R., Necessary and sufficient conditions for stability of a bin-packing system, Journal of Applied Probability, 23, 4, pp. 989-999, (1986); Daga A., Barreto E., (2017); de Jonge B., Teunter R., Tinga T., The influence of practical factors on the benefits of condition-based maintenance over time-based maintenance, Reliability Engineering and System Safety, 158, pp. 21-30, (2017); Dekker R., Voogd P., van Asperen E., Advanced methods for container stacking, OR Spectrum, 28, 4, pp. 563-586, (2006); Escudero L.F., Landete M., Rodriguez-Chia A.M., Stochastic set packing problem, European Journal of Operational Research, 211, 2, pp. 232-240, (2011); Federgruen A., Van Ryzin G., Probabilistic analysis of a generalized bin packing problem and applications, Operations Research, 45, 4, pp. 596-609, (1997); Fekete S.P., Schepers J., Van der Veen J.C., An exact algorithm for higher-dimensional orthogonal packing, Operations Research, 55, 3, pp. 569-587, (2007); Forster F., Bortfeldt A., A tree search procedure for the container relocation problem, Computers and Operations Research, 39, 2, pp. 299-309, (2012); Goerigk M., Knust S., Le X.T., Robust storage loading problems with stacking and payload constraints, European Journal of Operational Research, 253, 1, pp. 51-67, (2016); Imai A., Sasaki K., Nishimura E., Papadimitriou S., Multi-objective simultaneous stowage and load planning for a container ship with container rehandle in yard stacks, European Journal of Operational Research, 171, 2, pp. 373-389, (2006); Johnson D.S., Demers A., Ullman J.D., Garey M.R., Graham R.L., Worst-case performance bounds for simple one-dimensional packing algorithms, SIAM Journal on Computing, 3, 4, pp. 299-325, (1974); Junqueira L., Morabito R., Yamashita D.S., Three-dimensional container loading models with cargo stability and load bearing constraints, Computers and Operations Research, 39, 1, pp. 74-85, (2012); Karmarkar N., Karp R.M., An efficient approximation scheme for the one-dimensional bin-packing problem, Proceedings of the twenty-third annual symposium on foundations of computer science, pp. 312-320, (1982); Le X.T., Knust S., Mip-based approaches for robust storage loading problems with stacking constraints, Computers and Operations Research, 78, pp. 138-153, (2017); Lehnfeld J., Knust S., Loading, unloading and premarshalling of stacks in storage areas: Survey and classification, European Journal of Operational Research, 239, 2, pp. 297-312, (2014); Lei Z., (2017); Martello S., Pisinger D., Vigo D., The three-dimensional bin packing problem, Operations Research, 48, 2, pp. 256-267, (2000); Martello S., Vigo D., Exact solution of the two-dimensional finite bin packing problem, Management Science, 44, 3, pp. 388-399, (1998); Ong H.L., Magazine M.J., Wee T., Probabilistic analysis of bin packing heuristics, Operations Research, 32, 5, pp. 983-998, (1984); Rei R., Pedroso J.P., Tree search for the stacking problem, Annals of Operations Research, 203, 1, pp. 371-388, (2013); Romeijnders W., Teunter R., van Jaarsveld W., A two-step method for forecasting spare parts demand using information on component repairs, European Journal of Operational Research, 220, 2, pp. 386-393, (2012); Thapatsuwan P., Pongcharoen P., Hicks C., Chainate W., Development of a stochastic optimisation tool for solving the multiple container packing problems, International Journal of Production Economics, 140, 2, pp. 737-748, (2012); Wascher G., Haussner H., Schumann H., An improved typology of cutting and packing problems, European Journal of Operational Research, 183, 3, pp. 1109-1130, (2007); Zhang Y., Jiang R., Shen S., (2016); Zito M., Logistics J., (2014)","T. Deng; Department of Industrial Engineering, Tsinghua University, Beijing, China; email: deng13@mail.tsinghua.edu.cn",null,"Elsevier B.V.",{"$nulls":5},3772217.0,null,"EJORD",null,"English","Eur J Oper Res","Article","Final",null,"Scopus","2-s2.0-85063916699"]
["Yu Y.; Yu C.; Xu G.; Zhong R.Y.; Huang G.Q.","Yu, Ying (57191723934); Yu, Chenglin (57205731940); Xu, Gangyan (55361785800); Zhong, Ray Y. (55353690000); Huang, George Q. (7403425048)","57191723934; 57205731940; 55361785800; 55353690000; 7403425048","An operation synchronization model for distribution center in E-commerce logistics service",2020.0,"Advanced Engineering Informatics",43.0,null,101014.0,null,null,null,17.0,"10.1016/j.aei.2019.101014","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85077318120&doi=10.1016%2fj.aei.2019.101014&partnerID=40&md5=b521865e5f796b9af7bb10db2b3dd1a8","HKU-ZIRI Lab for Physical Internet, Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong; School of Engineering & Applied Science, The George Washington University, Washington DC, United States; School of Architecture, Harbin Institute of Technology, Shenzhen, China","Yu Y., HKU-ZIRI Lab for Physical Internet, Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong; Yu C., School of Engineering & Applied Science, The George Washington University, Washington DC, United States; Xu G., School of Architecture, Harbin Institute of Technology, Shenzhen, China; Zhong R.Y., HKU-ZIRI Lab for Physical Internet, Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong; Huang G.Q., HKU-ZIRI Lab for Physical Internet, Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong","This paper is among the first that proposes a synchronization measurement model for the distribution centre operation synchronization (DCOS) problem, which aims to ensure the E-commerce order's punctuality and synchronization at the same time. The main motivation of DCOS is that the intensified competition in E-commerce market makes efficient E-commerce logistics service extremely important, which means saving logistics cost and ensuring customer service at the same time. The synchronized operation may be a possible solution to ensure efficient order transhipment in the distribution center and to save cost. We thus introduce a measurement approach that is able to address the distribution center operation synchronization (DCOS) problem such as the trade-off relationship between synchronization and punctuality. In order to get persuasive conclusions, we adopt data from a real practice case and apply CPLEX to get the optimal solution. Our computational results show that considering the asynchronous cost in the total cost objective function will greatly improve the operation synchronization in the distribution center, by saving the storage space, the equipment, and the labour resources. And if the storage cost is in a reasonable range, the synchronized operation can be realized while the punctuality is also optimized. It is found in our case that the most efficient way to improve distribution center operation is expanding inbound operation capacity. © 2019 Elsevier Ltd","Distribution center; E-commerce logistics service; Operation synchronization; Punctuality; Synchronization measurement","Digital storage; Economic and social effects; Electronic commerce; Warehouses; Computational results; Distribution centers; Distribution centres; Logistics services; Objective functions; Operation synchronization; Punctuality; Trade-off relationship; Synchronization",{"$nulls":6},"Arabani A.R.B., Ghomi S.M.T.F., Zandieh M., 42 Meta-heuristics implementation for scheduling of trucks in a cross-docking system with temporary storage, Expert Syst. Appl., 38, 3, pp. 1964-1979, (2011); Baptiste P., Maknoon M., 5 Cross-docking: Scheduling of incoming and outgoing semi-trailers, (2007); Boysen N., 6 Truck scheduling at zero-inventory cross docking terminals, Comput. Oper. Res., 37, 1, pp. 32-41, (2010); Boysen N., Fliedner M., 8 Cross dock scheduling: classification, literature review and research agenda, Omega-Int. J. Manage. Sci., 38, 6, pp. 413-422, (2010); Boysen N., Fliedner M., Scholl A., 7 Scheduling inbound and outbound trucks at cross docking terminals, OR Spectrum, 32, 1, pp. 135-161, (2010); McWilliams D.L., Stanfield P.M., Geiger C.D., 17 The parcel hub scheduling problem: a simulation-based solution approach, Comput. Ind. Eng., 49, 3, pp. 393-412, (2005); Sadykov R., (2009); Stephan K., Boysen N., 53 Cross-docking, J. Manage. Control, 22, 1, pp. 129-137, (2011); Van Belle J., Valckenaers P., Cattrysse D., 39 Cross-docking: state of the art, Omega-Int. J. Manage. Sci., 40, 6, pp. 827-846, (2012); Agustina D., Lee C.K.M., Piplani R., Vehicle scheduling and routing at a cross docking center for food supply chains, Int. J. Prod. Econ., 152, pp. 29-41, (2014); Alpan G., Larbi R., Penz B., A bounded dynamic programming approach to schedule operations in a cross docking platform, Comput. Ind. Eng., 60, 3, pp. 385-396, (2011); Alvarez-Perez G.A., Gonzalez-Velarde J.L., Fowler J.W., Crossdocking-just in time scheduling: an alternative solution approach, J. Oper. Res. Soc., 60, 4, pp. 554-564, (2009); Bartholdi J.J., Gue K.R., Reducing labor costs in an LTL crossdocking terminal, Oper. Res., 48, 6, pp. 823-832, (2000); Boysen N., Truck scheduling at zero-inventory cross docking terminals, Comput. Oper. Res., 37, 1, pp. 32-41, (2010); Boysen N., Briskorn D., Tschoke M., Truck scheduling in cross-docking terminals with fixed outbound departures, OR Spectrum, 35, 2, pp. 479-504, (2013); Boysen N., Fliedner M., Cross dock scheduling: classification, literature review and research agenda, Omega-Int. J. Manage. Sci., 38, 6, pp. 413-422, (2010); Bozer Y.A., Carlo H.J., Optimizing inbound and outbound door assignments in less-than-truckload crossdocks, IIE Trans., 40, 11, pp. 1007-1018, (2008); Chen F., Lee C.Y., Minimizing the makespan in a two-machine cross-docking flow shop problem, Eur. J. Oper. Res., 193, 1, pp. 59-72, (2009); Chen F., Song K., Minimizing makespan in two-stage hybrid cross docking scheduling problem, Comput. Oper. Res., 36, 6, pp. 2066-2073, (2009); Chen J., Huang G.Q., Luo H., Wang J.Q., Synchronisation of production scheduling and shipment in an assembly flowshop, Int. J. Prod. Res., 53, 9, pp. 2787-2802, (2015); Cohen Y., Keren B., Trailer to door assignment in a synchronous cross-dock operation, Int. J. Log. Syst. Manage., 5, 5, pp. 574-590, (2009); Delfmann W., Albers S., Gehring M., The impact of electronic commerce on logistics service providers, Int. J. Phys. Distrib. Log. Manage., 32, 3, pp. 203-222, (2002); Forouharfard S., Zandieh M., An imperialist competitive algorithm to schedule of receiving and shipping trucks in cross-docking systems, Int. J. Adv. Manuf. Technol., 51, 9-12, pp. 1179-1193, (2010); Gue K.R., The effects of trailer scheduling on the layout of freight terminals, Transport. Sci., 33, 4, pp. 419-428, (1999); Lan S., Yang C., Huang G.Q., Data analysis for metropolitan economic and logistics development, Adv. Eng. Inf., 32, pp. 66-76, (2017); Larbi R., Alpan G., Baptiste P., Penz B., Scheduling of transhipment operations in a single strip and stack doors crossdock, (2007); Larbi R., Alpan G., Penz B., Scheduling transshipment operations in a multiple inbound and outbound door crossdock, (2009); Ley S., Elfayoumy S., Cross dock scheduling using genetic algorithms, (2007); Li Y., Lim A., Rodrigues B., 26 Crossdocking – JIT scheduling with time windows, J. Oper. Res. Soc., 55, 12, pp. 1342-1351, (2004); Li Z., Sim C.H., Low M.Y.H., Lim Y.G., Optimal product allocation for crossdocking and warehousing operations in FMCG supply chain, (2008); Liao T.W., Egbelu P.J., Chang P.-C., Two hybrid differential evolution algorithms for optimal inbound and outbound truck sequencing in cross docking operations, Appl. Soft Comput., 12, 11, pp. 3683-3697, (2012); Lim A., Ma H., Miao Z.W., Truck dock assignment problem with operational time constraint within crossdocks, Adv. Appl. Articial Intell., Proc., 4031, pp. 262-271, (2006); McWilliams D.L., A dynamic load-balancing scheme for the parcel hub-scheduling problem, Comput. Ind. Eng., 57, 3, pp. 958-962, (2009); McWilliams D.L., Genetic-based scheduling to solve the parcel hub scheduling problem, Comput. Ind. Eng., 56, 4, pp. 1607-1616, (2009); McWilliams D.L., Iterative improvement to solve the parcel hub scheduling problem, Comput. Ind. Eng., 59, 1, pp. 136-144, (2010); McWilliams D.L., Stanfield P.M., Geiger C.D., Minimizing the completion time of the transfer operations in a central parcel consolidation terminal with unequal-batch-size inbound trailers, Comput. Ind. Eng., 54, 4, pp. 709-720, (2008); Miao Z.W., Lim A., Ma H., Truck dock assignment problem with operational time constraint within crossdocks, Eur. J. Oper. Res., 192, 1, pp. 105-115, (2009); Oh Y., Hwang H., Cha C.N., Lee S., A dock-door assignment problem for the Korean mail distribution center, Comput. Ind. 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Rec., 2162, pp. 9-16, (2010); Zhong R.Y., Huang G.Q., Lan S., Dai Q.Y., Zhang T., Xu C., A two-level advanced production planning and scheduling model for RFID-enabled ubiquitous manufacturing, Adv. Eng. Inf., 29, 4, pp. 799-812, (2015); Xu G., Et al., Data-Driven Resilient Fleet Management for Cloud Asset-enabled Urban Flood Control, IEEE Transactions on Intelligent Transportation Systems, 19, 6, pp. 1827-1838, (2018); Xu G., Et al., Data-driven Operational Risk Analysis in E-Commerce Logistics., Advanced Engineering Informatics, 40, pp. 29-35, (2019); Qiu X., Et al., Optimizing rail transport service in a dry port system, IEEE Transactions on Engineering Management, (2019)","G.Q. Huang; HKU-ZIRI Lab for Physical Internet, Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong; email: gqhuang@hku.hk",null,"Elsevier Ltd",{"$nulls":5},1.4740346E7,null,null,null,"English","Adv. Eng. Inf.","Article","Final",null,"Scopus","2-s2.0-85077318120"]
["Jain N.; Verma D.","Jain, Nilesh (57212682564); Verma, Dhanraj (57211806608)","57212682564; 57211806608","Design a novel approach for electronic product",2019.0,"International Journal of Scientific and Technology Research",8.0,12.0,null,2893.0,2896.0,3.0,0.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85077340978&partnerID=40&md5=4ccd43cc12782393bb86183bfdc6ebaa",null,null,"E-Commerce websites are the major emerging trends in the current scenario, which facilitates online product selection, purchase and sales. Nowadays E-commerce websites have better popularity and advent nature, so numerous count of users wish to share their opinions about their experience in the form of making reviews, ratings and blogs. Each of the first four of these goals can be realized through recommender systems: ¨ ``Customize services around standardized products and services'': Recommender systems provide a customized service that enables E-commerce sites to sell their largely commodity products more efficiently. ¨ ``Create customizable products and ser vices'': Recommender systems are a customizable product of the E-commerce site. ¨ ``Provide point of delivery customization'': The recommender system directly customizes the point of delivery for the E-commerce site. ¨ ``Provide quick response throughout the value chain'': We predict that recommender systems will be used in the future to predict demand for products, enabling earlier communication back the supply chain. © IJSTR 2019.","E-Commerce; Information system; Predictive analytics; Recommender system",{"$nulls":7},"Romadhony A., Al Faraby S., Pudjoatmodjo B., Online Shopping Recommender System Using Hybrid Method. 2013 International Conference of Information and Communication Technology (Icoict), (2013); Zhu X., Huang J., Shi M., An Intelligent On-line Recommendation System, B2C Apparel E-Commerce. 2010 International Conference on E-Business and E-Government, (2010); Guo Y., Yin C., Li M., Ren X., Liu P., Mobile e-Commerce Recommendation System Based on Multi-Source Information Fusion for Sustainable e-Business, Sustainability, 2018, 10, (2018); Chen J., Miller C., Dagher G.G., Product recommendation system for small online retailers using association rules mining, Proceedings of the 2014 International Conference on Innovative Design and Manufacturing (ICIDM), (2014); Ju C., Wang J., Zhou G., The commodity recommendation method for online shopping based on data mining, Multimedia Tools and Applications, (2018); Deng X., Wu L., Ren X., Jia C., Zhong Y., Lu L., Inferring users’ preferences through leveraging their social relationships, IECON 2017-43Rd Annual Conference of the IEEE Industrial Electronics Society, (2017); Lu L., Medo M., Yeung C., Zhang Y., Zhang Z., Zhou T., Recom-mender systems, Phys. Rep, 519, 1, pp. 1-49, (2012); Nie D., Zhang Z., Zhou J., Fu Y., Zhang K., Information filtering on coupled social networks, Plos ONE, 9, 7, (2014); Schafer J.B., Konstan J., Riedl J., Recommender Systems in E-Commerce; Dumitru H., Gibiec M., Hariri N., Cleland-Huang J., Mobasher B., Castro-Herrera C., Mirakhorli M., On-Demand Feature Recommendations Derived from Mining Public Software Repositories, Proc. 33Rd Int'l Conf. Software Eng, (2011)",null,null,"International Journal of Scientific and Technology Research",{"$nulls":5},2.2778616E7,null,null,null,"English","Int. J. Sci. Technol. Res.","Article","Final",null,"Scopus","2-s2.0-85077340978"]
["Janjevic M.; Winkenbach M.; Merchán D.","Janjevic, Milena (55809152100); Winkenbach, Matthias (57189308132); Merchán, Daniel (56460391400)","55809152100; 57189308132; 56460391400","Integrating collection-and-delivery points in the strategic design of urban last-mile e-commerce distribution networks",2019.0,"Transportation Research Part E: Logistics and Transportation Review",131.0,null,null,37.0,67.0,30.0,77.0,"10.1016/j.tre.2019.09.001","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85072713527&doi=10.1016%2fj.tre.2019.09.001&partnerID=40&md5=c620a2ef23745874a0890be1fe097fe6","Massachusetts Institute of Technology (MIT), Center for Transportation & Logistics (CTL), United States","Janjevic M., Massachusetts Institute of Technology (MIT), Center for Transportation & Logistics (CTL), United States; Winkenbach M., Massachusetts Institute of Technology (MIT), Center for Transportation & Logistics (CTL), United States; Merchán D., Massachusetts Institute of Technology (MIT), Center for Transportation & Logistics (CTL), United States","The use of collection-and-delivery points (CDPs) within multi-echelon distribution networks is becoming an increasingly popular last-mile distribution strategy. In this work, we provide a method to integrate CDPs in the design of multi-echelon distribution networks. We formulate a non-linear optimization model that includes CDP location decisions and accounts for changes in demand patters occurring with their placement. To enable its application to large-scale problem instances, we formulate extended routing cost approximation formulae. We then propose a heuristic solution method and apply the model and solution approach to a real-world case study of last-mile distribution by a major Brazilian e-commerce player. © 2019 Elsevier Ltd","Collection-and-delivery points; Continuum approximation; Fulfillment options; Last-mile delivery","Brazil; Electronic commerce; Nonlinear programming; Collection-and-delivery point; Continuum approximation; Delivery point; Distribution strategies; E- commerces; Fulfillment option; Last mile; Last-mile delivery; Multiechelon; Strategic design; distribution system; network analysis; strategic approach; transportation development; transportation system; urban design; urban transport; Heuristic methods",{"$nulls":6},"Agatz N., Campbell A.M., Fleischmann M., Savelsbergh M., Challenges and opportunities in attended home delivery, The Vehicle Routing Problem: Latest Advances and New Challenges, pp. 379-396, (2008); Aksen D., Altinkemer K., A location-routing problem for the conversion to the ”click-and-mortar” retailing: The static case, Eur. 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Res., 257, 3, pp. 845-858, (2017); UPS U.P., (2015); UPS U.P., (2016); Wang H., Routing and Scheduling for a Last-Mile Transportation System, Transp. Sci., (2017); Weltevreden J.W., B2C e-commerce logistics: the rise of collection-and-delivery points in The Netherlands, Int. J. Retail Distrib. Manage., 36, 8, pp. 638-660, (2008); Winkenbach M., Janjevic M., pp. 209-229, (2018); Winkenbach M., Kleindorfer P.R., Spinler S., Enabling urban logistics services at La Poste through multi-echelon location-routing, Transp. Sci., 50, 2, pp. 520-540, (2016); Winkenbach M., Roset A., Spinler S., Strategic redesign of urban mail and parcel networks at La Poste, Interfaces, 46, 5, pp. 445-458, (2016); Zhao Q., Wang W., De Souza R., A heterogeneous fleet two-echelon capacitated location-routing model for joint delivery arising in city logistics, Int. J. Prod. Res., 56, 15, pp. 5062-5080, (2018)","M. Janjevic; Massachusetts Institute of Technology (MIT), Center for Transportation & Logistics (CTL), United States; email: mjanjevi@mit.edu",null,"Elsevier Ltd",{"$nulls":5},1.3665545E7,null,null,null,"English","Transp. Res. Part E Logist. Transp. Rev.","Article","Final",null,"Scopus","2-s2.0-85072713527"]
["Zhong Y.; Guo F.; Wang Z.; Tang H.","Zhong, Yaoguang (57212522808); Guo, Fangfang (57214441044); Wang, Zhiqiang (57763520100); Tang, Huajun (36794600000)","57212522808; 57214441044; 57763520100; 36794600000","Coordination Analysis of Revenue Sharing in E-Commerce Logistics Service Supply Chain With Cooperative Distribution",2019.0,"SAGE Open",9.0,3.0,{"$nulls":4},30.0,"10.1177/2158244019870536","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85071732231&doi=10.1177%2f2158244019870536&partnerID=40&md5=bb105922872912b23972f94afb16c0ac","Dongguan University of Technology, Guangdong, China; Macau University of Science and Technology, Taipa, Macao","Zhong Y., Dongguan University of Technology, Guangdong, China; Guo F., Dongguan University of Technology, Guangdong, China; Wang Z., Macau University of Science and Technology, Taipa, Macao; Tang H., Macau University of Science and Technology, Taipa, Macao","With the rapid development of e-commerce, logistics distribution has become the bottleneck of its development. It is urgent to study how to optimize the cooperation between e-commerce platforms and logistics service providers. Based on Stackelberg game theory, this research first studies the decision making of two-stage logistics service supply chains consisting of the e-commerce mall and the logistics service provider without cooperative distribution, in which decentralization and centralization are analyzed, respectively. Then, it is extended to the decision making of three-stage logistics service supply chains consisting of e-commerce malls, express delivery companies, and terminal distributors. The results show that the profit, sales volume, and logistics service effort of the centralized decision-making system are higher than those of the decentralized decision-making system, regardless of the two-stage or three-stage logistics service supply chain. Therefore, it is vital to formulate a reasonable profit distribution scheme based on revenue-sharing contract to achieve the cooperation among the partners of logistics service supply chain, so as to achieve a win-win situation in which all of their profits increase. Finally, a numerical example is presented to verify the results, and some issues are proposed for future research. © The Author(s) 2019.","cooperative distribution; e-commerce; logistics service supply chain; revenue sharing; Stackelberg game theory",{"$nulls":5},"Social Sciences Federation of Guangdong in China, (GD17XGL11); Ministry of Education of the People's Republic of China, MOE, (17YJC630230); Macau University of Science and Technology Foundation, MUST Foundation, (FRG-17-044-MSB)","The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research is supported by Macau University of Science and Technology Foundation (Grant FRG-17-044-MSB), Humanities and Social Sciences foundation of Ministry of Education in China (Grant 17YJC630230), and Social Sciences Federation of Guangdong in China (Grant GD17XGL11).","Bernstein F., Federgruen A., Decentralized supply chains with competing retailers under demand uncertainty, Management Science, 51, pp. 18-29, (2005); Cachon G.P., Lariviere M.A., Supply chain coordination with revenue-sharing contracts: Strengths and limitations, Management Science, 51, pp. 30-44, (2005); Cai X.Q., Chen J., Xiao Y., Xu X., Yu G., Fresh-product supply chain management with logistics outsourcing, Omega-International Journal of Management Science, 41, pp. 752-765, (2013); Dana J.D., Spier K.E., Revenue sharing and vertical control in the video rental industry, Journal of Industrial Economics, 49, pp. 223-245, (2001); Chabot T., Bouchard F., Legault-Michaud A., Renaud J., Coelho L.C., Service level, cost and environmental optimization of collaborative transportation, Transportation Research Part E-logistics and Transportation Review, 110, pp. 1-14, (2018); Chen F.R., Federgruen A., Zheng Y.S., Coordination mechanisms for a distribution system with one supplier and multiple retailers, Management Science, 47, pp. 693-708, (2001); Cho J.J.K., Ozment J., Sink H., Logistics capability, logistics outsourcing and firm performance in an e-commerce market, International Journal of Physical Distribution & Logistics Management, 38, pp. 336-359, (2008); Choi T.M., Wallace S.W., Wang Y.L., Risk management and coordination in service supply chains: Information, logistics and outsourcing, Journal of the Operational Research Society, 67, pp. 159-164, (2016); Collins A.T., Behavioural influences on the environmental impact of collection/delivery points, Green logistics and transportation. 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Taylor T.A., Supply chain coordination under channel rebates with sales effort effects, Management Science, 48, pp. 992-1007, (2002); Warren A., Peers M., Video retailers have day in court-plaintiffs say supply deals between Block-buster Inc. and studios violates laws, The Wall Street Journal, (2012); Weltevreden J.W.J., B2c e-commerce logistics: The rise of collection-and-delivery points in The Netherlands, International Journal of Retail & Distribution Management, 36, pp. 638-660, (2008); Weng Z.K., Channel coordination and quantity discounts, Management Science, 41, pp. 1509-1522, (1995); Xie J.X., Wei J.C., Coordinating advertising and pricing in a manufacturer-retailer channel, European Journal of Operational Research, 197, pp. 785-791, (2009); Yang D., Jiao J.R., Ji Y., Du G., Helo P., Valente A., Joint optimization for coordinated configuration of product families and supply chains by a leader-follower Stackelberg game, European Journal of Operational Research, 246, pp. 263-280, (2015); Yuan X.F., Shi L., Li H.X., Research on the relationship between the logistics service quality and customer loyalty in C2C e-commerce, Thirteenth Wuhan International Conference on E-business, 2014, pp. 104-113, (2014); Zhang M.D., Fu Y., Zhao Z., Pratap S., Huang G.Q., Game theoretic analysis of horizontal carrier coordination with revenue sharing in e-commerce logistics, International Journal of Production Research, 57, pp. 1524-1551, (2019); Zhang M.D., Pratap S., Huang G.Q., Zhiheng Z., Optimal collaborative transportation service trading in B2B e-commerce logistics, International Journal of Production Research, 55, pp. 5485-5501, (2017)","H. Tang; Macau University of Science and Technology, Taipa, Macao; email: hjtang@must.edu.mo",null,"SAGE Publications Inc.",{"$nulls":5},2.158244E7,null,null,null,"English","SAGE Open","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85071732231"]
["Halaweh M.","Halaweh, Mohanad (25960639300)",2.59606393E10,"Implementation of the COD payment method on e-commerce websites in the Arab Region",2019.0,"International Journal of Business Information Systems",32.0,2.0,null,145.0,160.0,15.0,6.0,"10.1504/IJBIS.2019.103071","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85073621875&doi=10.1504%2fIJBIS.2019.103071&partnerID=40&md5=0f2cfadf3e37595c5a665f276e18ab00","College of Business Administration, Al Falah University, Dubai, United Arab Emirates","Halaweh M., College of Business Administration, Al Falah University, Dubai, United Arab Emirates","The cash on delivery (COD) payment method has been increasingly used in recent years as a method of payment in e-commerce transactions. However, research within the e-commerce field to determine how widely this payment method has been adopted is limited, especially from the e-commerce websites’ perspective, at the global level, and specifically in Arab countries. Therefore, the aim of this paper was to study the current use of COD in the Arab region by evaluating e-commerce websites that accept this payment method. The research findings showed that all surveyed e-commerce websites have adopted the COD payment method in addition to other e-payment options. The findings also revealed that there is no consistency in the icon/image used to indicate acceptance of this payment method or where it is located on the website. Results also revealed that there is lack of clarity in policies pertaining to this payment method. The interpretations of the research findings and implications as well as future research are discussed. Copyright © 2019 Inderscience Enterprises Ltd.","Acceptance; Adoption; Arab region; Cash on delivery; COD; E-commerce; E-payment; Information systems; Online payment methods; Online shopping",{"$nulls":7},"Barkhordari M., Nourollah Z., Mashayekhi H., Mashayekhi Y., Ahangar M., Factors influencing adoption of e-payment systems: An empirical study on Iranian customers, Information Systems and E-Business Management, 15, 1, pp. 89-116, (2017); Dastan I., Gurler C., Factors affecting the adoption of mobile payment systems: An empirical analysis, Emerging Markets Journal, 6, 1, pp. 16-24, (2016); Cash on Delivery Still Wins out among Digital Shoppers in Indonesia, (2017); Rebirth of E-Commerce in India, (2013); Top 25 Ecommerce Sites in Middle East & UAE Loved by Shoppers, (2016); Gangeshwer D., E-commerce or internet marketing: A business review from Indian context, International Journal of U-and eService, Science and Technology, 6, 6, pp. 187-194, (2013); Most Popular E-Commerce Sites of the Middle East, (2015); Gupta R., Ponnuru K., Kumar A., Trivedi S.K., Factors identification of online reputation and relationship with trust: A study of generation Y, International Journal of Business Information Systems, 26, 2, pp. 151-165, (2017); Halaweh M., Intention to adopt the cash on delivery (COD) payment model for e-commerce transactions: An empirical study, Computer Information Systems and Industrial Management CISIM 2017, Lecture Notes in Computer Science, (2017); Hamid N., Cheng A., A risk perception analysis on the use of electronic payment systems by young adult, WSEAS Transactions on Information Science and Applications, 10, 1, pp. 26-35, (2013); Hamid T., Cash on Delivery the Biggest Obstacle to E-Commerce in UAE and Region, (2014); Hussain Z., Wallace J., Tassabehji R., Khan O., E-business in the developing world: An empirical study of payment methods and their implications, International Journal of Electronic Business, 5, 3, pp. 315-335, (2007); Top 100 Ecommerce Online Shopping Websites in UAE, Middle East, GCC: A Complete List, (2016); E- And M-Commerce and Payment Sector Development in Vietnam, (2014); Kalaiarasi H., Lakshmi P., Stephan A., Adoption of self service banking channels – the case of mobile banking in India, International Journal of Business Information Systems, 26, 1, pp. 1-14, (2017); Kelkar N., Top 4 Ecommerce Websites of Kuwait & Middle East, (2014); Kim C., Tao W., Shin N., Kim K.S., An empirical study of customers’ perceptions of security and trust in e-payment systems, Electronic Commerce Research and Applications, 9, 1, pp. 84-95, (2010); Makki E., Chang L., E-commerce acceptance and implementation in Saudi Arabia: Previous, current and future factors, International Journal of Management Research and Business Strategy, 4, 3, pp. 29-44, (2015); Ozkan S., Bindusara G., Hackney R., Facilitating the adoption of e-payment system: Theoretical constructs and empirical analysis, Journal of Enterprise Information Management, 23, 3, pp. 305-325, (2010); Rouibah K., Electronic payment systems use and satisfaction in an Arabic country: Evidence from Kuwait, Issues in Information Systems, 16, 2, pp. 149-160, (2015); Yaseen H., Dingley K., Adams C., Capturing the growth of e-commerce in Jordan using a novel research approach, International Journal of Management and Commerce Innovations, 3, 2, pp. 811-827, (2016)","M. Halaweh; College of Business Administration, Al Falah University, Dubai, United Arab Emirates; email: Mohanad.Halaweh@afu.ac.ae",null,"Inderscience Publishers",{"$nulls":5},1.7460972E7,null,null,null,"English","Int. J. Bus. Inf. Syst.","Article","Final",null,"Scopus","2-s2.0-85073621875"]
["Zhou M.; Zhao L.; Kong N.; Campy K.S.; Xu G.; Zhu G.; Cao X.; Wang S.","Zhou, Min (55448863800); Zhao, L. (7404455064); Kong, Nan (7005055833); Campy, Kathryn S. (57194341433); Xu, Ge (58441720500); Zhu, G. (57210414933); Cao, Xianye (57193825581); Wang, Song (57194334654)","55448863800; 7404455064; 7005055833; 57194341433; 58441720500; 57210414933; 57193825581; 57194334654","Understanding consumers’ behavior to adopt self-service parcel services for last-mile delivery",2020.0,"Journal of Retailing and Consumer Services",52.0,null,101911.0,null,null,null,89.0,"10.1016/j.jretconser.2019.101911","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85070598259&doi=10.1016%2fj.jretconser.2019.101911&partnerID=40&md5=6e10faa7cd6c547659a783d6cce92096","College of Business Administration, Hunan University of Technology and Business, Changsha, China; School of Economics and Management, Southeast University, Nanjing, China; Weldon School of Biomedical Engineering, Purdue University, West Lafayette, United States; Center for Public Health Initiatives, University of Pennsylvania, Philadelphia, United States","Zhou M., College of Business Administration, Hunan University of Technology and Business, Changsha, China, School of Economics and Management, Southeast University, Nanjing, China, Weldon School of Biomedical Engineering, Purdue University, West Lafayette, United States; Zhao L., School of Economics and Management, Southeast University, Nanjing, China; Kong N., Weldon School of Biomedical Engineering, Purdue University, West Lafayette, United States; Campy K.S., Center for Public Health Initiatives, University of Pennsylvania, Philadelphia, United States; Xu G., College of Business Administration, Hunan University of Technology and Business, Changsha, China; Zhu G., College of Business Administration, Hunan University of Technology and Business, Changsha, China; Cao X., College of Business Administration, Hunan University of Technology and Business, Changsha, China; Wang S., College of Business Administration, Hunan University of Technology and Business, Changsha, China","Self-service parcel delivery service has been favored by E-commerce retailers as an effective solution to the “last-mile” delivery, and consumers' adoption behavior is the key point to apply this emerging technology. The aim of the present study is to empirically test the influence of psychological factors on online consumers’ behavioral intention to adopt it. An extended UTAUT model is developed and 525 structured questionnaires were collected. Empirical results demonstrate that performance expectancy, effort expectancy, social influence and facilitating conditions are positive determinants, while perceived risk was negatively factor to behavioral intention. The difference in the behavioral intention among demographic groups was examined as it might provide an opportunity for developing a new strategy to promote the application of self-service parcel delivery service for last-mile delivery. © 2019 Elsevier Ltd","China; Perceived risk; Perceived satisfaction; Self-service parcel delivery service; UTAUT","China; consumption behavior; electronic commerce; information technology; performance assessment; retailing; risk perception; service provision; technology adoption",{"$nulls":4},"2017 Youth Innovation Driven Project in Hunan University of Technology and Business, China, (17QD06); Agency for Health Research and Quality; China Health and Health Commission; Social Science Fund of Hunan Province, China, (15YBA238); National Science Foundation, NSF; National Cancer Institute, NCI; Air Force Office of Scientific Research, AFOSR; Centers for Medicare and Medicaid Services, CMS; National Natural Science Foundation of China, NSFC, (71601043, 71704052); Anhui Development and Reform Commission","Funding text 1:  Min Zhou. He is an associate professor in Hunan University of Technology and Business. He was also worked as a postdoctoral at Southeast University and Purdue University. He received the Ph.D. in system engineering from Central South University in 2013. His research interests concern health service behavior and decision making. He has published over 20 papers peer-reviewed journal articles on international journals and conference proceedings. His research has been or currently being funded by the National Natural Science Foundation of China, China Development and Reform Commission, and China Health and Health Commission. ; Funding text 2:  Nan Kong. He is an associate professor in the Weldon School of Biomedical Engineering at Purdue University. He received his PhD in industrial engineering from the University of Pittsburgh in 2006. His research interest includes healthcare operations management, in particular healthcare network design, provider staff scheduling, and within-network patient flow control. Recently, he has expanded his research to machine learning for biomedicine. He has published over 50 peer-reviewed journal articles. He is an Associate Editor for the IIE Transactions on Healthcare Systems Engineering and for the International Conference on Automation Science and Engineering. His research has been or currently being funded by the National Science Foundation, National Cancer Institute, Agency for Health Research and Quality, Centers for Medicare and Medicaid Services, and Air Force Office of Scientific Research. He is currently President of the Public Sector OR Section in INFORMS and Committee Chair for the INFORMS Undergraduate Operations Research Prize. ; Funding text 3: This work was supported by the National Natural Science Foundation of China (NSFC) [grant number 71601043 , 71704052 ]; the Social Science Fund of Hunan Province, China [grant number 15YBA238 ]; and 2017 Youth Innovation Driven Project in Hunan University of Technology and Business, China [grant number 17QD06 ].  ","Alalwan A.A., Dwivedi Y.K., Rana N.P., Algharabat R., Examining factors influencing Jordanian customers' intentions and adoption of internet banking: extending UTAUT2 with risk, J. Retail. Consum. 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Behav., 26, 4, pp. 760-767, (2010); Zhuo J., Wei J., Liu L.C., Koong K.S., Miao S., An examination of the determinants of service quality in the Chinese express industry, Electron. Mark., 23, 2, pp. 163-172, (2013)","M. Zhou; College of Business Administration, Hunan University of Technology and Business, Changsha, NO.569 Yuelu Avenue, 410205, China; email: zhouminlaoshi@163.com",null,"Elsevier Ltd",{"$nulls":5},9696989.0,null,null,null,"English","J. Retail. Consum. Serv.","Article","Final",null,"Scopus","2-s2.0-85070598259"]
["Guo X.; Lujan Jaramillo Y.J.; Bloemhof-Ruwaard J.; Claassen G.D.H.","Guo, Xuezhen (56059300400); Lujan Jaramillo, Yngrid Jaqueline (57211011101); Bloemhof-Ruwaard, Jacqueline (6602637314); Claassen, G.D.H. (6602338348)","56059300400; 57211011101; 6602637314; 6602338348","On integrating crowdsourced delivery in last-mile logistics: A simulation study to quantify its feasibility",2019.0,"Journal of Cleaner Production",241.0,null,118365.0,null,null,null,66.0,"10.1016/j.jclepro.2019.118365","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85072259210&doi=10.1016%2fj.jclepro.2019.118365&partnerID=40&md5=b26397c0521b48038575b64b1e9fedfe","Wageningen Food & Biobased Research, Amsterdam Institute for Advanced Metropolitan Solutions, Operations Research and Logistics Group, Wageningen University, Netherlands; Operations Research and Logistics Group, Wageningen University, Netherlands","Guo X., Wageningen Food & Biobased Research, Amsterdam Institute for Advanced Metropolitan Solutions, Operations Research and Logistics Group, Wageningen University, Netherlands; Lujan Jaramillo Y.J., Operations Research and Logistics Group, Wageningen University, Netherlands; Bloemhof-Ruwaard J., Operations Research and Logistics Group, Wageningen University, Netherlands; Claassen G.D.H., Operations Research and Logistics Group, Wageningen University, Netherlands","The fast-growing practice of e-commerce implies a strong increase in parcel deliveries, which in turn creates significant pressure on last-mile city logistics. Due to the important role the city transportation plays in energy use and greenhouse gas emission, effective last-mile solutions in cities must be developed to contribute to sustainability and a cleaner world economy. Crowdsourced delivery as an emerging “sharing economy” initiative can be an effective tool to mitigate the problems emerging from the last-mile city logistics. To valorise the benefits of crowdsourced delivery, a transition towards a hybrid city logistic system is required where crowdsourced delivery and the conventional delivery networks are closely integrated. Due to the lack of theoretical guidelines for crowdsourced delivery integration, this research develops a conceptual framework to facilitate last-mile city logistics transition adopting the multi-level socio-technical transition theory as the basis. The core of the conceptual framework is the “five basic principles” to be followed by stakeholders when designing intervening niche innovations at the current stage of system transition. To demonstrate the usability of the conceptual framework, an illustrative discrete event simulation study with specific settings that fits in with the current status of last-mile city logistics is conducted. Results show that incorporating crowdsourced delivery as a supplement to the conventional delivery network, following the five basic principles proposed by the conceptual framework can reduce the last-mile logistic costs. Moreover, the offline participation rate plays a key role in ensuring the feasibility of the new hybrid last-mile model. To conclude, the developed conceptual framework has a great potential of improving last-mile delivery in the era of e-commerce and having a critical scale of potential deliverer pool is the prerequisite for the successful application of crowdsourced deliveries. © 2019","Crowdsourced delivery; E-commerce; Last miles; Sharing economy; Sustainable city logistics","Discrete event simulation; Electronic commerce; Greenhouse gases; Conceptual frameworks; Crowdsourced delivery; Last mile; Last mile solutions; Sharing economy; Socio-technical transitions; Sustainable cities; System transitions; Crowdsourcing",{"$nulls":6},"Archetti C., Savelsbergh M., Speranza M.G., The vehicle routing problem with occasional drivers, Eur. J. Oper. Res., 254, pp. 472-480, (2016); Arslan A., Agatz N., Kroon L., Zuidwijk R., Crowdsourced delivery-a pickup and delivery problem with ad-hoc drivers, SSRN Electron. J., pp. 1-29, (2016); Arslan A.M., Et al., Crowdsourced delivery—a dynamic pickup and delivery problem with ad hoc drivers, Transp. Sci., 53, 1, pp. 222-235, (2018); Basik F., Et al., Fair task allocation in crowdsourced delivery, IEEE Trans. Serv. Comput., (2018); Binetti M., Et al., A sustainable crowdsourced delivery system to foster free-floating bike-sharing, Sustainability, 11, 10, (2019); Castillo V.E., Et al., Crowdsourcing last mile delivery: strategic implications and future research directions, J. Bus. Logist., 39, 1, pp. 7-25, (2018); Crainic T.G., Montreuil B., Physical internet enabled Hyperconnected City logistics, Transp. Res. Procedia, 12, pp. 383-398, (2016); Dablanc L., Morganti E., Arvidsson N., Woxenius J., Browne M., Saidi N., The rise of on-demand ‘instant deliveries’ in European cities, Supply Chain Forum: An. Int. J. Taylor & Francis, pp. 203-217, (2017); Dai H., Liu P., Workforce planning for O2O delivery systems with crowdsourced drivers, Ann. Oper. Res., pp. 1-27, (2019); Devari A., Nikolaev A.G., He Q., Crowdsourcing the last mile delivery of online orders by exploiting the social networks of retail store customers, Transp. Res. E Logist. Transp. Rev., 105, pp. 105-122, (2017); Dye C., Health and urban living, Science, 319, pp. 766-769, (2008); Ecommerce Foundation, Global B2C E-commerce report 2016, (2016); Ecommerce News, Ecommerce in the Netherlands - Ecommerce News, (2018); European Commission, Climate action: reducing CO2 emissions from passenger cars, (2010); Fatnassi E., Et al., Planning and operating a shared goods and passengers on-demand rapid transit system for sustainable city-logistics, Transp. Res. Part B: Methodological, 81, pp. 440-460, (2015); Galante N., Lopez E.G., Monroe S., The Future of Online Grocery in Europe, pp. 22-31, (2013); Gammelgaard B., The emergence of city logistics: the case of Copenhagen's Citylogistik-kbh, Int. J. Phys. Distrib. Logist. Manag., 45, pp. 333-351, (2015); Geels F.W., Technological transitions as evolutionary reconfiguration processes: a multi-level perspective and a case-study, Res. Policy, 31, pp. 1257-1274, (2002); Geels F.W., The multi-level perspective on sustainability transitions: responses to seven criticisms, Environ. Innovat. Soc. Trans., 1, pp. 24-40, (2011); Ghilas V., Demir E., Van Woensel T., Integrating Passenger and Freight Transportation: Model Formulation and Insights, Beta Working Papers WP, 441, (2013); Gorczynski T., Kooijman D., The real estate effects of E-commerce for supermarkets in The Netherlands, Int. Rev. Retail Distrib. Consum. Res., 25, pp. 379-406, (2015); Hamari J., Sjoklint M., Ukkonen A., The sharing economy: why people participate in collaborative consumption, J. Assoc. Inf. Sci. Technol., 67, pp. 2047-2059, (2016); Huang Y., Oppewal H., Why consumers hesitate to shop online: an experimental choice analysis of grocery shopping and the role of delivery fees, Int. J. Retail Distrib. Manag., 34, pp. 334-353, (2006); Kafle N., Zou B., Lin J., Design and modeling of a crowdsource-enabled system for urban parcel relay and delivery, Transp. Res. Part B Methodol., 99, pp. 62-82, (2017); Li B., Krushinsky D., Reijers H.A., Van Woensel T., The share-a-ride problem: people and parcels sharing taxis, Eur. J. Oper. Res., 238, pp. 31-40, (2014); Li B., Krushinsky D., Van Woensel T., Reijers H.A., An adaptive large neighborhood search heuristic for the share-a-ride problem, Comput. Oper. Res., 66, pp. 170-180, (2016); Martin C.J., The sharing economy: a pathway to sustainability or a nightmarish form of neoliberal capitalism?, Ecol. Econ., 121, pp. 149-159, (2016); Masson R., Trentini A., Lehuede F., Malhene N., Peton O., Tlahig H., Optimization of a city logistics transportation system with mixed passengers and goods, EURO J. Transp. Logist., 6, pp. 81-109, (2017); Morganti E., Seidel S., Blanquart C., Dablanc L., Lenz B., The impact of E-commerce on final deliveries: alternative parcel delivery services in France and Germany, Transp. Res. Procedia, 4, pp. 178-190, (2014); Moriarty P., Honnery D., Greening passenger transport: a review, J. Clean. Prod., 54, pp. 14-22, (2013); Nielsen, What's In-Store for Online Grocery Shopping: Omni Channel Strategies to Reach Crossover Shoppers, (2017); Paloheimo H., Lettenmeier M., Waris H., Transport reduction by crowdsourced deliveries–a library case in Finland, J. Clean. Prod., 132, pp. 240-251, (2016); Punel A., Stathopoulos A., Modelling the acceptability of crowdsourced goods deliveries: role of context and experience effects, Transp. Res. E Logist. Transp. Rev., 105, pp. 18-38, (2017); Punel A., Et al., Push and pull factors in adopting a crowdsourced delivery system, Transp. Res. Rec., (2019); Rouges J.-F., Montreuil B., Crowdsourcing delivery: new interconnected business models to reinvent delivery, 1st International Physical Internet Conference, pp. 28-30, (2014); Savelsbergh M., Van Woensel T., 50th anniversary invited article—city logistics: challenges and opportunities, Transp. Sci., 50, pp. 579-590, (2016); Song L., Guan W., Cherrett T., Li B., Quantifying the greenhouse gas emissions of local collection-and-delivery points for last-mile deliveries, Transp. Res. Rec.: J. Transp. Res. Board, pp. 66-73, (2013); Statista, Netherlands: total number of Jumbo supermarkets 2011-2017 | Statistic, (2018); Syndicate Plus, The Online Grocery Shopper, (2014); Vaghi C., Percoco M., City Logistics in Italy: Success Factors and Environmental Performance. City Distribution and Urban Freight Transport: Multiple Perspectives, pp. 151-175, (2011); Van Cooten C., Crowdsourced Delivery the Traditional Delivery Method Reinvented, (2016); Van der Slikke T., Online Retailing in the Food Industry, (2015); Wang X., Zhan L., Ruan J., Zhang J., How to choose “last mile” delivery modes for E-fulfilment, Math. Probl. Eng., 2014, (2014); Wang Y., Zhang D., Liu Q., Shen F., Lee L.H., Towards enhancing the last-mile delivery: an effective crowd-tasking model with scalable solutions, Transp. Res. E Logist. Transp. Rev., 93, pp. 279-293, (2016)","X. Guo; Wageningen Food & Biobased Research, Amsterdam Institute for Advanced Metropolitan Solutions, Operations Research and Logistics Group, Wageningen University, Netherlands; email: Xuezhen.guo@wur.nl",null,"Elsevier Ltd",{"$nulls":5},9596526.0,null,"JCROE",null,"English","J. Clean. Prod.","Article","Final",null,"Scopus","2-s2.0-85072259210"]
["Suresh V.; Venugopalan G.; Jeyabalan S.; Kumar A.L.","Suresh, V. (57210683403); Venugopalan, G. (57209465709); Jeyabalan, S. (57214943449); Kumar, A. Lakshman (57191852623)","57210683403; 57209465709; 57214943449; 57191852623","A study on perceiver determinants to influence the E-commerce purchase for branded laptop",2019.0,"International Journal of Recent Technology and Engineering",8.0,1.0,null,495.0,499.0,4.0,0.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85067851652&partnerID=40&md5=72b52f8d05445e0c297e4b0d61f29eee","Faculty of Management, SRM Institute of Science and Technology, Tamil Nadu, India; Dept. Of Computer Science Engineering., Anand Institute of Higher Technology, Chennai, Tamil Nadu, India","Suresh V., Faculty of Management, SRM Institute of Science and Technology, Tamil Nadu, India; Venugopalan G., Faculty of Management, SRM Institute of Science and Technology, Tamil Nadu, India; Jeyabalan S., Dept. Of Computer Science Engineering., Anand Institute of Higher Technology, Chennai, Tamil Nadu, India; Kumar A.L., Faculty of Management, SRM Institute of Science and Technology, Tamil Nadu, India","The rapid development of Information Technology (IT) has lead to increase the sales of branded laptop/notebooks across the world. According to Gartner’s total shipments of PC’s worldwide reported the amount of around 290 million units in 2015 and the top PC sellers were Lenovo, HP, Dell Apple and Asus. This study analyses the branded laptop on e-commerce only. This study measured that there are nineteen features which influence consumers’ laptop purchase decisions on e-commerce. I trust that these websites would not do anything intentional that prejudice the user of branded laptop, It is short time period of home delivery facility of branded laptop, It is easy to cancel orders of branded laptop online, It is easy to return the products of branded laptop back through online websites, I don’t have to pay extra charges to branded laptops, I feel my personal information won't be leaked out when i order branded laptop online, I will receive the products of branded laptop on time as detailed out at website, I am very much satisfied at the availability of genuine shipper and product details of branded laptop in E-commerce site, It is very easy to access all type of information about laptop brand through social media, E-commerce is very easy to purchase the laptop brand than traditional, E-commerce takes minimum time to search the laptop brands than traditional channels, the quality trust of accuracy and reliability of information about laptop brands, I trust in purchasing a branded laptop through ecommerce websites, I will get what i ordered through an ecommerce websites, It is very easy to purchase laptop brands via E-commerce, It is very easy to share and guide information about laptop brand via social media, It is very easy to open the information about laptop brands at communities, It is very easy to communicate quickly with groups about laptop brands via social media and It is very easy to announce their views to the users of laptop brands at social media. Based on data collected from 824 branded laptop buyers on e-commerce at Chennai city, exploratory factor analysis were analyzed the perceivers’ determinants to impact the e-commerce purchase for laptop brand on e-commerce at Chennai city. © BEIESP.","Electronic-commerce and perceiver determinants; Laptop brands",{"$nulls":7},"Darley W.K., Blankson C., Luethge D.J., Toward an integrated framework for online consumer behavior and decision making process: A review, Psychology & Marketing, 27, 2, pp. 94-116, (2010); Aslihan Nasir V., Yoruker S., Gunes F., Ozdemir Y., Factors influencingconsumers’laptop Purchases, (2015); Cronin J.J., Brady M.K., Hult G.T.M., Assessing the effects of quality, value, and customer satisfaction on consumer behavioral intentions in service environments, Journal of Retailing, 76, 2, pp. 193-218, (2000); Jacksone C., Poulose J., Krishnan P., Mundeja S., Deep V., Singh V., Identifying the Factors of Customer Satisfaction in an E-Commerce Venture in India, (2014); Goolsbee A., Competition in the computer industry: Online versus retail, The Journal of Industrial Economics, 49, 4, pp. 487-499, (2001); Nasir V.A., Yoruker S., Gunes F., Ozdemir Y., FACTORS INFLUENCING CONSUMERS’LAPTOP PURCHASES, (2006); Kotler P., Keller K.L., Dirección De Marketing, (2009)",null,null,"Blue Eyes Intelligence Engineering and Sciences Publication",{"$nulls":5},2.2773878E7,null,null,null,"English","Int. J. Recent Technol. Eng.","Article","Final",null,"Scopus","2-s2.0-85067851652"]
["Weidinger F.; Boysen N.; Schneider M.","Weidinger, Felix (57194323182); Boysen, Nils (16201940600); Schneider, Michael (57192278274)","57194323182; 16201940600; 57192278274","Picker routing in the mixed-shelves warehouses of e-commerce retailers",2019.0,"European Journal of Operational Research",274.0,2.0,null,501.0,515.0,14.0,50.0,"10.1016/j.ejor.2018.10.021","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85055561530&doi=10.1016%2fj.ejor.2018.10.021&partnerID=40&md5=5f8401458d9bfe36a6f679e04fd86618","Friedrich-Schiller-Universität Jena Lehrstuhl für Operations Management, Carl-Zeiss-Str. 3, 07743 Jena, Germany; RWTH Aachen University, Deutsche Post Chair Optimization of Distribution Networks, Kackertstr. 7, 52072, Aachen, Germany","Weidinger F., Friedrich-Schiller-Universität Jena Lehrstuhl für Operations Management, Carl-Zeiss-Str. 3, 07743 Jena, Germany; Boysen N., Friedrich-Schiller-Universität Jena Lehrstuhl für Operations Management, Carl-Zeiss-Str. 3, 07743 Jena, Germany; Schneider M., RWTH Aachen University, Deutsche Post Chair Optimization of Distribution Networks, Kackertstr. 7, 52072, Aachen, Germany","E-commerce retailers face the challenge to assemble large numbers of time-critical picking orders, of which each typically consists of just a few order lines and low order quantities. To efficiently solve this task, many warehouses in this segment are organized according to the mixed-shelves paradigm. Incoming unit loads are isolated into single units, which are randomly spread all over the shelves of the warehouse. In such a setting, the probability that a picker always finds a demanded stock keeping unit (SKU) close-by is high, irrespective of his/her current position in the warehouse. In spite of this organizational adaption, picker routing, i.e., the sequencing of shelf visits when retrieving a set of picking orders, is still an important optimization problem. In a mixed-shelves warehouse, picker routing is much more complex than in traditional environments: Multiple orders are concurrently assembled by each picker, many alternative depots are available, and items of the same SKU are available in multiple shelves. This paper defines the resulting picker-routing problem in mixed-shelves warehouses and provides efficient solution methods. Furthermore, we use the developed methods to explore important managerial aspects. Specifically, we benchmark mixed-shelves storage against traditional storage policies for scenarios with different ratios between small-sized and large-sized orders. In this way, we investigate whether mixed-shelves storage is also a suitable policy if an omni-channel sales strategy is pursued, and large-sized orders of brick-and-mortar stores as well as small-sized online orders are to be jointly processed by the same warehouse. © 2018 Elsevier B.V.","Facility logistics; Mixed-shelves; Picker routing; Warehousing","Electronic commerce; Sales; Facility logistics; Managerial aspects; Mixed-shelves; Optimization problems; Picker routing; Sales strategies; Stock keeping unit; Warehousing; Warehouses",{"$nulls":6},"Agatz N.A., Fleischmann M., Van Nunen J.A., E-fulfillment and multi-channel distribution - a review, European Journal of Operational Research, 187, pp. 339-356, (2008); Akkerman R., Farahani P., Grunow M., Quality, safety and sustainability in food distribution: A review of quantitative operations management approaches and challenges, OR Spectrum, 32, pp. 863-904, (2010); Bartholdi J.J., (2014); Brynjolfsson E., Hu Y.J., Smith M.D., Consumer surplus in the digital economy: Estimating the value of increased product variety at online booksellers, Management Science, 49, pp. 1580-1596, (2003); Daniels R.L., Rummel J.L., Schantz R., A model for warehouse order picking, European Journal of Operational Research, 105, pp. 1-17, (1998); Gallien J., Weber T., To wave or not to wave? Order release policies for warehouses with an automated sorter, Manufacturing & Service Operations Management, 12, pp. 642-662, (2010); Ghiani G., Improta G., An efficient transformation of the generalized vehicle routing problem, European Journal of Operational Research, 122, pp. 11-17, (2000); Gu J., Goetschalckx M., McGinnis L.F., Research on warehouse operation: A comprehensive review, European Journal of Operational Research, 177, pp. 1-21, (2007); Gu J., Goetschalckx M., McGinnis L.F., Research on warehouse design and performance evaluation: A comprehensive review, European Journal of Operational Research, 203, pp. 539-549, (2010); Hong S., Johnson A.L., Peters B.A., Batch picking in narrow-aisle order picking systems with consideration for picker blocking, European Journal of Operational Research, 221, pp. 557-570, (2012); Johnson E., Meller R.D., Performance analysis of split-case sorting systems, Manufacturing & Service Operations Management, 4, pp. 258-274, (2002); Karp R.M., Reducibility among combinatorial problems, Complexity of computer computations, pp. 85-103, (1972); de Koster R., Le-Duc T., Roodbergen K.J., Design and control of warehouse order picking: A literature review, European Journal of Operational Research, 182, pp. 481-501, (2007); de Koster R., van der Poort E.S., Routing orderpickers in a warehouse: A comparison between optimal and heuristic solutions, IIE Transactions, 30, pp. 469-480, (1998); Laudon K.C., Traver C.G., E-commerce, (2007); Montoya-Torres J.R., Franco J.L., Isaza S.N., Jimenez H.F., Herazo-Padilla N., A literature review on the vehicle routing problem with multiple depots, Computers & Industrial Engineering, 79, pp. 115-129, (2015); Ratliff H.D., Rosenthal A.S., Order-picking in a rectangular warehouse: A solvable case of the traveling salesman problem, Operations Research, 31, pp. 507-521, (1983); Roodbergen K.J., de Koster R., Routing order pickers in a warehouse with a middle aisle, European Journal of Operational Research, 133, pp. 32-43, (2001); Schneider M., Schneider A., Hof J., An adaptive VNS algorithm for vehicle routing problems with intermediate stops, OR Spectrum, 37, pp. 353-387, (2015); Weidinger F., Picker routing in rectangular mixed shelves warehouses, Computers & Operations Research, 95, pp. 139-150, (2018); Weidinger F., (2018); Yaman H., Karasan O.E., Kara B.Y., Release time scheduling and hub location for next-day delivery, Operations Research, 60, pp. 906-917, (2012)","M. Schneider; RWTH Aachen University, Deutsche Post Chair Optimization of Distribution Networks, Aachen, Kackertstr. 7, 52072, Germany; email: schneider@dpo.rwth-aachen.de",null,"Elsevier B.V.",{"$nulls":5},3772217.0,null,"EJORD",null,"English","Eur J Oper Res","Article","Final",null,"Scopus","2-s2.0-85055561530"]
["Ulmer M.W.; Streng S.","Ulmer, Marlin W. (57147181500); Streng, Sebastian (57208079906)","57147181500; 57208079906","Same-Day delivery with pickup stations and autonomous vehicles",2019.0,"Computers and Operations Research",108.0,null,null,1.0,19.0,18.0,63.0,"10.1016/j.cor.2019.03.017","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85063747998&doi=10.1016%2fj.cor.2019.03.017&partnerID=40&md5=4a4e62ab1b91184497a226236ac47ca8","Technische Universität Braunschweig, Institut für Wirtschaftsinformatik, Mühlenpfordtstraße 23, Braunschweig, 38106, Germany","Ulmer M.W., Technische Universität Braunschweig, Institut für Wirtschaftsinformatik, Mühlenpfordtstraße 23, Braunschweig, 38106, Germany; Streng S., Technische Universität Braunschweig, Institut für Wirtschaftsinformatik, Mühlenpfordtstraße 23, Braunschweig, 38106, Germany","Same-day delivery has become a very important challenge for e-commerce providers. However, effective delivery concepts are still not established. In this paper, we analyze the potential of combining parcel pickup stations and autonomous vehicles for same-day delivery. This combination may allow for consolidation of goods, automated delivery processes, and reduced operation costs. We consider the problem on the operational planning level. A depot, a set of pickup stations, and an autonomous delivery fleet are given. Customers dynamically order goods to a preferred pickup station and expect fast service. The goods need to be delivered from the depot to the preferred pickup station or another pickup station in the close neighborhood. Autonomous vehicles are directly dispatched between the depot and the stations. To decide where and when to dispatch a vehicle and about the corresponding goods to load, we present a policy function approximation (PFA). Our intuitive PFA allows real-time decision making while balancing the tradeoff between fast delivery and consolidation. We conduct an extensive computational study for the pickup station network of the city of Braunschweig. We show how our delivery concept allows fast delivery for up to 100 delivered goods per vehicle and day. We further pair the PFA with a value function approximation to account for heterogeneity in demand. We finally derive important managerial insights for strategical and tactical planning and present an extensive outlook on promising future research directions. © 2019 Elsevier Ltd","Autonomous vehicles; Dynamic dispatching; Dynamic vehicle routing; Pickup stations; Policy function approximation; Same-Day delivery","Decision making; Pickups; Vehicle routing; Computational studies; Dynamic Vehicle Routing; Function approximation; Future research directions; Operational planning; Real time decision-making; Same-Day delivery; Value function approximation; Autonomous vehicles",{"$nulls":6},"Agatz N., Bouman P., Schmidt M., Optimization approaches for the traveling salesman problem with drone, Transp. 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Part C, 54, pp. 86-109, (2015); NHTSA, Automated driving systems: a vision for safety, (2017); Nothdurft T., Hecker P., Ohl S., Saust F., Maurer M., Reschka A., Bohmer J.R., Stadtpilot: First fully autonomous test drives in urban traffic, Intelligent Transportation Systems (ITSC), 2011 14th International IEEE Conference on, pp. 919-924, (2011); Persiel S., DHL und Deutsche Post in Braunschweig - Paketzentrum von DHL, (2017); Powell W., Approximate Dynamic Programming: Solving the Curses of Dimensionality, (2011); Ram A., UK Retailers face high cost of online deliveries, Financ. Times, (2015); Reyes D., Savelsbergh M., Toriello A., Vehicle routing with roaming delivery locations, Transp. Res. Part C, 80, pp. 71-91, (2017); Rivera A.E.P., Mes M.R.K., Anticipatory freight selection in intermodal long-haul round-trips, Transp. Res. Part E, 105, pp. 176-194, (2017); (2016); Savelsbergh M., Van Woensel T., 50Th anniversary invited article—city logistics: challenges and opportunities, Transp. Sci., 50, 2, pp. 579-590, (2016); Scherr Y.O., Neumann-Saavedra B.A., Hewitt M., Mattfeld D.C., Service network design for same day delivery with mixed autonomous fleets, Transp. Res. Procedia, 30, pp. 23-32, (2018); Scherr Y.O., Saavedra B.A.N., Hewitt M., Mattfeld D.C., Service network design with mixed autonomous fleets, Transp. Res. Part E, 124, pp. 40-55, (2019); Stevenson R., Black T., Amazon spurs delivery startups with shot at $300,000 profit, Bloomberg, (2018); Tipping A., Kauschke P., Shifting patterns, the future of the logistics industry, PriceWaterhouseCoopers, Phoenix, (2016); Ulmer M., Delivery deadlines in same-day delivery, Logist. Res., 10, 3, pp. 1-15, (2017); Ulmer M.W., Dynamic pricing and routing for same-day delivery, (2017); Ulmer M.W., Thomas B.W., Same-day delivery with heterogeneous fleets of drones and vehicles, Networks, 72, 4, pp. 475-505, (2018); Ulmer M.W., Thomas B.W., Campbell A.M., Woyak N., The restaurant meal delivery problem: dynamic pick-up and delivery with deadlines and random ready times, (2017); Ulmer M.W., Thomas B.W., Mattfeld D.C., Preemptive depot returns for dynamic same-day delivery, EURO J. Transp. Logist., (2018); Vakulenko Y., Hellstrom D., Hjort K., What'S in the parcel locker? exploring customer value in e-commerce last mile delivery, J. Bus. Res., 88, pp. 421-427, (2018); Verlinde S., Rojas C., Buldeo Rai H., Kin B., Macharis C., E-consumers and their perception of automated parcel stations, City Logistics 3: Towards Sustainable and Liveable Cities, pp. 147-160, (2018); Voccia S.A., Campbell A.M., Thomas B.W., The same-day delivery problem for online purchases, Transp. Sci., 53, 1, pp. 167-184, (2019); Yuen K.F., Wang X., Ng L.T.W., Wong Y.D., An investigation of customers’ intention to use self-collection services for last-mile delivery, Transp. Policy, 66, pp. 1-8, (2018); Zhang S., Ohlmann J.W., Thomas B.W., Dynamic orienteering on a network of queues, Transp. Sci., 52, 3, pp. 691-706, (2018); Zhou L., Baldacci R., Vigo D., Wang X., A multi-depot two-echelon vehicle routing problem with delivery options arising in the last mile distribution, Eur. J. Oper. Res., 265, 2, pp. 765-778, (2018)","M.W. Ulmer; Technische Universität Braunschweig, Institut für Wirtschaftsinformatik, Braunschweig, Mühlenpfordtstraße 23, 38106, Germany; email: m.ulmer@tu-braunschweig.de",null,"Elsevier Ltd",{"$nulls":5},3050548.0,null,"CMORA",null,"English","Comp. Oper. Res.","Article","Final",null,"Scopus","2-s2.0-85063747998"]
["Custodio L.; Machado R.","Custodio, Larissa (57212209240); Machado, Ricardo (57191675428)","57212209240; 57191675428","Flexible automated warehouse: a literature review and an innovative framework",2020.0,"International Journal of Advanced Manufacturing Technology",106.0,"2024-02-01",null,533.0,558.0,25.0,67.0,"10.1007/s00170-019-04588-z","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85076225920&doi=10.1007%2fs00170-019-04588-z&partnerID=40&md5=e0159303f55737a8ac4476f4da0415fd","Postgraduate Program in Industrial and Systems Engineering, Pontifical Catholic University of Goiás - PUC, Goiás, Brazil","Custodio L., Postgraduate Program in Industrial and Systems Engineering, Pontifical Catholic University of Goiás - PUC, Goiás, Brazil; Machado R., Postgraduate Program in Industrial and Systems Engineering, Pontifical Catholic University of Goiás - PUC, Goiás, Brazil","The logistics market has been impacted by increase of e-commerce, mass customization, omni-channel distribution, and just-in-time philosophy. In order to attend to this dynamic change, automation has been applied in warehouses. Although, some researches point out the lack of flexibility as a bottleneck. Therefore, a comprehensive literature review of recent papers is vital to draw a framework of the past and to shed light on future directions. This paper aims to review published papers in the last ten years related to flexible automation in warehouses and to construct a framework that could guide future researchers in the construction of an innovative conceptual model that may be applied at warehouses in the future. A total of 113 papers published between January 2008 and December 2018 have been selected, reviewed, and categorized to construct a useful foundation of past research. Results showed the key point to achieve a flexible automated warehouse is the combination of automated equipment, data collection technologies, and management solutions. Finally, based on the reviewed papers, an innovative framework of a flexible automated warehouse is proposed. © 2019, Springer-Verlag London Ltd., part of Springer Nature.","Automated warehouse; Distribution center; Flexible automation; Material handling equipment; Order picking system","Automation; Materials handling; Automated warehouse; Distribution centers; Flexible automation; Material handling equipments; Order-picking systems; Warehouses",{"$nulls":4},"Brazilian funding agency FAPEG","This study received financial support from the Brazilian funding agency FAPEG. ",{"$cut":{"chars":23223,"head":"Goetschalckx M., Ashayeri J., Classification and design of order picking, Logistics World, 2, 2, pp. 99-106, (1989); Jovane F., Koren Y., Boer C.R., Present and future of flexible automation: towards new paradigms, CIRP Ann Manuf Technol, 52, 2, pp. 543-560, (2003); Casado F., Losada D.P., Santana-Alonso A., Et al., Pose estimation and object tracking using 2d images, Procedia Manuf, 11, pp. 63-71, (2017); Petkovic T., Markovic I., Petrovic I., Human Intention Recognition in Flexible Robotized Warehouses Based on Markov Decision Processes, ROBOT 2017: Third Iberian Robotics Conference, pp. 629-640, (2017); Yamazaki Y., Shigematsu K., Kato S., Kojima F., Onari H., Takata S., Design method of material handling systems for lean automation—integrating equipment for reducing wasted waiting time, CIRP Ann Manuf Technol, 66, 1, pp. 449-452, (2017); Buckova M., Krajcovic M., Jerman B., Impact of digital factory tools on designing of warehouses, J Appl Eng Sci, 15, 2, pp. 173-180, (2017); Wang Q., McIntosh R., Brain M., A new-generation automated warehousing capability, Int J Comput Integr Manuf, 23, 6, pp. 565-573, (2010); Mancio V.G., Sellitto M.A., Sistemas flexíveis de manufatura: definições e quadro de trabalho para futura pesquisa, Revista GEINTEC-gestão Inovaç,ão e Tecnologias, 7, 2, pp. 3760-3773, (2017); Basile F., Chiacchio P., Del Grosso D., A control oriented model for manual-pick warehouses, Control Eng Pract, 20, 12, pp. 1426-1437, (2012); Lopez J., Perez D., Vaamonde I., Paz E., Vaamonde A., Cabaleiro J., Building a warehouse control system using ride, Robot 2015: Second Iberian Robotics Conference, pp. 757-768, (2016); Groover M.P., Fundamentals of Modern Manufacturing: Materials Processes, and Systems, (2007); Craig J.J., Introduction to robotics, mechanics and control, (2013); Macduffie J.P., Pil F.K., From Fixed to Flexible: Automation and Work Organization Trends from the International Assembly Plant, (1997); Gania I.P., Stachowiak A., Oleskow-Szlapka J., Flexible Manufacturing Systems Industry 4.0 Solution Number Icpr, (2017); Wiktorsson M., Granlund A., Lundin M., Sodergren B., Automation and Flexibility: An Apparent Or Real Dilemma? In: Innovative Quality Improvements in Operations, pp. 35-48, (2017); Zuniga E.R., Moris M.U., Syberfeldt A., Integrating simulation-based optimization, lean, and the concepts of industry 4.0, 2017 Winter Simulation Conference (WSC), pp. 3828-3839, (2017); Ying Y., Wang X., Zhong R.Y., Huang G.Q., E-commerce logistics in supply chain management implementations and future perspective in furniture industry, Ind Manage Data Syst, 117, 10, pp. 2263-2286, (2017); Kaihara T., Yao Y., A new approach on cps-based scheduling and wip control in process industries, Proceedings of the 2012 Winter Simulation Conference (WSC), pp. 1-11, (2012); Supply chain management, TERMS and GLOSSARY, (2013); Goetschalckx M., McGinnis L., Sharp G., Bodner D., Govindaraj T., Huang K., Development of a Design Methodology for Warehousing Systems: Hierarchical Framework, (2002); de Koster R., Le-Duc T., Jan Roodbergen K., Design and control of warehouse order picking: a literature review, Eur J Oper Res, 182, 2, pp. 481-501, (2007); Dallari F., Marchet G., Melacini M., Design of order picking system, Int J Adv Manuf Technol, 42, 1-2, pp. 1-12, (2009); Connolly C., Warehouse management technologies, Sens Rev, 28, 2, pp. 108-114, (2008); Lagorio A., Pinto R., Golini R., Research in urban logistics: a systematic literature review, Int J Phys Distr Log Manage, 46, 10, pp. 908-931, (2016); Govindan K., Soleimani H., Kannan D., Reverse logistics and closed-loop supply chain: a comprehensive review to explore the future, Eur J Oper Res, 240, 3, pp. 603-626, (2015); Ulutas B.H., Attila Islier A., A clonal selection algorithm for dynamic facility layout problems, J Manuf Syst, 28, 4, pp. 123-131, (2009); Accorsi R., Manzini R., Maranesi F., A decision-support system for the design and management of warehousing systems, Comput Ind, 65, 1, pp. 175-186, (2014); Nestinger S.S., Bo C., Cheng H.H., A mobile agent-based fram"}},"L. Custodio; Postgraduate Program in Industrial and Systems Engineering, Pontifical Catholic University of Goiás - PUC, Goiás, Brazil; email: larissa.rc.ifg@gmail.com",null,"Springer",{"$nulls":5},2683768.0,null,"IJATE",null,"English","Int J Adv Manuf Technol","Article","Final",null,"Scopus","2-s2.0-85076225920"]
["Moons S.; Braekers K.; Ramaekers K.; Caris A.; Arda Y.","Moons, S. (57192940030); Braekers, K. (50861009300); Ramaekers, K. (15127894700); Caris, A. (24460963600); Arda, Y. (14621642700)","57192940030; 50861009300; 15127894700; 24460963600; 14621642700","The value of integrating order picking and vehicle routing decisions in a B2C e-commerce environment",2019.0,"International Journal of Production Research",57.0,20.0,null,6405.0,6423.0,18.0,37.0,"10.1080/00207543.2019.1566668","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85060125015&doi=10.1080%2f00207543.2019.1566668&partnerID=40&md5=77a681ccdb0f6d1261418432b0570651","Research Group Logistics, UHasselt - Hasselt University, Diepenbeek, Belgium; QuantOM, HEC Liège - Management School of the University of Liège, Liège, Belgium","Moons S., Research Group Logistics, UHasselt - Hasselt University, Diepenbeek, Belgium; Braekers K., Research Group Logistics, UHasselt - Hasselt University, Diepenbeek, Belgium; Ramaekers K., Research Group Logistics, UHasselt - Hasselt University, Diepenbeek, Belgium; Caris A., Research Group Logistics, UHasselt - Hasselt University, Diepenbeek, Belgium; Arda Y., QuantOM, HEC Liège - Management School of the University of Liège, Liège, Belgium","In B2C e-commerce sales, customers expect a fast and low-cost delivery. To be able to fulfil these customer expectations, both warehouse and distribution operations have to be performed in an efficient and effective way. Ideally, these two supply chain functions should be considered simultaneously in an integrated problem since they are interrelated. In this paper, a record-to-record travel algorithm is proposed to solve the integrated order picking-vehicle routing problem (I-OP-VRP). Experiments with both small-size and large-size instances are conducted. Furthermore, the integrated approach is compared with an approach in which both problems are solved sequentially. Results show that integration leads to increased service levels, i.e. it allows to shorten the time between placing an order and receiving the goods. On top, the integrated approach leads to costs savings of on average 1.8%. Thus, integration is indispensable for a fast and cost-efficient delivery of goods. © 2019, © 2019 Informa UK Limited, trading as Taylor & Francis Group.","e-commerce logistics; integration; meta-heuristic algorithm; order picking; vehicle routing problem","Contracts; Electronic commerce; Heuristic algorithms; Integrated control; Integration; Sales; Supply chains; Vehicle routing; Vehicles; Customer expectation; Distribution operations; Integrated approach; Meta heuristic algorithm; Order picking; Record-to-record travels; Supply chain functions; Vehicle Routing Problems; Costs",{"$nulls":4},"Flemish Government - department EWI; Flemish Supercomputer Center; Research Foundation - Flanders; VSC; Fonds Wetenschappelijk Onderzoek, FWO","The computational resources and services used in this work were provided by the VSC (Flemish Supercomputer Center), funded by the Research Foundation - Flanders (FWO) and the Flemish Government - department EWI.","Belo-Filho M.A.F., Amorim P., Almada-Lobo B., An Adaptive Large Neighbourhood Search for the Operational Integrated Production and Distribution Problem of Perishable Products, International Journal of Production Research, 53, 20, pp. 6040-6058, (2015); Blauwens G., De Baere P., Van De Voorde E., Transport Economics, (2016); Cardenas I., Beckers J., Vanelslander T., E-commerce Last-mile in Belgium: Developing An External Cost Delivery Index, Research in Transportation Business & Management, 24, pp. 123-129, (2017); Chen Z.-L., Handbook of Quantitative Supply Chain Analysis: Modeling in the E-Business Era, (2004); Croes G.A., A Method for Solving Traveling-Salesman Problems, Operations Research, 6, 6, pp. 791-812, (1958); Du T.C., Li E.Y., Chou D., Dynamic Vehicle Routing for Online B2C Delivery, Omega, 33, 1, pp. 33-45, (2005); Dueck G., New Optimization Heuristics, Journal of Computational Physics, 104, 1, pp. 86-92, (1993); Vlaams Instituut voor de Logistiek, (2016); European B2C E-commerce Report 2016, (2016); European Ecommerce Report 2017, (2017); Gong Y., de Koster R., A Polling-Based Dynamic Order Picking System for Online Retailers, IIE Transactions, 40, 11, pp. 1070-1082, (2008); Groer C., Golden B., Wasil E., The Consistent Vehicle Routing Problem, Manufacturing & Service Operations Management, 11, 4, pp. 630-643, (2009); IMRG UK Consumer Home Delivery Review 2014, (2014); Li F., Golden B., Wasil E., The Open Vehicle Routing Problem: Algorithms, Large-Scale Test Problems, and Computational Results, Computers & Operations Research, 34, 10, pp. 2918-2930, (2007); Liu L., Li K., Liu Z., A Capacitated Vehicle Routing Problem with Order Available Time in E-Commerce Industry, Engineering Optimization, 49, 3, pp. 449-465, (2017); Lopez-Ibanez M., Dubois-Lacoste J., Perez Caceres L., Birattari M., Stutzle T., The Irace Package: Iterated Racing for Automatic Algorithm Configuration, Operations Research Perspectives, 3, pp. 43-58, (2016); Low C., Chang C.M., Gao B.Y., Integration of Production Scheduling and Delivery in Two Echelon Supply Chain, International Journal of Systems Science: Operations & Logistics, 4, 2, pp. 122-134, (2017); Low C., Chang C.M., Li R.K., Huang C.L., Coordination of Production Scheduling and Delivery Problems with Heterogeneous Fleet, International Journal of Production Economics, 153, pp. 139-148, (2014); Low C., Li R.K., Chang C.M., Integrated Scheduling of Production and Delivery with Time Windows, International Journal of Production Research, 51, 3, pp. 897-909, (2013); Moons S., Ramaekers K., Caris A., Arda Y., Integrating Production Scheduling and Vehicle Routing Decisions At the Operational Decision Level: A Review and Discussion, Computers & Industrial Engineering, 104, pp. 224-245, (2017); Moons S., Ramaekers K., Caris A., Arda Y., Flexible Services and Manufacturing Journal, (2017); Petersen C.G., An Evaluation of Order Picking Policies for Mail Order Companies, Production and Operations Management, 9, 4, pp. 319-335, (2000); Punakivi M., Saranen J., Identifying the Success Factors in E-grocery Home Delivery, International Journal of Retail & Distribution Management, 29, 4, pp. 156-163, (2001); Rosenkrantz D.J., Stearns R.E., Lewis II P.M., An Analysis of Several Heuristics for the Traveling Salesman Problem, SIAM Journal on Computing, 6, pp. 563-581, (1977); Ruben R.A., Jacobs F.R., Batch Construction Heuristics and Storage Assignment Strategies for Walk/Ride and Pick Systems, Management Science, 45, 4, pp. 575-596, (1999); Savelsbergh M.W.P., The Vehicle Routing Problem with Time Windows: Minimizing Route Duration, ORSA Journal on Computing, 4, 2, pp. 146-154, (1992); Schmid V., Doerner K.F., Laporte G., Rich Routing Problems Arising in Supply Chain Management, European Journal of Operational Research, 224, pp. 435-448, (2013); Schubert D., Scholz A., Wascher G., OR Spectrum, (2018); Speranza M.G., Trends in Transportation and Logistics, European Journal of Operational Research, 264, pp. 830-836, (2018); Toth P., Vigo D., Vehicle Routing: Problems, Methods, and Applications, (2014); Vidal T., Crainic T.G., Gendreau M., Prins C., Timing Problems and Algorithms: Time Decisions for Sequences of Activities, Networks, 65, 2, pp. 102-128, (2015); Zhang J., Wang X., Huang K., Integrated on-line Scheduling of Order Batching and Delivery Under B2C E-commerce, Computers & Industrial Engineering, 94, pp. 280-289, (2016); Zhang J., Wang X., Huang K., On-line Scheduling of Order Picking and Delivery with Multiple Zones and Limited Vehicle Capacity, Omega, 79, pp. 104-115, (2017)","S. Moons; Research Group Logistics, UHasselt - Hasselt University, Diepenbeek, Belgium; email: stef.moons@uhasselt.be",null,"Taylor and Francis Ltd.",{"$nulls":5},207543.0,null,"IJPRB",null,"English","Int J Prod Res","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85060125015"]
["Zhang M.; Huang G.Q.; Xu S.X.; Zhao Z.","Zhang, Mengdi (56204508000); Huang, George Q. (7403425048); Xu, Su Xiu (35773963700); Zhao, Zhiheng (57192180873)","56204508000; 7403425048; 35773963700; 57192180873","Optimization based transportation service trading in B2B e-commerce logistics",2019.0,"Journal of Intelligent Manufacturing",30.0,7.0,null,2603.0,2619.0,16.0,14.0,"10.1007/s10845-016-1287-x","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85000983748&doi=10.1007%2fs10845-016-1287-x&partnerID=40&md5=3dd9870d32c9e4da30e550d43ea69cb0","HKU-ZIRI Laboratory for Physical Internet, Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Pokfulam, Hong Kong; School of Electrical and Information Engineering, Jinan University, Zhuhai Campus, Zhuhai, 519070, China; Institute of Physical Internet, Jinan University, Zhuhai Campus, Zhuhai, 519070, China","Zhang M., HKU-ZIRI Laboratory for Physical Internet, Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Pokfulam, Hong Kong; Huang G.Q., HKU-ZIRI Laboratory for Physical Internet, Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Pokfulam, Hong Kong; Xu S.X., School of Electrical and Information Engineering, Jinan University, Zhuhai Campus, Zhuhai, 519070, China, Institute of Physical Internet, Jinan University, Zhuhai Campus, Zhuhai, 519070, China; Zhao Z., HKU-ZIRI Laboratory for Physical Internet, Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Pokfulam, Hong Kong","This paper addresses the e-commerce transportation service trading (ETST) problem in B2B e-commerce. ETST determines and optimizes the matching issue between the sets of online orders generated by the e-commerce platform and the sets of transport vehicles supplied by logistics service providers. We first establish a framework for formulating ETST problem with the consideration of its characteristics. We then apply the framework for developing a cost minimization model to optimize the assignment of B2B online orders and vehicles. A full-factorial simulation experiment is proposed to investigate the effects of factors on the performance indexes such as the total logistics cost per unit, the type of the vehicle required, and the number of the vehicle in use. The results show that the vehicle cost and order characteristics (ratio of weight and volume) significantly impact the vehicle assignment in terms of the vehicle type and vehicle quantity. We also find that the ratio of different vehicles is significantly affected by demand fluctuations and holding cost. © 2016, Springer Science+Business Media New York.","Analysis of variance; Designed experiments; E-commerce logistics; Global optimization; Transportation service procurement; Vehicle assignment","Analysis of variance (ANOVA); Electronic commerce; Global optimization; Cost minimization models; Demand fluctuations; Designed experiments; Logistics service provider; Performance indices; Total logistics costs; Transportation services; Vehicle assignment; Vehicles",{"$nulls":6},"Aguezzoul A., Third-party logistics selection problem: A literature review on criteria and methods, Omega, 49, pp. 69-78, (2014); Bell M.G.H., Liu X., Rioult J., Angeloudis P., A cost-based maritime container assignment model, Transportation Research Part B: Methodological, 58, pp. 58-70, (2013); Bontekoning Y.M., Macharis C., Trip J.J., Is a new applied transportation research field emerging? A review of intermodal rail-truck freight transport literature, Transportation Research Part A: Policy and Practice, 38, 1, pp. 1-34, (2004); Burns L.D., Hall R.W., Blumenfeld D.E., Daganzo C.F., Distribution strategies that minimize transportation and inventory costs, Operations Research, 33, 3, pp. 469-490, (1985); Caplice C., Sheffi Y., Combinatorial auctions for truckload transportation, Combinatorial Auctions, 21, pp. 539-572, (2006); Cramton P., Shoham Y., Steinberg R., Combinatorial Auctions, (2006); Figliozzi M.A., Mahmassani H.S., Jaillet P., Pricing in dynamic vehicle routing problems, Transportation Science, 41, 3, pp. 302-318, (2007); Grieger M., Electronic marketplaces: A literature review and a call for supply chain management research, European Journal of Operational Research, 144, 2, pp. 280-294, (2003); Ha A.Y., Li L., Ng S.-M., Price and delivery logistics competition in a supply chain, Management Science, 49, 9, pp. 1139-1153, (2003); Higuera A.G., de las Morenas J., Application of the classical levels of intelligence to structuring the control system in an automated distribution centre, Journal of Intelligent Manufacturing, 25, 5, pp. 1197-1206, (2014); Huang G.Q., Xu S.X., Truthful multi-unit transportation procurement auctions for logistics e-marketplaces, Transportation Research Part B: Methodological, 47, pp. 127-148, (2013); Jothi Basu R., Subramanian N., Cheikhrouhou N., Review of Full Truckload Transportation Service Procurement, Transport Reviews, pp. 1-23, (2015); Kang H.-Y., Lee A.H., Yang C.-Y., A fuzzy ANP model for supplier selection as applied to IC packaging, Journal of Intelligent Manufacturing, 23, 5, pp. 1477-1488, (2012); Khorshidian H., Shirazi M.A., Ghomi S.F., An intelligent truck scheduling and transportation planning optimization model for product portfolio in a cross-dock, Journal of Intelligent Manufacturing, pp. 1-22, (2016); Nof S.Y., Collaborative e-work and e-manufacturing: challenges for production and logistics managers, Journal of Intelligent Manufacturing, 17, 6, pp. 689-701, (2006); Pternea M., Kepaptsoglou K., Karlaftis M.G., Sustainable urban transit network design, Transportation Research Part A: Policy and Practice, 77, pp. 276-291, (2015); Ramos T.R.P., Gomes M.I., Barbosa-Povoa A.P., Planning a sustainable reverse logistics system: Balancing costs with environmental and social concerns, Omega, 48, pp. 60-74, (2014); Sarraj R., Ballot E., Pan S., Montreuil B., Analogies between Internet network and logistics service networks: challenges involved in the interconnection, Journal of Intelligent Manufacturing, 25, 6, pp. 1207-1219, (2014); Sheffi Y., Third party logistics-present and future prospects, Journal of Business Logistics, 11, 2, (1990); Sheffi Y., Third party logistics: Present and future prospects, Journal of Business Logistics, 11, 2, (1990); Sibalija T.V., Majstorovic V.D., An integrated approach to optimise parameter design of multi-response processes based on Taguchi method and artificial intelligence, Journal of Intelligent Manufacturing, 23, 5, pp. 1511-1528, (2012); Sun J., Debo L., Sustaining long-term supply chain partnerships using price-only contracts, European Journal of Operational Research, 233, 3, pp. 557-565, (2014); Wang J., Liu D., Ip W.H., Zhang W., Deters R., Integration of system-dynamics, aspect-programming, and object-orientation in system information modeling, IEEE Transactions on Industrial Informatics, 10, 2, pp. 847-853, (2014); Wang J., Wang H., Zhang W., Ip W.-H., Furuta K., On a unified definition of the service system: What is its identity?, IEEE Systems Journal, 8, 3, pp. 821-826, (2014); Wong J.-T., DSS for 3PL provider selection in global supply chain: Combining the multi-objective optimization model with experts’ opinions, Journal of Intelligent Manufacturing, 23, 3, pp. 599-614, (2012); Xu S.X., Cheng M., Huang G.Q., Efficient intermodal transportation auctions for B2B e-commerce logistics with transaction costs, Transportation Research Part B: Methodological, 80, pp. 322-337, (2015); Xu S.X., Huang G.Q., Efficient Multi-Attribute Multi-Unit Auctions for B2B E-Commerce Logistics, Production and Operations Management, 26, 2, pp. 292-304, (2016); Xu S.X., Huang G.Q., Cheng M., Truthful, Budget-Balanced Bundle Double Auctions for Carrier Collaboration, Transportation Science, 51, 4, pp. 1365-1386, (2017); Zhao Z., Fang J., Huang G.Q., Zhang M., Location Management of Cloud Forklifts in Finished Product Warehouse, International Journal of Intelligent Systems, 32, 4, pp. 342-370, (2016)","G.Q. Huang; HKU-ZIRI Laboratory for Physical Internet, Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Pokfulam, Hong Kong; email: gqhuang@hku.hk",null,"Springer New York LLC",{"$nulls":5},9565515.0,null,"JIMNE",null,"English","J Intell Manuf","Article","Final",null,"Scopus","2-s2.0-85000983748"]
["Wang Y.; He W.; Yeo G.-T.","Wang, Ying (55793744100); He, Wenjun (57211142065); Yeo, Gi-Tae (13907706200)","55793744100; 57211142065; 13907706200","Selection of location for cross-border e-commerce enterprises in China addressing the competitiveness of city logistics",2019.0,"International Journal of Transport Economics",46.0,"2024-02-01",null,139.0,160.0,21.0,2.0,"10.19272/201906702008","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85072786995&doi=10.19272%2f201906702008&partnerID=40&md5=fe1246c8464f40379b6e013519515506","School of Economics and Management, Yantai University, 30, Qingquan RD, Yantai, China; School of Logistics, Incheon National University, 119 Academy-Ro, YeonSu-Gu, Incheon, 22012, South Korea","Wang Y., School of Economics and Management, Yantai University, 30, Qingquan RD, Yantai, China; He W., School of Logistics, Incheon National University, 119 Academy-Ro, YeonSu-Gu, Incheon, 22012, South Korea; Yeo G.-T., School of Logistics, Incheon National University, 119 Academy-Ro, YeonSu-Gu, Incheon, 22012, South Korea","Cross-border e-commerce is a popular e-commerce mode in China that recently experienced rapid growth. With policy support from the Chinses government, cross-border e-commerce enterprises are trying to determine how best to initially select a city to host their long-Term development. This paper aims to select the optimal city for the location of cross-border e-commerce enterprises. The originality of this paper is to establish a hierarchical evaluation structure addressing the competitiveness of city logistics. Based on the literature review, as well as semistructured interviews conducted with experts, the hierarchical evaluation structure of criteria can be clarified. The fuzzy AHP and fuzzy TOPSIS methods are employed because they reflect the exact, real thought processes of decision makers. Additionally, the performances of alternative cities under quantitative criteria are evaluated by the real data fuzzy transforming to express the real condition of alternative cities more exactly. The analysis results demonstrate that transportation cost is the most considerable criterion, and Shanghai is ranked highest as the location for business. The results not only help decision makers within cross-border e-commerce enterprises select the appropriate city in which to locate their business but also suggest how governments can make future strategies to incentivize economic development at the city level. © 2019 Fabrizio Serra Editore Srl. All rights reserved.","City logistics; Cross-border e-commerce; Fuzzy AHP; Fuzzy TOPSIS; Location","China; analytical hierarchy process; competitiveness; electronic commerce; fuzzy mathematics; industrial location; logistics; multicriteria analysis; urban transport",{"$nulls":4},"Humanity and Social Science Foundation of Education Office of Shandong Province, (J16YF23); Incheon National University, INU","* School of Economics and Management, Yantai University, 30, Qingquan RD, Laishan District, Yantai, China; yingmickey@163.com ** Graduate School of Logistics, Incheon National University, 119 Academy-Ro, YeonSu-Gu, Incheon, 22012, Korea; winniehe257@gmail.com *** Corresponding author. Graduate School of Logistics, Incheon National University, 119 Academy-Ro, YeonSu-Gu, Incheon, 22012, Korea; ktyeo@inu.ac.kr Acknowledgments: This work was supported by the Incheon National University (International Cooperative) Research Grant in 2017, and by Humanity and Social Science Foundation of Education Office of Shandong Province (project number: J16YF23). The first author would like to thank Professor M. Xu (Faculty of Business and Law, University of Portsmouth) for valuable comments.","Armero E., Garcia-Cascales M.S., Gomez-Lopez M.D., Lamata M.T., Decision making in uncertain rural scenarios by means of fuzzy TOPSIS method, Advances in Decision Sciences, 2011, 1, pp. 1-15, (2011); Awasthi A., Chauhan S.S., A hybrid approach integrating Affinity Diagram, AHP and fuzzy TOPSIS for sustainable city logistics planning, Applied Mathematical Modelling, 36, pp. 573-584, (2012); Balli S., Korukoglu S., Operating system selection using fuzzy AHP and TOPSIS methods, Mathematical and Computational Applications, 14, 2, pp. 119-130, (2009); Bellman R., Kalaba R., Zadeh L., Abstraction and pattern classification, Journal of Mathematical Analysis and Applications, 13, pp. 1-7, (1966); Bozbura F.T., Beskese A., Prioritization of organizational capital measurement indicators using fuzzy AHP, International Journal of Approximate Reasoning, 44, pp. 124-147, (2007); Buyukozkan G., Cifci G., A combined fuzzy AHP and fuzzy TOPSIS based strategic analysis of electronic service quality in healthcare industry, Expert Systems with Applications, 39, pp. 2341-2354, (2012); Cao Y., Li Y., Xu C., Air freight market review in 2015 and outlook in 2016, Journal of Chongqing Jiaotong University (Social Sciences Edition, 16, 2, pp. 50-55, (2016); Cardenas I.D., Dewulf W., Vanelslander T., Smet C., Beckers J., The e-commerce parcel delivery market and the implications of home B2C deliveries vs pick-up points, International Journal of Transport Economics, 44, 2, pp. 235-256, (2017); Chang D., Applications of the extent analysis method on fuzzy AHP, European Journal of Operational Research, 95, pp. 649-655, (1996); Chaghooshi A.J., Integration of fuzzy AHP and fuzzy GTMA for location selection of gas pressure reducing stations : A case study, Journal of Management Research, 4, pp. 152-169, (2012); Chen J.F., Hsieh H.N., Do Q.H., Evaluating teaching performance based on fuzzy AHP and comprehensive evaluation approach, Applied Soft Computing, 28, pp. 100-108, (2015); Chen M.C., Hsu C.L., Chang K.C., Chou M.C., Applying Kansei engineering to design logistics services-A case of home delivery service, International Journal of Industrial Ergonomics, 48, pp. 46-59, (2015); Chou C.C., Application of FMCDM model to selecting the hub location in the marine transportation : A case study in southeastern Asia, Mathematical and Computer Modeling, 51, pp. 791-801, (2010); Chou C.C., An integrated quantitative and qualitative FMCDM model for location choices, Soft Computing, 14, 7, pp. 757-771, (2010); Crainic T.G., Ricciardi N., Storchi G., Models for evaluating and planning city logistics systems, Transportation Science, 43, 4, pp. 432-454, (2009); Dong L.H., Yang L.H., Reflections on the development of China's cross-border e-commerce under 'Internet + foreign trade, Special Zone Economy, 12, pp. 146-148, (2016); Dou C.C., Wu H.F., Research on the problems and countermeasures of cross-border electricity supplier logistics, Logistics Engineering and Management, 9, 37, pp. 155-156, (2015); Ekici S.O., Kabak O., Linking to compete : logistics and global competitiveness interaction, Transport PolicyUlengin, F, 48, pp. 117-128, (2016); Erfurth T., Transportation time and reliability in intermodal transport chains, International Journal of Transport EconomicsBendul, J, 44, 2, pp. 257-271, (2017); Gessner G.H., Snodgrass C.R., Designing e-commerce cross-border distribution networks for small and medium-size enterprises incorporating Canadian and U.S.Trade incentive programs, Research in Transportation Business & Management, 16, pp. 84-94, (2015); Giuffrida M., Mangiaracina R., Perego A., Tumino A., Cross-border B2C e-commerce to Greater China and the role of logistics : A literature review, International Journal of Physical Distribution & Logistics Management, 47, 9, pp. 772-795, (2017); Hazen B.T., Byrd T.A., Toward creating competitive advantage with logistics information technology, International Journal of Physical Distribution & Logistics Management, 42, 1, pp. 8-35, (2012); Hsiao Y.H., Chen M.C., Logistics service design for cross-border E-commerce using Kansei engineering with text-mining-based online content analysis, Telematics and InformaticsLiao, W. 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Liu J.Y., Chen H.Q., Analysis of collaborative development of port logistics industry and regional economy in Jing-Jin-Ji region, Logistics Technology, 11, 2, pp. 109-112, (2015); Luo Y.K., SME cross-border e-commerce logistics channel selection, Market Modernization, 2015, 15, pp. 43-44, (2015); Mardani A., Jusoh A., Zavadskas E.K., Fuzzy multiple criteria decision-making techniques and applications-Two decades review from 1994 to 2014, Expert Systems with Applications, 42, 8, pp. 4126-4148, (2015); McLntosh M.J., Morse J.M., Situating and constructing diversity in semi-structured interviews, Global Qualitative Nursing Research, 2, pp. 1-12, (2015); Mon D.L., Cheng C.H., Lin J.C., Evaluating weapon system using fuzzy analytic hierarchy process based on entropy weight, Fuzzy Sets System, 62, 2, pp. 127-134, (1994); Moroz M., Polkowski Z., The last mile issue and urban logistics : choosing parcel machines in the context of the ecological attitudes of the y generation consumers purchasing online, Transportation Research Procedia, 16, pp. 378-393, (2016); 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Wu L., Wang Y.J., A Book to Understand Cross-border E-commerce, (2016); Wu P.J., Lin K.C., Unstructured big data analytics for retrieving e-commerce logistics knowledge, Telematics and Informatics, 35, 1, pp. 237-244, (2017); Xu G.Y., Li Y.F., Empirical study on relationship between port logistics and foreign trade in Hainan, Logistics Technology, 2015, 11, pp. 121-123, (2015); Yapar B.K., Bayrakdara S., Yapar M., The role of taxation problems on the development of ecommerce, Procedia-Social and Behavioral Sciences, 195, pp. 642-648, (2015); Yeo G.T., Wang Y., Chou C.C., Evaluating the competitiveness of the aerotropolises in East Asia, Journal of Air Transport Management, 32, pp. 24-31, (2013); Yu H.H., Mu C.C., Wei C.L., Logistics service design for cross-border e-commerce using Kansei engineering with text-mining-based online content analysis, Telematics and Informatics, 34, pp. 284-302, (2017); Zhang B., Liu X.J., Tao Z., The study of current situation and operation pattern of the cross-border e-commerce logistics in China, Zhongguo Liutong Jingji, 2015, 1, pp. 51-56, (2015); Zhao G.H., Crack the difficulties of cross-border e-commerce logistics : A new strategy : The fourth party logistics, China Economic Trade Herald, 2014, 26, pp. 16-20, (2014); Zhang N., Zhou K., Du X., Application of fuzzy logic and fuzzy AHP to mineral prospectivity mapping of porphyry and hydrothermal vein copper deposits in the Dananhu-Tousuquan island arc, Xinjiang, NW China, Journal of African Earth Sciences, 128, pp. 84-96, (2017)","G.-T. Yeo; School of Logistics, Incheon National University, YeonSu-Gu, Incheon, 119 Academy-Ro, 22012, South Korea; email: ktyeo@inu.ac.kr",null,"Fabrizio Serra Editore Srl",{"$nulls":5},3035247.0,null,null,null,"English","Int. J. Transp. Econ.","Article","Final",null,"Scopus","2-s2.0-85072786995"]
["Hung C.-W.","Hung, Chien-Wen (57195470553)",5.7195470553E10,"Using cloud services to develop marketing information system applications",2019.0,"Journal of Internet Technology",20.0,1.0,null,157.0,166.0,9.0,2.0,"10.3966/160792642019012001014","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85071159087&doi=10.3966%2f160792642019012001014&partnerID=40&md5=a1572e962c5c3c4b45281d5970c67efe","Department of Information Management, Chia-Nan University of Pharmacy and Science, Taiwan","Hung C.-W., Department of Information Management, Chia-Nan University of Pharmacy and Science, Taiwan","This study presents a cloud services customized product information system to enable businesses to provide customized product marketing on the Internet to meet consumer demand for customized products. The cloud service of the information system development strategic framework proposed in this study contains three elements: (1) e-commerce services, (2) promotion type modules, and (3) cloud services customized promotional products. In this study, a mining cloud information system to detect customer behavior is proposed. The association rules from a relational database design are utilized to mine consumer behavior in order to generate cross-selling proposals for customer products and marketing for a retailing mall in Taiwan. The study is composed of several parts, as follows. A market segment and application of association rules in data exploration techniques (Association Rule Mining) and sequence-like exploration (Sequential Pattern Mining), efficient analysis of customers, consumer behavior, identification of candidates for promotional products, as well as using cloud service delivery and evaluation of targets to evaluate candidates for promotional products for production. However, in addition to cloud service customized promotional products, the quantity of promotional products sales varies for different customers. We strive to achieve increased customer loyalty and profits through the use of active cloud service customized promotional products. © 2019 Taiwan Academic Network Management Committee. All rights reserved.","Association rule mining; Cloud service customized product promotions; Data mining; Sequential pattern mining","Association rules; Commerce; Consumer behavior; Distributed database systems; Information systems; Information use; Petroleum reservoir evaluation; Product design; Relational database systems; Sales; Web services; Customized products; E-commerce services; Information system development; Marketing information system; Promotional products; Relational Database; Sequential-pattern mining; Strategic frameworks; Data mining",{"$nulls":4},"National Science Council, NSC, (NSC 101-2410-H-041-003)","Thanks to the case firm which provided the useful data and permitted us to publish the key part and results of the project. This partial work was supported by the National Science Council, Taiwan, under Grants NSC 101-2410-H-041-003.","Aaker D.A., Measuring brand equity across products and markets, California Management Review, 38, 3, pp. 102-120, (1996); Agrawal R., Srikant R., Fast algorithms for mining association rules, Proc. Of the 20th International Conference on Very Large Databases, pp. 487-499, (1994); Agrawal R., Srikant R., Mining sequential patterns, Proc. Of the 11th International Conference on Data Engineering, pp. 3-14, (1995); Anand S.S., Patrick A.R., Hughes J.G., Bell D.A., A Data Mining Methodology for Cross-sales, Knowledge-Based Systems, 10, 7, pp. 449-461, (1998); Berson A., Smith S.J., Thearling K., Building Data Mining Applications for CRM, (2015); Carpenter G.A., Grossberg S., The art of adaptive pattern recognition by self-organizing neural network, IEEE Computer, 21, 3, pp. 77-88, (1988); Changchien S.W., Lee C.-F., Hsu Y.-J., On-line Personalized Sales Promotion in Electronic Commerce, Expert Systems with Applications, 27, 1, pp. 35-52, (2004); Changchien S.W., Lu T.-C., Mining Association Rules Procedure to Support On-line Recommendation by Customers and Products Fragmentation, Expert Systems with Applications, 20, 4, pp. 325-335, (2001); Cho Y.H., Kim J.K., Kim S.H., A personalized recommender system based on web usage mining and decision tree induction, Expert Systems with Applications, 23, 3, pp. 329-342, (2002); Romero D., Vernadat F., Enterprise information systems state of the art: Past, present and future trends, Computers in Industry, 79, pp. 3-13, (2016); Gibbert M., Leibold M., Probst G., Five styles of customer knowledge management, and how smart companies use them to create value, European Management Journal, 20, 5, pp. 459-469, (2002); Han J., Pei J., Mortazavi-Asl B., Chen Q., Dayal U., Hsu M.-C., FreeSpan: Frequent pattern-projected sequential pattern mining, Proc. Of the International Conference on Knowledge Discovery and Data Mining, pp. 355-359, (2000); Hoffman D.L., Novak T.P., A new marketing paradigm for electronic commerce, The Information Society, 13, 1, pp. 43-54, (1997); Iyer G.R., Miyazaki A.D., Grewal D., Giordano M., Linking Web-based Segmentation to Pricing Tactics, Journal of Product & Brand Management, 11, 5, pp. 288-302, (2002); Keller A.M., Genesereth M.R., Using infomaster to create a housewares virtual catalog, Electronic Markets, 7, 4, pp. 41-44, (1997); Kim W., Cloud computing: Today and tomorrow, Journal of Object Technology, 8, 1, pp. 65-72, (2009); Lawrence R.D., Almasi G.S., Kotlyar V., Viveros M.S., Duri S.S., Personalization of supermarket product recommendations, Data Mining and Knowledge Discovery, 5, 1-2, pp. 11-32, (2001); Heilig L., Lalla-Ruiz E., Voss S., A Cloud Brokerage Approach for Solving the Resource Management Problem in Multi-cloud Environments, Computers & Industrial Engineering, 95, pp. 16-26, (2016); Lin C., Hong C., Using customer knowledge in designing electronic catalog, Expert Systems with Applications, 34, 1, pp. 119-127, (2008); Nash D., Sterna-Karwat A., An application of DEA to measure branch cross selling efficiency, Computers & Operations Research, 23, 4, pp. 385-392, (1996); Pan S.L., Lee J.-N., Using E-CRM for a unified view of the customer, Communications of the ACM, 46, 4, pp. 95-99, (2003); Shaw M.J., Subramaniam C., Tan G.W., Welge M.E., Knowledge management and data mining for marketing, Decision Support Systems, 31, 1, pp. 127-137, (2001); Stanoevska-Slabeva K., Schmid B., Internet electronic product catalogs: An approach beyond simple keywords and multimedia, Computer Networks, 32, 6, pp. 701-715, (2000); Subashini S., Kavitha V., A survey on security issues in service delivery models of cloud computing, Journal of Network and Computer Applications, 34, 1, pp. 1-11, (2011); Surprenant C.F., Solomon M.R., Predictability and personalization in the service encounter, Journal of Marketing, 51, 2, pp. 86-96, (1987); Terveen L., Hill W., Amento B., McDonald D., Creter J., Phoaks: A system for sharing recommendations, Communications of the ACM, 40, 3, pp. 59-62, (1997); Tsai J.-M., Hung S.-W., A novel model of technology diffusion: System dynamics perspective for cloud computing, Journal of Engineering and Technology Management, 33, pp. 47-62, (2014); Triantaphyllou E., Multi-Criteria Decision Making Methods: A Comparative Study, (2015); Kong X.T.R., Fang J., Luo H., Huang G.Q., Cloud-enabled Real-time Platform for Adaptive Planning and Control in Auction Logistics Center, Computers & Industrial Engineering, 84, pp. 79-90, (2015)","C.-W. Hung; Department of Information Management, Chia-Nan University of Pharmacy and Science, Taiwan; email: cwhong@mail.cnu.edu.tw",null,"Taiwan Academic Network Management Committee",{"$nulls":5},1.6079264E7,null,null,null,"English","J. Internet Technol.","Article","Final",null,"Scopus","2-s2.0-85071159087"]
["Lestari V.T.; Ellyawati J.","Lestari, Veronika Trivia (57210445479); Ellyawati, Jeanne (57197754881)","57210445479; 57197754881","Effect of E-Service quality on repurchase intention: Testing the role of e-satisfaction as mediator variable",2019.0,"International Journal of Innovative Technology and Exploring Engineering",8.0,"7C2",null,158.0,162.0,4.0,8.0,"10.35940/ijitee.g5400.0881019","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85070763553&doi=10.35940%2fijitee.g5400.0881019&partnerID=40&md5=7e56a2718f031cbede82f4684f4476cc","Universitas Atma Jaya Yogyakarta, Indonesia","Lestari V.T., Universitas Atma Jaya Yogyakarta, Indonesia; Ellyawati J., Universitas Atma Jaya Yogyakarta, Indonesia","Recent developments in information and communication technology have contributed to tremendous economic efficiency. Companies that can take advantage of the sophistication of information and communication technology can operate more efficiently. Firm efficiency will tend to lower product prices and faster delivery time. It is expected to increase consumer satisfaction and repurchase intention. This study investigates the influence of e-service quality on repurchase intention with satisfaction as mediating variable. E-service quality was measured by five variables, namely ease of use, website design, security, personalization, and responsiveness. Good service quality tends to satisfy consumers and leads to repurchase intentions. To collect data, this study used survey design with purposive sampling method. The sample in this study are respondents who have experience in purchasing airline e-tickets for domestic flights within last year. To collect data, we distributed structured questionnaires to 263 respondents. To verify hypothesis, this study used descriptive statistics and hierarchical regression analysis. The results showed that e-satisfaction partially mediate the influence of ease of use, website design, responsiveness, and personalization on repurchase intentions. While e-satisfaction proved fully mediates the influence of security guarantees on repurchase intention. © Blue Eyes Intelligence Engineering & Sciences Publication.","E-satisfaction; E-service quality; Online shopping; Repurchase intention",{"$nulls":7},"Anderson R.E., Srinivasan S.S., E-satisfaction and E-Loyalty: A Contigency Framework, Psychology and Marketing, 20, 2, pp. 123-138, (2003); Archana R., Subha M.V., A Study On Service Quality and Passenger Satisfaction On Indian Airlines, International Journal of Multidisciplinary Research, 2, 2, pp. 50-63, (2012); Aren S., Guzel M., Kabadayi E., Alpkan L., Factors Affecting Repurchase Intention to Shop at the Same Website, Social and Behavioral Sciences, 99, 1, pp. 536-544, (2013); Penetrasidan PerilakuPengguna Internet Indonesia Survey 2018; Azam A., Qiang F., Abdullah M.I., E-satisfaction in Business to Consumer Electronic Commerce, The Business and Management Review, 13, 1, pp. 18-26, (2012); Baron R.M., Kenny D.A., The Moderator-Mediator Variable Distinction in Social Psychological Research: Conceptual, Strategic, and Statistical Considerations, Journal of Personality and Social Psychology, 51, 6, pp. 1173-1182, (1986); Chang S.C., Chou P.Y., Chien L.W., Evaluation Of Satisfaction And Repurchase Intention In Online Food Group-Buying, Using Taiwan As An Example, British Food Journal, 116, 1, pp. 44-61, (2014); Cooper D.R., Schindler P., Business Research Methods, (2008); Ellyawati J., Double Deviation Investigation of Perceived Service Recovery Justice: A Study On The Indonesian Airline Industry, Journal of Applied Business Research, 33, 6, pp. 1263-1272, (2017); Ferrel O.C., Hartline M.O., Marketing Strategy, Text and Cases, (2014); Hair J.F., Black W.C., Babin B.J., Anderson R.E., Tatham R.J., Multivariate Data Analysis, (2014); Hellier P.K., Geursen G.M., Carr R.A., Rickard J.A., Customer Repurchase Intention: A General Structural Equation Model, European Journal of Marketing, 37, 11, pp. 1762-1800, (2003); Kotler P., Armstrong G., Principles of Marketing, (2018); Lau T.C., Kwek C.L., Tan H.P., Airline e-Ticketing Service: How e-Service Quality and Cusomer Satisfaction Impacted Purchase Intention, International Business Management, 5, 4, pp. 200-208, (2011); Lee G., Lin H., Customer Perceptions of E-Service Quality In Online Shopping, International Journal of Retail and Distribution Management, 33, 2, pp. 161-176, (2005); Lu Y., Lu Y., Wang B., Effects of Dissatisfaction on Customer Repurchase Decisions In E-Commerce-An Emotion-Based Perspective, Journal of Electronic Commerce Research, 13, 3, pp. 224-225, (2012); Parasuraman A., Zeithaml V.A., Malhotra A., E-S-QUAL: A Multiple-Item Scale for Assesing Electronic Service Quality, Journal of Service Research, 7, 10, pp. 1-21, (2005); Ribbink D., Van Riel A.C.R., Liljander V., Streukens S., Comfort Your Online Customer: Quality, Trust, and Loyalty On The Internet, Managing Service Quality, 14, 6, pp. 446-456, (2004); Santos J., E-Service Quality: A Model Of Virtual Service Quality Dimensions, Management Service Quality, 13, 3, pp. 233-246, (2003); Sekaran U., Bougie R., Research Methods for Business, (2013); Shih T., Comparative Analysis of Marketing Strategies For Manufacturers And Retailers Brands, International Journal of Electric Business Management, 8, 1, pp. 56-67, (2010); Wen C., Prybutok V.R., Xu C., An Integrated Model For Customer Online Repurchase Intention, The Journal of Computer Information Systems, 52, 1, pp. 14-23, (2011); Windi J.E., Trust, Antecedent and Consequence in Online Shopping Context: Testing The Role of E-WOM as Moderating Effect, International Journal of Management and Applied Science, 1, 5, pp. 41-45; Zhao J.G., Lynch J.R., Chen Q., Reconsidering Baron and Kenny: Myths and Thruths about Mediation Analysis, Journal of Consumer Research, 37, 1, pp. 197-206, (2010); (2014)","J. Ellyawati; Universitas Atma Jaya Yogyakarta, Indonesia; email: j.ellyawati@uajy.ac.id",null,"Blue Eyes Intelligence Engineering and Sciences Publication",{"$nulls":5},2.2783075E7,null,null,null,"English","Int. J. Innov. Technol. Explor. Eng.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85070763553"]
["Hu J.","Hu, Junmin (57201478581)",5.7201478581E10,"E-commerce big data computing platform system based on distributed computing logistics information",2019.0,"Cluster Computing",22.0,null,null,13693.0,13702.0,9.0,8.0,"10.1007/s10586-018-2074-6","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85045065398&doi=10.1007%2fs10586-018-2074-6&partnerID=40&md5=dc48c0832b8c667e6edd8cc69214d47e","Party School of Guangxi District Organs of C. P. C, Guangxi, Nanning, China","Hu J., Party School of Guangxi District Organs of C. P. C, Guangxi, Nanning, China","E-commerce websites generate a large amount of user behavior data, with the continuous increase of the business volume of e-commerce companies. Enterprises hope to have a deep understanding of each customer through these data and expect to form a learning relationship with customers. Based on this, this paper firstly elaborates the background and significance of the system development, the status quo of related technologies at home and abroad, then carries on the overall design and gives the system realization plan, and finally designs and realizes the big data T station based on distributed real-time computing framework, Enterprises, especially Internet companies, can provide internal data support by building a hierarchical data warehouse infrastructure and real-time data computing technology, and then cluster, divide and predict more relevant data through mathematical statistics and mining algorithms. Each of us is tagged with descriptions to get each of our attributes and hobbies, etc., providing a strong support for the external needs of enterprises and fast data-driven business. © 2018, Springer Science+Business Media, LLC, part of Springer Nature.","Big data; Computing platform; Distributed computing; E-commerce","Behavioral research; Cluster computing; Data mining; Data warehouses; Distributed computer systems; Electronic commerce; Statistics; Computing platform; Computing technology; E-commerce websites; Logistics information; Real time computing; System development; System realization; Warehouse infrastructures; Big data",{"$nulls":6},"Huang T.E., Guo Q., Sun H.A., Distributed computing platform supporting power system security knowledge discovery based on online simulation, IEEE Trans. Smart Grid., 8, 99, (2016); Wu P.L., He F., Zhong Y., An envelope analysis algorithm of experiment data based on distributed computing platform, Cyberspace Secur., 1, 2, pp. 12-14, (2017); Guo W., Liu F., Research on parallel algorithm based on Hadoop distributed computing platform, Int. J. Grid Distrib. Comput., 8, 1, pp. 77-78, (2015); Zhang X., Jiang J., Zhang X., Et al., A data transmission algorithm for distributed computing system based on maximum flow, Cluster Comput., 18, 3, pp. 1157-1169, (2015); Rho S., Park S., Hwang S., Privacy enhanced data security mechanism in a large-scale distributed computing system for HTC and MTC, Int. J. Contents., 12, 2, pp. 6-11, (2016); Kumar R.S., Chandrasekharan E., A parallel distributed computing framework for Newton-Raphson load flow analysis of large interconnected power systems, Int. J. Electr. Power Energy Syst., 73, pp. 1-6, (2015); Hofmann M., Runger G., Sustainability through flexibility: building complex simulation programs for distributed computing systems, Simul. Model. Pract. Theory., 58, pp. 65-78, (2015)","J. Hu; Party School of Guangxi District Organs of C. P. C, Nanning, Guangxi, China; email: WilhelminaaDbV@yahoo.com",null,"Springer",{"$nulls":5},1.3867857E7,null,null,null,"English","Cluster Comput.","Article","Final",null,"Scopus","2-s2.0-85045065398"]
["Thamaraiselvan N.; Jayadevan G.R.; Chandrasekar K.S.","Thamaraiselvan, N. (36629095800); Jayadevan, G.R. (57912320600); Chandrasekar, K.S. (57191022864)","36629095800; 57912320600; 57191022864","Digital food delivery apps revolutionizing food products marketing in India",2019.0,"International Journal of Recent Technology and Engineering",8.0,"2 Special Issue 6",null,662.0,665.0,3.0,19.0,"10.35940/ijrte.B1126.0782S619","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85073468529&doi=10.35940%2fijrte.B1126.0782S619&partnerID=40&md5=aca4dd1a0c0c494d44176c53d9b4ee8f","Department of Management Studies, National Institute of Technology, Tiruchirappalli, Tamil Nadu, India; Institute of Management in Kerala, University of Kerala, Thiruvananthapuram, Kerala, India; Department of Dairy Business Management, Faculty of Dairy Science, Kerala Veterinary and Animal Sciences University, Wayanad, Kerala, India","Thamaraiselvan N., Department of Management Studies, National Institute of Technology, Tiruchirappalli, Tamil Nadu, India; Jayadevan G.R., Department of Management Studies, National Institute of Technology, Tiruchirappalli, Tamil Nadu, India, Department of Dairy Business Management, Faculty of Dairy Science, Kerala Veterinary and Animal Sciences University, Wayanad, Kerala, India; Chandrasekar K.S., Institute of Management in Kerala, University of Kerala, Thiruvananthapuram, Kerala, India","Food delivery aided through digital apps has emerged as one of the fast-growing developments in the e-commerce space. The advent of digital tools has bestowed a different outlook on the food industry. Consumers today have the privilege to choose from a variety of cuisines, anywhere, anytime from a range of food providers listed in the e-commerce space. Added attractions like no minimum order value and the multitude of payment options like net banking, digital wallets, and cash on delivery all have increased the consumer convenience. Shrinking urban-rural divide with easy access to smartphones has hastened the growth and acceptance of online food delivery systems. Companies have remodelled their business strategies on a modern day digital platform to keep pace with the customer’s changing needs and preferences. In this paper, we particularly examine the growth and relevance of digital apps in the food delivery systems run by the food providers particularly fast food companies in India and a few strategies which could be adopted by them for sustainable business in the days to come. © BEIESP.","Consumer choice; Digital apps; E-commerce; Food products marketing",{"$nulls":7},"Bajaj K., Mehendale S., Food - Delivery Start-Ups: In Search of the Core, Prabandhan: Indian Journal of Management, 9, 10, (2016); Bhargava A., Jadhav N., Joshi A., Oke P., Lahane S.R., Digital ordering system for Restaurant using Android, International Journal of Scientific and Research Publications, 3, 4, (2013); Gera M., Nawander N., Tharwani N., Bhatia P., Operations research in food delivery, International Journal of Advance Research and Development, 3, 10, pp. 73-78, (2018); Hannu S., Lasse M., Yrjola M., From selling to supporting - Leveraging mobile services in the context of food retailing, Journal of Retailing and Consumer Services, 21, 1, pp. 26-36, (2014); Kanteti V., Innovative strategies of startup firms in India - A study on online food delivery companies in India, International Research Journal of Management Science & Technology, 9, 3, pp. 17-23, (2018); Kapoor A.P., Vij M., Technology at the dinner table: Ordering food online through mobile apps, Journal of Retailing and Consumer Services, 43, pp. 342-351, (2018); Kashyap K., The Food Delivery Apps That Are Competing To Gain Market Share in India, (2017); Kharas H., The unprecedented expansion of the global middle class: An update, (2017); Kimes S.E., Customer perceptions of electronic food ordering, Cornell Hospitality Report, 11, 10, pp. 6-15, (2011); Mckinsey, (2016); Raman P., Zomato: A shining armor in the food tech sector, Journal of Information Technology Case and Application Research, (2018); (2019); (2019)","N. Thamaraiselvan; Department of Management Studies, National Institute of Technology, Tiruchirappalli, India; email: selvanthamarai27@gmail.com",null,"Blue Eyes Intelligence Engineering and Sciences Publication",{"$nulls":5},2.2773878E7,null,null,null,"English","Int. J. Recent Technol. Eng.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85073468529"]
["Wang X.; Wong Y.D.; Teo C.C.; Yuen K.F.; Feng X.","Wang, Xueqin (57196484178); Wong, Yiik Diew (57218910096); Teo, Chee Chong (34267826000); Yuen, Kum Fai (56581269200); Feng, Xuehao (55579448300)","57196484178; 57218910096; 34267826000; 56581269200; 55579448300","The four facets of self-collection service for e-commerce delivery: Conceptualisation and latent class analysis of user segments",2020.0,"Electronic Commerce Research and Applications",39.0,null,100896.0,null,null,null,29.0,"10.1016/j.elerap.2019.100896","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85075780252&doi=10.1016%2fj.elerap.2019.100896&partnerID=40&md5=19f1bb829ee11a670de5857520219fc4","Ocean College, Zhejiang University, Zhoushan, China; School of Civil and Environmental Engineering, Nanyang Technological University, Singapore","Wang X., Ocean College, Zhejiang University, Zhoushan, China, School of Civil and Environmental Engineering, Nanyang Technological University, Singapore; Wong Y.D., School of Civil and Environmental Engineering, Nanyang Technological University, Singapore; Teo C.C., School of Civil and Environmental Engineering, Nanyang Technological University, Singapore; Yuen K.F., School of Civil and Environmental Engineering, Nanyang Technological University, Singapore; Feng X., Ocean College, Zhejiang University, Zhoushan, China","With the rapid growth of e-commerce and technology-based self-services, consumers are increasingly encouraged to co-create individualised self-collection services. This study aims to conceptualise the multiple key facets of self-collection as viewed from consumers' perspectives and identify the latent consumer segments of the service. A total of 603 valid responses are collected, and the data are analysed using the latent class analysis. Adopting the paradigm of value co-creation, we conceptualised the self-collection service as service innovation, an empowerment tool, a green initiative and a value-based experience. Based on the conceptualisation, five latent segments of the service are identified, which are labelled as Patrons, Traditionalists, Self-enhancers, Green-lovers and Haters (from the largest to the smallest segment). By doing this, this study contributes to the literature by demonstrating the heterogeneity in consumers' participation patterns of value co-creation in e-commerce last-mile logistics. © 2019 Elsevier B.V.","E-commerce; Last-mile logistics; Latent class analysis; Market segmentation; Value co-creation","Computer science; Marketing; Consumer segments; Last mile; Latent class analysis; Market segmentation; Service innovation; Technology-based self-services; User segment; Value co creations; Electronic commerce",{"$nulls":4},"Social Science Foundation of Zhejiang Province; Natural Science Foundation of Zhejiang Province, (17NDJC194YB)","Funding text 1: This work is supported by the Social Science Foundation of Zhejiang Province (No. 17NDJC194YB).; Funding text 2: This work is supported by the Social Science Foundation of Zhejiang Province (No. 17NDJC194YB ). 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Mark., (2017); Zhang M., Ren C., Wang G.A., He Z., The impact of channel integration on consumer responses in omnichannel retailing: the mediating effect of consumer empowerment, Electron. Commer. Res. Appl., 28, 1, (2018); Zwick D., Bonsu S.K., Darmody A., Putting consumers to work: ‘co-creation’ and new marketing govern-mentality, J. Consum. Cult., 8, 2, pp. 163-196, (2008)","K.F. Yuen; School of Civil and Environmental Engineering, Nanyang Technological University, Singapore; email: yuen0016@e.ntu.edu.sg",null,"Elsevier B.V.",{"$nulls":5},1.5674223E7,null,null,null,"English","Elect. Commer. Res. Appl.","Article","Final",null,"Scopus","2-s2.0-85075780252"]
["Jennings D.; Figliozzi M.","Jennings, Dylan (57209466510); Figliozzi, Miguel (6507854711)","57209466510; 6507854711","Study of Sidewalk Autonomous Delivery Robots and Their Potential Impacts on Freight Efficiency and Travel",2019.0,"Transportation Research Record",2673.0,6.0,null,317.0,326.0,9.0,103.0,"10.1177/0361198119849398","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85067893918&doi=10.1177%2f0361198119849398&partnerID=40&md5=27481ff4754c35fc78557a0bc44c2801","Transportation Technology and People (TTP) Lab, Department of Civil and Environmental Engineering, Portland State University, Portland, OR, United States","Jennings D., Transportation Technology and People (TTP) Lab, Department of Civil and Environmental Engineering, Portland State University, Portland, OR, United States; Figliozzi M., Transportation Technology and People (TTP) Lab, Department of Civil and Environmental Engineering, Portland State University, Portland, OR, United States","E-Commerce and package deliveries are growing at a fast pace and there is an increased demand for same-day deliveries. Established delivery companies and new startups are investing in technologies that reduce delivery times or increase delivery drivers’ productivity. In this context, the adoption of sidewalk automated (or autonomous) delivery robots (SADRs) has a growing appeal. SADRs are pedestrian sized robots that deliver items to customers without the intervention of a delivery person. Because SADRs travel on sidewalks they have been the subject of increasing regulation by local agencies in the U.S. The three research questions that guide this research effort are: (a) What are the limitations imposed by existing regulations in the U.S.?, (b) What are the technical capabilities of existing SADRs?, and (c) Given the existing capabilities and regulations, what are the time/cost savings and efficiencies that SADRs can bring about? The first part of the research discusses current U.S. regulations on SADRs and reviews existing SADR devices and their capabilities. Building on this knowledge, the second half of the research presents a novel model to estimate delivery time and number of customers served utilizing a combination of SADRs and a special delivery van. These results are compared with a baseline (or prevailing) delivery system utilizing only a conventional delivery van and human driver. Results, insights, and potential implications are discussed. The results show that SADRs can provide substantial cost and time savings in some scenarios. Furthermore, the introduction of SADRs may significantly reduce on-road travel per package delivered. © National Academy of Sciences: Transportation Research Board 2019.",null,"Efficiency; Pavements; Cost-efficiency; Delivery company; Delivery time; Local agencies; Package delivery; Potential impacts; Research efforts; Research questions; Technical capabilities; Time cost; Robots",{"$nulls":4},"Freight Mobility Research Institute; U.S. DOT University Transportation Center","This research project was funded by the Freight Mobility Research Institute (FMRI), a U.S. DOT University Transportation Center.","(2018); Rogers K., Higher Demand for Quick Delivery Is Creating a Boom in Jobs, CNBC News, (2018); Boysen N., Schwerdfeger S., Weidinger F., Scheduling Last-Mile Deliveries with Truck-Based Autonomous Robots, European Journal of Operational Research, 271, 3, pp. 1085-1099, (2018); Vleeshouwer T., Duin R.V., Verbraeck A., Implementatie van autonome bezorgrobots voor een kleinschalige thuisbenzorgdienst, ResearchGate, (2017); The Sydney Morning Herald; Harris-Burland H., Starship Technologies Launches Pilot Program with Domino’s Pizza Enterprises, Starship; Sawers P., Starship Technologies Launches Autonomous Robot Delivery Services for Campuses, Venturebeat; Dickey M.R., Self-Driving Delivery Vehicle Startup Dispatch Raises $2 Million Seed Round Led by Andreessen Horowitz, Techcrunch; Kolodny L., Marble and Yelp Eat24 Start Robot Food Delivery in San Francisco, Techcrunch; Fischer J., Thyssenkrupp Looks to Delivery Robots for Elevator Maintenance Logistics, Thyssenkrupp; Mercedes-Benz Vans Invests in Starship Technologies, the World’s Leading Manufacturer of Delivery Robots, (2017); Menlo College; Weiner A., Minor Roadblocks Stand in the Way of Personal Delivery Devices, The Spoon; CBS SF Bay Area; Harris M., Our Streets Are Made for People”: San Francisco Mulls Ban on Delivery Robots, The Guardian; Zaleski A., San Francisco to Delivery Robots: Get Off the Damn Sidewalk, Citylab; Zhang B., Personal Delivery Devices to Expand across Bay Area, The Campanile; Glaser A., A Robot-Delivery Startup Helped Write State Laws That Are Locking Out Competition, Recode; Robby.io; Kiwicampus; Figliozzi M., Analysis of the Efficiency of Urban Commercial Vehicle Tours: Data Collection, Methodology, and Policy Implications, Transportation Research Part B: Methodological, 41, pp. 1014-1032, (2007); Figliozzi M., The Impacts of Congestion on Commercial Vehicle Tour Characteristics and Costs, Transportation Research Part E: Logistics and Transportation Review, 46, pp. 496-506, (2010); Kershner R., The Number of Circles Covering a Set, American Journal of Mathematics, 61, 3, pp. 665-671, (1939); Pierce D., Delivery Drones Are Coming: Jeff Bezos Promises Half-Hour Shipping with Amazon Prime Air, The Verge; Green D., Amazon Bringing 2-Hour Delivery to Whole Foods Is a Sneaky Change in Strategy, and It Could Mean a Big Change Is Coming; Figliozzi M., Lifecycle Modeling and Assessment of Unmanned Aerial Vehicles (Drones) CO<sub>2</sub>e Emissions, Transportation Research Part D: Transport and Environment, 57, pp. 251-261, (2017); Outwater M., Kitchen M., Value of Time for Travel Forecasting and Benefit Analysis; Meek A., The Robots Are Coming (to Deliver Your Groceries), BGR; Condliffe J., Why Sidewalk Delivery Robots Still Need Safety Drivers, Technologyreview; Figliozzi M.A., Tipagornwong C., Impact of Last Mile Parking Availability on Commercial Vehicle Costs and Operations, Supply Chain Forum: An International Journal, 18, 2, pp. 60-68, (2017)","M. Figliozzi; Transportation Technology and People (TTP) Lab, Department of Civil and Environmental Engineering, Portland State University, Portland, United States; email: figliozzi@pdx.edu",null,"SAGE Publications Ltd",{"$nulls":5},3611981.0,null,"TRRED",null,"English","Transp Res Rec","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85067893918"]
["Le H.T.; Le N.T.T.; Phien N.N.; Duong-Trung N.; Son H.X.; Huynh T.T.; Nguyen T.P.","Le, Hai Trieu (57208802236); Le, Ngoc Tien Thanh (57220612632); Phien, Nguyen Ngoc (58179158800); Duong-Trung, Nghia (57191328820); Son, Ha Xuan (57193341872); Huynh, Thai Tam (57209173318); Nguyen, The Phuc (57208750325)","57208802236; 57220612632; 58179158800; 57191328820; 57193341872; 57209173318; 57208750325","Introducing multi shippers mechanism for decentralized cash on delivery system",2019.0,"International Journal of Advanced Computer Science and Applications",10.0,6.0,null,590.0,597.0,7.0,26.0,"10.14569/ijacsa.2019.0100676","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85070529693&doi=10.14569%2fijacsa.2019.0100676&partnerID=40&md5=064e165807b97a3cf89381b939cfc7a8","Cantho University of Technology, Can Tho city, Viet Nam; Center for Applied Information Technology, Ton Duc Thang University, Ho Chi Minh city, Viet Nam; Faculty of Information Technology, Ton Duc Thang University, Ho Chi Minh city, Viet Nam; Can Tho University of Technology, FPT University, Can Tho city, Viet Nam; Transaction Technologies PTE. LTD., Singapore; University of Trento, Trento, Italy","Le H.T., Cantho University of Technology, Can Tho city, Viet Nam; Le N.T.T., Cantho University of Technology, Can Tho city, Viet Nam; Phien N.N., Center for Applied Information Technology, Ton Duc Thang University, Ho Chi Minh city, Viet Nam, Faculty of Information Technology, Ton Duc Thang University, Ho Chi Minh city, Viet Nam; Duong-Trung N., Cantho University of Technology, Can Tho city, Viet Nam, Can Tho University of Technology, FPT University, Can Tho city, Viet Nam; Son H.X., Cantho University of Technology, Can Tho city, Viet Nam, Can Tho University of Technology, FPT University, Can Tho city, Viet Nam; Huynh T.T., Transaction Technologies PTE. LTD., Singapore; Nguyen T.P., University of Trento, Trento, Italy","One of the major problems of e-commerce globally is the selling and buying of goods among the parties over the Internet in which the traders may not trust their partners. Cash on delivery allows customers to pay in cash when the product is delivered to their home or a location they choose. This is sometimes called a payment system because customers receive goods before making a payment. This paper investigates a critical verification process issue in the cash on delivery system. In particular, we propose a multi shippers mechanism, which consists of blockchain technology, smart contracts and hyperledger fabric platform to achieve distributed and trustworthy verification across participants in the decentralized markets. Our proposed mechanism is given to not only ensure the benefits of the seller but also prevent shipper's fraudulent. The solution leverages the consistency and robustness of decentralized markets where trust is flexible and effectively controlled. To demonstrate the application and implementation of the proposed framework, we conduct several case studies on real-world transaction datasets from a local computer retailer. We also provide our sources codes for further reproducibility and development. Our conclusion is that the continued integration of multi-shipper mechanism and blockchain technology in the decentralized markets will cause significant transformations across several disciplines. © 2019 International Journal of Advanced Computer Science and Applications.","Blockchain; Cash on Delivery (COD); Hyperledger fabric; Smart contract","Distributed ledger; Sales; Ships; Block-chain; Cash on delivery; Cash-on-delivery; Decentralised; Delivery systems; E- commerces; Hyperledg fabric; Payment systems; Process issues; Verification process; Smart contract",{"$nulls":6},"Asgaonkar A., Krishnamachari B., Solving the buyer and seller's dilemma: A dual-deposit escrow smart contract for provably cheat-proof delivery and payment for a digital good without a trusted mediator, (2018); Hasan H.R., Salah K., Blockchain-based solution for proof of delivery of physical assets, in International Conference on Blockchain, pp. 139-152, (2018); Two party contracts,, (2015); How our escrow smart contract works,, (2017); Sites like ebay or etsy but decentralized-our features.; Sidhu J., Syscoin: A peer-to-peer electronic cash system with blockchain-based services for e-business, in 2017 26th international conference on computer communication and networks (ICCCN). IEEE, pp. 1-6, (2017); Double deposit escrow.; Le N.T.T., Nguyen Q.N., Phien N.N., Duong-Trung N., Huynh T.T., Nguyen T.P., Son H.X., Assuring nonfraudulent transactions in cash on delivery by introducing double smart contracts, International Journal of Advanced Computer Science and Applications, 10, 5, (2019); Ethereum project.; Son H.X., Nguyen M.H., Phien N.N., Le H.T., Nguyen Q.N., Dinh V.D., Tru P.T., Nguyen P., Towards a mechanism for protecting seller's interest of cash on delivery by using smart contract in hyperledger, International Journal of Advanced Computer Science and Applications, 10, 4, (2019); Hyperledger fabric.; Wood G., Et al., Ethereum: A secure decentralised generalised transaction ledger, Ethereum project yellow paper, 151, pp. 1-32, (2014); Hamid T., Cash on delivery the biggest obstacle to e-commerce in uae and region; Idelberger F., Governatori G., Riveret R., Sartor G., Evaluation of logic-based smart contracts for blockchain systems, in International Symposium on Rules and Rule Markup Languages for the Semantic Web, pp. 167-183, (2016); Alharby M., van Moorsel A., Blockchain-based smart contracts: A systematic mapping study, (2017); He D., Habermeier K.F., Leckow R.B., Haksar V., Almeida Y., Kashima M., Kyriakos-Saad N., Oura H., Sedik T.S., Stetsenko N., Et al., Virtual currencies and beyond: initial considerations, (2016); Delmolino K., Arnett M., Kosba A., Miller A., Shi E., Step by step towards creating a safe smart contract: Lessons and insights from a cryptocurrency lab, in International Conference on Financial Cryptography and Data Security, pp. 79-94, (2016); Androulaki E., Barger A., Bortnikov V., Cachin C., Christidis K., De Caro A., Enyeart D., Ferris C., Laventman G., Manevich Y., Et al., Hyperledger fabric: a distributed operating system for permissioned blockchains, Proceedings of the Thirteenth EuroSys Conference, (2018); Thakkar P., Nathan S., Viswanathan B., Performance benchmarking and optimizing hyperledger fabric blockchain platform, in 2018 IEEE 26th International Symposium on Modeling, pp. 264-276, (2018); Benhamouda F., Halevi S., Halevi T.T., Supporting private data on hyperledger fabric with secure multiparty computation, IBM Journal of Research and Development, (2019)",null,null,"Science and Information Organization",{"$nulls":5},"2158107X",null,null,null,"English","Intl. J. Adv.  Comput. Sci. Appl.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85070529693"]
["Anib A.; Gayathri A.; Shabu K.R.","Anib, Aparna (57209316385); Gayathri, A. (57212332188); Shabu, K.R. (57200081054)","57209316385; 57212332188; 57200081054","Consumer perception towards Swiggy digital food application service: a analytical study with special reference to Ernakulam City",2019.0,"International Journal of Innovative Technology and Exploring Engineering",8.0,6.0,null,791.0,797.0,6.0,3.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85067341882&partnerID=40&md5=c674b4cef4d427108e52e96c473016b6","Department of Commerce and Management, Amrita Vishwa Vidyapeetham, Amrita School of Arts and Science, Old NH17, Edappally North, Amrita Nagar, Brahmasthanam, Kochi, 682024, Kerala, India","Anib A., Department of Commerce and Management, Amrita Vishwa Vidyapeetham, Amrita School of Arts and Science, Old NH17, Edappally North, Amrita Nagar, Brahmasthanam, Kochi, 682024, Kerala, India; Gayathri A., Department of Commerce and Management, Amrita Vishwa Vidyapeetham, Amrita School of Arts and Science, Old NH17, Edappally North, Amrita Nagar, Brahmasthanam, Kochi, 682024, Kerala, India; Shabu K.R., Department of Commerce and Management, Amrita Vishwa Vidyapeetham, Amrita School of Arts and Science, Old NH17, Edappally North, Amrita Nagar, Brahmasthanam, Kochi, 682024, Kerala, India","Online food ordering and delivery is a new type of business model in the current era of e-commerce and that leads to the startups of several online business. Online food ordering and delivery is very successful because it bridges the gap between restaurants and consumers. It is a process were a customer will search for a restaurant and filter with the available items, cuisines and they deliver by an application in the mobile phone. Swiggy is an application for food ordering and delivery which is a Bangalore based company. Swiggy was mainly to provide a complete order and delivery solution to the urban foodies. The main aim of this research is to study the factors influencing the consumer perception and buying decision of Swiggy and to study the level of consumer satisfaction of Swiggy. For this purpose, with help of convenient sampling method 100 respondents were selected and data were collected through structured questionnaire. The result of the result showed that, there is significant relationship between usage and satisfaction of services of Swiggy, there is significant relationship between usage and preference over other food ordering apps, there is no association between age and frequent usage of Swiggy app, there is no association between gender and convenience of Swiggy app. © BEIESP.","Consumer perception; Customer satisfaction; Delivery; Online food ordering; Swiggy application",{"$nulls":7},"Hariramani S.G., Consumer Perception about online shopping in India. International, Journal of Management, IT & Engineering, 8, 2, (2018); Shafie F.A., Rennie D., Consumer perception towards organic food, Science Direct Proceedings of the 1St National Conference on Environment-Behaviour Studies, 1Ncebs, FAPS, Uitm, (2009); Miryala R.K., Mennakanti J.P., Responsible marketing for sustainable development, Zenon Academic Publishing, (2016); Goyal A., Singh N.P., Consumer perception about fast food in India: An exploratory study, British Food Journal, 109, 2, (2007); Goyal S., Comparative study on “consumer behavior of working women and homemakers for the ready to eat food products in Salem city, Asian Journal of Multidimensional Research, 7, 2, (2018); Kumaran M., Perception Towards Online Shopping an Empirical Study with Respect to Indian Buyers, 1, 9",null,null,"Blue Eyes Intelligence Engineering and Sciences Publication",{"$nulls":5},2.2783075E7,null,null,null,"English","Int. J. Innov. Technol. Explor. Eng.","Article","Final",null,"Scopus","2-s2.0-85067341882"]
["Mutimukwe C.; Kolkowska E.; Grönlund Å.","Mutimukwe, Chantal (26646798200); Kolkowska, Ella (43961188000); Grönlund, Åke (23388909200)","26646798200; 43961188000; 23388909200","Information privacy in e-service: Effect of organizational privacy assurances on individual privacy concerns, perceptions, trust and self-disclosure behavior",2020.0,"Government Information Quarterly",37.0,1.0,101413.0,null,null,null,74.0,"10.1016/j.giq.2019.101413","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85075404317&doi=10.1016%2fj.giq.2019.101413&partnerID=40&md5=65568e1d0a5e19228ba69b4f2de749cb","School of Business, Örebro University, Sweden; School of ICT, University of Rwanda, Rwanda","Mutimukwe C., School of Business, Örebro University, Sweden, School of ICT, University of Rwanda, Rwanda; Kolkowska E., School of Business, Örebro University, Sweden; Grönlund Å., School of Business, Örebro University, Sweden","The increasing use of the Internet for service delivery has paralleled an increase of e-service users' privacy concerns as technology offers ample opportunities for organizations to store, process, and exploit personal data. This may reduce individuals' perceived ability to control their personal information and increase their perceived privacy risk. A systematic understanding of individuals' privacy concerns is important as negative user perceptions are a challenge to service providers' reputation and may hamper service delivery processes as they influence users' trust and willingness to disclose personal information. This study develops and validates a model that examines the effect of organizational privacy assurances on individual privacy concerns, privacy control and risk perceptions, trust beliefs and non-self-disclosure behavior. Drawing on a survey to 547 users of different types of e-services – e-government, e-commerce and social networking – in Rwanda, and working within the framework of exploratory analysis, this study uses partial least square-structural equation modeling to validate the overall model and the proposed hypotheses. The findings show that perceptions of privacy risks and privacy control are antecedents of e-service users' privacy concerns, trust and non-self-disclosure behavior. They further show that the perceived effectiveness of privacy policy and perceived effectiveness of self-regulations influence both perceptions of privacy risks and control and their consequences; users' privacy concerns, trust and non-self-disclosure behavior. The hypotheses are supported differently across the three types of e-services, which means that privacy is specific to context and situation. The study shows that the effect of privacy assurances on trust is different in e-government services than in other services which suggest that trust in e-government may be more complex and different in nature than in other contexts. The findings serve to enhance a theoretical understanding of organizational privacy assurances and individual privacy concerns, trust and self-disclosure behavior. They also have implications for e-service providers and users as well as for regulatory bodies and e-services designers. © 2019 Elsevier Inc.",{"$nulls":8},"Abri D.A., Mcgill T., Dixon M., Examining the impact of E-privacy risk concerns on citizens'intentions to use E-government services: An Oman perspective, Journal of Information Privacy and Security, 5, 2, pp. 3-26, (2009); Akram W., Kumar R., A study on positive and negative effects of social media on society, International Journal of Computer Sciences and Engineering, 5, 10, pp. 351-354, (2018); Al-Jamal M., Abu-Shanab E., Privacypolicyof E-governmentwebsites: Anitemizedchecklistproposedandtested, Management Research and Practice, 7, 3, pp. 80-95, (2015); Bandyopadhyay S., Antecedents and consequences of consumers online privacy concerns, Journal of Business and Economics Research, 7, 3, pp. 41-48, (2009); Bansal G., Zahedi F.M., Gefen D., The role of privacy assurance mechanisms in building trust and the moderating role of privacy concern, European Journal of Information Systems, (2015); Bansal G., Zahedi F.M., Gefen D., Efficacy of privacy assurance mechanisms in the context of disclosing health information online, AMCIS 2008 proceedings, pp. 1-11, (2008); Belanger F., Carter L., Trust and risk in E-government adoption, Journal of Strategic Information Systems, 1, 17, pp. 165-176, (2008); Belanger F., Crossler R.E., Privacy in the digital age: A review of information privacy research in information system, Management Information Systems Quarterly, 35, 4, pp. 1-36, (2011); Belanger F., Hiller J., Smith W.J., Trustworthiness in electronic commerce: The role of privacy, security, and site attributes, Journal of Strategic Information Systems, 11, (2002); Bellman S., Johnson E.J., Kobrin S.J., Lohse G.L., International differences in information privacy concerns: A global survey of consumers, The Information Society, 20, 5, pp. 313-324, (2004); Bertram D., Likert scales, (2007); Borena B., Belanger F., Ejigu D., Informatiopraction privacy protection practices in Africa: A review trough the Lens on critical social theory, 48th Hawaii international conference on system sciences, pp. 3490-3497, (2015); 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The Republic of Rwanda, The constitution of the Republic of Rwanda of 2003 revised in 2015, (2015); The Republic of Rwanda, Law governing information and communication technologies, (2016); UNDESA, 2018 E-government survey, (2018); Van Slyke C., Shim J.T., Johnson R., Jiang J.J., Concern for information privacy and online consumer purchasing, Journal of the Association for Information Systems, 7, 1, pp. 415-444, (2006); Westin A.F., Privacy and freedom, (1967); Wirtz J., Lwin M.O., Regulatory focus theory, trust and privacy concern, Journal of Service Research, 12, 2, pp. 190-205, (2009); World Bank, Agricultural development in Rwanda, (2013); World Bank, DataBank, (2016); Wu K.W., Huang S.Y., Yen D.C., Popova I., The effect of online privacy policy on consumer privacy concern and trust, Computers in Human Behavior, 28, 3, pp. 889-897, (2012); Wu Y., Protecting personal data in E-government: A cross-country study, Government Information Quarterly, 31, 1, pp. 150-159, (2014); Xu H., Dinev T., Smith H.J., Hart P., Examining the formation of individual's privacy concerns: Toward an integrative view, International conference on information systems (ICIS) 2008 proceedings, pp. 1-16, (2008); Xu H., Dinev T., Smith J., Hart P., Information privacy concerns: Linking individual perceptions with institutional privacy assurances, Journal of the Association for Information Systems, 12, 12, pp. 798-824, (2011); Xu H., Teo H., Tan B.C.Y., Agarwal R., Effects of individual self-protection, industry self-regulation, and government regulation on privacy concerns: A study of location-based services, Information Systems Research, 23, 4, pp. 1342-1363, (2012); Yilma K.M., The quest for information privacy in Africa – A review essay, Journal of Information Policy, 7, pp. 111-119, (2017); Yu J., Electronic government and its implication for data privacy in Hong Kong: Can personal data (privacy) ordinance protect the privacy of personal information in cyberspace?, Internationl Review of Law, Computer and Technology, 19, 2, pp. 143-163, (2005)","C. Mutimukwe; School of Business, Örebro University, Sweden; email: chantal.mutimukwe@oru.se",null,"Elsevier Ltd",{"$nulls":5},"0740624X",null,"GIQUE",null,"English","Gov. Inf. Q.","Article","Final",null,"Scopus","2-s2.0-85075404317"]
["Kashurnikov S.N.; Sevalnev V.V.; Truntsevsky Y.V.; Cherepanova E.V.; Berestneva O.G.","Kashurnikov, Sergey N. (57200283461); Sevalnev, Viacheslav V. (57208903286); Truntsevsky, Yuri V. (57202821475); Cherepanova, Ekaterina V. (57210820414); Berestneva, Olga G. (10043013900)","57200283461; 57208903286; 57202821475; 57210820414; 10043013900","E-commerce in supply chain management: Its introduction and prospects in the light industry",2019.0,"International Journal of Supply Chain Management",8.0,4.0,null,727.0,732.0,5.0,5.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85071552954&partnerID=40&md5=0dd2c81d279119c227a49d4c7523a376","Department of Economics, Financial University under the Government of the Russian Federation, Moscow, Russian Federation; Department of Methodology of Combating Corruption, Institute of Legislation and Comparative Law under the Government of the Russian Federation, Moscow, Russian Federation; Department of Information Technology, Tomsk Polytechnic University, Tomsk, Russian Federation","Kashurnikov S.N., Department of Economics, Financial University under the Government of the Russian Federation, Moscow, Russian Federation; Sevalnev V.V., Department of Methodology of Combating Corruption, Institute of Legislation and Comparative Law under the Government of the Russian Federation, Moscow, Russian Federation; Truntsevsky Y.V., Department of Methodology of Combating Corruption, Institute of Legislation and Comparative Law under the Government of the Russian Federation, Moscow, Russian Federation; Cherepanova E.V., Department of Methodology of Combating Corruption, Institute of Legislation and Comparative Law under the Government of the Russian Federation, Moscow, Russian Federation; Berestneva O.G., Department of Information Technology, Tomsk Polytechnic University, Tomsk, Russian Federation","The research deals with current trends of e-commerce in supply chain management through the example of light industry. It is shown that one of the current trends in supply chain management is human labor reduction and almost complete automation of warehouse and transport operations. The practice of domestic online stores in e-commerce is regarded. It has been revealed that for domestic stores there is a lag in using innovative means. This is explained by the small volume of sales. The introduction of innovations, which include business analytics, mobile technologies and applications, omni channel logistics, the use of electric vehicles, autonomous vehicles and drones, the use of cloud computing technologies, e-commerce, automatic identification and data collection, 3D printing, has not become popular in domestic online stores. © ExcelingTech Pub, UK.","Delivery; E-commerce; Payment systems; Supply chain management; Warehouse automation",{"$nulls":5},"Russian Foundation for Basic Research, РФФИ, (18-29-16023)","The reported study was funded by RFBR according to the research project № 18-29-16023.","The Analysis of world experience in the development of industry and approaches to the digital transformation of the industry of the Eurasian Economic Union members; Panfilov E.E., Information security of industrial organization in the context of the development of the Internet economy, Scientific, technical and industrial journal \"Bulletin of Computer and Information Technologies\", 2, 56, pp. 23-29, (2009); Worldwide retail and ecommerce sales: eMarketer's estimates for 2016,2021, (2018); Yu Y., Wang X., Zhong R.Y., Huang G.Q., E-commerce logistics in supply chain management: Practice perspective, Procedia Cirp, 52, pp. 179-185, (2016); Kawa A., Pieranski B., Zdrenka W., Dynamic configuration of same-day delivery in E-commerce, In Modern Approaches for Intelligent Information and Database Systems, pp. 305-315, (2006); Riemer K., E-Commerce und Supply-Chain-Management: Maßnahmen und Instrumente zur Verbesserung der Koordination in Lieferketten (No 53), (2008); Rybalko M.A., Formation and development of modern market structures in supply chain management: thesis by the PhD in Economics, Lomonosov Moscow State University, (2011); Gorobechiya T., Formation of logistical supply chains of the industrial enterprise through the example of the textile industry market: thesis by the PhD in Economics, Russian institute of textile and light industry, (2011); Alrubaiee L., Alshaibi H., Al-bayati Y., Relationship between B2B e-commerce benefits, e-marketplace usage and supply chain management, Global Journal of Management and Business Research, 12, 9, (2012); Markina M.A., System analysis of the e-commerce impact on the distribution and storage system, Modern scientific research and innovation, 5, (2015); Curtis Barry F., 10 Supply Chain Strategies for eCommerce Businesses; Kaluzhskiy M.L., E-commerce: marketing networks and market infrastructure, M.: Economy, 328, (2014); Kaluzhskiy M.L., Logistics e-commerce infrastructure, Management in Russia and abroad, 3, pp. 18-26, (2014); Kaluzhskiy M.L., Electronic commerce: marketing networks and market infrastructure: monograph, (2015); Gilmore D., A Decade of Supply Chain Management, Supply Chain Digest, (2010); Ali Akbar A., Abolghasem B.S., Hossein Moghadasan M., Information technology; a facilitator for improving dynamic capabilities through knowledge management utilization, UCT Journal of Management and Accounting Studies, 2, pp. 27-36, (2014); Akhmetshin E.M., Mueller J.E., Pronskaya O.N., Innovative technologies in entrepreneurship education: The case of european and asian countries, Journal of Entrepreneurship Education, 22, 1, (2019); Panfilova E.E., The Mechanism of Management of Integrated Structures of Industrial Organizations, All-Russian Scientific and Practical Journal of Economics \"Russian Entrepreneurship\", 17, 239, pp. 65-71, (2013); Muhammad K., The Effects of Electronic Human Resource Management on Financial Institutes, Journal of Humanities Insights, 2, 1, pp. 1-5, (2018)",null,null,"ExcelingTech",{"$nulls":5},2.0513771E7,null,null,null,"English","Int. J. Supply Chain Manag.","Article","Final",null,"Scopus","2-s2.0-85071552954"]
["Tan K.S.; Subramanian P.","Tan, Kok Sheng (57211319913); Subramanian, Preethi (57203986937)","57211319913; 57203986937","Proposition of machine learning driven personalized marketing approach for E-Commerce",2019.0,"Journal of Computational and Theoretical Nanoscience",16.0,8.0,null,3532.0,3537.0,5.0,2.0,"10.1166/jctn.2019.8319","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85073454482&doi=10.1166%2fjctn.2019.8319&partnerID=40&md5=c845d21d26c215619c17975f2f116ac8","Asia Pacific University of Technology and Innovation, 57000, Malaysia","Tan K.S., Asia Pacific University of Technology and Innovation, 57000, Malaysia; Subramanian P., Asia Pacific University of Technology and Innovation, 57000, Malaysia","The ubiquity of digital devices and Internet has formed a constantly connected online environment which led to the extensive adoption of e-commerce. However, the active participation of growing number of stakeholders intensifies the highly competitive landscape of the dynamic e-commerce market and the scarcity of trust in e-commerce business impede the generation of consistent sales growth. The obstruction necessitates the implementation of innovative marketing strategies to enhance the relationships with customers to develop customer loyalty. Therefore, a machine learning driven personalized marketing approach is proposed to facilitate the implementation of personalized marketing in which there are 2 significant sequential elements namely, the development of personalized marketing contents and delivery of the contents to prospective customers. Cluster analysis is employed to perform customer segmentation to discover customer segments due to the capability of the analysis to identify similarities in customer preferences in which the discovered customer segments are used to construct personalized marketing contents. In addition, artificial neural network is employed to predict prospective customers due to the capability of artificial neural network to comprehend complex relationships between customer demographics and buying behaviour in which the prediction facilitates the delivery of the constructed personalized marketing contents to potential repeat customer to optimize the marketing initiative. The combination of cluster analysis and artificial neural network empowers the construction of an efficacious marketing pipeline which enhances the competency of e-commerce businesses. Copyright © 2019 American Scientific Publishers All rights reserved.","ANN; Clustering; E-Commerce; Machine Learning; Marketing; Personalization",{"$nulls":7},"Sin K.Y., Osman A., Salahuddin S.N., Abdullah S., Lim Y.J., Relative advantage and competitive pressure towards implementation of e-commerce: Overview of small and medium enterprises (SMEs), Procedia Economics and Finance, 35, pp. 434-443, (2016); Tang H., Liao S.S., Sun S.X., A prediction framework based on contextual data to support mobile personalized marketing, Decision Support Systems, 56, pp. 234-246, (2013); Xiao L., Guo Z., D'Ambra J., Fu B., Building loyalty in e-commerce: Towards a multidimensional trust-based framework for the case of China, Program: Electronic Library and Information Systems, 50, 4, pp. 431-461, (2016); Kaptein M., Parvinen P., Advancing e-commerce personalization: Process framework and case study, International Journal of Electronics Commerce, 19, 3, pp. 7-33, (2015); Oliveira T., Alhinho M., Rita P., Dhillon G., Modelling and testing consumer trust dimensions in e-commerce, Computers in Human Behavior, 71, 6, pp. 153-164, (2017); Kim Y., Peterson R.A., A meta-analysis of online trust relationships in e-commerce, Journal of Interactive Marketing, 38, 5, pp. 44-54, (2017); Zhao Y., Ming Y., Liu X., Zhu E., Zhao K., Yin J., Large-scale K-means clustering via variance reduction, Neurocomputing, 307, 9, pp. 184-194, (2018); Yu S.S., Chu S.W., Wang C.M., Chan Y.K., Chang T.C., Two improved K-means algorithms, Applied Soft Computing, 68, 7, pp. 747-755, (2018); Vanneschi L., Horn D.M., Castelli M., Popovic A., An artificial intelligence system for predicting customer default in e-commerce, Expert Systems with Applications, 104, 8, pp. 1-21, (2018); Tran T.P., Personalized Ads on facebook: An effective marketing tool for online marketers, Journal of Retailing and Consumer Services, 39, 11, pp. 230-242, (2017); Aggarwal C., Data Mining: The Textbook, (2015); Kanamori T., Fujiwara S., Takeda A., Robustness of learning algorithms using hinge loss with outlier indicators, Neural Networks, 94, 10, pp. 173-191, (2017); Witten I.H., Frank E., Hall M.A., Pal C.J., Data Mining, (2017); Vafeiadis T., Diamantaras K.I., Sarigiannidis G., Chatzisavvas K.C., A comparison of machine learning techniques for customer churn prediction, Simulation Modelling Practice and Theory, 55, 6, pp. 1-9, (2015)",null,null,"American Scientific Publishers",{"$nulls":5},1.5461955E7,null,null,null,"English","J. Comput. Theor. Nanosci.","Article","Final",null,"Scopus","2-s2.0-85073454482"]
["Ajitha P.; Gomathi R.M.; Sivasangari A.","Ajitha, P. (56378348300); Gomathi, R.M. (6507109762); Sivasangari, A. (56622983700)","56378348300; 6507109762; 56622983700","Design of online shopping cart using prestashop e-commerce",2019.0,"International Journal of Advanced Research in Engineering and Technology",10.0,5.0,null,134.0,142.0,8.0,2.0,"10.34218/IJARET.10.5.2019.014","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85080112555&doi=10.34218%2fIJARET.10.5.2019.014&partnerID=40&md5=a0835495d98e0646a613944c2cea92be","Sathyabama Institute of Science and Technology, Chennai, India","Ajitha P., Sathyabama Institute of Science and Technology, Chennai, India; Gomathi R.M., Sathyabama Institute of Science and Technology, Chennai, India; Sivasangari A., Sathyabama Institute of Science and Technology, Chennai, India","E-Commerce is a consumer and delivery individual shopping cart program. The main objective is to provide consumers with smart security service. This system provides good and efficient information, making the service more intelligent. Browse the catalog and order the products online is an app for consumers. Multiple stakeholders can order with full security and control using the power of the Internet. This program collects and stores all kinds of information about the order type choices that govern an order's life cycle. This offers a marketing and controlling end-to-end solution.Only with a tap can the information be accessed from anywhere by following this new approach. It helps users to save a lot of time and provide up-to-date information to the user. The software helps enhance customer and supplier support. We can monitor and control the positions and accuracy in this application. It can enable the vendor to monitor their data. The application's central concept is to allow the consumer to shop online using the Internet and enable customers to purchase from the store items and products of their choice.Each data can be easily manipulated by our GPS system through a centralized database. The database handles the shipment of customers and products to their submitted address. This software also allows us to track where we are. As an established and used market model, e-commerce is rapidly gaining ground. It is reasonable to say that the shopping cycle on the internet becomes a common place and continuous services. © IAEME Publication.","E-Commerce; GSM; Non-Preemptive Schedule; Preemptive Schedule",{"$nulls":7},"VizcarraMelgar M.E., MelgarSantander L.A., An Alternative proposal for tracking products, IEEE Colombian Conference, (2014); Salmsnalmishari N.A., The energy efficient real time vehicle tracking system, IEEE Conference, 21, (2017); Li G., Huang F., Cheng T.C.E., Ji P., Competition between manufacturer’s online customization Channel and computational retailer, IEEE Transaction on Engineering Management, 6, 2, (2015); Devaraju P., Challenges and opportunities in e-fulfillment, IEEE Transaction on Engineering Management, Vol5, (2016); Celies C.R., Marguarette, An Analysis of Supply Chain Best Practice in the Retail with Case Study of Wal-Mart and Amazon, (2016); Sivasangari A., Ajitha P., Indira K., Air Pollution Monitoring and Prediction using Multi view Hybrid Model, International Journal of Engineering and Advanced Technology(IJEAT), 8, 2 S, pp. 1370-1372; Brumancia E., Samuel S.J., Gladence L.M., Rathan K., Hybrid Data Fusion Model for Restricted Information Using Dempster–Shafer and Adaptive Neuro-Fuzzy Inference (DSANFI) System, 23, 8, pp. 2637-2644, (2019); Indira K., Ajitha P., Reshma V., Tamizhselvi A., An efficient secured routing protocol for software defined internet of vehicles, 2nd International Conference on Computational Intelligence in Data Science, Proceedings, (2019); Bhat S., A study on factors influencing online shopping behaviour among consumers in Panaji, Journal of Management, 5, 5, pp. 431-464, (2018); Mironko A., The impact of human capital and skill availability on attraction of foreign direct investment (FDI) into regions within developing economies, International Journal of Management, 9, 3, pp. 164-171, (2018); Sudhakar D., Kumari R.S.D., Customer satisfication towards online shopping: A study with reference to Chittoor district, International Journal of Management, 7, 3, pp. 34-38, (2016); Kaur J., Baghla S., Modified decision table classifier by using decision support and confidence in online shopping dataset, International Journal of Computer Engineering & Technology, 8, 6, pp. 83-88, (2017); Sreejith R.K., Trends in the online shopping patterns of customers in Kattakada panchayath of Thiruvananthapuram district, International Journal of Management, 9, 5, pp. 65-74, (2018)",null,null,"IAEME Publication",{"$nulls":5},9766480.0,null,null,null,"English","Int. J. Adv. Res. Eng. Technol.","Article","Final",null,"Scopus","2-s2.0-85080112555"]
["Frontoni E.; Rosetti R.; Paolanti M.; Alves A.C.","Frontoni, Emanuele (9737451300); Rosetti, Roberto (57191053540); Paolanti, Marina (57188734162); Alves, A.C. (55486406700)","9737451300; 57191053540; 57188734162; 55486406700","HATS project for lean and smart global logistic: A shipping company case study",2020.0,"Manufacturing Letters",23.0,null,null,71.0,74.0,3.0,20.0,"10.1016/j.mfglet.2019.12.003","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85077945212&doi=10.1016%2fj.mfglet.2019.12.003&partnerID=40&md5=7de4b4f8f915e891ce5caeb7f6b42a87","Dipartimento di Ingegneria dell'Informazione (DII), Universita Politecnica delle Marche, Via Brecce Bianche, Ancona, 60131, Italy; R&D Centre ALGORITMI, Department of Production and Systems, School of Engineering, University of Minho, Guimarães, 4800-058, Portugal","Frontoni E., Dipartimento di Ingegneria dell'Informazione (DII), Universita Politecnica delle Marche, Via Brecce Bianche, Ancona, 60131, Italy; Rosetti R., Dipartimento di Ingegneria dell'Informazione (DII), Universita Politecnica delle Marche, Via Brecce Bianche, Ancona, 60131, Italy; Paolanti M., Dipartimento di Ingegneria dell'Informazione (DII), Universita Politecnica delle Marche, Via Brecce Bianche, Ancona, 60131, Italy; Alves A.C., R&D Centre ALGORITMI, Department of Production and Systems, School of Engineering, University of Minho, Guimarães, 4800-058, Portugal","Global logistic activities related to e-commerce have become very time dependent in recent years. International couriers face everyday issues related to pick-up time windows, lead times delays, express/normal deliveries management, security and VAT management. There are supply chain management methodologies that, based on lean thinking principles integrated with industry 4.0 concepts, well address these issues. In this paper, a project developed in an Italian shipping company shows the potential of solutions based on these principles and concepts. Main results from this project were lead time reduction and cost reduction, with higher goods security level and a real-time data sharing policy. © 2019 Society of Manufacturing Engineers (SME)","Cost reduction; Lead time; Lean logistic; Security; Smart logistic","Ships; Supply chain management; Global logistics; Lead time reduction; Leadtime; Lean thinking principles; Real-time data; Security; Shipping companies; Time dependent; Cost reduction",{"$nulls":6},"Monden Y., Toyota production system - an integrated approach to just-in-time, (1983); Womack J.P., Jones D.T., Roos D., (1990); Ohno T., (1988); Womack J.P., Jones D.T., Lean thinking: banish waste and create wealth in your corporation, (1996); (2002); Jones D.T., Hines P., Rich N., Lean logistics, Int J Phys Distrib Logist Manage, 27, pp. 153-173, (1997); Kagermann H., Wahister W., Helbig J., (2013); Netland T.H.; Kolberg D., Zuhlke D.; Kolberg D., Knobloch J., Zuhlke D., Towards a lean automation interface for workstations, Int J Prod Res, 55, pp. 2845-2856, (2017); Costa F., Carvalho M.D.S., Fernandes J.M., Alves A.C., Silva P., Improving visibility using RFID – the case of a company in the automotive sector, Procedia Manuf, 13, pp. 1261-1268, (2017); Pereira A., Abreu M.F., Silva D., Alves A.C., Oliveira J.A., Lopes I., Et al., Reconfigurable standardized work in a lean company – a case study, Procedia CIRP, (2016); Chen J.C., Cheng C.H., Huang P.B., Supply chain management with lean production and RFID application: a case study, Expert Syst Appl, (2013); Chen J.C., Cheng C.H., Huang P.B., Wang K.J., Huang C.J., Ting T.C., Warehouse management with lean and RFID application: a case study, Int J Adv Manuf Technol, 69, (2013); Lean B.J., Principles dońt exclude automation, Manuf Eng Mag, (2009); De Felice F., Petrillo A., Zomparelli F., Prospective design of smart manufacturing: an Italian pilot case study, Manuf Lett, 15, pp. 81-85, (2018); Uckelmann D., A definition approach to smart logistics, Next Gener. Teletraffic Wired/Wireless Adv. Netw. Lecture No, pp. 273-284, (2008); Susman G.I., Evered R.D., An assessment of the scientific merits of action research, Adm Sci Q, 23, pp. 582-603, (1978); Susman G.I., Action research: a sociotechnical systems perspective, (1987); Hubner A., Wollenburg J., Holzapfel A., Retail logistics in the transition from multichannel to omni-channel, Int J Phys Distrib Logistics Manage, 46, 6-7, pp. 562-583, (2016)",null,null,"Elsevier Ltd",{"$nulls":5},2.2138463E7,null,null,null,"English","Manuf. Let.","Article","Final",null,"Scopus","2-s2.0-85077945212"]
["Vakulenko Y.; Shams P.; Hellström D.; Hjort K.","Vakulenko, Yulia (57198431040); Shams, Poja (55258669700); Hellström, Daniel (6603092522); Hjort, Klas (55480129900)","57198431040; 55258669700; 6603092522; 55480129900","Service innovation in e-commerce last mile delivery: Mapping the e-customer journey",2019.0,"Journal of Business Research",101.0,null,null,461.0,468.0,7.0,128.0,"10.1016/j.jbusres.2019.01.016","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85059896365&doi=10.1016%2fj.jbusres.2019.01.016&partnerID=40&md5=1936292cd41471b3469175867775e5ee","Lund University, Sweden; Karlstad University, Sweden","Vakulenko Y., Lund University, Sweden; Shams P., Karlstad University, Sweden; Hellström D., Lund University, Sweden; Hjort K., Lund University, Sweden","The remarkable growth of e-commerce has defined the recent years of various industries worldwide. Driven by consumers, the e-commerce surge (e-retail in particular) stems from the final leg of the supply chain: the last mile. As the growing flow of e-commerce orders continues to generate new records for annual revenues, key actors in the last mile face the challenges of increasing customer demands and transportation volumes. In response, e-retailers and logistics service providers seek innovative service solutions, often powered by technological advancements. This study consisted of focus group interviews and a usability test that incorporated an innovative technology in the delivery service. The study provides insights into how service innovation affects e-customer behavior and presents a basic map of the e-customer journey. The findings also provide a foundation for improving management of the customer experience and aiding managerial decision-making when designing new e-commerce last mile services. © 2019 Elsevier Inc.","Customer experience; Customer journey; e-Commerce; e-Customer; Last mile delivery; Service innovation",{"$nulls":5},"VINNOVA, (2015-03563)","This research was conducted within the framework of the “Parcel Lockers in Urban and Rural Areas at Workplaces and Authorities” project, funded by VINNOVA , Sweden's Innovation Agency, reference number 2015-03563 . The funding source had no role in any aspect of the study design, collection, analysis or interpretation of the data, writing the report, or the decision to submit the article for publication. 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Vakulenko; Lund University, LTH, Department of Design Sciences, Division of Packaging Logistics, Lund, Box 118, 221 00, Sweden; email: yulia.vakulenko@plog.lth.se",null,"Elsevier Inc.",{"$nulls":5},1482963.0,null,"JBRED",null,"English","J. Bus. Res.","Article","Final",null,"Scopus","2-s2.0-85059896365"]
["Chen C.-L.; Lin D.-P.; Chen H.-C.; Deng Y.-Y.; Lee C.-F.","Chen, Chin-Ling (57214694244); Lin, Dong-Peng (57196322219); Chen, Hsing-Chung (57144819600); Deng, Yong-Yuan (25932019800); Lee, Chin-Feng (35196103500)","57214694244; 57196322219; 57144819600; 25932019800; 35196103500","Design of a logistics system with privacy and lightweight verification",2019.0,"Energies",12.0,16.0,3061.0,null,null,null,8.0,"10.3390/en12163061","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85070539667&doi=10.3390%2fen12163061&partnerID=40&md5=a78ebb79cba763fdcf3190d0e21bbb51","School of Computer and Information Engineering, Xiamen University of Technology, Xiamen, 361024, China; School of Information Engineering, Changchun Sci-Tech University, Changchun, 130600, China; Department of Computer Science and Information Engineering, Chaoyang University of Technology, Taichung, 41349, Taiwan; Department of Information Management, Chaoyang University of Technology, Taichung, 41349, Taiwan; Department of Computer Science and Information Engineering, Asia University, Taichung, 41354, Taiwan; Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, 40402, Taiwan; Department of Bioinformatics and Medical Engineering, Asia University, Taichung, 41354, Taiwan","Chen C.-L., School of Computer and Information Engineering, Xiamen University of Technology, Xiamen, 361024, China, School of Information Engineering, Changchun Sci-Tech University, Changchun, 130600, China, Department of Computer Science and Information Engineering, Chaoyang University of Technology, Taichung, 41349, Taiwan; Lin D.-P., Department of Information Management, Chaoyang University of Technology, Taichung, 41349, Taiwan; Chen H.-C., Department of Computer Science and Information Engineering, Asia University, Taichung, 41354, Taiwan, Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, 40402, Taiwan, Department of Bioinformatics and Medical Engineering, Asia University, Taichung, 41354, Taiwan; Deng Y.-Y., Department of Computer Science and Information Engineering, Chaoyang University of Technology, Taichung, 41349, Taiwan; Lee C.-F., Department of Information Management, Chaoyang University of Technology, Taichung, 41349, Taiwan","Presently, E-commerce has developed rapidly as a result of many services and applications integrating e-commerce technologies offered online. Buyers can buy goods online and sellers can then deliver the goods to them. Logistics therefore plays an important role in online e-commerce applications, with a focus on rapid delivery, the integrity of goods, and the privacy of personal information. Previous studies have proposed secure mechanisms for the transfer of electronic cash and digital content, in which only the sender and the receiver know the secret information hidden in the signature. However, they did not consider requirements such as the anonymous and lightweight verification in the logistics architecture. Therefore, this study designs a secure logistics system, with anonymous and lightweight verification, in order to meet the following requirements: Mutual authentication, non-repudiation, anonymity, integrity and a low overhead for the logistics environment. A buyer could check the goods and know if the parcel has been exchanged by a malicious person. Moreover, the proposed scheme not only presents a solution to meet the logistics system's requirements, but also to reduce both computational and communication costs. © 2019 by the authors.","Ban logic; ECC; Logistics system; Mutual authentication; Privacy","Authentication; Computation theory; Electronic commerce; BAN logic; Communication cost; E-Commerce applications; Logistics system; Mutual authentication; Personal information; Secret information; Services and applications; Data privacy",{"$nulls":4},"Ministry of Science and Technology, Taiwan, MOST, (108-2221-E-324-013)","Funding: This research was funded by the Ministry of Science and Technology, Taiwan, ROC, under contract number MOST 108-2221-E-324-013.","Aijaz A., Bochow B., Dotzer F., Festag A., Gerlach M., Kroh R., Leinmuller T., Attacks on inter vehicle communication systems—An analysis, Proceedings of the 3rd International Workshop on Intelligent Transportation, pp. 189-194, (2006); Burrows M., Abadi M., Needham R., A logic of authentication, ACM Trans. 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Res., 264, pp. 830-836, (2018); Gope P., Amin R., Hafizul Islam S.K., Kumar N., Bhalla V.K., Lightweight and privacy-preserving RFID authentication scheme for distributed IoT infrastructure with secure localization services for smart city environment, Future Gener. Comput. Syst., 83, pp. 629-637, (2018); Liang K., Susilo W., Searchable attribute-based mechanism with efficient data sharing for secure cloud storage, IEEE Trans. Inf. Forensics Secur., 10, pp. 1981-1992, (2015); Das A.K., Goswami A., A robust anonymous biometric-based remote user authentication scheme using smart cards, J. King Saud Univ. Comput. Inf. Sci., 27, pp. 193-210, (2015); Madhusudhan R., Hegde M., Security bound enhancement of remote user authentication using smart card, J. Inf. Secur. Appl., 36, pp. 59-68, (2017); Qi M., Chen J., A fresh Two-party Authentication Key Exchange Protocol for Mobile Environment, Proceedings of the International Conference on Industrial Technology and Management Science, 30, pp. 933-936, (2015); Ray B.R., Abawajy J., Chowdhury M., Alelaiwi A., Universal and secure object ownership transfer protocol for the Internet of Things, Future Gener. Comput. Syst., 78, pp. 838-849, (2017); Rajput U., Abbas F., Eun H., Oh H., A Hybrid approach for Efficient Privacy-Preserving Authentication in VANET, IEEE Access, 5, pp. 12014-12030, (2017); Sharma V., Vithalkar A., Hashmi M., Lightweight security protocol for chipless RFID in Internet of Things (IoT) applications, Proceedings of the 2018 10th International Conference on Communication Systems & Networks (COMSNETS), pp. 468-471, (2018); Tu Y., Piramuthu S., Lightweight non-distance-bounding means to address RFID relay attacks, Decis. Support Syst., 102, pp. 12-21, (2017); Whitmore A., Agarwal A., Da X.L., The internet of things: A survey of topics and trends, Inf. Syst. Front., 17, pp. 261-274, (2015); Wang J., Floerkemeier C., Sarma S.E., Session-based security enhancement of RFID systems for emerging open-loop applications, Pers. Ubiquitous Comput., 18, pp. 1881-1891, (2014); Zhao S., Aggarwal A., Frost R., Bai X., A survey of applications of identity-based cryptography in mobile ad-hoc networks, IEEE Commun. Surv. Tutor., 14, pp. 380-400, (2012)","H.-C. Chen; Department of Computer Science and Information Engineering, Asia University, Taichung, 41354, Taiwan; email: cdma2000@asia.edu.tw",null,"MDPI AG",{"$nulls":5},1.9961073E7,null,null,null,"English","Energies","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85070539667"]
["Golant S.M.","Golant, Stephen M. (6701342037)",6.701342037E9,"Stop bashing the suburbs: Mobility limitations of older residents are less relevant as connectivity options expand",2019.0,"Journal of Aging Studies",50.0,null,100793.0,null,null,null,20.0,"10.1016/j.jaging.2019.100793","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85068750704&doi=10.1016%2fj.jaging.2019.100793&partnerID=40&md5=ce0cfab146285d7a1edabae88a76896c","Department of Geography, University of Florida,  Terrace, Gainesville, Florida, 32606, NW, United States","Golant S.M., Department of Geography, University of Florida,  Terrace, Gainesville, Florida, 32606, NW, United States","Most older persons (age 65 and over) in the United States occupy suburban residential areas. Distinguishing where the older population lives is important because critics argue that the built environments of their suburban communities make it difficult for them to age in place successfully, that is, to have healthy, independent, active, and enjoyable lives. They point to their low population and building densities, long distances separating their residences from services, amenities, and commercial areas, and few transit and walking options. Consequently, when the mobility limitations of older residents prevent them from safely driving their vehicles, they have difficulties reaching destinations outside their homes (mobility behaviors) to satisfy their discretionary and obligatory needs. This paper questions this suburban bashing. It argues that future cohorts of older people, especially women, will be more able to drive, cars will be technologically safer and easier to operate, and ride-sharing options will be more available. More suburbs will also have mixed-use and pedestrian-accessible built environments reducing the need for vehicular travel. Most importantly, the information, activities, goods, services, and care required by older people to age in place will be delivered to their dwellings. Home sharing, home care, internet connectivity, e-commerce, social media, smart homes, telemedicine and robotic technologies will make the mobility or out-of-home behaviors of older residents less necessary. The paper introduces the constructs of connectivity options and connectivity behaviors to encompass these expanded travel and in-home delivery strategies. These new ways of connecting with their environments will result in more self-reliant older persons who are less constrained by their mobility limitations. These conclusions offer insights for planners and policymakers seeking to make their suburban communities more age-friendly. They must keep pace with the changing ways that older people will access their environments if they are to improve the quality of their lives and help them to age in place successfully. © 2019 Elsevier Inc.","Age-friendly communities; Aging in place; Connectivity options; Mobility behaviors and limitations; Suburbs; Unmet travel needs","Aged; Aged, 80 and over; Female; Health Status; Home Care Services; Humans; Independent Living; Internet Access; Male; Mobility Limitation; Residence Characteristics; Suburban Population; Telemedicine; United States; Walking; aged; comparative study; demography; epidemiology; female; health status; home care; human; independent living; male; procedures; psychology; suburban population; telemedicine; United States; very elderly; walking; walking difficulty",{"$nulls":6},"Aaronson W.E., Zinn J.S., Rosko M.D., Structure, environment and strategic outcome: A study of Pennsylvania nursing homes, Health Services Management Research, 8, 1, pp. 23-37, (1995); Abdi J., Al-Hindawi A., Ng T., Vizcaychipi M.P., Scoping review on the use of socially assistive robot technology in elderly care, BMJ Open, 8, 2, (2018); Alsnih R., Hensher D.A., The mobility and accessibility expectations of seniors in an aging population, Transportation Research Part A: Policy and Practice, 37, 10, pp. 903-916, (2003); American Association of State Highway and Transportation Officials, Commuting in America, (2013); Baily L., Aging Americans: Stranded without options, (2004); Baker C.A., A connection for all ages: Enabling the benefits of high-speed internet access for older adults, (2013); (2017); Boyer R.H., Leland S., Cohousing for whom? 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H. A, Drivers and driver licensing, (2016); Van Cauwenberg J., Van Holle V., De Bourdeaudhuij I., Clarys P., Nasar J., Salmon J., Deforche B., Physical environmental factors that invite older adults to walk for transportation, Journal of Environmental Psychology, 38, pp. 94-103, (2014); Vanderbur M., Silverstein N.M., Community mobility and dementia, (2011); Vespa J., Historical living arrangements of older adults: 1967–2016, Working paper number SEHSD-WP2017–30, (2017); Webber S.C., Porter M.M., Menec V.H., Mobility in older adults: A comprehensive framework, The Gerontologist, 50, 4, pp. 443-450, (2010); World Health Organization, Global age-friendly cities: A guide, (2007)","S.M. Golant; Department of Geography, University of Florida, Florida,  Terrace, Gainesville, 32606, United States; email: golant@ufl.edu",null,"Elsevier Ltd",{"$nulls":5},8904065.0,null,null,3.1526491E7,"English","J. Aging Stud.","Article","Final",null,"Scopus","2-s2.0-85068750704"]
["Li M.; Shen L.; Huang G.Q.","Li, Ming (57196402801); Shen, L. (57202985842); Huang, George Q. (7403425048)","57196402801; 57202985842; 7403425048","Blockchain-enabled workflow operating system for logistics resources sharing in E-commerce logistics real estate service",2019.0,"Computers and Industrial Engineering",135.0,null,null,950.0,969.0,19.0,81.0,"10.1016/j.cie.2019.07.003","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85068447656&doi=10.1016%2fj.cie.2019.07.003&partnerID=40&md5=16675c4dfb0e2f9419c93ed62f9a85ed","School of Intelligent Systems Science and Engineering, Jinan University (Zhuhai Campus), Zhuhai, 519070, China; Institute of Physical Internet, Jinan University (Zhuhai Campus), Zhuhai, 519070, China; HKU-ZIRI Laboratory for Physical Internet, Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong","Li M., School of Intelligent Systems Science and Engineering, Jinan University (Zhuhai Campus), Zhuhai, 519070, China, Institute of Physical Internet, Jinan University (Zhuhai Campus), Zhuhai, 519070, China; Shen L., HKU-ZIRI Laboratory for Physical Internet, Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong; Huang G.Q., HKU-ZIRI Laboratory for Physical Internet, Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong","E-commerce logistics real estate (EcLRE) is on the rise with the rapid development of logistics industry and continuous prosperity of real estate. The profit model for EcLRE is moving towards offering professional logistics services instead of simple real estate leasing. As the attributes for real estate are definite and difficult to change, the improvement of logistics service becomes necessity for EcLRE service providers to gain competitiveness in the market. However, the heterogeneous requirements from different service demanders place great challenges for the EcLRE service providers. The most puzzled one is to prevent fragmentation of logistics resources to serve different demanders (customers). This phenomenon of resource fragmentation is aggravated by the implementation of demanders’ (customers’) own information technologies or management requirements. To achieve the central management of logistics resources to serve heterogeneous demanders becomes an imperative requirement for EcLRE service provider. Therefore, this paper proposed a blockchain-enabled workflow operating system (Bc-WfOS) to centrally share heterogeneous logistics resources with different customers. Three key innovative technologies are involved to empower Bc-WfOS. The first one is gateway technology introduced to realize the UPnP (Universal Plug and Play) management of heterogeneous logistics resources. Secondly, to effectively and efficiently coordinate logistics resources, a multi-dimensional workflow model is proposed with corresponding workflow operation mechanism to suit different business logic. Additionally, a resource blockchain is designed with the integration of blockchain technology with agent technology to guarantee the data reliability to provide accurate front-line resource execution data for different customers to conduct higher decision-makings. Aiming at verifying the proposed Bc-WfOS, a prototype system is also developed and implemented in laboratory environment for conducting experimental case studies based on a real-life case. © 2019","E-commerce logistics real estate service; Logistics resources sharing; Resource blockchain; Workflow operation","Blockchain; Decision making; Electronic commerce; Sales; GATEWAY technologies; Innovative technology; Laboratory environment; Logistics resources; Operation mechanism; Real estate; Universal plug and play; Workflow operation; Information management",{"$nulls":6},"Amjad A., Azam F., Anwar M.W., Butt W.H., Rashid M., Event-driven process chain for modeling and verification of business requirements–a systematic literature review, IEEE Access, 6, pp. 9027-9048, (2018); Cai H., Gu Y., Vasilakos A.V., Xu B., Zhou J., Model-driven development patterns for mobile services in cloud of things, IEEE Transactions on Cloud Computing, 6, 3, pp. 771-784, (2018); (2019); Chen L., Xu L., Shah N., Gao Z., Lu Y., Shi W., On security analysis of Proof-of-Elapsed-Time (PoET), International symposium on stabilization, safety, and security of distributed systems, pp. 282-297, (2017); Chen Q., Hsu M., Inter-enterprise collaborative business process management, Data engineering, 2001. 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Zhao Z., Zhang M., Yang C., Fang J., Huang G.Q., Distributed and collaborative proactive tandem location tracking of vehicle products for warehouse operations, Computers & Industrial Engineering, 125, pp. 637-648, (2018); Zisman M.D., Use of production systems for modeling asynchronous, concurrent processes, Pattern-directed inference systems, pp. 53-68, (1978); Zyskind G., Nathan O., Decentralizing privacy: Using blockchain to protect personal data, Security and Privacy Workshops (SPW), 2015 IEEE, pp. 180-184, (2015)","G.Q. Huang; HKU-ZIRI Lab for Physical Internet, Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong; email: gqhuang@hku.hk",null,"Elsevier Ltd",{"$nulls":5},3608352.0,null,"CINDD",null,"English","Comput Ind Eng","Article","Final",null,"Scopus","2-s2.0-85068447656"]
["Kitjacharoenchai P.; Ventresca M.; Moshref-Javadi M.; Lee S.; Tanchoco J.M.A.; Brunese P.A.","Kitjacharoenchai, Patchara (57205391393); Ventresca, Mario (21834723400); Moshref-Javadi, Mohammad (55911808200); Lee, Seokcheon (7601422142); Tanchoco, Jose M.A. (8444625000); Brunese, Patrick A. (24342926500)","57205391393; 21834723400; 55911808200; 7601422142; 8444625000; 24342926500","Multiple traveling salesman problem with drones: Mathematical model and heuristic approach",2019.0,"Computers and Industrial Engineering",129.0,null,null,14.0,30.0,16.0,199.0,"10.1016/j.cie.2019.01.020","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85059831827&doi=10.1016%2fj.cie.2019.01.020&partnerID=40&md5=a9e44d70c38935cb28b3abe7d5f21c10","School of Industrial Engineering, Purdue University, West Lafayette, IN, United States; Center for Transportation and Logistics, Massachusetts Institute of Technology, MA, United States","Kitjacharoenchai P., School of Industrial Engineering, Purdue University, West Lafayette, IN, United States; Ventresca M., School of Industrial Engineering, Purdue University, West Lafayette, IN, United States; Moshref-Javadi M., Center for Transportation and Logistics, Massachusetts Institute of Technology, MA, United States; Lee S., School of Industrial Engineering, Purdue University, West Lafayette, IN, United States; Tanchoco J.M.A., School of Industrial Engineering, Purdue University, West Lafayette, IN, United States; Brunese P.A., School of Industrial Engineering, Purdue University, West Lafayette, IN, United States","E-commerce and retail companies are seeking ways to cut delivery times and costs by exploring opportunities to use drones for making last mile delivery deliveries. This paper addresses the delivery concept of a truck-drone combination along with the idea of allowing autonomous drones to fly from delivery trucks, make deliveries, and fly to any available delivery truck nearby. We present a mixed integer programming (MIP) formulation that captures this scenario with the objective of minimizing the arrival time of both trucks and drones at the depot after completing the deliveries. A new algorithm based on insertion heuristics is also developed to solve large sized problems containing up to a hundred locations. Experiments are conducted to compare the MIP solutions with those obtained from different models with single truck, multiple truck and a single truck and drone system, as well as test the performance of the proposed algorithm. The numerical results demonstrate the potential operational gain when implementing the proposed drone delivery system compared to the conventional truck alone or single truck/drone delivery system. © 2019","Drone delivery; Heuristic; Optimization; Routing; Transportation; Unmanned aerial vehicles","Automobile testing; Automobiles; Heuristic methods; Integer programming; Optimization; Transportation; Traveling salesman problem; Trucks; Unmanned aerial vehicles (UAV); Delivery systems; Heuristic; Heuristic approach; Insertion heuristics; Mixed integer programming (MIP); Multiple traveling salesman problems; Numerical results; Routing; Drones",{"$nulls":6},"Adams E., (2017); Agatz N., Bouman P., Schmidt M., Optimization approaches for the traveling salesman problem with drone, Transportation Science, (2018); Arora K., Agarwal S., Tanwar R., Solving TSP using genetic algorithm and nearest neighbour algorithm and their comparison, International Journal of Scientific & Engineering Research, 7, 1, pp. 1014-1018, (2016); 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Campbell A.M., Vandenbussche D., Hermann W., Routing for relief efforts, Transportation Science, 42, 2, pp. 127-145, (2008); Carlsson J., Song S., (2017); Carter A.E., Ragsdale C.T., A new approach to solving the multiple traveling salesperson problem using genetic algorithms, European Journal of Operational Research, 175, 1, pp. 246-257, (2006); Daknama R., Kraus E., (2017); Desrochers M., Laporte G., Improvements and extensions to the Miller-Tucker-Zemlin subtour elimination constraints, Operations Research Letters, 10, 1, pp. 27-36, (1991); Dorling K., Heinrichs J., Messier G.G., Magierowski S., Vehicle routing problems for drone delivery, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 47, 1, pp. 70-85, (2017); Dorr L., Duquette A., (2016); Drexl M., Synchronization in vehicle routing—A survey of VRPs with multiple synchronization constraints, Transportation Science, 46, 3, pp. 297-316, (2012); Ferrandez S.M., Harbison T., Weber T., Sturges R., Rich R., Optimization of a truck-drone in tandem delivery network using k-means and genetic algorithm, Journal of Industrial Engineering and Management, 9, 2, (2016); 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Kivelevitch E.H., Cohen K., Kumar M., A binary programming solution to the min-max multiple-depots, multiple traveling salesman problem, AIAA Infotech@Aerospace (I@A) conference, (2013); Lee H., Chen Y., Gillai B., (2016); Li J., Sun Q., Zhou M., Dai X., A new multiple traveling salesman problem and its genetic algorithm-based solution, 2013 IEEE international conference on systems, man, and cybernetics, (2013); Lu Q., Dessouky M.M., A new insertion-based construction heuristic for solving the pickup and delivery problem with time windows, European Journal of Operational Research, 175, 2, pp. 672-687, (2006); Mathew N., Smith S.L., Waslander S.L., Planning paths for package delivery in heterogeneous multirobot teams, IEEE Transactions on Automation Science and Engineering, 12, 4, pp. 1298-1308, (2015); McFarland M., (2017); Meola A., (2016); Murray C.C., Chu A.G., The flying sidekick traveling salesman problem: Optimization of drone-assisted parcel delivery, Transportation Research Part C: Emerging Technologies, 54, pp. 86-109, (2015); Patil S., (2016); Perez S., Kolodny L., (2017); Poikonen S., Wang X., Golden B., The vehicle routing problem with drones: Extended models and connections, Networks, 70, 1, pp. 34-43, (2017); Ponza A., (2015); Rao B., Gopi A.G., Maione R., The societal impact of commercial drones, Technology in Society, 45, pp. 83-90, (2016); Reinelt G., TSPLIB—A traveling salesman problem library, ORSA Journal on Computing, 3, 4, pp. 376-384, (1991); Rose C., (2013); Sedighpour M., Yousefikhoshbakht M., Darani N., An effective genetic algorithm for solving the multiple traveling salesman problem, Journal of Optimization in Industrial Engineering, 8, pp. 73-79, (2011); Smith D., (2013); Ungerleider N., (2016); Vincent J., (2017); Wang X., Poikonen S., Golden B., The vehicle routing problem with drones: Several worst-case results, Optimization Letters, 11, 4, pp. 679-697, (2016); Zito D., Radocaj L., (2016)","P. Kitjacharoenchai; School of Industrial Engineering, Purdue University, West Lafayette, United States; email: pkitjach@purdue.edu",null,"Elsevier Ltd",{"$nulls":5},3608352.0,null,"CINDD",null,"English","Comput Ind Eng","Article","Final",null,"Scopus","2-s2.0-85059831827"]
["Xu Y.-Z.; Zhang J.-L.; Hua Y.; Wang L.-Y.","Xu, Yao-Zhi (57211351122); Zhang, Jian-Lin (36648271000); Hua, Ying (55272770900); Wang, Lin-Yue (57211357500)","57211351122; 36648271000; 55272770900; 57211357500","Dynamic credit risk evaluation method for e-commerce sellers based on a hybrid artificial intelligence model",2019.0,"Sustainability (Switzerland)",11.0,19.0,5521.0,null,null,null,22.0,"10.3390/su11195521","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85073589086&doi=10.3390%2fsu11195521&partnerID=40&md5=e826c392ace102b54beb0cab880f09f7","School of Information Technology and Management, University of International Business and Economics, Beijing, 100029, China; Alibaba Business School, Hangzhou Normal University, Hangzhou, 311121, China","Xu Y.-Z., School of Information Technology and Management, University of International Business and Economics, Beijing, 100029, China, Alibaba Business School, Hangzhou Normal University, Hangzhou, 311121, China; Zhang J.-L., Alibaba Business School, Hangzhou Normal University, Hangzhou, 311121, China; Hua Y., School of Information Technology and Management, University of International Business and Economics, Beijing, 100029, China; Wang L.-Y., School of Information Technology and Management, University of International Business and Economics, Beijing, 100029, China","Credit risk evaluation is important for e-commerce platforms, due to the uncertainty and transaction risk associated with buyers and sellers. Moreover, it is the key ingredient for the development of the e-commerce ecosystem and sustainability of the financial market. The main objective of this paper is to develop an effective and user-friendly system for seller credit risk evaluation. Three hybrid artificial intelligent models, including (1) decision tree-artificial neural network (ANN), (2) decision tree-logistic regression, and (3) decision tree-dynamic Bayesian network have been investigated. The models were trained using sellers credit cases from Taobao, which has 609 cases, and each case had 23 categorical and numerical attributes. The results suggest that the combination of decision tree-ANN provides the highest accuracy, which can promote healthy and fast transactions between buyers and sellers on the platforms. This model is regarded as a powerful tool that allows us to build an advanced credit risk evaluation system, and meet the requirements of the platform transaction mode to be dynamic and self-learning-which will ultimately contribute to the sustainable development of the e-commerce ecosystem. The empirical results can serve as a reference for e-commerce platforms promoting an optimum credit risk evaluation model to improve e-commerce transaction environment and for buyers and investors making decisions. © 2019 by the authors.","Artificial neural network; Decision tree; Dynamic credit risk evaluation; Hybrid artificial intelligent model","artificial intelligence; artificial nest; artificial neural network; decision analysis; decision making; financial crisis; financial market; risk assessment; sustainability; sustainable development",{"$nulls":4},"Federation for the Humanities and Social Sciences, (2018Z10)","Funding: The authors would like to thank Zhejiang Federation of Humanities and Social Sciences Circles (ZJFHSSC) of China for financially supporting this research under Contract No.2018Z10.","Beaver W.H., Financial Ratios as Predictors of Failure, J. Account. 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Res., 52, pp. 317-324, (2018); Zhao-Quan C., Guang-Cai C., Li-Ning X., Jing-Hui Y., Xu T., Evaluating hedge fund downside risk using a multi-objective neural network, J. Vis. Commun. Image. R., 59, pp. 433-438, (2019); Madjia T., Amir-Reza A., Debora D.C., Maryam P., An artificial neural network and Bayesian network model for liquidity risk assessment in banking, Neurocomputing, 275, pp. 2525-2554, (2018); Banachewicz K., Lucas A., Van-Der-Vaart A., Modelling Portfolio Defaults Using Hidden Markov Models with Covariates, Economet. J., 11, pp. 155-171, (2008); Murphy K.P., Dynamic Bayesian Networks: Representation, (2002); Morgan J.N., Sonquist J.A., Problems in the analysis of survey data, and a proposal, J. Am. Stat. Assoc., 58, pp. 415-434, (1963); Quinlan J., Discovering Rules form Large Collections of Examples: A Case Study, (1979); Quinlan J.R., C4.5: Programs for Machine Learning, (1993); Yang S.G., Zhu Q., Cheng C., Construction of Personal Credit Assessment Portfolio Model Based on Decision Tree-Neural Network, Fin. Forum., 18, pp. 57-61, (2013); Hai-Feng L., Yue-Jin Z., Ning Z., Evaluating the well-qualified borrowers from PaiPaiDai, Inform. Technol. Quant. Manag., 122, pp. 775-779, (2017)","Y. Hua; School of Information Technology and Management, University of International Business and Economics, Beijing, 100029, China; email: huaying@uibe.edu.cn",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85073589086"]
["Saunila M.; Ukko J.; Sore S.; Rantala T.; Nasiri M.","Saunila, Minna (37013922700); Ukko, Juhani (23502292000); Sore, Sariseelia (57015686400); Rantala, Tero (56469104200); Nasiri, Mina (57200529414)","37013922700; 23502292000; 57015686400; 56469104200; 57200529414","Managing buyer-supplier relationships in e-commerce projects: implications for relationship value",2019.0,"Supply Chain Forum",20.0,4.0,null,299.0,309.0,10.0,8.0,"10.1080/16258312.2019.1672505","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85074046076&doi=10.1080%2f16258312.2019.1672505&partnerID=40&md5=73960e3fa0e438ec1b72d4321cd67d91","School of Engineering Science, Department of Industrial Engineering and Management, LUT University, Lahti, Finland; Faculty of Business and Hospitality Management, Lahti University of Applied Sciences, Lahti, Finland","Saunila M., School of Engineering Science, Department of Industrial Engineering and Management, LUT University, Lahti, Finland; Ukko J., School of Engineering Science, Department of Industrial Engineering and Management, LUT University, Lahti, Finland; Sore S., Faculty of Business and Hospitality Management, Lahti University of Applied Sciences, Lahti, Finland; Rantala T., School of Engineering Science, Department of Industrial Engineering and Management, LUT University, Lahti, Finland; Nasiri M., School of Engineering Science, Department of Industrial Engineering and Management, LUT University, Lahti, Finland","This study investigates which e-commerce characteristics contribute to supplier relationship value in e-commerce projects. Further, it is examined if such contributions are moderated by the intensity of the buyer-supplier relationship. The hypotheses were developed based on previous research on e-commerce characteristics and buyer-supplier relationship intensity to test the links between e-commerce characteristics, buyer-supplier relationship intensity, and supplier relationship value. Using a structured online survey questionnaire, the data were collected from Finnish e-commerce companies, which had supplied an e-shop, and they were asked to evaluate the purchasing process of the shop as an example of an e-commerce project. The results suggest that one of the dimensions of e-commerce characteristics (service delivery characteristics) positively contributes to the supplier relationship value, whereas the other two dimensions (product characteristics and buyer operations) do not. Further, as the intensity of the buyer-supplier relationship increases, the strength of the connections between product characteristics and supplier relationship value and between buyer operations and supplier relationship value increases. This study could provide useful insights for supply chain managers by informing suppliers about which e-commerce characteristics are likely to influence supplier relationship value. © 2019, © 2019 Kedge Business School.","buyer-supplier relationships; digital service; digital supply chain; E-commerce; relationship intensity; Relationship value; supply chain",{"$nulls":7},"Armstrong J.S., Overton T.S., Estimating Nonresponse Bias in Mail Surveys, Journal of Marketing Research, pp. 396-402, (1977); Autry C.W., Golicic S.L., Evaluating Buyer–Supplier Relationship–Performance Spirals: A Longitudinal Study, Journal of Operations Management, 28, 2, pp. 87-100, (2010); Barlett J.E., Kotrlik J.W., Higgins C.C., Organizational Research: Determining Appropriate Sample Size in Survey Research. Information Technology, Learning, and Performance Journal, 19, 1, pp. 43-50, (2001); Bergkvist L., Rossiter J.R., The Predictive Validity of Multiple-item versus Single-item Measures of the Same Constructs, Journal of Marketing Research, 44, 2, pp. 175-184, (2007); Boyer K.K., Hallowell R., Roth A.V., E-services: Operating Strategy—A Case Study and a Method for Analyzing Operational Benefits, Journal of Operations Management, 20, 2, pp. 175-188, (2002); Brito C., Nogueira M., Capabilities Exchange through Business Interaction: An Empirical Investigation of a client–IT Supplier Relationship, Journal of Purchasing and Supply Management, 15, 4, pp. 227-239, (2009); Cheung M.S., Myers M.B., Mentzer J.T., Does Relationship Learning Lead to Relationship Value? A Cross-national Supply Chain Investigation, Journal of Operations Management, 28, 6, pp. 472-487, (2010); Craighead C.W., Ketchen D.J., Dunn K.S., Hult G.T.M., Addressing Common Method Variance: Guidelines for Survey Research on Information Technology, Operations, and Supply Chain Management, IEEE Transactions on Engineering Management, 58, 3, pp. 578-588, (2011); Dawes S.S., (2007); Diamantopoulos A., Sarstedt M., Fuchs C., Wilczynski P., Kaiser S., Guidelines for Choosing between Multi-item and Single-item Scales for Construct Measurement: a Predictive Validity Perspective, Journal of the Academy of Marketing Science, 40, 3, pp. 434-449, (2012); Drolet A.L., Morrison D.G., Do We Really Need Multiple-item Measures in Service Research?, Journal of Service Research, 3, 3, pp. 196-204, (2001); Fedi L., Lavissiere A., Russell D., Swanson D., The Facilitating Role of IT Systems for Legal Compliance: The Case of Port Community Systems and Container Verified Gross Mass (VGM), In Supply Chain Forum: An International Journal, 20, 1, pp. 29-42, (2019); 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A Comparison of Single-item and Multi-item Measures, Die Betriebswirtschaft, 69, 2, (2009); Saunila M., Ukko J., Rantala T., Value Co-creation through Digital Service Capabilities: The Role of Human Factors, Information Technology & People, 32, 3, pp. 627-645, (2019); So S., Sun H., Supplier integration strategy for lean manufacturing adoption in electronic‐enabled supply chains, Supply Chain Management: An International Journal, 15, 6, pp. 474-487, (2010); Su Q., Li Z., Song Y.T., Chen T., Conceptualizing Consumers’ Perceptions of E-commerce Quality, International Journal of Retail & Distribution Management, 36, 5, pp. 360-374, (2008); Tsai J.Y., Raghu T.S., Shao B.B., Information Systems and Technology Sourcing Strategies of e-Retailers for Value Chain Enablement, Journal of Operations Management, 31, 6, pp. 345-362, (2013); Ukko J., Saunila M., Understanding the Practice of Performance Measurement in Industrial Collaboration: From Design to Implementation, Journal of Purchasing and Supply Management, (2019); Weele A.J., Raaij E.M., The Future of Purchasing and Supply Management Research: About Relevance and Rigor, Journal of Supply Chain Management, 50, 1, pp. 56-72, (2014); Woodruff R.B., Customer Value: The Next Source for Competitive Advantage, Journal of the Academy of Marketing Science, 25, 2, pp. 139-153, (1997); Yoo B., Donthu N., Developing a Scale to Measure the Perceived Quality of an Internet Shopping Site (SITEQUAL), Quarterly Journal of Electronic Commerce, 2, 1, pp. 31-45, (2001); Zeithaml V.A., Parasuraman A., Malhotra A., Service Quality Delivery through Web Sites: A Critical Review of Extant Knowledge, Journal of the Academy of Marketing Science, 30, 4, pp. 362-375, (2002)","M. Saunila; LUT University, Lahti, Finland; email: minna.saunila@lut.fi",null,"Taylor and Francis Ltd.",{"$nulls":5},1.6258312E7,null,null,null,"English","Supply Chain Forum","Article","Final",null,"Scopus","2-s2.0-85074046076"]
["Liu X.; Liu W.; Liu T.; Sun H.","Liu, Xinying (58386241900); Liu, Wei (56796002400); Liu, Taian (35620603700); Sun, Hongwei (57217824477)","58386241900; 56796002400; 35620603700; 57217824477","The Ant Colony Algorithm Based on Logic Time Petri Nets and Application in Electronic-Commerce Logistics",2019.0,"IEEE Access",7.0,null,8908703.0,169011.0,169017.0,6.0,5.0,"10.1109/ACCESS.2019.2954986","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85077789340&doi=10.1109%2fACCESS.2019.2954986&partnerID=40&md5=3a683243cb3ee7f259d1c5b5d6d1b69c","College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, 266590, China; Department of Information Engineering, Shandong University of Science and Technology, Tai'an, 271019, China; College of Computer Science and Engineering, Weifang University of Science and Technology, Weifang, 262700, China","Liu X., College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, 266590, China, Department of Information Engineering, Shandong University of Science and Technology, Tai'an, 271019, China; Liu W., College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, 266590, China; Liu T., Department of Information Engineering, Shandong University of Science and Technology, Tai'an, 271019, China; Sun H., College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, 266590, China, College of Computer Science and Engineering, Weifang University of Science and Technology, Weifang, 262700, China","Based on Logic Time Petri nets (LTPNs) models, this paper focuses on improving the efficiency of Petri Net intelligent search method execution. With an analysis of the E-Commerce Logistics (ECL) system, the method of system scheduling using LTPNs is studied, and the Ant Colony algorithm is proposed based on it. By introducing the concept of pheromones to system transition, using the Ant Colony algorithm (ACA) in the processing of the network, and setting the heuristic factor in combination with the time boundary, the non-deterministic behavior can be automatically analyzed and selected in the LTPNs so that the efficiency of control and scheduling during the system dynamics operation is improved. The result of the analysis of the ECL system serves as evidence of the superiority of ACA. © 2019 IEEE.","Ant colony optimization; electronic-commerce logistics; logic time Petri nets","Computer circuits; Efficiency; Electronic commerce; Petri nets; Scheduling; Ant colony algorithms; Deterministic behavior; Intelligent search; Logic time; System Dynamics; System scheduling; System transitions; Ant colony optimization",{"$nulls":4},"Department of Science and Technology of Shandong Province, (J17KA023)","This work was supported by the Shandong Province Higher Educational Science and Technology Program under Grant J17KA023.","Zhu Z., Modeling of intelligent E-commerce logistics service system based on object-oriented time Petri nets, CAAI Trans. Intell. Syst., 13, pp. 303-313, (2018); Wang Y.Y., Du Y.Y., Conformance checking based on extended footprint matrix, J. Shandong Univ. Sci. 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Netw., Sens., Control, pp. 1-6, (2016); Du Y., Qi L., Zhou M., Analysis and application of logical Petri nets to E-commerce systems, IEEE Trans. Syst., Man, Cybern., Syst., 44, 4, pp. 468-481, (2014); Qi L., Zhou M., Luan W., An emergency traf-c light strategy to prevent traf-c congestion, Proc IEEE Int. Conf. Netw, Sens., Control (ICNSC), pp. 1-6, (2016); Du Y., Jiang C., On the design and temporal Petri net veri-ca-tion of grid commerce architecture, Chin. J. Electron., 17, 2, pp. 247-251, (2008); Du Y.Y., Jiang C.J., Zhou M.C., Modeling and analysis of real-time cooperative systems using Petri nets, IEEE Trans. Syst., Man, Cybern. A, Syst. Humans, 37, 5, pp. 643-654, (2007); Du Y., Jiang C., Zhou M., A Petri-net-based correctness analysis of Internet stock trading systems, IEEE Trans. Syst., Man, Cybern. C, Appl. Rev., 38, 1, pp. 93-99, (2008); Du Y., Jiang C., Zhou M., A Petri net-based model for veri-cation of obligations and accountability in cooperative systems, IEEE Trans. Syst., Man, Cybern. A, Syst. Humans, 39, 2, pp. 299-308, (2009); Qi H., Du Y., Liu W., Process model repairing method based on reachable markings, J. Shandong Univ. Sci. Technol., Nature Sci., 36, 1, pp. 118-124, (2017); Huang A.-C., Fu L.-C., Lin M.-H., Lin S.-Y., Modeling, scheduling, and prediction for wafer fabrication: Queueing colored Petri-net and GA based approach, Proc IEEE Int. Conf. Robot. Automat., pp. 3187-3192, (2002); Gang X., Wu Z., Deadlock-free scheduling method using Petri net model analysis andGAsearch, Proc. Int. Conf. Control Appl., 2, pp. 1153-1158, (2002); Liu W., Du Y., Modeling multimedia synchronization using Petri nets, Inf. Technol. J., 8, 7, pp. 1054-1058, (2009)","W. Liu; College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, 266590, China; email: liuwei_doctor@yeah.net",null,"Institute of Electrical and Electronics Engineers Inc.",{"$nulls":5},2.1693536E7,null,null,null,"English","IEEE Access","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85077789340"]
["Chu Z.; Yu P.","Chu, Zhipeng (57207828950); Yu, Ping (57207825715)","57207828950; 57207825715","Innovation of E-commerce terminal express cooperative distribution based on big data platform",2019.0,"International Journal of Performability Engineering",15.0,3.0,null,977.0,986.0,9.0,3.0,"10.23940/ijpe.19.03.p27.977986","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85063006885&doi=10.23940%2fijpe.19.03.p27.977986&partnerID=40&md5=91ec2bfda09a0c927ba63e02c6ccb2dd","Ningbo Institute of Finance and Economics, Ningbo, 315175, China; School of Electrical Engineering and Information Technology, Changchun Institute of Technology, Changchun, 130012, China","Chu Z., Ningbo Institute of Finance and Economics, Ningbo, 315175, China; Yu P., School of Electrical Engineering and Information Technology, Changchun Institute of Technology, Changchun, 130012, China","In order to strengthen the logistics distribution ability at the end of e-commerce, it is necessary to study the co-delivery collaborative delivery method of e-commerce. When the current delivery method is used to deliver the courier at the end of the e-commerce, the distribution takes a long time to meet the distribution requirements of the user, and there is a problem of low distribution efficiency and low customer satisfaction. On the basis of the big data platform, an e-commerce end express co-delivery distribution method is proposed. By calculating the inventory cost, fixed investment cost, storage cost and operation cost, the total cost of the distribution center is coordinated, and the lowest total cost is selected as the distribution center. The distribution time range is analyzed by the concept of time window to obtain a penalty function. According to the penalty function, the path optimization model of e-commerce end express delivery is established. According to the path optimization model, the optimal route of collaborative delivery is obtained, and the coordinated delivery of the e-commerce end express is completed. The experimental results show that the proposed method has high distribution efficiency and high customer satisfaction. © 2019 Totem Publisher, Inc. All rights reserved.","Big data platform; Collaborative distribution; E-commerce; Path optimization","Costs; Customer satisfaction; Digital storage; Efficiency; Electronic commerce; Optimization; Sales; Warehouses; Big data platform; Co deliveries; Collaborative distribution; Customers' satisfaction; Data platform; Delivery methods; Distribution centres; Distribution efficiency; E- commerces; Path optimizations; Big data",{"$nulls":6},"Xie L., Zhou W., Li Y., Application of improved recommendation system based on spark platform in big data analysis, Cybernetics and Information Technologies, 16, pp. 245-255, (2016); Roesener A.G., Barnes J.W., An advanced tabu search approach to the dynamic airlift loading problem, Logistics Research, 9, (2016); Zhu F., Ukkusuri S.V., A linear programming formulation for autonomous intersection control within a dynamic traffic assignment and connected vehicle environment, Transportation Research Part C: Emerging Technologies, 55, pp. 363-378, (2015); Sun M., Pang D., Vehicle routing optimisation algorithm for agricultural products logistics distribution, International Journal of Applied Decision Sciences, 10, pp. 327-334, (2017); Li C.B., Wang E.J., Yuan J.B., Research on the optimization of logistics distribution route of fresh agricultural produce under internet of things, Commercial Research, 4, (2017); Liu S., Fu W., Zhao W., Zhou J., Li Q., A novel fusion method by static and moving facial capture, Mathematical Problems in Engineering, 2013, (2013); Jeong S., Simeone O., Kang J., Mobile edge computing via a UAV-mounted cloudlet: Optimization of bit allocation and path planning, IEEE Transactions on Vehicular Technology, 67, pp. 2049-2063, (2018); Caputa P., Kundu N., Miyaji M., Takayanagi T., Watanabe K., Anti-de sitter space from optimization of path integrals in conformal field theories, Physical Review Letters, 119, (2017); Haddad O.B., Ashofteh P.S., Marino M.A., Levee layouts and design optimization in protection of flood areas, Journal of Irrigation and Drainage Engineering, 141, (2015); Chau C.K., Elbassioni K., Tseng C.M., Drive mode optimization and path planning for plug-in hybrid electric vehicles, IEEE Transactions on Intelligent Transportation Systems, 18, pp. 3421-3432, (2017); Yang G., Liu S., Distributed cooperative algorithm for k-m set with negative integer K by fractal symmetrical property, International Journal of Distributed Sensor Networks, 10, (2014); Berger J., Lo N., Barkaoui M., Static target search path planning optimization with heterogeneous agents, Annals of Operations Research, 244, pp. 295-312, (2016); Kungurtsev V., Jaschke J., A predictor-corrector path-following algorithm for dual-degenerate parametric optimization problems, SIAM Journal on Optimization, 27, pp. 538-564, (2017); Tzoreff E., Weiss A.J., Single sensor path design for best emitter localization via convex optimization, IEEE Transactions on Wireless Communications, 16, pp. 939-951, (2017); Pan Z., Liu S., Fu W., A review of visual moving target tracking, Multimedia Tools & Applications, 76, pp. 16989-17018, (2017); He X., Zhou Y., Chen Z., An evolution path based reproduction operator for many-objective optimization, IEEE Transactions on Evolutionary Computation, 23, 1, pp. 29-43, (2017)","P. Yu; School of Electrical Engineering and Information Technology, Changchun Institute of Technology, Changchun, 130012, China; email: 25280480@qq.com",null,"Totem Publishers Ltd",{"$nulls":5},9731318.0,null,null,null,"English","Int. J. Perform. Eng.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85063006885"]
["Davidavičienė V.; Davidavičius S.; Kaušinis J.","Davidavičienė, Vida (35368051300); Davidavičius, Sigitas (56418398000); Kaušinis, Justinas (57208029501)","35368051300; 56418398000; 57208029501","Consumer dissatisfaction structure - e-logistic perspective: Lithuania case",2019.0,"International Journal of Learning and Change",11.0,3.0,null,237.0,251.0,14.0,3.0,"10.1504/IJLC.2019.103328","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85074590723&doi=10.1504%2fIJLC.2019.103328&partnerID=40&md5=d2c8262865e7933fb2b489c40e3396c7","Department of Business Technologies and Entrepreneurship, Vilnius Gediminas Technical University, Vilnius, 10223, Lithuania; Department of Management, Vilnius Gediminas Technical University, Vilnius, 10223, Lithuania","Davidavičienė V., Department of Business Technologies and Entrepreneurship, Vilnius Gediminas Technical University, Vilnius, 10223, Lithuania; Davidavičius S., Department of Management, Vilnius Gediminas Technical University, Vilnius, 10223, Lithuania; Kaušinis J., Department of Business Technologies and Entrepreneurship, Vilnius Gediminas Technical University, Vilnius, 10223, Lithuania","With the growth of e-commerce, most of the shippers, especially multi-channel shippers, are just starting to develop their own distribution network infrastructure. Since year 2000, e-commerce started to expand rapidly with the 'pure-play' (online only) retailers, which enabled establishing of e-fulfilment distribution networks. Certain products specific brings additional challenges for e-commerce and e-supply chain. In this article, the consumer perception and understanding of e-logistic services and quality of these services in e-commerce satisfaction or dissatisfaction structure of Lithuania consumers will be analysed, not taking into account specifics of certain products. Methods of comparative analysis, questionnaire, and statistical data analysis will be employed. Copyright © 2019 Inderscience Enterprises Ltd.","Consumer behaviour; E-commerce; E-logistic; ICT development; Lithuania case",{"$nulls":7},"Aghaei S., Nematbakhsh M.A., Farsani H.K., Evolution of the world wide web: From Web 1.0 to Web 4.0, International Journal of Web & Semantic Technology (IJWesT), 3, 1, pp. 1-10, (2012); Asadabadi M.R., A Markovian-QFD approach in addressing the changing priorities of the customer needs, International Journal of Quality & Reliability Management, 33, 8, pp. 1062-1075, (2016); Bachhuber M.A., Cunningham C., Cunningham, availability of Buprenorphine on the internet for purchase without a prescription, Drug and Alcohol Dependence, 130, 1-3, pp. 238-240, (2013); Bancroft A., Scott P., Reid F.F., Concepts of illicit drug quality among darknet market users: Purity, embodied experience, craft and chemical knowledge, International Journal of Drug Policy, 35, pp. 42-49, (2016); Banyte J., Tarute A., Taujanskyte I., Customer engagement into value creation: Determining factors and relations with loyalty, Engineering Economics, 25, 5, pp. 568-577, (2014); Barnes S.J., Pressey A.D., Who needs cyberspace? 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Some evidence for the hierarchy of needs, Journal of Evolutionary Economics, 22, 4, pp. 649-676, (2012); Chang Y.P., Dong X.B., Sun W., Influence of characteristics of the internet of things on consumer purchase intention, Social Behavior and Personality: An International Journal, 42, 2, pp. 321-330, (2014); Chatzithomas N., Boutsouki C., Hatzithomas L., Zotos Y., Social media advertising platforms: A cross-cultural study, International Journal of Strategic Innovative Marketing, 1, 2, (2014); Chen H., Et al., Exploring the commercial value of social networks, Journal of Enterprise Information Management, 27, 5, pp. 576-598, (2014); Cheung C.M.K., Et al., Online consumer behavior: A review and agenda for future research, 16th Bled eCommerce Conference, eTransformation, Bled, (2003); Choudhury N., World wide web and its journey from Web 1.0 to Web 4.0, International Journal of Computer Science and Information Technologies, 5, 6, pp. 8096-8100, (2014); Claudy M.C., Garcia R., O'Driscoll A., Consumer resistance to innovation - A behavioral reasoning perspective, Journal of the Academy of Marketing Science, 43, 4, pp. 528-544, (2015); Culnan M.J., McHugh P.J., Zubillaga J.I., How large US companies can use Twitter and other social media to gain business value, MIS Quarterly Executive, 9, 4, pp. 243-259, (2010); Davidaviciene V., Measuring quality of e-commerce web sites, Economics & Management, 16, pp. 723-729, (2011); Davidaviciene V., Pabedinskaite A., Davidavicius S., Social networks in B2B and b2c communication, Transformations in Business and Economics, 16, 1, pp. 69-84, (2017); Davidaviciene V., Sabaityte J., Davidavicius S., Features of food industry on the internet: A case of Lithuania, Challenges for International Business in Central and Eastern Europe, pp. 197-209, (2017); Dhir A., Chen S., Nieminen M., Predicting adolescent internet addiction: The roles of demographics, technology accessibility, unwillingness to communicate and sought internet gratifications, Computers in Human Behavior, 51, pp. 24-33, (2015); Erdogmus I.E., Tatar S.B., Science direct drivers of social commerce through brand engagement, Procedia - Social and Behavioral Sciences, 207, pp. 189-195, (2015); Guidry J.P.D., Waters R.D., Saxton G.D., Moving social marketing beyond personal change to social change, Journal of Social Marketing, 4, 3, pp. 240-260, (2014); Hadlington L.J., Cognitive failures in daily life: Exploring the link with internet addiction and problematic mobile phone use, Computers in Human Behavior, 51, pp. 75-81, (2015); Hall A., Zwarun L., Challenging entertainment: Enjoyment, transportation, and need for cognition in relation to fictional films viewed online, Mass Communication and Society, 15, 3, pp. 384-406, (2012); Heidenreich S., Kraemer T., Handrich M., Satisfied and unwilling: Exploring cognitive and situational resistance to innovations, Journal of Business Research, 69, 7, pp. 2440-2447, (2016); Hodson H., Silk road bust hints at FBI's new cybercrime powers, New Scientist, 220, 2938, (2013); Hsu C.-L., Lin J.C.-C., An empirical examination of consumer adoption of internet of things services: Network externalities and concern for information privacy perspectives, Computers in Human Behavior, 62, 100, pp. 516-527, (2016); Jackson L.A., Wang J.-L., Cultural differences in social networking site use: A comparative study of China and the United States, Computers in Human Behavior, 29, 3, pp. 910-921, (2013); Jacobsson M., Wilson T.L., Partnering hierarchy of needs, Management Decision, 52, 10, pp. 1907-1927, (2014); Kirk K., Abrahams A.S., Evaluating public charity websites, Nonprofit Management and Leadership, 27, 4, pp. 475-491, (2017); Knezevic B., Davidaviciene V., Skrobot P., Social networks as a communication tool in social supermarkets, SOTICS 2017, the Seventh International Conference on Social Media Technologies, Communication, and Informatics, pp. 5-10, (2017); Lantos G.P., Consumer Behavior in Action: Real-Life Applications for Marketing Managers, (2010); Laudon K.C., Traver C.G., E-Commerce 2016: Business, Technology, (2016); Laukkanen T., Consumer adoption versus rejection decisions in seemingly similar service innovations: The case of the internet and mobile banking, Journal of Business Research, 69, 7, pp. 2432-2439, (2016); Lee M., Roux D., Cherrier H., Cova B., Anti-consumption and consumer resistance: Concepts, concerns, conflicts, and convergence, European Journal of Marketing, 45, 11-12, pp. 1680-1687, (2011); Lester D., Measuring Maslow's hierarchy of needs, Psychological Reports, 113, 1, pp. 15-17, (2013); Levina O., Vilnai-Yavetz I., E-visibility maturity model: A tool for assessment and comparison of individual firms and sets of firms in e-business, Electronic Commerce Research and Applications, 14, 6, pp. 480-498, (2015); Mani Z., Chouk I., Drivers of consumers' resistance to smart products, Journal of Marketing Management, 33, 1-2, pp. 76-97, (2017); Manuputty A., Noor S.M., Sumardi J., Cyber security: Rule of use internet safely?, Procedia - Social and Behavioral Sciences, 103, pp. 255-261, (2013); McCrindl M., Generations Defined, (2014); Technology, media, and telecom practice, Offline and Falling Behind: Barriers to Internet Adoption, (2014); Moreira A.C., Fortes N., Santiago R., Influence of sensory stimuli on brand experience, brand equity and purchase intention, Journal of Business Economics and Management, 18, 1, pp. 68-83, (2017); Moreno F.C., Et al., The role of perceived value and emotions in the satisfaction and future intentions of spectators, Engineering Economics, 27, 2, pp. 221-229, (2016); Population and Its Composition, (2017); Powers T., Et al., Digital and social media in the purchase decision process, Journal of Advertising Research, 52, 4, pp. 479-489, (2012); Racherla P., Friske W., Perceived Â€usefulnessâTM of online consumer reviews: An exploratory investigation across three services categories, Electronic Commerce Research and Applications, 11, 6, pp. 548-559, (2012); Reinecke L., Vorderer P., Knop K., Entertainment 2.0? The role of intrinsic and extrinsic need satisfaction for the enjoyment of Facebook use, Journal of Communication, 64, 3, pp. 417-438, (2014); Rhumorbarbe D., Et al., Buying drugs on a darknet market: A better deal? Studying the online illicit drug market through the analysis of digital, physical and chemical data, Forensic Science International, 267, pp. 173-182, (2016); San Y.W., Yazdanifard R., How consumer decision making process differ from youngster to older consumer generation, Journal of Research in Marketing, 2, 2, pp. 151-156, (2014); Saridakis G., Benson V., Ezingeard J.-N., Tennakoon H., Individual information security, user behaviour and cyber victimisation: An empirical study of social networking users, Technological Forecasting and Social Change, 102, pp. 320-330, (2015); E-Commerce - Europe Statista Market Forecast, (2017); Taormina R.J., Gao J.H., Maslow and the motivation hierarchy: Measuring satisfaction of the needs, American Journal of Psychology, 126, 2, pp. 155-177, (2013); Taylor D.G., Strutton D., Has e-marketing come of age? Modeling historical influences on post-adoption era internet consumer behaviors, Journal of Business Research, 63, 9-10, pp. 950-956, (2010); Turban E., Strauss J., Lai L., Social Commerce - Marketing, Technology and Management, (2016); Vande P.D., Verhelst M., Cyber crime: Can a standard risk analysis help in the challenges facing business continuity managers?, Journal of Business Continuity & Emergency Planning, 7, 2, pp. 126-137, (2013); Wang H., Kim K.H., Ko E., Liu H., Relationship between service quality and customer equity in traditional markets, Journal of Business Research, 69, 9, pp. 3827-3834, (2016); Xu K., Wang F., Jia X., Secure the internet, one home at a time, Security and Communication Networks, 9, 16, pp. 3821-3832, (2016)","V. Davidavičienė; Department of Business Technologies and Entrepreneurship, Vilnius Gediminas Technical University, Vilnius, 10223, Lithuania; email: vida.davidaviciene@vgtu.lt",null,"Inderscience Publishers",{"$nulls":5},1.7402875E7,null,null,null,"English","Int. J. Learn. Chang.","Article","Final",null,"Scopus","2-s2.0-85074590723"]
["Kedia A.; Kusumastuti D.; Nicholson A.","Kedia, Ashu (57207513712); Kusumastuti, Diana (35848438800); Nicholson, Alan (7201890701)","57207513712; 35848438800; 7201890701","Establishing collection and delivery points to encourage the use of active transport: A case study in New Zealand using a consumer-centric approach",2019.0,"Sustainability (Switzerland)",11.0,22.0,6255.0,null,null,null,24.0,"10.3390/su11226255","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85075894517&doi=10.3390%2fsu11226255&partnerID=40&md5=b26fd945392dadfb4cb858891c937372","Department of Civil and Natural Resources Engineering, University of Canterbury, Christchurch, 8041, New Zealand","Kedia A., Department of Civil and Natural Resources Engineering, University of Canterbury, Christchurch, 8041, New Zealand; Kusumastuti D., Department of Civil and Natural Resources Engineering, University of Canterbury, Christchurch, 8041, New Zealand; Nicholson A., Department of Civil and Natural Resources Engineering, University of Canterbury, Christchurch, 8041, New Zealand","The current and projected trends of growth in online shopping might change the activity and travel patterns in Christchurch, one of the largest cities in New Zealand. Online shopping might reduce consumers' shopping trips, but it has substantially increased courier companies' trips to deliver parcels to the end-consumers because a considerable proportion of parcels are often required to be redelivered due to consumers not being at home during the first delivery attempt. This also adds to the operational cost of courier companies and adverse traffic impacts. To mitigate these issues, collection-and-delivery points (CDPs) have recently been introduced in New Zealand on a trial basis. This study aims to identify the optimal density and locations for establishing CDPs in Christchurch using a modified p-median location-allocation (LA) model. A consumer-centric approach to locating CDPs has been adopted by considering the socio-demographic characteristics of Christchurch's residents and the distances to/from CDPs. Non-traditional CDP locations (e.g., supermarkets and dairies) were considered as potential candidate facilities and were found to be more suitable as CDPs than traditional post shops. Based on consumers' shopping pattern, supermarkets appeared to be the most frequently visited and preferred type of facility to be used as CDPs. However, the results of the LA analyses show that dairies are the most accessible locations, and CDPs at dairies located within two kilometres will encourage consumers to walk and cycle to receive their parcels from CDPs. The results suggest the optimal location configuration for each type of facility considered, based on their spatial distribution in the city. © 2019 by the authors.","Collection and delivery points; Last-mile travel; Location-allocation model; New Zealand; Online shopping","Christchurch [Canterbury]; consumption behavior; cost analysis; demographic trend; operations technology; p-median; shopping activity; spatial distribution; World Wide Web",{"$nulls":4},"University of Canterbury, UC","Funding: This research received no external funding. The APC was funded by University of Canterbury.","Schewel L.B., Schipper L.J., Shop 'TillWe Drop: A Historical and Policy Analysis of Retail Goods Movement in the United States, Environ. Sci. Technol, 46, pp. 9813-9821, (2012); Cherrett T., Dickinson J., McLeod F., Sit J., Bailey G., Whittle G., Logistics impacts of student online shopping-Evaluating delivery consolidation to halls of residence, Transport. Res. 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Pract, 51, pp. 56-62, (2013); O'Brien M., EBay Shuts Down Same-Day Delivery Pilots, (2015); Bates O., Friday A., Allen J., Cherrett T., McLeod F., Bektas T., Nguyen T., Piecyk M., Piotrowska M., Wise S., Et al., Transforming Last-mile Logistics: Opportunities for More Sustainable Deliveries, Proceedings of the CHI Conference on Human Factors in Computing Systems, pp. 1-14, (2018); Gevaers R., Van de Voorde E., Vanelslander T., Characteristics and typology of last-mile logistics from an innovation perspective in an urban context, City Distrib. Urban Freight. Transp: Multipl. Perspect, pp. 56-71, (2011); Onghena E., Integrators: werkwijze, strategieën, (2008); Wang X., Zhan L., Ruan J., Zhang J., How to choose 'last mile' delivery modes for E-fulfillment, Math. Probl. Eng, 2014, pp. 1-11, (2014); Harris I., Mumford C.L., Naim M.M., A hybrid multi-objective approach to capacitated facility location with flexible store allocation for green logistics modeling, Transport. Res. Pt. E: Log. Transport. Rev, 66, pp. 1-22, (2014); Government Policy Statement on Land Transport, (2018); New Zealand Vehicle Fleet Statistics, (2015); Kin B., Verlinde S., Macharis C., Sustainable urban freight transport in megacities in emerging markets, Sust. Cities Soc, 32, pp. 31-41, (2017); Zope R., Vasudevan N., Arkatkar S.S., Joshi G., Benchmarking: A tool for evaluation and monitoring sustainability of urban transport system in metropolitan cities of India, Sust. Cities Soc, 45, pp. 48-58, (2019); Edwards J., McKinnon A., Cherrett T., McLeod F., Song L., The impact of failed home deliveries on carbon emissions: Are collection/delivery points environmentally-friendly alternatives, Proceedings of the 14th Annual Logistics Research Network Conference, pp. 102-108, (2019); Morganti E., Dablanc L., Fortin F., Final deliveries for online shopping: The deployment of pickup point networks in urban and suburban areas, Res. Transport. Bus. 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Affairs, 33, pp. 276-296, (2005); History of New Zealand Post, (2015); Advertising in Supermarkets Provides the Following Advantages, (2012); 25 Years of New Zealand Travel, (2015); Brummelman H.J., Kuipers B., Vale N., Effecten van Packstations op Verkeersbewegingen [Impacts of Locker Points on Mobility], Tno Inro, Delft (Dutch), (2003); NZ Herald Lawyer: Supermarkets' collection of facial data an extension of surveillance net, (2018); Dijkstra E.W., A note on two problems in connexion with graphs, Numer. Math, 1, pp. 269-271, (1959); Hillsman E.L., The p-Median Structure as a Unified Linear Model for Location-Allocation Analysis, Environ. Plan. A, 16, pp. 305-318, (1984); Teitz M.B., Bart P., Heuristic Methods for Estimating the Generalized Vertex Median of aWeighted Graph, Oper. Res, 16, pp. 955-961, (1968); McLeod F., Cherrett T., Song L., Transport impacts of local collection/delivery points, Inter. Jrnl Log. Res. Applicat, 9, pp. 307-317, (2006)","A. Kedia; Department of Civil and Natural Resources Engineering, University of Canterbury, Christchurch, 8041, New Zealand; email: ashu.kedia@pg.canterbury.ac.nz",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85075894517"]
["Moore A.M.","Moore, Amy M. (58726481400)",5.87264814E10,"Innovative scenarios for modeling intra-city freight delivery",2019.0,"Transportation Research Interdisciplinary Perspectives",3.0,null,100024.0,null,null,null,14.0,"10.1016/j.trip.2019.100024","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85078412127&doi=10.1016%2fj.trip.2019.100024&partnerID=40&md5=bae9ea1e77d41bcd90a36f21a639344c","National Transportation Research Center, Oak Ridge National Laboratory, Knoxville, TN, United States","Moore A.M., National Transportation Research Center, Oak Ridge National Laboratory, Knoxville, TN, United States","There has been a shift in the focus of freight modeling to the short-haul (or last-mile) due to an increase in online shopping. This study considers innovative freight delivery modes and multi-modal shifts, especially for the last-mile portion of intra-city freight delivery. For this study, GPS data were obtained from a truck fleet from a major parcel delivery company's depot near Columbus, Ohio and used to develop a freight delivery demand estimation model. Freight delivery tours were modeled in TransCAD and used to develop scenarios to incorporate various modal shifts to compare energy usage in kilowatt-hour estimates. Innovative modes of freight delivery were considered for the scenarios and were compared to a class six truck: electric class six trucks, electric delivery vans, parcel delivery lockers, drones, and electric passenger vehicles. Initial findings suggest that electric trucks reduce energy usage when the majority of miles traveled are in the long-haul, or stem portion of the route. Parcel delivery lockers reduced energy usage in suburban areas, especially those with large neighborhoods with cul-de-sacs. The findings from this study were intended to provide decision makers, both in government and industry, with information to consider when determining suitable alternatives for energy-efficient intra-city freight transport. © 2019 The Author","Drones; GIS; Last-mile; Routing; Transportation planning; Urban freight",{"$nulls":5},"DOE Public Access Plan; US Department of Energy; U.S. Department of Energy, USDOE","Funding text 1: This manuscript has been authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan ( http://energy.gov/downloads/doe-public-access-plan ).; Funding text 2: This manuscript has been authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).","Beziat A., Launay P., Toillier F., Analysis of Different Types of Freight Tours According to Their Logistics Organization in the Paris Region, (2015); Boerkamps J., van Binsbergen A., GoodTrip – “A New Approach for Modelling and Evaluation of Urban Goods Distribution”., (1999); Donnelly R., Wigan M., Thompson R., “A Hybrid Micro-Simulation Model of Urban Freight Travel Demand,” Transportation Research Board, Compendium of Papers, (2010); Doustmohammadi E., Sisiopiku V.P., Sullivan A., Modeling freight truck trips in Birmingham using tour-based approach, J. Transport. Technol., 6, pp. 436-448, (2016); Gliebe J., Cohen O., Hunt J.D., Dynamic choice model of urban commercial activity patterns of vehicles and people, Transport. Res. Record J. Transport. Res. Board, pp. 17-26, (2003); Greaves S.P., Figliozzi M.A., Collecting commercial vehicle tour data with passive global positioning system technology, Transport. Res. Record J. Transport. Res. Board, 2049, pp. 158-166, (2008); Holguin-Veras J., Thorson E., Wang Q., Xu N., Gonzalez-Calderon C., Sanchez-Diaz I., Mitchell J., Urban freight tour models: state of the art and practice, Freight Transport Modeling, 117, pp. 335-352, (2013); Kim H., Park D., Kim C., Kim Y., “A Tour-Based Approach to Destination Choice Modeling Incorporating Agglomeration and Competition Effects,” Proceedings from the Eastern Asia Society for Transportation Studies, (2011); Kuppam A., Lemp J., Beagan D., Livshits V., Vallabhaneni L., Nippani S., “Development of a Tour-Based Truck Travel Demand Model Using Truck GPS Data,” Transportation Research Board Compendium of Papers, (2014); Outwater M., Smith C., Wies K., Yoder S., Sana B., Chen J., Tour-based and supply chain modeling for freight: an integrated model demonstration in Chicago, Transport. Lett. Int. J. Transport. Res., 5, 2, pp. 55-66, (2012); Wang Q., Holguin-Veras J., Tour-Based Entropy Maximization Formulations of Urban Commercial Vehicle Movements, (2008); You S., Chow J., Ritchie S., “Truck Tour Modeling Using GPS Data,” Metrans National Urban Freight Conference, (2012)",null,null,"Elsevier Ltd",{"$nulls":5},2.5901982E7,null,null,null,"English","Transp.  Res.  Interdiscip.  Perspect.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85078412127"]
["Ji S.-F.; Luo R.-J.; Peng X.-S.","Ji, Shou-feng (15119083600); Luo, Rong-juan (57203231891); Peng, Xiao-shuai (57201497707)","15119083600; 57203231891; 57201497707","A probability guided evolutionary algorithm for multi-objective green express cabinet assignment in urban last-mile logistics",2019.0,"International Journal of Production Research",57.0,11.0,null,3382.0,3404.0,22.0,20.0,"10.1080/00207543.2018.1533653","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85055584129&doi=10.1080%2f00207543.2018.1533653&partnerID=40&md5=6545bdbc98f9383cf66398fc92287e79","School of Business Administration, Northeastern University, Shenyang, 110167, China","Ji S.-F., School of Business Administration, Northeastern University, Shenyang, 110167, China; Luo R.-J., School of Business Administration, Northeastern University, Shenyang, 110167, China; Peng X.-S., School of Business Administration, Northeastern University, Shenyang, 110167, China","In the past decade, urban last-mile logistics (ULML) has attracted increasing attention with the growth of e-commerce. Under this background, express cabinet has been gradually advocated to improve the efficiency of ULML. This paper focuses on the multi-objective green express cabinet assignment problem (MGECAP) in ULML, where the objectives to be minimised are the total cost and the energy consumption. MGECAP is concerned with optimising the purchase and assignment decision of express cabinets, which is different from conventional assignment problems. To solve MGECAP, firstly, the integer programming model and the corresponding surrogate model are established. Secondly, problem-dependent heuristics, including the solution representation, genetic operators, and repair strategy of infeasible solutions, are proposed. Thirdly, a probability guided multi-objective evolutionary algorithm based on decomposition (PG-MOEA/D) is proposed, which can balance the limited computation resource among sub-problems during the iterative process. Meanwhile, a feedback strategy is put forward to alternatively generate new solutions when the probability condition is not satisfied. Finally, numerical results and a real-life case study demonstrate the effectiveness and the practical values of the PG-MOEA/D. © 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group.","energy consumption; evolutionary algorithm; green express cabinet assignment; multi-objective optimisation; urban last-mile logistics","Combinatorial optimization; Energy utilization; Integer programming; Iterative methods; Multiobjective optimization; Probability; Problem solving; Urban growth; Computation resources; green express cabinet assignment; Guided evolutionary algorithms; Infeasible solutions; Integer programming models; Last mile; Multi objective evolutionary algorithms; Solution representation; Evolutionary algorithms",{"$nulls":4},"Liaoning, China; Philosophy and Social Science Fund, Liaoning, China, (L16AZY032); National Natural Science Foundation of China, NSFC, (71572031); Hunan Provincial Philosophy and Social Science Planning Fund Office","This research was partially supported by National Natural Science Foundation of China [grant number 71572031], and Philosophy and Social Science Fund, Liaoning, China [L16AZY032].","Ahmadi M., Seifi A., Tootooni B., A Humanitarian Logistics Model for Disaster Relief Operation Considering Network Failure and Standard Relief Time: A Case Study on San Francisco District, Transportation Research Part E: Logistics and Transportation Review, 75, 1, pp. 145-163, (2015); 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Zhang Q., Liu W., Li H., The Performance of a New Version of MOEA/D on CEC09 Unconstrained MOP Test Instances, (2009); Zhou A., Zhang Q., Are All the Subproblems Equally Important? Resource Allocation in Decomposition-Based Multiobjective Evolutionary Algorithms, IEEE Transactions on Evolutionary Computation, 20, 1, pp. 52-64, (2016); Zhu S., Chen J., E-commerce Use in Urbanising China: The Role of Normative Social Influence, Behaviour & Information Technology, 35, 5, pp. 357-367, (2016); Zitzler E., Laumanns M., Thiele L., Evolutionary Methods for Design Optimization and Control with Applications to Industrial Problems, (2002)","R.-J. Luo; School of Business Administration, Northeastern University, Shenyang, 110167, China; email: rongjuanluo@163.com",null,"Taylor and Francis Ltd.",{"$nulls":5},207543.0,null,"IJPRB",null,"English","Int J Prod Res","Article","Final",null,"Scopus","2-s2.0-85055584129"]
["Sinha S.N.; Tanty G.; Panigrahi R.R.","Sinha, Sanjay Narayan (57212464346); Tanty, Goutam (57212149305); Panigrahi, Rashmi Ranjan (57212109579)","57212464346; 57212149305; 57212109579","E-commerce & m-commerce growth, issues & challenges in india",2019.0,"International Journal of Scientific and Technology Research",8.0,12.0,null,2970.0,2974.0,4.0,0.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85076721419&partnerID=40&md5=1b3cc0b826e3347deb75aff5f2977e56","ICFAI University Jharkhand, Ranchi, India; Faculty of Management Science, ICFAI University Jharkhand, Ranchi, India","Sinha S.N., ICFAI University Jharkhand, Ranchi, India; Tanty G., Faculty of Management Science, ICFAI University Jharkhand, Ranchi, India; Panigrahi R.R., Faculty of Management Science, ICFAI University Jharkhand, Ranchi, India","Over the last decade, Internet have changed the language of E-Commerce transactions for customer towards purchase and sell of good and service. M-Commerce (through E-Commerce) has transform the shopping experiences of customer of India. Emergence of latest technology bring paradigm shift from E-commerce to M-Commerce in online business scenario. According to Data Via Statista source E-Commerce sales graph showing a rising trend and expected to cross a mark of USD 4.878 billion sales growth by the end of year 2021. E-commerce offers wide range of products, choice and convenient delivery options whereas M Commerce offers platform for online transaction through mobile phone. The research objective is to analyze the present status of e-commerce business, its issues & challenges for business growth in India. It is an explanatory and conceptual Paper based on the market study and customer response towards M/E-Commerce transaction. © IJSTR 2019.","E-business; E-commerce; EMI; Internet Banking; M-commerce; Mobile applications; Transactional security",{"$nulls":5},"Society of Actuaries, SOA","valuable suggestion and guidance to develop this article. The contribution from Mr. Sanjaya N. Sinha, research scholar of ICFAI, University cannot ignore. Above all I convey both the SOA Deemed to be University and ICFAI, University, Jharkhand, Ranchi for providing financial support to complete the article successfully.","Alm J., Melnik M.I., Cross‐border shopping and state use tax liabilities: Evidence from ebay transactions, Public Budgeting & Finance, 32, 1, pp. 5-35, (2012); Anesbury Z., Nenycz-Thiel M., Dawes J., Kennedy R., How do shoppers behave online? An observational study of online grocery shopping, Journal of Consumer Behaviour, 15, 3, pp. 261-270, (2016); Bingi P., Mir A., Khamalah J.N., The challenges facing global e-commerce, IS Management, 17, 4, pp. 1-9, (2000); E-Commerce Industry in India (April 2019); Goyal N., Goyal D., Impact of E-Commerce in India: Issues & Challenges, International Journal of Advanced Research in Computer Science, 7, 6, (2016); Gupta C., Chandhok A., Gupta M., Hardship of M-commerce in India: Problems, Issues & challenges, IOSR Journal of Business and Management, 18, 1, pp. 22-26, (2016); Iqbal A., E-commerce vs mobile commerce, International Journal of Applied Research, pp. 02-24, (2013); Kasemsap K., The importance of electronic commerce in modern business, Encyclopedia of Information Science and Technology, Fourth Edition, pp. 2791-2801, (2018); Kumar N., E – Commerce in India: An Analysis of Present Status, Challenges and Opportunities International Journal of Management Studies, 5, (2018); Malhotra B., E-Business: Issues & Challenges in Indian Perspective, Global Journal of Business Management and Information Technology, 4, 1, pp. 11-16, (2014); Raghunath A., Panga M.D., Problem and Prospects of E-Commerce, International Journal of Research and Development-A Management Review (IJRDMR), 2, 1, pp. 59-68, (2013); Alm J., Melnik M.I., Cross‐border shopping and state use tax liabilities: Evidence from ebay transactions, Public Budgeting & Finance, 32, 1, pp. 5-35, (2012); Sharma R., Challenges and Opportunities of E-Commerce and Its Role in Management Education in India. International Journal of Current Trends in, Engineering & Technology, 1, 1, (2014); Singh A., Badal N., An Efficient Implementation of Multi Matrix Clocks in the Distributed System. in 2015 International Conference on Green Computing and Internet of Things (Icgciot) (Pp. 209-213). IEEE, (2015); Stead B.A., Gilbert J., Ethical issues in electronic commerce, Journal of Business Ethics, 34, 2, pp. 75-85, (2001); Tatnall A., Lepa J., The Internet, e-commerce and older people: An actor-network approach to researching reasons for adoption and use, Logistics Information Management, 16, 1, pp. 56-63, (2003); Velmurugan M.S., Security and Trust in e-Business: Problems and Prospects, International Journal of Electronic Business Management, 7, 3, (2009)",null,null,"International Journal of Scientific and Technology Research",{"$nulls":5},2.2778616E7,null,null,null,"English","Int. J. Sci. Technol. Res.","Article","Final",null,"Scopus","2-s2.0-85076721419"]
["Zeng Y.; Guo H.; Yao Y.; Huang L.","Zeng, Yiwu (57195252583); Guo, Hongdong (36978572900); Yao, Yanfei (57210443775); Huang, Lu (57210445223)","57195252583; 36978572900; 57210443775; 57210445223","The formation of agricultural e-commerce clusters: A case from China",2019.0,"Growth and Change",50.0,4.0,null,1356.0,1374.0,18.0,42.0,"10.1111/grow.12327","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85070740675&doi=10.1111%2fgrow.12327&partnerID=40&md5=99e6d7fa4eb2bee85f6bd2e3952508b8","Economics and Management School, Hangzhou Normal University, Hangzhou, China; China Academy for Rural Development, Zhejiang University, Hangzhou, China","Zeng Y., Economics and Management School, Hangzhou Normal University, Hangzhou, China; Guo H., China Academy for Rural Development, Zhejiang University, Hangzhou, China; Yao Y., China Academy for Rural Development, Zhejiang University, Hangzhou, China; Huang L., China Academy for Rural Development, Zhejiang University, Hangzhou, China","Agricultural e-commerce clusters are new phenomena that have emerged in rural China. In examining the case of Shuyang County in Jiangsu Province, this paper puts forward an integrated model revealing the formation mechanism of agricultural e-commerce clusters. The paper shows that the formation of agricultural e-commerce clusters involves four processes of technology introduction, technology diffusion, quality crisis, and industrial agglomeration based on elements such as industry bases, e-commerce platforms, network facilities, logistics services, entrepreneurial talent, local government, and market demand. Rural social networks and imitation behaviors promote technology diffusion by reducing the cost of technology introduction, and industrial agglomeration is found in the economies showing a deepening of labor divisions and geographic agglomeration. Throughout the formation process, a quality crisis may occur due to a race to the bottom and the opportunistic behaviors of local farmers. This work suggests that regional e-commerce development is a systematic project. Governments of developing countries should not only realize the positive impacts of e-commerce for the development of the agricultural industry but also recognize the premise and logic of how e-commerce can play a prominent role. © 2019 Wiley Periodicals, Inc.",null,"China; Jiangsu; developing world; electronic commerce; industrial agglomeration; labor division; regional development; rural economy; social network; technology diffusion",{"$nulls":4},"National Social Science Foundation of China, (18CSH025); Scientific Research Foundation; National Natural Science Foundation of China, NSFC, (71673244); Hangzhou Normal University, HNU, (RWSK20181010)","Funding text 1:  The authors acknowledge the financial support of National Science Foundation of China (Grand No. 71673244), National Social Science Foundation of China (Grand No. 18CSH025), and Scientific Research Foundation for New Scholars of Hangzhou Normal University (Grand No. RWSK20181010).  ; Funding text 2: The authors acknowledge the financial support of National Science Foundation of China (Grand No. 71673244), National Social Science Foundation of China (Grand No. 18CSH025), and Scientific Research Foundation for New Scholars of Hangzhou Normal University (Grand No. RWSK20181010).","Avgerou C., Li B., Relational and institutional embeddedness of web-enabled entrepreneurial networks: Case studies of netrepreneurs in China, Information Systems Journal, 23, 4, pp. 329-350, (2013); Baorakis G., Kourgiantakis M., Migdalas A., The impact of e-commerce on agro-food marketing: The case of agricultural cooperatives, firms and consumers in Crete, British Food Journal, 104, 8, pp. 580-590, (2002); Bruso S., The idea of industrial districts: Its genesis, Industrial districts and cooperation, pp. 10-19, (1990); Dana L.P., Winstone K.E., Wine cluster formation in New Zealand: Operation, evolution and impact, International Journal of Food Science and Technology, 43, 12, pp. 2177-2190, (2008); Feldman M., The entrepreneurship event revisited: firm formation in a regional context, Industrial and Corporate Change, 10, 4, pp. 861-891, (2001); Kurokawa K., Tembo F., Dirk W., Challenges for the OVOP movement in Sub-Saharan Africa: Insights from Malawi, Japan and Thailand, (2010); Lundvall B., National systems of innovation: Towards a theory of innovation and interactive learning, (1992); Markelova H., Meinzen-Dick R., Hellin J., Dohrn S., Collective action for smallholder market access, Food Policy, 34, 1, pp. 1-7, (2009); Marshall A., Principles of economics, (1890); Montealegre F., Thompson S., Eales J.S., An empirical analysis of the determinants of success of food and agribusiness e-commerce firms, International Food and Agribusiness Management Review, 10, 1, pp. 61-81, (2007); Mueller R.A.E., Sumner D.A., (2006); Nelson R., National innovation systems: A comparative analysis, (1993); Otsuka K., Sonobe T., (2011); Pan S.L., Tan B., Demystifying case research: A structured—pragmatic—situational (SPS) approach to conducting case studies, Information and Organization, 21, 3, pp. 161-176, (2011); Porter M., The competitiveness advantage of nations, (1990); Poulton C., Dorward A., Kydd J., The future of small farms: New directions for services, institutions, and intermediation, World Development, 38, 10, pp. 1413-1428, (2010); Ruan J., Shi Q., Zhang X., Industry cluster dynamic evolution law and local government policy, Management World, 12, pp. 79-91, (2014); Scott A., Industrial organization and location: Division of labor, the firm, and spatial process, Economic Geography, 62, 3, pp. 215-231, (1986); Sterns J.A., Spreen T.H., Industry networks and sustainable competitive advantages in Brazilian and US processed citrus supply chains, Circulation Research, 87, 7, pp. 588-595, (2007); Strauss A.L., Corbin J., Basics of qualitative research: Techniques and procedures for developing grounded theory, (1998); Visser E.J., Langen P.D., The importance and quality of governance in the chilean wine industry, GeoJournal, 65, 3, pp. 177-197, (2006); Walker G., Weber D., A transaction cost approach to make-or-buy decisions, Administrative Science Quarterly, 29, 3, pp. 373-391, (1984); White H.C., Were do markets come from, American Journal of Sociology, 87, 3, pp. 517-547, (1981); Whyte W.F., Street Corner Society, (1943); Wiggins S., Kirsten J., Llambi L., The future of small farms, World Development, 38, 10, pp. 1341-1348, (2010); Yin R., Case study research: Design and methods, (2003); Zeng Y., Guo H., The mechanism and operating logic of how e-commerce associations promote the development of Taobao Villages: Taking the practice of Junpu Village in Jieyang City of Guangdong Province as an example, Chinese Rural Economy, 6, pp. 51-60, (2016); Zeng Y., Jia F., Wan L., Guo H., E-commerce in agri-food sector: A systematic literature review, International Food and Agribusiness Management Review, 20, 4, pp. 439-459, (2017); Zeng Y., Qiu D., Shen Y., Guo H., Study on the formation of Taobao Village: Taking Dongfeng Village and Junpu Village as examples, Economic Geography, 35, 12, pp. 90-97, (2015); Zou L., Liang Q., Mass entrepreneurship, government support and entrepreneurial cluster: Case study of Junpu Taobao Village in China, Scholars Journal of Economics, Business and Management, 2, 12, pp. 1185-1193, (2015)","H. Guo; China Academy for Rural Development, Zhejiang University, Hangzhou, China; email: guohongdong@zju.edu.cn",null,"Blackwell Publishing Inc.",{"$nulls":5},174815.0,null,null,null,"English","Growth Change","Article","Final",null,"Scopus","2-s2.0-85070740675"]
["Li L.; Wang X.; Lin Y.; Zhou F.; Chen S.","Li, Longxiao (57200287438); Wang, Xu (55951735500); Lin, Yun (36655835400); Zhou, Fuli (57189093462); Chen, Shan (57193552168)","57200287438; 55951735500; 36655835400; 57189093462; 57193552168","Cooperative game-based profit allocation for joint distribution alliance under online shopping environment: A case in Southwest China",2019.0,"Asia Pacific Journal of Marketing and Logistics",31.0,2.0,null,302.0,326.0,24.0,29.0,"10.1108/APJML-02-2018-0050","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85062083347&doi=10.1108%2fAPJML-02-2018-0050&partnerID=40&md5=7e766dca3cd91bf614088fd047541a1a","Chongqing University, Chongqing, China; School of Economics and Management, Zhengzhou University of Light Industry, Zhengzhou, China","Li L., Chongqing University, Chongqing, China; Wang X., Chongqing University, Chongqing, China; Lin Y., Chongqing University, Chongqing, China; Zhou F., School of Economics and Management, Zhengzhou University of Light Industry, Zhengzhou, China; Chen S., Chongqing University, Chongqing, China","Purpose: In the context of sharing economy and online shopping, establishing a stable urban joint distribution alliance (JDA) is extremely necessary for the entire logistics service market. The purpose of this paper is to rationally allocate the profits and determine the most stable allocation scheme for the urban JDA as well as provide a direction for cooperation between express enterprises and lead managers to pay more attention to the comprehensive performance. Design/methodology/approach: Cooperative game-based methodologies including the proportion method, the core theory, nucleolus and Shapley value have been employed. Four criteria consisting of enterprise operation, customer satisfaction, environmental sustainability and information technology have been incorporated into Shapley value for improvement. Findings: This paper reveals that express enterprises in logistics service market can achieve more benefit from JDA than those who operate separately. Among proposed profit allocation schemes, improved Shapley value scheme shows more rationality by considering partners’ asymmetric contribution. Besides, a stable alliance can be always ensured with partners’ lower propensity to disrupt and relatively balanced negotiation power under improved Shapley value scheme. Originality/value: This paper makes a few attempts to contribute to the literature on the improvement of Shapley value and applies the concept of “propensity to disrupt” into the field of logistics. Besides, this paper provides various profit allocation schemes and incorporates influencing factors into Shapley value for an improvement thus helping policy-makers make better-informed decisions on urban distribution. Additionally, a case study based on urban express enterprises in Southwest China has been conducted to verify the proposed profit allocation schemes. © 2019, Emerald Publishing Limited.","E-marketing; Gaming research; Logistics operations and management; Physical distribution management",{"$nulls":5},"Fundamental Research Funds for the Central Universities, (106112015CDJSK02JD05)","This study was supported by the Fundamental Research Funds for the Central Universities Project (under Grant No. 106112015CDJSK02JD05). The authors would like to thank the members in the team of City Joint Distribution for Online Shopping Logistic for their assistance and guidance. The authors also appreciate the editor and the anonymous referees for their manuscript processing and remarkable comments.","Adenso-Diaz B., Lozano S., Garcia-Carbajal S., Smith-Miles K., Assessing partnership savings in horizontal cooperation by planning linked deliveries, Transportation Research Part A: Policy and Practice, 66, pp. 268-279, (2014); Agussurja L., Lau H.C., Cheng S.-F., Achieving stable and fair profit allocation with minimum subsidy in collaborative logistics, Thirtieth Conference on Artificial Intelligence, IEEE Xplore, Phoenix, AZ, pp. 970-972, (2016); Asgari S., Afshar A., Madani K., Cooperative game theoretic framework for joint resource management in construction, Journal of Construction Engineering & Management, 140, 3, pp. 1-13, (2013); Audy J.-F., D'amours S., Ronnqvist M., An empirical study on coalition formation and cost/savings allocation, International Journal of Production Economics, 136, 1, pp. 13-27, (2012); Cao Y., Ajjan H., Hong P., Post-purchase shipping and customer service experiences in online shopping and their impact on customer satisfaction: an empirical study with comparison, Asia Pacific Journal of Marketing and Logistics, 30, 2, pp. 400-416, (2018); 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Wang Z., Hu H., Zeng Q., Li X., Profit sharing and the stability of shipping alliances based on game theory, Journal of Transport Economics and Policy, 50, 3, pp. 245-261, (2016); Wu Q., Ren H., Gao W., Ren J., Benefit allocation for distributed energy network participants applying game theory based solutions, Energy, 119, pp. 384-391, (2017); Xu S.X., Cheng M., Huang G.Q., Efficient intermodal transportation auctions for B2B e-commerce logistics with transaction costs, Transportation Research Part B: Methodological, 80, pp. 322-337, (2015); Zakharov V.V., Shchegryaev A.N., Stable cooperation in dynamic vehicle routing problems, Automation and Remote Control, 76, 5, pp. 935-943, (2015); Zhou F., Wang X., Goh M., Zhou L., He Y., Supplier portfolio of key outsourcing parts selection using a two-stage decision making framework for Chinese domestic auto-maker, Computers & Industrial Engineering, 128, pp. 559-575, (2019); Zhou F., Wang X., Lin Y., He Y., Zhou L., Strategic part prioritization for quality improvement practice using a hybrid MCDM framework: a case application in an auto factory, Sustainability, 8, 6, (2016)","X. Wang; Chongqing University, Chongqing, China; email: wx921@163.com",null,"Emerald Group Holdings Ltd.",{"$nulls":5},1.3555855E7,null,null,null,"English","Asia Pac. J. Mark. Logist.","Article","Final",null,"Scopus","2-s2.0-85062083347"]
["Schmid B.; Axhausen K.W.","Schmid, Basil (57195198599); Axhausen, Kay W. (7003940899)","57195198599; 7003940899","In-store or online shopping of search and experience goods: A hybrid choice approach",2019.0,"Journal of Choice Modelling",31.0,null,null,156.0,180.0,24.0,59.0,"10.1016/j.jocm.2018.03.001","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85044360938&doi=10.1016%2fj.jocm.2018.03.001&partnerID=40&md5=cdc89f4f23445efbcd895d3cee5162d6","Institute for Transport Planning and Systems (IVT), ETH Zürich, Stefano-Franscini-Platz 5, Zürich, CH - 8093, Switzerland","Schmid B., Institute for Transport Planning and Systems (IVT), ETH Zürich, Stefano-Franscini-Platz 5, Zürich, CH - 8093, Switzerland; Axhausen K.W., Institute for Transport Planning and Systems (IVT), ETH Zürich, Stefano-Franscini-Platz 5, Zürich, CH - 8093, Switzerland","This paper aims at explaining the choice between online and in-store shopping for typical search and experience goods (standard electronic appliances and groceries)within an artificial experimental setting assuming no privately owned cars. We present the first alternative-specific integrated choice and latent variable (ICLV)model using stated preference data in the field of shopping behavior research, explicitly asking respondents to trade-off attributes specific to each shopping channel. Respondents with pro-online shopping attitudes have a higher shopping cost sensitivity, which can be explained by the expanded choice set when effectively considering both purchasing channels. They also exhibit a higher choice probability of online shopping for groceries compared to electronic appliances, given the nature of experience goods being preferably purchased in-store, while the pleasure of shopping shows no substantial effect on choice behavior. Results reveal a user profile of pro-online shoppers that is mainly characterized by a technology-oriented generation of younger and well-educated men. Also, given the relatively high value of travel time compared to the value of delivery time, we show that especially for electronic appliances, avoiding a shopping trip produces more benefits than waiting for the delivery of ordered products. © 2018 Elsevier Ltd","In-store shopping; Integrated choice and latent variable (ICLV)models; Online shopping; Value of delivery time; Value of travel time",{"$nulls":5},"Post-Car World project; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, SNF, (2-77894-13); University of Sydney","Funding text 1: The authors gratefully thank to the SNSF ( Swiss National Science Foundation ) for funding the Post-Car World project (grant number: 2-77894-13 ). We give thanks to Simon Schmutz, former research assistant at the IVT, for his outstanding contributions to the project. Furthermore, we acknowledge the work of Stephane Hess, Professor at the University of Leeds, and his team for developing and making available the basis of the R-code we used for model estimation. We give thanks to Michiel Bliemer, Professor at the University of Sydney, and to the three anonymous reviewers for their helpful comments and suggestions. ; Funding text 2: The authors gratefully thank to the SNSF (Swiss National Science Foundation)for funding the Post-Car World project (grant number: 2-77894-13). We give thanks to Simon Schmutz, former research assistant at the IVT, for his outstanding contributions to the project. Furthermore, we acknowledge the work of Stephane Hess, Professor at the University of Leeds, and his team for developing and making available the basis of the R-code we used for model estimation. 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Schmid; Institute for Transport Planning and Systems (IVT), ETH Zürich, Zürich, Stefano-Franscini-Platz 5, CH - 8093, Switzerland; email: basil.schmid@ivt.baug.ethz.ch",null,"Elsevier Ltd",{"$nulls":5},1.7555345E7,null,null,null,"English","J. Choice Model.","Article","Final",null,"Scopus","2-s2.0-85044360938"]
["Ingaldi M.; Ulewicz R.","Ingaldi, Manuela (55875626800); Ulewicz, Robert (7801620103)","55875626800; 7801620103","How to make e-commerce more successful by use of Kano's model to assess customer satisfaction in terms of sustainable development",2019.0,"Sustainability (Switzerland)",11.0,18.0,4830.0,null,null,null,56.0,"10.3390/su11184830","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85072602232&doi=10.3390%2fsu11184830&partnerID=40&md5=f830eba7683714289150d689d0c20afd","Faculty of Management, Czestochowa University of Technology, al. Armii Krajowej 19b, Czestochowa, 42-200, Poland","Ingaldi M., Faculty of Management, Czestochowa University of Technology, al. Armii Krajowej 19b, Czestochowa, 42-200, Poland; Ulewicz R., Faculty of Management, Czestochowa University of Technology, al. Armii Krajowej 19b, Czestochowa, 42-200, Poland","Personalization, mobility, deliveries on the same day, and perhaps artificial intelligence-all of these elements will shape e-commerce in the near future. It is necessary to consider what features and standards online shops will have to meet in order to achieve success and to adapt to the changing preferences and requirements of the customer and their awareness of the perception of the environment through the prism of, for example, sustainable development. This means there is a need to specify a set of attributes that will influence the decision to use the services of a given e-shop. Despite all efforts, many online shops fail because they do not meet the expectations of customers. At the same time, meeting customer expectations is a big challenge for newly emerging e-shops. There are many studies on sustainable development in e-commerce, but there is no specific methodology for e-shop design, especially in the aspect of sustainable development. The authors propose a methodology based on Kano's model and customer satisfaction to explore customers' stated needs and unstated desires and to divided them into different groups with different impacts on customer satisfaction. In this paper, a case study on the attributes of customer satisfaction for a newly opened e-shop with organic products, which is to operate in the countries of Central Europe and takes into account selected assumptions of sustainable development, was presented. The research took the form of an original (authorial), universal survey that can be used in other similar research. A total of 1069 correctly completed surveys were taken into account for the analysis. Respondents indicated 16 must-have features for the e-shop in order to make customers benefit from its services and 11 one-dimensional features that will determine the level of customer satisfaction. Among the must-have features, there were those related to sustainable development, which indicates the environmental awareness of potential customers. The obtained results were given to the management of the research e-shop and were included during the design of its operation. After one to two years of e-shop operation, the results will be verified. © 2019 by the authors.","E-commerce; Kano's model; Small and medium enterprises; Social challenges; Sustainable business","Central Europe; artificial intelligence; business development; electronic commerce; Internet; life satisfaction; numerical model; perception; preference behavior; small and medium-sized enterprise; sustainable development",{"$nulls":6},"Michalowska M., Kotylak S., Danielak W., Forming relationships on the e-commerce market as a basis to build loyalty and create value for the customer, Empirical findings. Management, 19, pp. 57-72, (2015); Matthews H., Hendrickson C., Soh D., Environmental and economic effects of e-commerce: A case study of book publishing and retail logistics, Transp. Res. Rec, 1763, pp. 6-12, (2001); Popescu G., E-commerce effects on social sustainability, Econ. Manag. Financ. 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Manag, 29, pp. 2708-2726, (2017); Bakhitar A., Hannan A., Basit A., Ahmad J., Prioritization of value based services of software by using Ahp and fuzzy KANO model, Proceedings of the International Conference on Computational and Social Sciences, (2015); Keshavarz A., Kano's Methods for Understanding Customer-defined Quality, Cent. Qual. Manag. J, 2, pp. 3-36, (1993); Ingaldi M., Kadlubek M., Dziuba S.T., Kano model as an instrument of total quality management, Proceedings of the 2nd International Conference Contemporary Issues in Theory and Practice of Management, Czestochowa, Poland, 19-20 April 2018, pp. 149-156, (2018); Kot S., Sustainable Supply Chain Management in Small and Medium Enterprises, Sustainability, 10, (2018); Hanggraeni D., Slusarczyk B., Sulung L.A.K., Subroto A., The Impact of Internal, External and Enterprise Risk Management on the Performance of Micro, Small and Medium Enterprises, Sustainability, 11, (2019)","M. Ingaldi; Faculty of Management, Czestochowa University of Technology, Czestochowa, al. Armii Krajowej 19b, 42-200, Poland; email: manuela.ingaldi@wz.pcz.pl",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85072602232"]
["Chen M.-C.; Wu P.-J.; Hsu Y.-H.","Chen, Mu-Chen (7407447746); Wu, Pei-Ju (56814106200); Hsu, Yu-Han (57205663800)","7407447746; 56814106200; 57205663800","An effective pricing model for the congestion alleviation of e-commerce logistics",2019.0,"Computers and Industrial Engineering",129.0,null,null,368.0,376.0,8.0,18.0,"10.1016/j.cie.2019.01.060","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85061000042&doi=10.1016%2fj.cie.2019.01.060&partnerID=40&md5=d70afd7d4e77195eba73854fbc910280","Department of Transportation and Logistics Management, National Chiao Tung University, 4F, No. 118, Section 1, Chung Hsiao W. Road, Taipei, 100, Taiwan; Department of Transportation and Logistics, Feng Chia University, No. 100, Wenhwa Road, Seatwen, Taichung, Taiwan","Chen M.-C., Department of Transportation and Logistics Management, National Chiao Tung University, 4F, No. 118, Section 1, Chung Hsiao W. Road, Taipei, 100, Taiwan; Wu P.-J., Department of Transportation and Logistics, Feng Chia University, No. 100, Wenhwa Road, Seatwen, Taichung, Taiwan; Hsu Y.-H., Department of Transportation and Logistics Management, National Chiao Tung University, 4F, No. 118, Section 1, Chung Hsiao W. Road, Taipei, 100, Taiwan","E-retailers and home delivery companies have struggled with logistics congestion. Hence, this study aims to develop a pricing model for alleviation of congestion in e-commerce logistics. The analytical results reveal that a congestion surcharge mechanism influences the behavior of a home delivery company and e-commerce consumers in terms of early delivery and delayed delivery, cargo volume, and consumers’ favorite delivery time. Moreover, e-commerce logistics fees in practice are established by negotiation between e-retailers and home delivery companies. The proposed model can be treated as a reference for e-retailers and home delivery companies to determine appropriate logistics fees. This pioneering study develops a congestion pricing model to deal with congestion problems in e-commerce logistics, which can effectively reflect the impact of various congestion fees on the behavior of e-commerce stakeholders. © 2019","Bottleneck; Congestion; E-commerce logistics; Last-mile delivery; Pricing model; Urban logistics","Consumer behavior; Costs; Electronic commerce; Sales; Bottleneck; Congestion; Last mile; Pricing models; Urban logistics; Traffic congestion",{"$nulls":4},"Ministry of Science and Technology, Taiwan, MOST, (MOST 106-2410-H-035-013-MY2)","This work was supported by the Ministry of Science and Technology, Taiwan, R.O.C. [Grant Number MOST 106-2410-H-035-013-MY2 ].  ","Abulibdeh A., Zaidan E., Analysis of factors affecting willingness to pay for high-occupancy-toll lanes: Results from stated-preference survey of travelers, Journal of Transport Geography, 66, pp. 91-105, (2018); Akgunduz A., Kazerooni H., A non-time segmented modeling for air-traffic flow management problem with speed dependent fuel consumption formulation, Computers & Industrial Engineering, 122, pp. 181-188, (2018); Andersson D., Nassen J., The Gothenburg congestion charge scheme: A pre-post analysis of commuting behavior and travel satisfaction, Journal of Transport Geography, 52, pp. 82-89, (2016); Arnott R., Congestion tolling and urban spatial structure, Journal of Regional Science, 38, 3, pp. 495-504, (1998); Arnott R., de Palma A., Lindsey C., Economics of a bottleneck, Journal of Urban Economics, 27, 1, pp. 111-130, (1990); Bao Y., Xiao F., Gao Z., Gao Z., Investigation of the traffic congestion during public holiday and the impact of the toll-exemption policy, Transportation Research Part B-Methodological, 104, pp. 58-81, (2017); Borjesson M., Kristoffersson I., Assessing the welfare effects of congestion charges in a real world setting, Transportation Research Part E-Logistics and Transportation Review, 70, pp. 339-355, (2014); Braid R.M., Uniform versus peak-load pricing of a bottleneck with elastic demand, Journal of Urban Economics, 26, 3, pp. 320-327, (1989); Brown J.R., Guiffrida A.L., Carbon emissions comparison of last mile delivery versus customer pickup, International Journal of Logistics-Research and Applications, 17, 6, pp. 503-521, (2014); Cardenas I.D., Dewulf W., Vanelslander T., Smet C., Beckers J., The E-commerce parcel delivery market and the implications of home B2c deliveries vs pick-up points, International Journal of Transport Economics, 44, 2, pp. 235-256, (2017); Daniel J.I., Congestion pricing and capacity of large hub airports: A bottleneck model with stochastic queues, Econometrica, 63, 2, pp. 327-370, (1995); Han D., Yang H., The multi-class, multi-criterion traffic equilibrium and the efficiency of congestion pricing, Transportation Research Part E-Logistics and Transportation Review, 44, 5, pp. 753-773, (2008); Hayel Y., Quadri D., Jimenez T., Brotcorne L., Decentralized optimization of last-mile delivery services with non-cooperative bounded rational customers, Annals of Operations Research, 239, 2, pp. 451-469, (2016); Hysing E., Isaksson K., Building acceptance for congestion charges – The Swedish experiences compared, Journal of Transport Geography, 49, pp. 52-60, (2015); Laih C.H., Effects of the optimal step toll scheme on equilibrium commuter behaviour, Applied Economics, 36, 1, pp. 59-81, (2004); Laih C.-H., Queueing at a bottleneck with single- and multi-step tolls, Transportation Research Part A: Policy and Practice, 28, 3, pp. 197-208, (1994); Laih C.-H., Sun P.-Y., The optimal toll scheme for ships queuing at the entrance of Panama Canal, Maritime Economics & Logistics, 16, 1, pp. 20-32, (2014); Laih C.-H., Tsai Y.-C., Chen Z.-B., Optimal non-queuing pricing for the Suez Canal, Maritime Economics & Logistics, 17, 3, pp. 359-370, (2015); Li S., Negenborn R.R., Lodewijks G., Planning inland vessel operations in large seaports using a two-phase approach, Computers & Industrial Engineering, 106, pp. 41-57, (2017); Lindsey C.R., van den Berg V.A.C., Verhoef E.T., Step tolling with bottleneck queuing congestion, Journal of Urban Economics, 72, 1, pp. 46-59, (2012); Liu W., Zhang F., Yang H., Modeling and managing morning commute with both household and individual travels, Transportation Research Part B-Methodological, 103, pp. 227-247, (2017); Liu Y., Li Y., Pricing scheme design of ridesharing program in morning commute problem, Transportation Research Part C-Emerging Technologies, 79, pp. 156-177, (2017); Ma S., Fast or free shipping options in online and Omni-channel retail? The mediating role of uncertainty on satisfaction and purchase intentions, International Journal of Logistics Management, 28, 4, pp. 1099-1122, (2017); Meng Q., Liu Z., Wang S., Optimal distance tolls under congestion pricing and continuously distributed value of time, Transportation Research Part E-Logistics and Transportation Review, 48, 5, pp. 937-957, (2012); Ng K.K.H., Lee C.K.M., Zhang S.Z., Wu K., Ho W., A multiple colonies artificial bee colony algorithm for a capacitated vehicle routing problem and re-routing strategies under time-dependent traffic congestion, Computers & Industrial Engineering, 109, pp. 151-168, (2017); Novaes A.G.N., Bez E.T., Burin P.J., Aragao D.P., Dynamic milk-run OEM operations in over-congested traffic conditions, Computers & Industrial Engineering, 88, pp. 326-340, (2015); Shirazi M., Aashtiani H.Z., Quadrifoglio L., Estimating the minimal revenue tolls in large-scale roadway networks using the dynamic penalty function method, Computers & Industrial Engineering, 107, pp. 120-127, (2017); Silva H.E., Verhoef E.T., van den Berg V.A.C., Airlines’ strategic interactions and airport pricing in a dynamic bottleneck model of congestion, Journal of Urban Economics, 80, pp. 13-27, (2014); Vickrey W., Congestion theory and transport investment, American Economic Review, 59, 2, pp. 251-260, (1969); Wan Y., Jiang C., Zhang A., Airport congestion pricing and terminal investment: Effects of terminal congestion, passenger types, and concessions, Transportation Research Part B-Methodological, 82, pp. 91-113, (2015); Wirth M., Emde S., Scheduling trucks on factory premises, Computers & Industrial Engineering, 126, pp. 175-186, (2018); Xiao F., Zhang H.M., Pareto-improving and self-sustainable pricing for the morning commute with nonidentical commuters, Transportation Science, 48, 2, pp. 159-169, (2014); Yang Z., Shi Y., Yan H., Analysis on pure e-commerce congestion effect, productivity effect and profitability in China, Socio-Economic Planning Sciences, 57, pp. 35-49, (2017); Zacharias J., Zhang B., Local distribution and collection for environmental and social sustainability – tricycles in central Beijing, Journal of Transport Geography, 49, pp. 9-15, (2015)","M.-C. Chen; Department of Transportation and Logistics Management, National Chiao Tung University, Taipei, 4F, No. 118, Section 1, Chung Hsiao W. Road, 100, Taiwan; email: ittchen@mail.nctu.edu.tw",null,"Elsevier Ltd",{"$nulls":5},3608352.0,null,"CINDD",null,"English","Comput Ind Eng","Article","Final",null,"Scopus","2-s2.0-85061000042"]
["Huang Y.; Savelsbergh M.; Zhao L.","Huang, Yixiao (36835640500); Savelsbergh, Martin (6701542933); Zhao, Lei (57199018816)","36835640500; 6701542933; 57199018816","Designing logistics systems for home delivery in densely populated urban areas",2018.0,"Transportation Research Part B: Methodological",115.0,null,null,95.0,125.0,30.0,40.0,"10.1016/j.trb.2018.07.006","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85050107450&doi=10.1016%2fj.trb.2018.07.006&partnerID=40&md5=a44156cad3a0a1cab2f789b25031d25b","Department of Industrial Engineering, Tsinghua University, Beijing, 100084, China; H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, 30332, Georgia","Huang Y., Department of Industrial Engineering, Tsinghua University, Beijing, 100084, China; Savelsbergh M., H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, 30332, Georgia; Zhao L., Department of Industrial Engineering, Tsinghua University, Beijing, 100084, China","To deliver to customers in densely populated urban areas, companies often employ a two-echelon logistics system. In a two-echelon logistics system, the starting point for goods to be delivered in the urban area is a fulfillment center or city distribution center. From there, the goods are first transported to a satellite, from where they are delivered to their final destinations. To simplify operations, companies, in practice, often restrict the route choices at one or both of the echelons. We study the impact on the delivery cost of such restrictions and conclude that when the number of orders to be delivered is large and the location density of delivery addresses is high, the impact is likely to be small, and the operational benefits probably outweigh the cost increases. To more easily accommodate delivery volume growth and to more effectively handle day-to-day delivery volume variations, we introduce a simple aggregation concept, which leads to quality improvements without affecting operational simplicity. We provide further insight by means of a worst-case analysis for specific geographic topologies. © 2018 Elsevier Ltd","Business-to-consumer e-commerce; City logistics; Delivery strategy; Megacities; Two-echelon vehicle routing problem","Vehicle routing; Business to consumer E commerces; City logistics; Delivery strategy; Megacities; Vehicle Routing Problems; design; electronic commerce; logistics; megacity; urban area; urban population; Logistics",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (71361130017, 71771137); Nederlandse Organisatie voor Wetenschappelijk Onderzoek, NWO, (629.001.012)","This research was funded by the National Natural Science Foundation of China (NSFC) under Project No. 71771137 and the international collaboration project between the National Natural Science Foundation of China (NSFC, under Project No. 71361130017) and the Netherlands Organisation for Scientific Research (NWO, under Project No. 629.001.012). We thank Prof. Vera Hemmelmayr of Vienna University of Economics and Business for providing the executive of the ALNS algorithm and Prof. Claudia Archetti and Nicola Bianchessi of University of Brescia for providing the executive of the Branch-and-Cut algorithm.   ","Analysys, GMV of B2C market in China reached 1.189 trillion RMB at the fourth quarter of 2017, (2017); Archetti C., Bianchessi N., Speranza M., Branch-and-cut algorithms for the split delivery vehicle routing problem, Eur. J. Oper. Res., 238, 3, pp. 685-698, (2014); Baldacci R., Mingozzi A., Roberti R., Calvo R., An exact algorithm for the two-echelon capacitated vehicle routing problem, Oper. Res., 61, 2, pp. 298-314, (2013); Beardwood J., Halton J., Hammersley J., The shortest path through many points, Mathematical Proceedings of the Cambridge Philosophical Society, 55, pp. 299-327, (1959); Belgin O., Karaoglan I., Altiparmak F., Two-echelon vehicle routing problem with simultaneous pickup and delivery: mathematical model and heuristic approach, Comput. Ind. Eng., 115, pp. 1-16, (2018); Blanco E., Fransoo J., Reaching 50 million nanostores: retail distribution in emerging megacities, Working Paper WP 404, (2013); Bogdanski R., Cycle logistics solutions in the 2017 sustainability study of the German parcel and express association, (2017); Breunig U., Schmid V., Hartl R., Vidal T., A large neighbourhood based heuristic for two-echelon routing problems, Comput. Oper. Res., 76, pp. 208-225, (2016); Brun Y., The four color theorem, MIT UG J. Math., pp. 21-28, (2002); Carlsson J., Dividing a territory among several vehicles, INFORMS J. 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Sci., 18, 4, pp. 331-350, (1984); Dellaert N., Saridarq F., Van Woensel T., Crainic T., Branch & price based algorithms for the two-echelon vehicle routing problem with time windows, Working Paper, (2016); DPD, Pilot project in Nuremberg: can micro-depots revolutionise the last mile?, (2016); Franceschetti A., Honhon D., Laporte G., Van Woensel T., Fransoo J., Strategic fleet planning for city logistics, Transport. Res. Part B Methodol., 95, pp. 19-40, (2017); Grangier P., Gendreau M., Lehuede F., Rousseau L., An adaptive large neighborhood search for the two-echelon multiple-trip vehicle routing problem with satellite synchronization, Eur. J. Oper. Res., 254, pp. 80-91, (2016); Groer C., Golden B., Wasil E., A library of local search heuristics for the vehicle routing problem, Math. Program. Comput., 2, 2, pp. 79-101, (2010); Hemmelmayr V., Cordeau J.-F., Crainic T., An adaptive large neighborhood search heuristic for two-echelon vehicle routing problems arising in city logistics, Comput. Oper. Res., 39, 12, pp. 3215-3228, (2012); Huang C., Shih T., On the complexity of point-in-polygon algorithms, Comput. Geosci., 23, 1, pp. 109-118, (1997); iResearch, 2017 China's brand e-commerce service industry report, (2017); Jepsen M., Spoorendonk S., Ropke S., A branch-and-cut algorithm for the symmetric two-echelon capacitated vehicle routing problem, Transport. Sci., 47, 1, pp. 23-37, (2013); Kalcsics J., Districting Problems, Location Science, pp. 595-622, (2015); Lei H., Laporte G., Guo B., Districting for routing with stochastic customers, EURO J. Transport. Logist., 1, pp. 67-85, (2012); Li H., Liu Y., Jian X., Lu Y., The two-echelon distribution system considering the real-time transshipment capacity varying, Transport. Res. Part B Methodol., 110, pp. 239-260, (2018); Li H., Yuan J., Lv T., Chang X., The two-echelon time-constrained vehicle routing problem in linehaul-delivery systems considering carbon dioxide emissions, Transport. Res. Part D Transport Environ., 49, pp. 231-245, (2016); Li H., Zhang L., Lv T., Chang X., The two-echelon time-constrained vehicle routing problem in linehaul-delivery systems, Transport. Res. Part B Methodol., 94, pp. 169-188, (2016); Liu R., Tao Y., Hu Q., Xie X., Simulation-based optimisation approach for the stochastic two-echelon logistics problem, Int. J. Prod. Res., 55, 1, pp. 187-201, (2017); Mahmoudi M., Zhou X., Finding optimal solutions for vehicle routing problem with pickup and delivery services with time windows: a dynamic programming approach based on state-space-time network representations, Transport. Res. Part B Methodol., 89, pp. 19-42, (2016); Muyldermans L., Cattrysse D., Van Oudheusden D., Lotan T., Districting for salt spreading operations, Eur. J. 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Soc., 68, 11, pp. 1409-1421, (2017); Wang K., Shao Y., Zhou W., Matheuristic for a two-echelon capacitated vehicle routing problem with environmental considerations in city logistics service, Transport. Res. Part D Transport Environ., 57, pp. 262-276, (2017); Wang Y., Ma X., Xu M., Liu Y., Wang Y., Two-echelon logistics distribution region partitioning problem based on a hybrid particle swarm optimization-genetic algorithm, Expert Syst. Appl., 42, pp. 5019-5031, (2015); Wong K., Beasley J., Vehicle routing using fixed delivery areas, Omega, 12, 6, pp. 591-600, (1984); Zhong H., Hall R., Dessouky M., Territory planning and vehicle dispatching with driver learning, Transport. Sci., 41, 1, pp. 74-89, (2007)","L. Zhao; Department of Industrial Engineering, Tsinghua University, Beijing, 100084, China; email: lzhao@tsinghua.edu.cn",null,"Elsevier Ltd",{"$nulls":5},1912615.0,null,null,null,"English","Transp. Res. Part B Methodol.","Article","Final",null,"Scopus","2-s2.0-85050107450"]
["Loewen K.","Loewen, Kyle (57202019576)",5.7202019576E10,"Reproducing disposability: Unsettled labor strategies in the construction of e-commerce markets",2018.0,"Environment and Planning D: Society and Space",36.0,4.0,null,701.0,718.0,17.0,16.0,"10.1177/0263775818770453","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85046729154&doi=10.1177%2f0263775818770453&partnerID=40&md5=e47cb27632806cb9e591f827fe95758c","University of British Columbia, Canada","Loewen K., University of British Columbia, Canada","Once the logistics revolution’s paradigmatic retail model, big box retail’s declining growth over the last 15 years has left retailers searching for new outlets of expansion. One solution to this problem has been to construct e-commerce markets in order sell delivery as much as the goods delivered. Similar to Walmart’s ascendance, warehousing is again at the vanguard of these new retail models. Significantly, e-commerce’s demands on warehousing dramatically increase the amount of labor warehouses employ and the quality requirements of warehouse work. This article investigates how warehouse labor is being reproduced and restructured in order to construct e-commerce markets. My research indicates an emerging management strategy to meet these demands by scaling back their reliance on labor market intermediaries. I demonstrate this trend through the examples of two different warehouses where management stopped using temp agencies in one case and reduced their reliance on agencies and third parties in a second case. While these changes moved workers closer to “standard” forms of employment, their disposability was reproduced through discourses of “unskilled” labor and logistical practices of retention. These insights develop our understanding of flexible labor’s production in logistics and challenge broader understandings of labor market intermediaries’ significance. © The Author(s) 2018.","contingent labor; e-commerce; Logistics; temporary labor; warehousing","electronic commerce; labor market; labor policy; management practice; market conditions; research work; retailing; storage; strategic approach",{"$nulls":6},"Abernathy F., Dunlop J., Hammond J., Et al., A Stitch in Time : Lean Retailing and the Transformation of Manufacturing, (1999); Allen W.B., The logistics revolution and transportation, Annals of the American Academy of Political and Social Science, 553, pp. 106-116, (1997); Bonacich E., Hardie K., Wal-Mart and the logistics revolution, Wal-Mart: The Face of Twenty-first-Century Capitalism, pp. 163-187, (2006); Brandt R.L., One Click: Jeff Bezos and the Rise of Amazon.com, (2012); Braverman H., Labor and Monopoly Capital: The Degradation of Work in the Twentieth Century, (1998); Burawoy M., Manufacturing Consent: Changes in the Labor Process under Monopoly Capitalism, (1982); Burawoy M., Forty years of labor, Michigan Sociological Review, 29, pp. 1-21, (2015); Cho E.H., Christman A., Emsellem M., Et al., (2012); Cidell J., Distribution centers as distributed places: Mobility, infrastructure, and truck traffic, Cargomobilities: Moving Materials in a Global Age, (2015); Coe N.M., Geographies of production III: Making space for labour, Progress in Human Geography, 37, 2, pp. 271-284, (2013); Coe N.M., Johns J., Ward K., Managed flexibility: Labour regulation, corporate strategies and market dynamics in the Swedish temporary staffing industry, European Urban and Regional Studies, 16, 1, pp. 65-85, (2009); Collins J.L., Threads: Gender, Labor, and Power in the Global Apparel Industry, (2003); Cowen D., (2011); Cowen D., The Deadly Life of Logistics: Mapping Violence in Global Trade, (2014); De Lara J., (2011); De Lara J., Goods movement and metropolitan inequality: Global restructuring, commodity flows, and metropolitan development, Cities, Regions and Flows, (2012); De Lara J., (2013); De Lara J., Reese E., Struna J., Organizing temporary, subcontracted, and immigrant workers: Lessons from change to win’s warehouse workers united campaign, Labor Studies Journal, 41, 4, pp. 309-332, (2016); Doussard M., Degraded Work: The Struggle at the Bottom of the Labor Market, (2013); Ganash B., Engleson S., UPS Pulse of the Online Shopper: Empowered Shoppers Propel Retail Change, (2015); Gereffi G., The organization of buyer driven global commodity chains: How U.S. retailers shape overseas production networks, Commodity Chains and Global Capitalism, pp. 95-122, (1993); Gertler M.S., The limits of flexibility: Comments on the post-Fordist vision of production and its geography, Transactions of the Institute of British Geographers, 13, 4, pp. 419-432, (1988); Gonos G., Martino C., Temps agency workers in New Jersey’s logistics hub: The case for a union hiring hall, WorkingUSA, 14, pp. 499-525, (2011); Graff T.O., Unequal competition among chains of supercenters: Kmart, Target, and Wal-Mart, The Professional Geographer, 58, 1, pp. 54-64, (2006); Gutelius B., Disarticulating distribution: Labor segmentation and subcontracting in global logistics, Geoforum, 60, pp. 53-61, (2015); Hall P.V., Persistent variation: flexibility, organization, and strategy in the logistics of importing automobiles to the United States, 1980–99, Environment and Planning A, 36, 3, pp. 529-546, (2004); Harvey D., The body as an accumulation strategy, Environment and Planning D: Society and Space, 16, 4, pp. 401-421, (1998); Hudson R., Producing Places, (2001); Kalleberg A.L., Nonstandard employment relations: Part-time, temporary and contract work, Annual Review of Sociology, 26, 1, pp. 341-365, (2000); Kanngieser A., Tracking and tracing: Geographies of logistical governance and labouring bodies, Environment and Planning D: Society and Space, 31, 4, pp. 594-610, (2013); LeCavalier J., Wal-Martians: Wal-Mart’s servo-organism, Media and Urban Space: Understanding, Investigating and Approaching Mediacity, (2008); Lichtenstein N., The Retail Revolution: How Wal-Mart Created a Brave New World of Business, (2009); 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Theodore N., Worlds of work: Changing landscapes of production and the new geographies of opportunity, Geography Compass, 10, 4, pp. 179-189, (2016); Tsing A., Supply chains and the human condition, Rethinking Marxism, 21, 2, pp. 148-176, (2009); Vance J.E., Merchant’s World: The Geography of Wholesaling, (1971); Vosko L.F., Temporary Work: The Gendered Rise of a Precarious Employment Relationship, (2000); (2010); Werner M., Global Displacements: The Making of Uneven Development in the Caribbean, (2015); Wills J., Datta K., Evans Y., Et al., Global Cities at Work: New Migrant Divisions of Labour, (2009); Wright M.W., Disposable Women and Other Myths of Global Capitalism, (2006)","K. Loewen; University of British Columbia, Vancouver, 1984 West Mall, V6T1Z2, Canada; email: kyle.loewen@geog.ubc.ca",null,"SAGE Publications Ltd",{"$nulls":5},2637758.0,null,null,null,"English","Environ. Plann. D Soc. Space","Article","Final",null,"Scopus","2-s2.0-85046729154"]
["Moons S.; Ramaekers K.; Caris A.; Arda Y.","Moons, Stef (57192940030); Ramaekers, Katrien (15127894700); Caris, An (24460963600); Arda, Yasemin (14621642700)","57192940030; 15127894700; 24460963600; 14621642700","Integration of order picking and vehicle routing in a B2C e-commerce context",2018.0,"Flexible Services and Manufacturing Journal",30.0,4.0,null,813.0,843.0,30.0,28.0,"10.1007/s10696-017-9287-5","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85016552311&doi=10.1007%2fs10696-017-9287-5&partnerID=40&md5=77391419335f5ed43bd9c0f542a516b8","UHasselt - Hasselt University, Research Group Logistics, Agoralaan Building D, Diepenbeek, 3590, Belgium; QuantOM, HEC Management School, University of Liège, Rue Louvrex 14, Liège, 4000, Belgium","Moons S., UHasselt - Hasselt University, Research Group Logistics, Agoralaan Building D, Diepenbeek, 3590, Belgium; Ramaekers K., UHasselt - Hasselt University, Research Group Logistics, Agoralaan Building D, Diepenbeek, 3590, Belgium; Caris A., UHasselt - Hasselt University, Research Group Logistics, Agoralaan Building D, Diepenbeek, 3590, Belgium; Arda Y., QuantOM, HEC Management School, University of Liège, Rue Louvrex 14, Liège, 4000, Belgium","E-commerce sales are increasing every year and customers who buy goods on the Internet have high service level expectations. In order to meet these expectations, a company’s logistics operations need to be performed carefully. Optimizing only internal warehouse processes will often lead to suboptimal solutions. The interrelationship between the order picking process and the delivery process should not be ignored. Therefore, in this study, an order picking problem and a vehicle routing problem with time windows and release dates are solved simultaneously using a single optimization framework. To the best of our knowledge, it is the first time that an order picking problem and a vehicle routing problem are integrated. A mixed integer linear programming formulation for this integrated order picking-vehicle routing problem (OP-VRP) is provided. The integrated OP-VRP is solved for small instances and the results are compared to these of an uncoordinated approach. Computational experiments show that integration can lead to cost savings of 14% on average. Furthermore, higher service levels can be offered by allowing customers to request their orders later and still get delivered within the same time windows. © 2017, Springer Science+Business Media New York.","E-commerce; Integrated problem; Order picking; Release dates; Vehicle routing","Electronic commerce; Integer programming; Sales; Vehicles; Computational experiment; Integrated problem; Mixed integer linear programming; Optimization framework; Order picking; Release date; Vehicle routing problem with time windows; Vehicle Routing Problems; Vehicle routing",{"$nulls":4},"Interuniversity Attraction Poles Programme; Belgian Federal Science Policy Office, BELSPO","Funding text 1: Acknowledgements This work is supported by the Interuniversity Attraction Poles Programme initiated by the Belgian Science Policy Office (research project COMEX, Combinatorial Optimization: Metaheuristics & Exact Methods).; Funding text 2: This work is supported by the Interuniversity Attraction Poles Programme initiated by the Belgian Science Policy Office (research project COMEX, Combinatorial Optimization: Metaheuristics & Exact Methods).","Agatz N.A.H., Fleischmann M., van Nunen J.A.E.E., E-fulfillment and multi-channel distribution—a review, Eur J Oper Res, 187, 2, pp. 339-356, (2008); 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Moons; UHasselt - Hasselt University, Research Group Logistics, Diepenbeek, Agoralaan Building D, 3590, Belgium; email: stef.moons@uhasselt.be",null,"Springer New York LLC",{"$nulls":5},1.9366582E7,null,null,null,"English","Flexible Serv Manuf J","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85016552311"]
["Yu M.; Yue G.; Lu Z.; Pang X.","Yu, Miao (55475847900); Yue, Guojun (57200318050); Lu, Zichen (57196345397); Pang, Xu (57200312132)","55475847900; 57200318050; 57196345397; 57200312132","Logistics Terminal Distribution Mode and Path Optimization Based on Ant Colony Algorithm",2018.0,"Wireless Personal Communications",102.0,4.0,null,2969.0,2985.0,16.0,12.0,"10.1007/s11277-018-5319-z","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85040793726&doi=10.1007%2fs11277-018-5319-z&partnerID=40&md5=584669362568657587db674fe3e7c5ea","Business School, China University of Political Science and Law, Beijing, China; Accounting School, Harbin University of Commerce, Harbin, China","Yu M., Business School, China University of Political Science and Law, Beijing, China; Yue G., Business School, China University of Political Science and Law, Beijing, China; Lu Z., Accounting School, Harbin University of Commerce, Harbin, China; Pang X., Business School, China University of Political Science and Law, Beijing, China","In order to discuss the logistics distribution that directly affects the satisfaction of consumers for the entire online shopping activities, this article mainly studies the logistics terminal distribution mode and path optimization, and combined with the application of ant colony algorithm in the traveling salesman problem, analyses the basic principle and implementation process of ant colony algorithm. In addition, through reference to map and field research, we consider the route length and road conditions (slope and congestion) of the the regional distribution point, and collect and draw the geographic information surrounding area A. Moreover, some key parameters in ant colony algorithm in value are chosen, and with the collected information as a concrete example, MATLAB simulation is carried out for the logistics terminal distribution path optimization based on ant colony algorithm, and its scientific nature and feasibility are verified. The simulation results showed that the ant colony algorithm has good feasibility so that it can be widely applied. As a result, it is concluded that the application of ant colony algorithm has great significance in the exploration of the logistics terminal distribution path optimization. © 2018, Springer Science+Business Media, LLC, part of Springer Nature.","Ant colony algorithm; Logistics terminal distribution; Path optimization","Geographical distribution; MATLAB; Traveling salesman problem; Vehicle routing; Ant colony algorithms; Geographic information; Implementation process; Logistics distribution; Matlab simulations; Path optimizations; Regional distribution; Terminal distribution; Ant colony optimization",{"$nulls":4},"CASTED; National Science Foundation, NSF, (L1422009); China University of Political Science and Law, CUPL, (17ZFG63001)","Funding text 1: Acknowledgements The authors acknowledge ‘‘Basic Tasks of Technical forecasting’’ commissioned by CASTED, College Scientific Research Project of China University of Political Science and Law (Grant No. 17ZFG63001), Training and Supporting Project for Young or Middle-aged Teachers of China University of Political Science and Law, and NSF of China (Grant No. L1422009).; Funding text 2: The authors acknowledge ?Basic Tasks of Technical forecasting? commissioned by CASTED, College Scientific Research Project of China University of Political Science and Law (Grant No. 17ZFG63001), Training and Supporting Project for Young or Middle-aged Teachers of China University of Political Science and Law, and NSF of China (Grant No. L1422009).","Zhang Y., Wu X.Y., Kwon O.K., Research on kruskal crossover genetic algorithm for multi-objective logistics distribution path optimization, International Journal of Multimedia and Ubiquitous Engineering, 10, 8, pp. 367-378, (2015); Moussi R., Euchi J., Yassine A., Ndiaye N.F., A hybrid ant colony and simulated annealing algorithm to solve the container stacking problem at seaport terminal, International Journal of Operational Research, 24, 4, pp. 399-422, (2015); Ran W., Shi X., Fu H., Yang G., Application research on ant colony algorithm in logistic distribution route-optimization of fresh agricultural products, International Journal of Digital Content Technology and its Applications, 7, 6, (2013); Chen X., Wang J., A novel hybrid cuckoo search algorithm for optimizing vehicle routing problem in logistics distribution system, Journal of Computational and Theoretical Nanoscience, 13, 1, pp. 114-119, (2016); Chang Y.C., Li V.C., Chiang C.J., An ant colony optimization heuristic for an integrated production and distribution scheduling problem, Engineering Optimization, 46, 4, pp. 503-520, (2014); Bagherinejad J., Dehghani M., A non-dominated sorting ant colony optimization algorithm approach to the bi-objective multi-vehicle allocation of customers to distribution centers, Journal of Optimization in Industrial Engineering, 9, 19, pp. 61-74, (2016); Wei X., Shi C., Song H., The research on improving China Post Logistics’ automobile part distribution efficiency, International Journal of Digital Content Technology and Its Applications, 7, 7, (2013); Yifeng Z., Ruhe X., Application of cold chain logistics safety reliability in fresh food distribution optimization, Advance Journal of Food Science and Technology, 5, pp. 356-360, (2013)","X. Pang; Business School, China University of Political Science and Law, Beijing, China; email: xupang1987@hotmail.com",null,"Springer New York LLC",{"$nulls":5},9296212.0,null,"WPCOF",null,"English","Wireless Pers Commun","Article","Final",null,"Scopus","2-s2.0-85040793726"]
["Chen F.; Xu G.; Wei Y.; Garciá-Alcaraz J.L.","Chen, Fangyu (55800364700); Xu, Gangyan (55361785800); Wei, Yongchang (55240909400); Garciá-Alcaraz, Jorge Luis (55616966800)","55800364700; 55361785800; 55240909400; 55616966800","An integrated metaheuristic routing method for multiple-block warehouses with ultranarrow aisles and access restriction",2019.0,"Complexity",2019.0,null,1280285.0,null,null,null,8.0,"10.1155/2019/1280285","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85068550843&doi=10.1155%2f2019%2f1280285&partnerID=40&md5=484859c334c611f8e9a50d1a81fe3fc2","Institute of Operations Management and System Engineering, School of Business Administration, Zhongnan University of Economics and Law, Wuhan, 430073, China; School of Architecture, Harbin Institute of Technology, Shenzhen, China","Chen F., Institute of Operations Management and System Engineering, School of Business Administration, Zhongnan University of Economics and Law, Wuhan, 430073, China; Xu G., School of Architecture, Harbin Institute of Technology, Shenzhen, China; Wei Y., Institute of Operations Management and System Engineering, School of Business Administration, Zhongnan University of Economics and Law, Wuhan, 430073, China; Garciá-Alcaraz J.L.","A problem-specific routing algorithm integrating ant colony optimization (ACO) and integer-coded genetic algorithm (GA) is developed to address the newly observed limitations imposed by ultranarrow aisles and access restriction, which exist in the largest e-commerce enterprise with self-run logistics in China. Those limitations prohibit pickers from walking through the whole aisle, and the access restriction even allows them to access the pick aisles only from specific entrances. The ant colony optimization is mainly responsible for generating the initial chromosomes for the genetic algorithm, which then searches the near-optimal solutions of picker-routing with our novel chromosome design by recording the detailed information of access modes and subaisles. To demonstrate the merits of the proposed algorithm, a comprehensive simulation for comparison is conducted with 12 warehouse layouts with real order information. The simulation results show that the proposed hybrid algorithm is superior to dedicated heuristics in terms of solution quality. The impacts of the parameters with respect to warehouse layout on the picking efficiency are analyzed as well. Setting more connect aisles and cross aisles is suggested to effectively optimize the picking-service efficiency in the presence of access limitations. © 2019 Fangyu Chen et al.",null,"Artificial intelligence; Chromosomes; Efficiency; Genetic algorithms; Integer programming; Warehouses; Access restriction; Ant Colony Optimization (ACO); E-commerce enterprise; Hybrid algorithms; Integer coded genetic algorithms; Near-optimal solutions; Picking efficiency; Warehouse layout; Ant colony optimization",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (71401181, 71701213); Ministry of Education of the People's Republic of China, MOE, (14YJC630136, 15YJC630008)","This work was supported by the National Natural Science Foundation of China [Grants nos. 71701213 and 71401181] and the MOE (Ministry of Education in China) Project of Humanities and Social Sciences [Grants nos. 15YJC630008 and 14YJC630136].","Garca J.L., Alvarado A., Blanco J., Jimenez E., Maldonado A.A., Cortes G., Multi-attribute evaluation and selection of sites for agricultural product warehouses based on an analytic hierarchy process, Computers and Electronics in Agriculture, 100, pp. 60-69, (2014); De Santis R., Montanari R., Vignali G., Bottani E., An adapted ant colony optimization algorithm for the minimization of the travel distance of pickers in manual warehouses, European Journal of Operational Research, 267, 1, pp. 120-137, (2018); Tompkins J.A., White J.A., Bozer Y.A., Tanchoco J.M.A., Facilities Planning, (2010); Chen F., Wei Y., Wang H., A heuristic based batching and assigning method for online customer orders, Flexible Services and Manufacturing Journal, 30, 4, pp. 640-685, (2018); Zhang J., Wang X., Huang K., On-line scheduling of order picking and delivery with multiple zones and limited vehicle capacity, OMEGA-five International Journal of Management Science, 79, pp. 104-115, (2018); Petersen I.I.C.G., An evaluation of order picking routeing policies, International Journal of Operations and Production Management, 17, 11, pp. 1098-1111, (1997); Gue K., Meller R., Skufca J., The effects of pick density on order picking areas with narrow aisles, Institute of Industrial Engineers (IIE). IIE Transactions, 38, 10, pp. 859-868, (2006); Parikh P.J., Meller R.D., Estimating picker blocking in wide-aisle order picking systems, Institute of Industrial Engineers (IIE). 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IIE Transactions, 37, 1, pp. 63-75, (2005); Alvarado-Iniesta A., Garcia-Alcaraz J.L., Rodriguez-Borbon M.I., Maldonado A., Optimization of the material flow in a manufacturing plant by use of artificial bee colony algorithm, Expert Systems with Applications, 40, 12, pp. 4785-4790, (2013); Guo H., Li C., Zhang Y., Zhang C., Wang Y., A nonlinear integer programming model for integrated location, inventory, and routing decisions in a closed-loop supply chain, Complexity, 2018, (2018); Huang C., Lan Y., Liu Y., Et al., A new dynamic path planning approach for unmanned aerial vehicles, Complexity, 2018, (2018); Kulak O., Sahin Y., Taner M.E., Joint order batching and picker routing in single and multiple-cross-aisle warehouses using cluster-based tabu search algorithms, Flexible Services and Manufacturing Journal, 24, 1, pp. 52-80, (2012); Matusiak M., De Koster R., Kroon L., Saarinen J., A fast simulated annealing method for batching precedenceconstrained customer orders in a warehouse, European Journal of Operational Research, 236, 3, pp. 968-977, (2014); Valle C.A., Beasley J.E., Da Cunha A.S., Optimally solving the joint order batching and picker routing problem, European Journal OfOperational Research, 262, 3, pp. 817-834, (2017); Lin C.-C., Kang J.-R., Hou C.-C., Cheng C.-Y., Joint order batching and pickerManhattan routing problem, Computers& Industrial Engineering, 95, pp. 164-174, (2016); Grosse E.H., Glock C.H., Ballester-Ripoll R., A simulated annealing approach for the joint order batching and order picker routing problem with weight restrictions, International Journal OfOperations AndQuantitativeManagement, 20, 2, pp. 65-83, (2014); Chen T.-L., Cheng C.-Y., Chen Y.-Y., Chan L.-K., An efficient hybrid algorithm for integrated order batching, sequencing and routing problem, International Journal of Production Economics, 159, pp. 158-167, (2015); Cheng C.-Y., Chen Y.-Y., Chen T.-L., Jung-Woon Yoo J., Using a hybrid approach based on the particle swarm optimization and ant colony optimization to solve a joint order batching and picker routing problem, International Journal of Production Economics, 170, pp. 805-814, (2015); Li J., Huang R., Dai J.B., Joint optimisation of order batching and picker routing in the online retailer's warehouse in China, International Journal of Production Research, 55, 2, pp. 447-461, (2017); Scholz A., Henn S., Stuhlmann M., Wascher G., A new mathematical programming formulation for the single-picker routing problem, European Journal of Operational Research, 253, 1, pp. 68-84, (2016); Chang T.-H., Fu H.-P., Hu K.-Y., A two-sided picking model of M-AS/RS with an aisle-assignment algorithm, International Journal of Production Research, 45, 17, pp. 3971-3990, (2007); Xu X., Liu T., Li K., Dong W., Evaluating order throughput timewith variable timewindowbatching, International Journal of Production Research, 52, 8, pp. 2232-2242, (2014); Henn S., Schmid V., Metaheuristics for order batching and sequencing in manual order picking systems, Computers & Industrial Engineering, 66, 2, pp. 338-351, (2013); Roodbergen K.J., De Koster R., Routing methods for warehouses with multiple cross aisles, International Journal of Production Research, 39, 9, pp. 1865-1883, (2001); Pan J.C.-H., Shih P.-H., Wu M.-H., Order batching in a pick-and-pass warehousing system with group genetic algorithm, OMEGA-five International Journal OfManagement Science, 57, pp. 238-248, (2015); Roodbergen K.J., De Koster R., Routing order pickers in a warehouse with a middle aisle, European Journal of Operational Research, 133, 1, pp. 32-43, (2001)","Y. Wei; Institute of Operations Management and System Engineering, School of Business Administration, Zhongnan University of Economics and Law, Wuhan, 430073, China; email: ivanwilts306@163.com",null,"Hindawi Limited",{"$nulls":5},1.0762787E7,null,null,null,"English","Complexity","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85068550843"]
["Jiang L.; Chang H.; Zhao S.; Dong J.; Lu W.","Jiang, Li (57194833199); Chang, Hongxia (57209207984); Zhao, Shuping (56376848700); Dong, Junfeng (55478035600); Lu, Wenxing (24314743900)","57194833199; 57209207984; 56376848700; 55478035600; 24314743900","A Travelling Salesman Problem with Carbon Emission Reduction in the Last Mile Delivery",2019.0,"IEEE Access",7.0,null,8709670.0,61620.0,61627.0,7.0,32.0,"10.1109/ACCESS.2019.2915634","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85066874493&doi=10.1109%2fACCESS.2019.2915634&partnerID=40&md5=5ec0f8975246d503c2995edbab8b733c","School of Management, Hefei University of Technology, Hefei, 230009, China; Key Laboratory of Process Optimization and Intelligent Decision-making, Ministry of Education, Hefei, 230009, China","Jiang L., School of Management, Hefei University of Technology, Hefei, 230009, China, Key Laboratory of Process Optimization and Intelligent Decision-making, Ministry of Education, Hefei, 230009, China; Chang H., School of Management, Hefei University of Technology, Hefei, 230009, China, Key Laboratory of Process Optimization and Intelligent Decision-making, Ministry of Education, Hefei, 230009, China; Zhao S., School of Management, Hefei University of Technology, Hefei, 230009, China, Key Laboratory of Process Optimization and Intelligent Decision-making, Ministry of Education, Hefei, 230009, China; Dong J., School of Management, Hefei University of Technology, Hefei, 230009, China, Key Laboratory of Process Optimization and Intelligent Decision-making, Ministry of Education, Hefei, 230009, China; Lu W., School of Management, Hefei University of Technology, Hefei, 230009, China, Key Laboratory of Process Optimization and Intelligent Decision-making, Ministry of Education, Hefei, 230009, China","The development of e-commerce has led to a surge in the number of online shopping parcels. However, given the lack of scale effect, last mile delivery is inefficient, expensive, and produces a considerable amount of carbon emissions, which has become an obstacle to the development of a sustainable economy. This work proposes a traveling salesman problem with carbon emission reduction in last mile delivery. The proposed problem aims to reduce the total costs and carbon emissions of last mile delivery by deciding on the allocation of parcel lockers while scheduling delivery routes. In addition, we take the customer self-collection intention into consideration and translate it into self-collection costs, which are included in the objective. An iterated local search (ILS) algorithm is proposed, and four new local search operators are designed to improve customer allocation. The proposed method is tested on a set of scattered and clustered instances, including a real-world instance. The computational results show the superiority and competitiveness of the proposed algorithm. © 2013 IEEE.","carbon emission; customer pickup; ILS; last mile; parcel lockers; Sustainable economy","Carbon; Electronic commerce; Emission control; Local search (optimization); Locks (fasteners); Sales; Carbon emission reductions; Carbon emissions; Computational results; Last mile; Local search operators; parcel lockers; Sustainable economy; Travelling salesman problem; Traveling salesman problem",{"$nulls":4},"Ministry of Chinese Education, Humanities and Social Sciences, (17YJA630037); Project of Graduate Teaching Quality in Hefei University of Technology, (2018YJG02); Natural Science Foundation of Anhui Province, (1808085QG229); Fundamental Research Funds for the Central Universities, (PA2019GDQT0005); National Science and Technology Planning Project, (71331002, 71502047, 71601061, 71771077)","This work was supported in part by the Ministry of Chinese Education, Humanities and Social Sciences under Grant 17YJA630037, in part by the National Science and Technology Support Program of China under Grant 71331002, Grant 71502047, Grant 71601061, and Grant 71771077, in part by the Fundamental Research Funds for the Central Universities under Grant PA2019GDQT0005, in part by the Project of Graduate Teaching Quality in Hefei University of Technology under Grant 2018YJG02, and in part by the Natural Science Foundation of Anhui Province in China under Grant 1808085QG229.","Deutsch Y., Golany B., A parcel locker network as a solution to the logistics last mile problem, Int. J. Prod. Res., 56, 1-2, pp. 251-261, (2018); Zhou L., Wang X., Ni L., Lin Y., Location-routing problem with simultaneous home delivery and customer's pickup for city distribution of online shopping purchases, Sustainability, 8, 8, pp. 20-32, (2016); Ferrucci F., Bock S., Real-time control of express pickup and delivery processes in a dynamic environment, Transp. Res. B, Methodol., 63, pp. 1-14, (2014); Wang X., Zhan L., Ruan J., Zhang J., How to choose 'last mile' delivery modes for E-fulfillment, Math. Problems Eng., 2014, (2014); Agatz N., Campbell A., Fleischmann M., Savelsbergh M., Time slot management in attended home delivery, Transp. Sci., 45, pp. 435-449, (2011); Punakivi M., Tanskanen K., Increasing the cost efficiency of efulfilment using shared reception boxes, Int. J. Retail Distrib. Manage., 30, 10, pp. 498-507, (2002); Kamarainen V., Saranen J., Holmstrom J., The reception box impact on home delivery efficiency in the e-grocery business, Int. J. Phys. Distrib. Logistics Manage., 31, 6, pp. 414-426, (2013); Yuen K.F., Wang X., Ng L.T.W., Wong Y.D., An investigation of customers' intention to use self-collection services for last-mile delivery, Transp. Policy, 66, pp. 1-8, (2018); Edwards J., McKinnon A., Cherrett T., McLeod F., Song L., Carbon dioxide benefits of using collection-delivery points for failed home deliveries in the United Kingdom, Transp. Res. Rec., 33, 1, pp. 136-143, (2010); Hoos H.H., Stutzle T., On the empirical time complexity of finding optimal solutions vs proving optimality for Euclidean TSP instances, Optim. Lett., 9, 6, pp. 1247-1254, (2015); Gendreau M., Hertz A., Laporte G., Stan M., A generalized insertion heuristic for the traveling salesman problem with time windows, Oper. Res., 46, 3, pp. 330-335, (1998); Erchong L., Liu C., A hierarchical algorithm based on density peaks clustering and ant colony optimization for traveling salesman problem, Ieee Access, 6, pp. 38921-38933, (2018); Gendreau M., Laporte G., Vigo D., Heuristics for the traveling salesman problem with pickup and delivery, Comput. Oper. Res., 26, 7, pp. 699-714, (2018); Zhao F., Li S., Sun J., Mei D., Genetic algorithm for the onecommodity pickup-and-delivery traveling salesman problem, Comput. Ind. Eng., 56, 4, pp. 1642-1648, (1999); Balma A., Salem S.B., Mrad M., Ladhari T., Strong multicommodity flow formulations for the asymmetric traveling salesman problem, Eur. J. Oper. Res., 271, 1, pp. 72-79, (2018); Panchamgam K., Xiong Y., Golden B., Dussault B., Wasil E., The hierarchical traveling salesman problem, Optim. Lett., 7, 7, pp. 1517-1524, (2013); Moran-Mirabal L.F., Gonzalez-Velarde J.L., Resende M.G.C., Randomized heuristics for the family traveling salesperson problem, Int. Trans. Oper. Res., 21, 1, pp. 41-57, (2013); Bernardino R., Paias A., Solving the family traveling salesman problem, Eur. J. Oper. Res., 267, 2, pp. 453-466, (2018); Manerba D., Mansini R., Riera-Ledesma J., The traveling purchaser problem and its variants, Eur. J. Oper. Res., 259, 1, pp. 1-18, (2017); Guo P., Liu Z.J., An ant system based on moderate search for TSP, Comput. Sci. Inf. Syst., 9, 4, pp. 1533-1551, (2012); Shaelaie M.H., Salari M., Naji-Azimi Z., The generalized covering traveling salesman problem, Appl. Soft Comput., 24, pp. 867-878, (2014); Current J.R., Schilling D.A., The covering salesman problem, Transp. Sci., 23, 3, pp. 208-213, (1989); Shariff S.S.R., Moin N.H., Omar M., Location allocation modeling for healthcare facility planning in Malaysia, Comput. Ind. Eng., 62, 4, pp. 1000-1010, (2012); Reina D.G., Marin S.L.T., Bessis N., Barrero F., Asimakopoulou E., An evolutionary computation approach for optimizing connectivity in disaster response scenarios, Appl. Soft Comput., 13, 2, pp. 833-845, (2013); McDougall J.A., Otero L.D., Optimal transfer point locations in twostage distribution systems, Ieee Access, 6, pp. 1974-1984, (2017); Chen Q., Conway A., Cheng J., Parking for residential delivery in New York City: Regulations and behavior, Transp. Policy, 54, pp. 53-60, (2017); Van Duin J.H.R., De Goffau W., Wiegmans B., Tavasszy L.A., Saes M., Improving home delivery efficiency by using principles of address intelligence for B2C deliveries, Transp. Res. Procedia, 12, pp. 14-25, (2016); Morganti E., Seidel S., Blanquart C., Dablanc L., Lenz B., The impact of E-commerce on final deliveries: Alternative parcel delivery services in France and Germany, Transp. Res. Procedia, 4, pp. 178-190, (2014); Park H., Park D., Jeong I.-J., An effects analysis of logistics collaboration in last-mile networks for CEP delivery services, Transp. Policy, 50, pp. 115-125, (2016); Zhou L., Baldacci R., Vigo D., Wang X., A multi-depot two-echelon vehicle routing problem with delivery options arising in the last mile distribution, Eur. J. Oper. Res., 265, 2, pp. 765-778, (2018); Lemke J., Iwan S., Korczak J., Usability of the parcel lockers from the customer perspective - The research in polish cities, Transp. Res. Procedia, 16, pp. 272-287, (2016); Vansteenwegen P., Souffriau W., Berghe G.V., Van Oudheusden D., Iterated local search for the team orienteering problem with time windows, Comput. Oper. Res., 36, 12, pp. 3281-3290, (2009); Kindervater G.A.P., Savelsbergh M.W.P., Vehicle routing: Handling edge exchanges, Local Search in Combinatorial Optimization, pp. 337-360, (1997); Brimberg J., Mladenovic N., Todosijevic R., Urosevic D., A basic variable neighborhood search heuristic for the uncapacitated multiple allocation p-hub center problem, Optim. Lett., 11, 2, pp. 313-327, (2017); Yu V.F., Lin S.-W., Lee W., Ting C.-J., A simulated annealing heuristic for the capacitated location routing problem, Comput. Ind. Eng., 58, 2, pp. 288-299, (2010)","S. Zhao; School of Management, Hefei University of Technology, Hefei, 230009, China; email: zhaoshuping1753@126.com",null,"Institute of Electrical and Electronics Engineers Inc.",{"$nulls":5},2.1693536E7,null,null,null,"English","IEEE Access","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85066874493"]
["Ounacer S.; El Bour H.A.; Oubrahim Y.; Ghoumari M.Y.; Azzouazi M.","Ounacer, Soumaya (57203636683); El Bour, Hicham Ait (57202829415); Oubrahim, Younes (57210467458); Ghoumari, Mohamed Yassine (8900781300); Azzouazi, Mohamed (57189220959)","57203636683; 57202829415; 57210467458; 8900781300; 57189220959","Using Isolation Forest in anomaly detection: The case of credit card transactions",2018.0,"Periodicals of Engineering and Natural Sciences",6.0,2.0,null,394.0,400.0,6.0,20.0,"10.21533/pen.v6i2.533","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85070835619&doi=10.21533%2fpen.v6i2.533&partnerID=40&md5=ad91439731a9ca1d1370363449268eb0","Department of mathematics and computer science, Information Technology and Modeling Laboratory, Hassan II University, Faculty of Sciences Ben M'Sik, Casablanca, Morocco","Ounacer S., Department of mathematics and computer science, Information Technology and Modeling Laboratory, Hassan II University, Faculty of Sciences Ben M'Sik, Casablanca, Morocco; El Bour H.A., Department of mathematics and computer science, Information Technology and Modeling Laboratory, Hassan II University, Faculty of Sciences Ben M'Sik, Casablanca, Morocco; Oubrahim Y., Department of mathematics and computer science, Information Technology and Modeling Laboratory, Hassan II University, Faculty of Sciences Ben M'Sik, Casablanca, Morocco; Ghoumari M.Y., Department of mathematics and computer science, Information Technology and Modeling Laboratory, Hassan II University, Faculty of Sciences Ben M'Sik, Casablanca, Morocco; Azzouazi M., Department of mathematics and computer science, Information Technology and Modeling Laboratory, Hassan II University, Faculty of Sciences Ben M'Sik, Casablanca, Morocco","With the evolution of new technology especially in the domain of e-commerce and online banking, the payment by credit card has seen a significant increase. The credit card has become the most used tool for online shopping. This high rate in use brings about fraud and a considerable damage. It is very important to stop fraudulent transactions because they cause huge financial losses over time. The detection of fraudulent transactions is an important application in anomaly detection. There are different approaches to detecting anomalies namely SVM, logistic regression, decision tree and so on. However, they remain limited since they are supervised algorithms that require to be trained by labels in order to know whether the transactions are fraudulent or not. The goal of this paper is to have a credit card fraud detection system which is able to detect the highest number of new transactions in real time with high accuracy. We will also compare, in this paper, different unsupervised techniques for credit card fraud detection namely LOF, one class SVM, K-means and Isolation Forest so as to single out the best approach. © 2018 International University of Sarajevo.","Anomaly detection; Credit card frauds; Isolation Forest; K-means; LOF; OCSVM",{"$nulls":7},"Banerjee T., Mishra M., Debnath N.C., Choudhury P., Implementing E-Commerce model for Agricultural Produce: A Research Roadmap, 7, 1, pp. 302-310, (2019); Ming H., Kishan G., Chilukuri M., Mohan K., Anomaly Algorithms Principles and Detection, (2017); Chandola V., Banerjee A., Kumar A.V., Anomaly Detection: a SURVEY, Conform. Predict. Reliab. Mach. Learn. Theory, Adapt. Appl, 41, 3, pp. 71-97, (2014); Flarence R.A., Bethu S., Sowmya V., Anusha K., Babu B.S., Importance of Supervised Learning in Prediction Analysis, 6, 1, pp. 201-214, (2018); Venkateswaran N., Shekhar A., Changder S., Using machine learning for intelligent shard sizing on the cloud, 7, 1, pp. 109-124, (2019); Sabinasz D., Dealing with Unbalanced Classes in Machine Learning, Deep Ideas, (2017); Jihal H., Talhaoui M.A., Daif A., Azzouazi M., Predictive Analytics as A Service on Moroccan Tax Evasion, 7, pp. 90-92, (2018); Maes S., Tuyl K., Credit Card Fraud Detection Using Bayesian and Neural Networks, (2013); Sahin Y., Duman E., Detecting Credit Card Fraud by Decision Trees and Support Vector Machines, 1, (2011); Malini N., Phil M., Analysis on Credit Card Fraud Identification Techniques based on KNN and Outlier Detection, pp. 3-6, (2017); Breunig M.M., Kriegel H., Ng R.T., Sander J., LOF: Identifying Density-Based Local Outliers, pp. 1-12, (2000); Breunig M.M., Kriegel H.-P., Ng R.T., Sander J., OPTICS-OF: Identifying Local Outliers, pp. 262-270, (2010); Sch B., Williamson R., Support Vector Method for Novelty Detection, pp. 582-588, (2000); Celebi M.E., Kingravi H.A., Vela P.A., A comparative study of efficient initialization methods for the k-means clustering algorithm, Expert Syst. Appl, 40, 1, pp. 200-210, (2013); Lewinson E., Outlier Detection with Isolation Forest, Towards Data Science, (2017); Liu F.T., Ting K.M., \"Isolation Forest.\", (2009); Liu F.T., Ting K.M., Zhou Z.H., Isolation forest, Proc.-IEEE Int. Conf. Data Mining, ICDM, pp. 413-422, (2008); Liu F.T., Ting K.M., Isolation Forest: Isolation Forest, (1980); \"Credit Card Fraud _ Kaggle, Anonymized credit card transactions labeled as fraudulent or genuine.\"","S. Ounacer; Department of mathematics and computer science, Information Technology and Modeling Laboratory, Hassan II University, Faculty of Sciences Ben M'Sik, Casablanca, Morocco; email: soumayaounacer@gmail.com",null,"International University of Sarajevo",{"$nulls":5},2.3034521E7,null,null,null,"English","Period. eng. nat. sci.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85070835619"]
["Ramaekers K.; Caris A.; Moons S.; van Gils T.","Ramaekers, Katrien (15127894700); Caris, An (24460963600); Moons, Stef (57192940030); van Gils, Teun (57190442923)","15127894700; 24460963600; 57192940030; 57190442923","Using an integrated order picking-vehicle routing problem to study the impact of delivery time windows in e-commerce",2018.0,"European Transport Research Review",10.0,2.0,56.0,null,null,null,13.0,"10.1186/s12544-018-0333-5","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85058849624&doi=10.1186%2fs12544-018-0333-5&partnerID=40&md5=bf9abc80d35fbb232827803d1d3fa61e","Hasselt University, Research Group Logistics, Agoralaan – building D, Diepenbeek, 3590, Belgium","Ramaekers K., Hasselt University, Research Group Logistics, Agoralaan – building D, Diepenbeek, 3590, Belgium; Caris A., Hasselt University, Research Group Logistics, Agoralaan – building D, Diepenbeek, 3590, Belgium; Moons S., Hasselt University, Research Group Logistics, Agoralaan – building D, Diepenbeek, 3590, Belgium; van Gils T., Hasselt University, Research Group Logistics, Agoralaan – building D, Diepenbeek, 3590, Belgium","European e-commerce sales are increasing every year. Nowadays, customers buy more frequently online in smaller quantities. Handling this large amount of customer orders puts the logistic activities of the supply chain under pressure. At the same time, customers have high expectations concerning the delivery of their online purchase. In order to meet these expectations at low cost, B2C e-commerce companies have to reconsider their logistic activities. Instead of optimizing every single process of the supply chain, related problems need to be tackled simultaneously. In the integrated order picking-vehicle routing problem(I-OP-VRP), picking lists and vehicle routes are determined simultaneously. One possibility to meet the high expectations of customers is to allow customers to choose the time window in which they want to be delivered. However, the more customers select a time window during the purchasing process, the higher the total costs for the B2C e-commerce company since the company has less flexibility to construct their delivery routes. To cover the cost increase, e-commerce companies often only provide this service at an additional cost. The objective of this paper is to estimate the additional cost of allowing customers to choose a preferred delivery time window using the integrated order picking-vehicle routing problem. An experimental design is set up to investigate this service cost under varying circumstances depending on customer characteristics, time window characteristics and operator size. Based on the results of the ANOVA it can be concluded that the investigated factors have a significant influence on the additional cost of allowing customers to select a delivery time window. © 2018, The Author(s).","Delivery time windows; E-commerce; Order picking; Pricing; Vehicle routing","Cost benefit analysis; Electronic commerce; Purchasing; Sales; Supply chains; Vehicle routing; Vehicles; Additional costs; Cost-increases; Customer orders; Delivery routes; Delivery time windows; Order picking; Single process; Vehicle Routing Problems; Costs",{"$nulls":4},"Flemish Government department EWI; Flemish Supercomputer Center; Research Foundation – Flanders; VSC; Fonds Wetenschappelijk Onderzoek, FWO","The computational resources and services used in this work were provided by the VSC (Flemish Supercomputer Center), funded by the Research Foundation – Flanders (FWO) and the Flemish Government department EWI.","Industrial change: current situation and prospects - an overall approach, Technical report, (2003); Reshoring of EU industries in the framework of reindustrialisation, Technical report, (2014); Hultkrantz O., Lumsden K., E-commerce and consequences for the logistics industry. Technical Report. Department of Transportation and Logistics, (2001); European ecommerce report 2017, (2017); E-commerce statistics for individuals. Technical report, Eurostat, (2016); European B2C E-commerce report 2016, (2016); de Koster R.M.B.M., Distribution strategies for online retailers, IEEE Trans Eng Manag, 50, (2003); van Gils T., Ramaekers K., Caris A., de Koster R.B.M., Designing efficient order picking systems by combining planning problems: state-of-the-art classification and review, Eur J Oper Res, 267, pp. 1-15, (2018); Moons S., Ramaekers K., Caris A., Arda Y., Integration of order picking and vehicle routing in a B2C e-commerce context, Flexible Services and Manufacturing Journal, 30, 4, pp. 813-843, (2017); Suel E., Polak J.W., Incorporating online shopping into travel demand modelling: challenges, progress, and opportunities, Transp Rev, 38, 5, pp. 576-601, (2018); Crocco F., Eboli L., Mazzulla G., Individual attitudes and shopping mode characteristics affecting the use of E-shopping and related travel, Transport and Telecommunication, 14, 1, pp. 45-56, (2013); Agatz N., Campbell A., Fleischmann M., Savelsbergh M., Time slot management in attended home delivery, Transp Sci, 45, 3, pp. 435-449, (2011); Yang X., Strauss A.K., Currie C.S.M., Eglese R., Choice-based demand management and vehicle routing in E-fulfillment, Transp Sci, 50, 2, pp. 473-488, (2016); Klein R., Neugebauer M., Ratkovitch D., Steinhardt C., Differentiated Time Slot Pricing Under Routing Considerations in Attended Home Delivery, Forthcoming in Transportation Science, (2017); Moons S., Braekers K., Ramaekers K., Caris A., Arda Y., The value of integrating order picking and vehicle routing decisions in a B2C e-commerce environment, submitted to international journal of production research, (2018); Schubert D., Scholz A., Wascher G., Integrated Order Picking and Vehicle Routing with Due Dates, (2017); Zhang J., Wang X., Huang K., Integrated on-line scheduling of order batching and delivery under B2C e-commerce, Comput Ind Eng, 94, pp. 280-289, (2016); Zhang J., Wang X., Huang K., On-line scheduling of order picking and delivery with multiple zones and limited vehicle capacity, Omega, 79, pp. 104-115, (2018); Mangiaracina R., Marchet G., Perotti S., Tumino A., A review of the environmental implications of B2C e-commerce: a logistics perspective, International Journal of Physical Distribution & Logistics Management, 45, 6, pp. 565-591, (2015); Ruben R.A., Jacobs F.R., Batch construction heuristics and storage assignment strategies for walk/ride and pick systems, Manag Sci, 45, pp. 575-596, (1999); Petersen C.G., An evaluation of order picking policies for mail order companies, Prod Oper Manag, 9, pp. 319-335, (2000); Gong Y., de Koster R., A polling-based dynamic order picking system for online retailers, IIE Trans, 40, pp. 1070-1082, (2008); Lu W., McFarlane D., Giannikas V., Zhang Q., An algorithm for dynamic order-picking in warehouse operations, Eur J Oper Res, 248, pp. 107-122, (2016); Cardenas I., Beckers J., Vanelslander T., E-commerce last-mile in Belgium: developing an external cost delivery index, Research in Transportation Business & Management, 24, pp. 123-129, (2017); Blauwens G., de Baere P., van De Voorde E., Cost calculation in a transport firm, Transport Economics, pp. 172-187, (2016); E-green. Technical Report, (2016); Punakivi M., Saranen J., Identifying the success factors in e-grocery home delivery, Int J Retail Distrib Manag, 29, pp. 156-163, (2001); Altarazzi S.A., Ammouri M.M., Concurrent manual-order-picking warehouse design: A simulation-based design of experiments approach, Int J Prod Res, (2018); Geisser S., Greenhouse S.W., An extension of box’ results on the use of the F distribution in multivariate analysis, The Annals of Mathematical Statistics, 29, 3, pp. 885-891, (1958); Glass G.V., Peckham P.D., Sanders J.R., Consequences of failure to meet assumptions underlying the fixed effects analyses of variance and covariance, Rev Educ Res, 42, 3, pp. 237-288, (1972); IMRG UK Consumer Home Delivery Review, (2014)","K. Ramaekers; Hasselt University, Research Group Logistics, Diepenbeek, Agoralaan – building D, 3590, Belgium; email: katrien.ramaekers@uhasselt.be",null,"Springer Verlag",{"$nulls":5},1.8670717E7,null,null,null,"English","Eur. Transp. Res. Rev.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85058849624"]
["Altenried M.","Altenried, Moritz (57202258345)",5.7202258345E10,"On the last mile: Logistical urbanism and the transformation of labour",2019.0,"Work Organisation, Labour and Globalisation",13.0,1.0,null,114.0,129.0,15.0,37.0,"10.13169/workorgalaboglob.13.1.0114","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85068675106&doi=10.13169%2fworkorgalaboglob.13.1.0114&partnerID=40&md5=15c0fa2769bc5dba2770f0a1501fe93f","Institute of Sociology and Cultural Organization (ISCO), Germany; Centre for Digital Cultures (CDC), Leuphana University, Lüneburg, Germany; Berlin Institute for Integration and Migration Research (BIM), Humboldt University, Berlin, Germany","Altenried M., Institute of Sociology and Cultural Organization (ISCO), Germany, Centre for Digital Cultures (CDC), Leuphana University, Lüneburg, Germany, Berlin Institute for Integration and Migration Research (BIM), Humboldt University, Berlin, Germany","In recent years, the last mile of delivery has become a crucial focus of logistical operations in urban contexts due to the rise of online shopping and the spread of platforms including Amazon to Foodora, Deliveroo and others. This article claims that the increasing importance and time-sensitivity of delivery reconfigures both urban spaces and labour relations. Through an analysis of labour relations in different segments of last mile delivery it argues that we are observing profoUnd changes driven most importantly by digital technologies and the hyper-flexible employment relations facilitated by online platforms. Labour on the last mile is increasingly characterised by intense time pressure, standardisation, algorithmic management and digitally enabled surveillance on the one hand, and platform-driven precarisation and flexibilisation on the other. These developments can also be observed in other areas of logistical labour and across different industries. Hence, labour on the last mile might be Understood as a specific but important expression of a broader tendency of the transformation of labour in digital capitalism. At the same time, the new importance of the last mile also signals changes in the production of urban space in the context of platform-driven forms of production, circulation and consumption, that are discussed as an emerging logistical urbanism. © 2019 Moritz Altenried.","Delivery; Digital Taylorism; Gig economy; Labour; Last mile; Logistics; Platforms; Urban space",{"$nulls":5},"Deutsche Forschungsgemeinschaft, DFG, (398798988)","I would like to thank my colleagues Mira Wallis and Manuela Bojadžijev, as well as the anonymous reviewer, for their very helpful and engaging comments. The paper is a product of an ongoing research project on the ‘Digitisation of Labour and Migration’ at Leuphana University, Lüneburg, funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Project Number 398798988.","Allen J., The UPS strike, 20 years later, Jacobin, (2017); Altenried M., Le container et l'algorithme: la logistique dans le capitalisme global, Revue Période, (2016); Altenried M., Die Plattform als Fabrik. Crowdwork, Digitaler Taylorismus Und die Vervielfältigung der Arbeit, PROKLA. Zeitschrift für Kritische Sozialwissenschaft, 47, 2, pp. 175-192, (2017); Bonacich E., Wilson J.B., Getting the Goods: Ports, Labor, and the Logistics Revolution, (2008); Brown P., Lauder H., Ashton D., The Global Auction: The Broken Promises of Education, Jobs, and Incomes, (2012); Bruder J., These workers have a new demand: Stop watching us, The Nation, (2015); KEP-Studie 2017-Analyse des Marktes in Deutschland, (2017); Burnett G.D., Coming full circle, Cabinet, 47, FALL, pp. 73-77, (2012); Cowen D., The Deadly Life of Logistics: Mapping Violence in Global Trade, (2014); De Certeau M., The Practice of Everyday Life, (1984); Frank M., How telematics has completely revolutionized the management of fleet vehicles, Entrepreneur, (2014); Grappi G., Logistica [Logistics], (2016); Haidinger B., On the Move in Global Delivery Chains: Labour Relations and Working Conditions in the Parcel Delivery Industries of Austria, Germany, the Czech Republic and Hungary, (2012); Head S., The New Ruthless Economy: Work and Power in the Digital Age, (2005); Head S., Mindless: Why Smarter Machines Are Making Dumber Humans, (2014); Hern A., Amazon claims first successful Prime Air drone delivery, The Guardian, (2016); Holst H., Singe I., Ungleiche Parallelwelten-Zur Organisation von Arbeit in der Paketzustellung, Arbeits-Und Industriesoziologische Studien, 6, 2, pp. 41-60, (2013); Huws U., Logged labour: A new paradigm of work organisation?, Work Organisation, Labour and Globalisation, 10, 1, pp. 7-26, (2016); Huws U., Spencer N.H., Joyce S., Crowd work in Europe. Preliminary results from a survey in the UK, Sweden, Germany, Austria and the Netherlands, FEPS Studies, (2016); Joerss M., Schroder J., Neuhaus F., Klink C., Mann F., Parcel delivery. The future of the last mile, McKinsey Report, (2016); Kaplan E., The spy who fired me, Harper's Magazine, (2015); Kassi O., Lehdonvirta V., Online labour index: Measuring the online gig economy for policy and research, Internet, Politics & Policy 2016, (2016); Kramer B., Frisse J., Flex Und Fertig, Die Zeit, (2017); LeCavalier J., The Rule of Logistics: Walmart and the Architecture of Fulfillment, (2016); Lopez E., Why is the last mile so inefficient?, Supply Chain Dive, (2017); Lyster C., Learning from Logistics: How Networks Change Our Cities, (2016); Marx K., GrUndrisse: FoUndations of the Critique of Political Economy, (2005); Nachtwey O., Staab P., Die Avantgarde des digitalen Kapitalismus, Mittelweg, 36, 24, pp. 59-84, (2015); Neilson B., Five theses on Understanding logistics as power, Distinktion: Scandinavian Journal of Social Theory, 13, 3, pp. 322-339, (2012); To Increase Productivity, UPS Monitors Drivers' Every Move, (2014); Raffetseder E.-M., Schaupp S., Staab P., Kybernetik Und Kontrolle, PROKLA. 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Restoring Middle-Class Jobs at America's Ports through Labor Law Enforcement, (2014); Staples W.G., Everyday Surveillance: Vigilance and Visibility in Postmodern Life, (2014); Tassinari A., Maccarrone V., Striking the startups, Jacobin, (2017); Tonnesmann J., Ein Land im Lieferkrieg, Die Zeit, (2016); ORION: The algorithm proving that left isn't right, UPS Compass, (2016); Annual Report on Form 10K, SEC Filing for 2017, (2018); Airborne fulfillment center utilizing unmanned aerial vehicles for item delivery, Granted 2016 to Amazon Technologies, Berg et Al, (2014); Woodcock J., Deliveroo and UberEATS: Organising in the gig economy in the UK, Connessione Precarie, (2016)",null,null,"Pluto Journals",{"$nulls":5},"1745641X",null,null,null,"English","Work Organ. Labour Glob.","Article","Final",null,"Scopus","2-s2.0-85068675106"]
["Florio A.M.; Feillet D.; Hartl R.F.","Florio, Alexandre M. (57203999778); Feillet, Dominique (22333489100); Hartl, Richard F. (7005524870)","57203999778; 22333489100; 7005524870","The delivery problem: optimizing hit rates in e-commerce deliveries",2018.0,"Transportation Research Part B: Methodological",117.0,null,null,455.0,472.0,17.0,36.0,"10.1016/j.trb.2018.09.011","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85054020069&doi=10.1016%2fj.trb.2018.09.011&partnerID=40&md5=25050d8307da0505d3fce04b1e229d67","University of Vienna, Oskar-Morgenstern-Platz 1, Vienna, 1090, Austria; École des Mines de Saint-Étienne and UMR CNRS 6158 LIMOS, CMP Georges Charpak, Gardanne, F-13541, France","Florio A.M., University of Vienna, Oskar-Morgenstern-Platz 1, Vienna, 1090, Austria; Feillet D., École des Mines de Saint-Étienne and UMR CNRS 6158 LIMOS, CMP Georges Charpak, Gardanne, F-13541, France; Hartl R.F., University of Vienna, Oskar-Morgenstern-Platz 1, Vienna, 1090, Austria","Unsuccessful delivery attempts, or failed hits, are still a recurring problem in the fulfillment of e-commerce orders to private customers. In this paper, we consider a parcel delivery company interested in optimizing the rate of successful deliveries. By doing so, the company is able to offer a differentiated service, increasing customer satisfaction, and reducing the costs related to failed delivery attempts. In order to achieve this, routes must be designed in a way that visiting times are convenient for the customers. Revisits to some customers may also be planned, so that the expected number of successful deliveries increases. We propose availability profiles to represent the availability of customers during the delivery period. Using these profiles, we are able to compute the expected number of successful hits in a given route. We model the delivery problem as a set-partitioning problem, and solve it with a branch-and-price algorithm. The corresponding pricing problem is solved with a labeling procedure, in which reduced cost bounds are employed to discard unpromising partial routes. We show that the reduced cost of route extensions is bounded by the optimal solution to an orienteering problem, and efficiently compute bounds for that problem within the labeling procedure. Computational experiments demonstrate the effectiveness of the approach for solving instances with up to 100 customers. A tradeoff analysis suggests that significant hit rate improvement can be achieved at the expense of small additional transportation cost. The results also indicate that flexibility regarding maximum route duration translates into an improved hit rate, and that planning revisits may reduce expected unsuccessful deliveries by more than 10%. © 2018 Elsevier Ltd","Branch-and-price; Column generation; e-commerce; Last mile logistics; Small package delivery","Communication channels (information theory); Cost benefit analysis; Cost reduction; Customer satisfaction; Electronic commerce; Integer programming; Linear programming; Sales; Branch and price; Branch-and-price algorithms; Column generation; Computational experiment; Differentiated Services; Last mile; Set partitioning problem; Small package; cost analysis; electronic commerce; optimization; transportation economics; transportation mode; travel time; Problem solving",{"$nulls":6},"Agatz N.A.H., Fleischmann M., Van Nunen J.A.E.E., E-fulfillment and multi-channel distribution–a review, Eur. J. Oper. Res., 187, 2, pp. 339-356, (2008); Barnhart C., Johnson E.L., Nemhauser G.L., Savelsbergh M.W.P., Vance P.H., Branch-and-price: column generation for solving huge integer programs, Oper. Res., 46, 3, pp. 316-329, (1998); Boyer K.K., Prud'homme A.M., Chung W., The last mile challenge: evaluating the effects of customer density and delivery window patterns, J. Bus. Logist, 30, 1, pp. 185-201, (2009); Castillo V.E., Bell J.E., Rose W.J., Rodrigues A.M., Crowdsourcing last mile delivery: strategic implications and future research directions, J. Bus. Logist, (2017); Cattaruzza D., Absi N., Feillet D., Gonzalez-Feliu J., Vehicle routing problems for city logistics, EURO J. Transp. Logist., 6, 1, pp. 51-79, (2017); Chao I.-M., Golden B.L., Wasil E.A., The team orienteering problem, Eur. J. Oper. Res., 88, 3, pp. 464-474, (1996); Desaulniers G., Desrosiers J., Solomon M.M., Column Generation, 5, (2006); Desaulniers G., Madsen O., Ropke S., The vehicle routing problem with time windows, Vehicle Routing: Problems, Methods, and Applications, pp. 119-159, (2014); Dewilde T., Cattrysse D., Coene S., Spieksma F.C.R., Vansteenwegen P., Heuristics for the traveling repairman problem with profits, Comput. Oper. Res., 40, 7, pp. 1700-1707, (2013); Gevaers R., Van de Voorde E., Vanelslander T., Characteristics and typology of last-mile logistics from an innovation perspective in an urban context, City Distribution and Urban Freight Transport: Multiple Perspectives, pp. 56-71, (2011); Goebel P., Moeller S., Pibernik R., Paying for convenience: attractiveness and revenue potential of time-based delivery services, Int. J. Phys. Distrib. Logist. Manage., 42, 6, pp. 584-606, (2012); Golden B.L., Levy L., Vohra R., The orienteering problem, Nav. Res. Logist., 34, 3, pp. 307-318, (1987); Jabali O., Leus R., Van Woensel T., De Kok T., Self-imposed time windows in vehicle routing problems, OR Spectr., 37, 2, pp. 331-352, (2015); Kafle N., Zou B., Lin J., Design and modeling of a crowdsource-enabled system for urban parcel relay and delivery, Transp. Res. Part B, 99, pp. 62-82, (2017); Kamarainen V., Saranen J., Holmstrom J., The reception box impact on home delivery efficiency in the e-grocery business, Int. J. Phys. Distrib. Logist. Manage., 31, 6, pp. 414-426, (2001); Laporte G., Martello S., The selective travelling salesman problem, Discrete Appl. Math., 26, 2-3, pp. 193-207, (1990); Lubbecke M.E., Desrosiers J., Selected topics in column generation, Oper. Res., 53, 6, pp. 1007-1023, (2005); Mangiaracina R., Marchet G., Perotti S., Tumino A., A review of the environmental implications of B2C e-commerce: a logistics perspective, Int. J. Phys. Distrib. Logist. Manage., 45, 6, pp. 565-591, (2015); McLeod F., Cherrett T., Song L., Transport impacts of local collection/delivery points, Int. J. Logist., 9, 3, pp. 307-317, (2006); Morganti E., Seidel S., Blanquart C., Dablanc L., Lenz B., The impact of e-commerce on final deliveries: alternative parcel delivery services in France and Germany, Transp. Res. Procedia, 4, pp. 178-190, (2014); Murat Afsar H., Labadie N., Team orienteering problem with decreasing profits, Electron. Notes Discrete Math., 41, pp. 285-293, (2013); Ozbaygin G., Karasan O.E., Savelsbergh M.W.P., Yaman H., A branch-and-price algorithm for the vehicle routing problem with roaming delivery locations, Transp. Res. Part B, 100, pp. 115-137, (2017); Pan S., Giannikas V., Han Y., Grover-Silva E., Qiao B., Using customer-related data to enhance e-grocery home delivery, Ind. Manage. Data Syst., 117, 9, pp. 1917-1933, (2017); Punakivi M., Saranen J., Identifying the success factors in e-grocery home delivery, Int. J. Retail Distrib. Manage., 29, 4, pp. 156-163, (2001); Rao S., Rabinovich E., Raju D., The role of physical distribution services as determinants of product returns in internet retailing, J. Oper. Manage., 32, 6, pp. 295-312, (2014); Reyes D., Savelsbergh M.W.P., Toriello A., Vehicle routing with roaming delivery locations, Transp. Res. Part C: Emerg. Technol., 80, pp. 71-91, (2017); Ryan D.M., Foster B.A., An integer programming approach to scheduling, Computer scheduling of public transport urban passenger vehicle and crew scheduling, pp. 269-280, (1981); Savelsbergh M.W.P., Van Woensel T., 50th anniversary invited article–city logistics: challenges and opportunities, Transp. Sci., 50, 2, pp. 579-590, (2016); Schneider M., Stenger A., Schwahn F., Vigo D., Territory-based vehicle routing in the presence of time-window constraints, Transp. Sci., 49, 4, pp. 732-751, (2014); Song L., Cherrett T., McLeod F., Guan W., Addressing the last mile problem: transport impacts of collection and delivery points, Transp. Res. Rec., 2097, pp. 9-18, (2009); Sungur I., Ren Y., Ordonez F., Dessouky M., Zhong H., A model and algorithm for the courier delivery problem with uncertainty, Transp. Sci., 44, 2, pp. 193-205, (2010); Uchoa E., Pecin D., Pessoa A., Poggi M., Vidal T., Subramanian A., New benchmark instances for the capacitated vehicle routing problem, Eur. J. Oper. Res., 257, 3, pp. 845-858, (2017); Van Duin J.H.R., De Goffau W., Wiegmans B., Tavasszy L.A., Saes M., Improving home delivery efficiency by using principles of address intelligence for B2C deliveries, Transp. Res. Procedia, 12, pp. 14-25, (2016); Vanelslander T., Deketele L., Van Hove D., Commonly used e-commerce supply chains for fast moving consumer goods: comparison and suggestions for improvement, International Journal of Logistics Research and Applications, 16, 3, pp. 243-256, (2013); Weltevreden J.W.J., B2C e-commerce logistics: the rise of collection-and-delivery points in The Netherlands, Int. J. Retail Distrib. Manage., 36, 8, pp. 638-660, (2008); Wong R.T., Vehicle routing for small package delivery and pickup services, The Vehicle Routing Problem: Latest Advances and New Challenges, 43, pp. 475-485, (2008); Xu M., Ferrand B., Roberts M., The last mile of e-commerce–unattended delivery from the consumers and etailers’ perspectives, Int. J. Electron. Market. Retail., 2, 1, pp. 20-38, (2008); Zhang J., Lam W.H.K., Chen B.Y., On-time delivery probabilistic models for the vehicle routing problem with stochastic demands and time windows, Eur. J. Oper. Res., 249, 1, pp. 144-154, (2016)","A.M. Florio; University of Vienna, Vienna, Oskar-Morgenstern-Platz 1, 1090, Austria; email: alexandre.de.macedo.florio@univie.ac.at",null,"Elsevier Ltd",{"$nulls":5},1912615.0,null,null,null,"English","Transp. Res. Part B Methodol.","Article","Final",null,"Scopus","2-s2.0-85054020069"]
["Qi W.; Li L.; Liu S.; Shen Z.-J.M.","Qi, Wei (57200731190); Li, Lefei (14070354800); Liu, Sheng (57203730003); Shen, Zuo-Jun Max (8947426700)","57200731190; 14070354800; 57203730003; 8947426700","Shared mobility for last-mile delivery: Design, operational prescriptions, and environmental impact",2018.0,"Manufacturing and Service Operations Management",20.0,4.0,null,737.0,751.0,14.0,110.0,"10.1287/msom.2017.0683","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85052613307&doi=10.1287%2fmsom.2017.0683&partnerID=40&md5=9bcb75baed3feec3b77d843288ab1e3c","Desautels Faculty of Management, McGill University, Montreal, H3A 1G5, QC, Canada; Department of Industrial Engineering, Tsinghua University, Be ing, 100084, China; Department of Industrial Engineering and Operations Research, University of California, Berkeley, Berkeley, 94720, CA, United States; Department of Civil and Environmental Engineering, University of California, Berkeley, Berkeley, 94720, CA, United States","Qi W., Desautels Faculty of Management, McGill University, Montreal, H3A 1G5, QC, Canada; Li L., Department of Industrial Engineering, Tsinghua University, Be ing, 100084, China; Liu S., Department of Industrial Engineering and Operations Research, University of California, Berkeley, Berkeley, 94720, CA, United States; Shen Z.-J.M., Department of Industrial Engineering and Operations Research, University of California, Berkeley, Berkeley, 94720, CA, United States, Department of Civil and Environmental Engineering, University of California, Berkeley, Berkeley, 94720, CA, United States","Two socioeconomic transformations, namely, the booms in the sharing economy and retail e-commerce, lead to the prospect where shared mobility of passenger cars prevails throughout urban areas for home delivery services. Logistics service providers as well as local governments are in need of evaluating the potentially substantial impacts of this mode shift, given their economic objectives and environmental concerns. This paper addresses this need by providing new logistics planning models and managerial insights. These models characterize open-loop car routes, car drivers’ wage-response behavior, interplay with the ride-share market, and optimal sizes of service zones within which passenger vehicles pick up goods and fulfill the last-mile delivery. Based on theoretical analysis and empirical estimates in a realistic setting, the findings suggest that crowdsourcing shared mobility is not as scalable as the conventional truck-only system in terms of the operating cost. However, a transition to this paradigm has the potential for creating economic benefits by reducing the truck fleet size and exploiting additional operational flexibilities (e.g., avoiding high-demand areas and peak hours, adjusting vehicle loading capacities, etc.). These insights are insignificantly a ected by the dynamic adjustment of wages and prices of the ride-share market. If entering into this paradigm, greenhouse gas emissions may increase because of prolonged car trip distance; on the other hand, even exclusively minimizing operating costs incurs only slightly more emissions than exclusively minimizing emissions. © 2018 INFORMS.","Logistics planning; Open vehicle routing problem; Shared mobility; Sustainability","Commerce; Cost benefit analysis; Fleet operations; Gas emissions; Greenhouse gases; Operating costs; Sustainable development; Trucks; Urban planning; Vehicle routing; Wages; Economic objectives; Environmental concerns; Home delivery services; Logistics planning; Logistics service provider; Open vehicle routing problems; Operational flexibility; Socio-economic transformations; Environmental impact",{"$nulls":4},"National Science Foundation, NSF, (CMMI 1265671)","Funding:This study was partially supported by the National Science Foundation [Grant CMMI 1265671]. SupplementalMaterial: The online appendix is available at https://doi.org/10.1287/msom.2017.0683.","Agatz N., Erera A., Savelsbergh M., Wang X., Optimization for dynamic ride-sharing: A review, Eur. J. Oper. Res., 223, 2, pp. 295-303, (2012); The California Global Warming Solutions Act of 2006, (2006); Bellos I., Ferguson M., Toktay L.B., The car sharing economy: Interaction of business model choice and product line design, Manufacturing Service Oper. Management, 19, 2, pp. 185-201, (2017); Botsman R., Crowdshipping: Using the crowd to transform delivery, AFR Boss Magazine, (2014); Cachon G.P., Retail store density and the cost of greenhouse gas emissions, Management Sci, 60, 8, pp. 1907-1925, (2014); Cachon G.P., Daniels K.M., Lobel R., The role of surge pricing on a service platform with self-scheduling capacity, Manufacturing Service Oper. 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Res., 238, 1, pp. 31-40, (2014); Li B., Krushinsky D., Van Woensel T., Re ers H.A., An adaptive large neighborhood search heuristic for the share-a-ride problem, Comput. Oper. Res., 66, February, pp. 170-180, (2016); Li F., Golden B., Wasil E., The open vehicle routing problem: Algorithms, large-scale test problems, and computational results, Comput. Oper. Res., 34, 10, pp. 2918-2930, (2007); Ouyang Y., Daganzo C.F., Discretization and validation of the continuum approximation scheme for terminal system design, Transportation Sci, 40, 1, pp. 89-98, (2006); The Sharing Economy—Consumer Intelligence Series, (2015); Roug s J.F., Montreuil B., Crowdsourcing delivery: New interconnected business models to reinvent delivery, 1st Internat. Physical Internet Conf., pp. 1-19, (2014); Schaefer B., Konur D., Economic and environmental considerations in a continuous review inventory control system with integrated transportation decisions, Transportation Res. Part E: Logist. Transportation Rev., 80, pp. 142-165, (2015); Shu J., Chou M.C., Liu Q., Teo C.P., Wang I.L., Models for e ective deployment and redistribution of bicycles within public bicycle-sharing systems, Oper. Res., 61, 6, pp. 1346-1359, (2013); Xie W., Ouyang Y., Optimal layout of transshipment facility locations on an infinite homogeneous plane, Transportation Res. Part B: Methodological, 75, pp. 74-88, (2015); Yang H., Fung C.S., Wong K.I., Wong S.C., Nonlinear pricing of taxi services, Transportation Res. Part A: Policy and Practice, 44, 5, pp. 337-348, (2010); Yang H., Ye M., Tang W.H., Wong S.C., Regulating taxi services in the presence of congestion externality, Transportation Res. Part A: Policy and Practice, 39, 1, pp. 17-40, (2005)",null,null,"INFORMS Inst.for Operations Res.and the Management Sciences",{"$nulls":5},1.5234614E7,null,"MSOMF",null,"English","Manuf. Serv. Oper. Manage.","Article","Final",null,"Scopus","2-s2.0-85052613307"]
["Zhuang Y.; Sun Y.; Yu M.; Hu X.","Zhuang, Yanling (57204676600); Sun, Yujiao (57189069648); Yu, Mengqi (57204670903); Hu, Xiangpei (24481299300)","57204676600; 57189069648; 57204670903; 24481299300","A path selection model for multimodal transportation problem of fresh fruits in online supermarket",2019.0,"ICIC Express Letters",13.0,3.0,null,201.0,208.0,7.0,4.0,"10.24507/icicel.13.03.201","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85062350559&doi=10.24507%2ficicel.13.03.201&partnerID=40&md5=884e2f2c771cd69e861cc7f2bf3bba78","Institute of Systems and Engineering, Dalian University of Technology, No. 2, Linggong Road, Ganjingzi District, Dalian, 116024, China","Zhuang Y., Institute of Systems and Engineering, Dalian University of Technology, No. 2, Linggong Road, Ganjingzi District, Dalian, 116024, China; Sun Y., Institute of Systems and Engineering, Dalian University of Technology, No. 2, Linggong Road, Ganjingzi District, Dalian, 116024, China; Yu M., Institute of Systems and Engineering, Dalian University of Technology, No. 2, Linggong Road, Ganjingzi District, Dalian, 116024, China; Hu X., Institute of Systems and Engineering, Dalian University of Technology, No. 2, Linggong Road, Ganjingzi District, Dalian, 116024, China","Multimodal transportation, as an effective way and method to improve the transport efficiency of the fresh fruits in online supermarket, involves a complicated decision process. Its complexity is of threefold: the unique transportation network structure of online supermarket, the multiple demands of each warehouse, and the restrictions of transshipment times and the delivery time. A mixed integer programming model of multimodal routing problem for fresh fruits in online supermarket is proposed in this paper using Demand Split Method. The objective is to minimize the total cost of online supermarket considering multiple origins, destinations, and products, and the restriction of transshipment times. The effectiveness of the proposed model is evaluated by a case study of an online supermarket. Results indicate that the proposed model can contribute to scientific decisions on multimodal transportation of online supermarket. © 2019, ICIC International. All rights reserved.","E-commerce; Fresh fruits; Multimodal routing problem; Multimodal transportation; Path selection",{"$nulls":5},"Innovative Research Group Project of the National Natural Science Foundation of China, AIC, (71421001); National Natural Science Foundation of China, NSFC","Funding text 1: Acknowledgment. This work is supported by the National Natural Science Foundation Innovation Research Group Project of China (NO. 71421001). The authors also gratefully acknowledge the helpful comments and suggestions of the reviewers, which have improved the quality of this paper.; Funding text 2: This work is supported by the National Natural Science Foundation Innovation Research Group Project of China (NO. 71421001). The authors also gratefully acknowledge the helpful comments and suggestions of the reviewers, which have improved the quality of this paper.","Chang T., Best routes selection in international intermodal networks, Computers & Operations Research, 35, 9, pp. 2877-2891, (2008); Ayar B., Yaman H., An intermodal multicommodity routing problem with scheduled services, Computational Optimization and Applications, 53, 1, pp. 131-153, (2012); Steadieseifi M., Dellaert N.P., Nuijten W., Et al., Multimodal freight transportation planning: A literature review, European Journal of Operational Research, 233, 1, pp. 1-15, (2014); Yamada T., Russ B.F., Castro J., Et al., Designing multimodal freight transport networks: A heuristic approach and applications, Transportation Science, 43, 2, pp. 129-143, (2009); Bouchery Y., Fransoo J., Cost, carbon emissions and modal shift in intermodal network design decisions, International Journal of Production Economics, 164, pp. 388-399, (2015); Wang X., Meng Q., Discrete intermodal freight transportation network design with route choice behavior of intermodal operators, Transportation Research Part B: Methodological, 95, pp. 76-104, (2017); Garcia J., Florez J.E., Torralba A., Et al., Combining linear programming and automated planning to solve intermodal transportation problems, European Journal of Operational Research, 227, 1, pp. 216-226, (2013); Sun Y., Lang M., Modeling the multicommodity multimodal routing problem with schedule-based services and carbon dioxide emission costs, Mathematical Problems in Engineering, 2015, pp. 1-21, (2015); Lelen P., Wasiak M., Optimization of multimodal transport technologies selection for packed non-climacteric vegetables and fruits, Proc. of the 14Th Scientific and Technical Conference Transport Systems Theory & Practice, Katowice, Poland, pp. 203-215, (2017)",null,null,"ICIC International",{"$nulls":5},"1881803X",null,null,null,"English","ICIC Express Lett.","Article","Final",null,"Scopus","2-s2.0-85062350559"]
["Yu J.; Gan M.; Ni S.; Chen D.","Yu, Juan (56701057000); Gan, Mi (25927121800); Ni, Shaoquan (24402553300); Chen, Dingjun (7405451877)","56701057000; 25927121800; 24402553300; 7405451877","Multi-objective models and real case study for dual-channel FAP supply chain network design with fuzzy information",2018.0,"Journal of Intelligent Manufacturing",29.0,2.0,null,389.0,403.0,14.0,24.0,"10.1007/s10845-015-1115-8","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85041502040&doi=10.1007%2fs10845-015-1115-8&partnerID=40&md5=87504d94024c4aa733983360d903049a","School of Transportation and Logistics, Southwest Jiaotong University, Chengdu, 610031, China; Department of business, Zhengzhou Chenggong University of Finance and Economics, Zhengzhou, 451200, China","Yu J., School of Transportation and Logistics, Southwest Jiaotong University, Chengdu, 610031, China, Department of business, Zhengzhou Chenggong University of Finance and Economics, Zhengzhou, 451200, China; Gan M., School of Transportation and Logistics, Southwest Jiaotong University, Chengdu, 610031, China; Ni S., School of Transportation and Logistics, Southwest Jiaotong University, Chengdu, 610031, China; Chen D., School of Transportation and Logistics, Southwest Jiaotong University, Chengdu, 610031, China","This paper studies on the dual-channel (the traditional channel and the E-commerce channel) supply chain network design (SCND) for fresh agri-product (FAP) under information uncertainty. The model is to solve the integration network design issues about production, supply, and sales of FAP, as well as to minimize the supply chain operation cost and maximizing the satisfaction degree of the logistics demand between supply chain (SC) nodes simultaneously. First, the triangular-fuzzy-number is used to depict the information uncertainty in the SCND. Then the handling cost of wasted FAP and quantitative traceability cost of FAP are considered in addition to the regular transportation cost and fixed cost for facility location, which makes it more closely and suitable for the real case when compared with the models in existing literatures. Due to there is always a lower and upper bound for delivery time of each logistics demand node in SC in real life. This problem is then formulated as an attenuation function, for depicting the satisfaction degree in each demand node. Afterwards, the multi-objective planning method is utilized to represent the mutual trade-off among supply-chain participants. The proposed models are solved with two-phase method to guarantee the optimality of the solution. Finally, the effectiveness and applicability of the proposed models and algorithm are validated with a real case. The result shows the presented SCND models can guide relevant enterprises to make optimize decisions with fuzzy information. © 2015, Springer Science+Business Media New York.","Dual-channel supply chain network design; Fuzzy multi-objective two-phase algorithm; Fuzzy supply chain optimization; Supply chain management; Time sensitive products","Costs; Economic and social effects; Fuzzy sets; Optimization; Supply chain management; Transportation; Dual channel supply chain; Multi-objective planning; Supply chain network design; Supply chain operation; Supply chain optimization; Time sensitive products; Triangular fuzzy numbers; Two phase algorithm; Product design",{"$nulls":4},"Sichuan province cyclic economy research program, (XHJJ-1411); Soft science foundation of Sichuan province STA, (2014ZR0019, 2015ZR0141); National Natural Science Foundation of China, NSFC, (71403225); Natural Science Foundation of Shaanxi Province; Fundamental Research Funds for the Central Universities, (SWJTU12CX114)","Funding text 1: The work is supported by the Nature Science Foundation of China (Grant No. 71403225) Fundamental Research Funds for the Central Universities (Grant No. SWJTU12CX114). And the Soft science foundation of Sichuan province STA of China (Grant Nos. 2014ZR0019 and 2015ZR0141) and Sichuan province cyclic economy research program (Grant No. XHJJ-1411). The authors declare that there is no conflict of interests regarding the publication of this article.; Funding text 2: Acknowledgements The work is supported by the Nature Science Foundation of China (Grant No. 71403225) Fundamental Research Funds for the Central Universities (Grant No. SWJTU12CX114). And the Soft science foundation of Sichuan province STA of China (Grant Nos. 2014ZR0019 and 2015ZR0141) and Sichuan province cyclic economy research program (Grant No. XHJJ-1411).","Aung M.M., Chang Y.S., Traceability in a food supply chain: Safety and quality perspectives, Food Control, 39, pp. 172-184, (2014); Ayag Z., Samanlioglu F., Buyukozkan G., A fuzzy QFD approach to determine supply chain management strategies in the dairy industry, Journal of Intelligent Manufacturing, 24, 5, pp. 1111-1122, (2013); Ballou R.H., Dynamic warehouse location analysis, Journal of Marketing Research (JMR), 5, 3, pp. 271-276, (1968); Berman O., Krass D., Drezner Z., The gradual covering decay location problem on a network, European Journal of Operational Research, 151, 3, pp. 474-480, (2003); Berman O., Wang J., Probabilistic location problems with discrete demand weights, Networks, 44, 1, pp. 47-57, (2004); Berman O., Wang J., The probabilistic 1-maximal covering problem on a network with discrete demand weights, Journal of the Operational Research Society, 59, 10, pp. 1398-1405, (2008); Bosona T., Gebresenbet G., Food traceability as an integral part of logistics management in food and agricultural supply chain, Food Control, 33, 1, pp. 32-48, (2013); Chern C.-C., Lei S.-T., Huang K.-L., Solving a multi-objective master planning problem with substitution and a recycling process for a capacitated multi-commodity supply chain network, Journal of Intelligent Manufacturing, 25, 1, pp. 1-25, (2014); Gan M., Lin W.-H., The effect of demand representation on locating facilities in a supply chain network, In 2010 IEEE international conference on service operations and logistics and informatics, (2010); Gan M., Chen S., Yan Y., The effect of roadway capacity expansion on facility sitting, Applied Mathematics & Information Sciences, 7, 2L, pp. 575-581, (2013); Gan M., Li Z., Chen S., On the transformation mechanism for formulate a multi-product two-layer supply chain network design problem as a network flow model, Mathematical Problems in Engineering, 2014, (2014); Gustavsson J., Cederberg C., Sonesson U., Van Otterdijk R., Meybeck A., Global food losses and food waste, (2011); Hiremath N.C., Sahu S., Tiwari M.K., Multi objective outbound logistics network design for a manufacturing supply chain, Journal of Intelligent Manufacturing, 24, 6, pp. 1071-1084, (2013); Jouzdani J., Sadjadi S.J., Fathian M., Dynamic dairy facility location and supply chain planning under traffic congestion and demand uncertainty: A case of Tehran, Applied Mathematical Modelling, (2013); Lai Y.-J., Hwang C.-L., A new approach to some possibilistic linear programming problems, Fuzzy Sets and Systems, 49, 2, pp. 121-133, (1992); Liang T.-F., Integrating production-transportation planning decision with fuzzy multiple goals in supply chains, International Journal of Production Research, 46, 6, pp. 1477-1494, (2008); Liang C.-J., Chen M., Gen M., Jo J., A multi-objective genetic algorithm for yard crane scheduling problem with multiple work lines, Journal of Intelligent Manufacturing, 25, 5, pp. 1013-1024, (2014); Liao S.-H., Hsieh C.-L., Lai P.-J., An evolutionary approach for multi-objective optimization of the integrated location-inventory distribution network problem in vendor-managed inventory, Expert Systems with Applications, 38, 6, pp. 67-76, (2011); Li X., Zhang B., Li H., Computing efficient solutions to fuzzy multiple objective linear programming problems, Fuzzy Sets and Systems, 157, 10, pp. 1328-1332, (2006); Manzini R., Bindi F., Strategic design and operational management optimization of a multi stage physical distribution system, Transportation Research Part E: Logistics and Transportation Review, 45, 6, pp. 915-936, (2009); Mohammadi Bidhandi H., Mohd Yusuff R., Megat Ahmad M.M.H., Abu Bakar M.R., Development of a new approach for deterministic supply chain network design, European Journal of Operational Research, 198, 1, pp. 121-128, (2009); Nagurney A., Masoumi A.H., Yu M., Supply chain network operations management of a blood banking system with cost and risk minimization, Computational Management Science, 9, 2, pp. 205-231, (2012); Paksoy T., Pehlivan N.Y., Ozceylan E., Application of fuzzy optimization to a supply chain network design: A case study of an edible vegetable oils manufacturer, Applied Mathematical Modelling, 36, 6, pp. 2762-2776, (2012); Rui L.I., The distribution and consideration of chinese agriculture product, Modern Economic Information, 16, (2010); Stanley Lee E., Li R.J., Fuzzy multiple objective programming and compromise programming with Pareto optimum, Fuzzy Sets and Systems, 53, 3, pp. 275-288, (1993); Talluri S., Baker R., A multi-phase mathematical programming approach for effective supply chain design, European Journal of Operational Research, 141, 3, pp. 544-558, (2002); Wang C.-H., Tsai S.-W., Optimizing bi-objective imperfect preventive maintenance model for series-parallel system using established hybrid genetic algorithm, Journal of Intelligent Manufacturing, 25, 3, pp. 603-616, (2013); Widodo K., Nagasawa H., Morizawa K., Ota M., A periodical flowering-harvesting model for delivering agricultural fresh products, European Journal of Operational Research, 170, 1, pp. 24-43, (2006); Yang L., Deuse J., Jiang P., Multi-objective optimization of facility planning for energy intensive companies, Journal of Intelligent Manufacturing, 24, 6, pp. 1095-1109, (2013); Yu M., Nagurney A., Competitive food supply chain networks with application to fresh produce, European Journal of Operational Research, 224, 2, pp. 273-282, (2013); Zhao D., Wang Y., Sheng S., Lin Z., Multi-objective optimal design of small scale resistance spot welding process with principal component analysis and response surface methodology, Journal of Intelligent Manufacturing, 25, 6, pp. 1335-1348, (2014); Zimmermann H.-J., Fuzzy programming and linear programming with several objective functions, Fuzzy Sets and Systems, 1, 1, pp. 45-55, (1978)","M. Gan; School of Transportation and Logistics, Southwest Jiaotong University, Chengdu, 610031, China; email: migan@swjtu.cn",null,"Springer New York LLC",{"$nulls":5},9565515.0,null,"JIMNE",null,"English","J Intell Manuf","Article","Final",null,"Scopus","2-s2.0-85041502040"]
["Dai Y.","Dai, Yu (57206475678)",5.7206475678E10,"Exploring the scale application of internet of things in the field of smart logistics",2018.0,"IPPTA: Quarterly Journal of Indian Pulp and Paper Technical Association",30.0,7.0,null,414.0,418.0,4.0,2.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85061749795&partnerID=40&md5=0635f869402faf44b9962d720ed89818","School of Marxism, Yellow River Conservancy Technical Institute, Kaifeng, China","Dai Y., School of Marxism, Yellow River Conservancy Technical Institute, Kaifeng, China","With the development of information technology, the Internet of Things has gradually become a part of people's work and life, and has penetrated into various fields and levels of society. The logistics industry has also developed rapidly. This paper, from the perspective of the sustainable and healthy development of logistics and the Internet of Things, combined with the current situation of logistics development at home and abroad, analyzes the intelligent logistics system architecture based on the Internet of Things, and points out the key technologies used by the Internet of Things in smart logistics. Finally, the issue of intelligent logistics application based on the Internet of Things in the era of big data is explained and constructive opinions are put forward. The research of this paper aims to effectively solve the dilemma of China's logistics industry, reduce logistics costs to a certain extent, improve logistics management efficiency and service level, and create modern intelligent logistics. Realize the better integration of the logistics industry and the modern Internet industry, and promote the construction process of China's smart logistics. Therefore, it is necessary and significant to study the large-scale application of the intelligent logistics field in the Internet of Things era. © Indian Pulp and Paper Technical Association. All rights reserved.","E-commerce; Internet of things; Large-scale application; Smart logistics","Application; Development; Integration; Internet; Life; Management; Materials Handling; Paper; Processes; Electronic commerce; Internet of things; Construction process; Current situation; Internet industries; Large-scale applications; Logistics development; Logistics industry; Logistics management; Logistics system; Logistics",{"$nulls":6},"Yawei C., Zhenhua X., Comparison between Traditional Escort and Third Party Logistics, China Storage and Transportation, 8, pp. 102-103, (2008); Fang R., The application of Internet of Things technology in the field of logistics is promising, Logistics Technology and Application, 22, 6, pp. 84-87, (2017); Lingfeng W., The Age of Internet of Things-The Transformation of Logistics Informationization and Wisdom, Air Transport Business, 18, pp. 30-32, (2010); Xiaoliang C., Chulin W., Smart Logistics Extends from Platform to Supply Chain, Internet Economy, 11, pp. 20-25, (2017); Yifang C., Shunlin W., Research on Matching of Logistics Service Capabilities and Data Mining-Based on Comparative Analysis of Traditional Logistics Informationization and Smart Logistics, Journal of Logistics Science, 38, 11, pp. 79-82, (2015); Yibo Z., Song D., The Strategy of Traditional Logistics Transformation to Smart Logistics, Open Herald, 6, pp. 105-109, (2017); Leonard D., Building and Sustaining the Sources of INNOVATION: An interview with Dorothy Leonard, Strategy\\&Leadership, 25, 4, pp. 22-27, (1997); Guolong L., Bowersox D.J., Et al., Logistics Management: Integration of Supply Chain Process [M), (1999); Guoxiong H., The integration effect of modern logistics, Shopping Mall Modernization, 12, pp. 18-19, (2000); Zuo W., On the Resource Integration of Logistics Enterprises, China Logistics and Purchasing, 22, pp. 8-15, (2002); Rappa M., Managing The Digital Enterprise-Business Models on The Web, (2001); Biehl M., Success factors for implementing global information systems, Communications of The ACM, 1, pp. 52-58, (2007); Yuqing P., Yehua S., Guiying Z., A Framework of General Logistics Platform Based on WebGIS, Microcomputer Information, 30, pp. 202-203, (2008); Wenqing Z., Jieming W., A new method for obtaining vehicle source information: Real-time intelligent matching platform for logistics information, Logistics Technology, z1, pp. 190-192, (2010); Morash E.A.C.L., Strategic logistics capabilities for competitive advantage and firm success, Journal of Business Logistics, 17, pp. 1-22, (1996); Juan D., Research on Logistics Operation Efficiency Based on Market Matching Rate, (2011); Zhaokang W., Min M., Research on the comprehensive weight model of distribution network based on supply-demand matching degree, Business Times, 23, pp. 34-35, (2011); Peng Y.-T., Zhang J., Wang K., Research on Logistics Super Network Optimization Model with Random Supply and Demand Characteristics, Transportation Systems Engineering and Information, 2, pp. 184-191, (2014); Dan W., Research on Distribution Network Evaluation Model Based on Supply and Demand Matching, Science and Technology Rich, 24, (2012); Jie G., Qinglan Z., Zhijun C., Discussion on the Application of Internet of Things Technology in the Field of Product Oil Sales, Information Systems Engineering, 10, pp. 88-89, (2017); Guohou L., Exploring the application of mobile communication technology in the Internet of Things, Communication World, 9, pp. 78-79, (2017); Yang Z., Internet of Things: Development must not miss the opportunity, Science and Technology and Economics Illustrated, 6, pp. 32-34, (2009); Bingbing L., Analysis of China's Logistics Informatization Process, Foreign Trade and Economics, 9, pp. 109-110, (2012); Xiaoxia L., Application of Internet of Things in Logistics Traceability Service, Logistics Technology, 32, 8, pp. 252-254, (2013); Tongzhou L., Internet of Things to Promote Smart Logistics-Interview with Wang Jixiang, China Ocean Shipping, 3, pp. 44-47, (2012); Xia H., Research on Logistics Management Optimization of Tobacco Companies Based on Internet of Things Technology, (2014); Shuang Z., Qinghe H., Dingwei W., Research on Decision Support System of Supply Chain Based on Agent, Journal of Computer Research and Development, 43, z1, pp. 000404-000408, (2006)",null,null,"Indian Pulp and Paper Technical Association",{"$nulls":5},3795462.0,null,"IPPTD",null,"English","IPPTA","Article","Final",null,"Scopus","2-s2.0-85061749795"]
["Song Z.; He S.; Xu G.","Song, Zilong (57203853864); He, Shiwei (7402690970); Xu, Guangshu (36702263700)","57203853864; 7402690970; 36702263700","Decision and coordination of fresh produce three-layer e-commerce supply chain: A new framework",2019.0,"IEEE Access",7.0,null,8533337.0,30465.0,30486.0,21.0,20.0,"10.1109/ACCESS.2018.2881106","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85056594925&doi=10.1109%2fACCESS.2018.2881106&partnerID=40&md5=8d14f7eb646a096052129ee8dc2b44db","MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, Beijing Jiaotong University, Beijing, 100044, China; School of Traffic and Transportation, Beijing Jiaotong University, Beijing, 100044, China; School of Logistics, Beijing Wuzi University, Beijing, 101149, China","Song Z., MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, Beijing Jiaotong University, Beijing, 100044, China; He S., School of Traffic and Transportation, Beijing Jiaotong University, Beijing, 100044, China; Xu G., School of Logistics, Beijing Wuzi University, Beijing, 101149, China","This paper considers a fresh produce three-layer e-commerce supply chain consisting of a producer, a third-party logistics service provider, and a fresh produce e-commerce enterprise in a new framework. The market demand for the fresh produce is affected by the safety traceability system availability, the freshness level, the unit online selling price, and the random factor. We develop the game models under different supply chain decision scenarios. Two different types of contracts, namely, unilateral cost-sharing and revenue-sharing contract, and consolidated rebate and revenue-sharing contract are proposed to facilitate coordination of the supply chain. The impact of the changes of market preferences on the supply chain decisions, the supply chain profits, and the contract policies implementation is examined. The theoretical derivations and results are illustrated with numerical examples. While enriching the relevant literature, this paper also provides a practical guidance for the production, operation, and sales of the fresh produce e-commerce supply chain. © 2019 IEEE.","coordination contract; Fresh produce; fresh produce e-commerce enterprise; safety traceability system availability; supply chain management","Accident prevention; Availability; Contracts; Cost effectiveness; Investments; Outsourcing; Safety factor; Supply chain management; Supply chains; E-commerce enterprise; Fresh produce; On-line Selling; Practical guidance; Revenue sharing contracts; Theoretical derivations; Third party logistics; Traceability systems; Electronic commerce",{"$nulls":4},"China Railway Company, (2017X004-D, 2017X004-E); Research Project of China Railway Company; National Natural Science Foundation of China, NSFC, (61374202); National Basic Research Program of China (973 Program), (2016YFE0201700, 2018YFB1201402)","This work was supported in part by the National Key Research and Development Program of China under Grants 2018YFB1201402 and 2016YFE0201700, in part by the National Natural Science Foundation of China under Grant 61374202, and in part by the Research Project of China Railway Company under Grants 2017X004-D and 2017X004-E.","The Scale of Fresh Produce E-Commerce of China in 2017 Was CNY 140.28 Billion; Liu G., Zhang J., Tang W., Joint dynamic pricing and investment strategy for perishable foods with price-quality dependent demand, Ann. 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Eng, 80, pp. 274-283, (2015); Chen X., Hao G., Li L., Channel coordination with a loss-averse retailer and option contracts, Int. J. Prod. Econ, 150, pp. 52-57, (2014); Giannoccaro L., Pontrandolfo P., Supply chain coordination by revenue sharing contracts, Int. J. Prod. Econ, 89, 2, pp. 131-139, (2004); Xiao T., Yang D., Shen H., Coordinating a supply chain with a quality assurance policy via a revenue-sharing contract, Int. J. Prod. Res, 49, 1, pp. 99-120, (2011); Chen X., Wan N., Wang X., Flexibility and coordination in a supply chain with bidirectional option contracts and service requirement, Int. J. Prod. Econ, 193, pp. 183-192, (2017); Anupindi R., Bassok Y., Centralization of stocks: Retailers vs. Manufacturer, Manage. Sci, 45, 2, pp. 91-178, (1999); Huang X., Choi S.-M., Ching W.-K., Siu T.-K., Huang M., On supply chain coordination for false failure returns: A quantity discount contract approach, Int. J. Prod. Econ, 133, 2, pp. 634-644, (2011); Palsule-Desai O.D., Supply chain coordination using revenue-dependent revenue sharing contracts, Omega, 41, 4, pp. 780-796, (2013); Xiong H., Xiong B., Xie J., A composite contract based on buy back and quantity fiexibility contracts, Eur. J. Oper. Res, 210, 3, pp. 559-567, (2011); Krishan H., Kapuscinski R., Butz D.A., Coordinating contracts for decentralized supply chains with retailer promotional effort, Manage. Sci, 50, 1, pp. 48-63, (2004); Tassy A.A., Lovejoy W.S., Quantity fiexibility contracts and supply chain performance, Manage. Sci., 45, 10, pp. 1339-1358, (1999); Lau A.H.L., Lau H.-S., Wang J.-C., How a dominant retailer might design a purchase contract for a newsvendor-type product with price-sensitive demand, Eur. J. Oper. Res, 190, 2, pp. 443-458, (2008); Ritchken P.H., Tapiero C.S., Contingent claims contracting for purchasing decisions in inventory management, Oper. Res, 34, 6, pp. 864-870, (1986); Sun G., Research on the fresh agricultural product supply chain coordination with supply disruptions, Discrete Dyn. Nature Soc, 2013, 5, (2013); Wang C., Chen X., Option pricing and coordination in the fresh produce supply chain with portfolio contracts, Ann. Oper. Res, 248, 1-2, pp. 471-491, (2017); Yang L., Chen K., Ma G., Optimal decisions and coordination mechanisms for a fresh agricultural product supply chain system, Int. J. U-, E-Service, Sci. Technol, 7, 5, pp. 63-78, (2014); Lim W.S., A lemons market An incentive scheme to induce truth-telling in third party logistics providers, Eur. J. Oper. Res, 125, 3, pp. 519-525, (2000); Alp O., Erkip N.K., Gudielludie R., Outsourcing logistics: Designing transportation contracts between a manufacturer and a transporter, Transport Sci, 37, 1, pp. 23-39, (2003); Wu Q., Mu Y., Feng Y., Coordinating contracts for fresh product outsourcing logistics channels with power structures, Int. J. Prod. Econ, 160, pp. 94-105, (2015); Cai X., Chen J., Xiao Y., Xu X., Yu G., Fresh-product supply chain management with logistics outsourcing, Omega, 41, 4, pp. 752-765, (2013); Feng Y., Yu Y.-L., Zhang Y.-Z., Wu Q., Coordination in a threeechelon supply chain of fresh agri-products with TPLSP's participation in decision-making, J. Ind. Eng. Eng. Manage, 29, 4, pp. 213-221, (2015); Sheu J.-B., Marketing-driven channel coordination with revenue-sharing contracts under price promotion to end-customers, Eur. J. Oper. Res, 214, 2, pp. 246-255, (2011); He Y., Zhao X., Zhao L., He J., Coordinating a supply chain with effort and price dependent stochastic demand, Appl. Math. Model, 33, 6, pp. 2777-2790, (2009); Wang L., Dan B., Coordination of fresh agricultural supply chain considering retailer's freshness-keeping and consumer Utility, Oper. Res. Manage, 24, 5, pp. 44-51, (2015); Wang L., Dan B., The incentive mechanism for preservation in Fresh agricultural supply chain considering consumer utility, J. Ind. Eng. Eng. Manage, 29, 1, pp. 200-206, (2015); Hafezalkotob A., Competition, cooperation, and coopetition of green supply chains under regulations on energy saving levels, Transp. Res. E, Logistics Transp. Rev, 97, pp. 228-250, (2017); Yoo S.H., Cheong T., Quality improvement incentive strategies in a supply chain, Transp. Res. E, Logistics Transp. Rev, 114, pp. 331-342, (2018); Yu Y., Xiao T., Pricing and cold-chain service level decisions in a fresh agri-products supply chain with logistics outsourcing, Comput. Ind. Eng, 111, pp. 56-66, (2017); Zhu Q., Li X., Zhao S., Cost-sharing models for green product production and marketing in a food supply chain, Ind. Manage. Data Syst, 118, 4, pp. 654-682, (2018); Xiao T., Choi T.-M., Competitive capacity and price decisions for two build-to-order manufacturers facing time-dependent demands, IEEE Trans. Syst., Man, Cybern. A, Syst. Humans, 40, 3, pp. 583-595, (2010); Xiao T., Choi T.-M., Cheng T.C.E., Pricing and benefit of decentralization for competing supply chains with-xed costs, IEEE Trans. Eng. Manage, 65, 1, pp. 99-112, (2018); Xie J., Wei J.C., Coordinating advertising and pricing in a manufacturerfiretailer channel, Eur. J. Oper. Res, 197, 2, pp. 785-791, (2009); Taylor T.A., Supply chain coordination under channel rebates with sales effort effects, Manage. Sci, 48, 8, pp. 992-1007, (2002); Taleizadeh A.A., Sane-Zerang E., Choi T.M., The effect of marketing effort on dual-channel closed-loop supply chain systems, IEEE Trans. Syst., Man, Cybern. Syst, 48, 2, pp. 265-276, (2018); Li Q., Xiao T., Qiu Y., Price and carbon emission reduction decisions and revenue-sharing contract considering fairness concerns, J. Cleaner Prod, 190, pp. 303-314, (2018); Chang P.-K., Chou F.-D., Dai X., Ye Y., Development of a supply chain integration process, IEEE Access, 6, pp. 40226-40244, (2017); Zheng B., Yang C., Yang J., Zhang M., Pricing, collecting and contract design in a reverse supply chain with incomplete information, Comput. Ind. Eng, 111, pp. 109-122, (2017); Chen X., Shen Z.-J., An analysis of a supply chain with options contracts and service requirements, IIE Trans, 44, 10, pp. 805-819, (2012)","S. He; School of Traffic and Transportation, Beijing Jiaotong University, Beijing, 100044, China; email: shwhe@bjtu.edu.cn",null,"Institute of Electrical and Electronics Engineers Inc.",{"$nulls":5},2.1693536E7,null,null,null,"English","IEEE Access","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85056594925"]
["Ilchenko N.; Kulik A.; Magda R.","Ilchenko, Nataliia (57191857182); Kulik, Anna (57992070000); Magda, Róbert (57195221758)","57191857182; 57992070000; 57195221758","Trends in development of wholesale trade in Ukraine",2018.0,"Economic Annals-XXI",170.0,"2024-04-03",null,38.0,42.0,4.0,4.0,"10.21003/ea.V170-07","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85057448650&doi=10.21003%2fea.V170-07&partnerID=40&md5=574d7e32d4f77a2f6f06679050c7d009","Department of Trade Entrepreneurship and Logistics, Kyiv National University of Trade and Economics, 19 Kyoto Str., Kyiv, 02156, Ukraine; Faculty of Economics and Social Science, Szent István University, 1 Páter Károly Str., Gödöllõ, H-2100, Hungary","Ilchenko N., Department of Trade Entrepreneurship and Logistics, Kyiv National University of Trade and Economics, 19 Kyoto Str., Kyiv, 02156, Ukraine; Kulik A., Department of Trade Entrepreneurship and Logistics, Kyiv National University of Trade and Economics, 19 Kyoto Str., Kyiv, 02156, Ukraine; Magda R., Faculty of Economics and Social Science, Szent István University, 1 Páter Károly Str., Gödöllõ, H-2100, Hungary","The article focuses on the problems of the development of wholesale trade in Ukraine. Adapting the activities of wholesalers to the changes taking place in the wholesale market and the development of e-commerce in the conditions of globalisation and the integration of economic processes require the formation of new ways of interaction in supply chains and optimisation of business processes. The purpose of the research is to develop proposals regarding the development of wholesale trade in Ukraine, taking into account the experience of European countries. To do the study, the authors applied comparative analysis and empirical research (in 2017, thirty enterprises of wholesale trade were investigated). Basing on the conducted research and taking into account the experience of the leading countries of the world, the following scenario of the development of wholesale trade in Ukraine is proposed. 1. On the basis of the conducted research it is proved that the wholesale turnover in Ukraine tends to decrease - 61.1% of the answers, however 52.8% of the respondents claim through that the wholesale turnover at wholesale enterprises where the respondents work will increase in the next three years. They foresee the development of the horizontal integration of wholesalers, since wholesale trade enterprises have advantages and fundamental differences associated with the period of turnover of funds. Also, such is the respondents' opinion regarding the vertical integration of wholesale enterprises in retail trade. Only a small number of the respondents agreed that wholesale companies would merge with retailers. Therefore, we can assume that this trend is decreasing, and there will be no significant changes in this area in the coming years. 2. The most effective way is the development of wholesale trade as a result of focusing on one of the functions (for example, specialisation in providing logistics services, provision of warehouse services or services to ensure the organisation of goods, the development of 3 PL (PL - provider of logistics services), provision of logistic services by 4 PL-providers with regard to storage, transportation and processing of orders). Such functions are often assumed by the former distribution companies. We consider this direction of wholesale trade to be the most possible. However, this can be achieved only in the presence of warehouses. 3. We have provided a conceptual framework for the development of wholesale trade in accordance with the implementation of the omni-channel strategy. The application of e-commerce in the activities by wholesalers (for B2B businesses) increases the level of customer service in the modern environment. The respondents acknowledge the tendency to create their own online stores at wholesale enterprises - 89%, which correlates with 97% of the respondents who will increase wholesale trade in e-commerce in the next three years. The introduction of e-commerce in the activities of wholesalers (for B2B businesses) will contribute to the enhanced level of customer service in the modern environment. Yet, the effective use of the omni-channel strategy is a complex process that requires integration of advanced technology and transformation of outdated organisational structures and business processes. © Institute of Society Transformation, 2018.","E-commerce; Fulfillment; Multi-channel; Omni-channel; Wholesale Trade",{"$nulls":7},"Apopii V.V., Khomyak Yu.M., Essence and typology of innovations in trade, Collection of Scientific Works \"Trade, Commerce, Entrepreneurship\", 12, pp. 5-7, (2011); Beglarashvili O.P., Implementation of organizational and marketing innovations by wholesale trade enterprises, Materials of the International Business-Forum \"Problems and Prospects of Innovation Activity in Ukraine\", 19, pp. 26-28, (2016); Bohoslovets H.M., Trubei O.M., Problems and prospects of wholesale enterprises' development, Scientific Herald of Kherson State University. Series \"Economics\", 5, 2, pp. 28-32, (2014); Virt M., Ya, Organization-economic Mechanism of Wholesale Trade Functioning in Market Environment, (2009); Mazaraki A.A., Blank I.O., Ligonenko L.O., Guliayeva N.M., Internal Trade in Ukraine: Economic Conditions of Effective Development, (2006); Holoshubova N.O., Institutional changes as a factor of innovation development in trade, Materials of the International Business Forum \"Problems and Prospects of Innovation Activity Development in Ukraine, 19, pp. 71-73, (2015); Trubei O.M., Innovative development of the wholesale enterprises, Theoretic and Practical Aspects of the Intellectual Property Economics, 10, 1, pp. 205-210, (2014); B2C E-commerce Sales Worldwide from 2012 to 2018 (In Billion U. S. Dollars), (2018); Press Release UNCTAD Designs Business-to-consumer Electronic-commerce Index (UNCTAD/PRESS/PR/2015/003), (2015); The Impact of Omni-Channel Commerce on Supply Chains, (2014); Gartner Top 5 Marketing Predictions for 2018, (2018); Dubovyk T.V., Internet Marketing Communications, (2014); 5 Trends in Wholesale Distribution 2018, (2018); Piotrowicz W., Cuthbertson R., Introduction to the special issue information technology in retail: Toward omnichannel retailing, International Journal of Electronic Commerce, 18, 4, pp. 5-16, (2014); Verhoef P.C., Kannan P.K., Inman J.J., From multi-channel retailing to omni-channel retailing: Introduction to the special issue on multi-channel retailing, Journal of Retailing, 91, 2, pp. 174-181, (2015); Mosquera A., Olarte Pascual C., Juaneda-Ayensa E., Understanding the customer experience in the age of omni-channel shopping, Journal ICONO14, 15, 2, pp. 92-114, (2017)",null,null,"Institute of Society Transformation",{"$nulls":5},1.728622E7,null,null,null,"English","Eco. Annals.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85057448650"]
["Yu F.","Yu, Fei (57204513771)",5.7204513771E10,"Integrated operation path of the tourism products supply chain in China: Online intelligentization",2018.0,"Journal of Discrete Mathematical Sciences and Cryptography",21.0,6.0,null,1305.0,1309.0,4.0,0.0,"10.1080/09720529.2018.1526406","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85055870342&doi=10.1080%2f09720529.2018.1526406&partnerID=40&md5=36ec27dec57183fa6bfa90f803f01f9a","College of Economics & Management, Anhui Agricultural University, Hefei, China","Yu F., College of Economics & Management, Anhui Agricultural University, Hefei, China","In China, smart tourism has been promoted by technological innovation. Technological progress makes new changes in the supply chain of tourism products. It is of great significance to explore the optimal path of the Tourism Products Supply Chain (TPSC) in the Internet era. Tourism node organization, tourism flow, tourism logistics, tourism products information flow and capital flow are the basic integrated elements of the TPSC. Tourism flow is the ultimate destination of the TPSC. The development of information technology in China provides the conditions for the optimization of the TPSC. Based on the integration of information technology, the intelligent integration path of the TPSC is constructed. The intelligent integration of TPSC is realized by tourism e–commerce platform as a tourism products integrator. Thus, the supply of lean tourism service can be effectively matched the tourism demand. The sustainability of the TPSC is ensured through intelligent integration, transmission, and operation path. By optimizing the expected returns, the probability of selecting the intelligent TPSC by tourists and related enterprises is greatly increased. © 2018, © 2018 Taru Publications.","Intelligentization; Operation; Path; Tourism Products Supply Chain (TPSC)","Integration; Integrated Operations; Intelligent integration; Intelligentization; Operation; Optimal paths; Path; Product supply chains; Technological innovation; Technological progress; Tourism product supply chain; Supply chains",{"$nulls":4},"Humanities and Social Sciences Research Project in Colleges and Universities of Anhui Province","This work was supported by the Humanities and Social Sciences Research Project in Colleges and Universities of Anhui Province [Grant No. SK2016A0326].","Hsu S.C., Lin C.T., Lee C., Measuring the effect of outbound Chinese tourists travel decision–making through tourism destination image and travel safety and security[J], Journal of Information & Optimization Sciences, 38, 3-4, pp. 559-584, (2017); Thanh-Lam N., Ming-Hung S., Ying-Fang H., Et al., Accurate forecasting models in predicting the inbound tourism demand in Vietnam[J], Journal of Statistics & Management Systems, 16, 1, pp. 25-43, (2013); Li W., Li P., Zhang P., Introduction to European tour operators and their experiences of tourism supply chain management, Journal of Guilin Institute of Tourism, 17, 1, pp. 112-115, (2006); Michailidou A.V., Vlachokostas C., Achillas C., Maleka D., Moussiopoulos N., Feleki E., Green tourism supply chain management based on life cycle impact assessment, European Journal of Environmental Sciences, 6, 1, pp. 30-36, (2016); Stephen H., Coordinating the tourism supply chain using bid prices, Journal of Revenue and Pricing Management, 7, 3, pp. 266-280, (2008); Zheng S., Fang F., Development of a model for a cluster–based virtual tourism supply chain, Tourism Tribune, 29, 2, pp. 46-54, (2014); Aaron T., Robert O., Willem S., Bishnu S., From tourism supply chains to tourism value ecology, Journal of New Business Ideas & Trends, 13, 1, pp. 47-65, (2015); Yang J., Huang F., Research on the coordination mechanism of tourism supply chain from multiple perspective, Modern Management Science, 10, pp. 14-16, (2012); Arzum B., Buket O., Ebru K., Buyer–supplier relationship in tourism supply chains: a research in Cappadocia region in Turkey, Journal of Applied Sciences, 14, 7, pp. 660-668, (2014)","F. Yu; College of Economics & Management, Anhui Agricultural University, Hefei, China; email: ahauyufei@163.com",null,"Taru Publications",{"$nulls":5},9720529.0,null,null,null,"English","J. Discrete Math. Sci. Cryptography","Article","Final",null,"Scopus","2-s2.0-85055870342"]
["Rose K.; Jones A.","Rose, Kristina (57199654710); Jones, Allen (57208330435)","57199654710; 57208330435","Unfulfilled: A Story of Users and Library Request Services",2018.0,"Journal of Interlibrary Loan, Document Delivery and Electronic Reserve",27.0,"2024-05-04",null,77.0,107.0,30.0,4.0,"10.1080/1072303X.2019.1579152","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85064493189&doi=10.1080%2f1072303X.2019.1579152&partnerID=40&md5=270ecb455f8d5ebf0149416d7d9b7b90","New York University Libraries, New York, NY, United States; The New School, Libraries & Archives, New York, NY, United States","Rose K., New York University Libraries, New York, NY, United States; Jones A., The New School, Libraries & Archives, New York, NY, United States","The current technology models for library request services present significant challenges for the user’s experience from discovery to delivery. Applying user-centered design and e-commerce modalities may allow libraries to create more engaging and useful request services for all users. The authors suggest six design principles to improve user’s experience with library request systems and offer practical applications of these principles based upon two case studies at The New School Libraries and New York University Libraries. Both cases utilize APIs currently available, suggesting that libraries may leverage current models to create a better experience for their users. © 2019, © 2019 The Author(s). Published with license by Taylor & Francis Group, LLC.","Discovery; interlibrary loan; request services; service design; user experience",{"$nulls":7},"Babich N., (2017); Ballav A., (2016); (2013); (2015); (2016); Next Generation Resource Delivery: Management System and UX Functional Requirements, (2017); Breeding M., Resource sharing in libraries: Concepts, products, technologies, and trends, Library Technology Reports, 49, 1, pp. 5-11, (2013); Brett K., Lierman A., Turner C., Lessons learned: A Primo usability study, Information Technology & Libraries, 35, 1, pp. 7-25, (2016); Budiu R., (2013); Bryant S., Ye G., From discovery to delivery: Successful systems integration, Technical Services Quarterly, 32, 4, pp. 383-389, (2015); Choi S., Kim S., Yang J., Lee J., Joo C., Jung H., Real-time measurement of human salivary cortisol for the assessment of psychological stress using a smartphone, Sensing and Bio-Sensing Research, 2, pp. 8-11, (2014); Clark A.R., Erdmann A., Ferguson J., Gambrell K., Shaw-Munderback J.B., Taking action on usability testing findings: Simmons College Library case study, Serials Librarian, 71, 3-4, pp. 186-196, (2016); Collins P.D., User analysis in the borrow direct marketplace, Interlending & Document Supply, 43, 4, pp. 179-181, (2015); Comeaux D.J., Usability testing of a web-scale discovery system at an academic library, College & Undergraduate Libraries, 19, pp. 189-206, (2012); Cugelman B., (2016); Deardorff T., Nance H., WorldCat Local implementation: The impact on interlibrary loan, Interlending and Document Supply, 37, 4, pp. 177-180, (2009); de Jong M., Service design for libraries: An introduction, Advances in librarianship, 38, pp. 137-151, (2014); Dulenko V., (2017); Fabiku A., Tomcik L., Enriching your wealth of resources by marketing interlibrary loan, Journal of Interlibrary Loan, Document Delivery and Electronic Reserve, pp. 1-14, (2018); Flaherty H., Kaley A., (2018); Foran K., New Zealand library patron expectations of an interloan service, New Zealand Library & Information Management Journal, 55, 3, pp. 3-9, (2015); Gaffney M., Reflecting usability engineering goals in interlibrary loan user interfaces, Journal of Interlibrary Loan, Document Delivery & Electronic Reserves, 19, 4, pp. 291-298, (2009); Gaffney M., Interlibrary loan requests for locally available materials: WorldCat Local's impact, College & Research Libraries, 73, 1, pp. 68-77, (2012); 37, (2018); Harley A., (2018); Hepburn P., Lewis K.M., What's in a name? Using card sorting to evaluate branding in an academic library's web site, College & Research Libraries, 69, 3, pp. 242-250, (2008); Understanding Motion, (2018); Goncalves R., Rocha T., Martins J., Branco F., Au-Yong-Oliveira M., Evaluation of e-commerce websites accessibility and usability: an e-commerce platform analysis with the inclusion of blind users, Universal Access in the Information Society, 17, 3, pp. 567-583, (2018); Huang D.L., Flipped Interlibrary Loan (F.I.L.L.): Putting interlibrary loan in the driver's seat of acquisitions, Journal of Interlibrary Loan, Document Delivery & Electronic Reserve, 25, 3-5, pp. 61-74, (2015); Jones W.J., Pritting S., Morgan B., Understanding availability: Usability testing of a consortial interlibrary loan catalog, Journal of Web Librarianship, 8, 1, pp. 69-87, (2014); Kenefick C., DeVito J.A., Google expectations and interlibrary loan: Can we ever be fast enough?, Journal of Interlibrary Loan, Document Delivery & Electronic Reserves, 23, 3, pp. 157-163, (2013); Krug S., Don't make me think, revisited: A common sense approach to Web usability, (2014); Little M., Leon L., Assessing the value of ILL to our users: A comparative study of three US libraries, Interlending & Document Supply, 43, 1, pp. 34-40, (2015); Litsey R., Daniel K., Resources—anytime, anywhere: Branding library services, a case study of Texas Tech's document delivery department, Journal of Interlibrary Loan, Document Delivery & Electronic Reserves, 23, 1, pp. 19-34, (2013); Loranger H., (2013); Mak C., Add to cart? E-commerce, self-service and the growth of interlibrary loan, Interlending & Document Supply, 40, 1, pp. 26-30, (2012); Marquez J.J., Downey A., Library Service Design: A LITA Guide to Holistic Assessment, Insight, and Improvement, (2016); Munson K., User-centered provisioning of interlibrary loan: A framework, The Library with the Lead Pipe, (2018); Munson K.I., Savage D., Interlibrary loan's efficacy in meeting students’ expectations to acquire textbooks: Results from a study conducted in a large research library, Journal of Interlibrary Loan, Document Delivery & Electronic Reserves, 23, 4-5, pp. 191-200, (2013); Musser L., Coopey B., Impact of a discovery system on interlibrary loan, College & Research Libraries, 77, 5, pp. 643-653, (2016); (2008); Nielsen J., Usability engineering: Usability engineering., (1994); Nielsen J., (1995); Nielsen J., (2001); Nielsen J., (2008); Norman D., The design of everyday things: Revised and expanded edition, (2013); (2018); (2018); Pritting S., Jones W., Jackson T., Mulligan M., Enhancing resource sharing access through system integration, Journal of Interlibrary Loan, Document Delivery & Electronic Reserves, 26, 1, pp. 11-24, (2016); Ritter F.E., Baxter G.D., Churchill E.F., Foundations for designing user-centered systems: What system designers need to know about people., (2014); Rochkind J., (2008); Scott R., Barton G., Promoting interlibrary loan in the traditional catalog and discovery layer: Two pilot projects, Library Resources & Technical Services, 62, 2, pp. 74-79, (2018); Sewell B., Gaffney M., RapidR: Innovative resource sharing for physical delivery, Journal of Interlibrary Loan, Document Delivery and Electronic Reserve, 26, 2, pp. 67-77, (2017); Sherwin K., (2014); Swanson T.A., Hayes T., Kolan J., Hand K., Miller S., Guiding choices: Implementing a library website usability study, Reference Services Review, 45, 3, pp. 359-367, (2017); (2016); Whitenton K., (2018); Whitenton K., (2018); Yang Z., Hahn D., Thornton E., Meeting our customers’ expectations: A follow-up customer satisfaction survey after 10 years of free document delivery and interlibrary loan services at Texas A&M University Libraries, Journal of Interlibrary Loan, Document Delivery & Electronic Reserves, 22, 2, (2012); Zhao S., (2015)","K. Rose; Access, Delivery, & Resource Sharing Services, New York University Libraries, Bobst Library, New York, 70 Washington Square South, 10012-1019, United States; email: kristina.rose@nyu.edu",null,"Routledge",{"$nulls":5},"1072303X",null,null,null,"English","J. Interlibr. Loan Doc. Deliv. Electron. Reserve","Article","Final",null,"Scopus","2-s2.0-85064493189"]
["Xu J.-J.; Liu X.","Xu, Jun-Jie (9735193900); Liu, Xu (57203993665)","9735193900; 57203993665","A quantitative investigation of exit intension of public pickup points",2018.0,"Journal of Interdisciplinary Mathematics",21.0,5.0,null,1151.0,1156.0,5.0,0.0,"10.1080/09720502.2018.1494312","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85053923914&doi=10.1080%2f09720502.2018.1494312&partnerID=40&md5=b12fbc52728391e594942f2f7c06bef9","School of Economics and Management, Anqing Normal University, Anqing, 246133, China","Xu J.-J., School of Economics and Management, Anqing Normal University, Anqing, 246133, China; Liu X., School of Economics and Management, Anqing Normal University, Anqing, 246133, China","Based on samples collected from logistics market in China, factors about withdrawing willingness of public pickup points were examined. The empirical study demonstrated that offline involvement experience had little effects on the exit decision. For the platform management efficiency, only settlement performance shown distinct negative effects, service efficiency did not bring the expected mechanisms. For the potential revenue perception, both the commission revenue and relationship promotion produced significant influence on the behavior of pickup points. However the perceived customer conversion was not proved to be significant. The detailed implications were also proposed as well as future research directions. © 2018, © 2018 Taru Publications.","E-commerce logistics; Joint delivery; Self-pickup point; The last mile problem","Efficiency; Customer conversion; Empirical studies; Future research directions; Last mile problems; Platform management; Potential revenue; Quantitative investigation; Self-pickup point; Pickups",{"$nulls":4},"Soft Science Foundation of Anhui Province, (1607a0202059); National Natural Science Foundation of China, NSFC, (71502002)","The authors acknowledge the financial support from Natural Science Foundation of China (71502002) and Soft Science Foundation of Anhui Province(1607a0202059) .","Yang J.P., Yang C.C., Yao X.X., Research on the “Last-Mile” issue in the e-commerce logistics system, Journal of business economics, 270, pp. 16-22, (2014); Weltevrenden J.W., B2c e-commerce logistics: the rise of collection and delivery points in the Netherlands, International journal of retail & distribution management, 36, pp. 638-660, (2008); Xu J.J., Jiang L., Li Y.L., Consumer’s selecting willingness of picking up parcels: an empirical retest for service driving hypothesis, Chinese journal of management, 11, pp. 1850-1857, (2014); Nordin F., Identifying intraorganisational and interorganisational alliance conflicts: A longitudinal study of an alliance pilot project in the high technology industry, Industrial Marketing Management, 35, pp. 116-127, (2006); Shi H.B., Wu J.G., The influence of justice perceptions on organizational cooperation behaviors in alliances based on task and institutional environment, Soft science, 27, pp. 27-30, (2013); Feng Z., Shu-Rong Y., Hui P., Hong-Ping Y., Jian-Zhong X., An empirical research on the influence of Chinese rural financial reform on cultivation of new agricultural business entities, Journal of Discrete Mathematical Sciences & Cryptography, 20, 1, pp. 389-405, (2017); Belik I., Jornsten K., A new Semi-Lagrangean Relaxation for the k-cardinality assignment problem, Journal of Information & Optimization Sciences, 37, 1, pp. 75-100, (2016); Artikis C.T., Voudouri A.P., Artikis T.P., Incorporating an Integral equation for characteristic functions in investigating a class of distributions, Journal of Statistics & Management Systems, 19, 1, pp. 89-97, (2016); Zhang S.X., Su Q., Song Y.T., The service quality’s impacts on relationship quality in B2B context, Chinese journal of management, 7, pp. 1514-1519, (2010)","J.-J. Xu; School of Economics and Management, Anqing Normal University, Anqing, 246133, China; email: xu.926@qq.com",null,"Taru Publications",{"$nulls":5},9720502.0,null,null,null,"English","J. Interdiscip. Math.","Article","Final",null,"Scopus","2-s2.0-85053923914"]
["Valarezo Á.; Pérez-Amaral T.; Garín-Muñoz T.; Herguera García I.; López R.","Valarezo, Ángel (57200541703); Pérez-Amaral, Teodosio (6505954111); Garín-Muñoz, Teresa (6507062892); Herguera García, Iñigo (57201378028); López, Rafael (56672367900)","57200541703; 6505954111; 6507062892; 57201378028; 56672367900","Drivers and barriers to cross-border e-commerce: Evidence from Spanish individual behavior",2018.0,"Telecommunications Policy",42.0,6.0,null,464.0,473.0,9.0,86.0,"10.1016/j.telpol.2018.03.006","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85044512466&doi=10.1016%2fj.telpol.2018.03.006&partnerID=40&md5=8c72f0d2ea88fe4bd0f23d4fbf3803b9","Instituto Complutense de Análisis Económico (ICAE), Universidad Complutense de Madrid (UCM), Spain; ICAE, UCM, Spain; Universidad Nacional de Educación a Distancia (UNED), Spain","Valarezo Á., Instituto Complutense de Análisis Económico (ICAE), Universidad Complutense de Madrid (UCM), Spain; Pérez-Amaral T., ICAE, UCM, Spain; Garín-Muñoz T., Universidad Nacional de Educación a Distancia (UNED), Spain; Herguera García I., ICAE, UCM, Spain; López R., ICAE, UCM, Spain","This paper explores the determinants of the individual's decision to perform cross-border e-commerce (CBeC). The European Union (EU) is especially interested in the promotion of CBeC because it is an important tool in its strategy to achieve the Digital Single Market in Europe. In this paper official data is used from a representative survey of 16,209 individuals on ICT usage by households and individuals that was carried out in Spain by the National Institute of Statistics (INE) for the year 2016. Using a standard neoclassical utility maximization framework, and logistic regression techniques, the results show that being a male is positively related to the probability of practicing CBeC. Education is positively and significantly related to the probability of being involved in CBeC with EU countries. Computer and Internet Skills are significant and positive factors in explaining CBeC (either with EU countries or with the rest of the world). The variable “how often the consumer sees other customer reviews before buying online”, has a positive effect. Foreign nationality also increases the likelihood of using CBeC. To promote CBeC in Spain measures towards developing digital skills, Internet trust and use of online information reviews of goods and services are discussed. © 2018 Elsevier Ltd","Cross-border e-commerce; Customer reviews; Digital skills; Domestic e-commerce; Logistic model; Online opinion seeker","Electronic commerce; Cross-border; Customer review; Digital skills; Logistic models; On-line opinions; Beryllium compounds",{"$nulls":4},"Autonomous Community of Madrid","This research is funded by the Autonomous Community of Madrid – Spain. Project: Finance, Innovation and Strategies: Economic Analysis of Business Productivity and its Determinants ( PRODECON-CM HM S2015/HUM-3491 ), 2016–2018.","Cardona M., Duch-Brown N., Francois J., Martens B., Yang F., The macro-economic impact of e-commerce in the eu digital single market. Institute for prospective technological studies digital economy working paper 2015/09, (2015); Cardona M., Duch-Brown N., Martens B., Consumer perceptions of (Cross-border) eCommerce in the EU digital Single market. Institute for prospective technological studies digital economy working paper (2015-06), (2015); Correa M., Garcia J.R., Tabanera A., Comercio electrónico y hábitos de consumo en España: la importancia de la banca on-line. Observatorio de Economía Digital, (2015); Drasgow F., Polychoric and polyserial correlations, Encyclopaedia of statistical sciences, (1988); European Commission, A coherent framework for building trust in the digital single market for e-commerce and online services, (2012); European Commission, A comprehensive approach to stimulating cross-border e-commerce for european citizens and businesses, (2016); European Commission, Europe's digital progress report (EDPR) 2017 country profile SpainEuropean commission, (2017); European Commission, Proposal for Regulation of the European Parliament and Council on cross border parcel delivery services, (2017); European Commission, Shaping the digital single market, (2017); European Parliament, Better cross-border parcel deliveries to boost e-commerce and help consumers, (2017); European Parliament and Council, The unfair commercial practices directive, (2005); Eurostat, Database - Eurostat, (2017); Falk M., Hagsten E., E-commerce trends and impacts across Europe, International Journal of Production Economics, 170, pp. 357-369, (2015); Garin Munoz T., Lopez R., Perez Amaral T., Herguera Garcia I., Valarezo Unda A., Models for individual adoption of eCommerce, eBanking and eGovernment in Spain, (2018); Garin Munoz T., Perez-Amaral T., Factores Determinantes del Comercio Electrónico en España, Boletín Económico Del ICE, 3016, pp. 51-65, (2011); Gefen D., E-commerce: The role of familiarity and trust, Omega, 28, 6, pp. 725-737, (2000); Gomez-Herrera E., Martens B., Turlea G., The drivers and impediments for cross-border e-commerce in the EU, Information Economics and Policy, 28, pp. 83-96, (2014); INE, Survey on equipment and use of information and communication technologies in households, (2016); Manyika J., Lund S., Bughin J., Woetzel J., Stamenov K., Dhingra D., Digital globalization: The new era of global flows, (2016); Marschak J., Binary choice constraints on random utility indicators (cowles foundation discussion papers No. 74), (1959); Martens B., What does economic research tell us about cross-border e-commerce in the EU digital single market? (SSRN Scholarly paper No. ID 2265305), (2013); McFadden D., Economic choices, The American Economic Review, 91, 3, pp. 351-378, (2001); ONTSI, Perfil sociodemográfico de los internautas (datos INE 2016), (2016); Park D.-H., Lee J., Han I., The effect of on-line consumer reviews on consumer purchasing Intention: The moderating role of involvement, International Journal of Electronic Commerce, 11, 4, pp. 125-148, (2007); PayPal, PayPal cross-border consumer research 2016, (2016); Pfeffermann D., The role of sampling weights when modeling survey data, International Statistical Review/Revue Internationale de Statistique, 61, 2, pp. 317-337, (1993); Stata Corporation, Stata manual, (2017); The Economist, E-commerce. The new bazaar, pp. 1-14, (2017)","Á. Valarezo; Instituto Complutense de Análisis Económico (ICAE), Universidad Complutense de Madrid (UCM), Spain; email: angelvalarezounda@gmail.com",null,"Elsevier Ltd",{"$nulls":5},3085961.0,null,"TEPOD",null,"English","Telecommun Policy","Article","Final",null,"Scopus","2-s2.0-85044512466"]
["Vanneschi L.; Horn D.M.; Castelli M.; Popovič A.","Vanneschi, Leonardo (8728011000); Horn, David Micha (57201215125); Castelli, Mauro (36052209100); Popovič, Aleš (35203730400)","8728011000; 57201215125; 36052209100; 35203730400","An artificial intelligence system for predicting customer default in e-commerce",2018.0,"Expert Systems with Applications",104.0,null,null,1.0,21.0,20.0,49.0,"10.1016/j.eswa.2018.03.025","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85043999337&doi=10.1016%2fj.eswa.2018.03.025&partnerID=40&md5=8ce6f62c2121dd90b9548fcfad2d315c","NOVA IMS, Universidade Nova de Lisboa, Lisboa, 1070-312, Portugal; Faculty of Economics, University of Ljubljana, Kardeljeva Ploščad 17, 1000, Ljubljana, Slovenia","Vanneschi L., NOVA IMS, Universidade Nova de Lisboa, Lisboa, 1070-312, Portugal; Horn D.M., NOVA IMS, Universidade Nova de Lisboa, Lisboa, 1070-312, Portugal; Castelli M., NOVA IMS, Universidade Nova de Lisboa, Lisboa, 1070-312, Portugal; Popovič A., NOVA IMS, Universidade Nova de Lisboa, Lisboa, 1070-312, Portugal, Faculty of Economics, University of Ljubljana, Kardeljeva Ploščad 17, 1000, Ljubljana, Slovenia","The growing number of e-commerce orders is leading to increased risk management to prevent default in payment. Default in payment is the failure of a customer to settle a bill within 90 days upon receipt. Frequently, credit scoring (CS) is employed to identify customers’ default probability. CS has been widely studied, and many computational methods have been proposed. The primary aim of this work is to develop a CS model to replace the pre-risk check of the e-commerce risk management system Risk Solution Services (RSS), which is currently one of the most used systems to estimate customers’ default probability. The pre-risk check uses data from the order process and includes exclusion rules and a generic CS model. The new model is supposed to replace the whole pre-risk check and has to work both in isolation and in integration with the RSS main risk check. An application of genetic programming (GP) to CS is presented in this paper. The model was developed on a real-world dataset provided by a well-known German financial solutions company. The dataset contains order requests processed by RSS. The results show that GP outperforms the generic CS model of the pre-risk check in both classification accuracy and profit. GP achieved competitive classificatory accuracy with several state-of-the-art machine learning methods, such as logistic regression, support vector machines and boosted trees. Furthermore, the GP model can be used in combination with the RSS main risk check to create a model with even higher discriminatory power. © 2018 Elsevier Ltd","Credit scoring; Genetic programming; Machine learning; Optimization; Risk management","Artificial intelligence; Commerce; Electronic commerce; Genetic algorithms; Genetic programming; Intelligent systems; Learning systems; Optimization; Risk perception; Risks; Sales; Artificial intelligence systems; Classification accuracy; Credit scoring; Default probabilities; Discriminatory power; Logistic regressions; Ordering process; State-of-the-art machine learning methods; Risk management",{"$nulls":6},"Abdou H.A., Genetic programming for credit scoring: The case of Egyptian public sector banks, Expert Systems with Applications, 36, 9, pp. 11402-11417, (2009); Abdou H.A., Pointon J., Credit scoring, statistical techniques and evaluation criteria: A review of the literature, Intelligent Systems in Accounting, Finance & Management, 18, 2-3, pp. 59-88, (2011); 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Vanneschi L., An introduction to geometric semantic genetic programming, NEO 2015: Results of the Numerical and Evolutionary Optimization Workshop NEO 2015 held at September 23–25 2015 in Tijuana, Mexico, pp. 3-42, (2017); Verbraken T., Bravo C., Weber R., Baesens B., Development and application of consumer credit scoring models using profit-based classification measures, European Journal of Operational Research, 238, 2, pp. 505-513, (2014); Wach E.P., (2011); Weinfurner S., Weisheit S., Wittmann G., Stahl E., Pur S., (2011); West D., Neural network credit scoring models, Computers and Operations Research, 27, 11-12, pp. 1131-1152, (2000); Wiginton J.C., A note on the comparison of logit and discriminant models of consumer credit behavior, The Journal of Financial and Quantitative Analysis, 15, 3, (1980); Yang Z., Wang Y., Bai Y., Zhang X., Measuring Scorecard Performance, Computational science ICCS 2004, 3038, pp. 900-906, (2004); Yao X., Crook J., Andreeva G., Support vector regression for loss given default modelling, European Journal of Operational Research, 240, 2, pp. 528-538, (2015); Zadrozny B., Elkan C., Obtaining calibrated probability estimates from decision trees and naive Bayesian classifiers, Icml, pp. 1-8, (2001); Zadrozny B., Elkan C., Transforming classifier scores into accurate multiclass probability estimates, Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining KDD 02, pp. 694-699, (2002); Zhang D., Huang H., Chen Q., Jiang Y., A comparison study of credit scoring models, Proceedings - Third International Conference on Natural Computation, ICNC 2007, 1, Icnc, pp. 15-18, (2007)","L. Vanneschi; NOVA IMS, Universidade Nova de Lisboa, Lisboa, 1070-312, Portugal; email: lvanneschi@novaims.unl.pt",null,"Elsevier Ltd",{"$nulls":5},9574174.0,null,"ESAPE",null,"English","Expert Sys Appl","Article","Final",null,"Scopus","2-s2.0-85043999337"]
["Zissis D.; Aktas E.; Bourlakis M.","Zissis, Dimitris (57119852500); Aktas, Emel (14059584200); Bourlakis, Michael (6506844873)","57119852500; 14059584200; 6506844873","Collaboration in urban distribution of online grocery orders",2018.0,"International Journal of Logistics Management",29.0,4.0,null,1196.0,1214.0,18.0,44.0,"10.1108/IJLM-11-2017-0303","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85053243378&doi=10.1108%2fIJLM-11-2017-0303&partnerID=40&md5=3141e7a53e79736f4455aae2deec356f","School of Management, University of Bath, Bath, United Kingdom; School of Management, Cranfield University, Cranfield, United Kingdom","Zissis D., School of Management, University of Bath, Bath, United Kingdom; Aktas E., School of Management, Cranfield University, Cranfield, United Kingdom; Bourlakis M., School of Management, Cranfield University, Cranfield, United Kingdom","Purpose: Population growth, urbanisation and the increased use of online shopping are some of the key challenges affecting the traditional logistics model. The purpose of this paper is to focus on the distribution of grocery products ordered online and the subsequent home delivery and click and collect services offered by online retailers to fulfil these orders. These services are unsustainable due to increased operational costs, carbon emissions, traffic and noise. The main objective of the research is to propose sustainable logistics models to reduce economic, environmental and social costs whilst maintaining service levels. Design/methodology/approach: The authors have a mixed methodology based on simulation and mathematical modelling to evaluate the proposed shared logistics model using: primary data from a major UK retailer, secondary data from online retailers and primary data from a consumer survey on preferences for receiving groceries purchased online. Integration of these three data sets serves as input to vehicle routing models that reveal the benefits from collaboration by solving individual distribution problems of two retailers first, followed by the joint distribution problem under single decision maker assumption. Findings: The benefits from collaboration could be more than 10 per cent in the distance travelled and 16 per cent in the time required to deliver the orders when two online grocery retailers collaborate in distribution activities. Originality/value: The collaborative model developed for the online grocery market incentivises retailers to switch from current unsustainable logistics models to the proposed collaborative models. © 2018, Emerald Publishing Limited.","Europe; Food logistics; Mixed method; Sustainability; Urban logistics",{"$nulls":5},"Horizon 2020 Framework Programme, H2020, (635773)","The authors are indebted to the three anonymous referees and the Associate Editor for their comments and suggestions that helped improve the context and the presentation of the material in the paper. This work has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 635773, U-TURN (www.u-turn-project.eu/).","Ballot E., Fontane F., Reducing transportation CO<sub>2</sub> emissions through pooling of supply networks: perspectives from a case study in French retail chains, Production Planning and Control: The Management of Operations, 21, 6, pp. 640-650, (2010); Bektas T., Laporte G., The pollution-routing problem, Transportation Research Part B: Methodological, 45, 8, pp. 1232-1250, (2011); Belavina E., Girotra K., Kabra A., Online grocery retail: revenue models and environmental impact, Management Science, 63, 6, pp. 1781-1799, (2017); Cachon G.P., Retail store density and the cost of greenhouse gas emissions, Management Science, 60, 8, pp. 1907-1925, (2014); Dantzig G., Ramser J., The truck dispatching problem, Management Science, 6, pp. 80-91, (1959); Doherty N.F., Ellis-Chadwick F., Internet retailing: the past, the present and the future, International Journal of Retail and Distribution Management, 38, 11-12, pp. 943-965, (2010); Edwards J., McKinnon A., Cullinane S., Comparative analysis of the carbon footprints of conventional and online retailing: a ‘last mile’ perspective, International Journal of Physical Distribution and Logistics Management, 40, 1-2, pp. 103-123, (2010); Inventory of US greenhouse gas emissions and sinks: 1990-2009, (2011); Fernie J., Sparks L., Logistics and Retail Management: Emerging Issues and New Challenges in the Retail Supply Chain, (2014); Frankel R., Goldsby T.J., Whipple J.M., Grocery industry collaboration in the wake of ECR, International Journal of Logistics Management, 13, 1, pp. 57-72, (2002); Hackney R., Grant K., Birtwistle G., The UK grocery business: towards a sustainable model for virtual markets, International Journal of Retail and Distribution Management, 34, 4-5, pp. 354-368, (2006); Hingley M., Lindgreen A., Grant D.B., Kane C., Using fourth-party logistics management to improve horizontal collaboration among grocery retailers, Supply Chain Management: An International Journal, 16, 5, pp. 316-327, (2011); UK grocery retailing, (2015); China’s online grocery market to hit $180bn by 2020, (2016); Ishfaq R., Defee C., Gibson B., Raja U., Realignment of the physical distribution process in Omni-channel fulfillment, International Journal of Physical Distribution and Logistics Management, 46, 6-7, pp. 543-561, (2016); Koc C., Bektas T., Jabali O., Laporte G., The impact of depot location, fleet composition and routing on emissions in city logistics, Transportation Research Part B: Methodological, 84, pp. 81-102, (2016); Kotzab H., Teller C., Value-adding partnerships and co-opetition models in the grocery industry, International Journal of Physical Distribution & Logistics Management, 33, 3, pp. 268-281, (2003); Krejcie R., Morgan D., Determining sample size for research activities, Educational and Psychological Measurement, 30, 3, pp. 607-610, (1970); Laporte G., The vehicle routing problem: an overview of exact and approximate algorithms, European Journal of Operational Research, 59, 3, pp. 345-358, (1992); Lindholm M., Behrends S., Challenges in urban freight transport planning – a review in the Baltic Sea region, Journal of Transport Geography, 22, pp. 129-136, (2012); Lozano S., Moreno P., Adenso-Diaz B., Algaba E., Cooperative game theory approach to allocating benefits of horizontal cooperation, European Journal of Operational Research, 229, 2, pp. 444-452, (2013); Mason R., Lalwani C., Boughton R., Combining vertical and horizontal collaboration for transport optimisation, Supply Chain Management: An International Journal, 12, 3, pp. 187-199, (2007); Online grocery retailing – UK – March 2014, (2014); Online grocery retailing – UK – March 2015, (2015); Online grocery retailing – UK – March 2016, (2016); Online grocery retailing – UK – March 2017, (2017); Montgomery D.C., Design and Analysis of Experiments, (2013); Murfitt N., Supermarket Giants ‘lose £100million a year from online delivery services’: cost of delivery means they are effectively paying customers to shop with them, mail online, 27 July 2014, (2014); Murphy A.J., Grounding the virtual: the material effects of electronic grocery shopping, Geoforum, 38, 5, pp. 941-953, (2007); Nathanail G., Adamos G., Gogas M., A novel approach for assessing sustainable city logistics, Transportation Research Procedia, 25, pp. 1036-1045, (2017); Niknamfar A.H., Niaki S.T.A., Fair profit contract for a carrier collaboration framework in a green hub network under soft time-windows: dual lexicographic max-min approach, Transportation Research Part E: Logistics and Transportation Review, 91, pp. 129-151, (2016); FY14 annual report and accounts, (2015); Ocado group PLC annual report and accounts, (2016); Usual resident population, (2011); Rushton A., Croucher P., Baker P., The Handbook of Logistics and Distribution Management, (2010); Sanchez Rodrigues V., Harris I., Mason R., Horizontal logistics collaboration for enhanced supply chain performance: an international retail perspective, Supply Chain Management: An International Journal, 20, 6, pp. 631-647, (2015); Shao J., Yang H., Xing X., Yang L., E-commerce and traffic congestion: an economic and policy analysis, Transportation Research Part B: Methodological, 83, pp. 91-103, (2016); Soysal M., Bloemhof-Ruwaard J.M., Haijema R., van der Vorst J.G.A.J., Modeling a green inventory routing problem for perishable products with horizontal collaboration, Computers and Operations Research, 89, pp. 168-182, (2018); Spence L., Bourlakis M., The evolution from corporate social responsibility to supply chain responsibility: the case of Waitrose, Supply Chain Management: An International Journal, 14, 4, pp. 291-302, (2009); Sprenger R., Monch L., A decision support system for cooperative transportation planning: design, implementation, and performance assessment, Expert Systems with Applications, 41, 11, pp. 5125-5138, (2014); Toth P., Vigo D., Models, relaxations and exact approaches for the capacitated vehicle routing problem, Discrete Applied Mathematics, 123, 1-3, pp. 487-512, (2002); World urbanization prospects, (2014); World urbanization prospects: the 2014 revision, (2015); Vanovermeire C., Sorensen K., Van Breedam A., Vannieuwenhuyse B., Verstrepen S., Horizontal logistics collaboration: decreasing costs through flexibility and an adequate cost allocation strategy, International Journal of Logistics: Research and Applications, 17, 4, pp. 339-355, (2014); Wei L., Zhang Z., Zhang D., Leung S., A simulated annealing algorithm for the capacitated vehicle routing problem with two-dimensional loading constraints, European Journal of Operational Research, 265, 3, pp. 843-859, (2018); Zissis D., Saharidis G., Aktas E., Ioannou G., Emission reduction via supply chain coordination, Transport Research Part D: Transport and Environment, 62, pp. 36-46, (2018)","D. Zissis; School of Management, University of Bath, Bath, United Kingdom; email: dzisis@aueb.gr",null,"Emerald Group Holdings Ltd.",{"$nulls":5},9574093.0,null,null,null,"English","Int. J. Logist. Manage.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85053243378"]
["Ge X.; Xue G.; Wen P.","Ge, Xianlong (55647754300); Xue, Guiqin (57204320633); Wen, Pengzhe (57205028615)","55647754300; 57204320633; 57205028615","Proactive Two-Level Dynamic Distribution Routing Optimization Based on Historical Data",2018.0,"Mathematical Problems in Engineering",2018.0,null,5191637.0,null,null,null,6.0,"10.1155/2018/5191637","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85058339631&doi=10.1155%2f2018%2f5191637&partnerID=40&md5=a5ecff75de447178b31890b143b98146","School of Economics and Management, Chongqing Jiaotong University, Chongqing, 400074, China; Key Laboratory of Intelligent Logistics Network, Chongqing, 400074, China","Ge X., School of Economics and Management, Chongqing Jiaotong University, Chongqing, 400074, China, Key Laboratory of Intelligent Logistics Network, Chongqing, 400074, China; Xue G., School of Economics and Management, Chongqing Jiaotong University, Chongqing, 400074, China; Wen P., School of Economics and Management, Chongqing Jiaotong University, Chongqing, 400074, China","In view of the dynamic dispersion of e-commerce logistics demand, this paper uses the historical distribution data of logistics companies to study data-driven proactive vehicle routing optimization. First, based on the classic 2E-VRP problem, a single-node/multistage 2E-VRP mathematical model is constructed. Then, a framework for solving the proactive vehicle routing optimization problem is proposed in combination with the characteristics of the proposed model, including four modules: data-driven demand forecasting methods, customer clustering methods, proactive demand quotas and replenishment strategies, and vehicle routing optimization procedure. The significant feature of the proposed solution framework is that the response to dynamic customers is proactive rather than passive. The solution is applied to the distribution practice of a large logistics company in Chongqing. The results show that the proposed method has better dynamic scene adaptability and customer response capabilities in traffic limit. © 2018 Xianlong Ge et al.",null,"Sales; Vehicles; Clustering methods; Customer response; Demand forecasting; Dynamic distribution; Logistics company; Replenishment strategies; Routing optimization; Vehicle routing optimization; Vehicle routing",{"$nulls":4},"Chongqing City Board of Education, Humanities and Social Science Research Project, (17SKG073); Chongqing Foundation and Frontier Research Project, (cstc2016jcyjA0160); Chongqing Municipal Science and Technology Research Project, (KJ1500702); National Natural Science Foundation of China, NSFC, (71502021, 71602015); China Postdoctoral Science Foundation, (2016T90862); Humanities and Social Science Fund of Ministry of Education of China, (2014YJC6300382015XJC630007)","This study is supported by the National Natural Science Foundation of China (71502021, 71602015), funded by the Ministry of Education of Humanities and Social Science Fund Project (2014YJC6300382015XJC630007), supported by Postdoctoral Science Foundation (2016T90862), funded by the Chongqing Foundation and Frontier Research Project (cstc2016jcyjA0160), Chongqing City Board of Education, Humanities and Social Science Research Project (17SKG073), and the Chongqing Municipal Science and Technology Research Project (KJ1500702).","Yang B.H., Asurvey on the real time vehicle routing problems, Science, 125, 3244, pp. 383-387, (2008); Laporte G., Scheduling issues in vehicle routing, Annals of Operations Research, 236, 2, pp. 1-12, (2013); Shi C.Y., Huang H., Vehicle routing problem: Research status and prospect, Logistics Sci-Tech, (2014); Braekers K., Ramaekers K., Van Nieuwenhuyse I., The vehicle routing problem: State of the art classification and review, Computers & Industrial Engineering, 99, 9, pp. 300-313, (2016); Rahmani Y., Cherifkhettaf W.R., Oulamara A., The twoechelon multi-products location-routing problem with pickup and delivery: Formulation and heuristic approaches, International Journal of Production Research, 54, 4, pp. 1-21, (2016); Liu R., Tao Y., Hu Q., Xie X., Simulation-based optimisation approach for the stochastic two-echelon logistics problem, International Journal of Production Research, 55, 1, pp. 1-15, (2017); Pillac V., Gueret C., Medaglia A., Dynamic vehicle routing problems: State of the art and prospects, Dynamic Vehicle Routing, (2011); Pillac V., Gendreau M., Gueret C., Medaglia A.L., A review of dynamic vehicle routing problems, European Journal of Operational Research, 225, 1, pp. 1-11, (2013); Psaraftis H.N., Wen M., Kontovas C.A., Dynamic vehicle routing problems: Three decades and counting, Networks, 67, 1, pp. 3-31, (2016); Wood C., Hartzel K., Factors that affect the improvement of demand forecast accuracy through point-of-sale reporting, European Journal of Operational Research, 26, 1, pp. 171-182, (2016); Thomas B.W., Waiting strategies for anticipating service requests from known customer locations, Informs, (2007); Lima C.A.F., Luz B.M., Takemoto S.T., Et al., Strategic modeling for the characterization of the conditions that allow the anticipation of the consumer's requests, Open Journal of Social Sciences, 3, 10, pp. 146-160, (2015); Cabello H., Lobillo F.J., Sound branch cash management for less: A low-cost forecasting algorithm under uncertain demand, Omega, 70, 3, pp. 118-134, (2016); Huiskonen J., Service parts management: Demand forecasting and inventory control, Production Planning & Control, 25, 6, pp. 489-494, (2011); Ma S., Fildes R., A retail store SKU promotions optimizationmodel for categorymulti-period profitmaximization, European Journal of Operational Research, 26, 2, pp. 680-692, (2017); Sha Z., Dekker R., Jaarsveld W.V., Et al., An improvedmethod for forecasting spare parts demand using extreme value theory, European Journal of Operational Research, 26, 1, pp. 169-181, (2017); Willemain T.R., Smart C.N., Schwarz H.F., A new approach to forecasting intermittent demand for service parts inventories, International Journal of Forecasting, 20, 3, pp. 375-387, (2004); Porras E., Dekker R., An inventory control systemfor spare parts at a refinery: An empirical comparison of different re-order point methods, European Journal of Operational Research, 184, 1, pp. 101-132, (2008); Lei H., Laporte G., Guo B., Districting for routing with stochastic customers, Euro Journal on Transportation & Logistics, 1, 12, pp. 67-85, (2012); Lei H., Laporte G., Guo B., A generalized variable neighborhood search heuristic for the capacitated vehicle routing problem with stochastic service times, TOP, 20, 1, pp. 99-118, (2012); Wang Y., Ma X., Lao Y., A fuzzy-based customer clustering approach with hierarchical structure for logistics network optimization, Expert Systems with Applications, 41, 2, pp. 521-534, (2014); Vidal T., Battarra M., Subramanian A., Et al., Hybrid metaheuristics for the clustered vehicle routing problem, Computers & Operations Research, 58, pp. 87-99, (2015); Battarra M., Erdogan G., Vigo D., Exact algorithms for the clustered vehicle routing problem, Operations Research, 62, 1, pp. 58-71, (2014); Marc A.H., Fuksz L., Pop P.C., Danciulescu D., A novel hybrid algorithm for solving the clustered vehicle routing problem, Hybrid Artificial Intelligent Systems, 9121, pp. 679-689, (2015); Lei H., Laporte G., Liu Y., Zhang T., Dynamic design of sales territories, Computers & Operations Research, 56, 11, pp. 84-92, (2015); Ferrucci F., Bock S., Real-time control of express pickup and delivery processes in a dynamic environment, Transportation Research Part B: Methodological, 63, 4, pp. 1-14, (2014); Ferrucci F., Bock S., Pro-active real-time routing in applications with multiple request patterns, European Journal of Operational Research, 253, 2, pp. 356-371, (2016); Wang Y., Ma X., Xu M., Wang Y., Liu Y., Vehicle routing problem based on a fuzzy customer clustering approach for logistics network optimization, Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology, 29, 4, pp. 1427-1442, (2015); Laporte G., Mercure H., Nobert Y., An exact algorithm for the asymmetrical capacitated vehicle routing problem, Networks, 16, 1, pp. 33-46, (1986); Laporte G., Exact algorithms for the traveling salesman problem and the vehicle routing problem, Progress in Industrial Mathematics at Ecmi, pp. 458-472, (1998); Baldacci R., Calvo R.W., An exact algorithm for the two-echelon capacitated vehicle routing problem, Operations Research, 61, 2, pp. 298-314, (2013); Santos F.A., Da Cunha A.S., Mateus G.R., Branch-andprice algorithms for the two-echelon capacitated vehicle routing problem, Optimization Letters, 7, 7, pp. 1537-1547, (2013); Santos F.A., Mateus G.R., Da Cunha A.S., Abranch-andcut-and-price algorithm for the two-echelon capacitated vehicle routing problem, Transportation Science, 49, 2, pp. 355-368, (2015); Breunig U., Schmid V., Hartl R.F., Vidal T., A large neighbourhood based heuristic for two-echelon routing problems, Computers & Operations Research, 76, pp. 208-225, (2016); Wang K., Lan S., Zhao Y., A genetic-algorithm-based approach to the two-echelon capacitated vehicle routing problem with stochastic demands in logistics service, Journal of the Operational Research Society, 68, 11, pp. 1-13, (2017); Cordeau J., Gendreau M., Laporte G., Atabu search heuristic for periodic and multi-depot vehicle routing problems, Networks, 30, 2, pp. 105-119, (2015); Alonso F., Alvarez M.J., Beasley J.E., A tabu search algorithm for the periodic vehicle routing problem with multiple vehicle trips and accessibility restrictions, Journal of the Operational Research Society, 59, 7, pp. 963-976, (2008); Maischberger M., A parallel iterated tabu search heuristic for vehicle routing problems, Computers & Operations Research, 39, 9, pp. 2033-2050, (2012); Silvestrin P.V., Ritt M., An iterated tabu search for the multi-compartment vehicle routing problem, Computers & Operations Research, 81, pp. 192-202, (2017)","X. Ge; School of Economics and Management, Chongqing Jiaotong University, Chongqing, 400074, China; email: gexianlong@cqjtu.edu.cn",null,"Hindawi Limited",{"$nulls":5},"1024123X",null,null,null,"English","Math. Probl. Eng.","Article","Final","All Open Access; Bronze Open Access; Green Open Access","Scopus","2-s2.0-85058339631"]
["Ajao B.F.; Oyebisi T.O.; Aderemi H.O.","Ajao, B.F. (56598049400); Oyebisi, T.O. (6602434437); Aderemi, H.O. (35101326300)","56598049400; 6602434437; 35101326300","Factors influencing the implementation of e-commerce innovations: The case of the Nigerian informal sector",2018.0,"African Journal of Science, Technology, Innovation and Development",10.0,4.0,null,473.0,481.0,8.0,2.0,"10.1080/20421338.2018.1475541","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85048816264&doi=10.1080%2f20421338.2018.1475541&partnerID=40&md5=da49c5ef92a76a2f1bca98faed4caaf4","National Centre for Technology Management, Obafemi Awolowo University, Ile-Ife, Nigeria; African Institute for Science Policy and Innovation, Obafemi Awolowo University, Ile-Ife, Nigeria; Department of Management and Accounting, Obafemi Awolowo University, Ile-Ife, Nigeria","Ajao B.F., National Centre for Technology Management, Obafemi Awolowo University, Ile-Ife, Nigeria; Oyebisi T.O., African Institute for Science Policy and Innovation, Obafemi Awolowo University, Ile-Ife, Nigeria; Aderemi H.O., Department of Management and Accounting, Obafemi Awolowo University, Ile-Ife, Nigeria","This paper investigated the factors influencing e-commerce adoption amongst small enterprises in Southwestern Nigeria with a view to contributing to debates on technological adoption in the informal sector. Primary data were collected from 387 enterprises engaged in furniture works, leather products, clothing and textiles through the use of questionnaire that were administered using multistage and simple random sampling technique. Data were analysed using logistic regression. The result showed that the significant technological factors influencing e-commerce adoption were the number of employees with ICT background (r = 0.654; p < 0.05), accessibility to good quality Internet bandwidth (r = 0.826; p < 0.05) and the availability of Internet security technologies (r = 0.809; p < 0.05) amongst others. The significant non-technological factors were basically e-readiness of customer and supplier for e-commerce (r = 0.612; p < 0.05), government policies (r = 0.684; p < 0.05) and the attitude of the owner of the enterprise towards e-commerce adoption (r = 0.598; p < 0.05). In addition, the non- technological factors had different influences on adoption when the enterprises were analysed by sector. The study concluded that factors influencing e-commerce adoption differs across the different categories of business in the informal sector; hence, there is the need for individual reassessment when designing policy towards technological adoption amongst small enterprises. © 2018, © 2018 African Journal of Science, Technology, Innovation and Development.","e-commerce adoption; Nigeria; non-technological factors; small enterprises; technological factors",{"$nulls":7},"Aderemi H.O., (2015); Aderemi H.O., Oyebisi T.O., Adegbite S.A., Hi-Tech Competence Building in Firms: Priority of Technological Efforts, IRCAB Journal of Social and Management Science, 1, 1, pp. 54-63, (2011); Ajzen I., The Theory of Planned Behavior, Organizational Behavior and Human Decision Processes, 50, 2, pp. 179-211, (1991); Al-Qirim N.A., E-Commerce Adoption in Small Businesses: Cases From New Zealand, Journal of Information Technology Case and Application Research, 9, 2, pp. 28-57, (2007); Ayo C.K., Adewoye J.O., Oni A.A., Business-to-consumer e-Commerce in Nigeria: Prospects and Challenges, African Journal of Business Management, 5, 13, pp. 5109-5117, (2011); Bekele E., Muchie M., Promoting Micro, Small and Medium Enterprises (MSMEs) for Sustainable Rural Livelihood, (2009); Chiemeke S.C., Evwiekpaefe A.E., A Conceptual Framework of a Modified Unified Theory of Acceptance and use of Technology (UTAUT) Model with Nigerian Factors in E-commerce Adoption, International Research Journals, 12, 2, pp. 1719-1726, (2011); Davis F.D., Perceived Usefulness, Perceived Ease of use, and User Acceptance of Information Technology, MIS Quarterly, 13, pp. 319-340, (1989); Fishbein M., Ajzen I., Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research, (1975); Gilaninia S., Danesh S., Amiri M., Mousavian S.J., Eskandarpour B., Effective Factors on Adoption of E-Commerce in SME Cooperative, Interdisciplinary Journal of Contemporary Research in Business, 3, 6, pp. 13-21, (2011); Grandon E., Pearson J.M., Electronic Commerce Adoption: An Empirical Study of Small and Medium US Businesses, Information and Management, 42, 1, pp. 197-216, (2004); Ibrahim W.F., (2008); Iddris F., Adoption of E-Commerce Solutions in Small and Medium-Sized Enterprises in Ghana, European Journal of Business and Management, 4, 10, pp. 48-57, (2012); Women and Men in the Informal Economy: A Statistical Picture, (2002); Jeffcoate J., Chappell C., Feindt S., Best Practice in SME Adoption of E-Commerce, Benchmarking: An International Journal, 9, 2, pp. 122-132, (2002); Jegede O.O., Ojo B.F., Science and Technology Knowledge Management in the ICT Sector in Emerging Economies: Policy Options for Nigeria, Scholarly Journal of Mathematics and Computer Science, 1, 4, pp. 71-77, (2012); Kabanda S., (2013); Kanbur R., Sumner A., Poor Countries or Poor People? Development Assistance and the New Geography of Global Poverty, Journal of International Development, 24, 6, pp. 686-695, (2012); Kinuthia J.N., Akinnusi D.M., The Magnitude of Barriers Facing E-Commerce Businesses in Kenya, Journal of Internet and Information Systems, 4, 1, pp. 12-27, (2014); Kshetri N., Barriers to E-Commerce and Competitive Business Models in Developing Countries: A Case Study, Electronic Commerce Research and Applications, 6, 4, pp. 443-452, (2008); Lawrence J.E., Tar U.A., Barriers to E-commerce in Developing Countries, Information, Society and Justice Journal, 3, 1, pp. 23-35, (2010); Mugenda O., Research Methods, Quantitative and Qualitative Approaches, (2013); (2013); Ochola P.B.O., (2013); Rogers E.M., Diffusion of Innovations, (1995); Rogers E.M., Elements of Diffusion, Diffusion of Innovations, 5, 1, pp. 1-38, (2003); Scott W.R., Christensen S., The Institutional Construction of Organisations: International and Longitudinal Studies, (1995); Scupola A., SMEs’ E-commerce Adoption: Perspectives from Denmark and Australia, Journal of Enterprise Information Management, 22, 1-2, pp. 152-166, (2009); (2013); Uzoka F.W., Organisational Influences on E-Commerce Adoption in a Developing Country Context Using UTAUT, International Journal of Business Information Systems, 3, 3, pp. 300-316, (2008); Venkatesh V., Davis F.D., A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies, Management Science, 46, 2, pp. 186-204, (2000); Yu C., Lu J., Dong X., Adoption of E-commerce Strategy in a Private SME in China, International Conference on Advanced Management Science, 2, 1, pp. 1-5, (2010); Zhai C., Study on Environment Factors Affecting B2B E-Marketplace Adoption in China: From E-Readiness Perspective, International Conference on Computer Science and Service System, 1, 1, pp. 4062-4065, (2011)","B.F. Ajao; National Centre for Technology Management, Obafemi Awolowo University, Ile-Ife, Nigeria; email: ojo_blessingf@yahoo.com",null,"Taylor and Francis Ltd.",{"$nulls":5},2.0421338E7,null,null,null,"English","Afr. J.  Sci.  Technol. Innov. Dev.","Article","Final",null,"Scopus","2-s2.0-85048816264"]
["Es Yurek E.; Ozmutlu H.C.","Es Yurek, Emine (57201679910); Ozmutlu, H. Cenk (6603061328)","57201679910; 6603061328","A decomposition-based iterative optimization algorithm for traveling salesman problem with drone",2018.0,"Transportation Research Part C: Emerging Technologies",91.0,null,null,249.0,262.0,13.0,154.0,"10.1016/j.trc.2018.04.009","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85045711875&doi=10.1016%2fj.trc.2018.04.009&partnerID=40&md5=4dee8f97f0533ccc79eaf85881b0ea24","Department of Industrial Engineering, Uludag University, Nilufer, 16059, Bursa, Turkey","Es Yurek E., Department of Industrial Engineering, Uludag University, Nilufer, 16059, Bursa, Turkey; Ozmutlu H.C., Department of Industrial Engineering, Uludag University, Nilufer, 16059, Bursa, Turkey","This study investigates a new delivery problem that has emerged after the attempts of several e-commerce and logistics firms to deploy drones in their operations to increase efficiency and reduce delivery times. In this problem, a delivery truck that carries a drone on its roof serves customers in coordination with a drone. The drone is considered to complement the truck due to its cost-efficiency and ability to access difficult terrains and to travel without exposure to congestion. This study presents an iterative algorithm that is based on a decomposition approach to minimize delivery completion time. In the first stage of the proposed methodology, the truck route and the customers assigned to the drone are determined. In the second stage, a mixed-integer linear programming model is solved to optimize the drone route by fixing the routing and the assignment decisions that are made in the first stage. Beginning with the shortest truck route, the assignment and the routing decisions are iteratively improved. The solution times of our algorithm are compared with the solution times of the state-of-the-art formulations that are solved by CPLEX. The results demonstrate that our algorithm yields shorter solution times for the instances that we generated with the specified parameters. An optimization-based heuristic algorithm, which obtains solutions for medium-sized instances, is developed by reducing the feasible search area. © 2018 Elsevier Ltd","Decomposition; Drone; Drone delivery; Iterative algorithm; MIP; TSP","Efficiency; Heuristic algorithms; Integer programming; Iterative methods; Traveling salesman problem; Trucks; Delivery problems; Drone delivery; E- commerces; e-Logistics; Iterative algorithm; Iterative optimization algorithms; Logistic firms; MIP; Solution time; TSP; algorithm; decomposition analysis; electronic commerce; linear programing; logistics; optimization; Drones",{"$nulls":6},"Agatz N., Bouman P., Schmidt M., (2016); Banker S., (2016); Bouman P., Agatz N., Schmidt M., (2015); Crowe S., (2017); Drexl M., Synchronization in vehicle routing-a survey of VRPs with multiple synchronization constraints, Transport. Sci., 46, 3, pp. 297-316, (2012); Ferrandez S.M., Harbison T., Weber T., Sturges R., Rich R., 9, 2, pp. 374-388, (2016); French S., (2015); Ha Q.M., Deville Y., Pham Q.D., Ha M.H., (2015); Ha Q.M., Deville Y., Pham Q.D., Ha M.H., On the min-cost traveling salesman problem with drone, Transport. Res. Part C: Emerg. Technol., 86, pp. 597-621, (2018); Murray C.C., Chu A.G., The flying sidekick traveling salesman problem: optimization of drone-assisted parcel delivery, Transport. Res. Part C: Emerg. Technol, 54, pp. 86-109, (2015); Paul F., (2015); Poikonen S., Wang X., Golden B., The vehicle routing problem with drones: extended models and connections, Networks, 70, 1, pp. 34-43, (2017); Ponza A., Optimization of Drone-Assisted Parcel Delivery, (2016); Snider M., Welch W.M., (2015); Wang X., Poikonen S., Golden B., The vehicle routing problem with drones: several worst-case results, Optim. Lett., 11, 4, pp. 679-697, (2017); Wohlsen M., (2014)","E. Es Yurek; Department of Industrial Engineering, Uludag University, Nilufer, 16059, Turkey; email: esyurek@uludag.edu.tr",null,"Elsevier Ltd",{"$nulls":5},"0968090X",null,null,null,"English","Transp. Res. Part C Emerg. Technol.","Article","Final",null,"Scopus","2-s2.0-85045711875"]
["Koiwanit J.","Koiwanit, Jarotwan (55839811700)",5.58398117E10,"Analysis of environmental impacts of drone delivery on an online shopping system",2018.0,"Advances in Climate Change Research",9.0,3.0,null,201.0,207.0,6.0,48.0,"10.1016/j.accre.2018.09.001","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85054356420&doi=10.1016%2fj.accre.2018.09.001&partnerID=40&md5=eb62a99ec6c48d9e1015690e8f2fed1d","Faculty of Engineering, King Mongkut's Institute of Technology Ladkrabang, Bangkok, 10520, Thailand","Koiwanit J., Faculty of Engineering, King Mongkut's Institute of Technology Ladkrabang, Bangkok, 10520, Thailand","In rural areas, drones are designed to replace road deliveries so as to overcome infrastructure challenges; though drones notably consume less fuel and consequently have a smaller impact on the environment, their full life cycle assessment should still be evaluated to comprehensively understand their environmental impact. This study presents a life cycle assessment study on drone delivery in Thailand using CML2001, the life cycle impact assessment (LCIA) method, to convert life cycle inventory data into environmental impacts. The observed results show that an online shopping system using drone delivery is one of the most environmentally friendly transportation options throughout a wide range of scenarios. However, the parts production contributed to significant impacts on environmental issues while the drone operation showed the least impact to all impact categories. The dominant contributors to global warming, abiotic depletion (ADP elements and fossil), acidification air, eutrophication, ozone layer depletion, and photochemical ozone creation impact categories were the coal mining and electricity generating station operation. However, the carbon fibers and the battery, are the main contributors to other impact categories, which include the human toxicity, freshwater aquatic ecotoxicity, marine aquatic ecotoxicity, and terrestric ecotoxicity. © 2018 National Climate Center (China Meteorological Administration)","CML2001; Drone delivery; GHG emissions; LCA; Online shopping",{"$nulls":5},"Chulalongkorn University, CU; King Mongkut's Institute of Technology Ladkrabang, KMITL","The author is grateful for the financial support from Research Seed Grant for New Lecturer from KMITL Research Fund and the technical support from Mr. Junraprach Petchang, a Chulalongkorn University's graduate student.","Belmonte N., Luetto C., Staulo S., Et al., Case studies of energy storage with fuel cells and batteries for stationary and mobile applications, Challenges, 8, 1, (2017); CBC News, Amazon Unveils Futuristic Plan: Delivery by Drone, (2013); Chan J., Thailand Consumer Trends: E-commerce ‘unstoppable’ as 4G Rollout Goes Rural, (2016); Davidson H., Drone Book Delivery Service Aims for Take-off in November, (2013); EEA, EMEP/EEA Emission Inventory Guidebook 2009. 2.C.5.a Copper Production, (2009); Guinee J.B., Handbook on Life Cycle Assessment. Operational Guide to the ISO Standards, (2002); Gulden T.R., The Energy Implications of Drones for Package Delivery: a Geographic Information System Comparison, (2017); Heutger M., Kuckelhaus M., Unmanned Aerial Vehicles in Logistics a DHL Perspective on Implications and Use Cases for the Logistics Industry, (2014); Freight Transport in Alaska: the Haul of the Wild, (2015); IPCC, Summary for Policymakers. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, (2014); Jennings R., What is Carbon Fiber? Can it Be Recycled?, (2015); Kang D.H.P., Chen M., Ogunseitan O.A., Potential environmental and human health impacts of rechargeable lithium batteries in electronic waste, Environ. Sci. Technol., 47, 10, pp. 5495-5503, (2013); Koiwanit J., Evaluation of Environmental Performance of Hypothetical Canadian Oxy-fuel Combustion Carbon Capture with Risk and Cost Analyses, (2015); Koiwanit J., Manuilova A., Chan C., Et al., A life cycle assessment study of a hypothetical Canadian oxy-fuel combustion carbon dioxide capture process, Int. J. GHG Con., 28, pp. 257-274, (2014); Koiwanit J., Piewkhaow L., Zhou Q., Et al., A life cycle assessment study of a Canadian post-combustion carbon dioxide capture process system, Int. J. LCA, 19, 2, pp. 357-369, (2014); Liddell H., Brueske S., Carpenter A., Cresko J., Manufacturing energy intensity and opportunity analysis for fiber-reinforced polymer composites and other lightweight materials, Proc., ASC: 31st Tech. Conf., (2016); Lohsomboon P., Silalertruksa W., Jirajariyavech A., Life Cycle Inventory for Cement Product and Steel Making towards Sustainable Development, (2004); Mangmeechai A., An economic input-output life cycle assessment of food transportation in Thailand, Int. J. Environ. Stud., 73, 5, pp. 778-790, (2016); McFarland M., UPS Drivers May Tag Team Deliveries with Drones, (2017); Miller P., Automotive lithium-ion batteries, Johnson Matthey Tech., 59, 1, pp. 4-13, (2015); Pandit D.D.V., Poojari A., A study on amazon prime air for feasibility and profitability-a graphical data analysis, IOSR JBM, 16, 11, pp. 6-11, (2014); Park J., Kim S., Suh K., A comparative analysis of the environmental benefits of drone-based delivery services in urban and rural areas, Sustainability, 10, 3, (2018); Rao B., Gopi A.G., Maione R., The societal impact of commercial drones, Technol. Soc., 45, pp. 83-90, (2016); The Life Cycle Energy Consumption and Greenhouse Gas Emissions from Lithium-ion Batteries: a Study with Focus on Current Technology and Batteries for Light-duty Vehicles. (No. C 243), (2017); Shrivastava K., An approach of shopping in 21st century: online shopping, SIJ Trans. Comput. Sci. Eng. Appl. (CSEA), 1, 4, pp. 133-135, (2013); Stolaroff J., The Need for a Life Cycle Assessment of Drone-based Commercial Package Delivery. Lawrence Livermore National Laboratory, LLNL-tr-652316, (2014); Tseng C., Chau C., Elbassioni K., Et al., Autonomous recharging and flight mission planning for battery-operated autonomous drones, arXiv, 1, 1, pp. 1-25, (2017); Wang D., The Economics of Drone Delivery, (2016); Wankanapon P., Chindapol S., Tantasavasdi C., Environmental impact assessment for typical and innovative housing construction materials in Thailand, Built, 2, pp. 43-53, (2013); Zhou Q., Koiwanit J., Piewkhaow L., Et al., A comparative of life cycle assessment of post-combustion, pre-combustion and oxy-fuel CO<sub>2</sub> capture, Ener. Pro., 63, pp. 7452-7458, (2014)",null,null,"National Climate Center",{"$nulls":5},1.6749278E7,null,null,null,"English","Adv. Clim. Change Manage.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85054356420"]
["Zhou L.; Baldacci R.; Vigo D.; Wang X.","Zhou, Lin (57868712000); Baldacci, Roberto (6602371948); Vigo, Daniele (7004088556); Wang, Xu (55951735500)","57868712000; 6602371948; 7004088556; 55951735500","A Multi-Depot Two-Echelon Vehicle Routing Problem with Delivery Options Arising in the Last Mile Distribution",2018.0,"European Journal of Operational Research",265.0,2.0,null,765.0,778.0,13.0,181.0,"10.1016/j.ejor.2017.08.011","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85027703592&doi=10.1016%2fj.ejor.2017.08.011&partnerID=40&md5=04801f7e11a08f3866b75e40ff387c00","College of Management, Chongqing University of Technology, Chongqing, 400054, China; DEI, University of Bologna, Cesena, Italy; College of Mechanical Engineering, Chongqing University, Chongqing, China","Zhou L., College of Management, Chongqing University of Technology, Chongqing, 400054, China; Baldacci R., DEI, University of Bologna, Cesena, Italy; Vigo D., DEI, University of Bologna, Cesena, Italy; Wang X., College of Mechanical Engineering, Chongqing University, Chongqing, China","In this paper, we introduce a new city logistics problem arising in the last mile distribution of e-commerce. The problem involves two levels of routing problems. The first requires a design of the routes for a vehicle fleet located at the depots to transport the customer demands to a subset of the satellites. The second level concerns the routing of a vehicle fleet from the satellites to serve all of the customers. A feature of the problem is that customers may provide different delivery options, allowing them to pick up their packages at intermediate pickup facilities. The objective is to minimize the total distribution cost. To solve the problem, a hybrid multi-population genetic algorithm is proposed. An effective heuristic algorithm is designed to generate initial solutions, and several procedures are designed to better manage the population as well as exploit and explore the solution space. The proposed method is tested on a large family of instances, including a real-world instance; the computational results obtained show the effectiveness of the different components of the algorithm. © 2017 Elsevier B.V.","City logistics; Hybrid genetic algorithm; Routing; Two-echelon","Fleet operations; Genetic algorithms; Heuristic algorithms; Pickups; Sales; Transportation routes; Vehicle routing; Vehicles; City logistics; Computational results; Distribution costs; Hybrid genetic algorithms; Multi-population genetic algorithm; Routing; Two-echelon; Vehicle Routing Problems; Problem solving",{"$nulls":4},"National Endowment for Science Technology and the Arts; China Scholarship Council; Science and Technology Support Program of Jiangsu Province, (2015BAH46F01)"," This study is supported by National Science and Technology Support Program of China under Grant No. 2015BAH46F01, and it is also part of the project supported by China Scholarship Council (CSC). The authors thank the anonymous referees for making several suggestions that improved the presentation of the paper.   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Soysal M., Bloemhof-Ruwaard J.M., Bektas T., The time-dependent two-echelon capacitated vehicle routing problem with environmental considerations, International Journal of Production Economics, 164, pp. 366-378, (2015); Toth P., Vigo D., The granular tabu search and its application to the vehicle-routing problem, Informs Journal on Computing, 15, 4, pp. 333-346, (2003); Tricoire F., Graf A., Gutjahr W.J., The bi-objective stochastic covering tour problem, Computers & Operations Research, 39, 7, pp. 1582-1592, (2012); Vidal T., Crainic T.G., Gendreau M., Lahrichi N., Rei W., A hybrid genetic algorithm for multidepot and periodic vehicle routing problems, Operations Research, 60, 3, pp. 611-624, (2012); Wang X., Zhan L., Ruan J., Zhang J., How to choose last mile delivery modes for e-fulfillment, Mathematical Problems in Engineering, 2014, (2014); Yu V.F., Lin S.-Y., A simulated annealing heuristic for the open location-routing problem, Computers & OperationsResearch, 62, pp. 184-196, (2015)","R. Baldacci; DEI, University of Bologna, Cesena, Italy; email: r.baldacci@unibo.it",null,"Elsevier B.V.",{"$nulls":5},3772217.0,null,"EJORD",null,"English","Eur J Oper Res","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85027703592"]
["Jia Y.-H.; Chen W.-N.; Gu T.; Zhang H.; Yuan H.; Lin Y.; Yu W.-J.; Zhang J.","Jia, Ya-Hui (56313876200); Chen, Wei-Neng (15073864100); Gu, Tianlong (7102898919); Zhang, Huaxiang (56012965100); Yuan, Huaqiang (14053218000); Lin, Ying (56226282100); Yu, Wei-Jie (55473198200); Zhang, Jun (36928402900)","56313876200; 15073864100; 7102898919; 56012965100; 14053218000; 56226282100; 55473198200; 36928402900","A Dynamic Logistic Dispatching System with Set-Based Particle Swarm Optimization",2018.0,"IEEE Transactions on Systems, Man, and Cybernetics: Systems",48.0,9.0,7894197.0,1607.0,1621.0,14.0,64.0,"10.1109/TSMC.2017.2682264","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85050735429&doi=10.1109%2fTSMC.2017.2682264&partnerID=40&md5=9d8c0cb015c9708e7f9f3f510040ea18","School of Computer Science and Engineering, South China University of Technology, Guangzhou, 510006, China; Sun Yat-sen University, Guangzhou, 510006, China; School of Computer Science and Engineering, Guilin University of Electronic Technology, Guilin, 541004, China; School of Information Science and Engineering, Shandong Normal University, Jinan, 250014, China; School of Computer Science and Network Security, Dongguan University of Technology, Dongguan, 523808, China","Jia Y.-H., School of Computer Science and Engineering, South China University of Technology, Guangzhou, 510006, China, Sun Yat-sen University, Guangzhou, 510006, China; Chen W.-N., School of Computer Science and Engineering, South China University of Technology, Guangzhou, 510006, China; Gu T., School of Computer Science and Engineering, Guilin University of Electronic Technology, Guilin, 541004, China; Zhang H., School of Information Science and Engineering, Shandong Normal University, Jinan, 250014, China; Yuan H., School of Computer Science and Network Security, Dongguan University of Technology, Dongguan, 523808, China; Lin Y., Sun Yat-sen University, Guangzhou, 510006, China; Yu W.-J., Sun Yat-sen University, Guangzhou, 510006, China; Zhang J., School of Computer Science and Engineering, South China University of Technology, Guangzhou, 510006, China","With the rapid development of e-commerce, logistics industry becomes a crucial component in the e-commercial ecological chain. Impelled by both economical and environmental benefit, logistics companies demand automated tools more urgently than ever. In this paper, a dynamic logistic dispatching system is proposed. The underlying model of the dispatching system is the dynamic vehicle routing problem which allows new orders being received as the working day progress. With this feature, the system becomes more practical than the systems with traditional static vehicle routing models, but is also more challenging as the vehicles must be scheduled in a dynamic way. The core of the system is a specially designed set-based particle swarm optimization algorithm. According to the characteristic of the problem, a new encoding scheme is defined by set and possibility, and a local refinement method is designed to accelerate the convergence speed of the algorithm. In addition, two more techniques: 1) region partition and 2) archive strategy are incorporated in the dispatching system to reduce the complexity of the problem and to facilitate the optimization process, helping the dispatcher control the vehicles in real time. The proposed system is tested on various benchmarks with different scales. Experimental results show that the proposed dispatching system is effective. © 2013 IEEE.","Capacitated vehicle routing problem (CVRP); dynamic vehicle routing problem (DVRP); set-based particle swarm optimization (S-PSO)","Vehicle routing; Vehicles; Capacitated vehicle routing problem; Dispatching systems; Dynamic vehicle routing problems; Ecological chains; Environmental benefits; Logistics industry; Particle swarm optimization algorithm; Setbased particle swarm optimizations (S-PSO); Particle swarm optimization (PSO)",{"$nulls":4},"Guangzhou Pearl River New Star of Science and Technology, (201506010002); National Natural Science Foundation of China, NSFC, (61332002, 61379061, 61622206); Natural Science Foundation of Guangdong Province, (2015A030306024); Tip-top Scientific and Technical Innovative Youth Talents of Guangdong Special Support Program, (2014TQ01X550)","Manuscript received December 13, 2016; accepted March 2, 2017. Date of publication April 7, 2017; date of current version August 16, 2018. This work was supported in part by the National Natural Science Foundation of China under Grant 61622206, Grant 61379061, and Grant 61332002, in part by the Natural Science Foundation of Guangdong under Grant 2015A030306024, in part by the Guangdong Special Support Program under Grant 2014TQ01X550, and in part by the Guangzhou Pearl River New Star of Science and Technology under Grant 201506010002. This paper was recommended by Associate Editor J.-H. Chou. (Corresponding authors: Wei-Neng Chen; Jun Zhang).","Wenqian Z., Traditional Shops Must Boost Their Online Links, (2016); McKinnon A.C., Browne M., Whiteing A.E., Piecyk M., Green Logistics: Improving the Environmental Sustainability of Logistics, (2015); Dantzig G.B., Ramser J.H., The truck dispatching problem, Manag. 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["Ul-Hameed W.; Shabbir M.S.; Imran M.; Raza A.; Salman R.","Ul-Hameed, Waseem (57203510019); Shabbir, Muhammad Salman (57188818896); Imran, Muhammad (57208560582); Raza, Ali (57224820735); Salman, Rabia (57193997687)","57203510019; 57188818896; 57208560582; 57224820735; 57193997687","Remedies of low performance among pakistani E-logistic companies: The role of firm’s IT capability and information communication technology (ICT)",2019.0,"Uncertain Supply Chain Management",7.0,2.0,null,369.0,380.0,11.0,48.0,"10.5267/j.uscm.2018.6.002","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85056318699&doi=10.5267%2fj.uscm.2018.6.002&partnerID=40&md5=7e8e7f1865052392cb0aaa0d876e6d7e","School of Economics, Finance & Banking (SEFB), Universiti Utara Malaysia, Sintok, Malaysia; School of Business Management (SBM), Universiti Utara Malaysia, Sintok, Malaysia; Othman Yeop Abdullah Graduate School of Business, Universiti Utara Malaysia, Sintok, Malaysia","Ul-Hameed W., School of Economics, Finance & Banking (SEFB), Universiti Utara Malaysia, Sintok, Malaysia; Shabbir M.S., School of Business Management (SBM), Universiti Utara Malaysia, Sintok, Malaysia; Imran M., School of Business Management (SBM), Universiti Utara Malaysia, Sintok, Malaysia; Raza A., Othman Yeop Abdullah Graduate School of Business, Universiti Utara Malaysia, Sintok, Malaysia; Salman R., School of Business Management (SBM), Universiti Utara Malaysia, Sintok, Malaysia","E-commerce market of Pakistan is instable which causes low performance of e-logistic industry. Thus, logistic industry of Pakistan is lacking as compared to other developing countries such as China, India, and Malaysia. Low performance is majorly based on low staff service quality, inappropriate website design and goods traceability system. As remedies of these issues, the current study introduced firm’s IT capability and information communication technology (ICT). The primary objective of this study is to investigate the determinants of e-logistic firm’s performance in Pakistan. To achieve this objective, quantitative research approach along with cross-sectional research design was used. By using the survey method, 300 questionnaires were distributed among the managerial staff of e-logistic companies. Smart PLS 3 was used as a statistical tool. It is found that staff service quality, website design and e-traceability had significant and positive relationships with firm’s e-logistic performance. Moreover, firm’s IT capability as a moderator enhanced the positive effect of staff service quality, website design and e-traceability. Nevertheless, information communication technology (ICT) positively mediated the relationship between e-traceability and firm’s e-logistic performance. Hence, firm’s IT capability and information communication technology (ICT) are the key elements to decrease various issues of staff service quality, website design and e-traceability. The study is much significant for practitioners and e-logistic companies to enhance performance by focusing on firm’s IT capability and information communication technology (ICT). © 2018 by the authors; licensee Growing Science, Canada.","E-logistics; E-traceability; Firm’s IT capability; Information communication technology (ICT); Staff service quality; Website design",{"$nulls":7},"Barcik R., Jakubiec M., E-logistics-aspects of functioning, Acta Academica Karviniensia, 1, (2012); Benfang Y., Feng X., Analysis on logistics service influencing factors of C2C E-commerce customer satisfaction, Modern Business, pp. 33-34, (2014); Berglund M., van Laarhoven P., Sharman G., Wandel S., Third-party logistics: Is there a future?, The International Journal of Logistics Management, 10, 1, pp. 59-70, (1999); Bhatnagar R., Sohal A.S., Millen R., Third party logistics services: A Singapore perspective, International Journal of Physical Distribution & Logistics Management, 29, 9, pp. 569-587, (1999); Campos J.G., Hardwick M., A traceability information model for CNC manufacturing, Computer-Aided Design, 38, 5, pp. 540-551, (2006); Changchit C., Garofolo T., Gonzalez J.J., A Cultural Study of E-Commerce Trust: Hispanic Versus Anglo, Journal of Information Science & Technology, 6, 4, (2009); Chin W.W., The partial least squares approach to structural equation modeling, Modern Methods for Business Research, 295, 2, pp. 295-336, (1998); Cichosz M., Goldsby T.J., Knemeyer A., Taylor D.F., Innovation in logistics outsourcing relationship–in the search of customer satisfaction, Logforum, 13, 2, (2017); Closs D.J., Goldsby T.J., Clinton S.R., Information technology influences on world class logistics capability, International Journal of Physical Distribution & Logistics Management, 27, 1, pp. 4-17, (1997); Cohen J., Statistical Power Analysis for the Behavioral Sciences, 2, (1988); Comrey A.L., Lee H.B., A First Course in Factor Analysis, (1992); Daniel A., Ashar M., Ihsan-ur-Rehman H., Shahbaz W., An impact of employee satisfaction on customer satisfaction in service sector of pakistan, Journal of Asian Scientific Research, 2, 10, pp. 548-561, (2012); Daugherty P.J., Ellinger A.E., Rogers D.S., Information accessibility: Customer responsiveness and enhanced performance, International Journal of Physical Distribution & Logistics Management, 25, 1, pp. 4-17, (1995); Gummesson E., Gronroos C., Quality of Services: Lessons from the Product Sector. 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World Academy of Science, Engineering and Technology, 78, pp. 790-795, (2011); Rana S.S., Osman A., Islam M.A., Customer satisfaction of retail chain stores: Evidence from Bangladesh, Journal of Asian Scientific Research, 4, 10, pp. 574-584, (2014); Shamsi M.I., Syed S.A., A study of the logistics capability factors for an e-commerce market, FAST-NU Research Journal (FRJ), 1, 2, pp. 143-149, (2015); Suominen M., Takala J., Support of information systems to decision making: A case analysis of information needs and factors in the forest industry, International Journal of Management and Enterprise Development, 3, 5, pp. 482-490, (2006); Thai V.V., Logistics service quality: Conceptual model and empirical evidence, International Journal of Logistics Research and Applications, 16, 2, pp. 114-131, (2013); van Hoek R.I., Using information technology to leverage transport and logistics service operations in the supply chain: An empirical assessment of the interrelation between technology and operations management, International Journal of Information Technology and Management, 1, 1, pp. 115-130, (2002); Xin L., Bo Y., Service Quality Evaluation of characteristics and service recovery strategies [J], Management Science, 6, pp. 72-76, (2004); Yuanxiao Z., A Study of Evaluation Logistic Perceived Services Quality in B2c E-Commerce, (2014)","M. Imran; School of Business Management (SBM), Universiti Utara Malaysia, Sintok, Malaysia; email: imran.imranb2001@gmail.com",null,"Growing Science",{"$nulls":5},2.2916822E7,null,null,null,"English","Uncertain Supply Chain Manag.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85056318699"]
["Chen W.; Goh M.; Zou Y.","Chen, Weijie (57189764918); Goh, Mark (58335238000); Zou, Yan (57189761628)","57189764918; 58335238000; 57189761628","Logistics provider selection for omni-channel environment with fuzzy axiomatic design and extended regret theory",2018.0,"Applied Soft Computing Journal",71.0,null,null,353.0,363.0,10.0,41.0,"10.1016/j.asoc.2018.07.019","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85049886121&doi=10.1016%2fj.asoc.2018.07.019&partnerID=40&md5=fbf85246da5e9dd7e5f2b74e04d6a647","School of Economics and Management, Chongqing Normal University, Chongqing, 400047, China; NUS Business School and The Logistics Institute-Asia Pacific, National University of Singapore, Singapore","Chen W., School of Economics and Management, Chongqing Normal University, Chongqing, 400047, China; Goh M., NUS Business School and The Logistics Institute-Asia Pacific, National University of Singapore, Singapore; Zou Y., School of Economics and Management, Chongqing Normal University, Chongqing, 400047, China","As e-commerce marketplaces proliferate, omni-channels will become the new engine of growth. Omni-channel retailers need to optimally determine how to select suitable logistics providers (LSPs) to help maintain their competitive advantage. Although there are many methods to solve the problem of LSP selection, most of them overlook the decision maker's psychology. Most importantly, previous studies paid little attention to the probability of success for each candidate under each criterion. To compensate for these shortcomings, this study proposes a new method of logistics provider selection in an omni-channel environment. We present the model in three phases. The first phase involves computing the probability of success of each LSP with respect to each criterion through axiomatic design method. The second phase uses the perspective of the extended regret aversion/rejoice preference to develop a bounded rational decision making model for determining the criteria weights. In this phase, the regret/rejoice levels are treated as continuous parameters, whereby decision makers can regret and rejoice simultaneously. The final phase computes the expected perceived utility values to select the best LSP. To validate the capability of the proposed model, LSPs of six from a case study are ranked based on the proposed model, and the results are compared with the traditional regret and TOPSIS. The findings suggest that the proposed method provides more reasonable and reliable results, which are in line with the psychological behavior of human beings. © 2018 Elsevier B.V.","Axiomatic design; Linguistic variables; Logistics provider selection; Omni-channel; Regret/Rejoice theory","Behavioral research; Competition; Computation theory; Decision making; Axiomatic design; Linguistic variable; Logistics providers; Omni-channel; Regret/Rejoice theory; Design",{"$nulls":4},"Education Commission of Science and Technology plan projects of Chongqing, (KJ1600317); Ministry of Education of the People's Republic of China, MOE, (13YJC630252); China Scholarship Council, CSC; National Office for Philosophy and Social Sciences, NPOPSS, (14AJL015)","This work is supported by the Education Commission of Science and Technology plan projects of Chongqing ( KJ1600317 ), the China Scholarship Council, the key project of National Social Science Foundation of China (No. 14AJL015 ), and the Humanities and Social Sciences Foundation of the Ministry of Education of the People’s Republic of China (No. 13YJC630252 ).","XiuXu S., Huang G.Q., Efficient multi-attribute multi-unit auctions for B2B E-Commerce logistics, Prod. 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Soft Comput. J.","Article","Final",null,"Scopus","2-s2.0-85049886121"]
["Tandon U.; Kiran R.; Sah A.N.","Tandon, Urvashi (57190029593); Kiran, Ravi (22985431500); Sah, Ash N. (57190030141)","57190029593; 22985431500; 57190030141","The influence of website functionality, drivers and perceived risk on customer satisfaction in online shopping: an emerging economy case",2018.0,"Information Systems and e-Business Management",16.0,1.0,null,57.0,91.0,34.0,78.0,"10.1007/s10257-017-0341-3","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85016034075&doi=10.1007%2fs10257-017-0341-3&partnerID=40&md5=17f7f74dc5785867aa21466e3a3af0ca","School of Humanities and Social Sciences (SHSS), Thapar University, P.O. Box 32, Patiala, 147004, India","Tandon U., School of Humanities and Social Sciences (SHSS), Thapar University, P.O. Box 32, Patiala, 147004, India; Kiran R., School of Humanities and Social Sciences (SHSS), Thapar University, P.O. Box 32, Patiala, 147004, India; Sah A.N., School of Humanities and Social Sciences (SHSS), Thapar University, P.O. Box 32, Patiala, 147004, India","The study analyzed website functionality, perceived risk and drivers of online shopping to evaluate their impact on customer satisfaction in India. The study empirically validates ease of ordering, Cash-on-delivery mode of payment, website functionality and different facets of perceived risk with Unified theory of acceptance and use of technology 2 (UTAUT2) (Venkatesh et al. in MIS Q 36(1):157–178, 2012). Findings of the study revealed that perceived risk had a negative relation with customer satisfaction where as the website functionality and drivers were positively associated with customer satisfaction. The research will help online retailers to recognize the important success factors that instill confidence among the consumers in developing economies. The study will also help online retailers to focus in the right direction to eliminate threats and convert non shoppers to online shoppers. The study throws light on a new aspect to research by validating the role of cash-on-delivery (COD) mode of payment as a construct and ease of ordering as new dimension to UTAUT2. © 2017, Springer-Verlag Berlin Heidelberg.","Customer satisfaction; Drivers of online shopping; India; Online shopping; Perceived risk; UTAUT2; Website functionality",{"$nulls":7},"Abdallah S., Jaleel B., Website appeal: development of an assessment tool and evaluation framework of e-marketing, J Theor Appl Commer Res, 10, 3, pp. 45-62, (2015); Ajzen I., The theory of planned behavior, Organ Behav Hum Decis Process, 50, 2, pp. 179-211, (1991); Albugami M., Bellaaj M., The continued use of Internet banking: combining UTAUT2 theory and service quality model, J Glob Manag Res, 10, 2, pp. 11-28, (2014); Almousa M., Perceived risk in apparel online shopping: a multi dimensional perspective, Can Soc Sci, 7, 2, pp. 23-31, (2011); Al-Gahtani S.S., Hubona G.S., Wang J., Information technology (IT) in Saudi Arabia: culture and the acceptance and use of IT, Inf Manag, 44, 8, pp. 681-691, (2007); Al-Sobhi F., Weerakkody V., El-Haddadeh R., The roles of intermediaries in e-government adoption: the case of Saudi-Arabia. tGov Workshop, London, (2011); Aoun C., Vatanasakdakul S., Li Y., AIS in Australia: UTAUT application and cultural implication. 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Tandon; School of Humanities and Social Sciences (SHSS), Thapar University, Patiala, P.O. Box 32, 147004, India; email: urvashiguptav@gmail.com",null,"Springer Verlag",{"$nulls":5},1.6179846E7,null,null,null,"English","Inf. Syst. e-Bus. Manage.","Article","Final",null,"Scopus","2-s2.0-85016034075"]
["Xiong F.; Gong P.S.; Peng Z.Q.; Fan J.F.","Xiong, F. (57189242556); Gong, P.S. (57201460686); Peng, Z.Q. (8223828400); Fan, J.F. (7402794591)","57189242556; 57201460686; 8223828400; 7402794591","Optimization of urban traffic distribution path under quick response demand",2018.0,"Open House International",43.0,1.0,null,108.0,112.0,4.0,2.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85045094441&partnerID=40&md5=99f0f5bacef0db63c6f3033f4a63e08f","School of Business Administration, Zhongnan University of Economics and Law, Wuhan, 430073, China; School of Economics and Management, China University of Geosciences, Wuhan, 430074, China; School of Civil Engineering and Architecture, Wuhan University of Technology, Wuhan, 430070, China","Xiong F., School of Business Administration, Zhongnan University of Economics and Law, Wuhan, 430073, China; Gong P.S., School of Economics and Management, China University of Geosciences, Wuhan, 430074, China; Peng Z.Q., School of Civil Engineering and Architecture, Wuhan University of Technology, Wuhan, 430070, China; Fan J.F., School of Civil Engineering and Architecture, Wuhan University of Technology, Wuhan, 430070, China","Under the background of the rapid development of e-commerce and information network, the demand for urban distribution is also changing; especially customers' demand for fast delivery of products is increasing. Based on this, the optimization of urban traffic distribution path was studied under the fast response demand. In this paper, the importance and theoretical basis of the design of urban traffic planning under rapid response demand were expounded; then, the urban traffic distribution path planning was designed, and the layout principle of urban traffic roads, the division of road levels and the planning and design of motor vehicle roads were analyzed; through the planning project of the traffic distribution path in a city, analysis of the planning on roadways, three-dimensional traffic paths was achieved. © 2018, Open House International Association.","Quick response demand; Roadway; Three-dimensional traffic; Urban traffic",{"$nulls":7},"Holguin-Veras J., Cruz C.A.T., Ban X., On the comparative performance of Urban delivery vehicle classes, Transportmetrica a: transport science, 9, 1, pp. 50-73, (2013); Cirovic G., Pamucar D., Bozanic D., Green logistic vehicle routing problem: Routing light delivery vehicles in Urban areas using a neuro-fuzzy model, Expert systems with applications, 41, 9, pp. 4245-4258, (2014); Nuzzolo A., Comi A., Urban freight demand forecasting: a mixed quantity/delivery/vehicle-based model, Transportation Research part e: Logistics and transportation review, 65, pp. 84-98, (2014); Rayman N., Redknap B.V., Aizlewood H., Et al., Discussion Of 7261 & 7262. Coventry Inner Ring Road: Planning and Traffic, Design and Construction, Proceedings of the institution of civil engineers, 47, 3, pp. 423-434, (1970); Nachtigall K., Jerosch K., Simultaneous network line planning and traffic assignment. Oasics-Openaccess series in informatics, Schloss Dagstuhl-Leibniz-zentrum für informatik, (2008); Selcuk I.A., Cubukcu K.M., Modeling Trafficinduced, In-Dwelling Vibration Using Urban Design and Planning Variables, Journal of architectural and planning Research, 32, 4, (2015); Ershova S., Smirnov E., Conceptual Justification of Town-Planning Design Standards for Streets and Roads in Large Cities for Ensuring Traffic Safety, Transportation Research procedia, 20, pp. 180-184, (2017); Jeon J.H., Kho S.Y., Park J.J., Et al., Effects of spatial aggregation level on an Urban transportation planning model, Ksce Journal of civil engineering, 16, 5, pp. 835-844, (2012); Xu T.D., Sun L.J., Peng Z.R., Et al., Integrated route guidance and ramp metering consistent with drivers' en-route diversion behaviour, Iet intelligent transport systems, 5, 4, pp. 267-276, (2011); Gao S., Wang Y., Gao Y., Et al., Understanding Urban traffic-flow characteristics: a rethinking of betweenness centrality, Environment and planning b: planning and Design, 40, 1, pp. 135-153, (2013)","J.F. Fan; School of Civil Engineering and Architecture, Wuhan University of Technology, Wuhan, 430070, China; email: fjeff_dj@whut.edu.cn",null,"Open House International Association",{"$nulls":5},1682601.0,null,null,null,"English","Open House Int.","Article","Final",null,"Scopus","2-s2.0-85045094441"]
["Suresh S.; Vasantha S.","Suresh, S. (57211236436); Vasantha, S. (56585826400)","57211236436; 56585826400","Influence of ICT in road transportation",2018.0,"Majlesi Journal of Electrical Engineering",12.0,4.0,null,49.0,56.0,7.0,1.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85082372964&partnerID=40&md5=ca308c4590e037bb6488be454b5412d6","School of Management Studies, Vels Institute Of Science Technology and Advanced Studies (VISTAS), India","Suresh S., School of Management Studies, Vels Institute Of Science Technology and Advanced Studies (VISTAS), India; Vasantha S., School of Management Studies, Vels Institute Of Science Technology and Advanced Studies (VISTAS), India","Purpose: Information and Communication Technology (ICT) in logistics performance on road transportation is expressed in terms of operation cost and turns rotund time. Though, numerous effects known from the utilization of ICT in the road transportation and importance of vehicle tracking for logistics industry is immeasurable. The most basic use of a GPS device is, of course, tracking vehicle locations an extremely useful device to companies that use a fleet of vehicles in their line of business. Tracking for logistics industry can also provide information necessary to fleet management for instance if the driver has done his distribution task, the time or estimated time of completion, the place, rapidity, etc. With GPS tracking for logistics industry, you are conscious of the actions of fleet at any given time. Design/methodology/approach: This analysis thus seeks to fill the gap of knowledge by examining the influence of ICT on logistics performance on road transport. Keeping in today's technology requirement, resources, the leading web-based ERP solution providers in India, offers a powerful and efficient ERP solution for logistic and warehouse management. Practical Implication: This research would be useful to understand the Logistics ERP software symbolizes an advanced manner of organizing, shipping and transport associated processes with comfort and convenience. Findings: This paper scrutinizes the influence of ICT on logistics by conducting a survey of writings on academic logistics magazines, newsletters and articles. It founds an outline for analysing the effect of information technology on road transport in terms of e-commerce, logistics and suggests theoretical mechanisms of impact. © ExcelingTech Pub, UK.","Enterprise Resource Planning (ERP); GPS tracking; Information and communication technology (ICT); Logistics performance; Road transport",{"$nulls":7},"Esposito E., Mastroianni M., Information technology and personal computers: the relational life cycle, Technovation, 22, 1, pp. 41-50, (2002); Hazen B.T., Byrd T.A., Toward creating competitive advantage with logistics information technology, International Journal of Physical Distribution & Logistics Management, 42, 1, pp. 8-35, (2012); Giannopoulos G.A., The application of information and communication technologies in transport, European Journal of Operational Research, 152, 2, pp. 302-320, (2004); Hong E., Son B., Menachof D., Exploring the link between IT systems and outsourcing of logistics activities: a transaction cost perspective, International Journal of Logistics: Research and Applications, 13, 1, pp. 41-58, (2010); Wallenburg C.M., Lukassen P., Proactive improvement of logistics service providers as driver of customer loyalty, European Journal of Marketing, 45, 3, pp. 438-454, (2011); Forslund H., Performance management in supply chains: logistics service providers' perspective, International Journal of Physical Distribution & Logistics Management, 42, 3, pp. 296-311, (2012); Zhuravleva O., Information technology and systems in transport supply chains, (2013); Western J.L., Ran B., Information Technology in Transportation Key Issues and a Look Forward, (2000); Harris I., Wang Y., Wang H., ICT in multimodal transport and technology trends: unleashing potential for the future, Int. J. Prod. Econ, 159, pp. 88-103, (2015); Wong C.W.Y., Lai K.H., Ngai E.W.T., The role of supplier operational adaptation on the performance of IT-enabled transport logistics under environmental uncertainty, Int. J. Prod. Econ, 122, pp. 47-55, (2009); Zomer G., Anten N., Vision on the crucial role of ITS for efficient and green European Logistics, In: Proceedings of the 15th World Congress on ITS, (2008); Hines M., Judicial Enforcement of Variable Speed Limits. National Cooperative Highway Research Program Legal Research Digest 47, Transportation Research Board, (2002); Toh K.T.K., Nagel P., Oakden R., A business and ICT infrastructure for a logistics city, Int. J. Prod. Econ, 122, pp. 216-228, (2009); Coronado Mondragon A.E., Lalwani C.S., Coronado Mondragon E.S., Coronado Mondragon E.S., Facilitating multi-modal logistics and enabling information systems connectivity through wireless vehicular networks, Int. J. Prod. Econ, 122, 1, pp. 229-240, (2009); Emmerink R.H.M., Nijkamp P., Rietveld P., Van Ommeren J.N., Variable message signs and radio traffic information: an integrated empirical analysis of drivers' route choice behaviour, Transp. Res. Part A Policy Pract, 30, pp. 135-153, (1996); Mokhtarian P.L., Tal G., Impacts of ICT on travel behavior: a tapestry of relationships, The Sage Handbook of Transport Studies, pp. 241-260, (2013); Marchet G., Perego A., Perotti S., An exploratory study of ICT adoption in the Italian freight transportation industry, Int. J. Phys. Distrib. Logist. Manag, 39, 9-10, pp. 785-812, (2009); Pokharel S., Lee C.K.M., '-Analyzing the Use of Information Systems in Logistics Industry', (2009); Perego A., Perotti S., Mangiaracina R., ICT for logistics and freight transportation: a literature review and research agenda, International Journal of Physical Distribution & Logistics Management, 41, 5, pp. 457-483, (2011); Pokharel S., Perception on information and communication technology perspectives in logistics-a study or transportation and warehouse sectors in Singapore, The Journal of Enterprise Information Management, 18, 2, pp. 136-149, (2005); Zunder T., Islam M., E-Logistics Systems Applications for Service Users and Providers, Transportation Research Record: Journal of the Transportation Research Board, 2238, 1, pp. 50-60, (2011); Townsend A., Mobile Communication and Sustainable Transportation: An Agenda for Research and Action, STELLA Focus Group 2 Synthesis meeting, (2004); Lee-Gosselin M., \"GPS Supported Travel Survey Methods\", (2002); Evangelista P., Sweeney E., Technology usage in the supply chain: the case of small 3PLs, The International Journal of Logistics Management, 17, 1, pp. 55-74, (2006); Hidalgo A., Lopez V., Drivers and impacts of ICT adoption on transport and logistics services, Asian Journal of Technology Innovation, 17, 2, pp. 27-47, (2009)",null,null,"Islamic Azad University",{"$nulls":5},"2345377X",null,null,null,"English","Majlesi J. Electr. Eng.","Article","Final",null,"Scopus","2-s2.0-85082372964"]
["Vyasa Bharadwaja A.; Ganesan V.","Vyasa Bharadwaja, A. (56845823600); Ganesan, V. (56381050900)","56845823600; 56381050900","A survey on security analysis and privacy issues of wireless multimedia communication system",2019.0,"International Journal of Electronic Security and Digital Forensics",11.0,3.0,null,338.0,346.0,8.0,0.0,"10.1504/IJESDF.2019.100484","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85068319370&doi=10.1504%2fIJESDF.2019.100484&partnerID=40&md5=c95474a0d898c7f2fcd169f11c54a286","Sathyabama Institute of Science and Technology, Jeppiaar Nagar, Rajiv Gandhi Salai, Chennai, 600-119, Tamilnadu, India","Vyasa Bharadwaja A., Sathyabama Institute of Science and Technology, Jeppiaar Nagar, Rajiv Gandhi Salai, Chennai, 600-119, Tamilnadu, India; Ganesan V., Sathyabama Institute of Science and Technology, Jeppiaar Nagar, Rajiv Gandhi Salai, Chennai, 600-119, Tamilnadu, India","Wireless multimedia communication (WMC) is an emerging service that integrates voice, video, and data in the same service. The wireless handheld device used to provide multimedia communication such as PDA, Sensor, Mobile phones etc., are resource constrained and also need security protocol for successful multimedia communication between server and user. Many researchers are put their effort to develop secure cryptography algorithms and protocol to allow the user to access the data securely in telemedicine, surveillance system, and video on demand, digital cash, online shopping, digital content delivery and video conferencing technology. This paper focuses on security analysis of different encryption algorithm, secure architecture, encoding algorithm, authentication protocol and video encoding method. It also discuss about security multimedia challenges, characteristics, multimedia services, different attacks, software information and forecasts future perspectives of wireless multimedia technology. Copyright © 2019 Inderscience Enterprises Ltd.","Authentication; DNA cryptographic algorithm; Elliptic curve cryptography; Privacy; Secure accumulation; Security; Wireless multimedia communication; WMC","Authentication; Bioinformatics; Data privacy; Encoding (symbols); Multimedia services; Network architecture; Online conferencing; Public key cryptography; Security systems; Signal encoding; Video conferencing; Video on demand; Video signal processing; Cryptographic algorithms; Elliptic curve cryptography; Secure accumulation; Security; Wireless multimedia communications; Multimedia systems",{"$nulls":6},"Al Zamil M.G.H., Rawashdeh M., Samarah S., Hossain M.S., Alnusair A., Rahman S.M.M., An annotation technique for in-home smart monitoring environments, IEEE Access, 6, pp. 1471-1479, (2017); Al-Adhami A., Ambroze M., Stengel I., Tomlinson M., A 256 bit implementation of ECC-RFID based system using Shamir secret sharing scheme and Keccak hash function, ICUFN, (2017); Amin R., Sherratt R.S., Giri D., Islam S.H., Khan M.K., A software agent enabled biometric security algorithm for secure file access in consumer storage devices, IEEE Transactions on Consumer Electronics, 63, 1, pp. 53-61, (2017); Amjad M., Rehmani M.H., Mao S., Wireless multimedia cognitive radio networks: A comprehensive survey, IEEE Communications Surveys and Tutorials, 20, 2, pp. 1056-1103, (2017); Arteaga-Falconi J.S., Al Osman H., El Saddik A., ECG authentication for mobile devices, IEEE Transactions on Instrumentation and Measurement, 65, 3, pp. 5591-5600, (2016); Aydos M., Yanik T., Koc C.K., High-speed implementation of an ECC-based wireless authentication protocol on an ARM microprocessor, IEEE Proc. Commun., 148, 5, pp. 273-279, (2001); Bernatin T., Kuzhaloli S., Premi M.S.G., Queen L.B., Perceptual video encryption in multimedia secure communication, Online International Conference on Green Engineering and Technologies, (2016); Boncelet C.G., The NTMAC for authentication of noisy messages, IEEE Transactions on Information Forensics and Security, 1, 1, pp. 35-42, (2006); Carla L., Fantacci R., Gei F., Marabisssi D., Micciullo L., LTE enhancements for public safety and security communications to support group multimedia communications, IEEE Network, (2016); Cui H., Yuan X., Wang C., Harnessing encrypted data in cloud for secure and efficient mobile image sharing, IEEE Transactions on Mobile Computing, 16, 5, pp. 1315-1329, (2017); Cui J., Zhang J., Zhong H., Xu Y., SPACF: A secure privacy-preserving authentication scheme for VANET with Cuckoo filter, IEEE Transactions on Vehicular Technology, 66, 11, (2017); Desai N., Juvekar C., Chandak S., Chandrakasan A.P., An actively detuned wireless power receiver with public key cryptographic authentication and dynamic power allocation, IEEE Journal of Solid-State Circuits, 53, 1, pp. 366-367, (2018); Foschini L., Taleb T., Corradi A., Bottazzi D., M2M-based metropolitan platform for IMS-enabled road traffic management in IoT, IEEE Communications Magazine, 49, 11, pp. 50-57, (2011); Grieco L.A., Boggia G., Sicari S., Colombo P., Secure wireless multimedia sensor networks: A survey, Third International Conference on Mobile Ubiquitous Computing Systems, Services and Technologies, (2009); Harjito B., Han S., Wireless multimedia sensor networks applications and security challenges, International Conferences on Broadband, Wireless Computing, Communication and Applications, (2010); Harjito B., Han S., Potdar V., Chang E., Xie M., Multimedia sensor networks using watermarking, 4th IEEE International Conference on Digital Ecosystems and Technologies, (2010); Hayajneh T., Ullah S., Mohd B.J., Balagani K.S., An enhanced WLAN security system with FPGA implementation for multimedia applications, IEEE Systems Journal, 11, 4, pp. 2536-2545, (2017); Hsu C.-L., Chuang T.-S., Chen Y.-H., Lin T.-W., Lu H.-C., A dynamic identity end-to-end authentication key exchange protocol for IoT environments, Twelfth International Conference on Digital Information Management (ICDIM), pp. 133-138, (2017); Hwu J.-H., Chen R.-J., Lin Y.-B., An efficient identity-based crytposystem for end-to-end mobile security, IEEE Transactions on Wireless Communications, 5, 9, pp. 133-138, (2006); Jia Y., Sun B., Zhu Q., A strategy of node membership verification for wireless multimedia sensor networks, IEEE, pp. 1-4, (2009); Jolfaei A., Wu X.-W., Muthukumarasamy V., On the security of permutation-only image encryption schemes, IEEE Transactions on Information Forensics and Security, 11, 2, pp. 235-246, (2016); Kankonkar J.T., Naik N., Image security using image encryption and image stitching, Proceedings of the IEEE 2017 International Conference on Computing Methodologies and Communication (ICCMC), (2017); Kuppuswamy P., Banu R., Rekha N., Preventing and Securing Data from Cyber Crime Using New Authentication Method Based on Block Cipher Scheme, (2017); Lauter K., The advantages of elliptic curve cryptography for wireless security, IEEE Wireless Communication, (2004); Li C., Lin D., Cryptanalyzing an image-scrambling encryption algorithm of pixel bits, IEEE Computer Society, 24, 3, pp. 64-71, (2017); Lin Y.-T., Wang C.-M., Chen W.-S., Lin F.-P., Lin W., A novel data hiding algorithm foe highly dynamic range images, IEEE Transactions on Multimedia, 19, 1, (2017); Liu X., Sun C., Kang K., Zhang L., Joint 3-D image quality assessment metric by using image view and depth information over the networking in IoT, IEEE Systems Journal, 10, 3, (2016); Liu Z., Seo H., Grobschadl J., Kim H., Efficient implementation of NIST-complaint elliptic curve cryptography for 8 bit AVR-based sensor nodes, IEEE Transactions on Information Forensics and Security, 11, 7, pp. 1385-1397, (2016); Mishra D., Vijayakumar P., Sureshkumar V., Amin R., Islam S.K.H., Gope P., Efficient authentication protocol for secure multimedia communications in IoT-enabled wireless sensor networks, Multimedia Tools and Applications, Part of Springer Nature, (2017); Mstafa R.J., Elleithy K.M., Abdelfattah E., A Robust and Secure Video Steganography Method in DWT-DCT Domains Based on Multiple Object Tracking and ECC, (2017); Odelu V., Das A.K., Choo K.-K.R., Kumar N., Park Y., Efficient and secure time-key based single sign-on authentication for mobile devices, IEEE, 5, pp. 22707-27721, (2017); Pramudita R., Hariadi F.I., Suwandi A., Development of IoT authentication mechanisms for microgrid applications, International Symposium on Electronics and Smart Devices, (2017); Ren Y., Chen J.-C., Chin J.-C., Tseng Y.-C., Design and analysis of the key management mechanism in evolved multimedia broadcast/multicast service, IEEE Transactions on Wireless Communications, 15, 12, pp. 8463-8476, (2016); Sun H.-M., Leu M.-C., An efficient authentication scheme for access control in mobile pay-TV systems, IEEE Transactions on Multimedia, 11, 5, pp. 1248-1259, (2009); Sun Q., Chang S.-F., A secure and robust digital signature scheme for JPEG2000 image authentication, IEEE Transactions on Multimedia, 7, 3, pp. 1-46, (2005); Sun Q., Ye S., Lin C.-Y., Chang S.-F., A crypto signature scheme for image authentication over wireless channel, IEEE International Conference on Multimedia and Expo, (2004); Suryadevara J., Sunil B., Kumar N., Secured multimedia authentication system for wireless sensor network data related to internet of things, Seventh International Conference on Sensing Technology, (2013); Tian X., Wong D.S., Zhu R.W., Analysis and Improvement of an authentication key exchange protocol for sensor networks, IEEE Communications Letters, 9, 11, pp. 970-972, (2005); Ullah S., Li X.-Y., Zhang L., A review of signcryption schemes based on hyper elliptic curve, 3rd International Conference on Big Data Computing and Communications, (2017); Vijayakumar P., Rajashree R., Hybrid A., Secure architecture for passport verification system using visual cryptography and steganography, Journal of Chemical and Pharmaceutical Sciences, 10, pp. 74-78, (2015); Vijayakumar P., Indupriya S., Rajashree R., A hybrid multilevel security scheme using DNA computing based color code and elliptic curve cryptography, Indian Journal of Science and Technology, 9, 10, pp. 1-7, (2016); Vijayakumar P., Vijayalakshmi V., Zayaraz G., An improved level of security for DNA steganography using hyperelliptic curve cryptography, SPRINGER – Wireless Personal Communications, 89, 4, pp. 1221-1242, (2016); Wang W., Wang Q., Sohraby K., Multimedia sensing as a service (MSaaS): Exploring resource saving potentials of at cloud-edge IoT and fogs, IEEE Internet of Things Journal, 4, 2, pp. 487-495, (2017); Wang Z., Mao S., Yang L., Tang P., A survey of multimedia big data, China Communications, 15, 1, pp. 155-176, (2018); Xia Y., Chen W., Liu X., Zhang L., Li X., Xiang Y., Adaptive multimedia data forwarding for privacy preservation in vehicular ad hoc networks, IEEE Transactions on Intelligent Transportation Systems, 18, 10, pp. 1-12, (2017); Yang K., Liu Z., Jia X., Shen X.S., Time-domain attribute-based access control for cloud-based video content sharing: A cryptographic approach, IEEE Transactions on Multimedia, 18, 5, pp. 940-950, (2016); Yao R., Wang W., Farrok-Baroughi M., Quality-driven energy-neutralized power and relay selection for smart grid wireless sensor based IoTs, IEEE Sensors Journal, 13, 10, pp. 3637-3644, (2013); Yeh L.-Y., Tsaur W.-J., A secure and efficient authentication scheme for access control in mobile pay-TV systems, IEEE Transactions on Multimedia, 14, 16, pp. 1690-1693, (2012); Zhu X., Chen C.W., A joint source-channel adaptive scheme for wireless H.264/ AVC video authentication, IEEE Transactions on Information Forensics and Security, 11, 1, pp. 141-153, (2016)","A. Vyasa Bharadwaja; Sathyabama Institute of Science and Technology, Chennai, Jeppiaar Nagar, Rajiv Gandhi Salai, 600-119, India; email: bharadwaja.akondi@gmail.com",null,"Inderscience Publishers",{"$nulls":5},"1751911X",null,null,null,"English","Int. J. Electron. Secur. Digit. Forensics","Article","Final",null,"Scopus","2-s2.0-85068319370"]
["Erum M.; Waqas M.; Arshad S.; Nawaz T.","Erum, Maria (57412696700); Waqas, Muhammad (57204216008); Arshad, Sidra (57218626559); Nawaz, Tahir (58485156100)","57412696700; 57204216008; 57218626559; 58485156100","Features Analysis of Online Shopping System Using WCM",2018.0,"EAI Endorsed Transactions on Scalable Information Systems",5.0,16.0,null,1.0,8.0,7.0,1.0,"10.4108/eai.13-4-2018.154471","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85122847661&doi=10.4108%2feai.13-4-2018.154471&partnerID=40&md5=d40558e53cf114ed7863f0713175cb25","Department of Computer Science, The University of Lahore, Sargodha Campus, Pakistan","Erum M., Department of Computer Science, The University of Lahore, Sargodha Campus, Pakistan; Waqas M., Department of Computer Science, The University of Lahore, Sargodha Campus, Pakistan; Arshad S., Department of Computer Science, The University of Lahore, Sargodha Campus, Pakistan; Nawaz T., Department of Computer Science, The University of Lahore, Sargodha Campus, Pakistan","Data mining techniques being used for web information extraction are unbelievable systems and suggested for the protection of extremely susceptible data. By the web sources huge amount of data is maintained and can be easily retrieved by using the web mining techniques as the techniques are applied exactly based on the needs of the users. ECommerce and online shopping noticed a huge growth in business industry. This facility has been mostly employed in western countries during the last two decades. In east online shopping is increasing as most of the business is running through web site as well as in west. This business can be boost by feature analysis of different successful running online web stores. This study is going to present analysis of different features of successful online business website and of those which are not that much popular and accessed infrequently, their features will be extracted and compared to get the reasons of popularity of frequently accessed online shopping websites and after that recommendations will be made to increase the traffic of unpopular online shopping websites to dominate online business in Pakistan. According to the presented work it has been concluded that unpopular websites lack some features that are included in popular websites such as brands, as people are more conscious about brands and labels so they visit and shop from the websites which offer them best quality famous brands, moreover it has been observed that unpopular websites have less categories they must broaden their variety of products especially related to sports, fitness, bathroom accessories, technology and cosmetics. Apart from these another interesting fact that has been found is that popular websites mostly attract their customers by giving them offers such as buy one get one free, free home delivery and free gifts, such offers are always attracting new and more customers. Unpopular websites can improve their business by including the features discussed above. The results of research on this dataset also show that the Naïve bayes is better than j48 in terms of efficiency and accuracy respectively. © 2018 Maria Erum et al., licensed to EAI. This is an open access article distributed under the terms of theCreative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.","Classification; Data Mining Techniques; Decision Tree; J48; Naïve Bayes; Online Shopping; WCM (Web Content Mining)","Electronic commerce; Sports; Websites; Business industry; Feature analysis; Home delivery; On-line Shopping systems; Online business; Online shopping; Web information extraction; Western countries; Data mining",{"$nulls":6},"chaturvedi M., Vidyapeeth J., A SURVEY ON WEB MINNING Algorithms, (2013); Menaka C., Nagadeepa N., A Survey of WCM Tools and Future Aspects; Johnson F., Gupta S.K., WCM Techniques: A Survey, 47, 11, (2012); Sarlaet R., Analysis & Approaches of Web Mining Prof, (2015); Liu B., Chiang K. C., Editorial Special Issue onWCM,Acm, Journal of Machine Learning Research, 4, pp. 177-210; Liu W., Et al., ViDE: A Vision -based Approach for Deep Web Data Extraction, IEEE Transactions on Knowledge and Data Engineering, 22, 3, pp. 447-460, (2010); Guo J., Keselj V., Gao Q., Integrating Web Content Clustering Into Web Log Association Rule Mining, SpringerVerlag, 3501, pp. 182-193, (2005); Miao G., Et al., Extracting Data Records from the Web Using Tag Path Clustering, International World Wide Web conference Committee (IW3C2), pp. 981-990, (2009); Gedovet al V., Matching Web Site Structure andContent, Proceedings ofthe 13th International World Wide Web Conference on Alternate Track Papers and Posters, (2004); Miao Gengxin, Tatemura Junichi, Hsiung Wang -pin, Sawires Arsany, Moser Louise E., Extracting Data Records from the Web Using Tag Path Clustering, Interna tional World Wide Web conference Committee (IW3C2), pp. 981-990, (2009); Liu Wei, Meng Xiaofeng, Meng Weiyi, ViDE: A Vision-based Approach for Deep Web Data Extraction, IEEE Transactions on Knowledge and Data Engineering, 22, 3, pp. 447-460, (2010)","T. Nawaz; Department of Computer Science, The University of Lahore, Sargodha Campus, Pakistan; email: tahir.nawaz@cs.uol.edu.pk",null,"European Alliance for Innovation",{"$nulls":5},2.0329407E7,null,null,null,"English","Endor. Trans. Scalable. Inf. Syst.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85122847661"]
["Abadi S.; Huda M.; Hehsan A.; Mohamad A.M.; Basiron B.; Ihwani S.S.; Jasmi K.A.; Safar J.; Mohamed A.K.; Wan Embong W.H.; Mohd Noor S.S.; Brahmono B.; Maseleno A.; Fauzi A.N.; Aminudin N.; Gumanti M.","Abadi, Satria (57203514043); Huda, Miftachul (56712456800); Hehsan, Aminudin (57190000565); Mohamad, Ahmad Marzuki (57211550287); Basiron, Bushrah (56287824600); Ihwani, Siti Suhaila (57196465095); Jasmi, Kamarul Azmi (56263553200); Safar, Jimaain (57192976911); Mohamed, Ahmad Kilani (57211320307); Wan Embong, Wan Hassan (57195613316); Mohd Noor, Sulaiman Shakib (57215914932); Brahmono, Boris (57215917856); Maseleno, Andino (55354910900); Fauzi, Almira Nabila (57215914389); Aminudin, Nur (57210387886); Gumanti, Miswan (57215918048)","57203514043; 56712456800; 57190000565; 57211550287; 56287824600; 57196465095; 56263553200; 57192976911; 57211320307; 57195613316; 57215914932; 57215917856; 55354910900; 57215914389; 57210387886; 57215918048","Design of online transaction model on traditional industry in order to increase turnover and benefits",2018.0,"International Journal of Engineering and Technology(UAE)",7.0,"2.27 Special Issue  27",null,231.0,237.0,6.0,29.0,"10.14419/ijet.v7i2.31.13449","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85067270798&doi=10.14419%2fijet.v7i2.31.13449&partnerID=40&md5=d97cdfd95b05348dbe04b1014fd6dc1d","Department of Information Systems, STMIK Pringsewu, Lampung, Indonesia; Faculty of Social Sciences and Humanities, Universiti Teknologi Malaysia, Malaysia; Institute of Informatics and Computing Energy, Universiti Tenaga Nasional, Malaysia; Faculty of Business, Monash University, Malaysia","Abadi S., Department of Information Systems, STMIK Pringsewu, Lampung, Indonesia; Huda M., Faculty of Social Sciences and Humanities, Universiti Teknologi Malaysia, Malaysia; Hehsan A., Faculty of Social Sciences and Humanities, Universiti Teknologi Malaysia, Malaysia; Mohamad A.M., Faculty of Social Sciences and Humanities, Universiti Teknologi Malaysia, Malaysia; Basiron B., Faculty of Social Sciences and Humanities, Universiti Teknologi Malaysia, Malaysia; Ihwani S.S., Faculty of Social Sciences and Humanities, Universiti Teknologi Malaysia, Malaysia; Jasmi K.A., Faculty of Social Sciences and Humanities, Universiti Teknologi Malaysia, Malaysia; Safar J., Faculty of Social Sciences and Humanities, Universiti Teknologi Malaysia, Malaysia; Mohamed A.K., Faculty of Social Sciences and Humanities, Universiti Teknologi Malaysia, Malaysia; Wan Embong W.H., Faculty of Social Sciences and Humanities, Universiti Teknologi Malaysia, Malaysia; Mohd Noor S.S., Faculty of Social Sciences and Humanities, Universiti Teknologi Malaysia, Malaysia; Brahmono B., Department of Information Systems, STMIK Pringsewu, Lampung, Indonesia; Maseleno A., Department of Information Systems, STMIK Pringsewu, Lampung, Indonesia, Institute of Informatics and Computing Energy, Universiti Tenaga Nasional, Malaysia; Fauzi A.N., Faculty of Business, Monash University, Malaysia; Aminudin N., Department of Information Systems, STMIK Pringsewu, Lampung, Indonesia; Gumanti M., Department of Information Systems, STMIK Pringsewu, Lampung, Indonesia","Online transactions are transactions made sellers and buyers online through the Internet media, there is no direct encounter between buyers and sellers. Currently with the rapid development of technology and the Internet in Indonesia, has had a great impact on the change of industrial business. That is starting from the way advertising, buying and selling, how to interact between humans, and so forth. With ecommerce has changed a lot in the process of buying and selling. Panda Alami is one of the banana chips industry established since 1998 in Cipadang Pesawaran village. This banana chips industry still uses manual way in transaction process. To increase the turnover and profit that is the purpose of this study, the transaction model is developed with SDLC (System Development Life Cycle) and software used to design and design this application is PHP programming language, MySQL Database and Adobe Photoshop CS3. Features include product search, order, delivery and payment confirmation and thus provide integration of the entire inventory unit sales network. An equally important factor is trust. In this process trust is the main capital. Because without the trust of both parties, then the process of online transactions can not happen and done. © 2018 Satria Abadi et. al.","E-Commerce; Internet; Online transaction; Traditional industry",{"$nulls":7},"Sri Haryanti T.I., Rancang Bangun Sistem Informasi E-Commerce untuk Usaha Fashion Study Kasus Omah Mode, Speed 13 FTI UNSA, 9, (2012); Artati Rejeki R.S., Utomo A.P., dan Stefi-Ana S.S., Perancangan dan Pengaplikasian Sistem Penjualan pada \"Distro Smith\" Berbasis ECommerce, (2011); Jogiyanto H.M., Perancangan Dan Pengaplikasian Sistem Penjualan Pada \"Distro Smith\" Berbasis E-commerce, (2005); Aplikasi Penjualan Online Berbasis Web Pada CV Monreal, (2008); Website Penjualan Hand Phone Online, (2006); Adela H., Jasmi K.A., Basiron B., Huda M., Maseleno A., Selection of dancer member using simple additive weighting, International Journal of Engineering & Technology, 7, 3, pp. 1096-1107, (2018); Aminin S., Huda M., Ninsiana W., Dacholfany M.I., Sustaining civic-based moral values: Insights from language learn-ing and literature, International Journal of Civil Engineering and Technology, 9, 4, pp. 157-174, (2018); Amin M.M., Nugratama M.A.A., Maseleno A., Huda M., Jasmi K.A., Design of cigarette disposal blower and automatic freshner using mq-5 sensor based on atmega 8535 microcontroller, International Journal of Engineering & Technology, 7, 3, pp. 1108-1113, (2018); Atmotiyoso P., Huda M., Investigating Factors Influ-encing Work Performance on Mathematics Teaching: A Case Study, International Journal of Instruction, 11, 3, pp. 391-402, (2018); Huda M., Teh K.S.M., Empowering Professional and Ethical Competence on Reflective Teaching Practice in Digital Era, Mentorship Strategies in Teacher Education, pp. 136-152, (2018); Huda M., Teh K.S.M., Nor N.H.M., Nor M.B.M., Transmitting Leadership Based Civic Responsibility: Insights from Service Learning, International Journal of Ethics and Systems, 34, 1, pp. 20-31, (2018); Huda M., Maseleno A., Muhamad N.H.N., Jasmi K.A., Ahmad A., Mustari M.I., Basiron B., Big Data Emerging Tech-nology: Insights into Innovative Environment for Online Learning Resources, International Journal of Emerging Technologies in Learning, 13, 1, pp. 23-36, (2018); Huda M., Maseleno A., Teh K.S.M., Don A.G., Basiron B., Jasmi K.A., Mustari M.I., Nasir B.M., Ahmad R., Understanding Modern Learning Environment (MLE) in Big Data Era, International Journal of Emerging Technologies in Learning, 13, 5, pp. 71-85, (2018); Huda M., Empowering Application Strategy in the Tech-nology Adoption: Insights from Professional and Ethical Engage-ment, Journal of Science and Technology Policy Management, (2018); Huda M., Sabani N., Empowering Muslim Children's Spirituality in Malay Archipelago: Integration between National Philosophical Foundations and Tawakkul (Trust in God), Interna-tional Journal of Children's Spirituality, 23, 1, pp. 81-94, (2018); Huda M., Qodriah S.L., Rismayadi B., Hananto A., Kardiyati E.N., Ruskam A., Nasir B.M., Towards Cooperative with Competitive Alliance: Insights into Performance Value in So-cial Entrepreneurship, Creating Business Value and Competitive Advantage with Social Entrepreneurship, (2018); Huda M., Hehsan A., Basuki S., Rismayadi B., Jasmi K.A., Basiron B., Mustari M.I., Empowering Technology Use to Promote Virtual Violence Prevention in Higher Education Con-text, In Intimacy and Developing Personal Relationships in the Vir-tual World, pp. 272-291, (2019); Huda M., Ulfatmi Luthfi M.J., Jasmi K.A., Basiron B., Mustari M.I., Safar A., Embong H.W.H., Mohamad A.M., Mohamed A.K., Adaptive online learning technology: Trends in big data era in Diverse Learning Opportunities Through Technology-Based Curriculum Design, (2019); Kurniasih D., Jasmi K.A., Basiron B., Huda M., Maseleno A., The uses of fuzzy logic method for finding agriculture and livestock value of potential village, International Journal of Engi-neering & Technology, 7, 3, pp. 1091-1095, (2018); Maseleno A., Pardimin Huda M., Ramlan Hehsan A., Yusof Y.M., Haron Z., Ripin M.N., Nor N.H.M., Junaidi J., Mathematical Theory of Evidence to Subject Expertise Diagnostic, ICIC Express Letters, 12, 4, (2018); Maseleno A., Huda M., Jasmi K.A., Basiron B., Mustari I., Don A.G., Ahmad R., Hau-Kashyap approach for student's level of expertise, Egyptian Informatics Journal, (2018); Maseleno A., Sabani N., Huda M., Ahmad R., Jasmi K.A., Basiron B., Demystifying Learning Analytics in Personal-ised Learning, International Journal of Engineering & Technology, 7, 3, pp. 1124-1129, (2018); Moksin A.I., Shahrill M., Anshari M., Huda M., Tengah K.A., The Learning of Integration in Calculus Using the Auto-graph Technology, Advanced Science Letters, 24, 1, pp. 550-552, (2018); Putra D.A.D., Jasmi K.A., Basiron B., Huda M., Maseleno A., Shankar K., Aminudin N., Tactical Steps for E-Government Development, International Journal of Pure and Ap-plied Mathematics, 119, 15, pp. 2251-2258, (2018); Rosli M.R.B., Salamon H.B., Huda M., Distribution Management of Zakat Fund: Recommended Proposal for Asnaf Riqab in Malaysia, International Journal of Civil Engineering and Technology, 9, 3, pp. 56-64, (2018); Sugiyarti E., Jasmi K.A., Basiron B., Huda M., Shankar K., Ma-seleno A., Decision support system of scholarship grantee selection using data mining, International Journal of Pure and Ap-plied Mathematics, 119, 15, pp. 2239-2249, (2018); Sundari E., Jasmi K.A., Basiron B., Huda M., Maseleno A., Web-Based Decision Making System for Assessment of Employee Revenue using Weighted Product, International Journal of Engineering and Technology, (2018); Susilowati T., Jasmi K.A., Basiron B., Huda M., Shankar K., Maseleno A., Julia A.S., Determination of Scholar-ship Recipients Using Simple Additive Weighting Method, Interna-tional Journal of Pure and Applied Mathematics, 119, 15, pp. 2231-2238, (2018); Anshari M., Almunawar M.N., Shahrill M., Wicaksono D.K., Huda M., Smartphones usage in the classrooms: Learning aid or interference, Education and Information Technologies, 22, 6, pp. 3063-3079, (2017); Huda M., Sabani N., Shahrill M., Jasmi K.A., Basiron B., Mustari M.I., Empowering Learning Culture as Student Identity Construction in Higher Education, Student Culture and Identity in Higher Education, pp. 160-179, (2017); Huda M., Jasmi K.A., Hehsan A., Shahrill M., Mustari M.I., Basiron B., Gassama S.K., Empowering Children with Adaptive Technology Skills: Careful Engagement in the Digital Information Age, International Electronic Journal of Elementary Education, 9, 3, pp. 693-708, (2017); Huda M., Shahrill M., Maseleno A., Jasmi K.A., Mustari I., Basiron B., Exploring Adaptive Teaching Competencies in Big Data Era, International Journal of Emerging Technologies in Learning, 12, 3, pp. 68-83, (2017); Huda M., Jasmi K.A., Basiran B., Mustari M.I.B., Sabani A.N., Traditional Wisdom on Sustainable Learning: An Insightful View From Al-Zarnuji's Ta 'lim al-Muta 'allim, SAGE Open, 7, 1, pp. 1-8, (2017); Huda M., Jasmi K.A., Embong W.H., Safar J., Mohamad A.M., Mohamed A.K., Muhamad N.H., Alas Y., Rahman S.K., Nurturing Compassion-Based Empathy: Innovative Approach in Higher Education, Violence Prevention and Safety Promotion in Higher Education Settings, pp. 154-173, (2017); Huda M., Jasmi K.A., Alas Y., Qodriah S.L., Dacholfany M.I., Jamsari E.A., Empowering Civic Responsibility: Insights From Service Learning, Engaged Scholarship and Civic Responsibility in Higher Education, pp. 144-165, (2017); Huda M., Jasmi K.A., Mustari M.I., Basiron B., Mohamed A.K., Embong W., Safar J., Innovative E-Therapy Service in Higher Education: Mobile Application Design, International Journal of Interactive Mobile Technologies, 11, 4, pp. 83-94, (2017); Huda M., Jasmi K.A., Mustari M.I., Basiron B., Understanding Divine Pedagogy in Teacher Education: Insights from Al-zarnuji's Ta'lim Al-Muta'Allim, The Social Sciences, 12, 4, pp. 674-679, (2017); Huda M., Jasmi K.A., Mustari M.I.B., Basiron A.B., Understanding of Wara' (Godliness) as a Feature of Character and Religious Education, The Social Sciences, 12, 6, pp. 1106-1111, (2017); Huda M., Siregar M., Ramlan Rahman S.K.A., Mat Teh K.S., Said H., Jamsari E.A., Yacub J., Dacholfany M.I., Ninsiana W., From Live Interaction to Virtual Interaction: An Exposure on the Moral Engagement in the Digital Era, Journal of Theoretical and Applied Information Technology, 95, 19, pp. 4964-4972, (2017); Huda M., Maseleno A., Jasmi K.A., Mustari I., Basiron B., Strengthening Interaction from Direct to Virtual Basis: Insights from Ethical and Professional Empowerment, International Journal of Applied Engineering Research, 12, 17, pp. 6901-6909, (2017); Huda M., Haron Z., Ripin M.N., Hehsan A., Yaacob A.B.C., Exploring Innovative Learning Environment (ILE): Big Data Era, International Journal of Applied Engineering Research, 12, 17, pp. 6678-6685, (2017); Maseleno A., Huda M., Siregar M., Ahmad R., Hehsan A., Haron Z., Ripin M.N., Ihwani S.S., Jasmi K.A., Combining the Previous Measure of Evidence to Educational Entrance Examination, Journal of Artificial Intelligence, 10, 3, pp. 85-90, (2017); Huda M., Anshari M., Almunawar M.N., Shahrill M., Tan A., Jaidin J.H., Masri M., Innovative Teaching in Higher Education: The Big Data Approach, The Turkish Online Journal of Educational Technology, 15, pp. 1210-1216, (2016); Huda M., Yusuf J.B., Jasmi K.A., Nasir G.A., Un-derstanding Comprehensive Learning Requirements in the Light of al-Zarnuji's Talim al-Mutaallim, Sage Open, 6, 4, pp. 1-14, (2016); Huda M., Yusuf J.B., Jasmi K.A., Zakaria G.N., Al-Zarnuji's Concept of Knowledge ('ilm), SAGE Open, 6, 3, pp. 1-13, (2016); Huda M., Jasmi K.A., Mohamed A.K., Wan Embong W.H., Safar J., Philosophical Investigation of Al-Zarnuji's Ta'lim al-Muta'allim: Strengthening Ethical Engagement into Teaching and Learning, Social Science, 11, 22, pp. 5516-5551, (2016); Kartanegara M., Huda M., Constructing Civil Society: An Islamic Cultural Perspective, Mediterranean Journal of Social Science, 7, 1, pp. 126-135, (2016); Othman R., Shahrill M., Mundia L., Tan A., Huda M., Investigating the Relationship between the Student's Ability and Learning Preferences: Evidence from Year 7 Mathematics Students, The New Educational Review, 44, 2, pp. 125-138, (2016); Wulandari Aminin S., Dacholfany M.I., Mujib A., Huda M., Na-sir B.M., Maseleno A., Sundari E., Fauzi Masrur M., Design of Library Application System, International Journal of Engineering and Technology (UAE); Susilowati T., Teh K.S.T., Nasir B.M., Don A.G., Huda M., Hensafitri T., Maseleno A., Oktafianto Irawan D., Learning Application of Lampung Language Based on Multimedia Software, International Journal of Engineering and Technology (UAE); Abadi S., Teh K.S.M., Nasir B.M., Huda M., Ivanova N.L., Sari T.I., Maseleno A., Satria F., Muslihudin M., Application Model of K-Means Clustering Insights into Promotion Strategy of Vocational High School, International Journal of Engineering and Technology (UAE); Susilowati T., Dacholfany M.I., Aminin S., Ikhwan A., Nasir B.M., Huda M., Prasetyo A., Maseleno A., Satria F., Hartati S.W., Getting Parents Involved in Child's School: Using Attendance Application System Based on SMS Gateway, Interna-tional Journal of Engineering and Technology (UAE); Aminudin N., Huda M., Ihwani S.S., Noor S.S.M., Basiron B., Jasmi K.A., Safar J., Mohamed A.K., Embong W.H.W., Mohamad A.M., Maseleno A., Masrur M., Trisnawati Rohmadi D., The Family Hope Program using AHP Method, International Journal of Engineering and Technology (UAE); Aminudin N., Fauzi Huda M., Hehsan A., Ripin M.N., Haron Z., Junaidi J., Irviani R., Muslihudin M., Hidayat S., Maseleno A., Gumanti M., Fauzi A., Application Program Learning Based on Android for Students' Experiences, International Journal of Engi-neering and Technology (UAE); Abadi S., Teh K.S.M., Huda M., Hehsan A., Ripin M.N., Haron Z., Muhamad N.H.N., Rianto R., Maseleno A., Renaldo R., Syarifudin A., Design of student score application for assessing the most outstanding student at vocational high school, International Journal of Engineering and Technology (UAE); Aminudin N., Huda M., Kilani A., Embong W.H.W., Mohamed A.M., Basiron B., Ihwani S.S., Noor S.S.M., Jasmi K.A., Safar J., Ivanova N.L., Maseleno A., Triono A.N., Higher Education Selection using Simple Additive Weighting, Internation-al Journal of Engineering and Technology (UAE); Anggraeni E.Y., Huda M., Maseleno A., Safar J., Jasmi K.A., Mohamed A.K., Hehsan A., Basiron B., Ihwani S.S., Embong W.H.W., Mohamad A.M., Noor S.S.M., Fauzi A., Wijaya D.A., Masrur M., Poverty Level Grouping using SAW Method, Interna-tional Journal of Engineering and Technology (UAE); Abadi S., Huda M., Jasmi K.A., Noor S.S.M., Safar J., Mohamed A.K., Embong W.H.W., Mohamad A.M., Hehsan A., Basiron B., Ihwani S.S., Maseleno A., Muslihudin M., Satria F., Irawan D., Hartati S., Determination of the Best Quail Eggs using Simple Additive Weighting, International Journal of Engineering and Technology (UAE); Abadi S., Huda M., Basiron B., Ihwani S.S., Jasmi K.A., Hehsan A., Safar J., Mohamed A.K., Embong W.H.W., Mohamad A.M., Noor S.S.M., Novita D., Maseleno A., Irviani R., Idris M., Muslihudin M., Implementation of Fuzzy Analytical Hierarchy Process on Notebook Selection, International Journal of Engineer-ing and Technology (UAE)","A. Maseleno; Department of Information Systems, STMIK Pringsewu, Lampung, Indonesia; email: andimaseleno@gmail.com",null,"Science Publishing Corporation Inc",{"$nulls":5},"2227524X",null,null,null,"English","Int. J. Eng. Technol.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85067270798"]
["Xu X.; Li Y.; Tang R.","Xu, Xiang (57205062106); Li, Yue (57205731968); Tang, Ruiyun (57205727642)","57205062106; 57205731968; 57205727642","Simulation Optimization of Discrete Logistics Processes: A Case Study on Logistics of an E-Commerce Enterprise in Shanghai",2019.0,"Discrete Dynamics in Nature and Society",2019.0,null,2493638.0,null,null,null,2.0,"10.1155/2019/2493638","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85061315333&doi=10.1155%2f2019%2f2493638&partnerID=40&md5=04abd9b7e1b5dc758d1e43e3a58ff16a","School of Management, Shanghai University, Shang Da Road 99, Shanghai, 200444, China","Xu X., School of Management, Shanghai University, Shang Da Road 99, Shanghai, 200444, China; Li Y., School of Management, Shanghai University, Shang Da Road 99, Shanghai, 200444, China; Tang R., School of Management, Shanghai University, Shang Da Road 99, Shanghai, 200444, China","With the rapid development of online shopping in recent years, logistics distribution has received much attention from enterprises and online consumers. Logistics distribution involves many factors and complex processes; conventional qualitative methods are unable to provide an effective analysis. Thus, this paper sets a framework to solve the above problem. A case study of an E-commerce enterprise in Shanghai on logistics distribution is proposed to discretize the whole process and minimize the total costs. Then the AnyLogic software is used to simulate and optimize the system from three aspects, including routes selection, warehouses quantity, and warehouses layout. Finally, this paper analyzes the simulation results, which would provide some valuable references for practical logistics. © 2019 Xiang Xu et al.",{"$nulls":8},"Zhen L., Tactical berth allocation under uncertainty, European Journal of Operational Research, 247, 3, pp. 928-944, (2015); Zhen L., Chew E.P., Lee L.H., An integrated model for berth template and yard template planning in transshipment hubs, Transportation Science, 45, 4, pp. 483-504, (2011); Casas P.F.I., Casanovas J., JGPSS, an open source GPSS framework to teach simulation, Proceedings of the 2009 Winter Simulation Conference, WSC 2009, 1-4, pp. 256-267, (2009); Pegden C.D., Alan A., Pritsker B., SLAM: Simulation language for alternativemodeling, Simulation, 33, 5, pp. 145-157, (1979); Ramani K.V., An interactive simulation model for the logistics planning of container operations in seaports, Simulation, 66, 5, pp. 291-300, (1996); Manuj I., Mentzer J.T., Bowers M.R., Improving the rigor of discrete-event simulation in logistics and supply chain research, International Journal of Physical Distribution & Logistics Management, 39, 3, pp. 172-201, (2009); Meng Q.-C., Zhang T., Li M., Rong X.-X., Optimal order strategy in uncertain demands with free shipping option, Discrete Dynamics in Nature and Society, (2014); Geng L., Xiao R.B., Xu X., Research on MAS-based supply chain resilience and its self-organized criticality, Discrete Dynamics in Nature and Society, 2014, (2014); Cui Y., Shi J., Wang Z., Discrete event logistics systems (DELS) simulation modeling incorporating two-step remaining useful life (RUL) estimation, Computers in Industry, 72, pp. 68-81, (2015); Li P.Q., He J., Zheng D.Y., Huang Y.S., Fan C.H., Vehicle routing problem with soft time windows based on improved genetic algorithm for fruits and vegetables distribution, Discrete Dynamics in Nature and Society, 2015, (2015); Lin C.Y., Gong B.W., Transit-based emergency evacuation with transit signal priority in sudden-onset disaster, Discrete Dynamics in Nature and Society, 2016, (2016); Beinke T., Ait Alla A., Freitag M., Resource sharing in the logistics of the offshore wind farm installation process based on a simulation study, International Journal of E-Navigation and Maritime Economy, 7, pp. 42-54, (2017); Li S.B., Wang G.M., Wang T., Ren H.L., Research on the method of traffic organization and optimization based on dynamic traffic flow model, Discrete Dynamics in Nature and Society, 2017, (2017); Wei Y., Chen F., Wang H., Inventory and production dynamics in a discrete-time vendor-managed inventory supply chain system, Discrete Dynamics in Nature and Society, 2018, (2018); Crainic T.G., Perboli G., Rosano M., Simulation of intermodal freight transportation systems: A taxonomy, European Journal of Operational Research, 270, 2, pp. 401-418, (2018); Noorizadegan M., Chen B., Vehicle routing with probabilistic capacity constraints, European Journal of Operational Research, 270, 2, pp. 544-555, (2018); Hu W.B., Wang H., Qiu Z.Y., Yan L.P., Nie C., Du B., An urban traffic simulation model for traffic congestion predicting and avoiding, Neural Computing Applications, 30, 6, pp. 1769-1781, (2018); Zhen L., Modeling of yard congestion and optimization of yard template in container ports, Transportation Research Part B: Methodological, 90, pp. 83-104, (2016)","R. Tang; School of Management, Shanghai University, Shanghai, Shang Da Road 99, 200444, China; email: try19970814@163.com",null,"Hindawi Limited",{"$nulls":5},1.0260226E7,null,null,null,"English","Discrete Dyn. Nat. Soc.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85061315333"]
["Park J.; Kim R.B.","Park, Joonyong (57195267470); Kim, Renee B. (35098816900)","57195267470; 35098816900","A new approach to segmenting multichannel shoppers in Korea and the U.S.",2018.0,"Journal of Retailing and Consumer Services",45.0,null,null,163.0,178.0,15.0,25.0,"10.1016/j.jretconser.2018.09.007","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85053836472&doi=10.1016%2fj.jretconser.2018.09.007&partnerID=40&md5=33425fd99840d42c2be10e97f70b1ae2","School of Business, Hanyang University, Seoul, South Korea; 811 School of Business, 222 Wangsimni-ro, Seongdong-gu, Seoul, South Korea","Park J., School of Business, Hanyang University, Seoul, South Korea, 811 School of Business, 222 Wangsimni-ro, Seongdong-gu, Seoul, South Korea; Kim R.B., School of Business, Hanyang University, Seoul, South Korea","Advancements in digital technology and devices enlarge dimensions of e-commerce, reforming the ways that consumers shop and purchase products and services. In particular, the mixed use of online, mobile, and offline channels and devices for shopping provides B2C firms with unprecedented challenges and opportunities to develop effective segmentation approaches that capture multitude of newly emerging consumers’ shopping patterns. This paper aims to classify consumers along with their shopping patterns and channel preferences by using rank order survey data from Korean and American consumers on their path-to-purchase behaviors. Cluster analysis and Association Rule Mining (ARM) are applied for segmentation and its characterization. Relative importance of path-to-purchase factors such as information search location, payment method, delivery option, and payment location are assessed to determine the differences in Korean and American consumers regarding their shopping patterns and preferences. Network visualization of rules shows the differences in shopping preference and patterns of Korean and US consumers both at micro and macro levels. © 2018 Elsevier Ltd","Association rule mining; Clustering of shopper; Data visualization; Rank ordered data","Korea; United States; cluster analysis; electronic commerce; shopping activity; visualization",{"$nulls":4},"Ministry of Education, MOE; National Research Foundation of Korea Research, (NRF-2016S1A3A2924243)","This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea Research (NRF-2016S1A3A2924243). ","Agrawal R., Srikant R., 1215, pp. 487-499, (1994); Agrawal R., Imielinski T., Swami A., Mining association rules between sets of items in large databases, In Acm sigmod record, 22, pp. 207-216, (1993); Ahn T., Ryu S., Han I., The impact of the online and offline features on the user acceptance of Internet shopping malls, Electron. Commer. Res. 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Sci., 33, 6, pp. 871-882, (2014); Shi S.W., Wedel M., Pieters F.G.M., Information acquisition during online decision making: a model-based exploration using eye-tracking data, Manag. Sci., 59, 5, pp. 1009-1026, (2013); Taihua W., Fan G., April, pp. 478-482, (2010); Verhoef P.C., Kannan P.K., Inman J.J., From multi-channel retailing to omni-channel retailing: introduction to the special issue on multi-channel retailing, J. Retail., 91, 2, pp. 174-181, (2015); Wedel M., Kannan P.K., Marketing analytics for data-rich environments, J. Mark., 80, pp. 97-121, (2016); Weng J., Zhu J.Z., Yan X., Liu Z., Investigation of work zone crash casualty patterns using association rules, Accid. Anal. Prev., 92, pp. 43-52, (2016); Wilding R., The 3Ts of highly effective supply chains, Supply Chain Practice, 5, 3, pp. 30-39, (2003); Wollenburg J., Holzapfel A., Hubner A., Kuhn H., (2016); Xu L., Duan J.A., Whinston A., Path to purchase: a mutually exciting point process model for online advertising and conversion, Manag. Sci., 60, 6, pp. 1392-1412, (2014)","R.B. Kim; Hanyang University, Seoul, 605, School of Business, 222 Wangsimni-ro, 133-791, South Korea; email: kimrby@hanyang.ac.kr",null,"Elsevier Ltd",{"$nulls":5},9696989.0,null,null,null,"English","J. Retail. Consum. Serv.","Article","Final",null,"Scopus","2-s2.0-85053836472"]
["Park J.; Kim R.B.","Park, Joonyong (57195267470); Kim, Renee Boyoung (35098816900)","57195267470; 35098816900","The effects of integrated information & service, institutional mechanism and need for cognition (NFC) on consumer omnichannel adoption behavior",2019.0,"Asia Pacific Journal of Marketing and Logistics",33.0,6.0,null,1386.0,1414.0,28.0,29.0,"10.1108/APJML-06-2018-0209","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85065747300&doi=10.1108%2fAPJML-06-2018-0209&partnerID=40&md5=148af64b105b24ef7018b8143b942100","School of Business, Hanyang University, Seoul, South Korea","Park J., School of Business, Hanyang University, Seoul, South Korea; Kim R.B., School of Business, Hanyang University, Seoul, South Korea","Purpose: The purpose of this paper is to examine the antecedents of consumers’ omnichannel (OC) adoption intention and explore how consumers’ personality trait affects their OC adoption behavior. Design/methodology/approach: A total of 227 Korean consumers were invited to participate in a survey study, and partial least squares–structural equation modeling was performed to analyze the measurement and structural models. Findings: The results show that three consumer groups by “Need for Cognition (NFC)” show different response to four identified OC attribute/benefits. Finally, the authors hypothesize and find that shed light on the possible ways to differentiate OC marketing for different target consumers and provide implications for practice and further research. Research limitations/implications: This study provides empirical evidence that OC is an expanded retail format of e-commerce, which is predominantly affected by how information on the cross-channel marketing mix/retail strategies is delivered to consumers. From communication perspective, findings suggest that retail communication strategy need more careful attention in dealing with individual difference of consumers. In addition, the significant role of NFC on consumers’ OC adoption process validates the importance of customization and differentiation in retailers’ message to different consumer groups. In order to do so, comprehensive analysis on consumer database may be necessary to develop personalized OC service. In-depth analysis of consumer profile may enable more specific methods for marketing and managing consumers in the OC context. Although the study provides additional empirical findings for consumers’ perception on selected characteristics of OC (i.e. delivery approach of information and service in OC and institutional mechanism of OC), there may be additional extrinsic motivation factors which affect consumers’ OC adoption behavior. Extrinsic factors such as web design, convenience, assortment, moving saving which trigger positive perception of OC, may be important determinants to consider. Furthermore, situational factor such as social media (Huseyinoglu et al., 2018) and behavioral factors such as platform use habit (Chen, 2018) may also be significant in assessing consumers’ OC adoption behavior. Finally, this study has been conducted on a particular culture setting, and the generalizability of study findings, particularly about the role of NFC may need to be improved by cross-culture evaluation. Practical implications: NFC-high and medium consumers are likely to use the four OC service options in future, while a larger proportion of the NFC-low consumers shows negative response to the OC service usage. This evidently shows that innovative features of OC service are not homogenously adopted by consumers, and subject to their experience and intrinsic difference, adoption rate was found to vary. This suggests that companies need to pay careful attention in implementing innovative OC service, and may approach communication of information strategically for different consumer groups. For high-NFC consumers with previous BOPIS experience, retailers may effectively engage them by enhancing and expanding the BOPIS service features, yet for low-NFC consumers, raising awareness and initiating interest among unexperienced consumers may be more imminent issue. Indirect communication using peripheral cues may be necessary to draw less motivated consumer group. Social implications: The OC retailers may need to set the scope and range of information into in-depth information and simplified/unified information, and address the different type of information to different consumer groups in order to facilitate consumers’ OC adoption. For consumers with medium and high NFC, it may be necessary to provide in-depth, detailed information relevant to product quality and promotional items consistently both in on/offline channels to gain their trust. Consumers with low NFC are found to prefer unified and simplified messages on information for price, delivery, inventory in on/offline channels. Originality/value: This study addresses the perceived value of unique and fundamental features and specificity of OC service by consumers with different personality trait. The authors develop consumers’ OC adoption model based on the theory of reasoned action, which depicts relationship between four extrinsic motivation factors and consumers’ intention for the OC usage, which is further differentiated by an intrinsic factor. We segment consumers based on individual difference of “NFC” and investigate how different consumer groups value different aspect of the selected OC attributes and benefits. Findings validate the importance of customization and differentiation in retailers’ message to different consumer groups and in facilitating consumers’ OC adoption. © 2019, Emerald Publishing Limited.","Consumer behaviour; Information consistency; Integrated information and service; Need for cognition; Omnichannel; Omnichannel institutional mechanisms; Retail management; Service integration",{"$nulls":5},"Ministry of Education, MOE; National Research Foundation of Korea, NRF, (NRF-2016S1A3A2924243)","This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2016S1A3A2924243). This paper forms part of a special section “E-tailing: the current landscape and future developments”, guest edited by Park Thaichon, James R. Brown and Scott Weaven.",{"$cut":{"chars":22700,"head":"Ailawadi K.L., Farris P.W., Managing multi- and omni-channel distribution: metrics and research directions, Journal of Retailing, 93, 1, pp. 120-135, (2017); Ajzen I., The theory of planned behavior, Organizational Behavior and Decision Processes, 50, 2, pp. 179-211, (1991); Ajzen I., Fishbein M., Understanding Attitudes and Predicting Social Behaviour, (1980); Aldas-Manzano J., Lassala-Navarre C., Ruiz-Mafe C., Sanz-Blas S., The role of consumer innovativeness and perceived risk in online banking usage, International Journal of Bank Marketing, 27, 1, pp. 53-75, (2009); Ashraf A.R., Thongpapanl N.T., Auh S., The application of the technology acceptance model under different cultural contexts: the case of online shopping adoption, Journal of International Marketing, 22, 3, pp. 68-93, (2014); Avery J., Steenburgh T.J., Deighton J., Carvella M., Adding bricks to clicks: predicting the patterns of cross-channel elasticities over time, Journal of Marketing, 76, 3, pp. 96-111, (2012); Awasthy D., Banerjee A., Banerjee B., Understanding the role of prior product knowledge to information search: an application of process theory to the Indian market, Asia Pacific Journal of Marketing and Logistics, 24, 2, pp. 257-287, (2012); Beck N., Rygl D., Categorization of multiple channel retailing in multi-, cross-, and omni-channel retailing for retailers and retailing, Journal of Retailing and Consumer Services, 27, pp. 170-178, (2015); Bell B.D.R., Gallino S., Moreno A., How to win in an omnichannel world how to win in an omnichannel world, MIT Sloan Management Review, 56, 1, pp. 45-54, (2014); Bigne-Alcaniz E., Ruiz-Mafe C., Aldas-Manzano J., Sanz-Blas S., Influence of online shopping information dependency and innovativeness on internet shopping adoption, Online Information Review, 32, 5, pp. 648-667, (2008); Bosnjak M., Galesic M., Tuten T., Personality determinants of online shopping: explaining online purchase intentions using a hierarchical approach, Journal of Business Research, 60, pp. 597-605, (2007); Breugelmans E., Campo K., Cross-channel effects of price promotions: an empirical analysis of the multi-channel grocery retail sector, Journal of Retailing, 92, 3, pp. 333-351, (2016); Brynjolfsson E., Hu Y.J., Rahman M.S., Competing in the age of omnichannel retailing, MIT Sloan Management Review, 54, 4, pp. 23-29, (2013); Cacioppo J.T., Petty R.E., The need for cognition, Journal of Personality and Social Psychology, 42, 1, pp. 116-131, (1982); Cao L., Business model transformation in moving to a cross-channel retail strategy: a case study, International Journal of Electronic Commerce, 18, 4, pp. 69-96, (2014); Celik H., Customer online shopping anxiety within the Unified Theory of Acceptance and Use Technology (UTAUT) framework, Asia Pacific Journal of Marketing and Logistics, 28, 2, pp. 278-307, (2016); Cervellon M.C., Sylvie J., Ngobo P.V., Shopping orientations as antecedents to channel choice in the French grocery multichannel landscape, Journal of Retailing and Consumer Services, 27, pp. 31-51, (2015); Chaiken S., Heuristic versus systematic information processing and the use of source versus message cues in persuasion, Journal of Personality and Social Psychology, 39, 5, pp. 752-766, (1980); Chatterjee P., Causes and consequences of ‘order online pick up in-store’ shopping behavior, The International Review of Retail, Distribution and Consumer Research, 20, 4, pp. 431-448, (2010); Chen H.J., What drives consumers’ mobile shopping? 4Ps or shopping preferences?, Asia Pacific Journal of Marketing and Logistics, 30, 4, pp. 797-815, (2018); Chopdar P.K., Korfiatis N., Sivakumar V.J., Lytras M.D., Mobile shopping apps adoption and perceived risks: a cross-country perspective utilizing the Unified theory of acceptance and use of technology, Computers in Human Behavior, 86, pp. 109-128, (2018); Christensen C.M., Raynor M.E., The Innovator’s Solution, (2003); Cohen A.R., Stotland E., Wolfe D.M., An experimental investigation of need for cognition, The Journal of Abnormal and Social Psychology, 51, 2, pp. 291-294, (1955); Crittende"}},"R.B. Kim; School of Business, Hanyang University, Seoul, South Korea; email: kimrby@gmail.com",null,"Emerald Group Holdings Ltd.",{"$nulls":5},1.3555855E7,null,null,null,"English","Asia Pac. J. Mark. Logist.","Article","Final",null,"Scopus","2-s2.0-85065747300"]
["Yanyan W.","Yanyan, Wu (57225128187)",5.7225128187E10,"Empirical analysis of factors influencing consumers' satisfaction in online shopping agricultural products in China",2018.0,"Journal of Electronic Commerce in Organizations",16.0,3.0,null,64.0,77.0,13.0,13.0,"10.4018/JECO.2018070106","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85048441041&doi=10.4018%2fJECO.2018070106&partnerID=40&md5=8644e7196955411dcf82cdaba8be7d5d","Harbin University of Commerce, Harbin, China","Yanyan W., Harbin University of Commerce, Harbin, China","With the development of e-commerce, online shopping for agricultural products has been more popular. And how to improve consumer's satisfaction has become more important. Literature review shows that few researches on online purchasing agricultural food focus on the consumers' satisfaction. This article designs a questionnaire, including 20 factors based on agricultural product characteristics, website quality and service quality to evaluate consumers' satisfaction. The evaluation shows that service quality, agricultural products' safety, brand and website quality significantly impact consumer satisfaction. Moreover, service quality is the most important factor. Finally, some recommendations are made in this article to develop cold chain logistics system, strictly control the agricultural products quality, build an agricultural products brand, improve the quality of agricultural product websites and strengthen policy control and guidance. © Copyright 2018, IGI Global.","Agricultural Products; Consumers' Satisfaction; Customer Experience; E-Commerce; Online Shopping",{"$nulls":7},"Anderson R.E., Srinivasan S.S., E-satisfaction and e-loyalty: A contingency framework, Psychology and Marketing, 20, 2, pp. 123-138, (2003); Brown I., Jayakody R., B2C e-commerce success: A test and validation of a revised conceptual model, Electronic Journal Information Systems Evaluation, 11, 3, pp. 167-184, (2008); Cao W., Analysis of Factors Influencing Customers' Online Shopping Intention of Agricultural Products Based on Sellers' Perspective, Zhongguo Nongxue Tongbao, 29, 17, pp. 239-244, (2013); Chen J.V., Yen D.C., Pornpriphet W., Widjaja A.E., E-commerce web site loyalty: A cross cultural comparison, Information Systems Frontiers, 17, 6, pp. 1283-1299, (2015); The 38th China Internet Development Report, (2016); Customer Service Worries Online Shoppers, (1999); De Ruyter J.C., Bloemer J.M.A., Peeters P., Merging Service Quality and Service Satisfaction: An Empirical Test of an Integrative Framework, Journal of Economic Psychology, 18, 4, pp. 387-406, (1997); Ernst, Young, Canadians Getting Comfortable with Online Shopping, (2000); Escobar-Rodriguez T., Bonson-Fernandez R., Analyzing online purchase intention in Spain: Fashion e-commerce, Information System E-Business Management, (2016); Gefen D., Customer loyalty in e-commerce, Journal of the Association for Information Systems, 3, 1, pp. 27-51, (2002); Hu T., Analysis on the development of Chinese agricultural products electronic commerce, Agricultural Economic Problems, 5, pp. 23-27, (2005); One-Third of Internet Users Have Made Online Purchasers, (1999); Zou J., Consumers' willingness to purchase fresh agricultural products and its influencing factors, Consumption Economy, 4, pp. 69-72, (2011); Kuan H.H., Bock G.-W., Vathanophas V., Comparing the effects of usability on customer: Conversion and retention at e-commerce websites, Proceedings of the 38th Hawaii International Conference on System Sciences, (2005); Kyriazopoulos P., Spyridakos A., Grigoroudis E., Siskos Y., Yannacopoulos D., The quality of e-services: Measuring Satisfaction of Internet Customers, Operations Research, 17, 2, pp. 233-254, (2007); Lai J.Y., Ulhas K.R., Lin J.-D., Assessing and managing ecommerce service convenience, Information Systems Frontier, (2012); Lee P.-M., Behavioral Model of Online Purchasers in E-Commerce Environment, Electronic Commerce Research, 2, 1-2, pp. 75-85, (2002); Li H., Jiang J., Wu M., The Effects of Trust Assurances on Consumers' Initial Online Trust: A Twostage Decision-making Process Perspective, International Journal of Information Management, 34, 3, pp. 395-405, (2014); Lin J., Wan J., Lu Y., Analysis of Factor Affecting Consumer Trust in E-commerce of Fresh Agricultural Products: Taking the Example of Fruits, Journal of Business Economics, 283, 5, pp. 5-15, (2015); Liu H., Zhu Y., Consumers' Online Shopping of Fresh Vegetables Influence Factors: Based on Shanghai Consumers' Survey, Zhongguo Nongxue Tongbao, 30, 21, pp. 289-293, (2014); Molla A., Licker P.S., Commerce systems success: An attempt to extend and respecify the DeLone and McLean model of IS success, Journal of Electronic Commerce Research, 2, 4, pp. 131-141, (2001); 10 Elements of A Successful Web Store, (1998); Petter S., DeLone W., McLean E., Measuring information systems success: Models, dimensions, measures, and interrelationships, European Journal of Information Systems, 17, 3, pp. 236-263, (2008); Petter S., DeLone W., McLean E.R., Information systems success: The quest for the independent variables, Journal of Management Information Systems, 29, 4, pp. 7-61, (2013); Riel A.C.R.V., Lemmink J., Streukens S., Liljander V., Boost customer loyalty with online support: The case of mobile telecoms providers, International Journal of Internet Marketing and Advertising, 1, 1, pp. 4-23, (2004); Wu Y., Research on agricultural products e-commerce based on category management, Business and Economic Review, 21, pp. 71-73, (2015); Zhang W., Advanced SPSS Statistical Analysis, (2004); Zhao P., Luo Y., Case analysis and Enlightenment of the development of electronic commerce of agricultural products: A case study of \"dish steward\" and FreshDirect, Business Economics and Management, 7, pp. 19-23, (2011)",null,null,"IGI Global",{"$nulls":5},1.5392937E7,null,null,null,"English","J. Electr. Commer. Organ.","Article","Final",null,"Scopus","2-s2.0-85048441041"]
["Nishimura N.; Sukegawa N.; Takano Y.; Iwanaga J.","Nishimura, Naoki (57150127100); Sukegawa, Noriyoshi (55246346000); Takano, Yuichi (15073427700); Iwanaga, Jiro (57151182200)","57150127100; 55246346000; 15073427700; 57151182200","A latent-class model for estimating product-choice probabilities from clickstream data",2018.0,"Information Sciences",429.0,null,null,406.0,420.0,14.0,21.0,"10.1016/j.ins.2017.11.014","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85035029931&doi=10.1016%2fj.ins.2017.11.014&partnerID=40&md5=91b1bf2375464802eac5d8f3e050bd3c","Data Science Group, Internet Business Development Division, Recruit Lifestyle Co., Ltd., GranTokyo SOUTHTOWER, 1-9-2 Marunouchi, Chiyoda-ku, Tokyo, 100-6640, Japan; Department of Information and System Engineering, Faculty of Science and Engineering, Chuo University, 1-13-27 Kasuga, Bunkyo-ku, Tokyo, 112-8551, Japan; School of Network and Information, Senshu University, 2-1-1 Higashimita, Tama-ku, Kawasaki-shi, 214-8580, Kanagawa, Japan; Sumitomo Fudosan Azabu Juban Building, 1-4-1 Mita, Minato-ku, Tokyo, 108-0073, Japan","Nishimura N., Data Science Group, Internet Business Development Division, Recruit Lifestyle Co., Ltd., GranTokyo SOUTHTOWER, 1-9-2 Marunouchi, Chiyoda-ku, Tokyo, 100-6640, Japan; Sukegawa N., Department of Information and System Engineering, Faculty of Science and Engineering, Chuo University, 1-13-27 Kasuga, Bunkyo-ku, Tokyo, 112-8551, Japan, Sumitomo Fudosan Azabu Juban Building, 1-4-1 Mita, Minato-ku, Tokyo, 108-0073, Japan; Takano Y., School of Network and Information, Senshu University, 2-1-1 Higashimita, Tama-ku, Kawasaki-shi, 214-8580, Kanagawa, Japan; Iwanaga J., Sumitomo Fudosan Azabu Juban Building, 1-4-1 Mita, Minato-ku, Tokyo, 108-0073, Japan","This paper analyzes customer product-choice behavior based on the recency and frequency of each customer's page views on e-commerce sites. Recently, we devised an optimization model for estimating product-choice probabilities that satisfy monotonicity, convexity, and concavity constraints with respect to recency and frequency. This shape-restricted model delivered high predictive performance even when there were few training samples. However, typical e-commerce sites deal in many different varieties of product, so the predictive performance of the model can be further improved by integrating such product heterogeneity. For this purpose, we develop a novel latent-class shape-restricted model for estimating product-choice probabilities for each latent class of products. We also give a tailored expectation-maximization algorithm for parameter estimation. Computational results demonstrate that higher predictive performance is achieved with our latent-class model than with the previous shape-restricted model or latent-class logistic regression. © 2017 Elsevier Inc.","Clickstream data; E-commerce; EM algorithm; Latent class; Optimization; Product choice","Commerce; Electronic commerce; Image segmentation; Maximum principle; Probability; Clickstream data; Computational results; EM algorithms; Expectation-maximization algorithms; Latent class; Predictive performance; Product choice; Recency and frequencies; Optimization",{"$nulls":4},"Japan Society for the Promotion of Science, JSPS, (26242027)",null,"Ait-Sahalia Y., Duarte J., Nonparametric option pricing under shape restrictions, J. 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Fusion, 37, pp. 132-156, (2017); Lazarsfeld P.F., Henry N.W., Latent Structure Analysis, (1968); Liu Z., Almhana J., Choulakian V., McGorman R., Online EM algorithm for mixture with application to internet traffic modeling, Comput. Stat. Data Anal., 50, 4, pp. 1052-1071, (2006); Manning C.D., Raghavan P., Schutze H., Introduction to Information Retrieval, (2008); Meyer M.C., Semi-parametric additive constrained regression, J. Nonparametr. Stat., 25, 3, pp. 715-730, (2013); McLachlan G., Krishnan T., The EM Algorithm and Extensions, 382, (2007); Moe W.W., Fader P.S., Dynamic conversion behavior at e-commerce sites, Manage. Sci., 50, 3, pp. 326-335, (2004); Montgomery A.L., Li S., Srinivasan K., Liechty J.C., Modeling online browsing and path analysis using clickstream data, Marketing Sci., 23, 4, pp. 579-595, (2004); Olbrich R., Holsing C., Modeling consumer purchasing behavior in social shopping communities with clickstream data, Int. J. Electron. Comm., 16, 2, pp. 15-40, (2011); Pardalos P.M., Xue G., Algorithms for a class of isotonic regression problems, Algorithmica, 23, 3, pp. 211-222, (1999); Qiu J., A predictive model for customer purchase behavior in e-commerce context, Proceedings of the 2014 Pacific Asia Conference on Information Systems 369, (2014); Ramirez-Gallego S., Krawczyk B., Garcia S., Wozniak M., Herrera F., A survey on data preprocessing for data stream mining: current status and future directions, Neurocomputing, 239, pp. 39-57, (2017); Reinartz W.J., Kumar V., On the profitability of long-life customers in a noncontractual setting: an empirical investigation and implications for marketing, J. Marketing, 64, 4, pp. 17-35, (2000); Reinartz W.J., Kumar V., The impact of customer relationship characteristics on profitable lifetime duration, J. Marketing, 67, 1, pp. 77-99, (2003); Robertson T., Wright F., Dykstra R., Order Restricted Statistical Inference, (1988); Sato S., Asahi Y., The model of purchasing and visiting behavior of customers in an e-commerce site for consumers, Int. Proc. Econ. Develop. Res., 52, pp. 72-76, (2012); Sismeiro C., Bucklin R.E., Modeling purchase behavior at an e-commerce web site: a task-completion approach, J. Marketing Res., 41, 3, pp. 306-323, (2004); Turban E., King D., Lee J., Liang T.-P., Turban D.C., Electronic Commerce: A Managerial and Social Networks Perspective, 8th, (2015); Terrell D., Incorporating monotonicity and concavity conditions in flexible functional forms, J. Appl. Econ., 11, pp. 179-194, (1996); Van den Poel D., Buckinx W., Predicting online-purchasing behaviour, Eur. J. Oper. Res., 166, 2, pp. 557-575, (2005); Wang J., Ghosh S.K., Shape restricted nonparametric regression with bernstein polynomials, Comput. Stat. Data Anal., 56, 9, pp. 2729-2741, (2012); Wedel M., DeSarbo W.S., A review of recent developments in latent class regression models, Adv. Methods Marketing Res., pp. 352-388, (1994); Wedel M., DeSarbo W.S., Mixture regression models, International Series in Quantitative Marketing, 8, 2000, pp. 101-124, (2000); Zhang Y., Pennacchiotti M., Predicting purchase behaviors from social media, Proceedings of the 22nd International Conference on World Wide Web, pp. 1521-1532, (2013)","N. Sukegawa; Department of Information and System Engineering, Faculty of Science and Engineering, Chuo University, Tokyo, 1-13-27 Kasuga, Bunkyo-ku, 112-8551, Japan; email: sukegawa@ise.chuo-u.ac.jp",null,"Elsevier Inc.",{"$nulls":5},200255.0,null,"ISIJB",null,"English","Inf Sci","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85035029931"]
["Rahman N.K.N.A.; Abidin S.Z.; Zandi G.R.; Amin M.; Hartani N.H.","Rahman, Nik Khadijah Nik Abdul (58282832800); Abidin, Salzainna Zainul (57205267861); Zandi, Gholam Reza (55091974300); Amin, Mohammad (57206934238); Hartani, Nira Hariyatie (57205100212)","58282832800; 57205267861; 55091974300; 57206934238; 57205100212","E-commerce logistic and supply chain management: Evidence from Indonesian perspectives",2018.0,"International Journal of Supply Chain Management",7.0,6.0,null,25.0,32.0,7.0,3.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85059311471&partnerID=40&md5=63f4564e9fe58e0fa7b8dbf74b22d44d","Business School, Universiti Kuala Lumpur (UniKL), Malaysia; School of Government (SoG), College of Law, Government and International Studies (COLGIS), Universiti Utara Malaysia (UUM), Sintok, Kedah, 06010, Malaysia","Rahman N.K.N.A., Business School, Universiti Kuala Lumpur (UniKL), Malaysia; Abidin S.Z., Business School, Universiti Kuala Lumpur (UniKL), Malaysia; Zandi G.R., Business School, Universiti Kuala Lumpur (UniKL), Malaysia; Amin M., Business School, Universiti Kuala Lumpur (UniKL), Malaysia; Hartani N.H., School of Government (SoG), College of Law, Government and International Studies (COLGIS), Universiti Utara Malaysia (UUM), Sintok, Kedah, 06010, Malaysia","The web is essentially affecting how firms cooperate with one another and their clienteles. Past interruptions for supply chain incorporation, for example, high exchange prices between allies, weak info accessibility, with encounters of overseeing multifaceted borders between utilitarian affiliations have been on the whole dissolving on the web. In this study, it is examined how the web has been altering SCM. 100 Questionnaire has been used to acquire the response from the employees of Indonesia companies having E-Commerce business. Smart PLS software has been used to get data examination. ponder presented a study of developing on the consequence of e-business on SCM with descriptive frameworks, e-procurement, e-collaboration and e-commerce. © ExcelingTech Pub, UK.","E-business; E-collaboration; E-commerce; E-procurement",{"$nulls":7},"Devaraj S., Krajewski L., Wei J.C., Impact of eBusiness technologies on operational performance: the role of production information integration in the supply chain, Journal of Operations Management, 25, 6, pp. 1199-1216; Manthou V., Vlachopoulou M., Folinas D., Virtual e-Chain (VeC) model for supply chain collaboration, International Journal of Production Economics, 87, 3, pp. 241-250, (2004); Ordanini A., Rubera G., Strategic capabilities and internet resources in procurement: A resource-based view of B-to-B buying process, International Journal of Operations & Production Management, 28, 1, pp. 27-52, (2008); Agatz N.A., Fleischmann M., Van Nunen J.A., E-fulfillment and multi-channel distribution-A review, European journal of operational research, 187, 2, pp. 339-356, (2008); Bai J., The Localized Marketing Strategy Choice for Global Retailer-A case study of Ikea, Future and Development, 8, pp. 83-87, (2011); Bask A., Lipponen M., Tinnila M., Ecommerce logistics: a literature research review and topics for future research, International Journal of E-Services and Mobile Applications (IJESMA), 4, 3, pp. 1-22, (2012); Khan F., Nakagawa K., Comparative study of spectrum sensing techniques in cognitive radio networks, In Computer and Information Technology (WCCIT), 2013 World Congress on, pp. 1-8, (2013); Cronin M.J., Amazon fast tracks transformation, In Top Down Innovation, pp. 49-60, (2014); Graham D., Manikas I., Folinas D., E-logistics and e-supply chain management: Applications for evolving business, IGI Global, (2013); Yu Y., Wang X., Zhong R.Y., Huang G.Q., E-commerce logistics in supply chain management: Practice perspective, Procedia Cirp, 52, pp. 179-185, (2016); Nzimande N., Padayachee P., Evaluation of the Current Procurement Planning Process in a District Municipality, International Journal of Public Policy and Administration Research, 4, 1, pp. 19-34, (2017); Yu Y., Wang X., Zhong R.Y., Huang G.Q., E-commerce logistics in supply chain management: Practice perspective, Procedia Cirp, 52, pp. 179-185, (2016); Yu Y., Wang X., Zhong R.Y., Huang G.Q., E-commerce logistics in supply chain management: Implementations and future perspective in furniture industry, Industrial Management & Data Systems, 117, 10, pp. 2263-2286, (2017); Kambi B., Kambi M., Local Content Agenda: The Role of Institution Theory on Policy and Practical Challenges in Local Procurement Practice by Mining Entities in Tanzania, Humanities and Social Sciences Letters, 5, 1, pp. 1-10, (2017); Liu J., Hou Y.R., Time based strategy in distribution logistics: gaining competitive advantages in IKEA, (2011); Bianchi C.C., Ostale E., Lessons learned from unsuccessful internationalization attempts: Examples of multinational retailers in Chile, Journal of Business Research, 59, 1, pp. 140-147, (2006); Chaabouni T., Kchaou H., Khemakhem M., Agent technology based resources management in Cloud Computing, In Computer and Information Technology (WCCIT), 2013 World Congress on, pp. 1-3, (2013); Mangiaracina R., Marchet G., Perotti S., Tumino A., A review of the environmental implications of B2C e-commerce: a logistics perspective, International Journal of Physical Distribution & Logistics Management, 45, 6, pp. 565-591, (2015); Masmoudi M., Benaissa M., Chabchoub H., Optimisation of e-commerce logistics distribution system: problem modelling and exact resolution, International Journal of Business Performance and Supply Chain Modelling, 6, 3-4, pp. 358-375, (2014); Dim N.U., Ezeabasili A.C.C., Strategic supply chain framework as an effective approach to procurement of public construction projects in Nigeria, International Journal of Management and Sustainability, 4, 7, pp. 163-172, (2015); Imran M., Hamid S., Aziz A., Hameed W., The contributing factors towards e-logistic customer satisfaction: a mediating role of information Technology, Uncertain Supply Chain Management, 7, 1, pp. 63-72, (2019); Asmara G., The Principles of Religious Tolerance and Harmony among the People of Sasak Tribe in Lombok Island, Indonesia, Journal of Legal, Ethical and Regulatory Issues, 21, 1, pp. 1-6, (2018); Azam M., Haseeb M., Binti Samsi A., Raji J.O., Stock market development and economic growth: Evidences from Asia-4 Countries, International Journal of Economics and Financial Issues, 3, 6, pp. 1200-1208, (2016); Azam M., Haseeb M., Samsudin S., The impact of foreign remittances on poverty alleviation: Global evidence, Economics & Sociology, 9, 1, (2016); Hamzah L.U., Bilateral Investment Treaties (Bits) In Indonesia: A Paradigm Shift, Issues And Challenges, Journal of Legal, Ethical and Regulatory Issues, 21, 1, (2018); Haseeb M., Emerging Issues in Islamic Banking & Finance: Challenges and Solutions, Academy of Accounting and Financial Studies Journal, 22, pp. 1-5, (2018); Haseeb M., Azam M., Energy consumption, economic growth and CO2 emission nexus in Pakistan, Asian Journal of Applied Sciences, 8, 1, pp. 27-36, (2015); Adusei C., Public Procurement in the Health Services: Application, Compliance and Challenges, Humanities and Social Sciences Letters, 6, 2, pp. 41-50, (2018); Hameed W.U., Azeem M., Ali M., Nadeem S., Amjad T., The Role of Distribution Channels and Educational level towards Insurance Awareness among the General Public, International Journal of Supply Chain Management, 6, 4, pp. 308-318, (2017); Ul-Hameed W., Mohammad H., Shahar H., Microfinance institute's non-financial services and women-empowerment: The role of vulnerability, Management Science Letters, 8, 10, pp. 1103-1116, (2018); Hameed W.U., Nadeem S., Azeem M., Aljumah A.I., Adeyemi R.A., Determinants of E-Logistic Customer Satisfaction: A Mediating Role of Information and Communication Technology (ICT), International Journal of Supply Chain Management, 7, 1, pp. 105-111, (2018); Hameed F.H., Ali M., Arif M., Enterprise Risk Management (ERM) System: Implementation Problem and Role of Audit Effectiveness in Malaysian Firms, Asian Journal of Multidisciplinary Studies, 5, (2017)","N.H. Hartani; School of Government (SoG), College of Law, Government and International Studies (COLGIS), Universiti Utara Malaysia (UUM), Sintok, Kedah, 06010, Malaysia; email: hariyatie@uum.edu.my",null,"ExcelingTech",{"$nulls":5},2.0513771E7,null,null,null,"English","Int. J. Supply Chain Manag.","Article","Final",null,"Scopus","2-s2.0-85059311471"]
["Bowering G.","Bowering, Geoff (57203588337)",5.7203588337E10,"Does e-commerce and the growing availability of trade data mean that the customs declaration may no longer be required?",2018.0,"World Customs Journal",12.0,1.0,null,3.0,16.0,13.0,1.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85052364480&partnerID=40&md5=2897c422b456a79fe04eb8c786fa52b2","Australian Department of Home Affairs, Australia","Bowering G., Australian Department of Home Affairs, Australia","This research examines whether the growth in the availability of trade and logistics data, and the ability of customs authorities to access it, means that the import declaration is no longer required. A literature review explored existing trade data, relevant technology and recent trade-data-related initiatives. Case studies of the role of the import declaration identified how it is used for customs border management and the data required. The analysis shows that an effective Authorised Economic Operator (AEO) program, combined with separately sourced data, may remove the need for an import declaration from compliant traders. © International Network of Customs Universities.",{"$nulls":8},"Altemoller F., Counter-terrorism and data transfers in international trade, World Customs Journal, 10, 1, pp. 27-34, (2016); 5368.0-International trade in goods and services, Australia, July 2017, (2017); Customs to customs data exchange proof of concept report, (2009); Documentary import declaration comprehensive guide, (2013); The Bolero Electronic Bill of Lading (eBL)-Overview; Brew J., Jenkins N.M., Customs 101: Importation process basics, (2010); Frequently asked questions, (2017); Choi J.Y., A survey of single window implementation, (2011); Chukwuma R.F.S.C., Can the functions of a paper bill of lading be replicated by electronic bill of lading?, Public Policy and Administration Research, 3, 8, pp. 101-108, (2013); den Butter F.A.G., Liu J., Tan Y.-H., Using IT to engender trust in government-to-business relationships: The Authorized Economic Operator (AEO) as an example, Government Information Quarterly, 29, 2, pp. 261-274, (2012); About digital certificates; Clearance of Cargo-Imports: Practice Statement PS2009/23, (2009); Department of Immigration and Border Protection: Annual report 2015-16, (2016); Global customs risk management: An examination of leading practices, (2006); Francis V., Supply chain visibility: Lost in translation?, Supply Chain Management: An International Journal, 13, 3, pp. 180-184, (2008); Grainger A., Customs and trade facilitation: from concepts to implementation, World Customs Journal, 2, 1, pp. 17-30, (2008); Good L., Gahan P., Butar I., Dehghan S., Leading technological innovation & productivity improvement across the supply chain: An evaluation of the ALC Intermodal Visibility Pilot of the GS1, (2015); Greis N.P., Nogueira M.L., Use of data mining for validation and verification of maritime cargo movement, (2011); Improving the consumer goods importing process, (2012); Hackius N., Petersen M., Blockchain in logistics and supply chain: Trick or treat? Paper presented at the Hamburg International Conference of Logistics, Hamburg, Germany, (2017); Henningsson S., Gal U., Bjorn-Andersen N., Tan Y.-H., The next generation information infrastructure for international trade, Journal of Theoretical and Applied Electronic Commerce Research, 6, 1, pp. 1-15, (2011); Hesketh D., Seamless electronic data and logistics pipelines shift focus from import declarations to start of commercial transaction, World Customs Journal, 3, 1, pp. 27-32, (2009); Hesketh D., Weaknesses in the supply chain: Who packed the box?, World Customs Journal, 4, 2, pp. 3-20, (2010); Hesketh D., Seamless integrated data pipelines, (2015); Hintsa J., Mannisto T., Urciuoli L., Ahokas J., Does better visibility help mitigate security risks in cross-border supply chains? Case FP7-CASSANDRA, Paper presented at e-Freight 2012. Conference, (2012); Hofman W., Supply chain visibility with linked open data for supply chain risk analysis, 1st workshop on IT innovations enabling seamless and secure supply chains, pp. 20-31, (2011); Hulstijn J., Hofman W., Zomer G., Tan Y.-H., Towards trusted trade-lanes, International Conference on Electronic Government and the Information Systems Perspective, pp. 299-311, (2016); Maersk and IBM unveil first industry-wide cross-border supply chain solution on blockchain, (2017); IBM and Maersk demo: Cross-border supply chain solution on blockchain, (2017); Risk management for cargo and passengers: A knowledge and capacity product (Technical Notes No, (2010); e-freight, (2017); Jones V.C., Rosenblum M.R., US customs and border protection: Trade facilitation, enforcement, and security, (2013); Klievink B., van Stijn E., Hesketh D., Aldewereld H., Overbeek S., Heijmann F., Tan Y.-H., Enhancing visibility in international supply chains: The data pipeline concept, International Journal of Electronic Government Research, 8, 4, pp. 14-33, (2012); Klievink A.J., Aldewereld H.M., Knol A., Tan Y.-H., Governing logistics information platforms: DINALOG extend single window (ESW), (2014); Kloeden P., ERP systems facilitating XBRL reporting and regulatory compliance, (2007); Lim Y.F., Digital signature, certification authorities and the law, Murdoch University Electronic Journal of Law, 9, 3, (2002); Madu C.N., Kuei C.H., ERP and supply chain management, (2005); What is a signature? The Journal of Information, Law and Technology (JILT), 3, (2000); Rukanova B., Henriksen H.Z., Henningsson S., Tan Y.-H., The anatomy of digital trade infrastructures, Presented at the International Conference on Business Informatics Research, pp. 184-198, (2017); Scholliers J., Permala A., Toivonen S., Salmela H., Improving the security of containers in port related supply chains, Transportation Research Procedia, 14, pp. 1374-1383, (2016); Shamsuzzoha A., Helo P.T., Real-time tracking and tracing system: Potentials for the logistics network, In Proceedings of the 2nd International Conference on Industrial Engineering and Operations Management, pp. 22-24, (2011); Stanton G., Detecting fraud: Utilizing new technology to advance the audit profession, (2012); Staples M., Chen S., Falamaki S., Ponomarev A., Rimba P., Tran A.B., Zhu J., Risks and opportunities for systems using blockchain and smart contracts, (2017); Tan Y.H., Bjorn-Andersen N., Klein S., Rukanova B., Accelerating global supply chains with IT-innovation: ITAIDE tools and methods, (2010); About CBP; Importing into the United States: A guide for commercial importers, (2006); Automated Commercial Environment (ACE) Automated Broker Interface (ABI) CBP and Trade Automated Interface Requirements: Introduction and getting started, (2010); CBP Form 3461-Instructions, (2016); Vaduva D., E-commerce, Legal and Administrative Studies, 178, 1, pp. 47-57, (2014); Van Oosterhout M.P., Veenstra A.W., Meijer M.A.G., Popal N., Van den Berg J., Visibility platforms for enhancing supply chain security: A case study in the Port of Rotterdam, In Proceeding of the International Symposium on Maritime Safety, Security and Environmental Protection, Athens, pp. 1-11, (2007); Van Stijn E., Hesketh D., Tan Y., Klievink B., Overbeek S., Heijmann F., Butterly T., The Data Pipeline, In Proceedings of the Global Trade Facilitation Conference, Geneva, pp. 1-26, (2011); Wang Y., Hulstijn J., Tan Y.-H., Data quality assurance in international supply chains: An application of the value cycle approach to customs reporting, International Journal of Advanced Logistics, 5, 2, pp. 76-85, (2016); Widdowson D., Holloway S., Maritime transport security regulation: Policies, probabilities and practicalities, World Customs Journal, 3, 2, pp. 17-42, (2009); Kyoto Convention: General Annex Guidelines: Chapter 6 Customs Control, (2000); International Convention on the Simplification and Harmonization of Customs Procedures (as amended), (2006); Recommendation of the Customs Co-operation Council on the Dematerialization of Supporting Documents, (2012); SAFE Framework of Standards to secure and facilitate global trade, (2015); Yasui T., Benefits of the Revised Kyoto Convention, (2010); Zomer G., Tan Y.-H., Hofman W., D9.1 CASSANDRA Final Report, (2014)",null,null,"International Network of Customs Universities",{"$nulls":5},1.8346707E7,null,null,null,"English","World Cust. J.","Article","Final",null,"Scopus","2-s2.0-85052364480"]
["Gabdullin L.V.; Bikulov R.A.; Khamitov I.M.; Stepanova Y.S.","Gabdullin, Lenar V. (57192301755); Bikulov, Rinat A. (56770136400); Khamitov, Ilnaz M. (57215917347); Stepanova, Yuliya S. (57215911831)","57192301755; 56770136400; 57215917347; 57215911831","E-integrator of LBP-provider of logistics barter",2018.0,"International Journal of Engineering and Technology(UAE)",7.0,"4.7 Special Issue  7",null,197.0,199.0,2.0,0.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85082366943&partnerID=40&md5=01b8d2a801bdf140046ec705e7d77127","Kazan Federal University, Russian Federation","Gabdullin L.V., Kazan Federal University, Russian Federation; Bikulov R.A., Kazan Federal University, Russian Federation; Khamitov I.M., Kazan Federal University, Russian Federation; Stepanova Y.S., Kazan Federal University, Russian Federation","Logistic barter is a normal commodity exchange among producers where one thing is exchanged to another without monetary pay on the basis of globally integrated trade procedure. The approach of barter logistics is not abandon money, however ignores it among producers. Logistics has touched and touches such heights, while the requirement for a \"universal equivalent of goods\" among producers could simply cease to exist [1]. A powerful combination of logistics and e-commerce is expected to lead to significant changes in the overall business landscape. E-commerce will provide an opportunity for many companies to make the necessary communications and conclude transactions with each other, and logistics will provide an opportunity to more effectively use this information to manage activities in their business. Instead of a two-way relationship between the supplier and the customer, the business will increasingly be based on networks of supply chains, made up of groups of suppliers and customer groups [2]. E-commerce, e-sourcing, e-markets are better to be united under the auspices of logistics barter into an e-integrator, which will be the serving element of the LBP-provider. An e-integrator is an integrator of information and communication technologies for supply chains of logistics barter, in the form of electronic means, taking into account a closing link, e-commerce, and the reverse distribution of added value. The paper describes the new LBP-providers which are not a servicing element of the economy, but become operators of an alternative economy themselves. We have also considered the basics for the mathematical concept of a future LBP (logistic barter) operator. © 2018 Authors.","e-integrator; Human factor; Indifference coefficient; LBP-provider; Mathematical model",{"$nulls":7},"Gabdullin L.V., Bikulov R.A., Efremova O.I., Logistic barter and working conditions of LBP-provider, International Journal of Economic Perspectives, 11, 4, pp. 768-775, (2017); Efremova O.I., Gabdullin L.V., Logistic barter features as a new concept of supply chain management, Academy of Strategic Management Journal, 15, 2, pp. 19-25, (2016); Bulatov A.S., Economy. Textbook, (2003); Sergeev V.I., Supply Chain Management: A Handbook by Gower Publishing house, (2008); Gabdullin L.V., Logistic barter and the future: perspectives and contradictions, Logistics today, 6, pp. 332-336, (2013); Gabdullin L.V., LBP-provider of logistics barter, Logistics-2014, 2, pp. 27-29, (2014); Gabdullin L.V., Possible sunset of the empire of money between producers due to logistic barter, Scientific Review, 7, pp. 397-400, (2014); Efremova O.I., Gabdullin L.V., Bikulov R.A., Problems and urban infrastructure development in Russia (for example, the city of Naberezhnye Chelny), Journal of Economics and Economic Education Research, 17, 2, pp. 178-184, (2016); Best Practice in Supply Chain Management. Ed, By Gattorna J.-Gower, (1998); Edited by John Gattorna, (1990); Vakifovich G.L., Abdulaevich B.R., Ilinichna E.O., PROBLEMS OF SMALL BUSINESS DEVELOPMENT IN NABEREZHNYE CHELNY (RUSSIA, REPUBLIC OF TATARSTAN), QUID-INVESTIGACION CIENCIA Y TECNOLOGIA, 28, N1, pp. 1608-1612, (2017)","R.A. Bikulov; Kazan Federal University, Russian Federation; email: len1510@mail.ru",null,"Science Publishing Corporation Inc",{"$nulls":5},"2227524X",null,null,null,"English","Int. J. Eng. Technol.","Article","Final",null,"Scopus","2-s2.0-85082366943"]
["Kuo Y.-W.; Hsieh C.-H.","Kuo, Yi-Wen (25930981800); Hsieh, Cheng-Hsien (26322990300)","25930981800; 26322990300","Effects of service recovery after service failure in online shopping logistics",2019.0,"Journal of Quality",26.0,1.0,null,23.0,41.0,18.0,1.0,"10.6220/joq.201902_26(1).0002","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85063682987&doi=10.6220%2fjoq.201902_26%281%29.0002&partnerID=40&md5=39924e0dcd20fa811d65926e0c15a07a","Department of Distribution Management, Shu-Te University, Taiwan; School of Business, Singapore University of Social Sciences, Singapore","Kuo Y.-W., Department of Distribution Management, Shu-Te University, Taiwan; Hsieh C.-H., School of Business, Singapore University of Social Sciences, Singapore","The service quality of online shopping logistics substantially affects the satisfaction and loyalty of the customer. This study determines the critical antecedents of online shopping logistics service quality based on a survey of the literature and cognitive maps, in which the interdependencies and feedback loops between the factors affecting logistics service quality are discussed through expert questionnaire. According to the results of systematic analysis, reliability and timeliness are the most crucial factors in logistics service quality. These factors are then employed to develop the scenarios of service failure. Statistical methods are used to discuss the effects of service recovery after online shopping logistics service failure on the satisfaction and repurchase intention of consumer. Results from the analysis of 434 effective responses show that recovery strategies significantly increase the level of customer satisfaction after service failure, but may not be effective at improving repurchase intention after failure in both timeliness and reliability. © 2019, Chinese Society for Quality. All rights reserved.","Fuzzy cognitive maps (FCMs); Logistics service quality; Repurchase intention; Service failure; Service recovery","Cognitive systems; Customer satisfaction; Electronic commerce; Failure (mechanical); Quality of service; Recovery; Reliability analysis; Surveys; Fuzzy cognitive maps (FCMs); Logistics service qualities; Repurchase intention; Service failure; Service recoveries; Quality control",{"$nulls":4},"National Science Council, NSC, (102-2410-H-366-014); Ministry of Science and Technology of the People's Republic of China, MOST; Ministerio de Ciencia y Tecnología, MICYT, (NSC 102-2410-H-366-014)","The authors would like to express the gratitude to the Ministry of Science and Technology of the Republic of China, Taiwan for financially supporting part of this research under contract number NSC 102-2410-H-366-014.","Akwensivie D.M., Narteh B., Affum S., Service failure, recovery and recovery outcomes in the Ghanaian banking industry, European Journal of Business and Management, 5, 30, pp. 167-175, (2013); Alberts H.C., Alberts R.M., Bloom M.F., Laflamme A.D., Teerikangas S., The three Gorges dam project from a systems viewpoint, Systems Research and Behavioral Science, 21, 6, pp. 585-602, (2004); Ambrose M., Hess R.L., Ganesan S., The relationship between justice and attitudes: An examination of justice effects on event and system-related attitudes, Organizational Behavior and Human Decision Processes, 103, 1, pp. 21-36, (2007); Andreassen T.W., Antecedents to satisfaction with service recovery, European Journal of Marketing, 34, 1-2, pp. 156-175, (2000); Anton C., Camarero C., Carrero M., Analysing firms’ failures as determinants of consumer switching intentions: The effect of moderating factors, European Journal of Marketing, 41, 1-2, pp. 135-158, (2007); Athanassopoulos A.D., Customer satisfaction cues to support market segmentation and explain switching behavior, Journal of Business Research, 47, 3, pp. 191-207, (2000); Ba S., Whinston A.B., Zhang H., Building trust in online auction markets through an economic incentive mechanism, Decision Support Systems, 35, 3, pp. 273-286, (2003); 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Kuo; Department of Distribution Management, Shu-Te University, Kaohsiung City, 59, Hengshan Rd., Yanchao Dist., 82445, Taiwan; email: shauai@stu.edu.tw",null,"Chinese Society for Quality",{"$nulls":5},1.022069E7,null,null,null,"English","J Qual.","Article","Final",null,"Scopus","2-s2.0-85063682987"]
["Kong X.T.R.; Xu S.X.; Cheng M.; Huang G.Q.","Kong, Xiang T.R. (56118661100); Xu, Su Xiu (35773963700); Cheng, Meng (55816616400); Huang, George Q. (7403425048)","56118661100; 35773963700; 55816616400; 7403425048","IoT-Enabled Parking Space Sharing and Allocation Mechanisms",2018.0,"IEEE Transactions on Automation Science and Engineering",15.0,4.0,8263112.0,1654.0,1664.0,10.0,68.0,"10.1109/TASE.2017.2785241","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85040921931&doi=10.1109%2fTASE.2017.2785241&partnerID=40&md5=79094cb403123ed1d9cefa23b593adf6","Department of Transportation Economics and Logistics Management, College of Economics, Shenzhen University, Shenzhen, 518061, China; HKU-ZIRI Laboratory for Physical Internet, Department of Industrial and Manufacturing Systems Engineering, University of Hong Kong, Hong Kong; Institute of Physical Internet, School of Electrical and Information Engineering, Jinan University, Zhuhai Campus, Zhuhai, 519070, China","Kong X.T.R., Department of Transportation Economics and Logistics Management, College of Economics, Shenzhen University, Shenzhen, 518061, China, HKU-ZIRI Laboratory for Physical Internet, Department of Industrial and Manufacturing Systems Engineering, University of Hong Kong, Hong Kong; Xu S.X., Institute of Physical Internet, School of Electrical and Information Engineering, Jinan University, Zhuhai Campus, Zhuhai, 519070, China; Cheng M., HKU-ZIRI Laboratory for Physical Internet, Department of Industrial and Manufacturing Systems Engineering, University of Hong Kong, Hong Kong; Huang G.Q., HKU-ZIRI Laboratory for Physical Internet, Department of Industrial and Manufacturing Systems Engineering, University of Hong Kong, Hong Kong","This paper is among the first proposing an integrated auction and market design method for the parking space sharing and allocation problem. Drivers (agents) who fail to exchange their own parking spaces can then rent them to the platform. The platform receives private parking spaces from agents and manages some public parking spaces. We first develop the urban parking management cloud platform through Internet of Things. Based on this systemic framework, parking spaces are shared among agents via a price-compatible top trading cycles and chains (PC-TTCCs) mechanism and the platform's parking spaces are reassigned via a one-sided Vickrey-Clarke-Groves (O-VCG) auction. Both the PC-TTCC mechanism with rule e (PC-TTCC [e]) and O-VCG auction are effective in terms of strategy-proofness and (allocative or Pareto) efficiency. In the PC-TTCC [e] mechanism, the platform's payment rule used in private parking space sharing is determined based on historical O-VCG auction prices. Our experimental results further show that the proposed mechanism results in system profitability of 20%-30% and ex post budget balance for the platform. Note to Practitioners - This paper was motivated by the problem of constantly climbing parking needs in major cities. This paper suggests a new approach for intelligent parking space sharing, allocation, and pricing from the integrated market design and auction perspective based on Internet of Things/cloud technological architecture. The proposed mechanisms are effective in terms of strategy-proofness and efficiency, leading to remarkable system profitability. Reasonable agents' cost saving, bidders' value, and ex post budget balance for the platform can also be guaranteed in a big city with larger population. Several key managerial implications have been gained. First, a public platform should choose the integrated mechanism that realizes higher agents' cost saving. Second, agents should be encouraged to rent their private parking slots to the platform for reaching more agents' welfare. Third, the platform should leverage his owned public parking spaces to achieve higher system profitability and agents' cost saving. Fourth, compared with Vickrey-Clarke-Groves auction, the simpler first-price auction may lead to higher cost saving for agents in some cases even if it cannot realize allocative efficiency and incentive compatibility. Finally, the platform's profit will increase and the agents' cost saving will decrease with the percentage of no show. Preliminary simulation experiments suggest that this approach is feasible but it has not yet been incorporated into a prototype system nor verified in real-world applications. Regarding future work, some other factors such as transaction costs, parking uncertainty, and release of traffic congestion can be included in the proposed mechanism. Our integrated price-compatible top trading cycles and chains [e] and one-sided Vickrey-Clarke-Groves mechanisms can exploit the allocation and pricing problems in B2B e-commerce logistics, on-demand traffic fleet management, and ridesharing optimization. © 2004-2012 IEEE.","Efficient auction; Internet of Things (IoT)-enabled cloud; mechanism design; parking space sharing and allocation; strategy proofness","Budget control; Commerce; Machine design; Parking; Efficient Auction; Internet of Things (IOT); Mechanism design; Parking spaces; Strategy-proofness; Internet of things",{"$nulls":4},"City governments; HKSAR RGC, (17203117, 17212016); Hangzhou Municipal; Hangzhou Municipal, Lin'an City governments; ITF Innovation and Technology Support Program of Hong Kong Government, (ITP/079/16LP); Zhejiang Provincial; National Natural Science Foundation of China, NSFC, (71671116, 71701079)","Funding text 1: Manuscript received May 5, 2017; revised September 29, 2017; accepted December 9, 2017. Date of publication January 18, 2018; date of current version October 4, 2018. This paper was recommended for publication by Associate Editor C. Occhiuzzi and Editor J. Li upon evaluation of the reviewers’ comments. This work was supported in part by Zhejiang Provincial, Hangzhou Municipal, Lin’an City governments, in part by ITF Innovation and Technology Support Program of Hong Kong Government under Grant ITP/079/16LP, in part by HKSAR RGC GRF under Grant 17212016 and Grant 17203117, and in part by the National Natural Science Foundation of China under Grant 71671116 and Grant 71701079. (Corresponding author: Su Xiu Xu.) X. T. R. Kong is with the Department of Transportation Economics and Logistics Management, College of Economics, Shenzhen University, Shenzhen 518061, China, and also with the HKU-ZIRI Laboratory for Physical Internet, Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong (e-mail: kongxtr@hku.hk).; Funding text 2: This work was supported in part by Zhejiang Provincial, Hangzhou Municipal, Lin'an City governments, in part by ITF Innovation and Technology Support Program of Hong Kong Government under Grant ITP/079/16LP, in part by HKSAR RGC GRF under Grant 17212016 and Grant 17203117, and in part by the National Natural Science Foundation of China under Grant 71671116 and Grant 71701079.","Abdulkadiroglu A., Sonmez T., Random serial dictatorship and the core from random endowments in house allocation problems, Econometrica, 66, 3, pp. 689-701, (1998); Ayala D., Wolfson O., Xu B., DasGupta B., Lin J., Pricing of parking for congestion reduction, Proc. 20th Int. 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Vehicles Symp, pp. 1039-1044, (2008); Panja B., Schneider B., Meharia P., Wirelessly sensing open parking spaces: Accounting and management of parking facility, Proc. AMCIS, pp. 1-7, (2011); Pham T.N., Tsai M.F., Nguyen D.B., Dow C.R., Deng D.J., A cloud-based smart-parking system based on Internet-of-Things technologies, IEEE Access, 3, pp. 1581-1591, (2015); Qian Z.S., Rajagopal R., Optimal occupancy-driven parking pricing under demand uncertainties and traveler heterogeneity: A stochastic control approach, Transp. Res. B, Methodol., 67, pp. 144-165, (2014); Roth A.E., Incentive compatibility in a market with indivisible goods, Econ. Lett., 9, 2, pp. 127-132, (1982); Roth A.E., Sonmez T., Unver M.U., Kidney exchange, Quart. J. Econ., 119, 2, pp. 457-488, (2004); Roth A.E., Sonmez T., Unver M.U., Pairwise kidney exchange, J. Econ. Theory, 125, 2, pp. 151-188, (2005); Roth A.E., Sonmez T., Unver M.U., Efficient kidney exchange: Coincidence of wants in markets with compatibility-based preferences, Amer. Econ. Rev., 97, 3, pp. 828-851, (2007); Shapley L., Scarf H., On cores and indivisibility, J. Math. Econ., 1, 1, pp. 23-37, (1974); Shoup D.C., Cruising for parking, Transp. Policy, 13, 6, pp. 479-486, (2006); Shoup D., Free parking or free markets, Access Mag., 1, 38, pp. 28-35, (2011); Sonmez T., Unver M.U., Altruistically unbalanced kidney exchange, J. Econ. Theory, 152, pp. 105-129, (2014); Vianna M.M.B., Da Silva Portugal L., Balassiano R., Intelligent transportation systems and parking management: Implementation potential in a Brazilian city, Cities, 21, 2, pp. 137-148, (2004); Vickrey W., Counterspeculation, auctions, and competitive sealed tenders, J. Finance, 16, 1, pp. 8-37, (1961); Wallsten S., The Competitive Effects of the Sharing Economy: How Is Uber Changing Taxis?, 22, (2015); Xu S.X., Cheng M., Kong X.T., Yang H., Huang G.Q., Private parking slot sharing, Transp. Res. B, Methodol., 93, pp. 596-617, (2016); Zou B., Kafle N., Wolfson O., Lin J.J., A mechanism design based approach to solving parking slot assignment in the information era, Transp. Res. B, Methodol., 81, pp. 631-653, (2015); Zervas G., Proserpio D., Byers J., The Rise of the Sharing Economy: Estimating the Impact of Airbnb on the Hotel Industry, (2016)","X.T.R. Kong; Department of Transportation Economics and Logistics Management, College of Economics, Shenzhen University, Shenzhen, 518061, China; email: kongxtr@hku.hk",null,"Institute of Electrical and Electronics Engineers Inc.",{"$nulls":5},1.5455955E7,null,null,null,"English","IEEE Trans. Autom. Sci. Eng.","Article","Final",null,"Scopus","2-s2.0-85040921931"]
["Zaboon A.A.; Ganawi N.K.; Dakhil A.A.","Zaboon, Amel Asmar (57208420400); Ganawi, Nadia Khutheir (57208427830); Dakhil, Alaa Abbas (57208423149)","57208420400; 57208427830; 57208423149","The role of e-commerce industry in the sustainable economic development of Iraq",2018.0,"International Journal of Entrepreneurship",22.0,"Specialissue",null,null,null,13.0,0.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85064730442&partnerID=40&md5=c8f00b30901b9c6915ae80183cbc1cbf","University Of Al-Qadisiyah, Iraq","Zaboon A.A., University Of Al-Qadisiyah, Iraq; Ganawi N.K., University Of Al-Qadisiyah, Iraq; Dakhil A.A., University Of Al-Qadisiyah, Iraq","In this modern era of technological advancement, e-commerce has emerged as an important economic partner for any country. The simple & quick purchasing model, different & easy payment methods and cash on delivery services with suitable return policies, have made the e-commerce industry highly significant. Customer satisfaction is high in this mode of online shopping and trading, globally. Therefore, the central objective of this research is to describe the role of e-commerce industry in the sustainable economic development of Iraq, with a wide range of e-commerce trends in different niches to facilitate national & international consumers. Hence, special attention is paid towards the role of e-commerce, customer satisfaction via this innovative & rising business way in Iraq. To explain further, four hypotheses are taken concerning the e-commerce in technological context, organizational, environmental & individual contexts. An online survey was conducted, and detailed questionnaires were distributed, in which simple random technique was used. Due the limitations and emerging e-commerce industry in Iraq, initially 50 questionnaires were distributed among the top level e-commerce websites across the country. This research shows the results that innovative & personal research in IT sector, especially in e-commerce which plays an important role to grow the industry. It contains a bright future if government plays its part as individuals are advancing with their innovative & creative ideas. SMEs have direct links with this industry to create employment in the country too. The buying trend is increasing through e-commerce, which has positive impact on country's economy. The current study is significant to prove the main role of e-commerce industry in sustainable economic development in Iraq. Hence, the study is supportive for e-commerce companies & websites to lessen latest online buying trends, e-paying methods and customer satisfactory ways in modern world. © 2002-2019 Allied Business Academies.","Developing economies; E-commerce; Fuzzy logic; Information technology (IT); Internet; Iraqi enterprises; Small to medium-sized enterprises (SMEs); SMEs; Sustainable economic development",{"$nulls":7},"Al-Qirim N., The adoption of e-Commerce communications and applications technologies in small businesses in New Zealand, Electronic Commerce Research and Applications, 6, 4, pp. 462-473, (2007); Budiarti I., Knowledge management and intellectual capital-A theoretical perspective of human resource strategies and practices, European Journal of Economics and Business Studies, 8, 1, pp. 148-155, (2017); Efendioglu A., Yip V., Murray W., E-Commerce in developing countries: issues and influences, (2004); El-Hossainy T.M., A fuzzy model for multi-criteria evaluation and ranking of technicians, Journal of King Abdulaziz University: Engineering Sciences, 22, 1, pp. 99-118, (2011); Fraser J., Fraser N., McDonald F., The strategic challenge of electronic commerce, Supply Chain Management, 5, 1, pp. 7-14, (2000); Ghobakhloo M., Arias-Aranda D., Benitez-Amado J., Adoption of e-commerce applications in SMEs, Industrial Management & Data Systems, 111, 8, pp. 1238-1269, (2011); Gibbs J.L., Kraemer K.L., A cross-country investigation of the determinants of scope of e-commerce Use: An Institutional Approach, Electronic Markets, 14, 2, pp. 124-137, (2004); Grandon E.E., Pearson J.M., Electronic commerce adoption: an empirical study of small and medium US businesses, Information & Management, 42, 1, pp. 197-216, (2004); Hall C., APEC and SME Policy: Suggestions for an action agenda, (1995); Hawk S., A comparison of B2C e-commerce in developing countries, Electronic Commerce Research, 4, pp. 181-199, (2004); Hsu Y.A., Fang W., Intellectual capital and new product development performance: The mediating role of organizational learning capability, Technological Forecasting & Social Change, 76, 1, pp. 664-677, (2009); Huy L.V., Filiatrault P., The adoption of e-commerce in SMEs in Vietnam: A study of users and prospectors, The Tenth Pacific Asia Conference on Information Systems (PACIS 2006), pp. 1335-1344, (2006); Iddris, Faisal, Adoption of e-commerce solutions in small and medium-sized enterprises in Ghana, European Journal of Business and Management, 4, 10, (2012); Kalakota R., Whinston A.B., Frontiers of electronic commerce, (1996); Korper S., Ellis J., The e-commerce book: Building the e-empire, (2000); Lawrence J.E., The challenges and utilization of e-Commerce: Use of internet by small to medium-sized enterprises in the United Kingdom, Information, Society and Justice, 1, 2, pp. 99-113, (2008); Lawrence J.E., Tar U.A., Barriers to ecommerce in developing countries, Information, Society and Justice, 3, 1, pp. 23-35, (2010); Limthongchai P., Speece M.W., The effect of perceived characteristics of innovation on ecommerce adoption by SMEs in Thailand, The Seventh International Conference on Global Business and Economic Development, pp. 1573-1585, (2003); Lina Z., Guiling Z., Weiwei D., Empirical analysis of factors influencing logistic service satisfaction of Customer of Taobao, Technology and Method, 33, 5, pp. 215-217, (2014); Molla A., Licker P.S., E-commerce adoption in developing countries: A model and instrument, Information & Management, 42, 6, pp. 877-899, (2005); Pearson J.N., Semeijn J., Service priorities in small and large firms engaged in international logistics, International Journal of Physical Distribution & Logistics Management, 29, 3, pp. 181-192, (1999); Premkumar G., A meta-analysis of research on information technology implementation in small business, Journal of Organizational Computing and Electronic Commerce, 13, 2, pp. 91-121, (2003); Rahayu R., Day J., Determinant factors of e-commerce adoption by SMEs in developing country: Evidence from Indonesia, Procedia-Social and Behavioral Sciences, 195, pp. 142-150, (2015); Rayport J.F., Jaworski B.J., E-commerce. McGraw-Hill, (2003); Sekaran U., Bougie R., Uma Sekaran and Roger Bougie, (2010); Sila I., Factors affecting the adoption of B2B e-commerce technologies, Electronic Commerce Research, 13, 2, pp. 199-236, (2013); Thabit H., Adoption the fuzzy logic to enhance the quality of the accounting information to operate balanced scorecard-Applied on Mosul Bank for development & investment in nineveh province, (2013); Thong J.Y.L., An integrated model of information systems adoption in small businesses, Journal of Management Information Systems, 15, 4, pp. 187-214, (1999); Tsiakis T., Sthephanides G., The concept of security and trust in electronic payments, Computers & Security, 24, 1, pp. 10-15, (2005)",null,null,"Allied Business Academies",{"$nulls":5},1.0999264E7,null,null,null,"English","Int. J. Enterp.","Article","Final",null,"Scopus","2-s2.0-85064730442"]
["Kirton J.J.; Warren B.","Kirton, John J. (6701350356); Warren, Brittaney (57204454684)","6701350356; 57204454684","G20 governance of digitalization; [Повестка дня «Группы двадцати» в области цифровизации]",2018.0,"International Organisations Research Journal",13.0,2.0,null,17.0,41.0,24.0,17.0,"10.17323/1996-7845-2018-02-02","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85055651748&doi=10.17323%2f1996-7845-2018-02-02&partnerID=40&md5=3280e4901c4072fd6fd9f96dc6a6770e","University of Toronto, 1 Devonshire Place, Toronto, M5S 3K7, ON, Canada; Director of Compliance of G7 Research Group, G20 Research Group, 1 Devonshire Place, Toronto, M5S 3K7, ON, Canada","Kirton J.J., University of Toronto, 1 Devonshire Place, Toronto, M5S 3K7, ON, Canada; Warren B., Director of Compliance of G7 Research Group, G20 Research Group, 1 Devonshire Place, Toronto, M5S 3K7, ON, Canada","В рамках данной статьи проводится системный анализ деятельности «Группы двадцати» в сфере цифровизации по основным измерениям институциональной эффективности и делаются выводы относительно причин опре- деленных тенденций, складывающихся в этой связи [Kirton, 2013]. Авторы утверждают, что «двадцатка» по- степенно повышала свою эффективность в осуществлении функций глобального управления в цифровой сфере. С самого начала деятельности института в 2008 г. повестка дня в данной области постоянно расширялась, достигнув пика в 2016-2017 гг. Лидеры «Группы двадцати» впервые обратили внимание на вопросы цифровиза- ции вследствие глобального финансово-экономического кризиса 2008 г. На саммите в Вашингтоне была признана роль электронной торговли как важного инструмента борьбы с кризисом. Впоследствии стали обсуждаться и проблемы неравенства, лежащие в основе идеологии антиглобализма. Таким образом, был осуществлен переход от борьбы с последствиями кризиса к принятию превентивных мер. Тенденции расширения круга обсуждаемых вопросов и резкий рост их числа фиксируются по функциям определения направления действий, принятия реше- ний и институционального развития глобального управления, однако не отражаются на функциях реализации принятых решений. Данный тренд обусловлен шокирующим ростом популистских настроений, вызванным про- явлениями неравенства в Великобритании и США в 2015 и 2016 гг., а также провалом традиционных междуна- родных институтов, глобальным коллективным превосходством членов «двадцатки» и конвергенцией их отно- сительных возможностей в цифровой сфере и, наконец, консенсусом о приоритетном характере экономического роста и открытости. Важнейшим фактором, однако, стали интересы Китая, принимавшего форум в 2016 г., и Германии, председательствовавшей в 2017 г. Лидеры этих стран, заручившись политической поддержкой на национальном уровне, стремились сформировать цифровую повестку дня, обеспечивающую справедливое распре- деление благ цифровизации в противовес нарастающим популистским и протекционистским тенденциям. © OECD.; This study systematically assesses the Group of 20 (G20) summit's performance on digitalization across the key dimensions and suggests what has caused its particular pattern of performance thus far [Kirton, 2013]. It argues that the G20 summit's digitalization governance has been increasingly successful. Its digitalization agenda steadily expanded since the beginning, with a major surge in 2016-17. G20 summits first addressed digitalization in response to the American-turned-global financial crisis of 2008. Then, G20 leaders acknowledged e-commerce as an important tool to manage the crisis. They then gradually expanded their agenda to finally focus on inequality, a root cause of antiglobalization. They thus moved from a crisis-response to a crisis-prevention approach. This spread and spike is seen in the G20's direction-setting, decision-making and institutional development of global governance, but not in its delivery of its decisions. This overall performance was driven partly by the shocking surge in populism bred by inequality in the UK and U.S. in 2015 and 2016, by the failure of the established multilateral organizations in response, by the global predominance and equalizing capabilities of G20 members in specialized digital capabilities and their convergence on the economic growth through openness that digitalization brought. Yet this performance flowed primarily from the hosting of economically reforming China in 2016 and export-oriented Germany in 2017, whose politically secure leaders sought to shape digitalization for the benefit of all in response to the rise of populism and protectionism in the UK and the United States. © OECD.","Antiglobalization; Causes of performance; Digital economy; Digitalization; Dimensions of performance; G20; Inequality; «Группа двадцати»; Антиглобализм; Неравенство; Факторы глобального управления; Факторы эффективности; Цифровая экономика; цифровизация",{"$nulls":7},"Carin B., G20 Safeguards Digital Economy Vulnerabilities with a Financial Sector Focus, Economics: The Open-Access, Open Assessment E-Journal, 11, (2017); Chetty K., Qigui L., Gcora N., Josie J., Wenwei L., Fang C., Bridging the Digital Divide: Measuring Digital Literacy, (2017); Donnan S., US, EU and Japan to Link up on China Trade, (2017); Donnan S., WTO Wrestles with Relevance in Age of Ecommerce, (2017); Gapper J., Bitcoin Casts a Shadow over Bank Payments, (2017); Declaration of the Summit on Financial Markets and the World Economy, (2008); The G20 Toronto Summit Declaration, (2010); G20 Leaders' Communiqué, (2015); G20 Blueprint on Innovative Growth, (2016); Overview of Argentina's G20 Presidency in 2018, (2017); G20 Leaders' Declaration: Shaping an Interconnected World, (2017); Global Wealth Report 2017, (2017); Global Commission on the Future of Work; The State of Broadband: Broadband Catalyzing Sustainable Development, (2017); Kirton J., G20 Governance for a Globalized World, (2013); Kirton J., China's G20 Leadership, (2016); Kirton J., A Summit of Solid Success at Hamburg in 2017, (2017); Kirton J., Warren B., G20 Insights: T20 Recommendations Realized, (2017); Mariani S., Dionne M., \"How Can the G20 Use AI to Help Create Sustainable Communities in an Inter-Connected World?\" G20 Information Centre, (2017); Maupin J., The G20 Countries Should Engage with Blockchain Technologies to Build an Inclusive, Transparent, and Accountable Digital Economy for All, (2017); Manyika J., Chui M., Miremadi M., Bughin J., George K., Wilmott P., Dewhurst M., A Future That Works: Automation, Employment, and Productivity, (2017); Measuring the Digital Economy: A New Perspective, (2014); Automation and Independent Work in a Digital Economy, (2016); Ministerial Declaration on the Digital Economy, (2016); Key Issues for Digital Transformation in the G20, (2017); OECD Digital Economy Outlook 2017, (2017); Patel P., Will Automation Kill or Create Jobs? The Institute, (2017); Rosenbaum M., Local Voting Figures Shed New Light on EU Referendum, (2017); Rothwell J.T., Diego-Rosell P., Explaining Nationalist Political Views: The Case of Donald Trump, (2016); Snower D., The G20 Summit was More Successful than You Think, (2017); Stirling R., Miller H., Truswell E.M., Government AI Readiness Index, (2017); Tyson A., Maniam S., Behind Trump's Victory: Divisions by Race, Gender, Education, (2016); Global Risks Report 2017, (2017)",null,null,"National Research University Higher School of Economics",{"$nulls":5},1.9967845E7,null,null,null,"English","Int. Organ. Res. J.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85055651748"]
["Millstein M.A.; Campbell J.F.","Millstein, Mitchell A. (55971786600); Campbell, James F. (25123472800)","55971786600; 25123472800","Total Hockey optimizes omnichannel facility locations",2018.0,"Interfaces",48.0,4.0,null,340.0,356.0,16.0,9.0,"10.1287/inte.2018.0942","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85055271284&doi=10.1287%2finte.2018.0942&partnerID=40&md5=9b9090ed738189c8f51da9f4adf2b225","College of Business Administration, University of Missouri-St. Louis, St. Louis, 63121, MO, United States","Millstein M.A., College of Business Administration, University of Missouri-St. Louis, St. Louis, 63121, MO, United States; Campbell J.F., College of Business Administration, University of Missouri-St. Louis, St. Louis, 63121, MO, United States","Omnichannel distribution, which blends brick-and-mortar retailing and e-commerce, is a key challenge for today's supply chains. In this paper, we report on a study to design an omnichannel distribution system for Total Hockey, a growing U.S. sporting goods retailer in a competitive environment. Management strongly believes that e-commerce success will depend on high service levels characterized by one- or twoday delivery and initially thought that a new omnichannel warehouse located on the East Coast could support its expansion plans. To study the situation, we developed a profit-maximizing optimization model for locating omnichannel warehouses that supports both e-commerce and store shipments. The model uses estimates of e-commerce demand by metropolitan statistical area (MSA) across the United States, while incorporating management's sales expectations regarding the value of high service levels, e-commerce sales lost to competitors' stores, and reverse cannibalism from Total Hockey's own retail stores. Multiple warehouse sizes allow modeling of nonlinear inventory costs. The facility-location optimization model allows exploration of multiple solutions and an assessment of the impact of higher service levels. The results of the study were contrary to management expectations and suggested a significant redesign of the distribution system. We report results for several analyses, implementation details, and managerial insights for omnichannel distribution. © 2018 The Author(s).","E-commerce; Facility-location modeling; Integer programming; Linear programming; Omnichannel; OR/MS implementation: applications",{"$nulls":5},"Total","History: This paper was refereed. Funding: This project was funded by Total Hockey as an applied research project.","Agatz N.A.H., Fleischmann M., Van Nunen J.A.E.E., E-fulfillment and multichannel distribution-A review, Eur. J. Oper. Res., 187, 2, pp. 339-356, (2008); Alptekinoglu A., Tang C., A model for analyzing multi-channel distribution systems, Eur. J. Oper. Res., 163, 3, pp. 802-824, (2005); Bendoly E., Blocher D., Bretthauer K., Venkataramanan M., Service and cost benefits through clicks-and-mortar integration: Implications for the centralization/decentralization debate, Eur. J. Oper. Res., 180, 1, pp. 426-442, (2007); Bretthauer K.M., Mahar S., Venakataramanan S.M.A., Inventory and distribution strategies for retail/e-tail organizations, Comput. Indust. Engrg., 58, 1, pp. 119-132, (2010); Cao L., Li L., The impact of cross-channel integration on retailers' sales growth, J. Retailing, 91, 2, pp. 198-216, (2015); Chao L., Norton S., Retailers bet big on retooling their supply chains for e-commerce, Wall Street Journal, (2016); Chiang W.K., Monahan G., Managing inventories in a twoechelon dual-channel supply chain, Eur. J. Oper. Res., 162, 2, pp. 325-341, (2005); Gallino S., Moreno A., Integration of online and offline channels in retail: The impact of sharing reliable inventory availability information, Management Sci., 60, 6, pp. 1434-1451, (2014); Griffin-Cryan B., Wall K., The rising relevance of brick-andmortar stores, CSCMP's Supply Chain Quart., 5, (2015); Huff D.L., A programmed solution for approximating an optimal retail location, Land Econom., 42, 3, pp. 293-303, (1966); Hubner A., Holzapfel A., Kuhn H., Distribution systems in omnichannel retailing, Bus. Res., 9, 2, pp. 255-296, (2016); Ishfaq R., Defee C., Gibson B.J., Raja U., Realignment of the physical distribution process in omnichannel fulfillment, Internat. J. Phys. Distribution Logist. Management, 46, 6-7, pp. 543-561, (2016); Levasseur R.E., People skills: Building analytics decision models that managers use-A change management perspective, Interfaces, 45, 4, pp. 363-364, (2015); Liu K., Zhou Y., Zhang Z., Capacitated location model with online demand pooling in a multi-channel supply chain, Eur. J. Oper. Res., 207, 1, pp. 218-231, (2010); Mahar S., Wright P., The value of postponing online fulfillment decisions in multi-channel retail/e-tail, Comput. Oper. Res., 36, 11, pp. 3061-3072, (2009); Millstein M.A., Yang L., Li H., Optimizing ABC inventory decisions, Internat. J. Production Econom., 148, pp. 71-80, (2014); Neale J.J., Willems S.P., Managing inventory in supply chains with nonstationary demand, Interfaces, 39, 5, pp. 388-399, (2009); Inventoryoptimizer, (2015); Pauwels K., Neslin S., Building with bricks and mortar: The revenue impact of opening physical stores in a multichannel environment, J. Retailing, 91, 2, pp. 182-197, (2015); Smith C., Same-day delivery: E-commerce giants are battling to own the \"last mile, Business Insider, (2014); Swaminathan J.M., Tayur S.R., Models for supply chains in ebusiness, Management Sci., 49, 10, pp. 1387-1406, (2003); Torabi S.A., Hassini E., Jeihoonian M., Fulfillment source allocation, inventory transshipment, and customer order transfer in e-tailing, Transportation Res. Part E: Logist. Transportation Rev., 79, pp. 128-144, (2015); Zhang S., Lee C., Wu K., Choy K., Multi-objective optimization for sustainable supply chain network design considering multiple distribution channels, Expert Systems Appl., 65, pp. 87-99, (2016)",null,null,"INFORMS Inst.for Operations Res.and the Management Sciences",{"$nulls":5},922102.0,null,null,null,"English","Interfaces","Article","Final",null,"Scopus","2-s2.0-85055271284"]
["Hanbazazah A.S.; Abril L.E.; Shaikh N.I.; Erkoc M.","Hanbazazah, Abdulkader S. (57201033466); Abril, Luis E. (57201034146); Shaikh, Nazrul I. (7005595472); Erkoc, Murat (8905996000)","57201033466; 57201034146; 7005595472; 8905996000","A redesigned benders decomposition approach for large-scale in-transit freight consolidation operations",2018.0,"International Journal of Information Systems and Supply Chain Management",11.0,2.0,null,1.0,15.0,14.0,4.0,"10.4018/IJISSCM.2018040101","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85042911512&doi=10.4018%2fIJISSCM.2018040101&partnerID=40&md5=196934126f3ff00ba9e2dddba8bdc13c","University of Jeddah, Jeddah, Saudi Arabia; University of Miami, Miami, United States","Hanbazazah A.S., University of Jeddah, Jeddah, Saudi Arabia; Abril L.E., University of Miami, Miami, United States; Shaikh N.I., University of Miami, Miami, United States; Erkoc M., University of Miami, Miami, United States","The growth in online shopping and third-party logistics has caused a revival of interest in finding optimal solutions to the large-scale, in-transit freight consolidation problem. Given the shipment date, size, origin, destination, and due dates of multiple shipments distributed over space and time, the problem requires determining when to consolidate some of these shipments into one shipment at an intermediate consolidation point so as to minimize shipping costs while satisfying the due date constraints. In this article, the authors develop a mixed-integer programming formulation for a multi-period freight consolidation problem that involves multiple products, suppliers, and potential consolidation points. Benders decomposition is then used to replace a large number of integer freight-consolidation variables by a small number of continuous variables that reduce the size of the problem without impacting optimality. The results show that Benders decomposition provides a significant scale-up in the performance of the solver. The authors demonstrate their approach using a large-scale case with more than 27.5 million variables and 9.2 million constraints. Copyright © 2018, IGI Global.","Benders Decomposition; Freight Consolidation; Mathematical Programming; Third Party Logistics","Integer programming; Mathematical programming; Outsourcing; Ships; Stochastic programming; Benders decomposition; Continuous variables; Freight consolidations; Mixed integer programming; Multiple products; Multiple shipments; Optimal solutions; Third party logistics; Constraint satisfaction problems",{"$nulls":6},"3PL Market Analysis, (2015); Croxton K.L., Gendron B., Magnanti T.L., Models and methods for merge-in-transit operations, Transportation Science, 37, 1, pp. 1-22, (2003); Dondo R.G., Mendez C.A., Solving large distribution problems in supply chain networks by a column generation approach, International Journal of Operations Research and Information Systems, 5, 3, pp. 50-80, (2014); Fischetti M., Ljubic I., Sinnl M., Redesigning Benders decomposition for large-scale facility location, Management Science, (2016); Golias M.M., Saharidis G.K.D., Boile M., Theofanis S., Scheduling of inbound trucks at a cross-docking facility: Bi-objective vs bi-level modeling approaches, International Journal of Information Systems and Supply Chain Management, 5, 1, pp. 20-37, (2012); Guastaroba G., Speranza M.G., Vigo D., Intermediate facilities in freight transportation planning: A survey, Transportation Science, 50, 3, pp. 763-789, (2016); Jin Y., Muriel A., Single‐warehouse multi‐retailer inventory systems with full truckload shipments. [NRL], Naval Research Logistics, 56, 5, pp. 450-464, (2009); Lim A., Miao Z., Rodrigues B., Xu Z., Transshipment through cross docks with inventory and time windows, Naval Research Logistics, 52, 8, pp. 724-733, (2005); Moccia L., Cordeau J.F., Laporte G., Ropke S., Valentini M.P., Modeling and solving a multimodal transportation problem with flexible-time and scheduled services, Networks, 57, 1, pp. 53-68, (2011); Popken D.A., An algorithm for the multiattribute, multicommodity flow problem with freight consolidation and inventory costs, Operations Research, 42, 2, pp. 274-286, (1994); Qian F., Xu Y., A simulation model for LTL trucking network, International Journal of Information Systems and Supply Chain Management, 5, 3, pp. 78-87, (2012); Song H., Hsu V.N., Cheung R.K., Distribution coordination between suppliers and customers with a consolidation center, Operations Research, 56, 5, pp. 1264-1277, (2008); Xiaomin X., Yi L., Customer satisfaction of the third-party logistics enterprise based on AHP: A case study, International Journal of Information Systems and Supply Chain Management, 10, 1, pp. 68-81, (2017)",null,null,"IGI Global",{"$nulls":5},1.9355726E7,null,null,null,"English","Int. J. Inf. Syst. Supply Chain Manage.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85042911512"]
["Goffnett S.P.; Paquet A.N.; Strong O.M.; McCarron K.P.","Goffnett, Sean P. (48561056800); Paquet, Andrew N. (57208908078); Strong, Oliver M. (26538857200); McCarron, Kevin P. (57208907351)","48561056800; 57208908078; 26538857200; 57208907351","Replication of a Six Sigma black belt case study: GEP box's paper helicopter experiment in a drone logistics scenario",2019.0,"International Journal of Productivity and Quality Management",27.0,1.0,null,17.0,65.0,48.0,4.0,"10.1504/IJPQM.2019.099628","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85066101539&doi=10.1504%2fIJPQM.2019.099628&partnerID=40&md5=c29d6410e106aff3bdaf637ba89651aa","Department of Marketing, Faculty of Logistics and Marketing, College of Business Administration, Central Michigan University, Mt. Pleasant, 48859, MI, United States; Faculty of Business Administration, College of Business Administration, Central Michigan University, Mt. Pleasant, 48859, MI, United States; Department of Computer Science, Faculty of Computer Science, College of Science and Engineering, Central Michigan University, Mt. Pleasant, 48859, MI, United States; Department of Information Systems, Faculty of Information Systems, College of Business Administration, Central Michigan University, Mt Pleasant, 48859, MI, United States","Goffnett S.P., Department of Marketing, Faculty of Logistics and Marketing, College of Business Administration, Central Michigan University, Mt. Pleasant, 48859, MI, United States; Paquet A.N., Faculty of Business Administration, College of Business Administration, Central Michigan University, Mt. Pleasant, 48859, MI, United States; Strong O.M., Department of Computer Science, Faculty of Computer Science, College of Science and Engineering, Central Michigan University, Mt. Pleasant, 48859, MI, United States; McCarron K.P., Department of Information Systems, Faculty of Information Systems, College of Business Administration, Central Michigan University, Mt Pleasant, 48859, MI, United States","Unmanned aerial vehicles (drones) have gained attention in business in recent years. Drones have demonstrated potential use in logistics operations, such as surveillance, inventory counting, order picking, and 'last-mile' delivery. Given the proliferation in potential uses of drones, it is no surprise companies are testing drone capabilities. This article presents a theoretical business case describing the Six Sigma DMAIC model applied in a logistics context involving drone capacity and reliability. Define, measure, analyse, improve and control are presented. This article builds on earlier studies on structuring Six Sigma projects. This service-related business case can be used for training and education purposes. © 2019 Inderscience Enterprises Ltd.","Distribution; DMAIC; DOE; Drone; E-commerce; Failure modes; FMEA; Fulfilment; Gage R&R; Logistics; Repeatability; Reproducibility; Six Sigma; Unmanned aerial vehicle; Warehousing",{"$nulls":7},"Aguirre-Torres V., Lopez-Alvarez M., Parts of the process, Quality Progress, 46, 6, pp. 34-39, (2013); Potential Failure Mode and Effects Analysis, (2008); Measurement System Analysis Reference Manual, (2010); Besseris G., Multi-response quality improvement by non-parametric DOE methods, International Journal of Productivity and Quality Management, 4, 3, pp. 303-323, (2009); Box G.E., Hunter W.G., Hunter J.S., Statistics for Experimenters: An Introduction to Design, Data Analysis, Model Building, (1978); Box G.E.P., Teaching engineers experimental design with a paper helicopter, Quality Engineering, 4, 3, pp. 453-459, (1992); Chakraborty A., Tan K.C., Case study analysis of Six Sigma implementation in service organisations, Business Process Management Journal, 18, 6, pp. 992-1019, (2012); Chen H.T., Chen K.S., A paired-test method to verify service speed improvement in the Six Sigma approach: A restaurant's case study, Total Quality Management and Business Excellence, 27, 11-12, pp. 1277-1297, (2016); Cheng C.Y., Chang P.Y., Implementation of the lean Six Sigma framework in non-profit organisations: A case study, Total Quality Management and Business Excellence, 23, 3-4, pp. 431-447, (2012); D'Andrea R., Guest editorial can drones deliver, IEEE Transactions on Automation Science and Engineering, 11, 3, pp. 647-648, (2014); Does R., Vanden Heuvel E., De Mast J., Bisgaard S., Comparing nonmanufacturing with traditional applications of Six Sigma, Quality Engineering, 15, 1, pp. 177-182, (2002); Edmund M., Drone dilemma, Quality Progress, 48, 9, (2015); English T., Simpson J., Landman D., Parker P., An efficient split-plot approach for modeling nonlinear aerodynamic effects, Quality Engineering, 24, 4, pp. 522-530, (2012); Hagen M., The wisdom of the coach: A review of managerial coaching in the Six Sigma context, Total Quality Management and Business Excellence, 21, 8, pp. 791-798, (2010); Jirasukprasert P., Arturo Garza-Reyes J., Kumar V., Lim M K., A Six Sigma and DMAIC application for the reduction of defects in a rubber gloves manufacturing process, International Journal of Lean Six Sigma, 5, 1, pp. 2-21, (2014); Johnson A., Swisher B., How Six Sigma improves R&D, Research Technology Management, 46, 2, pp. 12-15, (2003); Johnson J., Widener S., Gitlow H., Popovich E., A Six Sigma© black belt case study: GEP Box's paper helicopter experiment part A, Quality Engineering, 18, 4, pp. 413-430, (2006); Johnson J., Widener S., Gitlow H., Popovich E., A Six Sigma© black belt case study: GEP Box's paper helicopter experiment part B, Quality Engineering, 18, 4, pp. 431-442, (2006); Kuiper A., Vande Hoef R., Wesseling M., Lameijer B.A., Does R.J., Quality quandaries: Improving a customer value stream at a financial service provider, Quality Engineering, 28, 1, pp. 155-163, (2016); Laureani A., Antony J., Reducing employees' turnover in transactional services: A lean Six Sigma case study, International Journal of Productivity and Performance Management, 59, 7, pp. 688-700, (2010); Laureani A., Antony J., Douglas A., Lean six sigma in a call centre: A case study, International Journal of Productivity and Performance Management, 59, 8, pp. 757-768, (2010); Linderman K., Schroeder R., Zaheer S., Choo A., Six Sigma: A goal-theoretic perspective, Journal of Operations Management, 21, 2, pp. 193-203, (2003); Lipscomb B., Lewis A., The principles of Six Sigma: Building a quality claims management program, Risk Management, 51, 2, pp. 30-34, (2004); Montgomery D.C., Design and Analysis of Experiments, (1997); Murray C., Chu A., The flying sidekick traveling salesman problem: Optimization of drone-assisted parcel delivery, Transportation Research Part C: Emerging Technologies, 54, 1, pp. 86-109, (2015); Nadeau S., Lean, Six Sigma and lean Six Sigma in higher education: A review of experiences around the world, American Journal of Industrial and Business Management, 7, 5, pp. 591-603, (2017); Natarajan M., Senthil V., Devadasan S.R., Vijay Mohan N., QUARNEWSS: A model for applying Six Sigma framework to achieve continuous quality and reliability improvement in new product development, International Journal of Productivity and Quality Management, 7, 1, pp. 44-73, (2011); Natarajan R.N., Morse J., Six Sigma in services-challenges and opportunities, International Journal of Productivity and Quality Management, 4, 5-6, pp. 658-675, (2009); Pepitone J., Domino's Tests Drone Pizza Delivery, (2013); Prashar A., Six Sigma adoption in public utilities: A case study, Total Quality Management and Business Excellence, 27, 5-6, pp. 479-506, (2016); Statistical Solutions, Process Sigma Calculator, LLC Wisconsin USA; Ramadan Z.B., Farah M.F., Mrad M., An adapted TPB approach to consumers acceptance of service-delivery drones, Technology Analysis and Strategic Management, 29, 7, pp. 817-828, (2017); Rutkin A., Flight school for robots, New Scientist, 229, 3058, (2016); Schmidt M., Amazon's Going the 'last mile, Quality Progress, 47, 6, (2014); Scott C., Scott J., Efficient allocation of online grovery orders, International Journal of Productivity and Quality Management, 1, 1-2, pp. 88-102, (2006); Singh B., Khanduja D., Introduce quality processes through DOE: A case study in die casting foundry, International Journal of Productivity and Quality Management, 8, 4, pp. 373-397, (2011); Snee R., Six Sigma improves both statistical training and processes, Quality Progress, 33, 1, pp. 68-73, (2000); Southard P.B., Chandra C., Kumar S., RFID in healthcare: A Six Sigma DMAIC and simulation case study, International Journal of Health Care Quality Assurance, 25, 4, pp. 291-321, (2012); Srinivasan K., Muthu S., Devadasan S.R., Sugumaran C., Six Sigma through DMAIC phases: A literature review, International Journal of Productivity and Quality Management, 17, 2, pp. 236-257, (2016); Thomas A., Antony J., Haven-Tang C., Francis M., Fisher R., Implementing lean Six Sigma into curriculum design and delivery-a case study in higher education, International Journal of Productivity and Performance Management, 66, 5, pp. 577-597, (2017); Vinod M., Devadasan S.R., Sunil D.T., Thilak V.M.M., Murugesh R., POYSS: A model for integrating Poka-Yoke technique with Six Sigma concept, International Journal of Productivity and Quality Management, 22, 2, pp. 223-242, (2017); Wahba P., WalMart Has Found a Great Way to Use Drones, (2016); Waterworth A., Eldridge S., The development of an e-commerce failure mode and effects analysis, International Journal of Productivity and Quality Management, 8, 3, pp. 247-264, (2011); Wei C.C., Sheen G.J., Tai C.T., Lee K.L., Using Six Sigma to improve replenishment process in a direct selling company, Supply Chain Management: An International Journal, 15, 1, pp. 3-9, (2010); Yin R.K., Case Study Research: Design and Methods (Applied Social Research Methods) 5th Ed, (2014)","S.P. Goffnett; Department of Marketing, Faculty of Logistics and Marketing, College of Business Administration, Central Michigan University, Mt. Pleasant, 48859, United States; email: goffn1sp@cmich.edu",null,"Inderscience Publishers",{"$nulls":5},1.7466474E7,null,null,null,"English","Int. J. Prod. Qual. Manage.","Article","Final",null,"Scopus","2-s2.0-85066101539"]
["Vakulenko Y.; Hellström D.; Hjort K.","Vakulenko, Yulia (57198431040); Hellström, Daniel (6603092522); Hjort, Klas (55480129900)","57198431040; 6603092522; 55480129900","What's in the parcel locker? Exploring customer value in e-commerce last mile delivery",2018.0,"Journal of Business Research",88.0,null,null,421.0,427.0,6.0,144.0,"10.1016/j.jbusres.2017.11.033","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85036533718&doi=10.1016%2fj.jbusres.2017.11.033&partnerID=40&md5=3f83a0f1374a9ef96993876639e73dba","LTH, Lund University, Sweden","Vakulenko Y., LTH, Lund University, Sweden; Hellström D., LTH, Lund University, Sweden; Hjort K., LTH, Lund University, Sweden","This study explores customer value in relation to parcel lockers, a self-service tool that reshapes the delivery and returns experience in the context of e-commerce last mile delivery. Parcel lockers offer a response to retail and last mile delivery challenges provoked by the rapid growth of e-commerce worldwide. Retailers, logistics service providers, communities, and other stakeholders now face issues due to increased volumes of goods sold online. The introduction of parcel lockers to service algorithms is intended to address these issues by involving consumers in the service process. However, the existing research fails to provide knowledge about the customer's view on this new technological solution. This study followed a focus group design and built on grounded theory to provide insights into customer value in relation to parcel lockers. These insights can contribute to both research and practice. © 2017 Elsevier Inc.","Customer value; E-commerce; Focus groups; Last mile delivery; Parcel locker; Self-service technology",{"$nulls":5},"Swedish innovation agency; VINNOVA","This research was conducted within the frame of the “Parcel locker in urban-, rural areas at workplaces and at authorities” project, which is funded by Vinnova, the Swedish innovation agency. The funding source had no role in any aspect of the study design, collection, analysis, or interpretation of the data, writing the report, or the decision to submit the article for publication.","Alcock T., Millard N., Self-service — But is it good to talk?, BT Technology Journal, 24, 1, pp. 70-78, (2006); Amit R., Zott C., Value creation in E-business, Strategic Management Journal, 22, 6-7, pp. 493-520, (2001); Bader G.E., Rossi C.A., Focus groups: A step-by-step guide, (1998); Bitner M.J., Ostrom A.L., Meuter M.L., Implementing successful self-service technologies, The Academy of Management Executive, 16, 4, pp. 96-108, (2002); Chen Z., Dubinsky A.J., A conceptual model of perceived customer value in e-commerce: A preliminary investigation, Psychology and Marketing, 20, 4, pp. 323-347, (2003); Christensen G., Methlie L., Value creation in eBusiness: Exploring the impacts of internet-enabled business conduct, BLED 2003 Proceedings, (2003); Corbin J.M., Strauss A., Grounded theory research: Procedures, canons, and evaluative criteria, Qualitative Sociology, 13, 1, pp. 3-21, (1990); Cossio-Silva F.-J., Revilla-Camacho M.-A., Vega-Vazquez M., Palacios-Florencio B., Value co-creation and customer loyalty, Journal of Business Research, 69, 5, pp. 1621-1625, (2016); Czepiel J.A., Service encounters and service relationships: Implications for research, Journal of Business Research, 20, 1, pp. 13-21, (1990); Davis F.D., Bagozzi R.P., Warshaw P.R., User acceptance of computer technology: A comparison of two theoretical models, Management Science, 35, 8, pp. 982-1003, (1989); Dieke A.K., Bender C., Campbell J.I., Cohen R.H., Muller C., Niederprum A., Zanker C., Main developments in the postal sector (2010 − 2013), (2013); Drucker P.F., The practice of management: A study of the most important function in America society, (1954); Ducret R., Parcel deliveries and urban logistics: Changes and challenges in the courier express and parcel sector in Europe—The French case, Research in Transportation Business & Management, 11, pp. 15-22, (2014); Echeverri P., Skalen P., Co-creation and co-destruction: A practice-theory based study of interactive value formation, Marketing Theory, 11, 3, pp. 351-373, (2011); European Commission, GREEN PAPER. 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Vakulenko; Lund University, LTH, Department of Design Sciences, Division of Packaging Logistics, Lund, Sölvegatan 26, Box 118, 221 00, Sweden; email: yulia.vakulenko@plog.lth.se",null,"Elsevier Inc.",{"$nulls":5},1482963.0,null,"JBRED",null,"English","J. Bus. Res.","Article","Final",null,"Scopus","2-s2.0-85036533718"]
["Yu H.; Zhang R.; Liu B.","Yu, Han (57204941582); Zhang, Rong (56164017300); Liu, Bin (57193329132)","57204941582; 56164017300; 57193329132","Analysis on consumers' purchase and shopping well-being in online shopping carnivals with two motivational dimensions",2018.0,"Sustainability (Switzerland)",10.0,12.0,4603.0,null,null,null,31.0,"10.3390/su10124603","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85058043126&doi=10.3390%2fsu10124603&partnerID=40&md5=73af7f0d4a5677da315cc531ce414f43","School of Economics and Management, Shanghai Maritime University, Shanghai, 201306, China; Research Center of Logistics, Shanghai Maritime University, Shanghai, 201306, China","Yu H., School of Economics and Management, Shanghai Maritime University, Shanghai, 201306, China; Zhang R., Research Center of Logistics, Shanghai Maritime University, Shanghai, 201306, China; Liu B., School of Economics and Management, Shanghai Maritime University, Shanghai, 201306, China","The development of online shopping carnivals (OSCs) is in full bloom due to the support of logistics industry and information technology. More and more people are keen to participate in them. This study contributes to literature by exploring the role of motivational factors (based on utilitarian and hedonic shopping values dimension) of the intention to participate in the actual purchase behavior of consumers and their shopping well-being in OSC. A model is developed and tested to explain consumers' shopping process in the context of OSC. Results show that hedonic shopping values are primarily influenced by entertainment construct, and utilitarian shopping values are positively related to monetary saving, selection, and convenience. Furthermore, the correlation between hedonic shopping value and intention to participate is higher than that between utilitarian shopping value and intention to participate. The findings indicate that intention to participate in OSC exerts a stronger influence on shopping well-being than the effect on actual purchases. © 2018 by the authors.","Hedonic; Online shopping carnival; Shopping well-being; Utilitarian","consumption behavior; correlation; hedonic analysis; human behavior; information technology; Internet; logistics; participatory approach; perception; shopping activity",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (71571117)","This research was funded by National Natural Science Foundation of China, grant number 71571117, and Human and Social Science Foundation of Education Committee of China, grant number 18YJA630143. The authors are grateful to the editors and the anonymous referee for their very valuable comments and suggestions, which have significantly helped to improve the quality of this paper. The authors gratefully acknowledge the support from the National Science Foundation of China through grants 71571117 and Human and Social Science Funding of Education Committee of China through grants 18YJA630143.","Joines J.L., Scherer C., Scheufele D.A., Exploring motivations for consumer Web use and their implications for e-commerce, J. Consum. Mark, 20, pp. 90-108, (2003); Zhang R., Liu B., Group buying decisions of competing retailers with emergency procurement, Ann. Oper. Res, 257, pp. 1-17, (2017); Liao Y., Analysis of Herd Behavior in Online Shopping-A Case Study of \"Double 11 Festival, J. Guangxi Univ. Natl, 38, pp. 156-159, (2016); Xu X., Li Q., Peng L., Hsia T.-L., Huang C.-J., Wu J.-H., The impact of informational incentives and social influence on consumer behavior during Alibaba's online shopping carnival, Comput. Hum. Behav, 76, pp. 245-254, (2017); Yuan X., Chong T.W., Krilavicius T., Man K.L., Perceived benefits, risks and trust on Online Shopping Festival, Commun. 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Manag, 34, pp. 6-24, (2006); Boven L.V., Gilovich T., To do or to have?, That is the question. J. Personal. Soc. Psychol, 85, pp. 1193-1202, (2003)","B. Liu; School of Economics and Management, Shanghai Maritime University, Shanghai, 201306, China; email: liubin@shmtu.edu.cn",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85058043126"]
["Shanthi R.; Rajagopalan S.P.","Shanthi, R. (57205319139); Rajagopalan, S.P. (7103019562)","57205319139; 7103019562","A personalized hybrid recommendation procedure for internet shopping support",2018.0,"International Journal of Advanced Computer Science and Applications",9.0,12.0,null,363.0,372.0,9.0,2.0,"10.14569/IJACSA.2018.091252","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85059505655&doi=10.14569%2fIJACSA.2018.091252&partnerID=40&md5=31ac2657ef3387b87c8405e7c9a5435f","Sathyabama Institute of Science and Technology, Jeppiaar Nagar, Rajiv Gandhi Salai, Chennai, 600119, India; GKM College of Engineering and Technology, Chennai, 600063, India","Shanthi R., Sathyabama Institute of Science and Technology, Jeppiaar Nagar, Rajiv Gandhi Salai, Chennai, 600119, India; Rajagopalan S.P., GKM College of Engineering and Technology, Chennai, 600063, India","Lately, recommender systems (RS) have offered a remarkable breakthrough to users. It lessens the user time cost thereby delivering faster and better results. After purchasing a product there are recommendations according to the different comments provided by users. Within a short span of product utilization and quality, the users receive a product recommendation. But this doesn't work out good so as to make it much better;feedbacks, commands and reviews are fetched on the basis of in-depth commands, globally like and normal keys. Recommendation systems are crucially important for the delivery of personalized product to users. With personalized recommendation to product, users can enjoy a variety of targeted recommendations such as online product; the current paper suggests hybrid recommendation system (HRS) that makes use of rating and review to recommend any product to user. The main objective of this paper is to personalize recommendation of product that have become extremely effective revenue drivers for online shopping business. Despite the great benefits, deploying personalized recommendation services typically requires the collection of users' personal data for processing and analytics, which undesirably makes users. To implement product recommendations following are incorporated that is retrieving personal data, Logical Language based Rule Generation (LLRG), ranking and Hybrid recommendation system. The stages in the suggested recommendation system include, Data Gathering, preprocessing, filtering and Ranking. The Ranking algorithm ranks the products in relation to the sales count. The top list displays the product having greatest count number. In the LLRG strategy, the logic rule generation methodology retrieves useful and mandatory data from reviews, commands, products original state and thereafter comes the recommendation. The HRS enforces two techniques, namely, location based and the other being heterogeneous domain based. Also the recommendations presented to the user are in context to the user's activities, choices and conduct that are in accord with user's personal likings and aids in decision making. When comparing the outcome, it is clear that the suggested method is superior than the traditional with regard to clarity, effective recommendation and coverage rate. It's evaluated that Hybrid Recommendation System yields in greater results compared with rest of the existing recommendation techniques. We, also identity to some future research directions. © 2018 International Journal of Advanced Computer Science and Applications.","E-commerce; Hybrid approach; Online shopping market; Products; Ranking; Recommendation system; Web mining; Web search",{"$nulls":7},"Ricci F., Rokach L., Shapira B., \"Introduction to recommender systems handbook\", (2011); Jannach D., Zanker M., Felfernig A., Friedrich G., \"Recommender systems: an introduction\", (2010); Ekstrand M.D., Riedl J.T., Konstan J.A., Collaborative filtering recommender systems, Foundations and Trends in Human-Computer Interaction, 4, 2, pp. 81-173, (2011); Jannach D., Friedrich G., Tutorial: recommender systems, In Proceedings of the International Joint Conference on Artificial Intelligence, (2011); Yazdanfar N., Thomo A., Link recommender: Collaborative-Filtering for recommending URLS to Twitter users, Procedia Computer Science, 19, pp. 412-419, (2013); Xia Z., Xu S., Liu N., Zhao Z., Hot News Recommendation System from Heterogeneous Websites Based on Bayesian Model, Hindawi Publishing Corporation Scientific World Journal, 2014; Cai Y., Fung Leung H., Li Q., Min H., Tang J., Li J., Typicality-based collaborative filtering recommendation, IEEE Trans. Knowl. Data Eng, 26, 3, pp. 766-779, (2014); Aguilar J., Valdiviezo-Diaz P., Riofrio G., \" A general framework for intelligent recommender Systems\", 13, pp. 147-160, (2017); Ayub M., Cian A., Caliusco M., Reynares E., Developing an ontology-based team recommender system using EDON method: an experience report, SADIO: EJIOR, 13, pp. 1-13, (2014); Dhanda M., Verma V.,  Recommender System for Academic Literature with Incremental Dataset, Twelfth International Multi-Conference on Information Processing, (2016); Wan Y., Qigang G., An Ensemble Sentiment Classification System of Twitter Data for Airline Services Analysis, 2015 IEEE 15th International Conference on Data Mining Workshops; Ibrahim M.E.-H., El-Bakry H.M., Saleh A.A., Classification of Breast Cancer Using Softcomputing Techniques, International Journal of Electronics and Information Engineering, 4, 1, pp. 45-54, (2016); Kumar A., A Study on Cancer Perpetuation Using the Classification Algorithms, International Journal of Recent Research in Mathematics Computer Science and Information Technology, 2, 1, pp. 96-99; Leopord H., Wilson K.C., Kimani S., A Survey and Analysis on Classification and Regression Data Mining Techniques for Diseases Outbreak Prediction in Datasets, The International Journal Of Engineering And Science (IJES), 5, 9, pp. 01-11, (2016); Geetha G., Safa M., Fancy C., Saranya D., A Hybrid Approach using Collaborative filtering and Content based Filtering for Recommender System, National Conference on Mathematical Techniques and its Applications (NCMTA 18); Kumar M., Yadav D.K., Singh A., Gupta V.K., A Movie Recommender System: MOVREC, International Journal of Computer Applications, 124, 3, (2015); de Campos L.M., Fernandez-Luna J.M., Huete J.F., Rueda-Morales M.A., Combining content-based and collaborative recommendations: A hybrid approach based on Bayesian networks, International Journal of Approximate Reasoning, (2010); Virk H.K., Singh M., Analysis and Design of Hybrid Online Movie Recommender System, International Journal of Innovations in Engineering and Technology (IJIET), 5, 2, (2015); Gupta U., Patil D.N., Recommender System Based on Hierarchical Clustering Algorithm Chameleon, 2015 IEEE International Advance Computing Conference (IACC); Kuzelewska U., Clustering Algorithms in Hybrid Recommender System on MovieLens Data, Studies in Logic, Grammar and Rhetoric, (2014); Chiru C.-G., Dinu V.-N., Preda C., Macri M., Movie Recommender System Using the User's Psychological Profile, IEEE International Conference on ICCP, (2015); Megha K., Devaki M.P., Web Application for student trading using Data Mining Techniques, International Journal of Scientific Development and Research (IJSDR), 2018, IJSDR, 3, 5; Li H., Xu J., Semantic Matching in Search. Foundations and Trends, Information Retrieval, 7, 5, pp. 343-469, (2014); Pang L., Lan Y., Guo J., Xu J., Xu J., Cheng X., DeepRank: A NewDeep Architecture for Relevance Ranking in Information Retrieval, International Conference on Information and Knowledge Management (CIKM'17), (2017); He X., Liao L., Zhang H., Nie L., Hu X., Chua T.-S., Neural Collaborative Filtering, International Conference on World Wide Web (WWW '17), pp. 173-182, (2017); Ojha D., Pandey P., Optimizing Association Rule using Genetic Algorithm and Data Sampling Approach, International Journal of Computer Applications, 179, 11, (2018); Quadrana M., Cremonesi P., Jannach D., Sequence-Aware Recommender Systems, ACM Computing, (2018); Guo Y., Yin C., Li M., Ren X., Liu P., \"Mobile e-Commerce Recommendation System Based on Multi-Source Information Fusion for Sustainable e-Business\", 10, (2018)",null,null,"Science and Information Organization",{"$nulls":5},"2158107X",null,null,null,"English","Intl. J. Adv.  Comput. Sci. Appl.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85059505655"]
["Li M.; Lin P.; Xu G.; Huang G.Q.","Li, Ming (57196402801); Lin, Peng (56422951700); Xu, Gangyan (55361785800); Huang, George Q. (7403425048)","57196402801; 56422951700; 55361785800; 7403425048","Cloud-based ubiquitous object sharing platform for heterogeneous logistics system integration",2018.0,"Advanced Engineering Informatics",38.0,null,null,343.0,356.0,13.0,21.0,"10.1016/j.aei.2018.08.010","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85051778355&doi=10.1016%2fj.aei.2018.08.010&partnerID=40&md5=bd66b1483a406527e5fd7eba169e4f9d","HKU-ZIRI Laboratory for Physical Internet, Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong; School of Architecture, Harbin Institute of Technology, Shenzhen, China; School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore","Li M., HKU-ZIRI Laboratory for Physical Internet, Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong; Lin P., HKU-ZIRI Laboratory for Physical Internet, Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong; Xu G., School of Architecture, Harbin Institute of Technology, Shenzhen, China, School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore; Huang G.Q., HKU-ZIRI Laboratory for Physical Internet, Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong","The intelligence of infrastructure gradually becomes the straw for logistics enterprises to make data-based or date-driven optimization. The integration of heterogeneous logistics systems with existing enterprise information systems is one of the most critical steps to achieve the intelligent infrastructure. Unfortunately, the integration is always a time-consuming process with heavy investment, which suppresses the longings of enterprises, especially for small and medium enterprises (SMEs). Aiming at simplifying the system integration, this paper proposed a cloud-based ubiquitous object sharing platform (CUOSP) to share the integration across SMEs based on the concept of sharing economy. CUOSP acts as a middleware system to make heterogeneous logistics systems universal plug-and-play (UPnP) for enterprise information systems. A kernel-based agent (KBA) is designed as the sharing entity of physical systems. It maintains the features of physical systems and is scalable for different application scenarios. A series of cloud gateway services are emerged not only to provide the basic running and sharing environment, but also to remedy KBA's weaknesses in computing capacity. A prototype system is developed and implemented based on the framework of CUOSP and a laboratory case according to the consolidation scenario in E-commerce logistics is demonstrated. Comparison experiments are also conducted to explore the real-time and multitasking capacity of KBAs with different kernel characteristics and different computing resources. © 2018","Computing gateway; Heterogeneous system integration; Intelligent infrastructure; Kernel-based agent","Computer circuits; Economics; Information systems; Information use; Investments; Middleware; Multitasking; Application scenario; Enterprise information system; Heterogeneous systems; Intelligent infrastructures; Logistics enterprise; Small and medium enterprise; System integration; Universal plug and play; Logistics",{"$nulls":4},"Hangzhou Municipal and Lin’an City Governments","This research is supported by the HKSAR ITC/LSCM R&D Center through the Innovation and Technology Support Program (Project Reference: ITP/079/16LP ). Acknowledgements also given to Zhejiang Provincial, Hangzhou Municipal and Lin’an City Governments for partial financial supports.","Qiu X., Luo H., Xu G., Zhong R., Huang G.Q., Physical assets and service sharing for IoT-enabled Supply Hub in Industrial Park (SHIP), Int. J. Prod. Econ., 159, pp. 4-15, (2015); Da Xu L., He W., Li S., Internet of things in industries: a survey, IEEE Trans. Ind. Inf., 10, pp. 2233-2243, (2014); Xu G., Li M., Luo L., Chen C.-H., Huang G.Q., Cloud-based fleet management for prefabrication transportation, Enterp. Inf. Syst., pp. 1-20, (2018); Pang L.Y., Zhong R.Y., Fang J., Huang G.Q., Data-source interoperability service for heterogeneous information integration in ubiquitous enterprises, Adv. Eng. Inf., 29, pp. 549-561, (2015); Vetter J.S., Glassbrook R., Dongarra J., Schwan K., Loftis B., McNally S., Meredith J., Rogers J., Roth P., Spafford K., Keeneland: bringing heterogeneous GPU computing to the computational science community, Comput. Sci. Eng., 13, pp. 90-95, (2011); Grace P., Blair G.S., Samuel S., A reflective framework for discovery and interaction in heterogeneous mobile environments, ACM SIGMOBILE Mob. Comput. Commun. Rev., 9, pp. 2-14, (2005); Crago S., Dunn K., Eads P., Hochstein L., Kang D.-I., Kang M., Modium D., Singh K., Suh J., Walters J.P., Heterogeneous cloud computing, 2011 IEEE Int. Conf. on Clust. Comput. (CLUSTER), pp. 378-385, (2011); Xu G., Huang G.Q., Fang J., Cloud asset for urban flood control, Adv. Eng. Inf., 29, pp. 355-365, (2015); Fang J., Qu T., Li Z., Xu G., Huang G.Q., Agent-based Gateway Operating System for RFID-enabled ubiquitous manufacturing enterprise, Robot. Comput. Integr. Manuf., 29, pp. 222-231, (2013); Kyriazis G., Heterogeneous system architecture: A technical review, AMD Fusion Dev. Summit., (2012); Ubal R., Jang B., Mistry P., Schaa D., Kaeli D., Multi2Sim: a simulation framework for CPU-GPU computing, 2012 21st Int. Conf. on Parallel Archit. Compil. Tech. (PACT), pp. 335-344, (2012); Power J., Hestness J., Orr M.S., Hill M.D., Wood D.A., gem5-gpu: a heterogeneous cpu-gpu simulator, IEEE Comput. Archit. Lett., 14, pp. 34-36, (2015); Gelado I., Stone J.E., Cabezas J., Patel S., Navarro N., Hwu W.W., An asymmetric distributed shared memory model for heterogeneous parallel systems, ACM SIGARCH Comput. Archit. News, pp. 347-358, (2010); Agarwal N., Nellans D., Stephenson M., O'Connor M., Keckler S.W., Page placement strategies for GPUs within heterogeneous memory systems, ACM SIGPLAN Not., 50, pp. 607-618, (2015); Elshafei M., Modern Distributed Control Systems: A Comprehensive Coverage of Dcs Technologies and Standards, (2016); Shen W., Hao Q., Yoon H.J., Norrie D.H., Applications of agent-based systems in intelligent manufacturing: an updated review, Adv. Eng. Inf., 20, pp. 415-431, (2006); Papakostas N., Mourtzis D., Bechrakis K., Chryssolouris G., Doukas D., Doyle R., A flexible agent based framework for manufacturing decision-making, Proc. Conf. Flex. Autom. Intell. Manuf. (FAIM99), Tilburg, Netherlands, pp. 23-25, (1999); Lu T.-P., Yih Y., An agent-based production control framework for multiple-line collaborative manufacturing, Int. J. Prod. Res., 39, pp. 2155-2176, (2001); Jia H.Z., Ong S.K., Fuh J.Y.H., Zhang Y.F., Nee A.Y.C., An adaptive upgradable agent-based system for collaborative product design and manufacture, Robot. Comput. Integr. Manuf., 20, pp. 79-90, (2004); Chan F.T.S., Swarnkar R., Tiwari M.K., Infrastructure for co-ordination of multi-agents in a network–based manufacturing system, Int. J. Adv. Manuf. Technol., 31, pp. 1028-1033, (2007); Wang C., Ghenniwa H., Shen W., Real time distributed shop floor scheduling using an agent-based service-oriented architecture, Int. J. Prod. Res., 46, pp. 2433-2452, (2008); Zhang Y., Qu T., Ho O.K., Huang G.Q., Agent-based smart gateway for RFID-enabled real-time wireless manufacturing, Int. J. Prod. Res., 49, pp. 1337-1352, (2011); Zhang Y., Huang G.Q., Qu T., Ho O., Sun S., Agent-based smart objects management system for real-time ubiquitous manufacturing, Robot. Comput. Integr. Manuf., 27, pp. 538-549, (2011); Zhang Y., Huang G.Q., Sun S., Yang T., Multi-agent based real-time production scheduling method for radio frequency identification enabled ubiquitous shopfloor environment, Comput. Ind. Eng., 76, pp. 89-97, (2014); Lou P., Liu Q., Zhou Z., Wang H., Sun S.X., Multi-agent-based proactive–reactive scheduling for a job shop, Int. J. Adv. Manuf. Technol., 59, pp. 311-324, (2012); Erol R., Sahin C., Baykasoglu A., Kaplanoglu V., A multi-agent based approach to dynamic scheduling of machines and automated guided vehicles in manufacturing systems, Appl. Soft Comput., 12, pp. 1720-1732, (2012); Lim M.K., Tan K., Leung S.C.H., Using a multi-agent system to optimise resource utilisation in multi-site manufacturing facilities, Int. J. Prod. Res., 51, pp. 2620-2638, (2013); Barbosa J., Leitao P., Adam E., Trentesaux D., Dynamic self-organization in holonic multi-agent manufacturing systems: The ADACOR evolution, Comput. Ind., 66, pp. 99-111, (2015); Coad P., Yourdon E., (1991); Rumbaugh J., Blaha M., Premerlani W., Eddy F., Lorensen W.E., Object-oriented Modeling and Design, (1991); Russell S., Norvig P., Artificial Intelligence: A Modern Approach, (2016); Locati F.A., OpenStack Cloud Security, (2015); Grieves M., Vickers J., Digital twin: mitigating unpredictable, undesirable emergent behavior in complex systems, Transdiscipl. Perspect. Complex Syst., pp. 85-113, (2017)","G.Q. Huang; HKU-ZIRI Lab for Physical Internet, Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong; email: gqhuang@hku.hk",null,"Elsevier Ltd",{"$nulls":5},1.4740346E7,null,null,null,"English","Adv. Eng. Inf.","Article","Final",null,"Scopus","2-s2.0-85051778355"]
["Nelson D.","Nelson, Darryl (57203261344)",5.7203261344E10,"Distributed Computing: The Unsung Hero of the Modern Global Economy",2018.0,"IEEE Potentials",37.0,4.0,8419151.0,12.0,16.0,4.0,0.0,"10.1109/MPOT.2018.2824378","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85051090430&doi=10.1109%2fMPOT.2018.2824378&partnerID=40&md5=401686d5c4ca29fc2c7a268c7b437419","Raytheon Engineering, United States","Nelson D., Raytheon Engineering, United States","Invisible to all but small groups of elite practitioners, distributed computing (DC) is a foundational technology that undergirds much of the modern global economy. Hosted by massive data centers humming with thousands (or hundreds of thousands) of servers, DC facilitates e-commerce, social media, logistics, government, finance, gaming, and other mass-digital phenomena for hundreds of millions of people every day. Without it, many of today?s online services would either not exist or be greatly diminished in usefulness. © 1988-2012 IEEE.",null,"Education; Electrical engineering; Global economies; Massive data; On-line service; Social media; Distributed computer systems",{"$nulls":7},"D. Nelson; Raytheon Engineering, United States; email: darryl.nelson@raytheon.com",null,"Institute of Electrical and Electronics Engineers Inc.",{"$nulls":5},2786648.0,null,"IEPTD",null,"English","IEEE Potentials","Article","Final",null,"Scopus","2-s2.0-85051090430"]
["Le N.T.T.; Nguyen Q.N.; Phien N.N.; Duong-Trung N.; Huynh T.T.; Nguyen T.P.; Son H.X.","Le, Ngoc Tien Thanh (57220612632); Nguyen, Quoc Nghiep (57208798749); Phien, Nguyen Ngoc (58179158800); Duong-Trung, Nghia (57191328820); Huynh, Thai Tam (57209173318); Nguyen, The Phuc (57208750325); Son, Ha Xuan (57193341872)","57220612632; 57208798749; 58179158800; 57191328820; 57209173318; 57208750325; 57193341872","Assuring non-fraudulent transactions in cash on delivery by introducing double smart contracts",2019.0,"International Journal of Advanced Computer Science and Applications",10.0,5.0,null,677.0,684.0,7.0,41.0,"10.14569/ijacsa.2019.0100584","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85066747237&doi=10.14569%2fijacsa.2019.0100584&partnerID=40&md5=bc9bf3e9a3f4fbe39686ef2c49aa6b85","CanTho University of Technology, Can Tho city, Viet Nam; Center for Applied Information Technology, Ton Duc Thang University, Ho Chi Minh City, Viet Nam; Faculty of Information Technology, Ton Duc Thang University, Ho Chi Minh City, Viet Nam; FPT University, Can Tho City, Viet Nam; Transaction Technologies PTE. LTD., Singapore; University of Trento, Trento, Italy","Le N.T.T., CanTho University of Technology, Can Tho city, Viet Nam; Nguyen Q.N., CanTho University of Technology, Can Tho city, Viet Nam; Phien N.N., Center for Applied Information Technology, Ton Duc Thang University, Ho Chi Minh City, Viet Nam, Faculty of Information Technology, Ton Duc Thang University, Ho Chi Minh City, Viet Nam; Duong-Trung N., CanTho University of Technology, Can Tho city, Viet Nam, FPT University, Can Tho City, Viet Nam; Huynh T.T., Transaction Technologies PTE. LTD., Singapore; Nguyen T.P., University of Trento, Trento, Italy; Son H.X., CanTho University of Technology, Can Tho city, Viet Nam, FPT University, Can Tho City, Viet Nam","The adoption of decentralized cryptocurrency platforms is growing fast, thanks to the implementation of Blockchain technology and smart contracts. It encourages the novel frameworks in a wide range of applications including finance and payment methods such as cash on delivery. However, a large number of smart contracts developed for cash on delivery suffer from fraudulent transactions which enable malicious participants to break the signed contracts without sufficient penalties. A shipper will involve in the system and place a mortgage to ensure reliability. A buyer also pledges an amount of money when making the order. Our process not only ensures the interests of a seller but also prevents a fraud shipper. The penalties will be made in two scenarios: (i) the buyer refuses to receive the commodities without any reliable reasons; and (ii) the shipper attempts to make any modification on the delivered goods during transportation. To help developers create more secure and reliable cash on delivery system, we introduce double smart contracts, a framework rooted in Blockchain technology and Ethereum, to tackle those mentioned problems. We also contribute our solution as an open source software that developers can easily add to their implementation to enhance functionality. © 2018 The Science and Information (SAI) Organization Limited.","Blockchain; Cash on delivery (COD); E-commerce; Ethereum; Online payment; Smart contract","Ethereum; Open source software; Open systems; Ships; Block-chain; Cash on delivery; Cash-on-delivery; Decentralised; Delivery systems; Fraudulent transactions; Malicious participant; On-line payment; Payment methods; Smart contract",{"$nulls":6},"Timmers P., Electronic commerce, (1999); Halaweh M., Cash on delivery (cod) as an alternative payment method for e-commerce transactions: Analysis and implications, International Journal of Sociotechnology and Knowledge Development (IJSKD), 10, 4, pp. 1-12, (2018); Intention to adopt the cash on delivery (cod) payment model for e-commerce transactions: An empirical study, , IFIP International Conference on Computer Information Systems and Industrial Management. Springer, pp. 628-637, (2017); Tandon U., Kiran R., Study on drivers of online shopping and significance of cash-on-delivery mode of payment on behavioural intention, International Journal of Electronic Business, 14, 3, pp. 212-237, (2018); Alie J.D., Vliek P.E., International cash-on-delivery system and method; Asgaonkar A., Krishnamachari B., Solving the buyer and seller's dilemma: A dual-deposit escrow smart contract for provably cheat-proof delivery and payment for a digital good without a trusted mediator, (2018); \"Two party contracts, \", (2015); Antonopoulos A.M., Wood G., Mastering ethereum: building smart contracts and dapps, (2018); \"Ethereum project.\"; Son H.X., Nguyen M.H., Phien N.N., Le H.T., Nguyen Q.N., Dinh V.D., Tru P.T., Nguyen P., Towards a mechanism for protecting seller's interest of cash on delivery by using smart contract in hyperledger, , International Journal of Advanced Computer Science and Applications, 10, 4, (2019); \"Hyperledger fabric.\"; Hileman G., Rauchs M., Global cryptocurrency benchmarking study, , Cambridge Centre for Alternative Finance, 33, (2017); Hasan H.R., Salah K., Blockchain-based solution for proof of delivery of physical assets, , International Conference on Blockchain. Springer, pp. 139-152, (2018); Kosba A., Miller A., Shi E., Wen Z., Papamanthou C., Hawk: The blockchain model of cryptography and privacy-preserving smart contracts, , 2016 IEEE symposium on security and privacy (SP). IEEE, pp. 839-858, (2016); Nakamoto S., Et al., Bitcoin: A peer-to-peer electronic cash system, (2008); Lewenberg Y., Sompolinsky Y., Zohar A., Inclusive block chain protocols, , International Conference on Financial Cryptography and Data Security, pp. 528-547, (2015); Wood G., Et al., Ethereum: A secure decentralised generalised transaction ledger, , Ethereum project yellow paper, 151, pp. 1-32, (2014); Hamid T., \"Cash on delivery the biggest obstacle to e-commerce in uae and region, \", (2014); Idelberger F., Governatori G., Riveret R., Sartor G., Evaluation of logic-based smart contracts for blockchain systems, , International Symposium on Rules and Rule Markup Languages for the Semantic Web, pp. 167-183, (2016); Alharby M., van Moorsel A., Blockchain-based smart contracts: A systematic mapping study, (2017); He D., Habermeier K.F., Leckow R.B., Haksar V., Almeida Y., Kashima M., Kyriakos-Saad N., Oura H., Sedik T.S., Stetsenko N., Et al., Virtual currencies and beyond: initial considerations, (2016); \"Solidity.\"; Team E.U.C., \"Ethereum unit converter.\"; Delmolino K., Arnett M., Kosba A., Miller A., Shi E., Step by step towards creating a safe smart contract: Lessons and insights from a cryptocurrency lab, , International Conference on Financial Cryptography and Data Security, pp. 79-94, (2016); \"ethereum/remix-ide, \", (2019)",null,null,"Science and Information Organization",{"$nulls":5},"2158107X",null,null,null,"English","Intl. J. Adv.  Comput. Sci. Appl.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85066747237"]
["Perboli G.; Rosano M.; Saint-Guillain M.; Rizzo P.","Perboli, Guido (16176293900); Rosano, Mariangela (57190031827); Saint-Guillain, Michael (56652137700); Rizzo, Pietro (57201667184)","16176293900; 57190031827; 56652137700; 57201667184","Simulation-optimisation framework for City Logistics: An application on multimodal last-mile delivery",2018.0,"IET Intelligent Transport Systems",12.0,4.0,null,262.0,269.0,7.0,71.0,"10.1049/iet-its.2017.0357","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85045643672&doi=10.1049%2fiet-its.2017.0357&partnerID=40&md5=7d801293b2e74e499c51c1825d68c307","ICT for City Logistics and Enterprises Center, Politecnico di Torino, Turin, Italy; CIRRELT, Montréal, Canada; Institute of Information and Communication Technologies, Electronics and Applied Mathematics, Université catholique de Louvain, Louvain-la-Neuve, Belgium; Institut National des Sciences Appliquées de Lyon, France","Perboli G., ICT for City Logistics and Enterprises Center, Politecnico di Torino, Turin, Italy, CIRRELT, Montréal, Canada; Rosano M., ICT for City Logistics and Enterprises Center, Politecnico di Torino, Turin, Italy; Saint-Guillain M., Institute of Information and Communication Technologies, Electronics and Applied Mathematics, Université catholique de Louvain, Louvain-la-Neuve, Belgium, Institut National des Sciences Appliquées de Lyon, France; Rizzo P., ICT for City Logistics and Enterprises Center, Politecnico di Torino, Turin, Italy","City Logistics has attracted considerable interest from the operations research and logistics communities during past decades. It resulted in a broad variety of promising approaches from different fields of combinatorial optimisation. However, research on urban freight transportation is currently slowing down due to two different lacks, limiting the exploratory capacity and compromise the technology transfer to the industry. First, the majority of the instances in the literature are based on the generalisation of classical instances, often not created for urban applications, or on artificial data, i.e. data not coming from any historical or empirical datasets. Thus, the validation of models and methods becomes more difficult, being the results not directly compared with real or realistic settings. Second, even when some data sources become available, there is no standard way to mixing data gathered from different sources and, from them, generate new instances for urban applications. This study aims to overcome these issues, proposing a simulation-optimisation framework for building instances and assess operational settings. To illustrate the usefulness of the framework, the authors conduct a case study, in order to evaluate the impact of multimodal delivery options to face the demand from e-commerce, in an urban context as Turin (Italy). © The Institution of Engineering and Technology 2018",null,"Combinatorial optimization; Freight transportation; Operations research; Technology transfer; Urban planning; Artificial data; City logistics; Data-sources; Generalisation; Multi-modal; Simulation optimisation; Urban applications; Urban context; Urban transportation",{"$nulls":6},"Taniguchi E., Thompson R., Modeling city logistics, Trans. Res. Rec., 1790, 1, pp. 45-51, (2002); Kim G., Ong Y.S., Heng C.K., Et al., City vehicle routing problem (city VRP): A review, IEEE Trans. Intell. Transp. Syst., 16, 4, pp. 1654-1666, (2015); Vigo D., A heuristic algorithm for the asymmetric capacitated vehicle routing problem, Eur. J. Oper. Res., 89, 1, pp. 108-126, (1996); Kong L., Yang Y., Lu J.-L., Et al., Evaluation of urban vehicle routing algorithms, Int. J. Digit. Content Technol. Appl., 6, 23, pp. 790-799, (2012); Perboli G., Tadei R., Vigo D., The two-echelon capacitated vehicle routing problem: Models and math-based heuristics, Transp. Sci., 45, 3, pp. 364-380, (2011); Escuin D., Millan C., Larrode E., Modelization of time-dependent urban freight problems by using a multiple number of distribution centers, Netw. Spat. Econ., 12, 3, pp. 321-336, (2012); Minis I., Mamasis K., Zeimpekis V., Real-time management of vehicle breakdowns in urban freight distribution, J. Heuristics, 18, 3, pp. 375-400, (2012); Erdogan S., Miller-Hooks E., A green vehicle routing problem, Transp. Res. E, Logist. Transp. Rev., 48, 1, pp. 100-114, (2012); Bektas T., Laporte G., The pollution-routing problem, Transp. Res. B, Methodol., 45, 8, pp. 1232-1250, (2011); Maggioni F., Perboli G., Tadei R., The multi-path traveling salesman problem with stochastic travel costs: Building realistic instances for city logistics applications, Transp. Res. Procedia, 3, pp. 528-536, (2014); Tadei R., Perboli G., Perfetti F., The multi-path traveling salesman problem with stochastic travel costs, EURO J. Transp. Logist., 6, pp. 3-23, (2017); Van Woensel T., DATA2MOVE Initiative, (2017); Crainic T., Perboli G., Rosano M., Simulation of intermodal freight transportation systems: A taxonomy, Eur. J. Oper. Res., (2017); Hart W.E., Watson J.-P., Woodruff D.L., Pyomo: Modeling and solving mathematical programs in python, Math. Program. Comput., 3, 3, pp. 219-260, (2011); Watson J.-P., Woodruff D.L., Hart W.E., PySP: Modeling and solving stochastic programs in python, Math. Program. Comput., 4, 2, pp. 109-149, (2012); Saint-Guillain M., Deville Y., Solnon C., A multistage stochastic programming approach to the dynamic and stochastic VRPTW, 12th Int. Conf. Integration of AI and OR Techniques in Constraint Programming (CPAIOR 2015), pp. 357-374, (2015); Cardenas I., Beckers J., Vanelslander T., Et al., Spatial characteristics of failed and successful e-commerce deliveries in Belgian cities, Information Systems, Logistic and Supply Chain Conf, (2016); E-Commerce and Delivery, (2013); Project Web Site, (2015); Intra-Community Cross-Border Parcel Delivery London, (2011); Taniguchi E., Kakimoto Y., Modelling Effects of E-Commerce on Urban Freight Transport, 10, pp. 135-146, (2004); Perboli G., Rosano M., Gobbato L., Parcel delivery in urban areas: Do we need new business and operational models for mixing traditional and low-emission logistics?, Technical Report, CIRRELT 2017-02 Montréal (Canada), (2017)","G. Perboli; ICT for City Logistics and Enterprises Center, Politecnico di Torino, Turin, Italy; email: guido.perboli@polito.it",null,"Institution of Engineering and Technology",{"$nulls":5},"1751956X",null,null,null,"English","IET Intel. Transport Syst.","Article","Final",null,"Scopus","2-s2.0-85045643672"]
["Prilianti E.; Hikmat M.T.","Prilianti, Eliza (57215914474); Hikmat, Muhammad Tresnadi (57222316948)","57215914474; 57222316948","Proposed corporate performance management using Integrated Performance Management System (IPMS) at PT Pos Indonesia (Persero)",2018.0,"International Journal of Engineering and Technology(UAE)",7.0,3.0,null,71.0,83.0,12.0,1.0,"10.14419/ijet.v7i3.25.17472","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85082374463&doi=10.14419%2fijet.v7i3.25.17472&partnerID=40&md5=cf78e7a6068d74e553349edd82d38af6","School of Business and Management, Bandung Institute of Technology, Indonesia","Prilianti E., School of Business and Management, Bandung Institute of Technology, Indonesia; Hikmat M.T., School of Business and Management, Bandung Institute of Technology, Indonesia","The big market shifting in postal industry begun since a physical letter was being substituted by digitalization of technology, yet it brings new business opportunity in the e-commerce industry. The e-commerce industry in Indonesia is expected to grow by approximately 18% annually in the next five years. It triggers an increasing demand for parcel delivery services. However, the performance of PT Pos Indonesia (Persero) as a State Owned Enterprise engages in postal industry shows the declining trend. The volume of parcel delivery declined during the last three years. The company has not been able to manage its performance due to the incompatibility of performance management system. The purpose of this research is assisting the company to design new performance management system to improve its performance. The Integrated Performance Management System (IPMS) framework is selected because it is able to overcome the issues in the company. There are five stages of IPMS framework includes foundation, background and information, design process, implementation, and refreshment. It consist of three perspectives includes organizational output, internal process, and resources availability. This research proposed the performance management system for Pos Indonesia and produces 20 key performance indicators (KPI) that derived from company's vision, mission, and strategy. © 2018 Authors.","Corporate Performance; E-Commerce Industry; Integrated Performance Management System; Key Performance Indicators (KPI); Postal Industry",{"$nulls":7},"Aguinis H., Performance Management, (2013); Afiani W., Madiawati P.N., Influence of Brand Image and Service Quality on Customer Loyalti on Users of Shipping Service PT. Pos Indonesia (Persero) Bandung Head Office, E-Proceeding of Management, 2, 3, pp. 3721-3725, (2015); Anna A., Strategic Management Tools and Techniques and Organizational Performance: Findings from the Czech Republic, Journal of Competitiveness, 7, 3, pp. 19-36, (2015); (2016); Bititci U.S., Carrie A.S., McDevitt, Integrated Performance Measurment Systems: a Development Guide, International of Journal of Operations & Production Management, 17, 5 L, pp. 522-534, (1997); Bititci U.S., Mendibil K., Nudurupati, Garengo, Turner T., Dynamics of Performance Measurement and Organizational Culture, International Journal of Operations & Production Management, 26, 12, pp. 1325-1350, (2006); Dalimunthe A., PT Pos Indonesia Lakukan Brand Rejuvenation Untuk Rebut Pasar Paket, (2017); Das K., Gryseels M., Sudhir P., Tan K.T., Unlocking Indonesia's Digital Opportunity, pp. 7-23, (2016); Hartung A., Why the Postal Service Is Going Out of Business; Hitt M.A., Ireland R.D., Hoskisson R., Strategic Management: Competitiveness and Globalization, pp. 35-121, (2009); Hikmat M.T., Primiana I., Wibisono D., Analyzing Mainstreams In Current Performance Management Studies And Its Relationship With HR And Other Practices: A Literature Review, Sains Humanika (UTM, Malaysia), 8, 1-2, pp. 41-50, (2016); (2015); Isoraite M., Theoretical Aspects of Benchmarking Theory, Viesoji Politika IR Administravimas, 9, pp. 21-26, (2004); Jacobs F.R., Chase R.B., Operation and Supply Chain Management, (2011); Kaplan R.S., Norton D.P., Alignment: Using the Balanced Scorecard to Create Corporate Synergies, (2008); Niven P.R., Balanced Scorecard Step By Step-Maximizing Performance and Maintaining Results, (2006); Pearce J.A., The Company Mission as a Strategic Tool, Sloan Managemet Review, 23, 3, (1982); Razdan R., Das M., Sohoni A., The Evolving Indonesian Consumer, (2013); Soo K.G., Building Your Company with Strong Vision Platform, Advanced Technologies & Aerospace Database, 17, 7, pp. 3021-3026, (2017); Smither J.W., London M., Performance Management: Putting Research into Action, (2009); Wibisono D., How To Create A World Class Company: Panduan Bagi Direktur dan Manajer, (2016)","E. Prilianti; School of Business and Management, Bandung Institute of Technology, Indonesia; email: elizaprilianti@gmail.com",null,"Science Publishing Corporation Inc",{"$nulls":5},"2227524X",null,null,null,"English","Int. J. Eng. Technol.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85082374463"]
["Doktoralina C.M.; Apollo","Doktoralina, Caturida Meiwanto (57195426184); Apollo (57215673452)","57195426184; 57215673452","The contribution of strategic management accounting in supply chain outcomes and logistic firm profitability",2019.0,"Uncertain Supply Chain Management",7.0,2.0,null,145.0,156.0,11.0,24.0,"10.5267/j.uscm.2018.10.010","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85056318143&doi=10.5267%2fj.uscm.2018.10.010&partnerID=40&md5=36173844d232d3828238bad2d0f82297","Faculty of Economics and Business, Universitas Mercu Buana, Jakarta, Indonesia","Doktoralina C.M., Faculty of Economics and Business, Universitas Mercu Buana, Jakarta, Indonesia; Apollo, Faculty of Economics and Business, Universitas Mercu Buana, Jakarta, Indonesia","In the current decade, with an increase in e-commerce, the logistics activities have grown rapidly. However, the logistics industry of the Malaysian country is declining, as the ranking of this industry has shown downfall continuously during the past few years. The decrease in logistics industry performance reduces the contribution in a Gross Domestic Product (GDP). Therefore, to address this issue, the primary objective of this study was to examine the role of strategic management accounting practices to enhance the profitability of the Malaysian logistics firms. Questionnaires were adopted to collect the primary data and they were distributed among the employees of the logistics companies. All the questionnaires were distributed through area cluster sampling technique. Partial least square (PLS) structural equation modelling (SEM) was used to analyze the collected data. The results indicate that strategic management accounting practices had a significant positive relationship with supply chain outcomes and supply chain outcomes had a significant positive relationship with the profitability of the logistics companies. Finally, this is one of the pioneer studies, which examined the impact of strategic management accounting practices on the outcome of the logistics firms. © 2019 by the authors; licensee Growing Science, Canada.","Government policy; Information; Logistic; Strategic management accounting; Supply chain, Profitability; Technology",{"$nulls":7},"Almaryani M.A.H., Sadik H.H., Strategic management accounting techniques in Romanian companies: Some survey evidence, Procedia Economics and Finance, 3, pp. 387-396, (2012); Angbre F.A., The Role of Agricultural Education in Ensuring National Security in Nigeria, Agriculture and Food Sciences Research, 3, 1, pp. 25-28, (2016); Modern Business Management (Theory and Practice), (2000); Aziz M.A., Strategic Role of Strategic Management Accounting Towards Enhancing Smes Performance in Iraq, (2012); Carter C.R., Ellram L.M., Reverse logistics: A review of the literature and framework for future investigation, Journal of Business Logistics, 19, 1, (1998); Castorena O.H., Enriquez L.A., Adame M.G., The Influence of Information Technology and Communication Supply Chain Management Performance for Greater SME Manufacturing in Aguascalientes, International Journal of Business, Economics and Management, 1, 12, pp. 382-396, (2014); Chowdhury T.S., Habibullah M., Nahar N., Risk and Return Analysis of Closed-End Mutual Fund in Bangladesh, Journal of Accounting, Business and Finance Research, 3, 2, pp. 83-92, (2018); Cinquini L., Tenucci A., Is the Adoption of Strategic Management Accounting Techniques Really “strategy-driven”?, (2007); Dim N.U., Ezeabasili A.C.C., Strategic supply chain framework as an effective approach to procurement of public construction projects in Nigeria, International Journal of Management and Sustainability, 4, 7, pp. 163-172, (2015); Dixon R., Strategic management accounting, Omega, 21, 6, pp. 605-618, (1993); Hair J.F., Lukas B., 2, (2014); Hair J.F., Black W.C., Babin B.J., Anderson R.E., Tatham R., Multivariate Data Analysis, (2010); Hameed W.-U., Mohammad B., Hishamshahar K., Binti H., Aljumah A.I., Azizan S., The Effect of Integration between Audit and Leadership on Supply Chain Performance: Evidence from UK Based Supply Chain Companies, 7, (2018); Hameed W.-U., Nadeem S., Azeem M., Aljumah A.I., Adeyemi R.A., Determinants of E-Logistic Customer Satisfaction: A Mediating Role of Information and Communication Technology (ICT), International Journal of Supply Chain Management, 7, 1, pp. 105-111, (2018); Henseler J., Ringle C.M., Sinkovics R.R., The use of partial least squares path modeling in international marketing, New Challenges to International Marketing, pp. 277-319, (2009); Hoque Z., Strategic Management Accounting, (2002); Imran M., Hamid S., Aziz A., Hameed W., The contributing factors towards e-logistic customer satisfaction: A mediating role of information Technology, Uncertain Supply Chain Management, 7, 1, pp. 63-72, (2019); Intezar M.T., Marketing Communications in 21st Century: Trends & Strategies, Humanities and Social Sciences Letters, 5, 2, pp. 36-42, (2017); Jaya A.K., Verawaty V., The Accessibility Determinants of Internet Financial Reporting of Manufacture Company Listed in Indonesia Stock Exchange, Asian Economic and Financial Review, 5, 2, (2015); Juras A., Strategic Management Accounting-What Is the Current State of the Concept?, Economy Transdisciplinarity Cognition, 17, 2, (2014); Karim N.H., Rahman N.S.F.A., Shah S.F.S.S.J., Empirical evidence on failure factors of warehouse productivity in Malaysian logistic service sector, The Asian Journal of Shipping and Logistics, 34, 2, pp. 151-160, (2018); Kimengsi J.N., Gwan S.A., Reflections on decentralization, community empowerment and sustainable development in Cameroon, International Journal of Emerging Trends in Social Sciences, 1, 2, pp. 53-60, (2017); Krejcie R.V., Morgan D.W., Determining sample size for research activities, Educational and Psychological Measurement, 30, 3, pp. 607-610, (1970); Linton J.D., Klassen R., Jayaraman V., Sustainable supply chains: An introduction, Journal of Operations Management, 25, 6, pp. 1075-1082, (2007); Lord B.R., Strategic management accounting: The emperor's new clothes?, Management Accounting Research, 7, 3, pp. 347-366, (1996); Maqbool N., Hameed W., Habib M., Impact of political influences on stock returns, International Journal of Multidisciplinary Scientific Publication (IJMSP), 1, 1, (2018); Martin J., Management Accounting: Concepts, Techniques & Controversial Issues, (2016); Nazal A.I., Financial tables reports gaps in Jordanian Islamic banks, The Economics and Finance Letters, 4, 2, pp. 9-15, (2017); Nze I.C., Ogwude I.C., Nnadi K.U., Ibe C.C., Modelling the relationship between demand for river port services and vessel supply costs: Empirical evidence from Nigeria, Global Journal of Social Sciences Studies, 2, 3, pp. 144-149, (2016); Oboh C.S., Ajibolade S.O., Strategic management accounting and decision making: A survey of the Nigerian Banks, Future Business Journal, 3, 2, pp. 119-137, (2017); Okoye E., Akenbor C., Strategic Management Accounting Practices in A Competitive Environment: A Theoretical Exposition, (2008); Porter M.E., van der Linde C., Toward a new conception of the environment-competitiveness relationship, Journal of Economic Perspectives, 9, 4, pp. 97-118, (1995); Purnama C., Improved performance through empowerment of small industry, Journal of Social Economics Research, 1, 4, pp. 72-86, (2014); Rekarti E., Doktoralina C.M., Improving business performance: A proposed model for SMEs, European Research Studies Journal, 20, 3A, pp. 613-623, (2017); Roslender R., Hart S.J., In search of strategic management accounting: Theoretical and field study perspectives, Management Accounting Research, 14, 3, pp. 255-279, (2003); Roslender R., Hart S.J., Strategic Management Accounting: Lots in a Name?, (2010); Shehab M., Factors Influencing Accounting Information System Performance among Small and Medium Enterprises (Smes) in Tripoli, (2008); Simons R., Strategic orientation and top management attention to control systems, Strategic Management Journal, 12, 1, pp. 49-62, (1991); Soleman A.M., Factors Influencing the Adoption of Web-Based Information Systems: A Case Study at LADA in Langkawi, Kedah, (2008); Solomon C., Mohamad M.N., Jamaluddin R., Development in corporate sustainability: The green supply chain management perspective and challenges, Journal of Asian Scientific Research, 4, 10, (2014); Suryanto T., Quality Audit in Banking Industry, Prosiding International Conference on Information Technology and Business (ICITB), pp. 271-279, (2015); Suryanto T., Purnamasari F., Kurniawan M., Tax Revenue and Disparity: How to Improvement Income Inequality in Islamic Perspective, Asian Journal of Social Sciences and Management Studies, 5, 2, pp. 65-71, (2018); Tanoos J.J., East Asian Trade Cooperation versus US and EU Protectionist Trends and their Association to Chinese Steel Exports, Asian Journal of Economics and Empirical Research, 4, 1, pp. 1-7, (2017); Taqi M., Ajmal M., Ansari M.S., Financial efficiency of India tourism development corporation (ITDC) Limited: An empirical study, Journal of Tourism Management Research, 5, 1, pp. 14-22, (2018); Tillmann K., Strategic Management Accounting and Sense Making: A Grounded Theory Study, (2002); Ul-Hameed W., Mohammad H., Shahar H., Microfinance institute’s non-financial services and women-empowerment: The role of vulnerability, Management Science Letters, 8, 10, pp. 1103-1116, (2018); Wang Y.B., Lu J.R., A supply-lock competitive market for investable products, Asian Development Policy Review, 4, 4, pp. 127-133, (2016); Ward K., Strategic Management Accounting: Routledge, (2012); Wireko-Manu F.D., Amamoo C., Comparative studies on proximate and some mineral composition of selected local rice varieties and imported rice brands in Ghana, Agriculture and Food Sciences Research, 4, 1, pp. 1-7, (2017)","C.M. Doktoralina; Faculty of Economics and Business, Universitas Mercu Buana, Jakarta, Indonesia; email: caturida_meiwanto_drm@mercubuana.ac.id",null,"Growing Science",{"$nulls":5},2.2916822E7,null,null,null,"English","Uncertain Supply Chain Manag.","Article","Final","All Open Access; Bronze Open Access; Green Open Access","Scopus","2-s2.0-85056318143"]
["Sujata J.; Menachem D.; Rageshree M.","Sujata, Joshi (56554112100); Menachem, Domb (57193775015); Rageshree, Modi (57203620736)","56554112100; 57193775015; 57203620736","Mitigating risk of revenue leakages on the customer and vendor side in ecommerce sector",2018.0,"International Journal of Engineering and Technology(UAE)",7.0,3.0,null,161.0,166.0,5.0,0.0,"10.14419/ijet.v7i3.29.18549","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85082350076&doi=10.14419%2fijet.v7i3.29.18549&partnerID=40&md5=a227b02a7d82cee1b71e4dd0a946e67c","Institute of Telecom Management, constituent of Symbiosis International, Deemed University, Pune, India; Computer Science Ashkelon Academy, Ben, Zvi, Askelon, Israel","Sujata J., Institute of Telecom Management, constituent of Symbiosis International, Deemed University, Pune, India; Menachem D., Computer Science Ashkelon Academy, Ben, Zvi, Askelon, Israel; Rageshree M., Institute of Telecom Management, constituent of Symbiosis International, Deemed University, Pune, India","E-commerce is one of the rapidly booming sectors in India today, thanks to the rising internet user base and faster mobile penetration. The E-commerce industry is a complex ecosystem as it involves huge transaction volumes, complex procurement and logistics systems and reliance on new technologies for customer access and payment transactions. This complexity has given rise to frauds and revenue leakages, which is impacting the revenue for the ecommerce companies. Hence the major concern facing the Ecommerce sector today is how to mitigate the revenue loss. Very few studies have been done in academic literature in this area hence the objective of this study is to understand the sources of revenue leakage in the ecommerce sector and propose solutions for mitigating these revenue leakages. The study focusses on [2] major areas of revenue leakage viz. Customer side, Vendor side. The proposed revenue assurance model will be helpful to Ecommerce companies for detecting the sources of revenue leakages in the abovementioned areas and plugging the same thereby reducing losses. The study can also be helpful for consulting companies who are in the business of revenue assurance and fraud management for the ecommerce companies. © 2018 Joshi Sujata et. al.","Customer side; Ecommerce; Revenue assurance; Revenue leakages; Vendor side",{"$nulls":7},"Duh R.-R., Jamal K., Sunder S., Control and assurance in ecommerce: privacy, integrity, and security at eBay, Taiwan Accounting Review, 3, 1, pp. 1-27, (2002); \"Crusading against fraud in the e-commerce industry: Fraud Investigation & Dispute Services, India\", (2016); Deloitte W., \"Beyond the growth story mitigating fraud risks in the e-commerce industry\", (2016); \"Sharpening revenue assurance capabilities in the digital and converged space\", (2015); \"Fulfilled! India's e-commerce retail logistics growth story\", (2015); \"Trends in e-commerce & digital fraud: Mitigating the risks\", (2017); Leyde J., \"The Guide to E-Commerce Fraud. 2Checkout.com, Inc. [US\"], (2014); \"Revenue Assurance\", (2017); \"Revenue Assurance\", (2017); Pantigoso P., Bellina J.C., \"Revenue Assurance and Improvement: a tactical and transformational methodology for business improvement\", (2016); Baaman K., Data Quality Aspects of Revenue Assurance, In: INTERNATIONAL CONFERENCE ON INFORMATION QUALITY, (2007); Sjolin M., Damjanovic I., Burman J., A structured approach to revenue assurance, Ericsson Business Report, 2010; \"E-Commerce\", (2017); Bishnoi A., \"E-commerce Fraud in India-An Insight\"; \"GLOBAL FRAUD\", (2017); McCarthy D., Fader P., \"Customer-Based Corporate Valuation for Publicly Traded Non-Contractual Firms\"; Morrell A., \"A new study shows Wayfair is losing money on every new customer-and that's terrible news for the stock (W)\", (2017); Loyalty P.; Vishal K., \"Why the unit economics of Flipkart (and competitors) will not work for another decade\", (2017); \"What is Retargeting and how does it Work? \"; Geetha M., Bharadhwaj S., \"Impulse Buying Behavior in India-An Overview\", (2016); James C., \"4 Checkout Conversion Killers That Drive Your Buyers Away\", (2015); \"Online shopping cart abandonment rate worldwide from 2006 to 2017\", (2018); \"Reduce shopping cart abandonments at every step of the customer journey\", (2018); \"Maintaining Productive Partnerships with Coupon Affiliates and Other Sites\", (2017); \"6 Ways to Tackle the Promo Code Problem\", (2018); Khalid S., \"E-commerce Product Return Rate-Statistics and Trends\", (2018); Prahlad T., Kirtika D., \"Fulfilled! India's e-commerce retail logistics growth story\", (2016); Varsha B., \"Fashion ecommerce firms like Flipkart, Myntra uncover fake product returns\"; Janakiraman N., Ordonez L., Effect of effort and deadlines on consumer product returns, Journal of Consumer Psychology, 22, 2, pp. 260-271, (2012); \"Flipkart 'duped' of Rs1.05 crore, 152 smartphones; two youths arrested\", (2016); Tanveer M., \"Shopify Returns: 7 Best Practices to Reduce Your Return Rate\"; A discussion based on \"Customers replacing the product with different product & returning back\"; \"How Tech Companies Are Backing the Future of Retail through AR, AI and Drones\", (2018); \"A discussion based on \"Buyer unavailable at the time of delivery and product is returned\"; Ashna A., \"E-commerce: Not at home, order will still be delivered\", (2018); \"Preferred digital payment methods in India in 2015 and 2020\", (2018); Shukairy A., \"E-commerce Fraud and Chargebacks-Statistics and Trends\", (2018); \"3D Secure explained\", (2016); Sonya M., \"Amazon Scammers Are Using This Trick to Make Millions\", (2017); Sukanya M., \"Ecommerce Firms Flipkart and Amazon Deny Allegations Concerning Fake Products\"; \"How to prevent inventory loss or theft in warehouses\", (2015); Uhlmann S., \"Master Thesis on Reducing Counterfeit Products with Blockchains\", (2017); Steven H., \"Drop Shipping 101-Avoid the Common Mistakes and Dropship Scams-As seen on GetThatWholesale.com and eZines.com\", (2014); \"Vendor cheats Flipkart of Rs 1.5 lakh\"; \"Beyond the growth story mitigating fraud risks in the e-commerce industry\", (2016); Bailay R., Sikarwar D., \"Top ecommerce firms Flipkart, Amazon, Snapdeal shun UP, Uttarakhand post tax hassles\", (2015)","J. Sujata; Institute of Telecom Management, constituent of Symbiosis International, Deemed University, Pune, India; email: sjoshi@sitm.ac.in",null,"Science Publishing Corporation Inc",{"$nulls":5},"2227524X",null,null,null,"English","Int. J. Eng. Technol.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85082350076"]
["Karunanayaka K.; Johari N.; Hariri S.; Camelia H.; Bielawski K.S.; Cheok A.D.","Karunanayaka, Kasun (49961467800); Johari, Nurafiqah (57190405883); Hariri, Surina (57192819128); Camelia, Hanis (57200566004); Bielawski, Kevin Stanley (57200565652); Cheok, Adrian David (7003447496)","49961467800; 57190405883; 57192819128; 57200566004; 57200565652; 7003447496","New thermal taste actuation technology for future multisensory virtual reality and internet",2018.0,"IEEE Transactions on Visualization and Computer Graphics",24.0,4.0,null,1496.0,1505.0,9.0,29.0,"10.1109/TVCG.2018.2794073","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85041668000&doi=10.1109%2fTVCG.2018.2794073&partnerID=40&md5=b38e9ea17694c8124c86032082e9b735","Imagineering Institute, Malaysia","Karunanayaka K., Imagineering Institute, Malaysia; Johari N., Imagineering Institute, Malaysia; Hariri S., Imagineering Institute, Malaysia; Camelia H., Imagineering Institute, Malaysia; Bielawski K.S., Imagineering Institute, Malaysia; Cheok A.D., Imagineering Institute, Malaysia","Today's virtual reality (VR) applications such as gaming, multisensory entertainment, remote dining, and online shopping are mainly based on audio, visual, and touch interactions between humans and virtual worlds. Integrating the sense of taste into VR is difficult since humans are dependent on chemical-based taste delivery systems. This paper presents the 'Thermal Taste Machine', a new digital taste actuation technology that can effectively produce and modify thermal taste sensations on the tongue. It modifies the temperature of the surface of the tongue within a short period of time (from 25°C to 40 °C while heating, and from 25°C to 10 °C while cooling). We tested this device on human subjects and described the experience of thermal taste using 20 known (taste and non-Taste) sensations. Our results suggested that rapidly heating the tongue produces sweetness, fatty/oiliness, electric taste, warmness, and reduces the sensibility for metallic taste. Similarly, cooling the tongue produced mint taste, pleasantness, and coldness. By conducting another user study on the perceived sweetness of sucrose solutions after the thermal stimulation, we found that heating the tongue significantly enhances the intensity of sweetness for both thermal tasters and non-Thermal tasters. Also, we found that faster temperature rises on the tongue produce more intense sweet sensations for thermal tasters. This technology will be useful in two ways: First, it can produce taste sensations without using chemicals for the individuals who are sensitive to thermal taste. Second, the temperature rise of the device can be used as a way to enhance the intensity of sweetness. We believe that this technology can be used to digitally produce and enhance taste sensations in future virtual reality applications. The key novelties of this paper are as follows: 1. Development of a thermal taste actuation technology for stimulating the human taste receptors, 2. Characterization of the thermal taste produced by the device using taste-related sensations and non-Taste related sensations, 3. Research on enhancing the intensity for sucrose solutions using thermal stimulation, 4. Research on how different speeds of heating affect the intensity of sweetness produced by thermal stimulation. © 2018 IEEE Computer Society. All rights reserved.","Characterization of Thermal Taste; Digitizing Taste; Multisensory VR; Thermal Taste; TRPM5","Adult; Equipment Design; Female; Humans; Internet; Male; Signal Processing, Computer-Assisted; Taste; Temperature; Tongue; User-Computer Interface; Virtual Reality; Young Adult; Chemicals; Cooling; Cooling systems; Heating; Silver; Sugar (sucrose); Temperature sensors; Digitizing Taste; Heating system; Multisensory; Thermal Taste; Tongue; TRPM5; adult; computer interface; equipment design; female; human; Internet; male; physiology; signal processing; taste; temperature; tongue; virtual reality; young adult; Virtual reality",{"$nulls":6},"Auvray M., Spence C., The multisensory perception of flavor, Consciousness and Cognition, 17, 3, pp. 1016-1031, (2008); Bajec M.R., Pickering G.J., Thermal taste, prop responsiveness, and perception of oral sensations, Physiology & Behavior, 95, 4, pp. 581-590, (2008); Chandrashekar J., Yarmolinsky D., Buchholtz L.V., Oka Y., Sly W., Ryba N.J., Zuker C.S., The taste of carbonation, Science, 326, 5951, pp. 443-445, (2009); Cheok A.D., Karunanayaka K., Samshir N.A., Johari N., Initial basic concept of thermal sweet taste interface, Proceedings of the 12th International Conference on Advances in Computer Entertainment Technology, (2015); Cruz A., Green B.G., Thermal stimulation of taste, Nature, 403, 6772, (2000); Erceg-Hurn D.M., Mirosevich V.M., Modern robust statistical methods: An easy way to maximize the accuracy and power of your research, American Psychologist, 63, 7, (2008); Finger T.E., Evolution of taste and solitary chemoreceptor cell systems, Brain, Behavior and Evolution, 50, 4, pp. 234-243, (1997); Gilbertson T.A., Fontenot D.T., Liu L., Zhang H., Monroe W.T., Fatty acid modulation of k+ channels in taste receptor cells: Gustatory cues for dietary fat, American Journal of Physiology-Cell Physiology, 272, 4, pp. C1203-C1210, (1997); Green B.G., George P., Thermal tastepredicts higher responsiveness to chemical taste and flavor, Chemical Senses, 29, 7, pp. 617-628, (2004); Green B.G., Nachtigal D., Temperature affects human sweet taste via at least two mechanisms, Chemical Senses, 40, 6, pp. 391-399, (2015); Kortum P., HCI beyond the GUI: Design for Haptic, Speech, Olfactory, and other Nontraditional Interfaces, (2008); Leon N.D., Specific Heat and Heat Capacity, 2001; Liman E., Trpm5 and taste transduction, Transient Receptor Potential (TRP) Channels, pp. 287-298, (2007); Liu D., Liman E.R., Intracellular ca2+ and the phospholipid pip2 regulate the taste transduction ion channel trpm5, Proceedings of the National Academy of Sciences, 100, 25, pp. 15160-15165, (2003); Liu P., Shah B.P., Croasdell S., Gilbertson T.A., Transient receptor potential channel type m5 is essential for fat taste, Journal of Neuroscience, 31, 23, pp. 8634-8642, (2011); Maynes-Aminzade D., Edible bits: Seamless interfaces between people, data and food, Conference on Human Factors in Computing Systems (CHI'05)-ExtendedAbstracts, pp. 2207-2210, (2005); Narumi T., Nishizaka S., Kajinami T., Tanikawa T., Hirose M., Meta cookie+: An illusion-based gustatory display, Virtual and Mixed Reality- New Trends, pp. 260-269, (2011); Nelson G., Chandrashekar J., Hoon M.A., Feng L., Et al., An amino-Acid taste receptor, Nature, 416, 6877, (2002); Noguchi K., Gel Y.R., Brunner E., Konietschke F., Nparld: An R Software Package for the Nonparametric Analysis of Longitudinal Data in Factorial Experiments, (2012); O'Dwyer A., Handbook of PI and PID controller tuning rules, World Scientific, (2009); Ranasinghe N., Do E.Y.-L., Virtual sweet: Simulating sweet sensation using thermal stimulation on the tip of the tongue, Proceedings of the 29th Annual Symposium on User Interface Software and Technology, pp. 127-128, (2016); Ranasinghe N., Karunanayaka K., Cheok A.D., Fernando O.N.N., Nii H., Gopalakrishnakone P., Digital taste and smell communication, Proceedings of the 6th International Conference on Body Area Networks, pp. 78-84, (2011); Ranasinghe R.A.N., Digitally Stimulating the Sensation of Taste through Electrical and Thermal Stimulation, (2012); Spencer B., Specific Heat of Metals, 2001; Suzuki C., Narumi T., Tanikawa T., Hirose M., Affecting tumbler: Affecting our flavor perception with thermal feedback, Proceedings of the 11th Conference on Advances in Computer Entertainment Technology, (2014); Talavera K., Ninomiya Y., Winkel C., Voets T., Nilius B., Influence of temperature on taste perception, Cellular and Molecular Life Sciences, 64, 4, (2007); Talavera K., Yasumatsu K., Voets T., Droogmans G., Et al., Heat activation of trpm5 underlies thermal sensitivity of sweet taste, Nature, 438, 7070, (2005); R: A Language and Environment for Statistical Computing, (2014); Tutton M., Designers developing virtual-reality'cocoon, CNN, (2008); Yang Q., Hollowood T., Hort J., Phenotypic variation in oronasal perception and the relative effects of prop and thermal taster status, Food Quality and Preference, 38, pp. 83-91, (2014); Yeomans M.R., Tepper B.J., Rietzschel J., Prescott J., Human hedonic responses to sweetness: Role of taste genetics and anatomy, Physiology & Behavior, 91, 2, pp. 264-273, (2007); Zhang Y., Hoon M.A., Chandrashekar J., Mueller K.L., Cook B., Wu D., Zuker C.S., Ryba N.J., Coding of sweet, bitter, and umami tastes: Different receptor cells sharing similar signaling pathways, Cell, 112, 3, pp. 293-301, (2003)",null,null,"IEEE Computer Society",{"$nulls":5},1.0772626E7,null,"ITVGE",2.9543167E7,"English","IEEE Trans Visual Comput Graphics","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85041668000"]
["Azadeh A.; Salehi V.; Salehi R.; Hassani S.M.","Azadeh, A. (56268189600); Salehi, V. (36133595000); Salehi, R. (57191622894); Hassani, S.M. (57195518989)","56268189600; 36133595000; 57191622894; 57195518989","Performance optimization of an online retailer by a unique online resilience engineering algorithm",2018.0,"Enterprise Information Systems",12.0,3.0,null,319.0,340.0,21.0,10.0,"10.1080/17517575.2017.1365173","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85028546881&doi=10.1080%2f17517575.2017.1365173&partnerID=40&md5=6a45bfa56610e5fd08de0ff91dbe383a","School of Industrial and Systems Engineering, Center of Excellence for Intelligent-Based Experimental Mechanic, and Department of Engineering Optimization Research, College of Engineering, University of Tehran, Tehran, Iran","Azadeh A., School of Industrial and Systems Engineering, Center of Excellence for Intelligent-Based Experimental Mechanic, and Department of Engineering Optimization Research, College of Engineering, University of Tehran, Tehran, Iran; Salehi V., School of Industrial and Systems Engineering, Center of Excellence for Intelligent-Based Experimental Mechanic, and Department of Engineering Optimization Research, College of Engineering, University of Tehran, Tehran, Iran; Salehi R., School of Industrial and Systems Engineering, Center of Excellence for Intelligent-Based Experimental Mechanic, and Department of Engineering Optimization Research, College of Engineering, University of Tehran, Tehran, Iran; Hassani S.M., School of Industrial and Systems Engineering, Center of Excellence for Intelligent-Based Experimental Mechanic, and Department of Engineering Optimization Research, College of Engineering, University of Tehran, Tehran, Iran","Online shopping has become more attractive and competitive in electronic markets. Resilience engineering (RE) can help such systems divert to the normal state in case of encountering unexpected events. This study presents a unique online resilience engineering (ORE) approach for online shopping systems and customer service performance. Moreover, this study presents a new ORE algorithm for the performance optimisation of an actual online shopping system. The data are collected by standard questionnaires from both expert employees and customers. The problem is then formulated mathematically using data envelopment analysis (DEA). The results show that the design process which is based on ORE is more efficient than the conventional design approach. Moreover, on-time delivery is the most important factor from the personnel’s perspective. In addition, according to customers’ view, trust, security and good quality assurance are the most effective factors during transactions. This is the first study that introduces ORE for electronic markets. Second, it investigates impact of RE on online shopping through DEA and statistical methods. Third, a practical approach is employed in this study and it may be used for similar online shops. Fourth, the results are verified and validated through complete sensitivity analysis. © 2017 Informa UK Limited, trading as Taylor & Francis Group.","customer satisfaction; data envelopment analysis (DEA); online resilience engineering (ORE); Online shopping; retailing; statistical methods","Commerce; Customer satisfaction; Data envelopment analysis; Electronic commerce; Optimization; Ore analysis; Ores; Quality assurance; Sales; Sensitivity analysis; Statistical methods; Surveys; Conventional design; On-line Shopping systems; Online shopping; Performance optimisation; Performance optimizations; Resilience engineerings; retailing; Unexpected events; Online systems",{"$nulls":6},"Abdallah S., Jaleel B., Website Appeal: Development of an Assessment Tool and Evaluation Framework of E-Marketing, Journal of Theoretical and Applied Electronic Commerce Research, 10, 3, pp. 45-62, (2015); Ahn T., Ryu S., Han I., The Impact of Web Quality and Playfulness on User Acceptance of Online Retailing, Information & Management, 44, 3, pp. 263-275, (2007); The Top 500 Sites on the Web, (2016); Azadeh A., Saberi M., Jiryaei Z., An Intelligent Decision Support System for Forecasting and Optimization of Complex Personnel Attributes in a Large Bank, Expert Systems with Applications, 39, 16, pp. 12358-12370, (2012); Azadeh A., Salehi V., Ashjari B., Saberi M., Performance Evaluation of Integrated Resilience Engineering Factors by Data Envelopment Analysis: The Case of a Petrochemical Plant, Process Safety and Environmental Protection, 92, 3, pp. 231-241, (2014); Azemi F., Baholli F., Guberaj E., E-Tailing in Kosovo: The Effect of Trust, Satisfaction and Service Quality in Achieving Consumer E-Loyalty, Academic Journal of Interdisciplinary Studies, 4, 3 S1, pp. 502-508, (2015); Bao J., The Impacts of E-Service Quality on Customers’ Repurchase Intention in Platform Online Retailing: An Empirical Investigation, WHICEB Proceedings. Paper 15, (2015); Beck R., Wigand R.T., Konig V., The Diffusion and Efficient Use of Electronic Commerce among Small and Medium-Sized Enterprises: An International Three-Industry Survey, Electronic Markets, 15, 1, pp. 38-52, (2005); Bitter S., Grabner-Krauter S., Consequences of Customer Engagement Behavior: When Negative Facebook Posts Have Positive Effects, Electronic Markets, 26, 3, pp. 1-13, (2016); Collier J.E., A Conceptual Framework For Measuring E-service Quality., pp. 158-162, (2015); Cooper W.W., Muench M.L., Virtual Organizations: Practice and the Literature, Journal of Organizational Computing and Electronic Commerce, 10, 3, pp. 189-208, (2000); Edwards S.M., Lee J.K., Ferle C.L., Does Place Matter When Shopping Online? Perceptions of Similarity and Familiarity as Indicators of Psychological Distance, Journal of Interactive Advertising, 10, 1, pp. 35-50, (2009); Erol O., Sauser B.J., Mansouri M., A Framework for Investigation into Extended Enterprise Resilience, Enterprise Information Systems, 4, 2, pp. 111-136, (2010); Fathian M., Sadjadi S.J., Sajadi S., Optimal Pricing Model for Electronic Products, Computers & Industrial Engineering, 56, 1, pp. 255-259, (2009); Giovanis A.N., Gaining Customer Loyalty in the E-Tailing Marketplace: The Role of E-Service Quality, E-Satisfaction and E-Trust, International Journal of Technology Marketing, 9, 3, pp. 288-304, (2014); Hart C., Laing A., The Consumer Journey through the High Street in the Digital Area, Evolving High Streets: Resilience and Reinvention–Perspectives from Social Science, pp. 36-39, (2014); Jap S.D., Manolis C., Weitz B.A., Relationship Quality and Buyer-Seller Interactions in Channels of Distribution, Journal of Business Research, 46, 3, pp. 303-313, (1999); Jiang P., Rosenbloom B., Customer Intention to Return Online: Price Perception, Attribute-Level Performance, and Satisfaction Unfolding over Time, European Journal of Marketing, 39, 1-2, pp. 150-174, (2005); Jouini M., Rabai L.B.A., Aissa A.B., Classification of Security Threats in Information Systems, Procedia Computer Science, 32, pp. 489-496, (2014); Keating B.W., Quazi A.M., Kriz A., Financial Risk and Its Impact on New Purchasing Behavior in the Online Retail Setting, Electronic Markets, 19, 4, pp. 237-250, (2009); Liao T.H., Keng C.J., Online Shopping Delivery Delay: Finding a Psychological Recovery Strategy by Online Consumer Experiences, Computers in Human Behavior, 29, 4, pp. 1849-1861, (2013); Osborne M., Consumer Learning, Switching Costs, and Heterogeneity: A Structural Examination, Quantitative Marketing and Economics, 9, 1, pp. 25-70, (2011); Otto B., Lee Y.W., Caballero I., Information and Data Quality in Business Networking: A Key Concept for Enterprises in Its Early Stages of Development, Electronic Markets, 21, 2, pp. 83-97, (2011); Palmatier R.W., Dant R.P., Grewal D., Evans K.R., Factors Influencing the Effectiveness of Relationship Marketing: A Meta-Analysis, Journal of Marketing, 70, pp. 136-153, (2006); Pettit T.J., Ensuring Supply Chain Resilience: Development and Implementation of an Assessment Tool, Journal of Business Logistics, 34, 1, pp. 46-76, (2013); Piercy N., Online Service Quality: Content and Process of Analysis, Journal of Marketing Management, 30, 7-8, pp. 747-785, (2014); Raji R., Wang J., Nayak A., Tiwari W.K., Han B., Liu C., Zhang W.J., Measuring the Resilience of Supply Chain Systems Using a Survival Model, IEEE Systems Journal, 9, 2, pp. 377-381, (2014); Rhee H.-S., Riggins F.J., Kim C., The Impact of Product Type and Perceived Characteristics of the Web on Multifaceted Online Shopping Behavior, Journal of Organizational Computing and Electronic Commerce, 19, pp. 1-29, (2009); Riquelme I.P., Roman S., Is the Influence of Privacy and Security on Online Trust the Same for All Type of Consumers?, Electronic Markets, 24, 2, pp. 135-149, (2014); Serrano Cinca C., Mar Molinero C., Chaparro Garcia F., Behind DEA Efficiency in Financial Institutions, Account Finance, 40, pp. 30-45, (2002); Shih H.P., Jin B.H., Driving Goal-Directed and Experiential Online Shopping, Journal of Organizational Computing and Electronic Commerce, 21, pp. 136-157, (2011); Singleton A.D., Dolega L., Riddlesden D., Longley P.A., Measuring the Spatial Vulnerability of Retail Centres to Online Consumption through a Framework of E-Resilience, Geoforum, 69, pp. 5-18, (2016); Stamenkov G., Dika Z., Bank Employees’ Internal and External Perspectives on E-Service Quality, Satisfaction and Loyalty, Electronic Markets, 26, 3, pp. 291-309, (2016); Subramanian N., Gunasekaran A., Yu J., Cheng J., Ning K., Customer Satisfaction and Competitiveness in the Chinese E-Retailing: Structural Equation Modeling (SEM) Approach to Identify the Role of Quality Factors, Expert Systems with Applications, 41, 1, pp. 69-80, (2014); Tabaei Z., Fathian M., Developing Online Customer Satisfaction Strategic Maps: With Iranian Online Retailing Case Studies, International Journal of Electronic Customer Relationship Management, 6, 1, pp. 87-112, (2012); Tamimi N., Sebastianelli R., The Relative Importance of E-Tailer Website Attributes on the Likelihood of Online Purchase, Internet Research, 25, 2, pp. 169-183, (2015); Verma V., Sharma D., Sheth J., Does Relationship Marketing Matter in Online Retailing? A Meta-Analytic Approach, Journal of the Academy of Marketing Science, 44, 2, pp. 206-217, (2016); Vos A., Marinagi C., Trivellas P., Eberhagen N., Skourlas C., Giannakopoulos G., Risk Reduction Strategies in Online Shopping: E-Trust Perspective, Procedia-Social and Behavioral Sciences, 147, pp. 418-423, (2014); Wang J.W., Gao F., Ip W.H., Measurement of Resilience and Its Application to Enterprise Information Systems, Enterprise Information Systems, 4, 2, pp. 215-223, (2010); Wang J.W., Wang H.F., Zhou Y.M., Wang Y., Zhang W.J., On an Integrated Approach to Resilient Transportation Systems in Emergency Situations, Natural Computing, pp. 1-9, (2017); Wang J.W., Muddada R.R., Wang H.F., Ding J.L., Lin Y., Zhang W.J., Towards a Resilient Holistic Supply Chain Network System: Concept, Review and Future Direction, IEEE Systems Journal, 10, 2, pp. 410-421, (2016); Wang J.W., Ip W.H., Muddada R.R., Huang J.L., Zhang W.J., On Petri Net Implementation of Proactive Resilient Holistic Supply Chain Networks, The International Journal of Advanced Manufacturing Technology, 69, 1-4, pp. 427-437, (2013); Wang L., Law R., Guillet B.D., Hung K., Fong D.K.C., Impact of Hotel Website Quality on Online Booking Intentions: E-Trust as a Mediator, International Journal of Hospitality Management, 47, pp. 108-115, (2015); Wang P., Bradlow E.T., George E.I., Meta-Analyses Using Information Reweighting: An Application to Online Advertising, Quantitative Marketing and Economics, 12, 2, pp. 209-233, (2014); Wrigley N., Lambiri D., High Street Performance and Evolution: A Brief Guide to the Evidence, (2014); Wu J., Wen N., Dou W., Chen J., Exploring the Effectiveness of Consumer Creativity in Online Marketing Communications, European Journal of Marketing, 49, 1-2, pp. 262-276, (2015); Wu L., The Antecedents of Customer Satisfaction and Its Link to Complaint Intentions in Online Shopping: An Integration of Justice, Technology, and Trust, International Journal of Information Management, 33, 1, pp. 166-176, (2013); Zhang W.J., Lin Y., On the Principle of Design of Resilient Systems–Application to Enterprise Information Systems, Enterprise Information Systems, 4, 2, pp. 99-110, (2010); Zhu J., Data Envelopment Analysis Vs, Principal Component Analysis: An Illustrative Study of Economic Performance of Chinese Cities. European Journal of Operational Research, 111, 1, pp. 50-61, (1998)","V. Salehi; School of Industrial and Systems Engineering, Center of Excellence for Intelligent-Based Experimental Mechanic, and Department of Engineering Optimization Research, College of Engineering, University of Tehran, Tehran, Iran; email: vahidsalehielmi@gmail.com",null,"Taylor and Francis Ltd.",{"$nulls":5},1.7517575E7,null,null,null,"English","Enterp. Inf. Syst.","Article","Final",null,"Scopus","2-s2.0-85028546881"]
["Wu Z.L.; Wang D.; Su Y.T.; Li H.M.","Wu, Z.L. (57211201091); Wang, D. (56918728500); Su, Y.T. (57211207498); Li, H.M. (57151536400)","57211201091; 56918728500; 57211207498; 57151536400","Intelligent mode of electronic commerce based on data mining technology",2018.0,"Latin American Applied Research",48.0,4.0,null,267.0,272.0,5.0,0.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85072976544&partnerID=40&md5=f9c832a3b8a8ad17135eafbafa5a6719","Shenzhen graduate school of Peking University, School of urban planning and design, Shenzhen, China; Harbin Institute of Technology (Shenzhen), School of economics and management, Shenzhen, China; Nanjing university of technology, School of mathematical sciences, Nanjing, China; Harbin Institute of Technology, School of economics and management, Harbin, China","Wu Z.L., Shenzhen graduate school of Peking University, School of urban planning and design, Shenzhen, China; Wang D., Harbin Institute of Technology (Shenzhen), School of economics and management, Shenzhen, China; Su Y.T., Nanjing university of technology, School of mathematical sciences, Nanjing, China; Li H.M., Harbin Institute of Technology, School of economics and management, Harbin, China","With the rapid development of Internet technology, the penetration rate of Internet in China has exceeded 50 %, and more and more Internet users have chosen to shop online. Based on the analysis of the current situation of e-commerce development, this paper analyzes the influencing factors affecting the reliability of e-commerce logistics from the aspects of information technology, facilities and equipment, personnel operation and external environment. Additionally, it constructs the E-commerce intelligent logistics reliability distribution model and simulates the example. The research results show that, when the maximum and minimum reliability and complexity are not considered, the priority of improving the important high unit has a great impact on the reliability of the whole system. An increase in unit reliability can lead to an increase in system reliability and an increase in cost. When the reliability is increased to a certain extent, the continued increase will greatly increase the cost, and the cost of increasing the system unit reliability is greatly increased. © 2003-2012 Latin American Applied Research Journal.","Bayesian network; Data mining technology; E-commerce; Intelligent mode",{"$nulls":7},"Billinton R., Billinton J., Distribution system reliability indices, IEEE Transactions on Power Delivery, 4, 1, pp. 561-568, (1989); Borchani H., Larranaga P., Gama J., Bielza C., Mining multi-dimensional concept-drifting data streams using Bayesian network classifiers, Intelligent Data Analysis, 20, 2, pp. 257-280, (2016); Chakraborty B., Sinha M., Student Evaluation Model using Bayesian Network in an intelligent E-learning system, IIOABJ, 7, 2, pp. 51-60, (2016); D'Addabbo A., Refice A., Pasquariello G., Lover-gine F.P., Capolongo D., Manfreda S., A bayesian network for flood detection combining SAR imagery and ancillary data, IEEE Transactions on Geosci-ence and Remote Sensing, 54, 6, pp. 3612-3625, (2016); Gorecki J., Hofert M., Holena A.M., An approach to structure determination and estimation of hierar-chical Archimedean Copulas and its application to Bayesian classification, Journal of Intelligent In-formation Systems, 46, 1, pp. 21-59, (2016); Jiang Z.F., The application of data mining technology based on Bayesian network structure, Journal of Computational Methods in Sciences Engineering, 17, 2, pp. 1-10, (2017); Liang X., Wang H., Guo J., Et al., Bayesian network-based fault diagnosis method for on-board equip-ment of train control system, Tiedao Xuebao Jour-nal of the China Railway Society, 39, 8, pp. 93-100, (2017); Liu M., Qu M., Zhao B., Research and citation analysis of data mining technology based on bayes algorithm, Mobile Networks and Applications, 22, 3, pp. 418-426, (2017); Mohammed M., Hafida B., A bayesian network approach to mine spatial data cube, Journal of The-oretical and Applied Information Technology, 96, 4, pp. 865-874, (2018); Nega A., Kumlachew A., Data mining based hy-brid intelligent system for medical application, In-ternational Journal of Information Engineering and Electronic Business, 9, 4, pp. 38-46, (2017); Nissan E., Digital technologies and artificial intelli-gence's present and foreseeable impact on lawyer-ing, judging, policing and law enforcement, Artifi-cial Intelligence and Society, 32, 3, pp. 441-464, (2017); Qin Y., Luo Y., Zhao Y., Zhang J., Research on relationship between tourism income and economic growth based on meta-analysis, Applied Mathemat-ics and Nonlinear Sciences, 3, 1, pp. 105-114, (2018); Tucker J., Young-Gonzaga S., Krause J., A pro-posed model for authenticating knowledge in online discussion forums, International Journal of Higher Education, 3, 2, pp. 106-119, (2014); Tucker S.N., Formulating construction cash flow curves using a reliability theory analogy, Construc-tion Management and Economics, 4, 3, pp. 179-188, (2007); Wu M.C., Kraft P., Epstein M.P., Taylor D.M., Chanock S.J., Hunter D.J., Lin X., Powerful SNP-Set Analysis for Case-Control Genome-wide Asso-ciation Studies, The American Journal of Human Genetics, 86, pp. 929-942, (2010); Xie T.H., Lin Y., Chi W., Yang Z.Y., Intelligent identification of fires in ship compartments using a Bayesian network, Journal of Marine Science Technology, 24, 4, pp. 842-850, (2016); Zheng M.K., Ming X.G., Zhang X.Y., Li G.M., MapReduce Based Parallel Bayesian Network for Manufacturing Quality Control, Chinese. Journal of Mechanical Engineering, 30, 5, pp. 1216-1226, (2017); Zhu Z., Peng B., Xiong C., Zhang L., Short-term traffic flow prediction with linear conditional Gauss-ian Bayesian network, J. Adv. Transport, 50, 6, pp. 1111-1123, (2016); Zou X., Tao F., Jiang P., Gu S., A new approach for data processing in supply chain network based on FPGA, The International Journal of Advanced Manufacturing Technology, 84, 1-4, pp. 249-260, (2016)","Z.L. Wu; Shenzhen graduate school of Peking University, School of urban planning and design, Shenzhen, China; email: nortonLydiajFa@yahoo.com",null,"Plapiqui",{"$nulls":5},3270793.0,null,null,null,"English","Lat. Am. Appl. Res.","Article","Final",null,"Scopus","2-s2.0-85072976544"]
["Hilmola O.-P.; Tolli A.","Hilmola, Olli-Pekka (8352506000); Tolli, Andres (23135902500)","8352506000; 23135902500","Evaluation of chinese E-commerce cost and lead time performance to Estonia",2018.0,"Quality Innovation Prosperity",22.0,1.0,null,14.0,26.0,12.0,1.0,"10.12776/QIP.V22I1.1035","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85045037196&doi=10.12776%2fQIP.V22I1.1035&partnerID=40&md5=bed1f0c3dc34450b9d01116fa9368cd4","Tallinn University of Technology, Estonian Maritime Academy, Kopli 101, Tallinn, 11712, Estonia; Lappeenranta University of Technology, Kouvola Unit, Prikaatintie 9, Kouvola, FIN-45100, Finland","Hilmola O.-P., Tallinn University of Technology, Estonian Maritime Academy, Kopli 101, Tallinn, 11712, Estonia, Lappeenranta University of Technology, Kouvola Unit, Prikaatintie 9, Kouvola, FIN-45100, Finland; Tolli A., Tallinn University of Technology, Estonian Maritime Academy, Kopli 101, Tallinn, 11712, Estonia","Purpose: Retail sales growth has been sluggish in the recent decade in North European countries. Number of factors have caused this, like problems in macro-economy, sanctions and the effect of ageing population. Also increasing amount of e-commerce from China has taken its share. Future development paths need to be researched further to identify the outlook of North European retail. Methodology/Approach: Four different imported items were examined, which were hypothetically planned to be brought on Estonian consumer markets from China. We take into account freight costs, custom duties, VAT and profit margin requirement. Also lead time performance is being examined. Findings: Analysis shows that company based imports is not that viable model as profit margin requirement as well as governmental costs (duty and VAT) take lion share from overall costs. Even if profit requirement of company importing the products would decrease, wage inflation in Asia and freight will probably lead to higher product prices. Therefore, e-commerce needs to enlarge to lower cost manufacturing locations and/or use more direct sales to consumers. Total lead time soughts new solutions too (e.g. railway connection to Europe). Research Limitation/implication: Examination is limited to small Estonian market, and their custom tariffs and VAT. Also logistics costs to Northern Europe are higher than to Central Europe. Originality/Value of paper: Research is one of the first based on the examination of products and overall costs. It adds value through understanding of import cost structures. Category: Research paper. © 2018 by the authors.","Business-to-business; Business-to-consumers; E-commerce; Lead time; Total costs; Transportation",{"$nulls":7},"Alibaba Logistics Buyer Portal to Select Transportation Mode, (2017); Alibaba Group Announces June Quarter 2017 Results, (2017); Bury R., Alibaba Targets Silk Road Train Route for European Push, (2017); Chakravarthy B., Yau D., Becoming global leaders: Innovation challenges for five large Chinese firms, Strategy & Leadership, [E-Journal], 45, 2, pp. 19-24, (2017); Chen L.Y., Alibaba’s Shopping Spree: How the Web giant’s Universe has Expanded, (2016); (2017); Doplbauer G., European Retail in 2015, (2015); Doplbauer G., (2016); Eisenhardt K.M., Graebner M.E., Theory building from cases: Opportunities and challenges, Academy of Management Journal, 50, 1, pp. 25-32, (2007); Ellram L.M., The use of case study method in logistics research, Journal of Business Logistics, 17, 2, pp. 93-138, (1996); (2012); Hanninen M., Smedlund A., Mitronen L., Digitalization in retailing: Multisided platforms as drivers of industry transformation, Baltic Journal of Management, (2017); Hille A., (2017); Kumar S., Samad Arbi A., Outsourcing strategies for apparel manufacture: A case study, Journal of Manufacturing Technology Management, [E-Journal], 19, 1, pp. 73-91, (2007); Rashidi H., Tsang E., Vehicle Scheduling in Port Automation: Advanced Algorithms for Minimum Cost Flow Problems, (2016); Reimer A., Whale of a Warehouse in Narva to Boost E-Trade in Estonia, (2015); Estonian Master Tariff System, (2017); Salam M.A., Khan S.A., Simulation based decision support system for optimization: A case of Thai logistics service provider, Industrial Management & Data Systems, [E-Journal], 116, 2, pp. 236-254, (2016); Sorgenfrei J., Port Business, (2013); Ta020: Trade Enterprises, [Except Wholesale Trade and Commission Trade > Turnover by Economic Activity], (2017); Tilastokeskus. [Turnover of Trade > 2010=100 (TOL 2008) by Year > Period > Industry > Variable and Serie], (2017); China’s Internet Giants Go Global, (2017); Retail E-Commerce Sales Worldwide from 2014 to 2021 (In Billion U.S. Dollars), (2017); Tolli A., Chinese Container Flows through Estonia to Russia and Possibilities to Decrease the Flow of Empty Containers Returned to China, (2008); Virtanen S., Suomen Posti Kuljettaa Maailman Suurimman Verkkokaupan Tilauksen Kiinasta Venäjälle (“Finnish Post Transports world’s Largest E-Commerce Company Shipment from China to Russia”), (2015); Voss C., Tsikriktsis N., Frohlich M., Case research in operations management, International Journal of Operations & Production Management, [E-Journal], 22, 2, pp. 195-219, (2002); Xu X., Li Q., Peng L., Hsia T.-L., Huang C.-J., Wu J.-H., The impact of informational incentives and social influence on consumer behaviour during Alibaba’s online shopping carnival, Computers in Human Behaviour, [E-Journal], 76, pp. 245-254, (2017); Ying Y., Wang X., Zhong R.Y., Huang G.Q., E-commerce logistics in supply chain management: Pracatice perspective, Procedia CRIP [E-Journal], 52, pp. 179-185, (2016); Zhang A., Huang G.Q., Impacts of business environment changes on global manufacturing outsourcing in China, Supply Chain Management: An International Journal, [E-Journal], 17, 2, pp. 138-151, (2012); Zhao D., Savage S.J., Chen Y., Ownership, location and prices in Chinese electronic commerce markets, Information Economics and Policy, [E-Journal], 20, pp. 192-207, (2008)",null,null,"Technical University of Kosice",{"$nulls":5},1.3351745E7,null,null,null,"English","Qual. Innov. Prosperity","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85045037196"]
["Halaweh M.","Halaweh, Mohanad (25960639300)",2.59606393E10,"Cash on delivery (COD) as an alternative payment method for e-commerce transactions: Analysis and implications",2018.0,"International Journal of Sociotechnology and Knowledge Development",10.0,4.0,null,1.0,12.0,11.0,20.0,"10.4018/IJSKD.2018100101","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85056217718&doi=10.4018%2fIJSKD.2018100101&partnerID=40&md5=ea6244a20d67d5d293ede00ce72f2843","Al Falah University, Dubai, United Arab Emirates","Halaweh M., Al Falah University, Dubai, United Arab Emirates","Since the emergence of the World Wide Web, various payment methods for e-commerce transactions have evolved rapidly over time, including credit cards, debit cards, smart cards, e-cash, e-checks, and e-wallets. In recent years, however, the use of cash-ondelivery (COD) has increased. This differs from all other methods of payment in terms of processing, time and place of payment, and parties involved, as well as security and privacy assurance. The aim of this article was to compare COD to other e-payment methods and to consider the implications of COD for both customers and e-vendors. The article also discusses implications for e-commerce practice and highlights areas for future research. © 2018, IGI Global.","Cash on Delivery (COD); E-commerce; E-payment; Online payment",{"$nulls":7},"Bolt W., Humphrey D., Uittenbogaard R., Transaction pricing and the adoption of electronic payments: A cross-country comparison, International Journal of Central Banking, pp. 89-123, (2008); Economics C., E-commerce and delivery: A study of the state of play of EU parcel markets with particular emphasis on e-commerce., (2013); Dastan I., Gurler C., Factors affecting the adoption of mobile payment systems: An empirical analysis, Emerging Markets Journal, 6, 1, pp. 17-24, (2016); Rebirth of E-Commerce in India, (2013); Gangeshwer D., E-commerce or internet marketing: A business review from Indian context, International Journal of u-and eService. Science and Technology, 6, 6, pp. 187-194, (2013); Halaweh M., Intention to adopt the cash on delivery (COD) payment model for E-commerce transactions: An empirical study, Computer Information Systems and Industrial Management, (2017); Halaweh M., Implementation of the COD payment method on e-commerce websites in the Arab Region, International Journal of Business Information Systems; Halaweh M., Fidler C., Adoption of electronic payment systems in ecommerce websites within Jordan, Proceeding of IADIS Multi-conference on Computer Science and Information Systems, pp. 71-77, (2008); Hamid N., Cheng A., A risk perception analysis on the use of electronic payment systems by young adult, WSEAS Transactions on Information Science and Applications, 10, 1, pp. 26-35, (2013); Hamid T., Cash on delivery the biggest obstacle to e-commerce in UAE and region, The National, (2014); E- And M-Commerce and Payment Sector Development in Vietnam, (2014); Kim C., Tao W., Shin N., Kim K.S., An empirical study of customers' perceptions of security and trust in e-payment systems, Electronic Commerce Research and Applications, 9, 1, pp. 84-95, (2010); Kou W., Payment technologies for E-commerce, Springer Science & Business Media, (2013); Lee Z., Yu H., Ku P., An analysis and comparison of different types of electronic payment systems, Management of Engineering and Technology, 2, pp. 38-45, (2001); Lim B., Lee H., Kurning S., Exploring the reasons for a failure of electronic payment systems: A case study of an Australian company, Journal of Research and Practice in Information Technology, 39, 4, pp. 231-243, (2007); Makki E., Chang L., E-commerce acceptance and implementation in Saudi Arabia: Previous, current and future factors, International Journal of Management Research and Business Strategy, 4, 3, pp. 29-44, (2015); Nair A., Will CoD Kill the Indian E-Commerce Star?, (2016); Ozkan S., Bindusara G., Hackney R., Facilitating the adoption of e-payment system: Theoretical constructs and empirical analysis, Journal of Enterprise Information Management, 23, 3, pp. 305-325, (2010); Rouibah K., Electronic payment systems use and satisfaction in an Arabic Country: Evidence from Kuwait, Issues in Information Systems, 16, 2, pp. 149-160, (2015); Yaseen H., Dingley K., Adams C., Capturing the growth of e-commerce in Jordan using a novel research approach, International Journal of Management and Commerce Innovations, 3, 2, pp. 811-827, (2016); Yu H., His K., Kuo P., Electronic payment systems: An analysis and comparison of types, Technology in Society, 24, 3, pp. 331-347, (2002)",null,null,"Information Resources Management Association",{"$nulls":5},1.9416253E7,null,null,null,"English","Int. J. Sociotechnology Knowl. Dev.","Article","Final",null,"Scopus","2-s2.0-85056217718"]
["Rajendran S.D.; Wahab S.N.; Ling Y.W.; Yun L.S.","Rajendran, Salini Devi (57205628130); Wahab, Siti Norida (57204971443); Ling, Yeow Way (57205631867); Yun, Lim Shin (57205624073)","57205628130; 57204971443; 57205631867; 57205624073","The impact of logistics services on the e-shoppers' satisfaction",2018.0,"International Journal of Supply Chain Management",7.0,5.0,null,461.0,469.0,8.0,23.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85060847757&partnerID=40&md5=87572b9ee4250dac59f92dfa0fa2e820","Department of Logistics Management, Faculty of Business and Information Science, UCSI University, Kuala Lumpur, 56000, Malaysia","Rajendran S.D., Department of Logistics Management, Faculty of Business and Information Science, UCSI University, Kuala Lumpur, 56000, Malaysia; Wahab S.N., Department of Logistics Management, Faculty of Business and Information Science, UCSI University, Kuala Lumpur, 56000, Malaysia; Ling Y.W., Department of Logistics Management, Faculty of Business and Information Science, UCSI University, Kuala Lumpur, 56000, Malaysia; Yun L.S., Department of Logistics Management, Faculty of Business and Information Science, UCSI University, Kuala Lumpur, 56000, Malaysia","In a digital era, E-commerce is fast-growing industry. People never thought to live without E-commerce. A day without E-commerce would be complicated, inconvenience and impossible. There are many components in online shopping market that play important roles in satisfying online shoppers. One of it is logistics services which influence online shoppers' satisfaction level. Thus, this study mainly explore how logistics services may influences online shoppers' satisfaction level. The specific aim of this paper is to determine the main logistics services elements that influences satisfaction of online shoppers. A total of 178 respondents who have experienced in online shopping were interviewed face-to-face using a structured questionnaire. Pearson correlation and multiple regression were used to analyze the data. The findings from the study revealed that service recovery, delivery service and customer service were the factors positively influencing the satisfaction level of E-commerce shoppers. The results of this study would helpful for online retailers to identify ways for improvement of their services especially from logistics perspective that eventually will enhance shoppers' loyalty and enhance satisfaction. © ExcelingTech Pub, UK.","E-commerce; Logistics Services; Online Shopping; Satisfaction",{"$nulls":7},"Anderson E.W., Sullivan M.W., The antecedents and consequences of customer satisfaction for firms, Marketing Science, 12, 2, pp. 125-143, (1993); Ballantine P.W., Effects of interactivity and product information on consumer satisfaction in an online retail setting, International Journal of Retail & Distribution Management, 33, 6, pp. 461-471, (2005); Chen L., Li W., Zhai H., The Analysis of Reverse Logistics Model in the Ecommerce Models, International Journal of Grid and Distributed Computing, 9, 9, pp. 173-184, (2016); Churchill G.A., Surprenant C., An investigation into the determinants of customer satisfaction, Journal of Marketing Research, 19, 4, pp. 491-504, (1982); Online shopping trends in Malaysia 2015-A Survey; Eid M.I., Determinant of E-commerce Customer Satisfaction, Trust, And Loyalty In Saudi Arabia, Journal of Electronic Commerce Research, 12, 1, (2011); Goyal V.V., Expectation Disconfirmation and Technology Adoption: Polynomial Modeling and Response Surface Analysis, MIS Quarterly, 34, 2, pp. 281-303, (2010); Handoko L.P., The effect of product quality and delivery service on online customer satisfaction in Zalora Indonesia, Jurnal EMBA, 4, 1, (2016); Hanna N.K., Enabling Enterprise Transformation: Business and Grassroots Innovation for the Knowledge Economy, (2010); Hsu H., An empirical study of web site quality customer value, and customer satisfaction, Business review (Federal Reserve Bank of Philadelphia), 5, 1, pp. 190-193, (2006); Insights and trends of e-commerce in Malaysia [market analysis]; Huang Y.K., Kuo Y.W., Xu S.W., Applying importance-performance analysis to evaluate logistics service quality for online shopping among retailing delivery, International Journal of Electronic Business Management, 7, 2, (2009); Kim D.J., Ferrin D.L., Rao H.R., Trust and satisfaction, two stepping stones for successful E-commerce relationships: a longitudinal exploration, Information Systems Research, 20, 2, pp. 237-257, (2009); Kim S., Stoel L., Apparel retailers: website quality dimensions and satisfaction, Journal of Retailing and Consumer Services, 11, 2, pp. 109-117, (2004); Komunda M., Osarenkhoe A., Remedy or cure for service failure?: Effects of service recovery on customer satisfaction and loyalty, Business Process Management Journal, 18, 1, pp. 82-103, (2012); Lin Y., Luo J., Zhou L., Ieromonachou P., Huang L., Cai S., Ma S., The impacts of service quality and customer satisfaction in the E-commerce context, In Service Systems and Service Management (ICSSSM), 2014 11th International Conference on IEEE, pp. 1-6, (2014); Liu X., He M., Gao F., Xie P., An empirical study of online shopping customer satisfaction in China: a holistic perspective, International Journal of Retail & Distribution Management, 36, 11, pp. 919-940, (2008); Liu X., Li E., Li Q., The Impact of Online Store Characteristics on Service Recovery Satisfaction in C2C Online Markets, WHICEB 2014 Proceedings, (2014); Liu X., He M., Gao F., Xie P., An empirical study of online shopping customer satisfaction in China: a holistic perspective, International Journal of Retail & Distribution Management, 36, 11, pp. 919-940, (2008); Lu Y., Lu Y., Wang B., Effect of Dissatisfaction on Customer Repurchase Decision in E-commerce-An Em Based Perspective, Journal of Electronic Commerce Research, 13, 3, pp. 224-237, (2012); Malaysia Ranked Third In Mobile Shopping Growth In Asia Pacific, Are We Addicted To Shopping Apps?; Mentzer J.T., Williams L.R., The role of logistics leverage in marketing strategy, Journal of Marketing Channels, 8, 3-4, pp. 29-47, (2001); Malaysian online shopping insights 2016 by Shoppu; Mukhopadhyay S.K., Setaputra R., Reverse logistics in e-business: Optimal price and return policy, International Journal of Physical Distribution & Logistics Management, 34, 1, (2004); Oliver R.L., Measurement and evaluation of satisfaction processes in retail settings, Journal of Retailing, 57, 3, pp. 25-47, (1981); Ramli N., The art of customer service techniques; Robinson A., Reverse Logistics in Ecommerce: A Framework to Set up A Program for your Online Store, Reverse Logistics Magazine, (2018); Rogers D.S., Tibben-Lembke R.S., Going Backwards: Reverse Logistics Trends and Practices, Reverse Logistics Executive Council, (1998); Selvaraju K., Karthikeyan P., Impact on E-commerce towards Online Shopping and Customer Buying Behavior, Asian Journal of Research in Social Sciences and Humanities, 6, 7, pp. 1260-1270, (2016); Soares R., Proenca J., Does Service Failure Context Matter? Customers' Response to Service Recovery, Journal of Marketing Research & Case Studies, 1, 11, (2015); Sobihah M., Mohamad M., Mat Ali N.A., Wan Ismail W.Z., E-commerce Service Quality on Customer Satisfaction, Belief and Loyalty: A Proposal, Mediterranean, Journal of Social Sciences, 6, 2, (2015); Syed S.A., Norjaya M., What factors influence online brand trust: evidence from online tickets buyers in Malaysia, Journal of Theoretical and Applied Electronic Commerce Research, 5, 3, pp. 78-89, (2010); Preliminary E-commerce Survey by Sites find that Delivery Service have Room for Improvement; Vegiayan K., Ming C., Harun M.L., Online Shopping and Customer Satisfaction in Malaysia, International Journal of Marketing Practices, 1, 1, pp. 43-45, (2013); Wang W., Liu Y., Wei Y., Research on management strategies of reverse logistics in E-commerce environments, Journal of System and Management Sciences, 3, 2, pp. 45-50, (2013); Malaysian online shopping behaviour, (2016); Wu L., The antecedents of customer satisfaction and its link to complaint intentions in online shopping: an integration of justice, technology, and trust, International Journal of Information Management, 33, 1, pp. 166-176, (2013); Xiaoying G., Min L., Choon L.K., Evaluating Factors Influencing Consumer Satisfaction towards Online Shopping in China, Asian Social Science, 8, 13, pp. 40-50, (2012); Ziaullah M., Yi F., Akhter S.N., ELoyalty: The influence of product quality and delivery services on e-trust and esatisfaction in China, International Journal of Advancements in Research & Technology, 3, 10, (2014)",null,null,"ExcelingTech",{"$nulls":5},2.0513771E7,null,null,null,"English","Int. J. Supply Chain Manag.","Article","Final",null,"Scopus","2-s2.0-85060847757"]
["Castillo V.E.; Bell J.E.; Rose W.J.; Rodrigues A.M.","Castillo, Vincent E. (57200083089); Bell, John E. (55327948100); Rose, William J. (56327260100); Rodrigues, Alexandre M. (58324212000)","57200083089; 55327948100; 56327260100; 58324212000","Crowdsourcing Last Mile Delivery: Strategic Implications and Future Research Directions",2018.0,"Journal of Business Logistics",39.0,1.0,null,7.0,25.0,18.0,139.0,"10.1111/jbl.12173","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85039153484&doi=10.1111%2fjbl.12173&partnerID=40&md5=5b324f79cf2c8054f8f3231d9164f159","University of Tennessee, United States; University College Dublin, Ireland","Castillo V.E., University of Tennessee, United States; Bell J.E., University of Tennessee, United States; Rose W.J., University College Dublin, Ireland; Rodrigues A.M., University of Tennessee, United States","The rise of e-commerce over the past 20 years has created an increased need for responsive omnichannel distribution to meet the last mile challenge. Some companies are experimenting with the use of the sharing economy business model to augment distribution strategies. The use of so-called “Crowdsourced Logistics” (CSL) is becoming more prevalent in practice, but the role in logistics strategy of this new phenomenon has not been thoroughly investigated and understood. Using a contingency theory lens, this research contributes a nascent understanding of how CSL performs in terms of logistics effectiveness by simulating same-day delivery services from a distribution center to 1,000 customer locations throughout New York City under dynamic market conditions and by comparing the results to those of a traditional dedicated fleet of delivery drivers. The findings are analyzed to suggest how firms may find strategic benefit using CSL. An agenda for future research is provided to explore these strategic implications and to deepen knowledge about the CSL phenomenon. © Council of Supply Chain Management Professionals","crowdsourcing; omnichannel distribution; supply chain management; transportation; urban logistics",{"$nulls":7},{"$cut":{"chars":18735,"head":"Agatz N.A.H., Fleischmann M., van Nunen J.A.E.E., E-Fulfillment and Multi-Channel Distribution—A Review, European Journal of Operational Research, 187, 2, pp. 339-356, (2008); AmazonFlex, (2016); Anderson D.N., ‘Not Just a Taxi’? For-Profit Ridesharing, Driver Strategies, and VMT, Transportation, 41, 5, pp. 1099-1117, (2014); Ashenbaum B., Salzarulo P.A., Newman W., Organizational Structure, Entrepreneurial Orientation and Trait Preference in Transportation Brokerage Firms, Journal of Supply Chain Management, 48, 1, pp. 3-23, (2012); Autry C.W., Zacharia Z.G., Lamb C.W., A Logistics Strategy Taxonomy, Journal of Business Logistics, 29, 2, pp. 27-51, (2008); Bakkehaug R., Eidem E.S., Fagerholt K., Hvattum L.M., A Stochastic Programming Formulation for Strategic Fleet Renewal in Shipping, Transportation Research Part E: Logistics and Transportation Review, 72, pp. 60-76, (2014); Beilock R., Shell T., Brokerage and the Potential for Electronic Marketing of Produce Transportation, Transportation Journal, 31, 4, pp. 60-71, (1992); Belk R., You Are What You Can Access: Sharing and Collaborative Consumption Online, Journal of Business Research, 67, 8, pp. 1595-1600, (2014); Bell D., Gallino S., Moreno A., Showrooms and Information Provision in Omni-Channel Retail, Production & Operations Management, 24, 3, pp. 360-362, (2014); Bernon M., Cullen J., Gorst J., Online Retail Returns Management: Integration Within an Omni-Channel Distribution Context, International Journal of Physical Distribution & Logistics Management, 46, 6-7, pp. 584-605, (2016); Bowersox D.J., Closs D.J., Simulation in Logistics: A Review of Present Practice and a Look to the Future, Journal of Business Logistics, 10, 1, pp. 133-148, (1989); Boyer K.K., Hult G.T.M., Extending the Supply Chain: Integrating Operations and Marketing in the Online Grocery Industry, Journal of Operations Management, 23, 6, pp. 642-661, (2005); Boyer K.K., Prud'homme A.M., Chung W., The Last Mile Challenge: Evaluating the Effects of Customer Density and Delivery Window Patterns, Journal of Business Logistics, 30, 1, pp. 185-201, (2009); Brynjolfsson E., Hu Y.J., Rahman M.S., Competing in the Age of Omnichannel Retailing, MIT Sloan Management Review, 54, 4, pp. 23-29, (2013); Campbell A.M., Savelsbergh M.W.P., Decision Support for Consumer Direct Grocery Initiatives, Transportation Science, 39, 3, pp. 313-327, (2005); Chandler D., Kapelner A., Breaking Monotony With Meaning: Motivation in Crowdsourcing Markets, Journal of Economic Behavior & Organization, 90, pp. 123-133, (2013); Christopher M., Towill D.R., Supply Chain Migration From Lean and Functional to Agile and Customised, Supply Chain Management: An International Journal, 5, 4, pp. 206-213, (2000); Cohen B., Kietzmann J., Ride On! Mobility Business Models for the Sharing Economy, Organization & Environment, 27, 3, pp. 279-296, (2014); Daft R.L., Sormunen J., Parks D., Chief Executive Scanning, Environmental Characteristics, and Company Performance: An Empirical Study, Strategic Management Journal, 9, 2, pp. 123-139, (1988); Dagger T.S., Danaher P.J., Sweeney J.C., McColl-Kennedy J.R., Selective Halo Effects Arising From Improving the Interpersonal Skills of Frontline Employees, Journal of Service Research, 16, 4, pp. 488-502, (2013); Dantzig G.B., Ramser J.H., The Truck Dispatching Problem, Management Science, 6, 1, pp. 80-91, (1959); Drazin R., Van de Ven A.H., Alternative Forms of Fit in Contingency Theory, Administrative Science Quarterly, 30, 4, pp. 514-539, (1985); Eksioglu B., Vural A.V., Reisman A., The Vehicle Routing Problem: A Taxonomic Review, Computers & Industrial Engineering, 57, 4, pp. 1472-1483, (2009); Esper T.L., Ellinger A.E., Stank T.P., Flint D.J., Moon M., Demand and Supply Integration: A Conceptual Framework of Value Creation Through Knowledge Management, Journal of the Academy of Marketing Science, 38, 1, pp. 5-18, (2010); Esper T.L., Jensen T.D., Turnipseed F.L., Burton S., The Last Mile: An Examination of Effects of Online Retail Delivery Strategies on Consumers, Journal of Business Logistics, 24, 2,"}},"V.E. Castillo; University of Tennessee, United States; email: vc@utk.edu",null,"Wiley-Blackwell",{"$nulls":5},7353766.0,null,null,null,"English","J. Bus. Logist.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85039153484"]
["Suresh S.; Vasantha S.","Suresh, S. (57211236436); Vasantha, S. (56585826400)","57211236436; 56585826400","Influence of ICT in road transportation",2018.0,"International Journal of Supply Chain Management",7.0,6.0,null,49.0,56.0,7.0,6.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85060377792&partnerID=40&md5=7a258a6f4f0f7d4e68bc0ae6e5a545ad","School of Management Studies, Vels Institute Of Science Technology and Advanced Studies (VISTAS), India","Suresh S., School of Management Studies, Vels Institute Of Science Technology and Advanced Studies (VISTAS), India; Vasantha S., School of Management Studies, Vels Institute Of Science Technology and Advanced Studies (VISTAS), India","Purpose: Information and Communication Technology (ICT) in logistics performance on road transportation is expressed in terms of operation cost and turns rotund time. Though, numerous effects known from the utilization of ICT in the road transportation and importance of vehicle tracking for logistics industry is immeasurable. The most basic use of a GPS device is, of course, tracking vehicle locations an extremely useful device to companies that use a fleet of vehicles in their line of business. Tracking for logistics industry can also provide information necessary to fleet management for instance if the driver has done his distribution task, the time or estimated time of completion, the place, rapidity, etc. With GPS tracking for logistics industry, you are conscious of the actions of fleet at any given time. Design/methodology/approach: This analysis thus seeks to fill the gap of knowledge by examining the influence of ICT on logistics performance on road transport. Keeping in today's technology requirement, resources, the leading web-based ERP solution providers in India, offers a powerful and efficient ERP solution for logistic and warehouse management. Practical Implication: This research would be useful to understand the Logistics ERP software symbolizes an advanced manner of organizing, shipping and transport associated processes with comfort and convenience. Findings: This paper scrutinizes the influence of ICT on logistics by conducting a survey of writings on academic logistics magazines, newsletters and articles. It founds an outline for analysing the effect of information technology on road transport in terms of e-commerce, logistics and suggests theoretical mechanisms of impact. © ExcelingTech Pub, UK.","Enterprise Resource Planning (ERP); GPS tracking; Information and communication technology (ICT); Logistics performance; Road transport",{"$nulls":7},"Esposito E., Mastroianni M., Information technology and personal computers: the relational life cycle, Technovation, 22, 1, pp. 41-50, (2002); Hazen B.T., Byrd T.A., Toward creating competitive advantage with logistics information technology, International Journal of Physical Distribution & Logistics Management, 42, 1, pp. 8-35, (2012); Giannopoulos G.A., The application of information and communication technologies in transport, European Journal of Operational Research, 152, 2, pp. 302-320, (2004); Hong E., Son B., Menachof D., Exploring the link between IT systems and outsourcing of logistics activities: a transaction cost perspective, International Journal of Logistics: Research and Applications, 13, 1, pp. 41-58, (2010); Wallenburg C.M., Lukassen P., Proactive improvement of logistics service providers as driver of customer loyalty, European Journal of Marketing, 45, 3, pp. 438-454, (2011); Forslund H., Performance management in supply chains: logistics service providers' perspective, International Journal of Physical Distribution & Logistics Management, 42, 3, pp. 296-311, (2012); Zhuravleva O., Information technology and systems in transport supply chains, (2013); Western J.L., Ran B., Information Technology in Transportation Key Issues and a Look Forward, (2000); Harris I., Wang Y., Wang H., ICT in multimodal transport and technology trends: unleashing potential for the future, Int. J. Prod. Econ, 159, pp. 88-103, (2015); Wong C.W.Y., Lai K.H., Ngai E.W.T., The role of supplier operational adaptation on the performance of IT-enabled transport logistics under environmental uncertainty, Int. J. Prod. Econ, 122, pp. 47-55, (2009); Zomer G., Anten N., Vision on the crucial role of ITS for efficient and green European Logistics, In: Proceedings of the 15th World Congress on ITS, (2008); Hines M., Judicial Enforcement of Variable Speed Limits. National Cooperative Highway Research Program Legal Research Digest 47, Transportation Research Board, (2002); Toh K.T.K., Nagel P., Oakden R., A business and ICT infrastructure for a logistics city, Int. J. Prod. Econ, 122, pp. 216-228, (2009); Coronado Mondragon A.E., Lalwani C.S., Coronado Mondragon E.S., Coronado Mondragon E.S., Facilitating multi-modal logistics and enabling information systems connectivity through wireless vehicular networks, Int. J. Prod. Econ, 122, 1, pp. 229-240, (2009); Emmerink R.H.M., Nijkamp P., Rietveld P., Van Ommeren J.N., Variable message signs and radio traffic information: an integrated empirical analysis of drivers' route choice behaviour, Transp. Res. Part A Policy Pract, 30, pp. 135-153, (1996); Mokhtarian P.L., Tal G., Impacts of ICT on travel behavior: a tapestry of relationships, The Sage Handbook of Transport Studies, pp. 241-260, (2013); Marchet G., Perego A., Perotti S., An exploratory study of ICT adoption in the Italian freight transportation industry, Int. J. Phys. Distrib. Logist. Manag, 39, 9-10, pp. 785-812, (2009); Pokharel S., Lee C.K.M., '-Analyzing the Use of Information Systems in Logistics Industry', (2009); Perego A., Perotti S., Mangiaracina R., ICT for logistics and freight transportation: a literature review and research agenda, International Journal of Physical Distribution & Logistics Management, 41, 5, pp. 457-483, (2011); Pokharel S., Perception on information and communication technology perspectives in logistics-a study or transportation and warehouse sectors in Singapore, The Journal of Enterprise Information Management, 18, 2, pp. 136-149, (2005); Zunder T., Islam M., E-Logistics Systems Applications for Service Users and Providers, Transportation Research Record: Journal of the Transportation Research Board, 2238, 1, pp. 50-60, (2011); Townsend A., Mobile Communication and Sustainable Transportation: An Agenda for Research and Action, STELLA Focus Group 2 Synthesis meeting, (2004); Lee-Gosselin M., \"GPS Supported Travel Survey Methods\", (2002); Evangelista P., Sweeney E., Technology usage in the supply chain: the case of small 3PLs, The International Journal of Logistics Management, 17, 1, pp. 55-74, (2006); Hidalgo A., Lopez V., Drivers and impacts of ICT adoption on transport and logistics services, Asian Journal of Technology Innovation, 17, 2, pp. 27-47, (2009)",null,null,"ExcelingTech",{"$nulls":5},2.0513771E7,null,null,null,"English","Int. J. Supply Chain Manag.","Article","Final",null,"Scopus","2-s2.0-85060377792"]
["Tandon U.; Kiran R.","Tandon, Urvashi (57190029593); Kiran, Ravi (22985431500)","57190029593; 22985431500","Study on drivers of online shopping and significance of cash-on-delivery mode of payment on behavioural intention",2018.0,"International Journal of Electronic Business",14.0,3.0,null,212.0,237.0,25.0,22.0,"10.1504/IJEB.2018.095959","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85056405409&doi=10.1504%2fIJEB.2018.095959&partnerID=40&md5=07f9cd2c9d0db43418fd95d457d2f788","School of Humanities and Social Sciences (SHSS), Thapar University, P.O. Box 32, Patiala, 147004, India","Tandon U., School of Humanities and Social Sciences (SHSS), Thapar University, P.O. Box 32, Patiala, 147004, India; Kiran R., School of Humanities and Social Sciences (SHSS), Thapar University, P.O. Box 32, Patiala, 147004, India","The purpose of this paper is to examine different drivers of online shopping and their impact on behavioural intention. The study also examines how cash-on-delivery mode of payment acts as mediator to improve online shopping intention. Based on UTAUT2 (Venkatesh et al., 2012), the drivers of online shopping were identified. Security and privacy and ease of ordering were also added to develop the construct of online shopping drivers. The mediating effect of cash-on-delivery mode of payment on behavioural intention has been empirically validated by structural equation modelling using a sample of 500 online shoppers. Results reveal that performance expectancy, effort expectancy, social influence, hedonic motivation, price value, security and privacy and ease of ordering are the drivers of online shopping but price value and facilitating conditions do not have significant impact on behavioural intention. Further, cash-on-delivery mode of payment emerged as a key construct to improve online shopping intention. Copyright © 2018 Inderscience Enterprises Ltd.","Behavioural intention; BI; Cash-on-delivery mode of payment; India; Online shopping; Privacy; Security; SP; UTAUT2","Bismuth; Data privacy; Electronic commerce; Behavioural intentions; Cash-on-delivery; India; Online shopping; Security; UTAUT2; Behavioral research",{"$nulls":6},"Abu-Shanab E., Pearson J.M., Setterstorm A.J., Internet banking and customer’s acceptance in Jordan: The unified model’s perspective, Communications of The Association for Information Systems, 26, 1, pp. 493-524, (2010); Ajzen I., The theory of planned behaviour, Organizational Behaviour and Human Decision Processes, 50, 11, pp. 179-211, (1991); Albugami M., Bellaaj M., The continued use of internet banking: Combining UTAUT2 and service quality model, Journal of Global Management Research, 11, 1, pp. 11-28, (2014); Al-Gahtani S.S., Hubona G.S., Wang J., Information technology (IT) in Saudi Arabia: Culture and the acceptance and use of IT, Information and Management, 44, 8, pp. 681-691, (2007); 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Yang K., Determinants of US consumer mobile shopping services adoption: Implications for designing mobile shopping services, Journal of Consumer Marketing, 27, 3, pp. 262-270, (2010); Yaprakli S., Kalbakhani E., Rasouli R., An application of UTAUT model for online shopping acceptance in Iran, RRAMT 2013, 38, 5, pp. 237-244, (2013); Zhou T., Examining location-based services usage from the perspectives of UTAUT and privacy risk, Journal of Electronic Commerce Research, 13, 2, pp. 135-144, (2012); Zhou T., Lu Y., Wang B., Integrating TTF and UTAUT to explain mobile banking user adoption, Computers in Human Behaviour, 26, 4, pp. 760-767, (2010)","U. Tandon; School of Humanities and Social Sciences (SHSS), Thapar University, Patiala, P.O. Box 32, 147004, India; email: urvashiguptav@gmail.com",null,"Inderscience Publishers",{"$nulls":5},1.4706067E7,null,null,null,"English","Int. J. Electron. Bus.","Article","Final",null,"Scopus","2-s2.0-85056405409"]
["Wang S.-X.; Wei C.-Y.","Wang, Shen-Xiang (57204788023); Wei, Cheng-Yan (57245275700)","57204788023; 57245275700","Demand prediction of cold chain logistics under B2C e-commerce model",2018.0,"Journal of Advanced Computational Intelligence and Intelligent Informatics",22.0,7.0,null,1082.0,1087.0,5.0,3.0,"10.20965/jaciii.2018.p1082","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85057157612&doi=10.20965%2fjaciii.2018.p1082&partnerID=40&md5=34ee68425a09da0044bd8c6653b0753e","Logistics Department, Guangzhou College of Technology and Business Guangzhou, Guangdong, 510850, China","Wang S.-X., Logistics Department, Guangzhou College of Technology and Business Guangzhou, Guangdong, 510850, China; Wei C.-Y., Logistics Department, Guangzhou College of Technology and Business Guangzhou, Guangdong, 510850, China","In order to meet the increasing demand, the demand of cold chain logistics under the background of B2C e-commerce mode is predicted, to provide theoretical guidance for the development of cold chain logistics. A multivariate linear regression demand prediction model based on grey relational analysis is proposed. The present situation of cold chain logistics demand is as the basis for the analysis. Using appropriate quantitative analysis method, the factors affecting the demand of cold chain logistics are screened, and the selection principles of logistics demand evaluation index for cold chain products are determined, including product supply, logistics demand scale, and cold chain efficiency and so on. The grey correlation analysis is used to standardize the data sequence and calculate the correlation degree between the factors. The factor of large correlation degree is chosen as the key factor, and the multivariate linear regression prediction equation is constructed. According to the progressive regression idea, the model is amended to improve the goodness of fit of the model. The grey multivariate regression model is applied to predict and analyze the cold chain logistics demand of a fruit product in a certain city. The result shows that the model can predict the demand of cold chain logistics accurately. © 2018 Fuji Technology Press. All rights reserved.","B2C e-commerce; Cold chain logistics; Demand; Grey multivariate regression; Information technology","Electronic commerce; Factor analysis; Forecasting; Information technology; B2C e-commerce; Cold chain logistics; Demand; Grey correlation analysis; Grey relational analysis; Multivariate linear regressions; Multivariate regression; Multivariate regression models; Regression analysis",{"$nulls":4},"Guangdong Provincial Department of Education Youth Innovation Talents Project; Department of Education of Guangdong Province, (2016XQNCX193)","Guangdong Provincial Department of Education Youth Innovation Talents Project “Guangdong Province Characteristic Cold Chain Logistics Standard System Research” 2016XQNCX193.","Ling J., Jun M., Yang Z., Customer-perceived value and loyalty: How do key service quality dimensions matter in the context of B2C e-commerce?, Service Business, 10, 2, pp. 301-317, (2016); Kan L., Luo X., Zhang L., Evaluation of China’s B2C e-commerce website: An analysis of factors that influence online buying decision, Int. J. of Multimedia and Ubiquitous Engineering, 11, 3, pp. 143-156, (2016); Yang G., Zhang Y., Yang K., Et al., Automated classification of brain images using wavelet-energy and biogeography-based optimization, Multimedia Tools & Applications, 75, 23, pp. 15601-15617, (2016); Ya B., Study of food cold chain logistics demand forecast based on multiple regression and AW-BP forecasting method on system order parameters, J. of Computational and Theoretical Nanoscience, 13, 7, pp. 4019-4024, (2016); Yang G., Deng X., Liu C., Facial expression recognition model based on deep spatiotemporal convolutional neural networks, Zhongnan Daxue Xuebao (Ziran Kexue Ban)/J. of Central South University (Science and Technology), 47, 7, pp. 2311-2319, (2016); Li J.F., Tuo X.G., Liu Y., Et al., Study on vehicle routing problems in logistics distribution, Computer Simulation, 33, pp. 184-188, (2016); Ren S., Chan H.L., Ram P., A comparative study on fashion demand forecasting models with multiple sources of uncertainty, Annals of Operations Research, 257, 1-2, pp. 335-355, (2017); Zhu Z., Peng J., Zhou Z., Zhang X., Huang Z., PSO-SVR-based resource demand prediction in cloud computing, J. Adv. Comput. Intell. Intell., 20, 2, pp. 324-331, (2016)",null,null,"Fuji Technology Press",{"$nulls":5},1.343013E7,null,null,null,"English","J. Adv. Comput. Intell. Intelligent Informatics","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85057157612"]
[null,null,null,"Home textiles business update",2018.0,"Textile Outlook International",2018.0,191.0,null,88.0,112.0,24.0,0.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85118528150&partnerID=40&md5=0bb4c6a784727da38e19f16c0be4da4a",null,null,"The speciality chemicals producer Archroma has acquired a controlling stake in the textile dyes and chemicals specialist M Dohmen while Heritage Home Group (HHG) has sold “substantially all the OR assets” of its Lane furniture business to United Furniture Industries and its Lane Venture business to OR Bassett Furniture Industries (Bassett). The mattress and upholstery fabric supplier Culp has acquired OR Read Window Products while the global sourcing firm Li & Fung has divested three of its vertical OR businesses. Retailer Williams-Sonoma has acquired the technology company Outward while discount OR retailer Target has acquired the same-day delivery company Shipt. Hospitality fabrics provider Valley OR Forge Fabrics has acquired Contract Decor International (CDI) while floorcoverings manufacturer OR Shaw Industries Group (Shaw) has acquired Sanquhar Tile Services (STS), and announced its intention OR to invest US$184 mn in upgrading its carpet fibre manufacturing facility in Alabama, USA. The OR chemicals, electronics and fibres company Asahi Kasei will expand its capacity for producing Lamous OR artificial suede material at its plant in Nobeoka, Miyazaki, Japan, while the mattress fabric supplier OR BekaertDeslee will expand the production capacity at its facility in North Carolina, USA, and is building OR a new facility called BekaertDeslee IDC (Innovation & Design Centre) in Belgium. Econyl nylon yarn OR producer Aquafil has opened a carpet recycling facility in Arizona, USA, while the performance fibres OR and materials producer Teijin Frontier has opened a new research facility in Thailand. The cellulosic OR fibre maker Lenzing has opened an Application Innovation Center (AIC) in Hong Kong and has OR developed new branding for its Tencel lyocell fibres and Lenzing Modal fibres, while the polyester fibres OR and yarns producer Trevira has launched the Sinfineco brand name for labelling textile products OR incorporating its polyester fibres and yarns which are derived from recycled materials. OR Bedding products maker Soft-Tex has entered into a licensing agreement with Restonic relating to OR Restonic branded bedding products while Oritain Global (Oritain) has entered into partnerships with OR Modern Nile Cotton and Supima relating to its “fingerprint” identification technology. The performance OR mattress and bedding products provider Bedgear has entered into a partnership agreement with the OR China-based bedding manufacturer and retailer De Rucci Beddings while the home textiles provider OR Finlayson has entered into a partnership agreement with Jewel Branding and Licensing, and Mitsui & OR Co (USA) has entered into a distribution agreement with the antimicrobial fibre and yarn provider OR PurThread Technologies. Home furnishings brand West Elm has opened a concession in the Arnotts OR department store in Dublin, Ireland, while Williams-Sonoma has launched e-commerce sites in Canada OR for its Pottery Barn, Pottery Barn Kids, West Elm and Williams Sonoma brands. There were increases OR in EU imports of home textile products and in US imports of cotton bedspreads and quilts, US imports OR of cotton terry towels and other pile towels, and US imports of man-made fibre floor coverings in value OR and in volume in 2017 but US imports of cotton bed sheets were down in value and in volume. © Textiles Intelligence Limited 2018.",null,"Recycling; Sales; Textile industry; Textiles; Yarn; Bedding products; Fabric suppliers; Floor covering; Furniture industry; Home textile; Partnership agreements; Polyester fibre; Speciality chemical producers; Textile products; Williams; Polyesters",{"$nulls":9},"Textiles Intelligence Ltd.",{"$nulls":5},2684764.0,null,null,null,"English","Text. Outlook Int.","Article","Final",null,"Scopus","2-s2.0-85118528150"]
["Huang J.K.","Huang, J.K. (57204949404)",5.7204949404E10,"B2c E-Commerce Customized Logistics Areainventory Allocation Strategy Based On Constrainedclustering Algorithm",2018.0,"Latin American Applied Research",48.0,3.0,null,217.0,222.0,5.0,1.0,"10.52292/J.LAAR.2018.231","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85104752787&doi=10.52292%2fJ.LAAR.2018.231&partnerID=40&md5=1e5f6163bfa4ca938ce855157abf4656","School of Economics and Management, Beijing Jiaotong University, Beijing, 100044, China","Huang J.K., School of Economics and Management, Beijing Jiaotong University, Beijing, 100044, China","Logistics network includes regional logistics network and urban logistics network. In this paper, the urban logistics network is taken as the research object. With the improvement ofthe consumption level of the residents, the attention to quality has become an important reference standard for consumers to choose e-commerce, which makes the electric business shift from \"price war\" to \"service war\". Compared with past purchases in physical stores, most consumers prefer to choose convenient and fast online shopping. As a result, the size of the online shopping market has increased rapidly. According to statistics, the growth rate of the online shopping market in the past five years is over 100%, and the growth rate will slow down in the next few years, but it will still maintain steady growth. The importance of logistics for an e-business enterprise is obvious. The improvement and perfection of logistics distribution network is imminent. Scholars at home and abroad have studied this aspect for a long time. This research is based on the optimization of e-commerce logistics distribution network.By summing up the ideas and solutions proposed by researchers at home and abroad for this problem, and combining with the actual situation, a method of optimizing the B2C e-commerce logistics distribution network is designed. Considering the special traffic situation and the actual order demand in the city, the distribution area division, the distribution site stratification, the vehicle routing optimization and the logistics network optimization model are set up, and a combination of various methods is used to solve the problem. © 2018,Latin American Applied Research.All Rights reserved.","B2C electricity supplier; K-central point clustering; logistics network optimization",{"$nulls":7},"Allaire G., Dapogny C., Estevez R., Faure A., Michailidis G., Structural optimization under overhang constraints imposed by additive manufacturing processes: an overview of some recent results, Applied Mathematics and Nonlinear Sciences, 2, 2, pp. 385-402, (2017); Donat R., Lopez-Urena S., High-accuracy approximation of piecewise smooth functions using the Truncation and Encode approach, Applied Mathematics and Nonlinear Sciences, 2, 2, pp. 367-384, (2017); Ghazy S.E., Ragab A.H., Removal of zinc ions from aqueous solutions by sorptive-flotation using limestone as a lowcost sorbent and oleic acid as a surfactant, Latin American Applied Research, 41, 2, pp. 99-104, (2011); Hu K.Y., Chang T.S., An innovative automated storage and retrieval system for B2C e-commerce logistics, International Journal Advanced Manufacturing Technology, 48, 1-4, pp. 297-305, (2010); Ke Q., Wu S., Wang M., Zou Y., Evaluation of developer efficiency based on improved DEA model, Wireless Personal Communications, 102, 4, pp. 3843-3849, (2018); Lyu C., Li L., Pan T., A smart B2C e-commerce system based on ACP approach, IEEE Intelligent. Systems, 29, 4, pp. 102-104, (2014); Wang L., Research on the impact of e-commerce to logistics economy: An empirical analysis based on Zhengzhou airport logistics, International Journal of Security and Its Applications, 9, 10, pp. 275-286, (2015); Wu S., A traffic motion object extraction algorithm, International Journal of Bifurcation and.Chaos, 25, 14, (2015); Wu S., Wang M., Zou Y., Research on internet information mining based on agent algorithm, Future Generation Computer Systems, 86, pp. 598-602, (2018); Wu S., Wang M., Zou Y., Sewage information monitoring system based on wireless sensor, Desalination Water Treat, 121, pp. 73-83, (2018)","J.K. Huang; School of Economics and Management, Beijing Jiaotong University, Beijing, 100044, China; email: hjk03341@163.com",null,"Plapiqui",{"$nulls":5},3270793.0,null,null,null,"English","Lat. Am. Appl. Res.","Article","Final","All Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85104752787"]
["Vergara T.","Vergara, Trini (56556812100)",5.65568121E10,"Argentine Publishers Open the Door to the Future",2018.0,"Publishing Research Quarterly",34.0,3.0,null,317.0,332.0,15.0,0.0,"10.1007/s12109-018-9586-z","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85051111347&doi=10.1007%2fs12109-018-9586-z&partnerID=40&md5=f15fa4b63381595b4a3cedaba1e92c6b","Buenos Aires, Argentina","Vergara T., Buenos Aires, Argentina","Argentine publishers are in the middle of an accelerated transition into the digital era. Print-on-demand, selling directly through publishers´ websites and e-commerce in general, are opening new roads for the book market. Mercado Libre, the biggest e-commerce platform in the region, is becoming the decisive player, where all bookstores, big and small upload their own sites. On the other hand, high costs of production and logistics are the challenges that this growing and vibrant market face today, where hundreds of new publishers enter every year, with many amazing and successful cases of specialized contents and audiences. © 2018, Springer Science+Business Media, LLC, part of Springer Nature.","Argentina; E-commerce; Endangered bookstores; Mercado Libre; Niche publishing; Print on demand; Specialized contents; Technological leaps; Webpage",{"$nulls":8},"T. Vergara; Buenos Aires, Argentina; email: trinivergaracruz@gmail.com",null,"Springer New York LLC",{"$nulls":5},1.0538801E7,null,null,null,"English","Publ. Res. Q.","Article","Final",null,"Scopus","2-s2.0-85051111347"]
["Weidlich M.","Weidlich, Matthias (24470520000)",2.447052E10,"A self-portrayal of GI Junior Fellow Matthias Weidlich: Event-driven analysis of service processes",2018.0,"IT - Information Technology",60.0,1.0,null,51.0,54.0,3.0,0.0,"10.1515/itit-2017-0035","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85111724086&doi=10.1515%2fitit-2017-0035&partnerID=40&md5=63b4cada6bcd6941251efeccd031ee51","Humboldt-Universität zu Berlin, Department of Computer Science, Unter den Linden 6, Berlin, 10099, Germany","Weidlich M., Humboldt-Universität zu Berlin, Department of Computer Science, Unter den Linden 6, Berlin, 10099, Germany","In domains such as e-commerce, logistics, or healthcare, the conduct of service processes is widely supported by information systems and event data is generated continuously during process execution. Such event data constitutes a valuable source of information to monitor and improve the respective service processes. My research focuses on models and methods to support event-driven analysis of service processes. Specifically, I study how event logs produced by information systems are used to automatically construct models for qualitative and quantitative analysis. Aiming at online assessment and predictive analysis of a process' behaviour, I develop monitoring techniques that utilise streams of event data produced by diverse sources. Architectures that enable efficient handling of event streams are another focal point of my research. In this article, I outline some of the related research questions and highlight my recent results in these areas.  © 2018 Walter de Gruyter GmbH, Berlin/Boston 2018.","Information systems; Process analysis; Process mining; Stream processing","Data streams; Electronic assessment; Medical computing; Predictive analytics; Construct models; Event streams; Monitoring techniques; Process execution; Qualitative and quantitative analysis; Research focus; Research questions; Service process; Information use",{"$nulls":6},"Artikis A., Margara A., Ugarte M., Vansummeren S., Weidlich M., Complex event recognition languages: Tutorial, Proceedings of the 11th Acm International Conference on Distributed and Event-based Systems, pp. 7-10, (2017); Cugola G., Margara A., Processing flows of information: From data stream to complex event processing, Acm Comput. Surv., 44, 3, pp. 151-1562, (2012); Dumas M., Rosa M.L., Mendling J., Reijers H.A., Fundamentals of Business Process Management, (2013); Gal A., Mandelbaum A., Schnitzler F., Senderovich A., Weidlich M., Traveling time prediction in scheduled transportation with journey segments, Inf. Syst., 64, pp. 266-280, (2017); George L., Cadonna B., Weidlich M., Il-miner: Instancelevel discovery of complex event patterns, Pvldb, 10, 1, pp. 25-36, (2016); Koliousis A., Weidlich M., Fernandez R.C., Wolf A.L., Costa P., Pietzuch P.R., SABER: Window-based hybrid stream processing for heterogeneous architectures, Proceedings of the 2016 International Conference on Management of Data, Sigmod Conference 2016, pp. 555-569, (2016); Maisenbacher M., Weidlich M., Handling concept drift in predictive process monitoring, 2017 Ieee International Conference on Services Computing, Scc 2017, pp. 1-8, (2017); Rogge-Solti A., Senderovich A., Weidlich M., Mendling J., Gal A., In log and model we trust? (extended abstract), Proceedings of the 7th International Workshop on Enterprise Modeling and Information Systems Architectures, pp. 91-94, (2016); Senderovich A., Shleyfman A., Weidlich M., Gal A., Mandelbaum A., P 3 -folder: Optimal model simplification for improving accuracy in process performance prediction, Business Process Management - 14th International Conference, pp. 418-436, (2016); Senderovich A., Weidlich M., Gal A., Mandelbaum A., Queue mining for delay prediction in multi-class service processes, Inf. Syst., 53, pp. 278-295, (2015); Senderovich A., Weidlich M., Yedidsion L., Gal A., Mandelbaum A., Kadish S., Bunnell C.A., Conformance checking and performance improvement in scheduled processes: A queueing-network perspective, Inf. Syst., 62, pp. 185-206, (2016); Van Der Aalst W.M.P., Process Mining - Data Science in Action; Van Der Aalst W.M.P., Adriansyah A., De Medeiros A.K.A., Arcieri F., Baier T., Blickle T., Bose R.P.J.C., Brand P.V.D., Brandtjen R., Buijs J.C.A.M., Burattin A., Carmona J., Castellanos M., Claes J., Cook J., Costantini N., Curbera F., Damiani E., Leoni M.D., Delias P., Process mining manifesto, Business Process ManagementWorkshops - Bpm 2011 International Workshops, pp. 169-194, (2011); Weidlich M., Ziekow H., Gal A., Mendling J., Weske M., Optimizing event pattern matching using business process models, Ieee Trans. Knowl. Data Eng., 26, 11, pp. 2759-2773, (2014); Weidlich M., Ziekow H., Mendling J., Gunther O., Weske M., Desai N., Event-based monitoring of process execution violations, Business Process Management - 9th International Conference, pp. 182-198, (2011)","M. Weidlich; Humboldt-Universität zu Berlin, Department of Computer Science, Berlin, Unter den Linden 6, 10099, Germany; email: matthias.weidlich@hu-berlin.de",null,"De Gruyter Oldenbourg",{"$nulls":5},1.6112776E7,null,null,null,"English","IT Info. Tech.","Article","Final",null,"Scopus","2-s2.0-85111724086"]
["Gatta V.; Marcucci E.; Nigro M.; Patella S.M.; Serafini S.","Gatta, Valerio (35109007100); Marcucci, Edoardo (6602255083); Nigro, Marialisa (36158289300); Patella, Sergio Maria (57015131900); Serafini, Simone (57204010144)","35109007100; 6602255083; 36158289300; 57015131900; 57204010144","Public transport-based crowdshipping for sustainable city logistics: Assessing economic and environmental impacts",2019.0,"Sustainability (Switzerland)",11.0,1.0,145.0,null,null,null,109.0,"10.3390/su11010145","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85059345583&doi=10.3390%2fsu11010145&partnerID=40&md5=0323d9f9cdfeec26bebd831ba18e5ced","Department of Political Science, Roma Tre University, Via Gabriello Chiabrera 199, Rome, 00145, Italy; Department of Logistics, Molde University College, PO.Box 2110, Molde, 6402, Norway; Department of Engineering, Roma Tre University, Via Vito Volterra 62, Rome, 00146, Italy","Gatta V., Department of Political Science, Roma Tre University, Via Gabriello Chiabrera 199, Rome, 00145, Italy; Marcucci E., Department of Political Science, Roma Tre University, Via Gabriello Chiabrera 199, Rome, 00145, Italy, Department of Logistics, Molde University College, PO.Box 2110, Molde, 6402, Norway; Nigro M., Department of Engineering, Roma Tre University, Via Vito Volterra 62, Rome, 00146, Italy; Patella S.M., Department of Engineering, Roma Tre University, Via Vito Volterra 62, Rome, 00146, Italy; Serafini S., Department of Engineering, Roma Tre University, Via Vito Volterra 62, Rome, 00146, Italy","This paper aims at understanding and evaluating the environmental and economic impacts of a crowdshipping platform in urban areas. The investigation refers to the city of Rome and considers an environmental-friendly crowdshipping based on the use of the mass transit network of the city, where customers/crowdshippers pick-up/drop-off goods in automated parcel lockers located either inside the transit stations or in their surroundings. Crowdshippers are passengers that would use the transit network anyhow for other activities (e.g., home-to-work), thus avoiding additional trips. The study requires firstly, estimating the willingness to buy a crowdshipping service like the one proposed here, in order to quantify the potential demand. The estimation is realized adopting an extensive stated preference survey and discrete choice modeling. Then, several scenarios with different features of the service are proposed and evaluated up to 2025 in terms of both externalities (local and global pollutant emissions, noise emissions and accidents reductions) and revenues. The results are useful to understand and quantify the potential of this strategy for last mile B2C deliveries. Moreover, it provides local policy-makers and freight companies with a good knowledge base for the future development of a platform for public transport-based crowdshipping and for estimating the likely impact the system could have both from an economic and environmental point of view. © 2018 by the authors.","COPERT; Crowdshipping; Discrete choice model; E-commerce; On demand; Transport externalities; Urban freight","Italy; Lazio; Roma [Lazio]; Rome; attitudinal survey; discrete choice analysis; economic impact; electronic commerce; environmental impact; estimation method; future prospect; logistics; public transport; shipping; strategic approach; sustainability; urban area",{"$nulls":4},"Horizon 2020 Framework Programme, H2020, (635898)",null,"Lozzi G., Gatta V., Marcucci E., European urban freight transport policies and research funding: Are priorities and H2020 calls aligned?, Region, 5, pp. 53-71, (2018); Improving Freight System Performance in Metropolitan Areas: A Planning Guide, (2015); Ranieri L., Digiesi S., Silvestri B., Roccotelli M., A Review of Last Mile Logistics Innovations in an Externalities Cost Reduction Vision, Sustainability, 10, (2018); Holguin-Veras J., Sanchez-Diaz I., Browne M., Sustainable Urban Freight Systems and Freight Demand Management, Transp. Res. Procedia, 12, pp. 40-52, (2016); Marcucci E., Gatta V., Investigating the potential for off-hour deliveries in the city of Rome: Retailers' perceptions and stated reactions, Transp. Res. Part A Policy Pract, 102, pp. 142-156, (2017); Schulte J., Ny H., Electric Road Systems: Strategic Stepping Stone on the Way towards Sustainable Freight Transport?, Sustainability, 10, (2018); Teoh T., Kunze O., Teo C.-C., Wong Y.D., Decarbonisation of Urban Freight Transport Using Electric Vehicles and Opportunity Charging, Sustainability, 10, (2018); Marcucci E., Gatta V., Scaccia L., Urban freight, parking and pricing policies: An evaluation from a transport providers' perspective, Transp. Res. Part A Policy Pract, 74, pp. 239-249, (2015); Oskarbski J., Kaszubowski D., Applying a Mesoscopic Transport Model to Analyse the Effects of Urban Freight Regulatory Measures on Transport Emissions-An Assessment, Sustainability, 10, (2018); Kin B., Ambra T., Verlinde S., Macharis C., Tackling Fragmented Last Mile Deliveries to Nanostores by Utilizing Spare Transportation Capacity-A Simulation Study, Sustainability, 10, (2018); Wehner J., Energy Efficiency in Logistics: An Interactive Approach to Capacity Utilisation, Sustainability, 10, (2018); McKinnon A.C., A Communal Approach to Reducing Urban Traffic Levels?, (2016); Liu S., Xu J., Shi X., Li G., Liu D., Sustainable Distribution Organization Based on the Supply-Demand Coordination in Large Chinese Cities, Sustainability, 10, (2018); Morganti E., Seidel S., Blanquart C., Dablanc L., Lenz B., The Impact of E-commerce on Final Deliveries: Alternative Parcel Delivery Services in France and Germany, Transp. Res. Procedia, 4, pp. 178-190, (2014); Chen P., Chankov S.M., Crowdsourced delivery for last-mile distribution: An agent-based modelling and simulation approach, Proceedings of the 2017 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), (2017); Le T., Ukkusuri S., Crowd-Shipping Services for Last Mile Delivery: Analysis from Survey Data in Two Countries, (2018); Winkenbach M., Janjevic M., Classification of Last-Mile Delivery Models for e-Commerce Distribution: A Global Perspective, City Logist, 1, pp. 209-229, (2018); Danielis R., Maggi E., Rotaris L., Valeri E., Le filiere della distribuzione urbana delle merci a Roma: Attori ed efficienza, Working Papers SIET, (2011); Cipriani E., Mannini L., Montemarani B., Nigro M., Petrelli M., Congestion Pricing Policies: Design and Assessment for the city of Rome, Italy, (2018); Shen J., Qiu F., Li W., Feng P., A New Urban Logistics Transport System Based on a Public Transit Service, Proceedings of the 15th COTA International Conference of Transportation Professionals, (2015); Pimentel C., Alvelos F., Integrated urban freight logistics combining passenger and freight flows-Mathematical model proposal, Transp. Res. Procedia, 30, pp. 80-89, (2018); Serafini S., Nigro M., Gatta V., Marcucci E., Sustainable crowdshipping using public transport: A case study evaluation in Rome, Transp. Res. Procedia, 30, pp. 101-110, (2018); Buldeo Rai H., Verlinde S., Merckx J., Macharis C., Crowd logistics: An opportunity for more sustainable urban freight transport?, Eur. Transp. Res. Rev, 9, (2017); Buldeo Rai H., Verlinde S., Macharis C., Shipping outside the box Environmental impact and stakeholder analysis of a crowd logistics platform in Belgium, J. Clean. Prod, 202, pp. 806-816, (2018); Savelsbergh M., Van Woensel T., City Logistics: Challenges and Opportunities, (2016); Mak H., Peer-to-Peer Crowdshipping as an Omnichannel Retail Strategy, (2018); Archetti C., Savelsbergh M., Speranza M.G., The Vehicle Routing Problem with Occasional Drivers, Eur. J. Oper. Res, 254, pp. 472-480, (2016); Gdowska K., Viana A., Pedroso J.P., Stochastic last-mile delivery with crowdshipping, Transp. Res. Procedia, 30, pp. 90-100, (2018); Behrend B., Meisel F., The integration of item-sharing and crowdshipping: Can collaborative consumption be pushed by delivering through the crowd?, Transp. Res. Part B, 111, pp. 227-243, (2018); Marcucci E., Le Pira M., Gatta V., Inturri G., Ignaccolo M., Pluchino A., Simulating participatory urban freight transport policy-making: Accounting for heterogeneous stakeholders' preferences and interaction effects, Transp. Res. Part E Logist. Transp. Rev, 103, pp. 69-86, (2017); Marcucci E., Gatta V., Le Pira M., Gamification design to foster stakeholder engagement and behavior change: An application to urban freight transport, Transp. Res. Part A Policy Pract, 118, pp. 119-132, (2018); Marcucci E., Gatta V., Le Pira M., Carrocci C.S., Pieralice E., Connected shared mobility for passengers and freight: Investigating the potential of crowdshipping in urban areas, Proceedings of the 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems, pp. 839-843, (2017); Punel A., Stathopoulos A., Modeling the acceptability of crowdsourced goods deliveries: Role of context and experience effects, Transp. Res. Part E, 105, pp. 18-38, (2017); Punel A., Ermagun A., Stathopoulos A., Studying determinants of crowd-shipping use, Travel Behav. Soc, 12, pp. 30-40, (2018); Yildiz B., Savelsbergh M., Service and Capacity Planning in Crowd-Sourced Delivery; Slabinac M., Innovative solutions for a 'last-mile' delivery-A European experience, Proceedings of the 15th International Scientific Conference Business Logistics in Modern Management Osijek, pp. 111-129, (2015); Bensinger G., Amazon's next delivery drone: You, (2015); Marcucci E., Gatta V., Regional airport choice: Consumer behaviour and policy implications, J. Transp. Geogr, 19, pp. 70-84, (2011); Valeri E., Gatta V., Teobaldelli D., Polidori P., Barratt B., Fuzzi S., Maione M., Modelling individual preferences for environmental policy drivers: Empirical evidence of Italian lifestyle changes using a latent class approach, Environ. Sci. Policy, 65, pp. 65-74, (2016); Evangelinos C., Tscharaktschiew S., Marcucci E., Gatta V., Pricing workplace parking via cash-out: Effects on modal choice and implications for transport policy, Transp. Res. Part A Policy Pract, 113, pp. 369-380, (2018); Marcucci E., Delle Site P., Gatta V., Pompetti P., Ex-ante acceptability of road pricing and modal shift extimation: The case of Rome, Sci. Reg, 17, pp. 477-504, (2018); Alessandrini A., Site P.D., Gatta V., Marcucci E., Zhang Q., Investigating users' attitudes towards conventional and automated buses in twelve European cities, Int. J. Transp. Econ, 43, pp. 413-436, (2016); Felici G., Gatta V., The Analysis of Service Quality through Stated Preference Models and Rule-Based Classification, Mathematical Methods for Knowledge Discovery and Data Mining, pp. 65-81, (2007); Gatta V., Marcucci E., Urban freight transport and policy changes: Improving decision makers' awareness via an agent-specific approach, Transp. Policy, 36, pp. 248-252, (2014); Marcucci E., Gatta V., How Good are Retailers in Predicting Transport Providers' Preferences for Urban Freight Policies?. And Vice Versa?, Transp. Res. Procedia, 12, pp. 193-202, (2016); Gatta V., Marcucci E., Le Pira M., Scaccia L., Site P.D., Willingness to pay measures to tailor policies and foster stakeholder acceptability in urban freight transport, Sci Reg, 17, pp. 351-370, (2018); Le Pira M., Marcucci E., Gatta V., Ignaccolo M., Inturri G., Pluchino A., Towards a decision-support procedure to foster stakeholder involvement and acceptability of urban freight transport policies, Eur. Transp. Res. Rev, 9, (2017); Le Pira M., Marcucci E., Gatta V., Inturri G., Ignaccolo M., Pluchino A., Integrating discrete choice models and agent-based models for ex-ante evaluation of stakeholder policy acceptability in urban freight transport, Res. Transp. Econ, 64, pp. 13-25, (2017); Le Pira M., Marcucci E., Gatta V., Role-playing games as a mean to validate agent-based models: An application to stakeholder-driven urban freight transport policy-making, Transp. Res. 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Manag, 6, (2014); Ntziachristos L., Gkatzoflias D., Kouridis C., Samaras Z., COPERT: A European Road Transport Emission Inventory Model, Environmental Science and Engineering, pp. 491-504, (2009); Guerrieri M., Corriere F., Rizzo G., Casto B., Scaccianoce G., Improving the Sustainability of Transportation: Environmental and Functional Benefits of Right Turn By-Pass Lanes at Roundabouts, Sustainability, 7, pp. 5838-5856, (2015); Carteni A., Processi Decisionali e Pianificazione dei Trasporti, (2016); Improvements to the Definition of Lifetime Mileage of Light Duty Vehicles & Handbook on External Costs of Transport, (2014); Guida Operativa Alla Valutazione ex Ante Degli Investimenti Pubblici, (2016); Litman T., Climate Change Emission Valuation for Transportation Economic Analysis; Transport and Environmental Scenarios for Sustainable Urban Transport; (2014); Cantillo V., Amaya J., Ortuzar J.D., Thresholds and indifference in stated choice surveys, Transp. Res. Part B Methodol, 44, pp. 753-763, (2010); Gori S., Nigro M., Petrelli M., Walkability Indicators for Pedestrian-Friendly Design, Transp. Res. Rec. J. Transp. Res. Board, 2464, pp. 38-45, (2014); Carrese S., Giacchetti T., Nigro M., Patella S.M., An innovative car sharing electric vehicle system: An Italia experience, WIT Trans. Built Environ, 176, pp. 245-252, (2017); Carrese S., Giacchetti T., Patella S.M., Petrelli M., Real time ridesharing: Understanding user behavior and policies impact: Carpooling service case study in Lazio Region, Italy, Proceedings of the 2017 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS), (2017); L'eCommerce B2c in Italia: Le Prime Evidenze per il 2016, Osservatorio eCommerce B2c, (2016); L'eCommerce B2c in Italia: Le Prime Evidenze per il 2017, Osservatorio eCommerce B2c, (2017); Luci e Ombre del Commercio Online in Italia, (2017)","V. Gatta; Department of Political Science, Roma Tre University, Rome, Via Gabriello Chiabrera 199, 00145, Italy; email: valerio.gatta@uniroma3.it",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85059345583"]
["Davidaviciene V.; Raudeliuniene J.; Tvaronaviciene M.; Kaušinis J.","Davidaviciene, Vida (35368051300); Raudeliuniene, Jurgita (22938762700); Tvaronaviciene, Manuela (10041082800); Kaušinis, Justinas (57208029501)","35368051300; 22938762700; 10041082800; 57208029501","The importance of security aspects in consumer preferences in electronic environment",2019.0,"Journal of Security and Sustainability Issues",8.0,3.0,null,399.0,411.0,12.0,19.0,"10.9770/jssi.2019.8.3(9)","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85063649588&doi=10.9770%2fjssi.2019.8.3%289%29&partnerID=40&md5=d0682e3e800fed26610f962e2011d259","Vilnius Gediminas Technical University, Sauletekio al. 11, Vilnius, Lithuania","Davidaviciene V., Vilnius Gediminas Technical University, Sauletekio al. 11, Vilnius, Lithuania; Raudeliuniene J., Vilnius Gediminas Technical University, Sauletekio al. 11, Vilnius, Lithuania; Tvaronaviciene M., Vilnius Gediminas Technical University, Sauletekio al. 11, Vilnius, Lithuania; Kaušinis J., Vilnius Gediminas Technical University, Sauletekio al. 11, Vilnius, Lithuania","Organizations have to face both the opportunities that the technologies provide and the challenges that they create in the local or global market as the consumer behavior in the electronic environment is different from the behavior in an actual shop, therefore it is important to not only understand the changing needs of the customers, the factors that influence their behavior but also to choose suitable strategies while trying to satisfy these needs taking in consideration security issues. For this reason, an important purpose of this study is to indicate the factors that determine the behavior of an e-shop customer by conducting a pilot study in Lithuania. The research identified the key factors of consumer behavior in an e-shop. To establish factors determining the online shop customer preferences, five factor groups were identified on the basis of empirical research: product (service) characteristics, delivery, methods of payment, service quality and web page functionality characteristics. The results of the structured consumer survey showed that the factors that positively influence the decision to buy goods online are lower cost, less time consumption, an ability to make an order at any time of the day, and a larger range of products. The key factors that negatively affect the online shopping are product quality, delivery costs, security aspects, delivery time, and complicated online shopping process. The main problem areas faced by online shoppers were delays in product delivery, product quality, insufficient choice of payment methods, difficult return procedures, too little information about the product. After performing the correlation regression analysis of the structured survey, the following relationships are established: the frequency of online shopping is significantly correlated with the product's compliance with expectations, which indicates that the customers who were satisfied with the quality of online products, more often shop on the Internet. © 2019, General Jonas Zemaitis Military Academy of Lithuania.","Behavior; Behavior influencing factors; Consumer behaviour; E-commerce; Multiple criteria assessment",{"$nulls":7},"Aghaei S., Nematbakhsh M.A., Farsani H.K., Evolution of the world wide web: from WEB 1.0 TO WEB 4.0, International Journal of Web & Semantic Technology (IJWesT), 3, 1, pp. 1-10, (2012); Ahmed R.R., Vveinhardt J., Streimikiene D., Interactive digital media and impact of customer attitude and technology on brand awareness: evidence from the South Asian countries, Journal of Business Economics and Management, 18, 6, pp. 1115-1134, (2017); Asadabadi M.R., A Markovian-QFD approach in addressing the changing priorities of the customer needs, International Journal of Quality & Reliability Management, 33, 8, pp. 1062-1075, (2016); Benesova D., Husek M., Factors for efficient use of information and communication technologies influencing sustainable position of service enterprises in Slovakia, Entrepreneurship and Sustainability Issues, 6, 3, pp. 1082-1094, (2019); Banyte J., Tarute A., Taujanskyte I., Customer engagement into value creation: determining factors and relations with loyalty, Engineering Economics, 25, 5, pp. 568-577, (2014); Barnes S.J., Bauer H.H., Neumann M.M., Huber F., Segmenting cyberspace: a customer typology for the internet, European Journal of Marketing, 41, 2, pp. 71-93, (2014); Barnes S.J., Pressey A.D., Who needs cyberspace? Examining drivers of needs in second life, Internet Research, 21, 3, pp. 236-254, (2011); Barnett G., Kwon H.K., Stefanone M.A., Social network influence on online behavioral choices: exploring group formation on social network sites, American Behavioral Scientist, 58, 10, pp. 1345-1360, (2014); Berkowitz E.N., Kerin R.A., Hartley S.W., Rudelius W., Interactive Marketing and Electronic Commerce, (2000); Berkowitz E.N., Kerin R.A.W.H. S., Marketing, (1992); Cao H., Jiang J., Oh L., Li H., Liao X., Chen Z., A Maslow's hierarchy of needs analysis of social networking services continuance, Journal of Service Management, 24, 2, pp. 170-190, (2013); Chaffey D., Ellis-Chadwick F., Digital Marketing: Strategy, Implementation and Practice, (2012); Chai A., Moneta A., Back to Engel? 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Modeling historical influences on post-adoption era Internet consumer behaviors, Journal of Business Research, 63, 9-10, pp. 950-956, (2010); Taormina R.J., Gao J.H., Maslow and the motivation hierarchy: measuring satisfaction of the needs, American Journal of Psychology Summer, 126, 2, pp. 155-177, (2013); Thompson N., Ravindran R., Nicosia S., Government data does not mean data governance: Lessons learned from a public sector application audit, Government Information Quarterly, 32, 3, pp. 316-322, (2015); Tiago M.T., Tiago F., Revisiting the impact of integrated internet marketing on firms' online performance: European evidences, Procedia Technology, 5, pp. 418-426, (2012); Turban E., Strauss J., Lai L., Social Commerce-Marketing, (2016); Vo L., Van Le H.T., Le D.V., Phung M.T., Wang Y.H., Yang F.J., Customer satisfaction and corporate investment policies, Journal of Business Economics and Management, 18, 2, pp. 202-223, (2017); Zavadskas E.K., Turskis Z., Vilutiene T., Lepkova N., Integrated group fuzzy multi-criteria model: Case of facilities management strategy selection, Expert Systems with Applications, 82, pp. 317-331, (2017); Zheng C., Yu X., Jin Q., How user relationships affect user perceived value propositions of enterprises on social commerce platforms, Information Systems Frontiers, 19, 6, pp. 1261-1271, (2017)",null,null,"General Jonas Zemaitis Military Academy of Lithuania",{"$nulls":5},2.0297017E7,null,null,null,"English","J. Secur. Sustainability Issues","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85063649588"]
["Farooq Q.; Fu P.; Hao Y.; Jonathan T.; Zhang Y.","Farooq, Qamar (57201616661); Fu, Peihua (17345758000); Hao, Yunhong (35175916100); Jonathan, Tchamy (57205588691); Zhang, Yanni (57204041594)","57201616661; 17345758000; 35175916100; 57205588691; 57204041594","A Review of Management and Importance of E-Commerce Implementation in Service Delivery of Private Express Enterprises of China",2019.0,"SAGE Open",9.0,1.0,{"$nulls":4},40.0,"10.1177/2158244018824194","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85060579359&doi=10.1177%2f2158244018824194&partnerID=40&md5=2c8afd2a51197f4fa755ad9dfa428f7e","Zhejiang Gongshang University, Hangzhou, China; Riphah International University, Islamabad, Pakistan","Farooq Q., Zhejiang Gongshang University, Hangzhou, China, Riphah International University, Islamabad, Pakistan; Fu P., Zhejiang Gongshang University, Hangzhou, China; Hao Y., Zhejiang Gongshang University, Hangzhou, China; Jonathan T., Zhejiang Gongshang University, Hangzhou, China; Zhang Y., Zhejiang Gongshang University, Hangzhou, China","Express delivery is the growing industry that provides the means to facilitate people across the world by shipping goods and documents from one place to another. The profitability of sole companies is based on price, quality, reliability, and services. However, the impact of corporate value capture strategies on the overall sustainability of the value creation process is rarely discussed in the existing literature. This review article is aimed to develop a model to relate the effectiveness and efficiency of managerial processes with the quality of service delivery, employment, and customer retention. Extensive literature review establishes that Advancement in E-commerce Infrastructure strengthens the relationship of good management and customer retention. The present article further explains the mediation of automation in supply chain management in our model. This article has a theoretical contribution to the extant literature on e-commerce and supply chain management along with practical implication for taking care of contemporary techniques to automate the processes for success in Private Express Enterprise business, particularly for the managers, responsible for corporate performance. © The Author(s) 2019.","advance e-commerce; corporate social responsibility; customer retention; good management; recruitment",{"$nulls":5},"Key Research Center of Humanities and Social Sciences in Universities of Zhejiang Province, (JYTgs20151104); Natural Science Foundation of Zhejiang Province, ZJNSF, (LQ19G020004); Science and Technology Program of Zhejiang Province, (LGF18G010002); Humanities and Social Sciences Youth Foundation, Ministry of Education of the People's Republic of China, (17YJA630015)","The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by the Science and Technology Project of Zhejiang Province (No. LGF18G010002), the Humanities and Social Sciences Foundation of the Ministry of Education (No. 17YJA630015), the Natural Science Foundation of Zhejiang Province (LQ19G020004), and the Key Research Center of Humanities and Social Sciences in Universities of Zhejiang Province (JYTgs20151104).","Al-Obaidan A.M., Scully G.W., Efficiency differences between private and state-owned enterprises in the international petroleum industry, Applied Economics, 24, pp. 237-246, (1992); Amighini A., Rabellotti R., Sanfilippo M., Do Chinese state-owned and private enterprises differ in their internationalization strategies?, China Economic Review, 27, pp. 312-325, (2013); Beeri I., Uster A., Vigoda-Gadot E., Does performance management relate to good governance? 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Lam L.L., Beyond credibility of doing business in China: Strategies for improving corporate citizenship of foreign multinational enterprises in China, Journal of Business Ethics, 87, pp. 137-146, (2009); Liao K.H., Huang I.S., Impact of vision, strategy, and human resource on nonprofit organization service performance, Procedia—Social and Behavioral Sciences, 224, pp. 20-27, (2016); Masabo H.O., Self–service technology and customer satisfaction in commercial Banks in Kenya, (2013); Mitrega M., Pfajfar G., Business relationship process management as company dynamic capability improving relationship portfolio, Industrial Marketing Management, 46, pp. 193-203, (2015); Pan Y., Tian Y., Liu X., Gu D., Hua G., Urban big data and the development of city intelligence, Engineering, 2, pp. 171-178, (2016); Rashid N.R.N.A., Khalid S.A., Rahman N.I.A., Environmental Corporate Social Responsibility (ECSR): Exploring its influence on customer loyalty, Procedia Economics & Finance, 31, pp. 705-713, (2015); Santarelli E., D'altri S., The diffusion of e-commerce among SMEs: Theoretical implications and empirical evidence, Small Business Economics, 21, pp. 273-283, (2003); Sinkovics N., Hoque S.F., Sinkovics R.R., Supplier strategies and routines for capability development: Implications for upgrading, Journal of International Management, 24, pp. 348-368, (2018); Song M., Ai H., Li X., Political connections, financing constraints, and the optimization of innovation efficiency among China’s private enterprises, Technological Forecasting & Social Change, 92, pp. 290-299, (2015); Tang S., Deng G., Based on the theory of grey system to forecast China’s business volume of express services, Modern Economy, 6, pp. 283-288, (2015); Xin K.R., Inside Chinese business: A guide for managers worldwide, The Academy of Management Review, 27, pp. 127-129, (2002); Yang Y.H., Hui Y.V., Leung L.C., Chen G., An analytic network process approach to the selection of logistics service providers for air cargo, Journal of the Operational Research Society, 61, pp. 1365-1376, (2010); Zhongcheng L.I.U., Shiying H.U., Study on the evaluation index system of international competitiveness of Chinese private express delivery enterprises, International Business and Management, 14, 3, pp. 27-32, (2017); Zhu X.H., Analysis of the human resource management based on private express enterprise, Journal of Nanchang College of Education, (2014)","P. Fu; Zhejiang Gongshang University, Hangzhou, China; email: edwardfupeihua@hotmail.com",null,"SAGE Publications Inc.",{"$nulls":5},2.158244E7,null,null,null,"English","SAGE Open","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85060579359"]
["Colajanni G.; Daniele P.","Colajanni, Gabriella (57201409532); Daniele, Patrizia (7003415716)","57201409532; 7003415716","A convex optimization model for business management",2018.0,"Journal of Convex Analysis",25.0,2.0,null,487.0,514.0,27.0,6.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85046275474&partnerID=40&md5=ce70be3b209bdbf32013a1b58ddc4128","Dept. of Mathematics and Computer Science, University of Catania, Viale A. Doria 6, Catania, 95125, Italy","Colajanni G., Dept. of Mathematics and Computer Science, University of Catania, Viale A. Doria 6, Catania, 95125, Italy; Daniele P., Dept. of Mathematics and Computer Science, University of Catania, Viale A. Doria 6, Catania, 95125, Italy","We first present a supply chain network model with four different tiers of decision makers (suppliers of raw materials, manufacturers, retailers, demand markets), we derive the optimality conditions and the associated variational inequality problem for the representatives of each level and for the total supernetwork and focusing our attention on the behavior of the manufacturers. Then, in a more detailed model, we introduce the distinction by brand of the products of manufacturers and we add the e-commerce to the traditional physical links for the shipments from manufacturers to demand markets. Moreover, to the forward chain we add a reverse chain model where manufacturers, using the unsold product given back from retailers, after reworking, produce a new commodity which will be sold to new retailers. Also in this case we study the behavior of manufacturers obtaining their optimality conditions and the governing variational formulation. Finally, we apply our model to a concrete company (Valle del Dittaino, Italy), obtaining, after introducing additional constraints, the optimal amount of raw material, the optimal shipment of new product as well as the optimal production periods. © Heldermann Verlag.","Lagrange multipliers; Reverse logistics; Supply chains; Variational inequalities",{"$nulls":7},"Barbagallo A., Daniele P., Maugeri A., Variational formulation for a general dynamic financial equilibrium problem: Balance law and liability formula, Nonlinear Analysis: Theory, Methods Appl, 75, pp. 1104-1123, (2012); Daniele P., Evolutionary variational inequalities and economic models for demand supply markets, M3AS: Mathematical Models and Methods in Applied Sciences, 4, 13, pp. 471-489, (2003); Daniele P., Time-dependent spatial price equilibrium problem: Existence and stability results for the quantity formulation model, J. Global Optimization, 28, pp. 283-295, (2004); Daniele P., Dynamic Networks and Evolutionary Variational Inequalities, (2006); Daniele P., Evolutionary variational inequalities and applications to complex dynamic multi-level models, Transport. Res. Part E, 46, pp. 855-880, (2010); Kinderlehrer D., Stampacchia G., Variational Inequalities and their Applications, (1980); Matsypura D., Nagurney A., Liu Z., Modeling of electric power supply chain networks with fuel suppliers via variational inequalities, Internat. J. Emerging Electric Power Systems, 8, 1, (2007); Maugeri A., Raciti F., On existence theorems for monotone and nonmonotone variational inequalities, J. Convex Analysis, 16, 3-4, pp. 899-911, (2009); Nagurney A., Dong J., Supernetworks: Decision-Making for the Information Age, (2002); Nagurney A., Toyasaki F., Reverse supply chain management and electronic waste recycling: A multi-tiered network equilibrium framework for e-cycling, Transportation Research Part E, 41, pp. 1-28, (2005); Sodhi M.S., Reimer B., Models for recycling electronics end-of-life products, OR Spectrum, 23, 1, pp. 97-115, (2001); Toyasaki F., Daniele P., Wakolbinger T., A variational inequality formulation of equilibrium models for end-of-life products with nonlinear constraints, Eur. J. Oper. Research, 236, 1, pp. 340-350, (2014); Paksoy T., Ozceylan E., Gokcen H., Supply chain optimisation with assembly line balancing, Internat. J. Production Research, 50, 11, pp. 3115-3136, (2012); Wagner H.M., Whitin T.M., Dynamic version of the economic lot size model, Management Science, 9, 1, pp. 89-96, (1958)",null,null,"Heldermann Verlag",{"$nulls":5},9446532.0,null,null,null,"English","J. Convex Anal.","Article","Final",null,"Scopus","2-s2.0-85046275474"]
["Alhujaylan A.I.; Hosny M.I.","Alhujaylan, Abeer I. (57208797563); Hosny, Manar I. (19638353300)","57208797563; 19638353300","A GRASP-based solution construction approach for the multi-vehicle profitable pickup and delivery problem",2019.0,"International Journal of Advanced Computer Science and Applications",10.0,4.0,null,111.0,120.0,9.0,6.0,"10.14569/ijacsa.2019.0100412","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85065843629&doi=10.14569%2fijacsa.2019.0100412&partnerID=40&md5=5d51379f06475021cad198d78bd31ff5","Computer Science Department, College of Computer and Information Sciences (CCIS), King Saud University (KSU), Riyadh, Saudi Arabia","Alhujaylan A.I., Computer Science Department, College of Computer and Information Sciences (CCIS), King Saud University (KSU), Riyadh, Saudi Arabia; Hosny M.I., Computer Science Department, College of Computer and Information Sciences (CCIS), King Saud University (KSU), Riyadh, Saudi Arabia","With the advancement of e-commerce and Internet shopping, the high competition between carriers has made many companies rethink their service mechanisms to customers, in order to ensure that they stay competitive in the market. Therefore, companies with limited resources focus on serving only customers who provide high profits at the lowest possible cost. The Multi-Vehicle Profitable Pickup and Delivery Problem (MVPPDP) is a vehicle routing problem and one variant of the Selective Pickup and Delivery Problem (SPDP) that is considered to plan the services for these types of companies. The MVPPDP aims to serve only the profitable customers, where the products are transformed from a selection of pickup customers to the corresponding delivery customers, within a given travel time limit. In this paper, we utilize the construction phase of the well-known Greedy Randomized Adaptive Search Procedure (GRASP) to build initial solutions for the MVPPDP. The performance of the proposed method is compared with two greedy construction heuristics that were previously used in the literature to build the initial solutions of the MVPPDP. The results proved the effectiveness of the proposed method, where eight new initial solutions are obtained for the problem. Our approach is especially beneficial for building a population of solutions that combine both diversity and quality, which can help to obtain good solutions in the improvement phase of the problem. © 2018 The Science and Information (SAI) Organization Limited.","Greedy randomized adaptive search procedure; Metaheuristic algorithms; Multi-vehicle profitable pickup and delivery problem; Selective pickup and delivery problem","Electronic commerce; Heuristic algorithms; Heuristic methods; Pickups; Sales; Travel time; Vehicle routing; Vehicles; Construction approaches; E- commerces; Greedy randomized adaptive search procedure; Initial solution; Meta-heuristics algorithms; Multi-vehicle profitable pickup and delivery problem; Multi-vehicles; Pickup and delivery problems; Selective pickup and delivery problem; Profitability",{"$nulls":6},"Toth, Paolo and Vigo, The vehicle routing problem, (2002); Parragh R.F., Sophie N., Doerner K.F., A survey on pickup and delivery problems,, J. für Betriebswirtschaft, 58, 1, pp. 21-51, (2008); Saha J., An algorithm for bus scheduling problems,, J. Oper. Res. Soc, 21, 4, pp. 463-474, (1970); uceer U.Y.A.O., A truck loading problem,, Comput. Ind. Eng, 58, 4, pp. 766-773, (2010); Yan M.-W., Shangyao W., Sin-Siang W., A model with a solution algorithm for the cash transportation vehicle routing and scheduling problem,, Comput. Ind. Eng, 63, 2, pp. 464-473, (2012); Barnhart P.H., Cynthia J., Hong V., Railroad blocking: A network design application,, Oper. Res, 48, 4, pp. 603-614, (2000); Diaz-Parra R.A., Ruiz-Vanoye J.A., Bernabe Loranca B., Fuentes-Penna A., Barrera-Camara J., A survey of transportation problems,, J. Appl. Math., vol. 2014, (2014); Cornillier J.R.F., Boctor F.F., Laporte G., An exact algorithm for the petrol station replenishment problem,, J. Oper. Res. Soc, 59, 5, pp. 607-615, (2008); Zhu R.C.C., Hu J.Q., Wang F., Xu Y., On the tour planning problem,, Ann. Oper. Res, 192, pp. 67-86, (2012); Kodjak D., Policy discussion-heavy-duty truck fuel economy,, 10th Diesel Engine Emiss. Reduct, (2004); Gansterer M., Hartl R.F., Vetschera R., The cost of incentive compatibility in auction-based mechanisms for carrier collaboration,, Networks, Jun, (2018); Lin C., Choy K.L., Ho G.T.S., Chung S.H., Lam H.Y., Survey of Green Vehicle Routing Problem: Past and future trends,, Expert Syst. Appl, 41, 4, pp. 1118-1138, (2014); Prive J., Renaud J., Boctor F., Laporte G., Solving a vehicle-routing problem arising in soft-drink distribution,, J. Oper. Res. Soc, 57, 9, pp. 1045-1052, (2006); Aras N., Aksen D., Tugrul Tekin M., Selective multi-depot vehicle routing problem with pricing,, Transp. Res. Part C Emerg. Technol, 19, 5, pp. 866-884, (2011); Gribkovskaia I., Laporte G., Shyshou A., The single vehicle routing problem with deliveries and selective pickups,, Comput. Oper. Res, 35, 9, pp. 2908-2924, (2008); Ting C.-K., Liao X.-L., The selective pickup and delivery problem: Formulation and a memetic algorithm,, Int. J. Prod. Econ, 141, 1, pp. 199-211, (2013); Liao X.-L., Ting C.-K., An evolutionary approach for the selective pickup and delivery problem,, Evolutionary Computation (CEC), 2010 IEEE Congress on, IEEE, pp. 1-8, (2010); Ho W.Y., Sin C., GRASP with path relinking for the selective pickup and delivery problem,, Expert Syst. Appl., vol. 51, pp. 14-25, Jun, (2016); Coelho I.M., Munhoz P.L.A., Ochi L.S., Souza M.J.F., Bentes C., Farias R., An integrated CPU-GPU heuristic inspired on variable neighbourhood search for the single vehicle routing problem with deliveries and selective pickups,, Int. J. Prod. Res, 54, 4, pp. 945-962, (2016); Coelho I.M., Munhoz P.L.A., Haddad M.N., Souza M.J.F., Ochi L.S., A hybrid heuristic based on General Variable Neighborhood Search for the Single Vehicle Routing Problem with Deliveries and Selective Pickups,, Electron. Notes Discret. Math., vol. 39, pp. 99-106, Dec, (2012); Bruck B.P., dos Santos A.G., Arroyo J.E.C., Hybrid metaheuristic for the single vehicle routing problem with deliveries and selective pickups,, Evolutionary Computation (CEC), 2012 IEEE Congress on, IEEE, pp. 1-8, (2012); Gansterer M., Kucuktepe M., Hartl R.F., The multi-vehicle profitable pickup and delivery problem,, OR Spectr, 39, 1, pp. 303-319, (2017); Feo M.G., Thomas A., Greedy randomized adaptive search procedures,, J. Glob. Optim, 6, 2, pp. 109-133, (1995); Talbi E.-G., Metaheuristics: from design to implementation, (2009); Priore-Moreno P., Pino-Diez R., Martinez-Carcedo C., Villanueva-Madrileno V., Fernandez-Quesada I., Application of GRASP methodology to vehicle routing problem,, in Proceedings on the International Conference on Artificial Intelligence (ICAI), (2012); Layeb A., Ammi M., Chikhi S., A GRASP algorithm based on new randomized heuristic for vehicle routing problem,, J. Comput. Inf. Technol, 21, 1, pp. 35-46, (2013); Duhamel C., Christophe L., Philippe P., Christian P., A GRASP×ELS approach for the capacitated location-routing problem,, Comput. Oper. Res, 37, 11, pp. 1912-1923, (2010); Marinakis Y., Multiple Phase Neighborhood Search-GRASP for the Capacitated Vehicle Routing Problem,, Expert Syst. Appl, 39, 8, pp. 6807-6815, (2012); Haddad M., AN EFFICIENT HEURISTIC FOR ONE-TO-ONE PICKUP AND DELIVERY PROBLEMS,, Fluminense Federal Uneversity, (2017); Gutierrez-Jarpa G., Desaulniers G., Laporte G., Marianov V., A branch-and-price algorithm for the Vehicle Routing Problem with Deliveries, Selective Pickups and Time Windows,, Eur. J. Oper. Res, 206, 2, pp. 341-349, (2010); Qiu S., Xiaoqiu F., A MULTI-VEHICLE PROFIT-MAXIMIZING PICKUP AND DELIVERY SELECTION PROBLEM WITH TIME WINDOWS.; Baniamerian A., Bashiri M., Tavakkoli-Moghaddam R., Modified variable neighborhood search and genetic algorithm for profitable heterogeneous vehicle routing problem with cross-docking,, Appl. Soft Comput, 75, pp. 441-460, (2019); Wen M., Larsen J., Clausen J., Cordeau J., Laporte G., Vehicle routing with cross-docking,, J. Oper. Res. Soc, 60, 12, pp. 1708-1718, (2009); Archetti C., Speranza M.G., Vigo D., Chapter 10: Vehicle Routing Problems with Profits,, Vehicle Routing: Problems, Methods, and Applications, Second Edition, pp. 273-297, (2014); Toth D., Paolo V., Vehicle routing: problems, methods, and applications, (2014); Vidal P.H., Thibaut M., Nelson O., Satoru L., Penna V., Large neighborhoods with implicit customer selection for vehicle routing problems with profits,, Transp. Sci, 50, 2, pp. 720-734, (2015); Archetti C., Bianchessi N., Speranza M.G., Optimal solutions for routing problems with profits,, Discret. Appl. Math, 161, 4-5, pp. 547-557, (2013); Archetti M.G., Claudia F., Dominique H., Alain S., The capacitated team orienteering and profitable tour problems,, J. Oper. Res. Soc, 60, 6, pp. 831-842, (2009); Lahyani R., Khemakhem M., Semet F., Heuristics for rich profitable tour problems,, Modeling, Simulation and Applied Optimization, 2013 5th International Conference on, pp. 1-3, (2013); Kucuktepe M., A General Variable Neighbourhood Search Algorithm for the Multi-Vehicle Profitable Pickup and Delivery Problem,, University of Vienna, (2014)",null,null,"Science and Information Organization",{"$nulls":5},"2158107X",null,null,null,"English","Intl. J. Adv.  Comput. Sci. Appl.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85065843629"]
["Hossain M.A.; Rahman S.; Chowdhury T.A.; Chan C.; Yang X.; Su Q.","Hossain, Mohammad Alamgir (57189523491); Rahman, Shams (7402514584); Chowdhury, Tamgid Ahmed (55145642100); Chan, Caroline (55119829200); Yang, Xiaoyan (57202039663); Su, Qingxin (57202039356)","57189523491; 7402514584; 55145642100; 55119829200; 57202039663; 57202039356","How signaling mechanisms reduce “lemons” from online group buying (OGB) markets? A study of China",2018.0,"International Journal of Physical Distribution and Logistics Management",48.0,7.0,null,658.0,681.0,23.0,17.0,"10.1108/IJPDLM-02-2017-0113","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85046905387&doi=10.1108%2fIJPDLM-02-2017-0113&partnerID=40&md5=c6b15dffa76edde92d398b00398c2e1c","School of Business IT and Logistics, RMIT University, Melbourne, Australia; School of Business and Economics, North South University, Dhaka, Bangladesh; School of International and Continuing Education, Shanghai University of International Business and Economics, Shanghai, China; School of Information Systems, Shanghai University of International Business and Economics, Shanghai, China","Hossain M.A., School of Business IT and Logistics, RMIT University, Melbourne, Australia; Rahman S., School of Business IT and Logistics, RMIT University, Melbourne, Australia; Chowdhury T.A., School of Business and Economics, North South University, Dhaka, Bangladesh; Chan C., School of Business IT and Logistics, RMIT University, Melbourne, Australia; Yang X., School of International and Continuing Education, Shanghai University of International Business and Economics, Shanghai, China; Su Q., School of Information Systems, Shanghai University of International Business and Economics, Shanghai, China","Purpose: A major transformation in retail logistics over the few years is backed by enormous improvements in internet technologies. It is now easy for e-retailers to entertain delivery progression, or consumers can share use-experience with future customers and thereby reducing information asymmetry. The purpose of this paper is to investigate the effect of different signals on consumer behavior in the presence of information asymmetry, in the context of online group buying (OGB) markets in China. Design/methodology/approach: Based on the lemon market theory (LMT) and signaling theory, the study develops a research model of the OGB consumers’ context in China, which is validated using data from an online survey. A total of 528 responses are used for data analysis applying structural equation modeling technique. Findings: The findings of the study show that perceived vendor quality (PVQ) and perceived product quality (PPQ) have significantly positive effects on intention to purchase from OGB websites. PVQ is associated with perceived reputation and perceived trustworthiness (PT) of vendor, and the determinants of PPQ are quality assurance information of products, and information about mer-chants. Further, PT has a mediating effect, while asymmetry of information has a moderating effect. Research limitations/implications: The research model is valid as a generic OGB model that can be investigated in other contexts to understand the generalizability of the findings. Future research is needed to incorporate additional relevant factors (e.g. price, advertising activity/investments) that may help increase the acceptability of the model to a wide range of e-commerce contexts. Two of the control variables (gender and prior internet experience) were found to be significant; this could be further examined in future studies to determine the relative impact on each causal relationship. Originality/value: Whereas prior studies in the domain of consumer service proposed different signaling mechanisms that were believed to eliminate information asymmetry from a market, the study sheds light on the effectiveness of the signals in the OGB context. This is a unique effort that applies and extends LMT and signaling theory in OGB context by theorizing the associated dimensions and their causal effects. © 2018, Emerald Publishing Limited.","China; Consumer behaviour; Information asymmetry; Lemon market theory; Online group buying; Signaling theory",{"$nulls":7},"Aiken L.S., Stephen G., Multiple Regression: Testing and Interpreting Interactions, (1981); Akerlof G., The market for “lemons”: qualitative uncertainty and market mechanism, Quarterly Journal of Economics, 84, 3, pp. 488-500, (1970); Akter S., D'Ambra J., Ray P., Trustworthiness in mHealth information services: an assessment of a hierarchical model with mediating and moderating effects using partial least squares (PLS), Journal of the American Society for Information Science and Technology, 62, 1, pp. 100-116, (2011); Andreassen T.W., Lanseng E., The principal’s and agents’ contribution to customer loyalty within an integrated service distribution channel: an external perspective, European Journal of Marketing, 31, 7, pp. 487-503, (1997); 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Chinese consumers’ online group buying, Journal of International Consumer Marketing, 27, 1, pp. 54-68, (2015); Zhang Z., Gu C., Effects of consumer social interaction on trust in online group-buying contexts: an empirical study in China, Journal of Electronic Commerce Research, 16, 1, pp. 1-21, (2015); Zhang Z., Zhang Z., Wang F., Law R., Li D., Factors influencing the effectiveness of online group buying in the restaurant industry, International Journal of Hospitality Management, 35, pp. 237-245, (2013); Zhao X., Lynch J.G., Chen Q., Reconsidering Baron and Kenny: myths and truths about mediation analysis, Journal of Consumer Research, 37, 2, pp. 197-206, (2010)","S. Rahman; School of Business IT and Logistics, RMIT University, Melbourne, Australia; email: shams.rahman@rmit.edu.au",null,"Emerald Group Holdings Ltd.",{"$nulls":5},9600035.0,null,null,null,"English","Int. J. Phys. Distrib. Logist. Manage.","Article","Final",null,"Scopus","2-s2.0-85046905387"]
["Pferschy U.; Schauer J.","Pferschy, Ulrich (6603829867); Schauer, Joachim (35214011300)","6603829867; 35214011300","Order Batching and Routing in a Non-Standard Warehouse",2018.0,"Electronic Notes in Discrete Mathematics",69.0,null,null,125.0,132.0,7.0,13.0,"10.1016/j.endm.2018.07.017","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85051119074&doi=10.1016%2fj.endm.2018.07.017&partnerID=40&md5=a2d26b46734a6358d9df89b0f1a53a83","Department of Statistics and Operations Research, University of Graz, Graz, Austria","Pferschy U., Department of Statistics and Operations Research, University of Graz, Graz, Austria; Schauer J., Department of Statistics and Operations Research, University of Graz, Graz, Austria","We consider the retrieval of articles from a warehouse to fulfill customer orders of a large e-commerce business. The problem consists of an order batching phase, where orders are grouped together to be processed by one picking process, and a routing phase where the article locations of one batch are sequenced in a route of minimal length. Our application is characterized by several non-standard features concerning the warehouse structure as well as the storage strategy. We develope a heuristic solution algorithm based on a fairly general graph model. © 2018 Elsevier B.V.","order batching; order picking; routing; Warehouse logistics",{"$nulls":5},"COLIBRI Initiative of the University of Graz","1 Email: pferschy@uni-graz.at (corresponding author), supported by the COLIBRI Initiative of the University of Graz. 2 Email: joachim.schauer@uni-graz.at","Applegate D.L., Bixby R.E., Chvatal V., Cook W.J., The Traveling Salesman Problem: A Computational Study, (2006); Henn S., Order batching and sequencing for the minimization of the total tardiness in picker-to-part warehouses, Flexible Services and Manufacturing Journal, 27, pp. 86-114, (2015); Menendez B., Bustillo M., Pardo E.G., Duarte A., General Variable Neighborhood Search for the order batching and sequencing problem, European Journal of Operational Research, 263, pp. 82-93, (2017); Roodberger K.J., De Koster R., Routing order pickers in a warehouse with a middle aisle, European Journal of Operational Research, 133, pp. 32-43, (2001); Scholz A., Schubert D., Wascher G., Order picking with multiple pickers and due dates Simultaneous solution of order batching, batch assignment and sequencing, and picker routing problems, European Journal of Operational Research, 263, pp. 461-478, (2017); Scholz A., Wascher G., Order Batching and Picker Routing in manual order picking systems: the benefits of integrated routing, Central European Journal of Operations Research, 25, pp. 491-520, (2017); Theys C., Braysy O., Dullaert W., Raa B., Using a TSP heuristic for routing order pickers in warehouses, European Journal of Operational Research, 200, pp. 755-763, (2010); Valle C.A., Beasley J.E., da Cunha A.S., Optimally solving the joint order batching and picker routing problem, European Journal of Operational Research, 262, pp. 817-834, (2017)","U. Pferschy; Department of Statistics and Operations Research, University of Graz, Graz, Austria; email: pferschy@uni-graz.at",null,"Elsevier B.V.",{"$nulls":5},1.5710653E7,null,null,null,"English","Electron. Notes Discrete Math.","Article","Final",null,"Scopus","2-s2.0-85051119074"]
["Sarkar B.; Tayyab M.; Choi S.-B.","Sarkar, Biswajit (36806631400); Tayyab, Muhammad (57191958569); Choi, Seok-Beom (57183288500)","36806631400; 57191958569; 57183288500","Product channeling in an O2O supply chain management as power transmission in electric power distribution systems",2018.0,"Mathematics",7.0,1.0,4.0,null,null,null,12.0,"10.3390/math7010004","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85059457415&doi=10.3390%2fmath7010004&partnerID=40&md5=b39a8258e55dc395821d6782e367b6c5","Department of Industrial and Management Engineering, Hanyang University, Ansan, Gyeonggi-do, 155 88, South Korea; Department of International Business, Cheju Halla University, Jeju-do, 63092, South Korea","Sarkar B., Department of Industrial and Management Engineering, Hanyang University, Ansan, Gyeonggi-do, 155 88, South Korea; Tayyab M., Department of Industrial and Management Engineering, Hanyang University, Ansan, Gyeonggi-do, 155 88, South Korea; Choi S.-B., Department of International Business, Cheju Halla University, Jeju-do, 63092, South Korea","With the aim of delivering goods and services to customers, optimal delivery channel selection is a significant part of supply chain management. Several heuristics have been developed to solve the variants of distribution center allocation and vehicle routing problems. In reality, small-scale suppliers cannot afford research and development departments to optimize their distribution networks. In this context, this research work develops a model for an online to offline (O2O) supply chain management network of a small-scale household electric components manufacturer for delivering goods to its distribution centers and retailers. Retailers are acquired by the company through investment in the O2O channel of e-commerce. Electric power transmission and distribution is considered as representative of the product distribution network. A model is developed using a combination of the supply chain management technique and power transmission terminologies. The constrained linear programming model is solved through the linear programming tool of the LINGO optimization software and the global optimum results for the proposed quantity allocation problem are achieved. A numerical experiment is provided to illustrate the practical applicability of the model and the optimal results are analyzed for model robustness. © 2018 by the authors.","Customer acquisition cost; E-commerce; Electric power distribution; O2O channel; Supply chain management; Transshipments",{"$nulls":5},"National Research Foundation; National Research Foundation, NRF, (2017S1A2A2036758)","Funding text 1: This work was supported by the National Research Foundation Grant funded by the Korean Government. (NRF-2017S1A2A2036758); Funding text 2: Funding: This work was supported by the National Research Foundation Grant funded by the Korean Government. (NRF-2017S1A2A2036758).","Ghorbani A., Jokar M.R.A., A hybrid imperialist competitive-simulated annealing algorithm for a multisource multi-product location-routing-inventory problem, Comput. Ind. Eng, 101, pp. 116-127, (2016); Van Duin J.H.R., Tavasszy L.A., Taniguchi E., Real time simulation of auctioning and re-scheduling processes in hybrid freight markets, Transport. Res. B Meth, 41, pp. 1050-1066, (2007); Crainic T.G., Ricciardi N., Storchi G., Models for evaluating and planning city logistics systems, Transp. Sci, 43, pp. 432-454, (2009); Rosa G., Costa M.A., Robust functional analysis for fault detection in power transmission lines, Appl. Math. Model, 40, pp. 9067-9978, (2016); Yang S., Lu Y., Chau P.Y., Why do consumers adopt online channel? An empirical investigation of two channel extension mechanisms, Decis. Support Syst, 54, pp. 858-869, (2013); Cassab H., MacLachlan D.L., Interaction fluency: A customer performance measure of multichannel service, Int. J. Prod. Perform. 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Sci, 6, pp. 475-490, (1960); Sabri E.H., Beamon B.M., A multi-objective approach to simultaneous strategic and operational planning in supply chain design, Omega, 28, pp. 581-598, (2000); Nozick L.K., Turnquist M.A., Inventory, transportation, service quality and the location of distribution centers, Eur. J. Oper. Res, 129, pp. 362-371, (2001); Sarrafha K., Rahmati S.H., Niaki S.T., Zaretalab A., A bi-objective integrated procurement, production, and distribution problem of a multi-echelon supply chain network design: A. new tuned MOEA, Comput. Oper. Res, 54, pp. 35-51, (2015); Rudi N., Kapur S., Pyke D.F., A two-location inventory model with transshipment and local decision making, Manag. Sci, 47, pp. 1668-1680, (2001); Olsson F., Optimal policies for inventory systems with lateral transshipments, Int. J. Prod. 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Log, 3, pp. 291-302, (2000); Murali P., Ordonez F., Dessouky M.M., Facility location under demand uncertainty: Response to a large-scale bio-terror attack, Soc. Econ. Plan. Sci, 46, pp. 78-87, (2012); Chaiwuttisak P., Smith H., Wu Y., Potts C., Sakuldamrongpanich T., Pathomsiri S., Location of low-cost blood collection and distribution centres in Thailand, Oper. Res. Health Care, 9, pp. 7-15, (2016); Chen M.J., Hsu Y.F., Wu Y.C., Modified penalty function method for optimal social welfare of electric power supply chain with transmission constraints, Int. J. Electr. Power, 57, pp. 90-96, (2014); Tinney W.F., Hart C.E., Power flow solution by Newton's method, IEEE Trans. Power. Appl. Syst, PAS 86, pp. 1449-1460, (1967); Singh B., Mahanty R., Singh S.P., Optimal rescheduling of generators for congestion management and benefit maximization in a decentralized bilateral multi-transactions power network, Int. J. Emerg. Electr. Power Syst, 14, pp. 25-32, (2013); Bose S., Gayme D.F., Low S., Chandy K.M., Optimal power flow over tree networks, Proceedings of the IEEE 49th Annual Allerton Conference on Communication, pp. 1342-1348, (2011); Sivasubramani S., Swarup K.S., Sequential quadratic programming based differential evolution algorithm for optimal power flow problem, IET Gener. Transm. Dis, 5, pp. 1149-1154, (2011); Divshali P.H., Hosseinian S.H., Azadani E.N., Abedi M., Application of bifurcation theory in dynamic security constrained optimal dispatch in deregulated power system, Elect. Eng, 93, (2011); Sarkar B., Moon I., Improved quality, setup cost reduction, and variable backorder costs in an imperfect production process, Int. J. Prod. Econ, 155, pp. 204-213, (2014); Sarkar B., A production-inventory model with probabilistic deterioration in two-echelon supply chain management, Appl. Math. Model, 37, pp. 3138-3151, (2013); Sarkar B., An inventory model with reliability in an imperfect production process, Appl. Math. Comput, 218, pp. 4881-4891, (2012); Sarkar B., Sana S.S., Chaudhuri K., Optimal reliability, production lotsize and safety stock: An economic manufacturing quantity model, Int. J. Manag. Sci. Eng. Manag, 5, pp. 192-202, (2010); Moon I., Shin E., Sarkar B., Min-max distribution free continuous-review model with a service level constraint and variable lead time, Appl. Math. Comput, 229, pp. 310-315, (2014); Shin D., Guchhait R., Sarkar B., Mittal M., Controllable lead time, service level constraint, and transportation discounts in a continuous review inventory model, RAIRO Oper. Res, 50, pp. 921-934, (2016); Sarkar B., Mahapatra A.S., Periodic review fuzzy inventory model with variable lead time and fuzzy demand, Int. Trans. Oper. Res, 24, pp. 1197-1227, (2017); Sarkar B., Cardenas-Barron L.E., Sarkar M., Singgih M.L., An economic production quantity model with random defective rate, rework process and backorders for a single stage production system, J. Manuf. Syst, 33, pp. 423-435, (2014); Sarkar B., Ahmed W., Kim N., Joint effects of variable carbon emission cost and multi-delay-in-payments under single-setup-multiple-delivery policy in a global sustainable supply chain, J. Clean. Prod, 185, pp. 421-445, (2018); Sarkar B., Sana S.S., Chaudhuri K., An inventory model with finite replenishment rate, trade credit policy and price-discount offer, J. Ind. Eng, (2013); Sarkar B., Sarkar S., An improved inventory model with partial backlogging, time varying deterioration and stock-dependent demand, Econ. Model, 30, pp. 924-932, (2013); Kang C.W., Ullah M., Sarkar B., Hussain I., Akhtar R., Impact of random defective rate on lot size focusing work-in-process inventory in manufacturing system, Int. J. Prod. Res, 55, pp. 1748-1766, (2017); Ahmed W., Sarkar B., Impact of carbon emissions in a sustainable supply chain management for a second generation biofuel, J. Clean. Prod, 186, pp. 807-820, (2018); Cardenas-barron L.E., Sarkar B., Trevino-garza G., Easy and improved algorithms to joint determination of the replenishment lot size and number of shipments for an EPQ model with rework, Math. Comput. Appl, 18, pp. 132-138, (2013); Sarkar B., An EOQ model with delay in payments and time varying deterioration rate, Math. Comput. Model, 55, pp. 367-377, (2012); Tayyab M., Sarkar B., Optimal batch quantity in a cleaner multi-stage lean production system with random defective rate, J. Clean. Prod, 139, pp. 922-934, (2016); Kim M.S., Sarkar B., Multi-stage cleaner production process with quality improvement and lead time dependent ordering cost, J. Clean. Prod, 144, pp. 572-590, (2017)","S.-B. Choi; Department of International Business, Cheju Halla University, Jeju-do, 63092, South Korea; email: sbchoi777@naver.com",null,"MDPI AG",{"$nulls":5},2.227739E7,null,null,null,"English","Mathematics","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85059457415"]
["Ilham R.","Ilham, Romi (57203505013)",5.7203505013E10,"Improve quality of e-loyalty in online food delivery services: A case of Indonesia",2018.0,"Journal of Theoretical and Applied Information Technology",96.0,15.0,null,4760.0,4769.0,9.0,10.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85051936021&partnerID=40&md5=75a4c445bdd4be289a99e5952e548b64","STIE Perbanas Surabaya, Departement of Accounting, Indonesia","Ilham R., STIE Perbanas Surabaya, Departement of Accounting, Indonesia","This study aims to improve e-loyalty by analyzing the effect of e-service quality on customer e-loyalty through e-satisfaction in online food service delivery. This research uses quantitative approach with survey method. The population in this study were customers who had used online food service with a sample of 320 respondents. Data analysis using SEM-PLS (Partial Least Square) with Smart-PLS software. The results showed that e-service quality positively affects e-loyalty and e-satisfaction, e-satisfaction has positive affect on customer e-loyalty and e-service quality positively affect e-loyalty of customer through e-satisfaction. It can be concluded that e-satisfaction mediates the influence of e-service quality on e-loyalty of online food service customers, so e-service quality and e-satisfaction is required to improve e-loyalty. © 2005 - ongoing JATIT & LLS.","E-commerce; E-loyalty; E-satisfaction; E-service quality",{"$nulls":7},"Anderson R.E., Swaminathan S., Customer Satisfaction and Loyalty in E-Markets: A PLS Path Modeling Approach, The Journal of Marketing Theory and Practice, 19, 2, pp. 221-234, (2011); Barnes S.J., Vidgen R., An evaluation of cyber-bookshops: The WebQual method, International Journal of Electronic Commerce, 6, 1, pp. 11-30, (2001); Chang H.H., Wang Y.-.H., Yang W.-.Y., The impact of e-service quality, customer satisfaction and loyalty on e-marketing: Moderating effect of perceived value, Total Quality Management & Business Excellence, 20, 4, pp. 423-443, (2009); Chin W.W., The Partial Least Squares Approach for Structural Equation Modeling. in Modern Methods for Business Research, pp. 295-336, (1998); Cyr D., Head M., Ivanov A., Perceived interactivity leading to e-loyalty: Development of a model for cognitive-affective user responses, International Journal of Human Computer Studies, 67, 10, pp. 850-869, (2009); Evanschitzky H., Kenning P., Vogel V., Consumer price knowledge in the German retail market, Journal of Product & Brand Management, 13, 6, pp. 390-405, (2004); Ghalandari K., Ghorbani M., Jogh G., Imani M., Nia L.B., The Effect Of Emotional Labor Strategies On Employees Job Performance And Organizational Commitment In Hospital Sector: Moderating Role Of Emotional Intelligence In Iran, World Applied Sciences Journal, 17, 3, pp. 319-326, (2012); Ghane S., Fathian M., Gholamian M.R., Full relationship among e-satisfaction, e-trust, e-service quality, and e-loyalty: The case of Iran e-banking, Journal of Theoretical and Applied Information Technology, 33, 1, pp. 1-6, (2011); Ghozali I., Structural Equation Modeling Metode Alternatif Dengan Pendekatan Partial Least Square (PLS), (2008); Guo X., Ling K.C., Liu M., Evaluating factors influencing consumer satisfaction towards online shopping in China, Asian Social Science, 8, 13, pp. 40-49, (2012); Joseph F., Hair J., Ringle C., Sarstedt M., PLS-sem: Indeed a silver bullet, The Journal of Marketing Theory and Practice, 19, (2011); Kim W.G., Ng C.Y.N., Kim Y.S., Influence of institutional DINESERV on customer satisfaction, return intention, and word-of-mouth, International Journal of Hospitality Management, 28, 1, pp. 10-17, (2009); Komara A.T., Pengaruh E-Service Quality Dan E-Recovery Service Quality Terhadap E-Satisfaction Serta Implikasinya Pada E-Loyalty Pelanggan Maskapai Penerbangan Air Asia, Jurnal Ekonomi, 7, 2, pp. 105-115, (2013); Kotler P., Keller K.L., Marketing Management, (2015); Oliver R.L., Whence Consumer Loyalty?, Journal of Marketing, 63, (1999); Pearson S., Building brands directly: Creating business value from customer Relationships, Macmillan Business, 20, 6, pp. 68-82, (1996); Rolph E.A., Srinivasan S.S., E‐satisfaction and e‐loyalty: A contingency framework, Psychology & Marketing, 20, 2, pp. 123-138, (2003); Romadhoni B., Hadiwidjojo D., Noermijatiaisjah S., Relationship between E-Service Quality, E-Satisfaction, E-Trust, E-Commitment In Building Customer E-Loyalty: A Literature Review, International Journal of Business and Management Invention, 4, 2, pp. 1-9, (2015); Sabiote C.M., Frias D.M., Castaneda J.A., E‐service quality as antecedent to e‐satisfaction: The moderating effect of culture, Online Information Review, 36, 2, pp. 157-174, (2012); Santos J., E‐service quality: A model of virtual service quality dimensions, Managing Service Quality: An International Journal, 13, 3, pp. 233-246, (2003); Sativa A., Astuti S.R.T., Analisis Pengaruh E-Trust Dan E-Service Quality Terhadap E-Loyalty Dengan E-Satisfaction Sebagai Variabel Intervening (Studi pada Pengguna E-Commerce C2C Tokopedia), Diponegoro Journal of Management, 5, (2016); Shukri M., Yazid A., Khatibi A., Azam S.M.F., Service Quality, Customer Satisfaction and Customer Loyalty ot The Hotel Industry in United Arab Emirates (UAE): A Measurement Model, European Journal of Management and Marketing Studies, 2, 4, pp. 1-26, (2017); Sugiyono, Metodelogi Penelitian Kuantitatif, Kualitatif, Dan R&D, (2015); Tsai C.-.C., Yang Y.-.K., Cheng Y.-.C., Does relationship matter? - Customers’ response to service failure, Managing Service Quality: An International Journal, 24, 2, pp. 139-159, (2014); Valarie A., Zeithaml A.M.A.P., Service Quality DeliveryThrough Web Sites: A Critical Review of Extant Knowledge, Journal of the Academy of Marketing Science, 30, 4, (2002); Wolfinbarger M., Gilly C.M., ETailQ: Dimensionalising,Measuring and Predicitng eTail Quality, Journal of Retailing, 79, 3, pp. 183-198, (2003); Zeithaml V.A., Bitner M.J., Gremler D.D., Services Marketing: Integrating Customer Focus, (2009)","R. Ilham; STIE Perbanas Surabaya, Departement of Accounting, Indonesia; email: romi_ilham@perbanas.ac.id",null,"Little Lion Scientific",{"$nulls":5},1.9928645E7,null,null,null,"English","J. Theor. Appl. Inf. Technol.","Article","Final",null,"Scopus","2-s2.0-85051936021"]
["Watanabe C.; Naveed N.; Neittaanmäki P.","Watanabe, Chihiro (55619319799); Naveed, Nasir (57202497475); Neittaanmäki, Pekka (7004251871)","55619319799; 57202497475; 7004251871","Digital solutions transform the forest-based bioeconomy into a digital platform industry - A suggestion for a disruptive business model in the digital economy",2018.0,"Technology in Society",54.0,null,null,168.0,188.0,20.0,36.0,"10.1016/j.techsoc.2018.05.002","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85048579890&doi=10.1016%2fj.techsoc.2018.05.002&partnerID=40&md5=e7d5025019d92a4ffa0560487bff81f8","Faculty of Information Technology, University of Jyväskylä, Finland; International Institute for Applied Systems Analysis (IIASA), Austria","Watanabe C., Faculty of Information Technology, University of Jyväskylä, Finland, International Institute for Applied Systems Analysis (IIASA), Austria; Naveed N., Faculty of Information Technology, University of Jyväskylä, Finland; Neittaanmäki P., Faculty of Information Technology, University of Jyväskylä, Finland","With the notion that the transformation of the forest-based bioeconomy in recent years provides insightful suggestions not only on the bioeconomy, but on business innovation, this paper conducts an empirical analysis of the transformation and attempts to extract suggestions for a digital-solution-driven, disruptive business model in the digital economy. Notwithstanding the potential broad cross-sectoral benefits, the natural environment, locality constraints, and incessant challenge of distance have impeded the balanced development of the bioeconomy. However, driven by digital solutions, the bioeconomy has taken big steps forward in recent years. Digitalization has enabled real-time, end-to-end supply chain visibility, improved delivery accuracy as well as stock level optimization and alignment with demand planning. The advancement of e-commerce has also led to the elimination of distance between both the upstream and the downstream of the chain. This paper demonstrates a transformative stream observed at the forefront of the forest-based bioeconomy chain. An empirical analysis focusing on the core business activities at the forefront, both upstream and downstream of the chain, is conducted. A new insight common to all industries in the digital economy is thus explored for constructing a creative disruption platform by embracing digital solutions. © 2018 Elsevier Ltd","Creative disruption platform; Digital platform industry; Digital solutions; Forest-based bioeconomy; Transformation","Forestry; Business models; Creative disruption platform; Creatives; Digital economy; Digital platform industry; Digital platforms; Digital solutions; Empirical analysis; Forest-based bioeconomy; Transformation; accuracy assessment; business cycle; digitization; electronic commerce; innovation; optimization; real time; theoretical study; Supply chains",{"$nulls":4},"Academy of Finland, (293446); Strategic Research Council, SRC","The research leading to these results has received funding from the Strategic Research Council at the Academy of Finland under grant agreement 293446 – Platform Value Now: Value capturing in the fast emerging platform ecosystems.  ","Accenture, Digital's promise for forest products industry, (2018); Amazon, Earth's biggest selection, (2017); Amazon, Whole foods market + Amazon, (2018); Monthly Statshot, (2016); Beamon B., Supply chain design and analysis: models and methods, Int. J. Prod. Econ., 55, 3, pp. 281-294, (1998); Key Statistics 2014: European Pulp & Paper Industry, (2014); What Digital Can Do for the Paper Industry, (2015); Key Statistics 2016: European Pulp & Paper Industry, (2017); Innovating for Sustainable Growth: a Bioeconomy for Europe. COM(2012)60 Final, (2012); Enso S., A Focused Strategy, (2017); Enso S., Stora Enso invests EUR 94 million to grow in renewable materials, (2017); Finnish Forest Industries, Statistics, (2016); Statistics, (2016); Giurca A., Spath P., A forest-based bioeconomy for Germany? Strengths, weaknesses and policy options for lignocellulosic biorefineries, J. Clean. Prod., 153, pp. 51-62, (2017); Hetemaki L., Role of Sustainable Forest-based Bioeconomy in Europe, (2016); Hetemaki L., Hoen H.F., Schwarzbauer P., Future of the european forest-based sector and bioeconomy, Future of the European Forest-based Sector: Structural Changes towards Bioeconomy, (2014); Hohenauer T., The Future of Pulp and Paper: from Experience to Analytics, from Isolation to Ecosystems, (2017); Hurmekoski E., Hetemaki L., Studying the future of the forest sector: review and implications for long-term outlook studies, For. Policy Econ, (2013); Johnson N., Miller O., Moffitt D., Disruption at the gates: monitoring the threat of Amazon business, Applico, pp. 1-18, (2017); Kenney M., The growth and development of the internet in the United States, The Global Internet Economy, (2013); KSML, UPM kaavailee toista sellutehdasta Uruguayhin – “Suurempi kuin Äänekosken tehdas”, (2017); McDonagh D., Satisfying needs beyond the functional: the changing needs of the silver market consumer, Proceedings of the International Symposium on the Silver Market Phenomenon – Business Opportunities and Responsibilities in the Aging Society, Tokyo, (2008); Marimekko, Marimekko and Spinnova Start Cooperation, (2017); Metsa, About the bio-product mill, (2017); Ministry of Economic Affairs and Employment of Finland, Wood-based Bioeconomy Solving Global Challenges, (2017); Mubareka S., Jonsson R., Rinaldi F., Azevedo J.C., de Rigo D., Sikkema R., Forest bio-based Economy in Europe, (2016); Mustalahti I., The responsive bioeconomy: the need for inclusion of citizens and environmental capacity in the forest-based bioeconomy, J. 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From Science to Policy, 4, pp. 1-31, (2016); Yahoo Finance, Amazon stock prices; Yahoo Finance, S&P 500 Index; Yglesias M., The real reason Amazon buying whole foods terrifies the competition, (2017); Patari S., Tuppura A., Toppinen A., Korhonen J., Global sustainability megaforces in shaping the future of the European pulp and paper industry towards a bioeconomy, For. Pol. Econ., 66, pp. 38-46, (2016); Nielsen, Nielsen Book Research: 2015 In Review – The London book fair quantum conference April 2016, (2016); Food and Agriculture Organization of the United Nations, FAO Yearbook of Forest Products 2002-2015; EC, Energy efficient buildings – multi annual roadmap for the contractual PPP under Horizon 2020 prepared by Energy Efficient Buildings (E2B) and European Construction Technology Platform (ECTP), 2013, (2013); LaVecchia O., Mitchell S., Amazon's strangelehold: how the company's tightening grip is stifling competition, eroding jobs, and threatening communities, (2016); Kaicell F., Responsible innovation serving mankind and environment, (2017); Finnpulp, The world's first smart bioproduct plant, (2017)","C. Watanabe; Faculty of Information Technology, University of Jyväskylä, Finland; email: watanabe.c.pqr@gmail.com",null,"Elsevier Ltd",{"$nulls":5},"0160791X",null,null,null,"English","Technol. Soc.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85048579890"]
["Yuen K.F.; Wang X.; Ng L.T.W.; Wong Y.D.","Yuen, Kum Fai (56581269200); Wang, Xueqin (57196484178); Ng, Li Ting Wendy (57201028288); Wong, Yiik Diew (57218910096)","56581269200; 57196484178; 57201028288; 57218910096","An investigation of customers’ intention to use self-collection services for last-mile delivery",2018.0,"Transport Policy",66.0,null,null,1.0,8.0,7.0,155.0,"10.1016/j.tranpol.2018.03.001","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85042918678&doi=10.1016%2fj.tranpol.2018.03.001&partnerID=40&md5=75ab776eb243df2f21bc788f5a3e4a79","Department of International Logistics, Chung-Ang University, Seoul, South Korea; School of Civil and Environmental Engineering, Nanyang Technological University, Singapore","Yuen K.F., Department of International Logistics, Chung-Ang University, Seoul, South Korea; Wang X., School of Civil and Environmental Engineering, Nanyang Technological University, Singapore; Ng L.T.W., School of Civil and Environmental Engineering, Nanyang Technological University, Singapore; Wong Y.D., School of Civil and Environmental Engineering, Nanyang Technological University, Singapore","Anchored on Innovation Diffusion Theory (IDT), this paper analyses customers’ intention to use self-collection as a last-mile delivery method. Characteristics of innovation were hypothesised to be key factors influencing customers’ intention to use self-collection services. Demographic characteristics were also tested. Survey data were collected from 164 consumers located in Singapore and analysed using hierarchical regression analysis. The results show that among the five key characteristics of innovation, relative advantage, compatibility and trialability positively influence customers’ intention to use self-collection services. It is also found that the pre-eminent step to improve customers’ intention is to integrate self-collection into consumers’ lifestyle, values and needs. In addition, self-collection services should be marketed in a manner that confers a clear advantage over other last-mile delivery methods. This paper enriches the literature on IDT as well as the management and design of self-collection services for last-mile delivery. © 2018 Elsevier Ltd","Adoption behaviour; E-commerce; Innovation diffusion theory; Last-mile delivery; Self-collection","Singapore [Southeast Asia]; electronic commerce; innovation; supply chain management; technology adoption; technology diffusion",{"$nulls":6},"Agatz N., Campbell A., Fleischmann M., Savelsbergh M., Time slot management in attended home delivery, Transport. 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Manag., 30, 10, pp. 498-507, (2002); Punakivi M., YrjoElaE H., HolmstroEm J., Solving the last mile issue: reception box or delivery box?, Int. J. Phys. Distrib. Logist. Manag., 31, 6, pp. 427-439, (2001); Rogers E.M., The Diffusion of Innovation 5th Edition, (2003); Rogers E.M., Diffusion of Innovations, (2010); Stromberg H., Rexfelt O., Karlsson I.M., Sochor J., Trying on change–Trialability as a change moderator for sustainable travel behaviour, Trav. Behav. Soc., 4, pp. 60-68, (2016); Talke K., Heidenreich S., How to overcome pro-change bias: incorporating passive and active innovation resistance in innovation decision models, J. Prod. Innovat. Manag., 31, 5, pp. 894-907, (2014); Tan J.M., Overcoming the Last-mile Challenge, (2016); Van Duin J., De Goffau W., Wiegmans B., Tavasszy L., Saes M., Improving home delivery efficiency by using principles of address intelligence for B2C deliveries, Transport. Res. Procedia, 12, pp. 14-25, (2016); Wijaya B.S., The development of hierarchy of effects model in advertising, Int. Res. J. Bus. Stud., 5, 1, (2015); Xu J.-J., Hong L., Impact factors of choosing willingness for picking up service, Eng. Technol., 6, 14, pp. 2509-2513, (2013); Yuen K.F., Thai V.V., Wong Y.D., Are customers willing to pay for corporate social responsibility? A study of individual-specific mediators, Total Qual. Manag. Bus. Excel., 27, 7-8, pp. 912-926, (2016); Yuen K.F., Wang X., Wong Y.D., Zhou Q., Antecedents and outcomes of sustainable shipping practices: the integration of stakeholder and behavioural theories, Transport. Res. E Logist. Transport. Rev., 108, pp. 18-35, (2017)","X. Wang; School of Civil and Environmental Engineering, Nanyang Technological University, Singapore; email: wang1072@e.ntu.edu.sg",null,"Elsevier Ltd",{"$nulls":5},"0967070X",null,null,null,"English","Transp. Policy","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85042918678"]
["De Brito Sousa F.B.","De Brito Sousa, Felipe Brum (57207859859)",5.7207859859E10,"Model of shared distribution of newspapers and e-commerce",2019.0,"International Journal of Logistics Systems and Management",32.0,"2024-04-03",null,483.0,495.0,12.0,2.0,"10.1504/ijlsm.2019.10019772","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85063085101&doi=10.1504%2fijlsm.2019.10019772&partnerID=40&md5=d79a73624c9ef230d7e26d949cd9ccfa","Programa de Pós-Graduação em Engenharia de Produção - PPGEP - UFRGS, FTEC - Faculdade de Tecnologia, University do Vale do Sinos, UNISINOS, Brazil","De Brito Sousa F.B., Programa de Pós-Graduação em Engenharia de Produção - PPGEP - UFRGS, FTEC - Faculdade de Tecnologia, University do Vale do Sinos, UNISINOS, Brazil","The availability of news and reading online through smartphones, tablets and computers has reduced the sale of newspapers in the world. On the other hand, the logistics express cargo (characteristic of e-commerce models) grows every day making use of optimised outsourced resources. This study aims to develop a model for planning the shared physical distribution of newspapers and e-commerce products for use in the logistics operator. Its resolution will be performed by discrete optimisation (vehicles and entire cargo) through integer linear programming, through mathematical modelling and processing in MATLAB, in which scenarios of outsourcing physical distribution are analysed, taking into consideration the impact of an increase in demand coming in profitability, penalties revenue by charging postponements, cost variations by including extra fleet, introduction of contractual penalty for not carrying any product, and tests with varying postponement times of shipments. © 2019 Inderscience Enterprises Ltd.","E-commerce; Mathematical modelling; Newspapers; Shared logistics",{"$nulls":7},"Jornais: Breve História, (2015); Transporte Humano: Cidades Com Qualidade de Vida, (1997); Billaney J., Hull College: Design and development of a higher level apprenticeship in express logistics, Higher Education, Skills and Work-Based Learning, 2, 3, pp. 340-343, (2012); Brasileiro A., Orrico Filho R.D., Santos E.M., Aragao J.J.G., Ônibus Urbano: Regulamentação e Mercados, (1996); Cascetta E., Transportation Systems Analysis: Models and Applications, (2009); Chew E., Huang H., Johnson E., Nemhauser G., Sokol J., Leong C., Short-term booking of air cargo space, European Journal of Operational Research, 174, 3, pp. 1979-1990, (2006); Colin E., Pesquisa Operacional: 170 Aplicações Em Estratégia, Finanças, Logística, Produção, Marketing e Vendas, (2013); História Do E-Commerce, (2015); Ehrlich P.J., Modelos quantitativos de apoio às decisões, Revista Da Administração de Empresas São Paulo, 36, 1, pp. 33-41, (1996); Goldbarg M.C., Luna H.P.L., Otimização Combinatória e Programação Linear: Modelos e Algoritmos, (2000); Govindan K., Palaniappan M., Zhu Q., Kannan D., Analysis of third party reverse logistics provider using interpretative structural modeling, International Journal of Production Economics, 140, 1, pp. 204-211, (2012); Han D.L., Tang L.C., Huang H.C., A Markov model for single-leg air cargo revenue management under a bid-price policy, European Journal of Operational Research, 200, 3, pp. 800-811, (2010); Karmarkar U., Yoo J., The stochastic dynamic product cycling problem, European Journal of Operational Research, 73, 2 B, pp. 360-373, (1994); Klibi W., Lasalle F., Martel A., The stochastic multiperiod location transportation problem, Transportation Science, 44, 2, pp. 221-237, (2010); Lachtermacher G., Pesquisa Operacional Na Tomada de Decisões, (2002); Lachtermacher G., Pesquisa Operacional Na Tomada de Decisões, (2009); Luo S., Cakanyildirim M., Kasilingam R., Two-dimensional cargo overbooking models, European Journal of Operational Research, 197, 3, pp. 862-883, (2009); Mayer M., Scholz A.B., An assessment of economic costs of cargo transporting airlines by the use of a structural cost function, Journal of Air Transport Management, 25, pp. 30-32, (2012); Novaes A.G., Sistemas Logísticos: Transporte, Armazenagem e Distribuição Física de Produtos, (1989); The Impact of the Express Delivery Industry on the Global Economy, (2005); Russell R., Chiang W., Zepeda D., Integrating multi-product production and distribution in newspaper logistics, Computers and Operations Research, 35, 5, pp. 1576-1588, (2008); Sousa F., Gerenciamento Da Qualidade No Transporte Coletivo de Longa Distância Por Ônibus, (2004); Sousa F., Modelo de Apoio À Decisão para Distribuição Física Compartilhada de Jornais e Produtos de E-Commerce, (2016); Strandenes S.P., Freight transport pricing models, Freight Transport Modelling, (2013); Taha H., Pesquisa Operacional, (2008); Taniguchi E., Thompson R., Yamada T., Emerging techniques for enhancing the practical application of city logistics models, Procedia - Social and Behavioral Sciences, 39, 3, pp. 3-18, (2012); Teo J., Taniguchi E., Qureshi A., Evaluating city logistics measure in E-commerce with multi-agent systems, Procedia - Social and Behavioral Sciences, 39, pp. 349-359, (2012); Comércio Eletrônico Deve Crescer 17.3% Em 2015, (2015); Yamashita D.S., Morabito R., Um algoritmo branch-and-bound para o problema de programação de projetos com custo de disponibilidade de recursos e múltiplos modos, Gestão Da Produção, 14, 3, pp. 545-555, (2007); Ying W., Dayong S., Multi-agent framework for third party logistics in e-commerce, Expert Systems with Applications, 29, pp. 431-436, (2005)","F.B. De Brito Sousa; Programa de Pós-Graduação em Engenharia de Produção - PPGEP - UFRGS, FTEC - Faculdade de Tecnologia, University do Vale do Sinos, UNISINOS, Brazil; email: fbrums@unisinos.br",null,"Inderscience Publishers",{"$nulls":5},1.7427967E7,null,null,null,"English","Int. J. Logist. Syst. Manage.","Article","Final",null,"Scopus","2-s2.0-85063085101"]
["Cai Y.; Wang D.; Xia C.; Wang C.","Cai, Yi (57238964800); Wang, Deqiang (57208425959); Xia, Chunping (57201128860); Wang, Cuicui (57207370472)","57238964800; 57208425959; 57201128860; 57207370472","Study on the governance mechanism of rural e-commerce service centers in rural China: Agency problems and solutions",2019.0,"International Food and Agribusiness Management Review",22.0,3.0,null,381.0,396.0,15.0,5.0,"10.22434/IFAMR2018.0088","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85064737842&doi=10.22434%2fIFAMR2018.0088&partnerID=40&md5=261af453d83d0dc86f96b5f83c79e669","College of Economics and Management, Hubei Rural Development Research Center, Huazhong Agricultural University, Wuhan, 430070, China; College of Huamnity and Law, Huazhong Agricultural University, Wuhan, 430070, China","Cai Y., College of Economics and Management, Hubei Rural Development Research Center, Huazhong Agricultural University, Wuhan, 430070, China; Wang D., College of Huamnity and Law, Huazhong Agricultural University, Wuhan, 430070, China; Xia C., College of Economics and Management, Hubei Rural Development Research Center, Huazhong Agricultural University, Wuhan, 430070, China; Wang C., College of Economics and Management, Hubei Rural Development Research Center, Huazhong Agricultural University, Wuhan, 430070, China","Agency problems, such as moral hazard and adverse selection, are prevalent in the public service sector, and the Chinese rural e-commerce service sector is no exception. With the focus on the top-down project 'information and communication technology for development' implemented in the underdeveloped areas in China, the rural e-commerce service center (RESC) operation mechanism was analyzed in this study. Based on the tension between RESC operators, local governments, and e-commerce service providers that was reported in a field survey, this study further employs the principal-agent framework to analyze the problems of asymmetric information. Based on this analysis, solutions are suggested that can remedy the moral hazard issues in rural e-commerce service delivery, including developing a service evaluation system, promoting the usage of ICTs, and enhancing rural social capital. To address the problem of adverse selection, the RESC recruitment process should be improved. Moreover, by dividing the potential RESC employees into native villagers and e-commerce entrepreneurs, the optimal subsidy schemes can be designed for both types of applicants according to their ability and sensitivity to incentive. © 2019 Cai et al.","Adverse selection; Asymmetric information; Moral hazard; Rural China; Rural e-commerce service",{"$nulls":5},"Fundamental Research Funds for the Central Universities, (2662017PY064)","The authors would like to thank Scott Loveridge, John Mann, and Kyle Michael Jones for the contributions and comments, as well as the reviewers and editor for their constructive comments. This study on the ‘financial-law issue on Chinese elderly pulation’ was supported by the Fundamental Research Funds for the Central Universities (grant numbers 2662017PY064).","Abdulwahab L., Dahalin Z.M., A conceptual model of Unified Theory of Acceptance and Use of Technology (UTAUT) modification with management effectiveness and program effectiveness in context of telecentre, African Scientist, 11, 4, pp. 267-275, (2010); Akerlof G.A., The market for' lemons': quality uncertainty and the market mechanism, Quarterly Journal of Economics, 84, 3, pp. 488-500, (1970); Report on China's Taobao village, (2014); Report on China's Taobao village, (2015); Almajali D.A., Maqableh M., Moh'd Taisir Masa R.E., Assessing the digital divide status of the Jordanian telecentre, International Journal of Communications, Network and System Sciences, 8, 11, pp. 428-439, (2015); Arrow K.J., Uncertainty and the Welfare Economics of Medical Care (American Economic Review, 1963), Journal of Health Politics, Policy and Law, 26, 5, pp. 851-883, (2001); Asthana S., Halliday J., What can rural agencies do to address the additional costs of rural services?. 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The effective supply of information and the farm-gate price: an empirical study from micro-level, China Economic Quarterly, 12, 4, pp. 1513-1536, (2013); Zeng Y., Jia F., Wan L., Guo H., E-commerce in agri-food sector: a systematic literature review, International Food and Agribusiness Management Review, 20, 4, pp. 439-460, (2017); Zeng Y.W., Guo H.D., Jin S.Q., Does e-commerce increase farmers' income? Evidence from Shuyang county, Jiangsu province, China, Chinese Rural Economy, 2, 8, pp. 1-16, (2018); Zeng Y.W., Wan L., Guo H.D., Agricultural e-commerce research: a review of the current status and prospects, China Rural Survey, 3, 7, pp. 82-93, (2016)","Y. Cai; College of Economics and Management, Hubei Rural Development Research Center, Huazhong Agricultural University, Wuhan, 430070, China; email: wdq@mail.hzau.edu.cn",null,"Wageningen Academic Publishers",{"$nulls":5},1.5592448E7,null,null,null,"English","Int. Food Agribus. Manage. Rev.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85064737842"]
["Yu X.; Lang M.; Gao Y.; Wang K.; Su C.-H.; Tsai S.-B.; Huo M.; Yu X.; Li S.","Yu, Xueqiao (57202987841); Lang, Maoxiang (7202006319); Gao, Yang (57198713244); Wang, Kai (57200853527); Su, Ching-Hsia (57202990094); Tsai, Sang-Bing (55910203400); Huo, Mingkun (57202986550); Yu, Xiao (7404110758); Li, Shiqi (57202992522)","57202987841; 7202006319; 57198713244; 57200853527; 57202990094; 55910203400; 57202986550; 7404110758; 57202992522","An empirical study on the design of China high-speed rail express train operation plan-from a sustainable transport perspective",2018.0,"Sustainability (Switzerland)",10.0,7.0,2478.0,null,null,null,26.0,"10.3390/su10072478","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85050081568&doi=10.3390%2fsu10072478&partnerID=40&md5=25de8a0b59c481da41fed3ff691665cf","School of Traffic and Transportation, Beijing Jiaotong University, Beijing, 100044, China; MOE Key Laboratory for Urban Transportation Complex System Theory and Technology, Beijing Jiaotong University, Beijing, 100044, China; School of Business, Dalian University of Technology, Panjin, 124221, China; College of Business Administration, Capital University of Economics and Business, Beijing, 100070, China; College of Tourism and Service Management, Nankai University, Tianjin, 300071, China; Zhongshan Institute, University of Electronic Science and Technology of China, Zhongshan, 528400, China; Zhong Zi Hua Ke Traffic Construction Technology Co. Ltd., Beijing, 100195, China; Signal and Communication Research Institute, China Academy of Railway Sciences Corporation Limited, Beijing, 100044, China","Yu X., School of Traffic and Transportation, Beijing Jiaotong University, Beijing, 100044, China; Lang M., School of Traffic and Transportation, Beijing Jiaotong University, Beijing, 100044, China, MOE Key Laboratory for Urban Transportation Complex System Theory and Technology, Beijing Jiaotong University, Beijing, 100044, China; Gao Y., School of Business, Dalian University of Technology, Panjin, 124221, China; Wang K., College of Business Administration, Capital University of Economics and Business, Beijing, 100070, China; Su C.-H., College of Tourism and Service Management, Nankai University, Tianjin, 300071, China; Tsai S.-B., School of Business, Dalian University of Technology, Panjin, 124221, China, Zhongshan Institute, University of Electronic Science and Technology of China, Zhongshan, 528400, China; Huo M., Zhong Zi Hua Ke Traffic Construction Technology Co. Ltd., Beijing, 100195, China; Yu X., Signal and Communication Research Institute, China Academy of Railway Sciences Corporation Limited, Beijing, 100044, China; Li S., School of Traffic and Transportation, Beijing Jiaotong University, Beijing, 100044, China","The sustained and steady development of China's economy has led to the rapid improvement of the logistics. At the same time, the rise of the e-commerce mode has given rise to a huge demand for express delivery and the express industry has entered a period of boom. Fortunately, China's high-speed rail network has been networked, and the development of a high-speed rail express train has entered the test stage. After the high-speed rail express train is put into use, it could effectively relieve the pressure of highway transportation and significantly reduce transport pollution. To make better use of high-speed rail transport resources and give full play to its green and efficient advantages, this study established a two-stage model of a high-speed rail express train operation plan. In the first stage, a train candidate set generation model aiming for the minimum total cost of train operation was established that considered the high-speed line carrying capacity, section flow capacity, and OD requirement satisfaction constraints, which reduces the scale of train spare parts and improves the efficiency of solution. In addition, a column generation algorithm was designed to solve the model. In the second stage, an accurate flow distribution model aiming for the optimal economic efficiency was established, and then the high-speed express train operation plan was designed completely. The computational results are encouraging and demonstrate the effectiveness of the model and solution method. © 2018 by the authors.","Column generation algorithm; High-speed rail express; Sustainability; Sustainable transportation; Train operation plan","China; algorithm; electronic commerce; empirical analysis; high-speed train; logistics; operations technology; railway transport; sustainability",{"$nulls":4},"National Key R&D Program of China, (2016YFE0201700, 2017YFB1201400); Zhongshan City Science and Technology Bureau Project, (2017B1015)","Funding: This research was supported by National Key R&D Program of China (2017YFB1201400), National Key R&D Program of China (2016YFE0201700) and Zhongshan City Science and Technology Bureau Project (No. 2017B1015).","Chen F., Shen X., Wang Z., Yang Y., An Evaluation of the Low-Carbon Effects of Urban Rail Based on Mode Shifts, Sustainability, 9, (2017); Armah F.A., Yawson D.O., Pappoe A.A.N.M., A Systems Dynamics Approach to Explore Traffic Congestion and Air Pollution Link in the City of Accra, Ghana, Sustainability, 2, pp. 252-265, (2010); Jeong S.J., Lee C.G., Bookbinder J.H., The European freight railway system as a hub-and-spoke network, Transp. Res. Part A Policy Pract, 41, pp. 523-536, (2007); Troche G., Activity-Based Rail Freight Costing A Model for Calculating Transport Costs in Different Production Systems, (2009); Pazour J.A., Meller R.D., Pohl L.M., A model to design a national high-speed rail network for freight distribution, Transp. Res. Part A, 44, pp. 119-135, (2010); Fukasawa R., Aragao M.V.P.D., Porto O., Uchoa E., Solving the Freight Car Flow Problem to Optimality, Electron. Notes Theor. Comput. Sci, 66, pp. 42-52, (2002); Racunica I., Wynter L., Optimal location of intermodal freight hubs, Transp. Res. Part B, 39, pp. 453-477, (2008); Cao X., Lin B., Yan H., Optimization of direct freight train service in the loading place, J. China Railw. Soc, 28, pp. 6-11, (2006); Liang D., Lin B., Research on the Model of Optimizing Strategically Dynamic Railcar Operation, Syst. Eng. Theory Pract, 27, pp. 77-84, (2007); Li Y., Wu S., Peng Q., Network model and algorithm for freight train marshalling plan, J. Southwest Jiaotong Univ, 37, pp. 68-71, (2002); Li X., Lu H., Optimization of train formation diagram of express freight, China Railw. Sci, 25, pp. 117-120, (2004); Godwin T., Gopalan R., Narendran T.T., A heuristic for routing and scheduling freight trains in a passenger rail network, Int. J. Logist. Syst. Manag, 3, pp. 101-133, (2007); Bozejko W., Grymin R., Pempera J., Scheduling and Routing Algorithms for Rail Freight Transportation, Procedia Eng, 178, pp. 206-212, (2017); Kaspi M., Raviv T., Service-Oriented Line Planning and Timetabling for Passenger Trains, Transp. Sci, 47, pp. 295-311, (2013); Tsai S., Using the DEMATEL Model to Explore the Job Satisfaction of Research and Development Professionals in China's Photovoltaic Cell Industry, Renew. Sustain. Energy Rev, 81, pp. 62-68, (2018); Lee Y., Hsiao Y., Peng C., Tsai S., Wu C., Chen Q., Using Mahalanobis-Taguchi System, Logistic Regression and Neural Network Method to Evaluate Purchasing Audit Quality, Proc. Inst. Mech. Eng. Part B J. Eng. Manuf, 229, pp. 3-12, (2015); Lee Y., Chen C., Tsai S., Wang C., Discussing green environmental performance and competitive strategies, Pensee, 76, pp. 190-198, (2014); Liu B., Li T., Tsai S., Low carbon strategy analysis of competing supply chains with different power structures, Sustainability, 9, (2017); Qu Q., Tsai S., Tang M., Xu C., Dong W., Marine ecological environment management based on ecological compensation mechanisms, Sustainability, 8, (2016); Lee Y., Wang Y., Chien C., Wu C., Lu S., Tsai S., Dong W., Applying revised gap analysis model in measuring hotel service quality, SpringerPlus, 5, (2016); Wang J., Yang J., Chen Q., Tsai S., Collaborative Production Structure of Knowledge Sharing Behavior in Internet Communities, Mob. Inf. Syst, 2016, (2016); Tsai S., Lee Y., Guo J., Using modified grey forecasting models to forecast the growth trends of green materials, Proc. Inst. Mech. Eng. Part B J. Eng. Manuf, 228, pp. 931-940, (2014); Tsai S., Zhou J., Gao Y., Wang J., Li G., Zheng Y., Ren P., Xu W., Combining FMEA with DEMATEL Models to Solve Production Process Problems, PLoS ONE, (2017); Ge B., Jiang D., Gao Y., Tsai S., The influence of legitimacy on a proactive green orientation and green performance: A study based on transitional economy scenarios in china, Sustainability, 8, (2016); Lee S., Su J., Tsai S., Lu T., Dong W., A comprehensive survey of government auditors' self-efficacy and professional Development for improving audit quality, SpringerPlus, 5, (2016); Chen H., Wu C., Tsai S., Yu J., Wang J., Zheng Y., Exploring key factors in online shopping with a hybrid model, SpringerPlus, 5, (2016); Lee Y., Wang Y., Lu S., Hsieh Y., Chien C., Tsai S., Dong W., An empirical research on customer satisfaction study: A consideration of different levels of performance, SpringerPlus, 5, (2016); Wang J., Yang J., Chen Q., Tsai S., Creating the sustainable conditions for knowledge information sharing in virtual community, SpringerPlus, 5, (2016)","M. Lang; School of Traffic and Transportation, Beijing Jiaotong University, Beijing, 100044, China; email: mxlang@bjtu.edu.cn",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85050081568"]
["Erceg A.; Sekuloska J.D.","Erceg, Aleksandar (57191745264); Sekuloska, Jovanka Damoska (57209417104)","57191745264; 57209417104","E-logistics and e-SCM: How to increase competitiveness; [E-logistics i e-SCM: Jak zwiększyć konkurencyjność]",2019.0,"Logforum",15.0,1.0,null,155.0,169.0,14.0,17.0,"10.17270/J.LOG.2019.323","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85067695619&doi=10.17270%2fJ.LOG.2019.323&partnerID=40&md5=3fdd79e6ac75c5ab6292541010a89ed0","Josip Juraj Strossmayer University of Osijek, Faculty of Economics in Osijek, Trg Ljudevita Gaja 7, Osijek, Croatia; University of Information Science and Technology “St. Paul the Apostle”, UIST Ohrid, North Macedonia","Erceg A., Josip Juraj Strossmayer University of Osijek, Faculty of Economics in Osijek, Trg Ljudevita Gaja 7, Osijek, Croatia; Sekuloska J.D., University of Information Science and Technology “St. Paul the Apostle”, UIST Ohrid, North Macedonia","Background: Recent technology development and the rise of e-commerce activities influenced changes in the logistics field and have “forced” companies to change their approach to logistics. On the other side, we are witnessing new developments in logistics service providers and their transformation. Competitiveness today doesn’t depend only on price but also on customer service and delivery time. This can be influenced by the implementation of modern methods in logistics. Thus, logistics service providers in the global market are looked at as business partners and the relationship with logistics service company is considered as a partnership. Because of the development in technology e-logistics concept has become more frequently used since it gives concepts for information sharing and information transparency within partners within supply chains. Thus, one of the important tasks of e-logistics is to share information with its partners and with that, it can have an influence on their competitiveness. The main aim of the paper is to show that the right logistics service provider in the modern supply chain can help companies to gain and maintain competitiveness and especially by using different modern digital tools in doing business. Methods: Paper has been written based on the analyses of the reviewed literature together with determining potential influence e-logistics and e-SCM have on company’s competitiveness. The case of DHL included in this study has been selected to present potentials which e-logistics have on creating a competitive advantage. Results: Research results show that use of advanced logistics operator can help companies in increasing their competitiveness in today’s market Conclusions: Customer experience, new entrants, technology collaboration vs. competition are major characteristics of the new trend and logistics service providers will need to adapt to these changes. Improved running in one of the previously mentioned areas will create and maintain the company’s competitiveness and as more modern technological tools and solutions will be used, companies will be able to have more benefits. © Wyższa Szkoła Logistyki, Poznań, Polska.","Competitiveness; DHL; E-logistics; E-SCM; Logistics service provider",{"$nulls":7},"Agatz N.A., Fleischmann M., van Nunen J.A., E-fulfillment and multi-channel distribution–A review, European Journal of Operational Research, 187, 2, pp. 339-356, (2008); Bask A., Lipponen M., Tinnila M., E-Commerce Logistics: A Literature Research Review and Topics for Future Research, International Journal of E-Services and Mobile Applications, 4, 3, pp. 1-22, (2012); Barne D., Competing supply chains are the future, Financial Times, (2006); Bartels A., The Difference between E-Business and E-Commerce, (2016); Blau J., RFID-the price must be right, Financial Times, (2006); Bourlakis M., Julien D., Ali I., The Next Industrial Revolution – How E-Commerce is Transforming B2B, (2018); Chopra S., Meindl P., Supply Chain Management: Strategy, Planning, and Operation, (2015); Croom S.R., The impact of e-business on supply chain management: An empirical study of key developments, International Journal of Operations & Production Mana-Gement, 25, 1, pp. 55-57, (2005); The 21St Century Spice Trade: A Guide to the Cross-Border E-Commerce Opportunity, (2017); Press Release-95% of Companies are Yet to Realize the Full Benefits of Digitalization Technologies for Their Supply Chains; Eng T., Mobile supply chain manage-ment: Challenges for implementation, Technovation, 26, pp. 682-686, (2006); Groznik A., Kovacic A., Zoric B., Vicic D., E-logistics: Informatization of Slovenian Transport Logistics Cluster, Proceedings of 26Th International Conference on Information Technology Interfaces, pp. 101-106, (2004); Gunasekaran A., Ngai E.W.T., Information systems in supply chain integration and management, European Journal of Operational Research, 159, pp. 269-295, (2004); Handfield R.B., Straight S., How mature is your supply chain? The SCRD capability maturity model, Proceedings of ISM’s 89Th Annual International Supply Management Conference, pp. 512-515, (2004); Harrington L., Digitalization and the Supply Chain: Where are We and what’s Next?, (2018); Holten R., Dreiling A., Muehlen M., Becker J., Enabling Technologies for Supply Chain Process Management Report, (2002); Jelassi T., Enders A., Strategies for E-Business: Creating Value through Electronic and Mobile Commerce, 3Rd Edition, (2014); Jones P., Clarke-Hill C., Shears P., Comfort D., Hillier D., Radio frequency identification in the UK: Opportunities and challenges, International Journal of Retail & Distribution Management, 32, 3, pp. 164-171, (2004); Joong-Kun Cho J., Ozment J., Sink H., Logistics capability, logistics outsourcing and firm performance in an E-commerce market, International Journal of Physical Distribution & Logistics Management, 38, 5, pp. 336-359, (2008); Kakkainen M., Increasing efficiency in the supply chain for short shelf life goods using RFID tagging, International Journal of Retail & Distribution Management, 31, 10, pp. 529-536, (2003); Kurt O., Kalem G., Vayvay O., Kalender Z.T., The Role of Mobile Devices and Applications in Supply Chains, International Journal of Economics and Management Systems, 1, pp. 94-103, (2016); Li S., Ragu-Nathan T.S., Ragu-Nathan B., Subba Rao S., The impact of supply chain management practices on competitive advantage and organizational performance, The International Journal of Management Science Omega, 34, pp. 107-124, (2006); Ling L., Supply Chain Management: Concepts, Techniques and Practices, (2007); Liu J., Wen Y., Study of Competitiveness-A Case Study of DHL, (2012); Luo Y., Wirojanagud P., Caudill R., Network-based optimization and simulation of sustainable e-supply chain management, Proceedings of the 2001 IEEE International Symposium on Electronics and the Environment, pp. 185-190, (2001); Masmoudi M., Benaissa M., Chabchoub H., Optimization of E-commerce logistics distribution system: Problem modelling and exact resolution, International Journal of Business Performance and Supply Chain Modelling, 6, 3-4, pp. 358-375, (2014); McLaren T.S., Head M.M., Yuan Y., Supply Chain Management Information Systems Capabilities: An Exploratory Study of Electronics Manufacturers, Information Systems and Ebusiness Management, 2, 2, pp. 207-222, (2004); Merali Y., Papadopoulos T., Nadkarni T., Information systems strategy: Past, present, future?, The Journal of Strategic Information Systems, 21, 2, pp. 125-153, (2012); Moroz M., Nicu C., Pawel I.D.D., Polkowski Z., The Transformation of Logistics, (2014); Into e-logistics with the example of electronic freight exchange, Zeszyty Naukowe Dolnośląskiej Wyższej Szkoły Przedsiębiorczości i Techniki, Studia Z Nauk Technicznych, 3, pp. 111-128; Monczka R.M., Hanfield R.B., Giunipero L.C., Patterson J.L., Purchasing and Supply Chain Management, (2009); Muller-Versee F., Kohlenbach B., Bout D., Singh S., Golub G., Hayrynen J., Laitinen S., Autio E., UMTS-an investment perspective, Joint Durlacher, Eqvitec and Hut Report, (2001); Norris G., Hurley J.R., Hartley K.M., Dunleavy J.R., Balls J.D., E-Business and ERP: Transforming the Enterprise, (2000); Poirier C.C., Bauer M.J., E-Supply Chain – Using the Internet to Revolutionize Your Business, (2000); Quirk A., Forder J., Bentley D., Electronic Commerce and the Law, (2003); Ramanathan R., George J., Ramanathan U., The Role of Logistics in E-Commerce Transactions: An Exploratory Study of Customer Feedback and Risk, pp. 221-233, (2014); Reix R., Fallery B., Kalika M., Rowe F., Systèmes d’information Et Management Des Organisations [Systems of Infomration Managements in Organisations, (2011); Ruhi U., Turel O., Driving Visibility, Velocity and Versatility: The Role of Mobile Technologies in Supply Chain Management, Journal of Internet Commerce, 4, 3, pp. 95-117, (2005); Sanders N.R., An empirical study of the impact of e-business technologies on organizational collaboration and performance, Journal of Operations Management, 25, 6, pp. 1332-1347, (2007); Creating the Digital Supply Chain for the Digital Economy: A Smart, Connected, Digital Supply Chain of One, SAP Thought Leadership Paper, (2018); Sathyan J., Narayanan A., Narayan N., Shibu K.V., A Comprehensive Guide to Enterprise Mobility, (2013); Song Y., Hou H., On traditional M. F and Modern M. F, Journal of Beijing Jiaotong University (Social Sciences Edition), 3, 1, pp. 10-16, (2004); Stieglitz S., Lattemann C., Brockmann T., Mobile Applications for Knowledge Workers and Field Workers, Mobile Information Systems, 2015, pp. 1-8, (2015); Taniar D., Mobile Computing: Concepts, Methodologies, Tools and Applications, (2009); Tipping A., Kauschke P., Shifting Patterns – the Future of Logistics Industry, PwC’s Future in Sight Series, (2016); Verwijmeren M., Software component architecture in supply chain management, Computers in Industry, 53, pp. 165-178, (2004); Wang J., Yang D., Guo D., Huo Y., Taking Advantage of E-Logistics to Strengthen the Competitive Advantage of Enterprises in China, Proceedings of the Fourth International Conference on Electronic Business, pp. 185-189, (2004); Wang Y., Pettit S., E-logistics: An introduction, E-Logistics: Managing Your Digital Supply Chains for Competitive Advantage, Kogan Page, pp. 3-31, (2016); Wieczorek A., E-logistics as a source of modern tools affecting the competitiveness of enterprises, Transport Economics and Logistics, 68, pp. 117-123, (2017); Yu Y., Wang X., Zhong R.Y., Huang G.O., E-commerce Logistics in Supply Chain Management: Practice Perspective, Procedia CIRP, 52, pp. 176-185, (2016); Yuan Y., Zheng W., Mobile task characteristics and the needs for mobile work support: A comparison between mobile knowledge workers and field workers, Proceedings of the 8Th International Conference on Mobile Business, Dailan, pp. 7-11, (2009)",null,null,"Poznan School of Logistics",{"$nulls":5},1.8952038E7,null,null,null,"English","Logforum","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85067695619"]
["Raman P.","Raman, Prashant (57205211411)",5.7205211411E10,"Zomato: a shining armour in the foodtech sector",2018.0,"Journal of Information Technology Case and Application Research",20.0,"2024-04-03",null,130.0,150.0,20.0,14.0,"10.1080/15228053.2018.1552396","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85059088843&doi=10.1080%2f15228053.2018.1552396&partnerID=40&md5=b8b211df70e51f15cc0d60a1855eb013","Banasthali Vidyapith, Jaipur, India","Raman P., Banasthali Vidyapith, Jaipur, India","Purpose–The purpose of this case is to understand and study the life cycle of a technology start-up (Zomato in this case) right from scratch to its growth and consolidation phase. The consumer’s approach for information and the choice of decision-making related to products and services have changed considerably in the digital era. Zomato is one website/application that has pioneered the online search for information related to restaurants in India. The case tries to evaluate the opportunities and challenges faced by a start-up in an extremely competitive industry and deliberates on how an online restaurant discovery business can be monetized into a highly effective and profitable business. It also examines the diversification strategy (natural and acquisition) employed by Zomato. Design/methodology/approach–The case uses secondary research method. The information, interview excerpts and data related to the company are gathered from different sources such as online databases, magazines, personal blogs of founders and company websites. The case covers a wide range of topics and can be helpful to undergraduates, MBA students and executives in courses such as entrepreneurship, digital marketing, strategic marketing, and marketing management. Majority of the students and executives are familiar with the company and their personal experiences can definitely improve the class discussion. Findings–This case identifies the different factors that were instrumental to the success of Zomato, its various revenue sources, its development through new products and services and growth expansion through acquisitions. The company which was primarily known for restaurant reviews gradually expanded into other areas of foodtech business like online ordering and delivery of food, table bookings, and developing applications software for managing the operations of restaurants. Soon after conquering the Indian market, Zomato successfully expanded to international markets particularly Europe, US, UK, and Middle-East. Practical implications (if applicable)–India is at the cusp of a big e-commerce revolution. In the last 4–5 years, the e-commerce industry in India has witnessed a lot of activities. Many new companies have entered the arena, some got merged, a few got acquired and some had to shut up shops. The hottest trend which is driving the market today is of aggregators and one such aggregator market is the foodtech sector. In the Indian start-up e-commerce industry, Zomato is one tale that every Indian entrepreneur will want to imitate. It is one inspirational start-up that gives insights into inventive marketing techniques and services and shows how to diversify risk by getting into other similar businesses and when and how to opt for natural growth and expand through acquisition. Originality/value–The Indian technology start-up ecosystem is currently in an embryonic phase and companies are still trying to figure out the best path to success. This case gives an insight into the online restaurant discovery market and Zomato’s rise in the highly cash-risk industry. It provides a step-by-step analysis of the various strategies implemented by Zomato in different situations. The case study helps to enhance the existing research done in the field of entrepreneurship and marketing management. It provides the budding entrepreneurs and marketing practitioners a bird’s eye view to building a company from zilch. © 2018, © 2018 Prashant Raman.",{"$nulls":8},"Zomato raises USD 60 million from Vy Capital and existing investors Info Edge and Sequoia Capital, (2014); The amazing way zomato uses data science for success, (2018); With 11 mn customers, Zomato has edge over rivals: Deepinder Goyal, (2016); Zomato, (2017); Batting it out of the park: zomato founder and CEO Deepinder Goyal, (2017); Our users are our biggest brand ambassadors: Deepinder Goyal, (2014); Food startup zomato is India’s first e-commerce unicorn to break even, headed for profitability, (2016); Deepinder Goyal and Zomato: Serving the market, (2016); Goyal D., A snapshot of our international presence, (2016); Zomato hits it big with 2 million orders in march, (2017); India internet users, (2016); BookMyShow acquires restaurant search engine Burrp, (2017); Yelp earnings: revenues grows as the company winds down international business, (2016); Foodpanda narrows losses to Rs 44 crore in FY17, (2017); Indian food delivery startup swiggy enters the overfunded club, (2017); Serving it hot, (2014); Zomato’s social media strategy explained [Interview, (2012); India foodtech market by operation type (food aggregators & restaurant based), by source of order (web vs mobile app), by payment method (cash on delivery, mobile wallet, etc.), competition forecast and opportunities, 2011–2021, (2016); Interview with Zomato COO - Pankaj Chaddah on their marketing and expansion plans, (2012); 5 years on, a look back into Zomato’s past and a glimpse into their future, (2013); 8 months on, how is Zomato doing internationally?, (2013); Is a breakthrough moment round the corner for India’s foodtech startups?, (2017); Priceline buys openTable for $2.6 billion, (2014)","P. Raman; Banasthali Vidyapith, Newai, P.O. Banasthali, 304022, India; email: prashantraman5@gmail.com",null,"Routledge",{"$nulls":5},1.5228053E7,null,null,null,"English","J. Inf. Technol. Case Appl. Res.","Article","Final",null,"Scopus","2-s2.0-85059088843"]
["Qijun R.","Qijun, Ren (26039379500)",2.60393795E10,"E-commerce logistics network optimization and cost analysis",2018.0,"IPPTA: Quarterly Journal of Indian Pulp and Paper Technical Association",30.0,7.0,null,883.0,890.0,7.0,1.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85061741296&partnerID=40&md5=036e4e66f8eed69969bf26e80da69e30","Zhengzhou Institute of Technology, Zhengzhou Henan, 450044, China","Qijun R., Zhengzhou Institute of Technology, Zhengzhou Henan, 450044, China","In recent years, China's Internet technology has developed rapidly, which has created unprecedented opportunities for e-commerce development. The rapid development of e-commerce logistics services as one of the core business of e-commerce results in rapid growth of business volumes, but at present the domestic logistics companies generally cannot provide services to meet the e-commerce business logistics business needs. B2C e-commerce logistics network optimization can effectively allocate various types of resources within the logistics system, reduce system operating costs, improve system service capabilities, and improve system service levels. How to effectively develop B2C e-commerce logistics network optimization is a problem that needs to be solved by B2C e-commerce companies. This article mainly studies the logistics network optimization to analyze the cost of this e-commerce model, and explore the necessity of B2C e-commerce to establish cost advantages. © Indian Pulp and Paper Technical Association. All rights reserved.","Cost advantage; E-commerce logistics network optimization; Internet economy; Transaction cost","Development; E-commerce; Management; Materials Handling; Operating Costs; Optimization; Services; Systems; Cost benefit analysis; Electronic commerce; Logistics; Operating costs; Cost advantages; E-commerce business; E-commerce development; Internet economy; Internet technology; Logistics network; System service level; Transaction cost; Costs",{"$nulls":6},"Chen Y.K., Chiu F.R., Liao H.C., Yeh C.H., Joint optimization of inventory control and product placement on e-commerce websites using genetic algorithms, Electronic Commerce Research, 16, 4, pp. 1-24, (2016); Chen Z., Research on network architecture of the e-commerce platform and optimization of the system performance, Open Cybernetics & Systemics Journal, 9, 1, pp. 2266-2271, (2015); Du J., A novel hybrid differential particle swarm optimization algorithm and its application in logistics distribution optimization, Journal of Computational Information Systems, 11, pp. 4913-4922, (2015); Guo J., Liu X., Jo J., Dynamic joint construction and optimal operation strategy of multi-period reverse logistics network: A case study of Shanghai apparel e-commerce enterprises, Journal of Intelligent Manufacturing, 28, pp. 1-13, (2017); Huang Y., Geismar H.N., Rajamani D., Sethi S., Sriskandarajah C., Carlos M., Optimizing logistics operations in a country''s currency supply network, A I I E Transactions, 49, 2, pp. 223-237, (2017); Liu D., Network site optimization of reverse logistics for e-commerce based on genetic algorithm, Neural Computing & Applications, 25, pp. 67-71, (2014); Sun X., Logistics business optimization of small and medium-sized garment manufacturing, Advanced Materials Research, 915-916, pp. 1483-1486, (2014); Tian Z., Zhang Z., Gao R., Optimization in e-commerce market network based on value order parameter, Information Technology and Management, 17, pp. 187-197, (2016); Xiao Z., Logistics Process Optimization and Cost Control, International Conference on Logistics Engineering. Management and Computer Science, 26, pp. 125-128, (2014)",null,null,"Indian Pulp and Paper Technical Association",{"$nulls":5},3795462.0,null,"IPPTD",null,"English","IPPTA","Article","Final",null,"Scopus","2-s2.0-85061741296"]
["Jujjuvarapu S.K.; Bolem M.; Shankar A.U.","Jujjuvarapu, Seshu Kumar (57193005837); Bolem, Mahidhar (57193010154); Shankar, A. Udaya (57192803655)","57193005837; 57193010154; 57192803655","Online buying behavior of women: A comparative study on kalamkari with other handlooms in A.P (Andhra Pradesh)",2018.0,"Journal of Advanced Research in Dynamical and Control Systems",10.0,"8 Special Issue",null,391.0,398.0,7.0,1.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85053840493&partnerID=40&md5=defd19bf37f77beed14190340007a542","Koneru Lakshmaiah Education Foundation, Green Fields,Tadepalli Mandal, Guntur District, Vaddeswaram, Andhra Pradesh, India","Jujjuvarapu S.K., Koneru Lakshmaiah Education Foundation, Green Fields,Tadepalli Mandal, Guntur District, Vaddeswaram, Andhra Pradesh, India; Bolem M., Koneru Lakshmaiah Education Foundation, Green Fields,Tadepalli Mandal, Guntur District, Vaddeswaram, Andhra Pradesh, India; Shankar A.U., Koneru Lakshmaiah Education Foundation, Green Fields,Tadepalli Mandal, Guntur District, Vaddeswaram, Andhra Pradesh, India","With the shift in telecommunications arena from analog to digital transmission the traditional buying behavior of the consumers shifted from offline to online. A wide range of products and ease of selecting, make the buying transaction at anytime anywhere with secured payment gateways, and getting the delivery of the products with in no time across the locations makes the consumers to go online from traditional offline way of buying. With increased advertising on online shopping portals, lowered internet charges and the lifestyle changes due to increased working class population with disposable income, dynamically changing tastes and preferences of the consumers makes the online shopping inclination upwards. Clothing is the basic necessity of the mankind other than food and shelter. The lifestyle of any country will reflect in the clothing the people were. Individuals showcase their stature in the clothing they wear. Handloom and ethnic ware brings in the elegance and look on the consumer and gets attention in the crowd where he lives. Handlooms were mostly made with natural extracts like cotton and colors made from vegetable extracts, gives the consumer more comfort, good touch n feels, lacks irritation and bad odor. Now a day’s handlooms were produced using modern techniques, which makes the consumers to opt for handlooms. Which lifts the demand curve for handlooms and competing with Branded and Unbranded modern ware. This study is focused on the variables which are influencing the online buying behavior of women towards handlooms specific to kalamkari. © 2018, Institute of Advanced Scientific Research, Inc. All rights reserved.","Buying behavior of women; Cultural influence on purchase decision; Handlooms; Kalamkari; Online; Product attribute; Reference groups",{"$nulls":7},"Mitra A., E-commerce in India-A Review, International Journal of Marketing, Financial Services & Management Research, 2, 2, (2013); Auret F.D.T., An Investigation into the Needs and Purchasing Behaviour of Female Students at the University of Stellenbosch with a View to the Establishment of a New Enterprise Marketing Leisure Wear, (1990); Beaudoin P., Moore M.A., Goldsmith R.E., Fashion leaders’ and followers’ attitudes toward buying domestic and imported apparel, Clothing and Textiles Research Journal, 18, 1, pp. 56-64, (2000); Burger C., Herbst F., Attributes used by young consumers when assessing a fashion product: A conjoint approach, Journal of Family Ecology and Consumer Sciences, 30, pp. 40-45, (2002); Burns L.D., Bryant N., The Business of Fashion, (1997); Campbell L., Butaney G.T., Market segmentation: Using demographics, psychographics and other niche marketing techniques to predict customer behaviour, Journal of Consumer Marketing, 13, 2, (1996); Katawetawaraks C., Wang C.L., Online Shopper Behavior: Influences of Online Shopping Decision, Asian Journal of Business Research, 1, 2, (2011); Sharma R., Mehta K., Sharma S., Understanding Online Shopping Behaviour of Indian Shoppers, IJMBS, 4, 3, (2014); Upadhyay P., Kaur J., Analysis of Online Shopping Behavior of Customer in Kota City, International Journal in Multidisciplinary and Academic Research, 2, 1, (2015); Kalaiyarasi S., An empirical study of the preferences and buying behavior of silk sarees among women consumers in Vellore Town, Int. J. Bus. Adm. Res. Rev, 1, 5, (2014); Hamil A., Kothai Natchiar M., A Study on Consumer Behaviour Towards Pothys Textile in Tirunelveli District, International Journal of Research, 4, pp. 21-28, (2016); Behera S.; Herekar D., E-Commerce in India–Problems and Prospects, ASM’s International E-Journal of Ongoing Research on Management and IT E-Issn-2320-006, (2013); Jain D., Verma S.K., Mehta U., Factors Influencing Student’s Decision Making towards Online Shopping, PACIFIC BUSINESS REVIEW INTERNATIONAL, 8, 3, pp. 24-36, (2015); (2016); Lu J., Yiu A., Soman A., India Consumer Close, (2017); Kalyani A., Acharyulu G., A Demographic Study on Customer Satisfaction about Handloom Products in India-A Study on Andhra Pradesh State Handloom Weavers’ Cooperative Society Limited (APCO showrooms), Journal of Textile and Apparel, Technology and Management, 9, 3, (2015); Rizwana M., Problems Faced by Customers with Reference to Buying of Handloom Products-An Empirical Study, International Journal of Business and Administration Research Review, 2, 10, pp. 55-57, (2015); Lakshmi S., Consumer Buying Behavior Towards Online Shopping, International Journal of Research, (2016); Lim P.L., Yazdanifard R., What internal and external factors influence impulsive buying behavior in online shopping?, Global Journal of Management and Business Research, (2015); Wei L., Decision-making Behaviours toward Online Shopping, International Journal of Marketing Studies, 8, 3, (2016); Prakash M.R., Saravanan N., A Study on Female Consumers Buying Behavior Towards Textile Showrooms in Chennai, Indian Journal of Applied Research, (2015); Kumar M.M.S., Kumar D.P., Narayana M.S., Impact of Brand Equity on Customers Purchase Decision Making while Choosing Branded over Unbranded Apparel in Andhra Pradesh, International Journal of Applied Engineering Research, 11, 7, (2016); Divakala M., Muthian V.; Chitra B., A Study on Consumer Attitude towards Buying in Sri Devi Textiles, International Journal of Business and Management Invention, 3, 1, pp. 35-40, (2014); Nema J., Bhopatkar N., A Study of Women’s Buying Behaviour in Urban Areas with Respect to Branded and Non-Branded Apparels; Salehi M., Consumer Buying Behavior towards Online Shopping Stores in Malaysia, International Journal of Academic Research in Business and Social Sciences, 2, 1, (2012); Rajput N., Kesharwani S., Khanna A., Dynamics of female buying behaviour: A study of branded apparels in India, International Journal of Marketing Studies, 4, 4, (2012); Rani N., Bains A., Consumer Behaviour Towards Handloom Products In The State of Punjab & Haryana, International Journal of Advanced Research in Management and Social Sciences, (2014); Wang N., Liu D., Cheng J., Study on the influencing factors of online shopping. Proceedings of the 11th Joint Conference on Information Sciences, Published by Atlantis Press, pp. 1-4, (2008); Murali Krishna B., Venkata Ramana J.A., Study on Customer Awareness and Satisfaction towards handloom products with special reference to Guntur District–Andhra Pradesh. Acme Intellects International Journal of Research in Management, Social Sciences & Technology, 16, 16, (2016); Purohit P., The Study of Traditional Hand Painted Kalamkari to Design a Set of New Age Prints, (2015); Remaswamy N., Villvarayanallur M., Kumar G., Human Resource and Skill Requirements in the Handalooms and Handicraft Sector, (2015); Rayapatiraveendranadh, Handloom Market (Need For Market Assessment, Problems & Marketing Strategy), International Journal of Emerging Research in Management &Technology, 2, 5, pp. 6-11, (2013); Sanad R.A., Consumer Attitude and Purchase Decision towards Textiles and Apparel Products, World Journal of Textile Engineering and Technology, 2, pp. 16-30, (2016); Nazir S., Tayyab A., Sajid A., Rashid H., Javed I., How Online Shopping Is Affecting Consumers Buying Behavior in Pakistan?, International Journal of Computer Science Issues, 9, 3, pp. 486-495, (2012); Shim S., Kotsiopulos A., A typology of apparel shopping orientation segments among female consumers, Clothing and Textiles Research Journal, 12, 1, pp. 73-85, (1993); Hassan T.U., Factors Influencing Consumer Actual Online Buying, IOSR Journal of Business and Management (IOSR-JBM), 17, 6, pp. 56-61, (2015); Hoang T.P., Van N.T., Huong L.T.M., Van P.T.H., The factors affecting the decision to shop online of Vietnamese youth in fashion field, International Journal of Research in Finance and Marketing, 6, 9, pp. 64-73, (2016); Terblanche R.M., A Lifestyle Typification of Female Students, with Specific Reference to Fashion Awareness and Clothing Orientation, (1990); Lim Y.J., Osman A., Salahuddin S.N., Romle A.R., Abdullah S., Factors influencing online shopping behavior: The mediating role of purchase intention, Procedia Economics and Finance, pp. 401-410, (2016); Bauboniene Z., Guleviciute G., E-Commerce Factors Influencing Consumers’ Online Shopping Decision, Socialinės Technologijos Social Technologies, 5, 1, pp. 74-81, (2015)",null,null,"Institute of Advanced Scientific Research, Inc.",{"$nulls":5},"1943023X",null,null,null,"English","J. Adv. Res. Dyn. Control. Syst.","Article","Final",null,"Scopus","2-s2.0-85053840493"]
["Arnold F.; Cardenas I.; Sörensen K.; Dewulf W.","Arnold, F. (57198812855); Cardenas, I. (57191038157); Sörensen, K. (7202406244); Dewulf, W. (57191031550)","57198812855; 57191038157; 7202406244; 57191031550","Simulation of B2C e-commerce distribution in Antwerp using cargo bikes and delivery points",2018.0,"European Transport Research Review",10.0,1.0,2.0,null,null,null,127.0,"10.1007/s12544-017-0272-6","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85037095070&doi=10.1007%2fs12544-017-0272-6&partnerID=40&md5=0fb44e26ba1886aadaa78e5bf98ba135","Operations Research Group ANT/OR, University of Antwerp, Antwerp, Belgium; Department of Transport and Regional Economics, University of Antwerp, Antwerp, Belgium","Arnold F., Operations Research Group ANT/OR, University of Antwerp, Antwerp, Belgium; Cardenas I., Department of Transport and Regional Economics, University of Antwerp, Antwerp, Belgium; Sörensen K., Operations Research Group ANT/OR, University of Antwerp, Antwerp, Belgium; Dewulf W., Department of Transport and Regional Economics, University of Antwerp, Antwerp, Belgium","Purpose: The growth of e-commerce is accompanied by an increasing distribution of parcels in cities resulting in externalities like traffic congestion or emissions. As a consequence, different delivery concepts like bike deliveries or delivery points have been suggested. Naturally, companies will only accept these changes, if they do not result in higher costs. However, it is difficult to predict the impact of a certain delivery concept in a certain city. This leads to the research question, how different delivery scenarios for a certain area can be assessed and compared, especially if some of them have not been implemented. Methods: Using a case study, we demonstrate how the effects of different delivery concepts can be quantified with the help of a simulation study. We take care to accurately model the delivery processes and utilise a real-world dataset and realistic cost values. On the basis of these inputs, we simulate and analyse the current state-of-the-practice in the distribution of e-commerce goods in Antwerp and compare it to possible `what-if’ scenarios. Results: The results highlight that the investigated delivery concepts can benefit either the companies or the quality of life in the city. Operational costs of companies can be reduced by stimulating customer self-pick-up, while externalities decrease with the implementation of a cargo bike distribution system. Conclusions: We demonstrate that both operational and external costs can be minimised, if involved stakeholders from industry and the public look for sustainable delivery solution jointly. © 2017, The Author(s).","B2C e-commerce; city logistics; simulation; vehicle routing","Bicycles; Commerce; Costs; Electronic commerce; Traffic congestion; Vehicle routing; B2C e-commerce; City logistics; Distribution systems; Research questions; simulation; Simulation studies; State of the practice; Sustainable delivery; Distribution of goods",{"$nulls":6},"E-commerce and delivery. 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How the Internet changes city centre shopping, J Retail Consum Serv, 14, 3, pp. 192-207, (2007); Ducret R., Parcel deliveries and urban logistics: Changes and challenges in the courier express and parcel sector in Europe — The French case, Res Transp Bus Manag, 11, pp. 15-22, (2014); Cullinane S., From Bricks to Clicks: The Impact of Online Retailing on Transport and the Environment, Transp Rev, 29, 6, pp. 759-776, (2009); Weltevreden J.W.J., Rotem-Mindali O., Mobility effects of b2c and c2c e-commerce in the Netherlands: a quantitative assessment, J Transp Geogr, 17, 2, pp. 83-92, (2009); Brown J.R., Guiffrida A.L., Carbon emissions comparison of last mile delivery versus customer pickup, Int J Log Res Appl, 17, 6, pp. 503-521, (2014); Browne M., The impact of e-commerce on transport, (2001); Mokhtarian P.L., A conceptual analysis of the transportation impacts of B2C e-commerce, Transportation (Amst), 31, 3, pp. 257-284, (2004); Lin I.I., Mahmassani H.S., Can Online Grocers Deliver?: Some Logistics Considerations, Transp Res Rec J Transp Res Board, 1817, 1, pp. 17-24, (2007); Van Der Helm P., Competitiveness of Logistics Service Centers in the High Volume Parcel Delivery Market, (2015); Weltevreden J.W.J., B2c e-commerce logistics: the rise of collection-and-delivery points in The Netherlands, Int J Retail Distrib Manag, 36, 8, pp. 638-660, (2008); Morganti E., Dablanc L., Fortin F., Final deliveries for online shopping: The deployment of pickup point networks in urban and suburban areas, Res Transp Bus Manag, 11, pp. 23-31, (2014); Morganti E., Seidel S., Blanquart C., Dablanc L., Lenz B., The impact of e-commerce on final deliveries: Alternative parcel delivery services in france and germany, Trans Res Proc, 4, pp. 178-190, (2014); Durand B., Gonzalez-Feliu J., Urban Logistics and E-Grocery: Have Proximity Delivery Services a Positive Impact on Shopping Trips?, Procedia Soc Behav Sci, 39, pp. 510-520, (2012); Song L., Cherrett T., McLeod F., Guan W., Addressing the last mile problem: transport impacts of collection and delivery points, Transp Res Rec: J Transp Res Board, 2097, pp. 9-18, (2009); Click and collect booms in Europe, Retrieved from www2.deloitte.com/, (2015); Comi A., Nuzzolo A., Exploring the Relationships Between e-shopping Attitudes and Urban Freight Transport, Transp Res Procedia, 12, pp. 399-412, (2016); Park H., Park D., Jeong I.J., An effects analysis of logistics collaboration in last-mile networks for CEP delivery services, Transp Policy, 50, pp. 115-125, (2016); Perboli G., Rosano M., Gobbato L., Parcel delivery in urban areas: opportunities and threats for the mix of traditional and green business models. Working paper CIRRELT-2017-02, Montreal, (2017); Spijkerman R., Fashion Consumer Behaviour Impact on the Model of Last Mile Urban Area Emissions, Transp Res Procedia, 12, pp. 718-727, (2016); Pan S., Chen C., Zhong R.Y., A crowdsourcing solution to collect e-commerce reverse flows in metropolitan areas, IFAC-PapersOnLine, 48, 3, pp. 1984-1989, (2015); Wang X., Zhan L., Ruan J., Zhang J., How to choose ‘last mile’ delivery modes for E-fulfillment, Math Probl Eng, 2014, 1, (2014); Gevaers R., Evaluation of innovations in B2C last mile, B2C reverse & waste logistics, (2013); Giuffrida M., Mangiaracina R., Tumino A., Home Delivery vs Parcel Lockers: an economic and environmental assessment, Proceedings of XXI Summer School \"Francesco Turco\" - Industrial, Systems Engineering, pp. 225-230, (2012); Gonzalez-Feliu J., Ambrosini C., Routhier J.L., New trends on urban goods movement: Modelling and simulation of e-commerce distribution, Eur Transp - Trasp Eur, 50, 6, pp. 1-23, (2012); Siikavirta H., Punakivi M., Ka M., Linnanen L., Effects of E-Commerce on Greenhouse Gas Emissions A Case Study of Grocery Home Delivery, J Ind Ecol, 6, 2, pp. 83-97, (2003); The green mile? 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A simulation study on freight waterborne transport in the inner-city of Amsterdam, Int J Urban Sci, 18, 2, pp. 186-200, (2014); Teo J.S.E., Taniguchi E., Qureshi A.G., Evaluating City Logistics Measure in E-Commerce with Multiagent Systems, Procedia Soc Behav Sci, 39, pp. 349-359, (2012); Russo F., Comi A., A model system for the ex-ante assessment of city logistics measures, Res Transp Econ, 31, 1, pp. 81-87, (2011); Anderluh A., Hemmelmayr V.C., Nolz P.C., Synchronizing vans and cargo bikes in a city distribution network, (2016); Cardenas I., Beckers J., Vanelslander T., Verhetsel A., Spatial characteristics of failed and successful E- commerce deliveries in Belgian cities, ILS 2016, 6th International Conference on Information Systems, Logistics and Supply Chain, pp. 1-10, (2016); Shahid R., Bertazzon S., Knudtson M.L., Ghali W.A., Comparison of distance measures in spatial analytical modeling for health service planning, BMC Health Serv Res, 9, 1, (2009); Demir E., Bektas T., Laporte G., A review of recent research on green road freight transportation, Eur J Oper Res, 237, 3, pp. 775-793, (2014); Cattaruzza D., Absi N., Feillet D., Gonzalez-Feliu J., Vehicle routing problems for city logistics, EURO J Transp Logist, 6, 1, pp. 51-79, (2017); Clarke G., Wright J.W., Scheduling of vehicles from a central depot to a number of delivery points, Oper Res, 12, 4, pp. 568-581, (1964); Prud'homme R., Lee C.-W., Size, Sprawl, Speed and the Efficiency of Cities, Urban Stud, 36, 11, pp. 1849-1858, (1999); Browne M., Allen J., Leonardi J., Evaluating the use of an urban consolidation centre and electric vehicles in central London, IATSS Res, 35, 1, pp. 1-6, (2011); Cardenas I.D., Dewulf W., Vanelslander T., The e-commerce parcel delivery market: developing a model for comparing home B2C deliveries vs pick-up points. In: World Conference on Transport Research: WCTR 2016, Shanghai, 10–15 July 2016, pp 1–13, (2016); Update of the Handbook on External Costs of, Transport, (2014)","F. Arnold; Operations Research Group ANT/OR, University of Antwerp, Antwerp, Belgium; email: florian.arnold@uantwerpen.be",null,"Springer Verlag",{"$nulls":5},1.8670717E7,null,null,null,"English","Eur. Transp. Res. Rev.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85037095070"]
["Wu P.-J.; Lin K.-C.","Wu, Pei-Ju (56814106200); Lin, Kun-Chen (57196946330)","56814106200; 57196946330","Unstructured big data analytics for retrieving e-commerce logistics knowledge",2018.0,"Telematics and Informatics",35.0,1.0,null,237.0,244.0,7.0,75.0,"10.1016/j.tele.2017.11.004","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85033789276&doi=10.1016%2fj.tele.2017.11.004&partnerID=40&md5=927cccbbb115c503b302f89634cc298a","Department of Transportation and Logistics; Chief Innovation & Development Officer, Innovation Center for Intelligent Transportation and Logistics, Feng Chia University, Taiwan; Department of Transportation and Logistics, Feng Chia University, Taiwan","Wu P.-J., Department of Transportation and Logistics; Chief Innovation & Development Officer, Innovation Center for Intelligent Transportation and Logistics, Feng Chia University, Taiwan; Lin K.-C., Department of Transportation and Logistics, Feng Chia University, Taiwan","The divergent evolution of e-commerce has complicated its correspondingly logistics management. However, few studies have explored e-commerce logistics business models via big data analytics. Hence, this investigation explores e-commerce logistics business models from unstructured big data. Specifically, this work develops a hybrid content analytical model to scrutinize essential knowledge of e-commerce logistics. The empirical results of the proposed model incorporate theories of resource dependence theory (RDT) and innovation diffusion theory (IDT) to generate logistical strategies. Ten critical themes of e-commerce logistics from topic mining are “Southeast Asia's e-commerce logistics payments” “E-commerce order management” “E-commerce logistics cloud services” “E-commerce logistics package management” “Europe e-commerce trends” “India's e-commerce logistics” “E-commerce distribution management” “Tax policies” “E-commerce logistics platforms” and “E-commerce logistics networks”. Moreover, the fundamental rule of “cross-border e-commerce logistics” is uncovered by the association rules model. The proposed hybrid content analytics framework provides a research foundation for e-commerce logistics management. Furthermore, e-commerce logistics can be implemented by vital strategies: “Establish inter-organizational and technical collaboration to create positive operations performance” and “Comprehend law, policy, and cultural differences to customize appropriate technologies of e-commerce logistics”. © 2017 Elsevier Ltd","Big data analytics; Content analytics; E-commerce; Logistics management; Unstructured big data","Commerce; Data mining; Electronic commerce; Logistics; Appropriate technologies; Content analytics; Data analytics; Distribution management; E-commerce logistics business; Innovation diffusion theory; Inter-organizational; Logistics management; Big data",{"$nulls":4},"MOST 106-2410-H-035-013-MY2, (106-2410-H-035-013-MY2); Ministry of Science and Technology, Taiwan","This work is partially supported by Ministry of Science and Technology , Taiwan, ROC under grant MOST 106-2410-H-035-013-MY2 .  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["Ahmadi-Javid A.; Amiri E.; Meskar M.","Ahmadi-Javid, Amir (15623098100); Amiri, Elahe (25654631700); Meskar, Mahla (57202903349)","15623098100; 25654631700; 57202903349","A Profit-Maximization Location-Routing-Pricing Problem: A Branch-and-Price Algorithm",2018.0,"European Journal of Operational Research",271.0,3.0,null,866.0,881.0,15.0,32.0,"10.1016/j.ejor.2018.02.020","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85049733695&doi=10.1016%2fj.ejor.2018.02.020&partnerID=40&md5=d034a74c3a840c507a313be4cfa78b8c","Department of Industrial Engineering, Amirkabir University of Technology, Tehran, Iran","Ahmadi-Javid A., Department of Industrial Engineering, Amirkabir University of Technology, Tehran, Iran; Amiri E., Department of Industrial Engineering, Amirkabir University of Technology, Tehran, Iran; Meskar M., Department of Industrial Engineering, Amirkabir University of Technology, Tehran, Iran","This paper for the first time considers a profit-maximization location-routing problem with price-sensitive demands. The problem determines the location of facilities, the allocation of vehicles and customers to established facilities, and the pricing and routing decisions in order to maximize the total profit of serving customers. A mixed-integer linear programming model is presented, which can only be used to solve small-size instances with commercial optimization solvers. Then, the model is reformulated as a set-packing model and solved by an efficient branch-and-price algorithm for large-size instances. The proposed algorithm can also be used to solve the more basic problems such as location-routing with profit and price-inelastic demands or vehicle routing with profit and price-sensitive demands, which has not been considered by any research earlier. The column-generation procedure is developed based on a new variant of the elementary shortest path problem with resource constraints where demands are price dependent. Our numerical study indicates the substantial advantage of the integrated model. The proposed model can be used to design the distribution networks of online shopping systems in which delivered pricing is influenced by the last mile delivery. © 2018 Elsevier B.V.","Branch-and-price and column generation; Location-Routing Problems (LRP); Mixed-Integer Linear Programming (MILP); Price-sensitive demands and delivered pricing; Vehicle Routing Problems with Profit (VRPP)","Costs; Graph theory; Location; Online systems; Profitability; Routing algorithms; Vehicle routing; Vehicles; Column generation; Location routing problem; Mixed integer linear programming (MILP); Price-sensitive demand; Vehicle Routing Problems; Integer programming",{"$nulls":6},"Ahmadi-Javid A., Azad N., Incorporating location, routing and inventory decisions in supply chain network design, Transportation Research Part E: Logistics and Transportation Review, 46, pp. 582-597, (2010); Ahmadi-Javid A., Ghandali R., An efficient optimization procedure for designing a capacitated distribution network with price-sensitive demand, Optimization and Engineering, 15, pp. 801-817, (2014); 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Feillet D., Dejax P., Gendreau M., Travelling salesman problem with profits, Transportation Science, 39, pp. 188-205, (2005); Fernandez P., Pelegrin B., Perez M.D.G., Peeters P.H., A discrete long-term location–price problem under the assumption of discriminatory pricing: Formulations and parametric analysis, European Journal of Operational Research, 179, pp. 1050-1062, (2007); Gansterer M., Kucuktepe M., Hartl R.F., The multi-vehicle profitable pickup and delivery problem, OR Spectrum, 39, pp. 303-319, (2017); Greenhut M.L., Hwang M., Ohta H., Observations on the shape and relevance of the spatial demand function, Econometrica, 43, pp. 669-682, (1975); Gunawan A., Lau H.C., Vansteenwegen P., Orienteering problem: A survey of recent variants, solution approaches and applications, European Journal of Operational Research, 255, pp. 315-332, (2016); Hanjoul P., Hansen P., Peeters D., Uncapacitated plant location under alternative spatial price policies, Management Science, 36, pp. 41-57, (1990); Hansen P., Peeters D., Thisse J.F., Simple plant location under uniform delivered pricing, European Journal of Operational Research, 6, pp. 94-103, (1981); Hansen P., Thisse J.F., Hanjoul P., Facility location under zone pricing, Journal of Regional Science, 37, pp. 1-22, (1997); He Z., Cheng T.C.E., Dong J., Wang S., Evolutionary location and pricing strategies for service merchants in competitive O2O markets, European Journal of Operational Research, 254, pp. 595-609, (2016); Hoover E.M., Spatial price discrimination, The Review of Economic Studies, 4, pp. 182-191, (1937); Hotelling H., Stability in competition, Economic Journal, 39, pp. 41-57, (1929); Houck D.J., Picard J.-C., Queyranne M., Vemuganti R.R., The travelling salesman problem as a constrained shortest path problem: Theory and computational experience, Opsearch, 17, pp. 93-109, (1980); Irnich S., Desaulniers G., Shortest path problems with resource constraints, Column generation, pp. 33-65, (2005); Jamil M., Batta R., Malon D.M., The traveling repairperson home base location problem, Transportation Science, 28, pp. 150-161, (1994); Lambrecht A., Seim K., Vilcassim N., Cheema A., Chen Y., Crawford G.S., Hosanagar K., Iyengar R., Koenigsberg O., Lee R., Miravete E.J., Price discrimination in service industries, Marketing Letters, 23, pp. 423-438, (2012); Laporte G., Location-routing problems, Vehicle routing: Methods and studies, pp. 293-318, (1988); Lederer P.J., Thisse J.F., Competitive location on networks under delivered pricing, Operations Research Letters, 9, pp. 147-153, (1990); Lopez R.B., Ferreira C., Santos B.S., Barretto S., A taxonomical analysis, current methods and objectives on location-routing problems, International Transactions in Operational Research, 20, pp. 795-822, (2013); Lozano L., Duque D., Medaglia A.L., An exact algorithm for the elementary shortest path problem with resource constraints, Transportation Science, 50, 1, pp. 348-357, (2015); Miller C.E., Tucker A.W., Zemlin R.A., Integer programming formulations and traveling salesman problems, Journal of Association for Computing Machinery, 7, pp. 326-329, (1960); Min H., Jayaraman V., Srivastava R., Combined location-routing problems: A synthesis and future research directions, European Journal of Operational Research, 108, pp. 1-15, (1998); Nagy G., Salhi S., The many-to-many location-routing problem, TOP, 6, pp. 261-275, (1998); Nagy G., Salhi S., Location-routing, issues, models, and methods: A review, European Journal of Operational Research, 117, pp. 649-672, (2007); Pelegrin B., Fernandez P., Perez M.D.G., Hernandez S.C., On the location of new facilities for chain expansion under delivered pricing, Omega, 40, pp. 149-158, (2012); Perez M.D.G., Hernandez P.F., Pelegrin B.P., On price competition in location-price models with spatially separated markets, TOP, 12, pp. 351-374, (2004); Prodhon C., Prins C., A survey of recent research on location-routing problems, European Journal of Operational Research, 238, pp. 1-17, (2014); Pugliese L.D.P., Guerriero F., A survey of resource constrained shortest path problems: Exact solution approaches, Networks, 62, pp. 183-200, (2013); Righini G., Salani M., Symmetry helps: Bounded bi-directional dynamic programming for the elementary shortest path problem with resource constraints, Discrete Optimization, 3, pp. 255-273, (2006); Righini G., Salani M., New dynamic programming algorithms for the resource constrained elementary shortest path problem, Networks, 51, pp. 155-170, (2008); Ryan D.M., Foster B.A., An integer programming approach to scheduling, Computer scheduling of public transport urban passenger vehicle and crew scheduling, pp. 269-280, (1981); Salhi S., Rand G.K., The effect of ignoring routes when locating depots, European Journal of Operational Research, 39, pp. 150-156, (1989); Tilk C., Rothenbacher A.K., Gschwind T., Irnich S., Asymmetry matters: Dynamic half-way points in bidirectional labeling for solving shortest path problems with resource constraints faster, European Journal of Operational Research, 261, pp. 530-539, (2017); Vansteenwegen P., Souffriau W., Oudheusden D.V., The orienteering problem: A survey, European Journal of Operational Research, 209, pp. 1-10, (2011); Varian H.R., Price discrimination, Handbook of Industrial Organization, 1, pp. 597-654, (1989); Vidal T., Maculan N., Ochi L.S., Vaz Penna P.H., Large neighborhoods with implicit customer selection for vehicle routing problems with profits, Transportation Science, 50, pp. 720-734, (2015); Vogel J., Spatial price discrimination with heterogeneous firms, The Journal of Industrial Economics, 59, pp. 661-676, (2011); Wagner J.L., Falkson L.M., Optimal nodal location of public facilities with price-sensitive demand, Geographical Analysis, 7, pp. 69-83, (1975)","A. Ahmadi-Javid; Department of Industrial Engineering, Amirkabir University of Technology, Tehran, Iran; email: ahmadi_javid@aut.ac.ir",null,"Elsevier B.V.",{"$nulls":5},3772217.0,null,"EJORD",null,"English","Eur J Oper Res","Article","Final",null,"Scopus","2-s2.0-85049733695"]
[null,null,null,"Manna from heaven: How e-commerce with drone delivery is taking flight in China",2018.0,"Economist (United Kingdom)",414.0,9092.0,{"$nulls":4},0.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85048246984&partnerID=40&md5=0b6fae88fdffd3fbb45cdfe12b675563",null,null,"[No abstract available]",{"$nulls":11},"Economist Newspaper Ltd",{"$nulls":5},130613.0,null,null,null,"English","Economist","Article","Final",null,"Scopus","2-s2.0-85048246984"]
["Cattaruzza D.; Brotcorne L.; Semet F.; Tounsi B.","Cattaruzza, Diego (55779083000); Brotcorne, Luce (6507640397); Semet, Frédéric (6701702000); Tounsi, Bayrem (57203574092)","55779083000; 6507640397; 6701702000; 57203574092","A three-phase matheuristic for the Packaging and Shipping Problem",2018.0,"Applied Mathematical Modelling",64.0,null,null,713.0,732.0,19.0,1.0,"10.1016/j.apm.2018.07.041","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85052289694&doi=10.1016%2fj.apm.2018.07.041&partnerID=40&md5=857307be960db4f53f92e4a0ee1139c6","INRIA Lille - Nord Europe, Villeneuve d'Ascq, 59650, France; Université de Lille, CNRS, Centrale Lille, Inria UMR 9189 - CRIStAL Centre de Recherche en Informatique Signal et Automatique de Lille, Lille, F-59000, France","Cattaruzza D., Université de Lille, CNRS, Centrale Lille, Inria UMR 9189 - CRIStAL Centre de Recherche en Informatique Signal et Automatique de Lille, Lille, F-59000, France; Brotcorne L., INRIA Lille - Nord Europe, Villeneuve d'Ascq, 59650, France; Semet F., Université de Lille, CNRS, Centrale Lille, Inria UMR 9189 - CRIStAL Centre de Recherche en Informatique Signal et Automatique de Lille, Lille, F-59000, France; Tounsi B., INRIA Lille - Nord Europe, Villeneuve d'Ascq, 59650, France","E-commerce has been continuously growing in the last years to a primary retail market. Recently in France, the threshold of 1 billion of online transactions was overcome. Due to a high demand fluctuation of e-commerce, the workforce sizing for the logistic chain is a challenging problem. Companies have to develop good strategies to have a sustainable workforce size while guaranteeing a high-level service. In this paper, we consider the management of the workforce for a warehouse of an e-commerce company. Specifically, we address issues as i) How the workforce at the warehouse can be determined; ii) What is the daily operational production planning; iii) How the demand peaks can be smoothed, and the production maintained ideally constant over the time horizon. To provide answers to these issues, we introduce the Packaging and Shipping Problem (PSP). The PSP looks for a solution approach that jointly determines the workforce over a multi-period horizon and daily operational plans while minimizing the total logistics cost. We consider two strategies that aim to enhance the flexibility of the process and the efficiency of resources use: reassignment and postponement. To tackle the Packaging and Shipping Problem we propose a model, and a three-phase matheuristic. This heuristic is proved to be competitive with respect to the direct solution of the model with a commercial solver on real-life based instances. © 2018 Elsevier Inc.","E-commerce; Matheuristic; Packaging and Shipping Problem; Warehouse management","Electronic commerce; Personnel; Production control; Ships; Warehouses; Commercial solvers; High-level services; Matheuristic; Online transaction; Operational production planning; Solution approach; Total logistics costs; Warehouse management; Packaging",{"$nulls":4},"Agence Nationale de la Recherche, ANR, (ANR-11-VPTT-0009)","This work was supported by the French National Research Agency (ANR-Agence Nationale de la Recherche) and was part of project RESPET - Efficient network managing for the door-to-door transportation services (gestion de RésEaux de Services Porte áporte Efficace pour le Transport de marchandises, ANR-11-VPTT-0009). Thanks are also due to the referees for their valuable comments.   ","Alptekinoglu A., Tang C.S., A model for analyzing multi-channel distribution systems, Eur. J. Oper. Res., 163, pp. 802-824, (2015); Chandra P., Fisher M., Coordination of production and distribution planning, Eur. J. Oper. Res., 72, pp. 503-517, (1994); Strack G., Fortz B., Riane F., Vyve M.V., Comparison of heuristic procedures for an integrated model for production and distribution planning in an environment of shared resources, CORE Discussion Paper, (2011); Absi N., Archetti C., Dauzere-Peres S., Feillet D., A two-phase iterative heuristic approach for the production routing problem, Transp. Sci., 49, pp. 784-795, (2014); Shu M.H., Huang J.C., Fu Y.C., A production-delivery lot sizing policy with stochastic delivery time and in consideration of transportation cost, Appl. Math. Modell., 39, pp. 2981-2993, (2015); Adulyasak Y., Cordeau J.F., Jans R., The production routing problem: a review of formulations and solution algorithms, Comput. Oper. Res., 55, pp. 141-152, (2015); Hiassat A., Diabat A., Rahwan I., A genetic algorithm approach for location-inventory-routing problem with perishable products, J. Manuf. Syst., 42, pp. 93-103, (2017); Baptiste P., Gaudimier E., Alsene E., Integration of production and shipping planning: a cooperative approach, J. Prod. Plan. Control, 19, pp. 645-654, (2008); Lee C.Y., Cetinkaya S., Jaruphongsa W., A dynamic model for inventory lot-sizing and outbound shipment scheduling at a third-party warehouse, Oper. Res., 51, pp. 735-747, (2003); Wang H., Lee C.Y., Production and transport logistics scheduling with two transport mode choices, Naval Res. Logist., 52, pp. 796-809, (2005); Siddiqui A., Verma M., Verter V., An integrated framework for inventory management and transportation of refined petroleum products: Pipeline or marine?, Appl. Math. Modell., 55, pp. 224-247, (2018); Ernst A.T., Jiang H., Krishnamoorthy M., Sier D., Staff scheduling and rostering: a review of applications, methods and models, Eur. J. Oper. Res., 153, pp. 3-27, (2004); Rong A., Grunow M., Shift designs for freight handling personnel at air cargo terminals, Transp. Res. Part E, 45, pp. 725-739, (2009); Stolletz R., Zamorano E., A rolling planning horizon heuristic for scheduling agents with different qualifications, Transp. Res. Part E, 68, pp. 39-52, (2014); Carbonara N., Pellegrino R., Real options approach to evaluate postponement as supply chain disruptions mitigation strategy, Int. J. Prod. Res., (2017); Bertazzi L., Savelsbergh M., Speranza M.G., Inventory routing, The Vehicle Routing Problem: Last Advances and New Challenges, pp. 49-72, (2008); Pang G., Muyldermans L., Vehicle routing and the value of postponement, J. Oper. Res. Soc., 64, pp. 1429-1440, (2013); Mahar S., Wright P.D., The value of postponing online fulfillment decisions in multi-channel retail/e-tail organizations, Comput. Oper. Res., 36, pp. 3061-3072, (2009); neyro P.P., Viera O., The economic lot-sizing problem with remanufacturing and one-way substitution, Int. J. Prod. Econ., 124, pp. 482-488, (2010); Chen Z.L., Integrated production and outbound distribution scheduling: Review and extensions, Oper. Res., 58, pp. 130-148, (2010); Ball M.O., Heuristics based on mathematical programming, Surv. Oper. Res. Manag. Sci., 16, pp. 181-199, (2011); Gendron B., Crainic T.G., Frangioni A., Multicommodity capacitated network design, Telecommunications Network Planning, pp. 1-19, (1999); Cattaruzza D., Brotcorne L., Semet F., Tounsi B., (2018)","D. Cattaruzza; Université de Lille, CNRS, Centrale Lille, Inria UMR 9189 - CRIStAL Centre de Recherche en Informatique Signal et Automatique de Lille, Lille, F-59000, France; email: diego.cattaruzza@centralelille.fr",null,"Elsevier Inc.",{"$nulls":5},"0307904X",null,"AMMOD",null,"English","Appl. Math. Model.","Article","Final","All Open Access; Bronze Open Access; Green Open Access","Scopus","2-s2.0-85052289694"]
["Hasan H.R.; Salah K.","Hasan, Haya R. (57200504343); Salah, Khaled (35617663600)","57200504343; 35617663600","Blockchain-Based Proof of Delivery of Physical Assets with Single and Multiple Transporters",2018.0,"IEEE Access",6.0,null,8443322.0,46781.0,46793.0,12.0,79.0,"10.1109/ACCESS.2018.2866512","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85052687929&doi=10.1109%2fACCESS.2018.2866512&partnerID=40&md5=0d0baa338f90b0ca1b20374710a25691","Electrical and Computer Engineering Department, Khalifa University, Abu Dhabi, 127788, United Arab Emirates","Hasan H.R., Electrical and Computer Engineering Department, Khalifa University, Abu Dhabi, 127788, United Arab Emirates; Salah K., Electrical and Computer Engineering Department, Khalifa University, Abu Dhabi, 127788, United Arab Emirates","With the widespread of E-commerce, the need of a trusted system to ensure the delivery of traded items is crucial. Current proof of delivery (PoD) systems lacks transparency, traceability, and credibility. These systems are mostly centralized and rely on trusted third parties (TTPs) to complete the delivery between sellers and buyers. TTPs can be costly, a single point of failure, and subject to hacking, privacy evasion, and compromise. The blockchain is an immutable, trusted, and decentralized ledger with logs and events that can be used for transparency, traceability, and tracking. In this paper, we present a solution and a general framework using the popular permissionless Ethereum blockchain to create a trusted, decentralized PoD system that ensures accountability, auditability, and integrity. The solution uses Ethereum smart contracts to prove the delivery of a shipped item between a seller and a buyer irrespective of the number of intermediate transporters needed. In our proposed solution, all participating entities are incentivized to act honestly by using a double deposit collateral. Automated payment in ether is an integral part of a solution to ensure that every entity gets its intended share of ether upon successful delivery. An arbitration mechanism is also incorporated if a dispute arises during the shipping process. In this paper, we show how we implemented, verified, and tested the proper functionality of our PoD solution. We also provide security analysis and give estimates of the cost consumption in ether gas. We made the full code of the Ethereum smart contracts publicly available at Github. © 2013 IEEE.","Blockchain; cyber security; decentralized management; Ethereum; security analysis; smart contracts","Ethers; Network security; Personal computing; Security systems; Ships; Transparency; Cyber security; Decentralized management; Ethereum; Security analysis; Smart contracts; Blockchain",{"$nulls":4},"Telecommunications Regulatory Authority, TRA","This work was supported by ICT Fund, UAE.","Consumers Are Now Doing Most of Their Shopping Online; UPS Study: Purchases from Marketplaces Nearly Universal Retail Now Global As E-Commerce Shoppers Cross Borders; About Shipping Carrier Contacts; Hasan H.R., Salah K., Blockchain-based solution for proof of delivery of physical assets, Proc. Int. Conf. Blockchain, pp. 139-152, (2018); Toyoda K., Mathiopoulos P.T., Sasase I., Ohtsuki T., A novel blockchain-based product ownership management system (POMS) for anti-counterfeits in the post supply chain, IEEE Access, 5, pp. 17465-17477, (2017); Biswas K., Muthukkumarasamy V., Securing smart cities using blockchain technology, Proc. IEEE 18th Int. Conf. High Perform. Comput. Commun.; IEEE 14th Int. Conf. Smart City; IEEE 2nd Int. Conf. Data Sci. Syst. (HPCC/SmartCity/DSS), pp. 1392-1393, (2016); Singh S., Singh N., Blockchain: Future of financial and cyber security, Proc. 2nd Int. Conf. Contemp. Comput. Inform. (IC3I), pp. 463-467, (2016); Christidis K., Devetsikiotis M., Blockchains and smart contracts for the Internet of Things, IEEE Access, 4, pp. 2292-2303, (2016); Two Party Contracts; How Our Escrow Smart Contract Works; Truly Decentralized, Peer-to-Peer Ecommerce Features; Soma the Social Market Place; Syscoin 3.0: A Peer-to-Peer Electronic Cash System Built for Business Applications; Double Deposit Escrow-Bitbay; Eth Gas Station; Khan M.A., Salah K., Iot security: Review, blockchain solutions, and open challenges, Future Gener. Comput. Syst., 82, pp. 395-411, (2018)","H.R. Hasan; Electrical and Computer Engineering Department, Khalifa University, Abu Dhabi, 127788, United Arab Emirates; email: khaled.salah@kustar.ac.ae",null,"Institute of Electrical and Electronics Engineers Inc.",{"$nulls":5},2.1693536E7,null,null,null,"English","IEEE Access","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85052687929"]
["Kwon N.; Kim J.; Lim S.; Chae J.; Park H.","Kwon, Namgu (56538033000); Kim, Jibum (56387773100); Lim, Sunho (8437951300); Chae, Jinseok (15123874100); Park, Heemin (55443709900)","56538033000; 56387773100; 8437951300; 15123874100; 55443709900","T-reduce: Route-aware mobile trajectory data reduction in transportation management systems",2018.0,"IEEE Access",6.0,null,8403216.0,38934.0,38946.0,12.0,1.0,"10.1109/ACCESS.2018.2852787","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85049438902&doi=10.1109%2fACCESS.2018.2852787&partnerID=40&md5=a979385653c2dc20f3963030c26bc7d1","Department of Computer Science and Engineering, Incheon National University, Incheon, 22012, South Korea; T2WISTOR: TTU Wireless Mobile Networking Laboratory, Department of Computer Science, Texas Tech University, Lubbock, 79409, TX, United States; Department of Software, Sangmyung University, Cheonan, 31066, South Korea","Kwon N., Department of Computer Science and Engineering, Incheon National University, Incheon, 22012, South Korea; Kim J., Department of Computer Science and Engineering, Incheon National University, Incheon, 22012, South Korea; Lim S., T2WISTOR: TTU Wireless Mobile Networking Laboratory, Department of Computer Science, Texas Tech University, Lubbock, 79409, TX, United States; Chae J., Department of Computer Science and Engineering, Incheon National University, Incheon, 22012, South Korea; Park H., Department of Software, Sangmyung University, Cheonan, 31066, South Korea","Due to the increasingly popular e-commerce and rapidly growing global market of delivery services, transportation management system (TMS) has been playing a critical role in minimizing transportation delay and cost as well as improving reliability. However, how to efficiently keep track of running vehicles and judiciously store their corresponding trajectories become a key issue in the presence of scarce wireless bandwidth and limited storage space. In this paper, we propose a novel mobile trajectory reduction scheme, called T-Reduce, to reduce the size of trajectory data stored in a TMS server. We first develop a path refinement operation to adjust raw location update data transmitted from vehicles to a given road topology as close as possible to improve their location accuracy. Second, we develop a route matching operation consisting of three sub-operations, route extraction, route recognition, and trajectory generation, for the server to identify and extract a set of routes by decomposing the received location update data. Then, the server can store each trajectory as a set of corresponding route ids instead of storing entire location update data. We set up a small-scale testbed, implement the proposed scheme with a real-world trace data collected from a logistic company, and conduct extensive experiments for performance evaluation and comparison. The experimental results show that the proposed scheme can significantly reduce the average trajectory error and route information up to 26.4% and 88%, respectively, compared to that of two prior trajectory-based and corner-based approaches. The proposed approach can also achieve up to 5.72 times cost efficiency compared to the prior approaches. © 2013 IEEE.","Location update; mobile trajectory; route information; transportation management system","Approximation algorithms; Data mining; Digital storage; Highway administration; Information management; International trade; Location; Servers; Trajectories; Transportation routes; Wireless telecommunication systems; Location update; Roads; Route information; Transportation management systems; Wireless communications; Data reduction",{"$nulls":4},"Incheon National University, INU","This work was supported by a Incheon National University Research Grant in 2014.","Global Express and Small Parcels, (2015); Montly/Yearly Truck Registra-tion Information, (2015); Zhang Y., Zhao J., Cao G., On scheduling vehicle-roadside data access, Proc. ACM VANET, pp. 9-18, (2007); Gett. A Ride Sharing App; Lyft. A Ride Sharing App; Sidecar. A Ride Sharing App; Douglas D.H., Peucker T.K., Algorithms for the reduction of the number of points required to represent a digitized line or its caricature, Cartographica, 10, 2, pp. 112-122, (1973); Qian H., Lu Y., Simplifying GPS trajectory data with enhanced spatial-temporal constraints, ISPRS Int. J. Geo-Inf., 6, 11, pp. 329-353, (2017); Imai H., Iri M., Polygonal approximations of a curve-Formulations and algorithms, Proc. Comput. Morphol., pp. 71-86, (1988); Fard M.R., Mohaymany A.S., Shahri M., A new methodology for vehicle trajectory reconstruction based on wavelet analysis, Transp. Res. C, Emerg. Technol., 74, pp. 150-167, (2017); Zhou J., Leong H., Lu Q., Lee K.C.K., Optimizing update threshold for distance-based location tracking strategies in moving object environments, Proc. IEEE Int. Symp. World Wireless, Mobile Multimedia Netw. (WoWMoM), pp. 18-21, (2007); Pitoura E., Samaras G., Locating objects in mobile computing, IEEE Trans. Knowl. 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Int. Conf. Data Eng. (ICDE), pp. 1144-1155, (2012); Harris C., Stephens M., A combined corner and edge detector, Proc. Alvey Vis. Conf., pp. 147-151, (1988); Matouek J., Geometric range searching, ACM Comput. Surv., 26, 4, pp. 422-461, (1994); De Berg M., Cheong O., Van Kreveld M., Overmars M., Orthogonal range searching: Querying a database, Computational Geometry: Algorithms and Application, pp. 95-120, (2008); Willard D.E., New data structures for orthogonal range queries, SIAM J. Comput., 14, 1, pp. 232-253, (1985); Bentley J.L., Multidimensional binary search trees used for associative searching, Commun. ACM, 18, 9, pp. 509-517, (1975); Daum Maps API","J. Chae; Department of Computer Science and Engineering, Incheon National University, Incheon, 22012, South Korea; email: jschae@inu.ac.kr",null,"Institute of Electrical and Electronics Engineers Inc.",{"$nulls":5},2.1693536E7,null,null,null,"English","IEEE Access","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-85049438902"]
["Pan S.; Giannikas V.; Han Y.; Grover-Silva E.; Qiao B.","Pan, Shenle (36646395300); Giannikas, Vaggelis (53463493700); Han, Yufei (57303708000); Grover-Silva, Etta (56495381200); Qiao, Bin (57191037538)","36646395300; 53463493700; 57303708000; 56495381200; 57191037538","Using customer-related data to enhance e-grocery home delivery",2017.0,"Industrial Management and Data Systems",117.0,9.0,null,1917.0,1933.0,16.0,90.0,"10.1108/IMDS-10-2016-0432","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85031287982&doi=10.1108%2fIMDS-10-2016-0432&partnerID=40&md5=4ec56e2cf5d8f34fcfc2120914a507ed","CGS – Centre de Gestion Scientifique, MINES ParisTech, PSL Research University, Paris, France; Institute for Manufacturing, University of Cambridge, Cambridge, United Kingdom; CGS – Centre de Gestion Scientifique, MINES ParisTech, PSL Research University, Paris, France; PERSEE, Centre for Process Energies and Energy Systems, MINES ParisTech, PSL Research University, Sophia Antipolis, France; CGS – Centre de Gestion Scientifique, MINES ParisTech, PSL Research University, Paris, France","Pan S., CGS – Centre de Gestion Scientifique, MINES ParisTech, PSL Research University, Paris, France; Giannikas V., Institute for Manufacturing, University of Cambridge, Cambridge, United Kingdom; Han Y., CGS – Centre de Gestion Scientifique, MINES ParisTech, PSL Research University, Paris, France; Grover-Silva E., PERSEE, Centre for Process Energies and Energy Systems, MINES ParisTech, PSL Research University, Sophia Antipolis, France; Qiao B., CGS – Centre de Gestion Scientifique, MINES ParisTech, PSL Research University, Paris, France","Purpose – The development of e-grocery allows people to purchase food online and benefit from home delivery service. Nevertheless, a high rate of failed deliveries due to the customer’s absence causes significant loss of logistics efficiency, especially for perishable food. The purpose of this paper is to propose an innovative approach to use customer-related data to optimize e-grocery home delivery. The approach estimates the absence probability of a customer by mining electricity consumption data, in order to improve the success rate of delivery and optimize transportation. Design/methodology/approach – The methodological approach consists of two stages: a data mining stage that estimates absence probabilities, and an optimization stage to optimize transportation. Findings – Computational experiments reveal that the proposed approach could reduce the total travel distance by 3-20 percent, and theoretically increase the success rate of first-round delivery approximately by18-26 percent. Research limitations/implications – The proposed approach combines two attractive research streams on data mining and transportation planning to provide a solution for e-commerce logistics. Practical implications – This study gives an insight to e-grocery retailers and carriers on how to use customer-related data to improve home delivery effectiveness and efficiency. Social implications – The proposed approach can be used to reduce environmental footprint generated by freight distribution in a city, and to improve customers’ experience on online shopping. Originality/value – Being an experimental study, this work demonstrates the effectiveness of data-driven innovative solutions to e-grocery home delivery problem. The paper also provides a methodological approach to this line of research. © Shenle Pan, Vaggelis Giannikas, Yufei Han, Etta Grover-Silva and Bin Qiao. Published by Emerald Publishing Limited.","City logistics; Data mining; E-commerce; Food delivery; Freight transportation; Home delivery","Commerce; Data mining; Efficiency; Electronic commerce; Sales; City logistics; Computational experiment; Design/methodology/approach; Effectiveness and efficiencies; Electricity-consumption; Environmental footprints; Food delivery; Home delivery; Freight transportation",{"$nulls":6},"Abreu J., Pereira F., Household electricity consumption routines and tailored feedback, ACEEE Summer Study on Energy Efficiency in Buildings, pp. 3-6, (2012); Agatz N.A.H., Fleischmann M., Van Nunen J.A.E.E., E-fulfillment and multi-channel distribution – A review, European Journal of Operational Research, 187, 2, pp. 339-356, (2008); Agatz N., Campbell A., Fleischmann M., Savelsbergh M., Time slot management in attended home delivery, Transportation Science, 45, 3, pp. 435-449, (2011); Allen J., Browne M., Woodburn A., Leonardi J., A review of urban consolidation centres in the supply chain based on a case study approach, Supply Chain Forum: An International Journal, 15, 4, pp. 100-112, (2014); 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Pan; CGS – Centre de Gestion Scientifique, MINES ParisTech, PSL Research University, Paris, France; email: shenle.pan@mines-paristech.fr",null,"Emerald Group Publishing Ltd.",{"$nulls":5},2635577.0,null,"IMDSD",null,"English","Ind Manage Data Sys","Article","Final","All Open Access; Green Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85031287982"]
["Xu S.X.; Huang G.Q.","Xu, Su Xiu (35773963700); Huang, George Q. (7403425048)","35773963700; 7403425048","Efficient Multi-Attribute Multi-Unit Auctions for B2B E-Commerce Logistics",2017.0,"Production and Operations Management",26.0,2.0,null,292.0,304.0,12.0,62.0,"10.1111/poms.12638","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84992473188&doi=10.1111%2fpoms.12638&partnerID=40&md5=ca8a9710c6197376e64d615db5ffe4fa","Institute of Physical Internet, Jinan University (Zhuhai Campus), Zhuhai, 519070, China; School of Electrical and Information Engineering, Jinan University (Zhuhai Campus), Zhuhai, 519070, China; HKU-ZIRI Lab for Physical Internet, Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong","Xu S.X., Institute of Physical Internet, Jinan University (Zhuhai Campus), Zhuhai, 519070, China, School of Electrical and Information Engineering, Jinan University (Zhuhai Campus), Zhuhai, 519070, China; Huang G.Q., Institute of Physical Internet, Jinan University (Zhuhai Campus), Zhuhai, 519070, China, HKU-ZIRI Lab for Physical Internet, Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong","This study is the first proposing allocatively efficient multi-attribute auctions for the procurement of multiple items. In the B2B e-commerce logistics problem (ELP), the e-commerce platform is the shipper generating a large number of online orders between product sellers and buyers, and third-party logistics (3PL) providers are carriers that can deliver these online orders. This study focuses on the ELP with multiple attributes (ELP-MA), which is generally the problem of matching the shipper's online orders and 3PL providers given that price and other attributes are jointly evaluated. We develop a one-sided Vickrey–Clarke–Groves (O-VCG) auction for the ELP-MA. The O-VCG auction leads to incentive compatibility (on the sell side), allocative efficiency, budget balance, and individual rationality. We next introduce the concept of universally unsatisfied set to construct a primal-dual algorithm, also called the primal-dual Vickrey (PDV) auction. We prove that the O-VCG auction can be viewed as a single-attribute multi-unit forward Vickrey (SA-MFV) auction. Both PDV and SA-MFV auctions realize VCG payments and truthful bidding for general valuations. This result reveals the underlying link not only between single-attribute and multi-attribute auctions, but between static and dynamic auctions in a multi-attribute setting. © 2016 Production and Operations Management Society","allocative efficiency; E-commerce logistics problem (ELP); mechanism design; multi-attribute auctions; primal-dual algorithm",{"$nulls":5},"Hangzhou Municipal; Lin'an City; RGC, (17212016, 712513); Zhejiang Provincial; Procter and Gamble, P&G; National Natural Science Foundation of China, NSFC, (51405307)","The authors thank the reviewers and editors for their critical but constructive comments. The authors acknowledge the HKSAR RGC GRF Project [Grant 712513, Grant 17212016], National Natural Science Foundation of China [Grant 51405307], Collaborative Research Fund from Procter & Gamble, Zhejiang Provincial, Hangzhou Municipal, and Lin'an City governments for partial financial support for this research.","Agrali S., Tan B., Karaesmen F., Modeling and analysis of an auction-based logistics market, Eur. J. Oper. Res., 191, 1, pp. 272-294, (2008); Asker J., Cantillon E., Properties of scoring auctions, RAND J. Econ., 39, 1, pp. 69-85, (2008); Asker J., Cantillon E., Procurement when price and quality matter, RAND J. Econ., 41, 1, pp. 1-34, (2010); Ausubel L.M., On generalizing the English auction, (1997); Ausubel L.M., An efficient ascending-bid auction for multiple objects, Am. Econ. Rev., 94, 5, pp. 1452-1475, (2004); Ausubel L.M., An efficient dynamic auction for heterogeneous commodities, Am. Econ. 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Game Theory, 1, 1, pp. 11-26, (1971); Sheffi Y., Combinatorial auctions in the procurement of transportation services, Interfaces, 34, 4, pp. 245-252, (2004); Song J., Regan A., Approximation algorithms for the bid construction problem in combinatorial auctions for the procurement of freight transportation contracts, Transp. Res. Part B, 39, 10, pp. 914-933, (2005); Vickrey W., Counterspeculation, auctions, and competitive sealed tenders, J. Financ., 16, 1, pp. 8-37, (1961); Vidyasekar A.D., Future of B2B online retailing, (2014); Xu S.X., Truthful, efficient auctions for transportation procurement, (2014); Xu S.X., Huang G.Q., Transportation service procurement in periodic sealed double auctions with stochastic demand and supply, Transp. Res. Part B, 56, pp. 136-160, (2013); Xu S.X., Huang G.Q., Efficient auctions for distributed transportation procurement, Transp. Res. Part B, 65, pp. 47-64, (2014); Xu S.X., Huang G.Q., Auction-based transportation procurement in make-to-order systems, IIE Trans., 47, 11, pp. 1236-1251, (2015); Xu S.X., Cheng M., Huang G.Q., Efficient intermodal transportation auctions for B2B e-commerce logistics with transaction costs, Transp. Res. Part B, 80, pp. 322-337, (2015); Xu S.X., Huang G.Q., Cheng M., Truthful, budget-balanced bundle double auctions for carrier collaboration, Transp. Sci., (2016)",null,null,"Wiley-Blackwell",{"$nulls":5},1.0591478E7,null,null,null,"English","Prod. Oper. Manage.","Article","Final",null,"Scopus","2-s2.0-84992473188"]
["Xu Y.; Zhang X.; Zhang H.","Xu, Ying (57198773063); Zhang, Xuemei (56098285200); Zhang, Hong (57863997000)","57198773063; 56098285200; 57863997000","Research on the E-commerce platform performance and green supply chain based on data mining and SVM",2016.0,"International Journal of Database Theory and Application",9.0,12.0,null,141.0,150.0,9.0,2.0,"10.14257/ijdta.2016.9.12.14","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85009971891&doi=10.14257%2fijdta.2016.9.12.14&partnerID=40&md5=c7d4d35d732c782bff9dd833d4ce98d7","Business School, Sias International University, Xinzheng City, 451150, China; School of Electronic Commerce, Ningbo DaHongYing University, Ningbo City, 315175, China; Department of Economics and Management, Changsha University, Changsha City, 410022, China","Xu Y., Business School, Sias International University, Xinzheng City, 451150, China; Zhang X., School of Electronic Commerce, Ningbo DaHongYing University, Ningbo City, 315175, China; Zhang H., Department of Economics and Management, Changsha University, Changsha City, 410022, China","In the network environment, supply chain management has greatly reduced the product development cycle, reduce the inventory. With the continuous development of information technology, e-commerce logistics platform has become the main factor affecting the development of logistics industry. In this paper, the authors research on the E-commerce platform performance and green supply chain based on data mining and SVM. The green supply chain considers the environmental problems in every link of the supply chain, and promotes the coordinated development of economy and environment. The result shows that the most critical factor that affects the satisfaction of consumer to B2C e-commerce platform is the accurate, complete and reliable logistics service. © 2016 SERSC.","Data mining; E-commerce platform; Green supply chain; SVM algorithm","Commerce; Electronic commerce; Supply chain management; Continuous development; Environmental problems; Green supply chain; Logistics platforms; Logistics services; Network environments; Product development cycle; SVM algorithm; Data mining",{"$nulls":4},"ZheJiang Nature Science Foundation of China, (LY13G030031); ZheJiang Philosophy & Society Science Foundation of China, (16NDJC094YB); Natural Science Foundation of Ningbo, (2014A610174); Ministry of Education of the People's Republic of China, MOE, (14YJC630154); Soft Science Foundation of Ningbo, (2016A10059); Changsha Science and Technology Project","This work was financially supported by project of Humanities and Social Sciences Research Project of Ministry of Education, China (14YJC630154); ZheJiang Nature Science Foundation of China (LY13G030031); ZheJiang Philosophy & Society Science Foundation of China(16NDJC094YB); NingBo Nature Science Foundation of China (2014A610174); Ningbo Soft Science Foundation (2016A10059); Changsha Science and Technology Project: The design and implementation of the SMEs accounting original document information system based on cloud services.","Yao D., Liu Q., Competitive pricing of mixed retail and e-tail distribution channels, Omega, 33, pp. 235-247, (2005); Enders A., Jelassi T., The converging business models of Internet and bricks-and retailers, European Management Journal, 18, pp. 542-550, (2000); Anand K., Context-general and Context-specific Determinants of Online Satisfaction and Loyalty for Commerce and Content Sites, Journal of Interactive Marketing, 24, 3, pp. 222-238, (2010); Niklas A., Fredrik S., Electronic commerce, marketing channels and logistics platform-a wholesaler perspective, European Journal of Operational Research, 144, 2, pp. 270-279, (2003); Druehl C., Porteus E., Price competition between an Internet firm and a bricks and mortar firm, Working Paper, pp. 24-30, (2001); Kim J., The role of etail quality, e-satisfaction and e-trust in online loyalty development process, Journal of Retailing and Consumer Services, 16, 4, pp. 239-247, (2009); Park S., Keh H., Modeling hybrid distribution channels: a game-theoretic analysis, Journal of Retailing and Consumer Services, 10, pp. 155-167, (2003); Cattani K., Gilland W., pricing strategies for a manufacturer adding a direct channel that competes with the traditional channel, Production and Operations Management, 15, pp. 40-56, (2006); Huang Z., Benyoucef M., From e-commerce to social commerce: A close look at design features, Electronic Commerce Research and Applications, 12, 4, pp. 246-259, (2013); Jutla D., Bodorik P., Developing internet e-commerce benchmarks, Information Systems, 24, 6, pp. 475-493, (1999)","H. Zhang; Department of Economics and Management, Changsha University, Changsha City, 410022, China; email: 1445061952@qq.com",null,"Science and Engineering Research Support Society",{"$nulls":5},2.005427E7,null,null,null,"English","Int. J. Database Theory Appl.","Article","Final",null,"Scopus","2-s2.0-85009971891"]
["Tandon U.; Kiran R.; Sah A.N.","Tandon, Urvashi (57190029593); Kiran, Ravi (22985431500); Sah, Ash N. (57190030141)","57190029593; 22985431500; 57190030141","Understanding barriers and drivers to online shopping: An emerging economy case",2017.0,"International Journal of Electronic Business",13.0,"2024-03-02",null,216.0,243.0,27.0,13.0,"10.1504/IJEB.2017.10003871","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85018411220&doi=10.1504%2fIJEB.2017.10003871&partnerID=40&md5=fbe22faba37f05d7281cbf758a0a6989","School of Humanities and Social Sciences (SHSS), Thapar University, P.O. Box 32, Patiala, 147004, India","Tandon U., School of Humanities and Social Sciences (SHSS), Thapar University, P.O. Box 32, Patiala, 147004, India; Kiran R., School of Humanities and Social Sciences (SHSS), Thapar University, P.O. Box 32, Patiala, 147004, India; Sah A.N., School of Humanities and Social Sciences (SHSS), Thapar University, P.O. Box 32, Patiala, 147004, India","The purpose of this paper is to empirically analyse the barriers and drivers towards online shopping in India. Data was collected from 410 online shoppers from the North Indian States of India. The results of the study reveal significant relation of security and privacy protection measure, time performance, ease of use, website design, ease of understanding, perceived risk, delivery procedures, the risk of losing personal and financial information, technology ignorance factor, and Lack of touch and feel with Intention to buy. This is one of the initial studies dealing with barriers and drivers to online shopping and their relation with the intention to shop online. Items like slow internet speed, inapt query handling and intention to buy with cash-on-delivery have also been included into the study. This paper builds the foundations for researchers to extend online retailing research in developing countries like India where switch over to internet shopping is much later than developing countries. Copyright © 2017 Inderscience Enterprises Ltd.","Barriers; Consumer behaviour; Drivers; India; Internet retailing; Online shopping","Consumer behavior; Developing countries; Privacy by design; Risk assessment; Truck drivers; Barriers; Emerging economies; Financial information; India; Intention to buies; Internet retailing; Online shopping; Security and privacy protection; Electronic commerce",{"$nulls":6},{"$cut":{"chars":18136,"head":"Ajzen I., The theory of planned behavior, Organizational Behavior and Human Decision Processes, 50, 11, pp. 179-211, (1991); Al-Maghrabi T., Dennis C., What drives consumers' continuance intention to e-shopping? Conceptual framework and managerial implications in case of Saudi Arabia, International Journal of Retail and Distribution Management, 39, 12, pp. 899-926, (2011); Alreck P.L., DiBartolo G.R., Diriker M., Dover H.F., Passyn K.A., Settle R.B., Time pressure, time saving and online shopping: Exploring a contradiction, The Journal of Applied Business Research, 25, 5, pp. 85-92, (2009); Bansal H.S., Mc Dougall G.H.G., Dikolli S.S., Sedatole K.L., Relating e-satisfaction to behavioural outcomes; An empirical study, Journal of Services Marketing, 18, 4, pp. 290-302, (2004); Bhattacherjee A., Understanding information systems continuance: An expectationconfirmation model, MIS Quarterly, 25, 3, pp. 351-370, (2001); Bisen A., Singh P., E-tailing in India; Unlocking the Potential, pp. 5-20, (2013); Casalo L., Flavian C., Guinaliu M., The role of perceived usability, reputation, satisfaction and consumer familiarity on website loyalty formation process, Computers in Human Behaviour, 24, 2, pp. 325-345, (2008); Chaing K.P., Dholakia R.R., Factors driving consumer intention to shop online: An empirical investigation, Journal of Consumer Psychology, 13, 1-2, pp. 177-183, (2003); Chattaraman V., Kwon W.-S., Gilbert J.E., Virtual agents in retail websites; Benefits of stimulated social interaction for older users, Computers in Human Behaviour, 28, 6, pp. 2055-2066, (2012); Chen H.Y., Hsu C.I., Lin C.C., Website attributes that increase consumer purchase intention: A conjoint analysis, Journal of Business Research, 63, 9-10, pp. 1007-1014, (2010); Chiejina C., Olamide S.E., Investigating the significance of the 'pay on delivery' option in emerging prosperity of the Nigerian e-commerce sector, Journal of Marketing and Management, 5, 1, pp. 120-135, (2014); Chiu C.M., Wang E.T.G., Fang Y.H., Huang H.Y., Understanding customers' repeat purchase intentions in B2C e-commerce: The roles of utilitarian value, hedonic value and perceived risk, Information Systems Journal, 24, 7, pp. 85-114, (2012); Colla E., Lapoule P., E-commerce: Exploring the critical success factors, International Journal of Retail and Distribution Management, 40, 11, pp. 842-864, (2012); Dash S.B., Saji K.B., Role of self-efficacy and website social-presence in customers' adoption of B2C online shopping: An empirical study in the Indian context, Journal of International Consumer Marketing, 20, 2, pp. 33-48, (2007); Dash A., Online shopping and customer satisfaction: An empirical investigation, International Journal of Research in Management, Economics and Commerce, 2, 11, pp. 42-49, (2012); Davis F.D., Perceived usefulness, perceived ease of use and user acceptance of information technology, MIS Quarterly, 13, 3, pp. 319-339, (1989); Dawn S.K., Kar U., E-tailing in India-its issues, opportunities and effective strategies for growth and development, International Journal of Multidisciplinary Research, 1, 3, pp. 101-115, (2011); Demangeot C., Broderick A.J., Consumer perceptions of online shopping environments: A Gestalt approach, Psychology and Marketing, 27, 2, pp. 117-140, (2010); Devraj S., Fan M., Kohli R., Antecedents of B2C channel satisfaction and preference: Validating e-commerce metrics, Information Systems Research, 13, 3, pp. 16-33, (2002); Dholakia R.R., Zhao M., Effects of online store attributes on customer satisfaction and repurchase intentions, International Journal of Retail and Distribution Management, 38, 7, pp. 482-496, (2010); Doherty N.F., Ellis-Chadwick E., New perspectives in internet retailing: A review and strategic critique of the field, International Journal of Retail and Distribution Management, 34, 4-5, pp. 411-428, (2006); Faqih K.M.S., An empirical analysis of factors predicting the behavioral intention to adopt Internet shopping technology among non-shoppers in a developing country context: Does gender matter?, Journal of Retailing an"}},"U. Tandon; School of Humanities and Social Sciences (SHSS), Thapar University, Patiala, P.O. Box 32, 147004, India; email: urvashiguptav@gmail.com",null,"Inderscience Publishers",{"$nulls":5},1.4706067E7,null,null,null,"English","Int. J. Electron. Bus.","Article","Final",null,"Scopus","2-s2.0-85018411220"]
["Hopkins D.; McCarthy A.","Hopkins, Debbie (55387197300); McCarthy, Alaric (56624006800)","55387197300; 56624006800","Change trends in urban freight delivery: A qualitative inquiry",2016.0,"Geoforum",74.0,null,null,158.0,170.0,12.0,16.0,"10.1016/j.geoforum.2016.06.006","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84975055684&doi=10.1016%2fj.geoforum.2016.06.006&partnerID=40&md5=88c06c6f258b07a9dcce7f1c3683d6c6","Transport Studies Unit, School of Geography and the Environment, University of Oxford, United Kingdom; Centre for Sustainability (CSAFE), University of Otago, PO Box 56, Dunedin, New Zealand","Hopkins D., Transport Studies Unit, School of Geography and the Environment, University of Oxford, United Kingdom, Centre for Sustainability (CSAFE), University of Otago, PO Box 56, Dunedin, New Zealand; McCarthy A., Centre for Sustainability (CSAFE), University of Otago, PO Box 56, Dunedin, New Zealand","In this paper we present the findings of a qualitative investigation of change trends in urban freight deliveries. The empirical material was gathered with urban freight (courier) company managers and drivers in Aotearoa New Zealand. It presents personal accounts of the everyday lived experiences of those intimately involved in the delivery of goods within the urban environment. Twenty-five interviews were conducted across four urban centres between June and September 2015. We use the four elements of the Energy Cultures Framework to explore what urban freight managers and drivers 'have', 'do' and 'think', and the pressures of an external context. Four interrelated themes are presented. 1. Online shopping and home deliveries, 2. Tracking and transparency, 3. New technologies, and 4. Meeting (changing) expectations, with evidence provided by way of verbatim quotations. The 'mobility cultures' concept is used to explore the relationships between the four themes, and to identify the key change trends that may affect the ability of the freight industry to contribute to a low-carbon transport transition. We conclude by signalling some policy implications and future research directions. © 2016 Elsevier Ltd.","Carbon reductions; Change trends; Energy Cultures Framework; Freight; Qualitative; Urban delivery","New Zealand; carbon emission; emission control; freight transport; future prospect; policy approach; transportation planning; transportation system; urban transport",{"$nulls":4},"Engineering and Physical Sciences Research Council, EPSRC, (EP/K011790/1)",null,"Ait-Kadi D., Chouinard M., Marcotte S., Riopel D., Sustainable Reverse Logistics Networks: Engineering and Management, (2012); Anim-Addo A., Hasty W., Peters K., The mobilities of ships and shipped mobilities, Mobilities, 9, 3, pp. 337-349, (2014); Arvidsson N., Woxenius J., Lammgard C., Review of road hauliers' measures for increasing transport efficiency and sustainability in urban freight distribution, Transp. 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Geogr., 37, pp. 74-81, (2014); Industry Insights: Transport, Logistics and Distribution; Wygonik E., Goodchild A., Evaluating CO<sub>2</sub> emissions, cost and service quality trad-offs in an urban delivery system case study, IATSS Res., 35, pp. 7-15, (2011); Wygonik E., Goodchild A., Evaluating the efficacy of shared-use vehicles for reducing greenhouse gas emissions: a case study of grocery delivery in Seattle, J. Transport. Res. Forum, 51, 2, pp. 111-126, (2012); Wygonik E., Bassok A., Goodchild A., Mccormack E., Carlson D., Smart growth and goods movement: emerging research agendas, J. Urban., 8, pp. 115-132, (2015); Young W., Middlemiss L., A rethink of how policy and social science approach changing individuals' actions on greenhouse gas emissions, Energy Policy, 41, pp. 742-747, (2012); Zanni A.M., Bristow A.L., Emissions of CO<sub>2</sub> from road freight transport in London: trends and policies for long run reductions, Energy Policy, 38, 4, pp. 1774-1786, (2010)","D. Hopkins; Transport Studies Unit, School of Geography and the Environment, University of Oxford, United Kingdom; email: Debbie.hopkins@ouce.ox.ac.uk",null,"Elsevier Ltd",{"$nulls":5},167185.0,null,null,null,"English","Geoforum","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-84975055684"]
["Suel E.; Polak J.W.","Suel, Esra (57189900881); Polak, John W. (7401546543)","57189900881; 7401546543","Development of joint models for channel, store, and travel mode choice: Grocery shopping in London",2017.0,"Transportation Research Part A: Policy and Practice",99.0,null,null,147.0,162.0,15.0,51.0,"10.1016/j.tra.2017.03.009","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85017023216&doi=10.1016%2fj.tra.2017.03.009&partnerID=40&md5=4130923f2f10f7fda68bc70a18f959af","Centre for Transport Studies, Imperial College London, Exhibition Road, London, SW7 2AZ, United Kingdom","Suel E., Centre for Transport Studies, Imperial College London, Exhibition Road, London, SW7 2AZ, United Kingdom; Polak J.W., Centre for Transport Studies, Imperial College London, Exhibition Road, London, SW7 2AZ, United Kingdom","The nature of shopping activity is changing in response to innovation in retailing and the growth in online channels. There is a growing interest from transport researchers, policy makers, marketing and retail businesses in understanding the implications of this change. However, existing tools and techniques developed for analysing behaviour in traditional retail environments do not adequately represent emerging complexities resulting from digital innovation. In this paper, we advance existing destination and mode choice models by incorporating online channels in a unified framework. This is a critical extension to existing transport literature on destination choice which largely ignores online activity. Specifically, we develop discrete choice models using elemental store (including both online and in-store) alternatives for joint choice of channel, store, and travel mode. We demonstrate the use of a widely-accepted consumer panel dataset with minor modifications, for the first time in transport research, together with API based data mining tools that offer great potential for enrichment. The analysis focuses on grocery shopping and uses consumer data collected from two selected boroughs in London; results from multinomial logit and nested logit estimations are reported. The extension presented here provides the tools to quantify the effects of increased online shopping on traditional store formats and travel patterns. Our results showed virtual alternatives currently offer an attractive substitute among early adopters for large basket shopping mostly for high income groups. This might suggest a significant reduction in shopping trips to hypermarkets often associated with large basket shopping potentially leading to store closures. Online deliveries mostly draw from driving trips and less so from walking and public transport trips. The present study also confirmed previous findings related to smaller stores and longer travel distances being associated with declining utilities, agglomeration and competition significantly influencing store choice. © 2017","Destination and mode choice; Discrete choice modelling; E-commerce; Multi-channel shopping; Online shopping; Store choice","England; London [England]; United Kingdom; Application programming interfaces (API); Electronic commerce; Transportation routes; Discrete choice; Mode choice; Multi-channel shopping; Online shopping; Store choice; discrete choice analysis; electronic commerce; modeling; public transport; retailing; shopping activity; travel behavior; walking; Data mining",{"$nulls":4},"Engineering and Physical Sciences Research Council, EPSRC, (EP/I038837/1)",null,"Aaker D.A., Jones J.M., Modeling store choice behavior, J. Market. Res. (JMR), 8, pp. 38-42, (1971); Anderson M., Braak C.T., Permutation tests for multi-factorial analysis of variance, J. 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Retailing Consumer Serv., 14, pp. 73-82, (2007); Suel E., Modelling the Relationship between Multi-Channel Retail and Personal Mobility Behaviour (Ph.D. Thesis), (2016); Suel E., Le Vine S., Polak J.W., Empirical application of expenditure diary instrument to quantify relationships between in-store and online grocery shopping: case study of greater London, Transp. Res. Rec.: J. Transp. Res. Board, 2496, pp. 45-54, (2015); Teltzrow M., Meyer B., Lenz H.J., Multi-channel consumer perceptions, J. Electr. Comm. Res., 8, pp. 18-31, (2007); Thielman S., Google Gets Into the Home-Delivered Grocery Game with Express, (2016); Thill J.C., Wheeler A., Knowledge discovery and induction of decision trees in spatial decision problems, Spatial Economic Science, pp. 188-205, (2000); Train K.E., Discrete Choice Methods with Simulation, (2009); Visser E.J., Lanzendorf M., Mobility and accessibility effects of B2C ecommerce: a literature review, Tijdschrift voor Economische en Sociale Geografie, 95, pp. 189-205, (2004); Weltevreden J.W.J., Substitution or complementarity? How the Internet changes city centre shopping, J. Retailing Consumer Serv., 14, pp. 192-207, (2007); Whipp L., Walmart Partners with Uber and Lyft to Deliver Groceries, (2016); Zhou Y., Wang X.C., Explore the relationship between online shopping and shopping trips: an analysis with the 2009 NHTS data, Transp. Res. Part A: Policy Pract., 70, pp. 1-9, (2014)","E. Suel; email: esra.suel@imperial.ac.uk",null,"Elsevier Ltd",{"$nulls":5},9658564.0,null,null,null,"English","Transp. Res. Part A Policy Pract.","Article","Final","All Open Access; Green Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85017023216"]
["Fu M.; Xia W.; Wang L.","Fu, Ming (55552015200); Xia, Wanjun (57203915244); Wang, Lifang (57194691306)","55552015200; 57203915244; 57194691306","Optimization of parcels picking and delivery in a large e-commerce company using target-guided ant colony algorithm",2017.0,"Boletin Tecnico/Technical Bulletin",55.0,7.0,null,16.0,25.0,9.0,1.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85029598943&partnerID=40&md5=07c3cb2cc71ba77295a10a1efd3e880a","School of Management Science and Engineering, Anhui University of Finance and Economics, Bengbu Anhui, 233030, China","Fu M., School of Management Science and Engineering, Anhui University of Finance and Economics, Bengbu Anhui, 233030, China; Xia W., School of Management Science and Engineering, Anhui University of Finance and Economics, Bengbu Anhui, 233030, China; Wang L., School of Management Science and Engineering, Anhui University of Finance and Economics, Bengbu Anhui, 233030, China","With the development of e-commerce, how to send parcels to clients quickly, low-costly and accurately becomes an important problem which everyone has to face. The paper proposes a target-guided ant colony algorithm to solve the problem. First, ant colony algorithm is used to search the optimal order picking route under various constraints. Second, as soon as the quantity of the picking orders is about to reach the capacity of the vehicle, the vehicle will be notified to be ready to deliver parcels to customers. Parcels picking and delivery is conducted simultaneously. Third, the algorithm is also used to optimize vehicles delivery route. In the end, simulation results show that the algorithm proposed in the paper can solve the problem efficiently compared with traditional algorithm.","Ant Colony Algorithm; Artificial Intelligence; Swarm Algorithm","Ant colony optimization; Artificial intelligence; Commerce; Electronic commerce; Problem solving; Vehicles; Ant colony algorithms; Delivery routes; Optimal ordering; Swarm algorithms; Optimization",{"$nulls":4},"Anhui College of Humanities and social science research project, (SK2017A0437, acxnfz201701); University Natural Science Research Project of Anhui Province, (KJ2017A429)","This work was supported by 2017 natural science research project of Anhui University (KJ2017A429) , and supported by 2017 Anhui College of Humanities and social science research project(SK2017A0437), also supported by robot virtual simulation experimental teaching center project of anhui university of finance&economics (acxnfz201701)","Jiang Y., Xu Z.S., Shu Y.H., Distance measures between intuitionistic multiplicative sets and their application in site selection of building satellite earth stations, Systems Engineering-Theory and Practice, 36, 12, pp. 3210-3219, (2016); Fu Z.J., Ren K., Shu J.G., Sun X.M., Huang F.X., Enabling personalized search over encrypted outsourced data with efficiency improvement, IEEE Transactions on Parallel and Distributed Systems, 27, 9, pp. 2546-2559, (2016); Fu Z.J., Shu J.G., Wang J., Liu Y.L., Lee S.Y., Privacy-preserving smart similarity search based on simhash over encrypted data in cloud computing, Journal of Internet Technology, 16, 3, pp. 453-460, (2015); Liao H.C., Xu Z.S., Zeng X.J., Merigo J.M., Qualitative decision making with correlation coefficients of hesitant fuzzy linguistic term sets, Knowledge-Based Systems, 76, 1, pp. 127-138, (2015); Couso I., Garrido L., Sanchez L., Similarity and dissimilarity measures between fuzzy sets: A formal relational study, Information Sciences, 229, 6, pp. 122-141, (2013); Wang H., Extended hesitant fuzzy linguistic term sets and their aggregation in group decision making, International Journal of Computational Intelligence Systems, 8, 1, pp. 14-33, (2015); Nguyen H., A new knowledge-based measure for intuitionistic fuzzy sets and its application in multiple attribute group decision making, Expert Systems with Applications, 42, 22, pp. 8766-8774, (2015); Qian G., Wang H., Feng X.Q., Generalized hesitant fuzzy sets and their application in decision support system, Knowledge-Based Systems, 37, 4, pp. 357-365, (2013); Peng J.J., Wang J.Q., Wu X.H., Zhang H.Y., Chen X.H., The fuzzy cross-entropy for intuitionistic hesitant fuzzy sets and their application in multi-criteria decision-making, International Journal of Systems Science, 46, 13, pp. 1-16, (2014); Wang J.Q., Wang D.D., Zhang H.Y., Chen X.H., Multi-criteria outranking approach with hesitant fuzzy sets, OR Spectrum, 36, 4, pp. 1001-1019, (2016)","W. Xia; School of Management Science and Engineering, Anhui University of Finance and Economics, Bengbu Anhui, 233030, China; email: 284163261@qq.com",null,"Universidad Central de Venezuela",{"$nulls":5},"0376723X",null,null,null,"English","Boletin Tecnico","Article","Final",null,"Scopus","2-s2.0-85029598943"]
["Guo J.; Wang X.; Fan S.; Gen M.","Guo, Jianquan (56097694900); Wang, Xinyue (57193341653); Fan, Siyuan (57189040216); Gen, Mitsuo (7005506986)","56097694900; 57193341653; 57189040216; 7005506986","Forward and reverse logistics network and route planning under the environment of low-carbon emissions: A case study of Shanghai fresh food E-commerce enterprises",2017.0,"Computers and Industrial Engineering",106.0,null,null,351.0,360.0,9.0,109.0,"10.1016/j.cie.2017.02.002","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85014219499&doi=10.1016%2fj.cie.2017.02.002&partnerID=40&md5=5486665c2e63c9b296856e3485d72273","University of Shanghai for Science and Technology Shanghai, China; Business School of University of Shanghai for Science and Technology Shanghai, China; Tokyo University of Science, Japan Fuzzy Logic Systems Institute, Japan","Guo J., University of Shanghai for Science and Technology Shanghai, China; Wang X., Business School of University of Shanghai for Science and Technology Shanghai, China; Fan S., Business School of University of Shanghai for Science and Technology Shanghai, China; Gen M., Tokyo University of Science, Japan Fuzzy Logic Systems Institute, Japan","In view of the rapid development of low-carbon economy, the increasing distribution demand and returned demand which caused by the short shelf life and spoilage of fresh food, network and route planning model of a two-stage forward/reverse logistics is firstly proposed for fresh food e-commerce enterprises under the environment of low-carbon emissions (The objective in the first stage is to minimize the overall cost of the system, and the minimum overall cost of the circulation-type distribution vehicles routing is considered in the second stage). And the validity of the model is verified by adopting genetic algorithm (GA) and particle swarm optimization (PSO) algorithm with the study of the fresh food e-commerce enterprises of Shanghai. Furthermore, a good reference can be provided to build the forward and reverse logistics network and optimal route planning model of fresh food e-commerce enterprises and reduce the carbon emissions during its operation process. © 2017 Elsevier Ltd","Fresh food e-commerce enterprises; Genetic algorithm; Location and route planning; Logistics network; Low-carbon; Particle swarm optimization algorithm","Commerce; Electronic commerce; Genetic algorithms; Logistics; Optimization; Particle swarm optimization (PSO); Renewable energy resources; Transportation; E-commerce enterprise; Logistics network; Low carbon; Particle swarm optimization algorithm; Route planning; Spoilage",{"$nulls":4},"Natural Science Foundation of Shanghai, (10ZR1413300); Japan Society for the Promotion of Science, KAKEN, (15K00357); National Natural Science Foundation of China, NSFC, (71071093, 71301101, 71471110)","This work was supported by Shanghai Municipal Natural Science Foundation (10ZR1413300); and National Natural Science Foundation of China (71071093, 71471110, and 71301101). This work was also partly supported by the Grant-in-Aid for Scientific Research (C) of Japan Society of Promotion of Science (JSPS): No. 15K00357.","Alumur S.A., Et al., Multi-period reverse logistics network design, European Journal of Operational Research, 220, 1, pp. 67-78, (2012); Cattaruzza D., Et al., Vehicle routing problems for city logistics[J], EURO Journal on Transportation and Logistics, pp. 1-29, (2015); Cholette S., Venkat K., The energy and carbon intensity of wine distribution: A study of logistical options for delivering wine to consumers, Journal of Cleaner Production, 17, 16, pp. 1401-1413, (2009); Cui L.B., Et al., How will the emissions trading scheme save cost for achieving China's 2020 carbon intensity reduction target?, Applied Energy, 136, pp. 1043-1052, (2014); Dablanc L., Goods transport in large European cities: Difficult to organize, difficult to modernize, Transportation Research Part A: Policy and Practice, 41, 3, pp. 280-285, (2007); Fang S.J., Low-carbon development in the context of the green economy, Chinese Journal of Population, Resource and Environment, 20, 4, pp. 8-11, (2010); 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Osvald A., Stirn L.Z., A vehicle routing algorithm for the distribution of fresh vegetables and similar perishable food, Journal of food engineering, 85, 2, pp. 285-295, (2008); Ramezani M., Bashiri M., Tavakkoli-Moghaddam R., A new multi-objective stochastic model for a forward/reverse logistic network design with responsiveness and quality level, Applied Mathematical Modelling, 37, 1, pp. 328-344, (2013); Roghanian E., Pazhoheshfar P., An optimization model for reverse logistics network under stochastic environment by using genetic algorithm, Journal of Manufacturing Systems, 33, 3, pp. 348-356, (2014); Shaw K., Et al., Low carbon chance constrained supply chain network design problem: A Benders decomposition based approach, Computers & Industrial Engineering, 98, pp. 483-497, (2016); Song B.D., Ko Y.D., Hwang H.; Tang Y.L., Optimization of logistic distribution center location and vehicle routing problem, Journal of Beijing Union University, 3, pp. 47-52, (2014); Tang S., Et al., Low carbon logistics: Reducing shipment frequency to cut carbon emissions, International Journal of Production Economics, 164, pp. 339-350, (2015); Wang Y., Lu T., Zhang C., Integrated logistics network design in hybrid manufacturing/remanufacturing system under low-carbon restriction[M]//LISS 2012, (2013); Wang T.J., Wu Y.C., Study on optimization of logistics distribution route based on chaotic PSO, Computer Engineering and Applications, 47, 29, pp. 218-221, (2011); Yang J., Guo J., Ma S., Low-carbon city logistics distribution network design with resource deployment, Journal of Cleaner Production, 119, pp. 223-228, (2016); Yu X., Qu H., The role of China's renewable powers against climate change during the 12th Five-Year and until 2020, Renewable and Sustainable Energy Reviews, 22, pp. 401-409, (2013)","J. Guo; University of Shanghai for Science and Technology Shanghai, China; email: jasonguousst@126.com",null,"Elsevier Ltd",{"$nulls":5},3608352.0,null,"CINDD",null,"English","Comput Ind Eng","Article","Final",null,"Scopus","2-s2.0-85014219499"]
["Ji S.; Sun Q.","Ji, Shoufeng (15119083600); Sun, Qi (57190947157)","15119083600; 57190947157","Low-carbon planning and design in B & R logistics service: A case study of an E-commerce big data platform in China",2017.0,"Sustainability (Switzerland)",9.0,11.0,2052.0,null,null,null,28.0,"10.3390/su9112052","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85034222938&doi=10.3390%2fsu9112052&partnerID=40&md5=f99dd2a03526812d94194e1978fb1aff","School of Business Administration, Northeastern University, Shenyang, 110167, China","Ji S., School of Business Administration, Northeastern University, Shenyang, 110167, China; Sun Q., School of Business Administration, Northeastern University, Shenyang, 110167, China","The concept of sustainable development requires us to explore a completeness model of low carbon transport and service in the light of the advancement of changes in world cooperation policy. Various kinds of carbon constraints not only limit emissions of contaminants from E-commerce Enterprise of different countries, but they also ensure the market activity around the Belt and Road, so as to avoid the implementation reducing the company's profits significantly. This paper discusses of the strictest periodic low-carbon constraints_(PLC) and the expansion of the mainstream with three relatively weak attributes-cumulative_(CLC), full cycle_(FCLC), and volatility_(VLC)-taking into account the offline delivery of lead time and the online relationship between supply and demand on the platform. We have established four decision models with different carbon confinement intensities and inferred the impact of more detailed carbon constraints on E-commerce delivery strategies. The appropriate operational decisions, under a wide spectrum of carbon constraints, help e-companies develop scientific delivery plans, and provide some inspiration for the promotion of low carbon economy system construction and environmental significance. © 2017 by the authors.","Belt and Road initiative; Classification analysis; Internet plus plan; Sustainable e-commerce delivery programming model","China; carbon emission; classification; conceptual framework; data set; demand analysis; electronic commerce; environmental economics; environmental modeling; industrial enterprise; Internet; sustainable development; trade-environment relations",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (71572031); Liaoning Planning Office of Philosophy and Social Science, (L16AZY032)","Acknowledgments: This research was sponsored by the National Science Foundation of China (No. 71572031), Philosophy and Social Science Fund, Liaoning (L16AZY032).","Du S., Hu L., Song M., Production optimization considering environmental performance and preference in the cap-and-trade system, J. 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Manag, 374, pp. 297-312, (2017); Lesk C., Rowhani P., Ramankutty N., Influence of extreme weather disasters on global crop production, Nature, 529, pp. 84-87, (2016); Moss R.H., Edmonds J.A., Hibbard K.A., Manning M.R., Rose S.K., van Vuuren D.P., Carter T.R., Emori S., Kainuma M., Kram T., Et al., The next generation of scenarios for climate change research and assessment, Nature, 463, pp. 747-756, (2010); Howarth C., Viner D., Dessai S., Rapley C., Jones A., Enhancing the contribution and role of practitioner knowledge in the Intergovernmental Panel on Climate Change (IPCC) Working Group (WG) II process: Insights from UK workshops, Clim. Serv, 5, pp. 3-10, (2017); Geithner T.F., Liquidity Risk and the Global Economy, Int. 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Res, 2193, pp. 671-679, (2012); Havinga M., Hoving M., Swagemakers V., Alibaba: A Case Study on Building an International Imperium on Information and E-Commerce, pp. 13-32, (2016); Coase R.H., The problem of social cost, J. Law Econ, 3, pp. 1-44, (1960); Robinson J., Brase G., Griswold W., Jackson C., Erickson L., Business models for solar powered charging stations to develop infrastructure for electric vehicles, Sustainability, 6, pp. 7358-7387, (2014); Burtraw D., Kahn D., Palmer K., CO<sub>2</sub> Allowance Allocation in the Regional Greenhouse Gas Initiative and the Effect on Electricity Investors, Electr. J, 19, pp. 79-90, (2006); Sterner T., Muller A., Output and abatement effects of allocation readjustment in permit trade, Clim. Chang, 86, pp. 33-49, (2007); Lee D.H., Kim D., Kim S., Characteristics of forest carbon credit transactions in the voluntary carbon market, Clim. Policy, 12, pp. 1-11, (2017); Baldwin R., Regulation lite: The rise of emissions trading, Regul. 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Econ, 150, pp. 125-139, (2014); Kim N.S., van Wee B., Toward a Better Methodology for Assessing CO<sub>2</sub> Emissions for Intermodal and Truck-only Freight Systems: A European Case Study, Int. J. Sustain. Transp, 8, pp. 177-201, (2014); Demir E., Bektas T., Laporte G., A review of recent research on green road freight transportation, Eur. J. Oper. Res, 237, pp. 775-793, (2014); Soysal M., Bloemhof-Ruwaard J.M., Vander Vorst J.G.A.J., Modelling food logistics networks with emission considerations-The case of an international beef supply chain, Int. J. Prod. Econ, 152, pp. 57-70, (2014); Chen W.T., Hsu C.I., Greenhouse gas emission estimation for temperature-controlled food distribution systems, J. Clean. Prod, 104, pp. 139-147, (2015); Soysal M., Bloemhof-Ruwaard J.M., Haijema R., Vander Vorst J.G.A.J., Modeling an Inventory Routing Problem for perishable products with environmental considerations and demand uncertainty, Int. J. Prod. 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Math, 41, pp. 238-252, (1962); Fortz B., Poss M., An improved benders decomposition applied to a multi-layer network design problem, Oper. Res. Lett, 37, pp. 359-364, (2009); Bektas T., Formulations and Benders decomposition algorithms for multidepot salesmen problems with load balancing, Eur. J. Oper. Res, 216, pp. 83-93, (2012); Saharidis G.K.D., Minoux M., Ierapetritou M.G., Accelerating Benders method using covering cut bundle generation, Int. Trans. Oper. Res, 17, pp. 221-237, (2010); Wu P., Hartman J.C., Wilson G.R., A demand-shifting feasibility algorithm for Benders decomposition, Eur. J. Oper. Res, 148, pp. 570-583, (2003); Rei W., Cordeau J.F., Gendreau M., Soriano P., Accelerating Benders decomposition by local branching, Inf. J, 21, pp. 333-345, (2009); Poojari C.A., Beasley J.E., Improving benders decomposition using a genetic algorithm, Eur. J. Oper. Res, 199, pp. 89-97, (2009); Yang Y., Lee J.M., A tighter cut generation strategy for acceleration of benders decomposition, Comput. Chem. Eng, 44, pp. 84-93, (2012); Geoffrion A.M., Generalized benders decomposition, J. Optim. Theory Appl, 10, pp. 237-260, (1972); Lasdon L.S., Optimization Theory for Large Systems, (1970); Floudas C.A., Nonlinear and Mixed-Integer Optimization: Fundamentals and Applications, (1995); Hoen K.M.R., Tan T., Fransoo J.C., van Houtum G.J., Effect of carbon emission regulations on transport mode selection under stochastic demand, Flex. Serv. Manuf. J, 26, pp. 170-195, (2012); Toro E.M., Franco J.F., Echeverri M.G., Guimaraes F.G., A multi-objective model for the green capacitated location-routing problem considering environmental impact, Comput. Ind. Eng, 110, pp. 114-125, (2017); Eswaramurthy V.P., Tamilarasi A., Hybridizing tabu search with ant colony optimization for solving job shop scheduling problems, Int. J. Adv. Manuf. Technol, 40, pp. 1004-1015, (2008); Talbi E.G., Roux O., Fonlupt C., Robillard D., Parallel ant colonies for the quadratic assignment problem, Future Gener. Comput. Syst, 17, pp. 441-449, (2001)","S. Ji; School of Business Administration, Northeastern University, Shenyang, 110167, China; email: sfji@mail.neu.edu.cn",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85034222938"]
["Renganathan R.; Vijayabanu C.; Srinivasakumar V.; Vijay Anand V.; Gayathri B.","Renganathan, R. (54585765000); Vijayabanu, C. (56962734300); Srinivasakumar, V. (56612052500); Vijay Anand, V. (55305510400); Gayathri, B. (57614092600)","54585765000; 56962734300; 56612052500; 55305510400; 57614092600","Customer buying behaviour towards online shopping",2017.0,"International Journal of Applied Business and Economic Research",15.0,6.0,null,465.0,476.0,11.0,1.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85034216140&partnerID=40&md5=edf5028b36eb2f1edd76e32fb33be49e","School of Management, Sastra University, Thanjavur, India","Renganathan R., School of Management, Sastra University, Thanjavur, India; Vijayabanu C., School of Management, Sastra University, Thanjavur, India; Srinivasakumar V., School of Management, Sastra University, Thanjavur, India; Vijay Anand V., School of Management, Sastra University, Thanjavur, India; Gayathri B., School of Management, Sastra University, Thanjavur, India","Information technology, an important aspect of digital economy, is developed internationally and also advent of internet in our country India, since last two decades. Nowadays usage of internet and mobile phone are gaining momentum because of change in lifestyle of rural and urban people. Apart from brick and mortar type of shopping, youngsters especially college students prefer shopping by means of brick and click thro cyberspace. Because of the technological up gradation and immense use and availability of internet and changing lifestyle of buyers, organization would like to promote and augment the brand equity and sales of their products with the help of website. Buyers prefer on line mode than traditional mode of shopping because of the availability of information pertaining to the various aspects of the products, mode of delivery and after sale service of the on line shoppers. In order to understand the buying preferences of the college students towards online shopping a study is undertaken. This study deals with the college students' opinion about online e-commerce shoppers, their buying habits, preferences and characteristics of on line e-commerce websites. Under graduate and postgraduate students were included for this study. Most of the students preferred Amazon, Flipkart, Snapdeal as their online shoppers. According to this study laptop, mobile phone, books and dress materials are the favourite products choice for online shopping. Under graduate and postgraduate students were included for this study. This study will be useful for the online e commerce companies like Amazon, Snapdeal, Flipkart to understand the tastes, preferences and requirements of youngsters and college students. © Serials Publications Pvt. Ltd.","Consumer Behaviour; E-commerce; Internet; Online; Shopping; Website",{"$nulls":7},"Almousa M., Influence of risk perception in oline purchasing behaviour: Examination of an early stage on line market, International Review of Management and Business Research, 3920, pp. 779-787, (2014); Bhatnagar A., Misra S., Rao H.R., On risk, convenience, and Internet shopping behavior, Communications of, 43, 1, pp. 98-105, (2000); Lovelock C., Wirtz J., Chatterjee J., Services Marketing' People, Technology, Strategy, (2004); Geetha V., Rengarajan K., A conceptual framework for perceived risk in consumer online shopping, Sona Global Management Review, 10, 1, (2015); Komiak S.X., Benbasat I., Understanding customer trust in agent-mediated electronic commerce, web-mediated electronic commerce, and traditional commerce, Information Technology and Management, 5, 1-2, pp. 181-207, (2004); Nandakumar K., Lang R., Peng Q., Consumer Search Behavior in Online Shopping Environments, E-service Journal, 38th Hawaii International Conference on System Sciences (HICSS-38), January 2005., (2005); Kotler P., Lane Keller K., Marketing Management, (2016); Raman P., Factors influencing women consumers' buying behavior towards online shopping in India', , The Journal of Contemporary Management Research, 8, 2, (2014); Qinghe Y., Wenyuan C., Kaiming L., The online shopping change the retail business model: A survey of the people use online shopping in China, IOSR Journal of Business and Management., 15, 5, pp. 77-110, (2014); Ramaswamy V.S., Namakuamari S.,  Edition, pp. 249-250, (2009); Patnakar T., Marketing Management, (2013); Thakur R., Srivatsava M., A study on the impact of consumer risk perception and innovativeness on onlined shopping in India, International Journal of Retail & Distribution Management, 43, 2, pp. 148-166, (2015); Vaidehi P.U., Factors Influencing Online Shopping Behavior of Students in Engineering Colleges at Ranga Reddy District, 1. Consumers' Perception on FDI in Multi-Brand 4 Retailing in India-A Study, (2014); Zheng L., Favier M., Huang P., Coat F., Chinese consumer perceived risk and risk relievers in e-shopping for clothing, Journal of Electronic Commerce Research, 13, 3, pp. 255-274, (2012)",null,null,"Serials Publications",{"$nulls":5},9727302.0,null,null,null,"English","Int. J. Appl. Bus. Econ. Res.","Article","Final",null,"Scopus","2-s2.0-85034216140"]
["Katta R.M.R.; Patro C.S.","Katta, Rama Mohana Rao (57193279817); Patro, Chandra Sekhar (54783307500)","57193279817; 54783307500","Influence of Perceived Benefits on Consumers’ Online Purchase Behaviour: An Empirical Study",2017.0,"International Journal of Sociotechnology and Knowledge Development",9.0,3.0,null,38.0,64.0,26.0,11.0,"10.4018/IJSKD.2017070103","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85042083295&doi=10.4018%2fIJSKD.2017070103&partnerID=40&md5=0a5efca43c6594312d12cc0f40008c0d","Department of Commerce and Management Studies, Andhra University, Visakhapatnam, India; Department of Management Studies, GVP College of Engineering (A), Visakhapatnam, India","Katta R.M.R., Department of Commerce and Management Studies, Andhra University, Visakhapatnam, India; Patro C.S., Department of Management Studies, GVP College of Engineering (A), Visakhapatnam, India","This article describes how e-retailing has become one of the most important uses of technology relating to the internet. The activity of online shopping is considered to be one of the important features of e-retailing. The enormous advantages offered by online shopping stimulate corporate managers, marketing departments and retailers to offer their products through the websites to attract the largest number of shoppers, not only to local markets but also global markets. The change in consumer behavior along with the availability of cheaper and reliable technology for secure transactions has led to a significant growth in online sales around the world. The present article focuses on identifying the key factors influencing the consumers’ perceived benefits while shopping online. The article further focuses on the influence of demographic factors on consumers’ perceived benefits. The findings of the article would help e-retailers to have a better understanding and to develop strategies for making the online shopping experience more effective and trustworthy to the target consumers. Copyright © 2017, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.","Convenience; Delivery; Financial Advantage; Innovativeness; Personalization; Privacy; Product Variety; Reliability; Security; Website Functionality",{"$nulls":7},"Atchariyachanvanich K., Okada H., Sonehara N., Exploring factors effecting the continuance of purchasing behavior in internet shopping: Extrinsic benefits and intrinsic benefits, IPSJ Digital Courier, 4, pp. 91-102, (2008); Chakraborty D., Factors affecting consumer purchase decision towards online shopping: A study conducted in Gangtok, Sikkim. Adarsh Business Review, 3, 1, pp. 11-18, (2016); Devaraj S., Fan M., Kohli R., Examination of online channel preference: Using the structure-conduct-outcome framework, Decision Support Systems, 42, 2, pp. 1089-1103, (2006); Elwalda A., Lu K., Ali M., Perceived derived attributes of online customer reviews, Computers in Human Behavior, 56, pp. 306-319, (2016); Fei Y.M., Liat C.B., Factors Affecting Consumer’s Continuance Online Purchase Intention in Malaysia, Global Journal of Business and Social Science Review, 1, 1, pp. 309-321, (2015); Forsythe S., Liu C., Shannon D., Gardner L.C., Development of a scale to measure the perceived benefits and risks of online shopping, Journal of Interactive Marketing, 20, 2, pp. 55-75, (2006); Har Lee C., Cyril Eze U., Oly Ndubisi N., Analyzing key determinants of online repurchase intentions, Asia Pacific Journal of Marketing and Logistics, 23, 2, pp. 200-221, (2011); Heijden H.V., Verhagen T., Online store image: Conceptual foundations and empirical measurement, Information & Management, 41, 5, pp. 609-617, (2004); Hirst A., Ashwin M., Cross cultural difference between online shoppers in London and Bangkok, International Review of Business Research Papers, 5, 4, pp. 167-191, (2009); Hsu S., Bayarsaikhan B., Factors Influencing on Online Shopping Attitude and Intention of Mongolian Consumers, Journal of International Management Studies, 7, 2, pp. 167-176, (2012); Jadhav V., Khanna M., Factors Influencing Online Buying Behavior of College Students: A Qualitative Analysis, Qualitative Report, 21, 1, pp. 1-15, (2016); Jiradilok R., Malisuwan S., Madan N., Sivaraks J., The Impact of Customer Satisfaction on Online Purchasing: A Case Study Analysis in Thailand, Journal of Economics. Business and Management, 2, 1, pp. 5-11, (2014); Katta R.M.R., Patro C.S., Online Shopping Behavior: A Study of Factors Influencing Consumer Satisfaction on Online viz-a-viz Conventional Store Shopping, International Journal of Sociotechnology and Knowledge Development, 8, 4, pp. 21-36, (2016); Katta R.M.R., Patro C.S., Influence of Web Attributes on Consumer Purchase Intentions, International Journal of Sociotechnology and Knowledge Development, 9, 2, pp. 1-16, (2017); Kim D.J., Ferrin D.L., Rao H.R., A Trust-Based Consumer Decision Model in Electronic Commerce: The Role of Trust, Risk, and Their Antecedents, Decision Support Systems, 44, 2, pp. 544-564, (2008); Lee G.G., Lin H.F., Customer perceptions of e-service quality in online shopping, International Journal of Retail & Distribution Management, 33, 2, pp. 161-176, (2005); Lee K., Joshi K., An empirical investigation of customer satisfaction with technology mediated service encounters in the context of online shopping, Journal of Information Technology Management, 18, 2, pp. 18-37, (2007); Mee L.Y., Huei C.T., A profile of the Internet shoppers: Evidence from nine countries, Telematics and Informatics, 32, 2, pp. 344-354, (2015); Nayak P.K., Debashish S.S., Young Consumers Online Shopping Decision Influencers: A study on University Students of Odisha, Effulgence, 15, 1, pp. 45-50, (2017); Nazir S., Tayyab A., Sajid A., Rashid H., Javed I., How Online Shopping is Affecting Consumers Buying Behavior in Pakistan?, International Journal of Computer Science Issues, 9, 3, pp. 486-495, (2012); Park C., Kim Y., Identifying key factors affecting consumer purchase behavior in an online shopping context, InternationalJournalofRetail&DistributionManagement, 31, 1, pp. 16-29, (2003); Patro C.S., Attitudes of E-Shoppers and Non E-Shoppers towards E-Shopping: A Comparative Study, InternationalJournalofCyberBehavior,PsychologyandLearning, 6, 2, pp. 96-108, (2016); Patro C.S., Consumer Attitude and Loyalty in Online Shopping Environments: A Study of Facets Driving Shoppers Towards E-Stores, International Journal of Cyber Behavior, Psychology and Learning, 7, 3, pp. 57-72, (2017); Putro H.B., Haryanto B., Factors Affecting Purchase Intention of Online Shopping in Zalora Indonesia, British Journal of Economics. Management & Trade, 9, 1, pp. 1-12, (2015); Ranganathan C., Ganapathy S., Key dimensions of business-to-consumer websites, Information & Management, 39, 6, pp. 457-465, (2002); Rao K.R.M., Patro C.S., Shopper’s Stance Towards Web Shopping: An Analysis of Students Opinion of India, International Journal of Online Marketing, 7, 3, pp. 42-54, (2017); Rasool A., Gupta V., Slathia B., Mahajan G., Online Shopping Adoption and Influencing Factors: A Study in Karnataka, Apeejay-Journal of Management Sciences and Technology, 4, 2, pp. 29-40, (2017); San Lim Y., Heng P.C., Ng T.H., Cheah C.S., Customers’ online website satisfaction in online apparel purchase: A study of Generation Y in Malaysia, Asia Pacific Management Review, 21, 2, pp. 74-78, (2016); Saravanan R., Yoganandan G., Ruby N., A Study on Online Shopping Behaviour of Teachers Working in Self-Financing Colleges in Namakkal District With Special Reference to K.S.R College of Arts And Science, Tiruchengode, Namakkal District, International Journal of Research in Commerce. IT & Management, 3, 6, pp. 31-37, (2013); Sharma N.V., Khattri V., Study of online shopping behavior and its impact on online deal websites, Asian Journal of Management Research, 3, 2, pp. 394-405, (2013); Shergill G.S., Chen Z., Web-based shopping: Consumers’ attitudes towards online shopping in New Zealand, Journal of Electronic Commerce Research, 6, 2, pp. 79-94, (2005); Wolfinbarger M., Gilly M.C., ETailQ: Dimensionalizing, measuring and predicting e-tail quality, Journal of Retailing, 79, 3, pp. 183-198, (2003); Yi Y., Gong T., The Electronic Service Quality Model: The Moderating Effect of Customer Self-Efficacy, Psychology and Marketing, 25, 7, pp. 587-601, (2008)",null,null,"Information Resources Management Association",{"$nulls":5},1.9416253E7,null,null,null,"English","Int. J. Sociotechnology Knowl. Dev.","Article","Final",null,"Scopus","2-s2.0-85042083295"]
["Cao Y.; Ajjan H.; Hong P.","Cao, Yingxia (7404523519); Ajjan, Haya (24342685100); Hong, Paul (7102301600)","7404523519; 24342685100; 7102301600","Post-purchase shipping and customer service experiences in online shopping and their impact on customer satisfaction: An empirical study with comparison",2018.0,"Asia Pacific Journal of Marketing and Logistics",30.0,2.0,null,400.0,416.0,16.0,116.0,"10.1108/APJML-04-2017-0071","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85044513292&doi=10.1108%2fAPJML-04-2017-0071&partnerID=40&md5=7a518773949cee23dbc0f03134342c94","Department of Applied Business, University of La Verne, La Verne, CA, United States; Elon University, Elon, NC, United States; College of Business and Innovation, University of Toledo, Toledo, OH, United States","Cao Y., Department of Applied Business, University of La Verne, La Verne, CA, United States; Ajjan H., Elon University, Elon, NC, United States; Hong P., College of Business and Innovation, University of Toledo, Toledo, OH, United States","Purpose: The purpose of this paper is to understand the role of post-purchase logistic services on customer satisfaction and future purchase decision, to reveal any differences across China and Taiwan, to fill in a gap in the literature focused on post-purchase logistic activities related to shipping, return, and tracking, to provide managerial guidance in logistics for e-commerce, and to develop insights on logistic services for future research. Design/methodology/approach: Using a validated survey instrument, 384 respondents in China and 145 respondents in Taiwan are collected. The research model is analyzed using component-based estimation approach to structural equation modeling. Findings: The structural equation analysis of the study found that post-purchase shipping and tracking have an impact on customer satisfaction in both China and Taiwan. It also found that customer service is the most significant factor among the examined antecedents for online shoppers in China. While, return service is more important for shoppers in Taiwan. Finally, customer satisfaction played a stronger positive role for online shoppers in Taiwan as compared to their counterparts in China. Research limitations/implications: This research extended the current literature about post-purchase logistic services in an online shopping environment with a literature-based research model and good empirical data support. However, one limitation of the study is that the data collected represents a cross-sectional sample; future research should examine longitudinal sample to study customers’ purchase intentions over time. Practical implications: This study can help both scholars and practitioners understand the importance of tracking, return, shipping, and customer service in an online shopping environment and across countries. It provides insights on designing e-commerce relevant shipping services to satisfy and attract customers across countries. Originality/value: The study investigated how post-purchase activities contributed to customer satisfaction in online shopping and explored the influence of customer satisfaction on future purchase intention in China and Taiwan. This is one of the first studies available in the literature to provide empirical support and managerial insights about post-purchase activities related to shipping, tracking, and returns for e-commerce with cross-regional comparison. © 2018, Emerald Publishing Limited.","Customer satisfaction; Customer service; Future purchase intention; Online shopping; Post-purchase activity; Shipping",{"$nulls":7},"Chapman C.S., Kihn L.-A., Information system integration, enabling control and performance, Accounting, Organizations and Society, 34, 2, pp. 151-169, (2009); Chauhan V., Rambabu A., An exploratory study on consumer attitude towards buying on shopping, International Journal & Mangazine of Engineering, Technology, Management and Research, 4, 3, pp. 408-413, (2017); Chen S., Chang T., A descriptive model of online shopping process: some empirical results, International Journal of Service Industry Management, 14, 5, pp. 556-569, (2003); Chiang K.-P., Dholakia R.R., Factors driving consumer intention to shop online: an empirical investigation, Journal of Consumer Psychology, 13, 1-2, pp. 177-183, (2003); Chin W.W., Newsted P.R., Structural equation modeling analysis with small samples using partial least squares, Statistical Strategies for Small Sample Research, pp. 307-341, (1999); Study: consumers demand more flexibility when shopping online, (2014); Worldwide retail ecommerce sales will reach $1.915 trillion this year,, (2016); Garbarino E., Strahilevitz M., Gender differences in the perceived risk of buying online and the effects of receiving a site recommendation, Journal of Business Research, 57, 7, pp. 768-775, (2004); Gefen D., Straub D.W., A practical guide to factorial validity using PLS-graph: tutorial and annotated example, Communications of the AIS, 16, 5, pp. 91-109, (2005); Gefen D., Straub D.W., Boudreau M.-C., Structural equation modeling and regression: guidelines for research practice, Communications of the Association for Information Systems, 4, 7, pp. 2-77, (2000); Gensler S., Verhoef P.C., Bohm M., Understanding consumers’ multichannel choices across the different stages of the buying process, Marketing Letters, 23, 4, pp. 987-1003, (2012); Gurjeet K., Khanam Q.T., Factors obstructing intentions to trust and purchase products online, Asia Pacific Journal of Marketing and Logistics, 27, 5, pp. 758-783, (2015); Hair J.F., Ringle C.M., Sarstedt M., Editorial-partial least squares structural equation modeling: rigorous applications, better results and higher acceptance, (2013); Ho C.-F., Wu W.-H., Antecedents of customer satisfaction on the internet: an empirical study of online shopping, IEEE Proceedings of the 32nd Annual Hawaii International Conference on Systems Sciences (HICSS-32), (1999); Hsu S.-H., Developing an index for online customer satisfaction: adaptation of American customer satisfaction index, Expert Systems with Applications, 34, 4, pp. 3033-3042, (2008); Jain N.K., Gajjar H., Shah B.J., Sadh A., E-fulfillment dimensions and its influence on customers in e-tailing: a critical review, Asia Pacific Journal of Marketing and Logistics, 29, 2, pp. 347-369, (2017); Kalakota R., Whinston A., Electronic Commerce: A Manager’s Guide, (1997); Lee G.-G., Lin H.-F., Customer perceptions of e-service quality in online shopping, International Journal of Retail & Distribution Management, 33, 2, pp. 161-176, (2005); Lee H.L., Whang S., Winning the last Mile of E-Commerce, 42, 4, pp. 54-62, (2001); Levin A.M., Levin I.P., Weller J.A., A multi-attribute analysis of preferences for online and offline shopping: differences across products, consumers, and shopping stages, Journal of Electronic Commerce Research, 6, 4, pp. 281-290, (2005); Li H., Kuo C., Rusell M.G., The impact of perceived channel utilities, shopping orientations, and demographics on the consumer’s online buying behavior, Journal of Computer-Mediated Communication, 5, 2, (1999); Liu X., He M., Gao F., Xie P., An empirical study of online shopping customer satisfaction in China: a holistic perspective, International Journal of Retail & Distribution Management, 36, 11, pp. 919-940, (2008); McKinney V., Yoon K., Zahedi F.M., The measurement of web-customer satisfaction: an expectation and disconfirmation approach, Information Systems Research, 13, 3, pp. 296-315, (2002); Moth D., Free shipping and delivery timing are key for customer satisfaction, (2012); Norizan K., Abdullah N.A., The effect of perceived service quality dimensions on customer satisfaction, trust, and loyalty in e-commerce settings: a cross cultural analysis, Asia Pacific Journal of Marketing and Logistics, 22, 3, pp. 351-371, (2010); Nunnally J.C., Bernstein I.H., Psychometric Theory, (1978); Oh J.-C., Yoon S.-J., Park B., A structural approach to examine the quality attributes of e-shopping malls using the Kano model, Asia Pacific Journal of Marketing and Logistics, 24, 2, pp. 305-327, (2012); Park C., Kim Y., Identifying key factors affecting consumer purchase behavior in an online shopping context, International Journal of Retail & Distribution Management, 31, 1, pp. 16-29, (2003); Reibstein D.J., What attracts customers to online stores, and what keeps them coming back?, Journal of the Academy of Marketing Science, 30, 4, pp. 465-473, (2002); Santos J., Boote J., A theoretical exploration and model of consumer expectations, post-purchase affective states and affective behaviour, Journal of Consumer Behaviour, 3, 2, pp. 142-156, (2003); Sarstedt M., Henseler J., Ringle C.M., Multigroup analysis in partial least squares (PLS) path modeling: alternative methods and empirical results, Advances in International Marketing, 22, 1, pp. 195-218, (2011); Sorce P., Perotti V., Widrick S., Attitude and age differences in online buying, International Journal of Retail & Distribution Management, 33, 2, pp. 122-132, (2005); Spagnoletti A., Shipping and delivery: what customers expect from online retailers, (2014); Stevens L., Online shopping’s hot product: free shipping, (2014); Szymanski D.M., Hise R.T., E-satisfaction: an initial examination, Journal of Retailing, 76, 3, pp. 309-322, (2000); Tam J.L.M., The moderating effects of purchase importance in customer satisfaction process: an empirical investigation, Journal of Consumer Behaviour, 10, 4, pp. 205-215, (2011); Tuttle B., Holiday spending: just how important is free shipping to online shoppers, (2011); Van Slyke C., Comunale C.L., Belanger F., Gender differences in perceptions of web-based shopping, Communications of the ACM, 45, 8, pp. 82-86, (2002); Vegiayan K.D., Ming C.W., Harun M.L.O., Online shopping and customer satisfaction in Malaysia, International Journal of Marketing Practices, 1, 1, pp. 43-51, (2013); Yao Y., Zhang J., Online retailers, shipping fees, and the bottom line, (2012); Zeithaml V.A., Parasuraman A., Malhotra A., Service quality delivery through web sites: a critical review of extant knowledge, Journal of the Academy of Marketing Science, 30, 4, pp. 362-375, (2002); Zoltners A., Sinha P., Lorimer S., Sales Force Design for Strategic Advantage, (2004); Cao Y., Ajjan H., Hong P., Using social media applications for educational outcomes in college teaching: a structural equation analysis, British Journal of Educational Technology, 44, 4, pp. 581-593, (2013); Tandon U., Kiran R., Sah A.N., Understanding barriers and drivers to online shopping: an emerging economy case, International Journal of Electronic Business, 13, 2-3, pp. 216-243, (2017)","Y. Cao; Department of Applied Business, University of La Verne, La Verne, United States; email: ycao@laverne.edu",null,"Emerald Group Publishing Ltd.",{"$nulls":5},1.3555855E7,null,null,null,"English","Asia Pac. J. Mark. Logist.","Article","Final",null,"Scopus","2-s2.0-85044513292"]
["Xiaoyan J.","Xiaoyan, Jia (57204404897)",5.7204404897E10,"Analysis and research on B2C model of agricultural product logistics distribution under electronic commerce mode",2017.0,"Agro Food Industry Hi-Tech",28.0,1.0,null,1122.0,1126.0,4.0,2.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85020878461&partnerID=40&md5=33c53937509a445be39422b76ac3e411","Zhengzhou Institute of Technology, Zhengzhou, Henan, China","Xiaoyan J., Zhengzhou Institute of Technology, Zhengzhou, Henan, China","With the rapid development of e-commerce in today's era, agricultural products have become a part of e-commerce, but there are still many problems in the line of B2C distribution. In view of this, the B2C model of agricultural products logistics distribution under e-commerce mode was analyzed in this paper. The distribution paths of a farmer's distribution company in Shanghai were analyzed by applying the traditional B2C mode distribution route method, saving method based on time window constraint and distribution path setting method in this paper. The results showed that the hybrid time window algorithm can reduce the logistics cost and improve the operation efficiency and economic benefit under the mode of B2C.","Agricultural product logistics distribution; B2C model; Electronic commerce mode","Agricultural products; Commerce; Electronic commerce; Agricultural products logistics; B2c models; Distribution companies; Economic benefits; Logistics costs; Operation efficiencies; Product logistics; Time window constraint; Agriculture",{"$nulls":6},"Wang X., Li Y., Research on logistics distribution center location model and evaluation under electronic commerce, Journal of Systems & Management, 3, 8, pp. 1-5, (2006); Fa-Hong W., Qing-Li D.A., The decision-making analysis in deciding reverse logistics system with remanufacturing in electronic industry, Chinese Journal of Management Science, 6, 8, pp. 8-12, (2006); Wang X., Dong J., Wu J., Et al., Research on the evaluation of ecommerce logistics in the cloud computing environment, International Journal of U- and E-service, Science and Technology, 9, 7, pp. 187-196, (2016); Chen Z., The logistics mode under the electronic commerce environment, Journal of Fujian Commercial College, 12, 2, pp. 89-92, (2008); Shao H.Q., Bin W., Jiang Y.C., A validity study on the electronic commerce mode and informatization construction in the perspective of value chain, Advanced Materials Research, 756-759, pp. 1003-1007, (2014); Zhang X., Zhang H., Fresh fruits and vegetables \"last mile\" home delivery in China current situation research, American Journal of Industrial and Business Management, 6, 7, (2016); Tian J., Mao X.F., Study on centralized purchasing mode in domestic shipbuilding industry under the electronic commerce environment, Ship Engineering, 31, 1, pp. 75-78, (2009); Weng X., An J., Yang H., The analysis of the development situation and trend of the city-oriented cold chain logistics system for fresh agricultural products, Open Journal of Social Sciences, 3, 11, (2015); Yao J., Gu M., Optimization analysis of supply chain resource allocation in customized online shopping service mode, Mathematical Problems in Engineering, 43, 2, pp. 63-69, (2015); Cao W., Liu N., Coordination strategy of e-commerce logistics outsourcing with channel end-nodes involved, Journal of Industrial Engineering and Engineering Management, 4, 8, pp. 24-30, (2015); Bin D., Qiuhui L., Game-theoretic analyses on distribution capability for online retailers and logistics providers, Science Research Management, 3, 2, pp. 18-21, (2014); Yang H., Wang, A novel electronic commerce mode, efficient consumer response system, Computer Engineering & Applications, 40, 19, pp. 23-25, (2004); El-Gohary H., Edwards D., Eid R., Et al., Choice of export entry mode by developing economies SMEs, An empirical investigation of Egyptian SMEs, Journal of Economic and Administrative Sciences, 29, 2, pp. 113-133, (2013); Ou T.Y., Perng C., Constructing the e-commerce clustering platform and innovative business model-a case study for Chinese herbal medicine industry, International Journal of Electronic Business Management, 12, 2, (2014); Khan S.A., Liang Y., Shahzad S., Adoption of electronic supply chain management and e-commerce by small and medium enterprises and their performance, a survey of SMEs in Pakistan, American Journal of Industrial and Business Management, 2014",null,null,"TeknoScienze",{"$nulls":5},1.7226996E7,null,null,null,"English","Agro Food Ind. Hi-Tech","Article","Final",null,"Scopus","2-s2.0-85020878461"]
["Yang X.; Strauss A.K.","Yang, Xinan (57169073500); Strauss, Arne K. (36648125000)","57169073500; 36648125000","An approximate dynamic programming approach to attended home delivery management",2017.0,"European Journal of Operational Research",263.0,3.0,null,935.0,945.0,10.0,60.0,"10.1016/j.ejor.2017.06.034","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85021759512&doi=10.1016%2fj.ejor.2017.06.034&partnerID=40&md5=278e429fb0e459eda1930b661b509c65","Department of Mathematics, University of Essex, Colchester CO4 3SQ, United Kingdom; Warwick Business School, University of Warwick, Coventry CV4 7AL, United Kingdom","Yang X., Department of Mathematics, University of Essex, Colchester CO4 3SQ, United Kingdom; Strauss A.K., Warwick Business School, University of Warwick, Coventry CV4 7AL, United Kingdom","We propose a new method of controlling demand through delivery time slot pricing in attended home delivery management with a focus on developing an approach suitable for industry-scale implementation. To this end, we exploit a relatively simple yet effective way of approximating delivery costs by decomposing the overall delivery problem into a collection of smaller, area-specific problems. These cost estimations serve as inputs into an approximate dynamic programming method that provides estimates of the opportunity cost associated with having a customer from a specific area book delivery in a specific time slot. These estimates depend on the area and on the delivery time slot under consideration. Using real, large-scale industry data, we estimate a demand model including a multinomial logit model of customers’ delivery time slot choice, and show in simulation studies that we can improve profits by over two percent in all tested instances relative to using a fixed-price policy commonly encountered in e-commerce. These improvements are achieved despite making strong assumptions in estimating delivery cost. These assumptions allow us to reduce computational run-time to a level suitable for real-time decision making on delivery time slot feasibility and pricing. Our approach provides quantitative insight into the importance of incorporating expected future order displacement costs into opportunity cost estimations alongside marginal delivery costs. © 2017 Elsevier B.V.","Dynamic programming; E-commerce; Revenue management","Commerce; Cost estimating; Costs; Dynamic programming; Economics; Electronic commerce; Estimation; Approximate dynamic programming; Delivery problems; Multinomial logit model; Opportunity costs; Real time decision-making; Revenue management; Simulation studies; Specific problems; Cost benefit analysis",{"$nulls":6},"Adelman D., Dynamic bid prices in revenue management, Operations Research, 55, 4, pp. 647-661, (2007); Agatz N., Campbell A., Fleischmann M., Savelsbergh M., Time slot management in attended home delivery, Transportation Science, 45, 3, pp. 435-449, (2011); Agatz N.A.H., Fleischmann M., van Nunen J.A.E.E., E-fulfillment and multi-channel distribution: A review, European Journal of Operational Research, 187, 2, pp. 339-356, (2008); Asdemir K., Jacob V.S., Krishnan R., Dynamic pricing of multiple home delivery options, European Journal of Operational Research, 196, 1, pp. 246-257, (2009); Bell D., Song S., Neighborhood effects and trial on the internet: Evidence from online grocery retailing, Quantitative Marketing and Economics, 5, 4, pp. 361-400, (2007); Buhler D., Klein R., Neugebauer M., Model-based delivery cost approximation in attended home services, Computers & Industrial Engineering, 98, pp. 78-90, (2016); Campbell A.M., Savelsbergh M., Incentive schemes for attended home delivery services, Transportation Science, 40, 3, pp. 327-341, (2006); Campbell A.M., Savelsbergh M.W.P., Decision support for consumer direct grocery initiatives, Transportation Science, 39, 3, pp. 313-327, (2005); Cleophas C., Ehmke J.F., When are deliveries profitable? Considering order value and transport capacity in demand fulfillment for last-mile deliveries in metropolitan areas, Business and Information Systems Engineering, 6, 3, pp. 153-163, (2014); Daganzo C.F., Modelling distribution problems with time windows: Part 1, Transportation Science, 21, 3, pp. 171-179, (1987); Davis J., Gallego G., Topaloglu H., Assortment planning under the multinomial logit model with totally unimodular constraint structures, (2013); Dong L., Kouvelis P., Tian Z., Dynamic pricing and inventory control of substitute products, Manufacturing & Service Operations Management, 11, 2, pp. 317-339, (2009); Ehmke J.F., Campbell A.M., Customer acceptance mechanisms for home deliveries in metropolitan areas, European Journal of Operational Research, 233, 1, pp. 193-207, (2014); Hubner A., Kuhn H., Wollenburg J., Last mile fulfilment and distribution in omni-channel grocery retailing, International Journal of Retail & Distribution Management, 44, 3, pp. 228-247, (2016); Klein R., Mackert J., Neugebauer M., Steinhardt C., On the approximation of opportunity cost for dynamic pricing in attended home delivery, (2016); Klein R., Neugebauer M., Ratkovitch D., Steinhardt C., Differentiated time slot pricing under routing considerations in attended home delivery, (2015); Lang M., Ehmke J., Kohler C., Cleophas C., Considering equity in retail order acceptance for attended deliveries, Annual conference of the pricing & revenue management section of the German OR Society in February 2017, (2017); Meissner J., Strauss A., Network revenue management with inventory-sensitive bid prices and customer choice, European Journal of Operational Research, 216, 2, pp. 459-468, (2012); Mintel, Online Grocery Retailing UK – March 2016, Technical Report, (2016); Rayfield W.Z., Rusmevichientong P., Topaloglu H., Approximation methods for pricing problems under the nested logit model with price bounds, (2013); Yang X., Strauss A.K., Currie C.S.M., Eglese R., Choice-based demand management and vehicle routing in e-fulfillment, Transportation Science, 50, 2, pp. 473-488, (2016)","A.K. Strauss; Warwick Business School, University of Warwick, Coventry CV4 7AL, United Kingdom; email: arne.strauss@wbs.ac.uk",null,"Elsevier B.V.",{"$nulls":5},3772217.0,null,"EJORD",null,"English","Eur J Oper Res","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85021759512"]
["Patro C.S.","Patro, Chandra Sekhar (54783307500)",5.47833075E10,"Attitudes of E-Shoppers and Non E-shoppers towards E-Shopping: A comparative study",2016.0,"International Journal of Cyber Behavior, Psychology and Learning",6.0,2.0,null,96.0,108.0,12.0,11.0,"10.4018/IJCBPL.2016040106","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84978239655&doi=10.4018%2fIJCBPL.2016040106&partnerID=40&md5=df92c2fa14c76f33c3a0cd0fd91e8293","Department of Management Studies, Gayatri Vidya Parishad College of Engineering, Visakhapatnam, India","Patro C.S., Department of Management Studies, Gayatri Vidya Parishad College of Engineering, Visakhapatnam, India","Today, the emergence and rapid growth of E-commerce has triggered off many changes in daily life. This new phenomenon has promised change, challenges and even bright future, not only to consumers but also to the e-tailing companies, suppliers and middlemen. E-shopping plays a major role in the Indian economy and is expected to change the current scenario of shopping from physical stores to e-stores. This study aims to examine the buyers' attitude towards e-shopping and also to find the critical reasons for not shopping through online. The results reveal that buyers are still hesitating to shop online. The most important reasons for buyers in both cities not to shop online are online security, prefer to buy by touching and feeling, and customer service. The factors influencing to buy online are being able to get detailed product information, product delivery, convenience, product quality and competitive prices. These results also have some practical implications for managers and strategists of e-stores. Copyright © 2016, IGI Global.","Attitude; Buyer; E-Shoppers; E-Shopping; E-Stores",{"$nulls":7},"Ajzen I., Fishbein M., Understanding Attitudes and Predicting Social Behavior, (1980); Barsauskas P., Sarapovas T., Cvilikas A., The evaluation of e-commerce impact on business efficiency, Baltic Journal of Management, 3, 1, pp. 71-91, (2008); Case T., Burns O.M., Dick G.N., Drivers of online purchases among U.S. Students, Proceedings of the 7th American Conference on Information Systems, pp. 900-907, (2001); Chaturvedi S., Gupta S., Effect of social media on online shopping behaviour of apparels in Jaipur city - An analytical review, Journal of Business Management. Commerce & Research, 2, 7, pp. 1-8, (2014); Eagly A.H., Chaiken S., The Psychology of Attitudes, (1993); Gao Y., Web Systems Design and Online Consumer Behavior, (2005); Ghosh A.K., Securing e-commerce: A systematic approach, Journal of Internet Banking and Commerce, 2, 4, pp. 1-4, (1997); Goswami A., Baruah P., Borah S., Customer satisfaction towards online shopping with special reference to teenage group of jorhat town, PARIPEX - Indian Journal of Research, 3, 4, pp. 239-241, (2013); Gupta D.K., Khincha P.K., Factors influencing online shopping behavior of customers: An empirical study, Common Wealth Journal of Commerce & Management Research, 2, 7, pp. 39-50, (2015); Haq Z.U., Perception towards online shopping: An empirical study of Indian consumers, Abhinav National Monthly Refereed Journal of Research in Commerce & Management, 1, 8, pp. 9-22, (2014); Hasslinger A., Hodzic S., Obazo C., Consumer Behaviour in Online Shopping, pp. 18-22, (2007); Hirst A., Ashwin M., Cross cultural difference between online shoppers in london and Bangkok, International Review of Business Research Papers, 5, 4, pp. 167-191, (2009); Jiradilok R., Malisuwan S., Madan N., Sivaraks J., The impact of customer satisfaction on online purchasing: A case study analysis in Thailand, Journal of Economics. Business and Management, 2, 1, pp. 5-11, (2014); Jusoh Z.M., Ling G.H., Factors influencing consumers' attitude towards E-commerce purchases through online shopping, International Journal of Humanities and Social Science, 2, 4, pp. 223-230, (2012); Keisidou E., Sarigiannidis L., Maditinos D., Consumer characteristics and their effect on accepting online shopping in the context of different product types, International Journal of Business Science and Applied Management, 6, 2, pp. 31-51, (2011); Laudon K., Laudon J., Essentials of Management Information Systems (8th Edition), (2009); Li N., Zhang P., Consumer online shopping attitudes and behavior: An assessment of research, Proceedings of Eight American Conference on Information Systems, pp. 508-517, (2002); Lian J.W., Lin T.M., Effects of consumer characteristics on their acceptance of online shopping: Comparisons among different product types, Computers in Human Behavior, 24, 1, pp. 48-65, (2008); McCloskey D.W., Whiteley D., Electronic Commerce Acceptance: A Study Comparing the United States and the United Kingdom, Strategies for Ecommerce Success, (2002); Osman S., Yin-Fah B.C., Choo B.H., Undergraduates and online purchasing behavior, Asian Social Science, 6, 10, pp. 133-141, (2010); Richa D., Impact of demographic factors of consumers on online shopping behaviour: A study of consumers in India, International Journal of Engineering and Management Sciences, 3, 1, pp. 43-52, (2012); Schiffman L.G., Kanuk L.L., Consumer Behavior (9th Ed.), (2007); Sharma N.V., Khattri V., Study of online shopping behavior and its impact on online deal websites, Asian Journal of Management Research, 3, 2, pp. 394-405, (2013); Sharma R., Mehta K., Sharma S., Understanding online shopping behaviour of Indian shoppers, International Journal of Management & Business Studies, 4, 3, pp. 9-18, (2014); Shergill G.S., Chen Z., Web-based shopping: Consumers' attitudes towards online shopping in New Zealand, Journal of Electronic Commerce Research, 6, 2, pp. 79-94, (2005); Silverstein B., Business to Business Internet Marketing: Seven Proven Strategies for Increasing Profits Through Internet Direct Marketing (4th Ed.), (2002); Sorce P., Perotti V., Widrick S., Attitude and age differences in online buying, International Journal of Retail & Distribution Management, 33, 2, pp. 122-132, (2005); Tassabehji R., Applying E-commerce in Business, (2003); Treese G.W., Stewart L.C., Designing Systems for Internet Commerce, (2003); Vladimir Z., Electronic commerce: Structures and issues, International Journal of Electronic Commerce, 1, 1, pp. 3-23, (1996); Wang N., Liu D., Cheng J., Study on the influencing factors of online shopping,  Joint International Conference on Information Sciences, (2008); Yoruk D., Dundar S., Moga L.M., Neculita M., Drivers and attitudes towards online shopping: Comparison of Turkey with Romania, Communications of the IBIMA, pp. 1-13, (2011); Zeng M., Reinartz W., Beyond online search: The road to profitability, California Management Review, 45, 2, pp. 107-130, (2003)",null,null,"IGI Global",{"$nulls":5},2.1557136E7,null,null,null,"English","Int. J. Cyber Behav. Psychol. Learn.","Article","Final",null,"Scopus","2-s2.0-84978239655"]
["Emeç U.; Çatay B.; Bozkaya B.","Emeç, Uʇur (57053446500); Çatay, Bülent (6505945515); Bozkaya, Burcin (6507076223)","57053446500; 6505945515; 6507076223","An Adaptive Large Neighborhood Search for an E-grocery Delivery Routing Problem",2016.0,"Computers and Operations Research",69.0,null,null,109.0,125.0,16.0,49.0,"10.1016/j.cor.2015.11.008","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84954159847&doi=10.1016%2fj.cor.2015.11.008&partnerID=40&md5=8deecadd2ac29e3e57ed5142802b517f","Sabanci University, Faculty of Engineering and Natural Sciences, Tuzla, Istanbul, 34956, Turkey; Sabanci University, School of Management, Tuzla, Istanbul, 34956, Turkey","Emeç U., Sabanci University, Faculty of Engineering and Natural Sciences, Tuzla, Istanbul, 34956, Turkey; Çatay B., Sabanci University, Faculty of Engineering and Natural Sciences, Tuzla, Istanbul, 34956, Turkey; Bozkaya B., Sabanci University, School of Management, Tuzla, Istanbul, 34956, Turkey","Online shopping has become ever more indispensable to many people with busy schedules who have a growing need for services ranging for a wide variety of goods, which include standard (or \"staple\") goods as well as \"premium\" goods, i.e. goods such as organic food, specialty gifts, etc. that offer higher value to consumers and higher profit margins to retailers. In this paper, we introduce a new mathematical programming formulation and present an efficient solution approach for planning the delivery services of online groceries to fulfill this diverse consumer demand without incurring additional inventory costs. We refer to our proposed model as the E-grocery Delivery Routing Problem (EDRP) as it generically represents a family of problems that an online grocery is likely to face. The EDRP is based on a distribution network where premium goods are acquired from a set of external vendors at multiple locations in the supply network and delivered to customers in a single visit. To solve this problem, we develop an improved Adaptive Large Neighborhood Search (ALNS) heuristic by introducing new removal, insertion, and vendor selection/allocation mechanisms. We validate the performance of the proposed ALNS heuristic through an extensive computational study using both the well-known Vehicle Routing Problem with Time Windows instances of Solomon and a set of new benchmark instances generated for the EDRP. The results suggest that the proposed solution methodology is effective in obtaining high quality solutions fast. © 2015 Elsevier Ltd. All rights reserved.","Adaptive Large Neighborhood Search; E-grocery Delivery Routing Problem; Home Delivery Services; Premium Customer; Premium Good; Vehicle Routing Problem with Time Windows","Benchmarking; Distribution of goods; Mathematical programming; Network routing; Optimization; Routing algorithms; Sales; Vehicle routing; Adaptive large neighborhood searches; Home delivery services; Premium Customer; Premium Good; Routing problems; Vehicle routing problem with time windows; Problem solving",{"$nulls":6},"Adulyasak Y., Cordeau J.-F., Jans R., Optimization-based Adaptive Large Neighborhood Search for the production routing problem, Transp Sci, 48, 1, pp. 20-45, (2014); Aksen D., Kaya O., Salman S., Tuncel O., An Adaptive Large Neighborhood Search algorithm for a selective and periodic inventory routing problem, Eur J Oper Res, 239, pp. 413-426, (2014); Angelelli E., Speranza M.G., The periodic vehicle routing problem with intermediate facilities, Eur J Oper Res, 137, pp. 233-247, (2002); Attanasio A., Cordeau J.-F., Ghiani G., Laporte G., Parallel tabu search heuristics for the dynamic multi-vehicle dial-A-Ride problem, Parallel Comput, 30, pp. 377-387, (2004); Azi N., Gendreau M., Potvin J.-Y., An Adaptive Large Neighborhood Search for a vehicle routing problem with multiple routes, Comput Oper Res, 41, pp. 167-173, (2014); Bard J.F., Huang L., Dror M., Jaillet P., A branch and cut algorithm for the VRP with satellite facilities, IIE Trans, 30, pp. 821-834, (1998); Bard J.F., Huang L., Jaillet P., Dror M., A decomposition approach to the inventory routing problem with satellite facilities, Transp Sci, 32, pp. 189-203, (1998); Bent R., Hentenryck P.V., A two-stage hybrid algorithm for pickup and delivery vehicle routing problems with time windows, Comput Oper Res, 33, pp. 875-893, (2006); Bensinger G., Stevens, Threat to UPS, tries its own deliveries, The Wall Street Journal, (2014); Bozkaya B., De Kervenoael R., Aykac D.S.O., Premium e-grocery: Exploring value in logistics integrated service solutions, Proceedings of the International Conference on Prospects for Research in Transportation and Logistics on a Regional-Global Perspective, 3, pp. 173-178, (2009); Campbell A.M., Savelsbergh M.W.P., Decision support for consumer direct grocery initiatives, Transp Sci, 39, pp. 313-327, (2005); Caricato P., Ghiani G., Grieco A., Guerriero E., Parallel tabu search for a pickup and delivery problem under track contention, Parallel Comput, 29, pp. 631-639, (2003); Cordeau J., Laporte G., Pasin F., Ropke S., Scheduling technicians and tasks in a telecommunications company, J Sched, 13, pp. 1-17, (2010); Demir E., Bektas T., Laporte G., An Adaptive Large Neighborhood Search heuristic for the pollution-routing problem, Eur J Oper Res, 223, pp. 346-359, (2012); Doerner K., Hartl R.F., Reimann M., Ants solve time constrained pickup and delivery problems with full truckloads, Oper Res Proc, pp. 395-400, (2001); Ganesh K., Narendran T.T., CLOVES: A cluster-and-search heuristic to solve the vehicle routing problem with delivery and pick-up, Eur J Oper Res, 178, pp. 699-717, (2007); Hart S.M., The modeling and solution of a class of dial-A-Ride problems using simulated annealing, Control Cybern, 25, pp. 131-157, (1996); 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Bozkaya; Sabanci University, School of Management, Istanbul, Tuzla, 34956, Turkey; email: bbozkaya@sabanciuniv.edu",null,"Elsevier Ltd",{"$nulls":5},3050548.0,null,"CMORA",null,"English","Comp. Oper. Res.","Article","Final",null,"Scopus","2-s2.0-84954159847"]
["Kemény I.; Simon J.; Nagy Á.; Szucs K.","Kemény, Ildikó (57189493517); Simon, Judit (57213794268); Nagy, Ákos (57206143823); Szucs, Krisztián (57191663856)","57189493517; 57213794268; 57206143823; 57191663856","Measuring quality perception in electronic commerce A possible segmentation in the Hungarian market",2016.0,"Industrial Management and Data Systems",116.0,9.0,null,1946.0,1966.0,20.0,19.0,"10.1108/IMDS-09-2015-0398","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84992364630&doi=10.1108%2fIMDS-09-2015-0398&partnerID=40&md5=f40a09cec03e82e1e0e4abff36a7f3c4","Department of Marketing Research and Consumer Behaviour, Corvinus University of Budapest, Budapest, Hungary; Department of Marketing and Media, Corvinus University of Budapest, Budapest, Hungary; Faculty of Business and Economics, University of Pécs, Pécs, Hungary","Kemény I., Department of Marketing Research and Consumer Behaviour, Corvinus University of Budapest, Budapest, Hungary; Simon J., Department of Marketing and Media, Corvinus University of Budapest, Budapest, Hungary; Nagy Á., Faculty of Business and Economics, University of Pécs, Pécs, Hungary; Szucs K., Faculty of Business and Economics, University of Pécs, Pécs, Hungary","Purpose - The perceived electronic-service quality (e-SQ) has become a relevant research area, not only in developed but also in smaller, less-developed countries. The purpose of this paper is to provide a description of an analysis into the relationship of the dimensions of perceived e-SQ and satisfaction as well as WOM intention in case of an online bookstore in Hungary where technical development and internet penetration is emerging; however, it is developing from an economic perspective. Beyond this a potential segmentation is introduced in the Hungarian market. Design/methodology/approach - The direct effect of perceived e-SQ's dimensions on satisfaction and on traditional WOM were analysed using the PLS-SEM method, which was followed by the segmentation approach. The paper also demonstrates differences of the identified consumer segments, using multivariate analysis of variance. Findings - According to the research only the dimension of efficiency and responsiveness have a significant positive effect on satisfaction, and beside these the quality perception of fulfilment has a significant influence on WOM intention. Using the relevant latent variable scores segmentation was conducted and four clusters were identified. Originality/value - Due to peculiarities of e-services, quality measurement needs a constant revision and adoption. Extent amount of research has been dedicated to analyse the relationship of quality and satisfaction, but the direct effect of relevant quality dimensions on word-of-mouth intention is a new research field. Segmenting customers based on latent variable scores of the proposed model has not been conducted before in case of an online bookstore in Hungary. According to the results the evaluation of the technology-based components has the greatest effect on satisfaction and WOM intention. However, web-shops managers should focus not only on online characteristics but also on offline, human-based interactions and the service quality of their delivery partners. © 2016 Emerald Group Publishing Limited.","E-commerce; E-service quality perception; Segmentation","Customer satisfaction; Electronic commerce; Image segmentation; Multivariant analysis; Quality of service; Scanning electron microscopy; Design/methodology/approach; E-service quality; Economic perspective; Electronic service qualities; Less developed countries; Multivariate analysis of variances; Quality measurements; Technical development; Commerce",{"$nulls":6},"Ajzen I., Fishbein M., Attitudes and normative beliefs as factors influencing behavioral intentions, Journal of Personality and Social Psychology, 21, 1, pp. 1-9, (1972); Akinci S., Atilgan-Inan E., Aksoy S., Re-assessment of E-S-Qual and E-RecS-qual in a pure service setting, Journal of Business Research, 63, 3, pp. 232-240, (2010); Anderson R.E., Srinivasan S.S., E-satisfaction and e-loyalty: A contingency framework, Psychology and Marketing, 20, 2, pp. 123-138, (2003); 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Kemény; Department of Marketing Research and Consumer Behaviour, Corvinus University of Budapest, Budapest, Hungary; email: ildiko.kemeny@uni-corvinus.hu",null,"Emerald Group Publishing Ltd.",{"$nulls":5},2635577.0,null,"IMDSD",null,"English","Ind Manage Data Sys","Article","Final",null,"Scopus","2-s2.0-84992364630"]
["Lopez-Loces M.C.; Musial J.; Pecero J.E.; Fraire-Huacuja H.J.; Blazewicz J.; Bouvry P.","Lopez-Loces, Mario C. (56588022100); Musial, Jedrzej (36184609400); Pecero, Johnatan E. (56013709600); Fraire-Huacuja, Hector J. (25931955700); Blazewicz, Jacek (35586597300); Bouvry, Pascal (6603233977)","56588022100; 36184609400; 56013709600; 25931955700; 35586597300; 6603233977","Exact and heuristic approaches to solve the Internet shopping optimization problem with delivery costs",2016.0,"International Journal of Applied Mathematics and Computer Science",26.0,2.0,null,391.0,406.0,15.0,15.0,"10.1515/amcs-2016-0028","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84978374642&doi=10.1515%2famcs-2016-0028&partnerID=40&md5=a79c93ceff229d82dc7350d395e16db6","National Institute of Technology of Ciudad Madero, National Institute of Technology of Mexico, Sor Juana Inés de la Cruz s/n, Cd. Madero, Tamaulipas, Mexico, 89440, Mexico; Institute of Computing Science Poznań, University of Technology, ul. Piotrowo 2, Poznań, 60-965, Poland; Computer Science and Communications Research Unit, University of Luxembourg, rue Richard Coudenhove-Kalergi 6, Luxembourg, L-1359, Luxembourg; Institute of Bioorganic, Chemistry Polish Academy of Sciences, ul. Z. Noskowskiego 12/14, Poznań, 61-704, Poland","Lopez-Loces M.C., National Institute of Technology of Ciudad Madero, National Institute of Technology of Mexico, Sor Juana Inés de la Cruz s/n, Cd. Madero, Tamaulipas, Mexico, 89440, Mexico; Musial J., Institute of Computing Science Poznań, University of Technology, ul. Piotrowo 2, Poznań, 60-965, Poland; Pecero J.E., Computer Science and Communications Research Unit, University of Luxembourg, rue Richard Coudenhove-Kalergi 6, Luxembourg, L-1359, Luxembourg; Fraire-Huacuja H.J., National Institute of Technology of Ciudad Madero, National Institute of Technology of Mexico, Sor Juana Inés de la Cruz s/n, Cd. Madero, Tamaulipas, Mexico, 89440, Mexico; Blazewicz J., Institute of Computing Science Poznań, University of Technology, ul. Piotrowo 2, Poznań, 60-965, Poland, Institute of Bioorganic, Chemistry Polish Academy of Sciences, ul. Z. Noskowskiego 12/14, Poznań, 61-704, Poland; Bouvry P., Computer Science and Communications Research Unit, University of Luxembourg, rue Richard Coudenhove-Kalergi 6, Luxembourg, L-1359, Luxembourg","Internet shopping has been one of the most common online activities, carried out by millions of users every day. As the number of available offers grows, the difficulty in getting the best one among all the shops increases as well. In this paper we propose an integer linear programming (ILP) model and two heuristic solutions, the MinMin algorithm and the cellular processing algorithm, to tackle the Internet shopping optimization problem with delivery costs. The obtained results improve those achieved by the state-of-the-art heuristics, and for small real case scenarios ILP delivers exact solutions in a reasonable amount of time. © 2016 by Jedrzej Musial.","cellular processing algorithm; heuristic algorithms; integer linear programming; Internet shopping optimization; optimization in e-commerce","Algorithms; Electronic commerce; Heuristic algorithms; Heuristic methods; Heuristic programming; Integer programming; Internet; Heuristic approach; Heuristic solutions; Integer Linear Programming; Integer linear programming models; Internet shopping; Optimization problems; Processing algorithms; Real case scenarios; Optimization",{"$nulls":6},"Blazewicz J., Bouvry P., Kovalyov M.Y., Musial J., Erratum to: Internet shopping with price-sensitive discounts, 4OR-A Quarterly Journal of Operations Research, 12, 4, pp. 403-406, (2014); Blazewicz J., Bouvry P., Kovalyov M.Y., Musial J., Internet shopping with price sensitive discounts, 4OR-A Quarterly Journal of Operations Research, 12, 1, pp. 35-48, (2014); Blazewicz J., Burkard R., Finke G., Woeginger G., Vehicle scheduling in two-cycle flexible manufacturing systems, Mathematical and Computer Modelling, 20, 2, pp. 19-31, (1994); Blazewicz J., Cheriere N., Dutot P.-F., Musial J., Trystram D., Novel dual discounting functions for the Internet shopping optimization problem: New algorithms, Journal of Scheduling, 19, 3, pp. 245-255, (2016); Bazewicz J., Kovalyov M., Musia J., Urbanski A., Wojciechowski A., Internet shopping optimization problem, International Journal of Applied Mathematics and Computer Science, 20, 2, pp. 385-390, (2010); Blazewicz J., Musial J., E-commerce evaluation-multi-item internet shopping. Optimization and heuristic algorithms, Operations Research Proceedings 2010, pp. 149-154, (2011); Blazewicz J., Pesch E., Sterna M., Werner F., A note on the two machine job shop with the weighted late work criterion, Journal of Scheduling, 10, 2, pp. 87-95, (2007); Burke E., Kendall G., Newall J., Hart E., Ross P., Schulenburg S., Hyper-heuristics: An emerging direction in modern search technology, Handbook of Metaheuristics, International Series in Operations Research & Management Science, 57, pp. 457-474, (2003); Cheung C.M., Chan G.W., Limayem M., A critical review of online consumer behavior: Empirical research, Journal of Electronic Commerce in Organizations, 3, 4, pp. 1-19, (2005); Chu W., Choi B., Song M., The role of on-line retailer brand and infomediary reputation in increasing consumer purchase intention, International Journal of Electronic Commerce, 9, 3, pp. 115-127, (2005); Clay K., Krishnan R., Wolff E., Prices and price dispersion on the web: Evidence from the online book industry, Journal of Industrial Economics, 49, 4, pp. 521-539, (2001); 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Iyigun C., Ben-Israel A., A generalized Weiszfeld method for the multi-facility location problem, Operations Research Letters, 38, 3, pp. 207-214, (2010); Krarup J., Pisinger D., Plastria F., Discrete location problems with push-pull objectives, Discrete Applied Mathematics, 123, 1, pp. 363-378, (2002); Krichen S., Laabidi A., Abdelaziz F.B., Single supplier multiple cooperative retailers inventory model with quantity discount and permissible delay in payments, Computers & Industrial Engineering, 60, 1, pp. 164-172, (2011); Marszalkowski J., Marszalkowski J.M., Drozdowski M., Empirical study of load time factor in search engine ranking, Journal of Web Engineering, 13, 1-2, pp. 114-128, (2014); Marszalkowski J., Musial J., Database scheme optimization for online applications, Foundations of Computing and Decision Sciences, 36, 2, pp. 121-129, (2011); Melo M.T., Nickel S., Saldanha Da Gama F., Facility location and supply chain management-A review, European Journal of Operational Research, 196, 2, pp. 401-412, (2009); Mirmohammadi S.H., Shadrokh S., Kianfar F., An efficient optimal algorithm for the quantity discount problem in material requirement planning, Computers & Operations Research, 36, 6, pp. 1780-1788, (2009); Munson C., Hu J., Incorporating quantity discounts and their inventory impacts into the centralized purchasing decision, European Journal of Operational Research, 201, 2, pp. 581-592, (2010); Musial J., Applications of Combinatorial Optimization for Online Shopping, (2012); Nesmachnow S., Dorronsoro B., Pecero J.E., Bouvry P., Energy-aware scheduling on multicore heterogeneous grid computing systems, Journal of Grid Computing, 11, 4, pp. 653-680, (2013); Pan X., Ratchford B., Shankar V., The evolution of price dispersion in internet retail markets, Organizing the New Industrial Economy, Advances in Applied Microeconomics, 12, pp. 85-105, (2003); Pathak B., Comparison shopping agents and online price dispersion: A search cost based explanation, Journal of Theoretical and Applied Electronic Commerce Research, 7, 1, pp. 64-76, (2012); Ratchford B., Pan X., Shankar V., On the efficiency of internet markets for consumer goods, Journal of Public Policy & Marketing, 22, 1, pp. 4-16, (2003); Revelle C., Eiselt H., Daskin M., A bibliography for some fundamental problem categories in discrete location science, European Journal of Operational Research, 184, 3, pp. 817-848, (2008); Rose S., Dhandayudham A., Towards an understanding of Internet-based problem shopping behaviour: The concept of online shopping addiction and its proposed predictors, Journal of Behavioral Addictions, 3, 2, pp. 83-89, (2014); Rose S., Samouel P., Internal psychological versus external market-driven determinants of the amount of consumer information search amongst online shoppers, Journal of Marketing Management, 25, 1-2, pp. 171-190, (2009); Sawik B., Downside risk approach for multi-objective portfolio optimization, Operations Research Proceedings 2011, pp. 191-196, (2012); Simpson T., The Doctrine and Application of Fluxions, (1750); Sipper M., The emergence of cellular computing, Computer, 32, 7, pp. 18-26, (1999); Sterna M., Late work minimization in a small flexible manufacturing system, Computers & Industrial Engineering, 52, 2, pp. 210-228, (2007); Teran-Villanueva J.D., Huacuja H.J.F., Valadez J.M.C., Rangel R.P., Soberanes H.J.P., Flores J.A.M., A heterogeneous cellular processing algorithm for minimizing the power consumption in wireless communications systems, Computational Optimization and Applications, 62, 3, pp. 787-814, (2015); Weber A., The Theory of the Location of Industries, (1929); Wojciechowski A., Musial J., A customer assistance system: Optimizing basket cost, Foundations of Computing and Decision Sciences, 34, 1, pp. 59-69, (2009); Wojciechowski A., Musial J., Towards optimal multi-item shopping basket management: Heuristic approach, Lecture Notes in Computer Science, 6428, pp. 349-357, (2010)","J. Musial; Institute of Computing Science Poznań, University of Technology, Poznań, ul. Piotrowo 2, 60-965, Poland; email: Jedrzej.Musial@cs.put.poznan.pl",null,"Walter de Gruyter GmbH",{"$nulls":5},"1641876X",null,null,null,"English","Int. J. Appl. Math. Comput. Sci.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-84978374642"]
["Pålsson H.; Pettersson F.; Winslott Hiselius L.","Pålsson, Henrik (26023648700); Pettersson, Fredrik (57195356526); Winslott Hiselius, Lena (6507201120)","26023648700; 57195356526; 6507201120","Energy consumption in e-commerce versus conventional trade channels - Insights into packaging, the last mile, unsold products and product returns",2017.0,"Journal of Cleaner Production",164.0,null,null,765.0,778.0,13.0,113.0,"10.1016/j.jclepro.2017.06.242","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85027455623&doi=10.1016%2fj.jclepro.2017.06.242&partnerID=40&md5=6b1e99904e2f6cedbc0201a2c74f51f9","Division of Packaging Logistics, Department of Design Sciences, Lund University, Lund, Sweden; Division of Transport and Roads, Department of Technology and Society, Lund University, Lund, Sweden","Pålsson H., Division of Packaging Logistics, Department of Design Sciences, Lund University, Lund, Sweden; Pettersson F., Division of Transport and Roads, Department of Technology and Society, Lund University, Lund, Sweden; Winslott Hiselius L., Division of Transport and Roads, Department of Technology and Society, Lund University, Lund, Sweden","The purpose is to analyse and explain factors determining whether conventional trade with stores or e-commerce with home delivery is more energy-efficient. The findings from previous studies are compared in order to identify more general patterns of energy consumption, describe which energy consumption factors (product waste and product returns, buildings, packaging, passenger transport and freight transport) are considered and what assumptions are made. In this comparison, we analyse product characteristics and product classes, discuss the energy factors with the greatest impact and the contextual impact of each factor on the energy consumption. The paper is based on a structured literature review and a content analysis, which helped us to synthesise current knowledge and explain consistent and inconsistent findings across individual studies of energy consumption in conventional sales channels versus e-commerce channels. Our literature search identified 11 studies, with 16 cases, that compared the energy efficiency. The results show the following: 1) The net effect of energy consumption was in the majority of the cases positive for the e-commerce channel, 2) The proportion of unsold products and product returns seem to have a major impact on the energy efficiency of different sales channels, 3) Buildings had only a minor effect on the energy consumption difference. It was slightly lower in the home delivery systems, 4) Packaging contributed considerably to the energy consumption difference for some products. The e-commerce channel consumed generally more energy from packaging, but indirect effects (e.g. volume efficiency) were not considered, and 5) The total energy consumption from transportation was greater in the conventional supply chains, as the additional energy in passenger transport generally outweighed the increased energy in freight transport in e-commerce. The paper points out directions for future research and discusses implications for research, policy-making and practice. © 2017 Elsevier Ltd","E-commerce; Energy; Last mile; Packaging; Product waste; Supply chain","Commerce; Electronic commerce; Energy conservation; Energy utilization; Freight transportation; Packaging; Supply chains; Transportation; Energy; Last mile; Literature reviews; Literature search; Passenger transport; Product characteristics; Total energy consumption; Volume efficiency; Energy efficiency",{"$nulls":4},"Energimyndigheten, (P38944-1)","The authors would like to thank the Swedish Energy Agency (P38944-1) for funding this research.","Bhatnagar A., Ghose S., A latent class segmentation analysis of e-shoppers, J. Bus. Res., 57, 7, pp. 758-767, (2004); Borggren C., Moberg A., Finnvreden G., Books from an environmental perspective – part 1: environmental impacts of paper books sold in traditional and internet bookshops, Int. J. Life Cycle Assess., 11, 2, pp. 138-147, (2011); Browne M., Allen J., Rizet C., Assessing transport energy consumption in two product supply chains, Int. J. Logist. Res. Appl., 9, pp. 237-252, (2006); Bryman A., Samhällsvetenskapliga Metoder, (2004); Carrillo J.E., Vakharia A.J., Wang R., Environmental implications for online retailing, Eur. J. Oper. Res., 239, 3, pp. 744-755, (2014); Caudill R.J., Luo Y., Wirojanagud P., Zhou M., A lifecycle environmental study of the impact of e-commerce on electronic products, In Proceedings of the 2000 IEEE International Symposium on Electronics and the Environment, pp. 298-303, (2000); Chiang K.P., Dholakia R.R., Factors driving consumer intention to shop online, J. Consum. Psychol., 13, 1, pp. 177-183, (2003); Cholette S., Venkat K., The energy and carbon intensity of wine distribution: a study of logistical options for delivering wine to consumers, J. Clean. Prod., 17, 16, pp. 1401-1413, (2009); Cohen N., The Environmental impacts of E-commerce, In EnviroInfo 2001: Sustainability in the Information Society, pp. 41-52, (2001); Duch-Brown N., Grzybowski L., Verboven F., The Impact of Online Sales on Consumers and Firms. Evidence from Household Appliances, (2015); Edwards J.B., McKinnon A.C., Cullinane S.L., Comparative analysis of the carbon footprints of conventional and online retailing: a ‘last mile’ perspective, International J. Phys. Distrib. Logist. Manag., 401, pp. 103-123, (2010); Fichter K., E-Commerce: sorting out the environmental consequences, J. Ind. Ecol., 6, pp. 25-41, (2002); Gay R., Davis R., Phillips D.T., Sui D.Z., Modelling paradigm for the environmental impacts of the digital economy, J. Organ. Comput. Electron. Commer., 15, 1, pp. 61-82, (2005); Hendrickson C.T., Lave L.B., Matthews H.S., Environmental Life Cycle Assessment of Goods and Services: an Input-output Approach, (2006); Jespersen P.H., The transport contents of products, World Transp. Policy Pract., 10, 3, pp. 28-35, (2004); Kamarainen V., Saranen J., Holmstrom J., The reception box impact on home delivery efficiency in the e-grocery business, Int. J. Phys. Distrib. Logist. Manag., 31, 6, pp. 414-426, (2001); Koglin T., Vélomobility and the politics of transport planning, GeoJournal, 80, 4, pp. 569-586, (2015); Klein L.R., Evaluating the potential of interactive media through a new lens: search versus experience goods, J. Bus. Res., 41, 3, pp. 195-203, (1998); Lund University, LUBsearch and Electronic Resources, Content, (2015); Mangiaracina R., Marchet G., Perotti S., Tumino A., A review of the environmental implications of B2C e-commerce: a logistics perspective, Int. J. Phys. Distrib. Logist. Manag., 45, 6, pp. 565-591, (2015); Matthews H.S., Hendrickson C., Soh D., The net effect: environmental implications of e-commerce and logistics, Proceedings of the 2001 IIIEE International Symposium on Electronics and the Environment, Denver, (2001); Matthews H.S., Hendrickson C.T., Soh D.L., Environmental and economic effects of e-commerce: a case study of book publishing and retail logistics, Transp. Res. Rec. J. Transp. Res. Board, 1763, 2, pp. 6-12, (2001); Matthews H.S., Williams E., Tagami T., Hendrickson C.T., Energy implications of online book retailing in the United States and Japan, Environ. Impact Assess. Rev., 22, pp. 493-507, (2002); McLeod F., Cherret T., Song L., Transport impacts of local collection/delivery points, Int. J. Logist. Res. Appl., 9, 3, pp. 307-317, (2006); Mokhtarian P.L., A conceptual analysis of the transportation impacts of B2C e-commerce, Transportation, 3, 3, pp. 257-284, (2004); Molina-Besch K., Palsson H., Packaging for eco-efficient supply chains: why logistics should get involved in the packaging development process chapter 6, Sustainable Logistics – Transport and Sustainability, pp. 137-163, (2014); Palsson H., Finnsgard C., Wanstrom C., Selection of packaging systems in supply chains from a sustainability perspective: the case of Volvo, Packag. Technol. Sci., 26, 5, pp. 289-310, (2013); PRISMA, Preferred Reporting Items for Systematic Reviews and Meta-analyses; Prologis, Inside the global supply chain: E-commerce and a new demand model for logistics real estate, E-commerce and Logistics Real Estate, pp. 1-7, (2014); Punakivi M., Saranen J., Identifying the success factors in e-grocery home delivery, Int. J. Retail Distrib. Manag., 29, 4, pp. 156-163, (2001); Punakivi M., Yrjola H., Holmstrom J., Solving the last mile issue: reception box or delivery book?, Int. J. Phys. Distrib. Logist. Manag., 31, 6, pp. 427-439, (2001); Reijnders L., Hoogeveen M.J., Energy effects associated with e-commerce: a case study concerning online sales of personal computers in The Netherlands, J. Environ. Manag., 62, 3, pp. 271-282, (2001); Rizet C., Cornelis E., Browne M., Leonardi J., GHG emissions of supply chains from different retail systems in Europe, Proced. Soc. Behav. Sci., 2, 3, pp. 6154-6164, (2010); Rotem-Mindali O., E-tail versus retail: the effects on shopping related travel empirical evidence from Israel, Transp. Policy, 17, 5, pp. 312-322, (2010); Rotem-Mindali O., Salomon I., The impacts of e-retail on the choice of shopping trips and delivery: some preliminary findings, Transp. Res. Part A, 41, 2, pp. 176-189, (2007); Rotem-Mindali O., Weltevreden J.W.J., Transport effects of e-commerce: what can be learned after years of research?, Transportation, 40, pp. 867-885, (2013); Schwanen T., Dijst M., Kwan M.-P., Introduction —the internet, changing mobilities, and urban dynamics, Urban Geogr., 27, 7, pp. 585-589, (2006); Seuring S., Muller M., Westhaus M., Morana R., Conducting a literature review: the example of sustainability in supply chains, Research Methodologies in Supply Chain Management, pp. 91-106, (2005); Siikavirta H., Punakivi M., Karkkainen M., Linnanen L., Effects of e-commerce on greenhouse gas emission: a case study of grocery home delivery in Finland, J. Ind. Ecol., 6, 2, pp. 83-97, (2003); Sivaraman D., Pacca S., Mueller K., Lin J., Comparative energy, environmental, and economic analysis of traditional and e-tail DVD rental networks, J. Ind. Ecol., 11, pp. 77-91, (2007); Tehrani S.M., Karbassi A.R., Ghoddosi J., Monavvari S.M., Mirbagheri S.A., Prediction of energy consumption and urban air pollution reduction in e-shopping adoption, J. Food, Agric. Environ., 7, 4, pp. 898-903, (2009); Tonn B.E., Hemrick A., Impacts of the use of e-mail and the Internet on personal trip-making behaviour, Soc. Sci. Comput. Rev., 22, 2, pp. 270-280, (2004); van Loon P., Deketele L., Dewaele J., McKinnon A., Rutherford C., A comparative analysis of carbon emissions from online retailing of fast moving consumer goods, J. Clean. Prod., 106, pp. 478-486, (2014); Velasquez M., Ahmad A.-R., Bliemel M., Imam M., Online vs. offline movie rental: a comparative study of carbon footprints, Glob. Bus. Manag. Res. Int. J., 2, 1, pp. 1-12, (2010); Weber C., Hendrickson C., Jaramillo P., Matthews S., Nagengast A., Nealer R., Life cycle comparison of traditional retail and e-commerce logistics for electronic products: A case study of buy.com, (2008); Weber C.L., Koomey J.G., Matthews H.S., The energy and climate change implications of different music delivery methods, J. Ind. Ecol., 14, 5, pp. 754-769, (2010); Weltevreden J.W.J., Rotem-Mindali O., Mobility effects of B2C and C2C e-commerce in The Netherlands: a quantitative assessment, J. Transp. Geogr., 17, 2, pp. 83-92, (2009); Wiese A., Toporowsky W., Zielke S., Transport-related CO<sub>2</sub> effects of online and brick-and-mortar shopping: a comparison and sensitivity analysis of clothing retailing, Transp. Res. Part D, 17, 6, pp. 473-477, (2012); Williams E., Tagami T., Energy use in sales and distribution via e-commerce and conventional retail a case study of the Japanese book sector, J. Ind. Ecol., 6, 2, pp. 99-114, (2003); Williams H., Wikstrom F., Environmental impact of packaging and food losses in a life cycle perspective: a comparative analysis of five food items, J. Clean. Prod., 19, pp. 43-48, (2010); Winslott Hiselius L., Smidfelt Rosqvist L., Adell E., Travel behaviour of online shoppers in Sweden, J. Transp. Telecommun., 16, 1, pp. 21-30, (2015)","H. Pålsson; Division of Packaging Logistics, Department of Design Sciences, Lund University, Lund, Sweden; email: henrik.palsson@plog.lth.se",null,"Elsevier Ltd",{"$nulls":5},9596526.0,null,"JCROE",null,"English","J. Clean. Prod.","Article","Final",null,"Scopus","2-s2.0-85027455623"]
["Li H.; Miao X.","Li, Haiyan (57194578397); Miao, Xiaoming (57194576178)","57194578397; 57194576178","Research on the status quo and operation model of logistics of crossborder e-commerce in China",2017.0,"Agro Food Industry Hi-Tech",28.0,3.0,null,2845.0,2849.0,4.0,5.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85020920753&partnerID=40&md5=dfe11a4e57eef6fa7f3d0b74c0b45426","School of Management, Northwestern Polytechnical University, Xi'an, Shaanxi, China","Li H., School of Management, Northwestern Polytechnical University, Xi'an, Shaanxi, China; Miao X., School of Management, Northwestern Polytechnical University, Xi'an, Shaanxi, China","The development of cross-border e-commerce in China is very fast, and consumers have a higher level of requirements for cross-border e-commerce logistics and after-sales service. The development of crossborder e-commerce logistics in China does not match with the development of cross-border e-commerce, which specific performs as: The logistics infrastructure is not perfect, the national trade system is lagging behind, cross-border logistics enterprises are not in high degree of specialization, and the cross-border logistics international talents are in shortage, etc. At present, China's e-commerce cross-border logistics main modes are: international postal packet, international express, overseas warehouse, cross-border logistics, third party logistics, bonded zone and free trade zone, etc. In the future, the development of cross-border e-commerce logistics needs to integrate the advantages of various enterprises in the cross-border e-commerce supply chain. Cross border e-commerce logistics hub park mode and bonded zone and free trade zone logistics integrated service model should be adopted to promote cross-border e-commerce logistics mode upgrade, so as to establish a professional, large-scale, functional cross-border e-commerce logistics service system.","Cross border e-commerce logistics; International logistics; Logistics model; Logistics specialization","Commerce; Electronic commerce; International trade; Supply chains; After-sales services; Cross-border; International express; Logistics enterprise; Logistics infrastructure; Logistics model; Logistics services; Third party logistics; Logistics",{"$nulls":6},"Hameri A.P., Hintsa J., Assessing the drivers of change for crossborder supply chains, International Journal of Physical Distribution & Logistics Management, 39, 9, pp. 741-761, (2009); Gomez-Herrera E., Martens B., Turlea G., The drivers and impediments for cross-border e-commerce in the EU, Information Economics and Policy, 28, pp. 83-96, (2014); Gesner G.H., Cross-border E-commerce and logistics mode innovation, Research in Transportation Business & Management, 12, 3, pp. 21-35, (2015); Saen R.F., A new model for selecting third-party reverse logistics providers in the presence of multiple dual-role factors, The International Journal of Advanced Manufacturing Technology, 46, 1, (2016); Govindan K., Palaniappan M., Zhu Q., Et al., Analysis of third party reverse logistics provider using interpretive structural modeling, International Journal of Production Economics, 140, (2012); Creazza A., Dallari F., Rossi T., An integrated model for designing and optimising an international logistics network, International Journal of Production Research, 50, (2012); Mishra N., Kumar V., Chan F.T.S., A multi-agent architecture for reverse logistics in a green supply chain, International Journal of Production Research, 50, (2012); Gunasekaran A., Choy K.-L., Industrial logistics systems: Theory and applications, International Journal of Production Research, 50, (2012); Piplani R., Saraswat A., Robust optimisation approach to the design of service networks for reverse logistics, International Journal of Production Research, 50, (2012); Shaik M.N., Abdul-Kader W., Transportation in reverse logistics enterprise: A comprehensive performance measurement methodology, Production Planning & Control, 24, (2013)",null,null,"TeknoScienze",{"$nulls":5},1.7226996E7,null,null,null,"English","Agro Food Ind. Hi-Tech","Article","Final",null,"Scopus","2-s2.0-85020920753"]
["Nuin J.C.","Nuin, Javier Cuesta (57194540059)",5.7194540059E10,"Logistics management at Correos; [La gestión logística en Correos]",2017.0,"Revista de Obras Publicas",164.0,3585.0,null,38.0,47.0,9.0,0.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85020694757&partnerID=40&md5=e910cec9b8738a2c67d2ccfa8325bf39","Correos y Telégrafos, S.A. S.M.E., Spain","Nuin J.C., Correos y Telégrafos, S.A. S.M.E., Spain","Logistics at Correos, the Spanish national postal service, covers all operations from the time the sender enters our network to post a letter or package right up to the time of its delivery to the end customer. The four main sequential stages-collection, transport, sorting and distribution- are essentially characterised by a high level of automation in the classification of deliveries and the integration of IT systems to allow delivery tracking and due compliance with requisite quality standards. The entire system is based on a highly localised network, providing total national coverage for both collection and distribution, along with the incorporation of the latest technology and the professionalism of the service&#39;s nigh-on 50,000 employees. The present and future of logistics at Correos requires the development of innovative solutions adapted to the modern-day environment and one marked by the growth in parcel shipment services derived from e-commerce.",null,"Civil engineering; Public works; End customers; Entire system; Innovative solutions; IT system; Latest technology; Level of automations; Logistics management; Quality standard; Regulatory compliance",{"$nulls":9},"Colegio de Ingenieros de Caminos Canales y Puertos",{"$nulls":5},348619.0,null,"RVOPA",null,"English","Rev Obras Publicas","Article","Final",null,"Scopus","2-s2.0-85020694757"]
["Rishi B.; Kapoor A.; Bhatia S.","Rishi, Bikramjit (24345043700); Kapoor, Ashish (57215495300); Bhatia, Sameer (57215492744)","24345043700; 57215495300; 57215492744","AaramShop.com reinventing the e-grocery wheel in India",2016.0,"Emerald Emerging Markets Case Studies",6.0,2.0,null,1.0,28.0,27.0,2.0,"10.1108/EEMCS-06-2015-0138","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85080977396&doi=10.1108%2fEEMCS-06-2015-0138&partnerID=40&md5=a5e2ade80a4ab7f5bb00abc543174616","Department of Marketing, Institute of Management Technology, Ghaziabad, India; Mahindra Susten Private Limited, Mumbai, India; Tolexo Online Pvt. Ltd, Noida, India","Rishi B., Department of Marketing, Institute of Management Technology, Ghaziabad, India; Kapoor A., Mahindra Susten Private Limited, Mumbai, India; Bhatia S., Tolexo Online Pvt. Ltd, Noida, India","Subject area: Marketing. Study level/applicability: The courses in which this case can be used include e-business, e-commerce, digital marketing, retailing and marketing strategy. This case can be used to teach MBA students. This case is also having the equal relevance for the executive programmes. Case overview: AaramShop is digitizing the Grocery General Trade ecosystem. There are of millions of neighbourhood kirana stores spread across all the cities of India. AaramShop is bringing these neighbourhood kirana stores online, and making them not only e-commerce-ready but also capable of using technology to take their stores to the next level in terms of service and delivery. The case lists out the issues and challenges faced by AaramShop. Expected learning outcomes: This case challenges the participants to understand the new business model in the e-commerce space. The participants can look at the different angles of the business model proposition, namely, how AaramShop approach delivers on the retailer proposition, consumer proposition and the brands proposition. The participants can also be sensitized about the obstacles in making the business model more successful. These obstacles can be posed by the retailers, consumers or brands. The case will lead to a discussion about the logistics model opportunity available to Aaramshop.com. Supplementary materials: Teaching notes are available for educators only. Please contact your library to gain login details or email support@emeraldinsight.com to request teaching notes. Subject code: CSS 8: Marketing. © 2016, Emerald Group Publishing Limited.","Consumer behaviour; Digital marketing; E-business; E-commerce; Logistics",{"$nulls":5},"IMT; Institute of Management Technology"," Authors are thankful to Institute of Management Technology (IMT) Ghaziabad, India for funding this case study.  ","Darley W.K., Blankson C., Luethge D.J., Toward an integrated framework for online consumer behavior and decision making process: a review, Psychology and Marketing, 27, 2, pp. 94-116, (2010)","B. Rishi; Department of Marketing, Institute of Management Technology, Ghaziabad, India; email: brishi@imt.edu",null,"Emerald Group Holdings Ltd.",{"$nulls":5},2.0450621E7,null,null,null,"English","Emerald Emerg. Mark. Case Stud.","Article","Final",null,"Scopus","2-s2.0-85080977396"]
["Sundmaeker H.","Sundmaeker, Harald (16176483600)",1.61764836E10,"Accelerating system development for the food chain: A portfolio of over 30 projects, aiming at impact and growth",2016.0,"International Journal on Food System Dynamics",7.0,4.0,null,371.0,381.0,10.0,5.0,"10.18461/ijfsd.v7i4.747","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85006372702&doi=10.18461%2fijfsd.v7i4.747&partnerID=40&md5=e6967c39f28c718b5c6c8e0db2b84e10","ATB Institute for Applied Systems Technology Bremen GmbH, Germany","Sundmaeker H., ATB Institute for Applied Systems Technology Bremen GmbH, Germany","Supply of fresh food is of vital importance to feed Europe in a healthy way, while Europe has also an important role in feeding the world. Food products and other perishables such as flowers impose very challenging demands on the management of its supply chains. Food networks are struggling with an integrated usage of information and communication technology (ICT) that enables the heterogeneous stakeholders in the food chain to exchange information in real-time and control workflows based on requirements with respect to quality, costs and schedule. Innovative ICT systems that are addressing such challenges are currently being developed by a large European initiative, called FIWARE. Within this paper, we will discuss a portfolio of 31 projects that are realising solutions for the food chain in close collaboration with supporting business partners. Diverse food related topics are addressed, such as logistics, transport, planning and control, tracking and tracing, information management as well as new ways to realise e-commerce within the chain as well as for consumers. The FIWARE initiative is accelerating startups and supporting SME type technology developers that are realising solutions for real world business cases, which are serving as reference customers and test cases to assure an end-user acceptance and valid business models. This paper discusses the main food chain related topics and innovation potentials that are addressed as well as outlines the related methodological and technological approaches that are used to facilitate the realisation of impact and growth for commercial exploitation.","Acceleration; App development; Business models; FIWARE; Food chain; Future internet; Minimum viable product",{"$nulls":7},"Getting The MVP Right, (2013); The Global Startup Ecosystem Ranking 2015, (2015); FIspace Technical Architecture and Specification, (2013); Progress report on trial experimentation and App development and updated plan for Phase 3 rollout, (2014); Initial Applications Third Release, (2015); Osterwalder A., Pigneur Y., Smith A., (2010); Ries E., The Lean Startup: How Today's Entrepreneurs Use Continuous Innovation to Create Radically Successful Businesses, (2011); Sundmaeker H., Guillemin P., Friess P., Woelffle S., Vision and Challenges for Realising the Internet of Things, (2010); Sundmaeker H., Verdouw C., Dynamic Business Collaboration in Supply Chains with Future Internet technologies: Acceleration of SME-driven App Development, International Conference on IoT as a Service, (2014); Sundmaeker H., Einramhof P., Systematic Heterogeneity: How to combine Smartphone related Apps with FIspace, Journal on Food System Dynamics, 6, 2, pp. 117-128, (2015); Verdouw C.N., Sundmaeker H., Meyer F., Wolfert J., Verhoosel J., Smart Agri-Food Logistics: Requirements for the Future Internet, Dynamics in Logistics, pp. 247-257, (2013); Verdouw C., Vucic N., Sundmaeker H., Beulens A., Future Internet as a Driver for Virtualization, Connectivity and Intelligence of Agri-Food Supply Chain Networks, International Journal On Food System Dynamics, 4, 4, (2014)","H. Sundmaeker; ATB Institute for Applied Systems Technology Bremen GmbH, Germany; email: Sundmaeker@atb-bremen.de",null,"CentMa GmbH",{"$nulls":5},1.8696945E7,null,null,null,"English","Intl. J. Food Syst.","Article","Final",null,"Scopus","2-s2.0-85006372702"]
["Wright E.W.; Marvel J.; Wright M.K.","Wright, Edward W. (7401796418); Marvel, Jon (7007063719); Wright, Matthew K. (57200534883)","7401796418; 7007063719; 57200534883","Innovation in Hospital Revenues: Developing Retail Sales Channels",2018.0,"Health Care Manager",37.0,1.0,null,47.0,54.0,7.0,0.0,"10.1097/HCM.0000000000000202","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85041508537&doi=10.1097%2fHCM.0000000000000202&partnerID=40&md5=b05af55805339bb574b2f00263a2d1f1","School of Economics, Management, and Project Management, Western Carolina University, 315C Forsyth Bldg, Cullowhee, 28723, NC, United States; Retail Initiatives and ECommerce, Mission Healthcare, Asheville, NC, United States","Wright E.W., School of Economics, Management, and Project Management, Western Carolina University, 315C Forsyth Bldg, Cullowhee, 28723, NC, United States; Marvel J., School of Economics, Management, and Project Management, Western Carolina University, 315C Forsyth Bldg, Cullowhee, 28723, NC, United States; Wright M.K., Retail Initiatives and ECommerce, Mission Healthcare, Asheville, NC, United States","Hospitals are facing increasing cost pressures due to cutbacks by Medicare, Medicaid, and managed-care organizations. There are also rising concerns that public policy may exacerbate the problem. In lieu of these concerns, nascent innovative ways of generating increased revenues are beginning to appear. In particular, a few hospitals have adopted retail sales practices to generate significant nonmedical services revenues. The hospital retail sales opportunity has been compared with that of the airport industry where nearly 50% of revenues are generated by sales of retail products as opposed to aeronautical-related transactions. This initial investigation included a qualitative interview of a health care retail sales expert and a pilot survey of 100 hospital senior executives to gauge the current state of this phenomenon. The industry expert suggested that only 2% of US hospitals have pursued this initiative in a meaningful way. Of the 44 survey responses, only 9 institutions were engaged in e-commerce or retail sales activities. Questions remain as to why this opportunity remains unrealized, and additional research is proposed.","hospital administration; hospital revenues; retail sales channels","Commerce; Costs and Cost Analysis; Delivery of Health Care; Financial Management; Hospitals; Humans; Organizational Innovation; Surveys and Questionnaires; United States; commercial phenomena; cost; economics; financial management; health care delivery; hospital; human; organization; questionnaire; trends; United States",{"$nulls":6},"Curan J., Hospitals in the US, IBIS World Industry Report 62211; Kaufman B.G., Thomas S.R., Randolph R.K., Et al., The rising rate of rural hospital closures, J Rural Health., 32, 1, pp. 35-43, (2016); Totten M.K., Orlikoff J.E., Trustee workbook 3. Maximizing hospital revenue through retail, Trustee., 57, 7, pp. 15-18, (2004); Johnson D., Hospitals reach out to employers for new revenues, Health Care Strateg Manage., 23, 3, (2005); Thompson-Banko M., Strategic Healthcare Retail, (2009); Helland M., Simply Retail Says Retail Isn't Simple, (1998); Belardini A., Growing retail at airports, J Airport Manage, 7, 3, pp. 222-230; Fuerst F., Gross S., Working Paper-The Commercial Performance of Global Airports, (2014); Appold S.J., Kasarda J.D., The airport city phenomenon: Evidence from large US airports, Urban Studies., 6, pp. 1239-1259, (2013)","E.W. Wright; School of Economics, Management, and Project Management, Western Carolina University, 315C Forsyth Bldg, Cullowhee, 28723, United States; email: ewwright@wcu.edu",null,"Lippincott Williams and Wilkins",{"$nulls":5},1.5255794E7,null,null,2.9266085E7,"English","Health Care Manager","Article","Final",null,"Scopus","2-s2.0-85041508537"]
["Liu G.; Shen H.; Chandler H.; Li J.","Liu, Guoxin (56136737600); Shen, Haiying (7404522813); Chandler, Harrison (44661228400); Li, Jin (57216662271)","56136737600; 7404522813; 44661228400; 57216662271","Measuring and Evaluating Live Content Consistency in a Large-Scale CDN",2016.0,"IEEE Transactions on Parallel and Distributed Systems",27.0,7.0,7270312.0,2074.0,2090.0,16.0,7.0,"10.1109/TPDS.2015.2479222","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84976407584&doi=10.1109%2fTPDS.2015.2479222&partnerID=40&md5=a25b79f3557779277dd4fdcb58ae5524","Department of Electrical and Computer Engineering, Clemson University, Clemson, 29634, SC, United States; Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, 48109, MI, United States; Microsoft Research, Redmond, 98052, WA, United States","Liu G., Department of Electrical and Computer Engineering, Clemson University, Clemson, 29634, SC, United States; Shen H., Department of Electrical and Computer Engineering, Clemson University, Clemson, 29634, SC, United States; Chandler H., Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, 48109, MI, United States; Li J., Microsoft Research, Redmond, 98052, WA, United States","Content Delivery Networks (CDNs) play a central role in today's Internet infrastructure and have seen a sharp increase in scale. More and more internet sites are armed with live contents, such as live sports game statistics, e-commerce, and online auctions, and they rely on CDNs to deliver such contents freshly at scale. However, the problem of maintaining consistency for live (dynamic) contents while achieving high scalability is non-Trivial in CDNs. The large number of widely scattered replicas guarantees the QoS of end-users while substantially increasing the complexity of consistency maintenance under frequent updates. Current consistency maintenance infrastructures and methods cannot simultaneously satisfy both scalability and consistency. In this paper, we first analyze our crawled trace data of cached sports game content on thousands of content servers of a major CDN. We analyze the content consistency from different perspectives, from which we break down the reasons for inconsistency among content servers. We verify that the CDN uses unicast instead of multicast trees as the update infrastructure, which may not scale effectively. Then, we further evaluate the performance in consistency, scalability and overhead for different infrastructures with different update methods. We itemize the advantages and disadvantages of different methods and infrastructures in different scenarios through the evaluation. Based on this evaluation, we propose our hybrid and self-Adaptive update method to reduce network load and improve scalability under the conditions recorded in the trace and prove its effectiveness through trace-driven experiments. We aim to give guidance for appropriate selections of consistency maintenance infrastructures and methods for a CDN, and for choosing a CDN service with different considerations. © 1990-2012 IEEE.","Consistency Maintenance; Content Delivery Network; Scalability","Commerce; Complex networks; Electronic commerce; Internet; Maintenance; Sports; Adaptive update; Consistency maintenance; Content consistency; Content delivery network; Content servers; High scalabilities; Internet infrastructure; Trace driven experiments; Scalability",{"$nulls":6},"Rayburn D., CDN market getting crowded: Now tracking 28 providers in the industry, Bus. Online Video Blog, (2007); Akamai, (2015); Zhao M., Aditya P., Lin Y., Harberlen A., Druschel P., Wishon W., Maggs B., A first look at a commercial hybrid content delivery system, (2011); Huang C., Wang A., Li J., Ross K.W., Measuring and evaluating large-scale CDNs, Proc. 8th ACM SIGCOMM Conf. Int. Meas, pp. 15-59, (2008); Pallis G., Vakali A., Insight and perspectives for content delivery networks, Commun ACM, 49, pp. 101-106, (2006); Fei Z., A novel approach to managing consistency in content distribution networks, Proc. Workshop Web Caching Content Distrib, pp. 1-9, (2001); Cao P., Liu C., Maintaining strong cache consistency in the world-wide web, Proc. 17th Int. Conf. Distrib. Comput. Syst, pp. 12-21, (1997); Tang X., Xu J., Lee W., Analysis of TTL-based consistency in unstructured peer-To-peer networks, IEEE Trans. Parallel Distrib. Syst, 19, 12, pp. 1683-1694, (2008); Wang Z., Das S.K., Che H., Kumar M., A scalable asynchronous cache consistency scheme (SACCS) for mobile environments, IEEE Trans. Parallel Distrib. Syst, 15, 11, pp. 983-995, (2004); Lan J., Liu X., Shenoy P., Ramamritham K., Consistency maintenance in peer-To-peer file sharing networks, Proc IEEE Workshop Int. Appl, pp. 90-94, (2003); Datta A., Hauswirth M., Aberer K., Updates in highly unreliable, replicated peer-To-peer systems, Proc. 23rd Int. Conf. Distrib. Comput. Syst, pp. 76-85, (2003); Clarke I., Sandberg O., Wiley B., Hong T.W., Freenet:Adistributed anonymous information storage and retrieval system, Proc. Int. Workshop Des. Issues Anonymity Unobservability, pp. 46-66, (2001); Ninan A., KulkarniI P., Shenoy P., Ramamritham K., Tewari R., Cooperative leases: Scalable consistency maintenance in content distribution networks, Proc. 11th Int. Conf. World Wide Web, pp. 1-12, (2002); Roussopoulos M., Baker M., CUP: Controlled update propagation in peer to peer networks, Proc. USENIX Annu. Techn. Conf., San Antonio, TX, USA, pp. 167-180, (2003); Yin L., Cao G., Dynamic-Tree based update propagation in peer-To-peer networks, Proc. 21st Int. Conf. Data Eng, pp. 258-259, (2005); Chen X., Ren S., Wang H., Zhang X., SCOPE: Scalable consistency maintenance in structured P2P systems, Proc IEEE INFOCOM, pp. 1502-1513, (2005); Li Z., Xie G., Li Z., Locality-Aware consistency maintenance for heterogeneous P2P systems, Proc IEEE Int. Parallel Distrib. Process. Symp, pp. 1-10, (2007); Shen H., GeWave: Geographically-Aware wave for file consistency maintenance in P2P systems, Proc. 37th Int. Conf. Parallel Process, pp. 660-667, (2008); Tang X., Chi H., Chanson S.T., Optimal replica placement under TTL-based consistency, IEEE Trans. Parallel Distrib. Syst, 18, 3, pp. 351-363, (2007); Feng Z., Xu M., Wang Y., Li Q., An architecture for cache consistency support in information centric networking, Proc. Global Commun. Conf, pp. 2126-2131, (2013); Cate V., Alex: A global file system, Proc. USENIX File Syst. Workshop, pp. 1-12, (1992); Shen H., IRM: Integrated file replication and consistency maintenance in P2P systems, IEEE Trans. Parallel Distrib. Syst, 21, 1, pp. 100-113, (2010); Shen H., Liu G., A geographically aware poll-based distributed file consistency maintenance method for P2P systems, IEEE Trans. Parallel Distrib. Syst, 24, 11, pp. 2148-2159, (2013); Chen C., Matsumoto S., Perrig A., ECO-DNS: Expected consistency optimization for DNS, Proc IEEE 35th Int. Conf. Distrib. Comput. Syst, pp. 256-267, (2015); Diegues N., Romano P., STI-BT: A scalable transactional index, Proc IEEE 34th Int. Conf. Distrib. Comput. Syst, pp. 104-113, (2014); Shang P., Sehrish S., Wang J., TRAID: Exploiting temporal redundancy and spatial redundancy to boost transaction processing systems performance, IEEE Trans. Comput, 61, 4, pp. 517-529, (2012); Nygren E., Sitaraman R.K., Sun J., The Akamai network: A platform for high-performance internet applications, ACM SIGOPS Opearting Syst. Rev, 44, pp. 2-19, (2010); Thomson A., Abadi D.J., CalvinFS: Consistent WAN replication and scalable metadata management for distributed file systems, Proc. 13th USENIX Conf. File Storage Technol, pp. 1-14, (2015); Lloyd W., Freedman M.J., Kaminsky M., Andersen D.G., Stronger semantics for low-latency geo-replicated storage, Proc. 10th USENIX Conf. Netw. Syst. Des. Implementation, pp. 313-328, (2013); Abu-Libdeh H., Renesse R., Vigfusson Y., Leveraging sharding in the design of scalable replication protocols, Proc. 4th Annu. Symp. Cloud Comput, pp. 177-192, (2013); Tang X., Zhou S., Update scheduling for improving consistency in distributed virtual environments, IEEE Trans. Parallel Distrib. Syst, 21, 6, pp. 765-777, (2010); Peluso S., Ruivo P., Romano P., Quaglia F., Rodrigues L., When scalability meets consistency: Genuine multiversion update-serializable partial data replication, Proc IEEE 32nd Int. Conf. Distrib. Comput. Syst, pp. 455-465, (2012); Xiong J., Hu Y., Li G., Tang R., Fan Z., Metadata distribution and consistency techniques for large-scale cluster file systems, IEEE Trans. Parallel Distrib. Syst, 22, 5, pp. 803-816, (2011); Distler T., Kapitza R., Optimal algorithms and approximation algorithms for replica placement with distance constraints in tree networks, Proc. EuroSys, pp. 1022-1033, (2011); Dimitropoulos X.A., Hurley P., Kind A., Stoecklin M.Ph., On the 95-percentile billing method, Proc. 10th Int. Conf. Passive Active Netw. Meas, pp. 207-216, (2009); Best Practices When Developing with Akamai, (2011); Iplocation, (2015); Valancius V., Lumezanu C., Feamster N., Johari R., Vazirani V.V., How many tiers?: Pricing in the internet transit market, Proc. ACM SIGCOMM Conf, pp. 194-205, (2011); Shen H., Liu G., A lightweight and cooperative multifactor considered file replication method in structured P2P systems, IEEE Trans. Comput, 62, 11, pp. 2115-2130, (2013); PlanetLab, (2007); Wittie M.P., Pejovic V., Deek L.B., Almeroth K.C., Zhao Y.B., Exploiting locality of interest in online social networks, Proc ACM 6th Int. Conf, pp. 289-300, (2010); Bronson N., Amsden Z., Cabrera G., Chakka P., Dimov P., Ding H., Ferris J., Giardullo A., Kulkarni S., Li H., Marchukov M., Petrov D., Puzar L., Song Y.J., Venkataramani V., TAO: Facebooks distributed data store for the social graph, Proc. USENIX Conf. Annu. Techn. Conf, pp. 49-60, (2013); Beaver D., Kumar S., Li H.C., Sobel J., Vajgel P., Finding a needle in haystack: Facebooks photo storage, Proc. 9th USENIX Conf. Operating Syst. Des. Implementation, pp. 47-60, (2010); Xu Z., Mahalingam M., Karlsson M., Turning heterogeneity into an advantage in overlay routing, Proc IEEE INFOCOM, pp. 1499-1509, (2003)",null,null,"IEEE Computer Society",{"$nulls":5},1.0459219E7,null,"ITDSE",null,"English","IEEE Trans Parallel Distrib Syst","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-84976407584"]
["Chou Y.-C.; Chuang H.H.-C.; Shao B.B.M.","Chou, Yen-Chun (36006181600); Chuang, Howard Hao-Chun (55751428600); Shao, Benjamin B.M. (7103207904)","36006181600; 55751428600; 7103207904","The impact of e-retail characteristics on initiating mobile retail services: A modular innovation perspective",2016.0,"Information and Management",53.0,4.0,null,481.0,492.0,11.0,41.0,"10.1016/j.im.2015.11.003","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84954270910&doi=10.1016%2fj.im.2015.11.003&partnerID=40&md5=707d911153f4acd79e8c60273de06560","Department of Management Information Systems, College of Commerce, National Chengchi University, Taipei, 11605, Taiwan; Department of Information Systems, W. P. Carey School of Business, Arizona State University, Tempe, 85287-4606, AZ, United States","Chou Y.-C., Department of Management Information Systems, College of Commerce, National Chengchi University, Taipei, 11605, Taiwan; Chuang H.H.-C., Department of Management Information Systems, College of Commerce, National Chengchi University, Taipei, 11605, Taiwan; Shao B.B.M., Department of Information Systems, W. P. Carey School of Business, Arizona State University, Tempe, 85287-4606, AZ, United States","The rise and challenges of m-commerce have led to an urgent need to examine how firms adopt the emerging sales channel. Early studies mainly discussed the differences between e-commerce and m-commerce. Our study shows the modular innovation from e-retailing to m-retailing, which changes the core component of service delivery but keeps the operations intact, provides more opportunities for well-entrenched firms. Using a dataset of e-retailers, we find e-retail characteristics have an impact on firm's migration to the mobile domain. Firms with online service competencies, economies of scale, and physical outlets are more inclined to exploit opportunities provided by mobile technologies. © 2015 Elsevier B.V. All rights reserved.","e-Commerce; m-Commerce; Mobile retail services; Modular innovation; Multichannel retailing","Commerce; Costs; Economics; Electronic commerce; Sales; Core components; Economies of scale; M-commerce; Mobile Technology; Modular innovation; Multichannel retailing; Retail services; Service delivery; Mobile commerce",{"$nulls":4},"State University of New York; M.S.I. Foundation; National Chiao Tung University","    360° spin Microsites Widgets Affiliate program Mouseover Wish list Auction Online circular Zoom Blogs Online gift certificates Account status/History Catalog quick order Outlet center Buy online/Pick up in store Color switching Preorders Click to call Coupons/Rebates Product comparisons Currency converter Customer reviews Product customization Estimated shipping date Daily/Seasonal specials Product ratings Express checkout Dynamic imaging Product recommendations Free return shipping E-mail a friend Product wikis Live chat/E-mail Enlarged product view Registry Order confirmation Frequent buyer program RSS feed Order status Frequently asked questions Site personalization Prepaid labels Gadgets Social networking Rain checks Guided navigation Store locator Real-time inventory check Interactive catalog Syndicated content Ship to multiple addresses Interactive kiosks Top sellers Shipping cost calculator Mapping Videocasts Shipment tracking Mash-ups What's new Toll-free number  Yen-Chun Chou is an assistant professor of management information systems in the College of Commerce at National Chengchi University in Taipei, Taiwan. She received her B.A. in management information systems from National Chengchi University, Taiwan, her M.S. in information systems management from Carnegie Mellon University, and Ph.D. from Arizona State University. Her current research interests are the business value of information technology, service science, and e-commerce adoption and performance. She studies related issues from both macro- and micro-perspectives. At the macro-level, she studies the economic impacts of IT production industries and the innovation role of IT usage. At the micro-level, she analyzes mobile commerce (m-commerce) as an emerging sales channel and assessing its in-channel and cross-channel influences.  Howard Hao-Chun Chuang is an assistant professor in the College of Commerce at National Chengchi University. He holds a Ph.D. in information and operations management from the Mays Business School at Texas A&M University. Dr. Chuang's research interests include retail service operations, Internet commerce, and supply chain management. His research articles have appeared in Journal of Operations Management , Production and Operations Management , Decision Sciences , Decision Support Systems , and several other journals. Prior to his academic career, he served as a supply corporal for a year in the Penghu Defense Command of the Taiwanese army.  Benjamin B.M. Shao is an associate professor in the W. P. Carey School of Business at Arizona State University. He received his B.S. and M.S. from National Chiao Tung University, Taiwan, and his Ph.D. from the State University of New York at Buffalo. His research interests include IT impacts, IT services and business analytics, software project management, IS security, and health-care IT. He has published more than 70 refereed papers in leading journals and conference proceedings across the disciplines of information systems, production and operations management, computer science, operations research, and health-care management. He has been serving on the editorial boards of six journals including Journal of the AIS , Decision Support Systems , Information & Management , and MIS Quarterly and European Journal of Information Systems special issues. At ASU, he was recognized for teaching excellence as the DISC Professor of the Year and was a finalist for the John W. Teets Outstanding Teaching Award. ","Afuah A.N., Bahram N., The hypercube of innovation, Res. Policy, 24, 1, pp. 51-76, (1995); Anckar B., D'Incau D., Value creation in mobile commerce: Findings from a consumer survey, J. Inf. Technol. Theory Appl., 4, 1, pp. 43-64, (2002); Andrasick C., Breaking out of the mobile commerce metaphor trap, E-commerce Times, (2011); Baird N., Kilcourse B., Supply Chain Execution 2014: Making Omni-channel Profitable, (2013); Baird N., Kilcourse B., Omni-channel 2014: Double Trouble, (2014); Balasubramanian S., Peterson R.A., Jarvenpaa S.L., Exploring the implications of m-Commerce for markets and marketing, J. Acad. Mark. Sci., 30, 4, pp. 348-361, (2002); Bang Y., Lee D., Han K., Hwang M., Ahn J., Channel capabilities, product characteristics, and the impacts of mobile channel introduction, JMIS, 30, 2, pp. 101-125, (2013); Bell D.R., Gallino S., Moreno A., How to win in an omnichannel world, MIT Sloan Manag. Rev., 50, 1, pp. 45-53, (2014); Berner R., J.C. Penny gets the net, Business Week, (2007); Berry L.L., Shankar V., Parish J.T., Cadwallader S., Dotzel T., Creating new markets through service innovation, MIT Sloan Manag. 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Res., 17, 2, pp. 162-179, (2006); Hulland J., Michael W.R., Kersi A.D., The impact of capabilities and prior investments on online channel commitment and performance, JMIS, 23, 4, pp. 109-142, (2007); Kim H.W., Chan H.C., Gupta S., Value-based adoption of mobile internet: An empirical investigation, Decis. Support Syst., 43, 1, pp. 111-126, (2007); Kini R.B., Bandyopadhyay S.K., Adoption and diffusion of m-commerce, Mobile Computing: Concepts, Methodologies, Tools and Applications, pp. 38-46, (2009); Kumar V., Venkatesan R., Who are the multichannel shoppers and how do they perform? Correlate of multichannel shopping behavior, J. Interact. Mark., 19, 2, pp. 44-62, (2005); Lee Y., Benbasat I., Interface design for mobile commerce, CACM, 46, 12, pp. 49-52, (2003); Lee S., Shin B., Lee H.G., Understanding post-adoption usage of mobile data services: The role of supplier-side variables, J. Assoc. Inf. Syst., 10, 12, pp. 860-888, (2009); Lin H.H., The effect of multi-channel service quality on mobile customer loyalty in an online-and-mobile retail context, Serv. Ind. J., 32, 11, pp. 1865-1882, (2012); Mallat N., Tuunainen V.K., Exploring merchant adoption of mobile payment systems: An empirical study, E-Serv. J., 6, 2, pp. 24-57, (2008); Min S., Wolfinbarger M., Market share, profit margin, and marketing efficiency of early movers, bricks and clicks, and specialists in e-commerce, J. Bus. Res., 58, 8, pp. 1030-1039, (2005); Minnick F., What App? Wine.com Focuses on Cross-platform Site, (2012); Mitchell V., Walsh G., Gender differences in German consumer decision-making styles, J. Consum. Behav., 3, 4, pp. 331-346, (2004); Morris M., Venkatesh V., Age differences in technology adoption decisions: Implications for a changing work force, Pers. Psychol., 53, 2, pp. 375-403, (2000); Motorola Solutions, How Brick-and-Mortar Retailers Can Win the Omnichannel Battle, (2012); Economy Still Impacting Shoppers but Glimmers of Hope Appear in First NRF Holiday, (2010); Picoto W.N., Belanger F., Palma-Dos-Reis A., An organizational perspective on m-business: Usage factors and value determination, Eur. J. Inf. Syst., 23, 5, pp. 571-592, (2014); Porter M., Strategy and the Internet, Harv. Bus. Rev., 79, 3, pp. 63-78, (2001); Rabe-Hesketh S., Skrondal A., Multilevel and Longitudinal Modeling Using Stata, (2008); Reportlinker, Global M-commerce Market 2015-2019, (2015); Rogers E.M., Diffusion of Innovations, (2003); Shankar V., Balasubramanian S., Mobile marketing: A synthesis and prognosis, J. Interact. Mark., 23, 2, pp. 118-129, (2009); Shankar V., Smith A., Rangaswamy A., Customer satisfaction and loyalty in online and offline environments, Int. J. Res. 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Manag., 23, 1, pp. 88-104, (2003); Wang S., Cheung W., E-Business adoption by travel agencies: Prime candidates for mobile e-Business, Int. J. Electron. Commer., 8, 3, pp. 43-63, (2004); Wei J., Ozok A., Development of a web-based mobile airline ticketing model with usability features, Ind. Manag. Data Syst., 105, 9, pp. 1261-1277, (2005); Winkler R., Google gives boosts to mobile-friendly sites, Wall Street J., (2015); Witt U., Economic growth: What happens on the demand side? Introduction, J. Evol. Econ., 11, 1, pp. 1-5, (2001); Wu J.H., Wang S.C., What drives mobile commerce? An empirical evaluation of the revised technology acceptance model, Inf. Manag., 42, 5, pp. 719-729, (2004); Xia Y., Zhang G.P., The impact of the online channel on retailers' performances: An empirical evaluation, Decis. Sci., 41, 3, pp. 517-546, (2010); Xu J., Forman C., Kim J.B., Van Ittersum K., News media channels: Complements or substitutes? Evidence from mobile phone usage, J. Mark., 78, pp. 97-112, (2014); Yun H., Lee C.C., Kim B.G., Kettinger W.J., What determines actual use of mobile web browsing services? A contextual study in Korea, Commun. Assoc. Inf. Syst., 28, 1, pp. 313-328, (2011); Zhang J.J., Yuan Y., Archer N., Driving forces for m-Commerce success, J. Internet Commer., 1, 3, pp. 81-105, (2002); Zhu K., The complementarity of information technology infrastructure and e-commerce capability: A resource-based assessment of their business value, JMIS, 21, 1, pp. 167-202, (2004); Zhu K., Kraemer K.L., E-Commerce metrics for net-enhanced organizations: Assessing the value of e-commerce to firm performance in the manufacturing sector, Inf. Syst. Res., 13, 3, pp. 275-295, (2002); Zhu K., Kraemer K.L., Post-adoption variations in usage and value of e-Business by organizations: Cross-country evidence from the retail industry, Inf. Syst. Res., 16, 1, pp. 61-84, (2005)","B.B.M. Shao; Department of Information Systems, W. P. Carey School of Business, Arizona State University, Tempe, 85287-4606, United States; email: ben.shao@asu.edu",null,"Elsevier B.V.",{"$nulls":5},3787206.0,null,"IMAND",null,"English","Inf Manage","Article","Final",null,"Scopus","2-s2.0-84954270910"]
["Yao J.","Yao, Jianming (55478489100)",5.54784891E10,"Optimisation of one-stop delivery scheduling in online shopping based on the physical Internet",2017.0,"International Journal of Production Research",55.0,2.0,null,358.0,376.0,18.0,26.0,"10.1080/00207543.2016.1176266","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84964503283&doi=10.1080%2f00207543.2016.1176266&partnerID=40&md5=a0522723cf7353c5a8624c837497ce1f","School of Business, Renmin University of China, Beijing, China","Yao J., School of Business, Renmin University of China, Beijing, China","The circulation of online shopping commodities generally involves many entities, such as online manufacturers, wholesalers, retailers and customers. Goods from manufacturers to consumers undergo several exchange stages involving different economic entities. The logistics cost increases in certain supply chain nodes and the risk of backlog or running out of stock is high because of the different income and risk expectations of entities, as well as the varying degrees of information sharing between them. Clearly, a one-stop delivery mode crossing numerous transaction links in online shopping can effectively solve these problems and save social resources. However, realising this one-stop mode requires a series of specific premises, appropriate software and hardware technology support. This study introduces the Physical Internet into the one-stop delivery mode as an important logical and technical support, analyses the operating mechanism of the Physical Internet and discusses the operating conditions of one-stop delivery. It analyses the optimisation contents and objectives of one-stop delivery scheduling to construct a multi-objective optimisation mathematical model and propose a solving algorithm. Finally, this study uses an application case to verify the feasibility and effectiveness of the optimisation mechanism and algorithm. © 2016 Informa UK Limited, trading as Taylor & Francis Group.","online shopping; operations management; optimisation; physical Internet; supply chain management","Electronic commerce; Internet; Manufacture; Multiobjective optimization; Scheduling; Supply chain management; Delivery scheduling; Information sharing; Online shopping; Operating condition; Operating mechanism; Operations management; Optimisations; Software and hardwares; Optimization",{"$nulls":6},"Alibaba in China, (2015); (2015); Archer N., Wang S., Kang C., Barriers to the Adoption of Online Supply Chain Solutions in Small and Medium Enterprises, Supply Chain Management: An International Journal, 13, 1, pp. 73-82, (2008); Bailey J.P., Rabinovich E., Internet Book Retailing and Supply Chain Management: An Analytical Study of Inventory Location Speculation and Postponement, Transportation Research Part E: Logistics and Transportation Review, 41, 3, pp. 159-177, (2005); 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Liu B., Zhang R., Xiao M., Joint Decision on Production and Pricing for Online Dual Channel Supply Chain System, Applied Mathematical Modelling, 34, 12, pp. 4208-4218, (2010); Liu K., Zhou Y., Zhang Z., Capacitated Location Model with Online Demand Pooling in a Multi-channel Supply Chain, European Journal of Operational Research, 207, 1, pp. 218-231, (2010); Montreuil B., Toward a Physical Internet: Meeting the Global Logistics Sustainability Grand Challenge, Logistics Research, 3, 2-3, pp. 71-87, (2011); Montreuil B., Meller R.D., Ballot E., Towards a Physical Internet: The Impact on Logistics Facilities and Material Handling Systems Design and Innovation, pp. 305-327, (2010); Pan S., Ballot E., Fontane F., The Reduction of Greenhouse Gas Emissions from Freight Transport by Pooling Supply Chains, International Journal of Production Economics, 143, 1, pp. 86-94, (2013); Pan S., Nigrelli M., Ballot E., Sarraj R., Yang Y., Perspectives of Inventory Control Models in the Physical Internet: A Simulation Study, Computers & Industrial Engineering, 84, pp. 122-132, (2015); Panicker V.V., Vanga R., Sridharan R., Ant Colony Optimisation Algorithm for Distribution-allocation Problem in a Two-stage Supply Chain with a Fixed Transportation Charge, International Journal of Production Research, 51, 3, pp. 698-717, (2013); Qiu X., Luo H., Xu G., Zhong R., Huang G., Physical Assets and Service Sharing for IoT-enabled Supply Hub in Industrial Park (SHIP), International Journal of Production Economics, 159, pp. 4-15, (2015); Rahman Z., Internet-based Supply Chain Management: Using the Internet to Revolutionize Your Business, International Journal of Information Management, 23, 6, pp. 493-505, (2003); Saha S., Goyal S.K., Supply Chain Coordination Contracts with Inventory Level and Retail Price Dependent Demand, International Journal of Production Economics, 161, pp. 140-152, (2015); Sarraj R., Ballot E., Pan S., Hakimi D., Montreuil B., Interconnected Logistic Networks and Protocols: Simulation-based Efficiency Assessment, International Journal of Production Research, 52, 11, pp. 3185-3208, (2014); Tang L., Jing K., He J., An Improved Ant Colony Optimisation Algorithm for Three-tier Supply Chain Scheduling Based on Networked Manufacturing, International Journal of Production Research, 51, 13, pp. 3945-3962, (2013); (2015); Amazon Global Store Data Exposure, (2015); Walters P., Adding Value in Global B2B Supply Chains: Strategic Directions and the Role of the Internet as a Driver of Competitive Advantage, Industrial Marketing Management, 37, 1, pp. 59-68, (2008); Xue X., Wang Y., Shen Q., Yu X., Coordination Mechanisms for Construction Supply Chain Management in the Internet Environment, International Journal of Project Management, 25, 2, pp. 150-157, (2007); Yao J.M., Scheduling Optimisation of Co-operator Selection and Task Allocation in Mass Customisation Supply Chain Based on Collaborative Benefits and Risks, International Journal of Production Research, 51, 8, pp. 2219-2239, (2013); Yao J.M., Strategic Supply Chain Management, (2014); Yao J.M., Supply Chain Resources Integration Optimization in B2C Online Shopping, International Journal of Production Research, (2015); Yao J.M., Gu M.J., Optimisation Analysis of Supply Chain Resource Allocation in Customized Online Shopping Service Mode, Mathematical Problems in Engineering, Article ID, pp. 1-11, (2015); Yao J.M., Liu L.W., Optimization Analysis of Supply Chain Scheduling in Mass Customization, International Journal of Production Economics, 117, 1, pp. 197-211, (2009)","J. Yao; School of Business, Renmin University of China, Beijing, China; email: jmyao@163.com",null,"Taylor and Francis Ltd.",{"$nulls":5},207543.0,null,"IJPRB",null,"English","Int J Prod Res","Article","Final",null,"Scopus","2-s2.0-84964503283"]
["He C.; Gao J.","He, Chengfang (57195721511); Gao, Jiewen (57195714656)","57195721511; 57195714656","Research on warehouse and distribution integration of fresh products cold chain logistics under the background of E-business",2017.0,"Boletin Tecnico/Technical Bulletin",55.0,8.0,null,10.0,20.0,10.0,2.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85029592708&partnerID=40&md5=723b93008faaae587072e59d906a29f6","Anhui Audit College, Hefei, Anhui province, 232001, China","He C., Anhui Audit College, Hefei, Anhui province, 232001, China; Gao J., Anhui Audit College, Hefei, Anhui province, 232001, China","With the rapid development of e-commerce in recent years, the service form of warehouses has undergone qualitative changes, and the integration of warehouse and distribution has become a necessary condition for the development of the electricity supplier logistics. In this paper, the authors analyse the warehouse and distribution integration of fresh products cold chain logistics under the background of E-business.The establishment of sales forecasting model is the most important link in the supply chain of e-commerce. From the point of view of supply chain management, warehouse integration can reduce costs and improve logistics efficiency, is the inevitable trend of future development.","Cold chain logistics; Distribution integration; E-commerce; Fresh agricultural","Commerce; Electric utilities; Electronic commerce; Integration; Sales; Supply chain management; Cold chain logistics; eBusiness; Fresh agricultural; Inevitable trends; Logistics efficiency; Qualitative changes; Reduce costs; Sales forecasting; Warehouses",{"$nulls":4},"Anhui Provincial Department of Education, (KJ2017A869)","The work of this paper is supported byNatural science research project of Anhui Provincial Department of Education: The integration of e-commerce logistics mode based on Internet plus(KJ2017A869).","Alsaad A.K., Mohamad R., Ismail N.A., The moderating role of power exercise in B2B e-commerce adoption decision, Procedia-Social and Behavioral Sciences, 130, pp. 515-523, (2014); Alsheikh M.A., Lin S., Tan H.P., Niyato D., Toward a robust sparse data representation for wireless sensor networks, Local Computer Networks (LCN), 2015 IEEE 40th Conference, pp. 117-124, (2015); Bing L., Wong T.L., Lam W., Unsupervised extraction of popular product attributes from e-commerce web sites by considering customer reviews, ACM Transactions on Internet Technology (TOIT), 16, 2, pp. 12-15, (2016); Barnaghi P., Sheth A., Henson C., From data to actionable knowledge: Big data challenges in the web of things, IEEE Intelligent Systems, 28, 6, pp. 6-11, (2013); Charron B., Hirate Y., Purcell D., Rezk M., Extracting semantic information for e-commerce, International Semantic Web Conference, pp. 273-290, (2016); Colleoni E., Rozza A., Arvidsson A., Echo chamber or public sphere? Predicting political orientation and measuring political homophily in Twitter using big data, Journal of Communication, 64, 2, pp. 317-332, (2014); Demidova L., Sokolova Y., Nikulchev E., Use of Fuzzy Clustering Algorithms Ensemble for SVM classifier Development, International Review on Modelling and Simulations, 8, 4, pp. 446-457, (2015); Galanakis C.M., Emerging technologies for the production of nutraceuticals from agricultural by-products: A viewpoint of opportunities and challenges, Food and Bioproducts Processing, 91, 4, pp. 575-579, (2013); Gupta D., Anand R.S., Tyagi B., A hybrid segmentation method based on Gaussian kernel fuzzy clustering and region based active contour model for ultrasound medical images, Biomedical Signal Processing and Control, 16, pp. 98-112, (2015); Huang Z., Benyoucef M., From e-commerce to social commerce: A close look at design features, Electronic Commerce Research and Applications, 12, 4, pp. 246-259, (2013); Holm A.E., Decreton B., Nell P.C., Klopf P., The dynamic response process to conflicting institutional demands in MNC subsidiaries-An inductive study in the Sub-Saharan African e-commerce sector, Global Strategy Journal, pp. 15-20, (2016); Kaptein M., Parvinen P., Advancing e-commerce personalization: Process framework and case study, International Journal of Electronic Commerce, 19, 3, pp. 7-33, (2015); Lallmahamood M., An Examination of Individualâ s Perceived Security and Privacy of the Internet in Malaysia and the Influence of This on Their Intention to Use E-Commerce: Using An Extension of the Technology Acceptance Model, The Journal of Internet Banking and Commerce, pp. 12-15, (2015); Lin Z., An empirical investigation of user and system recommendations in e-commerce, Decision Support Systems, 68, pp. 111-124, (2014); Rotem-Mindali O., Weltevreden J.W., Transport effects of e-commerce: What can be learned after years of research?, Transportation, 40, 5, pp. 867-885, (2013); Tan W., Blake M.B., Saleh I., Dustdar S., Social-network-sourced big data analytics, IEEE Internet Computing, 17, 5, pp. 62-69, (2013); Wang H., Wang J., An effective image representation method using kernel classification, Tools with Artificial Intelligence (ICTAI), 2014 IEEE 26th International Conference, pp. 853-858, (2014); Wang L., Zhan J., Luo C., Zhu Y., Yang Q., He Y., Zheng C., Bigdatabench: A big data benchmark suite from internet services, High Performance Computer Architecture (HPCA), 2014 IEEE 20th International Symposium, pp. 488-499, (2014); Zhong R.Y., Huang G.Q., Lan S.L., Shopfloor Logistics Management using RFID-enabled Big Data under Physical Internet, Proceeding of 1st International Physical Internet Conference, pp. 1-14, (2014); Zhao F., Fan J., Liu H., Optimal-selection-based suppressed fuzzy c-means clustering algorithm with selftuning non local spatial information for image segmentation, Expert Systems with Applications, 41, 9, pp. 4083-4093, (2014); Zarinbal M., Zarandi M.F., Turksen I.B., Relative entropy fuzzy c-means clustering, Information Sciences, 260, pp. 74-97, (2014)","J. Gao; Anhui Audit College, Hefei, Anhui province, 232001, China; email: gjw831015@163.com",null,"Universidad Central de Venezuela",{"$nulls":5},"0376723X",null,null,null,"English","Boletin Tecnico","Article","Final",null,"Scopus","2-s2.0-85029592708"]
["Lin Y.; Luo J.; Cai S.; Ma S.; Rong K.","Lin, Yong (57385793000); Luo, Jing (55482645900); Cai, Shuqin (7202957163); Ma, Shihua (8599814700); Rong, Ke (35318749700)","57385793000; 55482645900; 7202957163; 8599814700; 35318749700","Exploring the service quality in the e-commerce context: A triadic view",2016.0,"Industrial Management and Data Systems",116.0,3.0,null,388.0,415.0,27.0,57.0,"10.1108/IMDS-04-2015-0116","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84962438911&doi=10.1108%2fIMDS-04-2015-0116&partnerID=40&md5=e83e10ab21d46bf6199d2be9243227ee","Business School, University of Greenwich, London, United Kingdom; School of Management, Huazhong University of Science and Technology, Wuhan, China; Business School, Bournemouth University, Bournemouth, United Kingdom","Lin Y., Business School, University of Greenwich, London, United Kingdom; Luo J., Business School, University of Greenwich, London, United Kingdom; Cai S., School of Management, Huazhong University of Science and Technology, Wuhan, China; Ma S., School of Management, Huazhong University of Science and Technology, Wuhan, China; Rong K., Business School, Bournemouth University, Bournemouth, United Kingdom","Purpose - The purpose of this paper is to explore the quality factors influencing customer satisfaction in the electronic commerce (e-commerce) context using a triadic view of customer-e-retailer-third-party logistics provider, and to investigate the impacts of service quality on customer satisfaction and loyalty in the e-retailing supply chain. Design/methodology/approach - A literature review is used to determine the conceptual model and develop the measurement scales. Data are collected through a web survey mainly conducted in China. Structural equation modeling is used to analyze the collected data and test the research hypotheses. Findings - The results verify the proposed service quality framework, consisting of two dimensions (electronic service (e-service) quality and logistics service quality), in the e-commerce context. The results indicate that e-service quality and logistics service quality are strongly linked to customer satisfaction; that is, with e-service and logistics service, respectively. e-Service quality positively impacts customer satisfaction with logistics services, but logistics service quality negatively impacts customer satisfaction with e-services. Moreover, customer satisfaction with e-services is positively associated with customer loyalty for both e-services and logistics services. However, customer satisfaction with logistics services has no direct impact on related customer loyalty, and negatively impacts customer loyalty with e-services. Research limitations/implications - The survey focusses only on China; future data should verify whether different cultural backgrounds will impact the research results. Practical implications - The results show that e-retailers should not only focus on e-service quality, but also logistics service quality, which is critical to the success of e-commerce. Originality/value - A two-dimensional (e-service and logistics) service quality framework is proposed and empirically assessed in the context of the e-retailing supply chain. These impacts of the path of service quality on customer satisfaction and loyalty are highlighted. © Emerald Group Publishing Limited.","Customer satisfaction; E-retailing; E-service; Logistics service; Service quality; Supply chain","Commerce; Electronic commerce; Logistics; Outsourcing; Quality of service; Sales; Supply chains; Surveys; Design/methodology/approach; E- services; E-Retailing; Logistics service qualities; Logistics services; Service Quality; Structural equation modeling; Third party logistics providers; Customer satisfaction",{"$nulls":4},"National Natural Science Foundation of China, NSFC","The paper was supported by Project 71472069 and 71402051, funded by the National Natural Science Foundation of China.","How Popular is taobao.com?, (2014); Anderson J.C., Gerbing D.W., Structural equation modeling in practice: A review and recommended two-step approach, Psychological Bulletin, 103, 3, pp. 411-423, (1988); Anderson R.E., Srinivasan S.S., E-satisfaction and e-loyalty: A contingency framework, Psychology & Marketing, 20, 2, pp. 123-138, (2003); Bagozzi R.P., Yi Y., On the evaluation of structural equation models, Journal of Academy Marketing Science, 6, 1, pp. 54-78, (1998); Barnes S.J., Vidgen R.T., An evaluation of cyber-bookshops: The WebQual method, International Journal of Electronic Commerce, 6, 1, pp. 11-30, (2001); Barrutia J.M., Gilsanz A., E-Service quality: Overview and research agenda, International Journal of Quality and Service Sciences, 1, 1, pp. 29-50, (2009); Bienstock C.C., Royne M.B., Technology acceptance and satisfaction with logistics services, International Journal of Logistics Management, 21, 2, pp. 271-292, (2010); Bienstock C.C., Mentzer J.T., Bird M.M., Measuring physical distribution service quality, Journal of the Academy of Marketing Science, 25, 1, pp. 31-44, (1997); Bode C., Lindemann E., Wagner S.M., Driving trucks and driving sales? 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Yang Z., Consumer perceptions of service quality in Internet-based electronic commerce, Proceedings of the EMAC Conference, 811, (2001); Yoo B., Donthu N., Developing a scale to measure the perceived quality of an internet shopping site (SITEQUAL), Quarterly Journal of Electronic Commerce, 2, 1, pp. 31-46, (2001); Zeithaml V., Service excellence in electronic channels, Managing Service Quality, 12, 3, pp. 135-139, (2002); Zeithaml V., Parasuraman A., Malhotra A., Service quality delivery through web sites: A critical review of extant knowledge, Journal of the Academy of Marketing Science, 30, 4, pp. 362-375, (2002); Zeithaml V.A., Service quality, profitability, and the economic worth of customers: What we know and what we need to know, Journal of the Academy of Marketing Science, 28, 1, pp. 67-85, (2000); Zeithaml V.A., Berry L.L., Parasuraman A., The behavioral consequences of service quality, Journal of Marketing, 60, 2, pp. 31-46, (1996)","K. Rong; Business School, Bournemouth University, Bournemouth, United Kingdom; email: k.rong@exeter.ac.uk",null,"Emerald Group Publishing Ltd.",{"$nulls":5},2635577.0,null,"IMDSD",null,"English","Ind Manage Data Sys","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-84962438911"]
["Liu Y.","Liu, Yinfeng (57194569434)",5.7194569434E10,"Innovation of marketing pattern of fresh agricultural products based on internet + and big data platform",2017.0,"Agro Food Industry Hi-Tech",28.0,3.0,null,1739.0,1743.0,4.0,3.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85020874996&partnerID=40&md5=26de296b4a05087183053acc09f618c6","Xi'an International University, Xi'an, Shaanxi, 710077, China","Liu Y., Xi'an International University, Xi'an, Shaanxi, 710077, China","The fresh product has the characteristics of short shelf life and high requirements for temperature and humidity, and the development of the Internet platform is an opportunity for the transformation of its existing marketing methods. At present, due to the disconnection between marketing and logistics, most of the fresh agricultural products are still facing great resistance. In view of this situation, the feasibility of combining Internet + and big data platform with fresh agricultural products marketing mode was explored to establish and perfect data platform of e-commerce by internet; according to the characteristics of different customer groups, marketing methods were innovated.","Big data; Fresh agricultural products; Internet +; Marketing mode","Agricultural products; Agriculture; Commerce; Internet; Marketing; Data platform; Fresh agricultural products; Shelf life; Temperature and humidities; Big data",{"$nulls":6},"Manikas I., Manos B., Vlachopoulou M., Et al., A case study evaluation of the factors affecting fresh produce traceability, International Journal of Business Innovation and Research, 4, 3, pp. 232-255, (2010); Hingley M., Lindgreen A., Casswell B., Supplier-retailer relationships in the UK fresh produce supply chain, Journal of International Food & Agribusiness Marketing, 18, 1-2, pp. 49-86, (2006); Sparkes A., Thomas B., The use of the Internet as a critical success factor for the marketing of Welsh agri-food SMEs in the twenty-first century, British Food Journal, 103, 5, pp. 331-347, (2001); Cook R., US fresh produce value chain, Dollar Sales, 1, 2, pp. 41-65, (2011); Shukla M., Jharkharia S., Agri-fresh produce supply chain management, a state-of-the-art literature review, International Journal of Operations & Production Management, 33, 2, pp. 114-158, (2013); Veena A., Babu K.N., Venkatesha H.R., Supply chain, a differentiator in marketing fresh produce, IUP Journal of Supply Chain Management, 8, 1, pp. 12-15, (2011); Seybold P.B., Get inside the lives of your customers, Harvard Business Review, 79, 5, pp. 80-91, (2001); Baltas G., Determinants of internet advertising effectiveness, an empirical study, International Journal of Market Research, 45, 4, pp. 505-515, (2003); Davenport T.H., Dyche J., Big data in big companies, International Institute for Analytics, 3, 2, pp. 74-78, (2013); Sundmaeker H., Verdouw C., Wolfert S., Et al., Internet of food and farm 2020, Digitising the Industry-Internet of Things Connecting Physical, Digital and Virtual Worlds. River Publishers, Gistrup/Delft, 2, 8, pp. 129-151, (2016); Michelson H., Reardon T., Perez F., Small farmers and big retail, tradeoffs of supplying supermarkets in Nicaragua, World Development, 40, 2, pp. 342-354, (2012); Carter C., Krissoff B., Zwane A.P., Can country - Of - origin labeling succeed as a marketing tool for produce? Lessons from three case studies, Canadian Journal of Agricultural Economics/Revue Canadienne d'Agroeconomie, 54, 4, pp. 513-530, (2006); De Valck K., Van Bruggen G.H., Wierenga B., Virtual communities, A marketing perspective, Decision Support Systems, 47, 3, pp. 185-203, (2009); Diamond A., Barham J., Moving Food Along the Value Chain, Innovations in Regional Food Distribution, 2, 8, pp. 78-82, (2012); Ahumada O., Villalobos J.R., Operational model for planning the harvest and distribution of perishable agricultural products, International Journal of Production Economics, 33, 2, pp. 677-687, (2011)",null,null,"TeknoScienze",{"$nulls":5},1.7226996E7,null,null,null,"English","Agro Food Ind. Hi-Tech","Article","Final",null,"Scopus","2-s2.0-85020874996"]
["Zhang Y.; Liu S.; Liu Y.; Li R.","Zhang, Yingfeng (8305738300); Liu, Sichao (56732162200); Liu, Yang (55812026500); Li, Rui (57161393800)","8305738300; 56732162200; 55812026500; 57161393800","Smart box-enabled product–service system for cloud logistics",2016.0,"International Journal of Production Research",54.0,22.0,null,6693.0,6706.0,13.0,93.0,"10.1080/00207543.2015.1134840","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84954212012&doi=10.1080%2f00207543.2015.1134840&partnerID=40&md5=a1d8b3f13f85a43ccf7cf16a1ba77339","Key Laboratory of Contemporary Design and Integrated Manufacturing Technology, School of Mechanical Engineering, Northwestern Polytechnical University, Shaanxi, China; Department of Production, University of Vaasa, Vaasa, Finland","Zhang Y., Key Laboratory of Contemporary Design and Integrated Manufacturing Technology, School of Mechanical Engineering, Northwestern Polytechnical University, Shaanxi, China; Liu S., Key Laboratory of Contemporary Design and Integrated Manufacturing Technology, School of Mechanical Engineering, Northwestern Polytechnical University, Shaanxi, China; Liu Y., Department of Production, University of Vaasa, Vaasa, Finland; Li R., Key Laboratory of Contemporary Design and Integrated Manufacturing Technology, School of Mechanical Engineering, Northwestern Polytechnical University, Shaanxi, China","Modern logistics takes significant progress and rapid developments with the prosperity of E-commerce, particularly in China. Typical challenges that logistics industry is facing now are composed by a lack of sharing, standard, cost-effective and environmental package and efficient optimisation method for logistics tasks distribution. As a result, it is difficult to implement green, sustainable logistics services. Three important technologies, Physical Internet (PI), product–service system (PSS) and cloud computing (CC), are adopted and developed to address the above issues. PI is extended to design a world-standard green recyclable smart box that is used to encapsulate goods. Smart box-enabled PSS is constructed to provide an innovative sustainable green logistics service, and high-quality packaging, as well as reduce logistics cost and environmental pollution. A real-time information-driven logistics tasks optimisation method is constructed by designing a cloud logistics platform based on CC. On this platform, a hierarchical tree-structure network for customer orders (COs) is built up to achieve the order-box matching of function. Then, a distance clustering analysis algorithm is presented to group and form the optimal clustering results for all COs, and a real-time information-driven optimisation method for logistics orders is proposed to minimise the unused volume of containers. Finally, a case study is simulated to demonstrate the efficiency and feasibility of proposed cloud logistics optimisation method. © 2016 Informa UK Limited, trading as Taylor & Francis Group.","cloud computing; logistics; Physical Internet; product–service system; smart box","Cloud computing; Clustering algorithms; Cost effectiveness; Distributed computer systems; Internet; Sustainable development; Trees (mathematics); Clustering analysis; Efficient optimisation; Environmental pollutions; Logistics optimisation; Logistics platforms; Real-time information; Service systems; smart box; Logistics",{"$nulls":6},"Ballot E., Montreuil B., Thivierge C., Functional Design of Physical Internet Facilities: A Road–Rail Hub, Progress in Material Handling Research: MHIA, pp. 1-36, (2012); Barchetti U., Bucciero A., De Blasi M., Mainetti L., Patrono L., Implementation and Testing of an EPCglobal-aware Discovery Service for Itemlevel Traceability, Proceedings of the International Conference on UltraModern Telecommunications and Workshops, pp. 1-8, (2009); Boussier J.M., Cucu T., Ion L., Breuil D., Simulation of Goods Delivery Process, International Journal of Physical Distribution & Logistics Management, 41, 9, pp. 913-930, (2011); Buyya R., Yeo C.S., Venugopal S., Broberg J., Brandic I., Cloud Computing and Emerging IT Platforms: Vision, Hype, and Reality for Delivering Computing as the 5th Utility, Future Generation Computer Systems, 25, 6, pp. 599-616, (2009); Geng X., Chu X., Xue D., Zhang Z., A Systematic Decision-making Approach for the Optimal Product–Service System Planning, Expert Systems with Applications, 38, 9, pp. 11849-11858, (2011); EPCglobal, (2003); Hu M., Cao Y., Mu X., Research of Logistics Vehicle Monitoring Platform Based on Cloud Computing, LISS 2013, pp. 359-364, (2013); Huang G.Q., Qu T., Zhong R.Y., Li Z., Yang H.D., Zhang Y.F., Chen Q.X., Establishing Production Service System and Information Collaboration Platform for Mold and Die Products, The International Journal of Advanced Manufacturing Technology, 52, 9-12, pp. 1149-1160, (2011); Huang G.Q., Qu T., Zhang Y.F., Yang H.D., RFID-enabled Product-service System for Automotive Part and Accessory Manufacturing Alliances, International Journal of Production Research, 50, 14, pp. 3821-3840, (2012); Li W., Zhong Y., Wang X., Cao Y., Resource Virtualization and Service Selection in Cloud Logistics, Journal of Network and Computer Applications, 36, 6, pp. 1696-1704, (2013); Lin Y.H., Meller R.D., Ellis K.P., Thomas L.M., Lombardi B.J., A Decomposition-based Approach for the Selection of Standardized Modular Containers, International Journal of Production Research, 52, 15, pp. 4660-4672, (2015); Mongeau M., Bes C., Optimization of Aircraft Container Loading, IEEE Transactions on Aerospace and Electronic Systems, 39, 1, pp. 140-150, (2003); Mont O.K., Clarifying the Concept of Product–Service System, Journal of Cleaner Production, 10, 3, pp. 237-245, (2002); Montreuil B., Towards a Physical Internet: Meeting the Global Logistics Sustainability Grand Challenge, Logistics Research, 3, 2-3, pp. 71-87, (2011); Pan S., Nigrelli M., Ballot M., Sarraj R., Yang Y., Perspectives of Inventory Control Models in the Physical Internet: A Simulation Study, Computer & Industrial Engineering, 84, pp. 122-132, (2014); The Physical Internet: A Survey of Logistics, The Economist, (2006); (2010); Ribeiro V.C., Borsato M., Integrating Product–Service System Tools into New Product Development Processes, Journal of Integrated Design and Process Science, 18, 3, pp. 3-18, (2014); Sarraj R., Ballot E., Pan S., Hakimi D., Montreuil B., Interconnected Logistic Network and Protocols: Simulation-based Efficiency Assessment, International Journal of Production Research, 52, 11, pp. 3185-3208, (2013); Sarraj R., Ballot E., Pan S., Montreuil B., Analogies between Internet Network and Logistics Service Networks: Challenges Involved in the Interconnection, Journal of Intelligent Manufacturing, 25, 6, pp. 1207-1219, (2014); Subramanian N., Abdulrahman M.D., Zhou X., Integration of Logistics and Cloud Computing Service Providers: Cost and Green Benefits in the Chinese Context, Transportation Research Part E: Logistics and Transportation Review, 70, pp. 86-98, (2014); Sun W., Tao L., Cloud Logistics Mode-based Location of Regional Logistics Distribution Center, Bridges, pp. 2477-2483, (2013); Tukker A., Eight Types of Product–Service System: Eight Ways to Sustainability? Experiences from SusProNet, Business Strategy and the Environment, 13, 4, pp. 246-260, (2004); Wang J., Zhang X., Hu X., Zhao J., Cloud Logistics Service Mode and Its Several Key Issues, Journal of System and Management Sciences, 4, 2, pp. 34-44, (2014); Want R., An Introduction to RFID Technology, IEEE Pervasive Computing, 5, 1, pp. 25-33, (2006); Wible B., Mervis J., Wigginton N.S., Rethinking the Global Supply Chain, Science, 344, 6188, pp. 1100-1103, (2014); Williams A., Product Service Systems in the Automobile Industry: Contribution to System Innovation?, Journal of Cleaner Production, 15, 11-12, pp. 1093-1103, (2007); Zhang Y.F., Huang G.Q., Sun S.D., Yang T., Multi-agent Based Real-time Production Scheduling Method for Radio Frequency Identification Enabled Ubiquitous Shopfloor Environment, Computers & Industrial Engineering, 76, pp. 89-97, (2014); Zhang Y.F., Wang W.B., Wu N.Q., Chen Q., IoT-enabled Real-time Production Performance Analysis and Exception Diagnosis Model, IEEE Transactions on Automation Science and Engineering, (2015); Zhang Y.F., Xi D., Li R., Sun S.D., Task-driven Manufacturing Cloud Service Proactive Discovery and Optimal Configuration Method, International Journal of Advanced Manufacturing Technology, (2015); Zhang Y.F., Zhang G., Du W., Wang J.Q., Ali E., Sun S.D., An Optimization Method for Shopfloor Material Handling Based on Real-time and Multi-source Manufacturing Data, International Journal of Production Economics, 165, pp. 282-292, (2015); Zhang Y.F., Zhang G., Liu Y., Hu D., Research on Services Encapsulation and Virtualization Access Model of Machine for Cloud Manufacturing, Journal of Intelligent Manufacturing, (2015); Zhang Y.F., Zhang G., Wang J.Q., Sun S.D., Si S.B., Yang T., Real-time Information Capturing and Integration Framework of the Internet of Manufacturing Things, International Journal of Computer Integrated Manufacturing, 28, 8, pp. 811-822, (2015); Zhong R.Y., Dai Q.Y., Qu T., Hu G.J., Huang G.Q., RFID-enabled Real-time Manufacturing Execution System for Mass-customization Production, Robotics and Computer-Integrated Manufacturing, 29, 2, pp. 283-292, (2013); Zhong R.Y., Huang G.Q., Lan S., Dai Q.Y., Chen X., Zhang T., A Big Data Approach for Logistics Trajectory Discovery from RFID-enabled Production Data, International Journal of Production Economics, 165, pp. 260-272, (2015); Zhong R.Y., Huang G.Q., Lan S., Dai Q., Zhang T., Xu C., A Two-level Advanced Production Planning and Scheduling Model for RFID-enabled Ubiquitous Manufacturing, Advanced Engineering Informatics, 29, 4, pp. 799-812, (2015)","Y. Zhang; Key Laboratory of Contemporary Design and Integrated Manufacturing Technology, School of Mechanical Engineering, Northwestern Polytechnical University, Shaanxi, China; email: zhangyf@nwpu.edu.cn",null,"Taylor and Francis Ltd.",{"$nulls":5},207543.0,null,"IJPRB",null,"English","Int J Prod Res","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-84954212012"]
["Misra H.","Misra, Harekrishna (25122965600)",2.51229656E10,"Managing user capabilities in information systems life cycle: Conceptual modeling",2017.0,"International Journal of Information Science and Management",15.0,1.0,null,39.0,58.0,19.0,1.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85010716462&partnerID=40&md5=578c80d3458f09b2c14ea8e69561d10b","Department of IT and Systems, Institute of Rural Management Anand, India","Misra H., Department of IT and Systems, Institute of Rural Management Anand, India","Information Systems (IS) acquisition prescribes induction of information technologies (IT) in the organization. At times, IS is used for managing broader enterprise level issues like implementing e-business, e-commerce. Enterprise level issues are addressed through adequate involvement of people in the organization which are termed as \"user capabilities\". Managing user capabilities is critical since their roles are very important in the entire Systems Development Life Cycle (SDLC). It is seen that failures in IT acquisition are not because of the technology, but failure in choosing it rightly, and poor user capabilities. If planned properly, user capabilities can contribute effectively to SDLC. SDLC works in stages with different sets of users and insensitivities to users contribute to the gap between satisfying organizational needs and end-user deliveries. This problem can be addressed by carefully integrating user capability issues in the SDLC process. In this paper a framework is suggested to capture user capabilities in an IT acquiring organization. User capabilities are identified in two categories: IT users who are IT experts and involved in design, development, and implementation of SDLC driven projects, and, second, non-IT users who, despite having inadequate or no exposure to IT, contribute to SDLC driven projects. The framework is implemented through Unified Modelling Language (UML) based approach. A case discusses the utility of this approach.","Information systems modeling; SDLC; UML; User capabilities",{"$nulls":7},"Abrahamson P., Jokela T., Implementing User-Centred Design in to a Software Development Organization: A Sub Cultural Analysis, 24th Information Systems Research Seminar, (2001); Basili, Victor R., Caldiera G., Rombach H.D., Goal Question Metrics Paradigm, Encyclopedia of Software Engineering, (1994); Basili, Victor R., Boehm B., COTS-Based Systems Top 10 List, Software Management, (2001); Boehm B., Wilfred J., The Spiral Model as a Tool for Evolutionary Acquisition, Journal of Defense Software Engineering, (2001); Bowen P., Heales J., Monthira V., Reliability Factors in Business Software: Volatility, Requirements and End-users, Information Systems Journal, 12, 3, (2002); Karuppan C., Karuppan M., Resilience of Super Users' Mental Models of Enterprise-wide Systems, European Journal of Information Systems, 17, (2008); Gordon B., Margarethe H., Management Information Systems: Conceptual Foundations, (2000); Frank K., A Contingency Based Approach to Requirements Elicitation and Systems Development, Journal of systems and software, 40, 1, (1998); Grady B., Practical Software Metrics for Project Management and Process Improvement, (1992); Herron D., IT Measurement: Practical Advice from Experts, International Function Point User Group, (2002); Jalote P., CMM in Practice: Process for Executing Software Projects at Infosys, (2002); Kumar K., Hillegersberg J., ERP Experiences and Evolution, Communications of the ACM, 43, 3, (2000); Lamb R., Kling R., Re-conceptualising Users as Social Actors in Information Systems Research, MIS Quarterly, 27, 2, (2003); Lee C., Modelling the Business Value of Information Technology, Information and Management, 39, 3, (2001); Leffingwell D., Scaling Software Agility: Best Practices for Large Enterprises, (2007); Lientz B., Chen M., Assessing Impact of New Technology in Information Systems, Long Range Planning, 14, 6, (1981); Luftman J., Assessing IT and Business Alignment, Information Systems Management, 20, 4, (2003); Lycett M., Macredie R., Patel C., Paul J., Migrating Agile Methods to Standardised Development Practice, Computer Magazine, 36, 6, (2003); Mead N., Robert E., Linger R., Lipson H., McHugh J., Life-Cycle Models for Survivable Systems, Proceedings of the Third Information Survivability, (2000); Mellor S., Balcer M., Executable UML: A Foundation for Model-Driven Architecture, (2002); Misra H.K., User Capabilities Dimensions in Information System Development Life Cycle: A UML Based Modeling, (2009); Misra H., Users' Computer Human Interface Capabilities in Information Systems Development Life Cycle: An Organizational Perspective, (2008); Misra H., Mohanty B., The IT-Acquisition Models and User's Perspective: A Review, (2003); Nuseibeh B., Easterbrook S., Requirements Engineering: A Roadmap, (2000); Pervan G., How the Chief Executive Officers in Large Organizations View the Management of their Information Systems, Journal of Information Technology, 13, (1998); Piekarski W., Plimmer B., A Conceptual Framework for Explaining the Value of End User Maturity Levels for IT Management, Proceedings of the Eighth Australasian User Interface Conference (AUIC), (2007); Zhang P., Te'eni D., Integrating Human-Computer Interaction Development into the Systems Development Life Cycle: A Methodology, Communications of the Association for Information Systems, 15, (2005); Rumbaugh J., Jacobson I., Booch G., \"The Unified Modelling Language Reference Manual\", (1999); Shaw M., David G., Software Architecture: Perspectives on an Emerging Discipline, (1996); Vijay K.K.M., Mathiassenl L., Pedersen K., The Post Mortem Paradox: A Delphi Study of IT Specialist Perceptions, European Journal of Information Systems, 17, (2008); Wang E., Tai J., Factors Affecting Information Systems PlanningEffectiveness: Organizational Contexts and Planning Systems Dimensions, Information and Management, 40, 4, (2003); Ward J., Griffiths P., Whitmore P., Strategic Planning for Information Systems, (1990); Watson T., Leyland P., Kavan B., Measuring Information Systems Service Quality: Lessons from Two Longitudinal Case Studies, (1998); Wohlin C., Ohlsson Regnell M.B., Wesslen A., Experimentation in Software Engineering: An Introduction, (2000)","H. Misra; Department of IT and Systems, Institute of Rural Management Anand, India; email: hkmishra@irma.ac.in",null,"Regional Inform. Center for Sci. and Technol.",{"$nulls":5},2.0088302E7,null,null,null,"English","Int. J. Inf. Sci. Manage.","Article","Final",null,"Scopus","2-s2.0-85010716462"]
["Iwanaga J.; Nishimura N.; Sukegawa N.; Takano Y.","Iwanaga, Jiro (57151182200); Nishimura, Naoki (57150127100); Sukegawa, Noriyoshi (55246346000); Takano, Yuichi (15073427700)","57151182200; 57150127100; 55246346000; 15073427700","Estimating product-choice probabilities from recency and frequency of page views",2016.0,"Knowledge-Based Systems",99.0,null,null,157.0,167.0,10.0,12.0,"10.1016/j.knosys.2016.02.006","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84961203543&doi=10.1016%2fj.knosys.2016.02.006&partnerID=40&md5=35752f0c21ffc489f04d43bc80337e2e","Business Intelligence Deployment Center, NTT DATA Mathematical Systems Inc., 1F Shinanomachi Rengakan, 35 Shinanomachi, Shinjyuku-ku, Tokyo, 166-0016, Japan; Product Management Unit, Internet Business Development Division, Recruit Lifestyle Co., Ltd., GranTokyo SOUTHTOWER 1-9-2 Marunouchi, Chiyoda-ku, Tokyo, 100-6640, Japan; Department of Information and System Engineering, Faculty of Science and Engineering, Chuo University, 1-13-27 Kasuga, Bunkyo-ku, Tokyo, 112-8551, Japan; School of Network and Information, Senshu University, 2-1-1 Higashimita, Tama-ku, Kawasaki-shi, Kanagawa, 214-8580, Japan","Iwanaga J., Business Intelligence Deployment Center, NTT DATA Mathematical Systems Inc., 1F Shinanomachi Rengakan, 35 Shinanomachi, Shinjyuku-ku, Tokyo, 166-0016, Japan; Nishimura N., Product Management Unit, Internet Business Development Division, Recruit Lifestyle Co., Ltd., GranTokyo SOUTHTOWER 1-9-2 Marunouchi, Chiyoda-ku, Tokyo, 100-6640, Japan; Sukegawa N., Department of Information and System Engineering, Faculty of Science and Engineering, Chuo University, 1-13-27 Kasuga, Bunkyo-ku, Tokyo, 112-8551, Japan; Takano Y., School of Network and Information, Senshu University, 2-1-1 Higashimita, Tama-ku, Kawasaki-shi, Kanagawa, 214-8580, Japan","This paper investigates the relationship between customers' page views (PVs) and the probabilities of their product choices on e-commerce sites. For this purpose, we create a probability table consisting of product-choice probabilities for all recency and frequency combinations of each customers' previous PVs. To reduce the estimation error when there are few training samples, we develop optimization models for estimating the product-choice probabilities that satisfy monotonicity, convexity and concavity constraints with respect to recency and frequency. Computational results demonstrate that our method has clear advantages over logistic regression and kernel-based support vector machine. © 2016 Elsevier B.V. All rights reserved.","Clickstream data; E-commerce; Frequency; Optimization; Page view; Product choice; Recency","Commerce; Electronic commerce; Estimation; Optimization; Probability; Clickstream data; Frequency; Page view; Product choice; Recency; Frequency estimation",{"$nulls":4},"Japan Society for the Promotion of Science, KAKEN, (26242027, 26750114)","The 20th data analysis competition, sponsored by the Joint Association Study Group of Management Science (JASMAC), provided the data set used in the computational experiments. This work was supported by a Grant-in-Aid for Young Scientists ((B) 26750114 ) by the Japan Society for the Promotion of Science . Finally, the authors thank the anonymous referees for their helpful and constructive comments, which significantly improved the quality of the paper.","Best M.J., Chakravarti N., Active set algorithms for isotonic regression; A unifying framework, Math. Program., 47, pp. 425-439, (1990); Boroujerdi E.G., Mehri S., Garmaroudi S.S., Pezeshki M., Mehrabadi F.R., Malakouti S., Khadivi S., A study on prediction of user's tendency toward purchases in websites based on behavior models, Proceedings of the 6th IEEE Conference on Information and Knowledge Technology, pp. 61-66, (2014); Boyd S., Vandenberghe L., Convex Optimization, (2004); Brunk H.D., Maximum likelihood estimates of monotone parameters, Ann. Math. Stat., 26, 4, pp. 607-616, (1955); Bucklin R.E., Lattin J.M., Ansari A., Gupta S., Bell D., Coupey E., Little J.D.C., Mela C., Montgomery A., Steckel J., Choice and the internet: From clickstream to research stream, Mark. Lett., 13, 3, pp. 245-258, (2002); Bucklin R.E., Sismeiro C., Click here for internet insight: Advances in clickstream data analysis in marketing, J. Interact. Mark., 23, 1, pp. 35-48, (2009); Chen Z.Y., Fan Z.P., Distributed customer behavior prediction using multiplex data: A collaborative MK-SVM approach, Knowl. Based Syst., 35, pp. 111-119, (2012); Cho Y.H., Kim J.K., Application of web usage mining and product taxonomy to collaborative recommendations in e-commerce, Expert Syst. Appl., 26, 2, pp. 233-246, (2004); Dykstra R.L., An algorithm for restricted least squares regression, J. Am. Stat. Assoc., 78, 384, pp. 837-842, (1983); Dykstra R.L., Robertson T., An algorithm for isotonic regression for two or more independent variables, Ann. Stat., 10, 3, pp. 708-716, (1982); Ekstrand M.D., Riedl J.T., Konstan J.A., Collaborative filtering recommender systems, Found. Trends Hum. Comput. Interact., 4, 2, pp. 81-173, (2011); Fader P.S., Hardie B.G., Lee K.L., RFM and CLV: Using iso-value curves for customer base analysis, J. Mark. Res., 42, 4, pp. 415-430, (2005); Fader P.S., Hardie B.G., Lee K.L., counting your customers\" the easy way: An alternative to the pareto/NBD model, Mark. Sci., 24, 2, pp. 275-284, (2005); Geyer C.J., Constrained maximum likelihood exemplified by isotonic convex logistic regression, J. Am. Stat. Assoc., 86, 415, pp. 717-724, (1991); Grenander U., On the theory of mortality measurement: Part II, Scand. Actuar. J., 1956, 2, pp. 125-153, (1956); Hildreth C., Point estimates of ordinates of concave functions, J. Am. Stat. Assoc., 49, 267, pp. 598-619, (1954); Huang T., Van Mieghem J.A., Clickstream data and inventory management: Model and empirical analysis, Product. Oper. Manag., 23, 3, pp. 333-347, (2014); Hui S.K., Fader P.S., Bradlow E.T., Path data in marketing: An integrative framework and prospectus for model building, Mark. Sci., 28, 2, pp. 320-335, (2009); Jamalzadeh M., Analysis of Clickstream Data, (2011); Jerath K., Fader P.S., Hardie B.G., New perspectives on customer \"death\" using a generalization of the pareto/NBD model, Mark. Sci., 30, 5, pp. 866-880, (2011); Kim Y.S., Yum B.J., Recommender system based on click stream data using association rule mining, Expert Syst. Appl., 38, 10, pp. 13320-13327, (2011); Manning C.D., Raghavan P., Schutze H., Introduction to Information Retrieval, (2008); Maxwell W.L., Muckstadt J.A., Establishing consistent and realistic reorder intervals in production-distribution systems, Oper. Res., 33, pp. 1316-1341, (1985); Moe W.W., Fader P.S., Dynamic conversion behavior at e-commerce sites, Manag. Sci., 50, 3, pp. 326-335, (2004); Moe W.W., A field experiment to assess the interruption effect of pop-up promotions, J. Interact. Mark., 20, 1, pp. 34-44, (2006); Montgomery A.L., Applying quantitative marketing techniques to the internet, Interfaces, 31, 2, pp. 90-108, (2001); Montgomery A.L., Li S., Srinivasan K., Liechty J.C., Modeling online browsing and path analysis using clickstream data, Mark. Sci., 23, 4, pp. 579-595, (2004); Ngai E.W., Xiu L., Chau D.C., Application of data mining techniques in customer relationship management: A literature review and classification, Expert Syst. Appl., 36, 2, pp. 2592-2602, (2009); Olbrich R., Holsing C., Modeling consumer purchasing behavior in social shopping communities with clickstream data, Int. J. Electron. Commer., 16, 2, pp. 15-40, (2011); Pardalos P.M., Xue G., Algorithms for a class of isotonic regression problems, Algorithmica, 23, 3, pp. 211-222, (1999); Qiu J., A predictive model for customer purchase behavior in e-commerce context, Proceedings of the 2014 Pacific Asia Conference on Information Systems, (2014); Reinartz W.J., Kumar V., On the profitability of long-life customers in a noncontractual setting: An empirical investigation and implications for marketing, J. Mark., 64, 4, pp. 17-35, (2000); Reinartz W.J., Kumar V., The impact of customer relationship characteristics on profitable lifetime duration, J. Mark., 67, 1, pp. 77-99, (2003); Resnick P., Iacovou N., Suchak M., Bergstrom P., Riedl J., Grouplens: An open architecture for collaborative filtering of netnews, Proceedings of the 1994 ACM Conference on Computer Supported Cooperative Work, pp. 175-186, (1994); Ricci F., Rokach L., Shapira B., Kantor P.B., Recommender Systems Handbook (Vol. 1), (2011); Roundy R., A 98% effective lot-sizing rule for a multi-product multistage production/inventory system, Math. Oper. Res., 11, pp. 699-727, (1986); Sato S., Asahi Y., The model of purchasing and visiting behavior of customers in an e-commerce site for consumers, International Proceedings of Economics Development & Research, pp. 72-76, (2012); Sismeiro C., Bucklin R.E., Modeling purchase behavior at an e-commerce web site: A task-completion approach, J. Mark. Res., 41, 3, pp. 306-323, (2004); Stout Q.F., Isotonic regression for multiple independent variables, Algorithmica, 71, 2, pp. 450-470, (2013); Turban E., King D., Lee J., Liang T.-P., Turban D.C., Electronic Commerce: A Managerial and Social Networks Perspective [8th Ed.], (2015); Van Den Poel D., Buckinx W., Predicting online-purchasing behaviour, Eur. J. Oper. Res., 166, 2, pp. 557-575, (2005); Wu J., Rangaswamy A., A fuzzy set model of search and consideration with an application to an online market, Mark. Sci., 22, 3, pp. 411-434, (2003); Zhang Y., Pennacchiotti M., Predicting purchase behaviors from social media, Proceedings of the 22nd International Conference on World Wide Web, pp. 1521-1532, (2013)","N. Sukegawa; Department of Information and System Engineering, Faculty of Science and Engineering, Chuo University, Bunkyo-ku, Tokyo, 1-13-27 Kasuga, 112-8551, Japan; email: sukegawa@ise.chuo-u.ac.jp",null,"Elsevier B.V.",{"$nulls":5},9507051.0,null,"KNSYE",null,"English","Knowl Based Syst","Article","Final",null,"Scopus","2-s2.0-84961203543"]
["Tandon U.; Kiran R.; Sah A.N.","Tandon, Urvashi (57190029593); Kiran, Ravi (22985431500); Sah, Ash N. (57190030141)","57190029593; 22985431500; 57190030141","Understanding online shopping adoption in India: Unified theory of acceptance and use of technology 2 (UTAUT2) with perceived risk application",2016.0,"Service Science",8.0,4.0,null,420.0,437.0,17.0,44.0,"10.1287/serv.2016.0154","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85029349785&doi=10.1287%2fserv.2016.0154&partnerID=40&md5=31366c8cac3708fcf4ae8833763154f1","School of Humanities and Social Sciences, Thapar University, Patiala, 147004, India","Tandon U., School of Humanities and Social Sciences, Thapar University, Patiala, 147004, India; Kiran R., School of Humanities and Social Sciences, Thapar University, Patiala, 147004, India; Sah A.N., School of Humanities and Social Sciences, Thapar University, Patiala, 147004, India","The purpose of this research is to analyze perceived risk and drivers of online shopping influencing behavioral intention in India. The study empirically validates website design, cash-on-delivery (COD) mode of payment, and different facets of perceived risk with the unified theory of acceptance and use of technology(2) (UTAUT2) of Venkatesh et al. [Venkatesh V, Thong JYL, Xu X (2012) Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quart. 36(1):157-178]. Findings of the study revealed that perceived risk had a negative relation with behavioral intention, whereas the drivers were positively associated with behavioral intention. Besides analyzing cashon-delivery mode of payment as a construct, it also includes website design to enhance application of UTUAT2 in Indian andother similar developing countries' context. The study will help online retailers to focus in the right direction by eliminating threats and convert nonshoppers to online shoppers. © 2016 INFORMS.","COD mode of payment; Drivers of online shopping; India; Online shopping; Perceived risk; UTAUT2; Website design",{"$nulls":7},"Abu-Shanab E., Pearson J.M., Setterstorm A.J., Internet banking and customer's acceptance in Jordan: The unified model's perspective, Comm. Assoc. Inform. Systems, 26, 1, pp. 493-524, (2010); Ajzen I., The theory of planned behavior, Organ. Behav. Human Decision Processes, 50, 11, pp. 179-211, (1991); Albugami M., Bellaaj M., The continued use of Internet banking: Combining UTAUT2 theory and service quality model, J. Global Management Res., 10, 2, pp. 11-28, (2014); Al-Gahtani S.S., Hubona G.S., Wang J., Information technology (IT) in Saudi Arabia: Culture and the acceptance and use of IT, Inform. Management, 44, 8, pp. 681-691, (2007); Almousa M., Perceived risk in apparel online shopping: A multidimensional perspective, Canadian Soc. Sci., 7, 2, pp. 23-31, (2011); Aoun C., Vatanasakdakul S., Li Y., AIS in Australia: UTAUT application and cultural implication, ACIS 2010 Proc., pp. 1-3, (2010); Evolution of E-commerce in India, Creating the Bricks behind the Clicks., (2014); Baabdullah A., Dwivedi Y., Williams M., Adopting an extended UTAUT2 to predict consumer adoption of m-technologies in Saudi Arabia, Proc. 19th UK Acad. Inform. Systems Conf., 5, pp. 1-25, (2014); Baptista G., Oliveira T., Understanding mobile banking: The unified theory of acceptance and use of technology combined with cultural moderators, Comput. 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["Walker J.H.; Saffu K.; Mazurek M.","Walker, John H. (58333956100); Saffu, Kojo (13106078200); Mazurek, Marica (55290535200)","58333956100; 13106078200; 55290535200","An Empirical Study of Factors Influencing E-Commerce Adoption/Non-Adoption in Slovakian SMEs",2016.0,"Journal of Internet Commerce",15.0,3.0,null,189.0,213.0,24.0,55.0,"10.1080/15332861.2016.1191049","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84988891966&doi=10.1080%2f15332861.2016.1191049&partnerID=40&md5=0022be1385e050ac6997d37f988c5a4d","Goodman School of Business, Brock University, St. Catharines, ON, Canada; Centre of Science and Research, Institute of Economic Sciences, University of Matej Bel, Banská Bystrica, Slovakia","Walker J.H., Goodman School of Business, Brock University, St. Catharines, ON, Canada; Saffu K., Goodman School of Business, Brock University, St. Catharines, ON, Canada; Mazurek M., Centre of Science and Research, Institute of Economic Sciences, University of Matej Bel, Banská Bystrica, Slovakia","While the global emergence of e-commerce has led businesses to take advantage of the technologies available to them to enhance their use of e-commerce, small and medium-sized enterprises (SMEs) are known for not adopting information technology to create jobs. Due to the dearth of studies of SME adoption of technology in transitioning European countries such as Slovakia, (Saffu, Walker, and Mazurek 2012), it is imperative to understand the factors that differentiate SME e-commerce adopters from non-adopters. Adoption and non-adoption factors of 230 Slovakian SMEs were empirically examined using logistic regression. Compatibility and Organizational Readiness, Decision and Operational Aids, and External Pressure were significant for discerning e-commerce adoption. Practical, policy, and research implications are presented. This study goes beyond the determinants of e-commerce adoption and contributes to the understanding of factors that distinguish between adopters and non-adopters of e-commerce for Slovakian SMEs. © 2016, Copyright © Taylor & Francis Group, LLC.","E-commerce adoption; Slovakia; SMEs",{"$nulls":7},"Alam S.S., Ali M.Y., Jani M.F.M., An empirical study of factors affecting electronic commerce adoption among SMEs in Malaysia, Journal of Business Economics and Management, 12, 2, pp. 375-399, (2011); AlGhamdi R., Nguyen J., Nguyen A., Drew S., Factors influencing e-commerce adoption by retailers in Saudi Arabia: A quantitative analysis, International Journal of Electronic Commerce Studies, 3, 1, pp. 83-100, (2012); Allison P.D., Logistic regression using SAS® system: Theory and application, (2001); Al-Weshah G.A., Al-Zubi K., E-business enablers and barriers: Empirical study of SMEs in Jordanian communication sector, Global Journal of Business Research, 6, 3, pp. 1-15, (2012); Beatty R.C., Shim J.P., Jones M.C., Factors influencing corporate web site adoption: A time-based assessment, Information & Management, 38, 6, pp. 337-354, (2001); 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Wanjau K., Macharia N.R., Ayodo E.M.A., Factors affecting adoption of electronic commerce among small medium enterprises in Kenya: Survey of tour and travel firms in Nairobi, International Journal of Business, Humanities, and Technology, 2, 4, pp. 76-91, (2012); Wilson H., Daniel E., Davies I.A., The diffusion of e-commerce in UK SMEs, Journal of Marketing Management, 24, 5-6, pp. 489-516, (2008); Zhu K., Kraemer K., Post-adoption variations in usage and value of e-business by organizations: Cross-country evidence from the retail industry, Information Systems Research, 16, 1, pp. 61-84, (2005); Zhu L., Thatcher S.M.B., National information ecology: A new institutional economics perspective on global e-commerce adoption, Journal of Electronic Commerce Research, 11, 1, pp. 53-72, (2010)","K. Saffu; Goodman School of Business, Brock University, Catharines, 1812 Sir Isaac Brock Way, St, L2S3A1, Canada; email: ksaffu@brocku.ca",null,"Routledge",{"$nulls":5},1.5332861E7,null,null,null,"English","J. Internet Commer.","Article","Final",null,"Scopus","2-s2.0-84988891966"]
["Huseynov F.; Yıldırım S.Ö.","Huseynov, Farid (57008979300); Yıldırım, Sevgi Özkan (56425367800)","57008979300; 56425367800","Internet users’ attitudes toward business-to-consumer online shopping: A survey",2016.0,"Information Development",32.0,3.0,null,452.0,465.0,13.0,43.0,"10.1177/0266666914554812","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84965097456&doi=10.1177%2f0266666914554812&partnerID=40&md5=ad9e40990b73fb8fb89935c7dad555c4","Middle East Technical University, Dumlupınar Blv. No:1, Çankaya, Ankara, 06800, Turkey","Huseynov F., Middle East Technical University, Dumlupınar Blv. No:1, Çankaya, Ankara, 06800, Turkey; Yıldırım S.Ö., Middle East Technical University, Dumlupınar Blv. No:1, Çankaya, Ankara, 06800, Turkey","Rapid growth of online shopping activities in recent years has required careful identifications of key factors influencing consumers’ behaviors and attitudes toward online shopping. Identifying critical factors influencing online consumer behavior is very crucial for effective customer relationship management. It is very important that online sellers clearly understand critical factors influencing online customers’ shopping intention and take necessary actions accordingly. If identified and managed properly, those critical factors can provide competitive advantage to online sellers and also increase consumers’ satisfaction level and experiences with sellers’ website. This research investigated the attitudes toward online shopping of university students in Ankara, Turkey. Internet users’ interest, evaluation, trust, intention and concerns toward online shopping were assessed by conducting survey type research. Internet users’ concerns toward online shopping were assessed by considering financial issues, product quality issues, refund issues, product delivery issues, security issues and privacy issues. Findings of this study guide online retailers which factors to focus on in order to develop successful marketing strategies for online consumers. © 2014, © The Author(s) 2014.","business-to-consumer; consumer attitude; consumer behavior; e-commerce; Internet users; online shopping; Turkey",{"$nulls":7},"Alam S.S., Bakar Z., Ismail H.B., Ahsan M.N., Young consumers online shopping: an empirical study, Journal of Internet Business, 5, pp. 81-98, (2008); Almousa M., Perceived risk in apparel online shopping: A multi dimensional perspective, Canadian Social Science, 7, 2, pp. 23-31, (2011); Azjen I., The theory of planned behavior, Organizational Behavior and Human Decision Processes, 50, pp. 179-211, (1991); Bellman S., Lohse G.L., Johnson E.J., Predictors of online buying behavior, Communications of the ACM, 42, 12, pp. 32-38, (1999); Bhattacherjee A., Acceptance of e-commerce services: The case of electronic brokerages, IEEE Transactions on Systems, Man, and Cybernetics—Part A: Systems And Humans, 3, 4, pp. 411-420, (2000); Brown M., Pope N., Voges K., Buying or browsing? 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Teo T.S.H., Liu J., Consumer trust in e-commerce in the United States, Singapore and China, Omega, 35, 1, pp. 22-38, (2007); Udo G.J., Privacy and security concerns as major barriers for e-commerce: A survey study, Information Management and Computer Security, 9, 4, pp. 165-174, (2011); Yulihasri I.M.A., Daud K.A.K., Factors that influence customers’ buying intention on shopping online, International Journal of Marketing Studies, 3, 1, pp. 128-139, (2011)","F. Huseynov; Middle East Technical University, Çankaya, Ankara, Dumlupınar Blv. No:1, 06800, Turkey; email: farid.huseynov@metu.edu.tr",null,"SAGE Publications Ltd",{"$nulls":5},2666669.0,null,null,null,"English","Inf. Dev.","Article","Final",null,"Scopus","2-s2.0-84965097456"]
["Ruan J.; Shi Y.","Ruan, Junhu (25652148000); Shi, Yan (57357241400)","25652148000; 57357241400","Monitoring and assessing fruit freshness in IOT-based e-commerce delivery using scenario analysis and interval number approaches",2016.0,"Information Sciences",373.0,null,null,557.0,570.0,13.0,100.0,"10.1016/j.ins.2016.07.014","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84978924696&doi=10.1016%2fj.ins.2016.07.014&partnerID=40&md5=9c884f5a50676f16751391adf4f9b087","College of Economics and Management, Northwest A&F University, Yangling 712100, China; General Education Center, Tokai University, Kumamoto 862-8652, Japan; Faculty of Management and Economics, Dalian University of Technology, Dalian 116024, China","Ruan J., College of Economics and Management, Northwest A&F University, Yangling 712100, China, Faculty of Management and Economics, Dalian University of Technology, Dalian 116024, China; Shi Y., General Education Center, Tokai University, Kumamoto 862-8652, Japan, Faculty of Management and Economics, Dalian University of Technology, Dalian 116024, China","We are concerned with the monitoring and assessment of in-transit fruit freshness in e-commerce deliveries. After comparing the fulfillment processes of fresh fruit transportation in traditional retailing and e-retailing, we formulate an Internet of Things–based framework for monitoring fruit e-commerce deliveries. Based on the fulfillment operations and monitoring modules of the framework, we propose an approach based on a two-stage scenario for assessing the freshness of in-transit fruits. In the first stage, we use a learning-by-doing mechanism to develop a scenario construction method to automatically obtain the most appropriate delivery environment and the occurrence probability for each scenario. In the second stage, we integrate the interval comparison technique into the scenario analysis method to address the freshness assessment of in-transit fruits. The effectiveness and advantages of our approach are verified using numerical simulations. © 2016 Elsevier Inc.","Freshness assessment; Fruit e-commerce; Internet of Things; Interval number; Scenario analysis","Commerce; Electronic commerce; Internet; Internet of things; Delivery environment; Freshness assessment; Interval comparisons; Interval number; Monitoring and assessment; Occurrence probability; Scenario analysis; Scenario constructions; Fruits",{"$nulls":4},"China Ministry of Education Social Sciences and Humanities Research Youth Fund; Hong Kong Scholars Program Mainland-Hong Kong Joint Postdoctoral Fellows Program, (G-YZ87); National Natural Science Foundation of China, NSFC, (71471025, 71531002); Northwest A and F University, NWAFU, (2452015325); Natural Science Basic Research Program of Shaanxi Province, (2016JQ7005)","This research is supported by the National Natural Science Foundation of China (Nos. 71471025 and 71531002 ), the Hong Kong Scholars Program Mainland-Hong Kong Joint Postdoctoral Fellows Program (No. G-YZ87), the Doctoral Scientific Research Foundation of Northwest A&F University (No. 2452015325), the Natural Science Basic Research Project in Shaanxi Province (No. 2016JQ7005) and China Ministry of Education Social Sciences and Humanities Research Youth Fund Project titled as “Delivery Optimization of Maturity-Based Fruit B2C Ecommerce-Taking Shaanxi Kiwifruit as the Example”.","Abad E., Palacio F., Nuin M., de Zarate A.G., Juarros A., Gomez J.M., Marco S., RFID smart tag for traceability and cold chain monitoring of foods: Demonstration in an intercontinental fresh fish logistic chain, J. 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Part B Appl., 4, 5, pp. 1175-1181, (2013); Yin Y.Y., Shi P., Liu F., Teo K.L., Filtering for discrete-time nonhomogeneous markov jump systems with uncertainties, Inf. Sci., 259, pp. 118-127, (2014); Yoo C.W., Parameswaran S., Kishore R., Knowing about your food from the farm to the table: using information systems that reduce information asymmetry and health risks in retail contexts, Inf. Manag., 52, 6, pp. 692-709, (2015); Yu M., Nagurney A., Competitive food supply chain networks with application to fresh produce, Eur. J. Oper. Res., 224, 2, pp. 273-282, (2013); Zhang F., Ignatius J., Lim C.P., Zhao Y., A new method for deriving priority weights by extracting consistent numerical-valued matrices from interval-valued fuzzy judgement matrix, Inf. Sci., 279, pp. 280-300, (2014); Zhang S., Liu X., Wang J., Cao J., Min G., Energy-efficient active tag searching in large scale RFID systems, Inf. 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["Zhang M.; Pratap S.; Huang G.Q.; Zhao Z.","Zhang, Mengdi (56204508000); Pratap, Saurabh (56667217800); Huang, George Q. (7403425048); Zhao, Zhiheng (57192180873)","56204508000; 56667217800; 7403425048; 57192180873","Optimal collaborative transportation service trading in B2B e-commerce logistics",2017.0,"International Journal of Production Research",55.0,18.0,null,5485.0,5501.0,16.0,62.0,"10.1080/00207543.2017.1322731","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85018169204&doi=10.1080%2f00207543.2017.1322731&partnerID=40&md5=17bd68dcdcbf8ef1a598d5782b3871ec","HKU-ZIRI Lab for Physical Internet, Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong","Zhang M., HKU-ZIRI Lab for Physical Internet, Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong; Pratap S., HKU-ZIRI Lab for Physical Internet, Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong; Huang G.Q., HKU-ZIRI Lab for Physical Internet, Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong; Zhao Z., HKU-ZIRI Lab for Physical Internet, Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong","This paper investigates a less-than-truckload carrier collaboration decision-making problem in the e-commerce logistics network. E-commerce less-than-truckload carrier collaboration problem considers multiple logistics service providers (LSPs) forming a collaborative alliance in an e-commerce logistics network. They share their transportation requests and vehicle capabilities to maximise the total profit of the entire alliance, improve their vehicle utilisation and cope with fluctuations in demand. An e-commerce logistics trading system with collaborative decisions is designed. A collaborative transportation planning model is introduced to maximise the total profit without reducing the individual profit of the carriers with information sharing. A stochastic plant-pollinator algorithm is proposed for the problem and extensive computational experiments are conducted. The results show that the proposed plant-pollinated algorithm performs better than the genetic algorithm. Furthermore, the results illustrate that the higher degree of cooperation, the more benefits for carriers. Last but not least, since the increasing gasoline price leads to the decreasing margins for the small- and medium-sized LSPs. The results also show that it is critical for them to join in the alliance to survive in the competition. © 2017 Informa UK Limited, trading as Taylor & Francis Group.","carrier collaboration; E-commerce logistics; less-than-truckload; meta-heuristic; optimisation; system design; transportation planning","Decision making; Electronic commerce; Genetic algorithms; Logistics; Optimization; Profitability; Stochastic systems; Systems analysis; Transportation; Trucks; Carrier collaboration; Less-than-truckload; Metaheuristic; Optimisations; Transportation planning; Commerce",{"$nulls":6},"Agarwal R., Ergun O., Network Design and Allocation Mechanisms for Carrier Alliances in Liner Shipping, Operations Research, 58, 6, pp. 1726-1742, (2010); Barnhart C., Schneur R.R., Air Network Design for Express Shipment Service, Operations Research, 44, 6, pp. 852-863, (1996); Berger S., Bierwirth C., Solutions to the Request Reassignment Problem in Collaborative Carrier Networks, Transportation Research Part E: Logistics and Transportation Review, 46, 5, pp. 627-638, (2010); 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Lei M., Liu H., Deng H., Huang T., Leong G.K., Demand Information Sharing and Channel Choice in a Dual-channel Supply Chain with Multiple Retailers, International Journal of Production Research, 52, 22, pp. 6792-6818, (2014); Lin Y.-K., Huang C.-F., Yeh C.-T., Network Reliability with Deteriorating Product and Production Capacity through a Multi-State Delivery Network, International Journal of Production Research, 52, 22, pp. 6681-6694, (2014); Mogale D.G., Kumar S.K., Marquez F.P.G., Tiwari M.K., Bulk Wheat Transportation and Storage Problem of Public Distribution System, Computers & Industrial Engineering, 104, pp. 80-97, (2017); Oum T.H., Park J.-H., Kim K., Yu C., The Effect of Horizontal Alliances on Firm Productivity and Profitability: Evidence from the Global Airline Industry, Journal of Business Research, 57, 8, pp. 844-853, (2004); Ozener O.O., Ergun O., Savelsbergh M., Lane-exchange Mechanisms for Truckload Carrier Collaboration, Transportation Science, 45, 1, pp. 1-17, (2011); Pratap S., Kumar B.M., Saxena D., Tiwari M., Integrated Scheduling of Rake and Stockyard Management with Ship Berthing: A Block Based Evolutionary Algorithm, International Journal of Production Research, 54, 14, pp. 4182-4204, (2016); Salanova Grau J.M., Rusich A., Mitsakis E., Ukovich W., Fanti M.P., Aifadopoulou G., Nolich M., Scala E., Papadopoulos C., Evaluation Framework in Cooperative Intelligent Transport Systems (C-ITS) for Freight Transport: The Case of the CO-GISTICS Speed Advice Service, International Journal of Advanced Logistics, 5, 1, pp. 30-43, (2016); Suweis S., Simini F., Banavar J.R., Maritan A., Emergence of Structural and Dynamical Properties of Ecological Mutualistic Networks, Nature, 500, 7463, pp. 449-452, (2013); Talley W.K., Ng M., Maritime Transport Chain Choice by Carriers, Ports and Shippers, International Journal of Production Economics, 142, 2, pp. 311-316, (2013); Xu S.X., Huang G.Q., Cheng M., Truthful, Budget-balanced Bundle Double Auctions for Carrier Collaboration, Transportation Science, (2016); Yilmaz O., Savasaneril S., Collaboration among Small Shippers in a Transportation Market, European Journal of Operational Research, 218, 2, pp. 408-415, (2012); Zhang Y., Liu S., Liu Y., Li R., Smart Box-enabled Product–Service System for Cloud Logistics, International Journal of Production Research, 54, 2, pp. 6693-6706, (2016); Zhang M., Huang G.Q., Xu S.X., Zhao Z., Optimization Based Transportation Service Trading in B2B E-commerce Logistics, Journal of Intelligent Manufacturing, pp. 1-17; Zhao Z., Fang J., Huang G.Q., Zhang M., Location Management of Cloud Forklifts in Finished Product Warehouse, International Journal of Intelligent Systems, (2016)","S. Pratap; HKU-ZIRI Lab for Physical Internet, Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong; email: s.pratapiitkgp@gmail.com",null,"Taylor and Francis Ltd.",{"$nulls":5},207543.0,null,"IJPRB",null,"English","Int J Prod Res","Article","Final",null,"Scopus","2-s2.0-85018169204"]
["Chen Y.-Y.K.; Jaw Y.-L.; Wu B.-L.","Chen, Ying-Yu Kerri (57207352247); Jaw, Yi-Long (13605814300); Wu, Bing-Li (57075395300)","57207352247; 13605814300; 57075395300","Effect of digital transformation on organisational performance of SMEs: Evidence from the Taiwanese textile industry’s web portal",2016.0,"Internet Research",26.0,1.0,null,186.0,212.0,26.0,93.0,"10.1108/IntR-12-2013-0265","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84955487448&doi=10.1108%2fIntR-12-2013-0265&partnerID=40&md5=486f477859166a052d4f4bd97912bc8c","Department of International Business, National Dong Hwa University, Hualien, Taiwan; Department of International Business, National Taiwan University, Taipei, Taiwan; Graduate Institute of Interdisciplinary Legal Studies, College of Law, National Taiwan University, Taipei, Taiwan","Chen Y.-Y.K., Department of International Business, National Dong Hwa University, Hualien, Taiwan; Jaw Y.-L., Department of International Business, National Taiwan University, Taipei, Taiwan; Wu B.-L., Graduate Institute of Interdisciplinary Legal Studies, College of Law, National Taiwan University, Taipei, Taiwan","Purpose – The purpose of this paper is to examine the effect of the pilot implementation of an industry-specific web portal as an IT resource on textile SMEs organisational performance. Using a resource-based perspective, portal delivery functionalities, considered as non-physical IT resources, are analysed using the dimensions of portal usefulness, portal interface, and service-oriented portal functions on SMEs users’ perceived outcomes of organisational performance. Design/methodology/approach – Qualitative and quantitative approaches are used to explore the research hypotheses. Data were collected using field interviews and survey from senior executives of small- and medium-sized enterprises (SMEs) in the Taiwanese textile industry. Findings – Results indicate that the service-oriented portal function dimension, consisting of portal maintenance service, B2B function, and cloud computing, significantly influences organisational performance. Unexpected findings, such as the negative impact of greater industry benchmark information on perceived SME performance, deserve further investigation. Research limitations/implications – The study extends the theory and knowledge on the resource-based view and its implications on e-business organisational performance of SMEs. The study also offers findings relevant to the design of portal sites for SME administrators and information service providers. Limitations of the research include a small size and the industry-specific data limiting the generalisability of the findings. Practical implications – Research results practically serve as informative indicators for policy makers, information service providers, and SMEs executives to evaluate feasible elements for web portal design in traditional industry. Findings from this study may help portal service providers in designing better web portal functionalities for SMEs. Originality/value – This study contributes to the IT business value literature by identifying the linkages between industry-specific portal delivery functionalities and perceived organisational performance through the examination of portal usefulness, portal interface, and service-oriented portal function for textile SMEs. © 2016, Emerald Group Publishing Limited.","E-commerce; Information services; International business",{"$nulls":7},"Albors-Garrigos J., Hervas-Oliver J.L., Marquex P., Internet and mature industries. Its role in the creation of value in the supply chain. 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Chen; Department of International Business, National Dong Hwa University, Hualien, Taiwan; email: kc615486@gmail.com",null,"Emerald Group Publishing Ltd.",{"$nulls":5},1.0662243E7,null,null,null,"English","Internet Res.","Article","Final",null,"Scopus","2-s2.0-84955487448"]
["He J.","He, Jie (57203345047)",5.7203345047E10,"Decision-making model of e-commerce logistics based on the analytic hierarchy process",2017.0,"Agro Food Industry Hi-Tech",28.0,1.0,null,2062.0,2066.0,4.0,0.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85020921349&partnerID=40&md5=e67b37fb44b32ebea44f53293ce4a923","School of Economics and Management, Pingdingshan University, Pingdingshan, 46700, China","He J., School of Economics and Management, Pingdingshan University, Pingdingshan, 46700, China","This study aims to examine the decision-making model of e-commerce logistics based on analytic hierarchy process (AHP). Through an actual case, the importance of logistics optimization is presented in the basic analysis and introduction. Therefore, a case study of a decision-making model of e-commerce logistics is conducted in this study, and the AHP is used to assess the quality and efficiency of this model. Results of the experiment study of the case show that the proposed method can substantially improve the overall performance.","Analytic hierarchy process; Decision making model; E-commerce logistics","Analytic hierarchy process; Commerce; Decision making; Electronic commerce; Hierarchical systems; Analytic hierarchy process (ahp); Decision making models; Experiment study; Logistics optimization; Analytical models",{"$nulls":6},"Garcia J.L., Alvarado A., Blanco J., Et al., Multi-attribute evaluation and selection of sites for agricultural product warehouses based on an Analytic Hierarchy Process, Computers & Electronics in Agriculture, 100, 1, pp. 60-69, (2014); Kahraman C., Oztaysi B., Ucal Sari I., Et al., Fuzzy analytic hierarchy process with interval type-2 fuzzy sets, Knowledge-based Systems, 59, 2, pp. 48-57, (2014); Chen T., Jin Y., Qiu X., Et al., A hybrid fuzzy evaluation method for safety assessment of food-waste feed based on entropy and the analytic hierarchy process methods, Expert Systems with Applications, 41, 16, pp. 7328-7337, (2014); Charles C., Gafni A., Whelan T., Decision-making in the physicianpatient encounter, revisiting the shared treatment decision-making model, Social Science & Medicine, 49, 5, pp. 651-661, (1999); Van D.K.G., Van Heck E., De Vries H.J., Et al., Supporting decision making in technology standards battles based on a fuzzy analytic hierarchy process, IEEE Transactions on Engineering Management, 61, 2, pp. 336-348, (2014); Jiang L., Wang J., Ye S., Et al., Application of group analytical hierarchy process on e-commerce performance evaluation considering expert weight, International Journal of Hybrid Information Technology, 7, 3, pp. 78-82, (2014); Sun X., E-commerce logistics distribution mode analysis and decision, Applied Mechanics & Materials, 744-746, pp. 1873-1877, (2015); Xue Y.L., Lv T.-J., Qi J.-Y., Et al., E-commerce operation under complex network based on analytic hierarchy process-An empirical study of Dianping.com, Journal of Beijing University of Posts & Telecommunications, 2, 1, pp. 52-59, (2014); Wang H.W., Yan Y.S., Duan H.W., Measuring the performance of e-commerce logistics system based on fuzzy-AHP, Applied Mechanics & Materials, 505-506, pp. 898-901, (2014); Xu T., E-commerce risk analysis with fuzzy analytic hierarchy process, Applied Mechanics & Materials, 571-572, pp. 1129-1132, (2014); Ye H., Wu J., Selection of a logistics service provider based on analytic hierarchy process (AHP) approach, A case study of Swedish Coffee Manufacturer-Gevalia, Department of Industrial Development It & Land Management, 3, 8, pp. 78-82, (2014); Liu B., Study on logistics park based on fuzzy analytic hierarchy process, Logistics Park Ahp Fuzzy Comprehensive Evaluation, 6, 8, pp. 12-16, (2014); Ding H.P., Yang H.L., PEST analysis of Anhui environmental logistics based on analytic hierarchy process, Journal of Kaili University, 79, 3, pp. 81-85, (2016)",null,null,"TeknoScienze",{"$nulls":5},1.7226996E7,null,null,null,"English","Agro Food Ind. Hi-Tech","Article","Final",null,"Scopus","2-s2.0-85020921349"]
["Wang Y.; Zhang D.; Liu Q.; Shen F.; Lee L.H.","Wang, Yuan (57079310600); Zhang, Dongxiang (34267886900); Liu, Qing (57043696100); Shen, Fumin (55272525500); Lee, Loo Hay (55667526300)","57079310600; 34267886900; 57043696100; 55272525500; 55667526300","Towards enhancing the last-mile delivery: An effective crowd-tasking model with scalable solutions",2016.0,"Transportation Research Part E: Logistics and Transportation Review",93.0,null,null,279.0,293.0,14.0,237.0,"10.1016/j.tre.2016.06.002","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84976433839&doi=10.1016%2fj.tre.2016.06.002&partnerID=40&md5=d4dc954b45eebca5d38b5bcf44fad54f","Department of Industrial and Systems Engineering, National University of Singapore, Singapore, 119260, Singapore; Department of Computer Science, School of Computing, National University of Singapore, 117417, Singapore; School of Computer Science and Engineering, University of Electronic Science and Technology of China, China","Wang Y., Department of Industrial and Systems Engineering, National University of Singapore, Singapore, 119260, Singapore; Zhang D., School of Computer Science and Engineering, University of Electronic Science and Technology of China, China; Liu Q., Department of Computer Science, School of Computing, National University of Singapore, 117417, Singapore; Shen F., School of Computer Science and Engineering, University of Electronic Science and Technology of China, China; Lee L.H., Department of Industrial and Systems Engineering, National University of Singapore, Singapore, 119260, Singapore","In urban logistics, the last-mile delivery from the warehouse to the consumer's home has become more and more challenging with the continuous growth of E-commerce. It requires elaborate planning and scheduling to minimize the global traveling cost, but often results in unattended delivery as most consumers are away from home. In this paper, we propose an effective large-scale mobile crowd-tasking model in which a large pool of citizen workers are used to perform the last-mile delivery. To efficiently solve the model, we formulate it as a network min-cost flow problem and propose various pruning techniques that can dramatically reduce the network size. Comprehensive experiments were conducted with Singapore and Beijing datasets. The results show that our solution can support real-time delivery optimization in the large-scale mobile crowd-sourcing problem. © 2016 Elsevier Ltd.","Crowdsourcing; Last-mile delivery; Minimum cost flow","Beijing [China]; China; Singapore [Southeast Asia]; Urban growth; Cost flow; Flow problems; Large-scales; Last mile; Last-mile delivery; Minimum cost flows; Planning and scheduling; Scalable solution; Urban logistics; Workers'; electronic commerce; numerical model; optimization; transportation planning; travel behavior; travel time; urban planning; urban transport; Costs",{"$nulls":6},"Ahuja R.K., Magnanti T.L., Orlin J.B., Network Flows - Theory, Algorithms and Applications, (1993); Benouaret K., Valliyur-Ramalingam R., Charoy F., Crowdsc: building smart cities with large-scale citizen participation, IEEE Internet Comput., 17, 6, pp. 57-63, (2013); Chen C., Cheng S., Gunawan A., Misra A., Dasgupta K., Chander D., TRACCS: a framework for trajectory-aware coordinated urban crowd-sourcing, Proceedings of the Second AAAI Conference on Human Computation and Crowdsourcing, (2014); Chen Z., Fu R., Zhao Z., Liu Z., Xia L., Chen L., Cheng P., Cao C.C., Tong Y., Zhang C.J., Gmission: a general spatial crowdsourcing platform, Proc. VLDB Endow., 7, 13, pp. 1629-1632, (2014); Cheng P., Lian X., Chen Z., Fu R., Chen L., Han J., Zhao J., Reliable diversity-based spatial crowdsourcing by moving workers, PVLDB, 8, 10, pp. 1022-1033, (2015); Dantzig G.B., Ramser J.H., The truck dispatching problem, Manage. Sci., 6, pp. 80-91, (1959); de Souza R., Goh M., Lau H.-C., Ng W.-S., Tan P.-S., Collaborative urban logistics ĺc synchronizing the last mile a singapore research perspective, Procedia - Social Behav. Sci., 125, pp. 422-431, (2014); DellaAmico M., Hadjidimitriou S., Innovative logistics model and containers solution for efficient last mile delivery, Procedia - Social Behav. 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Bull., 37, 4, pp. 3-14, (2014); Kazemi L., Shahabi C., Geocrowd: enabling query answering with spatial crowdsourcing, SIGSPATIAL '12, pp. 189-198, (2012); Kennington J.L., Helgason R.V., Algorithms for Network Programming, (1980); Kiraly Z., Kovacs P., Efficient implementations of minimum-cost flow algorithms, CoRR, abs/1207.6381, (2012); Liakos P., Delis A., An interactive freight-pooling service for efficient last-mile delivery, 2015 16th IEEE International Conference on Mobile Data Management (MDM), 2, pp. 23-25, (2015); Petrovic O., Harnisch M., Puchleitner T., Opportunities of mobile communication systems for applications in last-mile logistics, 2013 International Conference on Advanced Logistics and Transport (ICALT), pp. 354-359, (2013); Pournajaf L., Xiong L., Sunderam V.S., Goryczka S., Spatial task assignment for crowd sensing with cloaked locations, IEEE 15th International Conference on Mobile Data Management, MDM 2014, 1, pp. 73-82, (2014); Su H., Zheng K., Huang J., Jeung H., Chen L., Zhou X., Crowdplanner: a crowd-based route recommendation system, ICDE, pp. 1144-1155, (2014); Zhang C.J., Tong Y., Chen L., Where to: crowd-aided path selection, PVLDB, 7, 14, pp. 2005-2016, (2014); Zheng Y., Zhang L., Xie X., Ma W., Mining interesting locations and travel sequences from GPS trajectories, pp. 791-800, (2009)","D. Zhang; School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan, No. 2006, Xi Yuan Road, 611731, China; email: zhangdongxiang37@gmail.com",null,"Elsevier Ltd",{"$nulls":5},1.3665545E7,null,null,null,"English","Transp. Res. Part E Logist. Transp. Rev.","Article","Final",null,"Scopus","2-s2.0-84976433839"]
["Zhou L.; Wang X.; Ni L.; Lin Y.","Zhou, Lin (57868712000); Wang, Xu (55951735500); Ni, Lin (56207926300); Lin, Yun (36655835400)","57868712000; 55951735500; 56207926300; 36655835400","Location-routing problem with simultaneous home delivery and customer's pickup for city distribution of online shopping purchases",2016.0,"Sustainability (Switzerland)",8.0,8.0,828.0,null,null,null,56.0,"10.3390/su8080828","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84983740462&doi=10.3390%2fsu8080828&partnerID=40&md5=2a901eaeaada53a658ea87ff280c5301","College of Mechanical Engineering, Chongqing University, Chongqing, 400030, China; Chongqing Key Laboratory of Logistics, Chongqing University, Chongqing, 400030, China; State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing, 400030, China","Zhou L., College of Mechanical Engineering, Chongqing University, Chongqing, 400030, China; Wang X., Chongqing Key Laboratory of Logistics, Chongqing University, Chongqing, 400030, China, State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing, 400030, China; Ni L., College of Mechanical Engineering, Chongqing University, Chongqing, 400030, China, Chongqing Key Laboratory of Logistics, Chongqing University, Chongqing, 400030, China; Lin Y., College of Mechanical Engineering, Chongqing University, Chongqing, 400030, China, Chongqing Key Laboratory of Logistics, Chongqing University, Chongqing, 400030, China","With the increasing interest in online shopping, the Last Mile delivery is regarded as one of the most expensive and pollutive-and yet the least efficient-stages of the e-commerce supply chain. To address this challenge, a novel location-routing problem with simultaneous home delivery and customer's pickup is proposed. This problem aims to build a more effective Last Mile distribution system by providing two kinds of service options when delivering packages to customers. To solve this specific problem, a hybrid evolution search algorithm by combining genetic algorithm (GA) and local search (LS) is presented. In this approach, a diverse population generation algorithm along with a two-phase solution initialization heuristic is first proposed to give high quality initial population. Then, advantaged solution representation, individual evaluation, crossover and mutation operations are designed to enhance the evolution and search efficiency. Computational experiments based on a large family of instances are conducted, and the results obtained indicate the validity of the proposed model and method. © 2016 by the authors; licensee MDPI, Basel, Switzerland.","Genetic algorithm; Location-routing problem; Simultaneous home delivery and customer's pickup","distribution system; electronic commerce; genetic algorithm; Internet; location decision; service provision; shopping activity; supply chain management",{"$nulls":6},"China's E-Commerce Report 2015; Gevaers R., Van de Voorde E., Vanelslander T., Characteristics of innovations in last-mile logistics-Using best practices, case studies and making the link with green and sustainable logistics, Proceedings of the European Transport Conference, (2009); Esper T.L., Jensen T.D., Turnipseed F.L., Burton S., The last mile: An examination of effects of online retail delivery strategies on consumers, J. Bus. Logist, 24, pp. 177-203, (2003); Aized T., Srai J.S., Hierarchical modelling of Last Mile logistic distribution system, Int. J. Adv. Manuf. Technol, 70, pp. 1053-1061, (2014); Wang X., Zhan L., Ruan J., Zhang J., How to choose \"Last Mile\" delivery modes for E-fulfillment, Math. Probl. Eng, 2014, (2014); Agatz N.A., Fleischmann M., Van Nunen J.A., E-fulfillment and multi-channel distribution-A review, Eur. J. Oper. Res, 187, pp. 339-356, (2008); Gevaers R., Van de Voorde E., Vanelslander T., Cost Modelling and Simulation of Last-mile Characteristics in an Innovative B2C Supply Chain Environment with Implications on Urban Areas and Cities, Procedia Soc. Behav. Sci, 125, pp. 398-411, (2014); Boyer K.K., Prud'homme A.M., Chung W., The last mile challenge: Evaluating the effects of customer density and delivery window patterns, J. Bus. Logist, 30, pp. 185-201, (2009); Hayel Y., Quadri D., Jimenez T., Brotcorne L., Decentralized optimization of last-mile delivery services with non-cooperative bounded rational customers, Ann. Oper. Res, 239, pp. 451-469, (2016); Lopes R.B., Ferreira C., Santos B.S., Barreto S., A taxonomical analysis, current methods and objectives on location-routing problems, Int. Trans. Oper. Res, 20, pp. 795-822, (2013); Prodhon C., Prins C., A survey of recent research on location-routing problems, Eur. J. Oper. Res, 238, pp. 1-17, (2014); Drexl M., Schneider M., A survey of variants and extensions of the location-routing problem, Eur. J. Oper. Res, 241, pp. 283-308, (2015); Vincent F.Y., Lin S.-Y., A simulated annealing heuristic for the open location-routing problem, Comput. Oper. Res, 62, pp. 184-196, (2015); Ponboon S., Qureshi A.G., Taniguchi E., Branch-and-price algorithm for the location-routing problem with time windows, Transp. Res. E Logist. Transp. Rev, 86, pp. 1-19, (2016); Govindan K., Jafarian A., Khodaverdi R., Devika K., Two-echelon multiple-vehicle location-routing problem with time windows for optimization of sustainable supply chain network of perishable food, Int. J. Prod. Econ, 152, pp. 9-28, (2014); Wang H., Du L., Ma S., Multi-objective open location-routing model with split delivery for optimized relief distribution in post-earthquake, Transp. Res. E Logist. Transp. Rev, 69, pp. 160-179, (2014); Stenger A., Schneider M., Schwind M., Vigo D., Location routing for small package shippers with subcontracting options, Int. J. Prod. Econ, 140, pp. 702-712, (2012); Karaoglan I., Altiparmak F., Kara I., Dengiz B., The location-routing problem with simultaneous pickup and delivery: Formulations and a heuristic approach, Omega, 40, pp. 465-477, (2012); Rieck J., Ehrenberg C., Zimmermann J., Many-to-many location-routing with inter-hub transport and multi-commodity pickup-and-delivery, Eur. J. Oper. Res, 236, pp. 863-878, (2014); Rahmani Y., Cherif-Khettaf W.R., Oulamara A., A local search approach for the two-echelon multi-products location-routing problem with pickup and delivery, IFAC-PapersOnLine, 48, pp. 193-199, (2015); Vincent F.Y., Lin S.-W., Multi-start simulated annealing heuristic for the location routing problem with simultaneous pickup and delivery, Appl. Soft Comput, 24, pp. 284-290, (2014); Rahmani Y., Ramdane Cherif-Khettaf W., Oulamara A., The two-echelon multi-products location-routing problem with pickup and delivery: Formulation and heuristic approaches, Int. J. Prod. Res, 54, pp. 1-21, (2015); Gianessi P., Alfandari L., Letocart L., Wolfler Calvo R., The multicommodity-ring location routing problem, Transp. Sci, 50, pp. 541-558, (2015); Prodhon C., Prins C., A memetic algorithm with population management (MA|PM) for the periodic location-routing problem, Hybrid Metaheuristics, pp. 43-57, (2008); Klibi W., Lasalle F., Martel A., Ichoua S., The stochastic multiperiod location transportation problem, Transp. Sci, 44, pp. 221-237, (2010); Guerrero W.J., Prodhon C., Velasco N., Amaya C.A., Hybrid heuristic for the inventory location-routing problem with deterministic demand, Int. J. Prod. Econ, 146, pp. 359-370, (2013); Rath S., Gutjahr W.J., A math-heuristic for the warehouse location-routing problem in disaster relief, Comput. Oper. Res, 42, pp. 25-39, (2014); Tang J., Ji S., Jiang L., The Design of a sustainable location-routing-inventory model considering consumer environmental behavior, Sustainability, 8, (2016); Contardo C., Hemmelmayr V., Crainic T.G., Lower and upper bounds for the two-echelon capacitated location-routing problem, Comput. Oper. Res, 39, pp. 3185-3199, (2012); Nguyen V.-P., Prins C., Prodhon C., Solving the two-echelon location routing problem by a GRASP reinforced by a learning process and path relinking, Eur. J. Oper. Res, 216, pp. 113-126, (2012); Nguyen V.-P., Prins C., Prodhon C., A multi-start iterated local search with tabu list and path relinking for the two-echelon location-routing problem, Eng. Appl. Artif. Intell, 25, pp. 56-71, (2012); Ting C.-J., Chen C.-H., A multiple ant colony optimization algorithm for the capacitated location routing problem, Int. J. Prod. Econ, 141, pp. 34-44, (2013); Ardjmand E., Weckman G., Park N., Taherkhani P., Singh M., Applying genetic algorithm to a new location and routing model of hazardous materials, Int. J. Prod. Res, 53, pp. 916-928, (2015); Ardjmand E., Young W.A., Weckman G.R., Bajgiran O.S., Aminipour B., Park N., Applying genetic algorithm to a new bi-objective stochastic model for transportation, location, and allocation of hazardous materials, Expert Syst. Appl, 51, pp. 49-58, (2016); Vincent F.Y., Lin S.-W., Lee W., Ting C.-J., A simulated annealing heuristic for the capacitated location routing problem, Comput. Ind. Eng, 58, pp. 288-299, (2010); Duhamel C., Lacomme P., Prins C., Prodhon C., A GRASP× ELS approach for the capacitated locationrouting problem, Comput. Oper. Res, 37, pp. 1912-1923, (2010); Escobar J.W., Linfati R., Toth P., A two-phase hybrid heuristic algorithm for the capacitated location-routing problem, Comput. Oper. Res, 40, pp. 70-79, (2013); Escobar J.W., Linfati R., Baldoquin M.G., Toth P., A Granular Variable Tabu Neighborhood Search for the capacitated location-routing problem, Transp. Res. B Methodol, 67, pp. 344-356, (2014); Prins C., Prodhon C., Calvo R.W., A memetic algorithm with population management (MA|PM) for the capacitated location-routing problem. Evolutionary Computation in Combinatorial Optimization, Proceedings of the 6th European Conference, EvoCOP 2006, pp. 183-194, (2006); Derbel H., Jarboui B., Hanafi S., Chabchoub H., Genetic algorithm with iterated local search for solving a location-routing problem, Expert. Syst. Appl, 39, pp. 2865-2871, (2012); Montoya-Torres J.R., Lopez Franco J., Nieto Isaza S., Felizzola Jimenez H., Herazo-Padilla N., A literature review on the vehicle routing problem with multiple depots, Comput. Ind. Eng, 79, pp. 115-129, (2015); Marinakis Y., Marinaki M., A bilevel genetic algorithm for a real life location routing problem, Int. J. Logist. Res. Appl, 11, pp. 49-65, (2008); Lopes R.B., Ferreira C., Santos B.S., A simple and effective evolutionary algorithm for the capacitated location-routing problem, Comput. Oper. Res, 70, pp. 155-162, (2016); Lin S., Kernighan B.W., An effective heuristic algorithm for the traveling-salesman problem, Oper. Res, 21, pp. 498-516, (1973); Prins C., A simple and effective evolutionary algorithm for the vehicle routing problem, Comput. Oper. Res, 31, pp. 1985-2002, (2004); Vidal T., Crainic T.G., Gendreau M., Lahrichi N., Rei W., A hybrid genetic algorithm for multidepot and periodic vehicle routing problems, Oper. Res, 60, pp. 611-624, (2012); Ahmadizar F., Zeynivand M., Arkat J., Two-level vehicle routing with cross-docking in a three-echelon supply chain: A genetic algorithm approach, Appl. Math. Model, 39, pp. 7065-7081, (2015); Toth P., Vigo D., The granular tabu search and its application to the vehicle-routing problem, Inf. J. Comput, 15, pp. 333-346, (2003); Prins C., Prodhon C., Calvo R.W., Solving the capacitated location-routing problem by a GRASP complemented by a learning process and a path relinking, 4OR, 4, pp. 221-238, (2006); Prins C., Prodhon C., Ruiz A., Soriano P., Wolfler Calvo R., Solving the capacitated location-routing problem by a cooperative Lagrangean relaxation-granular tabu search heuristic, Transp. Sci, 41, pp. 470-483, (2007); Hemmelmayr V.C., Cordeau J.-F., Crainic T.G., An adaptive large neighborhood search heuristic for two-echelon vehicle routing problems arising in city logistics, Comput. Oper. Res, 39, pp. 3215-3228, (2012); Contardo C., Cordeau J.-F., Gendron B., An exact algorithm based on cut-and-column generation for the capacitated location-routing problem, INFORMS J. Comput, 26, pp. 88-102, (2013)","X. Wang; Chongqing Key Laboratory of Logistics, Chongqing University, Chongqing, 400030, China; email: wx921@163.com",null,"MDPI",{"$nulls":5},2.071105E7,null,null,null,"English","Sustainability","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-84983740462"]
["Mergel I.","Mergel, Ines (16646443600)",1.66464436E10,"Agile innovation management in government: A research agenda",2016.0,"Government Information Quarterly",33.0,3.0,null,516.0,523.0,7.0,102.0,"10.1016/j.giq.2016.07.004","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84991826592&doi=10.1016%2fj.giq.2016.07.004&partnerID=40&md5=3f73a7d9a48a3973109fffe7051ce05f","University of Konstanz, Germany","Mergel I., University of Konstanz, Germany","Governments are facing an information technology upgrade and legacy problem: outdated systems and acquisition processes are resulting in high-risk technology projects that are either over budget or behind schedule. Recent catastrophic technology failures, such as the failed launch of the politically contested online marketplace Healthcare.gov in the U.S. were attributed to an overreliance on external technology contractors and failures to manage large-scale technology contracts in government. As a response, agile software development and modular acquisition approaches, new independent organizational units equipped with fast reacting teams, in combination with a series of policy changes are developed to address the need to innovate digital service delivery in government. This article uses a process tracing approach, as well as initial qualitative interviews with a subset of executives and agency-level digital services members to provide an overview of the existing policies and implementation approaches toward an agile innovation management approach. The article then provides a research framework including research questions that provide guidance for future research on the managerial implementation considerations necessary to scale up the initial efforts and move toward a collaborative and agile innovation management approach in government. © 2016","Agile development; Agile government; Agility; Digital service delivery; Innovation",{"$nulls":7},"Agile Manifesto, Manifesto for agile software development, (2001); Amazon.com., Diego Piacentini: He will take a two-year leave to head the Italian Prime Minister's digital technology office, (2016); Anthopoulos L., Reddick C.G., Giannakidou I., Mavridis N., Why e-government projects fail? An analysis of the healthcare.gov website, Government Information Quarterly, 33, 1, pp. 161-173, (2016); Balter B.J., Toward a more agile government: The case for rebooting federal IT procurement, Public Contract Law Journal, 41, 1, pp. 151-171, (2011); Bertot J., Estevez E., Janowski T., Digital public service innovation: Framework proposal, ICEGOV2016, Montevideo, Uruguay, March 1–3, 2016, (2016); Blasc A., Jung O.S., Lakhani K.R., Motivating effort in contributing to public goods inside organizations: Field experimental evidence, (2016); Boehm B., Turner R., Management challenges to implementing agile processes in traditional development organizations, IEEE Software September/October:30–39, (2005); Broadus W., The challenges of being agile in DoD, Defense AT&L January–February:5–9, (2013); Budhathoki N.R., Haythornthwaite C., Motivation for open collaboration crowd and community models and the case of OpenStreetMap, American Behavioral Scientist, 57, 5, pp. 548-575, (2013); Christy A., Government goes agile, Stanford Social Innovation Review Spring, 2016, (2016); Cockburn A., Learning from agile software development – Part one, The Journal of Defense Software Engineering, 15, 10, pp. 10-14, (2002); Collier D., Understanding process tracing, PS: Political Science and Politics, 44, 4, pp. 823-830, (2011); Committee on Oversight and Government Reform, 18F and U.S. digital services oversight, Congressional hearing, (2016); Crowston K., Wei K., Howison J., Wiggins A., Free/libre open-source software development: What we know and what we do not know, ACM Computing Surveys (CSUR), 44, 2, (2012); Department of Defense Appropriations Act, H.R.3326 111th Congress (2009), (2010); Drever E., Using Semi-Structured Interviews in Small-Scale Research: A Teacher's Guide, (1995); Dullemond K., van Gameren B., van Solingen R., How technological support can enable advantages of agile software development in a GSE setting, Fourth IEEE International Conference on Global Software Engineering, (2009); Dunleavy P., Margetts H., Design principles for essentially digital governance, 111th Annual Meeting of the American Political Science Association, San Francisco, 3–6 September 2015, (2015); Dunleavy P., Margetts H., Bastow S., Tinkler J., New public management is dead - Long live digital-era governance, Journal of Public Administration Review and Theory, 16, pp. 467-494, (2005); Fowler M., Highsmith J., The Agile Manifesto, (2001); Fulgham C., Johnson J., Crandall M., Jackson L., Burrows N., The FBI gets agile, ITProfessional, 13, 5, pp. 57-59, (2011); Gagne M., Deci E.L., Self-determination theory and work motivation, Journal of Organizational Behavior, 26, 4, pp. 331-362, (2005); GAO, Software development: Effective practices and federal challenges in applying agile methods, Report to the Subcommittee on Federal Financial Management, Government Information, Federal Services, and International Security, Committee on Homeland Security and Governmental Affairs United States Senate, (2012); GAO, Leveraging best practices to help ensure successful major acquisitions, Information technology, (2013); GAO, HEALTHCARE.GOV: Contract planning and oversight practices were ineffective given the challenges and risks, (2014); GAO, Information technology: Additional actions and oversight urgently needed to reduce waste and improve performance in acquisitions and operations, GAO-15-675T, (2015); Goldman S.L., Preiss K., Agile competitors and virtual organizations: Strategies for enriching the customer, (1994); Grant A.M., Relational job design and the motivation to make a prosocial difference, Academy of Management Review, 32, 2, pp. 393-417, (2007); Janssen M., van der Voort H., Adaptive governance: Towards a stable, accountable and responsive government, Government Information Quarterly, 33, 1, pp. 1-5, (2016); Jeffreis A., Why the government unpublished the source code for Healthcare, (2013); Lapham M.A., DoD agile adoption: Necessary considerations, concerns, and changes, CROSSTALK - The Journal of Defense Software Engineering January/February:31–35, (2012); Leetaru K., System failure: What I've learned as a data scientist in Washington, Forbes, (2016); Margetts H., Dunleavy P., The second wave of digital-era governance: A quasi-paradigm for government on the web, Philosophical Transactions of the Royal Society, (2013); Martin R.C., Agile software development: Principles, patterns, and practices, Alan Apt series, (2003); Mergel I., Open collaboration in the public sector: The case of social coding on github, Government Information Quarterly, 32, 4, pp. 464-472, (2015); Office of Management and Budget, Implementing Executive Order 13571 on streamlining service delivery and improving customer service, (2011); Raymonds E.S., The Cathedral and the Bazaar: Musings on Linux and Open Source, (1999); Read R.L., Don't ask for permission to use agile, Just start doing it. NextGov, (2016); Riby D., Sutherland J., Understanding agile management, Harvard Business Review, (2016); Rigby D.K., Sutherland J., Takeuchi H., Embracing agile, Harvard Business Review, (2016); Rigby D.K., Sutherland J., Takeuchi H., The secret history of agile innovation, Harvard Business Review, (2016); Royce W., Managing the development of large software systems, (1970); Ryan K., Ali A., The new government leader: Mobilizing agile public leadership in disruptive times, A GovLab report, (2016); Schumpeter J.A., Economic theory and entrepreneurial history, reprinted from change and the entrepreneur, Essays on entrepreneurs, innovations, business cycles, and the evolution of capitalism, (1949); Scott T., “Title.” The White House: What is Happening, (2016); Shaikh M., Negotiating open source software adoption in the UK public sector, Government Information Quarterly, 33, pp. 115-132, (2016); Strauss A., Corbin J., Basics of qualitative research: Techniques and procedures for developing grounded theory, (1998); Surdu J., Parsons D.J., Army simulation program balances agile and traditional methods with success, CROSSTALK - The Journal of Defense Software Engineering April:4–8, (2006); Sutherland J., “Title.” Scrum Blog, (2012); Takeuchi H., Nonaka I., The new. New product development game, Harvard Business Review, 64, 1, pp. 137-146, (1986); The White House, Executive order 13571–streamlining service delivery and improving customer service, Executive order 13571, (2011); The White House. 2012a. Contracting guidance to support modular development. In Procurement, edited by Office of Management and Budget. (Washington, DC).; The White House, Digital government: Building a 21st century platform to better serve the American people, (2012); The White House, Presidential memorandum — Building a 21st century digital government, (2012); The White House, Executive order — Presidential Innovation Fellows Program, (2015); Torgovnick M.K., What happens when you disrupt the White House: Haley Van Dyck speaks at TED2016, Live from TED2016, (2016); U.S. DoD, Secretary of defense speech: Drell lecture: “Rewiring the Pentagon: Charing a new path on innovation and cybersecurity”, (2015); UK.gov., Government digital service, (2016); USDS, U.S. digital services playbook, (2015); USDS, The TechFAR handbook, (2016)",null,null,"Elsevier Ltd",{"$nulls":5},"0740624X",null,"GIQUE",null,"English","Gov. Inf. Q.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-84991826592"]
["Chung J.; Choi B.","Chung, Jibok (7404002381); Choi, Byungcheon (11539931400)","7404002381; 11539931400","Complexity and algorithms for optimal bundle search problem with pairwise discount",2017.0,"Journal of Distribution Science",15.0,7.0,null,35.0,41.0,6.0,1.0,"10.15722/jds.15.7.201707.35","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85028051077&doi=10.15722%2fjds.15.7.201707.35&partnerID=40&md5=3457e41761adfe1c358cb3f073876393","Department of Retail Management, Kongju National University, South Korea; School of Business, Chungnam National University, South Korea","Chung J., Department of Retail Management, Kongju National University, South Korea; Choi B., School of Business, Chungnam National University, South Korea","Purpose - A product bundling is a marketing approach where multiple products or components are packaged together into one bundle solution. This paper aims to introduce an optimal bundle search problem (hereinafter called \"OBSP\") which may be embedded with online recommendation system to provide an optimized service considering pairwise discount and delivery cost. Research design, data, and methodology - Online retailers have their own discount policy and it is time consuming for online shoppers to find an optimal bundle. Unlike an online system recommending one item for each search, the OBSP considers multiple items for each search. We propose a mathematical formulation with numerical example for the OBSP and analyzed the complexity of the problem. Results - We provide two results from the complexity analysis. In general case, the OBSP belongs to strongly NP-Hard which means the difficulty of the problem while the special case of OBSP can be solved within polynomial time by transforming the OBSP into the minimum weighted perfect matching problem. Conclusions - In this paper, we propose the OBSP to provide a customized service considering bundling price and delivery cost. The results of research will be embedded with an online recommendation system to help customers for easy and smart online shopping.","Bundle search problem; Internet shopping optimization problem; Online shopping recommendation; Perfect matching problem",{"$nulls":5},"Kongju National University, KNU; Ministry of Education, MOE; National Research Foundation of Korea, NRF, (NRF-2016S1A5A2A01023036)","This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2016S1A5A2A01023036). This work was also supported by the research grant of the Kongju National University Fund in 2017.","Beladev M., Rokach L., Shapira B., Recommender Systems for Product Bundling, Knowledge Based Systems, 111, pp. 193-206, (2016); Blazewicz J., Kovalyov M., Musial J., Urbanski A., Wojciechowski A., Internet Shopping Optimization Problem, International Journal of Applied Mathematics and Computer Science, 20, 2, pp. 385-390, (2010); Ernst R., Kouvelis P., The Effects of Selling Packaged Goods on Inventory Decisions, Management Science, 45, 8, pp. 1142-1155, (1999); Garey M.R., Johnson D.S., Computers and Intractability: A Guide to the Theory of NP-Completeness, (1979); Garfinkel R., Gopal R., Tripathi A., Yin F., Design of a Shopbot and Recommender System for Bundle Purchases, Decision Support Systems, 42, 3, pp. 1974-1986, (2006); He L., Ioerger T.R., Combining Bundle Search with Buyer Coalition Formation in Electronic Markets, (2004); Jedidi K., Jagpal S., Manchanda P., Measuring Heterogeneous Reservation Prices for Product Bundles, Marketing Science, 22, 1, pp. 107-130, (2003); Jeong D.Y., An Object-Oriented Case-Base Design and Similarity Measures for Bundle Products Recommendation Systems, Journal of intelligent information systems, 9, 1, pp. 23-51, (2003); Jiang Y., Shang J., Kemerer C.F., Liu Y., Optimizing E-tailer Profits and Customer Savings: Pricing Multistage Customized Online Bundles, Marketing Science, 30, 4, pp. 737-752, (2011); Kim E.H., Differences in Perceived Financial Risk according to Price Discounts and Product Types of Consumers in Korea and Thailand, International Journal of Industrial Distribution & Business, 7, 2, pp. 25-32, (2016); Kim Y.M., Kireyeva A.A., Youn M.K., Effects of SNS Characteristics upon Consumers' Awareness, Purchase Intention, and Recommendation, International Journal of Industrial Distribution & Business, 5, 1, pp. 27-37, (2014); McCardle K.F., Rajaram K., Tang C.S., Bundling Retail products: Models and analysis, European Journal of Operational Research, 177, pp. 1197-1217, (2007); MohanKumar R., Saravanan D., Design of Quality-based Recommender System for Bundle Purchases, Data Mining and Knowledge Engineering, pp. 1-8, (2013); Pathak B.K., Comparison Shopping Agents and Online Price Dispersion: A Search Cost Based Explanation, Journal of Theoretical and Applied Electronic Commerce Research, 7, 1, pp. 64-76, (2012); Pu P., Chen L., Hu R., Evaluating Recommender Systems from the User's Perspective: Survey of the State of the Art, User Modeling and User-Adapted Interaction, 22, 4, pp. 317-355, (2012); Singh D.P., Online Shopping Motivations, Information Search, and Shopping Intentions in an Emerging Economy, East Asian Journal of Business Management, 4, 3, pp. 5-12, (2014); Stigler G., A Note on Block Booking, U.S. Supreme Court Review, 1963, pp. 152-175, (1963); Stremersch S., Tellis G.J., Strategic Bundling of Products and Prices: A New Synthesis for Marketing, Journal of Marketing, 66, 1, pp. 55-72, (2002); Yang T.C., Lai H., Comparison of Product Bundling Strategies on Different Online Shopping Behaviors, Electronic Commerce Research and Applications, 5, pp. 295-304, (2006)","B. Choi; School of Business, Chungnam National University, South Korea; email: polytime@cnu.ac.kr",null,"Korea Distribution Science Association (KODISA)",{"$nulls":5},1.738311E7,null,null,null,"English","J. Distribution Science","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85028051077"]
["Adeyemi I.R.; Razak S.A.; Salleh M.; Venter H.S.","Adeyemi, Ikuesan Richard (57200145399); Razak, Shukor Abd (57202120585); Salleh, Mazleena (36992863900); Venter, Hein S. (7005841055)","57200145399; 57202120585; 36992863900; 7005841055","Leveraging human thinking style for user attribution in digital forensic process",2017.0,"International Journal on Advanced Science, Engineering and Information Technology",7.0,1.0,null,198.0,206.0,8.0,14.0,"10.18517/ijaseit.7.1.1383","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85013990395&doi=10.18517%2fijaseit.7.1.1383&partnerID=40&md5=b28005864065b29f2e576476d78f838d","Department of Computer Science, Universiti Teknologi Malaysia, Skudai, Malaysia; Department of Computer Science, University of Pretoria, Pretoria, 0082, South Africa","Adeyemi I.R., Department of Computer Science, Universiti Teknologi Malaysia, Skudai, Malaysia, Department of Computer Science, University of Pretoria, Pretoria, 0082, South Africa; Razak S.A., Department of Computer Science, Universiti Teknologi Malaysia, Skudai, Malaysia; Salleh M., Department of Computer Science, Universiti Teknologi Malaysia, Skudai, Malaysia; Venter H.S., Department of Computer Science, University of Pretoria, Pretoria, 0082, South Africa","User attribution, the process of identifying a human in a digital medium, is a research area that has received significant attention in information security research areas, with a little research focus on digital forensics. This study explored the probability of the existence of a digital fingerprint based on human thinking style, which can be used to identify an online user. To achieve this, the study utilized Server-side web data of 43-respondents were collected for 10-months as well as a self-report thinking style measurement instrument. Cluster dichotomies from five thinking styles were extracted. Supervised machine-learning techniques were then applied to distinguish individuals on each dichotomy. The result showed that thinking styles of individuals on different dichotomies could be reliably distinguished on the Internet using a Meta classifier of Logistic model tree with bagging technique. The study further modelled how the observed signature can be adopted for a digital forensic process, using high-level universal modelling language modelling process- specifically, the behavioural state-model and use-case modelling process. In addition to the application of this result in forensics process, this result finds relevance and application in human-centered graphical user interface design for recommender system as well as in e-commerce services. It also finds application in online profiling processes, especially in e-learning systems.","Digital forensic process; Online digital-signature; Online user identification; Sternberg thinking style; User attribution",{"$nulls":7},"LaRose R., Mastro D., Eastin M., Understanding Internet usage a social-cognitive approach to uses and gratifications, Soc. Sci. Comput. Rev, 19, 4, pp. 395-413, (2001); Kao G.Y.M., Lei P.L., Sun C.T., Thinking style impacts on Web search strategies, Comput. Human Behav, 24, 4, pp. 1330-1341, (2008); Fiorina L., Antonietti A., Colombo B., Bartolomeo A., Thinking style, browsing primes and hypermedia navigation, Comput. Educ, 49, 3, pp. 916-941, (2007); Khamsum K.K., Towards Modelling Web Search Behaviour: Integrating Users ' Cognitive Styles, (2013); Kozhevnikov M., Cognitive styles in the context of modern psychology: Toward an integrated framework of cognitive style, Psychol. Bull, 133, 3, pp. 464-481, (2007); Richmond A.S., Krank H.M., Cummings R., A brief research report: Thinking styles of online distance education students, Int. J. Technol. Teach. Learn, 2, 1, pp. 58-64, (2006); Pilli E.S., Joshi R.C., Niyogi R., Framework for Network Forensic Analysis, Communications in Computer and Information Science, 101, pp. 142-147, (2010); Valjarevic A., Harmonised Digital Forensic Investigation Process Model, Information Security for South Africa, pp. 1-10, (2012); Adeyemi I.R., Razak S.A., Azhan N.A.N., A Review of Current Research in Network Forensic Analysis, Int. J. Digit. Crime Forensics, 5, 1, pp. 1-26, (2013); Riding R.J., Sadler-Smith E., Cognitive Style and Learning Strategies: Some Implications for Training Design, Int. J. Train. Dev, 1, 3, pp. 199-208, (1997); Zimmerman B.J., A social cognitive view of self-regulated academic learning, J. Educ. Psychol, 81, 3, pp. 329-339, (1989); Sternberg R.J.R., Zhang L., Styles of Thinking as a Basis of Differentiated Instruction, Theory Pract, 44, 3, pp. 245-253, (2005); Huang A.H., Yen D.C., Hung S.Y., Research issues of internet-integrated cognitive style, Comput. Human Behav, 28, 5, pp. 1547-1554, (2012); Zhang L., Thinking styles, self-esteem, and extracurricular experiences, Int. J. Psychol, 36, 2, pp. 100-107, (2001); Zhang L., Are Thinking Styles and Personality Types Related?, Educ. Psychol, 20, 3, pp. 271-283, (2000); Zhang L., Thinking styles and the big five personality traits revisited, Pers. Individ. 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Learn, 20, 1, pp. 31-39, (2004); Kao G.Y.-M., Lei P.-L., Sun C.-T., Thinking style impacts on Web search strategies, Comput. Human Behav, 24, 4, pp. 1330-1341, (2008); Fan J., Zhang L., The role of learning environments in thinking styles, Educ. Psychol, 32, pp. 1-18, (2013); Zhang L.-F., Thinking Styles: Their relationships with modes of thinking and academic performance, Educ. Psychol, 22, pp. 331-348, (2002); Zhu C., Zhang L., Thinking styles and conceptions of creativity among university students, Educ. Psychol, 31, 3, (2011); Yu T.M., Chen C., Thinking styles and preferred teacher interpersonal behavior among Hong Kong students, Learn. Individ. Differ, 22, 4, pp. 554-559, (2012); Wang H., Yang H., Sun C., Thinking Style and Team Competition Game Performance and Enjoyment, IEEE Trans. Comput. Intell. AI Games, 7, 3, pp. 243-254, (2015); Sternberg R., Mental self-government: A theory of intellectual styles and their development, Hum. 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Dif, 38, 8, pp. 1915-1925, (2005); Adeyemi I.R., Razak A.S., Salleh M., Individual Difference for HCI Systems: Examining the Probability of Thinking Style Signature in Online Interaction, 4th International Conference on User Science and Engineering 2016 (i-USEr 2016), (2016); Yang Y., Padmanabhan B., Toward user patterns for online security: Observation time and online user identification, Decis. 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Tutorials, IEEE, 10, 4, pp. 56-76, (2008); Kotsiantis S., Zaharakis I., Pintelas P., Supervised machine learning: A review of classification techniques, Informatical, 31, pp. 249-268, (2007); Othman F.M., Moh T., Yau S., Comparison of Different Classification Techniques Using WEKA for Breast Cancer, 3rd Kuala Lumpur International Conference on Biomedical Engineering, 15, pp. 520-523, (2007); Freund Y., Schapire R.R.E., Experiments with a New Boosting Algorithm, Int. Conf. Mach. Learn, pp. 148-156, (1996); Rokach L., Ensemble-based classifiers, Artif. Intell. Rev, 33, 1-2, pp. 1-39, (2010); Yang Y.C., Web user behavioral profiling for user identification, Decis. Support Syst, 49, 3, pp. 261-271, (2010); White R., Hassan A., Singla A., Horvitz E., From devices to people: Attribution of search activity in multi-user settings, Proceedings of the 23rd International World WIde Web Conference Committee (IW3C2), pp. 431-441, (2014); Kuurstra J., Individual differences in Human-Computer Interaction: A review of empirical studies, (2015)","I.R. Adeyemi; Department of Computer Science, Universiti Teknologi Malaysia, Skudai, Malaysia; email: raikuesan2@live.utm.my",null,"Insight Society",{"$nulls":5},2.0885334E7,null,null,null,"English","Int. J. Adv. Sci. Eng. Inf. Technol.","Article","Final","All Open Access; Green Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85013990395"]
["Wu J.","Wu, Junhong (57194570807)",5.7194570807E10,"Research on operation and risk control of cold chain logistics of electricity supplier fresh products",2017.0,"Agro Food Industry Hi-Tech",28.0,3.0,null,609.0,613.0,4.0,2.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85020928937&partnerID=40&md5=9b554350daf9a6e809073833667c9b6d","International School of Education, Xuchang University, China","Wu J., International School of Education, Xuchang University, China","With the vigorous development of e-commerce, in the field of fresh products, the traditional consumption patterns of consumers' stores are gradually changing. The cold chain logistics operation system which supports the continuous operation of fresh e-commerce plays a vital role in it. The safety accidents caused by product pollution, product deterioration and rotting of goods have caused people's attention. Cold chain logistics risk control management is imminent. Based on the characteristics of the logistics operation of the electricity supplier, the existence security risks and the main risk were analyzed. The evaluation model was constructed. Fresh grape logistics operations were used as an example to conduct empirical analysis, trying to put forward effective safety control measures for raw cold chain logistics.","Cold chain logistics; E-commerce; Fresh; Risk control","Chains; Commerce; Electric utilities; Electronic commerce; Cold chain logistics; Consumption patterns; Continuous operation; Empirical analysis; Evaluation modeling; Fresh; Logistics operations; Risk controls; Safety engineering",{"$nulls":6},"Yuhong H., Study of countermeasures relating to develop Chinese cold chain logistics, Academic Periodical of Farm Products Processing, 6, 8, (2006); Dan B., Chen J., Coordinating fresh agricultural supply chain under the valuable loss, Chinese Journal of Management Science, 5, 6, pp. 52-56, (2008); Stanger S.H.W., Wilding R., Yates N., Et al., What drives perishable inventory management performance? Lessons learnt from the UK blood supply chain, Supply Chain Management, An International Journal, 17, 2, pp. 107-123, (2012); Shukla M., Jharkharia S., Agri-fresh produce supply chain management, a state-of-The-art literature review, International Journal of Operations & Production Management, 33, 2, pp. 114-158, (2013); Yuan Y., Liang P., Zhang J.J., Using Agent Technology to Support Supply Chain Management, Potentials and Challenges, 3, 8, pp. 854-859, (2001); Bai H., Guo Q., Analysis on the influencing factors of the development of Chinese fresh cold chain logistics under e-commerce background, Journal of Management and Strategy, 8, 1, (2017); Cagliano A.C., Cagliano A.C., De Marco A., Et al., E-grocery supply chain management enabled by mobile tools, Business Process Management Journal, 23, 1, pp. 47-70, (2017); Ruan J., Shi Y., Monitoring and assessing fruit freshness in IOT-based e-commerce delivery using scenario analysis and interval number approaches, Information Sciences, 373, 8, pp. 557-570, (2016); Srivastava S.K., Chaudhuri A., Srivastava R.K., Propagation of risks and their impact on performance in fresh food retail, The International Journal of Logistics Management, 26, 3, pp. 568-602, (2015); Weng X., An J., Yang H., The analysis of the development situation and trend of the city-oriented cold chain logistics system for fresh agricultural products, Open Journal of Social Sciences, 3, 11, (2015); Hayashi K., Nemoto T., Visser J.J., E-commerce and city logistics solution, City Logistics, Mapping the Future, 55, 8, pp. 78-82, (2014); Wu L., Yue X., Jin A., Et al., Smart supply chain management, a review and implications for future research, The International Journal of Logistics Management, 27, 2, pp. 395-417, (2016); Liu Y., Study on the improvement of fresh electricity suppliers cold chain logistics service quality, Journal of Service Science and Management, 9, 6, (2016); Fredriksson A., Liljestrand K., Capturing food logistics, a literature review and research agenda, International Journal of Logistics Research and Applications, 18, 1, pp. 16-34, (2015); Han L., Li F., Study on reasonable measures of promoting the city cold chain logistics transfer resources to rural-A case study of yunnan underdeveloped areas, Resource Development & Market, 10, 8, (2014)",null,null,"TeknoScienze",{"$nulls":5},1.7226996E7,null,null,null,"English","Agro Food Ind. Hi-Tech","Article","Final",null,"Scopus","2-s2.0-85020928937"]
["Wang F.; Li Q.","Wang, Fang (57199195813); Li, Qian (57191033565)","57199195813; 57191033565","E-commerce supply chain security and influencing factors of logistics industry development based on VAR model",2016.0,"International Journal of Security and its Applications",10.0,9.0,null,129.0,140.0,11.0,3.0,"10.14257/ijsia.2016.10.9.14","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84992047450&doi=10.14257%2fijsia.2016.10.9.14&partnerID=40&md5=0d63f732b12029a33017f5b70af895e6","School of economics and management, Chang'an University, Xian city, 710064, China","Wang F., School of economics and management, Chang'an University, Xian city, 710064, China; Li Q., School of economics and management, Chang'an University, Xian city, 710064, China","With the development of E-business, logistics industry has become an important part of China's economic development. E-commerce market brings a great opportunity to traditional logistics industry, as more than 70% express business is derived from the network shopping; however, E-commerce supply chain security problem also produced some adverse effects. In this paper, the authors analyze the key factor of logistics industry in E-commerce market, and find out three factors affecting logistics capability as logistics infrastructure optimization, industrial structure and marketization degree. By using VAR model, the empirical results show that there exist a long-term relationship between the basic logistics optimization degree, industrial structure and the degree of marketization, and marketization degree has positive related to the logistics optimization degree. At the same time, the market degree has obvious promotion effect on logistics optimization in the short term. This conclusion shows that in order to play the role of logistics industry to promote economic growth, government should optimize the industrial structure, and improve network infrastructure. © 2016 SERSC.","E-business; Logistics industry; Logistics security; Network data; VAR model","Commerce; Economics; Electronic commerce; Network security; Structural optimization; Supply chains; Value engineering; eBusiness; Logistics industry; Logistics infrastructure; Logistics optimization; Long-term relationships; Network data; Network infrastructure; VAR models; Industrial economics",{"$nulls":4},"China Postdoctoral Science Foundation, (2015M572531)","This paper is supported by China Postdoctoral Science Foundation (2015M572531)","Manjit S., Kristine V., Social Commerce: A Contingency Framework for Assessing Marketing Potential, Journal of Interactive Marketing, 27, pp. 311-323, (2013); Ramanathan R., Ramanathan U., The impact of e-commerce on Taiwanese SMEs: Marketing and operations effects, International Journal of Production Economics, 140, 2, pp. 934-943, (2012); Grant K., Edgar D., Risky business: Perceptions of e-business risk by UK small and medium sized enterprises (SMEs), International Journal of Information Management, 34, 2, pp. 99-122, (2014); Deniss S., Impact of e-environment on SMEs Business Development, Procedia-Social and Behavioral Sciences, 156, pp. 409-413, (2014); Shoki M., Yun L., Zakuan N., Examining Dimensions of Electronic Service Quality for Internet Banking Services, Procedia-Social and Behavioral Sciences, 65, pp. 854-859, (2012); Liem V., Cass A., Innovation and business success: The mediating role of customer participation, Journal of Business Research, 66, 8, pp. 1134-1142, (2013); Zaridis A.D., Dimosthenis T., Entrepreneurship and SME's Organizational Structure. Elements of a Successful Business, Procedia-Social and Behavioral Sciences, 148, pp. 463-467, (2014); Gebauer H., Paiola M., Edvardsson B., A capability perspective on service business development in small and medium-sized suppliers, Scandinavian Journal of Management, 28, 4, pp. 321-339, (2012); Djelassi S., Decoopman I., Customers' participation in product development through crowd sourcing: Issues and implications, Industrial Marketing Management, 42, 5, pp. 683-692, (2013); Sinem E.H., Kabadayi Z., Innovation Orientation, Market Orientation and e-Loyalty: Evidence from Turkish e-Commerce Customers, Procedia-Social and Behavioral Sciences, 99, pp. 509-516, (2013)","F. Wang; School of economics and management, Chang'an University, Xian city, 710064, China; email: wangfang_jg@chd.edu.cn",null,"Science and Engineering Research Support Society",{"$nulls":5},1.7389976E7,null,null,null,"English","Int. J. Secur. Appl.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-84992047450"]
["Dhote T.; Zahoor D.","Dhote, Tripti (57193896239); Zahoor, Danish (57193906394)","57193896239; 57193906394","Framework for sustainability in E - commerce business models: A perspective based approach",2017.0,"Indian Journal of Marketing",47.0,4.0,null,35.0,50.0,15.0,6.0,"10.17010/ijom/2017/v47/i4/112681","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85017410873&doi=10.17010%2fijom%2f2017%2fv47%2fi4%2f112681&partnerID=40&md5=515a5aaedcb17651b8fba4e891995a2e","Symbiosis Institute of Telecom Management, A constituent of Symbiosis International University, Pune, Symbiosis Hilltop Campus, Lavale, Pune, Maharashtra, 412115, India; Symbiosis Institute of Telecom Management, A constituent of Symbiosis International University, Pune, Old Boys' Hostel, Symbiosis Hilltop Campus, Lavale, Pune , Maharashtra, 412115, India","Dhote T., Symbiosis Institute of Telecom Management, A constituent of Symbiosis International University, Pune, Symbiosis Hilltop Campus, Lavale, Pune, Maharashtra, 412115, India; Zahoor D., Symbiosis Institute of Telecom Management, A constituent of Symbiosis International University, Pune, Old Boys' Hostel, Symbiosis Hilltop Campus, Lavale, Pune , Maharashtra, 412115, India","E-commerce businesses in the Indian scenario have lately seen an overwhelming growth and acceptance owing to factors like better Internet penetration and advancement in technology. The E - commerce business models, in particular, have aroused a great interest among researchers and academicians. Majority of the players operating within the e-commerce space in the country have a single-point agenda of driving motivation and creating needs by way of offering lucrative discounts, cash on delivery options, and a wide variety in terms of products and services. In terms of'value' offered, several rewarding options are made available to the customers, but the point of differentiation for the players is thinning, leading to a visible clutter, and hence, pressures on profitability, indicating a need for innovation to make the business models more sustainable. Integrating secondary data and expert opinion, this paper attempted at proposing a framework by identifying key areas, which can be reinforced by these companies to differentiate themselves and create a sustainable advantage.","Business model; E-commerce; Innovation; Sustainability; Value",{"$nulls":7},"Barney J., Firm resources and sustained competitive advantage, Journal of Management, 77, 1, pp. 99-120, (1991); Bhatia N., The future of E-commerce in India, (2012); Bogaisky J., Retail in crisis: These are the changes brick and mortar stores must make, Forbes, (2014); Damanpour F., Damanpour J.A., E-business e-commerce evolution: Perspective and strategy, Managerial Finance, 27, 7, pp. 16-33, (2001); Ghosh S., Making business sense of the Internet, Harvard Business Review, 76, 2, pp. 126-135, (1997); Hansen E.G., Schaltegger S., The sustainability balanced scorecard: A systematic review of architectures, Journal of Business Ethics, 133, 2, pp. 193-221, (2016); Hoessle U., Ten steps towards a sustainable business, (2013); Joshi D.J., An analysis of the existing literature on B2C E-commerce, Indian Journal of Marketing, 43, 12, pp. 34-46, (2013); Lee C.-S., An analytical framework for evaluating e-commerce business models and strategies, Internet Research, 11, 4, pp. 349-359, (2001); Lin M., Ke X., Whinston A.B., Vertical differentiation and a comparison of online advertising models, Journalof ManagementInformation Systems, 29, 1, pp. 195-236, (2012); Lopez-Nores M., Bianco-Fernandez Y., Pazos-Arias J.J., Cloud-based personalization of new advertising and e-commerce models for video consumption, The Computer Journal, 56, 5, pp. 573-592, (2013); Minculete G., Minculete G.D., Approaches related to E-commerce models in the e-business, Land Forces Academy Review, 18, 1, pp. 101 -101, (2013); Mitra S., The curious case of India's e-commerce, Business Standard; Nair A.A., Will CoD kill the Indian e - commerce star?, (2016); Oliver C., Sustainable competitive advantage: Combining institutional and resource-based views, Strategic Management Journal, 18, 9, pp. 697-713, (1997); Osterwalder A., Pigneur Y., Business model generation: A handbook for visionaries, game changers, and challengers, (2010); Peterovic O., Kittl C., Teksten R.D., Developing business models for eBusiness, International Conference on Electronic Commerce 2001, (2001); Porter M.E., Competitive advantage: Creating and sustaining superior performance, (1985); Evolution ofe-commerce in India: Creating the bricks behind the clicks, (2014); eCommerce in India: Accelerating growth, (2014); Sardana M.M.K., Evolution ofecommerce in India: Challenges ahead (Part 1) [Discussion Notes], New Delhi: Institute for Studies in Industrial Development, (2015); Teece D.J., Business models, business strategy and innovation, Long Range Planning, 43, 2, pp. 172-194, (2010); Tian Z., Zhang Z., Guan X., Anew evolution model for B2C e-commerce market, Information Technology and Management, 14, 3, pp. 205-215, (2013); Wagner B.A., Fillis I., Johansson U., E-business and e-supply strategy in small and medium sized businesses (SMEs), Supply Chain Management: An International Journal, 8, 4, pp. 343-354, (2003)",null,null,"Associated Management Consultants Pvt. Ltd.",{"$nulls":5},9738703.0,null,null,null,"English","Ind. J. Mark.","Article","Final",null,"Scopus","2-s2.0-85017410873"]
["Oliveira L.K.D.; Morganti E.; Dablanc L.; Oliveira R.L.M.D.","Oliveira, Leise Kelli de (57194449016); Morganti, Eleonora (55808986200); Dablanc, Laetitia (15118955600); Oliveira, Renata Lúcia Magalhães de (57195954186)","57194449016; 55808986200; 15118955600; 57195954186","Analysis of the potential demand of automated delivery stations for e-commerce deliveries in Belo Horizonte, Brazil",2017.0,"Research in Transportation Economics",65.0,null,null,34.0,43.0,9.0,81.0,"10.1016/j.retrec.2017.09.003","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85030468185&doi=10.1016%2fj.retrec.2017.09.003&partnerID=40&md5=9c2a6ab1e63abba22798000a8e827c1e","Universidade Federal de Minas Gerais (UFMG), Avenue Antônio Carlos, 6627, Belo Horizonte, 31.270-901, Minas Gerais, Brazil; Institute for Transport Studies (ITS), University of Leeds, 34-40 University Road, Leeds, LS2 9JT, United Kingdom; IFSTTAR – Université Paris-Est, 14-20 Boulevard Newton, Cité Descartes, 77447 Marné la Vallée cedex 2, France; Centro Federal de Educação Tecnológica de Minas Gerais (CEFET-MG), Transportation Engineering Department, Avenue Amazonas, 5.253, Belo Horizonte, 30.421-169, Minas Gerais, Brazil","Oliveira L.K.D., Universidade Federal de Minas Gerais (UFMG), Avenue Antônio Carlos, 6627, Belo Horizonte, 31.270-901, Minas Gerais, Brazil; Morganti E., Institute for Transport Studies (ITS), University of Leeds, 34-40 University Road, Leeds, LS2 9JT, United Kingdom; Dablanc L., IFSTTAR – Université Paris-Est, 14-20 Boulevard Newton, Cité Descartes, 77447 Marné la Vallée cedex 2, France; Oliveira R.L.M.D., Centro Federal de Educação Tecnológica de Minas Gerais (CEFET-MG), Transportation Engineering Department, Avenue Amazonas, 5.253, Belo Horizonte, 30.421-169, Minas Gerais, Brazil","The problems related to home delivery become increasingly evident with the growth of electronic commerce. Automatic delivery stations represent a solution to reduce mislaid deliveries and consolidate parcels drop-off, minimizing the kilometers travelled, and the costs of urban goods distribution. In order to better understand online shoppers' attitudes towards new delivery services, we analyze the potential demand of automatic delivery stations (lockers) in the city of Belo Horizonte, Brazil. For this purpose, we develop a survey according to stated preference and revealed preference methods, and we assess potential users considering two deliveries services: home delivery and automated delivery stations. The results indicate that, although home delivery is the preferred option, automatic delivery stations score high potential demand for online shoppers. This paper provides an approach to integrate the impact of final consumers' preferences on shaping last-mile operations, and it thus helps policymakers to identify the most suitable innovations to specific urban settings. © 2017 Elsevier Ltd","E-commerce; Home delivery; Last mile problem; Pick-up points; Stated preference survey",{"$nulls":5},"French Institute of Science and Technology for Transport; Conselho Nacional de Desenvolvimento Científico e Tecnológico, CNPq","The authors would like to thank CNPq (National Council for Scientific and Technological Development) for its direct financial support to the research and IFSTTAR (The French Institute of Science and Technology for Transport, Development, and Networks) for hosting Leise Kelli de Oliveira in a post doc programme. The authors would like to thank anonymous referees for all the precious suggestions. Additionally, the authors would also like to thank all the participants to collect data process.","Anand N., Quak H., Duin R.V., Tavasszy L., City logistics modelling efforts: Trends and gaps – a review, Procedia - Social and Behavioral Sciences, 39, pp. 101-115, (2012); Browne M., Allen J., Anderson S., Jackson M., Overview of home deliveries in the UK (A study for DTI), (2001); CGI.br, Survey on the use of information and communication technologies in Brazil, (2014); Cochran W.G., Cox G.M., Diseños experimentales, (1978); Comi A., Nuzzolo A., Exploring the relationships between e-shopping attitudes and urban freight transport, Transportation Research Procedia, 12, pp. 399-412, (2016); Dell'Amico M., Hadjidimitriou S., Innovative logistics model and containers solutions for efficient last mile delivery, Procedia – Social and Behavioral Sciences, 48, pp. 1505-1514, (2012); Ding Z., Evaluating different last mile logistics solutions: A case study of SF Express, (2013); Dominguez A., Holguin-Veras J., Ibeas A., Dell'Olio L., Receivers' response to new urban freight policies, Procedia - Social and Behavioral Sciences, 54, pp. 886-896, (2012); Dutra N.G.S., The focus of city logistics in the urban parcel, (2004); E-bit, WebShoppers, (2015); E-bit, WebShoppers, (2016); Edwards J., McKinnon A., Cherrett T., McLeod F., Song L., The CO2 benefits of using collection/delivery points for failed home deliveries, Transportation Research Record, 10, 1901, pp. 136-143, (2010); Folkert S., Eichhorn C., Innovative approaches in city logistics: Alternatives solution for home delivery, (2007); Gatta V., Marcucci E., Urban freight transport and policy changes: Improving decision makers' awareness via an agent-specific approach, Transport Policy, 36, pp. 248-252, (2014); Gatta V., Marcucci E., Behavioural implications of non-linear effects on urban freight transport policies: The case of retailers and transport providers in Rome, Case Studies on Transport Policy, 4, 1, pp. 22-28, (2016); Gatta V., Marcucci E., Scaccia L., On finite sample performance of confidence intervals methods for willingness to pay measures, Transportation Research Part A: Policy and Practice, 82, pp. 169-192, (2015); Holguin-Veras J., Silas M., Polimeni J., Cruz B., An investigation on the effectiveness of joint receiver-carrier policies to increase truck traffic in the off-peak hours—Part I: The behavior of receivers, Networks and Spatial Economics, 7, 3, pp. 277-295, (2007); Holguin-Veras J., Silas M., Polimeni J., Cruz B., An investigation on the effectiveness of joint receiver-carrier policies to increase truck traffic in the off-peak hours—Part II: The behavior of carriers, Netw. Spat. 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Oliveira; Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Avenue Antônio Carlos, 6627, 31.270-901, Brazil; email: leise@etg.ufmg.br",null,"Emerald Group Holdings Ltd.",{"$nulls":5},7398859.0,null,null,null,"English","Res. Transp. Econ.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85030468185"]
["Gabdullin L.V.; Bikulov R.A.; Efremova O.I.","Gabdullin, Lenar V. (57192301755); Bikulov, Rinat A. (56770136400); Efremova, Oksana I. (57192303851)","57192301755; 56770136400; 57192303851","Logistic barter and working conditions of LBP-provider",2017.0,"International Journal of Economic Perspectives",11.0,4.0,null,768.0,775.0,7.0,2.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85041506733&partnerID=40&md5=452f0cd715ae4261e44419f31b2de684","Kazan Federal University, Naberezhnye Chelny Institute, Department of Production Management, Russian Federation","Gabdullin L.V., Kazan Federal University, Naberezhnye Chelny Institute, Department of Production Management, Russian Federation; Bikulov R.A., Kazan Federal University, Naberezhnye Chelny Institute, Department of Production Management, Russian Federation; Efremova O.I., Kazan Federal University, Naberezhnye Chelny Institute, Department of Production Management, Russian Federation","Logistics reaches such heights when the need for \"money which is a universal equivalent of goods\" in relations between manufacturers simply disappears. New LBP providers are considered that are not a servicing element of the economy, they are operators of another economic system, where there is no place for money and banks between producers. At the moment, the highest level of supply chain management is 5PL providers, but 6 or 7PL providers will be needed for logistics barter, or they need to be called logistics barter providers because there must be a completely different, predominant view of the role of logistics and logistics barter in the new economy system. Logistic barter is some kind of web (system), a spider (operator) is a LBP provider [1]. The theory of the proposed economy scheme on the basis of logistic barter assumes a developed infrastructure, i.e. a supersystem for supply chain management based on LBP- providers. Yes, there is a question of the \"maturity\" of logistics functional areas (procurement, production, distribution, transportation and information), i.e. Their ability to adopt new rules of the game in the sphere of another operator of the economy. The abilities to manage supply chains can be completely different. Logistics barter offers another alternative in the economy. Are the functional areas of the supply chains ready? First, you need to exclude the human factor in the collaboration with a LBP provider. Logistic barter will be the central unifying link, and the main operators will be the LBP-provider. E-commerce, e-auctions, e-sourcing, and e-markets are better integrated under the auspices of logistics barter into an e-integrator, which will be the serving element (one of the tools) of the LBP-provider. E-integrator is an integrator of information and communication technologies for supply chains of logistics barter in the form of electronic means taking into account the closing link - e-commerce and the reverse distribution of added value. © International Economic Society.","E-integrator; Human factor; Indifference coefficient; Indifference level; LBP-provider; Logistic barter; Objectivity",{"$nulls":5},"Kazan Federal University","The work is carried out according to the Russian Government's Program of Competitive Growth of Kazan Federal University.","Efremova O.I., Gabdullin L.V., Logistic barter features as a new concept of supply chain management, Academy of Strategic Management Journal, 15, pp. 19-25, (2016); Bulatov A.S., Economy. Textbook, (2003); Sergeev V.I., Supply Chain Management, (2008); Gabdullin L.V., Logistical barter and the future: Perspectives and contradictions., Logistics Today, 6, pp. 332-336, (2013); Dybskaya V.V., Logistics. Integration and Optimization of Logistics Business Processes in Supply Chains, (2008); Gabdullin L.V., Evolution of economic theory and the place of logistic barter in it, Logistics Today, 1, pp. 62-66, (2014); Gabdullin L.V., Possibilities of LBP- logistics barter provider., Logistics, 2, pp. 27-29, (2014); Efremova O.I., Gabdullin L.V., Bikulov R.A., Problems and urban infrastructure development in Russia (For example, the city of Naberezhnye Chelny), Journal of Economics and Economic Education Research, 17, pp. 178-184, (2016); Gabdullin L.V., Possible sunset of the empire of money between producers due to logistic barter, Scientific Review, 7, pp. 397-400, (2014); Best Practice in Supply Chain Management, (1998); (1990)","L.V. Gabdullin; Kazan Federal University, Naberezhnye Chelny Institute, Department of Production Management, Russian Federation; email: len1510@mail.ru",null,"International Economic Society",{"$nulls":5},1.3071637E7,null,null,null,"English","Int. J. Econ. Perspect.","Article","Final",null,"Scopus","2-s2.0-85041506733"]
["Fagerstrøm A.; Ghinea G.; Sydnes L.","Fagerstrøm, Asle (23396496800); Ghinea, Gheorghita (35616295700); Sydnes, Lars (56653288600)","23396496800; 35616295700; 56653288600","Understanding the Impact of Online Reviews on Customer Choice: A Probability Discounting Approach",2016.0,"Psychology and Marketing",33.0,2.0,null,125.0,134.0,9.0,23.0,"10.1002/mar.20859","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84954111643&doi=10.1002%2fmar.20859&partnerID=40&md5=2c408f892b544231b9e5575bd1689c9b","Westerdals Oslo School of Arts, Communication and Technology, Norway; Brunel University, United Kingdom","Fagerstrøm A., Westerdals Oslo School of Arts, Communication and Technology, Norway; Ghinea G., Westerdals Oslo School of Arts, Communication and Technology, Norway, Brunel University, United Kingdom; Sydnes L., Westerdals Oslo School of Arts, Communication and Technology, Norway","This study uses the concept of probability discounting to understand the impact of online customer reviews on consumer choice. Probability discounting describes how the subjective value of an outcome alters when its delivery shifts from certain to uncertain. An experimental study with 29 participants was conducted. Participants were run through an online shopping scenario where they had to choose whether to buy a product from a Web shop with customer reviews on reliability or from a Web shop without reviews but with a lower product price. A titration procedure over sales price for the Web shop without reviews was run over seven probability conditions. The mean switching points where participants chose where to buy the product were extracted from the experimental data, and probability discounting factors were calculated. The results supported the assumption that online reviews indicate the probability of a successful transaction online and function as a guide to choices. 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Delay discounting, magnitude effects, and domain independence of utility for career decisions, Journal of Vocational Behavior, 62, pp. 43-55, (2003); Smith C.L., Hantula D.A., Pricing effects on foraging in a simulated Internet shopping mall, Journal of Economic Psychology, 24, pp. 653-674, (2003); Smith C.L., Hantula D.A., Methodological considerations in the study of delay-discounting in itertemporal choice: A comparison of tasks and modes, Behavior Research Methods, 40, pp. 940-953, (2008); Soman D., The effect of time delay on multi-attribute choice, Journal of Economic Psychology, 25, pp. 153-175, (2004); Stevenson M.K., A discounting model for decisions with delayed positive or negative outcomes, Journal of Experimental Psychology: General, 115, pp. 131-154, (1986); Turkle S., The second self: Computers and the human spirit, (1984); Wei P., Lu H., An examination of the celebrity endorsements and online customer reviews influence female customers' shopping behavior, Computers in Human Behavior, 29, pp. 193-201, (2013); Weller R.E., Cook Iii E.W., Avsar K.B., Cox J.E., Obese women show greater delay discounting than healthy-weight women, Appetite, 51, pp. 563-569, (2008); Whitley B.E., Kite M.E., Principles of research in behavioral science, (2013); Wilkinson N., Klaes M., An introduction to behavioral economics, (2012); Wu P.F., In search of negativity bias: An empirical study of perceived helpfulness of online reviews, Psychology & Marketing, 30, pp. 971-984, (2013)","A. Fagerstrøm; Faculty of Technology, Westerdals Oslo School of Arts, Communication and Technology, Oslo, Schweigaardsgate 14, 0185, Norway; email: asle.fagerstrom@westerdals.no",null,"Wiley-Liss Inc.",{"$nulls":5},7426046.0,null,null,null,"English","Psychol. Mark.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-84954111643"]
["Reyes-Mercado P.; Karthik M.; Mishra R.K.; Rajagopal","Reyes-Mercado, Pável (56102632600); Karthik, M. (57212223156); Mishra, Ram Kumar (56221649900); Rajagopal (23025659500)","56102632600; 57212223156; 56221649900; 23025659500","Drivers of consumer attitudes towards online shopping in the Indian market: Analysis through an extended TAM model",2017.0,"International Journal of Business Innovation and Research",13.0,3.0,null,326.0,343.0,17.0,11.0,"10.1504/IJBIR.2017.10005068","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85020442991&doi=10.1504%2fIJBIR.2017.10005068&partnerID=40&md5=04b0739d203ddc61fa0937ec23aa4c2b","Department of Doctoral Studies in Management Sciences, EGADE Business School, ITESM, Calle del Puente 222, Delegación Tlalpan, Distrito Federal, C.P. 14380, Mexico; Institute of Public Enterprise, Survey No. 1266, Shamirpet (VandM), Hyderabad, Rangareddy Dist., Telangana, 500 101, India","Reyes-Mercado P., Department of Doctoral Studies in Management Sciences, EGADE Business School, ITESM, Calle del Puente 222, Delegación Tlalpan, Distrito Federal, C.P. 14380, Mexico; Karthik M., Institute of Public Enterprise, Survey No. 1266, Shamirpet (VandM), Hyderabad, Rangareddy Dist., Telangana, 500 101, India; Mishra R.K., Institute of Public Enterprise, Survey No. 1266, Shamirpet (VandM), Hyderabad, Rangareddy Dist., Telangana, 500 101, India; Rajagopal, Department of Doctoral Studies in Management Sciences, EGADE Business School, ITESM, Calle del Puente 222, Delegación Tlalpan, Distrito Federal, C.P. 14380, Mexico","The diffusion of the internet has changed advertising, sales, and delivery channels in the retailing industry. Currently, e-commerce industry in India is investing high amounts of money to increase its sales capabilities to perform a wider range of transactions. The main feature of online retailing is the convenience of shopping at any time and receiving the purchased items instead of approaching a physical store. There is a need to analyse consumer's attitudes towards shopping products online in order to gain competitive advantage in the India context which has an 11% of internet penetration. This research proposes a conceptual framework to explore trust, social influence, and digital literacy in forming consumer's intentions to shop online by extending the technology adoption model (TAM). On the basis of 123 collected observations and the analytical technique of partial least squares, this study finds that trust has a strong influence on formation of consumer attitudes and perceived usefulness is a core belief that also influences further attitudes and intentions to shop online. Implications for managers and researchers are discussed. © Copyright 2017 Inderscience Enterprises Ltd.","Consumer behaviour; India; Online retailing; Technology adoption",{"$nulls":7},"Ajzen I., The theory of planned behaviour, Organizational Behavior and Human Decision Processes, 50, 2, pp. 179-211, (1991); Ali S.S., Kaur R., An empirical approach to customer perception of mobile banking in Indian scenario, International Journal of Business Innovation and Research, 9, 3, pp. 272-294, (2015); Al-Somali S.A., Gholami R., Clegg B., An investigation into the acceptance of online banking in Saudi Arabia, Technovation, 29, 2, pp. 130-141, (2009); Bagozzi R.P., The legacy of the technology acceptance model and a proposal for a paradigm shift, Journal of the Association for Information Systems, 8, 4, pp. 243-254, (2007); Bagozzi R.P., Yi Y., On the evaluation of structural equation models, Journal of the Academy of Marketing Science, 16, 1, pp. 74-94, (1988); Bandura A., Self-efficacy: Toward a unifying theory of behavioral change, Psychological Review, 84, 2, pp. 191-215, (1977); 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Davis F.D., Perceived usefulness, perceived ease of use, and user acceptance of information technology, MIS Quarterly, 13, 3, pp. 319-340, (1989); Davis F.D., Bagozzi R.P., Warshaw P.R., User acceptance of computer technology: A comparison of two theoretical models, Management Science, 35, 8, pp. 982-1003, (1989); Eastin M.S., LaRose R., Internet self-efficacy and the psychology of the digital divide, Journal of Computer-Mediated Communication, 6, 1, (2006); Fishbein M., Ajzen I., Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research, (1975); Fornell C., Larcker D.F., Evaluating structural equation models with unobservable variables and measurement error, Journal of Marketing Research, 18, 1, pp. 39-50, (1981); Ganguly B., Dash S.B., Cyr D., Head M., The effects of website design on purchase intention in online shopping: The mediating role of trust and the moderating role of culture, International Journal of Electronic Business, 8, 4-5, pp. 302-330, (2010); 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Ling K.C., Chai L.T., Piew T.H., The effects of shopping orientations, online trust and prior online purchase experience toward customers' online purchase intention, International Business Research, 3, 3, pp. 63-76, (2010); Nunnally J.C., Berstein I., Psychometric Theory, (1994); Ringle C.M., Wende S., Becker J.M., SmartPLS 3, (2015); Sahney S., Ghosh K., Shrivastava A., Conceptualizing consumer 'trust' in online buying behaviour: An empirical inquiry and model development in Indian context, Journal of Asia Business Studies, 7, 3, pp. 278-298, (2013); Schierz P.G., Schilke O., Wirtz B.W., Understanding consumer acceptance of mobile payment services: An empirical analysis, Electronic Commerce Research and Applications, 9, 3, pp. 209-216, (2010); Retail E-Commerce Sales in India from 2012 to 2017, (2014); Venkatesh V., Morris M.G., Davis G.B., Davis F.D., User acceptance of information technology: Toward a unified view, MIS Quarterly, 27, 3, pp. 425-478, (2003); Wang Y.S., Wang Y.M., Lin H.H., Tang T.I., Determinants of user acceptance of internet banking: An empirical study, International Journal of Service Industry Management, 14, 5, pp. 501-519, (2003); Wu L., The antecedents of customer satisfaction and its link to complaint intentions in online shopping: An integration of justice, technology, and trust, International Journal of Information Management., 33, 1, pp. 166-176, (2013)","P. Reyes-Mercado; Department of Doctoral Studies in Management Sciences, EGADE Business School, ITESM, Delegación Tlalpan, Distrito Federal, Calle del Puente 222, C.P. 14380, Mexico; email: pavelreyesmercado@hotmail.com",null,"Inderscience Publishers",{"$nulls":5},1.7510252E7,null,null,null,"English","Int. J. Bus. Innov. Res.","Article","Final",null,"Scopus","2-s2.0-85020442991"]
["Xiaolong J.","Xiaolong, Jiang (56656468700)",5.66564687E10,"The research on the logistics management mode and the application of AHP and DEA of X group’s chain supermarket under the E- commerce environment",2016.0,"International Journal of Grid and Distributed Computing",9.0,12.0,null,181.0,190.0,9.0,0.0,"10.14257/ijgdc.2016.9.12.16","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85027037869&doi=10.14257%2fijgdc.2016.9.12.16&partnerID=40&md5=348686f5319ee3c026c262f4f7606010","Guangdong Jidian Polytechnic, Guangdong, China","Xiaolong J., Guangdong Jidian Polytechnic, Guangdong, China","With the rapid development of science and technology, people’s life style has changed greatly. Under the background of that, the electronic commerce, conforming to the historical tide, has been used by more and more businesses man and customers. At the same time, the logistics management, which was born along with the electronic commerce, makes a lot difference to social development. This article cites the theory of logistics management to establish the Grey correlation methods of analytic hierarchy process and data envelopment analysis through analyzing the chain operation enterprise. And after a comprehensive analysis from some specific examples, it also draws a conclusion that the main factors which affect the logistics management are the cost and the availability of investment, and the choice of logistics management mode is the third party logistics management model and joint distribution logistics management mode. The research of the theory points out the emphasis of the construction of logistics management, and guides the development direction of logistics management. © 2016 SERSC.","Analytic hierarchy process; Data envelopment analysis; E-commerce; Grey correlation methods; Logistics management","Analytic hierarchy process; Chains; Commerce; Correlation methods; Data envelopment analysis; Electronic commerce; Outsourcing; Comprehensive analysis; Development directions; Development of science and technologies; Grey correlation methods; Joint distributions; Logistics management; Social development; Third party logistics; Research and development management",{"$nulls":6},"Tyan-Kwun Wang J.C., Du T.C., An evaluation of freight consolidation Policies in global third Party logistics, Omega, (2013); Asosheh A., Shahidi-Nejad H., Khod-Kari H., A Model of a Localized Cross- Border Ecommerce, Business, 4, pp. 125-145, (2012); Ying W., Sang D.-Y., Multi-agent Framework for Third Party Logistics in Ecommerce, Expert Systems with Applications, 1, pp. 401-415, (2005); Gendreau M., Laporte G., Vigo D., Heuristic for the traveling salesman problem with pickup and delivery, Computers & Operations Research, 26, 7, (1999); Lee H., Whang S.-J., Winning the Last Mile of E-Commerce, (2002); Christopher M., Logistics and Supply Chain management, Financial Times/Pitman Publishing, 6, pp. 47-48, (1994); Gunasekaran A., Research and Applications in e-commerce and third-party Logistics management, International Journal of Production Economies, 5, 113, pp. 123-126, (2008); Gunasekaran A., Sarkis J., Research and applications in e-commerce and third-party logistics management, International Journal of Production Economics, (2007); Chen L.-Y., Li X.-Y., Liu H.-C., Design of nonlinear variable structure controller in HVDC systems, Automation of Electric Power Systems, 27, 4, pp. 6-9, (2003); Du D., Pang Q.H., Wu Y., Modem Comprehensive Evaluation Method and Case Selection, pp. 25-36, (2006)","J. Xiaolong; Guangdong Jidian Polytechnic, China; email: jiangxiaolong@163.com",null,"Science and Engineering Research Support Society",{"$nulls":5},2.0054262E7,null,null,null,"English","Int. J. Grid Distrib. Comput.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85027037869"]
["Rosen J.W.","Rosen, Jonathan W. (57196510818)",5.7196510818E10,"Ghana's last mile",2017.0,"Technology Review",120.0,1.0,null,73.0,87.0,14.0,1.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85023161335&partnerID=40&md5=4f1a4ba31144d6ff68fa2d06307a0cb6","Alicia Patterson Foundation, United States","Rosen J.W., Alicia Patterson Foundation, United States","Online shoppong is growing in Ghana and many other African countries despite many logistics challenges. Many online retailers are operating in Ghana, including Tisu which delivers different kinds of products and consumer goods to customers across the country. African e-commerce has started to grow, reaching a watershed moment when Jumia Group, the parent company of Africa’s largest e-retailer, Jumia.com, became the continent’s first tech company to cross $1 billion in market value in early 2017. Jumia.com has got its funding primarily from large international corporations, among them French insurer Axa, Wall Street leviathan Goldman Sachs, German technology investor Rocket Internet, and South Africa’s top telecommunications company, MTN Group. ",null,"Financial markets; Rockets; Sales; Consumer Goods; Goldman Sachs; International corporation; Market values; Parent company; South Africa; Wall streets; Watershed moment; Electronic commerce",{"$nulls":9},"Massachusetts Institute of Technology",{"$nulls":5},"1099274X",null,"TEREA",null,"English","Technol Rev","Article","Final",null,"Scopus","2-s2.0-85023161335"]
["Guo J.; Liu X.; Jo J.","Guo, Jianquan (56097694900); Liu, Xinxin (56486273800); Jo, Jungbok (7102413079)","56097694900; 56486273800; 7102413079","Dynamic joint construction and optimal operation strategy of multi-period reverse logistics network: a case study of Shanghai apparel E-commerce enterprises",2017.0,"Journal of Intelligent Manufacturing",28.0,3.0,null,819.0,831.0,12.0,27.0,"10.1007/s10845-015-1034-8","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84921333815&doi=10.1007%2fs10845-015-1034-8&partnerID=40&md5=6d38ef2968ee989f2d289c87d6460a05","Business School of University of Shanghai for Science and Technology, Shanghai, 200093, China; Division of Computer and Information Engineering, Dongseo University, Busan, South Korea","Guo J., Business School of University of Shanghai for Science and Technology, Shanghai, 200093, China; Liu X., Business School of University of Shanghai for Science and Technology, Shanghai, 200093, China; Jo J., Division of Computer and Information Engineering, Dongseo University, Busan, South Korea","With the rapid development of our economy, the demand for reverse logistics is becoming increasingly urgent. This paper proposes a multi-period and dynamic joint construction model to build the reverse logistics network and verifies the feasibility of the rendered model by adopting particle swarm optimization (PSO) algorithm and genetic algorithm (GA) with a case study of the apparel E-commerce enterprises of Shanghai. The calculation indicates that, compared with traditional single-period reverse logistics system, dynamic joint construction model is more accordant with the practical situation, the capacity of multi-period model node is easier to optimize and the total operation cost of multi-period model reduces a lot. Furthermore, this research provides reference for reducing the operation costs as well as the building of regional reverse logistics network. © 2015, Springer Science+Business Media New York.","Apparel E-commerce enterprises; Dynamic joint construction; Multi-period network; Particle swarm optimization (PSO) and genetic algorithm (GA); Reverse logistics","Commerce; Cost reduction; Electronic commerce; Operating costs; Particle swarm optimization (PSO); Transportation; Construction model; E-commerce enterprise; Multi-period; Optimal operation strategy; Particle swarm optimization algorithm; Reverse logistics; Reverse logistics network; Total operation costs; Logistics",{"$nulls":4},"Shanghai Education Commission Leading Academic Discipline Project, (J50504, J50604); Natural Science Foundation of Shanghai, (10ZR1413300); National Natural Science Foundation of China, NSFC, (71071093, 71301101, 71471110); Dongseo University, DSU","This work was supported by Shanghai Education Commission Leading Academic Discipline Project (J50504, J50604); National Natural Science Foundation of China (71071093, 71471110, 71301101); Shanghai Municipal Natural Science Foundation (10ZR1413300) and the Dongseo Frontier Project Research Fund of Dongseo University in 2011.","Alumur S.A., Nickel S., Saldanha-da-Gama F., Et al., Multi-period reverse logistics network design, European Journal of Operational Research, 220, 1, pp. 67-78, (2012); Das K., Chowdhury A.H., Designing a reverse logistics network for optimal collection, recovery and quality-based product-mix planning, International Journal of Production Economics, 135, 1, pp. 209-221, (2012); Ding Y., Li X., Gao Y., Multi-period and mutil-objective dynamic location model for remanufacturing logistics network, Chinese Journal of Management, 11, 3, pp. 428-433, (2014); Gan H., Integration of forward and reverse logistics based on RFID, Logistics Technology, 28, 2, pp. 14-16, (2009); Geng X., Model design on reverse logistics with collection sites, Computer Engineering and Applications, 46, 20, pp. 219-221, (2010); He B., Meng W., Reverse logistics network design based on customers’ choice behavior, Chinese Journal of Management Science, 17, 6, pp. 104-108, (2009); Huang C.C., Liang W.Y., Tseng T.L., The rough set based approach to generic routing problems: Case of reverse logistics supplier selection, Journal of Intelligent Manufacturing, pp. 1-15, (2014); Huang Z., Reverse logistics network optimal design for wastes material recycling, Systems Engineering, 27, 7, pp. 49-53, (2009); Kannan D., Diabat A., Alrefaei M., A carbon footprint based reverse logistics network design model, Resources & Conservation and Recycling, 67, pp. 75-79, (2012); Kannan D., Diabat A., Alrefaei M., Et al., A carbon footprint based reverse logistics network design model, Resources, Conservation and Recycling, 67, pp. 75-79, (2012); Kara S., Rugrungruang F., Kaebernick H., Simulation modelling of reverse logistics networks, International Journal of Production Economics, 106, 1, pp. 61-69, (2007); Kennedy J., Eberhart R.C., A discrete binary version of the particle swarm algorithm, In Proceedings of IEEE international conference on computational cybernetics and simulation, systems, man, and cybernetics, 5, pp. 4104-4108, (1997); Kim J.S., Lee D.H., A restricted dynamic model for refuse collection network design in reverse logistics, Computers & Industrial Engineering, 66, 4, pp. 1131-1137, (2013); Kubat C., Yuce B., A hybrid intelligent approach for supply chain management system, Journal of Intelligent Manufacturing, 23, 4, pp. 1237-1244, (2012); Lee J.-E., Chung K.-Y., Lee K.-D., Gen M., A multi-objective hybrid genetic algorithm to minimize the total cost and delivery tardiness in a reverse logistics, Multimedia Tools & Applications, (2013); Lei L., Qu L., Review of electronic waste reverse logistics, Ecological Economy, 9, pp. 141-145, (2010); Li S., Wang N., He Z., Ma Y., Decision-making for reverse logistics network optimization considering service level, Operations Research and Management Science, 22, 5, pp. 90-97, (2013); Liang Q., The research on reverse logistics model in Hebei at present stage, Logistics Economy, 45, pp. 36-37, (2014); Liu Z., Research on reverse logistics operation improvement of household appliances industry, PhD Dissertation, Dalian University of Technology, (2012); Liu C., Huang G., Tabu Search Heuristic Procedure The design of forward and reverse logistics network for multiple products based on search heuristic procedure, Statistics and Decision, 18, pp. 168-171, (2010); Liu B., Zhang C., Wang D., The optimal for returned logistics networks of recycling plastic products, Journal of Northeast Normal University (Natural Science Edition), 43, 4, pp. 33-38, (2011); Luo Y., Wan F., Zhao H., Research on facility location of re-manufacturing network based on MILP, Industrial Engineering and Management, 17, 5, pp. 16-28, (2012); Mahmoudzadeh M., Mansour S., Karimi B., To develop a third-party reverse logistics network for end-of-life vehicles in Iran, Resources & Conservation and Recycling, 78, pp. 1-14, (2013); Marimuthu S., Sait A.N., Performance evaluation of proposed differential evolution and particle swarm optimization algorithms for scheduling m-machine flow shops with lot streaming, Journal of Intelligent Manufacturing, 24, 1, pp. 175-191, (2013); 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PhD Dissertation, Beijing University of Chemical Technology, (2010); Wang Y., The countermeasures for the development of reverse logistics in SMEs, China Business and Market, 9, pp. 52-54, (2009); Weng C., Guo J., Research on reverse logistics network joint construction in B2C apparel E-business enterprise, Resource Development & Market, 30, 9, pp. 1046-1050, (2014); Wu C.H., Wang D.Z., Ip A., A particle swarm optimization approach for components placement inspection on printed circuit boards, Journal of Intelligent Manufacturing, 20, 5, pp. 535-549, (2009); XiaoYan Q., Yong H., Qinli D., Et al., Reverse logistics network design model based on e-commerce, International Journal of Organizational Analysis, 20, 2, pp. 251-261, (2012); Xu J., Liu N., Research on closed loop supply chain with reference price effect, Journal of Intelligent Manufacturing, pp. 1-14, (2014); Xu M., Deng Y., Optimization model for reverse logistics network design in hybrid manufacturing system of disassemble products, Systems Engineering, 27, 12, pp. 56-61, (2009); Yang J., Guo J., Ma S., Low-carbon city logistics distribution network design with resource deployment, Journal of Cleaner Production, pp. 1-6, (2013); Yang M., Wu J., Kong D., Reverse logistics E-business environment returns management, Logistics Sci-tech, 4, pp. 81-84, (2012); Zhang F., The research based on B2C E-commerce mode of return logistics problems, PhD Dissertation, (2011); Zhang G., Study on the developing path of china returned logistics about waste household appliances, Ecological Economy, 6, pp. 96-101, (2011); Zhenqiang B., Congwei Z., Yuqin Z., Et al., Research on reverse logistics location under uncertainty environment based on grey prediction, Physics Procedia, 24, pp. 1996-2003, (2012); Zuo Z., Tan G., Xu B., Review and outlook on the adverse logistics network, Science and Technology Management Research, 6, pp. 75-78, (2012)","J. Guo; Business School of University of Shanghai for Science and Technology, Shanghai, 200093, China; email: jasonguousst@126.com",null,"Springer New York LLC",{"$nulls":5},9565515.0,null,"JIMNE",null,"English","J Intell Manuf","Article","Final",null,"Scopus","2-s2.0-84921333815"]
["Gordini N.; Veglio V.","Gordini, Niccolò (55521230400); Veglio, Valerio (56572630600)","55521230400; 56572630600","Customers churn prediction and marketing retention strategies. An application of support vector machines based on the AUC parameter-selection technique in B2B e-commerce industry",2017.0,"Industrial Marketing Management",62.0,null,null,100.0,107.0,7.0,91.0,"10.1016/j.indmarman.2016.08.003","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84996482980&doi=10.1016%2fj.indmarman.2016.08.003&partnerID=40&md5=c9de50528a89acc14343504627a47453","University of Milano-Bicocca, Italy; Università della Svizzera Italiana (USI), Switzerland","Gordini N., University of Milano-Bicocca, Italy; Veglio V., Università della Svizzera Italiana (USI), Switzerland","E-commerce has provided new opportunities for both businesses and consumers to easily share information, find and buy a product, increasing the ease of movement from one company to another as well as to increase the risk of churn. In this study we develop a churn prediction model tailored for B2B e-commerce industry by testing the forecasting capability of a new model, the support vector machine (SVM) based on the AUC parameter-selection technique (SVMauc). The predictive performance of SVMauc is benchmarked to logistic regression, neural network and classic support vector machine. Our study shows that the parameter optimization procedure plays an important role in the predictive performance and the SVMauc points out good generalization performance when applied to noisy, imbalance and nonlinear marketing data outperforming the other methods. Thus, our findings confirm that the data-driven approach to churn prediction and the development of retention strategies outperforms commonly used managerial heuristics in B2B e-commerce industry. © 2016 Elsevier Inc.","B2B e-commerce; Churn prediction modeling; Marketing retention strategies; Parameter-selection technique; Support vector machines",{"$nulls":7},"Agnihotri R., Kothandaraman P., Kashyap R., Singh R., Bringing “social” into sales: The impact of salespeople's social media use on service behaviors and value creation, Journal of Personal Selling & Sales Management, 32, 3, pp. 333-348, (2012); Ali H., Exchanging value within individuals’ networks: Social support implications for health marketers, Journal of Marketing Management, 27, 3-4, pp. 316-335, (2011); Au W.H., Chan K.C.C., Yao X., A novel evolutionary data mining algorithm with application to churn prediction, IEEE Transactions on Evolutionary Computation, 7, pp. 532-545, (2003); Baesens B., Viaene S., Van Den Poel D., Vanthienen J., Dedene G., Bayesian neural network learning for repeat purchase modelling in direct marketing, European Journal of Operational Research, 138, 1, pp. 191-211, (2002); Bauer C.L., A direct mail customer purchase model, Journal of Direct Marketing, 2, 3, pp. 16-24, (1988); Boone D.S., Roehm M., Evaluating the appropriateness of market segmentation solutions using artificial neural networks and the membership clustering criterion, Marketing Letters, 13, 4, pp. 317-333, (2002); Boone D.S., Roehm M., Retail segmentation using artificial neural networks, International Journal of Research in Marketing, 19, 3, pp. 287-301, (2002); Buckinx W., Van Den Poel D., Customer base analysis: Partial defection of behaviourally loyal clients in a non-contractual FMCG retail setting, European Journal of Operational Research, 164, 1, pp. 252-268, (2005); Bucklin R.E., Gupta S., Brand choice, purchase incidence, and segmentation: An integrated modeling approach, Journal of Marketing Research, 29, 2, (1992); Burez J., Van den Poel D., CRM at a pay-TV company: Using analytical models to reduce customer attrition by targeted marketing for subscription services, Expert Systems with Applications, 32, 2, pp. 277-288, (2007); Burez J., Van den Poel D., Expert systems with applications handling class imbalance in customer churn prediction, Expert Systems with Applications, 36, 3, pp. 4626-4636, (2009); Chang C., Lin C., LIBSVM : A library for support vector machines, ACM Transactions on Intelligent Systems and Technology (TIST), 2, pp. 1-39, (2011); Chen J., Xu H., Whinston A.B., Moderated online communities and quality of user-generated content, Journal of Management Information Systems, 28, 2, pp. 237-268, (2011); Chen Y., Fay S., Wang Q., The role of marketing in social media: How online consumer reviews evolve, Journal of Interactive Marketing, 25, 2, pp. 85-94, (2011); Coussement K., Improving customer retention management through cost-sensitive learning, European Journal of Marketing, 48, 3/4, pp. 477-495, (2014); Coussement K., Bock K.W.D., Customer churn prediction in the online gambling industry : The beneficial effect of ensemble learning, Journal of Business Research, 66, 9, pp. 1629-1636, (2013); Coussement K., Van den Poel D., Churn prediction in subscription services: An application of support vector machines while comparing two parameter-selection techniques, Expert Systems with Applications, 34, pp. 313-327, (2008); DeLong E.R., DeLong D.M., Clarke-Pearson D.L., Comparing the areas under two or more correlated receiver operating characteristic curves: A nonparametric approach, Biometrics, 44, 3, pp. 837-845, (1988); Eriksson K., Vaghult A.L., Customer retention, purchasing behavior and relationship substance in professional services, Industrial Marketing Management, 29, 4, pp. 363-372, (2000); Ganesh J., Arnold M.J., Reynolds K.E., Understanding the customer base of service providers: An examination of the differences between switchers and stayers, Journal of Marketing, 64, 3, pp. 65-87, (2000); Gordini N., Market-driven management: A critical literature review, Symphonya. 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Gordini; University of Milano-Bicocca, Italy; email: niccolo.gordini@unimib.it",null,"Elsevier Inc.",{"$nulls":5},198501.0,null,"IMMAD",null,"English","Ind. Mark. Manage.","Article","Final",null,"Scopus","2-s2.0-84996482980"]
["Chong A.Y.L.; Li B.; Ngai E.W.T.; Ch'ng E.; Lee F.","Chong, Alain Yee Loong (26654029000); Li, Boying (56733847400); Ngai, Eric W.T. (7003298974); Ch'ng, Eugene (6507026255); Lee, Filbert (57188555372)","26654029000; 56733847400; 7003298974; 6507026255; 57188555372","Predicting online product sales via online reviews, sentiments, and promotion strategies: A big data architecture and neural network approach",2016.0,"International Journal of Operations and Production Management",36.0,4.0,null,358.0,383.0,25.0,125.0,"10.1108/IJOPM-03-2015-0151","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84961626635&doi=10.1108%2fIJOPM-03-2015-0151&partnerID=40&md5=1cd32500e341b8dfac54d8bfd85d5934","Nottingham University Business School China, University of Nottingham Ningbo China, Ningbo, China; Management & Marketing Department, The Hong Kong Polytechnic University, Hong Kong; Big Data and Visual Analytics Lab, University of Nottingham Ningbo China, Ningbo, China; International Studies Department, University of Nottingham Ningbo China, Ningbo, China","Chong A.Y.L., Nottingham University Business School China, University of Nottingham Ningbo China, Ningbo, China; Li B., Nottingham University Business School China, University of Nottingham Ningbo China, Ningbo, China; Ngai E.W.T., Management & Marketing Department, The Hong Kong Polytechnic University, Hong Kong; Ch'ng E., Big Data and Visual Analytics Lab, University of Nottingham Ningbo China, Ningbo, China; Lee F., International Studies Department, University of Nottingham Ningbo China, Ningbo, China","Purpose – The purpose of this paper is to investigate if online reviews (e.g. valence and volume), online promotional strategies (e.g. free delivery and discounts) and sentiments from user reviews can help predict product sales. Design/methodology/approach – The authors designed a big data architecture and deployed Node.js agents for scraping the Amazon.com pages using asynchronous input/output calls. The completed web crawling and scraping data sets were then preprocessed for sentimental and neural network analysis. The neural network was employed to examine which variables in the study are important predictors of product sales. Findings – This study found that although online reviews, online promotional strategies and online sentiments can all predict product sales, some variables are more important predictors than others. The authors found that the interplay effects of these variables become more important variables than the individual variables themselves. For example, online volume interactions with sentiments and discounts are more important than the individual predictors of discounts, sentiments or online volume. Originality/value – This study designed big data architecture, in combination with sentimental and neural network analysis that can facilitate future business research for predicting product sales in an online environment. This study also employed a predictive analytic approach (e.g. neural network) to examine the variables, and this approach is useful for future data analysis in a big data environment where prediction can have more practical implications than significance testing. This study also examined the interplay between online reviews, sentiments and promotional strategies, which up to now have mostly been examined individually in previous studies. © 2016, Emerald Group Publishing Limited.","Big data; Neural network; Online marketplace; Online reviews; Product demands; Promotional marketing; Valence",{"$nulls":7},"Archak N., Ghose A., Ipeirotis P.G., Deriving the pricing power of product features by mining consumer reviews, Management Science: INFORMS, 57, 8, pp. 1485-1509, (2011); Ayat S., Pour Z.A., Comparison between artificial neural network learning algorithms for prediction of student average considering effective factors in learning and educational progress, Journal of Mathematics and Computer Science, 8, 3, pp. 215-225, (2014); Baker B.M., Ayechew M.A., A genetic algorithm for the vehicle routing problem, Computers & Operations Research, 30, 5, pp. 787-800, (2003); Bakos Y., Dellarocas C., Cooperation without enforcement? 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Effects of discrete emotions on the perceived helpfulness of online reviews, Mis Quarterly, 38, 2, pp. 539-560, (2014); Yip L., Law R., User preferences for web site attributes: a study of the Hong Kong Disneyland, Asia Pacific Journal of Tourism Research, 7, 1, pp. 36-44, (2002); Yu X., Liu Y., Huang X., An A., Mining online reviews for predicting sales performance: a case study in the movie domain, IEEE Transactions on Knowledge and Data Engineering, 24, 4, pp. 720-734, (2012); Zhang J.Q., Craciun G., Shin D., When does electronic word-of-mouth matter? A study of consumer product reviews, Journal of Business Research, 63, 12, pp. 1336-1341, (2010); Zhao C., Wu Z., A genetic algorithm for manufacturing cell formation with multiple routes and multiple objectives, International Journal of Production Research, 38, 2, pp. 385-395, (2000); Zhu F., Zhang X.M., Impact of online consumer reviews on sales: the moderating role of product and consumer characteristics, Journal of Marketing, 74, 2, pp. 133-148, (2010); Ch'ng E., The bottom-up formation and maintenance of a twitter community: analysis of the #FreeJahar Twitter community, Industrial Management & Data Systems, 115, 4, pp. 612-624, (2015); Liau B.Y., Tan P.P., Gaining customer knowledge in low cost airlines through text mining, Industrial Management & Data Systems, 114, 9, pp. 1344-1359, (2014); Wang H., Wang W., Product weakness finder: an opinion-aware system through sentiment analysis, Industrial Management & Data Systems, 114, 8, pp. 1301-1320, (2014)","A.Y.L. Chong; Nottingham University Business School China, University of Nottingham Ningbo China, Ningbo, China; email: alain.chong@gmail.com",null,"Emerald Group Publishing Ltd.",{"$nulls":5},1443577.0,null,null,null,"English","Int. J. Oper. Prod. Manage.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-84961626635"]
["Fan W.; Xu M.; Dong X.; Wei H.","Fan, Weiguo (57193392838); Xu, Ming (55519747200); Dong, Xiaobin (10138958700); Wei, Hejie (57193387118)","57193392838; 55519747200; 10138958700; 57193387118","Considerable environmental impact of the rapid development of China's express delivery industry",2017.0,"Resources, Conservation and Recycling",126.0,null,null,174.0,176.0,2.0,68.0,"10.1016/j.resconrec.2017.07.041","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85026833341&doi=10.1016%2fj.resconrec.2017.07.041&partnerID=40&md5=1eedd9fbdbd1a1019cf29ece610bdc35","State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, 100875, China; Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China; Department of Civil and Environmental Engineering, University of Michigan, Ann Arbor, 48109-2125, MI, United States","Fan W., State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, 100875, China, Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China; Xu M., Department of Civil and Environmental Engineering, University of Michigan, Ann Arbor, 48109-2125, MI, United States; Dong X., State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, 100875, China, Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China; Wei H., State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, 100875, China, Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China","The environmental and social problems related to global production and consumption are matters of concern. One component of this is how the express delivery industry is continuing to grow and develop with the rapid development of e-commerce. However, the indirect environmental impacts of the express delivery industry have not been seriously considered. Based on statistics of the types and quantities of packaging materials consumed by China's express delivery industry in 2015, this paper estimated the environmental load of express packaging materials consumed in the processes of production and distribution of express delivery in China. The results show that the rapid development of the express delivery industry will lead to a large consumption of express packaging materials. Even when only considering the processes of production and distribution of express packaging materials, this industry will still become a serious burden on China's environment. This study provides a scientific reference for the environmental impact assessment of China's express delivery industry and may promote the healthy and sustainable development of the express delivery industry. © 2017","Environmental impact; Express delivery industry; Express packaging materials","China; Environmental impact assessments; Packaging; Packaging materials; Sustainable development; Environmental loads; Global production; Scientific references; Social problems; environmental impact assessment; service sector; statistical analysis; sustainable development; air pollution; Article; carbon footprint; China; energy consumption; environmental exploitation; environmental impact; environmental impact assessment; express delivery industry; industry; packaging material; Environmental impact",{"$nulls":4},"National Societal Science Foundation of China, (15ZDB163); National Natural Science Foundation of China, NSFC, (41271549, 41671531); Fundamental Research Funds for the Central Universities, (2014KJJCB33)","This study was supported by National Natural Science Foundation of China (41671531, 41271549), Key Project of the National Societal Science Foundation of China (15ZDB163) and the Fundamental Research Funds for the Central Universities (2014KJJCB33).","Beijing Institute of Graphic Communication, Green Packaging Development Status and Trend Report of China Express Delivery Field, (2015); Chen T., Lin C.W., A fuzzy collaboration system for ubiquitous loading/unloading space recommendation in the logistics industry, Rob. Comput. Integr. Manuf., 45, pp. 86-98, (2017); Davis S.J., Peters G.P., Caldeira K., The supply chain of CO<sub>2</sub> emissions, Proc. Natl. Acad. Sci. U. S. A., 108, pp. 18554-18559, (2011); Feng M.K., Cao G.R., Cheng L., Fu Y.B., Status and greenization of express packaging, J. Beijing Inst. Graph. Commun., 24, pp. 22-25, (2016); IFENG.com, China's Express Business Volume Exceeded 30 Billion, (2016); Liu J.Q., Liu Y., Research on construction of express packaging waste recycling industry in China and its impacts on environment, Environ. Sci. Manage., 42, pp. 18-21, (2017); Takahashi K., Nansai K., Tohno S., Nishizawa M., Kurokawa J., Ohara T., Production-based emissions: consumption-based emissions and consumption-based health impacts of PM2.5 carbonaceous aerosols in Asia, Atmos. Environ., 97, pp. 406-415, (2014); Thinkstep A.G., GaBi 6 Software and Databases, (2016); World Bank, CO, (2017); World Bank, Methane Emissions (thousands of Tons CO, (2017)","X. Dong; State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, 100875, China; email: xbdong@bnu.edu.cn",null,"Elsevier B.V.",{"$nulls":5},9213449.0,null,"RCREE",null,"English","Resour. Conserv. Recycl.","Article","Final",null,"Scopus","2-s2.0-85026833341"]
["Zhang J.; Wang X.; Huang K.","Zhang, Jun (55966697500); Wang, Xuping (35273544600); Huang, Kai (55238241400)","55966697500; 35273544600; 55238241400","Integrated on-line scheduling of order batching and delivery under B2C e-commerce",2016.0,"Computers and Industrial Engineering",94.0,null,null,280.0,289.0,9.0,73.0,"10.1016/j.cie.2016.02.001","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84959334880&doi=10.1016%2fj.cie.2016.02.001&partnerID=40&md5=86d620d466c498f56c8dbb659b5004b8","Institute of Systems Engineering, Dalian University of Technology, Dalian, China; School of Business, Dalian University of Technology, Panjin, China; DeGroote School of Business, McMaster University, Hamilton, Canada","Zhang J., Institute of Systems Engineering, Dalian University of Technology, Dalian, China, DeGroote School of Business, McMaster University, Hamilton, Canada; Wang X., Institute of Systems Engineering, Dalian University of Technology, Dalian, China, School of Business, Dalian University of Technology, Panjin, China; Huang K., DeGroote School of Business, McMaster University, Hamilton, Canada","Order batching is a general method of grouping a set of orders into several sub sets, i.e., batches. As many warehouses outsource order delivery to a Third Party Logistics (3PL) provider in B2C e-commerce, small lot-size orders arriving dynamically within a certain time period should be grouped into batches and packed up before a fixed departure time. Research on on-line order batching problems, however, seldom takes delivery constraints into consideration. This paper studies the integrated on-line order batching and distribution scheduling problem in which the maximal number of orders has to be completed before the vehicles' departure time in the shortest service time. Several novel rule-based solutions are proposed, including the formation of batches, which are assigned to appropriate pickers without any information on the arrival times of future orders. Moreover, the solutions define which orders are urgent and should be picked up directly, and which ones can be satisfied later. The solution algorithms are evaluated through a series of experiments. It is demonstrated that these algorithms can lead to a substantial increase of the number of delivered orders, which reveals the importance of integrating order batching with delivery. © 2016 Elsevier Ltd. All rights reserved.","On-line order batching; Order batching and delivery; Rule-based solutions; Urgency degree","Commerce; Electronic commerce; Outsourcing; Scheduling; Transportation; Delivery constraints; Distribution scheduling; Online scheduling; Order batching; Rule based; Solution algorithms; Third-party logistics (3PL) providers; Urgency degree; Scheduling algorithms",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (71171029, 71471025)","The authors appreciate the constructive suggestions provided by the editor and two anonymous referees. This work is supported by National Natural Science Foundation of China by Grant (Nos. 71471025 , 71171029 ).","Agnetis A., Aloulou M.A., Fu L., Coordination of production and interstage batch delivery with outsourced distribution, European Journal of Operational Research, 238, 1, pp. 130-142, (2014); Amir H.A., Shahrooz T., Pezhman G., Muhamad Z.M.S., Kuan Y.W., Order batching in warehouses by minimizing total tardiness: A hybrid approach of weighted association rule mining and genetic algorithms, The Scientific World Journal, 2013, (2013); Bukchin Y., Khmelnitsky E., Yakuel P., Optimizing a dynamic order-picking process, European Journal of Operational Research, 219, 2, pp. 335-346, (2012); Chang Y.C., Lee C.Y., Machine scheduling with job delivery coordination, European Journal of Operational Research, 158, 2, pp. 470-487, (2004); Chen Z.L., Integrated production and outbound distribution scheduling: Review and extensions, Operations Research, 58, 1, pp. 130-148, (2010); Chen B., Lee C.Y., Logistics scheduling with batching and transportation, European Journal of Operational Research, 189, 3, pp. 871-876, (2008); 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De Koster R., Van Der Poort E.S., Wolters M., Efficient order batching methods in warehouses, International Journal of Production Research, 37, 7, pp. 1479-1504, (1999); Gademann N., Van De Velde S., Order batching to minimize total travel time in a parallel-aisle warehouse, IIE Transactions, 37, 1, pp. 63-75, (2005); Gao S., Qi L., Lei L., Integrated batch production and distribution scheduling with limited vehicle capacity, International Journal of Production Economics, 160, pp. 13-25, (2015); Geismar H.N., Laporte G., Lei L., Sriskandarajah C., The integrated production and transportation scheduling problem for a product with a short lifespan, INFORMS Journal on Computing, 20, 1, pp. 21-33, (2008); Gibson D.R., Sharp G.P., Order batching procedures, European Journal of Operational Research, 58, 1, pp. 57-67, (1992); Hajiaghaei-Keshteli M., Aminnayeri M., Solving the integrated scheduling of production and rail transportation problem by Keshtel algorithm, Applied Soft Computing, 25, pp. 184-203, (2014); Hajiaghaei-Keshteli M., Aminnayeri M., Fatemi Ghomi S.M.T., Integrated scheduling of production and rail transportation, Computers & Industrial Engineering, 74, pp. 240-256, (2014); Henn S., Algorithms for on-line order batching in an order picking warehouse, Computers & Operations Research, 39, 11, pp. 2549-2563, (2012); Henn S., Schmid V., Metaheuristics for order batching and sequencing in manual order picking systems, Computers & Industrial Engineering, 66, 2, pp. 338-351, (2013); Ho Y.C., Tseng Y.Y., A study on order-batching methods of order-picking in a centre with two cross-aisles distribution, International Journal of Production Research, 44, 17, pp. 3391-3417, (2006); Hsieh L.F., Huang Y.C., New batch construction heuristics to optimize the performance of order picking systems, International Journal of Production Economics, 131, 2, pp. 618-630, (2011); Le-Duc T., De Koster R., Travel time estimation and order batching in a 2-block warehouse, European Journal of Operational Research, 176, 1, pp. 374-388, (2007); Li K.P., Ganesan V.K., Sivakumar A.I., Scheduling of single stage assembly with air transportation in a consumer electronic supply chain, Computers & Industrial Engineering, 51, 2, pp. 264-278, (2006); Li C.L., Vairaktarakis G., Coordinating production and distribution of jobs with bundling operations, IIE Transactions, 39, 2, pp. 203-215, (2007); Liu Z., Cheng T.C.E., Scheduling with job release dates, delivery times and preemption penalties, Information Processing Letters, 82, 2, pp. 107-111, (2002); Low C.-R., Chang C.M., Li R.K., Huang C.L., Coordination of production scheduling and delivery problems with heterogeneous fleet, International Journal of Production Economics, 153, pp. 139-148, (2014); Low C.-R., Li R.K., Chang C.M., Integrated scheduling of production and delivery with time windows, International Journal of Production Research, 51, 3, pp. 897-909, (2013); Mastrolilli M., Efficient approximation schemes for scheduling problems with release dates and delivery times, Journal of Scheduling, 6, 6, pp. 521-531, (2003); Matusiak M., De Koster R., Kroon L., Saarinen J., A fast simulated annealing method for batching precedence-constrained customer orders in a warehouse, European Journal of Operational Research, 236, 3, pp. 968-977, (2014); Pratap S., Nayak A., Cheikhrouhou N., Tiwari M.K., Decision support system for discrete robust berth allocation, IFAC-PapersOnLine, 48, 3, pp. 875-880, (2015); Tsai C.Y., Liou J.J.H., Huang T.M., Using a multiple-GA method to solve the batch picking problem: Considering travel distance and order due time, International Journal of Production Research, 46, 22, pp. 6533-6555, (2008); Xu X.H., Liu T., Li K.P., Dong W.H., Evaluating order throughput time with variable time window batching, International Journal of Production Research, 52, 8, pp. 2232-2242, (2014)","X. Wang; School of Business, Dalian University of Technology, Panjin, China; email: wxp@dlut.edu.cn",null,"Elsevier Ltd",{"$nulls":5},3608352.0,null,"CINDD",null,"English","Comput Ind Eng","Article","Final",null,"Scopus","2-s2.0-84959334880"]
["Liu L.; Li K.; Liu Z.","Liu, Ling (57189715639); Li, Kunpeng (55894405000); Liu, Zhixue (55656822100)","57189715639; 55894405000; 55656822100","A capacitated vehicle routing problem with order available time in e-commerce industry",2017.0,"Engineering Optimization",49.0,3.0,null,449.0,465.0,16.0,35.0,"10.1080/0305215X.2016.1188092","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84974802705&doi=10.1080%2f0305215X.2016.1188092&partnerID=40&md5=33e8f3c16f9e2082f683c020b926aa65","School of Management, Huazhong University of Science & Technology, Wuhan, China","Liu L., School of Management, Huazhong University of Science & Technology, Wuhan, China; Li K., School of Management, Huazhong University of Science & Technology, Wuhan, China; Liu Z., School of Management, Huazhong University of Science & Technology, Wuhan, China","In this article, a variant of the well-known capacitated vehicle routing problem (CVRP) called the capacitated vehicle routing problem with order available time (CVRPOAT) is considered, which is observed in the operations of the current e-commerce industry. In this problem, the orders are not available for delivery at the beginning of the planning period. CVRPOAT takes all the assumptions of CVRP, except the order available time, which is determined by the precedent order picking and packing stage in the warehouse of the online grocer. The objective is to minimize the sum of vehicle completion times. An efficient tabu search algorithm is presented to tackle the problem. Moreover, a Lagrangian relaxation algorithm is developed to obtain the lower bounds of reasonably sized problems. Based on the test instances derived from benchmark data, the proposed tabu search algorithm is compared with a published related genetic algorithm, as well as the derived lower bounds. Also, the tabu search algorithm is compared with the current operation strategy of the online grocer. Computational results indicate that the gap between the lower bounds and the results of the tabu search algorithm is small and the tabu search algorithm is superior to the genetic algorithm. Moreover, the CVRPOAT formulation together with the tabu search algorithm performs much better than the current operation strategy of the online grocer. © 2016 Informa UK Limited, trading as Taylor & Francis Group.","Lagrangian relaxation; Order available time; tabu search; vehicle routing","Commerce; Electronic commerce; Genetic algorithms; Lagrange multipliers; Learning algorithms; Network routing; Routing algorithms; Tabu search; Vehicle routing; Vehicles; Capacitated vehicle routing problem; Completion time; Computational results; LaGrangian relaxation; Lagrangian relaxation algorithms; Operation strategy; Order available time; Tabu search algorithms; Algorithms",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (71131004, 71372133)","This work was supported by National Natural Science Foundation of China [grant number 71372133], [grant number 71131004].","Adulyasak Y., Cordeau J.F., Jans R., Optimization-based adaptive large neighbourhood search for the production routing problem, Transportation Science, 48, 1, pp. 20-45, (2012); 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Du T.C., Li E.Y., Chou D., Dynamic vehicle routing for online B2C delivery, Omega, 33, 1, pp. 33-45, (2005); Desrosiers J., Dumas Y., Solomon M.M., Soumis F., Time constraints routing and scheduling, Network Routing, Handbooks in Operations Research and Management Science 8, pp. 35-139, (1995); Dabia S., Ropke S., Van Woensel T., De Kok T., Branch and price for the time-dependent vehicle routing problem with time windows, Transportation Science, 47, 3, pp. 380-396, (2013); Ehmke J.F., Campbell A.M., Urban T.L., Ensuring service levels in routing problems with time windows and stochastic travel times, European Journal of Operational Research, 240, pp. 539-550, (2015); Ehmke J.F., Mattfeld D.C., Vehicle routing for attended home delivery in city logistics, Procedia—Social and Behavioral Sciences, 39, pp. 622-632, (2012); Fisher M.L., The lagrangian relaxation method for solving integer programming problems, Management Science, 27, 1, pp. 1-18, (1981); Fisher M.L., An applications oriented guide to lagrangian relaxation, Interfaces, 15, 2, pp. 10-21, (1985); Garcia J.M., Lozano S., Production and vehicle scheduling for ready-mix operations, Computers & Industrial Engineering, 46, 4, pp. 803-816, (2004); Gendreau M., Hertz A., Laporte G., New insertion and post-optimization procedures for the traveling salesman problem, Operations Research, 40, 6, pp. 1086-1094, (1992); Gong Y.J., Zhang J., Liu O., Huang R.Z., Chung S.H., Shi Y.H., Optimizing the Vehicle Routing Problem with Time Windows: A Discrete Particle Swarm Optimization Approach, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), 42, 2, pp. 254-267, (2012); Guignard M., Kim S., Lagrangean Decomposition: A model yielding stronger lagrangean bounds, Mathematical Programming, 39, pp. 215-228, (1987); Handler G.Y., Zang I., A dual algorithm for the constrained shortest path problem, Networks, 10, 4, pp. 293-309, (1980); Held M., Wolfe P., Crowder H.P., Validation of subgradient optimization, Mathematical Programming, 6, 1, pp. 62-88, (1974); Hong S.C., Park Y.B., A heuristic for bi-objective vehicle routing with time window constraints, International Journal of Production Economics, 62, 3, pp. 249-258, (1999); Jornsten K., Nasberg M., Smeds P., (1985); Jha J.K., Shanker K., A coordinated two-phase approach for operational decisions with vehicle routing in a single-vendor multi-buyer system, International Journal of Production Research, 51, 5, pp. 1426-1450, (2013); Kohl N., Madsen O.B.G., An optimization algorithm for the vehicle routing problem with time windows based on lagrangian relaxation, Operations Research, 45, 3, pp. 395-406, (1997); Lee J., Kim B.I., Johnson A.L., Lee K., The nuclear medicine production and delivery problem, European Journal of Operational Research, 236, 2, pp. 461-472, (2014); Li K., Chen B., Sivakumar A.I., Wu Y., An inventory-routing problem with the objective of travel time minimization, European Journal of Operational Research, 236, 3, pp. 936-945, (2014); Li K.P., Ganesan V.K., Sivakumar A.I., Synchronized scheduling of assembly and multi-destination air-transportation in a consumer electronics supply chain, International Journal of Production Research, 43, 13, pp. 2671-2685, (2005); Li K.P., Ganesan V.K., Sivakumar A.I., Scheduling of single stage assembly with air transportation in a consumer electronic supply chain, Computers & Industrial Engineering, 51, 2, pp. 264-278, (2006); Low C., Li R.K., Chang C.M., Integrated scheduling of production and delivery with time windows, International Journal of Production Research, 51, 3, pp. 897-909, (2013); Malandraki C., Daskin M.S., Time dependent vehicle routing problems: formulations, properties and heuristic algorithms, Transportation Science, 26, 3, pp. 185-200, (1992); Teo J.S., Taniguchi E., Qureshi A.G., Evaluating city logistics measure in e-commerce with multiagent systems, Procedia—Social and Behavioral Sciences, 39, pp. 349-359, (2012); Toth P., Vigo D.M., The Vehicle Routing Problem, (2002); Toth P., Vigo D., The Granular Tabu Search and Its Application to the Vehicle-Routing Problem, INFORMS Journal on Computing, 15, 4, pp. 333-346, (2003); Ullrich C.A., Integrated machine scheduling and vehicle routing with time windows, European Journal of Operational Research, 227, 1, pp. 152-165, (2013); Vallada E., Ruiz R., A genetic algorithm for the unrelated parallel machine scheduling problem with sequence dependent setup times, European Journal of Operational Research, 211, 3, pp. 612-622, (2011); Van Buer M.G., Woodruff D.L., Olson R.T., Solving the medium newspaper production/distribution problem, European Journal of Operational Research, 115, 2, pp. 237-253, (1999); Viergutz C., Knust S., Integrated production and distribution scheduling with lifespan constraints, Annals of Operations Research, 213, 1, pp. 293-318, (2014); Zachariadis E.E., Tarantilis C.D., Kiranoudis C.T., Designing vehicle routes for a mix of different request types, under time windows and loading constraints, European Journal of Operational Research, 229, 2, pp. 303-317, (2013)","K. Li; School of Management, Huazhong University of Science & Technology, Wuhan, China; email: likp@mail.hust.edu.cn",null,"Taylor and Francis Ltd.",{"$nulls":5},"0305215X",null,"EGOPA",null,"English","Eng Optim","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-84974802705"]
["Hayel Y.; Quadri D.; Jiménez T.; Brotcorne L.","Hayel, Yezekael (55694789800); Quadri, Dominique (23397895000); Jiménez, Tania (7004259182); Brotcorne, Luce (6507640397)","55694789800; 23397895000; 7004259182; 6507640397","Decentralized optimization of last-mile delivery services with non-cooperative bounded rational customers",2016.0,"Annals of Operations Research",239.0,2.0,null,451.0,469.0,18.0,36.0,"10.1007/s10479-014-1647-x","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84901738976&doi=10.1007%2fs10479-014-1647-x&partnerID=40&md5=64f2ea744b6c417fdbcac5e19f776063","LIA/CERI, Avignon, France; LRI, Paris, France; INRIA, Lille, France","Hayel Y., LIA/CERI, Avignon, France; Quadri D., LRI, Paris, France; Jiménez T., LIA/CERI, Avignon, France; Brotcorne L., INRIA, Lille, France","The goal of this paper is to introduce bounded rational behaviors in a competitive queuing system. Furthermore, we propose a realistic queuing model for two last-mile delivery services in which consumers are in competition. This work is derived from a real-world e-commerce application. We study the problem using a game theoretical point of view: the e-consumers are interacting through the last-mile delivery service system creating congestion for each other. Specifically, we focus our analysis on several equilibrium concepts from congestion/routing games: Wardrop and Logit equilibria. The difference in these equilibrium concepts is on the rationality level of players in the game. We are able to prove the existence and uniqueness of both equilibria. We compare them through a new metric called the Price of Rationality and we also compare each one to the social optimum solution through the Price of Anarchy. Some numerical results are presented in order to illustrate the theoretical results obtained. © 2014, Springer Science+Business Media New York.","Game theory; Queueing systems; Rationality",{"$nulls":7},"Agatz N.A.H., Fleischmann M., van Nunen J.A.E.E., E-fulfillment and multi-channel distribution: A review, European Journal of Operational Research, 187, 2, pp. 339-356, (2008); Anderson S.P., Goeree J.K., Holt C.A., The logit equilibrium: A perspective on intuitive behavioral anomalies, Southern Economic Journal, 69, 1, pp. 21-47, (2002); Ben-Akiva M., Lerman S., Discrete choice analysis: Theory and application to travel demand, (1985); Boyer K.K., Hult G.T.M., Extending the supply chain: Integrating operations and marketing in the online grocery industry, Journal of Operations Management, 23, 6, pp. 642-661, (2005); Braess D., Uber ein Paradoxon aus der Verkehrsplanung, Unternehmensforschung, 12, (1968); Brouwer L.E.J., Mannigfaltigkeiten Mathematische Annalen (Vol. 71), (1911); Cooper R.B., Introduction to queueing theory, (1981); Dafermos S.C., Sparrow F.T., The traffic assignment problem for a general network, Journal of Research of the U.S. National Bureau of Standards, pp. 91-118, (1969); Erlander S., Stewart N.F., The gravity model in transportation analysis: Theory and extensions; Fudenberg D., Tirole J., Game theory, (1991); Gigerenzer G., Selten R., Bounded rationality, (2002); Hassin R., (2003); Hassin R., Haviv M., Hassin S., To queue or not to queue: Equilibrium behavior in queueing systems, International Series in Operations Research and Management Science, (2006); MacFadden D., Conditional logit analysis of qualitative choice behavior, Frontier of Econometrics, (1974); MacFadden D., Quantal choice analysis: A survey, Annals of Economic and Social Measurement, 5, pp. 363-390, (1976); MacFadden D., Domencich T., Urban travel demand: A behavioral analysis, (1996); Palfrey T., McKelvey R., Quantal response equilibria for normal form games, Games and Economic Behavior, 10, 1, pp. 6-38, (1995); Patriksson M., The traffic assignment problem: Models and methods. Topics in transportation, VS, (1994); Rabinovich E., Bailey J.P., Physical distribution service quality in Internet retailing: Service pricing, transaction attributes, and firm attributes, Journal of Operations Management, 21, 6, pp. 651-672, (2004); Roughgarden T., The price of anarchy, (2005); Wardrop J., Some theoretical aspects of road traffic research, In Proceedings of the institution of civil engineers, 1, (1952)","Y. Hayel; LIA/CERI, Avignon, France; email: yezekael.hayel@univ-avignon.fr",null,"Springer New York LLC",{"$nulls":5},2545330.0,null,null,null,"English","Ann. Oper. Res.","Article","Final",null,"Scopus","2-s2.0-84901738976"]
["Roy D.; Sahoo A.","Roy, Deepankar (57213481981); Sahoo, Amarendra (58823263000)","57213481981; 58823263000","Payment systems in India: Opportunities and challenges",2016.0,"Journal of Internet Banking and Commerce",21.0,2.0,197.0,null,null,48.0,2.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-84987851039&partnerID=40&md5=1e76812326f384b5774e5edb017bf936","National Institute of Bank Management (NIBM), Kondhwe khurd, Pune, 411048, Maharashtra, India; Flame University, 1102 5a, Kalpataru Estate, Pimple Gurav, Pune, Maharashtra, India","Roy D., National Institute of Bank Management (NIBM), Kondhwe khurd, Pune, 411048, Maharashtra, India; Sahoo A., Flame University, 1102 5a, Kalpataru Estate, Pimple Gurav, Pune, Maharashtra, India","An efficient payment system acts as an enabler for speeding up liquidity flow in the economy, apart from ensuring proper utilization of limited resources it also eliminates systemic risks. Flow of funds across borders demands the security, integrity of the payment system and the harmonization of the systems in the related countries. The paper dwells with the need to modernize the payment system and migrate from paper-based to electronic mode of payment system to enhance efficiency and save cost. It delves in to the core of payment systems in the select countries with a comparative analysis. Benchmarking against the BIS core principles of Systemically Important Payment Systems revised as core principles of Financial Markets Infrastructure has been done to ensure convergence with the international best standards for Governance of Payment systems. The payment system of any country, though advanced and sophisticated, does face various risks, viz. bank failures, frauds, counter-party failures, etc. Such aberrations could trigger a chain-reaction that might ultimately result in disruption and distrust of the payment system. For example, if one large payment transaction cannot be settled, it disturbs other transactions leading to failure of the institutions involved in the process ultimately upsetting the entire payment system in the country. Such systematic and cascading breakdown of the payment system can hinder efficacy of monetary policy and badly impact confidence in the financial system. Minimization of systemic risk is therefore a critical challenge facing the regulators. Like in any ambitious economy, in India too, the fast advances in information technology, changes in regulatory framework, setting up of new institutions have aided to the rise of new payment practices, products and delivery channels for small as well as large value, and urgent payments. The paper shows areas for improvement in the efficiency in existing payment systems in India and the other countries especially in regard to the liquidity risk, operational risks, access criterion, transparency etc. In the end, the paper makes a modest attempt to identify opportunities and challenges for India. Numerous major changes in the payment system would take place at a quicker pace as e-commerce becomes more prevalent in the economic activities in the country. © Deepankar Roy, 2016.","Developed economies; Efficiency; India; Payment systems; Payment systems regulation",{"$nulls":7},"(2007); Humphrey David B., Setsuya S., Transforming Payment Systems: Meeting the Needs of Emerging Market Economies, World Bank Discussion, (1995); The Payment and Settlement Act, (2007); Lamberte M.B., The Philippine Payment System: Efficiency and Implications for the Conduct of Monetary Policy, (2005); Sangsubhan K., The Payment System in Thailand: The Evolution of Information Communication Technology, (2009); Murphy N.B., The Future of Banking in America: The Effect on US Banking of Payment System Changes, FDIC Banking Review, (2004); Shirakawa M., Toward Development of Robust Payment and Settlement Systems, (2009); He L.-L., Sappideen O., The Payment System in China, Journal of International Banking Law and Regulation (JIBLR), 23, pp. 168-174, (2008); Balakrishnan M., Improving Payment System Efficiency in India: Next Steps, Journal of Payment Strategy and Systems, 3, pp. 1750-1806, (2009); The Payment System, (2010); Annual Report, (2014); Mavadiya M., European Payments Council Paper Clarifies How to Use E-Mandates, (2015); Poole B., European Payments: Regulators Appetite for Intervention, (2015); The 2013 Federal Reserve Payments Study, (2014); Payment Systems Oversight Report 2008, (2009); Cpss Red Book U.K., Payment, Clearing and Settlement Systems in the United Kingdom, Bank for International Settlements, (2012); Payment Systems in Japan, (2012); Takeshi M., Yasufumi T., Payment Services Act, 2009: The New Japanese Regulatory Framework for Payment Services, Journal of Payments Strategy and Systems, 4, pp. 67-72, (2009); Payment, Clearing and Settlement Systems in China, BIS, (2012); China Payment System Development Report 5, (2008); Meijer C.R., Ming J., Towards an International Payments System in China: An overview of progress and remaining challenges, Journal of Payments Strategy and Systems, (2015); (1998); Hirve A.K., Retail Payments in India - Imperatives of Digital Transformation, Working Paper Presented at the First Banking Research Conference Jointly Hosted by the IBS and Gokhale Institute of Politics and Economy, (2016)",null,null,"ARRAY Development (Canada) Inc.",{"$nulls":5},1.2045357E7,null,null,null,"English","J. Internet Bank. Commer.","Article","Final",null,"Scopus","2-s2.0-84987851039"]
["Cardenas I.D.; Dewulf W.; Vanelslander T.; Smet C.; Beckers J.","Cardenas, Ivan Dario (57191038157); Dewulf, Wouter (57191031550); Vanelslander, Thierry (6504080142); Smet, Christophe (57224489968); Beckers, Joris (57191037901)","57191038157; 57191031550; 6504080142; 57224489968; 57191037901","The e-commerce parcel delivery market and the implications of home B2C deliveries vs pick-up points",2017.0,"International Journal of Transport Economics",44.0,2.0,null,235.0,256.0,21.0,48.0,"10.19272/201706702004","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85027499369&doi=10.19272%2f201706702004&partnerID=40&md5=295eb7c1142eac6880323420d5da69cf","University of Antwerp, Department of Transport and Regional Economics, Belgium; University of Antwerp, Faculty of Applied Economic Sciences, Belgium","Cardenas I.D., University of Antwerp, Department of Transport and Regional Economics, Belgium; Dewulf W., University of Antwerp, Department of Transport and Regional Economics, Belgium; Vanelslander T., University of Antwerp, Department of Transport and Regional Economics, Belgium; Smet C., University of Antwerp, Faculty of Applied Economic Sciences, Belgium; Beckers J., University of Antwerp, Department of Transport and Regional Economics, Belgium","The last mile has been characterised as the most expensive and complicated part of the supply chain, featuring negative impacts on pollution and congestion in densely populated areas. The arrival of e-commerce has accentuated the number of individual home deliveries, increasing the flows in the last-mile. Investigating how to improve the efficiency of logistics in urban areas is a major driver for the success of e-commerce, and contributes to alleviating the negative externalities of urban freight transport derived from it. By means of interviews and empirical analysis, this article targets two goals. Firstly, to conciliate different perspectives about the structure and cost drivers in the market. Secondly, within this framework, to propose a cost model for two of the most popular methods of last-mile delivery: the home delivery and delivery through pick-up points. Main findings: It is concluded that the parcel delivery market remains under a strong competition, driven by efficiency and with little space for innovations. Parcel delivery companies have been handling with failed deliveries via different solutions. While failed deliveries have an impact on the cost structure, achieving higher economies of density has a higher impact on costs reduction. Pick-up points offer a solution to failed deliveries while they increase the density of deliveries at the same time. When the number of parcels to the pick-up point is high enough, benefits for both logistics carriers and the society are achieved. This is due to the reductions in the overall number of vehicle kilometres travelled (VKT). Results show that reductions can be obtained with a limited number of pick-up points. In this paper, a novel typology of the B2C logistics sector is presented together with the most important cost drivers for the sector. In the analysis, an original cost model incorporates cost drivers disregarded in previous modelling efforts, such as the failed deliveries, the modal choice of companies and customers and the stoppage time of a delivery. Furthermore, primary data were obtained to develop the calculations and the results were validated by companies of the sector.","E-commerce; Home delivery; Last mile; Urban logistics",{"$nulls":7},"Adarme Jaimes W., Arango Serna M.D., Cardenas I.D., Logistics behavior in the last mile distribution of alimentary products in Villavicencio, Colombia, Revista EIA, 11, 21, pp. 145-156, (2014); Beardwood J., Halton J.H., Hammersley J.M., The shortest path through many points, Mathematical Proceedings of the Cambridge Philosophical Society, 55, 4, (1959); Blauwens G., De Baere P., Van De Voorde E., Transport Economics, (2014); Borbon-Galvez Y., Cross-border Parcel Logistics, pp. 1-77, (2015); Brown J.R., Guiffrida A.L., Carbon emissions comparison of last mile delivery versus customer pickup, International Journal of Logistics Research and Applications, 17, 6, pp. 503-521, (2014); Browne M., The impact of E-commerce in transport, Joint OECD/ECMT Seminar, (2001); Carlsson J.G., Behroozi M., Worst-case demand distributions in vehicle routing, European Journal of Operational Research, pp. 1-29, (2016); Cherrett T., Et al., Understanding urban freight activity - Key issues for freight planning, Journal of Transport Geography, 24, pp. 22-32, (2012); Collins A.T., Behavioral influences on the environmental impact of collection/delivery points, Green Logistics and Transportation, pp. 15-34, (2015); Cools M., Et al., Onderzoek Verplaatsingsgedrag, (2009); E-commerce and Delivery, (2013); Deflorio F., Et al., The influence of time windows on the costs of urban freight distribution services in city logistics applications, European Journal of Transport and Infrastructure Research, 12, 12, pp. 256-274, (2012); Click and Collect Booms in Europe, (2015); Dennis W.T., Parcel and Small Package Delivery Industry, (2001); Logistics Trend Radar: Delivering Insight Today, (2014); Ducret R., Parcel deliveries and urban logistics: Changes and challenges in the courier express and parcel sector in Europe - The French case, Research in Transportation Business & Management, 11, pp. 15-22, (2014); Durand B., Gonzalez-Feliu J., Urban logistics and e-grocery: Have proximity delivery services a positive impact on shopping trips?, Procedía - Social and Behavioral Stiences, 39, pp. 510-520, (2012); European B2C E-commerce Report 2016, (2016); Edwards J., Et al., Carbon dioxide benefits of using collection-delivery points for failed home deliveries in the United Kingdom, Transportation Research Record: Journal of the Transportation Research Board, 2191, 1, pp. 136-143, (2010); European Cross-border E-commerce Parcels Delivery 2014 ERGP Opinion to the European Commission on a Better Understanding of European Cross-border E-commerce Parcels Delivery Markets and the Functioning of Competition on These Markets, 14, pp. 1-33, (2014); Bringing E-commerce Benefits to Consumers, pp. 1-66, (2011); Green Paper: An Integrated Parcel Delivery Market for the Growth of E-commerce in the EU., (2012); The Green Mile?, (2015); Fernie J., Sparks L., Mckinnon A.C., Retail logistics in the UK: Past, present and future, International Journal of Retail & Distribution Management, 38, 11-12, pp. 894-914, (2010); Figliozzi M.A., Planning approximations to the average length of vehicle routing problems with varying customer demands and routing constraints, Transportation Research Record: Journal of the Transportation Research Board, 2089, 1, pp. 1-8, (2009); Intra-community Cross-border Parcel Delivery, (2011); Gevaers R., Evaluation of Innovations in B2C Last Mile, B2C Reverse & Waste Logistics, (2013); Gevaers R., Van De Voorde E., Vanelslander T., Cost modelling and simulation of last-mile characteristics in an innovative B2C supply chain environment with implications on urban areas and cities, Procedía - Social and Behavioral Sciences, 125, pp. 398-411, (2014); Gonzalez-Feliu J., Cedillo-Campo M.G., Garcia-Alcaraz J.L., An emission model as an alternative to O-D matrix in urban goods transport modelling un modelo de emisión como una alternativa a la generación de matrices O-D para modelar el transporte urbano de carga, DYNA, 81, 187, pp. 249-256, (2014); Van Der Helm P., Competitiveness of Logistics Service Centers in the High Volume Parcel Delivery Market, (2015); Kamarainen V., Saranen J., Holmstrom J., The reception box impact on home delivery efficiency in the e-grocery business, International Journal of Physical Distribution & Logistics Management, 31, 6, pp. 414-426, (2001); Korzhenevych A., Et al., Update of the Handbook on External Costs of Transport, (2014); Lin I.I., Mahmassani H.S., Can online grocers deliver?: Some logistics considerations, Transportation Research Record: Journal of the Transportation Research Board, 1817, 1, pp. 17-24, (2007); Manyika J., Roxburgh C., The Great Transformer: The Impact of the Internet on Economic Growth and Prosperity, (2011); Morganti E., Seidel S., Et al., The impact of e-commerce on final deliveries: Alternative parcel delivery services in France and Germany, International Scientific Conference on Mobility and Transport, (2014); Morganti E., Dablanc L., Fortin F., Final deliveries for online shopping: The deployment of pickup point networks in urban and suburban areas, Research in Transportation Business & Management, 11, pp. 23-31, (2014); Morganti E., Dablanc L., Fortin F., Final deliveries for online shopping: The deployment of pickup point networks in urban and suburban areas, Research in Transportation Business & Management, 11, pp. 23-31, (2012); Onghena E., The Impact of the Cost Structure on the Strategic Behaviour of Integrators, (2013); Pei Z., Paswan A., Yan R., E-tailer's return policy, consumer's perception of return policy fairness and purchase intention, Journal of Retailing and Consumer Services, 21, 3, pp. 249-257, (2014); Rotem-Mindali O., Weltevreden J.W.J., Transport effects of e-commerce: What can be learned after years of research?, Transportation, 40, 5, pp. 867-885, (2013); Song L., Et al., Addressing the Last Mile Problem - The Transport Impacts of Collection/delivery Points, (2009); Stone R.E., Some average distance results, Transportation Science, 25, 1, pp. 83-90, (1991); Vanelslander T., Deketele L., Van Hove D., Commonly used e-commerce supply chains for fast moving consumer goods: Comparison and suggestions for improvement, International Journal of Logistics: Research and Applications, 16, 3, pp. 243-256, (2013); Visser J., Nemoto T., Browne M., Home delivery and the impacts on urban freight transport: A review, Procedía - Social and Behavioral Sciences, 125, pp. 15-27, (2014); Weltevreden J.W.J., B2c e-commerce logistics: The rise of collection-and-delivery points in The Netherlands, International Journal of Retail & Distribution Management, 36, 8, pp. 638-660, (2008)","I.D. Cardenas; University of Antwerp, Department of Transport and Regional Economics, Belgium; email: ivandario.cardenasbarbosa@uantwerpen.be",null,"Gruppo Editoriale Internazionale Srl.",{"$nulls":5},3035247.0,null,null,null,"English","Int. J. Transp. Econ.","Article","Final",null,"Scopus","2-s2.0-85027499369"]
["Tandon U.; Kiran R.; Sah A.N.","Tandon, Urvashi (57190029593); Kiran, Ravi (22985431500); Sah, Ash N. (57190030141)","57190029593; 22985431500; 57190030141","Customer Satisfaction as mediator between website service quality and repurchase intention: An emerging economy case",2017.0,"Service Science",9.0,2.0,null,106.0,120.0,14.0,75.0,"10.1287/serv.2016.0159","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85029378722&doi=10.1287%2fserv.2016.0159&partnerID=40&md5=bf13183baab6cc18c3d6bd253114053c","School of Humanities and Social Sciences, Thapar University, Patiala, 147004, India","Tandon U., School of Humanities and Social Sciences, Thapar University, Patiala, 147004, India; Kiran R., School of Humanities and Social Sciences, Thapar University, Patiala, 147004, India; Sah A.N., School of Humanities and Social Sciences, Thapar University, Patiala, 147004, India","The purpose of this research is to develop a research model to understand the important dimensions of website service quality and its influence on repurchase intention. The study also analyzes the mediating effect of customer satisfaction on repurchase intention. The results of empirical analysis confirmed that website quality can be conceptualized as a composite of navigation, ease of understanding, information usefulness, website design, ease of use, security and privacy, ease of ordering, and customization. Second, website quality positively affects repurchase intention and customer satisfaction. Third, website service quality can affect repurchase intention by enhancing mediators like customer satisfaction, as it has full mediating effect on repurchase intention. This study has developed the instrument dimensions of website service quality in online shopping context. The study has also refined the scale of repurchase intention by including \"cash-on-delivery\" (COD) mode of payment as a new dimension to inculcate confidence for online shopping in emerging economies. © 2017 INFORMS.","Customer satisfaction; Ease of use; Information usefulness; Internet marketing; Navigation; Online shopping; Repurchase intention; Website design; Website service quality",{"$nulls":7},"Ahn T., Ryu S., Han I., The impact of Web quality and playfulness on user acceptance of online retailing, Inform. Management, 44, 3, pp. 263-275, (2007); Aladwani A.M., Palvia P.C., Developing and validating an instrument for measuring user-perceived web quality, Inform. Management, 39, 6, pp. 467-476, (2002); Bai B., Law R., Wen I., The impact of website quality on customer satisfaction and purchase intentions: Evidence from Chinese online visitors, Internat. J. Hospitality Management, 27, 3, pp. 391-402, (2008); Bansal H.S., Mc Dougall G.H.G., Dikolli S.S., Sedatole K.L., Relating e-satisfaction to behavioural outcomes; An empirical study, J. Services Marketing, 18, 4, pp. 290-302, (2004); Barnes S., Vidgen R., An evaluation of cyber bookshops: The WebQual method, Internat. J. Electronic Commerce, 6, 1, pp. 11-30, (2001); Bisen A., Singh P., E-tailing in India; Unlocking the Potential, (2013); Boulding W., Kalra A., Staelin R., Zeithaml V., A dynamic process model of service quality: From expectations to behavioral intentions, J. Marketing Res., 30, 1, pp. 7-27, (1993); Chang H.H., Wang Y.H., Yang W.H., The impact of e-service quality, customer satisfaction and loyalty on e-marketing: Moderating effect of perceived value, Total Quality Management Bus. Excellence, 20, 4, pp. 423-443, (2009); Chau V.S., Kao Y.Y., Bridge over troubled water or long and winding road? Gap-5 in airline service quality performance measures, Managing Service Quality, 19, 1, pp. 106-134, (2009); Chen H.Y., Hsu C.I., Lin C.C., Website attributes that increase consumer purchase intention: A conjoint analysis, J. Bus. Res., 63, 9-10, pp. 1007-1014, (2010); Chiejina C., Olamide S.E., Investigating the significance of the \"Pay on Delivery\" option in emerging prosperity of the Nigerian e-commerce sector, J. Marketing Management, 5, 1, pp. 120-135, (2014); Cristobal E., Flavian C., Guinaliu M., Perceived e-service quality: Measurement, validation and effects on consumer satisfaction and website loyalty, Managing Service Quality, 17, 3, pp. 317-340, (2007); Floh A., Treiblmaier H., What keeps the e-banking customer loyal? A multigroup analysis of the moderating role of consumer characteristics on e-loyalty in the financial service industry, J. 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Retail Distribution Management, 33, 2, pp. 161-176, (2005); Li W.Z., Jiao A.Y., The impact of website and offline equality on relationship quality: An empirical study on e-retailing, 4th Internat. Conf. Wireless Communications, Networking Mobile Computing \"WiCOM\", October 12-14, Dalian, China, (2008); Loiacono E., Watson R., Goodhue D., WebQual: An instrument for consumer evaluation of web sites, Internat. J. Electronic Commerce, 11, 3, pp. 51-87, (2007); MacKinnon D.P., Warsi G., Dwyer J.H., A simulation study of mediated effect measures, Multivariate Behav. Res., 30, 1, pp. 41-62, (1995); Mithas S., Ramasubbu N., Krishnan M.S., Fornell C., Designing websites for customer loyalty: A multilevel analysis, J. Management Inform. Systems, 23, 3, pp. 97-120, (2006); Nair J.R., E-tailing paradigm: A diagnostic and prognostic study of e-tailing practices in Bangalore metropolitan area/Dharana: Bhavan's Internat, J. Bus., 3, 1, pp. 32-59, (2009); Oliver R.L., Satisfaction: A Behavioral Perspective on the Consumer, (1997); Omar M., Bathgate I., Nwankwo S., Internet marketing and customer satisfaction in emerging markets: The case of Chinese online shoppers, Competitiveness Rev.: Internat. Bus. J., 21, 2, pp. 224-237, (2011); Palvia P., Editorial preface the World IT project: A program on international research and call for participation, J. Global Inform. Tech. Management, 16, 2, pp. 1-5, (2013); Parasuraman A., Grewel D., The impact of technology on the quality-value-loyalty chain: A research agenda, J. Acad. Marketing Sci., 28, 1, pp. 168-174, (2000); Parasuraman A., Zeithaml V.A., Berry L., SERVQUAL: A multi-item scale for measuring consumer perception of service quality, J. Retailing, 64, 1, pp. 2-40, (1998); Parasuraman A., Zeithaml V.A., Malhotra A., E-S-Qual: A multiple-item scale for assessing electronic service quality, J. Service Res., 7, 3, pp. 213-233, (2005); Ranganathan C., Ganapathy S., Key dimensions of business to consumer web sites, Inform. Management, 39, 6, pp. 457-465, (2002); Santos J., E-service quality: A model of virtual service quality dimensions, Managing Service Quality, 13, 1, pp. 233-246, (2003); Shankar V., Smith A.K., Rangaswamy A., Customer satisfaction and loyalty in online and offline environments, Internat. J. Res. Marketing, 20, 2, pp. 153-175, (2003); Shin J.K., Chung K.H., Oh J.S., Lee C.W., The effect of site quality on repurchase intention in Internet shopping through mediating variables: The case of university students in South Korea, Internat. J. Inform. Management, 33, 3, pp. 453-463, (2013); Singh S.S., Dalal N., Spears N., Understanding web home page perception, Eur. J. Inform. Systems, 14, 3, pp. 288-302, (2006); Srivastava R., Customer satisfaction-loyalty link in Indian online retail, Management Insight, 10, 2, pp. 57-60, (2014); Swaid S.I., Wigand R.T., Measuring the quality of e-service: Scale development and initial validation, J. Electronic Commerce Res., 10, 1, pp. 13-28, (2009); Tandon U., Kiran R., Sah A.N., Customer satisfaction using website functionality, perceived usability and perceived usefulness towards online shopping in India, Inform. Development, 32, 5, pp. 1657-1673, (2015); Tandon U., Kiran R., Sah A.N., Analyzing deterrents to online retailing: A study of users and non users in India, Global Bus. Management Res.: Internat. J., 7, 4, pp. 21-41, (2015); Thakur R., Srivastava M., A study on the impact of consumer risk perception and innovativeness on online shopping in India, Internat. J. Retail Distribution Management, 43, 2, pp. 148-166, (2015); Treiblmaier H., Pinterits A., Developing metrics for web sites, J. Comput. Inform. Systems, 50, 3, pp. 1-10, (2010); Udo J.G., Bagchi K.K., Peeter J.K., An assessment of customers e-service quality perception, satisfaction and intention, Internat. J. Informa. Management, 30, 6, pp. 481-492, (2010); Wang Y.J., Hernandez M.D., Minor M.S., Web aesthetics effects on perceived online service quality and satisfaction in an e-tail environment: The moderating role of purchase task, J. Bus. Res., 63, 9-10, pp. 935-942, (2010); Wolfinbarger M., Gilly M., E-TailQ: Dimensionalizing, measuring and predicting e-tail quality, J. Retailing, 79, 3, pp. 183-198, (2003); Wolner-Rosslhuber K., Burger C., Gussenbauer J., Internet payment behavior in Austria, Monetary Policy Econom., 13, 3, pp. 29-41, (2013); Yang Z., Jun M., Peterson R.T., Measuring customer perceived online service quality: Scale development and managerial implications, Internat. J. Oper. Production Management, 24, 11, pp. 149-174, (2004); Yoo B., Donthu N., Developing a scale to measure the perceived quality of Internet shopping sites (SITEQUAL), Quart. J. Electronic Commerce, 2, 1, pp. 31-47, (2001); Zeithaml V.A., Parasuraman A., Malhotra A., A Conceptual Framework for Understanding E-service Quality: Implications for Future Research and Managerial Practice, (2000); Zeithaml V.A., Parasuraman A., Malhotra A., Service quality delivery through web sites: A critical review of extant knowledge, J. Acad. Marketing Sci., 30, 4, pp. 362-375, (2002); Zhang Y., Fang Y., Wei K.K., Ramsey E., McCole P., Chen H., Repurchase intention in B2C e-commerce-A relationship quality perspective, Inform. Management, 48, 6, pp. 192-200, (2011); Zhou T., Lu Y., Wang B., The relative importance of website design quality and service quality in determining consumers' online repurchase behavior, Inform. Systems Management, 26, 4, pp. 327-337, (2009)",null,null,"INFORMS Inst.for Operations Res.and the Management Sciences",{"$nulls":5},2.1643962E7,null,null,null,"English","Serv. Sci.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85029378722"]
["Xue W.","Xue, Weizhong (57194524450)",5.719452445E10,"Employment status of graduates of logistics management specialty based on ARCS motivation design pattern",2017.0,"Agro Food Industry Hi-Tech",28.0,1.0,null,1680.0,1684.0,4.0,0.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85020506757&partnerID=40&md5=8c54ade37e4939b5779096a7e8c0396c","Tianjin Sino-German University of Applied Sciences, Tianjin, China","Xue W., Tianjin Sino-German University of Applied Sciences, Tianjin, China","The demand for personnel with logistics management skills is increasing with the continuous development and progress of the global e-commerce industry. Therefore, analyzing the comprehensive training and employment of logistics management graduates is crucial. Considering the current situation, this study examined and discussed the employment status of graduates who specialize in logistics management based on the motivation design pattern of attention, correlation, confidence, and satisfaction (ARCS). The connotation of the ARCS motivation design model and its positive effect on the actual employment of logistics management graduates are introduced. The actual employment statuses of these graduates and the employed research method are described. The employment rate, quality, employment direction, the ARCS model of motivation design, logistics management, and other aspects that affect the employment of graduates are identified. Analysis results on the employment status of logistics management graduates based on the ARCS model of motivational design are presented. The main objectives of the current study are as follows: First is to explain the employment status of graduates who specialize in logistics management based on the ARCS model of motivational design; Second is to identify and analyze the current problems of logistics management graduates in training and employment by conducting a survey. The study provides a suitable direction in conducting surveys to determine the employment status of logistics management graduates based on the ARCS model of motivation design and contribute to future development.","ARCS motivation design; Employment situation; Investigation and research; Logistics management","Human resource management; Motivation; Personnel; Surveys; Continuous development; Current problems; Current situation; Employment situation; Employment status; Global e commerces; Logistics management; research methods; Employment",{"$nulls":6},"Keller J., Suzuki K., Learner motivation and e-learning design: A multinationally validated process, Journal of Educational Media, 29, 3, pp. 229-239, (2004); Liao H.C., Wang Y., Applying the ARCS motivation model in technological and vocational education, Contemporary Issues in Education Research (CIER), 1, 2, pp. 53-58, (2011); Keller J.M., Development and use of the ARCS model of instructional design, Journal of Instructional Development, 10, 3, pp. 2-10, (1987); Hodges C.B., Designing to motivate: Motivational techniques to incorporate in e-learning experiences, The Journal of Interactive Online Learning, 2, 3, pp. 1-7, (2004); Colakoglu O.M., Akdemir O., Motivational Measure of the Instruction Compared: Instruction Based on the ARCS Motivation Theory vs Traditional Instruction in Blended Courses, Turkish Online Journal of Distance Education, 11, 2, pp. 73-89, (2012); Cheng Y.C., Yeh H.T., From concepts of motivation to its application in instructional design: Reconsidering motivation from an instructional design perspective, British Journal of Educational Technology, 40, 4, pp. 597-605, (2009); Huett J.B., Kalinowski K.E., Moller L., Et al., Improving the motivation and retention of online students through the use of ARCS-based e-mails, The Amer. Jrnl. of Distance Education, 22, 3, pp. 159-176, (2008); Huang W.H., Huang W.Y., Tschopp J., Sustaining iterative game playing processes in DGBL: The relationship between motivational processing and outcome processing, Computers & Education, 55, 2, pp. 789-797, (2010); Kebritchi M., Hirumi A., Bai H., The effects of modern mathematics computer games on mathematics achievement and class motivation, Computers & Education, 55, 2, pp. 427-443, (2010); Bowersox D.J., Carter P.L., Monczka R.M., Materials logistics management, International Journal of Physical Distribution & Logistics Management, 3, 8, pp. 12-16, (2013); Wu Y.C.J., Huang S.K., Goh M., Et al., Global logistics management curriculum: Perspective from practitioners in Taiwan, Supply Chain Management: An International Journal, 18, 4, pp. 376-388, (2013); Habib M., Jungthirapanich C., International Supply Chain Management: Integrated Educational Supply Chain Management (IESCM) Model for the Universities, International Retailing: Text and Readings, 3, 8, pp. 1-18, (2010); Sweeney D., Campbell J., Mundy R., Teaching supply chain and logistics management through commercial software, The International Journal of Logistics Management, 21, 2, pp. 293-308, (2010); Kot S., Slusarczyk B., Survey on requirements for logistics employee, Advanced Logistic Systems, 4, 1, pp. 27-32, (2010); Shi Y., Handfield R., Talent management issues for multinational logistics companies in China: Observations from the field, International Journal of Logistics Research and Applications, 15, 3, pp. 163-179, (2012)",null,null,"TeknoScienze",{"$nulls":5},1.7226996E7,null,null,null,"English","Agro Food Ind. Hi-Tech","Article","Final",null,"Scopus","2-s2.0-85020506757"]
["Yang M.; Mahmood M.; Zhou X.; Shafaq S.; Zahid L.","Yang, Mengke (56486399700); Mahmood, Movahedipour (57192377176); Zhou, Xiaoguang (9746372900); Shafaq, Salam (57199270114); Zahid, Latif (57195309570)","56486399700; 57192377176; 9746372900; 57199270114; 57195309570","Design and implementation of cloud platform for intelligent logistics in the trend of intellectualization",2017.0,"China Communications",14.0,10.0,8107642.0,180.0,191.0,11.0,38.0,"10.1109/CC.2017.8107642","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85037719000&doi=10.1109%2fCC.2017.8107642&partnerID=40&md5=236bc7d5c12a94fc3eacb5f39b8ff373","School of Automation, Beijing University of Posts and Telecommunications, Beijing, 100876, China; Academic Center for Education, Culture and Research, Tehran, 14155-4364, Iran; School of Economics and Management, Beijing University of Posts and Telecommunications, Beijing, 100876, China","Yang M., School of Automation, Beijing University of Posts and Telecommunications, Beijing, 100876, China; Mahmood M., Academic Center for Education, Culture and Research, Tehran, 14155-4364, Iran, School of Economics and Management, Beijing University of Posts and Telecommunications, Beijing, 100876, China; Zhou X., School of Automation, Beijing University of Posts and Telecommunications, Beijing, 100876, China; Shafaq S., School of Economics and Management, Beijing University of Posts and Telecommunications, Beijing, 100876, China; Zahid L., School of Economics and Management, Beijing University of Posts and Telecommunications, Beijing, 100876, China","Intellectualization has become a new trend for telecom industry, driven by intelligent technology including cloud computing, big data, and Internet of things. In order to satisfy the service demand of intelligent logistics, this paper designed an intelligent logistics platform containing the main applications such as e-commerce, self-service transceiver, big data analysis, path location and distribution optimization. The intelligent logistics service platform has been built based on cloud computing to collect, store and handling multi-source heterogeneous mass data from sensors, RFID electronic tag, vehicle terminals and APP, so that the open-access cloud services including distribution, positioning, navigation, scheduling and other data services can be provided for the logistics distribution applications. And then the architecture of intelligent logistics cloud platform containing software layer (SaaS), platform layer (PaaS) and infrastructure (IaaS) has been constructed accordance with the core technology relative high concurrent processing technique, heterogeneous terminal data access, encapsulation and data mining. Therefore, intelligent logistics cloud platform can be carried out by the service mode for implementation to accelerate the construction of the symbiotic win-win logistics ecological system and the benign development of the ICT industry in the trend of intellectualization in China. © 2013 IEEE.","big data; cloud computing; cloud platform; intellectualization; intelligent logistics",{"$nulls":5},"China Postdoctoral Science Foundation, (2016M600972); National Key Research and Development Program of China, NKRDPC, (2016YFC0803206)","This research was supported in part by National Key Research and Development Program under Grant No. 2016YFC0803206 and China Postdoctoral Science Foundation under Grant No.2016M600972 .","Firdhous M., Ghazali O., Hassan S., Cloud computing for rural ICT development: Opportunities and challenges, Proc. International Conference On Computing, Electrical and Electronics Engineering. 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IEEE, pp. 305-308, (2010); Cegielski C.G., Farmer L.A., Wu Y., Et al., Adoption of cloud computing technologies in supply chains: An organizational information processing theory approach, International Journal of Logistics Management, 23, 2, pp. 184-211, (2012); Smirnov A., Levashova T., Shilov N., RFID-Based Intelligent Logistics for Distributed Production Networks, pp. 117-124, (2008); Deng H., Deng W., Identity authentication in RFID based logistics-customs clearance service platform, Proc.Fifth International Conference On Intelligent Information Hiding and Multimedia Signal Processing. IEEE Computer Society, pp. 604-607, (2009); Yang M.K., Zhou X.G., Et al., Challenges and solutions of information security issues in the age of big data, China Communications, 13, 3, pp. 193-202, (2016); Mayer V., Cukier K., Big Data: A revolution that will transform how we live, work, think, American Journal of Epidemiology, 17, 9, pp. 181-183, (2014); Taniguchi E., Shimamoto H., Intelligent transportation system based dynamic vehicle routing and scheduling with variable travel times, Transportation Research Part C Emerging Technologies, 12, 3, pp. 235-250, (2004); Xia Z.H., Zhang L.G., Liu D.D., Attribute-based access control scheme with efficient revocation in cloud computing, China Communications, 13, 7, pp. 92-99, (2016); Nunez A., Poletti J.L., Caminero A.C., Et al., Design of a new cloud computing simulation platform, Proc.Computational Science and Its Applications, pp. 582-593, (2011); Dong J.K., Wang H.B., Cheng H.B., Shiduan energy-performance tradeoff s in iaas cloud with virtual machine scheduling, China Communications, 12, 2, pp. 155-166, (2015); Arnold U., Oberlander J J., Schwarzbach B., Logical-Development of cloud computing platforms and tools for logistics hubs and communities, Proc.Computer Science and Information Systems. IEEE, pp. 1083-1090, (2012); Loutas N., Kamateri E., Tarabanis K., A semantic interoperability framework for cloud platform as a service, Proc.Third International Conference On Cloud Computing Technology and Science. IEEE, pp. 280-287, (2011); Wu X., Zhu X., Wu G.Q., Et al., Data mining with big data, IEEE Transactions On Knowledge & Data Engineering, 26, 1, pp. 97-107, (2014); Han J., Kamber M., Data mining: Concepts and techniques, Morgan Kaufmann, Proc. Machine Press, pp. 394-395, (2001); Zhao L., Liu A., Keung J., Evaluating cloud platform architecture with the CARE framework, Proc. Software Engineering Conference IEEE, pp. 60-69, (2010)","M. Yang; School of Automation, Beijing University of Posts and Telecommunications, Beijing, 100876, China; email: yangmengke@139.com",null,"Editorial Department of China Communications",{"$nulls":5},1.6735447E7,null,null,null,"English","China Commun.","Article","Final",null,"Scopus","2-s2.0-85037719000"]
["Li H.","Li, Huang (57194578362)",5.7194578362E10,"Research on logistics transportation management information system based on the third generation mobile communication technology",2017.0,"Agro Food Industry Hi-Tech",28.0,3.0,null,761.0,765.0,4.0,0.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85020931223&partnerID=40&md5=b370cc0bf7677da36f864da650782f28","Chongqing City Managment College, Chongqing, China","Li H., Chongqing City Managment College, Chongqing, China","The rapid development of Internet technology and e-commerce has directly led to the rapid logistics transportation industry since the 21st Century. Logistics transportation management has become an important aspect in competition among enterprises and good logistics transportation service has become an important medium to promote the progress of market economy and regional economies in China. Based on the starting point of technology, this thesis introduces the third generation mobile communication technology, analyzes several key technologies in logistics transportation management system and finally discusses the development design of logistics transportation management system on the basis of third generation mobile communication technology so as to further improve the logistics transportation service level and logistics transportation capacity.","Logistics transportation; MBT; MIS; System design","Competition; Economics; Information management; Management information systems; Mobile telecommunication systems; Systems analysis; Transportation; Development designs; Internet technology; Key technologies; Logistics transportations; Market economies; Regional economy; Third generation mobile communications; 3G mobile communication systems",{"$nulls":6},"Adibi J.J., Cartus A., Et al., Teratogenic effects of the zika virus and the role of the placenta, Lancet, 387, 1027, pp. 1587-1590, (2016); Varella L., Buss G.M., Information technology as the main competence in the design of the strategic planning of logistics Platforms, Journal of Technology Management & Innovation, 8, 3, pp. 29-30, (2013); Zhou X.L., Research on management of emergency material based on information technology, Applied Mechanics & Materials, 644-650, pp. 6178-6180, (2014); Demir E., Bektas T., Laporte G., A review of recent research on green road freight transportation, European Journal of Operational Research, 237, 3, pp. 775-793, (2013); Amponsahtawiah K., Annor F., Arthur B.G., Linking commuting stress to job satisfaction and turnover intention: The mediating role of burnout, Journal of Workplace Behavioral Health, 31, 2, pp. 104-123, (2016); Oliveira R.R., Cardoso I.M.G., Barbosa J.L.V., Et al., An intelligent model for logistics management based on geofencing algorithms and RFID technology, Expert Systems with Applications, 42, 15-16, pp. 6082-6097, (2015); Chen K.K., Ho H.P., Chang C.T., Estimating attributes importance for container shipping industry by closing the listening gap with maximum convergent validity, Transportation Research Part e Logistics & Transportation Review, 79, pp. 145-163, (2015); Zhang Q., Li Z., Design and implementation of an intelligent logistics distribution system based on the internet of things, Bioresource Technology, 99, 8, (2015); Hu P., Tang K., Five-axis tool path generation based on machinedependent potential field, International Journal of Computer Integrated Manufacturing, 29, 6, pp. 1-16, (2015)",null,null,"TeknoScienze",{"$nulls":5},1.7226996E7,null,null,null,"English","Agro Food Ind. Hi-Tech","Article","Final",null,"Scopus","2-s2.0-85020931223"]
["Jeng Y.-L.; Huang T.-C.","Jeng, Yu-Lin (8967553400); Huang, Tien-Chi (16309511500)","8967553400; 16309511500","Design of a self-learning recommendation system with integration of personal cloud storage technology",2017.0,"Journal of Internet Technology",18.0,7.0,null,1525.0,1532.0,7.0,1.0,"10.6138/JIT.2017.18.7.20151123","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85041813840&doi=10.6138%2fJIT.2017.18.7.20151123&partnerID=40&md5=90a89ae34dd5a4a682651a138cc063df","Departmentt of Information Management, Southern Taiwan University of Science and Technology, Taiwan; Department of Information Management, National Taichung University of Science and Technology, Taiwan","Jeng Y.-L., Departmentt of Information Management, Southern Taiwan University of Science and Technology, Taiwan; Huang T.-C., Department of Information Management, National Taichung University of Science and Technology, Taiwan","The success of mobile commerce adoption hinges on their ability to cover user shopping behaviors and attract consumer interest. In addition to anytime and anywhere paradigm, mobile commerce applications required to be flexible and personalized. In this work, we develop a mobile commerce system which introduces the Personal and Entry Level Storage (PELS) technology and its integration and applications with other e-commerce modules such as POS and vendor system. The benefits of the proposed system include: (1) Against advertising harassment, (2) Expanding the ability of personal cloud storage, (3) Analyzing the shopping trend for consumers and (4) Explicit shopping recommendation and shopping discount message delivery. A system scenario process is depicted to provide a generic paradigm for consumers and vendors. Furthermore, in terms of this innovative personalized e-commerce system, we discuss three managerial implications for future research and practice.","Mobile Commerce; Open APIs; Personal And Entry Level Storage; POS System; Shopping Recommendation Service","Behavioral research; Commerce; Consumer behavior; Electronic commerce; Recommender systems; Consumer interests; Managerial implications; Mobile commerce applications; Open APIs; Personalized e commerces; Shopping behavior; Shopping Recommendation Service; System scenarios; Mobile commerce",{"$nulls":4},"Ministry of Science and Technology, MOST; Ministry of Science and Technology of the People's Republic of China, MOST, (103-2511-S-025-001-MY3, 104-2511-S-025-002-MY3, MOST 104-2511-S-218-001, MOST 104-2511-S-218-006)","This research was supported in part by the Ministry of Science and Technology of the Republic of China, Taiwan, under grants MOST 104-2511-S-218-001, MOST 104-2511-S-218-006, MOST 103-2511-S-025-001-MY3 and MOST 104-2511-S-025-002-MY3","Schafer J.B., Konstan J., Riedl J., Recommender systems in E-commerce, 1st ACM Conference On Electronic Commerce, pp. 158-166, (1999); Hung L.-P., A personalized recommendation system based on product taxonomy for one-to-one marketing online, Expert Systems with Applications, 29, 2, pp. 383-392, (2005); Choi S.H., Kang S., Jeon Y.J., Personalized recommendation system based on product specification values, Expert Systems with Applications, 31, 3, pp. 607-616, (2006); Zhang Y., Jiao J.R., An associative classificationbased recommendation system for personalization in B2C E-commerce applications, Expert Systems with Applications, 33, 2, pp. 357-367, (2007); Lee S.-C., Kim S.-W., Park S., Recommendation in online shopping malls: Results and experiences, 2013 Research in Adaptive and Convergent Systems, pp. 116-117, (2013); Wei K., Huang J., Fu S., A survey of E-commerce recommender systems, International Conference On Service Systems and Service Management, pp. 1-5, (2007); Corbitt B.J., Thanasankit T., Yi H., Trust and E-commerce: A study of consumer perceptions, Electronic Commerce Research and Applications, 2, 3, pp. 203-215, (2003); Jun S., Sha-Sha Y., The application of cloud storage technology in SMEs, International Conference On E-Business and E-Government, (2011); Huang Y.-M., Liang T.-H., A technique for tracking the reading rate to identify the e-book reading behaviors and comprehension outcomes of elementary school students, British Journal of Educational Technology, 46, 4, pp. 864-876, (2014); Liang T.-H., Huang Y.-M., An investigation of reading rate patterns and retrieval outcomes of elementary school students with e-books, Journal of Educational Technology & Society, 17, 1, pp. 218-230, (2013); Deng J., Hu J., Liuand J Wu A.C.M., Research and application of cloud storage, 2nd International Workshop On Intelligent Systems and Applications, (2010); Al Feel H.T., Khafagy M.H., OCSS: Ontology cloud storage system, First International Symposium On Network Cloud Computing and Applications, pp. 9-13, (2011); Srinivasan J., Wei W., Ma X., Yu T., EMFS: Email-based personal cloud storage, 6th IEEE International Conference On Networking, Architecture and Storage, pp. 248-257, (2011); He Q., Li Z., Zhang X., Study on cloud storage system based on distributed storage systems, International Conference On Computational and Information Sciences, pp. 1332-1335, (2010); Koletka R., Hutchison A., An architecture for secure searchable cloud storage, Information Security South Africa, pp. 1-7, (2011); Hao L., Han D., The study and design on securecloud storage system, International Conference On Electrical and Control Engineering, pp. 5126-5129, (2011); Zhang D.-W., Sun F.-Q., Cheng X., Liu C., Research on hadoop-based enterprise file cloud storage system, 3rd International Conference On Awareness Science and Technology, pp. 434-437, (2011); Zhang X., Du H.-T., Chen J.-Q., Lin Y., Zeng L.-J., Ensure data security in cloud storage, International Conference On Network Computing and Information Security, pp. 284-287, (2011); Liu W., Research on cloud computing security problem and strategy, 2nd International Conference On Consumer Electronics, Communications and Networks, pp. 1216-1219, (2012); Adomavicius G., Tuzhilin A., Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions, IEEE Transactions On Knowledge and Data Engineering, 17, 6, pp. 734-749, (2005); Hwang W.-S., Li S., Kim S.-W., Choi H.J., Exploiting trustors as well as trustees in trustbased recommendation, 22nd ACM International Conference On Conference On Information & Knowledge Management, pp. 1893-1896, (2013); Hwang W.-S., Lee H.-J., Kim S.-W., Lee M., On using category experts for improving the performance and accuracy in recommender systems, 21st ACM International Conference On Information and Knowledge Management, pp. 2355-2358, (2012); Ha J., Kwon S.-H., Kim S.-W., Faloutsos C., Park S., Top-N recommendation through belief propagation, 21st ACM International Conference On Information and Knowledge Management, pp. 2343-2346, (2012); Shaw C.-W., Lin S.-W., The antecedents of consumers' loyalty toward online stores, 11th Annual Conference of Asia Pacifi C Decision Sciences Institute, pp. 14-18, (2006); Huang Y.-M., Chiu P.-S., The effectiveness of a meaningful learning-based evaluation model for context-aware mobile learning, British Journal of Educational Technology, 46, 2, pp. 437-447, (2015); Huang Y.-M., Chiu P.-S., The effectiveness of the meaningful learning-based evaluation for different achieving students in a ubiquitous learning context, Computers & Education, 87, pp. 243-253, (2015); Valvi A.C., Fragkos K.C., Critical review of the e-loyalty literature: A purchase-centred framework, Electron Commer Research, 12, 3, pp. 331-378, (2012); Ulbrich F., Christensen T., Stankus L., Genderspecific on-line shopping preferences, Electronic Commerce Research, 11, 2, pp. 181-199, (2011); Kadlec D., Have Americans Given Up On Saving for Retirement, (2013); Schafer J.B., Konstan J.A., Riedl J., E-commerce recommendation applications, Applications of Data Mining to Electronic Commerce, (2001); Chaudhuri A., Holbrook M.B., The chain of effects from brand trust and brand affect to brand performance: The role of brand loyalty, Journal of Marketing, 65, 2, pp. 81-93, (2001); Liu Q., Wan J., Zhou K., Cloud manufacturing service system for industrial-cluster-oriented application, Journal of Internet Technology, 15, 3, pp. 373-380, (2014); Wu Z., Wan Z., Huang Y.-N., Gu Q., Hu C.-Y., Wu Z.-B., Optimal service distribution in cloud service system subject to data security constraints, Journal of Internet Technology, 15, 5, pp. 863-880, (2014)","T.-C. Huang; Department of Information Management, National Taichung University of Science and Technology, Taiwan; email: tchuang@nutc.edu.tw",null,"Taiwan Academic Network Management Committee",{"$nulls":5},1.6079264E7,null,null,null,"English","J. Internet Technol.","Article","Final",null,"Scopus","2-s2.0-85041813840"]
["Sharma A.K.; Archana T.; Selvam V.","Sharma, Ajay Kumar (57191986369); Archana, T. (56565494100); Selvam, V. (56755050400)","57191986369; 56565494100; 56755050400","Factors influencing youngsters’ behavior towards online shopping in Vellore district of Tamilnadu, India",2016.0,"Journal of Internet Banking and Commerce",21.0,"Special Issue 5",3.0,null,null,13.0,0.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-84995679764&partnerID=40&md5=b29d208d9aa122d7f474db731cc75616","VIT University, Vellore, Tamil Nadu, India; Commerce Division, School of Social Sciences and Languages, VIT University, Vellore, Tamil Nadu, India","Sharma A.K., VIT University, Vellore, Tamil Nadu, India; Archana T., Commerce Division, School of Social Sciences and Languages, VIT University, Vellore, Tamil Nadu, India; Selvam V., Commerce Division, School of Social Sciences and Languages, VIT University, Vellore, Tamil Nadu, India","Digital universe in India is doubling in size every two years and will multiply nine-fold between 2014 and 2020. As per ASSOCHAM, the value of Indian e-commerce market in 2012 was $8.5 billion and $16 billion in 2013 and it is estimated to be $56 billion in 2023. Sources of e-commerce depend on the effective shopping, prompt delivery and increased use of online payment mechanism. Online shopping has changed the face of marketing globally. It has helped in easier, simpler and faster business transactions. Today each and every household is using online shopping. India being a highly populated country is positively transforming towards online shopping. Therefore there is a huge scope for both business and teenagers in India for online selling and buying household goods. As the Indian population is adding more educated and expert in internet technology, online shopping is moving drastically. In this background, the present descriptive study is an attempt to investigate the important factors influencing teenager’s behaviour, attitude and perception towards online shopping in Vellore district of Tamil Nadu in India. © Ajay Kumar Sharma, 2016.","Behaviour and e-commerce; Online shopping",{"$nulls":7},"Sridevi K.S., Emerging trends in online marketing, ICTACT Journal on Management Studies, 1, pp. 34-38, (2015); Peter J.P., Tarpey L.X., A comparative analysis of three consumer decision strategies, Journal of Consumer Research, 2, pp. 29-37, (1975); Peattie K., Crane A., Green marketing: Legend, myth, farce or prophesy?, Qualitative Market Research: An International Journal, 8, pp. 357-370, (2005); Zhu Q., Sarkis J., Geng Y., Green supply chain management in China: Pressures, practices and performance, International Journal of Operations & Production Management, 25, pp. 449-468, (2005); Alam S.S., Norjaya M.Y., An Investigation into the Antecedents of Customer Satisfaction of Online Shopping, 5, pp. 71-78, (2010); Impact of E-commerce Marketing, HRD Times, 12, pp. 21-22, (2010); Research C., Walmart to expand in E-retailing in India, Monthly Commentary on Indian Economic Conditions, 9, pp. 4-6, (2014); FDI in retailing: Leads to economic growth and better value to end consumers, International Journal of Economics and Finance, 7, pp. 1-9, (2015); Alba J., Lynch J., Weitz B., Janiszewski C., Lutz R., Et al., Interactive Home Shopping: Consumer, Retailer, and Manufacturers Incentives to Participate in Electronic Marketplaces, Journal of Marketing, 61, pp. 38-53, (1997); Hernandez B., Jimenez J., Jose M.M., Consumer behavior in electronic commerce: The moderating effect of e-purchasing experience’, Journal of Business Research, 63, pp. 964-971, (2010); Lohse B., Johnson E., Predictors of Online Buying Behavior, Communications of the ACM, 42, pp. 32-38, (1999); Butler P., Peppard J., Consumer purchasing on the Internet: Process and Prospects, European Management Journal, 16, pp. 600-610, (1998); Hirschman A., Experience Seeking: A Subjectivist Perspective of Consumption, Journal of Business Research, pp. 115-136, (1984); Schaupp L.C., Belanger F., A conjoint analysis of online consumer satisfaction, Journal of Electronic Commerce Research, 6, pp. 95-111, (2005); Abdeldayem M.M., A study of customer satisfaction with online shopping: Evidence from the UAE, International Journal of Advanced Media and Communication, 4, pp. 235-257, (2010); Al Karim R., Customer Satisfaction in Online Shopping: A study into the reasons for motivations and inhibitions, IOSR Journal of Business and Management, 11, pp. 13-20, (2013)",null,null,"ARRAY Development (Canada) Inc.",{"$nulls":5},1.2045357E7,null,null,null,"English","J. Internet Bank. Commer.","Article","Final",null,"Scopus","2-s2.0-84995679764"]
["Yu Y.; Wang X.; Zhong R.Y.; Huang G.Q.","Yu, Ying (57191723934); Wang, Xin (57194787640); Zhong, Ray Y. (55353690000); Huang, G.Q. (7403425048)","57191723934; 57194787640; 55353690000; 7403425048","E-commerce logistics in supply chain management Implementations and future perspective in furniture industry",2017.0,"Industrial Management and Data Systems",117.0,10.0,null,2263.0,2286.0,23.0,96.0,"10.1108/IMDS-09-2016-0398","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85034833967&doi=10.1108%2fIMDS-09-2016-0398&partnerID=40&md5=d16399c9252f3ab7e99d051bb6575bab","Department of Mechanical Engineering, University of Auckland, Auckland, New Zealand; Department of Industrial and Manufacturing Systems Engineering, University of Hong Kong, HKU-ZIRI Lab for Physical Internet, Hong Kong","Yu Y., Department of Industrial and Manufacturing Systems Engineering, University of Hong Kong, HKU-ZIRI Lab for Physical Internet, Hong Kong; Wang X., Department of Industrial and Manufacturing Systems Engineering, University of Hong Kong, HKU-ZIRI Lab for Physical Internet, Hong Kong; Zhong R.Y., Department of Mechanical Engineering, University of Auckland, Auckland, New Zealand; Huang G.Q., Department of Industrial and Manufacturing Systems Engineering, University of Hong Kong, HKU-ZIRI Lab for Physical Internet, Hong Kong","Purpose – The purpose of this paper is to present the state-of-the-art E-commerce logistics in supply chain management by investigating worldwide implementations and corresponding models together with supporting techniques via furniture industry. Design/methodology/approach – Typical E-commerce logistics companies from North America, Europe, and Asia Pacific are comprehensively investigated so as to get the lessons and insights from these practices. Findings – Future technologies like Internet of Things, Big Data Analytics, and Cloud Computing would be possibly adopted to enhance the E-commerce logistics in terms of system level, operational level, and decision-making level that may be real time and intelligent in the next decade. Research limitations/implications – This paper takes the furniture industry for example to illustrate the E-commerce logistics and supply chain management (LSCM). Other industries like electronic appliance industry are not considered. Practical implications – Opportunities and future perspectives are summarized from practical implementations so that interested parties like E-commerce and logistics companies are able to get some guidance when they are contemplating the business. Social implications – E-commerce is booming with the development of new business models and will be continuously boosted in the near future. With large number of enterprises carrying out E-commerce, logistics has been largely influenced. Originality/value – Insights and lessons from this paper are significant for academia and practitioners for considering E-commerce LSCM. © Emerald Publishing Limited.","E-commerce; Implementation; Logistics; State-of-the-art; Supply chain management","Big data; Commerce; Decision making; Distributed computer systems; Electronic commerce; Logistics; Design/methodology/approach; Electronic appliance industries; Future perspectives; Future technologies; Implementation; Logistics and supply chain management; New business models; State of the art; Supply chain management",{"$nulls":6},{"$cut":{"chars":18711,"head":"Agatz N.A., Fleischmann M., Van Nunen J.A., E-fulfillment and multi-channel distribution – A review, European Journal of Operational Research, 187, 2, pp. 339-356, (2008); Armbrust M., Fox A., Griffith R., Joseph A.D., Katz R., Konwinski A., Lee G., Patterson D., Rabkin A., Stoica I., A view of cloud computing, Communications of The ACM, 53, 4, pp. 50-58, (2010); Bai J., The localized marketing strategy choice for global retailer-a case study of IKEA, Future and Development, 8, pp. 83-87, (2011); Banker S., In-store logistics at IKEA, Logistics Viewpoints, (2009); Bardi E.J., Tracey M., Transportation outsourcing: A survey of US practices, International Journal of Physical Distribution & Logistics Management, 21, 3, pp. 15-21, (1991); Bask A., Lipponen M., Tinnila M., E-commerce logistics: A literature research review and topics for future research, International Journal of E-Services and Mobile Applications, 4, 3, pp. 1-22, (2012); Bayles D.L., Bhatia H., E-Commerce Logistics & Fulfillment: Delivering The Goods, (2000); Bianchi C., Home Depot in Chile: Case study, Journal of Business Research, 59, 3, pp. 391-393, (2006); Bianchi C.C., Ostale E., Lessons learned from unsuccessful internationalization attempts: Examples of multinational retailers in Chile, Journal of Business Research, 59, 1, pp. 140-147, (2006); Bolumole Y.A., The supply chain role of third-party logistics providers, The International Journal of Logistics Management, 12, 2, pp. 87-102, (2001); Bolumole Y.A., Closs D.J., Rodammer F.A., The economic development role of regional logistics hubs: A cross-country study of interorganizational governance models, Journal of Business Logistics, 36, 2, pp. 182-198, (2015); Bond J., The Home Depot builds an omni-channel supply chain, Modern Materials Handling, 78, pp. 18-22, (2015); Bond J., The Home Depot: Flexible picking processes achieve same-day order fulfillment, Modern Materials Handling, 70, 2, pp. 18-22, (2015); Boyer K.K., Frohlich M.T., Hult G.T.M., Extending The Supply Chain: How Cutting-Edge Companies Bridge The Critical Last Mile into Customers' Homes, (2005); Cegielski C.G., Allison Jones-Farmer L., Wu Y., Hazen B.T., Adoption of cloud computing technologies in supply chains: An organizational information processing theory approach, The International Journal of Logistics Management, 23, 2, pp. 184-211, (2012); Chaabouni T., Kchaou H., Khemakhem M., Agent technology based resources management in cloud computing, World Congress on Computer and Information Technology, IEEE, Sousse, (2013); Chen J.C., Cheng C.-H., Huang P.B., Wang K.-J., Huang C.-J., Ting T.-C., Warehouse management with lean and RFID application: A case study, The International Journal of Advanced Manufacturing Technology, 69, 1-4, pp. 531-542, (2013); Cheng L., Analysis of the strategic direction of the JingDong Mall, Fifth International Conference on Business Intelligence and Financial Engineering, IEEE, pp. 434-437, (2012); Chiles C.R., An analysis of current supply chain best practices in the retail industry with case studies of Wal-Mart and, CiteSeerX, (2005); Ciobanu R.-I., Cristea V., Dobre C., Pop F., Big Data platforms for the Internet of Things, Big Data and Internet of Things: A Roadmap for Smart Environments, pp. 3-34, (2014); Cronin M.J., Amazon fast tracks transformation, Top Down Innovation, pp. 49-60, (2014); Cui M., Cross-border comparative analysis of E-commerce and logistics – Take JingDong logistics and SF best as the examples, Market Modernization, 15, pp. 35-36, (2014); Damme D.A.V., Amstel M.J., Outsourcing logistics management activities, The International Journal of Logistics Management, 7, 2, pp. 85-94, (1996); Delfmann W., Albers S., Gehring M., The impact of electronic commerce on logistics service providers, International Journal of Physical Distribution & Logistics Management, 32, 3, pp. 203-222, (2002); Ding Y.P., Study on e-commerce system of green mechanical processing enterprises, Applied Mechanics and Materials, Trans Tech Publications, 340, pp. 218-221, (2013); Ellinger A.E., Lynch D.F., Andzulis J.K.,"}},"R.Y. Zhong; Department of Mechanical Engineering, University of Auckland, Auckland, New Zealand; email: zhongzry@gmail.com",null,"Emerald Group Publishing Ltd.",{"$nulls":5},2635577.0,null,"IMDSD",null,"English","Ind Manage Data Sys","Article","Final",null,"Scopus","2-s2.0-85034833967"]
["Momo A.M.; Twum-Darko M.","Momo, Alain Michael (55250505400); Twum-Darko, Michael (56541663000)","55250505400; 56541663000","Usability of online business registration improvisation as Congo-Brazzaville re-branding tool",2017.0,"Electronic Journal of Information Systems in Developing Countries",83.0,1.0,3.0,null,null,null,3.0,"10.1002/j.1681-4835.2017.tb00611.x","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85032393131&doi=10.1002%2fj.1681-4835.2017.tb00611.x&partnerID=40&md5=85051ef2edf214879e6e64bbcb43a4c0","Cape Peninsula University of Technology, South Africa","Momo A.M., Cape Peninsula University of Technology, South Africa; Twum-Darko M., Cape Peninsula University of Technology, South Africa","There is growing concern that Congolese business' inability to compete in a fiercely competitive international economy spells ruin. Thus, the study uses bricolage and information systems (IS) improvisation as a lens to explore the use of online business registration as a means to rebrand government services. Building and achieving brand status is challenging, however; public service organisations and country of any size with a name can become high status brands. The research problem is that if sufficient attention is not given to reconcile IS improvisation with other organisational dimensions such as expertise, team work, culture, communication and training in the business registration process, it is a foregone conclusion that the automatic assumption that improvisation alone creates brand image and identify might not yield desired results. The main objective of this study was to determine the role of online business registration in service branding. The overarching research question is (a) how does the DTI Congo-Brazzaville intend to improvise business registration process using e-commerce technology as branding tool? The study is significant in the way that it boosts DTI Congo's brand image; with potentials to improve the country's ranking in terms of ease of doing business; and extends previous research by examining the usability of online business registration system as branding tool in developing countries. The study focused less on merely identifying IS improvisation benefits; or in solving DTI Congo problems. However, the focal point was creating awareness for DTI Congo to weight current study outcomes, available resource and contemporary e-commerce technologies in order to make informed decision in terms of technology adoption. The investigation was done at the Department of Trade and Industry (DTI) in Congo-Brazzaville using a mixed methodology. A survey questionnaire on a sample size of N = 260 from a total of 800 DTI full-time employees was used to elicit information by requiring respondents to answer objective questions. A focus group comprising of five full-time employees selected according to their level of IT awareness and position were invited for discussions to gain a broader understanding of the research problem. Observation in the form field work was also done to experience what it is like when there is no other alternative to register a business but to follow the only lengthy and bureaucratic process of traditional business registration. It was evident from the data that 74.2% of respondents agreed that an online business registration system adoption can re-brand the organisation for innovative public service delivery.","Bricolage; Department of trade and industry; Information systems improvisation; Nation branding; Online business registration",{"$nulls":7},"Andreasen A.R., Kotler P.,  ed.), (2003); Brace I., Questionnaire Design: How to Plan, Structure and Write Survey Material for Effective Market Research, (2004); Browning C.S., Nation Branding and Development: Poverty Panacea or Business as Usual?, Journal of International Relations and Development, 19, 1, pp. 50-75, (2016); Guide to Branding in the Public and Not-for-Profit Sectors, (2009); Chelariu C., Johnston W.J., Young L., Learning to Improvise, Improvising to Learn: A Process of Responding to Complex Environments, Journal of Business Research, 55, 2, pp. 141-147, (2002); Ciborra C.U., Notes on Improvisations and Time in Organizations, Accounting, Management and Information Technologies, 9, 2, pp. 77-94, (1999); Les plus belles voix musicales des deux Congo réunies dans Terre sacrée, (2015); Croom S., Romano P., Giannakis M., Supply Chain Management: An Analytical Framework For Critical Literature Review, European Journal of Purchasing & Supply Management, 6, 1, pp. 67-83, (2000); Faraj S., Sproull L., Coordinating Expertise in Software Development Teams, Management Science, 46, 12, pp. 1554-1568, (2000); Design Options Paper SME Value Chains: Peer Learning of Innovation Agencies about Innovation Support in SMEs in Transnational Business Value Chains, (2016); Garud R., Karnoe P., Bricolage versus Breakthrough: Distributed and Embedded Agency in Technology Entrepreneurship, Research Policy, 32, 2, pp. 277-300, (2003); Golafshani N., Understanding Reliability and Validity in Qualitative Research, The Qualitative Report, 8, 4, pp. 597-607, (2003); Service Canada Branding Presentation, Paper Presented at Canadian Conference on Public Service Branding, February 17, (2009); Heaton J., The Difference between Marketing and Branding, (2017); Henn M., Weinstein M., Foard N.,  ed.), (2009); Research Methodology, (2010); Agence Publicitaires Locales, (2015); Kokt D., Koelane T., Reflecting on Information and Communication Technology (ICT) in Marketing from a Marketer's and Student Perspective, African Journal of Businesss Management, 7, 31, pp. 3098-3108, (2013); Kotler P., Lee N., Marketing in the Public Sector: A Roadmap for Improved Performance, (2007); Lauren D., The Importance of Fax Machines, (2017); Leedy P.D.,  ed.), (1989); Levi-Strauss C., The Savage Mind, (1966); Molnar W.A., Information System Development in a Process Management Environment: The Dynamics of Improvisation and Bricolage During Embedded Software Design, (2009); Momo A.M., Ukpere W.I., The Economic and Logistic Benefits of Online Business Registration for Congolese Immigrants in Cape Town, African Journal of Business Management, 5, 14, pp. 5994-6004, (2011); Momo A.M., Improvisational Model of Business Registration for Branding Services in Congo-Brazzaville, Digital Knowledge, 1, 2, pp. 163-194, (2016); Momo A.M., President Trump's Threats in Coltan Supply Chain Due Diligence Stunt Congo's 2020 Nation Branding Vision, World Scientific News, 69, pp. 86-97, (2017); Nacioglu A., As a Critical Behaviour to Improve Quality and Patient Safety in Health Care: Speaking Up!, Safety in Health, 2, 10, pp. 1-25, (2016); Nneka A.A., Extent of Application of Marketing Mix Strategy by Small and Micro Scale Enterprises in Osun State, Nigeria, African Journal of Marketing Management, 7, 2, pp. 16-19, (2015); Pisano G.P., You Need an Innovation Strategy, Harvard Business Review, 93, 6, pp. 44-54, (2016); étude diagnostique du Guichet unique et des barrières à l'investissement privé au Congo, (2006); South African Retail and Consumer Products Outlook 2012-2016, (2012); Invité Afrique, (2015); Ramnarain Y., Govender K.K., Social Media Browsing and Consumer Behaviour: Exploring the Youth Market, African Journal of Business Management, 7, 18, pp. 1885-1893, (2013); Secchi E., Roth A., Verma R., The Role of Service Improvisation in Improving Hotel Customer Satisfaction, Cornell Hospitably Report, 16, 1, pp. 3-10, (2016); Shemi A.P., Factors Affecting E-Commerce Adoption in Small and Medium Enterprises: An Interpretative Study of Botswana, (2012); African Digitisation Maturity Report 2017, (2017); Smith D.J., Blundel R.K., Improvisation and Entrepreneurial Bricolage versus Rationalisation: A Case-Based Analysis of Contrasting Responses to Economic Instability in the UK Brass Musical Instruments Industry, Journal of General Management, 40, 1, pp. 53-78, (2014); Random Number Table, (2017); Struwig F.W., Stead G.B., Planning, Designing and Reporting Research, (2001); Teo T.S.H., Pian Y., A Contingency Perspective on Internet Adoption and Competitive Advantage, European Journal of Information Systems, 12, 2, pp. 78-92, (2003); The Republic of Congo at a Glance, (2008); Mobile Cellular Subscriptions (per 100 People), (2015); Vera D., Crossan M., Improvisation and Innovative Performance in Teams, Organization Science, 16, 3, pp. 203-224, (2005); Vukasovic T., Building Successful Brand by Using Social Networking Media, Journal of Media and Communication Studies, 5, 6, pp. 56-63, (2013); Wasserman D., A Stress-Vulnerability Model and the Development of the Suicidal Process, Suicide: An Unnecessary Death, pp. 13-27, (2001); Yetela M., Présentation de CFBAP, (2012)",null,null,"City University of Hong Kong Press",{"$nulls":5},1.6814835E7,null,null,null,"English","Electron. J. Inf. Syst. Dev. Ctries","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-85032393131"]
["Li Q.","Li, Qian (57230436300)",5.72304363E10,"A study on information sharing in logistics supply chains within e-commerce environments",2016.0,"International Journal of Simulation: Systems, Science and Technology",17.0,18.0,null,"2024-01-17","2024-06-17",null,0.0,"10.5013/IJSSST.a.17.18.17","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84992053119&doi=10.5013%2fIJSSST.a.17.18.17&partnerID=40&md5=3999140154252a227399450d1c5857cc","Neijiang Vocational and Technical College, Neijiang City, 641100, China","Li Q., Neijiang Vocational and Technical College, Neijiang City, 641100, China","In the network economy era, it is vital to operate more efficiently and create more value in the e-business environment which has involved ever more companies. They are concerned with the supply chain management which occupies an increasingly important position. The e-commerce technology presents new features and trends on how to build and improve the supply chain, how to integrate the supply chain as a single whole which is highly competitive and has become an important topic for research. In this paper, the system knowledge base provides a deeper understanding of the nature of e-commerce and supply chain and its management. Based on the analysis of the impact of electronic commerce, and focusing on the supply chain under the premise to build e-commerce environment, we discuss the principles, policies and method to provide reference for corporate design and supply chain information sharing in e-commerce. This will provide scientific and business information quickly into the economy, and promote the economic value of e-commerce in the whole economy with extensive and real implementation. © 2016, UK Simulation Society. All rights reserved.","E-commerce; Information sharing; Logistics supply chain management","Commerce; Economics; Electronic commerce; Information analysis; Information dissemination; Knowledge based systems; Business information; E business environment; Economic values; Information sharing; Logistics supply chain managements; Logistics supply chains; Supply chain information sharing; System knowledge; Supply chain management",{"$nulls":6},"Klein R., Rai A., Interfirm strategic information flows in logistics supply chain relationships, MIS Quarterly, pp. 735-762, (2009); Bayraktar E., Demirbag M., Koh S., Et al., A causal analysis of the impact of information systems and supply chain management practices on operational performance: Evidence from manufacturing SMEs in Turkey, International Journal of Production Economics, 122, 1, pp. 133-149, (2009); Fawcett S.E., Wallin C., Allred C., Et al., Information technology as an enabler of supply chain collaboration: A dynamic ‐ capabilities perspective, Journal of Supply Chain Management, 47, 1, pp. 38-59, (2011); Iyer K., Germain R., Claycomb C., B2B e-commerce supply chain integration and performance: A contingency fit perspective on the role of environment, Information & Management, 46, 6, pp. 313-322, (2009); Xu L.D., Information architecture for supply chain quality management, International Journal of Production Research, 49, 1, pp. 183-198, (2011); Sarac A., Absi N., Dauzere-Peres S., A literature review on the impact of RFID technologies on supply chain management, International Journal of Production Economics, 128, 1, pp. 77-95, (2010); Wong C., Lai K.H., Cheng T.C.E., Complementarities and alignment of information systems management and supply chain management, International Journal of Shipping and Transport Logistics, 1, 2, pp. 156-171, (2009); Chong A., Ooi K.B., Sohal A., The relationship between supply chain factors and adoption of e-collaboration tools: An empirical examination, International Journal of Production Economics, 122, 1, pp. 150-160, (2009); Trkman P., McCormack K., Supply chain risk in turbulent environments—A conceptual model for managing supply chain network risk, International Journal of Production Economics, 119, 2, pp. 247-258, (2009); Dong S., Xu S.X., Zhu K.X., Research note-information technology in supply chains: The value of it-enabled resources under competition, Information Systems Research, 20, 1, pp. 18-32, (2009); Sarkis J., A boundaries and flows perspective of green supply chain management, Supply Chain Management: An International Journal, 17, 2, pp. 202-216, (2012)","Q. Li; Neijiang Vocational and Technical College, Neijiang City, 641100, China; email: Calla2015@163.com",null,"UK Simulation Society",{"$nulls":5},1.4738031E7,null,null,null,"English","Int. J. Simul. Syst. Sci. Technol.","Article","Final",null,"Scopus","2-s2.0-84992053119"]
["Kafalı Ö.; Yolum P.","Kafalı, Özgür (26025243600); Yolum, Pınar (8840406900)","26025243600; 8840406900","PISAGOR: a proactive software agent for monitoring interactions",2016.0,"Knowledge and Information Systems",47.0,1.0,null,215.0,239.0,24.0,11.0,"10.1007/s10115-015-0848-1","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84959557650&doi=10.1007%2fs10115-015-0848-1&partnerID=40&md5=67e829442f862763ced51ce93fe560b5","Department of Computer Science, North Carolina State University, Raleigh, NC, United States; Department of Computer Engineering, Bogazici University, Istanbul, Turkey","Kafalı Ö., Department of Computer Science, North Carolina State University, Raleigh, NC, United States; Yolum P., Department of Computer Engineering, Bogazici University, Istanbul, Turkey","E-commerce has become an integral part of everyday life. Many e-commerce systems enable users to browse products, place orders, and track deliveries online. However, these interactions is time-consuming, especially if they do not proceed as expected. Instead of a human user, software can offer automated support to monitor e-commerce transactions to ensure that they are completed by the businesses as planned. Accordingly, this paper studies methods to develop a software agent for monitoring its users’ interactions with businesses (PISAGOR). The interactions are represented as commitments, which have been extensively studied in multiagent systems. With a commitment-based specification at hand, the agent knows what the meaning of its interactions are and can therefore reason over its actions. The reasoning is accompanied with the as-good-as relation that compares the agent’s current state with its expectations from a transaction. This enables PISAGOR to decide whether the transaction is progressing as expected. Moreover, we propose operational rules for the agent to create expectations based on its commitments and check its progress toward them. We demonstrate via a case study how PISAGOR can detect if a user’s interactions are not progressing well and identify a problem for the user to take action. © 2015, Springer-Verlag London.","Agent-based commerce; Commitments; Expectations; Multiagent systems","Electronic commerce; Multi agent systems; Online systems; Agent based; Automated support; Based specification; Commitments; E-commerce systems; E-commerce transactions; Expectations; Integral part; Software agents",{"$nulls":4},"Bogazici University; Bogazici University Research Fund, (BAP13A01P2); Royal Holloway; University of London, UoL; Türkiye Bilimsel ve Teknolojik Araştırma Kurumu, TÜBİTAK, (113E543)","Funding text 1: We thank the anonymous reviewers for their useful comments and suggestions. Most of this work was done while Ã\u0096zgÃ¼r Kafal? was doing research in Bogazici University and Royal Holloway, University of London. This research is supported by Bogazici University Research Fund under Grant BAP13A01P2 and the Scientific and Technological Research Council of Turkey (TUBITAK) under Grant 113E543.; Funding text 2: We thank the anonymous reviewers for their useful comments and suggestions. Most of this work was done while Özgür Kafalı was doing research in Bogazici University and Royal Holloway, University of London. This research is supported by Bogazici University Research Fund under Grant BAP13A01P2 and the Scientific and Technological Research Council of Turkey (TUBITAK) under Grant 113E543. 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In: Proceedings of the 9th international conference on autonomous agents and multiagent systems (AAMAS), pp 457–464, (2010); Chopra A.K., Singh M.P., Multiagent commitment alignment, Proceedings of the 8th international conference on autonomous agents and multiagent systems, AAMAS ’09, 2, pp. 937-944, (2009); El Kholy W., El Menshawy M., Bentahar J., Qu H., Dssouli R., Representing and reasoning about communicative conditional commitments. In: Proceedings of the 12th international conference on autonomous agents and multiagent systems, pp 1169–1170, (2013); El Menshawy M., Benthar J., Qu H., Dssouli R., On the verification of social commitments and time. 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In: Handbook of research on multi-agent systems: semantics and dynamics of organizational models, pp 263–284, (2009); Wood D., Kafali O., Stathis K., DIESECT: a distributed environment for simulating e-commerce contracts, ‘E-Commerce and Web Technologies’ lecture notes in business information processing, pp. 39-50, (2013); Yan Z., Fong S., Shi M., Knowledge-empowered automated negotiation system for e-commerce, Knowl Inf Syst, 17, 2, pp. 167-191, (2008); Yao Y., Ruohomaa S., Xu F., Addressing common vulnerabilities of reputation systems for electronic commerce, J Theor Appl Electron Commer Res, 7, 1, pp. 1-20, (2012); Yolum P., Singh M.P., Enacting protocols by commitment concession. In: Proceedings of the 6th international conference on autonomous agents and multiagent systems (AAMAS), pp 116–123, (2007)","Ö. Kafalı; Department of Computer Science, North Carolina State University, Raleigh, United States; email: rkafali@ncsu.edu",null,"Springer London",{"$nulls":5},2191377.0,null,null,null,"English","Knowl. Inf. Systems. Syst.","Article","Final",null,"Scopus","2-s2.0-84959557650"]
["Yi S.","Yi, Shanan (57196421207)",5.7196421207E10,"Research on evaluation and selection of logistics mode of b2c e-commerce enterprise",2017.0,"Boletin Tecnico/Technical Bulletin",55.0,10.0,null,504.0,513.0,9.0,0.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85032958614&partnerID=40&md5=188d67c29bf19ec677f1f108846a18fc","School of Economics and Management, Changzhou Institute of Mechatronic Technology, Changzhou, Jiangsu Province, China","Yi S., School of Economics and Management, Changzhou Institute of Mechatronic Technology, Changzhou, Jiangsu Province, China","In recent years, the rapid development of e-commerce in China has entered the golden period. However, in the vigorous development of e-commerce, the electricity supplier enterprises are facing the problem that the traditional express logistics cannot meet its development needs. These problems forced the B2C E-commerce enterprise to make effective action, so as to ensure the normal operation of the smooth and sustainable development. And the choice of logistics model is the core of logistics, which urgently needs to be solved. First of all, this paper analyzes the relevant theoretical basis and typical patterns of the electricity supplier logistics field. Then, the author discusses the development situation, and analyzes the influence index. System is evaluated on the basis of the evaluation system established. Finally, the fuzzy comprehensive evaluation method is used to make the most suitable logistics model for B2C enterprises. Some suggestions are put forward for the selection of the logistics mode of B2C enterprises.","B2C model; E-commerce; Evaluation and selection; Logistics model","Electric utilities; Electronic commerce; B2c models; Development needs; Development situations; Evaluation and selection; Fuzzy comprehensive evaluation method; Logistics model; Normal operations; Typical patterns; Commerce",{"$nulls":6},"Li Y., Li C., Song Y., Research on Distribution Route of Electricity Supplier Logistics Based on the Customer's Hidden Cost, (2016); Wang C.L., Wang D.Z., Liu L.F., Et al., Study on the performance evaluation of logistics enterprise in the online supply chain finance, Logistics Sci-Tech, (2015); Wang H.W., Performance research on the B2C E-commerce self-logistics and third-party logistics, Value Engineering, (2012); Wang L., Research on the development strategy of logistics firms in China, Open Journal of Social Sciences, 2, 9, pp. 253-257, (2015); Wang W., Analysis and evaluation of Chinese cross-border electricity supplier logistics, Open Journal of Business & Management, 4, 3, pp. 500-504, (2016); Wang W., Comparative research on states of cross-border electricity supplier logistics, Ibusiness, 6, 4, pp. 726-730, (2016); Zhao W., Ye S., Research on Credit Risk Management Mechanism of B2B Online Financing Mode, pp. 1465-1470, (2015); Zhao W., Ye S., Research on Credit Risk Management Mechanism of B2B Online Financing Mode, LISS 2014, pp. 1465-1470, (2015)","S. Yi; School of Economics and Management, Changzhou Institute of Mechatronic Technology, Changzhou, Jiangsu Province, China; email: czyishanan@163.com",null,"Universidad Central de Venezuela",{"$nulls":5},"0376723X",null,null,null,"English","Boletin Tecnico","Article","Final",null,"Scopus","2-s2.0-85032958614"]
["Jiao W.; Li J.","Jiao, Weiwei (27170892300); Li, Jingji (57195715840)","27170892300; 57195715840","Information recommendation system based on collaborative filtering in cloud computing",2017.0,"Boletin Tecnico/Technical Bulletin",55.0,7.0,null,98.0,104.0,6.0,2.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85029595644&partnerID=40&md5=d32dd89fb4ea855d319a8a8c931d18bb","Computer Center, Liaoning University of Technology, Jinzhou, Liaoning, 121001, China; State Grid Liaoning Electric Power Corp Jinzhou Branch, Jinzhou, Liaoning, 121000, China","Jiao W., Computer Center, Liaoning University of Technology, Jinzhou, Liaoning, 121001, China; Li J., State Grid Liaoning Electric Power Corp Jinzhou Branch, Jinzhou, Liaoning, 121000, China","In the field of information system and e-commerce, personalized recommendation is a very mature technology and performs well. However, the rapid growth of the amount of data not only makes it difficult to store and manage data, but also blocks the development of personalized recommendation as well as diversity. As a new computing model and service delivery model, cloud computing makes it possible to solve massive data management and improve the speed of recommendation. But, cloud computing also brings new problems to personalized recommendations, such as low recommendation accuracy, long recommendation time and high network overhead. To address this issue, a collaborative filtering (CF) recommendation mechanism for cloud computing is proposed in this paper. This paper gives a working principle of the model and discusses abstract technology of the model that presents a new application of a weighted offline evaluation to reduce this bias for collaborative filtering algorithms. Experimental results show that the proposed method achieved the goal of solving the issues raised and can improve the performance of personalized recommendation to some extent.","Cloud Computing; Collaborative Filtering; Explicit Feedback; Implicit Feedback; Personalized Recommendation","Cloud computing; Distributed computer systems; Information filtering; Information management; Network function virtualization; Collaborative filtering algorithms; Explicit feedback; Implicit feedback; Information recommendation; Massive data managements; Personalized recommendation; Recommendation accuracy; Recommendation mechanism; Collaborative filtering",{"$nulls":6},"Bharadwaj K.K., Tyagi S., A hybrid knowledge-based approach to collaborative filtering for improved recommendations, International Journal of Knowledge-based and Intelligent Engineering Systems, 18, 2, pp. 121-133, (2014); Hubalek Z., Coefficients of association and similarity, based on binary (presence-Absence) data: An evaluation, Biological Reviews, 57, 4, pp. 669-689, (1982); Komkhao M., Lu J., Li Z., Halang W.A., Incremental collaborative filtering based on Mahalanobis distance and fuzzy membership for recommender systems, International Journal of General Systems, 42, 1, pp. 41-66, (2013); Liu H., Hu Z., Mian A., Tian H., Zhu X., A new user similarity model to improve the accuracy of collaborative filtering, Knowledge-Based Systems, 56, 4, pp. 156-166, (2014); Liu Z., Collaborative filtering recommendation algorithm based on user interests, International Journal of U-& E-Service, Science & Technology, 8, 4, pp. 67-81, (2015); Nilashi M., Bin Ibrahim O., Ithnin N., Multi-criteria collaborative filtering with high accuracy using higher order singular value decomposition and Neuro-Fuzzy system, Knowledge-Based Systems, 60, 4, pp. 82-101, (2014); Park Y., Park S., Jung W., Lee S.-G., Reversed CF: A fast collaborative filtering algorithm using a knearest neighbor graph, Expert Systems with Applications, 42, 8, pp. 4022-4028, (2015); Patra B.K., Launonen R., Ollikainen V., Nandi S., A new similarity measure using Bhattacharyya coefficient for collaborative filtering in sparse data, Knowledge-Based Systems, 82, 5, pp. 163-177, (2015); Nikolaos P.C.K., A dynamic multi-level collaborative filtering method for improved recommendations, Computer Standards & Interfaces, 51, 3, pp. 14-21, (2017); Ramezani M., Moradi P., Akhlaghian F., A pattern mining approach to enhance the accuracy of collaborative filtering in sparse data domains, Physica A: Statistical Mechanics and Its Applications, 40, 8, pp. 72-84, (2014); Wasid M., Kant V., A particle swarm approach to collaborative filtering based recommender systems through fuzzy features, Procedia Computer Science, 54, 8, pp. 40-48, (2015)","W. Jiao; Computer Center, Liaoning University of Technology, Jinzhou, Liaoning, 121001, China; email: lgvivian@126.com",null,"Universidad Central de Venezuela",{"$nulls":5},"0376723X",null,null,null,"English","Boletin Tecnico","Article","Final",null,"Scopus","2-s2.0-85029595644"]
["Fagerstrøm A.; Ghinea G.; Sydnes L.","Fagerstrøm, Asle (23396496800); Ghinea, Gheorghita (35616295700); Sydnes, Lars (56653288600)","23396496800; 35616295700; 56653288600","How Does Probability Impact Consumers' Choice? The Case of Online Reviews",2016.0,"Managerial and Decision Economics",37.0,"2024-05-04",null,331.0,336.0,5.0,8.0,"10.1002/mde.2720","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84929692543&doi=10.1002%2fmde.2720&partnerID=40&md5=c841f4134bcfd10e2d1d4550324308f1","Westerdals Oslo School of Arts, Communication and Technology, Faculty of Technology, Oslo, Norway; Brunel University, Department of Computer Science, London, United Kingdom","Fagerstrøm A., Westerdals Oslo School of Arts, Communication and Technology, Faculty of Technology, Oslo, Norway; Ghinea G., Westerdals Oslo School of Arts, Communication and Technology, Faculty of Technology, Oslo, Norway, Brunel University, Department of Computer Science, London, United Kingdom; Sydnes L., Westerdals Oslo School of Arts, Communication and Technology, Faculty of Technology, Oslo, Norway","Consumers are frequently in situations that include evaluating the probability of the outcome of a particular choice. It is, therefore, essential to analyze how probability influences choice in order to fully understand consumer behavior. This paper investigates how probability discounting contributes to the understanding of the impact of online reviews on consumer choice. An experiment with 25 participants was conducted. Participants were presented with an online shopping scenario in which they had to choose between two online shops: one with (positive) customer reviews (on delivery reliability and customer service) and higher product prices, while the other had lower prices, but no customer reviews at all. We employed a titration procedure over sales price for the web shop without customer reviews; this was run over seven probability conditions. The point where participants switched between one web shop and another was recorded, and the probability discounting factors were calculated. The results highlight that online reviews are indicators of successful online transactions (i.e., intention to buy) and therefore function as choice benchmarks. In the light of these results, the paper presents practical implications, as well as directions for future research. © 2016 John Wiley & Sons, Ltd.",{"$nulls":8},"Alhadeff D.A., Microeconomics and Human Behavior: Toward a New Synthesis of Economics and Psychology, (1982); Camerer C.F., Hogarth R.M., The effects of financial incentives in experiments: a review and capital-labor production framework, Journal of Risk and Uncertainty, 19, 1-3, pp. 7-42, (1999); Chatterjee P., Online review: do consumers use them?, Advances in Consumer Research, 28, 1, pp. 129-133, (2001); Dellarocas C., Zhang X., Awad N.F., Exploring the value of online product reviews in forecasting sales: the case of motion pictures, Journal of Interactive Marketing, 21, 4, pp. 23-45, (2007); DiFonzo N., Hantula D.A., Bordia P., Microworlds for experimental research: having your (control and collection) cake, and realism too, Behavior Research Methods, Instruments, and Computers, 30, 2, pp. 278-286, (1998); Liu Y., Word of mouth for movies: its dynamics and impact on box office revenue, Journal of Marketing, 70, 3, pp. 74-89, (2006); Loewenstein G., Prelec D., Anomalies in intertemporal choices: evidence and an interpretation, Quarterly Journal of Economics, 107, 2, pp. 573-597, (1992); McKerchar T.L., Renda C.R., Delay and probability discounting in humans: an overview, The Psychological Record, 62, 4, pp. 817-834, (2012); Rachlin H., Judgment, Decition, and Choice: A Cognitive/Behavioral Synthesis, (1989); Rachlin H., Raineri A., Cross D., Subjective probability and delay, Journal of the Experimental Analysis of Behavior, 55, 2, pp. 233-244, (1991); Raineri A., Rachlin H., The effect of temporal constraints on the value of money and other commodities, Journal of Behavoral Decision Making, 6, 2, pp. 77-94, (1993); Smith C.L., Hantula D.A., Methodological considerations in the study of delay-discounting in itertemporal choice: a comparison of tasks and modes, Behavior Research Methods, 40, 4, pp. 940-953, (2008); Wei P., Lu H., An examination of the celebrity endorsements and online customer reviews influence female customers' shopping behavior, Computers in Human Behavior, 29, pp. 193-201, (2013); Oguta H., Tasb B.K.O., The influence of Internet customer reviews on the online sales and price in hotel industry, The Service Industries Journal, 32, 2, pp. 197-214, (2012)","A. Fagerstrøm; Westerdals Oslo School of Arts, Communication and Technology, Faculty of Technology, Oslo, Schweigaardsgate 14, 0185, Norway; email: asle.fagerstrom@westerdals.no",null,"John Wiley and Sons Ltd",{"$nulls":5},1436570.0,null,null,null,"English","Manage. Decis. Econ.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-84929692543"]
["Luo J.; Liu D.","Luo, Jing (57195559744); Liu, Dongyan (57195557226)","57195559744; 57195557226","Fresh agricultural products e-business chain logistics and risk control based on big data platform",2017.0,"Boletin Tecnico/Technical Bulletin",55.0,6.0,null,200.0,208.0,8.0,4.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85028746034&partnerID=40&md5=4477da88a998ce793e255634328f7a1e","School of Business, Anhui Xinhua University, China","Luo J., School of Business, Anhui Xinhua University, China; Liu D., School of Business, Anhui Xinhua University, China","With the development of the Internet industry, online shopping platform brings great convenience; most enterprises have also carried out fresh agricultural products suppliers. In this paper, the authors analyze the E-business mechanism and fresh agricultural products marketing innovation based on Internet big data platform. Through analyzing the current problems faced by fresh products suppliers within the value chain, we put forward the e-commerce marketing model innovation mechanism, trying to solve the standardization problems, the problems of high loss in distribution and high costs, and to make fresh agricultural products suppliers generate more profits. At the same time, the authors have put forward the development countermeasures of agricultural products marketing.","Big data platform; E-commerce marketing; Fresh agricultural products; Marketing innovation","Agricultural products; Agriculture; Chains; Commerce; Electronic commerce; Marketing; Problem solving; Current problems; Data platform; Development countermeasures; Fresh agricultural products; Innovation mechanisms; Internet industries; Marketing innovations; Marketing models; Big data",{"$nulls":4},"Anhui Provincial Education Bureau, (SK2016A0450); Anhui quality engineering project, (2016mooc206)","This work is supported by Humanities and social science project of Anhui Provincial Education Bureau: Research on the export of agricultural products in Anhui under the cross border electricity supplier environment (SK2016A0450); and Anhui quality engineering project: Introduction to e-commerce MOOC, (2016mooc206).","Anand K., Context-general and context-specific determinants of online satisfaction and loyalty for commerce and content sites, Journal of Interactive Marketing, 24, 3, pp. 222-238, (2010); Cattani K., Gilland W., Pricing strategies for amanufacturer adding a direct channel that competes with the traditional channel, Productionand Operations Management, 15, pp. 40-56, (2006); Druehl C., Porteus E., Price competition between an Internet firm and a bricks and mortar firm, Working Paper, pp. 14-30, (2001); Enders A., Jelassi T., The converging business models of internet and bricks-and retailers, European Management Journal, 18, pp. 542-550, (2000); Huang Z., Benyoucef M., From e-commerce to social commerce: A close look at design features, Electronic Commerce Research and Applications, 12, pp. 246-259, (2013); Jutla D., Bodorik P., Developing internet e-commerce benchmarks, Information Systems, 24, pp. 475-493, (1999); Kim J., The role of etail quality, e-satisfaction and e-trust in online loyalty development process, Journal of Retailing and Consumer Services, 16, pp. 239-247, (2009); Niklas A., Fredrik S., Electronic commerce, marketing channels and logistics platform-a wholesaler perspective, European Journal of Operational Research, 144, pp. 270-279, (2003); Park S., Keh H., Modeling hybrid distribution channels: A game-theoretic analysis, Journal of Retailing and Consumer Services, 10, pp. 155-167, (2003); Yao D., Liu Q., Competitive pricing of mixed retail and e-tail distribution channels, Omega, 33, pp. 235-247, (2005)","J. Luo; School of Business, Anhui Xinhua University, China; email: 99298221@qq.com",null,"Universidad Central de Venezuela",{"$nulls":5},"0376723X",null,null,null,"English","Boletin Tecnico","Article","Final",null,"Scopus","2-s2.0-85028746034"]
["Chong A.Y.L.; Ch’ng E.; Liu M.J.; Li B.","Chong, Alain Yee Loong (26654029000); Ch’ng, Eugene (6507026255); Liu, Martin J. (22993817300); Li, Boying (56733847400)","26654029000; 6507026255; 22993817300; 56733847400","Predicting consumer product demands via Big Data: the roles of online promotional marketing and online reviews",2017.0,"International Journal of Production Research",55.0,17.0,null,5142.0,5156.0,14.0,131.0,"10.1080/00207543.2015.1066519","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84937788667&doi=10.1080%2f00207543.2015.1066519&partnerID=40&md5=33c673ca05e6d95e56ecc18629de4a4a","Nottingham University Business School China, University of Nottingham Ningbo China, Ningbo, China; School of Computer Science, International Doctoral Innovation Centre, University of Nottingham Ningbo China, Ningbo, China","Chong A.Y.L., Nottingham University Business School China, University of Nottingham Ningbo China, Ningbo, China; Ch’ng E., School of Computer Science, International Doctoral Innovation Centre, University of Nottingham Ningbo China, Ningbo, China; Liu M.J., Nottingham University Business School China, University of Nottingham Ningbo China, Ningbo, China; Li B., School of Computer Science, International Doctoral Innovation Centre, University of Nottingham Ningbo China, Ningbo, China","This study aims to investigate the contributions of online promotional marketing and online reviews as predictors of consumer product demands. Using electronic data from Amazon.com, we attempt to predict if online review variables such as valence and volume of reviews, the number of positive and negative reviews, and online promotional marketing variables such as discounts and free deliveries, can influence the demand of electronic products in Amazon.com. A Big Data architecture was developed and Node.JS agents were deployed for scraping the Amazon.com pages using asynchronous Input/Output calls. The completed Web crawling and scraping data-sets were then preprocessed for Neural Network analysis. Our results showed that variables from both online reviews and promotional marketing strategies are important predictors of product demands. Variables in online reviews in general were better predictors as compared to online marketing promotional variables. This study provides important implications for practitioners as they can better understand how online reviews and online promotional marketing can influence product demands. Our empirical contributions include the design of a Big Data architecture that incorporate Neural Network analysis which can used as a platform for future researchers to investigate how Big Data can be used to understand and predict online consumer product demands. © 2015 Informa UK Limited, trading as Taylor & Francis Group.","Big Data; neural network; online marketplace; online reviews; product demands; promotional marketing","Computer aided network analysis; Consumer products; Electronic commerce; Forecasting; Marketing; Network architecture; Neural networks; Product design; Social networking (online); Data architectures; Electronic data; Electronic product; Marketing strategy; On-line marketplaces; Online marketing; Online reviews; Product demand; Big data",{"$nulls":4},"China’s MoST; International Doctoral Innovation Centre; University of Nottingham, (2012B10055, 71402076); National Natural Science Foundation of China, NSFC; Ningbo Municipal Bureau of Science and Technology; Ningbo Municipal Bureau of Education","The work was financially support by the National Natural Science Foundation of China (NSFC), International Doctoral Innovation Centre, Ningbo Education Bureau, Ningbo Science and Technology Bureau, China’s MoST and The University of Nottingham. The project is supported by NSFC no. 71402076 and NBSTB Project 2012B10055.","Aljahdali S.H., Sheta A., Rine D., Prediction of Software Reliability: A Comparison between Regression and Neural Network Non-Parametric Models, Computer Systems and Applications, ACS/IEEE International Conference on 2001, pp. 470-473, (2001); Bollen J., Mao H., Zeng X., Twitter Mood Predicts the Stock Market, Journal of Computational Science, 2, 1, pp. 1-8, (2011); Cao Q., Schniederjans M.J., Empirical Study of the Relationship between Operations Strategy and Information Systems Strategic Orientation in an e-Commerce Environment, International Journal of Production Research, 42, 15, pp. 2915-2939, (2004); Chakravarty A., Liu Y., Mazumdar T., The Differential Effects of Online Word-of-Mouth and Critics’ Reviews on Pre-Release Movie Evaluation, Journal of Interactive Marketing, 24, 3, pp. 185-197, (2010); Chase C.W., Using Big Data to Enhance Demand–Driven Forecasting and Planning, Journal of Business Forecasting, 32, 2, pp. 26-32, (2013); 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Davis A., Khazanchi D., An Empirical Study of Online Word of Mouth  as a Predictor for Multi-Product Category E-Commerce Sales, Electronic Markets, 18, 2, pp. 130-141, (2008); Dellarocas C., Awad N., Zhang X., Exploring the Value of Online Reviews to Organizations: Implications for Revenue Forecasting and Planning, ICIS 2004 Proceedings, 30, pp. 379-386, (2004); Dobrzykowski D., Deilami V.S., Hong P., Kim S.-C., A Structured Analysis of Operations and Supply Chain Management Research in Healthcare (1982–2011), International Journal of Production Economics, 147, pp. 514-530, (2014); Doern R.R., Fey C.F., E-Commerce Developments and Strategies for Value Creation: The Case of Russia, Journal of World Business, 41, 4, pp. 315-327, (2006); Dreiseitl S., Lucila O.-M., Logistic Regression and Artificial Neural Network Classification Models: A Methodology Review, Journal of Biomedical Informatics, 35, 5, pp. 352-359, (2002); Drozdenko R., Jensen M., Risk and Maximum Acceptable Discount Levels, Journal of Product & Brand Management, 14, 4, pp. 264-270, (2005); 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Evidence from Online Restaurant Reviews, Information Systems Research, 24, 3, pp. 596-612, (2013); Madan V., Suri R., Quality Perception and Monetary Sacrifice: A Comparative Analysis of Discount and Fixed Prices, Journal of Product & Brand Management, 10, 3, pp. 170-182, (2001); Marshall R., Leng S.B., Price Threshold and Discount Saturation Point in Singapore, Journal of Product & Brand Management, 11, 3, pp. 147-159, (2002); Min H.-J., Park J.C., Identifying Helpful Reviews Based on Customer’s Mentions about Experiences, Expert Systems with Applications, 39, 15, pp. 11830-11838, (2012); Moosmayer D.C., Chong A.Y.L., Liu M.J., Schuppar B., A Neural Network Approach to Predicting Price Negotiation Outcomes in Business-to-Business Contexts, Expert Systems with Applications, 40, 8, pp. 3028-3035, (2013); Mudambi S.M., Schuff D., What Makes a Helpful Online Review? A Study of Customer Reviews on Amazon. Com, Management Information Systems Quarterly, 34, 1, pp. 185-200, (2010); Ou C.X., Pavlou P.A., Davison R.M., Swift Guanxi in Online Marketplaces: The Role of Computer-Mediated Communication Technologies, MIS Quarterly, 38, 1, pp. 209-230, (2014); Sargent D.J., Comparison of Artificial Neural Networks with Other Statistical Approaches, Cancer, 91, S8, pp. 1636-1642, (2001); Shmueli G., Koppius O.R., Predictive Analytics in Information Systems Research, MIS Quarterly, 35, 3, pp. 553-572, (2011); Sim J.-J., Tan G.W.-H., Wong J.C.J., Ooi K.-B., Hew T.-S., Understanding and Predicting the Motivators of Mobile Music Acceptance–A Multi-Stage MRA-Artificial Neural Network Approach, Telematics and Informatics, 31, 4, pp. 569-584, (2014); Smith A.D., Rupp W.T., Strategic Online Customer Decision Making: Leveraging the Transformational Power of the Internet, Online Information Review, 27, 6, pp. 418-432, (2003); Sonnier G.P., McAlister L., Rutz O.J., A Dynamic Model of the Effect of Online Communications on Firm Sales, Marketing Science, 30, 4, pp. 702-716, (2011); Suominen K., How Big Data Streamlines Globalization, Globalization 4.0., (2014); Suri R., Manchanda R.V., Kohli C.S., Brand Evaluations: A Comparison of Fixed Price and Discounted Price Offers, Journal of Product & Brand Management, 9, 3, pp. 193-207, (2000); Teo A.-C., Tan G.W., Ooi K.-B., Hew T.-S., Yew K.-T., The Effects of Convenience and Speed in m-Payment, Industrial Management & Data Systems, 115, 2, pp. 311-331, (2015); Tirunillai S., Tellis G.J., Does Chatter Really Matter? Dynamics of User-generated Content and Stock Performance, Marketing Science, 31, 2, pp. 198-215, (2012); Westbrook R.A., Product/Consumption-Based Affective Responses and Postpurchase Processes, Journal of Marketing Research, 24, 3, pp. 258-270, (1987); Yip L., Law R., User Preferences for Web Site Attributes: A Study of the Hong Kong Disneyland, Asia Pacific Journal of Tourism Research, 7, 1, pp. 33-44, (2002); Zhang J.Q., Craciun G., Shin D., When Does Electronic Word-of-Mouth Matter? A Study of Consumer Product Reviews, Journal of Business Research, 63, 12, pp. 1336-1341, (2010); Zhu F., Zhang X., Impact of Online Consumer Reviews on Sales: The Moderating Role of Product and Consumer Characteristics, Journal of Marketing, 74, 2, pp. 133-148, (2010)","A.Y.L. Chong; Nottingham University Business School China, University of Nottingham Ningbo China, Ningbo, China; email: alain.chong@nottingham.edu.cn",null,"Taylor and Francis Ltd.",{"$nulls":5},207543.0,null,"IJPRB",null,"English","Int J Prod Res","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-84937788667"]
["Xiao K.; Hu X.","Xiao, Kefeng (38962289600); Hu, Xiaolan (57195723628)","38962289600; 57195723628","Study on maritime logistics warehousing center model and precision marketing strategy optimization based on fuzzy method and neural network model",2017.0,"Polish Maritime Research",24.0,"s2",null,30.0,38.0,8.0,12.0,"10.1515/pomr-2017-0061","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85029637980&doi=10.1515%2fpomr-2017-0061&partnerID=40&md5=2e978aa3e9471e5bd92237357109c895","Economics and Management School, Wuhan University, Wuhan, 430074, China","Xiao K., Economics and Management School, Wuhan University, Wuhan, 430074, China; Hu X., Economics and Management School, Wuhan University, Wuhan, 430074, China","The bulk commodity, different with the retail goods, has a uniqueness in the location selection, the chosen of transportation program and the decision objectives. How to make optimal decisions in the facility location, requirement distribution, shipping methods and the route selection and establish an effective distribution system to reduce the cost has become a burning issue for the e-commerce logistics, which is worthy to be deeply and systematically solved. In this paper, Logistics warehousing center model and precision marketing strategy optimization based on fuzzy method and neural network model is proposed to solve this problem. In addition, we have designed principles of the fuzzy method and neural network model to solve the proposed model because of its complexity. Finally, we have solved numerous examples to compare the results of lingo and Matlab, we use Matlab and lingo just to check the result and to illustrate the numerical example, we can find from the result, the multi-objective model increases logistics costs and improves the efficiency of distribution time.","Fuzzy method; Maritime logistics warehousing center mode; Neural network model; Polarity reversal; Precision marketing strategy optimization","Commerce; Costs; Marketing; MATLAB; Planning; Strategic planning; Warehouses; Fuzzy methods; Maritime logistics; Neural network model; Polarity reversal; Precision marketings; Fuzzy inference",{"$nulls":6},"Psaraftis H.N., Green maritime logistics: The quest for win-win solutions, Transportation Research Procedia, 14, pp. 133-142, (2016); Parola F., Satta G., Panayides P.M., Corporate strategies and profitability of maritime logistics firms, Maritime Economics & Logistics, 17, 1, pp. 52-78, (2015); Bell M.G.H., Meng Q., Special issue in transportation research Part B - Shipping, port and maritime logistics, Transportation Research Part B Methodological, 93, pp. 697-699, (2016); Seo Y.J., Dinwoodie J., Roe M., The influence of supply chain collaboration on collaborative advantage and port performance in maritime logistics, International Journal of Logistics, 19, 6, pp. 1-21, (2016); Wang S.J., Yuan P., Li D., Jiao Y.H., An overview of ocean renewable energy in China, Renew Sustain Energy Rev, 15, 1, pp. 91-111, (2011); Lopez I., Andreu J., Ceballos S., Alegria I.M.D., Kortabarria I., Review of wave energy technologies and the necessary power-equipment, Renewable and Sustainable Energy Reviews, 27, 6, pp. 413-434, (2013); Coiro D.P., Troise G., Calise G., Bizzarrini N., Wave energy conversion through a point pivoted absorber: Numerical and experimental tests on a scaled model, Renewable Energy, 87, 1, pp. 317-325, (2016); Martinez M., Molina M.G., Machado I.R., Mercado P.E., Watanabe E.H., Modelling and simulation of wave energy hyperbaric converter (WEHC) for applications in distributed generation, International Journal of Hydrogen Energy, 37, 9, pp. 14945-14950, (2012); Gaspar J.F., Calvario M., Kamarlouei M., Guedes Soares C., Power take-off concept for wave energy converters based on oil-hydraulic transformer units, Renewable Energy, 86, pp. 1232-1246, (2016); Yang L., Hals J., Moan T., Analysis of dynamic effects relevant for the wear damage in hydraulic Machines for wave energy conversion, Ocean Engineering, 37, 13, pp. 1089-1102, (2010); De Falcao A.F.O., Modelling and control of oscillating-body wave energy converters with hydraulic power take-off and gas accumulator, Ocean Engineering, 34, 14-15, pp. 2021-2032, (2007); Virvalo T., Hydraulic Systems in Wave Energy Application, pp. 56-60, (2009); Lin Y.G., Huang W., Zhang D.F., Li W., Bao J.W., Application of hydraulic system in wave energy converter, Electrical, Information Engineering and Mechatronics 2011, Lecture Notes in Electrical Engineering, 138, pp. 275-283, (2012); Wang C.W., Jiao Z.X., Wu S., Shang Y.X., An experimental study of the dualloop control of electro-hydraulic load simulator, Chinese Journal of Aeronautics, 26, 6, pp. 1586-1595, (2013)","K. Xiao; Economics and Management School, Wuhan University, Wuhan, 430074, China; email: 2373751844@qq.com",null,"De Gruyter Open Ltd",{"$nulls":5},1.2332585E7,null,null,null,"English","Pol. Marit. Res.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85029637980"]
["Batarfi R.; Jaber M.Y.; Aljazzar S.M.","Batarfi, Raaid (57190276689); Jaber, Mohamad Y. (57203764536); Aljazzar, Salem M. (58163109800)","57190276689; 57203764536; 58163109800","A profit maximization for a reverse logistics dual-channel supply chain with a return policy",2017.0,"Computers and Industrial Engineering",106.0,null,null,58.0,82.0,24.0,95.0,"10.1016/j.cie.2017.01.024","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85012107831&doi=10.1016%2fj.cie.2017.01.024&partnerID=40&md5=5efdec4d20fb02710e928a7360a01f57","Department of Mechanical and Industrial Engineering, Ryerson University, Toronto, M5B 2K3, Ontario, Canada","Batarfi R., Department of Mechanical and Industrial Engineering, Ryerson University, Toronto, M5B 2K3, Ontario, Canada; Jaber M.Y., Department of Mechanical and Industrial Engineering, Ryerson University, Toronto, M5B 2K3, Ontario, Canada; Aljazzar S.M., Department of Mechanical and Industrial Engineering, Ryerson University, Toronto, M5B 2K3, Ontario, Canada","In the last few decades, the rapid development of e-commerce technologies has encouraged many manufacturers to adopt an online channel in addition to their existing traditional retail channel, which resulted in redesigning their supply chain channel structure. Additionally, an increasing number of manufacturers nowadays offer a return policy to attract more customers and to stay competitive. This paper studies a supply chain system, which is comprised of production, refurbishing, collection, and waste disposal processes. A return policy in which customers can return the purchased item for a refund is also considered. Two selling strategies, a single-channel strategy (i.e., a retail channel) and a dual-channel (i.e., a retail channel and an online channel) strategy are discussed from which mathematical models are developed. The purpose is to examine the effect of different return policies on the behavior of SC systems before and after adopting the dual-channel. In both strategies, the paper analyzes the change in the profit, the pricing and inventory decisions. Numerical examples and sensitivity analyses are provided with their results discussed. The findings of this paper demonstrate that in both strategies, the more generous the return policy is, the higher the demand, the selling prices and the overall profit. The findings also indicate that adopting a dual-channel strategy is more profitable to the supply chain. © 2017 Elsevier Ltd","Customization; Dual-channel; Refurbish; Return policy; Reverse logistics; Supply chain","Chains; Costs; Logistics; Manufacture; Numerical methods; Profitability; Sensitivity analysis; Supply chains; Waste disposal; Customization; Dual channel; Refurbish; Return policy; Reverse logistics; Sales",{"$nulls":6},"Agrawal S., Singh R.K., Murtaza Q., A literature review and perspectives in reverse logistics, Resources, Conservation and Recycling, 97, pp. 76-92, (2015); Aulkemeier F., Paramartha M.A., Iacob M.-E., van Hillegersberg J., A pluggable service platform architecture for e-commerce, Information Systems and E-Business Management, 1-21, (2015); Batarfi R., Jaber M.Y., Zanoni S., Dual-channel supply chain: A strategy to maximize profit, Applied Mathematical Modelling, 40, 21-22, pp. 9454-9473, (2016); Bazan E., Jaber M.Y., Zanoni S., A review of mathematical inventory models for reverse logistics and the future of its modeling: An environmental perspective, Applied Mathematical Modelling, 40, 5-6, pp. 4151-4178, (2016); Bloomberg D.J., LeMay S.B., Hanna J.B., Logistics, (2001); Chen J., Bell P.C., Implementing market segmentation using full-refund and no-refund customer returns policies in a dual-channel supply chain structure, International Journal of Production Economics, 136, 1, pp. 56-66, (2012); Cheng Y.-H., Lee F., Outsourcing reverse logistics of high-tech manufacturing firms by using a systematic decision-making approach: TFT-LCD sector in Taiwan, Industrial Marketing Management, 39, 7, pp. 1111-1119, (2010); Choi T.-M., Li D., Yan H., Optimal returns policy for supply chain with e-marketplace, International Journal of Production Economics, 88, 2, pp. 205-227, (2004); Davis S., Gerstner E., Hagerty M., Money back guarantees in retailing: Matching products to consumer tastes, Journal of Retailing, 71, 1, pp. 7-22, (1995); Dhanda K.K., Hill R.P., The role of information technology and systems in reverse logistics: A case study, International Journal of Technology Management, 31, 1-2, pp. 140-151, (2005); El Saadany A.M.A., Jaber M.Y., A production/remanufacturing inventory model with price and quality dependant return rate, Computers & Industrial Engineering, 58, 3, pp. 352-362, (2010); El Saadany A.M.A., Jaber M.Y., A production/remanufacture model with returns’ subassemblies managed differently, International Journal of Production Economics, 133, 1, pp. 119-126, (2011); El Saadany A.M.A., Jaber M.Y., Bonney M., How many times to remanufacture?, International Journal of Production Economics, 143, 2, pp. 598-604, (2013); Gunasekaran A., Ngai E.W.T., Modeling and analysis of build-to-order supply chains, European Journal of Operational Research, 195, 2, pp. 319-334, (2009); Hasanov P., Jaber M.Y., Zolfaghari S., Production, remanufacturing and waste disposal models for the cases of pure and partial backordering, Applied Mathematical Modelling, 36, 11, pp. 5249-5261, (2012); Hsieh C.-C., Liu Y.-T., Quality investment and inspection policy in a supplier–manufacturer supply chain, European Journal of Operational Research, 202, 3, pp. 717-729, (2010); Jaber M.Y., Learning curves: Theory, models, and applications, (2011); Jaber M.Y., El Saadany A.M.A., The production, remanufacture and waste disposal model with lost sales, International Journal of Production Economics, 120, 1, pp. 115-124, (2009); Jaber M.Y., Goyal S.K., Coordinating a three-level supply chain with multiple suppliers, a vendor and multiple buyers, International Journal of Production Economics, 116, 1, pp. 95-103, (2008); Jaber M.Y., Zanoni S., Zavanella L.E., A consignment stock coordination scheme for the production, remanufacturing and waste disposal problem, International Journal of Production Research, 52, 1, pp. 50-65, (2014); Ketzenberg M.E., Zuidwijk R.A., Optimal pricing, ordering, and return policies for consumer goods, Production and Operations Management, 18, 3, pp. 344-360, (2009); Krumwiede D.W., Sheu C., A model for reverse logistics entry by third-party providers, Omega, 30, 5, pp. 325-333, (2002); Li Y., Xu L., Li D., Examining relationships between the return policy, product quality, and pricing strategy in online direct selling, International Journal of Production Economics, 144, 2, pp. 451-460, (2013); Liu N., Choi T.-M., Yuen C.-W.M., Ng F., Optimal pricing, modularity, and return policy under mass customization, IEEE Transactions on Systems, Man, and Cybernetics – Part A: Systems and Humans, 42, 3, pp. 604-614, (2012); Liu J., Mantin B., Wang H., Supply chain coordination with customer returns and refund-dependent demand, International Journal of Production Economics, 148, pp. 81-89, (2014); Martin P., Guide V.D.R., Craighead C.W., Supply chain sourcing in remanufacturing operations: An empirical investigation of remake versus buy, Decision Sciences, 41, 2, pp. 301-324, (2010); Mitra S., Analysis of a two-echelon inventory system with returns, Omega, 37, 1, pp. 106-115, (2009); Mukhopadhyay S.K., Setaputra R., The role of 4PL as the reverse logistics integrator: Optimal pricing and return policies, International Journal of Physical Distribution & Logistics Management, 36, 9, pp. 716-729, (2006); Mukhopadhyay S.K., Setoputro R., Reverse logistics in e-business: Optimal price and return policy, International Journal of Physical Distribution & Logistics Management, 34, 1, pp. 70-89, (2004); Mukhopadhyay S.K., Setoputro R., Optimal return policy and modular design for build-to-order products, Journal of Operations Management, 23, 5, pp. 496-506, (2005); Ofek E., Katona Z., Sarvary M., “Bricks and Clicks”: The impact of product returns on the strategies of multichannel retailers, Marketing Science, 30, 1, pp. 42-60, (2011); Olorunniwo F.O., Li X., An overview of some reverse logistics practices in the United States, Supply Chain Forum: An International Journal, 12, 3, pp. 2-9, (2011); Partridge A.R., Full circle: Reverse logistics keeps products green to the end, (2011); Pattinson S., What is reverse logistics?, (2014); Pfister M., 3 strategies to empower customers & reduce returns, (2014); Prahinski C., Kocabasoglu C., Empirical research opportunities in reverse supply chains, Omega, 34, 6, pp. 519-532, (2006); Retail Sales Worldwide Will Top $22 Trillion This Year - eMarketer, (2014); Returns and exchanges policy - Best Buy Canada, (2016); Savaskan R.C., Bhattacharya S., Van Wassenhove L.N., Closed-loop supply chain models with product remanufacturing, Management Science, 50, 2, pp. 239-252, (2004); Sharma A., Revankar A.M., Sathvik R.S., Risk management in reverse supply chain, International conference on challenges and opportunities in mechanical engineering, industrial engineering and management studies, pp. 11-13, (2012); Tahirov N., Hasanov P., Jaber M.Y., Optimization of closed-loop supply chain of multi-items with returned subassemblies, International Journal of Production Economics, 174, pp. 1-10, (2016); Takahashi K., Aoi T., Hirotani D., Morikawa K., Inventory control in a two-echelon dual-channel supply chain with setup of production and delivery, International Journal of Production Economics, 133, 1, pp. 403-415, (2011); Tsay A.A., Agrawal N., Channel dynamics under price and service competition, Manufacturing & Service Operations Management, 2, 4, pp. 372-391, (2000); Tsay A.A., Agrawal N., Channel conflict and coordination in the e-commerce age, Production and Operations Management, 13, 1, pp. 93-110, (2004); Waters C.D.J., Inventory control and management, (2003); Yao D.-Q., Yue X., Wang X., Liu J.J., The impact of information sharing on a returns policy with the addition of a direct channel, International Journal of Production Economics, 97, 2, pp. 196-209, (2005); Zahran S.K., Jaber M.Y., Zanoni S., Zavanella L.E., Payment schemes for a two-level consignment stock supply chain system, Computers & Industrial Engineering, 87, pp. 491-505, (2015); Zanoni S., Mazzoldi L., Jaber M.Y., Vendor-managed inventory with consignment stock agreement for single vendor–single buyer under the emission-trading scheme, International Journal of Production Research, 52, 1, pp. 20-31, (2014)","R. Batarfi; Department of Mechanical and Industrial Engineering, Ryerson University, Toronto, M5B 2K3, Canada; email: raaid.batarfi@ryerson.ca",null,"Elsevier Ltd",{"$nulls":5},3608352.0,null,"CINDD",null,"English","Comput Ind Eng","Article","Final",null,"Scopus","2-s2.0-85012107831"]
["Cai Z.","Cai, Zhiwen (57223009786)",5.7223009786E10,"Research on vertical synergy mechanism between diversified e-commerce platform and service provider",2017.0,"Boletin Tecnico/Technical Bulletin",55.0,15.0,null,728.0,733.0,5.0,0.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85037814651&partnerID=40&md5=6c5e9a85818e3894bada1a5671b692b6","School of Economics and Management, Xiamen University of Technology, Xiamen, Fujian Province, 361005, China; School of Management, Xiamen University, Xiamen, Fujian Province, 361024, China","Cai Z., School of Economics and Management, Xiamen University of Technology, Xiamen, Fujian Province, 361005, China, School of Management, Xiamen University, Xiamen, Fujian Province, 361024, China","In recent years, the development momentum of e-commerce is very fierce. In the double eleven activities in 2017, the sales of two electronic business platform of Tmall and Taobao reached a new level with 168 billion 200 million. With the development of e-commerce, the development speed of related industries is gradually accelerated, such as online payment and express logistics. In addition, there are obvious differences in the characteristics of different industries. In view of this situation, the enterprise development speed of electricity supplier and related industries is not balanced. In this regard, the electricity supplier enterprises should start from themselves and take strategic change. From the perspective of vertical governance, this paper analyzes and studies e-commerce and related industries. On this basis, the author studies the diversified development mode, so that these industries can develop harmoniously.","E-commerce platform; Service providers; Vertical collaboration mechanisms","Commerce; Electric utilities; Development modes; Electronic business; Enterprise development; On-line payment; Service provider; Strategic changes; Vertical collaborations; Electronic commerce",{"$nulls":6},"Aulkemeier F., Paramartha M.A., Iacob M.E., Et al., A pluggable service platform architecture for e-commerce, Information Systems and E-Business Management, 14, 3, pp. 469-489, (2016); Chen L., Cao Y., The design framework of E-commerce platform of Chinese forest products, Management and Service Science (MASS), 2010 International Conference On, pp. 1-6, (2010); Clarke C.J., Brennan K., Building synergy in the diversified business, Long Range Planning, 23, 2, pp. 9-16, (1990); Cong S., Hunt E., Dittrich K.R., IEIP: An inter-enterprise integration platform for e-commerce based on web service mediation, European conference on web services, IEEE Computer Society, pp. 201-210, (2006); De Souza C.C., Merry S.D., E-commerce Application Service Provider Micro-billing Method and System, (2002); Kleinschmidt P., Anonymous E-health Commerce Device Uses E-commerce Platform for Health Product and Service Providers and/or Connected Marketplace, Preferably Internet Forum, with Database of Prefabricated Templates, (2004); Li Y., Nie Q., The construction of diversified learning platform based on bilingual education - The teaching practice of E-commerce course in SIFT, international conference on E-business and E-government, IEEE Computer Society, pp. 5560-5563, (2010); Saini A., Johnson J.L., Organizational capabilities in e-commerce: An empirical investigation of e-brokerage service providers, Journal of the Academy of Marketing Science, 33, 3, pp. 360-375, (2005); Sun X.M., Luo X., Discussion on the synergy mechanism of diversified coal enterprises, Advanced Materials Research, 1079-1080, pp. 1162-1165, (2015); Sun X., Luo X., The synergy mechanism research on diversified coal enterprises based on grounded theory, Information, Computer and Application Engineering, (2015); Yang K., Research on the synergy produced by diversification in service firms, Future & Development, (2008)","Z. Cai; School of Economics and Management, Xiamen University of Technology, Xiamen, Fujian Province, 361005, China; email: caizhiwen1982@126.com",null,"Universidad Central de Venezuela",{"$nulls":5},"0376723X",null,null,null,"English","Boletin Tecnico","Article","Final",null,"Scopus","2-s2.0-85037814651"]
["Kong L.; Liu Z.; Pan Y.; Xie J.; Yang G.","Kong, Lingcheng (57194776418); Liu, Zhiyang (56101473600); Pan, Yafei (57195554069); Xie, Jiaping (55341933700); Yang, Guang (57195560540)","57194776418; 56101473600; 57195554069; 55341933700; 57195560540","Pricing and service decision of dual-channel operations in an O2O closed-loop supply chain",2017.0,"Industrial Management and Data Systems",117.0,8.0,null,1567.0,1588.0,21.0,61.0,"10.1108/IMDS-12-2016-0544","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85028773871&doi=10.1108%2fIMDS-12-2016-0544&partnerID=40&md5=1bc5de0528760dab9ab9ea56622bec2a","Business School, East China University of Science and Technology, Shanghai, China; School of International Business Administration, Shanghai University of Finance and Economics, Shanghai, China","Kong L., Business School, East China University of Science and Technology, Shanghai, China; Liu Z., School of International Business Administration, Shanghai University of Finance and Economics, Shanghai, China; Pan Y., School of International Business Administration, Shanghai University of Finance and Economics, Shanghai, China; Xie J., School of International Business Administration, Shanghai University of Finance and Economics, Shanghai, China; Yang G., School of International Business Administration, Shanghai University of Finance and Economics, Shanghai, China","Purpose - The online direct selling mode has been widely accepted by enterprises in the O2O era. However, the dual-channel (online/offline, forward/backward) operations of the closed-loop supply chain (CLSC) changed the relationship between manufacturers and retailers, thus resulting in channel conflict. The purpose of this paper is to take a dual-channel operations of CLSC as the research target, where a manufacturer sells a single product through a direct e-channel as well as a conventional retail channel; the retailer are responsible for collecting used products in the reverse supply chain and the manufacturer are responsible for remanufacturing. Design/methodology/approach - The authors build a benchmark model of dual-channel price and service competition and take the return rate, which is considered to be related to the service level of the retailer, as the function of the service level to extend the model in the reverse SC. The authors then analyze the optimal pricing and service decision under centralization and decentralization, respectively. Finally, with the revenue-sharing factor, wholesale price and recycling price transfer payment coefficient as contract parameters, the paper also designs a revenue-sharing contract led by the manufacturer and explores in what situation the contract could realize the Pareto optimization of all players. Findings - In the baseline model, the results show that optimal price and service level correlate positively in centralization; however, the relation relies on consumers' price sensitivity in decentralization. In the extension model, the relationship between price and service level also relies on the relative value of increased service cost and remanufacturing saved cost. When the return rate correlates with the service level, a recycling transfer payment can elevate the service level and thus raise the return rate. Through analyzing the parameters in revenue-sharing contract, a point can be reached where lowering the wholesale price and raising the transfer payment coefficient will promote retailers to share revenue. Practical implications - Many enterprises establish the dual-channel distribution system both online and offline, which need to understand how to resolve their channel conflict. The conflict is especially strong in CLSC with remanufacturing. The result helps the node enterprises realize the coordination of the dual-channel CLSC. Originality/value - It takes into account the fact that there are two complementary relationships, such as online selling and offline delivery; used product recycling and remanufacturing. The authors optimize the strategy of product pricing and service level in order to solve channel conflict and double marginalization in the closed-loop dual-channel distribution network. © 2017 Emerald Publishing Limited.","Closed-loop supply chain; Dual-channel; E-commerce; Pricing strategy; Revenue-sharing contract","Economics; Electronic commerce; Linear matrix inequalities; Manufacture; Multiobjective optimization; Pareto principle; Recycling; Sales; Supply chains; Centralization and decentralizations; Closed-loop supply chain; Closed-loop supply chains (CLSC); Complementary relationship; Design/methodology/approach; Dual channel; Pricing strategy; Revenue sharing contracts; Costs",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (71272015, 71402053); National Office for Philosophy and Social Sciences, NSSFC, (15ZDB161)","The work was supported by National Social Science Fund of China (Grant No. 15ZDB161) and National Natural Science Foundation of China (Grant No. 71272015 and 71402053).","Cachon G.P., Supply chain coordination with revenue sharing: Strength and limitations, Management Science, 51, 1, pp. 30-44, (2005); Cao E.B., Wan C., Lai M.Y., Coordination of a supply chain with one manufacturer and multiple competing retailers under simultaneous demand and cost disruptions, International Journal of Production Economics, 141, 1, pp. 425-433, (2013); Chen C.Y., Fang S., Wen U., Pricing policies for substitutable products in a supply chain with internet and traditional channels, European Journal of Operational Research, 224, 3, pp. 542-551, (2013); Chen K.-Y., Dual sales channel management with service competition, Manufacture & Service Operations Management, 10, 4, pp. 654-675, (2008); Chen J., Bell P.C., Implementing market segmentation using full-refund and no-refund customer returns policies in a dual-channel supply chain structure, Production Economics, 136, 1, pp. 56-66, (2012); Dan B., Xu G.Y., Liu C., Pricing policies in a dual-channel supply chain with retail services, Production Economics, 139, 1, pp. 312-320, (2012); Dumrongsiri A., Fan M., Jain A., Moinzadeh K., A supply chain model with direct and retail channels, European Journal of Operational Research, 187, 3, pp. 691-718, (2008); Global online retailing report: Survey findings, Electronic Retailing & EMarketing, 10, 5, pp. 1-5, (2000); Gallino S., Moreno A., Integration of online and offline channels in retail: The impact of sharing reliable inventory availability information, Management Science, 60, 6, pp. 1434-1451, (2014); Giutini R., Gaudette K., Remanufacturing: The next great opportunity for boosting US productivity, Business Horizons, 46, 6, pp. 41-48, (2003); Karakul M., Chan L., Joint pricing and procurement of substitutable products with random demands: A technical note, European Journal of Operational Research, 201, 1, pp. 324-328, (2010); Kaya O., Incentive and production decisions for remanufacturing operations, European Journal of Operational Research, 201, 2, pp. 442-453, (2009); Lado A.A., Paulraj A., Chen I.J., Customer focus, supply-chain relational capabilities and performance: Evidence from US manufacturing industries, International Journal of Logistics Management, 22, 2, pp. 202-221, (2011); Lin I.I., Mahmassani H.S., Can online grocers deliver some logistics considerations, Transportation Record, (2002); Niu R.H., Zhao X., Castillo I., Joro T., Pricing and inventory strategies for a two-stage dual-channel supply chain, Asia Pacific Journal of Operational Research, 29, 1, pp. 340-409, (2012); Opresnik D., Taisch M., The value of big data in servitization, International Journal of Production Economics, 165, 7, pp. 174-184, (2015); Park S.Y., Keh H.T., Modeling hybrid distribution channels: A game-theoretic analysis, Journal of Retailing and Consumer Service, 10, 3, pp. 155-167, (2003); Savaskan R.C., Bhattacharya S., Van Wassenhove L.N., Closed-loop supply chain models with product remanufacturing, Management Science, 50, 2, pp. 239-252, (2004); Shankar V., Rangasamy A., Pusaterim M., The Online Medium and Customer Price Sensitivity, (1999); Stavrulaki E., Davis M.M., A typology for service supply chains and its implications for strategic decisions, Service Science, 6, 1, pp. 34-46, (2014); Tracht K., Mederer M., Schneider D., Impact of parameter changes in a service provider closed-loop supply chain with customer-owned-stock, 19th CIRP International Conference on Life Cycle Engineering, pp. 593-598, (2012); Tsay A.A., Agrawal N., Channel conflict and coordination in the e-commerce age, Production & Operations Management, 13, 1, pp. 93-110, (2004); Wei Y., Choi T.M., Mean-variance analysis of supply chains under wholesale pricing and profit sharing schemes, European Journal of Operational Research, 204, 2, pp. 255-262, (2010); Xu G., Dan B., Zhang X., Liu C., Coordinating a dual-channel supply chain with risk-averse under a two-way revenue sharing contract, Production Economics, 147, 1, pp. 171-179, (2014); Yan R., Gary, Information asymmetry, pricing strategy and firm's performance in the retailer multi-channel manufacturer supply chain, Journal of Business Research, 64, 4, pp. 377-384, (2011); Yan R.L., Pei Z., Retail services and firm profit in a dual-channel market, Journal of Retailing and Consumer Services, 16, 4, pp. 306-314, (2009); Yao D., Yue X., Wang X., The impact of information sharing on a returns policy with the addition of a direct channel, International Journal of Production Economics, 97, 2, pp. 196-209, (2005)","J. Xie; School of International Business Administration, Shanghai University of Finance and Economics, Shanghai, China; email: jiaping@mail.shufe.edu.cn",null,"Emerald Group Publishing Ltd.",{"$nulls":5},2635577.0,null,"IMDSD",null,"English","Ind Manage Data Sys","Article","Final",null,"Scopus","2-s2.0-85028773871"]
["Chung J.-B.","Chung, Ji-Bok (7404002381)",7.404002381E9,"Internet shopping optimization problem with delivery constraints",2017.0,"Journal of Distribution Science",15.0,2.0,null,15.0,20.0,5.0,12.0,"10.15722/jds.15.2.201702.15","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85021069361&doi=10.15722%2fjds.15.2.201702.15&partnerID=40&md5=3a12682f65a3f9c3e9ffbf3dcb2fc0f0","Department of Retail Management, Kongju National University, Kongju, South Korea","Chung J.-B., Department of Retail Management, Kongju National University, Kongju, South Korea","Purpose - This paper aims to suggest a delivery constrained internet shopping optimization problem (DISOP) which must be solved for online recommendation system to provide a customized service considering cost and delivery conditions at the same time. Research design, data, and methodology - To solve a (DISOP), we propose a multi-objective formulation and a solution approach. By using a commercial optimization software (LINDO), a (DISOP) can be solved iteratively and a pareto optimal set can be calculated for real-sized problem. Results - We propose a new research problem which is different with internet shopping optimization problem since our problem considers not only the purchasing cost but also delivery conditions at the same time. Furthermore, we suggest a multi-objective mathematical formulation for our research problem and provide a solution approach to get a pareto optimal set by using numerical example. Conclusions - This paper proposes a multi-objective optimization problem to solve internet shopping optimization problem with delivery constraint and a solution approach to get a pareto optimal set. The results of research will contribute to develop a customized comparison and recommendation system to help more easy and smart online shopping service.","Internet shopping optimization problem; Multi-objective optimization; Online shopping recommendation; Pareto optimal set",{"$nulls":5},"Kongju National University, KNU; Ministry of Education, MOE; National Research Foundation of Korea, NRF, (NRF-2016S1A5A2A01023036)","This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2016S1A5A2A01023036). This work was supported by the research grant of the Kongju National University Fund in 2017.","Blazewicz J., Kovalyov M., Musial J., Urbanski A., Wojciechowski A., Internet Shopping Optimization Problem, International Journal of Applied Mathematics and Computer Science, 20, 2, pp. 385-390, (2010); Deb K., Multi-Objective Optimization Using Evolutionary Algorithms, (2001); Kim K.J., Ahn H.C., A Recommender System Using GA K-means Clustering in an Online Shopping Market, Expert Systems with Applications, 34, 2, pp. 1200-1209, (2008); Lee K.K., Ahn S.H., Kim H.D., Youn M.K., Effects of the Flow of an Internet Shopping Mall upon Revisit Intention and Purchase Intention, The East Asian Journal of Business Management, 4, 4, pp. 27-38, (2014); Lee K.K., Jang S.N., Kim P.J., Research on Purchase Decision Factors to TV Home Shopping Product: Digital Home Appliance, The East Asian Journal of Business Management, 2, 2, pp. 13-21, (2012); Lee S.C., Kim S.W., Park S.J., A Recommendation Method Based on Analysis of Item Groups in Price-Comparison Services, KIISE Transactions on Computing Practices, 19, 11, pp. 541-546, (2013); Li F., Inventory-Transportation Optimization in Online Shopping Supply Chain Based on Retailer's Decision-Making Power on Pricing, International Journal of Simulation-Systems, Science & Technology, 17, 14, pp. 1-6, (2016); Pathak B.K., Comparison Shopping Agents and Online Price Dispersion: A Search Cost Based Explanation, Journal of Theoretical and Applied Electronic Commerce Research, 7, 1, pp. 64-76, (2012); Singh D.P., Online Shopping Motivations, Information Search, and Shopping Intentions in an Emerging Economy, The East Asian Journal of Business Management, 4, 3, pp. 5-12, (2014); Ulukan Z., Demircioglu E., A Survey of Discrete Facility Location Problems, International Journal of Social, Behavioral, Educational, Economic, Business and Industrial Engineering, 9, 7, pp. 2487-2492, (2015); Wojciechowski A., Musial J., A Customer Assistance System: Optimizing Basket Cost, Foundations of Computing and Decision Sciences, 34, 1, pp. 59-69, (2009)","J.-B. Chung; Department of Retail Management, Kongju National University, Kongju, South Korea; email: jbchung@kongju.ac.kr",null,"Korea Distribution Science Association (KODISA)",{"$nulls":5},1.738311E7,null,null,null,"English","J. Distribution Science","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85021069361"]
["Schrotenboer A.H.; Wruck S.; Roodbergen K.J.; Veenstra M.; Dijkstra A.S.","Schrotenboer, Albert H. (57190299865); Wruck, Susanne (55862885400); Roodbergen, Kees Jan (6506018019); Veenstra, Marjolein (57188554816); Dijkstra, Arjan S. (56581529900)","57190299865; 55862885400; 6506018019; 57188554816; 56581529900","Order picker routing with product returns and interaction delays",2017.0,"International Journal of Production Research",55.0,21.0,null,6394.0,6406.0,12.0,38.0,"10.1080/00207543.2016.1206982","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84979026666&doi=10.1080%2f00207543.2016.1206982&partnerID=40&md5=08853abc9b087b468b865016b4ddc2d8","Department of Operations, University of Groningen, Groningen, Netherlands; Bringmeister GmbH, Berlin, Germany","Schrotenboer A.H., Department of Operations, University of Groningen, Groningen, Netherlands; Wruck S., Bringmeister GmbH, Berlin, Germany; Roodbergen K.J., Department of Operations, University of Groningen, Groningen, Netherlands; Veenstra M., Department of Operations, University of Groningen, Groningen, Netherlands; Dijkstra A.S., Department of Operations, University of Groningen, Groningen, Netherlands","E-commerce companies often use manual order-picking systems in their warehouses since these systems can provide the required flexibility and scalability. Manual systems have been widely studied, but the operating policies may require significant changes for e-commerce settings. First, to maintain consumers’ loyalty, it is important to maintain delivery reliability even on the busiest days. When the number of order pickers in an area increases, however, more delays due to interactions may occur. For example, travel speed may need to be lowered when order pickers pass each other in narrow aisles. Second, many products sold through e-commerce are returned by consumers. Before these returned products can be sold again, they must be reintegrated in the stock. This paper presents hybrid genetic algorithms to determine routes for simultaneous pickup of products in response to consumers’ orders and delivery of returned products to storage locations. Furthermore, interactions between the order pickers are considered in the routing decisions. The developed algorithms use specific warehouse problem characteristics. We identify the mix of pickups and deliveries to realise the highest savings in practice. It is shown that order-picker interactions can be a significant cause for delay and should be accounted for in the routing. © 2016 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.","genetic algorithms; order-picker interaction; pickup and delivery problem; routing; warehousing systems","Commerce; Electronic commerce; Genetic algorithms; Pickups; Delivery reliability; Hybrid genetic algorithms; Operating policies; Order pickers; Order-picking systems; Pickup and delivery problems; routing; Warehousing systems; Warehouses",{"$nulls":6},"Chen F., Wang H., Qi C., Xie Y., An Ant Colony Optimization Routing Algorithm for Two Order Pickers with Congestion Consideration, Computers & Industrial Engineering, 66, 1, pp. 77-85, (2013); Chen F., Wang H., Xie Y., Qi C., An ACO-Based Online Routing Method for Multiple Order Pickers with Congestion Consideration in Warehouse, Journal of Intelligent Manufacturing, 27, 2, pp. 389-408, (2014); De Koster R., De Brito M.P., Van de Vendel M.A., Return Handling: An Exploratory Study with Nine Retailer Warehouses, International Journal of Retail & Distribution Management, 30, 8, pp. 407-421, (2002); De Koster R., Le-Duc T., Roodbergen K.J., Design and Control of Warehouse Order Picking: A Literature Review, European Journal of Operational Research, 182, 2, pp. 481-501, (2007); Gong Y., De Koster R.B.M., A Review on Stochastic Models and Analysis of Warehouse Operations, Logistics Research, 3, 4, pp. 191-205, (2011); Gu J., Goetschalckx M., McGinnis L.F., Research on Warehouse Operation: A Comprehensive Review, European Journal of Operational Research, 177, 1, pp. 1-21, (2007); Hong S., Johnson A.L., Peters B.A., Large-Scale Order Batching in Parallel-Aisle Picking Systems, IIE Transactions, 44, 2, pp. 88-106, (2012); Mosheiov G., The Travelling Salesman Problem with Pick-Up and Delivery, European Journal of Operational Research, 79, 2, pp. 299-310, (1994); Mostard J., De Koster R., Teunter R., The Distribution-Free Newsboy Problem with Resalable Returns, International Journal of Production Economics, 97, 3, pp. 329-342, (2005); Pan J.C.-H., Shih P.-H., Evaluation of the Throughput of a Multiple-Picker Order Picking System with Congestion Consideration, Computers & Industrial Engineering, 55, 2, pp. 379-389, (2008); Parikh P.J., Meller R.D., Estimating Picker Blocking in Wide-Aisle Order Picking Systems, IIE Transactions, 41, 3, pp. 232-246, (2009); Stock J.R., Mulki J.P., Product Returns Processing: An Examination of Practices of Manufacturers, Wholesalers/Distributors, and Retailers, Journal of Business Logistics, 30, 1, pp. 33-62, (2009); Theys C., Braysy O., Dullaert W., Raa B., Using a TSP Heuristic for Routing Order Pickers in Warehouses, European Journal of Operational Research, 200, 3, pp. 755-763, (2010); Tompkins J.A., White J.A., Bozer Y.A., Azana Tanchoco J.M., Facilities Planning, (2010); Vidal T., Crainic T.G., Gendreau M., Lahrichi N., Rei W., A Hybrid Genetic Algorithm for Multidepot and Periodic Vehicle Routing Problems, Operations Research, 60, 3, pp. 611-624, (2012); Vidal T., Crainic T.G., Gendreau M., Prins C., A Hybrid Genetic Algorithm with Adaptive Diversity Management for a Large Class of Vehicle Routing Problems with Time-Windows, Computers & Operations Research, 40, 1, pp. 475-489, (2013); Zhao F., Li S., Sun J., Mei D., Genetic Algorithm for the One-Commodity Pickup-and-Delivery Traveling Salesman Problem, Computers & Industrial Engineering, 56, 4, pp. 1642-1648, (2009); Zhao F.-G., Sun J.-S., Li S.-J., Liu W.-M., A Hybrid Genetic Algorithm for the Traveling Salesman Problem with Pickup and Delivery, International Journal of Automation and Computing, 6, 1, pp. 97-102, (2009)","A.H. Schrotenboer; Department of Operations, University of Groningen, Groningen, Netherlands; email: a.h.schrotenboer@rug.nl",null,"Taylor and Francis Ltd.",{"$nulls":5},207543.0,null,"IJPRB",null,"English","Int J Prod Res","Article","Final","All Open Access; Green Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-84979026666"]
["Musial J.; Pecero J.E.; Lopez-Loces M.C.; Fraire-Huacuja H.J.; Bouvry P.; Blazewicz J.","Musial, J. (36184609400); Pecero, J.E. (56013709600); Lopez-Loces, M.C. (56588022100); Fraire-Huacuja, H.J. (25931955700); Bouvry, P. (6603233977); Blazewicz, J. (35586597300)","36184609400; 56013709600; 56588022100; 25931955700; 6603233977; 35586597300","Algorithms solving the Internet shopping optimization problem with price discounts",2016.0,"Bulletin of the Polish Academy of Sciences: Technical Sciences",64.0,3.0,null,505.0,516.0,11.0,7.0,"10.1515/bpasts-2016-0056","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85021723653&doi=10.1515%2fbpasts-2016-0056&partnerID=40&md5=22b61a9010dfb3339b7552d368eb777b","Institute of Computing Science, Poznan University of Technology, 2 Piotrowo St., Poznan, 60-965, Poland; Comp. Sci. and Commun. Res. Unit, University of Luxembourg, 6 rue Coudenhove Kalergi, Luxembourg, L-1359, Luxembourg; Instituto Tecnológico de Ciudad Madero, Tecnológico Nacional de México, 1 de Mayo S/N, Ciudad Madero, 89440, Mexico; Institute of Bioorganic Chemistry, Polish Academy of Sciences, 12/14 Noskowskiego St., Poznan, 61-704, Poland","Musial J., Institute of Computing Science, Poznan University of Technology, 2 Piotrowo St., Poznan, 60-965, Poland; Pecero J.E., Comp. Sci. and Commun. Res. Unit, University of Luxembourg, 6 rue Coudenhove Kalergi, Luxembourg, L-1359, Luxembourg; Lopez-Loces M.C., Instituto Tecnológico de Ciudad Madero, Tecnológico Nacional de México, 1 de Mayo S/N, Ciudad Madero, 89440, Mexico; Fraire-Huacuja H.J., Instituto Tecnológico de Ciudad Madero, Tecnológico Nacional de México, 1 de Mayo S/N, Ciudad Madero, 89440, Mexico; Bouvry P., Comp. Sci. and Commun. Res. Unit, University of Luxembourg, 6 rue Coudenhove Kalergi, Luxembourg, L-1359, Luxembourg; Blazewicz J., Institute of Computing Science, Poznan University of Technology, 2 Piotrowo St., Poznan, 60-965, Poland, Institute of Bioorganic Chemistry, Polish Academy of Sciences, 12/14 Noskowskiego St., Poznan, 61-704, Poland","The Internet shopping optimization problem arises when a customer aims to purchase a list of goods from a set of web-stores with a minimum total cost. This problem is NP-hard in the strong sense. We are interested in solving the Internet shopping optimization problem with additional delivery costs associated to the web-stores where the goods are bought. It is of interest to extend the model including price discounts of goods. The aim of this paper is to present a set of optimization algorithms to solve the problem. Our purpose is to find a compromise solution between computational time and results close to the optimum value. The performance of the set of algorithms is evaluated through simulations using real world data collected from 32 web-stores. The quality of the results provided by the set of algorithms is compared to the optimal solutions for small-size instances of the problem. The optimization algorithms are also evaluated regarding scalability when the size of the instances increases. The set of results revealed that the algorithms are able to compute good quality solutions close to the optimum in a reasonable time with very good scalability demonstrating their practicability. © 2016 De Gruyter Open Ltd. All rights reserved.","Algorithms; Applications of operations research; Approximations; Combinatorial optimization; E-commerce; Heuristics; Internet shopping","Algorithms; Approximation algorithms; Combinatorial optimization; Costs; Electronic commerce; Operations research; Problem solving; Scalability; Approximations; Computational time; Heuristics; Internet shopping; Optimal solutions; Optimization algorithms; Optimization problems; Price discount; Optimization",{"$nulls":4},"FNR, (Luxembourg); NCBiR, (INTER/POLLUX/13/6466384)","Acknowledgments. This study was partially supported by the FNR (Luxembourg) and NCBiR (Poland), through IShOP project, INTER/POLLUX/13/6466384.","Tolle K.M., Chen H., Intelligent software agents for electronic commerce, Handbook on Electronic Commerce, pp. 365-382, (2000); Rose S., Dhandayudham A., Towards an understanding of Internet-based problem shopping behaviour: The concept of online shopping addiction and its proposed predictors, Journal of Behavioral Addictions, 3, 2, pp. 83-89, (2014); Blazewicz J., Kovalyov M., Musial J., Urbanski A., Wojciechowski A., Internet shopping optimization problem, International Journal of Applied Mathematics and Computer Science, 20, 2, pp. 385-390, (2010); Blazewicz J., Musial J., E-commerce evaluation - Multiitem Internet shopping. Optimization and heuristic algorithms, Operations Research Proceedings, 2010, pp. 149-154, (2011); Blazewicz J., Bouvry P., Kovalyov M.Y., Musial J., Internet shopping with price sensitive discounts, 4OR-Q J Oper Res, 12, 1, pp. 35-48, (2014); Blazewicz J., Bouvry P., Kovalyov M.Y., Musial J., Erratum to: Internet shopping with price-sensitive discounts, 4OR-Q J Oper Res, 12, 4, pp. 403-406, (2014); Sawik B., Downside risk approach for multi-objective portfolio optimization, Operations Research Proceedings, 2011, pp. 191-196, (2012); Goossens D.R., Maas A.J.T., Exact algorithms for procurement problems under a total quantity discount structure, European Journal of Operational Research, 178, 2, pp. 603-626, (2007); Wojciechowski A., Musial J., Towards optimal multi-item shopping basket management: Heuristic approach, Lecture Notes in Computer Science (LNCS), 6428, pp. 349-357, (2010); Wojciechowski A., Musial J., A customer assistance system: Optimizing basket cost, Foundations of Computing and Decision Sciences, 34, 1, pp. 59-69, (2009); Shaw M., Blanning R., Strader T., Whinston A., Handbook on Electronic Commerce, International Handbooks on Information Systems, (2000); Revelle C., Eiselt H., Daskin M., A bibliography for some fundamental problem categories in discrete location science, European Journal of Operational Research, 184, 3, pp. 817-848, (2008); Krarup J., Pisinger D., Plastria F., Discrete location problems with push-pull objectives, Discrete Applied Mathematics, 123, 13, pp. 363-378, (2002); Eiselt H., Sandblom C., Decision Analysis, Location Models, and Scheduling Problems, (2004); Melo M., Nickel S., Saldanha-Da Gama F., Facility location and supply chain management - A review, European Journal of Operational Research, 196, 2, pp. 401-412, (2009); Iyigun C., Ben-Israel A., A generalized Weiszfeld method for the multi-facility location problem, Operations Research Letters, 38, 3, pp. 207-214, (2010); Garey M., Johnson D., Computers and Intractability: A Guide to the Theory of NP-Completeness, (1979); Krichen S., Laabidi A., Abdelaziz F.B., Single supplier multiple cooperative retailers inventory model with quantity discount and permissible delay in payments, Computers & Industrial Engineering, 60, 1, pp. 164-172, (2011); Manerba D., Mansini R., An exact algorithm for the capacitated total quantity discount problem, European Journal of Operational Research, 222, 2, pp. 287-300, (2012); Mirmohammadi S.H., Shadrokh S., Kianfar F., An efficient optimal algorithm for the quantity discount problem in material requirement planning, Computers & Operations Research, 36, 6, pp. 1780-1788, (2009); Munson C., Hu J., Incorporating quantity discounts and their inventory impacts into the centralized purchasing decision, European Journal of Operational Research, 201, 2, pp. 581-592, (2010); Cormen T., Leiserson C., Rivest R., Stein C., Introduction to Algorithms, (2001); Teran-Villanueva J.D., Huacuja H.J.F., Valadez J.M.C., Pazos Rangel R.A., Soberanes H.J.P., Flores J.A.M., Cellular processing algorithms, Studies in Fuzziness and Soft Computing, 294, pp. 53-74, (2013); Burke E., Kendall G., Newall J., Hart E., Ross P., Schulenburg S., Hyper-heuristics: An emerging direction in modern search technology, Handbook of Metaheuristics, pp. 457-474, (2003); Diaz C.O., Pecero J.E., Bouvry P., Scalable, low complexity, and fast greedy scheduling heuristics for highly heterogeneous distributed computing systems, Journal of Supercomputing, 67, 3, pp. 837-853, (2014); Nesmachnow S., Dorronsoro B., Pecero J.E., Bouvry P., Energy-aware scheduling on multicore heterogeneous grid computing systems, Journal of Grid Computing, 11, 4, pp. 653-680, (2013); Wu M., Shu W., Zhang H., Segmented min-min: A static mapping algorithm for meta-tasks on heterogeneous computing systems, Heterogeneous Computing Workshop, pp. 375-385, (2000); Braun T., Siegel H., Beck N., Boloni L., Maheswaran M., Reuther A., Robertson J., Theys M., Yao B., Hensgen D., Et al., A comparison of eleven static heuristics for mapping a class of independent tasks onto heterogeneous distributed computing systems, Journal of Parallel and Distributed Computing, 61, 6, pp. 810-837, (2001); Land A., Doig A., An automatic method for solving discrete programming problems, Econometrica, 28, 3, pp. 497-520, (1960); Karen Clay E.W., Krishnan R., Prices and price dispersion on the web: Evidence from the online book industry, The Journal of Industrial Economics, 49, 4, pp. 521-539, (2001); Chu W., Choi B., Song M., The role of on-line retailer brand and infomediary reputation in increasing consumer purchase intention, International Journal of Electronic Commerce, 9, 3, pp. 115-127, (2005); Marszalkowski J., Marszalkowski J.M., Drozdowski M., Empirical study of load time factor in search engine ranking, Journal of Web Engineering, 13, 1-2, pp. 114-128, (2014); Pinel F., Dorronsoro B., Bouvry P., Solving very large instances of the scheduling of independent tasks problem on the GPU, Journal of Parallel and Distributed Computing, 73, 1, pp. 101-110, (2013); Ezzatti P., Pedemonte M., Martin A., An efficient implementation of the Min-Min heuristic, Computers & Operations Research, 40, 11, pp. 2670-2676, (2013); Marszalkowski J., Marszalkowski J., Musial J., Database scheme optimization for online applications, Foundations of Computing and Decision Sciences, 36, 2, pp. 121-129, (2011); Blazewicz J., Cheriere N., Dutot P.-F., Musial J., Trystram D., Novel dual discounting functions for the Internet shopping optimization problem: New algorithms, Journal of Scheduling, 19, 3, pp. 245-255, (2016); Guzek M., Gniewek A., Bouvry P., Musial J., Blazewicz J., Cloud Brokering: Current Practices and Upcoming Challenges","J. Musial; Institute of Computing Science, Poznan University of Technology, Poznan, 2 Piotrowo St., 60-965, Poland; email: Jedrzej.Musial@cs.put.poznan.pl",null,"De Gruyter Open Ltd",{"$nulls":5},2397528.0,null,null,null,"English","Bull. Pol. Acad. Sci. Tech. Sci.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-85021723653"]
["Yu H.","Yu, Haiyong (57193251652)",5.7193251652E10,"Study on the innovation and mode comparative of E-business supply chain under the background of Cross border trading",2017.0,"Boletin Tecnico/Technical Bulletin",55.0,14.0,null,281.0,289.0,8.0,2.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85039077233&partnerID=40&md5=dde2ccea092ec5a87d8d5c630d328643","School of Business Administration, University of Science and Technology, Liaoning, Anshan, 114051, China","Yu H., School of Business Administration, University of Science and Technology, Liaoning, Anshan, 114051, China","Cross border e-commerce is an emerging industry, with the popularity of consumer online shopping, cross-border e-commerce logistics has developed rapidly. In this paper, the author analyzes the innovation and mode comparative of E-business supply chain under the background of cross border trading. By comparing the main forms of cross-border logistics, as well as the existing problems, it can be seen that the cross-border e-commerce logistics in China has some problems as high cost, long time, low tracking and supervision ability. On this basis, the author puts forward some suggestions to optimize cross-border logistics capability. With the development of information technology, the mobile terminal logistics will become a new direction of cross-border e-commerce development.","Cross border logistics; E-commerce; Information system; Overseas storage","Commerce; Electronic commerce; Information systems; Supply chains; Cross-border; Cross-border trading; E-commerce development; Existing problems; High costs; Logistics capabilities; Mobile terminal; Online shopping; Mobile commerce",{"$nulls":6},"Fan X., Research on B2C cross-border logistics distribution mode in e-commerce, Journal of Pingxiang University, (2015); Liu L., Research on logistics problems and countermeasures in Chinese cross-border e-commerce development, international conference on education, Management and Computing Technology, (2015); Luo J.T., University C.J., Research on the development of logistics based on cross-border e-commerce in China, Logistics Engineering & Management, (2015); Wang L., Research on the development strategy of logistics firms in China, Open Journal of Social Sciences, 2, 9, pp. 253-257, (2015); Wang W., Chinese cross-border e-business supplier logistics development analysis, Modern Economy, 7, 8, pp. 875-880, (2016); Wang W., Comparative research on states of cross-border e-business supplier logistics, Ibusiness, 6, 4, pp. 726-730, (2016); Wang Y., Zhao M., Comparative Research on Chinese Logistics Models of Cross-border E-commerce, (2015); Yan P., Research on international logistics operation mode under the environment of cross-border e-business, China Business & Market, (2015); Yu X., Development of China cross-border e-business supplier, International Conference on Economics, Social Science, Arts, Education and Management Engineering, (2016); Zhong X.L., Research on SWOT analysis of cross-border e-commerce logistics in China, Logistics Engineering & Management, (2016)","H. Yu; School of Business Administration, University of Science and Technology, Liaoning, Anshan, 114051, China; email: haiyong_1977@163.com",null,"Universidad Central de Venezuela",{"$nulls":5},"0376723X",null,null,null,"English","Boletin Tecnico","Article","Final",null,"Scopus","2-s2.0-85039077233"]
["Hu D.","Hu, Dajiang (57196094024)",5.7196094024E10,"Uncertain environment time series of cross - Border E - Commerce logistics dynamic distribution path optimization algorithm",2017.0,"Boletin Tecnico/Technical Bulletin",55.0,9.0,null,187.0,193.0,6.0,0.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85031796702&partnerID=40&md5=350c9e41082b8faa0a1029448ea23225","School of Industry and Commerce Management, Chongqing City Management College, Chongqing, 401331, China","Hu D., School of Industry and Commerce Management, Chongqing City Management College, Chongqing, 401331, China","Based on the dynamic distribution data of E-commerce logistics, this paper studies the cognition of distribution route selection. Based on the pheromone of urban road function level and distribution frequency of e-commerce logistics, we establish e-commerce logistics path selection pheromone grade road network and use this as the initial pheromone of the road network. A dynamic distribution route based on ant colony optimization algorithm is proposed for cross - border e - commerce logistics distribution of uncertain environment time series. Taking the road network and the floating car as the experimental data, the path of the model planning and the trajectories in the floating vehicle database is compared. The results show that the ant colony optimization algorithm is very similar to the travel path chosen by the e - commerce logistics distribution driver, and can provide the best driving route for the dynamic distribution of e - commerce logistics.","Cross-border.; E-commerce; Logistics Dynamic Distribution; TimeSeries","Ant colony optimization; Artificial intelligence; Commerce; Electronic commerce; Roads and streets; Time series; Transportation; Transportation routes; Ant Colony Optimization algorithms; Cross-border; Distribution route; Dynamic distribution; Function levels; Logistics distribution; Path optimizations; Uncertain environments; Optimization",{"$nulls":4},"City Management Vocational College research and innovation","This work was supported byChongqing City Management Vocational College research and innovation","Feng N., Xie J., Chang P., An intelligent system to assessing information systems security risks in electronic business, Symposium on Information Science and Engineering, pp. 303-306, (2012); Ghatasheh N., Fraud prevention framework for electronic business environments: Automatic segregation of online phishing attempts, Cybersecurity and Cyberforensics Conference, pp. 89-95, (2010); Jerkovic H., Vranesic P., Slamic G., Implementation and analysis of open source information systems in electronic business course for economy students, Information and Communication Technology, Electronics and Microelectronics, pp. 912-917, (2016); Peng J., Li C., Liu J., Notice of retraction dynamic customer segmentation analysis based on customer value in electronic business environment, E-business and E-government, pp. 1-4, (2011); Sadighi M., Ghobadi M.M., Matikolaee S.H.H., A conceptual model for customer lock-in effect in electronic business, Information Technology - New Generations, pp. 746-750, (2015); Talamo M., Povilionis A., Arcieri F., Schunck C.H., Providing online operational support for distributed, security sensitive electronic business processes, Security Technology, pp. 49-54, (2015); Torki L., Rezaei A.A., Analyzing the impact of electronic business on investment in Iran during the period from 1981 to 2012, Commerce in Developing Countries: With Focus on E-business, pp. 1-6, (2015); Talamo M., Arcieri F., Schunck C.H., D'Iddio A.C., Conformance checking of electronic business processes to secure distributed transactions, Security Technology, pp. 1-6, (2013); Wang W., Fang H., Tang B., A capital management mode of electronic business service for Chinese medicine trading, Computer Supported Cooperative Work in Design, pp. 476-480, (2016); Yue I., Wang L., Zhang Y., The analysis of rural consumer adoption behavior of mobile electronic business platform, Information Management, pp. 88-92, (2017)",null,null,"Universidad Central de Venezuela",{"$nulls":5},"0376723X",null,null,null,"English","Boletin Tecnico","Article","Final",null,"Scopus","2-s2.0-85031796702"]
["He Y.; Wang X.; Lin Y.; Zhou F.; Zhou L.","He, Yandong (55951616500); Wang, Xu (55951735500); Lin, Yun (36655835400); Zhou, Fuli (57189093462); Zhou, Lin (57868712000)","55951616500; 55951735500; 36655835400; 57189093462; 57868712000","Sustainable decision making for joint distribution center location choice",2017.0,"Transportation Research Part D: Transport and Environment",55.0,null,null,202.0,216.0,14.0,78.0,"10.1016/j.trd.2017.07.001","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85030472343&doi=10.1016%2fj.trd.2017.07.001&partnerID=40&md5=88c32e8803353a117e9328aac5601971","College of Mechanical Engineering, Chongqing University, Chongqing, 400030, China; Management School, Chongqing University of Technology, Chongqing, 400054, China; Department of Electrical, Electronic, and Information Engineering “Guglielmo Marconi” (DEI), University of Bologna, Via Venezia, Cesena, 52-47521, Italy","He Y., College of Mechanical Engineering, Chongqing University, Chongqing, 400030, China; Wang X., College of Mechanical Engineering, Chongqing University, Chongqing, 400030, China; Lin Y., College of Mechanical Engineering, Chongqing University, Chongqing, 400030, China; Zhou F., College of Mechanical Engineering, Chongqing University, Chongqing, 400030, China; Zhou L., Management School, Chongqing University of Technology, Chongqing, 400054, China, Department of Electrical, Electronic, and Information Engineering “Guglielmo Marconi” (DEI), University of Bologna, Via Venezia, Cesena, 52-47521, Italy","Implementing joint distribution between express service providers is important in order to achieve operational efficiency and reduce operational cost. Joint distribution centers (JDCs) are an important part of the modern urban logistics system for online shopping, and selecting the location for a JDC has become a key problem for stakeholders considering sustainability. In this paper, we present a new hybrid fuzzy multiple-criteria decision-making method for selecting the location of a JDC considering sustainability. First, we identify the evaluation criteria for location selection integrating the economic, environmental, and social dimensions of sustainability. Secondly, a fuzzy set is used to translate linguistic preferences into triangular fuzzy numbers. Subjective criteria weights are calculated by combining the decision makers’ superiority linguistic ratings with a fuzzy AHP method. Objective criteria weights are determined by combining superiority linguistic ratings with a fuzzy-entropy method. Then, improved fuzzy TOPSIS is achieved by using weighted criterion distances to rank these alternatives. This permits a more stable ranking order to be obtained compared to traditional fuzzy TOPSIS which uses Euclidean distance. Finally, an empirical location selection and sensitivity analysis study is conducted to illustrate the effectiveness and robustness of the proposed method. This new method allows the location of a JDC to be selected considering sustainability, and will contribute to promoting the sustainable development of China's express industry and, to some extent, the sustainability and harmony of city development. © 2017 Elsevier Ltd","Fuzzy EW-AHP; Fuzzy TOPSIS; Joint distribution center; Location selection; Weighted criterion distance","China; Decision making; Fuzzy sets; Hierarchical systems; Linguistics; Location; Logistics; Sensitivity analysis; Urban growth; Warehouses; Fuzzy EW-AHP; FUZZY TOPSIS; Joint distributions; Location selection; Weighted criterion distance; analytical hierarchy process; decision making; fuzzy mathematics; sensitivity analysis; stakeholder; sustainability; sustainable development; Sustainable development",{"$nulls":4},"Chongqing City Key Science Program Project; National Science and Technology Support Program of China, (2015BAH46F01); Fundamental Research Funds for the Central Universities, (106112015CDJSK02JD05, CDJZR14110001); Specialized Research Fund for the Doctoral Program of Higher Education of China, SRFDP, (20130191110045)","This study was supported by the National Science and Technology Support Program of China (under Grant No. 2015BAH46F01 ), the Specialized Research Fund for the Doctoral Program of Higher Education of China (under Grant No. 20130191110045 ), the Fundamental Research Funds for the Central Universities Project (under Grant Nos. CDJZR14110001 and 106112015CDJSK02JD05 ), and the Chongqing City Key Science Program Project (under Grant Nos. cstc2015zdcy-ztzx60009 and cstc2015yykfC60002 ). We are also grateful to the other people in the City Joint Distribution for Online Shopping Logistic team for their stimulating collaboration and discussion. Finally, we would also like to thank the Editor and anonymous reviewers for their suggestions in improving the quality of this paper.  ","AliResearch, (2015); Abbaspour M., Karimi E., Nassiri P., Monazzam M.R., Taghavi L., Hierarchal assessment of noise pollution in urban areas – a case study, Transport. Res. Part D Transp. Environ., 34, pp. 95-103, (2015); Awasthi A., Adetiloye T., Crainic T.G., Collaboration partner selection for city logistics planning under municipal freight regulations, Appl. Math. 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Syst., 22, 4, pp. 1139-1147, (2016); Zhou J., Zhong X., TAOBAO Logistics Model Based on Joint Distribution//LISS 2014, pp. 29-33, (2015)","X. Wang; College of Mechanical Engineering, Chongqing University, Chongqing, 400030, China; email: wx921@163.com",null,"Elsevier Ltd",{"$nulls":5},1.3619209E7,null,"TRDTF",null,"English","Transp. Res. Part D Transp. Environ.","Article","Final",null,"Scopus","2-s2.0-85030472343"]
["Rejikumar G.; Aswathy Asokan A.","Rejikumar, G. (55513688700); Aswathy Asokan, A. (57219838768)","55513688700; 57219838768","Customer perceived determinants of online buying: A conjoint experiment",2017.0,"Journal of Advanced Research in Dynamical and Control Systems",9.0,"Special Issue  18",null,1907.0,1918.0,11.0,0.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85042727180&partnerID=40&md5=b59c646e3e0004fb6cf6dc0cd7d5cf71","Department of Management, Amrita University, Kochi, India; Doms, IIT Madras, India","Rejikumar G., Department of Management, Amrita University, Kochi, India; Aswathy Asokan A., Doms, IIT Madras, India","This paper examines the application of conjoint analysis for identifying customer preferences on different levels in certain attributes that significantly decides satisfaction towards e-commerce. The results of the tests identified that logistic dimension followed by attributes creating better customer experience occupies top importance in the perceptions of Indian customers. At attribute level, interactive features and shipping cost considerations are perceived more important by customers. A general conclusion drawn from the study was that innovative aspects that bring better interactive capabilities and developing trust about inward and outward logistic activities are essential to develop and retain customer satisfaction in e-commerce. © 2017, Institute of Advanced Scientific Research, Inc. All rights reserved.","Conjoint analysis; Consumer behavior; E-commerce; Online satisfaction; Utility",{"$nulls":7},"Ajzen I., Fishbein M., Attitude-behavior relations: A theoretical analysis and review of empirical research, Psychological Bulletin, 84, 5, (1977); Bhatnagar A., Misra S., Rao H.R., On risk, convenience, and Internet shopping behavior, Communications of the ACM, 43, 11, pp. 98-105, (2000); Butler P., Peppard J., Consumer purchasing on the Internet:: Processes and prospects, European Management Journal, 16, 5, pp. 600-610, (1998); Chen L.D., Tan J., Technology Adaptation in E-commerce:: Key Determinants of Virtual Stores Acceptance, European Management Journal, 22, 1, pp. 74-86, (2004); Childres L.T., Carr L.C., Peck J., Carson S., Hedonic and utilitarian motivations for online retail shopping behavior, Journal of Retailing, 77, 4, pp. 511-535, (2001); Chuang C., Hu F.L., An empirical analysis of the relationship between website characteristics and consumer online buying behavior, Interdisciplinary Journal of Contemporary Research in Business, 4, 7, pp. 286-294, (2012); Citrin A.V., Stem D.E., Spangenberg E.R., Clark M.J., Consumer need for tactile input: An internet retailing challenge, Journal of Business Research, 56, 11, pp. 915-922, (2003); Daniellwigder Z., Bahl M., Trends in India’s Ecommerce Market, 3, (2012); Davis F.D., Bagozzi R.P., Warshaw P.R., User acceptance of computer technology: A comparison of two theoretical models, Management Science, 35, 8, pp. 982-1003, (1989); Dubey A., Raitani S., E-shopping momentum: A conceptual framework, International Journal of Electronic Marketing and Retailing, 7, 4, pp. 346-365, (2016)",null,null,"Institute of Advanced Scientific Research, Inc.",{"$nulls":5},"1943023X",null,null,null,"English","J. Adv. Res. Dyn. Control. Syst.","Article","Final",null,"Scopus","2-s2.0-85042727180"]
["Park S.-H.; Kim J.-Y.; Lee Y.-H.","Park, Se-Hwan (55603420300); Kim, Jong-Yun (57196169815); Lee, Young-Hyun (57201585785)","55603420300; 57196169815; 57201585785","Technical and market trend analysis of Li-Fi Lan system",2017.0,"Journal of Engineering and Applied Sciences",12.0,10.0,null,2575.0,2579.0,4.0,0.0,"10.3923/jeasci.2017.2575.2579","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85045312009&doi=10.3923%2fjeasci.2017.2575.2579&partnerID=40&md5=6e0ba588d281f74446a6a3a66de9a5e6","Department of Reset Program, Korea Institute of Science and Technology Information (KISTI), 66 Hoegi-ro, Dongdaemun-gu, Seoul, 02456, South Korea; Department of Computer Engineering, Kyungdong University, Gangwon, South Korea; Department of Tax Accounting, Gumi University, Gumi, South Korea","Park S.-H., Department of Reset Program, Korea Institute of Science and Technology Information (KISTI), 66 Hoegi-ro, Dongdaemun-gu, Seoul, 02456, South Korea; Kim J.-Y., Department of Computer Engineering, Kyungdong University, Gangwon, South Korea; Lee Y.-H., Department of Tax Accounting, Gumi University, Gumi, South Korea","Within 10 m WLAN and within 10 cm from the two-way data communication possible close contact/contactless data communications technology is applied very widely spread. In this study, the visible light wavelength using optical wireless communication technology in ultra wideband characteristics of LED-VLC systems technology trends, seems to have promise, Li-Fi technology characteristics and indoor navigation/ITS/cultural content delivery/u-home construction, etc. Li-Fi a wide variety of applications in the system such as building, posed an obstacle between the chip and smart appliances the beacon light wave transmission characteristics of problems/strong external light due to the communication failure is due to a century of telecommunications/light such as the limits of the problem to be solved due to the improving the performance of high-value industries, LED by noted LED-VLC and standardizes the marketability of technology about the prospect. Wi-Fi > 100 times over high-speed bidirectional wireless transmission system, possible Li-Fi network powered by the next generation of growth emerging. Li-Fi technology Wi-Fi high efficiency lighting technology and internet shares LED the technology combines LED-VLC technology. LED lighting technology-based Li-Fi system for indoor navigation, ITS, content delivery and u-home construction was the application in a variety of industries are going to spread those values. Indoor navigation GPS systems that are difficult to operate in the field of Interior of barriers will be able to solve. Li-Fi technology is applied very widely spread that WLAN (10 cm~10 m) from the two-way data communication possible close contact/contactless. © Medwell Journals, 2017.","Backbone network; E-Commerce; GPS system; High-efficiency LED; ITS; LED-VLC; Li-Fi; M2M/D2D; Mobile media; U-home; Visible light intelligent network; Wi-Fi; WLAN",{"$nulls":5},"National Research Foundation of Korea, NRF; Ministry of Science ICT and Future Planning, MSIP","This research was supported by the ReSEAT Program funded by the Korean Minishy of Science ICT and Future Planning through, the National Research Foundation of Korea and the Korea Lottery Commission Grants","Li-Fi(visible light LED lighting wireless technology) key patent analysis, (2015); Global by region Li-Fi technology market growth research-related materials, (2015); Cisco visual networking index: Forecast and methodology 2012-2017, (2015); Colin R.J., Visible light illuminates a new approach for wireless comm's, (2010); Dong K.K., The prospect and strategy of 5G mobile communication technologies, (2014); Hee-Suk K., A study on security system of 4G Network system, J. Inst. Internet Broadcast. Commun, 16, pp. 15-23, (2016); Hwan S.P., Industry Trends of Li-FI and Beacon, (2016); Jang Y.H., A proposal for innovative app developing tool, J. Convergence Culture Technol, 2, pp. 41-44, (2016); Jeon D.K., Lee Y., Performance evaluation of WiMedia UWB MAC protocol algorithm supporting mixed video and shipboard control data traffic, Intl. J. Internet Broadcast. Commun, 8, pp. 99-109, (2016); Smart media service usage survey, (2014); Kim S.J., Lee H., Lee M., A study of 4G network for security system, Intl. J. Adv. Culture Technol, 3, pp. 77-86, (2015); Kim Y.M., Woo Suk L.E.E., Kwon O.S., Jung K., Lee J.Y., Adaptive method for selecting cluster head according to the energy of the sensor node, Intl. J. Adv. Cult. Technol, 4, pp. 19-26, (2016); Kwon M.R., The impact of emotional intelligence and self-esteem on internet and smart phone addiction, sports activities and reading of youth, Intl. J. Internet Broadcasting Commun, 9, pp. 35-41, (2017); Kyu K., 5G mobile communication technology trends based on the millimeter-wave, (2014); Patcharaprakiti N., Tripak K., Saelao J., Load modeling based on system identification with kalman filtering of electrical energy consumption of residential air-conditioning, Intl. J. Adv. Smart Convergence, 4, pp. 45-53, (2015)",null,null,"Medwell Journals",{"$nulls":5},"1816949X",null,null,null,"English","J. Eng. Appl. Sci.","Article","Final",null,"Scopus","2-s2.0-85045312009"]
["Khopkar S.S.; Nikolaev A.G.","Khopkar, Sushant S. (55605223600); Nikolaev, Alexander G. (24076936000)","55605223600; 24076936000","Predicting long-term product ratings based on few early ratings and user base analysis",2017.0,"Electronic Commerce Research and Applications",21.0,null,null,38.0,49.0,11.0,7.0,"10.1016/j.elerap.2016.12.002","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85008441803&doi=10.1016%2fj.elerap.2016.12.002&partnerID=40&md5=dfcf3cde06d8b7af998bd90d065e0091","Department of Industrial and Systems Engineering, State University of New York at Buffalo, Buffalo, 14260, NY, United States","Khopkar S.S., Department of Industrial and Systems Engineering, State University of New York at Buffalo, Buffalo, 14260, NY, United States; Nikolaev A.G., Department of Industrial and Systems Engineering, State University of New York at Buffalo, Buffalo, 14260, NY, United States","Product reviews and ratings are major quality indicators in online shopping systems. In making the decision about carrying a product as part of their inventory, an online seller often pays attention to the product's rating. However, when the observed average is based on a small number of individual user-submitted ratings, the decision-maker may not feel as confident about the product, even when the average is high. The long-term average rating predictions can help online retailers to identify products to promote on their websites as “top picks”. The paper proposes a Bayesian Network model to predict the long-term average product ratings based on a (limited) number of early submitted ratings. Performance of the proposed model is compared with the performance of five other prediction methods/models; a Linear Regression model, two variations of a Running Average predictor, an Ordered Logistic Regression model and a Confirmatory Factor Analysis model. Each model's performance is evaluated using the “MovieLens” dataset (GroupLensResearch, 2012). The training is done on 56,590 data points, the ratings submitted for 1155 movies, and the prediction results are reported for 495 movies. It is demonstrated that the proposed Bayesian Network and the Linear Regression models are particularly effective in making accurate predictions around the time of product introduction when the information about the prospective, future ratings is especially valuable. The Bayesian Network model performs better in the very early stage of feedback collection, and in the later stages, as more feedback is received, the Linear Regression model emerges as the best predictor. The strengths and weaknesses of all the assessed prediction methods are discussed. © 2016 Elsevier B.V.","Bayesian network modeling; Machine learning; Product rating prediction","Bayesian networks; Decision making; Electronic commerce; Factor analysis; Knowledge based systems; Learning systems; Linear regression; Online systems; Rating; Regression analysis; Accurate prediction; Bayesian network models; Confirmatory factor analysis; Linear regression models; Logistic Regression modeling; On-line Shopping systems; Product introduction; Product ratings; Forecasting",{"$nulls":4},"Academy of Finland, (268078)","The authors would like to thank Mr. Harshalkumar Patel for his valuable help in computational work. Alexander Nikolaev was partially funded by the Academy of Finland, Grant 268078 (MineSocMed).","Adomavicius G., Tuzhilin A., Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions, IEEE Trans. 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Neural Inf. Process. Syst., 11, 11, (1999); Smyth B., Cotter P., A personalised tv listings service for the digital TV age, Knowledge-Based Syst., 13, 2, pp. 53-59, (2000); Sun M., How does the variance of product ratings matter?, Manage. Sci., 58, 4, pp. 696-707, (2012); Tran T., Cohen R., Hybrid recommender systems for electronic commerce, Proc. Knowledge-Based Electronic Markets, Papers from the AAAI Workshop, Technical Report WS-00-04, (2000); Trusov M., Rand W., Joshi Y.V., Improving prelaunch diffusion forecasts: using synthetic networks as simulated priors, J. Market. Res., 50, 6, pp. 675-690, (2013); Yang Y., An evaluation of statistical approaches to text categorization, Inf. Retrieval, 1, 1-2, pp. 69-90, (1999); Yu X., Liu Y., Huang X., An A., Mining online reviews for predicting sales performance: a case study in the movie domain, IEEE Trans. Knowledge Data Eng., 24, 4, pp. 720-734, (2012); Zhang L., Luo J., Yang S., Forecasting box office revenue of movies with bp neural network, Expert Syst. Appl., 36, 3, pp. 6580-6587, (2009); Zhu F., Zhang X., Impact of online consumer reviews on sales: the moderating role of product and consumer characteristics, J. Market., 74, 2, pp. 133-148, (2010)","S.S. Khopkar; Department of Industrial and Systems Engineering, State University of New York at Buffalo, Buffalo, 14260, United States; email: skhopkar@buffalo.edu",null,"Elsevier B.V.",{"$nulls":5},1.5674223E7,null,null,null,"English","Elect. Commer. Res. Appl.","Article","Final",null,"Scopus","2-s2.0-85008441803"]
["Zhou G.; Si L.; Mo Y.; Hu J.","Zhou, Guanglan (26421507400); Si, Li (57201007793); Mo, Yutao (57201011378); Hu, Jun (57201012354)","26421507400; 57201007793; 57201011378; 57201012354","The effect on the growth and evolution model of logistics symbiosphere",2018.0,"International Journal of Manufacturing Technology and Management",32.0,2.0,null,162.0,175.0,13.0,1.0,"10.1504/IJMTM.2018.090064","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85042881148&doi=10.1504%2fIJMTM.2018.090064&partnerID=40&md5=59dbdba093260bb0b571269f6241fa5e","Contemporary Business and Trade Research Center, Zhejiang Gongshang University, Hangzhou, China; School of Accounting, Zhejiang Gongshang University, Hangzhou, China; School of Computer Science and Information Engineering, Zhejiang Gongshang University, Hangzhou, China; National Economic and Technology Development, Zone of Xiangyang Government, Xiangyang, 441000, Hubei, China","Zhou G., Contemporary Business and Trade Research Center, Zhejiang Gongshang University, Hangzhou, China; Si L., School of Accounting, Zhejiang Gongshang University, Hangzhou, China; Mo Y., School of Computer Science and Information Engineering, Zhejiang Gongshang University, Hangzhou, China; Hu J., National Economic and Technology Development, Zone of Xiangyang Government, Xiangyang, 441000, Hubei, China","With the fast development of industrial internet, big data, cloud computing technology, these applications continue to improve the environment of e-commerce which has become a new corporate business activity. In this e-logistics environment, many businesses and companies must form an ecosystem to seek survival and development, which has interdependent, collaborative and innovative relationships. This article will adopt the symbiosis theory to build symbiotic circle model. By solving the planning model, it draws the conclusion that the logistics service providers must follow the differential route in development in line with prominent features. Through an accurate positioning of market requirements, it could achieve the standard profit maximisation. Copyright © 2018 Inderscience Enterprises Ltd.","E-commerce ecosystem; Fourth party logistics service providers; Symbiosis model; Symbiosis theory","Ecosystems; Electronic commerce; Business activities; Cloud computing technologies; E-commerce ecosystems; Fourth party logistics; Logistics service provider; Market requirements; Prominent features; Symbiosis theory; Computation theory",{"$nulls":4},"Contemporary Business and Trade Research Center and Center for Collaborative Innovation Studies of Modern Business of Zhejiang Gongshang University of China; E-Business Technology of Zhejiang Province, (2010R50041); Foundation of Department of Education of Zhejiang Province, (Y201329545); Key Laboratory of Electronic Business and Logistics Information Technology of Zhejiang Province, (2011E10005); Zhejiang Department of Education; Zhejiang Gongshang University, ZJSU, (14SMXY05YB, 15SMGK26YB); National Natural Science Foundation of China, NSFC, (71203196, 71401156, 71571162); Ministry of Education of the People's Republic of China, MOE, (10YJA630030, 11YJC630019, 14JJD630011, 14YJCZH226, 15SMGK28YB); Natural Science Foundation of Zhejiang Province, ZJNSF, (LQ12G01007, LY12G03015, LY14F020002, LY7100673); Ministry of Electronics and Information technology, Meity; Department of Education of Zhejiang Province","Funding text 1: The authors sincerely thank the anonymous reviewers for their comments and suggestions to improve the paper. This paper is supported by humanities and social science research project of Ministry of Education of the People’s Republic of China (No. 10YJA630030, 14YJCZH226, 14JJD630011, 11YJC630019, 15SMGK28YB), Foundation of Department of Education of Zhejiang Province (Y201329545), Key Laboratory of Electronic Business and Logistics Information Technology of Zhejiang Province (2011E10005), Innovative Group of E-Business Technology of Zhejiang Province (2010R50041), Natural Science Foundation of China (No. 71203196, 71401156, 71571162), Zhejiang Provincial Natural Science Foundation of China (LY14F020002, LY7100673, LY12G03015, LQ12G01007), Contemporary Business and Trade Research Center and Center for Collaborative Innovation Studies of Modern Business of Zhejiang Gongshang University of China(Grant No. 14SMXY05YB, 15SMGK28YB and 15SMGK26YB). The authors thank them heartedly for supporting the paper funds.; Funding text 2: Biographical notes: Guanglan Zhou is the Director of Zhejiang International Centre of E-Business and Modern Logistics. He chairs a couple of projects funded by the Ministry of Education, China and Zhejiang Department of Education. His research interests include e-business and service supply chain management.; Funding text 3: Li Si is a post-graduate student in the School of Accounting, Zhejiang Gongshang University. She chairs the university student innovation projects funded by Zhejiang Gongshang University. Her research interests include the financial management in e-business and service supply chain management.","Adner R., Kapoor R., Value creation in innovation ecosystems: How the structure of technological interdependence affects firm performance in new technology generations, Strategic Management Journal, 31, 3, pp. 306-333, (2010); Alberto S., Raffaella T., Anna M., Analysing the development of industrial symbiosis in a motorcycle local industrial network: The role of contextual factors, Journal of Cleaner Production, 66, 3, pp. 372-383, (2014); Behera S., Evolution of ‘designed’ industrial symbiosis networks in the Ulsan eco-industrial park: ‘research and development into business’ as the enabling framework, Journal of Cleaner Production, 29, 7, pp. 103-112, (2012); Chen D., Some issues of supply chain management research and progress on, Journal of Systems Engineering Theory and Practice, 23, 10, pp. 1-11, (2010); Chen F., Facing the WTO of our country enterprise knowledge alliance with foreign multinational firms to explore, China Industrial Economy, 17, 9, pp. 41-50, (2000); Craighead C.W., Hult G.M., Ketchen D.J., The effects of innovation-cost strategy, knowledge, and action in the supply chain on firm performance, Journal of Operations Management, 27, 5, pp. 405-421, (2009); Crook T.R., Ketchen D.J., Combs J.G., Todd S.Y., Strategic resources and performance: A meta-analysis, Strategic Management Journal, 29, 11, pp. 1141-1154, (2008); Guo L., Industrial Symbiosis Evolution and Technology Impetus Research, (2005); Hu W., Enterprise strategic alliance and the alliance partner selection, Journal of Beijing Institute of Machinery Industry, 20, 12, pp. 54-60, (2005); Ketchen D.J., Crook T.R., Craighead C.W., From supply chains to supply ecosystems: Implications for strategic sourcing research and practice, Journal of Business Logistics, 35, 3, pp. 165-171, (2014); Li C., Luo Y., Supply chain management coordination mechanism model research, Science and Technology Progress and Countermeasures, 20, 7, pp. 108-110, (2010); Li P., This social symbiotic ethical, Journal of Xiangtan Normal University (Social Science Edition), 24, 5, pp. 29-35, (2000); Lu C., Rong K., You J., Shi Y., Business ecosystem and stakeholders’ role transformation: Evidence from Chinese emerging electric vehicle industry, Expert Systems with Applications, 41, 10, pp. 4579-4595, (2014); Lu S., Supply chain coordination mechanism research, Journal of Logistics Technology, 29, 29, (2011); Mei X., Luo L., The difficulty and the methods of the strategic alliance partner relationship management, Science and Technology Pioneer, 4, 1, pp. 22-23, (2005); Spekkink W., Institutional capacity building for industrial symbiosis in the Canal Zone of Zeeland in the Netherlands: A process analysis, Journal of Cleaner Production, 52, pp. 342-355, (2013); Tao Y., Based on The Symbiosis Theory of Ship Formation Mechanism of Industry Cluster and Evolution Research, (2005); Wei W., The stability of strategic alliance organization governance and credit constraints mechanism, Journal of Economic Management, 28, 8, pp. 49-55, (2006); Yuan Z., Lei S., Improving enterprise competitive advantage with industrial symbiosis: Case study of a smeltery in China, Journal of Cleaner Production, 17, 14, pp. 1295-1302, (2009); Zhuang P., Wang N., The status and development trend of supply chain coordination mechanism, Journal of Mechanical Science and Technology, 22, S2, pp. 204-206, (2003)","G. Zhou; Contemporary Business and Trade Research Center, Zhejiang Gongshang University, Hangzhou, China; email: guanglanzhou@zjgsu.edu.cn",null,"Inderscience Publishers",{"$nulls":5},1.3682148E7,null,null,null,"English","Int. J. Manuf. Technol. Manage.","Article","Final",null,"Scopus","2-s2.0-85042881148"]
["Zhang S.; Guo K.; Sun Y.","Zhang, Shushan (56099056200); Guo, Kun (57196218513); Sun, Yi (57196217077)","56099056200; 57196218513; 57196217077","Study on integrated optimization model of inventory and routing roblem and its application in china’s online agricultural products logistics",2017.0,"Custos e Agronegocio",13.0,2.0,null,73.0,87.0,14.0,2.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85032289123&partnerID=40&md5=482067743221d49ab0963243bacb04f6","Logistics and Supply Chain Management, Business School: Northeast Normal University, Business School, Northeast Normal University, Changchun, 130117, Jilin Province, China; Strategic Management -Business School, Northeast Normal University, Business School, Northeast Normal University, Changchun, 130117, Jilin Province, China; Electronic Business -Business School, Northeast Normal University, Business School, Northeast Normal University, Changchun, 130117, Jilin Province, China","Zhang S., Logistics and Supply Chain Management, Business School: Northeast Normal University, Business School, Northeast Normal University, Changchun, 130117, Jilin Province, China; Guo K., Strategic Management -Business School, Northeast Normal University, Business School, Northeast Normal University, Changchun, 130117, Jilin Province, China; Sun Y., Electronic Business -Business School, Northeast Normal University, Business School, Northeast Normal University, Changchun, 130117, Jilin Province, China","China's online shopping marketdeveloped rapidly in the last ten years. More and more companies focus on the performance of the supply chain instead of their own performance. Relatively short agricultural products shelf life leads to low profit. According to the characteristics of the online agricultural products logistics, the way how to control inventory cost and transportationcostin order to increase profits has become a serious and urgently solved problem. In order to solve the shortage of the practical applicationof the VMI modeunder online shopping environment, the paper makesthe combinationof the VMIand 3PL. Firstly, the inventory routing modelofa three-level distribution system with avendor, a third party logistics companyand multiple geographically dispersed retailersbased on VMI-3PL and fixed partition policiesis built.The goal is tominimizethe total cost including the transportation cost and the inventory cost withno allowing storage.Secondly, the paper proposed a heuristic algorithm whichisbased on Matlab7.5 and ant colony algorithm.Lastly,Computational results show the performance of the solution approach. © 2017, Universidade Federal Rural de Pernambuco. All rights reserved.","3PL, Fixed Partition Policies; Agricultural products online; Antcolony algorithm; Inventory and Routing",{"$nulls":5},"People's Government of Jilin Province, (14RY002); Ministry of Agriculture of the People's Republic of China, MOA, (1504008)","The project was supported by the Science and technology planning project of Changchun, JiLin Province (14RY002), Electronic commerce logistics research project of Ministry of Commerce of the People's Republic of China (1504008). We would like to thank editorial team support.","Coelho L.C., Cordeau J.F., Laporte G., Heuristics for dynamic and stochastic inventory-routing, Computers & Operations Research, 52, 12, pp. 55-67, (2014); Diabat A., Hybrid algorithm for a vendor managed inventory system in a two-echelon supply chain, European Journal of Operational Research, 238, 1, pp. 114-121, (2014); Ekici A., Ozener O.O., Kuyzu G., Cyclic Delivery Schedules for an Inventory Routing Problem., Transportation Science, 49, 4, pp. 817-829, (2015); Guo S.M., Hou C.W., Multi-Objective Optimization for VMI Operations in the LCD Supply Chain, 7, pp. 1-6, (2010); Govindan K., The optimal replenishment policy for time-varying stochastic demand under vendor managed inventory, European Journal of Operational Research, 242, 2, pp. 402-423, (2015); Huang S.H., Lin P.C., A modified ant colony optimization algorithm for multi-item inventory routing problems with demand uncertainty, Transportation Research Part E, 46, pp. 598-611, (2014); Ivanov D., Pavlov A., Sokolov B., Optimal distribution planning in a centralized multi-stage supply network under conditions of the ripple effect and structure dynamics, European Journal of Operational Research, 237, 2, pp. 758-770, (2014); Leandro C.C., Cordeau J.F., The Inventory-Routing Problem with Transshipment, 11, pp. 2537-2548, (2012); Li J.X., Chu F., Chen H.X., A solution approach to the inventory routing problem in a three-level distribution system, European Journal of Operationalresearch, 210, pp. 736-744, (2011); Niknamfar A.H., Multi-objective production-distribution planning based on vendor-managed inventory strategy in a supply chain, Industrial Management & Data Systems, 15, 6, pp. 1086-1112, (2015); Park Y.B., Park H.S., Smart vending machine systems: Operation and performance, European of Industrial Engineering, 9, 4, pp. 409-431, (2015); Pasandideh S.H.R., Niaki S.T.A., Nia A.R., An investigation of vendor-managed inventory application in supply chain: The EOQ model with shortage, International Journal Advanced Manufacturing Technology, 5, 49, pp. 329m-339m, (2010); Vansteenwegen P., Mateo M., An iterated local search algorithm for the single-vehicle cyclic inventory routing problem, European Journal of Operational Research, 237, 3, pp. 802-813, (2014); Xu J., Research on Integrated Optimization of Inventory and Routing Problem Based on VMI-TPL, (2012); Zhong Y.Q., Aghezzaf E.H., Combining DC programming and steepest-descent to solve the single-vehicle inventory routing problem, Computers & Industrial Engineering, 61, pp. 313-321, (2011); Zhao Q.H., Chen S., Zang C.X., Model and algorithm for inventory/routing decision in a three-echelon logistics system, European Journal of Operational Research, pp. 623-635, (2008)","S. Zhang; Logistics and Supply Chain Management, Business School: Northeast Normal University, Business School, Northeast Normal University, Changchun, 130117, China; email: zhangss591@nenu.edu.cn",null,"Universidade Federal Rural de Pernambuco",{"$nulls":5},1.8082882E7,null,null,null,"English","Custos Agronegocio","Article","Final",null,"Scopus","2-s2.0-85032289123"]
["Alyahya S.; Wang Q.; Bennett N.","Alyahya, Saleh (57191669645); Wang, Qian (55533227000); Bennett, Nick (8657853100)","57191669645; 55533227000; 8657853100","Application and integration of an RFID-enabled warehousing management system – a feasibility study",2016.0,"Journal of Industrial Information Integration",4.0,null,null,15.0,25.0,10.0,71.0,"10.1016/j.jii.2016.08.001","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85016106087&doi=10.1016%2fj.jii.2016.08.001&partnerID=40&md5=750da7fda7bebdbd38c0dd4e83422e54","School of Engineering, University of Portsmouth, PO1 3DJ, Portsmouth, United Kingdom","Alyahya S., School of Engineering, University of Portsmouth, PO1 3DJ, Portsmouth, United Kingdom; Wang Q., School of Engineering, University of Portsmouth, PO1 3DJ, Portsmouth, United Kingdom; Bennett N., School of Engineering, University of Portsmouth, PO1 3DJ, Portsmouth, United Kingdom","In supply chain and logistics sectors, accuracy of inventory data can be crucial for warehouse operations, SKU planning, and inventory management and control of incoming and outgoing goods. For the past decade, it has been seen a sharp rise for online shopping activities across the UK. Many customers now prefer to purchase goods online and demand a fast delivery of ordered products to be dispatched directly at their door steps. Thus, there is a desire for these sectors to seek even more efficient and effective methods for storing, picking and dispatching goods in increasingly centralised distribution centres in which automation and integration of warehousing systems is inevitable. As part of a study for future generation warehouses, this paper presents an investigation into a methodology in which an RFID-based inventory management system has capability of interacting with a proposed RFID-enabled automated storage and retrieval mechanism without any human intervention. To maximise efficiency in material-handling operations and minimise operational costs, a selection algorithm was developed within the RFID-inventory management system to seek an optimal solution in which it allows a manipulation of RFID-tracked items under pre-defined rules by assigning a priority (in an order if applicable) to one of selected items to travel to a specified collection point. A pilot test was carried out for examining the feasibility and applicability of the RFID-based management system based on the developed selection algorithm. In theory, such a system can be expanded by incorporating any pre-defined selection parameters. © 2016","Automation; Integration; Inventory management; RFID; Warehousing systems","Automation; Digital storage; Integration; Inventory control; Radio frequency identification (RFID); Supply chains; Warehouses; Distribution centres; Feasibility studies; Inventory management; Inventory management systems; Selection algorithm; Selection parameters; Warehouse operation; Warehousing systems; Distribution of goods",{"$nulls":6},"Wang Q., Mclntosh R., Brain M., A new-generation automated warehousing capability, Int. J. Comput. Integrat. Manufactur., 6, pp. 565-573, (2010); Lim M.K., Bahr W., Leung S.C.H., RFID in the warehouse: a literature analysis (1995-2010) of its applications, benefits, challenges and future trends, Int. J. Production Econ., 145, pp. 409-430, (2013); Sahin E., Dallery Y., A literature review on the impact of inventory data record inaccuracies on inventory management and the potential of the RFID technology to tackle this issue, (2007); Wang H., Chen S., Xie Y., An RFID-based digital warehouse management system in the tobacco industry: a case study, Int. J. Production Res., 48, 9, pp. 2513-2548, (2010); Chow H.K.H., Choy K.L., Lee W.B., Lau K.C., Design of a RFID case–based resource management system for warehouse operations, J. Business Logist., 30, pp. 561-576, (2006); Liu G., Yu W., Liu Y., Resource management with RFID technology in automatic warehouse system, IEEE/RSJ International Conference On Intilegent Robots And Systems, Beijing, pp. 3706-3711, (2006); Poon T.C., Choy K.L., Chow H.K.H., Lau H.C.W., Chan F.T.S., Ho K.C., A RFID case-based logistics resource management system for managing order-picking operations in warehouses, Expert Syst. Appl., 36, pp. 8277-8301, (2009); Ting J.S.L., Tsang A.H.C., Design of an RFID-based inventory control and management system: a case study, West Ind. J. Eng., 34, pp. 70-79, (2012); Ross A.D., Twede D., Clarke R.H., Ryan R.H., A framework for developing implementation strategies for a radio frequency identification (RFID) system in a distribution centre environment, J. Business Logist., 30, pp. 157-183, (2009); Xu Z., Ming X.G., Zhou J., Song W., He L., Miao Li, Management optimisation based on dynamic SKU for RFID-enabled warehouse management in the steel supply chain, Int. J. Prod. Res., 51, pp. 2981-2996, (2013); Liu Y., Wang D., An RFID middleware business process integration framework based on EPC modeling and complex event processing, International Conference on Computer Sciences and Convergence Information Technology, Seoul, pp. 64-69, (2009); Wang L., Xu L.D., Bi Z., Xu Y., Data cleaning for RFID and WSN integration, IEEE Trans. Indus. Inf., 10, pp. 408-418, (2014); Zhou X., Long W., The research of network architecture in warehouse management system based on RFID and WSN integration, International Conference on Automation and Logistics, Qingdao, pp. 2556-2560, (2008); Jehng W.K., Peng S., Huang W.H., Using LabVIEW to integrate RFID system and database for supply chain efficiency improvement, Int. J. Intell. Control Syst., 13, pp. 189-195, (2008); Zhai C., Zou Z., Zhou Q., Mao J., Chen Q., Tenhunena H., Lirong Z., Xu L., A 2.4-GHz ISM RF and UWB Hybrid RFID Real-Time Locating System for Industrial Enterprise Internet of Things (IoT), Enterprise Inf. Syst., (2016); Liu C.M., Chen L.S., Applications of RFID technology for improving production efficiency in an integrated-circuit packaging house, Int. J. Prod. Res., 47, pp. 2203-2216, (2009); Liu G., Mao L., Chen L., Xie S., Locatable-body temperature monitoring based on semi-active UHF RFID tags, Sensors, 14, pp. 5952-5966, (2014); Lee S.G., de Souza R., Ong E.K., Simulation modelling of a narrow aisle automated storage and retrieval system (AS/RS) serviced by rail-guided vehicles, Comput. Indus., 30, pp. 241-253, (1996)","S. Alyahya; email: ece80469@myport.ac.uk",null,"Elsevier B.V.",{"$nulls":5},"2452414X",null,null,null,"English","J.  Ind. Infor. Integr.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85016106087"]
["Shang J.; Zhou J.; Li Y.","Shang, Jie (36443152100); Zhou, Jungang (57195155056); Li, Yan (57196300196)","36443152100; 57195155056; 57196300196","Research on the innovation of agricultural products circulation based on food safety coordination mechanism",2017.0,"Boletin Tecnico/Technical Bulletin",55.0,4.0,null,55.0,65.0,10.0,1.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85025816685&partnerID=40&md5=a34b0607b7a25b5e512d8879a8694f2f","Northeast Forestry University, School of Economics and Management, Harbin Heilongjiang, 150040, China; Harbin University of Commerce, School of Economics, Harbin, 150028, China","Shang J., Northeast Forestry University, School of Economics and Management, Harbin Heilongjiang, 150040, China; Zhou J., Northeast Forestry University, School of Economics and Management, Harbin Heilongjiang, 150040, China; Li Y., Harbin University of Commerce, School of Economics, Harbin, 150028, China","Agricultural products food safety and circulation affect and restraint each other. The nature and structure of agricultural production determines the choice of depth, breadth and mode of circulation of agricultural products, and the benefit mechanism of exchange relationship in the circulation guides the production of agricultural products. Auction, direct sales, forward transactions, adversaries and other price formation mechanism determines the main body and responsibility for food safety management. There are different food safety risks in the circulation patterns of agricultural products including peasant school docking, farmer docking, e-commerce and which are dominated by wholesale market or supermarkets, take the logistics center as the main body, lead enterprises as the core. From the commodity attribute of the agricultural product, the risk access point and the circulation mode the food safety coordination mode is divided into the administrative coordination mode, the organization coordination mode and the social coordination mode.","Benefit mechanism; Circulation mode; Circulation of agricultural products; Food safety","Agricultural products; Chemical contamination; Docking; Food safety; Safety engineering; Agricultural productions; Circulation mode; Circulation patterns; Coordination mechanisms; Coordination modes; Food safety management; Organization coordinations; Social coordination; Agriculture",{"$nulls":4},"Harbin University of Commerce; National Natural Science Foundation of China, NSFC, (70973016, 71573036); National Office for Philosophy and Social Sciences, NSSFC, (16BJY125)","This paper is supported by National Natural Science Foundation of China 71573036; 70973016, discipline construction project of Harbin University of Commerce: the optimization of the circulation system of agricultural products in Heilongjiang Province under the background of agricultural supply side reforms; National Social Science Fund Project: Study on Structure Optimization of China retailing and supply side reform based on Innovation, Item number 16BJY125.","Carlos Ms., Isengildina-Massa O., Lamie D., Zapata S., Does e -commerce help agricultural markets? the case of marketmaker, The Magazine of the Food, Farm, and Resource Issues, 28, 4, pp. 1-9, (2013); Wang C., Chen X., The cause of the agricultural product prices and the thoughts of the reform of the circulation study, China Soft Science, 2012, 4, pp. 11-17, (2012); Li C., Chongguang Li., Some thoughts of perfecting our country's agricultural product circulation system, Journal of Rural Economy, 2005, 3, pp. 16-18, (2005); Lin D., Ying Qu., Comparative study on food safety management system of China and the United States, Journal of Wuhan University of Technology, 6, pp. 154-158, (2004); Food Safety Working Group, Health, Environment and Development BBS (FORHEAD) : Food Safety in China -problems, Management and Research, 8, (2014); Meng G., Chunjie Qi., Cross of the spring festival. 2012. China's agricultural products circulation efficiency restriction factor and the breakthrough point, based on the perspective of supply chain theory, China's Circulation Economy, 2012, 11, pp. 43-47, (2012); Henderson J., Dooley F., Andersson C., Andersson O., Sealed bid auctions versus ascending the bid auctions: An experimental study rev, Journal of Planet Econ. Design, 3, 17, pp. 1-16, (2013); Zhuang J., Qunfeng huang. under the perspective of supply chain policy guidance for the construction of agricultural product circulation system in our country and realization model, Journal of Agricultural Economy, 6, pp. 98-102, (2009); Chen L., Agricultural enterprise development research, The Central Party School, 3, pp. 19-21, (2013); Xiao L., Circulation of green agricultural products supply chain model and operation process study, Journal of Technology Economy and Management Research, 2011, 11, pp. 109-112, (2011); Li L., Chongguang Li., Main problems and countermeasures of agricultural product circulation modernization with Chinese characteristics, China's Circulation Economy, 2012, 2, pp. 21-25, (2012); Cheng M.-H., Kang H.-H., Emerging markets finance and trade, Price -Formation Process of An Emerging Futures Market, 43, pp. 74-97, (2007); Gao M., The Chinese government food safety regulatory system problems and countermeasures, Journal of Reform and Openness, 1, (2012); Wang X., The socialist market economy under the background of the development of circulation industry research, literature review based on the current market and circulation modernization, China's Circulation Economy, 8, pp. 16-19, (2011); Chen X., The quality of the solid base of safety quickening construction of our country agricultural product quality safety credit system, Journal of Quality and Safety of Agricultural Products, 5, pp. 3-5, (2014); Zhao X., Wen Ke., Social construction of food safety problem analysis, from the methodology of scientism to the S&TS parse, Journal of Science and Society, 1, 2, pp. 92-102, (2012); Chen X., From the milk powder incident in fuyang analysis China's food safety regulatory system, Journal of Public Health of China, 20, 10, pp. 1262-1263, (2004); Zhou Y., Wang E., China's food safety regulation: An overall framework, Journal of Reform, 3, 4, pp. 19-27, (2013)","J. Shang; Northeast Forestry University, School of Economics and Management, Harbin Heilongjiang, 150040, China; email: hero1068@126.com",null,"Universidad Central de Venezuela",{"$nulls":5},"0376723X",null,null,null,"English","Boletin Tecnico","Article","Final",null,"Scopus","2-s2.0-85025816685"]
["Gorla N.; Chiravuri A.; Chinta R.","Gorla, Narasimhaiah (55956734100); Chiravuri, Ananth (7801313484); Chinta, Ravi (36711471200)","55956734100; 7801313484; 36711471200","Business-to-business e-commerce adoption: An empirical investigation of business factors",2017.0,"Information Systems Frontiers",19.0,3.0,null,645.0,667.0,22.0,26.0,"10.1007/s10796-015-9616-8","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85027894156&doi=10.1007%2fs10796-015-9616-8&partnerID=40&md5=5d83c52be95b336707d1057ce18cc82b","School of Business and Management, American University of Sharjah, PO Box 26666, Sharjah, United Arab Emirates; Department of Business Administration, College of Business and Economics, UAE University, PO Box 15551, Al Ain, United Arab Emirates; College of Business, University at Montgomery, Montgomery, AL, United States","Gorla N., School of Business and Management, American University of Sharjah, PO Box 26666, Sharjah, United Arab Emirates; Chiravuri A., Department of Business Administration, College of Business and Economics, UAE University, PO Box 15551, Al Ain, United Arab Emirates; Chinta R., College of Business, University at Montgomery, Montgomery, AL, United States","We develop an overarching model to explain the adoption of business-to-business e-commerce using five business factors: external environment, organizational context, decision-maker’s characteristics, technology context, and organizational learning. Data collected from IS executives was analyzed using logistic regression. Our model has a good fit with over 77 % variance explained. Findings indicate that the existence of informal interest groups, and the tolerant attitude of decision makers towards negative information about business-to-business e-commerce have significant influence on the adoption decision. In addition, our results indicate that price intensity and perceived barriers negatively affect the adoption decision. © 2015, Springer Science+Business Media New York.","B2B e-commerce adoption; Business factors; Business to Business (B2B); Electronic commerce; Information systems; IT adoption; Organizational adoption; Technology diffusion","Commerce; Decision making; Information systems; B2B e-commerce; Business to business; IT adoption; Organizational adoptions; Technology diffusion; Electronic commerce",{"$nulls":6},{"$cut":{"chars":21987,"head":"Abdul-Gader A.H., Kozar K.A., The impact of computer alienation on information technology investment decisions: an exploratory cross-national analysis, MIS Quarterly, 19, 4, pp. 535-559, (1995); Ahmad I., Agrawal A.M., Major impediments in the Growth of B2B E-Commerce market in Kuwait: an empirical study from industrial perspective, European Journal of Business and Management, 6, (2014); Ahmed M., Hussein R., Minakhatun R., Islam R., Building consumers’ confidence in adopting e-commerce: a Malaysian case, International Journal of Business and Systems Research, 1, 2, pp. 236-255, (2007); Alam S.S., Khatibi A., Ahmad M.I.S., Ismail H.B., Factors affecting e-commerce adoption in the electronic manufacturing companies in Malaysia, International Journal of Commerce and Management, 17, 1-2, pp. 129-139, (2007); Alsaad A.K.H., Mohamad R., Ismail N.A., The Moderating Role of Power Exercise in B2B E-commerce Adoption Decision, Procedia – Social and Behavioral Sciences, 130, pp. 515-523, (2014); Al-Somali S.A., Gholami R., Clegg B., Determinants of B2B e-commerce adoption in Saudi Arabian firms, International Journal of Digital Society (IJDS), 2, 2, (2011); Archer N., Wang S., Kang C., Barriers to the adoption of online supply chain solutions in small and medium enterprises, Supply Chain Management: An International Journal, 13, 1, pp. 73-82, (2008); Asher A., Developing a B2B E-Commerce implementation framework: a study of EDI implementation for procurement, Information Systems Management, 24, 4, pp. 373-390, (2007); Attewell P., Technology diffusion and organizational learning: the case of business computing, Organization Science, 3, 1, pp. 1-19, (1992); Awad N., Ragowsky A., Establishing trust in electronic commerce through online word of mouth: an examination across genders, Journal of Management Information Systems, 24, 4, pp. 101-121, (2008); Bajwa D.S., Lewis L.F., Does size matter? An investigation of collaborative information technology adoption by U.S. firms, Journal of Information Technology Theory and Application, 5, 1, (2003); Bakos J.P., A strategic analysis of electronic marketplaces, MIS Quarterly, 15, 3, pp. 295-310, (1991); Bala H., Venkatesh V., Assimilation of interorganizational business process standards, Information Systems Research, 18, 3, pp. 340-362, (2007); Barua A., Konana P., Whinston A.B., An empirical investigation of net enabled business value, MIS Quarterly, 28, 4, pp. 585-620, (2004); Baumeister R.F., Bratslavsky E., Finkenauer C., Vohs K.D., Bad is stronger than good, Review of General Psychology, 5, pp. 323-370, (2001); Beath C.M., Supporting the information technology champion, MIS Quarterly, 15, 3, pp. 355-374, (1991); Bharati P., Chaudhury A., Studying the current status of technology adoption, Communications of the ACM, 49, 10, (2006); Bhattacherjee A., Hikmet N., Menachemi N., Kayhan V.O., Brooks R.G., The differential performance effects of healthcare information technology adoption, Information Systems Management, 24, 1, pp. 5-14, (2007); Bigne-Alcaniz E., Aldas-Manzano J., Andreu-Simo L., Ruiz-Mafe C., Business-to-Business e-commerce adoption and perceived benefits: evidence from small and medium Spanish enterprises, International Journal of Electronic Business, 7, 6, pp. 599-624, (2009); Campbell D.T., Fiske D.W., Convergent and discriminate validation by the multi-trait multi-method matrix, Psychology Bulletin, 56, 1, pp. 81-150, (1959); Cao Q., Duan W., Gan Q., Exploring determinants of voting for the “helpfulness” of online user reviews: A text mining approach, Decision Support Systems, 50, pp. 511-521, (2011); Chad L., Yu-An H., Man-Shin C., Wo-Chung L., Effects of information technology maturity on the adoption of investment evaluation methodologies: a survey of large Australian organizations, International Journal of Management, 24, 4, pp. 697-711, (2007); Chang H.H., Wong K.H., Adoption of e-procurement and participation of e-marketplace on firm performance, Information and Management, 47, pp. 262-270, (2010); Chang H.-L., Easley R.F., Shaw M.J., Market model-based channel select"}},"A. Chiravuri; Department of Business Administration, College of Business and Economics, UAE University, Al Ain, PO Box 15551, United Arab Emirates; email: ananth.chiravuri@uaeu.ac.ae",null,"Springer New York LLC",{"$nulls":5},1.3873326E7,null,null,null,"English","Inf. Syst. Front.","Article","Final",null,"Scopus","2-s2.0-85027894156"]
["Ai W.; Yang J.; Wang L.","Ai, Weina (57191410022); Yang, Jianzheng (35732607200); Wang, Lin (57018379900)","57191410022; 35732607200; 57018379900","Revelation of cross-border logistics performance for the manufacturing industry development",2016.0,"International Journal of Mobile Communications",14.0,6.0,null,593.0,609.0,16.0,21.0,"10.1504/IJMC.2016.079302","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84989813671&doi=10.1504%2fIJMC.2016.079302&partnerID=40&md5=4c26dc2d1fe38b54e28070333a5e061c","Business School, University of Shanghai for Science and Technology, Jun Gong Road, Shanghai, 200093, China","Ai W., Business School, University of Shanghai for Science and Technology, Jun Gong Road, Shanghai, 200093, China; Yang J., Business School, University of Shanghai for Science and Technology, Jun Gong Road, Shanghai, 200093, China; Wang L., Business School, University of Shanghai for Science and Technology, Jun Gong Road, Shanghai, 200093, China","The rapid development of cross-border e-commerce is transforming and upgrading Chinese manufacturing industry. This paper uses the theory of two markets to build an integrated e-commerce logistics performance evaluation model. Data collected by the Ministry of Commerce's \"Cross-border e-commerce transactions specifications\" survey are used to analyze relevant factors in the manufacturing, circulation, service, and other industries. By comparing the above the logistics performance factors, this paper shows that cross-border payment is a bottleneck in developing cross-border e-commerce in the manufacturing industry, and the coordination between countries' legal systems affects the implementation of electronic customs clearance procedures. The problems in cross-border payment and regulatory coordination need to be solved before cross-border e-commerce can further develop in Chinese manufacturing industry. The research has more value on cross-border m-commerce, for its suggestions on cross-border e-commerce laws and technology applications will make great contribution to the application and future development of cross-border m-commerce. Copyright © 2016 Inderscience Enterprises Ltd.","Cross-Border E-Commerce; Cross-Border Logistics; Cross-Border M-Commerce; Cross-Border Payment; E-Commerce; Electronic Customs Clearance; Empirical Research; International Logistics; Legal Systems; Manufacturing; Regulatory Coordination; Structural Equation Model","Electronic commerce; Industrial research; International trade; Laws and legislation; Manufacture; Mobile commerce; Cross-border; Customs clearance; Empirical research; Legal system; M-commerce; Regulatory Coordination; Structural equation modeling; Commerce",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (70973079)","This work was supported by the National Natural Science Foundation of China under Grant No. 70973079","Aleksandar T., Jovanka B., Logistic services trade balance as indicator of Macedonian logistic industry potential original research article, Procedia-Social and Behavioral Sciences, 44, pp. 314-322, (2012); Cao C., 4G era of mobile e-commerce business model research, Business, 11, (2015); Cao Y., Lu Y., Gupta S., Yang S., The effects of differences between e-commerce and m-commerce on the consumers usage transfer from online to mobile channel, International Journal of Mobile Communications, 13, 1, pp. 51-70, (2015); The 35th China Internet Development Statistics Report, (2015); Du Y., Du J., Chen J., The quality measurement index system of the e-commerce, System Engineering Theory and Practice, 10, pp. 1870-1876, (2010); Feng Y., Yan C., Yang D., Zhang J., Identifications and regulations of money laundering in e-commerce environment based on the internet payment, System Engineering Theory and Practice, 12, pp. 60-69, (2008); Jane C., Evidence of payments for ecosystem services as a mechanism for supporting biodiversity conservation and rural livelihoods, Original Research Article Ecosystem Services, 1, pp. 39-43, (2014); Li J., Wu J., Zhang J., Ke L., The credit evaluation of the middle and small sized company in the background of e-commerce, System Engineering Theory and Practice, 3, pp. 555-560, (2012); Li L., Chai Y., Liu Y., Evolution mechanism modeling and economy analysis of e-commerce models, Journal of Tsinghua University (Natural Science Edition), 11, pp. 1524-1529, (2012); Li Q., Zhao K., Zhang W., Li P., The operation mechanism analysis of the cheat in the third-hand platform transactions in the perspective of e-commerce chains, Management Modernization, 2, pp. 96-98, (2014); Li W., Ping L., Chen X., Wu Z., Based on the Dirichlet distribution model fits the e-commerce reputation theory, Journal of UEST of China, 5, pp. 737-741, (2011); E-commerce Report of China 2013, pp. 1-4, (2014); Musa A., Khan H., Alshare K., Factors influence consumers adoption of mobile payment devices in Qatar, International Journal of Mobile Communications, 13, 6, pp. 670-689, (2015); E-commerce Report of Shanghai 2013, pp. 6-12, (2014); Teo A., Tan G., Ooi K., Lin B., Why consumers adopt mobile payment? A partial least squares structural equation modelling (PLS-SEM) approach, International Journal of Mobile Communications, 13, 5, pp. 478-497, (2015); Wang H., The Liner and the Nonlinear Method of the Partial Least Square, pp. 24-27, (2006); Wang L., Yang J., Analysis of influencing factors of international logistics performance, China Business and Market, 5, pp. 50-55, (2014); Wu M., Constructional Formula Models: Methods and Applications, pp. 15-18, (2010); Yang J., Yang L., The Foundation and the Application of Electronic Commerce, pp. 12-13, (2013); Yoris A., Robert J., The economics of mobile payments: Understanding stakeholder issues for an emerging financial technology application original research article, Electronic Commerce Research and Applications, 7, 2, pp. 141-164, (2008); Yu L., E-commerce credit risk early warning based on least square approximate support vector regression model, System Engineering Theory and Practice, 3, pp. 508-514, (2012); Zhu J., WTO \"cases of measures of e-commerce payment\" and the influencing analysis of its affection to Chinese financial services industry, International Trading, 9, pp. 52-58, (2013)","W. Ai; Business School, University of Shanghai for Science and Technology, Shanghai, Jun Gong Road, 200093, China; email: aiweina2000@163.com",null,"Inderscience Enterprises Ltd.",{"$nulls":5},"1470949X",null,null,null,"English","Int. J. Mobile Commun.","Article","Final",null,"Scopus","2-s2.0-84989813671"]
["Reyes-Mercado P.; Karthik M.; Mishra R.K.; Rajagopal","Reyes-Mercado, Pável (56102632600); Karthik, M. (57212223156); Mishra, Ram Kumar (56221649900); Rajagopal (23025659500)","56102632600; 57212223156; 56221649900; 23025659500","Drivers of consumer attitudes towards online shopping in the Indian market: Analysis through an extended TAM model",2017.0,"International Journal of Business Innovation and Research",13.0,3.0,null,326.0,343.0,17.0,2.0,"10.1504/IJBIR.2017.084425","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85116047714&doi=10.1504%2fIJBIR.2017.084425&partnerID=40&md5=91eda1b5b3c4891320f7c74c1888c78f","Department of Doctoral Studies in Management Sciences, EGADE Business School, ITESM, Calle del Puente 222, Col. Ejidos de Huipulco, Distrito Federal, Delegación Tlalpan, C.P. 14380, Mexico; Institute of Public Enterprise, Shamirpet (V&M), Survey No. 1266, Rangareddy Dist, Telangana, Hyderabad, 500 101, India","Reyes-Mercado P., Department of Doctoral Studies in Management Sciences, EGADE Business School, ITESM, Calle del Puente 222, Col. Ejidos de Huipulco, Distrito Federal, Delegación Tlalpan, C.P. 14380, Mexico; Karthik M., Institute of Public Enterprise, Shamirpet (V&M), Survey No. 1266, Rangareddy Dist, Telangana, Hyderabad, 500 101, India; Mishra R.K., Institute of Public Enterprise, Shamirpet (V&M), Survey No. 1266, Rangareddy Dist, Telangana, Hyderabad, 500 101, India; Rajagopal, Department of Doctoral Studies in Management Sciences, EGADE Business School, ITESM, Calle del Puente 222, Col. Ejidos de Huipulco, Distrito Federal, Delegación Tlalpan, C.P. 14380, Mexico","The diffusion of the internet has changed advertising, sales, and delivery channels in the retailing industry. Currently, e-commerce industry in India is investing high amounts of money to increase its sales capabilities to perform a wider range of transactions. The main feature of online retailing is the convenience of shopping at any time and receiving the purchased items instead of approaching a physical store. There is a need to analyse consumer's attitudes towards shopping products online in order to gain competitive advantage in the India context which has an 11% of internet penetration. This research proposes a conceptual framework to explore trust, social influence, and digital literacy in forming consumer's intentions to shop online by extending the technology adoption model (TAM). On the basis of 123 collected observations and the analytical technique of partial least squares, this study finds that trust has a strong influence on formation of consumer attitudes and perceived usefulness is a core belief that also influences further attitudes and intentions to shop online. Implications for managers and researchers are discussed. Copyright © 2017 Inderscience Enterprises Ltd.","Consumer behaviour; India; Online retailing; Technology adoption",{"$nulls":7},"Ajzen I., The theory of planned behaviour, Organizational Behavior and Human Decision Processes, 50, 2, pp. 179-211, (1991); Ali S.S., Kaur R., An empirical approach to customer perception of mobile banking in Indian scenario, International Journal of Business Innovation and Research, 9, 3, pp. 272-294, (2015); Al-Somali S.A., Gholami R., Clegg B., An investigation into the acceptance of online banking in Saudi Arabia, Technovation, 29, 2, pp. 130-141, (2009); Bagozzi R.P., The legacy of the technology acceptance model and a proposal for a paradigm shift, Journal of the Association for Information Systems, 8, 4, pp. 243-254, (2007); Bagozzi R.P., Yi Y., On the evaluation of structural equation models, Journal of the Academy of Marketing Science, 16, 1, pp. 74-94, (1988); Bandura A., Self-efficacy: toward a unifying theory of behavioral change, Psychological Review, 84, 2, pp. 191-215, (1977); 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Davis F.D., Perceived usefulness, perceived ease of use, and user acceptance of information technology, MIS Quarterly, 13, 3, pp. 319-340, (1989); Davis F.D., Bagozzi R.P., Warshaw P.R., User acceptance of computer technology: a comparison of two theoretical models, Management Science, 35, 8, pp. 982-1003, (1989); Eastin M.S., LaRose R., Internet self-efficacy and the psychology of the digital divide, Journal of Computer-Mediated Communication, 6, 1, (2006); Fishbein M., Ajzen I., Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research, (1975); Fornell C., Larcker D.F., Evaluating structural equation models with unobservable variables and measurement error, Journal of Marketing Research, 18, 1, pp. 39-50, (1981); Ganguly B., Dash S.B., Cyr D., Head M., The effects of website design on purchase intention in online shopping: the mediating role of trust and the moderating role of culture, International Journal of Electronic Business, 8, 4, pp. 302-330, (2010); Ghosh A., Ghosh A., Traditional buying to online buying: a study of the paradigm shift in consumer buying behavior, Asian Journal of Management, 5, 2, pp. 113-116, (2014); Gomez-Barroso J.L., Marban-Flores R., Simple mobile banking: learning from developing countries, International Journal of Business Innovation and Research, 8, 5, pp. 485-497, (2014); Ha S., Stoel L., Consumer e-shopping acceptance: antecedents in a technology acceptance model, Journal of Business Research, 62, 5, pp. 565-571, (2009); Hair J.F., Black W.C., Babin B.J., Anderson R.E., Multivariate Data Analysis, (2010); Hsu M.H., Chiu C.M., Internet self-efficacy and electronic service acceptance, Decision Support Systems, 38, 3, pp. 369-381, (2004); Hulland J., Use of partial least squares (PLS) in strategic management research: a review of four recent studies, Strategic Management Journal, 20, 2, pp. 195-204, (1999); Israel G.D., Combining mail and e-mail contacts to facilitate participation in mixed-mode surveys, Social Science Computer Review, 31, 3, pp. 346-358, (2012); Jarvis C.B., MacKenzie S.B., Podsakoff P.M., A critical review of construct indicators and measurement model misspecification in marketing and consumer research, Journal of Consumer Research, 30, 2, pp. 199-218, (2003); Jiang L., Yang Z., Jun M., Measuring consumer perceptions of online shopping convenience, Journal of Service Management, 24, 2, pp. 191-214, (2013); Kesharwani A., Singh S., The impact of trust and perceived risk on internet banking adoption in India: an extension of technology acceptance model, International Journal of Bank Marketing, 30, 4, pp. 303-322, (2012); Kim S., Eastin M.S., Hedonic tendencies and the online consumer: an investigation of the online shopping process, Journal of Internet Commerce, 10, 1, pp. 68-90, (2011); King W.R., He J., A meta-analysis of the technology acceptance model, Information and Management, 43, 6, pp. 740-755, (2006); Li P., Xie W., A strategic framework for determining e-commerce adoption, Journal of Technology Management in China, 7, 1, pp. 22-35, (2012); Ling K.C., Chai L.T., Piew T.H., The effects of shopping orientations, online trust and prior online purchase experience toward customers' online purchase intention, International Business Research, 3, 3, pp. 63-76, (2010); Nunnally J.C., Berstein I., Psychometric Theory, (1994); Ringle C.M., Wende S., Becker J.M., SmartPLS 3, (2015); Sahney S., Ghosh K., Shrivastava A., Conceptualizing consumer 'trust' in online buying behaviour: an empirical inquiry and model development in Indian context, Journal of Asia Business Studies, 7, 3, pp. 278-298, (2013); Schierz P.G., Schilke O., Wirtz B.W., Understanding consumer acceptance of mobile payment services: an empirical analysis, Electronic Commerce Research and Applications, 9, 3, pp. 209-216, (2010); Retail E-Commerce Sales in India from 2012 to 2017, (2014); Venkatesh V., Morris M.G., Davis G.B., Davis F.D., User acceptance of information technology: toward a unified view, MIS Quarterly, 27, 3, pp. 425-478, (2003); Wang Y.S., Wang Y.M., Lin H.H., Tang T.I., Determinants of user acceptance of internet banking: an empirical study, International Journal of Service Industry Management, 14, 5, pp. 501-519, (2003); Wu L., The antecedents of customer satisfaction and its link to complaint intentions in online shopping: an integration of justice, technology, and trust, International Journal of Information Management, 33, 1, pp. 166-176, (2013)","P. Reyes-Mercado; Department of Doctoral Studies in Management Sciences, EGADE Business School, ITESM, Delegación Tlalpan, Calle del Puente 222, Col. Ejidos de Huipulco, Distrito Federal, C.P. 14380, Mexico; email: pavelreyesmercado@hotmail.com",null,"Inderscience Publishers",{"$nulls":5},1.7510252E7,null,null,null,"English","Int. J. Bus. Innov. Res.","Article","Final",null,"Scopus","2-s2.0-85116047714"]
["Wang W.","Wang, Wenjuan (57215072968)",5.7215072968E10,"Decision model of returns logistics under Multinomial Logit Model considering the customer behavior",2016.0,"ICIC Express Letters",10.0,7.0,null,1575.0,1580.0,5.0,0.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-84976638395&partnerID=40&md5=c20f8f0819a8ea7bc2ebb68dc44dd561","School of Management Science and Engineering, Dongbei University of Finance and Economics, No. 217, Jianshan St., Shahekou District, Dalian, 116025, China","Wang W., School of Management Science and Engineering, Dongbei University of Finance and Economics, No. 217, Jianshan St., Shahekou District, Dalian, 116025, China","In this paper a model is presented that locates the decision method. We consider a decision optimization problem where a logistics enterprise chooses whether to accept the returns logistics requirement of the customer. This model will support future decision making protocols. Random utility theory assigns utility to each returns activity of the system with the waiting time of the customer and the extra time of the logistics vehicle. The paper presents a methodology to determine the most suitable period to accept the customer’s demand. At last, a case study is given. This will provide reference for decision-making when they improve the quality of work in Systems Engineering. © 2016, ICIC Express Letters Office. All rights reserved.","Customer behavior; E-commerce; Multinomial Logit Model; Random utility theory; Returns logistics","Decision making; Electronic commerce; Optimization; Customer behavior; Decision method; Decision modeling; Logistics enterprise; Logistics vehicles; Multinomial logit model; Optimization problems; Random utility theory; Sales",{"$nulls":6},"Murphy P.R., Poist R.P., Managing of logistics retro movements: An empirical analysis of literature suggestions, Transp. Res. Forum, 29, 1, pp. 177-184, (1989); Carter C.R., Ellram L.M., Reverse logistics: A review of the literature and framework for future investigation, J. Bus Logist., 19, 1, pp. 85-102, (1998); Rogers D.S., Tibben-Lembke R., Going Backwards: Reverse Logistics Trends and Practices, (1999); Stock J.R., Development and Implementation of Reverse Logistics Program, (1998); Srivastava S., Network design for reverse logistics, Omega, 36, 4, pp. 535-548, (2008); Kannan G., Palaniappan M., Zhu Q., Kannan D., Analysis of third party reverse logistics provider using interpretive structural modeling, Int. J. Prod. Res., 140, 1, pp. 204-211, (2012); Agrawal S., Singh R.K., Murtaza Q., A literature review and perspectives in reverse logistics resources, Conservation and Recycling, 97, pp. 76-92, (2015); Autry C.W., Formalization of reverse logistics programs: A strategy for managing liberalized returns, Industrial Marketing Management, 34, 7, pp. 749-757, (2005); Wang W., Ding Q., Disruption measurement model based on behavior of passengers in ferry passenger system, ICIC Express Letters, 9, 4, pp. 1115-1119, (2015); Ding Q., A model of disruption management with human behavior in logistics distribution, ICIC Express Letters, Part B: Applications, 4, 4, pp. 991-998, (2013); Wang W., Hu X., Wu L., Et al., A simulation optimization approach to campus bus routing with diversion, The 4Th International Conference on Innovative Computing, Information and Control, pp. 713-716, (2009); Waddell P., Accessibility and residential location: The interaction of workplace, residential mobility, tenure, and location choices, The Lincoln Land Institute TRED Conference, (1996); Guo J., Bhat C., Residential Location Choice Modeling: Accommodating Sociodemographic, (2001); Ibeas .A., Cordera R., Dell'Olio L., Coppola P., Modelling the spatial interactions between workplace and residential location, Transportation Research Part A: Policy and Practice, 49, pp. 110-122, (2013); Sando R., Bordagaray M., Dell'Olio L., Ibeas A., Discrete choice models to determine high-speed passenger stop under emergency conditions, Transportation Research Procedia, 3, pp. 234-240, (2014); Mohammadian A., Kanaroglou P., Applications of spatial multinomial logit model to transportation planning, The 10Th International Conference on Travel Behaviour Research, (2003); Domencich T.A., McFadden D., Urban Travel Demand: A Behavioral Analysis: A Charles River Associates Research Study, (1975); Ben-Akiva M.E., Lerman S.R., Discrete Choice Analysis: Theory and Application to Travel Demand, (1985); Breslow N.E., Clayton D.G., Approximate inference in generalized linear mixed models, Journal of the American Statistical Association, 88, pp. 9-25, (1993); Chen Z., Kuo L., A note on the estimation of multinomial logit models with random effects, The American Statistician, 55, pp. 89-95, (2001)","W. Wang; School of Management Science and Engineering, Dongbei University of Finance and Economics, Dalian, No. 217, Jianshan St., Shahekou District, 116025, China; email: Wangwenjuan.cn@163.com",null,"ICIC Express Letters Office",{"$nulls":5},"1881803X",null,null,null,"English","ICIC Express Lett.","Article","Final",null,"Scopus","2-s2.0-84976638395"]
["Tandon U.; Kiran R.; Sah A.N.","Tandon, Urvashi (57190029593); Kiran, Ravi (22985431500); Sah, Ash N. (57190030141)","57190029593; 22985431500; 57190030141","Understanding barriers and drivers to online shopping: An emerging economy case",2017.0,"International Journal of Electronic Business",13.0,"2024-03-02",null,216.0,243.0,27.0,2.0,"10.1504/IJEB.2017.083326","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85115991003&doi=10.1504%2fIJEB.2017.083326&partnerID=40&md5=8cfd33559eee90bd1a7bf59195e5ebf2","School of Humanities and Social Sciences (SHSS), Thapar University, P.O. Box 32, Patiala, 147004, India","Tandon U., School of Humanities and Social Sciences (SHSS), Thapar University, P.O. Box 32, Patiala, 147004, India; Kiran R., School of Humanities and Social Sciences (SHSS), Thapar University, P.O. Box 32, Patiala, 147004, India; Sah A.N., School of Humanities and Social Sciences (SHSS), Thapar University, P.O. Box 32, Patiala, 147004, India","The purpose of this paper is to empirically analyse the barriers and drivers towards online shopping in India. Data was collected from 410 online shoppers from the North Indian States of India. The results of the study reveal significant relation of security and privacy protection measure, time performance, ease of use, website design, ease of understanding, perceived risk, delivery procedures, the risk of losing personal and financial information, technology ignorance factor, and Lack of touch and feel with Intention to buy. This is one of the initial studies dealing with barriers and drivers to online shopping and their relation with the intention to shop online. Items like slow internet speed, inapt query handling and intention to buy with cash-on-delivery have also been included into the study. This paper builds the foundations for researchers to extend online retailing research in developing countries like India where switch over to internet shopping is much later than developing countries. Copyright © 2017 Inderscience Enterprises Ltd.","Barriers; Consumer behaviour; Drivers; India; Internet retailing; Online shopping","Developing countries; Privacy by design; Risk assessment; Cash-on-delivery; Emerging economies; Financial information; Intention to buies; Internet shopping; Online retailing; Online shoppers; Security and privacy protection; Electronic commerce",{"$nulls":6},{"$cut":{"chars":18070,"head":"Ajzen I., The theory of planned behavior, Organizational Behavior and Human Decision Processes, 50, 11, pp. 179-211, (1991); Al-Maghrabi T., Dennis C., What drives consumers' continuance intention to e-shopping? Conceptual framework and managerial implications in case of Saudi Arabia, International Journal of Retail and Distribution Management, 39, 12, pp. 899-926, (2011); Alreck P.L., DiBartolo G.R., Diriker M., Dover H.F., Passyn K.A., Settle R.B., Time pressure, time saving and online shopping: exploring a contradiction, The Journal of Applied Business Research, 25, 5, pp. 85-92, (2009); Bansal H.S., Mc Dougall G.H.G., Dikolli S.S., Sedatole K.L., Relating e-satisfaction to behavioural outcomes; an empirical study, Journal of Services Marketing, 18, 4, pp. 290-302, (2004); Bhattacherjee A., Understanding information systems continuance: an expectation-confirmation model, MIS Quarterly, 25, 3, pp. 351-370, (2001); Bisen A., Singh P., E-tailing in India; Unlocking the Potential, pp. 5-20, (2013); Casalo L., Flavian C., Guinaliu M., The role of perceived usability, reputation, satisfaction and consumer familiarity on website loyalty formation process, Computers in Human Behaviour, 24, 2, pp. 325-345, (2008); Chaing K.P., Dholakia R.R., Factors driving consumer intention to shop online: an empirical investigation, Journal of Consumer Psychology, 13, 1-2, pp. 177-183, (2003); Chattaraman V., Kwon W-S., Gilbert J.E., Virtual agents in retail websites; benefits of stimulated social interaction for older users, Computers in Human Behaviour, 28, 6, pp. 2055-2066, (2012); Chen H.Y., Hsu C.I., Lin C.C., Website attributes that increase consumer purchase intention: a conjoint analysis, Journal of Business Research, 63, 9-10, pp. 1007-1014, (2010); Chiejina C., Olamide S.E., Investigating the significance of the 'pay on delivery' option in emerging prosperity of the Nigerian e-commerce sector, Journal of Marketing and Management, 5, 1, pp. 120-135, (2014); Chiu C.M., Wang E.T.G., Fang Y.H., Huang H.Y., Understanding customers' repeat purchase intentions in B2C e-commerce: the roles of utilitarian value, hedonic value and perceived risk, Information Systems Journal, 24, 7, pp. 85-114, (2012); Colla E., Lapoule P., E-commerce: exploring the critical success factors, International Journal of Retail and Distribution Management, 40, 11, pp. 842-864, (2012); Dash S.B., Saji K.B., Role of self-efficacy and website social-presence in customers' adoption of B2C online shopping: an empirical study in the Indian context, Journal of International Consumer Marketing, 20, 2, pp. 33-48, (2007); Dash A., Online shopping and customer satisfaction: an empirical investigation, International Journal of Research in Management, Economics and Commerce, 2, 11, pp. 42-49, (2012); Davis F.D., Perceived usefulness, perceived ease of use and user acceptance of information technology, MIS Quarterly, 13, 3, pp. 319-339, (1989); Dawn S.K., Kar U., E-tailing in India- its issues, opportunities and effective strategies for growth and development, International Journal of Multidisciplinary Research, 1, 3, pp. 101-115, (2011); Demangeot C., Broderick A.J., Consumer perceptions of online shopping environments: a Gestalt approach, Psychology and Marketing, 27, 2, pp. 117-140, (2010); Devraj S., Fan M., Kohli R., Antecedents of B2C channel satisfaction and preference: validating e-commerce metrics, Information Systems Research, 13, 3, pp. 16-33, (2002); Dholakia R.R., Zhao M., Effects of online store attributes on customer satisfaction and repurchase intentions, International Journal of Retail and Distribution Management, 38, 7, pp. 482-496, (2010); Doherty N.F., Ellis-Chadwick E., New perspectives in internet retailing: a review and strategic critique of the field, International Journal of Retail and Distribution Management, 34, 4-5, pp. 411-428, (2006); Faqih K.M.S., An empirical analysis of factors predicting the behavioral intention to adopt Internet shopping technology among non-shoppers in a developing country context: Does gender matter?, Journal of Retailing a"}},"U. Tandon; School of Humanities and Social Sciences (SHSS), Thapar University, Patiala, P.O. Box 32, 147004, India; email: urvashiguptav@gmail.com",null,"Inderscience Publishers",{"$nulls":5},1.4706067E7,null,null,null,"English","Int. J. Electron. Bus.","Article","Final",null,"Scopus","2-s2.0-85115991003"]
["Chang J.-J.; Peng Z.-R.; Sun J.","Chang, Jing-Jing (55899513500); Peng, Zhong-Ren (7401791063); Sun, Jian (55242813700)","55899513500; 7401791063; 55242813700","Freight vehicle routing optimization for sporadic orders using floating car data",2013.0,"Journal of Donghua University (English Edition)",30.0,2.0,null,96.0,102.0,6.0,1.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-84886255527&partnerID=40&md5=5014ba07d2ba0028fe3ee1db269c6556","Center for ITS and UAV Applications Research, Shanghai Jiaotong University, Shanghai 200240, China; Department of Urban and Regional Planning, University of Florida, Gainesville 115706, United States","Chang J.-J., Center for ITS and UAV Applications Research, Shanghai Jiaotong University, Shanghai 200240, China; Peng Z.-R., Center for ITS and UAV Applications Research, Shanghai Jiaotong University, Shanghai 200240, China, Department of Urban and Regional Planning, University of Florida, Gainesville 115706, United States; Sun J., Center for ITS and UAV Applications Research, Shanghai Jiaotong University, Shanghai 200240, China","The increasing popularity of e-commerce brings large volumes of sporadic orders from different customers, which have to be handled by freight trucks and distribution centers. To improve the level of service and reduce the total shipping cost as well as traffic congestions in urban area, flexible methods and optimal vehicle routing strategies should be adopted to improve the efficiency of distribution effort. An optimization solution for vehicle routing and scheduling problem with time window for sporadic orders (VRPTW-S) was provided based on time-dependent travel time extracted from floating car data (FCD) with ArcGIS platform. A VRPTW-S model derived from the traditional vehicle routing problem was proposed, in which uncertainty of customer orders and travel time were considered. Based on this model, an advanced vehicle routing algorithm was designed to solve the problem. A case study of Shenzhen, Guangdong province, China, was conducted to demonstrate the vehicle operation flow, in which process of FCD and efficiency of delivery systems under different situations were discussed. The final results demonstrated a good performance of application of time-dependent travel time information using FCD in solving vehicle routing problems. Copyright © 2013 Editorial Department of Journal of Donghua University.","ArcGIS; Floating car data (FCD); Freight routing and scheduling; Sporadic order; Time-dependent travel time","Efficiency; Problem solving; Scheduling; Traffic congestion; Travel time; Vehicles; ArcGIS; Floating car data; Routing and scheduling; Sporadic order; Time dependent; Vehicle routing",{"$nulls":6},"Taniguchi E., Heijden R., An evaluation methodology for city logistics, Transport Reviews, 20, 1, pp. 65-90, (2000); Ando N., Taniguchi E., Travel time reliability in vehicle routing and scheduling with time windows, Networks and Spatial Economics, 6, 3-4, pp. 293-311, (2006); Directive of the european parliament and of the council, (2010); Schafer R., Thiessenhusen K., Wagner P., A traffic information system by means of real-time floating car data, For Presentation at the 9th World Congress on Intelligent Transportation System, (2002); Dowling R.G., Cheng W.W.K., Evaluation of speed measurement and prediction techniques for signalized arterials, Transportation Research Record: Journal of the Transportation Research Board, 1564, pp. 20-29, (1996); Fabritiis C., Ragona R., Valenti G., Traffic estimation and prediction based on real time floating car data, Proceeding of the 11th International IEEE Conference on Intelligent Transportation System, pp. 197-203, (2008); Wang H.D., Zou H.X., Yue Y., Et al., Visualizing hot spot analysis result based on mashup, Proceedings of the 2009 International Workshop on Location Based Social Networks, pp. 45-48, (2009); Song G.H., Yu L., Estimation of fuel efficiency of road traffic by characterization of vehicle-specific power and speed based on floating car data, Transportation Research Record: Journal of the Transportation Research Board, 2139, pp. 11-20, (2009); Ertugay K., Duzgun S., GIS-based stochastic modeling of physical accessibility using GPS-based floating car data and monte carlo simulation, International Journal of Geographical Information Science, 25, 9, pp. 1491-1506, (2011); Pilli-Sihvola Y., Floating car road weather information monitoring system, Transportation Research Record: Journal of the Transportation Research Board, 1741, pp. 3-5, (2004); Quayle S., Koonce P., DePencier D., Et al., Arterial performance measures with media access control readers, Transportation Research Record: Journal of the Transportation Research Board, 2192, pp. 185-193, (2010); Brockfeld E., Lorkowski S., Mieth P., Et al., Benefits and limits of recent floating car data technology - An evaluation study, For Presentation at the 11th WCTR Conference, (2007); Yue Y., Zou H.X., Li Q.Q., Urban road travel speed estimation based on low sampling floating car data, Proceeding of the 9th International Conference of Chinese Transportation Professionals, pp. 1719-1725, (2009); Loustau P., Morency C., Trepanier M., Et al., Travel time reliability on a highway network: Estimations using floating car data, Transportation Research Record: Journal of the Transportation Research Board, 2, 1, pp. 27-37, (2010); Simroth A., Zahle H., Travel time prediction using floating car data applied to logistics planning, IEEE Transactions on Intelligent Transportation Systems, 12, 1, pp. 243-253, (2011); Ehmake J.F., Meisel S., Mattfeld D.C., Floating car based travel times for city logistics, Transportation Research Part C: Emerging Technologies, 21, 1, pp. 338-352, (2012); Shieh H.M., May M., On-line vehicle routing with time windows: Optimization-based heuristics approach for freight demands requested in real-time, Transportation Research Record: Journal of the Transportation Research Board, 1617, pp. 171-180, (1998); Jung S., Haghani A., Genetic algorithm for the time-dependent vehicle routing problem, Transportation Research Record: Journal of the Transportation Research Board, 1771, pp. 164-171, (2001); Liao T.Y., Tabu search algorithm for dynamic vehicle routing problems under real-time information, Transportation Research Record: Journal of the Transportation Research Board, 1882, pp. 140-149, (2004); Hu T.Y., Evaluation framework for dynamic vehicle routing strategies under real-time information, Transportation Research Record: Journal of the Transportation Research Board, 1774, pp. 115-122, (2001); Tang H., Efficient implementation of improvement procedures for vehicle routing with time-dependent travel times, Transportation Research Record: Journal of the Transportation Research Board, 2089, pp. 66-75, (2008); Thompson R.G., Taniguchi E., Yamada T., Estimating the benefits of considering travel time variability in urban distribution, Transportation Research Record: Journal of the Transportation Research Board, 2238, pp. 86-96, (2011); Liu H.X., Recker W., Chen A., Uncovering the contribution of travel time reliability to dynamic route choice using real-time loop data, Transportation Research Part A: Policy and Practice, 38, 6, pp. 435-453, (2004)","J. Sun; Center for ITS and UAV Applications Research, Shanghai Jiaotong University, Shanghai 200240, China; email: danielsun@sjtu.edu.cn",null,"Editorial Board of Journal of Dong Hua University",{"$nulls":5},1.672522E7,null,null,null,"English","J. Donghua Univ.","Article","Final",null,"Scopus","2-s2.0-84886255527"]
["Masmoudi M.; Benaissa M.; Chabchoub H.","Masmoudi, Mariem (57206424456); Benaissa, Mounir (15219785300); Chabchoub, Habib (56007650900)","57206424456; 15219785300; 56007650900","Optimisation of e-commerce logistics distribution system: Problem modelling and exact resolution",2014.0,"International Journal of Business Performance and Supply Chain Modelling",6.0,"2024-04-03",null,358.0,375.0,17.0,11.0,"10.1504/IJBPSCM.2014.065275","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84992646896&doi=10.1504%2fIJBPSCM.2014.065275&partnerID=40&md5=f7583146e71ed300a9b9c6a69c70125b","LOGIQ Research Unit, Higher Institute of Industrial Management of Sfax, Cité El Ons Km 11 Road Tunis Technopole BP, Sfax, 1164 - 3021, Tunisia; OASIS Laboratory, National Engineering School of Tunis, BP 37, Le belvédère, Tunis, 1002, Tunisia; MODEOR Laboratory, Institute of Business Studies of Sfax, Road Sidi Mansour Km 10 BP, Sfax, 43 - 3061, Tunisia","Masmoudi M., LOGIQ Research Unit, Higher Institute of Industrial Management of Sfax, Cité El Ons Km 11 Road Tunis Technopole BP, Sfax, 1164 - 3021, Tunisia; Benaissa M., OASIS Laboratory, National Engineering School of Tunis, BP 37, Le belvédère, Tunis, 1002, Tunisia; Chabchoub H., MODEOR Laboratory, Institute of Business Studies of Sfax, Road Sidi Mansour Km 10 BP, Sfax, 43 - 3061, Tunisia","In order to provide a decision support tool for home deliveries planning to e-commerce websites, four variants of the VRP have been combined into a single called load specific of multiple products types within heterogeneous fixed fleet vehicle routing and scheduling problem with time windows (LS-MPT-HFFVRSPTW). This problem includes constraints that can be observed in the electronic commerce environment. This paper to consider multiple types of products and vehicles, transport conditions and time windows. The main new idea is to assure compatibility between product type and vehicle type in order to satisfy required transport conditions. Mathematically this problem is formulated as a mixed integer linear programme. The formulation has been validated by tests on instances that bring the basic model of HVRPTW. New instances were built and optimal solutions have been provided by the CPLEX solver. In the future, this base of optimal solutions can be used for comparison with other approximate solutions. Copyright © 2014 Inderscience Enterprises Ltd.","Compatibility; CPLEX; E-commerce logistics distribution; Exact resolution; Mathematical model; Multiple products type; Transport conditions; VRP",{"$nulls":7},"Choia E., Tchab D., A column generation approach to the heterogeneous fleet vehicle routing problem, Computers and Operations Research, 34, 7, pp. 2080-2095, (2007); Descours T., Interview with Thomas DESCOURS, Supply Chain Director-unique.com Sale, (2013); Eksioglu B., Vural A.V., Reisman A., The vehicle routing problem: A taxonomic review, Computers and Industrial Engineering, 57, 4, pp. 1472-1483, (2009); Fallahi A., Prins C., Calvo R.W., A mimetic algorithm and a tabu search for the multi compartment vehicle routing problem, Computers and Operations Research, 35, 5, pp. 1725-1741, (2008); Gregory P., New planning benchmarks: Vehicle routing problem variants, 28th Workshop of the UK Planning and Scheduling Special Interest Group Jointly with the 4th Italian Workshop on Planning and Scheduling, (2010); Joseph G., Et al., Applications of Supply Chain Management and E-Commerce Research (Applied Optimization), (2010); Kamarainen V., The Impact of Investments on E-Grocery Logistics Operations, (2003); Kumar M.K.S., Anil B., Fleet optimization of single depot multi product VRP under stochastic environment, Proceedings of 10th National Conference on Technological Trends, pp. 12-16, (2009); Li F., Golden B., Wasilc E., A record-to-record travel algorithm for solving the heterogeneous fleet vehicle routing problem, Computers and Operations Research, 34, 9, pp. 2734-2742, (2007); Mahdavi A.V., Sadeghi S.A., Ostadali Makhmalbaf M.R., A stochastic hybrid algorithm for multi-depot and multi-product routing problem with heterogeneous vehicles, Journal of American Science, 7, 9, pp. 1006-1015, (2011); Masmoudi M., Benaissa M., Chabchoub H., Mathematical modeling for a rich vehicle routing problem in e-commerce logistics distribution, Proceedings of International Conference on Advanced Logistics and Transport, ICALT'2013, pp. 290-295, (2013); Melechovsky J., Evolutionary local search algorithm to solve the multi-compartment vehicle routing problem with time windows, Proceedings of 30th International Conference Mathematical Methods in Economics, pp. 564-568, (2012); Panicker V.V., Sridharan R., Modelling supply chain decision problem with fixed charge - A review, International Journal of Business Performance and Supply Chain Modelling, 3, 3, pp. 195-207, (2011); Prins C., Two memetic algorithms for heterogeneous fleet vehicle routing problems, Engineering Applications of Artificial Intelligence, 22, 6, pp. 916-928, (2009); Repoussis P.P., Tarantilis C.D., Ioannou G., A hybrid metaheuristic for a real life vehicle routing problem, Numerical Methods and Applications, Lecture Notes in Computer Science, pp. 247-254, (2007); Savelsbergh M., Sol M., Drive: Dynamic routing of independent vehicles, Operations Research, 46, 4, pp. 474-490, (1998); Schmid V., Doerner K.F., Laporte G., Rich routing problems arising in supply chain management, European Journal of Operational Research, 224, 3, pp. 435-448, (2013); Solomon M.M., Desrosiers J., Time window constrained routing and scheduling problems, Transportation Science, 22, 1, pp. 1-13, (1988); Tarantilisa C.D., Kiranoudisa C.T., Vassiliadis V.S., A threshold accepting metaheuristic for the heterogeneous fixed fleet vehicle routing problem, European Journal of Operational Research, 152, 1, pp. 148-158, (2004); Timon C.D., Eldon Y.L., Defrose C., Dynamic vehicle routing for online B2C delivery, The International Journal of Management Science, 33, 1, pp. 33-45, (2005); Ying X., Colin A., Information technologies in retail supply chains: A comparison of Tesco and Asda, International Journal of Business Performance and Supply Chain Modelling, 5, 1, pp. 46-62, (2013)","M. Masmoudi; LOGIQ Research Unit, Higher Institute of Industrial Management of Sfax, Sfax, Cité El Ons Km 11 Road Tunis Technopole BP, 1164 - 3021, Tunisia; email: masmoudi_mariem@yahoo.fr",null,"Inderscience Publishers",{"$nulls":5},1.7589401E7,null,null,null,"English","Int. J. Bus. Perform. Supply Chain Model.","Article","Final",null,"Scopus","2-s2.0-84992646896"]
["Shibata K.; Shibata K.; Isozaki N.; Yoshimura S.","Shibata, Kazuki (57650563400); Shibata, Kiyoshi (55869994900); Isozaki, Naoki (55868867900); Yoshimura, Shinobu (35595524400)","57650563400; 55869994900; 55868867900; 35595524400","A simulation model of display advertising on the web based on site browsing behavior type",2013.0,"IEEJ Transactions on Electronics, Information and Systems",133.0,9.0,null,1762.0,"1769+15",null,0.0,"10.1541/ieejeiss.133.1762","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84884824120&doi=10.1541%2fieejeiss.133.1762&partnerID=40&md5=d1544cddc202d01bbdbdfe4bd25286d8","School of Engineering, University of Tokyo, PRESTO, JST, Bunkyo-ku, Tokyo 113-8656, 7-3-1, Hongo, Japan; So-net Media Networks Corporation, Shinagawa-ku, Tokyo 141-6009, 2-1-1, Osaki, Japan","Shibata K., School of Engineering, University of Tokyo, PRESTO, JST, Bunkyo-ku, Tokyo 113-8656, 7-3-1, Hongo, Japan; Shibata K., School of Engineering, University of Tokyo, PRESTO, JST, Bunkyo-ku, Tokyo 113-8656, 7-3-1, Hongo, Japan; Isozaki N., So-net Media Networks Corporation, Shinagawa-ku, Tokyo 141-6009, 2-1-1, Osaki, Japan; Yoshimura S., School of Engineering, University of Tokyo, PRESTO, JST, Bunkyo-ku, Tokyo 113-8656, 7-3-1, Hongo, Japan","These days the deveopment of information technology has enabled us more easily to get information on user behaviors on the Internet such as web browsing history and products purchase on the E-commerce sites. E-commerce and Web advertising companies try to make effective use of those data to their businesses by segmenting or modeling their customers. In particular, Web advertising companies analyze browsing histories and interesting advertisements of their customers and intend to display ads which their customers likely to have interests in. These changes have influence on marketers, who make decision about ads delivery. They are required to image and decide their targets, or try some delivery and find them. This study introduces the concept of site browsing behavior type and models customer behaviors on browsing and clicking ads on the Internet based on actual customer browsing history data. This study also assumes that this model should be helpful to the marketers, constructs and runs agent simulations with modelized users to validate the user model, and finally analyzes some particular examples and shows the model is useful for customer targeting. © 2013 The Institute of Electrical Engineers of Japan.","Behavioral data; Customer targeting; Marketing analysis; Web advertisement; Web browsing model","Commerce; Computer simulation; Industry; Information technology; Sales; Web browsers; Behavioral data; Customer targeting; Marketing analysis; Web advertisement; Web Browsing Model; Behavioral research",{"$nulls":4},"Japan Society for the Promotion of Science, JSPS, (25540095)",null,"Attenberg J., Pandey S., Suel T., Modeling and Predicting User Behavior in Sponsored Search, (2009); Awad M.A., Khalil I., Prediction of user's web-browsing behavior: Application of markov model, IEEE Trans. Systems, Man and Cybernetics -Part B: Cybernetics, 42, 4, (2012); Chen Y., Pavlov D., Canny J.F., Large-Scale Behavioral Targeting, (2009); Dai W., Dai X., Sun T., A smart targeting system for online advertising, Journal of Computers, 4, 8, (2009); Ghose A., Yang S., An Empirical Analysis of Search Engine Advertising: Sponsored Search in ElectronicMarkets, (2009); Gupta N., Khurana U., Lee T.Y., Nawathe S., Optimizing display advertisements based on historic user trails, SIGIR, (2011); Kim C., Park S., Kwon K., Chang W., An emprical test to measure the effectiveness of online advertising in online marketplaces using a hierarchical bayes model, Expert Systems with Applications, 39, pp. 117-128, (2012); Panchanda P., Dube J., Goh K.Y., Chintagunta P.K., The Effect of Banner Advertising on Internet Purchasing, Journal OfMarketing Research, 43, pp. 98-106, (2006); Montgomery A.L., Li S., Srinivasan K., Liechty J.C., Modeling Online Browsing and Path Analysis Using ClickstreamData, Marketing Science, 23, pp. 579-595, (2004); Srikant R., Basu S., Wand N., Pregibon D., User Browsing Models: Relevance Versus Examination, (2010); Yan J., Liu N., Wang G., Zhang W., Jiang Y., Chen Z., How much can behavioral targeting help online advertising?, Proc. of the 18th International Conference on World Wide Web, pp. 261-270, (2009); Yao S., Mela C.F., A Dynamic Model of Sponsored Search Advertising, Marketing Science, 30, 3, (2011); Zhuw. Chen Z.A., Minka T., Zhu C., Chen Z., A novel click model and its applications to online advertising, Proc. of the Third ACM International Conference on Web Search and Data Mining, (2010)",null,null,"Institute of Electrical Engineers of Japan",{"$nulls":5},3854221.0,null,null,null,"English","IEEJ Trans. Electron. Inf. Syst.","Article","Final",null,"Scopus","2-s2.0-84884824120"]
["Hsieh C.-H.; Kuo Y.-W.","Hsieh, Cheng-Hsien (26322990300); Kuo, Yi-Wen (25930981800)","26322990300; 25930981800","Antecedents of retail delivery loyalty: An empirical study on online auction logistics",2014.0,"Journal of Quality",21.0,4.0,null,285.0,304.0,19.0,3.0,"10.6220/joq.2014.21(4).05","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84940962733&doi=10.6220%2fjoq.2014.21%284%29.05&partnerID=40&md5=e6075f0d6b36d7b1a7e71410fce79c73","Department of Marketing and Logistics Management, Chihlee Institute of Technology, Taiwan; Department of Logistics Management, Shu-Te University, Taiwan","Hsieh C.-H., Department of Marketing and Logistics Management, Chihlee Institute of Technology, Taiwan; Kuo Y.-W., Department of Logistics Management, Shu-Te University, Taiwan","An exploration into the logistics choice behaviors of online consumers is crucial to help logistics operators increase their share on e-commerce markets. In Taiwan, a new logistics mechanism has been introduced, whereby consumers receive their products from a designated convenience store, a process also known as retail delivery. According to 395 effective samples on online auction markets, logistics service quality, which consists of reliability, information, and quality of personal contact, significantly influences customer loyalty to retail delivery supplier directly and indirectly through an intermediate construct, namely, satisfaction. Appropriate psychological, effort-based and timebased switching costs for consumers assist in enhancing customer loyalty. The information and communication technologies, the training and necessary resources to employees, as well as a more reliable logistics operating procedure agreed upon with the customer improve logistics service quality. This study recommends several strategies for creating switching costs and improving logistics service quality to pledge customer loyalty. © 2014, Journal of Quality. All rights reserved.","Logistics service quality; Loyalty; Online auction; Retail delivery; Switching cost","Consumer behavior; Customer satisfaction; Electronic commerce; Personnel training; Quality of service; Sales; Logistics service qualities; Loyalty; Online auctions; Retail delivery; Switching costs; Costs",{"$nulls":6},"Anderson J.C., Gerbing D.W., Structural equation modeling in practice: a review and recommended two-step approach, Psychological Bulletin, 103, 3, pp. 411-423, (1988); Athanassopoulos A.D., Customer satisfaction cues to support market segmentation and explain switching behavior, Journal of Business Research, 47, 3, pp. 191-207, (2000); Aydin S., Ozer G., Arasil O., Customer loyalty and the effect of switching costs as a moderator variable: A case in the Turkish mobile phone market, Marketing Intelligence & Planning, 23, 1, pp. 89-103, (2005); Ba S., Whinston A.B., Zhang H., Building trust in online auction markets through an economic incentive mechanism, Decision Support Systems, 35, 3, pp. 273-286, (2003); Bagozzi R.P., Yi Y., Phillips L.W., Assessing construct validity in organizational research, Administrative Science Quarterly, 36, 3, pp. 421-458, (1991); Bailey J.P., Rabinovich E., Internet book retailing and supply chain management: An analytical study of inventory location speculation and postponement, Transportation Research Part E: Logistics and Transportation Review, 41, 3, pp. 159-177, (2005); Barry J., Terry T.S., Empirical study of relationship value in industrial services, The Journal of Business & Industrial Marketing, 23, 4, pp. 228-241, (2008); Bauer H.H., Falk T., Hammerschmidt M., eTransQual: A transaction process-based approach for capturing service quality in online shopping, Journal of Business Research, 59, 7, pp. 866-875, (2006); Beam C., Segev A., Bichler M., Krishnana R., On negotiations and deal making in electronic markets, Information Systems Frontiers, 1, 3, pp. 241-258, (1999); Berry L.L., Parasuraman A., Zeithaml V.A., Improving service quality in America: Lessons learned, Academy of Management Executive, 8, 2, pp. 32-52, (1994); Bienstock C.C., Mentzer J.T., Bird M.M., Measuring physical distribution service quality, Journal of the Academy of Marketing Science, 25, 1, pp. 31-44, (1997); Boyer K.K., Hallowell R., Roth A.V., E-services: Operating strategy-a case study and a method for analyzing operational benefits, Journal of Operations Management, 20, 2, pp. 175-188, (2002); Brady M.K., Knight G.A., Cronin J.J., Tomas G., Hult M., Keillor B.D., Removing the contextual lens: A multinational, multi-setting comparison of service evaluation models, Journal of Retailing, 81, 3, pp. 215-230, (2005); Burnham T.A., Frels J.K., Mahajan V., Consumer switching costs: A typology, antecedents, and consequence, Journal of the Academy of Marketing Science, 31, 2, pp. 109-126, (2003); Cardozo R.N., An experimental study of customer effort, expectation and satisfaction, Journal of Marketing Research, 2, 3, pp. 244-249, (1965); Chen P.-Y., Hitt L.M., Measuring switching costs and the determinants of customers retention in Internet-enabled businesses: A study of the online brokerage industry, Information Systems Research, 13, 3, pp. 255-274, (2002); Chou C.-P., Bentler P.M., Estimates and tests in structural equation modelling, Structural Equation Modeling: Concepts, Issues and Applications, pp. 37-55, (1995); Cortina J.M., What is the coefficient alpha? 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["Liang C.-C.; Liang W.-Y.","Liang, Chih-Chin (13907640300); Liang, Wen-Yau (7402026606)","13907640300; 7402026606","Efficient communication architecture for the C2C agent",2014.0,"Computer Standards and Interfaces",36.0,3.0,null,641.0,647.0,6.0,4.0,"10.1016/j.csi.2013.09.001","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84892439129&doi=10.1016%2fj.csi.2013.09.001&partnerID=40&md5=051300671b2b0c9261e41e2964299bde","Department of Business Administration, National Formosa University, Yunlin, Taiwan; Department of Information Management, National Changhua University of Education, Changhua, Taiwan","Liang C.-C., Department of Business Administration, National Formosa University, Yunlin, Taiwan; Liang W.-Y., Department of Information Management, National Changhua University of Education, Changhua, Taiwan","In C2C communication, all necessary information must be collected promptly when a buyer and a seller communicate. That is, an intelligent C2C agent is needed to provide information to buyers and sellers. Along with the evolution of computing technology, C2C agents can exploit the efficient delivery capabilities of peer-to-peer (P2P) technology. However, P2P also increases traffic between agents, but communication faults are a fatal problem for C2C business. This study proposes a robust communication architecture based on current P2P content-delivery standards and its efficiency and robustness have been verified from an experiment. © 2013 Elsevier B.V. All rights reserved.","Consumer-to-consumer; E-commerce; Intelligent agent; Peer-to-peer communication","Communication; Electronic commerce; Intelligent agents; Buyers and sellers; C2C Communications; Computing technology; Consumer-to-consumer; Efficient communications; Peer-to-peer communications; Peer-to-peer technologies; Robust communication; Distributed computer systems",{"$nulls":4},"National Science Council of the Republic of China, (NSC 96-2416-H-018-005-MY3)","This work was partially supported by funding from the National Science Council of the Republic of China ( NSC 96-2416-H-018-005-MY3 ).  ","Bhide M., Deolasee P., Katkar A., Panchbudhe A., Ramamritham K., Shenoy P., Adaptive push-pull: Disseminating dynamic web data, IEEE Trans. Comput., 51, 6, pp. 652-668, (2002); Biswas P., Towards an agent-oriented approach to conceptualization, Appl. Soft Comput., 8, pp. 127-139, (2008); Bodendorf F., Zimmermann R., Proactive supply-chain event management with agent technology, Int. 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Commer., 10, 3, pp. 71-93, (2006)","W.-Y. Liang; Department of Information Management, National Changhua University of Education, Changhua, Taiwan; email: wyliang@cc.ncue.edu.tw",{"$nulls":7},9205489.0,null,"CSTIE",null,"English","Comput Stand Interfaces","Article","Final",null,"Scopus","2-s2.0-84892439129"]
["Vinodhini G.; Chandrasekaran R.M.","Vinodhini, G. (56180342800); Chandrasekaran, R.M. (7006808993)","56180342800; 7006808993","Measuring the quality of hybrid opinion mining model for e-commerce application",2014.0,"Measurement: Journal of the International Measurement Confederation",55.0,null,null,101.0,109.0,8.0,13.0,"10.1016/j.measurement.2014.04.033","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84901397448&doi=10.1016%2fj.measurement.2014.04.033&partnerID=40&md5=623d4487d34a5dfa335906d56bd76275","Department of Computer Science and Engineering, Annamalai University, Annamalai Nagar 608002, India","Vinodhini G., Department of Computer Science and Engineering, Annamalai University, Annamalai Nagar 608002, India; Chandrasekaran R.M., Department of Computer Science and Engineering, Annamalai University, Annamalai Nagar 608002, India","With the rapid expansion of e-commerce over the decades, the growth of the user generated content in the form of reviews is enormous on the Web. A need to organize the e-commerce reviews arises to help users and organizations in making an informed decision about the products. Opinion mining systems based on machine learning approaches are used online to categorize the customer opinion into positive or negative reviews. Different from previous approaches that employed single rule based or statistical techniques, we propose a hybrid machine learning approach built under the framework of combination (ensemble) of classifiers with principal component analysis (PCA) as a feature reduction technique. This paper introduces two hybrid models, i.e. PCA with bagging and PCA with Bayesian boosting models for feature based opinion classification of product reviews. The results are compared with two individual classifier models based on statistical learning i.e. logistic regression (LR) and support vector machine (SVM). We found that hybrid methods do better in terms of four quality measures like misclassification rate, correctness, completeness and effectiveness in classifying the opinion into positive and negative. © 2014 Elsevier Ltd. All rights reserved.","Bigram; Classification; Feature; Mining; Opinion; Reviews; Unigram","Artificial intelligence; Classification (of information); Data mining; Mining; Principal component analysis; Reviews; Support vector machines; Bigram; E-Commerce applications; Feature; Hybrid machine learning; Misclassification rates; Opinion; Statistical techniques; Unigram; Electronic commerce",{"$nulls":6},"Reyes A., Rosso P., Making objective decisions from subjective data: Detecting irony in customers reviews, Decis. Support Syst., 53, pp. 754-760, (2012); Abbasi A., Chen H., Salem A., Sentiment analysis in multiple languages: Feature selection for opinion classification in web forums, ACM Trans. Inf. 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Appl., 38, 6, pp. 7674-7682, (2011)","G. Vinodhini; Department of Computer Science and Engineering, Annamalai University, Annamalai Nagar 608002, India; email: g.t.vino@gmail.com",null,"Elsevier B.V.",{"$nulls":5},2632241.0,null,"MSRMD",null,"English","Meas J Int Meas Confed","Article","Final",null,"Scopus","2-s2.0-84901397448"]
["Mangiaracina R.; Perego A.; Perotti S.; Tumino A.","Mangiaracina, Riccardo (35325033800); Perego, Alessandro (7004535933); Perotti, Sara (35220345000); Tumino, Angela (25929706400)","35325033800; 7004535933; 35220345000; 25929706400","Assessing the environmental impact of logistics in online and offline B2C purchasing processes in the apparel industry",2016.0,"International Journal of Logistics Systems and Management",23.0,1.0,null,98.0,124.0,26.0,45.0,"10.1504/IJLSM.2016.073300","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84948844590&doi=10.1504%2fIJLSM.2016.073300&partnerID=40&md5=48b47f3202a30108c6075f172536488c","Department of Management, Economics and Industrial Engineering, Politecnico di Milano, Via Lambruschini 4/B, Milano, 20156, Italy","Mangiaracina R., Department of Management, Economics and Industrial Engineering, Politecnico di Milano, Via Lambruschini 4/B, Milano, 20156, Italy; Perego A., Department of Management, Economics and Industrial Engineering, Politecnico di Milano, Via Lambruschini 4/B, Milano, 20156, Italy; Perotti S., Department of Management, Economics and Industrial Engineering, Politecnico di Milano, Via Lambruschini 4/B, Milano, 20156, Italy; Tumino A., Department of Management, Economics and Industrial Engineering, Politecnico di Milano, Via Lambruschini 4/B, Milano, 20156, Italy","This paper presents an activity-based model for the assessment of the environmental impact of the purchasing process in the apparel industry, comparing traditional in-store and B2C e-commerce channels with a focus on logistics activities. Interviews with company managers and secondary sources were used to develop and validate the model. A base case was selected and a sensitivity analysis was carried out. The impact of logistics is generally very high in both the online and offline purchasing processes (i.e., 99% and 62% of total CO2e emissions respectively). In the online case, the location of the consumer house (i.e., inside or outside the city centre) is the parameter with the greatest environmental impact, whereas in the offline case the distance between the consumer house and the store was the most significant factor. From a managerial viewpoint, the model helps practitioners understand the environmental consequences of their business and supports internal monitoring procedures. Copyright © 2016 Inderscience Enterprises Ltd.","B2C e-commerce; Environmental sustainability; Logistics; Quantitative model",{"$nulls":7},"Allen J., Browne M., Vans and the Economy, (2010); Bruce G.M., Daly L., Innovative process in e-commerce fashion supply chains, Innovative Quick Response Programs in Logistics and Supply Chain Management, pp. 227-241, (2010); Brugnoli G., Mangiaracina R., Perego A., The e-commerce customer journey: A model to assess and compare the user experience of the e-commerce websites, Journal of Internet Banking and Commerce, 14, 3, pp. 1-11, (2009); Caniato F., Caridi M., Crippa L., Moretto A., Environmental sustainability in fashion supply chains: An exploratory case based research, International Journal of Production Economics, 135, 2, pp. 659-670, (2012); Cardoso P.R., Costa H.S., Novais L.A., Fashion consumer profiles in the Portuguese market: Involvement, innovativeness, self-expression and impulsiveness as segmentation criteria, International Journal of Consumer Studies, 34, 6, pp. 638-647, (2010); 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From the perspective of social network, International Journal of Networking and Virtual Organizations, 11, 3, pp. 212-224, (2012); Sivaraman D., Pacca S., Mueller K., Lin J., Comparative energy, environmental, and economic analysis of traditional and e-commerce DVD rental networks, Journal of Industrial Ecology, 11, 3, pp. 77-91, (2007); Smith A.D., Green manufacturing in the packaging and materials industry: Case study of small-to-medium sized corporate eco-friendly initiatives, International Journal of Logistics Systems and Management, 11, 4, pp. 429-449, (2012); Smithers R., Supermarket home delivery service promotes its green credentials, The Guardian, (2007); Taniguchi E., Kakimoto Y., Effects of e-commerce on urban distribution and the environment, Journal of the Eastern Asia Society for Transportation Studies, 5, pp. 2355-2366, (2003); Volpe A., Spinelli M., E-Commerce for the Furniture Industry, (2012); Weber C.L., Koomey J.G., Matthews H.S., The energy and climate change implications of different music delivery methods, Journal of Industrial Ecology, 14, 5, pp. 754-769, (2010); Wei Z., Zhou L., Case study of online retailing fast fashion industry, International Journal of E-Education, E-Business, E-Management and E-Learning, 1, 3, pp. 195-200, (2011); Wiese A., Toporowsky W., Zielke S., Transport-related CO2 effects of online and brick-and-mortar shopping: A comparison and sensitivity analysis of clothing retailing, Transportation Research Part D, 17, 6, pp. 473-477, (2012); Williams E., Tagami T., Energy use in sales and distribution via e-commerce and conventional retail: A case study of the Japanese book sector, Journal of Industrial Ecology, 6, 2, pp. 99-114, (2003); Zeng C., Xu D., Views on the development of e-commerce of Chinese clothing industry, International Journal of Business and Management, 5, 8, pp. 215-218, (2010)","S. Perotti; Department of Management, Economics and Industrial Engineering, Politecnico di Milano, Milano, Via Lambruschini 4/B, 20156, Italy; email: sara.perotti@polimi.it",null,"Inderscience Publishers",{"$nulls":5},1.7427967E7,null,null,null,"English","Int. J. Logist. Syst. Manage.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-84948844590"]
["Xu X.","Xu, Xiaoming (56595702700)",5.65957027E10,"IOT T echnology research in e-commerce",2014.0,"Information Technology Journal",13.0,16.0,null,2552.0,2559.0,7.0,16.0,"10.3923/itj.2014.2552.2559","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84927802582&doi=10.3923%2fitj.2014.2552.2559&partnerID=40&md5=3fa1ce085abe07d5a7337ed2c40546cb","Business College, Hunan International Economics University, Changsha, 410205, China","Xu X., Business College, Hunan International Economics University, Changsha, 410205, China","Internet of Tilings (IOT) is a new revolution in information technology after the internet and mobile communication network, it contains a huge room for innovation and opportunity. Internet of things takes advantage of smart devices and sensing technology to perceive and recognize the physical world. By RFID radio frequency technology, network transmission interconnection, signal processing and computing, information is shared and seamless connection is realized between tilings or between persons and tilings, the real-time monitoring things, accurate management and scientific decision-making are achieved. In this study, the development trend of IOT applications has been analyzed in e-commerce, the problems are described in traditional e-commerce. In the IOT technology application, there are three important aspects, such as e-commerce inventoiy, logistics, payment. We studied the key technical issues of Things development, e-commerce security measures, their system configuration structures and that the intelligent identification, positioning, tracking, monitoring and management are integrated between the IOT and e-commerce. © 2014 Asian Network for Scientific Information","E-commerce; Intelligent platform; Internet of things; RFID; Secure payment",{"$nulls":7},"Deng J., Li Q., Liu Y.Z., RFID technology application in the warehouse management of the internet of things, Discovering Value, 15, pp. 128-130, (2014); Ha J.H., Moon S.J., Zhou J., Ha J.C., A new formal proof model for RFID location privacy, Proceedings of the 13th European Symposium on Research in Computer Security, pp. 267-281, (2008); Han J., Li Z.P., Constructing logistics e-commerce platform based on internet of things, Value Eng, 31, pp. 10-14, (2012); Han J.L., Application research on RFID technology of IOT in electronic commerce, Agric. Network Inform., 13, 22, pp. 9-11, (2013); Jin Q., Zeng J., Liu Y., Shen J.S., The application of RFID technology in mobile commerce, Applic. Electron. Tech., 33, 97, pp. 90-91, (2007); Phan R.C.W., Wu J., Ouafi K., Stinson D.R., Privacy analysis of forward and backward untraceable RFID authentication schemes, Wireless Personal Commun, 61, pp. 69-81, (2011); Song B., Mitchell C.J., Scalable RFID security protocols supporting tag ownership transfer, Comput. Commun., 34, pp. 556-566, (2011); Van Deursen T., Radomirovic S., On a new formal proof model for RFID location privacy, Inform. Proces. Lett., 110, pp. 57-61, (2009); Van Deursen T., Mauw S., Radomirovic S., Untraceability of RFID protocols, Proceedings of the 2nd IFIP WG 11.2 International Conference on Information Security Theory and Practices: Smart Devices, Convergence and Next Generation Networks, pp. 1-15, (2008); Yang D., Tian L.W., Applied research on E-commerce logistics and distribution based on internet of things, Logist. Eng. Manage., 34, pp. 23-37, (2012); Yang H.Q., Ran L., Discussion on development of electronic commerce based on internet of things technology, Sci. Technol. Inform., 35, pp. 10-11, (2011); Zhang Z., Xu Q.L., Universal composable grouping-proof protocol for RFID tags in the internet of things, Chinese J. Comput., 34, pp. 1188-1194, (2011); Zheng N., Things technology in the B2C E-commerce distribution transportation applications, Electron. Sci. Technol., 27, pp. 20-25, (2014)",null,null,"Asian Network for Scientific Information",{"$nulls":5},1.8125638E7,null,null,null,"English","Inf. Technol. J.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-84927802582"]
["Niraj S.; Nageswara Rao S.V.D.","Niraj, S. (57189505445); Nageswara Rao, S.V.D. (56576232900)","57189505445; 56576232900","Sustainability of E-retail in India",2015.0,"Journal of Internet Banking and Commerce",20.0,2.0,1000107.0,null,null,6.0,1.0,"10.4172/1204-5357.1000107","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84942163639&doi=10.4172%2f1204-5357.1000107&partnerID=40&md5=309c8fb2ecf3c94d20f525683a4b80e9","Shailesh J. Mehta School of Management (SJMSOM), IIT Bombay, Maharashtra, India","Niraj S., Shailesh J. Mehta School of Management (SJMSOM), IIT Bombay, Maharashtra, India; Nageswara Rao S.V.D., Shailesh J. Mehta School of Management (SJMSOM), IIT Bombay, Maharashtra, India","Sustainability of a business entails the objective of sustainable development which includes three main parameterspeople, profit and planet. The Brundtland report of 1987 did help in setting the stage on sustainability for companies. However, in India one of the business models which lack several aspects of sustainability is e-Retail or the electronic retail. This paper outlines the need of sustainable business and also determines important parameters for sustainability of business. Further, the paper also analyses the sustainability of Indian e-retail business. The main agenda for most of the Indian e-retailers has been customer acquisition. Spending big bucks on marketing, and brand building is something which is seen round the clock 365 days a year. The aggressiveness of the e-retailers definitely makes sense in the Indian economy given the fact that the penetration of e-retail in overall retailing market in India is still in its infancy (with penetration less than 3 per cent). The companies in India are following a similar paradigm which was fooled by the global players like eBay Inc. and Amazon Inc. in the United States. Also, private equity players and venture capitalists are supporting the e-retailers by making massive investments which are purely based on base line assumption of promising future returns the business the investors would make. However, on the contrary, if the Indian e-retailers continue to offer huge discounts, they will only attract volumes thereby gaining significant market share but it would lead to un-sustainability as profitability with such deep discounts remains a distant dream. Lastly, the paper also makes a qualitative and quantitative correlation of emergence of e-retail in developed economies like US, UK along with developing economies like Brazil and Chine to that of Indian market. This correlation helped in understanding the tipping point post which a change in strategy for Indian players and increased focus on profitability will only result in sustainable business model. It is inferred from the analysis that the Indian e-retailers will have to relook their strategy and change their focus on profitability. This can be achieved by two means- one by means of cost optimisation and other by discount reduction. Cost optimisation techniques would involve reduction of cost in overheads like employee cost, fulfilment cost, payment gateway cost, logistic cost and others. This would be possible by inorganic growth route as the players have positive gross margins while negative operating margins which indicates high cost in operations. The paper outlines that the tipping point will be the ideal penetration of e-Retail in India and beyond this point players have to shift focus solely on profitability and returns. If not done, the companies won’t sustain in the market and continuous triple digit growth and whooping valuations will result in a bubble which will eventually burst. © 2015 Niraj S, et al.","Business sustainability; E-commerce; E-retail; Tipping point",{"$nulls":7},"Sean T.M., John L.K., Kalle L., Globalization of E-Commerce: Growth and Impacts in the United States of America, (2008); Singh R.K., Murty H.R., Gupta S.K., Dikshit A.K., Development of composite sustainability performance index for steel industry, Ecological Indicators, 7, pp. 565-588, (2007); Bocken N., Short S.W., Rana P., Evans S., A literature and practice review to develop sustainable business model archetypes, Journal of Cleaner Production, 65, pp. 42-56, (2014); Singh R.K., Murty H.R., Gupta S.K., Dikshit A.K., An overview of sustainability assessment methodologies, Ecological Indicators, 9, pp. 189-212, (2009); Gomes C.M., Kneipp J.M., Kruglianskas I., Da Rosa L., Bichueti R.S., Management for sustainability: An analysis of the key practices according to the business size, Ecological Indicators, 52, pp. 116-127, (2015); Kolk A., Tulder R.V., International Business, Corporate Social Responsibility and Sustainable Development, International Business Review, 19, pp. 119-125, (2010); Molla A., Licker P.S., ECommerce adoption in developing countries: A model and instrument, Information and Management, 42, pp. 877-899, (2005); Griffis S.E., Rao S., Goldsby T.J., Niranjan T.T., The customer consequences of returns in online retailing: An empirical analysis, Journal of Operations Management, 30, pp. 282-294, (2012); Chaudhry R., The Future of Sustainable Business It lies in Aligning Corporate Objectives with Societal Expectations, Futures, (2013); Kettles D., Lu L., International differences in trust in e-Commerce Settings, Journal of Accounting Information Science and Leadership, 7, (2014); Ferris D., Lessons in Sustainability from India’s Entrepreneurs; Business sustainability, Financial Times Lexicon - the Definitive Dictionary of Economic, Financial and Business Terms; Hawken P., The Ecology of Commerce and Natural Capitalism, (2010); McDonough B., Braungart M., Cradle to Cradle Cradle-To-Cradle Design: Creating Healthy Emissions a Strategy for Eco-Effective Product and System Design, (2006); Benyus J., Biomimicry, (1997); Arora R., Banwet D.K., E-Commerce implementation in India: A study of selected organizations, Asia-Pacific Development Journal, (2003); Svensson G., Wood G., Callaghan M., A corporate model of sustainable business practices: An ethical perspective, Journal of World Business, 45, pp. 336-345, (2010); Ingham J., Cadieux J., Berrada A.M., E-Shopping acceptance: A qualitative and meta-analytic review, Information & Management, 52, pp. 44-60, (2015); Yang J.C., Environmental impact of e-commerce and other sustainability implications of the information economy, Center for Applied Policy Research, pp. 1-19; Bahl K., Brand India and E-Commerce, IBEF Blogs Perspective on India, (2014); Srinivasan S., Is Indian eCommerce Growth Sustainable?, IDG Connect, (2014); Government E-payments adoption ranking: A global index and benchmarking study, Economist Intelligence Unit. The Economist, (2011); The Evolution of Ecommerce Business Models in India [Going Back to Where It Started?] Next Big What, (2013); Evolution of E-Commerce in India: Creating the Bricks behind the Clicks, (2015); Labuschagne C., Brent A.C., Van Erck R., Assessing the sustainability performances of industries, Journal of Cleaner Production, 13, pp. 373-385, (2005); Chen R., Beyond sustainability: From sustainable consumer services to sustainable business, Journal of Retailing and Consumer Services, 22, pp. 223-224, (2014); Debbarma S., Nandi G., Promoting E-commerce in India: Main Issues and Challenges, International Journal of Computer Science and Information Technologies, 5, pp. 7371-7375, (2014); Terzi N., The impact of e-commerce on international trade and Employment, Procedia-Social and Behavioral Sciences, 24, pp. 745-753, (2011); Vyas S.D., E-Banking and E-Commerce in India and USA, pp. 1-4; Wells P., Sustainable business models and the automotive industry: A commentary, IIMB Management Review, 25, pp. 228-239, (2013); Anil S., Tan L.H., ICT Investments and Electronic Commerce Initiatives in ASEAN, J World Investment, (2003); Singh R.K., Murty H.R., Gupta S.K., Dikshit A.K., An overview of sustainability assessment methodologies, Ecological Indicators, 15, pp. 281-299, (2012); Grewala D., Iyer G.R., Levya M., Internet retailing: Enablers, limiters and market consequences, Journal of Business Research, 57, pp. 703-713, (2004); Gupta B., Dasgupta S., Gupta A., Adoption of ICT in a government organization in a developing country: An empirical study, Journal of Strategic Information Systems, 17, pp. 140-154, (2008); Lim M.Y., Cham H.T., A profile of the Internet shoppers: Evidence from nine countries, Telematics and Informatics, 32, pp. 344-354, (2015); Reddy N.A., Divekar B.R., A study of challenges faced by E-commerce companies in India and methods employed to overcome them, Procedia Economics and Finance, 11, pp. 553-560, (2014); As one store opens, Retail in China, Industry Briefing, The Economist, (2014); Ecommerce trends in the UK, £91bn Spent Online in 2013, (2014); Unlocking the potential of e-commerce for developing countries, United Nations Conference on Trade and Development, (2015); Rhodes C., The retail industry: Statistics and policy, Economic Policy and Statistics, (2014); At the tipping point: Financial services in Africa comes of age, How Financial Institutions Can Capitalise on the Growth Opportunities, (2011); E-commerce in China: Driving a new consumer culture, KPMG Global China Practice, (2014); Gupta A., Profitable business model is a must for ecommerce firms, says PwC Director, Business Today, (2014); The Indian Express, Profitable Biz Model, a Must for E-Commerce Firms, (2014)",null,null,"ARRAY Development (Canada) Inc.",{"$nulls":5},1.2045357E7,null,null,null,"English","J. Internet Bank. Commer.","Article","Final",null,"Scopus","2-s2.0-84942163639"]
["Chen P.-W.; Lin W.-Y.; Huang T.-H.; Pan W.-T.","Chen, Peng-Wen (57223823017); Lin, Wei-Yuan (22958389900); Huang, Tsui-Hua (56082266200); Pan, Wen-Tsao (25925332600)","57223823017; 22958389900; 56082266200; 25925332600","Using fruit fly optimization algorithm optimized grey model neural network to perform satisfaction analysis for e-business service",2013.0,"Applied Mathematics and Information Sciences",7.0,"2 L",null,459.0,465.0,6.0,51.0,"10.12785/amis/072L12","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84896694126&doi=10.12785%2famis%2f072L12&partnerID=40&md5=d437f7fa29e24aaa9d20bd3819c9d1c2","Department of Information Management, Oriental Institute of Technology, Taiwan; Department of Economics, Soochow University, Taiwan; Department of Business Administration, Hwa Hsia Institute of Technology, Taiwan","Chen P.-W., Department of Information Management, Oriental Institute of Technology, Taiwan; Lin W.-Y., Department of Economics, Soochow University, Taiwan; Huang T.-H., Department of Economics, Soochow University, Taiwan; Pan W.-T., Department of Business Administration, Hwa Hsia Institute of Technology, Taiwan","In recent years, the automation and electronic system in the logistics industry have become popular topics in management, which consist of five segments, including marketing, logistics, information technology, banking system, and service system in the online stores (B2C & C2C) of the E-Commerce system. This study contains questionnaires and collective information that focus on logistics. In this article, the results of the survey questionnaires regarding the service quality level of the e-business seller will be used first to conduct the Principal Components Analysis; then the FOA Optimized Grey Model Neural Network(FOAGMNN), the Grey Model Neural Network, and Multiple Regression will be further utilized to perform the construction of service satisfaction detection models. Based on the analysis results in this article, the FOAGMNN model has the fastest error convergence and the best classification forecast capability. © 2013 NSP. Natural Sciences Publishing Cor.","E-business; Fruit fly optimization algorithm; Grey model; Multiple regression; Neural network; Principal components",{"$nulls":7},"Bradley A.P., The Use of the Area under the ROC Curve in the Evaluation of Machine Learning Algorithms, Pattern Recognit., 30, 7, pp. 1145-1159, (1997); Cheng R., Yao M., Particle Swarm Optimizer with Time-Varying Parameters based on a Novel Operator, Appl. Math. Inf. Sci., 5, 2, pp. 26-33, (2011); Chiang C.C., Ho M.C., Chen J.A., A Hybrid Approach of Neural Networks and Grey Modelling for Adaptive Electricity Load Forecasting, Neural Computing & Applications, 15, 3, pp. 328-338, (2006); Damanpour F., E-business E-commerce Evolution: Perspectives and Strategy, J. Managerial Finance, 27, 7, pp. 16-33, (2001); Dondeti S., Kannan K., Manavalan R., Genetic Algorithm Optimized Neural Networks Ensemble for Estimation of Mefenamic Acid and Paracetamol in Tablets, Acta Chimica Slovenica, 52, pp. 440-449, (2005); Gale J., Abraham D., Introduction: Toward Understanding E-Business Transformation, Journal of Organizational Change, 18, 2, pp. 113-116, (2005); Gao L., Zhou C., Gao H.B., Shi Y.R., Credit Scoring Model Based on Neural Network with Particle Swarm Optimization, 4221, pp. 76-79, (2006); Gudise V.G., Venayagamoorthy G.K., Comparison of Particle Swarm Optimization and Backpropagation as Training Algorithms for Neural Networks, pp. 110-117, (2003); Hand D.J., Till R.J., A Simple Generalisation of the Area under the ROC Curve to Multiple Class Classification Problems, Mach. Learn., 45, 2, pp. 171-186, (2001); Hong M., Kim E., E-commerce Client-side System Security: The Government Regulation Issue in Korea, Appl. Math. Inf. Sci., 6, 1 S, (2012); Hung J.C., Lin C.C., Hybridization of Genetic Algorithm and IBMUSIC Applied to DOA Estimation Under Coherent Signals, Appl. Math. Inf. Sci. special issues, 6, 2 S, pp. 489-496, (2012); Mohamed A.W., Zaher H., Korshid M., A Particle Swarm Approach for Solving Stochastic Optimization Problems, Appl. Math. Inf. Sci., 5, 3, (2011); Pan W.T., A New Fruit Fly Optimization Algorithm: Taking the Financial Distress Model as an Example, Knowledge-Based Systems, 26, pp. 69-74, (2011); Rovithakis G.A., Maniadakis M., Zervakis M., A Hybrid Neural Network/Genetic Algorithm Approach to Optimizing Feature Extraction for Signal Classification, IEEE Transactions On Systems, Man, And Cybernetics-Part B: Cybernetics, 34, 1, pp. 695-702, (2004); Shi F., Wang S.C., Yu L., Li Y., Zhang Y.L., Matlab Neural Network 30 Case Analysis; Tu C.S., Chang C.T., Chen K.K., Lu H.A., A Study on Business Performance with the Combination of Zscore and FOAGRNN Hybrid Model, African J. Business Management., (2012); Wang F., Xia H., Network Traffic Prediction Based on Grey Neural Network Integrated Model, International Conference on Computer Science and Software Engineering, pp. 915-918, (2008); Wang Y.M., Wang D.M., Zhong X.X., Shi G.Q., Modified Particle Swarm Algorithm for Radiation Properties of Semi-transparent Rectangular Material, Appl. Math. Inf. Sci., 5, 2, (2011); Yang S.C., Lee C.S., Lee H.S., Construction of the Prediction Model of Business Operation Performance in the Electronic Industry, J. Business Management and Economics, 3, 2, pp. 079-089, (2012)","W.-Y. Lin; Department of Economics, Soochow University, Taiwan; email: k8888@scu.edu.tw",{"$nulls":7},2.3250399E7,null,null,null,"English","Appl. Mat. Inf. Sci.","Article","Final",null,"Scopus","2-s2.0-84896694126"]
["Jiang L.A.; Yang Z.; Jun M.","Jiang, Ling (Alice) (55747940100); Yang, Zhilin (8113149300); Jun, Minjoon (7006544861)","55747940100; 8113149300; 7006544861","Measuring consumer perceptions of online shopping convenience",2013.0,"Journal of Service Management",24.0,2.0,null,191.0,214.0,23.0,314.0,"10.1108/09564231311323962","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84878230893&doi=10.1108%2f09564231311323962&partnerID=40&md5=d0cfe2900e0464872d43b7c46aee8204","Faculty of Management and Administration, Macau University of Science and Technology, Taipa, Macau, Macao; Department of Marketing, City University of Hong Kong, Hong Kong, Hong Kong; Management Department, New Mexico State University, Las Cruces, NM, United States","Jiang L.A., Faculty of Management and Administration, Macau University of Science and Technology, Taipa, Macau, Macao; Yang Z., Department of Marketing, City University of Hong Kong, Hong Kong, Hong Kong; Jun M., Management Department, New Mexico State University, Las Cruces, NM, United States","Purpose: The purpose of this paper is to identify the key convenience dimensions of online shopping, as convenience has been one of the principal motivations underlying customer inclinations to adopt online shopping. Design/methodology/approach: The authors first employ in-depth focus group interviews with online consumers to identify the attributes of online shopping convenience and then develop and validate an instrument of five key dimensions to measure online shopping convenience by analyzing data collected via a Web-based questionnaire survey. Findings: The five dimensions of online shopping convenience are: access, search, evaluation, transaction, and possession/post-purchase convenience. Practical implications: Online retailers can employ the five-factor measurement instrument to assess the degree of customer perceived online shopping convenience. This instrument can assist managers in identifying and overcoming key obstacles to the delivery of a highly convenient online shopping service to customers, and also helps them enlarge their loyal customer base. Originality/value: This study focuses on uncovering the key dimensions of convenience and their associated sub-dimensions specific to the context of online shopping. Theoretically, the identified dimensions and their related sub-items comprise a validated scale for measuring Web-based service convenience and can serve as building blocks for further studies in e-commerce customer relationship management. © Emerald Group Publishing Limited.","Consumer behaviour; Convenience; e-commerce; Electronic commerce; Internet; Online shopping; Perception; Scale development; Shopping",{"$nulls":7},"Ahmad S., Service failures and customer defection: A closer look at online shopping experiences, Managing Service Quality, 12, 1, pp. 19-29, (2002); Armstrong J.S., Overton T.S., Estimating nonresponse bias in mail surveys, Journal of Marketing Research, 13, pp. 396-402, (1977); Beauchamp M.B., Ponder N., Perceptions of retail convenience for in-store and online shoppers, The Marketing Management Journal, 20, 1, pp. 49-65, (2010); Berry L.L., Seiders K., Grewal D., Understanding service convenience, Journal of Marketing, 66, 3, pp. 1-17, (2002); Brown L.G., The strategic and tactical implications of convenience in consumer product marketing, Journal of Consumer Marketing, 6, pp. 13-19, (1989); Brown L.G., Convenience in services marketing, The Journal of Services Marketing, 4, 1, pp. 53-59, (1990); Bucklin L.P., Retail strategy and the classification of consumer goods, Journal of Marketing, 27, pp. 50-55, (1963); Churchill G.A., A paradigm for developing better measures of marketing constructs, Journal of Marketing Research, 16, pp. 64-73, (1979); Clulow V., Reimers V., How do consumers define the retail centre convenience?, Australasian Marketing Journal, 17, pp. 125-132, (2009); Colwell S.R., Aung M., Kanetkar V., Holden A.L., Toward a measure of service convenience: Multiple-item scale development and empirical test, Journal of Services Marketing, 22, 2, pp. 160-169, (2008); Copeland M.T., Relation of consumers' buying habits to marketing methods, Harvard Business Review, 1, 2, pp. 282-289, (1923); Cowles D.L., Kiecker P., Little M.W., Using key informant insights as a foundation for e-retailing theory development, Journal of Business Research, 55, pp. 629-636, (2002); Degeratu A.M., Rangaswamy A., Wu J.N., Consumer choice behavior in online and traditional supermarkets: The effects of brand name, price, and other search attributes, International Journal of Research in Marketing, 17, pp. 55-78, (2000); Easterbrook G., A Moment on the Earth: The Coming of Age of Environmental Optimism, (1995); Etgar M., Intrachannel conflict and use of power, Journal of Marketing Research, 15, 2, pp. 273-274, (1978); Fennema M., Kleinmuntz D., Anticipations of effort and accuracy in multiattribute choice, Organizational Behavior & Human Decision Processes, 63, 1, pp. 21-32, (1995); Fiske S.T., Taylor S.E., Social Cognition, (1984); Fitch D., Measuring convenience: Scot's perceptions of local food and retail provision, International Journal of Retail & Distribution Management, 32, 2, pp. 100-108, (2004); Ford R.C., Bach S.A., Fottler M.D., Methods of measuring patient satisfaction in health care organizations, Health Care Management Review, 22, 2, pp. 74-89, (1997); Fornell C., Larcker D.F., Structural equation model with unobservable variables and measurement error: Algebra and statistics, Journal of Marketing Research, 18, 3, pp. 382-389, (1981); Gehrt K.C., Yale L.J., The dimensionality of the convenience phenomenon: A qualitative reexamination, Journal of Business and Psychology, 18, 2, pp. 163-180, (1993); Gerbing D.W., Anderson J.C., An updated paradigm for scale development incorporating unidimensionality and its assessment, Journal of Marketing Research, 25, pp. 186-192, (1988); Hu L., Bentler P.M., Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives, Structural Equation Modeling, 6, 1, pp. 1-55, (1999); Hu P.J., Brown S.A., Thong J.Y.L., Chan F.K.Y., Tam K.Y., Determinants of service quality and continuance intention of online services: The case of eTax, Journal of the American Society for Information Science & Technology, 60, 2, pp. 292-306, (2009); Hui M.K., Thakor M.V., Gill R., The effect of delay type and service stage on consumers' reactions to waiting, Journal of Consumer Research, 24, pp. 269-279, (1998); Jayawardhena C., Wright L.T., Dennis C., Consumers online: Intentions, orientations and segmentation, International Journal of Retail & Distribution Management, 35, 6, pp. 515-526, (2007); Jih W.J., Effects of consumer-perceived convenience on shopping intention in mobile commerce: An empirical study, International Journal of E-Business Research, 3, 4, pp. 33-48, (2007); Jun M., Yang Z., Kim D., Customers' perceptions of online retailing service quality and their satisfaction, International Journal of Quality & Reliability Management, 21, 8, pp. 1149-1174, (2004); Kelley E.J., The importance of convenience in consumer purchasing, Journal of Marketing, 23, pp. 32-38, (1958); Kim B.C., Park Y.W., Security versus convenience? An experimental study of user misperceptions of wireless internet service quality, Decision Support Systems, 53, 1, pp. 1-11, (2012); Koo D.M., Kim J.J., Lee S.H., Personal values as underlying motives of shopping online, Asia Pacific Journal of Marketing and Logistics, 20, 2, pp. 156-173, (2008); Kotler P., Zaltman G., Social marketing: An approach to planned social change, Journal of Marketing, 35, pp. 3-12, (1971); Kwek C.L., Tan H.P., Lau T.C., Investigating the shopping orientations on online purchase intention in the e-commerce environment: A Malaysian study, Journal of Internet Banking and Commerce, 15, 2, pp. 1-22, (2010); Lohse G.L., Spiller P., Electronic shopping, Communications of the ACM, 41, 7, pp. 81-87, (1998); Marsh H.W., Hocevar D., Application of confirmatory factor analysis to the study of self-concept: First- and higher-order factor models and their invariance across groups, Psychological Bulletin, 97, 3, pp. 562-582, (1985); Moeller S., Fassnacht M., Ettinger A., Retaining customers with shopping convenience, Journal of Relationship Marketing, 8, pp. 313-329, (2009); Morganosky M.A., Cude B.J., Consumer response to online grocery shopping, International Journal of Retail & Distribution Management, 28, 1, pp. 17-26, (2000); Parasuraman A., Zeithaml V., Malhotra A., E-S-Qual: A multiple-item scale for assessing electronic service quality, Journal of Service Research, 7, 3, pp. 213-233, (2005); Prasad C.J.S., Aryasri A.R., Determinants of shopper behavior in e-tailing: An empirical analysis, Paradigm, 13, 1, pp. 73-83, (2009); Reimers V., Clulow V., Retail centres: It's time to make them convenient, International Journal of Retail & Distribution Management, 37, 7, pp. 541-562, (2009); Segars A.H., Grover V., Strategic information systems planning success: An investigation of the construct and its measurement, MIS Quarterly, 22, 2, pp. 139-163, (1998); Seiders K., Berry L.L., Gresham L., Attention retailers: How convenient is your convenience strategy?, Sloan Management Review, 49, 3, pp. 79-90, (2000); Seiders K., Voss G.B., Godfrey A.L., Grewal D., SERVCON: Development and validation of a multidimensional service convenience scale, Journal of the Academy Marketing Science, 35, pp. 144-156, (2007); Seiders K., Voss G.B., Grewal D., Godfrey A.L., Do satisfied customers buy more? Examining moderating influences in a retailing context, Journal of Marketing, 69, pp. 26-43, (2005); Smith J.S., Karwan K.R., Markland R.E., An empirical examination of the structural dimensions of the service recovery system, Decision Sciences, 40, 1, pp. 165-186, (2009); Tanskanen K., Yrjola H., Holmstro J., The way to profitable internet grocery retailing - six lessons learned, International Journal of Retail & Distribution Management, 30, 4, pp. 169-178, (2002); Udo G.J., Bagchi K.K., Kirs P.J., An assessment of customers' e-service quality perception, satisfaction and intention, International Journal of Information Management, 30, 6, pp. 481-492, (2010); Wolfinbarger M., Gilly M., eTailQ: Dimensionalizing, measuring and predicting etail quality, Journal of Retailing, 79, 3, pp. 183-198, (2003); Yale L., Venkatesh A., Toward the construct of convenience in consumer research, Advances in Consumer Research, 13, pp. 403-408, (1986); Yang Z., Fang X., Online service quality dimensions and their relationships with satisfaction: A content analysis of customer reviews of securities brokerage services, International Journal of Service Industry Management, 15, 3, pp. 302-326, (2004); Yang Z., Peterson R.T., Customer perceived value, satisfaction, and loyalty: The role of switching costs, Psychology & Marketing, 21, 10, pp. 799-822, (2004); Yang Z., Cai S., Zhou Z., Zhou N., Development and validation of an instrument to measure user perceived service quality of information presenting web portals, Information & Management, 42, 4, pp. 575-589, (2005); Devaraj S., Fan M., Kohli R., Antecedents of B2C channel satisfaction and preference: Validating e-commerce metrics, Information Systems Research, 13, 3, pp. 316-334, (2002); Mittal V., Baldasare P.M., Eliminate the negative: Managers should optimize rather than maximize performance to enhance patient satisfaction, Journal of Health Care Marketing, 16, 3, pp. 24-31, (1996)","Z. Yang; Department of Marketing, City University of Hong Kong, Hong Kong, Hong Kong; email: mkzyang@cityu.edu.hk",null,"Emerald Group Publishing Ltd.",{"$nulls":5},1.7575818E7,null,null,null,"English","J. Serv. Manage.","Article","Final",null,"Scopus","2-s2.0-84878230893"]
["Hu Y.-C.; Chiu Y.-J.; Hsu C.-S.; Chang Y.-Y.","Hu, Yi-Chung (57138742500); Chiu, Yu-Jing (7202775724); Hsu, Chung-Sheng (56879606200); Chang, Yu-Ying (56415265600)","57138742500; 7202775724; 56879606200; 56415265600","Identifying Key Factors for Introducing GPS-Based Fleet Management Systems to the Logistics Industry",2015.0,"Mathematical Problems in Engineering",2015.0,null,413203.0,null,null,null,40.0,"10.1155/2015/413203","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84942771699&doi=10.1155%2f2015%2f413203&partnerID=40&md5=f01d73362f445d0a03fd1d73b028b009","Department of Business Administration, Chung Yuan Christian University, Chung Li District, Taoyuan City, 32023, Taiwan","Hu Y.-C., Department of Business Administration, Chung Yuan Christian University, Chung Li District, Taoyuan City, 32023, Taiwan; Chiu Y.-J., Department of Business Administration, Chung Yuan Christian University, Chung Li District, Taoyuan City, 32023, Taiwan; Hsu C.-S., Department of Business Administration, Chung Yuan Christian University, Chung Li District, Taoyuan City, 32023, Taiwan; Chang Y.-Y., Department of Business Administration, Chung Yuan Christian University, Chung Li District, Taoyuan City, 32023, Taiwan","The rise of e-commerce and globalization has changed consumption patterns. Different industries have different logistical needs. In meeting needs with different schedules logistics play a key role. Delivering a seamless service becomes a source of competitive advantage for the logistics industry. Global positioning system-based fleet management system technology provides synergy to transport companies and achieves many management goals such as monitoring and tracking commodity distribution, energy saving, safety, and quality. A case company, which is a subsidiary of a very famous food and retail conglomerate and operates the largest shipping line in Taiwan, has suffered from the nonsmooth introduction of GPS-based fleet management systems in recent years. Therefore, this study aims to identify key factors for introducing related systems to the case company. By using DEMATEL and ANP, we can find not only key factors but also causes and effects among key factors. The results showed that support from executives was the most important criterion but it has the worst performance among key factors. It is found that adequate annual budget planning, enhancement of user intention, and collaboration with consultants with high specialty could be helpful to enhance the faith of top executives for successfully introducing the systems to the case company. © 2015 Yi-Chung Hu et al.",null,"Budget control; Competition; Energy conservation; Global positioning system; Logistics; Competitive advantage; Consumption patterns; Fleet management system; Logistics industry; Management goals; Monitoring and tracking; Seamless services; Transport companies; Fleet operations",{"$nulls":6},"Crainic T.G., Laporte G., Fleet Management and Logistics, (1998); Mele J., Fleet management systems: The future is here, Fleet Owner, 100, 8, (2005); McLoad T., Fleetmanagement systems:the future is here, Fleet Owner, (2005); Heijden Der R.Van, Marchau V., Innovating road traffic management by ITS: A future perspective, International Journal of Technology, Policy and Management, 2, 1, pp. 20-39, (2002); Sorensen C.G., Bochtis D.D., Conceptual model of fleet management in agriculture, Biosystems Engineering, 105, 1, pp. 41-50, (2010); Mintsis G., Basbas S., Papaioannou P., Taxiltaris C., Tziavos I.N., Applications of GPS technology in the land transportation system, European Journal of Operational Research, 152, 2, pp. 399-409, (2004); Nandan N., Online grid-based dynamic arrival time prediction using GPS locations, International Journal OfMachine Learning and Computing, 3, 6, pp. 516-519, (2013); Lu J., Chen G., Atime-varying complex dynamical network model and its controlled synchronization criteria, IEEE Transactions on Automatic Control, 50, 6, pp. 841-846, (2005); Lu J., Yu X., Chen G., Cheng D., Characterizing the synchronizability of small-world dynamical networks, IEEE Transactions on Circuits and Systems. 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Hu Y.C., Wang J.H., Hung L.P., Evaluating the e-service quality of microblogging, Proceedings of the International Symposiumon the Analytic Hierarchy Process,Naples, (2011); Lin C.-L., Hsieh M.-S., Tzeng G.-H., Evaluating Vehicle Telematics System by using a novel MCDM techniques with dependence and feedback, Expert Systems with Applications, 37, 10, pp. 6723-6736, (2010); Wu W.-W., Choosing knowledge management strategies by using a combined ANP and DEMATEL approach, Expert Systems with Applications, 35, 3, pp. 828-835, (2008); Yang J.L., Tzeng G.-H., An integrated MCDM technique combined with DEMATEL for a novel cluster-weighted with ANP method, Expert Systems with Applications, 38, 3, pp. 1417-1424, (2011); Tzeng G.-H., Huang J.-J., Multiple attribute decision making: Methods and applications, CRC Press, (2011); Hern C.Y., Schedule planning for the development of intelligent transportation systems (ITS) in Taiwan area, Transportation Planning Journal, 29, 1, pp. 109-142, (2000); Chiu Y.J., Tzeng G.H., Evaluating intelligent transportation security systems using MCDM, Proceedings of the 30th International Conference on Computers and Industrial Engineering, pp. 131-136, (2002); Cheung B.K.S., Choy K.L., Li C.L., Shi W., Tang J., Dynamic routing model and solution methods for fleet management with mobile technologies, International Journal of Production Economics, 113, 2, pp. 694-705, (2008); Adam E.E., Ebert R.J., Production and OperationsManagement: Concepts,Models and Behaviour, (1991); Definition of global positioning systems, The American Heritage Dictionary, Houghton Mifflin, (2000); Drane C.R., Rizos C., Positioning Systems in Intelligent Transportation Systems, (1998); Zhao Y., Vehicle Location and Navigation Systems, (1997); Theiss A., Yen D.C., Ku C.-Y., Global positioning systems: An analysis of applications, current development and future implementations, Computer Standards and Interfaces, 27, 2, pp. 89-100, (2005); Karp J., GPS in interstate trucking in Australia: Intelligence, surveillance-or compliance tool, IEEE Technology and Society Magazine, 33, 2, pp. 47-52, (2014); Auernhammer H., Precision farming-the environmental challenge, Computers and Electronics in Agriculture, 30, 1-3, pp. 31-43, (2001); Yang Y.P.O., Shieh H.M., Leu J.D., Tzeng G.H., A novel hybrid MCDM model combined with DEMATEL and ANP with applications, International Journal of Operations Research, 5, 3, pp. 160-168, (2008); Hu Y.-C., Tsai J.-F., Backpropagation multi-layer perceptron for incomplete pairwise comparison matrices in analytic hierarchy process, Applied Mathematics and Computation, 180, 1, pp. 53-62, (2006); Xu Z., Wei C., Consistency improving method in the analytic hierarchy process, European Journal of Operational Research, 116, 2, pp. 443-449, (1999); Martilla J.A., James J.C., Importance-performance analysis, Journal of Marketing, 41, 1, pp. 77-79, (1977); Chen C.C., Chen K.C., Chen J.R., The study of key success factors of ERP implementation in the small business, Journal of Chinese Economic Research, 10, 2, pp. 31-42, (2012); Chiou H.Y., Analyses of the Critical Success Factors on the Implementation of ERP System: A Study in the Point of ERP Project Manager, (2010); Huang J.H., Apply Analytic Network Process to Explore the Critical Success Factors for Enterprises Implementing ERP Systems, (2012); Huang S.M., Chang S.I., Su K.H., Critical success factors for implementing BS7799 information security management system-based on petrochemical industry, Journal of Information Management, 13, 2, pp. 171-192, (2006); Lee H.C., Applying Grey Analytic Hierarchy Process to Analyze the Critical Success Factors of ERP, (2007); Lin H.C., Exploration of Key Successful Factors of ERP Implementation for Small and Medium Firms, (2010); Liu C.M., Critical Success Factors Research of Information System of Military Organization Implementation: Example of Army Training and Supply Systems, (2012); Pai J.C., Lee G.G., Tseng W.G., Chang Y.L., Organizational, technological and environmental factors affecting the implementation of ERP systems: Multiple-case study in Taiwan, Journal of Electronic Commerce Studies, 5, 2, pp. 175-195, (2007); Sheu I.H., Influence Enterprise Resources Plan System CSF (Critical Success Factor) Implement Success-from Consultant Discussion Viewpoint, (2006)",null,null,"Hindawi Publishing Corporation",{"$nulls":5},"1024123X",null,null,null,"English","Math. Probl. Eng.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-84942771699"]
["Sekar K.R.; Ravichandran K.S.; Jangiti S.; Sethuraman J.","Sekar, K.R. (55497370700); Ravichandran, K.S. (7102687553); Jangiti, SaiKishor (56370626000); Sethuraman, J. (55216681600)","55497370700; 7102687553; 56370626000; 55216681600","Best electronic shopping technique (BEST) - An AdHoc component using bat model",2015.0,"ARPN Journal of Engineering and Applied Sciences",10.0,18.0,null,8097.0,8107.0,10.0,0.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-84944936922&partnerID=40&md5=cf12294b05809f16daa4e759012fcc94","School of Computing, SASTRA University, India","Sekar K.R., School of Computing, SASTRA University, India; Ravichandran K.S., School of Computing, SASTRA University, India; Jangiti S., School of Computing, SASTRA University, India; Sethuraman J., School of Computing, SASTRA University, India","The rapid development of internet and technology made internet based virtual electronic shops come true. The moral stuff of online shopping is \"Avail anything from anywhere at any time\". Online shopping paves a sophisticated way for customers to buy the commodity in less time. It helps the customers to know the feedback about the commodity that makes them to take corrective decisions. In addition to that, it serves the privacy to the customers as the traditional way does not suit this. Comparison shopping have emerged a new path to the online shopping. It assists the customers to compare the 'N' commodity simultaneously. However, umpteen number of online shops exists that makes a gap, since no website contribute adequate solution to meet the request of the customers about other aspects of commodity such as warranty, delivery days, review rating, quantity, EMI, COD, shipping cost, compare option etc. In this paper we are proposing BEST - Best Electronic Shopping Technique with a new model called TIM (Training Set - Interface - Model) which is imbibed, considering important attributes from top 20 popular sites to perform evaluation based on Crisp and Fuzzy methodologies. At the same time, details will be hunted and filtered by their demands and sorted them accordingly. Arrived results were obtained using variance, chi square, ANOVA and Theil indexing. As a consequence the customers will be able to yield commodity without spending more time and effort in visiting numerous number of sites. © 2006-2015 Asian Research Publishing Network (ARPN).","ANOVA classification; Chi squared distribution; Fuzzy K-Means; K-Medoid; Variance and theilindex",{"$nulls":7},"Lin W.-S., Cassaigne N., Huan T.-C., A framework of online shopping support for information recommendations, Expert systems with applications, 37, pp. 6874-6884, (2010); Ganu G., Kakodkar Y., Marian A., Improving the quality of predictions using textual information in online user reviews, Information Systems, 38, 1, pp. 1-15, (2013); Leea M.K.O., Shi N., Cheung C.M.K., Lim K.H., Sia C.L., Consumer's decision to shop online: The moderating role of positiveinformational social influence, Elsevier, Information and Management, 48, pp. 185-191, (2011); Liao S.-H., Chen Y.-J., Lin Y.-T., Mining customer knowledge to implement online shopping and home delivery for hypermarkets, Elsevier, 38, pp. 3982-3991, (2011); Velasquez J.D., Dujovne L.E., L'Huiller G., Extracting Significant Website Key Objects: A semantic web mining approach, Engineering Applications of Artificial Intelligence, 24, 8, pp. 1532-1541, (2011); Sekukcebi, A quality evaluation model for the design quality of online shopping websites, Electronic Commerce Research and Application, 12, 2, pp. 124-135, (2013); Lim G.G., Kang J.Y., Lee J.K., Lee D., Rule based personalized comparison shopping including delivery cost, Electronic Commerce Research and Applications, pp. 637-649, (2011); Chang Y.S., Lee K.J., A Comparison shopping optimization model based on supplier's pricing contexts, Expert systems with Applications, pp. 5736-5744, (2010); Liu L., Fong S., Evaluation of ECommerce websites by Multi-Criteria Decision Analysis, IADIS International Conference e-society, (2011); Labroche N., Online fuzzy medoid based clustering algorithm, Neurocomputing, pp. 141-150, (2013); Mei J.-P., Lihuichen, Fuzzy relational clustering around medoids: A Unified View, Fuzzy Sets and Systems, pp. 44-56, (2011); Chiou W.-C., Lin C.-C., Perng C., A Strategic framework for website evaluation based on review of the literature from 1995-2006, Information and Management, 47, pp. 282-290, (2010); Shao K., Cheng Y., E-Commerce Comparison-Shopping Model of Neural Network Based on Ant Colony Optimization, Advances in Wireless Networks and Information SystemsLecture Notes in Electrical Engineering, 72, pp. 397-404, (2010); Lichen F.W., Preference based clustering reviews for augmenting e-commerce recommendation, Knowledge-Based Systems, 50, pp. 44-59, (2013); Wang L., Wang H., Zhao H., E-Commerce Website Credible Model based on Fuzzy Grey Method.Computer Science and Automation Engineering (CSAE), IEEE International Conference on, 3, pp. 769-772, (2012); Skabar A., Abdalgader K., Clustering SentenceLevel Text Using a Novel Fuzzy Relational Clustering Algorithm, IEEE Transactions on knowledge and data engineering, 25, 1, pp. 62-75, (2013); Bafna K., Toshniwal D., Feature based summarization of customer's Reviews of online Products, Procedia Computer Science, 22, pp. 164-171, (2013); Wu M.-L., Chang C.H., Liu R., Fan T., Aggregate two way co-clustering of ads and user analysis for online advertisements, Computer Symposium (ICS),IEEE, pp. 587-593, (2010); Zhao D., Evaluating Customer perceived value of Busineess to Conusumer websites from the aspect of online consumers, Business Intelligence and Financial Engineering (BIFE),IEEE, pp. 235-238, (2011); Storto C.I., Evaluating e-commerce websites cognitive efficiency: An integrative framework based on data development analysis, Applied Ergonomics, 44, 6, pp. 1004-1014, (2013)",null,null,"Asian Research Publishing Network",{"$nulls":5},1.8196608E7,null,null,null,"English","ARPN J. Eng. Appl. Sci.","Article","Final",null,"Scopus","2-s2.0-84944936922"]
["Kaur G.; Khanam Quareshi T.","Kaur, Gurjeet (57213507301); Khanam Quareshi, Tahira (56916158700)","57213507301; 56916158700","Factors obstructing intentions to trust and purchase products online",2015.0,"Asia Pacific Journal of Marketing and Logistics",27.0,5.0,null,758.0,783.0,25.0,41.0,"10.1108/APJML-10-2014-0146","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84944899411&doi=10.1108%2fAPJML-10-2014-0146&partnerID=40&md5=efad1123d693481f247ad243ced340e0","Department of Commerce, University of Jammu, Jammu, India","Kaur G., Department of Commerce, University of Jammu, Jammu, India; Khanam Quareshi T., Department of Commerce, University of Jammu, Jammu, India","Purpose – The purpose of this paper is to explore reasons for not buying products through online. The study also tries to explain the relationship between intentions to trust (IT) and online purchase intentions. Design/methodology/approach – Data were collected through well-structured instrument, distributed to 226 students of Masters of Business Administration and Masters of Computer Applications departments of a north Indian University. Confirmatory Factor Analysis and Structural Equation Modelling were used to analyse the data and to test the formulated hypotheses. Findings – The results of the study highlight that 90 per cent of the respondents are aware about online shopping sites but only 38 per cent are online buyers of various products. Major reasons for not shopping are lack of security, absence of physical examination and testing of products, lack of product’s complete information, unattractive visual displays and layouts, etc. However, it is observed that nearly 79 per cent respondents have positive intentions to buy products online in near future. Research limitations/implications – There is a need to study actual online buying behaviour. Also, models like Technology Acceptance Model and Diffusion of Innovation have not been studied. As the study was confined to students only, it can be replicated to other age group consumer segments and extended to other emerging economies as well. There is a need to take into consideration some other important dimensions in the future studies, namely, predictability, familiarity, third party certification, attitude, ease of use, perceived risk, etc., for the better analysis of behaviour. Practical implications – E-vendors must properly implement money back guarantee schemes when there is non-delivery of ordered goods, provide dispute resolution system, instil confidence in customers, highlight security, privacy policy, display contacts details, etc., to increase customers’ IT and purchase products online. Originality/value – The paper identifies the factors that obstruct customer to purchase products online. More particularly, in Indian context the present study makes valuable contribution as the Indians have been reported to be techno phobic and uncertainty avoidant. © 2015, Emerald Group Publishing Limited.","Firm’s image; Intentions to trust; Propensity to trust; Purchase intentions; Uncertainty avoidance",{"$nulls":7},"Atkin D., Jeffres L., Neuendorf K., Understanding internet adoption as telecommunications behaviour, Journal of Broadcasting and Electronic Media, 42, 4, pp. 475-490, (1998); Ba S., Pavlou P.A., Evidence of the effects of trust building technology in electronic markets: price performance and buyer behaviour, MIS Quarterly, 26, 3, pp. 243-268, (2002); Bagozzi R.P., Edwards J.F., A general approach to construct validation in organisational psychology: application to the measurement of work values, Organizational Research Methods, 1, 1, pp. 45-87, (1998); Bagozzi R.P., Yi Y., On the evaluation of structural equation models, Academy of Marketing Science, 16, 1, pp. 76-94, (1998); 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Pavlou P.A., Dimoka A., The nature and role of feedback text comments in online marketplaces: implications for trust building, price premiums, and seller differentiation, Information System Research, 17, 4, pp. 392-414, (2006); Schreiber J.B., Nora A., Stage F.K., Barlow E.A., King J., Reporting structural equation modelling and confirmatory factor analysis results: a review, Journal of Educational Research, 99, 6, pp. 323-337, (2006)","G. Kaur; Department of Commerce, University of Jammu, Jammu, India; email: gurjeetkaur18@gmail.com",null,"Emerald Group Holdings Ltd.",{"$nulls":5},1.3555855E7,null,null,null,"English","Asia Pac. J. Mark. Logist.","Article","Final",null,"Scopus","2-s2.0-84944899411"]
["Abid S.H.; Li Z.; Li R.; Waleed J.","Abid, Saad Hameed (56566248700); Li, Zhiyong (57020064900); Li, Renfa (7404723125); Waleed, Jumana (56380595300)","56566248700; 57020064900; 7404723125; 56380595300","Heat based odors delivery apparatus for interactive game playing",2015.0,"International Journal of Multimedia and Ubiquitous Engineering",10.0,5.0,null,331.0,342.0,11.0,5.0,"10.14257/ijmue.2015.10.5.31","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84932083075&doi=10.14257%2fijmue.2015.10.5.31&partnerID=40&md5=3a71a89b267b93f352ba764f9f0bd75f","College of Computer Sciences and Electronic Engineering, Hunan University, Changsha, 410082, Hunan, China; AL-Mansour University College, Al-Andalus square, Baghdad, Iraq; School of information science and engineering, Central South University, Changsha, 410083, China","Abid S.H., College of Computer Sciences and Electronic Engineering, Hunan University, Changsha, 410082, Hunan, China, AL-Mansour University College, Al-Andalus square, Baghdad, Iraq; Li Z., College of Computer Sciences and Electronic Engineering, Hunan University, Changsha, 410082, Hunan, China; Li R., College of Computer Sciences and Electronic Engineering, Hunan University, Changsha, 410082, Hunan, China; Waleed J., School of information science and engineering, Central South University, Changsha, 410083, China","Scent delivery systems or what are known as olfactory displays has been the most recent trend in human computer interaction, control and automation, virtual reality, augmented reality, e-commerce and many other fields in the computer world. These devices have the ability to generate smell combinations for some digital items in the computer virtual world. The idea is to deliver additional perception (olfactory perception) to the user to enrich his/her indulgence while interacting with the computer. The proposed olfactory display is similar to this concept but greatly differ in many aspects, using laser based atomization method to produce enough sudden heat to generate odors that cannot be generated using chemical materials these odors are smoke, gun powder, wood milling, cigarettes smoking, plastic melting and Incense. All olfactory displays researchers avoid involving these types of odors in their studies due to the difficulty of the generation and control of such odors and the absence of their correct and precise generation using chemical materials. The proposed system will provide a way of generating such odors while interactive game is being played by a user with minimum impact on the environment to avoid adaption to the user's olfactory system and polluting the environment that the user occupies. © 2015 SERSC.","Games; Odor; Olfactory displays; Scent; Smell","Augmented reality; Digital devices; Human computer interaction; Odors; Virtual reality; Chemical materials; Control and automation; Games; Impact on the environment; Interactive games; Olfactory display; Scent; Smell; Computer control systems",{"$nulls":6},"Nakamoto T., Minh H.P.D., Improvement of Olfactory Display Using Solenoid Valves, Proc. IEEE Virtual Reality, pp. 179-186, (2007); Nakamoto T., Kinoshita M., Murakami K., Yossiri A., Demonstration of Improved Olfactory Display using Rapidly-Switching Solenoid Valves, \", IEEE Virtual Reality Conference, Lafayette, LA, pp. 301-302, (2009); Nakamoto T., Yoshikawa K., Movie with Scents Generated by Olfactory Display Using Solenoid Valves, IEEE Virtual Reality Conference, pp. 291-292, (2006); Matsukura H., Yoshida H., Ishida H., Saitoh A., Nakamoto T., Odor Presentation with a Vivid Sense of Reality: Incorporating Fluid Dynamics Simulation into Olfactory Display, IEEE Virtual Reality Conference, Lafayette, LA, pp. 295-296, (2009); Hirose M., A Study of Olfactory Display, Proc. Of the Virtual Reality Society Of Japan 2Nd Annual Conference, in Japanese, pp. 155-158, (1997); Tanikawa T., Tanaka S., Sakikawa S., Hirose M., A Study of Olfactory Display, Proc. Of the Virtual Reality Society Of Japan 5Th Annual Conference, pp. 193-196, (2000); Mochizuki A., Amada T., Sawa S., Takeda T., Motoyashiki S., Kohyama K., Imura M., Chihara K., Fragra: A Visual-Olfactory VR Game, ACM SIGGRAPH Sketches & Applications, (2004); Gobel M., Trends in VR Display & Interaction Technology, IEEE Virtual Reality Alexandria, pp. 122-125, (2006); McCarthy R., Scent-Emitting Systems, (1984); Ariyakul Y., Nakamoto T., Olfactory Display Using a Miniaturized Pump and a SAW Atomizer for Presenting Low-volatile Scents, IEEE Virtual Reality Conference, pp. 193-194, (2011); Kadowaki A., Sato J., Bannai Y., Okada K., Presentation Technique of Scent to Avoid Olfactory Adaptation, IEEE 17Th International Conference on Artificial Reality and Telexistence, pp. 97-104, (2007); Kim S.M., Sung M.Y., A Haptic Gaming System for Tactile Textures and 3D Shapes Discrimination, International Journal of Multimedia and Ubiquitous Engineering, 9, 9, pp. 319-334, (2014); Nizar Baharom S., Tan W.H., Idris M.Z., Emotional Design for Games: A Framework for Player-Centric Approach in the Game Design Process, International Journal of Multimedia and Ubiquitous Engineering, 9, 10, pp. 387-398, (2014)",null,null,"Science and Engineering Research Support Society",{"$nulls":5},1.975008E7,null,null,null,"English","Int. J. Multimedia Ubiquitous Eng.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-84932083075"]
["Yang Q.; Hu X.; Cheng Z.; Miao K.","Yang, Qinghong (56227486900); Hu, Xiangquan (56226401900); Cheng, Zhichao (47360970800); Miao, Kang (56548431900)","56227486900; 56226401900; 47360970800; 56548431900","Machine Learning Based Prediction and Prevention of Malicious Inventory Occupied Orders",2014.0,"International Journal of Mobile Computing and Multimedia Communications",6.0,4.0,null,56.0,72.0,16.0,0.0,"10.4018/IJMCMC.2014100104","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84961385624&doi=10.4018%2fIJMCMC.2014100104&partnerID=40&md5=308dae33f46f04b96ffa0e1c6c949e23","School of Economics and Management, Beihang University, Beijing, China; School of Software, Beihang University, Beijing, China","Yang Q., School of Economics and Management, Beihang University, Beijing, China; Hu X., School of Software, Beihang University, Beijing, China; Cheng Z., School of Economics and Management, Beihang University, Beijing, China; Miao K., School of Software, Beihang University, Beijing, China","MIOOs are orders created temporarily for the purpose of occupying the inventories of sellers. MIOOs disrupt normal business activities and harm both sellers and consumers. This study aims to determine the best practice and model of the technical solutions that can effectively and systematically limit malicious inventory occupied orders (MIOOs), using the methods of analytical mining and case studies. This work contains three contributions. Firstly, this work solves MIOOs problem by using machine learning technology. The result of the study indicates that 93% of MIOOs from the sample data are actually predictable and preventable. Secondly, this work presents a methodology of solving MIOOs problem which can be applied by other companies. The methodology in this paper consists of four major steps, namely doing statistics concerning MIOOs, using logistic regression algorithm to train a mode, optimizing the model, and applying the model. Finally, this work finds unique features of MIOOs, and they can help better understanding the behind logic of MIOO producers. Copyright © 2014, IGI Global.","Beihang University; E-commerce; Feature Matrix; Logistic Regression; Machine Learning; Malicious Inventory; Qinghong Yang; Xiangquan Hu","Artificial intelligence; Electronic commerce; Regression analysis; Beihang University; Feature matrices; Logistic regressions; Malicious Inventory; Qinghong Yang; Xiangquan Hu; Learning systems",{"$nulls":6},"Almendra V., Enachescu D., A fraudster in a haystack: Crafting a classifier for nondelivery fraud prediction at online auction sites, Proceedings of the 2012 14th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC), pp. 233-239, (2012); Bell T.B., Carcello J.V., A decision aid for assessing the likelihood of fraudulent financial reporting. 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Proceedings of the 2010, ACM Symposium on Applied Computing, pp. 1454-1455, (2010); Mehdi M., Zair S., Anou A., Bensebti M., A Bayesian networks in intrusion detection systems, Journal of Computer. Science, 3, 5, pp. 259-265, (2007); Ngai E.W.T., Hu Y., Wong Y.H., Chen Y., Sun X., The application of data mining techniques in financial fraud detection: A classification framework and an academic review of literature, Decision Support Systems, 50, 3, pp. 559-569, (2011); Owusu-Ansah S., Moyes G.D., Babangida Oyelere P., Hay D., An empirical analysis of the likelihood of detecting fraud in New Zealand, Managerial Auditing Journal, 17, 4, pp. 192-204, (2002); Panigrahi S., Kundu A., Sural S., Majumdar A.K., Credit card fraud detection: A fusion approach using Dempster-Shafer theory and Bayesian learning, Information Fusion, 10, 4, pp. 354-363, (2009); Phua C., Lee V., Smith K., Gayler R., A Comprehensive Survey of Data Mining-based Fraud Detection Research, (2010); Sebring M.M., Shellhouse E., Hanna M., Whitehurst R., Expert systems in intrusion detection: A case study, Proceedings of the 11th National Computer Security Conference, 7, pp. 4-81, (1988); Spathis C.T., Detecting false financial statements using published data: Some evidence from Greece, Managerial Auditing Journal, 17, 4, pp. 179-191, (2002); Teng H.S., Chen K., Lu S.C., Adaptive real-time anomaly detection using inductively generated sequential patterns, Proceedings of the IEEE Computer Society Symposium on Research in Security and Privacy '90, pp. 278-284, (1990); Viaene S., Dedene G., Derrig R.A., Auto claim fraud detection using Bayesian learning neural networks, Expert Systems with Applications, 29, 3, pp. 653-666, (2005); Viaene S., Derrig R., Dedene G., A case study of applying boosting Naive Bayes to claim fraud diagnosis, IEEE Transactions on Knowledge and Data Engineering, 16, 5, pp. 612-620, (2004); Yang Q., Hu X., Cheng Z., Miao K., Zheng X., Based Big Data Analysis of Fraud Detection for Online Transaction Orders, pp. 98-106, (2014); Yuan J., Yuan C., Deng X., The effects of manager compensation and market competition on financial fraud in public companies: An empirical study in China, International Journal of Management, 25, 2, (2008); Zhang H., Lin Z., Hu X., The effectiveness of the escrow model: An experimental framework for dynamic online environments, Journal of Organizational Computing and Electronic Commerce, 17, 2, pp. 119-143, (2007)",null,null,"IGI Global",{"$nulls":5},1.9379412E7,null,null,null,"English","Int. J.Mob. Comput. Multimedia Commun.","Article","Final",null,"Scopus","2-s2.0-84961385624"]
["Joris J.J.; Travassos X.L.; Figueiredo P.S.","Joris, Jair Jairo (56049830000); Travassos, X. Lucas (12789881400); Figueiredo, Paulo S. (24173055400)","56049830000; 12789881400; 24173055400","A discrete simulation model for incorporating RFID technology into the Brazilian Postal Service",2013.0,"International Journal of Services Operations and Informatics",8.0,1.0,null,59.0,77.0,18.0,2.0,"10.1504/IJSOI.2013.059377","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84894635512&doi=10.1504%2fIJSOI.2013.059377&partnerID=40&md5=241975afcb0022fa818baa43471771bc","SENAI CIMATEC, Salvador, Bahia 41650-010, Avenida Orlando Gomes, 1845 Piatã, Brazil; Universidade Federal de Santa Catarina, Santo-Antônio, 89218000 - Joinville, SC, Rua Presidente Prudente Moraes Ate 1326 Lado par, Brazil","Joris J.J., SENAI CIMATEC, Salvador, Bahia 41650-010, Avenida Orlando Gomes, 1845 Piatã, Brazil; Travassos X.L., Universidade Federal de Santa Catarina, Santo-Antônio, 89218000 - Joinville, SC, Rua Presidente Prudente Moraes Ate 1326 Lado par, Brazil; Figueiredo P.S., SENAI CIMATEC, Salvador, Bahia 41650-010, Avenida Orlando Gomes, 1845 Piatã, Brazil","The market of logistic operators in the segment of parcel delivery in Brazil has grown considerably in the last few years. This growth is caused mainly by e-commerce transactions. Companies that excel in this business offer services that enable traceability of objects and near real-time availability of information to customers. This research aims to study the current process for receiving and handling mail pouches at the Brazilian Postal Service (ECT), with the objective of verifying the technical viability using RFID - Radio Frequency Identification technology. Discrete simulation analysis is used for this purpose. It was found that ECT currently does not offer full traceability of its products. The applicability of RFID technology is determined. Based on the results of the simulations, advantages of the use of RFID tags are discussed. Copyright © 2013 Inderscience Enterprises Ltd.","Discrete-events simulation; Post office; Postal service; RFID; Services operations; Simulations; Technology management; Tracing of postal objects; Tracking","Post offices; Postal services; Surface discharges; Discrete events simulation; Services operations; Simulations; Technology managements; Tracing of postal objects; Radio frequency identification (RFID)",{"$nulls":6},"Araujo Filho F.W.G., Travassos X.L., Figueiredo P.S., A Financial Viability Analysis of A RFID System in the Microcomputer Supply Chain: Are There Any Profits?, (2012); Balocco R., Miragliotta G., Perego A., Tumino A., RFID adoption in the FMCG supply chain: An interpretative framework, Supply Chain Management: An International Journal, 16, 5, pp. 299-315, (2011); Banks J., Carson Ii J.S., Nelson B.L., Discrete-event System Simulation, (1996); Chow H.K.H., Choy K.L., Lee W.B., Lau K.C., Design of a RFID case-based resource management system for warehouse operations, Expert Systems with Applications, 30, 4, pp. 561-576, (2006); Administrative Reports, (2010); Annual Business Reports: 1995 to 2007, (2007); Strategic Plan 2000-2005, (1999); Strategic Plan 2004-2007; Strategic Plan 2008-2017; Evangelista P., Sweeney E., Technology usage in the supply chain: The case of small 3PLs, The International Journal of Logistics Management, 17, 1, pp. 55-74, (2006); Evangelista P., Mogre R., Perego A., Raspagliesi A., Sweeney E., A survey based analysis of IT Adoption and 3PLs' performance, Supply Chain Management: An International Journal, 17, 2, pp. 172-186, (2012); Forrester J.W., Senge P.M., Tests for building confidence in system dynamics models, TIME Studies in the Management Science, 14, pp. 209-228, (1980); Gaukler G.M., Ozer O., Hausman W., RFID and Product Progress Information: Improved Dynamic Ordering Policies, (2004); Heinrich C., RFID and beyond, (2005); Kach A., Borzabad A.F., Use of RFID technology to overcome inefficiencies in the supply chain: An analysis of Renault's operations in Iran, International Journal of Management, 28, pp. 365-378, (2011); Kinley J.D., RFID ROI, (2004); News Briefs IT Professional Magazine, 6-7, pp. 8-9, (2005); Jones E.C., Riley M.W., Franca R., Reigle S., Case study: The engineering economics of RFID in specialized manufacturing, Engineering Economist, 52, 3, pp. 285-303, (2007); Miragliotta G., Perego A., Tumino A., A quantitative model for the introduction of RFID in the fast moving consumer goods supply chain, International Journal of Operations and Production Management, 29, 10, pp. 1049-1082, (2009); Park J.-H., Park J.-H., Postal RFID application model and performance, ETRI Journal, 28, 3, pp. 405-408, (2006); Mogre R., Gadh R., Chattopadhyay A., Using survey data to design a RFID centric service system for hospitals, Service Science, 1, 3, pp. 189-206, (2009); Robinson S., Simulation-The Practice of Model Development and Use, (2004); Stambaugh C.T., Carpenter F.W., Wireless innovation in inventory monitoring and accounting, Strategic Finance, 91, 6, pp. 35-40, (2009); Sterman J.D., Business Dynamics: Systems Thinking and Modeling for A Complex World, (2000); Wagner S.M., Sutter R., A qualitative investigation of innovation between third-party logistics providers and customers, International Journal of Production Economics, 140, 2, pp. 944-958, (2012); Fosso Wamba S., Lefebvre L.A., Bendavid Y., Lefebvre E., Exploring the impact of RFID technology and the EPC network on mobile B2B eCommerce: A case study in the retail industry, International Journal of Production Economics, 112, 2, pp. 614-629, (2008); Whang S., Timing of RFID adoption in a supply chain, Management Science, 56, 2, pp. 343-355, (2010); Zhang X.-D., Yue S.-J., Wang W.-M., The review of RFID applications in global postal and courier services, Journal of China Universities of Posts and Telecommunications, 13, 4, pp. 106-110, (2006)","P.S. Figueiredo; SENAI CIMATEC, Salvador, Bahia 41650-010, Avenida Orlando Gomes, 1845 Piatã, Brazil; email: paulo_s_figueiredo@hotmail.com",null,"Inderscience Publishers",{"$nulls":5},"1741539X",null,null,null,"English","Int. J. Serv. Oper. Inf.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-84894635512"]
["Rajagopal D.","Rajagopal, Dr (23025659500)",2.30256595E10,"Architecting MexGro: introducing online experience for shopping ethnic products",2013.0,"Emerald Emerging Markets Case Studies",3.0,5.0,null,1.0,11.0,10.0,1.0,"10.1108/EEMCS-10-2013-0196","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85080988449&doi=10.1108%2fEEMCS-10-2013-0196&partnerID=40&md5=83a4098c01a8f1187c4e2f8c9efcbbe4","Instituto Tecnológico y de Estudios Superiores de Monterrey, Mexico City, Mexico","Rajagopal D., Instituto Tecnológico y de Estudios Superiores de Monterrey, Mexico City, Mexico","Subject area: Marketing plan; virtual shopping; consumer behavior. Study level/applicability: Undergraduate. Case overview: This case discusses the e-commerce plan of new online grocery company in Mexico, MexGro, which is planning to emerge as low-cost outlet as compared to the brick-and-mortar establishments in the market. MexGro is an online grocer with a round-the-clock call center to process phone-based orders and to provide customer support. The grocery online company is aimed at setting up a virtual grocery shop by the name of MexGro S.A de C.V to serve cross-cultural products to the Hispanic and Asian communities in Mexico. The MexGro, being a virtual shop, need not pay for checkout clerks; display cases, or parking lots, online grocers can drop prices below those of retail stores and remain profitable. This case explores online consumer-shopping behavior, the economics of online and offline grocery distribution, and the challenges of uniting a pure information business with a mundane package delivery service. Expected learning outcomes: This case may be discussed towards learning developing effective online marketing planning strategy for the niche markets. The specific learning objectives of the case are: to analyze the virtual marketing planning constituents for developing customer-centric marketing within a niche and explore the possibilities of sustainable business growth to encourage strategic thinking towards developing online marketing plan and develop effective communications among the consumers and to address the critical online planning issues, such as what are the prospects for grocery shopping on the internet. The case allows students to grapple with the strategic and tactical decisions on planning for the online marketing companies. Students will also become familiar with key questions/issues raised by the various executives of the company in formulating the online marketing plan for ethnic grocery in a niche business environment: the case challenges students to think about how online grocer creates the most value for customers and how grocer will likely be able to overcome the competition from the brick-and-mortar grocers. Should Wal-Mart be aggressive in launching its grocery brand? The case raises issues to debate on how the organizational and system decisions are faced by managers in developing a virtual shopping culture in Mexico as the company has the goal to move among more efficient competitors in the supermarket industry, and How the online marketing plan can be implemented within a niche. This case study would take students through the rise of a private brand to the strategies of its sustainability in the competitive marketplace. This case illustrates the importance of using new variables in developing an effective marketing plan when companies reinforce their products in the niche markets. The discussion in the case allows students an opportunity to evaluate online marketing planning and their brands in a niche as well as in a competitive marketplace. Supplementary materials: Teaching notes are available for educators only. Please contact your library to gain login details or email support@emeraldinsight.com to request teaching notes. © 2013, Emerald Group Publishing Limited.","Effective communication; Online marketing",{"$nulls":7},"Palmer J., Kallio J., Saarinen T., Tinnila M., Tuunainen V.K., van Heck E., Online grocery shopping around the world: examples of key business models, Communications of the Association for Information Systems, 4, pp. 1-44, (2000); Porter M.E., Strategy and the internet, Harvard Business Review, 79, 3, pp. 63-78, (2001); Urbaczewski A., Jessup L.M., A manager's primer in electronic commerce, Business Horizons, 41, 5, pp. 5-12, (1998); Laudon K., Traver C., E-Commerce: Business, Technology, Society, (2007)","D. Rajagopal; Instituto Tecnológico y de Estudios Superiores de Monterrey, Mexico City, Mexico; email: rajagopal@itesm.mx",null,"Emerald Group Publishing Ltd.",{"$nulls":5},2.0450621E7,null,null,null,"English","Emerald Emerg. Mark. Case Stud.","Article","Final",null,"Scopus","2-s2.0-85080988449"]
["Zaarour N.; Melachrinoudis E.; Solomon M.; Min H.","Zaarour, Nizar (53869755900); Melachrinoudis, Emanuel (7004681176); Solomon, Marius (7202021641); Min, Hokey (7102292247)","53869755900; 7004681176; 7202021641; 7102292247","A reverse logistics network model for handling returned products",2014.0,"International Journal of Engineering Business Management",6.0,1.0,13.0,null,null,null,17.0,"10.5772/58827","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84925844988&doi=10.5772%2f58827&partnerID=40&md5=a033aaecc728e1feb4803f95f7257e81","Department of Mechanical and Industrial Engineering, Northeastern University, Snell Engineering Center, Boston, United States; Department of Information and Operations Analysis, College of Business Administration, Northeastern University, Boston, United States; Department of Management, College of Business Administration, Bowling Green State University, Bowling Green, United States","Zaarour N., Department of Mechanical and Industrial Engineering, Northeastern University, Snell Engineering Center, Boston, United States; Melachrinoudis E., Department of Mechanical and Industrial Engineering, Northeastern University, Snell Engineering Center, Boston, United States; Solomon M., Department of Information and Operations Analysis, College of Business Administration, Northeastern University, Boston, United States; Min H., Department of Management, College of Business Administration, Bowling Green State University, Bowling Green, United States","Due to the emergence of e-commerce and the proliferation of liberal return policies, product returns have become daily routines for many companies. Considering the significant impact of product returns on the company's bottom line, a growing number of companies have attempted to streamline the reverse logistics process. Products are usually returned to initial collection points (ICPs) in small quantities and thus increase the unit shipping cost due to lack of freight discount opportunities. One way to address this issue is to aggregate the returned products into a larger shipment. However, such aggregation increases the holding time at the ICP, which in turn increases the inventory carrying costs. Considering this logistics dilemma, the main objectives of this research are to minimize the total cost by determining the optimal location and collection period of holding time of ICPs; determining the optimal location of a centralized return centre; transforming the nonlinear objective function of the proposed model formulation by Min et al. (2006a) into a linear form; and conducting a sensitivity analysis to the model solutions according to varying parameters such as shipping volume. Existing models and solution procedures are too complicated to solve real-world problems. Through a series of computational experiments, we discovered that the linearization model obtained the optimal solution at a fraction of the time used by the traditional nonlinear model and solution procedure, as well as the ability to handle up to 150 customers as compared to 30 in the conventional nonlinear model. As such, the proposed linear model is more suitable for actual industry applications than the existing models. © 2014 The Author(s).","Linear transformation; Optimization; Reverse logistics",{"$nulls":7},"Baig E.C., Study: Costly electronics product returns on the rise [online], (2011); Chandiran P., Rao K.S.P., Design of reverse and forward supply chain network: a case study, International Journal of Logistics Systems and Management, 4, 5, pp. 574-595, (2008); Chang T.S., Liao Y.F., Routing strategies for integrating forward distribution and reverse collection, Journal of Operational Research Society, 62, 6, pp. 971-981, (2011); Chanintrakul P., Mondragon A.E.C., Lalwani C., Wong C.Y., Reverse logistics network design: a state-of-the-art literature review, International Journal of Business Performance and Supply Chain Modelling, 1, 1, pp. 61-81, (2009); de Brito M.P., van der Laan E.A., Inventory control with product returns: the impact of imperfect information, European Journal of Operational Research, 194, 1, pp. 85-101, (2009); Du F., Evans G.W., A bi-objective reverse logistics network analysis for post-sale service, Computers and Operations Research, 35, 8, pp. 2617-2634, (2008); Ferguson M., Guide V., Daniel R., Souza G.C., Supply chain coordination for false failure returns, Manufacturing & Service Operations Management, 8, 4, pp. 376-393, (2006); Fleischmann M., Krikke H.R., Dekker R., Flapper D.P., A characterization of logistics networks for product recovery, Omega, 28, pp. 653-666, (2000); Fleischmann M., Reverse logistics network structures and design, Business aspects of closed-loop supply chains: exploring the issues, pp. 117-148, (2003); Gecker R., Industry best practices in reverse logistics, (2007); Geoffrion A.M., Graves G.W., Multicommodity distribution system design by Benders decomposition, Management Science, 20, pp. 822-844, (1974); Guide V.D.R., Harrison T.P., Van Wassenhove L.K., The challenges of closedloop supply chains, Interfaces, 33, 6, pp. 3-6, (2003); Jayaraman V., Patterson R.A., Rolland E., The design of reverse distribution networks: models and solution procedures, European Journal of Operational Research, 150, 1, pp. 128-149, (2003); Kannan G., Haq N., Devika M., Analysis of closed-loop supply chain using genetic algorithm and particle swarm optimization, International Journal of Production Research, 47, 5, pp. 1175-1200, (2009); LINGO 14.0: the modeling language and optimizer, (2013); McCullough K., Dolberg S., Leyne L., Reinhard A.A., Gatoff J., Mastering commerce logistics, (1999); Mead L., Sarkis J., Presley A., The theory and practice of reverse logistics, International Journal of Logistics Systems and Management, 3, 1, pp. 56-84, (2007); Melachrinoudis E., Min H., Wu X., A multiobjective model for the dynamic location of landfills, Location Science, 3, 3, pp. 143-166, (1995); Meyer H., Many happy returns, The Journal of Business Strategy, 20, 4, pp. 27-31, (1999); Min H., A bi-criterion reverse distribution model for product recall, Omega, 17, 5, pp. 483-490, (1989); Min H., Kim I., Green supply chain research: past, present, and future, Logistics Research, 4, 1, pp. 39-47, (2012); Min H., Ko H.K., Ko C.S., A genetic algorithm approach to developing the multi-echelon reverse logistics network for product returns, Omega, 34, 1, pp. 56-59, (2006); Min H., Ko C.S., Ko H.K., The spatial and temporal consolidation of returned products in a closed-loop supply chain network, Computers and Industrial Engineering, 51, 2, pp. 309-320, (2006); Min H., Ko C.S., Ko H.J., Managing product returns in customer-centric e-tail environments, International Journal of Services Technology and Management, 9, 1, pp. 51-70, (2008); Norman L., Sumner W., The six hidden costs of reverse logistics [online], (2006); Petersen J.A., Kumar V., Can product returns make you money?, MIT Sloan Management Review, 51, 3, pp. 85-89, (2010); The new dynamics of returns: the profit, customer and business intelligence opportunities in returns, (2000); Pochampally K.K., Metrics for performance measurement of a reverse/closed-loop supply chain, International Journal of Business Performance and Supply Chain Modelling, 1, 1, pp. 8-32, (2009); Pokharel S., Mutha A., Perspectives in reverse logistics: a review, Resources, Conservation and Recycling, 53, 4, pp. 175-182, (2009); Schultmann F., Engels B., Rentz O., Closed-loop supply chains for spent batteries, Interfaces, 33, 6, pp. 57-71, (2003); Seuring S., Muller M., From a literature review to a conceptual framework for sustainable supply chain management, Journal of Cleaner Production, 16, 15, pp. 1699-1710, (2008); Shear H., Speh T.W., Stock J.R., The warehousing link of reverse logistics, (2003); Sheriff K.M.M., Nachiappan S., Min H., Combined location and routing problems for designing the quality-dependent and multi-product reverse logistics network, Journal of the Operational Research Society, 64, 4, pp. 1-15, (2013); Srivastava R., Network design for reverse logistics, Omega, 36, 4, pp. 535-548, (2007); Srisvastava S.K., Green supply chain management: a state-of-the art literature review, International Journal of Management Reviews, 9, 1, pp. 53-80, (2007); Stock J.R., Reverse logistics, (1992); Tan A., Kumar A., A decision making model to maximize the value of reverse logistics in the computer industry, International Journal of Logistics Systems and Management, 4, 3, pp. 297-312, (2008); Van Wassenhove L.N., Guide V.D.R., End of life returns: closed-loop supply chains, Business aspects of closed-loop supply chains: exploring the issues, pp. 9-14, (2003); Zaarour N., Melachrinoudis E., Solomon M., Min H., The optimal determination of the collection period for returned products in the sustainable supply chain, International Journal of Logistics Research and Applications, 17, 1, pp. 35-45, (2014); Zhou G., Min H., Designing a closedloop supply chain with stochastic product returns: a genetic algorithm approach, International Journal of Logistics Systems and Management, 9, 4, pp. 397-418, (2011)",null,null,"InTech Europe",{"$nulls":5},1.847979E7,null,null,null,"English","Intern. J. Eng. Bus. Manage.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-84925844988"]
["Fu P.; Chen Y.; Yin H.","Fu, Peihua (17345758000); Chen, Yangfei (54882939900); Yin, Hongbo (55627503200)","17345758000; 54882939900; 55627503200","IUCstream: A novel increment update clustering algorithm for commodity stream data analysis in e-commerce and logistics",2013.0,"Journal of Computers (Finland)",8.0,3.0,null,795.0,802.0,7.0,2.0,"10.4304/jcp.8.3.795-802","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84875180512&doi=10.4304%2fjcp.8.3.795-802&partnerID=40&md5=00aa276ff3d3d2972c46538f49afbbc2","Col of Comp.and Inf Eng., Zhejiang Gongshang Univ., Hangzhou, China","Fu P., Col of Comp.and Inf Eng., Zhejiang Gongshang Univ., Hangzhou, China; Chen Y., Col of Comp.and Inf Eng., Zhejiang Gongshang Univ., Hangzhou, China; Yin H., Col of Comp.and Inf Eng., Zhejiang Gongshang Univ., Hangzhou, China","With China's rapid development of e-commerce and logistics, many large electronic business enterprises start to establish large volume warehouses. It takes a long time to distribute the goods every time, so the optimal distribution link can save a lot of time and it has important practical significance. In order to optimize goods inventory and delivery, the electronic commerce goods shopping cart stream data need to be analyzed. In this paper, a novel increment update clustering algorithm, named as IUCStream for commodity stream data analysis in ecommerce and logistics is proposed. In this algorithm, the correlation between goods is calculated and an efficient algorithm processing incremental updating of the data stream of goods is used to cluster different goods into groups. Finally, the algorithms' superiority and effectiveness are verifying by an example. © 2013 ACADEMY PUBLISHER.","Clustering algorithm; Commodity correlation; Data stream; E-commerce; Logistics","Clustering algorithms; Data communication systems; Electronic commerce; Logistics; Optimization; Data stream; Electronic business; Incremental updating; Large volumes; Optimal distributions; Shopping carts; Stream data; Distribution of goods",{"$nulls":6},"Han J., Kamber M., Data Mining: Concepts and Techniques, pp. 467-589, (2006); Henziger M.R., Raghavan P., Rajagopalan S., Computing on data streams. SRC Technical Note 1998-011., (1998); Ester M., Kriegel H.-P., Sander J., Incremental Clustering for Mining in a Data Warehousing Environment, Proceedings of the 24th International Conference on VLDB, pp. 323-333, (1998); Niu Q., Huang X., An Improved Fuzzy C-means Clustering Algorithm based on PSO, Journal of Software, 6, 5, pp. 873-879, (2011); Li X., A New Text Clustering Algorithm Based on Improved K-means, Journal of Software, 7, 1, pp. 95-101, (2012); Aggarwal C.C., Han J., Wang J., Et al., A Framework for Clustering Evolving Data Streams, Proceedings of the 29th International Conference on Very Large Data Bases, pp. 81-92, (2003); Cao F., Ester M., Qian W., Et al., Density-Based Clustering over an Evolving Data Stream with Noise, Proceedings of the 6th SIAM International Conference on Data Mining, pp. 328-339, (2006); Bhatnagar V., Kaur S., Exclusive and Complete Clustering of Streams., pp. 629-638, (2007); Aggarwal C.C., Yu P.S., A Framework for Clustering Uncertain Data Streams, Proceedings of the 24th International Conference on Data Engineering, pp. 150-159, (2008); Sebastian L., Mihai L., Incremental Clustering of Dynamic Data Streams Using Connectivity Based Representative Points, Data & Knowledge Engineering., 68, 1, pp. 1-27, (2009); Vasudha B., Sharanjit K., Et al., A Parameterized Framework for Clustering Streams, International Journal of Data Warehousing and Mining, 5, 1, pp. 36-56, (2009); Li H.-F., Lee S.-Y., Mining Frequent Item Sets over Data Streams Using Efficient Window Sliding Techniques, Expert System with Applications, 36, 2, pp. 1466-1477, (2009); Cao F., Liang J., Bai L., Et al., A Framework for Clustering Categorical Time-Evolving Data, IEEE Trans. On Fuzzy Systems, 18, 5, pp. 872-882, (2010); Bae E., Bailey J., Et al., A Clustering Comparison Measure Using Density Profiles and Its Application to the Discovery of Alternate Clusterings, Data Mining and Knowledge Discovery, 21, 3, pp. 427-471, (2010); Skala J., Kolingerova I., Dynamic Hierarchical Triangulation of a Clustered Data Stream, Comptures & Geosciences, 37, 8, pp. 1092-1101, (2011); Pierre B., Wei J., Et al., A Cluster-Based Context-Tree Model for Multivariate Data Streams with Applications to Anomaly Detection, Informs Journal on Computing, 23, 3, pp. 364-376, (2011); Kaufman L., Rousseeuw P.J., Finding Groups in Data: An Introduction to Cluster Analysis., (1990); Sneath P.H.A., Sokal R.R., Numerical Taxonomy., (1999)","P. Fu; Col of Comp.and Inf Eng., Zhejiang Gongshang Univ., Hangzhou, China; email: fph@mail.zjgsu.edu.cn",{"$nulls":7},"1796203X",null,null,null,"English","J. Comput.","Article","Final",null,"Scopus","2-s2.0-84875180512"]
["Zhu S.; Chen J.","Zhu, Shizhan (51462440700); Chen, Juan (7501888040)","51462440700; 7501888040","The digital divide in individual e-commerce utilization in China: Results from a national survey",2013.0,"Information Development",29.0,1.0,null,69.0,80.0,11.0,28.0,"10.1177/0266666912450168","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84875059998&doi=10.1177%2f0266666912450168&partnerID=40&md5=cc68e2917789c49e7ce2a1ac8cf17da9","Guangdong University of Technology, School of Management, Guangzhou 510520, 161 Yinglong Road, China; The Hong Kong Polytechnic University, Hong Kong","Zhu S., Guangdong University of Technology, School of Management, Guangzhou 510520, 161 Yinglong Road, China; Chen J., The Hong Kong Polytechnic University, Hong Kong","Using data from a national survey with 1,288 respondents, this study investigates the socio-demographic determinants of the first-order digital divide (access to the Internet) and the second-order digital divide (e-commerce use) in China. The survey employed spatial probability sampling technology so it would encompass migrants as well as registered residents. Multiple logistic regressions were applied to model the associations between access to the Internet/e-commerce use and demographic characteristics, socio-economic attributes, and migration and residency status. The results demonstrate the significant effects of rural-urban inequality and socio-economic divisions in Internet access. Age, gender, education, and residency were identified as significant predictors for individual e-commerce use. The findings provide helpful information for enterprises wishing to broaden their business horizons. The research can also be used in designing effective policies to reduce China's digital inequality. © The Author(s) 2013.","China; digital divide; e-commerce use; Internet u.; rural-urban inequality",{"$nulls":5},"General Research Fund of the Research Grants Council of Hong Kong, (PolyU 5416/10H); Chiang Ching-Kuo Foundation for International Scholarly Exchange, CCKF, (RG022-P-09); Hong Kong Polytechnic University, PolyU, (PolyU 5409/09H)","The national household survey Migration and Quality of Life was funded by the General Research Fund of the Research Grants Council of Hong Kong [PolyU 5416/10H]. The research undertaken for this article also received support from The Hong Kong Polytechnic University [PolyU 5409/09H] and the Chiang Ching-Kuo Foundation for International Scholarly Exchange [RG022-P-09].","Ajzen I., Perceived behavioral control, self-efficacy, locus of control, and the theory of planned behavior, Journal of Applied Social Psychology, 32, 4, pp. 665-683, (2002); Ajzen I., The theory of planned behavior, Organizational Behavior and Human Decision Processes, 50, 2, pp. 179-211, (1991); Akhter S.H., Digital divide and purchase intention: Why demographic psychology matters, Journal of Economic Psychology, 24, 3, pp. 321-327, (2003); Belanger F., Carter L., The impact of the digital divide on e-government use, Communications of the ACM, 52, 4, pp. 132-135, (2009); Billon M., Marco R., Lera-Lopezc F., Disparities in ICT adoption: A multidimensional approach to study the cross-country digital divide, Telecommunications Policy, 33, 10-11, pp. 596-610, (2009); Bimber B., Measuring the gender gap on the Internet, Social Science Quarterly, 81, 3, pp. 868-876, (2000); Chan K.W., Cities with Invisible Walls: Reinterpreting Urbanization in Post-1949 China, (1994); Chan K.W., Zhang L., The hukou system and rural-urban migration: Processes and changes, The China Quarterly, 160, pp. 818-855, (1999); Chau P.Y., Cole M., Massey A.P., Montoya-Weiss M., O'Keefe R.M., Cultural differences in the online behavior of consumers, Communications of the ACM, 45, 10, pp. 138-143, (2002); Statistical survey report on the Internet development in China (2002), (2003); Statistical survey report on the Internet development in China (2009), (2010); Survey report on the Internet usage in Chinese rural areas (2009), (2010); Cho H., Jialin S.K., Influence of gender on Internet commerce: An explorative study in Singapore, Journal of Internet Commerce, 7, 1, pp. 95-119, (2008); Dai H., King R.C., Are Chinese online consumers different? An investigation of online consumers' repeat purchase intention in China, Americas Conference on Information Systems (AMCIS) 2008 Proceedings, (2008); Davis F.D., Perceived usefulness, perceived ease of use, and user acceptance of information technology, MIS Quarterly, 13, 3, pp. 319-340, (1989); DeBell M., Chapman C., Computer and Internet use by students in 2003. Statistical analysis report, National Center for Education Statistics, (2006); Dewan S., Riggins F.J., The digital divide: Current and future research directions, Journal of the Association for Information Systems, 6, 12, pp. 298-337, (2005); Efendioglu A.M., Yip V.F., Chinese culture and e-commerce: An exploratory study, Interacting with Computers, 16, 1, pp. 45-62, (2004); Information and communication technologies in development: The role of ICTs in EC development policy, Brusseles, (2001); Fairlie R.W., Race and the digital divide. 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Zhu; Guangdong University of Technology, School of Management, Guangzhou 510520, 161 Yinglong Road, China; email: shizhan_nc@gdut.edu.cn",{"$nulls":7},1.7416469E7,null,null,null,"English","Inf. Dev.","Article","Final",null,"Scopus","2-s2.0-84875059998"]
["Zhang L.; Zhang Y.","Zhang, Liyi (57190174980); Zhang, Yi (57196205328)","57190174980; 57196205328","A Comparative Study of Environmental Impacts of Two Delivery Systems in the Business-to-Customer Book Retail Sector",2013.0,"Journal of Industrial Ecology",17.0,3.0,null,407.0,417.0,10.0,15.0,"10.1111/j.1530-9290.2012.00570.x","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84878935335&doi=10.1111%2fj.1530-9290.2012.00570.x&partnerID=40&md5=b8d5c8bf72b8f8db44373dd3cff923bc",null,null,"Summary: China has the highest carbon dioxide (CO2) emissions in the world. In China, logistics accounts for a significant portion of the total energy use and CO2 emissions in business-to-customer (B2C) retailing. This study focuses on the environmental impacts of B2C delivery in China, focusing on the book retail industry. Mathematical models are proposed based on the practical operations of the \"e-commerce networked delivery\" (END) system and the \"sustainable networked delivery\" (SND) system. The energy consumption and CO2 emissions per book are then determined and compared for the two systems. Furthermore, we contrast the findings with those of similar studies conducted for other countries and provide explanations for the differences. The results show that (1) in general, in China, the SND system is better than the END system in terms of environmental impacts; (2) the END system in China generates fewer environmental impacts than those in the United States and the United Kingdom, while the SND system in China has greater environmental impacts than that in the United States; and (3) the wide use of vehicles such as electric bicycles that have low energy consumption rates contributes to the reduction of environmental impacts per book in both the END and SND systems in China. The limitations of the study and suggestions for future research are also discussed. © 2013 by Yale University.","Distribution; Energy consumption; Environmental impact assessment; Industrial ecology; Sustainable networked delivery (SND)","China; Carbon dioxide; Energy utilization; Environmental impact assessments; Mathematical models; Business to customers; Comparative studies; Delivery systems; Distribution; Electric bicycles; Industrial ecology; Low energy consumption; Sustainable networked delivery (SND); carbon dioxide; carbon emission; comparative study; electric vehicle; energy use; environmental impact assessment; industrial ecology; logistics; nucleic acid analysis; numerical model; retailing; sustainability; Environmental impact",{"$nulls":6},"Brynjolfsson E., Smith M.D., Frictionless commerce? A comparison of internet and conventional retailers, Management Science, 46, 4, pp. 563-585, (2000); Cao Y., Gruca T.S., The influence of pre- and post-purchase service on prices in the online book market, Journal of Interactive Marketing, 18, 4, pp. 51-62, (2004); Chiou J.S., Pan L.Y., Antecedents of Internet retailing loyalty: Differences between heavy versus light shoppers, Journal of Business and Psychology, 23, 3, pp. 327-339, (2009); Clay K., Krishnan R., Wolff E., Fernandes D., Retail strategies on the Web: Price and non-price competition in the online book industry, Journal of Industrial Economics, 50, 3, pp. 351-367, (2002); (2011); Edwards J.B., McKinnon A.C., Cullinane S.L., Comparative analysis of the carbon footprints of conventional and online retailing: A \"last mile\" perspective, International Journal of Physical Distribution and Logistics Management, 40, 1-2, pp. 103-123, (2010); Huang Y.K., Fan W.S., Hsieh C.H., Lan C.H., Chang R.S., Using cusp catastrophe theory to model pick-up point choice behavior for online bookstore shopper, pp. 44-48, (2010); (2010); (2011); Kim J., Xu M., Kahhat R., Allenby B., Williams E., pp. 1-5, (2008); Kim J., Xu M., Kahhat R., Allenby B., Williams E., Designing and assessing a sustainable networked delivery (SND) system: Hybrid business-to-consumer book delivery case study, Environmental Science and Technology, 43, 1, pp. 181-187, (2009); Matthews H.S., Hendrickson C.T., Lave L., Harry Potter and the health of the environment, IEEE Spectrum, 37, 11, pp. 20-22, (2000); Matthews H.S., Hendrickson C.T., Soh D.L., Environmental and economic effects of e-commerce: A case study of book publishing and retail logistics, Journal of the Transportation Research Board, 1763, 2, pp. 6-12, (2001); Matthews H.S., Hendrickson C.T., Soh D.L., The net effect: Environmental implications of e-commerce and logistics, pp. 191-195, (2001); Matthews H.S., Williams E., Tagami T., Hendrickson C.T., Energy implications of online book retailing in the United States and Japan, Environment Impact Assessment Review, 22, 5, pp. 493-507, (2002); (2010); (2010); To calculate the CO<sub>2</sub> emission in your house, (2010); Punakivi M., Saranen J., Identifying the success factors in e-grocery home delivery, International Journal of Retail and Distribution Management, 29, 4, pp. 156-163, (2001); Reichling M., Otto T., The environmental impact of the new economy: Deutshe Telekom, telecommunications services and the sustainable future, The ecology of the new economy: Sustainable transformation of global information, communications and electronics industries, (2002); Ricker F.R., Kalakota R., Order fulfillment: The hidden key to e-commerce success, Supply Chain Management Review, 3, 3, pp. 60-70, (1999); Weltevreden J., Rotem-Mindali O., (2008); Williams E., Tagami T., Energy use in sales and distribution via e-commerce and conventional retail: A case study of the Japanese book sector, Journal of Industrial Ecology, 6, 2, pp. 99-114, (2003); Williams E.D., Energy efficiency of B2C e-commerce in Japan, IEEE International Symposium on Electronics and the Environment, pp. 38-43, (2002); Xu M., Allenby B., Kim J., Kahhat R., A dynamic agent-based analysis for the environmental impacts of conventional and novel book retailing, Environmental Science and Technology, 43, 8, pp. 2851-2857, (2009); Xu M., Kim J., Kahhat R., Allenby B., Market dynamics and environmental impacts of e-commerce: A case study on book retailing, Electronics and the Environment, (2008); Ying W., Dayong S., Multi-agent framework for third party logistics in e-commerce, Expert Systems with Applications, 29, 2, pp. 431-436, (2005)","L. Zhang; Department of Information Systems and E-Commerce, School of Information Management, Wuhan University, Wuhan 430072, China; email: lyzhang@whu.edu.cn",null,"Blackwell Publishing",{"$nulls":5},1.088198E7,null,"JINEF",null,"English","J. Ind. Ecol.","Article","Final",null,"Scopus","2-s2.0-84878935335"]
["Zhou Y.; Wang X.","Zhou, Yiwei (55596585700); Wang, Xiaokun (Cara) (55482185200)","55596585700; 55482185200","Explore the relationship between online shopping and shopping trips: An analysis with the 2009 NHTS data",2014.0,"Transportation Research Part A: Policy and Practice",70.0,null,null,1.0,9.0,8.0,109.0,"10.1016/j.tra.2014.09.014","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84908613280&doi=10.1016%2fj.tra.2014.09.014&partnerID=40&md5=4bbb8aca73ff0a25adcaebf46ad7ef31","Department of Civil and Environmental Engineering, Rensselaer Polytechnic Institute, 4027 JEC Building, 110 8th Street, Troy, 12180-3590, NY, United States; Department of Civil and Environmental Engineering, Rensselaer Polytechnic Institute, 4032 JEC Building, 110 8th Street, Troy, 12180-3590, NY, United States","Zhou Y., Department of Civil and Environmental Engineering, Rensselaer Polytechnic Institute, 4027 JEC Building, 110 8th Street, Troy, 12180-3590, NY, United States; Wang X., Department of Civil and Environmental Engineering, Rensselaer Polytechnic Institute, 4032 JEC Building, 110 8th Street, Troy, 12180-3590, NY, United States","The rapid growth of ecommerce brings great changes to the transportation system. However, most existing studies focus on the impact of ecommerce on freight system. Its impact on personal trips is relatively less studied. It is reasonable to argue that online shopping reduces the need of shopping trips by making goods accessible via door-to-door deliveries. On the other hand, online shopping may also create more shopping trips as online shoppers travel to stores to experience, compare or pick up the goods. Understanding the connections between online shopping and shopping trips is critical for transportation planners to prepare for changes that information technology will continue to bring to this nation in the future. Using the 2009 National Household Travel Survey (NHTS) data and a structural equation model (SEM), this paper disentangles the bidirectional connections between online shopping and shopping trips. Results show that online shopping encourages shopping trips while shopping trips tend to suppress the online shopping propensity. Besides, both online shopping and shopping trips are influenced by exogenous factors such as shoppers' demographic features, regional specific factors and household attributes. A closer examination at the state level further confirms model validity while disclosing spatial variation in their relationship. © 2014 Elsevier Ltd.","E-commerce; NHTS; Online shopping; Personal trips; SEM","Motor transportation; Scanning electron microscopy; Bi-directional connections; National household travel surveys; NHTS; Online shopping; Personal trips; Structural equation modeling; Transportation planners; Transportation system; economic growth; electronic commerce; freight transport; Internet; shopping activity; Electronic commerce",{"$nulls":6},"Aguilera A., Guillot C., Rallet A., Mobile ICTs and physical mobility: review and research agenda, Transport. Res. A Policy Pract., 46, 4, pp. 664-672, (2012); Calderwood E., Freathy P., Consumer mobility in the Scottish isles: the impact of internet adoption upon retail travel patterns, Transport. Res. A Policy Pract., 59, pp. 192-203, (2014); Cao X., Xu Z., Douma F., The interactions between e-shopping and traditional in-store shopping: an application of structural equations model, Transportation, 39, 5, pp. 957-974, (2012); Choo S., Lee T., Mokhtarian P.L., Do transportation and communications tend to be substitutes, complements, or neither? U.S. consumer expenditures perspective, 1984-2002, Transp. Res. Rec., 2010, pp. 121-132, (2008); Fan X., Wang L., Effects of potential confounding factors on fit indices and parameter estimates for true and misspecified SEM models, Educ. Psychol. Measur., 58, pp. 701-735, (1998); Farag S., Schwanen T., Dijst M., Empirical investigation of online searching and buying and their relationship to shopping trips, Transp. Res. Rec., 1926, pp. 242-251, (2005); Farag S., Weltevreden J., van Rietbergen T., Dijst M., van Oort F., E-shopping in the Netherlands: does geography matter?, Environ. Plann B Plann. Des., 33, 1, pp. 59-74, (2006); Farag S., Schwanen T., Dijst M., Faber J., Shopping online and/or in-store? A structural equation model of the relationships between e-shopping and in-store shopping, Transport. Res. A Policy Pract., 41, 2, pp. 125-141, (2007); (2012); (2014); Ferrell C., Home-based teleshoppers and shopping travel: do teleshoppers travel less?, Transp. Res. Rec., 1894, pp. 241-248, (2004); Ferrell C., Home-based teleshoppers and shopping travel: where do people find the time?, Transp. Res. Rec., 1926, pp. 212-223, (2005); Krizek K., Li Y., Handy S., Spatial attributes and patterns of use in household-related information and communications technology activity, Transp. Res. Rec., 1926, pp. 252-259, (2005); Mokhtarian P.L., A conceptual analysis of the transportation impacts of B2C e-commerce, Transportation, 31, 3, pp. 257-284, (2004); Pearl J., Linear models: a useful, \"microscope\" for causal analysis, J. Causal Inference, 1, 1, pp. 155-170, (2013); Ren F., Kwan M.P., The impact of geographic context on e-shopping behavior, Environ. Plann. B Plann. Des., 36, 2, pp. 262-278, (2009); Sim L.L., Koi S.M., Singapore's internet shoppers and their impact on traditional shopping patterns, J. Retail. Consum. Serv., 9, pp. 115-124, (2002); Srinivasan S., Bhat C.R., Modeling household interactions in daily in-home and out-of-home maintenance activity participation, Transportation, 32, 5, pp. 523-544, (2005); Swinyard W.R., Smith S.M., Why people (don't) shop online: a lifestyle study of the internet consumer, Psychol. Mark., 20, 7, pp. 567-597, (2003); Tonn B.E., Hemrick A., Impacts of the use of e-mail and the internet on personal trip-making behavior, Soc. Sci. Comput. Rev., 22, pp. 270-280, (2004); The 4th Quarter 2012 Retail E-Commerce Sales Report, (2013); Weltevreden J.W.J., Rietbergen T.V., E-shopping versus city centre shopping: the role of perceived city centre attractiveness, Tijdschrift voor economische en sociale geografie, 98, 1, pp. 68-85, (2007); Yun D.S., O'Kelly M.E., Modeling the day-of-the-week shopping activity and travel patterns, Socio-Economic Plann. Sci., 31, pp. 307-319, (1997)",null,null,"Elsevier Ltd",{"$nulls":5},9658564.0,null,null,null,"English","Transp. Res. Part A Policy Pract.","Article","Final",null,"Scopus","2-s2.0-84908613280"]
["Mangiaracina R.; Marchet G.; Perotti S.; Tumino A.","Mangiaracina, Riccardo (35325033800); Marchet, Gino (6506899318); Perotti, Sara (35220345000); Tumino, Angela (25929706400)","35325033800; 6506899318; 35220345000; 25929706400","A review of the environmental implications of B2C e-commerce: a logistics perspective",2015.0,"International Journal of Physical Distribution and Logistics Management",45.0,6.0,null,565.0,591.0,26.0,152.0,"10.1108/IJPDLM-06-2014-0133","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84931069984&doi=10.1108%2fIJPDLM-06-2014-0133&partnerID=40&md5=78f67b4a35985ea4e398b59356888d80","Department of Management, Economics and Industrial Engineering, Politecnico di Milano, Milano, Italy","Mangiaracina R., Department of Management, Economics and Industrial Engineering, Politecnico di Milano, Milano, Italy; Marchet G., Department of Management, Economics and Industrial Engineering, Politecnico di Milano, Milano, Italy; Perotti S., Department of Management, Economics and Industrial Engineering, Politecnico di Milano, Milano, Italy; Tumino A., Department of Management, Economics and Industrial Engineering, Politecnico di Milano, Milano, Italy","Purpose – Given the importance of logistics operations in business-to-consumer (B2C) e-commerce and growing interest in the related environmental effects, the purpose of this paper is to offer an up-to-date literature review on the topic of B2C e-commerce environmental sustainability, specifically from a logistics perspective. Design/methodology/approach – The analysis focussed on a set of 56 papers published from 2001 to 2014 in 38 peer-reviewed international journals. The papers were analyzed and categorized according to the main features of the paper, the research method(s) adopted and the themes tackled. Findings – There is a growing interest in sustainability issues. In the last 14 years, the focus has progressively shifted from the mere identification of the wide-ranging environmental effects of e-commerce to the need for a quantitative evaluation of their impact, although much remains to be done in this regard. Some industries, such as books and grocery, have largely been addressed, however, promising sectors in the e-commerce field, such as clothing and consumer electronics, have only been considered to a certain degree. Moreover, despite the emerging role of multichannel strategies, the environmental implications of the related logistics activities have not yet been studied in detail. Originality/value – B2C e-commerce has grown in popularity, and its environmental implications are currently of key interest. This paper contributes to the understanding of the existing body of knowledge on this topic, presenting an up-to-date classification of articles and highlighting themes for further research activities. From a managerial perspective, this paper helps supply chain managers develop a clear understanding of both the logistics areas with the most impact on environmental sustainability and the KPIs used to quantify the environmental implications of e-commerce logistics operations comprehensively and effectively. © Emerald Group Publishing Limited.","B2C e-commerce; Logistics; Sustainability",{"$nulls":7},{"$cut":{"chars":18174,"head":"Abukhader S.M., Jonson G., The environmental implications of electronic commerce: a critical review and framework for future investigation, Management of Environmental Quality: An International Journal, 14, 4, pp. 460-476, (2003); Abukhader S.M., Jonson G., E-commerce and the environment: A gateway to the renewal of greening supply chains, International Journal of Technology Management, 28, 2, pp. 274-288, (2004); Abukhader S.M., Jonson G., Eco-efficiency in the era of electronic commerce – is there a need for adopting ‘eco-effectiveness?”, Journal of Cleaner Production, 1, 7, pp. 801-808, (2008); Allen J., Browne M., Vans and the economy, Project Report, Commission for Integrated Transport, (2010); Aronsson H., Brodin M.H., The environmental impact of changing logistics structures, International Journal of Logistics Management, 17, 3, pp. 394-415, (2006); Borggren C., Moberg A., Finnvreden G., Books from an environmental perspective –part 1: Environmental impacts of paper books sold in traditional and internet bookshops, The International Journal of Life Cycle Assessment, 11, 2, pp. 138-147, (2011); Bruce G.M., Daly L., Innovative process in e-commerce fashion supply chains, Innovative Quick Response Programs in Logistics and Supply Chain Management, pp. 227-241, (2010); Brugnoli G., Mangiaracina R., Perego A., The ecommerce customer journey: A model to assess and compare the user experience of the ecommerce websites, Journal of Internet Banking and Commerce, 14, 3, pp. 1-11, (2009); Cairns S., Delivering supermarket shopping: More or less traffic?, Transport Reviews: A Transnational Transdisciplinary Journal, 25, 1, pp. 51-84, (2005); Carrillo J.E., Vakharia A.J., Wang R., Environmental implications for online retailing, European Journal of Operational Research, 239, 3, pp. 744-755, (2014); Carter C.R., Rogers D.S., A framework of sustainable supply chain management: Moving toward new theory, International Journal of Physical Distribution &Amp; Logistics Management, 38, 5, pp. 360-387, (2008); Carter C.R., Kauffman L., Michel A., Behavioral supply management: A taxonomy of judgment and decision-making biases, International Journal of Physical Distribution &Amp; Logistics Management, 37, 8, pp. 631-669, (2007); Colicchia C., Marchet G., Melacini M., Perotti S., Building environmental sustainability: Empirical evidence from logistics service providers, Journal of Cleaner Production, 59, pp. 197-209, (2013); Durand B., Gonzalez-Feliu J.G., Urban logistics and e-grocery: Have proximity delivery services a positive impact on shopping trips?, Procedia – Social and Behavioral Sciences, 39, pp. 510-520, (2012); Edwards J.B., McKinnon A.C., Cullinane S.L., Comparative analysis of the carbon footprints of conventional and online retailing: A ‘last mile perspective”, International Journal of Physical Distribution &Amp; Logistics Management, 40, 1, pp. 103-123, (2010); Edwards J.B., McKinnon A.C., Cullinane S.L., Comparative carbon auditing of conventional and online retail supply chains: A review of methodological issues, Supply Chain Management: An International Journal, 16, 1, pp. 57-63, (2011); Elkington J., Towards the sustainable corporation: Win-win-win strategies for sustainable development, California Management Review, 36, pp. 90-100, (1994); Evans P.F., Camus L., Western European Online Retail Forecast, 2009-2014, (2010); Farag S., Schwanen T., Dijst M., Faber J., Shopping online and/or in-store? A structural equation model of the relationships between e-shopping and in-store shopping, Transportation Research Part A: Policy and Practice, 41, 2, pp. 125-141, (2007); Fitcher K., E-commerce, sorting out the environmental consequences, Journal of Industrial Ecology, 6, 2, pp. 25-41, (2002); Fulton K., Lee S.E., Assessing sustainable initiatives of apparel retailers on the internet, Journal of Fashion Marketing and Management, 17, 3, pp. 353-366, (2013); Gay R.H., Davis R.A., Phillis D.T., Sui D.Z., Modeling paradigm for the environmental impacts of the digital economy, Journal of Organizational Computing and Electronic Comm"}},"S. Perotti; Department of Management, Economics and Industrial Engineering, Politecnico di Milano, Milano, Italy; email: sara.perotti@polimi.it",null,"Emerald Group Holdings Ltd.",{"$nulls":5},9600035.0,null,null,null,"English","Int. J. Phys. Distrib. Logist. Manage.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-84931069984"]
["Zhou L.; Lin Y.; Wang X.; Ni L.; He Y.","Zhou, Lin (57868712000); Lin, Yun (36655835400); Wang, Xu (55951735500); Ni, Lin (56207926300); He, Yandong (55951616500)","57868712000; 36655835400; 55951735500; 56207926300; 55951616500","Integrated multi-objective scheduling for multi-task on perishable products",2015.0,"Journal of Information and Computational Science",12.0,18.0,null,6653.0,6664.0,11.0,1.0,"10.12733/jics20107123","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84957810872&doi=10.12733%2fjics20107123&partnerID=40&md5=f8be8158c196af6ef9a752f49a4d7904","College of Mechanical Engineering, Chongqing University, Chongqing, 400030, China; State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing, 400030, China; Chongqing Key Laboratory of Logistics, Chongqing University, Chongqing, 400030, China","Zhou L., College of Mechanical Engineering, Chongqing University, Chongqing, 400030, China; Lin Y., College of Mechanical Engineering, Chongqing University, Chongqing, 400030, China, State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing, 400030, China, Chongqing Key Laboratory of Logistics, Chongqing University, Chongqing, 400030, China; Wang X., College of Mechanical Engineering, Chongqing University, Chongqing, 400030, China, State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing, 400030, China, Chongqing Key Laboratory of Logistics, Chongqing University, Chongqing, 400030, China; Ni L., College of Mechanical Engineering, Chongqing University, Chongqing, 400030, China, State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing, 400030, China, Chongqing Key Laboratory of Logistics, Chongqing University, Chongqing, 400030, China; He Y., College of Mechanical Engineering, Chongqing University, Chongqing, 400030, China","The cost and delivery time have become the biggest challenges in small volume perishable products logistics under E-commerce. In order to better solve this problem, an integrated multi-task operation framework is proposed from the system optimization perspective by analyzing the characteristics of perishable products. As the current scheduling models seldom consider both the benefits of individual tasks and overall multi-task simultaneously, a novel multi-objective model aiming at maximizing the mean fractional remaining shelf-life, minimizing the total logistics cost and remaining fractional shelflife deviation of all tasks is proposed. In view of variable length path selection and resources capability conflict in the process of solving, a Non-dominated Sorting Genetic Algorithm (NSGA-II) with adaptive variable length chromosome cross and double mutation mechanisms is designed. Finally, the validity of the model is verified by comparing different models based on a corresponding case. © 2015 by Binary Information Press.","Integrated scheduling; Multi-objective optimization; Non-dominated sorting genetic algorithm; Perishable products","Genetic algorithms; Optimization; Scheduling; Integrated scheduling; Multi-objective modeling; Multi-objective scheduling; Non dominated sorting genetic algorithm (NSGA II); Non- dominated sorting genetic algorithms; Perishable product; Total logistics costs; Variable length chromosome; Multiobjective optimization",{"$nulls":6},"Chen H.K., Hsueh C.F., Chang M.S., Production scheduling and vehicle routing with time windows for perishable food products, Computers & Operations Research, 36, 7, pp. 2311-2319, (2009); Wong W.H., Leung L.C., Hui Y.V., Airfreight forwarder shipment planning: A mixed 0-1 model and managerial issues in the integration and consolidation of shipments, European Journal of Operational Research, 193, 1, pp. 86-97, (2009); Cui Y., Huang M., Yang S., Lee L.H., Wang X., Fourth party logistics routing problem model with fuzzy duration time and cost discount, Knowledge-Based Systems, 50, pp. 14-24, (2013); Wang Y., Zhang Z.H., Lai Z.Z., A multi-attribute assignment model for fourth party logistics based on TOPSIS method, Journal of Systems & Management, 20, 5, pp. 569-577, (2011); Liu Q., Zhang C., Zhu K., Rao Y., Novel multi-objective resource allocation and activity scheduling for fourth party logistics, Computers & Operations Research, 44, pp. 42-51, (2014); Kouki C., Sahin E., Jema Z., Dallery Y., Assessing the impact of perishability and the use of time temperature technologies on inventory management, International Journal of Production Economics, 143, 1, pp. 72-85, (2013); Olsson F., Tydesj P., Inventory problems with perishable items: Fixed lifetimes and backlogging, European Journal of Operational Research, 202, 1, pp. 131-137, (2010); Azi N., Gendreau M., Potvin J.Y., An adaptive large neighborhood search for a vehicle routing problem with multiple routes, Computers & Operations Research, 41, pp. 167-173, (2014); Amorim P., Gnther H.O., Almada-Lobo B., Multi-objective integrated production and distribution planning of perishable products, International Journal of Production Economics, 138, 1, pp. 89-101, (2012); Yan C., Banerjee A., Yang L., An integrated production-distribution model for a deteriorating inventory item, International Journal of Production Economics, 133, 1, pp. 228-232, (2011); Zheng H.Y., Zhao W.L., Yang J., Et al., QoS analysis for web service compositions with complex structures, IEEE Transactions on Services Computing, 6, 3, pp. 373-386, (2013); Nariman-Zadeh N., Salehpour M., Jamali A., Et al., Pareto optimization of a five-degree of freedom vehicle vibration model using a multi-objective uniform-diversity genetic algorithm (MUGA), Engineering Applications of Artificial Intelligence, 23, 4, pp. 543-551, (2010); Sriniva N., Deb K., Multi-objective function optimizadon using non-dominated sorting genetic algorithms, Evolutionary Computation, 2, 3, pp. 221-248, (1995); Deb K., Pratap A., Agarwal S., Meyarivan T., A fast and elitist multiobjective genetic algorithm: NSGA-II, IEEE Transactions on Evolutionary Computation, 6, 2, pp. 182-197, (2002)","Y. Lin; College of Mechanical Engineering, Chongqing University, Chongqing, 400030, China; email: linyun417@126.com",null,"Binary Information Press",{"$nulls":5},1.5487741E7,null,null,null,"English","J. Inf. Comput. Sci.","Article","Final",null,"Scopus","2-s2.0-84957810872"]
["Allen G.; Feils D.; Disbrow H.","Allen, Grace (56669237500); Feils, Dorothee (22940832100); Disbrow, Holly (56669806400)","56669237500; 22940832100; 56669806400","The rise and fall of netflix: What happened and where will it go from here?",2014.0,"Journal of the International Academy for Case Studies",20.0,2.0,null,119.0,128.0,9.0,2.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-84962500913&partnerID=40&md5=98b6ef388e4dd4990dee20e368de9f46","Western Carolina University, United States; University of Alberta, Canada","Allen G., Western Carolina University, United States; Feils D., University of Alberta, Canada; Disbrow H., Western Carolina University, United States","CASE DESCRIPTION: The primary subject matter of this case concerns company analysis. Secondary issues include financial statement analysis, corporate strategy and international expansion. The case has a difficulty level of three and should be appropriate for undergraduate and graduate courses in investments and financial and strategic management. The case is designed to be taught in one to two class hours, with three hours of outside preparation by students. CASE SYNOPSIS: Netflix is an innovative company that has changed the way we rent movies and watch TV shows. Its business model is based on a subscription service that provides home-delivery of DVD rentals and streaming of movies and TV shows. The company took advantage of the rapid growth in the DVD rental market, the internet and e-commerce by providing a service that the traditional brick-and-mortar retailers, such as Blockbuster, could not compete with. In 2011, however, a price hike, poor management decisions, changes in technology, and increased competition threatened Netflix, leading to a sharp decline in its share price. In this case, students analyze the fundamentals of Netflix including its financials and management decisions to help determine if Netflix's poor stock performance in 2011 was predictable as well as what the future might hold for this company.",{"$nulls":11},"Allied Business Academies",{"$nulls":5},1.078495E7,null,null,null,"English","J. Int. Acad. Case Stud.","Article","Final",null,"Scopus","2-s2.0-84962500913"]
["Pozzi A.","Pozzi, Andrea (55553286200)",5.55532862E10,"E-commerce as a stockpiling technology: Implications for consumer savings",2013.0,"International Journal of Industrial Organization",31.0,6.0,null,677.0,689.0,12.0,23.0,"10.1016/j.ijindorg.2013.05.005","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84890115374&doi=10.1016%2fj.ijindorg.2013.05.005&partnerID=40&md5=0ca6ebae058f6dac71992018f3d2f296","Einaudi Institute for Economics and Finance, Italy","Pozzi A., Einaudi Institute for Economics and Finance, Italy","Shopping on the Internet spares customers the discomfort of carrying around heavy and bulky baskets of goods, since the service usually includes home delivery. This makes e-commerce a technology well suited to helping consumers to buy in bulk or to stockpile items on discount. I use grocery scanner data provided by a supermarket chain selling both online and through traditional stores to show that the introduction of e-commerce leads to an increase in bulk purchase and stockpiling behavior by customers. Since bulk and discounted items are sold at a lower price per unit, my findings highlight a new dimension in which online shopping can be beneficial to consumers. According to my calculations, the reduction in the cost of stockpiling triggered by the introduction of electronic commerce generates significant savings. © 2013 Elsevier B.V.","Consumer savings; E-commerce; Retail; Stockpiling","Sales; Consumer savings; Home delivery; New dimensions; Online shopping; Retail; Scanner data; Stockpiling; Supermarket chains; Electronic commerce",{"$nulls":6},"Boizot C., Robin J.-M., Visser M., The demand for food products: An analysis of interpurchase times and purchased quantities, Economic Journal, 111, 470, pp. 391-419, (2001); Brown J.R., Goolsbee A., Does the internet make markets more competitive? Evidence from the life insurance industry, Journal of Political Economy, 110, 3, pp. 481-507, (2002); Brynjolfsson E., Smith M.D., Frictionless Commerce? A Com- parison of Internet and Conventional Retailers, Management Science, 46, 4, (2000); Brynjolfsson E., Yu J.H., Smith M.D., Consumer surplus in the digital economy:Estimating the value of increased product variety at online booksellers, Management Science, 49, 11, pp. 1580-1596, (2003); Brynjolfsson E., Hu Y.J., Simester D., Goodbye Pareto Prin- ciple, Hello Long Tail: The Effect of Search Costs on Concentration of Product Sales, Management Science, 55, 11, pp. 1755-1765, (2011); Chintagunta P., Chu J., Cebollada J., Quantifying trasnsaction costs in online/off-Line Grocery Channel Choice, Marketing Science, 31, 1, pp. 96-114, (2012); Chu J., Chintagunta P., Cebollada J., A comparison of within- Household price sensitivity across online and offline channels, Marketing Science, 27, pp. 283-299, (2008); Danaher P.J., Wilson I.W., Davis R.A., A comparison of online and offline consumer brand loyalty, Marketing Science, 22, 4, pp. 461-476, (2003); Ellison G., Ellison S., Search, obfuscation, and Price Elasticities on the internet, Econometrica, 77, pp. 427-452, (2009); Erdem T., Imai S., Keane M., Price and Promotion Expectations: Capturing Consumer Brand and Quantity Choice Dynamics under Price Uncer- tainty, Quantitative Marketing and Economics, 1, pp. 5-64, (2003); Goldfarb A., McDevitt R.C., Samila S., Silverman B., \"the Effect of Social Interaction on Economic Transactions: An Embarrassment of Niches\", Working Paper, (2012); Griffith R., Leibtag E., Leicester A., Nevo A., Consumer shopping behavior:How much do consumers save, Journal of Economic Perspectives, 23, 2, pp. 99-120, (2009); Hendel I., Nevo A., Intertemporal Substitution and Storable Prod- ucts, Journal of the European Economic Association, 2, 23, pp. 536-547, (2004); Hendel I., Nevo A., Measuring the implications of sales and consumer inventory behavior, Econometrica, 74, 6, pp. 1637-1673, (2006); Hendel I., Nevo A., Sales and Consumer Inventory, RAND Journal of Economics, 37, 3, pp. 543-561, (2006); Neslin S.A., Schneider Stone L.G., Consumer inventory sensitivity and the postpromotion dip, Marketing Letters, 7, 1, pp. 77-94, (1996); Neslin S.A., Henderson C., Quelch J., Consumer Promotions and the Acceleration of Product Purchases, Marketing Science, 4, pp. 147-165, (1985); Pozzi A., Shopping Cost and Brand Exploration in Online Grocery, American Economic Journal: Microeconomics, 4, 3, pp. 96-120, (2012); Zentner A., Smith M.D., Kaya C., How Video Rental Patterns Change as Consumers Move Online, Management Science, (2013)","A. Pozzi; Einaudi Institute for Economics and Finance, Italy; email: andrea.pozzi@eief.it",{"$nulls":7},1677187.0,null,"IJIOD",null,"English","Int J Ind Organiz","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-84890115374"]
["Rezaee M.; Reisabadi E.","Rezaee, Mohammad (13104754500); Reisabadi, Esmatzare (57208116319)","13104754500; 57208116319","The necessity of using information technology in reverse logistics",2014.0,"Advances in Environmental Biology",8.0,13.0,null,1317.0,1323.0,6.0,0.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85063832712&partnerID=40&md5=cedfed980e12efaa4a4b26e1177dc7ac","Department of Industrial Engineering, Persian Gulf University of Technology, Bushehr, Iran","Rezaee M., Department of Industrial Engineering, Persian Gulf University of Technology, Bushehr, Iran; Reisabadi E., Department of Industrial Engineering, Persian Gulf University of Technology, Bushehr, Iran","Reverse logistics or returns management is one of the subjects that have received increasing attention in logistics and supply chain management in different industries during this period. In recent decades, many companies in developed countries have begun searching in this subject and taking it into account as one of the main processes in their supply chain management. Reverse logistics gain increased attention globally for economic and environmental reasons and it has caused to existence of new global competition between organizations. Reverse logistics include all operations that are related to the product returns such as: collection and inspection, material classification, processes related to returns, reuse and extension of useful lifecycle for used products. Nowadays, making connection and information transaction with suppliers, manufacturers and customers without information technology supporting, is not possible; according this, implementing information technology and e-commerce play an essential role in the chain. E-commerce focused on sharing business information, operating business negotiations, maintaining business relationships, settling and executing agreements by means of telecommunication networks, often the Internet, in order to achieve business transactions. In this paper, at first we consider the reverse logistics and related processes, then we discuss about the differences between forward and reverse logistics, the role of information technology and e-commerce, and new e-business models in reverse logistics. Finally, we talk about the challenges in this topic. © 2014 AENSI Publisher All rights reserved.","E-commerce; Information technology; Returns; Reverse logistics; Supply chain",{"$nulls":7},"Genchev E.S., Reverse logistics program design: A company study, Business Horizons, 52, pp. 139-148, (2009); Alshamrani A., Mathur K., Ballou R.H., Reverse logistics: Simultaneous design of delivery routes and returns strategies, Computers & Operations Research, 34, pp. 595-619, (2007); Dekker R., Fleischmann M., Wassenhove L., Reverse Logistics: Quantitive models for closed-loop supply chains, (2003); Kokkinaki A.I., Dekker R., Nunen J.V., Pappis C., An Exploratory Study on Electronic Commerce for Reverse Logistics Econometric Institute.Supply Chain Forum: An International Journal, 1, pp. 10-17, (2000); Fleischmann M., Bloemhof-Ruwaard J.M., Dekker R., Quantitative models for reverse logistics: A review, Eur. J. Oper, 103, pp. 1-17, (1997); Jamshidi M., Reverse Logistics, Logistics Operations and Management, pp. 247-326, (2011); Jayaraman V., Ros D., Agarwal A., Role of information technology and collaboration in reverse logistics supply chains, International Journal of Logistics: Research and Applications, 11, pp. 409-425, (2008); Patterson K.A., Grimm C.M., Corsi T.M., Adopting new technologies for supply chain management, Transportation Research part E, 39, pp. 95-121, (2003); Gunasekaran A., James Williams H., McGaughey R.E., Performance measurement and costing system in new enterprise, Technovation, 25, pp. 523-533, (2005); Lancioni R., Hope J.S., Michaeal F.S., Internet impacts on supply chain management, Industrial Marketing Management, 32, pp. 173-175, (2003); Mahajan J., Asoo J.V., Determining firm-level IT investments to facility value chain activities: Should spillovers accruing to value chain members be incorporated?, European Journal of Operational, 156, pp. 665-682, (2004); Gunasekaran A., Ngai E.W.T., Information systems in supply chain integration and management, European Journal of Operational Research, 159, pp. 269-295, (2004); Kokkinaki A.I., Dekker R., de Koster M.B.M., Pappis C., Verbeke W., E-business Models for Reverse Logistics: Contributions and Challenges, International Conference on Information Technology, pp. 1-7, (2002); Lee H.G., AUCNET: Electronic Intermediary for Used-Car Transactions, Electronic Markets, 7, pp. 24-28, (1997)",null,null,"American-Eurasian Network for Scientific Information",{"$nulls":5},1.9950756E7,null,null,null,"English","Adv. Environ. Biol.","Article","Final",null,"Scopus","2-s2.0-85063832712"]
["Chou S.; Chen C.-W.; Lin J.-Y.","Chou, Shihyu (7401538519); Chen, Chi-Wen (56729737900); Lin, Jiun-You (56729243400)","7401538519; 56729737900; 56729243400","Female online shoppers: Examining the mediating roles of e-satisfaction and e-trust on e-loyalty development",2015.0,"Internet Research",25.0,4.0,null,542.0,561.0,19.0,102.0,"10.1108/IntR-01-2014-0006","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84937579208&doi=10.1108%2fIntR-01-2014-0006&partnerID=40&md5=ebf858724df332c3ecba2a45ee363f47","Department of Business Administration, National Taiwan Normal University, Taipei, Taiwan; Department of Computer Information Systems, City University of New York, New York, NY, United States; Department of Marketing, National Chung Hsing University, Taichung, Taiwan","Chou S., Department of Business Administration, National Taiwan Normal University, Taipei, Taiwan; Chen C.-W., Department of Computer Information Systems, City University of New York, New York, NY, United States; Lin J.-Y., Department of Marketing, National Chung Hsing University, Taichung, Taiwan","Purpose – As the number of female customers shopping in online clothing stores increases, understanding how female customers’ e-loyalty is formed and fostered in this type of online store becomes very pivotal. Yet, despite its importance, little research has been done on this issue. The purpose of this paper is to focus on female online clothing shoppers and aim to examine the mediators of e-loyalty in the context of online clothing stores: e-satisfaction and e-trust. Design/methodology/approach – A total of 482 subjects who are female and have online clothing store shopping experience in Taiwan were obtained and structural equation modeling was performed to analyze the measurement and structural models. Findings – The results show that both perceived online privacy and security are positively associated with e-trust, whereas web design is not. Furthermore, perceived delivery time and web site design are positively associated with e-satisfaction. Both e-trust and e-satisfaction in turn positively influence e-loyalty for female online clothing shoppers. Research limitations/implications – On the basis of the literature review, there is a lack of theoretical knowledge of the relationships between e-loyalty, e-satisfaction, and e-trust among female online clothing shoppers. The research fulfills this important theoretical gap by extending prior studies on e-loyalty to further examine the factors that form e-satisfaction and e-trust, and how they, as mediators, influence the development of female customers’ e-loyalty in the context of online clothing stores. The result provides a model that contributes to understanding the formation of female customers’ e-loyalty. Practical implications – The results of this study are helpful to online store managers in increasing their customers’ loyalty. Specifically, online clothing store managers have to create quick item delivery methods and friendly online shopping web sites that provide all necessary information and are easy to navigate and use so as to increase customers’ e-satisfaction. They also need to establish reliable and trustworthy web sites by letting their customers easily perceive the web sites’ privacy and security features to enhance customers’ e-trust. As e-satisfaction and e-trust increase, e-loyalty is fostered. Originality/value – The contributions of this study are threefold. First, this study focusses on an important but previously neglected group in the context of online clothing stores: female online clothing shoppers. Second, the authors’ investigation extends the literature on e-loyalty by identifying important mediators (e-satisfaction and e-trust) and probing into their relationships to e-loyalty in the context of online clothing stores. Third, the findings contribute to academia and to future research by increasing understandings of the importance of the concerns and experiences of female online clothing shoppers and by suggesting that future research pay more attention to female online shoppers. © Emerald Group Publishing Limited.","e-Loyalty; e-Satisfaction; e-Trust; Female online clothing shoppers; Perceived online privacy; Perceived online security",{"$nulls":7},"Anderson R.E., Srinivasan S.S., E-satisfaction and e-loyalty: A contingency framework, Psychology &Amp; Marketing, 20, 2, pp. 123-138, (2003); Bagozzi R.P., Yi Y., On the evaluation of structural equation models, Journal of the Academy of Marketing Science, 16, 1, pp. 74-94, (1988); Brown S.A., Viswanath V., Model of adoption of technology in households: A baseline model test and extension incorporating household life cycle, MIS Quarterly, 29, 3, pp. 399-426, (2005); Chandrashekaran M., Rotte K., Tax S.S., Grewal R., Satisfaction strength and customer loyalty, Journal of Marketing Research, 44, 1, pp. 153-163, (2007); Chen Y.H., Wu J.J., Chang H.T., Examining the mediating effect of positive moods on trust repair in e-commerce, Internet Research, 23, 3, pp. 355-371, (2013); Cho H., Fiorito S.S., Acceptance of online customization for apparel shopping, International Journal of Retail &Amp; Distribution Management, 37, 5, pp. 389-407, (2009); Cho J., Likelihood to abort an online transaction: Influences from cognitive evaluations, attitudes, and behavioral variables, Information &Amp; Management, 41, 7, pp. 827-838, (2004); Collier J.E., Carol C.B., Measuring service quality in e-retailing, Journal of Service Research, 8, 3, pp. 260-275, (2006); Connolly R., Frank B., Consumer trust in electronic commerce: Social & technical antecedents, World Academy of Science, Engineering and Technology, 2, 4, pp. 239-248, (2007); Constantinides E., Influencing the online consumers behavior: The web experience”, Internet Research, 14, 2, pp. 111-126, (2004); Constantinides E., Lorenzo-Romeroand C., Gomez M.A., Effects of web experience on consumer choice: A multicultural approach, Internet Research, 20, 2, pp. 188-209, (2010); 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Management, 43, 1, pp. 1-14, (2006); Garbarino E., Strahilevitz M., Gender differences in the perceived risk of buying online and the effects of receiving a site recommendation, Journal of Business Research, 57, 7, pp. 768-775, (2004); Goetzinger L., Park J.K., Widdows R., E-customers third party complaining and complimenting behavior”, International Journal of Service Industry Management, 17, 2, pp. 193-206, (2006); Goldsmith R.E., Flynn L.R., Psychological and behavioral drivers of online clothing purchase, Journal of Fashion Marketing and Management, 8, 1, pp. 84-95, (2004); Gommans M., Krishnan K.S., Scheffold K.B., From brand loyalty to e-loyalty: A conceptual framework, Journal of Economic and Social Research, 3, 1, pp. 43-58, (2001); Ha S., Stoel L., Online apparel retailing: Roles of e-shopping quality and experiential e-shopping motives, Journal of Service Management, 23, 2, pp. 197-215, (2012); Hampton-Sosa W., Koufaris M., The effect of web site perceptions on initial trust in the owner company, International Journal of Electronic Commerce, 10, 1, pp. 55-81, (2005); 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Luscombe B., Woman power: The rise of the sheconomy, Time Magazine, (2010); Milne G.R., Culnan M.J., Strategies for reducing online privacy risks: Why consumers read (or dont read) online privacy notices”, Journal of Interactive Marketing, 18, 3, pp. 15-29, (2004); Mueller R.O., Basic Principles of Structural Equation Modeling: An Introduction to LISREL and EQS, (1996); Munro B.H., Statistical Methods for Health Care Research, (2005); Myers C.A., Mintu-Wimsatt A., Exploring antecedents influencing internet shopping satisfaction: The case of the apparel industry, International Journal of Business and Social Science, 3, 8, pp. 1-9, (2012); Nguyen N., Leclerc A., Leblanc G., The mediating role of customer trust on customer loyalty, Journal of Service Science &Amp; Management, 6, 1, pp. 96-109, (2013); Nsairi Z.B., Khadraoui M., Website satisfaction: Determinants and consequences on website loyalty, International Business Research, 6, 9, pp. 77-92, (2013); Oliver R.L., Satisfaction: A Behavioral Perspective on the Consumer, (1997); 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Yang Z., Peterson R.T., Customer perceived value, satisfaction, and loyalty: The role of switching costs, Psychology &Amp; Marketing, 21, 10, pp. 799-822, (2004); Yen Y.S., Can perceived risks affect the relationship of switching costs and customer loyalty in e-commerce?, Internet Research, 20, 2, pp. 210-224, (2010); Yousafzai S.Y., Pallister J.G., Foxall G.R., A proposed model of e-trust for electronic banking, Technovation, 23, 11, pp. 847-860, (2003); Zhou L., Dai L., Zhang D., Online shopping acceptance model-a critical survey of consumer factors in online shopping, Journal of Electronic Commerce Research, 8, 1, pp. 41-62, (2007)","C.-W. Chen; Department of Computer Information Systems, City University of New York, New York, United States; email: chchen@csudh.edu",null,"Emerald Group Holdings Ltd.",{"$nulls":5},1.0662243E7,null,null,null,"English","Internet Res.","Article","Final",null,"Scopus","2-s2.0-84937579208"]
["Doherty N.F.; Shakur M.; Ellis-Chadwick F.","Doherty, Neil F. (7006826558); Shakur, Mahani (56811255500); Ellis-Chadwick, Fiona (6506549147)","7006826558; 56811255500; 6506549147","The role of e-service quality management in the delivery business value",2015.0,"Journal of Retailing and Consumer Services",27.0,null,null,52.0,62.0,10.0,16.0,"10.1016/j.jretconser.2015.07.002","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84940492053&doi=10.1016%2fj.jretconser.2015.07.002&partnerID=40&md5=4598e20b93072ba811f7257fac986789","School of Business and Economics, Loughborough University, Loughborough, Leicestershire, LE11 3TU, United Kingdom; Department of Economics, Faculty of Economics and Business, University of Malaysia, Sarawak, Malaysia","Doherty N.F., School of Business and Economics, Loughborough University, Loughborough, Leicestershire, LE11 3TU, United Kingdom; Shakur M., Department of Economics, Faculty of Economics and Business, University of Malaysia, Sarawak, Malaysia; Ellis-Chadwick F., School of Business and Economics, Loughborough University, Loughborough, Leicestershire, LE11 3TU, United Kingdom","In sharp contrast to the extensive debate that has been conducted in the contemporary literature, with regard to consumers' perceptions of e-service quality, the voice of those managing e-service quality has remained relatively silent. Against this backdrop, the primary aim of the research presented in this paper is to address the gap in the literature with regard to the role of electronic service quality management in leveraging business value from on-line retailing strategies. The study was undertaken using a quantitative research methodology, based upon questionnaires, which resulted in a sample of 225 responses, completed by senior managers from across the UK's on-line retail sector. The results of the statistical analyses have demonstrated that the perceived success of a retailer's e-commerce operations is strongly associated with both the management approaches to e-service quality and the level of e-commerce adoption. Of particular interest is our finding that as the scale and scope of a retailer's e-commerce operations grow, there is a concomitant need for its e-service quality operations to develop, if it is to realise the full value from its on-line activities. The article adds to the body of knowledge regarding the management of electronic service quality while also seeking to stimulate critical debate concerning the role of service quality practises within prevailing IT value discourses. © 2015 Elsevier Ltd.","Business value; Electronic-commerce; Retail trade; Service quality; Survey","United Kingdom; business service; electronic commerce; management; qualitative analysis; retailing; survey; trade",{"$nulls":6},"Aguila-Obra A.R.D., Padilla-Melendez A., Organizational factors affecting Internet technology adoption, Internet Res., 16, 1, pp. 91-110, (2006); Armstrong J.S., Overton T.A., Estimating non-response bias in mail surveys, Marketing Research: Applications and Problems, (1982); Ashurst C., Doherty N.F., Peppard J., Improving the impact of IT development projects: the benefits realization capability model, Eur. J. Inf. Syst., 17, pp. 352-370, (2008); Basu A., Muylle S., Online support for commerce processes by web retailers, Decis. 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Commer., 7, 3, pp. 7-37, (2003)","N.F. Doherty; School of Business and Economics, Loughborough University, Loughborough, Leicestershire, LE11 3TU, United Kingdom; email: N.F.Doherty@lboro.ac.uk",null,"Elsevier Ltd",{"$nulls":5},9696989.0,null,null,null,"English","J. Retail. Consum. Serv.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-84940492053"]
["Tandon U.; Kiran R.; Sah A.N.","Tandon, Urvashi (57190029593); Kiran, Ravi (22985431500); Sah, Ash N. (57190030141)","57190029593; 22985431500; 57190030141","Analysing the complexities of website functionality, perceived ease of use and perceived usefulness on customer satisfaction of online shoppers in India",2016.0,"International Journal of Electronic Marketing and Retailing",7.0,2.0,null,115.0,140.0,25.0,18.0,"10.1504/IJEMR.2016.077118","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84976641109&doi=10.1504%2fIJEMR.2016.077118&partnerID=40&md5=cbf209511446e1fbf72be327ad95963b","School of Humanities and Social Sciences (SHSS), Thapar University, P.O. Box 32, Patiala, 147004, India","Tandon U., School of Humanities and Social Sciences (SHSS), Thapar University, P.O. Box 32, Patiala, 147004, India; Kiran R., School of Humanities and Social Sciences (SHSS), Thapar University, P.O. Box 32, Patiala, 147004, India; Sah A.N., School of Humanities and Social Sciences (SHSS), Thapar University, P.O. Box 32, Patiala, 147004, India","This research was undertaken to examine key predictors influencing customer satisfaction towards online retailing in India. The findings of the study reveal that perceived usefulness, perceived ease of use and website design have positive impact on customer satisfaction. Perceived time performance emerged as strongest predictor of customer satisfaction indicating a strong positive association between perceived usefulness and customer satisfaction. The emergence of ease of purchase, ease of understanding, and ease of navigation also appeared as significant variables leading to customer satisfaction where ease of ordering had a significant but negative impact. This research will help online retailers in India to motivate new customers for online shopping and existing customers to extend it in their daily purchase. The scale of ease of use and perceived usefulness have been extended in emerging economies context. New scale items like satisfaction with cash-on-delivery mode of payment have been examined in the present study. © Copyright 2016 Inderscience Enterprises Ltd.","Customer satisfaction; India; Online retailing; Online shopping; Perceived ease of use; Perceived usefulness; TAM; Technology acceptance model; Website functionality",{"$nulls":7},"Ajzen I., The theory of planned behavior, Organizational Behavior and Human Decision Processes, 50, 11, pp. 179-211, (1991); Bhattacharjee A., Understanding information system continuance; an expectation confirmation model, MIS Quarterly, 25, 13, pp. 351-370, (2001); Cassalo L., Flavian C., Guinaliu M., The role of perceived usability, reputation, satisfaction and consumer familiarity on website loyalty formation process, Computers in Human Behaviour, 24, 2, pp. 325-345, (2008); Chen H.Y., Hsu C.I., Lin C.C., Website attributes that increase consumer purchase intention: A conjoint analysis, Journal of Business Research, 63, 9-10, pp. 1007-1014, (2010); 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Udo J.G., Bagchi K.K., Peeter J.K., An assessment of customer's e-service quality perception, satisfaction and intention, International Journal of Information Management, 30, 6, pp. 481-492, (2010); Varshney R., India's digital commerce market to grow 33% to $ 11.6 bn in 2013, e-commerce-market-to-grow-33-to-11-6b-in-2013-e-tailing to lead growth, IAMAI, (2013); Venkatesh V., Morris M.G., Davis G.B., Davis F.D., User acceptance of information technology: Toward a unified view, MIS Quarterly, 27, 3, pp. 425-478, (2003); Wang F., Head M., How can web help build customer relationships? An empirical study on e-tailing, Information and Management, 44, 2, pp. 115-129, (2007); Wolfinbarger M., Gilly M.C., Etailq: Dimensionalising, measuring and predicting e-tail quality, Journal of Retailing, 79, 3, pp. 183-198, (2003); Wu L.-I., The antecedents of customer satisfaction and its link to complaint intentions in online shopping: An integration of justice, technology, and trust, International Journal of Information Management, 33, 1, pp. 166-176, (2013); Zhou L., Dai L., Zhang D., Online shopping acceptance model - A critical survey of consumer factors in online shopping, Journal of Electronic Commerce Research and Applications, 8, 1, pp. 41-62, (2007)","U. Tandon; School of Humanities and Social Sciences (SHSS), Thapar University, Patiala, P.O. Box 32, 147004, India; email: urvashiguptav@gmail.com",null,"Inderscience Publishers",{"$nulls":5},1.7411025E7,null,null,null,"English","Int. J. Electron. Mark. Retail.","Article","Final",null,"Scopus","2-s2.0-84976641109"]
["Lai L.S.L.; To W.-M.","Lai, Linda S.L. (24338465700); To, Wai-Ming (57205130555)","24338465700; 57205130555","Internet diffusion in China: Economic and social implications",2012.0,"IT Professional",14.0,6.0,6203494.0,16.0,21.0,5.0,15.0,"10.1109/MITP.2012.65","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84870502808&doi=10.1109%2fMITP.2012.65&partnerID=40&md5=268ff9ee8d1a8294452ca341fd80c0bb","Macao Polytechnic Institute, Macao","Lai L.S.L., Macao Polytechnic Institute, Macao; To W.-M., Macao Polytechnic Institute, Macao","This article explores the economic and social implications of Internet diffusion in China. With the penetration rate and application of e-commerce technologies expected to surge in the next three years, IT professionals will have ample opportunities to engage customers. © 1999-2012 IEEE.","China; innovation diffusion; Internet adoption; logistic growth","Diffusion; Social aspects; China; Innovation diffusion; Internet adoption; Internet diffusion; IT professional; Logistic growth; Penetration rates; Social implication; Internet",{"$nulls":6},"Harwit E., Clark D., Shaping the internet in China: Evolution of political control over network infrastructure and content, Asian Survey, 41, 3, pp. 377-408, (2001); Top 20 countries with highest number of internet users, Internet World Stats, (2012); Lai L.S.L., To W.M., The emergence of china in the internet market, IT Professional, 14, 1, pp. 6-9, (2012); Rogers E.M., Diffusion of Innovation, (2003); Yang Y., Williams E., Logistic model-based forecast of sales and generation of obsolete computers in the US, Technological Forecasting and Social Change, 76, 8, pp. 1105-1114, (2009); Morris M., Ogan C., The internet as mass medium, J. Comm, 46, 1, pp. 39-50, (1996); Robinson J.P., Kestnbaum M., Neustadtl A., Alvarez A., Mass Media Use and Social Life Among Internet Users, Social Science Computer Review, 18, 4, pp. 490-501, (2000); DiMaggio P., Hargittai E., Neuman W.R., Robinson J.P., Social Implications of the Internet, Annual Review of Sociology, 27, pp. 307-336, (2001); The 27th china internet development statistics report, China Internet Information Center, (2011); Alexa Internet Rankings, (2011); Liu Y., Li H., Mobile internet diffusion in china: An empirical study, Industrial Management & Data Systems, 110, 3, (2010); Lu J., Weber I., Internet software piracy in china: A user analysis of resistance to global software copyright enforcement, J. Int'l and Intercultural Comm, 2, 4, (2009); Song M., The evaluation model about youth selforganizations in china based on internet media perspective, Proc. 3rdInt'l Symp. Intelligent Information Technology Application (IITA 09 IEEE, (2009); Millman C., Et al., Entrepreneurship education and students' internet entrepreneurship intentions evidence from chinese HEIs, J. Small Business and Enterprise Development, 17, 4, (2010); MacKinnon R., Flatter world and thicker walls? blogs, censorship and civic discourse in china, Public Choice, 134, 1, pp. 31-46, (2008)","L.S.L. Lai; Macao Polytechnic Institute, Macao; email: sllai@ipm.edu.mo",{"$nulls":7},1.5209202E7,null,"IPMAF",null,"English","IT Prof","Article","Final",null,"Scopus","2-s2.0-84870502808"]
["Crocco F.; Eboli L.; Mazzulla G.","Crocco, Federica (35783922900); Eboli, Laura (24921250100); Mazzulla, Gabriella (6506549346)","35783922900; 24921250100; 6506549346","Individual attitudes and shopping mode characteristics affecting the use of e-shopping and related travel",2013.0,"Transport and Telecommunication",14.0,1.0,null,45.0,56.0,11.0,47.0,"10.2478/ttj-2013-0006","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84882254607&doi=10.2478%2fttj-2013-0006&partnerID=40&md5=8d6cce575261d253d079e22f279e1080","University of Calabria, Faculty of Engineering, Department of Land Use Planning, 87036 Rende (CS), P. Bucci, Cubo 46/B, Italy","Crocco F., University of Calabria, Faculty of Engineering, Department of Land Use Planning, 87036 Rende (CS), P. Bucci, Cubo 46/B, Italy; Eboli L., University of Calabria, Faculty of Engineering, Department of Land Use Planning, 87036 Rende (CS), P. Bucci, Cubo 46/B, Italy; Mazzulla G., University of Calabria, Faculty of Engineering, Department of Land Use Planning, 87036 Rende (CS), P. Bucci, Cubo 46/B, Italy","New telecommunication technologies and services have caused important challenges on travel behaviour and trip characteristics. Existing literature studies show many different outcomes regarding the effects of the new technologies on the participation of people to their personal activities and related travel; specifically, e-shopping may produce the reduction of shopping trips (substitution effect), but also an increase of trips thanks to the reuse of the travel time saved for other activities and trips (complementarity's effect). The focus of this study is to analyse the aspects mostly affecting consumer choices of purchasing goods by web or in-store, with the aim of understanding how to operate so that e-shopping can positively modify consumers' travel behaviour. Our research findings show that individual social and economic factors, consumer attitudes, and shopping mode characteristics influence the usage of online shopping. An experimental survey addressed to a sample of Italian consumers is used in the study.","E-commerce; Logistic regression models; Travel behaviour",{"$nulls":7},"Salomon I., Telecommunications and travel relations: A review, Transportation Research Part A, 20, 3, pp. 223-238, (1986); Salomon I., Technological change and social forecasting: The case of telecommuting as a travel substitute, Transportation Research Part C, 6, pp. 17-45, (1998); Handy S.L., Yantis T., The Impacts of Telecommunications Technologies on Nonwork Travel Behaviour., (1997); Golob T.F., Regan A.C., Impacts of information technology on personal travel and commercial vehicle operations: Research challenges and opportunities, Transportation Research Part C, 9, pp. 87-121, (2001); Mokhtarian P.L., Salomon I., Handy S., A Taxonomy of Leisure Activities: The Role of ICT, (2004); Weltevreden J.W.J., Rotem-Mindali O., Mobility effects of b2c and c2c e-commerce in the Netherlands: A quantitative assessment, Journal of Transport Geography, 17, pp. 83-92, (2009); Salomon I., Can telecommunications help solve transportation problems, Handbook of Transport Modelling, pp. 449-462, (2000); Mokhtarian P.L., A typology of relationships between telecommunications and transportation, Transportation Research Part A, 24, pp. 231-242, (1990); Andreev P., Salomon I., Pliskin N., Review: State of teleactivities, Transportation Research Part C, 18, pp. 3-20, (2010); Mokhtarian P.L., A conceptual analysis of the transportation impacts of B2C e-commerce, Transportation, 31, pp. 25-284, (2004); Ferrell C.E., Home-based teleshopping and shopping travel: Where do we find the time?, Transportation Research Record, 1926, pp. 211-223, (2005); Papola A., Polydoropoulou A., Shopping-related travel in a rich ICT era. A case study on the impact of e-shopping on travel demand, Proceedings of the 85th Annual Meeting of the Transportation Research Board, (2006); Casas J., Zmud J., Bricka S., Impact of shopping via internet on travel for shopping purposes, Proceedings of the 80th Annual Meeting of the Transportation Research Board, (2001); Circella G., Mokhtarian P., Complementarity or substitution of online and in-store shopping: An empirical analysis from northern california, Proceedings of the 89th Annual Meeting of the Transportation Research Board, (2010); Hjorthol R., Information searching and buying on the Internet: Travel-related activities?, Environment and Planning Part B, 36, pp. 229-244, (2009); Chang M.K., Cheung W., Lai V.S., Literature derived reference models for the adoption of online shopping, Information & Management, 42, pp. 543-559, (2005); Peterson R.A., Balasubramanian S., Bronnenberg B.J., Exploring the implications of the internet for consumer marketing, Journal of the Academy of Marketing Science, 25, 4, pp. 329-346, (1997); Schiffman L.G., Kanuk L.L., Consumer Behavior, (1987); Salomon I., Koppelman F., A framework for studying teleshopping versus store shopping, Transportation Research Part A, 22, 4, pp. 247-255, (1988); Hsiao M.H., Shopping mode choice: Physical store shopping versus e-shopping, Transportation Research Part E, 45, pp. 86-95, (2009); Farag S., Dijst M., Lanzendorf M., Exploring the use of e-shopping and its impact on personal travel behaviour in the Netherlands, Proceedings of the 82nd Annual Meeting of the Transportation Research Board, (2003); Salomon I., Koppelman F., Teleshopping or going shopping: An information acquisition perspective, Behaviour and Information Technology, 11, pp. 189-198, (1992); Vrechopoulos A.P., Siomkos G.J., Doukidis G.I., Internet shopping adoption by greek consumers, European Journal of Innovation Management, 3, pp. 142-152, (2001); Lee P., Behavioral model of online purchasers in E-commerce environment, Electronic Commerce Research, 2, pp. 75-85, (2002); Szymanski D.M., Hise R.T., E-Satisfaction: An initial examination, Journal of Retailing, 76, pp. 309-322, (2000); Koppelman F., Salomon I., Proussalogou K., Teleshopping or store shopping? A choice model for forecasting the use of new telecommunications-based services, Environment and Planning B, 18, pp. 473-489, (1991); Raijas A., The consumer benefits and problems in the electronic grocery store, Journal of Retailing and Consumer Services, 9, pp. 107-113, (2002); Hjorthol R.J., The relation between daily travel and use of the home computer, Transportation Research Part A, 36, pp. 437-452, (2002); Zmud J., Arce C., E-mobility (Electronic travel): Measuring new and evolving behaviour, Proceedings of the 9th Conference of the International Association for Travel Behaviour Research, (2000); Dijst M., Farag S., Schwanen T., A comparative study of attitude theory and other theoretical models for understanding travel behaviour, Environment and Planning A, 40, pp. 831-847, (2008); Farag S., Schwanen T., Dijst M., Shopping online and/or in-store? A structural equation model of the relationships between e-shopping and in-store shopping, Transportation Research Part A, 41, pp. 125-141, (2007); Van U.P., Senior M., The contribution of mixed land uses to sustainable travel in cities, Achieving Sustainable Urban Form, pp. 139-148, (2000)",{"$nulls":8},1.4076179E7,null,null,null,"English","Transp. Telecommun.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-84882254607"]
["Piercy N.","Piercy, Niall (26639839800)",2.66398398E10,"Online service quality: Content and process of analysis",2014.0,"Journal of Marketing Management",30.0,"2024-08-07",null,747.0,785.0,38.0,26.0,"10.1080/0267257X.2013.839571","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84996781292&doi=10.1080%2f0267257X.2013.839571&partnerID=40&md5=cdb0047f40a349802efc9f56764639cb","Operations Management and Entrepreneurship Department, School of Management, Swansea University, United Kingdom","Piercy N., Operations Management and Entrepreneurship Department, School of Management, Swansea University, United Kingdom","The purpose of this paper is to build a comprehensive model of online service quality that confirms both the content of, and process of measuring, this higher-order construct. While the past decade has seen the Internet become a key channel for service delivery, there remains uncertainty around many aspects of both the content of, and process of how to measure, online service quality. We use a large sample of European consumers (n = 3399) of four companies (two pure play and two multichannel) to develop a new nine-dimension model of online service quality. We validate importance as a disconfirmation standard. We find trust in the company to be the most important dimension of online service quality, with customer service also highly rated. Issues of personalisation/customisation were very low rated. We find the online pure-play companies in the sample delivering better performance than multichannel retailers, despite having customers who are actually more demanding. We discuss the practical and research implications of these findings © 2013 Westburn Publishers Ltd.","E-commerce; Retail; Service quality",{"$nulls":7},{"$cut":{"chars":20008,"head":"Armstrong J., Overton T., Estimate nonresponse bias in mail surveys, Journal of Marketing Research, 14, 3, pp. 396-402, (1977); Assael H., A demographic and psychographic profile of heavy Internet users, Journal of Advertising Research, 45, 1, pp. 93-123, (2005); Asubonteng P., McCleary K., Swan E., Servqual revisited: A critical review of service quality, The Journal of Services Marketing, 10, 6, pp. 62-81, (1996); Babakus E., Boller G., An empirical assessment of the SERVQUAL scale, Journal of Business Research, 24, pp. 253-268, (1992); Bacon D., A comparison of approaches to importance-performance analysis, International Journal of Market Research, 45, 1, pp. 55-140, (2003); Barnes S., Vidgen R., An integrative approach to the assessment of e-commerce quality, Journal of Electronic Commerce, 3, 3, pp. 114-127, (2002); Bauer H., Falk T., Hammerschmidt M., ETransQual: A transaction process-based approach for capturing service quality in online shopping, Journal of Business Research, 59, pp. 866-875, (2006); Bell J., Loane S., New wave global firms, Journal of Marketing Management, 26, 3-4, pp. 213-229, (2010); Boulding W., Kalra A., Staelin R., Zeithaml V., A dynamic process model of service quality, Journal of Marketing Research, 30, pp. 7-27, (1993); Boyer K., Hult T., Customer behavioural intentions for online purchasers, Journal of Operations Management, 24, pp. 124-147, (2006); Brown T., Churchill G., Peter J., Improving the measurement of service quality, Journal of Retailing, 69, 1, pp. 127-139, (1993); Byrne B., Structural Equation Modeling with AMOS, (2001); Carman J., Consumer perceptions of service quality, Journal of Retailing, 66, 1, pp. 33-55, (1990); Caruana A., Ewing M., Ramaseshan B., Assessment of the three-column format SERVQUAL, Journal of Business Research, 49, pp. 57-65, (2000); Cattell R.B., The Scientific Use of Factor Analysis, (1978); Chazelle B., The Discrepancy Method: Randomness and Complexity, (2000); Chen Q., Wells W., Attitude toward the site, Journal of Advertising Research, 39, 5, pp. 27-37, (1999); Churchill J., A paradigm for developing better measures of marketing constructs, Journal of Marketing Research, 16, 1, pp. 64-73, (1979); Cohen J., Cohen P., Applied Multiple Regression/Correlation Analysis for the Behavioural Sciences, (1983); Collier J., Bienstock C., A conceptual framework for measuring e-service quality, Proceedings of the Developments in Marketing Science, pp. 158-162, (2003); Connolly R., Bannister F., Kearney A., Government website service quality, European Journal of Information Systems, 19, pp. 649-667, (2010); Cravens D., Dielman T., Harrington C., Using buyers perceptions of service quality to guide strategy development, American Marketing Association Educators Proceedings, pp. 297-301, (1985); Crompton J., Duray N., An investigation of the relative efficacy of four alternative approaches to importance-performance analysis, Academy of Marketing Science Journal, 13, 4, pp. 69-80, (1985); Cronin J., Taylor S., Measuring service quality: A re-examination and extension, Journal of Marketing, 56, 3, pp. 55-68, (1992); Dabholkar P.A., Thorpe D., Rentz J., A measure of service quality for retail stores: Scale development and validation, Journal of the Academy of Marketing Science, 24, 1, pp. 3-16, (1996); Demangeot C., Broderick A., Exploration and its manifestations in the context of online shopping, Journal of Marketing Management, 26, 13-14, pp. 1256-1278, (2010); Dennis C., Jayawardhena C., Papamatthaiou E., Antecedents of Internet shopping intentions and the moderating effects of substitutability, International Review of Retail Distribution and Consumer Research, 20, 4, pp. 411-430, (2010); Dennis C., Merrilees B., Jayawardhena C., Wright L., E-consumer behaviour, European Journal of Marketing, 43, 9-10, pp. 1121-1139, (2009); Deutskens E., Ruyter K., Wetzels M., Oosterveld P., Response rate and response quality of Internet based surveys, Marketing Letters, 15, 1, pp. 21-36, (2004); Evanschitzky H., Iyer G., Hesse J., Ahlert D., E-satisfaction: A re-examination, Jou"}},"N. Piercy; School of Management, Swansea University, Swansea, SA2 8PP, United Kingdom; email: N.C.Piercy@swansea.ac.u",null,"Routledge",{"$nulls":5},"0267257X",null,null,null,"English","J. Mark. Manage.","Article","Final",null,"Scopus","2-s2.0-84996781292"]
["Li H.; Ru Y.; Han J.","Li, Hanqing (36918620000); Ru, Yihong (25929574400); Han, Jihua (56170985400)","36918620000; 25929574400; 56170985400","Distribution network optimization and risk analysis of chinese ecommerce enterprise",2012.0,"Advances in Information Sciences and Service Sciences",4.0,23.0,null,41.0,47.0,6.0,2.0,"10.4156/AISS.vol4.issue23.5","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84872091743&doi=10.4156%2fAISS.vol4.issue23.5&partnerID=40&md5=4591cbd50f4fe60135c4564f40b31e1c","Beijing Jiaotong University, China","Li H., Beijing Jiaotong University, China; Ru Y., Beijing Jiaotong University, China; Han J., Beijing Jiaotong University, China","The current study shows that the target of the optimization model of the logistics distribution network is to obtain the minimum vehicle driving distance. They take the total operation cost into consideration, which relates closely to the vehicle driving distance and the unit cost. However in China, those large-scale E-commerce enterprises unusually choose to build their own distribution network. Therefore, the initial cost will far outnumber the operating cost in a certain time. It takes two factors into account, which are the operating cost and vehicle starting cost, to make up the distribution network optimization model. This paper selects a large-scale E-commerce enterprise in China called GD as the case study. And we establish a model based on the lowest starting and operating costs of the time windows. This model optimize the GD distribution networks of Shanghai, which proves that the vehicle starting cost is an important factor in optimizing the distribution networks. Also, we identify the risk conduction mechanism of the E-commerce logistics outsourcing as a future research direction.","Distribution network; E-commerce enterprise; Logistics risk","Electric power distribution; Industry; Mathematical models; Operating costs; Optimization; Vehicles; Conduction Mechanism; Driving distance; Future research directions; Initial costs; Logistics distribution; Logistics outsourcing; Model-based OPC; Network optimization; Operation cost; Optimization models; Time windows; Unit cost; Electronic commerce",{"$nulls":6},"IResearch: 2011 China Buying Online market research report, pp. 2-3, (2011); Ramanathan R., The moderating roles of risk and efficiency on the relationship between logistics performance and customer loyalty in e-commerce, Transportation Research Part E: Logistics and Transportation Review, 46, 6, pp. 950-962, (2010); Tao Z., Chaovalitwongse W.A., Yuejie Z., Scatter search for the stochastic travel-time vehicle routing problem with simultaneous pick-ups and deliveries, Computers & Operations Research, 39, pp. 2277-2290, (2012); Cordeau J.-F., Mirko M., A parallel iterated tabu search heuristic for vehicle routing problems, Computers & Operations Research, 39, (2012); Andreas B., A hybrid algorithm for the capacitated vehicle routing problem with threedimensional loading constraints, Computers & Operations Research, 39, 9, pp. 2248-2257, (2012); Andres F.M., The time dependent vehicle routing problem with time windows: Benchmark problems, an efficient solution algorithm, and solution characteristics, Transportation Research Part E-Logistics And Transportation Review, 48, (2011); Chen R.-M., Wang C.-M., Vehicle Routing Problem Application in Tour Planning Multimedia System with Metaheuristic Designed, AISS: Advances in Information Sciences and Service Sciences, 3, 2, pp. 1-11, (2011); Ahmadir D., Charkari N.M., Enami N., E-Negotiation System Based on Intelligent Agents in B2C E-Commerce, AISS: Advances in Information Sciences and Service Sciences, 3, 2, pp. 60-70, (2011); Pan W.-T., Chen P.-W., A Study on the Logistic Service Satisfaction for Internet Marketing Enterprise Using Data Mining Technology, AISS: Advances in Information Sciences and Service Sciences, 3, 2, pp. 114-120, (2011); Kim S., Hoffmann C., Lee J.M., An Experimental in Rule-based Crowd Behavior for Intelligent Games, AISS: Advances in Information Sciences and Service Sciences, 2, 3, pp. 32-39, (2010)","H. Li; Beijing Jiaotong University, China; email: hanqingbjtu@gmail.com",{"$nulls":7},2.2339345E7,null,null,null,"English","Adv. Inf. Sci. Serv. Sci.","Article","Final",null,"Scopus","2-s2.0-84872091743"]
["Liu D.","Liu, Dawei (26643477600)",2.66434776E10,"Network site optimization of reverse logistics for E-commerce based on genetic algorithm",2014.0,"Neural Computing and Applications",25.0,1.0,null,67.0,71.0,4.0,29.0,"10.1007/s00521-013-1448-1","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84902511236&doi=10.1007%2fs00521-013-1448-1&partnerID=40&md5=d5cc50d52a8f7f8ae8bbb711352dd436","School of Management, Hangzhou Dianzi University, Hangzhou, 310018 Zhejiang, No. 1st, 2nd Ave. Xiasha Education Zone, China","Liu D., School of Management, Hangzhou Dianzi University, Hangzhou, 310018 Zhejiang, No. 1st, 2nd Ave. Xiasha Education Zone, China","Product returns have been viewed as an unavoidable cost for online sales, forfeiting any chance of cost savings. As competition pressure continues to mount in E-commerce, B2B or B2C, E-commerce corporations have begun to explore the possibility of managing product returns in a more cost-efficient manner by rescheduling the locations of recycling centers. However, few studies have addressed the problem of optimization of the numbers and location of collecting points, recycling centers and remanufacturing centers for E-commerce based on genetic algorithm. To fill the void in such a line of research, this paper proposes a genetic algorithm-based model that can solve the location-allocation optimization of reverse logistics for E-commerce. The usefulness of the proposed model and algorithm was validated by its application to an illustrative example dealing with logistics sites allocation from online sales. © 2013 Springer-Verlag London.","E-commerce; Genetic algorithm; Network site; Reverse logistics","Algorithms; Genetic algorithms; Logistics; Recycling; Cost saving; Cost-efficient; ITS applications; Location-allocation; Model and algorithms; Online sales; Product returns; Reverse logistics; Electronic commerce",{"$nulls":4},"Hangzhou Social Science Fund, (2011JD23); Natural Science Foundation of Zhejiang Province, ZJNSF, (Y6110648)","The research on which this paper reports has been financially supported by Natural Science Foundation of Zhejiang Province with Project Y6110648 and Hangzhou Social Science Fund by Project 2011JD23.","Shi H., Et al., Association between PPAR-γ and RXR-α gene polymorphism and metabolic syndrome risk: a case-control study of a Chinese han population, Arch Med Res, 43, 3, pp. 233-242, (2012); Lee C.K.M., Lam J.S.L., Managing reverse logistics to enhance sustainability of industrial marketing, Ind Mark Manag, 41, 4, pp. 589-598, (2012); Ilgin M.A., Gupta S.M., Environmentally conscious manufacturing and product recovery (ECMPRO): a review of the state of the art, J Environ Manag, 91, 3, pp. 563-591, (2010); Aras N., Aksen D., Gonul T.A., Locating collection centers for incentive-dependent returns under a pick-up policy with capacitated vehicles, Eur J Oper Res, 191, 3, pp. 1223-1240, (2008); Alagador D., Cerdeira J.O., Designing spatially-explicit reserve networks in the presence of mandatory sites, Biol Conserv, 137, 2, pp. 254-262, (2007); Brandao S.N., Sauer J., Schon I., Circumantarctic distribution in Southern Ocean benthos? A genetic test using the genus Macroscapha (Crustacea, Ostracoda) as a model, Mol Phylogenet Evol, 55, 3, pp. 1055-1069, (2010); Kerh T., Gunaratnam D., Chan Y.L., Neural computing with genetic algorithm in evaluating potentially hazardous metropolitan areas result from earthquake, Neural Comput Appl, 19, 4, pp. 521-529, (2010); Acampora G., Gaeta M., Loia V., Hierarchical optimization of personalized experiences for e-Learning systems through evolutionary models, Neural Comput Appl, 20, 5, pp. 641-657, (2011); Dash N.B., Et al., Hybrid neural modeling for groundwater level prediction, Neural Comput Appl, 19, 8, pp. 1251-1263, (2010); Dehuri S., Cho S.B., A hybrid genetic based functional link artificial neural network with a statistical comparison of classifiers over multiple datasets, Neural Comput Appl, 19, 2, pp. 317-328, (2010)","D. Liu; School of Management, Hangzhou Dianzi University, Hangzhou, 310018 Zhejiang, No. 1st, 2nd Ave. Xiasha Education Zone, China; email: hduldw@163.com",null,"Springer-Verlag London Ltd",{"$nulls":5},9410643.0,null,null,null,"English","Neural Comput. Appl.","Article","Final",null,"Scopus","2-s2.0-84902511236"]
["Trimble J.; Chilumani K.R.; Sibangiso N.","Trimble, John (57188640537); Chilumani, Khesani R. (57190340890); Sibangiso, Ngwenya (57192428968)","57188640537; 57190340890; 57192428968","Strategies for community focused postal service development",2015.0,"African Journal of Science, Technology, Innovation and Development",7.0,5.0,null,358.0,363.0,5.0,1.0,"10.1080/20421338.2015.1085175","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85006401133&doi=10.1080%2f20421338.2015.1085175&partnerID=40&md5=08abb80d985fefff08bda65f0088ce3c","Computer Science Department, National University of Science and Technology (NUST), Bulawayo, Zimbabwe","Trimble J., Computer Science Department, National University of Science and Technology (NUST), Bulawayo, Zimbabwe; Chilumani K.R., Computer Science Department, National University of Science and Technology (NUST), Bulawayo, Zimbabwe; Sibangiso N., Computer Science Department, National University of Science and Technology (NUST), Bulawayo, Zimbabwe","To maintain its relevance, the postal system must look at ways to innovate and optimize. It must optimize its use of resources and delivery of current services. It must employ innovation to develop new opportunities and services. The key will be to leverage its infrastructure and build on its strong community linkage, while taking advantages of emerging trends in information and communication technology. This study uses information gathered from the postal systems in Africa and other less developed settings. It also draws on postal expansion options identified by the Universal Postal Union (UPU) in the areas of e-post, e-commerce, e-government and e-finance, as a basis for a framework orientated to community service in southern Africa. This framework is designed to facilitate the development of a more effective postal research strategy that is well integrated into the overall business strategy of the post office, building on existing services and incorporating new e-postal services. This overall process should encourage regional and continental integration of postal services and foster citizen and community empowerment. © 2015 African Journal of Science. All rights reserved.","Innovation; Postal service; Service optimization; Simulation; Value chain",{"$nulls":7},"Abdallah F., Shakurova Y., Measuring postal e-service development: A global perspective, Universal Postal Union (UPU), (2012); Banda M., Postal News, (2014); Banks J., Carson J., Nelson B.L., Nicol D., Discrete- Event System Simulation, (2005); Bao F., Chen I., Dynamic Trust Management for Internet of Things Applications, Proceedings of the International Workshop on Self-Aware Ioft, (2012); Boulding K.E., General systems theory–the skeleton of science., MD. Management Science, 2, 3, pp. 197-208, (1956); Domingos P., A Few Useful Things to Know About Machine Learning Tapping into the ‘folk Knowledge needed to advance machine learning applications.”, Communications of the ACM, 55, 10, pp. 78-87, (2012); Ducasse J.P., Reinventing a Long-term and Sustainable Role for Posts in Least Developed Countries., Reinventing the Post, Emerging Opportunities for the Postal Industry, pp. 179-185, (2013); Evans S., How labour broking almost broke the post office, Mail & Guardian, (2015); Ford A., Modelling the Environment, An Introduction to System Dynamics Modelling of Environmental Systems, (1999); Forrester J.W., Principles of Systems, System Dynamics Series, (1968); Gershenfeld N., Krikorian R., Cohen D., The Internet of Things., Scientific American, 291, 4, pp. 76-81, (2004); Giarratano J., Riley G., Expert Systems Principles and Programming, (2005); Hachem S., Teixeira T., Issarny V., Ontology for the Internet of Things, MDS '11. Proceedings of the 8Th Middleware Doctoral Symposium Lisbon, (2011); Hand D., Mannila H., Smyth P., Principles of Data Mining, (2001); Morrison J., Rudolph J., Carroll J., Dynamic modelling as a multidiscipline collaborative journey., System Dynamics Review, 29, 1, pp. 24-25, (2013); Integrated Annual Report 2012, (2012); Media Release SA Post Office/Trust Centre, (2013); Integrated Annual Report 2014, (2014); Sterman J., Business Dynamics: Systems Thinking and Modelling for a Complex World, (2000); Sterman J., C-ROADS, Climate Interactive and Ventana Systems, (2014); Taha T., Operations Research: An Introduction, (2010); Trimble J., Keeling H., Computational Intelligence and Computational Science used toward a Postal Information Systems Strategy, Proceedings of the Joint International Conference on Engineering Education and Research and International Conference on Information Technology (ICEE ICIT), pp. 674-684, (2013); Trimble J., University and Postal Services Research: An ICT grounded Pan-African Approach, Southern African Postal Operators’ Association (SAPOA) Meeting, (2014); A Framework for Delivery Network Optimization, (2012); Ward J., Peppard J., Strategic Planning for Information Systems, (2002)","J. Trimble; Computer Science Department, National University of Science and Technology (NUST), Bulawayo, Zimbabwe; email: jtrimblefamily@hotmail.com",null,"Taylor and Francis Ltd.",{"$nulls":5},2.0421338E7,null,null,null,"English","Afr. J.  Sci.  Technol. Innov. Dev.","Article","Final",null,"Scopus","2-s2.0-85006401133"]
["Park S.-B.; Chung K.","Park, Seung-Bo (37025061900); Chung, Kyungyong (25927027500)","37025061900; 25927027500","Annotation alignment method on P2P-TV system",2015.0,"Peer-to-Peer Networking and Applications",8.0,4.0,null,578.0,586.0,8.0,4.0,"10.1007/s12083-014-0264-4","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84931561086&doi=10.1007%2fs12083-014-0264-4&partnerID=40&md5=2a0a9fa2fcf6f9bb2a5815d633e50fc6","Institute of Media Content, Dankook University, 152, Jukjeon-ro, Suji-gu, Yongin-si, 448-701, Gyeonggi-do, South Korea; School of Computer Information Engineering, Sangji University, 83 Sangjidae-gil, Wonju-si, 220-702, Gangwon-do, South Korea","Park S.-B., Institute of Media Content, Dankook University, 152, Jukjeon-ro, Suji-gu, Yongin-si, 448-701, Gyeonggi-do, South Korea; Chung K., School of Computer Information Engineering, Sangji University, 83 Sangjidae-gil, Wonju-si, 220-702, Gangwon-do, South Korea","P2P-TV is a TV system that receives content through a peer-to-peer network. Content is stored in the distributed manner then to be serviced to users, and thus expenses incurred by the content delivery are regarded as a near zero cost. This is why various studies are being conducted on the P2P-TV of late. Furthermore, the spread of smart televisions with combined functions of the Internet and PC enhanced the feasibility of P2P-TV greatly. Current discussions surrounding the P2P-TV, however, are mostly focused on studies that aim to improve the quality of content delivery. On just rare occasions are there studies that investigate the possibility of a significant profit source, P2P-TV based T-Commerce. As for the T-commerce to work, product information shall be extracted from content to be delivered to online shopping mall websites as a basic service. In this respect, this paper suggests methods and system to align content with annotation data so as to be used for T-Commerce through the P2P-TV system while evaluating the system performance. The alignment is divided into total matching process and partial matching process. When content is sent through the P2P network and stored afterwards, there can be unintentional content corruption depending on the network quality. There are five types of such content variations suggested as follows: (1) frame loss; (2) key frame corruption; (3) shot loss; (4) changes in the number of frames; and (5) changes in the resolution. These variations cause mismatching between content and annotation data. Against this backdrop, the paper proposes reasons for such mismatching as well as methods for mismatching-related decisions while conducting an experimentation and performance evaluation. The experimentation on these five different types of content corruption has generated relatively strong annotation results of 82.63 %. This shows that the proposed methods for alignment between content and annotation data are effective. © 2014, Springer Science+Business Media New York.","Alignment; Annotation data; P2P-TV; Quality; T-Commerce","Alignment; Commerce; Crime; Distributed computer systems; Image quality; Alignment methods; Annotation data; Combined functions; Content variation; Network qualities; Product information; Quality of contents; T-commerce; Peer to peer networks",{"$nulls":4},"National Research Foundation of Korea, (R1A1A2061737); National Research Foundation of Korea, NRF; Kementerian Pendidikan Malaysia, KPM, (NRF-2013R1A1A2061737)","This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2013R1A1A2061737)","Jan M., Dick E., Henk S., The orchard algorithm: building multicast trees for P2P video multicasting without free-riding, IEEE Trans Multimed, 9, 8, pp. 1593-1604, (2007); Jin L., On peer-to-peer (P2P) content delivery, Peer-to-Peer Netw Appl, 1, pp. 45-63, (2008); Yong L., Yang G., Chao L., A survey on peer-to-peer video streaming systems, Peer-to-Peer Netw Appl, 1, pp. 18-28, (2008); Raimund S., Siegfried W., Norbert J., Mobile social TV: extending DVB-H services with P2P-Interaction, In: Proceedings 2nd International Conference on Digital Telecommunications (ICDT’07):1–14, (2007); Alexandro S., Gustavo M., Mario G., Leonard K., Will IPTV ride the peer-to-peer stream? [Peer-to-peer multimedia streaming], IEEE Commun Mag, 45, 6, pp. 86-92, (2007); Ha O.K., Song Y.S., Chung K.Y., Lee K.D., Park D., Relation model describing the effects of introducing RFID in the supply chain: evidence from the food and beverage industry in South Korea, Pers Ubiquit Comput, 18, 3, pp. 553-561, (2014); Kim J.Y., Chung K.Y., Jung J.J., Single tag sharing scheme for multiple-object RFID applications, Multimed Tools Appl, 68, 2, pp. 465-477, (2014); Boutaba R., Chung K., Gen M., Recent trends in interactive multimedia computing for industry. Clust Comput, doi:10.1007/s10586-014-0349-0, (2014); Kim J.H., Ryu J.K., Recent trends on high-performance computing and security, Clust Comput, 16, 2, pp. 207-208, (2013); Martin L., Marta R., Jose P., Jorge G., Yolanda B., Alberto G., Rebeca D., Ana F., Manuel R., Spontaneous interaction with audiovisual contents for personalized ecommerce over digital TV, Expert Syst Appl, 36, pp. 4192-4197, (2009); Yoowon K., Seung-Bo P., Kee-Sung L., Jahyun C., Geun-Sik J., Semantic interaction TV based on spatial relations and ontology, Proceeding of the International Conference on Information Science and Application (ICISA, 2011, (2011); John L., Tamer O., Duane S., Modeling of moving objects in a video database, In: Proceedings of IEEE International Conference on Multimedia Computing and Systems’97:336–343, (1997); Cozar J.R., Guil N., Gonzalez-Linares J.M., Zapata E.L., Izquierdo E., Logotype detection to support semantic-based video annotation, Signal Process Image Commun, 22, pp. 669-679, (2007); Jun Y., Rong Y., Alexander H., Multiple instance learning for labeling faces in broadcasting news video, In: Proceedings of the ACM International Conference on Multimedia:31–40, (2005); Chung K.Y., Recent trends on convergence and ubiquitous computing, Pers Ubiquit Comput, (2013); Kim S.H., Chung K.Y., Medical information service system based on human 3D anatomical model, Multimed Tools Appl, (2013); Chung K.Y., Na Y.J., Lee J.H., Interactive design recommendation using sensor based smart wear and weather WebBot, Wirel Pers Commun, 73, 2, pp. 243-256, (2013); Jung H., Chung K.Y., Mining based associative image filtering using harmonic mean, Clust Comput, (2013); Eduard T., Lena S., John M., Share it! by bringing P2P into the TV-domain, In: Proceedings of the Third International Conference on Peer-to-Peer Computing (P2P’03):206–207, (2003); Peter H., Eric V., Keith B., Peer-to-peer Internet Television, In: Proceedings of the First International Conference on Automated Production of Cross Media Content for Multi-Channel Distribution (AXMEDIS’05):267–268, (2005); Xiaojun H., Chao L., Jian L., Yong L., Keith R., A measurement study of a large-scale P2P IPTV system, IEEE Trans Multimed, 9, 8, pp. 1672-1687, (2007); Chenjie Z., Dejian Y., Clear P2P IPTV Live Streaming System for Set-Top Box Clients, 7th IEEE International Conference on Computer and Information Technology (CIT, 2007, pp. 539-544, (2007); Majed A., Antonio L., Characterization of signaling and traffic in Joost, Peer-to-Peer Netw Appl, 2, 1, pp. 75-83, (2009); Su H., Xin Z., Zhihong J., Hao K., TVMonitor: A P2P-TV content monitoring platform, In: 2011 Third International Conference on Multimedia Information Networking and Security:371–375, (2011); Jun L., Lei S., Xiaoming F., An experimental analysis of Joost peer-to-peer VoD service, Peer-to-Peer Netw Appl, 3, 4, pp. 351-362, (2010); Dario R., Elisa S., Paolo V., Black-box analysis of Internet P2P applications, Peer-to-Peer Netw Appl, 4, 2, pp. 146-164, (2011); Paolo V., Dario R., Performance evaluation of P2P-TV diffusion algorithms under realistic settings, Peer-to-Peer Netw Appl, 6, 1, pp. 26-45, (2013); Pouwelse J.A., Garbacki P., Epema D.H.J., Sips H.J., A Measurement Study of the BitTorrent Peer-to-Peer File-Sharing System, Technical Report PDS-2004-003, (2004); Cheng H., Angela W., Jin L., Keith R., Understanding Hybrid CDN-P2P: Why Limelight Needs its Own Red Swoosh, In: Proceedings of the 18th International Workshop on Network and Operating Systems Support for Digital Audio and Video(NOSSDAV’08):75–80, (2008); Zong N., Chunk Discovery for P2P Streaming, Draft-zong-ppsp-chunk-discovery-00, (2009); Jin-Hwal L., Kee-Sung L., Geun-Sik J., Representation method of the moving object trajectories by interplation with dynamic sampling, 2013 International Conference on Information Science and Applications (ICISA, 2013, pp. 189-192, (2013)",null,null,"Springer New York LLC",{"$nulls":5},1.9366442E7,null,null,null,"English","Peer-to-Peer Netw. Appl.","Article","Final",null,"Scopus","2-s2.0-84931561086"]
["Yao J.; Gu M.","Yao, Jianming (55478489100); Gu, Mengjie (56658231600)","55478489100; 56658231600","Optimization analysis of supply chain resource allocation in customized online shopping service mode",2015.0,"Mathematical Problems in Engineering",2015.0,null,519125.0,null,null,null,9.0,"10.1155/2015/519125","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84930001091&doi=10.1155%2f2015%2f519125&partnerID=40&md5=a996003569121872c462b3524c116421","School of Business, Renmin University of China, Beijing, 100872, China","Yao J., School of Business, Renmin University of China, Beijing, 100872, China; Gu M., School of Business, Renmin University of China, Beijing, 100872, China","For an online-shopping company, whether it can provide its customers with customized service is the key to enhance its customers' experience value and its own competence. A good customized service requires effective integration and reasonable allocation of the company's supply chain resources running in the background. Based on the analysis of the allocation of supply chain resources in the customized online shopping service mode and its operational characteristics, this paper puts forward an optimization model for the resource allocation and builds an improved ant algorithm to solve it. Finally, the effectiveness and feasibility of the optimization method and algorithm are demonstrated by a numerical simulation. This paper finds that the special online shopping environments lead to many dynamic and uncertain characters of the service demands. Different customized service patterns and their combination patterns should match with different supply chain resource allocations. The optimization model not only reflects the required service cost and delivery time in the objective function, but also considers the service scale effect optimization and the relations of integration benefits and risks. The improved ant algorithm has obvious advantages in flexibly balancing the multiobjective optimizations, adjusting the convergence speed, and adjusting the operation parameters. © 2015 Jianming Yao and Mengjie Gu.",null,"Algorithms; Chains; Electronic commerce; Multiobjective optimization; Numerical methods; Optimization; Resource allocation; Supply chains; Convergence speed; Customized services; Objective functions; Operation parameters; Operational characteristics; Optimization analysis; Optimization method; Optimization modeling; Social networking (online)",{"$nulls":4},"National Natural Science Foundation of China, (41271440)",null,"Boyer K.K., Hult G.T.M., Extending the supply chain: Integrating operations and marketing in the online grocery industry, Journal of Operations Management, 23, 6, pp. 642-661, (2005); Zhu D.L., Hu Y.H., Xu Z., Research on the competition and coordination in online shopping supply chain management, Journal of University of Shanghai for Science and Technology, 33, 3, pp. 248-252, (2011); Hu Y.H., Li X.Q., Zhang J.H., Zhang J.T., Research on the equilibrium model in the online shopping supply chain management, Operations Research and Management Science, 21, 4, pp. 34-40, (2012); Hu Y.H., Qiang Q., An equilibrium model of online shopping supply chain networks with service capacity investment, Service Science, 5, 3, pp. 238-248, (2013); Elik H.C., Influence of social norms, perceived playfulness and online shopping anxiety on customers' adoption of online retail shopping: An empirical study in the Turkish context, International Journal of Retail and DistributionManagement, 39, 6, pp. 390-413, (2011); Mu Y.P., Research on \" warehouse explosion\" in the era of online shopping, Corporation Research, 9, pp. 49-51, (2011); Kros J.F., Nadler S.S., Chen H., The adoption and utilization of online auctions by supply chainmanagers, Transportation Research Part E: Logistics and Transportation Review, 47, 2, pp. 105-114, (2011); Banker R.D., Mitra S., Procurement models in the agricultural supply chain: A case study of online coffee auctions in India, Electronic Commerce Research and Applications, 6, 3, pp. 309-321, (2007); Chen Y.C., Fang S.-C., Wen U.-P., Pricing policies for substitutable products in a supply chain with Internet and traditional channels, European Journal of Operational Research, 224, 3, pp. 542-551, (2013); Selvarajah E., Steiner G., Approximation algorithms for the supplier's supply chain scheduling problem to minimize delivery and inventory holding costs, Operations Research, 57, 2, pp. 426-438, (2009); Yao J.M., Decision optimization analysis on supply chain resource integration in fourth party logistics, Journal of Manufacturing Systems, 29, 4, pp. 121-129, (2010); Hall N.G., Potts C.N., Supply chain scheduling: Batching and delivery, Operations Research, 51, 4, pp. 566-584, (2003); Wang F., Choi I.-C., Optimal decisions in a single-period supply chain with price-sensitive randomdemand under a buyback contract, Mathematical Problems in Engineering, 2014, (2014); Yao J.M., Scheduling optimisation of co-operator selection and task allocation in mass customisation supply chain based on collaborative benefits and risks, International Journal of Production Research, 51, 8, pp. 2219-2239, (2013); Yao J., Supply chain scheduling optimisation in mass customisation based on dynamic profit preference and application case study, Production Planning and Control, 22, 7, pp. 690-707, (2011); Yao J., Liu L., Optimization analysis of supply chain scheduling in mass customization, International Journal of Production Economics, 117, 1, pp. 197-211, (2009); Dadzie K.Q., Winston E., Consumer response to stockout in the online supply chain, International Journal of Physical Distribution and Logistics Management, 37, 1, pp. 19-42, (2007); Zhou R., Nee A.Y.C., Lee H.P., Performance of an ant colony optimisation algorithm in dynamic job shop scheduling problems, International Journal of Production Research, 47, 11, pp. 2903-2920, (2009); Gravel M., Price W.L., Gagne C., Scheduling continuous casting of aluminum using a multiple objective ant colony optimization metaheuristic, European Journal of Operational Research, 143, 1, pp. 218-229, (2002)",null,null,"Hindawi Publishing Corporation",{"$nulls":5},"1024123X",null,null,null,"English","Math. Probl. Eng.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-84930001091"]
["Wang J.J.; Xiao Z.","Wang, James J. (7701342886); Xiao, Zuopeng (56643687900)","7701342886; 56643687900","Co-evolution between etailing and parcel express industry and its geographical imprints: The case of China",2015.0,"Journal of Transport Geography",46.0,null,null,20.0,34.0,14.0,29.0,"10.1016/j.jtrangeo.2015.05.005","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84929301950&doi=10.1016%2fj.jtrangeo.2015.05.005&partnerID=40&md5=7cae15328cf9d1d2fe464e0b9b0c552a","Department of Geography, University of Hong Kong, Hong Kong Special Administrative Region, Hong Kong","Wang J.J., Department of Geography, University of Hong Kong, Hong Kong Special Administrative Region, Hong Kong; Xiao Z., Department of Geography, University of Hong Kong, Hong Kong Special Administrative Region, Hong Kong","This study conceptualizes the relationship between etailing (e-retailing) and the parcel express industry (PEI) and analyzes their co-evolution in China. Four operational models of etailing are discussed in the context of their intertwining relations with different forms of parcel express services. This co-evolution generated compound outcomes because of the late start of PEI and the fast growth of online shopping in China. These four models coexist, with two standing out as major types that suggest future directions. Two major geographical imprints of this process are explained and conceptualized: (1) the zonal delivery strategy by supply-chain-based e-merchants, which is conceptualized into a choice model of order-fulfilling locations to strengthen timely delivery; and (2) the Baoyou strategy advocated by e-market-based retailers and their logistic support for a slower, low-cost market of larger geographical coverage compared to the first strategy. Both strategies demonstrate that co-evolution is not only a path-dependent process but is also associated with place-dependent institutions. © 2015 Elsevier Ltd.","China; Co-evolution; Etailing; Logistics geography; Parcel express industry","China; conceptual framework; economic growth; electronic commerce; institutional framework; logistics; retailing; service sector",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (71390335)","This research is partly supported by the National Science Foundation Committee (NSFC) (Project Number: 71390335). Our appreciation also goes to Ms. Jing Li and Ms. Tina Tsang for their research assistance and technical support.","JD: The Rise of Fourth Pillar on The Internet in China, (2015); Anderson W.P., Chatterjee L., Lakshmanan T.R., E-commerce, transportation, and economic geography, Growth Change, 34, pp. 415-432, (2003); Ballou R.H., The evolution and future of logistics and supply chain management, Eur. Bus. Rev., 19, 4, pp. 332-348, (2007); Boschma R., Frenken K., Why is economic geography not an evolutionary science? Towards an evolutionary economic geography, J. Econ. Geogr., 6, 3, pp. 273-302, (2006); The Handbook of Evolutionary Economic Geography, (2010); Boyer K.K., Prud'homme A.M., Chung W., The last mile challenge: evaluating the effects of customer density and delivery window patterns, J. Bus. Logist., 30, 1, pp. 185-201, (2009); 2013 niandu zhongguo wangluo lingshou shichang shuju jiance baogao, (2014); 2013 nian Taobao he Tianmao gong shengchan 50 yige baoguo, (2014); Christopher M., Towill D., An integrated model for the design of agile supply chains, Int. J. Phys. Distrib. Logist. Manage., 31, 4, pp. 235-246, (2001); Ehmke J., Chapter 2 City Logistics, Integration of Information and Optimization Models for Routing in City Logistics, 177, (2012); Ehrlich P.R., Raven P.H., Butterflies and plants: a study in coevolution, Evolution, 18, 4, pp. 586-608, (1964); E-commerce and Delivery: A Study of the State of Play of EU Parcel Markets with Particular Emphasis on e-commerce, (2013); Gevaers R., Van de Voorde E., Vanelslander T., Characteristics and typology of last-mile logistics from an innovation perspective in an urban context, City Distribution and Urban Freight Transport: Multiple Perspectives, pp. 56-71, (2011); Hall P.V., Hesse M., Reconciling cities and flows in geography and regional studies, Cities, Regions and Flows, pp. 3-20, (2012); Hesse M., The City as a Terminal: The Urban Context of Logistics and Freight Transport, (2008); Hesse M., Cities and flows: re-asserting a relationship as fundamental as it is delicate, J. Transp. Geogr., 29, 2013, pp. 33-42, (2013); Hesse M., Rodrigue J.-P., The transport geography of logistics and freight distribution, J. Transp. Geogr., 12, 3, pp. 171-184, (2004); Jiang B., Prater E., Distribution and logistics development in China: the revolution has begun, Int. J. Phys. Distrib. Logist. Manage., 32, 9, pp. 783-798, (2002); Kearney A.T., China's E-Commerce Market: The Logistics Challenges, (2011); Lee H.L., Whang S., Winning the last mile of e-commerce, MIT Sloan Manage. Rev., 42, 4, pp. 54-62, (2001); Madlberger M., Sester A., The last mile in an electronic commerce business model - service expectations of Austrian online shoppers, ECIS 2005 Proceedings, (2005); McKinnon A.C., Tallam D., Unattended delivery to the home: assessment of the security implications, Int. J. Retail Distrib. 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["Romano P.; Quaglia F.","Romano, Paolo (7201601248); Quaglia, Francesco (55551213300)","7201601248; 55551213300","Design and evaluation of a parallel invocation protocol for transactional applications over the web",2014.0,"IEEE Transactions on Computers",63.0,2.0,6655873.0,317.0,334.0,17.0,9.0,"10.1109/TC.2013.214","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84892396567&doi=10.1109%2fTC.2013.214&partnerID=40&md5=c17994224953c7a59d6c235986793bbb","INESC-ID, University of Lisboa, Portugal; DIS, Sapienza Università di Roma, Italy","Romano P., INESC-ID, University of Lisboa, Portugal; Quaglia F., DIS, Sapienza Università di Roma, Italy","Edge computing is a powerful tool to face the challenging performance requirements of modern Internet applications. By replicating applications' data and logic across a large number of geographically distributed servers, edge computing platforms allow to achieve significant enhancements of the proximity between clients and contents, and of the system scalability. These platforms reveal highly effective when handling requests entailing read-only access to the application data, as these requests can be autonomously served by some edge server typically located closer to the client than the origin site. However, in contexts where end users can trigger transactional manipulations of the application state (e.g., e-Commerce, auctions or financial applications), the corresponding update requests typically need to be redirected to the origin transactional data sources, thus, nullifying any performance benefit arising from data replication and client proximity. To cope with this issue, in this paper, we present a parallel invocation protocol, which exploits the path-diversity along the end-to-end interaction toward the origin sites by concurrently routing transactional requests toward multiple-edge servers. Request processing is finally carried out by a single-edge server, adaptively selected as the most responsive one depending on current system conditions. The proposed edge server selection scheme does not require coordination among (geographically distributed) edge server instances, thus, being very light and scalable. The benefits from our protocol in terms of both reduced and more predictable end-to-end latency are quantified via an extended simulation study. © 1968-2012 IEEE.","application delivery networks; application level protocols; asp infrastructures; Path-diversity; transactional applications; web applications","Distributed computer systems; Application delivery; Application-level protocol; asp infrastructures; Path-diversity; WEB application; Internet protocols",{"$nulls":6},"Aguilera M., Gallet C., Fauconnier H., Toueg S., Stable leader election, Proc. 15th Conf. Distributed Computing (DISC '01), pp. 108-122, (2001); Allman M., A web server's view of the transport layer, ACM Computer Comm. Rev., 30, 5, pp. 10-20, (2000); Amza C., Cox A.L., Zwaenepoel W., Data replication strategies for fault tolerance and availability on commodity clusters, Proc. Conf. 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Dependable and Secure Computing, 2, 1, pp. 20-33, (2005); The Need for Speed, (1999)",null,null,"IEEE Computer Society",{"$nulls":5},189340.0,null,"ITCOB",null,"English","IEEE Trans Comput","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-84892396567"]
["Bai S.; Xu N.","Bai, Shizhen (18933408300); Xu, Na (57189359200)","18933408300; 57189359200","The online seller's optimal price and inventory policies under different payment schemes",2016.0,"European Journal of Industrial Engineering",10.0,3.0,null,285.0,300.0,15.0,6.0,"10.1504/EJIE.2016.076380","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84969766914&doi=10.1504%2fEJIE.2016.076380&partnerID=40&md5=818290db472dfa19cb98d8484bdf750e","School of Management, Harbin University of Science and Technology, Harbin, 150080, China; School of Management, Harbin University of Commerce, Harbin, 150028, China","Bai S., School of Management, Harbin University of Science and Technology, Harbin, 150080, China, School of Management, Harbin University of Commerce, Harbin, 150028, China; Xu N., School of Management, Harbin University of Science and Technology, Harbin, 150080, China","We develop an analytical model to determine the seller's optimal price and inventory decisions under different e-commerce payment schemes. There are two types of payment schemes for consumers to choose from: pay-to-order, with payment occurring when an order is taken online; and pay-on-delivery, in which payment occurs after delivery of the product. Considering different consumer behaviours after consumers evaluate the products, we characterize the rational expectations equilibrium for the online seller. We obtain the optimal price and order quantity to maximise the online seller's profit under different payment schemes. We provide the conditions when it is feasible for online sellers to offer every payment scheme. Numerical examples are provided to illustrate the comparison of online seller's performance between the two payment schemes. © Copyright 2016 Inderscience Enterprises Ltd.","e-commerce; order quantity; pay-on-delivery; pay-to-order; payment scheme; price","Industrial engineering; Order quantity; pay-on-delivery; pay-to-order; Payment schemes; price; Electronic commerce",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (71371061)","The authors are very grateful to the careful and constructive reviews from the editor Professor Ilkyeong Moon and two anonymous referees. This work was supported by the National Natural Science Foundation of China (with Grant number 71371061).","Balakrishnan A., Sundaresan S., Zhang B., Browse-and-switch: Retail online competition under value uncertainty, Production and Operations Management, 23, 7, pp. 1129-1145, (2014); Survey Report of the Data of Online Retail in China, (2013); Chandra S., Srivastava S.C., Theng Y.L., Evaluating the role of trust in consumer adoption of mobile payment systems: An empirical analysis, Communications of the Association for Information Systems, 27, pp. 561-588, (2010); Chen L., Kok A., Tong J., The effect of payment options on inventory decisions: The role of mental accounting, Management Science, 59, 2, pp. 436-451, (2013); Chern S., Pan Q., Teng J.T., Chan Y.L., Chen S.C., Stackelberg solution in a vendor-buyer supply chain model with permissible delay in payments, International Journal of Production Economics, 144, 1, pp. 397-404, (2013); Chiejina C., Soremekun E., Investigating the significance of the 'pay on delivery' option in the emerging prosperity of the Nigerian ecommerce sector, Journal of Marketing and Management, 5, 1, pp. 120-135, (2014); Chong S., Bagnall J., Smith K.E., Australian consumer payment behavior and preferences, JASSA, 2, 4, pp. 20-29, (2011); (2014); Statistical Report on Internet Development in China, (2014); Crocker K.J., Letizia P., Optimal policies for recovering the value of consumer returns, Production and Operations Management, 23, 10, pp. 1667-1680, (2014); Dan L., Jing Z., TAM-based study on factors influencing the adoption of mobile payment, China Communications, 5, 3, pp. 198-204, (2011); Giannetti M., Burkart M., Ellingsen T., What you sell is what you lend? Explaining trade credit contracts, Review of Financial Studies, 24, 4, pp. 1261-1298, (2011); Griffisa S.E., Rao S., Goldsby T.J., Niranjan T.T., The customer consequences of returns in online retailing: An empirical analysis, Journal of Operations Management, 30, 4, pp. 282-294, (2012); Hsiao L., Chen Y.J., Returns policy and quality risk in e-business, Production and Operations Management, 21, 3, pp. 489-503, (2012); Huang S., Yang J., Contracting under asymmetric customer returns information and market valuation with advertising-dependent demand, European Journal of Industrial Engineering, 9, 4, pp. 538-560, (2015); Kahneman D., Tversky A., Prospect theory: An analysis of decision under risk, Econometrica, 47, 2, pp. 263-291, (1979); Koyuncu C., Gautam B., The impacts of quickness, price, payment risk, and delivery issues on on-line shopping, Journal of Socio-Economics, 33, 2, pp. 241-251, (2004); Lee L., Tsai C., How price promotions influence post purchase consumption experience over time, Journal of Consumer Research, 40, 5, pp. 943-959, (2014); Liu X., He M., Gao F., Xie P., An empirical study of online shopping customer satisfaction in China: A holistic perspective, International Journal of Retail & Distribution Management, 36, 11, pp. 919-940, (2008); Luo J., Sulin B., Han Z., The effectiveness of online shopping characteristics and well-designed websites on satisfaction, MIS Quarterly, 36, 4, pp. 1131-1144, (2012); Mangiaracina R., Perego A., Payment systems in the B2c eCommerce: Are they a barrier for the online customer, Journal of Internet Banking and Commerce, 14, 3, pp. 1-16, (2009); Michael D., Clemes C.G., Zhang J., An empirical analysis of online shopping adoption in Beijing, China, Journal of Retailing and Consumer Services, 21, 3, pp. 364-375, (2014); Mohan S., Mohan G., Chandrasekhar A., Multi-item, economic order quantity model with permissible delay in payments and a budget constraint, European Journal of Industrial Engineering, 2, 4, pp. 446-460, (2008); Moon Y., Yao T., Investment timing for a dual channel supply chain, European Journal of Industrial Engineering, 7, 2, pp. 148-174, (2013); Muth J.F., Rational expectations and the theory of price movements, Econometrica, 29, pp. 315-335, (1961); Patrick V.M., Park C.W., Paying before consuming: Examining the robustness of consumers' preference for prepayment, Journal of Retailing, 82, 3, pp. 165-175, (2006); Prelec D., Loewenstein G., The red and the black: Mental accounting of savings and debt, Marketing Science, 17, 1, pp. 4-28, (1998); Shafir E., Thaler R.H., Invest now, drink later, spend never: On the mental accounting of delayed consumption, Journal of Economic Psychology, 27, 5, pp. 694-712, (2006); Song J.S., Tong J., Payment Options, (2011); Su X., Zhang F., Strategic customer behavior, commitment, and supply chain performance, Management Science, 54, 10, pp. 1759-1773, (2008); Yang C.T., Pan Q., Ouyang L.Y., Teng J.T., Retailer's optimal order and credit policies when a supplier offers either a cash discount or a delay payment linked to order quantity, European Journal of Industrial Engineering, 7, 3, pp. 370-392, (2013); Yang S., Lu Y., Gupta S., Caso Y., Zhang R., Mobile payment services adoption across time: An empirical study of the effects of behavioral beliefs, social influences, and personal traits, Computers in Human Behavior, 28, 1, pp. 129-142, (2012); Zhang J., Zhang R.Q., Optimal replenishment and pricing decisions under the collect-on-delivery payment option, OR Spectrum, 36, 2, pp. 503-524, (2014); Zhao M., Sooner rather than later? the implications of delay on enjoyment and consumption, Advances in Consumer Research, 40, pp. 168-172, (2012)","N. Xu; School of Management, Harbin University of Science and Technology, Harbin, 150080, China; email: xnlucky_2012@163.com",null,"Inderscience Publishers",{"$nulls":5},1.7515254E7,null,null,null,"English","Eur. J. Ind. Eng.","Article","Final",null,"Scopus","2-s2.0-84969766914"]
["Ahire S.L.; Malhotra M.K.; Jensen J.B.","Ahire, Sanjay L. (7004505172); Malhotra, Manoj K. (7103190754); Jensen, John B. (7404522262)","7004505172; 7103190754; 7404522262","Carton-mix optimization for Walmart.com distribution centers",2015.0,"Interfaces",45.0,4.0,null,341.0,357.0,16.0,3.0,"10.1287/inte.2015.0797","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84940389340&doi=10.1287%2finte.2015.0797&partnerID=40&md5=a6a591dc38c307b98886e341656f3829","Department of Management Science, Moore School of Business, University of South Carolina, Columbia, 29208, SC, United States","Ahire S.L., Department of Management Science, Moore School of Business, University of South Carolina, Columbia, 29208, SC, United States; Malhotra M.K., Department of Management Science, Moore School of Business, University of South Carolina, Columbia, 29208, SC, United States; Jensen J.B., Department of Management Science, Moore School of Business, University of South Carolina, Columbia, 29208, SC, United States","Walmart's Internet shopping business has grown considerably since 2006. To effectively and efficiently serve this business model, Walmart launched distribution centers (DCs) in the United States; these DCs focus on fulfilling orders placed online at the Walmart.com website. The Carrollton, Georgia distribution center (CDC) handles a significant portion of the volume of products shipped directly to customers and stores for customer pickup. In spring 2011, the CDC executed a focused cost-improvement project to optimize its carton mix, defined as the sizes of the shipping cartons that can be erected using automation or built manually. The goals of this project were to develop a process to create an optimal mix of carton sizes to reduce shipping, material, and labor costs of conveyable orders, and improve customer satisfaction. Working in close coordination with CDC managers and Walmart's corporate supply chain team, we developed an Excel-based solution algorithm to determine the optimal carton sizes for four automated and six manual carton sizes. Walmart has fully implemented this solution algorithm into a decision support system for reconfiguring the carton mix at the CDC. The company has certified order-fulfillment cost savings of $600,000 per year and has projected annual cost savings of $2 million across the entire Walmart.com network. © 2015 INFORMS.","Business-to-consumer orders; Distribution center logistics; Online shopping; Packaging",{"$nulls":7},"Bortfeldt A., Wascher G., Constraints in container loading: A state-of-the-art review, Eur. J. Oper. Res., 229, 1, pp. 1-20, (2013); Brunetta L., Gregoire P., A general purpose algorithm for three-dimensional packing, INFORMS J. Comput., 17, 3, pp. 328-338, (2005); Cachon G., Managing a retailer's shelf space, inventory, and transportation, Manufacturing Service Oper. Management, 3, 3, pp. 211-229, (2001); Ceschia S., Schaerf A., Local search for a multi-drop multicontainer loading problem, J. Heuristics, 19, 2, pp. 275-294, (2011); De Almeida A., Figueiredo M.B., A particular approach for the three-dimensional packing problem with additional constraints, Comput. Oper. Res., 37, 11, pp. 1968-1976, (2010); Fraser H.J., George J.A., Integrated container loading software for pulp and paper industry, Eur. J. Oper. Res., 77, 3, pp. 466-474, (1994); Jin Z., Ito T., Ohno K., A three-dimensional bin packing problem and its practical algorithm, JSME Internat. J. Ser. C, 46, 1, pp. 60-66, (2003); Johnson E.M., Meller R.D., Performance analysis of split-case sorting systems, Manufacturing Service Oper. Management, 4, 4, pp. 258-274, (2002); Lin J.L., Chang C.H., Yang J.Y., A study of optimal system for multiple-constraint multiple-container packing problems, Proc. Advances Appl. Artificial Intelligence, 19th Internat. Conf. Indust. Engrg. Other Appl. Appl. Intelligent Systems, IEA/AIE 2006, pp. 1200-1210, (2006); Techanitisawad A., Tangwiwatwong P., A GA-based heuristic for the interrelated container selection loading problems, Indust. Engrg. Management Systems, 3, 1, pp. 22-37, (2004)",null,null,"INFORMS Inst.for Operations Res.and the Management Sciences",{"$nulls":5},922102.0,null,null,null,"English","Interfaces","Article","Final",null,"Scopus","2-s2.0-84940389340"]
["Huang L.","Huang, Lijuan (55324150500)",5.53241505E10,"Optimizing site selection of rural distribution center under two-way forward e-logistics",2012.0,"International Review on Computers and Software",7.0,7.0,null,3729.0,3734.0,5.0,0.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-84875160375&partnerID=40&md5=a353aeefce3c467862569b356935b820","School of Business, Guangzhou University, Guangzhou 510006, Guangdong, China; Business Administration School, Jiangxi University of Finance and Economics, Nanchang 330013, China","Huang L., School of Business, Guangzhou University, Guangzhou 510006, Guangdong, China, Business Administration School, Jiangxi University of Finance and Economics, Nanchang 330013, China","With the rapid development of Chinese New Rural Construction and e-logistics technology, it is important to select rural logistics distribution center scientifically and reasonably to integrate two-way forward e-logistics and reduce the logistics costs. In this paper, a new optimized model with minimum cost is established based on the characteristics of two-way forward e-logistics and traditional mixed integer programming model. Through setting an example of site selection with enough data tables, and considering economic losses of agricultural products mainly due to decay during transportation, the best location is ultimately determined with the help of Lingo software. More optimizations are mainly focused on selecting industrial distribution center than selecting rural one, and traditional optimizations are usually based on one-way logistics other than two-way one in the E-commerce environment. So, the research fruits are innovation, and it is proved by this example that the new model can effectively overcome some deficiencies of the traditional site selection methods, and have an important reference value for decision-makers. © 2012 Praise Worthy Prize S.r.l.","e-Logistics; Lingo; Rural distribution center; Two-way","Agricultural products; Geographical distribution; Losses; Optimization; Site selection; e-Logistics; Industrial distribution; Lingo; Mixed integer programming model; New rural constructions; Optimized models; Rural distributions; Two-way; Warehouses",{"$nulls":6},"Berman O., Drezner Z., Wesolowsky G.O., Multiple location of transfer points, Journal of Operational Research Society, 59, 14, pp. 805-811, (2008); Rafay I., Charles R.S., Hub location-allocation in intermodal logistic networks, Journal of Operational Research, 21, 2, pp. 213-230, (2011); Siddhartha S., Model and methodologies for the location problem with logistical components, Computers & Operations Research, 29, 12, pp. 173-193, (2009); Salema M.I., Povoa A.P.B., Novais A.Q., A warehouse-based design model for reverse logistics, Journal of the Operational Research Society, 6, 57, pp. 615-629, (2006); O'Connor K., Global city regions and the location of logistics activity, Journal of Transport Geography, 8, 18, pp. 354-362, (2010); Jonathan P.D., Kraiwinee B., Eugene D.H., Separable but not equal: The location determinants of discrete services offshoring activities, Journal of International Business Studies, 6, 40, pp. 926-943, (2009); Yoshiaki S., Takeshi W., Logistic optimization for site location and route selection under capacity constraints using hybrid Tabu search, Computer Aided Chemical Engineering, 15, 20, pp. 612-617, (2007); Cidell J., Distribution centers among the rooftops:The global logistics network meets the suburban spatial imaginary, International Journal of Urban and Regional Research, 16, 8, pp. 32-96, (2010); O'Connor K., Global city regions and the location of logistics activity, Journal of Transport Geography, 3, 18, pp. 354-362, (2010); Cachon G.P., Swinney R., Purchasing, pricing, and quick response in the presence of strategic consumers, Management Science, 7, 19, pp. 497-511, (2009); Chen T.C., A fuzzy approach to select the location of the distribution center, Fuzzy Sets and Systems, 10, 118, pp. 65-73, (2007); Cheng C.S., Su L.L., DEA application in the logistics center location, The Journal of Changsha University of Technology, 125, 1, pp. 8-12, (2009); Huang L.J., Modeling and planning on urban logistics park location selection based on the artificial neural network, Journal of Computer, 36, 6, pp. 256-272, (2011); Hu J.Z., The shortest path algorithm of Floyd application in distribution center location, Journal of Hunan Agricultural University, 236, 30, pp. 382-384, (2009); Meng D.W., Multi-objective and multi-distribution center location problem, Journal of Logistics Technology, 124, 10, pp. 28-32, (2010); Tony Y.K., Distribution center location based on combining gravity method with fuzzy-AHP model, Logistics Technology, 129, 72, pp. 119-132, (2009); Dai Y.Z., Ma X.L., The comprehensive evaluation method of distribution center program, The Journal of Shijiazhuang College, 17, 6, pp. 93-96, (2008); Huang L.J., Construction of Chinese New Rural E-Commerce Platform and Its Key Technologies Research Based on Double E-markets, Mechatronic Sciences, Electric Engineering and Computer, 29, 12, pp. 28-37, (2010); Wang Y., Zhang W.K., Research on agricultural product logistical development under the New Rural Construction, China Storage, 72, 8, pp. 320-334, (2007)",{"$nulls":8},1.8286011E7,null,null,null,"English","Int. Rev. Comput. Softw.","Article","Final",null,"Scopus","2-s2.0-84875160375"]
["Du J.","Du, Jianbin (56816098300)",5.68160983E10,"A novel hybrid differential particle swarm optimization algorithm and its application in logistics distribution optimization",2015.0,"Journal of Computational Information Systems",11.0,13.0,null,4913.0,4922.0,9.0,2.0,"10.12733/jcis14702","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84940762810&doi=10.12733%2fjcis14702&partnerID=40&md5=be8a6f0b81789cb2a4aa6d24e19ae9f9","Academic Affairs Office, Qilu Normal University, Jinan, 250013, China","Du J., Academic Affairs Office, Qilu Normal University, Jinan, 250013, China","B2C e-commerce logistics distribution optimization is an important problem, yet the current algorithm accuracy is not satisfactory. In this paper, we propose an algorithm for B2C e-commerce logistics distribution optimization based on a new hybrid Differential particle swarm optimization. First, we take the particle swarm population as the mutation operator. Second, we use it to perform the crossover operation with Differential evolution algorithm. The produced new population has the advantage of the last generation. Third, we test the proposed algorithm on benchmark functions. Compared with existing algorithms, the proposed algorithm can effectively jump out of local minima. We may avoid the premature convergence and increase the convergence speed. Finally, We apply the proposed optimization algorithm to the B2C path optimization. Related experiments has been carried out and the results show that the designed distribution scheme has a faster computing speed and a better target convergence value. ©, 2015, Journal of Computational Information Systems. All right reserved.","Hybrid Differential Particle Swarm; Directional Variation; Logistics Path Optimization","Electronic commerce; Algorithm accuracies; Crossover operations; Differential evolution algorithms; Directional variation; Logistics distribution; Optimization algorithms; Particle swarm optimization algorithm; Pre-mature convergences; Particle swarm optimization (PSO)",{"$nulls":6},"Jin M., Lu H.X., A multi-subgroup hierarchical hybrid of genetic algorithm and particle swarm optimization, Control Theory & Applications, 30, 10, pp. 1231-1237, (2013); Storm R., On the usage of Differential evolution for function optimization, Proceedings of Biennial Conference of the North American Fuzzy Information Processing Society, pp. 519-526, (1996); Zhang J., Pei F., Multi-strategy cooperative evolutionary particle swarm optimization, Application Research of Computers, 30, 10, pp. 2965-2967, (2013); Kom F., Muth S., Inuence sets based on reverse nearest neighbor queries, Proc of ACM SIGMOD International Conference on Management of Date, pp. 201-212, (2000); Cheema M.A., Zhang W.J., Lin X.M., Continuous reverse K nearest neighbors queries in Euclidean space and in spatial networks, The VLDB Journal, 21, 1, pp. 69-95, (2012); Yao F., Yang W.D., Zhang M., Li Z.D., Improved space-adaptive-based Differential evolution algorithm, Control Theory & Applications, 27, 1, pp. 32-38, (2010); Kaelo P., Ali M.M., A numerical study of some Modified Differential evolution algorithms, European Journal of Operational Research, 169, pp. 1176-1184, (2006); Shi Y., Eberhart R.C., A Modified particle swarm optimizer, Proc of IEEE Congress on Evolutionary Computation. Piscataway, (1998); Lovbjerg M., Rasmussen T.K., Krink T., Hybrid particle swarm optimization with breeding and subpopulations, Proc of Genetic and Evolutionary Computation conference, (2001); Yang C.H., Qian X.S., Gui W.H., Hybrid algorithm of chaotic Differential evolution and particle swarm optimization, Application Research of Computers, 28, 2, pp. 32-35, (2011); Sayah S., Hamouda A., A hybrid Differential evolution algorithm based on particle swarm optimization for non-convex economic dispatch problems, Applied Soft Computing, pp. 1608-1619, (2013); Yang W.D., Yao F., Zhang M., Differential Evolution Algorithm Based on Adaptive Crossover Probability Factor and Its Application, Information and Control, 39, 2, pp. 187-193, (2010); Hu W., Li Z.S., A Simpler and More Effective Particle Swarm Optimization Algorithm, Journal of Software, 18, 4, pp. 861-868, (2007); Eberhart R.C., Shi Y., Comparing inertia weights and constriction factors in particle swarm optimization, Proc of the IEEE Conference on Evolutionary Computation, pp. 84-88, (2000); Wang L.F., Zeng J.C., A cooperative evolutionary algorithm based on particle swarm optimization and simulated annealing algorithm, Acta Automatic Sinica, 32, 4, pp. 630-635, (2006); Du H.F., Gong M.G., Liu R.C., Adaptive chaos clonal evolutionary programming, Science in China, Serials E: Information Sciences, 35, 8, pp. 817-829, (2005); Jiang Z.Z., Wang D.W., Model and Algorithm for Logistics Distribution Routing of B2C Ecommerce, Information and Control, 34, 1, pp. 481-485, (2005); Wang D.W., Wang J.W., Wang H.F., Intelligent Optimization Algorithm, (2007)","J. Du; Academic Affairs Office, Qilu Normal University, Jinan, 250013, China; email: dazhao06@sina.com",null,"Binary Information Press",{"$nulls":5},1.5539105E7,null,null,null,"English","J. Comput. Inf. Syst.","Article","Final",null,"Scopus","2-s2.0-84940762810"]
["Militino A.F.; Ugarte M.D.; Goicoa T.","Militino, A.F. (6603358936); Ugarte, M.D. (7005900325); Goicoa, T. (23566660700)","6603358936; 7005900325; 23566660700","Deriving small area estimates from information technology business surveys",2015.0,"Journal of the Royal Statistical Society. Series A: Statistics in Society",178.0,4.0,null,1051.0,1067.0,16.0,8.0,"10.1111/rssa.12105","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84942364042&doi=10.1111%2frssa.12105&partnerID=40&md5=9b4a1d23e755805cd7db5f8bf12df021","Universidad Pública de Navarra, Pamplona, Spain","Militino A.F., Universidad Pública de Navarra, Pamplona, Spain; Ugarte M.D., Universidad Pública de Navarra, Pamplona, Spain; Goicoa T., Universidad Pública de Navarra, Pamplona, Spain","Knowledge of the current state of the art in information and communication technology of businesses (ICTB) is an important issue for governments, markets and policy makers, because information technology improves access to information and plays an important role in firms' competitiveness. Statistical agencies use normalized surveys to provide harmonized statistics about the use of technology in enterprises. Classical design-based estimators are appropriate for large domains, because direct estimates are consistent and easy to obtain by using sampling weights. However, to supply estimates for unplanned domains, where the sample size is random, model-based estimators are usually required. In this paper, alternative logistic model-based estimators are suggested to derive small area estimates from ICTB surveys. Final estimates are benchmarked to achieve coherence with direct estimates in larger domains, and standard errors are given by using bootstrap techniques. A Monte Carlo simulation study is conducted to compare the performance of the small area estimators proposed and to evaluate the behaviour of the mean-squared error estimator. Results are illustrated with the 2010 ICTB survey of the Basque country (Spain). © 2015 The Royal Statistical Society and John Wiley & Sons Ltd.","E-commerce; Electronic data interchange; Finite population; Internet connection; Logistic models; Prediction theory",{"$nulls":7},"Chambers R., Tzavidis N., M-quantile models for small area estimation, Biometrika, 93, pp. 255-268, (2006); Datta G.S., Model-based approach to small area estimation, Handbook of Statistics, 29B, (2009); Communication from the Commission to the Council, the European Parliament, the European Economic and Social Committee and the Committee of the Regions: i2010-a European Information Society for growth and employment {SEC(2005) 717}, (2005); Farrell P.J., MacGibbon B., Tomberlin T.J., Empirical Bayes small-area estimation using logistic regression models and summary statistics, J. Bus. Econ. Statist., 15, pp. 101-108, (1997); Ghosh M., Kim D., Sinha K., Maiti T., Katzoff M., Parsons V.L., Hierarchical and empirical Bayes small domain estimation of the proportion of persons without health insurance for minority subpopulations, Surv. Methodol., 35, pp. 53-66, (2009); Ghosh M., Rao J.N.K., Small area estimation: an appraisal, Statist. Sci., 9, pp. 55-93, (1994); Gonzalez-Manteiga W., Lombardia M.J., Molina I., Morales D., Santamaria L., Estimation of the mean squared error of small area linear parameters under a logistic mixed model, Computnl Statist. Data Anal., 51, pp. 2720-2733, (2007); Jiang J., Lahiri P., Estimation of finite population domain means: a model-assisted empirical best prediction approach, J. Am. Statist. Ass., 101, pp. 301-311, (2006); Jiang J., Lahiri P., Mixed model prediction and small area estimation, Test, 15, pp. 1-96, (2006); Lehtonen R., Sarndal C.E., Veijanen A., The effect of model choice in estimation for domains including small domains, Surv. Methodol., 29, pp. 33-44, (2003); Lehtonen R., Veijanen A., Logistic generalized regression estimators, Surv. Methodol., 24, pp. 51-55, (1998); Lehtonen R., Veijanen A., Design-based methods of estimation for domains and small areas, Handbook of Statistics, 29B, (2009); MacNab Y.C., Dean C.B., Parametric bootstrap and penalized quasi-likelihood inference in conditional autoregressive models, Statist. Med., 19, pp. 2421-2435, (2000); Malec D., Small area estimation from the American Community Survey using a hierarchical logistic model of persons and housing units, J. Off. Statist., 21, pp. 411-432, (2005); Malec D., Sedransk J., Moriarity C.L., Leclere F.B., Small area inference for binary variables in the National Health Interview Survey, J. Am. Statist. Ass., 92, pp. 815-826, (1997); Manzi G., Spiegelhalter D.J., Turner R.M., Flowers J., Thompson S.G., Modelling bias in combining small area prevalence estimates from multiple surveys, J. R. Statist. Soc. A, 174, pp. 31-50, (2011); Militino A.F., Goicoa T., Ugarte M.D., Estimating the percentage of food expenditure in small areas using bias-corrected P-spline estimators, Computnl Statist. Data Anal., 56, pp. 2934-2948, (2012); Militino A.F., Ugarte M.D., Goicoa T., Combining sampling and model weights in agricultural small area estimation, Environmetrics, 18, pp. 87-99, (2007); Militino A.F., Ugarte M.D., Goicoa T., A BLUP synthetic versus an EBLUP estimator: an empirical study of a small area estimation problem, J. Appl. Statist., 34, pp. 153-165, (2007); Molina I., Saei A., Lombarda M.J., Small ares estimates of labour force participation under a multinomial logit mixed model, J. R. Statist. Soc. A, 170, pp. 975-1000, (2007); Noble A., Haslett S., Arnold G., Small area estimation via generalized linear models, J. Off. Statist., 18, pp. 45-60, (2002); Pfeffermann D., Small area estimation: new developments and directions, Int. Statist. Rev., 70, pp. 125-143, (2002); Pfeffermann D., New important developments in small area estimation, Statist. Sci., 28, pp. 40-68, (2013); Rao J.K.N., Small Area Estimation, (2003); Salvati N., Tzavidis N., Pratesi M., Chambers R., Small area estimation via M-quantile geographically weighted regression, Test, 21, pp. 1-28, (2012); Sarndal C.E., Design-consistent versus model-dependent estimators for small domains, J. Am. Statist. Ass., 79, pp. 624-631, (1984); Sarndal C.E., Swensson B., Wretman J., Model Assisted Survey Sampling, (1992); Tanton R., Vidyattama Y., Nepal B., McNamara J., Small area estimation using a reweighting algorithm, J. R. Statist. Soc. A, 174, pp. 931-951, (2011); Ugarte M.D., Goicoa T., Etxeberria J., Militino A.F., Testing for space-time interaction in conditional autoregressive models, Environmetrics, 23, pp. 3-11, (2012); Ugarte M.D., Goicoa T., Militino A.F., Durban M., Spline smoothing in small area trend estimation and forecasting, Computnl Statist. Data Anal., 53, pp. 3616-3629, (2009); Ugarte M.D., Militino A.F., Goicoa T., Adjusting economic estimates in business surveys, J. Appl. Statist., 35, pp. 1253-1265, (2008); Ugarte M.D., Militino A.F., Goicoa T., Benchmarked estimates in small areas using linear mixed models with restrictions, Test, 18, pp. 342-364, (2009); Ugarte M.D., Militino A.F., Goicoa T., Sagaseta-Lopez M., Estimating unemployment in very small areas, Sort, 33, pp. 49-70, (2009); Valliant R., Dorfman A.H., Royall R.M., Finite Population Sampling and Inference: a Prediction Approach, (2000); You Y., An integrated modeling approach to unemployment rate estimation for sub-provincial areas of Canada, Surv. Methodol., 34, pp. 19-27, (2008); You Y., Rao J.N.K., A pseudo-empirical best linear prediction approach to small-area estimation using survey weights, Can. J. Statist., 30, pp. 431-439, (2002); Zhang L.-C., Chambers R.L., Small area estimates for cross classifications, J. R. Statist. Soc. B, 66, pp. 479-496, (2004)","A.F. Militino; Departamento de Estadística e Investigación Operativa, Universidad Pública de Navarra, Pamplona, Campus Arrosadia, 31006, Spain; email: militino@unavarra.es",{"$nulls":7},9641998.0,null,null,null,"English","J. R. Stat. Soc. Ser. A Stat. Soc.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-84942364042"]
["Cobb N.K.; Brookover J.; Cobb C.O.","Cobb, Nathan K. (35106641700); Brookover, Jody (55857470900); Cobb, Caroline O. (35602833600)","35106641700; 55857470900; 35602833600","Forensic analysis of online marketing for electronic nicotine delivery systems",2015.0,"Tobacco Control",24.0,2.0,null,128.0,131.0,3.0,40.0,"10.1136/tobaccocontrol-2013-051185","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84923227388&doi=10.1136%2ftobaccocontrol-2013-051185&partnerID=40&md5=b8fe3446b278f5fee003af2354fe14df","Division of Pulmonary and Critical Care, Department of Medicine, Georgetown University Medical Center, Washington, DC, United States; Department of Health, Behavior and Society, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States; Schroeder Institute for Tobacco, Research and Policy Studies Legacy, Washington, DC, United States","Cobb N.K., Division of Pulmonary and Critical Care, Department of Medicine, Georgetown University Medical Center, Washington, DC, United States, Department of Health, Behavior and Society, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States, Schroeder Institute for Tobacco, Research and Policy Studies Legacy, Washington, DC, United States; Brookover J., Schroeder Institute for Tobacco, Research and Policy Studies Legacy, Washington, DC, United States; Cobb C.O., Schroeder Institute for Tobacco, Research and Policy Studies Legacy, Washington, DC, United States","Background Electronic nicotine delivery systems (ENDS) are growing in awareness and use in the USA. They are currently unregulated as the Food and Drug Administration has yet to assert jurisdiction under its tobacco authority over these products, and a US Court of Appeals held they cannot be regulated as drugs/ delivery devices if they are not marketed for a therapeutic purpose. Observation of the current online marketplace suggests ENDS, like some nutraceutical products, are being promoted using affiliate marketing techniques using claims concerning purported health benefits. Objective This study performed a forensic analysis to characterise the relationships between online ENDS affiliate advertisements and ENDS sellers, and evaluated descriptive content on advertisements and websites to inform future policy and regulatory efforts. Methods A purposive sampling strategy was used to identify three forms of ENDS advertising. Web proxy software recorded identifiable objects and their ties to each other. Network analysis of these ties followed, as well as analysis of descriptive content on advertisements and websites identified. Results The forensic analysis included four ENDS advertisements, two linked affiliate websites, and two linked seller websites, and demonstrated a multilevel relationship between advertisements and sellers with multiple layers of redirection. Descriptive analysis indicated that advertisements and affiliates, but not linked sellers, included smoking cessation claims. Results suggest that ENDS sellers may be trying to distance marketing efforts containing unsubstantiated claims from sales. A separate descriptive analysis of 20 ENDS seller web pages indicated that the use of affiliate marketing by sellers may be widespread. Conclusions These findings support increased monitoring and regulation of ENDS marketing to prevent deceptive marketing tactics and ensure consumer safety. © 2015, BMJ Publishing Group. All rights reserved.",null,"Commerce; Electronic Cigarettes; Electronics; Government Regulation; Humans; Internet; Marketing; Nicotine; Product Labeling; Smoking; Smoking Cessation; Tobacco Industry; Tobacco Products; nicotine; commercial phenomena; economics; electronic cigarette; electronics; government regulation; human; Internet; marketing; packaging; smoking; smoking cessation; tobacco; tobacco industry",null,"nicotine, 54-11-5; Nicotine, ",{"$nulls":4},"King B.A., Alam S., Promoff G., Et al., Awareness and ever use of electronic cigarettes among U.S. Adults, 2010–2011, Nicotine Tob Res, 15, pp. 1623-1627, (2013); (2011); Yamin C.K., Bitton A., Bates D.W., E-cigarettes: A rapidly growing Internet phenomenon, Ann Intern Med, 153, pp. 607-609, (2010); De Andrade M., Hastings G., The Marketing of E-Cigarettes; Ayers J.W., Ribisl K.M., Brownstein J.S., Tracking the rise in popularity of electronic nicotine delivery systems (Electronic cigarettes) using search query surveillance, Am J Prev Med, 40, pp. 448-453, (2011); Elliot S., Campaigns for E-Cigarettes Borrow from tobacco’s Heyday, (2012); Prussakov G., Size of Affiliate Marketing Industry Worldwide; Evans P.F., US Affiliate Marketing Forecast, (2009); (2012); (2013); (2012); (2013); Polosa R., Caponnetto P., Morjaria J.B., Et al., Effect of an electronic nicotine delivery device (E-Cigarette) on smoking reduction and cessation: A prospective 6-month pilot study, BMC Public Health, 11, (2011); Flouris A.D., Poulianiti K.P., Chorti M.S., Et al., Acute effects of electronic and tobacco cigarette smoking on complete blood count, Food Chem Toxicol, 50, pp. 3600-3603, (2012); Vardavas C.I., Anagnostopoulos N., Kougias M., Et al., Short-term pulmonary effects of using an electronic cigarette: Impact on respiratory flow resistance, impedance, and exhaled nitric oxide, Chest, 141, pp. 1400-1406, (2012); Bullen C., Williman J., Howe C., Et al., Study protocol for a randomised controlled trial of electronic cigarettes versus nicotine patch for smoking cessation, BMC Public Health, 13, (2013); (2013); Choi K., Forster J., Characteristics associated with awareness, perceptions, and use of electronic nicotine delivery systems among young US midwestern adults, Am J Public Health, 103, pp. 556-561, (2013); Pearson J.L., Richardson A., Niaura R.S., Et al., E-Cigarette awareness, use, and harm perceptions in US adults, Am J Public Health, 102, pp. 1758-1766, (2012); (2013); (2011); Burritt C., Altria to Sell E-Cigarette as Marlboro Demand Slides, (2013); Modi N., Schid B., Miller R., Clearing the smoke on e-cigarettes, UBS Investment Research, (2012)",null,null,"BMJ Publishing Group",{"$nulls":5},9644563.0,null,null,2.4038037E7,"English","Tob. Control","Article","Final",null,"Scopus","2-s2.0-84923227388"]
["Xiao X.; Liu Y.; Zhang Z.","Xiao, Xiao (55710739500); Liu, Yu (56592459600); Zhang, Zhenji (23391566600)","55710739500; 56592459600; 23391566600","The analysis of the logistics mode decision to E-commerce",2012.0,"Journal of Electronic Commerce in Organizations",10.0,4.0,null,57.0,70.0,13.0,18.0,"10.4018/jeco.2012100105","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84877893349&doi=10.4018%2fjeco.2012100105&partnerID=40&md5=017ec7cf96dfe2c50d9e8444f794b02f","School of Economics and Management, Beijing Jiaotong University, Beijing, China","Xiao X., School of Economics and Management, Beijing Jiaotong University, Beijing, China; Liu Y., School of Economics and Management, Beijing Jiaotong University, Beijing, China; Zhang Z., School of Economics and Management, Beijing Jiaotong University, Beijing, China","E-commerce is a complete process that consists of information flow, capital flow, business flow, and logistics. With the development of network and electronic technology, the information flow, capital flow, and business flow can be momentarily available through computer and network communication equipment. The logistics that must be achieved in reality become a key part in influencing the efficiency of E-commerce. Therefore, for portals, manufacturers, retailers, and logistics companies in E-commerce, the primary problem is the choice of a logistics mode. They must choose the most appropriate logistics mode according to practical situation in different environments. To B2C, this paper uses the logistics mode decision of Jingdong to find a solution for the choice of logistics mode in E-commerce and verifies the feasibility of AHP on such solution. To C2C, this paper introduces Taobao Logistics Po and other logistics modes. Copyright © 2012, IGI Global.","Analytic hierarchy process (AHP); Business to customer (B2C); Company to customer (C2C); E-commerce; Logistics modes","Hierarchical systems; Industry; Sales; Analytic hierarchy process (ahp); Business flow; Business to customers; Computer and networks; Electronic technologies; Information flows; Logistics company; Logistics modes; Electronic commerce",{"$nulls":6},"Chen Y., Wang J.X., B2B2C e-commerce environment supply chain income distribution mechanism research, Journal of Qingdao University (Natural Science Edition), 5, 1, pp. 77-78, (2011); Dada D., E-readiness for developing countries, moving the focus from the environment to the users, The Electronic Journal of Information Systems in Developing Countries, 27, 6, pp. 1-14, (2006); Gunasekaran A., Sarkis J., Research and applications in e-commerce and third-party logistics management, International Journal of Production Economics, 1, pp. 113-114, (2008); Hammer M., Champy J.A., Reengineering the Corporation: A Manifesto for Business Revolution, (2007); Hau L.L., Whang S., Winning the last mile of e-commerce, MIT Sloan Management Review, pp. 54-62, (2001); China's Online Shopping Logistics Study in 2009, (2009); Online Shopping Annual Data Released in 2010, (2010); Jiang H.D., Taken the pace of self-built logistics system - Visit the Jingdong Mall, Logistics Technology and Application, 15, 1, pp. 58-60, (2010); Kim J.W., Hwang C.S., Applying the analytic hierarchy process to the evaluation of customer-oriented success factors in mobile commerce, Services Systems and Services Management, 6, 1, pp. 69-74, (2005); Kwon O.B., Sadeh N., Applying casebased reasoning and multi-agent intelligent system to context-aware comparative shopping, Decision Support Systems, 37, 2, pp. 199-213, (2004); Li F., Luo H., E-commerce logistics model study, Business Research, 17, pp. 180-184, (2007); Liu L.Z., Jiao Y.H., Analysis of process of physical distribution in e-commerce environment, Logistics Technology, pp. 36-39, (2009); Liu S.J., Zhang Y., Yang C.W., Based on the SaaS service of small and medium-sized enterprises with business system, Journal of Southeast University (Natural Science Edition), 5, 1, pp. 458-459, (2011); Molla A., Taylor R., Licker P.S., Ecommerce diffusion in small island countries: The influence of institutions in Barbados, The Electronic Journal on Information Systems in Developing Countries, 28, 2, pp. 1-15, (2006); The Electricity Supplier Singles Crazy Suction Gold, (2011); Song B., Zhang H.W., A new operation model of e-business, Proceedings of the International Conference on Internet Technology and Applications, pp. 1-3, (2010); Sunil C., Peter M., Supply Chain Management Strategy, Planning, and Operation, (2008); Wade M., Hulland J., Review: The resource-based view and information systems research: Review, extension and suggestions for future research, Management Information Systems Quarterly, 28, 1, pp. 107-142, (2004); Wang Y.M., Li D.M., Taobao logistics plan development strategy, Scientific Era, 12, 1, pp. 64-66, (2010); Jingdong Mall, (2011); Wresch W., Initial e-commerce efforts in nine least developed countries: A review of national infrastructure, business approaches and product selection, Journal of Global Information Management, 11, 2, pp. 67-78, (2003); Wu N.N., Zheng L., Zhen L., B2B2C e-commerce mode of study - For example with alibaba, Market Modernization, 11, pp. 131-132, (2010); Yin R.K., Case Study Research: Design and Methods, (2003); Zhang Y.H., Analysis of the causes and the pros and cons of the Guanhua. B2C e-commerce businesses self-logistics, Business Times, 26, pp. 29-30, (2010); Zhao G.H., SaaS + e-commerce- - SMEs information platform, Computer Information, 2, 1, pp. 37-38, (2008); Zhao Y., China's C2C e-commerce logistics mode selection, Market of China, 41, pp. 15-16, (2010)",{"$nulls":8},1.5392929E7,null,null,null,"English","J. Electr. Commer. Organ.","Article","Final",null,"Scopus","2-s2.0-84877893349"]
["Zacharias J.; Zhang B.","Zacharias, John (56271080000); Zhang, Bingjie (56901967500)","56271080000; 56901967500","Local distribution and collection for environmental and social sustainability - tricycles in central Beijing",2015.0,"Journal of Transport Geography",49.0,null,null,9.0,15.0,6.0,16.0,"10.1016/j.jtrangeo.2015.10.003","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84944242526&doi=10.1016%2fj.jtrangeo.2015.10.003&partnerID=40&md5=4504119dc2db438d14d7e8dfa28290ba","College of Architecture and Landscape, Peking University, Beijing, China","Zacharias J., College of Architecture and Landscape, Peking University, Beijing, China; Zhang B., College of Architecture and Landscape, Peking University, Beijing, China","Goods distribution is a growing proportion of intra-urban transport worldwide due to changes in supply chains and e-commerce, yet has received scant attention in research. Cities have opted for a regulatory approach to truck movement and deliveries at a local level but few have tried to develop a systematic approach to management. Following certain suggestions in the literature, a hierarchical deliveries approach is being adopted in some new developments in Europe and Australia using light vehicles at the local level. In East, South and South-East Asia, where 3-wheeled non-motorised vehicles have been a mainstay of goods and people transport for several decades, they are under renewed pressure from city governments. This study of the tricycle in Beijing examines their role for packages delivery, food and beverage distribution and waste and recycling services, which covers nearly all of the uses of utilitarian tricycles in northern Chinese cities. Drivers (n = 97) were interviewed, their usual trips were mapped, and the subsequent trip was recorded using a geo-positioning system. These trips were compared with trips executed by small, motorised vans, favoured since 2014 by Beijing government. Operations can be divided into four categories according to delivery chain organisation, field operations and vehicle type. Motorised alternatives to the tricycle are shown to be uncompetitive in terms of time, cost and energy efficiency. This first detailed examination of the operations of the tricycle in a Chinese city provides a useful base for consideration of local distribution services organisation and a possible model for cities outside China. © 2015 Elsevier Ltd.","China; Distribution; Logistics; Non-motorised transport; Rickshaw; Tricycle","Australia; Beijing [China]; China; Europe; cycle transport; electronic commerce; environmental management; sustainability; urban transport",{"$nulls":4},"State Administration for Foreign Experts Affairs of the People’s Republic of China","The authors are grateful to three anonymous reviewers who helped us improve this text. The work was undertaken with infrastructure funding from the State Administration for Foreign Experts Affairs of the People’s Republic of China.","Brown K., China and the battle with modernity, Journal Contemp. Asia, 41, 2, pp. 324-330, (2011); Cau R., Cochoy F., Place and mobility: a statistical archaeology of pedestrian logistics in 20th and 21st century Toulouse, Flux, 88, pp. 19-33, (2012); Meeting the Carbon Budget: Progress Report to Parliament, 2014; Crainic T.G., Ricciardi N., Storchi G., Advanced freight transportation systems for congested urban areas, Transp. Res. C, 12, pp. 119-137, (2004); Dablanc L., Goods transport in large European cities: difficult to organize, difficult to modernize, Transp. Res. A, 41, pp. 280-285, (2007); Dey P.P., Chandra S., Gangopadhyay S., Simulationof mixed traffic flow on two-lane roads, J. Transp. Eng., 134, 9, pp. 361-369, (2008); Gallagher R., The rickshaws of Bangladesh, (1992); Goldman ., Gorham R., Sustainable urban transport: four innovative directions, Technol. Soc., 28, pp. 261-273, (2006); Hesse M., Rodrigue J.-P., The transport geography of logistics and freight distribution, J. Transp. Geogr., 12, pp. 171-184, (2004); Hewner S., Sun W., Worker motivation and productivity in Chinese (Beijing) tricycle haulers: integrating social and biological variables, Am. J. Hum. Biol., 7, pp. 21-32, (1995); Hussain M., Susilo Y.O., Rickshaw use and social impacts in Dhaka, Bangladesh, Transp. Res. Rec., 2239, pp. 74-83, (2011); Hyrapiet S., Greiner A., Calcutta's hand-pulled rickshaws: cultural politics and placemaking in a globalizing city, Geogr. Rev., 102, 4, pp. 407-426, (2012); Kohrman M., Motorcycles for the disabled: mobility, modernity and the transformation of experience in urban China, Cult. Med. Psychiatry, 23, pp. 133-155, (1999); Lindholm M., A sustainable perspective on urban freight transport: factors affecting local authorities in the planning procedures, Procedia Soc. Behav. Sci., 2, pp. 6205-6216, (2010); Marsden G., Mullen C., Bache I., Bartle I., Flinders M., Carbon reduction and travel behaviour: Discourses, disputes and contradictions in governance, Transp. Policy, 35, pp. 71-78, (2014); Munuzuri J., Larraneta J., Onieva L., Cortes P., Solutions applicable by local administrations for urban logistics improvement, Cities, 22, 1, pp. 15-28, (2005); Munuzuri J., Cortes P., Guadix Jose, Onieva L., City logistics in Spain: why it might never work, Cities, 29, pp. 133-141, (2012); Muttamara S., Visvanathan C., Alwis K.U., Solid waste recycling and reuse in Bangkok, Waste Manag. Res., 12, pp. 151-163, (1994); Norcliffe G., Neoliberal mobility and its discontents: working tricycles in China's cities, City Cult. Soc., 2, 4, pp. 235-242, (2011); Pan Y., Cao X., Spatial patterns and their formation mechanism of supply logistics network of wholesale markets in Guangzhou, Acta Geograph. Sin., 67, 2, pp. 179-188, (2012); Rahul R.M., Verma A., Economic impact of non-motorized transportation in Indian cities, Res. Transp. Econ., 38, pp. 22-34, (2013); Sadhu S.I.N.S., Tiwari G., Jain H., Impact of cycle rickshaw trolley (CRT) as non-motorised freight transport in Delhi, Transp. Policy, 35, pp. 64-70, (2014); Sharma D.C., Indian rickshaw pullers demand their due, Front. Ecol. Environ., 8, 4, (2010); Wang H., China's new order: society, politics, and economy in transition, (2003); Yang G., Et al., Rapid health transition in China, 1990-2010: findings from the Global Burden of Disease Study 2010, Lancet, 381, 9882, pp. 1987-2015, (2013); Zacharias J., Sun Z., Chuang L., Lee F., The hutong development model compared with contemporary suburban development in Beijing, Habitat Int., 49, pp. 260-265, (2015); Zhang Q., Study on traffic improvement for the historical cultural area in Beijing, (2008); Zhang Q.I., Study on traffic improvement for the historical cultural area in Beijing, (2008); Zhao X., Systematic strategic research on the protection and organic renewal of historic residential area in Old Beijing, (2010)",null,null,"Elsevier Ltd",{"$nulls":5},9666923.0,null,null,null,"English","J. Transp. Geogr.","Article","Final",null,"Scopus","2-s2.0-84944242526"]
["Li X.; Liu Z.; Xu Z.","Li, Xiuli (55988938400); Liu, Zhaohui (36135732100); Xu, Zhikun (56173423500)","55988938400; 36135732100; 56173423500","Research on the model of agricultural products distribution optimization under electronic commerce",2014.0,"International Journal of Multimedia and Ubiquitous Engineering",9.0,6.0,null,315.0,327.0,12.0,2.0,"10.14257/ijmue.2014.9.6.30","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84903548556&doi=10.14257%2fijmue.2014.9.6.30&partnerID=40&md5=dcc8040e657247d31c931fd3740c6531","College of Finance, Hebei Normal University of Science and Technology, Qinhuangdao, Hebei, 066004, China; Hebei Normal University of Science and Technology, Qinhuangdao, Hebei, 066004, China","Li X., College of Finance, Hebei Normal University of Science and Technology, Qinhuangdao, Hebei, 066004, China; Liu Z., Hebei Normal University of Science and Technology, Qinhuangdao, Hebei, 066004, China; Xu Z., College of Finance, Hebei Normal University of Science and Technology, Qinhuangdao, Hebei, 066004, China","Recently, people pay more and more attention to the healthy lifestyles. And there is an increasing demand for the green agricultural products in real life. With the rapid development of the computer network technology and the electronic commerce, the emergence of e-business provides a new idea to promote the service of agricultural products. A huge supply chain network is established by the new idea and the technology. More and more agricultural products firms establish the electronic sale channel and get great profits. Firstly, we analyze the status of the agricultural products logistics distribution in both traditional sale channel and electronic sale channel in this paper. Then, we summarize the problems appeared in e- commerce channel. To solve these problems, we build an optimization model of the agricultural products distribution in e- commerce channel. © 2014 SERSC.","E-commerce; Logistics distribution; SC network","Electronic commerce; Optimization; Supply chains; Agricultural products logistics; Computer network technology; E- commerces; Healthy lifestyles; Logistics distribution; Optimization modeling; Products distributions; Supply chain network; Agricultural products",{"$nulls":6},"Robson, Rawnsley V., Co-operation or coercion Supplier networks and relationships in the UK food industry, Supply Chain Management: An International Journal, 6, 1, pp. 39-47, (2001); Hsu C.I., Hung S.F., Li H.C., Vehicle routing problem with time-windows for perishable food delivery, Food Engineering, 80, 2, pp. 465-475, (2007); Montanari R., Cold chain tracking: A managerial perspective, Trends in Food Science andTechnology, 19, 8, pp. 425-431, (2008); Rediers H., Claes M., Peeters L., Willems K.A., Evaluation of the cold chain of fresh-cut endive from farmer to plate, Postharvest Biology and Technology, 51, 2, pp. 257-262, (2009); Ovca A., Jevnik M., Maintaining a cold chain from purchase to the home and at home: Consumer opinions, Food Control, 20, 2, pp. 167-172, (2009); Dabbene F., Gay P., Sacco N., Optimization of fresh-food supply chains in uncertain environments, Part I: Back ground and methodology, Bio systems Engineering, 99, 3, pp. 348-359, (2008); Osvald A., Stirn L.Z., A vehicle routing algorithm for the distribution of fresh vegetables and similar perishable food, Food Engineering, 85, 2, pp. 285-295, (2008); Zhaowei D., Jishun L., Analysis and Countermeasures of agricultural products supply chain coordination problem, Modern Business, 3, pp. 48-491, (2007); Zhao-yun L., Shi-min S., Ji-yong W., The Trend of Agricultural Supply Chain Management in China, Commercial Research, 3, pp. 161-1641, (2009); Bin D., Jun C., Bin D., Jun C., Chinese Journal of Management Science, 16, 5, pp. 42-49, (2008); Lin J., Study on network marketing current situation and development about Chinese agricultural product, Hunan Agricultural University, (2003); Wenhui X., Study on the operation mode of agricultural products logistics under e-commerce platform, Rural Economy, 3, pp. 5-6, (2003); Hong-xin Y., Study on the Supply Chain Management of Agriculture Product under E-commerce Environment, Journal of Anhui Agricultural Sciences, 21, (2010)",null,null,"Science and Engineering Research Support Society",{"$nulls":5},1.975008E7,null,null,null,"English","Int. J. Multimedia Ubiquitous Eng.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-84903548556"]
["Lips M.","Lips, Miriam (16069117200)",1.60691172E10,"E-Government is dead: Long live public administration 2.0",2012.0,"Information Polity",17.0,"2024-04-03",null,239.0,250.0,11.0,53.0,"10.3233/IP-120292","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84876228504&doi=10.3233%2fIP-120292&partnerID=40&md5=94bb0b1752a145a3b32b9896d50eddba","School of Government, Victoria University of Wellington, Wellington, New Zealand","Lips M., School of Government, Victoria University of Wellington, Wellington, New Zealand","Many complexities associated with e-Government are caused by using the wrong perspectives to understand and explain e-Government phenomena. This argument will be further introduced and explained by using e-Government initiatives and approaches in New Zealand as an illustrative case study. Generally, two dominant streams of e-Government thinking about the role of ICTs in government can be identified over time: e-Government 1.0-a perspective where ICTs are seen as a driving force of change in public administration and governance, and e-Government 2.0-a perspective that directly and explicitly relates the use of ICTs in government and its external relationships with transformational change. In this contribution it is argued that an alternative stream of thinking on e-Government is needed which accommodates the challenging dynamic, unpredictable, complex, and non-linear aspects of e-Government. As these aspects have everything to do with the unique characteristics of government, this alternative stream of thinking will be addressed as 'Public Administration 2.0', to reflect that current mainstream Public Administration thinking persistently separate out e-Government from their own domains of interest and treat them as technology-related topics without any relevance to the Public Administration discipline. The value of applying a Public Administration 2.0 perspective to e-Government phenomena is further demonstrated by discussing two examples based on empirical research from New Zealand, one example in which transactional e-Government service provision is compared with e-Commerce service delivery, and a second example exploring benefits realisation around three e-Government initiatives. © 2012 - IOS Press and the authors. All rights reserved.","e-Government; governance; government; ICT; institutional shaping; New Zealand; public administration",{"$nulls":7},"Andersen K.V., Henriksen H.Z., E-government maturity models: Extension of the Layne and Lee model, Government Information Quarterly, 23, pp. 236-248, (2006); Andersen K.V., Henriksen H.Z., The first leg of e-government research: Domains and application areas 1998-2003, International Journal of Electronic Government Research, 1, 4, pp. 26-44, (2005); Bekkers V.J.J.M., Van Duivenboden H., Thaens M., Information and Communication Technology and Public Innovation, (2006); Bellamy C., Taylor J.A., Governing in the Information Age, (1998); Bennett C.J., Raab C.D., The Governance of Privacy: Policy Instruments in Global Perspective, (2003); Borins S., Is iT transforming government? Evidence and lessons from Canada, Digital State at the Leading Edge, pp. 355-383, (2007); Borins S., Kernaghan K., Brown D., Bontis P.N., Thompson F., Digital State at the Leading Edge, (2007); Breese R., Benefits realisation management: Panacea or false dawn?, International Journal of Project Management, 30, pp. 341-351, (2012); Chadwick A., Internet Politics. States Citizens and New Communication Technologies, (2006); Doherty N.F., Ashurst C., Peppard J., Factors affecting the successful realisation of benefits fromsystems development projects: Findings from three case studies, Journal of Information Technology, 27, pp. 1-16, (2012); Dunleavy P., Margetts H., Bastow S., Tinkler J., Digital Era Governance: IT Corporations the State, and EGovernment, (2006); Eppel E.A., The Contribution of Complexity Theory to Understanding and Explaining Policy Processes: A Study of Tertiary Education Policy Processes in New Zealand, (2010); Foley P., Alfonso X., EGovernment and the transformation agenda, Public Administration, 87, 2, pp. 371-396, (2009); Fountain J.E., Building the Virtual State. Information Technology and Institutional Change, (2001); Frissen P.H.A., Public administration in cyberspace. A postmodern perspective, Public Administration in An Information Age: A Handbook, pp. 33-46, (1998); Gronlund A., State of the art in e-gov research: Surveying conference publications, International Journal of Electronic Government Research, 1, 4, pp. 1-25, (2005); Heeks R., Bailur S., Analyzing e-government research: Perspectives, philosophies, theories, methods, and practice, Government Information Quarterly, 24, pp. 243-265, (2007); Heeks R., Implementing and Managing EGovernment, (2006); Henman P., Governing Electronically: E-government and the Reconfiguration of Public Administration, Policy and Power, (2010); Homburg V., Understanding E-government: Information Systems in Public Administration, (2008); System Error: Fixing the Flaws in Government IT, (2010); Layne K., Lee J., Developing fully functional E-government: A four stage model, Government Information Quarterly, 18, 2, pp. 122-136, (2001); Lenk K., Reconstructing Public Administration theory from below, Information Polity, 12, 4, pp. 207-212, (2007); Lips A.M.B., Eppel E., Sylvester A., Pacheco E., Cunningham A., Improving Benefits Realisation from ICT-enabled Projects Through Identifying and Promoting Good Practice from Selected Public Entity Case Studies, (2012); Lips A.M.B., E-Government is dead - Long live networked governance: Fixing system errors in the New Zealand Public Management System, Future State: Directions for Public Management in New Zealand, pp. 248-261, (2011); Lips A.M.B., Eppel E.A., Cunningham A., Hopkins-Burns V., Public Attitudes to the Sharing of Personal Information in the Course of Online Public Service Provision, Final Research Report, (2010); Lips A.M.B., Schuppan T., Transforming e-government knowledge through public management research, Public Management Review, 11, 6, pp. 739-749, (2009); Lips A.M.B., Frissen P.H.A., Wiring Government. Integrated Public Service Delivery Through ICT in the UK and the USA, NWO/ITeR-series, 8, pp. 67-164, (1997); Lips A.M.B., Does public administration have artefacts?, Information Polity, 12, 4, pp. 243-252, (2007); MacKenzie D.A., Wajcman J., The Social Shaping of Technology: How the Refrigerator Got Its Hum, (1985); Meijer A.J., Why don't they listen to us? Reasserting the role of ICT in Public Administration, Information Polity, 12, 4, pp. 233-242, (2007); Benefits Realisation Guideline, (2011); Realising Benefits from Six Public Sector Technology Projects, (2012); O'Neill R.R., E-government: Transformation of Public Governance in New Zealand?, (2009); Rethinking E-Government Services: User-Centred Approaches Paris, (2009); Benefits Realisation Management, (2007); The Egovernment Imperative Paris: Organisation for Economic Co-operation and Development, (2003); Orlikowski W.J., Barley S.R., Technology and institutions: What can research on information technology and research on organizations learn from each other?, MIS Quarterly, 25, 2, pp. 145-165, (2001); Roy J., E-Government in Canada. Transformation for the Digital Age, (2006); Snellen I.Th.M., Donk De Van W.B.H.J., Public Administration in An Information Age: A Handbook, (1998); Snellen I.Th.M., Is \"informatisation\" after 20 years still a \"corpus alienum\" in Public Administration?, Information Polity, 12, 4, pp. 201-206, (2007); Taylor J.A., Lips A.M.B., The citizen in the information polity: Exposing the limits of the e-government paradigm, Information Polity, 13, 3-4, pp. 139-152, (2008); Taylor J.A., Rediscovering the grand narratives of the information polity: Reflections on the achievement and potential of the EGPA study group on ICT in public administration, Information Polity, 12, 4, pp. 213-217, (2007); Taylor J.A., Informatization as X-ray: What is public administration for the information age?, Public Administration in An Information Age: A Handbook, pp. 21-32, (1998); Transformational Government - Enabled by Technology, (2005)","M. Lips; School of Government, Victoria University of Wellington, Wellington, New Zealand; email: Miriam.Lips@vuw.ac.nz",{"$nulls":7},1.8758754E7,null,null,null,"English","Inf. Polity","Article","Final",null,"Scopus","2-s2.0-84876228504"]
["Li Y.; Guo H.; Wang L.; Fu J.","Li, Yanhui (56040405100); Guo, Hao (57190736884); Wang, Lin (57193123129); Fu, Jing (54790969200)","56040405100; 57190736884; 57193123129; 54790969200","A hybrid genetic-simulated annealing algorithm for the location-inventory- routing problem considering returns under E-supply chain environment",2013.0,"The Scientific World Journal",2013.0,null,125893.0,null,null,null,56.0,"10.1155/2013/125893","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84896288011&doi=10.1155%2f2013%2f125893&partnerID=40&md5=45b0c59e9e49ab16ce3ed4c7e73c6d6c","School of Information Management, Central China Normal University, Wuhan 430079, China; School of Management, Huazhong University of Science and Technology, Wuhan 430074, China; Department of Industrial and System Engineering, State University of New York at Buffalo, Buffalo, NY 14228, United States","Li Y., School of Information Management, Central China Normal University, Wuhan 430079, China; Guo H., School of Information Management, Central China Normal University, Wuhan 430079, China; Wang L., School of Management, Huazhong University of Science and Technology, Wuhan 430074, China; Fu J., School of Information Management, Central China Normal University, Wuhan 430079, China, Department of Industrial and System Engineering, State University of New York at Buffalo, Buffalo, NY 14228, United States","Facility location, inventory control, and vehicle routes scheduling are critical and highly related problems in the design of logistics system for e-business. Meanwhile, the return ratio in Internet sales was significantly higher than in the traditional business. Many of returned merchandise have no quality defects, which can reenter sales channels just after a simple repackaging process. Focusing on the existing problem in e-commerce logistics system, we formulate a location-inventory-routing problem model with no quality defects returns. To solve this NP-hard problem, an effective hybrid genetic simulated annealing algorithm (HGSAA) is proposed. Results of numerical examples show that HGSAA outperforms GA on computing time, optimal solution, and computing stability. The proposed model is very useful to help managers make the right decisions under e-supply chain environment. © 2013 Yanhui Li et al.",null,"Algorithms; Internet; Models, Theoretical; article; cost; genetic algorithm; genetic variability; genotype; health care policy; hybrid genetic simulated annealing algorithm; Internet; inventory control; mathematical computing; mathematical model; point mutation; population dynamics; population size; algorithm; Internet; theoretical model",{"$nulls":4},"National Natural Science Foundation of China, (70801030, 70871050, 71131004, 71171093, 71371080)",null,"Ecommerce Sales Topped $1 Trillion for the First Time in 2012; Meyer H., Many happy returns, Journal of Business Strategy, 20, 4, pp. 27-31, (1999); Gentry C.R., Reducing the cost of returns, Chain Store Age, 75, 10, pp. 124-126, (1999); Yang J., Fei Z., Statistical filtering based broadcast protocol for vehicular networks, Proceedings of the 20th International Conference on Computer Communications and Networks (ICCCN '11), pp. 1-6, (2011); Yang J., Fei Z., HDAR: Hole detection and adaptive geographic routing for ad hoc networks, Proceedings of the 19th International Conference on Computer Communications and Networks (ICCCN '10), pp. 1-6, (2010); Watson-Gandy C., Dohrn P., Depot location with van salesmen: A practical approach, Omega, 1, 3, pp. 321-329, (1973); Nagy G., Salhi S., Location-routing: Issues, models and methods, European Journal of Operational Research, 177, 2, pp. 649-672, (2006); Moin N.H., Salhi S., Inventory routing problems: A logistical overview, Journal of the Operational Research Society, 58, 9, pp. 1185-1194, (2007); Liu S.C., Lee S.B., A two-phase heuristic method for the multi-depot location routing problem taking inventory control decisions into consideration, International Journal of Advanced Manufacturing Technology, 22, 11-12, pp. 941-950, (2003); Liu S.C., Lin C.C., A heuristic method for the combined location routing and inventory problem, International Journal of Advanced Manufacturing Technology, 26, 4, pp. 372-381, (2005); Max Shen Z.-J., Qi L., Incorporating inventory and routing costs in strategic location models, European Journal of Operational Research, 179, 2, pp. 372-389, (2007); Ahmadi Javid A., Azad N., Incorporating location, routing and inventory decisions in supply chain network design, Transportation Research e, 46, 5, pp. 582-597, (2010); Ahmadi-Javid A., Seddighi A.H., A location-routing-inventory model for designing multisource distribution networks, Engineering Optimization, 43, 10, pp. 1-19, (2012); Fleischmann M., Beullens P., Bloemhof-Ruwaard J.M., Van Wassenhove L.N., The impact of product recovery on logistics network design, Production and Operations Management, 10, 2, pp. 156-173, (2001); Jayaraman V., Patterson R.A., Rolland E., The design of reverse distribution networks: Models and solution procedures, European Journal of Operational Research, 150, 1, pp. 128-149, (2003); Lieckens K., Vandaele N., Reverse logistics network design with stochastic lead times, Computers and Operations Research, 34, 2, pp. 395-416, (2007); Sahyouni K., Savaskan R.C., Daskin M.S., A facility location model for bidirectional flows, Transportation Science, 41, 4, pp. 484-499, (2007); Easwaran G., Uster H., Tabu search and Benders decomposition approaches for a capacitated closed-loop supply chain network design problem, Transportation Science, 43, 3, pp. 301-320, (2009); Srivastava S.K., Network design for reverse logistics, Omega, 36, 4, pp. 535-548, (2008); Vlachos D., Dekker R., Return handling options and order quantities for single period products, European Journal of Operational Research, 151, 1, pp. 38-52, (2003); Jakobs S., On genetic algorithms for the packing of polygons, European Journal of Operational Research, 88, 1, pp. 165-181, (1996); Gen M., Cheng R., Lin L., Network Models and Optimization: Multi-Objective Genetic Algorithm Approach, (2008); Leung T.W., Yung C.H., Troutt M.D., Applications of genetic search and simulated annealing to the two-dimensional non-guillotine cutting stock problem, Computers and Industrial Engineering, 40, 3, pp. 201-214, (2001); Location-Routing Problems (LRP); Orkcu H.H., Subset selection in multiple linear regression models: A hybrid of genetic and simulated annealing algorithms, Applied Mathematics and Computation, 129, 23, pp. 11018-11028, (2013); Xu Y., Qu R., Li R.F., A simulated annealing based genetic local search algorithm for multi-objective multicast routing problems, Annals of Operations Research, 206, 1, pp. 527-555, (2013); Wang L., Fu Q.L., Lee C.G., Zeng Y.R., Model and algorithm of fuzzy joint replenishment problem under credibility measure on fuzzy goal, Knowledge-Based Systems, 39, pp. 57-66, (2013); Wang L., Dun C.X., Lee C.G., Fu Q.L., Zeng Y.R., Model and algorithm for fuzzy joint replenishment and delivery scheduling without explicit membership function, International Journal of Advanced Manufacturing Technology, 66, 9-12, pp. 1907-1920, (2013); Wang L., Qu H., Li Y.H., He J., Modeling and optimization of stochastic joint replenishment and delivery scheduling problem with uncertain costs, Discrete Dynamics in Nature and Society, 2013, (2013)","L. Wang; School of Management, Huazhong University of Science and Technology, Wuhan 430074, China; email: wanglin982@gmail.com",null,"ScientificWorld Ltd.",{"$nulls":5},"1537744X",null,null,2.4489489E7,"English","Sci. World J.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-84896288011"]
["George A.; Kumar G.S.G.","George, Ajimon (55947911000); Kumar, G.S. Gireesh (55949117400)","55947911000; 55949117400","Antecedents of Customer Satisfaction In Internet Banking: Technology Acceptance Model (TAM) Redefined",2013.0,"Global Business Review",14.0,4.0,null,627.0,638.0,11.0,49.0,"10.1177/0972150913501602","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84889016226&doi=10.1177%2f0972150913501602&partnerID=40&md5=b88a76b2917944fc1f4f8be0be35c73e","Marian college, Kuttikkanam-685531, Kerala, India; Nirmala College, Muvattupuzha-686661, Kerala, India","George A., Marian college, Kuttikkanam-685531, Kerala, India; Kumar G.S.G., Nirmala College, Muvattupuzha-686661, Kerala, India","In the banking sector, various electronic delivery channels are increasingly used for delivering products and services for the convenience of customers at low cost. Internet banking (IB) is one among them. IB is a product of e-commerce in the field of banking and financial services. The present study has been carried out to use the Technology Acceptance Model (TAM) from the Information Technology (IT) literature to investigate the effect of TAM variables on customer satisfaction in the internet-banking context. The model was constructed by incorporating Perceived Risk (PR) to the twin traditional TAM constructs, Perceived Ease of Use (PEOU) and Perceived Usefulness (PU). The model has been empirically validated using 406 IB users selected from the state of Kerala, India. It is found that the constructs PEOU and PU have positive effect on customer satisfaction and PR has negative effect on customer satisfaction. A profile analysis of the respondents revealed that young males, well-educated employees with a moderately high level of monthly income are the major users of IB in Kerala. © 2013 IMI SAGE Publications.","Perceived Ease of Use; Perceived Risk; Perceived Usefulness; Public Key Infrastructure; Technology Acceptance Model",{"$nulls":7},"Ajay P., Garima M., Empirical study of internet banking in India, CURIE, BITS Pilani, 1, 3, pp. 83-92, (2008); Akram J.K., Evaluating the influence of reliability, usability, usefulness and website design on the satisfaction of online consumers, Research Journal of Economics, Business and ICT, 2, pp. 28-32, (2011); Al-Gahtani S., The applicability of TAM outside North America: An empirical test in the United Kingdom, Information Resource Management Journal, 14, 3, pp. 37-46, (2001); Al-Ghatani S., King M., Attitudes, satisfaction and usage: Factors contributing to each in the acceptance of information technology, Behaviour & Information Technology, 18, 4, pp. 277-297, (1999); Al-hawari M.A., Mouakket S., The influence of technology acceptance model (TAM) factors on students' e-satisfaction and e-retention within the context of UAE e-learning, Education, Business and Society: Contemporary Middle Eastern Issues, 3, 4, pp. 299-314, (2010); Awamleh R., Cedwyn F., Diffusion of Internet Banking amongst educated consumers in a high income non-OECD country, Journal of Internet Banking and Commerce, 11, 3, (2006); Chau P.Y.K., Lai V.S.K., An empirical investigation of the determinants of user acceptance of Internet banking, Journal of Organizational Computing and Electronic Commerce, 13, 2, pp. 123-145, (2003); Chen S., Chen H., Lin M., Chen Y., A conceptual model to understand the effects of perception on the continuance intention in Facebook, Australian Journal of Business and Management Research, 1, 8, pp. 29-34, (2011); Cheng T.C.E., Lam D.Y.C., Yeung A.C.L., Adoption of internet banking: An empirical study in Hong Kong, Decision Support Systems, 42, 3, pp. 1558-1572, (2006); 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Scheepers R., Scheepers H., Ngwenyama O.K., Contextual influences on user satisfaction with mobile computing: Findings from two healthcare organizations, European Journal of Information Systems, 15, 3, pp. 261-268, (2006); Seddon P., Kiew M., A partial test and development of the DeLone and McLean model of IS success, Proceedings of the Fifteenth International Conference on Information Systems. Vancouver, British Columbia, Canada, (1994); Sibona C., Choi J.H., Proceedings of the Sixth International AAAI Conference on Weblogs and Social Media, pp. 575-578, (2012); Soud A., Fisal A.R., 2011 International Conference on Telecommunication Technology and Applications, (2011); Srivastava R., Customer's perception on usage of internet banking, Innovative Marketing, 3, 4, pp. 67-73, (2007); Sujana A., Adoption of Internet shopping: Cultural considerations in India and Australia, Journal of Internet Banking and Commerce, 13, 2, pp. 1-17, (2008); Tabachnik B.G., Fidel L.S., Using Multivariate Statistics, (2001); Thulani D., Chitura T., Runyowa L., Adoption and use of internet banking in Zimbabwe: An exploratory study, Journal of Internet Banking and Commerce, 14, 1, pp. 1-13, (2009); Wang Y.S., Wang Y.M., Lin H.H., Tang I., Determinants of user acceptance of internet banking: An empirical study, International Journal of Service Industry Management, 14, 5, pp. 501-519, (2003); Winnie C., John P., An evaluation if internet banking in New Zealand, Proceedings from the 35th Hawaii International Conference on System Sciences, (2002); Yi Y., A Critical Review of Consumer Satisfaction, (1990); Yiu S.C., Grant K., Edgar D., Factors affecting the adoption of internet banking in Hong Kong- implications for the banking sector, International Journal of Information Management, 27, 5, pp. 336-351, (2007)",{"$nulls":8},9730664.0,null,null,null,"English","Global Bus. Rev.","Article","Final",null,"Scopus","2-s2.0-84889016226"]
["Pandey S.; Chawla D.","Pandey, Shweta (56305755700); Chawla, Deepak (36184900900)","56305755700; 36184900900","E-lifestyles of Indian online shoppers: A scale validation",2014.0,"Journal of Retailing and Consumer Services",21.0,6.0,null,1068.0,1074.0,6.0,21.0,"10.1016/j.jretconser.2014.06.012","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84908052642&doi=10.1016%2fj.jretconser.2014.06.012&partnerID=40&md5=7961da3b679092ca04bc71bd62caca34","International Management Institute B-10, Qutub Institution, Block A, New Delhi, 110016, India","Pandey S., International Management Institute B-10, Qutub Institution, Block A, New Delhi, 110016, India; Chawla D., International Management Institute B-10, Qutub Institution, Block A, New Delhi, 110016, India","Online shopping in India is growing at a dramatic rate and marketers are still working on understanding the lifestyles of online shoppers for purpose of segmentation, targeting and promotions. The scales for such requirements developed in other countries may not be apt for use in India. Hence there is a need to develop appropriate scales applicable in the Indian context. By way of review of the previous literature as well as exploratory study through interviews and focus group with online shoppers and experts in the field, the authors develop a pool of items relating to electronic lifestyles, henceforth called e-lifestyles of Indian online shoppers. Further using exploratory as well as confirmatory factor analysis, reliability and validity of the scale is confirmed and a six factor scale consisting of e-enjoyment, e-distrust, e-self-inefficacy, e-logistic concerns, e-negative beliefs and e-offers is developed. The study is a first step towards identifying a more holistic picture of factors that influence Indian online shopper lifestyles or e-lifestyles. The findings of this study can be integrated into marketing and promotional strategies of the web retailers. © 2014 Elsevier Ltd.","E-lifestyles; India; Online shopping; Scale validation","India; Internet; lifestyle; marketing; shopping activity; World Wide Web",{"$nulls":6},"Ahmad N., Omar A., Ramayah T., Consumer lifestyles and online shopping continuance intention, Bus. Strateg. Ser., 11, 4, pp. 227-243, (2010); Ahmad N., Omar A., Ramayah T., Examining the validity and reliability of e-lifestyles scale in the malaysian context: a preliminary results, pp. 589-597, (2012); Allred C.R., Smith S.M., Swinyard W.R., E-shopping lovers and fearful conservatives: a market segmentation analysis, Int. J. Retail Distrib. Manag., 34, 4, pp. 308-333, (2006); Assael H., A demographic and psychographic profile of heavy Internet users and users by type of internet usage, J. Advert. Res., 45, 1, pp. 93-123, (2005); Bellman S., Lohse G.L., Johnson E.J., Predictors of online buying behaviour, Commun. 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Retail., 76, 3, pp. 309-322, (2000); Wang E.T.G., Yeh H.Y., Jiang J.J., The relative weights of Internet shopping fundamental objectives: effect of lifestyle differences, Psychol. Mark., 23, 5, pp. 353-367, (2006); Wells W., Psychographics: a critical review, J. Mark. Res., 12, pp. 196-213, (1975); Wells W., Tigert D., Activities, interests, and opinions, J. Adv. Res., 11, pp. 27-35, (1971); Wu S.I., The relationship between consumer characteristics and attitude toward online shopping, Mark. Intell. Planning, 21, 1, pp. 37-44, (2003); Ye Q., Li G., Gu B., A cross-cultural validation of the internet usage-related lifestyle scale: an empirical investigation in China, Electron. Commer. Res. Appl., 10, 3, pp. 304-312, (2011); Yu C.-S., Construction and validation of an e-lifestyle instrument, Internet Res., 21, 3, pp. 214-235, (2011)",null,null,"Elsevier Ltd",{"$nulls":5},9696989.0,null,null,null,"English","J. Retail. Consum. Serv.","Article","Final",null,"Scopus","2-s2.0-84908052642"]
["Liu B.; Chen H.; Li Y.; Liu X.","Liu, Bailing (56065758500); Chen, Hui (39260933200); Li, Yanhui (56040405100); Liu, Xiang (54412750500)","56065758500; 39260933200; 56040405100; 54412750500","A pseudo-parallel genetic algorithm integrating simulated annealing for stochastic location-inventory-routing problem with consideration of returns in e-commerce",2015.0,"Discrete Dynamics in Nature and Society",2015.0,null,586581.0,null,null,null,32.0,"10.1155/2015/586581","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84925310755&doi=10.1155%2f2015%2f586581&partnerID=40&md5=9517014aefc66b48299544803a189a4d","School of Information Management, Central China Normal University, Wuhan, 430079, China; Hubei Research Center for E-Commerce, Wuhan, 430079, China","Liu B., School of Information Management, Central China Normal University, Wuhan, 430079, China, Hubei Research Center for E-Commerce, Wuhan, 430079, China; Chen H., School of Information Management, Central China Normal University, Wuhan, 430079, China; Li Y., School of Information Management, Central China Normal University, Wuhan, 430079, China, Hubei Research Center for E-Commerce, Wuhan, 430079, China; Liu X., School of Information Management, Central China Normal University, Wuhan, 430079, China, Hubei Research Center for E-Commerce, Wuhan, 430079, China","Facility location, inventory control, and vehicle routes scheduling are three key issues to be settled in the design of logistics system for e-commerce. Due to the online shopping features of e-commerce, customer returns are becoming much more than traditional commerce. This paper studies a three-phase supply chain distribution system consisting of one supplier, a set of retailers, and a single type of product with continuous review (Q, r) inventory policy. We formulate a stochastic location-inventory-routing problem (LIRP) model with no quality defects returns. To solve the NP-hand problem, a pseudo-parallel genetic algorithm integrating simulated annealing (PPGASA) is proposed. The computational results show that PPGASA outperforms GA on optimal solution, computing time, and computing stability. © 2015 Bailing Liu et al.",{"$nulls":6},"National Natural Science Foundation of China, (71101061, 71171093, 71471073)",null,"Gentry C.R., Reducing the cost of returns, Chain Store Age, 75, 10, pp. 124-126, (1999); Meyer H., Many happy returns, Journal of Business Strategy, 20, 4, pp. 27-31, (1999); Watson-Gandy C.D.T., Dohrn P., Depot location with van salesmen-a practical approach, Omega, 1, 3, pp. 321-329, (1973); Nagy G., Salhi S., Location-routing: Issues, models and methods, European Journal of Operational Research, 177, 2, pp. 649-672, (2007); Moin N.H., Salhi S., Inventory routing problems: A logistical overview, Journal of the Operational Research Society, 58, 9, pp. 1185-1194, (2007); Max Shen Z.J., Qi L., Incorporating inventory and routing costs in strategic location models, European Journal of Operational Research, 179, 2, pp. 372-389, (2007); Liu S.C., Lee S.B., A two-phase heuristic method for the multi-depot location routing problem taking inventory control decisions into consideration, International Journal of Advanced Manufacturing Technology, 22, 11-12, pp. 941-950, (2003); Liu S.C., Lin C.C., A heuristic method for the combined location routing and inventory problem, International Journal of Advanced Manufacturing Technology, 26, 4, pp. 372-381, (2005); Ahmadi Javid A., Azad N., Incorporating location, routing and inventory decisions in supply chain network design, Transportation Research Part E: Logistics and Transportation Review, 46, 5, pp. 582-597, (2010); Ahmadi-Javid A., Seddighi A.H., A location-routinginventory model for designing multisource distribution networks, Engineering Optimization, 44, 6, pp. 637-656, (2012); Guerrero W.J., Prodhon C., Velasco N., Amaya C.A., Hybrid heuristic for the inventory location-routing problem with deterministic demand, International Journal of Production Economics, 146, 1, pp. 359-370, (2013); Fleischmann M., Beullens P., Bloemhof-Ruwaard J.M., Vanwassenhove L.N., The impact of product recovery on logistics network design, Production and Operations Management, 10, 2, pp. 156-173, (2001); Jayaraman V., Patterson R.A., Rolland E., The design of reverse distribution networks:models and solution procedures, European Journal of Operational Research, 150, 1, pp. 128-149, (2003); Lieckens K., Vandaele N., Reverse logistics network design with stochastic lead times, Computers and Operations Research, 34, 2, pp. 395-416, (2007); Sahyouni K., Savaskan R.C., Daskin M.S., A facility location model for bidirectional flows, Transportation Science, 41, 4, pp. 484-499, (2007); Easwaran G., Uster H., Tabu search and Benders decomposition approaches for a capacitated closed-loop supply chain network design problem, Transportation Science, 43, 3, pp. 301-320, (2009); Srivastava S.K., Network design for reverse logistics, Omega, 36, 4, pp. 535-548, (2008); Li Y.H., Lu M.M., Liu B.L., A two-stage algorithm for the closed-loop location-inventory problem model considering returns in e-commerce, Mathematical Problems in Engineering, 2014, (2014); Li Y.H., Guo H., Wang L., Fu J., Ahybridgenetic-simulated annealing algorithm for the location-inventory-routing problem considering returns under E-supply chain environment, The Scientific World Journal, 2013, (2013); Vlachos D., Dekker R., Return handling options and order quantities for single period products, European Journal of Operational Research, 151, 1, pp. 38-52, (2003); De Toronegro F., Ortega J., Ros E., Mota S., Paechter B., Martin J.M., PSFGA: Parallel processing and evolutionary computation for multiobjective optimisation, Parallel Computing, 30, 5-6, pp. 721-739, (2004); Jakobs S., On genetic algorithms for the packing of polygons, European Journal of Operational Research, 88, 1, pp. 165-181, (1996); Gen M., Cheng R., Lin L., Network Models and Optimization: Multi-Objective Genetic Algorithm Approach, (2008); Leung T.W., Yung C.H., Troutt M.D., Applications of genetic search and simulated annealing to the two-dimensional non-guillotine cutting stock problem, Computers and Industrial Engineering, 40, 3, pp. 201-214, (2001); Wang L., Fu Q.L., Lee C.G., Zeng Y.R., Model and algorithm of fuzzy joint replenishment problem under credibility measure on fuzzy goal, Knowledge-Based Systems, 39, pp. 57-66, (2013); Wang L., Qu H., Li Y.H., He J., Modeling and optimization of stochastic joint replenishment and delivery scheduling problem with uncertain costs, Discrete Dynamics in Nature and Society, 2013, (2013); Qu H., Wang L., Zeng Y.R., Modeling and optimization for the joint replenishment and delivery problem with heterogeneous items, Knowledge-Based Systems, 54, pp. 207-215, (2013)",null,null,"Hindawi Publishing Corporation",{"$nulls":5},1.0260226E7,null,null,null,"English","Discrete Dyn. Nat. Soc.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-84925310755"]
["Yang H.; Li J.","Yang, Haoxiong (34878124800); Li, Jindan (55981022500)","34878124800; 55981022500","Study on the optimization of vehicle scheduling problem under the e-commerce environment",2013.0,"Information Technology Journal",12.0,23.0,null,7827.0,7832.0,5.0,1.0,"10.3923/itj.2013.7827.7832","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84901795091&doi=10.3923%2fitj.2013.7827.7832&partnerID=40&md5=4646b079e83d431a3b874352d71eccbd","School of Business, Beijing Technology and Business University, 100048, Beijing, China; Research Base of Capital Retail, 100048, Beijing, China","Yang H., School of Business, Beijing Technology and Business University, 100048, Beijing, China, Research Base of Capital Retail, 100048, Beijing, China; Li J., School of Business, Beijing Technology and Business University, 100048, Beijing, China, Research Base of Capital Retail, 100048, Beijing, China","Studying vehicle scheduling problem under the e-business environment, is beneficial to reduce distribution costs, improve service quality, promote the development of e-commerce enterprises. In this study, for the new characteristics of logistics distribution such as small demand, many kinds of goods, scattered location, the vehicle scheduling problem under electronic commerce environment is studied, using clustering analysis method to divide distribution area. The VRPTW model is established, using genetic algorithm to solve the model. Through simulation experiment, comparing with the traditional VRP model, it found the optimized cost is lower than the unoptimized cost. This study is verified on the effectiveness of the method for VRPTW optimization model. © 2013 Asian Network for Scientific Information.","Cluster analysis; Electronic commerce; Genetic algorithm; Time window; Vehicle scheduling","Cluster analysis; Computer simulation; Costs; Electronic commerce; Genetic algorithms; Scheduling; Vehicle routing; Clustering analysis; E business environment; E-commerce enterprise; Logistics distribution; Optimization modeling; Time windows; Vehicle scheduling; Vehicle scheduling problem; Distribution of goods",{"$nulls":6},"Clarke G., Wright G.W., Scheduling of vehicles from a central depot to a number of delivery points, Operat. Res., 12, pp. 568-581, (1964); Dantzig G.B., Ramser J.H., The truck dispatching problem, Manage. Sci., 6, pp. 80-91, (1959); Gendreau M., Hertz A., Laporte G., A tabu search heuristic for the vehicle routing problem, Working Paper CRT-777, Centre de Recherche sur les Transport, Univeriste de Montreal, (1991); Gong J.L., Cheng Z.M., The realization of genetic algor ithm of VRP based on the MATLAB, J. Logist. Technol, 29, pp. 103-105, (2006); He X., Study on B2C E-commerce Distribution Problem, (2009); Lawrence S., Mohammad A., Parametric experimentation with a genetic algorithmic configuration for solving the vehicle routing problem, Proceedings of the Annual Meeting of the Decision Sciences Institute, pp. 488-490, (1996); Li L.W., Research on Innovative Mode of E-commerce Logistics, (2007); Tang J., Study on problem of distribution vehicle scheduling with time window constraints, J. Comput. Eng. Appl, 47, pp. 243-248, (2011); Xie T.B., Lei X.L., Xi W.L., Study on stowage vehicle scheduling in logistics distribution center, J. Comput. Eng. Appl, 46, pp. 237-240, (2010); Zhu J.Q., Research on innovation for the main responsibility tracing system, J. Beijing Technol. Bus. Univ. (Soc. Sci. Edn), 2, pp. 58-64, (2012)",null,null,"Asian Network for Scientific Information",{"$nulls":5},1.8125638E7,null,null,null,"English","Inf. Technol. J.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-84901795091"]
["Qiu Z.","Qiu, Zeguo (55866151000)",5.5866151E10,"On the analysis of building a public information platform based on e-Commerce for coal logistics",2013.0,"Journal of Industrial Engineering and Management",6.0,4.0,null,986.0,995.0,9.0,3.0,"10.3926/jiem.746","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84890947637&doi=10.3926%2fjiem.746&partnerID=40&md5=6648b0b673f0caee324159af9f175674","School of computer and information engineering, Harbin University of Commerce, Harbin, Heilongjiang, China","Qiu Z., School of computer and information engineering, Harbin University of Commerce, Harbin, Heilongjiang, China","Purpose: Putting forward the concept and features of the public information platform for coal logistics based on electronic commerce, as well as the requirements of upper and lower intersections of the coal supply chain. Meanwhile, this paper will also probe into the current condition of statistics management in coal logistics, and then discuss how to build a public information platform based on electronic commerce for coal logistics. Design/methodology/approach: According to the further exploring the concepts and relevant characteristics and the development of coal logistics and supply chain management in China of the current period. Findings/practical implications: An advanced public information platform for coal logistics utilizes to best advantage modern information technologies and managerial concepts in the operation of coal logistics, such as e-commerce, e-information, supply chain management, etc. This not only stimulates efficient integration of business flow, information flow, logistics and capital flow of the coal industry, brings about in-depth integration of the logistics resources of the coal industry, but also greatly improves the efficiency of the operation of coal logistics, reduces the cost of coal logistics, and enhances the overall competitiveness of upstream and downstream companies along the coal supply chain. Research limitations/implications: Although the coal logistics public information platform has been applied in some enterprises in China, not yet in a broader range of applications, which need the joint efforts of all parties. Originality/value: Fitted to the e-commerce era, the Public Information Platform for Coal Logistics envisioned in this article is highly feasible and worthy of reference to relevant institutions.","Coal logistics; Electronic commerce; Public information platform; Supply chain management","Coal; Coal deposits; Coal industry; Competition; Electronic commerce; Industry; Information technology; Supply chain management; Business flow; Capital flow; Design/methodology/approach; Information flows; Logistics and supply chain management; Logistics resources; Modern information technologies; Public information; Information management",{"$nulls":6},"Aldin N., Stahre F., Electronic commerce, marketing channels and logistics platforms-a wholesaler perspective, European Journal of Operational Research, 144, 2, pp. 270-279, (2003); Berman O., Drezner Z., Wesolowsky G.O., Satisfying partial demand in facilities location, HE Transactions, 34, 11, pp. 971-978, (2002); Gattuso D., Cassone G.C., Micro-simulation Model Supporting the Management of an Interregional Logistic Platform, Procedia - Social and Behavioral Sciences, 54, 4, pp. 557-566, (2012); Lai K.-H., Wong C.W.Y., Cheng T.C.E., A coordination-theoretic investigation of the impact of electronic integration on logistics performance, Information & Management, 45, 1, pp. 10-20, (2008); Xifeng T., Jing Y., Research on Coal Logistics System Structure, Logistics Technology, 10, pp. 16-18, (2004); Yunliang W., Shaopeng H., China's coal logistics network system: Optimization and policy side suggestions, China Coal, 34, 10, pp. 27-33, (2008); Zaklan A., Cullmann A., Neumann A., von Hirschhausen C., The globalization of steam coal markets and the role of logistics: An empirical analysis, Energy Economics, 34, 1, pp. 105-116, (2012); Zhao Q.H., Chen S., Leung S.C.H., Lai K.K., Integration of inventory and transportation decisions in a logistics system, Transportation Research Part E: Logistics and Transportation Review, 46, 6, (2010)","Z. Qiu; School of computer and information engineering, Harbin University of Commerce, Harbin, Heilongjiang, China; email: qiuzeguo@sina.com",{"$nulls":7},2.0130953E7,null,null,null,"English","J. Ind. Eng. Manage.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-84890947637"]
["Allen G.; Feils D.; Disbrow H.","Allen, Grace (56669237500); Feils, Dorothee (22940832100); Disbrow, Holly (56669806400)","56669237500; 22940832100; 56669806400","The rise and fall of Netflix: What happened and where will it go from here?",2014.0,"Journal of the International Academy for Case Studies",20.0,1.0,null,135.0,144.0,9.0,3.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-84930451201&partnerID=40&md5=32fd747821591073170d6ccc94a0133a","Western Carolina University, United States; University of Alberta, Canada","Allen G., Western Carolina University, United States; Feils D., University of Alberta, Canada; Disbrow H., Western Carolina University, United States","Case Description: The primary subject matter of this case concerns company analysis. Secondary issues include financial statement analysis, corporate strategy and international expansion. The case has a difficulty level of three and should be appropriate for undergraduate and graduate courses in investments and financial and strategic management. The case is designed to be taught in one to two class hours, with three hours of outside preparation by students. Case Synopsis: Netflix is an innovative company that has changed the way we rent movies and watch TV shows. Its business model is based on a subscription service that provides home-delivery of DVD rentals and streaming of movies and TV shows. The company took advantage of the rapid growth in the DVD rental market, the internet and e-commerce by providing a service that the traditional brick-and-mortar retailers, such as Blockbuster, could not compete with. In 2011, however, a price hike, poor management decisions, changes in technology, and increased competition threatened Netflix, leading to a sharp decline in its share price. In this case, students analyze the fundamentals of Netflix including its financials and management decisions to help determine if Netflix's poor stock performance in 2011 was predictable as well as what the future might hold for this company.",{"$nulls":8},"Argitis T., Netflix Said not To Face Broadcast Regulations in Canada, Bloomberg, (2011); Barnes B., Stelter B., Netflix Secures Streaming Deal With DreamWorks, The New York Times Reprints, (2011); Akkad E., Omar K.S., Marlow I., Netflix tweaks Canadian service to lower data usage, The Globe and Mail, (2011); Securities and Exchange Commission, (2012); Netflix vs. HULU Plus, Gadget Review, (2012); Gorman M., Comcast to launch Xfinity Streampix streaming video services challenge Netflix, HULU, and Amazon (update), Engadget, (2012); Hollister S., Netflix loses Starz Play deal on the eve of controversial price hike, The Verge, (2011); Netflix Canada To Get Comparable Quality To U.S.Service in 2012, (2011); Lang B., Waxman S., Netflix Stock Plunge: Will Reed Hastings' Hubris Bring Down an Internet Meteor?, (2011); Morningstar Investment Research Center (nd)., (2012); (2013); Netflix Introduces New Plans and Announces Price Changes, (2011); (2011); Annual Report, (2003); Marketline, (2011); No Value in Netflix: Is Carl Icahn Wrong?, Seeking Alpha, (2012); Daily Report: Netflix Transitions to TV Shows, New York Times Bits, (2012); Reisinger D., Netflix's international expansion: Analysts Shout Cut!, CNET News, (2012); Are Netflix's Eyes For International Expansion Bigger Than Its Stomach?, Forbes, (2011); Warren C., Netflix Heading to Europe in 2012 [Report], Mashable, (2011); Wingfield N., Netflix Market Value Shrivels, NYTimes.com:Bits, (2011); Wingfield N., Postal Service Cutbacks Add New Light to Netflix Saga, NYTimes.com:Bits, (2011); Wingfield N., Stelter B., How Netflix Lost 800,000 Members, and Good Will, The New York Times Reprints, (2011); Historical Prices",null,null,"Allied Academies",{"$nulls":5},1.078495E7,null,null,null,"English","J. Int. Acad. Case Stud.","Article","Final",null,"Scopus","2-s2.0-84930451201"]
["Niraj S.; Nageswara Rao S.V.D.","Niraj, S. (57189505445); Nageswara Rao, S.V.D. (56576232900)","57189505445; 56576232900","Inorganic growth only route to achieve economies of scale for Indian E-retailers",2015.0,"Journal of Internet Banking and Commerce",1.0,null,4.0,null,null,7.0,0.0,"10.4172/1204-5357.S2-004","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85000351015&doi=10.4172%2f1204-5357.S2-004&partnerID=40&md5=6c2ab221417c5f7093a4ffc61a281ee7","Shailesh J. Mehta School of Management (SJMSOM), IIT Bombay, Maharashtra, India","Niraj S., Shailesh J. Mehta School of Management (SJMSOM), IIT Bombay, Maharashtra, India; Nageswara Rao S.V.D., Shailesh J. Mehta School of Management (SJMSOM), IIT Bombay, Maharashtra, India","Indian e-retail market has come a long way since inception of leading player, Flipkart, in 2007. The market has tremendous opportunity to grow due to fact that the current penetration of e-retail in overall retail is significantly low and penetration of internet in India is also significantly low. Rising penetration of internet, coupled with increasing use of smartphone, computers will attract the consumers to the online channel. However, price differentiation from traditional retail, offered in the form of discounts by e-retailers will remain the key driver of the growth. Based on a survey it is found that majority of the people will switch back to traditional way of shopping as the look and feel of product is generally not available in online channel despite the benefits provided such as wider portfolio, easy delivery, easy return, convenience, etc. Consumers find discounts and offers as the primary reason for the change in consumer behaviour and shift of channel. On the other hand, the e-retail companies cannot afford to sell the products at heavy discounts as it leads to diseconomies of scale where companies incur heavy investment in logistics and technology and also offer discounts to generate volume. Amidst this, the in-organic style of growth will be an ideal strategy for companies to grow. Growth by mergers and acquisitions (including all forms like forward, backward, or parallel integration) will not only help the company diversify its product portfolio but will also give the companies an upper edge to save on customer acquisition cost, logistic lost, infrastructure development cost, and technology cost. Leading global players like Amazon Inc. adopted a similar strategy to grow in the international market. Amazon Inc. which is one of the leading players in the e-Commerce market acquired 57 companies since 1998 to clock revenue of around USD 89 billion in the year 2014 while its major rival eBay Inc. could reach USD 18 billion in 2014 with 3 acquisitions since 1998. This article covers if a similar paradigm will be seen in the Indian economy too, where the indigenous companies will re-look at their strategies in order to be profitable in the dynamically changing, fastest growing e-Commerce market of India. An early adoption of in-organic growth to scale up operations in the geographically diversified and huge economy like India will only help these players become profitable. Absence of right strategy mix will result in players bleeding and the bubble will eventually burst. © 2015 Niraj S, et al.","Acquisitions; E-commerce; E-retail; Economies of scale; Global players; Inorganic growth; Strategy; Volume",{"$nulls":7},"Sassen S., Electronic space and power, Journal of Urban Technology, 4, pp. 1-17, (1997); Prithiani R., Satnalika N., Retail business models transforming to survive e-Commerce threat, CRISIL Opinion, (2015); Gereffi G., Shifting governance structures in global commodity chains, with special reference to the Internet, American Behavioural Scientist, 44, pp. 1616-1637, (2001); Esper T., Jensen T., Turnipseed F., Burton S., The last mile: An examination of effects of online retail delivery strategies on consumers, Journal of Business Logistics, 24, pp. 177-203, (2003); Alba J., Lynch J.J., Weitz B., Janiszewski C., Lutz R., Et al., Interactive home shopping: Consumer, retailer, and manufacturer incentives to participate in electronic marketplaces, Journal of Marketing, 61, pp. 38-53, (1997); De Koster R., Distribution strategies for online retailers, IEEE Transactions on Engineering Management, 50, pp. 448-457, (2003); Grewal D., Iyer G., Levy M., Internet retailing: Enablers, limiters and market consequences, J Bus Res, 57, pp. 703-713, (2004); Lee H.L., Whang S., Winning the last mile of E-commerce, Sloan Management Review, 42, pp. 54-62, (2001); Boyer K.K., Hult G., Extending the supply chain - Integrating operations and marketing in the grocery industry, Journal of Operations Management, 23, pp. 642-661, (2005); Ricker F.R., Kalakota R., Order fulfilment: The hidden key to e-Commerce success, Supply Chain Management Review, 11, pp. 60-70, (1999); Rabinovich E., Bailey J.P., Physical distribution service quality in Internet retailing: Service pricing, transaction attributes, and firm attributes, Journal of Operations Management, 21, pp. 651-672, (2004); Clark G.L., Wrigley N., Exit, the firm and sunk costs: Reconceptualising the corporate geography of disinvestment and plant closure, Progress in Human Geography, 21, pp. 338-358, (1997); Leyshon A., Time-space (And digital) compression: Software formats, musical networks and the reorganization of the music industry, Environment and Planning, 33, pp. 49-77, (2001); Rosen K.T., Howard A.L., E-retail: Gold rush or fool’s gold?, California Management Review, 42, pp. 72-100, (2000); Ring L.J., Tigert D.J., The decline and fall of internet grocery retailers, International Journal of Retail and Distribution Management, 28, pp. 417-444, (2001); Thornton J., Marche S., Sorting through the dot bomb rubble: How did the high-profile e-tailers fail?, International Journal of Information Management, 35, pp. 121-138, (2003); Wrigley N., Lowe M.S., Currah A.D., Progress report 2: Retailing and e-tailing, Urban Geography, 23, pp. 180-197, (2002); Murphy A., The Web, the Grocer and the City, pp. 226-230, (2004); Lindholm A., An Economic System of Technology-Related Acquisitions and Spin-Offs, (1996); Dahlstrand A.L., Growth and inventiveness in technology-based spin-off firms, Res. Policy, 26, pp. 331-344, (1997); Baumol W.J., Entrepreneurship, innovation and growth: The David-Goliath symbiosis, J. Entrepreneurial Finance, 7, pp. 1-10, (2002); Stigler G.J., Monopoly and oligopoly by merger, Am Econ Rev, 40, pp. 23-34, (1950); Granstrand O., Sjolander S., The acquisition of technology and small firms by large firms, J Econ Behav Organ, 13, pp. 367-386, (1990); Hall B.H., The Effect of Takeover Activity on Corporate Research and Development, (1987); Williamson O.E., Markets and Hierarchies: Analysis and Antitrust Implications, (1975); Bonardo D., Paleari S., Vismara S., The M&A dynamics of European science-based entrepreneurial firms, J Technol Transf, 35, pp. 141-180, (2010); Ahmetoglu G., Furnham A., Fagan P., Pricing practices: A critical review of their effects on consumer perceptions and behavior, J Retail Consum Serv, 21, pp. 696-707, (2014); Sotgiu F., Ancarani F., Exploiting the opportunities of internet and multichannel pricing: An exploratory research, J Prod Brand Manag, 13, pp. 125-136, (2004); Wolk A., Ebling C., Multi-channel price differentiation: An empirical investigation of existence and causes, Int J Res Mark, 27, pp. 142-150, (2010); Paul M., Beckmann J., Channel-based Price Differentiation: Does it Affect Customer Retention and is it Feasible for Mobile Communications Retailers?, American Marketing Association Conference, 23, pp. 133-139, (2012); Darke P., Dahl D., Fairness and discounts: The subjective value of a bargain, J Consum Psychol, 13, pp. 328-338, (2003); Anderson E.T., Simester D.I., Research note-does demand fall when customers perceive that prices are unfair? The case of premium pricing for large sizes, Mark Sci, 27, pp. 492-500, (2008); Wu C.C., Liu Y.F., Chen Y.J., Wang C.J., Consumer responses to price discrimination: Discriminating bases, inequality status, and information disclosure timing influences, J Bus Res, 65, pp. 106-116, (2012); Choi S., Mattila A.S., Perceived fairness of price differences across channels: The moderating role of price frame and norm perceptions, J Mark Theory Pract, 17, pp. 37-47, (2009); Anderson E., Day G.S., Rangan V.K., Strategic channel design, Sloan Manag Rev, 38, pp. 59-69, (1997); Ratchford B.T., Online pricing: Review and directions for research, J Interact Mark, 23, pp. 82-90, (2009); Zhang J., Farris P.W., Irvin J.W., Kushwaha T., Steenburgh T.J., Et al., Crafting Integrated Multichannel Retailing Strategies, J Interact Mark, 24, pp. 168-180, (2010); Jensen T., Kees J., Burton S., Turnipseed F.L., Advertised reference prices in an internet environment: Effects on consumer price perceptions and channel search intentions, J Interact Mark, 17, pp. 20-33, (2003); Mandelker G., Risk and return: The case of merging firms, Journal of Financial Economics, 1, pp. 303-335, (1974); Jensen M.C., Ruback R., The market for corporate control: The scientific evidence, Journal of Financial Economics, 11, pp. 5-50, (1983); Kim E.H., Singal V., Mergers and market power: Evidence from the airline industry, American Economic Review, 83, pp. 549-569, (1993); McGuckin R.H., Nguyen S.V., On productivity and plant ownership change: New evidence from the Longitudinal Research Database, Rand Journal of Economics, 26, pp. 257-276, (1995); King D.R., Slotegraaf R.J., Kesner I., Performance implications of firm resource interactions in the acquisition of R&D-intensive firms, Organization Science, 19, pp. 327-340, (2008); Williamson O.E., The Economic Institutions of Capitalism, (1985); Casciaro T., Piskorski M.J., Power imbalance, mutual dependence, and constraint absorption: A close look at resource dependence theory, Administrative Science Quarterly, 50, pp. 167-199, (2005); Pfeffer J., Merger as a response to organizational interdependence, Administrative Science Quarterly, 17, pp. 382-394, (1972); Meyer K.E., Estrin S., Bhaumik S., Peng M.W., Institutions, resources & entry strategies in emerging economies, Strategic Management Journal, 30, pp. 61-80, (2009); Meyer K.E., Estrin S., Bhaumik S., Peng M.W., Company Reports from Securities and Exchange Commission and Registrar of Companies, (2015); Srinvasan A., Rajde S., Satnalika N., It’s advantage customers as E-Com players play the price game, CRISIL Opinion, (2014); Prithiani R., Lodha M., Satnalika N., E-tail eats into retail, CRISIL Opinion, (2014)","S. Niraj; Shailesh J. Mehta School of Management (SJMSOM), IIT Bombay, India; email: m.safari@ut.ac.ir",null,"ARRAY Development (Canada) Inc.",{"$nulls":5},1.2045357E7,null,null,null,"English","J. Internet Bank. Commer.","Article","Final","All Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-85000351015"]
["Razmi J.; Hassani A.; Babazadeh R.","Razmi, Jafar (58034876600); Hassani, Anis (57200194667); Babazadeh, Reza (55154890000)","58034876600; 57200194667; 55154890000","A hybrid fuzzy bi-objective delivery planning model for leagile e-tailing under uncertainty",2015.0,"International Journal of Management Science and Engineering Management",10.0,1.0,null,62.0,72.0,10.0,5.0,"10.1080/17509653.2014.962110","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85017090416&doi=10.1080%2f17509653.2014.962110&partnerID=40&md5=9468456e7e8b81d4ded5057616de97b8","School of Industrial and Systems Engineering, College of Engineering, University of Tehran, P.O. Box 11155-45632, Tehran, Iran","Razmi J., School of Industrial and Systems Engineering, College of Engineering, University of Tehran, P.O. Box 11155-45632, Tehran, Iran; Hassani A., School of Industrial and Systems Engineering, College of Engineering, University of Tehran, P.O. Box 11155-45632, Tehran, Iran; Babazadeh R., School of Industrial and Systems Engineering, College of Engineering, University of Tehran, P.O. Box 11155-45632, Tehran, Iran","The rapid growth of e-business has paved the way for traditional retailers to distribute their items via the Internet. The success of online retailers (e-tailers) in the extremely competitive online marketplace depends on providing a beneficial and efficient scheme for customers' orders fulfillment. In this paper, a joint model of pricing and online fulfillment assignment is presented for a distribution system in which a supplier sells items through an e-tail channel under the possibility of using substitute items with the satisfaction of customers' demands and delivery times. The aim of the model is to be ‘lean’ by minimizing operational cost and ‘agile’ through providing quick simultaneous reactions to market changes. We present a hybrid fuzzy bi-objective nonlinear programming model which is composed of a qualitative objective related to customers' satisfaction and a quantitative objective function, i.e. the maximization of revenue minus the total cost. After applying an appropriate strategy to defuzzify the model, the equivalent bi-objective crisp model is solved by an interactive fuzzy goal programming method to handle goals as well as their imprecise target levels simultaneously in order to find an efficient compromise solution. Moreover, an illustrative example is provided in order to prove the usefulness and efficiency of the proposed model and the solution approach. © 2014 International Society of Management Science and Engineering Management.","delivery planning; leagile; online retailer; optimization method; pricing; uncertainty",{"$nulls":5},"Iran National Science Foundation, INSF","We would like to express our appreciation to the Iran National Science Foundation (INSF) for financial support of this study.","Agatz N.A.H., Fleischmann M., Van Nunen J.A.E.E., E-fulfillment and multi-channel distribution–a review, European Journal of Operational Research, 187, pp. 339-356, (2008); Babazadeh R., Razmi J., A robust stochastic programming approach for agile and responsive logistics under operational and disruption risks, Logistics Systems and Management, 13, pp. 458-482, (2012); Becerril-Arreola R., Leng M., Parlar M., Online retailers' promotional pricing, free-shipping threshold, and inventory decisions: A simulation-based analysis, European Journal of Operational Research, 2, pp. 272-283, (2013); Bretthauer K.M., Mahar S., Venakataramanan M.A., Inventory and distribution strategies for retail/e-tail organizations, Computers & Industrial Engineering, 58, pp. 119-132, (2010); Chen L.H., Tsai F.C., Fuzzy goal programming with different importance and priorities, European Journal of Operational Research, 133, pp. 548-556, (2001); Christiansen P.E., Kotzab H., Mikkola J.H., Coordination and sharing logistics information in leagile supply chains, Procurement Management, 1, pp. 79-96, (2007); GhasemyYaghin R., Torabi S.A., FatemiGhomi S.M.T., Integrated markdown pricing and aggregate production planning in a two echelon supply chain: A hybrid fuzzy multiple objective approach, Applied Mathematical Modelling, 36, pp. 6011-6030, (2012); Goldsby T.J., Griffis S.E., Roath A.S., Modeling lean, agile, and leagile supply chain strategies, Business Logistics, 27, pp. 57-80, (2006); Hannan E.L., Linear programming with multiple fuzzy goals, Fuzzy Sets and Systems, 6, pp. 235-248, (1981); Hsu C.I., Li H.C., Optimal delivery service strategy for Internet shopping with time-dependent consumer demand, Transportation Research, 42, pp. 473-497, (2006); Inuiguchi M., Ramik J., Possibilistic linear programming: A brief review of fuzzy mathematical programming and a comparison with stochastic programming in portfolio selection problem, Fuzzy Sets and Systems, 111, pp. 3-28, (2000); Jamalnia A., Soukhakian M.A., A hybrid fuzzy goal programming approach with different goal priorities to aggregate production planning, Computers & Industrial Engineering, 56, pp. 1474-1486, (2009); Jimenez M., Arenas M., Bilbao A., Rodriguez M.V., Linear programming with fuzzy parameters: An interactive method resolution, European Journal of Operational Research, 177, pp. 1599-1609, (2007); Johansson H.J., McHugh P., Pendlebury A.J., Wheeler W.A., Business Process Reengineering: Breaking Strategies for Market Dominance, (1993); Li L., Lai K.K., Fuzzy dynamic programming approach to hybrid multi objective multi stage decision making problems, Fuzzy Sets and Systems, 117, pp. 13-25, (2001); Liu F.O., Price or proficiency? A household production explanation on consumers' choice of online retailer, Journal of Business and Economics, 4, pp. 1247-1264, (2013); Lo S.K., Chou Y.J., Teng C.I., Source effect of advertised reference price influences on transaction value in online shopping environments, Electronic Commerce Research, 4, pp. 411-421, (2013); Mason-Jones R., Naylor B., Towill D.R., Lean, agile or leagile? Matching your supply chain to the marketplace, International Journal of Production Research, 38, pp. 4061-4070, (2010); Min H., Ko C.S., Ko H.J., Managing product returns in customer-centric e-tail environments, Services Technology and Management, 9, pp. 51-70, (2008); Mohebbi S., Shafaei R., e-Supply network coordination: The design of intelligent agents for buyer–supplier dynamic negotiations, Journal of Intelligent Manufacturing, 23, pp. 375-391, (2012); Mula J., Poler R., Garcia J.P., MRP with flexible constraints: A fuzzy mathematical programming approach, Fuzzy Sets and Systems, 157, pp. 74-97, (2006); Narasimhan R., Goal programming in a fuzzy environment, Decision Sciences, 11, pp. 325-336, (1980); Okongwu U., Laurasab M., Dupont L., Humez V., A decision support system for optimising the order fulfilment process, Production Planning & Control, 8, pp. 581-598, (2012); Parra M.A., Terol A.B., Gladish B.P., Rodriguez M.V., Solving a multi objective possibilistic problem through compromise programming, European Journal of Operational Research, 164, pp. 748-759, (2005); Tagaras G., Effects of pooling in two-location inventory systems, IEE Transactions, 21, pp. 250-257, (1989); Watada J., Fuzzy portfolio selection and its applications to decision making, Tatra Mountains Mathematics Publication, 13, pp. 219-248, (1997); Yan T., Rabinovich E., Dooley K., Evers P.T., Managing backlog variation in order fulfillment: The case of Internet retailers, Production Economics, 128, pp. 261-268, (2010); Zadeh L.A., Fuzzy sets, Information and Control, 8, pp. 338-353, (1965); Zimmermen H.J., Description and optimization of fuzzy sets, International Journal of General Systems, 2, pp. 209-215, (1976); Zimmermen H.J., Fuzzy programming and linear programming with several objective functions, Fuzzy Sets and Systems, 1, pp. 45-56, (1978)","R. Babazadeh; School of Industrial and Systems Engineering, College of Engineering, University of Tehran, Tehran, P.O. Box 11155-45632, Iran; email: r.babazadeh@ut.ac.ir",null,"Taylor and Francis Ltd.",{"$nulls":5},1.7509653E7,null,null,null,"English","Int. J. Manage. Sci. Eng. Manage.","Article","Final",null,"Scopus","2-s2.0-85017090416"]
["Cepolina E.M.; Farina A.","Cepolina, Elvezia M. (55957475100); Farina, Alessandro (36655661000)","55957475100; 36655661000","A new urban freight distribution scheme and an optimization methodology for reducing its overall cost",2015.0,"European Transport Research Review",7.0,1.0,null,null,null,14.0,24.0,"10.1007/s12544-014-0149-x","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84921847471&doi=10.1007%2fs12544-014-0149-x&partnerID=40&md5=f5644bd27119450f319e2e8b12cae4c9","Department of Civil and Industrial Engineering, University of Pisa, Pisa, Italy","Cepolina E.M., Department of Civil and Industrial Engineering, University of Pisa, Pisa, Italy; Farina A., Department of Civil and Industrial Engineering, University of Pisa, Pisa, Italy","Purpose: The paper refers to an innovative urban freight distribution scheme, aimed at reducing the externalities connected with the freight delivery process. Both packages destined to commercial activities and to end consumers (e-commerce) are taken into account. Each package is characterized by an address and dimensions. In the proposed transport system, freight is firstly delivered to the UDC on the border of urban areas through trucks or trains which perform the long distance transport. After, freight is reorganized and consolidated into load units, i.e. the FURBOT boxes, according to packages dimensions and to the addresses of receivers. Each box is addressed to a temporary unloading bay and it is delivered there by a FURBOT vehicle. The receivers are in charge of collecting their packages in the related unloading bays where they have been delivered.; Methods and results: The paper concerns a methodology for optimizing this freight transport system’s performances. The overall methodology receives in input the actual freight demand and the road network, and finds the transport system parameters (number of required FURBOT boxes, their temporary unloading bay, the FURBOT fleet dimension and the FURBOT vehicle routing) that minimize the system overall cost. The overall cost is a sum of the users’ cost, which depends on the distance they have to walk for collecting their packages in the FURBOT box, and of the operator’s cost, which depends on the number of required boxes, the total distance travelled by the FURBOT vehicles and the required number of FURBOT vehicles.; Application: The overall procedure has been applied to the case study of Barreiro old town, a suburb of Lisbon, Portugal. © 2015, The Author(s).","Capacitated vehicle routing problem; E-commerce; Fuzzy k-means clustering; Genetic algorithms; Urban freight distribution","Electronic commerce; Fleet operations; Freight transportation; Genetic algorithms; K-means clustering; Traffic control; Unloading; Urban transportation; Vehicle routing; Vehicles; Capacitated vehicle routing problem; Freight deliveries; Freight transport systems; Fuzzy K means clustering; Long-distance transport; Optimization methodology; Transport systems; Urban freight distribution; Costs",{"$nulls":4},"European Commission; European Commission, EC, (FP7-SST-2011-RTD-1)","The research has been carried out within the FURBOT project funded by the European commission [FP7-SST-2011-RTD-1].","Cepolina E.M., A methodology for defining building evacuation routes, Civ Eng Environ Syst, 22, 1, pp. 29-47, (2005); Cepolina E.M., Farina A., An optimization methodology for the consolidation of urban freight boxes. Proc HMS2013, Athens, September, pp. 25-27, (2013); Dablanc L., Goods transport in large European cities: difficult to organize, difficult to modernize, Transport Res A-Pol, 41, 3, pp. 280-285, (2007); Dablanc L., Dizian D., Levifve H., Urban freight consultations in the Paris region, Eur Transp Res Rev, 3, pp. 47-57, (2011); Dinale A., Molfino R., Huang P., Athens, September, pp. 25-27, (2013); Gonzales-Feliu J., Salanova J.M., Defining and evaluating collaborative urban freight transportation systems, Procedia Soc Behav Sci, 39, pp. 172-183, (2012); Gonzales-Feliu J., Morana J., Salanova J.M., Ma T.Y., Design and scenario assessment for collaborative logistics and freight transport systems, Int J Transp Econ, 40, 2, pp. 207-240, (2013); Hoppner F., Klawonn F., Clustering with size constraints, Computational intelligence paradigms, (2008); Klawonn F., Hoeppner F., Equi-sized, homogeneous partitioning, Knowledge-based intelligent information and engineering systems, part II, pp. 70-77, (2006); Laarhoven J.M., Aarts E.H.L., Simulated annealing: theory and applications, (1987); A novel robotic handling device integrated on a freight urban robotic vehicle; Park M., Regan A., Issues in emerging home delivery operations, UC Berkeley: Univ of California Transportation Center, (2004); Ren C.E.N., Applying genetic algorithm for capacitated vehicle routing problem. Proc of EMEIT-2012, Shenyang (China), September, pp. 7-9, (2012); Shimamoto H., Murayama N., Fujiwara A., Zhang J., Evaluation of an existing bus network using a transit network optimisation model: a case study of the Hiroshima City Bus network, Transportation, 37, 5, pp. 801-823, (2010); Toth P., Vigo D., The vehicle routing problem, (2002); Yao X., Simulated annealing with extended neighbourhood, Int J Comput Math, 40, pp. 169-189, (1991); Yao X., Dynamic neighbourhood size in simulated annealing, Proc. of Int Joint Conference on Neural Networks, Beijing, November 3–6. Vol.1, IEEE Press, Piscataway, NJ, pp. 411-416, (1992); Zheng Y., Dalian (China), October, pp. 12-14, (2014); Population diversity in genetic algorithm for vehicle routing problem with time windows; Zhu S., Wang D., Li T., Data clustering with size constraints, Knowl-Based Syst, 23, 8, pp. 883-889, (2010); CityLog project website; Eurostat; Furbot project website","E.M. Cepolina; Department of Civil and Industrial Engineering, University of Pisa, Pisa, Italy; email: elvezia.cepolina@dic.unipi.it",null,"Springer Verlag",{"$nulls":5},1.8670717E7,null,null,null,"English","Eur. Transp. Res. Rev.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-84921847471"]
["Aichner T.; Coletti P.","Aichner, Thomas (36650466300); Coletti, Paolo (55490661200)","36650466300; 55490661200","Customers' online shopping preferences in mass customization",2013.0,"Journal of Direct, Data and Digital Marketing Practice",15.0,1.0,null,20.0,35.0,15.0,23.0,"10.1057/dddmp.2013.34","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84886655762&doi=10.1057%2fdddmp.2013.34&partnerID=40&md5=bd0d99f99f1c2f4fd33ea380e191b351","Department of Management and Engineering, University of Padova, Italy; School of Economics and Management, Free University of Bozen Bolzano, 39100 Bozen-Bolzano, Universitätsplatz 1, Italy","Aichner T., Department of Management and Engineering, University of Padova, Italy; Coletti P., School of Economics and Management, Free University of Bozen Bolzano, 39100 Bozen-Bolzano, Universitätsplatz 1, Italy","Mass customization has become important to business because of the difficulties for customers in finding what they want despite an increase in product variety for many categories over the past decades. The emergence of modern technologies in production and communication, however, allows companies to offer customised products and services without relinquishing economies of scale. The advent of web interfaces has finally given the opportunity to achieve completely the involvement of the customer in the product's entire design process. The results of our survey on more than 500 European customers show a declining willingness of customers to compromise on the issue of suitability of products to their personal needs and preferences, the possibility for companies to break brand loyalty through mass customization and the influence of immediate availability, delivery time and price on the customer's willingness to take part in the co-creation process of products. © 2013 Macmillan Publishers Ltd.","customer survey; electronic commerce; mass customization; mass customization marketing; product personalisation",{"$nulls":7},"Pine I.I.B.J., Victor B., Boynton A., Making mass customisation work, Harvard Business Review, 71, 5, pp. 108-119, (1993); Davis S.M., From future perfect: Mass customizing, Strategy & Leadership, 17, 2, pp. 16-21, (1989); Merle A., Chandon J.L., Roux E., Alizon F., Perceived value of the mass-customised product and mass customisation experience for individual consumers, Production and Operations Management, 19, 5, pp. 503-514, (2010); Bock S., Using distributed search methods for balancing mixed-model assembly lines in the automotive industry, OR Spectrum, 30, 3, pp. 551-578, (2008); Clymer F., Treasury of Early American Automobiles, pp. 1877-1925, (1950); Cox M.W., Aim R., The Right Stuff: America's Move to Mass Customisation, (1998); Moser K., Mass Customisation Strategies-Development of A Competence-based Framework for Identifying Different Mass Customisation Strategies, (2007); Lampel J., Mintzberg H., Customising customization, Sloan Management Review, 38, 1, pp. 21-30, (1996); Kaplan A.M., Haenlein M., Toward a parsimonious definition of traditional and electronic mass customization, Journal of Product Innovation Management, 23, 2, pp. 168-182, (2006); Fogliatto F.S., Da Silveira G.J.C., Royer R., Flexibility-driven index for measuring mass customisation feasibility on industrialised products, International Journal of Production Research, 41, 8, pp. 1811-1829, (2003); Hart C.W.L., Mass customisation: Conceptual underpinnings, opportunities and limits, International Journal of Service Industry Management, 6, 2, pp. 36-45, (1995); Lau R., Mass customisation: The next industrial revolution, Industrial Management, 37, 9-10, pp. 18-19, (1995); Lee C.H.S., Baraa A., Whinston A.B., The complementarity of mass customisation and electronic commerce, Economics of Innovation and New Technology, 9, 2, pp. 81-109, (2000); Turowski K., Agent-based e-commerce in case of mass customization, International Journal of Production Economics, 75, 1-2, pp. 69-81, (2002); Fogliatto F.S., Da Silveira G.J.C., Borenstein D., The mass customisation decade: An updated review of the literature, International Journal of Production Economics, 138, 1, pp. 14-25, (2012); Fiirstner I., Anisic Z., Takacs M., Product configurator self-adapting to different levels of customer knowledge, Acta Polytechnica Hungarica, 9, 4, pp. 129-150, (2012); Gourville J.T., Soman D., Overchoice and assortment type: When and why variety backfires, Marketing Science, 24, 3, pp. 382-395, (2005); Trentin A., Perin E., Forza C., Avoiding the variety paradox through product configurators, Proceedings of the 5th International Conference on Mass Customisation and Personalisation in Central Europe, pp. 252-260, (2012); Franke N., Schreier M., Kaiser U., The \"i designed it myself effect\" in mass customization, Management Science, 56, 1, pp. 125-140, (2010); Dellaert B.G.C., Dabholkar P.A., Increasing the attractiveness of mass customization: The role of complementary on-line services and range of options, International Journal of Electronic Commerce, 13, 3, pp. 43-70, (2009); Choi S.Y., Stahl D.O., Whinston A.B., The Economics of Electronic Commerce, (1997); Frischmann T., Hinz O., Skiera B., Retailers' use of shipping costs strategies: Free shipping or partitioned prices?, International Journal of Electronic Commerce, 16, 3, pp. 65-87, (2012); Starkey A., E-Retail-Using home delivery as a service differentiator and strategic marketing tool, Journal of Direct, Data and Digital Marketing Practice, 12, 2, pp. 165-173, (2010); Stores Can Be Ultimate Merchandise Lockers for Shoppers Looking to Avoid Online Purchase Delivery Hassles, (2012); Songlin C., Mitchell M.T., Aligning demand and supply flexibility in custom product co-design, International Journal of Flexible Manufacturing Systems, 19, 4, pp. 596-611, (1998); Bardakci A., Whitelock J., Mass-customisation in marketing: The consumer perspective, Journal of Consumer Marketing, 20, 5, pp. 463-479, (2003); Ganesh J., Reynolds K.E., Luckett M., Pomirleanu N., Online shopper motivations, and e-store attributes: An examination of online patronage behavior and shopper typologies, Journal of Retailing, 86, 1, pp. 106-115, (2010); Loginova O., Brand familiarity and product knowledge in customization, International Journal of Economic Theory, 6, 3, pp. 297-309, (2010); Huang C.Y., Excess loyalty in online retailing, International Journal of Electronic Commerce, 16, 2, pp. 115-133, (2011); Franke N., Schreier M., Product uniqueness as a driver of customer utility in mass customization, Marketing Letters, 19, 2, pp. 93-107, (2008); Pine I.I.B.J., Mass Customisation: The New Frontier in Business Competition, (1993); Fiore A., Lee S.E., Kunz G., Campell J., Relationships between optimum stimulation level and willingness to use mass customisation options, Journal of Fashion Marketing and Management, 5, 2, pp. 99-107, (2001); Reichwald R., Piller F.T., Interaktive Wertschopfung: Open Innovation, Individualisierung und Neue Formen der Arbeitsteilung, (2006); Franke N., Piller F., Toolkits for user innovation and design: An exploration of user interaction and value creation, Journal of Product Innovation Management, 21, 6, pp. 401-415, (2004); Schreier M., The value increment of mass-customised products: An empirical assessment, Journal of Consumer Behavior, 5, 4, pp. 317-327, (2006); Shen A., Ball A.D., How do customers evaluate mass-customised products?, Proceedings of the Summer American Marketing Association Conference, pp. 388-389, (2006); Glover S., Benbasat I., A comprehensive model of perceived risk of e-commerce transactions, International Journal of Electronic Commerce, 15, 2, pp. 47-78, (2010); McKenna R., Marketing in the age of diversity, Harvard Business Review, 66, 5, pp. 88-95, (1988); Peppers D., Rogers M., Enterprise One-to-One: Tools for Competing in the Interactive Age, (1999); Pine I.I.B.J., Peppers D., Rogers M., Do you want to keep your customers forever?, Harvard Business Review, 73, 2, pp. 103-114, (1995); Ansari A., Mela C.F., E-customisation, Journal of Marketing Research, 40, 2, pp. 131-145, (2003); Simonson I., Determinants of customers' responses to customised offers: Conceptual framework and research propositions, Journal of Marketing, 69, 1, pp. 32-45, (2005)",{"$nulls":8},1.7460174E7,null,null,null,"English","J. Dir. Data Digit. Mark. Pract.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-84886655762"]
["Ma J.; Qin Y.","Ma, Jingyi (57189347329); Qin, Ye (57189347406)","57189347329; 57189347406","Scale planning of logistics node in the context of modern commerce electronics",2015.0,"International Journal of Simulation: Systems, Science and Technology",16.0,"4B",null,"2024-01-19","2024-05-19",null,0.0,"10.2013/IJSSST.a.16.4B.19","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84969540655&doi=10.2013%2fIJSSST.a.16.4B.19&partnerID=40&md5=469e5787aae8605642a27d04c4183ee6","Inner Mongolia Agricultural University, Huhhot, 010018, Inner Mongolia, China","Ma J., Inner Mongolia Agricultural University, Huhhot, 010018, Inner Mongolia, China; Qin Y., Inner Mongolia Agricultural University, Huhhot, 010018, Inner Mongolia, China","With the rapid development of electronic commerce, to domestic electric business logistics industry have brought enormous development opportunities, but also the scale of logistics node of electric business logistics have been put forward more advanced requests. High logistics costs, low efficiency of logistics and distribution, logistics, cargo damage and high quality of service to the poor seriously affected the rapid development of e-commerce, how in the modern e-commerce background to the scale of logistics nodes were planning numerous electronic business platform has become the bottleneck solved issues. This paper describes the current situation and existing problems of the current scale planning of Logistics node, carries on an in-depth discussion in terms of the total scale of city logistics node and the distributional issues of scale, and comes out certain methods, which Provides certain Theoretical references for the work of Related fields in the planning of city Logistics. © 2015, UK Simulation Society. All right reserved.","E-Commerce; Electronic commerce; Logistics nodes; Scale logistics planning","Electric automobiles; Electronic commerce; Quality of service; Business logistics; Cargo damage; City logistics; Current situation; Electronic business; Existing problems; Logistics costs; Logistics planning; Commerce",{"$nulls":6},"Ozdamar L., Demir O., A hierarchical clustering and routing procedure for large scale disaster relief logistics planning, Transportation Research Part E: Logistics and Transportation Review, 48, 3, pp. 591-602, (2012); Li L., Tang S., An artificial emergency-logistics-planning system for severe disasters, Intelligent Systems, IEEE, 23, 4, pp. 86-88, (2008); Taniguchi E., Noritake M., Yamada T., Et al., Optimal size and location planning of public logistics terminals, Transportation Research Part E: Logistics and Transportation Review, 35, 3, pp. 207-222, (1999); Ben-Tal A., Do Chung B., Mandala S.R., Et al., Robust optimization for emergency logistics planning: Risk mitigation in humanitarian relief supply chains, Transportation Research Part B: Methodological, 45, 8, pp. 1177-1189, (2011); Shih L.H., Reverse logistics system planning for recycling electrical appliances and computers in Taiwan, Resources, Conservation and Recycling, 32, 1, pp. 55-72, (2001); Chang M.S., Tseng Y.L., Chen J.W., A scenario planning approach for the flood emergency logistics preparation problem under uncertainty, Transportation Research Part E: Logistics and Transportation Review, 43, 6, pp. 737-754, (2007); Vidal C.J., Goetschalckx M., Strategic production-distribution models: A critical review with emphasis on global supply chain models, European Journal of Operational Research, 98, 1, pp. 1-18, (1997); Sear T.N., Logistics planning in the downstream oil industry, Journal of the Operational Research Society, 9, 9, pp. 9-17, (1993); Awasthi A., Chauhan S.S., A hybrid approach integrating Affinity Diagram, AHP and fuzzy TOPSIS for sustainable city logistics planning, Applied Mathematical Modelling, 36, 2, pp. 573-584, (2012); Dempster M., Pedron N.H., Medova E.A., Et al., Planning logistics operations in the oil industry, Journal of the Operational Research Society, 8, 7, pp. 1271-1288, (2000); Geoffrion A.M., A priori error bounds for procurement commodity aggregation in logistics planning models, Naval Research Logistics Quarterly, 24, 72, pp. 201-212, (1977); Allen J., Browne M., Hunter A., Et al., Logistics management and costs of biomass fuel supply, International Journal of Physical Distribution & Logistics Management, 28, 6, pp. 463-477, (1998); Simroth A., Zahle H., Travel time prediction using floating car data applied to logistics planning, Intelligent Transportation Systems, IEEE Transactions On, 12, 1, pp. 243-253, (2011); Wang Z., Yang D.Y., Study on logistics park planning, Systems Engineering, 1, 9, (2001); Zinn W., Bowersox D.J., Planning physical distribution with the principle of postponement, Journal of Business Logistics, 9, 2, pp. 78-85, (1988); Schmid H.A., Rossi G., Modeling and designing processes in ecommerce applications, Internet Computing, IEEE, 8, 1, pp. 19-27, (2004)",null,null,"UK Simulation Society",{"$nulls":5},1.4738031E7,null,null,null,"English","Int. J. Simul. Syst. Sci. Technol.","Article","Final",null,"Scopus","2-s2.0-84969540655"]
["Deng S.; Li Y.; Guo H.; Liu B.","Deng, Shuai (50561290900); Li, Yanhui (56040405100); Guo, Hao (57190736884); Liu, Bailing (56065758500)","50561290900; 56040405100; 57190736884; 56065758500","Solving a Closed-Loop Location-Inventory-Routing Problem with Mixed Quality Defects Returns in E-Commerce by Hybrid Ant Colony Optimization Algorithm",2016.0,"Discrete Dynamics in Nature and Society",2016.0,null,6467812.0,null,null,null,28.0,"10.1155/2016/6467812","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84982856719&doi=10.1155%2f2016%2f6467812&partnerID=40&md5=4ae9634e60e8aa198b360989f3589e0c","School of Information Management, Central China Normal University, Wuhan, 430079, China; School of Economic Management, Hunan Institute of Technology, Hengyang, 421001, China","Deng S., School of Information Management, Central China Normal University, Wuhan, 430079, China, School of Economic Management, Hunan Institute of Technology, Hengyang, 421001, China; Li Y., School of Information Management, Central China Normal University, Wuhan, 430079, China; Guo H., School of Information Management, Central China Normal University, Wuhan, 430079, China; Liu B., School of Information Management, Central China Normal University, Wuhan, 430079, China","This paper presents a closed-loop location-inventory-routing problem model considering both quality defect returns and nondefect returns in e-commerce supply chain system. The objective is to minimize the total cost produced in both forward and reverse logistics networks. We propose a combined optimization algorithm named hybrid ant colony optimization algorithm (HACO) to address this model that is an NP-hard problem. Our experimental results show that the proposed HACO is considerably efficient and effective in solving this model. © 2016 Shuai Deng et al.",{"$nulls":8},"Ecommerce Sales Worldwide Reach $1. 471 Trillion in 2014; Mostard J., Teunter R., Thenewsboyproblemwithresalable returns: A single periodmodel and case study, European Journal of Operational Research, 169, 1, pp. 81-96, (2006); Zeng F., Chi Y., Zheng J., The newsvendor problem with different delivery time, resalable returns, and an additional order, Mathematical Problems in Engineering, 2015, (2015); Ballou R.H., Business LogisticsManagement, (1992); Perl J., Sirisoponsilp S., Distribution networks: Facility location, transportation and inventory, International Journal of PhysicalDistribution&MaterialsManagement, 18, 6, pp. 18-26, (1988); Ballou R.H., Masters J.M., Commercial software for locating warehoused and other facilities, Journal of Business Logistics, 14, 2, pp. 70-107, (1993); Erlebacher S.J., Meller R.D., The interaction of location and inventory in designing distribution systems, IIE Transactions, 32, 2, pp. 155-166, (2000); Daskin M.S., Coullard C.R., Shen Z.J., An inventorylocation model: Formulation, solution algorithm and computational results, Annals of Operations Research, 110, 1-4, pp. 83-106, (2002); Shen Z.-J.M., Coullard C., Daskin M.S., A joint locationinventory model, Transportation Science, 37, 1, pp. 40-55, (2003); Liao S.-H., Hsieh C.-L., Lai P.-J., An evolutionary approach for multi-objective optimization of the integrated locationinventory distribution network problem in vendor-managed inventory, Expert Systems with Applications, 38, 6, pp. 6768-6776, (2011); Balakrishnan A., Ward J.E., Wong R.T., Integrated facility location and vehicle routing models: Recent work and future prospects, American Journal OfMathematical AndManagement Sciences, 7, 1-2, pp. 35-61, (1987); Min H., Jayaraman V., Srivastava R., Combined locationrouting problems: A synthesis and future research directions, European Journal of Operational Research, 108, 1, pp. 1-15, (1998); Nagy G., Salhi S., Location-routing: Issues, models and methods, European Journal OfOperational Research, 177, 2, pp. 649-672, (2007); Chan L.M.A., Federgruen A., Simchi-Levi D., Probabilistic analyses and practical algorithms for inventory-routing models, Operations Research, 46, 1, pp. 96-106, (1998); Kleywegt A.J., Nori V.S., Savelsbergh M.W.P., The stochastic inventory routing problem with direct deliveries, Transportation Science, 36, 1, pp. 94-118, (2002); Adelman D., A price-directed approach to stochastic inventory/ routing, Operations Research, 52, 4, pp. 499-514, (2004); Moin N.H., Salhi S., Inventory routing problems: A logistical overview, Journal of the Operational Research Society, 58, 9, pp. 1185-1194, (2007); Liu S.C., Lee S.B., A two-phase heuristic method for the multi-depot location routing problem taking inventory control decisions into consideration, International Journal of Advanced Manufacturing Technology, 22, 11, pp. 941-950, (2003); Liu S.C., Lin C.C., A heuristic method for the combined location routing and inventory problem, International Journal of Advanced Manufacturing Technology, 26, 4, pp. 372-381, (2005); Shen Z.-J.M., Qi L., Incorporating inventory and routing costs in strategic location models, European Journal of Operational Research, 179, 2, pp. 372-389, (2007); Javid A.A., Azad N., Incorporating location, routing and inventory decisions in supply chain network design, Transportation Research Part E: Logistics and Transportation Review, 46, 5, pp. 582-597, (2010); Ahmadi-Javid A., Seddighi A.H., A location-routinginventory model for designing multisource distribution networks, Engineering Optimization, 44, 6, pp. 637-656, (2012); Guerrero W.J., Prodhon C., Velasco N., Amaya C.A., Hybrid heuristic for the inventory location-routing problem with deterministic demand, International Journal of Production Economics, 146, 1, pp. 359-370, (2013); Zhang Y., Qi M.Y., Miao L.X., Liu E., Hybrid metaheuristic solutions to inventory location routing problem, Transportation Research Part E: Logistics and Transportation Review, 70, 1, pp. 305-323, (2014); Nekooghadirli N., Tavakkoli-Moghaddam R., Ghezavati V.R., Javanmard S., Solving a new bi-objective locationrouting-inventory problem in a distribution network by metaheuristics, Computers and Industrial Engineering, 76, 1, pp. 204-221, (2014); Guerrero W.J., Prodhon C., Velasco N., Amaya C.A., A relax-and-price heuristic for the inventory-location-routing problem, International Transactions in Operational Research, 22, 1, pp. 129-148, (2015); Li Y.H., Guo H., Wang L., Fu J., Ahybridgenetic-simulated annealing algorithm for the location-inventory-routing problem considering returns under E-supply chain environment, The Scientific World Journal, 2013, (2013); Liu B.L., Chen H., Li Y.H., Liu X., A pseudo-parallel genetic algorithm integrating simulated annealing for stochastic location-inventory-routing problem with consideration of returns in e-commerce, Discrete Dynamics in Nature and Society, 2015, (2015); Petersen J.A., Kumar V., Perceived risk, product returns, and optimal resource allocation: Evidence from a field experiment, Journal OfMarketing Research, 52, 2, pp. 268-285, (2015); Niu Y., Wang S., He J., Xiao J., Anovelmembrane algorithm for capacitated vehicle routing problem, SoftComputing, 19, 2, pp. 471-482, (2014); Ball M., Bodin L., Dial R., A matching based heuristic for scheduling mass transit crews and vehicles, Transportation Science, 17, 1, pp. 4-31, (1983); Dror M., Laporte G., Trudeau P., Vehicle routing with stochastic demands: Properties and solution frameworks, Transportation Science, 23, 3, pp. 166-176, (1989); Dumas Y., Desrosiers J., Soumis F., The pickup and delivery problem with time windows, European Journal of Operational Research, 54, 1, pp. 7-22, (1991); Dorigo M., Gambardella L.M., Ant colony system: A cooperative learning approach to the traveling salesman problem, IEEE Transactions on Evolutionary Computation, 1, 1, pp. 53-66, (1997); Dervis K., Bahriye B., A powerful and efficient algorithmfor numerical function optimization: Artificial bee colony (ABC) algorithm, Journal of Global Optimization, 39, 3, pp. 459-471, (2007); Location-Routing Problems (LRP); Wang L., Shi Y., Liu S., An improved fruit fly optimization algorithm and its application to joint replenishment problems, Expert Systems with Applications, 42, 9, pp. 4310-4323, (2015)","H. Guo; School of Information Management, Central China Normal University, Wuhan, 430079, China; email: haoguo@mails.ccnu.edu.cn",null,"Hindawi Publishing Corporation",{"$nulls":5},1.0260226E7,null,null,null,"English","Discrete Dyn. Nat. Soc.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-84982856719"]
["Liu D.; Sarkar S.; Sriskandarajah C.","Liu, Dengpan (17435049800); Sarkar, Sumit (7403239069); Sriskandarajah, Chelliah (7004614677)","17435049800; 7403239069; 7004614677","Who's next? Scheduling personalization services with variable service times",2015.0,"ACM Transactions on Management Information Systems",6.0,2.0,8.0,null,null,null,1.0,"10.1145/2764920","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84937886534&doi=10.1145%2f2764920&partnerID=40&md5=93f57d6925ae302ddf0b232d84e17264","College of Business, Iowa State University, United States; Naveen Jindal School of Management, University of Texas, Dallas, United States; Mays Business School, Texas A and M University, United States","Liu D., College of Business, Iowa State University, United States; Sarkar S., Naveen Jindal School of Management, University of Texas, Dallas, United States; Sriskandarajah C., Mays Business School, Texas A and M University, United States","Online personalization has become quite prevalent in recent years, with firms able to derive additional profits from such services. As the adoption of such services grows, firms implementing such practices face some operational challenges. One important challenge lies in the complexity associated with the personalization process and how to deploy available resources to handle such complexity. The complexity is exacerbated when a site faces a large volume of requests in a short amount of time, as is often the case for e-commerce and content delivery sites. In such situations, it is generally not possible for a site to provide perfectly personalized service to all requests. Instead, a firm can provide differentiated service to requests based on the amount of profiling information available about the visitor. We consider a scenario where the revenue function is concave, capturing the diminishing returns from personalization effort. Using a batching approach, we determine the optimal scheduling policy (i.e., time allocation and sequence of service) for a batch that accounts for the externality cost incurred when a request is provided service before other waiting requests. The batching approach leads to sunk costs incurred when visitors wait for the next batch to begin. An optimal admission control policy is developed to prescreen new request arrivals. We show how the policy can be implemented efficiently when the revenue function is complex and there are a large number of requests that can be served in a batch. Numerical experiments show that the proposed approach leads to substantial improvements over a linear approximation of the concave revenue function. Interestingly, we find that the improvements in firm profits are not only (or primarily) due to the different service times that are obtained when using the nonlinear personalization function - there is a ripple effect on the admission control policy that incorporates these optimized service times, which contributes even more to the additional profits than the service time optimization by itself. © 2015 ACM.","Admission control policy; Batch processing; Hierarchical decision tables; Online personalization; Resource allocation","Batch data processing; Decision tables; Profitability; Resource allocation; Scheduling; Social networking (online); Admission control policies; Differentiated Services; Hierarchical decisions; Linear approximations; Operational challenges; Personalization services; Personalizations; Profiling informations; Economics",{"$nulls":6},"Adler M., Gibbons P.B., Matias Y., Scheduling space-sharing for internet advertising, Journal of Scheduling, 5, 2, pp. 103-119, (2002); Ba S., Johansson W.C., An exploratory study of the impact of e-service process on online customer satisfaction, Production and Operations Management, 17, 1, pp. 107-119, (2008); Baumol W.J., Bushnell R.C., Error produced in linearization in mathematical programming, Econometrica, 35, 3-4, pp. 447-471, (1967); Beales H., The Value of Behavioral Targeting, (2010); Brohan M., J. C. Penney Grows Annual Web Sales for the First Time in Years, (2014); Brynjolfsson E., Smith M.D., Frictionless commerce? A comparison of internet and conventional retailers, Management Science, 46, 4, pp. 563-585, (2000); Cardellini V., Colajanni M., Yu P.S., Dynamic load balancing on web-server systems, IEEE Internet Computing, 3, 3, pp. 28-39, (1999); Caruana A., Pitt L., INTQUAL - An internal measure of service quality and the link between service quality and business performance, European Journal of Marketing, 31, 8, pp. 604-616, (1997); Chen Y., Pavlov D., Canny J.F., Large-scale behavioral targeting, Proceeding of KDD '09, (2009); DaSilva L.A., Petr D.W., Akar N., Static pricing and quality of service in multiple service networks, Proceedings of the 5th International Conference on Computer Science and Informatics, 1, pp. 355-358, (2000); Geoffrion A.M., Objective function approximations in mathematical programming, Mathematical Programing, 13, pp. 27-37, (1977); Gupta S., Koulamas C., Kyparisis G.J., E-business: A review of research published in production and operations management (1992-2008), Production and Operations Management, 18, 6, pp. 604-620, (2009); Huang T., Van Mieghem J.A., The promise of strategic customer behavior: On the value of click tracking, Production and Operations Management, (2012); Jaillet P., Stafford M., Online Searching, Operations Research, 49, 4, pp. 501-515, (2001); Joshi A., Bagherjeiran A., Ratnaparkhi A., User demographic and behavioral targeting for content match advertising, Proceedings of the 5th International Workshop on Data Mining and Audience Intelligence for Advertising (ADKDD'11), pp. 53-60, (2011); Knight K., AudienceScience: 77% of Marketers to Use Targeting This Year, (2010); Liu D., Sarkar S., Sriskandarajah C., Resource allocation policies for personalization in content delivery sites, Information Systems Research, 21, 2, pp. 227-248, (2010); Love J., Sales Grow 16.7% in 2013 for Online Grocer OcadoO, (2014); Marr K., Yahoo Unveils Personalized Ads, (2007); Milgrom P.R., Good news and bad news: Representation theorems and applications, Bell Journal of Economics, 12, 2, pp. 380-391, (1981); Mulpuru S., US Online Retail Forecast, 2012-2017, (2013); Ou J., Parlar M., Sharafali M., A differentiated service scheme to optimize website revenue, Journal of the Operational Research Society, 57, 11, pp. 1323-1340, (2006); Patel H., Yahoo Debuts Smart Ads on Homepage in Video Format, (2011); Pinedo M., Scheduling: Theory, Algorithms, and Systems, (2012); Rust R.T., Zahorik A.J., Keiningham T.L., Return on quality (ROQ): Making service quality financially accountable, Journal of Marketing, 59, pp. 58-70, (1995); Sonderman J., New York Times to Add Active Personalization of Article Recommendations, (2011); Quarterly Retail E-commerce Sales 1st Quarter 2013; Watson J., Web 3.0: The Battle between Performance and Personalization, (2011); Zivan R., Dudik M., Paruchuri P., Sycara K., Maximizing revenue in symmetric resource allocation systems when user utilities exhibit diminishing returns, Proceedings of the 10th International Conference on Autonomous Agents and Multiagent Systems (AAMAS'11), 3, pp. 1165-1166, (2011)",null,null,"Association for Computing Machinery",{"$nulls":5},"2158656X",null,null,null,"English","ACM Trans. Manage. Inf. Syst.","Article","Final",null,"Scopus","2-s2.0-84937886534"]
["Cai Y.; Lang Y.; Zheng S.; Zhang Y.","Cai, Yuqiu (57092385000); Lang, Yuqi (57188867243); Zheng, Shulan (57188862625); Zhang, Yongqiang (57008617900)","57092385000; 57188867243; 57188862625; 57008617900","Research on the influence of e-commerce platform to agricultural logistics: An empirical analysis based on agricultural product marketing",2015.0,"International Journal of Security and its Applications",9.0,10.0,null,287.0,296.0,9.0,10.0,"10.14257/ijsia.2015.9.10.26","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84963958018&doi=10.14257%2fijsia.2015.9.10.26&partnerID=40&md5=576087ac72cfec516aedee81f1affa3a","College of Economics and Management, Northeast Agricultural University, Harbin, China","Cai Y., College of Economics and Management, Northeast Agricultural University, Harbin, China; Lang Y., College of Economics and Management, Northeast Agricultural University, Harbin, China; Zheng S., College of Economics and Management, Northeast Agricultural University, Harbin, China; Zhang Y., College of Economics and Management, Northeast Agricultural University, Harbin, China","Along with the rapid development of information technology, the traditional agricultural products sales model is facing a huge challenge. Agricultural products E-commerce platform, which carries three layers service functions, one is its most basic functions, which provides an information exchange, online payment, logistics transportation and sales activity; second is intermediate function, it can provide financial analysis, market research and business plan; the final advanced features, it strongly promoted the related subsidiary industry and service industry. In this paper, we make empirical analysis about the factors that influence the agricultural logistics economy, the result shows that agricultural prices, logistics time, product quality, service level, credibility, spending habits, profits and operating capital are the key factors that will affect the agricultural product marketing. © 2015 SERSC.","Agricultural logistics; E-commerce; Economic development; Regression model","Agricultural products; Commerce; Economics; Electronic commerce; Marketing; Quality control; Regression analysis; Sales; Economic development; Empirical analysis; Financial analysis; Information exchanges; Intermediate function; Logistics transportations; Regression model; Service industries; Agriculture",{"$nulls":6},"Samiee S., Global marketing effectiveness via alliances and electronic commerce in business-to-business markets, Industrial Marketing Management, 37, 1, pp. 3-8, (2008); Mohamad S., Ahmad U., The Attributes of Electronic Service Quality (e-SQ) among Academic Librarians, Procedia-Social and Behavioral Sciences, 65, pp. 260-265, (2012); Liem V., Cass A., Innovation and business success: The mediating role of customer participation, Journal of Business Research, 66, 8, pp. 1134-1142, (2013); Djelassi S., Decoopman I., Customers' participation in product development through crowd sourcing: Issues and implications, Industrial Marketing Management, 42, 5, pp. 683-692, (2013); Wen W., A knowledge-based intelligent electronic commerce system for selling agricultural products, Computers and Electronics in Agriculture, 57, 1, pp. 33-46, (2007); Helander M.G., Modeling the customer in electronic commerce, Applied Ergonomics, 31, 6, pp. 609-619, (2000); Bao L., Huang Y., On the Supply Chain Management Supported by E-Commerce Service Platform for Agreement based Circulation of Fruits and Vegetables, Physics Procedia, 33, pp. 1957-1963, (2012); Tao T., An Ontology-Based Information Retrieval Model for Vegetables E-Commerce, Journal of Integrative Agriculture, 11, 5, pp. 800-807, (2012); Savrul M., Incekara A., The Potential of E-commerce for SMEs in a Globalizing Business Environment, Procedia-Social and Behavioral Sciences, 150, 1, pp. 35-45, (2014); Lefebvre L.A., E-commerce and virtual enterprises: issues and challenges for transition economies, Technovation, 22, 5, pp. 313-323, (2002); Carlos S., A networked platform for agricultural management systems, Computers and Electronics in Agriculture, 31, 1, pp. 75-90, (2001)","Y. Zhang; College of Economics and Management, Northeast Agricultural University, Harbin, China; email: zyqlss@126.com",null,"Science and Engineering Research Support Society",{"$nulls":5},1.7389976E7,null,null,null,"English","Int. J. Secur. Appl.","Article","Final",null,"Scopus","2-s2.0-84963958018"]
["Wu T.-J.; Zhao R.-H.; Tzeng S.-Y.","Wu, Tung-Ju (54409758800); Zhao, Ren-Hui (57189520492); Tzeng, Shian-Yang (57189523919)","54409758800; 57189520492; 57189523919","An empirical research of consumer adoption behavior on catering transformation to mobile O2O",2015.0,"Journal of Interdisciplinary Mathematics",18.0,6.0,null,769.0,788.0,19.0,27.0,"10.1080/09720502.2015.1108088","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84971613784&doi=10.1080%2f09720502.2015.1108088&partnerID=40&md5=9b2dc87faacdd2f49256de71b384fd07","College of Business Administration, Huaqiao University, Quanzhou, 362021, China; Business School, Shantou University, Shantou, 515063, China","Wu T.-J., College of Business Administration, Huaqiao University, Quanzhou, 362021, China; Zhao R.-H., College of Business Administration, Huaqiao University, Quanzhou, 362021, China; Tzeng S.-Y., Business School, Shantou University, Shantou, 515063, China","With the decline of the performance and prospects of catering industry and the rapid development of the network economy and e-commerce, merchants try to join the mobile O2O business. Its starting point and the end-result is attract more consumers through the network to complete meal ordering and delivery business, it also make consumers and business operators through online trading achieve convenient services and achieve satisfaction on both sides. This article mainly starts from the consumption of college students consumer groups of the characteristic of psychological behavior and catering industry, using the technology acceptance model (TAM) for consumers (mobile catering service platform) to find the influence factors of using attitude has carried on the empirical analysis, the research conclusion, and put forward the businessman is how to make use of O2O model use attitude to better grasp the young consumer groups, improve their efforts expectations, performance expectations and perception is favorable, reduce the perceived risk and perceived costs of countermeasures and suggestions. © TARU PUBLICATIONS.","Consumer adoption behavior; Food and beverage industry; Mobile O2O business; Technology acceptance model","Behavioral research; Beverages; Mobile commerce; Risk assessment; Risk perception; Students; Catering industries; Consumer adoptions; Empirical analysis; Empirical research; Food and beverage industry; Performance expectations; Service platforms; Technology acceptance model; Consumer behavior",{"$nulls":4},"Maritime Silk Road Fund of Huaqiao University, (HSZD2014-07); Scientific Research Fund of Huaqiao University, (15SKBS203)","The authors are grateful to the valuable comments made by the reviewers. This research was supported by Scientific Research Fund of Huaqiao University (15SKBS203) and Maritime Silk Road Fund of Huaqiao University (HSZD2014-07).","Chen Q.J., Zuo X.J., Constructing an O2O Service Quality Appraisal System Based on Fuzzy Comprehensive Evaluation Method, Proc of the 9Th Int. Symp. On Linear Drives for Industry Applications, pp. 37-42, (2013); David C.Y., Wu C.S., Cheng F.F., Determinants of Users’ Intention to Adopt Wireless Technology: An Empirical Study by Integrating TTF with TAM, Computers in Human Behavior, 26, 5, pp. 906-915, (2010); Davis F.D., Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology, MIS Quarterly, 13, 3, pp. 319-340, (1989); Deng Z.H., Lu Y.B., Wang B., Understanding Chinese Enterprises’ Adoption of Enterprise Short Message Services: Combining IDT and TTF, International Journal of Services Technology and Management, 12, 2, pp. 192-215, (2009); He D.H., Lu Y.B., Consumers Perceptions and Acceptances Towards Mobile Advertising: An Empirical Study in China, The 3Rd Int. Conf. Of Wireless Communications, Networking and Mobile Computing, pp. 3775-3778, (2007); Hsieh H.C., Chen Y.C., Lin H.C., Improved Precision Recommendation Scheme by BPNN Algorithm in O2O Commerce, Proc of the 10Th IEEE Int. Conf. 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Interdiscip. Math.","Article","Final",null,"Scopus","2-s2.0-84971613784"]
["Zhang X.","Zhang, Xuqi (56239894300)",5.62398943E10,"Research on optimizing model for logistics location under electronic commerce based on heuristic algorithm",2014.0,"International Journal of Multimedia and Ubiquitous Engineering",9.0,6.0,null,335.0,345.0,10.0,2.0,"10.14257/ijmue.2014.9.6.32","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84903538452&doi=10.14257%2fijmue.2014.9.6.32&partnerID=40&md5=b3a1736ba650161a8781438bbf3d2189","Xi'an International University, Logistics Department, Xi'an, Shanxi, Zhang eight North Road No. 408, China","Zhang X., Xi'an International University, Logistics Department, Xi'an, Shanxi, Zhang eight North Road No. 408, China","With the development of the computer network technology and the electronic commerce, more and more firms establish the electronic sale channel and get great profits. The huge supply chain network is established through the new idea and technology. The node location selection is a planning process that chooses a location to set up a logistics node in an economy zone with multi demands. Hence, its location selection is a key link in the logistics system planning. In this paper, we consider the specific particularity of the e-commerce. Then, we constraints cost and delivery time of the logistics model. At last, we apply the heuristic algorithm to the location model. The results show that the algorithm can apply to the logistics distribution problem under the electronic commerce environment excellently. © 2014 SERSC.","Electronic commerce; Time constraint; Vehicle scheduling problem","Electronic commerce; Heuristic algorithms; Supply chains; Computer network technology; Location modeling; Location selection; Logistics distribution; Optimizing models; Supply chain network; Time constraints; Vehicle scheduling problem; Logistics",{"$nulls":6},"Teo J.S.E., Taniguchi E., Quresh A.G., Evaluating city logistics measure in e-commerce with multi-agent systems, Procedia-Social and Behavioral Sciences, 29, pp. 349-359, (2012); Ramanathan R., The moderating roles of risk and efficiency on the relationship between logistics performance and customer loyalty in e-commerce, Transportation Research Part E: Logistics and Transportation Review, 46, 6, pp. 950-962, (2010); Ying W., Dayong S., Multi-agent framework for third party logistics in E-commerce, Expert Systems with Applications, 29, 2, pp. 431-436, (2005); Hesse M., Shipping news: The implications of electronic commerce for logistics and freight transport, Resources, Conservation and Recycling, 36, 3, pp. 211-240, (2002); Francis R.L., White J.A., Facility layout and location: An analytical approach, (1974); Hansen P., Mladenovic N., Variable neighborhood search for the p-median, Location Science, 5, pp. 207-226, (1997); Da-yuan J., Study on Location Selection based on Multi-Node Logistics, Railway transport and economy, 27, 8, pp. 24-26, (2005); Masood A.B., Combining the analytic hierarchy process and goal programming for global facility location-allocation problem, International Journal of Production Economics, 62, 2, pp. 237-248, (1999); Gong D.J., Gen M.S., Yamazaki G.J., Hybrid evolutionary method for capacitated location-allocation problem, Computers Industrial Engineering, 33, 3, pp. 577-580, (1997); Aikens C.H., Facility Location Models for Distribution Planning, European Journal of Operational Research, 22, 2, pp. 263-279, (1985); Frantzeskakis M., Waston-Gandy C.D.T., The use of state space relaxation for the dynamic facility location problem, Annals of operations research, 18, pp. 189-212, (1989); Shulman A., An algorithm for solving dynamic capacitated plant location problems with discrete expansion sizes, Operations research, 39, 3, pp. 423-436, (1991); Berman O., Krass D., Facility Location with Stochastic Demand and Congestion, Facility Location: Applications and Theory, (2001)","X. Zhang; Xi'an International University, Logistics Department, Xi'an, Shanxi, Zhang eight North Road No. 408, China; email: 1020640555@qq.com",null,"Science and Engineering Research Support Society",{"$nulls":5},1.975008E7,null,null,null,"English","Int. J. Multimedia Ubiquitous Eng.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-84903538452"]
["Liu H.","Liu, Haibin (56672766500)",5.66727665E10,"Simulation of lateral transshipment in order delivery under e-commerce environment",2016.0,"International Journal of Simulation and Process Modelling",11.0,1.0,null,51.0,65.0,14.0,2.0,"10.1504/IJSPM.2016.075080","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84961173393&doi=10.1504%2fIJSPM.2016.075080&partnerID=40&md5=f23fad0f33edd84fe2514706e730782f","Zhengzhou Institute of Aeronautical Industry Management, No. 2 Middle of DAXUE Road, ERQI District, Zhengzhou, Henan, China","Liu H., Zhengzhou Institute of Aeronautical Industry Management, No. 2 Middle of DAXUE Road, ERQI District, Zhengzhou, Henan, China","In this research, we apply a discrete event simulation approach to explore how enterprises in the Chinese mainland make a successful operation with the aid of e-commerce. This paper examines the effects of proposed four kinds of transshipment operation network structures on the performance under different policies of transshipment and inventory allocation. Results show that: 1) transshipment based on availability (TBA) policy can produce the high service level, while transshipment based on the inventory equalisation (TIE) policy can give high profits; 2) adoption of TBA or TIE is contingent on different stages of development; 3) an optimal service level and performance can both be acquired at the same time by adjusting transshipping structure; 4) the 'complete link' transshipping structure is the best in improving the service level; 5) the 'small-world' transshipping structure is optimal; 6) the 'scale-free' transshipping structure should be averted forming in operation. © Copyright 2016 Inderscience Enterprises Ltd.","Discrete event simulation; Lateral transshipment; TBA; TIE; Transshipment based on availability; Transshipment based on the inventory equalisation","Discrete event simulation; Electronic commerce; Equalizers; Chinese mainland; Different stages; Equalisation; Inventory allocation; Lateral trans shipments; Network structures; Service levels; Small worlds; Structural optimization",{"$nulls":6},"Banerjee A., Burton J., Banerjee S., A simulation study of lateral transshipments in a single supplier multiple buyers supply chain network, International Journal of Production Economics, 81-82, 2, pp. 103-114, (2003); Barabasi A.-L., Albert R., Emergence of scaling in random networks, Nature, 286, 5439, pp. 509-512, (1999); Bendoly E., Integrated inventory pooling for firms servicing both on-line and store demand, Computers and Operations Research, 31, 9, pp. 1465-1480, (2004); Burton J., Banerjee A., Cost parametric analysis of lateral transshipment policies in two-echelon supply chains, International Journal of Production Economics, 93-94, 1, pp. 169-178, (2005); Ching W., Huang X., Ng M., Siu T., Markov chains: Models, algorithms and applications, International Series in Operations Research and Management Science, (2013); Corning P.A., The synergism hypothesis': On the concept of synergy and its role in the evolution of complex systems, Journal of Social and Evolutionary Systems, 21, 2, pp. 133-172, (2000); Dong L., Rudi N., Who benefits from transshipment? Exogenous vs. Endogenous wholesale prices, Management Science, 50, 5, pp. 645-657, (2004); Gross D., Centralized inventory control in multilocation supply systems, Multistage Inventory Models and Techniques, pp. 47-84, (1963); Hoadley B., Heyman D.P., A two-echelon inventory model with purchases, dispositions, shipments, returns and transshipments, Naval Research Logistics Quarterly, 24, 1, pp. 1-19, (1977); IResearch China Online Shoppers' Behaviour Research, (2011); IResearch China Online Shopping Research, (2011); IResearch on China Top Fifty Online B2C Retailers, (2011); Karmarkar U.S., Patel N.R., The one-period N-location distribution problem, Naval Research Logistics Quarterly, 24, 4, pp. 559-575, (1977); Krishnan K., Rao V., Inventory control in N warehouses, Journal of Industrial Engineering, 16, 3, pp. 212-215, (1965); Kukreja A., Schmidt C.P., A model for lumpy demand parts in a multi-location inventory system with transshipments, Computers & Operations Research, 32, 8, pp. 2059-2075, (2005); Lee H.L., A multi-echelon inventory model for repair-able items with emergency lateral transshipments, Management Science, 33, 10, pp. 1302-1316, (1987); Lee Y.H., Jung J.W., Jeon Y.S., An effective lateral transshipment policy to improve service level in the supply chain, International Journal of Production Economics, 106, 1, pp. 115-126, (2007); Liao Y., Shen W., Hu X., Et al., Optimal responses to stockouts: Lateral transshipment versus emergency order policies, Omega, 49, 12, pp. 79-92, (2014); Newmann M.E.J., Watss D.J., Renormalization group analysis of the small-world network model, Physics Letter A, 263, 4, pp. 341-346, (1999); Newmann M.E.J., Watss D.J., Scaling and percolation in the small-world network model, Physics Review E, 60, 6, pp. 7332-7342, (1999); Paterson C., Kiesmuller G., Teunter R., Glazebrook K., Inventory models with lateral transshipments: A review, European Journal of Operational Research, 210, 2, pp. 125-136, (2011); Paterson C., Teunter R., Glazebrook K., Enhanced lateral transshipments in a multi-location inventory system, European Journal of Operational Research, 221, 2, pp. 317-327, (2012); Paul A., Yenipazarli A., A note on lateral transshipment under point-process driven demand, Operations Research Letters, 41, 2, pp. 159-163, (2013); Robinson L.W., Optimal and approximate policies in multiperiod, multi-location inventory models with transshipments, Operations Research, 38, 2, pp. 278-295, (1990); Rudi N., Kapur S., Pyke D.F., A two-location inventory model with transhipment and local decision making, Management Science, 47, 12, pp. 1668-1680, (2001); Shenkar O., Li J., Knowledge search in international cooperative ventures, Organization Science, 10, 2, pp. 134-133, (1999); Tagaras G., Effects of pooling on the optimization and service levels of two-location inventory systems, IIE Transactions, 21, 9, pp. 250-257, (1989); Tagaras G., Cohen M.A., Pooling in two-location inventory systems with non-negligible replenishment lead times, Management Science, 38, 8, pp. 1067-1083, (1992); Tagaras G., Vlachos D., Effectiveness of stock transshipment under various demand distributions and non-negligible transshipment times, Production and Operations Management, 11, 2, pp. 183-198, (2002); Tai A.H., Ching W.-K., Optimal inventory policy for a Markovian two-echelon system with returns and lateral transshipment, International Journal of Production Economics, 151, 7, pp. 48-55, (2014); Utterbeeck F.V., Wong H., Oudheusden D.V., Cattrysse D., The effects of resupply flexibility on the design of service parts supply systems, Transportation Research Part E, 45, 1, pp. 72-85, (2009); Watts D.J., Strogatz S.H., Collective dynamics of 'small worlds' networks, Nature, 393, 4, pp. 440-442, (1998); Yu D.Z., Tang S.Y., Niederhoff J., On the benefits of operational flexibility in a distribution network with transshipment, Omega, 39, 3, pp. 350-361, (2011)","H. Liu; Zhengzhou Institute of Aeronautical Industry Management, Zhengzhou, Henan, No. 2 Middle of DAXUE Road, ERQI District, China; email: haibin_liu@yeah.net",null,"Inderscience Publishers",{"$nulls":5},1.7402123E7,null,null,null,"English","Int. J. Simul. Process Model.","Article","Final",null,"Scopus","2-s2.0-84961173393"]
["Sharma G.; Lijuan W.","Sharma, Gajendra (37075772400); Lijuan, Wang (56615402200)","37075772400; 56615402200","The effects of online service quality of e-commerce Websites on user satisfaction",2015.0,"Electronic Library",33.0,3.0,null,468.0,485.0,17.0,99.0,"10.1108/EL-10-2013-0193","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84930329179&doi=10.1108%2fEL-10-2013-0193&partnerID=40&md5=8e57473f163fd61b86699abb10f634a4","Department of Computer Science and Engineering, School of Engineering, Dhulikel, Kavre, Nepal; Department of Marketing Management, Liaoning Technical University, Huludao, China","Sharma G., Department of Computer Science and Engineering, School of Engineering, Dhulikel, Kavre, Nepal; Lijuan W., Department of Marketing Management, Liaoning Technical University, Huludao, China","Purpose - The purpose of this paper is to investigate service quality of e-commerce Websites in online platform and their contribution on e-business promotion. Design/methodology/approach - The online survey was performed on a survey portal provided by Nepal Telecom in Nepal. Findings - The findings of this study suggest that information quality and online service quality were the key determinants for user satisfaction and sustainability of e-commerce technology. Research limitations/implications - Research opportunities of web services and e-commerce area are fruitful and important for both academics and practitioners. Practical implications - The findings on online service quality of e-commerce technology will be useful for current management practice such as making business policies and strategies and sharing information to managers and organization leaders. This study can be used for e-commerce Website operators wishing to enhance the competitiveness of their Websites in the highly competitive online market. Originality/value - E-commerce is considered an excellent alternative for individuals and companies to reach new customers. Service quality delivery through Internet is an essential strategy to success, more important than price and web presence. The e-commerce Website has been identified as having a significant impact on business activities in solving the geographical problem.Anumber of performance problems have been observed for e-commerce Websites, and much work has gone into characterizing the performance of web-servers and Internet applications.","E-commerce; Satisfaction; Service quality; Websites",{"$nulls":7},"Ahire S.L., Golhar D.Y., Walter M.A., Development and validation of TQM implementation constructs, Decision Science, 27, 1, pp. 21-56, (1996); Aladwani A.M., Prashant C.P., Developing and validating an instrument for measuring user perceived web quality, Information and Management, 39, 6, pp. 467-476, (2002); Alzola L.M., Robaina V.P., The impact of pre-sale and post-sale factors on online purchasing satisfaction: A survey, International Journal of Quality and Reliability Management, 27, 2, pp. 121-137, (2010); Anderson J.C., Gerbing D.W., Structural equation modeling in practice: A review and recommended two-step approach, Psychological Bulletin, 103, 3, pp. 411-423, (1988); 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A large scale exploratory empirical study, Journal of Marketing, 69, pp. 133-152, (2005); Yang B., Internet User Behavior and Online Shopping in Taiwan: Key Trends in 2007, (2008); Yang M.H., Chandlrees N., Lin B., Chao H.Y., The effect of perceived ethical performance of shopping websites on consumer trust, Journal of Computer Information Systems, 50, 1, pp. 15-24, (2009); Yu Y.L., Chung Y.F., Chen T.S., Electronic signatures for long-term storage purpose in electronic anamnesis, International Journal of Innovative Computing, Information and Control, 4, 11, pp. 3047-3058, (2008); Zamzuri N.H.A., Mohamed N., Hussein R., Antecedents of customer satisfaction in repurchase intention in the electronic commerce environment, Proceedings of ITSim, (2008); Zhou T., An empirical examination of initial trust in mobile banking, Internet Research, 21, 5, pp. 527-540, (2011); Zwass V., Electronic commerce and organizational innovative: Aspects and opportunities, International Journal of Electronic Commerce, 7, 3, pp. 7-37, (2003)",null,null,"Emerald Group Holdings Ltd.",{"$nulls":5},2640473.0,null,"ELLID",null,"English","Electron. Libr.","Article","Final",null,"Scopus","2-s2.0-84930329179"]
["Westbrook R.N.; Watkins S.","Westbrook, R. Niccole (55338902600); Watkins, Sean (55369550100)","55338902600; 55369550100","High res at high speed: Automated delivery of high-resolution images from digital library collections",2012.0,"Journal of Web Librarianship",6.0,2.0,null,109.0,124.0,15.0,0.0,"10.1080/19322909.2012.677314","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84866881661&doi=10.1080%2f19322909.2012.677314&partnerID=40&md5=751ee3769bfb169bbce155ff747875a8","University of Houston Libraries, Houston, TX 77204-2000, 114 University Libraries, United States","Westbrook R.N., University of Houston Libraries, Houston, TX 77204-2000, 114 University Libraries, United States; Watkins S., University of Houston Libraries, Houston, TX 77204-2000, 114 University Libraries, United States","As primary source materials in the library are digitized and made available online, the focus of related library services is shifting to include new and innovative methods of digital delivery via social media, digital storytelling, and community-based and consortial image repositories. Most images on the Web are not of sufficient quality for most media outlets, so what happens when patrons require high-resolution versions of images for use in their print publications or projects? Until recently, patrons at the University of Houston Libraries used a clunky, paper-based request process for high-resolution images that was frustrating for them and timeconsuming for staff. The authors of this article outline how an interdepartmental team of University of Houston Libraries staff used Drupal to develop an automated patron request system that is modeled after online shopping cart experiences and integrates with the CONTENTdm-based University of Houston Digital Library. The article provides suggestions for libraries with digital collections about how to create a system that efficiently captures patron requests and streamlines staff delivery of high-resolution files. © Taylor & Francis Group, LLC.","Automation; CONTENTdm; Digital collection; Digital library; Drupal; High resolution; Image delivery; Image request; Web applications; Web services",{"$nulls":8},"R. N. Westbrook; University of Houston Libraries, Houston, TX 77204-2000, 114 University Libraries, United States; email: rnwestbrook@uh.edu",{"$nulls":7},1.9322917E7,null,null,null,"English","J. Web Librariansh.","Article","Final",null,"Scopus","2-s2.0-84866881661"]
["Li Y.; Lu M.; Liu B.","Li, Yanhui (56040405100); Lu, Mengmeng (56066114000); Liu, Bailing (56065758500)","56040405100; 56066114000; 56065758500","A two-stage algorithm for the closed-loop location-inventory problem model considering returns in E-commerce",2014.0,"Mathematical Problems in Engineering",2014.0,null,260869.0,null,null,null,15.0,"10.1155/2014/260869","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84911941628&doi=10.1155%2f2014%2f260869&partnerID=40&md5=83d508426227312686951b06b385b261","School of Information Management, Central China Normal University, Wuhan, 430079, China","Li Y., School of Information Management, Central China Normal University, Wuhan, 430079, China; Lu M., School of Information Management, Central China Normal University, Wuhan, 430079, China; Liu B., School of Information Management, Central China Normal University, Wuhan, 430079, China","Facility location and inventory control are critical and highly related problems in the design of logistics system for e-commerce. Meanwhile, the return ratio in Internet sales was significantly higher than in the traditional business. Focusing on the existing problem in e-commerce logistics system, we formulate a closed-loop location-inventory problem model considering returned merchandise to minimize the total cost which is produced in both forward and reverse logistics networks. To solve this nonlinear mixed programming model, an effective two-stage heuristic algorithm named LRCAC is designed by combining Lagrangian relaxation with ant colony algorithm (AC). Results of numerical examples show that LRCAC outperforms ant colony algorithm (AC) on optimal solution and computing stability. The proposed model is able to help managers make the right decisions under e-commerce environment. © 2014 Yanhui Li et al.",null,"Ant colony optimization; Electronic commerce; Heuristic algorithms; Inventory control; Location; Sales; Stages; Ant colony algorithms; Existing problems; Facility locations; LaGrangian relaxation; Nonlinear mixed programming; Reverse logistics network; Two-stage algorithm; Two-stage heuristic algorithms; Logistics",{"$nulls":4},"National Natural Science Foundation of China, (71101061, 71171093)",null,"Ecommerce Sales Topped $1 Trillion for the First Time in 2012; Meyer H., Many happy returns, Journal of Business Strategy, 20, 4, pp. 27-31, (1999); Gentry C.R., Reducing the cost of returns, Chain Store Age, 75, 10, pp. 124-126, (1999); Watson-Gandy C.D.T., Dohrn P.J., Depot location with van salesmen - A practical approach, Omega, 1, 3, pp. 321-329, (1973); Singh A.R., Jain R., Mishra P.K., Capacities-based supply chain network design considering demand uncertainty using two-stage stochastic programming, International Journal of Advanced Manufacturing Technology, 69, 1-4, pp. 555-562, (2013); Berman O., Krass D., Tajbakhsh M.M., A coordinated location-inventory model, European Journal of Operational Research, 217, 3, pp. 500-508, (2012); Shahabi M., Akbarinasaji S., Unnikrishnan A., James R., Integrated inventory control and facility location decisions in a multi-echelon supply chain network with hubs, Networks and Spatial Economics, 13, pp. 497-514, (2013); Lieckens K., Vandaele N., Reverse logistics network design with stochastic lead times, Computers and Operations Research, 34, 2, pp. 395-416, (2007); Srivastava S.K., Network design for reverse logistics, Omega, 36, 4, pp. 535-548, (2008); Wang Z., Yao D.-Q., Huang P., A new location-inventory policy with reverse logistics applied to B2C e-markets of China, International Journal of Production Economics, 107, 2, pp. 350-363, (2007); Tancrez J.-S., Lange J.-C., Semal P., A location-inventory model for large three-level supply chains, Transportation Research E: Logistics and Transportation Review, 48, 2, pp. 485-502, (2012); Diabat A., Kannan D., Kaliyan M., Svetinovic D., A optimization model for product returns using genetic algorithms and artificial immune system, Resources, Conservation and Recycling, 74, pp. 156-169, (2013); Sahyouni K., Savaskan R.C., Daskin M.S., A facility location model for bidirectional flows, Transportation Science, 41, 4, pp. 484-499, (2007); Easwaran G., Uster H., Tabu search and Benders decomposition approaches for a capacitated closed-loop supply chain network design problem, Transportation Science, 43, 3, pp. 301-320, (2009); Abdallah T., Diabat A., Simchi-Levi D., Sustainable supply chain design: A closed-loop formulation and sensitivity analysis, Production Planning and Control, 23, 2-3, pp. 120-133, (2012); Li Y., Guo H., Wang L., Fu J., A hybrid genetic-simulated annealing algorithm for the location-inventory-routing problem considering returns under e-supply chain environment, The Scientific World Journal, 2013, (2013); Vlachos D., Dekker R., Return handling options and order quantities for single period products, European Journal of Operational Research, 151, 1, pp. 38-52, (2003); Lu Z., Bostel N., A facility location model for logistics systems including reverse flows: The case of remanufacturing activities, Computers and Operations Research, 34, 2, pp. 299-323, (2007); Daskin M.S., Coullard C.R., Shen Z.-J.M., An inventory-location model: Formulation, solution algorithm and computational results, Annals of Operations Research, 110, pp. 83-106, (2002); Shen Z.-J.M., Coullard C.R., Daskin M.S., A joint location-inventory model, Transportation Science, 37, 1, pp. 40-55, (2003); Fisher M.L., The Lagrangian relaxation method for solving integer programming problems, Management Science, 27, 1, pp. 1-18, (1981); Fisher M.L., An applications oriented guide to Lagrangian relaxation, Interfaces, 15, 2, pp. 10-21, (1985); Location-Routing Problems (LRP); Wang L., Qu H., Li Y., He J., Modeling and optimization of stochastic joint replenishment and delivery scheduling problem with uncertain costs, Discrete Dynamics in Nature and Society, 2013, (2013); Qu H., Wang L., Zeng Y.-R., Modeling and optimization for the joint replenishment and delivery problem with heterogeneous items, Knowledge-Based Systems, 54, pp. 207-215, (2013)",null,null,"Hindawi Publishing Corporation",{"$nulls":5},"1024123X",null,null,null,"English","Math. Probl. Eng.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-84911941628"]
["Pan J.C.-H.; Shih P.-H.; Wu M.-H.; Lin J.-H.","Pan, Jason Chao-Hsien (7404098325); Shih, Po-Hsun (54586021500); Wu, Ming-Hung (7405595572); Lin, Jyh-Horng (57137069600)","7404098325; 54586021500; 7405595572; 57137069600","A storage assignment heuristic method based on genetic algorithm for a pick-and-pass warehousing system",2015.0,"Computers and Industrial Engineering",81.0,null,null,1.0,13.0,12.0,87.0,"10.1016/j.cie.2014.12.010","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84920748633&doi=10.1016%2fj.cie.2014.12.010&partnerID=40&md5=6abbf7e7f42f197dfec5a7c4f2f51d22","Department of Business Administration, Takming University of Science and Technology, No. 56 Huanshan Road, Taipei, 11451, Taiwan; Department of Information Management, Vanung University, No. 1 Van-Nung Road, Chung-Li, Tao-Yuan, 320, Taiwan; Department of Digital Media Design, Cardinal Tien College of Healthcare and Management, No. 407,Jian Fu Road, Sanshing Township, Yilan County, 26646, Taiwan","Pan J.C.-H., Department of Business Administration, Takming University of Science and Technology, No. 56 Huanshan Road, Taipei, 11451, Taiwan; Shih P.-H., Department of Information Management, Vanung University, No. 1 Van-Nung Road, Chung-Li, Tao-Yuan, 320, Taiwan; Wu M.-H., Department of Business Administration, Takming University of Science and Technology, No. 56 Huanshan Road, Taipei, 11451, Taiwan; Lin J.-H., Department of Digital Media Design, Cardinal Tien College of Healthcare and Management, No. 407,Jian Fu Road, Sanshing Township, Yilan County, 26646, Taiwan","An order storage assignment problem (SAP) is to find an effective way to locate products in a warehouse in order to improve the operational efficiency of order picking. Since SAP is an NP-hard problem, many heuristic algorithms have been proposed. Most of previous researches focused on picker-to-parts warehousing systems or automated storage and retrieval systems. However, pick-and-pass systems play an important role for the faster delivery of small and frequent orders of inventory with the rise of e-commerce and e-business in the global supply chain. Two factors lead to idle time of pickers in a pick-and-pass system: picking line imbalance and shortage replenishment of products. This paper develops a genetic based heuristic method to solve SAP for a pick-and-pass system with multiple pickers to determine the appropriate storage space for each product and balance the workload of each picking zone so that the performance of the system can be improved. A simulation model based on FlexSim is used to implement the proposed heuristic algorithm and compare the throughput for different storage assignment methods as well. The results indicate that the proposed heuristic policy outperforms existing assignment methods in a pick-and-pass system. ©2014 Elsevier Ltd. All rights reserved.","Order picking; Pick-and-pass system; Storage assignment policy; Warehouse management","Algorithms; Combinatorial optimization; Computational complexity; Computer control systems; Electronic commerce; Heuristic algorithms; Supply chains; Warehouses; Automated storage and retrieval system; Global supply chain; Operational efficiencies; Order picking; Pick and pass; Storage assignment policies; Warehouse management; Warehousing systems; Heuristic methods",{"$nulls":6},"Abdel-Hamid A.A.A., Borndorfer R., On the Complexity of Storage Assignment Problems, (1994); Benjamin P., Bart V., Denis D., Dynamic ABC storage policy in erratic demand environments, Jurnal Teknik Industri, 5, pp. 1-12, (2003); Bottani E., Cecconi M., Vignali G., Montanari R., Optimisation of storage allocation in order picking operations through a genetic algorithm, International Journal of Logistics Research and Applications: A Leading Journal of Supply Chain Management, 15, 2, pp. 127-146, (2012); Brynzer H., Johansson M.I., Design and performance of kitting and order picking systems, International Journal of Production Economics, 41, pp. 115-125, (1995); Chan F.T.S., Chan H.K., Improving the productivity of order picking of a manual-pick and multi-level rack distribution warehouse through the implementation of class-based storage, Expert Systems with Applications, 38, pp. 2686-2700, (2011); Chen M.C., Wu H.P., An association based clustering approach to order batching considering customer demand patterns, Omega, 33, pp. 333-343, (2005); Chuang Y.F., Lee H.T., Laih Y.C., Item-associated cluster assignment model on storage allocation problems, Computers & Industrial Engineering, 63, 4, pp. 1171-1177, (2012); De Koster R., Performance approximation of pick-to-belt order picking systems, European Journal of Operational Research, 72, pp. 558-573, (1994); De Koster R., Le-Duc T., Roodbergen K.J., Design and control of warehouse order pickimg: A literature review, European Journal of Operation Research, 182, pp. 481-501, (2013); Falkenauer E., Genetic Algorithms and Grouping Problem, (1998); Flexsim Simulation Software User Guide 4, (2007); Frazelle E.H., Sharp G.P., Correlated assignment strategy can improve any order-picking operation, Industrial Engineering, 21, pp. 33-37, (1989); Gagliardi J.P., Ruiz A., Renaud J., Space allocation and stock replenishment synchronization in a distribution center, International Journal of Production Economics, 115, pp. 19-27, (2008); Glock C.H., Grosse E.H., Storage policies and order picking strategies in U-shaped order-picking systems with a movable base, International Journal of Production Research, 50, 16, pp. 4344-4357, (2012); Grosse E.H., Glock C.H., Jaber M.Y., The effect of worker learning and forgetting on storage reassignment. Decisions in order picking systems, Computers & Industrial Engineering, 66, pp. 653-662, (2013); Holland J., Adaptation in Natural and Artificial Systems, (1975); Hsu C.M., Chen K.Y., Chen M.C., Batching orders in warehouses by minimizing travel distance with genetic algorithms, Computers in Industry, 56, pp. 169-178, (2005); Jane C.C., Laih Y.W., A clustering algorithm for item assignment in a synchronized zone order picking system, European Journal of Operational Research, 166, pp. 489-496, (2005); Jewkes E., Lee C., Vickson R., Product location, allocation and server home base location for an order picking line with multiple servers, Computers & Operations Research, 31, pp. 623-626, (2004); Kovaks A., Optimizing the storage assignment in a warehouse served by milkrun logistics, International Journal of Production Economics, 133, 1, pp. 312-318, (2011); Malmborg C.J., Optimization of cubic-per-order index layout with zoning constraints, International Journal of Production Research, 33, pp. 465-482, (1995); Maloney D., Seeing the Light. Modern Materials Handling, pp. 49-53, (2000); Muppani V.R., Adil G.K., A branch and bound algorithm for class based storage location assignment, European Journal of Operational Research, 189, pp. 492-507, (2008); Muppani V.R., Adil G.K., Efficient formation of storage classes for warehouse storage location assignment: Simulated annealing approach, Omega, 36, pp. 609-618, (2008); Pan J.C.H., Wu M.H., A study of storage assignment problem for an order picking line in a pick-and-pass warehousing system, Computer & Industrial Engineering, 57, pp. 261-268, (2009); Park C., Seo J., Mathematical modeling and solving procedure of the planar storage location assignment problem, Computers & Industrial Engineering, 57, pp. 1062-1071, (2009); Park C., Seo J., Comparing heuristic algorithms of the planar storage location assignment problem, Transportation Research Part e, 46, pp. 171-185, (2010); Petersen C.G., Gerald A., Considerations in order picking zone configuration, International Journal of Operations & Production Management, 27, pp. 793-805, (2002); Petersen C.G., Gerald A., A comparison of picking, storage, and routing policies in manual order picking, International Journal of Production Economics, 92, pp. 11-19, (2004); Rouwenhorst B., Reuter B., Stockrahm V., Van Houtum G.J., Mantel R.J., Zijm W.H.M., Warehouse design and control: Framework and literature review, European Journal of Operational Research, 122, pp. 515-533, (2000); Rylander B., Foster J., Computational complexity and genetic algorithms, Proceedings of the World Science and Engineering Society's Conference on Soft Computing, pp. 248-253, (2001)",null,null,"Elsevier Ltd",{"$nulls":5},3608352.0,null,"CINDD",null,"English","Comput Ind Eng","Article","Final",null,"Scopus","2-s2.0-84920748633"]
["Gao J.; Wang J.; Wang B.","Gao, Jing (57094331900); Wang, Jinkuan (55954402400); Wang, Bin (57188712191)","57094331900; 55954402400; 57188712191","Model for evaluating the router security of wireless sensor network with interval grey linguistic variables",2012.0,"Information",15.0,"11 B",null,5003.0,5008.0,5.0,0.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-84869456001&partnerID=40&md5=385f58794c38385cbd26c5d36229a2a1","School of Information Science and Engineering, Northeastern University, Shenyang, Liaoning, 110004, China","Gao J., School of Information Science and Engineering, Northeastern University, Shenyang, Liaoning, 110004, China; Wang J., School of Information Science and Engineering, Northeastern University, Shenyang, Liaoning, 110004, China; Wang B., School of Information Science and Engineering, Northeastern University, Shenyang, Liaoning, 110004, China","Wireless sensor network (WSN), as an integrated network which can perform information gathering, processing and delivering, can connect the real world and logistic information world. It is greatly changing the interaction between people and nature. There are wide potential applications for wireless sensor network, such as industry, agriculture, military affairs, environment monitoring, biomedicine, city managing and disaster succoring. In this paper, we investigate the multiple attribute group decision making (MAGDM) problems for evaluating the router security of wireless sensor network with interval grey linguistic variables. We utilize the interval grey linguistic variables weighted geometric (IGLWG) operator and interval grey linguistic hybrid geometric (IGLHG) operator to aggregate the linguistic information corresponding to each alternative and get the overall value of router security of wireless sensor network, then rank the e-commerce websites and select the most desirable one(s) by using the overall value of router security of wireless sensor network. Finally, an illustrative example is given. © 2012 International Information Institute.","Interval grey linguistic variables; Multiple attribute group decision making (MAGDM); Router security of wireless sensor network",{"$nulls":7},"Herrera F., Nartinez L., A 2-tuple fuzzy linguistic representation model for computing with words, DEEE Transactions on Fuzzy Systems, 8, 6, pp. 746-752, (2000); Herrera F., Martinez L., A model based on linguistic 2-tuples for dealing with multigranular hierarchical linguistic contexts in multi-expert decision-making, IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 31, 2, pp. 227-234, (2001); Herrera F., Herrera-Viedma E., Martinez L., A fuzzy linguistic methodology to deal with unbalanced linguistic term sets, IEEE Transactions on Fuzzy Systems, 16, 2, pp. 354-370, (2008); Wei G.W., GRA-based linear-programming methodology for multiple attribute group decision making with 2-tuple linguistic assessment information, Information-an International Interdisciplinary Journal, 14, 4, pp. 1105-1110, (2011); Chen Y.J., An approach to evaluating the quality of public physical education class in universal institutions of higher learning with intuitionistic fuzzy information, Information: An International Interdisciplinary Journal, 15, 10, pp. 3917-3922, (2012); Wei G.W., Extension of TOPSIS method for 2-tuple linguistic multiple attribute group decision making with incomplete weight information, Knowledge and Information Systems, 25, 3, pp. 623-634, (2010); Wei G., Some generalized aggregating operators with linguistic information and their application to multiple attribute group decision making, Computers & Industrial Engineering, 61, 1, pp. 32-38, (2011); Xu Z.S., Uncertain linguistic aggregation operators based approach to multiple attribute group decision making under uncertain linguistic environment, Information Science, 168, 3, pp. 171-184, (2004); Xu Z.S., Induced Uncertain Linguistic OWA Operators Applied to Group Decision Making, Information Fusion, 7, 2, pp. 231-238, (2006); Xu Z.S., An approach based on the uncertain LOWG and induced uncertain LOWG operators to group decision making with uncertain multiplicative linguistic preference relations, Decision Support Systems, 41, 2, pp. 488-499, (2006); Xu Z.S., On the method of multi-attribute group decision making under pure linguistic information, China Journal of Control and Decision, 19, 7, pp. 778-782, (2004); Xu Z.S., Correlated linguistic information aggregation, International Journal of Uncertainty, Fuzziness and Knowledge-based Systems, 17, 5, pp. 633-647, (2009); Chen D.W., Grey Fuzzy Set Introduction, (1994); Liu P.D., Fang J., The multi-attribute group decision making method based on the interval grey linguistic variables, African Journal of Business Management, 4, 17, pp. 3708-3715, (2010); Liu P.D., Zhang X., The multi-attribute group decision making method based on the interval grey linguistic variables weighted geometric aggregation operator, Control and Decision, 26, 5, pp. 743-747, (2011)","J. Gao; School of Information Science and Engineering, Northeastern University, Shenyang, Liaoning, 110004, China; email: summergj@l26.com",{"$nulls":7},1.3448994E7,null,null,null,"English","Information","Article","Final",null,"Scopus","2-s2.0-84869456001"]
["Bazan E.; Jaber M.Y.; El Saadany A.M.A.","Bazan, Ehab (56511641900); Jaber, Mohamad Y. (57203764536); El Saadany, Ahmed M.A. (6504052384)","56511641900; 57203764536; 6504052384","Carbon emissions and energy effects on manufacturing-remanufacturing inventory models",2015.0,"Computers and Industrial Engineering",88.0,null,4097.0,307.0,316.0,9.0,132.0,"10.1016/j.cie.2015.07.002","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84938906540&doi=10.1016%2fj.cie.2015.07.002&partnerID=40&md5=30467738b33172753966bd169b14a31c","Department of Mechanical and Industrial Engineering, Ryerson University, Toronto, M5B 2K3, ON, Canada; Independent Scholar, Toronto, ON, Canada","Bazan E., Department of Mechanical and Industrial Engineering, Ryerson University, Toronto, M5B 2K3, ON, Canada; Jaber M.Y., Department of Mechanical and Industrial Engineering, Ryerson University, Toronto, M5B 2K3, ON, Canada; El Saadany A.M.A., Independent Scholar, Toronto, ON, Canada","Abstract Reverse logistics is inevitable in today's business environment with the most common reasons being product returns, incorrect product delivery, damaged products, and product exchange programs. The use and adoption of reverse logistics has increased with the start of product recalls, but the rise of e-commerce and insight into the positive environmental impact has elevated the formal use and sophistication of reverse logistics. There are many environmental issues that may arise from the production and transportation of products. The focus of this study is to evaluate supply chain environmental implications presented in a reverse logistic setting. These environmental contributions come with associated costs that can no longer be ignored in the mathematical modeling of reverse logistics. The model developed in this paper considers energy used for manufacturing and remanufacturing as well as greenhouse gas emissions from manufacturing, remanufacturing and transportation activities with emissions penalty tax as per The European Union Emissions Trading System. The objective of the model is to develop a total cost function that is minimized by determining the following: the manufacturing batch size per cycle, the number of manufacturing batches per cycle, the number of remanufacturing batches per cycle, and the number of times an item may be remanufactured. Numerical examples are provided. The results show that optimizing for financial costs and all the environmental costs collectively promotes less remanufacturing to protect the environment as opposed to just focusing on solid waste disposal, which has been the focus of previous 'traditional' reverse logistics models that consider remanufacturing. In addition, the results show the need to increase the recollection of available used products that can be remanufactured. The proposed model is seen as a preliminary step into developing an environmentally responsible reverse logistics inventory model. © 2015 Elsevier Ltd.","Energy; Green supply chains; Greenhouse gas emissions; Remanufacturing; Reverse logistics","Carbon; Cost functions; Costs; Environmental impact; Environmental protection; Environmental regulations; Gas emissions; Greenhouse gases; International law; Inventory control; Ionization of gases; Manufacture; Supply chains; Waste disposal; Energy; Environmental contributions; Environmental implications; Environmentally responsible; Green supply chain; Production and transportations; Remanufacturing; Reverse logistics; Logistics",{"$nulls":4},"Natural Sciences and Engineering Research Council of Canada, NSERC","The authors thank the Natural Sciences and Engineering Research Council (NSERC) of Canada for supporting their research.  ","Bazan E., Jaber M.Y., Zanoni S., Supply chain models with greenhouse gases emissions, energy usage and different coordination decisions, Applied Mathematical Modelling, 39, 17, pp. 5131-5151, (2015); Bei W., Linyan S., A review of reverse logistics, Applied Sciences, 7, pp. 16-29, (2005); Bishop P.L., Pollution prevention: A new paradigm for engineering education, Environmental challenges, pp. 505-515, (2000); Bogaschewsky R., Natürliche Umwelt und Produktion, (1995); Bonney M., Jaber M.Y., Environmentally responsible inventory models: Non-classical models for a non-classical era, International Journal of Production Economics, 133, pp. 43-53, (2011); Bostel N., Dejax P., Lu Z., The design, planning, and optimization of reverse logistics networks, Logistics systems: Design and optimization, pp. 171-212, (2005); Bozorgi A., Pazour J., Nazzal D., A new inventory model for cold items that considers costs and emissions, International Journal of Production Economics, 155, pp. 114-125, (2014); Boustani A., Sahni S., Gutowski T., Graves S., Tire remanufacturing and energy savings, (2010); De Brito M.P., Dekker R., A framework for reverse logistics, Reverse logistics, pp. 3-27, (2004); Devoldere T., Dewulf W., Deprez W., Willems B., Duflou J.R., Improvement potential for energy consumption in discrete part production machines, Advances in life cycle engineering for sustainable manufacturing businesses, pp. 311-316, (2007); Dietmair A., Verl A., A generic energy consumption model for decision making and energy efficiency optimisation in manufacturing, International Journal of Sustainable Engineering, 2, pp. 123-133, (2009); Dobos I., Richter K., A production/recycling model with stationary demand and return rates, Central European Journal of Operations Research, 11, pp. 35-46, (2003); Dobos I., Richter K., An extended production/recycling model with stationary demand and return rates, International Journal of Production Economics, 90, 3, pp. 311-323, (2004); Dowlatshahi S., Developing a theory of reverse logistics, Interfaces, 30, pp. 143-155, (2000); El Saadany A.M.A., Jaber M.Y., The EOQ repair and waste disposal model with switching costs, Computers & Industrial Engineering, 55, pp. 219-233, (2008); El Saadany A.M.A., Jaber M.Y., A production/remanufacturing inventory model with price and quality dependent return rate, Computers & Industrial Engineering, 58, pp. 352-362, (2010); El Saadany A.M.A., Jaber M.Y., A production/remanufacture model with returns' subassemblies managed differently, International Journal of Production Economics, 133, pp. 119-126, (2011); El Saadany A.M.A., Jaber M.Y., Bonney M., Environmental performance measures for supply chains, Management Research Review, 34, pp. 1202-1221, (2011); El Saadany A.M.A., Jaber M.Y., Bonney M., How many times to remanufacture?, International Journal of Production Economics, 143, pp. 598-604, (2013); Fleischmann M., Reverse logistics network structures and design, (2001); Fleischmann M., Bloemhof-Ruwaard J.M., Dekker R., Van Der Laan E., Van Nunen J.A.E.E., Van Wassenhove L.N., Quantitative models for reverse logistics: A review, European Journal of Operational Research, 103, pp. 1-17, (1997); Gulsun B., Biyik G., Ozgen D., Reverse logistics: A survey, 10th international research/expert conference TMT 2006, 11-15 September, pp. 569-572, (2006); Gurtu A., Jaber M.Y., Searcy C., Impact of fuel price and emissions on inventory policies, Applied Mathematical Modelling, 39, 3, pp. 1202-1216, (2015); Hasanov P., Jaber M.Y., Zolfaghari S., Production, remanufacturing and waste disposal models for the cases of pure and partial backordering, Applied Mathematical Modelling, 36, pp. 5249-5261, (2012); Hua G., Cheng T.C.E., Wang S., Managing carbon footprints in inventory management, International Journal of Production Economics, 132, pp. 178-185, (2011); I.P.C.C., 2006 IPCC guidelines for national greenhouse gas inventories, (2006); Jaber M.Y., El Saadany A.M.A., The production, remanufacture and waste disposal model with lost sales, International Journal of Production Economics, 120, pp. 115-124, (2009); Jaber M.Y., Glock C.H., El Saadany A.M.A., Supply chain coordination with emissions reduction incentives, International Journal of Production Research, 51, pp. 69-82, (2013); Jaber M.Y., Goyal S.K., Coordinating a three-level supply chain with multiple suppliers, a vendor and multiple buyers, International Journal of Production Economics, 116, 1, pp. 95-103, (2008); Kaygusuz K., Energy and environmental issues relating to greenhouse gas emissions for sustainable development in Turkey, Renewable and Sustainable Energy Reviews, 13, pp. 253-270, (2009); Kruger J., Pizer W.A., The EU emissions trading directive: Opportunities and potential pitfalls, resources for the future, (2004); Li W., Kara S., An empirical model for predicting energy consumption of manufacturing processes: A case of turning process, Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 225, pp. 1636-1646, (2011); Matar N., Jaber M.Y., Searcy C., A reverse logistics inventory model for plastic bottles, International Journal of Logistics Management, 25, pp. 315-333, (2014); Mouzon G., Yildirim M.B., A framework to minimise total energy consumption and total tardiness on a single machine, International Journal of Sustainable Engineering, 1, pp. 105-116, (2008); Narita H., Environmental burden analyzer for machine tool operations and its application, (2012); Richter K., The extended EOQ repair and waste disposal model, International Journal of Production Economics, 45, pp. 443-447, (1996); Schrady D.A., A deterministic inventory model for reparable items, Naval Research Logistics Quarterly, 14, pp. 391-398, (1967); Sheu J.-B., Chen Y.J., Impact of government financial intervention on competition among green supply chains, International Journal of Production Economics, 138, pp. 201-213, (2012); Sundin E., Lee H.M., In what way is remanufacturing good for the environment?, Design for innovative value towards a sustainable society, pp. 552-557, (2012); Rogers D.S., Tibben-Lembke R.S., Going backwards: Reverse logistics trends and practices, 2, (1999); Remanufactured goods: an overview of the US and global industries, markets, and trade, USITC Publication, 4356, pp. 332-525, (2012); Wahab M.I.M., Mamun S.M.H., Ongkunaruk P., EOQ models for a coordinated two-level international supply chain considering imperfect items and environmental impact, International Journal of Production Economics, 134, pp. 151-158, (2011); Zanoni S., Mazzoldi L., Jaber M.Y., Vendor-managed inventory with consignment stock agreement for single vendor-single buyer under the emission-trading scheme, International Journal of Production Research, 52, pp. 20-31, (2014)",null,null,"Elsevier Ltd",{"$nulls":5},3608352.0,null,"CINDD",null,"English","Comput Ind Eng","Article","Final",null,"Scopus","2-s2.0-84938906540"]
["Mishra S.; Mathew P.M.","Mishra, Sita (55463285700); Mathew, Priya Mary (57212543903)","55463285700; 57212543903","Analyzing perceived risks and website attributes in E-retailing: A study from India",2013.0,"Journal of Internet Banking and Commerce",18.0,2.0,{"$nulls":4},6.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-84885161297&partnerID=40&md5=ab5964b76097afd844306e17f01f92b0","Institute of Management Technology, Ghaziabad (U.P.), Rajnagar, Hapur Road, India; Business and Technology Department, Pearl Academy, Naraina Industrial Area, Naraina, New Delhi, Phase II, CH Girdhari Lal Marg, India","Mishra S., Institute of Management Technology, Ghaziabad (U.P.), Rajnagar, Hapur Road, India; Mathew P.M., Business and Technology Department, Pearl Academy, Naraina Industrial Area, Naraina, New Delhi, Phase II, CH Girdhari Lal Marg, India","With the Internet users crossing the figure of 150 million in 2012, India is witnessing a more mature growth among the users. The large internet user market despite a low penetration level also suggests that the online market of India has huge business potential. This research study examines the behavior of online consumer in India in terms of internet usage, perceived risks, and website attributes influencing online users. Further, we studied influence of perceived risks on intent to do online purchase in future. A structured questionnaire was administered to 600 online consumers using field and online survey mediums. Results show that Indian online users had high level of perceived risks, highest fear being related to the delivery of products purchased online. Information quality, product range and after online sales service are most preferred website attributes which influence Indian online users. © Sita Mishra and Priya Mary Mathew, 2013.","E-retailing; India; Internet usage; Online shopping; Perceived risks; Website attributes",{"$nulls":7},"Antony S., Lin Z., Xu B., Determinants of escrow service adoption in consumer-to-consumer online auction market: An experimental study, Decision Support Systems, 42, 3, pp. 1889-1900, (2006); Belanger F., Hiller J.S., Smith W.J., Trustworthiness in electronic commerce: The role of privacy, security, and site attributes, Journal of Strategic Information Systems, 11, 3-4, pp. 245-270, (2002); Bellman S., Lohse G.L., Johnson E.J., Predictors of online buying behaviour, Communications of the ACM, 42, 12, pp. 32-38, (1999); Bhatnagar A., Misra S., Rao H.R., On risk, convenience, and internet shopping behaviour, Communications of the ACM, 43, 11, pp. 98-114, (2000); Chang H.H., Chen S.W., The impact of online store environment cues on purchase intention: Trust and perceived risk as a mediator, Online Information Review, 32, 6, pp. 818-841, (2008); Chaudhuri A., Holbrook M., The chain of effects from brand trust and brand affect to brand performance: The role of brand loyalty, Journal of Marketing, 65, 2, pp. 81-93, (2001); Chen S., Chang T., A descriptive model of online shopping process: Some empirical results, International Journal of Service Industry Management, 14, 5, pp. 556-569, (2003); Cheng J.M., Wang E.S., Lin J.Y., Vivek S.D., Why do customers utilize the internet as a retailing platform?: A view from consumer perceived value, Asia Pacific Journal of Marketing and Logistics, 21, 1, pp. 144-160, (2009); Choi J., Lee K.H., Risk perception and e-shopping: A cross cultural study, Journal of Fashion Marketing and Management, 7, 1, pp. 49-64, (2003); Citrin A.V., Sprott D.E., Silverman S.N., Adoption of Internet shopping: The role of consumer innovativeness, Industrial Management & Data Systems, 100, 7, pp. 294-300, (2000); State of E-commerce In India, (2012); Cox D.F., Rich S.U., The Influence of Perceived Product risk on Consumers' e-tailer shopping preference, Journal of Business Psychology, 22, pp. 55-64, (1964); Constantinides E., Influencing the online consumer's behavior: The web experience, Internet Research, 14, 2, pp. 111-126, (2004); Cunningham L.F., Gerlach J.H., Harper M.D., Young C.E., Perceived risk and the consumer buying process: Internet airline reservations, International Journal of Service Industry Management, 16, 4, pp. 357-372, (1967); Davis F.D., Perceived usefulness, perceived ease of use, and user acceptance of information technology, MIS Quarterly, 13, 3, pp. 318-340, (1989); Demangeot C., Broderick A.J., Conceptualising consumer behaviour in online shopping environments, International Journal of Retail and Distribution Management, 35, 11, pp. 878-894, (2007); Dowling G.R., Staelin R., A model of perceived risk and intended risk-handling activity, Journal of Consumer Research, 21, pp. 119-135, (1986); Fogg B.J., Cathy S., Danielsen D., Marable L., Stanford J., Tauber E.R., How do users evaluate the credibility of Web sites?: A study with over 2,500 participants, Proceedings of the 2003 Conference On Designing For User Experiences, pp. 1-15, (2003); Forsythe S.M., Shi B., Consumer patronage and risk perceptions in internet shopping, Journal of Business Research, 56, 11, pp. 867-875, (2003); Gefen D., Rose G.M., Warkentin M., Pavlou P.A., Cultural Diversity and Trust in IT Adoption: A Comparison of Potential e-Voters in the USA and South Africa, Journal of Global Information Management, 13, 1, pp. 54-78, (2005); Grazioli S., Jarvenpaa S., Perils of Internet fraud: An empirical investigation of deception and trust with experienced Internet consumers, IEEE Transactions On Systems, Man, and Cybernetics, 30, 4, pp. 395-410, (2000); Hahn K.H., Kim J., The effect of offline brand trust and perceived internet confidence on online shopping intention in the integrated multi-channel context, International Journal of Retail and Distribution Management, 37, 2, pp. 126-141, (2009); Hannah B., Lybecker K.M., Determinants of Recent Online Purchasing and the Percentage of Income Spent Online, International Business Research, 3, 4, pp. 60-71, (2010); Online Shopping Touched New Heights In India In 2012, (2012); Hoffman D.L., Novak T.P., Peralta M., Building consumer trust online, Communications of the ACM, 42, 4, pp. 80-85, (1999); Internet In India, Internet and Mobile Association of India, (2010); B2C Global E-Commerce Overview, (2012); Jarvenpaa S.L., Tractinsky N., Consumer Trust in an Internet Store: A Cross-Cultural Validation, Journal of Computer-Mediated Communication, 5, 2, pp. 1-35, (1999); Korgaonkar P., Wolin L.D., Web usage, advertising, and shopping: Relationship patterns, Internet Research: Electronic Networking Applications and Policy, 12, 2, pp. 191-204, (2002); Kotha S., Rajgopal S., Venkatachalam M., The role of online buying experience as a competitive advantage: Evidence from third-party ratings for e-commerce firms, Journal of Business, 77, 2, pp. 109-133, (2004); Kuhlmeier D., Knight G., Antecedents to internet-based purchasing: A multinational study, International Marketing Review, 22, 4, pp. 460-473, (2004); Li N., Zhang P., Consumer online shopping attitudes and behavior: An assessment of research, Proceedings of 8th Americas Conference On Information System, pp. 508-517, (2002); Liebermann Y., Stashevsky S., Perceived risks as barriers to internet and e-commerce usage, Qualitative Market Research: An International Journal, 5, 4, pp. 291-300, (2002); Lim N., Consumers' perceived risks: Sources versus consequences, Electronic Commerce Research and Applications, 2, 3, pp. 216-228, (2003); Loebbecke C., E-business trust concepts based on seals and insurance solutions, Information Systems and E-business Management, 1, 1, pp. 55-72, (2003); Lohse G., Spiller P., Electronic shopping, Communications of the ACM, 41, 7, pp. 81-87, (1998); Lohse G.L., Bellman S., Johnson E.J., Consumer buying behavior on the internet: Findings from panel data, Journal of Interactive Marketing, 14, 1, pp. 15-29, (2000); McKnight D.H., Choudhury V., Kacmar C., Developing and Validating Trust Measures for e-Commerce: An Integrative Typology, Information Systems Research, 13, 3, pp. 334-359, (2002); Mitchell V., Consumer perceived risk: Conceptualizations and models, European Journal of Marketing, 33, 1-2, pp. 163-195, (1999); Park C., Jun J., A cross-cultural comparison of Internet buying behavior: Effects of Internet usage, perceived risks, and innovativeness, International Marketing Review, 20, 5, pp. 534-553, (2003); Pennanen K., Tiainen T., Luomala H.T., A Qualitative exploration of a consumer's value based e-trust building process, Qualitative Market Research: An International Journal, 10, 1, pp. 28-47, (2007); du Plassis P.J., Mostert P.G., North E.J., Period of Internet Usage: An Indicator of the Buying Behaviour of Internet Users?, South African Journal of Economic and Management Sciences, l7, 1, pp. 75-88, (2004); Ranganathan C., Ganapathy S., Key dimensions of business to consumer web sites, Information and Management, 39, 6, pp. 457-465, (2002); Ratchford B.T., Talukdar D., Lee M.S., A Model of Consumer Choice of the Internet as an Information Source, International Journal of Electronic Commerce, 5, 3, pp. 7-22, (2001); Ruyter K., Wetzels M., Kleijnen M., Customer Adoption of E-Service: An Experimental Study, International Journal of Service Industry Management, 12, 2, pp. 184-208, (2001); Shim S., Eastlick M.A., Lotz S.L., Warrington P., An Online Purchase Intention Model: The Role Of Intention To Search, Journal of Retailing, 77, 3, pp. 397-416, (2001); Szymanski D., Hise R., E-Satisfaction: An initial examination, Journal of Retailing, 76, 3, pp. 309-322, (2000); Wolfinbarger M., Gilly M., Shopping online for freedom, control, and fun, California Management Review, 43, 2, pp. 34-55, (2001); Zhang P., von Dran G.M., Satisfiers and Dissatisfiers: A Two-Factor Model for Website Design and Evaluation, Journal of the American Society For Information Science, 51, 14, pp. 1253-1268, (2000); Zhang P., von Dran G.M., Blake P., Pipithsuksunt V., Important Design Features in Different Website Domains: An Empirical Study of User Perceptions, E-Service Journal, 1, 1, pp. 77-91, (2001); Zhou L., Dai L., Zhang D., Online Shopping Acceptance Model -A critical survey of consumer factors in online shopping, Journal of Electronic Commerce Research, 8, 1, pp. 41-62, (2008)",{"$nulls":8},1.2045357E7,null,null,null,"English","J. Internet Bank. Commer.","Article","Final",null,"Scopus","2-s2.0-84885161297"]
["Gomez-Herrera E.; Martens B.; Turlea G.","Gomez-Herrera, Estrella (55120646000); Martens, Bertin (56197295200); Turlea, Geomina (23669627600)","55120646000; 56197295200; 23669627600","The drivers and impediments for cross-border e-commerce in the EU",2014.0,"Information Economics and Policy",28.0,1.0,null,83.0,96.0,13.0,164.0,"10.1016/j.infoecopol.2014.05.002","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84906781001&doi=10.1016%2fj.infoecopol.2014.05.002&partnerID=40&md5=9753f645b1b062f4455dbce3020389c0","Institute for Prospective Technological Studies, Joint Research Centre, European Commission, E-41092 Seville, C/Inca Garcilaso 3, Spain","Gomez-Herrera E., Institute for Prospective Technological Studies, Joint Research Centre, European Commission, E-41092 Seville, C/Inca Garcilaso 3, Spain; Martens B., Institute for Prospective Technological Studies, Joint Research Centre, European Commission, E-41092 Seville, C/Inca Garcilaso 3, Spain; Turlea G., Institute for Prospective Technological Studies, Joint Research Centre, European Commission, E-41092 Seville, C/Inca Garcilaso 3, Spain","The rise of the internet is often associated with the \"death of distance\" or at least the decreasing relevance of geographical distance in the supply of information. We investigate whether distance still matters for online trade in physical goods. We use data from an online consumer survey panel on online cross-border trade in goods in a linguistically fragmented EU market. The analysis confirms that distance-related trade costs are greatly reduced compared to offline trade in the same goods. However, language-related trade costs increase. Moreover, online trade introduces new sources of trade costs such as parcel delivery and online payments systems. On balance, there are no indications that online trade is less biased in favour of home market products than offline trade. We examine options available to policy makers to boost cross-border e-commerce in the EU Digital Single Market. A 1% increase in the use of efficient and flexible cross-border payment systems could increase cross-border e-commerce by as much as 7%. We also show that online trade gives a comparative advantage to English-language exporting countries. © 2014 Elsevier B.V.","E-commerce; European Union; Gravity equation","Cost benefit analysis; Costs; Electronic commerce; Online systems; Comparative advantage; Cross-border trades; European union; Market products; On-line payment; Online consumers; Parcel delivery; Payment systems; border region; electronic commerce; European Union; gravity survey; international trade; Internet; policy making; International trade",{"$nulls":6},"Anderson J., Van Wincoop E., Gravity with gravitas: a solution to the border puzzle, Am. Econ. Rev., 93, pp. 170-192, (2003); Baier S.L., Bergstrand J.H., Estimating the effects of free trade agreements on international trade flows using matching econometrics, J. Int. Econ., 77, pp. 63-76, (2009); Berthelon M., Freund C., On the conservation of distance in international trade, J. Int. Econ., 75, pp. 310-320, (2008); Blum B., Goldfarb A., Does the internet defy the law of gravity, J. Int. Econ., 70, pp. 384-405, (2006); Cairncross F., The Death of Distance; How the Communications Revolution will Change Our Lives, (1997); (2011); (2011); Coughlin C., Novy D., Is the International Border Effect Larger than the Domestic Border Effect: Evidence from US Trade, Research Article Series 2009/29, (2009); Disdier A., Head K., The puzzling persistence of the distance effect on bilateral trade, Rev. Econ. Stat., 90, pp. 37-48, (2008); (2011); (2012); Feenstra R.C., Border effects and the gravity equation: consistent methods for estimation, Scot. J. Polit. Econ., 49, pp. 491-506, (2002); Frankel J., Wei S.J., Trading blocks and the Americas, J. Dev. Econ., 47, pp. 61-96, (1995); Freund C., Weinhold D., The effect of the internet on international trade, J. Int. Econ., 62, pp. 171-189, (2000); Helpman E., Melitz M., Rubinstein Y., Estimating trade flows: trading partners and trading volumes, Q. J. Econ., 123, pp. 441-487, (2008); Hortacsu A., Martinez-Jerez F., Douglas J., The geography of trade in online transactions: evidence from eBay and Mercado Libre, Am. Econ. J., 1, pp. 53-74, (2009); Kuwamori H., The role of distance in determining international transport costs: evidence from Philippine import data, (2006); Lendle A., Olarreaga M., Schropp S., Vezina P.L., There goes gravity: how eBay reduces trade costs, (2012); Martinez-Zarzoso I., Nowak-Lehmann D., Is distance a good proxy for transport costs? The case of competing transport modes, J. Int. Trade and Econ Dev., 16, pp. 411-434, (2007); McCallum J., National borders matter: Canada-US regional trade patterns, Am. Econ. Rev., 85, pp. 615-623, (1995); Meschi M., Irving T., Gillespie M., Intra-Community Cross-Border Parcel Delivery, (2011); Pacchioli C., Is the EU internal market suffering from an integration deficit?, (2011); Rauch J., Networks versus markets in international trade, J. Int. Econ., 48, pp. 7-35, (1999); Santos Silva J.M.C., Tenreyro S., The log of gravity, Rev. Econ. Stat., 88, pp. 641-658, (2006); Shepotylo O., Gravity with zeros: estimating trade potential of CIS countries, (2009); Wolf H., International home bias in trade, Rev. Econ. Stat., 84, pp. 555-563, (2000)","E. Gomez-Herrera; Institute for Prospective Technological Studies, Joint Research Centre, European Commission, E-41092 Seville, C/Inca Garcilaso 3, Spain; email: estrellagh@gmail.com",null,"Elsevier",{"$nulls":5},1676245.0,null,"IEPOD",null,"English","Inf. Econ. Policy","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-84906781001"]
["Li Y.; Fan K.; Wen J.; Ma N.","Li, Yuanyuan (57192523236); Fan, Kun (23110501600); Wen, Jiwen (15521325700); Ma, Ning (58592333600)","57192523236; 23110501600; 15521325700; 58592333600","The research on influencing factors of forest farmers' intention of adopting online trading based on logistic regression model",2012.0,"Advances in Information Sciences and Service Sciences",4.0,22.0,null,658.0,665.0,7.0,2.0,"10.4156/AISS.vol4.issue22.82","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84871357313&doi=10.4156%2fAISS.vol4.issue22.82&partnerID=40&md5=f0d885f5a806993ef83ac4063303e778","School of Economics and Management, Beijing Forestry University, China","Li Y., School of Economics and Management, Beijing Forestry University, China; Fan K., School of Economics and Management, Beijing Forestry University, China; Wen J., School of Economics and Management, Beijing Forestry University, China; Ma N., School of Economics and Management, Beijing Forestry University, China","Forestry e-commerce is a new research area for many countries. This paper investigates the influencing factors of forest farmers' intention of adopting online trading by investigating 177 farmers who lived in the typical forest rural area in China. The Theory of Reasoned Action (TRA) and Technology Acceptance Model (TAM) were used to design the questionnaire, and Logistic regression model was proposed to study the influencing factors. In addition, the descriptive statistics of forest farmers' network adoption are analyzed. The results indicate that perceived usefulness, perceived ease of use and environment factor have positive effects, while awareness of self-ability and concerns factors produce negative effects. Some policies and suggestions are put forward at the end.","Forestry e-commerce; Logistic regression; TAM","Commerce; Forestry; Forests; Materials Handling; Regression Analysis; Transport; Electronic commerce; Logistics; Regression analysis; Rural areas; Timber; Descriptive statistics; Environment factors; Logistic regression models; Logistic regressions; Online trading; Perceived ease of use; Perceived usefulness; TAM; Technology acceptance model; Theory of reasoned action; Forestry",{"$nulls":6},"Zazueta F.S., Using the Internet for agricultural business, Engineering and Technology for Sustainable World, 3, 5, pp. 10-12, (1996); Rolfe J., Gregor S., Menzies D., Reasons why farmers in Australia adopt the Internet, Electronic Commerce Research and Applications, pp. 27-41, (2002); Batte M.T., Changing computer use in agriculture: Evidence from Ohio, Computers and Electronics in Agriculture, 47, 1, pp. 1-13, (2005); Michailidis A., Partalidou M., Nastis S.A., Papadaki-Klavdianou A., Charatsari C., Who goes online? Evidence of internet use patterns from rural Greece, Telecommunications Policy, 35, 4, pp. 333-343, (2011); Wang W., Agricultural E-commerce application mode in China, IEEE International Conference on Information Management and Engineering, pp. 616-619, (2010); Yang H., Zhou P., Study on situation and countermeasures of agricultural E-commerce in Heilongjiang, Proceedings of International Conference on E-Business and E-Government, pp. 7316-7319, (2011); Fan K., Comparative analysis on E-commerce application of agriculture in china, JCIT: Journal of Convergence Information Technology, 6, 7, pp. 210-218, (2011); Ahmed A., Kabir L., Yasuura H., An information platform for low-literate villagers, Proceedings of International Conference on Advanced Information Networking and Applications, pp. 1271-1277, (2010); Huang L.-J., Luo Q.-Q., Yu P., Yu G.-P., Construction of Chinese new rural ecommerce platform and its key technologies research based on double E-markets, Proceedings of International Conference on Mechatronic Science, Electric Engineering and Computer, pp. 2106-2111, (2011); Wen Y.-G., Kang Y.-N., Zang W.-H., The study on Chinese agricultural E-commerce development, Advances in Intelligent and Soft Computing, 114, pp. 207-213, (2012); Wang H.-P., Huo Y.-F., Explore the topology nature of opinion network of China farmer's adoption of mobile commerce, ICIC Express Letters, 6, 1, pp. 185-192, (2012); Huo Y.-F., Zhang B., Ma L., Zhang P., The M-commerce service influence the consumption network of Chinese farmers, ICIC Express Letters, 5, 6, pp. 1899-1906, (2011); Huo Y.-F., Zhang B., Ma L., Zhang P., The influencing factors of Chinese farmers adopt M-Commerce services: Social network perspective, International Journal of Innovative Computing, Information and Control, 7, 6, pp. 3559-3570, (2011); Wang H.-P., Huo Y.-F., The worm diffusion mechanism of the Chinese farmer's adoption behavior of mobile E-commerce under social network perspective, ICIC Express Letters, 5, 1, pp. 1-6, (2011); Shook S.R., Zhang Y., Braden R., Baldridge J., The use of eBusiness in the Pacific Northwest secondary forest products industry, Forest Products Journal, 52, 1, pp. 59-66, (2002); Vlosky R., Punches J., For forest products industry, now is the time for e-business, Wood Technology, 127, 1, (2000); Cheng B.-D., Wang D.-L., Guan H.-L., The trade of Chinese forestry products in electronic commerce environment, Proceedings of International Conference on Industrial and Information Systems, pp. 285-288, (2010); Davis F.D., Perceived usefulness, perceived ease of use, and user acceptance of information technology, MIS Quarterly, 13, 3, pp. 319-340, (1989); Tiwari K.R., Sitaula B.K., Ingrid Nyborg L.P., Paudel G.S., Determinants of farmers' adoption of improved soil conservation technology in a Middle Mountain Watershed of Central Nepal, Environmental Management, 42, 2, pp. 210-222, (2008); Asrat P., Belay K., Hamito D., Determinants of farmers' willingness to pay for soil conservation practices in the southeasterns highlands of Ethiopia, Land Degradation and Development, 15, 4, pp. 423-438, (2004); Bakopoulou S., Polyzos S., Kungolos A., Investigation of farmers' willingness to pay for using recycled water for irrigation in Thessaly region, Greece, Desalination, 250, 1, pp. 329-334, (2010); Chen Z., Zhang X., Li Y., Xi N., Analysis of the factors impacting on rural poverty in the view of transaction cost-based on Logistic regression model, JCIT: Journal of Convergence Information Technology, 7, 14, pp. 478-485, (2012)","K. Fan; School of Economics and Management, Beijing Forestry University, China; email: fankun@bjfu.edu.cn",{"$nulls":7},2.2339345E7,null,null,null,"English","Adv. Inf. Sci. Serv. Sci.","Article","Final",null,"Scopus","2-s2.0-84871357313"]
["Yang J.; Li J.; Chen Y.; Liu X.","Yang, Jianjie (55867109700); Li, Jin (56025151700); Chen, Yun (55868094000); Liu, Xintong (57206740426)","55867109700; 56025151700; 55868094000; 57206740426","Multi-objective distribution model and algorithm for online shopping express logistics",2013.0,"Journal of Computers (Finland)",8.0,10.0,null,2558.0,2564.0,6.0,4.0,"10.4304/jcp.8.10.2558-2564","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84884745719&doi=10.4304%2fjcp.8.10.2558-2564&partnerID=40&md5=4b3ae7dfe94eb91671117c938770f9a2","School of Computer Science and Information Engineering, Zhejiang Gongshang University, Hangzhou, China; Contemporary Business and Trade Research Center of Zhejiang Gongshang University, Hangzhou, China","Yang J., School of Computer Science and Information Engineering, Zhejiang Gongshang University, Hangzhou, China; Li J., School of Computer Science and Information Engineering, Zhejiang Gongshang University, Hangzhou, China, Contemporary Business and Trade Research Center of Zhejiang Gongshang University, Hangzhou, China; Chen Y., School of Computer Science and Information Engineering, Zhejiang Gongshang University, Hangzhou, China; Liu X., School of Computer Science and Information Engineering, Zhejiang Gongshang University, Hangzhou, China","The multi-objective distribution problem with time windows for online shopping express logistics (OSEDP) is an extension of the vehicle routing problem with time windows (VRPTW). In additional to the time windows, we also take the customers' satisfaction degree (CSD), the cost, and both integrated conditions into consideration. To solve this problem, we design a modified particle swarm optimization algorithm (PSO) which can enhance the quality of the particle evolution and the speed of the original algorithm. This algorithm begins with random solutions, uses the fitness degree as the evaluation function, and searches for optimal solution by the iterative steps. The simulation experimental results also show that the proposed model and algorithm are efficient and effective for online shopping express logistics distribution problem. © 2013 ACADEMY PUBLISHER.","Customers'satisfaction degree; Particle swarm algorithm; Penalty function; Time windows","Algorithms; Computer simulation; Electronic commerce; Iterative methods; Particle swarm optimization (PSO); Problem solving; Vehicle routing; Customers' satisfaction degree; Logistics distribution; Model and algorithms; Modified particle swarm optimization algorithms; Particle swarm algorithm; Penalty function; Time windows; Vehicle routing problem with time windows; Mathematical models",{"$nulls":6},"Dantzig G., Ramser J., The truck dispatching problem, Management Science, 10, 6, pp. 80-91, (1959); Lenstra J.K., Rinnooy A.H.G., Complexity of vehicle routing problem with time windows, Networks, 11, pp. 221-227, (1981); Kyung H., Simulated annealing by grand canonical ensemble and the TSPs, WSEAS Transactions On Computers, 4, 8, pp. 890-897, (2005); Tuzun D., Burkel T., A two-phase tabu search approach to the location routing problem, European Journal of Operational Research, 116, pp. 87-99; Baker M., Barrie A., Yechew, A genetic algorithm for the vehicle routing problem, Computers and Operations Research, 30, 5, pp. 787-800, (2003); Yang S.L., Ma H.W., Gu T.J., Simulated Annealing Algorithm for Vehicle Routing Problem with Time Window under Time-Varying, OR TRANSACTIONS, 14, 3, pp. 83-90, (2010); Pang K.W., An adaptive parallel route construction heuristic for the vehicle routing problem with time windows constraints, Expert Systems With Applications, 38, 9, pp. 11939-11946, (2011); Homberge J., Gehring H., A two-phase hybrid metaheuristic for the vehicle routing problem with time windows, European Journal of Operational Research, 162, 1, pp. 220-238, (2005); Najera A.G., Bullinaria J.A., An improved multi-Objective evolutionary algorithm for the vehicle routing problem with time windows, Computers & Operations Research, 38, pp. 287-300, (2011); Mester D., Braysy O., Active guided evolution strategies for large-scale vehicle routing problems with time windows, Computers & Operations Research, 32, pp. 1593-1614, (2005); Ren C.Y., Research on single and mixed fleet strategy for open vehicle routing problem, Journal of Software, 6, 10, pp. 2076-2081, (2011); Wang J.W., Zhu R.B., Efficient intelligent optimized algorithm for dynamic vehicle routing problem, Journal of Software, 6, 11, pp. 2201-2208, (2011); Ren Y.C., Xing T., Song H.J., Chen X.J., Urban delivery distribution routing optimizing key technology based on web GIS, Journal of Software, 6, 6, pp. 1103-1109, (2011); Li J., Research on team orienteering problem with dynamic travel times, Journal of Software, 7, 2, pp. 249-255, (2012); Li J., Fu P.H., Label correcting algorithm for dynamic tourist trip planning, Journal of Software, 7, (2012)","J. Li; School of Computer Science and Information Engineering, Zhejiang Gongshang University, Hangzhou, China; email: 522679455@qq.com",{"$nulls":7},"1796203X",null,null,null,"English","J. Comput.","Article","Final",null,"Scopus","2-s2.0-84884745719"]
["Satnalika N.","Satnalika, Niraj (57189505445)",5.7189505445E10,"Inorganic growth only route to achieve economies of scale for Indian e-retailers",2016.0,"Journal of Internet Banking and Commerce",21.0,{"$nulls":4},18.0,2.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-84971505157&partnerID=40&md5=82cb7838b55542a45a0a0380d55c14ee","Shailesh J. Mehta School of Management (SJMSOM), IIT Bombay, Maharashtra, India","Satnalika N., Shailesh J. Mehta School of Management (SJMSOM), IIT Bombay, Maharashtra, India","Indian e-retail market has come a long way since inception of leading player, Flipkart, in 2007. The market has tremendous opportunity to grow due to fact that the current penetration of e-retail in overall retail is significantly low and penetration of internet in India is also significantly low. Rising penetration of internet, coupled with increasing use of smartphone, computers will attract the consumers to the online channel. However, price differentiation from traditional retail, offered in the form of discounts by e-retailers will remain the key driver of the growth. Based on a survey it is found that majority of the people will switch back to traditional way of shopping as the look and feel of product is generally not available in online channel despite the benefits provided such as wider portfolio, easy delivery, easy return, convenience, etc. Consumers find discounts and offers as the primary reason for the change in consumer behaviour and shift of channel. On the other hand, the e-retail companies cannot afford to sell the products at heavy discounts as it leads to diseconomies of scale where companies incur heavy investment in logistics and technology and also offer discounts to generate volume. Amidst this, the in-organic style of growth will be an ideal strategy for companies to grow. Growth by mergers and acquisitions (including all forms like forward, backward, or parallel integration) will not only help the company diversify its product portfolio but will also give the companies an upper edge to save on customer acquisition cost, logistic lost, infrastructure development cost, and technology cost. Leading global players like Amazon Inc. adopted a similar strategy to grow in the international market. Amazon Inc. which is one of the leading players in the e-Commerce market acquired 57 companies since 1998 to clock revenue of around USD 89 billion in the year 2014 while its major rival eBay Inc. could reach USD 18 billion in 2014 with 3 acquisitions since 1998. This article covers if a similar paradigm will be seen in the Indian economy too, where the indigenous companies will re-look at their strategies in order to be profitable in the dynamically changing, fastest growing e-Commerce market of India. An early adoption of in-organic growth to scale up operations in the geographically diversified and huge economy like India will only help these players become profitable. Absence of right strategy mix will result in players bleeding and the bubble will eventually burst. © Niraj Satnalika, 2016.","Acquisitions; E-commerce; E-retail; Economies of scale; Global players; Inorganic growth; Strategy; Volume",{"$nulls":7},"Sassen S., Electronic space and power, Journal of Urban Technology, 4, pp. 1-17, (1997); Prithiani R., Satnalika N., Retail business models transforming to survive e-Commerce threat, CRISIL Opinion, (2015); Gereffi G., Shifting governance structures in global commodity chains, with special reference to the Internet, American Behavioural Scientist, 44, pp. 1616-1637, (2001); Esper T., Jensen T., Turnipseed F., Burton S., The last mile: An examination of effects of online retail delivery strategies on consumers, Journal of Business Logistics, 24, pp. 177-203, (2003); Alba J., Lynch J.J., Weitz B., Janiszewski C., Lutz R., Et al., Interactive home shopping: Consumer, retailer, and manufacturer incentives to participate in electronic marketplaces, Journal of Marketing, 61, pp. 38-53, (1997); De Koster R., Distribution strategies for online retailers, IEEE Transactions on Engineering Management, 50, pp. 448-457, (2003); Grewal D., Iyer G., Levy M., Internet retailing: Enablers, limiters and market consequences, J Bus Res, 57, pp. 703-713, (2004); Lee H.L., Whang S., Winning the last mile of E-commerce, Sloan Management Review, 42, pp. 54-62, (2001); Boyer K.K., Hult G., Extending the supply chain - Integrating operations and marketing in the grocery industry, Journal of Operations Management, 23, pp. 642-661, (2005); Ricker F.R., Kalakota R., Order fulfilment: The hidden key to e-Commerce success, Supply Chain Management Review, 11, pp. 60-70, (1999); Rabinovich E., Bailey J.P., Physical distribution service quality in Internet retailing: Service pricing, transaction attributes, and firm attributes, Journal of Operations Management, 21, pp. 651-672, (2004); Clark G.L., Wrigley N., Exit, the firm and sunk costs: Reconceptualising the corporate geography of disinvestment and plant closure, Progress in Human Geography, 21, pp. 338-358, (1997); Leyshon A., Time-space (And digital) compression: Software formats, musical networks and the reorganization of the music industry, Environment and Planning, 33, pp. 49-77, (2001); Rosen K.T., Howard A.L., E-retail: Gold rush or fool’s gold?, California Management Review, 42, pp. 72-100, (2000); Ring L.J., Tigert D.J., The decline and fall of internet grocery retailers, International Journal of Retail and Distribution Management, 28, pp. 417-444, (2001); Thornton J., Marche S., Sorting through the dot bomb rubble: How did the high-profile e-tailers fail?, International Journal of Information Management, 35, pp. 121-138, (2003); Wrigley N., Lowe M.S., Currah A.D., Progress report 2: Retailing and e-tailing, Urban Geography, 23, pp. 180-197, (2002); Murphy A., The Web, the Grocer and the City, pp. 226-230, (2004); Lindholm A., An Economic System of Technology-Related Acquisitions and Spin-offs, ESRC Centre for Business Research, (1996); Dahlstrand A.L., Growth and inventiveness in technology-based spin-off firms, Res Policy, 26, pp. 331-344, (1997); Baumol W.J., Entrepreneurship, innovation and growth: The David-Goliath symbiosis, J. Entrepreneurial Finance, 7, pp. 1-10, (2002); Stigler G.J., Monopoly and oligopoly by merger, Am Econ Rev, 40, pp. 23-34, (1950); Granstrand O., Sjolander S., The acquisition of technology and small firms by large firms, J Econbehav Organ, 13, pp. 367-386, (1990); Hall B.H., The Effect of Takeover Activity on Corporate Research and Development, National Bureau of Economic Research (NBER), (1987); Williamson O.E., Markets and Hierarchies: Analysis and Antitrust Implications, (1975); Bonardo D., Paleari S., Vismara S., The M&A dynamics of European science-based entrepreneurial firms, J Technoltransf, 35, pp. 141-180, (2010); Ahmetoglu G., Furnham A., Fagan P., Pricing practices: A critical review of their effects on consumer perceptions and behavior, J Retail Consum Serv, 21, pp. 696-707, (2014); Sotgiu F., Ancarani F., Exploiting the opportunities of internet and multichannel pricing: An exploratory research, J Prod Brand Manag, 13, pp. 125-136, (2004); Wolk A., Ebling C., Multi-channel price differentiation: An empirical investigation of existence and causes, Int J Res Mark, 27, pp. 142-150, (2010); Paul M., Beckmann J., Channel-based Price Differentiation: Does it Affect Customer Retention and is it Feasible for Mobile Communications Retailers?, American Marketing Association Conference, 23, pp. 133-139, (2012); Darke P., Dahl D., Fairness and discounts: The subjective value of a bargain, J Consum Psychol, 13, pp. 328-338, (2003); Anderson E.T., Simester D.I., Research note-does demand fall when customers perceive that prices are unfair? The case of premium pricing for large sizes, Mark Sci, 27, pp. 492-500, (2008); Wu C.C., Liu Y.F., Chen Y.J., Wang C.J., Consumer responses to price discrimination: Discriminating bases, inequality status, and information disclosure timing influences, J Bus Res, 65, pp. 106-116, (2012); Choi S., Mattila A.S., Perceived fairness of price differences across channels: The moderating role of price frame and norm perceptions, J Mark Theory Pract, 17, pp. 37-47, (2009); Anderson E., Day G.S., Rangan V.K., Strategic channel design, Sloan Manag Rev, 38, pp. 59-69, (1997); Ratchford B.T., Online pricing: Review and directions for research, J Interact Mark, 23, pp. 82-90, (2009); Zhang J., Farris P.W., Irvin J.W., Kushwaha T., Steenburgh T.J., Et al., Crafting Integrated Multichannel Retailing Strategies, J Interact Mark, 24, pp. 168-180, (2010); Jensen T., Kees J., Burton S., Turnipseed F.L., Advertised reference prices in an internet environment: Effects on consumer price perceptions and channel search intentions, J Interact Mark, 17, pp. 20-33, (2003); Mandelker G., Risk and return: The case of merging firms, Journal of Financial Economics, 1, pp. 303-335, (1974); Jensen M.C., Ruback R., The market for corporate control: The scientific evidence, Journal of Financial Economics, 11, pp. 5-50, (1983); Kim E.H., Singal V., Mergers and market power: Evidence from the airline industry, American Economic Review, 83, pp. 549-569, (1993); Mc-Guckin R.H., Nguyen S.V., On productivity and plant ownership change: New evidence from the Longitudinal Research Database, Rand Journal of Economics, 26, pp. 257-276, (1995); King D.R., Slotegraaf R.J., Kesner I., Performance implications of firm resource interactions in the acquisition of R&D-intensive firms, Organization Science, 19, pp. 327-340, (2008); Williamson O.E., The Economic Institutions of Capitalism, (1985); Casciaro T., Piskorski M.J., Power imbalance, mutual dependence, and constraint absorption: A close look at resource dependence theory, Administrative Science Quarterly, 50, pp. 167-199, (2005); Pfeffer J., Merger as a response to organizational interdependence, Administrative Science Quarterly, 17, pp. 382-394, (1972); Meyer K.E., Estrin S., Bhaumik S., Peng M.W., Institutions, resources, & entry strategies in emerging economies, Strategic Management Journal, 30, pp. 61-80, (2009); Company Reports from Securities and Exchange Commission and Registrar of Companies, (2015); Srinvasan A., Rajde S., Satnalika N., It's advantage customers as E-Com players play the price game, CRISIL Opinion, (2014); Prithiani R., Lodha M., Satnalika N., E-tail eats into retail, CRISIL Opinion, (2014)","N. Satnalika; Shailesh J. Mehta School of Management (SJMSOM), IIT Bombay, India; email: m.safari@ut.ac.ir",null,"ARRAY Development (Canada) Inc.",{"$nulls":5},1.2045357E7,null,null,null,"English","J. Internet Bank. Commer.","Article","Final",null,"Scopus","2-s2.0-84971505157"]
["Huang M.-H.; Rust R.T.","Huang, Ming-Hui (55725698900); Rust, Roland T. (7005108007)","55725698900; 7005108007","IT-Related Service: A Multidisciplinary Perspective",2013.0,"Journal of Service Research",16.0,3.0,null,251.0,258.0,7.0,84.0,"10.1177/1094670513481853","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84880991533&doi=10.1177%2f1094670513481853&partnerID=40&md5=7cab5151a1f905e6dff5b8106a07ac9a","Department of Information Management, College of Management, National Taiwan University, Taipei, Taiwan; Robert H. Smith School of Business, University of Maryland, College Park, MD, United States","Huang M.-H., Department of Information Management, College of Management, National Taiwan University, Taipei, Taiwan; Rust R.T., Robert H. Smith School of Business, University of Maryland, College Park, MD, United States","Information technology (IT)-related service is the strategic management of the creation and delivery of service in which information and communication technology (referred to as IT here) plays a substantial role. IT can serve as a facilitator (e.g., facilitates access to customer information and customer communication) or enabler (e.g., enables value cocreation), serves as the context (e.g., mobile phone market or e-commerce), or is itself service (e.g., social networking sites or information goods). There are three essential characteristics of IT-related service-it is information-intensive, customer-centric, and multidisciplinary. IT-related service is information-intensive. The ability to communicate (firm-to-customer, firm-to-firm, and customer-to-customer) anytime, anywhere, and to anyone, is significantly facilitated by the recent technology trends of big data, cloud computing, and mobile and networking platforms. IT-related service is customer-centric. The use of IT, both by firms and by customers, alleviates the common observation that there is a trade-off between customer satisfaction and productivity improvement for service. Customers are able to talk back to firms with their new communication power and firms are better able to cost-efficiently satisfy their customers. The study of IT-related service is thus inherently multidisciplinary involving such fields as marketing, strategic management, computer science/information systems, and operations management/organizational research. The results of the IT-service transformation are that IT blurs the distinction between goods and service; service is becoming more goods-like and goods are acquiring the characteristics of service. The Journal of Service Research special issue on IT-related service brings together all of these elements, and provides rich strategic implications for managers. © The Author(s) 2013.","big data; customer analytics; customer-centric; environmental scanning; information systems; information technology; service; service marketing; service operations; service science; service transformation",{"$nulls":5},"University of Maryland, UMD; National Science Council, NSC"," The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by grants (100-2911-I-002-509, 101-2911-I-002-524, and 102-2911-I-002-502) from the National Science Council, Taiwan, as well as the Center for Excellence in Service at the University of Maryland.","Ba S., Whinston A.B., Zhang H., Understanding the Digital Economy: Data, Tools, and Research, pp. 185-200, (2000); Bieler D., Google Becomes More 'Tangible' by Building its Own High-Broadband Network into the Home, (2012); Scaling Facebook to 500 Million Users and Beyond, (2010); Goldenberg J., Libai B., Muller E., The Chilling Effect of Network Externalities, International Journal of Research in Marketing, 27, 1, pp. 4-15, (2010); Haltiwanger J., Jarmin R.S., Understanding the Digital Economy: Data, Tools, and Research, pp. 13-33, (2000); Hammer M., Mangurian G.E., The Changing Value of Communications Technology, Sloan Management Review, 28, 2, pp. 65-71, (1987); Hoffman K.D., Marketing + MIS = E-Service, Communications of the ACM, 46, 6, pp. 53-55, (2003); Huang M.-H., Wang E.T.G., Information Systems are from Mars, Marketing is from Venus: Aligning the Worldviews for Firm Performance, Decision Sciences, 44, 1, pp. 87-125, (2013); Rand W., Rust R.T., Agent-based Modeling in Marketing: Guidelines for Rigor, International Journal of Research in Marketing, 28, 3, pp. 181-193, (2011); Rust R.T., Huang M.-H., Optimizing Service Productivity, Journal of Marketing, 76, 2, pp. 47-66, (2012); Rust R.T., Huang M.-H., (2011); Shapiro C., Varian H.R., Information Rules: A Strategic Guide to the Network Economy, (1998); Ulaga W., Reinartz W.J., Hybrid Offerings: How Manufacturing Firms Combine Goods and Services Successfully, Journal of Marketing, 75, 6, pp. 5-23, (2011)","M.-H. Huang; Department of Information Management, College of Management, National Taiwan University, Taipei 10617, 1, Sec. 4, Roosevelt Rd., Taiwan; email: huangmh@ntu.edu.tw",{"$nulls":7},1.5527379E7,null,null,null,"English","J. Serv. Res.","Article","Final",null,"Scopus","2-s2.0-84880991533"]
["Yu J.; Subramanian N.; Ning K.; Edwards D.","Yu, Jie (55574203827); Subramanian, Nachiappan (14037699900); Ning, Kun (57193792084); Edwards, David (56763280700)","55574203827; 14037699900; 57193792084; 56763280700","Product delivery service provider selection and customer satisfaction in the era of internet of things: A Chinese e-retailers' perspective",2015.0,"International Journal of Production Economics",159.0,null,null,104.0,116.0,12.0,125.0,"10.1016/j.ijpe.2014.09.031","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84915793308&doi=10.1016%2fj.ijpe.2014.09.031&partnerID=40&md5=4919615864bcc39eda93faa7cd233f3e","Nottingham University Business School China, University of Nottingham Ningbo China, 199 Taikang East Road, Ningbo, Zhejiang, 315 100, China","Yu J., Nottingham University Business School China, University of Nottingham Ningbo China, 199 Taikang East Road, Ningbo, Zhejiang, 315 100, China; Subramanian N., Nottingham University Business School China, University of Nottingham Ningbo China, 199 Taikang East Road, Ningbo, Zhejiang, 315 100, China; Ning K., Nottingham University Business School China, University of Nottingham Ningbo China, 199 Taikang East Road, Ningbo, Zhejiang, 315 100, China; Edwards D., Nottingham University Business School China, University of Nottingham Ningbo China, 199 Taikang East Road, Ningbo, Zhejiang, 315 100, China","In this study we focus on how e-retailers who deal with innovative products in the era of the Internet of Things (IoT) select product delivery service providers to ensure timely and efficient delivery to customers. Based on the asset-process-performance framework, we propose a triadic model that includes e-retailers, product delivery service providers and customers to achieve synergy and customer satisfaction in the era of the IoT. We find that substantive selective criteria should include consideration of product delivery service providers' hard and soft infrastructure. In addition, flexibility is a key criterion that will strengthen the relationship between e-retailers and product delivery service providers to improve the competitiveness of e-retailers as well as to satisfy the customers. We validate the model using data from 148 Taobao e-retailers. Our results indicate that both hard and soft infrastructures have positive influence on flexibility which in turn has a positive impact on customer satisfaction. Indeed, flexibility fully mediates the relationship between hard and soft infrastructures and customer satisfaction. Our theoretical triadic model is one of the first attempts in providing product delivery service providers selection criteria for e-retailers selling innovative products and its influence on customer satisfaction. Our findings provide guidelines for both e-retailers and product delivery service providers to improve their competitiveness. © 2014 Elsevier B.V. All rights reserved.","Customer satisfaction; E-commerce; Product delivery service provider; Triads","Competition; Electronic commerce; Innovation; Internet of Things; Sales; Innovative product; Internet of thing (IOT); Performance frameworks; Product delivery; Selection criteria; Triads; Customer satisfaction",{"$nulls":6},"Ambastha A., Momaya K., Competitiveness of firms: Review of the theory, frameworks and models, Singapore Manage. Rev., 26, 1, pp. 45-61, (2004); Anderson J.C., Gerbing D.W., Structural equation modelling in practice: A review and recommended two-step approach, Psychol. 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["Chen C.-C.; Huang T.-C.; Park J.J.; Yen N.Y.","Chen, Chia-Chen (14218855200); Huang, Tien-Chi (16309511500); Park, James J. (55665406600); Yen, Neil Y. (57209491931)","14218855200; 16309511500; 55665406600; 57209491931","Real-time smartphone sensing and recommendations towards context-awareness shopping",2015.0,"Multimedia Systems",21.0,1.0,null,61.0,72.0,11.0,21.0,"10.1007/s00530-013-0348-7","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84922001887&doi=10.1007%2fs00530-013-0348-7&partnerID=40&md5=7e57961e706caec64656c9f32d53d74b","Department of Management Information Systems, National Chung Hsing University, Taichung, Taiwan; Department of Information Management, National Taichung University of Science and Technology, Taichung, Taiwan; Department of Computer Science and Engineering, Seoul National University of Science and Technology, Seoul, South Korea; School of Computer Science and Engineering, The University of Aizu, Aizuwakamatsu, Japan","Chen C.-C., Department of Management Information Systems, National Chung Hsing University, Taichung, Taiwan; Huang T.-C., Department of Information Management, National Taichung University of Science and Technology, Taichung, Taiwan; Park J.J., Department of Computer Science and Engineering, Seoul National University of Science and Technology, Seoul, South Korea; Yen N.Y., School of Computer Science and Engineering, The University of Aizu, Aizuwakamatsu, Japan","This study investigates a smart environment, namely “Intelligent Shopping-aid Sensing System (iS3)” for online shopping support in the next era by developing a context-aware automated service system. Sensors, radio frequency identification (RFID), are applied for the recognition, collection, and delivery of user contexts. Following the collected contexts from sensors, integrated mining and analysis techniques (i.e., customized clustering analysis and association rules) were implemented for the provision of instant and personal information to users. Information of products, such as locations, specifications, and characteristics can be collected quickly through the deployed RFID reader and display. Moreover, local applications on mobile devices offer real-time interactions between central system and end users. The system is expected to prompt the product promotion, inquiry and online marketing to shopping malls (and related companies as well). In the empirical results, the quality of recommendations with the proposed approach reaches 70 % accuracy rate. The traditional and non-clustering approaches are 56 and 46 %, respectively. This study reduces long-term operation costs of retailers, stimulates service innovation and experience economy and enhances corporate operational performance. © 2013, Springer-Verlag Berlin Heidelberg.","Association rules; Context-awareness; Recommendation system; Smartphone sensing","Association rules; Electronic commerce; Recommender systems; Smartphones; Analysis techniques; Clustering analysis; Context- awareness; Operational performance; Personal information; Quality of recommendations; Real time interactions; Smartphone sensing; Radio frequency identification (RFID)",{"$nulls":4},"National Science Council Taiwan, (101-2622-E-005-016-CC3, 102-2511-S-025-003); National Scientific Council, (102-2410-H-005-064, 102-2622-E-005-014-CC3, NSC 101-2622-E-005-016-CC3, NSC 102-2511-S-025-003)","The authors are grateful for the support of the National Scientific Council (NSC) of the Republic of China (ROC) under Grant No. NSC 101-2622-E-005-016-CC3, NSC 102-2410-H-005-064, NSC 102-2622-E-005-014-CC3, and the partially support under Grant No. NSC 102-2511-S-025-003.","Pine B.J., Gilmore J.H., The experience economy: work is theatre and every business a stage, (1999); Rashvand H.F., Hsiao K.F., Smartphone intelligent applications: a brief review, Multimedia Syst, Published online, (2013); Adams F.G., The e-business revolution and the new economy: economics after the dot-com crash, South-Western Educational Pub, (2003); Bohnenberger T., Jameson J.O., A. 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Mark., 17, 1, pp. 9-24, (2003); Salton G., McGill M.J., Introduction to modern information retrieval, (1983); Van Rijsbergen C.J., Information retrieval, (1979)",null,null,"Springer Verlag",{"$nulls":5},9424962.0,null,"MUSYE",null,"English","Multimedia Syst","Article","Final",null,"Scopus","2-s2.0-84922001887"]
["Al-Nawayseh M.K.; Alnabhan M.M.; Al-Debei M.M.; Balachandran W.","Al-Nawayseh, Mohammad K. (57200550864); Alnabhan, Mohammad M. (55032470500); Al-Debei, Mutaz M. (35753216500); Balachandran, Wamadeva (7005027807)","57200550864; 55032470500; 35753216500; 7005027807","An adaptive decision support system for last mile logistics in e-commerce: A study on online grocery shopping",2013.0,"International Journal of Decision Support System Technology",5.0,1.0,null,40.0,65.0,25.0,29.0,"10.4018/jdsst.2013010103","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84891769052&doi=10.4018%2fjdsst.2013010103&partnerID=40&md5=41a2d652418f6344995617d3a98d668e","Jerash University, Jerash, Jordan; University of Jordan, Amman, Jordan; Brunel University, London, United Kingdom","Al-Nawayseh M.K., Jerash University, Jerash, Jordan; Alnabhan M.M., Jerash University, Jerash, Jordan; Al-Debei M.M., University of Jordan, Amman, Jordan; Balachandran W., Brunel University, London, United Kingdom","Last mile logistics represent one of the most important challenging issues in online grocery shopping. Online customers are expecting high logistical services, demanding convenience, high reliable and on-time delivery services. As such, online retailers have to respond to these expectations by providing convenient logistical services while keeping this process cost efficient as much as possible. This research aims to design an e-commerce logistical decision support system for online grocery shopping in Jordan as a case study from the developing countries. Online grocery retailers are supposed to use this model in order to select the most suitable delivery operating system in the future. To implement and evaluate this model, one of the available routing and scheduling online solutions (i.e. \"My Route Online\") is used to identify, analyse, and compare the cost efficiencies of the available alternative delivery solutions. The system is tested using real data over three different delivery alternatives (i.e. home delivery, delivery point and pickup point) in order to evaluate and compare their cost efficiencies. The findings from the experiments show that there are significant differences amongst the three delivery alternatives on the basis of three KPIs: cost, distance and time. The findings also indicate that the time indicator has more powerful change effect on cost than distance for all delivery alternatives. According to the level of investments online grocery retailers are willing to offer, customer preferences, and the experimental results, it is concluded that pickup point solution is the best logistical strategy for online grocery retailers to start with. Copyright © 2013, IGI Global.","Decision support systems; Developing countries; E-commerce; Last mile logistics; Modelling; Online grocery shopping; Small-to-medium enterprises","Artificial intelligence; Cost effectiveness; Costs; Decision support systems; Developing countries; Electronic commerce; Models; Pickups; Sales; Adaptive decision support system; Customer preferences; Last mile; Logistical services; On-time delivery; Online customers; Online grocery shopping; Routing and scheduling; Logistics",{"$nulls":6},"Akkeren J., Cavaye A.L.M., Factors affecting entry-level internet technology adoption by small business in Australia: An empirical study, Proceedings of the 10th Australasian Conference on Information Systems, pp. 1071-1083, (1999); Al-Debei M.M., Shannak R.O., The current state of e-commerce in Jordan: Applicability and future prospects, Proceedings of the 5th IBIMA Conference on the Internet & Information Technology in Modern Organizations, pp. 457-489, (2005); Al-Nawayseh M., Balachandran, Online grocery shopping in developing countries: Jordanian consumers as case study, International Journal of Social Ecology and Sustainable Development, 3, (2012); Al-Oun S., Available sheep cheese supply chain: Governance system of channels in the Badia of Jordan, Journal of International Food & Agribusiness Marketing, 21, 1, pp. 27-43, (2008); Al-Qirim N., E-commerce innovations in Jordan: Theoretical model development and implications for small businesses, AMCIS 2010 Proceedings, (2010); Auramo J., Aminoff A., Punakivi M., Research agenda for e-business logistics -based on professional opinions, International Journal of Physical Distribution & Logistics Management, 32, 7, pp. 513-531, (2002); Boyer K., Hult T., Extending the supply chain: Integrating operations and marketing in the online grocery industry, Journal of Operations Management, 23, 6, pp. 642-661, (2005); Boyer K., Hult T., Customer behavioural intentions for online purchases: An examination of fulfilment method and customer experience level, Journal of Operations Management, 24, 2, pp. 124-147, (2006); Boyer K.K., Prud'Homme A.M., Chung W., The last-mile challenge: Evaluating the effects of customer density and delivery window patterns, Journal of Business Logistics, 30, 1, pp. 185-201, (2009); Burke R.R., Do you see what I see? The future of virtual shopping, Journal of the Academy of Marketing Science, 25, 4, pp. 352-360, (1997); Chaudhry A., Jordan retail food sector, USDA Foreign Agriculture Service, (2006); Delaney-Klinger K., Boyer K., Frohlich M., The return of online grocery shopping: A comparative analysis of Webvan and Tesco's operational methods, The TQM Journal, 15, 3, pp. 187-196, (2003); (2010); Ghazali E., Mutum D., Mahbob N.A., Exploratory study of buying fish online: Are Malaysians ready to adopt online grocery shopping?, International Journal of Electronic Marketing and Retailing, 1, 1, pp. 67-82, (2006); Goldman A., Adoption of supermarket shopping in a developing country: The selective adoption phenomenon, European Journal of Marketing, 16, 1, pp. 17-26, (1993); Grando A., Gosso M., Electronic commerce and logistics: The last mile dilemma reference framework and simulation, Revista de Administração e Inovação, 2, 2, pp. 77-97, (2006); Jordanpost, (2009); Kamarainen V., The reception box impact on home delivery efficiency in the e-grocery business, International Journal of Physical Distribution & Logistics, 31, 6, pp. 414-426, (2001); Kurnia S., Exploring e-commerce readiness in china: The case of the grocery industry, Proceedings of HICSS, (2008); Kurnia S., Chien J.A.W., Online grocery shopping in Australia, Proceedings of the International Telecommunications Society Asia-Australasian Regional Conference, (2003); MacGregor R.C., Vrazalic L., A basic model of electronic commerce adoption barriers: A study of regional small businesses in Sweden and Australia, Journal of Small Business and Enterprise Development, 12, 4, pp. 510-527, (2005); Ministry of Planning in Jordan, (2011); Ministry of Trade in Jordan, (2011); Mofleh S.I., Wanous M., Strachan P., Developing countries and ICT initiatives: Lessons learnt from Jordan's experience, The Electronic Journal of Information Systems in Developing Countries, 34, 5, pp. 1-17, (2008); Muller-Lankenau C., Klein S., Wehmeyer K., Developing a framework for multi-channel strategies: An analysis of cases from the grocery retail industry, Proceedings of the 17th Bled E-Commerce Conference, pp. 1-19, (2004); O'Connor R., Europe trails US in web grocery shopping, Chain Store Age, 74, 6, pp. 70-72, (1998); Palmer J., Kallio J., Saarinen T., Tinnila M., Tuunainen V.K., Van Heck E., Online grocery shopping around the world: Examples of key business models, Communications of the AIS, 4, 3, pp. 1-44, (2000); Punakivi M., Comparing Alternative Home Delivery Models for E-grocery Business, (2003); Punakivi M., Saranen J., Identifying the success factors in e-grocery home delivery, International Journal of Retail & Distribution Management, 29, 4, pp. 156-163, (2001); Punakivi M., Tanskanen K., Increasing the cost-efficiency of e-fulfilment using shared reception boxes, International Journal of Retail & Distribution Management, 30, 10, pp. 498-507, (2002); Punakivi M., Yrjola H., Holmstrom J., Solving the last mile issue: Reception box or delivery box, International Journal of Physical Distribution & Logistics, 31, 6, pp. 427-239, (2001); Scott J.E., Scott C.H., Online grocery order fulfilment tradeoffs,  Annual International Conference on System Sciences (HICSS), 90, (2008); Tanskanen K., Yrjola H., Holmstrom J., The way to profitable internet grocery retailing-six lessons learned, International Journal of Retail & Distribution Management, 30, 4, pp. 169-178, (2002); Weltevreden J.W.J., B2C e-commerce logistics: The rise of collection and- delivery points in the Netherlands, International Journal of Retail & Distribution Management, 36, 8, pp. 638-660, (2008); Xia X., Huang Y., Zhu H., Consumer logistics tradeoffs in EGS environment, Proceedings of the IEEE International Conference on Logistics Systems and Intelligent Management, (2010); Xu M., Ferrand B., Roberts M., The last mile of e-commerce-unattended delivery from the consumers and eTailers' perspectives, International Journal of Electronic Marketing and Retailing, 2, 1, pp. 20-38, (2008); Yousept I., Li F., Online supermarkets: Emerging strategies and business models in the UK, Proceedings of the 17th Bled ECommerce Conference, pp. 1-22, (2004); Yrjola H., Physical distribution considerations for electronic grocery shopping, International Journal of Physical Distribution & Logistics Management, 31, 10, pp. 746-761, (2001); Yrjola H., Supply Chain Considerations for E-grocery Shopping, (2003)",{"$nulls":8},"1941630X",null,null,null,"English","Int. J. Decis. Support Syst. Technol.","Article","Final",null,"Scopus","2-s2.0-84891769052"]
["Xiao H.; Qian J.; Tang X.","Xiao, Hong (35294471200); Qian, Jingjing (56191929900); Tang, Xingli (56189063800)","35294471200; 56191929900; 56189063800","B2C e-commerce vehicle delivery model and simulation",2013.0,"Information Technology Journal",12.0,20.0,null,5891.0,5895.0,4.0,7.0,"10.3923/itj.2013.5891.5895","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84901778730&doi=10.3923%2fitj.2013.5891.5895&partnerID=40&md5=7e44e4be32f33a0a778e09f166c11cd1","School of Management, Chongqing Jiaotong University, Chongqing, 400074, China","Xiao H., School of Management, Chongqing Jiaotong University, Chongqing, 400074, China; Qian J., School of Management, Chongqing Jiaotong University, Chongqing, 400074, China; Tang X., School of Management, Chongqing Jiaotong University, Chongqing, 400074, China","B2C e-commerce develops quickly in China, mainly for the express logistics. China's national economy has always been growing steady and fast in the recently decades, it provides a good external environment for the development of the express logistics. B2C e-commerce logistics distribution system should be a part of the city logistic, some characteristics of B2C e-commerce logistics services cause logistics distribution to be difficult, such as large quantity, small batch, high timeliness, dispersion and uncertainties and so on. Based on the work about optimization and scheduling of e-commerce vehicles, this study intends to solve the optimization and scheduling of non-fully-loaded delivery vehicles under the constraints of traffic conditions and time window. It should improve the efficiency of the B2C e-commerce delivery. © 2013 Asian Network for Scientific Information.","Business to custom (B2C); Electronic commerce (e-commerce); Logistics; Model; Simulation; Vehicle","Computer simulation; Logistics; Models; Scheduling; Vehicles; Delivery vehicle; External environments; Logistics distribution; Logistics services; National economy; Simulation; Traffic conditions; Vehicle delivery; Electronic commerce",{"$nulls":6},"Golob T.F., Regan A.C., Impacts of information technology on personal travel and commercial vehicle operations: Research challenges and opportunities, Transp. Res. PartC: Emerg. Technol., 9, pp. 87-121, (2001); Haughton M., Isotupa K.P.S., Scheduling commercial vehicle queues at a canada-us border crossing, Transp. Res. Part E: Logist. Transp. Rev., 48, pp. 190-201, (2012); Kim S.H., Sekiyama K., Fukuda T., Pattern adaptive and finger image guided keypad interface for in-vehicle information systems, Int. I. Smart Sensing Intell. Syst, 1, pp. 572-591, (2008); Liu C.L., Lyons A.C., An analysis of third-party logistics performance and service provision, Transp. Res. PartE: Logist. Transp. Rev., 47, pp. 547-570, (2011); Mason S.J., Ribera P.M., Farris J.A., Kirk R.G., Integrating the warehousing and transportation functions of the supply chain, Transp. Res. Part E: Logist. Transp. Rev., 39, pp. 141-159, (2003); Ramanathan R., The moderating roles of risk and efficiency on the relationship between logistics performance and customer loyalty in e-commerce, Transp. Res. PartE: Logist. Transp. Rev., 46, pp. 950-962, (2010); Reijula I., Rosendahl T., Reijula K., Roilas P., Roilas H., Sepponen R., New method to assess service quality in care homes for the elderly, Int. J. Smart Sensing Intell. Syst., 3, pp. 14-26, (2010); Roorda M.J., Cavalcante R., McCabe S., Kwan H., A conceptual framework for agent-based modelling of logistics services, Transp. Res. PartE: Logist. Transp. Rev., 46, pp. 18-31, (2010); Rutner S.M., Gibson B.J., Williams S.R., The impacts of the integrated logistics systems on electronic commerce and enterprise resource planning systems, Transport. Res. Part E: Logist. Transp. Rev., 39, pp. 83-93, (2003); Secomandi N., Comparing neuro-dynamic programming algorithms for the vehicle routing problem with stochastic demands, Comput Operat. Res., 27, pp. 1201-1225, (2000); Tavasszy L.A., Smeenk B., Ruijgrok C.I., A dss for modelling logistic chains in freight transport policy analysis, Int. Trans. Oper. Res., 5, pp. 447-459, (1998); Tong H., Liu P., Study on the congestion controller for time-delay networked control systems with external disturbances, Int. J. Smart Sensing Intell. Syst, 5, pp. 859-878, (2012); VanDuin I.H.R., Tavasszy L.A., Taniguchi E., Real time simulation of auctioning and re-scheduling processes in hybrid freight markets, Transp. Res. Part B: Methodol, 41, pp. 1050-1066, (2007)",null,null,"Asian Network for Scientific Information",{"$nulls":5},1.8125638E7,null,null,null,"English","Inf. Technol. J.","Article","Final",null,"Scopus","2-s2.0-84901778730"]
["Qiuping L.","Qiuping, Lu (57189378269)",5.7189378269E10,"Research on the customer satisfaction in electronic business environment based on DEA method: An empirical analysis",2016.0,"International Journal of Smart Home",10.0,4.0,null,267.0,278.0,11.0,3.0,"10.14257/ijsh.2016.10.4.24","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84969940759&doi=10.14257%2fijsh.2016.10.4.24&partnerID=40&md5=f51d7d944da02adc95c3e662869422e8","Faculty of Economics and Management, Henan Polytechnic Institute, Nanyang, Henan, 473000, China","Qiuping L., Faculty of Economics and Management, Henan Polytechnic Institute, Nanyang, Henan, 473000, China","With the rapid development of the global economy, information technology has impacted obviously on the way of life. However, trust issues became one of the important obstacles hindering the development when B2C e-commerce vigorous development. In this paper, the author analyzes the key factors affecting the development of electronic commerce, then find out the factors that affect customer satisfaction by using DEA method. The result shows that commodity characteristics, service features and website quality are the main factors that influence the customer satisfaction. At the same time, the variance contribution rate of commodity information is 72.57%, and the variance contribution rate of commodity brand is 66.17%. In service features, the variance contribution rate of logistics service is 81.25%. In website quality, the variance contribution rate of layout is 70.84%, and the variance contribution rate of easy operate is 68.13%.On this basis, we put forward relevant policy suggestions. © 2016 SERSC.","Customer satisfaction; DEA method; Electronic business; Service characteristics",{"$nulls":7},"Gebauer H., Paiola M., Edvardsson B., A capability perspective on service business development in small and medium-sized suppliers, Scandinavian Journal of Management, 28, 4, pp. 321-339, (2012); Janita I., Chong W., Barriers of B2B e-Business Adoption in Indonesian SMEs: A Literature Analysis , Procedia Computer Science, 17, pp. 571-578, (2013); Zaridis A.D., Dimosthenis T., Entrepreneurship and SME's Organizational Structure. Elements of a Successful Business, Procedia-Social and Behavioral Sciences, 148, pp. 463-467, (2014); Sinem E.H., Kabadayi Z., Innovation Orientation, Market Orientation and e-Loyalty: Evidence from Turkish e-Commerce Customers, Procedia-Social and Behavioral Sciences, 99, pp. 509-516, (2013); Manjit S., Kristine V., Social Commerce: A Contingency Framework for Assessing Marketing Potential, Journal of Interactive Marketing, 27, pp. 311-323, (2013); Grant K., Edgar D., Risky business: Perceptions of e-business risk by UK small and medium sized enterprises (SMEs), International Journal of Information Management, 34, 2, pp. 99-122, (2014); Savrul M., The Potential of E-commerce for SMEs in a Globalizing Business Environment, Procedia-Social and Behavioral Sciences, 150, pp. 35-45, (2014); Deniss S., Impact of e-environment on SMEs Business Development, Procedia-Social and Behavioral Sciences, 156, pp. 409-413, (2014); Shoki M., Yun L., Zakuan N., Examining Dimensions of Electronic Service Quality for Internet Banking Services, Procedia-Social and Behavioral Sciences, 65, pp. 854-859, (2012); Djelassi S., Decoopman I., Customers' participation in product development through crowd sourcing: Issues and implications, Industrial Marketing Management, 42, 5, pp. 683-692, (2013)","L. Qiuping; Faculty of Economics and Management, Henan Polytechnic Institute, Nanyang, Henan, 473000, China; email: qiuping6862@126.com",null,"Science and Engineering Research Support Society",{"$nulls":5},1.9754094E7,null,null,null,"English","Int. J. Smart Home","Article","Final",null,"Scopus","2-s2.0-84969940759"]
["Syukur A.; Marjuni A.","Syukur, Abdul (55746556500); Marjuni, Aris (36348450200)","55746556500; 36348450200","Design of an intangible-based E-commerce for digital creative industry",2015.0,"International Journal of Applied Engineering Research",10.0,13.0,null,32842.0,32846.0,4.0,2.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-84940177794&partnerID=40&md5=f8214ca2773286d91b55b1e70d4d6119","Dian Nuswantoro University, Semarang 50131, Jawa Tengah, Indonesia","Syukur A., Dian Nuswantoro University, Semarang 50131, Jawa Tengah, Indonesia; Marjuni A., Dian Nuswantoro University, Semarang 50131, Jawa Tengah, Indonesia","Creative industries are an industries that transform an individual intellectual properties into creative economic value by optimizing skills, creativity, and talent. Based on the use intensity of resources and products, creative industry can be divided into tangible and intangible sectors. Tangible creative industries produce a physically products, such as fashion, architectures, crafts, and printing and publishing sectors. While intangible creative industries produce a non-physically products or digital products, such as music, film, movies, television and radio content, software, interactive games, digital design, and many more. Creative industries usually focused to transform individual creativity into the economic value. With the growth of the information and communication technology (ICT) rapidly in recent decades, the growth of creative industries are also increased significantly. Almost all processes in the creative industry value chain, that are: creation, production, distribution, and commercialization were supported by ICT. Creative industry not only tried to find, create, and produce a new ideas and products, but their products must also be distributed and commercialized to get an economic added values. Related to the type of creative industries products, intangible products or digital goods are usually need a special management because of their characteristics. For example, in the digital goods market, there is no need a products delivery to customer physically because customer can download it directly upon payment confirmed. In inventory aspect, the digital content has an eternal characteristic and it can be sold and delivered to customers without limit. This paper presents the design of the use of ICT to support a distribution and commercialization of a digital products in the form of an e-commerce which can meet the buyer and seller needs for transaction satisfaction. © Research India Publications.","Creative industry; Digital goods; Distribution and commercialization; E-commerce; Intangible",{"$nulls":7},"Cunningham S.D., From cultural to creative industries: Theory, industry, and policy implications, J. of Media Research and Resources, pp. 54-65, (2002); Kakiuchi E., Takeuchi K., Creative industries: Reality and potential in Japan, National Graduate Institute for Policy Studies, pp. 1-19, (2014); Kulliki T.-V., Lassur S., Explaining the Change: Creative Industries Policy from the Perspective of Social Innovation. Case of Tallinn, (2013); Development Plan of Indonesia Creative Industry: 2009-2015, (2008); Bhattacharjee S., Gopal R.D., Marsden J.R., Sankaranarayanan R., Digital goods and markets: Emerging issues and challenges, J. of ACM Trans. on Man. Inf. Sys, 2, 2, pp. 8-14, (2011); Rousseau R., Getting Cozy with Your Content, (2015); Wen H.J., Chen H., Hwang H., E-commerce web site design: Strategies and model, Inf. Man.& Comp. Sec, 9, 1, pp. 5-12, (2001); Farooqi M., Dhusia D.K., Emerging Impact of e-Commerce on CRM, Int. J. of Comp. Networks and Wireless Comm, 2, 1, pp. 41-45, (2012); Indrajit R., Indrakshi R., Fair Exchange in e-commerce, J. Of. ACM Sigecom Exchange, 3, 2, pp. 9-17, (2002); Andam Z.R., E-Commerce and E-Business, E-Asian Task Force UNDP - APDIP, (2003); Nanehkaran Y.A., An introduction to electronic commerce, Int. J. Sci. & Tech. Res, 2, 1, pp. 190-193, (2013); Gangeshwer D.K., E-commerce or internet marketing: A business review from Indian context, Int. J. U-. and E-. Serv., Sci. and Tech, 6, 6, pp. 187-194, (2013); Pavlovski C.J., Quentin S.-P., Digital media and entertainment service delivery platform, Proc. of the 1St ACM Int. Workshop on Multimedia Service Composition, pp. 47-54, (2005); Featherman M.S., Wells J.D., The intangibility of e-services: Effect on perceived risk and acceptance, The Data Base for Adv. in Inf. Sys, 41, 2, pp. 110-131, (2010); Erson B.B., Hansen J.V., Lowry P.B., Summers S.L., The application of model checking for securing e-commerce transaction, The ACM Magazine of Communication, 49, 6, pp. 97-101, (2006); Laisuzzaman I.M., Imran N., Nahid A.A., Amin M.Z., Alim M.A., The framework for implementing e-commerce: The role of bank and telecom in Bangladesh, J. Of. Telecommunications, 1, 1, pp. 57-62, (2010); Bandoh F., Bryson K.-M.O., Gyampah K.A., A hybrid decision tree based methodology for event studies and its application to e-commerce initiative announcements, The Data Base for Adv. in Inf. Sys, 44, 1, pp. 78-101, (2013); Zhang J., Cohen R., A framework for trust modeling in multi agent electronic marketplaces with buying advisors to consider varying seller behavior and the limiting of seller bids, J. of ACM Trans. on Intelligent Syst. and Tech, 4, 2, pp. 241-252, (2013); French A.M., Web Development Life Cycle: A New Methodology for Developing Web Applications, J. of Internet Banking and Commerce, 16, 2, pp. 1-11, (2011); Turban E., Bolloju N., Liang T.-P., Social Commerce: An Ecommerce Perspective, Proc. of the Int. Conf. on E. Commerce, pp. 33-42, (2010); Hauswirth M., Jazayeri M., Schneider M., A phase model for e-commerce business models, Proc. of the Hawai’i Int. Conf. on Sys. Sci, pp. 1-10, (2001); Paypal Buyer and Seller Protection [Online]",null,null,"Research India Publications",{"$nulls":5},9734562.0,null,null,null,"English","Int. J. Appl. Eng. Res.","Article","Final",null,"Scopus","2-s2.0-84940177794"]
["Jiang X.","Jiang, Xuehui (57717065300)",5.77170653E10,"Establishment and analysis of the sales model of fresh agriculture food based on business to business e-commerce platform",2015.0,"Advance Journal of Food Science and Technology",9.0,3.0,null,202.0,205.0,3.0,5.0,"10.19026/ajfst.9.1993","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84940731192&doi=10.19026%2fajfst.9.1993&partnerID=40&md5=9ef6faac260a11b179f98c5b97a9275e","Zhengzhou University of Industrial Technology, Zhengzhou, Henan, 451100, China","Jiang X., Zhengzhou University of Industrial Technology, Zhengzhou, Henan, 451100, China","This study introduced the network sales model of agricultural products from the view of business to business e-commerce and analyzed the features, we found the sales model was featured by pattern diversity which was however of low level; the existing e-commerce operation scale of agricultural products is small and the anti-risk capacity is weak; its resource integration capacity is insufficient and thus it can't make full use of the advantages of e-commerce. Based on this, this study established sales chain of fresh agriculture products based on business to business e-commerce, i.e., to trade on the internet; the products are delivered to consumers by third-party according to the delivery of producing area and wholesale market of sales area and then collected by consumers themselves. Meanwhile, we should establish information center of price demand for online trading market and modern refrigeration base of wholesale market, accelerate the development of specialized rural cooperative or industrial company and assure the long-term operation of e-commerce of agricultural products circulation in the future. © Maxwell Scientific Organization, 2015.","Business to business model; E-commerce model; Fresh agricultural products","Agricultural products; Agriculture; Electronic commerce; Industrial refrigeration; Sales; Agriculture products; Business to business; Business-to-business e-commerce; E-commerce model; E-commerce operations; Fresh agricultural products; Industrial companies; Resource integration; Commerce",{"$nulls":6},"Deng C., Long J., Information security of ecommerce, Audit. Financ., 5, pp. 52-53, (2010); Fan L.J., A Review of recent domestic research on agricultural products circulation pattern, Manage. Agric. Sci. Technol., 30, 5, pp. 75-77, (2011); Guo D.M., Lu D.Y., Research on the ecommerce system establishing of fresh agriculture products in central cities-also discussion on the optimization and integration of agricultural organization and structure in city circle of Wuhan, Agr. Econ., 11, pp. 117-119, (2012); Hu J.B., Research on the development of ecommerce of agriculture products: A conception of model, Rural Econ, 11, pp. 111-113, (2011); Li B.Q., Current condition and prospect of ecommerce in China, World Surv. Res., 1, pp. 15-18, (2015); Liu G., Research on innovation of the circulation model of fresh agricultural products based on farmer cooperatives, Bus. Econ. Admin., 8, pp. 5-10, (2013); Lv J.J., Sun S.S., Cold-chain logistics system for fresh agricultural products in metropolis, Guangdong Agric. Sci., 40, 7, pp. 233-236, (2013); Shi Y.F., Zheng X.L., Zhao N., Research on the innovative business model of e-commerce, China Bus. Trade, 6, pp. 133-134, (2012); Sun L., Zhang Y., The evolution and innovation of business to business e-commerce: Empirical analysis based on main business to business platform, Lect. Notes Comput. Sc., 1, pp. 21-24, (2015); Tong H.B., Pan H.H., Research on B2A model of agriculture products circulation in Zhejiang province, Commercial Times, 9, pp. 41-42, (2011); Yan Y., Constraints and strategies of network marketing of fruits, J. Hunan Agric. Univ., Soc. Sci., 13, 6, pp. 28-32, (2012); Yang H.X., Wang J., Study on the ecommerce system for fresh agricultural products in metropolis, Guangdong Agric. Sci., 7, pp. 221-222, (2012); Yang H.X., Zhang M.N., Application of new B2B2C e-commerce model in promoting logistics information management of fresh agricultural products, Hunan Agric. Sci., 13, pp. 123-124, (2012); Yu Y.H., The logistic restriction of fresh agricultural products and relevant improvement strategies, Chinese Market, 6, pp. 10-12, (2011)",null,null,"Maxwell Science Publications",{"$nulls":5},2.0424868E7,null,null,null,"English","Adv. J. Food Sci. Technol.","Article","Final","All Open Access; Green Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-84940731192"]
["Ducret R.","Ducret, Raphaëlle (56235876600)",5.62358766E10,"Parcel deliveries and urban logistics: Changes and challenges in the courier express and parcel sector in Europe - The French case",2014.0,"Research in Transportation Business and Management",11.0,null,null,15.0,22.0,7.0,99.0,"10.1016/j.rtbm.2014.06.009","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84905718293&doi=10.1016%2fj.rtbm.2014.06.009&partnerID=40&md5=617b62df2d7ce650cbca7cb3897897db","Ecole des Mines de Paris, 75006 Paris, 60 blvd Saint Michel, France","Ducret R., Ecole des Mines de Paris, 75006 Paris, 60 blvd Saint Michel, France","The European Courier, Express and Parcel sector, a strategic and dynamic sector involved in globalization, has undergone significant changes during the past fifteen years. CEP players are \"co-evolving\" (evolving together), the sector is consolidating itself, strategy and logistics organizations are converging and a new segment dedicated to urban parcel deliveries has emerged. Thanks to a literature review, interviews of the players of the French CEP sector and urban parcel delivery sector, as well as comparisons with other European countries, this article analyzes the sector's changes, its drivers, and provides an accurate picture, based on examples and figures, of an under-studied sector. The article also highlights some future prospects for the new segment such as the segment's consolidation and the rise of cross-border e-commerce. © 2014 Elsevier Ltd.","European CEP sector; Parcel delivery issues; Urban freight",{"$nulls":7},"Beyer A., Dynamique territoriale des systèmes coopératifs dans le transport, Le cas des réseaux français de messagerie, Les Cahiers Scientifiques du Transport, 36, pp. 113-135, (1999); Browne M., Allen J., Attlassy M., Comparing freight transport strategies and measures in London and Paris, International Journal of Logistics Research and Applications, 10, pp. 205-219, (2007); Cherrett T., Et al., Understanding urban freight activity - Key issues for freight planning, Journal of Transport Geography, 24, pp. 22-32, (2012); Dablanc L., Freight transport, a key for the new urban economy, World Bank, freight transport for development: A policy toolkit, (2009); Dablanc L., City distribution, a key element of the urban economy: Guidelines for practitioners, City distribution and urban freight transport: Multiples perspectives, pp. 201-216, (2011); CEP definition; Diziain D., Gardrat M., Routhier J.-L., Far from the Capitals: What are the relevant city logistics public policies, 13th World Conference on Transport Research (Rio de Janeiro, Brazil, 15-18 July), (2013); Esser K., Kurte J., B2C e-commerce: impact on transport in urban areas, Recent Advances in City Logistics: Proceedings of the 4th International Conference on City Logistics (Langkawi, Malaysia, 12-14 july, 2005), pp. 437-448, (2005); Green paper, an integrated parcel delivery market for the growth of e-commerce in the EU, (2012); Intra-Community cross-border parcel delivery a study for the European commission, (2011); Gevaers R., Van de Voorde E., Vanelslander T., Characteristics and typology of last-mile logistics from an innovation perspective in an urban context, City distribution and urban freight transport: Multiples perspectives, pp. 201-216, (2011); Giuliano G., Et al., NCFRP project 36(05) synthesis of freight research in urban transportation planning, (2013); Grand L., La sous-traitance en transport routier de marchandises: causes, formes, effets, (1999); Gruber J., Kihm A., Lenz B., Technical potential and user requirements for the implementation of electric cargo bikes in courier logistics services, 13th World Conference on Transport Research, (2013); Hesse M., Shipping news: The implications of electronic commerce for logistics and freight transport, Resources, Conservation and Recycling, 36, 3, pp. 211-240, (2002); The Evolution of the European Postal Market since 1997, (2009); Lindholm M., How local authority decision makers address freight transport in the urban area, Procedia - Social and Behavioral Sciences, 39, pp. 134-145, (2012); Lindholm M., Enabling sustainable development of urban freight from local authority perspective, 13th World Conference on Transport Research, (Rio de Janeiro, Brazil, 15-18 July), working paper, (2013); Lindholm M., Urban freight transport from a local authority perspective - A literature review, European Transport, 54, (2013); Maes J., Vanelslander T., The use of bicycle messengers in the logistics chain, concepts further revised, Procedia - Social and Behavioral Sciences, 39, pp. 409-423, (2012); Menge J., Hebes P., Optimization of urban deliveries: Evaluating a courier, express and parcel services pilot project in Berlin, City Distribution and Urban Freight Transport: Multiples Perspectives, pp. 201-216, (2011); Miyatake K., Nemoto T., Efficient network design of a parcel delivery service, 13th World Conference on Transport Research, (Rio de Janeiro, Brazil, July 15-18), (2013); Moati P., La nouvelle révolution commerciale, (2011); Etude Conditions économiques et sociales du transport léger de marchandises en Pays de la Loire, 1, (2008); Delivering the goods: 21st century challenges to urban goods transport, (2003); Patier-Marque D., La logistique dans la ville, (2002); Rotem-Mindali O., Salomon I., The impacts of E-retail on the choice of shopping trips and delivery: Some preliminary findings, Transportation Research Part A: Policy and Practice, 41, 2, pp. 176-189, (2007); Russo F., Comi A., A classification of city logistics measures and connected impacts, Procedia Social and Behavioral Science, 2, pp. 6355-6365, (2010); Savy M., Burnham J., Freight transport and the modern economy, (2013); Taylor M., Hallsworth A., Power relations and market transformation in the transport sector: The example of the courier services industry, Journal of Transport Geography, 8, 4, pp. 237-247, (2000); Visser E.-J., Lanzendorf M., Mobility and accessibility effects of B2C e-commerce: A literature review, Tijdschrift voor Economische en Sociale Geografie, 95, 2, pp. 189-205, (2004); Weltevreden J.-W.-J., Rotem-Mindali O., Mobility effects of B2C and C2C e-commerce in the Netherlands: A quantitative assessment, Journal of Transport Geography, 17, 2, pp. 83-92, (2009)","R. Ducret; Ecole des Mines de Paris, 75006 Paris, 60 blvd Saint Michel, France; email: raphaelle.ducret@mines-paristech.fr",null,"Elsevier Ltd",{"$nulls":5},2.2105395E7,null,null,null,"English","Res. Transport. Bus. Manage.","Article","Final",null,"Scopus","2-s2.0-84905718293"]
["Ma D.","Ma, Dan (35305318500)",3.53053185E10,"Push or pull? A website's strategic choice of content delivery Mechanism",2015.0,"Journal of Management Information Systems",32.0,1.0,null,291.0,321.0,30.0,6.0,"10.1080/07421222.2015.1029400","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84943376848&doi=10.1080%2f07421222.2015.1029400&partnerID=40&md5=9ab5d4fa1141590fb8413c872f4af412","Department of Information Systems and Management, School of Information Systems, Singapore Management University, Singapore","Ma D., Department of Information Systems and Management, School of Information Systems, Singapore Management University, Singapore","Really simple syndication (RSS) technology enables an alternative delivery mechanism for online content. Instead of waiting passively for users to pull online content out, websites can push it to potential users through RSS. This is expected to significantly affect user behavior, website profitability, and market equilibrium. This research uses an economic model to study the impact of RSS adoption and examine whether it increases a website's profit and competitive advantage. The findings are intriguing: they demonstrate that RSS can either increase or decrease website profit. In a competitive context, RSS adoption can actually be a disadvantage; in some cases, it hurts the adopter but benefits the competitor. Moreover, under certain conditions, the first mover will be worse off when the competitor mimics its adoption decision, which discourages the earlier adoption and thus creates an obstacle to using RSS. Derivation of the adoption equilibria in sequential and simultaneous games shows that multiple market outcomes may result. Finally, regardless of whether or not a website operator adopts RSS, it will still benefit by increasing user awareness of RSS technology, but only up to a certain level. Once this critical awareness level has been reached, websites will not gain by continuing to promote RSS to users. As a whole, these results show how technology adoption will have an impact on firm performance and market outcome, and illustrate the complexity of technology adoption strategy in a competitive setting. Copyright © Taylor & Francis Group, LLC.","Competition; E-commerce; Game theory; Information economics; Online content delivery; RSS","Behavioral research; Commerce; Competition; Economics; Electronic commerce; Game theory; Profitability; Websites; Competitive advantage; Delivery mechanism; Economic modeling; Information economics; Market equilibria; On-line contents; Really simple syndication technologies; Technology adoption; RSS",{"$nulls":6},"Bang Y., Lee D.J., Han K., Hwang M., Ahn J.H., Channel capabilities, product characteristics, and the impacts of mobile channel introduction, Journal of Management Information Systems, 30, 2, pp. 101-125, (2013); Blekas A., Garofalakis J., Stefanis V., Use of RSS feeds for content adaptation in mobile web browsing, Proceedings of the 2006 International Cross-Disciplinary Workshop on Web Accessibility (W4A): Building the Mobile Web, 134, pp. 79-85, (2006); Bustos L., Google Reader Dying, But RSS Lives on for Ecommerce; Clemons E.K., Business models for monetizing internet applications and web sites: Experience, theory, and predictions, Journal of Management Information Systems, 26, 2, pp. 15-41, (2009); Cohen H., RSS and E-commerce: A Natural Fit, (2006); Dewan R., Jing B., Seidmann A., Product customization and price competition on the internet, Management Science, 49, 7, pp. 1055-1070, (2003); Dewan R., Freimer M., Consumers prefer bundled add-ins, Journal of Management Information Systems, 20, 6, pp. 99-111, (2003); Dewan R., Freimer M., Zhang J., Management and valuation of advertisement-supported web sites, Journal of Management Information Systems, 19, 3, pp. 87-98, (2002); (2007); Foley J., The Weblog Question, 39, (2005); Garofalakis J., Stefanis V., Using RSS feeds for effective mobile web browsing, Universal Access in the Information Society, 6, 3, pp. 249-257, (2007); Geng X., Lee Y.J., Competing with piracy: A multichannel sequential search approach, Journal of Management Information Systems, 30, 2, pp. 159-184, (2013); Glotzbach R.J., Mohler J.L., Radwan J.E., Syndicated RSS feeds for course information distribution, Journal of Information Technology Education, 7, pp. 163-183, (2008); Granados N.F., Kauffman R.J., Lai H., Lin H., Decommoditization, resonance marketing, and information technology: An empirical study of air travel services amid channel conflict, Journal of Management Information Systems, 28, 1, pp. 39-74, (2011); Guenther K., The web gets pushy, CIO Enterprise Section, 12, 7, pp. 66-67, (1999); Housley S., Advertising in RSS Feeds; Housley S., Financial Companies use RSS Feeds; Hrastnik R., Unleash the Marketing and Publishing Power of RSS. RSS E-Book, (2005); Kapyla T., Niemi I., Lehtola A., Towards an accessible web by applying PUSH technology, Proceedings of the Fourth ERCIM Workshop on User Interfaces for All, 15, pp. 15-17, (1998); Kendall J., Kendall K., Information delivery systems: An exploration of web PULL and PUSH technologies, Communications of the AIS, 1, (1999); Kesmodel D., E-commerce: Really Simple Sale? As RSS Feeds Catch On, Advertisers are Taking Notice, (2005); Kirkpatrick M., The Year in RSS; Lee B.K., Lee W.N., The effect of information overload on consumer choice quality in an on-line environment, Psychology and Marketing, 21, 3, pp. 159-183, (2004); Li J., Wu W.G., RSS made easy: A basic guide for librarians, Medical Reference Services Quarterly, 26, 1, pp. 27-35, (2007); Lin M., Ke X., Whinston A.B., Vertical differentiation and a comparison of online advertising models, Journal of Management Information Systems, 29, 1, pp. 195-236, (2012); Hicks M., Google puts RSS advertising to the test, EWEEK, (2005); Ma D., Use of RSS feeds to push online content to users, Decision Support Systems, 54, pp. 740-749, (2012); Morrissey B., RSS Feeds Becoming Hot Real Estate for Online Ads, (2005); Ning X., Jin H., Wu H., RSS: A framework enabling ranked search on the semantic web, Information Processing and Management, 44, pp. 893-909, (2008); Parker P., Lessons from the Cutting Edge: RSS Advertising, (2005); Quentin J., Gilad R., Sheizaf R., Information overload and the message dynamics of online interaction spaces: A theoretical model and empirical exploration, Information Systems Research, 15, 2, pp. 194-210, (2004); Rajan B., Seidmann A., Dorsey E.R., The competitive business impact of using telemedicine for the treatment of patients with chronic conditions, Journal of Management Information Systems, 30, 2, pp. 127-157, (2013); Reitsma R., The Data Digest: Usage of RSS Feeds, (2013); Ruebeck C.S., Model exit in a vertically differentiated market: Interfirm competition versus intrafirm cannibalization in the computer hard disk drive industry, Review of Industrial Organization, 26, 1, pp. 27-59, (2005); Saucers M.P., Blogging and RSS, (2010); Scoble R., Why Haven't RSS Readers Gain Mass Adoption?; Shaked A., Sutton J., Multiproduct firms and market structure, RAND Journal of Economics, 21, pp. 45-62, (1990); Stahl D.O., Oligopolistic pricing with sequential consumer search, American Economic Review, 79, 4, pp. 700-712, (1989); Steinfield C., Markus M.L., Wigand R.T., Through a glass clearly: Standards, architecture, and process transparency in global supply chains, Journal of Management Information Systems, 28, 1, pp. 75-108, (2011); The New York Times Company Reports NYTimes.com's Record-breaking Traffic, (2006); VanBoskirk S., Organize to Support Integrated Messaging, (2014); Xu L., Chen J., Whinston A.B., Oligopolistic pricing with online search, Journal of Management Information Systems, 27, 3, pp. 111-142, (2011)",null,null,"Routledge",{"$nulls":5},7421222.0,null,"JMISE",null,"English","J Manage Inf Syst","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-84943376848"]
["Montegut-Salla Y.; Cristóbal-Fransi E.; Gómez-Adillón M.J.","Montegut-Salla, Yolanda (55355674500); Cristóbal-Fransi, Eduard (8588970900); Gómez-Adillón, Maria Jesús (55669765100)","55355674500; 8588970900; 55669765100","Understanding the situation and factors of ICT adoption in agricultural cooperatives",2013.0,"Journal of Electronic Commerce in Organizations",11.0,3.0,null,1.0,26.0,25.0,8.0,"10.4018/jeco.2013070101","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84887448591&doi=10.4018%2fjeco.2013070101&partnerID=40&md5=aa990c5dd3e74ec9669d3461594b037f","Faculty of Law and Economics, University of Lleida, Lleida, Spain","Montegut-Salla Y., Faculty of Law and Economics, University of Lleida, Lleida, Spain; Cristóbal-Fransi E., Faculty of Law and Economics, University of Lleida, Lleida, Spain; Gómez-Adillón M.J., Faculty of Law and Economics, University of Lleida, Lleida, Spain","The phenomenon of the information and communication technologies (ICT) in general and Internet in particular has forced businesses and organizations to examine their existing business practices and adopt new methods of working, both for existing and potential customers. This paper presents an analysis of a study of 49 agri-food cooperatives in the province of Lleida, Spain, which seeks to analyse the current situation of Internet usage and electronic commerce in agrarian cooperatives and obtain the different factors of employing ICTs and the level of sophistication of use. The results are focused in the questionnaire that was completed by olive oil and sweet fruit cooperatives in 2010 that addressed the following aspects: computer equipment, Internet connection and presence, and finally, the level of electronic commerce. The discussion, based on the initial findings, examines the circumstances for ICT success and strategic effects resulting from implementation and use of such technologies. Afterwards, a logistic regression was carried out for determining the relevant factors in ICT adoption. The findings highlight that main activity and own website, including the variable training under particular circumstances are clearly significant to the extent of adoption and exploitation of ICTs by cooperatives. © 2013, IGI Global.","Agrarian Sector; Cooperatives; E-Commerce; Information and Communication Technologies (ICT); Internet; Logistic Regression; Social Economy","Electronic commerce; Information technology; Oils and fats; Regression analysis; Agrarian Sector; Cooperatives; Information and Communication Technologies; Logistic regressions; Social economy; Internet",{"$nulls":6},"Ahuja V., Cyber extension: A convergence of ICT and agricultural development, Global Media Journal, 2, 2, pp. 1-8, (2011); Al-Hassan R.M., Egyir I.S., Abakah J., Farm household level impacts of information communication technology (ICT)-based agricultural market information in Ghana, Journal of Development and Agricultural Economics, 5, 4, pp. 161-167, (2013); Aleke B., Ojiako U., Wainwright D.W., ICT adoption in developing countries: Perspectives from small-scale agribusinesses, Journal of Enterprise Information Management, 24, 1, pp. 68-84, (2010); Las Tecnologías de la Información y Las Comunicaciones en la Empresa Española, (2011); XV Encuesta AIMC A Usuarios de Internet, (2013); Avgerou C., Information systems in developing countries: A critical research review, Journal of Information Technology, 23, pp. 133-146, (2008); Banegas J., Efectos de las tecnologías de la información y comunicación en la vida empresarial, Revista Del Instituto de Estudios Económicos, 1 &, 2, pp. 415-440, (2001); Bruque S., Vargas A., Moyano J., Hernandez M.J., Estructura de la propiedad tecnologías de la información y ventaja competitiva. Una aproximación empírica, Revista de Economía y Empresa, 44, pp. 105-125, (2002); Burque K., Sewake K., Adoption of computer and internet technologies in small firm agriculture: A study of flower growers in Hawaii, Journal of Extension, 46, 3, pp. 1-11, (2008); Caballer V., Ilse G., Las nuevas tecnologías de la información en las cooperativas. Una aplicación a las cooperativas de crédito y citrícolas de la Comunidad Valenciana, CIRIEC-España Revista de Economía Pública. Social y Cooperativa, 49, pp. 239-261, (2004); Cox S., Information technology: The global key to precision agriculture and sustainability, Computers and Electronics in Agriculture, 36, 2-3, pp. 93-111, (2002); Cristobal E., Montegut Y., Marimon F., La Gestión de las Cooperativas Agrarias: Tipificación de las Cooperativas del Sector Oleico de Cataluña. CIRIEC-España, Revista de Economía Pública. Social y Cooperativa, 59, pp. 197-230, (2007); Dimara E., Skuras D., Adoption of agricultural innovations as a two-stage partial observability process, Agricultural Economics, 28, pp. 187-196, (2003); Estape G., Torreguitart C., ICT adoption in the small and medium-size social enterprises in Spain: Opportunity or priority, Social E-enterprise: Value Creation Through ICT, pp. 200-220, (2013); Farhat R., Management of logistics and ICT in food supply chain network: A conceptual framework, International Journal Logistics Economics and Globalisation, 4, 3, pp. 162-178, (2012); Frambach R., Schillewaert N., Organisational innovation adoptions: A multi-level framework of determinants and opportunities for future research, Journal of Business Research, 55, 2, pp. 163-176, (2002); Freeman C., Technology Policy and Economic Performance: Lessons from Japan, (1987); Hall A.J., Public-private sector partnerships in a system of agricultural innovation: Concepts and challenges, International Journal of Technology Management and Sustainable Development, 5, (2006); Jafar A., Eshghi T., The role of information and communication technology (ICT) in Iranian olive industrial cluster, The Journal of Agricultural Science, 3, 1, pp. 228-232, (2011); Julia J.F., Garcia Martinez G., Melia E., Internet, cooperativismo agrario y desarrollo rural. El caso de las cooperativas de la Comunidad Valenciana. CIRIEC-España, Revista de Economía Pública, Social y Cooperativa, 55, pp. 221-251, (2006); Kameswari V.L.V., Kishore D., Gupta V., ICTS for agricultural extension: A study in the Indian Himalayan region, The Electronic Journal on Information Systems in Developing Countries, 48, 3, pp. 1-12, (2011); Kiiza B., Pederson G., ICT-based market information and adoption of agricultural seed technologies: Insights from Uganda, Telecommunications Policy, 36, pp. 253-259, (2012); Knudson W., Wysocki A., Champagne J., Peterson H.P., Entrepreneurship and innovation in the agri-food system, American Journal of Agricultural Economics, 86, 5, pp. 1330-1336, (2004); Laudon K., Traver C., E-commerce: Business, Technology, Society, (2001); Lee S., Kim K.J., Factors affecting the implementation success of Internet-based information systems, Computers in Human Behavior, 23, 4, pp. 1853-1880, (2007); Lundvall B., National Systems of Innovation: Towards A Theory of Innovation and Interactive Learning, (1992); Marcuello C., Sanz M.I., Los principios cooperativos facilitadores de la innovación: Un modelo teórico, Revesco, 94, pp. 59-79, (2008); Merono A., Arcas N., Equipamiento y gestión de las tecnologías de la información en las cooperativas agroalimentarias. Ciriec-España, Revista de Economía Pública. Social y Cooperativa, 54, pp. 5-31, (2006); Molla A., Heeks R., Exploring e-commerce benefits for businesses in a developing country, The Information Society, 23, 2, pp. 95-108, (2007); Molla A., Licker P.S., ECommerce adoption in developing countries: A model and instrument, Information & Management, 42, 6, pp. 877-899, (2005); Montegut Y., Cristobal E., Análisis empresarial de las cooperativas del sector de la fruta dulce de Cataluña, REVESCO: Revista de Estudios Cooperativos, 101, pp. 28-57, (2010); Montegut Y., Cristobal E., Análisis de la gestión de la cooperativa agroalimentaria desde una perspectiva comparativa: el sector del aceite y el sector de la fruta dulce, REVESCO: Revista de Estudios Cooperativos, 108, pp. 113-151, (2012); Montegut Y., Cristobal E., Gomez Adillon M.J., La implementación de las TIC en la gestión de las cooperativas agroalimentarias: El caso de la provincia de Lleida, REVESCO: Revista de Estudios Cooperativos, 110, pp. 223-254, (2013); Montegut Y., Cristobal E., Marimon F., The singularity of agrarian cooperatives management: Cooperatives typologies in the olive oil sector in Spain, International Journal of Business and Management, 6, 6, pp. 16-30, (2011); Monzon Campos J.L., Las Grandes Cifras de la Economía Social en España, (2010); Mozas A., Bernal E., Integración cooperativa y TIC: Presente y futuro. Ciriec-España, Revista de Economía Pública. Social y Cooperativa, 49, pp. 143-166, (2004); Tecnologías de la Información y Las Comunicaciones en Las PYMES y Grandes Empresas Españolas. Edición 2012, (2012); Rao N., A framework for implementing information and communication technologies in agricultural development in India, Technological Forecasting and Social Change, 74, pp. 491-518, (2007); Rodriguez-Ardura I., Meseguer A., Towards a longitudinal model of e-commerce: Environmental, technological and organizational drivers of B2C adoption, The Information Society, 26, 3, pp. 209-227, (2010); Rodriguez-Ardura I., Meseguer A., Vilaseca J., Factors influencing the evolution of e-commerce: An empirical analysis in a developed market economy, Journal of Theoretical and Applied Electronic Commerce Research, 3, 2, pp. 18-29, (2008); Sacristan F., Las Tecnologías de la Información en el ámbito económico de las cooperativas agroalimentarias, Investigacion y Ciencia, 14, 36, pp. 25-28, (2006); Sagarna J., Macromagnitudes del cooperativismo agroalimentario español, OSCAE (Observatorio Socioeconómico Del Cooperativismo Agroalimentario Español), (2010); Suarez A., Nueva Economía y Nueva Sociedad, (2001); Sung T.K., Gibson D.V., Critical success factors in electronic commerce: Korean experiences, Journal of Organizational Computing and Electronic Commerce, 15, 1, pp. 19-34, (2005); Tan K., Chong S., Lin B., Eze U., Internet-based ICT adoption among SMEs: Demographic versus benefits, barriers, and adoption intention, Journal of Enterprise Information Management, 23, 1, pp. 27-55, (2009); Vargas A., Empresas cooperativas, ventaja competitiva y tecnología de la información. Ciriec- España, Revista de Economía Pública., Socialy Cooperativa, 49, pp. 13-29, (2004); Vilaseca J., Torrent J., Meseguer A., Rodriguez-Ardura I., An integrated model of adoption and development of e-commerce in companies, International Advances in Economic Research, 13, 2, pp. 222-241, (2007)",{"$nulls":8},1.5392929E7,null,null,null,"English","J. Electr. Commer. Organ.","Article","Final",null,"Scopus","2-s2.0-84887448591"]
["Wang X.; Yi C.; Zhang J.","Wang, Xuping (35273544600); Yi, Caiyu (56830031400); Zhang, Jun (55966697500)","35273544600; 56830031400; 55966697500","The research framework of B2C e-logistics integrated optimization",2015.0,"ICIC Express Letters, Part B: Applications",6.0,10.0,null,2801.0,2807.0,6.0,0.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-84941283500&partnerID=40&md5=649e67a68cdf5a964e8367829536a27c","Institute of Systems Engineering, Dalian University of Technology, No. 2, Linggong Road, Dalian, 116023, China; School of Business, Dalian University of Technology, No. 2, Dagong Road, Panjin, 124221, China","Wang X., Institute of Systems Engineering, Dalian University of Technology, No. 2, Linggong Road, Dalian, 116023, China, School of Business, Dalian University of Technology, No. 2, Dagong Road, Panjin, 124221, China; Yi C., Institute of Systems Engineering, Dalian University of Technology, No. 2, Linggong Road, Dalian, 116023, China; Zhang J., Institute of Systems Engineering, Dalian University of Technology, No. 2, Linggong Road, Dalian, 116023, China","B2C enterprises with their own logistics can serve customers through the whole online shopping processes. However, in practice each link (such as order picking, distribution) is optimized respectively. To realize the global optimal and tackle some prob- lems existing in e-logistics, the purpose of this paper is to develop a research framework of B2C e-commerce logistics integrated optimization. Firstly we analyze the B2C e-logistics operation processes from the overall perspective. Then we propose a systematic research framework including the research contents and methods of B2C e-logistics integrated op- timization. The framework consists of warehouse operation optimization, distribution optimization and integrated order picking and delivery scheduling. Finally, a numerical example is created to verify the validity and practicability of the framework. The research theoretically explores a systematic framework and feasible ideas for the further research on B2C e-logistics integrated optimization and in practice provides some decision support to the operation of e-logistics. ©, 2015 ICIC Express Letters Office.All Rights Reserved.","B2C e-commerce; Logistics integrated optimization; Research framework","Commerce; Decision support systems; Warehouses; B2C e-commerce; Delivery scheduling; Distribution optimization; Integrated optimization; Research frameworks; Systematic framework; Systematic research; Warehouse operation; Electronic commerce",{"$nulls":4},"National Natural Science Foundation of China, (71171029, 71471025)",null,"Koster R., Tho L.D., Roodbergen K.J., Design and control of warehouse order picking: A literature review, European Journal of Operational Research, 182, 1, pp. 481-501, (2007); Wang X., Ruan J., Zhang K., Ma C., Study on combinational disruption management for vehicle routing problem with fuzzy time windows, Journal of Management Sciences in China, 14, 6, pp. 2-15, (2011); Huang M., Zhang Y., Hu X., Intelligent delivery scheme generation method for organic vegetables under B2C direct sale, Journal of Systems Engineering, 28, 5, pp. 600-607, (2013); Chen Z.L., Integrated production and outbound distribution scheduling: Review and extensions, Operations Research, 58, 1, pp. 130-148, (2010); Geismar H.N., Laporte G., Lei L., Sriskandarajah C., The integrated production and transportation scheduling problem for a product with a short life span and non-instantaneous transportation time, INFORMS Journal on Computing, 20, 1, pp. 21-23, (2008); Low C.Y., Li R.K., Chang C.M., Integrated scheduling of production and delivery with time windows, International Journal of Production Research, 51, 3, pp. 897-909, (2013); Goetschalckx M., Ashayeri J., Classification and design of order picking systems, Logistics World, pp. 99-106, (1989); Tompkins J.A., White J.A., Bozer Y.A., Frazelle E.H., Tanchoco J.M., Facilities Planning, (2003); Frazelle E., World-Class Warehousing and Material Handling, (2002); Lin C.H., Lu I.Y., The procedure of determining the order picking strategies in distribution center, International Journal of Production Economics, 60, 2, pp. 301-307, (1999); Henn S., Algorithms for on-line order batching in an order picking warehouse, Computers &Amp Opera- Tions Research, 39, 11, pp. 2549-2563, (2012); Bukchin Y., Khmelnitsky E., Yakuel P., Optimizing a dynamic order-picking process, European Journal of Operational Research, 219, 2, pp. 335-346, (2012); Azadnia A.H., Taheri S., Ghadimi P., Saman M.Z., Wong K.Y., Order batching in warehouses by minimizing total tardiness: A hybrid approach of weighted association rule mining and genetic algorithms, The Scientific World Journal, (2013); Bilotkach V., A framework for modeling \\real-life\" airline networks, Review of Network Economics, 8, 3, pp. 255-270, (2009); Gutierrez-Jarpa G., Desaulniers G., Laporte G., Marianov V., A branch-and-price algorithm for the vehicle routing problem with deliveries, selective pickups and time windows, European Journal of Operational Research, 206, 2, pp. 341-349, (2010); Punakivi M., Yrjoolaa H., Holmstroom J., Solving the “last mile\" issue: Reception box or delivery box?, International Journal of Physical Distribution &Amp Logistics Management, 31, 6, pp. 427-439, (2001); McLeod F., Cherrett T., Song L., Transport impacts of local collection/delivery points, Interna- Tional Journal of Logistics, 9, 3, pp. 307-317, (2006)",null,null,"ICIC Express Letters Office",{"$nulls":5},2.1852766E7,null,null,null,"English","ICIC Express Lett Part B Appl.","Article","Final",null,"Scopus","2-s2.0-84941283500"]
["Zhu Y.Y.","Zhu, Y.Y. (36469573800)",3.64695738E10,"Research on the design and implementation of E-Commerce teaching simulation operating platform",2014.0,"International Journal of Online Engineering",10.0,1.0,null,53.0,58.0,5.0,1.0,"10.3991/ijoe.v10i1.2743","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84894361260&doi=10.3991%2fijoe.v10i1.2743&partnerID=40&md5=30ab9cc837b775a80618f0d0c07f9631","Department of Economics and Business Administration of Chongqing, Chongqing University of Education, Chongqing, China; Southwest University of Political Science and Law, Chongqing, China","Zhu Y.Y., Department of Economics and Business Administration of Chongqing, Chongqing University of Education, Chongqing, China, Southwest University of Political Science and Law, Chongqing, China","With the development of information technology, the traditional commercial trade activities are gradually substituted by the e-commerce, in order to better show the transaction process of among the manufacturers, shopping malls, logistics enterprises, foreign trade companies, banks and consumers to adapt to the development of e-commerce professional practice teaching, We designed the e-commerce teaching simulation operating platform, which is constituted by the e-commerce teaching simulation software, ecommerce simulation experiment management systems and e-commerce sand table. The platform can simulate the processes of e-commerce transactions, such as the electronic currency exchange, electronic trading market, electronic data interchange, supply chain management and enterprise financial management etc, through the combination of theory and practical operation to enable students to master the e-commerce practical skills from the emotional perspective and rational perspective to enhance students' understanding of e-commerce.","CA certification; E-commerce; Sand table; Teaching simulation operating platform",{"$nulls":7},"Ayo C., Adewoye J., Oni A., Business-to-consumer e-commerce in Nigeria: Prospects and challenges, African Journal of Business Management, 5, pp. 5109-5117, (2011); Gefen D., E-commerce: the role of familiarity and trust, Omega: Oxford Pergamon Press, 28, 6, pp. 725-737, (2000); Shahibi M.S., Australian Journal of Basic and Applied Sciences, 5, pp. 2028-2033, (2011); Bhatia R., Dave M., Joshi R.C., Retrieval System for Distributed Component Repositories, International Review on Computers and Software, 2, 2, pp. 118-123, (2007); Boud D., Cohen R., Sampson J., Peer learning and assessment, Assessment and Evaluation in Higher Educ, 24, 4, pp. 413-426, (1999); Minocha S., A case study-based investigation of students' experiences with social software tools, New Review of Hypermedia and Multimedia, 15, 3, pp. 245-265, (2009); Boud D., Lee A., Peer le arning as pedagogic discourse for research education, Studies in Higher Educ, 30, 5, pp. 501-516, (2005); Boud D., Cohen R., Sampson J., Peer learning and assessment, Assessment and Evaluation in Higher Educ, 24, 4, pp. 413-426, (1999); El Bejjet R., Medromi H., A Generic Platform for a Multi-Agent Systems Simulation, International Review on Computers and Software, 5, 5, pp. 505-509, (2010); Li Y.R., Zhu Y.Y., Zhang C.N., The K-Means Clustering Algorithm Based On Chaos Particle Swarm, Journal of Theoretical and Applied Information Technology, 48, 2, pp. 762-767, (2013); Zhang C.N., Zhu Y.Y., Li Y.R., An Improved Semi-supervised Clustering Algorithm Based on Active Learning, Journal of Theoretical and Applied Information Technology, 48, 2, pp. 741-748, (2013); Aghdaie S.A., Fathi S., Piraman A., An Analysis of Factors Affecting the Consumer's Attitude of Trust and their Impact on Internet Purchasing Behavior, International Journal of Business and Social Science, 2, 23, pp. 147-158, (2011); Eiben A., Smith J.E., Introduction to Evolutionary Computing; Pavlou P.A., Consumer acceptance of electronic commerce: Integrating trust and risk with the technology acceptance model, International Journal of Electronic Commerce, 7, pp. 101-134, (2003); Drazdilova P., Obadi G., Slaninova K., Martinovic J., Snasel V., Analysis and visualization of relations in eLearning, in Computational Social Network Anal, (2010)","Y.Y. Zhu; Department of Economics and Business Administration, Chongqing University of Education, Chongqing, China; email: zhuyongyong@126.com",{"$nulls":7},1.8612121E7,null,null,null,"English","Int. J. Online Eng.","Article","Final","All Open Access; Gold Open Access","Scopus","2-s2.0-84894361260"]
["Nandi S.; Nandi M.L.","Nandi, Santosh (57216657139); Nandi, Madhavi L. (36708278600)","57216657139; 36708278600","Introducing an M-commerce course into the business management curriculum: Experiences and recommendations",2015.0,"Journal of Information Systems Education",26.0,3.0,null,235.0,243.0,8.0,1.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85017639398&partnerID=40&md5=a5018b9a4ac8a812a7d777ef9fc15cf0","Department of Management, University of Texas, Rio Grande Valley, Edinburg, 78541, TX, United States; T. A. Pai Management Institute, Manipal, KA, 576104, India","Nandi S., Department of Management, University of Texas, Rio Grande Valley, Edinburg, 78541, TX, United States; Nandi M.L., T. A. Pai Management Institute, Manipal, KA, 576104, India","Mobility has become an important extension to the business strategies of present-day organizations. Thus, organizations are increasingly seeking managers with knowledge of value chain related to mobile-oriented business activities, usually referred to as mobile commerce (m-commerce). Accordingly, business management schools are interesting in designing their curricula to respond to the need for m-commerce knowledge and, in particular, the scope of the content for an m-commerce course. The general conception of m-commerce is that it is a component of e-business or e-commerce. This paper presents the unique dimensions of m-commerce that makes it stand out as a separate course for postgraduate business management students. This paper also provides input in regard to the design and delivery of the course by drawing upon the recent teaching experience of the authors at a highly respected business school in India. The course design covers mobility-related technology elements as related to business in diverse industry segments and is expected to enable students to develop a suitable mobile strategy for a real-time business scenario. The course content was drawn primarily from research papers, industry reports, and examples of trending mobile applications. The pedagogy was a blend of lectures and classroom exercises on innovative case studies. The response of the students to the course indicated a high degree of satisfaction in regard to its relevance. The inputs provided in this paper are believed to serve as guidance to business management schools that are interested developing such a course. © 2015 by the Education Special Interest Group (EDSIG) of the Association of Information Technology Professionals.","Curriculum design and development; E-commerce or E-business; M-commerce","Commerce; Curricula; Education; Electronic commerce; Mobile telecommunication systems; Societies and institutions; Students; Teaching; Business management; Curriculum design and development; Degree of satisfaction; eBusiness; M-commerce; Mobile applications; Mobile commerce (m-commerce); Teaching experience; Mobile commerce",{"$nulls":6},"Abbruzzese J., Spotify May Kill Pandora and iTunes, (2013); Angeles S., Blippar: Augmented Reality App Turns Everyday Products into Interactive Experience, (2013); Balasubramanian S., Peterson R., Jarvenpaa S., Exploring the Implications of M-Commerce for Markets and Marketing, Journal of Academy of Marketing Science, 30, 4, pp. 348-361, (2002); Bandyopadhyay K., Mobile Commerce, (2013); Barnes S., The Mobile Commerce Value Chain: Analysis and Future Developments, International Journal of Information Management, 22, 2, pp. 91-108, (2002); Buczkowski A., Foursquare Rolls Out Ads Platform for Small Businesses, (2013); Catone J., Picollator Image Recognition Search, (2008); Chang Y., Chen C., Zhou H., Smart Phone for Mobile Commerce, Computer Standards & Interfaces, 31, 4, pp. 740-747, (2009); Coursaris C., Hassanein K., Understanding M-commerce: A Consumer-Centric Model, Quarterly Journal of Electronic Commerce, 3, pp. 247-272, (2002); Dholakia R., Dholakia N., Mobility and Markets: Emerging Outlines of M-Commerce, Journal of Business Research, 57, 12, pp. 1391-1396, (2004); Ferreira D., Kostakos V., Dey A., Lessons Learned from Large-Scale User Studies: Using Android Market as a Source of Data, International Journal of Human Interaction, 4, 3, pp. 28-43, (2012); Fichman R., Santos B., Zheng Z., Digital Innovation as a Fundamental and Powerful Concept in the Information Systems Curriculum, MIS Quarterly, 38, 2, pp. 329-354, (2014); France-Presse A., Explained: How Candy Crush, (2014); (2014); Gilpin L., The World's Unlikely Leader in Mobile Payments: Kenya, (2014); Johnson M., Top 10 Mobile Ad Campaigns from H1 2013, (2013); Jones C., Ecommerce Is Growing Nicely While Mcommerce is on a Tear, (2013); Kuo Y., Yu C., 3G Telecommunication Operators' Challenges and Roles: A Perspective of Mobile Commerce Value Chain, Technovation, 26, 12, pp. 1347-1356, (2006); Lunden I., TripAdvisor Continues Acquisition Spree, (2013); Madrigal D., McClain B., Usability for Mobile Devices, (2010); Maitland C., Bauer J., Westerveld R., The European Market for Mobile Data: Evolving Value Chains and Industry Structures, Telecommunication Policy, 26, 9-10, pp. 485-504, (2002); May P., Mobile Commerce: Opportunities, Applications, and Technologies of Wireless Business, (2001); Mennecke B., Strader T., Mobile Commerce: Technology, Theory, and Applications, (2003); Mobile Sites and Responsive Design: Part 1, (2013); Integrating Mobile Strategy With Your Marketing Strategy, (2013); What Is Apple Passbook?, (2014); Rowles D., Mobile Marketing: How Mobile Technology Is Revolutionizing Marketing, Communications and Advertising, (2014); Sadeh N., M-Commerce: Technologies, Services, and Business Models, (2002); Safari E., Zissis D., Comparative Study of In-store Mobile Commerce Applications and Feature Selection, Targeted at Enhancing the Overall Shopping Experience, Mobile Electronic Commerce: Foundations, Development, and Applications, pp. 107-130, (2015); Saxena A., Vodafone India Launches M-Pesa Mobile Wallet With ICICI Bank, (2013); Schwartz G., Mobile Advertising Implications of Millennial Media's Buy of Jumptap, (2013); Scornavacca E., Barnes S., Huff S., Mobile Business Research Published in 2000-2004: Emergence, Current Status, and Future Opportunities, Communications of the Association for Information Systems, 17, pp. 635-646, (2006); Skeldon P., M-Commerce, (2011); Tarasewich P., Nickerson R., Warkentin M., Wireless/Mobile E-Commerce: Technologies, Applications, and Issues, Americas Conference on Information Systems, (2001); Tripathi R., Moving Toward a Mobile Website, pp. 131-146, (2015); Varshney U., Vetter R., Mobile Commerce: Framework, Applications and Networking Support, Mobile Networks and Applications, 7, 3, pp. 185-198, (2002); Varshney U., Vetter R., Kalakota R., Mobile Commerce: A New Frontier, Computer, 33, 10, pp. 32-38, (2000); Venkatesh V., Ramesh V., Massey A., Understanding Usability in Mobile Commerce, Communications of the ACM, 46, 12, pp. 53-56, (2003); Verkasalo H., Contextual Patterns in Mobile Service Usage, Personal Ubiquitous Computing, 13, 5, pp. 331-342, (2009); Wang Y., Lu T., Analysis of Mobile Commerce Value Chain, Research and Practical Issues of Enterprise Information Systems II, 255, pp. 1277-1281, (2008)",null,null,"Journal of Information Systems Education",{"$nulls":5},1.0553096E7,null,null,null,"English","J. Inf. Syst. Educ.","Article","Final",null,"Scopus","2-s2.0-85017639398"]
["Kim S.; Park H.","Kim, Sanghyun (36067473900); Park, Hyunsun (55533334100)","36067473900; 55533334100","Effects of various characteristics of social commerce (s-commerce) on consumers’ trust and trust performance",2013.0,"International Journal of Information Management",33.0,2.0,null,318.0,332.0,14.0,689.0,"10.1016/j.ijinfomgt.2012.11.006","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84871365586&doi=10.1016%2fj.ijinfomgt.2012.11.006&partnerID=40&md5=b181c80b7f20b6f79fa9f0388c0dae09","School of Business Administration, Kyungpook National University, 1370 Sankyuk-dong, Puk-gu, Daegu, 702-701, South Korea","Kim S., School of Business Administration, Kyungpook National University, 1370 Sankyuk-dong, Puk-gu, Daegu, 702-701, South Korea; Park H., School of Business Administration, Kyungpook National University, 1370 Sankyuk-dong, Puk-gu, Daegu, 702-701, South Korea","The development of social networking sites (SNSs) has given rise to a new e-commerce paradigm called social commerce (s-commerce). S-commerce is a subset of e-commerce and uses SNSs for social interactions and user contributions to facilitate the online buying and selling of various products and services. Recent years have witnessed the rapid growth of s-commerce in Korea, but this growth has involved a number of transaction-related issues such as no delivery and the delivery of wrong items. In particular, consumers’ trust has become a crucial factor in the success of s-commerce firms, requiring these firms to make more effort to gain this trust. In this regard, this study identifies the key factors in s-commerce [reputation, size, information quality, transaction safety, communication, economic feasibility, and word-of-mouth (WOM) referrals], that is, the characteristics of s-commerce influencing Korean consumers’ trust in s-commerce. In addition, the study assesses the effects of trust on trust performance (purchase intentions and WOM intentions). The results of an empirical analysis based on a sample of 371 s-commerce users indicate that all the characteristics of s-commerce (except for economic feasibility) had significant effects on trust and that trust had significant effects on purchase and WOM intentions. The results have important implications for s-commerce firms wishing to develop a successful business model for providing their customers with trustworthy services. © 2012 Elsevier Ltd","Purchase intentions; Social commerce; Trust; Trust performance; Word-of-mouth intentions","Economic analysis; Electronic commerce; Purchasing; Sales; Purchase intention; Social commerces; Trust; Trust performance; Word of mouth; Social networking (online)",{"$nulls":6},"Anckar B., D'Incau D., Value creation in mobile commerce: findings from consumer survey, Journal of Information Technology Theory and Application, 4, 1, pp. 43-64, (2002); Anderson E.W., Customer satisfaction and word of mouth, Journal of Service Research, 1, 1, pp. 5-17, (1998); Ajzen I., Fishbein M., Understanding attitudes and predicting social behavior, (1980); Ba S., Pavlou P.A., Evidence of the effect of trust building technology in electronic markets: price premiums and buyer behavior, Management Information Systems Quarterly, 26, 3, pp. 243-268, (2002); Bansal G., Chen L., (2011); Bart Y., Shankar V., Sultan F., Urban G.L., Are the drivers and role of online trust and same for all web sites and consumers? A large-scale exploratory empirical study, The Journal of Marketing, 69, pp. 133-152, (2005); Beldad A., Jong M., Steehouder M., How shall I trust the faceless and intangible? 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Kim K., Prabhakar B., Initial trust, perceived risk, and the adoption of internet banking, Proceedings of Information Systems International Conference, Atlanta, Georgia, USA, (2000); Kim D.J., Song Y.I., Braynoy S.B., Rao H.R., A multidimensional trust formation model in B-to-C E-commerce: a conceptual framework and content analyses of academia/practitioner perspectives, Decision Support systems, 40, 2, pp. 143-165, (2005); Kim D.J., Ferrin D.L., Rao H.R., A trust-based consumer decision-making model in electronic commerce: the role of trust, perceived risk, and their antecedents, Decision Support Systems, 44, 2, pp. 544-564, (2008); Kim H.-W., Xu Y., Gupta S., Which is more important in Internet shopping, perceived price or trust?, Electronic Commerce Research and Applications, 11, pp. 241-252, (2012); Koufaris M., Hampton-Sosa W., The development of initial trust in an online company be new customers, Information & Management, 41, 3, pp. 377-397, (2004); Kuan H.H., Bock G.W., Trust transference in brick and click retailer:an investigation of the before-online-visit phase, Information & Management, 44, 2, pp. 175-187, (2007); Landon S., Smith C.E., The use of quality and reputation indicators by consumers: the case of Bordeaux wine, Journal of consumer Policy, 20, 3, pp. 289-323, (1997); Lewis J.D., Weigert A., Trust as a social reality, Social Forces, 63, 4, pp. 967-985, (1985); Liao C., Palvia P., Lin H.N., The roles of habit and web site quality in e-commerce, International Journal of Information Management, 26, 6, pp. 469-483, (2006); Lin K.Y., Lu H.P., Why people use social networking sites: an empirical study integrating network externalities and motivation theory, Computers in Human Behavior, 27, 3, pp. 1152-1161, (2011); Linda S.L.A.I., Social commerce – e-commerce in social media context. 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Weijun W., Lin L., Research on social commerce in Web 2.0 environment. E-Business and E-Government (ICEE), 2011, International Conference on E-Business and E-Government (ICEE), 6–8 May, Shanghai, China, (2011); Westbrook R.A., Product/consumption-based affective responses and post-purchase processes, Journal of Marketing Research, 24, 3, pp. 258-270, (1987); Wixom B., Watson H., An empirical investigation of the factors affecting data warehousing success, Management Information Systems Quarterly, 25, 1, pp. 17-41, (2001); Yoon S.-J., The antecedents and consequences of trust in online purchase decisions, Journal of Interactive Marketing, 16, 2, pp. 47-63, (2002); Yousafzai S., Pallister J., Foxall G., Multi-dimensional role of trust in Internet banking adoption, The Service Industries Journal, 29, 5, pp. 591-605, (2009)","S. Kim; School of Business Administration, Kyungpook National University, Puk-gu, Daegu, 1370 Sankyuk-dong, 702-701, South Korea; email: ksh@knu.ac.kr",null,"Elsevier Ltd",{"$nulls":5},2684012.0,null,"IJMAE",null,"English","Int J Inf Manage","Article","Final",null,"Scopus","2-s2.0-84871365586"]
["Hu Z.-H.; Wei C.; Yu X.-K.","Hu, Zhi-Hua (35279757500); Wei, Chen (56424564700); Yu, Xiao-Kun (55490475000)","35279757500; 56424564700; 55490475000","Apparel distribution with uncertain try-on time by evolutionary algorithm",2015.0,"International Journal of Clothing Science and Technology",27.0,1.0,null,75.0,90.0,15.0,4.0,"10.1108/IJCST-08-2013-0099","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84924084521&doi=10.1108%2fIJCST-08-2013-0099&partnerID=40&md5=751cb769febcc65cf8473e4fa7e88731","Logistics Research Center, Shanghai Maritime University, Shanghai, China; College of Fashion, Donghua University, Shanghai, China","Hu Z.-H., Logistics Research Center, Shanghai Maritime University, Shanghai, China; Wei C., Logistics Research Center, Shanghai Maritime University, Shanghai, China; Yu X.-K., College of Fashion, Donghua University, Shanghai, China","Purpose – The purpose of this paper is to study the problem of a routing problem with uncertain try-on service time (VRPUS) for apparel distribution, and to devise solution strategies coping with the uncertainty by an evolutionary algorithm. VRPUS belongs to the category of practical routing models integrated with uncertain service times. However, in the background of apparel distribution, it has distinct features. The try-on service will improve the customer satisfaction by providing experiences to customers; the return cost is saved; the customer loyalty is improved for experiencing face-to-face try-on services. However, the uncertainty of try-on service time makes the apparel distribution process uncertain and incurs additional risk management cost, such that the logistics companies should optimally make decisions on the choice of the service and the service processes. Design/methodology/approach – This paper devised a mixed-integer programming (MIP) model for the base vehicle routing problem (VRP) and then it is extended to support the solution strategies for uncertain try-on times. A try-on time estimation parameter and a time reservation parameter are used to cope with the uncertain try-on time, and the try-on rejection strategy is applied when the uncertain try-on time is realized at customer and no surplus time can be used for try-on service besides distributing to remainder customers. Due to the computational complexity of VRPUS, an evolutionary algorithm is designed for solving it. These parameters and strategy options are designed for the operational decisions by logistics companies. Finally, a decision support system (DSS) is designed. Findings – Five experimental scenarios are performed to reveal the impacts of parameters and solution strategies coping with uncertain try-on time on the distribution cost, return cost, and the tryon service failure. The tuning methods are designed to assist the decisions by logistics companies. Originality/value – A new routing problem is addressed for apparel distribution in fashion industry especially in the context of booming apparel e-commerce, which is a VRP with uncertain try-on service time for apparel distribution; three strategies are developed to cope with the try-on time uncertainty. The proposed method is also a theoretical base for designing a practical DSS for logistics companies to provide try-on service to customers. © Emerald Group Publishing Limited.","Apparel distribution; Apparel e-commerce; Apparel industry; Evolutionary algorithm; Try-on service; Vehicle routing problem","Clothes; Customer satisfaction; Decision support systems; Electronic commerce; Evolutionary algorithms; Integer programming; Risk management; Sales; Service industry; Uncertainty analysis; Vehicle routing; Apparel industry; Decision support system (dss); Design/methodology/approach; Distribution process; Mixed integer programming model; Operational decisions; Try-on service; Vehicle Routing Problems; Costs",{"$nulls":6},"Ak A., Erera A.L., A paired-vehicle recourse strategy for the vehicle routing problem with stochastic demands, Transportation Science, 41, 2, pp. 222-237, (2007); Bertsimas D., Simchi-Levi D., The new generation of vehicle routing research: Robust algorithms addressing uncertainty, Operations Research, 44, 2, pp. 286-304, (1994); 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Toth P., Vigo D., The Vehicle Routing Problem, (2001); Wassan N.A., Wassan A.H., Nagy G., A reactive tabu search algorithm for the vehicle routing problem with simultaneous pickups and deliveries, Journal of Combinatorial Optimization, 15, 4, pp. 368-386, (2008); Wiese A., Toporowski W., Zielke S., Transport-related CO2 effects of online and brick-and-mortar shopping: A comparison and sensitivity analysis of clothing retailing, Transportation Research Part D: Transport and Environment, 17, 6, pp. 473-477, (2012); Yang W., Mathur K., Ballou R.H., Stochastic vehicle routing problem with restocking, Transportation Science, 34, 1, pp. 99-112, (2000)","Z.-H. Hu; Logistics Research Center, Shanghai Maritime University, Shanghai, China; email: zhhu@shmtu.edu.cn",null,"Emerald Group Holdings Ltd.",{"$nulls":5},9556222.0,null,null,null,"English","Int. J. Cloth. Sci. Technol.","Article","Final",null,"Scopus","2-s2.0-84924084521"]
["Djuric Z.; Gasevic D.","Djuric, Zoran (7003319003); Gasevic, Dragan (8549413500)","7003319003; 8549413500","FEIPS: A Secure Fair-Exchange Payment System for Internet Transactions",2014.0,"Computer Journal",58.0,10.0,null,2537.0,2556.0,19.0,12.0,"10.1093/comjnl/bxu120","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84943416288&doi=10.1093%2fcomjnl%2fbxu120&partnerID=40&md5=bfa00e354aad50f6a50e56fc5402d844","Faculty of Electrical Engineering, University of Banjaluka, Patre 5, Banjaluka, 78 000, Bosnia and Herzegovina; School of Computing and Information Systems, Athabasca University, Athabasca, Canada","Djuric Z., Faculty of Electrical Engineering, University of Banjaluka, Patre 5, Banjaluka, 78 000, Bosnia and Herzegovina; Gasevic D., School of Computing and Information Systems, Athabasca University, Athabasca, Canada","To be considered secure, a payment system needs to address a number of security issues. Besides fundamental security requirements, like confidentiality, data integrity, authentication and non-repudiation, another important requirement for a secure payment system is fair exchange. Many existing payment protocols require that customers must pay for products before their delivery (in the case of delivery of digital goods) or the delivery of the receipt (in the case of delivery of physical goods). This unfair situation should be eliminated afterward; that is, it is necessary to rebalance fairness for customers. To address these issues, we propose the Fair Exchange Internet Payment Protocol (FEIPS). The FEIPS protocol is designed for the payment of physical goods and falls into the category that uses a trusted third party for ensuring fair exchange. Although FEIPS has a strong emphasis on fair exchange, it still guarantees strong security properties, including confidentiality, data integrity, authentication and non-repudiation. The FEIPS protocol is designed to be simple and practical, unlike other similar protocols designed for the payment of physical goods. To demonstrate that FEIPS satisfies the desired properties, we perform a formal verification using the HLPSL language and the AVISPA tool. © 2014 The British Computer Society 2014. All rights reserved.","cryptography; e-commerce; fair exchange; formal verification; payment system; security","Authentication; Electronic commerce; Formal verification; Fair exchange; Internet transaction; Payment systems; Secure payment systems; security; Security requirements; Strong securities; Trusted third parties; Cryptography",{"$nulls":6},"Nenadic A., A Security Solution for Fair-exchange and Non-repudiation in E-commerce, (2005); Lawrence E., Corbitt B., Tidwell A., Fisher J., Internet Commerce: Digital Models for Business, (1998); Ford W., Baum M., Secure Electronic Commerce, (1997); Stallings W., Network and Internetwork Security, Principles and Practice, (1995); Merkow S., Breithhaupt J., Wheeler K., Building SET Applications for Secure Transactions, (1998); Bhimani A., Securing the commercial internet, Commun. ACM, 39, pp. 29-35, (1996); Tsiakis T., Stephanides G., The concept of security and trust in electronic payments, Comput. 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Conf. on Information Security Theory and Practices: Smart Cards, Mobile and Ubiquitous Computing Systems, pp. 90-101, (2007); Santiago J., Vigneron L., Study for automatically analysing non-repudiation, Actes du 1er Colloque sur les Risques et la Sécurité d'Internet et des Systèmes, CRiSIS, pp. 157-171, (2005); Ryan P., Schneider S., Goldsmith M., Lowe G., Roscoe B., Modelling & Analysis of Security Protocols, (2000); Heather J., Lowe G., Schneider S., How to prevent type flaw attacks on security protocols, Proc. 13th Computer Security Foundations Workshop (CSFW'00), pp. 105-119, (2000); Klay F., Santiago J., Vigneron L., Automatic methods for analyzing non-repudiation protocols with an active intruder, Lecture Notes Comput. Sc., 5491, pp. 192-209, (2007)","Z. Djuric; Faculty of Electrical Engineering, University of Banjaluka, Banjaluka, Patre 5, 78 000, Bosnia and Herzegovina; email: zoran.djuric@etfbl.net",null,"Oxford University Press",{"$nulls":5},104620.0,null,"CMPJA",null,"English","Comput J","Article","Final",null,"Scopus","2-s2.0-84943416288"]
["Tanadi T.; Samadi B.; Gharleghi B.","Tanadi, Trisna (51965071800); Samadi, Behrang (36070815300); Gharleghi, Behrooz (55348793600)","51965071800; 36070815300; 55348793600","The impact of perceived risks and perceived benefits to improve an online intention among generation-Y in Malaysia",2015.0,"Asian Social Science",11.0,26.0,null,226.0,238.0,12.0,36.0,"10.5539/ass.v11n26p226","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84987850974&doi=10.5539%2fass.v11n26p226&partnerID=40&md5=a10acc14ab34567dd5e2cab34315f162","Faculty of Business and Management, Asia Pacific University of Technology and Innovation (A.P.U), Technology Park Malaysia, Bukit Jalil, Kuala Lumpur, Malaysia","Tanadi T., Faculty of Business and Management, Asia Pacific University of Technology and Innovation (A.P.U), Technology Park Malaysia, Bukit Jalil, Kuala Lumpur, Malaysia; Samadi B., Faculty of Business and Management, Asia Pacific University of Technology and Innovation (A.P.U), Technology Park Malaysia, Bukit Jalil, Kuala Lumpur, Malaysia; Gharleghi B., Faculty of Business and Management, Asia Pacific University of Technology and Innovation (A.P.U), Technology Park Malaysia, Bukit Jalil, Kuala Lumpur, Malaysia","This study examines the role of perceived risk and perceived benefit in improving the online intention among Generation-Y in Malaysia. The purpose of this study is to identify the valid measure of perceived risk and perceived benefit as the result with, associated with online intention among Gen-Y in Malaysia. In addition, this research proposes a new research framework on online intention by referring to numerous antecedent literatures of online intention. The conceptualization of consumer perceived risk and perceived benefits of this study provides empirical evidence in the study of online intention. Four types of risk, such as delivery risk, privacy risk, quality risk and time risk and four types of benefit such as shopping convenience, product selection, ease of shopping and shopping enjoyment were used to examine their impact toward online intention. In this study, a total of 200 questionnaires is distributed by the researcher which focus specifically on Gen-Y in Malaysia. Pearson Correlation and Multiple Regression analysis are employed in order to test the hypothesis and examine the relationship between the variables. The finding confirmed that all the dimensions of perceived risk and perceived benefit have played an important role in improving the intention of consumers to shop online. All the dimension of perceived risks has a significant negative relationship toward online intention and all the dimension of perceived benefits has a significant positive relationship toward online intention. In fact, this study provides useful assistance for online marketers to develop an effective marketing strategy in targeting Generation-Y consumers at the same time, they can get a broad overview about the risks and benefits of online intention where it leads to increase the involvement of Gen-Y in online shopping. © 2015, Canadian Center of Science and Education. All rights reserved.","Ease of shopping and shopping enjoyment; Perceived benefit; Perceived risk; Product selection; Shopping convenience",{"$nulls":7},"Abdulahi A., Samadi B., Gharleghi B., A Study on the Negative Effects of Social Networking Sites Such as Facebook among, International Journal of Business and Social Science, 5, 10, pp. 133-145, (2014); Alba J., Lynch J., Weitz B., Janiszewski C., Lutz R., Sawyer A., Et al., Interactive Home Shopping: Consumer, Retailer, and Manufacturer Incentives to Participate in Electronic Marketplaces, Journal of Marketing, 61, 3, pp. 38-53, (1997); Ali Zaidi S.D., Gondal B.J., Yasmin A., Antecedents of Online Shopping Intention: A Study held in Pakistan, Journal of Sociological Research, 5, 1, pp. 231-247, (2014); Barnes S.J., Segmenting cyberspace: A customer typology for the internet, European Journal of Marketing, 41, 1-2, pp. 71-93, (2007); Bhatnagar A., Misra S., Rao H.R., On risk, convenience, and Internet shopping behavior, Communications of the ACM, 43, 11, pp. 98-105, (2000); Cemberci M., Civelek M.E., Sozer E.G., The determinants of intention to shop online and effects of brand equity on e-store patronage, Journal of Global Strategic Management, 13, pp. 125-145, (2013); Cohen J., Statistical Power Analysis for the Behavioral Sciences, (1988); David F.D., Bagozzi R.P., Warshaw P.R., Perceived enjoyment is a condition where consumers perceived an enjoyable online service experience as well as performance consequences that can be anticipated, Management Science, 35, 8, pp. 982-1003, (1989); Delafrooz N., Paim L.H., Khatibi A., Understanding consumer’s internet purchase intention in Malaysia, Journal of Business Management, 5, 3, pp. 2837-2846, (2011); Dillon T.W., Rief H.L., Factors Influencing Consumers’ E-Commerce Commodity Purchases, Information Technology, Learning, and Performance Journal, 22, 2, (2004); Forsythe S., Liu C., Shannon D., Gardner L.C., Development of a scale to measure the perceived benefits and risk of online shopping, Journal of Interactive Marketing, 20, 2, pp. 55-75, (2006); Haque A., Sadeghzadeh J., Khatibi A., Identifying Potentiality Online Sales In Malaysia: A Study On Customer Relationships Online Shopping, The Journal of Applied Business Research, 22, 4, pp. 119-130, (2006); Harn A.C., Khatib A., Ismai H.B., E-Commerce: A Study on Online Shopping in Malaysia, Journal of Social Science, 13, 3, pp. 231-242, (2006); Jaafar S.N., Lalp P.E., Naba M.M., Consumers’ Perceptions, Attitudes and Purchase Intention towards Private Label Food Products in Malaysia, Asian Journal of Business and Management Sciences, 2, 8, pp. 73-90, (2012); Jamali S.K., Samadi B., Marthandan G., Prioritizing Electronic Commerce Technologies in Iranian Family SMEs, Interdisciplinary Journal of Contemporary Research in Business, 6, 2, pp. 148-180, (2014); Jamali S.K., Marthandan G., Khazaei M., Samadi B., Fie D.Y.G., Conceptualizing Model of Factors Influencing Electronic Commerce Adoption in Iranian Family SMEs, Asian Social Science, 11, 10, (2015); Jariah M., Husniyah A.R., Laily P., Britt S., Financial behavior and problems among university students: Need for financial education, Journal of Personal Finance, 3, 1, pp. 82-96, (2004); Jarvenpaa S.L., Todd P.A., Consumer reactions to electronic shopping on the world wide web, International Journal of Electronic Commerce, 1, 2, pp. 59-88, (1996); Jarvenpaa S.L., Noam T., Lauri S., Consumer Trust in an Internet Store: A Cross-Cultural Validation, Journal of Computer-Mediated Communication, 5, 2, (1999); Jin B., Suh Y.G., Integrating effect of consumer perception factors in predicting private brand purchase in a Korean discount store context, Journal of Consumer Marketing, 22, 2, pp. 62-71, (2005); Influence of Perceived Usefulness, Ease of Use, Risk on Attitude and Intention to Shop Online, European Journal of Business and Management, 6, 27, pp. 218-228, (2014); Khojeh E., Mohseni S., Samadi B., Enhancing Customer Satisfaction Among SMEs through Web Technology, Research Notes in Information Science, 11, pp. 13-28, (2013); Ko H., Jung J., Kim J.Y., Shim S.W., Cross-cultural differences in perceived risk of online, Journal of Interactive Advertising, 4, 2, pp. 20-29, (2004); Koufaris M., Applying the Technology Acceptance Model and Flow Theory to Online Consumer Behavior, Journal of Information Systems Research, 13, 2, pp. 205-223, (2002); Kwek C.L., Tan H.P., Lau T.C., Investigating the Shopping Orientations on Online Purchase Intention in the e-Commerce Environment: A Malaysian Study, Journal of Internet Banking and Commerce, 15, 2, (2010); Kyauk S.T., Chaipoopirutana S., Factors Influencing Repurchase Intention:A Case Study of Xyz.Com Online Shopping Website in Myanmar, International Conference on Trends in Economics, Humanities and Management, pp. 177-180, (2014); Luo J., Ba S., Zhang H., The effectiveness of online shopping characteristics and well-designed websites on satisfaction, MIS Quaterly, 36, 4, pp. 1131-1144, (2012); Malaysian Website Rankings for February 2012, (2012); Masoud E.Y., The Effect of Perceived Risk on Online Shopping in Jordan, European Journal of Business and Management, 5, 6, pp. 76-87, (2013); McKinney L.N., Creating a Satisfying Internet Shopping Experience via Atmospheric Variables, International Journal of Consumer Studies, 28, 3, pp. 268-283, (2004); Monsuwe T.P., Dellaert B.G., Ruyter K.D., What drives consumers to shop online? A literature review, International Journal of Service Industry Management, 15, 1, pp. 102-121, (2004); Naiyi Y., Dimensions of Consumer’s Perceived Risk in Online Shopping, Journal of Electronic Science and Technology of China, 2, 3, pp. 177-182, (2004); Pallant J., SPSS Survival Manual: A Step by Step Guide to Data Analysis Using IBM SPSS, (2013); Pavlou P.A., Consumer Acceptance of Electronic Commerce: Integrating Trust and Risk with the Technology Acceptance Model, International Journal of Electronic Commerce, 7, 3, pp. 101-134, (2003); Rowley J., Product Search in E-Shopping: A review and research propositions, Journal of Consumer Marketing, 17, 1, pp. 20-25, (2000); Ruane L., Wallace E., Generation Y females online:Insights from brand narratives, Qualitative Market Research: An International Journal, 16, 3, (2013); Seiders K., Berry L.L., Gresham L.G., Attention, Retailers! How Convenient Is Your Convenience Strategy?, Sloan Management Review, (2000); Kiong T.P., Gharleghi B., Chan Yin F.B., Lim M.K., Electronic Ticketing in Airline Industries among Malaysians; the Determinants, International Journal of Business and Social Science, 5, 9, pp. 168-174, (2014); Tee P.K., Gharleghi B., Chan B.Y.F., Malaysian Young Consumer Preferences in Choosing International Fashion Brand, Journal of Human and Social Science Research, 1, 1, pp. 31-38, (2013); Tsai Y.C., Yeh J.C., Perceived risk of information security and privacy in online shopping: A study of environmentally sustainable products, Journal of Business Management, 4, 18, pp. 4057-4066, (2010); Wood S.L., Future fantasies: A social change perspective of retailing in the 21st century, Journal of Retailing, 78, 1, (2002); Daud K., Factors that Influence Customers’ Buying Intention on Shopping Online, International Journal of Marketing Studies, 3, 1, pp. 128-139, (2011); Zhang L., Tan W., Xu Y., Tan G., Dimensions of Consumers’ Perceived Risk and Their Influences on Online Consumers’ Purchasing Behavior, Communications in Information Science and Management Engineering, 2, 7, pp. 8-14, (2012); Zulhuda S., E-Commerce and Consumer Protection in Malaysia, Trubute, (2009)","B. Samadi; Faculty of Business and Management, Asia Pacific University of Technology and Innovation (A.P.U), Technology Park Malaysia, Bukit Jalil, 57000, Malaysia; email: behrang@apu.edu.my",null,"Canadian Center of Science and Education",{"$nulls":5},1.9112017E7,null,null,null,"English","Asian Soc. Sci.","Article","Final","All Open Access; Gold Open Access; Green Open Access","Scopus","2-s2.0-84987850974"]
["Pounder P.; Bovell G.; Pilgrim-Worrell S.","Pounder, Paul (35737719700); Bovell, Gavin (56497005600); Pilgrim-Worrell, Shannelle (56497118900)","35737719700; 56497005600; 56497118900","A review of supply chain management and its main external influential factors",2013.0,"Supply Chain Forum",14.0,3.0,null,42.0,50.0,8.0,10.0,"10.1080/16258312.2013.11517320","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84921884634&doi=10.1080%2f16258312.2013.11517320&partnerID=40&md5=63b962268d759f7a099c7b7d52251a5c","The University of the West Indies, Barbados, United States","Pounder P., The University of the West Indies, Barbados, United States; Bovell G., The University of the West Indies, Barbados, United States; Pilgrim-Worrell S., The University of the West Indies, Barbados, United States","Supply chain management (SCM) is a concept that has gained much popularity and importance since the new millennium. The literature and practice of SCM have exhibited a cadre of definitions. However, SCM lacks a universally accepted definition and hence this article looks at the nature and principles of SCM as they have evolved based on a series of external influential factors. Observation has been given to the drastic refocus of the definitions that existed during the periods 1980–1989, 1990–1999, and 2000–present. The research shows that the historical evolution of the subject area has led to academic and practitioner rethinking. The purpose of this article is to give a strategic, historical perspective to the changing nature and principles of SCM and to preview the main external factors influencing SCM. © Copyright KEDGE BS","Competition; E-commerce; Globalization; Logistics; Recession; References; Supply chain; Technology; Trade",{"$nulls":7},"Abberger K., Nierhaus W., How to Define a Recession, (2008); Baily M.N., Macroeconomic Implications of the New Economy, (2001); Berg-Anderassen J.A., US Depressions and Recessions 1930–2011: A Comparative Severity Analysis, (2011); Bishop J.H., On New Hires, Market Failure in Training?, pp. 66-91, (1991); Carter C.R., Rogers D.S., A framework of sustainable supply chain management. 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Stockholm, (2000); Mentzer J.T., Dewitt W., Keebler J.S., Min S., Nix N.W., Smith C.D., Zacharia Z.G., What is supply chain management?, Supply Chain Management, pp. 1-25, (2001); Molahosseini A., Impact of supply chain integration on the performance of Bahman Group, Interdisciplinary Journal of Contemporary Research in Business, 5, 1, pp. 184-192, (2013); Monczka R.M., Peterson K.J., Handfield R.B., Success factors in strategic supplier alliances: The buying company perspective, Decision Sciences, 29, 3, pp. 553-573, (1998); Morrison W., China's Economic Conditions, (2012); Naslund D., Williamson S., What is management in supply chain management? 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Cscmp's Supply Chain Quarterly, (2013); Stock J., Boyer S., Developing a consensus definition of supply chain management: Aqualitative study, International Journal of Physical Distribution & Logistics Management, 39, 8, pp. 690-711, (2009); Tan K., A framework of supply chain management literature, European Journal of Purchasing & Supply Management, 7, pp. 39-48, (2001); Turban E., King D., Lang J., Introduction to Electronic Commerce, (2010); Vida I., Reardon J., Fairhurst A., Determinants of international retail involvement: The case of large U.S. retail chains, Journal of International Marketing, 8, 4, pp. 37-60, (2000); Wen C., Li X., Bai Y., Research on dynamic supply chain integration network model basedon collaboration theory and non-linear polya processes, 2007 International Conference on Wireless Communications, Networking and Mobile Computing, pp. 6085-6088, (2007); Yang M., Supply chain management under e-commerce environment, International Journal of Innovation, Management and Technology, 3, 3, pp. 210-212, (2012)","P. Pounder; The University of the West Indies, Barbados, United States; email: paul.pounder@cavehill.uwi.edu",null,"Institute for Supply Chain Excellence of BEM - Bordeaux",{"$nulls":5},1.6258312E7,null,null,null,"English","Supply Chain Forum","Article","Final",null,"Scopus","2-s2.0-84921884634"]
["Khare A.; Khare A.; Mukherjee S.; Goyal T.","Khare, Arpita (36458467200); Khare, Anshuman (7101836341); Mukherjee, Sourjo (56924241100); Goyal, Tanuj (56925041800)","36458467200; 7101836341; 56924241100; 56925041800","Do consumer shopping styles influence consumer attitudes toward services offered by shopping websites?",2016.0,"Journal of International Consumer Marketing",28.0,1.0,null,28.0,41.0,13.0,11.0,"10.1080/08961530.2015.1072075","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84953357602&doi=10.1080%2f08961530.2015.1072075&partnerID=40&md5=328eec7f27adc44e4b8cf063b7a792f7","IIM Rohtak, Rohtak, India; Athabasca University, St. Albert, AB, Canada","Khare A., IIM Rohtak, Rohtak, India; Khare A., Athabasca University, St. Albert, AB, Canada; Mukherjee S., IIM Rohtak, Rohtak, India; Goyal T., IIM Rohtak, Rohtak, India","The purpose of the current research was to examine the influence of consumer shopping styles on Indian consumers' attitude toward services offered by shopping websites. Online service factors like product information, refunds, transactions, ability to return and exchange products, ability to cancel orders, and customer support services were examined. Unlike research findings from other countries, it was found that different consumer styles had no influence on consumers' online service attitude. Only a quality-conscious shopping style influenced consumers' website service attitude. The findings can help online shopping firms and retailers in understanding fears and apprehensions of consumers regarding online service. Service-related factors like refunds, product delivery, information availability, customer service, and financial transactions can be modified to improve consumers' attitudes toward online shopping websites. Future research can address issues related to consumer attitudes toward website features, layout, design, displays, and pictorial images. © 2016 Taylor & Francis Group, LLC.","Consumer shopping styles; India; online shopping; service",{"$nulls":7},"Future of e-commerce, (2013); Kearny A.T., E-commerce is the next frontier in global expansion, (2012); Bakewell C., Mitchell V., Generation Y female consumer decision-making styles, International Journal of Retail and Distribution Management, 31, 2, pp. 95-106, (2003); Bakewell C., Mitchell V., Male versus female consumer decision making styles, Journal of Business Research, 59, pp. 1297-1300, (2006); Bao Y., Zhou K.Z., Su C., Face consciousness and risk aversion: Do they affect consumer decision making?, Psychology & Marketing, 20, 8, pp. 733-755, (2003); Baoku L., Cuixia Z., Weimin B., An empirical study on the decision-making styles of the Chinese peasant consumers, Journal of Consumer Marketing, 27, 7, pp. 629-637, (2010); Bauer H.H., Sauer N.E., Becker C., Investigating the relationship between product involvement and consumer decision-making styles, Journal of Consumer Behaviour, 5, pp. 342-354, (2006); 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Wang C.-L., Siu N.Y.M., Hui A.S.Y., Consumer decision-making styles on domestic and imported brand clothing, European Journal of Marketing, 38, 1-2, pp. 239-252, (2004); Wang H., Pallister J.G., Foxall G.R., Innovativeness and involvement as determinants of website loyalty: I. A test of the style/involvement model in the context of Internet buying, Technovation, 26, 12, pp. 1357-1365, (2006); Wesley S., LeHew M., Woodside A.G., Consumer decision-making styles and mall shopping behavior: Building theory using exploratory data analysis and the comparative method, Journal of Business Research, 59, pp. 535-548, (2006); Wickliffe V.P., Refinement and re-assessment of the consumer decision-making style instrument, Journal of Retailing and Consumer Services, 11, pp. 9-17, (2004); Wilson-Jeanselme M., Reynolds J., Understanding shoppers’ expectations of online grocery retailing, International Journal of Retail and Distribution Management, 34, 7, pp. 529-540, (2006); Wolfinbargar M., Gilly M.G., Shopping online for freedom, control, and fun, California Management Review, 43, 2, pp. 34-55, (2001); Zhou L., Dai L., Zhang D., Online shopping acceptance model: A critical survey of consumer factors in online shopping, Journal of Electronic Commerce Research, 8, 1, pp. 41-62, (2007)","A. Khare; Athabasca University, St. Albert, T8N 6L2, Canada; email: anshuman.khare@fb.athabascau.ca",null,"Routledge",{"$nulls":5},8961530.0,null,null,null,"English","J. Int. Consum. Mark.","Article","Final",null,"Scopus","2-s2.0-84953357602"]
["Hua G.; Wang S.; Cheng T.C.E.","Hua, Guowei (24724222400); Wang, Shouyang (35195168500); Cheng, T.C.E. (13302593800)","24724222400; 35195168500; 13302593800","Price and lead time decisions in dual-channel supply chains",2010.0,"European Journal of Operational Research",205.0,1.0,null,113.0,126.0,13.0,415.0,"10.1016/j.ejor.2009.12.012","https://www.scopus.com/inward/record.uri?eid=2-s2.0-75849127286&doi=10.1016%2fj.ejor.2009.12.012&partnerID=40&md5=f2f1eb994918d1b8940e08ab448d6d6f","School of Economics and Management, Beijing Jiaotong University, Beijing, 100044, China; Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, 100190, China; Department of Logistics and Maritime Studies, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, Hong Kong","Hua G., School of Economics and Management, Beijing Jiaotong University, Beijing, 100044, China, Department of Logistics and Maritime Studies, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, Hong Kong; Wang S., Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, 100190, China; Cheng T.C.E., Department of Logistics and Maritime Studies, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, Hong Kong","Manufacturers today are increasingly adopting a dual channel to sell their products, i.e., the traditional retail channel and an online direct channel. Empirical studies have shown that service quality (we focus on the delivery lead time of the direct channel) even goes beyond product price as one of the major factors influencing consumer acceptance of the direct channel. Delivery lead time has significant effects on demand, profit, and pricing strategy. However, there is scant literature addressing the decision on the promised delivery lead time of a direct channel and its impact on the manufacturer's and retailer's pricing decisions. To fill this gap, we examine the optimal decisions of delivery lead time and prices in a centralized and a decentralized dual-channel supply chain using the two-stage optimization technique and Stackelberg game, and analyze the impacts of delivery lead time and customer acceptance of a direct channel on the manufacturer's and retailer's pricing behaviours. We analytically show that delivery lead time strongly influences the manufacturer's and the retailer's pricing strategies and profits. Our numerical studies reveal that the difference between the demand transfer ratios in the two channels with respect to delivery lead time and direct sale price, customer acceptance of the direct channel, and product type have great effects on the lead time and pricing decisions. © 2009 Elsevier B.V. All rights reserved.","Dual channel; E-commerce; Game theory; Internet/direct marketing; Supply chain management","Costs; Electronic commerce; Game theory; Manufacture; Profitability; Sales; Supply chains; Consumer acceptance; Customer acceptance; Delivery lead time; Direct channel; Dual channel; E-Commerce; Empirical studies; Internet/direct marketing; Leadtime; Numerical studies; On-Demand; Optimal decisions; Pricing decision; Pricing strategy; Product price; Product types; Retail channel; Sale price; Service Quality; Stackelberg Games; Transfer ratio; Two channel; Two stage optimizations; Supply chain management",{"$nulls":4},"National Natural Science Foundation of China, NSFC, (70731003); Hong Kong Polytechnic University, PolyU, (G-U341); National Key Research and Development Program of China, NKRDPC, (2009CB326205)","We thank two anonymous referees and an Editor for their insightful comments and suggestions that have helped improve our paper greatly. This research was supported in part by The Hong Kong Polytechnic University under grant number G-U341 , the NSFC under grant number 70731003 , and the 973 program of China under grant number 2009CB326205 . ","Baker W., Marn M., Zawada C., Price smarter on the net, Harvard Business Review, 79, 2, pp. 122-127, (2001); Balasubramanian S., Mail versus mall: A strategic analysis of competition between direct marketers and conventional retailers, Marketing Science, 17, 3, pp. 181-195, (1998); Boyaci T., Ray S., Production differentiation and capacity cost interaction in time and price sensitive demand, Manufacturing & Service Operations Management, 5, pp. 18-36, (2003); Cattani K., Gilland W., Swaminathan J.M., Coordinating Internet and traditional supply chains, Handbook of Quantitative Supply Chain Analysis: Modeling in the E-Business Era, (2004); Cattani K., Gilland W., Heese S., Swaminathan J., Boling frogs: Pricing strategic for a manufacturer adding an internet channel, Production and Operations Management, 15, 1, pp. 40-56, (2006); Chen K.Y., Kaya M., Ozer O., Dual sales channel management with service competition, Manufacturing & Service Operations Management, 10, 4, pp. 654-675, (2008); Chiang W.K., Chhajed D., Hess J.D., Direct marketing, indirect profits: A strategic analysis of dual-channel supply chain design, Management Science, 49, 1, pp. 1-20, (2003); Choi S.C., Price competition in a duopoly common retailer channel, Journal of Retailing, 72, 2, pp. 117-134, (1996); Choi S.C., Expanding to direct channel: Market coverage as entry barrier, Journal of Interactive Marketing, 17, 1, pp. 25-40, (2003); Devaraj S., Fan M., Kohli R., Antecedents of B2C channel satisfaction and preference: Validating e-commerce metrics, Information Systems Research, 13, 3, pp. 316-333, (2002); Dumrongsiri A., Fan M., Jain A., Moinzadeh K., A supply chain model with direct and retail channels, European Journal of Operational Research, 187, 3, pp. 691-718, (2008); Hanover D., It's not a threat just a promise, Chain Store Age, 75, 9, (1999); Hopp W., Sturgis M., A simple, robust lead time-quoting policy, Manufacturing & Service Operations Management, 3, 4, pp. 321-336, (2001); Huang W., Swaminathan J.M., Introduction of a second channel: Implications for pricing and profits, European Journal of Operational Research, 194, pp. 258-279, (2009); 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Maltz A., Rabinovich E., Sinha R., Logistics: The key to e-retailer success, Supply Chain Management Review, 8, pp. 56-63, (2004); Mangalindan M., Online retail sales are expected to rise to $172 billion this year, The Wall Street Journal, (2005); McGuire T.M., Staelin R., An industry equilibrium analysis of downstream vertical integration, Marketing Science, 2, 2, pp. 161-191, (1983); Palaka K., Erleba S., Kropp D.H., Lead-time setting, capacity utilization, and pricing decisions under lead-time dependent demand, IIE Transactions, 30, pp. 151-163, (1998); Raju J., Abhik R., Market information and firm performance, Management Science, 46, 8, pp. 1075-1084, (2000); Reichheld F., Schefter P., E-loyalty: Your secret weapon in the web, Harvard Business Review, 78, 4, pp. 105-113, (2000); Rhee B.D., Park S.Y., Online stores as a new direct channel and emerging hybrid channel system, (2000); Rohm A.J., Swaminathan V., A typology of online shoppers based on shopping motivations, Journal of Business Research, 57, pp. 748-757, (2004); Schlesinger J.M., New E-conomy: If E-Commerce helps kill inflation, why did prices just spike?, The Wall Street Journal, 18, (1999); So K.C., Song J., Price, delivery time guarantees and capacity selection, European Journal of Operational Research, 111, pp. 28-49, (1998); Spengler J., Vertical restraints and antitrust policy, Journal of Political Economy, 58, 4, pp. 347-352, (1950); Tedeschi B., Compressed data; big companies go slowly in devising net strategy, New York Times, (2000); Tsay A., Agrawal N., Channel conflict and coordination in the e-commerce age, Production and Operations Management, 13, 1, pp. 93-110, (2004); Tsay A., Agrawal N., Manufacturer and reseller perspectives on channel conflict and coordination in multiple-channel distribution, Handbook of Quantitative Supply Chain Analysis: Modeling in the E-Business Era, (2004); Urban G., Sultan F., Qualls W., Placing trust at the center of your Internet strategy, Sloan Management Review, 42, pp. 39-48, (2000); Webster S., Dynamic pricing and lead-time policies for make-to-order systems, Decision Science, 33, 4, pp. 579-599, (2002); Wilder C., HP's online push, (1999); Yang B., Geunes J., Inventory and lead time planning with lead-time-sensitive demand, IIE Transactions, 39, pp. 439-452, (2007); Yao D.Q., Liu J.J., Competitive pricing of mixed retail and e-tail distribution channels, Omega, 33, pp. 235-247, (2005); Yue X., Liu J.J., Demand forecast sharing in a dual-channel supply chain, European Journal of Operational Research, 174, pp. 646-667, (2006)","T.C.E. Cheng; Department of Logistics and Maritime Studies, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, Hong Kong; email: lgtcheng@polyu.edu.hk",{"$nulls":7},3772217.0,null,"EJORD",null,"English","Eur J Oper Res","Article","Final",null,"Scopus","2-s2.0-75849127286"]
["Lu X.; Wu G.; Li H.","Lu, Xin (57212319266); Wu, Gao (55483865900); Li, Huixing (54880338900)","57212319266; 55483865900; 54880338900","Research on consumer interest model based on latent semantic analysis",2011.0,"Journal of Information and Computational Science",8.0,15.0,null,3677.0,3685.0,8.0,0.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-84855178703&partnerID=40&md5=2b2a33c666026dbf3cbe35c42cc56dd2","School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China; Institute of Economics, Shenzhen University, Shenzhen 518061, China","Lu X., School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China; Wu G., School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China; Li H., Institute of Economics, Shenzhen University, Shenzhen 518061, China","Sending commodity news to potential consumers accurately is an effective e-commerce marketing strategy for improving sales volume. The accurate consumer interest model is favourable to improve the accuracy of the delivery of commodity news. According to the principle of the delivery of commodity news based on Latent Semantic Analysis (LSA), this paper proposes a consumer interest model represented by eigenvector space. At the same time, on the basis of the traditional weighting approach, the paper applies LSA technology to construct a Latent semantic space to identify synonymy and polysemy of the words in consumer profiles indicating consumer's interest. What's morethe paper proposes a new weighting approach, with which the LSA-based local weight calculation is more accurate and the consumer interest model is more accord with consumer demand. Experimental results have demonstrated that the constructed consumer interest model can effectively improve the hitting probability in the delivery of commodity news. © 2009 by Binary Information Press.","Consumer interest model; Latent semantic analysis; Weighting approach","Marketing; Consumer demands; Consumer interests; Hitting probabilities; Latent Semantic Analysis; Latent semantics; Marketing strategy; Model-based OPC; Sales volume; Weight calculation; Weighting approach; Semantics",{"$nulls":6},"Somlo G., Howe A.E., Adaptive lightweight text filtering, In Proceedings of IDA, pp. 319-329, (2001); Chang Y.-I., Shen J.-H., Chen T.-I., A data mining-based method for the incremental update of supporting personalized information filtering, Journal of Information Science and Engineering, 24, 1, pp. 129-14, (2008); Degemmis M., Lops P., Semeraro G., A content-collaborative recommender that exploits WordNet-based user profiles for neighborhood formation, User Modeling and User-Adapted Interaction, 17, 3, pp. 217-255, (2007); Zhang Y., Callan J., Minka T., Novelty and redundancy detection in adaptive filtering, Proc 25th Ann Int'l ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 81-88, (2002); Dumais S.T., Improving the retrieval of information from external source behavior research methods, Instruments & Computers, 23, 2, pp. 229-236, (1991); Song W., Park S.C., Latent semantic analysis for vector space expansion and fuzzy logic-based genetic clustering, Knowledge and Information Systems, 22, 3, pp. 347-369, (2010); Liu M., Zheng D., Zhao T., Et al., Text similarity cumulative model and algorithm research for dynamic multi-document summarization, Journal of Computational Information Systems, 7, 5, pp. 1698-1705, (2011)","X. Lu; School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China; email: luxinmail@uestc.edu.cn",{"$nulls":7},1.5487741E7,null,null,null,"English","J. Inf. Comput. Sci.","Article","Final",null,"Scopus","2-s2.0-84855178703"]
["Agatz N.A.H.; Fleischmann M.; van Nunen J.A.E.E.","Agatz, Niels A.H. (22978538100); Fleischmann, Moritz (56256963800); van Nunen, Jo A.E.E. (6603697491)","22978538100; 56256963800; 6603697491","E-fulfillment and multi-channel distribution - A review",2008.0,"European Journal of Operational Research",187.0,2.0,null,339.0,356.0,17.0,398.0,"10.1016/j.ejor.2007.04.024","https://www.scopus.com/inward/record.uri?eid=2-s2.0-36048948226&doi=10.1016%2fj.ejor.2007.04.024&partnerID=40&md5=57606f95a2b2bad4052e3ae1f9cf0603","RSM Erasmus University, 3000 DR Rotterdam, P.O. Box 1738, Netherlands","Agatz N.A.H., RSM Erasmus University, 3000 DR Rotterdam, P.O. Box 1738, Netherlands; Fleischmann M., RSM Erasmus University, 3000 DR Rotterdam, P.O. Box 1738, Netherlands; van Nunen J.A.E.E., RSM Erasmus University, 3000 DR Rotterdam, P.O. Box 1738, Netherlands","This review addresses supply chain management issues specific to Internet fulfillment in a multi-channel environment. It provides a systematic overview of managerial planning tasks and corresponding quantitative models. Our objective is to twofold, namely to enhance the understanding of multi-channel e-fulfillment by documenting the current state of affairs, and to inspire fruitful future research by identifying gaps between relevant managerial issues and available academic literature. One of the recurrent patterns in today's e-commerce operations is the combination of 'bricks-and-clicks' - the integration of e-fulfillment into a portfolio of multiple alternative distribution channels. From a supply chain management perspective, multi-channel distribution provides opportunities for serving different customer segments, creating synergies, and exploiting economies of scale. However, in order to successfully exploit these opportunities companies must master novel challenges. In particular, the design of a multi-channel distribution system requires a constant trade-off between process integration and separation across multiple channels. In addition, sales and operation decisions are ever more tightly intertwined as delivery and after-sales services are becoming key components of the product offering. © 2007 Elsevier B.V. All rights reserved.","Distribution; E-fulfillment; Literature review; Online retailing","Customer satisfaction; Decision theory; Online systems; Supply chain management; Web services; E-fulfillment; Literature review; Multi-channel distribution; Online retailing; Electronic commerce",{"$nulls":4},"Stichting Transumo","This work was financially supported by Stichting Transumo through the project ketensynchronisatie.  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Boyer K.K., Hult G.T., Frohlich M., An exploratory analysis of extended grocery supply chain operations and home delivery, Integrated Manufacturing Systems, 14, 8, pp. 652-663, (2003); Boyer K.K., Frohlich M., Hult G.T., Extending the Supply Chain: How Cutting-Edge Companies Bridge the Critical Last Mile into Customers' Homes, (2005); Braysy I., Gendreau M., Vehicle routing problem with time windows, Part I: Route construction and local search algorithms, Transportation Science, 39, 1, pp. 104-118, (2005); Braysy I., Gendreau M., Vehicle routing problem with time windows, Part II: Metaheuristics, Transportation Science, 39, 1, pp. 119-139, (2005); Brynjolfsson E., Hu Y.J., Smith M.D., Consumer surplus in the digital economy: Estimating the value of increased product variety at online booksellers, Management Science, 49, 11, pp. 1580-1596, (2003); Campbell A.M., Savelsbergh M.W.P., Decision support for consumer direct grocery initiatives, Transportation Science, 39, 3, pp. 313-327, (2005); 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Fleischmann; RSM Erasmus University, 3000 DR Rotterdam, P.O. Box 1738, Netherlands; email: MFleischmann@rsm.nl",{"$nulls":7},3772217.0,null,"EJORD",null,"English","Eur J Oper Res","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-36048948226"]
["Tabbitt S.","Tabbitt, Sue (23091856600)",2.30918566E10,"Caught in the web craze",2007.0,"Drapers",null,"2024-11-17",null,4.0,5.0,1.0,0.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-37249084008&partnerID=40&md5=1384789a42301a6b1e968237094bbe8f",null,null,"Fashion retailers are launching several e-commerce sites to enhance their online shopping strategies and improve Internet sales, with a particular focus on customer usability, and thereby command a market advantage. Customers have become accustomed to shopping online, which means they demand as much from their online shopping experience as from their offline experience. The Monsoon site uses zoom technology, which allows sophisticated searches that can identify keywords, which can help consumers to search by the product attributes of their choices. Next has also significantly done well in its e-commerce through its mail order heritage and its subsequent experience of putting together attractive catalogues and robust logistics. Various companies are also planning to have the highest online conversion rates, average order value, and revenue per visit. Providing personalized recommendations based on user ratings also is a much more efficient method and can increase a website's sales.",null,"business plan; customer service; e-commerce; fashion; mail order; marketing; retailing; sales",{"$nulls":15},1.4791617E7,null,null,null,"English","Drapers","Article","Final",null,"Scopus","2-s2.0-37249084008"]
["Khare A.; Dixit S.; Chaudhary R.; Kochhar P.; Mishra S.","Khare, Arpita (36458467200); Dixit, Saumya (55340373500); Chaudhary, Ruchi (55339740200); Kochhar, Priyanka (58375401200); Mishra, Shruti (57213026551)","36458467200; 55340373500; 55339740200; 58375401200; 57213026551","Customer behavior toward online insurance services in India",2012.0,"Journal of Database Marketing and Customer Strategy Management",19.0,2.0,null,120.0,133.0,13.0,9.0,"10.1057/dbm.2012.14","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84865171873&doi=10.1057%2fdbm.2012.14&partnerID=40&md5=95e21a8103d268bc730507fe0e074897","Indian Institute of Management Rohtak, Haryana, India; Indian Institute of Information Technology, Allahabad, India","Khare A., Indian Institute of Management Rohtak, Haryana, India; Dixit S., Indian Institute of Information Technology, Allahabad, India; Chaudhary R., Indian Institute of Information Technology, Allahabad, India; Kochhar P., Indian Institute of Information Technology, Allahabad, India; Mishra S., Indian Institute of Information Technology, Allahabad, India","The use of web-based technologies as a service delivery medium has added new elements to service dissemination. Escalation in self-service technologies has provided customers with multiple choice for using services offered by an organization. The online service attributes of convenience and ease of use are being given priority by companies for designing web-based services. In India, online shopping in general and online insurance services in particular, are yet to gain momentum. A large population still remains skeptical about its relative advantage over the traditional delivery channels. Limited Internet accessibility coupled with low technology literacy makes customers suspicious about online insurance services. The current research was directed toward understanding Indian customers behavior toward using online insurance services. Correlation, ANOVA and multiple regression tests were run to understand customer behavior. 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Khare; Indian Institute of Management Rohtak, Haryana, India; email: khare.arpita@gmail.com",{"$nulls":7},1.7412447E7,null,null,null,"English","J. Database Mark. Cust. Strategy Manage.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-84865171873"]
["Jiang H.; Ruan J.","Jiang, Hua (54910283700); Ruan, Junhu (25652148000)","54910283700; 25652148000","Applying rough set theory to evaluate network marketing performance of China's agricultural products",2010.0,"Journal of Computers",5.0,8.0,null,1264.0,1272.0,8.0,2.0,"10.4304/jcp.5.8.1264-1272","https://www.scopus.com/inward/record.uri?eid=2-s2.0-78651548671&doi=10.4304%2fjcp.5.8.1264-1272&partnerID=40&md5=27336447b97310395e38c52bb2f4f852","School of Economics and Management, Hebei University of Engineering, Handan, China","Jiang H., School of Economics and Management, Hebei University of Engineering, Handan, China; Ruan J., School of Economics and Management, Hebei University of Engineering, Handan, China","Agricultural products network marketing means fully introducing e-commerce systems into the sale process of agricultural products, using information technologies to publish and collect the demand and price information, and relying on agricultural production bases and logistics distribution systems to enhance brand images, improve customer services, develop online marketing channels and ultimately expand marketing activities. It is very important to evaluate the performance of agricultural products network marketing. The paper proposed a performance evaluation model of agricultural products network marketing based on rough set theory. The model used genetic algorithm to reduce the initial decision table and, through calculating the importance of the decision attributes in the reduced decision table, identified the weight coefficients of various influencing indexes, effectively overcoming the subjectivity of weight coefficient determination in the current evaluation models. In the same time, the paper evaluated the network marketing performance of six agricultural enterprises and the results were in line with the actual results, which verified the validity of the proposed evaluation model. Lastly, the paper, according to the reduced results of the initial index system, proposed specific measures and suggestions to improve the network marketing performance of agricultural products. © 2010 ACADEMY PUBLISHER.","Agricultural products; Measures and suggestions; Network marketing; Performance evaluation; Rough set theory","Agricultural products; Decision tables; Marketing; Online systems; Agricultural enterprise; Agricultural productions; Brand image; Customer services; Decision attribute; E-commerce systems; Evaluation models; In-line; Index systems; Logistics distribution; Marketing activities; Measures and suggestions; Network marketing; Online marketing; Performance evaluation; Performance evaluation models; Price information; Rough set; Sale process; Weight coefficients; Rough set theory",{"$nulls":6},"Kotler P., Armstrong G., Principles of Marketing, (2001); Hanson W., Principles of Internet Marketing, (1999); Don P., Martha R., The One to One Future, (1996); Cliff A., Internet World Guide to One-to-One Web Marketing, (1998); Feng Y., The core idea of network marketing; Qu Y., Qi L., Network Marketing, (1998); Man-feng L., Zhi-cheng L., Study on the network marketing performance evaluation index system, Science & Technology Progress and Policy, 8, pp. 19-20, (2001); Wen-juan W., Shen-fu Q., Sheng-hai L., Developing network marketing of agricultural products to open up agricultural products circulation channel, Science Forum, 12, (2007); Kai-zhi H., Zhang-you W., Agricultural Products Network Marketing, Science, 10, (2006); Jiao L., Study on Network Marketing Current Situation and Development about Chinese Agricultural Product, (2004); Li P., Yong-zhuang L., Comprehensive Evaluation of Enterprise network marketing performance, Business Cultural, 1, (2008); Hassanien A.E., Intelligent Data Analysis of Breast Cancer Based on Rough Sets Theory, International Journal on Artificial Intelligence Tools, 12, 4, pp. 465-479, (2003); Kai-di L., Yan-jun P., Guang-yong S., Li-gen Y., The Unascertained Measurement Evaluation on a City's Environmental Quality, Systems Engineering-Theory & Practice, 12, pp. 53-58, (1999); Qing-Kui C., Xiang-Yang R., Chen L., Li-Bo L., The Analysis and Study of the Ability of Technical Innovation of Enterprises Based on Rough Set and Unascertained Measure Appraisement Model, Systems Engineering-Theory & Practice, 4, pp. 67-72, (2006)","H. Jiang; School of Economics and Management, Hebei University of Engineering, Handan, China; email: hdjianghua@126.com",{"$nulls":7},"1796203X",null,null,null,"English","J. Comput.","Article","Final",null,"Scopus","2-s2.0-78651548671"]
["Lau H.C.W.; Jiang Z.-Z.; Ip W.H.; Wang D.","Lau, H.C.W. (7201497785); Jiang, Zhong-Zhong (9335480600); Ip, W.H. (55498852200); Wang, Dingwei (10041877000)","7201497785; 9335480600; 55498852200; 10041877000","A credibility-based fuzzy location model with Hurwicz criteria for the design of distribution systems in B2C e-commerce",2010.0,"Computers and Industrial Engineering",59.0,4.0,null,873.0,886.0,13.0,56.0,"10.1016/j.cie.2010.08.018","https://www.scopus.com/inward/record.uri?eid=2-s2.0-78049361602&doi=10.1016%2fj.cie.2010.08.018&partnerID=40&md5=3566741aed9881b3ad3a72501e12e7fa","School of Management, University of Western Sydney, Sydney, Australia; Department of Management Science and Engineering, School of Business Administration, Northeastern University, Shenyang 110004, China; Department of Industrial and Systems Engineering, Hong Kong Polytechnic University, Hong Kong; Department of Systems Engineering, School of Information Science and Engineering, Northeastern University, Shenyang 110004, China","Lau H.C.W., School of Management, University of Western Sydney, Sydney, Australia; Jiang Z.-Z., Department of Management Science and Engineering, School of Business Administration, Northeastern University, Shenyang 110004, China; Ip W.H., Department of Industrial and Systems Engineering, Hong Kong Polytechnic University, Hong Kong; Wang D., Department of Systems Engineering, School of Information Science and Engineering, Northeastern University, Shenyang 110004, China","Facility location problem is one of the most critical elements in the design of distribution systems, and numerous studies have focused on this issue. However, facility location theory and guidelines for B2C firms are sparse. In this paper, with regard to the customer characteristics peculiar to B2C e-commerce and the turbulence of the competitive market, a new fuzzy location model is proposed to optimize the distribution system design in B2C e-commerce. The model adopts a hierarchical agglomerative clustering method to classify customers and estimate the fuzzy delivery cost. At the same time, due to the turbulence of competitive market, both market supply and customer demand are treated as fuzzy variables in the model. Afterward, the credibility measure and Hurwicz criterion are introduced to convert the model into a crisp one which has NP-hard complexity. In order to solve the crisp model, an improved genetic algorithm with particle swarm optimization is developed. Finally, the computational results of some numerical examples are used to illustrate the application and performance of the proposed model and algorithm. © 2010 Elsevier Ltd. All rights reserved.","B2C e-commerce; Credibility measure; Fuzzy location model; Fuzzy programming; Logistics; Meta-heuristics","Competition; Customer satisfaction; Design; Fuzzy systems; Hierarchical systems; Local area networks; Particle swarm optimization (PSO); Sales; Turbulence; B2C e-commerce; Credibility measure; Fuzzy location model; Fuzzy programming; Meta heuristics; Electronic commerce",{"$nulls":4},"Northeastern University Postdoctoral Science Foundation of China, (20080413); National Natural Science Foundation of China, NSFC, (70801012, 70931001); China Postdoctoral Science Foundation, (20080441087, 200902543); Hong Kong Polytechnic University, PolyU, (G-YF56)","The authors are grateful to the editor and reviewers for their valuable comments. This work was supported by the Hong Kong Polytechnic University Funding (Project No. G-YF56), the National Natural Science Foundation of China (Project Nos. 70801012, 70931001), China Postdoctoral Science Foundation (Project Nos. 20080441087, 200902543) and Northeastern University Postdoctoral Science Foundation of China (Project No. 20080413).  ","Banks A., Vincent J., Anyakoha C., A review of particle swarm optimization. Part II: Hybridisation, combinatorial, multicriteria and constrained optimization, and indicative applications, Natural Computing, 7, pp. 109-124, (2008); Bhattacharya U., Rao J.R., Tiwari R.N., Fuzzy multi-criteria facility location problem, Fuzzy Sets and Systems, 51, pp. 277-287, (1992); Bhattacharya U., Rao J.R., Tiwari R.N., Bi-criteria multi facility location problem in fuzzy environment, Fuzzy Sets and Systems, 56, pp. 145-153, (1993); Bin Q., Chen S.J., Sun S.Q., Cultural difference in e-commerce: A comparison between the US and China, Journal of Global Information Management, 11, pp. 199-214, (2003); Canos M.J., Ivorra C., Liern V., An exact algorithm for the fuzzy p-median problem, European Journal Operational Research, 116, pp. 80-86, (1999); Charnes A., Cooper W., Management Models and Industrial Applications of Linear Programming, (1961); Chen C.T., A fuzzy approach to select the location of the distribution center, Fuzzy Sets and Systems, 118, pp. 65-73, (2001); Chen C.B., Wei C.C., An efficient fuzzy MADM method for selecting facility locations, Journal of Engineering Valuation and Cost Analysis, 2, pp. 19-32, (1998); Cooper L., Location-allocation problems, Operation Research, 11, pp. 331-344, (1963); Darzentas J., A discrete location model with fuzzy accessibility measures, Fuzzy Sets and Systems, 23, pp. 149-154, (1987); Dong Y., Tang J.F., Xu B.D., Wang D.W., An application of swarm optimization to nonlinear programming, Computers & Mathematics with Applications, 49, pp. 1655-1668, (2005); Fang S.C., Wang D.W., Fuzzy Mathematics and Fuzzy Optimization, (1997); Goetschalckx M., Vidal C.J., Dogan K., Modeling and design of global logistics systems: A review of integrated strategic and tactical models and design algorithms, European Journal Operational Research, 143, pp. 1-18, (2002); Holland J.M., Adaptation in Natural and Artificial Systems, (1975); Huang X., Credibility-based chance-constrained integer programming models for capital budgeting with fuzzy parameters, Information Science, 176, pp. 2698-2712, (2006); Huang X., Chance-constrained programming models for capital budgeting with NPV as fuzzy parameters, Journal of Computational and Applied Mathematics, 198, 1, pp. 149-159, (2007); Huang X., A review of credibilistic portfolio selection, Fuzzy Optimization and Decision Making, 8, pp. 263-281, (2009); Hurwicz L., Some specification problems and application to econometric models (abstract), Econometrica, 19, pp. 343-344, (1951); Ishii H., Lee Y.L., Yeh K.Y., Fuzzy facility location problem with preference of candidate sites, Fuzzy Sets and Systems, 158, pp. 1922-1930, (2007); Jiang Z.Z., Wang D.W., Ip W.H., Fuzzy programming model and algorithm for optimal design of distribution centers for B2C e-commerce, Proceedings of 2007 IEEE International Conference on Automation and Logistics, pp. 1533-1539, (2007); Kennedy J., Eberhart R., Particle swarm optimization, Proceedings of IEEE International Conference on Neural Networks, pp. 1942-1948, (1995); Klose A., Using clustering methods in problems of combined location and routing, Operations Research Proceedings, pp. 411-416, (1995); Klose A., Drexl A., Facility location models for distribution system design, European Journal Operational Research, 162, pp. 4-29, (2005); Li X., Liu B., A sufficient and necessary condition for credibility measures, International Journal of Uncertainty, Fuzziness & Knowledge-Based Systems, 14, pp. 527-535, (2006); Li P.K., Liu B., Entropy of credibility distributions for fuzzy variables, IEEE Transactions on Fuzzy Systems, 16, pp. 123-129, (2008); Liu B., A survey of credibility theory, Fuzzy Optimization and Decision Making, 5, pp. 387-408, (2006); Liu B., Uncertain Theory, (2008); Liu B., Theory and Practice of Uncertain Programming, (2009); Liu B., Liu Y.-K., Expected value of fuzzy variable and fuzzy expected value models, IEEE Transactions on Fuzzy Systems, 10, 4, pp. 445-450, (2002); Liu M.L., Sahinidis N.V., Process planning in a fuzzy environment, European Journal of Operational Research, 100, pp. 142-169, (1997); Manzini R., Gebennini E., Optimization models for the dynamic facility location and allocation problem, International Journal of Production Research, 46, pp. 2061-2086, (2008); Orvosh D., Davis L., Using a genetic algorithm to optimize problems with feasibility constraints, Proceedings of the First IEEE Conference on Evolutionary Computation, pp. 548-553, (1994); Peidroa D., Mula J., Poler R., Verdegay J.L., Fuzzy optimization for supply chain planning under supply, demand and process uncertainties, Fuzzy Sets and Systems, 160, pp. 2640-2657, (2009); Perez J.M., Vega J.M., Verdegay J.L., Fuzzy location problems on networks, Fuzzy Sets and Systems, 142, pp. 393-405, (2004); Rao J.R., Saraswati K., Facility location problem on network under multiple criteria fuzzy set theoretic approach, International Journal of Systems Science, 19, pp. 2555-2559, (1988); Sivanandam S.N., Deepa S.N., Introduction to Genetic Algorithms, (2008); Spath H., Cluster-Formation Und-Analyse: Theorie, FORTRAN-Programme und Beispiele, (1983); Tan A., Wu O., Diffusion and impacts of the Internet and e-commerce in China, Electronic Market, 14, pp. 25-35, (2004); Wang J.T., Shu Y.F., Fuzzy decision modeling for supply chain management, Fuzzy Sets and Systems, 150, pp. 107-127, (2005); Wang Z.P., Yao D.Q., Huang P.Q., A new location-inventory policy with reverse logistics applied to B2C e-markets of China, International Journal of Production Economics, 107, pp. 350-363, (2007); Wen M., Iwamura K., Fuzzy facility location-allocation problem under the Hurwicz criterion, European Journal Operational Research, 184, pp. 627-635, (2008); Xu R.N., Zhai X.Y., Optimal models for single-period supply chain problems with fuzzy demand, Information Science, 178, pp. 3374-3381, (2008); Yang L.X., Ji X.Y., Gao Z.Y., Li K.P., Logistics distribution centers location problem and algorithm under fuzzy environment, Journal of Computational and Applied Mathematics, 208, pp. 303-315, (2007); Zadeh L.A., Fuzzy sets, Information and Control, 8, pp. 338-353, (1965); Zadeh L.A., Fuzzy sets as a basis for a theory of possibility, Fuzzy Sets and Systems, 1, pp. 3-28, (1978); Zhou J., Liu B., Modeling capacitated location-allocation problem with fuzzy demands, Computers & Industrial Engineering, 53, pp. 454-468, (2007)","Z.-Z. Jiang; Department of Management Science and Engineering, School of Business Administration, Northeastern University, Shenyang 110004, China; email: zzjiang@mail.neu.edu.cn",{"$nulls":7},3608352.0,null,"CINDD",null,"English","Comput Ind Eng","Article","Final",null,"Scopus","2-s2.0-78049361602"]
["Montealegre F.; Thompson S.; Eales J.S.","Montealegre, Fernando (54419003400); Thompson, Sarahelen (57188785530); Eales, James S. (7005254668)","54419003400; 57188785530; 7005254668","An empirical analysis of the determinants of success of food and agribusiness e-commerce firms",2007.0,"International Food and Agribusiness Management Review",10.0,1.0,null,61.0,81.0,20.0,21.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-33947100368&partnerID=40&md5=8116aeabefcbc6cf61ffb3c0071547ba","Department of Agricultural Economics, Purdue University, West Lafayette, IN 47907-2056, 403 W. State St., United States","Montealegre F., Department of Agricultural Economics, Purdue University, West Lafayette, IN 47907-2056, 403 W. State St., United States; Thompson S., Department of Agricultural Economics, Purdue University, West Lafayette, IN 47907-2056, 403 W. State St., United States; Eales J.S., Department of Agricultural Economics, Purdue University, West Lafayette, IN 47907-2056, 403 W. State St., United States","E-commerce's value creation in agricultural and food markets will only occur to the extent that e-commerce firms exist throughout the supply chain. The problem is that e-commerce firms throughout the agricultural and food supply chain have faced a serious challenge in staying in business. Many have been forced to exit the market, and only a few have survived to develop into functional web-based businesses. The objective of this research study is to identify characteristics that are associated with successful e-commerce firms throughout the agricultural and food supply chain. Relevant e-commerce and agricultural e-commerce literature suggests several characteristics that influence the success for agricultural and food e-commerce firms. A limited-dependent variable technique, logistic regression, is used to relate websites' characteristics to their probability of survival. © 2007 International Food and Agribusiness Management Association (IAMA). All rights reserved.","E-commerce; Food chains; Logistical regression; Survival probability",{"$nulls":7},"Allison P.D., Logistic Regression Using the SAS System: Theory and Application, (1999); Carrere A., E-Business Models in Agriculture, (2001); Cash Jr. J.I., Konsynski B.R., IS Redraws Competitive Boundaries, Harvard Business Review, 63, 2, (1985); Dai Q., Kauffman R.J., Business Models for Internet-Based B2B Electronic Markets: An Exploratory Assessment, (2001); Dai I., Kauffman R.J., To Be or Not B2B? An Evaluative Model for E-Procurement Channel Adoption, (2001); The Best of the Web B2B Directory, (2001); Harrell F.E., Regression Modeling Strategies: With Applications to Linear Models, Logistic Regression and Survival Analysis, (2001); Kaplan S., Showney M., E-Hubs: The New B2B Marketplaces, Harvard Business Review, 78, 6, pp. 119-125, (2000); Lucking-Reiley D., Spulber D.F., Business-to-Business Electronic E-Commerce, Journal of Economic Perspectives, 15, 1, pp. 55-68, (2001); Lucking-Reiley D., Auctions on the Internet: What's being Auctioned, and How?, Journal of Industrial Economics, 48, 3, pp. 227-252, (2000); Schiefer G., Kreuder A.C., Vertical and Horizontal Information Portals: Cooperation Models for Sector and Chain Information Services, (2001); Spulber D.F., Market microstructure: Intermediaries and the theory of the firm 1999; Thompson S., Nageotte C., List of Agricultural e-commerce Web sites. May 19, 2001; Thompson S., Sonka S.T., Potential Effects of Information Technology on the Economic Performance of Agricultural and Food Markets, American Journal of Agricultural Economics, pp. 657-662, (1997); Timmers P., Electronic Commerce: Strategies and Models for Business to Business Trading, (1999); Vulkan N., The Economics of E-Commerce: A Strategic Guide to Understanding and Designing the Online Marketplace, (2003); Wheatley W.P., Buhr B., DiPietre D., E-Commerce in Agriculture: Development, Strategy, and Market Implications, (2001)","S. Thompson; Department of Agricultural Economics, Purdue University, West Lafayette, IN 47907-2056, 403 W. State St., United States; email: sallyt@purdue.edu",{"$nulls":7},1.5592448E7,null,null,null,"English","Int. Food Agribus. Manage. Rev.","Article","Final",null,"Scopus","2-s2.0-33947100368"]
["Wu H.-H.","Wu, Hsing-Hao (35239056800)",3.52390568E10,"Evolving medical service in the information age: A legal analysis of applying telemedicine programs in Taiwan",2008.0,"Medicine and Law",27.0,4.0,null,775.0,785.0,10.0,1.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-58549096522&partnerID=40&md5=f9b12af5542fcc24575416926da65870","Department of Financial and Economic Law, National University of Kaohsiung, Kaohsiung, Taiwan; Indiana University-Bloomington, Bloomington, IN, United States","Wu H.-H., Department of Financial and Economic Law, National University of Kaohsiung, Kaohsiung, Taiwan, Indiana University-Bloomington, Bloomington, IN, United States","In the face of the information age, internet and telecommunication technologies have been widely applied in various settings. These innovational technologies have been used in the areas of e-commerce, long distance learning programs, entertainment, e-government, and so on. In recent years, the evolution of internet technology is also pervading the health care industry. This dramatic trend may significantly alter traditional medical practice as well as the means of delivery of health care. The idea of telemedicine is to use modern information technology as a means or platform to deliver health care service in remote areas and to manage medical information in digitalized forms. The progress of developing telemedicine, however, is rather slow. The main reason for this slow progress is not technological but rather legal. Health care providers are reluctant to promote this innovation in medical service mainly due to uncertain legal consequences and ethical concerns. Although there are many legal challenges surrounding telemedicine, this note will examine major legal issues including licensure, malpractice liability, and privacy protection. Furthermore, I will discuss the potential of applying telemedicine programs in Taiwan's National Health Insurance Program (hereinafter referred to as NHI). © YOZMOT 2008.","E-health; Medical information; Medical liability; Privacy protection; Telemedicine",{"$nulls":7},"(2006); Kearney J., Telemedicine: Ringing in a New Era of Health Care Delivery, 5, Commlaw Conspectus, 289, (1997); Derek F., Meek T., elemedicine: How an Apple (or Another Computer) May Bring Your Doctor Closer? 29, Colum. L. Rev, 173, (1999); Boxer B.K., Telemedicine: Overcoming the Legal Issues Surrounding Telemedicine or Allowing Physicians to Charge for Phone Calls, Health Law, 10, (1998); Rackett C.M., Telemedicine Today and Tomorrow: Why \"Virtual\" Privacy is not Enough, 25, Fordham Urb. L.J, 167, (1997); Standards for Privacy of Individually Identifiable Health Information, PART 164, (2001); (2006); Blum J.D., The Role of Law In Global E-Health: A Tool For Development And Equity In A Digitally Divided World, 46, St. Louis U. L.J, 85, (2002)",null,null,"Yozmot Heiliger Ltd",{"$nulls":5},7231393.0,null,"MELAD",1.9202856E7,"English","Med. Law","Article","Final",null,"Scopus","2-s2.0-58549096522"]
["Janssen M.; Kuk G.; Wagenaar R.W.","Janssen, Marijn (16199813000); Kuk, George (6603024719); Wagenaar, René W. (55909611800)","16199813000; 6603024719; 55909611800","A survey of Web-based business models for e-government in the Netherlands",2008.0,"Government Information Quarterly",25.0,2.0,null,202.0,220.0,18.0,100.0,"10.1016/j.giq.2007.06.005","https://www.scopus.com/inward/record.uri?eid=2-s2.0-40649101514&doi=10.1016%2fj.giq.2007.06.005&partnerID=40&md5=c2e15d02f0fb27fc8dab7c824cd780e6","School of Technology, Policy and Management, Delft University of Technology, NL-2600 GA Delft, Jaffalaan 5, Netherlands; Nottingham University Business School, Nottingham, NG8 1BB, Jubilee Campus, Wollaton Road, United Kingdom","Janssen M., School of Technology, Policy and Management, Delft University of Technology, NL-2600 GA Delft, Jaffalaan 5, Netherlands; Kuk G., Nottingham University Business School, Nottingham, NG8 1BB, Jubilee Campus, Wollaton Road, United Kingdom; Wagenaar R.W., School of Technology, Policy and Management, Delft University of Technology, NL-2600 GA Delft, Jaffalaan 5, Netherlands","Governments worldwide are increasingly using Web-based business models to enhance their service delivery. Yet the concept of the business model is unexplored within the context of e-government. Drawing upon the literature on e-commerce, we develop a taxonomy for analyzing Web-based business models for e-government. Based on a systematic survey of 59 e-government Web sites in the Netherlands, our findings indicate that most of the Web sites use the content provider or direct-to-customer business models, while only a few are using novel business models. Overall, the concept of business model is appealing and useful in the public sector. Specifically it compliments research on Web site quality by analyzing and describing Web sites using atomic e-government business models and suggesting improvements by using combinations of business models. © 2007 Elsevier Inc. All rights reserved.","Business models; e-Government; e-Government business models; Value creation; Web site survey",{"$nulls":7},"Afuah A., Tucci C.L., Internet business models and strategies, (2000); Bertot J.C., Jaeger P.T., User-centered e-government: Challenges and benefits for government Web sites, Government Information Quarterly, 23, 2, pp. 163-169, (2006); Evans D., Yen D.C., E-Government: Evolving relationship of citizens and government, domestic and international development, Government Information Quarterly, 23, 2, pp. 207-235, (2006); Hawkins R., Looking beyond the dot com bubble: Exploring the form and function of business models in the electronic marketplace, E-life after the dot com bust, (2004); Hazlett S.A., Hill F., E-government: The realities of using IT to transform the public sector, Managing Service Quality, 13, 6, pp. 445-452, (2003); Hedman J., Kalling T., The business model concept: Theoretical underpinnings and empirical illustrations, European Journal of Information Systems, 12, 1, pp. 49-59, (2003); Janssen M., Joha A., Motives for establishing shared service centers in public administrations, International Journal of Information Management, 26, 2, pp. 102-116, (2006); Kelly J.M., The dilemma of the unsatisfied customer in a market model of pubic administration, Public Administration Review, 65, 1, pp. 76-84, (2005); King C.S., Feltey K.M., Susel B.O.l., The question of participation: Toward authentic public participation in public administration, Public Administration Review, 58, 4, pp. 317-326, (1998); Layne K., Lee J., Developing fully functional e-government: A four stage model, Government Information Quarterly, 18, 2, pp. 122-136, (2001); Mahadevan B., Business models for Internet-based e-commerce, California Management Review, 42, 4, pp. 55-69, (2000); Milward H.B., Snyder L.O., Electronic government: Linking citizens to public organizations through technology, Journal of Public Administration Research and Theory, 6, 2, pp. 261-275, (1996); MinBZK, Terug naar de toekomst. Over het gebruik van informatie-en communicatietechnologie in de openbare sector, (1995); MinBZK, Actieprogramma Elektronische Overheid. Een efficiëntere en effectievere overheid op de elektronische snelweg, (1998); MinBZK, Contract met de Toekomst. Een visie op de elektronische relatie overheid-burger, (2000); MinBZK, Publiek dienstverlening 65% elektronisch, (2004); Moon M.J., The evolution of e-government among municipalities; rhetoric or reality?, Public Administration Review, 62, 4, pp. 424-433, (2002); Naushad F., Wield D., From followers to leaders. Managing technology and innovation in newly industrializing countries, (2002); Porter M.E., Strategy and the Internet, Harvard Business Review, 79, 2, pp. 63-78, (2001); Reddick C.G., A two-stage model for e-government growth: Theories and empirical evidence for U.S. cities, Government Information Quarterly, 21, pp. 51-64, (2004); Scott J.R., E\" the people: Do US municipal government web sites support public involvement?, Public Administration Review, 66, 3, pp. 341-353, (2006); Strejcek G., Theil M., Technology push, legislation pull? E-government in the European Union, Decision Support Systems, 34, 3, pp. 305-313, (2002); Thomas J.C., Streib G., The new face of government: Citizen-initiated contact in the era of e-government, Journal of Public Administration Research and Theory, 13, 1, pp. 83-102, (2003); Timmers P., Business models for electronic markets, Electronic Markets, 8, 2, pp. 3-8, (1998); Tolbert C.J., Mossberger K., The effects of e-government on trust and confidence in government, Public Administration Review, 66, 3, pp. 354-369, (2006); Wallace W., The logic of science in sociology, (1971); Weill P., Vitale M., Place to space: Migrating to e-business models, (2001); Welch E.W., Hinnant C.C., Moon M.J., Linking citizen satisfaction with e-government and trust in government, Journal of Public Administration Research and Theory, 15, 3, pp. 371-391, (2004); West D.M., e-government and the transformation of service delivery and citizen attitudes, Public Administration Review, 64, 1, pp. 15-27, (2004); Wimmer M.A., Integrated service modelling for online one-stop government, Electronic Markets, 12, 3, pp. 149-156, (2002); Winkel N., Gemeenten op het Internet, problemen en mogelijkheden, (2005)","M. Janssen; School of Technology, Policy and Management, Delft University of Technology, NL-2600 GA Delft, Jaffalaan 5, Netherlands; email: M.F.W.H.A.Janssen@tudelft.nl",{"$nulls":7},"0740624X",null,"GIQUE",null,"English","Gov. Inf. Q.","Article","Final",null,"Scopus","2-s2.0-40649101514"]
["Abbad M.; Abbad R.; Saleh M.","Abbad, Muneer (34167491600); Abbad, Rami (55955714100); Saleh, Malik (55744204900)","34167491600; 55955714100; 55744204900","Limitations of e-commerce in developing countries: Jordan case",2011.0,"Education, Business and Society: Contemporary Middle Eastern Issues",4.0,4.0,null,280.0,291.0,11.0,39.0,"10.1108/17537981111190060","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84884507970&doi=10.1108%2f17537981111190060&partnerID=40&md5=e5b5ec177f19730e586a96e1c6b89a2c","PMU University, Dammam, Saudi Arabia; Coventry University, Coventry, United Kingdom","Abbad M., PMU University, Dammam, Saudi Arabia; Abbad R., Coventry University, Coventry, United Kingdom; Saleh M., PMU University, Dammam, Saudi Arabia","Purpose: The purpose of this paper is to clarify the status of e-commerce in terms of limitations, problems and barriers facing the application and use of e-commerce in Jordan. Design/methodology/approach: A questionnaire approach was employed in this research study to obtain the most appropriate information for identifying the main limitations of e-commerce in the context of the study. A delivery and collection questionnaire was used as a method for obtaining data from e-commerce customers contacted through a number of universities. Findings: There are found to be six main limitations of e-commerce: security and trust; internet experience; enjoyment; language; legal issues; and technology acceptance (ease of use and usefulness). The results of this research showed that the main limitations of e-commerce in Jordan appeared to be related to non-technical limitations. The reason behind this result could be related to the lack of students' awareness of technical issues, in that they might not have known about the technical issues that could face e-commerce. Research limitations/implications: This research provides the foundation for additional research in developing countries related to e-commerce, the results of which would be internationally useful. Comparison between countries could also be significant. Finally, investigation of the limitations of e-commerce from a company point of view could be useful because companies are the providers of these services. Originality/value: The paper summarizes the main limitations of e-commerce from the Jordanian customer's point of view. In addition, the results of this study extend the body of knowledge by providing a set of limitations that may explain customers' perceptions of e-commerce benefits and limitations. One finding - the difference in attitudes related to age, gender, internet experience, and income - may be of use to the development of company marketing strategies, for example, in regard to what enjoyment factors might motivate customers to do their shopping online. Managers and designers may find such information useful for predicting which systems will be acceptable to customers, diagnosing reasons why the system may not be fully acceptable to customers, and which corrective actions to take in increasing the acceptability of their systems. © Emerald Group Publishing Limited.","Consumer behaviour; Developing countries; Electronic commerce; Jordan",{"$nulls":7},"Al-Jaghoub S., Westrup C., Jordan and ICT development: Towards a competition state, International Technology and People, 16, 1, pp. 93-110, (2003); Bajaj C., Pfister H., Lorensen B., Kindlmann G., Schroeder W., Avila L.S., Martin K., Machiraju R., Lee J., The transfer function bake-off, Computer Graphics and Applications, IEEE, 21, 3, pp. 16-22, (2001); Google Privacy Chief calls for international data protection standards, BeSpacific - Accurate Focused Law and Technology News, (2007); Chircu A.M., Kauffman R.J., Limits to value in electronic commerce-related IT investments, Journal of Management Information Systems, 17, 2, pp. 59-80, (2000); Connolly C., Electronic Commerce: Legal and Consumer Issues, (1998); Davis F.D., A technology acceptance model for empirically testing new end-user acceptance of information technology, (1986); Davis F.D., Bagozzi R., Warshaw P., Extrinsic and intrinsic motivation to use computers in the workplace, Journal of Applied Social Psychology, 22, 14, pp. 1111-1122, (1992); Eastin M.S., Diffusion of e-commerce: An analysis of the adoption of four e-commerce activities, Telematics and Informatics, 19, 3, pp. 251-267, (2002); Hair J.F., Anderson R.E., Tatham R.L., Black W.C., Multivariate Data Analysis, (2006); Heung V.C.S., Barriers to implementing e-commerce in the travel industry: A practical perspective, International Journal of Hospitality Management, 22, pp. 111-118, (2003); Usage and Population Statistics, (2008); Kotab M., Helsen K., Global Marketing Management, (2001); Liao Z., Cheung M.T., Internet-based e-banking and consumer attitudes: An empirical study, Information & Management, 39, 4, pp. 283-295, (2001); Mayer R., Davis J., Schoorman F., An integrate model of organisational trust, Academy of Management Review, 20, 3, pp. 709-734, (1995); Naser K., Comprehensives of disclosure of non-financial companies listed on the Amman financial market, International of Commerce and Management, 2, 8, pp. 88-119, (1998); Palumbo F., Herbig P., International marketing tool: The internet, Industrial Management & Data Systems, 98, 6, pp. 253-261, (1998); Pikkarainen T., Pikkarainen K., Karjaluoto H., Pahnila S., Consumer acceptance of online banking: An extension of the technology acceptance model, Internet Research, 14, 3, pp. 224-235, (2004); Sahawneh M., E-Commerce: The Jordanian Experience, (2003); Singh S.P., Abbott D., Stoutjesdijk P.A., Construct design for efÛcient, effective and highthroughput gene silencing in plants, The Plant Journal, 27, 6, pp. 581-590, (2001); Turban E., Lee J.K., King D., Liang T.P., Turban D., Electronic Commerce 2010: A Managerial Perspective, (2010); van Slyke C., Belanger F., Haynes J., The impact of interface complexity on elderly users: An extension of the technology acceptance model, (2003)","M. Abbad; PMU University, Dammam, Saudi Arabia; email: muneerabbad@yahoo.com",{"$nulls":7},1.7537991E7,null,null,null,"English","Educ. Bus. Soc. Contemp. Middle East Issues","Article","Final",null,"Scopus","2-s2.0-84884507970"]
["Kauffman R.J.; Li T.; Van Heck E.","Kauffman, Robert J. (35083571300); Li, Ting (55936186500); Van Heck, Eric (55903215400)","35083571300; 55936186500; 55903215400","Business network-based value creation in electronic commerce",2010.0,"International Journal of Electronic Commerce",15.0,1.0,null,113.0,144.0,31.0,46.0,"10.2753/JEC1086-4415150105","https://www.scopus.com/inward/record.uri?eid=2-s2.0-77958146597&doi=10.2753%2fJEC1086-4415150105&partnerID=40&md5=ff363cb867e98b3d9514721a97d75351","W.P. Carey School of Business, Arizona State University, United States; Rotterdam School of Management, Erasmus University, Netherlands","Kauffman R.J., W.P. Carey School of Business, Arizona State University, United States; Li T., Rotterdam School of Management, Erasmus University, Netherlands; Van Heck E., Rotterdam School of Management, Erasmus University, Netherlands","Information technologies (IT) have affected economic activities within and beyond the boundaries of the firm, changing the face of e-commerce. This article explores the circumstances under which value is created in business networks made possible by IT. Business networks combine the capabilities of multiple firms to produce and deliver products and services that none of them could more economically produce on its own and for which there is demand in the market. We call this business network-based value creation. We apply economic theory to explain the conditions under which business networks will exist and are able to sustain their value-producing activities. Informedness has the potential to increase the complexity of consumer demand. Addressing this demand requires flexible production and delivery of products and services, and can be achieved by value-adding business networks supported by IT, standardized technology, and business process solutions. We also examine the benefits associated with business network-based value creation and fair value-sharing to support the sustainability of business networks. We develop a set of propositions and draw upon multiple case examples from the travel and hospitality industry to validate our theoretical perspectives on business network-based value creation. The results demonstrate that this industry is going through a digital transformation that makes it possible for many firms to engage in highly effective and innovative network-based value creation. © 2010 M.E. Sharpe, Inc. All rights reserved.","Business networks; case studies; e-commerce; economic theory; network stability; network sustainability; theory development; travel and hospitality industry; value creation; value sharing",{"$nulls":5},"Rotterdam School of Management at Erasmus University; Nederlandse Organisatie voor Wetenschappelijk Onderzoek, NWO, (645000001)","An earlier version of this article, called “A Theory of Informedness and Business Network Co-Production,“ appeared in R.H. Sprague (ed.), Proceedings of the 43rd Hawaii International Conference on System Sciences (Los Alamitos, CA: IEEE Computer Society Press, 2010). The authors thank Eric Clemons, Thomas Weber, and the reviewers for their suggestions for improving this paper. They appreciate the helpful comments of Qizhi Dai, Otto Koppius, Juliana Tsai, Diederik van Liere, Peter Vervest, Bin Wang, and Hugh Watson. They also thank the participants and the anonymous reviewers from the Competitive Strategy, Economics and IS mini-track of the 2010 Hawaii International Conference on System Sciences. Rob Kauffman acknowledges generous support from the W.P. Carey Chair in Information Systems and the Center for Advancing Business Through Information Technology at Arizona State University, as well as from the Rotterdam School of Management at Erasmus University. The Dutch National Science Foundation (NWO) supports Ting Li’s research under Complexity Grant #645000001. She also thanks the Erasmus Research Institute of Management at Erasmus University for additional funding. The usual disclaimers apply.","Almasy S., Results by Social Networking with Airlines, (2009); Bakos J.Y., Nault B.R., Ownership and investment in electronic networks, Information Systems Research, 8, 4, pp. 321-341, (1997); Bala H., Venkatesh V., Assimilation of interorganizational business process standards, Information Systems Research, 18, 3, pp. 340-362, (2007); Barrett S., Konsynski B., Inter-organization information sharing systems, MIS Quarterly, 6, pp. 93-105, (1982); Baumol W.J., Willig R.D., Fixed costs, sunk costs, entry barriers, and sustainability of monopoly, Quarterly Journal of Economics, 96, 3, pp. 405-431, (1981); Beardi C., Carlson brings loyalty to the Internet: Web site allows consumer offers based on Gold Points, Advertising Age, (2000); Benbasat I., Goldstein D., Mead M., The case research strategy in studies of information systems, MIS Quarterly, 11, 3, pp. 369-386, (1987); Breuckner J.K., The benefits of code-sharing and antitrust immunity for international passengers, with an application to the Star alliance, Journal of Air Transport Management, 9, 2, pp. 83-89, (2003); Business wire staff. 24k Gold Points selects USInternetworking to manage innovative e-commerce platform, Business Wire, (2000); Clemons E.K., How information changes consumer behavior and consumer behavior determines corporate strategy, Journal of Management Information Systems, 25, 2, pp. 13-40, (2008); Clemons E.K., Gao G.G., Consumer informedness and diverse consumer purchasing behaviors: Traditional mass-market, trading down, and trading out into the long tail, Electronic Commerce Research and Applications, 7, 1, pp. 3-17, (2008); Clemons E.K., Kimbrough S.O., Information systems, telecommunications, and their effects on industrial organization, Proceedings of the Seventh International Conference on Information Systems, pp. 99-108, (1986); Clemons E.K., Kleindorfer P.R., An economic analysis of interorganizational information technology, Decision Support Systems, 8, 5, pp. 431-446, (1992); Clemons E.K., Row M.C., Information technology at Rosenbluth travel: Competitive advantage in a rapidly growing global service company, Journal of Management Information Systems, 8, 2, pp. 53-79, (1991); Clemons E.K., Gu B., Lang K.R., Newly vulnerable markets in an age of pure information products: An analysis of online music and online news, Journal of Management Information Systems, 19, 3, pp. 17-42, (2002); Clemons E.K., Reddi S.P., Row M.C., The impact of IT on the organization of economic activity: \"Move to the middle\" hypothesis, Journal of Management Information Systems, 10, 2, pp. 9-35, (1993); Coase R.H., The nature of the firm, Economica, 4, 16, pp. 386-405, (1937); Copeland D.G., McKenney J.L., Airline reservations systems: Lessons from history, MIS Quarterly, 12, 3, pp. 353-370, (1988); Cowen M., Dynamic packaging drives ancillary sales growth for BA, Travolution, (2010); Crawford J., Larsons M., Case Study: Integration of Travel Technology. 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Hotel and Restaurant Administration Quarterly, 41, 3, (2000); History of Loyalty Programs, (2010); Fung V., Fung W., Wind Y.J., Competing in A Flat World: Building Enterprises for A Borderless World, (2008); Gilbert R.J., Mobility barriers and the value of incumbency, Handbook of Industrial Organization, 1, pp. 475-535, (1989); Outlook 2001: Aroundtable discussion, Hotel Online, (2001); Granados N., Kauffman R.J., King B., How has electronic travel distribution been transformed? A test of the theory of newly vulnerable markets, Journal of Management Information Systems, 25, 2, pp. 73-96, (2008); Granovetter M.S., The strength of weak ties, American Journal of Sociology, 78, 6, pp. 1360-1380, (1973); Gulati R., Kletter D., Shrinking core, expanding periphery: The relational architecture of high-performing organizations, California Management Review, 47, 3, pp. 77-104, (2005); Han K., Kauffman R.J., Nault B.R., Relative importance, specific investment and ownership in interorganizational IS, Information Technology and Management, 9, 3, pp. 181-200, (2008); About HHonors, (2010); Hitt L.M., IT and firm boundaries: Evidence from panel data, Information Systems Research, 10, 2, pp. 134-149, (1999); Ito H., Lee D., Domestic code-sharing practices in the U. S. airline industry, Journal of Air Transport Management, 11, 2, pp. 89-97, (2005); Jarvenpaa S.L., Ives B., The global network organization of the future: Information management opportunities and challenges, Journal of Management Information Systems, 10, 4, pp. 25-58, (1994); Jensen M.C., Meckling W.H., Theory of the firm: Managerial behavior, agency costs and ownership structure, Journal of Financial Economics, 3, 4, pp. 305-360, (1976); Jones C., Jet Blue and United give twitter a try to sell airline seats fast, USA Today, (2009); Kambil A., Short J.E., Electronic integration and business network redesign: A roles-linkage perspective, Journal of Management Information Systems, 10, 4, pp. 59-83, (1994); Katz M., Shapiro C., Network externalities, competition, and compatibility, American Economic Review, 75, 3, pp. 424-440, (1985); Katz M., Shapiro C., Technology adoption in the presence of network externalities, Journal of Political Economy, 94, 4, pp. 822-841, (1986); Kauffman R.J., Mohtadi H., Proprietary and open systems adoption in e-procurement: A risk-augmented transaction cost perspective, Journal of Management Information Systems, 21, 1, pp. 137-166, (2004); Kauffman R.J., Li T., Van Heck E., Vervest P., Consumer informedness and hyperdifferentiation: An empirical test of the \"trading down\" and \"trading out\" hypotheses, Proceedings of the 42th Annual Hawaii International Conference on System Sciences, (2009); Kohli R., Grover V., Business value of IT: An essay for expanding research directions to keep up with the times, Journal of the Association for Information Systems, 9, 1, pp. 23-29, (2008); Kontzer T., Momentum builds behind travel-industry XML spec, Information Week, (2005); Li T., Van Heck E., Vervest P., Information capability and value creation strategy: Advancing revenue management through mobile ticketing technologies, European Journal of Information Systems, 18, 1, pp. 38-51, (2009); Magretta J., Fast, global, and entrepreneurial: Supply chain management, Hong Kong style, Harvard Business Review, 76, 5, pp. 102-115, (1998); Malone T.W., Modeling coordination in organizations and markets, Management Science, 33, 10, pp. 1317-1332, (1987); Malone T.W., Yates J., Benjamin R.I., Electronic markets and electronic hierarchies, Communications of the ACM, 30, 6, pp. 484-497, (1987); McFarlan F.W., Kirby W.C., Manty T.Y., Li, Fung, Harvard Business School Case No. 307-077, (2006); NS Business Card: Relaxed Travel, Relaxed Business, (2009); O'Neal J.W., Jacob M.S., Farmer A.K., Martin K.G., Development of a code-share flight-profitability system at Delta Air Lines, Interfaces, 37, 5, pp. 436-444, (2007); Home Page, Sidebar Quotation, (2010); Pfeffer J., Salancik G.R., The External Control of Organizations: A Resource Dependence Perspective, (1978); Powell W.W., Neither market nor hierarchy: Network forms of organization, Research in Organizational Behavior, pp. 295-336, (1990); Prahalad C.K., Ramaswamy V., The Future of Competition: Co-Creating Unique Value with Customers, (2004); Rai A., Patnayakuni R., Seth N., Firm performance impacts of digitally enabled supply chain integration capabilities, MIS Quarterly, 30, 2, pp. 225-246, (2006); Riggins F.J., Kriebel C.H., Mukhopadhyay T., The growth of interorganizational systems in the presence of network externalities, Management Science, 40, 8, pp. 984-998, (1994); Shapiro C., Varian H.R., Information Rules: A Strategic Guide to the Network Economy, (1999); Thorelli H.B., Networks: Between markets and hierarchies, Strategic Management Journal, 7, 1, pp. 37-51, (1986); Continental Airlines and United Airlines Announce Comprehensive Plan for Global Cooperation, (2008); Van Heck E., Vervest P., Smart business networks: How the network wins, Communications of the ACM, 50, 6, pp. 28-37, (2007); Vinod B., Alliance revenue management, Journal of Revenue and Pricing Management, 4, 1, pp. 66-82, (2005); Weber K., Sparks B., Consumer attributions and behavioral responses to service failures in strategic airline alliance settings, Journal of Air Transport Management, 10, 5, pp. 361-367, (2004); Wigand R.T., Steinfield C.W., Markus M.L., IT standards choices and industry structure outcomes: The case of the U. 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["Wallace D.W.; Johnson J.L.; Umesh U.N.","Wallace, David W. (12143552500); Johnson, Jean L. (35114901000); Umesh, U.N. (6505986362)","12143552500; 35114901000; 6505986362","Multichannels strategy implementation: The role of channel alignment capabilities",2009.0,"Decision Sciences",40.0,4.0,null,869.0,900.0,31.0,21.0,"10.1111/j.1540-5915.2009.00254.x","https://www.scopus.com/inward/record.uri?eid=2-s2.0-72449142193&doi=10.1111%2fj.1540-5915.2009.00254.x&partnerID=40&md5=8a098166a872deede1a7d311a8f60c50","Department of Marketing, College of Business, Illinois State University, Normal, IL 61790-5590, United States; Department of Strategy and Marketing, Amsterdam Business School, Amsterdam, Netherlands; Department of Marketing, College of Business and Economics, Washington State University, Vancouver, WA 98686-9600, United States","Wallace D.W., Department of Marketing, College of Business, Illinois State University, Normal, IL 61790-5590, United States; Johnson J.L., Department of Strategy and Marketing, Amsterdam Business School, Amsterdam, Netherlands; Umesh U.N., Department of Marketing, College of Business and Economics, Washington State University, Vancouver, WA 98686-9600, United States","A firm's distribution, channels represent a key portfolio of resources that can be leveraged for competitive advantage. One approach to this portfolio that has become increasingly important in recent years is multichannel distribution. (MCD). While this strategy has important benefits in terms of market coverage and firm performance, the use of multiple channels seriously affects downstream channel roles such as service delivery, as the financial rewards to channel members and the services they offer are separated. A channel member who offers poor or no service can free-ride on the services offered to the same customer from a different channel. We draw on agency theory to explain these negative consequences. Additionally, the resource-based view of the firm, along with capabilities theory provides two key means of alleviating these consequences: channel tracking capabilities and reward alignment capabilities. The study, conducted in an. industry facing serious MCD issues (the outdoor sporting goods industry), used key informant data matched to secondary data. Our results show that managers can reap the performance rewards of MCD strategies while minimizing its negative consequences. In particular, monitoring practices such as frequent site visits and phone contact with customers develop the firm's channel tracking capabilities, allowing managers to better monitor downstream activities. This becomes particularly important as the complexity from having multiple channels increases. Likewise, reward alignment capabilities such as retail price maintenance agreements and cooperative advertising enable the manager to minimize conflict among channel participants by ensuring sufficient profitability for all channel members. © 2009, Decision Sciences Institute.","B2C E-Commerce; Business-to-business marketing; Channel management; Distribution channels; Supplier-customer relationship",{"$nulls":7},"Achrol R.S., Stern L.W., Environmental determinants of decisionmaking uncertainty in marketing channels, Journal of Marketing Research, 25, 1, pp. 36-50, (1988); Alchian A., Demsetz H., Production, information costs, and economic organization, American Economic Review, 62, 5, pp. 777-795, (1972); Anderson J.C., Narus J.A., A model of the distributor's perspective of distributor-manufacturer working relationships, Journal of Marketing, 48, 4, pp. 62-74, (1984); Armstrong J.S., Overton T.S., Estimating nonresponse bias in mail surveys, Journal of Marketing Research, 14, 3, pp. 396-402, (1977); 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Kearns G.S., Lederer A.L., A resource-based view of strategic IT alignment: How knowledge sharing creates competitive advantage, Decision Sciences, 34, 1, pp. 1-29, (2003); Kumar V., Venkatesan R., Who are the multichannel shoppers and how do they perform?: Correlates of multichannel shopping behavior, Journal of Interactive Marketing, 19, 2, pp. 44-63, (2005); Lee R.P., Grewal R., Strategic responses to new technologies and their impact on firm performance, Journal of Marketing, 68, 4, pp. 157-171, (2004); MacKinnon D.P., Warsi B., Dwyer J.H., A simulation study of mediated effect measures, Multivariate Behavioral Research, 30, 1, (1995); Mahajan J., Radas S., Vakhaira A.J., Channel strategies and stocking policies in uncapacitated and capacitated supply chains, Decision Sciences, 33, 2, pp. 191-222, (2002); Marsh H.W., Hocevar D., Application of confirmatory factor analysis to the study of self-concept: First-and higher order factor models and their invariance across groups, Psychological Bulletin, 97, 3, pp. 562-582, (1985); McHugh M., Humphreys P., McIvor R., Buyer-supplier relationships and organizational health, Journal of Supply Chain Management, 39, 2, (2003); Nunnally J.C., Bernstein I.H., Psychometric Theory, (1994); Penrose E.T., The Theory of the Growth of the Firm, (1958); Pisano G.P., Knowledge, integration, and the locus of learning: An empirical analysis of process development, Strategic Management Journal, 15, pp. 85-100, (1994); Podsakoff P.M., MacKenzie S.B., Lee J.Y., Podsakoff N.P., Common method biases in behavioral research: A critical review of the literature and recommended remedies, Journal of Applied Psychology, 88, 5, pp. 879-903, (2003); Rangaswamy A., Van Bruggen G.H., Opportunities and challenges in multichannel marketing: An introduction to the special issue, Journal of Interactive Marketing, 19, 2, pp. 5-11, (2005); Rabinovich E., Bailey J.P., Carter C.R., A transaction-efficiency analysis of an Internet retailing supply chain in the music CD industry, Decision Sciences, 34, 1, pp. 131-172, (2003); 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Management View, (1994); Saeed K.A., Malhotra M.K., Grover V., Examining the impact of interorganizational systems on process efficiency and sourcing leverage in buyer-supplier dyads, Decision Sciences, 36, 3, pp. 365-396, (2005); Sahin F., Robinson E.P., Flow coordination and information sharing in supply chains: Review, implications, and directions for future research, Decision Sciences, 33, 4, pp. 505-536, (2002); Sa Vinhas A., Anderson E., How potential conflict drives channel structure: Concurrent (direct and indirect) channels, Journal of Marketing Research, 42, 4, pp. 507-515, (2005); Stern L.W., Weitz B.A., The revolution in distribution: Challenges and opportunities, Long Range Planning, 30, 6, pp. 823-829, (1997); Teece D.J., Pisano G., Shuen A., Dynamic capabilities and strategic management, Strategic Management Journal, 18, 8, pp. 509-533, (1997); Vanbaal S., Dach C., Free riding and customer retention across retailers' channels, Journal of Interactive Marketing, 19, 2, pp. 75-85, (2005); Vickery S.K., Jayaram J., Droge C., Calantone R., The effects of an integrative supply chain strategy on customer service and financial performance: An analysis of direct versus indirect relationships, Journal of Operations Management, 21, 5, pp. 526-539, (2003); Wallace D.W., Giese J.L., Johnson J.L., Customer loyalty in the context of multiple channel strategies, Journal of Retailing, 80, 4, (2004); Weitz B.A., Jap S.D., Relationship marketing and distribution channels, Journal of the Academy of Marketing Sciences, 23, 4, pp. 305-320, (1995); Wemerfelt B., A resource-based view of the firm, Strategic Management Journal, 5, 2, pp. 171-180, (1984); Wu D., Ray G., Geng X., Whinston A., Implications of reduced search cost and free riding in e-commerce, Marketing Science, 23, 2, pp. 255-262, (2004)","D. W. Wallace; Department of Marketing, College of Business, Illinois State University, Normal, IL 61790-5590, United States; email: dwallac@ilstu.edu",{"$nulls":7},1.5405915E7,null,null,null,"English","Decis. Sci.","Article","Final",null,"Scopus","2-s2.0-72449142193"]
["Symonds J.","Symonds, Judith (22941889000)",2.2941889E10,"Palming the Future: E-Government Strategy Development for a Tertiary Education Organisation",2007.0,"International Journal of Electronic Government Research (IJEGR)",3.0,2.0,null,62.0,74.0,12.0,2.0,"10.4018/jegr.2007040104","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85001630766&doi=10.4018%2fjegr.2007040104&partnerID=40&md5=6e1e5359c32b98c8124538931f54ec28","Auckland University of Technology, New Zealand","Symonds J., Auckland University of Technology, New Zealand","Trans Training is a tertiary education organisation concerned with the provision of quality driving training for the commercial road transport, logistics, distribution, warehousing, port and stevedoring industry sectors. At present much of their service delivery to agents, clients and trainees is administered manually. This process is slow, inefficient and allows many opportunities for errors to creep into the enrolment process. eGovernment offers the Industry Training Organisation the potential for improved service delivery and client and trainee satisfaction as well as several interesting value-adding opportunities. However, there are several challenges to adopting an eGovernment strategy including security concerns, privacy concerns and acceptance of coordination of technological investments. Many of the challenges for eGovernment strategy occur at the point where theory is applied by individual organisations and this is not covered by the literature. Readers are given the opportunity to explore some of the realities of eGoverment strategy in this case study. © 2007, IGI Global. All rights reserved.","case study; e-commerce in SMEs; e-commerce strategy; electronic commerce; governmental IS; management issues; strategic planning",{"$nulls":7},"Bartels A., E-government in 2002: Initiatives for transforming public services using internet technologies, Planning Assumption, (2002); Chadwick A., May C., Interaction between states and citizens in the age of the internet: “e-government” in the United States, Britain, and the European Union, Governance: An International Journal of Policy, Administration and Institutions, 16, 2, pp. 271-300, (2003); Cohen S., Eimicke W., The use of the internet in government service delivery, e-government series, The PricewaterhouseC-oopers Endowment for The Business of Government, (2001); NZQA Spends $6.5m on Web-friendly Revamp, (2003); Grant G., Chau D., Developing a generic framework for e-government, Journal of Global Information Management, 13, 1, pp. 1-30, (2005); Layne K., Lee J., Developing fully functional e-government: A four stage model, Government Information Quarterly, 18, pp. 122-136, (2001); The digital strategy: Creating our digital future, (2005); Strategic Plan 2003 - 2008, A road transport industry training strategy in the new millennium; Porter M.E., Strategy and the internet, Harvard Business Review, pp. 62-78, (2001); Reddick C.G., A two-stage model of e-government growth: Theories and empirical evidence for U.S. cities, Government Information Quarterly, 21, pp. 51-64, (2004); E-government directions, (2003); Budget 2003 - education initiatives summary, (2003); Zimmermann W., ‘Estrategy’ for e-government in cities: An introduction, UMP-Asia Occasional Paper No. 62, (2005)",{"$nulls":8},1.5483886E7,null,null,null,"English","Int. J. Electron. Gov. Res.","Article","Final",null,"Scopus","2-s2.0-85001630766"]
["To M.L.; Ngai E.W.T.","To, March L. (55039263200); Ngai, E.W.T. (7003298974)","55039263200; 7003298974","Predicting the organisational adoption of B2C e-commerce: An empirical study",2006.0,"Industrial Management and Data Systems",106.0,8.0,null,1133.0,1147.0,14.0,140.0,"10.1108/02635570610710791","https://www.scopus.com/inward/record.uri?eid=2-s2.0-33749403190&doi=10.1108%2f02635570610710791&partnerID=40&md5=9d69389098620ece0d411d4c6fbd5347","Department of Management and Marketing, Hong Kong Polytechnic University, Kowloon, Hong Kong","To M.L., Department of Management and Marketing, Hong Kong Polytechnic University, Kowloon, Hong Kong; Ngai E.W.T., Department of Management and Marketing, Hong Kong Polytechnic University, Kowloon, Hong Kong","Purpose - Using the literature on innovation research, this paper proposes to establish and empirically test a prediction model which consists of four major factors in the adoption of online retailing by organisations, namely relative advantage, competitive pressure, channel conflict and technical resource competence. Design/methodology/approach - Data collected from 140 different companies indicate strong empirical support for the model. Relevant hypotheses were derived and tested by logistic regression analysis. Findings - The results revealed that relative advantage, competitive pressure and technical resource competence have positive effects on the adoption of online retailing. Research limitations/implications - The research was conducted in Hong Kong, which may limit the generalisability of the findings. Practical implications - While many studies contribute to an understanding of behaviours of the online market from a consumer perspective, there are few concrete investigations of the organisational viewpoint. With data obtained from practitioners in 140 companies, the major factors of online retailing adoption are addressed, providing strategic directions for managers to evaluate its adoption. Originality/value - Although many conceptual papers and case studies have identified different potential factors affecting the adoption of online retailing, there are few empirical studies which establish prediction models for its adoption. In fact, during the past decade, in spite of growing interest in B2C transactions, organisations have not necessarily rushed towards adopting online sales. It is critical to have more empirical evidence of the factors affecting the adoption of online sales to help managers further access the benefits of its continuous and potential development. This study attempts to fill the research gap. © Emerald Group Publishing Limited.","Electronic commerce; Innovation; Online operations; Retailing","Data acquisition; Mathematical models; Online systems; Regression analysis; Societies and institutions; Strategic planning; Innovation; Online operations; Retailing; Electronic commerce",{"$nulls":6},"Adham K.A., Ahmad M., Adoption of web site and e-commerce technology among Malaysian public companies, Industrial Management & Data Systems, 105, 2, pp. 1172-1187, (2005); Anderson J.C., Narus J.A., A model of distributor firm and manufacturer firm and manufacturer firm working partnerships, Journal of Marketing, 48, pp. 62-74, (1984); Bailey J.P., Bakos Y., An exploratory study of the emerging role of electronic intermediaries, International Journal of Electronic Commerce, 1, 3, pp. 7-29, (1997); Bakos Y., The emerging role of electronic marketplaces on the internet, Communication of the ACM, 41, 8, pp. 35-42, (1998); Benjamin R., Wigand R., Electronic markets and virtual value chains on the information superhighway, Sloan Management Review, 36, 2, pp. 62-72, (1995); 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Downs G.W.J., Mohr L.B., Conceptual issues in the study of innovation, Administrative Science Quarterly, 21, 4, pp. 700-714, (1976); Dubelaar C., Sohal A., Savic V., Benefits, impediments and critical success factors in B2C e-business adoption, Technovation, 25, pp. 1251-1262, (2005); Eid R., Trueman M., Factors affecting the success of business-to-business international internet marketing (B-to-B IIM): An empirical study of UK companies, Industrial Management & Data Systems, 104, pp. 16-30, (2004); Gatignon H., Robertson T.S., Technology diffusion: An empirical test of competitive effects, Journal of Marketing, 53, 1, pp. 35-49, (1989); Grandon E.E., Pearson J.M., Electronic commerce adoption: An empirical study of small and medium US businesses, Information & Management, 42, pp. 197-216, (2004); Grover V., Goslar M.D., The initiation, adoption, and implementation of telecommunications technologies in US organisation, Journal of Management Information Systems, 10, 1, pp. 141-163, (1993); Hair J.F., Anderson R.E., Tatham R.L., Black W.C., Multivariate Data Analysis, (1998); Hammond K., B2C e-commerce 2000-2010: What expert predict, Business Strategy Review, 12, 1, pp. 43-50, (2001); Hausman A., Stock J.R., Adoption and implementation of technological innovations within long-term relationships, Journal of Business Research, 56, pp. 681-686, (2003); Hsu M.H., Chiu C.M., Fu T.L., Determinants of continued use of the WWW: An integration of two theoretical models, Industrial Management & Data Systems, 104, 9, pp. 766-775, (2004); Huber G.P., Power D.J., Retrospective reports of strategic-level managers: Guidelines for increasing their accuracy, Strategic Management Journal, 6, 2, pp. 171-180, (1985); Iacovou C.L., Benbasat I., Dexter A.S., Electronic data interchange and small organisations: Adoption and impact of technology, MIS Quarterly, 19, 4, pp. 465-485, (1995); Indushobha C.S., Duchessi P., The initiation and adoption of client-server technology in organisations, Information & Management, 35, pp. 77-88, (1999); Kuan K.K.Y., Chau P.Y.K., A perception-based model for EDI adoption in small businesses using a technology-organisation-environment framework, Information & Management, 38, 8, pp. 507-521, (2001); Liang T.-P., Lin C.-Y., Chen D.-N., Effects of electronic commerce models and industrial characteristics on firm performance, Industrial Management & Data Systems, 104, 7, pp. 538-545, (2004); Lind M.R., Zmud R.W., Fischer W.A., Microcomputer adoption - The impact of organisational size and structure, Information & Management, 16, pp. 157-162, (1989); Moore G.C., Benbasat I., Development of an instrument to measure the perceptions of adopting an information technology innovation, Information Systems Research, 2, 3, pp. 192-223, (1991); Ngai E.W.T., Gunasekaran A., Implementation of EDI in Hong Kong: An empirical analysis, Industrial Management & Data Systems, 104, 1, pp. 88-100, (2004); Nunnally J.C., Psychometric Theory, (1978); Peng Y.-C., Trappey C.V., Liu N.-Y., Internet and e-commerce adoption by Taiwan semiconductor industry, Industrial Management & Data Systems, 105, 2, pp. 476-490, (2005); Premkumar G., Ramamurthy K., Nilakanta S., Implementation of electronic data interchange: An innovation diffusion perspective, Journal of Management Information Systems, 11, 2, pp. 157-186, (1994); Rogers E.M., Diffusion of Innovations, (1983); Salisbury W.D., Pearson R.A., Pearson A.W., Miller D.W., Perceived security and world wide web purchase intention, Industrial Management & Data Systems, 101, 4, pp. 165-176, (2001); Simpson M., Docherty A., E-commerce adoption support and advice for UK SMEs, Journal of Small Business and Enterprise Development, 11, 3, pp. 315-328, (2004); Srinivasan R., Lilien G.L., Rangaswamy A., Technological opportunism and radical technology adoption: An application to e-business, Journal of Marketing, 66, 3, pp. 47-60, (2002); Steinfield C., Bouwman H., Adelaar T., The dynamics of click-and-mortar electronic commerce: Opportunities and management strategies, International Journal of Electronic Commerce, 7, 1, pp. 93-119, (2002); Teo H.H., Wei K.K., Benbasat I., Predicting intention to adopt interorganisational linkages: An institutional perspective, MIS Quarterly, 27, 1, pp. 19-49, (2003); Thong J.Y.L., An integrated model of information systems adoption in small businesses, Journal of Management Information Systems, 15, 4, pp. 187-214, (1999); Warrts E., Van Everdingen Y.M., Hillegersberg J., The dynamics of factors affecting the adoption of innovations, The Journal of Product Innovation Management, 19, pp. 412-423, (2002)","M.L. To; Department of Management and Marketing, Hong Kong Polytechnic University, Kowloon, Hong Kong; email: msmto@polyu.edu.hk",{"$nulls":7},2635577.0,null,"IMDSD",null,"English","Ind Manage Data Sys","Article","Final",null,"Scopus","2-s2.0-33749403190"]
["Yaobin L.; Tao Z.","Yaobin, Lu (55506464900); Tao, Zhou (35304425400)","55506464900; 35304425400","A research of consumers' initial trust in online stores in China",2007.0,"Journal of Research and Practice in Information Technology",39.0,3.0,null,167.0,180.0,13.0,44.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-34548781303&partnerID=40&md5=9f959ba2761ed123b206427c1e03ca59","School of Management, Huazhong University of Science and Technology, Wuhan 430074, China","Yaobin L., School of Management, Huazhong University of Science and Technology, Wuhan 430074, China; Tao Z., School of Management, Huazhong University of Science and Technology, Wuhan 430074, China","With the development of e-commerce in China, some obstacles, such as poor Internet infrastructure and logistics problems have been gradually removed. Consumers ' distrust of online stores becomes the main problem impeding the acceptance of online shopping. Initial trust is the focus of this study because most Internet users in China have no experience of online shopping. Although the technology acceptance model (TAM) has been extensively studied, it is rarely tested in the context of initial trust or in developing countries such as China. Because China has a very different cultural environment from western countries, the results of existing studies on TAM and trust may not be directly applied to China without actual examination. The study integrates TAM with initial trust to explain online shopping behaviour of Chinese consumers. The results demonstrate that perceived usefulness, consumers ' trust propensity, website security and vendor reputation have significant effect on initial trust. Perceived usefulness fully mediates the \\ relationship between perceived ease of use and initial trust as well as the relationship between perceived ease of use and purchase intention. Copyright© 2007, Australian Computer Society Inc.","Initial trust; Online stores; Online trust; TAM","Consumer products; Online systems; Problem solving; Initial trust; Online stores; Online trust; Electronic commerce",{"$nulls":6},"AJZEN I., The theory of planned behaviour, Organizational Behaviour and Human Decision Processes, 50, 2, pp. 179-211, (1991); ANDERSON J.C., GERBING D.W., Structural equation modeling in practice: A review and recommended two-step approach, Psychological bulletin, 103, 3, pp. 411-423, (1988); BA S., Establishing online trust through a community responsibility system, Decision Support Systems, 31, 3, pp. 323-336, (2001); BELANGER F., HILLER J.S., SMITH W.J., Trustworthiness in electronic commerce: The role of privacy, security, and site attributes, The Journal of Strategic Information Systems, 11, 3-4, pp. 245-270, (2002); BHATTACHERJEE A., Individual trust in online firms: Scale development and initial test, Journal of Management Information Systems, 19, 1, pp. 211-241, (2002); BRYNJOLFSSON E., SMITH M.D., Frictionless commerce? A comparison of Internet and conventional retailers, Management Science, 46, 4, pp. 563-585, (2000); eCommerce Trust Study, (1999); 18th Statistical Survey Report, (2006); CORRITORE C.L., KRACHER B., WIEDENBECK S., On-line trust: Concepts, evolving themes, a model, International Journal of Human-Computer Studies, 58, 6, pp. 737-758, (2003); DAVIS F.D., Perceived usefulness, perceived ease of use, and user acceptance of information technology, MIS Quarterly, 13, 3, pp. 319-340, (1989); DAVIS F.D., BAGOZZI R.P., WARSHAW P.R., User acceptance of computer technology: A comparison of two theoretical models, Management Science, 35, 8, pp. 982-1003, (1989); FISHBEIN M., AJZEN I., Belief, attitude, intention and behaviour: An introduction to theory and research, (1975); GEFEN D., E-commerce: The role of familiarity and trust, Omega, 28, 6, pp. 725-737, (2000); GEFEN D., KARAHANNA E., STRAUB D.W., Inexperience and experience with online stores: The importance of TAM and trust, IEEE Transactions on Engineering Management, 50, 3, pp. 307-321, (2003); GEFEN D., KARAHANNA E., STRAUB D.W., Trust and TAM in online shopping: An integrated model, MIS Quarterly, 27, 1, pp. 51-90, (2003); GEFEN D., STRAUB D., The relative importance of perceived ease of use in IS adoption: A study of ecommerce adoption, Journal of the Association for Information Systems, 1, 8, pp. 1-28, (2000); GEFEN D., STRAUB D.W., BOUDREAU M.C., Structural equation modeling and regression: Guidelines for research practice, Communications of the Association for Information Systems, 4, 7, pp. 1-70, (2000); GRABNER-KRAUTER S., KALUSCHA E.A., Empirical research in on-line trust: A review and critical assessment, International Journal of Human-Computer Studies, 58, 6, pp. 783-812, (2003); HAMPTON-SOSA W., KOUFARIS M., The effect of Web site perceptions on initial trust in the owner company?, International Journal of Electronic Commerce, 10, 1, pp. 55-81, (2005); HOFFMAN D.L., NOVAK T.P., PERALTA M., Building consumer trust online, Communications of the ACM, 42, 4, pp. 80-85, (1999); HUFF L., KELLEY L., Is collectivism a liability? The impact of culture on organizational trust and customer orientation: A seven-nation study, Journal of Business Research, 58, 36, pp. 96-102, (2005); China Online Shopping Research Report, (2005); JARVENPAA S.L., TRACTINSKY N., VITALE M., Consumer trust in an Internet store, Information Technology and Management, 1, 1, pp. 45-71, (2000); JORESKOG K.G., SORBOM D., LISREL 8: User's Reference Guide, (1996); KIM K.K., PRABHAKAR B., Initia ltrust and the adoption of B2C e-commerce: The case of Internet banking, The DATABASE for Advances in Information Systems, 35, 2, pp. 50-64, (2004); KOUFARIS M., Applying the technology acceptance model and flow theory to online consumer behaviour, Information Systems Research, 13, 2, pp. 205-223, (2002); KOUFARIS M., HAMPTON-SOSA W., The development of initial trust in an online company by new customers, Information & Management, 41, 3, pp. 377-397, (2004); LEE M.K.O., TURBAN E., A trust model for consumer Internet shopping, International Journal of ElectronicCommerce, 6, 1, pp. 75-91, (2001); LIKERT R., A technique for the measurement of attitudes, Archives of Psychology, 140, pp. 5-53, (1932); LIU C., MARCHEWKA J.T., LU J., YU C.-S., Beyond concern - a privacy-trust-behavioural intention model of electronic commerce, Information & Management, 42, 2, pp. 289-304, (2005); LUO X., Trust production and privacy concerns on the Internet: A framework based on relationship marketing and social exchange theory, Industrial Marketing Management, 31, 2, pp. 111-118, (2002); McKNIGHT D.H., CHOUDHURY V., KACMAR C., Developing and validating trust measures for ecommerce: An integrative typology, Information Systems Research, 13, 3, pp. 334-359, (2002); McKNIGHT D.H., CUMMINGS L.L., CHERVANY N.L., Initial trust formation in new organizational relationships, Academy of Management Review, 23, 3, pp. 473-490, (1998); McKNIGHT H.D., CHOUDHURY V., KACMAR C., The impact of initial consumer trust on intentions to transact with a web site: A trust building model, The Journal of Strategic Information Systems, 11, 3-4, pp. 297-323, (2002); NUNNALLY J.C., Psychometric theory, (1978); PAVLOU P.A., Consumer acceptance of electronic commerce: Integrating trust and risk with the technology acceptance model, International Journal of Electronic Commerce, 7, 3, pp. 101-134, (2003); PHELPS J.E., SOUZA G.D., NOWAK G.J., Antecedents and consequences of consumer privacy concerns: An empirical investigation, Journal of Interactive Marketing, 15, 4, pp. 2-17, (2001); Electronic Signature Law of People's, (2005); ROUSSEAU D.M., SITKIN S.B., BURT R.S., CAMERER C., Not so different after all: A cross-discipline view of trust, Academy of Management Review, 23, 3, pp. 393-404, (1998); STEWART K.J., Trust transfer on the world wide Web, Organization Science, 14, 1, pp. 5-17, (2003); STEWART K.J., How hypertext links influence consumer perceptions to build and degrade trust online, Journal of Management Information Systems, 23, 1, pp. 183-210, (2006); STRAUB D., BOUDREAU M.-C., GEFEN D., Validation guidelines for IS positivist research, Communications of AIS, 13, pp. 380-427, (2004); WAKEFIELD R.J., STOCKS M.H., WILDER W.M., The role of Web site characteristics in initial trust formation, Journal of Computer Information Systems, 45, 1, pp. 94-103, (2004); WALCZUCH R., LUNDGREN H., Psychological antecedents of institution-based consumer trust in eretailing, Information & Management, 42, 1, pp. 159-177, (2004); YOON S.-J., The antecedents and consequences of trust in online-purchase decisions, Journal of Interactive Marketing, 16, 2, pp. 47-63, (2002)","Z. Tao; School of Management, Huazhong University of Science and Technology, Wuhan 430074, China; email: zhoubosi@yahoo.com.cn",{"$nulls":7},"1443458X",null,"JRPTF",null,"English","J. Res. Pract. Inf. Technol.","Article","Final",null,"Scopus","2-s2.0-34548781303"]
["Clements A.","Clements, Alison (53363252600)",5.33632526E10,"Signed, sealed, delivered",2010.0,"Drapers",null,"2010-04-17",null,40.0,41.0,1.0,0.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-77951777370&partnerID=40&md5=0962641b594f357ca182012f8cf92f14",null,null,"E-commerce which consists of the buying and selling of products or services over electronic systems such as the Internet and other computer networks has gradually gained momentum with the coming of big retailing brands. Fashion retailers are getting more sophisticated when it comes to fulfillment of orders, and their delivery fulfillment partners are working incredibly hard to improve home delivery service levels and meet shoppers' rising expectations. Fashion home delivery fulfillment is by far our biggest growth area, and there is huge investment going into perfecting delivery. GeoPost UK, which encompasses delivery firms including Interlink Express and Homecall, has just developed a new system that will narrow down delivery time to, potentially, a one-hour window. Asda is developing an e-Catalogue to maximize multi channel opportunities and is installing Argos-style order and pick-up areas in stores, perfect for giving clothing shoppers access to the full range and sizes not on display.",null,"buying; e-commerce; information processing; information technology; investment; retailing; sales",{"$nulls":15},1.4791617E7,null,null,null,"English","Drapers","Article","Final",null,"Scopus","2-s2.0-77951777370"]
["Weber R.H.","Weber, RoIf H. (55479804200)",5.54798042E10,"Digital trade in wto-law - Taking stock and looking ahead",2010.0,"Asian Journal of WTO and International Health Law and Policy",5.0,1.0,null,1.0,24.0,23.0,25.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-84869032350&partnerID=40&md5=9920facbd48a497c7ee15b5be1a0e04a","University of Zurich, University of Hong Kong, Hong Kong","Weber R.H., University of Zurich, University of Hong Kong, Hong Kong","Figures in digital trade show a substantial growth over the last years, but WTO law does not provide for an adequate legal framework encompassing digital trade rules. The Information Technology Agreement might not encompass all new goods since the relevant Appendices have not been amended for 14 years and the digital services are only partially covered in the Specific GATS Commitments of WTO Members due to the fact that the so-called positive list approach requires active national commitments with respect to newly developed services. The most recent court practice (US-Gambling, China-AVHE), however, contains some promising signs of accepting e-commerce as service covered by the GATS. Legal scholars are now invited to formulate new digital trade rules facilitating the cross-border delivery of electronic goods and services as well as to develop concepts to overcome anticipated digital trade barriers (such as lack of access to technology, of interconnectivity and compatibility). Finally, the present digital divide must be overcome and turned into a digital opportunity for all.","E-Commerce; Future digital trade rules; GATT v. GATS; Information technology agreement; Preferential trade agreements",{"$nulls":7},"Geradin D., Luff D., The WTO and Global Convergence in Telecommunications and Audio-Visual Services, (2004); Kariyawasam R., International Economic Law and the Digital Divide - A New Silk Road, (2007); Panizzon M., Et al., Gats and the Regulation of International Trade in Services, (2008); Trebilcock Michael J., Howse R.L., The Regulation of International Trade, (2005); Weber Rolf H., Regulatory Models for the Online World, (2002); Weber Rolf H., Shaping Internet Governance: Regulatory Challenges, (2009); Weber Rolf H., Menoud V., The Information Society and the Digital Divide - Legal Strategies to Finance Global Access, (2008); Wunsch-Vincent S., The WTO, the Internet and Trade in Digital Products: EC-US Perspectives, (2006); Chaturvedi S., Mohanty S.K., The WTO and trade in electronically delivered software emerging challenges and policy options - An indian perspective, Journal of World Trade, 42, 5, (2008); Fink C., Molinuevo M., East asian preferential trade agreements in services: Liberalization content and WTO rules, World Trade Review, 7, 4, (2008); Forbes R., Sakellariou C., The WTO to settle dispute over EU tariffs for IT products - The ITA case, International Trade Law and Regulation, 15, 1, (2009); Islam R., Alam S., Preferential trade agreements and the scope of GATT article XXIV, GA TS article V and the enabling clause: An appraisal of GATT/WTO jurisprudence, Netherland International Law Review, 56, 1, (2009); Mattoo A., Wunsch-Vincent S., Pre-empting protectionism in services: The GATS and outsourcing, Journal of International Economic Law, 7, 4, (2004); Peng S.-Y., Trade in telecommunications services: Doha and beyond, Journal of World Trade, 41, 2, (2007); Peng S.-Y., Liberalization of trade in television services: The negotiation dilemma and challenges for the future, Journal of World Trade, 43, 4, (2009); Roy M., Et al., Services liberalization in the new generation of preferential trade agreements (PTAs): How much further than GATS?, World Trade Review, 6, 2, (2007); Weber R.H., Information technology markets - Asia's opportunity to revitalise the WTO, Hong Kong Law Journal, 37, (2007); Wilkinson R., Scott J., Developing country participation in the GATT: A reassessment, World Trade Review, 7, (2008); Wusch-Vincent S., The digital trade agenda of the U.S.: Parallel tracks of bilateral, regional and multilateral liberalization, Aussenwirtschaft, 58, 1, (2003); Wunsch-Vincent S., The internet, cross border trade in services, and the GATS: Lessons from US-gambling, World Trade Review, 5, 3, (2006); European Communities - Measures Affecting Asbestos and Asbestos-Containing Products, (2001); China - Measures Affecting Trading Rights and Distribution Services for Certain Publications and Audiovisual Entertainment Products, (2009); United States - Measures Affecting the CrossBorder Supply of Gambling and Betting Services, (2005); Compilation of the Submissions by the Secretariat: Revision: The Non-Tariff Measures Work Programme, (2003); Background Note by the Secretariat: Computer and Related Services, (1998); Computer and Related Services: Communication from the Separate Customs Territory of Taiwan, Penghu, Kinmen and Mats, (2003); Coverage of CPC 84 - Computer and Related Services: Communication from the European Communities and Their Member States, (2002); Interim Report to the General Council: Work Programme on E-Commerce, (1999); Towards An Information Society Approach: Green Paper on the Convergence of the Telecommunications, Media and Information Technology Sectors, and the Implications for Regulation, (1997); Work Programme on Electronic Commerce, (1998); WTO Agreements and Electronic Commerce, (1998); Note by the Secretariat: Revision: Overview of Divergences of Classification of Attachment B Items, (1999); China - Measures Affecting Trading Rights and Distribution Services for Certain Publications and Audiovisual Entertainment Products, (2009); Mexico - Measures Affecting Telecommunications Services, (2004); United States - Measures Affecting the Cross Border Supply of Gambling and Betting Services, (2004); Note by the Secretariat: Services Sectoral Classification List, (1991); Information Economy Report 2009: Trends and Outlook in Turbulent Times, Geneva, (2009); E-commerce and Information Technologies: From the Uruguay Round Through the Doha Development Agenda: A Report for the UN ICT Task Force, (2005); Note by the Secretariat, Services Sectoral Classification List, (1991); Ministerial Declaration on Trade in Information Technology Products, (1996); The Geneva Ministerial Declaration on Global Electronic Commerce, (1998); Susan C.S., USTR Remarks on EU, ITA, WTO Case, (2008); A Discussion Paper by the Alliance for Global Business on Trade-Related Aspects of Electronic Commerce in Response to the WTO 'S E-Commerce Work Programme; Doing doha down, The Economist, (2009); Peng S.-Y., Taxing Innovation? - The Evolving Coverage of the Information Technology Agreement, (2009); Sauve P., The Trade Policy Implications of the New Economy; The noodle bowl, The Economist, (2009); (2003)",{"$nulls":8},1.8195164E7,null,null,null,"English","Asian J. WTO Int. Heal. Law Policy","Article","Final",null,"Scopus","2-s2.0-84869032350"]
["Moital M.; Vaughan R.; Edwards J.; Peres R.","Moital, Miguel (35088581100); Vaughan, Roger (7202019570); Edwards, Jonathan (55372927500); Peres, Rita (35240646100)","35088581100; 7202019570; 55372927500; 35240646100","Determinants of intention to purchase over the Internet",2009.0,"Anatolia",20.0,2.0,null,345.0,358.0,13.0,16.0,"10.1080/13032917.2009.10518913","https://www.scopus.com/inward/record.uri?eid=2-s2.0-72749114373&doi=10.1080%2f13032917.2009.10518913&partnerID=40&md5=6a0cbf792dc8cf4c234a334a2aabec69","School of Services Management, Bournemouth University, United Kingdom; Estoril Higher Institute for Hotel and Tourism Studies, Portugal","Moital M., School of Services Management, Bournemouth University, United Kingdom; Vaughan R., School of Services Management, Bournemouth University, United Kingdom; Edwards J., School of Services Management, Bournemouth University, United Kingdom; Peres R., Estoril Higher Institute for Hotel and Tourism Studies, Portugal","More than 10 years on since the launch of the Internet, there are clear differential levels of adoption of the Internet for purchasing leisure travel across countries. In some countries, such as Portugal, only a minority of travel purchasing is conducted over the Internet. This paper aims to contribute to a greater understanding of adoption of purchasing over the Internet by evaluating the determinants of intention to adopt the Internet for purchasing leisure travel. A number of variables are used to assess which factors influence intention, including the attributes of purchasing over the Internet (relative advantage and complexity), involvement, and the stage in the e-commerce adoption path. Kruskal-Wallis and logistic regression were employed and the results indicated that relative advantage, involvement and stage in the e-commerce adoption path were important predictors of the intention to purchase leisure travel over the Internet, while complexity was not.","Adoption; Attitudes; Ieisure travel; Internet; Logistic regression; Portugal","Portugal; electronic commerce; Internet; recreational activity; regression analysis; technology adoption",{"$nulls":6},"Anckar B., Walden P., Self-booking of High-and Low-complexity Travel Products: Exploratory Findings, Technology & Tourism, 4, pp. 151-165, (2002); Athiyaman A., Internet Users' Intention to Purchase Air Travel Online: An Empirical Investigation, Marketing Intelligence & Planning, 20, 4, pp. 234-242, (2002); Buhalis D., ETourism: Information Technologies Far Strategic Tourism Management, (2002); Card J., Chen C., Cole S.T., Online Travel Products Shopping: Differences between Shoppers and Non-shoppers, Journal of Travel Research, 42, pp. 133-139, (2003); Chang M., Cheung W., Lai V., Literature Derived Reference Models for the Adoption of Online Shopping, Information & Management, 42, pp. 543-559, (2005); Chen L., Gillenson M., Sherrell D., Enticing Online Consumers: An Extended Technology Acceptance Perspective, Information & Management, 39, pp. 705-719, (2002); Childers T., Carr C., Peck J., Carson S., Hedonic and Utilitarian Motivations for Online Retail Shopping Behaviour, Journal of Retailing, 77, pp. 511-535, (2001); Davis F., Perceived Usefulness, Perceived Ease of Use and User Acceptance of Information Technology, MIS Quarterly, pp. 319-339, (1989); Eason K., Information Technology and Organizational Change, (1988); Eastin M., Diffusion of e-Commerce: An Analysis of the Adoption of Four e-Commerce Activities, Telematics and Informatics, 19, pp. 251-267, (2002); Eastlick M., Lotz S., Profiling Potential Adopters and Non-Adopters of an Interactive Electronic Shopping Medium, Journal of Retail and Distribution Management, 27, 6, pp. 209-223, (1999); Efendioglu A., Yip V., Chinese Culture and e-Commerce: An Exploratory Study, Interacting with Computers, 16, pp. 45-62, (2004); Engel J., Blackwell R.D., Miniard P.W., Consumer Behaviour, (1995); Field A., Discovering Statistics Using SPSS for Windows, (2000); Fishbein M., Ajzen I., Belief, Attitude, Intention and Behaviour, (1975); Heung V., Internet Usage by International Travellers: Erasons and Barriers, International Journal of Contemporary Hospitality Management, 15, 7, pp. 370-378, (2003); Howard J., Sheth A., The Theory of Buyer Behaviour, (1969); Kappelman L., Measuring User Involvement: A Diffusion of Innovation Perspective, DATA BASE Advances, 26, 2-3, pp. 65-83, (1995); Kardes F., Consumer Behavior. Managerial Decision Making, (1999); Kim W.G., Ma X.M., Kim D.J., Determinants of Chinese Hotel Customers' e-Satisfaction and Purchase Intentions, Tourism Management, 27, pp. 980-900, (2006); Laaksonen P., Consumer Involvement: Concepts and Research, (1994); Morrison A., Jing S., O'Leary J.T., Cai L.A., Predicting Usage of the Internet for Travel Bookings: An Exploratory Study, Information Technology & Tourism, 4, pp. 15-30, (2001); Pavlou P., Consumer Acceptance of Electronic Commerce: Integrating Trust and Risk with the Technology Acceptance Model, International Journal of Electronic Commerce, 7, 3, pp. 101-134, (2003); Peterson R., Balasubramanian S., Bronnenberg B.J., Exploring the Implications of the Internet for Consumer Marketing, Journal of the Academy of Marketing Science, 25, 4, pp. 329-346, (1997); Rogers E., The Diffusion of Innovations, (1995); Rosen K., Howard A., E-retail: Gold Rush or Fool's Gold, California Management Review, 42, 3, pp. 72-100, (2000); Salam A., Rao H.R., Pegels C.C., Internet Involvement: Instrument Development, Measurement and Implications for Electronic Commerce, pp. 175-188, (2000); Shon Z., Et al., Airline e-Commerce: The Revolution in Ticketing Channels, Journal of Air Transport Management, 9, pp. 325-331, (2003); Siegel S., Castellan N.J., Nonparametric Statistics for the Behavioural Sciences, (1988); Indicadores Sociais, (2006); First Release: Internet Access, Households and Individuals, (2006); Strutton H., Lumpkin J.R., Bitell S., An Applied Investigation of Rogers and Shoemaker's Perceived Innovation Attribute Typology when Marketing to Elderly Consumers, Journal of Applied Business Research, 10, 1, pp. 118-132, (1994); Verhoef P., Langerak F., Possible Determinants of Consumer's Adoption of Electronic Grocery Shopping in the Netherlands, Journal of Retailing and Consumer Services, 8, pp. 275-285, (2001); Vijayasarathy L., Predicting Consumer Intentions to Use Online Shopping: The Case for an Augmented Technology Acceptance Model, Information & Management, 41:747-762, (2004); Weber K., Roehl W., Profiling People Searching for and Purchasing Travel Products on the World Wide Web, Journal of Travel Research, 37, pp. 291-298, (1999); Wong J., Law R., Analysing the Intention to Purchase on Hotel Websites: A Study of Travellers to Hong Kong, Tourism Management, 24, pp. 311-329, (2005); Worthy S., Hyllegard K., Damhorst M., Trautmann J., Bastow-Shoop H., Gregory S., Lakner H., Lyons N., Manikowske L., Rural Consumers' Attitudes Toward the Internet for Information Search and Product Purchase, Family and Consumer Decision Sciences Family, 33, 1, pp. 517-535, (2004); Zaichkowsky J., Measuring the Involvement Construct, Journal of Consumer Research, 12, pp. 341-352, (1985)","M. Moital; School of Services Management, Bournemouth University, United Kingdom; email: mmoital@bournemouth.ac.uk",null,"Anatolia",{"$nulls":5},1.3032917E7,null,null,null,"English","Anatolia","Article","Final",null,"Scopus","2-s2.0-72749114373"]
["Khasawneh A.; Al Azzam I.; Bsoul M.","Khasawneh, Ahmad (57219049746); Al Azzam, Iyad (35572601500); Bsoul, Mohammad (32367449500)","57219049746; 35572601500; 32367449500","A study on e-commerce security in Jordan",2009.0,"International Journal of Electronic Finance",3.0,2.0,null,166.0,176.0,10.0,9.0,"10.1504/IJEF.2009.026358","https://www.scopus.com/inward/record.uri?eid=2-s2.0-77956288241&doi=10.1504%2fIJEF.2009.026358&partnerID=40&md5=a103c8042b3b28c5cbd3dc61dfcd0616","Prince Al-Hussein Bin Abdullah Ii Faculty of Information Technology, Hashemite University, Zarqa, Jordan; Faculty of Information Technology, Yarmouk University, Jordan","Khasawneh A., Prince Al-Hussein Bin Abdullah Ii Faculty of Information Technology, Hashemite University, Zarqa, Jordan; Al Azzam I., Faculty of Information Technology, Yarmouk University, Jordan; Bsoul M., Prince Al-Hussein Bin Abdullah Ii Faculty of Information Technology, Hashemite University, Zarqa, Jordan","The internet and all other kinds of networks have changed our way of life in general and the way to do business in particular and, as a result, many companies nowadays are conducting and transferring their businesses online. However, some of them are not successful. Until now, the majority of companies and customers have not been certain that doing business online is secure and protects them from any illegal activities, since there is no physical interaction (face-to-face) between customers and companies and every business will be cautious about payment methods, the quality and quantity of products or services and the delivery system, among many others. This paper attempts to evaluate whether security issues are the major obstacles to the growth of e-commerce in Jordan. A survey conducted for the study reveals that security issues are major barriers to internet banking and e-commerce activities among consumers. © 2009 Inderscience Enterprises Ltd.","E-commerce; Electronic commerce; ICTs; Information and communications technologies; Internet banking; Jordan; Perception; Privacy; Security; Security tools; Survey",{"$nulls":7},"Aldridge A., White M., Forch K., Security considerations of doing business via the internet: Cautions to be considered, Internet Research: Electronic: Networking Applications and Policy, 7, 1, pp. 9-15, (1997); Attaran M., Vanlaar L., Privacy and security on the internet: How to secure your personal information and company data, Information Management and Computer Security, 7, 5, pp. 241-246, (1999); Calder B.J., Phillips L.W., Tybout A.M., Designing research for application, Journal of Consumer Research, 8, pp. 197-207, (1981); Chellappa R., Pavlou P., Perceived information security, financial liability and customer trust in electronic commerce transactions, Logistics Information Management, 15, 4-6, pp. 358-368, (2002); Cranitch G., Nguyen D., Nguyen A., Australian banks' approaches to privacy in an online world, Int. J. Electronic Finance, 1, 4, pp. 389-405, (2007); Desai M., Richards T., Embed T., System insecurity - Firewalls, Information Management & Computer Security, 10, 3, pp. 135-139, (2002); Ein-Dor P., Goodman S., Wolcott P., The Global Diffusion of the Internet Project: The Hashemite Kingdom of Jordan, (1999); Gao P., Owolabi O., Consumer adoption of internet banking in Nigeria, Int. J. Electronic Finance, 2, 3, pp. 284-299, (2008); Gritzalls S., Gritzlis D., A digital seal solution for deploying trust on commercial transaction, Information Management and Computer Security, 9, 2, pp. 71-79, (2001); Hamann E., Et al., Securing e-business applications using smart cards, Ibm Systems Journal, 40, 3, pp. 635-648, (2001); Hung Y., Lu Y., The inhibitory factors of implementing internet banks, Int. J. Electronic Finance, 2, 3, pp. 419-432, (2008); Hutchinson D., Warren M., Security for internet banking: A framework, Logistics Information Management, 16, 1, pp. 64-73, (2003); Keen A., Electronic Commerce Relationships: Trust by Design, (2000); Ki J., Et al., Taxonomy of online game security, The Electronic Library, 22, 1, pp. 65-73, (2004); Kippenberger T., E-security, The Antidote the Essential E-business Enabler, 5, 1, (2000); Kumar S., Deploying Novell's border manager internet security firewall: A case study, Campus-Wide Information System, 16, 2, pp. 57-62, (1999); Kuo F., Tseng F., Liou D., Understanding the effects of relationships on the intention of a firm to adopt e-banking, Int. J. Electronic Finance, 1, 4, pp. 484-501, (2007); Martyn W., Guy D., Just how safe is safe?, Euronet, 1, 13, pp. 18-22, (2001); Momut R., Crawley L., Geier P., Dsl Security Whitepaper, (2000); Ratnasingham P., The importance of trust in electronic commerce, Internet Research: Electronic Networking Applications and Policy, 8, 4, pp. 313-321, (1998); Ratnasingham P., Trust in web-based electronic commerce security, Information Management & Computer Security, 6, 4, pp. 162-166, (1998); Shih K., Is e-banking a competitive weapon? A causal analysis, Int. J. Electronic Finance, 2, 2, pp. 180-196, (2008); Smedinghoff T., Phishing the legal challenge for business, Banking & Financial Services Policy Report, 24, 4, pp. 1-5, (2005); Venter H., Oliver M., Eloff J., PIDS: A privacy intrusion detection system, Internet Research, 14, 5, pp. 360-365, (2004); Wilson S., Certificates and trust in electronic commerce, Information Management and Computer Security, 5, 5, pp. 175-181, (1997); Yan J., Chio H., Security issues in online games, The Electronic Library, 20, 2, pp. 125-133, (2002)","A. Khasawneh; Prince Al-Hussein Bin Abdullah Ii Faculty of Information Technology, Hashemite University, Zarqa, Jordan; email: akhasawneh@hu.edu.jo",null,"Inderscience Enterprises Ltd.",{"$nulls":5},1.7460069E7,null,null,null,"English","Int. J. Electron. Finance","Article","Final",null,"Scopus","2-s2.0-77956288241"]
["Ng J.M.J.","Ng, J.M.J. (28167694100)",2.81676941E10,"Barriers to e-commerce policy in logistics: An exploratory study of the Pearl River Delta, China",2009.0,"International Journal of Logistics Research and Applications",12.0,3.0,null,195.0,212.0,17.0,7.0,"10.1080/13675560802200113","https://www.scopus.com/inward/record.uri?eid=2-s2.0-67650869817&doi=10.1080%2f13675560802200113&partnerID=40&md5=2cb0321825d49e339c33e3fd3d6688c6","Department of Logistics, The Hong Kong Polytechnic University, Kowloon, Hong Kong","Ng J.M.J., Department of Logistics, The Hong Kong Polytechnic University, Kowloon, Hong Kong","With the help of the information and communication technology and the continual ingress of foreign direct investment, the use of the internet in the Pearl River Delta (PRD) has developed rapidly. While physical infrastructure is a key factor for successful world trade, government policy relating to e-commerce is also a critical element to success. This study, based on the feedback of questionnaires and interviews with practitioners in the logistics industry in the PRD, has collected empirical evidence and confirmed causes of the barriers related to e-commerce policy in logistics operations in the PRD. These included availability and interpretation of rules and regulations, interface between the Chinese law and international law, execution of law and policy, and electronic payments in e-commerce in the PRD. The impact of the observed barriers to e-commerce policy may result in reduced competitiveness for the logistics operations of multinational enterprises in China.","Barriers; China; E-commerce policy; Logistics; Pearl River Delta",{"$nulls":5},"Hong Kong Polytechnic University, PolyU, (A634)","This study was supported in part by The Hong Kong Polytechnic University under a research grant (project code: A634) from the Area of Strategic Development in China Business Services (Logistics and Maritime Studies).","Anil S., Electronic commerce in Asia: The legal, regulatory and policy issues, International Journal of Law and Information Technology, 9, 2, pp. 93-114, (2001); Arambulo R.T., China centre of rapid growth, South China Morning Post, (2001); Arbor A., E-commerce Customer Satisfaction Outpaces Most Other Industries, (2004); An Overview of China's Internet Market and Its Regulation, (2000); Blumental D., Reform' or 'opening'? Reform of China's state-owned enterprises and WTO accession - The dilemma of applying GATT to marketizing economies, UCLA Pacific Basin Law Journal, 16, 198, (1998); Chan F., Logistics management and its legal environment in China, Hong Kong Law Journal, 31, 3, pp. 498-528, (2001); Chan F., The dynamic legal landscape for logistics management in China, Asia Business Law Review, 7, 36, pp. 61-67, (2002); Cheung R., Law expert welcomes era of reform, South China Morning Post, (2001); The 9th Survey Report on the Development of China's Internet, (2002); 13th Statistical Survey on the Internet Development in China, (2004); 16th Statistical Survey Report on the Internet Development in China, (2005); Christopher M.G., Logistics and Supply Chain Management: Strategies for Reducing Costs and Improving Services, (1998); Clarke D., What's law got to do with it? 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Liu J., Open Society Spells Liberal Regime: The Political Consequences of WTO, PNTR, and the Internet in China, (2004); Martinsons M.G., Electronic commerce in China: Emerging success stories, Information and Management, 39, 7, pp. 571-579, (2002); Michaelides Z., Ho J., Boughton N., Kehoe D., The development and evaluation of internet-based supply of non-production (MRO) items, International Journal of Logistics: Research and Applications, 6, 4, pp. 319-332, (2003); Min H., Galle W.P., Electronic commerce-based purchasing: A survey on the perceptual differences between large and small organisations, International Journal of Logistics: Research and Applications, 4, 1, pp. 79-95, (2001); Ng J., Barriers to e-commerce logistics in China (legal aspects), Journal of the UNEA Asia Centre, (2004); Ng J., Li K.X., Implication of ICT for knowledge management in globalization, Information Management and Computer Security, 11, 4, pp. 168-174, (2003); Olsson A., Karlsson S., The integration of customer needs in the establishment of an e-business system for internal service, International Journal of Logistics: Research and Applications, 6, 4, pp. 305-317, (2003); Pace N., China Surpasses U.S, (2006); Peng M.W., Lu Y., Shenkar O., Wang D.Y.L., Treasures in the China house: A review of management and organizational research in greater China, Journal Business Research, 52, 2, pp. 95-110, (2001); China's Actual FDI in 2005 Reaches 72.4 Billion U.S. Dollars, (2006); Foreign-funded Enterprises Gain 200 Bln USD in Profits in China, (2006); Pollitt D., Filling the logistics gaps in China in logistics management at the threshold of the new millennium, International Journal of Physical Distribution and Logistics Management, 28, 3, pp. 167-226, (1998); PRC Contract law, Articles 10 and 11, Contract Law in China, pp. 469-519, (2002); Ratnasingham P., Kumar K., Trading partner trust in electronic commerce participation, Proceedings of the Twenty First International Conference on Information Systems Brisbane, pp. 544-552, (2000); E-commerce brings positive prospects to China's import-export business, Retail Asia, (2005); Riddalls C.E., Icasati-Johanson B., Axtell C.M., Bennett S., Clegg C., Quantifying the effects of trust in supply chains during promotional periods, International Journal of Logistics: Research and Applications, 5, 3, pp. 257-274, (2002); 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Dongguan Customs Implement EDI, (2000); Shenzhen Customs to Fully Implement Automated Cargo Inspection in 2002, (2002); Logistics Battle Looming, (2002); The Cash Flow Problem, (2004); Prospects for FDI Flows and Transnational Corporation Strategies and Promotion Policies: 2004-2007 Global Investment Prospects Assessment (GIPA) Research Note 1: Results of a Survey of Location Experts, (2004); Prospects for FDI Flows and TNC Strategies, 2004-2007 World's Largest Transnational Companies Opt for Expansionary Strategies, (2004); 2004 Report to Congress on China's WTO Compliance, (2004); Van Der Vorst J.G.A.J., Van Dongen S., Nouguier S., Hilhorst R., E-business initiatives in food supply chains: Definition and typology of electronic business models, International Journal of Logistics: Research and Applications, 5, 2, pp. 119-138, (2002); Wang G., The legal system of China, Chinese Law, pp. 6-8, (1999); Wigand R.T., Electronic commerce: Definition, theory and context, Theory and Practice of Electronic Commerce, 13, 1, pp. 1-16, (1997); 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J. Logist. Res. Applic.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-67650869817"]
["Ehmke J.F.; Steinert A.; Mattfeld D.C.","Ehmke, Jan Fabian (37017183900); Steinert, André (55028844100); Mattfeld, Dirk Christian (35607509500)","37017183900; 55028844100; 35607509500","Advanced routing for city logistics service providers based on time-dependent travel times",2012.0,"Journal of Computational Science",3.0,4.0,null,193.0,205.0,12.0,71.0,"10.1016/j.jocs.2012.01.006","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84861952220&doi=10.1016%2fj.jocs.2012.01.006&partnerID=40&md5=38f3875bb63cb3e3fdf5f67ae4220390","University of Braunschweig, Carl-Friedrich Gauss Department, Business Information Systems, Decision Support Group, 38106 Braunschweig, Germany","Ehmke J.F., University of Braunschweig, Carl-Friedrich Gauss Department, Business Information Systems, Decision Support Group, 38106 Braunschweig, Germany; Steinert A., University of Braunschweig, Carl-Friedrich Gauss Department, Business Information Systems, Decision Support Group, 38106 Braunschweig, Germany; Mattfeld D.C., University of Braunschweig, Carl-Friedrich Gauss Department, Business Information Systems, Decision Support Group, 38106 Braunschweig, Germany","Increasing traffic demand, recurring congestion and sophisticated e-commerce business models lead to enormous challenges for routing in city logistics. We introduce a planning system for city logistics service providers, which faces those challenges by more realistic vehicle routing considering time-dependent travel times. Time-dependent travel times arise from telematics-based traffic data collection city-wide. Well-known heuristics for the Traveling Salesman Problem and for the Vehicle Routing Problem are adapted to time-dependent planning data. Computational experiments allow for insights into the efficiency of individual heuristics, their adaptability to time-dependent planning data sets, and the quality and structure of resulting delivery tours. © 2012 Elsevier B.V.","Floating Car Data; Heuristics; Time-dependent travel times; Time-dependent Traveling Salesman Problem; Vehicle routing","Traveling salesman problem; Vehicle routing; Wireless telecommunication systems; City logistics; Computational experiment; E-commerce business; Floating car data; Heuristics; Planning data; Planning systems; Time-dependent; Time-dependent traveling salesman; Traffic data collection; Traffic demands; Vehicle Routing Problems; Travel time",{"$nulls":6},"Agatz N., Campbell A.M., Fleischmann M., Savelsbergh M., Time slot management in attended home delivery, Transportation Science, 45, pp. 435-449, (2011); Barcelo J., Kuwahara M., Traffic Data Collection and its Standardization, International Series in Operations Research & Management Science, (2010); Bierwirth C., Mattfeld D.C., Kopfer H., On permutation representations for scheduling problems, Proceedings of the 4th International Conference on Parallel Problem Solving from Nature, pp. 310-318, (1995); Bishop R., Intelligent Vehicle Technology and Trends, (2005); Braysy O., Gendreau M., Vehicle Routing Problem with Time Windows. 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Proceedings of 10th International Symposium SSTD 2007, pp. 460-477, (2007); George B., Shekhar S., Modeling spatio-temporal network computations: a summary of results, Proceedings of the 2nd International Conference on GeoSpatial Semantics 2007, (2007); Gevaers R., van de Voorde E., Vanelslander T., Characteristics and typology of last-mile logistics from an innovation perspective in an urban context, Proceedings of WCTR 2010, (2010); Glover F., Laguna M., Tabu Search, (1998); Golden B.L., Stewart R.W., Empirical analysis of heuristics, The Traveling Salesman Problem. A Guided Tour of Combinatorial Optimization, pp. 207-249, (1985); Han J., Kamber M., Data Mining. Concepts and Techniques, (2006); Ichoua S., Gendreau M., Potvin J.Y., Vehicle dispatching with time-dependent travel times, European Journal of Operational Research, 144, pp. 379-396, (2003); Kaufman D.E., Smith R.L., Fastest paths in time-dependent networks for intelligent vehicle-highway systems application, IVHS, 1, pp. 1-11, (1993); Kohler E., Langtau K., Skutella M., Time-expanded graphs for flow-dependent transit time, Proceedings of 10th Annual European Symposium on Algorithms - ESA, pp. 599-611, (2002); Lu Q., George B., Shekhar S., Capacity Constrained Routing Algorithms for Evacuation Planning: A Summary of Results, SSTD, pp. 22-24, (2005); Maden W., Eglese R., Black D., Vehicle routing and scheduling with time-varying data: a case study, Journal of the Operational Research Society, 61, pp. 515-522, (2010); Malandraki C., Dial R.B., A restricted dynamic programming heuristic algorithm for the time dependent Traveling Salesman Problem, European Journal of Operational Research, 90, pp. 45-55, (1996); Orda A., Rom R., Minimum weight paths in time-dependent networks, Networks, 21, pp. 295-319, (1991); Pape J., (2006); Potvin J.Y., Rousseau J.M., A parallel route building algorithm for the vehicle routing and scheduling problem with time windows, European Journal of Operational Research, 66, pp. 331-340, (1993); Schneider J., The Time-dependent Traveling Salesman Problem, Physica A: Statistical Mechanics and its Applications, 314, pp. 151-155, (2002); Solomon M., Algorithms for vehicle routing and scheduling problem with time windows constraints, Operations Research, 35, pp. 254-265, (1987); Taniguchi E., Thompson R.G., Yamada T., Modelling city logistics, City Logistics. I. Proceeding, Institute of City Logistics, (1999); Taniguchi E., Thompson R.G., Yamada T., van Duin R., City Logistics. Network Modelling and Intelligent Transport Systems, (2008); van Woensel T., Kerbache L., Peremans H., Vandaele N., Vehicle routing with dynamic travel times: a queueing approach, European Journal of Operational Research, 186, pp. 990-1007, (2008)","J.F. Ehmke; University of Braunschweig, Carl-Friedrich Gauss Department, Business Information Systems, Decision Support Group, 38106 Braunschweig, Germany; email: j-f.ehmke@tu-bs.de",{"$nulls":7},1.8777503E7,null,null,null,"English","J. Comput. Sci.","Article","Final",null,"Scopus","2-s2.0-84861952220"]
["Bucki R.; Suchánek P.","Bucki, Robert (53979314600); Suchánek, Petr (57196543233)","53979314600; 57196543233","The method of logistic optimization in E-commerce",2012.0,"Journal of Universal Computer Science",18.0,10.0,null,1238.0,1258.0,20.0,19.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-84864321312&partnerID=40&md5=340e0aec5a3237d62f3aed543b9ccc5b","The College of Informatics and Management in Bielsko-Biała, Bielsko-Biała, Poland; Silesian University in Opava, School of Business Administration in Karviná, Karviná, Czech Republic","Bucki R., The College of Informatics and Management in Bielsko-Biała, Bielsko-Biała, Poland; Suchánek P., Silesian University in Opava, School of Business Administration in Karviná, Karviná, Czech Republic","Rapidly changing business environment requires new approaches and methods for supporting management systems in all types of companies. Modern companies doing business use e-commerce systems by default. One of the key areas of e-commerce systems is logistics and the supply chain. The optimal way to ensure the success of logistics and supply chains is to use the methods of modeling and simulation based on appropriate models and especially its mathematical representation. In this paper, authors highlight the customer-oriented model of the e-commerce system and deal with logistic optimization and simulations. As an example, a sample logistic structure which requires the adequate control approach is presented. This is realized by means of heuristic algorithms which are responsible for meeting the set criterion. Moreover, the criteria to either maximize the production output or minimize the lost flow capacity of the logistic system or minimize the tool replacement criterion are introduced. Equations of state are given in order to represent the flow of material through the logistic system. © J.UCS.","E-commerce system; Logistic process; Logistics; Production maximization criterion; Simulation",{"$nulls":7},"Arsham H., Systems Simulation: The Shortest Route to Applications, (1996); Balan A., The Knowledge Management - Necessity for the Modernization of the Organizations, Journal of Applied Economic Science, 4, 10, (2009); Bora C., Advantages and Disadvantages of Electronic Commerce (e-commerce, From Advantages and Disadvantages of Electronic Commerce (e-commerce, (2009); Bredford M., Modern ERP: Select, Implement & Use Today's Advanced Business Systems, (2009); Bucki R., Managing Flexibility of the Production System with Interoperation Store. Mezinárodní vědecký seminář: Nové trendy v ekonometrii a operačním výzkumu, Zbornik, (2010); Bucki R., Antonyova A., Suchanek P., Economic Control of the Distribution System By Means of Heuristic Approach, 12, (2009); Burd S.D., Systems Architecture, (2009); Cantrell B., Logistics Vs SCM, (2004); Chang Y., Makatsoris H., Supply Chain Modeling Using Simulation, International Journal of Simulation Modelling, 1, (2003); Chopra S., Meindl P., Supply Chain Management, (2009); Cordeau J.F., Laporte G., Pasin F., An iterated local search heuristic for the logistics network design problem with single assignment, Elsevier, International Journal of Production Economics, 113, (2008); Frazelle E., How to Design a Logistics Network In 10 Steps, (2006); Fu M.C., Hu J., Sensitivity analysis for Monte Carlo simulation of option pricing, Probability In the Engineering and Information Sciences, 9, 3, pp. 417-446, (1995); Groothedde B., Logistics Network Design and Collaboration: Design, Theory, and Practice, (2011); Kim P., Ding Z., Optimal engineering system design guided by data-mining methods, Technometrics, 47, 3, pp. 336-348, (2005); Kleijnen J.P.C., Supply Chain Simulation: A Survey, Center For Economic Research, (2003); Langevin A., Riopel D., Logistics Systems: Design and Optimization, (2010); (1996); Nedjah N., Mourelle L.M., Evolutionary Optimization for Intelligent Systems Design, J.UCS Journal of Universal Computer Science, 14, 15, (2008); Pradeep I.K., Et al., CRM System Using CM-AKD Approach of D3M, International Journal of Engineering Science and Technology, 2, 3, pp. 237-242, (2010); Ratliff H.D., The 10 Rules For Logistics Optimization, (2003); Schropfer A., Kerschbaum F., Schutz C., Pibernik R., Optimizations for Risk- Aware Secure Supply Chain Master Planning, J.UCS Journal of Universal Computer Science, 15, 15, (2009); Semini M., Fauske H., Applications of Discrete-event Simulation to Support Manufacture Logistics Decision-making: A Survey; Shaked M., Shanthikumar J.G., Stochastic Orders, (2007); Shanthikumar J.G., Yao D.D., Zijm W., Henk M., Stochastic Modeling And Optimization Of Manufacturing Systems And Supply Chains, International Series In Operations Research & Management Science, 63, (2003); Silva C.A., Sousa J.M.C., Runkler T., Palm R., Soft computing optimization methods applied to logistic processes, International Journal of Approximate Reasoning Archive, 40, 3, (2005); Customer-oriented Systems, (2011); Suchanek P., Business Intelligence as a Support of E-commerce Systems in Connection with Decision Making and Cross-Border Online Shopping, Journal of Applied Economic Science, 5, 11, (2010); Suchanek P., Dolak R., Miskus M., Sperka R., Intelligence Decision Support Systems In E-commerce, (2011); White J.J., Principles of Payment Systems, (2008)","R. Bucki; The College of Informatics and Management in Bielsko-Biała, Bielsko-Biała, Poland; email: rbucki@wsi.edu.pl",{"$nulls":7},9486968.0,null,null,null,"English","J. Univers. Comput. Sci.","Article","Final",null,"Scopus","2-s2.0-84864321312"]
["Saha P.; Nath A.K.; Salehi-Sangari E.","Saha, Parmita (23390670100); Nath, Atanu K. (23390209800); Salehi-Sangari, Esmail (12783679300)","23390670100; 23390209800; 12783679300","Evaluation of government e-tax websites: An information quality and system quality approach",2012.0,"Transforming Government: People, Process and Policy",6.0,3.0,null,300.0,321.0,21.0,44.0,"10.1108/17506161211251281","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84864133727&doi=10.1108%2f17506161211251281&partnerID=40&md5=42f744dcff04a3d4c59b8bf584d5724f","Department of Engineering and Science, Sogn og Fjordane University College, Sogndal, Norway; Faculty of Social Sciences, Sogn og Fjordane University College, Sogndal, Norway; Division of Industrial Marketing, KTH, Royal Institute of Technology, Stockholm, Sweden","Saha P., Department of Engineering and Science, Sogn og Fjordane University College, Sogndal, Norway; Nath A.K., Faculty of Social Sciences, Sogn og Fjordane University College, Sogndal, Norway; Salehi-Sangari E., Division of Industrial Marketing, KTH, Royal Institute of Technology, Stockholm, Sweden","Purpose - Despite the growth in adoption of technology by governments, the assessment of quality in electronically delivered public services has been relatively lacking. Past researches on information systems have identified information and service quality, system use, playfulness, and system design quality as critical factors of successful service delivery in e-commerce. The purpose of this paper is to empirically test the applicability of system and information quality criteria in evaluating government e-services websites. The main research problem identified in this study was \"what are the system and information quality characteristics of government service delivery websites?\" Design/methodology/approach - Based on a survey of 97 Municipalities from all the 21 regions of Sweden, the authors examine the presence of system quality features, specifically functionality, navigation, and accessibility; and measures of information quality in government websites. A systematic random sampling was chosen as the suitable approach; 290 municipalities are organized in 21 counties and we have chosen every 3rd number of municipalities from the list. An online survey was conducted, with 408 valid responses taken. A confirmatory factor analysis was conducted for system and information quality. Findings - Results indicate that accessibility and the navigation facility are important in determining a citizen's perceived system quality. Information preciseness, timeliness, and sufficiency were found to be key measures of information quality in government e-services. Furthermore, an important finding from this research is that theories from information systems (IS), e-commerce, and marketing were found to be applicable in assessing government e-tax services within the broader area of government-to-citizen (G2C) service delivery systems. In addition, a quantitative study was conducted among citizens to determine system and information quality characteristics. Originality/value - The results presented in this paper can help the authorities to identify key quality criteria for e-tax services that are valued by citizens and consequently improve service levels. Taking the context into consideration, additional variables are incorporated from literature that spans several disciplines (IS, e-commerce, and marketing), and some re-specifications are made to identify system and information quality criteria in the context of an e-tax filing service, which was the main theoretical contribution of this study. © Emerald Group Publishing Limited.","e-governance; e-tax services; Government policy; Information management; Information quality; Public services; Sweden; System quality; Taxes; Web sites",{"$nulls":7},"Aladwania A.M., Palvia P.C., Developing and validating an instrument for measuring user-perceived web quality, Information & Management, 39, pp. 467-476, (2002); Al-Sebie M., Irani Z., E-government: Defining boundaries and lifecycle maturity, Proceedings of 3rd European Conference on E-Government, Ireland, 3-4 July, pp. 19-29, (2003); Bailey J.E., Pearson S.W., Development of a tool for measuring and analyzing computer user satisfaction, Management Science, 29, 5, pp. 530-545, (1983); Barnes S.J., Vidgen R.T., Data triangulation and web quality metrics: A case study in e-government, Information & Management, 43, pp. 767-777, (2006); Baroudi J.J., Orlikowski W.J., A short-form measure of user information satisfaction: A psychometric evaluation and notes on use, Journal of Management Information Systems, 4, 4, pp. 44-59, (1988); Bavec C., On stimulus for citizens' use of e-government services, International Multiconference on Computer Science and Information Technology, Wisia, pp. 391-395, (2008); Cao M., Qingyu Z., Seydel J., B2C e-commerce web site quality: An empirical examination, Industrial Management & Data Systems, 105, 5, pp. 645-661, (2002); Cao M., Zhang Q., Seydel J., B2C e-commerce web site quality: An empirical examination, Industrial Management & Data Systems, 105, 5, pp. 645-661, (2005); Centeno C., Bavel R.V., Burgelman J.C., A prospective view of e-government in the European union, The Electronic Journal of E-Government, 3, 2, pp. 59-66, (2005); Chang I.-C., Li Y.-C., Hung W.-F., Hwang H.-G., An empirical study on the impact of quality antecedents on tax payers acceptance of internet tax-filing systems, Government Information Quarterly, 22, pp. 389-410, (2005); Chen C., Impact of quality antecedents on taxpayer satisfaction with online tax-filing systems - an empirical study, Information & Management, 47, pp. 308-315, (2010); Colclough G., The user challenge benchmarking the supply of online public services - 7th measurement, (2007); Colclough G., Tinholt D., Smarter, faster, better e-government - 8th benchmarking measurement, (2009); Connolly R., Bannister F., eTax filing and service quality: The case of the revenue online service, Proceedings of World Academy of Science, Engineering and Technology, April, 48, (2008); Csetenyi A., Electronic government: Perspective from e-commerce, pp. 294-298, (2000); Curtin G., Issues and challenges global e-government/e-participation models, measurement and methodology: A framework for moving forward, (2006); DeLone W.H., McLean E.R., Information system success: The quest for dependent variable, Information System Research, 3, 1, (1992); DeLone W.H., McLean E.R., The DeLone and McLean model of information system success: A ten-year update, Journal of Management Information System, 19, 4, pp. 9-30, (2003); DeLone W.H., McLean E.R., Measuring e-commerce success: Applying the DeLone and McLean information systems success model, International Journal of Electronic Commerce, 9, 1, pp. 31-47, (2004); Ebrahim Z., Irani Z., E-government adoption: Architecture and barriers, Business Process Management Journal, 11, 5, pp. 589-611, (2005); Freed L., The American customer satisfaction index: E-government satisfaction index, (2009); Hair J.F., Babin B., Money A.H., Samouel P., Essentials of Business Research Methods, (2007); Heeks R., Understanding E-Governance for Development, (2001); Hung S., Chang C., Yu T., Determinants of user acceptance of the e-government services: The case of online tax filing and payment system, Government Information Quarterly, 23, pp. 97-122, (2006); Iivari J., An empirical test of the DeLone-McLean model of information system success, The Data Base for Advances in Information Systems, 36, 2, (2005); Irani Z., Al-Sebie M., Elliman T., Transaction stage of e-government systems: Identification of its location and importance, Proceedings of the 39th Hawaii International Conference on System Sciences, (2006); Irani Z., Sharif A.M., Love P.E.D., Linking knowledge transformation to information systems evaluation, European Journal of Information Systems, 14, 4, pp. 1-16, (2005); Irani Z., Osman I.H., Balci A., Ozkan S., Medeni T.D., Research note toward a reference process model for citizen-oriented evaluation of e-government services, Transforming Government: People, Process and Policy, 2, 4, pp. 297-310, (2008); Kim S., Stoel L., Apparel retailers: Website quality dimensions and satisfaction, Journal of Retailing and Consumer Services, 11, pp. 109-117, (2004); Latif M.H.A., Masrek M.N., Accessibility evaluation on Malaysian e-government websites, Journal of E-Government Studies and Best Practices, 2040, (2010); Li E.Y., Perceived importance of information system success factors: A meta analysis of group differences, Information & Management, 32, 1, pp. 15-28, (1997); Liu C., Arnett K.P., Exploring the factors associated with web site success in the context of electronic commerce, Information & Management, 38, pp. 23-33, (2000); Lociacono E., Watson R.T., Goodhue D., WebQual Tm: A web site quality instrument, (2000); Lu Z., Lu J., Zhang C., Website development and evaluation in the Chinese tourism industry networks and communication studies, NETCOM, 16, 3-4, pp. 191-208, (2002); Luo D., Shi Y., Evaluation on e-government websites based on rough set and genetic neural network algorithm, Proceedings of the Third International Symposium on Computer Science and Computational Technology (ISCSCT '10) Jiaozuo, People's Republic of China, 14-15 August, pp. 124-128, (2010); McKinney V., Yoon K., Zahedi F.M., The measurement of web-customer satisfaction: An expectation and disconfirmation approach, Information System Research, 13, 3, pp. 296-315, (2002); Markaki O., Charilas D., Askounis D., Evaluating the quality attributes of e-government websites, E-Government Website Development: Future Trends and Strategic Models, pp. 65-86, (2010); Podsakoff P.M., MacKenzie S.B., Lee J.Y., Podsakoff N.P., Common method biases in behavioral research: A critical review of the literature and recommended remedies, Journal of Applied Psychology, 88, 5, pp. 879-903, (2003); Rai A., Lang S.S., Welker R.B., Assessing the validity of IS success models: An empirical test and theoretical analysis, Information Systems Research, 13, 1, pp. 50-69, (2002); Ray S., Rao V., Evaluating government service: A customers' perspective of e-government, Proceedings of the 4th European Conference on E-Government, Dublin, Ireland, 17-18 June, (2004); Roca C.J., Chiu C.-M., Martinez F.J., Understanding e-learning continuance intention: An extension of the technology acceptance model, International Journal of Human-Computer Studies, 64, pp. 683-696, (2006); Roldan J.L., Leal A., A validation test of an adaptation of the DeLone and McLean's model in the Spanish EIS field, Critical Reflections on Information Systems: A Systemic Approach, (2003); Seddon P.B., Kiew M.Y., A partial test and development of Delone and McLean's model of is success, Australian Journal of Information System (AJIS), 4, 2, (1996); Seifert J., Peterson R.E., The promise of all things E? Expectations and challenges of emergent electronic government, Perspectives on Global Development and Technology, 1, 2, pp. 193-212, (2002); Smith A.G., Applying evaluation criteria to New Zealand government websites, International Journal of Information Management, 21, pp. 87-114, (2001); Stockdale R., Borovicka M., Using quality dimensions in the evaluation of web sites, Proceedings of the International Conference in Information and Communication Technologies in Tourism, Lausanne, Switzerland, (2006); Wangpipatwong S., Chutimaskul W., Papasratorn B., Factors influencing the adoption of Thai egovernment websites: Information quality and system quality approach, Proceedings of the Fourth International Conference on EBusiness, Bangkok, 19-20 November, (2005); Wang L., Bretschneider S., Gant J., Evaluating web-based e government services with a citizen-centric approach, Proceedings of the 38th Hawaii International Conference on System Sciences - 2005, (2005); Wauters P., Colclough G., On-line availability of public services: How is Europe progressing?, (2006); Wilkin C., Hewett B., Quality in a respecification of Delone and McLean's IS success model, Managing IT Resources in Organizations in the Next Milennium, IRMA International Conference, Hershey, PA, (1999); Zviran M., Chanan Glezer C., Avni I., User satisfaction from commercial web sites: The effect of design and use, Information & Management, 43, 2, pp. 157-178, (2005); Collin N., Butler P., Marketing public sector services: Concept and characteristics, Journal of Marketing Management, 11, pp. 83-96, (1995); Sweden - e-service for citizens, Egovernment News, (2005); Hamilton B.A., (2005); Li E.Y., Perceived importance of information system success factors: A meta analysis of group differences, Information & Management, 32, pp. 15-28, (1997); (2007); (2009)","P. Saha; Department of Engineering and Science, Sogn og Fjordane University College, Sogndal, Norway; email: Parmita.saha@hisf.no",{"$nulls":7},1.7506166E7,null,null,null,"English","Trans. Gov. People Process Policy","Article","Final",null,"Scopus","2-s2.0-84864133727"]
["Eisenstein D.D.","Eisenstein, Donald D. (7005970183)",7.005970183E9,"Analysis and optimal design of discrete order picking technologies along a line",2008.0,"Naval Research Logistics",55.0,4.0,null,350.0,362.0,12.0,24.0,"10.1002/nav.20289","https://www.scopus.com/inward/record.uri?eid=2-s2.0-43949096233&doi=10.1002%2fnav.20289&partnerID=40&md5=79ac07f6feb8da97f10584aa6304c50b","Graduate School of Business, University of Chicago, Chicago, IL 60637, United States","Eisenstein D.D., Graduate School of Business, University of Chicago, Chicago, IL 60637, United States","Order picking accounts for most of the operating expense of a typical distribution center, and thus is often considered the most critical function of a supply chain. In discrete order picking a single worker walks to pick all the items necessary to fulfill a single customer order. Discrete order picking is common not only because of its simplicity and reliability, but also because of its ability to pick orders quickly upon receipt, and thus is commonly used by e-commerce operations. There are two primary ways to reduce the cost (walking distance required) of the order picking system. First is through the use of technology - conveyor systems and/or the ability to transmit order information to pickers via mobile units. Second is through the design - where best to locate depots (where workers receive pick lists and deposit completed orders) and how best to lay out the product. We build a stochastic model to compare three configurations of different technology requirements: single-depot, dual-depot, and no-depot. For each configuration we explore the optimal design. © 2008 Wiley Periodicals, Inc.","Optimal depot location; Optimal product layout; Order picking; Warehouse logistics","Distribution functions; Electronic commerce; Optimization; Stochastic models; Supply chains; Order picking systems; Typical distribution center; Finite difference method",{"$nulls":6},"Bartholdi J.J., Eisenstein D.D., Foley R.D., Performance of bucket brigades when work is stochastic, Oper Res, 49, pp. 710-719, (2001); de Koster R., Le-Duc T., Roodbergen K.J., Design and control of warehouse order picking: A literature review, Eur J Oper Res, 182, pp. 481-501, (2007); Caron F., Marchet G., Perego A., Routing policies and COI‐based storage policies in picker‐to‐part systems, Int J Prod Res, 36, pp. 713-732, (1998); Caron F., Marchet G., Perego A., Optimal layout in low‐level picker‐to‐part systems, Int J Prod Res, 38, pp. 101-117, (2000); Chew E.P., Tang L.C., Travel time analysis for general item location assignment in a rectangular warehouse, Eur J Oper Res, 112, pp. 582-597, (1999); Francis R.L., McGinnis L.F., White J.A., Facility layout and location: An analytical approach, (1992); Frazelle E.D., World‐class warehousing, (1996); Hall R.W., Distance approximations for routing manual pickers in a warehouse, IIE Trans, 25, pp. 76-87, (1993); Jarvis J.M., McDowell E.D., Optimal product layout in an order picking warehouse, IIE Trans, 23, pp. 93-102, (1991); Jewkes E., Lee C., Vickson R., Product location, allocation and server home base location for an order picking line with multiple servers, Comput Oper Res, 31, pp. 623-636, (2004); Le-Duc T., de Koster R.M.B.M., Travel distance estimation and storage zone optimization in a 2‐block class‐based storage strategy warehouse, Int J Prod Res, 43, pp. 3561-3581, (2005); Le-Duc T., de Koster R.M.B.M., Travel time estimation and order batching in a 2‐block warehouse, Eur J Oper Res, 176, pp. 374-388, (2007); Matson J.O., White J.A., Operational research and material handling, Eur J Oper Res, 11, pp. 309-318, (1982); Ratliff H.D., Rosenthal A.S., Order‐picking in a rectangular warehouse: A solvable case of the traveling salesman problem, Oper Res, 31, pp. 507-521, (1983); Roodbergen K.J., Vis I.F.A., A model for warehouse layout, IIE Trans, 38, pp. 799-811, (2006); Rosenwein M.B., A comparison of heuristics for the problem of batching orders for warehouse selection, Int J Prod Res, 34, pp. 657-664, (1996); Tompkins J.A., Smith J.D., The warehouse management handbook, (1998); van den Berg J.P., A literature survey on planning and control of warehousing systems, IIE Trans, 31, pp. 751-762, (1999); Vickson R.G., Lu X., Optimal product and server locations in one‐dimensional storage racks, Eur J Oper Res, 105, pp. 18-28, (1998)","D. D. Eisenstein; Graduate School of Business, University of Chicago, Chicago, IL 60637, United States; email: don.eisenstein@chicagogsb.edu",null,"John Wiley and Sons Inc",{"$nulls":5},"0894069X",null,"NRLOE",null,"English","Nav Res Logist","Article","Final",null,"Scopus","2-s2.0-43949096233"]
["Smith A.D.","Smith, Alan D. (7406757527)",7.406757527E9,"Automatic identification and voice-recognition technologies for quality improvement: Case studies of Pittsburgh-area service firms",2008.0,"International Journal of Services and Standards",4.0,3.0,null,284.0,302.0,18.0,3.0,"10.1504/IJSS.2008.019043","https://www.scopus.com/inward/record.uri?eid=2-s2.0-47049124534&doi=10.1504%2fIJSS.2008.019043&partnerID=40&md5=e032399dff5e6ced015982d734ca4008","Department of Management and Marketing, Robert Morris University, Pittsburgh, PA 15219-3099, United States","Smith A.D., Department of Management and Marketing, Robert Morris University, Pittsburgh, PA 15219-3099, United States","The strategies for profitability in e-commerce must be able to integrate the use of the internet and AIDC (automatic identification and data capture) technologies, especially barcoding, smart card, and voice-recognition systems in data sharing and new product development. In e-commerce, this integration essentially serves as a foundation for the management of data flows for strategic IT purposes; especially in tracking distribution and ensuring quality of manufacture and service delivery. A combination of personal interviews of middle to management, as well as comments from convenient samples of employees was used to gather perceptions of recent AIDC-based initiatives of four highly regarded firms in the Pittsburgh, PA area to examine the technology advancements and continuous quality improvement initiatives of these service-industry firms. © 2008, Inderscience Publishers.","Automatic identification; E-commerce applications; IT project management; Quality assurance; Service marketing; Services; Standards; Systems integration; Voice-recognition system",{"$nulls":7},"Blyth A., The language barrier, Third Sector, 311, (2003); Chin T., Speech recognition programs pin hopes on transcription, American Medical News, 43, 24, (2000); Furness A., Machine-readable data carriers - a brief introduction to automatic identification and data capture, Assembly Automation, 20, 1, (2000); Hamann E.-M., Henn H., Schack T., Seliger F., Securing e-business applications using smart cards, IBM Systems Journal, 40, 3, pp. 635-647, (2001); Heizer J., Render B., Principles of Operations Management, (2007); Lawson S., Voice-activated services gaining attention, Network World, 20, 32, (2003); Pelagagge M.P., Efficiency improvement programme, in a mniti-site production system: An overview, Industrial Management and Data Systems, 101, 4, pp. 181-185, (2001); Pelton D., By word of mouth: Speech-directed systems offer workable hands-free alternative to mobile computing applications, Canadian Packaging, 54, 12, (2001); Shulman R., Talking efficiency inthe warehouse, Supermarket Business, 56, 11, (2001); Small S., Talk your day away, Warehousing Management, 6, 4, (1999); Smith A.D., Technology advancements for service marketing and quallity improvement: Multi-firm case study, Services Marketing Quarterly, 27, 4, pp. 99-113, (2006); Smith A.D., Supply chain management using electronic reverse auction: A multi-firm case study, International Journal of Services and Standards, 2, 2, pp. 176-1889, (2006); Smith A.D., Exploring the efficiencies associated with the e-fashious industry, International Journal of business Information Systems, 1, 4, pp. 353-369, (2006); Smith A.D., Exploring security and comfort issues associated with online banking, International Journal of Electronic Finance, 1, 1, pp. 19-49, (2006); Smith A.D., Offodile O.F., Information management of automated data capture: An overview of technical developments, Information Management and Computer Security, 10, 3, pp. 109-118, (2002); Smith A.D., Offodile O.F., Exploring forcasting and project management characteristics of supply chain management, International Journal of Logistics and Supply Management, 3, 2, pp. 174-214, (2007); Speak and ye shall receive real-time information, Modern Materials Handling, 54, 2, (1999); Speech recognition reduced Sears' Costs by factor 10, Voice Technology and Services News, 17, 9, (1998); Wright C., Voice recognition is integral part of Telematics, Automotive New, 78, 6067, (2003)","A.D. Smith; Department of Management and Marketing, Robert Morris University, Pittsburgh, PA 15219-3099, United States; email: smitha@rmu.edu",null,"Inderscience Enterprises Ltd.",{"$nulls":5},1.7408849E7,null,null,null,"English","Int. J. Serv. Stand.","Article","Final",null,"Scopus","2-s2.0-47049124534"]
["Lan H.; Ding Y.; Hong J.; Huang H.; Lu B.","Lan, Hongbo (55671097600); Ding, Yucheng (7404136873); Hong, Jun (7404118243); Huang, Hailiang (56138721000); Lu, Bingheng (7401752665)","55671097600; 7404136873; 7404118243; 56138721000; 7401752665","Web-based quotation system for stereolithography parts",2008.0,"Computers in Industry",59.0,8.0,null,777.0,785.0,8.0,19.0,"10.1016/j.compind.2008.03.006","https://www.scopus.com/inward/record.uri?eid=2-s2.0-49949087441&doi=10.1016%2fj.compind.2008.03.006&partnerID=40&md5=b10fd3f97d642dcefa6177fe3ef1ebca","State Key Laboratory for Manufacturing System Engineering, Xi'an Jiaotong University, Xi'an, 710049, China; School of Mechanical Engineering, Shandong University, Jinan, 250061, China","Lan H., State Key Laboratory for Manufacturing System Engineering, Xi'an Jiaotong University, Xi'an, 710049, China, School of Mechanical Engineering, Shandong University, Jinan, 250061, China; Ding Y., State Key Laboratory for Manufacturing System Engineering, Xi'an Jiaotong University, Xi'an, 710049, China; Hong J., State Key Laboratory for Manufacturing System Engineering, Xi'an Jiaotong University, Xi'an, 710049, China; Huang H., State Key Laboratory for Manufacturing System Engineering, Xi'an Jiaotong University, Xi'an, 710049, China; Lu B., State Key Laboratory for Manufacturing System Engineering, Xi'an Jiaotong University, Xi'an, 710049, China","RP service bureaus or providers constantly face urgent requirements for price and delivery quotations on complicated RP parts. They are challenged to respond quickly and accurately with bids that are tailored to each customer's specifications. In order to satisfy the current quotation requirements of RP service bureaus and providers, this paper investigates and develops a web-based automated quotation system which can provide instant price quotations for stereolithography (SL) parts. Two quoting approaches which include the rough quotation based on weight and precise quotation based on build-time were proposed to determine the price quotation for SL parts. Furthermore, a Java-enabled solution together with web techniques was employed to develop the on-line price quotation system. Implementation of precise quotation method, as a typical module, was used to demonstrate the development of the system. The system offers a new choice for RP customers to allow them to quote instantly and compare multiple rapid prototyping processes. © 2008 Elsevier B.V. All rights reserved.","E-commerce; On-line quotation system; Rapid prototype; Stereolithography parts","Concurrent engineering; Customer satisfaction; Job analysis; Product development; Rapid prototyping; Sonoluminescence; Specifications; Stereolithography; E-commerce; Java-enabled solution; On-line quotation system; Prototyping; Rapid prototype; Stereolithography (SL); Stereolithography parts; Pinch effect",{"$nulls":4},"Natural Science Foundation of Shandong Province, (No.Y2007F49)","This project was partly supported by the National Science Foundation of Shandong Province (Grant No.Y2007F49). We would like to especially acknowledge these anonymous referees who give us many significant suggestions and point out some mistakes in our paper, which can result in largely improvement for the paper. ","Veeramani D., Joshi P., Methodologies for rapid and effective response to requests for quotation (RFQs), IIE Transactions, 29, 10, pp. 825-838, (1997); Ben-Arieh D., Li Q., Web-based cost estimation of machining rotational parts, Production Planning and Control, 14, 8, pp. 778-788, (2003); De Carvalho R.A., Costa G.H., A Web-based contract selection tool, WSEAS Transactions on Computers, 12, 4, pp. 1838-1845, (2005); Chan C.L., Chen C.L., Usage pattern of web-based system for mobile phone purchasing, International Journal of Services, Technology and Management, 4, 4-6, pp. 549-562, (2003); Huang G.Q., Lee S.W., Mak K.L., Synchronised web applications for product development in the 21st century, International Journal of Advanced Manufacturing Technology, 18, 8, pp. 605-613, (2001); Simpson T.W., Umapathy K., Nanda J., Halbe S., Hodge B., Development of a framework for web-based product platform customization, Journal of Computing and Information Science in Engineering, 3, 2, pp. 119-129, (2003); Buyukozkan G., Bavkasolu A., Dereli T., Integration of Internet and web-based tools in new product development process, Production Planning & Control, 18, 1, pp. 44-53, (2007); Roy R., Kelvesjo S., Forsberg S., Et al., Quantitative and qualitative cost estimating for engineering design, Journal of Engineering Design, 12, 2, pp. 147-162, (2001); Layer A., Brinke E.T., Van Houten F., Et al., Recent and future trends in cost estimation, International Journal of Computer Integrated Manufacturing, 15, 6, pp. 499-510, (2002); Duverlie P., Castelain J.M., Cost estimation during design step: parametric method versus case based reasoning method, International Journal of Advanced Manufacturing Technology, 15, 12, pp. 895-906, (1999); Chua C.K., Leong K.F., Lim C.S., Rapid Prototyping Principles and Applications, (2003); Alexander P., Allen S., Dutta D., Part orientation and build cost determination in layered manufacturing, Computer-Aided Design, 30, 5, pp. 343-356, (1998); Lan H.B., Networked service system of RP&M and its key techniques, PhD Dissertation, (2004); Lan H.B., Ding Y.C., Hong J., Et al., A web-based manufacturing service system for rapid product development, Computers in Industry, 54, 1, pp. 51-67, (2004); Lan H.B., Chin K.S., Hong J., Development of a teleservice system for RP service bureaus, Rapid Prototyping Journal, 11, 2, pp. 98-105, (2005)","H. Lan; State Key Laboratory for Manufacturing System Engineering, Xi'an Jiaotong University, Xi'an, 710049, China; email: hblan@sdu.edu.cn",{"$nulls":7},1663615.0,null,"CINUD",null,"English","Comput Ind","Article","Final",null,"Scopus","2-s2.0-49949087441"]
["Papagiannidis S.; Bourlakis M.; Li F.","Papagiannidis, Savvas (8848778400); Bourlakis, Michael (6506844873); Li, Feng (36071633100)","8848778400; 6506844873; 36071633100","E-fulfilling the e-supply chain of digital print",2008.0,"International Journal of Information Technology and Management",7.0,1.0,null,98.0,112.0,14.0,1.0,"10.1504/IJITM.2008.015891","https://www.scopus.com/inward/record.uri?eid=2-s2.0-37849003143&doi=10.1504%2fIJITM.2008.015891&partnerID=40&md5=8183e61d78220496ed2c661c4e59e808","University of Newcastle upon Tyne, NE1 7RU, Newcastle upon Tyne, United Kingdom; eBusiness Group, Business School, University of Newcastle upon Tyne","Papagiannidis S., University of Newcastle upon Tyne, NE1 7RU, Newcastle upon Tyne, United Kingdom, eBusiness Group, Business School, University of Newcastle upon Tyne; Bourlakis M., University of Newcastle upon Tyne, NE1 7RU, Newcastle upon Tyne, United Kingdom; Li F., University of Newcastle upon Tyne, NE1 7RU, Newcastle upon Tyne, United Kingdom","This paper employs a qualitative case study methodology aiming to shed light on the integration process between the supply chain and the information technology operations of a business network in the UK digital print sector. That integration process, combined with the simultaneous and parallel transformation of the supply chain management operations in order to distribute and print material online, via numerous partners and distributors, results in the emergence of a fourth party digital print logistics network. The unique characteristics of the network are related to the fast response to on-print customer demand and to the ability to print material in numerous locations; hence, it is gradually becoming a demand-chain digital print logistics network. It also illustrates a new business model and a new way of working, enabled by the internet and related technologies, that were not financially viable in the past. Copyright © 2008 Inderscience Enterprises Ltd.","4th party logistics network; Information Technology (IT); Supply Chain Management (SCM); UK","Digital Printing; E-commerce; Supply Chain Management; Digital printing; Information technology; Supply chain management; Logistics networks; Parallel transformation; Electronic commerce",{"$nulls":6},"Alexander A., Young D., Strategic outsourcing, Long Range Planning, 54, 1, pp. 116-119, (1996); Bourlakis M., Transaction costs, internationalisation and logistics: The case of European food retailing, International Journal of Logistics: Research and Applications, 1, 3, pp. 251-264, (1998); Bourlakis C., Bourlakis M., Information technology safeguards, logistics asset specificity and 4th party logistics network creation in the food retail chain, Journal of Business and Industrial Marketing, 20, 2-3, pp. 88-98, (2005); Bourlakis M., Bourlakis C., Integrating logistics and information technology strategies for sustainable competitive advantage, Journal of Enterprise Information Management, 19, 2, (2006); Bowersox D.J., Daugherty P.J., Droge C.L., Germain R.N., Rogers D.S., Logistical Excellence: It's not Business as Usual, (1992); Christopher M., Logistics and supply chain management: Strategies for reducing cost and improving service, Financial Times Prentice Hall, (1998); Ciborra C.C., Olson M.H., Encountering electronic work groups: A transaction costs perspective, Office: Technology and People, 4, 4, pp. 277-290, (1989); Fitzgerald G., Willcocks L., Outsourcing information technology: Contracts and the client/vendor relationship, (1994); Gattorna J., Fourth party logistics: En route to breakthrough performance in the supply chain, Strategic Supply Chain Alignment, (1998); Johanson J., Mattsson L.G., Interorganisational relations in industrial systems: A network approach compared with the transaction cost approach, International Studies of Management and Organisation, 17, 1, pp. 34-48, (1987); Lamming R., Beyond Partnership: Strategies for Innovation and Lean Supply, (1993); Li F., What is E-Business? How the Internet Transforms Organizations, (2007); Lucas Jr. H.C., Turner J.A., A corporate strategy for the control of information processing, The Strategic Use of Information Technology, (1987); Naylor J.B., Nairn M.M., Berry D., Leagility: Integrating the lean and agile manufacturing paradigms in the total supply chain, International Journal of Production Economics, 62, 1, pp. 107-118, (1999); Papagiannidis S., Li F., Management and delivery of digital print via the web: A case study of Gaia fulfilment, International Journal of Cases of Electronic Commerce, 1, 1, pp. 1-18, (2005); Quarrie J., Hobbs S., Supply chain technology: Improving retail efficiency and effectiveness, Financial Times Retail and Consumer Publishing, (1997); Ragin C.C., The Comparative Method: Moving Beyond Qualitative and Quantitative Strategies, (1987); Silverman D., Interpreting Qualitative Data: Methods for Analysing Talk, Text and Interaction, (1994); Thorelli H.B., Networks: Between markets and hierarchies, Strategic Management Journal, 7, 1, pp. 37-51, (1986); Venkatraman N., Information technology induced business reconfiguration, The Corporation of the, (1991); Web Services Activity Statement, (2005); Yin R.K., Case Study Research: Design and Methods, (1984)","S. Papagiannidis; University of Newcastle upon Tyne, NE1 7RU, Newcastle upon Tyne, United Kingdom; email: Savvas.Papagiannidis@ncl.ac.uk",null,"Inderscience Publishers",{"$nulls":5},1.4614111E7,null,null,null,"English","Int. J. Inf. Technol. Manage.","Article","Final",null,"Scopus","2-s2.0-37849003143"]
["Angeles R.; Nath R.","Angeles, Rebecca (6701781298); Nath, Ravi (35404552800)","6701781298; 35404552800","Business-to-business e-procurement: Success factors and challenges to implementation",2007.0,"Supply Chain Management",12.0,2.0,null,104.0,115.0,11.0,104.0,"10.1108/13598540710737299","https://www.scopus.com/inward/record.uri?eid=2-s2.0-33947106968&doi=10.1108%2f13598540710737299&partnerID=40&md5=1475f52eefb3ad0a25a198bee92b7e9d","Management Information Systems Area, Faculty of Administration, University of New Brunswick Fredericton, Fredericton, Canada; College of Business Administration, Creighton University, Omaha, NE, United States","Angeles R., Management Information Systems Area, Faculty of Administration, University of New Brunswick Fredericton, Fredericton, Canada; Nath R., College of Business Administration, Creighton University, Omaha, NE, United States","Purpose - The paper seeks to pursue the understanding of current business-to-business e-procurement practices by describing the success factors and challenges to its implementation in the corporate setting. Design/methodology/approach - Members of the Institute for Supply Management and the Council of Logistics Management were asked to respond to a survey questionnaire. Factor analysis was used to analyze data from valid responses received from 185 firms. Findings - Factor analysis resulted in three e-procurement success factors (SF):supplier and contract management; end-user behavior and e-procurement business processes; and information and e-procurement infrastructure. Three challenge-to-implementation factors (CIF) also emerged: lack of system integration and standardization issues; immaturity of e-procurement-based market services and end-user resistance; and maverick buying and difficulty in integrating e-commerce with other systems. Research limitations/implications - A representative sampling design should be used in the future to be able to make claims for generalizable results. Practical implications - E-procurement is a very important initiative with significant cost savings potential for firms. This study's findings can guide various stages of corporate implementation efforts. Originality/value - This study fulfills the need for solid empirical findings on this very important topic that has a direct impact on a firm's bottom line. E-procurement is still in the early stages of marketplace deployment and guidance is still needed on how to do it right. © Emerald Group Publishing Limited.","Business-to-business marketing; Electronic commerce; Procurement; Supply chain management",{"$nulls":7},"Group A., Best Practices in E-Procurement: The Abridged Report, (2001); Attaran M., Attaran S., Catch the wave of e-procurement, Industrial Management, 11, 3, (2002); Bartels A., Organizing the Procurement Function: What to Centralize, What to Decentralize, (2004); Bartels A., Trends 2005: EProcurement/eSourcing: the 'Glass Floor' Effect Persists, (2004); Bushell S., Getting a grip on spending, CIO Magazine, 2, (2004); Churchill G.A., A paradigm for developing better measures of marketing constructs, Journal of Marketing Research, 16, pp. 64-73, (1979); Croom S.R., The impact of web-based procurement on the management of operating resources supply, The Journal of Supply Chain Management, 36, 1, pp. 4-13, (2000); Dai Q., Kauffman R., B2B e-commerce revisited: Leading perspectives on the key issues and research directions, Electronic Markets, 12, 2, pp. 67-83, (2002); Davila A., Gupta M., Palmer R., Moving procurement systems to the internet: The adoption and use of e-procurement technology models, European Management Journal, 21, 1, (2003); Day G.S., Fein A.J., Ruppersberger G., Shakeouts in digital markets lessons from B2B exchanges, California Management Review, 45, 2, pp. 131-50, (2003); Doyon T., Hope-Ross D., Luebbers J., Purchase E., Reilly B., E-procurement: Perspective, Preparation and Selection, (2001); Fitzgerald K.R., Best practices in procurement, ASCET, 4, (2002); Furlonger D., Landry S., Questions to Ask Potential B2B Marketplace Partners, (2001); Hannon D., Unready' suppliers slow move to e-procurement, Purchasing, 130, 23, (2001); Hayward C., E-procurement is no panacea, Financial Management (CIMA), (2001); Hensley R., Irani Z.J., Satpathy A., Better purchasing for auto suppliers, McKinsey Quarterly, 3, (2003); Hope-Ross D., E-procurement ROI: One Last Time Update: 10 April 2001, (2001); Hope-Ross D., E-procurement Odyssey: 2002 and Beyond, (2001); Hope-Ross D., Management Update: E-procurement - Opportunities and Market Forces in 2002 and Beyond, (2001); Hope-Ross D., Reilly B., CEO and CIO Update: Examining the Business Case for E-procurement, (2000); Hope-Ross D., Reilly B., CEO and CIO Update: E-procurement Yields Benefits but Takes Planning, Time, Work, (2000); Hope-Ross D., Luebbers J., Purchase E., Reilly B., E-procurement: A Blueprint for Revolution or Hype? Update: 9 February 2000, (2000); Huber B., Sweeney E., Smyth A., Purchasing consortia and electronic markets - A procurement direction in integrated supply chain management, Electronic Markets, 14, 4, pp. 284-94, (2004); Kaiser H.F., An index of factorial simplicity, Psychometrika, 39, pp. 31-6, (1974); Kanakamedala K.B., Ramsdell G., Roche P.J., The promise of purchasing software, McKinsey Quarterly, 4, (2003); Kheng C.B., Al-Hawandeh S., The adoption of electronic procurement in Singapore, Electronic Commerce Research, 2, 12, pp. 61-73, (2002); Kyte A., E-procurement: Yet Another Three-tier Architecture, (2000); Kyte A., There is no First-mover Advantage in E-procurement, (2000); Kyte A., Procurement: An Overview of Electronic Catalog Commerce, (2001); Kyte A., Selecting Suppliers for White-collar MRO E-procurement, (2001); Kyte A., E-procurement: Employee Self-service is the Real Benefit, (2001); Kyte A., Miklovic D., ESCM Q&A Archive, (2001); Laudon K.C., Traver C.G., E-Commerce: Business, Technology, Society, (2004); Lee G.I., Clark T.H., Market process reengineering through electronic market systems: Opportunities and challenges, Journal of Management Information Systems, 13, 3, pp. 113-36, (1997); Lennon C., Achieving Bottom Line Results in A Flat Economy: Leveraging Procurement Business Services, (2002); Lin B., Hsieh C., Online procurement: Implementation and managerial implications, Human Systems Management, 19, pp. 105-10, (2000); Lucking-Reiley D., Business-to-business electronic commerce, Journal of Economic Perspectives, 15, 1, (2001); Min H., Galle W.P., Electronic commerce-based purchasing: A survey on the perceptual differences between large and small organizations, International Journal of Logistics: Research and Applications, 4, 1, pp. 79-95, (2001); Mitchell P., Field Tactics in Spending Analysis: Commodities, Contracts and Continuous Improvement, (2004); Mukhopadhyay T., Kekre S., Strategic and operational benefits of electronic integration in B2B procurement processes, Management Science, 48, 10, (2002); Norusis M.J., SPSS Base System User's Guide, (1990); Olivia R.A., The promise of XML, Marketing Management, 10, 1, (2001); Orr B., The case for web-based procurement, ABA Banking Journal, 94, 4, (2002); Presutti W., Jr, Supply management and e-procurement: Creating value added in the supply chain, Industrial Marketing Management, 32, 3, (2003); Rajkumar T.M., E-procurement business and technical issues, Information Systems Management, 18, 4, pp. 52-61, (2001); Ranganathan C., Evaluating the options for business-to-business e-exchanges, Information Systems Management, 20, 3, (2003); Riggins F.J., Mukhopadhyay T., Interdependent benefits from interorganizational systems: Opportunities for business partner reengineering, Journal of Management Information Systems, 11, 2, pp. 37-57, (1994); Roth R.T., EProcurement: Cutting costs, adding value, Financial Executive, 17, 7, pp. 62-3, (2001); Saeed K.A., Leith R.A., Controlling sourcing risk in electronic marketplaces, Electronic Markets, 13, 2, pp. 163-72, (2003); Stevens J., Applied Multivariate Statistics for the Social Sciences, (1986); Subramaniam C., Shaw M.J., A study of the value and impact of B2B e-commerce: The case of web-based procurement, International Journal of Electronic Commerce, 6, 4, pp. 19-40, (2002); Selection S., Report M., E-procurement: Are the cost savings worth the investment?, Supplier Selection & Management Report, 1, 5, (2001); Turban E., King D., Lee J., Viehland D., Electronic Commerce 2006: A Managerial Perspective, (2006); Vesset D., IDC Surveys Procurement Analytic Application Users: Software Products Need Improvement, (2003); Yen B.P.C., Ng E.O.S., Migrating procurement onto the internet, Electronic Commerce Research, 2, pp. 113-34, (2002); Zhu K., Information transparency in electronic marketplaces: Why data transparency may hinder the adoption of B2B exchanges, Electronic Markets, 12, 2, pp. 92-9, (2002)","R. Angeles; Management Information Systems Area, Faculty of Administration, University of New Brunswick Fredericton, Fredericton, Canada; email: rangeles@unb.ca",{"$nulls":7},1.3598546E7,null,null,null,"English","Supply Chain Manage.","Article","Final",null,"Scopus","2-s2.0-33947106968"]
["Liu W.-Y.; Lin C.-C.; Yu C.-S.","Liu, Wan-Yu (16313527900); Lin, Chun-Cheng (55730237400); Yu, Chang-Sung (56141916400)","16313527900; 55730237400; 56141916400","On the three-dimensional container packing problem under home delivery service",2011.0,"Asia-Pacific Journal of Operational Research",28.0,5.0,null,601.0,621.0,20.0,15.0,"10.1142/S0217595911003466","https://www.scopus.com/inward/record.uri?eid=2-s2.0-80855139340&doi=10.1142%2fS0217595911003466&partnerID=40&md5=ad82198d96f1df502b7b418f02a80030","Department of Applied Natural Resources, Aletheia University, Tainan 721, Taiwan; Department of Industrial Engineering and Management, National Chiao Tung University, Hsinchu 300, Taiwan; Department of Business Administration, National Taiwan University, Taipei 106, Taiwan","Liu W.-Y., Department of Applied Natural Resources, Aletheia University, Tainan 721, Taiwan; Lin C.-C., Department of Industrial Engineering and Management, National Chiao Tung University, Hsinchu 300, Taiwan; Yu C.-S., Department of Business Administration, National Taiwan University, Taipei 106, Taiwan","Home delivery service is one of the most important cost drivers in e-commerce industry. We consider the three-dimensional container packing problem under home delivery service, where each rectangular item with its specific destination is loaded orthogonally onto a rectangular container so that the utilization rate of the container space is maximized. In our framework, we assume the routing of a consignment to be given, which turns out that there is an order of unloading items with respect to the consignment. If we load items without considering the order of unloading items, we may unload and reload other unconcerned items drastically while unloading the required item. Therefore, in this paper, the unloading costs for a consignment are precisely defined according to the invisible and untouchable rule, and a subvolume scheme based algorithm is proposed. Our experimental results suggest our approach to be promising. © 2011 World Scientific Publishing Co. & Operational Research Society of Singapore. © 2011 World Scientific Publishing Co. & Operational Research Society of Singapore.","Container packing problem; home delivery; logistics; transportation","Three dimensional; Unloading; Cost drivers; Home delivery; Home delivery services; Packing problems; Rectangular containers; Utilization rates; Containers",{"$nulls":4},"National Science Council, NSC, (98-2218-E-009-026-MY3)","The authors thank the anonymous referees for comments that improved the content as well as the presentation of this paper. The first two authors (Wan-Yu Liu and Chun-Cheng Lin) were supported in part by National Science Council, Taiwan (NSC Grant 98-2218-E-009-026-MY3).","Abdou G., Elmasry M., 3D random stacking of weakly heterogeneous palletization problems, International Journal of Production Research, 37, pp. 1505-1524, (1999); Abdou G., Yang M., A systematic approach for the three dimensional palletization problems, International Journal of Production Research, 32, pp. 2381-2394, (1994); Beasley J.E., An exact two-dimensional non-cutting tree search procedure, Operations Research, 33, 1, pp. 49-64, (1985); Beasley J., OR-library: Distributing test problems by electronic mail, Journal of the Operational Research Society, 41, pp. 1069-1072, (1990); Bischoff E., Ratcliff M., Issues in the development of approaches to container loading, Omega-International Journal of Management Sciences, 23, pp. 377-390, (1995); Bortfeldt A., Gehring H., MacK D., A parallel tabu search algorithm for solving the container loading problem, Parallel Computing, 29, pp. 641-662, (2003); Cormen T., Leiserson C., Rivest R., Stein C., Introduction to Algorithms, (2002); Fanslau T., Bortfeldt A., A tree search algorithm for solving the container loading problem, INFORMS Journal on Computing, (2009); Garey M., Johnson D., Computers and Intractability: A Guide to the Theory of NP-Completeness, (1979); Gehring H., Bortfeldt A., A genetic algorithm for solving the container loading problem, International Transactions on Operational Research, 4, pp. 401-418, (1997); George J., Robinson D., A heuristic for packing boxes into a container, Computers and Operations Research, 7, pp. 147-156, (1980); Gilmore P., Gomory R., Multistage cutting stock problems of two and more dimensions, Operations Research, 13, pp. 94-120, (1965); Jin Z., Ohno K., Du J., An efficient approach for the three-dimensional container packing problem with practical constraints, Asia-Pacific Journal of Operational Research, 21, pp. 279-295, (2004); Kamarainen V., Punakivi M., Developing Cost-effective Operations for the e-Grocery Supply Chain, International Journal of Logistics: Research and Applications, 5, 3, pp. 285-298, (2002); Kamarainen V., Saranen S., Jan H., How goods receipt affects e-grocery efficiently?, Proc. of 11th International Working Seminar on Production Economics, (2000); Lim A., Rodrigues B., Wang Y., A multi-faced buildup algorithm for three-dimensional packing problems, Omega, 31, 6, pp. 471-481, (2003); Mack D., Bortfeldt A., Gehring H., A parallel hybrid local search algorithm for the container loading problem, International Transactions in Operational Research, 11, 5, pp. 511-533, (2004); Morabito R., Arenales M., An AND/OR-graph approach to the container loading problem, International Transactions in Operational Research, 1, pp. 59-74, (1994); Moura A., Oliveira J.F., A GRASP approach to the container-loading problem, IEEE Intelligent Systems, 20, 4, pp. 50-57, (2005); (2007); Parreno F., Alvarez-Valdes R., Tamarit J., Oliveira J., A maximal-space algorithm for the container loading problem, INFORMS Journal on Computing, 20, pp. 412-422, (2008); Punakivi M., Comparing Alternative Home Delivery Models for E-Grocery Home Delivery, (2003); Punakivi M., Saranen J., Identifying the success factors in e-grocery home delivery, International Journal of Retail and Distribution Management, 29, pp. 156-163, (2001); Survey: E-commerce-Shopping around the web, The Economist, 354, (2000); Wascher G., Haussner H., Schumann H., An improved typology of cutting and packing problems, European Journal of Operational Research, 183, 3, pp. 1109-1130, (2007)","C.-C. Lin; Department of Industrial Engineering and Management, National Chiao Tung University, Hsinchu 300, Taiwan; email: cclin321@nctu.edu.tw",{"$nulls":7},2175959.0,null,"APJRE",null,"English","Asia Pac J Oper Res","Article","Final",null,"Scopus","2-s2.0-80855139340"]
["Kim J.; Xu M.; Kahhat R.; Allenby B.; Williams E.","Kim, Junbeum (24174599400); Xu, Ming (55519747200); Kahhat, Ramzy (17346379100); Allenby, Braden (35613906700); Williams, Eric (7403996458)","24174599400; 55519747200; 17346379100; 35613906700; 7403996458","Designing and assessing a sustainable networked delivery (SND) system: Hybrid business-to-consumer book delivery case study",2009.0,"Environmental Science and Technology",43.0,1.0,null,181.0,187.0,6.0,21.0,"10.1021/es800648s","https://www.scopus.com/inward/record.uri?eid=2-s2.0-61849132835&doi=10.1021%2fes800648s&partnerID=40&md5=da2d348bbc338beea72209926e81a154","Center for Earth Systems Engineering and Management, Department of Civil and Environmental Engineering, Arizona State University, Tempe, AZ 85287, United States; School of Sustainability, Arizona State University, Tempe, AZ 85287, United States","Kim J., Center for Earth Systems Engineering and Management, Department of Civil and Environmental Engineering, Arizona State University, Tempe, AZ 85287, United States; Xu M., Center for Earth Systems Engineering and Management, Department of Civil and Environmental Engineering, Arizona State University, Tempe, AZ 85287, United States; Kahhat R., Center for Earth Systems Engineering and Management, Department of Civil and Environmental Engineering, Arizona State University, Tempe, AZ 85287, United States; Allenby B., Center for Earth Systems Engineering and Management, Department of Civil and Environmental Engineering, Arizona State University, Tempe, AZ 85287, United States; Williams E., Center for Earth Systems Engineering and Management, Department of Civil and Environmental Engineering, Arizona State University, Tempe, AZ 85287, United States, School of Sustainability, Arizona State University, Tempe, AZ 85287, United States","We attempted to design and assess an example of a sustainable networked delivery (SND) system: a hybrid business-to-consumer book delivery system. This system is intended to reduce costs, achieve significant reductions in energy consumption, and reduce environmental emissions of critical local pollutants and greenhouse gases. The energy consumption and concomitant emissions of this delivery system compared with existing alternative delivery systems were estimated. We found that regarding energy consumption, an emerging hybrid delivery system which is a sustainable networked delivery system (SND) would consume 47 and 7 times less than the traditional networked delivery system (TND) and e-commerce networked delivery system (END). Regarding concomitant emissions, in the case of C0 2, the SND system produced 32 and 7 times fewer emissions than the TND and END systems. Also the SND system offer meaningful economic benefit such as the costs of delivery and packaging, to the online retailer, grocery, and consumer. Our research results show that the SND system has a lot of possibilities to save local transportation energy consumption and delivery costs, and reduce environmental emissions in delivery system. ©2009 American Chemical Society.",null,"Books; Carbon Dioxide; Commerce; Conservation of Energy Resources; Environment; Family Characteristics; Internet; Transportation; Global warming; Greenhouse gases; carbon dioxide; carbon dioxide; Alternative delivery systems; Business to consumers; Delivery costs; Delivery systems; E commerces; Economic benefits; End systems; Energy consumption; Environmental emissions; Hybrid deliveries; Research results; Sustainable networked delivery systems; comparative study; cost-benefit analysis; design; economic impact; emission control; energy conservation; greenhouse gas; hybrid; pollution control; sustainability; article; commercial phenomena; comparative study; consumer; cost benefit analysis; economic aspect; energy conservation; energy consumption; greenhouse gas; online system; packaging; pollutant; traffic and transport; book; economics; energy conservation; environment; family size; Internet; traffic and transport; Electronic commerce",null,"carbon dioxide, 124-38-9, 58561-67-4; Carbon Dioxide, 124-38-9",{"$nulls":4},"Allenby B., Unger D., Information Technology Impacts on the U.S. Energy Demand Profile;U.S. Department of Energy, E- Vision2000 Conference, (2000); Allenby B., Creating economic, social and environmental value: An information infrastructure perspective, Int. J Environ. Technol. Manage, 7, 5-6, pp. 618-631, (2007); Ralph S., George R., Principles of Information Systems, (2006); Richard K., Miller &Associates, The 2007 E-commerce Market Research Handbook, Richard K, (2006); Frank F., Linh T., Launching Your Yahoo! Business, (2006); Romm J., The internet and the new energy economy, Resour., Conserv. Recycl, 36, 3, pp. 197-210, (2002); Gay R.H., Davis R.A., Phillips D.T., Sui D.Z., Modeling paradigm for the environmental impacts of the digital economy, J. Organ. Comp. Elec. Comm, 15, 1, pp. 61-82, (2005); Sivaraman D., Pacca S., Mueller K., Lin J., Comparative energy, environmental, and economic analysis of traditional and e-commerce DVD rental networks, J. Ind. Ecol, 11, 3, pp. 77-91, (2007); Matthews H.S., Williams E., Tagami T., Hendrickson C.T., Energy implications of online book retailing in the United States and Japan, Environ. Impact. Assess. Rev, 22, 5, pp. 493-507, (2002); Hoogeveen M.L., Reijnders L., E-commerce, paper and energy use: A case study concerning a Dutch electronic computer retailer, Int. J. Environ. Pollut, 18, 6, pp. 541-548, (2002); Sui D.Z., Rejeski D.W., Environmental impacts of the emerging digital economy: The e-for-environment e-commerce, Environ. Manage, 29, 2, pp. 155-163, (2002); Brynjolfsson E., Smith M.D., Frictionless commerce? A comparison of internet and conventional retailers, Manage. Set, 46, 4, pp. 563-585, (2000); Matthews H.S., Hendrickson C.T., Soh D., The net effect: Environmental implications of e-commerce and logistics, Proceedings of the 2001 IEEE International Symposium on Electronics and the Environment, pp. 191-195, (2001); Matthews H.S., Hendrickson C.T., Lave L., The economic and environmental implications of centralized stock keeping, J. Ind. Ecol, 6, 2, pp. 71-81, (2002); Dinlersoz E.M., Li H., The shipping strategies of internet retailers: Evidence from internet book retailing, Quant Mark. Econ, 4, 4, pp. 407-438, (2006); Cao Y., Gruca T.S., Klemz B.R., Internet pricing, pricing satisfaction, and customer satisfaction, Int. J. Elec. Comm, 8, 2, pp. 31-50, (2003); Ancarani F., Shankar V., Price levels and price dispersion within and across multiple retailer types: Further evidence and extension, J Acad. Market. Sci, 32, 2, pp. 176-187, (2004); Fichter K., E-commerce: Sorting out the environmental consequences, J. Ind. Ecol, 6, 2, pp. 25-41, (2002); Kim J., Xu M., Kahhat R., Allenby B., Williams E., Design and assessment of a sustainable networked system in the United States: Case study of book delivery system, Proceedings of the 2008 IEEE International Symposium on Electronics and the Environment, (2008); Israel G.D., Sampling the Evidence of Extension Program Impact;Program Evaluation and Organizational Development, IFAS, University of Florida; PEOD-5, (1992); Cochran W.G., Sampling Techniques, (1977); Integrated Municipal Solid Waste Management: Six Case Studies of System, Cost and Energy Use, Summary Report, (1995); Toth P., Vigo D., The Vehicle Routing Problem, (2002); Emissions of Greenhouse Gases Report; A Wedge Analysis of the U.S. Transportation Sector; The Household Diary Study: Mail Use and Attitudes in FY 2006; The Household Diary Study: Mail Use and Attitudes in FY 2005, (2006); The 2001 National Household Travel Survey, (2004)","J. Kim; Center for Earth Systems Engineering and Management, Department of Civil and Environmental Engineering, Arizona State University, Tempe, AZ 85287, United States; email: Junbeum.kim@asu.edu",{"$nulls":7},1.5205851E7,null,"ESTHA",1.9209604E7,"English","Environ. Sci. Technol.","Article","Final",null,"Scopus","2-s2.0-61849132835"]
["XiaoYan Q.; Yong H.; Qinli D.; Stokes P.","XiaoYan, Qian (51665991200); Yong, Han (55232487600); Qinli, Da (55232442500); Stokes, Peter (8151664500)","51665991200; 55232487600; 55232442500; 8151664500","Reverse logistics network design model based on e-commerce",2012.0,"International Journal of Organizational Analysis",20.0,2.0,null,251.0,261.0,10.0,19.0,"10.1108/19348831211227864","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84861549072&doi=10.1108%2f19348831211227864&partnerID=40&md5=7936ebb4f1ab454dcde16a8e4b2153a9","Department of Management Science and Engineering, Southeast University, Nanjing, China; Chester Business School, University of Chester, Chester, United Kingdom","XiaoYan Q., Department of Management Science and Engineering, Southeast University, Nanjing, China; Yong H., Department of Management Science and Engineering, Southeast University, Nanjing, China; Qinli D., Department of Management Science and Engineering, Southeast University, Nanjing, China; Stokes P., Chester Business School, University of Chester, Chester, United Kingdom","Purpose: The aim of this paper is to study reverse logistics network design in order to better facilitate the location of factories, online retailers, and the third party logistics in the context of e-commerce. Design/methodology/approach: Drawing on types of third party collections of returned products, the paper proposes a 0-1 mixed integrate linear programming (0-1MILP) mathematic model for reverse logistics networks in e-business and a further mathematical model is discussed in relation to determining the market demands and returns. Furthermore, a case study is developed and described with the intention of illustrating the value of this model and network. Findings: The paper identifies possibilities for the application of the reverse logistics network models to deal with returned products from customers in companies using e-business. Research limitations/implications: There is scope for future research to build on the present research and consider further factors in relation to the influences on return logistics. Originality/value: This paper provides novel insights for e-companies setting up and operating a reverse logistics network. The application of these models could decrease costs and allow optimal decisions on price and return price in order to increase efficiency and profit levels. © Emerald Group Publishing Limited.","Electronic commerce; Return policy; Returns; Reverse logistics; Third-party logistics",{"$nulls":7},"Fleischmann M., Krikke H.R., Dekker R., Flapper S.D.P., A characterization of logistics networks for product recovery, Omega, 28, 16, pp. 653-666, (2000); Krishnan T.V., Bass F.M., Jain D.C., Optimal pricing strategy for new products, Management Science, 45, 12, pp. 1650-1663, (1999); Liu L., Xue H.C., Wang X., Research on reverse logistics distribution center location problem in E-business, IEEE International Conference on E-Business Engineering, Shanghai, pp. 501-504, (2010); Ni M., Liao R.H., Four types of reverse logistics model based on E-commerce environment, Journal of E-Business, 53, 18, pp. 137-139, (2009); Xiong Y., Reverse logistics profit-maximization model and its application strategy based on E-business, Journal of Shanghai Institution of Technology, 5, 3, pp. 180-182, (2005); Zhou Y.S., Wang S., Generic model of reverse logistics network design, Journal of Transportation Systems Engineering and Information Technology, 8, 3, pp. 71-78, (2008); Du J., Guo C., Return policy e-commerce optimization, Logistics Engineering and Management, 32, 6, pp. 116-117, (2010); Lu Z.Q., Bostel N., A facility model for logistics systems including reverse flows: The case of remanufacturing actives, Computers & Operation Research, 34, 2, pp. 299-323, (2007); Samar K.M., Robert S., Reverse logistics in E-business: Optimal price and return policy, International Journal of Physical Distribution & Logistics Management, 34, 1, pp. 70-80, (2004); Woo-Tsong L., Huei-Ching L., Ya-Hui L., A decision model for reverse logistics service providers in determining robust optimal processing quantities of returned products, Journal of the Chinese Institute of Industrial Engineers, 26, 5, pp. 397-410, (2010)","Q. XiaoYan; Department of Management Science and Engineering, Southeast University, Nanjing, China; email: qian-xiao-yan@163.com",{"$nulls":7},1.9348835E7,null,null,null,"English","Int. J. Organ. Anal.","Article","Final",null,"Scopus","2-s2.0-84861549072"]
["Picot-Coupey K.; Huré E.; Cliquet G.; Petr C.","Picot-Coupey, Karine (35747121000); Huré, Elodie (35745986200); Cliquet, Gérard (23988577200); Petr, Christine (14030556600)","35747121000; 35745986200; 23988577200; 14030556600","Grocery shopping and the Internet: Exploring French consumers' perceptions of the 'hypermarket' and 'cybermarket' formats",2009.0,"International Review of Retail, Distribution and Consumer Research",19.0,4.0,null,437.0,455.0,18.0,39.0,"10.1080/09593960903331477","https://www.scopus.com/inward/record.uri?eid=2-s2.0-77949469284&doi=10.1080%2f09593960903331477&partnerID=40&md5=ae56344c6ade6a86ec13d88f160dec50","CREM UMR CNRS 6211, IGR-IAE, Université de Rennes 1, Rennes, France; CERMAT, IAE de Tours, Université Francçois Rabelais, Tours, France","Picot-Coupey K., CREM UMR CNRS 6211, IGR-IAE, Université de Rennes 1, Rennes, France; Huré E., CREM UMR CNRS 6211, IGR-IAE, Université de Rennes 1, Rennes, France; Cliquet G., CREM UMR CNRS 6211, IGR-IAE, Université de Rennes 1, Rennes, France; Petr C., CERMAT, IAE de Tours, Université Francçois Rabelais, Tours, France","The growth of e-commerce calls into question the viability of traditional retail formats. Information and Communication Technologies (ICT), especially the Internet, now play a major role in retailing. With the stagnation of the hypermarket format in France, developing ICT could be a way for grocery retail companies to reinitiate growth. Some questions arise concerning the consumers' acceptance of these new technologies for food retailing. How does the consumer perceive the opportunities for the Internet and what associations do they hold for their favourite store? To what extent could consumers integrate ICT, especially the Internet, in their current or in future grocery shopping behaviours? Within this context, this paper focuses on the 'consumer-store' relationships. The research aims to explore consumers' perceptions of hypermarket and cybermarket formats for grocery shopping. The methodology is qualitative and based on 18 semi-structured interviews and on three focus groups of French consumers. Results show that the hypermarket format continues to appeal to French consumers while the cybermarket format remains unclear. The two targets - 'the organised' and 'the grumblers' - are an exception to this trend. © 2009 Taylor & Francis.","Cybermarket; Drive-in delivery system; E-grocery retailing; French retailers; Hypermarket",{"$nulls":7},"Baray J., Cliquet G., Delineating and analyzing trade areas through morphological analysis, European Journal of Operational Research, 182, 2, pp. 886-898, (2007); Bawa K., Ghosh A., A model of household grocery shopping behaviour, Marketing Letters, 10, 2, pp. 149-160, (1999); Berkowitz E.N., Walton J.R., Walker O.C., In-home shoppers: The market for innovative distribution systems, Journal of Retailing, 55, 2, pp. 15-33, (1979); Bevan J., Murphy R., The nature of value created by UK online grocery retailers, International Journal of Consumer Studies, 25, 4, pp. 279-289, (2001); Biswas A., Krishnan R., The Internet's impact on marketing: Introduction to the JBR special issue on 'Marketing on the web - behavioral, strategy and practices and public policy, Journal of Business Research, 57, 7, pp. 681-684, (2004); Bray F., Les supermarches en ligne accélèrent enfin, LSA, 2061-2062, pp. 22-25, (2008); Brooks C.H., Kaufman P.J., Lichtenstein D.R., Travel configuration on consumer Trip-chained Store Choice, Journal of Consumer Research, 31, 2, pp. 241-248, (2004); Childers T.L., Carr C.L., Peck J., Carson S., Hedonic and utilitarian motivations for online retail shopping behaviour, Journal of Retailing, 77, 4, pp. 511-535, (2001); Clark L., Wright P., Off their trolley - Understanding online grocery shopping behaviour, Home Informatics and Telematics: Ict For the Next Billion, pp. 157-170, (2007); Cliquet G., Implementing a subjective MCI model: An application to the furniture market, European Journal of Operational Research, 84, 2, pp. 279-291, (1995); Cliquet G., L'attraction commerciale: Fondement de la localisation différentielle, Revue Belge de Géographie, 121, 1-4, pp. 57-70, (1997); Cliquet G., Geomarketing: Methods and Strategies In Spatial Marketing, (2006); Cooper L.G., Nakanishi M., Market-share Analysis: Evaluating Competitive Marketing Effectiveness, (1988); Corbett J.J., Is online grocery shopping increasing in strength?, Journal of Food Distribution Research, 32, 1, pp. 37-40, (2001); Dandouau J.-C., Risque, inference et biais decisionnels dans les choix de consommation alimentaire, Revue Française De Marketing, 183-184, 3-4, pp. 133-147, (2001); Darian J.C., In-home shopping: Are there consumer segments?, Journal of Retailing, 63, 2, pp. 163-186, (1987); Desarbo W.S., Degeratu A.M., Ahearne M.J., Saxton M.K., Desaggregate market share response models, International Journal of Research In Marketing, 19, 3, pp. 253-266, (2002); Dholakia R.R., Dholakia N., Mobility and markets: Emerging outlines of m-commerce, Journal of Business Research, 57, 12, pp. 1391-1396, (2004); Donthu N., Garcia A., The Internet shopper, Journal of Advertising Research, 39, 3, pp. 52-58, (1999); Ellis-Chadwick F., Doherty N., Hart C., Signs of change? A longitudinal study of Internet adoption in the UK retail sector, Journal of Retailing and Consumer Service, 9, 2, pp. 71-80, (2002); Fernandez J., Pelegrin B., Plastria F., Toth B., Solving a Huff-like competitive location and design model for profit maximization in the plane, European Journal of Operational Research, 179, 3, pp. 1274-1287, (2007); Fernie J., McKinnon A.C., Online shopping: The logistic issues, The Retailing Book: Principles and Applications, pp. 273-285, (2003); Les Chiffres-clés 2008, (2008); Fox E.J., Montgomery A.L., Lodish L.M., Consumer shopping and spending across retail formats, Journal of Business, 77, 2, pp. 25-60, (2004); Golledge R.G., Stimson R.J., Spatial Behavior: A Geographic Perspective, (1997); Gonzalez-Benito O., Geodemographic and socioeconomic characterization of the retail attraction of leading hypermarket chains in Spain, International Review of Retail, Distribution and Consumer Research, 12, 1, pp. 81-103, (2000); Gonzalez-Benito O., Greatorex M., Munoz-Gallego P.A., Assessment of potential retail segmentation variables: An approach based on a subjective MCI resource allocation model, Journal of Retailing and Consumer Services, 7, 3, pp. 171-179, (2000); Gonzalez-Benito O., Munoz-Gallego P.A., Kopalle P.K., Asymmetric competition in retail store formats: Evaluating inter- and intra-format spatial effects, Journal of Retailing, 81, 1, pp. 59-73, (2005); Grunert K.G., Ramus K., Consumers' willingness to buy food through the internet - A review of the literature and a model for future research, British Food Journal, 107, 6, pp. 381-403, (2005); Guerin J.-Y., Les hypermarchés se convertissent au \"drive, Le Figaro, 5-22, (2009); Hackney R., Grant K., Birtwistle G., The UK grocery business: Towards a sustainable model for virtual markets, International Journal of Retail and Distribution Management, 34, 4-5, pp. 354-368, (2006); Hansen T., Consumer adoption of online grocery buying: A discriminant analysis, International Journal of Retail and Distribution Management, 33, 2, pp. 101-121, (2005); Hart C., Doherty N., Ellis-Chadwick F., Retailer adoption of the Internet - Implications for retail marketing, European Journal of Marketing, 34, 8, pp. 954-974, (2000); Helme-Guizon A., Le comportement du consommateur sur un site marchand est-il fondamentalement différent de son comportement en magasin? Proposition d'un cadre d'apprehension de ses spécificités, Recherche Et Applications En Marketing, 16, 3, pp. 25-38, (2001); Hoffman D.L., Novak T.P., Marketing in hypermedia computer-mediated environments: Conceptual foundations, Journal of Marketing, 60, 3, pp. 50-68, (1996); Huff D.L., Defining and estimating a trading area, Journal of Marketing, 28, 3, pp. 34-38, (1964); Konus U., Verhoef P.C., Neslin S.A., Multichannel shopper segments and their covariates, Journal of Retailing, 84, 4, pp. 398-413, (2008); Latour P., Le Floc'h J., Géomarketing: Principes, Méthodes Et Applications, (2001); Lenz B., Nobis C., The changing allocation of activities in space and time by the use of ICT - ''Fragmentation'' as a new concept and empirical results, Transportation Reearch Part A: Policy & Practice, 41, 3, pp. 190-204, (2007); Mathwick C., Malhotra N., Rigdon E., Experiential value: Conceptualization, measurement and application in the catalogue and the Internet shopping environment, Journal of Retailing, 77, 1, pp. 39-56, (2001); McGoldrick P.J., Andre E., Consumer misbehaviour: Promiscuity of loyalty in grocery shopping, Journal of Retailing and Consumer Services, 4, 2, pp. 73-81, (1997); McGoldrick P.J., Collins N., Multichannel retailing: Profiling multichannel shoppers, International Review of Retail, Distribution and Consumer Research, 17, 2, pp. 139-158, (2007); Miles M.B., Huberman A.M., Qualitative Data Analysis, (1994); Morganosky M.A., Retail market structure change: Implications for retailers and consumers, International Journal of Retail & Distribution, 25, 8, pp. 269-274, (1997); Morganosky M., Cude B., Consumer response to online grocery shopping, International Journal of Retail and Distribution Management, 28, 1, pp. 17-26, (2000); Morganosky M., Cude B., Consumer demand for online food retailing: Is it really a supply side issue?, International Journal of Retail and Distribution Management, 30, 10, pp. 451-458, (2002); Nakanishi M., Cooper L.G., Parameter estimation for a multiplicative competitive interaction model - Least square approach, Journal of Marketing Research, 11, 3, pp. 303-311, (1974); Newton I., The Principia, (1686); Nicholson M., Clarke I., Blakemore M., One brand, three ways to shop: Situational variables and multichannel consumer behaviour, The International Review of Retail, Distribution and Consumer Research, 12, 2, pp. 131-148, (2002); Okunuki K.-I., Okabe A., Solving the Huff-based competitive location model on a network with link-based demand, Annals of Operations Research, 111, 1-4, pp. 239-252, (2002); Park C.W., Iyer I.S., Smith D.C., The effects of situational factors on in-store grocery shopping behavior: The role of store environment and time available for shopping, Journal of Consumer Research, 15, 4, pp. 422-433, (1989); Peterson R.A., Balasubramanian S., Bronnenberg B.J., Exploring the implications of the Internet for consumer marketing, Journal of The Academy of Marketing Science, 25, 4, pp. 329-346, (1997); Raijas A., The consumer benefits and problems in the electronic grocery store, Journal of Retailing and Consumer Services, 9, 2, pp. 107-113, (2002); Raijas A., Tuunainen V.P., Critical factors in electronic grocery shopping, The International Review of Retail, Distribution and Consumer Research, 11, 3, pp. 255-265, (2001); Reilly W.J., The Law of Retail Gravitation, (1931); Reinert M., Alceste, (2006); Reutterer T., Teller C., Store format choice and shopping trip types, International Journal of Retail & Distribution Management, 37, 8, pp. 695-710, (2009); Rogers D., Retail location analysis in the United States, European Retail Digest, 37, 1, pp. 24-25, (2003); Schenk T.A., Loffler G., Rauh J., Agent-based simulation of consumer behavior in grocery shopping on a regional level, Journal of Business Research, 60, 8, pp. 894-903, (2007); Seth A., Randall G., Supermarket Wars: Global Strategies For Food Retailers, (2005); Tashakkori A., Teddlie C., Mixed Methodolgy: Combining Quantitative and Qualitatives Approaches, (2003); Teller C., Kotzab H., Grant D., The consumer direct services revolution in grocery retailing: An exploratory investigation, Managing Service Quality, 16, 1, pp. 78-96, (2006); Vande Walle S., Steenberghen T., Space and time related determinants of public transport use in trip chains, Transportation Research Part A, 40, 2, pp. 151-162, (2006); Verhoef P.C., Langerak F., Possible determinants of consumers' adoption of electronic grocery shopping in the Netherlands, Journal of Retailing and Consumer Services, 8, 5, pp. 275-285, (2001); White G.K., Online speciality food consumers in 2000: Who they are and what they buy?, Journal of Food Distribution Research, 32, 2, pp. 39-52, (2001); Wilson-Jeanselme M., Reynolds J., Understanding shoppers' expectations of online grocery retailing, International Journal of Retail and Distribution Management, 34, 7, pp. 529-540, (2006); Zipf G.K., Human Behavior and The Principle of Least Effort, (1949)","K. Picot-Coupey; CREM UMR CNRS 6211, IGR-IAE, Université de Rennes 1, Rennes, France; email: karine.picot@univ-rennes1.fr",null,"Routledge",{"$nulls":5},9593969.0,null,null,null,"English","Int. Rev. Retail Distrib. Consum. Res.","Article","Final",null,"Scopus","2-s2.0-77949469284"]
["Asdemir K.; Jacob V.S.; Krishnan R.","Asdemir, Kursad (24072886800); Jacob, Varghese S. (7006604302); Krishnan, Ramayya (7402451300)","24072886800; 7006604302; 7402451300","Dynamic pricing of multiple home delivery options",2009.0,"European Journal of Operational Research",196.0,1.0,null,246.0,257.0,11.0,63.0,"10.1016/j.ejor.2008.03.005","https://www.scopus.com/inward/record.uri?eid=2-s2.0-56549124436&doi=10.1016%2fj.ejor.2008.03.005&partnerID=40&md5=cf2cc769e0d327bfeedd949722db3600","School of Business, University of Alberta, Edmonton, AB T6G 2R6, 323 Business Building, Canada; School of Management, The University of Texas at Dallas, Richardson, TX 75083-0688, United States; H. John Heinz III School of Public Policy and Management, CMU, Pittsburgh, PA 15213, United States","Asdemir K., School of Business, University of Alberta, Edmonton, AB T6G 2R6, 323 Business Building, Canada; Jacob V.S., School of Management, The University of Texas at Dallas, Richardson, TX 75083-0688, United States; Krishnan R., H. John Heinz III School of Public Policy and Management, CMU, Pittsburgh, PA 15213, United States","Online grocers accept delivery bookings and have to deliver groceries to consumers' residences. Grocery stores operate on very thin margins. Therefore, a critical question that an online grocery store needs to address is the cost of home delivery operations. In this paper, we develop a Markov decision process-based pricing model that recognizes the need to balance utilization of delivery capacity by the grocer and the need to have the goods delivered at the most convenient time for the customer. The model dynamically adjusts delivery prices as customers arrive and make choices. The optimal prices have the following properties. First, the optimal prices are such that the online grocer gains the same expected payoff in the remaining booking horizon, regardless of the delivery option independently chosen by a consumer. Second, with unit order sizes, delivery prices can increase due to dynamic substitution effects as there is less time left in the booking horizon. © 2008 Elsevier B.V. All rights reserved.","Dynamic programming; E-commerce; Pricing; Revenue management","Economics; Electronic commerce; Management; Retail stores; Systems engineering; Wireless telecommunication systems; Critical questions; Delivery capacities; Dynamic pricing; Dynamic substitutions; Dynamically adjusts; E-commerce; Grocery stores; Home deliveries; Markov Decision processes; Order sizes; Pricing; Pricing models; Revenue management; Costs",{"$nulls":4},"University of Alberta, U of A","Kursad Asdemir’s research is partly supported by the Winspear Senior Faculty Fellowship at the School of Business, University of Alberta. We acknowledge extensive and helpful comments by three anonymous referees that improved this paper significantly.  ","Ben-Akiva M., Lerman R.S., Discrete Choice Analysis, (1985); Campbell A.M., Savelsbergh P.W.M., Decision support for consumer direct grocery initiatives, Transportation Science, 39, pp. 313-327, (2005); Campbell A.M., Savelsbergh P.W.M., Incentive schemes for attended home delivery services, Transportation Science, 40, pp. 327-341, (2006); Elmaghraby W., Keskinocak P., Dynamic pricing in the presence of inventory considerations: research overview, current practices, and future directions, Management Science, 49, pp. 1287-1309, (2003); Favier J., Europe's eCommerce Forecast: 2006 to 2011, (2006); Gallego G., Phillips R., Revenue management of flexible products, Management and Service Operations Management, 6, pp. 321-337, (2004); Gallego G., van Ryzin G., Optimal dynamic pricing of inventories with stochastic demand over finite horizons, Management Science, 40, pp. 999-1020, (1994); Gallego G., van Ryzin G., A multiproduct dynamic pricing problem and its applications to network yield management, Operations Research, 45, pp. 24-41, (1997); Johnson C.A., US eCommerce: 2005 to 2010, (2005); Kamarainen V., Saranen J., Holmstrom J., The reception box impact on home delivery efficiency in the e-grocery business, International Journal of Physical Distribution and Logistics Management, 31, pp. 414-426, (2001); Lee T.C., Hersh M., A model for dynamic airline seat inventory control with multiple seat bookings, Transportation Science, 27, pp. 252-265, (1993); McGill J.I., van Ryzin G., Revenue management: Research overview and prospects, Transportation Science, 33, pp. 233-256, (1999); Punakivi M., Saranen J., Identifying the success factors in e-grocery home delivery, International Journal of Retail and Distribution Management, 29, pp. 156-163, (2001); Punakivi M., Yrjola H., Holmstrom J., Solving the last mile issue: Reception box or delivery box?, International Journal of Physical Distribution and Logistics Management, 31, pp. 427-439, (2001); Puterman M., Markov Decision Processes: Discrete Stochastic Dynamic Programming, (1994); Subramanian J., Lautenbacher J.C., Stidham J.S., Yield management with overbooking, cancellations, and no-shows, Transportation Science, 33, pp. 147-167, (1999); Talluri K., Van Ryzin G., Revenue management under a general discrete choice model of consumer behavior, Management Science, 50, pp. 15-33, (2004); Tanskanen K., Yrjola H., Holmstrom J., The way to profitable internet grocery retailing - six lessons learned, International Journal of Retail & Distribution Management, 30, pp. 169-178, (2002); Topkis D., Supermodularity and Complementarity, (1998); Van Slyke R., Young Y., Finite horizon stochastic knapsacks with applications to yield management, Operations Research, 48, pp. 155-172, (2000); Weatherford L.R., Bodily E.S., A taxonomy and research overview of perishable-asset revenue management: Yield management, overbooking and pricing, Operations Research, 40, pp. 831-844, (1992); Yrjola H., Physical distribution considerations for electronic grocery shopping, International Journal of Physical Distribution and Logistics Management, 31, pp. 746-761, (2001)","K. Asdemir; School of Business, University of Alberta, Edmonton, AB T6G 2R6, 323 Business Building, Canada; email: kasdemir@ualberta.ca",{"$nulls":7},3772217.0,null,"EJORD",null,"English","Eur J Oper Res","Article","Final",null,"Scopus","2-s2.0-56549124436"]
["Vatovec Krmac E.","Vatovec Krmac, Evelin (55609456700)",5.56094567E10,"Interdependence between logistics activities and information communication technologies (ICT)",2007.0,"Promet - Traffic and Transportation",19.0,2.0,null,115.0,119.0,4.0,3.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-34250349144&partnerID=40&md5=8fff07035d3d3ce2c3b82dfd9aa1d58b","University of Ljubljana, Faculty of Maritime Studies and Transport, SI-6320 Portorož, Pot pomorščakov 4, Slovenia","Vatovec Krmac E., University of Ljubljana, Faculty of Maritime Studies and Transport, SI-6320 Portorož, Pot pomorščakov 4, Slovenia","With the growing trend toward the use of international supply chains and e-commerce, logistics service providers for product warehousing, transportation and delivery are placing greater emphasis on information communication technologies (ICT) in order to remain competitive globally. In the last decades, innovative ICT have deeply affected the way business is performed and the way that organizations compete. Innovations in electronic commerce play a key role in managing inter-organizational networks of supply chain members. The internet represents a powerful technology for commerce and communication between supply chain participants as well as a technique for the improvement of supply chain management. But there are still some barriers that prevent the use of ICT in supply chains and consequently the ability to utilize all potential ICT advantages.","Information communication technology; Internet; Logistics service provider; Supply chain","Competitive intelligence; Electronic commerce; Information technology; Innovation; International trade; Logistics; Supply chain management; e-commerce; information and communication technology; innovation; Internet; logistics",{"$nulls":6},"Daniel E.M., Et al., Exploring the role of third parties in inter-organizational Web service adoption, The Journal of Enterprise Information Management, 15, 5, pp. 351-360, (2004); Lancioni R., Et al., Internet impacts on supply chain management, Industrial Marketing Management, 32, pp. 173-175, (2003); Lemoine W., Dagnaes L., Globalisation strategies and business organisation of a network of logistics service providers, International Journal of Physical Distribution & Logistics Management, 33, 3, pp. 209-228, (2003); McIvor R., Humphreys P., The implications of electronic B2B intermediaries for the buyer-supplier interface, International Journal of Operations & Production Management, 24, 3, pp. 241-269, (2004)","E. Vatovec Krmac; University of Ljubljana, Faculty of Maritime Studies and Transport, SI-6320 Portorož, Pot pomorščakov 4, Slovenia; email: evelin.vatovec@fpp.edu",null,"Faculty of Transport and Traffic Engineering",{"$nulls":5},3535320.0,null,"POMEE",null,"English","Promet Traffic Traffico","Article","Final",null,"Scopus","2-s2.0-34250349144"]
["Teo J.S.E.; Taniguchi E.; Qureshi A.G.","Teo, Joel S. E. (55975657300); Taniguchi, Eiichi (35607247900); Qureshi, Ali Gul (26634365500)","55975657300; 35607247900; 26634365500","Evaluation of distance-based and cordon-based urban freight road pricing in E-Commerce environment with multiagent model",2012.0,"Transportation Research Record",null,2269.0,null,127.0,134.0,7.0,30.0,"10.3141/2269-15","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84891045106&doi=10.3141%2f2269-15&partnerID=40&md5=1e245c9a76412187b759e46cbcb50117","Department of Urban Management, Graduate School of Engineering, Kyoto University, Kyoto 615-8540, C1-2-338 Nishikyo, Japan; Department of Urban Management, Graduate School of Engineering, Kyoto University, Kyoto 615-8540, C1-2-335 Nishikyo, Japan; Department of Urban Management, Graduate School of Engineering, Kyoto University, Kyoto 615-8540, C1-3-183, Nishikyo, Japan","Teo J.S.E., Department of Urban Management, Graduate School of Engineering, Kyoto University, Kyoto 615-8540, C1-2-338 Nishikyo, Japan; Taniguchi E., Department of Urban Management, Graduate School of Engineering, Kyoto University, Kyoto 615-8540, C1-2-335 Nishikyo, Japan; Qureshi A.G., Department of Urban Management, Graduate School of Engineering, Kyoto University, Kyoto 615-8540, C1-3-183, Nishikyo, Japan","E-commerce is gradually changing the way shoppers acquire goods and services. Shoppers seek ways to purchase goods easily through the Internet, and shippers or producers offer cheap ways to deliver goods to their customers through the services of carriers for home delivery. A theoretical model was established to evaluate city logistics schemes for multiple stakeholders before implementation. Policy measures to manage truck operations in the city and keep pollution levels at a minimum were evaluated. Cordon-based freight road pricing was found to provide better pollution reduction compared with distance-based pricing, but cordon-based pricing had less impact on areas outside a city. The problem was solved with a modeling approach for multiagent systems that used a vehicle routing problem with time windows, freight electronic marketplaces, and Q-learning.",null,"Costs; Multi agent systems; Pollution; Roads and streets; Vehicle routing; City logistics; Distance-based; Good and services; Home delivery; Multi-Agent Model; Multiple stakeholders; Policy measures; Pollution level; Road pricing; Theoretical modeling; Electronic commerce",{"$nulls":4},"Japan Society for the Promotion of Science, JSPS, (23360222)",null,"Conference on Empowering E-Consumers: Strengthening Consumer Protection in the Internet Economy, (2009); Global Trends in Online Shopping: A Nielsen Global Consumer Report, (2010); Retail and Shopper Trends Asia Pacific 2010: The Latest in Retailing and Shopper Trends for the FMCG Industry, (2010); Visser J., Hassall K., The future of city logistics: Estimating the feasibility of home delivery in urban areas, Recent Advances in City Logistics: Proceedings of the 4th International Conference on City Logistics, pp. 147-161, (2006); Esser K., Kurte J., B2C e-Commerce: Impact on transport in urban areas, Recent Advances in City Logistics: Proceedings of the 4th International Conference on City Logistics, pp. 437-448, (2006); Cullinane S., From bricks to clicks: The impact of online retailing on transport and the environment, Transport Reviews, 29, 6, pp. 759-776, (2009); Browne M., Allen J., Anderson S., Jackson M., Overview of Home Deliveries in the UK (A Study for DTI), (2001); Taniguchi E., Yamada T., Okamoto M., Multi-agent modelling for evaluating dynamic vehicle routing and scheduling systems, Journal of the Eastern Asia Society for Transportation Studies, 7, pp. 933-948, (2007); Tamagawa D., Taniguchi E., Yamada T., Evaluating city logistics measures using a multi-agent model, Proc., Sixth International Conference of City Logistics, pp. 6141-6153, (2009); Visser J., Nemoto T., Boerkamps J., E-commerce and city logistics, City Logistics, 2, pp. 35-66, (2001); Winners/Media Lions Winners; Taniguchi E., Thomson R.G., Yamada T., Van Duin R., City logistics: Network modelling and intelligent transport systems, Elsevier Science, (2001); Delivering the Goods: 21st Century Challenges to Urban Goods Transport, (2003); Russo F., Comi A., A classification of city logistics measures and connected impacts, Proc., Sixth International Conference on City Logistics, pp. 6355-6365, (2010); Taniguchi E., Nemoto T., Transport-demand management for freight transport, Innovations in Freight Transport, pp. 101-124, (2003); Anderson S., Allen J., Browne M., Urban logistics: How can it meet policy makers' sustainability objectives, Journal of Transport Geography, 13, 1, pp. 71-81, (2005); Ogden K.W., Urban Goods Movement: A Guide to Policy and Planning, (1992); De Palma A., Lindsey R., Traffic congestion pricing methodologies and technologies, Transportation Research Part C, 19, 6, pp. 1377-1399, (2011); Quak H., Van Duin J., The influence of road pricing on physical distribution in urban areas, Proc., Sixth International Conference on City Logistics, pp. 6141-6153, (2010); Holguin-Veras J., Wang Q., Xu N., Ozbay K., Cetin M., Polimeni J., The impacts of time of day pricing on the behaviour of freight carriers in a congested urban area: Implications to road pricing, Transportation Research Part A, 40, 9, pp. 744-766, (2006); Holguin-Veras J., The truth, the myths and the possible in freight road pricing in congested urban areas, Proc., Sixth International Conference on City Logistics, pp. 6366-6377, (2010); Thompson R.G., Chiang C., Jeevaptsa M., Modelling the effects of E-commerce, City Logistics, pp. 99-110, (2001); Taniguchi E., Kakimoto Y., Modelling effects of E-commerce on urban freight transport, Logistics Systems for Sustainable Cities, pp. 135-146, (2004); Yamada T., Taniguchi E., Modelling the effects of city logistics schemes, Recent Advances in City Logistics: Proceedings of the 4th International Conference on City Logistics, pp. 75-89, (2006); Taniguchi E., Thompson R.G., Yamada T., Incorporating risks in city logistics, Proc., Sixth International Conference on City Logistics, pp. 5899-5910, (2010); Parunak H., Industrial and practical applications of DAI, In Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence, (1999); Davidsson P., Henesey L., Ramstedt L., Tornquist J., Wernstedt F., An analysis of agent-based approaches to transport logistics, Transportation Research Part C, 13, 4, pp. 255-271, (2005); Weiss G., Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence, (1999); Wooldridge M., An Introduction to Multiagent Systems, (2009); Thompson R., Van Duin R., Vehicle routing and scheduling, Innovations in Freight Transport, pp. 47-63, (2003); Barcelo J., Grzybowska H., Pardo S., Vehicle routing and scheduling models, simulation and city logistics, Dynamic Fleet Management: Concepts, Systems, Algorithms, and Case Studies, pp. 163-195, (2007); Sirikijpanichkul A., Van Dam K.H., Ferreira L., Lukszo Z., Optimizing the location of intermodal freight hubs: An overview of the agent based modelling approach, Journal of Transportation Systems Engineering and Information Technology, 7, 4, pp. 71-81, (2007); Louie M.A., Carley K.M., Balancing the criticisms: Validating multi-agent models of social systems, Simulation Modelling Practice and Theory, 16, 2, pp. 242-256, (2008); Taniguchi E., Thompson R., Yamada T., Data collection for modelling, evaluating and benchmarking city logistics schemes, Recent Advances in City Logistics: Proceedings of the 4th International Conference on City Logistics, pp. 1-14, (2006); Van Duin J., Tavasszy L., Taniguchi E., Real-time simulation of auctioning and re-scheduling processes in hybrid freight markets, Transportation Research Part B, 41, 9, pp. 1050-1066, (2007); Song J., Regan A., Combinatorial auctions for transportation service procurement: The carrier perspective, Transportation Research Record: Journal of the Transportation Research Board No 11833, pp. 40-46, (2003); Nandiraju S., Regan A., Freight Transportation Electronic Marketplaces: A Survey of the Industry and Exploration of Important Research Issues, (2008); Krishna V., Auction Theory, (2010); Watkins C.J.C.H., Learning from Delayed Rewards, (1989); Quantitative Appraisal Index Calculations Used for Basic Unit Computation of CO2, (2003)",null,null,"National Research Council",{"$nulls":5},3611981.0,null,"TRRED",null,"English","Transp Res Rec","Article","Final",null,"Scopus","2-s2.0-84891045106"]
["Germanakos P.; Tsianos N.; Lekkus Z.; Mourlas C.; Samaras G.","Germanakos, Panagiotis (23389317300); Tsianos, Nikos (24077468700); Lekkus, Zacharias (25653572000); Mourlas, Constantinos (35088636400); Samaras, George (7003437264)","23389317300; 24077468700; 25653572000; 35088636400; 7003437264","Improving m-commerce services effectiveness with the use of user-centric content delivery",2008.0,"Journal of Electronic Commerce in Organizations",6.0,1.0,null,1.0,18.0,17.0,11.0,"10.4018/jeco.2008010101","https://www.scopus.com/inward/record.uri?eid=2-s2.0-56649124531&doi=10.4018%2fjeco.2008010101&partnerID=40&md5=a4d92db4ea899e41569f91a7cf744333","Laboratory of New Technologies, Faculty of Communication and Media Studies, National and Kapodistrian University of Athens, Athens, Greece; National and Kapodistrian University of Athens, Athens, Greece; University of Cyprus, Cyprus","Germanakos P., Laboratory of New Technologies, Faculty of Communication and Media Studies, National and Kapodistrian University of Athens, Athens, Greece; Tsianos N., Laboratory of New Technologies, Faculty of Communication and Media Studies, National and Kapodistrian University of Athens, Athens, Greece; Lekkus Z., Laboratory of New Technologies, Faculty of Communication and Media Studies, National and Kapodistrian University of Athens, Athens, Greece; Mourlas C., National and Kapodistrian University of Athens, Athens, Greece; Samaras G., University of Cyprus, Cyprus","Advances in wireless communications and information technology have made the Mobile Web a reality. The Mobile Web is the response to the need for anytime, anywhere access to information and services. Many wireless applications have already been deployed and are available to customers via their mobile phones and wirelessly-connected PDAs. However, as communications and other IT usage becomes an integral part of many people's lives and the available products and services become more varied and capable, users expect to be able to personalize a service to meet their individual needs and preferences. The involved sectors have to meet these challenges by reengineering their front-end and back-end office. This article will examine the interaction requirements regarding a friendlier, personalized and more effective multi-channel services environment. It will present the mobility challenges and constraints implemented into the business sector, investigating the current m-commerce situation and the extended user characteristics presenting a high level user-centric m-commerce architecture. Copyright © 2008, IGI Global.","E-commerce models; Information filtering; Mobile commerce; Web architecture; XML","Commerce; Information filtering; Web crawler; Wireless telecommunication systems; XML; Content delivery; E-commerce model; Multi-channel services; Products and services; User characteristics; Web architecture; Wireless application; Wireless communications; Mobile commerce",{"$nulls":6},"Adomavicious G., Tuzhilin A., User profiling in personalization applications through rule discovery and validation, Proceedings of the ACM Fifth International Conference on Data Mining and Knowledge Discovery (KDD'99), pp. 377-381, (1999); Balasubramanian S., Peterson R.A., Jarvnpaa S.L., Exploring the implications of m-commerce for markets and marketing, Journal of the Academy of Marketing Science, 30, 4, pp. 348-361, (2002); Bayne K.M., Marketing without wires, (2002); Caldow J., E-gov goes wireless: From Palm to shining Palm, (2001); Candace D.P., E-commerce and m-commerce technologies, (2005); Drucker P.F., Managing the non-profit organisation: Practices and principles, (1995); Easton J., Going wireless: Transform your business with mobile technology, (2002); User interaction, (2004); Frolick M.N., Chen L.-D., Assessing m-commerce opportunities, Information Systems Management, pp. 53-61, (2004); Germanakos P., Tsianos N., Lekkas Z., Mourlas C., Samaras G., Capturing essential intrinsic user behaviour values for the design of comprehensive Web-based personalized environments, Computers in Human Behavior Journal, (2006); Germanakos P., Tsianos N., Mourlas C., Samaras G., New fundamental profiling characteristics for designing adaptive Web-based educational systems, Proceeding of the IADIS International Conference on Cognition and Exploratory Learning in Digital Age (CELDA2005), pp. 10-17, (2005); Germanakos P., Mourlas C., Samaras G., Considering the new user requirements for apt mobile Internet services delivery, Proceedings of the IADIS International Conference on WWW/Internet 2005, (2005); Giaglis G.M., Kourouthanassis P., Tsamakos A., Towards a classification framework for mobile location services, Mobile Commerce: Technology, Theory, and Applications, (2003); Haig M., Mobile marketing: The message revolution, (2002); Heman R.D., Renz D.O., Theses on nonprofit organisational effectiveness, Nonprofit and Voluntary Sector Quarterly, 28, 2, pp. 107-126, (1999); Hesmondhalgh D., The cultural industries, (2002); Kleijnen M., Wetzels M., de Ruyter K., Consumer acceptance of wireless finance, Journal of Financial Services Marketing, 8, 3, pp. 206-217, (2004); Knell S., The shape of things to come: Museums in the technological landscape, Museum and Society, 1, 3, pp. 132-146, (2003); Mahatanankoon P., Wen J.H., Lim B., Consumer-based m-commerce: Exploring consumer perception of mobile applications, Computer Standards and Interfaces, 27, pp. 347-357, (2005); O'Connor J., Galvin E., Marketing in the digital age, (2001); Panayiotou C., Samaras G., Mobile user personalization with dynamic profiles: Time and activity, Proceedings of On the Move to Meaningful Internet Systems 2006: OTM 2006 Workshops (PerSys 2006), PART II, pp. 1295-1304, (2006); Panayiotou C., Samaras G., mPERSONA: Personalized portals for the wireless user: An agent approach, Mobile Networks and Applications (MONET), 9, 6, (2004); Paavilainen J., Mobile business strategies: Understanding the technologies and opportunities, (2002); Postma P., The new marketing era: Marketing to the imagination in a technology-driven world, (1999); Stafford M.R., Faber R.J., Advertising, promotion and new media, (2004); A handbook of cultural economics, (2003); Tsang M.M., Ho S.-C., Liang T.-P., Consumer attitudes toward mobile advertising: An empirical study, International Journal of Electronic Commerce, 8, 3, pp. 65-78, (2004); Turban E., King D., Lee J., Warkentin M., Chung H.M., Electronic commerce 2002: A managerial perspective, (2002); Wang J., Lin J., Are personalization systems really personal? - Effects of conformity in reducing information overload, Proceedings of the 36th Hawaii International Conference on Systems Sciences (HICSS'03), (2003)",null,null,"IGI Publishing",{"$nulls":5},1.5392937E7,null,null,null,"English","J. Electr. Commer. Organ.","Article","Final",null,"Scopus","2-s2.0-56649124531"]
["Pentina I.; Hasty R.W.","Pentina, Iryna (16239928500); Hasty, Ronald W. (57223378468)","16239928500; 57223378468","Effects of multichannel coordination and e-commerce outsourcing on online retail performance",2009.0,"Journal of Marketing Channels",16.0,4.0,null,359.0,374.0,15.0,40.0,"10.1080/10466690903188021","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84991475686&doi=10.1080%2f10466690903188021&partnerID=40&md5=1b8fb40452492ab2ed363f50afd89bb3","College of Business Administration, The University of Toledo, Toledo, OH, United States; College of Business, University of North Texas, Denton, TX, United States","Pentina I., College of Business Administration, The University of Toledo, Toledo, OH, United States; Hasty R.W., College of Business, University of North Texas, Denton, TX, United States","This article assesses the role of multichannel coordination strategy in impacting online performance, and the need for E-commerce functions outsourcing at the initial stages of multichannel integration. Our findings indicate that a higher degree of interchannel coordination increases retailers’ online sales. The article also concludes that integrated retailers that outsource more E-commerce functions, such as Web site hosting, site design, content development, order processing, E-mail marketing, Web performance monitoring, and E-logistics, do not show higher online sales performance than those who develop them in-house. Managerial implications of these findings are proposed, and directions for future research are outlined. Based on prior conceptual research, the article develops and empirically tests the construct of multichannel coordination. © 2009, Taylor & Francis Group, LLC. All rights reserved.","E-commerce outsourcing; Multichannel coordination; Multichannel retailing; Sales performance",{"$nulls":7},"Clicks to Customers: The Real ROI in B2C Ecommerce, (2006); One-Tenth of the world’s Population Shopping Online, (2005); Ansari A., Mela C., Neslin S., Customer Channel Migration, Working Paper Series No. 13, (2005); Barney J., Firm resources and sustained competitive advantage, Journal of Management, 17, 1, pp. 99-120, (1991); Bendoly E., Blocher J.D., Bretthauer K.M., Krishnan S., Vankataramanan M.A., Online/in-store integration and customer retention, Journal of Service Research, 7, 4, pp. 313-327, (2005); Berger P.D., Lee J., Weinberg B.D., Optimal cooperative advertising integration strategy for organization adding a direct online channel, Journal of the Operational Research Society, 57, pp. 920-927, (2005); Burke R., Technology and the customer interface: What consumers want in the physical and virtual store, Journal of the Academy of Marketing Science, 30, 4, pp. 411-432, (2002); Bush A.J., Bush V., Harris S., Advertiser perceptions of the Internet as a promotions tool, Journal of Advertising Research, 38, 2, pp. 17-27, (1998); Cao Y., Zhao H., Evaluations of E-tailers’ delivery fulfillment: Implications of firm characteristics and buyer heterogeneity, Journal of Service Research, 6, 4, pp. 347-360, (2004); Chung A., Jackson T., Laseter T., Why Outsourcing is In, (2007); Coase R.H., The nature of the firm, Economica, 4, pp. 386-405, (1937); You know what it stands for, but you may not know what it means, Marketing News, 41, 15, (2007); Online Ad Spend Growth is Historic, (2007); Goersch D., Multi-channel integration and its implications for retail websites, Proceedings of the 10Th European Conference on Information Systems, pp. 748-758, (2002); Gulati R., Garino J., Get the right mix of bricks and clicks, Harvard Business Review, 78, 3, pp. 107-114, (2000); Harrington L.H., What 3PLs bring to the E-tailing party, Material Handling Management, 55, 12, pp. 77-85, (2000); Hunt S.D., A General Theory of Competition: Resources, Competences, Productivity, Economic Growth, (2000); Top 500 Guide: Profiles and Statistics of America’s 500 Largest Retail Websites Ranked by Annual Sales, (2006); Top 500 Guide: Profiles and Statistics of America’s 500 Largest Retail Websites Ranked by Annual Sales, (2007); Johnson C., Getting multichannel retailing right, Forrester Research, (2004); Montoya-Weiss M.M., Voss G.B., Grewal D., Determinants of online channel use and overall satisfaction with a relational, multichannel service provider, Journal of the Academy of Marketing Science, 31, 4, pp. 448-458, (2003); Neslin S.A., Grewal D., Leghorn R., Shankar V., Teerling M.L., Thimas J.S., Verhoef P.C., Challenges and opportunities in multichannel customer management, Journal of Service Research, 9, 2, pp. 95-112, (2006); Perry M.L., Bodkin C.D., Fortune 500 manufacturer Web sites: Innovative marketing strategies or cyberbrochures?, Industrial Marketing Management, 31, 2, pp. 133-144, (2002); Philport J.C., Arbittier J., Advertising: Brand communications styles in established media and the Internet, Journal of Advertising Research, 37, 2, pp. 68-76, (1997); Porter M.E., Strategy and the Internet, Harvard Business Review, 79, 3, pp. 62-78, (2001); Rangaswamy A., Van Bruggen G.H., Opportunities and challenges in multichannel marketing: An introduction to the special issue, Journal of Interactive Marketing, 19, 2, pp. 5-11, (2005); Reed R., Defillippi R.J., Causal ambiguity, barriers to imitation, and sustainable competitive advantage, Academy of Management Review, 15, 1, pp. 88-102, (1990); Twenty trends for 2010: Retailing in the age of uncertainty, (2003); Rindfleisch A., Heide J.B., Transaction cost analysis: Past, present, and future applications, Journal of Marketing, 61, 4, pp. 30-54, (1997); Statistics: US Online Shoppers, (2006); Steinfield C., Mahler A., Bauer J., Electronic commerce and the local merchant: Opportunities for synergy between physical and web presence, Electronic Markets, 9, 2, pp. 51-57, (1999); Stump R.L., Heide J.B., Controlling supplier opportunism in industrial relationships, Journal of Marketing Research, 33, 4, pp. 431-441, (1996); Teece D.J., Pisano G., Shuen A., Dynamic capabilities and strategic management, Strategic Management Journal, 18, 7, pp. 509-533, (1997); Teerling M.L., Van Nierop J.E.M., Leeflang P.S.H., Huizingh K.R.E., The impact of an informational Web site on offline consumer purchases, Working Paper, (2006); Varadarajan P.R., Yadav M.S., Marketing strategy and the Internet: An organizing framework, Journal of the Academy of Marketing Science, 30, 4, pp. 296-312, (2002); Vishwanath V., Mulvin G., Multi-channels: The real winners in the B2C Internet wars, Business Strategy Review, 12, 1, pp. 25-33, (2001); Williamson O.E., Markets and hierarchies, Analysis and Antitrust Implications: A Study in the Economics of Internal Organization, (1975); Williamson O.E., The economics of organization: The transaction cost approach, American Journal of Sociology, 87, 3, pp. 548-577, (1981); Williamson O.E., The Economic Institutions of Capitalism: Firms, Markets, Relational Contracting, (1985); Zettelmeyer F., Expanding to the Internet: Pricing and communications strategies when firms compete on multiple channels, Journal of Marketing Research, 37, 3, pp. 292-308, (2000)","I. Pentina; Department of Marketing & International Business, College of Business Administration, The University of Toledo, Toledo, OH, 43606-3390, 2801 W. Bancroft St, United States; email: iryna.pentina@utoledo.edu",{"$nulls":7},"1046669X",null,null,null,"English","J. Mark. Channels","Article","Final",null,"Scopus","2-s2.0-84991475686"]
["Silahtaroǧlu G.","Silahtaroǧlu, Gökhan (15119651200)",1.51196512E10,"International multi-user electronic data interchange for logistics sector",2007.0,"WSEAS Transactions on Information Science and Applications",4.0,2.0,null,428.0,431.0,3.0,0.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-33847696098&partnerID=40&md5=0d9644deef623f9c7c48505739dd123c","Maths and Computing Department, Beykent University, Sisli, Istanbul, Turkey","Silahtaroǧlu G., Maths and Computing Department, Beykent University, Sisli, Istanbul, Turkey","A great deal of firms benefit from the facilities, services and conveniences of the internet however\" logistics sector does not use all they can in this new world. Like well known ODETTE and EDIFACT some new standards may be developed just for logistics and transportation firms and for their clients as well. This is quite easy and useful with today's developed internet, DSL, TCP/IP amenities. In this paper, a peer to peer technology structured, some sample standards have been proposed to be adapted by logistics and client firm globally and possible advantages of the suggested systems are discussed.","E-commerce; EDI; Logistics; Market; Peer to peer; Transportation","DSL; Electronic commerce; Internet protocols; Multiuser detection; Societies and institutions; Logistics sector; Transportation firms; Electronic data interchange",{"$nulls":6},"Bakos Y.J., Reducing buyer search costs implications for electronic market place, Management Science, 43, 12, pp. 1676-1692, (1997); Silahtaroglu G., Internet as a Way of International Transportation and Logistic Market - International Multi-user Electronic Data Interchange, Proceedings of 5th WSEAS Int. Conf. on E-ACTIVITIES (E-ACTIVITIES '06), (2006); Rahman Z., E-commerce solution for services, European Business Review, 16, 6, pp. 564-576, (2004); Singh M., Costabile A., Paull S., E-commerce and customer relationship management (eCRM), E-Commerce Infusions: Strategies and Challenges, pp. 95-108, (2001); Singh M., E-services and their role in B2C e-commerce, Managing Service Quality, 12, 6, pp. 434-446, (2002); Whiteley D., E Commerce: Strategy, Technologies and Applications, (2000); Riel A.C.R., Lilijander V., Jurrinies P., Exploring Consumer evaluations of e-services: A portal site, International Journal of Service Industry Management, 12, 4, pp. 359-377, (2001); Hanfield B.R., Nichols Jr. E.L., Introduction to Supply Chain Management, (1999); Iyer K.N.S., Germain R., Frankwick G.L., Supply chain B2B e-commerce and time-based delivery performance, International Journal of Physical Distribution & Logistics Management, 34, 8, pp. 645-661, (2004); Hohpe G., Woolf B., Enterprise Integration Patterns: Designing, Building, and Deploying Messaging Solutions, (2003); Galbraith J.R., Competing With Flexible Lateral Organizations, (1994); (2005); Richardson H., How much should you outsource?, Transportation and Distribution, (1994); Cooper J., Browne M., Peters M., European Logistics: Markets, Management and Strategy, (1991); Schary P., Skjott-Larsen T., Managing the Global Supply Chain, (2001); Aktas E., Ulengin F., Outsourcing logistics activities in Turkey, The Journal of Enterprise Information Management, 18, 3, pp. 316-329, (2005); Sivadas E., Grewal R., Kellaris J., The Internet as a micro marketing tool targeting consumers through preference revealed in music newsgroup usage, Journal of Business Search, 3, 41, pp. 179-186, (1998)","G. Silahtaroǧlu; Maths and Computing Department, Beykent University, Sisli, Istanbul, Turkey; email: gsilah@beykent.edu.tr",{"$nulls":7},1.7900832E7,null,null,null,"English","WSEAS Trans. Inf. Sci. Appl.","Article","Final",null,"Scopus","2-s2.0-33847696098"]
["Hung J.C.; Wang Y.-B.; Deng L.Y.; Yang S.; Huang C.-H.","Hung, Jason C. (7201963626); Wang, Yu-Bing (36195278500); Deng, Lawrence Y. (7202007484); Yang, Schummi (36195070400); Huang, Chun-Hong (36021290100)","7201963626; 36195278500; 7202007484; 36195070400; 36021290100","A framework of online chain store integrated with personalised recommendation for e-commerce",2010.0,"International Journal of Wireless and Mobile Computing",4.0,3.0,null,228.0,239.0,11.0,1.0,"10.1504/IJWMC.2010.034222","https://www.scopus.com/inward/record.uri?eid=2-s2.0-77955102317&doi=10.1504%2fIJWMC.2010.034222&partnerID=40&md5=bcc31e373e64370e3d8c060628f59cf7","Department of Information Management, Overseas Chinese University, Taichung 407, Taiwan; Department of Business Administration, University of Northern Virginia, Northern Virginia, VA 22003, United States; Department of Computer Science and Information Engineering, St. John's University, Taipei 25135, Taiwan; Department of Information Management, China University of Technology, Hsing-Chu 30301, Taiwan; Department of Computer Information and Network Engineering, Lunghwa University of Science and Technology, Taoyuan County 33306, Taiwan","Hung J.C., Department of Information Management, Overseas Chinese University, Taichung 407, Taiwan; Wang Y.-B., Department of Business Administration, University of Northern Virginia, Northern Virginia, VA 22003, United States; Deng L.Y., Department of Computer Science and Information Engineering, St. John's University, Taipei 25135, Taiwan; Yang S., Department of Information Management, China University of Technology, Hsing-Chu 30301, Taiwan; Huang C.-H., Department of Computer Information and Network Engineering, Lunghwa University of Science and Technology, Taoyuan County 33306, Taiwan","With the rapid growth of the internet and communication technologies, many real world activities were applied on the internet. We proposed the nomadic media server to achieve the maximum use of network bandwidth. The mobile server will play an important role in the future virtual society. Chain store over the internet is a rare management model in electronic commerce. In this paper, we construct many chain stores via using nomadic media server. Besides, online merchants must know what customers want and make them buying something from their sites, so recommendation process becomes an important strategy for the merchants. We propose a recommendation system for the e-commerce portal, which will help merchants to make suitable business decision and delivery personal information to the customers. © 2010 Inderscience Enterprises Ltd.","Broadband communication; Chain store; EC; Electronic commerce; Nomadic media server; Recommendation; Virtual society","Computer science; Mobile computing; Broadband Communication; Communication technologies; Media servers; Personal information; Personalised recommendations; Real-world activities; Recommendation; Virtual societies; Electronic commerce",{"$nulls":6},"Balabanovic M., Shoham Y., Fab: Content-based collaborative recommendation, Communication of the ACM, 40, 3, pp. 64-72, (1997); Charas P., Peer-to-peer mobile network architecture, Proceedings of the First International Conference on Peer-to-Peer Computing, pp. 55-61, (2002); Gordijn J., Akkermans H., Designing and evaluating e-business models, IEEE Intelligent Systems, 16, 4, pp. 11-17, (2001); Resnick P., Varian H.R., Recommendation system, Communication of the ACM, 40, 3, pp. 56-58, (1997); Shih T.K., Lu Y-C., Hung J.C., The design and implementation of a mobile distributed web server system, Proceedings of National Computer Symposium, 2001, pp. 35-42, (2001); Warkentin M., Sugumaran V., Bapna V., Intelligent Agents for Electronic Commerce: Trends and Future Impact on Business Models and Markets, (2001)","J. C. Hung; Department of Information Management, Overseas Chinese University, Taichung 407, Taiwan; email: jhung@ocu.edu.tw",null,"Inderscience Publishers",{"$nulls":5},1.7411084E7,null,null,null,"English","Int. J. Wireless Mobile Comput.","Article","Final",null,"Scopus","2-s2.0-77955102317"]
["Lunce S.E.; Lunce L.M.; Kawai Y.; Maniam B.","Lunce, Stephen E. (6602659638); Lunce, Leslie M. (36488167500); Kawai, Yoko (36488113800); Maniam, Balasundrum (6603360359)","6602659638; 36488167500; 36488113800; 6603360359","Success and failure of pure-play organizations: Webvan versus Peapod, a comparative analysis",2006.0,"Industrial Management and Data Systems",106.0,9.0,null,1344.0,1358.0,14.0,15.0,"10.1108/02635570610712618","https://www.scopus.com/inward/record.uri?eid=2-s2.0-33749993027&doi=10.1108%2f02635570610712618&partnerID=40&md5=9d49f5e85ea8b9bc97f926dbddf4d7ff","MIS Department, Dillard College of Business Administration, Midwestern State University, Wichita Falls, TX, United States; Computer Information Technology Division, North Lake College of the Dallas, Irving, TX, County Community College District, United States; Department of General Business and Finance, Sam Houston State University, Huntsville, TX, United States","Lunce S.E., MIS Department, Dillard College of Business Administration, Midwestern State University, Wichita Falls, TX, United States; Lunce L.M., Computer Information Technology Division, North Lake College of the Dallas, Irving, TX, County Community College District, United States; Kawai Y., MIS Department, Dillard College of Business Administration, Midwestern State University, Wichita Falls, TX, United States; Maniam B., Department of General Business and Finance, Sam Houston State University, Huntsville, TX, United States","Purpose: The purpose of this study is a comparative analysis of two electronic grocers, one success and one failure, in order to attempt to identify the critical success factors that contributed to their different performances. Design/methodology/approach: Four aspects of each company's operations are explored and compared in this side-by-side case study. The foci of this study are strategic management, logistical infrastructure, information technology deployments, and marketing strategies. Findings: The success of Peapod was the result, in general, of application of good strategy and knowledge about the opportunities provided in e-commerce. Webvan's failure, in general, was attributable to the design of its logistics system, the misunderstanding of the capabilities of information technology, and ineffective marketing. Research limitations/implications: This study investigates only two online grocers, and the lessons learned in this comparative case study may not be applicable to other types of online business. Practical implications: This paper provides insights into successful retail e-commerce operations through the comparison of successful and unsuccessful firms in a specific business. From the analysis, businesses and individuals who are considering the future of e-commerce for their enterprise should better understand the factors that contribute to success and failure in a pure-play environment. Originality/value: Several studies have investigated how internet businesses function, and how the customers of online businesses differ from traditional business customers. Some studies have offered comparisons of differing levels of performance within a specific e-business; however, this report investigates the reasons for the success and failure through its comparative analysis of specific managerial activities. © Emerald Group Publishing Limited.","Electronic-commerce; Internet; Online operations; Retail management; Strategic management","Electronic commerce; Information technology; Logistics; Marketing; Online systems; Societies and institutions; Strategic planning; Online business; Online grocers; Strategic management; Competitive intelligence",{"$nulls":6},"Alsop S., The tragedy of Webvan, Fortune, 144, 3, (2001); Andelin M., Home service concept-technology, logistics and business models, VTT Tiedotteota - Research Notes, 2226, (2003); Anders G., Will net grocery shopping ever take off, Wall Street Journal Online, (1999); Caltagirone J.A., Peapod's virtual supermarket, Supply Chain Management, 4, 1, pp. 44-51, (2000); Cecil M., Webvan drives toward no-man's land, Mergers & Acquisitions Report, 14, 31, pp. 1-4, (2001); Farmer M.A., Webvan Delivers its Last Word: Bankruptcy, (2001); Flavian C., Guinaliu M., Consumer trust, perceived security and privacy policy - Three basic elements of loyalty to a web site, Industrial Management & Data Systems, 106, 5, pp. 601-620, (2006); Fox B., For Peapod, fulfillment is the key to success, Chain Store Age Executive with Shopping Center Age, 70, 10, pp. 33-35, (1994); Grabarek B., Peapod works to strike a balance, Direct Newsline, pp. 12-19, (2004); Greene J., On the Webvan wagon, Materials Management in Health Care, 11, 3, pp. 8-9, (2002); Hayes T., Keskinocak P., Malcome De Lopez V., Strategies and challenges of internet grocery retailing logistics, Applications of Supply Chain Management and E-commerce Research in Industry, (2004); Heun C.T., Delivery, anyone?, InformationWeek, 846, pp. 22-25, (2001); Himelstein L., Can you sell groceries like books?, BusinessWeek Online, (1999); Hsu M., Chiu C., Ju T., Determinants of continued use of the WWW: An integration of two theoretical models, Industrial Management & Data Systems, 104, 9, pp. 766-775, (2004); Kuo H., Hwang S., Wang E.M., Evaluation research of information and supporting interface in electronic commerce web sites, Industrial Management & Data Systems, 104, 9, pp. 712-721, (2004); Liang T., Lin C., Chen D., Effects of electronic commerce models and industrial characteristics on firm performance, Industrial Management & Data Systems, 104, 7, pp. 538-545, (2004); Lofstock J., Peapod takes control, Convenience Store News, 37, 11, (2001); Mark R., Peapod bags streamline's DC metro operations, DC.internet.com, (2000); Morganosky M.A., Cude B.J., Consumer demand for online food retailing: Is it really a supply side issue?, International Journal of Retail & Distribution Management, 30, 10, pp. 451-458, (2002); Ogawara S., Chen J.C.H., Zhang Q., Internet grocery business in Japan: Current business models and future trends, Industrial Management & Data Systems, 103, 9, pp. 727-735, (2003); Peapod, (2005); Platoni K., The Last Mile, (2001); Punakivi M., Tanskanen K., Increasing the cost efficiency of e-fulfillment using shared reception boxes, International Journal of Retail & Distribution Management, 30, 10, pp. 498-507, (2002); Punakivi M., Yrjola H., Holmstrom J., Solving the last mile issue: Reception box or deliversy box?, International Journal of Physical Distribution & Logistics Management, 31, 6, pp. 427-439, (2001); Ring L.J., Tigert D.J., Viewpoint: The decline and fall of internet grocery retailers, International Journal of Retail & Distribution Management, 29, 67, pp. 266-273, (2001); Rizzo T., The death of Webvan, Internet World, 7, 15, pp. 4-7, (2001); Rubinstein E., Peapod picks, delivers groceries ordered by PC, Discount Store News, 34, 18, pp. 99-101, (1995); Sandoval G., Webvan bags HomeGrocer for $1.2 billion, CNET news.com, (2000); Sandoval G., Webvan hikes delivery fees, CNET news.com, (2001); Scheraga D., Spoiled groceries, Chain Store Age, (2001); So W.C.M., Wong T.N.D., Sculli D., Factors affecting intentions to purchase via the internet, Industrial Management & Data Systems, 105, 9, pp. 1225-1244, (2005); Turban E., Electronic Commerce: A Managerial Prospective, (2004); Cao M., Zhang Q., Seydel J., B2C e-commerce web site quality: An empirical examination, Industrial Management & Data Systems, 106, 5, pp. 645-661, (2006); Huang E.Y., Is revamping your website worthwhile?, Industrial Management & Data Systems, 105, 6, pp. 737-751, (2005)","S.E. Lunce; MIS Department, Dillard College of Business Administration, Midwestern State University, Wichita Falls, TX, United States; email: stephen.lunce@mwsu.edu",{"$nulls":7},2635577.0,null,"IMDSD",null,"English","Ind Manage Data Sys","Article","Final",null,"Scopus","2-s2.0-33749993027"]
["Kim D.; Ow T.T.; Jun M.","Kim, Daesoo (55922266200); Ow, Terence T. (6507703410); Jun, Minjoon (7006544861)","55922266200; 6507703410; 7006544861","SME strategies: An assessment of high vs. low performers",2008.0,"Communications of the ACM",51.0,11.0,null,113.0,117.0,4.0,13.0,"10.1145/1400214.1400237","https://www.scopus.com/inward/record.uri?eid=2-s2.0-55149089524&doi=10.1145%2f1400214.1400237&partnerID=40&md5=28cb83c92e74a32814b61ad7c70c2566","Department of Logistics Service and Operations Management, Business School; Institute for Business Research and Education, Korea University, Seoul, South Korea; Center for Supply Chain Management, College of Business Administration, Marquette University, Milwaukee, WI, United States; Department of Information Technology, College of Business Administration, Marquette University, Milwaukee, WI, United States; Department of Production and Operations Management, College of Business, New Mexico State University, Las Cruces, NM, United States","Kim D., Department of Logistics Service and Operations Management, Business School, Institute for Business Research and Education, Korea University, Seoul, South Korea, Center for Supply Chain Management, College of Business Administration, Marquette University, Milwaukee, WI, United States; Ow T.T., Department of Information Technology, College of Business Administration, Marquette University, Milwaukee, WI, United States; Jun M., Department of Production and Operations Management, College of Business, New Mexico State University, Las Cruces, NM, United States","Some of the significant factors that need to be considered by small-medium sized enterprises (SMEs) to improve their business by using e-commerce, are discussed. Internet, inter-organization information system, e-commerce, e-business, and integrated supply chain management (SCM) can help SMEs to reduce their logistics and administrative costs. The SMEs need to implement e-business and SCM strategies to improve their human resources and organizational capabilities. SMEs need to understand their industry characteristics to enhance their supply chain and to remain competitive. SMEs need to improve their supply chain capabilities and planning to respond against any change in business environments. SMEs need to re-evaluate their strategic, operational, technological, and financial investment planning.",null,"Commerce; Electric energy storage; Electronic commerce; Investments; Supply chains; Administrative costs; Business environments; E businesses; E commerces; Financial investments; Human resources; Integrated supply chain managements; Medium sized enterprises; Organizational capabilities; Significant factors; Supply chain management",{"$nulls":6},"Barney J.B., Gaining and Sustaining Competitive Advantage, (2002); Bourgeois III L.J., Strategy and environment: A conceptual integration, Academy of Management Review, 5, 5, pp. 25-39, (1980); Carr C.L., Reciprocity: The golden rule of IS-user service relationship quality and cooperation, Comm. of the ACM, 49, 6, pp. 77-83, (2000); Christopher M., Logistics and Supply Chain Management, (1902); Hayes R.H., Wheelwright S.O., Restoring Our Competitive Edge: Competing through Manufacturing, (1984); Kaplan R.S., Norton D.P., Using the balanced scorecard as a strategic management system, Harvard Business Review, pp. 75-85, (1996); United States Department of Commerce e-stats; Ward P.T., Duray R., Manufacturing strategy in context: Environment, competitive strategy and manufacturing strategy, J. of Operations Management, 18, pp. 123-138, (2000); Wondergem J., Supply chain operations reference-model includes all elements of demand satisfaction, Global Purchasing and Supply Chain Strategics, pp. 27-30, (2001)","D. Kim; Department of Logistics Service and Operations Management, Business School, North Korea; email: kimd@korea.ac.kr",{"$nulls":7},1.5577317E7,null,"CACMA",null,"English","Commun ACM","Article","Final",null,"Scopus","2-s2.0-55149089524"]
["Etzion H.; Pinker E.; Seidmann A.","Etzion, Hila (12790609400); Pinker, Edieal (6603181996); Seidmann, Abraham (35615751100)","12790609400; 6603181996; 35615751100","Analyzing the simultaneous use of auctions and posted prices for online selling",2006.0,"Manufacturing and Service Operations Management",8.0,1.0,null,68.0,91.0,23.0,57.0,"10.1287/msom.1060.0101","https://www.scopus.com/inward/record.uri?eid=2-s2.0-33645139078&doi=10.1287%2fmsom.1060.0101&partnerID=40&md5=295cf2057362c91dbc1aca01caeffc8e","Stephen M. Ross School of Business, University of Michigan, Ann Arbor, MI 48109, United States; W. E. Simon School of Business Administration, University of Rochester, Rochester, NY 14618, United States","Etzion H., Stephen M. Ross School of Business, University of Michigan, Ann Arbor, MI 48109, United States; Pinker E., W. E. Simon School of Business Administration, University of Rochester, Rochester, NY 14618, United States; Seidmann A., W. E. Simon School of Business Administration, University of Rochester, Rochester, NY 14618, United States","Many firms in the business-to-consumer market sell identical products online using auctions and posted prices at the same time. In this paper, we develop and analyze a model of the key trade-offs sellers face in such a dual-channel setting built around the optimal choice of three design parameters: the posted price, the auction lot size, and the auction duration. Our results show how a monopolist seller can increase his revenues by offering auctions and a fixed price concurrently, and we identify when either a posted price only or a dual-channel strategy is optimal for the seller. We model consumer choice of channels, and thus market segmentation, and find a unique (symmetric) auction-participation equilibrium exists in which consumers who value the item for more than its posted price use a threshold policy to choose between the two channels. The threshold defines an upper bound on the remaining time of the auction. We explain how optimizing the design parameters enables the seller to segment the market so that the two channels reinforce each other and cannibalization is mitigated. Our findings also demonstrate that there are two dominant auction design strategies in this setting: one-unit auctions that tend to be short and long multiunit auctions. The optimal strategy for the seller depends on the consumer arrival rate and the disutility of delivery delay incurred by high-valuation consumers. In either case, the optimal design of the dual channel can significantly outperform a single posted-price channel. We show even greater benefits over a naive approach to managing the two channels that optimizes each independently. Our results suggest that unless firms jointly manage these online channels, they may find that adding auctions actually reduces their revenues. © 2006 INFORMS.","E-commerce; Marketing; Online auctions","Costs; Electronic commerce; Industrial management; Online systems; Parameter estimation; Design parameters; Online auctions; Online selling; Industrial economics",{"$nulls":6},"Arnold M., Lippman S., Selecting a selling institution: Auctions versus sequential, Econom. Inquiry, 33, 1, pp. 1-23, (1995); Bajari P., Hortacsu A., The winner's curse, reserve prices, and endogenous entry: Empirical insights from eBay auctions, RAND J. Econom., 34, 2, pp. 329-355, (2003); Budish E.B., Takeyama L.N., Buy prices in online auctions: Irrationality on the Internet?, Econom, Lett., 72, pp. 325-333, (2001); Carare O., Rothkopf M., Slow Dutch auctions, RUTCOR Res. Rep., 42, 2001, (2001); De Vany A., Institutions for stochastic markets, J. Institutional and Theoret. Econom., 143, pp. 91-103, (1987); Ehrman C., Peters M., Sequential selling mechanisms, Econom. Theory, 4, pp. 237-253, (1994); Epstein L.G., Peters M., A revelation principle for competing mechanisms, J. Econom. Theory, 88, pp. 119-160, (1999); Gallien J., Dynamic mechanism design for online commerce, Working Paper, (2002); Gibbons R., Game Theory for Applied Economists, (1992); Hann I., Terwiesch C., Measuring the frictional costs of online transactions: The case of a name-your-own-price channel, Management Sci., 43, 11, pp. 1563-1579, (2003); Harris M., Raviv A., Allocation mechanisms and the design of auctions, Econometrica, 49, 6, pp. 1477-1499, (1981); Harstad R.M., Alternative common-value auction procedures: Revenue comparisons with free entry, J. Political Econom., 98, 2, pp. 421-430, (1990); Hidvegi Z., Wang W., Whinston A.B., Buy-price English auction, Working Paper, (2002); Klemperer P., Auction theory: A guide to the literature, J. Econom. Surveys, 13, 3, pp. 227-286, (1999); Kultti K., Equivalence of auctions and posted prices, Working Paper, (1997); Lucking-Reiley D., Using field experiments to test equivalence between auction formats: Magic on the Internet, Amer. Econom. Rev., 89, 5, pp. 1063-1081, (1999); Mas-Colell A., Whinston M.D., Green J.R., Microeconomic Theory, (1995); Maskin E., Riley J., Optimal multi-unit auctions, The Economics of Missing Markets, Information and Games, pp. 312-335, (1989); McAfee R., McMillan J., Auctions and bidding, J. Econom. Literature, 25, pp. 699-738, (1987); McAfee R., McMillan J., Auctions with a stochastic number of bidders, J. Econom. Theory, 43, pp. 1-19, (1987); Milgrom P.R., Auction theory, Advances in Economic Theory, pp. 1-32, (1987); Peters M., Competition among mechanism designers in a common value environment, Rev. Econom. Design, 4, pp. 273-292, (1999); Pinker E., Seidmann A., Vakrat Y., The design of online auctions: Business issues and current research, Management Sci., 49, 11, pp. 1457-1484, (2003); Reynolds S., Wooders J., Auctions with a buy price, Working Paper, (2003); Riley J., Zeckhauser R., Optimal selling strategies: When to haggle, when to hold firm, Quart. J. Econom., 98, pp. 267-289, (1983); Roth A.E., Ockenfels A., Last-minute bidding and the rules for ending second-price auctions: Evidence from eBay and Amazon auctions on the Internet, Amer. Econom. Rev., 92, 4, pp. 1093-1103, (2002); Vakrat Y., Seidmann A., Can online auctions beat online catalogs?, Proc. 20th Internat. Conf. Inform. Systems (ICIS), (1999); Van Ryzin G., Vulcano G., Optimal auctioning and ordering in an infinite horizon inventory-pricing system, Oper. Res., 52, 3, pp. 346-367, (2004); Wang R., Auctions versus posted-price selling, Amer. Econom. Rev., 83, 4, pp. 838-851, (1993)","H. Etzion; Stephen M. Ross School of Business, University of Michigan, Ann Arbor, MI 48109, United States; email: etzionh@bus.umich.edu",{"$nulls":7},1.5265498E7,null,"MSOMF",null,"English","Manuf. Serv. Oper. Manage.","Article","Final",null,"Scopus","2-s2.0-33645139078"]
["Moreno M.","Moreno, Margarita (8331899600)",8.3318996E9,"Streamlining interlibrary loan and document delivery workflows: Tools, techniques, and outcomes",2012.0,"Interlending and Document Supply",40.0,1.0,null,31.0,36.0,5.0,5.0,"10.1108/02641611211214260","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84857620127&doi=10.1108%2f02641611211214260&partnerID=40&md5=4d76bf34dfe6e4bc53f21ad40147215a","Document Supply Service, National Library of Australia, Canberra, Australia","Moreno M., Document Supply Service, National Library of Australia, Canberra, Australia","Purpose: This paper aims to describe a review of interlending and document delivery work processes at the National Library of Australia, the purpose of which was to develop a new integrated approach to interlending and document delivery services and to improve turnaround times for users by reducing administrative functions and improving request management processes. Design/methodology/approach: This paper provides a brief overview of business process modeling notation (BPMN) and its use in the National Library to evaluate workflows, reports on implementation of the project's recommendations, and highlights lessons learned. Findings: Good communication and teamwork were critical to the project's success. Use of the BPMN enabled stakeholders to retain objectivity when evaluating existing workflows. The new workflows and processes resulted in demonstrably greater customer satisfaction. Originality/value: Discussions of Relais ILL customization to streamline workflows and facilitate e-commerce are especially useful. The paper describes library application of both BPMN and Prince 2 project management methodology. © Emerald Group Publishing Limited.","Australia; Document delivery; Interlending; National libraries; Process improvement; Relais; Workflow analysis",{"$nulls":7},"Australian Copyright Act 1968, (1968); Guidelines for best practice in interlibrary loan and document delivery, (2007)","M. Moreno; Document Supply Service, National Library of Australia, Canberra, Australia; email: mmoreno@nla.gov.au",{"$nulls":7},2641615.0,null,null,null,"English","Interlending Doc. Supply","Article","Final",null,"Scopus","2-s2.0-84857620127"]
["Uzoka F.-M.E.; Seleka G.G.; Khengere J.","Uzoka, Faith-Michael E. (8712970500); Seleka, Geoffrey G. (14619689500); Khengere, Joseph (36806009700)","8712970500; 14619689500; 36806009700","E-commerce adoption in developing countries: A case analysis of environmental and organisational inhibitors",2007.0,"International Journal of Information Systems and Change Management",2.0,3.0,null,232.0,260.0,28.0,16.0,"10.1504/IJISCM.2007.015598","https://www.scopus.com/inward/record.uri?eid=2-s2.0-66149166639&doi=10.1504%2fIJISCM.2007.015598&partnerID=40&md5=375ac5cd0c6f8d9308eba3856ccb5b00","Information Systems Group, Department of Accounting and Finance, University of Botswana, Gaborone, Botswana; Department of Infrastructure/Systems, Debswana Old Mines, Orapa, Botswana","Uzoka F.-M.E., Information Systems Group, Department of Accounting and Finance, University of Botswana, Gaborone, Botswana; Seleka G.G., Department of Infrastructure/Systems, Debswana Old Mines, Orapa, Botswana; Khengere J., Information Systems Group, Department of Accounting and Finance, University of Botswana, Gaborone, Botswana","A number of studies have been conducted on e-commerce and other technology adoption. However, most of these studies have been conducted in developed countries. Developing countries have been slow in fitting into the global digital market. This study attempts to take a comprehensive look at e-commerce development in a developing country, Botswana, which has a very good and well managed economy. The results of the study show that environmental factors affecting the adoption of e-commerce include the internet marketing factor and customer/logistic factor. Though security factor is an issue, it is not statistically significant because other factors, especially organisational such as management support, information availability and communications impact on the organisation's intention and ability to adopt e-commerce. Firm size and gender also affect the intention to and ability to adopt e-commerce. © 2007, Inderscience Publishers.","Developing countries; E-commerce; E-readiness; Internet; Unified theory of acceptance and use of technology","Developing countries; Internet; Marketing; Developed countries; E-commerce adoption; E-commerce development; E-readiness; Environmental factors; Information availability; Technology adoption; Unified theory of acceptance and use of technology; Electronic commerce",{"$nulls":6},"Aghaunor L., Fotoh X., Factors Affecting Ecommerce Adoption in Nigerian Banks, (2006); Aguila-Obra A.R.D., Padilla-Melendez A., Organizational factors affecting internet technology adoption, Internet Research, 16, 1, pp. 94-110, (2006); Ajzen I., The theory of planned behaviour, Organizational Behavior and Human Decision Process, 1, 50, pp. 179-211, (1991); Akinyokun O.C., Survey of the attitude of people towards computer in Nigeria, Proceedings of the Second International Conference in Science and Technology in Third World Development, (1993); Bagossi R.P., Davis F.D., Warshaw P.R., Development and test of a theory of technological learning and usage, Human Relations, 45, 7, pp. 660-686, (1992); Campbell E.K., Attitudes of Botswana citizens towards immigrants: Signs of xenophobia, International Migration, 41, 4, pp. 71-111, (2003); Cooper R.B., Zmud R.W., Information technology implementation research: A technological diffusion approach, Management Science, 36, 2, pp. 123-139, (1990); Dada D., E-readiness for developing countries: Moving focus from the environment to users, Electronic Journal of Information Systems in Developing Countries, 27, 6, pp. 1-14, (2006); Damanpour F., Organizational innovation: A meta analysis of effects of determinants and moderators, Academy of Management Journal, 34, 3, pp. 555-591, (1991); Davis F.D., Perceived usefulness, perceived ease of use, and user accdeptance of information technology, MIS Quarterly, 13, pp. 319-340, (1989); Driedonks C., Gregor S., Wassenaar A., Heck E.V., Economic and social analysis of the adoption of B2B electronic marketplaces: A case study in the Australian beef industry, International Journal of Electronic Commerce, 9, 3, pp. 49-72, (2005); Elliot R., Boshoff C., The influence of organizational factors in small tourism businesses on success of internet marketing, Management Dynamics, 14, 3, pp. 44-58, (2005); Fife E., Pereira F., Socio-economic and cultural factors affecting adoption of broadband access: A cross-country analysis, 41st European Telecommunications Congress, (2002); Garcia-Murillo M., Institutions and the adoption of electronic commerce in Mexico, Electronic Commerce Research Journal, 4, 3, pp. 201-219, (2004); Hage J., Dewar R., Elite values versus organizational structure in predicting innovation, Administrative Science Quarterly, 18, pp. 279-290, (1973); Hawk S., A comparison of B2C e-commerce in developing countries, Electronic Commerce Research, 4, 3, pp. 181-199, (2004); Ifinedo P., Measuring Africa's e-readiness in the global networked economy: A nine-country data, International Journal of Education and Development using ICT, 1, 1, pp. 53-71, (2005); Kanugo R.P., Cross culture and business practice: Are they coterminous or cross-verging?, Cross Cultural Management, 13, 1, pp. 23-31, (2006); Kaynak E., Tatoglu E., Kula V., An analysis of the factors affecting the adoption of electronic commerce by SMEs, International Marketing Review, 22, 6, pp. 623-640, (2005); Lane M.S., Van Der Vyver G., Delpachitra S., Howard S., An electronic commerce initiative in regional Sri Lanka: The vision for the central province electronic commerce portal, The Electronic Journal on Information Systems in Developing Countries, 16, 1, pp. 1-18, (2004); Lawson R., Alcock C., Cooper J., Burgess L., Factors affecting adoption of electronic commerce technologies by SMEs: An Australian study, The Electronic Journal on Information Systems in Developing Countries, 14, 1, pp. 1-9, (2003); Lee G.-G., Lin H.-F., Pai J.-C., Influence of environmental and organizational factors on the success of internet based systems planning, Internet Research, 15, 5, pp. 527-543, (2005); Cyber crime and punishment, (2000); Molla A., Licker P.S., Perceived e-readiness factors in e-commerce adoption: An empirical investigation in a developing country, International Journal of Electronic Commerce, 10, 1, pp. 83-110, (2005); Munene J.C., Organizational environment in Africa: A factor analysis of critical incidents, Human Relations, 44, pp. 439-458, (1991); Mutula S.M., Brakel P.V., E-readiness of SMEs in the ICT sector in Botswana with respect to information access, The Electronic Library, 24, 3, pp. 402-417, (2006); Nelson M.L., Shaw M.J., Adoption of technology standards in supply chains: A case of adopting rosettanet standards, (2001); Pavlou P.A., Consumer acceptance of electronic commerce: Integrating trust and risk with the technology acceptance model, International Journal of Electronic Commerce, 7, 3, pp. 69-103, (2003); Orlikowski W.J., CASE tools as organizational change: Investigating incremental and radical changes in systems development, MIS Quaterly, 17, 3, pp. 309-340, (1993); Rogers E.M., Diffusion of Innovations, (1995); Shen L., Hawley J., Dickerson K., e-Commerce adoption for supply chain management in U.S apparel manufacturers, Journal of Textile and Apparel Technology and Management, 4, 1, pp. 1-11, (2004); Stanfield M., Grant K., An investigation into issues influencing the use of the internet and electronic commerce among small-medium sized enterprises, Journal of Electronic Commerce Research, 4, 1, pp. 15-33, (2003); Swami B., Seleka G.G., Problems, prospects, and development of e-commerce - case study of southern African development community (SADC), IADIS International Conference e-Commerce, pp. 379-384, (2005); Tarafdar M., Vaidya S.D., Adoption of electronic commerce by organisations in India: Strategic and environment imperatives, The Electronic Journal on Information Systems in Developing Countries, 17, 2, pp. 1-25, (2004); E-Commerce and Development Report, (2001); E-Commerce in Developed Countries Continues on Strong Growth Path, (2003); Unhelkar B., Understanding the impact of cultural issues in global e-business alliances, Fourth International Web Conference, (2003); Uzoka F.M.E., Seleka G.G., Shemi A.P., Infrastructural and behavioural influences on the adoption of e-commerce in developing countries, IST Africa Conference Proceedings, (2006); Venkatesh V., Morris M.G., Davis B., Davis F.D., User acceptance of information technology: Towards a unified view, MIS Quarterly, 27, 3, pp. 425-478, (2003); Watson R.T., Kelly G.G., Galliers R.D., Brancheau J.C., Key issues in information systems management: An international perspective, Journal of Management Information Systems, 13, 4, pp. 91-115, (1997); The Networked Readiness Index Rankings 2003, (2004); Yang K.C.C., Explaining factors affecting the adoption of mobile commerce in Singapore, Telematics and Informatics, 22, pp. 257-277, (2005); Yasin M.M., Czuchry A.J., Gonzales M., Bayes P.E., E-commerce implementation challenges: Small to medium sized versus large organizations, International Journal of Business Information Systems, 1, 3, pp. 256-275, (2006)","F.-M.E. Uzoka; Information Systems Group, Department of Accounting and Finance, University of Botswana, Gaborone, United Kingdom; email: uzokaf@mopipi.ub.bw",null,"Inderscience Publishers",{"$nulls":5},1.4793121E7,null,null,null,"English","Int. J. Inf. Syst. Change Mange.","Article","Final",null,"Scopus","2-s2.0-66149166639"]
["Gheorghe D.","Gheorghe, Dan (57190071418)",5.7190071418E10,"The impact of progress in information and communication technology on distribution and logistic activities",2011.0,"Metalurgia International",16.0,9.0,null,39.0,42.0,3.0,1.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-79960378191&partnerID=40&md5=62c762d56c02c3f8937e021ce845c260","Ovidius University of Constanta, Faculty of Economic Sciences, Romania","Gheorghe D., Ovidius University of Constanta, Faculty of Economic Sciences, Romania","This paper aims at exploring the impact of internet on goods distribution systems and at the same time tries to present the significance of on-line business. Starting from other specialty papers, the objective is to present the significance of processes and concepts used by the science of marketing and especially in one of the components of marketing mix, respectively the distribution and logistics of goods. The application of economic restructuring generated by the information and communication technology is not only a mandatory necessity, but it should be understood that the ignorance of its importance can lead to the disappearance of any company. Information and communication technologies created on-line businesses (dot.com) which restructure the global economy, global markets, entire branches of economic activities, test the conventional economic thinking, redefine the types of businesses and generate changes in labor processes and its relocation. Successful companies shall be those which will fully apply this new technology, in an economy with borderless markets, opened non-stop, where the size of the company matters no more.","Business networks (b-webs); Cybermarketing; E-commerce (sales site); E-store (virtual store); Virtual businesses (on-line or internet)",{"$nulls":7},"Capital magazine - the article \"IT industry restart with state aid, Industria IT se restarteaza cu ajutor de stat; Capital magazine, the article \" How to profit from the explosion of social networks , Cum profita de pe urma exploziei retelelor sociale; Danciu V., Grigorescu A., The quoted magazine and article; John Middleton - Gurus on e-Business, Maiestrii Afacerilor On-line (Gurus on e-Business), (2010); Kevin K., Out of Control, (1994); Purcarea T., Popa V., Impact of e-business on the distribution of consumer goods, Impactul e-business asupra distribuţiei bunurilor de larg consum, The Marketing) - The Marketing - Management Magazine, 3, (2002); Capital magazine, 39, (2007); Capital magazine no. 10/2009, the article \"The main rivals in online trading, ready for confrontation, Principalii rivali din comerţul on-line, gata de înfruntare","D. Gheorghe; Ovidius University of Constanta, Faculty of Economic Sciences, Romania; email: secretariat@traian-sa.com",{"$nulls":7},1.5822214E7,null,null,null,"English","Metal. Int.","Article","Final",null,"Scopus","2-s2.0-79960378191"]
["Xu M.; Ferrand B.; Roberts M.","Xu, Mark (8930788200); Ferrand, Brett (23501491000); Roberts, Martyn (56159420000)","8930788200; 23501491000; 56159420000","The last mile of e-commerce - Unattended delivery from the consumers and eTailers' perspectives",2008.0,"International Journal of Electronic Marketing and Retailing",2.0,1.0,null,20.0,38.0,18.0,37.0,"10.1504/IJEMR.2008.016815","https://www.scopus.com/inward/record.uri?eid=2-s2.0-39149088930&doi=10.1504%2fIJEMR.2008.016815&partnerID=40&md5=ae17e895e3357e31400e7aae36f194a4","Portsmouth Business School, University of Portsmouth, Portsmouth, Hampshire PO1 3DE, United Kingdom","Xu M., Portsmouth Business School, University of Portsmouth, Portsmouth, Hampshire PO1 3DE, United Kingdom; Ferrand B., Portsmouth Business School, University of Portsmouth, Portsmouth, Hampshire PO1 3DE, United Kingdom; Roberts M., Portsmouth Business School, University of Portsmouth, Portsmouth, Hampshire PO1 3DE, United Kingdom","Many products ordered online need to be physically delivered to the consumers. The home delivery logistics in e-commerce, as it is so-called 'the last mile' of online shopping, has been one of the key factors leading to failures of pioneering dot coms, and is becoming a great challenge facing many eTailers. The convenience and time saving benefits of online shopping may not be realised due to the inefficiency or failure of the last mile delivery. This paper examines consumers' experience with the current delivery services, and the perceptions of unattended delivery from both consumers and eTailers' perspectives. It found that UK e-shoppers do not perceive unattended delivery as favourably as reported elsewhere in Europe, but have a great desire for picking up from local collection points. Differences exist on future delivery preferences between eTailers and consumers. The results have many implications for eTailers to develop their home delivery logistics strategy. Copyright © 2008 Inderscience Publishers.","e-commerce; e-shopping; Home delivery; Logistic model; Online tracking; UK survey; Unattended delivery; United Kingdom",{"$nulls":7},"Alreck P.L., Settle R.B., The hurried consumer: Time-saving perceptions of internet and catalogue shopping, The Journal of Database Marketing, 10, 1, pp. 25-35, (2002); Blyth A., Geoghegan A., Delivering the goods - the future of home delivery, Cambridge Consultants, pp. 2-14, (2002); Borrus A., Can a new digital appliance solve home delivery dilemmas, Business Week, 37, 1, pp. 82-83, (2002); Charatan A., Get delivery right, then worry about price survey, e.logistics Magazine, (2001); Consignia, Retailers set to overhaul delivery options to maintain home shopping growth, (2001); Cooke J., Shippers are paying more for \"last mile\" deliveries, Logistics Management, 43, 9, (2004); Dimaria F., Wrap session, IE Solutions, pp. 34-38, (2002); Survey results RAC, (2001); Fillis I., Johannson U., Wagner B., Factors impacting on adoption and development in the smaller firm, International Journal of Enterpreneurial Behaviour & Research, 10, 3, pp. 178-191, (2004); Frazer B., Home delivery is the weakest link in internet chain, Marketing Week, 23, 16, (2000); Gary C., A stage model of ICT adoption in small firms, Workshop in Rimini - Firms and Consumers Facing E-commerce: Strategies to Increase Its Adoption and Usage, (2003); Hong W., Zhu K., Migrating to internet-based e-commerce: Factors affecting e-commerce adoption and migration at the firm level, Information and Management, 43, 2, pp. 204-221, (2006); ISOTrack, The uses of timed delivery slots, ISOTrack 2003, London: ISOTrack, pp. 1-34, (2003); Kau A.K., Tang Y.E., Ghose S., Typology of online shoppers, Journal of Consumer Marketing, 20, 2, pp. 139-156, (2003); Lambert K., UK shops and stores, Shops & Shopping on the Internet - A Practical Guide to Online Stores, Catalogues, Retailers and Shopping Malls, pp. 67-81, (2000); Lee H.L., Whang S., Winning the last mile of e-commerce, MIT Sloan Management Review, pp. 54-62, (2001); Lokken S.L., Cross G.W., Halbert L.K., Lindsey G., Derby C., Stanford C., Comparing online and non-online shoppers, International Journal of Consumer Studies, 27, 2, pp. 126-133, (2003); Lopperi K., Puumalainen K., Kappi J., Technological opportunism and wireless e-business adoption: A case of Finland, International Journal of Technology Marketing, 1, 3, pp. 321-338, (2006); McKinnon A., Tallam D., Unattended delivery to the home: An assessment of the security implications, International Journal of Retail & Distribution Management, 31, 1, pp. 30-41, (2003); Molla A., Licker P.S., eCommerce adoption in developing countries: A model and instrument, Information and Management, 42, 6, pp. 877-899, (2005); Morganosky M.A., Cude B.F., Consumer response to online grocery shopping, International Journal of Retail & Distribution Management, 28, 1, pp. 17-26, (2000); Morganosky M.A., Cude B.F., Consumer demand for online food retailing: Is it really a supply side issue?, International Journal of Retail & Distribution Management, 30, 10, pp. 451-458, (2002); Newton C., Home delivery can make or break of B2C, Supply Chain Management Review, 5, 1, pp. 21-24, (2001); Park M., Regan A., Issues in emerging home delivery operations, (2004); Partington D., Qualitative and quantitative issues in research design, Essential Skills for Management Research, pp. 99-116, (2002); Punakivi M., Tanskanen K., Increasing the cost efficiently of e-fulfilment using shared reception boxes, International Journal of Retail & Distribution Management, 30, 10, pp. 498-507, (2002); Punakivi M., YrjOla H., HolmstrOm J., Solving the last mile issue: Reception box or delivery box?, International Journal of Physical Distribution & Logistics Management, 31, 6, pp. 427-439, (2001); Ring L.F., Tigert D.F., Viewpoint: The decline and fall of internet grocery retailers, International Journal of Retail & Distribution Management, 29, 6, pp. 264-271, (2001); Roberts M., Xu M., Mettos N., Internet shopping: The supermarket model and customer perceptions, Journal of Electronic Commerce in Organisations, 1, 2, pp. 33-44, (2003); Rohm A.J., Swaminathan V., A typology of online shoppers based on shopping motivations, Journal of Business Research, 57, 7, pp. 748-757, (2004); Saarenpaa T., Tiainen T., Empirical samples of IS studies on e-commerce consumers, Proceedings of the IRIS28, (2005); Saunders M., Lewis P., Thornhill A., Collecting primary data using questionnaires, Research Methods for Business Studies, pp. 243-286, (1997); Seybold P., Shopping online at Tesco, Business Line, (2002); Tanskanen K., Yrjola H., Holmstrom F., The way to profitable internet grocery retailing - six lessons learned, International Journal of Retail & Distribution Management, 30, 4, pp. 169-178, (2002); Tinnila M., Jarvela P., First steps - second thoughts - third parties, (2000); Torkzadeh G., Dhillon G., Measuring factors that influence the success of internet commerce, Information Systems Research, 13, 2, pp. 187-204, (2002); Wu F., Mahajan V., Balasubramanian S., An analysis of e-business adoption and its impact on business performance, Journal of the Academy of Marketing Science, 31, 4, pp. 425-447, (2003); Xu M., Roberts M., Internet shopping model and customer perceptions - a study of UK supermarkets, The Social and Cognitive Impacts of E-commerce on Modern Organizations, pp. 73-89, (2004); Yu J., The evolution of Chinese consumers on the internet and its implications for marketing, International Journal of Electronic Marketing and Retailing, 1, 1, pp. 30-47, (2006)","M. Xu; Portsmouth Business School, University of Portsmouth, Portsmouth, Hampshire PO1 3DE, United Kingdom; email: mark.xu@port.ac.uk",null,"Inderscience Publishers",{"$nulls":5},1.7411025E7,null,null,null,"English","Int. J. Electron. Mark. Retail.","Article","Final",null,"Scopus","2-s2.0-39149088930"]
["Weltevreden J.W.J.","Weltevreden, Jesse W.J. (15822715600)",1.58227156E10,"B2c e-commerce logistics: The rise of collection-and-delivery points in the Netherlands",2008.0,"International Journal of Retail and Distribution Management",36.0,8.0,null,638.0,660.0,22.0,153.0,"10.1108/09590550810883487","https://www.scopus.com/inward/record.uri?eid=2-s2.0-46749121460&doi=10.1108%2f09590550810883487&partnerID=40&md5=0592ecd3e78f13a070cf715af5da0924","Netherlands Institute for Spatial Research (RPB), Hague, Netherlands","Weltevreden J.W.J., Netherlands Institute for Spatial Research (RPB), Hague, Netherlands","Purpose - To empirically study the uptake of collection-and-delivery points (CDPs) in The Netherlands and its consequences for retailers, shopping centres, and mobility. Design/methodology/approach - The study uses 2006 data from an online consumer survey and data provided by the major CDP companies in The Netherlands. In addition, two Dutch directors of CDP companies were interviewed. Findings - The service point is nowadays the dominant form of CDP in The Netherlands. However, in 2006 only 1.4 percent of all online orders in The Netherlands were delivered at a service point. In addition, Dutch consumers currently mainly use service points for returning their online orders. As such, positive mobility effects of service points are so far small. Nevertheless, for retailers operating a service point may lead to additional revenues, as one in four online shoppers make a purchase when collecting or returning a parcel. Research limitations/implications - Since service points - at least in The Netherlands - are nowadays mainly used for returning online orders, future empirical research should not neglect the reverse logistics function of CDPs. Practical implications - Online shoppers are more willing to use the service point concept when they have many service points in the vicinity of their home. In addition, service points with many consumers in their immediate surroundings also perform best. A five minutes driving distance by car seems the critical accessibility value for the success of this concept. Originality/value - Using nation-wide representative samples the paper makes a significant contribution to the scarce empirical literature on the uptake and consequences of CDPs for retailers, shopping centres, and mobility. © Emerald Group Publishing Limited.","Distribution management; Electronic commerce; Retailing; Service delivery; The Netherlands",{"$nulls":7},"Browne M., E-commerce and urban transport, OECD/ECMT Seminar the Impact of e-Commerce on Transport, (2001); Browne M., Allen J., Anderson S., Jackson M., Overview of Home Deliveries in the UK, (2001); Brummelman H.J., Kuipers B., Vale N., Effecten Van Packstations Op Verkeersbewegingen (Impacts of Locker Points on Mobility), (2003); Dhl, Data DHL Collection Points, (2006); Esser K., Kurte J., B2C-Handel: Qualitative und Quantitative Analyse des Konsumenten- Und Anbieterverhaltens und Deren Verkehrliche Auswirkungen in Ballungsräumen (B2C E-commerce: A Qualitative and Quantitative Analysis of the Consumer and Supplier Relationships and Their Implications for Urban Transport), (2005); Esser K., Kurte J., B2C e-commerce: Impact on transport in urban areas, Recent Advances in City Logistics: Proceedings of the 4th International Conference on City Logistics, pp. 447-58, (2006); Esser K., Kurte J., Strategien Zur Optimierung von Abhol- Und Lieferverkehren des Internethandels - Am Beispiel der Packstation in Köln (OPTIMAL) (Strategies for Optimizing Pick-up and Delivery Traffic of Internet Commerce - Packstations in Cologne (OPTIMAL)), (2007); Fernie J., McKinnon A.C., Online shopping: The logistic issues, The Retailing Book: Principles and Applications, pp. 273-85, (2003); Fernie J., McKinnon A.C., The development of e-tail logistics, Logistics and Retail Management, pp. 164-87, (2004); Fischer L., Die Symbiose von Kundenorientierung und Kostenreduzierung am Point of Information: Die Packstation der Deutschen Post AG\" (\"The Symbiosis of Customer Orientation and Cost Reduction: The Packstation from Deutschen Post), (2003); Foresight, The (R)etail (R)evolution: From A Nation of Shopkeepers to A World of Opportunities, (2000); Foresight, ± Your Home; New Markets for Customer Service and Delivery, (2001); Gls, (2006); Gls, GLS Netherlands Opent Eerste Pakketshops (GLS Netherlands Opens Its First Parcel Shops), (2006); Gls, Drop off Servicepunt (Drop off Service Point), (2007); Imrg, Valuing Home Delivery; A Cost - Benefit Analysis, (2006); Gmbh I., E-Business und Verkehrsaufkommen: Der Endkunde Als Einflussfaktor (E-Business and Mobility: The Role of the Consumer), (2001); Kiala, Data Kialapunten (Data Kiala Points), (2006); Kiala, (2006); Kiala, Marktonderzoek Kiala Nederland BV - 2006 (Market Research Kiala Netherlands BV - 2006), (2006); Locatus, Retaillocatiebestand April 2006 (Retail Location Database April 2006), (2006); McKinnon A.C., Tallam D., Unattended delivery to the home: An assessment of the security implications, International Journal of Retail & Distribution Management, 31, 1, pp. 30-41, (2003); McLeod F., Cherrett T., Song L., Transport impacts of local collection/delivery points, International Journal of Logistics: Research and Applications, 9, 3, pp. 307-17, (2006); Muconsult, ICT, Ruimte en Mobiliteit (ICT, Spae and Mobility), (2003); Nemoto T., Visser J., Yoshimoto R., Impacts of information and communication technology on urban logistics system, OECD/ECMT Seminar the Impact of e-Commerce on Transport, (2001); Oecd, Delivering the Goods; 21st Century Challenges to Urban Goods Transport, (2003); Punakivi M., Tanskanen K., Increasing the cost efficiency of e-fulfilment using shared reception boxes, International Journal of Retail & Distribution Management, 30, 10, pp. 498-507, (2002); Redpack, Redpack Network Inc. Announces Expansion to the United Kingdom and Acquires Assests of Collectpoint, (2007); Rowlands P., Unattended delivery solutions - Finally picking up?, Fulfilment and E. Logistics, 39, pp. 19-20, (2006); Netherlands S., Statline, Statistics Netherlands, Voorburg/Heerlen, (2006); Inro T., Op Weg Naar Een Omgevingsverkenner ICT, Ruimte en Mobiliteit (Towards An ICT, Space and Mobility Monitor), (2002); Post T., (2006); Van Der Zwan J., Van Der Wel R., Ritsema Van Eck J., De Jong T., Floor H., Manual Flowmap 7.2, (2005); Van Oosterhout M., Kiala: A new distribution concept for the home shopping market, Prediction of Eeconomy Impacts on Transport (POET); Actual Case Studies for Passenger and Freight Transport, (2004); Weltevreden J.W.J., Winkelen in Het Internettijdperk [Shopping in the Internet Age], (2007); Weltevreden J.W.J., Substitution or complementarity? How the internet changes city centre shopping, Journal of Retailing and Consumer Services, 14, 3, pp. 192-207, (2007)","J. W. J. Weltevreden; Netherlands Institute for Spatial Research (RPB), Hague, Netherlands; email: jweltevreden@gmail.com",{"$nulls":7},9590552.0,null,null,null,"English","Int. J. Retail Disrtib. Manage.","Article","Final",null,"Scopus","2-s2.0-46749121460"]
["Chong A.Y.L.; Ooi K.B.; Tak Y.K.; ShuYang Z.","Chong, Alain Yee Loong (26654029000); Ooi, Keng Boon (14619509700); Tak, Yew King (37023671800); ShuYang, Zhu (57194870421)","26654029000; 14619509700; 37023671800; 57194870421","Factors affecting the adoption of e-commerce: A study of the textile industry in Wujin, China",2009.0,"International Journal of Business and Management Science",2.0,2.0,null,117.0,130.0,13.0,6.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-79952613348&partnerID=40&md5=e4a793c027f1c3596f038eb041868dca","Faculty of Computing and IT, INTI University College, Malaysia; Faculty of Business and Finance, University Tunku Abdul Rahman, Malaysia","Chong A.Y.L., Faculty of Computing and IT, INTI University College, Malaysia; Ooi K.B., Faculty of Business and Finance, University Tunku Abdul Rahman, Malaysia; Tak Y.K., Faculty of Business and Finance, University Tunku Abdul Rahman, Malaysia; ShuYang Z., Faculty of Computing and IT, INTI University College, Malaysia","The purpose of this paper is to examine the factors that influence the adoption of e-commerce with emphasis on textile companies in WuJin, China. The factors are organizational readiness, innovation characteristics, government influence and culture. Binary logistic regression was applied to test the research model. The result shows that organizational readiness, innovation characteristics and culture influence the adoption of e-commerce among textile companies in WuJin. As China's culture is different from many western countries, it is found that relationships between organizations, or GuanXi as it is commonly known in China, needs to be established before organizations collaborating with each other are willing to adopt e-commerce. The findings of this study are useful for the Malaysian companies who are interested to adopt e-commerce with their business partners in China.","Culture; E-commerce; Organizational readiness; Textile industry; Wujin",{"$nulls":7},"Aghaunor L., Fotoh X., Factors Affecting Ecommerce Adoption in Nigerian Banks, (2006); Al-Mashari. M., Electronic commerce: A comparative study of organizational experiences, Benchmarking: An International Journal, 9, 2, pp. 182-189, (2002); Burn J.M., The new cultural revolution: The impact of EDI on Asia, Journal of Global Information Management, 3, 4, pp. 16-23, (1995); Chai L., Pavlou P.A., From 'ancient' to 'modern': A cross-cultural investigation of electronic commerce adoption in Greece and the United States, Journal of Enterprise Information Management, 16, 6, pp. 416-423, (2004); Chan B., Al-Hawamdeh S., The development of e-commerce in Singapore: The impact of government initiatives, Business Process Management Journal, 8, 3, pp. 278-288, (2002); Chong A.Y.L., An Empirical Examination of Collaborative Commerce Adoption for Supply Chain Management among Malaysian Electrical and Electronic Organizations, (2008); Chong A.Y.L., Ooi K.B., Adoption of inter-organizational system standards in supply chains: An empirical analysis of RosettaNet Standards, Industrial Management and Data Systems, 108, 4, pp. 529-547, (2008); Chong A.Y.L., Ooi K.B., Lin B., Tang S.Y., A study on impact of Malaysian SMEs inter-organizational relationships and knowledge management towards e-business supply chain technology implementation, Internet Research, 19, 3, pp. 313-331, (2009); Chong A.Y.L., Ooi K.B., Sohal A., The relationship between supply chain factors and e-collaboration tools adoption: An empirical examination, International Journal of Production Economics, 122, 1, pp. 150-160, (2009); Davis F.D., Perceived usefulness, perceived ease of use, and user acceptance of information technology, MIS Quarterly., 13, 3, pp. 319-340, (1989); Erez M., Earley P.C., Culture, self-Identity, and work, NY: Oxford University Press, (1993); Fan M., Join from traditional industry to e-commerce. China venture capital & Hi-Technic. Beijing, Academic Journal Electronic Publishing House, (2006); Ford R.C., McLaughlin F., Questions and Answers about Telecommuting Programs, (1995); Hair J.F., Anderson R.E., Tatham R.L., Black W.C., Multivariate Data Analysis, (2006); Analysis of Industry Configuration in Wujin, (2007); King J.L., Gurbaxani V., Kraemer K.L., McFarlan F.W., Raman K.S., Yap C.S., Institutional factors in information technology innovation, Information Systems Research, 5, 2, pp. 139-169, (1994); Kowalski K.B., Swanson J.A., Critical success factors in developing teleworking programs, Benchmarking, 12, 3, pp. 236-249, (2005); Lederer A.L., Mendelow A.L., Convincing top management of the strategic potential of information systems, MIS Quarterly, 12, 4, pp. 525-534, (1986); Lin B., Managing in an information highway age: Critical issues, Industrial Management and Data Systems, 94, 8, pp. 3-7, (1994); Lin H., Empirically testing innovation characteristics and organizational learning capabilities in e-business implementation success, Internet Research, 18, 1, pp. 60-78, (2008); Ngai E.W.T., Gunasekaran A., Implementation of EDI in Hong Kong: An empirical analysis, Industrial Management & Data Systems, 104, 1, pp. 88-100, (2004); Nelson M.J., Shaw M.L., The Adoption and Diffusion of Inter-organizational Systems Standards and Process Innovation, (2003); Nunnally J., Psychometric Theory, (1978); Ouyang F., Li Y., The Actuality, Questions and Countermeasures of Electronic Commerce Application in SMEs: A Survey in the East of Guangdong Province, China, (2005); Rogers E.M., Diffusion of Innovations, (1983); Shen L., Hawley J., Dickerson K., E-Commerce adoption for supply chain management in US apparel manufacturers, Journal of Textile and Apparel, Technology and Management, 4, 1, pp. 1-11, (2004); Stoneman P., David P., Adoption subsidies vs. information provision as instruments of technology policy, Economic Journal, 96, pp. 142-150, (1986); Thatcher S.M.B., Foster W., B2B e-commerce adoption decisions in Taiwan: The interaction of organizational, industrial, governmental and cultural factors,  Hawaii International Conference on System Sciences (HICSS'03), (2002); SMES and E-commerce, (2002); To M.L., Ngai E.W.T., Predicting the organisational adoption of B2C e-commerce: An empirical study, Industrial Management and Data Systems, 106, 8, pp. 1133-1147, (2006); Toh T.W., Marthandan G., Chong A.Y.L., Ooi K.B., Seetharaman A., What drives Malaysian m-commerce adoption: An empirical analysis?, Industrial Management and Data Systems, 109, 3, pp. 370-388, (2009); Tornatzky L., Fleischer M., The Processes of Technological Innovation, (1990); Wei Y.H.D., Beyond the Sunan model: Trajectory and underlying factors of development in Kunshan, China, Environment and Planning, 34, 10, pp. 1725-47, (2002); Six Bottleneck to Restrict E-Commerce Development in China, (2005)","A. Y. L. Chong; Faculty of Computing and IT, INTI University College, Malaysia; email: alain.chong@gmail.com",{"$nulls":7},"1985692X",null,null,null,"English","Int. J. Bus. Manage. Sci.","Article","Final",null,"Scopus","2-s2.0-79952613348"]
["Coughlan J.; Macredie R.D.; Patel N.","Coughlan, Jane (7006567224); Macredie, Robert D. (35577358500); Patel, Nayna (57214100584)","7006567224; 35577358500; 57214100584","Evaluating the effectiveness of customers' communication experiences with online retailers - A study of e-mortgages",2007.0,"Interacting with Computers",19.0,1.0,null,83.0,95.0,12.0,4.0,"10.1016/j.intcom.2006.06.003","https://www.scopus.com/inward/record.uri?eid=2-s2.0-33846057462&doi=10.1016%2fj.intcom.2006.06.003&partnerID=40&md5=0952953fd2c24206957b092a10b0f944","School of Information Systems, Computing and Mathematics, Brunel University, Uxbridge, Middlesex UB8 3PH, United Kingdom","Coughlan J., School of Information Systems, Computing and Mathematics, Brunel University, Uxbridge, Middlesex UB8 3PH, United Kingdom; Macredie R.D., School of Information Systems, Computing and Mathematics, Brunel University, Uxbridge, Middlesex UB8 3PH, United Kingdom; Patel N., School of Information Systems, Computing and Mathematics, Brunel University, Uxbridge, Middlesex UB8 3PH, United Kingdom","Retailers increasingly use the Internet for supporting customer interaction in the delivery of products and services online, whilst simultaneously displacing direct communication to a seller with 'faceless' technology. Research has tended to marginalise the importance of this communication change, possibly because of the lack of appropriate models for evaluating communication effectiveness. This paper therefore seeks to develop and apply such an evaluative model, which is underpinned by communication theory. The context of application is e-mortgage lending - based on the selection of two banks' interfaces - as evidence suggests that this type of e-commerce activity presents difficulties in electronic communication where, for example, the customer need for face-to-face mortgage advice prevails. Findings from the model's application reveal that whilst users respond socially to the interfaces, a number of communication problems can be identified by theme. Reflection is provided on the model's usefulness for evaluating the effectiveness of customers' online communication experiences. © 2006 Elsevier B.V. All rights reserved.","Communication; E-commerce; E-mortgages; Interactivity; Online banking","Customer satisfaction; Electronic commerce; Information theory; Internet; Mathematical models; Speech communication; User interfaces; E-mortgages; Electronic communication; Face to face mortgage; Online banking; Online systems",{"$nulls":6},"Aladwani A.M., Online banking: a field study of drivers, development challenges, and expectations, International Journal of Information Management, 21, 3, pp. 213-225, (2001); Benbunan-Fich R., Using protocol analysis to evaluate the usability of a commercial web site, Information and Management, 39, 2, pp. 151-163, (2001); Berry L.L., Carbone L.P., Haeckel S.H., Managing the total customer experience, MIT Sloan Management Review, 43, 3, pp. 85-89, (2002); Bidgoli H., Electronic Commerce: Principles and Practice, (2002); Blumler J.G., Katz E., The Uses of Mass Communications: Current Perspectives on Gratifications Research, (1974); Browne G.J., Durrett J.R., Wetherbe J.C., Consumer reactions toward clicks and bricks: investigating buying behaviour on-line at stores, Behaviour and Information Technology, 23, 4, pp. 237-245, (2004); Burke R.R., Technology and the customer interface: what customers want in the physical and virtual store, Journal of the Academy of Marketing Science, 30, 4, pp. 411-432, (2002); Cassell M.M., Jackson C., Cheuvront B., Health communication on the internet: an effective channel for health behavior change?, Journal of Health Communication, 3, pp. 71-79, (1998); Colgate M., Alexander N., Banks, retailers and their customers: a relationship marketing perspective, International Journal of Bank Marketing, 16, 4, pp. 144-152, (1998); Daft R.L., Lengel R.H., Organizational information requirements, media richness and structural design, Management Science, 32, 5, pp. 554-571, (1986); Delone W.H., McLean E.R., Measuring e-Commerce success: applying the Delone & McLean information systems success model, International Journal of Electronic Commerce, 9, 1, pp. 31-47, (2004); Eastin M.S., Diffusion of e-commerce: an analysis of the adoption of four e-commerce activities, Telematics and Informatics, 19, 3, pp. 251-267, (2002); Fulk J., Schmitz J., Steinfield C.W., A social influence model of technology use, Organizations and Communication Technology, pp. 117-140, (1990); Ha L., James E.L., Interactivity reexamined: a baseline analysis of early business web sites, Journal of Broadcasting and Electronic Media, 42, 4, pp. 457-474, (1998); Jayawardhena C., Foley P., Changes in the banking sector - the case of Internet banking in the UK, Internet Research: Electronic Networking Applications and Policy, 10, 1, pp. 19-30, (2000); Keeler M.A., Denning S.M., The challenge of interface design for communication theory: from interaction metaphor to contexts of discovery, Interacting with Computers, 3, 3, pp. 283-301, (1991); Klobas J.E., Clyde L.A., Social influence and internet use, Library Management, 22, 1-2, pp. 61-67, (2001); Kumar N., Benbasat I., Para-social presence and communication capabilities of a web site, e-Service Journal, 1, 3, pp. 5-24, (2002); Li H., Daugherty T., Biocca F., Characteristics of virtual experience in electronic commerce: a protocol analysis, Journal of Interactive Marketing, 15, 3, pp. 13-30, (2001); Light A., Wakeman I., Beyond the interface: users' perceptions of interaction and audience on websites, Interacting with Computers, 13, 3, pp. 325-351, (2001); Morris M., Ogan C., The internet as a mass medium, Journal of Communication, 46, 1, pp. 39-50, (1996); Nass C.I., Mason L., On the study of technology and task: a variable based approach, Organizations and Communication Technology, pp. 46-67, (1990); Nielsen J., Usability Engineering, (1994); Nielsen J., Molich R., Snyder C., Farrell S., E-Commerce User Experience, (2001); O'Donnell A., Durkin M.G., McCartan-Quinn D., Corporate banking in the UK: personal vs remote interaction, International Journal of Bank Marketing, 20, 6, pp. 273-284, (2002); Pack T., Use it or lose it: Jakob Nielsen champions content usability, EContent, 24, 4, pp. 44-46, (2001); Peterson R.A., Balasubramanian S., Bronnenberg B.J., Exploring the implications of the internet for consumer marketing, Journal of the Academy of Marketing Science, 25, 4, pp. 329-346, (1997); Prates R.O., Barbosa S.D.J., de Souza C.S., A Case Study for Evaluating Interface Design Through Communicability, (2000); Reynolds C., As we may communicate, SIGCHI Bulletin, 30, 3, pp. 40-44, (1998); Shannon C., Weaver W., The Mathematical Theory of Communication, (1949); Shneiderman B., Designing the User Interface: Strategies for Effective Human-Computer Interaction, (1998); Stafford T.F., Stafford M.R., Schkade L.L., Determining uses and gratifications for the Internet, Decision Sciences, 35, 2, (2004); Sundar S.S., Nass C., Source orientation in human-computer interaction - Programmer, networker, or independent social actor?, Communication Research, 27, 6, pp. 683-703, (2000); Tan M., Teo T.S.H., Factors influencing the adoption of internet banking, Journal of the Association for Information Systems, 1, 5, (2000); Tubbs S.L., Moss S., Human Communication, (2000); Verhallen T.M.M., Greve H., Frambach R.T., Consultative selling in the financial services: an observational study of the mortgage mediation process, International Journal of Bank Marketing, 15, 2, pp. 54-59, (1997); Vijayasarathy L.R., Shopping orientations, product types and internet shopping intentions, Electronic Markets, 13, 1, pp. 67-79, (2003); Walther J.B., Computer-mediated communication: impersonal, interpersonal, and hyperpersonal interaction, Communication Research, 23, 1, pp. 3-43, (1996); Wang P., Hawk W.B., Tenopir C., Users' interaction with World Wide Web resources: an exploratory study using a holistic approach, Information Processing and Management, 36, 2, pp. 229-251, (2000); Williams F., Strover S., Grant A.E., Social aspects of new media technologies, Media Effects: Advances in Theory and Research, pp. 463-482, (1994); Zwass V., Electronic commerce: structures and issues, Journal of Electronic Commerce, 1, 1, pp. 3-23, (1994)","J. Coughlan; School of Information Systems, Computing and Mathematics, Brunel University, Uxbridge, Middlesex UB8 3PH, United Kingdom; email: Jane-Lisa.Coughlan@brunel.ac.uk",null,"Elsevier",{"$nulls":5},9535438.0,null,"INTCE",null,"English","Interact Comput","Article","Final",null,"Scopus","2-s2.0-33846057462"]
["Golnoosh sadeghi F.A.; Reza banan S.B.M.","Golnoosh sadeghi, F.A. (36805959200); Reza banan, S.B Mohammad (36806494400)","36805959200; 36806494400","How is E-insurance in developing countries?",2009.0,"World Academy of Science, Engineering and Technology",37.0,null,null,1195.0,1221.0,26.0,0.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-78651572502&partnerID=40&md5=2eb9ded683ab908b37241c36b352e2ae","Islamic Azad university, Arsanjan branch, Iran","Golnoosh sadeghi F.A., Islamic Azad university, Arsanjan branch, Iran; Reza banan S.B.M., Islamic Azad university, Arsanjan branch, Iran","E-insurance can be broadly defined as the application of Internet and related information technologies (IT) to the production and distribution of insurance services. In a narrower sense, it can be defined as the provision of an insurance cover whereby an insurance policy is solicited, offered, negotiated and contracted online. While payment, policy delivery and claims processing may all be done online as well, technical and regulatory constraints may not allow these elements to be subject to full e- commerce application in certain countries. However, insurance legislation worldwide is being continuouslymodified to accommodate online payment and policy delivery, and, outside the discussion of e-insurance metrics, these elements should be included in the narrow definition. The anticipated efficiency effect of e- insurance is twofold. First, e-insurance should reduce internal administration and management costs by automating business processes,permitting real-time networking of company departments, and improving management information. Secondly, it should reduce the commissions paid to intermediaries since it can be sold directly to clients. For insurance sold to individuals, agents typically receive a commission of 10 to 15 percent for non-life policy sales and renewals and from 35 to 100 per cent for life insurance policies in the first policy year, but much less on renewal. However, some of the income gained in commissions that are not paid to intermediaries must be spent on online customer acquisition and marketing. Assuming cost savings do materialize, in a competitive market they would be passed on to consumers thereby allowing them to buy more insurance, or other products or services. Since insurance penetration in developing countries is only of that in developed countries, the efficiency gains created by e-insurance may contribute substantially to growth in insurance spending and thus intensify its indisputable role in promoting trade and article, we development. In this investigate the role and position of e- insurance in developing countries. © 2009 WASET.ORG.","Developing Countries; E-commerce (EC); E-Insurance; Information Technology (IT)","Contracts; Developing countries; Electric conductivity measurement; Electronic commerce; Information technology; Laws and legislation; Business Process; Competitive markets; Cost saving; Developed countries; E-commerce (EC); E-Commerce applications; E-Insurance; Efficiency gain; Insurance policies; Life insurance policies; Management costs; Management information; On-line payment; Online customers; Insurance",{"$nulls":6},"Outreville J.F., The economic significance of insurance markets in developing countries, Journal of Risk and Insurance, 57, 3, (1990); Brown J.R., Research Working Papers Series, Does the Internet Make Markets More Competitive? Evidence from the Life Insurance Industry, (2000); Nielsen, NetRatings; Overview of selected legal and regulatory developments in electronic commerce, UNCTAD/SDTE/ECB/1, 2000; UNCTAD, Electronic Commerce: Legal considerations, UNCTAD/SDTE/BFB/1, E-commerce and Development Report 2001, (1998); Walker T., NAIC Electronic Commerce and Regulation Working Group, NAIC, Research Quarterly, 5, 2, (1999); The results of the KPMG LLP e- insurance survey were reported; TechnologyDecisions for Insurance, The Tangled Webs They Weave; Brown J.R., Does the Internet Make Markets More Competitive? Evidence from the Life Insurance Industr y, Harvard University, Research Working Papers Series, RWP00-007; and gsb, (2000); Emerging Strategies in Insurance and Technology y, (2001); Helwig D.B., Burning Issues, (2001); Helwig D.B., Burning Issues, (2001); Wanted: Reassurance about Online Insurance - Business Owners Say They Need Guidance and Trust before Buying Coverage on the Web, Business Week Online, (2000); Main B.G.M., Large Companies and Insurance Purchases: Some Survey Evidence, The Geneva Papers on Risk and Insurance, 25, 2, (2000); Building Confidence: Electr onic Commerce and Development, Section IV, E-commerce and Financial Services, UNCTAD/SDTE/Misc, 11, (2000); Dyson B., Online Reinsurance: Exchanges Built on Shi ing Sands, Reactions, (2001); Helwig D.B., Burning Issues, (2001); Infosys Press Release; Principles on the Supervision of Insurance Activities on the Internet, (2000); Electronic Finance: Economics and Institutional Factors, (2001); Principles on the Supervision of Insurance Activities on the Internet, (2000)","F. A. Golnoosh sadeghi; Islamic Azad university, Arsanjan branch, Iran; email: golnoosh_sadeghi@yahoo.com",{"$nulls":7},2.0103778E7,null,null,null,"English","World Acad. Sci. Eng. Technol.","Article","Final",null,"Scopus","2-s2.0-78651572502"]
["Wen W.","Wen, W. (16641002800)",1.66410028E10,"A knowledge-based intelligent electronic commerce system for selling agricultural products",2007.0,"Computers and Electronics in Agriculture",57.0,1.0,null,33.0,46.0,13.0,44.0,"10.1016/j.compag.2007.01.016","https://www.scopus.com/inward/record.uri?eid=2-s2.0-33947670473&doi=10.1016%2fj.compag.2007.01.016&partnerID=40&md5=eae285efd3f3335364a284fedf33d346","Department of Information Management, LungHwa University of Science and Technology, Taiwan","Wen W., Department of Information Management, LungHwa University of Science and Technology, Taiwan","This paper presents a knowledge-based intelligent e-commerce system for selling agricultural products. The KIES system not only provides agricultural products sales, financial analysis and sales forecasting, but also provides feasible solutions or actions based on the results of rule-based reasoning. The intelligent system integrates a database, a rule base and a model base to create a tool of which managers can use to deal with decision-making problems via the Internet. Rules in the rule base are explained in detail to illustrate the processes of reasoning. Also, an automatic and practical inference engine that provides monitoring and controlling a verity of processes is presented to show how the system can deal with knowledge management. In order to obtain more profits and manage future change, artificial neural network models in the model base have been developed and compared for demand forecasting. Finally, for offering convenient delivery and user-friendly services to customers, an e-map combined with a GPS is used. © 2007 Elsevier B.V. All rights reserved.","e-Commerce; Knowledge-based intelligent system; Model base; Rule base","Agriculture; Artificial Intelligence; Commerce; Information Retrieval; Agricultural products; Artificial intelligence; Electronic commerce; Knowledge based systems; agricultural market; agroindustry; artificial neural network; database; decision making; e-commerce; GPS; Internet; knowledge based system; Knowledge-based intelligent system; Model base; Rule base; Knowledge engineering",{"$nulls":6},"Adelaar T., Bouwman H., Steinfield C., Enhancing customer value through click-and-mortar e-commerce: implementation for geographical market reach and customer type, Telematics Inform., 21, pp. 167-182, (2004); Al-Saba T., El-Amin I., Artificial networks as applied to long-term demand forecasting, Artif. Intell. Engineer, pp. 189-197, (1999); Chan F.T.S., Jiang B., Tang N.K.H., The development of intelligent decision support tools to aid the design of flexible manufacturing system, Int. J. Prod. Econ., 65, pp. 73-84, (2000); Eriksson H., Expert systems as knowledge servers, IEEE Exp. Syst. Web, pp. 14-18, (1996); Fish K.E., Barnes J.H., Aiken M.W., Artificial neural networks: a new methodology for industrial market segmentation, Ind. Market. Manage., 24, pp. 431-438, (1995); Kong S.C.W., Li H., Hung T.P.L., Shi J.W.Z., Castro-Lacouture D., Skibniewski, Enabling information sharing between e-commerce systems for construction material procurement, Autom. Construct., 13, pp. 261-276, (2004); Kuo R.J., Xue K.C., A decision support system for sales forecasting through fuzzy neural networks with asymmetric fuzzy weights, Decis. Support Syst., 24, pp. 105-126, (1998); Li S., The development of a hybrid intelligent system for developing marketing strategy, Decis. Support Syst., 27, pp. 395-409, (2000); Liang T.P., Huang J.S., A framework for applying intelligent agents to support electronic trading, Decis. Support Syst., 28, pp. 305-317, (2000); Matsatsinis N.F., Doumpos M., Zopounidis C., knowledge acquisition and representation for expert systems in the field of financial analysis, Exp. Syst. Appl., 12, 2, pp. 247-262, (1997); Matsatsinis N.F., Siskos Y., MARKEX:an intelligent decision support system for product development decisions, Eur. J. Oper. Res., 113, pp. 336-354, (1999); Morton S., Management Decision Systems: Computer Based Support for Decision Making, (1971); Negnevitsky M., Artificial Intelligence, (2002); Ozbayrak M., Bell R., A knowledge-based decision support system for the management of parts and tools in FMS, Decis. Support Syst., 35, pp. 487-515, (2003); Pal K., Palmer O., A decision support system for business acquisitions, Decis. Support Syst., 27, pp. 411-429, (2000); Park C.S., Han I., A case-based reasoning with the feature weights derived by analytic hierarchy process for bankruptcy prediction, Exp. Syst. Appl., 23, pp. 255-264, (2002); Srinivasan D., Liew A.C., Chang C.S., A neural network short-term load forecaster, Electr. Power Syst. Res., 28, pp. 227-234, (1994); Srinivasan D., Evolving artificial neural networks for short term load forecasting, Neurocomputing, 23, pp. 265-276, (1998); Tang Z., Fishwick P.A., Time series forecasting using neural networks versus Box-Jenkins methodology, Simulation, 57, 5, pp. 303-310, (1993); Turb E., Aronson J.E., Decision Support Systems and Intelligent Systems, (2001); Vellido A., Lisboa P.J.G., Vaughan J., Neural networks in business: a survey of applications, Exp. Syst. Appl., 17, pp. 51-70, (1999); Vishwakarma K.P., A neural network to predict multiple economic time series, Proceedings of the IEEE international Conference on Neural Networks, vol. 6, pp. 3670-3674, (1995); Wen M., e-Commerce, productivity, and fluctuation, J. Econ. Behav. Organ., 55, pp. 187-206, (2004); Wen W., Wang W.K., Wang C.H., A knowledge-based intelligent decision support system for national defense budget planning, Exp. Syst. Appl., 28, 1, pp. 55-66, (2005); Wen W., Wang W.K., Wang C.H., A hybrid knowledge-based decision support system for enterprise mergers and acquisitions, Exp. Syst. Appl., 28, 3, pp. 569-582, (2005); Zhang G., Patuwo B.E., Hu M.Y., Forecasting with artificial neural networks: the state of the art, Int. J. Forecasting, 14, pp. 35-62, (1998); Zopounidis C., Doumpos M., Matsatsinis N.F., On the use of knowledge-based decision support systems in financial management: a survey, Decis. Support Syst., 20, pp. 259-277, (1997); Zott C., Amit R., Donlevy J., Strategies for value creation in e-commerce best practice in Europe, Eur. Manage. J., 18, 5, pp. 463-475, (2000)","W. Wen; Department of Information Management, LungHwa University of Science and Technology, Taiwan; email: wenwu@mail.lhu.edu.tw",{"$nulls":7},1681699.0,null,"CEAGE",null,"English","Comput. Electron. Agric.","Article","Final",null,"Scopus","2-s2.0-33947670473"]
["Rotem-Mindali O.C.; Salomon I.","Rotem-Mindali, Orit C. (14519663500); Salomon, Ilan (7003435440)","14519663500; 7003435440","Modeling consumers' purchase and delivery choices in the face of the information age",2009.0,"Environment and Planning B: Planning and Design",36.0,2.0,null,245.0,261.0,16.0,15.0,"10.1068/b34013t","https://www.scopus.com/inward/record.uri?eid=2-s2.0-66349132413&doi=10.1068%2fb34013t&partnerID=40&md5=7a079cdacb3ce66e0bd8d3e24eb2cb49","OTB Research Institute for Housing Urban and Mobility Studies, Delft University of Technology, 2600 GA Delft, PO Box 5030, Netherlands; School of Public Policy, Department of Geography, The Hebrew University of Jerusalem, Jerusalem 91905, Israel","Rotem-Mindali O.C., OTB Research Institute for Housing Urban and Mobility Studies, Delft University of Technology, 2600 GA Delft, PO Box 5030, Netherlands; Salomon I., School of Public Policy, Department of Geography, The Hebrew University of Jerusalem, Jerusalem 91905, Israel","A major trend, recently drawing much attention, is the employment of new technologies in retailing. This involves a shift from some aspects of the traditional store format towards the introduction of electronic means of performing retail activities. E-retail encompasses three main activities - specifically, a product search activity (often referred to as a product-evaluation or information-gathering facility), an online purchase function, and the product delivery capability. Early studies have asserted that information technology would generate a revolution in the retail sector, owing to the potential of the web to reduce the costs of transaction, transportation, and searching. Yet the proportion of virtual shopping is significantly smaller than that of traditional shopping. An understanding of this difference can be obtained by modeling consumer choices. This paper will examine the different shopping activities, by modeling both purchase and delivery choices. Identifying the reasons that consumers use virtual (electronic) modes is crucial in order to influence the share of electronic shopping and to understand the potential impacts. Modeling the probability of using e-shopping should reveal the significant variables that may encourage or discourage the use of this mode of shopping. © 2008 Pion Ltd and its Licensors.",null,"consumption behavior; e-commerce; information technology; modeling; probability; retailing; shopping activity",{"$nulls":6},"Alba J., Lynch J., Weitz B., Janiszewski C., Lutz R., Sawyer A., Wood S., Interactive home shopping: Consumer, retailer, and manufacturer incentives to participate in electronic marketplaces, Journal of Marketing, 61, 3, pp. 38-53, (1997); Alerck P.L., Settle R.B., The Survey Research Handbook, (2004); Anderson W.P., Basilevski A., Hum D.P.J., Measurement, theory and techniques, Handbook of Survey Research, pp. 231-287, (1983); Ariely D., Controlling the information flow: Effects on consumers' decision making and preferences, Journal of Consumer Research, 27, pp. 233-248, (2000); Bart Y., Shankar V., Sultan F., Urban G.L., Are the drivers and role of online trust the same for all web sites and consumers? 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Childers T.L., Carr C.L., Peck J., Carson S., Hedonic and utilitarian motivations for online retail shopping behavior, Journal of Retailing, 77, pp. 511-535, (2001); Choi J.Y., Geistfeld L.V., A cross-cultural investigation of consumer e-shopping adoption, Journal of Economic Psychology, 25, pp. 821-838, (2004); Cohen N., Greening the Internet: Ten ways e-commerce could affect the environment, Environmental Quality Management, 9, 11, pp. 1-16, (1999); Dawson J., Retail trends in Scotland: A review, International Journal of Retail and Distribution Management, 23, 4, pp. 4-20, (1995); Dixon T., Marston A., UK retail real estate and the effects of online shopping, Journal of Urban Technology, 9, 3, pp. 19-47, (2002); Evans F., Wurster T.S., Blown to Bits: How the New Economics of Information Transforms Strategy, (2000); Farag S., Krizek K.J., Dijst M., E-shopping and its relationship with in-store shopping: Empirical evidence from the Netherlands and the USA, 26, 1, pp. 43-61, (2006); Feitelson E., Rotem O., The case for taxing surface parking, Transportation Research D, 9, pp. 319-333, (2004); 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The perceptions of recreation practitioners and others, Leisure Sciences, 26, pp. 1-17, (2004); Peterson R.A., Merino M.C., Consumer information search behavior and the Internet, Psychology and Marketing, 20, pp. 99-121, (2003); Quarmby D.A., Developments in the retail market and their effect on freight distribution, Journal of Transport Economics and Policy, 23, pp. 75-87, (1989); Ramus K., Nielsen N.A., Online grocery retailing: What do consumers think?, Internet Research, 15, pp. 335-352, (2005); Ratchford B.T., Talukdar D., Lee M.S., A model of consumer choice of the Internet as an information source, International Journal of Electronic Commerce, 5, 3, pp. 7-21, (2001); Rohm A.J., Swaminathan V., A typology of online shoppers based on shopping motivations, Journal of Business Research, 57, pp. 748-757, (2004); Rosen K.T., Howard A.L., E-retail: Gold rush or fool's gold?, California Management Review, 42, 3, pp. 72-100, (2000); Rotem-Mindali O., Salomon I., The impacts of E-retail on the choice of shopping trips and delivery: Some preliminary findings, Transportation Research Part A: Policy and Practice, 41, pp. 176-189, (2007); Salomon I., Telecommunications and travel, Journal of Transport Economics and Policy, 19, pp. 219-235, (1985); Salomon I., Koppelman F.S., Teleshopping or going shopping? An information acquisition perspective, Behaviour and Information Technology, 11, 4, pp. 189-198, (1992); Schroder H.M., Driver M.J., Streufert S., Human Information Processing, (1967); Teo T.S.H., Attitudes toward online shopping and the Internet, Behaviour and Information Technology, 21, pp. 259-271, (2002); Torkzadeh G., Dhillon G., Measuring factors that influence the success of Internet commerce, Information Systems Research, 13, pp. 187-204, (2002); Visser E.J., Lanzendorf M., Mobility and accessibility effects of b2c e-commerce: A literature review, Tijdschrift Voor Economische En Sociale Geografie, 95, pp. 189-205, (2004); Wang E.T.G., Yeh H.Y., Jiang J.J., The relative weights of Internet shopping fundamental objectives: Effects of lifestyle differences, Psychology and Marketing, 23, pp. 353-367, (2006); Wang S.T., Yu M.L., Wang C.J., Huang C.C., Bridging the gap between the pros and cons in treating ordinal scales as interval scales from an analysis point of view, Nursing Research, 48, pp. 226-229, (1999); Ylikoski T., A sequence analysis of consumers' online searches, Internet Research: Electronic Networking Applications and Policy, 15, pp. 181-194, (2005); Zhang M., Exploring the relationship between urban form and nonwork travel through time use analysis, Landscape and Urban Planning, 73, pp. 244-261, (2005)","O.C. Rotem-Mindali; OTB Research Institute for Housing Urban and Mobility Studies, Delft University of Technology, 2600 GA Delf, PO Box 5030, Netherlands; email: o.c.rotem@tudelft.nl",null,"Pion Limited",{"$nulls":5},2658135.0,null,null,null,"English","Environ. Plann. B Plann. Des.","Article","Final",null,"Scopus","2-s2.0-66349132413"]
["Jafari M.; Taghavifard M.T.; Rouhani S.; Moalagh M.","Jafari, Mostafa (12765310100); Taghavifard, Mohammad Taghi (26423333500); Rouhani, Saeed (35324988400); Moalagh, Morteza (35324990800)","12765310100; 26423333500; 35324988400; 35324990800","E-commerce development experiences in world's leading container ports and offering a model for Shahid Rajaee Port",2010.0,"Maritime Policy and Management",37.0,1.0,null,53.0,72.0,19.0,5.0,"10.1080/03088830903461191","https://www.scopus.com/inward/record.uri?eid=2-s2.0-74949100733&doi=10.1080%2f03088830903461191&partnerID=40&md5=a6f1014f54b0dc4a5fef46f840060a77","Iran's University of Science and Technology, Narmak, Tehran, Iran; Department of Management and Accounting, Alame Tabatabaie University, Tehran, Iran; Department of Management, Information Technology group, Shahid Beheshti University, Tehran, Iran","Jafari M., Iran's University of Science and Technology, Narmak, Tehran, Iran; Taghavifard M.T., Department of Management and Accounting, Alame Tabatabaie University, Tehran, Iran; Rouhani S., Iran's University of Science and Technology, Narmak, Tehran, Iran; Moalagh M., Department of Management, Information Technology group, Shahid Beheshti University, Tehran, Iran","In order to develop e-commerce in Iran's maritime transportation sector and make the necessary planning for development of e-commerce at Shahid Rajaee Port, experiences in the world's leading container ports are being studied. In this research, the existing scientific IT models and logistical communications are put together while Shahid Rajaee Port undergoes scrutiny to reach a model of e-commerce development and single window system. This model could set the example for other container ports in Iran to follow. © 2010 Taylor & Francis.",null,"Iran; communication; electronic commerce; information technology; logistics; maritime transportation; port development; port operation; technological development; transportation planning",{"$nulls":6},"Unctad Technical Assistant In Trade Facilitation, (2006); Neo B.S., Managing new information technologies: Lessons from Singapore's experience with EDI, Information & Management, 26, pp. 317-326, (1994); Ang C.-L., Tahar R.M., Murat R., An empirical study on electronic commerce diffusion in the Malaysian shipping industry, The Electronic Journal On Information Systems In Developing Countries, 14, pp. 1-9, (2003); Report of The Expert Meeting On Ict Solutions to Facilitate Trade At Border Crossing and Ports, (2006); Sharp B., Creating e-commerce architecture, Unix Review, 47, 2, pp. 45-51, (1998); Kalakota R., Winston A.B., Electronic Commerce: A Manager's Guide, (1997); Levis K., Electronic commerce, British Telecommunications Engineering, 14, 4, pp. 281-285, (1996); Garrett S.G.E., Skevington P.J., An introduction to e-commerce, Bt Technology Journal, 17, 3, pp. 11-16, (1999); Gunasekaran A., Marri H.B., McCaughey R.E., Nebhwani M.D., E-commerce and its impact on operations management, Int. J. Production Economics, 75, pp. 185-197, (2002); Turban E., Leidner D., McLean E., Wetherbe J., Information Technology For Management, (2006); Ngai E.W.T., Wat F.K.T., A literature review and classification of electronic commerce research, Information & Management, 39, pp. 415-429, (2002); Hesse M., Shipping news: The implications of electronic commerce for logistics and freight transport, Resources, Conservation and Recycling, 36, pp. 211-240, (2002); Brookes M., Wahhaj Z., The Shocking Economic Effect of B2B, Goldman Sachs Global Economics, Paper, 37, (2000); Reynolds J., E-commerce - a critical review, International Journal of Retail and Distribution Management, 28, 10, pp. 417-444, (2000); Matthews H., Hendrickson C., Lave L., Harry Potter and the hole in the ozone layer, While Online Shopping May Appear to Cause Less Impact On the Environment Than Driving to the Mall, The Net Effect of E-commerce Remains Unclear, (2000); Nieuwe Wijn In Oude Zakken, (2003); Fassa S., Tsitsamis D., Container terminal information management system of the port of Thessaloniki, IT&T Solutions In Logistic and Maritime Applications, pp. 77-85, (2006); Backstrom R., Portnet - a National Maritime Logistic Information Hub, pp. 95-102, (2006); Commercial Development of Regional Ports As Logistics Centers, (2002); Review of Maritime Transport, Chapter Vi, Geneva, (1999); Study On the Use of Information Technology In Small Ports, (2001); Unedocs Project, (2005); Schroth C., Janner T., Stuhec G., UN/CEFACT Service-Oriented Architecture Enabling Both Semantic and Application Interoperability, Un/cefact Publication, (2006); Blueprint For a Virtual Port, (2002); Study For the Development of A Digital Trade and Transportation Network (dttn) System to Support the Development of Hong Kong As An International Logistics Hub, (2002); Greenstein M., Electronic Commerce: Security Risk Management and Control (New York: Mcgraw-hill), (2000); Pathak J., A conceptual risk framework for internal auditing in e-commerce, Managerial Auditing Journal, 19, 4, pp. 556-564, (2004); Ngai E.W.T., Wat F.K.T., Fuzzy decision support system for risk analysis in e-commerce development, Decision Support Systems, 40, pp. 235-255, (2005)","S. Rouhani; Iran's University of Science and Technology, Narmak, Tehran, Iran; email: srouhani@iust.ac.ir",{"$nulls":7},1.4645254E7,null,null,null,"English","Marit. Policy Manage.","Article","Final",null,"Scopus","2-s2.0-74949100733"]
["Su C.-J.; Chuang H.-C.","Su, Chuan-Jun (36553317500); Chuang, Hsin-Chi (36105700700)","36553317500; 36105700700","Toward mass customized product deployment in e-commerce: The modularization function and postponement strategy",2011.0,"Journal of Organizational Computing and Electronic Commerce",21.0,1.0,null,24.0,49.0,25.0,1.0,"10.1080/10919392.2011.541000","https://www.scopus.com/inward/record.uri?eid=2-s2.0-79551558832&doi=10.1080%2f10919392.2011.541000&partnerID=40&md5=0656c9a21304bd6ab0dfca3d4b3732bc","Department of Industrial Engineering and Management, Yuan Ze University, Jhongli City, Taoyuan, 320, No.135 Yuandong Rd., Taiwan","Su C.-J., Department of Industrial Engineering and Management, Yuan Ze University, Jhongli City, Taoyuan, 320, No.135 Yuandong Rd., Taiwan; Chuang H.-C., Department of Industrial Engineering and Management, Yuan Ze University, Jhongli City, Taoyuan, 320, No.135 Yuandong Rd., Taiwan","Strategically deploying customized products in an e-commerce environment not only helps businesses respond with greater agility to customer needs and strengthen their market position, but also helps businesses gain competitive edge and increase profitability. Underlying successful mass customization within the digital marketplace, a firm needs a methodology for striking a balance between the degree of customization and product pricing and delivery time-a critical supply chain issue. Providing either too much or too little customization can negatively impact both the business and the customer. This study introduces a decision-making method for product customization. This method takes into account the level of customization, production costs, and the product delivery time and applies the concept of postponement strategy to the product supply chain to boost overall supply chain effectiveness and customer satisfaction. Bicycle customization is used as an example to demonstrate the feasibility of the new approach to determine the optimal level of customization in product deployment. © Taylor & Francis Group, LLC.","Customer order decoupling point (codp); E-commerce; Mass customization; Postponement strategy; Product deployment",{"$nulls":7},"Anderson B., Hagen C., Reifel J., Stettler E., Complexity: Customization's evil twin, Strategy & Leadership, 34, 5, pp. 19-27, (2006); Lee H.L., Billington C., Carter B., Hewlett-Packard gains control of inventory and service through design for location, Interfaces, 23, pp. 1-11, (1993); Ballou R.H., Business Logistics Management, (1999); Yang B., Burns N.D., Backhouse C.J., Postponement: A review and an integrated ramework, International Journal of Operations & Production Management, 24, 5, pp. 468-487, (2004); Feitzinger E., Lee H., Mass customization at Hewlett-Packard: The power of postponement, Harvard Business Review, 75, 1, pp. 116-121, (1997); Pine B.J., Mass Customization- the New Frontier In Business Competition, (1993); Mikkola J.H., Gassmann O., Managing modularity of product architectures: Toward an integrated theory, IEEE Transactions On Engineering Management, 50, 2, pp. 204-218, (2003); Stan D., Future Perfect, 10th Anniversary Edition, (1996); Kaplan A.M., Haenlein M., Toward a parsimonious definition of traditional and electronic mass customization, Journal of Product Innovation Management, 23, 2, pp. 168-182, (2006); Chase R.B., Jacobs F.R., Aquilano N.J., Operations Management For Competitive Advantage, (2006); Mikkola J.H., Management of product architecture modularity for mass customization: Modeling and theoretical considerations, IEEE Transactions On Engineering Management, 54, 1, pp. 27-69, (2007); Alderson W., Marketing efficiency and the principle of postponement, Cost and Profit Outlook, 3, 4, pp. 15-18, (1950); Zinn W., Bowersox D.J., Planning physical distribution with the principle of ostponement, International Journal of Business Logistics, 9, 2, pp. 117-136, (1988); Graman G.A., Bukovinsky D.M., From mass production to mass customization: Postponement of inventory differentiation, The Journal of Corporate Accounting & Finance, 17, 1, pp. 61-65, (2005); Bucklin L.P., Postponement, speculation and the structure of distribution channels, Journal of Marketing Research, 2, pp. 26-32, (1965); Droge C., Germain R., Spears N., Form postponement as a strategic initiative affecting organizational design, Proceedings of the American Marketing Association Educators' Conference, pp. 263-269, (1995); The Challenge of Managing Continuous Change, (1995); Huang Y.Y., Li S.J., Suitable application situations of different postponement approaches: Standardization vs. modularization, Journal of Manufacturing Systems, 27, 3, pp. 111-122, (2008); Aviv Y., Federgruen A., Design for postponement: A comprehensive characterization of its benefits under unknown demand distributions, Operations Research, 49, 4, pp. 578-598, (2001); Ernst R., Kamrad B., Evaluation of supply chain structures through modularization and postponement, European Journal of Operational Research, 124, pp. 495-510, (2000); Ma S., Wang W., Liu L., Commonality and postponement in multistage assembly systems, European Journal of Operational Research, 142, 3, pp. 523-538, (2002); Lee H.L., Tang C.S., Modeling the costs and benefits of delay product differentiation, Management Science, 43, 1, pp. 40-54, (1997); Brun A., Zorzini M., Evaluation of product customization strategies through modularization and postponement, International Journal of Production Economics, 120, 1, pp. 205-220, (2009); Su J.C., Chang Y.L., Ferguson M., Evaluation of postponement structures to accommodate mass customization, Journal of Operations Management, 23, 4, pp. 305-318, (2005); Yang B., Burns N., Backhouse C.J., Management of uncertainty through postponement, International Journal of Production Research, 42, 6, pp. 1049-1064, (2004); Yang B., Yang Y., Wijngaard J., Postponement: An inter-organizational perspective, International Journal of Production Research, 45, 4, pp. 971-988, (2007); Olhager J., Strategic positioning of the order penetration point, International Journal of Production Economics, 85, pp. 319-329, (2003); Rudberg M., Wikner J., Mass customization in terms of the customer order decoupling point, Production Planning & Control, 15, 4, pp. 445-458, (2004); Fan Z.Q., Zhuang J.F., Chen J.S., Research for postponed production based on supply chain, Storage, Transportation & Preservation of Commodities, 27, 3, pp. 19-21, (2005); Yang B., Burns N.D., The implications of postponement for the supply chain, International Journal of Production Research, 41, 9, pp. 2075-2090, (2003); Vollmann J., Breu R., Dual J., High-resolution analysis of the complex wave spectrum in a cylindrical shell containing a viscoelastic medium. Part II. Experimental results versus theory, International Journal of the Acoustical Society of America, 102, 2, pp. 909-920, (1997); Graman G.A., A partial-postponement decision cost model, European Journal of Operational Research, 201, 1, pp. 34-44, (2010); Leung S.C.H., Ng W.L., A goal programming model for production planning of perishable products with postponement, Computers & Industrial Engineering, 53, 3, pp. 531-541, (2007); Li J., Wang S., Cheng T.C.E., Analysis of postponement strategy by EPQ-based models with planned backorders, Omega, 36, 5, pp. 777-788, (2008); Swaminathan J.M., Lee H.L., Design for postponement, Handbooks In Operations Research and Management Science, 11, pp. 199-226, (2003); Hoek V., Remko I., The rediscovery of postponement: A literature review and directions for research, International Journal of Operations Management, 11, pp. 161-184, (2001); Wikner J., Rudberg M., Integrating production and engineering perspectives on the customer order decoupling point, International Journal of Operations & Production Management, 25, 7, pp. 623-641, (2005); Hau L., Billington C., Designing products and processes for postponement, Management of Design: Engineering and Management Perspectives, pp. 105-122, (1994); Dewan R., Jing B., Seidmann A., Adoption of Internet-based product customization and pricing strategies, Journal of Management Information Systems, 17, 2, pp. 9-28, (2000); Chang H., Easley R.F., Shaw M.J., Market model-based channel selection in B2B E-commerce: Exploring a buyer's adoption decisions, Journal of Organizational Computing and Electronic Commerce, 19, 4, pp. 237-264, (2009); Goldsby T.J., Garcia-Dastugue S.J., The manufacturing flow management process, International Journal of Logistics Management, 14, 2, pp. 33-52, (2003); Lee H.L., Padmanabhan V., Whang S., Information distortion in a supply chain: The bullwhip effect, Management Science, 43, 4, pp. 546-558, (1997); Pekkarinen S., Modularity in developing business services by platform approach, The International Journal of Logistics Management, 19, 1, pp. 84-103, (2008); Peters L., Saidin H., IT and the mass customization of services: The challenge of mplementation, International Journal of Information Management, 20, 2, pp. 103-119, (2000)","C.-J. Su; Department of Industrial Engineering and Management, Yuan Ze University, Jhongli City, Taoyuan, 320, No.135 Yuandong Rd., Taiwan; email: iecjsu@saturn.yzu.edu.tw",{"$nulls":7},1.0919392E7,null,null,null,"English","J. Org. Comput. Electr. Commer.","Article","Final",null,"Scopus","2-s2.0-79551558832"]
["Kim J.S.; Ratchford T.B.","Kim, Jung Seek (57061664100); Ratchford, T. Brian (6601908752)","57061664100; 6601908752","Consumer choice and use of multiple information sources for automobile purchases",2012.0,"International Journal of Electronic Commerce",16.0,3.0,null,7.0,40.0,33.0,28.0,"10.2753/JEC1086-4415160301","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84859065596&doi=10.2753%2fJEC1086-4415160301&partnerID=40&md5=e6d934c8a85e4cde1ba5bbcd1e5f363e","Department of Marketing, School of Business, Edinboro University of Pennsylvania, United States; Department of Marketing, School of Management, University of Texas, Dallas, United States","Kim J.S., Department of Marketing, School of Business, Edinboro University of Pennsylvania, United States; Ratchford T.B., Department of Marketing, School of Management, University of Texas, Dallas, United States","People consult various sources, including the Internet, to search for information before purchasing an automobile. We develop an econometric model for a consumer's time allocation over multiple information sources. The process of searching is viewed as a formal choice problem in which the consumer attempts to choose the amount of search from multiple sources to maximize the benefit of purchase net of search cost. Observed data on time allocation over representative sources are postulated to arise from this optimizing behavior, and the proposed econometric model is calibrated to four waves of survey data from buyers of new automobiles, covering purchases made in 1999, 2001, 2003, and 2005. Consistent with the requirement that buyers must complete the transaction and obtain delivery at dealerships, we find that, on average, the baseline preference for sources is the highest for dealer-related activities. However, we also find that the share of time devoted to the Internet increases considerably with overall search time. In particular, we find that more educated buyers under age 40 who search extensively are likely to rely heavily on the Internet in their search. This indicates that the Internet has become the key medium for manufacturers and dealers who are targeting younger, more educated buyers. © 2012 M.E. Sharpe, Inc. All rights reserved.","Automobile market; business-to-consumer e-commerce; consumer information search; discrete-continuous choice model; economics of information; limited dependent variable",{"$nulls":7},"Becker G., Human Capital, (1993); Bettman J.R., Luce M.F., Payne J.W., Constructive consumer choice processes, Journal of Consumer Research, 25, 3, pp. 83-93, (1998); Bhat C.R., A multiple discrete-continuous extreme value model: Formulation and application to discretionary time-use decisions, Transportation Research Part B: Methodological, 39, 8, pp. 679-707, (2005); Chu W., Choi B., Song M.R., The role of on-line retailer brand and infomediary reputation in increasing consumer purchase intention, International Journal of Electronic Commerce, 9, 3, pp. 115-127, (2005); Claxton J.D., Fry J.N., Portis B., A taxonomy of purchase information gathering patterns, Journal of Consumer Research, 1, 3, pp. 35-42, (1994); Erdem T., Keane M., Oncu T., Strebel J., Learning about computers: An analysis of information search and technology choice, Quantitative Marketing and Economics, 3, 3, pp. 207-247, (2005); Furse D.H., Punj G.N., Stewart D.W., Typologies of individual search strategies among purchasers of new automobiles, Journal of Consumer Research, 10, 4, pp. 417-431, (1984); Gupta A., Su B.-C., Walter Z., An empirical study of consumer switching from traditional to electronic channels: A purchase-decision process perspective, International Journal of Electronic Commerce, 8, 3, pp. 131-161, (2004); Hauser J., Urban G., Weinberg B., How consumers allocate their time when searching for information, Journal of Marketing Research, 30, 4, pp. 452-466, (1993); Power J.D., New Autoshopper.com Study, (2004); Power J.D., New Autoshopper.com Study, (2008); Kerin R.A., Hartley S.W., Rudelius W., Marketing, (2009); Kiel G.C., Layton R.A., Dimensions of consumer information seeking behavior, Journal of Marketing Research, 18, 2, pp. 233-239, (1981); Kim J., Allenby G.M., Rossi P., Modeling consumer demand for variety, Marketing Science, 21, 3, pp. 229-250, (2002); Kim J., Allenby G.M., Rossi P.E., Product attributes and models of multiple discreteness, Journal of Econometrics, 138, 1, pp. 208-230, (2007); Klein L.R., Ford G.T., Consumer search for information in the digital age: An empirical study of prepurchase search for automobiles, Journal of Interactive Marketing, 17, 3, pp. 29-49, (2003); Marmorstein H., Grewal D., Fishe R.P.H., The value of time spent in price comparison shopping, Journal of Consumer Research, 19, 1, pp. 52-61, (1992); McFadden D., Train K., Mixed MNL models of discrete response, Journal of Applied Econometrics, 15, 5, pp. 447-470, (2000); Moorthy K.S., Ratchford B.T., Talukdar D., Consumer information search revisited: Theory and empirical analysis, Journal of Consumer Research, 23, 4, pp. 263-277, (1997); Pollak R.A., Wales T.J., Demand System Specification and Estimation, (1992); Ratchford B.T., Lee M., Talukdar D., The impact of the Internet on search for automobiles, Journal of Marketing Research, 40, 2, pp. 193-209, (2003); Ratchford B.T., Talukdar D., Lee M.-S., A model of consumer choice of the internet as an information source, International Journal of Electronic Commerce, 5, 3, pp. 7-21, (2001); Ratchford B.T., Talukdar D., Lee M., The impact of the Internet on consumers' use of information sources for automobiles: A re-inquiry, Journal of Consumer Research, 34, 1, pp. 111-119, (2007); Strebel J., Erdem T., Swait J., Consumer Search in High Technology Markets: Exploring the Use of Traditional Information Channels, Journal of Consumer Psychology, 14, 1-2, pp. 96-104, (2004); Su B., Characteristics of consumer search on-line: How much do we search?, International Journal of Electronic Commerce, 13, 1, pp. 109-129, (2008); Walter Z., Gupta A., Su B.-C., The sources of on-line price dispersion across product types: An integrative view of on-line search costs and price premiums, International Journal of Electronic Commerce, 11, 1, pp. 37-62, (2006); Westbrook R.A., Fornell C., Patterns of information source usage among durable goods buyers, Journal of Marketing Research, 16, 3, pp. 303-312, (1979); Zettelmeyer F., Morton F.S., Silva-Risso J., How the internet lowers prices: Evidence from matched survey and automobile transaction data, Journal of Marketing Research, 43, 2, pp. 168-181, (2006)","J.S. Kim; Department of Marketing, School of Business, Edinboro University of Pennsylvania, United States; email: jskim@edinboro.edu",{"$nulls":7},1.0864415E7,null,null,null,"English","Int. J. Elect. Commer.","Article","Final",null,"Scopus","2-s2.0-84859065596"]
["Mǎrunţelu I.A.","Mǎrunţelu, Irina Albǎstroiu (55600190700)",5.56001907E10,"The particularities of logistics related to e-commerce; [Particularitǎţile logisticii în comerţul electronic]",2008.0,"Amfiteatru Economic",10.0,24.0,null,177.0,191.0,14.0,7.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-69249131217&partnerID=40&md5=53859f16c1be14383394f0e68e692304","Academia de Studii Economice din Bucureşti, Romania","Mǎrunţelu I.A., Academia de Studii Economice din Bucureşti, Romania","The gains related the productiveness and efficiency generated by the e-commerce on the economy ensemble are so promising so that practically any attempt to ignore this new channel of business life development would be against productiveness. The companies must accelerate the incorporation of the new informational technologies in business strategies, and in their logistics activities, because, at present, this seems to be the most efficient solution for the rendering more valuable the advantages of the present globalization wave. The structural and functional organization of logistics related to electronic commerce has to comply with the requirements imposed by the particularities of this modern form of commerce and adapt to a specific model of electronic commerce and to the characteristics of products and services transacted through Internet This article presents the function and specific characteristics of the logistics system related to electronic commerce. Thus this article aims to present the essential differences between the logistics activities required by the electronic commerce and traditional form of commerce based on the characteristics and trends of e-commerce and the impact of innovations supported by the electronic commerce upon transactional processes. The article emphasizes the difference between specific models of electronic commerce in terms of the ratio product value/transportation expenses and the complexity of inventory.","Delivery; Electronic commerce; Inventory; Logistics system; Transport",{"$nulls":7},"Deborah B., E-commerce logistics and fulfillment: delivering the goods, (2001); Dantuma L.M.Y., Hawkins R.W., E-commerce in the logistics sector. Assessing the effects on the logistics value chain, (2001); Vasile F., Valentin D., Comerţul electronic şi impactul organizaţional, (2007); Robert W., Birgit L., Mark L., Annie L., Corporate and brand web sites as customer relationship management tools: an overview of alternative approaches, Journal of Relationship Marketing, 3, 1, (2004)","I.A. Mǎrunţelu; Academia de Studii Economice din Bucureşti, Romania; email: irina_albastroiu@yahoo.com",{"$nulls":7},1.5829146E7,null,null,null,"Romanian","Amfiteatru Econ.","Article","Final",null,"Scopus","2-s2.0-69249131217"]
["Gunasekaran A.; Kobu B.","Gunasekaran, Angappa (56238759300); Kobu, Bulent (6507461108)","56238759300; 6507461108","Performance measures and metrics in logistics and supply chain management: A review of recent literature (1995-2004) for research and applications",2007.0,"International Journal of Production Research",45.0,12.0,null,2819.0,2840.0,21.0,571.0,"10.1080/00207540600806513","https://www.scopus.com/inward/record.uri?eid=2-s2.0-34247887551&doi=10.1080%2f00207540600806513&partnerID=40&md5=45fc00d86a29736472b3fff955276a89","University of Massachusetts Dartmouth, United States","Gunasekaran A., University of Massachusetts Dartmouth, United States; Kobu B., University of Massachusetts Dartmouth, United States","Performance measures and metrics are essential for effectively managing logistics operations, particularly in a competitive global economy. The global economy is featured with global operations, outsourcing and supply chain and e-commerce. The real challenge for managers of this new enterprise environment is to develop suitable performance measures and metrics to make right decisions that would contribute to an improved organizational competitiveness. Now the question is whether traditional performance measures can be used and out of them which ones should be given priority for measuring the performance in a new enterprise environment. Some of the traditional measures and metrics may not be suitable for the new environment wherein many activities are not easily identifiable. Measuring intangibles and nonfinancial performance measures pose the greater challenge in the so-called knowledge economy. Nevertheless, measuring them is so critical for the successful operations of companies in this environment. Considering the importance of nonfinancial measures and intangibles, an attempt has been made in this paper to determine the key performance measures and metrics in supply chain and logistics operations. This is based on a literature survey and some of the reported case experiences. Suggestions for future research directions are also indicated.","Logistics; Metrics; Performance measures; Supply chain","Competitive intelligence; Electronic commerce; Industrial research; Metric system; Supply chain management; Supply chains; Knowledge economy; Logistics operations; Metrics; Logistics",{"$nulls":6},"Bagchi P.K., Role of benchmarking as a competitive strategy: The logistics experience, Int. J. Phys, Distrib. Log, 26, pp. 4-22, (1996); Basu R., New criteria of performance measurement, Meas. Bus. Excel, 5, 4, pp. 7-12, (2001); Beamon B.M., Measuring supply chain performance, Int. J. Oper. Prod. Manag, 19, pp. 275-292, (1999); Bechtel C., Jayaram J., Supply chain management: A strategic perspective, Int. J. Log. Manag, 8, pp. 15-34, (1997); Bhatnagar R., Sohal A.S., Supply chain competitiveness: Measuring the impact of location factors, uncertainty and manufacturing practices, Technovation, 25, pp. 443-456, (2005); Bolstorff P., Measuring the impact of supply chain performance, Logistkstoday, 12, pp. 6-11, (2003); Chan F.T.S., Qi H.J., An innovative performance measurement method for supply chain management, Supply Chain Manage.: Int. J, 8, pp. 209-223, (2003); Chan F.T.S., Qi H.J., Feasibility of performance measurement system for supply chain: A process-based approach and measures, Integ. Manufact. Sys, 14, pp. 179-190, (2003); Christopher M., Logistics - Key Competitive Advantage, Supply Chain World Class Best Practice, (1999); Collins III T.J., Harris G.I., Productivity measurement: A shifting paradigm in purchasing, NAPM Insights, 2, pp. 10-11, (1992); Cooke J.A., Want real collaboration? Change your measures, Log. Manag, 42, 1, pp. 37-40, (2003); De Toni A., Tonchia S., Performance measurement systems, Int. J. Oper. Prod. Manag, 21, pp. 46-70, (2001); Dumond E.J., Applying value-based management to procurement, Int. J. Phys. Distrih. Log, 26, pp. 5-24, (1996); Fitzgerald L., Johnston R., Brignall S., Silvestro R., Voss C., Performance Measurement in Service Business, (1991); Folan P., Browne J., A review of performance measurement: Towards performance management, Comp. Indus, 56, pp. 663-680, (2005); Fynes B., Voss C., Burca D.S., The impact of supply chain relationship quality on quality performance, Int. J. Prod. Econom, 96, pp. 339-354, (2005); Garvin D.A., Competing on the eight dimensions of quality, Harvard Bus. Rev, 65, pp. 101-109, (1987); Giachetti R.E., Martinez L.D., Saenz O.A., Chen C.-S., Analysis of the structural measures of flexibility and agility using a measurement theoretical framework, Int. J. Prod. 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Account, 67, pp. 32-33, (1989); Mattila H., King R., Ojala N., Retail performance measures for seasonal fashion, J. Fashion Market. Manag, 6, pp. 340-351, (2002); McAdam R., McCormack D., Integrating business processes for global alignment and supply chain management, Bus. Proc. Manag, 7, pp. 113-130, (2001); McIntyre K., Smith H., Henham A., Pretlove J., Environmental performance indicators for integrated supply chain: The case of Xerox Ltd, Supply Chain Manag, 3, pp. 149-156, (1998); Morita M., Flynn E.J., The linkage among management systems, practices, and behavior in successful manufacturing strategy, Int. J. Oper. Prod. Manag, 17, pp. 967-993, (1997); Neely A., Gregory M., Platts K., Performance measurement system design, Int. J. Oper. Prod. Manag, 15, pp. 80-116, (1995); Parker C., Performance measurement, Work Study, 49, pp. 63-66, (2000); Plant R., Willcocks L., Olson N., Measuring e-business performance: Towards a revised balanced scorecard approach, Inform. Sys. e-Busi. Manag, 1, pp. 265-281, (2003); Poon W.K., Lau K.H., Value challenges in supply chain management, Log. Inform. Manag, 13, pp. 150-155, (2000); Porter M.E., Competitive Advantage: Creating and Sustaining Superior Performance, (1985); Richardson H.L., score K., Transport. Distrib, 41, pp. 63-66, (2000); Rudberg M., Klingenberg N., Kronhamn K., Collaborative supply chain planning using electronic marketplaces, Integ. Manufact. Sys, 13, pp. 596-610, (2002); Said A.A., Hassabelnaby H.R., Wier B., An empirical investigation of the performance consequences of nonfinancial measures, J. Manag. Account. Res, 15, pp. 193-223, (2003); Scapens R.W., Management accounting and strategic control, implications for management accounting research, Bedriffskunde, 70, pp. 11-17, (1998); Schonberger R.J., Creating a Chain of Customer, (1990); Skinner W., The productivity paradox, Harvard Busi. Rev, 64, pp. 55-59, (1986); Slack N., The Manufacturing Advantage: Achieving Competitive Manufacturing Operations, (1991); Spekman R.E., Kamauff Jr J.W., Mhyr N., An empirical investigation into supply chain management: A perspective on partnership, Supply Chain Manag, 3, pp. 53-67, (1998); Stalk G., Time- the next source of competitive advantage, Harvard Bus. Rev, 66, pp. 41-51, (1988); Stevens J., Integrating the supply chain, Int. J. Phys. Distrib. Mater. Manage, 19, pp. 3-8, (1989); Stewart G., Supply chain performance benchmarking study reveals keys to supply chain excellence, Log. Inform. Manag, 8, pp. 38-44, (1995); World Class Logistics, (1995); van Donselaar K., Kokke K., Allessie M., Performance measurements in the transportation and distribution sector, Int. J. Phys. Distrib. Log. Manag, 28, pp. 434-450, (1998); Van Hoek R.I., Measuring and improving performance in the supply chain, Supply Chain Manag, 3, pp. 187-192, (1998); van Landeghem R., Persoons K., Benchmarking of logistical operations based on a causal model, Int. J. Oper. Prod. Manag, 21, pp. 254-266, (2001); Weber M.M., Measuring supply chain agility in the virtual organizations, Int. J. Phys. Distrib. Log. Manag, 32, pp. 577-590, (2002); Wisner J.D., Fawcett S.E., Linking firm strategy to operating decisions through performance measurement, Prod. Invent. Manag. J, 32, pp. 5-11, (1991)","A. Gunasekaran; University of Massachusetts Dartmouth, United States; email: agunasekaran@umassd.edu",{"$nulls":7},"1366588X",null,"IJPRB",null,"English","Int J Prod Res","Article","Final",null,"Scopus","2-s2.0-34247887551"]
["Gunasekaran A.; Ngai E.W.T.; Cheng T.C.E.","Gunasekaran, A. (56238759300); Ngai, E.W.T. (7003298974); Cheng, T.C.E. (57977788500)","56238759300; 7003298974; 57977788500","Developing an e-logistics system: a case study",2007.0,"International Journal of Logistics Research and Applications",10.0,4.0,null,333.0,349.0,16.0,43.0,"10.1080/13675560701195307","https://www.scopus.com/inward/record.uri?eid=2-s2.0-54349094533&doi=10.1080%2f13675560701195307&partnerID=40&md5=81369c71b6476a7695b3fbe091105e70","Department of Management, University of Massachusetts–Dartmouth, North Dartmouth, 02747-2300, MA, United States; Department of Management and Marketing, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong; Department of Logistics, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong","Gunasekaran A., Department of Management, University of Massachusetts–Dartmouth, North Dartmouth, 02747-2300, MA, United States; Ngai E.W.T., Department of Management and Marketing, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong; Cheng T.C.E., Department of Logistics, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong","Third-party logistics (3PL), a relatively new industry, has gained momentum since the emergence of global market and the Internet, in particular electronic commerce (e-commerce). Global competitive-ness places more pressure on companies to improve their delivery performance of products and services to customers. In an effort to improve the quality of delivery service, companies have outsourced their logistics services, including packing, warehousing (inventory management) and shipping of goods to customers. Communication plays an important role in integrating the activities along the logistics value chain. Information technologies such as electronic data interchange (EDI), the Internet, World Wide Web (WWW) and e-commerce have contributed greatly to improving communication with partners in the logistics chain. In particular, real-time information systems such as web-based logistics information systems help to improve 3PL services. In this paper, a case study of e-logistics is used to illustrate the implications of information technology, in particular the Internet, WWW and EDI, on the performance of the logistics value chain. A framework based on the literature survey and case study is proposed to help companies develop an e-logistics system to improve their competitiveness. © 2007, Copyright Taylor & Francis Group, LLC.","Case study; E-logistics; Framework",{"$nulls":5},"University of Massachusetts, UMASS; Hong Kong Polytechnic University, PolyU, (A632)","The authors are grateful to anonymous reviewers and the Editor-in-Chief, Professor Kulwant Singh Pawar, for their constructive and helpful comments on the earlier version of this manuscript, which helped to improve the presentation of the paper considerably. The authors are most grateful to the Chief Operating Officer, Mr Edmon Fung, the Managing Director, Mr Johnny Leung, and several senior managers of ecL for providing the necessary information for this case study research. This research was supported in part by the University of Massachusetts–Dartmouth (USA) and The Hong Kong Polytechnic University under grant number A632.","Aldin N., Stahre F., Electronic commerce, marketing channels and logistics platforms–a wholesaler perspective, Eur. J. Operational Res., 144, pp. 270-279, (2003); Alshawi S., Logistics in the Internet age: towards a holistic information and processes picture, Logistics Inf. Mgmnt., 14, pp. 235-241, (2001); Calza F., Passaro R., EDI network and logistics management at Unilver-Sagit, Supply Chain Mgmnt., 2, pp. 158-170, (1997); Chiu H.N., The integrated logistics management system: a framework and case study, Int. J. Physical Distrib. Logistics Mgmnt., 25, pp. 4-22, (1995); Clarke M.P., Virtual logistics: an introduction and overview of the concepts, Int. J. Physical Distrib. Logistics Mgmnt., 28, pp. 486-507, (1998); Damsgaard J., Global logistics system Asia Co., Ltd, J. Inf. Technol., 14, pp. 303-314, (1999); Dawe R.L., An investigation of the pace and determination of information technology use in the manufacturing materials logistics system: a case study of Northern California’s electronic manufacturers, J. Business Logistics, 15, pp. 229-259, (1994); Delfman W., Albers S., Gehring M., The impact of electronic commerce on logistics service providers, Int. J. Physical Distrib. Logistics, 32, pp. 203-222, (2002); Feraud G.J.S., Improving strategic decision making in logistics information management–a framework, Logistics Inf. Mgmnt., 11, pp. 232-243, (1998); Gibson B.J., Cook R.L., Hiring practices in US third-party logistics firms, Int. J. Physical Distrib. Logistics Mgmnt., 31, pp. 714-732, (2001); Graham G., Hardaker G., Supply chain management across the Internet, Int. J. Physical Distrib. Logistics Mgmnt., 30, pp. 286-295, (2000); Gudmundsson S.V., Walczuck R., The development of electronic markets in logistics, Int. J. Logistics Mgmnt., 10, pp. 99-113, (1999); Gunasekaran A., Ngai E.W.T., The successful management of a small logistics company, Int. J. Physical Distrib. Logistics Mgmnt., 33, pp. 825-837, (2003); Gunasekaran A., Ngai E.W.T., Virtual supply chain management, Prod. Planning Control, 15, pp. 582-596, (2004); Gunasekaran A., Ngai E.W.T., 3PL: experiences from China Resources Logistics (Hong Kong), Int. J. Logistics Syst. Mgmnt., 1, pp. 81-111, (2004); Hesse M., Shipping news: the implications of electronic commerce for logistics and freight transport, Resources, Conservation Recycling, 36, pp. 211-240, (2002); Leung L.C., Cheung W.M., Van Hui Y., A framework for a logistics e-commerce community network: the Hong Kong air cargo industry, IEEE Trans. Syst. Man Cybernet. Part A, 30, pp. 446-455, (2000); Liao Z.Q., Cheung M.T., Internet-based e-shopping and consumer attitudes: an empirical study, Inf. Mgmnt., 38, pp. 299-306, (2001); Ligon G.C., Schill R.L., O'Donnel P.F., Technology strategy: EDI and global air express, Int. J. Physical Distrib. Logistics Mgmnt., 22, pp. 43-48, (1992); Martinsons M.G., Electronic commerce in China: emerging success stories, Inf. Mgmnt., 39, pp. 571-579, (2002); McFarlan F.W., Information technology changing the way you compete, Harvard Business Rev., 57, pp. 115-126, (1984); Ngai E.W.T., Wat F.K.T., A literature review and classification of electronic commerce research, Inf. Mgmnt., 39, pp. 415-429, (2002); Rao K., Young R.R., Novick J.A., Third-party services in the logistics in the logistics of global firms, Logistics Transport. Rev., 29, pp. 363-370, (1993); Schary P.B., Coakley J., Logistics organization and the information system, Int. J. Logistics Mgmnt., 2, pp. 22-29, (1991); Strader T.J., Lin F.-R., Shaw M.J., Information infrastructure for electronic virtual organization management, Decision Support Syst., 25, pp. 75-94, (1998); Stratton F., Recognizing 3PL excellence, Inbound Logistics, 21, pp. 43-46, (2001); Sum C.C., Teo C.B., Ng K.K., Strategic logistics management in Singapore, Int. J. Operations Prod. Mgmnt., 21, pp. 1239-1260, (2001); Tarantilis C.D., Kiranoudis C.T., Using a spatial decision support system for solving the vehicle routing problem, Inf. Mgmnt., 39, pp. 359-375, (2002); van Hoek R.I., Epilogue: UPS logistics–practical approaches to the e-supply chain, Int. J. Physical Distrib. Logistics, 31, pp. 463-468, (2001)","A. Gunasekaran; Department of Management, University of Massachusetts–Dartmouth, North Dartmouth, 02747-2300, United States; email: agunasekaran@umassd.edu",null,"Taylor and Francis Ltd.",{"$nulls":5},1.3675567E7,null,null,null,"English","Int. J. Logist. Res. Applic.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-54349094533"]
["Paul J.; Trehan R.","Paul, Justin (36997235800); Trehan, Ruchi (53464374000)","36997235800; 53464374000","Enhancing customer base and productivity through e-delivery channels - Study of banks in India",2011.0,"International Journal of Electronic Marketing and Retailing",4.0,"2024-03-02",null,151.0,164.0,13.0,8.0,"10.1504/IJEMR.2011.043045","https://www.scopus.com/inward/record.uri?eid=2-s2.0-80054104476&doi=10.1504%2fIJEMR.2011.043045&partnerID=40&md5=8777d40e534b24a978f7f460c7ee35f9","Nagoya University of Commerce and Business, Naka-ku, Nagoya City, Aichi, 1-20-1, Nishiki, Japan; Apeejay College of Fine Arts, Jalandhar 144001, Punjab, Mahavir Marg, India","Paul J., Nagoya University of Commerce and Business, Naka-ku, Nagoya City, Aichi, 1-20-1, Nishiki, Japan; Trehan R., Apeejay College of Fine Arts, Jalandhar 144001, Punjab, Mahavir Marg, India","The process of globalisation has affected each and every aspect of life where technology has become the predecessor of this dynamic change. There is certainly a high level of importance attached to technology. In the new millennium with the rapidly changing economic scene owing to emergence of e-commerce facilitated by the growth and expansion of internet and information technology, banking scenario and financial activity everywhere is changing rapidly. The main objective of the present study is to analyse the impact of technology on bank customers using e-delivery channels. This paper takes into account all the technological initiatives by banks as part of their channel diversification strategy. Further, we describe the extent to which these developments have taken place in the banking industry with special reference to India. The results show that public sector banks have the least average increase of customers as compared to other bank groups. The employee, branch and total productivity index has shown an increase in all bank groups, but on the other hand financial productivity index has shown a decline in new private sector bank groups. On the basis of analysis, an effort has been made to foresee the future of e-delivery channels in banks. Copyright © 2011 Inderscience Enterprises Ltd.","Banking sector; Channels; e-banking; e-delivery; India; Performance and customer base; Productivity",{"$nulls":7},"Aggarwal A.K., Singh D., Chaturvedi N., 2008) 'India's banking sector - Consolidation and convergence: Balancing on the brink?, Punjab Journal of Business Studies, October-March, 3, 2, pp. 39-46, (2007); Avasthi G.P., Sharma M., Information technology in banking: Challenges for regulators, Prajanan, 29, 4, (2000); Bhasin N., Indian Financial System (Reforms, Policies & Prospects, (2004); Bhattacharya B., Sinha T.N., Microeconomic determinants of asset quality of Indian public sector banks: A recursive VAR approach, The ICFAI Journal of Bank Management, 7, 1, pp. 20-40, (2008); Chopra V.K., Emerging Challenges, Strategies and Solutions in Indian Public Sector Banks, 23, 3, pp. 47-51, (2001); Husain F., Computerization and Mechanization in Indian Banks, (1988); Jain A.K., Jain P., Customer Satisfaction in retail banking services, NICE Journal of Business, 1, 2, pp. 95-102, (2006); Jalan B., Strengthening Indian banking and finance: Progress and prospects, IBA Bulletin, 25, 3, pp. 5-14, (2003); Janki B., Unleashing employee productivity: Need for a paradigm shift, Indian Banking Association Bulletin, 24, 3, pp. 7-9, (2002); Lal R.C., Banking transformation through IT in India, Journal of Commerce and Trade, 2, 2, pp. 46-48, (2007); Mittal R.K., Dingra S., Technology in banking sector: Issues & challenges, Vinimaya, 27, 4, pp. 14-22, (2007); Pathrose P.P., Hi-tech banking - Prospects and problem, IBA Bulletin, 23, 7, (2001); Paul J., Mukherjee A., Retail banking, ATMs and supply chain management in banking: A study of two banks, Prajnan, 35, 1, pp. 47-60, (2006); Sharma R.D., Kaur G., Sharma J., Customer delight a road to excellence for banks, NICE Journal of Business, 2, 2, pp. 1-12, (2007); Shastri R.V., Technology for banks in India-challenges, IBA Bulletin, 23, 3, (2001); Uppal R.K., Kaur R., Indian banking moving towards IT, Journal of Commerce and Trade, 2, 1, pp. 26-32, (2007); Vageesh N.S., New Private Banks: New Kids on the Block, (2000); Verma S., Saini R., Competition and market power in the Indian banking industry in the post reforms scenario, The ICFAI Journal of Bank Mgt., 7, 1, pp. 7-19, (2008)","J. Paul; Nagoya University of Commerce and Business, Naka-ku, Nagoya City, Aichi, 1-20-1, Nishiki, Japan; email: profjust@gmail.com",null,"Inderscience Publishers",{"$nulls":5},1.7411025E7,null,null,null,"English","Int. J. Electron. Mark. Retail.","Article","Final",null,"Scopus","2-s2.0-80054104476"]
["Stolz C.; Barth M.","Stolz, Carsten (56209925200); Barth, Michael (35399036500)","56209925200; 35399036500","Web site performance analysis success assessment of information driven web site on user traces",2007.0,"International Journal of Information Technology and Web Engineering",2.0,3.0,null,37.0,52.0,15.0,1.0,"10.4018/jitwe.2007070103","https://www.scopus.com/inward/record.uri?eid=2-s2.0-47349086949&doi=10.4018%2fjitwe.2007070103&partnerID=40&md5=5965c5d9e350b45170f4c4080391f96b","University of Eichstaett-Ingolstadt, Eichstaett, Germany; Department of Computer Science and Informatics, Ludwig-Maximilian-University, Munich, Germany","Stolz C., University of Eichstaett-Ingolstadt, Eichstaett, Germany; Barth M., Department of Computer Science and Informatics, Ludwig-Maximilian-University, Munich, Germany","Web metrics help to identify improvement potentials for web sites. In contrast to transaction based sites, the success of web sites geared toward information delivery is harder to quantify without direct feedback out of a transaction. We propose a generic success measure for information driven web sites by observing the users in context of the web site semantics. Thus we identify target pages, analyze the web page content and evaluate effectiveness and efficiency of the user actions with respect to the web site's objectives. The user's perspective has to be incorporated for a comprehensive success measure. We propose to integrate search queries from referrer information carrying the user's intentions. Out of an integrated web site meta model we derive formally a new success measure. This approach uses common data mining techniques and text mining algorithms like PLSA and shows its applicability in two case studies and an independent user enquiry. Copyright © 2007, IGI Global.","Business models; Clustering; Consumer-Web site interaction; Data mining algorithms; E-commerce models; Information and communications technologies; Knowledge discovery; Web authoring tools; Web site design","Semantics; Web crawler; Websites; Business models; Clustering; Consumer-Web site interaction; Data mining algorithm; E-commerce model; Information and communications technology; Web authoring; Web site design; Data mining",{"$nulls":6},"Baldi P., Frasconi P., Smyth P., Modeling the Internet and the Web - Probabillistic methods and algorithms, (2003); Barnard L., Wesson J.L., Usability issues for e-commerce in South Africa: An empirical investigation, Proceedings of SAICSIT 2003, pp. 258-267, (2003); Barth M., Skubacz M., Stolz C., Web performance indicator by implicit user feedback - Application and formal approach, Proceedings from the LNCS International Conference (WISE 2005), (2005); Barth M., Stolz C., Viermetz M., Wilde K.D., Searchstrings revealing user intent - A better understanding of user perception, (2006); Broder A., A taxonomy of Web search, SIGIR Forum, 36, 2, (2002); Cutler M., Sterne J., E-metrics business metrics for the new economy, (2000); Eirinaki M., Vazirgiannis M., Web mining for Web personalization, ACM Transactions on Internet Technology, 3, pp. 1-27, (2003); Hao J., Mendes E., Usage-based statistical testing of Web applications, Proceedings of the ICWE 2006, pp. 17-24, (2006); Heer J., Chi E.H., Separating the swarm: Categorization methods for user sessions on the Web, (2002); Hofmann T., Probabilistic latent semantic indexing, Proceedings of SIGIR 1999, pp. 50-57, (1999); Jacoby G.A., Luqi, Intranet model and metrics, Communications of the ACM, 50, 2, pp. 43-50, (2007); Jin X., Zhou Y., Mobasher B., Web usage mining based on probabilistic latent semantic analysis, Proceedings of ACM SIGKDD 2004, pp. 197-205, (2004); Lee U., Liu Z., Cho J., Automatic identification of user goals in Web search, Proceedings of ACM WWW Conference 2005, (2005); Pather S., Erwin G., Remenyi D., Measuring e-commerce effectiveness: A conceptual model, Proceeding's of SAICSIT 2003, pp. 143-152, (2003); Spiliopoulou M., Pohle C., Data mining for measuring and improving the success of Web sites, Journal for Data Mining & Knowledge Discoverv, 5, 1-2, pp. 85-114, (2001); Stolz C., Viermetz M., Skubacz M., Neuneier R., Guidance performance indicator - Web metrics for information driven Web sites, Proceedings of IEEE International. Conference Web Intelligence 2005, (2005); Viermetz M., Stolz C., Gedov V., Skubacz M., Relevance and impact of tabbed browsing behavior on Web usage mining, Web Intelligence 2006, (2006); Yeung W.L., Lu M., Functional characteristics of commercial Web sites: A Longitudinal, Information & Management Journal, 41, pp. 483-495, (2004); Zviran M., Glezer C., Avni I., User satisfaction from commercial Web sites: The effect of design and use, Information & Management Journal, (2005)",null,null,"IGI Publishing",{"$nulls":5},1.5541045E7,null,null,null,"English","Int. J. Inf. Technol. Web. Eng.","Article","Final",null,"Scopus","2-s2.0-47349086949"]
["Tan M.I.I.; Ibrahim I.S.","Tan, Mohd Iskandar bin Illyas (53263813400); Ibrahim, Iziati Saadah bt (36815815200)","53263813400; 36815815200","A survey on supply chain management and E-Commerce technology adoption among logistics service providers in Johor",2010.0,"World Academy of Science, Engineering and Technology",65.0,null,null,678.0,683.0,5.0,2.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-78751671270&partnerID=40&md5=17c5cc1678cece3ad455ff9ab4235a1a","Faculty of Computer Science and Information Systems, Universiti Teknologi Malaysia, 81310 UTM Skudai, Johor, Malaysia","Tan M.I.I., Faculty of Computer Science and Information Systems, Universiti Teknologi Malaysia, 81310 UTM Skudai, Johor, Malaysia; Ibrahim I.S., Faculty of Computer Science and Information Systems, Universiti Teknologi Malaysia, 81310 UTM Skudai, Johor, Malaysia","Logistics is part of the supply chain processes that plans, implements, and controls the efficient and effective forward and reverse flow and storage of goods, services, and related information between the point of origin and the point of consumption in order to meet customer requirements. This research aims to investigate the current status and future direction of the use of Information Technology (IT) for logistics, focusing on Supply Chain Management (SCM) and E-Commerce adoption in Johor. Therefore, this research stresses on the type of technology being adopted, factors, benefits and barriers affecting the innovation in SCM and ECommerce technology adoption among Logistics Service Providers (LSP). A mailed questionnaire survey was conducted to collect data from 265 logistics companies in Johor. The research revealed that SCM technology adoption among LSP was higher as they had adopted SCM technology in various business processes while they perceived a high level of benefits from SCM adoption. Obviously, ECommerce technology adoption among LSP is relatively low.","E-Commerce; Johor; Logistics Service Providers; Supply Chain Management","Electronic commerce; Innovation; Logistics; Research; Supply chains; Surveys; Technology; Digital storage; Information technology; Supply chain management; Business Process; Current status; Customer requirements; E-Commerce; E-commerce adoption; Future directions; Information technologies (it); Johor; Logistics company; Logistics service provider; Logistics Service Providers; Questionnaire surveys; Reverse flow; Supply chain process; Technology adoption; Type of technology; Supply chain management; Electronic commerce",{"$nulls":6},"Chopra S., Meindl P., Supply Chain Management, (2003); Hl L., Creating Value through Supply Chain Integration, Supply Chain Management Review, (2000); McLaren, Et al., Supply chain management information systemscapabilities. An exploratory study of electronics manufacturers, Information Systems and E-Business Management, 2, 2-3, (2004); Ndubisi N.O., Jantan M., Evaluating IS usage in Malaysian smalland medium-sized firms using the technology acceptance model, Logistics Information Management, 16, 6, pp. 440-450, (2003); Dagenais T.G.D., Net Markets: Driving Success in the B2BNetworked Economy, On Effect.Management Science., 43, (2002); Zailani S., Et al., Supply Chain Technology: An Empirical Study In The Context Of Malaysia in Proceedings of the 9th Asia Pasific Industrial Engineering & Management Systems Conference, (2008); Mukhopadhyay T., Kekre S.K.S., Business Value of InformationTechnology: A Study of Electronic Data Interchange, MIS Quarterly, 19, 2, pp. 137-156, (1995); Piplani R., Pokharel S., Tan A., Perspectives on the Use of Information Technology at Third Party Logistics Service Providers in Singapore, Asia Pacific Journal of Marketing and Logistics, 16, 1, pp. 27-41, (2004); Gulati R., Garino J., Get the right mix of bricks & clicks, Harvard Business Review, 78, 3, pp. 107-114, (2000); Delfmann W., Albers S., Gehring M., The Impact of electroniccommerce on logistics service providers, International Journal of Physical Distribution & Logistics Management, 32, 3, pp. 203-222, (2002); What Is Logistics, (2006); Turban E., Et al., Information Technology for Management-Transforming Organizations in the Digital Economy, (2008); Rushton A., Oxley J., Croucher P., Handbook of Logistics and Distribution Management, (2001); Turban E., Et al., Electronic Commerce 2006 A Managerial Perspective, (2008); Rayport J.F., Jaworski B.J., e-Commerce, E-Commerce Series, (2001); Fang L., Zhang C.-Q., The E-Logistics Framework in E-commerce, pp. 408-412, (2005); Norris G., E-Business and ERP: Transforming the Enterprise, (2000); Kumar R., Research Methodology -A Step-by-Step Guide for Beginners, (1999); Madanan S.K., Benchmarking the Effectiveness of Logistics Management, 1-8, (2008); Logistics Questionnaire, 1-11, (2008); Patterson K.A., Grimm C.M., Corsi T.M., Adopting newtechnologies for supply chain management, Transportation Research Part E, pp. 95-121, (2003); Brah S.A., Lim H.Y., The effects of technology and TQM on the performance of logistics companies, International Journal of Physical Distribution & Logistics Management, 36, 3, pp. 192-209, (2006); Molla A., Licker P.S., eCommerce adoption in developing countries:A model and instrument, Information & Management, pp. 877-899, (2005); Tan J., Tyler K., Manica A., Business-to-business adoption of eCommerce in China, Information & Management, pp. 332-351, (2007)","M. I. I. Tan; Faculty of Computer Science and Information Systems, Universiti Teknologi Malaysia, 81310 UTM Skudai, Johor, Malaysia; email: iskandar@fsksm.utm.my",{"$nulls":7},2.0103778E7,null,null,null,"English","World Acad. Sci. Eng. Technol.","Article","Final",null,"Scopus","2-s2.0-78751671270"]
["Edwards J.B.; McKinnon A.C.; Cullinane S.L.","Edwards, Julia B. (55450050000); McKinnon, Alan C. (7005291138); Cullinane, Sharon L. (6701664384)","55450050000; 7005291138; 6701664384","Comparative analysis of the carbon footprints of conventional and online retailing: A \"last mile\" perspective",2010.0,"International Journal of Physical Distribution and Logistics Management",40.0,"2024-02-01",null,103.0,123.0,20.0,225.0,"10.1108/09600031011018055","https://www.scopus.com/inward/record.uri?eid=2-s2.0-77949322043&doi=10.1108%2f09600031011018055&partnerID=40&md5=388ba15f4f1365a83ac0300016dce6f7","Logistics Research Centre, Heriot-Watt University, Edinburgh, United Kingdom","Edwards J.B., Logistics Research Centre, Heriot-Watt University, Edinburgh, United Kingdom; McKinnon A.C., Logistics Research Centre, Heriot-Watt University, Edinburgh, United Kingdom; Cullinane S.L., Logistics Research Centre, Heriot-Watt University, Edinburgh, United Kingdom","Purpose: The purpose of this paper is to focus on the carbon intensity of \"last mile\" deliveries (i.e. deliveries of goods from local depots to the home) and personal shopping trips. Design/methodology/approach: Several last mile scenarios are constructed for the purchase of small, non-food items, such as books, CDs, clothing, cameras and household items. Official government data, operational data from a large logistics service provider, face-to-face and telephone interviews with company managers and realistic assumptions derived from the literature form the basis of the calculations. Allowance has been made for home delivery failures, \"browsing\" trips to the shops and the return of unwanted goods. Findings: Overall, the research suggests that, while neither home delivery nor conventional shopping has an absolute CO2 advantage, on average, the home delivery operation is likely to generate less CO2 than the typical shopping trip. Nevertheless, CO2 emissions per item for intensive/infrequent shopping trips by bus could match online shopping/home delivery. Research limitations/implications: The number of items purchased per shopping trip, the choice of travel mode and the willingness to combine shopping with other activities and to group purchases into as few shopping trips or online transactions as possible are shown to be critical factors. Online retailers and home delivery companies could also apply measures (e.g. maximising drop densities and increasing the use of electric vehicles) to enhance the CO2 efficiency of their logistical operations and gain a clearer environmental advantage. Practical implications: Both consumers and suppliers need to be made more aware of the environmental implications of their respective purchasing behaviour and distribution methods so that potential CO2 savings can be made. Originality/value: The paper offers insights into the carbon footprints of conventional and online retailing from a \"last mile\" perspective. © Emerald Group Publishing Limited.","Air pollution; Carbon; Delivery services; Distribution channels and markets; Internet shopping",{"$nulls":5},"Engineering and Physical Sciences Research Council, EPSRC, (EP/D043328/1)",null,"Abukhader S.M., Jonson G., The environmental implications of electronic commerce: A critical review and framework for future investigation, Management of Environmental Quality: An International Journal, 14, 4, pp. 460-476, (2003); Agatz N., Fleischmann M., van Nunen J., e-Fulfilment and multi-channel distribution: A review, (2006); Beveridge I., Personal communications, meeting with Beveridge Associates, (2007); Beveridge I., Personal communications, (2009); Brooks C.M., Kaufmann P.J., Lichtenstein D.R., Trip chaining behaviour in multi-destination shopping trips: A field experiment and laboratory replication, Journal of Retailing, 84, 1, pp. 29-38, (2008); Brown M., Allen J., Rizet C., Assessing transport energy consumption in two product supply chains, International Journal of Logistics: Research and Applications, 9, 3, pp. 237-252, (2006); Browne M., Rizet C., Leonardi J., Allen J., Analysing energy use in supply chains: The case of fruits and vegetables and furniture, Proceedings of the Logistics Research Network Conference, Liverpool, September, (2008); Cairns S., Delivering supermarket shopping: More or less traffic?, Transport Reviews, 25, 1, pp. 51-84, (2005); Cairns S., Sloman L., Newson C., Anable J., Kirkbridge A., Goodwin P., Home shopping, Smarter Choices - Changing the Way We Travel, (2004); Passenger transport emissions factors, (2007); Guidelines for Company Reporting on Greenhouse Gas Emissions, (2008); de Koster M.B.M., The logistics behind the enter click, Quantitative Approaches to Distribution Logistics & Supply Chain Management, (2002); Focus on Personal Travel, (2005); Personal communications\", data supplied from National Travel Survey, (2009); Public Experiences of Home Working and Internet Shopping, (2009); Van Activity Baseline Survey 2008: Provisional Results, (2009); The Impact of Information and Communications Technologies on Travel and Freight Distribution Patterns: Review and Assessment of Literature, (2002); The impact of ICT on sustainable development, Part 2 in Annual Report, (2002); Farag S., Krizek K.J., Dijst M., e-Shopping and its relationship with in-store shopping: Empirical evidence from the Netherlands and the USA, Transport Reviews, 26, 1, pp. 43-61, (2006); Fernie J., McKinnon A.C., The development of e-tail logistics, Logistics and Retail Management, (2009); Foley P., Alfonso X., Brown K., Palmer A., Lynch D., Jackson M., The Home Delivery Sector in the UK 1995 to 2010, (2003); The Manager's Guide to Distribution Costs, (2007); Shopping miles, (2007); Gould J., Golob T.F., Shopping without travel or travel without shopping? An investigation of electronic home shopping, Transport Reviews, 1, 4, pp. 355-376, (1997); Hackney R., Grant K., Birtwistle G., The UK grocery business: Towards a sustainable model for virtual markets, International Journal of Physical Distribution & Logistics Management, 35, 4-5, pp. 354-368, (2006); Valuing Home Delivery: A Cost-Benefit Analysis, (2006); Valuing Home Delivery: E-Retail Industry Review, (2008); E-Retail Sales Index, (2008); Jespersen P.H., The transport content of products, World Transport Policy & Practice, 10, 3, pp. 28-35, (2004); Kamarainen V., Saranen J., Holmstrom J., The reception box impact on home delivery efficiency in the e-grocery business, International Journal of Physical Distribution & Logistics Management, 31, 6, pp. 414-426, (2001); Kroger K., Fergusson M., Skinner I., Critical issues in decarbonising transport: The role of technologies, (2003); McKinnon A.C.,  Emissions from Freight Transport in the UK, (2007); McKinnon A.C., Tallam D., Unattended delivery to the home: Assessment of the security implications, International Journal of Retail & Distribution Management, 31, 1, pp. 30-41, (2003); McLeod F., Cherrett T.J., Optimising vehicles undertaking waste collection, Final Report for the Department for Transport, (2006); Matthews H., Hendrickson C., Soh D.L., Environmental and economic effects of e-commerce: A study of book publishing and retail logistics, Transportation Research Record, 1763, pp. 6-12, (2001); Moe W.W., Fader P.S., Uncovering patterns in cybershopping, California Management Review, 43, 4, pp. 106-117, (2001); Mukhopadhyay S.A., Setoputro R., Reverse logistics in e-business: Optimal price and return policy, International Journal of Physical Distribution & Logistics Management, 34, 1, pp. 70-88, (2004); Nairn G., Not many happy returns, The Financial Times, (2003); Vehicle Emissions, Version 8, (2008); Popowski Leszczyc P.T.L., Timmermans H., Experimental choice analysis of shopping strategies, Journal of Retailing, 77, 4, pp. 493-509, (2001); Primerano F., Taylor M.A., Pitaksringkarn L., Tisato P., Defining and understanding trip chaining behaviour, Transportation, 35, pp. 55-72, (2008); Prologis, Internet retailing: Opportunities and challenges for the UK'S distribution property markets, Prologis Supply Chain Research Reports, (2008); Punakivi M., Comparing alternative home delivery models for e-grocery business, (2003); Motoring Towards 2050: Shopping and Transport Policy, (2006); @ Your Home: New Markets for Customer Service and Delivery, (2001); RHA Cost Tables 2008, (2008); Romm J., The Internet Economy and Global Warming: A Scenario of the Impact of E-Commerce on Energy and the Environment, (1999); Rotem-Mindali O., Salomon I., The impacts of e-tail on the choice of shopping trips and delivery: Some preliminary findings, Transportation Research Part A, 41, pp. 176-189, (2007); Home Shopper Tracker 2007, (2007); First electric vans to hit road with green shopping, (2007); Sarkis J., Meade L.M., Talluri S., E-logistics and the natural environment, Supply Chain Management: An International Journal, 9, 4, pp. 303-312, (2004); Skinner I., Fergusson M., Kroger K., Kelly C., Bristow A., Critical issues in decarbonising transport, Final Report of the Theme 2 Project T2.22, (2004); Smithers R., Supermarket home delivery service promotes its green credentials, The Guardian, (2007); Song L., Cherrett T., McLeod F., Guan W., Addressing the last mile problem - the transport impacts of collection/delivery points, (2009); van der Laan J.W., The future of online food retailing, Retail Economics, (2000); Weber C., Hendrickson C., Jaramillo P., Matthews S., Nagengast A., Nealer R., Life Cycle Comparison of Traditional Retail and E-Commerce Logistics for Electronic Products: A Case Study of Buy.Com, (2008); Webster B., Boom in internet shopping may be adding to carbon dioxide emissions, The Times, (2007); Weltevreden J.W., Rotem-Mindali T.O., Mobility Effects of b2c and c2c E-Commerce: A Literature Review and Assessment, (2008); Environmental Trends and Climate Impacts: Findings from the US Book Industry, (2007); Brown M., Rizet C., Anderson S., Allen J., Keita B., Life cycle assessment in the supply chain: A review and case study, Transport Reviews, 26, 6, pp. 761-782, (2005); Carbon Footprints in the Supply Chain, (2006); Product Carbon Footprinting: The New Business Opportunity, Experience from Leading Companies, (2008); Corpus G., Peachman J., Measuring the impacts of internet usage on travel behaviour in the Sydney Household Travel Survey, (2003); Results of the review of the community strategy to reduce CO<sub>2</sub> emissions from passenger cars and light-commercial vehicles, (2007); In-Home Eating Habits and Food Shopping, (2008); Reducing Climate Impacts: A Guide for the Book and Newspaper Industries, (2008); Emissions, (2008)","J. B. Edwards; Logistics Research Centre, Heriot-Watt University, Edinburgh, United Kingdom; email: j.b.edwards@hw.ac.uk",{"$nulls":7},9600035.0,null,null,null,"English","Int. J. Phys. Distrib. Logist. Manage.","Article","Final",null,"Scopus","2-s2.0-77949322043"]
["Griffis S.E.; Rao S.; Goldsby T.J.; Niranjan T.T.","Griffis, Stanley E. (6506269346); Rao, Shashank (55651763500); Goldsby, Thomas J. (6506420342); Niranjan, Tarikere T. (18038505300)","6506269346; 55651763500; 6506420342; 18038505300","The customer consequences of returns in online retailing: An empirical analysis",2012.0,"Journal of Operations Management",30.0,4.0,null,282.0,294.0,12.0,169.0,"10.1016/j.jom.2012.02.002","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84859057294&doi=10.1016%2fj.jom.2012.02.002&partnerID=40&md5=e9a2cc533c1d5582cf1023d944807711","Logistics, Eli Broad College of Business, Michigan State University, East Lansing, MI 48824, United States; Supply Chain Management, Auburn University College of Business, Auburn, AL 36849, United States; Logistics, Fisher College of Business, Ohio State University, Columbus, OH 43210, United States; Supply Chain Management, Shailesh J. Mehta School of Management, Indian Institute of Technology, Bombay, India","Griffis S.E., Logistics, Eli Broad College of Business, Michigan State University, East Lansing, MI 48824, United States; Rao S., Supply Chain Management, Auburn University College of Business, Auburn, AL 36849, United States; Goldsby T.J., Logistics, Fisher College of Business, Ohio State University, Columbus, OH 43210, United States; Niranjan T.T., Supply Chain Management, Shailesh J. Mehta School of Management, Indian Institute of Technology, Bombay, India","Pressure continues to build on the operations management function to facilitate system and firm level benefits. In the online marketplace, one area of growing interest is that of product returns. Though commonly viewed as a cost center from an operations perspective, operations' actions have the potential to strongly influence future customer buying behavior in several ways. Using an archival database of actual purchase and returns history provided by a moderately sized online retailer, this study examines the relationship between a customer's experience of product returns, and subsequent shopping behavior. Employing transaction cost, consumer risk, and procedural justice theories, we demonstrate that the returns management process, rather than being regarded as an afterthought to the production and deployment of goods, can significantly and positively influence repurchase behavior. Additionally, we provide evidence that certain customers should be considered for prioritization in the returns process. We suggest ways through which operations managers can take care in discharging their responsibilities in this area - to make returns processing more than simply a \"necessary cost of doing business\" rather, using it to their advantage in engendering repeat and increased purchase behavior. © 2012 Elsevier B.V. All rights reserved.","Archival data; Customer satisfaction; Logistics; Procedural justice; Product returns; Repurchase behavior; Seemingly Unrelated Regression (SUR); Service recovery; Supply chain; Transaction cost","Cost accounting; Costs; Customer satisfaction; Electronic commerce; Logistics; Sales; Supply chains; Archival data; Procedural justice; Product returns; Repurchase behavior; Seemingly unrelated regression; Transaction cost; Consumer behavior",{"$nulls":6},{"$cut":{"chars":16714,"head":"Reverse Logistics: Driving Improved Returns Directly to the Bottom Line, (2009); Abernathy W.J., Production process structure and technological change, Decision Science, 7, 4, pp. 607-619, (1976); Anderson E., Weitz B., Determinants of continuity in conventional industrial channel dyads, Marketing Science, 8, 4, pp. 310-323, (1989); Autry C., Golicic S., Evaluating buyer-supplier performance spirals: A longitudinal study, Journal of Operations Management, 28, 2, pp. 87-100, (2010); Bearden W.O., Teel J.E., Selected determinants of customer satisfaction and complaint reports, Journal of Marketing Research, 20, 1, pp. 21-28, (1983); Bitner M.J., Hubbert A.R., Encounter satisfaction versus overall satisfaction versus quality: The customer's voice, Service Quality: New Directions in Theory and Practice, pp. 72-94, (1994); Blackburn J.D., Guide Jr. V.D.R., Souza G.C., Van Wassenhove L.N., Reverse supply chains for commercial returns, California Management Review, 46, 2, pp. 6-22, (2004); Bonifield C., Cole C., Schultz R., Product returns on the Internet - A case of mixed signals, Journal of Business Research, 63, 10, pp. 1058-1065, (2010); Boshoff C., An experimental study of service recovery options, International Journal of Service Industry Management, 8, 2, pp. 110-130, (1997); Boyer K.K., Hallowell R., Roth A.V., E-services: Operating strategy - A case study and a method for analyzing operational benefits, Journal of Operations Management, 20, 2, pp. 175-188, (2002); Boyer K.K., Hult G.T.M., Extending the supply chain: Integrating operations and marketing in the online grocery industry, Journal of Operations Management, 23, 6, pp. 642-661, (2005); Boyer K.K., Hult G.T.M., Customer behavioral intentions for online purchases: An examination of fulfillment method and customer experience level, Journal of Operations Management, 24, 2, pp. 124-147, (2006); Boyer K.K., Swink M., Editorial-Empirical elephants: Why multiple methods are essential to quality research in operations and supply chain management, Journal of Operations Management, 26, 3, pp. 345-348, (2008); Brennan B., Remarks on marketing ethics, Journal of Business Ethics, 10, 4, pp. 255-258, (1991); Brohan M., Online Retailers Learn to Live with That Persistent Problem of Returns, (2005); Calantone R.J., Vickery S.K., Introduction to the special topic forum: Using archival and secondary data sources in supply chain management research, Journal of Supply Chain Management, 46, 3, pp. 68-69, (2009); E-Commerce Returns, (2008); Cha A., Some shoppers find fewer happy returns, The Washington Post, (2004); Charlton G., Returning Online Purchases Is Too Much Hassle - Survey, (2007); Chircu A.M., Mahajan V., Managing electronic commerce retail transaction costs for customer value, Decision Support Systems, 42, 2, pp. 898-914, (2006); Coase R.H., The nature of the firm, Economica, 4, 16, pp. 386-405, (1937); Cooil B., Keiningham T.L., Aksoy L., Hsu M., A longitudinal analysis of customer satisfaction and share of wallet, Journal of Marketing, 71, 1, pp. 67-83, (2007); Cooper M.C., Lambert D.M., Pagh J.D., Supply Chain Management: More Than a New Name for Logistics, International journal of logistics management, 8, 1, pp. 1-14, (1997); Davis S., Hagerty M., Gerstner E., Return policies and the optimal level of \"Hassle, Journal of Economics and Business, 50, 5, pp. 445-460, (1998); Derbaix C., Perceived risk and risk relievers, Journal of Economic Psychology, 3, 1, pp. 19-38, (1983); Devaraj S., Hollingwood D., Schroeder G.R., Generic manufacturing strategies and plant performance, Journal of Operations Management, 22, 3, pp. 313-333, (2010); Dholakia R., Zhao M., Dholakia N., Multi-channel retailing: A case study of early experiences, Journal of Interactive Marketing, 19, 2, pp. 63-74, (2005); Fader P.S., Hardie B.G.S., Common ground exists, Marketing Research, 13, 4, pp. 41-49, (2001); Flint D.J., Mentzer J.T., Logisticians as marketers: Their role when customers' desired value changes, Journal of Business Logistics, 21, 2, pp. 19-45, (2000); Folkes V.S., Consumer reactions t"}},"S.E. Griffis; Logistics, Eli Broad College of Business, Michigan State University, East Lansing, MI 48824, United States; email: griffis@bus.msu.edu",{"$nulls":7},2726963.0,null,"JOTME",null,"English","J Oper Manage","Article","Final",null,"Scopus","2-s2.0-84859057294"]
["Golany B.; Shmueli O.","Golany, Boaz (7004229103); Shmueli, Oded (7003850948)","7004229103; 7003850948","A quantitative foundation for defining and manipulating deals to facilitate automated e-commerce",2007.0,"Electronic Commerce Research",7.0,"2024-04-03",null,341.0,365.0,24.0,2.0,"10.1007/s10660-007-9010-9","https://www.scopus.com/inward/record.uri?eid=2-s2.0-36248973164&doi=10.1007%2fs10660-007-9010-9&partnerID=40&md5=bd440d411d8e56bb3784b3483cb1e526","Industrial Engineering and Management Faculty, Technion - Israel Institute of Technology, Haifa 32000, Israel; Computer Science Faculty, Technion - Israel Institute of Technology, Haifa 32000, Israel","Golany B., Industrial Engineering and Management Faculty, Technion - Israel Institute of Technology, Haifa 32000, Israel; Shmueli O., Computer Science Faculty, Technion - Israel Institute of Technology, Haifa 32000, Israel","We propose a goal programming framework that aims at automating e-commerce transactions. This framework consists of three basic layers: deal definition - defining the deal's parameters and associated constraints (e.g., item, price, delivery dates); deal manipulation - a collection of procedures for shaping deals to attain desired goals (e.g., earliest delivery and minimum price) and an applications layer that employs these procedures within some negotiations settings (e.g., an auction-related application presents a \"better offer\" while bidding on a contract). Our proposed foundation is rich enough to support a wide array of applications ranging from 1-1 and 1-n negotiations (auctions) to deal valuation and deal splitting. Whereas the techniques are appropriate to a multitude of settings, we shall mainly present them in the context of business-to-business (B2B) commerce where we see the greatest short term benefits. © Springer Science+Business Media, LLC 2007.","Automated e-commerce; Automated negotiations; Deal manipulation; Goal programming","Computer programming; Electronic commerce; Linear programming; Multiobjective optimization; Application layers; Automated e-commerce; Automated negotiations; Deal manipulation; Delivery dates; E- commerces; E-commerce transactions; Goal-programming; Programming framework; Splittings; Automation",{"$nulls":4},"Fund for the Promotion of Research; Technion-Israel Institute of Technology","O. Shmueli’s work is partially supported by the Fund for the Promotion of Research at the Technion.","Beam C., Segev A., Automated negotiations: A survey of the state of the art, Wirtschafts-Informatik, 3, 97, pp. 263-267, (1997); Chen E., Kersten G.E., Vahidov R., An E-marketplace for Agent-supported Commerce Negotiations, (2003); Kersten G.E., Noronha S.J., WWW-based negotiation support: Design implementation, and use, Decision Support Systems, 25, pp. 135-154, (1999); Christensen E., Curbera F., Meredith G., Weerawarana S., Web Services Description Language (WSDL) 1.1. W3C Note 15, March 2001, (2001); Faratin P., Automated service negotiation between autonomous computational agents, (2000); Faratin P., Sierra C., Jennings N.R., Using similarity criteria to make issue trade-offs in automated negotiations, Artificial Intelligence, 142, 2, pp. 205-237, (2002); Golany B., Shmueli O., Catalog-based purchasing: Illustrating a quantitative approach to electronic commerce, IEEE CEC 2005, 7th International IEEE Conference on E-commerce Technology 2005, (2005); Hannan E.L., Non-dominance in goal programming, INFOR, 18, 4, pp. 300-309, (1980); Hannan E.L., Narasimhan R., On fuzzy goal programming, Decision Sciences, 12, 3, pp. 522-531, (1981); Hannan E.L., An assessment of some criticisms of goal programming, Computers & Operations Research, 12, 6, pp. 525-541, (1985); Heiskanen P., Decentralized method for computing Pareto solutions in multi-party negotiations, European Journal of Operational Research, 117, 3, pp. 578-590, (1999); Hammond K.R., New directions in research on conflict resolution, The Journal of Social Issues, 21, pp. 44-66, (1965); Web services architecture overview, The Next Stage of Evolution for E-business, (2000); Ignizio J.P., Goal Programming and Extensions, (1976); Ignizio J.P., Cavalier T.M., Linear Programming, (1994); Kersten G.E., Szpakowicz S., Modeling Business Negotiations for E-commerce, (1998); Kersten G.E., Strecker S.E., Law K.P., Protocols for electronic negotiation systems: Theoretical foundations and design issues, Lecture Notes in Computer Science, 3182, pp. 106-115, (2004); Konopnicki D., Leiba L., Shmueli O., Sagiv Y., A formal yet practical approach to electronic commerce, International Journal of Cooperative Information Systems, 11, 1-2, pp. 93-117, (2002); Kraus S., Lehmann D., Designing and building a negotiating automated agent, Computational Intelligence, 11, 1, pp. 132-171, (1995); Lee S.M., Goal Programming for Decision Analysis, (1972); Myerson R.B., Game Theory-analysis of Conflict, (1997); Osborn M.J., Rubinstein A., A Course in Game Theory, (1999); Raiffa H., The Art and Science of Negotiations, (1982); Romero C., Handbook of Critical Issues in Goal Programming, (1991); Rosenschein J.S., Zlotkin G., Rules of Encounter: Designing Conventions for Automated Negotiation Among Computers, (1994); Schniederjans M.J., Goal Programming Methodology and Applications, (1995); Shachnai H., Shmueli O., Sayegh R., Approximation schemes for deal splitting and covering integer programs with multiplicity constraints, ALGO 2004 (WAOA), (2004); Shmueli O., Golany B., Sayegh R., Shachnai H., Perry M., Gradovitch N., Yehezkel B., Negotiation platform, International Patent Application WO 02077759, (2004); Shmueli O., Architectures for internal web services deployment, VLDB 2001, pp. 641-644, (2001); Teich J.E., Wallenius H., Advances in negotiation sciences, Transactions in Operational Research,,, 6, pp. 55-94, (1994); Teich J.E., Wallenius H., Wallenius J., Koppius O.R., Emerging multiple issue e-auctions, European Journal of Operational Research, 159, pp. 1-16, (2004); (2000); (2000); W3c, (2005); Vickrey W., Counterspeculation, auctions, and competitive sealed tenders, Journal of Finance, 16, pp. 8-37, (1961)","B. Golany; Industrial Engineering and Management Faculty, Technion - Israel Institute of Technology, Haifa 32000, Israel; email: golany@ie.technion.ac.il",null,"Kluwer Academic Publishers",{"$nulls":5},1.3895753E7,null,null,null,"English","Electron. Commer. Res.","Article","Final",null,"Scopus","2-s2.0-36248973164"]
["Wu L.; Cai Y.; Liu D.","Wu, Lingfei (56127475300); Cai, Yi (55418925900); Liu, Dehuan (55418406600)","56127475300; 55418925900; 55418406600","Online shopping among Chinese consumers: An exploratory investigation of demographics and value orientation",2011.0,"International Journal of Consumer Studies",35.0,4.0,null,458.0,469.0,11.0,27.0,"10.1111/j.1470-6431.2010.00982.x","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84867663214&doi=10.1111%2fj.1470-6431.2010.00982.x&partnerID=40&md5=8e99c7313e405da29ef4cd926cbb5738","College of Media and Communication, Peking University, Haidian District, Beijing, China; Family and Consumer Sciences Department, California State University, Northridge, United States","Wu L., College of Media and Communication, Peking University, Haidian District, Beijing, China; Cai Y., Family and Consumer Sciences Department, California State University, Northridge, United States; Liu D., College of Media and Communication, Peking University, Haidian District, Beijing, China","The current study examined the relationship between Chinese consumers' personal value orientations and their Internet usage and online shopping behaviour. The study was based on responses from a sample of 1620 respondents in five cities in China. Based on Schwartz's value structure, four value orientations were identified and named as 'openness to change orientation', 'self-enhancement orientation', 'conservation orientation' and 'self-transcendence orientation.' Logistic regression analysis was used to investigate the relationship between respondents' demographics, socio-economic characteristics, value orientations and their Internet usage and online shopping behaviour. Also, a structural equation modelling analysis was employed. 'Openness to change orientation' and 'self-enhancement orientation' were found to have direct or indirect positive effect on respondents' online shopping behaviour; whereas 'conservation orientation' and 'self-transcendence orientation' were not significant in the equation estimation. © 2011 Blackwell Publishing Ltd.","Chinese consumers; Diffusion of innovation; Internet usage; Online shopping; Schwartz's value structure; Structural equation modelling",{"$nulls":7},"Alba J., Lynch J., Weitz B., Janiszewski C., Lutz R., Sawyer A., Wood S., Interactive home shopping: consumer, retailer, and manufacturer incentives to participate in electronic marketplaces, Journal of Marketing, 61, pp. 38-53, (1997); Allen M.W., A practical method for uncovering the direct and indirect relationships between human values and consumer purchases, Journal of Consumer Marketing, 18, pp. 102-120, (2001); Anderson J.C., Gerbing D.W., Structural equation modeling in practice: a review and recommended two-step approach, Psychological Bulletin, 103, pp. 411-423, (1988); Anderson R.E., Srinivasan S., E-satisfaction and e-loyalty: a contingency framework, Psychology and Marketing, 20, pp. 123-138, (2003); Arnould E.J., Toward a broadened theory of preference formation and the diffusion of innovations: cases from Zinder province, Niger Republic, Journal of Consumer Research, 16, pp. 239-267, (1989); Azjen I., The theory of planned behavior, Organizational Behavior and Human Decision Processes, 50, pp. 179-211, (1991); Becker B.W., Connor P.E., Personal values of the heavy user of mass media, Journal of Advertising Research, 21, pp. 37-43, (1981); Belk R.W., Possessions and the extended self, Journal of Consumer Research, 15, pp. 139-168, (1988); Carman J.M., Values and consumption patterns: a closed loop, Advances in Consumer Research, 5, pp. 403-407, (1977); Casas J., Zmud J., Bricka S., (2001); Chan J.K., Leung L., Lifestyles, reliance on traditional news media and online news adoption, New Media & Society, 7, pp. 357-381, (2005); Chen S.H., Lee K.P., The role of personality traits and perceived values in persuasion: an elaboration likelihood model perspective on online shopping, Social Behavior and Personality, 36, pp. 1379-1400, (2008); Childers T.L., Carr C.L., Peck J., Carson S., Hedonic and utilitarian motivations for online retail shopping behavior, Journal of Retailing, 77, pp. 511-535, (2001); (2009); Cohrs J.C., Moschner B., Maes J., Kielmann S., Personal values and attitudes toward war, Peace and Conflict: Journal of Peace Psychology, 11, pp. 293-312, (2005); Davidov E., Schmidt P., Are values in the Benelux countries comparable? 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Fan J.X., Chern W.S., Analysis of food consumption patterns in China: nonparametric and parametric approaches, Journal of Family and Economic Issues, 12, pp. 113-126, (1997); Forsythe S., Shi B., Consumer patronage and risk perceptions in Internet shopping, Journal of Business Research, 56, pp. 867-875, (2003); Fulk J., Steinfeld C.W., Schmitz J., Power G.J., A social information processing model of media use in organizations, Communications Research, 14, pp. 520-552, (1987); Gates M., VALS changes with the times, Incentive, 163, pp. 27-30, (1989); George J.F., Influences on the intent to make Internet purchases, Internet Research: Electronic Networking Applications and Policy, 12, pp. 165-180, (2002); Greenland S.J., McGoldrick P.J., From mail order to home shopping - revitalising the non-store channel, Journal of Marketing Channels, 1, pp. 59-85, (1992); Henry W.A., Cultural values do correlate with consumer behavior, Journal of Marketing Research, 13, pp. 121-127, (1976); Hoffman D.L., Novak T.P., Marketing in the hypermedia computer-mediated environments: conceptual foundations, Journal of Marketing, 60, pp. 50-68, (1996); 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Kim J., Forsythe S., Gu Q., Moon S.J., Cross-cultural consumer values, needs and purchase behavior, Journal of Consumer Marketing, 19, pp. 481-502, (2002); Klein L.P., Evaluating the potential of interactive media through a new lens: search versus experience goods, Journal of Business Research, 41, pp. 195-203, (1998); Krantz M., pp. 34-41, (1998); Kraut R., Kiesler S., Boneva B., Cummings J., Helgeson V., Crawford V., Internet paradox revisited, Journal of Social Issues, 58, pp. 49-74, (2002); Levitt T., The globalization of markets, Harvard Business Review, 61, pp. 92-102, (1983); Levy S.J., Symbolism and lifestyle, Toward Scientific Marketing, pp. 140-150, (1963); Li H., Huang L., Health, education, and economic growth in China: empirical findings and implications, China Economic Review, 20, pp. 374-387, (2008); Ma H., pp. 11-13, (2004); McCracken G., Culture and Consumption: New Approaches to the Symbolic Character of Consumer Goods and Activities, (1988); McEwen W., Fang X., Zhang C., Burkholder R., pp. 68-76, (2006); McQuarrie E.F., Langmeyer D., Using values to measure attitudes toward discontinuous innovations, Psychology and Marketing, 2, pp. 239-252, (1985); Palmer J.W., Electronic commerce in retailing: differences across retail formats, The Information Society, 13, pp. 75-91, (1997); Peterson R.A., Balasubramanian S., Bronnenberg B.J., Exploring the implications of the Internet for consumer marketing, Journal of Academy of Marketing Science, 25, pp. 329-346, (1997); Pitts R.E., Woodside A.G., Personal value influences on consumer product class and brand preferences, The Journal of Social Psychology, 119, pp. 37-53, (1983); Rogers E.M., Diffusion of Innovations, (2003); Rokeach M., Belief, Attitude and Values, (1968); Schmitt B., Who is the Chinese consumer? 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A cross-cultural study of executives' choice, decisiveness, and risk adjustment in international marketing, The Journal of Marketing, 52, pp. 81-95, (1988); Veltri J.J., Schiffman L.G., Fifteen years of consumer lifestyle and value research at AT&T, Personal Values and Consumer Psychology, pp. 271-285, (1984); Vinson D.E., Scott J.E., Lamont L.M., The role of personal values in marketing and consumer behavior, Journal of Marketing, 41, pp. 44-50, (1977); Williams Jr. R.M., Change and stability in values and value systems: a sociological perspective, Understanding Human Values Individual and Societal, pp. 15-46, (1979); Yau O.H.M., Consumer Behavior in China: Customer Satisfaction and Cultural Values, (1994); Yin X., New trends of leisure consumption in China, Journal of Family and Economic Issues, 26, pp. 175-182, (2005)","Y. Cai; Family and Consumer Sciences Department, California State University, Northridge, CA 91330-8308, United States; email: tomcai@csun.edu",{"$nulls":7},1.4706431E7,null,null,null,"English","Int. J. Consum. Stud.","Article","Final",null,"Scopus","2-s2.0-84867663214"]
["Xiaomei C.","Xiaomei, Chen (23986656900)",2.39866569E10,"2010: The turning point for chinese book publishing industry",2011.0,"Publishing Research Quarterly",27.0,1.0,null,76.0,82.0,6.0,4.0,"10.1007/s12109-011-9203-x","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84878725712&doi=10.1007%2fs12109-011-9203-x&partnerID=40&md5=ce14167fb421701625bf70bddf631108","China Publishers Magazine, Xicheng District, Beijing 100045, Zhen Wu Miao Er Tiao, China","Xiaomei C., China Publishers Magazine, Xicheng District, Beijing 100045, Zhen Wu Miao Er Tiao, China","This is the only English language summary report on the major and rapid developments that have taken place in China's book publishing industry during 2010. The key companies and individuals who have been the change agents are presented in context of the developments in traditional and digital book publishing. The transition to capital investment and shares sold in the major Chinese stock markets is described including specific examples of this completely new business practice. The further dramatic growth of the mobile phone market with related information delivery for publishers is presented with financial data for the past, present and future trends for the installed base. The new roles of the General Administration for Press and Publications (GAPP) is described in relation to the reorganization of smaller publishing companies into groups with outside capital investments. Also, the role of GAPP in relation to the new requirements of copyright for digital and electronic publishing is covered. Very interesting is the emergence of three major players in e-commerce selling both consumer products and books as a form of online department stores. Finally, the emergence of Chinese language publishing as a regional language including the mainland China, Hong Kong and Taiwan is a welcome new development. © 2011 Springer Science+Business Media, LLC.","Acquisitions; Book distribution; Capital investments; Capital markets; Digital copyright; E-commerce; E-readers; iPad; IPO; Kindle; Mergers; Mobile phones; Stock exchange; Taiwan",{"$nulls":8},"C. Xiaomei; China Publishers Magazine, Xicheng District, Beijing 100045, Zhen Wu Miao Er Tiao, China; email: chxmbook@vip.sina.com",{"$nulls":7},1.9364792E7,null,null,null,"English","Publ. Res. Q.","Article","Final",null,"Scopus","2-s2.0-84878725712"]
["Ghobakhloo M.; Arias-Aranda D.; Benitez-Amado J.","Ghobakhloo, Morteza (36141576300); Arias-Aranda, Daniel (7801374665); Benitez-Amado, Jose (36008097000)","36141576300; 7801374665; 36008097000","Adoption of e-commerce applications in SMEs",2011.0,"Industrial Management and Data Systems",111.0,8.0,null,1238.0,1269.0,31.0,384.0,"10.1108/02635571111170785","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84858180431&doi=10.1108%2f02635571111170785&partnerID=40&md5=26167666ee1af12815ebe10ed5d90548","Departamento de Organización de Empresas, Facultad de Ciencias Económicas y Empresariales, Universidad de Granada, Granada, Spain","Ghobakhloo M., Departamento de Organización de Empresas, Facultad de Ciencias Económicas y Empresariales, Universidad de Granada, Granada, Spain; Arias-Aranda D., Departamento de Organización de Empresas, Facultad de Ciencias Económicas y Empresariales, Universidad de Granada, Granada, Spain; Benitez-Amado J., Departamento de Organización de Empresas, Facultad de Ciencias Económicas y Empresariales, Universidad de Granada, Granada, Spain","Purpose The purpose of this paper is to examine the factors within the technology-organization-environment (TOE) framework that affect the decision to adopt electronic commerce (EC) and extent of EC adoption, as well as adoption and non-adoption of different EC applications within small- and medium-sized enterprises (SMEs). Design/methodology/approach A questionnaire-based survey was conducted to collect data from 235 managers or owners of manufacturing SMEs in Iran. The data were analyzed by employing factorial analysis and relevant hypotheses were derived and tested by multiple and logistic regression analysis. Findings EC adoption within SMEs is affected by perceived relative advantage, perceived compatibility, CEO's innovativeness, information intensity, buyer/supplier pressure, support from technology vendors, and competition. Similarly, description on determinants of adoption and non-adoption of different EC applications has been provided. Research limitations/implications Cross-sectional data of this research tend to have certain limitations when it comes to explaining the direction of causality of the relationships among the variables, which will change overtime. Practical implications The findings offer valuable insights to managers, IS experts, and policy makers responsible for assisting SMEs with entering into the e-marketplace. Vendors should collaborate with SMEs to enhance the compatibility of EC applications with these businesses. To enhance the receptiveness of EC applications, CEOs, innovativeness and perception toward EC advantages should also be aggrandized. Originality/value This study is perhaps one of the first to use a wide range of variables in the light of TOE framework to comprehensively assess EC adoption behavior, both in terms of initial and post-adoption within SMEs in developing countries, as well adoption and non-adoption of simple and advanced EC applications such as electronic supply chain management systems. Copyright © 2011 Emerald Group Publishing Limited. All rights reserved.","Adoption; Electronic commerce; Iran; Small to medium-sized enterprises","Developing countries; Electronic commerce; Management; Managers; Regression analysis; Surveys; Adoption; Adoption behavior; Design/methodology/approach; E-Commerce applications; E-marketplaces; Electronic supply chain management; Factorial analysis; Information intensity; Innovativeness; Iran; Logistic regression analysis; Policy makers; Research limitations; Small and medium-sized enterprise; Small to medium-sized enterprise; Technology vendors; Technology-organization-environment frameworks; Industry",{"$nulls":6},"Agarwal R., Prasad J., A conceptual and operational definition of personal innovativenessin the domain of information technology, Information Systems Research, 9, 2, pp. 204-15, (1998); Al-Qirim N.A.Y., E-commerce in the aerial mapping industry: A New Zealand case study, Journal of Systems and Information Technology, 7, 1-2, pp. 67-92, (2003); Al-Qirim N., The adoption of eCommerce communications and applications technologies in small businesses in New Zealand, Electronic Commerce Research and Applications, 6, 4, pp. 462-473, (2007); Anandarajan M., Arinze B., Matching client/server processing architectures with information processing requirements: A contingency study, Information and Management, 34, 5, pp. 265-274, (1998); Attewell P., Technology diffusion and organizational learning: The case of business computing, Organization Science, 3, 1, pp. 1-19, (1992); Barua A., Konana P., Whinston A.B., Yin F., Assessing internet enabled business value: An exploratory investigation, MIS Quarterly, 28, 4, pp. 585-620, (2004); Beatty R.C., Shim J.P., Jones M.C., Factors influencing corporate web site adoption: A time-based assessment, Information and Management, 38, 6, pp. 337-354, (2001); Benitez-Amado J., Llorens-Montes F.J., Perez-Arostegui M.N., Information technology-enabled intrapreneurship culture and firm performance, Industrial Management & Data Systems, 110, 4, pp. 550-66, (2010); Benitez-Amado J., Perez-Arostegui M.N., Tamayo-Torres J., Information technology-enabled innovativeness and green capabilities, Journal of Computer Information Systems, 51, 2, pp. 87-96, (2010); Blili S., Raymond L., Information technology: Threats and opportunities for small and medium-sized enterprises, International Journal of Information Management, 13, 6, pp. 439-48, (1993); Bruque S., Moyano J., Organisational determinants of information technology adoption and implementation in SMEs: The case of family and cooperative firms, Technovation, 27, 5, pp. 241-253, (2007); Caldeira M.M., Ward J.M., Using resource-based theory to interpret the successful adoption and use of information systems and technology in manufacturing small and medium-sized enterprises, European Journal of Information Systems, 12, 2, pp. 127-141, (2003); Chatterjee D., Grewal R., Sambamurthy V., Shaping up for e-commerce: Institutional enablers of the organizational assimilation of web technologies, MIS Quarterly, 26, 2, pp. 65-89, (2002); Chwelos P., Benbasat I., Dexter A.S., Research report: Empirical test of an EDI adoption model, Information Systems Research, 12, 3, pp. 304-21, (2001); Cragg P.B., Zinatelli N., The evolution of information systems in small firms, Information & Management, 29, 1, pp. 1-8, (1995); Davis F.D., Perceived usefulness, perceived ease of use, and user acceptance of information technology, MIS Quarterly, 13, 3, pp. 319-39, (1989); De Burca S., Fynes B., Marshall D., Strategic technology adoption: Extending ERP across the supply chain, Journal of Enterprise Information Management, 18, 4, pp. 427-440, (2005); Delone W.H., Firm size and the characteristics of computer use, MIS Quarterly, 4, 5, pp. 65-77, (1981); Dibrell C., Davis P.S., Craig J., Fueling innovation through information technology in SMEs, Journal of Small Business Management, 46, 2, pp. 203-18, (2008); Elbertsen L., Van Reekum R., To ERP or not to ERP? 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Tung L.L., Rieck O., Adoption of electronic government services among business organizations in Singapore, Journal of Strategic Information Systems, 14, 4, pp. 417-440, (2005); Welsh J.A., White J.F., A small business is not a little big business, Harvard Business Review, 59, 4, pp. 18-32, (1981); Wu F., Yeniyurt S., Kim D., Cavusgil S.T., The impact of information technology on supply chain capabilities and firm performance: A resource-based view, Industrial Marketing Management, 35, 4, pp. 493-504, (2006); Zhu K., The complementarity of information technology infrastructure and e-commerce capability: A resource-based assessment of their business value, Journal of Management Information Systems, 21, 1, pp. 167-202, (2004); Zhu K., Kraemer K.L., E-commerce metrics for net-enhanced organizations: Assessing the value of e-commerce to firm performance in the manufacturing sector, Information Systems Research, 13, 3, pp. 275-95, (2002); Zhu K., Kraemer K.L., Post-adoption variations in usage and value of e-business by organizations: Cross-country evidence from the retail industry, Information Systems Research, 16, 1, pp. 61-84, (2005); Zhu K., Kraemer K., Xu S., Electronic business adoption by European firms: A cross-country assessment of the facilitators and inhibitors, European Journal of Information Systems, 12, 4, pp. 251-268, (2003)","D. Arias-Aranda; Departamento de Organización de Empresas, Facultad de Ciencias Económicas y Empresariales, Universidad de Granada, Granada, Spain; email: darias@ugr.es",{"$nulls":7},2635577.0,null,"IMDSD",null,"English","Ind Manage Data Sys","Article","Final",null,"Scopus","2-s2.0-84858180431"]
["Tariq A.N.; Eddaoudi B.","Tariq, Abdul Naveed (37023600100); Eddaoudi, Badr (57217886588)","37023600100; 57217886588","Assessing the effect of trust and security factors on consumers' willingness for online shopping among the urban moroccans",2009.0,"International Journal of Business and Management Science",2.0,1.0,null,17.0,32.0,15.0,8.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-79952655301&partnerID=40&md5=d90aad57b8121aec166f13b29968f6c6","School of Business Administration, Al Akhawayn University, Morocco","Tariq A.N., School of Business Administration, Al Akhawayn University, Morocco; Eddaoudi B., School of Business Administration, Al Akhawayn University, Morocco","This study attempts to examine the customers' willingness to shop online by taking into account demographic factors as well as trust, and security-related factors. The research area of the study included the most prominent cities of Rabat, Casablanca and Al Akhawayn University in Ifrane. A logistic regression analysis was demonstrated and the findings indicate that the customers' willingness to shop online is explained by age, trust, security, awareness and piracy factors. The findings of the study also indicates that majority of the respondents intends to shop online. The research outcomes are undoubtedly useful for both the government and online vendors for better understanding online shoppers. The study also facilitates policy makers to set and develop a better online shopping infrastructure with the technological competitive advantage for both online vendors and consumers.","Consumers' willingness; Online shopping; Trust and security factors",{"$nulls":7},"Ang L., Dubelaar C., Lee B., To trust or not to trust? A model of internet trust from the customer's point of view, Everything: E-commerce, 14th Bled Electronic Commerce of Conference, (2001); Bagchi K., Mahmood A., A longitudinal study of business model of on-line shopping behavior using a latent growth curve approach. Proceedings of the 10<sup>th</sup>, Americas Conference on Information Systems, pp. 41-50, (2004); Bellman S., Lohse G.L., Johnson E.J., Predictors of online buying behavior, Communications of the ACM, 42, 12, pp. 32-38, (1999); Bhatnagar A., Misra S., Rao H.R., On risk, convenience, and internet shopping behavior, Communications of the ACM, 43, 11, pp. 98-105, (2000); Christopher J., E-commerce: Comparison of On-line Shopping Trends, Patterns and Preferences Against A Selected Survey of Females, (2004); CIA-The World Factbook, (2009); Culnan M.J., Armstrong P.K., Information privacy concerns, procedural fairness, and impersonal trust: An empirical investigation, Organization Science, 10, 1, pp. 104-116, (1999); Dillon N., Women Buying More Online, Study Finds, (1999); Doney P.M., Cannon J.P., An examination of the nature of trust in buyer-seller relationship, Journal of Marketing, 61, 2, pp. 35-51, (1997); Donthu N., Garcia A., The internet shopper, Journal of Advertising Research, 39, 3, pp. 52-58, (1999); Egelman S., Tsai J., Cranor L., Acquisti A., Studying the Impact of Privacy Information on Online Purchase Decisions, (2004); Ganesan S., Determinants of long-term orientation in buyer-seller relationships, Journal of Marketing, 58, 2, pp. 1-19, (1994); Gefen D., E-commerce: The role of familiarity and trust, Qmega, 28, 6, pp. 725-737, (2000); Gefen D., Straub D., Managing user trust in B2C, EService Journal, 2, 2, pp. 7-24, (2003); Gefen D., Silver M., Lessons learned from the successful adoption of an ERP system,  International Conference of the Decision Sciences Institute, pp. 1054-1057, (1999); Giffin K., The contribution of studies of source credibility to a theory of interpersonal trust in the communication process, Psychological Bulletin, 68, 2, pp. 104-120, (1967); Hoffman D.L., Kalsbeek W.D., Novak T.P., Internet and web use in the US, Communications of the ACM, 39, 12, pp. 36-46, (1996); Hoffmeyer-Zlotnik J.H.P., New sampling designs and the quality of data, Developments in Applied Statistics, 19, pp. 205-217, (2003); Hofstede G., The Poverty of Management Control Philosophy, The Academy of Management Review, 3, 3, pp. 450-461, (1978); Hosmer L.T., Trust: The connecting link between organizational theory and philosophical ethics, Academy of Management Review, 20, 2, pp. 379-403, (1995); Internet Usage Statistics for Africa, (2008); Iraqi F., E-commerce. le Dirham Passe sur la Toile, (2006); Jankari R., E-commerce: Nouveau Virage Au Maroc Pour les Paiements en Ligne, (2008); Jaques R., UK tops European online shopping league, Business News, (2004); Johnson C.A., Us E-commerce: 2005 to 2010, A Five-year Forecast and Analysis of Us Online Retail Sales, (2005); Joines J., Scherer C., Scheufele D., Exploring motivations for consumer web use and their implications for e-commerce, Journal of Consumer Marketing, 20, 2, pp. 90-109, (2003); Koufaris M., William H., Customer trust online: Examining the role of the experience with the web site, The Department of Statistics & Computer Information Systems, (2002); Larzeiere R.E., Huston T.L., The dyadic trust scale: Toward understanding interpersonal trust in close relationships, Journal of Marriage and the Family, 42, 3, pp. 595-604, (1980); Leech N.L., Barrett K.C., Morgan G.A., SPSS for Intermediate Statistics: Use and Interpretations, (2005); Li H., Kuo C., Russell M.G., The impact of perceived channel utilities, shopping orientations, and demographics on the consumer's online buying behaviour, Journal of Computer Mediated Communication, 5, 2, (1999); Liao Z., Cheung M.T., Internet-based e-shopping and consumer attitudes: An empirical study, Information & management, 38, 5, pp. 299-306, (2001); Mayer R.C., Davis J.H., Schoorman F.D., An integrative model of organizational trust, Academy of Management Review, 20, 3, pp. 709-734, (1995); McKnight H., Chervany L., What trust means in e-commerce customer relationships: An interdisciplinary conceptual typology, International Journal of Electronic Commerce, 6, 2, pp. 35-59, (2002); McKnight H., Cummings L., Chervany L., Initial trust formation in new organizational relationships, Academy of Management Review, 23, 3, pp. 473-490, (1998); Moorman C., Zaltman G., Deshpande R., Relationships between providers and users of market research: The dynamics of trust within and between organizations, Journal of Marketing Research, 29, 3, pp. 314-328, (1992); Ponnurangam K., Acquisti A., Cranor L., Trust modelling for online transactions: A phishing scenario, Proceedings of Privacy Security Trust, (2006); Ruppel C., Underwood-Queen L., Harrington J., E-Commerce: The roles of trust, security, and type of e-commerce involvement, E-Service Journal, 2, 2, pp. 25-45, (2006); Sqalli N., Paiement Électronique : Comment Ça Marchera. l'Economiste, (2007); Stafford T.F., Turan A., Raisinghani M.S., International and cross-cultural influences on online shopping behaviour, Journal of Global Information Management, 7, 2, pp. 70-87, (2004); Susskind A., Electronic commerce and world wide web apprehensiveness: An examination of consumers' perceptions of the world wide web, Journal of Computer-Mediated Communication, (2004); Tracy B., Seasoned users lead in e-commerce, Advertising Age, 69, 26, (1998); UK Vs US Online Shopping - June, 2000, (2000); Wells W.D., Giihn Q., Surf's up-Differences between Web surfers and non surfers: Theoretical and practical implications, Proceedings of the Conference of the American Academic of Advertising, (1999); Zucker L.G., Production of trust: Institutional sources of economic structure: 1840-1920, Research in Organizational Behaviour, 8, pp. 53-111, (1986)","A. N. Tariq; School of Business Administration, Al Akhawayn University, Morocco; email: antariq@yahoo.com",{"$nulls":7},"1985692X",null,null,null,"English","Int. J. Bus. Manage. Sci.","Article","Final",null,"Scopus","2-s2.0-79952655301"]
["Milkman K.L.; Rogers T.; Bazerman M.H.","Milkman, Katherine L. (20433982500); Rogers, Todd (57001107300); Bazerman, Max H. (7004218476)","20433982500; 57001107300; 7004218476","I'll have the ice cream soon and the vegetables later: A study of online grocery purchases and order lead time",2010.0,"Marketing Letters",21.0,1.0,null,17.0,35.0,18.0,81.0,"10.1007/s11002-009-9087-0","https://www.scopus.com/inward/record.uri?eid=2-s2.0-75849116073&doi=10.1007%2fs11002-009-9087-0&partnerID=40&md5=aac97daecd1583532f3e3ddbb4c00f01","The Wharton School, Philadelphia, PA 19104, 3730 Walnut Street, 561 Jon M. Huntsman Hall, United States; Analyst Institute, Washington, DC, United States; Harvard Business School, Boston, MA 02163, Baker Library 453, Soldiers Field Road, United States","Milkman K.L., The Wharton School, Philadelphia, PA 19104, 3730 Walnut Street, 561 Jon M. Huntsman Hall, United States; Rogers T., Analyst Institute, Washington, DC, United States; Bazerman M.H., Harvard Business School, Boston, MA 02163, Baker Library 453, Soldiers Field Road, United States","How do decisions made for tomorrow or 2 days in the future differ from decisions made for several days in the future? We use data from an online grocer to address this question. In general, we find that as the delay between order completion and delivery increases, grocery customers spend less, order a higher percentage of \"should\" items (e.g., vegetables), and order a lower percentage of \"want\" items (e. g., ice cream), controlling for customer fixed effects. These field results replicate previous laboratory findings and are consistent with theories suggesting that people's should selves exert more influence over their choices the further in the future outcomes will be experienced. However, orders placed for delivery tomorrow versus 2 days in the future do not show this want/should pattern, and we discuss a potential explanation. © Springer Science+Business Media, LLC 2009.","E-commerce; Intertemporal choice; Intrapersonal conflict; Lead time; Want/should",{"$nulls":7},"Ainslie G., Specious reward: A behavioral theory of impulsiveness and impulse control, Psychological Bulletin, 82, pp. 463-496, (1975); Ashraf N., Karlan D., Yin W., Tying Odysseus to the mast: Evidence from a commitment savings product in the Philippines, Quarterly Journal of Economics, 121, 2, pp. 635-672, (2006); Bazerman M.H., Tenbrunsel A.E., Wade-Benzoni K., Negotiating with yourself and losing: Making decisions with competing internal preferences, Academy of Management Review, 23, 2, pp. 225-241, (1998); Benzion U., Rapopport A., Yagil Y., Discount rates inferred from decisions: An experimental study, Management Science, 35, 3, pp. 270-284, (1989); ComScore Networks Reports Total Non-Travel E-commerce Spending Reaches $102 Billion in 2006; Up 24 Percent Versus 2005, (2007); Drewnowski A., Barratt-Fornell A., Do healthier diets cost more?, Nutrition Today, 39, 4, pp. 161-168, (2004); Heilman C.M., Nakamoto K., Rao A.G., Pleasant surprises: Consumer response to unexpected in-store coupons, Journal of Marketing Research, 39, 2, pp. 242-252, (2002); Khan U., Dhar R., Wertenbroch K., A behavioral decision theory perspective on hedonic and utilitarian choice, Inside Consumption: Frontiers of Research on Consumer Motives, Goals, and Desires, pp. 144-165, (2005); Loewenstein G.F., Out of control: Visceral influences on behavior, Organizational Behavior and Human Decision Processes, 65, 3, pp. 272-292, (1996); Loewenstein G.F., Prelec D., Anomalies in intertemporal choice: Evidence and an interpretation, Quarterly Journal of Economics, 107, pp. 573-597, (1992); Malmendier U., della vigna S., Paying not to go to the gym, American Economic Review, 96, 3, pp. 694-719, (2006); Martin J.M., Beshears J., Milkman K.L., Bazerman M.H., Sutherland L., Modeling expert opinions on food healthiness: A nutrition metric, Journal of the American Dietetic Association, 109, 6, pp. 1088-1091, (2009); Milkman K.L., Beshears J., Mental accounting and small windfalls: Evidence from an online grocer, Journal of Economic Behavior and Organization, 71, 2, pp. 384-394, (2009); Milkman K.L., Rogers T., Bazerman M.H., Harnessing our inner angels and demons: What we have learned about want/should conflicts and how that knowledge can help us reduce short-sighted decision making, Perspectives on Psychological Science, 3, pp. 324-338, (2008); Milkman K.L., Rogers T., Bazerman M.H., Highbrow films gather dust: Time-inconsistent preferences and online DVD rentals, Management Science, 55, 6, pp. 1047-1059, (2009); Oster S., Scott Morton F.M., Behavioral biases meet the market: The case of magazine subscription prices, BE Journals Economic Analysis and Policy-Advances, 5, 1, (2005); Read D., Intrapersonal dilemmas, Human Relations, 54, 8, pp. 1093-1117, (2001); Rogers T., Bazerman M.H., Future lock-in: Future implementation increases selection of should choices, Organizational Behavior and Human Decision Processes, 106, 1, pp. 1-20, (2008); Schelling T.C., Choice and Consequence: Perspectives of an Errant Economist, (1984); Shefrin H., Thaler R.H., The behavioral life-cycle hypothesis, Economic Inquiry, 26, 4, pp. 609-643, (1988); Shrout P.E., Fleiss J.L., Intraclass correlations: Uses in assessing rater reliability, Psychological Bulletin, 86, 2, pp. 420-428, (1979); Sunstein C.R., Thaler R.H., Libertarian paternalism is not an oxymoron, University of Chicago Law Review, 70, pp. 1159-1199, (2003); Trope Y., Liberman N., Temporal construal, Psychological Review, 110, pp. 403-421, (2003); van Duyn M.A.S., Pivonka E., Overview of the health benefits of fruit and vegetable consumption for the dietetics profession: Selected literature, Journal of the American Dietetic Association, 100, 12, pp. 1511-1521, (2000); Willet W.C., Diet and health: What should we eat?, Science, 264, 5158, pp. 532-537, (1994); Wooldridge J.M., Econometric Analysis of Cross Section and Panel Data, (2002); Zauberman G., Lynch J.G., Resource slack and propensity to discount delayed investments of time versus money, Journal of Experimental Psychology: General, 134, 1, pp. 23-37, (2005)","K. L. Milkman; The Wharton School, Philadelphia, PA 19104, 3730 Walnut Street, 561 Jon M. Huntsman Hall, United States; email: kmilkman@wharton.upenn.edu",{"$nulls":7},9230645.0,null,null,null,"English","Mark. Lett.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-75849116073"]
["Davies I.; Mason R.; Lalwani C.","Davies, Ian (36808830600); Mason, Robert (19035393300); Lalwani, Chandra (6603598012)","36808830600; 19035393300; 6603598012","Assessing the impact of ICT on UK general haulage companies",2007.0,"International Journal of Production Economics",106.0,1.0,null,12.0,27.0,15.0,47.0,"10.1016/j.ijpe.2006.04.007","https://www.scopus.com/inward/record.uri?eid=2-s2.0-33845501362&doi=10.1016%2fj.ijpe.2006.04.007&partnerID=40&md5=022c4c4c4f1c4e26c10b642b0af51a7d","Logistics and Operations Management, Cardiff Business School, Cardiff, CF10 3EU, United Kingdom; University of Hull Logistics Institute, Business School, Hull, HU6 7RX, United Kingdom","Davies I., Logistics and Operations Management, Cardiff Business School, Cardiff, CF10 3EU, United Kingdom; Mason R., Logistics and Operations Management, Cardiff Business School, Cardiff, CF10 3EU, United Kingdom; Lalwani C., University of Hull Logistics Institute, Business School, Hull, HU6 7RX, United Kingdom","This paper focuses on the road freight transport industry, using the UK as a case study. It examines the extent to which Internet freight exchanges and the use of information and communication technology (ICT) processes are affecting general haulage. Recent surveys suggest that there is scope within the road transport industry to improve efficiency in terms of fill rates and empty running. Any improvements may also help to alleviate the pressures faced in many developed countries by the haulage industry, which include driver shortages, new legislation, such as the Working Time Directive in Europe, increasing road congestion, as well as to support improvements desired for sustainability. A background summary of the UK road haulage industry and the potential impact of e-commerce are provided before the results of a survey from 49 general haulage operators in their attitude to and adoption of ICT developments are analysed and assessed. The study concludes that a split picture is emerging. While many of the smaller haulage operators remain dependent upon traditional communication and process systems, the larger logistics companies, who control the majority of vehicles and freight movements, are progressively developing new ways of working supported by ICT adoption. © 2006 Elsevier B.V. All rights reserved.","Electronic commerce; Haulage industry; Information and communication technology; Internet freight exchanges","Electronic commerce; Freight transportation; Highway traffic control; Internet; Laws and legislation; Process control; Haulage industry; Information and communication technology (ICT); Internet freight exchanges; Information technology",{"$nulls":6},"Allen S., Leveraging procurement: the quiet e-business, Logistics and Transport Focus, May, pp. 29-30, (2001); Auramo J., Aminoff A., Punakivi M., Research agenda for e-business logistics based on professional opinions, International Journal of Physical Distribution & Logistics Management, 32, 7, pp. 513-531, (2002); Blaikie N., Analysing Quantitative Data, (2003); Boughton R.F., Addressing the escalating cost of road transport, Logistics and Transport Focus, April, pp. 36-43, (2003); Brown A., Not enough time to deliver goods, Motor Transport, March 13, (2003); Impact of the Working Time Directive, (2003); Christopher M., Logistics and Supply Chain Management, (1992); Cox A., The art of the possible; relationship management in power regimes and supply chains, Supply Chain Management, An International Journal, 9, 5, pp. 346-356, (2004); Craik D., Semple J., Look east as EU expands, Motor Transport, April, (2003); Delfmann W., Albers S., Gehring M., The impact of electronic commerce on logisitcs service providers, International Journal of Physical Distribution & Logistics Management, 32, 3, pp. 203-222, (2002); Report: logistics directors' forum stresses WTD positives, Logistics and Transport Focus, May, (2003); Hesse M., Shipping news: the implications of electronic commerce for logistics and freight transport, Resources, Conservation and Recycling, 36, pp. 211-240, (2002); Higginbottom D., Digital tachographs a challenging change, Logistics and Transport Focus, December, pp. 39-41, (2002); Kast F.E., Rosenzwieg J.E., Organization and Management-A Systems and Contingency Approach, (1981); King D., Wright D., Back to basics use process mapping, Logistics and Transport Focus, April, pp. 42-45, (2002); Mason S.J., Ribera M.P., Farris J.A., Kirk R.G., Integrating the warehousing and transportation functions of the supply chain, Transportation Research Part E, 39, pp. 141-159, (2003); Mendenhall W., Reinmuth J.E., Beaver R., Statistics for Management and Economics. sixth ed, (1989); Murphy S., Working time directive: a practical guide, Logistics and Transport Focus, September, pp. 26-28, (2002); O'Connor D., Growing revenue while cutting costs, Logistics and Transport Focus, April, pp. 21-22, (2002); de Palacio L., The transport policy white paper: one year on, Transport Journal, January, (2003); Penny E., Raft of measures to relieve congestion, Commercial Motor, March-April, (2003); Piercy N.C., Looking back at the third e-Christmas, Logistics and Transport Focus, May, pp. 54-57, (2003); Porter M., Strategy and the internet, Harvard Business Review, March, pp. 62-79, (2001); Semple J., 31% More room on average load deck, Motor Transport, April, (2003); Towill D.R., The seamless supply chain: the predator's strategic advantage, International Journal of Technology Management, 13, 1, pp. 37-56, (1997); Womack J.P., Jones D.T., Lean Thinking, (1996)","R. Mason; Logistics and Operations Management, Cardiff Business School, Cardiff, CF10 3EU, United Kingdom; email: masonrj@cardiff.ac.uk",{"$nulls":7},9255273.0,null,"IJPCE",null,"English","Int J Prod Econ","Article","Final",null,"Scopus","2-s2.0-33845501362"]
["Illyas Tan M.I.B.; Ibrahim I.S.B.","Illyas Tan, Mohd Iskandar Bin (53263813400); Ibrahim, Iziati Saadah Bt (36815815200)","53263813400; 36815815200","Supply chain management and E-commerce technology adoption among logistics service providers in Malaysia",2010.0,"World Academy of Science, Engineering and Technology",65.0,null,null,451.0,456.0,5.0,2.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-78751630598&partnerID=40&md5=2f045c3187aeebfa0f0cd4afa52c879e","Faculty of Computer Science and Information Systems, Universiti Teknologi Malaysia, 81310 UTM Skudai, Johor, Malaysia","Illyas Tan M.I.B., Faculty of Computer Science and Information Systems, Universiti Teknologi Malaysia, 81310 UTM Skudai, Johor, Malaysia; Ibrahim I.S.B., Faculty of Computer Science and Information Systems, Universiti Teknologi Malaysia, 81310 UTM Skudai, Johor, Malaysia","Logistics is part of the supply chain processes that plans, implements, and controls the efficient and effective forward and reverse flow and storage of goods, services, and related information between the point of origin and the point of consumption in order to meet customer requirements. This research aims to investigate the current status and future direction of the use of Information Technology (IT) for logistics, focusing on Supply Chain Management (SCM) and E-Commerce adoption in Malaysia. Therefore, this research stresses on the type of technology being adopted, factors, benefits and barriers affecting the innovation in SCM and E-Commerce technology adoption among Logistics Service Providers (LSP). A mailed questionnaire survey was conducted to collect data from 265 logistics companies in Johor. The research revealed a high level of SCM technology adoption among LSP as they had adopted SCM technology in various business processes while they perceived a high level of benefits from SCM adoption.","E-Commerce; Logistics Service Providers; Malaysia; Supply Chain Management","Electronic commerce; Innovation; Logistics; Research; Supply chains; Surveys; Technology; Digital storage; Information technology; Supply chain management; Business Process; Current status; Customer requirements; E-Commerce; E-commerce adoption; Future directions; Information technologies (it); Logistics company; Logistics service provider; Logistics Service Providers; Malaysia; Questionnaire surveys; Reverse flow; Supply chain process; Technology adoption; Type of technology; Supply chain management; Electronic commerce",{"$nulls":6},"McLaren M., Et al., Supply chain management information systemscapabilities, An exploratory study of electronics manufacturers, 2, 2-3, (2004); Chopra S., Meindl P., Supply Chain Management, (2003); Dagenais T., Markets G.D.N., Driving Success in the B2BNetworked Economy, ON Effect. Management Science, 43, (2002); Hl L., Creating Value through Supply Chain Integration, Supply Chain Management Review, (2000); Ndubisi N.O., Jantan M., Evaluating IS usage in Malaysian smalland medium-sized firms using the technology acceptance model, Logistics Information Management, 16, 6, pp. 440-450, (2003); Zailani S., Et al., Supply Chain Technology: An Empirical Study In The Context Of Malaysia, Proceedings of the 9th Asia Pasific Industrial Engineering & Management Systems Conference, (2008); Mukhopadhyay T., Kekre S.K.S., Business Value of Information Technology: A Study of Electronic Data Interchange, MIS Quarterly, 19, 2, pp. 137-156, (1995); Piplani R., Pokharel S., Tan A., Perspectives on the Use of Information Technology at Third Party Logistics Service Providers in Singapore, Asia Pacific Journal of Marketing and Logistics, 16, 1, pp. 27-41, (2004); Gulati R., Garino J., Get the right mix of bricks & clicks, Harvard Business Review, 78, 3, pp. 107-114, (2000); Delfmann W., Albers S., Gehring M., The Impact of electroniccommerce on logistics service providers, International Journal of Physical Distribution & Logistics Management, 32, 3, pp. 203-222, (2002); What Is Logistics, (2006); Turban E., Et al., Information Technology for Management -Transforming Organizations in the Digital Economy, (2008); Rushton A., Oxley J., Croucher P., Handbook of Logistics and Distribution Management, (2001); Turban E., Et al., Electronic Commerce 2006 A Managerial Perspective, (2006); Rayport J.F., Jaworski B.J., e-Commerce. E-Commerce Series, (2001); Fang L., Zhang C.-Q., The E-Logistics Framework in E-commerce, in ICEC'05, pp. 408-412, (2005); Norris G., Et al., E-Business and ERP:Transforming the Enterprise, (2000); Kumar R., Research Methodology -A Step-by-Step Guide for Beginners, (1999)","M. I. B. Illyas Tan; Faculty of Computer Science and Information Systems, Universiti Teknologi Malaysia, 81310 UTM Skudai, Johor, Malaysia; email: iskandar@fsksm.utm.my",{"$nulls":7},2.0103778E7,null,null,null,"English","World Acad. Sci. Eng. Technol.","Article","Final",null,"Scopus","2-s2.0-78751630598"]
["Li J.; Wang X.; Chen M.; Ruan J.","Li, Juntao (57209631818); Wang, Xuping (35273544600); Chen, Mingtian (36863270900); Ruan, Junhu (25652148000)","57209631818; 35273544600; 36863270900; 25652148000","Disturbance recovery strategies for demand changes in vehicle routing problem with time windows",2011.0,"ICIC Express Letters, Part B: Applications",2.0,2.0,null,459.0,466.0,7.0,1.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-79952437082&partnerID=40&md5=9e7174b23ef760eac9f53e147b038681","Information School, Beijing Wuzi University, Beijing 101149, China; Institute of Systems Engineering, Dalian University of Technology, Dalian 116023, No. 2, Linggong Road, Ganjingzi District, China","Li J., Information School, Beijing Wuzi University, Beijing 101149, China; Wang X., Institute of Systems Engineering, Dalian University of Technology, Dalian 116023, No. 2, Linggong Road, Ganjingzi District, China; Chen M., Institute of Systems Engineering, Dalian University of Technology, Dalian 116023, No. 2, Linggong Road, Ganjingzi District, China; Ruan J., Institute of Systems Engineering, Dalian University of Technology, Dalian 116023, No. 2, Linggong Road, Ganjingzi District, China","In the environment of e-commerce, customers' demands change continually. In order to improve customer satisfaction and reaction ability for customers' orders of logistic enterprises, the paper solves demand changes disturbance in vehicle routing problem with time windows. Disruption events and their influences are analyzed. Rescuing different disruption events is transferred to rescuing a new customer with new demands. Based on disruption management thoughts, a disruption recovery model for the problem is developed. Then the react strategies for disruption events are also proposed, including adding vehicles policy, get-off later policy and exchange policy. A nested partitions method is designed to realize the react strategies. The effectiveness of the react strategies is showed by the experiment results. © 2011 ISSN 2185-2766.","Disruption management; Nested partitions method; New customer disruption event; VRPTW","Routing algorithms; Sales; Vehicle routing; Demand changes; Disruption management; E-Commerce; In-vehicle; Nested partitions; Nested partitions method; New customer disruption event; Recovery model; Recovery strategies; VRPTW; Customer satisfaction",{"$nulls":6},"Chinese Internet Network Development Statistics Report, pp. 28-32, (2009); Zhang J.-y., Guo Y.-h., Li J., Research of vehicle routing problem under condition of fuzzy demand, XITONG GONGCHENG XUEBAO, 19, 1, pp. 74-78, (2004); Chen B., Song S., Chen X., Vehicle routing problem with fuzzy demands and its heuristic ant colony algorithm, Computer Applications, 26, 11, pp. 2639-2642, (2006); Xie B.-L., An S., Guo Y.-H., Multi-tour optimization policy for stochastic vehicle routing problem, Xitong Gongcheng Lilun yu Shijian/System Engineering Theory and Practice, 27, 2, pp. 167-171, (2007); Braysy O., Gendreau M., Vehicle routing problem with time windows, Part II: Metaheuristics, Transportation Science, 39, 1, pp. 119-139, (2005); Bouthillier A.L., Crainic T.G., A cooperative parallel meta-heuristic for the vehicle routing problem with time windows, Computers & Operations Research, 32, 7, pp. 1685-1708, (2005); Li N., Zou T., Sun D., Particle swarm optimization for vehicle routing problem with time windows, System Engineering Theory & Practice, 24, 4, pp. 130-135, (2004); Zhang L., Chai Y., Improved genetic algorithm for vehicle routing problem with time windows, System Engineering Theory & Practice, 8, 6, pp. 451-454, (2002); Yang Y., Lang M., Hu S., Study on the model and improved simulated annealing algorithm for vehicle routing problem with time windows, J. of Industrial Engineering/Engineering Management, 20, 3, pp. 104-107, (2006); Shi L., Olafsson S., An integrated framework for deterministic and stochastic optimization, Proc. of the 1997 Winter Simulation Conference, pp. 358-365, (1997); Shi L., Olafsson S., Nested partitions method for global optimization, Operations Research, 48, 3, pp. 390-407, (2000); Shi L., Olafsson S., Chen Q., An optimization framework for product design, Management Science, 47, 12, pp. 1681-1692, (2001); Pi L., Pan Y., Shi L., Nested partitions method for the local pickup and delivery problem, Proc. of the 2006 IEEE International Conference on Automation Science and Engineering, pp. 375-380, (2006); Liu C., Su Q., Wei J., Application of nested partitions method in traveling salesman problem, J. of System Simulation, 20, 24, pp. 6858-6861, (2008); Song S., Nested partitions method for vehicle routing problem with stochastic demand, Computer Knowledge and Technology, 5, 9, pp. 2195-2197, (2009); Clausen J., Larsen J., Larsen A., Hansen J., Disruption management - Operations research between planning and execution, Informatics and Mathematical Modelling, 28, 5, pp. 40-43, (2001); Yu G., Qi X., Disruption Management: Framework, Models and Applications, (2004); Hu X., Ding Q., Zhang Y., Wang X., A review on disruption management, Journal of Management Sciences, 20, 2, pp. 2-8, (2007); Wang M., Gao C., Zeng Y., Recovery of the VRPTW disruption and the tabu search algorithm, Journal of Math., 26, 2, pp. 104-110, (2007); Wang X., Niu J., Hu X., Rescue strategies of the VRPTW disruption, System Engineering Theory & Practice, 27, 12, pp. 104-110, (2007); Wang X., Xu C., Hu X., Study on disruption management of vehicle routing problem with the changes of time windows and delivery weight of customers, Journal of Management Sciences, 21, 5, pp. 111-120, (2008); Solomon M.M., Algorithms for the vehicle routing and scheduling problems with time window constraints, Operations Research, 35, 2, pp. 254-265, (1987); Lang M., Optimizing Models and Algorithms in Distribution, (2009)","J. Li; Information School, Beijing Wuzi University, Beijing 101149, China; email: lijuntao@bwu.edu.cn",{"$nulls":7},2.1852766E7,null,null,null,"English","ICIC Express Lett Part B Appl.","Article","Final",null,"Scopus","2-s2.0-79952437082"]
["Lim H.; Shiode N.","Lim, Hyunwoo (24740833800); Shiode, Narushige (6701758603)","24740833800; 6701758603","The impact of online shopping demand on physical distribution networks: A simulation approach",2011.0,"International Journal of Physical Distribution & Logistics Management",41.0,8.0,null,732.0,749.0,17.0,26.0,"10.1108/09600031111166401","https://www.scopus.com/inward/record.uri?eid=2-s2.0-80052627036&doi=10.1108%2f09600031111166401&partnerID=40&md5=864bcaebb1f8a571b39969e64fd740bc","Graduate School of Logistics, Inha University, Incheon, South Korea; School of City and Regional Planning, Cardiff University, Cardiff, United Kingdom","Lim H., Graduate School of Logistics, Inha University, Incheon, South Korea; Shiode N., School of City and Regional Planning, Cardiff University, Cardiff, United Kingdom","Purpose – The purpose of this paper is to study how cost efficiency and the reliability of a physical distribution network are affected by changes in online shopping demand and to suggest how logistics service providers can respond to such changes. Design/methodology/approach – Based on a discrete event simulation approach, possible adaptive measures to online shopping demand increase are tested at three levels of decision making in parcel distribution network: priority assignment in the main hub (operational), introduction of sub-hubs (tactical), and increase in the hub-terminal capacity (strategic). The feasibility of the simulation is tested with parameters adopted from the logistics service data of an existing major parcel carrier in South Korea. Findings – Findings from the simulation model suggest that the existing physical distribution network can improve its cost efficiency and service reliability by evolving into a more centralized network structure with increased capacity of transshipment facilities if the online shopping demand is expected to increase consistently over the long run. Practical implications – This research will help logistics service providers to have good insights into performances of their distribution networks at different levels of demand and to devise a plan for adaptation to meet future demand. Originality/value – This paper provides a framework to understand the complex relationship between network configurations, service levels, costs, and other decision-making processes with respect to changes in online shopping demand based on a simulation approach. © 2011, Emerald Group Publishing Limited","Demand management; Discrete-event simulation; Distribution management; Logistics service; Online shopping; Parcel delivery services; Physical distribution networks; South Korea",{"$nulls":7},"Abernathy F.H., Dunlop J.T., Hammond J.H., Weil D., Retailing and supply chains in the information age, Technology Society, 22, pp. 5-31, (2000); Anderson W.P., Leinbach T.R., E-commerce, logistics and the future of globalized freight, Globalized Freight Transport: Intermoality, E-Commerce, Logistics and Sustainability, (2007); Anderson W.P., Chatterjee L., Lakshmanan T.R., E-commerce, transportation, and economic geography, Growth and Change, 34, pp. 415-432, (2003); Bakos J.Y., The emerging landscape for retail e-commerce, Journal of Economic Perspectives, 15, pp. 69-80, (2001); Borenstein S., Saloner G., Economics and electronic commerce, Journal of Economic Perspectives, 15, pp. 3-12, (2001); User's Manual: Simprocess, (2006); Campbell J.F., Locating transportation terminals to serve an expanding demand, Transportation Research Part B: Methodological, 24, pp. 173-192, (1990); Cheung R.K., Muralidharan B., Impact of dynamic decision making on hub-and-spoke freight transportation networks, Annals of Operations Research, 87, pp. 49-71, (1999); Chong L., Kennedy D., Chan W.M., Direct shipping logistics planning for a hub-and-spoke network with given discrete intershipment times, International Transactions in Operational Research, 13, pp. 17-32, (2006); Colin J., The impact of e-commerce on logistics, (2001); Crainic T.G., Service network design in freight transportation, European Journal of Operations Research, 122, pp. 272-288, (2000); Deshpande P.J., Yalcin A., Zayas-Castro J., Herrera L.E., Simulating less-than-truckload operations, Benchmarking: An International Journal, 14, pp. 1463-5771, (2007); Farag S., Weltevreden J., Rietbergen T., Dijst M.V., Oort F.V., E-shopping in the Netherlands: does geography matter?, Environment and Planning B: Planning and Design, 33, pp. 59-74, (2006); Hesse M., Shipping news: the implications of electronic commerce for logistics and freight transport, Resources, Conservation, and Recycling, 36, pp. 211-240, (2002); Huppertz P., Market changes require new supply chain thinking, Transportation & Distribution, 40, pp. 70-74, (1999); Iida Y., Basic concepts and future directions of road network reliability analysis, Journal of Advanced Transportation, 33, pp. 125-134, (1999); Jayakrishnan R., Cortes C.E., Pages L., Lavanya R., Regan A.C., High Coverage Point to Point Transit (HCPPT): A New Design Concept and Simulation – Evaluation of Operational Schemes, (2005); Lappierre S.D., Ruiz A.B., Soriano P., Desinging distribution networks: formulation and solution heuristics, Transportation Science, 38, pp. 174-187, (2004); Law A.M., Kelton W.D., Simulation Modeling and Analysis, (2006); Lim H., Lim J.W., Lee H., Exploratory study on the efficient operation of parcel delivery network with the growth of online shopping industries, Korean Journal of Marketing, 9, pp. 97-129, (2007); Lin C.-C., Lin J.S., The multistage stochastic integer load planning problem, Transportation Research Part E, 43, pp. 143-156, (2007); Manuj I., Mentzer J.T., Bowers M.R., Improving the rigor of discrete-event simulation in logistics and supply chain research, International Journal of Physical Distribution & Logistics Management, 39, pp. 172-201, (2009); Ren F., Kwan M.-P., The impact of geographic context on e-shopping behavior, Environment and Planning B: Planning and Design, 36, pp. 262-278, (2009); Robinson A., Competition within the United States parcel delivery market, (2003); Smith N., Chow G., Ferreira L., E-business challenge for intermodal freight, Transportation Research Record, 1790, pp. 20-28, (2002); 2007 E-Commerce Multi-Sector E-Stats Report, (2009); Visser E.-J., Lanzendorf M., Mobility and accessibility effects of B2C E-commerce: a literature review, Tijdschrift voor Economische en Sociale Geografie, 95, pp. 189-205, (2004); Weltevreden J.W.J., Rotem-Mindali O., Mobility effects of b2c and c2c e-commerce in the Netherlands: a quantitative assessment, Journal of Transport Geography, 17, pp. 83-92, (2009)",{"$nulls":8},9600035.0,null,null,null,"English","Int. J. Phys. Distrib. Logist. Manage.","Article","Final",null,"Scopus","2-s2.0-80052627036"]
["Mangiaracina R.; Perego A.","Mangiaracina, Riccardo (35325033800); Perego, Alessandro (7004535933)","35325033800; 7004535933","Payment systems in the B2c eCommerce: Are they a barrier for the online customer?",2009.0,"Journal of Internet Banking and Commerce",14.0,3.0,{"$nulls":4},22.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-74949097971&partnerID=40&md5=6a76bdb47ead79bf8217b780757219da","Department of Management, Economics and Industrial Engineering Politecnico di Milano, 20156 Milano, Riccardo Mangiaracina, Via Lambruschini 4/B, Italy","Mangiaracina R., Department of Management, Economics and Industrial Engineering Politecnico di Milano, 20156 Milano, Riccardo Mangiaracina, Via Lambruschini 4/B, Italy; Perego A., Department of Management, Economics and Industrial Engineering Politecnico di Milano, 20156 Milano, Riccardo Mangiaracina, Via Lambruschini 4/B, Italy","The B2c eCommerce is still far from realizing its full potential, despite its considerable growth in all the most important markets (USA, UK, France, Germany, Italy, etc.) in the last ten years. Several hurdles have to be overcome by both the customers and the merchants. One of the most cited is the lack of trust in the electronic payment. This is particularly so for the Italian market where customers have shown a strong reluctance in using the online shopping channel. The study presented in this paper seeks to understand if the payment systems can be considered as a barrier for the B2c eCommerce diffusion. More in detail the objectives of the paper are two-fold: • to give a detailed picture of the payment systems used to shop online and of the main related issues both from the merchant and the consumer side; • to build an explanatory theory to justify the current and future diffusion of the various payment systems that takes into account the factors influencing their suitability for the B2c eCommerce. The analysis is mainly based on case studies among the most important (top100) Italian eCommerce merchants which have been carried out as part of the B2c Observatory of the School of Management of Politecnico di Milano. The latter has studied the online sales in Italy since 2000 and has activated a research stream focused on the payment systems supporting the B2c eCommerce transactions. The 90% of the value of the B2c eCommerce transactions in 2008 in Italy has been supported by electronic Payments (credit cards,65%, eWallets,16%, and bank transfer,9%), but the trust building in the ePayment is low: 52% of the Italian Internet Users is afraid of using the credit card online. Despite the low trust, the security of the credit cards supporting the B2c eCommerce transactions is very high: the online frauds in Italy represent about 0,2% of the value of the online transactions in 2008 and, moreover, most of the frauds take place offline. Fraud prevention systems are widely adopted among the top 100 eCommerce websites: 4 out of 5 adopt at least one of them. The main driver affecting the diffusion of the different payment systems is their suitability to the online channel and not the trust of the users. We clustered the main payment systems according to all the main factors affecting their suitability to support the B2c eCommerce transactions. The most appropriate systems for the B2c eCommerce (we called them \"eCommerce Best fitting\"-credit cards and eWallets), are also the most diffused ones. They are followed by the bank transfer (defined as an \"eCommerce Appropriate\" system) and by all the other systems (loan, cash on delivery, postal order) that have been called \"eCommerce only if necessary\". Trust does not seem to be the critical factor driving the diffusion of the payment systems. The correlation of the diffusion with trust is negligible with respect to the one with suitability. Despite their high trust, cash on delivery and postal orders are not very diffused, while the credit cards, despite their low trust, are the most diffused payment system. © Riccardo Mangiaracina and Alessandro Perego, 2009.","eCommerce; Payment systems",{"$nulls":7},"Indagine Netcomm-gfk Eurisko2009, (2009); Abrazhevich D., Classification and Characteristics of Electronic Payment Systems, Electronic Commerce and Web Technologies, (2001); Chitura T., Et al., Bariers to Electronic Commerce Adoption in Small and Medium Enterprises: A critical Literature Review, Journal of Internet Banking and Commerce, 13, 2, (2008); Eisenhardt K.M., Building theories from case study research, Academy of Management Review, 14, 4, pp. 532-550, (1989); Garrett S., Skevington P.J., An Introduction to eCommerce, Bt Technology Journal, (1999); Hawk S., A comparison of B2c e-Commerce in developing countries, Electronic Commerce Research, (2004); Hsiao-Cheng Y., Kuo-Hua H., Pei-Jen K., Electronic Payment Systems: An Analysis and Comparison of Types, Technology In Society, (2002); Jakobsson M., Mraihi D., Tsiounis Y., Yung M., Electronic Payments: Where Do We Go From Here?, (1999); Johnson C.A., US eCommerce: 2005 to 2010, Forrester Research Report, (2005); Kannen M., Leischner M., Stein T., A framework for Providing Electronic Payment Services, Annual Workshop of Hp-ovua, (2003); Omwando H.K., Europe's Ecommerce: The Next Five Years, (2004); Panurach P., Money in Electronic Commerce: Digital Cash, Electronic Fund Transfer and Ecash Commuincations of The Acm, 39, 6, (1996); Pettigrew A., The Management of Strategic Change, (1988); Sahut J.M., Electronic wallets in danger, Journal of Banking and Commerce, 2, (2006); Yin R.K., Case Study Research: Design and Methods, (2003)","R. Mangiaracina; Department of Management, Economics and Industrial Engineering Politecnico di Milano, 20156 Milano, Riccardo Mangiaracina, Via Lambruschini 4/B, Italy; email: riccardo.mangiaracina@polimi.it",{"$nulls":7},1.2045357E7,null,null,null,"English","J. Internet Bank. Commer.","Article","Final",null,"Scopus","2-s2.0-74949097971"]
["Weber C.L.; Koomey J.G.; Matthews H.S.","Weber, Christopher L. (14017121300); Koomey, Jonathan G. (55909535900); Matthews, H. Scott (7202534265)","14017121300; 55909535900; 7202534265","The energy and climate change implications of different music delivery methods",2010.0,"Journal of Industrial Ecology",14.0,5.0,null,754.0,769.0,15.0,100.0,"10.1111/j.1530-9290.2010.00269.x","https://www.scopus.com/inward/record.uri?eid=2-s2.0-78049473979&doi=10.1111%2fj.1530-9290.2010.00269.x&partnerID=40&md5=0d3095d26735d1e445396e325fb3507f","Carnegie Mellon University, United States; Yale University School of Forestry, United States; Green Design Institute, Carnegie Mellon University, United States","Weber C.L., Carnegie Mellon University, United States; Koomey J.G., Yale University School of Forestry, United States; Matthews H.S., Green Design Institute, Carnegie Mellon University, United States","Summary: The impacts of information and communications technology (ICT) on the environment have been a rich area for research in recent years. A prime example is the continuing rise of digital music delivery, which has obvious potential for reducing the energy and environmental impacts of producing and delivering music to final consumers. This study assesses the energy and carbon dioxide (CO2) emissions associated with several alternative methods for delivering one album of music to a final customer, either through traditional retail or e-commerce sales of compact discs or through a digital download service. We analyze a set of six (three compact disc and three digital download) scenarios for the delivery of one music album from the recording stage to the consumer's home in either CD or digital form. We find that despite the increased energy and emissions associated with Internet data flows, purchasing music digitally reduces the energy and carbon dioxide (CO2) emissions associated with delivering music to customers by between 40% and 80% from the best-case physical CD delivery, depending on whether a customer then burns the files to CD. Despite the dominance of the digital music delivery method, however, there are scenarios by which digital music performs less well, and these scenarios are explored. We suggest future areas of research, including alternative digital media services, such as subscription and streaming systems, for which Internet energy usage may be larger than for direct downloads. © 2010 by Yale University.","Climate change; Energy; Industrial ecology; Information and communications technology (ICT); Life cycle assessment (LCA); Technology and environment","Carbon dioxide; Compact disks; Customer satisfaction; Environmental impact; Information technology; Internet; Media streaming; Sales; Alternative methods; Compact disc; Delivery methods; Digital forms; Digital media; Digital music; E-Commerce; Energy; Energy usage; Industrial ecology; Information and communications technology; Internet data flows; Life cycle assessment (LCA); carbon emission; climate change; consumption behavior; data transmission; ecological approach; energy use; environmental economics; environmental impact assessment; information and communication technology; Internet; life cycle analysis; material flow analysis; music; technological development; Climate change",{"$nulls":6},"Abukhader S., Jonson G., E-tail and the environment: A gateway to the renewal of greening supply chains, International Journal of Technology Management, 28, pp. 274-288, (2004); Atkyns R., Blazek M., Roitz J., Measurement of environmental impacts of telework adoption amidst change in complex organizations: AT&T survey methodology and results, Resources, Conservation, and Recycling, 36, 3, pp. 267-285, (2002); Sept. 16 2008, (2008); 2008 consumer expenditure survey, (2009); Bottrill C., Lye G., Boykoff M., Liverman D., First step: UK music industry greenhouse gas emissions for 2007: Executive summary, (2008); Burnham A., Wang M., Wu Y., Development and applications of GREET 2.7: The transportation vehicle-cycle model, (2006); Davis S.C., Diegel S.W., Transportation energy data book: Edition 26, (2007); (2003); (2002); Annual energy review 2007, (2008); (2009); (2009); Facanha C., Horvath A., Environmental assessment of freight transportation in the U.S, International Journal of Life-Cycle Assessment, 11, 4, pp. 229-239, (2006); Frischknecht R., Rebitzer G., The Ecoinvent database system: A comprehensive Web-based LCA database, Journal of Cleaner Production, 13, 13-14, pp. 1337-1343, (2005); (2009); Harris J., Roturier J., Norford L.K., Rabl A., Technology assessment: Electronic office equipment, (1988); Hendrickson C.T., Lave L.B., Matthews H.S., Environmental life cycle assessment of goods and services: An input-output approach, (2005); Hertwich E.G., Consumption and the rebound effect: An industrial ecology perspective, Journal of Industrial Ecology, 9, 1-2, pp. 85-98, (2005); Hogg N., Jackson T., Digital media and dematerialization: An exploration of the potential for reduced material intensity in music delivery, Journal of Industrial Ecology, 13, 1, pp. 127-146, (2008); Energy balances of OECD countries, (2008); Kawamoto K., Koomey J., Nordman B., Brown R., Piette M., Ting M.K., Meier A., Electricity used by office equipment and network equipment in the U.S, Energy, 27, 3, pp. 255-269, (2002); Koomey J., Piette M., Cramer M., Eto J., Efficiency improvements in U.S. office equipment: Expected policy impacts and uncertainties, Energy Policy, 24, 12, pp. 1101-1110, (1996); Koomey J., Chong H., Loh W., Nordman B., Blazek M., Network electricity use associated with wireless personal digital assistants, ASCE Journal of Infrastructure Systems, 10, 3, pp. 131-137, (2004); Liverman D., Impacts and opportunities: Reducing the carbon emissions of CD packaging, (2009); Matthews H.S., Hendrickson C., Lave L., Harry Potter and the health of the environment, IEEE Spectrum, 37, 11, pp. 20-22, (2000); Matthews H.S., Hendrickson C.T., Soh D.L., Environmental and economic effects of e-commerce: A case study of book publishing and retail logistics, Transportation Research Record 1763, pp. 6-12, (2001); Matthews H.S., Williams E., Tagami T., Hendrickson C.T., Energy implications of online book retailing in the United States and Japan, Environmental Impact Assessment Review, 22, 5, pp. 493-507, (2002); Roth K., Goldstein F., Kleinman J., Energy consumption baseline. Vol. 1, Energy consumption by office and telecommunications equipment in commercial buildings, (2002); Roth K., Ponoum R., Goldstein F., U.S. residential information technology consumption in 2005 and 2010, (2006); Sivaraman D., Pacca S., Mueller K., Lin J., Comparative energy, environmental, and economic analysis of traditional and e-tail DVD rental networks, Journal of Industrial Ecology, 11, 3, pp. 77-91, (2007); Taylor C., Koomey J., Estimating energy use and greenhouse gas emissions of Internet advertising, (2008); Toffel M.W., Horvath A., Environmental implications of wireless technologies: News delivery and business meetings, Environmental Science & Technology, 38, 11, pp. 2961-2970, (2004); Turk V., Alakeson V., Kuhndt M., Rithoff M., The environmental and social impacts of digital music: A case study with EMI, (2003); (2007); US imports and exports of merchandise monthly DVD-ROM, (2005); (2007); Weber C.L., Hendrickson C., Jaramillo P., Matthews H.S., Nagengast A., Nealer R., Life cycle comparison of traditional retail and e-commerce logistics for electronic products: A case study of buy.com, (2009); Weber C.L., Jaramillo P., Marriott J., Samaras C., Life cycle assessment and grid electricity: What do we know and what can we know, Environmental Science & Technology, 44, 6, pp. 1895-1901, (2010); Williams E., Energy intensity of computer manufacturing: Hybrid assessment combining process and economic input-output methods, Environmental Science & Technology, 38, 22, pp. 6166-6174, (2004); Williams E., Tagami T., Energy use in sales and distribution via e-commerce and conventional retail, Journal of Industrial Ecology, 6, 2, pp. 99-114, (2003); (2007)","C.L. Weber; Civil and Environmental Engineering, Pittsburgh, PA, 15217, 118K Porter Hall, 5000 Forbes Ave, United States; email: clweber@cmu.edu",{"$nulls":7},1.530929E7,null,"JINEF",null,"English","J. Ind. Ecol.","Article","Final",null,"Scopus","2-s2.0-78049473979"]
["Smith A.D.","Smith, Alan D. (7406757527)",7.406757527E9,"Customer relationship management: A look at incentive programmes and their usefulness in selected service firms",2009.0,"International Journal of Business Innovation and Research",3.0,1.0,null,1.0,16.0,15.0,15.0,"10.1504/IJBIR.2009.021652","https://www.scopus.com/inward/record.uri?eid=2-s2.0-57349137288&doi=10.1504%2fIJBIR.2009.021652&partnerID=40&md5=ac9d1a4d55413a9ab3f25902e7af71a0","Department of Management and Marketing, Robert Morris University, Pittsburgh, PA 15219-3099, United States","Smith A.D., Department of Management and Marketing, Robert Morris University, Pittsburgh, PA 15219-3099, United States","A total of six organisations within the service industry and regionally headquartered in the Pittsburgh metropolitan area were investigated to study how they strategically leverage Customer Relationship Management (CRM) related concepts in order to attract and retain customers. As evident from the case studies, those companies that have a fixation on technology and did not paid attention to the features and service that customers wanted were in risk of reduced profits and market share. It was found that by maintaining and improving customer and employee loyalty, generating a positive attitude in terms of its culture, maintaining direct communication with customers through newsletters and other forms, leveraging logistics and trade discounts, allowing Knowledge Management (KM) related initiatives and strategies to prevail in its operations, using programmes that highlight their different customers through making reasonable attempts to adapt to customers' changing wants and needs, firms tend to be successful. CRM-related systems and the proper incentives offered to organisations' internal customer, namely employees, have allowed firms to leverage CRM to further differentiate themselves from their competition and ultimately enhance both customer and employee satisfaction. © 2009, Inderscience Publishers.","Case study; CRM; Customer relationship management; Customer retention and loyalty; E-commerce; Incentives; Supply chain management",{"$nulls":7},"Andries B., Gelders L., Time based manufacturing logistics, Logistics Information Management, 8, 3, pp. 30-37, (1995); Anton J., Petouhoff N., Customer Relations Management: The Bottom Line to Optimizing Your ROI, (2002); Baker T., Customer-focused organizations: Challenges for managers, workers and HR practitioners, Journal of Management Development, 21, 3-4, pp. 306-314, (2002); Britt P., Finding the formula for successful CM: Managing financial content, EContent, 28, 1-2, pp. 38-42, (2005); Chiagouris L., Ray I., Saving the world with cause-related marketing, Marketing Management, 16, 4, pp. 48-55, (2007); Coltmanm T., Can superior CRM capabilities improve performance in banking, Journal of Financial Services Marketing, 12, 2, pp. 102-124, (2007); Kotorov R., Customer relationship management: Strategic lessons and future directions, Business Process Management Journal, 9, 5, pp. 566-571, (2003); Hansen M., Nohria N., Tierney T., What's your strategy for managing knowledge?, Harvard Business Review, pp. 106-116, (1999); Hastings D.F., Lincoln Electric's harsh lessons from international expansion, Harvard Business Review, 77, 3, (1999); Johnstone M.-J., Kanitsaki O., Processes influencing the development of graduate nurse capabilities in clinical risk management: An Australian study, Quality Management in Health Care, 15, 4, pp. 268-271, (2006); Krell E., The 2004 CRM elite, Customer Relationship Management, 8, 9, pp. 30-37, (2004); Lindgreen A., The design, implementation and monitoring of a CRM Programme: A case study, Marketing Intelligence and Planning, 22, 2-3, pp. 160-172, (2004); Liljander V., Polsa P., Forsberg K., Do mobile CRM services appeal to loyalty program customers?, International Journal of E-Business Research, 3, 2, pp. 24-39, (2007); McGovern T., Panaro J., The human side of customer relationship management, Benefit quarterly, 20, 3, pp. 26-34, (2004); Michalisin M.D., Smith R.F., Kline D.M., In search of strategic assets, International Journal of Organizational Analysis, 5, 4, pp. 360-387, (1997); Michalisin M.D., Kline D.M., Smith R.F., Intangible strategic assets and firm performance: A multi-industry study of the resource-based view, Journal of Business Strategy, 17, 2, pp. 91-117, (2000); Oller S., Motivating employees, from cash to ping-pong, printers are taking the creative approach to motivation, American Printer, 230, 1, pp. 33-35, (2002); Patterson M., Warr P., West M., Organizational climate and company productivity: The role of employee affect and employee level, Journal of Occupational and Organizational Psychology, 77, 2, pp. 193-201, (2004); Phillip B., Revitalizing your CRM solution, Customer Relationship Management, 9, 4, pp. 19-27, (2005); Porter M.E., Towards a dynamic theory of strategy, Strategic Management Journal, 12, pp. 95-117, (1991); Porter M.E., What is strategy?, Harvard Business Review, 74, 6, pp. 61-78, (1996); Porter M.E., Clusters and the new economics of competition, Harvard Business Review, 76, 6, pp. 77-90, (1998); Porter M.E., Creating advantage, Executive Excellence, 16, 11, pp. 13-14, (1999); Porter M.E., Strategy and the Internet, Harvard Business Review, 79, 3, pp. 62-78, (2001); Porter M.E., Competition and antitrust: Toward a productivity-based approach to evaluating mergers and joint ventures, Antitrust Bulletin, 46, 4, pp. 919-959, (2001); Pries C., Stone M., Managing CRM implementation with consultants CRM or change management, Journal of Change Management, 4, 4, pp. 351-370, (2004); Rado K., Customer relationship management: Strategic lessons and future directions, Business Process Management Journal, 9, 5, pp. 566-572, (2003); Rangan V.K., Integrating distribution strategy and tactics: A model and an application, Management Science, 37, 11, pp. 1377-1385, (1991); Remmen D., Performance pays off, Strategic Finance, 84, 9, pp. 27-32, (2003); Reichheld F., Sasser W.E., Zero defections: Quality comes to services, Harvard Business Review, 68, 5, pp. 105-111, (1990); Smith A.D., Loyalty and e-marketing issues: Customer retention on the web, Quarterly Journal of E-commerce, 3, 2, pp. 149-161, (2002); Smith A.D., Technology advancements for service marketing and quality improvement: Multi-firm case study, Services Marketing Quarterly, 27, 4, pp. 99-113, (2006); Smith A.D., Supply chain management using electronic reverse auction: A multi-firm case study, International Journal of Services and Standards, 2, 2, pp. 176-189, (2006); Smith A.D., Exploring the efficiencies associated with the e-fashions industry, International Journal of Business Information Systems, 1, 4, pp. 353-369, (2006); Smith A.D., CRM & customer service: Strategic asset or corporate overhead?, Handbook of Business Strategy 2006, pp. 87-93, (2006); Smith A.D., Identity theft and e-fraud driving CRM information exchanges, Modeling and Analysis of Enterprise Information Systems, pp. 110-133, (2007); Smith A.D., Mobile technology and communications: Exploring aspects of customer relationship management (CRM), International Journal of Mobile Communications, 5, 6, pp. 618-645, (2007); Soeters J., VanLuijk H., Van Nimwegen T., Managing values and ethics in an international bank, International Journal of Cross Cultural Management, 4, 1, pp. 101-123, (2004)","A.D. Smith; Department of Management and Marketing, Robert Morris University, Pittsburgh, PA 15219-3099, United States; email: smitha@rmu.edu",null,"Inderscience Publishers",{"$nulls":5},1.7510252E7,null,null,null,"English","Int. J. Bus. Innov. Res.","Article","Final",null,"Scopus","2-s2.0-57349137288"]
["Yuan S.-T.; Lu M.-R.","Yuan, Soe-Tsyr (14049457500); Lu, Mei-Rung (26653073500)","14049457500; 26653073500","An value-centric event driven model and architecture: A case study of adaptive complement of SOA for distributed care service delivery",2009.0,"Expert Systems with Applications",36.0,"2 PART 2",null,3671.0,3694.0,23.0,30.0,"10.1016/j.eswa.2008.02.024","https://www.scopus.com/inward/record.uri?eid=2-s2.0-56949095070&doi=10.1016%2fj.eswa.2008.02.024&partnerID=40&md5=de44c3385ea03d3813240397abf49126","MIS Department, National Chengchi University, Wenshan District, Taipei City 11605, No. 64, Sec. 2, ZhiNan Road, Taiwan","Yuan S.-T., MIS Department, National Chengchi University, Wenshan District, Taipei City 11605, No. 64, Sec. 2, ZhiNan Road, Taiwan; Lu M.-R., MIS Department, National Chengchi University, Wenshan District, Taipei City 11605, No. 64, Sec. 2, ZhiNan Road, Taiwan","The Web is now evolving into a medium for providing a wide array of e-commerce and other information based services that are solely based on distributed software interactions for collaborative work. Service-oriented and event-driven architectures (SOA and EDA) are the complementary paradigms for building such distributed information systems based on software interactions as their characteristics of modularity, loose-couplings, and flexibility. However, given the rapid change of the web environment (including the dynamic behavior of the users), these paradigms are not yet able to empower a built system adapting its behavior according to the changes in its environment or in parts of the system itself. This paper presents an architecture of adaptive integration of EDA and SOA based on the novel concept of value-centric processing and communication of events grounded on value theory. This architecture has also been used on a case study of distributed care service delivery. In the architecture, value models are devised to represent events consumed and develop a value-centric mechanism for this adaptive integration. We have also implemented the system and simulated certain representative scenarios in order to justify the claimed values of this adaptive integration on the case study. © 2008 Elsevier Ltd. All rights reserved.","Distributed service delivery; EDA; Electronic care systems; Intelligent agents; SOA; Value theory","Integration; Intelligent agents; Adaptive integration; Distributed information systems; Distributed service delivery; Distributed software; Electronic care systems; Event-driven architectures; Information based services; Value theory; Service oriented architecture (SOA)",{"$nulls":6},"Blau P., Exchange and power in social life, (1964); Canales A., Pena A., Peredo R., Sossa H., Gutierrez A., Adaptive and intelligent web based education system: Towards an integral architecture and framework, Expert Systems with Applications, 33, 4, pp. 1076-1089, (2007); Ekeh P., Social exchange theory, (1974); Eugster P.Th., Felber P.A., Guerraoui R., Kermarrec A.-M., The many faces of publish/subscribe, ACM Computing Surveys, 35, 2, pp. 114-131, (2003); Frondizi R., What is value? An introduction of axiology. 2nd ed., (1971); Homans G., Social behavior, (1961); Levina N., Collaborating on multiparty information systems development projects: A collective reflection-in-action view, Information Systems Research, 16, 2, pp. 109-132, (2005); Maslow A., A theory of human motivation, Psychological Review, 50, 4, pp. 370-396, (1943); Mitchell T., Machine learning, (1997); Niblett P., Graham S., Events and service-oriented architecture: The OASIS Web services notification specifications, IBM Systems Journal, 44, 4, pp. 869-886, (2005); Piaget J., Sociological studies, (1995); Rokeach M., The nature of human values, (1973); Schumpeter J.A., History of Economic Analysis, (1987); Williams A.B., Padmanabhan A., Blake M.B., Experimentation with local consensus ontologies with implications for automated service composition, IEEE Transactions on Knowledge and Data Engineering, 17, 7, pp. 969-981, (2005)","S.-T. Yuan; MIS Department, National Chengchi University, Wenshan District, Taipei City 11605, No. 64, Sec. 2, ZhiNan Road, Taiwan; email: yuans@seed.net.tw",null,"Elsevier Ltd",{"$nulls":5},9574174.0,null,"ESAPE",null,"English","Expert Sys Appl","Article","Final",null,"Scopus","2-s2.0-56949095070"]
["Clinton S.R.","Clinton, Steven R. (7005268246)",7.005268246E9,"Importance of technology investments in the logistics service providers: A case study of UPS and its use of online tools",2008.0,"Journal of Applied Business Research",24.0,2.0,null,67.0,80.0,13.0,4.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-42549135423&partnerID=40&md5=7824be27eeccd7ad8491725944d8366e","Robert Morris University","Clinton S.R., Robert Morris University","Logistics service providers must become competitive in mail delivery, customer relationship management (CRM) strategies, and technological integration. UPS, for example, uses a logistics service strategy to effectively manage the logistical requirements for its 7.9 million daily customers. Within the competitive market of parcel delivery, logistics service providers must routinely invest in technology in an e-commerce environment in order to successfully develop strategies to meet the demands of B2B and B2C customers, while accomplishing customer efficiency and return on investments. This strategy has helped logistics service providers to leverage their core competencies; in particular for UPS to become the shipping industry leader in e-commerce. This research outlines the history, inner workings and culture of UPS, while simultaneously examining the subtleties, which have led to the company's extraordinary success. Throughout this analysis, the research will show that in fact there is a rather complex model, which allows UPS to function, as it incorporates B2B, B2C, investments in technology and on-line tools into an outcome of seemingly effortless customer efficiency.",{"$nulls":17},8927626.0,null,null,null,"English","J. Appl. Bus. Res.","Article","Final",null,"Scopus","2-s2.0-42549135423"]
["Kamarulzaman N.H.; Nawi N.M.","Kamarulzaman, Nitty Hirawaty (6506933695); Nawi, Nolila Mohd (57209294954)","6506933695; 57209294954","The use of internet applications in managing logistics activities among palm oil industry participants",2009.0,"International Journal of Economics and Management",3.0,2.0,null,262.0,277.0,15.0,3.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-77953595990&partnerID=40&md5=abff8bfa29e5804414f9ea6d58944448","Department of Agribusiness and Information Systems, Faculty of Agriculture Universiti Putra, Malaysia","Kamarulzaman N.H., Department of Agribusiness and Information Systems, Faculty of Agriculture Universiti Putra, Malaysia; Nawi N.M., Department of Agribusiness and Information Systems, Faculty of Agriculture Universiti Putra, Malaysia","With the advancement of Internet technologies, many companies have adopted the use of the technologies to improve the efficiency and effectiveness of their activities. This paper aims to investigate the utilization of Internet technologies in the Malaysian Palm Oil Industry (MPOI) and explore how the technologies have been exploited by the palm oil industry participants to manage their logistics activities. The respondents of the study were the MPOI participants involved in Internet-based activities. The findings revealed that Internet applications were still new and at an early stage. Many participants did not realise the potential of advanced Internet technologies in managing their business activities. Lack of understanding of advanced Internet technologies explains the low level of utilization of these technologies among the MPOI participants. Most of the participants were comfortable with conventional ways of managing their logistics activities.","E-Commerce; E-Logistics; Internet; Logistics activities",{"$nulls":7},"Ahmad F., Zakaria N.H., Osman W.R.S., Transforming Information-Based Agricultural Portal to Knowledge-Based Agricultural Hub, 2008, pp. 1-4, (2008); Bendoly E., Schoenherr T., ERP System and Implementation-Process Benefits: Implications for B2B E-Procurement, International Journal of Operations & Production Management, 25, 4, pp. 304-319, (2005); Benjamin R.I., Wigand R., Electronic Markets and Virtual Value Chains on the Information Highway, Sloan Management Review, 36, 2, pp. 62-72, (1995); Chaffey D., E-Business and E-Commerce Management: Strategy, Implementation and Practice, (2002); Chapman R.L., Soosay C., Kandampully J., Innovation in Logistic Services and the New Business Model: A Conceptual Framework, Managing Service Quality, 12, 6, pp. 358-371, (2002); Davila A., Gupta M., Palmer R., Moving Procurement Systems to the Internet: The Adoption and Use of E-Procurement Technology Models, European Management Journal, 21, 1, pp. 11-23, (2003); Elliff S.A., Who's Who? Sorting Out the E-Logistics Players, Logistics Management and Distribution Report, (2001); Fritz M., Hausen T., Electronic Trade Platforms in Food Networks: An Analysis of Emerging Platform Models and Strategies, Journal of Information Technology in Agriculture, 3, pp. 26-36, (2008); Garau C., Ranchhod A., Hackney R., Internet Transactions and Physical Logistics: Conflict or Complementary?, Logistics Information Management, 14, 1-2, pp. 33-43, (2001); Hartley J.L., Lane M.D., Hong Y., An Exploration of the Adoption of E-Auctions in Supply Management, IEEE Transactions on Engineering Management, 51, 2, pp. 153-161, (2004); Hesse M., Shipping News: The Implications of Electronic Commerce for Logistics and Freight Transport, Resources, Conservation & Recycling, 36, pp. 211-240, (2002); Hidalgo J.cnM., Overview: impact of electronic commerce on logistics/supply chain management, (2000); Hultkrantz O., Lumsden K., E-Commerce and Consequences for the Logistics Industry, (2001); Juliana H.K., Dianne C.L., Azlin A., Measuring the Perception of Malaysian SME towards E-Commerce as an Innovation, pp. 14-15, (2009); Karestos S., Costopoulou C., Lambrou M., Zorkadis V., The Use of Intelligent Agents in the E-agribusiness Environment, pp. 19-26, (2002); Khatibi A., Haque A., Ismail H., Al Mahmud S., Factors Driving Electronic Commerce Initiative in Malaysian Organization, Journal of Social Science, 14, 1, pp. 1-11, (2007); Kheng C.B., Al-Hawamdeh S., The Adoption Of Electronic Procurement in Singapore, Electronic Commerce Research, 2, 1-2, (2002); Le T.T., Koh A.C., A Managerial Perspective on Electronic Commerce Development in Malaysia, Electronic Commerce Research, 2, 1-2, pp. 7-29, (2002); Lewis I., Logistics and Electronic Commerce: An Interorganizational Systems Perspective, Transportation Journal, Summer, 40, 4, pp. 5-13, (2001); Liew V.K., The Prospect of E-commerce for the Small and Medium Enterprises in Malaysia, (2002); Lockett N., Brown D.H., A Framework for the Engagement of SMEs in E-Business, (2001); (2008); Mohd Zulkifli M.A.A., Small Medium Enterprise: Taking the First Steps into E-Commerce. Accessed date: 23 June 2009, (2001); Muffatto M., Payaro A., Implementation of E-Procurement and E-Fulfilment Processes: A Comparison of Cases in the Motorcycle Industry, International Journal of Production Economics Manufacturing Strategy, 89, 3, pp. 339-351, (2004); Nedyalkov A., Borisova V., Internet Penetration in Agriculture Markets: The Pattern of Bulgaria and Ukraine, (2005); Paterson J., E-Procurement: The New Model for Purchasing in the Internet Age, Touch Briefings, (2005); Prahalad C.K., Hamel G., The Core Competence of the Corporation, Harvard Business Review, pp. 79-91, (1990); Presutti W.D. Jr., Supply Management and E-Procurement: Creating Value Added in the Supply Chain, Industrial Marketing Management, 32, 3, pp. 219-226, (2003); Puschmann T., Alt R., Successful Use of E-Procurement in Supply Chains, Supply Chain Management: An International Journal, 10, 2, pp. 122-133, (2005); Rabah M.Y., Mahmassani H.S., Impact of Electronic Commerce on Logistics Operations: A Focus on Vendor Managed Inventory Strategies, (2002); Roumana M., Vlachopoulou M., Manos B., E-commerce in Agriculture: Applications, Impacts, Benefits and Drawbacks, pp. 93-102, (2002); Rutner S.M., Gobson B.J., Williams S.R., The Impact of the Integrated Logistics Systems on Electronic Commerce and Enterprise Resource Planning Systems, Transportation Research Part E: Logistics and Transportation Review, 39, 2, pp. 83-93, (2003); Schiefer G., The New Technologies and their Impact to Agriculture, the Environment and the Food Industry, pp. 93-102, (2002); Singer T., MRO E-Procurement: Where Is It Now?, Plant Engineering, 57, pp. 28-29, (2003); (2004); Sondoh S.L. Jr., Tanakinjal G.H., Supporting Readiness of Small and Medium Industries in Malaysia, pp. 21-22, (2002); Sulaiman A., The Status of E-Commerce Applications in Malaysia, Information Technology for Development, 9, 3-4, pp. 153-163, (2000); Suraya R.M.Y., Culture and the Acceptance Usage of E-Business: Is there a Dilemma?, ICEC Proceedings, pp. 10-11, (2005); Thompson R., Manrodt K., Holcomb M., Allen G., Hoffman R., Logistics @ Internet speed: the impact of e-commerce on logistics, (2000); Vlachopoulou M., Manthou V., A Portal for Agricultural and Agribusiness Network, pp. 27-36, (2002); Vlachos P., Business-to-Business E-commerce: the Innovative Tool for Effective Food Chain Management, pp. 37-46, (2002); Warnert J., Agriculture is a Growing Part of the E-commerce World, News and Information Outreach, (2000); Yang M.H., Liao C.H., Liu S.C., Applying Internet-Based Information Systems to Facilitate Business Alliance Activities, Industry Management & Data Systems, 107, 1, pp. 125-140, (2007)","N.H. Kamarulzaman; Department of Agribusiness and Information Systems, Faculty of Agriculture Universiti Putra, Malaysia; email: nitty@agri.upm.edu.my",{"$nulls":7},"1823836X",null,null,null,"English","Int. J. Econ. Manage.","Article","Final",null,"Scopus","2-s2.0-77953595990"]
["Xing Long X.I.E.","Xing Long, X.I.E. (57224425338)",5.7224425338E10,"Scaling service quality of five distribution firms serving e-commerce from services science, management and engineering",2012.0,"Research Journal of Applied Sciences, Engineering and Technology",4.0,11.0,null,1536.0,1544.0,8.0,0.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-84862095864&partnerID=40&md5=f76d3112d536913e59ccecd834f07df5","Xi'an University of Technology, Xi'an 710048, China","Xing Long X.I.E., Xi'an University of Technology, Xi'an 710048, China","In this study, we outline business characteristics of a distribution company in the context of E-commerce spreading far and wide as well as its operation forms. Firstly, we set an indicator framework for a measurement of distribution service quality from services science, management and engineering. Then, we score five distribution firms, which engage in B-C business, through the AHP method. In this way, we concludes that among all dimensions of assessing distribution service quality for E-commerce, distribution service is the most important and information service is fairly important. Moreover, we also finds that all sampling firms have achieved superior performance in both customer and order processing services but three companies need to put a larger quantity of efforts into information service for enhancing performance of logistics distribution for E-commerce. The paper concludes with pointing out limitations and a future research direction.© Maxwell Scientific Organization, 2012.","Engineering; Physical distribution; Service quality; Services science","Electronic commerce; Engineering; Information services; Quality of service; AHP method; Distribution companies; Distribution services; Future research directions; Logistics distribution; Order processing; Physical distribution; Service Quality; Services Science; Industry",{"$nulls":6},"Abe T., What is service science?, (2005); Agatz N.A.H., Fleischmann M., Van Nunen J.A.E.E., E-fulfillment and multi-channel distribution-a review, Eur. J. Oper. Res., 187, pp. 339-356, (2008); Aldin N., Stahre F., Electronic commerce, marketing channels and logistics platforms-a wholesaler perspective, Eur. J. Oper. Res., 144, pp. 270-279, (2003); Bailey J.P., Rabinovich E., The adoption of inventory postponement and speculation: An empirical assessment of oligopolistic internet retailers, Transport. Res. E-Log., 42, 4, pp. 258-271, (2006); Bitner M.J., (2008); Cai H., Yeh J., Su H., Relooking at services science and services innovation, SOCA, 2, pp. 1-14, (2008); Chesbrough H., Spohrer J., A research manifesto for services science, Commun. ACM, 49, 7, pp. 35-40, (2006); Cho J.J.K., Ozment J., Sink H., Logistics capability, logistics outsourcing and firm performance in an e-commerce market, Int. J. Phys. Distr. Logist. Manage., 38, 5, pp. 336-359, (2008); Esper T.L., Jensen T.D., Turnipseed F.L., Burton S., The last mile: An examination of effects of online retail delivery strategies on consumers, J. Bus. Logistics, 24, pp. 177-203, (2003); Frederick R., Physical distribution service: A neglected aspect of marketing management, MSU Bus. Topics, 22, pp. 37-45, (1974); Guo C.Q., Services Science-an emerging research field, Bull. Nat. Nat. Sci. Foundation, 4, pp. 217-220, (2008); Heim G.R., Field J.M., Process drivers of eservice quality: Analysis of data from an online rating site, J. 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["Sinha J.; Kim J.","Sinha, Jayendra (57317828800); Kim, Jiyeon (57865569200)","57317828800; 57865569200","Factors affecting Indian consumers’ online buying behavior",2012.0,"Innovative Marketing",8.0,2.0,null,46.0,57.0,11.0,19.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-84983308904&partnerID=40&md5=23b32983306de44adc1b195b5cfd02ba","United States","Sinha J., United States; Kim J., United States","India has been gaining importance as a high potential lucrative market for global retailers. Since the recent economic reforms, Indian consumers have just begun to understand benefits of using Internet for shopping. However, the growing number of Internet users has not been reflected to the online sales. Thus, it is important to identify factors affecting Indian consumers’ online buying behavior in order to find the way to stimulate their online shopping behavior. The purpose of this study is to identify factors affecting Indian consumers’ attitude toward shopping online by investigating Indian consumers’ risk perceptions about shopping online. Constructs tested included previously identified factors (convenience risk, product risk, financial risk, perceived behavior control, return policy, subjective norm, attitude, and technology specific innovativeness) and Indian-specific factors (concerns associated with delivery of an ordered product and cyber laws, shipping fees, and after service) specifically developed for this study. The concerns associated with delivery of product, social and perceived behavioral control have been found to be significant factors affecting attitude toward using Internet for shopping. In terms of gender difference, perceived risks (product, convenience, financial, and non-delivery) and technology specific innovativeness were found to be significant for males and, for females, convenience risk and attitude towards online shopping were significant factors. © Jayendra Sinha, Jiyeon Kim, 2012.","Indian consumer behavior; Online shopping",{"$nulls":7},"Agarwal R., Prasad J., A conceptual and operational definition of personal innovativeness in the domain of information technology, Information Systems Research, 9, 2, pp. 204-215, (1998); Ajzen I., From intentions to actions: A theory of planned behavior, Action-Control: From Cognition to Behavior, pp. 11-39, (1985); Ajzen I., Madden T.J., Prediction of goal-directed behavior: Attitudes, intentions, and perceived behavioral control, Journal of Experimental Social Psychology, 22, pp. 453-474, (1986); Bailay R., In India, shopping takes on a whole new meaning, Wall Street Journal (Eastern Edition), (2003); Beilock R., Dimitrova D.V., An exploratory model of inter-country internet diffusion, Telecommunications Policy, 27, 3-4, pp. 237-252, (2003); Bellman S., Lohse G.L., Johnson E.J., Predictors of online buying behavior, Communications of the ACM, 42, 12, pp. 32-38, (1999); Bhatnagar A., Ghose S., Segmenting consumers based on the benefits and risks of internet shopping, Journal of Business Research, 57, 12, pp. 1352-1360, (2004); Bhatnagar A., Misra S., Rao H.R., On risk, convenience and internet shopping behavior, Communications of the ACM, 48, 2, pp. 98-105, (2000); Bingi P., Ali M., Khamalah J., The challenges facing global e-commerce, Information Systems Management, pp. 26-34, (2000); Biswas D., Biswas A., Perceived risks in online shopping: Do signals matter more on the web?, Journal of Interactive Marketing, 18, 3, pp. 30-45, (2004); Cho C.H., Kang J., Cheon J.H., Online shopping hesitation, Cyber Psychology & Behavior, 9, 3, pp. 261-274, (2006); Choi J., Lee K.H., Risk perception and e-shopping: A cross-cultural study, Journal of Fashion Marketing and Management, 7, 1, pp. 49-64, (2003); Cox D.F., Rich S.J., Perceived risk and consumer decision-making: The case of telephone shopping, Journal of Marketing Research, 1, 4, pp. 32-39, (1964); Desai A., Adaptive india-changing market scenario, European Association for Comparative Economics Studies EACES 9th Bi-Annual Conference: Development Strategies – A Comparative View, (2006); Donthu N., Garcia A., The internet shopper, Journal of Advertising Research, 39, 3, pp. 52-58, (1999); Dowling G.R., Staelin R., A model of perceived risk and intended risk-handling activity, Journal of Consumer Research, 21, 1, pp. 119-134, (1994); Eastlick M.A., Predictors of videotext adoption, Journal of Direct Marketing, 7, pp. 66-74, (1993); Ernst, Young, Third Annual Online Retailing Report, (1999); Explaining The Global Digital Divide: Economic, Political, and Sociological Drivers of Cross-National Internet Use, (2004); Festervand T.A., Snyder D.R., Tsalikis J.D., Influence of catalog vs. Store shopping and prior satisfaction on perceived risk, Academy of Marketing Science Journal, 14, 4, pp. 28-37, (1986); Fishbein M., Ajzen I., Belief, Attitude, Intention and Behavior: An Introduction to Theory and Research, (1975); Flynn L.R., Goldsmith R.E., A validation of the goldsmith and hofacker innovativeness scale, Educational and Psychological Measurement, 53, 4, pp. 1105-1116, (1993); Forsythe S.M., Shi B., Consumer patronage and risk perceptions in internet shopping, Journal of Business Research, 56, 11, pp. 867-875, (2003); Forsythe S.M., Liu C., Shannon D., Gardner L.C., Development of a scale to measure the perceived benefits and risks of online shopping, Journal of Interactive Marketing, 20, 2, pp. 55-75, (2006); Garbarino E., Strahilevitz M., Gender differences in the perceived risk of buying online and the effects of receiving a site recommendation, Journal of Business Research, 57, pp. 768-775, (2004); George J.F., The theory of planned behavior and internet purchasing, Journal of Internet Research, 14, 3, pp. 198-212, (2004); Goldsmith R.E., Hofacker C.F., Measuring consumer innovativeness, Journal of the Academy of Marketing Science, 19, pp. 1004-1016, (1991); Goldsmith R.E., Freiden J.B., Eastman J.K., The generality/specificity issue in consumer innovativeness research, Technovation, 15, 10, pp. 601-612, (1995); Guillen M.F., Suarez S.L., Developing the internet: Entrepreneurship and public policy in Ireland, Singapore, Argentina, and spain, Telecommunications Policy, 25, pp. 349-371, (2001); Hae Y.L., Qu H., Yoo S.K., A study of the impact of personal innovativeness on online travel shopping behavior – a case study of korean travelers, Tourism Management, 28, 3, pp. 886-897, (2007); Hamel G., Sampler J., December 7. 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Mark.","Article","Final",null,"Scopus","2-s2.0-84983308904"]
["Darbyshire P.","Darbyshire, Paul (7005813856)",7.005813856E9,"Adding value to SMEs in the courier industry by adopting a web-based service delivery model",2008.0,"Journal of Electronic Commerce in Organizations",6.0,4.0,null,47.0,76.0,29.0,1.0,"10.4018/jeco.2008100104","https://www.scopus.com/inward/record.uri?eid=2-s2.0-56549101392&doi=10.4018%2fjeco.2008100104&partnerID=40&md5=9d0188ab1677eff281f4ed88a933d61b","Victoria University, Melbourne, VIC, Australia","Darbyshire P., Victoria University, Melbourne, VIC, Australia","The aim of this research is to design a framework for a Web system that is intended for linking small and medium transport companies with their customers. The unique aspects of the framework are two-fold. The framework utilizes Web services, which means that it can be applied to existing software and hardware environments. This reduces the need for specialized integration and development, the cost of which becomes a further barrier to SMEs in adding value to customers through existing systems. The framework is additionally designed to link both communities of SMEs and customers in a fledgling digital ecosystem arrangement. Such arrangements offer inherent added value to both types of participants. Copyright © 2008, IGI Global.","Architecture; Courier industry; Digital ecosystem; E-commerce; SME; Value-added services; Web services","Architecture; Ecology; Ecosystems; Electronic commerce; Network function virtualization; Sales; Web crawler; Websites; Added values; Courier industry; Digital ecosystem; Existing systems; Software and hardwares; Transport companies; Value added service; Web-based service; Web services",{"$nulls":6},"Bieberstein N., Et al., Service-oriented architecture compass: Business value, planning, and enterprise roadmap, (2005); Campbell A., Technology levels the playing field, (2004); Canada I.T., TMW systems acquires Maddocks Systems Inc, (2006); Cerami E., Web services essentials, (2002); Chang E., West M., Hadzic M., A digital ecosystem for extended logistics enterprises, Proceedings of the 11th International Workshop on Telework, (2006); Chang V., Uden L., The three e's: E-learning, e-knowledge and e-ecosystems for SMEs, Proceedings of the Eighth International We-B (Working for E-Business) Conference, (2007); Technology information center, (2005); Digital business ecosystems, (2004); Giorgetti M., Louarn M.L., Technologies for digital ecosystems - Supporting regional growth and innovation, (2004); Nexus G.T., GT Nexus' Web site, (2005); Morlok E., Nitzberg B., Balasubramaniam K., The parcel service industry in the US: Its Size and role in commerce, Tech. Rep, (2000); Newcomer E., Understanding Web services: XML, WSDL, SOAP, and UDDI, (2002); Nickerson J., Hamilton B., Wada T., Market position, resource profile, and governance: Linking Porter and Williamson in the context of international courier and small package services in Japan, Strategic Management Journal, 22, 3, pp. 251-273, (2001); Roy J., Recent trends in logistics and the need for real-time decision tools in the trucking industry, Proceedings of the 34th Annual Hawaii International Conference, (2001); Logistics sample application: Design, (2003); Warkentin M., Bajaj A., The On-demand delivery services model for e-commerce, Managing business with electronic commerce: Issues and trends, (2001); Postal and courier services (S/C/W/39), (1998); Zhang L.-J., Chang H., E-logistics processes integration framework, (2002)",null,null,"IGI Publishing",{"$nulls":5},1.5392937E7,null,null,null,"English","J. Electr. Commer. Organ.","Article","Final",null,"Scopus","2-s2.0-56549101392"]
["Malmarugan D.","Malmarugan, Devanathan (57965487000)",5.7965487E10,"Strategic model for predicting customer’s intention to purchase apparel online",2008.0,"Innovative Marketing",4.0,1.0,null,29.0,36.0,7.0,2.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85065569575&partnerID=40&md5=76c0600061ac53546f43f6e6a972fa32","India","Malmarugan D., India","Shopping for apparel over the internet is a growing phenomenon. Customers make use of the net for information search and purchase. Based on the extensive literature review the objectives of the research are to enlist the service quality parameters, customers expect in online shopping for apparel, and to develop a prediction model using logistic regression, for purchase intention of consumers. This research paper discusses the service quality parameters, the customers expect from online shopping of apparel. The parameters are grounded from available literature on the topic. The tool (questionnaire) and items were developed based on literature, and series of focus group interviews. The reliability was found to be good. The responses were collected from customers from various demographic segments. Based on empirical research, a prediction model for customers intention to purchase is developed. The parameters and the prediction model are useful for decision makers in online marketing of apparel. © Devanathan Malmarugan, 2008.","Apparel; Online marketing; Prediction model; Service quality parameters",{"$nulls":7},"Aladwani A.M., Palvia P.C., Developing and validating an instrument for measuring user-perceived Web quality, Information & Management, 6, pp. 467-476, (2002); Beck B., Key Strategic Issues in Online Apparel Retailing: The Need for An Online Fitting Solution, pp. 2-3, (2001); Bhatnagar A., Misra S., Rao H.R., On risk, convenience, and Internet shopping behavior, Communications of the ACM, 11, 43, pp. 98-105, (2000); Bienstock C.C., Measuring physical distribution service quality, Journal of the Academy of Marketing Science, 1, 25, pp. 31-44, (1997); Beaudry L.M., Consumer catalog shopping survey, Catalog Age, 6, 16, pp. a5-a18, (1999); Cox J., Dale B.G., Service quality and e-commerce: An exploratory analysis, Managing Service Quality, 2, 11, pp. 121-131, (2001); Darden W.R., Reynolds F.D., Backward profiling of Male innovators, Journal of Marketing Research, 11, pp. 79-85, (1974); 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Liu C., Arnett K.P., Exploring the factors associated with Web site success in the context of electronic commerce, Information & Management, 1, 38, pp. 23-34, (2000); Lohse G.L., Spiller P., Internet retailer store design: How the user interface influence traffic and sales, Journal of Computer-Mediated Communication; Madu C.N., Madu A.A., Dimensions of e-quality, International Journal of Quality & Reliability Management, 3, 19, pp. 246-258, (2002); Parasuraman A., Zeithaml V.A., Berry L.L., SeRVQUAL: A multiple-item scale for measuring consumer perceptions of service quality, Journal of Retailing, 1, 64, pp. 12-40, (1988); Parasuraman A., Zeithaml V.A., Berry L.L., A conceptual model of service quality and its implications for future research, Journal of Marketing, 4, 49, pp. 41-50, (1985); Pastore M., Women Use Web to Change Social Landscape; Pastore M., The Lifestyle of the Online Shoppers, (1999); Pastore M., Online Clothing Sales Continue Climbing E-Commerce Ladder; Pepermans R., Verleye G., Cappellen S.V., Wallbanking’, innovativeness and computer attitudes: 25-40-year-old ATM-users on the spot, Journal of Economic Psychology, 17, pp. 731-748, (1996); 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Yoo B., Donthu N., Developing a scale to measure the perceived quality of Internet shopping sites (SITEQUAL), Quarterly Journal of Electronic Commerce, 1, 2, pp. 31-47, (2001); Zhang P., Von Dran G.M., User expectations and rankings of quality factors in different Web site domains, International Journal of Electronic Commerce, 2, 6, pp. 9-35, (2001); Zeithaml V.A., Parasuraman A., Malhotra A., A conceptual framework for understanding e-service quality: Implications for future research and managerial practice, Working Paper, (2000)",null,null,"LLC CPC Business Perspectives",{"$nulls":5},1.8142427E7,null,null,null,"English","Innov. Mark.","Article","Final",null,"Scopus","2-s2.0-85065569575"]
["Ayday E.; Fekri F.","Ayday, Erman (20435500700); Fekri, Faramarz (6603758115)","20435500700; 6603758115","An Iterative Algorithm for Trust Management and Adversary Detection for Delay-Tolerant Networks",2012.0,"IEEE Transactions on Mobile Computing",11.0,9.0,null,1514.0,1531.0,17.0,77.0,"10.1109/TMC.2011.160","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85008532916&doi=10.1109%2fTMC.2011.160&partnerID=40&md5=903e857d23fee186fa9c2f0289424984","Department of Electrical and Computer Engineering, Georgia Institute of Technology, GA 30332, Georgia","Ayday E., Department of Electrical and Computer Engineering, Georgia Institute of Technology, GA 30332, Georgia; Fekri F., Department of Electrical and Computer Engineering, Georgia Institute of Technology, GA 30332, Georgia","Delay/Disruption Tolerant Networks (DTNs) have been identified as one of the key areas in the field of wireless communication, wherein sparseness and delay are particularly high. They are emerging as a promising technology in vehicular, planetary/interplanetary, military/tactical, disaster response, underwater and satellite networks. DTNs are characterized by large end-to-end communication latency and the lack of end-to-end path from a source to its destination. These characteristics pose several challenges to the security of DTNs. Especially, Byzantine attacks in which one or more legitimate nodes have been compromised and fully controlled by the adversary can give serious damages to the network in terms of latency and data availability. Using reputation-based trust management systems is shown to be an effective way to handle the adversarial behavior in Mobile Ad hoc Networks (MANETs). However, because of the unique characteristics of DTNs, those traditional techniques do not apply to DTNs. Our main objective in this paper is to develop a robust trust mechanism and an efficient and low cost malicious node detection technique for DTNs. Inspired by our recent results on reputation management for online systems and e-commerce, we develop an iterative malicious node detection mechanism for DTNs referred as ITRM. The proposed scheme is a graph-based iterative algorithm motivated by the prior success of message passing techniques for decoding low-density parity-check codes over bipartite graphs. Applying ITRM to DTNs for various mobility models, we observed that the proposed iterative reputation management scheme is far more effective than well-known reputation management techniques such as the Bayesian framework and EigenTrust. Further, we concluded that the proposed scheme provides high data availability and packet-delivery ratio with low latency in DTNs under various adversary attacks which attempt to both undermine the trust and detection scheme and the packet delivery protocol. © 2012 IEEE","delay-tolerant networks; iterative algorithms; malicious node detection; Security; trust and reputation management",{"$nulls":5},"Cisco University Research Program Fund; US National Science Foundation, (IIS-1115199); Silicon Valley Community Foundation, SVCF","This material is based upon work supported by the US National Science Foundation under Grant No. IIS-1115199, and a gift from the Cisco University Research Program Fund, an advised fund of Silicon Valley Community Foundation.","Fall K., A Delay-Tolerant Network Architecture for Challenged Internets, Proc. ACM SIGCOMM, pp. 27-34, (2003); Wang Y., Jain S., Martonosi M., Fall K., Erasure-Coding Based Routing for Opportunistic Networks, Proc. ACM SIGCOMM Workshop Delay-Tolerant Networking (WDTN ′05), pp. 229-236, (2005); Zhu Y., Guo D., Honig M.L., A Message-Passing Approach for Joint Channel Estimation, Interference Mitigation and Decoding, IEEE Trans. Wireless Comm., 8, 12, pp. 6008-6018, (2009); Pishro-Nik H., Fekri F., Results on Punctured Low-Density Parity-Check Codes and Improved Iterative Decoding Techniques, IEEE Trans. Information Theory, 53, 2, pp. 599-614, (2007); Ayday E., Lee H., Fekri F., An Iterative Algorithm for Trust and Reputation Management, Proc. IEEE Intŉl Symp. Information Theory (ISIT ′09), (2009); Pirzada A.A., McDonald C., Datta A., Performance Comparison of Trust-Based Reactive Routing Protocols, IEEE Trans. Mobile Computing, 5, 6, pp. 695-710, (2006); Marti S., Giuli T., Lai K., Baker M., Mitigating Routing Misbehavior in Mobile Ad-Hoc Networks, Proc. ACM MobiCom, pp. 255-265, (2000); Paul K., Westhoff D., Context Aware Detection of Selfish Nodes in DSR Based Ad-Hoc Networks, Proc. IEEE GlobeCom, pp. 178-182, (2002); Buchegger S., Boudec J., Performance Analysis of CONFIDANT Protocol (Coorperation of Nodes: Fairness in Dynamic Ad-Hoc Networks), Proc. ACM MobiHoc, (2002); Buchegger S., Boudec J., A Robust Reputation System for P2P and Mobile Ad-Hoc Networks, Proc. Second Workshop the Economics of Peer-to-Peer Systems, (2004); Ayday E., Fekri F., Using Node Accountability in Credential Based Routing for Mobile Ad-Hoc Networks, Proc. Fifth IEEE Intŉl Conf. Mobile Ad-Hoc and Sensor Systems, (2008); Ayday E., Fekri F., A Protocol for Data Availability in Mobile Ad-Hoc Networks in the Presence of Insider Attacks, Elsevier Ad Hoc Networks, 8, 2, pp. 181-192, (2010); Dewan P., Dasgupta P., Bhattacharya A., On Using Reputations in Ad-Hoc Networks to Counter Malicious Nodes, Proc. 10th Intŉl Conf. Parallel and Distributed Systems (ICPADS ′04), (2004); Liu K., Deng J., Varshney P.K., Balakrishnan K., An Acknowledgment-Based Approach for the Detection of Routing Misbehavior in MANETs, IEEE Trans. Mobile Computing, 6, 5, pp. 536-550, (2007); Yu W., Liu K.R., Game Theoretic Analysis of Cooperation Stimulation and Security in Autonomous Mobile Ad-Hoc Networks, IEEE Trans. Mobile Computing, 6, 5, pp. 507-521, (2007); Resnick P., Zeckhauser R., Friedman E., Kuwabara K., Reputation Systems: Facilitating Trust in Internet Interactions, Comm. ACM, 43, 12, pp. 45-48, (2000); J0sang A., Ismail R., Boyd C., A Survey of Trust and Reputation Systems for Online Service Provision, Decision Support Systems, 43, 2, pp. 618-644, (2007); Aberer K., Despotovic Z., Managing Trust in a Peer-2-Peer Information System, Proc. 10th Intŉl Conf. Information and Knowledge Management (CIKM ′01), pp. 310-317, (2001); Cornelli F., Damiani E., di Vimercati S.D.C., Paraboschi S., Samarati P., Choosing Reputable Servents in a P2P Network, Proc. 11th Intŉl Conf. World Wide Web (WWW ′02), pp. 376-386, (2002); Damiani E., di Vimercati D.C., Paraboschi S., Samarati P., Violante F., A Reputation-Based Approach for Choosing Reliable Resources in Peer-to-Peer Networks, Proc. Ninth ACM Conf. Computer and Comm. Security (CCS ′02), pp. 207-216, (2002); Kamvar S.D., Schlosser M.T., Garcia-Molina H., The Eigentrust Algorithm for Reputation Management in P2P Networks, Proc. 12th Intŉl Conf. World Wide Web (WWW ′03), pp. 640-651, (2003); Dellarocas C., Immunizing Online Reputation Reporting Systems against Unfair Ratings and Discriminatory Behavior, Proc. Second ACM Conf. Electronic Commerce (EC ′00), pp. 150-157, (2000); Macnaughton-Smith P., Williams W.T., Dale M.B., Mockett L.G., Dissimilarity Analysis: A New Technique of Hierarchical Sub-Division, Nature, 202, pp. 1034-1035, (1964); Seth A., Keshav S., Practical Security for Disconnected Nodes, Proc. First IEEE ICNP Workshop Secure Network Protocols (NPSec), pp. 31-36, (2005); Cui S., Duan P., Chan C., An Efficient Identity-Based Signature Scheme with Batch Verifications, Proc. First Intŉl Conf. Scalable Information Systems (InfoScale ′06), (2006); Kate A., Zaverucha G., Hengartner U., Anonymity and Security in Delay Tolerant Networks, Proc. Third Intŉl Conf. Security and Privacy in Comm. Networks (SecureComm ′07), (2007); Burgess J., Bissias G., Corner M., Levine B., Surviving Attacks on Disruption-Tolerant Networks without Authentication, Proc. Eighth ACM Intŉl Symp. 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First Intŉl MobiSys Workshop Mobile Opportunistic Networking (MobiOpp ′07), pp. 91-98, (2007); Bloom B.H., Space/Time Trade-Offs in Hash Coding with Allowable Errors, ACM Comm., 13, 7, pp. 422-426, (1970); Hao F., Kodialam M., Lakshman T.V., Building High Accuracy Bloom Filters Using Partitioned Hashing, Proc. ACM Intŉl Conf. Measurement and Modeling of Computer Systems, pp. 277-288, (2007); Groenevelt R., Nain P., Koole G., The Message Delay in Mobile Ad Hoc Networks, Performance Evaluation, 62, 14, pp. 210-228, (2005); Whitby A., Josang A., Indulska J., Filtering Out Unfair Ratings in Bayesian Reputation Systems, Proc. Seventh Intŉl Workshop Trust in Agent Societies (AAMAS ′04), (2004); Zhang C., Lu R., Lin X., Ho P.-H., Shen X., An Efficient Identity Based Batch Verification Scheme for Vehicular Sensor Networks, Proc. IEEE INFOCOM, (2008)",{"$nulls":8},1.5361233E7,null,null,null,"English","IEEE Trans. Mob. Comput.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-85008532916"]
["Hu X.; Wang X.; Sun L.; Xu Z.","Hu, Xiangpei (24481299300); Wang, Xuyin (57218362486); Sun, Lijun (55700855500); Xu, Zhichao (56173438100)","24481299300; 57218362486; 55700855500; 56173438100","A real-time intelligent system for order processing in B2C e-Commerce",2009.0,"International Journal of Innovative Computing, Information and Control",5.0,11.0,null,3691.0,3706.0,15.0,9.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-71149106418&partnerID=40&md5=5d9a559611c01d4e3031766e049538ec","Institute of Systems Engineering, Dalian University of Technology, Dalian, Liaoning Province 116023, Linggong Road, China","Hu X., Institute of Systems Engineering, Dalian University of Technology, Dalian, Liaoning Province 116023, Linggong Road, China; Wang X., Institute of Systems Engineering, Dalian University of Technology, Dalian, Liaoning Province 116023, Linggong Road, China; Sun L., Institute of Systems Engineering, Dalian University of Technology, Dalian, Liaoning Province 116023, Linggong Road, China; Xu Z., Institute of Systems Engineering, Dalian University of Technology, Dalian, Liaoning Province 116023, Linggong Road, China","The development of a real-time intelligent order processing system is one of today's challenging issues in B2C e-Commerce. This kind of systems can process cus tomers' orders intelligently and real-timely based on their requirements, such as goods quantity and expected delivery time. However, this kind of systems applicable in B2C e-Commerce is scarce. Hence, we aim to develop such a system by agent technologies in B2C e-Commerce. The system is a robust one applicable in e-Commerce environ ment. In the paper, we analyze the key tasks and the flow of real-time intelligent order processing in e-Commerce through making reference to manual order processing. The principles of these key tasks with theories and technologies of Artificial Intelligence are investigated. Based on the analysis of the key tasks, a three-layer hierarchical structure of the real-time intelligent order processing in B2C e-Commerce is presented and a multiagent systematic structure of the processing is designed, in which each agent structure for the corresponding key task is designed according to the three-layer hierarchical structure. Finally, we develop the real-time intelligent order processing system for an online urban bookstore to demonstrate the feasibility of the system in B2C e-Commerce. The application results show that the research is beneficial to improving the intelligence and real-time performance of e-Commerce order processing.© 2009 ISSN.","Agent; Artificial Intelligence; E-Commerce; Order processing; Real-time","Computer crime; Electronic commerce; Industrial research; Intelligent systems; Agent structure; Agent technology; B2C e-commerce; Delivery time; E-Commerce; Hierarchical structures; Multi-Agent; Order processing; Real time performance; Three-layer; Real time systems",{"$nulls":6},"Pyke D.F., Johnson M.E., Desmond P., E-fulfillment: It's harder than it looks, Supply Chain Management Review, 5, 1, pp. 26-32, (2001); Calosso T., Cantamessa M., Gualano M., Negotiation support for make-to-order operations in business-to-business electronic commerce, Robotics and Computer-Integrated Manufacturing, 20, 5, pp. 405-416, (2004); Tsai M.J., The voiceXML dialog system for the e-Commerce ordering service, The 9th International Conference on Computer Supported Cooperative Work in Design, pp. 95-100, (2005); Dai K.Y., Li Y.S., Han J., Et al., An interactive web system for integrated three-dimensional customization, Computers in Industry, 57, 8-9, pp. 827-837, (2006); Chen C.T., Huang S.F., Order-fulfillment ability analysis in the supply-chain system with fuzzy operation times, International Journal of Production Economics, 101, 1, pp. 185-193, (2006); Lee Y.H., Jung J.W., Eum S.C., Al E., Production quantity allocation for order fulfillment in the supply chain: A neural network based approach, Production Planning and Control, 17, 4, pp. 378-389, (2006); Chan F.T.S., Chung S.H., Choy K.L., Optimization of order fulfillment in distribution network problems, Journal of Intelligent Manufacturing, 17, 3, pp. 307-319, (2006); Hau L.L., Whang S.J., Winning the last mile of e-Commerce, Sloan Management Review, 42, 4, pp. 54-62, (2001); Thirumalai S., Sinha K.K., Customer satisfaction with order fulfillment in retail supply chains: Implications of product type in electronic B2C transactions, Journal of Operations Management, 23, 3-4, pp. 291-303, (2005); Rao H.R., Sridhad R., Narain S., Anactive intelligent decision support system - Architecture and simulation, Decision Support Systems, 12, 1, pp. 79-91, (1994); Shaw M.J., Machine learning methods for intelligent decision support: An introduction, Decision Support Systems, 10, 2, pp. 79-83, (1993); Viktor H.L., Cloete I., Inductive Learning with a computational network, Journal of Intelligent and Robotic Systems, 21, 2, pp. 131-144, (1998); Holsapple C.W., Jacob V.S., Zaveri J.S., Learning by problem processors: Adaptive decision support systems, Decision Support Systems, 10, 2, pp. 85-108, (1993); Lamer D.L., Bradley A., A distributed, operating system based, blackboard architecture for realtime control, Proc. of the 3rd International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, 1, pp. 99-108, (1990); Musliner D.J., Hendler J.A., Agrawala H.K., Al E., The challenges of real-time AI, Computer, 28, 1, pp. 58-66, (1995); Palopoli L., Lipari G., Lamastra G., Al E., An object-oriented tool for simulating distributed real-time control systems, Software-Practice & Experience, 32, 9, pp. 907-932, (2002); Ravindrann B., Engineering dynamic real-time distributed systems: Architecture, system description language, and middleware, IEEE Trans, on Software Engineering, 28, 1, pp. 30-57, (2002); Shi Z.Z., Tian Q.J., Li Y.F., RAO logic for multi-agent framework, Journal of Computer Science and Technology, 14, 4, pp. 393-400, (1999); Bonzon P., Situated BD agents subsume BDI agents, Proc. of Fourth International Conference on MultiAgent Systems, pp. 367-368, (2000); Pechoueek M., Stepank Ova O., Malik V., Barta J., Abstract architecture for meta-reasoning in multiagent systems, CEEMAS, 2003, pp. 84-99, (2003); Lemaitre C., Fallah-Seghrouchni A.E., A comprehensive theory of meaning for communication acts in multi-agent systems, Proc. of Fourth International Conference on MultiAgent Systems, pp. 407-408, (2000); Sato E., Human to robots communication using ontological network system, International Journal of Innovative Computing, Information and Control, 2, 1, pp. 205-220, (2006); Soriano J., Alonso F., Lopez G., A formal specification language for agent conversations, CEEMAS 2003, pp. 214-225, (2003); Wu D.J., Software agents for knowledge management: Coordination in multi-agent supply chains and auctions, Expert Systems with Applications, 20, 1, pp. 51-64, (2001); Nakano N., An agent-based approach to simulations of global influence with random effect, International Journal of Innovative Computing, Information and Control, 2, 5, pp. 1153-1163, (2006); Hu X.P., Wang X.Y., Sun L.J., Amy Z.Z., A knowledge-based supplier selection system for real-time e-Commerce order processing, International Journal of Knowledge and Systems Sciences, 12, 2, pp. 1-8, (2005); Xu Z.H., Hu X.P., Li G.Q., Li Y.M., A method on real-time selection of third party logistics center in e-Commerce, Journal of Harbin Institute of Technology, 37, 11, pp. 1519-1521, (2005); Xu Z.H., Hu X.P., Li Y.M., Huang M.F., A man-machine interaction software robot for e-Commerce order human-like real-time processing, Journal of Harbin Institute of Technology, 38, 2, pp. 274-278, (2006)","X. Hu; Institute of Systems Engineering, Dalian University of Technology, Dalian, Liaoning Province 116023, Linggong Road, China; email: drhxp@dlut.edu.cn",{"$nulls":7},1.3494198E7,null,null,null,"English","Int. J. Innov. Comput. Inf. Control","Article","Final",null,"Scopus","2-s2.0-71149106418"]
["Kim K.; Ra I.","Kim, Kwanghoon (35748853400); Ra, Ilkyeun (6506437152)","35748853400; 6506437152","e-Lollapalooza: A process-driven e-Business service integration system for e-Logistics services",2007.0,"KSII Transactions on Internet and Information Systems",1.0,1.0,null,33.0,51.0,18.0,5.0,"10.3837/tiis.2007.01.003","https://www.scopus.com/inward/record.uri?eid=2-s2.0-67650216194&doi=10.3837%2ftiis.2007.01.003&partnerID=40&md5=68f88c41c3a4315602872a410bc03e25","Dept. of Computer Science, Kyonggi University, Gyeonggi-Do 443-760, San 94-6 Yiui-Dong, Youngtong-Gu, South Korea; Dept. of Computer Science and Engineering, Unversity of Colorado at Denver, Denver, CO 80217-3364, Campus Box 109, United States","Kim K., Dept. of Computer Science, Kyonggi University, Gyeonggi-Do 443-760, San 94-6 Yiui-Dong, Youngtong-Gu, South Korea; Ra I., Dept. of Computer Science and Engineering, Unversity of Colorado at Denver, Denver, CO 80217-3364, Campus Box 109, United States","There are two newly emerging research issues in the enterprise information systems literature. One is the scalability issue for rapidly increasing choreographic volumes between interrelated organizations. The other is the business intelligence issue for traceable and monitorable business processes and services interchanging e-Business data and applications across organizations. Based upon these emerging issues, through a functional extension of the ebXML technology we have developed a process-driven e-Business service integration (BSI) system, which is named 'e-Lollapalooza'. It consists of three major components - the Choreography Modeler coping with the process-driven collaboration issue, the Runtime & Monitoring Client for coping with the business intelligence issue and the EJB-based BSI Engine coping with the scalability issue. This paper particularly focuses on the e-Lollapalooza's development aspects for supporting the ebXML-based choreography and orchestration among the engaged organizations in a process-driven multiparty collaboration for e-Logistics and e-Commerce services. Here, it is fully deployed in an EJB-based middleware computing environment for e-Logistics process automation and B2B choreography. Copyright © 2007 KSII.","B2B choreography and orchestration; e-Business service integration system; e-Logistics",{"$nulls":7},"Dogac A., Tambag Y., Pembecioglu P., Pektas S., Laleci G.B., Kurt G., Toprak S., Kabak Y., An ebXML Infrastructure Implementation through UDDI Registries and RosettaNet PIPs, ACM SIGMOD International Conference on Management of Data, (2002); Fosdick H., The Sociology of Technology Adaptation, Enterprise System Journal, (1992); Hayami H., Katsumata M., Okada K.-I., Interworkflow: A Challenge for Business-to-Business Electronic Commerce, Workflow Handbook 2001, WfMC, (2000); Kim K.-H., Ellis C.A., A Framework for Workflow Architectures, (1997); Dong-Keun O., Kim K.-H., An EJB-Based Database Agent for Workflow Definition, Journal of Korean Society for Internet Information, 4, 5, (2001); Kim K.-H., Ellis C.A., Performance Analytic Models and Analyses for Workflow Architectures, Information Systems Frontiers, 3, 3, pp. 339-355, (2001); Sim S.-S., Kim K.-H., Workcase based Very Large Scale Workflow System Architecture, Proceedings of Korea Database Society, (2002); Oh D.-K., Chun J.-M., Hong J.-S., Oh S.-W., Hwang J.-G., Lee Y.-J., Kim K.-H., ebXML-Based e-Logistics Workflow Engine Architecture, Proceedings of the Conference of Korean Society for Internet Information, 3, 3, pp. 348-351, (2002); (2001); Siddalingaiah M., Overview of ebXML, (2001); Hayami H., Katsumata M., Okada K.-I., Interworkflow: A Challenge for Business-to-Business Electronic Commerce, Workflow Handbook 2001, WfMC, (2000); Hwang J.-G., Oh S.-W., Lee Y.-J., e-Logistics Integration System based on ebXML specifications, Proceedings of the Conference of Korea Information Science Society, Vol 29, No 2, (2002); Kim K.-H., A Process-Driven e-Business Service Integration System and Its Application to e-Logistics Services, Proceedings of the WISE Conference, Lecture Note in Computer Science, 3806, pp. 669-678, (2005); Kim K.-H., A Process-Driven Interorganizational Choreography Modeling System, Proceedings of the OTM Workshop, Lecture Note in Computer Science, 3762, pp. 485-494, (2005)","K. Kim; Dept. of Computer Science, Kyonggi University, Gyeonggi-Do 443-760, San 94-6 Yiui-Dong, Youngtong-Gu, South Korea; email: kwang@kgu.ac.kr",{"$nulls":7},1.9767277E7,null,null,null,"English","KSII Trans. Internet Inf. Syst.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-67650216194"]
["Gopalakrishna P.; Subramanian R.","Gopalakrishna, Pradeep (6602109999); Subramanian, Ram (7202796342)","6602109999; 7202796342","Understanding virtual value chains in a retail environment: A case study of Wal-Mart",2008.0,"International Journal of Productivity and Quality Management",3.0,3.0,null,263.0,274.0,11.0,6.0,"10.1504/IJPQM.2008.017498","https://www.scopus.com/inward/record.uri?eid=2-s2.0-40949150755&doi=10.1504%2fIJPQM.2008.017498&partnerID=40&md5=6c09b564a778ed6274d4bfd9db7c9441","Department of Marketing, Lubin School of Business, Pace University, New York, NY 10038, United States; School of Business, Montclair State University, Montclair, NJ 07043, United States","Gopalakrishna P., Department of Marketing, Lubin School of Business, Pace University, New York, NY 10038, United States; Subramanian R., School of Business, Montclair State University, Montclair, NJ 07043, United States","With the advent of the internet and explosion of e commerce across borders in the 21st century, global firms will adapt their value chain philosophies to capitalise on cost efficiencies and strengthen their sustainable competitive advantage. This case study illustrates the application of Rayport and Sviokla's three-stage Virtual Value Chain (VVC) philosophy to Wal-Mart, the world's largest retailer. Value chains using information technology allow managers and suppliers/vendors to track operations more effectively, with a holistic and integrated approach to managing information seamlessly. The focus of the VVC in the new economy is on information, unlike physical supply chain management where the focus was on inventory management. This paper applies the three stages of the VVC to Wal-Mart, including visibility entailing tracking of physical operations via information; mirroring capability substituting virtual activities for physical ones in the marketspace realm, and creation of new customer relationships using information. In particular, the authors focus upon the name of the game in supply chain management for the 21st century collaboration among channel partners, information sharing and improved efficiencies in the value chain delivery network. Finally, this paper examines Wal-Mart's physical value chain activities and the emerging VVC, as the company considers expansion globally into emerging markets. © 2008, Inderscience Publishers.","Economics of information; Virtual Value Chain; VVC; Wal-Mart",{"$nulls":7},"Evans P.B., Wurster T.S., Strategy and the new economics of information, Harvard Business Review, 75, 5, pp. 70-82, (1997); Fishman C., The Wal-Mart you don't know, Fast Company, pp. 68-80, (2003); Hamilton J., Selen W., Service value encounters in the virtual service value chain: A conceptual framework, International Journal of Value Chain Management, 1, 2, pp. 139-158, (2006); Kotler P., Keller K., Marketing Management, (2006); Lawton T.C., Michaels K.P., Advancing to the virtual value chain: Learning from the Dell model, Irish Journal of Management, 22, 1, pp. 91-112, (2001); Middleton P., Taylor P.S., Flaxel A., Cookson A., Lean principles and techniques for improving the quality and productivity of software development projects: A case study, International Journal of Productivity and Quality Management, 2, 4, pp. 387-403, (2007); Oakland J.S., Tanner S.J., Quality management in the 21st century - implementing successful change, International Journal of Productivity and Quality Management, 1-2, pp. 69-87, (2006); Pandya M., Singh H., Millelstaedt R.E., Clemons E., Knowledge at Wharton on Building Corporate Value, (2003); Porter E., Millar V., How information gives you competitive advantage, Harvard Business Review, pp. 149-160, (1985); Porter M.E., Competitive Advantage: Creating and Sustaining Superior Performance, (1985); Rayport J.F., Sviokla J.J., Exploiting the virtual value chain, Harvard Business Review, pp. 75-85, (1995); Reid R.A., Productivity and quality improvement: An implementation framework, International Journal of Productivity and Quality Management, 1, 2, pp. 26-36, (2006); Varian H.R., An ipod has global value: Ask the (many) countries that make it, The New York Times, (2007)","P.G. Gopalakrishna; Department of Marketing, Lubin School of Business, Pace University, New York, NY 10038, United States; email: pgopalakrishna@pace.edu",null,"Inderscience Publishers",{"$nulls":5},1.7466474E7,null,null,null,"English","Int. J. Prod. Qual. Manage.","Article","Final",null,"Scopus","2-s2.0-40949150755"]
["Meeus L.; Verhaegen K.; Belmans R.","Meeus, Leonardo (55682345300); Verhaegen, Karolien (11339204600); Belmans, Ronnie (16068077100)","55682345300; 11339204600; 16068077100","Block order restrictions in combinatorial electric energy auctions",2009.0,"European Journal of Operational Research",196.0,3.0,null,1202.0,1206.0,4.0,71.0,"10.1016/j.ejor.2008.04.031","https://www.scopus.com/inward/record.uri?eid=2-s2.0-58849123748&doi=10.1016%2fj.ejor.2008.04.031&partnerID=40&md5=65fa97f516677beffdfcffcc4027238f","Department of Electrical Engineering, University of Leuven, 3001 Leuven, Kasteelpark Arenberg 10, Belgium","Meeus L., Department of Electrical Engineering, University of Leuven, 3001 Leuven, Kasteelpark Arenberg 10, Belgium; Verhaegen K., Department of Electrical Engineering, University of Leuven, 3001 Leuven, Kasteelpark Arenberg 10, Belgium; Belmans R., Department of Electrical Engineering, University of Leuven, 3001 Leuven, Kasteelpark Arenberg 10, Belgium","In Europe, the auctions organized by \"power exchanges\" one day ahead of delivery are multi-unit, double-sided, uniformly priced combinatorial auctions. Generators, retailers, large consumers and traders participate at the demand as well as at the supply side, depending or whether they are short or long in electric energy. Because generators face nonconvex costs, in particular startup costs and minimum run levels, the exchanges allow \"block orders\" that are all-or-nothing orders of a given amount of electric energy in multiple consecutive hours, while the standard order consists of an amount for a single hour that can be curtailed. All exchanges restrict the size (MWh/h), the type (span in terms of hours) or the number (per participant per day) of blocks that can be introduced. This paper discusses the rationale of block order restrictions. Based on simulations with representative scenarios, it is argued that the restrictions could be relaxed, which some exchanges have already started doing. © 2008 Elsevier B.V. All rights reserved.","Combinatorial auctions/bidding; E-commerce; Integer programming; OR in energy; Pricing","Commerce; Competition; Costs; Dynamic programming; Electronic commerce; Industrial economics; Integer programming; Operating rooms; Programming theory; Combinatorial auctions; Combinatorial auctions/bidding; E-commerce; Electric energies; Large consumers; Multi units; Nonconvex; OR in energy; Order restrictions; Power exchanges; Pricing; Start-up costs; Electric generators",{"$nulls":6},"Combinatorial Auctions, (2006); De Vries S., Vohra R.V., Combinatorial auctions: A survey, INFORMS Journal on Computing., 3, pp. 284-309, (2003); Elmaghraby W.J., O'Neill R., Rothkopf M., Stewart W., Pricing and efficiency in lumpy energy markets, The Electricity Journal, 17, 5, pp. 54-64, (2004); Meeus L., Purchala K., Belmans R., Development of the internal electricity market in Europe, The Electricity Journal, 18, 6, pp. 25-35, (2005); O'Neill R.P., Sotkiewicz P.M., Hobbs B.F., Rothkopf M.H., Stewart Jr. W.R., Efficient market-clearing prices in markets with nonconvexities, European Journal of Operational Research, 164, 1, pp. 269-285, (2005); Park S., Rothkopf M.H., Auctions with bidder-determined allowable combinations, European Journal of Operational Research, 161, 2, pp. 399-415, (2005); Pekec A., Rothkopf M.H., Combinatorial auction design, Management Science, 49, 11, pp. 1485-1503, (2003); Scarf H.E., The allocation of resources in the presence of indivisibilities, The Journal of Economic Perspectives, 8, 4, pp. 111-128, (1994); Xia M., Koehler G.J., Whinston A.B., Pricing combinatorial auctions, European Journal of Operational Research, 154, 1, pp. 251-270, (2004); Xia M., Stallaert J., Whinston A.B., Solving the combinatorial double auction problem, European Journal of Operational Research, 164, 1, pp. 239-251, (2005)","L. Meeus; Department of Electrical Engineering, University of Leuven, 3001 Leuven, Kasteelpark Arenberg 10, Belgium; email: leonardo.meeus@esat.kuleuven.be",{"$nulls":7},3772217.0,null,"EJORD",null,"English","Eur J Oper Res","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-58849123748"]
["Collier J.E.; Bienstock C.C.","Collier, Joel E. (13408671200); Bienstock, Carol C. (6602778468)","13408671200; 6602778468","How do customers judge quality in an E-tailer?",2006.0,"MIT Sloan Management Review",48.0,1.0,null,35.0,40.0,5.0,59.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-33750325572&partnerID=40&md5=5bca1a3ad3491ca768e768b9122c682f","Mississippi State University, College of Business and Industry, Department of Marketing, Quantitative Analysis and Business Law, United States; Department of Marketing, Radford University, United States","Collier J.E., Mississippi State University, College of Business and Industry, Department of Marketing, Quantitative Analysis and Business Law, United States; Bienstock C.C., Department of Marketing, Radford University, United States","Early research in e-commerce projected that online retailing would spiral into a never-ending price war, but recent research has shown that customers are more likely to pay higher prices to online retailers of high quality that they trust. But how do customers evaluate quality in online retailing? What are the specific aspects of an online transaction that customers value and use to distinguish one site from another? The authors explored these issues by surveying customers who had recently engaged in an online retail transaction to determine how they evaluate the quality of their experiences with online retailers. The results demon-strated that customers' perceptions of quality and satisfaction with online purchases depend upon three things: interaction with the Web site, delivery of the product and how prepared retailers are to address problems when they occur. Of the three, product delivery has the strongest influence on customers' satisfaction and future purchase intentions. The authors further break down each of the three aspects of quality to create a complete picture of what it takes to build a trusting relationship with customers in an e-commerce environment. Copyright © Massachusetts Institute of Technology, 2006. All rights reserved.",{"$nulls":8},"Koiso-Kanttila N., Time, attention, authenticity and consumer benefits of the Web, Business Horizons, 48, 1, pp. 63-70, (2005); Brynjolfsson E., Smith M.D., Frictionless commerce? A comparison of Internet and conventional retailers, Management Science, 46, 4, pp. 563-585, (2000); Davis F.D., Bagozzi R.P., Warshaw P.R., User acceptance of computer technology: A comparison of two theoretical models, Management Science, 35, 8, pp. 982-1003, (1989); Wind J., Rangaswamy A., Customerization: The next revolution in mass customization, Journal of Interactive Marketing, 15, 1, pp. 13-32, (2001); Odom M.D., Kumar A., Saunders L., Web assurance seals: How and why they influence consumers' decisions, Journal of Information Systems, 16, 2, pp. 231-250, (2002); Esper T.L., Jensen T.D., Turnipseed F.L., Burton S., The last mile: An examination of effects of online retail delivery strategies on consumers, Journal of Business Logistics, 24, 2, pp. 177-203, (2003); Bienstock C.C., Mentzer J.T., Bird M.M., Measuring physical distribution service quality, Journal of the Academy of Marketing Science, 25, 1, pp. 31-44, (1996); Holloway B.B., Beatty S.E., Service failure in online retailing: A recovery opportunity, Journal of Service Research, 6, 1, pp. 92-105, (2003)","J.E. Collier; Mississippi State University, College of Business and Industry, Department of Marketing, Quantitative Analysis and Business Law, United States; email: jcollier@cobilan.msstate.edu",{"$nulls":7},1.5329194E7,null,null,null,"English","MIT Sloan Manage. Rev.","Article","Final",null,"Scopus","2-s2.0-33750325572"]
["Hesse K.; Clausen U.","Hesse, Kathrin (55959140100); Clausen, Uwe (14630099600)","55959140100; 14630099600","Eco-efficient logistics; [Ökoeffiziente Logistik]",2012.0,"IT - Information Technology",54.0,1.0,null,24.0,33.0,9.0,1.0,"10.1524/itit.2012.0660","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85101982171&doi=10.1524%2fitit.2012.0660&partnerID=40&md5=4c0daf35f1c7ce8506e5d0a79f4606ad","Fraunhofer IML, Joseph-von-Fraunhofer- Str. 2-4, Dortmund, 44221, Germany","Hesse K., Fraunhofer IML, Joseph-von-Fraunhofer- Str. 2-4, Dortmund, 44221, Germany; Clausen U., Fraunhofer IML, Joseph-von-Fraunhofer- Str. 2-4, Dortmund, 44221, Germany","Reducing the emissions of greenhouse gases (GHG) like CO2 is one of the predominant concerns for ensuring sustainable future living conditions on Earth. However, current trends in globalization of production processes, just-in-time manufacturing, and increased numbers of parcel shipments due to a growing trend towards online shopping threaten to further increase GHG emissions. An analysis of GHG emissions is complex to perform since it has to include data from multiple sources and processes. The standard way to obtain an overview of the general emission impact is to perform a life cycle assessment (LCA), which is detailed in the first part of this paper. The same trend leads to an increasingly important contribution of logistics processes in the life cycle analysis of GHG emissions. Thus, the reduction of emissions in logistics is a major challenge for logistics research. Reductions are possible using a combination of IT-based and conventional methods on macroscopic as well as microscopic optimizations. However, the resulting economical impact must be considered when applying these optimizations. This article gives an overview of possible optimization approaches, augmented by a description of case studies, based on previous research projects.  © by Oldenbourg Wissenschaftsverlag, Dortmund, Germany 2012.","J [Computer Applications]; Logistics, process optimization, greenhouse gases, CO<sub>2</sub>emission, carbon footprint, life cycle assessment","Carbon footprint; Life cycle; Optimization; 'current; CO 2 emission; Greenhouse gas emissions; Greenhouses gas; J [computer application]; Living conditions; Logistic, process optimization, greenhouse gas, CO2emission, carbon footprint, life cycle assessment; Logistics process; Optimisations; Process optimisation; Greenhouse gases",{"$nulls":6},"Berz G., Naturkatastrophen und Klimaänderung: Was erwartet uns in Mitteleuropa? Was können wir tun?, Vortrag, (2007); Gabriel S., Klimaschutz Bedeutet Umbau der Industriegesellschaft: 8-Punkte-Plan Zur Senkung der Treibhausgas-Emissionen Um 40 Prozent Bis 2020, (2007); Umwelt-Kernindikatorsystem/Thema: Klimaänderungen/Unterthema: Treibhauseffekt - Eine Globale Herausforderung/ Indikator: CO2-Emissionen Nach Quellkategorien, (2011); Treibhausgase Deutlich Unter Dem Limit; Emissionen der Sechs im Kyoto- Protokoll Genannten Treibhausgase in Deutschland, (2011); Buyny S., Klink S., Lauber U., Thomas J., Umweltökonomische Aspekte der Globalisierung. Teil 2: CO2-Emissionen des internationalen Güter- und Personenverkehrs, Wirtschaft und Statistik, 2, pp. 148-156, (2008); Kuczmierczyk G., Relevanz der Grünen Logistik Aus Sicht der Bundesregierung, (2009); Reducing Transport Greenhouse Gas Emissions - Trends & Data 2010., (2010); GaBi Software.; Ifu Hamburg. Umberto - Handbuch. Version 2, (1996); Introduction to LCA with SimaPro 7. Version 4.5, (2010); PricewaterhouseCoopers/Ecobilan TEAM.; ProBas - Prozessorientierte Basisdaten für Umweltmanagement-Instrumente.; Ökoinstitut Gemis.; Clausen U., Deymann S., Friedrichs J., Schmied M., Measures to abate greenhouse gas emissions of stationary and mobile processes in logistics companies, Proc. Of the Transport Research Arena Conf., TRA 2008, (2008); Clausen U., Chmielewski A., Deymann S., Effiziente Planung und wirtschaftlicher Betrieb von Logistikanlagen, Jahrbuch der Logistik 2009, (2009); Deymann S., Der Logistikdienstleister als Integrator internationaler Beschaffungsketten - Potenziale und Lösungsansätze in der IT, Jahrbuch der Logistik 2008, Korschenbroich, Free Beratung GmbH, (2008); Deymann S., Klimaschutz kann Kosten senken, Ruhrwirtschaft 12/09 Seite 46, (2009); Marchiso A., Pennestri P.F., Sonnabend P., Vehicle development and transport logistics in the information age, The Best Urban Freight Solutions Workshop, (2003); Hesse K., Carbon Footprints zur Bewertung der ökologischen Wirkung logistischer Prozesse, Praxishandbuch Logistik, (2009); Hesse K., Bilanzierung von CO2-Emissionen, Software in der Logistik - Klimaschutz im Fokus Seiten 22-28, (2009); Hesse K., Clausen U., Klimawandel und die Folgen für den Verkehr: Energieeffizienz von Logistikprozessen, Jahrbuch der Logistik 2008, Seiten 16-22, (2008); Hesse K., Clausen U., Nachhaltige Gestaltung der Logistik, Duisport Magazin, 25, 4, pp. 19-21, (2008)",null,null,"De Gruyter Oldenbourg",{"$nulls":5},1.6112776E7,null,null,null,"English","IT Info. Tech.","Article","Final",null,"Scopus","2-s2.0-85101982171"]
["Chandra C.","Chandra, Charu (7004122799)",7.004122799E9,"The case for healthcare supply chain management: Insights from problem-solving approaches",2008.0,"International Journal of Procurement Management",1.0,3.0,null,261.0,279.0,18.0,15.0,"10.1504/IJPM.2008.017525","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84872472876&doi=10.1504%2fIJPM.2008.017525&partnerID=40&md5=59617e856509cc5dc8b380e223c573d8","Industrial and Manufacturing Systems Engineering Department, University of Michigan-Dearborn, Dearborn, MI 48128-1491, 4901 Evergreen Road, United States","Chandra C., Industrial and Manufacturing Systems Engineering Department, University of Michigan-Dearborn, Dearborn, MI 48128-1491, 4901 Evergreen Road, United States","The US healthcare industry is a large enterprise accounting for over 14.1% of the national economic output in 2001. It has been under pressure for cost containment and providing quality healthcare services to consumers. Its record of investing heavily in the development of sophisticated drugs and diagnostic systems does not match that of technologies to manage its day-to-day operations. In order to achieve improved performance, the healthcare supply chain must be efficient and integrated. The driver for this integration is logistics and supply chain management. This paper describes trends, issues and some solutions for logistics management for the healthcare supply chain with concepts drawn from industrial engineering, and operations research disciplines applied to specific domains. A healthcare supply chain template utilising e-commerce strategy is presented. Use of simulation, optimisation and information-sharing techniques are demonstrated to optimise purchasing and inventory policies. © 2012 Inderscience Enterprises Ltd.","E-healthcare; Healthcare logistics; Healthcare supply chain",{"$nulls":7},"Study: E-commerce will improve logistics, Hospital Materials Management, 25, 11, pp. 2-11, (2000); Arboleda C.A., Abraham D.M., Lubitz R., Simulation as a tool to assess the vulnerability of the operation of a health care facility, Journal of Performance of Constructed Facilities, 21, 4, pp. 302-312, (2007); Baldwin L.P., Eldabi T., Paul R.J., Simulation in healthcare management: A soft approach (mapiu), Simulation Modelling Practice and Theory, 12, pp. 541-557, (2004); Bose R., Knowledge management-enabled health care management systems: Capabilities, infrastructure, and decision-support, Expert Systems with Applications, 24, 1, pp. 59-71, (2003); Bowman R.J., Ehcr at a glance, Distribution February, 96, 2, (1997); Bradley P., Taking on the health care supply chain, Manufacturing Systems (MSI), pp. 50-51, (2000); Brennan C.D., Integrating the healthcare supply chain, Healthcare Financial Management, 52, 1, pp. 31-34, (1998); Chandra C., Chilov N., Object-oriented data model for supply chain configuration management, Proceedings of the Tenth Annual Industrial Engineering Research Conference (IERC), (2001); Chandra C., Grabis J., Reconfiguration of multi-stage production systems to support product customisation using generic simulation models, Proceedings of the Sixth Annual International Conference on Industrial Engineering, (2001); Chandra C., Grabis J., Modeling floating supply chains, Proceedings of the Eleventh Annual Industrial Engineering Research Conference (IERC), (2002); Chandra C., Marukyan R., Elaborating process models for supply chain reconfiguration, Proceedings of the Eleventh Annual Industrial Engineering Research Conference (IERC), (2002); Chandra C., Nastasi A.J., Norris T.L., Tag P., Enterprise modeling for capacity management in supply chain simulation, Proceedings of the Ninth Industrial Engineering Research Conference (IERC), (2000); Chandra C., Tumanyan A., Supply chain reconfiguration: Designing information support with system taxonomy principles, Proceedings of the Eleventh Annual Industrial Engineering Research Conference (IERC), (2002); Danese P., The extended VMI for coordinating the whole supply network, Journal of Manufacturing Technology Management, 17, 7, pp. 888-907, (2006); Dembeck C., Online healthcare expected to reach $370b by 2004, E-commerce Times, pp. 1-2, (2000); Doerner K.F., Reimann M., Logistics of health care management, Computers and Operations Research, 34, 3, pp. 621-623, (2007); Dongsoo K., An integrated supply chain management system: A case study in healthcare sector, Proceedings of the E-commerce and Web Technologies: Sixth International Conference, 35, pp. 218-227, (2005); Ford E.W., Hughes J.A., A collaborative product commerce approach to value-based health plan purchasing supply chain management, An International Journal, 12, 1, pp. 32-41, (2007); Gunasekaran A., Ngai E.W.T., McGaughey R.E., Information technology and systems justification: A review for research and applications, European Journal of Operational Research, 173, 3, pp. 957-983, (2006); Holmes S.C., Miller R.H., The strategic role of e-commerce in the supply chain of the healthcare industry, International Journal of Services Technology and Management, 4, pp. 507-517, (2003); Knels R., Case study: New logistic possibilities and challenges for RFID in transfusion medicine and hospital environment, Building Intelligence into Healthcare Packaging - Technology Advances in Pharmaceutical and Medical Packaging - Pira International - Seminar Proceedings, pp. 15-37, (2004); Kumar S., Chandra C., E-health care: A novelty or a vehicle for change, IIE Solutions, pp. 28-33, (2001); Lannon E., Capitalizing On Opportunities In The Hospital Supply Chain Process, (2001); Maruster L., Jorna R.J., From data to knowledge: A method for modeling hospital logistic processes, IEEE Transactions on Information Technology in Biomedicine, 9, 2, pp. 248-255, (2005); Metz R., Mogk G., Rossi H., Schlichtharle P., Tolle F.-J., A supply chain management system in a pharmaceutical company: A case study at Bayer, Pharmazeutische Industrie, 66, A11, pp. 1436-1441, (2004); Nicholson L., Vakharia A.J., Erenguc S.S., Outsourcing inventory management decisions in healthcare: Models and application, European Journal of Operational Research, 154, pp. 271-290, (2004); Nugent D., E-commerce: An rx for organizational pain, Health Management Technology, 21, 10, pp. 32-37, (2000); Rivard-Royer H., Landry S., Beaulieu M., Hybrid stockless: A case study - Lessons for health-care supply chain integration, International Journal of Operations Production Management, 22, 4, pp. 412-424, (2002); Simchi-Levi D., Kaminsky D., Simchi-Levi E., Designing and Managing the Supply Chain: Concepts Strategies and Case Studies, (2003); Srivastava R., Jayaraman V., Kirche E., Reverse logistics in healthcare, Proceedings of the Thirty fourth Annual Meeting of the Decision Sciences Institute, pp. 2079-2084, (2003); Van Merode G.G., Groothuis S., Hasman A., Enterprise resource planning for hospitals, International Journal of Medical Informatics, 73, 6, pp. 493-501, (2004); Vermond K., Supply chain management in health care: The oha taskforce report, Health Care Information Management Communications, pp. 30-32, (2000); Zheng J., Bakker E., Knight L., Gilhespy H., Harland C., Walker H., A strategic case for e-adoption in healthcare supply chains, International Journal of Information Management, 26, 4, pp. 290-301, (2006)",null,null,"Inderscience Publishers",{"$nulls":5},1.7538432E7,null,null,null,"English","Int. J. Procure. Manage.","Article","Final",null,"Scopus","2-s2.0-84872472876"]
["Yang M.-H.; Chen J.C.H.; Wu C.-H.; Chao H.-Y.","Yang, Ming-Hsien (55800840600); Chen, Jason C.H. (10243764200); Wu, Cheng-Hang (7501673589); Chao, Hung-Yi (24467518000)","55800840600; 10243764200; 7501673589; 24467518000","On characteristics influencing consumer's intention to use web-based self-service",2010.0,"Human Systems Management",29.0,1.0,null,41.0,49.0,8.0,3.0,"10.3233/HSM-2010-0717","https://www.scopus.com/inward/record.uri?eid=2-s2.0-77950538563&doi=10.3233%2fHSM-2010-0717&partnerID=40&md5=fee362954fe0934c956f0693ec0f3295","College of Management, Fu Jen Catholic University, Xinzhuang City, Taipei County, Taiwan; Graduate School of Business, Gonzaga University, WA, United States; Department of Information Management, Fu Jen Catholic University, Xinzhuang City, Taipei County, Taiwan; Graduate Institute of Business Administration, Fu Jen Catholic University, Xinzhuang City, Taipei County, Taiwan","Yang M.-H., College of Management, Fu Jen Catholic University, Xinzhuang City, Taipei County, Taiwan; Chen J.C.H., Graduate School of Business, Gonzaga University, WA, United States; Wu C.-H., Department of Information Management, Fu Jen Catholic University, Xinzhuang City, Taipei County, Taiwan; Chao H.-Y., Graduate Institute of Business Administration, Fu Jen Catholic University, Xinzhuang City, Taipei County, Taiwan","Information technology (IT) brings unforeseeable impacts and challenges on service industries. This is because IT creates endless possibilities for them to revolutionize their service delivery process. For example, interactive voice response systems, interactive kiosks, the Internet, and multimedia DVDs all become new channels that allow companies to directly communicate with consumers. Facing pressure of mounting labor costs, most enterprises rush to adopt technologies to improve their operational efficiency and service quality. The consumer's intention to use the web-based self service (WBSS) becomes a key factor to determine if the WBSS will be successful. In this study we adopted the Technology Acceptance Model (TAM) as the research framework and conducted an empirical study to examine what effects that WBSS characteristics such as response time, responsiveness, and customized control may have on the consumers' intention to use the WBSS. The result shows that the customized control characteristic directly affects the consumers' intention to use the WBSS. It suggests that companies need to enhance the flexibility of the WBSS in the service delivery process so that the consumer can increase the intention to use the WBSS. © 2010 IOS Press and the authors. All rights reserved.","Behavior; Consumer; E-commerce; Intention; IS use; Self-service systems","Cost accounting; Electronic commerce; Employment; Speech recognition; Wages; Control characteristics; E-Commerce; Empirical studies; Interactive kiosks; Interactive voice response systems; Key factors; Labor costs; Operational efficiencies; Response time; Service industries; Service Quality; Service systems; Service-delivery process; Technology acceptance model; Information technology",{"$nulls":6},"Anitsal I., Schumann D.W., Toward a conceptualization of customer productivity: The customer's perspective on transforming customer labor into customer outcomes using technology-based self-service options, Journal of Marketing Theory and Practice, 15, 4, pp. 349-363, (2007); Arbin K., The structure of determinants of individual adoption and use of e-ordering systems, Human Systems Management, 27, 2, pp. 143-159, (2008); Averill J., Personal control over aversive stimuli and its relationship to stress, Psychological Bulletin, 80, 4, pp. 286-303, (1973); Barney D., E-commerce intelligence report, Network World, 17, 9, pp. 56-57, (2000); Bitner M.J., Ostorm A.L., Meuter M.L., Implementing successful self-service technologies, Academy of Management Executive, 16, 4, pp. 96-109, (2002); Cooper V.A., Lichtenstein S., Smith R., Knowledge transfer in enterprise information technology support using web-based self-service systems, International Journal Technology Marketing, 1, 2, pp. 145-170, (2006); Curran J.M., Meuter M.L., Encouraging existing customers to use self-service technologies: Put a little fun in their lives, Journal of Marketing Theory and Practice, 15, 4, pp. 283-298, (2007); Dabholkar P.A., Consumer evaluations of new technologybased self-service options: An investigation of alternative models of service quality, International Journal of Research in Marketing, 13, pp. 29-51, (1996); Davis F.D., Perceived usefulness, perceived ease of use, and user acceptance of information technology, MIS Quarterly, 13, 3, pp. 319-340, (1989); Evans P., Wurster T., Blown to Bits, (2000); Fantazy K.A., Kumar V., Kumar U., Mishra S., The impact of strategy and information systems flexibility on the supply chain performance: A path analysis approach, International Journal of Business and Systems Research, 3, 1, pp. 119-133, (2009); Globerson S., Maggard M.J., A conceptual model of self- Service, International Journal of Operations and Production Management, 11, 4, pp. 33-43, (1991); Hair J.F., Anderson R.E., Tatham R.L., Black W.C., Multivariate Data Analysis, (1998); Ho S.H., Ko Y.Y., Effects of self-service technology on customer value and customer readiness: The case of internet banking, Internet Research, 18, 4, pp. 427-446, (2008); Jarvenpaa S., Todd P., Consumer reactions to electronic shopping on the world wide web, International Journal of Electronic Commerce, 1, 2, pp. 59-88, (1997); Lovelock C.H., Young R.F., Look to consumers to increase productivity, Harvard Business Review, 57, 3, pp. 168-178, (1979); Marzocchi G.L., Zammit A., Self-scanning technologies in retail: Determinants of adoption, Service Industries Journal, 26, 6, pp. 651-669, (2006); Meuter M.L., Ostrom A.L., Roundtree R.I., Bitner M.J., Self-service technologies: Understanding customer satisfaction with technology-bases service encounters, Journal of Marketing, 64, 3, pp. 50-64, (2000); Meuter M.L., Ostrom A.L., Bitner M.J., Roundtree R.I., The influence of technology anxiety on consumer use and experiences with self-service technologies, Journal of Business Research, 56, 11, pp. 899-906, (2003); Moon J.W., Kim Y.G., Extending the TAM for a worldwide- web context, Information and Management, 38, 4, pp. 217-230, (2001); Nielsen J., Designing Web Usability: The Practice of Simplicity, (2000); Palmer J.W., Web site usability, design, and performance metrics, Information Systems Research, 13, 2, pp. 151-167, (2002); Pujari D., Self-service with a smile? Self-service technology (SST) encounters among Canadian business-to-business, International Journal of Service Industry Management, 15, 2, pp. 200-219, (2004); Rose G., Straub D., The effect of download time on consumer attitude toward the E-service retailer, E-Service Journal, 1, 1, pp. 55-76, (2001); Schubert P., Selz D., Web assessment:Amodel for the evaluation and the assessment of successful electronic commerce applications, Proc 31st Hawaii International Conference Systems Science, (1998); Shamdasani P., Mukherjee A., Malhotra N., Antecedents and consequences of service quality in consumer evaluation of self-service internet technologies, Service Industries Journal, 28, 1, pp. 117-138, (2008); Shneiderman B., Designing the User Interface: Strategies for Effective Human-Computer Interaction, (1998); Simon F., Usunier J., Cognitive, demographic and situational determinants of service customer preference for personnel-in-contact over self-service technology, International Journal of Research in Marketing, 24, 2, pp. 163-173, (2007); Thompson R., Compeau D., Higgins C., Intentions to use information technologies: An integrative model, Journal of Organizational and End User Computing, 18, 3, pp. 25-46, (2006); Venkatesh V., Davis F.D., A model of the antecedents of perceived ease of use:Development and test, Decision Sciences, 27, 3, pp. 451-481, (1996); Yasin M.M., Augusto M., Alavi J., Lisboa J., A structural equation modeling approach to assessing the effectiveness of quality improvement initiatives in service organizations:Asystematic perspective, International Journal of Business and Systems Research, 3, 3, pp. 372-386, (2009); Zeithaml V.A., Bitner M.J., Service Marketing: Integrating Customer Focus Across the Firm, (2000)","J. C. H. Chen; Graduate School of Business, Gonzaga University, Spokane, WA 99258, E. 502 Boone Ave., United States; email: chen@jepson.gonzaga.edu",{"$nulls":7},1672533.0,null,"HSMAD",null,"English","Hum Syst Manage","Article","Final",null,"Scopus","2-s2.0-77950538563"]
["Liao S.-H.; Chen Y.-J.; Lin Y.-T.","Liao, Shu-Hsien (7401923068); Chen, Yin-Ju (7601439698); Lin, Yi-Tsun (36774944300)","7401923068; 7601439698; 36774944300","Mining customer knowledge to implement online shopping and home delivery for hypermarkets",2011.0,"Expert Systems with Applications",38.0,4.0,null,3982.0,3991.0,9.0,41.0,"10.1016/j.eswa.2010.09.059","https://www.scopus.com/inward/record.uri?eid=2-s2.0-78650713938&doi=10.1016%2fj.eswa.2010.09.059&partnerID=40&md5=b9bd9bbcf9f07d2578903a89d81251fe","Department of Management Sciences and Decision Making, Tamkang University, Danshuei Jen, Taipei Country 251, No. 151, Yingjuan Road, Taiwan","Liao S.-H., Department of Management Sciences and Decision Making, Tamkang University, Danshuei Jen, Taipei Country 251, No. 151, Yingjuan Road, Taiwan; Chen Y.-J., Department of Management Sciences and Decision Making, Tamkang University, Danshuei Jen, Taipei Country 251, No. 151, Yingjuan Road, Taiwan; Lin Y.-T., Department of Management Sciences and Decision Making, Tamkang University, Danshuei Jen, Taipei Country 251, No. 151, Yingjuan Road, Taiwan","With advances in modern technology, the Internet population has increased year by year globally. For young customers who consider convenience and speed as prerequisites, online shopping has become a new type of consumption. In addition, business-to-customer (B2C) home delivery markets have taken shape gradually, because virtual stores have risen and developed, e.g. mail-order, TV marketing, e-commerce. To integrate the above statements, this study combines online shopping and home delivery, and attempts to use association rules to determine unknown bundling of fresh products and non-fresh products in a hypermarket. Customers are then divided up in clusters by clustering analysis, and the catalog is design based on each of the cluster's consumption preferences. By this method, to increase the catalogue's attraction to customers, hypermarkets are offered an online shopping and home delivery business model for sales services and propositions. With such a model, we can expect to attract more customers open up more broad markets, and earn the higher profits for hypermarkets. © 2010 Elsevier Ltd. All rights reserved.","Association rule; Cluster analysis; Data mining; Database marketing; Electronic commerce; Home delivery; On-line shopping","Association rules; Cluster analysis; Customer satisfaction; Data handling; Data mining; Electronic commerce; Libraries; Profitability; Business models; Business to customers; Clustering analysis; Database marketing; E-Commerce; Home delivery; Hypermarkets; IS design; Modern technologies; On-line shopping; Sales",{"$nulls":4},"National Science Council, Taiwan, Republic of China, (NSC 98-2410-H-032-038 –MY2)","This research was funded by the National Science Council, Taiwan, Republic of China, under contract No. NSC 98-2410-H-032-038 –MY2.","Agrawal R., Imilienski T., Swami A., Mining association rules between sets of items in large databases, Proceedings of the 1993 ACM SIGMOD International Conference on Management of Data, pp. 207-216, (1993); Agrawal R., Shafer J., Parallel mining of association rules, IEEE Transactions on Knowledge and Data Engineering, 8, 6, pp. 962-969, (1996); Anita P., Dirk Den V.P., Constrained optimization of data-mining problems to improve model performance: A direct-marketing application, Expert Systems with Applications, 29, 3, pp. 630-640, (2005); Arie B., Sterling L., Generating rules from examples of human multiattribute decision making should be simple, Expert Systems with Applications, 31, 2, pp. 390-396, (2006); Berzal F., Cubero J., Marin N., Serrano J., TBAR: An efficient method for association rule mining in relational databases, Data and Knowledge Engineering, 37, pp. 47-64, (2001); Boyer K.K., Hult G.T.M., Customer behavioral intentions for online purchases: An examination of fulfillment method and customer experience level, Journal of Operations Management, 24, 2, pp. 124-147, (2006); Carrefour of Taiwan Annual Report in 2007, (2008); Codd E.F., A relational model of data for large shared data banks, Communications of the ACM, 13, 6, pp. 377-387, (1970); Keim D.A., Pansea C., Sipsa M., Northb S.C., Pixel based visual data mining of geo-spatial data, Computers and Graphics, 28, pp. 327-344, (2004); Kouris I.N., Makris C.H., Tsakalidis A.K., Using Information Retrieval techniques for supporting data mining, Data and Knowledge Engineering, 52, pp. 353-383, (2005); Liao S.H., Knowledge management technologies and applications - Literature review from 1995 to 2002, Expert Systems with Applications, 25, pp. 155-164, (2003); Liao S.H., Chen Y.J., Mining customer knowledge for electronic catalog marketing, Expert Systems with Applications, 27, pp. 521-532, (2004); Liao S.H., Expert system methodologies and applications - A decade review from 1995 to 2004, Expert Systems with Applications, 28, pp. 93-103, (2005); Liao S.H., Hsieh C.L., Huang S.P., Mining product maps for new product development, Expert Systems with Applications, 34, 1, pp. 50-62, (2008); Liao S.H., Chen C.M., Chieh C.L., Hsiao S.C., Mining information users' knowledge for one-to-one marketing on information appliance, Expert Systems with Applications, 36, 3, pp. 4967-4979, (2009); Liao S.H., Chen Y.N., Tseng Y.Y., Mining demand chain knowledge of life insurance market for new product development, Expert Systems with Applications, 36, 2, pp. 9422-9437, (2009); Liao S.H., Chen J.L., Hsu T.Y., Ontology-based data mining approach implemented for sport marketing, Expert Systems with Applications, 36, 8, pp. 11045-11056, (2009); Liang T.P., Huang J.S., An empirical study on consumer acceptance on products in electronic markets: A transaction cost model, Decision Support Systems, 24, 1, pp. 29-43, (1998); Mehta K., Bhattacharyya S., Adequacy of training data for evolutionary mining of trading rules, Decision Support Systems, 37, pp. 461-474, (2004); Musaev A.A., Analytic information technologies in oil refinery, Expert Systems with Applications, 26, pp. 81-85, (2004); Padmanabhan B., Tuzhilin A., Knowledge refinement based on the discovery of unexpected patterns in data mining, Decision Support Systems, 33, pp. 309-321, (2002); Peterson R.A., Balasubramanian S., Bronnenberg B.J., Exploring the implications of the Internet for consumer marketing, Journal of Academy of Marketing Science, 25, 4, pp. 329-346, (1997); Ranganathan C., Ganapathy S., Key dimensions of business-to-consumer web sites, Information and Management, 39, 6, pp. 457-465, (2002); Reichheld F.F., Schefter P., E-loyalty: Your secret weapon on the web, Harvard Business Review, 78, 4, pp. 105-113, (2000); Thabtah F., Cowling P., Hammoud S., Improving rule sorting, predictive accuracy and training time in associative classification, Expert Systems with Applications, 31, 2, pp. 414-426, (2006); Tsechansky M., Pliskin N., Rabinowitz G., Porath N., Mining relational patterns from multiple relational tables, Decision Support Systems, 27, pp. 177-195, (1999); Ture M., Kurt I., Turhan K.A., Ozdamar K., Comparing classification techniques for predicting essential hypertension, Expert Systems with Applications, 16, 4, pp. 379-384, (2005); Verhoef P.C., Langerak F., Possible determinants of consumers' adoption of electronic grocery shopping in the Netherlands, Journal of Retailing and Consumer Services, 8, 5, pp. 275-285, (2001); Vrahatis M.N., Boutsinas B., Alevizos P., Pavlides G., The new k-windows algorithm for improving the k-means clustering algorithm, Journal of Complexity, 18, 1, pp. 375-391, (2002); Wang Y.F., Chuang Y.L., Hsu M.H., Keh H.C., A personalized recommender system for the cosmetic business, Expert Systems with Applications, 26, pp. 427-434, (2004)","S.-H. Liao; Department of Management Sciences and Decision Making, Tamkang University, Danshuei Jen, Taipei Country 251, No. 151, Yingjuan Road, Taiwan; email: michael@mail.tku.edu.tw",{"$nulls":7},9574174.0,null,"ESAPE",null,"English","Expert Sys Appl","Article","Final",null,"Scopus","2-s2.0-78650713938"]
["Xiaoping Z.; Chunxia W.; Dong T.; Xiaoshuan Z.","Xiaoping, Zheng (36191539000); Chunxia, Wu (35108722500); Dong, Tian (7101795859); Xiaoshuan, Zhang (8448836000)","36191539000; 35108722500; 7101795859; 8448836000","B2B E-Marketplace adoption in agriculture",2009.0,"Journal of Software",4.0,3.0,null,232.0,238.0,6.0,13.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-78651569735&partnerID=40&md5=7951da2bf47ed1ddd6eb503e7e5565cb","College of Economics and Management, China Agricultural University, Beijing, China; College of Information and Electrical Engineering, China Agricultural University, Beijing, China","Xiaoping Z., College of Economics and Management, China Agricultural University, Beijing, China; Chunxia W., College of Economics and Management, China Agricultural University, Beijing, China; Dong T., College of Information and Electrical Engineering, China Agricultural University, Beijing, China; Xiaoshuan Z., College of Information and Electrical Engineering, China Agricultural University, Beijing, China","Abstract The Internet provides new opportunities and challenges for agricultural product marketing. B2B E-marketplace is a model of E-commerce, which has been used to trade a wide range of goods, including agricultural products. The paper attempted to analyze the benefits and critical factors of B2B e-marketplace in agriculture product marketing case study by Shandong Shouguang Vegetable Trading Market Online (SSVTMO), which is a integral system including information publish system, visual digital transaction system and online auction system based on medium long-term spot trading. SSVTMO can implement value creation by personalized information services, control of the fulfillment process, Strategic partners network and controlling complexity. Furthermore, E-marketplace adoption in agriculture still faces technology and collaboration barriers. © 2009 ACADEMY PUBLISHER.","Agricultural product logistic; B2B E-marketplace; E-commerce; Medium Long-term Spot Trading; Vegetable Trading","Electronic commerce; Information services; Marketing; Agriculture products; B2B E-marketplace; Controlling complexity; Critical factors; E-commerce; E-marketplaces; Integral Systems; Medium Long-term Spot Trading; New opportunities; Online auction system; Personalized information; Shandong; Strategic partners; Transaction systems; Value creation; Vegetable Trading; Agricultural products",{"$nulls":6},"Barua A., Chcllappa R., Whinston A., The design and development of internet and intranet-based collaboratories, International Journal of Electronic Commerce, pp. 32-58, (1996); Economic Research Service, Agricultural Resource Management Study, (1999); Mueller R.A.E., Emergent E-Commerce in Agriculture, (2000); Goswami R., Juneja E., Sharma S., Agribusiness sector in Rural India and increasing opportunities of E-Commerce, Marketing to Rural Consumers-Understanding and tapping the rural market potential, (2008); Nicolaisen R., How Will Agricultural E-Markets Evolve?, Paper Presented at the USDA OutlookForum, pp. 22-23, (2001); Porter M., Strategy and the Internet, Harvard Business Review, 79, 2, pp. 63-78, (2001); Poole B., How will Agricultural E-Markets Evolve?, Paper Presented at the USDA Outlook Forum, pp. 22-23, (2001); China launches first agricultural e-commerce website, (2000); Zhili Y., Agriculture Websites up to 2200 in China, (2001); Zhao J., Wang S., Huang W.V., A study of B2B e-market in China: E-commerce process perspective, Information & Management, 45, pp. 242-248, (2008); Folorunso O., Longe H.O.D., Akinde A.D., Ishola K.A., A framework for establishing Agriculture E-Commerce, Agric-ECRC: Resource Centre, Nigeria. J. Comp. Sci. Applic, 10, pp. 141-149, (2004); Leroux N., Wortman Jr. M.S., Mathias E., Dominant factors impacting the development of Business-to-business e-commerce in Agriculture, Paper for the 2001 IAMA Symposium; Folorunso O., Sharma S.K., Longe H.O.D., Lasaki K., An Agent Based Model for Agriculture E-commerce, Information Technology Journal, 5, 2, pp. 230-234, (2006); E-commerce beyond 2000, The Commonwealth Department of Communications; Mueller R.A.E., E-Commerce and Agricultural Commodity Markets: E-Commerce and Entrepreneurship in Agricultural Markets, American Journal of Agricultural Economics, 83, 5, pp. 1243-1249, (2003); Ordanini A., Pol A., Infomediation and competitive advantage in B2b digital marketplaces, European Management Journal, 19, 3, pp. 276-285, (2001); Sachs G., B2B e-markets; Consulting D., Development and Trend of eMarketplace, E Business Executive Report, 19, pp. 12-13, (2000); Kaplan S., Sawhney M., EHub: The New B2B Marketplace, (2000); Butler T., Unpacking the systems development process: An empirical application of the CSF concept in a research context, The Journal of Strategic Information Systems, 8, 4, pp. 351-371, (1999); Li J., Li L., On the Critical Success Factors for B2B E-marketplace, Proceedings of the 7th international conference on Electronic commerce, pp. 119-122, (2005); Brunn P., Martin Jensen and Jakob Skovgaard, E-Marketplaces: Crafting A Winning Strategy, European Management Journal, 20, 3, (2002); Movahedi B., Lavassani K.M., Kumar V., How Can B2B E-Marketplaces (EM) Enhance the Quality of Supply Chain?, IFIP International Federation for Information Processing, 255, pp. 857-867, (2008); Farhoomand A.F., Tuunainen V.K., Yee L.W., Barriers to global electronic commerce: Across-country study of HongKong and Finland, Journal of Organizational Computing and Electronic Commerce, 10, 1, pp. 23-48, (2000); Kumar R.L., Crook C.W., A multi-disciplinary framework for the management of inter-organizational systems, Database for Advances in Information Systems, 30, 1, pp. 22-37, (1999); Hsiao R.-L., Technology fears: Distrust and cultural persistence in electronic marketplace adoption, Journal of Strategic Information Systems, 12, pp. 169-199, (2003); Porter M., Strategy and the Internet, Harvard Business Review, 79, 2, pp. 63-78, (2001); Yoo B., Choudhary V., Mukhopadhyay T., Neutral vs.biased marketplaces: A comparison of electronic B2B marketplaces with different ownership structures, Proceedings of 23nd International Conference on Information Systems, (2001)","Z. Xiaoshuan; College of Information and Electrical Engineering, China Agricultural University, Beijing, China; email: zhxshuan@cau.edu.cn",{"$nulls":7},"1796217X",null,null,null,"English","J. Softw.","Article","Final",null,"Scopus","2-s2.0-78651569735"]
["Huang X.; Gattiker T.F.; Schroeder R.G.","Huang, Xiaowen (23099765500); Gattiker, Thomas F. (7801650480); Schroeder, Roger G. (7202012355)","23099765500; 7801650480; 7202012355","Do competitive priorities drive adoption of electronic commerce applications? Testing the contingency and institutional views",2010.0,"Journal of Supply Chain Management",46.0,3.0,null,57.0,69.0,12.0,39.0,"10.1111/j.1745-493X.2010.03198.x","https://www.scopus.com/inward/record.uri?eid=2-s2.0-77955040503&doi=10.1111%2fj.1745-493X.2010.03198.x&partnerID=40&md5=9b62096575feedaa0bc18e4af4fe76ef","Miami University, United States; Boise State University, United States; University of Minnesota, United States","Huang X., Miami University, United States; Gattiker T.F., Boise State University, United States; Schroeder R.G., University of Minnesota, United States","This paper expands on recent research by Huang and colleagues examining the drivers of electronic commerce (e-commerce) adoption. Two competing theories are evaluated as predictors of e-commerce adoption: contingency theory and institutional theory. For the contingency view, we focus on three strategic priorities (cost, flexibility and delivery), and for the institutional view, we examine three institutional factors (region, industry and information technology benchmarking). The model is evaluated with logistic regression analysis using survey data from nine countries and three industries. While contingency theory is the norm in the literature, we find only limited evidence that competitive priorities guide e-commerce adoption. By contrast, institutional factors have greater explanatory power. © 2010 Institute for Supply Management, Inc.™.","Competitive priorities; Contingency theory; Electronic commerce; Institutional theory; Logistic regression; Strategy",{"$nulls":7},"Adam E.E., Swamidass P.M., Assessing Operations Management from a Strategic Perspective, Journal of Management, 15, 2, pp. 181-203, (1989); Agresti A., An Introduction to Categorical Data Analysis, (1996); Ahire S.O., Golhar D.Y., Waller M.A., Development and Validation of TQM Implementation Constructs, Decision Sciences, 27, 1, pp. 23-56, (1996); Anderson J.C., Cleveland G., Schroeder R.G., Operations Strategy: A Literature Review, Journal of Operations Management, 16, 9, pp. 48-59, (1989); Banker R.D., Bardhan I.R., Change H., Lin S., Plant Information Systems, Manufacturing Capabilities, and Plant Performance, MIS Quarterly, 30, 2, pp. 315-337, (2006); Bensaou M., Venkatraman N., Configurations of Interorganizational Relationships, Management Science, 41, 9, pp. 1471-1493, (1995); Berry W.L., Hill T., Linking Systems to Strategy, International Journal of Operations & Production Management, 12, 10, pp. 3-15, (1992); Bogan C.E., English M.J., Benchmarking for Best Practices: Winning through Innovative Adaptation, (1994); Boyer K.K., Longitudinal Linkages between Intended and Realized Operations Strategies, International Journal of Operations & Production Management, 18, 4, pp. 356-373, (1998); Burns T., Stalker G., The Management of Innovation, (1961); Burt D., Petcavage S., Pinkerton R., Supply Management, (2010); Camp R.C., Benchmarking: The Search for Industry Best Practices that Lead to Superior Performance, (2006); Cebon P., Love E.G., Why Do Late Adopters Perform Poorly: Symbolic Adoption, or Cultural Incongruity?, Academy of Management Proceedings, (2002); Chandler A., Strategy and Structure, (1962); Cua K.O., McKone K.E., Schroeder R.G., Relationships between Implementation of TQM, JIT, and TPM and Manufacturing Performance, Journal of Operations Management, 19, 6, pp. 675-694, (2001); Dean J.W., Snell S.A., The Strategic Use of Integrated Manufacturing: An Empirical Examination, Strategic Management Journal, 17, 6, pp. 459-480, (1996); DiMaggio P.J., Powell W.W., The Iron Cage Revisited: Institutional Isomorphism and Collective Rationality in Organizational Fields, American Sociological Review, 48, 2, pp. 147-160, (1983); Droge C., Jayaram J., Vickery S.K., The Effects of Internal Versus External Integrating Practices on Time-Based Performance and Overall Firm Performance, Journal of Operations Management, 22, 6, pp. 557-573, (2004); Duray R., Ward P.T., Milligan G.W., Berry W.L., Approaches to Mass Customization: Configurations and Empirical Validation, Journal of Operations Management, 18, 6, pp. 605-625, (2000); Emiliani M., Stec D., Aerospace Parts Suppliers' Reaction to Online Reverse Auctions, Supply Chain Management, 9, 2, pp. 139-153, (2004); Essig M., Arnold U., Electronic Procurement in Supply Chain Management: An Information Economics-Based Analysis of Electronic Markets, Journal of Supply Chain Management, 37, 4, pp. 43-49, (2001); Ferdows K., DeMeyer A., Lasting Improvements in Manufacturing Performance: In Search of a New Theory, Journal of Operations Management, 9, 2, pp. 168-184, (1990); Frohlich M.T., Westbrook R., Demand Chain Management in Manufacturing and Services: Web-Based Integration, Drivers and Performance, Journal of Operations Management, 20, pp. 729-745, (2002); Galaskiewicz J., Wasserman S., Mimetic and Normative Processes within an Interorganizational Field: An Empirical Test, Administrative Science Quarterly, 34, 3, pp. 454-479, (1989); Gattiker T.F., Goodhue D.L., What Happens after ERP Implementation: Understanding the Impact of Inter-Dependence and Differentiation on Plant-Level Outcomes, MIS Quarterly, 29, 3, pp. 559-585, (2005); Hair J.F., Anderson R.E., Tatham D.L., Black W.C., Multivariate Data Analysis, (1998); Hannan M.T., Freeman J., Organizational Ecology, (1989); Haunschild P.R., Miner A.S., Modes of Interorganizational Imitation: The Effects of Outcome Salience and Uncertainty, Administrative Science Quarterly, 42, 3, pp. 472-500, (1997); Haveman H.A., Follow the Leader: Mimetic Isomorphism and Entry into New Markets, Administrative Science Quarterly, 38, 4, pp. 593-627, (1993); Hayes R.H., Wheelwright S.C., Link Manufacturing Processes and Product Life Cycles, Harvard Business Review, 57, 1, pp. 133-140, (1979); Hayes R.H., Wheelwright S.C., Restoring Our Competitive Edge: Competing through Manufacturing, (1984); Hosmer D.W., Lemeshow S., Applied Logistic Regression, (1989); Culture, Leadership, and Organizations: The GLOBE Study of 62 Societies, (2004); Huang X., Gattiker T.F., Schroeder R.G., Structure-Infrastructure Alignment: The Relationship between TQM Orientation and the Adoption of Supplier-Facing Electronic Commerce among Manufacturers, Journal of Supply Chain Management, 44, 1, pp. 40-54, (2008); Huang X., Kristal M.M., Schroeder R.G., Linking Learning and Effective Process Implementation to Mass Customization Capability, Journal of Operations Management, 26, 6, pp. 714-729, (2008); Jasperson J.S., Carter P.E., Zmud R.W., A Comprehensive Conceptualization of Post-Adoptive Behaviors Associated with Information Technology Enabled Work Systems, MIS Quarterly, 29, 3, pp. 525-557, (2005); Judge W.Q., Douglas T.J., Kutan A.M., Institutional Antecedents of Corporate Governance Legitimacy, Journal of Management, 34, 4, pp. 765-785, (2008); Kaufmann L., Carter C.R., Deciding on the Mode of Negotiation: To Auction or Not to Auction Electronically, Journal of Supply Chain Management, 40, 2, pp. 15-26, (2004); Ketokivi M.A., Schroeder R.G., Strategic, Structural Contingency and Institutional Explanations in the Adoption of Innovative Manufacturing Practices, Journal of Operations Management, 22, 1, pp. 63-89, (2004); Kotha S., Orne D., Generic Manufacturing Strategies: A Conceptual Synthesis, Strategic Management Journal, 10, 3, pp. 211-231, (1989); Kraljic P., Purchasing Must Become Supply Management, Harvard Business Review, 61, 5, pp. 109-117, (1983); Lai F., Li D., Wang Q., Zhao X., The Information Technology Capability of Third-Party Logistics Providers: A Resource-Based View and Empirical Evidence from China, Journal of Supply Chain Management, 44, 3, pp. 22-38, (2008); Larson P.D., Carr P., Dhariwal K., SCM Involving Small Versus Large Suppliers: Relational Exchange and Electronic Communication Media, Journal of Supply Chain Management, 41, 1, pp. 18-28, (2005); Lawrence P.R., Lorsch J.W., Organization and Environment, (1967); Lee H.L., Padmanabhan V., Whang S., The Bullwhip Effect in Supply Chains, Sloan Management Review, 38, 3, pp. 93-102, (1997); Leong G.K., Snyder D., Ward P.T., Research in the Process and Content of Manufacturing Strategy, Omega, 18, pp. 109-122, (1990); Matten D., Moon J., Implicit' and 'Explicit' CSR: A Conceptual Framework for a Comparative Understanding of Corporate Social Responsibility, Academy of Management Review, 33, 2, pp. 404-424, (2008); Miner A.S., Raghavan S.V., Interorganizational Imitation: A Hidden Engine of Selection, Variations in Organization Science, pp. 35-62, (1999); Murray M., Understanding the SAP Logistics Information System (LIS), (2007); Oliver C., Sustainable Competitive Advantage: Combining Institutional and Resource Based Views, Strategic Management Journal, 18, 9, pp. 697-713, (1997); Paulraj A., Chen I.J., Strategic Buyer-Supplier Relationships, Information Technology and External Logistics Integration, Journal of Supply Chain Management, 43, 2, pp. 2-14, (2007); Pearcy D., Giunipero L., Wilson A., A Model of Relational Governance in Reverse Auctions, Journal of Supply Chain Management, 43, 1, pp. 4-45, (2007); Rogers K.W., Purdy L., Safayeni F., Duimering P.R., A Supplier Development Program: Rational Process or Institutional Image Construction?, Journal of Operations Management, 25, pp. 556-572, (2007); Roth A.V., Competitive Progression Theory: Explanation and Empirical Evidence, Manufacturing Strategy: Operations Strategy in a Global Context, pp. 309-314, (1996); Roylance D., Purchasing Performance: Measuring, Marketing and Selling the Purchasing Function, (2009); Sabri E.H., Gupta A., Beitler M., Purchase Order Management Best Practices: Process, Technology, and Change Management, (2006); Safizadeh M.H., Ritzman L.P., Sharma D., Wood C., An Empirical Analysis of the Product-Process Matrix, Management Science, 42, 11, pp. 1576-1587, (1996); Sanders N.R., Pattern of Information Technology Use: The Impact on Buyer-Supplier Coordination and Performance, Journal of Operations Management, 26, 3, pp. 349-367, (2008); Schoenherr T., Mabert V.A., The Effect of Buyer-Imposed Bidding Requirements and Bundle Structure on Purchase Performance, Journal of Supply Chain Management, 43, 1, pp. 27-39, (2007); Scott W., The Adolescence of Institutional Theory, Administrative Science Quarterly, 32, 4, pp. 493-511, (1987); Scott W., Institutions and Organizations, (2001); Sila I., Examining the Effects of Contextual Factors on TQM and Performance through the Lens of Organizational Theories: An Empirical Study, Journal of Operations Management, 25, 1, pp. 83-109, (2007); Smeltzer L.R., Carr A.S., Reverse Auctions in Industrial Marketing and Buying, Business Horizons, 45, 2, pp. 47-52, (2002); Strader T.J., Lin F., Shaw M.J., The Impact of Information Sharing on Order Fulfillment in Divergent Differentiation Supply Chains, Journal of Global Information Management, 7, 1, pp. 16-25, (1999); Tsikriktsis N., Lanzolla G., Frohlich M.T., Adoption of e-Processes by Service Firms: An Empirical Study of Antecedents, Production & Operations Management, 13, 3, pp. 216-229, (2004); Westphal J.D., Gulati R., Shortell S.M., Customization or Conformity? An Institutional and Network Perspective on the Content and Consequences of TQM Adoption, Administrative Science Quarterly, 42, 2, pp. 366-394, (1997); Woodward J., Industrial Organization: Theory and Practice, (1965); Yao Y., Dresner M., Palmer J.W., Impact of Boundary-Spanning Information Technology and Position in Chain on Firm Performance, Journal of Supply Chain Management, 45, 4, pp. 3-16, (2009); Zsidisin G.A., Melnyk S.A., Ragatz G.L., An Institutional Theory Perspective of Business Continuity Planning for Purchasing and Supply Management, International Journal of Production Research, 43, 16, pp. 3401-3420, (2005)",{"$nulls":8},"1745493X",null,null,null,"English","J. Supply Chain Manage.","Article","Final",null,"Scopus","2-s2.0-77955040503"]
["Mǎrincaş D.A.","Mǎrincaş, Delia Adriana (33568042900)",3.35680429E10,"Information system for the supply chain management; [Sistem informatic pentru managementul lanţului logistic]",2008.0,"Amfiteatru Economic",10.0,24.0,null,236.0,253.0,17.0,3.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-69249139448&partnerID=40&md5=17b010846ba09f9df3538d3cdcee8100","Universitatea Babeş-Bolyai, Facultatea de Ştiinţe Economice şi Gestiunea Afacerilor, Cluj Napoca, Romania","Mǎrincaş D.A., Universitatea Babeş-Bolyai, Facultatea de Ştiinţe Economice şi Gestiunea Afacerilor, Cluj Napoca, Romania","Supply chain management SCM is the integration and management of supply chain organizations and activities through collaboration, effective business processes and high levels of information sharing. The supply chain concept has become a concern due to global competition and increasing customer demand for value. Thus, the information must be available in real time across the supply chain and this can not be achieved without an integrated software system for supply chain management. Supply chain members have to collaborate, sharing information for improving customers satisfaction. Web technologies enable enterprises to become more effective, to trade with suppliers and customers over the Internet in real time. For this, businesses have to integrate their information systems and applications with those of their suppliers and customers. First, companies have to redesign their supply chain to create an integrated value system and afterwards, companies can develop business to business applications across supply chain structure for the optimization of the supply chain. The implementation of the supply chain information systems in companies facilitates an increase in their competitiveness and their profits.","Collaboration; E-commerce; Information system; Information visibility; Logistics; Supply chain management; Web technology",{"$nulls":7},"Chandra C., Grabis J., Supply Chain Configuration - Concepts, Solutions and Applications, (2007); Fotache D., Hurbean L., Supply chain management: from linear interactions to networked processes, 4, 40, pp. 73-76, (2007); Handfield, Robert B., Ernest N.L., Supply chain redesign. transforming supply chains into integrated value systems, (2002); Ilies L., Management logistic, (2003); Inovis, Supply chain event management: Proactive supply chain visibility, (2007); Lefter V., Roman C., Sendroiu C., Roman C., Electronic cost alternatives for e-commerce, 21, pp. 79-90, (2007); Marakas M.G.,  century, (2003); Rosca I.Gh., Et al., Comerţ electronic. Concepts, technologies and applications, (2004); Turban E., Aronson J.E., Decision support systems and intelligent systems, (2001)","D.A. Mǎrincaş; Universitatea Babeş-Bolyai, Facultatea de Ştiinţe Economice şi Gestiunea Afacerilor, Cluj Napoca, Romania; email: marincasdelia@gmail.com",null,"Edituraase",{"$nulls":5},1.5829146E7,null,null,null,"English","Amfiteatru Econ.","Article","Final",null,"Scopus","2-s2.0-69249139448"]
["Sun H.; Teh P.-L.; Chiu A.","Sun, Hongyi (7404827637); Teh, Pei-Lee (24802337400); Chiu, Anron (55344001600)","7404827637; 24802337400; 55344001600","An empirical study on the websites service quality of Hong Kong small businesses",2012.0,"Total Quality Management and Business Excellence",23.0,"2024-08-07",null,931.0,947.0,16.0,7.0,"10.1080/14783363.2012.704273","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84865385468&doi=10.1080%2f14783363.2012.704273&partnerID=40&md5=36bd97afabedb5181a514a04007eeeff","Department of Systems Engineering and Engineering Management, City University of Hong Kong, Kowloon Tong, Hong Kong, Hong Kong; School of Business, Monash University, Petaling Jaya, Selangor, Malaysia","Sun H., Department of Systems Engineering and Engineering Management, City University of Hong Kong, Kowloon Tong, Hong Kong, Hong Kong; Teh P.-L., School of Business, Monash University, Petaling Jaya, Selangor, Malaysia; Chiu A., Department of Systems Engineering and Engineering Management, City University of Hong Kong, Kowloon Tong, Hong Kong, Hong Kong","This paper reports an empirical research on the service quality (SQ) of the websites of small businesses in Hong Kong. The research is based on a questionnaire survey of 124 netizens (net citizen) and a review of 30 websites in terms of 60 features related to website content. The research found that (1) about 13% of the website features are not highly expected by netizens, but most websites provide these features, (2) about 37% features are highly expected by netizens but few websites provide these features, and (3) about 50% features are in a balance, i.e. relevant expectations are provided by websites. Additionally, the research produces a ranked checklist of netizen expectations and a ranked checklist of website deliveries. The findings of this study provide valuable insights into website quality as an assessment of web site design and netizens' expectation. The implications for improving the existing websites or designing new websites for small businesses are discussed. This paper also contributes to the electronic SQ literature by employing a different approach to the dominant focus of E-S-QUAL in past studies. This paper concludes with recommendations for future research in the field of SQ in websites. © 2012 Copyright Taylor and Francis Group, LLC.","business-to-customer e-commerce; content of websites; netizen expectation and satisfaction; service quality of website",{"$nulls":7},"Azzone G., Bianchi R., Noci G., The company's web site: Different configurations, evolutionary path, Management Decision, 38, 7, pp. 470-479, (2000); Barrutia J.M., Gilsanz A., E-service quality: Overview and research agenda, International Journal of Quality and Service Sciences, 1, 1, pp. 29-50, (2009); Bennett P.D., Dictionary of marketing terms, (1995); Berger M., It's your move: How to use the Internet and databases to stay one step ahead of the competition, Sales & Marketing Management, 150, 3, pp. 44-53, (1998); Cao M., Zhang Q., Seydel J., B2C e-commerce web site quality: An empirical examination, Industrial Management & Data Systems, 105, 5, pp. 645-661, (2005); Cary M., Kay B., Orleman P., Robertshaw W., Ross G., Saunders D., Wittenbraker J., The customer Window<sup>SM</sup>, Quality Progress, 20, 6, pp. 37-43, (1987); Chang H.H., Lee C.H., Lai C.Y., E-service quality and relationship quality on dealer satisfaction: Channel power as a moderator, Total Quality Management & Business Excellence, (2012); Chang W.L., A mixed-initiative model for quality-based e-services pricing, Total Quality Management & Business Excellence, 22, 9, pp. 975-991, (2011); Chen H.M., Sheldon P.J., Destination information systems: Design issues and directions, Journal of Management Information System, 14, 2, pp. 151-176, (1997); Collier J.E., Bienstock C.C., Measuring service quality in e-retailing, Journal of Service Research, 8, 3, pp. 260-275, (2006); Flint D., Electronic commerce: The coming of perfect market, Electronic Commerce World Edition, 7, 3, pp. 23-24, (1997); Geissler G.L., Building customer relationships online: The web site designers' perspective, Journal of Consumer Marketing, 18, 6, pp. 488-502, (2001); Ghosh S., Selling on the Internet: Achieving competitive advantage and market lead, Planning Review, 25, 3, pp. 53-55, (1997); Gnaneswaran V., Pujari P.S., Bishu R.R., Evaluating website quality using e-service quality dimensions, Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 52, 16, pp. 1117-1121, (2008); Goodale M., Building a better web site, Civil Engineering, 29, 3, pp. 76-77, (2002); Hong Kong's new media: Driving SME business prospects, (2012); Ho J., Evaluating the World Wide Web: A study of 1000 commercial sites, (1996); Ho J., Evaluating the World Wide Web: A global study of commercial sites, Journal of Computer Mediated Communication, 3, 1, (1997); Huang W., Le T., Li X., Gandha S., Categorizing web features and functions to evaluate commercial web sites: An assessment framework and an empirical investigation of Australian companies, Industrial Management & Data Systems, 106, 4, pp. 523-539, (2006); Kuo T., Lu L.Y., Huang C.H., Wu G.C., Measuring users' perceived portal service quality: An empirical study, Total Quality Management & Business Excellence, 16, 3, pp. 309-320, (2005); Lee C.C., Investigating e-marketing development in Hong Kong SMEs (Project Report), (2002); Li Y.N., Tan K.C., Xie M., Measuring web-based service quality, Total Quality Management & Business Excellence, 13, 5, pp. 685-700, (2002); Lin H.F., The impact of website quality dimensions on customer satisfaction in the B2C e-commerce context, Total Quality Management & Business Excellence, 18, 4, pp. 363-378, (2007); Lociacono E., Watson R.T., Goodhue D., : A web site quality instrument, (2000); Marimon F., Yaya L.H.P., Fa M.C., Impact of e-quality and service recovery on loyalty: A study of e-banking in Spain, Total Quality Management & Business Excellence, (2012); Martin C., The digital estate: Strategies for competing, surviving, and thriving in an internetworked world, (1997); Melian-Alzola L., Padron-Robaina V., Tangibility as a quality factor in electronic commerce b2c, Managing Service Quality, 16, 3, pp. 320-338, (2006); Murphy J., Forrest E.J., Wotring C.E., Brymer R.A., Hotel management and marketing on the Internet: An analysis of sites and features, Cornell Hospitality Quarterly, 37, 3, pp. 70-82, (1996); Parasuraman A., Zeithaml V.A., Malhotra A., A multiple-item scale for assessing electronic service quality, Journal of Service Research, 7, 3, pp. 213-233, (2005); Perry M., Bodkin C., Content analysis of 100 company Web sites, Corporate Communications: An International Journal, 5, 2, pp. 87-97, (2000); Santos J., E-service quality: A model of virtual service quality dimensions, Managing Service Quality, 13, 3, pp. 233-246, (2003); Santouridis I., Trivellas P., Tsimonis G., Using E-S-QUAL to measure Internet service quality of e-commerce web sites in Greece, International Journal of Quality and Service Sciences, 4, 1, pp. 86-98, (2012); Sinha M., Wellborn W., The management of quality assurance, (1985); Tsai M.C., Chen L.F., Chan Y.H., Lin S.P., Looking for potential service quality gaps to improve customer satisfaction by using a new GA approach, Total Quality Management & Business Excellence, 22, 9, pp. 941-952, (2011); Tsang N.K.F., Lai M.T.H., Law R., Measuring e-service quality for online travel agencies, Journal of Travel & Tourism Marketing, 27, 3, pp. 306-323, (2010); Ware J.P., Gebauer J., Hartman A., Roldan M., 5 sins of doing business on the web, Informationweek, 682, pp. 73-88, (1998); Yoo B., Donthu N., Developing and validating a multidimensional consumer-based brand equity scale, Journal of Business Research, 52, 1, pp. 1-14, (2001); Zeithaml V.A., Parasuraman A., Malhotra A., E-service quality: Definition, dimensions and conceptual model, (2000); Zeithaml V.A., Parasuraman A., Malhotra A., Service quality delivery through web sites: A critical review of extant knowledge, Journal of the Academy of Marketing Science, 30, 4, pp. 362-375, (2002)","H. Sun; Department of Systems Engineering and Engineering Management, City University of Hong Kong, Kowloon Tong, Hong Kong, Hong Kong; email: mehsun@cityu.edu.hk",null,"Routledge",{"$nulls":5},1.4783363E7,null,"TQMAE",null,"English","Total Qual. Manage. Bus. Excellence","Article","Final",null,"Scopus","2-s2.0-84865385468"]
["Pavlovic M.; Koumboulis F.N.; Tzamtzi M.P.; Rozman C.","Pavlovic, Martin (16646401500); Koumboulis, Fotis N. (7004906738); Tzamtzi, Maria P. (6602733369); Rozman, Crtomir (7201408832)","16646401500; 7004906738; 6602733369; 7201408832","Role of automation agents in agribusiness decision support systems; [Función de los agentes de automatización en los sistemas de apoyo a la toma de decisiones en agronegocios]",2008.0,"Agrociencia",42.0,8.0,null,913.0,923.0,10.0,8.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-59549092914&partnerID=40&md5=55d19458f54efa6e90f036115e2fbd20","International Hop Growers' Convention - Secretary General, F-67173 Brumath, 22, Rue des roses, France; Department of Automation, Halkis Institute of Technology, Greece; Faculty of Agriculture, University of Maribor, Maribor, Slovenia","Pavlovic M., International Hop Growers' Convention - Secretary General, F-67173 Brumath, 22, Rue des roses, France; Koumboulis F.N., Department of Automation, Halkis Institute of Technology, Greece; Tzamtzi M.P., Department of Automation, Halkis Institute of Technology, Greece; Rozman C., Faculty of Agriculture, University of Maribor, Maribor, Slovenia","Various automation agents can be embedded in a modern Decision Support System in agriculture, based on the following design approaches: E-Learning Agent, Monitoring Agent, Fault Diagnosis Agent, Weather Information Agent, E-Commerce Agent and Logistics Agent. The proposed Agents contribute to farmers' education, to timely correct fault diagnosis and the incorporation of modern agricultural techniques. Moreover, they allow processing historical data, while taking into account several factors in order to support decision making. The preliminary Automation Agents for Decision Support Systems (AADSS) model idea may be applied to various agribusiness activities on international level. Moreover, an operator agent is proposed, that exploits technological and economic information gathered from all the aforementioned Automation Agents in order to make decisions regarding the proposal of possible scenarios in a chain of raw material production to a final product. An initiative to develop and introduce stepwise a model for hop industry decision support system with embedded automation agents has been launched within the International Hop Growers' Convention (IHGC). It is intended to support growers, merchants and brewers through their various decision making activities in agribusiness. The first concept results validate the application of a model for future research.","Applied computer modelling; Decision support systems; Forecasting; IHGC; Information management","Humulus",{"$nulls":6},"Berlo van J.M., A decision support tool for the vegetable processing industry; an integrative approach of market, industry and agriculture, Agric. Systems, 23, pp. 91-109, (1993); Biere A.W., Agribusiness logistics: An emerging field in agribusiness education, IAMA World Food and Agribusiness Symposium, 27, (2001); Folinas D., Vlachopoulou M., Manthou V., Manos B., A web-based integration of data and processes in the agribusiness supply chain, EFITA 2003 Conference, pp. 143-149, (2003); Koumboulis F.N., Tzamtzi M.P., Automation Agents Embedded in Industrial Decision Support Systems, International Conference on Intelligent Agents, pp. 51-57, (2005); Lambert M., Riera B., Martel G., Application of functional analysis techniques to supervisory systems, Reliability Eng. & System Safety, 64, pp. 209-224, (1999); McCown R.L., Changing systems for supporting farmers decisions: Problems, paradigms, and prospects, Agric. Systems, 74, pp. 179-220, (2002); Mira da Silva L., Park J.R., Keatinge J.D.H., Pinto P.A., A decision support system to improve planning and management in large irrigation schemes, Agric. Water Manag, 51, pp. 187-201, (2001); Parrott L., Lacroix R., Wade K.M., Design considerations for the implementation of multi-agent systems in the dairy industry, Computers and Electronics in Agric, 38, pp. 79-98, (2003); Pavlovic M., Koumboulis F.N., Tzamtzi M.P., Karras D.A., Model of information management and data exchange on a global hop supply, Proc. of the 2nd Int. Symp. on Intelligent Information Technology in Agriculture, pp. 20-23, (2003); Pavlovic M., Koumboulis F.M., Methodology of an IHGC Market Supply Data Collation. Hop Bull, 11, pp. 17-24, (2004); Pavlovic M., Luo X., Kosir I.J., Virant M., Gu F., Expansion of the Chinese hop and brewing industry, Hop Bull, 13, pp. 61-69, (2006); Recio B., Rubio F., Criado J.A., A decision support system for farm planning using AgriSupport II, Decision Support Systems, 36, pp. 189-203, (2003); Sanchez M., Cortes U., Lafuente J., Roda I.R., Poch M., DAIDEPUR: An integrated and distributed architecture for waste-water treatments plants, Artificial Intelligence in Eng, 1, pp. 275-285, (1996); Thangavadivelu S., Colvin T.S., Fuzzy-Logic-Based decision support system for scheduling tillage operations, Eng. Applications of Artificial Intelligence, 10, pp. 463-472, (1997); Welch S.M., Jones J.W., Brennan M.W., Reeder G., Jacobson B.M., PCYield: Model-based decision support for soybean production, Agric. Systems, 74, pp. 79-98, (2002)","M. Pavlovic; International Hop Growers' Convention - Secretary General, F-67173 Brumath, 22, Rue des roses, France; email: martin.pavlovic@guest.arnes.si",{"$nulls":7},1.4053195E7,null,null,null,"English","Agrociencia","Article","Final",null,"Scopus","2-s2.0-59549092914"]
["Gheorghe D.","Gheorghe, Dan (57190071418)",5.7190071418E10,"The impact of progress in information and communication technology on distribution and logistic activities",2011.0,"Metalurgia International",16.0,7.0,null,67.0,70.0,3.0,0.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-80052840544&partnerID=40&md5=90a186c8f87bb62ce45f65eccca1cde4","Ovidius University of Constanta, Faculty of Economic Sciences, Romania","Gheorghe D., Ovidius University of Constanta, Faculty of Economic Sciences, Romania","This paper aims at exploring the impact of internet on goods distribution systems and at the same time tries to present the significance of on-line business. Starting from other specialty papers, the objective is to present the significance of processes and concepts used by the science of marketing and especially in one of the components of marketing mix, respectively the distribution and logistics of goods. The application of economic restructuring generated by the information and communication technology is not only a mandatory necessity, but it should be understood that the ignorance of its importance can lead to the disappearance of any company. Information and communication technologies created on-line businesses (dot.com) which restructure the global economy, global markets, entire branches of economic activities, test the conventional economic thinking, redefine the types of businesses and generate changes in labor processes and its relocation. Successful companies shall be those which will fully apply this new technology, in an economy with borderless markets, opened non-stop, where the size of the company matters no more.","Business networks (b-webs); Cybermarketing; E-commerce (sales site); E-store (virtual store); Virtual businesses (on-line or internet)",{"$nulls":7},"Capital Magazine - the Article \"Industria it Se Restarteaza Cu Ajutor De Stat\"; Capital Magazine, the Article \"Cum Profita De Pe Urma Exploziei Retelelor Sociale\"; Danciu V., Grigorescu A., The Quoted Magazine and Article; Middleton J., Maiestrii Afacerilor On-line (Gurus on E-Business), (2010); Kelly K., Out of Control, (1994); Purcarea T., Popa V., Impactul e-business asupra distribuţiei bunurilor de larg consum, The Marketing - Management Magazine, 3, (2002); Capital Magazine, (2007); Capital Magazine, 10, (2009)","D. Gheorghe; Ovidius University of Constanta, Faculty of Economic Sciences, Romania; email: secretariat@traian-sa.com",{"$nulls":7},1.5822214E7,null,null,null,"English","Metal. Int.","Article","Final",null,"Scopus","2-s2.0-80052840544"]
["Campbell A.M.; Savelsbergh M.W.P.","Campbell, Ann Melissa (7403504864); Savelsbergh, Martin W. P. (6701542933)","7403504864; 6701542933","Decision support for consumer direct grocery initiatives",2005.0,"Transportation Science",39.0,3.0,null,313.0,327.0,14.0,130.0,"10.1287/trsc.1040.0105","https://www.scopus.com/inward/record.uri?eid=2-s2.0-25144435942&doi=10.1287%2ftrsc.1040.0105&partnerID=40&md5=ab083a04c378dad843470f9ce7cd15bb","Department of Management Sciences, Tippie College of Business, University of Iowa, Iowa City, IA 52242-1000, United States; School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA 30332-0205, United States","Campbell A.M., Department of Management Sciences, Tippie College of Business, University of Iowa, Iowa City, IA 52242-1000, United States; Savelsbergh M.W.P., School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA 30332-0205, United States","Many companies with consumer direct service models, especially grocery delivery services, have found that home delivery poses an enormous logistical challenge due to the unpredictability of demand coupled with strict delivery windows and low profit margin products. These systems have proven difficult to manage effectively and could benefit from new technology, particularly to manage the interaction between order capture and order delivery. In this article, we define routing and scheduling problems that incorporate important features of this emerging business model and propose algorithms, based on insertion heuristics, for their solution. In the proposed home delivery problem, the company decides which deliveries to accept or reject as well as the time slot for the accepted deliveries so as to maximize expected profits. Computational experiments reveal the importance of an approach that integrates order capture with order delivery and demonstrates the quality and value of the proposed algorithms. © 2005 INFORMS.","Delivery windows; e-commerce; Home delivery; Insertion heuristics; Real-time decision making; Vehicle routing","Algorithms; Decision making; Electronic commerce; Heuristic methods; Integration; Mathematical models; Problem solving; Real time systems; Routers; Scheduling; Delivery windows; Home delivery; Insertion heuristics; Real-time decision making; Vehicle routing; Customer satisfaction",{"$nulls":6},"Bagchi P.K., Nag B.N., Dynamic vehicle scheduling: An expert systems approach, Internat. J. Physical Distribution Logistics Management, 21, 2, pp. 10-18, (1991); Bertsimas D., A vehicle-routing problem with stochastic demand, Oper. Res., 40, 3, pp. 574-585, (1992); Bertsimas D., Simchi-Levi D., A new generation of vehicle routing research: Robust algorithms, addressing uncertainty, Oper. Res., 44, 2, pp. 286-303, (1996); Bertsimas D., Jaillet P., Odoni A., A priori optimization, Oper. Res., 38, 6, pp. 1019-1033, (1990); Cheung R.K., Powell W., An algorithm for multistage dynamic networks with random arc capacities with an application to dynamic fleet management, Oper. Res., 44, 6, pp. 951-963, (1996); Cox B., Internet grocer seeks an angel, InternetNews, (2001); Farmer M., Sandoval G., Webvan Delivers its Last Word: Bankruptcy, (2001); Fendelman A., First Time, First Market: Peapod Achieves Profitability in Chicago, (2001); Frantzekakis L.F., Powell W.B., A successive linear approximation procedure for stochastic, dynamic vehicle allocation problems, Transportaion Sci., 24, pp. 40-57, (1990); Gendreau M., Laporte G., Seguin R., An exact algorithm for the vehicle routing problem with stochastic demands and customers, Transportation Sci., 29, 2, pp. 143-155, (1995); Gendreau M., Laporte G., Seguin R., Stochastic vehicle routing, Eur. J. Oper. Res., 88, pp. 3-12, (1996); Logistics J., The Challenge of e-logistics, (2001); Kontoravdis G., Bard J., A grasp for the vehicle routing problem with time windows, ORSA J. Comput., 7, pp. 10-23, (1995); Littlewood K., Forecasting and control of passengers, 12th AGIFORS Sympos. Proc., pp. 95-117, (1972); Powell W., A stochastic formulation of the dynamic assignment problem with an application to truckload motor carriers, Transportation Sci., 30, pp. 195-219, (1996); Prosser P., Kilby P., Shaw P., Dynamic VRPs: A study of scenarios, Technical Report, APES-06-1998, (1998); Psaraftis H., Dynamic vehicle routing problems, Vehicle Routing: Methods and Studies, pp. 223-249, (1988); Psaraftis H., Dynamic vehicle routing: Status and prospects, Ann. Oper. Res., 61, pp. 143-164, (1995); Punakivi M., The value added of route optimisation in home delivery, Working Paper, (2000); Regan A., Mahmassani H., Jaillet P., Dynamic decision making for commercial fleet operations using real-time operations, Transportation Res. Record, 1537, pp. 91-97, (1998); Regan A., Mahmassani H., Jaillet P., Evaulation of dynamic fleet management systems, Transportation Res. Record, 1645, pp. 176-184, (1998); Rego C., Roucairol C., Using tabu search for solving a dynamic multi-terminal truck dispatching problem, Eur. J. Oper. Res., 83, pp. 411-429, (1995); Saranen J., Smaros J., An analytical model for home delivery in the new economy, Working Paper, (2001); Savelsbergh M., Local search for routing problems with time windows, Ann. Oper. Res., 4, pp. 285-305, (1986); Savelsbergh M., Sol M., Drive: Dynamic routing of independent vehicles, Oper. Res., 46, pp. 474-490, (1998); Talluri K., Van Ryzin G., An analysis of bid-price controls for network revenue management, Management Sci., 44, pp. 1577-1593, (1998); Talluri K., Van Ryzin G., A randomized linear programming method for computing network bid prices, Transportation Sci., 33, 2, pp. 207-216, (1999); Rjola H., Physical distribution considerations for electronic grocery shopping, Internat. J. Physical Distribution Logistics Management, 31, 10, pp. 746-761, (2001); Zhu K., Ong K.-L., A reactive method for real time dynamic vehicle routing problems, 12th IEEE Internat. Conf. Tools Artificial Intelligence, (2000)","A.M. Campbell; Department of Management Sciences, Tippie College of Business, University of Iowa, Iowa City, IA 52242-1000, United States; email: ann-campbell@uiowa.edu",null,"INFORMS Inst.for Operations Res.and the Management Sciences",{"$nulls":5},411655.0,null,"TRSCB",null,"English","Transp Sci","Article","Final",null,"Scopus","2-s2.0-25144435942"]
["Gerber A.; Russ C.; Klusch M.","Gerber, Andreas (56224861100); Russ, Christian (57224564621); Klusch, Matthias (56229075300)","56224861100; 57224564621; 56229075300","Supply web co-ordination by an agent-based trading network with integrated logistics services",2003.0,"Electronic Commerce Research and Applications",2.0,"2 SPEC.",null,133.0,146.0,13.0,19.0,"10.1016/S1567-4223(03)00015-2","https://www.scopus.com/inward/record.uri?eid=2-s2.0-0038711506&doi=10.1016%2fS1567-4223%2803%2900015-2&partnerID=40&md5=26a1f85e6455693fcc8a0fa5379f8102","German Res. Ctr. for Artif. Intell., 66123 Saarbrücken, Stuhlsatzenhausweg 3, Germany","Gerber A., German Res. Ctr. for Artif. Intell., 66123 Saarbrücken, Stuhlsatzenhausweg 3, Germany; Russ C., German Res. Ctr. for Artif. Intell., 66123 Saarbrücken, Stuhlsatzenhausweg 3, Germany; Klusch M., German Res. Ctr. for Artif. Intell., 66123 Saarbrücken, Stuhlsatzenhausweg 3, Germany","B2B interactions, like electronic negotiations and auctions between suppliers and customers, could be significantly improved by enabling the participants to adapt their bidding strategies to current logistics information (e.g., about transportation condition, cost or dates) while the negotiation goes on. We present an approach of an agent-based information and trading network (ITN) called CASA for dynamic production and sales of timber; the integrated services for logistics and e-commerce are efficiently coordinated by appropriate types of holonic structured intelligent agents of the network. We introduce the agent-based architecture and describe how the agents build their plans and optimize them afterwards. For optimizing their plans, the agents use various market-based negotiation mechanisms, i.e., several auction mechanisms and the simulated trading mechanism described in detail in this article. The effects of the different mechanisms on resulting cost and surplus have been evaluated by various simulation runs in different competitive and co-operative settings. It turned out that the simulated trading mechanism as well as matrix auction mechanisms for two or three items are especially suitable for supply web co-ordination and optimization tasks. © 2003 Published by Elsevier Science B.V.","Agent-based trading network; Integrated logistics services; Supply web co-ordination","Computer simulation; Costs; Marketing; Production; World Wide Web; Intergrated logistics services; Intelligent agents",{"$nulls":6},"Bachem A., Hochstattler W., Malich M., Simulated trading: A new approach for solving vehicle routing problems, Technical Report 92.125, (1992); Burckert H.-J., Fischer K., Vierke G., Transportation scheduling with holonic MAS - The teletruck approach, Proceedings of the Third International Conference on Practical Applications of Intelligent Agents and Multiagents (PAAM'98), (1998); Burckert H.-J., Fischer K., Vierke G., Holonic transport scheduling with TeleTruck, Applied Artificial Intelligence, 14, pp. 697-725, (2000); Fischer K., Muller J.P., Pischel M., Cooperative transportation scheduling: An application domain for DAI, Journal of Applied Artificial Intelligence, 10, (1996); Gerber A., Klusch M., CASA: Agents for mobile integrated commerce in forestry and agriculture, Proceedings of the Workshop of the Seventeenth International Joint Conference on Artificial Intelligence (IJCAI 2001) on E-Business and the Intelligent Web, (2001); Gerber C., Russ C., Vierke G., An empirical evaluation on the suitability of marketbased mechanisms for telematics applications, Technical Report, TM9802, (1998); Gerber C., Russ C., Vierke G., On the suitability of market-based mechanisms for telematics applications, Proceedings of the International Conference on Autonomous Agents (Agents'99), (1999); Gerber C., Siekmann J., Vierke G., Holonic multi-agent systems, DFKI Research Report, RR-99-03, (1999); Gomber P., Schmidt C., Weinhardt C., Efficiency incentives and computational tractability in the coordination of multiagent systems, Proceedings of the Workshop Kooperationsnetze und Elektronische Koordination, (1998); Klusch M., Burckert H.-J., Gerber A., Russ C., Applications of information agents and systems, Practical Applications of Intelligent Agents, (2002); Laseter T.M., Balanced Sourcing: Cooperation and Competition in Supplier Relationships, (1998); Smith R.G., The contract net protocol: High-level communication and control and a distributed problem solver, IEEE Transactions and Computers, C29, 12, pp. 1104-1113, (1980); Vickrey W., Counterspeculation, auctions, and competitive sealed tenders, Journal of Finance, 16, pp. 8-37, (1961); Vierke G., TELETRUCK - A Holonic Multi-Agent System for Telematics, (2000); Warzecha A., The content of e-business, Internet Content Management 2001, (2001); Wolfstetter E., Auctions: An introduction, Economic Surveys, 10, 4, (1996)","A. Gerber; German Res. Ctr. for Artif. Intell., 66123 Saarbrücken, Stuhlsatzenhausweg 3, Germany; email: agerber@dfki.de",null,"Elsevier",{"$nulls":5},1.5674223E7,null,null,null,"English","Elect. Commer. Res. Appl.","Article","Final",null,"Scopus","2-s2.0-0038711506"]
["Khouja M.","Khouja, Moutaz (7006682916)",7.006682916E9,"The evaluation of drop shipping option for e-commerce retailers",2001.0,"Computers and Industrial Engineering",41.0,2.0,null,109.0,126.0,17.0,59.0,"10.1016/S0360-8352(01)00046-8","https://www.scopus.com/inward/record.uri?eid=2-s2.0-0035501496&doi=10.1016%2fS0360-8352%2801%2900046-8&partnerID=40&md5=c58ad8019acbc394e105c356a9ed322d","Department of Business Information Systems and Operations Management, The Belk College of Business Administration, The University of North Carolina at Charlotte, Charlotte, NC 28223, United States","Khouja M., Department of Business Information Systems and Operations Management, The Belk College of Business Administration, The University of North Carolina at Charlotte, Charlotte, NC 28223, United States","Many e-commerce retailers use drop shipping to satisfy demand. A retailer simply forwards customers' orders to the manufacturer who fills the orders directly to the customers and is paid a predetermined price by the retailer. Advantages of drop shipping include lower costs of holding inventory, materials handling, and obsolescence. Disadvantages of drop shipping include fragmented order delivery when a single customer order involves products from different manufacturers and longer delivery times. A mix of holding inventory and drop shipping is frequently optimal for e-retailers. In this paper, we design an optimal mix strategy which captures the advantages of drop shipping and avoids many of its shortcomings. We use two different optimization criterion, maximizing the expected profit and maximizing the probability of achieving a target profit. We provide results for uniform, exponential, and normal demand distributions. We illustrate the results with numerical examples. © 2001 Elsevier Science Ltd. All rights reserved.","Drop shipping; e-Commerce; Inventory management","Internet; Inventory control; Materials handling; Obsolescence; Optimization; Drop shipping; Electronic commerce",{"$nulls":6},"Frook J.E., Commerce sites need inventory management, InternetWeek, (1998); Gallego G., Moon I., The distribution free newsboy problem: Review and extensions, Journal of the Operational Research Society, 44, pp. 825-834, (1993); Ismail B., Louderback J., Optimizing and satisfying in stochastic cost-volume-profit analysis, Decision Sciences, 10, pp. 205-217, (1979); Kabak I., Schiff A., Inventory models and management objectives, Sloan Management Review, 10, pp. 53-59, (1978); Kaplan W., Advanced calculus, (1984); Lanzilotti R.F., Pricing objectives in large companies, American Economic Review, 48, pp. 921-940, (1958); Li J., Lau H., Lau A.H., A two-product newsboy problem with satisfying objective and independent exponential demands, IIE Transactions, 23, pp. 29-39, (1991); Lau H., The newsboy problem under alternative optimization objectives, Journal of the Operational Research Society, 31, pp. 525-535, (1980); Meyer P.L., Introductory probability and statistical applications, (1970); Nahmias S., Production and operations management, 3rd ed, (1996); Scheel N.T., Drop shipping as a marketing function, A handbook of methods and policies, (1990); Weatherford L.R., Pfeifer P.E., The economic value of using advance booking of orders, Omega, 22, pp. 105-111, (1994); Wilson R.F., Analyzing the drop-shipping model for online stores, Web commerce Today, 16, (1988); Wilson R.F., Distribution decisions: Drop shipping vs. inventory vs. fulfillment house, Web Marketing Today; Wood L., For retailers, the sale seems to be easy part, Chicago Tribune, Internet Edition, (1999)","M. Khouja; Department of BISOM, Belk College of Bus. Administration, University of North Carolina, Charlotte, NC 28223, United States; email: mjkhouja@email.uncc.edu",{"$nulls":7},3608352.0,null,"CINDD",null,"English","Comput Ind Eng","Article","Final",null,"Scopus","2-s2.0-0035501496"]
["Nikoloyuk G.M.; Marche S.; McNiven J.","Nikoloyuk, Gerald M. (8585468400); Marche, Sunny (6603308764); McNiven, James (8585468300)","8585468400; 6603308764; 8585468300","E-commerce impact on Canadian public sector audit practice",2005.0,"International Journal of Public Sector Management",18.0,1.0,null,83.0,95.0,12.0,6.0,"10.1108/09513550510576161","https://www.scopus.com/inward/record.uri?eid=2-s2.0-19944374793&doi=10.1108%2f09513550510576161&partnerID=40&md5=7cfb3c8fdd2fdba89674b1931aad9850","Public Works and Government Services Canada, Gatineau, Que., Canada; Dalhousie University, Halifax, NS, Canada","Nikoloyuk G.M., Public Works and Government Services Canada, Gatineau, Que., Canada; Marche S., Dalhousie University, Halifax, NS, Canada; McNiven J., Dalhousie University, Halifax, NS, Canada","Purpose - This paper reports on the research conducted into the adaptations Canadian public sector auditors have made to the emergence of e-commerce and e-business in the delivery of public services. Design/methodology/approach - A comprehensive review of the literature was completed as a foundation for creating a semi-structure interview questionnaire used in a series of interviews with audit executives from 20 audit organizations in Canada's public sectors. Findings - The study found a distinct disconnect between what is reported in the literature and what has actually happened in practice. Practicing auditors do have a significant interest in the impact of e-business on the audit profession specifically and on their client organizations generally. But there is significant disagreement about whether e-business constitutes just another set of technologically mediated changes, not much different from the many others of the past 30 years, or whether e-business is truly disruptive in nature. The consequence of this disagreement is difference in audit practice among constituencies and highly variable dependency on external expertise in favour of developing internal capacity. Research limitations/implications - The research is limited to internal auditors of public sector organizations in Canada. Practical implications - A key area for future research is the impact on e-business on horizontality of management practice in the public sector and the need for more holistic audit interventions. Originality/value - The paper identifies key differences between what is said in the literature and what is done on the ground. It identifies key lessons from audit experience related to evolving e-government, including the management of new risks. The research is valuable to both researchers and practicing public sector audit executives alike. © Emerald Group Publishing Limited.","Auditing standards; Canada; Electronic commerce; Professional education; Public administration","business; e-commerce; public sector",{"$nulls":6},"Adam S., Deans K.R., WebQUAL: An e-commerce audit, Proceedings of the AusWeb99: 5th Australian World Wide Web Conference, (1999); Attaway Sr. M.C., What every auditor needs to know about e-commerce, The Internal Auditor, 57, 3, pp. 56-60, (2000); Brune C., Combating e-crime, The Internal Auditor, 57, 6, pp. 13-15, (2000); Brune C., E-business misses the mark on customer service, The Internal Auditor, 57, 3, pp. 13-15, (2000); Buckstein J., The impact of e-commerce and electronic service delivery on Canada's federal government, (2001); Burr T., Gandara M., Robinson K., E-commerce: Auditing the rage, The Internal Auditor, 59, 5, pp. 49-53, (2002); Cashell J.D., Aldhizer III G.R., Webtrust: A seal of approval, The Internal Auditor, 56, 3, pp. 50-53, (1999); Chan S., Risky e-business, The Internal Auditor, 58, 6, pp. 62-63, (2001); Conley J., Outwitting cybercriminals, Risk Management, 47, 7, pp. 18-24, (2000); Flesher D.L., Zarzeski M.T., The roots of operational (value-for-money), auditing in English-speaking nations, Accounting and Business Research, 32, 2, pp. 93-104, (2002); Gray G.L., Debreceny R., The electronic frontier, Journal of Accountancy, 185, 5, pp. 32-38, (1998); Helms G.I., Information technology issues for the attest, audit, and assurance services functions, The CPA Journal, 69, 5, pp. 62-63, (1999); Helms G.L., Lilly F.L., Case study on auditing in an electronic environment, The CPA Journal, 70, 4, pp. 52-54, (2000); Hermanson D.R., Callahan Hill M., Ivancevich D.M., Information technology-related activities of internal auditors, Journal of Information Systems, 14, 1, pp. 39-53, (2000); Hughes D.A., Assurance services issues, Australian CPA, 69, 9, pp. 36-38, (1999); Hunton J.E., Discussant's comments on presentations by John Lainhart and Gerald Trites, Journal of Information Systems, 14, 1, pp. 33-36, (2000); Hunton J.E., Benford T., Arnold V., Sutton S., The impact of electronic commerce assurance on financial analysts' earnings forecasts and stock price estimates, Auditing: A Journal of Practice & Theory, 19, pp. 5-23, (2000); Hussain M., The role of Pakistan's SAI in promoting good national governance, International Journal of Government Auditing, 28, 1, pp. 6-8, (2001); Larson R.K., Larson L.L., Coming to terms with international accounting standards, The Internal Auditor, 58, 1, pp. 42-47, (2001); Locatelli M., Good internal controls and auditor independence, The CPA Journal, 72, 10, pp. 12-15, (2002); McNamee D., Chan S., Understanding e-commerce risk, The Internal Auditor, 58, 2, pp. 60-61, (2001); McPhie D., AICPA/CICA SYSTRUST principles and criteria, Journal of Information Systems, 14, 1, (2000); Marche S., McNiven J.D., E-government and e-governance: The future isn't what it used to be, Canadian Journal of Administrative Sciences, 20, 1, pp. 74-86, (2003); Nearon B.H., Auditing e-business, The CPA Journal, 70, 11, pp. 22-27, (2000); Olson W.E., The accounting profession in the 20th century, The CPA Journal, 69, 7, pp. 28-33, (1999); Pentland B.T., Will auditors take over the world? Program, technique and the verification of everything, Accounting, Organizations and Society, 25, 3, pp. 307-312, (2000); Price J., Auditing e-business applications, The Internal Auditor, 58, 4, pp. 21-24, (2001); Primoff W.M., Electronic commerce and WebTrust, The CPA Journal, 68, 11, pp. 14-21, (1998); Ratliff R.L., Reding K.F., Introduction to Auditing: Logic, Principles, and Techniques, (2002); Rohleder S.J., Jupp V., eGovernment leadership: Engaging the customer, Online Accenture, (2003); Roussey R.S., The development of international standards on auditing, The CPA Journal, 69, 10, pp. 14-20, (1999); Salierno D., IFAC proposes new guidance, The Internal Auditor, 58, 6, pp. 16-17, (2001); Salmon E.R., Internal audit in government: Responding to changing demands, OPTIMUM: A Forum for Management, 19, 4, pp. 7-28, (1988); Sinclair G., Dodds R., Audit guidelines for e-commerce, Chartered Accountants Journal of New Zealand, 80, 1, (2001); Slyph J., Bennett C., The trust business: Assurance services and e-commerce, Australian Accountant, 68, 2, pp. 43-44, (1998); Street D.L., Large firms envision worldwide convergence of standards, Accounting Horizons, 16, 3, pp. 215-218, (2002); Tie R., IFAC: Firms to apply international standards consistently, Journal of Accountancy, 189, 4, (2000); History of internal audit in the federal government, (2003); Trites G., Overview of CICA's information technology control guidelines, Journal of Information Systems, 14, 1, (2000); von Solms R., Driving safely on the information superhighway, Asian Libraries, 6, 3-4, (1997); Building a Higher Quality of Life for All Canadians: Speech from the Throne to Open the Second Session of the Thirty-Sixth Parliament of Canada, (1999); Lainhart IV J.W., COBIT: A methodology for managing and controlling information and information technology risks and vulnerabilities, Journal of Information Systems, 14, 1, pp. 21-25, (2000); Lainhart IV J.W., An IT assurance framework for the future, Ohio CPA Journal, 60, 1, pp. 19-23, (2001); Stamp E., Moonitz M., International auditing standards: Part II, The CPA Journal, 52, pp. 48-53, (1982); Government online: Guiding principles, (2001)",{"$nulls":8},9513558.0,null,null,null,"English","Int. J. Public Sect. Manage.","Article","Final",null,"Scopus","2-s2.0-19944374793"]
["Carter C.R.; Kaufmann L.; Beall S.; Carter P.L.; Hendrick T.E.; Petersen K.J.","Carter, Craig R. (7403317396); Kaufmann, Lutz (8550014700); Beall, Stewart (7004118939); Carter, Phillip L. (7201989118); Hendrick, Thomas E. (6602328197); Petersen, Kenneth J. (7202488438)","7403317396; 8550014700; 7004118939; 7201989118; 6602328197; 7202488438","Reverse auctions--grounded theory from the buyer and supplier perspective",2004.0,"Transportation Research Part E: Logistics and Transportation Review",40.0,3.0,null,229.0,254.0,25.0,143.0,"10.1016/j.tre.2003.08.004","https://www.scopus.com/inward/record.uri?eid=2-s2.0-1542715879&doi=10.1016%2fj.tre.2003.08.004&partnerID=40&md5=6886c61e931a1219f970b1c759a46459","College of Business Administration, University of Nevada, Reno, NV 89557-0206, United States; Otto Beisheim Grad. Sch. of Mgmt., WHU, Vallendar/Koblenz D-56179, Germany; CAPS Research, Tempe, AZ 85285, United States; W.P. Carey School of Business, Arizona State University, Tempe, AZ 85287, United States","Carter C.R., College of Business Administration, University of Nevada, Reno, NV 89557-0206, United States; Kaufmann L., Otto Beisheim Grad. Sch. of Mgmt., WHU, Vallendar/Koblenz D-56179, Germany; Beall S., CAPS Research, Tempe, AZ 85285, United States; Carter P.L., W.P. Carey School of Business, Arizona State University, Tempe, AZ 85287, United States; Hendrick T.E., W.P. Carey School of Business, Arizona State University, Tempe, AZ 85287, United States; Petersen K.J., W.P. Carey School of Business, Arizona State University, Tempe, AZ 85287, United States","Supply chain relationships are increasingly impacted by the use of the Internet and the adoption of logistics technology. In this paper we report the results of a large-scale field study of a diverse group of buyers and their suppliers who have participated in a unique and recently adopted Internet technology: electronic reverse auctions (e-RAs). We examine the barriers to implementing e-RAs, as well as such consequences as cycle time and productivity. We also investigate the parameters that affect the savings that occur during a specific e-RA event, including lotting strategies and the degree of supplier visibility. © 2003 Published by Elsevier Ltd.","Case studies; E-commerce; Ethics; Negotiations; Reverse auctions; Supply chain management","logistics",{"$nulls":6},"Anon, Reverse auction should drive prices down, Purchasing, 127, 7, (1999); Atkinson W., Automotive firm likes e-Procurement but sees limits, Purchasing, 129, 5, (2000); Bargh J.A., Chen M., Burrows L., Automaticity of social behavior: Direct effects of trait construct and stereotype activation on action, Journal of Personality and Social Psychology, 71, 2, pp. 230-244, (1996); Battalio R.C., Kogut C.A., Meyer D.J., The effect of varying number of bidders in first-price private value auctions: An application of a dual market bidding technique, Advances in Behavioral Economics, 2, 50, (1990); Bonoma T., Case research in marketing: Opportunities, problems, and a process, Journal of Marketing Research, 22, 2, pp. 199-208, (1985); Bowersox D.J., Daugherty P.J., Droge C., Germain R., Rogers D.S., Logistical Excellence: It's Not Business As Usual, (1992); Brunelli M., Online auctions save millions for Quaker oats and Smithkline Beecham, Purchasing, 128, 4, (2000); Bulow J., Klemperer P., Auctions versus negotiations, The American Economic Review, 86, 1, pp. 180-194, (1996); Carter C.R., Ethical issues in international buyer-supplier relationships: A dyadic examination, Journal of Operations Management, 18, 2, pp. 191-208, (2000); Cavinato J.L., Evolving procurement organizations: Logistics implications, Journal of Business Logistics, 13, 1, pp. 27-45, (1992); Coppinger V.M., Smith V.L., Titus J.A., Incentives and behavior in english, dutch and sealed-bid auctions, Economic Inquiry, 18, 1, pp. 1-22, (1980); Cox J.C., Roberson B., Smith V.L., Theory and behavior of single object auctions, Research in Experimental Economics, (1982); Cox J.C., Smith V.L., Walker J.M., Theory and individual behavior of first-price auctions, Journal of Risk and Uncertainty, 1, 1, pp. 61-99, (1988); Coyle J.J., Bardi E.J., Langely C.J., The Management of Business Logistics, (2003); Cross G.J., How e-Business is transforming supply chain management, Journal of Business Strategy, pp. 36-39, (2000); de Saint-Seine S., Supplier groups criticize reverse auction abuses, Automotive News, 2, (2002); Daft R.L., Lengel R.H., Trevino L.K., Message equivocality, media selection, and manager performance: Implications for information systems, MIS Quarterly, 11, 3, pp. 355-366, (1987); Davies G.L., Entering the second generation of online reverse auctions, Inside Supply Management, 5, 6, (2002); Dawson R., Secrets of Power Persuasion, (1992); Drolet A.L., Morris M.W., Rapport in conflict resolution: Accounting for how nonverbal exchange fosters cooperation on mutually beneficial settlements to mixed-motive conflicts, Journal of Experimental Social Psychology, 36, 1, pp. 26-50, (2000); Dyer D., Kagel J.H., Levin D., Resolving uncertainty about the number of bidders in independent private-value auctions: An experimental analysis, Rand Journal of Economics, 20, 2, pp. 268-279, (1989); European Aluminum Foil Association, (2003); Eisenhardt K.M., Building theories from case study research, Academy of Management Review, 14, 4, pp. 532-550, (1989); Ellram L.M., The use of the case study method in logistics research, Journal of Business Logistics, 17, 2, pp. 93-139, (1996); Fisher R., Ury W., Patton B., Getting to Yes: Negotiating Agreement Without Giving In, (1991); Glaser B.G., Strauss A.L., The Discovery of Grounded Theory, (1967); Hong H., Shum M., Increasing competition and the Winner's curse: Evidence from procurement, Review of Economic Studies, 69, 4, pp. 871-898, (2002); Hong Y., Hartley J.L., An exploration of on-line reverse auctions as a procurement tool, The 12th Annual North American Research/Teaching Symposium on Purchasing and Supply Management, pp. 80-90, (2001); Jap S.D., Online reverse auctions: Issues, themes, and prospects for the future, Journal of the Academy of Marketing Science, 30, 4, pp. 506-525, (2002); Kagel J.H., Auctions: A survey of experimental research, The Handbook of Experimental Economics, (1995); Kagel J.H., Levin D., The Winner's curse and public information in common value auctions, American Economic Review, 76, 5, pp. 894-920, (1986); Kagel J.H., Levin D., Independent private value auctions: Bidder behavior in first-, second-, and third-price auctions with varying numbers of bidders, Economic Journal, 103, pp. 868-879, (1993); Kagel J.H., Levin D., Battalio R., Meyer D.J., First-price common value auctions: Bidder behavior and the Winner's curse, Economic Inquiry, 27, 2, pp. 241-258, (1989); Kagel J.H., Harstad R.M., Levin D., Information impact and allocation rules in auctions with affiliated private values: A laboratory study, Econometrica, 55, 6, pp. 1275-1304, (1987); Kenczyk M., Reverse auctions are risky models for buying custom parts, Machine Design, 73, 6, pp. 148-149, (2001); Kjerstad E., Vagstad S., Procurement auctions with entry bidders, International Journal of Industrial Organization, 18, pp. 1243-1257, (2000); Kuzel A.J., Sampling in qualitative inquiry, Doing Qualitative Research, pp. 31-44, (1992); LaLonde B.J., Preface, Journal of Business Logistics, 9, 2, (1988); Lambert D.R., Stock J.R., Strategic Logistics Management, (1993); Lewicki R.J., Robinson R.J., Ethical and unethical bargaining tactics: An empirical study, Journal of Business Ethics, 17, 6, pp. 665-682, (1998); Lincoln Y.S., Guba E.G., Naturalistic Inquiry, (1985); Luton R., McAfee R.P., Sequential procurement auctions, Journal of Public Economics, 31, pp. 181-195, (1986); Maddux R.B., Successful Negotiation: \"Win-Win\" Strategies and Tactics, (1988); Marshall C., Rossman G.B., Designing Qualitative Research, (1995); McAfee R.P., McMillan J., Auctions with a stochastic number of bidders, Journal of Economic Theory, 43, 1, pp. 1-19, (1987); McCracken G.D., The Long Interview, (1988); McGrath J.E., Dilemmatics: The study of research choices and dilemmas, Judgement Calls in Research, pp. 69-102, (1982); Meredith J., Building operations management theory through case and field research, Journal of Operations Management, 16, 4, pp. 441-454, (1998); Miles M.B., Huberman A.M., Qualitative Data Analysis, (1994); Milgrom P.R., Weber R.J., A theory of auctions and competitive bidding, Econometrica, 50, 5, pp. 1089-1122, (1982); Milgrom P., Auctions and bidding: A primer, Journal of Economic Perspectives, 3, 3, pp. 3-22, (1989); Miller W.L., Crabtree B.F., Primary care research: A multimethod typology and qualification road map, Doing Qualitative Research, (1992); Miyazaki A.D., Phillips J.K., Phillips D.M., Twenty years of JBL: An analysis of published research, Journal of Business Logistics, 20, 2, pp. 1-19, (1999); Original Equipment Suppliers Association of North America, (2003); Patton M.Q., Qualitative Evaluation Methods, (1990); Pearcy D.H., Larry C.G., Dandeo L.M., The impact of purchase type on the reverse auction process: A conceptual model, The 13th Annual North American Research/Teaching Symposium on Purchasing and Supply Management, pp. 327-346, (2002); Reingen P.H., Kernan J.B., Social perception and interpersonal influence: Some consequences of the physical attractiveness stereotype in a personal selling setting, Journal of Consumer Psychology, 2, 1, pp. 25-38, (1993); Riley J.G., Samuelson W.F., Optimal auctions, American Economic Review, 71, 3, pp. 381-392, (1981); Sparrowe R.T., Liden R.C., Wayne S.J., Kraimer M.L., Social networks and the performance of individuals and groups, Academy of Management Journal, 44, 2, pp. 316-325, (2001); Spradely J.P., The Ethnographic Interview, (1979); Strauss A.L., Qualitative Analysis for Social Scientists, (1987); Strauss A.L., Corbin J., Basics of Qualitative Research: Grounded Theory Procedures and Techniques, (1990); Stuhlmacher A.F., Gillespie T.L., Champagne M.V., The impact of time pressure in negotiation: A meta-analysis, International Journal of Conflict Management, 9, 2, pp. 97-116, (1998); Thompson L., Hastie R., Social perception in negotiation, Organizational Behavior and Human Decision Processes, 47, 1, pp. 98-123, (1990); Vickrey W., Counterspeculation, auctions, and competitive sealed tenders, Journal of Finance, 16, 1, pp. 8-37, (1961); Vyas N., Woodside A.G., An inductive model of industrial supplier choice processes, Journal of Marketing, 48, 1, pp. 30-45, (1984); Wang R., Bidding and renegotiation in procurement auctions, European Economic Review, 44, pp. 1577-1597, (2000); Weller S.C., Romney A.K., Systematic Data Collection, (1988); Yin R.K., Applications of Case Study Research, (1991); Yin R.K., Case Study Research, (1994)","C.R. Carter; College of Business Administration, University of Nevada, Reno, NV 89557-0206, United States; email: crcarter@unr.edu",null,"Elsevier Ltd",{"$nulls":5},1.3665545E7,null,null,null,"English","Transp. Res. Part E Logist. Transp. Rev.","Article","Final",null,"Scopus","2-s2.0-1542715879"]
["Kwok S.H.; Yang C.C.","Kwok, Sai Ho (7103139583); Yang, Christopher C. (7407740308)","7103139583; 7407740308","Copyright protection schemes for on-line media distribution E-services",2003.0,"International Journal of Electronic Commerce",8.0,2.0,null,119.0,138.0,19.0,4.0,"10.1080/10864415.2003.11044296","https://www.scopus.com/inward/record.uri?eid=2-s2.0-1342290267&doi=10.1080%2f10864415.2003.11044296&partnerID=40&md5=5ae7bada2c3588f650f332809d54463d","Department of Information and Systems Management, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong; Dept. of Systems Eng. and Eng. Mgmt., Chinese University of Hong Kong, Shatin, NT, Hong Kong","Kwok S.H., Department of Information and Systems Management, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong; Yang C.C., Dept. of Systems Eng. and Eng. Mgmt., Chinese University of Hong Kong, Shatin, NT, Hong Kong","Copyright protection is a necessity for on-line media distribution e-services. Watermarking technology enables copyright protection for e-services but delays the packaging process and delivery. Instant delivery is a primary requirement for on-line businesses. The imperceptibility and robustness of watermarking has been studied extensively, but its impact on the performance of e-services, such as deferring delivery and requiring extra storage, has not yet been addressed. This paper investigates four watermarking schemes based on one-bit watermarking, multiple-bit watermarking, and their combinations, and explores such performance issues as preparation time, delivery time, and storage requirements. The paper derives equations that describe the performance of watermarking schemes. It proves that schemes with multiple-bit watermarking can ensure instant delivery with the penalty of some extra storage requirements in the on-line media e-service setup. © 2004 M.E. Sharpe, Inc. All rights reserved.","Copyright protection; Digital watermaking; Electronic service; Media distribution; On-line business; On-line service; Watermarking","e-commerce; goods exchange; media industry",{"$nulls":4},"Research Grants Council, University Grants Committee, RGC, UGC, (DAG01/02)","This research was supported in part by the Innovation and Technology Support Programme (AF/168/99), the Hong Kong Research Grants Council through a Direct Allocation Grant (DAG01/02.BM16), and a Sino Software Research Institute (SSRI01/02.BM01).","Cormen T.H., Leiserson C.E., Rivest R.L., Introduction to Algorithms, (1990); Cox I.J., Kilian J., Leighton F.T., Shamoon T., Secure spread spectrum watermarking for multimedia, IEEE Transactions of Image Processing, 6, 12, pp. 1673-1687, (1997); Craver S., Memon N., Yeo B.L., Yeung M., Can Invisible Watermarks Resolve Rightful Ownership?, (1996); Deguillaume F., Csurka G., O'Ruanaidh J., Pun T., Robust 3D DFT video watermarking, SPIE: International Society for Optical Engineering Proceedings, pp. 113-124, (1999); Doherty S., Managing your digital rights, Network Computing, 13, 19, pp. 65-68, (2002); Fridrich J., Goljan M., Comparing robustness of watermarking techniques, SPIE: International Society for Optical Engineering Proceedings, pp. 214-225; George M., Chouinard J.V., Georganas N., Digital watermarking of images and video using direct sequence spread spectrum techniques, IEEE Canadian Conference on Electrical and Computer Engineering, 1, pp. 116-121, (1999); Gibeaut J., Zapping cyber piracy, ABA Journal, 83, pp. 60-63, (1997); Hartung F., Girod B., Watermarking of uncompressed and compressed video, Signal Processing, 66, 3, pp. 283-301, (1998); Kutter M., Watermarking resistance to translation, rotation, and scaling, SPIE: International Society for Optical Engineering Proceedings, pp. 423-431, (1999); Kwok S.H., Digital rights management for online music business, ACM SIGecom Exchanges, 3, 3, pp. 17-24, (2002); Kwok S.H., Hybrid audio watermarking for copyright protection, Proceedings of the Sixth Pacific Asia Conference on Information Systems, pp. 1038-1042, (2002); Kwok S.H., Watermark-based copyright protection system system security, Communications of the ACM, 46, 10, pp. 98-101, (2003); Kwok S.H., Cheung S.C., Wong K.C., Tsang K.F., Lui S.M., Tam K.Y., Integration of digital rights management into Internet open trading protocol (IOTP), Decision Support Systems, 34, 4, pp. 413-425, (2003); Kwok S.H., Lui S.M., A license management model for peer-to-peer music sharing special issue on virtual organizations and E-Commerce applications, International Journal of Information Technology and Decision Making, 1, 3, pp. 541-558, (2002); Kwok S.H., Yang C.C., Watermarking in online media e-business, Proceedings of the International Conference on Information Technology: Coding and Computing, pp. 158-163, (2002); Kwok S.H., Yang C.C., Tam K.Y., Watermark design pattern for intellectual property protection in electronic commerce applications, Proceedings of the Thirty-third Annual Hawaii International Conference on System Sciences, pp. 2020-2029, (2000); Kwok S.H., Yang C.C., Tam K.Y., Wong J.S.W., An SDMI-based rights management system for electronic media using digital watermarking, Proceedings of the International Conference on Electronic Commerce, pp. 193-200, (2000); Lintain Q., Nahrstedt K., Non-invertible watermarking methods for MPEG encoded audio, SPIE: International Society for Optical Engineering Proceedings, pp. 194-202; Memon N., Wong P.W., Protecting digital media content, Communications of the ACM, 41, 7, pp. 35-43, (1998); O'Ruanaidh J.J.K., Pun T., Rotation, scale and translation invariant digital image watermarking, International Conference on Image Processing, pp. 536-539, (1997); Piron L., Arnold M., Kutter M., Funk W., Boucqueau J.M., Craven F., OCTALIS benchmarking: Comparison of four watermarking techniques, SPIE: International Society for Optical Engineering Proceedings, pp. 240-250, (1999); Piva A., Barni M., Bartolini F., Cappellini V., DCT-based watermark recovering without resorting to the uncorrupted original image, International Conference on Image Processing, pp. 520-523, (1997); Wayner P., Protecting your property in cyberspace, Computerworld, 34, 2, pp. 68-69, (2000); Zhao J., Koch E., Embedding robust labels into images for copyright protection, Intellectual Property Rights and New Technologies: Proceedings of the KnowRight'95 Conference, pp. 242-251, (1995)","S.H. Kwok; Dept. of Information/Systems Mgmt., Hong Kong Univ. of Sci./Technology, Claer Water Bay, Kowloon, Hong Kong; email: jkwok@ust.hk",null,"M.E. Sharpe Inc.",{"$nulls":5},1.0864415E7,null,null,null,"English","Int. J. Elect. Commer.","Article","Final",null,"Scopus","2-s2.0-1342290267"]
["Beyers W.B.","Beyers, William B. (36896204600)",3.68962046E10,"Impacts of IT advances and E-commerce on transportation in producer services",2003.0,"Growth and Change",34.0,4.0,null,433.0,455.0,22.0,11.0,"10.1046/j.0017-4815.2003.00229.x","https://www.scopus.com/inward/record.uri?eid=2-s2.0-0347594805&doi=10.1046%2fj.0017-4815.2003.00229.x&partnerID=40&md5=9666221f711ef13b027668de91a7de45","University of Washington, Seattle, WA, United States","Beyers W.B., University of Washington, Seattle, WA, United States","Producer services have been among the most rapidly growing industries, as measured by employment, in the United States and in Europe in recent decades. The production and delivery of these specialized forms of service industry work require the use of transportation and communications systems in a variety of ways, including the physical movement of people working in these industries, as well as the movement of the information related to the production and distribution of their work. Some of this work is performed in localized markets, requiring travel between clients and suppliers in local transportation modes, such as auto, bus, or other types of transportation. Other work is done by specialists who travel interregionally and globally to do their work, primarily traveling to their clients. There is little knowledge of how these production relationships have changed with the advent of the Internet and the widespread use of e-mail in the business production process. Within the framework of this STELLA initiative. this paper outlines research needs in this area, and frames an approach that would produce badly needed knowledge about impacts on the producer services of the Internet and related e-commerce initiatives on physical transportation systems at a local to interregional scale.",null,"e-commerce; employment; information technology; service sector; transportation economics",{"$nulls":6},"Ansoff H.I., Corporate Strategy: an Analytic Approach to Business Policy for Growth and Expansion, (1965); Bancel-Charensol L., Impacts on information and communication technologies on service production systems, The Service Industries Journal, 19, pp. 147-157, (1999); Bennett R.J., Bratton W.A., Robson P., Business advice: The influence of distance, Regional Studies, 34, pp. 813-828, (2000); Bennett R.J., Smith C., The influence of location and distance on the supply of business advice, Environment and Planning A, 34, pp. 251-270, (2002); Beyers W., Cyberspace or human space: Wither cities in the age of telecommunications?, Cities in the Telecommunications Age: The Fracturing of Geographies, (2000); Beyers W.B., Lindahl D.P., Explaining the demand for producer services: Is cost-driven externalization the major factor?, Papers in Regional Science, 75, pp. 351-374, (1996); Beyers W.B., Lindahl D.P., Lone eagles and high fliers in rural producer services, Rural Development Perspectives, 12, pp. 2-10, (1996); Beyers W.B., Lindahl D.P., Workplace flexibilities in the producer services, The Service Industries Journal, 19, pp. 35-60, (1999); Bryson J.R., Services and internationalisation: Annual report on the progress of research into service activities in Europe in 1998, The Service Industries Journal, 21, 1, pp. 227-240, (2001); Button K., Taylor S., Towards an economics of the internet and e-commerce, Worlds of E-Commerce: Economic, Geographical and Social Dimensions, (2001); Cairncross F., The Death of Distance. How the Communications Revolution Will Change Our Lives, (1997); Coe N.M., The externalisation of producer services debate: The UK computer services sector, The Service Industries Journal, 20, pp. 64-81, (2000); Coffey W.J., Drolet R., Make or buy?: Internalization and externalization of producer service inputs in the Montreal Metropolitan area, Canadian Journal of Regional Science, 29, pp. 25-48, (1996); Cooke S.D., Jobs in the new economy, Digital Economy 2002, (2002); The Emerging Digital Economy, (1998); The Emerging Digital Economy II, (1999); Digital Economy 2000, (2000); Digital Economy 2002, (2002); Freel M., External unkages and product development in small manufacturing firms, Entrepreneurship and Regional Development, 12, pp. 245-266, (2000); Harrison B., Lean and Mean. The Changing Landscape of Corporate Power in the Age of Flexibility, (1994); Illeris S., The Service Economy. A Geographical Approach, (1996); Leinbach T.R., Emergence of the digital economy and e-commerce, Worlds of E-commerce: Economic, Geographical and Social Dimensions, (2001); Leinbach T.R., Bowen Jr. J.T., Lepawsky J., Air cargo services and the electronics industry in Southeast Asia: Towards a demand based typology, AAG Meetings, (2002); Li F., Whalley J., Williams H., Between physical and electronic spaces: The implications for organisations in the networked economy, Environment and Planning A, 33, pp. 699-716, (2001); Lindahl D.P., Beyers W.B., The creation of competitive advantage by producer service firms, Economic Geography, 75, pp. 1-20, (1999); Ochel W., Wegner M., Service Economies in Europe. Opportunities for Growth, (1987); O'Conner K., Daniels P.W., The geography of international trade in services: Australia and the APEC region, Environment and Planning A, 33, pp. 281-296, (2001); O'Farrell P., Wood P., Zheng J., Regional influences on foreign market development by business service companies: Elements of a strategic context explanation, Regional Studies, 32, pp. 31-48, (1998); Porter M.E., The Competitive Advantage of Nations, (1990); Rubalcaba-Bermejo L., Business Services in European Industry: Growth, Employment and Competitiveness, (1999); Scott A.J., Metropolis. From the Division of Labor to Urban Form, (1988); Storey C., Kelly D., Measuring the performance of new service development activities, The Service Industries Journal, 21, 2, pp. 71-90, (2001); 2001 E-commerce Multi-Sector Data Tables, (2003); Vilhelmson B., Thulin E., Is regular work at fixed places facing away? The development of ICT-based and travel-based modes of work in Sweden, Environment and Planning A, 33, pp. 1015-1029, (2001); Yeh A., The Hong Kong - Pearl River Delta Producer Services Linkages. Service Industries and New Models of Urban Change Within the Asia-Pacific Region, (2002)","W.B. Beyers; University of Washington, Seattle, WA, United States; email: beyers@u.washington.edu",{"$nulls":7},174815.0,null,null,null,"English","Growth Change","Article","Final",null,"Scopus","2-s2.0-0347594805"]
["Chang P.-L.; Chien C.-F.","Chang, Pao-Long (7403573310); Chien, Chen-Fu (57219656467)","7403573310; 57219656467","Managing technologies to enhance and enrich services in high-tech industry",2003.0,"International Journal of Services, Technology and Management",4.0,"2024-06-04",null,323.0,330.0,7.0,3.0,"10.1504/ijstm.2003.003618","https://www.scopus.com/inward/record.uri?eid=2-s2.0-0345357667&doi=10.1504%2fijstm.2003.003618&partnerID=40&md5=fc852277c45bc23bbf43e4253f5a9dd7","Department of Business Admin., Feng Chia University, Seatwen, Taichung, 100 Wenhwa Rd., Taiwan; Dept. of Indust. Eng. and Eng. Mgmt., National Tsing Hua University, Hsinchu 30013, Taiwan","Chang P.-L., Department of Business Admin., Feng Chia University, Seatwen, Taichung, 100 Wenhwa Rd., Taiwan; Chien C.-F., Dept. of Indust. Eng. and Eng. Mgmt., National Tsing Hua University, Hsinchu 30013, Taiwan","New information technologies and business models have had a profound effect on how services are created and delivered, in particular with regard to the innovation, contents, delivery methods, systems, enabling technologies and management. This special issue of the International Journal of Services Technology and Management (IJSTM) focuses on all aspects of managing the hard and soft technologies to enhance and enrich services in high-tech industries, e.g., semiconductor manufacturing. This introduction gives an overview of this special issue from different perspectives.","E-commerce; High-tech industry; Service technology management; Supply chain management","Electronic commerce; Electronics industry; Information technology; Semiconductor device manufacture; Technology transfer; High technology industry; Service technology management; Supply chain management; Industrial management",{"$nulls":6},"Zhang Q., Cao M., Human-machine web interface design for electronic commerce: A review of design perspective, objectives, dimensions, and techniques, International Journal of Services Technology and Management, (2002); Shi Y., Gregory M., From original equipment manufacturers to total solution providers: An emergence of global manufacturing virtual network in the electronics industry, International Journal of Services Technology and Management, (2002); Chien C., Hsu S., Deng J., A cutting algorithm for optimising the wafer exposure pattern, IEEE Transactions on Semiconductor Manufacturing, 14, 2, pp. 157-162, (2001); Chen T., Chang P., Lin C., An agent-based framework for information exchange in semiconductor supply chains, International Journal of Services Technology and Management, (2002); Peng C., Chien C., Data value development to enhance competitive advantage: A retrospective study of EDA system for semiconductor fabrication, International Journal of Services Technology and Management, (2002); Jiao J., Ma Q., Lee A.C.G., Chin K.M., Chang C.S., BPR-based information systems planning for e-logistics: A case study, International Journal of Services Technology and Management, (2002); Dabbas R.M., Chen H., Factory shutdown: A managerial approach', international technologies to enhance the services in high-tech industry, Journal of Services Technology and Management, (2002); Hou J., Trappey C.V., Trappey A.J.C., Enabling centralised enterprise knowledge management services for the technology value chain, International Journal of Services Technology and Management, (2002); Chen R., He F., Using brand knowledge to understand consumer's intention to adopt an online retailer, International Journal of Services Technology and Management, (2002); Rau P.P., Liang S.M., A study of cultural effects on designing user interface design in web-based electronic hub, International Journal of Services Technology and Management, (2002); Roztocki N., The integrated activity-based costing and economic value added system for the service sector, International Journal of Services Technology and Management, (2002); Holmes S.C., Miller R., The strategic role of e-commerce in the supply chain of the health care industry, International Journal of Services Technology and Management, (2002); Selen W., A collaborative commerce framework for the real estate industry, International Journal of Services Technology and Management, (2002); Scott J.P., Rishel T.D., Stenger A.J., Managing information in the supply chain to enhance customer service and build relationships, International Journal of Services Technology and Management, (2002); Chan C., Chen C., Usage pattern of web-based system for cellular phone purchasing, International Journal of Services Technology and Management, (2002); Huang X., Research to Australian e-retailers: Strategic issues, success factors, and challenges, International Journal of Services Technology and Management, (2002)","P.-L. Chang; Department of Business Admin., Feng Chia University, Seatwen, Taichung, 100 Wenhwa Rd., Taiwan; email: paolong@cc.nctu.edu.tw",null,"Inderscience Publishers",{"$nulls":5},1.460672E7,null,null,null,"English","Int. J. Serv. Technol. Manage.","Article","Final",null,"Scopus","2-s2.0-0345357667"]
["Yang J.-Z.; Shi Q.-L.; Millar G.; Sarker R.A.","Yang, Jian-Zheng (35732607200); Shi, Qi-Liang (8435511100); Millar, Gary (57225380461); Sarker, Ruhul A. (57214204734)","35732607200; 8435511100; 57225380461; 57214204734","Risk analysis and consumer protection in B2C transactions",2005.0,"Journal of Dong Hua University (English Edition)",22.0,1.0,null,83.0,89.0,6.0,0.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-20144384846&partnerID=40&md5=c901c9b49a20bb7131696418d9f4de86","Business School, University of Shanghai for Science and Technology, Shanghai 200031, China; Glorious Sun School of Business and Management, Donghua University, Shanghai 200051, China; School of Computer Science, The University of New South Wales, Australia","Yang J.-Z., Business School, University of Shanghai for Science and Technology, Shanghai 200031, China, Glorious Sun School of Business and Management, Donghua University, Shanghai 200051, China; Shi Q.-L., Business School, University of Shanghai for Science and Technology, Shanghai 200031, China; Millar G., School of Computer Science, The University of New South Wales, Australia; Sarker R.A., School of Computer Science, The University of New South Wales, Australia","Recent studies have shown that the perceived lack of security is a major obstacle to the wider acceptance of e-commerce. To overcome this barrier, businesses need to implement comprehensive consumer protection systems that protect consumers during every stage of the purchasing process. This paper used the consumer behaviour model as the basis for analyzing risks in Bussiness-to-Consumer (B2C) transactions. Four categories of risks were identified: information, agreement, payment and delivery risk. By combining these risk categories with the three dimensions of management, technology and legislation, a comprehensive B2C consumer protection framework is developed.","Business-to-Consumer; Consumer protection","Risk assessment; Security of data; Three dimensional; B2C consumer protection framework; B2C transactions; Business to Consumer; Consumer protection; Risk categories; Electronic commerce",{"$nulls":6},"Hoffman, Lance J., Risk analysis and computer security: Bridging the cultural gaps, The 9th National Computer Security Conference, (1986); Jung C., Han I., Suh B., Risk analysis for EC using case-based reasoning, Int. J. Intell. Sys. Ace. Fin. Mgmt 8, pp. 61-73, (1999); Wat F.K.T., Ngai E.W.T., Risk analysis in EC development using fuzzy set, IFSA World Congress and 20th NAFIPS International Conference, 2, pp. 807-811, (2001); Mosoove S.A., E-business security and controls, The CPA Journal, pp. 40-46, (2001); King D., Lee J., Warkentin M., EC 2002: A Managerial Perspective, pp. 129-127, (2002); Wu W., China's fledgling B2C in crisis, (2001); Yu L., Xu S., The First Judgment of China First Web Site Bring an Accusation Against Net Customer to an End in Shanghai, (2002); (2003); Self-regulatory principles for online preference marketing by network advertisers, (2002); (2002); The Standard for Information Security Management, (2002); Electronic Mail Advertising Bill 2001, (2003); Anti-Spamming Act of 2001 (H. R. 718), (2003); Electronic Freedom of Information Act Amendments of 1996, (2002); New Zealand Model Code for Consumer Protection in EC, (2002); Identity Theft and Assumption Deterrence Act, (2002); UNCITRAL Model Law on EC with Guide to Enactment (1996), (2002); Model Law on Electronic Signatures of the United Nations Commission on International Trade Law, (2003); Council Definitively Adopts Directive on Protection of Personal Data, (2002); Privacy Act 1988, (2003); Gramm-Leach-Bliley Act, (2003); The Law of the People's Republic of China on Products Quality, (2003); Law of the People's Republic of China on Protecting Consumers' Rights and Interests, (2002)","J.-Z. Yang; Business School, University of Shanghai for Science and Technology, Shanghai 200031, China; email: yangjz@citiz.net",{"$nulls":9},"JCTUE",null,"English","J. Dong Hua Univ.","Article","Final",null,"Scopus","2-s2.0-20144384846"]
["Boyer K.K.","Boyer, Kenneth K. (35512115800)",3.55121158E10,"Customer behavior in an online ordering application: A decision scoring model",2005.0,"Decision Sciences",36.0,4.0,null,569.0,598.0,29.0,85.0,"10.1111/j.1540-5414.2005.00103.x","https://www.scopus.com/inward/record.uri?eid=2-s2.0-33745297733&doi=10.1111%2fj.1540-5414.2005.00103.x&partnerID=40&md5=b2de654040c694e3731bbbeff0ffbf98","Eli Broad Graduate School of Management, Michigan State University, East Lansing, MI 48824-1122, United States; Department of Supply Chain Management, Michigan State University, United States","Boyer K.K., Eli Broad Graduate School of Management, Michigan State University, East Lansing, MI 48824-1122, United States, Department of Supply Chain Management, Michigan State University, United States","This research presents the development of behavioral scoring models to predict future customer purchases in an online ordering application. Internet retailing lowers many barriers for customers switching between retailers for repeat purchases; thus, retaining existing customers is a key challenge for achieving profitability. Survey data were collected from 1,089 online customers of two companies. The subjective survey data were then used to predict purchases over the ensuing 12 months based on data from the company databases. The analysis illustrates the general applicability of predictive models of future customer purchases while also demonstrating the need to develop specific models tailored for an individual company's operating and marketing environment. The models provide insight on how companies can target marketing dollars more effectively and allocate investment across multiple operational areas for maximum return. The research answers a call for rigorous research in the area of predictive marketing, an area in which many companies are excelling but where there is a scarcity of detailed knowledge regarding application of such models. © 2005, Decision Sciences Institute.","E-Commerce; Grocery Home Delivery; Internet Ordering; Longitudinal Research; Order Fulfillment; Service Quality",{"$nulls":7},"Agarwal R., Prasad J., Are individual differences germane to the acceptance of new information technologies?, Decision Sciences, 30, 2, pp. 361-391, (1999); Alreck P.L., Settle R.B., The hurried consumer: Time-saving perceptions of Internet and catalogue shopping, Journal of Database Marketing, 10, 1, pp. 25-35, (2002); Anderson J.C., Gerbing D.W., Some methods for respecifying measurement models to obtain unidimensional construct measurement, Journal of Marketing Research, 19, 4, pp. 453-460, (1982); Armstrong J.S., Overton T.S., Estimating nonresponse bias in mail surveys, Journal of Marketing Research, 14, 3, pp. 396-402, (1977); Baertlein L., Late surge boosts holiday Internet sales, USA Today, (2004); Baesens B., Van Gestel T., Viaene S., Stepanova M., Suykens J., Vanthienen J., Benchmarking state-of-the-art classification algorithms for credit scoring, The Journal of the Operational Research Society, 54, 6, pp. 627-635, (2003); Bagozzi R.P., Phillips L.W., Representing and testing organizational theories: A holistic construal, Administrative Science Quarterly, 27, 3, pp. 459-489, (1982); Bakos J.Y., Reducing buyer search costs: Implications for electronic marketplaces, Management Science, 43, 12, pp. 1676-1692, (1997); Bellman S., Lohse G.L., Johnson E.J., Predictors of online buying behavior, Communications of the Association for Computing Machinery, 42, 12, pp. 32-38, (1999); Bhatnagar A., Misra S., Rao H.R., On risk, convenience, and Internet shopping behavior, Communications of the Association for Computing Machinery, 43, 11, pp. 98-105, (2000); Bodapati A., Gupta S., A direct approach to predicting discretized response in target marketing, Journal of Marketing Research, 41, 1, pp. 73-85, (2004); Bolton R.N., Lemon K.N., Verhoef P.C., The theoretical underpinnings of customer asset management: A framework and propositions for future research, Journal of the Academy of Marketing Science, 32, 3, pp. 271-292, (2004); Boulding W., Kalra A., Staelin R., The quality double whammy, Marketing Science, 18, 4, pp. 463-484, (1999); Boyer K.K., Olson J.R., Drivers of Internet purchasing, Production and Operations Management, 11, 4, pp. 180-198, (2002); Boyer K.K., Frohlich M., Huit G.T.M., Extending the Supply Chain: How Cutting-edge Companies Bridge the Critical Last Mile into Customers' Homes, (2005); Brucks M., Zeithaml V.A., Naylor G., Price and brand name as indicators of quality dimensions for consumer durables, Journal of the Academy of Marketing Science, 28, 3, pp. 359-374, (2000); Brynjolfsson E., Smith M.D., Frictionless commerce? 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Boyer; Eli Broad Graduate School of Management, Michigan State University, East Lansing, MI 48824-1122, United States; email: boyerk@msu.edu",null,"Blackwell Publishing Ltd",{"$nulls":5},117315.0,null,null,null,"English","Decis. Sci.","Article","Final",null,"Scopus","2-s2.0-33745297733"]
["Liu J.; You J.","Liu, James (55851927700); You, Jane (7201682787)","55851927700; 7201682787","Smart shopper: An agent-based Web-mining approach to Internet shopping",2003.0,"IEEE Transactions on Fuzzy Systems",11.0,2.0,null,226.0,237.0,11.0,24.0,"10.1109/TFUZZ.2003.809900","https://www.scopus.com/inward/record.uri?eid=2-s2.0-0037389186&doi=10.1109%2fTFUZZ.2003.809900&partnerID=40&md5=581b03ee6ca193aa9ce186ee71b68145","Department of Computing, Hong Kong Polytechnic University, Kowloon, Hong Kong","Liu J., Department of Computing, Hong Kong Polytechnic University, Kowloon, Hong Kong; You J., Department of Computing, Hong Kong Polytechnic University, Kowloon, Hong Kong","With the rapid development of e-commerce, there is an immediate need for an autonomous and robust system that can offer decision-making support for customers who are looking for the cheapest, the most familiar, or the best-quality product. This paper presents an agent-based web-mining approach to Internet shopping. In contrast to the traditional multiagent systems, which use rule-based or case-based process flows to coordinate communications for system automation, we propose a fuzzy neural network to tackle the uncertainties in practical shopping activities, such as consumer preferences, product specification, product selection, price negotiation, purchase, delivery, after-sales service and evaluation. The fuzzy neural network provides an automatic and autonomous product classification and selection scheme to support fuzzy decision making by integrating fuzzy logic technology and the back propagation feed forward neural network. In addition, a new visual data model is introduced to overcome the limitations of the current web browsers that lack flexibility for customers to view products from different perspectives. Such a model also extends the conventional data warehouse schema to deal with intensive data volumes and complex transformations with a high degree of flexibility for multiperspective visualization and morphing capability in an interactive environment. Furthermore, an agent development tool named \"Aglet\" is used as a programming framework for system implementation. The integration of dynamic object visualization, interactive user interface and data mining decision support provides an effective technique to close the gap between the \"real world\" and the \"cyber world\" from a business perspective. The experimental results demonstrate the feasibility of the proposed approach for web-based business transactions.","Feature selection; Fuzzy neural network; Internet shopping; Multiagent; Web-mining","Data mining; Data warehouses; Decision making; Electronic commerce; Feedforward neural networks; Interactive computer systems; Multi agent systems; Web browsers; Internet shopping; Internet",{"$nulls":4},"Hong Kong Polytechnic University, PolyU, (G-T375, H-ZJ87)","Manuscript received December 30, 2000; revised October 7, 2002. This work was supported in part by the the Hong Kong Polytechnic University under University Research Grant G-T375 and under Department Research Grant H-ZJ87. The authors are with the Department of Computing, The Hong Kong Polytechnic University, Kowloon, Hong Kong (e-mail: csnkliu@comp.polyu. edu.hk). Digital Object Identifier 10.1109/TFUZZ.2003.809900","Ames A.L., Nadeau D.R., Moreland J.L., The VRML 2.0 Sourcebook, 2nd Ed., (1997); Anahory S., Murray D., Data Warehousing in the Real World - A Practical Guide for Building Decision Support Systems, (1997); Bettman J., An Information Processing Theory to Consumer Choice, (1979); Blake A., Isard M., Active Contours, (1998); Caelli T.M., Reye D., On the classification of image regions by color, texture and shape, Pattern Recognit., 26, 4, pp. 461-470, (1993); Cohen F.S., Huang Z., Yang Z., Invariant matching and identification of curves using B-splines curve representation, IEEE Trans. Image Processing, 4, pp. 1-10, (1995); Cootes T., Taylor C., Lanitis A., Cooper D., Graham J., Building and using flexible models incorporating grey-level information, Proc. 4th Int. Conf. Computer Vision, pp. 242-246, (1993); Dasgupta P., Narasimhan N., Moser L.E., Smith P.M., MAGNET: Mobile agents for networked electronic trading, IEEE Trans. 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["Zekos G.","Zekos, Georgios (6506079167)",6.506079167E9,"Foreign direct investment in a digital economy",2005.0,"European Business Review",17.0,1.0,null,52.0,68.0,16.0,13.0,"10.1108/09555340510576267","https://www.scopus.com/inward/record.uri?eid=2-s2.0-18844402643&doi=10.1108%2f09555340510576267&partnerID=40&md5=7266fb5fc882a198d0399ba0d4d276de","Attorney at Law and Economist, Komotini, Greece","Zekos G., Attorney at Law and Economist, Komotini, Greece","Purpose - The analysis of the role of foreign direct investment (FDI) in the emergence and development of digital economy. Design/methodology/approach - Examination of the developments of FDI and the new destinations explained by the liberalization measures undertaken by governments and inward investment agencies in globalization. Findings - While FDI does displace some exports, it also creates a number of reverse imports. Companies are forced to improve their managerial efficiency. The elimination of internal barriers to trade and capital mobility has been accompanied by a rapid growth of multinational enterprises (MNEs) in EU. Originality/value - The development of e-MNEs will bring different utilization of the production plants and use of logistics to distribute tangible goods, while intangible goods will be distributed by very advanced technology centres based on home locations. The digital economy should not be confined just to e-business and e-commerce. © Emerald Group Publishing Limited.","Electronic commerce; International economics; International investments; Multinational companies",{"$nulls":7},"Abbate J., Inventing the Internet, (1999); Ahn S., Hemmings P., Policy Influence on Economic Growth in OECD Countries: An Evaluation of the Evidence, (2000); Almeida P., Knowledge sourcing by foreign multinationals: Patent citation analysis in the US semiconductor industry, Strategic Management Journal, 17, pp. 155-165, (1996); Antonelli C., The Microeconomics of Technological Systems, (2001); Antonelli C., The digital divide: Understanding the economics of new information and communication technology in the global economy, Information Economics and Policy, 15, 2, pp. 173-199, (2003); Aristotelous K., Fountas S., An empirical analysis of inward foreign direct investment flows in the EU with emphasis on the market enlargement hypothesis, Journal of Common Market Studies, 34, pp. 571-583, (1996); 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Bus. Rev.","Article","Final",null,"Scopus","2-s2.0-18844402643"]
["Murphy A.J.","Murphy, Andrew J. (18434848000)",1.8434848E10,"(Re)solving space and time: Fulfilment issues in online grocery retailing",2003.0,"Environment and Planning A",35.0,7.0,null,1173.0,1200.0,27.0,42.0,"10.1068/a35102","https://www.scopus.com/inward/record.uri?eid=2-s2.0-0042388631&doi=10.1068%2fa35102&partnerID=40&md5=d6f0a4b1f178fef135467c2187fb0579","School of Geogr. Earth/Environ. Sci., University of Birmingham, Edgbaston, Birmingham B15 2TT, United Kingdom; Department of Geography, University of British Columbia, Vancouver, BC V6T 1Z2, 1984 West Mall, Canada","Murphy A.J., School of Geogr. Earth/Environ. Sci., University of Birmingham, Edgbaston, Birmingham B15 2TT, United Kingdom, Department of Geography, University of British Columbia, Vancouver, BC V6T 1Z2, 1984 West Mall, Canada","There has been much hype and speculation in the media and in academe on the vitality and future of the 'Internet economy'. In this paper the author uses case studies from Britain, Canada, New Zealand and the United States to assess the strengths and weaknesses of online grocery retailers, from national chain stores pursuing a 'bricks and clicks' strategy to 'pure-play' startups. He argues that delivering groceries via the Internet to customer doorsteps requires ways of solving space and time that are markedly different from previous trends in food retail logistics. He holds that solving problems of space management creates problems in the management of time and vice versa. In particular, 'e-tailers' struggle with fulfilment costs and logistics, and have attempted to manage customers' time and locations to reduce these costs. Store-based operations may be best suited for short-term profitability (or loss minimisation), whereas warehouse-based fulfilment may hold future promise of greater efficiency and flexibility. The author suggests that online organic home delivery may be the most successful type of online food retailer, for its size, given greater customer commitment and problems with store-based supply of organic food.",null,"Canada; New Zealand; United Kingdom; United States; e-commerce; Internet; retailing",{"$nulls":6},"Abernathy F., Dunlop J., Hammond J., Weil D., Retailing and supply chains in the information age, Technology and Society, 22, pp. 5-31, (2000); Anders G., Will net grocery shopping ever take off?, Wall Street Journal Interactive, (1999); Aoyama Y., The information society, Japanese style: Corner stores as hubs for e-commerce access, Worlds of E-commerce: Economic, Geographical and Social Dimensions, pp. 109-128, (2001); Aoyama Y., Structural foundations for e-commerce adoption: A comparative organization of retail trade between Japan and the United States, Urban Geography, 22, pp. 130-153, (2001); Batty M., The world wide web, Environment and Planning B: Planning and Design, 21, pp. 651-652, (1994); Batty M., The retail revolution, Environment and Planning B: Planning and Design, 24, pp. 1-2, (1997); Beamon B., Supply chain design and analysis: Models and methods, International Journal of Production Economics, 55, pp. 281-294, (1998); Bennison D., Domestic viewdata services in Britain: Past experience, present status, and future potential, Environment and Planning B: Planning and Design, 12, pp. 151-164, (1985); Birkin M., Clarke G., Clarke M., Retail Geography and Intelligent Network Planning, (2002); Bromley R., Thomas C., The retail revolution, the carless shopper and disadvantage, Transactions of the Institute of British Geographers: New Series, 18, pp. 222-236, (1993); Caicco P., The Green Mile Digest 2001, (2001); Cairncross F., The Death of Distance: How the Communications Revolution Will Change Our Lives, (1997); Cassidy J., Dot.con: The Greatest Story Ever Sold, (2002); Christensen C., The Innovator's Dilemma: When New Technologies Cause Great Firms to Fail, (1997); Christensen C., Tedlow R., Patterns of disruption in retailing, Harvard Business Review, pp. 42-45, (2000); Christopher M., Mole R., Rushton A. 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Wrigley N., Store Choice, Store Location and Market Analysis, (1988); Wrigley N., Sunk costs and corporate restructuring: British food retailing and the property crisis, Retailing, Consumption and Capital: Towards the New Retail Geography, pp. 116-136, (1996); Wrigley N., How British retailers have shaped food choice, The Nations Diet: The Social Science of Food Choice, pp. 112-128, (1998); Wrigley N., Understanding store development programmes in post-property-crisis UK food retailing, Environment and Planning A, 30, pp. 15-35, (1998); Wrigley N., The globalization of retail capital: Themes for economic geography, The Oxford Handbook of Economic Geography, pp. 292-313, (2000); Wrigley N., Transforming the corporate landscape of US food retailing: Market power, financial re-engineering, and regulation, Tijdschrift Voor Economische En Sociale Geografie, 93, pp. 63-83, (2002); Wrigley N., Lowe M., Retailing, Consumption and Capital: Towards the New Retail Geography, (1996); Wrigley N., Lowe M., Reading Retail, (2002); Wrigley N., Lowe M., Currah A., Progress report: Retailing and E-tailing, Urban Geography, 23, pp. 180-197, (2002)","A.J. Murphy; School of Geogr. Earth/Environ. Sci., University of Birmingham, Department of Geography, Edgbaston, Birmingham B15 2TT, United Kingdom; email: a.murphy@bham.ac.uk",{"$nulls":7},"0308518X",null,null,null,"English","Environ. Plann. A","Article","Final",null,"Scopus","2-s2.0-0042388631"]
["Corbitt B.J.; Thanasankit T.","Corbitt, Brian J. (6603461390); Thanasankit, Theerasak (6506028838)","6603461390; 6506028838","Acceptance and leadership - Hegemonies of e-Commerce policy perspectives",2002.0,"Prometheus: Critical Studies in Innovation",20.0,1.0,null,39.0,57.0,18.0,17.0,"10.1080/08109020110110916","https://www.scopus.com/inward/record.uri?eid=2-s2.0-0036096168&doi=10.1080%2f08109020110110916&partnerID=40&md5=18422cc8c670bc6b55eef881f3bbc67b",null,null,"This paper presents an analysis of the e-Commerce policies developed and implemented in the USA, Canada, Australia, Victoria, Finland, Norway, the UK, Ireland, the EU (by the OECD), Singapore, Japan, Malaysia, Thailand and Hong Kong (Special Administrative Region). The paper shows that e-Commerce policy adopted is generally trying to achieve two fundamental aims: 1. to minimize regulatory environments for e-Commerce; and 2. to ease logistical problems in doing e-Commerce - i.e. in paying electronically, in delivery of goods and in customs, tariffs and duties. These strategies are designed to create an environmental where e-Commerce is adopted by business and governmental in these countries to achieve 'best practice', to become 'modern', to gain 'efficiencies', because 'it is the way to go', because 'we must have it, because everybody has it', and because they 'percieve the benefits of it'. In essence it is being used to gain hegemony in the economic competitiveness of the geopolitical environment created by the Internet. This paper argues that differentiating types of policy is related to ideology and hegemony in the various countries.","E-Commerce policy; Hegemony; Policy analysis; Policy typology","e-commerce; hegemony; Internet; leadership; technology policy",{"$nulls":6},"Corbitt B.J., Exploring the social construction of IT policy - Thailand and Singapore, Prometheus, 17, 3, pp. 309-321, (1999); Gramsci A., Selections from the Prison Notebook, (1971); Strinati D., An Introduction to Theories of Popular Culture, (1995); Lee C.Y., Corbitt B., Kong W.C., Stakeholder relationships and e-commerce differentiation: A preliminary investigation in Singapore and Australia, Pacific Asia Conference on Information Systems, pp. 1-3, (2000); Corbitt B.J., Developing intraorganisational electronic commerce strategy: An ethnographic study, Journal of Information Technology, 165, pp. 119-130, (2000); Ransome P., Antoni G., A New Introduction, (1992); Simon R., Gramsci's Political Thought: An Introduction, (1991); Self P., Planning: Rational or political?, Policy Analysis and Policy Innovation: Patterns, Problems and Potentials, pp. 221-236, (1981); Gershuny J.I., What should forecasters do?, Policy Analysis and Policy Innovation: Patterns, Problems and Potentials, pp. 193-207; Corbitt B.J., Implementing policy for homeless kids in schools: Re-assessing the micro and macro levels in the policy debate in Australia, Journal of Education Policy, 12, 3, pp. 165-176, (1997); Ball S.J., Politics and Policy Making in Education, (1990); Bosetti L., Landy D., Miklos E., Critical perspectives on educational planning and policy analysis, The Canadian Administrator, 29, 2, pp. 1-7, (1989); Hofferbert R.I., The Reach and Grasp of Policy Analysis: Comparative Views of the Craft, (1986); Rein M., From Policy to Practice, (1983); Wallace M., Contradictory interests in policy implementation: The case of LEA development plans for schools, Journal of Education Policy, 6, 4, pp. 385-399, (1991); Habermas J., Legitimation Crisis, (1976); Giddens A., Central Problems in Social Theory: Action, Structure and Contradiction in Social Analysis, pp. 215-216, (1979); Sabatier P., Mazmanian D., Policy implementation, Encyclopedia of Public Policy, (1983); Forester J., Planning in the Face of Power, (1989); Foucault M., The Archeology of Knowledge, (1977); Kenway J., Education and right's discursive politics: Private versus state schooling, Foucault and Education, (1990); Hatcher R., Troyna B., The policy cycle: A ball by ball account, Journal of Education Policy, 9, 2, (1994); Geller H., Johnston A., Policy as linear and non-linear science, Journal of Education Policy, 5, 1, pp. 49-65, (1990); Kogan M., Educational Decision Making, (1975); Ball S.J., What is policy? Texts, trajectories and toolboxes, Discourse, 13, 2, pp. 10-17, (1993); Thanasankit T., Exploring Social Aspects of Requirements Engineering - An Ethnographic Study of Thai Systems Analysts, (1999); Clinton W., Gore A., A Framework for Global Electronic Commerce, (1997); The Emerging Digital Economy II, (1999); Electronic Commerce, (1999); Building Trust in Digital Economy, (1998); The Economic and Social Impact of Electronic Commerce: Preliminary Findings and Research Agenda, (1999); Chambers Launch Secure E-Commerce Package, (2000); Singapore Launches Electronic Master Plan, (2000); Wong P.K., Implementing the NII vision: Singapore's experience and future challenges, Information Infrastructure and Policy, 5, 2, pp. 95-117, (1996); Teo T.S.H., Lim V.K.G., Lai R.Y.C., Users and uses of the internet: The case of Singapore, International Journal of Information Management, 17, 5, pp. 330-331, (1997); Kong W., Electronic Transactions Act 1998 and the National Information Infrastructure - A New Scene for Doing Business in Singapore, (1998); Kong W.C., Issues Affecting the Implementation of Electronic Commerce in SMEs in Singapore, (1999); Wong P.K., Leveraging the global information revolution for economic development: Singapore's evolving information industry strategy, Information Systems Research, 9, 4, pp. 323-341, (1998); Main Guiding Principles, (1998); Policy, Reports and Consultation Papers; Digital 21: Hong Kong, Special Administrative Region Information Technology Strategy, (1998); Report on E-Commerce - The Policy Requirement; Global Victoria: Victorian Government Information Technology and Multimedia Policy, (1999); What is the MSC?; Malaysia's Position on E-Commerce, (1997); An Opportunity to Re-invent Goverment; Model Law on Electronic Commerce, (1998); Shannon D., Baker, McKenzie, Legal and regulatory issues, APEC Task Force on Electronic Commerce, (1998); Getting Ready for the New Millenium - What are the Thai Government's Actions Toward the Year 2000; Responses to: Building Confidence in Electronic Commerce - A Consultation Document, (1999)",null,null,"Carfax Publishing Company",{"$nulls":5},8109028.0,null,null,null,"English","Prometheus Crit. Stud. Innov.","Article","Final",null,"Scopus","2-s2.0-0036096168"]
["Teltscher S.","Teltscher, Susanne (6507909160)",6.50790916E9,"From physical to digital delivery: Definition, scope and tariff revenue implications of electronic goods trading",2001.0,"Proceedings of the Hawaii International Conference on System Sciences",null,null,null,297.0,null,null,0.0,"10.1109/HICSS.2001.927278","https://www.scopus.com/inward/record.uri?eid=2-s2.0-0034966262&doi=10.1109%2fHICSS.2001.927278&partnerID=40&md5=0ec15fc63aa1d7d4f9189759adcde722","United Nations Conference on Trade and Development, United States","Teltscher S., United Nations Conference on Trade and Development, United States","With the advent of cross-border electronic commerce, an increasing number of products that have been traded physically in the past are now imported digitally. This raises a number of issues, which are currently debated at the international level: should these products be defined as goods or services; which multilateral trade rules should govern them; and, should they remain tariff and tax exempted? The paper addresses these questions by discussing definitional, regulatory and fiscal aspects of electronic goods trading and demonstrates the links among them. In particular, it analyzes data on trade, tariffs and other import duties for \"digitizable products\" and calculates potential revenue losses, should physical delivery of products be replaced by digital delivery. Findings show that, while for most countries overall shares in trade are still small, and thus fiscal losses negligible, some developing countries would be affected considerably by tariff revenue cuts. © 2001 IEEE.","Digital goods; E-commerce; Tariffs","Information analysis; Regulatory compliance; Taxation; Electronic goods trading; Electronic commerce",{"$nulls":19},"English","Proc Hawaii Int Conf Syst Sci","Article","Final",null,"Scopus","2-s2.0-0034966262"]
["Aoyama Y.; Ratick S.J.; Schwarz G.","Aoyama, Yuko (7201631047); Ratick, Samuel J. (6701548408); Schwarz, Guido (8264780600)","7201631047; 6701548408; 8264780600","Modeling the impact of business-to-business electronic commerce on the organization of the logistics industry",2005.0,"Geographical Analysis",37.0,1.0,null,46.0,68.0,22.0,25.0,"10.1111/j.1538-4632.2005.00587.x","https://www.scopus.com/inward/record.uri?eid=2-s2.0-12444329798&doi=10.1111%2fj.1538-4632.2005.00587.x&partnerID=40&md5=163312af0dd2fa936e7972a6f3449317","Graduate School of Geography, The George Perkins Marsh Res. Inst., Clark University, Worcester, MA 01610-1477, 950 Main street, United States","Aoyama Y., Graduate School of Geography, The George Perkins Marsh Res. Inst., Clark University, Worcester, MA 01610-1477, 950 Main street, United States; Ratick S.J., Graduate School of Geography, The George Perkins Marsh Res. Inst., Clark University, Worcester, MA 01610-1477, 950 Main street, United States; Schwarz G., Graduate School of Geography, The George Perkins Marsh Res. Inst., Clark University, Worcester, MA 01610-1477, 950 Main street, United States","In this article, we analyze patterns and recent trends of the logistics industry with specific emphasis on the impact of business-to-business (B-to-B) electronic commerce on its industrial organization. From this conceptualization, we develop an optimization-based logistics model comprising two interlinked networks representing commodity flow and information flow, respectively. The model is operationalized using Monte Carlo simulation to highlight possible scenarios of logistics industry changes in response to the use of B-to-B e-commerce. Through this endeavor, we examine how new technologies affect the cost of information and transportation transactions in the logistics industry. © 2005 The Ohio State University.",null,"e-commerce; freight transport; logistics; modeling; organizational framework; spatial analysis",{"$nulls":6},"Andersson S., Jansen K., Waidringer J., Optimisation of a Generic Multi-Mode Transportation and Logistics Network, Information Systems in Logistics and Transportation, pp. 329-334, (1997); Aoyama Y., Structural Foundations for Electronic Commerce: A Comparative Organization of Retail Trade in Japan and the United States, Urban Geography, 22, pp. 130-153, (2001); Aoyama Y., The Information Society, Japanese Style: Corner Stores as Hubs of E-Commerce Access, Worlds in Electronic Commerce, pp. 109-128, (2001); Aoyama Y., Sheppard E., The Dialectics of Geographic and Virtual Spaces, Environment and Planning A, 35, pp. 1151-1156, (2003); Arntzen B.C., Shumway H.M., Driven by Demand: A Case Study, Supply Chain Management Review, pp. 34-41, (2002); Barnes-Viera P., Claycomb C., Business-to-Business E-Commerce: Models and Managerial Decisions, Business Horizons, 44, 3, pp. 13-20, (2001); Berglund M., van Laarhoven P., Sharman G., Wandel S., Third-Party Logistics: Is There a Future?, The International Journal of Logistics Management, 10, 1, pp. 59-70, (1999); Berman O., Jaillet P., Simchi-Levi D., Location-Routing Problems with Uncertainty, Facility Location: A Survey of Applications and Methods, pp. 427-452, (1995); Best M., The New Competition: Institutions of Industrial Restructuring, (1990); Blake M.B., Gini M., Introduction to the Special Section: Agent-Based Approaches to B2B Electronic Commerce, International Journal of Electronic Commerce, 7, 1, pp. 7-8, (2002); Brunn S., Leinbach T., Worlds of E-Commerce: Economic, Geographical and Social Dimensions, (2001); Bryan D., Extensions to the Hub Location Problem: Formulations and Numerical Examples, Geographical Analysis, 30, pp. 315-330, (1998); Chan Y., Carter W.B., Burnes M.D., A Multiple-Depot, Multiple-Vehicle, Location-Routing Problem with Stochastically Processed Demands, Computers and Operations Research, 28, pp. 803-826, (2001); Clay K., Monk T., What's Next for Internet Data Analysis? Status and Challenges Facing the Community, Proceedings of the IEEE, 85, 10, pp. 1563-1571, (1997); Collins J., Ketter W., Gini M., A Multi-Agent Negotiation Testbed for Contracting Tasks with Temporal and Precedence Constraints, International Journal of Electronic Commerce, 7, 1, pp. 35-58, (2002); Dodge M., Mapping Cyberspace, (2001); Great Predictions That Never Happened, (2002); Elli S.A., Who's Who? Sorting out the e-Logistics Players, Logistics Management and Distribution Report, 40, 4, (2001); Evans P.B., Wurster T.S., Strategy and the New Economics of Information, Harvard Business Review, 75, 5, pp. 71-82, (1997); Gertler M., The Limits to Flexibility: Comments on the Post-Fordist Vision of Production and its Geography, Transactions: Institute of British Geographers, 13, pp. 419-432, (1988); Gijsen J.W.J., Szirbik N.B., Wagner G., Agent Technologies for Virtual Enterprises in the One-of-a-Kind Production Industry, International Journal of Electronic Commerce, 7, 1, pp. 9-34, (2002); Golob T.F., Regan A.C., Impacts of Information Technology on Personal Travel and Commercial Vehicle Operations: Research Challenges and Opportunities, Transportation Research Part C: Emerging Technologies, 9, 4, pp. 87-121, (2001); Graham S., Marvin S., Telecommunications and the City: Electronic Spaces, Urban Places, (1996); Graham S., Marvin S., Splintering Urbanism. Networked Infrastructures, Technological Mobilities and the Urban Condition, (2001); Greis N.P., Kasarda J.D., Enterprise Logistics in the Information Era, California Management Review, 39, 4, pp. 55-78, (1997); Grubesic T.H., Spatial Dimensions of Internet Activity, Telecommunications Policy, 26, 7-8, pp. 363-387, (2002); Haddad C., Ewing J., Ground Wars. UPS's Rapid Ascent Leaves FedEx Scrambling, Business Week, pp. 64-68, (2001); Hadjiconstantinou E., Quick Response in the Supply Chain, (1999); Horner M.W., O'Kelly M.E., Embedding Economies of Scale Concepts for Hub Network Design, Journal of Transport Geography, 9, pp. 255-265, (2001); Jallat F., Capek M.J., Disintermediation in Question: New Economy, New Networks, New Middlemen, Business Horizons, 44, 2, (2001); Kaplan S., Sawhney M., E-Hubs: The New B2B Marketplaces, The Harvard Business Review, 78, 3, pp. 97-106, (2000); Karageorgos A., Thompson S., Mehandjiev N., Agent-Based System Design for B2B Electronic Commerce, International Journal of Electronic Commerce, 7, 1, pp. 59-90, (2002); Kuby M., Ratick S.J., Osleeb J., Modeling US Coal Export Planning Decisions, Annals of the Association of American Geographers, 81, pp. 627-649, (1991); Li F., Whalley J., Williams H., Between Physical and Electronic Spaces: The Implications for Organizations in the Networked Economy, Environment and Planning A, 33, pp. 699-716, (2001); Lieb R., Schwarz B., The Year 2001 Survey: CEO Perspectives on the Current Status and Future Prospects of the Third Party Logistics Industry in the United States, (2001); Liker J.K., Wu Y.-C., Japanese Automakers, U.S. Suppliers and Supply-Chain Superiority, Sloan Management Review, 42, 1, pp. 81-93, (2000); Lipietz A., New Tendencies in the International Division of Labor: Regimes of Accumulation and Modes of Regulation, Production, Work, Territory: The Geographical Anatomy of Industrial Capitalism, (1986); Lucking-Reiley D., Spulber D.F., Business-to-Business Electronic Commerce, Journal of Economic Perspectives, 15, 1, pp. 55-68, (2001); Malecki E.J., Oinas P., Making Connections: Technological Learning and Regional Economic Change, (1999); Melkote S., Daskin M.S., An Integrated Model of Facility Location and Transportation Network Design, Transportation Research Part A: Policy and Practice, 35, 6, pp. 515-538, (2001); Murphy A., The Emergence of Online Food Retailing: A Stakeholder Perspective, Tijdschrift Voor Economische En Sociale Geografie, 93, 1, pp. 47-61, (2002); Odlyzko A., The Internet and Other Networks: Utilization Rates and Their Implications, Information Economics and Policy, 12, 4, pp. 341-365, (2000); OECD Economic Outlook 67 (June), (2000); O'Kelly M.E., A Geographer's Analysis of Hub-and-Spoke Networks, Journal of Transport Geography, 6, 3, pp. 171-186, (1998); O'Kelly M.E., On the Allocation of a Subset of Nodes to a Mini-Hub in a Package Delivery Network, Papers in Regional Science, 77, 1, pp. 77-99, (1998); O'Kelly M.E., Grubesic T.H., Backbone Topology, Access, and the Commercial Internet, 1997-2000, Environment and Planning B: Planning and Design, 29, 4, pp. 533-552, (2002); Osleeb J.P., Ratick S.J., A Dynamic Location-Allocation Model for Evaluating the Spatial Impacts for Just-in-Time Planning, Geographical Analysis, 22, pp. 50-69, (1990); Osleeb J.P., Ratick S.J., Kuby M.J., Olson H.E., Antle L.G., Hawnn A.F., Coal Logistics System, Transportation Research Record 1222: Ports, Waterways, and Inland Water Transportation, pp. 6-13, (1989); Piore M., Sabel C., The Second Industrial Divide, (1984); Ralston B.A., GIS and Logistics: Potential Contributions and the Current State-of-the-Art, International Workshop on Geographic Information Systems for Transportation (GIS-T) and Intelligent Transportation Systems (ITS), (1999); Ratick S.J., Osleeb J.P., Kuby M., Lee K., Interperiod Network Storage Location-Allocation (INSLA) Models, Spatial Analysis and Location-Allocation Models, pp. 269-301, (1987); Rogerson P.A., Plane D.A., Modelling Temporal Change in Flow Matrices, Papers of the Regional Science Association, 54, pp. 147-164, (1984); Sheppard E., The Spaces and Times of Globalization: Place, Scale, Networks, and Positionality, Economic Geography, 78, 3, pp. 307-330, (2002); Turowski K., Agent-Based e-Commerce in Case of Mass Customization, International Journal of Production Economics, 75, pp. 69-81, (2002); Wheeler J.O., Aoyama Y., Warf B., Introduction: City Space, Industrial Space, and Cyberspace, Cities in the Telecommunication Age: Fractured Geographies, pp. 3-17, (2000); Wilson R., Delaney R.V., Managing Logistics in a Perfect Storm (12th Annual \"State of Logistics Report\"), (2001); Wilson R., Delaney R.V., Understanding Inventory-Stay Curious (13th Annual \"State of Logistics Report\"), (2002); Zook M.A., Old Hierarchies or New Networks of Centrality? The Global Geography of the Internet Content Market, American Behavioral Scientist, 44, pp. 1679-1696, (2001)","Y. Aoyama; Graduate School of Geography, George Perkins Marsh Research Inst., Clark University, Worcester, MA 01610-1477, 950 MAin Street, United States; email: yaoyama@clarku.edu",null,"Blackwell Publishing Ltd",{"$nulls":5},167363.0,null,null,null,"English","Geogr. Anal.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-12444329798"]
["Suarez-Villa L.","Suarez-Villa, Luis (6603777601)",6.603777601E9,"The E-economy and the rise of technocapitalism: Networks, firms, and transportation",2003.0,"Growth and Change",34.0,4.0,null,390.0,414.0,24.0,25.0,"10.1046/j.0017-4815.2003.00227.x","https://www.scopus.com/inward/record.uri?eid=2-s2.0-0347594811&doi=10.1046%2fj.0017-4815.2003.00227.x&partnerID=40&md5=31375109db56f1c4ad33cc7e6904de8f","Social Ecol./Planning, Policy/Design, School of Social Ecology, University of California, Irvine, CA, United States","Suarez-Villa L., Social Ecol./Planning, Policy/Design, School of Social Ecology, University of California, Irvine, CA, United States","The e-economy is part of a larger phenomenon, technocapitalism, that is transforming business organizations and the ways in which they transact, produce, and ship their goods. Technocapitalism is an evolution of market capitalism that is rooted in technological innovation and supported by such intangibles as creativity and knowledge. This paper considers first the main characteristics of networks that support the e-economy and its source phenomenon, the emergence of technocapitalism. Networks are thought to be the main vehicle through which the e-economy spreads, and they have major effects on the organization of business firms. The culture of technocapitalism, with its emphasis on continuous innovation and rapid adjustment, is largely behind the rising importance of networks. A second section then considers the deconstruction of business firms and its relation to networks, the e-economy, and the rise of technocapitalism. A historical perspective is provided to show the contrast with previous eras. The deconstruction of business organizations involves a major transformation of the norms and ways in which firms are run and structured. Finally, the likely implications for transportation and shipping of the rise of the e-econonny, its networks, and the deconstruction of firms are discussed. The logistics, pricing, and infrastructure of shipping are likely to be substantially affected by the spread of the e-economy, its networks, and the deconstruction of firms.",null,"e-commerce; networking; shipping; spatial analysis; transportation economics",{"$nulls":6},"Ashkenas R., Ulrich D., Jick T., Kerr S., The Boundaryless Organization, (1995); Baldi P., Brunak S., Bioinformatics, (2001); Bell D., The Coming of Post-Industrial Society, (1973); Beyers W.B., Services and the new economy: Elements of a research agenda, Journal of Economic Geography, 2, pp. 1-29, (2002); Brown K., The human genome business today, Scientific American, pp. 50-55, (2000); Buderi R., Engines of Tomorrow: How the World's Best Companies Are Using Their Research Labs to Win the Future, (2000); Bunnell D., Making the Cisco Connection: The Story Behind the Real Internet Superpower, (2000); Carr N.G., The Digital Enterprise, (2001); Clarke D., The Encyclopedia of Transportation, (1976); Clarke T., Clegg S., Changing Paradigms: The Transformation of Management Knowledge for the 21st Century, (1998); Cooke P., Morgan K., The Associational Economy, (1998); Coombs R., Georghiu L., A new \"industrial ecology, Science, 296, (2002); Crainer S., The Management Century: A Critical Review of 20th Century Thought and Practice, (2000); Cronin M.J., Doing More Business on the Internet: How the Electronic Highway Is Transforming American Companies, (1995); DiMaggio P., The Twenty-First Century Firm, (2001); The Shape of the New E-Company, E-Management Survey, (2000); A Moving Story, pp. 65-66, (2002); Evans P., Wurster T.S., Blown to Bits: How the New Economics of Information Transforms Strategy, (2000); Fischer M.M., Suarez-Villa L., Steiner M., Innovation, Networks and Localities, (1999); Forrest J.E., Martin M.J.C., Strategic alliances between large and small research intensive organizations: Experiences in the biotechnology industry, R and D Management, 22, pp. 41-53, (1992); Galambos L., Sewell J.E., Networks of Innovation, (1996); Galbraith J.K., The Affluent Society, (1969); Grubler A., The Rise and Fall of Intrastructure: Dynamics of Evolution and Technological Change in Transport, (1990); Harding J., Why B2B is the place to be, Financial Times, (2000); Hartman A., Sifonis J., Kador J., Net Ready: Strategies for Success in the E-conomy, (2000); Kellner D., Critical Theory, Marxism and Modernity, (1989); Kim W.C., Mauborgne R., Strategy, value innovation, and the knowledge economy, Sloan Management Review, 40, pp. 19-32, (1999); Kuhn T.S., The Structure of Scientific Revolutions, (1962); Larsen C.F., R and D Industry in 1999, (2000); Leinbach T., Brunn S.D., The Worlds of E-commerce: Economic, Geographical and Social Dimensions, (2001); Lewis I., Talalayevsky A., Third-party logistics: Leveraging information technology, Journal of Business Logistics, 21, pp. 173-186, (2000); Liebeskind J., Oliver A., Zucker L., Brewer M., Social networks, learning and flexibility: Sourcing scientific knowledge in new biotechnology firms, Organization Science, 3, pp. 783-831, (1996); Lucas H.C., Strategies for Electronic Commerce and the Internet, (2003); Encyclopedia of Transportation, (2000); McKenna R., Real Time: Preparing for the Age of the Never Satisfied Customer, (1997); Meyer C., Fast Cycle Time: How to Align Purpose, Strategy, and Structure for Speed, (1993); Mulhall D., Our Molecular Future, (2002); Noam E.M., Interconnecting the Network of Networks, (2001); Norton R.D., Creating the New Economy, (2001); Orsenigo L., Pammolli F., Riccaboni M., Technological change and network dynamics: Lessons from the pharmaceutical industry, Research Policy, 30, pp. 485-508, (2001); Pal N., Ray J.M., Pushing the Digital Frontier: Insights Into the Changing Landscape of E-Business, (2001); Petroff J.N., Handbook of MRP II and JIT: Strategies for Total Manufacturing Control, (1993); Pilling D., Guerrera F., Drug giant plans radical research move, Financial Times, (2000); Pisano G.P., The Development Factory: Unlocking the Potential for Process Innovation, (1997); Powell W.W., Doput K.W., Smith-Doerr L., Interorganizational collaboration and the locus of innovation: Networks of learning in biotechnology, Administrative Science Quarterly, 41, pp. 116-145, (1996); Regan A., Transforming the freight industry: From regulation to competition to decentralization in the information age, Access, 20, pp. 26-31, (2002); Reich L., The Making of American Industrial Research, (1985); Rivette K.G., Kline D., Rembrandts in the Attic: Unlocking the Hidden Value of Patents, (2000); Robbins-Roth C., From Alchemy to IPO: The Business of Biotechnology, (2000); Scase R., Towards the Virtual Corporation and Beyond: Trends and Changes in Mobile Working, (1999); Schumpeter J.A., The Theory of Economic Development, (1934); Shapiro C., Varian H.R., Information Rules: A Strategic Guide to the Network Economy, (1998); Spengler S.J., Bioinformatics in the information age, Science, 287, pp. 1221-1223, (2000); Suarez-Villa L.; Suarez-Villa L., Invention, inventive learning, and innovative capacity, Behavioral Science, 35, pp. 290-310, (1990); Suarez-Villa L., The dynamics of regional invention and innovation: Innovative capacity and regional change in the twentieth century, Geographical Analysis, 25, pp. 147-164, (1993); Suarez-Villa L., The structures of cooperation: Downscaling, outsourcing and the networked alliance, Small Business Economics, 10, pp. 5-16, (1998); Suarez-Villa L., Invention and the Rise of Technocapitalism, (2000); Suarez-Villa L., Southern California as a global gateway region: Polycentricity and network segmentation as competitive advantages, Gateways to the Global Economy, pp. 83-104, (2000); Suarez-Villa L., The rise of technocapitalism, Science Studies, 14, pp. 4-20, (2001); Suarez-Villa L., Networked alliances and innovation, The Emergence of the Knowledge Economy: A Regional Perspective, pp. 65-80, (2002); Suarez-Villa L., Technocapitalism and the new ecology of entrepreneurship, International Workshop on Entrepreneurship in the Modern Space Economy: Evolutionary and Policy Perspectives, (2002); Suarez-Villa L., High technology clustering in the polycentric metropolis: A view from the Los Angeles metropolitan region, International Journal of Technology Management, 25, pp. 818-842, (2002); Suarez-Villa L., Innovative capacity, networks and the rise of the experimental firm: Implications for regional development and policy, International Workshop on Modern Entrepreneurship, Regional Development and Policy: Dynamic and Evolutionary Perspectives, (2003); Suarez-Villa L., Fischer M.M., Technology, organization and export-driven research and development in Austria's electronics industry, Regional Studies, 29, pp. 19-42, (1995); Suarez-Villa L., Giaoutzi M., Stratigea A., Territorial and border barriers in information and communication networks: A conceptual exploration, Tijdschrift Voor Economische En Sociale Geografie, 83, pp. 93-104, (1992); Suarez-Villa L., Hasnath S.A., The effect of infrastructure on invention: Innovative capacity and the dynamics of public construction investment, Technological Forecasting and Social Change, 44, pp. 333-358, (1993); Suarez-Villa L., Karlsson C., The development of Sweden's R and D-intensive electronics industries: Exports, outsourcing and territorial distribution, Environment and Planning A, 28, pp. 783-818, (1996); Suarez-Villa L., Walrod W., The collaborative economy of biotechnology: Alliances, outsourcing, and R and D, International Journal of Technology Management, 26, (2003); Takahashi D., Opening the Xbox, (2002); Thrift N., Virtual capitalism: The globalisation of business knowledge, Virtualism: A New Political Economy, pp. 161-186, (1998); Tolliday S., The Rise and Fall of Mass Production, (1998); Tsang C.D., Microsoft Girst Generation: The Success Secrets of the Visionaries Who Launched a Technology Empire, (2000); Tvede L., Ohnemus P., Marketing Strategies for the New Economy, (2001); van Hoek R.I., The role of third-party logistics providers in mass customization, International Journal of Logistics Management, 11, pp. 37-46, (2000); von Krogh G., Roos J., Kleine D., Knowing in Firm: Understanding, Managing and Meaning Knowledge, (1998); Wayner P., Free for All: How Linux and the Free Software Movement Undercut the High-Tech Titans, (2000); Webb B., Consi T.R., Biorobotics, (2001); Weinberger D., Small Pieces Loosely Joined: A Unified Theory of the Web, (2002)","L. Suarez-Villa; Social Ecol./Planning, Policy/Design, School of Social Ecology, University of California, Irvine, CA, United States; email: lsuarez@uci.edu",{"$nulls":7},174815.0,null,null,null,"English","Growth Change","Article","Final",null,"Scopus","2-s2.0-0347594811"]
["Bauer H.H.; Falk T.; Hammerschmidt M.","Bauer, Hans H. (8639860900); Falk, Tomas (8412658600); Hammerschmidt, Maik (8639860800)","8639860900; 8412658600; 8639860800","eTransQual: A transaction process-based approach for capturing service quality in online shopping",2006.0,"Journal of Business Research",59.0,7.0,null,866.0,875.0,9.0,588.0,"10.1016/j.jbusres.2006.01.021","https://www.scopus.com/inward/record.uri?eid=2-s2.0-33744535216&doi=10.1016%2fj.jbusres.2006.01.021&partnerID=40&md5=5b9cc7f42c86e4f6d3d2bb61f0893d89","University of Mannheim, Business School, D-68131 Mannheim, L 5, 1, Germany","Bauer H.H., University of Mannheim, Business School, D-68131 Mannheim, L 5, 1, Germany; Falk T., University of Mannheim, Business School, D-68131 Mannheim, L 5, 1, Germany; Hammerschmidt M., University of Mannheim, Business School, D-68131 Mannheim, L 5, 1, Germany","Existing e-service quality scales mainly focus on goal-oriented e-shopping behavior excluding hedonic quality aspects. As a consequence, these scales do not fully cover all aspects of consumer's quality evaluation. In order to integrate both utilitarian and hedonic e-service quality elements, we apply a transaction process model to electronic service encounters. Based on this general framework capturing all stages of the electronic service delivery process, we develop a transaction process-based scale for measuring service quality (eTransQual). After conducting exploratory and confirmatory factor analysis, we identify five discriminant quality dimensions: functionality/design, enjoyment, process, reliability and responsiveness. All extracted dimensions of eTransQual show a significant positive impact on important outcome variables like perceived value and customer satisfaction. Moreover, enjoyment is a dominant factor in influencing both relationship duration and repurchase intention as major drivers of customer lifetime value. As a result, we present conceptual and empirical evidence for the need to integrate both utilitarian and hedonic e-service quality elements into one measurement scale. © 2006 Elsevier Inc. All rights reserved.","Electronic service quality; Online shopping; Scale development; Transaction process",{"$nulls":7},"Anderson E.W., Fornell C., Mazvancheryl S.K., Customer satisfaction and shareholder value, J Mark, 68, pp. 172-185, (2004); Babin B.J., Darden W.R., Griffin M., Work and/or fun: measuring hedonic and utilitarian shopping value, J Consum Res, 20, 4, pp. 644-656, (1994); Babin B.J., Lee Y.K., Kim E.J., Griffin M., Modeling consumer satisfaction and word-of-mouth: restaurant patronage in Korea, J Serv Mark, 19, 3, pp. 133-139, (2005); Bagozzi R., Baumgartner H., The evaluation of structural equation models and hypothesis testing, Principles of marketing research, pp. 386-422, (1994); Barnes S.J., Vidgen R., An evaluation of cyber-bookshops: the WebQual method, International Journal of Electronic Commerce, 6, 1, pp. 11-30, (2001); Bauer H.H., Hammerschmidt M., Falk T., Measuring the service quality of e-banking portals, Int J Bank Mark, 23, 2, pp. 153-175, (2005); Baumgartner H., Homburg C., Applications of structural equation modeling in marketing and consumer research: a review, Int J Res Mark, 13, 2, pp. 139-161, (1996); Bitner M.J., Evaluating service encounters: the effects of physical surroundings and employee responses, J Mark, 54, 2, pp. 69-82, (1990); Browne M.W., Cudeck R., Alternative ways of assessing model fit, Testing structural equation models, pp. 136-162, (1993); Childers T.L., Carr C.L., Peck J., Carson S., Hedonic and utilitarian motivations for online retail shopping behaviour, J Retail, 77, 4, pp. 511-535, (2001); Churchill G., Marketing research, (1987); Csikszentmihalyi M., The flow experience and its significance for human psychology, Optimal experience: psychological studies of flow in consciousness, pp. 15-35, (1988); Dellaert B.G.C., Kahn B.E., How tolerable is delay? Consumers' evaluations of internet web sites after waiting, J Interact Market, 13, 1, pp. 41-54, (1999); Evanschitzky H., Iyer G.R., Hesse J., Ahlert D., E-Satisfaction: a re-examination, J Retail, 80, pp. 239-247, (2004); Fornell C., Larcker D., Evaluating structural equation models with unobservable variables and measurement error, J Mark Res, 18, 1, pp. 39-50, (1981); Garvin D.A., Competing on the eight dimensions of quality, Harvard Bus Rev, 65, 6, pp. 101-109, (1987); Gerbing D., Anderson J., An updated paradigm for scale development incorporating unidimensionality and its assessment, J Mark Res, 25, pp. 186-192, (1988); Gronroos C., Heinonen F., Isoniemi K., Lindholm M., The NetOffer model: a case example from the virtual marketspace, Manage Decis, 38, 4, pp. 243-252, (2000); Gupta S., Lehman D.R., Stuart J.A., Valuing customers, J Mark Res, 41, pp. 7-18, (2004); Hair J.F., Anderson R.E., Tatham R.L., Black W.C., Multivariate data analysis, (1998); Henning-Thurau T., Gwinner K.P., Gremler D.D., Understanding relationship marketing outcomes-an integration of relational benefits and relationship quality, J Serv Res, 4, 3, pp. 230-247, (2002); Homburg C., Giering A., Personal characteristics as moderators of the relationship between customer satisfaction and loyalty-an empirical analysis, Psychol Mark, 18, 1, pp. 43-67, (2000); Hoffman D.L., Novak T.P., Marketing in hypermedia computer-mediated environments: conceptual foundations, J Mark, 60, 3, pp. 50-68, (1996); Holbrook M.B., Hirschman E.C., The experiential aspects of consumption: consumer fantasies, feelings, and fun, J Consum Res, 9, 2, pp. 132-140, (1982); Jayawardhena C., Measurement of service quality in internet banking: the development of an instrument, J Market Manag, 20, pp. 185-207, (2004); Juran J.M., Gryna F.M., Quality planning and analysis, (1970); Lages C., Lages C.R., Lages L.F., The RELQUAL scale: a measure of relationship quality in export market ventures, J Bus Res, 58, 9, pp. 1040-1048, (2005); McFarlin D.B., Sweeney P.D., Distributive and procedural justice as predictors of satisfaction with personal and organizational outcomes, Acad Manage J, 35, 3, pp. 626-638, (1992); Meuter M.L., Ostrom A.L., Roundtree R.I., Bitner M.J., Self-service technologies: understanding customer satisfaction with technology-based service encounters, J Mark, 64, 3, pp. 50-65, (2000); Montgomery A.L., Li S., Srinivasan K., Liechty J.C., Modeling online browsing and path analysis using clickstream data, Mark Sci, 23, 4, pp. 579-595, (2004); Parasuraman A., Zeithaml V.A., Malhotra A., E-S-QUAL-a multiple-item scale for assessing electronic service quality, J Serv Res, 7, 3, pp. 213-233, (2005); Podsakoff P.M., Organ D.W., Self-reports in organizational research: problems and prospects, J Manage, 12, 4, pp. 531-544, (1986); Reichheld F.F., Teal T., The loyalty effect, (1996); Rust R.T., The rise of e-service, J Serv Res, 3, 4, pp. 283-285, (2001); Rust R.T., Lemon K.N., E-service and the consumer, Int J Electron Commer, 5, 3, pp. 85-101, (2001); Rust R.T., Lemon K.N., Zeithaml V.A., Return on marketing: using customer equity to focus marketing strategy, J Mark, 68, pp. 109-127, (2004); Sismeiro C., Bucklin R.E., Modeling purchase behavior at an e-commerce web site: a task-completion approach, J Mark Res, 41, 3, pp. 306-323, (2004); Thompson C.J., Locander W.B., Pollio H.R., Putting consumer experience back into consumer research: the philosophy and method of existential-phenomenology, J Consum Res, 16, pp. 133-147, (1989); Van Riel A.C.R., Liljander V., Jurriens P., Exploring consumer evaluations of e-services: a portal site, Int J Serv Ind Manage, 12, 3-4, pp. 359-377, (2001); Vargo S.L., Lusch R.F., Evolving to a new dominant logic for marketing, J Mark, 68, pp. 1-17, (2004); Wakefield K.L., Blodgett J.G., Customer response to intangible and tangible service factors, Psychol Mark, 16, 1, pp. 51-68, (1999); Wolfinbarger M., Gilly M.C., eTailQ: dimensionalizing, measuring and predicting etail quality, J Retail, 79, pp. 183-198, (2003); Yoo B., Donthu N., Developing a scale to measure the perceived quality of an Internet shopping site (SITEQUAL), Q J Electron Commer, 2, 1, pp. 31-46, (2001); Zeithaml V.A., How consumer evaluation processes differ between goods and services, Services marketing, pp. 191-199, (1984); Zeithaml V.A., Parasuraman A., Malhotra A., Service quality delivery through web sites: a critical review of extant knowledge, J Acad Mark Sci, 30, 4, pp. 362-375, (2002); Zimmermann H.D., A model for electronic markets, Mark Commun, 6, pp. 18-19, (1997)","H.H. Bauer; University of Mannheim, Business School, D-68131 Mannheim, L 5, 1, Germany; email: hans.bauer@bwl.uni-mannheim.de",{"$nulls":7},1482963.0,null,"JBRED",null,"English","J. Bus. Res.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-33744535216"]
["Hesse M.","Hesse, Markus (16309590300)",1.63095903E10,"Shipping news: The implications of electronic commerce for logistics and freight transport",2002.0,"Resources, Conservation and Recycling",36.0,3.0,null,211.0,240.0,29.0,100.0,"10.1016/S0921-3449(02)00083-6","https://www.scopus.com/inward/record.uri?eid=2-s2.0-0036805843&doi=10.1016%2fS0921-3449%2802%2900083-6&partnerID=40&md5=2a945a7ae68f8e2e1fa6c15415f66b7b","Department of Earth Sciences, Geographic Sciences and Urban Research, Free University of Berlin, 12249 Berlin, Malteserstr. 74-100, Germany","Hesse M., Department of Earth Sciences, Geographic Sciences and Urban Research, Free University of Berlin, 12249 Berlin, Malteserstr. 74-100, Germany","The paper considers the significance of electronic commerce (e-commerce) for freight transport, logistics and physical distribution, regarding both business to business and business to consumer commerce. The possible implications of e-commerce are analysed in the broader context of structural change, going beyond narrow assessments that overstate the significance of e-commerce and its potential to make freight traffic more efficient. The main argument of the paper is threefold: first, most recent analyses of freight transport and logistics implications of e-commerce are overstating the current relevance of e-commerce applications on the one hand, and neglecting the influence of the underlying structural change in the entire logistics system on the other. Second, conventional analyses of certain efficiency benefits of e-commerce are probably too optimistic, whereas its negative effects are underestimated at the same time. E-commerce is likely to support longer transport distances and often higher delivery frequencies, increasing demand for land, due to the establishment of new transhipment points (distribution centres) and, to a certain extent, a shift towards truck and air freight transport modes. Third, e-commerce and IT are interrelated components of the structural change in distribution. They affect the environment in terms of vehicle miles, related emissions and energy consumption, by speeding up the time and increasing the geographic area of transport operations. Whether e-commerce contributes to a more efficient distribution system or not very much depends on particular regional circumstances, such as consumer habits, delivery modes and population density. Overall, there is some evidence that e-commerce is likely to reinforce longstanding trends of transport growth, rather than breaking them. Future research should investigate e-commerce more comprehensively, in relation to the entire distribution system and to its application in firms and households. This would also be more useful for dealing with a generic property of modern economy and society: increasing demand for flexibility, speed and mobility. © 2002 Elsevier Science B.V. All rights reserved.","Corporate re-organisation; E-commerce; Environment; Freight transport; Home delivery; Land use; Logistics; On-line retail; Physical distribution; Structural change; Traffic generation; User behaviour; Warehousing","Trixis; Electronic commerce; Energy utilization; Information technology; Logistics; Consumer habits; e-commerce; freight transport; logistics; shipping; commercial phenomena; consumer; cost; economic aspect; energy consumption; environmental factor; population density; research; review; society; Freight transportation",{"$nulls":6},"Abbey D.D., Twist D.C., Koomen L.J., The Need for Speed: Impact on Supply Chain Real Estate, (2001); Abernathy F.H., Dunlop J.T., Hammond J.H., Weil D., Retailing and supply chains in the information age, Technology in Society, 22, pp. 5-31, (2000); (2002); Annual Reports, 2000. cf. the Annual Reports 2000 of Amazon, (2000); Bahrami B., E-Commerce: Implications for Supply Chain Productivity, Carrier Competitiveness, and Efficient Allocation of the External Costs of Transportation, The Transportation Research Board, 80th Annual Meeting, (2001); Bovet D., Martha J., Value Nets. Breaking the Supply Chain to Unlock Hidden Profits, (2000); Bowersox D.J., Smykay E.W., LaLonde B.J., Physical Distribution Management. Logistics Problems of the Firm, (1968); Bowersox D.J., Closs D.J., Stank T.P., Ten mega-trends that will revolutionise supply chain logistics, Journal of Business Logistics, 21, 2, pp. 1-16, (2000); Broens D.F., Vanroye K., Demkes R.; Brooks M., Wahhaj Z., The economic effects of business to business internet activity, National Institute Economic Review, 175, (2001); Browne M., E-Commerce and urban transport, (2001); Burnson P., Seeking Solution for E-commerce. With the Internet business clicking off, air freight companies are looking for the legacy in Web systems, (2001); Cairns S., Delivering Alternatives, Transport Policy, 3, 4, pp. 155-176, (1996); Casas J., Zmud J., Bricka S., Impact of Shopping Via Internet on Travel for Shopping Purposes, 80th Annual Meeting of the Transportation Research Board, (2001); State of the Logistic's 12th annual Report, (2000); Castells M., High Technology, Economic Restructuring and the Urban-Regional Process in the United States, Urban Affairs Annual Reviews, 28, pp. 11-40, (1985); Castells M., The rise of the network society, The Information Age: Economy, Society, and Culture, 1, (1996); Chinitz B., Freight and the metropolis, The Impact of America's Transport Revolutions on the New York Region, (1960); Clancy B., Hoppin D., Converging on Air Freight. The Merge Global 2001 World Air Freight Forecast, Air Cargo World online, (2001); Colin J., The impact of e-commerce on logistics, Joint OECD/ECMT-Seminar 'The Impact of E-commerce on Transport', Session 2: E-commerce and logistics, (2001); Dixon R., How to Select an Optimal Distribution Site, Site Selection magazine, (1999); Flamig H., E-commerce, Ernaehrung und Umwelt. Gutachten fuer den Ausschuss fuer Bildung, Forschung und Technikfolgenabschaetzung des Deutschen Bundestags. Unveroeff. Forschungsbericht der TU Hamburg-Harburg. Hamburg. (E-commerce, food and the environment. Unpublished expertise for the Commission on Education, (2001); Forkenbrock D., Comparison of external costs of rail and truck freight transportation, Transportation Research A, 35, pp. 321-337, (2001); Gillespie A., Healy P., Robins K., Movement and mobility in the Post-Fordist city, Transport Policy and the Environment, pp. 243-266, (1998); Gould J., Golob T.F., Barwise P., Why do People Drive to Shop? Future Travel and Telecommunications Tradeoffs, Working Papers of the Center for Activity Systems Analysis (CASA), (1998); Graham S., Marvin S., Telecommunications and the City, Electronic Spaces, Urban Places, (1996); Harrison B., Lean and Mean, The Changing Landscape of Corporate Power in the Age of Flexibility, (1994); Hesse M., Physical Distribution and The City: Goods movement as an indicator of urban and regional development, Proceedings of the 2001 Meeting of the Commission on Urban Development of the International Geographical Union, (2002); Hesse M., Transport and Logistics in City Regions: Driving Forces for Counter-Urbanization? Investigations on the Postmodern Urban Landscape, Social Change and Sustainable Transport, (2002); Contemporary Capitalism. The Embeddedness of Institutions, (1997); Hu P., Developing an 'E-Sensible' Transportation System. What Are the Research and Data Needs?, TR News, 216, pp. 4-8, (2001); E-commerce and Logistical Consequences, (2000); External Costs of Transport: Accident, Environmental and Congestion Costs in Western Europe, Report for the International Union of Railways, (2000); Janz O., Mehr Verkehr durch E-Commerce?-Eine analyse der Auswirkungen des E-Commerce-Wachstums (B2C) auf den Verkehr, Zeitschrift für Verkehrswissenschaften, 1, 72, 1, pp. 48-69, (2001); Jindel S., Delivering E-Commerce. The retail world is in upheaval over E-Commerce - can transport carriers be far behind?, Air Cargo World online, (2001); Kirschbraun T., Bomba T., The New Economy. Effects on corporate real estate strategies, Occupier Strategies in the New Economy, (2000); Komor P., Reducing energy use in US freight transport, Transport Policy, 2, 2, pp. 119-128, (1995); Matthews H., Hendrickson C., Lave L., Harry Potter and the Hole in the Ozone Layer. While on-line shopping may appear to cause less impact on the environment than driving to the mall, the net effect of e-commerce remains unclear, IEEE Spectrum, (2000); Matthews H.S., Hendrickson C.T., Soh D.L., Environmental and economic effects of e-commerce: A case study of book publishing and retail logistics, Transportation Research Record, 1763, pp. 6-12, (2001); Matthews H.S., Williams E., Tagami T., Hendrickson C.T., Energy Implications of Online Book Retailing in the United States and Japan, Environmental Impact Assessment Review, (2002); McKinnon A., Physical distribution, Services and Uneven Development, (1988); McKinnon A., Logistical restructuring, freight traffic growth and the environment, Transport Policy and the Environment, pp. 97-109, (1998); Meyer M.D., Delivering The Future: E-Freight. Provided by the Foundation for Intermodal Research and Education; O'Kelly M., A geographer's analysis of hub-and-spoke systems, Journal of Transport Geography, 6, 3, pp. 171-186, (1998); Environmental Data Compendium, (1999); Business to consumer electronic commerce. An update on the statistics, (2001); Orremo F., Wallin C., Joensson G., Ringsberg K.; Penner J., Lister D., Griggs D., Dokken D., McFarland M., Aviation and the Global Atmosphere. Special; Pflaum A., Kille C., Wilhelm M., Prockl G., Consumer Direct - The Last Mile, (2000); Pratt A.C., New media, the new economy and new spaces, Geoforum, 31, pp. 425-436, (2000); Reynolds J., E-commerce-a critical review, International Journal of Retail and Distribution Management, 28, 10, pp. 417-444, (2000); Robeson J.F., Kollat D.T., Channels of distribution: Structure and change, The Distribution Handbook, pp. 225-234, (1985); Rondinelli D., Making metropolitan areas competitive and sustainable in the new economy, Journal of Urban Technology, 8, 1, pp. 1-21, (2001); Schipper L., Scholl L., Price L., Energy use and carbon emissions from freight in 10 industrialised countries: An analysis of trends from 1973 to 1992, Transportation Research D, 2, 1, pp. 57-76, (1997); Schipper L., Scholl L., Price L., Energy use and carbon emissions from freight in 10 industrialised countries: An analysis of trends from 1973 to 1992, Transportation Research D, 2, 1, pp. 57-76, (1997); Schoenberger E., The Cultural Crisis of the Firm, (1997); Skinner R.E.,  Century, (2000); Sobie B.; Song J., Regan A., Transition or transformation? Emerging freight transportation intermediaries, Transportation Research Record, 1763, pp. 1-5, (2001); Strauss-Wieder A.; Ten Hompel M., Siebel L.; Digital Economy 2000, (2000); Womack J., Jones D., Roos D., The Machine that Changed the World, (1990); Zook M.A., The web of production: The economic geography of commercial internet content production in the United States, Environment and Planning A, 32, pp. 411-426, (2000)","M. Hesse; Department of Earth Sciences, Geographic Sci. and Urban Research, Free University of Berlin, 12249 Berlin, Malteserstr. 74-100, Germany; email: mhesse@zedat.fu-berlin.de",null,"Elsevier",{"$nulls":5},9213449.0,null,"RCREE",null,"English","Resour. Conserv. Recycl.","Article","Final",null,"Scopus","2-s2.0-0036805843"]
["Brengman M.; Geuens M.; Weijters B.; Smith S.M.; Swinyard W.R.","Brengman, Malaika (6603256071); Geuens, Maggie (6603621890); Weijters, Bert (6504645781); Smith, Scott M. (56000366100); Swinyard, William R. (6603282131)","6603256071; 6603621890; 6504645781; 56000366100; 6603282131","Segmenting Internet shoppers based on their Web-usage-related lifestyle: A cross-cultural validation",2005.0,"Journal of Business Research",58.0,"1 SPEC.ISS",null,79.0,88.0,9.0,110.0,"10.1016/S0148-2963(02)00476-9","https://www.scopus.com/inward/record.uri?eid=2-s2.0-6944237118&doi=10.1016%2fS0148-2963%2802%2900476-9&partnerID=40&md5=4b57ec8b1a3f30619aebb0b504ca4615","Limburgs Universitair Centrum, BEDR-BBK, B-3590 Diepenbeek, Universitaire Campus, Gebouw D, Belgium; Ghent University, Dept. of Economics/Business Admin., 9000 Ghent, Hoveniersberg 24, Belgium; Vlerick Leuven Gent Management Sch., Ghent 9050, Bellevue 6, Belgium; Marriott School of Management, Brigham Young University, Provo, UT 84602, United States","Brengman M., Limburgs Universitair Centrum, BEDR-BBK, B-3590 Diepenbeek, Universitaire Campus, Gebouw D, Belgium, Ghent University, Dept. of Economics/Business Admin., 9000 Ghent, Hoveniersberg 24, Belgium; Geuens M., Ghent University, Dept. of Economics/Business Admin., 9000 Ghent, Hoveniersberg 24, Belgium, Vlerick Leuven Gent Management Sch., Ghent 9050, Bellevue 6, Belgium; Weijters B., Vlerick Leuven Gent Management Sch., Ghent 9050, Bellevue 6, Belgium; Smith S.M., Marriott School of Management, Brigham Young University, Provo, UT 84602, United States; Swinyard W.R., Marriott School of Management, Brigham Young University, Provo, UT 84602, United States","Online surveys in the United States and Belgium were conducted to cross-culturally validate the Internet shopper lifestyle scale [S.M. Smith, W.R. Swinyard, The identification of shopping behaviors among Internet users. World Marketing Congress, Cardiff Business School, 2001]. Special attention was devoted to sample, construct, and measurement equivalence. In both countries, the same six basic dimensions were found to underlie the scale: Internet convenience, perceived self-inefficacy, Internet logistics, Internet distrust, Internet offer, and Internet window-shopping. Except from having the same basic meaning and structure in Belgium as in the United States, the Web-usage-related lifestyle scale also led to the same segments in both countries. Four online shopping segments (tentative shoppers, suspicious learners, shopping lovers, and business users) and four online nonshopping segments (fearful browsers, positive technology muddlers, negative technology muddlers, and adventurous browsers) are profiled with regard to their Web-usage-related lifestyle, themes of Internet Usage, Internet attitude, psychographic, and demographic characteristics. © 2002 Elsevier Inc. All rights reserved.","Cross-cultural research; E-shoppers; Internet lifestyle; Internet segmentation; Scale validation",{"$nulls":7},"Baumgartner H., Steenkamp J.B.E.M., Response styles in marketing research: A cross-national investigation, J. Mark. Res., 38, pp. 143-156, (2001); Brengman M., Geuens M., Profiling Internet users based on their propensity to adopt online shopping, Asia Pacific Advances in Consumer Research Conference, (2002); Brunso K., Grunert K.G., Development and testing of a cross-culturally valid instrument: Food-related lifestyle, Adv. Consum. Res., 22, pp. 475-480, (1995); Chang S., Internet segmentation: State-of-the-art marketing applications, J. Segm. Mark., 2, 1, pp. 19-34, (1998); Crisp C.B., Jarvenpaa S.L., Todd P.A., Individual differences and Internet shopping attitudes and intentions, (1997); Dahlen M., Closing in on the Web consumer, Convergence in Communications and Beyond, (1999); Donthu N., Garcia A., The Internet shopper, J. Advert. Res., 39, pp. 52-58, (1999); Fram E.H., Grady D.B., Internet buyers: Will the surfers become buyers?, Direct Mark., 58, 6, pp. 63-65, (1995); Geuens M., Brengman M., S'Jegers R., Food retailing Now and in the future, Journal of Retailing and Consumer Services; Hoffman D.L., Novak T.P., A new marketing paradigm for electronic commerce, Inf. Soc., 13, 1, pp. 43-54, (1997); Hoffman D.L., Kalsbeek W.D., Novak T.P., Internet and Web use in the United States: Baselines for commercial development, Commun. ACM, 39, pp. 36-46, (1996); Jarvenpaa S.L., Tractinsky N., Saarinen L., Consumer trust in an Internet store: A cross-cultural validation, J. Comput.-Mediat. Commun., 5, 2, (1999); Kahle L.R., Lifestyles, values and psychographics: Perspectives from around the world, Eur. Adv. Consum. Res., 4, pp. 1-3, (1999); Kumar V., International Marketing Research, (2000); McDonald W.J., Internet customer segments: An international perspective, Enhancing Knowledge Development in Marketing, pp. 338-344, (1996); Novak T.P., Hoffman D.L., Yung Y.-F., Measuring the customer experience in online environments: A structural modeling approach, Mark. Sci., 19, 1, pp. 22-42, (2000); Pastore M., Number of net users shopping online up 50 percent, Cyber Atlas, (2001); Paulhus D.L., Measurement and control of response bias, Measures of Personality and Social Psychological Attitudes, pp. 17-59, (1991); Plummer J.T., The concept and application of lifestyle segmentation, J. Mark., (1974); Quelch J.A., Klein R.L., International business and the Internet, Sloan Management Review, 37, 3, pp. 60-75, (1996); Rangaswamy A., Gupta S., Innovation adoption and diffusion in the digital environment: Some research opportunities; Sheehan K.B., Hoy M.G., Using E-mail to survey Internet users in the United States: Methodology and assessment, J. Comput.-Mediat. Commun., 4, 3, (1999); Smith S.M., Swinyard W.R., The identification of shopping behaviors among Internet users, (2001); Steenkamp J.-B.E.M., Ter Hofstede F., International market segmentation: Issues and perspectives, Int. J. Res. Mark., (2002); Vellido A., A methodology for the characterization of business-to-consumer E-commerce, (2000); Vellido A., Lisboa P.J.G., Meehan K., Segmentation of the on-line shopping market using neural networks, Expert Syst. Appl., 17, pp. 303-314, (2002); Wedel M., Kamakura W., Market Segmentation: Conceptual and Methodological Foundations, (2000)","M. Brengman; Limburgs Universitair Centrum, BEDR-BBK, B-3590 Diepenbeek, Universitaire Campus, Gebouw D, Belgium; email: malaika.brengman@luc.ac.be",null,"Elsevier Inc.",{"$nulls":5},1482963.0,null,"JBRED",null,"English","J. Bus. Res.","Article","Final",null,"Scopus","2-s2.0-6944237118"]
["Mason S.J.; Ribera P.M.; Farris J.F.; Kirk R.G.","Mason, Scott (7202152323); Ribera, P. Mauricio (6701509796); Farris, Jennifer A. (8547665600); Kirk, Randall G. (57190590327)","7202152323; 6701509796; 8547665600; 57190590327","Integrating the warehousing and transportation functions of the supply chain",2003.0,"Transportation Research Part E: Logistics and Transportation Review",39.0,2.0,null,141.0,159.0,18.0,136.0,"10.1016/S1366-5545(02)00043-1","https://www.scopus.com/inward/record.uri?eid=2-s2.0-0037356406&doi=10.1016%2fS1366-5545%2802%2900043-1&partnerID=40&md5=0fd96f8c545ee569a9549e250d7e0a20","Dept. of Industrial Eng., Univ. of Arkansas, Fayetteville, AR 72701, 4207 Bell Engineering Center, United States; The Grado Dept. of Ind./Syst., Virginia Tech, Blacksburg, VA 24061, 250 Durham Hall (0118), United States; Global Concepts, Incorporated, Fayetteville, AR 72701, 700 Research Center Boulevard M/S 28, United States","Mason S.J., Dept. of Industrial Eng., Univ. of Arkansas, Fayetteville, AR 72701, 4207 Bell Engineering Center, United States; Ribera P.M., Dept. of Industrial Eng., Univ. of Arkansas, Fayetteville, AR 72701, 4207 Bell Engineering Center, United States; Farris J.F., The Grado Dept. of Ind./Syst., Virginia Tech, Blacksburg, VA 24061, 250 Durham Hall (0118), United States; Kirk R.G., Global Concepts, Incorporated, Fayetteville, AR 72701, 700 Research Center Boulevard M/S 28, United States","Electronic commerce and associated business-to-business transaction capabilities have changed the way in which supply chains operate. The Internet has enabled information exchange on an unprecedented scale, often at a pace too fast for normal consumption. Companies are not equipped to make effective use of data from warehouse management systems-which contain information on supplier/customer warehouse inventory levels and key customer ordering patterns-and transportation management systems-within which information pertaining to the location of important supply chain assets such as products or vehicles is typically stored. These systems are key factors in integrating the physical flow of goods along the supply chain. The integration of these systems leads to global inventory visibility, which, in turn, leads to reduced costs and improved customer service by decreasing shipping and receiving cycle times, increasing shipment and inventory accuracy, and decreasing lead-time variability. This paper examines the total cost benefits that can be achieved by suppliers and warehouses through the increased global visibility provided by an integrated system. We develop a discrete event simulation model of a multi-product supply chain to examine the potential benefits to be gained from global inventory visibility and trailer yard dispatching and sequencing techniques. Experimental results demonstrate the potential for this integrated paradigm to improve customer service through improved efficiencies, reduced costs, and reduced lead-time variability. © 2003 Elsevier Science Ltd. All rights reserved.","Logistics; Supply chain management; Transportation; Warehouse management systems","Cost reduction; Discrete event simulation; Information management; Sales; Ships; Visibility; Warehouses; Business-to-business transactions; Customer orders; Customer-service; Global inventories; Information exchanges; Inventory levels; Lead-time variability; Order patterns; Reduced cost; Warehouse management systems; distribution system; e-commerce; Internet; management; transportation system; Supply chain management",{"$nulls":6},"Ballou R.H., Business Logistics Management, (1999); Ganeshan R., Harrison T.P., An introduction to supply chain management, Supply Chain Management, Version 1, (1995); Gilmore D., Linking transportation and communication, ID Systems 5, (1997); Gilmore D., Tompkins J., WMS footprint expands into supply chain, ID Systems 5, (1997); Gilmore D., Tompkins J., Transport plays key role in supply strategy, ID Systems 8, (2000); Hopp W.J., Spearman M.L., Factory Physics: Foundations of Manufacturing Management, (1996); Landers T.L., Cole M.H., Walker B., Kirk R.G., The virtual warehousing concept, Transportation Research Part E, 36, pp. 115-125, (2000); Lattmann P., WMS: Lower costs, more options for growing companies, ID Systems 8, pp. 1-10, (2000); Corporate Profile, (2001); Minahan T., How the supply chain changes your job, Purchasing, 124, 2, pp. 57-58, (1998); Monczka R.M., Morgan J., What will happen and what should you know, Purchasing, 124, pp. 78-85, (1998); Montgomery D.C., Design and Analysis of Experiments, (1991); Napolitano M., Making the Move to Cross Docking: A Practical Guide to Planning, Designing and Implementing a Cross Dock Operation, (2001); SAP Transportation Management Solution, (2000); Stuart D.E., Owen J., Landers T.L., Establishing the virtual warehouse, Manufacturing Science and Engineering-1995 (MED-Vol. 2-2, MH-Vol. 3-2), (1995); Supply chain management: What's hot for 2001, ID Systems 9, (2001); Szgenda R., Information's competitive edge, InformationWeek, 720, pp. 4-10, (1999); TMSs to the rescue, Modern Materials Handling, 55, 11, pp. 51-57, (2000); Thomas J., Are there limits?, Distribution, 95, 8, (1996); WMS: flexibility and visibility matter, Modern Materials Handling, 55, 13, pp. 42-45, (2000)","S.J. Mason; Dept. of Industrial Eng., Univ. of Arkansas, Fayetteville, AR 72701, 4207 Bell Engineering Center, United States; email: mason@uark.edu",null,"Elsevier Ltd",{"$nulls":5},1.3665545E7,null,null,null,"English","Transp. Res. Part E Logist. Transp. Rev.","Article","Final",null,"Scopus","2-s2.0-0037356406"]
["Sparks L.; Wagner B.A.","Sparks, Leigh (7102080046); Wagner, Beverly A. (7402578181)","7102080046; 7402578181","Retail exchanges: A research agenda",2003.0,"Supply Chain Management",8.0,1.0,null,17.0,25.0,8.0,27.0,"10.1108/13598540310463323","https://www.scopus.com/inward/record.uri?eid=2-s2.0-3242689514&doi=10.1108%2f13598540310463323&partnerID=40&md5=fb578d0c3040bb48b9a816a35a5ec3ad","Department of Marketing, University of Stirling, Stirling, United Kingdom","Sparks L., Department of Marketing, University of Stirling, Stirling, United Kingdom; Wagner B.A., Department of Marketing, University of Stirling, Stirling, United Kingdom","The nature of logistics and supply chain management has dramatically changed as a result of new information technology. Information is now critical in supply systems and information technology has allowed companies to transform their dealings with customers and suppliers. The development of retail exchanges is stimulating further change in supply chains and buyer-supplier relationships in the retail sector. This paper briefly considers concepts such as QR, ECR and CPFR utilised by the retail sector to promote supply-chain efficiencies. It then goes on to explore the impact of retail exchanges and outlines progress so far. Finally, research issues arising from the retail exchanges are set in the context of research questions and propositions to further understanding of the impact of retail exchanges on supply chain management and the retail industry as a whole.","Channel relationships; E-commerce; Supply-chain management","Customer satisfaction; Forecasting; Industrial management; Industrial research; Information technology; Internet; Management information systems; Strategic planning; Transportation; Warehouses; Channel relationships; Quick responses(QR); Retail exchanges; Supply-chain management; Electronic commerce",{"$nulls":6},"Angeles R., Revisiting the role of the internet-EDI in the current electronic scene, Logistics Information Management, 13, 1, pp. 45-57, (2000); Business Wire, (2002); Eng Yong T., Spickett-Jones G., An investigation of the concept of e-marketplace in supply chain management, BAM International Conference, (2002); Evans P., Wurster T.S., Blown to Bits: How the New Economics of Information Transforms Strategy, (2000); Dawson J.A., Retailing at century end; competing in volatile markets, Industrial Marketing Management, 29, pp. 37-44, (2000); Dawson J.A., Is there a new commerce in Europe?, International Review of Retail and Distribution Management, 11, pp. 287-299, (2001); Dawson J.A., Shaw S., The changing character of retailer-supplier relationships, Retail Distribution Management, (1990); Fernie J., Quick response: An international perspective, International Journal of Physical Distribution & Logistics Management, 24, 6, pp. 38-46, (1994); Fernie J., Sparks L., Logistics and Retail Management, (1998); Fiorito S., May E., Straughn K., Quick response in retailing: Components and implementation, International Journal of Retail & Distribution Management, 23, 5, pp. 12-21, (1995); Huffman W., Keedy J., Roberts K., The unexpected return of B2B, The McKinsey Quarterly, 3, (2002); Karolefski J., Trading exchanges, Food Logistics, pp. 15-18, (2002); Kincade D.H., Vass D., Cassill N.L., Implementation of technology and relationships to supply chain performance: Apparel manufacturers' perspectives, International Review of Retail and Distribution Management, 11, pp. 301-327, (2001); Kotzab H., Improving supply chain performance by efficient consumer response? A critical comparison of existing ECR approaches, Journal of Business and Industrial Marketing, 14, 5-6, pp. 364-367, (1999); Economic Consumer Response: Enhancing Customer Value in the Grocery Industry, (1993); McMichael H., Mackay D., Altmann G., Quick response in the Australian TCP industry: A case study of supplier response, International Journal of Physical Distribution & Logistics Management, 30, 7-8, pp. 611-626, (2000); Perry M., Sohal A.S., Quick response practices and technologies in developing supply chains, International Journal of Physical Distribution & Logistics, 30, 7-8, pp. 627-639, (2000); GNX helps build on basics, Retail Week, (2002); Sparks L., The retail logistics transformation, Logistics and Retail Management, pp. 1-22, (1998); B2B exchanges must make strides in supply chain services, The Grocer, (2002); Information Pack for Potential Members, (2000)",{"$nulls":8},1.3598546E7,null,null,null,"English","Supply Chain Manage.","Article","Final",null,"Scopus","2-s2.0-3242689514"]
["Gudmundsson S.V.","Gudmundsson, Sveinn Vidar (7005246334)",7.005246334E9,"A Global Electronic Market (GEM) for logistics services and supply-chain management: the expert view",2006.0,"World Review of Intermodal Transportation Research",1.0,1.0,null,3.0,23.0,20.0,4.0,"10.1504/WRITR.2006.011148","https://www.scopus.com/inward/record.uri?eid=2-s2.0-66949119338&doi=10.1504%2fWRITR.2006.011148&partnerID=40&md5=a77c543be71c3db92bb4f845717d9699","Department of Strategy and CERMAS Research Centre, Toulouse Business School, 31068 Toulouse, 20 Blvd Lascrosses, France","Gudmundsson S.V., Department of Strategy and CERMAS Research Centre, Toulouse Business School, 31068 Toulouse, 20 Blvd Lascrosses, France","The aim of the research was to clarify why integration efforts in logistics, through electronic markets, have been difficult to accomplish and to seek industry expert opinion on where the key benefits and barriers lie. A three round Delphi approach was used. The first step was to generate factors in response to three probes and then to iterate the responses among the experts until stability occurred. Factors suggested by the experts fall into groupings suggested in prior research on Inter-Organisational Systems (IOS). Factors having high consensus likely to influence adoption, fell into three categories: trust, pressure and perceived benefits. This research indicates that logistics integration through electronic markets is viable and sellers are likely to feel pressure from buyers, but are most likely to resist market adoption on trust and competition issues. © 2006 Inderscience Enterprises Ltd.","Delphi forecasting; e-Commerce; e-marketplaces; electronic markets; GEM; Global Electronic Market; Inter-Organisational Systems; IOS; logistics; logistics integration; supply-chain management; technology adoption",{"$nulls":7},"Alt R., Klein S., Learning from failure: the myths and magic of electronic transportation markets, Proceedings of the Thirty-First Hawaii International Conference on Systems Sciences, 4, 6-9, pp. 102-110, (1998); Bakos J.Y., Brynjolfsson E., Information technology, incentives and the optimal number of suppliers, Journal of Management Information Systems, 10, 2, pp. 37-53, (1993); Bakos Y., A strategic analysis of electronic marketplaces, MIS Quarterly, 15, 3, pp. 295-310, (1991); Bakos Y., Reducing buyer search costs: implications for electronic marketplaces, Management Science, 43, 12, pp. 1676-1692, (1997); Bakos Y., The emerging role of electronic marketplaces on the internet, Communications of the ACM, 41, 8, pp. 35-42, (1998); Banerjee S., Golhar D.Y., Characteristics differentiating users and non-users of EDI, Information and Management, 26, 2, pp. 65-74, (1994); Banerjee S., Golhar D.Y., Security issues in EDI environment, International Journal of Operations and Production Management, 14, 4, pp. 97-108, (1994); Benjamin R.I., Wigand R., Electronic markets and virtual value chains on the information superhighway, Sloan Management Review, 36, pp. 62-72, (1995); Bijl R., Delphi in a future scenario study on mental health and mental health care, Futures, 33, pp. 149-158, (1992); Boje D.M., Murnighan J.K., Group confidence pressures in iterative decisions, Management Science, 28, pp. 1187-1196, (1982); Bonney J., Encompass: what went wrong?, American Shipper, 33, pp. 32-38, (1997); Bowersox D.J., Daugherty P.J., Logistics paradigms: the impact of information technology, Journal of Business Logistics, 16, 1, pp. 65-78, (1995); Bowman R.J., From public to private: trading exchanges change with the times, Global Logistics and Supply Chain Strategies, (2003); Brockhoff K., The performance of forecasting groups in computer dialogue and face to face discussions, The Delphi Method: Techniques and Applications, pp. 291-321, (1975); Christiaanse E., Markus M.L., Participation in collaboration electronic marketplaces, Proceedings of the 36th International Conference on System Sciences, pp. 178-186, (2002); Chwelos P., Benbasat I., Dexter A.S., Empirical test of an EDI adoption model, Information Systems Research, 12, 3, pp. 304-321, (2001); Crook C.W., Kumar R.L., Electronic data-interchange: a multi-industry investigation using grounded theory, Information and Management, 34, pp. 75-89, (1998); Dalkey N.C., The Delphi Method: An Experimental Study of Group Opinion, (1969); Dalkey N.C., Helmer. O., An experimental application of the Delphi method to the use of experts, Management Science, 9, pp. 458-467, (1963); Dalkey N.C., Brown B., Cochran S.W., The Delphi method III: use of self-ratings to improve group estimates, Technological Forecasting, 1, pp. 283-291, (1970); Damsgaard J., Electronic markets in hong kong’s cargo community: thanks, but no thanks, Journal of Electronic Markets, 8, 3, pp. 46-49, (1998); Delbecq A.L., van de Ven A.H., Gustafson D.H., Group Techniques for Program Planning: A Guide to Nominal Group and Delphi Processes, (1975); Ellram L.M., Cooper M.C., Supply chain management, partnerships and the shipper – third party relationship, International Journal of Logistics Management, 1, 2, pp. 1-9, (1990); Emerson R.M., Power-dependence relations, American Sociological Review, 27, pp. 31-41, (1962); Farrell J., Competition with Lock-in, Working Paper 8722, (1987); Giarraputo J., Moore H., Electrifying business, Global Finance, 13, 9, pp. 93-100, (1999); Grieger M., Electronic marketplaces: a literature review and a call for supply chain management research, European Journal of Operational Research, 144, pp. 280-294, (2003); Grossman S., Hart O., The costs and benefits of ownership: a theory of vertical and lateral integration, Journal of Political Economy, 94, 4, pp. 691-719, (1986); Gudmundsson S.V., Walczuch R., The development of electronic markets in logistics, International Journal of Logistics Management, 10, 2, pp. 99-113, (1999); Hart P., Saunders C., Power and trust: critical factors in the adoption and use of Electronic Data Interchange, Organization Science, 8, 1, pp. 23-42, (1997); Hitt L., Brynjolfsson E., Productivity, business profitability and consumer surplus: three different measures of information technology value, MIS Quarterly, 20, 2, pp. 121-142, (1996); Iacovou C.L., Benbasat I., Dexter A.S., Electronic Data Interchange and small organizations: adoption and impact of technology, MIS Quarterly, 19, 4, pp. 465-485, (1995); Jenkins P., VAT and electronic commerce: the challenges and opportunities, VAT Monitor, 10, 1, pp. 3-5, (1999); King J., Christiaanse E., Forster P., A problem shared, Cargovision, 9, 10, pp. 25-27, (1995); Levitt J., Smith G., Are you vulnerable?, Informationweek, 774, pp. 79-88, (2000); Malone T.W., Yates J., Benjamin R.I., Electronic markets and electronic hierarchies: effects of information technologies on market structure and corporate strategies, Communications of the ACM, 30, 6, pp. 484-497, (1987); Masser I., Foley P., Delphi revisited: expert opinion in urban analysis, Urban Studies, 24, 3, pp. 217-224, (1987); Mohr J., Spekman R., Characteristics of partnership success: partnership attributes, communications behavior and conflict resolution techniques, Strategic Management Journal, 15, 2, pp. 135-152, (1994); O'Callaghan R., Kauffman P.J., Konsynski B., Adoption correlates and share effects of Electronic Data Interchange systems in marketing channels, Journal ofMarketing, 56, 2, pp. 45-56, (1992); OECD, Dismantling The Barriers to Global Electronic Commerce, (1998); Pfeffer J., Salancik G.R., The External Control Of Organizations: A Resource Dependence Perspective, (1978); Porter M.E., Millar V.E., How information gives you competitive advantage, Harvard Business Review, 4, pp. 149-160, (1985); Premkumar G., Ramamurthy K., The role of interorganizational and organisational factors on the decision mode for adoption of interorganizational systems, Decision Sciences, 26, 3, pp. 303-336, (1995); Premkumar G.K., Ramamurthy K., Nilakanta S., Implementation of Electronic Data Interchange: an innovation diffusion perspective, Journal of Management Information Systems, 11, 2, pp. 157-186, (1994); Rogers E.M., Diffusion of Innovations, (1995); Rowe G., Wright G., The Delphi technique as a forecasting tool: issues and analysis, International Journal of Forecasting, 15, pp. 353-375, (1999); Rowe G., Wright G., Bolger F., Delphi: a reevaluation of research and theory, Technological Forecasting and Social Change, 39, pp. 235-251, (1991); Scala S., McGrath R., Advantages and disadvantages of Electronic Data Interchange, Information and Management, 25, 2, pp. 85-91, (1993); Scheele S., Reality construction as a product of Delphi interaction, The Delphi Method: Techniques and Applications, pp. 37-71, (1975); Stijins W., Gunton M., Safe from prying eyes, World Trade, 13, 9, pp. 64-65, (2000); Tan M., Teo T.S.H., Factors influencing the adoption of the internet, International Journal of Electric Commerce, 2, 3, pp. 5-18, (1998); Thompson J.D., Organizations in Action, (1967); Thong J.Y.L., An integrated model of information systems adoption in small business, Journal of Management Information Systems, 15, 4, pp. 187-214, (1999); Turoff M., The Policy Delphi, The Delphi Method: Techniques and Applications, pp. 80-96, (1975); Williams L.R., Magee G.D., Suzuki Y., A multidimensional view of EDI: testing the value of EDI participation to firms, Journal of Business Logistics, 19, 2, pp. 73-101, (1998); Williamson O.E., Markets and Hierarchies: Analysis and Antitrust Implications, (1975)",{"$nulls":8},1.7494729E7,null,null,null,"English","World Rev.of Intermodal Transp. Res.","Article","Final",null,"Scopus","2-s2.0-66949119338"]
["Hudson J.","Hudson, John (57200085214)",5.7200085214E10,"Digitising the structures of government: The UK's information age government agenda",2002.0,"Policy and Politics",30.0,4.0,null,515.0,531.0,16.0,44.0,"10.1332/030557302760590431","https://www.scopus.com/inward/record.uri?eid=2-s2.0-0036794354&doi=10.1332%2f030557302760590431&partnerID=40&md5=004a8a474a03b42b32a88c4dce1a9289","Dept. of Social Policy/Social Work, University of York, United Kingdom","Hudson J., Dept. of Social Policy/Social Work, University of York, United Kingdom","Since its election the UK Blair government has initiated a radical programme to redesign the apparatus of government through the use of information and communication technologies (ICTs). However, unpacking the operational implications of this 'e-government' strategy is a far from easy task and numerous policy dilemmas of considerable significance for the future of governance have arisen. This article considers the broad policy questions raised by the information age government agenda, the implications for delivery mechanisms of the government's current strategy and issues surrounding access, exclusion and equity that are likely to be of increasing significance as their digitisation programme gathers pace.","E-government; Electronic service delivery; Modernising government","United Kingdom; communication; e-commerce; governance approach; information technology",{"$nulls":6},"Jupp B., Divided by Information? The 'Digital Divide' and the Implications of the New Meritocracy, (2001); Bell D., The Coming of Post-industrial Society, (1974); Bellamy C., Taylor J., Informatisation and new public management: An alternative agenda for public administration, Public Policy and Administration, 7, pp. 29-41, (1992); Blair T., Foreword, Masters of the Wired World: Cyberspace Speaks Out, (1999); Booz A., Hamilton, Achieving Universal Access, (2000); Brown G., (1997); E-government: Ready or Not?, (2000); Byrne L., Information Age Government: Delivering the Blair Revolution, (1997); Our Information Age: The Government's Vision, (1998); Modernising Government, (1999); Government to Speed up Introduction of Online Services, (2000); E-government: A Strategic Framework for Public Services in the Information Age, (2000); Government Direct: A Prospectus for the Electronic Delivery of Government Services, (1996); Channels for Electronic Service Delivery: An Outline of the Policy, (1999); Framework for Information Age Government: Digital TV, (2000); Framework for Information Age Government: Websites, (2000); Electronic Service Delivery: Spring 2000, (2000); Information Age Government: Benchmarking Electronic Service Delivery, (2000); Information Age Government Champions, (2001); Collins T., Crash, (1997); Cresson E., Towards an information- and knowledge-based society, Masters of the Wired World: Cyberspace Speaks Out, pp. 355-361, (1999); Currie G., Brown A., Implementation of an IT system in a hospital trust, Public Money and Management, 17, 4, pp. 69-76, (1997); At the Dawn of E-government, (2000); GovernmentOnline: The Commonwealth Government's Strategy, (2000); Skills for the Information Age, (1999); Our Competitive Future: Building the Knowledge-driven Economy, (1998); Closing the Digital Divide: Information and Communication Technologies in Deprived Areas, (2000); Fallon I., The Paper Chase: A Decade of Change at the DSS, (1993); Fitzpatrick T., Critical cyberpolicy: Network technologies, massless citizens, virtual rights, Critical Social Policy, 20, 3, pp. 375-407, (2000); Freeman L., Democracy in the Digital Age, (1997); Frissen P., The Virtual Reality of Informatization in Public Administration, (1994); Frissen P., Snellen I., Informatization Strategies in Public Administration, (1990); Garnham N., Information society as theory or ideology: A critical perspective on technology, education and employment in the information age, Information, Communication and Society, 3, (2000); Golding P., Forthcoming features: Information and communications technologies and the sociology of the future, Sociology, 34, 1, pp. 156-184, (2000); Goodwin S., Blair offers a vision of a new young Britain as party's left clings to old certainties, Independent, (1995); Gore A., Putting people first in the information age, Masters of the Wired World: Cyberspace Speaks Out, pp. 7-18, (1999); Henman P., Does computerisation save governments money?, Information Infrastructure and Policy, 5, 4, pp. 235-252, (1996); Budget 1999 Website, (1999); Hood C., Emerging issues in public administration, Public Administration, 73, pp. 165-183, (1995); Hudson J., Informatization and public administration: A political science perspective, Information, Communication and Society, 2, 3, pp. 318-339, (1999); Hudson J., The prospects for information age government, Wired Welfare? Essays on the Rhetoric and the Reality of E-social Policy, pp. 1-18, (2000); Hudson J., E-galitarianism? Social policy, the information society and the third way, The European Sociological Association Social Policy Research Network's New Technologies and Welfare Stream, (2001); The Quest for Electronic Government: A Defining Vision, (1999); Islam F., Can it be made to compute?, Observer, (2001); Kongas O., E-government - Scandinavian perspective, GC2001 Conference, (2001); It's Time to get Britain Working Again, (1992); New Labour: Because Britain Deserves Better, (1997); Ambitions for Britain, (2001); Loader B., Cyberspace divide: Equality, agency and policy in the information society, Cyberspace Divide: Equality, Agency and Policy in the Information Society, pp. 3-18, (1998); Margetts H., The computerization of social security: The way forward or a step backwards?, Public Administration, 69, pp. 325-343, (1991); Margetts H., Information Technology in Government, (1998); Margetts H., Dunleavy P., Public services on the world markets, Demos Quarterly, 7, pp. 30-32, (1995); Milner H., Hillman J., Pearce N., Thorne M., Piloting the University for Industry: Report of the North East Project, (1999); Government on the Web, (1999); (2001); Nicholson B., Freedom in the Electronic Age, (1999); Information Technology as an Instrument of Public Management Reform: A Study of five OECD Countries, (1998); Improving the Delivery of Government IT Projects, (2000); Report by the Comptroller and Auditor General: Government on the Web, (2000); Peled A., The politics of outsourcing: Bureaucrats, vendors and public information technology (IT) projects, Information Infrastructure and Policy, 6, 4, pp. 209-226, (2000); Pinder A., Keynote session, GC2001 Conference, (2001); E.gov. Electronic Government Services for the 21st Century, (2000); ESD Clearinghouse, (2001); Porat M., Information Economy: Definition and Measurement, (1977); Pratt C., New plan to close \"tech gap, The Tico Times, (2001); Rhodes R., From institutions to dogma: Tradition, eclecticism, and ideology in the study of British public administration, Public Administration Review, 56, pp. 507-516, (1996); Sharpe R., Citizens' Preferences: Measuring the Acceptability of E-channels, (2000); Sims M., Easier said than done, Government Computing, pp. 18-19, (2001); Steward A., E-government in practice, GC2001 Conference, (2001); Tambini D., Universal Internet Access: A Realistic View, (2000); Taylor J., Williams H., Themes and issues in an information polity, Journal of Information Technology, 5, pp. 151-160, (1990); Taylor J., Williams H., Public administration and the information polity, Public Administration, 69, pp. 171-190, (1991); Temple M., New labour's third way: Pragmatism and governance, British Journal of Politics and International Relations, 2, 3, pp. 302-325, (2000); (2001); Toffler A., The Third Wave, (1980); Brown Sets Out Multi-million Pound Programme to Bridge the Digital Divide, (2000); Uttley S., Technology and the Welfare State: The Development of Health Care in Britain and America, (1991); Wills M., E-quality, (2001); Zuboff S., In the Age of the Smart Machine: The Future of Work and Power, (1988)",null,null,"Policy Press",{"$nulls":5},3055736.0,null,null,null,"English","Policy Polit.","Article","Final",null,"Scopus","2-s2.0-0036794354"]
["Kärkkäinen M.; Holmström J.","Kärkkäinen, Mikko (7006531950); Holmström, Jan (7003740924)","7006531950; 7003740924","Wireless product identification: enabler for handling efficiency, customisation and information sharing",2002.0,"Supply Chain Management",7.0,4.0,null,242.0,252.0,10.0,168.0,"10.1108/13598540210438971","https://www.scopus.com/inward/record.uri?eid=2-s2.0-0043003224&doi=10.1108%2f13598540210438971&partnerID=40&md5=bd39a89d52ed22fa1feb26a02b0729d6","Department of Industrial Engineering, Helsinki University of Technology, Helsinki, Finland","Kärkkäinen M., Department of Industrial Engineering, Helsinki University of Technology, Helsinki, Finland; Holmström J., Department of Industrial Engineering, Helsinki University of Technology, Helsinki, Finland","More sophisticated customer demand chains and electronic business pose new challenges to supply chain management. Delivery sizes decrease as a result of more deliveries directly to the point of use. Customers are demanding products and deliveries customised to their specific needs. Also, the information concerning small, customised deliveries has to be shared in volatile supply networks. This article analyses the opportunities of wireless product identification technology in transforming supply chain management. A new concept of item level supply chain management and enabling steps to achieve the benefits are proposed. Innovative companies already use wireless product identification with great benefits in specific functional areas, e.g. manufacturing and warehousing. However, the biggest potential is in supply chain wide solutions, i.e. item level supply chain management.","Customization; E-commerce; Materials handling; Product information; Supply chain management; Wireless technology","Demand; Information Retrieval; Product Development; Storage; Supply Chain Management; Technical Services; Ware Houses; Customer satisfaction; Functions; Information analysis; Warehouses; Delivery sizes; Product identification; Volatile supply networks; Wireless products; Product development",{"$nulls":6},"Ackley S., 93i, RFID and bar code synergy, Tag 2000, (2000); Ashton K., Internet things - MIT, embedded technology and the next Internet revolution, Tag 2000, (2000); Boxall G., The use of RFID for retail supply chain logistics, Tag 2000, (2000); Burnell J., The jury's out in the case for RFID in logistics, Frontline Solutions, 1, 6, pp. 18-27, (2000); Burnell J., Users parlay RFID system success into new business ventures, Frontline Solutions, 1, 5, (2000); Burnell J., Big air Three more RFID standards proposed, Frontline Solutions, 1, 8, (2000); Bushnell R., RFID's wide range of possibilities, Modern Materials Handling, 55, 1, (2000); Butler S., Smart toilets and wired refrigerators, US News & World Report, 126, 22, (1999); Bylinsky G., Hot new technologies for American factories, Fortune, (2000); C-store advance technology in the fast lane, Chain Store Age, 75, 6; Chamberlain G., Shopping Becomes a 'Smart' Experience, (1997); Christianson R., After the merger: Negotiating IT integration, Public Utilities Fortnightly, 138, SPEC. ISSUE, pp. 44-55, (2000); Christopher M., Logistics and Supply Chain Management, (1992); David P.A., Understanding digital technology's evolution and the path of measured productivity growth: Present and future in the mirror of the past, Understanding the Digital Economy, pp. 49-95, (2000); DeJong C.A., Material handling tunes in, Automotive Manufacturing & Production, 110, 7, pp. 66-69, (1998); Dierkx K., Taking Supply Chain Visibility To the Next Level: Powering the Smart Supply Chain, (2000); Feare T., Pump up the volume, Modern Materials Handling, 55, 3, pp. 55-59, (2000); Finkenzeller K., RFID Handbook, pp. 267-269, (1999); Money well spent, Frontline Solutions, 1, 6, pp. 30-31; Fuller J.B., O'Conor J., Rawlinson R., Tailored logistics: The next advantage, Harvard Business Review, 71, 3, pp. 87-98, (1993); Gormley T., Cameron B., Extend for collaboration, Manufacturing systems, 16, 7, (1998); Gould L.S., What you need to know about RFID, Automotive Manufacturing & Production, 112, 2, pp. 46-49, (2000); Hawkes P., Supertag - Stock counting off its trolley, Sensor Review, 14, 3, pp. 23-26, (1994); Hennessy T., The front-end frontier, Progressive Grocer, 79, 4, pp. 93-101, (2000); House R., Stank T., Insights from a logistics partnership, Supply Chain Management: An international Journal, 6, 1, pp. 16-20, (2001); Jacobs B., At last, IT departments can directly track assets to reduce their costs, Frontline Solutions Online RFID Source Book, (2000); Jedd M., Fulfilment: A crucial e-business challenge, Logistics Management and Distribution Report, (2000); Johnson J.R., RFID gets the green light, Warehousing Management, 7, 4, pp. 28-29, (2000); Johnston R.B., Yap A.K.C., Two-dimensional bar code as a medium for electronic data interchange, International Journal of Electronic Commerce, 3, 1, pp. 86-101, (1998); Jones H., Asset management easier with RFID, Automatic ID News, 15, 9, (1999); Jones L., Working without wires, Industrial Distribution, 88, 8, (1999); Kim W.C., Mauborgne R., Strategy, value innovation and the knowledge economy, Sloan Management Review, 40, 3, pp. 41-54, (1999); Kamarainen V., Internet Muuttaa Jakelurakenteita - Elektronisen PäIvittäIstavarakaupan Liiketoimintamallit ja Loppujakelupaikan Valinta, (2000); RFID makers submit standards plan to ISO, Logistics Management and Distribution Report, 39, 5, (2000); Magretta J., The power of virtual integration: An interview with Dell Computer's Michael Dell, Harvard Business Review, 76, 2, pp. 72-84, (1998); Maloyney D., The newest better idea at Ford, Modern Materials Handling, 55, 7, pp. 34-39, (2000); Milner C., How Radio Tags Benefit the Retailer and the Shopper, (1999); How RFID tags speed parts delivery to assembly lines, Modern Materials Handling, 53, 5; Moore B., Bar code or RFID: Which will win the high speed sortation race?, Automatic ID News, 15, 7, pp. 29-30, (1999); Nelms D.W., Move forward on RFID, Air Transport World, 2, 3, (1999); Olliver M., RFID enhances materials handling, Sensor Review, 15, 1, pp. 36-39, (1995); (2000); Philips Semiconductors, (2000); Reid K., Pass and pay technology, NPN, National Petroleum News, 92, 2, (2000); Rickhardson H.L., Packaging for today's demanding fulfilment, Transportation & Distribution, 41, 7, pp. 72-75, (2000); RFID asset management system to US Virgin Islands, Security, 39, 10; Smros J., Holmstrom J., Reaching the consumer through e-grocery VMI, International Journal of Retail & Distribution Management, 28, 2, pp. 55-61, (2000); Smros J Holmstrom J., Kamarainen J., New service opportunities in the e-grocery business, International Journal of Logistics Management, 11, 1, pp. 61-73, (2000); Stebbins J., Motorola to use barcode scanner to net connect, The Australian IT, (2000); Stone T., Hollier R., Electronic data capture and operational performance monitoring: A supply chain perspective, International Journal of Logistics: Research and Applications, 3, 3, pp. 213-226, (2000); Suomi S., Automatic Identification, (1992); Out-of-Stoks... the details, Supermarket Business, 51, 5; Toyryla I., Realising the Potential of Traceability - A Case Study Research on Usage and Impacts of Product Traceability, (1999); Turek N., Cargill: On top of app integration, InformationWeek, 739, pp. 110-112, (1999); Van Hoek R., E-supply chains - Virtually non-existing, Supply Chain Management: An International Journal, 6, 1, pp. 21-24, (2001)",{"$nulls":8},1.3598546E7,null,null,null,"English","Supply Chain Manage.","Article","Final",null,"Scopus","2-s2.0-0043003224"]
["Swartz J.","Swartz, J. (7102058538)",7.102058538E9,"E-commerce and megamachines: Identification, connectivity, and inference engines",2001.0,"Technology in Society",23.0,2.0,null,159.0,175.0,16.0,8.0,"10.1016/S0160-791X(01)00007-0","https://www.scopus.com/inward/record.uri?eid=2-s2.0-0034967084&doi=10.1016%2fS0160-791X%2801%2900007-0&partnerID=40&md5=36f3feb3f1c4a4732f7eed0c5470da26","Symbol Technologies Inc., Mail Stop A-37, Holtsville, NY 11742-1300, One Symbol Plaza, United States","Swartz J., Symbol Technologies Inc., Mail Stop A-37, Holtsville, NY 11742-1300, One Symbol Plaza, United States","Bar-code scanning has enabled the digitized identification of products. At the same time, networked computers, especially portable and wireless (usually hand-held) devices, have facilitated the communication and processing of product-identifying data. Electronic commerce has been driven by the synergy of the technologies of identification and connectivity, which together have been called 'megamachines'. The combination has enabled new connections between scanners and networked databases that are creating entirely new patterns for both purchasers and vendors. For example, consumers using hand-held scanning and wireless net-working devices can select and identify products in the store or at home from the pantry or a printed catalog and simultaneously arrange for prompt and accurate delivery, whether from the store or from distant supplier. The result has been an improved satisfaction of buyer's needs, especially for selection and prompt and accurate fulfillment, and improved performance of vendor's requirements for lower costs and more accurately focused marketing. Clicks and mortar have worked well together. Now a third megamachine, the inference engine, is under development. This will increasingly enable suppliers to go beyond the explicit selections of buyers and to infer and anticipate their needs and wishes. Combining inference engines with the technologies of identification and portable connectivity is beginning to produce another revolution in patterns of commerce. © 2001 Published by Elsevier Science Ltd.","Bar-code; Information utility; Megamachine","Computer networks; Cost effectiveness; Electronic document identification systems; Inference engines; Marketing; Portable equipment; e-commerce; information technology; innovation; Megamachines; Electronic commerce",{"$nulls":6},"Markoff J., The soul of the ultimate machine, The New York Times, (2000); Moore G., Co-founder of Intel. Predicted Accurately in 1967 That the Number of Transistors or Amount of Data Storage on Each Chip Would Double Every Year, or at Least Every 18 Months; Metcalfe R.; Hebb D.O., (1904); Being Digital, (1995)","J. Swartz; Symbol Technologies Inc., Holtsville NY 11742-1300, Mail Stop A-37, United States; email: picker@symbol.com",{"$nulls":7},"0160791X",null,null,null,"English","Technol. Soc.","Article","Final",null,"Scopus","2-s2.0-0034967084"]
["Madhusudan T.","Madhusudan, T. (6506892090)",6.50689209E9,"An experience report on developing an automated web services platform",2005.0,"Information Systems and e-Business Management",3.0,3.0,null,243.0,263.0,20.0,2.0,"10.1007/s10257-005-0020-7","https://www.scopus.com/inward/record.uri?eid=2-s2.0-29444460787&doi=10.1007%2fs10257-005-0020-7&partnerID=40&md5=43936382daef70bcd4ab1863a4713da2","Department of MIS, Eller College of Management, University of Arizona, Tucson, AZ 85721, United States","Madhusudan T., Department of MIS, Eller College of Management, University of Arizona, Tucson, AZ 85721, United States","Web services have attracted significant industry interest as a low-cost and flexible technology alternative to distributed object and proprietary message-oriented methods for delivery of on-demand business processes, enabling intra-organizational systems integration, and in the long term, development of dynamic inter-organizational process networks that may revolutionize B2C and B2B e-commerce. Exploiting this latent potential of web services technology requires the development of automated techniques for scalable and reliable service composition and execution in web service platforms. In this paper, we summarize our experience in developing an architectural framework for web services platforms, called Integrated Service Planning and Execution architecture (ISP & E). The use of recent advances in AI planning, learning and semantic web technologies for service composition, reliable service execution, transaction synthesis, and model-driven deployment of services is discussed. Furthermore, we discuss implications for and research issues in the development of web services based systems to aid e-business. © Springer-Verlag 2005.","AI planning; Interleaving execution; Transactions; Web service composition",{"$nulls":7},"Arenas M., Bertossi L., Hypothetical temporal reasoning in databases, J. Intell. Inform. Syst., 19, 2, pp. 231-259, (2002); Arkin A., Askary S., Fordin S., Jekell W., Kawaguchi K., Orchard D., Pogliani S., Riemer K., Struble S., Takacsi-Nagy P., Trickovic I., Zimek S., Web services choreography interface, (2002); Basu A., Kumar A., Research commentary: Workflow management issues in e-business, Inform. Syst. Res., 13, 1, pp. 1-14, (2002); Benatallah B., Sheng Q.Z., Dumas M., The self-serv environment for web services composition, IEEE Computer, 7, 1, pp. 40-48, (2003); Bertossi L., Arenas M., Ferretti C., SCDBR: An automated reasoner for specification of database updates, J. Intell. Inform. Syst., 10, pp. 253-280, (1998); Blake M.B., Agent-oriented approaches to B2B interoperability, The Knowl. Eng. Rev., 16, 4, pp. 383-388, (2000); Bock C., Gruninger M., PSL: A Semantic domain for flow models. Software and system modeling 2004, (2004); Cabrera F., Copeland G., Freund T., Klein J., Langworthy D., Orchard D., Shewchuk J., Storey T., Web services coordination, (2002); Cardelli L., Davies R., Service combinators for web computing, IEEE Trans. Software Eng., 25, 3, pp. 309-316, (1999); Cardoso J., Quality of service and semantic composition of workflows, (2002); Casati F., Shan M., Dynamic and adaptive composition of e-services, Inform. Syst., 26, 3, pp. 143-163, (2001); Chakraborty D., Perich F., Joshi A., Finin T., Yesha Y., Middleware for mobile information access, Proceedings of the 5th International Workshop on Mobility in Databases and Distributed Systems (MDDS.2002), (2002); Universal description, discovery and integration of web services, (2002); WSDL standards, (2001); Curbera F., Goland Y., Klein J., Leymann F., Roller S., Thatte S., Weerawarana S., Business process execution language, (2002); Davies J., Fensel D., van Harmelen F., Towards the Semantic Web: Ontology-driven Knowledge Management, (2002); Felber P., Chan C., Garofalakis M.N., Rastogi R., Scalable filtering of XML data for web services, IEEE Internet Comput., 7, 1, pp. 49-57, (2003); Ghallab M., Nau D., Traverso P., Automated Planning: Theory and Practice, (2004); Graunke P.T., Findler R.B., Krishnamurthi S., Felleisen M., Modeling web interactions, Proceedings of European Symposium on Programming, (2003); Gruser J., Raschid L., Zadorozhny V., Zhan T., Learning response time for web-sources using query feedback and application in query optimization, VLDB J., 9, 1, pp. 18-37, (2000); Harel D., From play-in scenarios to code: An achievable dream, IEEE Comput., 34, 1, pp. 53-60, (2001); Harel D., Marelly R., Specifying and executing behavioral requirements: The play-in/play-out approach, Software Syst. Model, 2, pp. 82-107, (2003); Java business process management, (2004); Leymann F., Roller D., Schmidt M., Web services and business process management, IBM Systems J., 41, 2, pp. 198-211, (2002); Linden T.A., Representing software designs as partially developed plans, Automating Software Design, pp. 603-625, (1991); Maamar Z., Sheng Q.Z., Benatallah B., On composite web services provisioning in an environment of fixed and mobile computing resources, Information and Technology Management, (2003); Madhusudan T., An intelligent mediator-based framework for enterprise application integration, ASME J. Comput. Inform. Sci. Eng., 4, 4, pp. 294-304, (2004); Madhusudan T., Cha H.S., Uttamsingh N., Mudireddy S.R., Garg A., Sun W., Chirtsabesan B., An experience report on developing an automated web services platform, Proceedings of the Second Workshop on E-Business, (2003); Madhusudan T., Uttamsingh N., A declarative approach for composition of web services in dynamic environments. Decision support systems, (2004); Madhusudan T., Zhao L., Marshall B., A case-based reasoning framework for workflow model management, Data Knowl. Eng., 50, 1, pp. 87-115, (2004); Madhusudan T., Zeng D., Dror M., Decentralized resource management in autonomic systems, Proceedings of IJCAI 2003: Workshop on AI and Autonomic Computing, (2003); Magee J., Kramer J., Concurrency, (1999); McIlraith S., Son T., Adapting Golog for composition of semantic web services, Proceedings of 8th International Conference of Knowledge Representation and Reasoning, (2002); Mennie B., Pagurek D., A runtime composite service creation and deployment infrastructure and its applications in internet security, e-commerce, and software provisioning, Proceedings of the 25th Annual International Computer Software and Applications Conference (COMPSAC 2001), pp. 371-376, (2001); Paolucci M., Kawmura T., Payne T., Sycara K., Semantic matching of web services capabilities, (2002); Papazoglou M.P., Georgakopoulos D., Service-oriented computing, Commun. the ACM, 46, 10, pp. 25-28, (2002); Patel-Schneider P.F., Simeon J., The Yin/Yang web: A unified model for XML syntax and RDF semantics, IEEE Trans. Knowl. Data Eng., 15, 4, pp. 797-812, (2003); Payne T., Proceedings of Semantic Web Services, AAAI Spring Symposium, (2004); Srivastava B., Koehler J., Web service composition-current solutions and open problems, Proceedings of ICAPS.03 Workshop on Planning for Web Services, (2003); Staab S., Web services: Been there, done that?, IEEE Intell. Syst., 18, 1, pp. 72-85, (2003); Tanenbaum A., Steen M.V., Distributed Systems: Principles and Paradigms, (2001); Uchitel S., Kramer J., Magee J., Synthesis of behavioral models from scenarios, IEEE Trans. Software Eng., 29, 2, pp. 99-115, (2003); Wiederhold G., Beringer D., Sample N., Melloul L., Composition of multi-site services, Proceedings of IDPT, (2000); Nie Z., Nambiar U., Vaddi S., Kambhampati S., Mining coverage statistics for web-source selection in a mediator, Proceedings of ACM CIKM, (2002)","T. Madhusudan; Department of MIS, Eller College of Management, University of Arizona, Tucson, AZ 85721, United States; email: madhu@e-mail.arizona.edu",{"$nulls":7},1.6179854E7,null,null,null,"English","Inf. Syst. e-Bus. Manage.","Article","Final",null,"Scopus","2-s2.0-29444460787"]
["Seifert J.W.; Petersen R.E.","Seifert, Jeffrey W. (7201868560); Petersen, Eric R. (7202854850)","7201868560; 7202854850","The promise of all things E? Expectations and challenges of emergent electronic government",2002.0,"Perspectives on Global Development and Technology",1.0,2.0,null,193.0,212.0,19.0,69.0,"10.1163/156915002100419808","https://www.scopus.com/inward/record.uri?eid=2-s2.0-0036034256&doi=10.1163%2f156915002100419808&partnerID=40&md5=c066836ffb99629e33f17d1f83ca4681","Information Science/Technology Plcy., Congressional Research Service, Library of Congress, Washington, DC, United States","Seifert J.W., Information Science/Technology Plcy., Congressional Research Service, Library of Congress, Washington, DC, United States; Petersen R.E., Information Science/Technology Plcy., Congressional Research Service, Library of Congress, Washington, DC, United States","The ambiguous nature of electronic government (e-government) has resulted in hype and confusion, with little systematic consideration of the expectations and limitations of taking government online. This paper seeks to examine the role of e-government in the United States as an evolving process that manifests itself in three distinct sectors: government-to-government, government- to-business, and government-to-citizen. Using this typology as an organizing principle, we show how information technology has the potential to enhance government accessibility and citizen participation. We also show how the move toward a market-focused conceptualization of government information and service delivery raises the potential for blurring citizen and consumer roles, possibly at the cost of a robust, informed, and engaged citizenry.",null,"United States; e-commerce; information technology; political participation; political system",{"$nulls":6},"Atkinson R.D., Ulevich J., Digital Government: The Next Step to Reengineering the Federal Government, (2000); Bacal R., Are Government Customers Really Customers?, (1998); Ballard T.N., Final rules governing IT accessibility issued, Government Executive, (2001); Baum C., Di Maio A., Gartner's Four Phases of E-Government Model, (2000); Breen J., At the dawn of e-government: The citizen as customer, Government Finance Review, (2000); Caterinicchia D., Tough times for 8(a)s, Federal Computer Week, (2000); Cohen S., Eimicke W., The Use of the Internet in Government Service Delivery, (2001); Duffy D., Q and A: Balancing the role of E-government, CNN, (2000); A Survey of Government and the Internet, Digital Democracy, pp. 30-33, (2000); Fountain J.E., Building the Virtual State: Information Technology and Institutional Change, (2001); Frank D., OMB adds guidance on privacy, Federal Computer Week, (2001); Key issues in E-government strategy and management, Research Notes, Key Issues, (2000); Information Security: Weaknesses at 22 Agencies, (1999); Internet Privacy: Agencies' Efforts to Implement OMB's Privacy Policy, (2000); Computer Security: Weaknesses Continue to Place Critical Federal Operations and Assets at Risk, (2001); Gilbert A., President Bush backs E-government, digital signatures, Information Week, (2001); What's E-government? How do we do it?, Government Computer News, (2001); Haque M.S., The diminishing publicness of public service under the current mode of governance, Public Administration Review, 61, 1, pp. 65-82, (2001); Harris J.F., Schwartz J., Anti-drug web site tracks visitors, The Washington Post, (2000); Hasson J., Treasury CIO promotes expanded fed portal, Federal Computer Week, (2001); Heeks R., Bhatnagar S., Understanding success and failure in information age reform, Reinventing Government in the Information Age: International Practice in IT-Enabled Public Sector Reform, (1999); Langlois G., An equal slice of success, Federal Computer Week, (2001); Langlois G., Trimble P.S., Projecting a hip image, Federal Computer Week, (2001); Matthews W., States More Freewheeling in E-Gov, (2000); Matthews W., Setting a course for E-government, Federal Computer Week, (2000); Mello J.P. Jr., Building a Better Bureaucracy, (2000); Moe R.C., The emerging federal quasi government: Issues of management and accountability, Public Administration Review, 61, 3, pp. 290-312, (2001); Moe R.C., Gilmour R.S., Rediscovering principles of public administration: The neglected foundation of public law, Public Administration Review, 55, 2, pp. 135-146, (1995); Moteff J.D., Critical Infrastructures: Background, Policy, and Implementation, (2002); McClure D.L., Testimony Before the Subcommittee on Government Management, Information and Technology, (2000); Nakashima E., Transition on the web: The cyber house rules, The Washington Post, (2001); From Red Tape to Results: Creating a Government That Works Better and Costs Less, (1993); Nunno R.M., Electronic Signatures: Technology Developments and Legislative Issues, (2002); O'Hara C., Trimble P.S., Agencies fill IT pay gaps, Federal Computer Week, (2001); Peckenpaugh J., Council issues online procurement rules, Government Executive Magazine, (2001); Relyea H.C., Electronic Government: A Conceptual Overview, (2002); Relyea H.C., Paperwork Reduction Act Reauthorization and Government Information Management Issues, (2002); Relyea H.C., The Privacy Act: Emerging Issues and Related Legislation, (2002); Saldarini K., Feeling the consequences of procurement reform, Government Executive Magazine, (2000); Schneider F.B., Trust In Cyberspace, (1999); Seifert J.W., Government Information Technology Management: Past and Future Issues (The Clinger-Cohen Act), (2002); Seifert J.W., Federal Chief Information Officer (CIO): Opportunities and Challenges, (2002); Smith M.S., Internet Privacy: An Analysis of Technology and Policy Issues, (2002); Sprehe T., States show feds the way, Federal Computer Week, (2001); Strate J.M., Parrish C.J., Elder C.D., Ford C., Life span civic development and voting participation, American Political Science Review, 83, (1989); Trattner J., E-GOV revolution transforms federal operations, Government Executive Magazine, (2000); Government at the Brink: Urgent Federal Government Management Problems Facing the Bush Administration, 1, (2000); Falling Through the Net: Toward Digital Inclusion, (2000); White B., Federal IT for the disabled gets boost, The Washington Post, (2001)",null,null,"Brill Academic Publishers",{"$nulls":5},1.56915E7,null,"PGDTA",null,"English","Perspect. Global Dev.Technol.","Article","Final",null,"Scopus","2-s2.0-0036034256"]
["Shan T.C.; Hua W.W.","Shan, Tony Chao (57223611858); Hua, Winnie Wei (12800101400)","57223611858; 12800101400","Service-oriented solution framework for internet banking",2006.0,"International Journal of Web Services Research",3.0,1.0,null,29.0,48.0,19.0,33.0,"10.4018/jwsr.2006010102","https://www.scopus.com/inward/record.uri?eid=2-s2.0-33645509269&doi=10.4018%2fjwsr.2006010102&partnerID=40&md5=5890449ab6671bfb1173e72a7bddfddd","Wachovia Corporation, United States; CTS Inc., United States; Wachovia Bank, United States; Greater Charlotte Rational User Group, United States; CTS Inc., United States","Shan T.C., Wachovia Corporation, United States, Wachovia Bank, United States, Greater Charlotte Rational User Group, United States; Hua W.W., CTS Inc., United States, CTS Inc., United States","This paper describes a service-oriented solution framework designed for Internet banking in financial, services. A pragmatic approach is developed to help migrate conventional, n-tier e-commerce systems to a service-oriented computing paradigm, composed of Service-Oriented Architecture (SOA), Integration (SOI), Process (SOP), and Management (SOM). This comprehensive framework comprises Service Patterns, Architecture Process, Hybrid Methodology, Service-Oriented Enterprise Model, and Solution Platform. E-business patterns are applied to categorize diverse online services, which form the baseline for subsequent selection justifications of appropriate technologies, products/tools, and infrastructure. A multilevel architecture process is developed to cope with the architecture complexity in a disciplined way. Furthermore, a hybrid methodology is designed to leverage the benefits of both top-down and bottom-up approaches, in which a converging layer is conceived to incorporate the latest technologies such as portal, process orchestration, Web services, service aggregations, business rule engine, and so forth. In the enterprise model, common business functionalities are built as shared services to be reused across lines of business as well as delivery channels, and the Internet channel-specific SOA is defined by applying the hybrid methodology, Finally, a holistic solution platform is introduced to address the key design artifacts in the implementation of service-oriented solutions. Challenges of conflicting specifications and immature cutting-edge technologies are also discussed in the context. Copyright © 2006, Idea Group Inc.","Application software; Architecture types; Bottom-up design; Conceptual model; Electronic commerce; Enterprise modeling; Internet commerce; IS development methodologies; Online banking; Online collaboration; Software design; Systems development techniques","Competitive intelligence; Computer software; Computer supported cooperative work; Electronic commerce; Online systems; Software engineering; Application software; Architecture types; Conceptual model; IS development methodologies; Systems development techniques; Internet",{"$nulls":6},"Albin S., The Art of Software Architecture: Design Methods and Techniques, (2003); Bass L., Clements P., Kazman R., Software Architecture in Practice, (1998); Broemmer D., J2EE Best Practices: Java Design Patterns, Automation, and Performance, (2002); Carbone J.A., IT Architecture Toolkit, (2004); Dustdar S., Gall H., Schmidt R., Web services for groupware in distributed and mobile collaboration, Proceedings of 12th IEEE Euromicro Conference on Parallel, Distributed and Network-based Processing (PDP 2004), (2004); Erl T., Service-oriented Architecture: A Field Guide to Integrating XML and Web Services, (2004); Fowler M., Patterns of Enterprise Application Architecture, (2003); Frankel D.S., Model Driven Architecture: Applying MDA to Enterprise Computing, (2003); Giaglis G.M., A taxonomy of business process modeling and information systems modeling techniques, International Journal of Flexible Manufacturing Systems, 13, 2, pp. 209-228, (2001); Gronmo R., Solheim I., Towards modeling Web service composition in UML, Proceedings of the 2nd International Workshop on Web Services: Modeling, Architecture and Infrastructure (WSMAI 2004), pp. 72-86, (2004); Gulzar M., Gaueshan K., Practical J2EE Application Architecture, (2003); Extended Enterprise Architecture Framework, (2004); Jorstad I., Thanh D.V., Dustdar S., An analysis of service continuity in mobile services, Proceedings of the 2nd International Workshop on Distributed and Mobile Collaboration (DMC 2004), pp. 121-126, (2004); Krachten P., The Rational Unified Process: An Introduction (3rd Ed.), (2003); McGovern J., Java Web Services Architecture, (2003); McGovern J., Ambler S.W., Stevens M.E., Linn J., Sharan V., Jo E.K., A Practical Guide to Enterprise Architecture, (2003); Model Driven Architecture, (2002); Schekkerman J., How to Survive in the Jungle of Enterprise Architecture Framework: Creating or Choosing an Enterprise Architecture Framework, (2003); Sessions R., Sickler J.V., Software Fortresses: Modeling Enterprise Architectures, (2003); Shan T.C., Hua W.W., High-performance data caching mechanisms, Proceedings of 2005 Web Information and System Application Conference (WISA 2005), (2005); Shan T.C., Et al., WebSphere MQ Solutions in A Microsoft .NET Environment, (2004); Shan T.C., Et al., WebSphere Business Integration for SAP, (2004); The Open Group Architecture Framework Version 8 (\"Enterprise Edition\"), (2003); Zachman J., Zachman Framework, (2002); Zimmermann O., Tomlinson M., Peuser S., Perspectives on Web Services, (2003)",null,null,"IGI Global",{"$nulls":5},1.5457362E7,null,null,null,"English","Int. J. Web Serv. Res.","Article","Final",null,"Scopus","2-s2.0-33645509269"]
["Zwass V.","Zwass, Vladimir (8232569300)",8.2325693E9,"The web-internet compound as the infrastructure of digital government",2006.0,"Business Process Management Journal",12.0,1.0,null,7.0,12.0,5.0,9.0,"10.1108/14637150610643715","https://www.scopus.com/inward/record.uri?eid=2-s2.0-31644446724&doi=10.1108%2f14637150610643715&partnerID=40&md5=7591edb8b90efb11fefa41b027246255","Computer Science and Management Information Systems, Fairleigh Dickinson University, Teaneck, New Jersey, United States","Zwass V., Computer Science and Management Information Systems, Fairleigh Dickinson University, Teaneck, New Jersey, United States","Purpose – To provide the framework for digital government in its e-government and e-democracy aspects. Design/methodology/approach – Using the aspects-and-opportunities framework of the internet-web compound, the nodal aspects of the continuing and potential technologically-based change known as digital government are discussed. Reallocation of certain government functions to the market becomes newly attractive economically in the presence of the web as marketplace. The web as a broadly accessible medium and a forum offers new opportunities in digital democracy. The utilitarian aspects of the internet-web, those of the universal telecommunications network, delivery vehicle, and a common development platform, render the compound a new societal infrastructure, with the consequent benefits and exposures. The opportunities, as well as vulnerabilities, need to be the focus of information specialists as technologists and as citizens. Findings – Opportunities are surfaced to reallocate the functions of e-government from the hierarchy to the market using e-commerce methods and tools. Research limitations/implications – Vulnerabilities of the web-internet combine in the application to e-government are not investigated here. Practical implications – Move from the bureaucratic to market-oriented structures is implied. Originality/value – A broad application of e-commerce facilities to digital government is presented within a disciplined framework. © 2006, Emerald Group Publishing Limited","Digital communication systems; Internet; Societal organization; Telecommunications; Worldwide web",{"$nulls":7},"Andrews D., Preece J., Turoff M., A conceptual framework for demographic groups resistant to online community interaction, International Journal of Electronic Commerce, 6, 3, pp. 9-24, (2002); Becker T., Rating the impact of new technologies on democracy, Communications of the ACM, 44, 1, pp. 39-43, (2001); Brown J.S., Duguid P., The Social Life of Information, (2002); Castells M., The Rise of the Network Society, (1996); Cummings J., Behind dean surge: a gang of bloggers and webmasters, The Wall Street Journal, pp. 1-14, (2003); United Nations Conference on Trade and Development (UNCTAD), United Nations, New York and Geneva, available at: http://r0.unctad.org/ecommerce/ecommerce_en/edr02_en.htm (accessed November 18, 2002)., (2002); United Nations Department for Economic and Social Affairs, available at: www.unpan.org/discover.asp (accessed October 3, 2003)., (2003); Habermas J., The Structural Transformation of the Public Sphere: An Inquiry into a Category of a Bourgeois Society, (1991); Larsen K.R.T., A taxonomy of antecedents of information systems success: variable analysis studies, Journal of Management Information Systems, 20, 2, pp. 169-246, (2003); Malone T.W., Benjamin R.I., Yates J., Electronic markets and electronic hierarchies: effects of information technology on market structure and corporate strategies, Communications of the ACM, 30, 6, pp. 484-497, (1987); Miller J.Z., The Mind and the Market: Capitalism in Modern European Thought, (2002); Mylonopoulos N.A., Doukidis G.I., Introduction to the special issue: mobile business: technological pluralism, social assimilation, and growth, International Journal of Electronic Commerce, 8, 1, pp. 5-22, (2003); Rheingold H., Smart Mobs: The Next Social Revolution, (2002); Simon L.D., Netpolicy.com: Public Agenda for the Digital World, (2000); Van de Ven A.H., Poole M.S., Explaining development and change in organizations, Academy of Management Review, 20, 3, pp. 510-540, (1995); Williamson O., Markets and Hierarchies: Analysis and Antitrust Implications, (1975); Zwass V., Electronic commerce: structures and issues, International Journal of Electronic Commerce, 1, 1, pp. 3-23, (1996); Zwass V., Electronic commerce and organizational innovation: aspects and opportunities, International Journal of Electronic Commerce, 7, 3, pp. 7-37, (2003)",{"$nulls":8},1.4637154E7,null,null,null,"English","Bus. Process Manage. J.","Article","Final",null,"Scopus","2-s2.0-31644446724"]
["Chen Y.-C.; Fan G.-M.","Chen, Yen-Cheng (7601447119); Fan, Gang-Ming (12041218900)","7601447119; 12041218900","Location-based push services in Wireless LAN hotspots",2006.0,"Journal of Internet Technology",7.0,1.0,null,59.0,67.0,8.0,1.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-31544472314&partnerID=40&md5=652e1d350e77806252adda862c2c6cfa","Department of Information Management, National Chi Nan University, Taiwan, Taiwan","Chen Y.-C., Department of Information Management, National Chi Nan University, Taiwan, Taiwan; Fan G.-M., Department of Information Management, National Chi Nan University, Taiwan, Taiwan","Due to the small cell sizes in Wireless LANs (WLANs), it is practical to develop location dependent services based upon the awareness of the WLAN access points (AP) that mobile clients currently access. One possible E-commerce application in public WLAN hotspots is the delivery of location dependent information to mobile users. In this paper, we will discuss how to provide location-based push services in WLAN hotspots. It will be shown that the location of a mobile client can be determined effectively from the SNMP traps sent by APs. APs identify each mobile client by its MAC address. To deliver information to the mobile client, we also have to know the current IP address of the mobile client. We propose an effective technique for mapping MAC addresses into IP addresses. Two web service frameworks are then proposed to enable location-based push services in WLAN hotspots.","Location-based service; Push service; SNMP; Wireless LAN","Electronic commerce; Mobile telecommunication systems; Wireless telecommunication systems; Location-based service; Push service; SNMP; Wireless LAN; Local area networks",{"$nulls":6},"Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications, (1999); Case J., Fedor M., Schoffstall M., Davin J., Simple network management protocol, RFC, 1157, (1990); Location technologies for GSM, GPRS and WCDMA networks, White Paper, (2001); Hightower J., Borriello G., A survey and taxonomy of location systems for ubiquitous computing, Extended Paper from Computer, 34, 8 AUGUST, pp. 57-66, (2001); Bahl P., Padmanabhan V.N., RADAR: An in-building RF-based user location and tracking system, Proc. IEEE INFOCOM 2000, 2, pp. 775-784, (2000); Castro P., Chiu P., Kremenek T., Muntz R., A probabilistic location service for wireless network environments, Proc. Ubicomp 2001, pp. 18-24, (2001); Smailagic A., Kogan D., Location sensing and privacy in a context-aware computing environment, IEEE Wireless Communications, 9, 5, (2002); Pahlavan K., Krishnamurthy P., Principles of Wireless Networks: A Unified Approach, (2002); Prasithsangaree P., Krishnamurthy P., Chrysanthis P.K., On indoor position location with wireless LANs, Proc. the 13th IEEE Int'l Symposium on Personal, Indoor, and Mobile Radio Communications, (2002); Koo S.G.M., Rosenberg C., Chan H.H., Lee Y.C., Location discovery in enterprise-based wireless networks: Implementation and applications, Proc. the 2nd IEEE Workshop on Applications and Services in Wireless Networks (ASWN 2002), (2002); Rigney C., Willens S., Rubens A., Simpson W., Remote Authentication Dial in User Service (RADIUS), RFC, 2865, (2000); Koo S.G.M., Rosenberg C., Chan H., Lee Y.C., Location discovery in enterprise-based wireless networks: Case studies and applications, Annals of Telecommunications; McCloghrie K., Rose T., Management information base for network management of TCP/IP -based internets, RFC, 1213, (1991); Cisco Aironet 350 Series Access Points; Intel PRO/Wireless 201 IB LAN Access Point; WAP11 - Instant Wireless Network Access Point; Simple Object Access Protocol; AdventNet SNMP API 4, (2005); WAP Push Access Protocol Specification, (1999); Service Aspect: Push Service; Stage L, (2003)","Y.-C. Chen; Department of Information Management, National Chi Nan University, Taiwan, Taiwan; email: ycchen@ncnu.edu.tw",{"$nulls":7},1.6079264E7,null,null,null,"English","J. Internet Technol.","Article","Final",null,"Scopus","2-s2.0-31544472314"]
["Brousseau E.","Brousseau, Eric (55917030600)",5.59170306E10,"The governance of transactions by commercial intermediaries: An analysis of the re-engineering of intermediation by electronic commerce",2002.0,"International Journal of Phytoremediation",21.0,1.0,null,353.0,374.0,21.0,41.0,"10.1080/1357151021000010355","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85066225455&doi=10.1080%2f1357151021000010355&partnerID=40&md5=029bbcf57b347fdbf95ccccba13ac18d","Universite de Paris X and IUF, Nanterre Cedex, F-92001, FORUM, Batiment K200 avenue de la rÂepublique, France","Brousseau E., Universite de Paris X and IUF, Nanterre Cedex, F-92001, FORUM, Batiment K200 avenue de la rÂepublique, France","Efficiency arguments explain why commercial intermediaries exist and will continue to be involved in the exchanges despite the spread of digital networks. Commercial intermediaries provide producers and consumers with a set of information, logistic, securization and insurance (and liquidity) services. By bundling these services and by dedicating assets and learning capabilities to their production, commercial intermediaries allow transaction costs to be reduced. Digital networks per se cannot allow transacting parties to benefit from such efficient providers of intermediation services. Rather than establishing direct relationships among producers and consumers, the Internet will support a re-organization of existing intermediation chains, because traditional intermediaries will reinforce their ability to provide these service by using ITs. The analysis of the role of commercial intermediaries thus leads to a better understanding of the future of e-commerce. In turn, e-commerce provides New-Institutional Economics with a stimulating case study. © 2002, Copyright Taylor & Francis Group, LLC.","Bundled services; Commercial intermediation; Digital economy; Distribution channels; E-commerce; Transaction costs",{"$nulls":7},"Avery C., Resnick P., Zeckhauser R., Roles for Electronic Brokers, In Toward a Competitive Telecommunication Industry. Selected Papers from the 1994 Telecommunications Policy Research Conference, NJ: Lawrence Erlbaum Associates, pp. 289-304, (1995); Bailey J.P., Electronic Commerce: Prices and Consumer Issues for Three Products: Books, Compact Discs, and Software, DSTI/ICCP/Ie (98)4, (1998); Bailey J.P., Intermediation and Electronic Markets: Aggregation and Pricing in Internet Commerce,\" Ph. D. Dissertation, Technology, Management and Policy, Massachusetts Institute of Technology, (1998); Bell D., The Coming of Post Industrial Society, (1973); Benghozi P.-J., Relations interentreprises et nouveaux modèles d'affaires,\" Revue Economique, Special issue \"Economie de l'Internet, 52, pp. 165-190, (2001); Benjamin R., Wigand R., Electronic Markets and Virtual Value Chains on the Information Superhighway, Sloan Management Review, pp. 62-72, (1995); Betancourt R.R., Gautschi D.A., Two Essential Characteristics of Retail Markets and Their Economic Consequences, Journal of Economic Behavior and Organization, 21, 3, pp. 277-294, (1993); Biglaiser G., Middlemen as Experts, Rand Journal of Economics, 24, 2, pp. 212-223, (1993); Biglaiser G., Friedman J.W., Middlemen as Guarantors of Quality, International Journal of Industrial Organization, 12, 4, pp. 509-531, (1994); Brousseau E., L'économie des contrats, technologies de l'information et coordination inter entreprise, (1993); Brousseau E., What Institutions to Organize Electronic Commerce: Private Institutions and the Organization of Markets, Economics of Innovation and New Technology, 9, 3, pp. 245-273, (2000); Brousseau E., Commerce Electronique: Ce que disent les chiffres et ce qu'il faudrait savoir, Economie et Statistiques, 9, 10, pp. 147-170, (2000); Brousseau E., E-Commerce in France: Did Early Adoption Prevented the development?, The Information Society, 19, 1, (2003); Brousseau E., Curien N., Economie de l'Internet,\" Revue Economique, Special Issue, (2001); Brynjolfsson E., Smith M.D., Frictionless Commerce? A Comparison of Internet and Conventional Retailers, Management Science, 46, 4, pp. 563-585, (2000); Clemons E.K., Row M., Mckesson Drug Co.: A Case Study of Economost, a Strategic Information System, Journal of Management Information Systems, 5, 1, pp. 36-50, (1988); Glower R., Leijonhufvud A., The Coordination of Economic Activities: A Keynesian Perspective, American Economic Review, 65, pp. 182-188, (1975); Crane A., Information Age Will Curb Inflation, The Financial Times, (1997); Dang N'Guyen G., Les systèmes de reservation aérienne et l'économie des réseaux, Mutations des Télécommunications, des Industries et des Marchés, pp. 231-261, (1996); Dang N'Guyen G., Du commerce électronique à l'intermediation électronique, Technologies de l'Information, Organisation et Performances Economiques, Paris: Commissariat Général du Plan, pp. 231-308, (1999); Diamond D.W., Financial Intermediation and Delegated Monitoring, Review of Economic Studies, 51, 3, pp. 393-414, (1984); Elkin-Koren N., Salzberger E.M., The Economic Analysis of Cyberspace: Challenges Posed by Cyberspace to Legal Theory and Legal Rules, International Review of Law and Economics, 19, pp. 553-582, (2000); Ellison G., Fisher Ellison S., Search, Obfuscation, and Price Elasticities on the Internet, (2000); Faulhaber G., Noam E., Tasley R., Services in Transition, the Impact of ICTs on the Service Sector, (1986); Faverie M., France's Experience with the Minitel: Lessons for Electronic Commerce over the Internet, OECD, Working Party on the Information Economy. DSTI/ICCP/Ie 97, (1998); Friberg R., Ganslandt M., Sandstrom M., Pricing Strategies in E-Commerce: Bricks vs. Clicks; Gensollen M., Internet: Marché électronique ou réseaux commerciaux?,\" Revue Economique, Special Issue \"Economie de l'Internet, 52, pp. 97-118, (2001); Cyber Commerce: Internet Tsunami, Mimeo, (1997); Hackett S.C., A Comparative Analysis of Merchant and Broker Intermediation, Journal of Economic Behavior and Organization, 18, 3, pp. 299-315, (1992); Hagel J., Armstrong A.G., Boston N.G., MA: Harvard Business School Press, (1997); Hagel J., Singer M., NetWork, Shaping Markets when Customers Make the Rules, (1999); Johnson E.J., Moe W., Fader P., Bellman S., Lohse J., On the Depth and Dynamics of World Wide Web Shopping Behavior, (2000); Jonscher C., Information Resources and Economic Productivity, Information Economics and Policy, 1, pp. 13-35, (1983); Jonscher C., An Economic Study of the Information Technology Revolution, Information Technology And The Corporation Of The 1990s. Research Studies, pp. 5-42, (1994); Kokuryo J., Takeda K., The Role of 'Platform Businesses, Intermediaries Of Electronic Commerce, (1995); Lamberton D.M., The Information Revolution, (1974); Lancaster K., Variety Equity and Efficiency, (1979); Lee H.G., Do Electronic Marketplaces Lower the Price of Goods?, Communications of the ACM, 41, 1, pp. 73-80, (1998); Lewis M.K., Financial Intermediaries, Elgar Reference Collection. International Library of Critical Writings in Economics, 43. Aldershot, (1995); Licoppe C., Pratiques et trajectoires de la grande distribution dans le commerce alimentaire sur internet: Vers un autre modèle de coordination pour le commerce électronique?,\", Revue Economique, Special Issue, \"Economie de l'Internet, 52, pp. 191-212, (2001); Lin C., Risk Pooling and Intermediate Trading Agents, Canadian Journal of Economics, 14, 2, pp. 261-275, (1981); Lorentz F., Commerce électronique: Une nouvelle donne pour les consommateurs, les entreprises, les citoyens et les pouvoirs publics,\" Rapport du Groupe de Travail sur le Commerce Electronique, Ministère de l'Economie, des Finances et de l'Industrie, (1998); Machlup F., The Production and Distribution of Knowledge in the United States, (1962); Malone T.W., Yates J., Benjamin R.Y., Electronic Markets and Electronic Hierarchies, Communications of the ACM, 30, 6, pp. 484-497, (1987); Michael S.C., Competition in Organizational Form: Mail Order versus Retail Stores, 1910-40, Journal of Economic Behavior and Organization, 23, 3, pp. 269-286, (1994); Mookherjee D., Reichelstein S., Dominant Strategy Implementation of Bayesian Incentive Compatible Allocation Rules, Journal of Economic Theory, 56, 2, pp. 378-399, (1992); Myerson R.B., Satterthwaite M.A., Efficient Mechanisms for Bilateral Trading, Journal of Economic Theory, 29, 2, pp. 265-281, (1983); Measuring Electronic Commerce, (1997); Business to Consumer Electronic Commerce: Survey of Status and Issues, (1997); Electronic Commerce. Opportunities and Challenges for the Government (The Sacher Report), (1997); The Economic and Social Impacts of Electronic Commerce: Preliminary Findings and Research Agenda, (2000); Porat M., The Information Economy: Definition and Measurement, (1977); Spulber D.F., Bargaining and Regulation with Asymmetric Information about Demand and Supply, Journal of Economic Theory, 44, 2, pp. 251-268, (1988); Spulber D.F., Market Microstructure and Intermediation, Journal of Economic Perspectives, 10, 3, pp. 135-152, (1996); A Survey of Electronic Commerce, pp. 1-18, (1998); US Census Bureau of the Department of Commerce, Retail e-Commerce Sales in First Quarter 2002, (2002); Wallis J., North D.C., Measuring the Transaction Sector in the American Economy, Long Term Factorsin American Economic Growth, (1986); White E., No Comparison. Shopping 'Bots' Were Supposed to Unleash Brutal Price Wars. Why Haven't They?, Wall Street Journal, (2000); Wigand R.T., Electronic Commerce: Definition, Theory, and Context, The Information Society, 13, pp. 1-16, (1997); Long Boom, Special Issue, (1997); Yardeni E., Economic Consequences of the Internet, (1996); Zwass V., Structure and Macro-Level Impacts of Electronic Commerce: From Technological Infrastructure to Electronic Marketplaces, Emerging Information Technologies, (1998)","E. Brousseau; Universite de Paris X and IUF, Nanterre Cedex, F-92001, FORUM, Batiment K200 avenue de la rÂepublique, France; email: eric@brousseau.info.",{"$nulls":7},1.5226514E7,null,null,null,"English","Int. J. Phytorem.","Article","Final",null,"Scopus","2-s2.0-85066225455"]
["Slater A.","Slater, Alan (7102987861)",7.102987861E9,"Specification for a dynamic vehicle routing and scheduling system",2002.0,"International Journal of Transport Management",1.0,1.0,null,29.0,40.0,11.0,35.0,"10.1016/S1471-4051(01)00004-0","https://www.scopus.com/inward/record.uri?eid=2-s2.0-0036473376&doi=10.1016%2fS1471-4051%2801%2900004-0&partnerID=40&md5=ddd1bed4c108cbf1abaa5b293a543af2","Added Value Logistics Consulting Ltd., Grosvenor House, Altrincham, WA14 2QG, 45 The Downs, United Kingdom","Slater A., Added Value Logistics Consulting Ltd., Grosvenor House, Altrincham, WA14 2QG, 45 The Downs, United Kingdom","In an e-commerce environment, order fulfilment is driven by customer demands and expectations. A dynamic vehicle routing and scheduling system may be specified which allows e-commerce customers to select their own delivery Time Windows and have these confirmed on-line as they place their order. The methodology is based upon demand forecasting, which leads to the generation of phantom orders and phantom routes. Subsequently, actual orders substitute for phantom orders in an on-line customer order process. The routing and scheduling method includes using both parallel tour-building and parallel insertion algorithms. Customer service levels are confirmed using GPS tracking and tracing, and a feedback loop uses expert systems or artificial intelligence as an input to the demand forecasting data to restart the whole process. © 2002 Elsevier Science Ltd. All rights reserved.","GPS tracking and tracing; Heuristics; Parallel insertion algorithms; Parallel tour-building Algorithms; Time Windows; Transport planning; Vehicle routing and scheduling","Algorithms; Artificial intelligence; Feedback; Scheduling; Vehicles; Vehicle routing systems; Electronic commerce",{"$nulls":6},"Bagchi P.K., Nag B.N., Dynamic vehicle scheduling: An expert systems approach, International Journal of Physical Distribution and Logistics Management, 21, 2, pp. 10-18, (1991); Benton W.C., Rossetti M.D., The vehicle scheduling problem with intermittent customer demands, Computers and Operations Research, 19, 6, pp. 521-531, (1992); Beulens A.J.M., Robust vehicle routing DSS and road networks on a European scale, Annals of Operations Research, 55, pp. 489-509, (1995); Bodin L., Golden B., Assad A., Ball M., Routing and scheduling of vehicles and crews: The state of the art, Computers and Operations Research, 10, 2, pp. 63-211, (1983); Christofides N., Mingozzi A., Toth P., Exact algorithms for the vehicle routing problem, Mathematical Programming, 20, pp. 255-282, (1981); Christofides N., Mingozzi A., Toth P., State space relaxation procedures for the computation of bounds to routing problems, Networks, 11, pp. 145-164, (1981); Clark G., Wright J.W., Scheduling of vehicles from a central depot to a number of delivery points, Operational Research, 11, pp. 568-581, (1963); Crainic T.G., Laporte G., Fleet Management and Logistics, (1998); Dantzig G.B., Ramser H.J., The truck dispatching problem, Management Science, 6, 1, pp. 80-91, (1959); Desrosiers J., Dumas Y., Soumis F., A dynamic programming solution of the large scale single vehicle dial-a-ride problem with Time Windows, American Journal of Management Science, 6, pp. 301-325, (1986); Dror M., Modelling vehicle routing with uncertain demands as a stochastic program: Properties of the corresponding solution, European Journal of Operational Research, 64, 3, pp. 432-441, (1993); Duhamel C., Potvin J.Y., Rousseau J.M., A Tabu search heuristic for the vehicle routing problem with backhaul and Time Windows, Transportation Science, 31, 1, pp. 49-59, (1997); Goetschalckx M., A decision support system for dynamic truck despatching, International Journal of Physical Distribution and Materials Management, pp. 34-42, (1988); Haines G.H., Wolfe R.N., Alternative approaches to demand responsive scheduling algorithms, Transportation Research A, 16, pp. 43-54, (1982); Haughton M.A., Stenger A.J., Semi-variable delivery routes and the efficiency of outbound logistics, International Journal of Physical Distribution and Logistics Management, 27, 8, pp. 459-474, (1997); Jaw J., Odoni A., Psaraftis H.N., Wilson N., A heuristics algorithm for the multivehicle advanced request dial-a-ride problem with Time Windows, Transportation Resources B, 20, pp. 243-257, (1986); Lee T.R., Ueng J.H., A study of vehicle routing problems with load-balancing, International Journal of Physical Distribution and Logistics Management, 29, 10, pp. 646-658, (1999); Lenstra J.L., Kan A.H.G., Complexity of vehicle routing and scheduling problems, Networks, 11, pp. 221-227, (1981); Liu F.H., Shen S.Y., The fleet size and mix vehicle routing problem with Time Windows, Journal of the Operations Research Society, 50, 7, pp. 721-732, (1999); Lowe D., The Transport Manager's and Operator's Handbook 2000, (2000); Magnanti T.L., Combinatorial optimization and vehicle fleet planning: Perspectives and prospects, Networks, 11, pp. 179-213, (1981); Computers in Vehicle Scheduling, (1969); Potvin J.Y., Rousseau J.M., A parallel route building algorithm for the vehicle routing and scheduling problem with Time Windows, European Journal of Operational Research, 66, pp. 331-340, (1993); Potvin J.Y., The travelling salesman problem: A neural network perspective, ORSA Journal on Computing, 5, pp. 328-348, (1993); Powell W.B., A comparative review of alternative algorithms for the dynamic vehicle allocation problem, Vehicle Routing Methods and Studies, (1988); Powell W.B., On languages for dynamic resource scheduling problems, Fleet Management and Logistics, (1999); Powell W.B., Jaillet P., Odoni A., Stochastic and dynamic networks and routing, Network Routing, (1995); Psaraftis H.N., A dynamic programming solution for the single vehicle many-to-many immediate request dial-a-ride problem, Transportation Science, 14, 8, pp. 130-154, (1980); Psaraftis H.N., An exact algorithm for the single vehicle many-to-many dial-a-ride problem with Time Windows, Transportation Science, 17, 3, pp. 351-357, (1983); Psaraftis H.N., Dynamic vehicle routing: Status and prospects, Annals of Operations Research, 61, pp. 143-164, (1995); Psaraftis N.N., Solomon M.M., Megnanti T.L., Kim T., Routing and scheduling on a shoreline with release times, Management Science, 36, 2, pp. 212-223, (1990); Renauld J., Laporte G., Boctor F.F., A Tabu search heuristic for the multi-depot vehicle routing problem, Computers and Operations Research, 23, 3, pp. 229-235, (1996); Rochat Y., Sement F., A Tabu search approach for delivering pet food and flour in Switzerland, Journal of the Operations Research Society, 45, 11, pp. 1233-1246, (1994); Ross G.T., Soland R.M., A branch and bound algorithm for the generalised assignment problem, Mathematical Programming, 8, pp. 91-103, (1975); Russell R.A., Hybrid heuristics for the vehicle routing and scheduling problem with Time Windows, Transportation Science, 29, pp. 156-166, (1995); Slater A.G., Vehicle load planning, International Journal of Physical Distribution and Materials Management, 19, 2, pp. 79-99, (1979); Solomon M.M., Algorithms for the vehicle routing and scheduling problems with Time Window constraints, Operations Research, 35, 2, pp. 254-265, (1987); Sussams J.E., Efficient Road Transport Scheduling, (1971); Thongiah S.R., Potvin J.Y., Sun T., Heuristic approaches to vehicle routing with back hauls and Time Windows, Computers and Operations Research, 23, 11, pp. 1043-1057, (1996); Tyagi M.S., A practical method for truck despatching problems, Journal of the Operations Research Society of Japan, 10, 3, pp. 351-357, (1983); Walters C.D.J., Vehicle scheduling problems with uncertainty and omitted customers, Journal of the Operations Research Society, 40, 12, pp. 1099-1108, (1989); Walters C.D.J., Expert systems for vehicle scheduling, Journal of the Operations Research Society, 41, 6, pp. 505-515, (1990)","A. Slater; Added Value Logistics Consul. Ltd., Grosvenor House, Altrincham, WA14 2QG, 45 The Downs, United Kingdom; email: alanslater@avlc.co.uk",{"$nulls":7},1.4714051E7,null,null,null,"English","Int. J. Transp. Manage.","Article","Final",null,"Scopus","2-s2.0-0036473376"]
["Vatovec Krmac E.","Vatovec Krmac, Evelin (55609456700)",5.56094567E10,"Modern information communication technologies and tools for supply chain management",2005.0,"Promet - Traffic and Transportation",17.0,6.0,null,303.0,309.0,6.0,0.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-30344434934&partnerID=40&md5=72ae177994de3ba7069fef50175c7ee6","University of Ljubljana, Faculty of Maritime Studies and Transportation, SI-6320 Portorož, Pot pomorščakov 4, Slovenia","Vatovec Krmac E., University of Ljubljana, Faculty of Maritime Studies and Transportation, SI-6320 Portorož, Pot pomorščakov 4, Slovenia","The paper presents the most important supply chain technlogies, including the latest applications and software tools used by companies that operate in the transportation and logistics fields. The primary goals of these technologies are information exchanges within and between organizations and/or managing supply chain related data and activities. New electronic logistics applications are increasingly being moved off proprietary systems and private networks onto the internet. With the e-commerce market exploding, portals are becoming a key element in bringing together an enterprise's employees, business partners, and customers - the principle actors of every supply chain - through one interface, accessible via the internet. Because of this capacity they are sometimes called e- supply chain mega portals.","Information and communication technology; Software systems; Supply chain; Supply chain management","information management; logistics; software",{"$nulls":6},"Fliedner G., CPFR: An emerging supply chain tool, Industrial Management & Data Systems, 103, 1, pp. 14-21, (2003); Gabbert P., Globalization and the Computing Curriculum, Inroads - The SIGCSE Bulletin, 35, 2, pp. 61-64, (2003); Knorr E., The New Enterprise Portal!, pp. 42-52, (2004); Lambert D.M., Cooper M.C., Pagh J.D., Supply Chain Management: Implementation Issues and Research Opportunities, The International Journal of Logistics Management, 9, 2, pp. 1-19, (1998); Light B., Holland C.P., Wills K., ERP and best of breed: A comparative analysis, Bussines Process Management Journal, 7, 3, pp. 216-224, (2001); McIvor R., Humphreys P., The implications of electronic B2B intermediaries for the buyer-supplier interface, International Journal of Operations & Production Management, 24, 3, pp. 241-269, (2004); Obank A., Leaney P., Roberts S., Data Management within a manufacturing organization, Integrated Manufacturing Systems, 6, 3, pp. 37-43, (1995); Razi M.A., Tarn J.M., An applied model for improving inventory management in ERP systems, Logistics Information Management, 16, 2, pp. 114-124, (2003); \"Meeting the Manufacturing Challenge\", 20, 11, pp. 28-30, (2004); Verwijmeren M., Software component architecture in supply chain management, Computers in Industry, 53, pp. 165-178, (2003); Winter R., Strauch B., Information Requirements Engineering for Data Warehouse Systems, ACM Symphosium on Applied Computing, (2004)","E. Vatovec Krmac; University of Ljubljana, Faculty of Maritime Studies and Transportation, SI-6320 Portorož, Pot pomorščakov 4, Slovenia; email: evelin.vatovec@fpp.edu",null,"Faculty of Transport and Traffic Engineering",{"$nulls":5},3535320.0,null,"POMEE",null,"English","Promet Traffic Traffico","Article","Final",null,"Scopus","2-s2.0-30344434934"]
["Lau H.C.W.; Lee C.K.M.; Ho G.T.S.; Choy K.L.; Leung B.P.K.","Lau, H.C.W. (7201497757); Lee, C.K.M. (24468281700); Ho, G.T.S. (8348673600); Choy, K.L. (7005477047); Leung, Bartholomew P.K. (7102271840)","7201497757; 24468281700; 8348673600; 7005477047; 7102271840","Design of an adaptable logistics workflow management system for e-business",2006.0,"International Journal of Agile Systems and Management",1.0,4.0,null,329.0,345.0,16.0,1.0,"10.1504/IJASM.2006.011627","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84881251882&doi=10.1504%2fIJASM.2006.011627&partnerID=40&md5=86ad0cdea299f337f8d26505c72f2fb8","Department of Industrial and Systems Engineering, Hong Kong Polytechnic University, Hunghom, Hong Kong; Department of Applied Mathematics, Hong Kong Polytechnic University, Hunghom, Hong Kong","Lau H.C.W., Department of Industrial and Systems Engineering, Hong Kong Polytechnic University, Hunghom, Hong Kong; Lee C.K.M., Department of Industrial and Systems Engineering, Hong Kong Polytechnic University, Hunghom, Hong Kong; Ho G.T.S., Department of Industrial and Systems Engineering, Hong Kong Polytechnic University, Hunghom, Hong Kong; Choy K.L., Department of Industrial and Systems Engineering, Hong Kong Polytechnic University, Hunghom, Hong Kong; Leung B.P.K., Department of Applied Mathematics, Hong Kong Polytechnic University, Hunghom, Hong Kong","Owing to the rapid development of information technology, there is a growing interest in e-commerce and trading on the internet. However, the downturns of e-business in recent years have indicated that the supply chain dimension of e-business has not received the attention it deserves. If the basic logistics performance is not assured, the advanced technologies and well-defined business infrastructures of e-business applications will never save an e-company; the company will not make profit without the physical support for the concepts behind the virtual store. To meet the existing turbulent and volatile global and virtual marketplace, it is necessary for the supply chain network to equip itself with some degree of flexibility and ability to adapt to unforeseeable changes in the market. This paper focuses on the supply chain and logistics dimensions of e-business and suggests practical approaches and models to avoid their poor management, thereby improving productivity and cost-effectiveness to support the virtual stores. © 2006 Inderscience Enterprises Ltd.","e-business; supply chain management; supply chain model; value chain",{"$nulls":7},"Agrawal R., Srikant R., Fast algorithms for mining association rules, Proceedings of the 20th VLDB Conference, pp. 478-499, (1994); Alt R., Zimmermann H., Preface: Introduction to special section-business models, Electronic Markets, 11, 1, pp. 3-9, (2001); Ba S., Whinston A.B., Zhang H., Small digital business in electronic markets: A blueprint for survival, Electronic Markets, 11, 1, pp. 59-63, (2001); Bertino E., Ferrari E., XML and data integration, IEEE Internet Computing, 5, 6, (2001); Cingil I., Dogac A., An architecture for supply chain integration and automation on the internet, Distributed and Parallel Databases, 10, pp. 59-102, (2001); Conway D.G., Supplier affiliated extended supply chain backbones, Information Systems Frontiers, 2, 1, pp. 57-64, (2000); Datta A., Thomas H., The cube data model: A conceptual model and algebra for online analytical processing in data warehouses, Decision Support Systems, December, 27, 3, pp. 289-301, (1999); Georgakopoulos D., Hornick M., Sheth A., An overview of workflow management-from process modeling to workflow automation infrastructure, Distrib. Parallel Databases, 3, 2, pp. 119-153, (1995); Gunasekaran A., Marri H.B., McGaughey R.E., Nebhwani M.D., E-commerce and its impacts on operation management, International Journal of Production Economics, 75, pp. 185-197, (2002); Hoek R., E-supply chains-virtually non-existing, Supply Chain Management: An International Journal, 6, 1, pp. 21-28, (2001); 21st Century Manufacturing Enterprise Strategy: An Industry Led View, (1991); Inmon W.H., 'Data Warehouse - A Perspective of Data over Time, pp. 370-390, (1992); Kotok A., When the Going Gets Tough: Real World XML, (2001); Lau H.C.W., Ip R.W.L., Chan F.T.S., An intelligent information infrastructure to support knowledge discovery, Expert Systems with Applications, 22, pp. 1-10, (2002); Lau H.C.W., Jiang B., Lee W.B., Lau K.H., Development of an intelligent data mining system for dispersed manufacturing network, Expert Systems, 18, 4, (2001); Leenders M., Nollet J., Ellram L.M., Adapting purchasing to supply chain management, International Journal of Physical Distribution and Logistic Management, 23, 4, pp. 42-54, (1993); Leung B.P.K., Spiring F.A., The inverted beta loss function: Properties and applications, IIE Transactions, 34, 12, pp. 1101-1109, (2002); Ma C., Chou D.C., Yen D.C., Data warehousing, technology assessment and management, Industrial Management and Data Systems, 3, pp. 125-134, (2000); Malaga R.A., Consumer costs in electronic commerce: An empirical examination of electronic versus traditional markets, Journal of Organizational Computing and Electronic Commerce, 11, 1, pp. 47-58, (2001); Maskell B., The age of agile manufacturing, Supply Chain Management, An International Journal, 6, 1, pp. 5-11, (2001); Mason-Jones R., Towill D.R., Total cycle time compression and the agile supply chain dynamics, International Journal of Logistics Management, 8, 2, pp. 47-62, (1999); Moreno M.D.R., Kearney P., Integrating AI planning techniques with workflow management system, Knowledge Based Systems, 15, 5-6, pp. 285-291, (2002); Nagel R., Understanding Agile Competition, A Quick Look at How to Make Your Company Agile, (1993); O'Daniel T., A value-added model for e-commerce, Electronic Markets, 11, 1, pp. 37-43, (2001); Pastore M., Experienced Internet Shopper Satisfied with Online Shopping, (2000); Rigby C., Day M., Forrester P., Burnett J., Agile supply: Rethinking systems thinking, system practice, International Journal of Agile Management Systems, 3, 2, pp. 178-186, (2000); Shim J.P., Warkentin M., Courtney J.F., Power D.J., Sharda R., Carlsson C., Past, present, and future of decision support technology, Decision Support Systems, 33, pp. 111-126, (2002); Tamas M., Mismatched strategies: The weak link in the supply chain, Supply Chain Management: An International Journal, 5, 4, pp. 171-175, (2000); Vickers M., Models from mars, Business Week, pp. 58-59, (2000); Volkmann C., Tokarski K.O., Growth strategies for young e-ventures through structured collaboration, International Journal of Services Technology and Management, 7, 1, pp. 68-84, (2006); Walsh N., What Is XML, (1998); Yung S.K., Yang C.C., Intelligent multi-agents for supply chain management, IEEE SMC 1999 Conference Proceedings, 2, pp. 528-533, (1999)","H.C.W. Lau; Department of Industrial and Systems Engineering, Hong Kong Polytechnic University, Hunghom, Hong Kong; email: mfhenry@inet.polyu.edu.hk",null,"Inderscience Publishers",{"$nulls":5},1.7419174E7,null,null,null,"English","Int. J. Agil. Syst. Manag.","Article","Final",null,"Scopus","2-s2.0-84881251882"]
["Power D.","Power, Damien (7101806777)",7.101806777E9,"Adoption of supply chain management-enabling technologies in SMEs: The view from the top vs. the view from the middle",2006.0,"International Journal of Value Chain Management",1.0,1.0,null,64.0,93.0,29.0,22.0,"10.1504/IJVCM.2006.009024","https://www.scopus.com/inward/record.uri?eid=2-s2.0-34447635204&doi=10.1504%2fIJVCM.2006.009024&partnerID=40&md5=f71b86755da70ae46aa3c54e3e0e22c2","Department of Management, Faculty of Economics and Commerce, University of Melbourne, Parkville, VIC 3010, Australia","Power D., Department of Management, Faculty of Economics and Commerce, University of Melbourne, Parkville, VIC 3010, Australia","This paper uses data from two separate surveys conducted within Australian SMEs in the Fast Moving Consumer Goods sector. The perceptions of two groups - Senior Managers (CEOs, Managing Directors, General Managers) and Functional Managers (Marketing, Operations, Logistics, Financial Controller, etc.) - are compared in relation to the benefits accruing from the use of Business-to-Business (B2B) enabling technologies for the management of supply chains. The evidence from this research indicates that there are significant differences in perception of contribution to performance, understanding and knowledge of the implications and potential of B2B e-commerce technologies between these two groups. Compared with managers of functional areas, senior managers are found to be more negative about their contribution to business outcomes, and they generally display a lower level of understanding of their potential and of the implications of adoption. The implications of the research are important for the theory of innovation adoption and diffusion, as in this case, the extent of adoption appears to be influenced by this gap in perceptions. As such, the characteristics of the innovation and of the two separate groups in organisations, which will have some role to play in the adoption decision, are being influenced by another important dimension - the strategic implications of the innovation. The observation of this interaction provides some insight into the dynamics of adoption of technology-related innovations in SMEs. Copyright © 2006 Inderscience Enterprises Ltd.","E-commerce; Information technology; Innovation; SMEs",{"$nulls":7},"Abcede A., EDI, internet connect as data goes electronic, National Petroleum News, 89, 11, pp. 110-114, (1997); Adams E.J., Second coming for electronic data interchange, World Trade, 10, 11, pp. 36-38, (1997); Ballou R.H., Gilbert S.M., Mukherjee A., New managerial challenges from supply chain opportunities, Industrial Marketing Management, 29, 1, pp. 7-18, (2000); Barber N.F., Will EDI survive?, Transportation and Distribution, 38, 9, pp. 39-45, (1997); Barua A., Lee B., An economic analysis of the introduction of an electronic data interchange system, Information Systems Research, 8, 4, pp. 398-422, (1997); Baum D., Transcending EDI, Info World, 19, 12, pp. 67-68, (1997); Belyea K., How electrolux takes cost out of the chain, Journal of Purchasing, 128, 5, pp. 59-65, (2000); Bianchi C., Bivona E., Commercial and financial policies in family firms: The small business growth management flight simulator, Simulation and Gaming, 31, 2, pp. 197-229, (2000); 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Lee H.L., So K.C., Tang C.S., The value of information sharing in a two-level supply chain, Management Science, 46, 5, pp. 626-643, (2000); Lockett N.J., Brown D.H., eClusters: The potential for the emergence of digital enterprise communities enabled by one or more intermediaries in SME's, Knowledge and Process Management, 7, 3, pp. 196-206, (2000); Lummus R.R., Okra R.J., Abler K.L., Strategic supply chain planning, Production and Inventory Management Journal, 39, 3, pp. 49-58, (1998); McCormack K., What really works, IIE Solutions, 31, 8, pp. 30-32, (1999); McCutcheon D., Stuart I.F., Issues in the choice of supplier alliance partners, Journal of Operations Management, 18, 3, pp. 279-301, (1999); McIntyre P., Australian CPA, 70, 10, pp. 52-53, (2000); Magretta J., Dell M., The power of virtual integration: An interview with Dell computers' Michael Dell, Harvard Business Review, 76, 2, pp. 72-84, (1998); Manasco B., The emergence of networked markets, American Productivity and Quality Centre (APQC), (2000); Min H., Galle W.P., Electronic commerce usage in business-to-business purchasing, International Journal of Operations and Production Management, 19, 9-10, pp. 909-921, (1999); Mohta P., Conducting EDI over the internet, AS/400 Systems Management, pp. 46-48, (1997); Monczka R.M., Petersen K.J., Handfield R.B., Ragatz G.L., Success factors in strategic supplier alliances: The buying company perspective, Decision Sciences, 29, 3, pp. 553-577, (1998); Narasimhan R., Jayaram J., Causal linkages in supply chain management: An exploratory study of North American manufacturing firms, Decision Sciences, 29, 3, pp. 579-605, (1998); Survey of Technology and E-commerce in Australian Small and Medium Business, (2000); Taking the Plunge 2000 - Sink or Swim - Small Business Attitudes to Electronic Commerce, (2000); New S.J., A framework for analyzing supply chain improvement, International Journal of Operations and Production Management, 16, 4, pp. 19-35, (1996); Parnell C., Supply chain management in the soft goods industry, Apparel Industry Magazine, 59, 6, (1998); Power D.J., Application of established and emerging B2B e-commerce technologies: Australian empirical evidence, Integrated Manufacturing Systems - Special Issue on Enabling Supply Chain Integration Using Internet Technologies, 13, 8, pp. 573-585, (2002); Power D.J., Sohal A.S., Implementation and usage of electronic commerce in managing the supply chain: A comparative study of ten Australian companies, Benchmarking - An International Journal, 9, 2, pp. 190-208, (2002); Radjou N., Manufacturing deconstructed, (2000); Ramamurthy K., Premkumar G., Crum M.R., Organizational and inter-organizational determinants of EDI diffusion and organizational performance: A causal model, Journal of Organizational Computing and Electronic Commerce, 9, 4, pp. 253-285, (1999); Rogers E.M., Diffusion of Innovations, (1983); Segev A., Porra A., Roldan M., Internet-based EDI strategy, Decision Support Systems, 21, 3, pp. 157-170, (1997); Shin H., Collier D.A., Wilson D.D., Supply management orientation and supplier/buyer performance, Journal of Operations Management, 18, 3, pp. 317-333, (2000); Sim S., The evolution of the internet, Journal of the Institution of British Telecommunications Engineers, Part 1, 1, pp. 31-39, (2000); Staw B.M., Epstein L.A., What bandwagons bring: Effects of popular management techniques on corporate performance, reputation and CEO pay, Administrative Science Quarterly, 45, 3, pp. 523-556, (2000); Sterman J., Modelling managerial behaviour: Misperception of feedback in a dynamic decision making environment, Management Science, 35, 3, pp. 321-339, (1989); Stuart F.I., Supplier alliance success and failure - a longitudinal dyadic perspective, International Journal of Operations and Production Management, 17, 5-6, pp. 539-557, (1997); Stuart F.I., McCutcheon D., Sustaining strategic supplier alliances: Profiling the dynamic requirements for continued development, International Journal of Operations and Production Management, 16, 10, pp. 5-21, (1996); Suzuki Y., Williams L.R., Analysis of EDI resistance behaviour, Transportation Journal, 37, 4, pp. 36-44, (1998); Tait D., Make strong relationships a priority, Canadian Manager, 23, 1, pp. 21-28, (1998); Tan K.C., Kannan V.R., Handfield R.B., Ghosh S., Supply chain management: An empirical study of its impact on performance, International Journal of Operations and Production Management, 19, 9-10, pp. 1034-1052, (1999); Tornatzky L.G., Fleischer M., The Process of Technological Innovation, (1990); Tornatzky L.G., Klein K.J., Innovation characteristics and innovation adoption-implementation: A meta-analysis of findings, IEEE Transactions on Engineering Management, 29, 1, pp. 28-45, (1982); Truman G., Integration in electronic exchange environments, Journal of Management Information Systems, 17, 1, pp. 209-244, (2000); Tucker D., Jones L., Leveraging the power of the internet for optimal supplier sourcing, International Journal of Physical Distribution and Logistics Management, 30, 3-4, pp. 255-267, (2000); Upin E.B., Beckwith M.J., Jennings C.L., Chen B.Y., Schaeffer K.B., B2B: Building technology bridges outside the four walls of the enterprise, Robertson Stephens Research, (2000); Westhead K., Mortenson C., Moore J., Rice A.W., New economy: Forget the WEB, make way for the GRID, Deutsche Bank Global Technology Research, (2000); Weston R., Manufacturers turn to net for improved supply chain, Computerworld, 31, 44, (1997); Whipple J.M., Frankel R., Strategic alliance success factors, The Journal of Supply Chain Management, 36, 3, pp. 21-28, (2000); Wolfe R.A., Organizational innovation: Review, critique and suggested research directions, Journal of Management Studies, 31, 3, pp. 405-431, (1994); Wood A., Extending the supply chain: Strengthening links with IT, Chemical Week, 159, 25, (1997)","D. Power; Department of Management, Faculty of Economics and Commerce, University of Melbourne, Parkville, VIC 3010, Australia; email: damien@unimelb.edu.au",null,"Inderscience Publishers",{"$nulls":5},1.7415357E7,null,null,null,"English","Int. J. Value Chain Manage.","Article","Final",null,"Scopus","2-s2.0-34447635204"]
["Koehne J.; Howard J.","Koehne, J. (7003609300); Howard, J. (56327836000)","7003609300; 56327836000","Property assist: A new approach to the delivery of property information to South Australia",2001.0,"Cartography",30.0,1.0,null,59.0,68.0,9.0,0.0,"10.1080/00690805.2001.9714136","https://www.scopus.com/inward/record.uri?eid=2-s2.0-0034881423&doi=10.1080%2f00690805.2001.9714136&partnerID=40&md5=bd4694f1f4b7847ae1f23615e49f7101","Envrn. and Geographic Information, Department for Environment Heritage, Australia","Koehne J., Envrn. and Geographic Information, Department for Environment Heritage, Australia; Howard J., Envrn. and Geographic Information, Department for Environment Heritage, Australia","Developed by Environmental and Geographic Information, a division of the Department for Environment and Heritage, PropertyAssist provides a new and innovative mechanism for the delivery of property information in South Australia. Taking advantage of current technology, PropertyAssist ensures the delivery of Government information remains relevant in today's modern business environment. The design of PropertyAssist allows the user to enquire across a range of state held databases via the Internet, returning details of title, sales, plans and valuation. The spatial data display feature of the system allows the user to view locality maps and survey plan images online. The ease of access to property information provides benefits to the general public and business community, including real estate agents, conveyancers, valuers, surveyors and others, by placing information at the user's fingertips. Users can purchase information through a secure, on-line credit card payment facility developed in conjunction with Camtech, a leading South Australian company providing e-commerce solutions. The initial Property Assist prototype, InfoShop, was awarded the 1998 Government Technology Productivity Gold Award.",null,"(South); Australia; data management; database; Internet; property market; spatial data",{"$nulls":7},"J. Koehne; Envrn. and Geographic Information, Department for Environment Heritage, Australia; email: koehne.joanne@saugov.sa.gov.au",null,"Mapping Sciences Institute Australia",{"$nulls":5},690805.0,null,null,null,"English","Cartography","Article","Final",null,"Scopus","2-s2.0-0034881423"]
["So H.W.T.; Gunasekaran A.; Chung W.W.C.","So, Harry W.T. (35816311600); Gunasekaran, Angappa (56238759300); Chung, Walter W.C. (7401983286)","35816311600; 56238759300; 7401983286","Last Mile fulfilment strategy for competitive advantage",2006.0,"International Journal of Logistics Systems and Management",2.0,4.0,null,404.0,418.0,14.0,4.0,"10.1504/IJLSM.2006.010384","https://www.scopus.com/inward/record.uri?eid=2-s2.0-33747364514&doi=10.1504%2fIJLSM.2006.010384&partnerID=40&md5=45c485abe4f9ed50bfb520028abc1178","Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong; Department of Management, Charlton College of Business, University of Massachusetts-Dartmouth, North Dartmouth, MA 02747-2300, United States","So H.W.T., Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong; Gunasekaran A., Department of Management, Charlton College of Business, University of Massachusetts-Dartmouth, North Dartmouth, MA 02747-2300, United States; Chung W.W.C., Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong","One of the biggest challenges in e-business is the so-called 'Last Mile', the fulfilment service for the customer. It is particularly difficult to combine profitability and a high service level for competitive advantage. This paper defines and describes a model of the Last Mile advantage from the perspective of competition. The Last Mile advantage is the innovation in combining inbound and outbound logistics within the supply network to bring together fragmented buyers and sellers. The model outlines two businesses - architecture and infrastructure businesses - both of which are responsible for managing different competitive forces for the firm's competitiveness. Essentially, all firms can be evaluated based on these two businesses, which can be used to translate corporate strategy into project initiatives that add value to and control value in the firm. This paper also outlines the different Last Mile configuration and initiatives for those players located within the value system. Copyright © 2006 Inderscience Enterprises Ltd.","E-business; E-commerce; Last Mile advantage; Order fulfilment process; Production network; Supply chain management",{"$nulls":7},"Busby J.S., Fan I.-S., The extended manufacturing enterprise: Its nature and its needs, International Journal of Technology Management, Special Issue on 'Manufacturing Technology: Diffusion, Implementation and Management', 8, 3-5, pp. 294-308, (1993); Christensen C.M., The Innovator's Dilemma, (1997); Garud R., Kumaraswamy A., Changing competitive dynamics in network industries: An exploration of Sun Microsystems open systems strategy, Strategic Management Journal, 14, 5, pp. 351-369, (1993); Lee H.L., Whang S., Winning the Last Mile of e-commerce, MIT Sloan Management Review Summer, (2001); Meyer M.H., Lehnerd A.P., The Power of Product Platform - Building Value and Cost Leadership, (1997); Parolini C., The Value Net - The Tool for Competitive Strategy, (2000); Porter M.E., Competitive Advantage: Creating and Sustaining Superior Performance, (1985); Porter M.E., On Competition, (1998); Porter M.E., Strategy and the internet, Harvard Business Review, pp. 63-78, (2001); Wiendahl H.-P., Helms L., Lutz S., Supply net - New methods for capacity flexibilization in production network, Proceedings of 15th International Conference on Computer-Aided Production Engineering, pp. 609-614, (1999); Wiendahl H.-P., Helms L., Lutz S., Management of variable production networks, Strategic Production Network, (2002); A Technology Paper: Last Mile Broadband Technologies, (2001)","W.W.C. Chung; Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong; email: Walter.Chung@inet.polyu.edu.hk",null,"Inderscience Publishers",{"$nulls":5},1.7427967E7,null,null,null,"English","Int. J. Logist. Syst. Manage.","Article","Final",null,"Scopus","2-s2.0-33747364514"]
["Cook D.P.; Dave D.S.","Cook, David P. (36905599500); Dave, Dinesh S. (7005408190)","36905599500; 7005408190","Structural elements of online service product quality",2004.0,"International Journal of Business Performance Management",6.0,2.0,null,189.0,207.0,18.0,1.0,"10.1504/IJBPM.2004.005015","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84946441860&doi=10.1504%2fIJBPM.2004.005015&partnerID=40&md5=fb0f252eb8b26faeaeffd34247c61ad7","Department of Information Systems & Decision Sciences, College of Business and Public Administration, Old Dominion University, Norfolk, Virginia 23529, United States; Department of Information Technology & Operations Management, John A. Walker College of Business, Appalachian State University, Boone, North Carolina 28608, United States","Cook D.P., Department of Information Systems & Decision Sciences, College of Business and Public Administration, Old Dominion University, Norfolk, Virginia 23529, United States; Dave D.S., Department of Information Technology & Operations Management, John A. Walker College of Business, Appalachian State University, Boone, North Carolina 28608, United States","The Internet is at the centre of a whirlwind of economic hype and activity with more and more adults going online both at home and work. An increasing proportion of retail sales is being conducted online, and is expected to continue to increase for the foreseeable future. The combination of the proliferation of online retail sales and the recent shakeout of internet firms, is a clear indicator that significant opportunities exist online; but not without lurking dangers. What differentiates the successful internet player from the also ran? This article posits that one differentiating factor is the ability to successfully deliver high quality service products. A service quality stack is developed that demonstrates the interplay between the service product delivery system, service quality judgment criteria, and an underlying infrastructure based on the following empirically identified elements: methods standardisation, customer contact, and customer involvement. © 2004 Inderscience Enterprises Ltd.","e-commerce; framework; quality; service",{"$nulls":7},"Anders G., E-commerce: revamping the model – at your service: how Amazon tries to keep its customers satisfied, The Wall Street Journal, (2000); Bulkeley W.M., Carlton J., E-tail gets derailed: how web upstarts misjudged the game, The Wallstreet Journal, (2000); Chase R.B., Where does the customer fit in a service operation?, Harvard Business Review, 56, 6, pp. 137-142, (1978); Cook D.P., Goh C.H., Chung C.H., Service typologies: a state of the art survey, Production and Operations Management, 8, 3, pp. 318-338, (1999); Creswell J., First cold front, Fortune, pp. 24-25, (2001); Dillman D.A., Mail and Telephone Surveys: The Total Design Method, (1978); Florian E., Dead and (mostly) gone, Fortune, pp. 46-47, (2001); Flynn B.B., Et al., Empirical research methods in operations management, Journal of Operations Management, 9, 2, pp. 250-284, (1990); Greenspan R., Two-Thirds Hit the Net, (2002); Heim G.R., Sinha K.K., A product-process matrix for electronic B2C operations, Journal of Service Research, 3, 4, pp. 286-299, (2001); Hof R.D., Suddenly, Amazon’s books look better, BusinessWeek, (2000); ICSA/TARP, ICSA/TARP Benchmarking Study of Electronic Customer Care, (2001); Kotler P., Armstrong G., Principles of Marketing, (1994); Lovelock C.H., Classifying services to gain strategic marketing insights, Journal of Marketing, 47, 3, pp. 9-20, (1983); Lovelock C.H., Young R.F., Young, look to consumers to increase productivity, Harvard Business Review, 57, 3, pp. 168-178, (1979); Mullaney T.J., Break out the black ink, BusinessWeek, pp. 74-76, (2002); Parasuraman A., Zeithaml V.A., Berry L.L., A conceptual model of service quality and its implications for future research, Journal of Marketing, 49, pp. 41-50, (1985); Parasuraman A., Zeithaml V.A., Berry L.L., SERVQUAL: a multiple-item scale for measuring consumer perceptions of service quality, Journal of Retailing, 64, 1, pp. 12-40, (1988); Piesto N., King C., United States Department of Commerce News, (2002); Rust R.T., Zahorik A.J., Keiningham T.L., Services Marketing, (1996); Ryans A.B., Wittink D.R., The marketing of services: categorization with implications for strategy, Contemporary Marketing Thoughts; Schmenner R.W., How can service businesses survive and prosper?, Sloan Management Review, 27, 3, pp. 21-32, (1986); Sharma S., Applied Multivariate Techniques, (1996); Shostack G.L., Breaking free from product marketing, Journal of Marketing, 41, pp. 73-80, (1977); Silpakit P., Fisk R.P., Participatizing the service encounter: a theoretical framework, Services Marketing in a Changing Environment",{"$nulls":8},1.3684892E7,null,null,null,"English","Int. J. Bus. Perform. Manage.","Article","Final",null,"Scopus","2-s2.0-84946441860"]
["Siikavirta H.; Punakivi M.; Kärkkäinen M.; Linnanen L.","Siikavirta, Hanne (15027482500); Punakivi, Mikko (6506144327); Kärkkäinen, Mikko (7006531950); Linnanen, Lassi (6507834628)","15027482500; 6506144327; 7006531950; 6507834628","Effects of e-commerce on greenhouse gas emissions: A case study of grocery home delivery in Finland",2002.0,"Journal of Industrial Ecology",6.0,2.0,null,83.0,97.0,14.0,109.0,"10.1162/108819802763471807","https://www.scopus.com/inward/record.uri?eid=2-s2.0-0036524934&doi=10.1162%2f108819802763471807&partnerID=40&md5=ecfbc8441f682f67229b057a9edd832d","Helsinki University of Technology, Dept. of Indust. Eng. and Management, FIN-02015 TKK Espoo, POB 9500, Finland; Helsinki University of Technology, Dept. of Indust. Eng. and Management, Espoo, Finland","Siikavirta H., Helsinki University of Technology, Dept. of Indust. Eng. and Management, FIN-02015 TKK Espoo, POB 9500, Finland, Helsinki University of Technology, Dept. of Indust. Eng. and Management, Espoo, Finland; Punakivi M., Helsinki University of Technology, Dept. of Indust. Eng. and Management, Espoo, Finland; Kärkkäinen M., Helsinki University of Technology, Dept. of Indust. Eng. and Management, Espoo, Finland; Linnanen L., Helsinki University of Technology, Dept. of Indust. Eng. and Management, Espoo, Finland","In this article, we present a literature review of the general and environmental effects of e-commerce in various parts of the demand-supply chain. These are further translated into effects on greenhouse gas (GHG) emissions in the food production and consumption system. The literature study revealed many opportunities for e-commerce to reduce GHG emissions in the food production and consumption system. Some possibly negative effects were also identified. Electronic grocery shopping (e-grocery) home delivery service was chosen as the subject of a case study because of its direct and indirect potential for reducing the GHG emissions in the food production and consumption system. GHG emission reduction potential through the implementation of various e-grocery home delivery strategies was quantified. Depending on the home delivery model used, it is possible to reduce the GHG emissions generated by grocery shopping by 18% to 87% compared with the situation in which household members go to the store themselves. We estimate that the maximum theoretical potential of e-grocery home delivery service for reducing the GHG emissions of Finland is roughly 0.3% to 1.3%; however, the current and estimated future market potential is much smaller, because the estimated market share of e-grocery services is only 10% by 2005. Narrowing the gap between the theoretical and the actual potential requires a model that would simultaneously provide additional value to the consumer and be profitable to companies. To be able to achieve significant reductions in GHG emissions, system-level innovations and changes are required. Further research is needed before conclusions can be reached as to whether e-commerce and e-grocery are useful tools in that respect.","Distribution; E-grocery; Food consumption; Food production; Greenhouse gas (GHG) emissions; Logistics","Food products; Gas emissions; Greenhouse effect; Food production; Electronic commerce",{"$nulls":6},"Aarnio P., Hamekoski K., Koskentalo T., Ilmanlaatu Pääkaupunkiseudulla Vuonna 1997. [The Quality of the Air in the Metropolitan Area of Helsinki in 1997.], (1998); Banks A., The intelligent chip: Tracking perishables (RFID tagging), Sainsbury's perspective, The InTelligent Supply Chain - Recent Impacts of IT on the Supply Chain, (2001); Blomqvist M., Materials and capacity management, Operations Management Course, (2000); Boxall G., The use of RFID for retail supply chain logistics, Tag 2000, (2000); Brooksher D., E-commerce and logistics, Traffic World, 260, 7, (1999); Burnell J., The jury's out in the case for RFID in logistics, Frontline Solutions, 1, 6, pp. 18-27, (2000); Buzzell R.D., Ortmeyer G., Channel partnerships streamline distribution, Sloan Management Review, 36, 3, pp. 85-97, (1995); Cairns S., Promises and problems: Using GIS to analyse shopping travel, Journal of Transport Geography, 6, 4, pp. 273-284, (1998); Cairns S., Home Delivery: Environmental Solution or Disaster?, (1999); Cameron B., Gormely T., Extend for collaboration, Manufacturing Systems, 16, 7, (1998); (2001); Deering K., Dedicated infrastructure: The only way to deliver a compelling value proposition to North American consumers, Conference Handout at CIES: Supply Chain for E-Commerce and Home Delivery in the Food Industry, (2000); DeJong C.A., Material handling tunes in, Automotive Manufacturing and Production, 110, 7, pp. 66-69, (1998); (2001); Fisher M.L., What is the right supply chain for your product?, Harvard Business Review, 75, 2, pp. 105-116, (1997); Granfelt J., Lehtinen U., Hynynen A., The Shopping Habits of Consumers 1994 and Problems Associated with Shopping (in Finnish), (1995); Gurin R., Integration tightens ERP, supply chain connections, Automatic I.D. News, 15, 8, pp. 1-3, (1999); Harari O., The logistics of success, Management Review, 88, 6, pp. 24-27, (1999); Heikkonen H., Valttila J., (2000); Hurst E., E-commerce and the Environment, (2001); Third Assessment Report - Climate Change 2001: Mitigation, (2001); James P., Hopkinson P., Virtual traffic: E-commerce, transport, and distribution, Digital Futures: Living in a Dot.com World, (2001); Jedd M., Fulfillment: A crucial e-business challenge, Logistics Management and Distribution Report, 39, 4, (2000); Jones H., Asset management easier with RFID, Automatic I.D. News, 15, 9, (1999); Joseph S., Garnett T., Response to \"Virtual traffic: E-commerce, transport, and distribution, Digital Futures: Living in a Dot.com World, (2001); Kiely T., Business processes: Consider outsourcing, Harvard Business Review, 75, 3, pp. 11-12, (1997); Kasvihuonekaasujen Vähentämistarpeet ja - Mahdollisuudet Suomessa. [National Climate Strategy, Government Report to Parliament.], (2001); Levy D., Lean production in an international supply chain, Sloan Management Review, 38, 2, pp. 94-101, (1997); Lindstrom T., (2000); Magretta J., The power of virtual integration: An interview with Dell Computer's Michael Dell, Harvard Business Review, 76, 2, pp. 72-84, (1998); Makela K., (1999); Narus J., Anderson J., Rethinking distribution: Adaptive channels, Harvard Business Review, 74, 4, pp. 112-120, (1996); Nelms D.W., Move forward on RFID, Air Transport World, 2, 3, (1999); Nummenpaa J., Ollikainen T., The Goods Traffic in Densely Populated Areas in Finland (in Finnish), (1999); Pastinen V., Henkilöliikennetutkimus 1998-1999. [Passenger Transport Survey 1998-1999.], (1999); Pietila M., Henkilöliikennetutkimus 1992 [Passenger Transport Survey 1992], (1993); Powell M., A perspective on the key issues in the development of food home shopping in the UK, Conference Handout at CIES: Supply Chain for e-Commerce and Home Delivery in the Food Industry, (2000); Prahalad C.K., Hamel G., The core competence of the corporation, Harvard Business Review, 68, 3, pp. 79-92, (1990); Prouty K., Flow manufacturing: An answer to ebusiness, Material Handling Management, 55, 5, pp. 67-70, (2000); Punakivi M., Saranen J., Identifying the critical success factors in e-grocery home delivery, International Journal of Retail and Distribution Management, 29, 4, pp. 156-163, (2001); Reinhardt A., Tesco bets small - And wins big, Businessweek Online, (2001); Chain Store Age, pp. 10-20, (1999); Rickhardson H.L., Packaging for today's demanding fulfillment, Transportation and Distribution, 41, 7, pp. 72-75, (2000); Romm J., Rosenfeld A., Herrmann S., The Internet Economy and Global Warming: A Scenario of the Impact of E-commerce on Energy and the Environment, (1999); Seideman T., Weapons for an new world, Logistics Management and Distribution Report, 39, 4, (2000); Smaros J., Holmstrom J., Reaching the consumer through e-grocery VMI, International Journal of Retail and Distribution Management, 28, 2, pp. 51-61, (2000); Smaros J., Holmstrom J., Kamarainen V., New service opportunities in the e-grocery business, International Journal of Logistics Management, 11, 1, pp. 61-73, (2000); Stalk G., Hout T., Competing Against Time, (1990); Finland in Statistics on CD-1996 (in Finnish), (1996); Information Regarding the Roads and Road Traffic (in Finnish), (1999); Road Traffic Forecast for 1997-2030: Revised from 1995 Forecast (in Finnish), (1999); (2000); (2000); (2000); (2000); (2001); Wilsdon J., Digital Futures: Living in a Dot.com World, (2001); (2001)","H. Siikavirta; Helsinki University of Technology, Dept. of Indust. Eng. and Management, FIN-02015 TKK Espoo, POB 9500, Finland; email: hanne.siikavirta@ltk.hut.fi",{"$nulls":7},1.088198E7,null,"JINEF",null,"English","J. Ind. Ecol.","Article","Final",null,"Scopus","2-s2.0-0036524934"]
["Slack F.; Rowley J.","Slack, Frances (7004379705); Rowley, Jennifer (7201756587)","7004379705; 7201756587","Online kiosks: The alternative to mobile technologies for mobile users",2002.0,"Internet Research",12.0,3.0,null,248.0,257.0,9.0,19.0,"10.1108/10662240210430928","https://www.scopus.com/inward/record.uri?eid=2-s2.0-0036054494&doi=10.1108%2f10662240210430928&partnerID=40&md5=2531150305b595258545769caa33a281","Sheffield Hallam University, Sheffield, United Kingdom; School of Management and Social Sciences, Edge Hill College of Higher Education, Ormskirk, United Kingdom","Slack F., Sheffield Hallam University, Sheffield, United Kingdom; Rowley J., School of Management and Social Sciences, Edge Hill College of Higher Education, Ormskirk, United Kingdom","Online kiosks have the potential to be a significant alternative to mobile technologies in retailing, information provision and service delivery. This article describes the development and use of different types of online kiosk in contexts where users are on the move and away from fixed technologies. A case study of a major UK airport terminal is used to illustrate different types of kiosk applications. Comparisons are made with mobile phone technologies. Online kiosks have a niche in allowing access to information, services and e-commerce technologies for all potential consumers. However, they also have a much wider role in self-managed, self-service delivery of information, services, goods and relationships to consumers on the move.","Information technology; Internet; Mobile communications",{"$nulls":7},"Ashford R.A., Et al., Making a success of kiosks, Managing Information, pp. 46-47, (2001); De Kare Silver M., E-shock: The Electronic Shopping Revolution; Strategies for Retailers and Manufacturers, 2nd ed., (2000); Lipperts S., Park A.S.-B., An agent-based middleware - A solution for terminal and user mobility, Computer Networks, 31, pp. 2053-2062, (1999); Lord C., The practicalities of developing a successful e-business, Journal of Business Strategy, 21, 2, pp. 40-47, (2000); Nicholas D., Huntington P., Williams P., Establishing metrics for the evaluation of touch screen kiosks, Journal of Information Science, 27, 2, pp. 61-71, (2001); Palazzo S., Et al., Design and evaluation of a replicated database for mobile systems, Wireless Networks, 6, pp. 131-144, (2000); Rowley J., Multimedia kiosks in retailing, International Journal of Retail & Distribution Management, 23, 5, pp. 32-40, (1995); Rowley J., Slack F., Designing Public Access Systems, (1998); Rowley J.E., Slack F.E., The retail experience in airport departure lounges: Reaching for timelessness and placelessness, International Marketing Review, 16, 4-5, pp. 363-375, (1999); Rowley J.E., Slack F.E., Kiosks in retailing: the quiet revolution, (2002); Slack F.E., Rowley J.E., Kiosks 21: A new role for information kiosks?, International Journal of Information Management, 22, 1, pp. 67-83, (2002); Tung L.L., Tan J.H., A model for the classification of information kiosks in Singapore, International Journal of Information Management, 18, 4, pp. 255-265, (1998); Useem J., Internet defense strategy: Cannibalise yourself: Call it survival by suicide, Fortune, 140, 5, pp. 121-134, (1999); Venkatraman N., Five steps to a dot-com strategy: How to find your footing on the Web, Sloan Management Review, 41, 3, pp. 15-25, (2000)",{"$nulls":8},1.0662243E7,null,null,null,"English","Internet Res.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-0036054494"]
["Koh S.C.L.; Tan Z.","Koh, S.C.L. (24824748600); Tan, Z. (57019940800)","24824748600; 57019940800","Using e-commerce to gain a competitive advantage in 3PL enterprises in China",2005.0,"International Journal of Logistics Systems and Management",1.0,"2024-03-02",null,187.0,210.0,23.0,23.0,"10.1504/ijlsm.2005.005970","https://www.scopus.com/inward/record.uri?eid=2-s2.0-39149091898&doi=10.1504%2fijlsm.2005.005970&partnerID=40&md5=3b9299e4b5332d76a1f232498f23145b","University of Sheffield, Management School, Sheffield, S1 4DT, 9 Mappin Street, United Kingdom; Shanghai Science and Technology Investment Co., 1634 Huaihai Central Road, Post Code 200031, China","Koh S.C.L., University of Sheffield, Management School, Sheffield, S1 4DT, 9 Mappin Street, United Kingdom; Tan Z., Shanghai Science and Technology Investment Co., 1634 Huaihai Central Road, Post Code 200031, China","This paper presents an investigation of how the selected foreign and domestic Third-Party Logistics (3PL) enterprises in China use e-commerce to gain competitive advantages. The study starts with an introduction that illustrates how China’s economic growth will hinge on the ability of logistics service providers to offer a cost-effective and efficient supply chain. Using e-commerce, 3PL providers now supply more and more value-added services to their customers. With the advent of the boom in the Chinese 3PL industry, both foreign and domestic 3PL providers came and tried to capture the huge market. This represents a theoretical background for conducting research among these 3PL enterprises. The theoretical literature on e-commerce and 3PL logistics is reviewed in order to give a framework of relevant theories and contemporary findings. Four in-depth case studies (two foreign 3PL providers and two 3PL domestic providers) are examined and eight semi-structured interviews are conducted with the senior managers and IT managers in these selected cases. A comparison of the present applications of e-commerce in the case enterprises and the difference in the ways they use e-commerce to gain competitive advantages are made. However, due to the different nature and technological level, the foreign 3 PL providers could take a totally different strategy. The study also provides an insight into how they develop their technology and marketing strategies in terms of their own strengths and target markets. That could be a useful reference to relevant researchers or firms. © 2005 Inderscience Enterprises Ltd.","3PL; competitive advantage; e-commerce",{"$nulls":7},"Azumah G., Koh S.C.L., Maguire S., E-organisation and its future implication for SMEs, Proceedings of the 2nd International Workshop on Supply Chain Management and Information Systems, (2004); Basu R., New criteria of performance management: a transition from enterprise to collaborative supply chain, Measuring Business Excellence, 5, 4, pp. 7-12, (2001); Boyson S., Corsi T., Dresner M., Rabinovich E., Managing effective third party logistics relationships: what does it take?, Journal of Business Logistics, 20, 1, pp. 73-100, (1999); Carter J.R., Pearson J.N., Peng L., Logistics barriers to international operations: the case of the People’s Republic of China, Journal of Business Logistics, 18, 2, pp. 129-145, (1997); Chen F.Y., Goh M., Lee J., Ou J., Sharafali M., Teo C., Goh P., Sivanathan P., ST logistics: distributing consumer goods in China, International in Transactions in Operational Research, 8, pp. 203-219, (2001); Christopher M., Logistics and Supply Chain Management, (1992); CNNIC (China Internet Network Information Center), The Semiannual Survey Report on the Development of China’s Internet, (2002); Coyle J.J., Bardi E.J., Langley C.J., The Management of Business Logistics, (1996); Dedrick J., Kraemer K.L., China IT Report, (2001); Franceschini F., Galetto M., Pignatelli A., Varetto M., Outsourcing: guidelines for a structured approach, Benchmarking: An International Journal, 10, 3, pp. 246-260, (2003); Huang D., Kadar M., Third-party logistics in China: still a tough market, Travel and Transport, 3, (2002); Johnson G., Scholes K., Exploring Corporate Strategy, (1999); Kalakota R., Whinston A.B., Electronic Commerce: A Manager’s Guide, (1997); Lambert D.M., Emmelhainz M.A., Gardner J.T., Building successful logistics partnerships, Journal of Business Logistics, 20, 1, pp. 165-182, (1999); Langley J.L., Allen G.R., Tyndall G.R., Third-party logistics study: results and findings of the 2001 Sixth Annual Study, (2001); Lieb R.C., Randall H., A comparison of the use of third-party logistics services by large american manufacturers, 1991, 1994, and 1995, Journal of Business Logistic, 17, 1, pp. 305-320, (1996); Murphy P.R., Foist R.F., Third-party logistics usage: an assessment of propositions based on previous research, Transportation Journal, Summer, pp. 26-35, (1998); Porter M.E., Competitive Advantage, (1985); Prahalad C.K., Hamel G., The core competence of the corporation, Harvard Business Review, May-June, pp. 84-98, (1990); Rao B., Navoth Z., Horwitch M., Building a world-class logistics, distribution and electronic commerce infrastructure, Electronic Markets, 9, 3, pp. 174-180, (1999); Rayport J.F., Jaworski B.J., E-commerce, (2001); Riggins F.J., Rhee H.S., Toward a unified view of electronic commerce, Communications of the ACM, 41, 10, pp. 88-95, (1998); Ruppel C., Underwood-Queen L., Harrington S.J., E-commerce: the roles of trust, security, and type of e-commerce involvement, E-service Journal, pp. 25-47, (2003); Ryan P., E-Logistics: Potential, Strategies and Challenges, (2003); Saunders C., Gebelt M., Achieving success in information systems outsourcing, California Management Review, 39, 2, pp. 63-77, (1997); Saunders M., Lewis P., Thornhill A., Research Methods for Business Students, (2003); Sink H.L., Langley C.J., A managerial framework for the acquisition of third-party logistics services, Journal of Business Logistics, 18, 2, pp. 163-190, (1997); Sink H.L., Langley C.J., Gibson B.J., Buyer observations of the US third-party logistics market, International Journal of Physical Distribution and Logistics Management, 26, 3, pp. 38-46, (1996); Sullivan C., Beyond traditional EDI: electronic commerce demystified, Inform, 12, 10, pp. 22-25, (1998); Taylor D.H., Global Cases in Logistics and Supply Chain Management, (1997); Viswanadham N., Gaonkar R., E-logistics: trends and opportunities, Asia Pacific, (2001); Zhu J.J., A reality check of e-commerce development in China: an analysis of challenges facing E-commerce in China, (2002)",{"$nulls":8},1.7427967E7,null,null,null,"English","Int. J. Logist. Syst. Manage.","Article","Final",null,"Scopus","2-s2.0-39149091898"]
["Sohal A.S.; D’Netto B.","Sohal, Amrik S. (7005819911); D’Netto, Brian (6602438190)","7005819911; 6602438190","Incumbent perceptions of the logistics profession",2004.0,"International Journal of Logistics Systems and Management",1.0,1.0,null,5.0,25.0,20.0,10.0,"10.1504/IJLSM.2004.005535","https://www.scopus.com/inward/record.uri?eid=2-s2.0-34249022686&doi=10.1504%2fIJLSM.2004.005535&partnerID=40&md5=7d9d6b97cccc7f980b3ce2c24c4622dd","Department of Management, Faculty of Business and Economics, Monash University, Caulfield East, Victoria 3145, PO Box 197, Australia; Mt Eliza Business School, Melbourne, Victoria 3004, PO Box 7262, St Kilda Road Post Office, Australia","Sohal A.S., Department of Management, Faculty of Business and Economics, Monash University, Caulfield East, Victoria 3145, PO Box 197, Australia; D’Netto B., Mt Eliza Business School, Melbourne, Victoria 3004, PO Box 7262, St Kilda Road Post Office, Australia","As we move into the new millennium, organisations are increasingly turning to the logistics function to gain competitive advantage. This implies that qualified and ambitious logistics managers will be required to achieve strategic organisational objectives. This paper seeks to assess Logistics Managers’ perceptions of their profession. More specifically, it examines their educational qualifications, career progression, job content and reward perceptions. To assess the current position, a survey of logistics managers in Australia was conducted and 303 completed and usable responses were obtained. The data indicated that logistics managers are generally middle-aged employees with around 62.5% between 35 to 49 years old. The study found that Australian logistics managers are well qualified (75.7% had a higher degree or diploma), highly paid (56.1% earn over AUS $90,000 per annum) and find their jobs challenging and interesting. Respondents joined the logistics management function relatively early in their careers and 63.3% had worked in the logistics function for over 10 years. However, respondents indicated that working hours were too long and that benefits were not adequate. Logistics managers indicated a strong need for additional training in computers, business management, new technology management and logistics management. Respondents indicated that they require increased control of systems design, business to business e-commerce, transport management and warehouse operations. Nearly two-thirds of the respondents were members of a professional institution. The logistics profession still continues to be dominated by male managers. The paper discusses the implications of these findings. © 2004 Inderscience Enterprises Ltd.","career development and job satisfaction; education; logistics managers; training",{"$nulls":7},"Bowersox D.J., Closs D.J., Stank T.P., The mega-trends that will revolutionize supply chain logistics, Journal of Business Logistics, 21, 2, pp. 1-16, (2000); Bradley J., Who’s minding the store?, Canadian Transportation Logistics, 107, 1, (2004); Bradley P., Facing the millennium, Logistics, pp. 45-51, (1998); Buxbaum P.A., The next generation of logistics managers: fearless communicators, Transportation and Distribution, 36, 10, pp. 84-85, (1995); Christopher M., Logistics and Supply Chain Management, (1998); Dapiran P., Lieb R., Millen R., Sohal A., Third party logistics services usage by large Australian firms, International Journal of Physical Distribution and Logistics Management, 26, 10, pp. 36-45, (1996); Dessler G., Griffiths J., Lloyd-Walker B., Williams A., Human Resource Management, (1999); D'Netto B., Information processing and reward perception accuracy, Unpublished Doctoral Dissertation, (1993); D'Netto B., Sohal A.S., Changes in the production manager’s job: past, present and future trends, International Journal of Operations and Production Management, 19, 2, pp. 157-181, (1999); Ellinger A.E., Ellinger A.D., Keller S.B., Logistics managers’ learning environments and firm performance, Journal of Business Logistics, 23, 1, pp. 19-37, (2002); Gammelgaard B., Larson P.D., Logistics and competencies for supply chain management, Journal of Business Logistics, 22, 2, pp. 27-50, (2001); Hale B.J., Logistics perspectives for the new millennium, Journal of Business Logistics, 20, 1, pp. 5-8, (1999); Hannon D., Third party logistics: maximizing value of outsource partners requires new skills, Purchasing, 132, 13, pp. 50-53, (2003); Herron D.P., The educational needs of physical distribution managers, The Distribution Handbook, pp. 849-855, (1985); Herzberg F., The Motivation to Work, (1959); Johnson J.C., McClure D.J., Schneider K.C., Job satisfaction of logistics managers: female versus male perspectives, Transportation Journal, Fall, pp. 5-19, (1999); King M.J., Breaking away, Distribution, 94, 6, pp. 32-36, (1995); La Londe B.J., Emmelhainz L.W., Where do you Fit in? Distribution, 84, 11, pp. 32-36, (1985); La Londe B.J., Ginter J.L., The Ohio State University 2001 survey of career patterns in logistics, Unpublished Paper, Supply Chain Management Research Group, (2001); Mangan J., Gregory O., Lalwani C., Education, training and the role of logistics managers in Ireland, International Journal of Logistics: Research and Applications, 4, 3, pp. 313-327, (2001); MacDonald M.E., From supply-chain manager to CEO, 37, 6, (1998); Menzies H.D., Australia’s hot Asian connection, International Business, September, pp. 42-47, (1995); Millen R., Sohal A., Dapiran P., Lieb R., Van Wassenhove L.N., Benchmarking Australian firms’ usage of contract logistics services: a comparison with American and Western European practice, Benchmarking for Quality Management & Technology, 4, 1, (1997); Newman J.N., Krzystofiak F.J., The importance of reward sources? who pays the piper, Unpublished Working Paper, (1990); Razzaque M.A., Sirat M.S.B., Skill requirements: perception of the senior Asian logisticians, International Journal of Physical Distribution and Logistics Management, 31, 5, pp. 374-395, (2001); Richardson H.L., Logistics in the limelight, Training and Development, January, pp. 46-50, (1996); Skojett-Larsen T., Supply chain management: a new challenge for researchers and managers in logistics, The International Journal of Logistics Management, 10, 2, pp. 41-53, (1999); Sohal A.S., Millen R., Moss S., A comparison of the use of third party logistics services by Australian firms between 1995 and 1999, International Journal of Physical Distribution and Logistics Management, 32, 1-2, pp. 59-68, (2002); Tompkins J.A., Logistics: a challenge for today, IIE Solutions, February, pp. 16-17, (1997); Walsh E., Logistics managers find happiness, Logistics, November, pp. 40-44, (2000); Williams A.W., Currey P., Desired attributes of logistics managers and a learning hierarchy in management education, Logistics and Transportation Review, 26, 4, pp. 369-379, (1990)",{"$nulls":8},1.7427967E7,null,null,null,"English","Int. J. Logist. Syst. Manage.","Article","Final",null,"Scopus","2-s2.0-34249022686"]
["Rezaee Z.; Lambert K.R.; Ken Harmon W.","Rezaee, Zabihollah (6603153872); Lambert, Kenneth R. (54418850900); Ken Harmon, W. (55873319800)","6603153872; 54418850900; 55873319800","Electronic commerce education: Analysis of existing courses",2006.0,"Accounting Education",15.0,1.0,null,73.0,88.0,15.0,19.0,"10.1080/06939280600579370","https://www.scopus.com/inward/record.uri?eid=2-s2.0-54049128812&doi=10.1080%2f06939280600579370&partnerID=40&md5=ed1bc5e6525518a389cf8fb2c8198acd","University of Memphis, United States; Millsaps College, United States","Rezaee Z., University of Memphis, United States; Lambert K.R., University of Memphis, United States; Ken Harmon W., Millsaps College, United States","E-commerce is reshaping business practices and education, yet many have expressed concern over the e-commerce education and training provided to students. This study examines the extent to which business schools, particularly accounting programs, are integrating e-commerce education into their curricula. An analysis of 79 syllabi provides evidence regarding: (1) the scope and nature of e-commerce education; (2) educational approaches to e-commerce; (3) e-commerce topics that could be taught as part of e-commerce education; (4) methods of coverage of e-commerce education; and (5) methods and reference materials for teaching an e-commerce course. This study initiates a general dialogue on the nature, content, objectives, and delivery of e-commerce education. An exploratory review and content analysis of a sample of 79 syllabi, representing different sizes of universities worldwide, reveals that business schools and accounting programs offer e-commerce courses emphasizing a broad range of skills, objectives, perspectives, teaching methods, and cognitive content. However, many common themes, topics, and assignments have emerged. The e-commerce education issues addressed in this study should help business schools and accounting programs prepare students for the challenges awaiting them in the area of emerging technological advances. © 2006 Taylor & Francis.","business and accounting curricula; business education; E-commerce courses; Electronic commerce; information technology",{"$nulls":7},"Challenges to audit education for the 21st century: A survey of curricula, course content, and delivery methods, Issues in Accounting Education, 18, 3, pp. 241-263, (2003); Albrecht W.S., Sack R.J., Accounting Education: Charting the Course through a Perilous Future, (2000); Besalel S., Technology's impact on academic achievement, The Journal, (2004); E.BIZ 25—Introduction. The Comeback Kids (3851): 116, (2003); Celsi R., Wolfinbarger M., Creating renaissance employees in an era of convergence between information technology and business strategy: A proposal for business schools, Journal of Education for Business, 76, 6, pp. 308-317, (2001); Chang C., Hwang N.C., Accounting education, firm training, and information technology: a research note, Accounting Education: an international journal, 12, 4, pp. 441-450, (2003); David J.S., Integrating technology and business process analysis into introductory accounting courses, Issues in Accounting Education, 18, 4, pp. 417-425, (2003); Demb A., Change dynamics and leadership in technology implementation, Journal of Higher Education, 75, 6, pp. 636-666, (2004); Average online retail purchase prices in the U.S., 2002 and 2003, (2004); Etheridge H.L., E-business education at AACSB-affiliated business schools: A survey of programs and curricula, Journal of Education for Business, 76, 6, pp. 328-331, (2001); eCommerce and ‘US eCommerce: The next five years’, July 2003, January 2004, (2003); Frakes A., Survey of undergraduate auditing education, Journal of Accounting Education, 5, 1, pp. 99-126, (1987); Groomer S., Heintz J., A survey of advanced auditing courses in the United States and Canada, Issues in Accounting Education, 9, 1, pp. 96-108, (1994); Harrington A., E-curriculum: Easy Come, Easy Go, Fortune, (2001); Hastings C.I., The state of accounting curriculum: where it is and where it needs to be, (2003); Marriott N., Using computerized business simulations and spreadsheet models in accounting education: a case study, Accounting Education: an international journal, 13, pp. 55-70, (2004); Melymuka K., Mastering E-Commerce by Degrees, Computerworld, 34, 47, pp. 48-49, (2000); Article 5: Certified Public Accountants, (2005); Rezaee Z., Electronic commerce education: insights from academicians and practitioners, Advances in Accounting, (2005); Strauss J., Similarities and differences in university internet marketing courses, Society for Marketing Advances 1999 Proceedings, pp. 147-151; (2004)","Z. Rezaee; Fogelman College of Business and Economics, The University of Memphis, Memphis, TN, 38152–3120, 300 Fogelman College Admin Building, United States; email: zrezaee@memphis.edu",{"$nulls":7},9639284.0,null,null,null,"English","Account. Educ.","Article","Final",null,"Scopus","2-s2.0-54049128812"]
["Pechtl H.","Pechtl, Hans (6507441255)",6.507441255E9,"Adoption of online shopping by German grocery shoppers",2003.0,"International Review of Retail, Distribution and Consumer Research",13.0,2.0,null,145.0,159.0,14.0,47.0,"10.1080/0959396032000099088","https://www.scopus.com/inward/record.uri?eid=2-s2.0-77951692316&doi=10.1080%2f0959396032000099088&partnerID=40&md5=7edb60b5a690358c57c9776b7484de17","Marketing Department, Ernst-Moritz-Arndt-Universität Greifswald, 17489 Greifswald, Friedrich-Loeffler-Straβe 70, Germany","Pechtl H., Marketing Department, Ernst-Moritz-Arndt-Universität Greifswald, 17489 Greifswald, Friedrich-Loeffler-Straβe 70, Germany","This study investigates how perceived attributes of online shopping and the psychological characteristics of consumers such as market mavenism, time-stressed behaviour and familiarity with the Internet impact the acceptance and frequency of shopping for physical goods on the Internet. In the study, the traditional adoption paradigm is refined by specifying in a more differentiated manner the outcome of the adoption behaviour and by postulating a mediator and moderator structure which underlies the relation between psychological characteristics, innovation attributes and adoption outcome. Empirical results identify missing touch and feel experiences as the most influential negative obstacle, and the chance to make better deals, the convenience of a delivery service and the independence of opening hours as the most influential positive factors for the adoption of online shopping. Familiarity also favours adoption behaviour, leading to a uniformly better assessment of many online shopping attributes. The influence of time-stressed behaviour and market mavenism on adoption behaviour is ambiguous and their effects appear to be more complex. © 2003, Taylor & Francis Group, LLC.","Adoption behaviour; E-commerce; Online shopping attributes",{"$nulls":8},"H. Pechtl; Marketing Department, Ernst-Moritz-Arndt-Universität Greifswald, 17489 Greifswald, Friedrich-Loeffler-Straβe 70, Germany; email: pechtl@uni-greifswald.de",{"$nulls":7},9593969.0,null,null,null,"English","Int. Rev. Retail Distrib. Consum. Res.","Article","Final",null,"Scopus","2-s2.0-77951692316"]
["Taylor J.; Burt E.","Taylor, John (55652859300); Burt, Eleanor (7004396057)","55652859300; 7004396057","Voluntary organisations as e-democratic actors: Political identity, legitimacy and accountability and the need for new research",2005.0,"Policy and Politics",33.0,4.0,null,601.0,616.0,15.0,13.0,"10.1332/030557305774329127","https://www.scopus.com/inward/record.uri?eid=2-s2.0-26944460834&doi=10.1332%2f030557305774329127&partnerID=40&md5=fb392d3967d50dbff6c40a277ef58543","The Oxford Internet Institute, University of Oxford, Oxford, United Kingdom; Division of Business Information Management, Caledonian Business School, Glasgow Caledonian University, Glasgow, United Kingdom; Department of Management, University of St. Andrews, St. Andrews, United Kingdom","Taylor J., The Oxford Internet Institute, University of Oxford, Oxford, United Kingdom, Division of Business Information Management, Caledonian Business School, Glasgow Caledonian University, Glasgow, United Kingdom; Burt E., Department of Management, University of St. Andrews, St. Andrews, United Kingdom","Voluntary sector organisations (VSOs) are actors of growing significance within the 'information polity'. One testament to their significance is the UK government's recent proposal for the development of an electronic mixed economy that will see VSOs act as 'intermediaries' in the delivery of e-government services, including e-democratic services. As VSOs independently harness information and communication technologies (ICTs) in ways that are enabling them to strengthen their 'voices' within both the national and international political system, so interrelated questions about their political identity, democratic legitimacy and accountability become profoundly important within the intermediaries context. © The Policy Press, 2005.","Accountability; E-democracy; Legitimacy; Voluntary","Harness; e-commerce; identity construction; political participation; voluntary approach",{"$nulls":6},"Restricting the Freedom of Speech of Charities: Do the Rationales Stand-Up?; Bimber B., The internet and political transformation: Populism, community, and accelerated pluralism, Polity, 20, 1, pp. 133-160, (1998); Boli J., Thomas G.M., Constructing World Culture: International Nongovernmental Organizations Since 1875, (1999); Brown D.L., Fox J., Transnational Civil Society Coalitions and the World Bank: Lessons from Project and Policy Influence Campaigns, (2000); Brown D.L., Moore M.H., Accountability, Strategy, and International Nongovernmental Organizations, (2001); EGovernment. Ready or Not?, 1, (2000); Burt E., Taylor J.A., Information and Communication Technologies: Re-Shaping the Voluntary Sector in the Information Age, (1998); Burt E., Taylor J.A., Voluntary Organisations in the Electronic Polity: Technological Capacity, Organisational Capabilities, and Competitive Edge, (2002); Burt E., Taylor J.A., Voluntary organisations; In the UK: Re-positioning within the information polity?, Conference Proceedings of the Eighth International Research Symposium on Public Management, (2004); Burt E., Taylor J.A., Constructing new ways of living together: Government relationships with the voluntary sector in the information polity, Information Polity: The International Journal of Government and Democracy in the Information Age, 8, 3-4, pp. 181-192, (2004); Cammaerts B., Van Audenhove L., ICT-Usage Among Transnational Social Movements in the Networked Society:To Organise, to Mediate, and to Influence, (2003); Clark J.D., Worlds Apart: Civil Society and the Battle for Ethical Globalisation, (2003); Davis Smith J., National Survey of Volunteering, (1997); DiMaggio P.J., Powell W.W., The iron cage revisited: Institutional isomorphism and collective rationality in organizational fields, American Sociological Review, 48, 2, pp. 147-160, (1983); Etzioni A., The New Golden Rule: Community and Morality in a Democratic Society, (1997); Goodin R.E., Reflective Democracy, (2002); Goodin R.E., Democratic Accountability: The Third Sector and All, (2003); Grant W., Pressure politics: The changing world of pressure groups, Parliamentary Affairs, 5, 2, pp. 408-419, (2004); Hall A., E-Enabling the Voluntary and Community Sectors: Final Report, (2003); Future Builders: An Investment Fund for Voluntary and Community Sector Public Service Delivery: Proposals for Consultation, (2003); Equipping community groups for the 21st century, (2003); Supporting the voluntary sector, (2004); Keck E., Sikkink K., Activists Beyond Borders: Advocacy Networks in International Politics, (1998); Milburn A., The voluntary sector: A partner in reform, (2004); The UK Voluntary Sector Almanac, (2004); Norris P., The Democratic Phoenix, (2001); Policy Framework for a Mixed Economy in the Supply of E-Government Services: A Consultation Document, (2003); Policy Framework for a Mixed Economy in the Supply of E-Government Services: Official Response to Public Consultation, (2003); Policy Framework for a Mixed Economy in the Supply of E-Government Services: Implementation Guidelines, 1, (2003); Park A., The generation game, British Social Attitudes: Focusing on Diversity, (2000); Prime D., Zimmeck M., Zurawan A., Active Communities: The Home Office Citizenship Survey, (2001); Putnam R., Bowling Alone, (2000); Rutherford K.R., Essential partners: Landmines-related NGOs and information technologies, Civil Society in the Information Age, (2002); Salamon L.M., Anheier H.K., The Emerging Sector:An Overview, (1994); Saxton J., Game S., Virtual Promise, (2000); Saxton J., Game S., Virtual Promise, (2003); Siochru S.O., Constanza-Chock S., Global Governance of Information and Communication Technologies: Implications for Transnational Civil Society Networking, (2003); Smith R.S., Lipsky M., Nonprofits for Hire: The Welfare State in the Age of Contracting, (1993); Snow D.A., Benford R.D., Ideology, frame resonance, and participant mobilization, From Structure to Action: Comparing Social Movement Research Across Cultures, (1988); Social Trends, (2003); Spykerman J., Scientists and missile defence: Organizing against a dangerous plan, Civil Society in the Information Age, (2002); Taylor J.A., Burt E., Not-for-profits in the democratic polity, Communications of the Association for Computing Machinery, 44, 1, pp. 58-62, (2001); Taylor J.A., Burt E., Pluralising teledemocracy: Not-for-profits in the democratic polity, Designing E-Government: On the Crossroads of Technological Innovation and Institutional Change, (2001); Taylor M., Warburton D., Legitimacy and the role of UK third sector organizations in the policy process, Voluntas, 14, 3, pp. 321-338, (2003); Ward H., CEOs still view IT as an administrative function, Computer Weekly, (2002); Whiteley P., The state of participation in Britain, Parliamentary Affairs, 56, 4, pp. 610-615, (2003)",null,null,"Policy Press",{"$nulls":5},3055736.0,null,null,null,"English","Policy Polit.","Article","Final",null,"Scopus","2-s2.0-26944460834"]
["Muir L.; Douglas A.","Muir, Lindsey (24177175400); Douglas, Alex (12446225300)","24177175400; 12446225300","Advent of e-business concepts in legal services and its impact on the quality of service",2001.0,"Managing Service Quality: An International Journal",11.0,3.0,null,175.0,181.0,6.0,9.0,"10.1108/09604520110391360","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84986109088&doi=10.1108%2f09604520110391360&partnerID=40&md5=d1f48602e2dd10398fed38c3c9369d81","Business Strategy at Liverpool Business School, John Moores University, Liverpool, United Kingdom; Operations Management, Liverpool Business School, John Moores University, Liverpool, United Kingdom","Muir L., Business Strategy at Liverpool Business School, John Moores University, Liverpool, United Kingdom; Douglas A., Operations Management, Liverpool Business School, John Moores University, Liverpool, United Kingdom","This paper examines the rise of electronic-commerce and its implications for quality and service delivery with particular reference to its impact on legal services. E-commerce is growing at a phenomenal rate with more organisations offering their goods and services on-line every day. Importantly, this growth is being matched by the number of people gaining access to the Internet in a variety of ways. E-commerce offers both opportunities and threats to law firms. The main threat is identified as coming from on-line competitors offering reduced prices and higher customer services. This competition is forcing law firms to change their attitude to new technology generally and the Internet in particular. A Web presence allows legal practices to be more transparent and to offer greater access to information to customers by way of improving their services. This improved communication may lead to a reduction in complaints against solicitors. The paper concludes that the Internet will have a profound effect on the way private law firms conduct business. © 2001, MCB UP Limited","Communications; E-commerce; Internet; Service",{"$nulls":7},"Abraham S.E., Spencer M.S., Monk E.L., Total quality management: applicability to law firms, International Journal of Quality and Reliability Management, 15, 5, pp. 541-554, (1997); Arrends B., Now Freeserve have to reward for surfing, Daily Mail, (2000); Barnard M., Law society Gazette-Focus, (1999); Bindman D., Law society Gazette-News-Infotech, (1999); BS EN ISO 9001: Quality Systems: Model For Quality Assurance in Design, Development, Production, Installation and Servicing, (1994); Crockett R.O., Keep ‘em coming back, Business Week: e-biz, (2000); Croft T., Lexcel helps solicitors to excel, TheTimes, (2000); De Kare-Silver M., E-shock 2000, (2000); Drummond H., The Quality Movement: What Total Quality Management Is Really All About, (1992); Investors In People, (1992); Fraser J., Fraser N., McDonald F., The strategic challenge of electronic commerce, Supply Chain Management, 5, 1, pp. 7-14, (2000); Furnell S.M., Karweni T., Security implications of electronic commerce: a survey of consumers and businesses, Internet Research: Electronic Networking Applications and Policy, 9, 5, pp. 372-382, (1999); Gerth G., Barth A., Machill E., Electronic Commerce in Europe, (1999); Hancock B., Security views, Computers and Security, 18, 3, pp. 184-198, (1999); Henning J.F., Total Quality Management for Law Firms, (1992); Supplement: “The informed executive experience”, Woolfall Plc, Independent on Sunday, (2000); Lexcel: Practice Management Standard, (1999); Lewis L., Business blasé about web fraud, Independent on Sunday, (2000); Malpas J., Net Rivals, The Times, (2000); McIntosh B., New allowances and tax breaks for IT investment by firms, Independent, (2000); McRae H., Online auctions and trading hubs are cutting net costs, The Independent, (2000); Partridge C., Take on the big boys with PC power, The Times, (2000); Survey of 3533 Adults Including 1690 Internet users, (2000); Rees A., Couple save £500 with a quick divorce on the net, The Times, (2000); Regan W., The service revolution, Journal of Marketing, 27, 3, pp. 57-62, (1963); Edgett S., Parkinson S., Marketing for service industries – A review, The Services Industries Journal, 13, 3, pp. 19-39, (1993); Sasser W.E., Olsen R.P., Wyckoff D.D., Management of service operations, (1978); Strader T.S., Shaw M.J., Consumer cost differences for traditional and Internet markets, Internet Research: Electronic Networking Applications and Policy, 9, 2, pp. 82-92, (1999); Susskind R., The number’s up for the Internet, The Times, (2000); Tsang L., Law society Gazette-Focus; Women no longer a blip on computer screen, USA Today, (2000); Zellner W., Wooing the newbies, Business Week: e-biz, pp. 116-120, (2000); Zeithaml V., How consumer evaluation processes differ between goods and services, Marketing Services, (1981)",{"$nulls":8},9604529.0,null,null,null,"English","Managing Serv. Qual.","Article","Final",null,"Scopus","2-s2.0-84986109088"]
[null,null,null,"Taking e-commerce to a new level: Winner takes all",2004.0,"Strategic Direction",20.0,11.0,null,20.0,22.0,2.0,0.0,"10.1108/02580540410567238","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84993044207&doi=10.1108%2f02580540410567238&partnerID=40&md5=60cbc8871f2ae9c5d1f1bfb6c611043d",null,null,"A recent advertisement on British television made great play of the fact that there is no substitute in the business world for face-to-face contact. Two firms were vying for a contract and the winner was the one whose boss crossed the Atlantic to deal in person with the commissioning business. The inference viewers were able to make was obvious. For all that, technology continues to revolutionize the way business is carried out and its potential is a long way from being fully tapped. © 2004, Emerald Group Publishing Limited","Business development; Channel management; Electronic commerce; Logistics; Marketing",{"$nulls":7},"Aldfer N., Brehmer P.O., Johannsson A., Business development with electronic commerce – refinement and repositioning, Business Process Management Journal, 10, 1, pp. 44-62, (2004)",{"$nulls":8},2580543.0,null,null,null,"English","Strateg. Dir.","Article","Final",null,"Scopus","2-s2.0-84993044207"]
["Waurzyniak Patrick","Waurzyniak, Patrick (6601915202)",6.601915202E9,"ERP embraces the Web",2000.0,"Manufacturing Engineering",125.0,4.0,null,42.44,46.49,null,5.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-0034290249&partnerID=40&md5=08ad7ddcaae3ca59d1847ebb2fc125d5",null,null,"To address the demand of faster, more efficient delivery and information systems, suppliers of enterprise resource planning (ERP) software are incorporating Web-based technologies into newer systems capable of leveraging the speed and vast reach of the Internet. Major suppliers of ERP are joining the current e-commerce rush on the Web by using Internet-based technologies like XML in their rewritten packages, and establishing business alliance involving trading exchanges and Web portals.",null,"Computer integrated manufacturing; Computer software; Electronic commerce; Industrial management; Investments; World Wide Web; Customer relationship management; Human resource management; Manufacturing execution systems; Manufacturing resource planning; Supply chain management; Enterprise resource planning",{"$nulls":9},"SME",{"$nulls":5},3610853.0,null,"MAEND",null,"English","Manuf Eng","Article","Final",null,"Scopus","2-s2.0-0034290249"]
["Hong W.; Zhu K.","Hong, Weiyin (7401528074); Zhu, Kevin (7201425580)","7401528074; 7201425580","Migrating to internet-based e-commerce: Factors affecting e-commerce adoption and migration at the firm level",2006.0,"Information and Management",43.0,2.0,null,204.0,221.0,17.0,273.0,"10.1016/j.im.2005.06.003","https://www.scopus.com/inward/record.uri?eid=2-s2.0-30944443323&doi=10.1016%2fj.im.2005.06.003&partnerID=40&md5=384eabeb993c466e1806368af289ceff","Department of Management Information Systems, College of Business, University of Nevada, Las Vegas, NV 89154, 4505 Maryland Parkway, United States; Paul Merage School of Business, University of California, Irvine, CA, United States; Department of Management Information Systems, University of Nevada, Las Vegas, United States; Paul Merage School of Business, University of California, Irvine, United States","Hong W., Department of Management Information Systems, College of Business, University of Nevada, Las Vegas, NV 89154, 4505 Maryland Parkway, United States, Department of Management Information Systems, University of Nevada, Las Vegas, United States; Zhu K., Paul Merage School of Business, University of California, Irvine, CA, United States, Paul Merage School of Business, University of California, Irvine, United States","Web technology has enabled e-commerce. However, in our review of the literature, we found little research on how firms can better position themselves when adopting e-commerce for revenue generation. Drawing upon technology diffusion theory, we developed a conceptual model for assessing e-commerce adoption and migration, incorporating six factors unique to e-commerce. A series of propositions were then developed. Survey data of 1036 firms in a broad range of industries were collected and used to test our model. Our analysis based on multi-nominal logistic regression demonstrated that technology integration, web functionalities, web spending, and partner usage were significant adoption predictors. The model showed that these variables could successfully differentiate non-adopters from adopters. Further, the migration model demonstrated that web functionalities, web spending, and integration of externally oriented inter-organizational systems tend to be the most influential drivers in firms' migration toward e-commerce, while firm size, partner usage, electronic data interchange (EDI) usage, and perceived obstacles were found to negatively affect e-commerce migration. This suggests that large firms, as well as those that have been relying on outsourcing or EDI, tended to be slow to migrate to the internet platform. © 2005 Elsevier B.V. All rights reserved.","E-commerce; EDI; Innovation adoption; Internet technology; Migration; Outsourcing; Technology diffusion","Computer simulation; Electronic data interchange; Internet; Logic design; Outsourcing; Regression analysis; Innovation adoption; Internet technology; Migration; Technology diffusion; Electronic commerce",{"$nulls":6},"Arrow K., The economic implications of learning by doing, Review of Economic Studies, 29, pp. 166-170, (1962); Attewell P., Technology diffusion and organizational learning: The case of business computing, Organization Science, 3, 1, pp. 1-19, (1992); Aubert B.A., Dussault S., Patry M., Rivard M., Managing the risk of IT outsourcing, Proceedings of the Thirty-Second Hawaii International Conference on System Sciences, pp. 7068-7079, (1999); Barua A., Mukhopadhyay T., Information technology and business performance: Past, present and future, Framing the Domains of IT Management: Projecting the Future Through the Past, (2000); Beatty R.C., Shim J.P., Jones M.C., Factors influencing corporate website adoption: A time-based assessment, Information and Management, 38, 6, pp. 337-354, (2001); 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Chircu A.M., Kauffman R.J., Limits to value in electronic commerce-related IT investments, Journal of Management Information Systems, 17, 2, pp. 59-81, (2000); Cooper R., Zmud R., Information technology implementation: A technology diffusion approach, Management Science, 36, 2, pp. 156-172, (1990); Damanpour F., Organizational innovation: A meta-analysis of effects of determinants and moderators, Academy of Management Journal, 34, 3, pp. 555-590, (1991); Davern M.J., Kauffman R.J., Discovering potential and realizing value from information technology investments, Journal of Management Information Systems, 16, 4, pp. 121-144, (2000); Fichman R.G., The diffusion and assimilation of information technology innovations, Framing the Domains of IT Management: Projecting the Future Through the Past, (2000); Fichman R.G., Kemerer C.F., The assimilation of software process innovations: An organizational learning perspective, Management Science, 43, 10, pp. 1345-1363, (1997); Fornell C., A Second Generation of Multivariate Analysis, Methods, 1, (1982); Hair J., Anderson R., Tatham R., Black W., Multivariate Data Analysis, (1998); Hosmer D.W., Lemeshow S., Applied Logistic Regression, (2000); Iacovou C.L., Benbasat I., Dexter A.S., Electronic data interchange and small organizations: Adoption and impact of technology, MIS Quarterly, 19, 4, pp. 465-485, (1995); Assessing the Impact of E-business on Europe Retail Financial Services, (2001); Kowtha N.R., Choon T.M.I., Determinants of website development: A study of electronic commerce in Singapore, Information and Management, 39, 3, pp. 227-242, (2001); Kraemer K.L., Gibbs J., Dedrick J., Environment and policy factors shaping e-commerce diffusion: A cross-country comparison, Proceedings of the 23rd International Conference on Information Systems, (2002); Kuan K.K.Y., Chau P.Y.K., A perception-based model for EDI adoption in small business using a technology-organization-environment framework, Information and Management, 38, 8, pp. 507-512, (2001); Lacity M.C., Willcocks L.P., An empirical investigation of information technology sourcing practices: Lessons from experience, MIS Quarterly, 22, 3, pp. 363-408, (1998); Mehrtens J., Cragg P.B., Mills A.M., A model of internet adoption by SMEs, Information and Management, 39, 3, pp. 165-176, (2001); Meyer A.D., Goes J.B., Organizational assimilation of innovations: A multilevel contextual analysis, Academy of Management Journal, 31, 4, pp. 897-923, (1988); Mukhopadhyay T., Kekre S., Kalathur S., Business value of information technology: A study of electronic data interchange, MIS Quarterly, 19, 2, pp. 137-156, (1995); Nunnally J., Psychometric Theory, (1978); Ramamurthy K., Premkumar G., Crum M.R., Organizational and interorganizational determinants of EDI diffusion and organizational performance: A cause model, Journal of Organizational Computing and Electronic Commerce, 9, 4, pp. 253-285, (1999); Raymond L., Organizational context and information systems success: A contingency approach, Journal of Management Information Systems, 6, 4, pp. 5-20, (1990); Rogers E.M., Diffusion of Innovations, (1983); Schoenecker T.S., Cooper A.C., The role of firm resources and organizational attributes in determining entry timing: A cross-industry study, Strategic Management Journal, 19, pp. 1127-1143, (1998); Shapiro C., Varian H.R., Information Rules: A Strategic Guide to the Network Economy, (1999); Straub D., Validating instruments in MIS research, MIS Quarterly, 13, 2, pp. 147-169, (1989); Swanson E.B., Information systems innovation among organizations, Management Science, 40, 9, pp. 1069-1092, (1994); Teo T.S.H., Tan M., Wong K.B., A contingency model of internet adoption in Singapore, International Journal of Electronic Commerce, 2, 2, pp. 95-118, (1998); Teo H.H., Wei K.K., Benbasat I., Predicting intention to adopt interorganizational linkages: An institutional perspective, MIS Quarterly, 27, 1, pp. 19-49, (2003); Thong J.Y.L., An integrated model of information systems adoption in small business, Journal of Management Information Systems, 15, 4, pp. 187-214, (1999); Thornton J., Marche S., Sorting through the dot bomb rubble: How did the high-profile e-tailers fail?, International Journal of Information Management, 23, 2, pp. 121-138, (2003); Tornatzky L.G., Fleischer M., The Processes of Technological Innovation, (1990); Vadapalli A., Ramamurthy K., Business use of the internet: An analytical framework and exploratory case study, International Journal of Electronic Commerce, 2, 2, pp. 71-95, (1997); Weill P., Broadbent M., Leveraging the New Infrastructure: How Market Leaders Capitalize on Information Technology, (1998); Zhu K., Information transparency of business-to-business electronic markets: A game-theoretic analysis, Management Science, 50, 5, pp. 670-685, (2004); Zhu K., Kraemer K., E-commerce metrics for net-enhanced organizations: Assessing the value of e-commerce to firm performance in the manufacturing sector, Information Systems Research, 13, 3, pp. 275-295, (2002); Zhu K., Kraemer K., Post-adoption variations in usage and value of e-business by organizations: Cross-country evidence from the retail industry, Information Systems Research, 16, 1, pp. 61-84, (2005); Zhu K., Kraemer K., Xu S., Electronic business adoption by European firms: A cross-country assessment of the facilitators and inhibitors, European Journal of Information Systems, 12, 4, pp. 251-268, (2003); Zhu K., Kraemer K., Gurbaxani V., Xu S., Migration to open-Standard inter-organizational systems: Network effects, switching Costs, and path dependency, MIS Quarterly","W. Hong; Department of Management Information Systems, College of Business, University of Nevada, Las Vegas, NV 89154, 4505 Maryland Parkway, United States; email: whong@unlv.nevada.edu",{"$nulls":7},3787206.0,null,"IMAND",null,"English","Inf Manage","Article","Final",null,"Scopus","2-s2.0-30944443323"]
["Kinder T.","Kinder, T. (7004417879)",7.004417879E9,"The use of Call Centres by local public administrations",2001.0,"Futures",33.0,10.0,null,837.0,860.0,23.0,14.0,"10.1016/S0016-3287(01)00022-2","https://www.scopus.com/inward/record.uri?eid=2-s2.0-0034750949&doi=10.1016%2fS0016-3287%2801%2900022-2&partnerID=40&md5=1871b865a8033c198f92cc7023c1322a","TechMaPP, Department of Business Studies, University of Edinburgh, Edinburgh EH8 9JY, 50 George Square, United Kingdom","Kinder T., TechMaPP, Department of Business Studies, University of Edinburgh, Edinburgh EH8 9JY, 50 George Square, United Kingdom","European local public administrations (PA) are rapidly adopting information and communications technologies often with a view to offering e-commerce. Call Centres (CCs) feature prominently in the technology mix used by private sector e-commerce, but as a survey in this paper shows, CCs are less often used in public sector. This paper analyses the differences between private and public sector commerce and their implications for public sector e-commerce and its prospective use of CCs over the next ten years. It outlines the evolution of CC technologies and argues that current developments make the technology increasingly appropriate for the public sector. A model of e-commerce featuring connectivity, interactivity and agility is developed in the paper. From this it is concluded that many of the advantages from the use of CCs by PAs, are in system integration and process re-engineering - attributes positioned in terms of bridging technology and acting as a learning organisation. From this perspective, the paper concludes that CCs are likely to increasingly feature in the information and communications technology-mix for e-commerce delivery of PAs over the next ten years. © 2001 Elsevier Science Ltd. All rights reserved.",null,"Europe; e-commerce; information technology; public administration; technology adoption; telecommunications",{"$nulls":6},"Government on Line - Local and Regional Aspects, (1997); Building the European Information Society for Us All - Final Policy Report of the High Level Group of Experts, (1997); Cusamano M.A., Selby R.W., Microsoft Secrets, (1996); Olim J., The Cdnow Story: Rags to Riches on the Internet, (1998); Argent N.M., Rolley F., Financial exclusion in rural and remote New South Wales, Australia: A geography of bank branch rationalisation, 1981-1998, Aust Geogr Stud, 38, 2, pp. 182-203, (2000); Betts A., Meadows W.P., Call centre capacity management, Int J Serv Ind Manage, 11, 2, pp. 185-196, (2000); Dawson K., Call Centre Savvy: How to Position Your Call Centre for the Business Challenges of the 21st Century, (2000); Huws U., Telework projections, Futures, 23, 1, pp. 19-31, (1991); Crome M., Call centres: Battery farming or free range, Ind Commercial Training, 30, 4, pp. 137-141, (1998); Taylor P., Bain P., An assembly line in the head: Work and employee relations in the call centre, Ind Relations J, 30, 2, pp. 101-117, (1999); Feldberg R.L., Glenn E.N., Technology and work degradation: Effects of office automation on women clerical workers, Machina Ex Dea: Feminist Perspectives on Technology, (1983); Gillespie A., Richardson R., Cornford J., Review of Telework in Britain: Implications for Public Policy, Centre for Urban and Regional Development Studies, (1995); Kinder T., Issues of theory and practice for ecommerce diffusion and analysis evolving of labour markets - Internet-based recruitment in West Lothian, Technovation, 20, 9, pp. 461-475, (2000); Frier P.P., Evaluation of an on-call diabetes service in a large teaching hospital, Diabetic Med, 17, 5, pp. 386-389, (2000); Kinder T., Klaes M., Molina A.H., Sociotechnical alignment in the build-up of a telemedicine constituency in Scotland, Sci. Public Policy, 26, 6, pp. 415-435, (1999); Kinder T., A sociotechnical approach to the innovation of a network technology in the public sector - The introduction of smart homes in West Lothian, Eur J Innovation Manage, 3, 2, pp. 72-90, (2000); Levine M.A., Birnbaum H.A., Integrated health management: The patient-centred future of demand management, Dis Manage Health Outcomes, 3, 1, pp. 11-22, (1998); Blankenship J.C., The telephone booth: A worthwhile stop along the information super-highway, Am J Med, 108, 7, pp. 592-593, (2000); Robinson J.G., Conroy C., Wickemeyer W.J., A novel telephone-based system for management of secondary prevention to low-density lipoprotein cholesterol ≤ 100 mg/dl, Am J Cardiol, 85, 3, pp. 305-308, (2000); Electronic Service Delivery of Government Services - Progress Report on Electronic Government 25% Target, (1999); Our Competitive Future - Building the Knowledge Driven Economy, (1998); Correll D., Using technology intelligently, Gov Information Q, 17, 2, pp. 137-146, (2000); Kinder T., The Introduction of an Infrastructure for Tele-working and Implementation of Joined-up -Government in Local Public Administration: A Sociotechnical Analysis of a West Lothian Case Study, (2000); Kinder T., Winskell M., Molina A., A Sociotechnical Analysis of Emerging Ecommerce Business Models: An Analysis of Case Studies from West Lothian, (2000); Nagel R., Dove R., 21st Century Manufacturing Strategy - An Industry Led View, (1992); Anton J., The past, present and future of customer access centres, Int J Serv Ind Manage, 11, 2, pp. 120-130, (2000); Belt V., Richardson R., Webster J., Tijdens K., Van Kalveren M., Work opportunities for women in the information society: Call centre tele-working, Centre for Urban and Regional Development Studies, (1998); Whitt W., Dynamic staffing in a telephone call centre aiming to immediately answer all calls, Operations Res Lett, 24, 5, pp. 205-212, (1999); Jain M., Queuing analysis of a mobile trunked system with mixed traffic and finite population, Appl Math Modelling, 23, 8, pp. 621-637, (1999); Kodama F., Technology fusion and the new RandD, Harv Business Rev, pp. 70-78, (1992); Fleck J., Configurations: Crystallising contingency, PICT Working Paper, 40, (1992); Rinde J., Telephony in the year 2005, Comput Networks, 31, 3, pp. 157-168, (1999); Kinder T., Molina A.H., A Sociotechnical Model of Learning Organisations - New Ways of Working and Emerging Organisational Forms, (2000); Madden G., Savage S.J., Telecommunications productivity, catch-up and innovation, Telecommunications Policy, 23, 1, pp. 65-81, (1999); Kodama M., Business innovation through customer-value creation, J Manage Dev, 19, 1, pp. 49-70, (2000); Fleck J., Informal information flow and the nature of expertise in financial services, Int J Technol Manage, 11, 1-2, pp. 104-128, (1996); Molina A.H., Insights into the nature of technology diffusion and implementation: The perspective of sociotechnical alignment, Technovation, 17, 11-12, pp. 601-626, (1997); Molina A.H., The role of the technical in innovation and technology development: The perspective of sociotechnical constituencies, Technovation, 19, pp. 1-29, (1999); Molina A.H., Transforming visionary products into realities: Constituency-building and observacting in the case of newspad, Futures, 31, pp. 191-232, (1999); Maude B., The return of the public servant, Local Gov Stud, 20, pp. 7-15, (1994); Radcliffe J., Community care and new public management: The local government response, Local Gov Stud, 22, pp. 153-166, (1996); Hood C., A public management for all seasons, Public Adm, 69, pp. 3-19, (1991); Brereton M., Temple. The new public service ethos: An ethical environment for governance, Public Adm, 77, 3, pp. 455-474, (1999); Pratchett L., Wingfield M., Petty bureaucracy and woolly-minded liberalism? The changing ethos of local government officers, Public Adm, 74, pp. 639-656, (1996); Pratchett L., New technologies and the modernisation of local government: An analysis of biases and constraints, Public Adm, 77, 4, pp. 731-750, (1999)","T. Kinder; TechMaPP, Department of Business Studies, University of Edinburgh, Edinburgh EH8 9JY, 50 George Square, United Kingdom; email: t.kinder@ed.ac.uk",{"$nulls":7},163287.0,null,null,null,"English","Futures","Article","Final",null,"Scopus","2-s2.0-0034750949"]
["Wickramasinghe N.; Mills G.L.","Wickramasinghe, Nilmini (12795213000); Mills, Gail L (7201923208)","12795213000; 7201923208","Integrating e-commerce and knowledge management - What does the Kaiser experience really telll us",2002.0,"International Journal of Accounting Information Systems",3.0,2.0,null,83.0,98.0,15.0,33.0,"10.1016/S1467-0895(02)00037-4","https://www.scopus.com/inward/record.uri?eid=2-s2.0-0036696723&doi=10.1016%2fS1467-0895%2802%2900037-4&partnerID=40&md5=bddd65ecd8f909e8e2966f3e28c6d6bd","Department of Accounting, Faculty of Economics, University of Melbourne, Melbourne, Vic. 3010, Australia; Kaiser Permanente, Cleveland, OH 44131, United States; Computer and Information Science Department, James J. Nance College of Business Administration, Cleveland State University, Cleveland, OH, United States","Wickramasinghe N., Department of Accounting, Faculty of Economics, University of Melbourne, Melbourne, Vic. 3010, Australia, Computer and Information Science Department, James J. Nance College of Business Administration, Cleveland State University, Cleveland, OH, United States; Mills G.L., Kaiser Permanente, Cleveland, OH 44131, United States","The growth of e-commerce (electronic commerce) is vast, complex and rapidly expanding. E-commerce is clearly an integral part of business, spreading across the areas of Business to Consumer, Business to Business, e-government and e-health. In fact, we could be forgiven for thinking we are in the e-millennium. E-medical record is an example of one such e-initiative to touch the health care sector. However, the true advantages of these e-medical records are not clear. We present the case example of medical automated record system (MARS), the automated medical record system at Kaiser Permanente-Ohio. In so doing, we show that the true advantage of this system is that it functions as a knowledge management system (KMS) simultaneously enabling and facilitating convergence and compliance of health care treatment, as well as enhancing and supporting the creation and renewal of knowledge pertaining to health care delivery. This demonstrates the importance of integrating a knowledge management focus in many e-commerce initiatives and we conclude by outlining the implications of such a focus for all organisations trying to increase their customer moment of value. © 2002 Elsevier Science Inc. All rights reserved.","Customer moment of value; E-medical records; Information systems; Information technology; Knowledge management; Knowledge management systems; Knowledge workers",{"$nulls":7},"Alavi M., Managing organisational knowledge, (1999); Applegate L., Mason R., Thorpe D., Design of a management support system for hospital strategic planning, J. Med. Syst, 10, 1, pp. 79-94, (1986); Beckman T., The current state of knowledge management, Knowledge Management Handbook, pp. 54-72, (1999); Boland R., Tenkasi R., Perspective making perspective taking, Organ Sci, 6, pp. 350-372, (1995); Borghoff U., Pareschi R., Information technology for knowledge management, (1998); Boyatzis R., Transforming qualitative information thematic analysis and code development, (1998); Chandra R., Knickrehm M., Miller A., Health care's IT mistake, McKinsey Q, 5, pp. 12-22, (1995); Davenport T., Prusak L., Working knowledge, (1998); Enthoven A., The history and principles of managed competition, Health Affairs, pp. 25-48, (1993); Grant R., The resource-based theory of competitive advantage: Implications for strategy formulation, Calif. Manage Rev, 33, 3, pp. 114-135, (1991); Hagg S., Cummings M., Dawkins J., Management information systems for the information age, (2000); Hedlund G., A model of knowledge management and the N-form corporation, Strategic Manage J, 15, pp. 73-90, (1994); Kanter J., Knowledge management practically speaking, Inf. Syst. Manage, pp. 7-15, (1999); Kavale S., Interviews an introduction to qualitative research interviewing, (1996); Knight W., Managed care: What it is and how it works, (1998); Kongstvedt P., The managed health care handbook, (1997); Malhotra Y., Knowledge management and new organisational form, Knowledge Management and Virtual Organisations, (2000); Miles M., Huberman A., Qualitative Data Analysis: An Expanded Source Book, (1994); Moody D., Shanks G., Using knowledge management and the Internet to support evidence based practice: A medical case study, (1999); Nonaka I., A dynamic theory of organisational knowledge creation, Organ Sci, 5, pp. 14-37, (1994); Polyani M., Personal knowledge: Towards a post-critical philosophy, (1958); Polyani M., The tacit dimension, (1966); Prahalad C., Hammel G., The core competence of the corporation, Harv. Bus. Rev, 68, pp. 79-90, (1990); Schultz U., Investigating the contradictions in knowledge management, (1998); Watts A., (1992); Wickramasinghe N., IS/IT as a tool to achieve goal alignment in the context of the knowledge worker in the health care industry, (1999); Wickramasinghe N., IS/IT as a tool to achieve goal alignment in the health care industry, Int. J. Healthcare Technol. Manage, 2, 1-2, pp. 163-180, (2000); Wickramasinghe N., Silvers J.B., IS/IT: Enabling medical group practices in a managed care environment, (2001); Wigg K., Knowledge management foundations, (1993); Wolper L., Health care administration, (1995); Yin R., Case Study Research: Design and Methods, (1994); Zack M., Knowledge and strategy, (1999)","N. Wickramasinghe; Computer/Information Science Dept., J.J. Nance Coll. of Business Admin., Cleveland State University, Cleveland, OH, United States; email: n.wickramasinghe@csuohio.edu",{"$nulls":7},1.4670895E7,null,null,null,"English","Int. J. Account. Inf. Syst.","Article","Final",null,"Scopus","2-s2.0-0036696723"]
["Malhotra M.; Tari Z.","Malhotra, Manish (7103190759); Tari, Zahir (7003792859)","7103190759; 7003792859","MIDAS: An integrated e-commerce solution for Australian transport industries",2004.0,"International Journal of Web Engineering and Technology",1.0,3.0,null,353.0,373.0,20.0,0.0,"10.1504/IJWET.2004.005238","https://www.scopus.com/inward/record.uri?eid=2-s2.0-13144252269&doi=10.1504%2fIJWET.2004.005238&partnerID=40&md5=15f1bedeed00e1812b3ed36505aa2812","Sch. Comp. Sci. and Info. Technol., Roy. Melbourne Inst. of Technology, Melbourne, Australia","Malhotra M., Sch. Comp. Sci. and Info. Technol., Roy. Melbourne Inst. of Technology, Melbourne, Australia; Tari Z., Sch. Comp. Sci. and Info. Technol., Roy. Melbourne Inst. of Technology, Melbourne, Australia","MIDAS provides an autonomous delivery management system from client orders to the electronic proof of delivery for the Australian transport industry. To accomplish this, MIDAS utilises different technologies, including global positioning system (GPS), wireless technologies (short message service (SMS)/wireless application protocol (WAP)) and the internet. MIDAS overcomes the issue of optimal routing and scheduling and mobile communication within the integrated Australian transport industry. MIDAS supports both static and dynamic scheduling utilising wireless communication channels to keep drivers up-to-date with information in real time when they are off-site. MIDAS also benefits the clients of the transport companies whose orders can be easily placed and traced anywhere, anytime. MIDAS is an advanced e-commerce solution to track and fulfil the orders throughout the entire supply chain.","Binary tree; Global positioning system; Internet procurement; Logistic applications; Mobile e-commerce; Palm applications; Routing and scheduling; Supply chain management; Transport applications; Web services; Wireless application protocol","Computer software; Database systems; Global positioning system; Logistics; Mobile telecommunication systems; Network protocols; Routers; Scheduling; Binary tree; Internet procurement; Mobile e-commerce; Palm applications; Routing and scheduling; Supply chain management; Transport applications; Web services; Wireless application protocol (WAP); Electronic commerce",{"$nulls":6},"Fong S.F., Dynamic Route Scheduling System for the Transport Industry, (2003); Solomon M., Algorithms for the vehicle routing and scheduling problems with time window constrains, Operations Research, 35, 2, (1987); Tengono Y., Wireless Real-time Information Exchange Using Hand-held Devices, (2003); Rohdes N., McKeehan J., Ten Common Palm OS Programming Pitfalls, (2001); Gossett B., Introduction to Conduit Development, (2002); ESRI Shapefile Technical Description, (1998)","M. Malhotra; Sch. Comp. Sci. and Info. Technol., Roy. Melbourne Inst. of Technology, Melbourne, Vic., Australia; email: manish@cs.rmit.edu.au",null,"Inderscience Publishers",{"$nulls":5},1.4761289E7,null,null,null,"English","Int. J. Web Eng. Technol.","Article","Final",null,"Scopus","2-s2.0-13144252269"]
["Delaney-Klinger K.; Boyer K.K.; Frohlich M.","Delaney-Klinger, Kelly (6508031519); Boyer, Kenneth K. (35512115800); Frohlich, Mark (7006415785)","6508031519; 35512115800; 7006415785","The return of online grocery shopping: A comparative analysis of Webvan and Tesco's operational methods",2003.0,"TQM Magazine",15.0,3.0,null,187.0,196.0,9.0,43.0,"10.1108/09544780310469334","https://www.scopus.com/inward/record.uri?eid=2-s2.0-0038102511&doi=10.1108%2f09544780310469334&partnerID=40&md5=ac0cb2236b8434ea05f586ad3e58f37b","Eli Broad Grad. Sch. of Management, Michigan State University, East Lansing, MI, United States; Operations Management Technol. Dept., London Business School, London, United Kingdom","Delaney-Klinger K., Eli Broad Grad. Sch. of Management, Michigan State University, East Lansing, MI, United States; Boyer K.K., Eli Broad Grad. Sch. of Management, Michigan State University, East Lansing, MI, United States; Frohlich M., Operations Management Technol. Dept., London Business School, London, United Kingdom","This paper provides an examination of the Internet grocery industry by providing a comparison of two business models, that of the now-defunct Wefavan and that of Tesco, the UK's leading grocer and the world's leading online grocer. The two businesses are first compared according to the level of strategic alignment between marketing and operations strategies displayed. Demonstrates how creating a match between a firm's operations and marketing strategies is critical for success. In addition, an e-operations profiling method is used to compare the operating characteristics of the two e-commerce ventures to traditional business operations. The result is further evidence as to why Tesco and other bricks-and-mortar grocers are achieving greater success selling groceries online than did Webvan. Finally, predictions are offered as to the future of electronic commerce in the grocery industry.","Delivery; Electronic commerce; Grocery; Operations Strategy; Supply chain management","Competition; Industrial management; Internet; Marketing; Online systems; Operations research; Strategic planning; Technological forecasting; Online grocery shopping; Operations strategy; Supply chain management; Electronic commerce",{"$nulls":6},"Boyer K.K., E-operations: A guide to how the internet streamlines operations, Business Horizons, 44, 1, pp. 47-54, (2001); Boyer K.K., McDermott C., Strategic consensus in operations strategy, Journal of Operations Management, 17, 3, pp. 289-305, (1999); Boyer K.K., Hallowell R., Roth A., E-services: Operating strategy, a case study and a method for analyzing operational benefits, Journal of Operations Management, 20, 2, pp. 177-190, (2002); Bozarth C.C., Berry W.L., Measuring the congruence between market requirements and manufacturing: A methodology and illustration, Decision Sciences, 28, 1, pp. 121-150, (1997); Ocado's online grocery gambit goes live, E. Logistics Magazine, (2002); Fine C.H., Hax A.C., Manufacturing strategy: A methodology and an illustration, Interfaces, 15, 6, pp. 28-46, (1985); Hall J., British supermarket giant cooks up plans to go global - Tesco's move to duplicate high growth at home comes with big risks, Wall Street Journal, (2001); Hill T.J., Manufacturing Strategy: Text and Cases, 1st Ed., (1989); Himelstein L., Khermouch G., Webvan left the basics on the shelf, Business Week, (2001); The grocer examines the UK supermarket web sites, Internet Business News, (2002); Koller M., Grocer builds net traffic - Albertson's expands in Seattle, pushes online/storefront strategy, Internetweek, 872, pp. 13-14, (2001); Leong G.K., Snyder D., Ward P., Research in the process and content of manufacturing strategy, Omega, 18, pp. 109-122, (1990); O'Briant E., Webvan revs up, IIE Solutions, pp. 26-33, (2000); Porter M., Strategy and the internet, Harvard Business Review, 79, 3, pp. 62-78, (2001); Reinhardt A., Tesco bets small - and wins big, Business Week, (2001); Rizzo T., The death of Webvan, Internet World, pp. 4-5, (2001); Skinner W., Manufacturing: Missing link in corporate strategy, Harvard Business Review, 3, pp. 136-145, (1969); Tomlinson R., A British e-grocer takes on Amazon, Fortune, pp. 246-255, (2000); Urbanski A., The super 50, Supermarket Business, 56, 4, pp. 1-18, (2001); Veitch M., E-grocers square up for food fight, Vnunet.com, (2002); Weir T., 53rd annual consumer expenditures study: Sales boom with the economy, Supermarket Business, 55, 9, pp. 27-45, (2000)",{"$nulls":8},"0954478X",null,"TQMME",null,"English","TQM Mag","Article","Final",null,"Scopus","2-s2.0-0038102511"]
["Golicic S.L.; Davis D.F.; McCarthy T.M.; Mentzer J.T.","Golicic, Susan L. (6506074413); Davis, Donna F. (7404612322); McCarthy, Teresa M. (8572283700); Mentzer, John T. (7003448331)","6506074413; 7404612322; 8572283700; 7003448331","The impact of e-commerce on supply chain relationships",2002.0,"International Journal of Physical Distribution and Logistics Management",32.0,10.0,null,851.0,871.0,20.0,72.0,"10.1108/09600030210455447","https://www.scopus.com/inward/record.uri?eid=2-s2.0-2342439030&doi=10.1108%2f09600030210455447&partnerID=40&md5=3e957ac763abbc47055eda9f2d1447a4","The University of Tennessee, Knoxville, TN, United States","Golicic S.L., The University of Tennessee, Knoxville, TN, United States; Davis D.F., The University of Tennessee, Knoxville, TN, United States; McCarthy T.M., The University of Tennessee, Knoxville, TN, United States; Mentzer J.T., The University of Tennessee, Knoxville, TN, United States","E-commerce is such a new phenomenon that little research has addressed the effects it has on relationships in supply chains. A qualitative study was conducted with eight e-commerce companies in order to construct theoretical relationships with which to develop a grounded theory of the impact of e-commerce on managing supply chain relationships. The e-commerce environment was perceived as highly uncertain, stemming from increased information visibility and dynamic market structures. A stronger emphasis on relationship management as part of business strategy enables managers to manage uncertainty better. Interestingly, increased information does not decrease the perception of uncertainty, but creates more uncertainty. As logistics is the function often involved with both information and relationship management within the supply chain, it may prove to be invaluable in helping firms succeed in this dynamic environment. Our research also found support for the application of transaction cost analysis and the resource dependence theory in explaining interorganizational relationship formation in e-commerce. © MCB UP Limited.","Internet; Relationship marketing; Supply chain; Uncertainty",{"$nulls":7},"Achrol R.S., Changes in the theory of interorganizational relations in marketing: Toward a network paradigm, Journal of the Academy of Marketing Science, 25, pp. 56-71, (1997); Achrol R.S., Stern L.W., Environmental determinants of decision-making uncertainty in marketing channels, Journal of Marketing Research, 25, pp. 36-50, (1988); Adler T.R., Scherer R.F., A multivariate investigation of transaction cost analysis dimensions: Do contract types differ?, Journal of Applied Business Research, 15, pp. 65-79, (1999); Aldridge A., Forcht K., Pierson J., Get linked or get lost: Marketing strategy for the Internet, Internet Research, 7, 3, pp. 161-169, (1997); Bauer R.A., Consumer behavior as risk taking, Risk Taking and Information Handling in Consumer Behavior, (1960); Cairncross F., The Death of Distance-How the Communications Revolution Will Change Our Lives, (1997); Colvin G., How to be a great eCEO, Fortune, pp. 104-110, (1999); Cox D.F., Risk Taking and Information Handling in Consumer Behavior, (1967); Cravens D.W., Piercy N.F., Shipp S.H., New organizational forms for competing in highly dynamic environments: The network paradigm, British Journal of Management, 7, pp. 203-218, (1996); Dahlstrom R., McNeilly K.M., Speh T.W., Buyer-seller relationships in the procurement of logistical services, Journal of the Academy of Marketing Services, 24, pp. 110-124, (1996); Davis S., Meyer C., Blur: The Speed of Change in the Connected Economy, (1998); Day G.S., Managing market relationships, Journal of the Academy of Marketing Science, 28, 1, pp. 24-30, (2000); Dolber S., Cheema S., Sharrard J., Resizing on-line business trade, The Forrester Report, pp. 1-13, (1998); Flint D.J., Change in customers' desired value: A grounded theory study of its nature and processes based on business customers' lived experiences in the US automobile industry, (1997); Ganesan S., Determinants of long-term orientation in buyer-seller relationships, Journal of Marketing, 58, pp. 1-19, (1994); Glazer R., Marketing in an information-intensive environment: Strategic implications of knowledge as an asset, Journal of Marketing, 55, pp. 1-19, (1991); B2B: 2B or not 2B?, (1999); Greenstein M., Feinman T.M., Electronic Commerce: Security, Risk Management and Control, (2000); Hamill J., The Internet and international marketing, International Marketing Review, 14, pp. 300-323, (1997); Heide J.B., Interorganizational governance in marketing channels, Journal of Marketing, 58, pp. 71-85, (1994); Hirschman E.C., Humanistic inquiry in marketing research: Philosophy, method, and criteria, Journal of Marketing Research, 23, pp. 237-249, (1986); Hoffman D.L., Novak T.P., Chatterjee P., Commercial scenarios for the Web: Opportunities and challenges, Journal of Computer-Mediated Communication, 1, (1995); Lambe C.J., Spekman R.E., Alliances, external technology acquisition, and discontinuous technological change, Journal of Production Innovation Management, 14, pp. 102-116, (1997); McCracken G., The Long Interview, (1988); Mentzer J.T., DeWitt W., Keebler J.S., Min S., Nix N.W., Smith C.D., Zacharia Z.G., What is supply chain management?, Supply Chain Management, pp. 5-62, (2001); Mentzer J.T., Min S., Zacharia Z.G., The nature of interfirm partnering in supply chain management, Journal of Retailing, 76, 4, pp. 1-20, (2000); Miles M.B., Qualitative data as an attractive nuisance: The problem of analysis, Administrative Science Quarterly, 24, pp. 590-601, (1979); Miles M.B., Huberman A.M., Qualitative Data Analysis: An Expanded Sourcebook, pp. 245-287, (1994); Moorthy S., Ratchford B.T., Talukdar D., Consumer information search revisited: Theory and empirical analysis, Journal of Consumer Research, 23, pp. 263-277, (1997); Noordewier T.G., John G., Nevin J.R., Performance outcomes of purchasing arrangements in industrial buyer-vendor relationships, Journal of Marketing, 54, pp. 80-93, (1990); Osborn R.N., Baughn C.C., Forms of interorganizational governance for multiple alliances, Academy of Management Journal, 33, 3, pp. 503-519, (1990); Palmisano S.J., There's no business like e-business, Directors and Boards, 22, pp. 38-40, (1998); Pastore M., Economic downturn slows B2B commerce, Cyberatlas. com, (2001); Patton M.Q., Qualitative Evaluation and Research Methods, (1990); Potter W.J., Levine-Donnerstein D., Rethinking validity and reliability in content analysis, Journal of Applied Communication Research, 27, 3, pp. 258-284, (1999); Nvivo Qualitative Data Analysis Program, (2000); Rayport J.F., Sviokla J.J., Exploiting the virtual value chain, Harvard Business Review, pp. 75-85, (1995); Sanchez R., Strategic flexibility, firm organization, and managerial work in dynamic markets: A strategic-options perspective, Advances in Strategic Management, 9, pp. 251-291, (1993); Skjoett-Larsen T., Third party logistics-from an interorganizational point of view, International Journal of Physical Distribution and Logistics Management, 30, 2, pp. 112-127, (1999); Stalk G., Time-the next source of competitive advantage, Harvard Business Review, pp. 41-51, (1988); Stern P.N., Grounded theory methodology: Its uses and processes, Image, 12, pp. 20-23, (1980); Strauss A.L., Qualitative Analysis for Social Scientists, (1987); Strauss A.L., Corbin J., Basics of Qualitative Research: Grounded Theory Procedures and Techniques, (1998); Swan J.E., Grounded theory: An inductive methodology for theory building research in marketing, Proceedings of the AMA Educator's Conference, pp. 348-354, (1985); Urbany J.E., Dickson P.R., Wilkie W.L., Buyer uncertainty and information search, Journal of Consumer Research, 16, pp. 208-215, (1989); Weiber R., Kollmann T., Competitive advantages in virtual markets-perspectives of \"information-based marketing' in cyberspace, European Journal of Marketing, 32, pp. 603-615, (1998)",{"$nulls":8},9600035.0,null,null,null,"English","Int. J. Phys. Distrib. Logist. Manage.","Article","Final",null,"Scopus","2-s2.0-2342439030"]
["Li S.-T.; Shue L.-Y.","Li, Sheng-Tun (8524895300); Shue, Li-Yen (7004463437)","8524895300; 7004463437","Towards XML-enabling E-Commerce infomediary: A case study in cargo tracking",2001.0,"Proceedings of the Hawaii International Conference on System Sciences",null,null,288.0,160.0,null,null,0.0,"10.1109/HICSS.2001.927038","https://www.scopus.com/inward/record.uri?eid=2-s2.0-0034965492&doi=10.1109%2fHICSS.2001.927038&partnerID=40&md5=432b7ef7f1e6dde54d3466cd2af05ba5","Department of Information Management, National Kaoshiung First University of Science and Technology, Yenchao, Kaohsiung, 1 University Road, Taiwan","Li S.-T., Department of Information Management, National Kaoshiung First University of Science and Technology, Yenchao, Kaohsiung, 1 University Road, Taiwan; Shue L.-Y., Department of Information Management, National Kaoshiung First University of Science and Technology, Yenchao, Kaohsiung, 1 University Road, Taiwan","In E-Commerce, the infomediary is rapidly becoming an important business model on the Web. It helps customers deal more efficiently and effectively with online vendors, and it also provides vendors with consumer information to help them focus on products and services customers want. In this paper, we propose a three-tier paradigm for developing a logistics infomediary. This paradigm integrates emerging technologies of the next-generation Web-based systems-XML, Java Servlet, and wireless computing-to address the three issues for the development: data acquisition, data analysis and extraction, and unified message exchange. It is capable of accepting requests from general browsers and retrieving data from different platforms of intended information sources, and presents them in a consistent and personalized format. An application was made to the air cargo tracking function to facilitate the operation of a customs clearance company.","Cargo tracking; EC; Infomediary; XML","Data acquisition; Data reduction; Information retrieval systems; Java programming language; Mobile computing; Online systems; Sales; Web browsers; World Wide Web; XML; Cargo tracking; Online vendors; Electronic commerce",{"$nulls":15},1.0603425E7,null,null,null,"English","Proc Hawaii Int Conf Syst Sci","Article","Final",null,"Scopus","2-s2.0-0034965492"]
["Tsay A.A.; Agrawal N.","Tsay, Andy A. (6603843787); Agrawal, Narendra (7103245210)","6603843787; 7103245210","Channel conflict and coordination in the E-commerce age",2004.0,"Production and Operations Management",13.0,1.0,null,93.0,110.0,17.0,844.0,"10.1111/j.1937-5956.2004.tb00147.x","https://www.scopus.com/inward/record.uri?eid=2-s2.0-5644302582&doi=10.1111%2fj.1937-5956.2004.tb00147.x&partnerID=40&md5=8b405badd9f67f089aa8e377a1f7d11d","Leavey School of Business, Santa Clara University, Santa Clara, CA 95053-0382, United States","Tsay A.A., Leavey School of Business, Santa Clara University, Santa Clara, CA 95053-0382, United States; Agrawal N., Leavey School of Business, Santa Clara University, Santa Clara, CA 95053-0382, United States","A number of factors, including developments in Internet-based commerce and third-party logistics, have led many companies to consider engaging in direct sales. Such a company may at once be both a supplier to and a direct competitor of any existing reseller partners (e.g., land-based retailers), which can result in \"channel conflict.\" This can have momentous implications for distribution strategy. To generate managerial insights into this important issue, we develop a model that captures key attributes of such a setting, including various sources of inefficiency. We examine these in detail and identify a number of counterintuitive structural properties. For instance, the addition of a direct channel alongside a reseller channel is not necessarily detrimental to the reseller, given the associated adjustment in the manufacturer's pricing. In fact, both parties can benefit. Finally, we examine ways to adjust the manufacturer-reseller relationship that have been observed in industry. These include changes in wholesale pricing, paying the reseller a commission for diverting customers toward the direct channel, or conceding the demand fulfillment function entirely to the reseller. The latter two schemes could be mutually beneficial in that they achieve a division of labor according to each channel's competitive advantage.","Catalog sales; Channel conflict; Channels of distribution; Coordination; Direct sales; Dual distribution; Electronic commerce; Game theory; Intermediaries; Internet commerce; Mathematical modeling; Resellers; Retail sales; Supply chain management",{"$nulls":7},"Ahn H., Duenyas I., Zhang R.Q., Price Competition between Retailers and Manufacturer-owned Stores, (2002); Artle R., Berglund S., A note on manufacturers' choice of distribution channels, Management Science, 5, 2, pp. 460-471, (1959); Axsater S., Continuous review policies for multi-level inventory systems with stochastic demand, Handbooks in Operations Research and Management Science, Vol. 4 (Logistics of Production and Inventory), 4, pp. 175-197, (1993); Balderston F.E., Communication networks in intermediate markets, Management Science, 4, 2, pp. 154-171, (1958); Baligh H.H., Richartz L.E., An analysis of vertical market structures, Management Science, 10, 4, pp. 667-689, (1964); 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Tsay; Leavey School of Business, Santa Clara University, Santa Clara, CA 95053-0382, United States; email: atsay@stanfordalumni.org",null,"Florida International University",{"$nulls":5},1.0591478E7,null,null,null,"English","Prod. Oper. Manage.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-5644302582"]
["Fridensköld E.","Fridensköld, Emilie (57208997181)",5.7208997181E10,"VAT and the internet: The application of consumption taxes to e-commerce transactions",2004.0,"Information and Communications Technology Law",13.0,2.0,null,175.0,203.0,28.0,5.0,"10.1080/13600830410001687273","https://www.scopus.com/inward/record.uri?eid=2-s2.0-38549126398&doi=10.1080%2f13600830410001687273&partnerID=40&md5=0150a9ea8e5bbb4bc651a96b5c561cd3","District Court of Örebro, Sweden","Fridensköld E., District Court of Örebro, Sweden","The taxation of citizens' consumption of goods and services is of great importance for government revenue worldwide. However, the constantly growing Internet market is changing the ways in which those goods and services are acquired and consumed, making it difficult to administer and enforce existing tax rules. Tax rules, being directly connected to the government's chosen policy of raising revenue to finance its spending on the public sector, are matters of a highly sovereign nature, and their efficient working clashes with the inherently borderless and intangible nature of the Internet. New methods of delivery and new categories of products that can be delivered between jurisdictions without passing any physical borders raise particular problems for VAT purposes. To achieve the twin goals of encouraging e-commerce and protecting national revenue bases, international cooperation must be sought in the development of mechanisms to collect tax in the new digital commercial environment. Without a mutual understanding of common interests and respect for domestic tax policies, the changing dynamic in commerce to which the Internet is giving rise may prove an unbeatable barrier to the efficient working of a VAT system that guarantees fair competition between suppliers, and provides technological neutrality and equity among consumers. © 2004, Taylor & Francis Group, LLC.",{"$nulls":8},"(2003); (2003); Basu S., European VAT on digital sales, Journal of Information, Law and Technology, 3, (2002); Bevers G., Value added tax and electronic commerce, British Tax Review, 6, (1998); Bleuel J., Stewen M., Grundlegende Probleme einer Besteuerung von Internettransaktionen, Wirtschaftsdienst, (1998); Bleuel J., Stewen M., Value added taxes on electronic commerce: Obstacles to the EU Commission's approach, Intereconomics, 35, (2000); Chan C.W., Taxation of global e-commerce on the Internet: The underlying issues and proposed plans, Minnesota Journal of Global Trade, (2000); Chissick M., Alistair Kelman A., Electronic Commerce Law and Practice, (2002); Clinton W.J., Gore A., A Framework for Global Electronic Commerce, (1997); (2000); (2003); Dickie J., Internet and Electronic Commerce Law in the European Union, (1999); Doernberg R., Electronic commerce and international tax sharing, Tax Notes International, (1998); Eden S., The taxation of electronic commerce, Law and the Internet: Regulating Cyberspace, (1997); (1997); (1996); (1997); (1998); (1998); (1999); (2000); (2000); (2000); (2001); Fairpo A., VAT and e-commerce, (2002); Fawkes T., The proposed EU VAT on electronically transmitted services: Enforcement and compliance issues, Northwestern Journal of International Law and Business, 22, (2001); Frieden K.A., Porter M.E., The taxation of cyberspace: State tax issues related to the Internet and electronic commerce, State Tax Notes, (1996); Gershuny P., Gruber J., Tax and the Internet, International Company and Commercial Law Review, 11, 2, (2000); Goolsbee A., In a world without borders: The impact of taxes on Internet commerce, Quarterly Journal of Economics, 115, 2, (2000); Goolsbee A., Zittrain J., Evaluating the costs and benefits of taxing Internet commerce, National Tax Journal, 52, (1999); Gringras C., The Laws of the Internet, (2003); Hardesty D., Europe proposes new taxes on non-EU sellers, (2000); Hardesty D., EU tries again for laws to tax downloads, (2001); Hardesty D., European VAT on digital sales, (2002); Hickey J.J.B., The fiscal challenge of e-commerce, British Tax Review, 2, (2000); (1998); (1999); James S., Nobes C., The Economics of Taxation, (2000); Johnston N., Administration urges keeping online-tax ban, The Washington Post, (2003); Jones R., Basu S., Taxation of electronic commerce: A developing problem, International Review of Law, Computers and Technology, 16, 1, (2002); Kay J.A., King M.A., The British Tax System, (1990); Korf R., Six thoughts on the VAT treatment of electronic commerce, (2000); Krever R., Electronic commerce and taxation: An overview of the key issues, Asia-Pacific Tax Bulletin, (2000); Lloyd I.J., Information Technology Law, (2000); Lukas A., Tax bytes—A primer on the taxation of electronic commerce, Trade Policy Analysis, 9, (1999); Lukas A., Closing the net tax debate (part 1): The myth of the level playing field, TechKnowledge, 22, (2001); Mann C.L., Electronic commerce in developing countries: Issues for domestic policy and WTO negotiations, (2000); Marsh C.L., Electronic commerce and tax competition: When consumers can shop across borders and online, (2000); McCaleb I.C., States argue for taxing Internet transactions, (2001); Mecklenburg K.S.V., The legal issues of Internet taxation, Computer Law and Security Report, 15, 4, (1999); (2002); (2002); O'Donnell T.A., Levey M.M., Powers J.P., International tax issues for cyberspace transactions, (2000); (1997); (1998); (2000); (2001); (2001); (2001); Piazolo D., Multilateral and European responses to e-commerce, European Integration Online Papers, 5, 4, (2001); Riksskatteverket, Handledning för Mervärdesskatt, (2002); Rosander D., Handla på nätet lockar allt fler, Svenska Dagbladet, (2004); Sanderson C., EU forges ahead on e-commerce, International Tax Review, 11, 8, (2000); Schulzki-Haddouti C., Steuern für das Internet, c't Magazin für Computer Technik, (1998); Smith G.J.H., Internet Law and Regulation, (2002); Snel J.L.N., European Union reaches out across borders: European Union proposes to tax US-based e-commerce companies with value added TAX in the European Union, (2000); Snel J.L.N., Taxation of electronic commerce: E-commerce developments and EU VAT, (2000); Swindells C., Henderson K., Legal regulation of electronic commerce, Journal of Information, Law and Technology, 3, (1998); Teltscher S., Tariffs, taxes and electronic commerce: Revenue implications for developing countries, (2000); Terra B., Kajus J., Introduction to the VAT in the EC after 1992, (1995); Terra B., Wattel P., European Tax Law, (1992); Terret A., A lawyer's introduction to the Internet, Law and the Internet: Regulating Cyberspace, pp. 1-16, (1997); Thierer A., Closing the net tax debate (part 2): Identifying the real sales tax drain, Techknowledge, 23, (2001); Williams D.W., EC Tax Law, (1998); Woodside S., Electronic Commerce: Answering the Emerging Taxation Challenges, (1999)",{"$nulls":8},1.3600834E7,null,null,null,"English","Inf. Commun. Technol. Law","Article","Final",null,"Scopus","2-s2.0-38549126398"]
["Chondrocoukis G.","Chondrocoukis, Gregory (36863306900)",3.68633069E10,"E-Commerce in pharmacy - the Greek reality",2004.0,"Journal of Interdisciplinary Mathematics",7.0,1.0,null,1.0,27.0,26.0,1.0,"10.1080/09720502.2004.10700355","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84890049793&doi=10.1080%2f09720502.2004.10700355&partnerID=40&md5=2c70789cd88c6fcc781ecdbab9b3d705","Department of Industrial Management and Technology, University of Piraeus, 18534 Piraeus, 80 Karaoli and Dimitriou Street, Greece","Chondrocoukis G., Department of Industrial Management and Technology, University of Piraeus, 18534 Piraeus, 80 Karaoli and Dimitriou Street, Greece","This article examines matters related to Electronic Commerce (EC), the pharmaceutical field and their interrelation. The pharmaceutical industry indulges in EC mainly so as to ameliorate its transactions, its communications and the promotion of its products (B2B EC); whereas the greater availability of products and medical advice, home delivery and the consequent gain in time, have been well appreciated from the consumer's point of view (B2C EC). However promising a technology though, B2C EC raises a variety of ethical and legal concerns. On the one hand, a clear distinction seems to exist between online prescriptions and online pharmacies. Therefore, while it may be acceptable to sell medication over the Internet given the current technologies, it must be done within the confines of a traditional doctor-patient and pharmacist-patient relationship. On the other hand, online prescriptions must be limited to patients who live in regions in which the prescribing doctor and pharmacist are licensed. Furthermore, the validity of online prescriptions and pharmacies should be verified by legal and voluntary regulatory agencies set up for this cause. The U.S. are the undoubted pioneers in the application of EC in pharmacy, whilst Europe is currently considering the terms of such applications. Sole country that seems to be making decisions in favor of electronic pharmacies so far is the United Kingdom. As far as Greece is concerned, EC of pharmaceuticals, namely of prescription drugs, is prohibited. An online research that took place during February/April 2002 illustrates how merely 0.19% of private pharmacies, 1.38% of drug wholesalers and 0.94% of pharmaceutical companies utilize some types of EC services. In conclusion, the establishment of the requisite regulatory mechanisms for the adoption of EC in pharmacy may give rise to the improvement of customer service, of health care provisions and of qualitative communication amongst patients and health scientists. © Taru Publications.",null,"Mathematical techniques; Current technology; Customer services; Pharmaceutical company; Pharmaceutical fields; Pharmaceutical industry; Prescription drugs; Regulatory agencies; Regulatory mechanism; Electronic commerce",{"$nulls":6},"(2000); Baker D.B., Masys P., Design For Secure Communication of Personal; Brailer D.J., Hackett T.S., Points (& Clicks) On Quality, Hosp. Health Netw., 71, (1997); Casey M., The Internet Writes Its Own Prescription, (1999); Cashin J.R., Ads may cause adverse reaction, Best's Review, 2, 101, (1999); Damster G., Williams J.R., The Internet, virtual communities and threats to confidentiality, S-Afr-Med-J, 89, 11, pp. 1175-1178, (1999); Business: Click and drug (Editorial), Economist, pp. 348-352, (1998); Distribution of Pharmaceutical Products Via Internet; Fisher D., 163, 10, pp. 73-74, (1999); Granade P.F., Medical malpractice issues related to the use of telemedicine - an analysis of he ways in which telecommunications affect the principle of medical malpractice, N.D, Law Rev, 73, (1997); Kahan S.E., Seftel A.D., Resnick M.I., Sildenafil and the Internet, The Journal of Urology, 163, 3, pp. 919-923, (2000); Kalakota R., Whinston A.B., Electronic Commerce: A Manager's Guide, (1997); Lin B., Internet in the pharmaceutical industry: Infrastructure issues, American Business Review, 18, 1, pp. 101-106, (2000); McConnell J., Internet Subverts European Drug Regulation, 352, (1998); Meek D.F., Telemedicine: How an Apple (or another computer) may bring your doctor closer, Cumberland Law Rev, 29, (1999); (2000); Opderback D.W., How should FDA regulate prescription drug promotions on the Internet, Food Drug Law J, 53, (1998); Pharmaceutical Guide, (2002); Reiser S.J., Medicine and The Reign of Technology, (1981); Rekkas D., Korakianiti E., Buying Drugs On the Internet, 66, pp. 30-36, (2000); Rubin R., Your Drugstore is Just a Few Clicks Away, (1999); Rublin L.R., 17, 79, (1999); Spielberg A.R., On call and online: Sociohistorical, legal and ethical implications of e-mail for patient-physician relationships, JAMA, 280, (1998); Stevens L., E-pharmacies a Slow Go-Marketing Prescriptions On the Internet Still Seen As a Big Headache, 28, (2000); Tilenius S.S., pp. 54-56, (2000); Turban E., Lee J., King D., Chung H.M., Electronic Commerce: A Managerial Perspective, pp. 361-362, (2000); Walker J.F., Telehealth a complex issue being addressed by state and federal governments, AORN J, 66, (1997)",{"$nulls":8},9720502.0,null,null,null,"English","J. Interdiscip. Math.","Article","Final",null,"Scopus","2-s2.0-84890049793"]
["Hou J.-L.; Trappey C.V.","Hou, Jiang-Liang (7401966140); Trappey, Charles V. (6603075752)","7401966140; 6603075752","Connecting small and medium enterprises to the global market via the global logistics service chain—sector analyses and case studies",2002.0,"Journal of the Chinese Institute of Industrial Engineers",19.0,5.0,null,75.0,87.0,12.0,5.0,"10.1080/10170660209509361","https://www.scopus.com/inward/record.uri?eid=2-s2.0-24644496104&doi=10.1080%2f10170660209509361&partnerID=40&md5=08f42924daba97bba5138522e9ddaf2a","Department of Industrial Engineering and Engineering Management, National Tsing Hua University, Hsinchu, 300, 101, Section 2, Kuang Fu Road, Taiwan; Department of Management Science, National Chiao Tung University, Taiwan","Hou J.-L., Department of Industrial Engineering and Engineering Management, National Tsing Hua University, Hsinchu, 300, 101, Section 2, Kuang Fu Road, Taiwan; Trappey C.V., Department of Management Science, National Chiao Tung University, Taiwan","Developing countries, such as Taiwan, Singapore and Korea, are transforming to a multi-faceted consumer economy where financial services, medical services, research and development, education, distribution services, international business, technology product development and design, and retail development are fueling economic growth. The logistic and distribution services as a result have become information and technology-oriented businesses with global status. In order to maintain competitiveness in the global market, economic entities, such as Taiwan, are developing modern distribution channels not only for the local market, but also for the surrounding region and for the global marketplace. The local channel must act as an integrated link and intermediary source for other widely distributed supply and demand chains. During the last decade, global distribution channels have undergone accelerated transformation. This paper describes the business operations of critical components supporting the modern value chain underlying the distribution and logistics industry. Statistical data and four industry cases demonstrate the trends and future for Taiwan firms as members of the global logistics network. A wealth of information and a spirit of openness, new partnerships and international outreach are creating business opportunities around the world. The case studies and benchmark statistics provide the basis for proposing an e-commerce driven logistics center model applicable to serve small and medium enterprises in developing regions. © 2002 Taylor & Francis Group, LLC.","Demand chain; Distribution center; Global logistics; Supply chain","Data reduction; Electronic commerce; Industrial economics; Logistics; Marketing; Statistical methods; Technology transfer; Demand chain; Distribution center; Global logistics; Supply chain; Industrial management",{"$nulls":4},"Nation Science Council of the Republic of China, (NSC89-2218-E-212-014, NSC90-2218-E-007-066)","This research was partially supported by the Nation Science Council of the Republic of China (NSC89-2218-E-212-014, NSC90-2218-E-007-066).","Berg J.P., Zijm W.H.M., Models for warehouse management: Classification and examples, International Journal of Production Economics, 59, 1, pp. 519-528, (1999); Braam I.T.J., Dormolen M., Frings M.H.W., The work load of warehouse workers in three different working systems, International Journal of Industrial Ergonomics, 17, 6, pp. 469-480, (1996); Carlson J.G., Yao A.C., A visually interactive expert system for a distribution center environment, International Journal of Production Economics, 45, 1, pp. 101-109, (1996); Chen C.T., A fuzzy approach to select the location of the distribution center, Fuzzy Sets and System, 118, 1, pp. 65-73, (2001); Chen C.Y., Lin C.C., Discussion on Locations for the Domestic Break-bulk Transportation Industry, (2000); Das C., Tyagi R., Role of inventory and transportation costs in determining the optimal degree of centralization, Transportation Research Part E: Logistics and Transportation Review, 33, 3, pp. 171-179, (1997); Dubi A., Gurvitz N., A note on the analysis of systems with time dependent transition rates, Annals of Nuclear Energ, 22, 3, pp. 215-248, (1995); Geunes J., Zeng A.Z., Impacts of inventory shortage policies on transportation requirements in two-stage distribution systems, European Journal of Operational Research, 129, 2, pp. 299-310, (2001); Heijden M.C., Multi-echelon inventory control in divergent systems with shipping frequencies, European Journal of Operational Research, 116, 2, pp. 331-351, (1999); Hwang H.S., A food distribution model for famine relief, Computers and Industrial Engineering, 37, 1, pp. 335-338, (1999); Hwang H.S., Inventory models for both deteriorating and ameliorating items, Computers and Industrial Engineering, 37, 1, pp. 257-260, (1999); Jansen D.R., Weert A.V., Beulens A.J.M., Huirne R.B.M., Simulation model of multi-compartment distribution in the catering supply chain, European Journal of Operational Research, 133, 1, pp. 210-224, (2001); Jayaraman V., Pirkul H., Planning and coordination of production and distribution facilities for multiple commodities, European Journal of Operational Research, 133, 2, pp. 394-408, (2001); Korpela J., Tuominen M., A decision aid in warehouse site selection, International Journal of Production Economics, 45, 3, pp. 169-180, (1996); Lin C.H., Lu I.Y., The procedure of determining the order picking strategies in distribution center, International Journal of Production Economics, 60, 1, pp. 301-307, (1999); Min H., Jayaraman V., Srivastava R., Combined location-routing problems: A synthesis and future research direction, European Journal of Operational Research, 108, 1, pp. 1-15, (1998); Logistics Industry White Book, (2000); Ministry of Economic Affair's Business Automation Series, (1995); Taiwan Logistics Yearbook, (2000); Morabito R., Morales S.R., Widmer J.A., Loading optimization of palletized products on truck, Transportation Research Part E: Logistics and Transportation Review, 36, 4, pp. 285-296, (2000); Nozick L.K., Turnquist M.A., Inventory, transportation, service quality and the location of distribution centers, European Journal of Operational Research, 129, 2, pp. 362-371, (2000); Ogryczak W., On the distribution approach to location problem, Computers and Industrial Engineering, 37, 3, pp. 595-612, (1999); Rabinowitz G., Mehrez A., A multi-echelon multi-commodity, logistic system design at the Dead Sea Works Ltd, Computers and Industrial Engineering, 39, 2, pp. 65-79, (2001); Taniguchi E., Noritake M., Yamada T., Izumitani T., Optimal size and location planning of public logistics terminals, Transportation Research Part E: Logistics and Transportation Review, 35, 3, pp. 207-222, (1999); Trappey C.V., Hou J.L., The Taiwan Distribution Market, (2001); Vidal C.J., Goetschalckx M., Strategic production-distribution models: A critical review with emphasis on global supply chain models, European Journal of Operational Researc, 98, 1, pp. 1-18, (1997); Vroblefski M., Ramesh R., Zionts S., Efficient lot-sizing under a differential transportation cost structure for serially distributed warehouse, European Journal of Operational Research, 127, 3, pp. 574-593, (2000)","J.-L. Hou; Department of Industrial Engineering and Engineering Management, National Tsing Hua University, Hsinchu, 300, 101, Section 2, Kuang Fu Road, Taiwan; email: adamhou@ie.nthu.edu.tw",{"$nulls":7},1.0170669E7,null,null,null,"English","J. Chin. Inst. Ind. Eng.","Article","Final",null,"Scopus","2-s2.0-24644496104"]
["Barnes D.; Hinton M.; Mieczkowska S.","Barnes, David (57202034114); Hinton, Matthew (7102533979); Mieczkowska, Suzanne (7801636267)","57202034114; 7102533979; 7801636267","Managing the transition from bricks-and-mortar to clicks-and-mortar: A business process perspective",2004.0,"Knowledge and Process Management",11.0,3.0,null,199.0,209.0,10.0,15.0,"10.1002/kpm.205","https://www.scopus.com/inward/record.uri?eid=2-s2.0-33744774810&doi=10.1002%2fkpm.205&partnerID=40&md5=d30b043b905c69b8e65f00c8e9c126c0","Royal Holloway, University of London, United Kingdom; Open University Business School, United Kingdom","Barnes D., Royal Holloway, University of London, United Kingdom; Hinton M., Open University Business School, United Kingdom; Mieczkowska S., Open University Business School, United Kingdom","This paper reports from case study-based research that investigates the impact of the transition from bricks-and-mortar to clicks-and-mortar businesses on the management of core internal business processes. It has two main aims: firstly, to identify the business models for the processes of order fulfilment and delivery used in clicks-and-mortar e-businesses, and any organizational and environmental factors affecting these processes; secondly, to identify the main factors involved in the adoption and use of Internet-based ICTs for e-commerce in clicks-and-mortar e-businesses, and any organizational and environmental factors affecting adoption and use. Results from eight UK-based companies that have been changing from traditional bricks-and-mortar companies to clicks-and-mortar e-businesses are reported. Five main conclusions are drawn from a cross-case analysis: (1) increased integration in e-commerce business processes is inhibited by both technological and business barriers; (2) organizations display various and often confused motives for adopting e-commerce; (3) barriers to the increased adoption of e-commerce are not just technological, but also sociological and economic; (4) the adoption of e-commerce challenges existing supply network relationships; (5) the adoption of e-commerce is tending to automate rather than redesign existing business processes. A three-pronged approach to future research work in this under-researched area is recommended. This encompasses undertaking longitudinal case study research to track e-commerce developments over time, extending the range of cases to include other industry sectors (such as not for profits), and undertaking survey research across a large number of organizations, using quantitative methods, to test the generalizability of the findings from this research. © 2004 John Wiley & Sons, Ltd.",{"$nulls":8},"Anupindi R., Chopra S., Deshmukh S.D., Van Mieghem J.A., Zemel E., Managing Business Process Flows, (1999); Armistead C., Machin S., The implications of business process management for operations management, Industrial Management, 17, 9-10, pp. 886-899, (1997); Barnes D.L., Hinton C.M., Mieczkowska S.M., Developing a framework to investigate the impact of e-commerce on the management of internal business processes, Knowledge and Process Management, 9, 3, pp. 133-142, (2002); Boddy D., Boonstra A., Kennedy G., Managing the Information Revolution, (2001); Bryman A., Quantity and Quality in Social Research, (1988); Childe S.J., Maull R.S., Bennett J., Frameworks for understanding business process re-engineering, International Journal of Operations and Production Management, 14, 12, pp. 22-34, (1994); Christopher M., Logistics and Supply Chain Management, (1998); Davenport T., Process Innovation: Reengineering Work Through Technology, (1993); Eisenhardt K.M., Building theories from case study research, Academy of Management Review, 14, 4, pp. 532-550, (1989); Hammer M., Re-engineering work: don't automate, obliterate, Harvard Business Review, pp. 104-112, (1990); Hammer M., Beyond Re-engineering, (1996); Hammer M., Champy J., Reengineering the Corporation, (1993); Harrington H.J., Business Process Improvement, (1992); Katz D., Kahn R.L., The Social Psychology of Organizations, (1978); Meredith J.R., Raturi A., Amoako-Gympah K., Kaplan B., Alternative research paradigms in operations, Journal of Operations Management, 8, 4, pp. 297-326, (1989); Miles M.B., Hubermann A.M., Qualitative Data Analysis, (1994); Poon S., Swatman P., An exploratory study of small business Internet commerce issues, Information and Management, 35, pp. 9-18, (1999); Shapiro B.P., Rangan V.K., Sviokla J.J., Staple yourself to an order, Harvard Business Review, pp. 113-122, (1992); Slack N., Chambers S., Johnston R., Operations Management, (2001); Wigand R., Electronic commerce: definition, theory and context, The Information Society, 13, pp. 1-16, (1999); Yin R.K., Case Study Research, (1994)","D. Barnes; School of Management, Royal Holloway, University of London, Egham, Surrey, TW20 0EX, United Kingdom; email: david.barnes@rhul.ac.uk",{"$nulls":7},1.0924604E7,null,null,null,"English","Knowl. Process Manage.","Article","Final",null,"Scopus","2-s2.0-33744774810"]
["Deakins E.; Dillon S.","Deakins, Eric (8969565600); Dillon, Stuart (8969565500)","8969565600; 8969565500","A helical model for managing innovative product and service initiatives in volatile commercial environments",2005.0,"International Journal of Project Management",23.0,1.0,null,65.0,74.0,9.0,14.0,"10.1016/j.ijproman.2004.05.007","https://www.scopus.com/inward/record.uri?eid=2-s2.0-11944250245&doi=10.1016%2fj.ijproman.2004.05.007&partnerID=40&md5=07763d6dfc698f8749a70b71f6b60cb3","Department of Management Systems, Waikato Management School, University of Waikato, Hamilton, Private Bag 3105, New Zealand","Deakins E., Department of Management Systems, Waikato Management School, University of Waikato, Hamilton, Private Bag 3105, New Zealand; Dillon S., Department of Management Systems, Waikato Management School, University of Waikato, Hamilton, Private Bag 3105, New Zealand","Organisations operating in highly competitive and volatile commercial environments require the ability to cost-effectively build market share quickly, via rapid time-to-market of repeated high quality and innovative solutions. This has created the need for an approach to product development that encourages experimentation and mass customisation, yet also allows just in time (JIT) delivery of cutting edge solutions. This paper reports on field research with a dotcom start-up company that evolved a traditional spiral (software) development methodology into a generic management tool suitable for the design, production, and marketing of innovative, high-quality e-commerce products and services. Advantages and limitations of the method are presented and its generalisability to a range of projects is illustrated, with the aid of Action Learning undertaken within an academic setting. © 2004 Elsevier Ltd and IPMA. All rights reserved.","Innovation; Managing projects; Technology","Competition; Cost effectiveness; Electronic commerce; Just in time production; Marketing; Mathematical models; Project management; Societies and institutions; Software engineering; commercial activity; innovation; project management; Generalizablity; Market shares; Mass customization; Product development",{"$nulls":6},"(2003); Johnson J., Turning chaos into success, reported in SoftwareMag.com, 1999, (2003); Deakins E., Dillon S.M., Managing innovative IS projects in dotcom companies, Proceedings of the Pacific Asia Conference on Information Systems (PACIS2000), (2000); Prahalad C.K., Ramaswamy V., Co-opting customer competence, Harvard Bus. Rev., (2000); Gray C.F., Larson E.W., Project management: The managerial process, (2000); Keen P.G.W., Knapp M., Business processes, (1996); Haeckel S.H., Adaptive enterprise: Creating and leading sense-and-respond organizations, (1999); Boar B.H., Strategic thinking for information technology, (1997); Forrester J.W., Principles of systems, (1968); England E., Finney A., Managing multimedia, (1996); Wynekoop J.L., Russo N.L., Systems development methodologies; unanswered questions, J. Inform. Technol., pp. 65-73, (1995); Fitzgerald B., The use of systems development methodologies in practice: A field study, Inform. Syst. J., 7, 3, pp. 201-212, (1997); Paynter J., Pearson M., An analysis of WWW-based information systems, Multimedia Information Systems in Practice, pp. 53-63, (1999); Yourdon E., Developing applications for the Internet: Advice for the Java generation, Am. Program., pp. 36-41, (1996); Gellersen H.-W., Wicke R., Gaedke M., Web composition: An object-oriented support system for the web engineering lifecycle, Comput. Networks ISDN Syst., 29, pp. 429-437, (1997); Morrell P., Building intranet-based information systems for international companies, Aslib Proc., 49, 2, pp. 27-31, (1997); Wynekoop J.L., Russo N.L., Studying system development methodologies an examination of research methods, Inform. Syst. J., 1, pp. 47-65, (1997); Barry C., Lang M., A survey of multimedia and web development techniques and methodology usage, IEEE Multimedia, 8, 3, pp. 52-60, (2001); Orlikowski W.J., CASE tools as organizational change: Investigating incremental and radical changes in systems development, MIS Quart., 17, 3, pp. 309-340, (1993); Wastell D.G., The Fetish of technique: Methodology as a social defence, Inform. Syst. J., 6, pp. 25-49, (1996); Fitzgerald B., Formalized systems development methodologies: A critical perspective, Inform. Syst. J., 6, pp. 3-23, (1996); Nandhakumar J., Avison D.E., The fiction of methodological development: A field study of information systems development, Inform. Technol. People, 12, 2, pp. 176-191, (1999); Veryard R., What are methodologies good for?, Data Process., 27, 6, pp. 9-12, (1985); Ould M.A., Strategies for software engineering: The management of risk and quality, (1990); (2003); McConnell S.C., Rapid development: Taming wild software schedules, (1996); Royce W., Software project management: A unified approach, (1998); Smith P.G., A portrait of risk, PM Network, pp. 44-48, (2003); Remertsen D.G., Managing the design factory: A product developer's toolkit, (1997); Smith P.G., Leverage the cycle time capability of your rapid prototypes, Time Compress. Technol., 7, 2, pp. 50-57, (1999); Livari J., Hierarchical spiral model for information system and software development - Part 1: Theoretical background, Inform. Software Technol., 32, 6, pp. 386-399, (1990); Simon H.A., Rational choice and the structure of the environment, Models of Man, (1957); Deakins E., Makgill H.H., The importance of alignment in business process change projects, Proceedings of the Ninth Australasian Conference on Information Systems Sydney, pp. 148-160, (1998); Tong G., Software development process improvement: The forgotten son?, World Class Design to Manufacture, 1, 3, pp. 21-25, (1994); Fitzgerald B., Systems development methodologies: The problem of tenses, Inform. Technol. People, (1999); Boahene M., Information systems development methodologies: Are you being served?, Proceedings of 10th Australasian Conference on Information Systems, (1999); Howard A., A new RAD-based approach to commercial information systems development: The dynamic system development method, Ind. Manage. Data Syst., 97, 5, pp. 175-177, (1997)","E. Deakins; Department of Management Systems, Waikato Management School, University of Waikato, Hamilton, Private Bag 3105, New Zealand; email: edeakins@waikato.ac.nz",{"$nulls":7},2637863.0,null,null,null,"English","Int. J. Proj. Manage.","Article","Final",null,"Scopus","2-s2.0-11944250245"]
["Trappey A.J.C.; Trappey C.V.; Hou J.-L.; Chen B.J.G.","Trappey, Amy J.C. (7003314683); Trappey, Charles V. (6603075752); Hou, Jiang-Liang (7401966140); Chen, Bird J.G. (7408608758)","7003314683; 6603075752; 7401966140; 7408608758","Mobile agent technology and application for online global logistic services",2003.0,"Industrial Management and Data Systems",104.0,"2024-02-01",null,169.0,183.0,14.0,52.0,"10.1108/02635570410522143","https://www.scopus.com/inward/record.uri?eid=2-s2.0-2342418969&doi=10.1108%2f02635570410522143&partnerID=40&md5=731994ffc9ad029f547ba1c9ac340a64","Department of Industrial Engineering, National Tsing Hua University, Hsinchu, Taiwan; Department of Management Science, National Chiao Tung University, Hsinchu, Taiwan","Trappey A.J.C., Department of Industrial Engineering, National Tsing Hua University, Hsinchu, Taiwan; Trappey C.V., Department of Management Science, National Chiao Tung University, Hsinchu, Taiwan; Hou J.-L., Department of Industrial Engineering, National Tsing Hua University, Hsinchu, Taiwan; Chen B.J.G., Department of Industrial Engineering, National Tsing Hua University, Hsinchu, Taiwan","With the growing trend toward the use of international supply chain and e-commerce, logistic service providers for product warehousing, transportation and delivery are placing great emphasis on information technology (IT) to be competitive globally. Realizing that the current service tracking system merely supports order status tracking within a service provider, applies mobile agent technology for online order tracking across the global logistic alliances. Utilizes a three-tier architecture for mobile agent technology and develops a prototype system for global logistic service tracking. Demonstrates the concept and technology proposed. The online service tracking services enable customers to monitor the real-time status of their service requests and therefore becomes key tool for modern enterprises to compete successfully in a global marketplace.","Logistics management; Real time scheduling; Services","Costs; Data processing; Electronic commerce; Information technology; Internet; Inventory control; Investments; Scheduling; Societies and institutions; Global logistic services; Logistics management; Mobile agent technology; Real time scheduling; Industrial management",{"$nulls":6},"Adam E., Vergison E., Mandiau R., Kolski C., Interaction with agent systems for technological watch, Usability Evaluation and Interface Design, pp. 489-493, (2001); Aitken J., Supply Chain Integration Within the Context of a Supplier Association, (1998); Anton J., Call Center Benchmark Report, (2000); (1999); Chandra C., Kumar S., Enterprise architectural framework for supply-chain integration, Industrial Management & Data Systems, 101, 6, pp. 290-304, (2001); Falchuk B., Ahmed K., A mobile agent prototype for autonomous multimedia information access, interaction, and retrieval, Proceedings of Multimedia Modeling, (1997); Fischer K., Mueller J.P., Heimig I., Scheer A.-W., Intelligent agents in virtual enterprises, Proceedings of PAAM'96, pp. 205-223, (1996); Florescu D., Alon L., Alberto M., Database Techniques for the World Wide Web: A Survey, (1998); Graesser A., Is it an agent, or just a program? A taxonomy for autonomous agents, Proceedings of 3rd International Workshop on Agent Theories, Architectures, and Languages, (1996); Huang S.-M., Kwan I.S.Y., Hung Y.-C., Planning enterprise resources by use of a reengineering approach to build a global logistics management system, Industrial Management & Data Systems, 101, 9, pp. 483-491, (2001); Lummus R.R., Krumwiede D.W., Vokurka R.J., The relationship of logistics to SCM: Developing a common industry definition, Industrial Management & Data Systems, 101, 8, pp. 426-432, (2001); Martin C., Logistics and Supply Chain Management, 273, 3, pp. 84-86, (1998); Mayes P., Intelligent software, Scientific American, (1995); Yearbook of Logistic Service Industry in Taiwan, (2000); Morreale P., Agents on the move, IEEE Spectrum, pp. 34-41, (1998); Nwana H.S., Azarmi N., Soft agents and soft computing: Concepts and applications, Lecture Notes in Artficial Intelligence, 1198, (1997); (1998); Rothermel K., Hohl F., Radouniklis N., Mobile agent systems: What is missing, Proceedings of the International Working Conference on Distributed Applications and Interoperable Systems DAISY97, (1997); Trappey C.V., Hou J.-L., The Taiwan Distribution Market, (2001); Van Dyke Parunak H., What can agents do in industry, and why?, Proceedings of PAAM, pp. 205-223, (1996); Watson R., Pitt L., Remarrying marketing and logistics with information systems technology, Industrial Management & Data Systems, 89, (1989); Wooldridge J., Intelligent agents: Theory and practice, The Knowledge Engineering Review, 10, 2, pp. 115-152, (1995)",null,null,"Emerald Group Publishing Ltd.",{"$nulls":5},2635577.0,null,"IMDSD",null,"English","Ind Manage Data Sys","Article","Final",null,"Scopus","2-s2.0-2342418969"]
["Leung L.C.; Cheung W.; Hui Y.V.","Leung, Lawrence C. (7202048181); Cheung, Waiman (7202743106); Hui, Yer Van (7103107708)","7202048181; 7202743106; 7103107708","A framework for a logistics E-commerce community network: The Hong Kong air cargo industry",2000.0,"IEEE Transactions on Systems, Man, and Cybernetics Part A:Systems and Humans.",30.0,4.0,null,446.0,455.0,9.0,34.0,"10.1109/3468.852438","https://www.scopus.com/inward/record.uri?eid=2-s2.0-0034228370&doi=10.1109%2f3468.852438&partnerID=40&md5=a2af778a03f0bb9f550926a2652b9ddc","Decision Sciences and Managerial Economics, Chinese University of Hong Kong, Hong Kong; Management Sciences, City University of Hong Kong, Hong Kong","Leung L.C., Decision Sciences and Managerial Economics, Chinese University of Hong Kong, Hong Kong; Cheung W., Decision Sciences and Managerial Economics, Chinese University of Hong Kong, Hong Kong; Hui Y.V., Management Sciences, City University of Hong Kong, Hong Kong","E-commerce has brought new challenges as well as opportunities to the air cargo industry. With careful planning and cooperation among industry agents and with e-commerce as an enabler, the air cargo industry can be transformed into one that can provide customized services to individual shippers at the cost level of mass production. The key component is in the setting up of a third-party e-commerce community network. In this paper, we present a framework for such a network, which extends the traditional business-to-business (B2B) e-commerce to e-commerce at the industry level. The proposed infrastructure differs from traditional portals in that it features the online integration of business transactions. It provides a virtual market for agents of the air cargo industry, enabling them to develop and engage in logistics integration. It also facilitates tracking and tracing, and minimizes unnecessary travel and inventory costs - thus achieving Supply Chain Management (SCM) at the industry level. The establishment of a global community network will be a challenging endeavor. We provide an implementation scenario for the air cargo industry in Hong Kong. © 2000 IEEE.","Air cargo; E-commerce; Hong Kong; Integration; Logistics; Marketplace","Telecommunication services; Virtual reality; Supply chain management (SCM); Electronic commerce",{"$nulls":6},"Alt R., Cathomen I., Handbuch Interorganizationssysteme, (1995); Auger P., Gallaugher J.M., Factors affecting the adoption of an internet-based sales presence for small businesses, Inform. Soc., 13, 1, pp. 55-74, (1997); Benjamin R., Wigand R., Electronic markeets and virtual value chains on the information superhighway, Sloan Manage. Rev., pp. 62-72, (1995); Chiu H.N., The integrated logistics management system: A framework and case study, Int. J. Physical Distribution and Logistics Management, 25, 6, pp. 4-22, (1995); DHL Investment in Super Regions; Euwe M.J., Wortmann J.C., Logistics control enabled by IT - A window in the future, Human Systems Management, 17, 2, pp. 123-136, (1998); Federal Express, 1999 Annual Report; Gooley T.B., Air freight gears up for the 21st century, Logist. Manag. Distrib. Rep., 37, 3, pp. 87-90, (1998); Hamilton S., E-commerce for the 21st century, IEEE Comput., 30, 5, pp. 44-47, (1997); Hoffman D.L., Kalsbeek W.D., Novak T.P., Internet and Web Use in the U.S, Commun. ACM, 39, 12, pp. 36-46, (1996); Hsu C., Pant S., Innovative Planning for Electronic Commerce and Enterprises: A Reference Model, (1999); Jutla D., Bodorik P., Hajnal C., Davis C., Making business sense of electronic commerce, IEEE Comput., 32, 3, pp. 67-75, (1999); La Londe B., Masters J.M., Emerging logistics strategies: Blueprints for the next century, Int. J. Phys. Disrib. Logist. Manag., 24, 7, pp. 35-47, (1994); Lewis I., Talalayevsky A., Logistics and information technology: A coordination perspective, J. Bus. Logist., 18, 1, pp. 141-157, (1997); Melbin J.E., The need for speed, Disribution, 96, 8, pp. 58-84, (1997); Reinheimer S., Bodendorf F., A framework for electronic coordination in the air cargo markete, Inform. Soc., 15, pp. 51-55, (1999); Scheerck T.R., Air cargo: Beyond the valley lies a land of milk, honey and profits, Transportation and Distribution, 39, 7, pp. 45-47, (1998); Tenenbaum J.M., Chowdhry T.S., Hughes K., Eco System: An internet commerce architecture, IEEE Comput., 30, 5, pp. 48-55, (1997); Williams L.R., Nibbs A., Irby D., Finley T., Logistics Integration: The effect of information technology, team composition, and corporate competitive positioning, J. Business Logistics, 18, 2, pp. 31-41, (1997)",{"$nulls":8},1.0834427E7,null,"ITSHF",null,"English","IEEE Trans Syst Man Cybern Pt A Syst Humans","Article","Final",null,"Scopus","2-s2.0-0034228370"]
["Pavlou P.A.; Gefen D.","Pavlou, Paul A. (6507186334); Gefen, David (6601945888)","6507186334; 6601945888","Psychological contract violation in online marketplaces: Antecedents, consequences, and moderating role",2005.0,"Information Systems Research",16.0,4.0,null,372.0,399.0,27.0,460.0,"10.1287/isre.1050.0065","https://www.scopus.com/inward/record.uri?eid=2-s2.0-29444459006&doi=10.1287%2fisre.1050.0065&partnerID=40&md5=e5e3062bcf1f4e65fb4b967134632380","Anderson Graduate School of Management, University of California, Riverside, Anderson Hall 010, Riverside, CA 91251, 900 University Avenue, United States; Management Department, LeBow College of Business, Drexel University, Philadelphia, PA 19104-2875, 101 North 33rd Street, United States","Pavlou P.A., Anderson Graduate School of Management, University of California, Riverside, Anderson Hall 010, Riverside, CA 91251, 900 University Avenue, United States; Gefen D., Management Department, LeBow College of Business, Drexel University, Philadelphia, PA 19104-2875, 101 North 33rd Street, United States","This study examines the nature and role of Psychological Contract Violation (PCV) in online marketplaces, a critical factor that has been largely overlooked by previous research. Applied to buyer-seller relationships, PCV is defined as a buyer's perception of having being treated wrongly regarding the terms of an exchange agreement with an individual seller. PCV with individual sellers is proposed as a formative first-order construct driven by the occurrence of fraud, product misrepresentation, contract default, delivery delay, and failure to follow product guarantees and payment policies. PCV with an individual seller is proposed to prompt a generalized perception of PCV with the entire community of sellers in a marketplace. PCV with the community of sellers is hypothesized to negatively affect buyer transaction behavior in a marketplace by directly impacting transaction intentions, price premiums, trust, perceived risk, and the perceived effectiveness of institutional structures. PCV is also hypothesized to act as a moderator, transforming the buyers' initial trust-based mindset to one more centered on perceived risk. Finally, PCV is hypothesized to attenuate the positive impact of trust on transaction intentions, while reinforcing the negative impact of perceived risk on transaction intentions. It is also proposed to attenuate the impact of the perceived effectiveness of institutional structures on trust, while strengthening its negative effect on perceived risk. As a means of preventing PCV, the buyers' positive experience and the sellers' favorable past performance are hypothesized to make PCV with the community of sellers less likely. A combination of primary and secondary longitudinal data from 404 buyers in eBay's and Amazon's online auctions support the proposed hypotheses, validating PCV as a central element of buyer-seller relationships in online marketplaces. Interestingly, ex post facto results show that buyers with higher perceptions of PCV with the community of sellers are less likely to experience PCV with an individual seller in the future. Implications for buyer-seller relationships in online marketplaces and the PCV literature are discussed. Also discussed is how the increasing number of buyers who experience PCV in online marketplaces extends the literature that has been largely developed based on buyers who had not experienced PCV. © 2005 INFORMS.","Institutional structures; Online auction marketplaces; Psychological Contract Violation; Risk; Trust","Risks; Sales; Societies and institutions; Buyer-seller relationships; Institutional structure; Longitudinal data; On-line marketplaces; Online auctions; Positive experiences; Psychological contract violations; Trust; Electronic commerce",{"$nulls":6},"Agarwal R., Karahanna E., Time flies when you're having fun: Cognitive absorption and beliefs about information technology usage, MIS Quart., 24, 4, pp. 665-694, (2000); Ajzen I., The theory of planned behavior, Organ. Behavior Human Decision Processes, 50, pp. 179-211, (1991); Akerlof G., The market for \"lemons\": Quality under uncertainty and the market mechanism, Quart. J. Econom., 84, pp. 488-500, (1970); Argyris C., Understanding Organizational Behavior, (1960); Armstrong J.S., Overton T., Estimating nonresponse bias in mail surveys, J. Marketing Res., 19, pp. 396-402, (1976); Ba S., Pavlou P.A., Evidence of the effect of trust building technology in electronic markets: Price premiums and buyer behavior, MIS Quart., 26, 3, pp. 243-268, (2002); Bauer R.A., Consumer behavior as risk taking, Dynamic Marketing for a Changing World, pp. 389-398, (1960); Berenstein G.L., Campbell C.E., Electronic contracting: The current state of the law and best practices, Intellectual Property Tech. Law J., 14, 9, pp. 1-11, (2002); Bergen M., Dutta S., Walker O., Agency relationships in marketing: A review of the implications and applications of agency and related theories, J. 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Pavlou; Anderson Graduate School of Management, University of California, Riverside, Anderson Hall 010, Riverside, CA 91251, 900 University Avenue, United States; email: paul.pavlou@ucr.edu",null,"INFORMS Inst.for Operations Res.and the Management Sciences",{"$nulls":5},1.0477047E7,null,null,null,"English","Inf. Syst. Res.","Article","Final",null,"Scopus","2-s2.0-29444459006"]
["Doherty N.F.; McAulay L.","Doherty, Neil F. (7006826558); McAulay, Laurie (6602166229)","7006826558; 6602166229","Towards the formulation of a comprehensive framework for the evaluation of investments in sell-side e-commerce",2002.0,"Evaluation and Program Planning",25.0,2.0,null,159.0,165.0,6.0,11.0,"10.1016/S0149-7189(02)00009-5","https://www.scopus.com/inward/record.uri?eid=2-s2.0-0036241432&doi=10.1016%2fS0149-7189%2802%2900009-5&partnerID=40&md5=b5aec2c8267243c8faecae2741133b8a","Business School, Loughborough University, Leicestershire LE11 3TU, Ashby Road, United Kingdom","Doherty N.F., Business School, Loughborough University, Leicestershire LE11 3TU, Ashby Road, United Kingdom; McAulay L., Business School, Loughborough University, Leicestershire LE11 3TU, Ashby Road, United Kingdom","In recent years, whilst considerable attention has been focussed on the Internet, and in particular its potential as a sales medium, little research has been conducted into how such investments can be objectively evaluated. Based upon a review of the literature and a series of exploratory interviews, a provisional framework for evaluating e-commerce investments is presented. It is shown that in addition to considering generic issues such as flexibility and implementability, an e-commerce evaluation framework should address specifics, such as customer management, marketing and logistics. \"The key question is not whether to deploy Internet technology-companies have little choice if they want to remain competitive- but how to deploy it\" [Porter 2001] © 2002 Elsevier Science Ltd. All rights reserved.","Information technology; Sell-side e-commerce; Systems evaluation; The Internet and qualitative research","assessment method; e-commerce; investment",{"$nulls":6},"Bacon C.J., The use of decision criteria in selecting IS/IT investments, MIS Quarterly, 16, 3, pp. 335-350, (1992); Ballantine J., Galliers R., Stray S., Information systems/technology evaluation practices: Evidence from UK organisations, Journal of Information Technology, 11, 2, pp. 129-142, (1996); On-line Retail Market in North America to Reach $65 Billion in 2001, (2001); Chaffey D., Mayer R., Johnston K., Ellis-Chadwick F.E., Internet Marketing, (2000); Doherty N.F., Ellis-Chadwick F., Hart C.A., Cyber retailing in the UK: The potential of the Internet as a retail channel, International Journal of Retail and Distribution Management, 27, 1, pp. 22-36, (1999); E-commerce: How Trading On-line Can Work for You, (2001); Farbey B., Land F., Target D., Moving IS evaluation forward: Learning themes and research issues, Journal of Strategic Information Systems, 8, 2, pp. 198-207, (1999); Fitzgerald G., Evaluating information systems projects: A multi-dimensional approach, Journal of Information Technology, 13, pp. 15-27, (1998); Fuchs S., Organisational change in the internet age, The Rational Edge, (2001); Hart C., Doherty N.F., Ellis-Chadwick F., Retailer adoption of the Internet: Implications for retail marketing, European Journal of Marketing, 34, 8, pp. 954-974, (2000); Kotler P., Armstrong G., Saunders J., Wong V., Principles of Marketing, (2001); Miles M.B., Huberman A.M., Qualitative Data Analysis, (1994); Misic M., Johnson K., Benchmarking: A tool for web-site evaluation and improvement, Internet Research - Electronic Networking Applications and Policy, 9, 5, pp. 383-392, (1999); O'Keefe R., O'Connor G., Kung H.J., Early adopters of the Web as a retail medium: Small company winners and losers, European Journal of Marketing, 32, 7-8, pp. 629-643, (1998); Porter M., Strategy and the Internet, Harvard Business Review, pp. 63-78, (2001); Pyle R., Electronic commerce and the Internet, Communications of the ACM, 39, 6, pp. 22-24, (1996); Remenyi D., Just Because You Can, Doesn't Mean You Should, (2001); Remenyi D., Sherwood-Smith M., White T., Achieving Maximum Value from IT Investments, (1998); Simeon R., Evaluating domestic and international web-site strategies, Internet Research - Electronic Networking Applications and Policy, 9, 4, pp. 297-308, (1999); Teo T.S., Tan M., Buk W.K., A contingency model of Internet adoption in Singapore, International Journal of Electronic Commerce, 2, 2, pp. 57-69, (1997); Willcocks L., Evaluating information technology investments: Research findings and reappraisal, Journal of Information Systems, 2, 3, pp. 243-268, (1992)","N.F. Doherty; The Business School, Loughborough University, Loughborough, Leicester. LE11 3TU, Ashby Road, United Kingdom; email: n.f.doherty@lboro.ac.uk",null,"Elsevier Ltd",{"$nulls":5},1497189.0,null,"EPPLD",null,"English","Eval. Program Plann.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-0036241432"]
["Daly S.P.; Cui L.X.","Daly, Shawn P. (8245036100); Cui, Lindsay X. (7201555095)","8245036100; 7201555095","E-logistics in China: Basic problems, manageable concerns and intractable solutions",2003.0,"Industrial Marketing Management",32.0,3.0,null,235.0,242.0,7.0,31.0,"10.1016/S0019-8501(02)00267-5","https://www.scopus.com/inward/record.uri?eid=2-s2.0-0037378492&doi=10.1016%2fS0019-8501%2802%2900267-5&partnerID=40&md5=b41efe727354eb47ec9148d54543734b","Graduate School of Business, Tiffin University, Tiffin, OH 44883, 155 Miami Street, United States; Qingdao University, Shandong, China","Daly S.P., Graduate School of Business, Tiffin University, Tiffin, OH 44883, 155 Miami Street, United States; Cui L.X., Qingdao University, Shandong, China","This paper examines the reality of issues surrounding e-commerce and logistics in China today. Interviews were conducted with government, business and academic leaders in a major Chinese coastal city. From these interviews, the magnitude of nine major e-commerce and logistics challenges was investigated. Based on the scope of the problems and the scale of potential solutions, the various issues are characterized as basic, manageable or intractable. Conclusions are made about the challenges to be found both today and in the future of e-commerce and logistics in China. © 2002 Elsevier Science Inc. All rights reserved.","China; E-commerce; Logistics",{"$nulls":7},"The Economist, China's economic power: Enter the dragon, pp. 23-25, (2001); Roy A., Walters P.G.P., Luk S.T.C., Introduction to the special issue on \"doing business in China, J. Bus. Res., 52, 2, pp. 93-94, (2001); Pollitt D., Filling the logistics gaps in China, Int. J. Phys. Distrib. Logist. Manag., 28, 3, pp. 173-174, (1998); Ta H.-P., Choo H.-L., Sum C.-C., Transportation concerns of foreign firms in China, Int. J. Phys. Distrib. Logist. Manag., 30, 1, pp. 35-54, (2000); Lancioni R., Smith M.F., Oliva T.A., The role of the internet in supply chain management, Ind. Mark. Manage., 29, pp. 45-56, (2000); Daskin M.S., Logistics: An overview of the state of the art and perspectives on future research, Transp. Res., 19, 5-6, pp. 383-398, (1985); Peng M.W., Lu Y., Shenkar O., Wang D.Y.L., Treasures in the China house: A review of management and organizational research in greater China, J. Bus. Res., 52, 2, pp. 95-110, (2001); Ralston D.A., Holt D.H., Terpstra R.H., Kai-cheng Y., The impact of national culture and economic ideology on managerial work values: A study of the United States, Russia, Japan, and China, J. Int. Bus. Stud., 28, 1, pp. 177-207, (1997); Harrison G.L., McKinnon J., Wu A., Chow C.W., Cultural influences on adaptation to fluid workgroups and teams, J. Int. Bus. Stud., 31, 3, pp. 489-505, (2000); Davies H., Leung T.K.P., Luk S.T.K., Wong Y.-H., The benefits of \"Guanxi, Ind. Mark. Manage., 24, pp. 207-214, (1995); Jefferson G.H., Rawski T.G., Enterprise reform in Chinese Industry, J. Econ. Perspect., 8, 2, pp. 47-70, (1994); Ralston D.A., Egri C.P., Stewart S., Terpstra R.H., Kaicheng Y., Doing business in the 21st century with the new generation of Chinese managers: A study of generational shifts in work values in China, J. Int. Bus. Stud., 30, 2, pp. 415-428, (1999); Speece M.W., Kawahara Y., Transportation in China in the 1990's, Int. J. Phys. Distrib. Logist. Manag., 25, 8, pp. 53-71, (1995); Yam R.C.M., Tang E.P.Y., Transportation systems in Hong Kong and Southern China: A manufacturing industries perspective, Int. J. Phys. Distrib. Logist. Manag., 26, 10, pp. 46-59, (1996); Chang K., Ding C.G., The influence of culture on industrial buying selection criteria in Taiwan and Mainland China, Ind. Mark. 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Manag., 26, 10, pp. 79-95, (1996); O'Callaghan R., Kaufmann P.J., Konsynski B.R., Adoption correlates and share effects of electronic data interchange systems in marketing channels, J. Mark., 56, pp. 45-56, (1992); Murphy P.R., Daley J.M., International freight forwarder perspectives on electronic data interchange and information management issues, J. Bus. Logist., 17, 1, pp. 63-84, (1996); Avlonitis G.J., Karayanni D.A., The impact of internet use on business-to-business marketing: Examples from American and European companies, Ind. Mark. Manage., 29, pp. 441-459, (2000); Closs D.J., Goldsby T.J., Clinton S.R., Information technology influences on world class logistics capability, Int. J. Phys. Distrib. Logist. Manag., 27, 1, pp. 4-17, (1997); Birou L.M., Fawcett S.E., International purchasing: Benefits, requirements, and challenges, Int. J. Purch. Mater. Manage., 29, 2, pp. 27-37, (1993); Roy A., Walters P.G.P., Luk S.T.C., Chinese puzzles and paradoxes: Conducting business research in China, J. Bus. Res., 52, 2, pp. 93-94, (2001); (2000); Handfield R.B., Withers B., A comparison of logistics management in Hungary, China, Korea, and Japan, J. Bus. Logist., 14, 1, pp. 81-109, (1993); Luk S.T.K., Structural changes in China's distribution system, Int. J. Phys. Distrib. Logist. Manag., 28, 1, pp. 44-67, (1998); Shenkar O., Li J., Knowledge search part in international cooperative ventures, Organ. Sci., 10, pp. 134-143, (1999); Bloomen D.R.V., Petrov I.P., Logistics in Bulgaria: Concepts for new market expansion, Int. J. Phys. Distrib. Logist. Manag., 24, 2, pp. 30-36, (1994); Clarke M.P., Virtual logistics: An introduction and overview of the concepts, Int. J. Phys. Distrib. Logist. Manag., 28, 7, pp. 486-507, (1998); Bowersox D.J., Closs D.J., Stank T.P., Ten mega-trends that will revolutionize supply chain logistics, J. Bus. Logist., 21, 2, pp. 1-16, (2000)","S.P. Daly; Graduate School of Business, Tiffin University, Tiffin, OH 44883, 155 Miami Street, United States; email: sdaly@tiffin.edu",{"$nulls":7},198501.0,null,"IMMAD",null,"English","Ind. Mark. Manage.","Article","Final",null,"Scopus","2-s2.0-0037378492"]
["Razi M.A.; Tarn J.M.; Siddiqui F.A.","Razi, Muhammad A. (6602730537); Tarn, J. Michael (7006709448); Siddiqui, Faisal A. (36819750200)","6602730537; 7006709448; 36819750200","Exploring the failure and success of DotComs",2004.0,"Information Management and Computer Security",12.0,3.0,null,228.0,244.0,16.0,26.0,"10.1108/09685220410542598","https://www.scopus.com/inward/record.uri?eid=2-s2.0-9244261091&doi=10.1108%2f09685220410542598&partnerID=40&md5=440c29c7e0bda1b8d68e4d4a1055d1f1","Dept. of Bus. Info. Systems, Haworth College of Business, Western Michigan University, Kalamazoo, MI, United States","Razi M.A., Dept. of Bus. Info. Systems, Haworth College of Business, Western Michigan University, Kalamazoo, MI, United States; Tarn J.M., Dept. of Bus. Info. Systems, Haworth College of Business, Western Michigan University, Kalamazoo, MI, United States; Siddiqui F.A., Dept. of Bus. Info. Systems, Haworth College of Business, Western Michigan University, Kalamazoo, MI, United States","The Internet added another dimension to traditional commerce when online business became available. Because of the mushroom growth of online businesses in the late 1990s. DotCom bubbles began to burst after the initial euphoria of e-commerce. Since mid-2000, the mass failure of DotComs has had a significant impact on the e-ecosystem. However, there were strong survivors and successful DotComs as well. Employing a comparative analysis, this study investigates the causes for DotCom failures and successes. The examination found that successful DotComs overcame the technical, operational and behavioral shortcomings of their failed counterparts and led the way in logistics, customer support, Web design, promotion and Internet security. © Emerald Group Publishing Limited.","Business failures; Business performance; Electronic commerce; Internet","Decision making; Electronic commerce; Information technology; Online systems; Security of data; Business failures; Business performance; Internet",{"$nulls":6},"Addison T., E-commerce project development risks: Evidence from a Delphi survey, International Journal of Information Management, 23, 1, pp. 25-40, (2003); Agarwal R., Gort M., The evolution of markets and entry, exit and survival of firms, The Review of Economics and Statistics, 78, 3, pp. 489-498, (1996); Atif Y., Building trust in e-commerce, IEEE Internet Computing, pp. 18-24, (2002); Bazac D., Why Dotcoms fail, (2002); Bertagnoli L., It takes a community to build e-success, Marketing News, 35, 1, (2001); Clark B., Welcome to my parlor, Marketing Management, 5, 4, pp. 10-25, (1997); Coltman T., Devinney T., Latukefu A., Midgley D., Keeping e-business in perspective, Communications of the ACM, 45, 8, pp. 69-73, (2002); Crell B., Web site design: What do I need to know?, Pennsylvania CPA Journal, 71, 1, pp. 15-20, (2000); Crowley D., Sports dotcorn backed by McDonagh closes in US, (2001); Fineman M., The rise and fall of Africa.com, Business2, (2000); Goldsborough R., Words for the wise: Tips for Web site design, Canadian Plastics, 57, 11, (1999); Hensler D., Rutherford R., Springer T., The survival of initial public offerings in the aftermarket, The Journal of Financial Research, 20, 1, pp. 93-110, (1997); Honjo Y., Business failure of new firms: An empirical analysis using a multiplicative hazards model, International Journal of Industrial Organization, 18, 4, pp. 557-574, (2000); Hoover S., McLean A., Mishina M., O'Brien K., An e-commerce success, American Printer, 227, 3, pp. 30-33, (2001); Johnson E., Bellman S., Lohse G., What makes a Web site sticky? Cognitive lock-in and the power law of practice, Columbia Business School, (2000); Kelley C., Delhagen K., Yuen E., Online credit card security confidence erodes, (2003); Kemp T., DotCom postmortem, Internetweek, (2000); Laudon K., Laudon J., Essentials of Management Information Systems: Organization and Technology in the Networked Enterprise, (2001); Laudon K., Traver C., E-commerce: Business Technology and Society, (2002); Lee C., An analytical framework for evaluating e-commerce business models and strategies, Internet Research, 11, 4, pp. 349-359, (2001); Lemos R., ΦTD.com hole leaks personal information, CNET News.com, (2003); Lumpkin G., Droege S., Dess G., E-commerce strategies: Achieving sustainable competitive advantage and avoiding pitfalls, Organizational Dynamics, 30, 4, pp. 325-340, (2002); McQuivey J., Delhagen K., Yuen E., RIP: The online consumer, 1998 to 2003, (2003); Madsen H., Survival rules, Management Today, (1999); Morgan L., Be afraid, be very afraid, Internetweek, (2001); Pappas L., Making money '90s style, National Real Estate Investor, 41, 9, (1999); Robbins S., Anatomy of a business model: What is one of those things, anyway?, (2001); Scarborough C., Spatarella J., Getting behind the business of electronic commerce, TMA Journal, 18, 4, pp. 42-44, (1998); (2002); Ticehurst J., Microsoft reverses Windows ME strategy, Gartner Spring Symposium, (2000); Swartz J., Not all dot-coms bomb, USA Today, (2001); Wen H., Tarn J., The impact of the next generation Internet protocol on e-commerce security, Information Strategy: The Executive Journal, pp. 22-28, (2001); Wilson S., Abel I., So you want to get involved in E-commerce?, Industrial Marketing Management, 31, 2, pp. 85-94, (2002); Wolff C., Permission is key to e-commerce success, Lodging Hospitality, 65, 8, pp. 25-26, (2000)",{"$nulls":8},9685227.0,null,"IMCSE",null,"English","Inf Manage Comput Secur","Article","Final",null,"Scopus","2-s2.0-9244261091"]
["Nitse P.S.; Parker K.R.; Krumwiede D.; Ottaway T.","Nitse, Philip S. (8421860700); Parker, Kevin R. (15078511000); Krumwiede, Dennis (6603382715); Ottaway, Thomas (6602600739)","8421860700; 15078511000; 6603382715; 6602600739","The impact of color in the e-commerce marketing of fashions: an exploratory study",2004.0,"European Journal of Marketing",38.0,7.0,null,898.0,915.0,17.0,45.0,"10.1108/03090560410539311","https://www.scopus.com/inward/record.uri?eid=2-s2.0-31744449195&doi=10.1108%2f03090560410539311&partnerID=40&md5=7383b77ac0653d1c128b86b52bb2d724","College of Business, Idaho State University, Pocatello, ID, United States","Nitse P.S., College of Business, Idaho State University, Pocatello, ID, United States; Parker K.R., College of Business, Idaho State University, Pocatello, ID, United States; Krumwiede D., College of Business, Idaho State University, Pocatello, ID, United States; Ottaway T., College of Business, Idaho State University, Pocatello, ID, United States","As the number of Internet purchases of fashion items increases, the problem of inaccurate color representation on the Web becomes more significant. Color inaccuracy has many negative consequences for marketers, including loss of sales, increased returns and complaints, and customer defections. This research reports the findings of a survey conducted as part of an initial investigation into consumer opinions about fashion merchandise purchasing over the Internet. Results indicate that companies are losing customers and sales as a result of having colors on e-commerce sites that do not accurately represent the actual colors of the products being sold. Increased dissatisfaction on the part of consumers leads to greater costs in both customer service and reverse logistics. Further, a majority of the respondents indicated that they would not make additional purchases from an e-tailer if they received items in colors different than they expected. The paper concludes with suggestions for future research. © 2004, Emerald Group Publishing Limited.","Colour; Consumer behaviour; Fashion industry; Internet; Shopping; Trust",{"$nulls":7},"Alba J., Hutchinson W., Dimensions of consumer expertise, Journal of Consumer Research, 13, pp. 411-454, (1987); Ariely D., Carmon Z., Gestalt characteristics of experiences: the defining features of summarized events, Journal of Behavioral Decision Making, 13, 2, pp. 191-201, (2000); Berry L.L., Zeithaml V.A., Parasuraman A., Five imperatives for improving service quality, Sloan Management Review, Summer, pp. 29-38, (1990); Boulding W., Kalra A., Staelin R., Zeithaml V.A., A dynamic process model of service quality: from expectations to behavioral intentions, Journal of Marketing Research, 30, February, pp. 7-27, (1993); Bunn J., Centralizing reverse logistics: how to understand if it will work for you, Consumer Markets, August, pp. 11-12, (1999); Burke R.R., Technology and the customer interface: what consumers want in the physical and virtual store, Journal of the Academy of Marketing Science, 30, 4, pp. 411-432, (2002); Study finds lack of color consistency hampers electronic commerce; cyber dialogue reports consumer awareness of monitor color variance, Business Wire, (1999); Dholakia V., Bagozzi R.P., Consumer behavior in digital environments, Digital Marketing, pp. 163-200, (2001); Elliot S., Fowell S., Expectations versus reality: a snapshot of consumer experiences with Internet retailing, International Journal of Information Management, 20, pp. 323-336, (2000); Gardial S.F., Clemons S., Woodruff R.B., Schumann D.W., Burns M.J., Comparing consumers’ recall of prepurchase and postpurchase product evaluation experiences, Journal of Consumer Research, 20, March, pp. 548-560, (1994); Griffith D.A., Krampf R.F., Palmer J.W., The role of interface in electronic commerce: consumer involvement with print versus online catalogs, International Journal of Electronic Commerce, 5, 4, pp. 135-153, (2001); Imation tames unruly Web color with verifi technology, Imation, (2001); An e-retailing odyssey, (2001); Kotler P., Marketing Management, (2000); Krantz M., Click till you drop, Time Magazine, 152, 3, pp. 34-37, (1998); Lebo H., The UCLA Internet report: surveying the digital future: year three, (2003); Oliver R.L., Satisfaction: A Behavioral Perspective on the Consumer, (1997); Business-to-consumer e-commerce statistics, (2001); Parasuraman A., Grewal D., The impact of technology on the quality-value-loyalty chain: a research agenda, Journal of the Academy of Marketing Science, 28, 1, pp. 168-174, (2000); Parasuraman A., Berry L.L., Zeithaml V.A., SERVQUAL: a multiple-item scale for measuring consumer perceptions of service quality, Journal of Retailing, 64, 1, pp. 12-40, (1988); Parasuraman A., Berry L.L., Zeithaml V.A., Understanding customer expectations of service, Sloan Management Review, 39, Spring, pp. 39-48, (1991); Parasuraman A., Berry L.L., Zeithaml V.A., Refinement and reassessment of the SERVQUAL scale, Journal of Retailing, 67, 4, pp. 420-450, (1991); Puente M., Online experience is now a much better fit, USA Today, December 4, (2002); Quick R., Return to sender, Wall Street Journal, July 17, (2000); Reibstein D.J., What attracts customers to online stores, and what keeps them coming back?, Journal of the Academy of Marketing Science, 30, 4, pp. 465-473, (2002); Reichheld F.F., The Loyalty Effect, (1996); Reichheld F.F., Schefter P., E-loyalty: your secret weapon on the Web, Harvard Business Review, July/August, pp. 105-113, (2000); Richins M., Negative word-of-mouth by dissatisfied consumers: a pilot study, Journal of Marketing, 47, Winter, pp. 68-78, (1983); Scaglione F., Two-way communication: tapping into gripes and profits, Management Review, 77, pp. 51-53, (1988); Sharrard J., Expand globally, comply locally, Forrester Research, (2001); Singh J., Consumer complaint intentions and behavior: definitional and taxonomical issues, Journal of Marketing, 52, January, pp. 93-107, (1988); Stone M.D., Color matching: color (mis)matching, and why colors are matching better than ever, ExtremeTech, (2001); Technical Assistance Research Programs (TARP), (1986); Voss G., Parasuraman A., Grewal D., The roles of price, performance, and expectations in determining satisfaction in service exchanges, Journal of Marketing, 62, October, pp. 46-61, (1998); Zeithaml V.A., Berry L.L., Parasuraman A., The behavioral consequences of service quality, Journal of Marketing, 60, April, pp. 31-46, (1996)",null,null,"Emerald Group Holdings Ltd.",{"$nulls":5},3090566.0,null,null,null,"English","Eur. J. Mark.","Article","Final",null,"Scopus","2-s2.0-31744449195"]
["Gooneratne Y.","Gooneratne, Yuki (6505945808)",6.505945808E9,"Digitizing isolated communities: The Japanese experience in reviving dynamism and creating opportunities",2002.0,"Regional Development Dialogue",23.0,2.0,null,121.0,135.0,14.0,2.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-0142135848&partnerID=40&md5=53a163d36903279ade580416e680822a","UNCRD, Nakamura-ku, Nagoya 450-0001, Nagono 1-47-1, Japan","Gooneratne Y., UNCRD, Nakamura-ku, Nagoya 450-0001, Nagono 1-47-1, Japan","The development and utilization of information and communication technologies (ICTs) in Japan have played a prominent role in facilitating accelerated growth of industries, e-commerce, new employment opportunities, better services, and a range of possibilities through rapid information diffusion and exchange. In the midst of the information technology (IT) revolution with increasing global emphasis on its vast possibilities, the Government of Japan announced its e-Japan IT strategy in 2001 with the intention of becoming the most advanced IT nation in the world by 2006. Priority areas include promoting higher speed Internet infrastructure and lower network costs, enhancing IT education, producing high quality network content, promoting e-government and e-local government, and engaging more actively in IT-related international activities. The Information and Communications in Japan White Paper 2002 indicates that the information and communication industry contributed 30 per cent, the largest contribution, to total economic growth in 2000. The article aims to focus on the use of ICTs in ensuring human security through a study of the changes in the daily lives of people in a remote mountain community. Of particular concern is how effectively ICTs are used in such isolated areas to facilitate community support and development. Emphasis is directed towards the economic and social development of communities in Japan, which are increasingly confronted with depopulation, dwindling economic activities, uncertainty, and social marginalization. To promote human security, people need to be empowered against socioeconomic threats. Economic security is ensured where there is a rise in income levels, higher economic development, better employment prospects, reduced uncertainty, and an improved quality of life. Social vulnerability is reduced where there are fewer threats in terms of access to social services, where the quality of social services is not compromised, and where there is less social isolation and exclusion from socioeconomic activities. The article looks at the role of ICTs and their effectiveness as tools to ensure human security at the local level by increasing access to information, resources, and education and health services, while promoting interaction and participation within and among local communities. A successful example of the Japanese rural experience as exemplified by a small agricultural and tourism-related village will be included to illustrate a participatory approach to community development using ICTs. The essential factors that have led to its successful outcome will be identified through an examination of community needs, how ICTs were applied to achieve community objectives, and the underlying policy characteristics such as funding and public sector service delivery. Issues concerning sustainability will also be addressed.",null,"communication; e-commerce; information technology; Internet; rural area",{"$nulls":6},"E-Japan Summary, (2001); Information and Communications in Japan White Paper 2002, (2002); What's new in Japanese local government?, Newsletter, 21, (2000); The Information Revolution in Development Assistance Executive Summary, (2001); Shearman C., Local Connections: Making the Network for Neighbourhood Renewal, (2001); Telemedicine Development and Diffusion in Japan, (2000); Masatsugu T., Et al., An estimation of economic effects of tele-home-care: Hospital cost-savings of the elderly, Medinfo 2001, (2001); (2002); Kamiya H., Et al., Survey on computer usage in Yamada Village, Toyama prefecture, Geography Studies Newsletter, 92, pp. 42-49, (2001); Youichi I., Introduction of the Internet to Yamada-mura: Efforts and Issues, (2001); Tetsuo O., About the Informational Technology in Yamada Village, (1996); Mutsuko M., I.T. takes a village, Asiaweek, (2001); The Significance of Regional Information Policy of Yamada-mura, (2002); Versweyveld L., Use of telehealth and telehomecare devices bound to get big in Japan, Virtual Medical Worlds Monthly, (2002); Masatsugu T., Masaaki T., Shoichi M., an Ordered Probit Analysis of Factors Promoting a Regional Information Policy Based on Multimedia, (2000); Sheppard K., The Remote Community Service Telecentres of Newfoundland and Labrador, Canada, Perspectives on Distance Education. Telecentres: Case Studies and Key Issues, pp. 41-51",{"$nulls":8},2506505.0,null,null,null,"English","Reg. Dev. Dialogue","Article","Final",null,"Scopus","2-s2.0-0142135848"]
["Tate M.; Coker B.; Hope B.","Tate, Mary (7102419445); Coker, Brent (41561002300); Hope, Beverley (7006670101)","7102419445; 41561002300; 7006670101","Moving to multi-channel e-commerce: Lessons learned from a case study of an apparel and home-ware catalogue company",2005.0,"Journal of Internet Commerce",4.0,2.0,null,3.0,32.0,29.0,4.0,"10.1300/J179v04n02_02","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85010589235&doi=10.1300%2fJ179v04n02_02&partnerID=40&md5=43893730d445850b00fbdd0c39b99c7e","Victoria University of Wellington, New Zealand; Victoria University, New Zealand","Tate M., Victoria University of Wellington, New Zealand; Coker B., Victoria University, New Zealand; Hope B., Victoria University, New Zealand","After the “dot-com bust” there is considerable evidence that multi-channel retailers are more successful than purely on-line retailers. We talked to the management team of one of the most successful multi-channel apparel and home-ware retailers in Australasia about the business and technology factors that enabled their growth. We found seven key business strategies enabled growth and expansion into new channels, including e-commerce: integrated operational functions, channel synergy, logistics management, presenting a consistent brand, effective customer management, learning from customers, and informed imitation. These strategies were supported by integrated information technology applications. At the time of our study, the recently added Internet channel was not fully integrated with the other core systems. This was being adequately managed through strong internal processes but had the potential to constrain future growth in this channel. We examine the factors that led to the firm’s success and some of the issues and constraints they are experiencing. We then extract from their experiences the lessons that can be learned by other organisations. © 2005 by The Haworth Press, Inc. All rights reserved.","Apparel; E-commerce strategy; E-tailing; Multi-channel",{"$nulls":7},"Bitner M.J., Brown S., Meuter M.L., Technology infusion in service encounters, Academy of Marketing Science Journal, Winter, (2000); Boles De Boer D., Evans L., Howell B., The State of e-New Zealand, New Zealand Institute for the Study of Competition and Regulation, (2000); Day G.S., The capabilities of market driven organisations, Journal of Marketing Management, 58, 4, (1994); Day G.S., Hubbard K.J., Customer relationships go digital, Business Strategy Review, 14, 1, (2002); Earl M.J., Experiences in strategic information systems planning, MIS Quarterly, 17, 1, (1993); Earl M.J., Finance and Economics: First will be last; Economics focus, The Economist, 364, 8292, (2002); Capturing Cross Channel Dollars, (2002); Retail February 2003 Data Overview: A Gender Analysis of Online Shopping Behaviors, (2003); Garland R., Ezibuy Market Research Report; Ghoshal S., Gratton L., Integrating the enterprise, MIT Sloan Management Review, 44, 1, (2002); Goersch D., Multi-channel Integration and its implications for retail Websites, European Conference on Information Systems, (2002); Greenspan R., Apparel Sales Apparent Online, (2003); Gulati R., Garino J., Get the right mix of bricks and clicks, Harvard Business Review, 78, 3, (2002); Lee H.L., Whang S., Winning the last mile of e-commerce, MIT Sloan Management Review, 42, 4, pp. 54-62, (2001); Lee J.K., EC Reality in Broadband Society, (Keynote Address), PACIS, (2003); Lieberman M.B., Montgomery D.B., First-mover (Dis)advantages: Retrospective and link with the resource based view, Strategic Management Journal, 19, 12, pp. 111-1125, (1998); Neelamiegham R., Jain D., Consumer choice process for experience goods: An econometric model and analysis, Journal of Marketing Research, 36, 3, (1999); SMEs in New Zealand: Structure and dynamics, New Zealand Ministry of Economic Development; Broadband Access in OECD Countries per 100 Inhabitants, (2003); Pyke D.F., Johnson M.E., Desmond P., E-fulfillment: Its harder than it looks, Supply Chain Management Review, January/February, pp. 26-32, (2001); Schneider G., Perry J., Electronic Commerce. Thomson Learning, (2001); Schoenbachler D.D., Gordon G.L., Multi-channel shopping: Understanding what drives channel choice, Journal of Consumer Marketing, 19, 1, pp. 42-53, (2002); The Multi-Channel Retail Report 2.0, (2001); A Changing New Zealand, (2002); The Digital Divide 2004, (2004); Steinfield C., Bouwman H., Adelaar T., The dynamic of click-and-mortar electronic commerce: Opportunities and management strategies, International Journal of Electronic Commerce, 7, 1, (2002); Tate M., Coker B., Hope B., Insights into Selling Apparel Remotely: A Case Study of A Successful Multi Channel Retailer; Turban E., King D., Introduction to E-Commerce, (2003); The UCLA Internet Report, (2003); Ward M.R., Will online shopping compete more with traditional retailing or catalog shopping?, Netnomics, 3, 2, pp. 103-117, (2001); Westerman G., Mixing bricks with clicks: Organisation design for business-to-consumer electronic commerce in incumbent retailers, International Conference on Information Systems, (2002); Willcocks L.P., Plant R., Pathways to e-business leadership: Getting from bricks to clicks, MIT Sloan Management Review, 42, pp. 50-59, (2001); Winer R.S., A framework for customer relationship management, California Management Review, 43, 4, pp. 89-104, (2001); Zeng M., Reinartz W., Beyond online search: The road to profitability, California Management Review, 43, 4, (2003)",{"$nulls":8},1.5332861E7,null,null,null,"English","J. Internet Commer.","Article","Final",null,"Scopus","2-s2.0-85010589235"]
["Li W.-S.; Hsiung W.-P.; Candan K.S.","Li, Wen-Syan (36064148600); Hsiung, Wang-Pin (6602318809); Candan, K. Selcuk (7003683729)","36064148600; 6602318809; 7003683729","Multitiered cache management and acceleration for database-driven websites",2004.0,"Concurrent Engineering Research and Applications",12.0,3.0,null,221.0,235.0,14.0,1.0,"10.1177/1063293X04046189","https://www.scopus.com/inward/record.uri?eid=2-s2.0-4444267701&doi=10.1177%2f1063293X04046189&partnerID=40&md5=1e429c4e0848044b4ba79de58be9e87d","NEC Laboratories America, Inc., Cupertino, CA 95014, 10080 North Wolfe Road, United States","Li W.-S., NEC Laboratories America, Inc., Cupertino, CA 95014, 10080 North Wolfe Road, United States; Hsiung W.-P., NEC Laboratories America, Inc., Cupertino, CA 95014, 10080 North Wolfe Road, United States; Candan K.S., NEC Laboratories America, Inc., Cupertino, CA 95014, 10080 North Wolfe Road, United States","Response time is a key differentiation point among electronic commerce (e-commerce) applications. For many e-commerce applications, web pages are created dynamically based on the current state of a business stored in database systems. To improve the response time, many e-commerce websites deploy caching solutions for acceleration of content delivery. There are multiple tiers in the content delivery infrastructure where cache servers can be deployed, including (1) data caching (in data centers), (2) content page caching (in edge or front end caches), and (3) database query result set caching (between application servers and DBMS). The architecture of database-driven e-commerce websites is more complex than that of typical websites. It requires the integration of web servers, application servers, and back end database systems as well as dynamic content caching solutions. In this paper, the issues associated with the management of content page caching and database query result set caching tiers are studied. It is observed that caching management for these two tiers have their unique characteristics. It is because cached object types and information available for the caching management in the two tiers are different. Solutions are proposed for effective caching management for each tier and extensive evaluations are conducted. The experimental results show the usefulness of the technology in improving overall system performance. © 2004 Sage Publications.","Application server; Cache replacement; Dynamic content caching; Multitiered caching; Web acceleration","Cache memory; Client server computer systems; Distributed database systems; Electronic commerce; Query languages; Response time (computer systems); Application server; Cache replacement; Dynamic content caching; Multitiered caching; Web acceleration; Websites",{"$nulls":6},"Heddaya A., Mirdad S., WebWave: Globally load balanced fully distributed caching of hot published documents, Proceedings of the 1997 IEEE International Conference on Distributed Computing and Sytems, (1997); Heddaya A., Mirdad S., Yates D., Diffusion-based caching: Webwave, Proceedings of the 1997 NLANR Web Caching Workshop, (1997); Carter R.L., Crovella M.E., On the network impact of dynamic server selection, Computer Networks, 31, 23-24, pp. 2529-2558, (1999); Li W.-S., Hsiung W.-P., Kalashnikov D.V., Sion R., Po O., Agrawal D., Candan K.S., Issues and evaluations of caching solutions for web application acceleration, Proceedings of the 28th Very Large Data Bases Conference, (2002); Oracle9i Data Cache; Luo Q., Krishnamurthy S., Mohan C., Pirahesh H., Woo H., Lindsay B.G., Naughton J.F., Middle-tier database caching for e-business, Proceedings of 2002 ACM SIGMOD Conference, (2002); Oracle9i Web Cache; Candan K.S., Li W.-S., Luo Q., Hsiung W.-P., Agrawal D., Enabling dynamic content caching for database-driven web sites, Proceedings of the 2001 ACM SIGMOD Conference, (2001); Li W.-S., Candan K.S., Hsiung W.-P., Po O., Agrawal D., Luo Q., Huang W.-K., Akca Y., Yilmaz C., Cache portal: Technology for accelerating databasedriven E-commerce web sites, Proceedings of the 2001 VLDB Conference, (2001); Candan K.S., Agrawal D., Li W.-S., Po O., Hsiung W.-P., View invalidation for dynamic content caching in multitiered architectures, Proceedings of the 28th Very Large Data Bases Conference, (2002); Deolasee P., Katkar A., Panchbudhe A., Ramamritham K., Shenoy P., Adaptive push-pull: Dissemination of dynamic web data, The Proceedings of the 10th WWW Confernece, (2001); Ninan A., Kulkarni P., Shenoy P., Ramamritham K., Tewari R., Cooperative leases: Scalable consistency maintenance in content distribution networks, Proceedings of the 2002 World-Wide Web Confernece, (2002); Datta A., Dutta K., Thomas H.M., VanderMeer D., Suresha E., Ramamritham K., Proxy-based acceleration of dynamically generated content on the world wide web: An approach and implementation, Proceedings of 2002 ACM SIGMOD Conference, (2002); Datta A., Dutta K., Ramamritham K., Thomas H., VanderMeer D., Dynamic content acceleration: A caching solution to enable scalable dynamic web page generation, Proceedings of the 2001 ACM SIGMOD Conference, (2001); Mohan C., Application servers: Born-again TP monitors for the web? (panel abstract), Proceedings of the 2001 ACM SIGMOD Conference, (2001); Mohan C., Caching technologies for web applications, Proceedings of the 2001 VLDB Conference, (2001); Cherniack M., Franklin M.J., Zdonik S.B., Data management for pervasive computing, Proceedings of the 2001 VLDB Conference, (2001); Challenger J., Dantzig P., Iyengar A., A scalable and highly available system for serving dynamic data at frequently accessed web sites, Proceedings of ACM/IEEE Supercomputing'98, (1998); Challenger J., Iyengar A., Dantzig P., Scalable system for consistently caching dynamic web data, Proceedings of the IEEE INFOCOM'99, (1999); Levy E., Iyengar A., Song J., Dias D., Design and performance of a web server accelerator, Proceedings of the IEEE INFOCOM'99, (1999); Li D., Cao P. Dahlin M., WCIP: Web Cache Invalidation Protocol, 2000, (2000); Yin J., Alvisi L., Dahlin M., Iyenger A., Engineering server-driven consistency for large scale dynamic web services, The Proceedings of the 10th WWW Conference, (2001); Abrams M., Standbridge C.R., Abdulla G., Williams S., Fox E.A., Caching proxies: Limitations and potentials, The Proceedings of the 4th WWW Conference, (1995); Williams S., Abrams M., Standbridge C.R., Abdulla G., Fox E.A., Removal policies in network caches for world-wide web documents, Proceedings of the 1996 ACM SIGCOMM Conference, (1996); Shim J., Scheuermann P., Vingralek R., Proxy cache design: Algorithms, implementation and performance, IEEE Transactions on Knowledge and Data Engineering, 11, 4, pp. 549-562, (1999); Cao P., Irani S., Cost-aware WWW proxy caching algorithms, Proceedings of the Symposium on Internet Technologies and Systems, (1997); Barford P., Bestavros A., Bradley A., Crovella M., Changes in web client access patterns: Characteristics and caching implications, World Wide Web, 2, 1-2, (1999); Douglis F., Haro A., Rabinovich M., HPP: HTML macro-preprocessing to support dynamic document caching, Proceedings of USENIX Symposium on Internet Technologies and Systems, (1997); Smith B., Acharya A., Yang T., Zhu H., Exploiting result equivalence in caching dynamic web content, Proceedings of USENIX Symposimn on Internet Technologies and Systems, (1999); Korupolu M.R., Dahlin M., Coordinated placement and replacement for large-scale distributed caches, Proceedings of the 1999 IEEE Workshop on Internet Applications, (1999); Tewari R., Dahlin M., Vin H.M., Kay J.S., Design considerations for distributed caching on the internet, Proceedings of the 19th International Conference on Distributed Computing Systems, (1999); Rodriguez P., Sibal S., Spread: Scaleable platform for reliable and efficient automated distribution, Proceedings of the 9th World-Wide Web Conference, pp. 33-49, (2000); Cao P., Liu C., Maintaining strong cache consistency in the world wide web, IEEE Transactions on Computers, 47, 4, (1998); Gwertzman J., Seltzer M., World-wide web cache consistency, Proceedings of 1996 USENIX Technical Conference, pp. 141-151, (1996); Yu H., Breslau L., Shenker S., A scalable web cache consistency architecture, Proceedings of the ACM SIGCOMM'99 Conference, (1999)","W.-S. Li; IBM Almaden Research Center, Newyork, United States; email: wen@almaden.ibm.com",{"$nulls":7},"1063293X",null,"CRAPE",null,"English","Concurrent Eng Res Appl","Article","Final",null,"Scopus","2-s2.0-4444267701"]
["Kapuscinski R.; Zhang R.Q.; Carbonneau P.; Moore R.; Reeves B.","Kapuscinski, Roman (6602219108); Zhang, Rachel Q. (7404864614); Carbonneau, Paul (6507408603); Moore, Robert (55484253100); Reeves, Bill (7102248872)","6602219108; 7404864614; 6507408603; 55484253100; 7102248872","Inventory decisions in Dell's supply chain",2004.0,"Interfaces",34.0,3.0,null,191.0,"205+242",null,92.0,"10.1287/inte.1030.0068","https://www.scopus.com/inward/record.uri?eid=2-s2.0-3042853813&doi=10.1287%2finte.1030.0068&partnerID=40&md5=076412941f1a19cc31b34a652301b900","University of Michigan, Business School, Ann Arbor, MI 48109, United States; Johnson Grad. School of Management, Cornell University, Ithaca, NY 14853, United States; McKinsey and Company, Stamford, CT 06901, 3 Landmark Square, United States; Dell Inc., Mail Stop 6363, Austin, TX 78682, United States","Kapuscinski R., University of Michigan, Business School, Ann Arbor, MI 48109, United States; Zhang R.Q., Johnson Grad. School of Management, Cornell University, Ithaca, NY 14853, United States; Carbonneau P., McKinsey and Company, Stamford, CT 06901, 3 Landmark Square, United States; Moore R., Dell Inc., Mail Stop 6363, Austin, TX 78682, United States; Reeves B., Dell Inc., Mail Stop 6363, Austin, TX 78682, United States","The Tauber Manufacturing Institute (TMI) is a partnership between the engineering and business schools at the University of Michigan. In the summer of 1999, a TMI team spent 14 weeks at Dell Inc. in Austin, Texas, and developed an inventory model to identify inventory drivers and quantify target levels for inventory in the final stage of Dell's supply chain, the revolvers or supplier logistics centers (SLC). With the information and analysis provided by this model, Dell's regional materials organizations could tactically manage revolver inventory while Dell's worldwide commodity management could partner with suppliers in improvement projects to identify inventory drivers and to reduce inventory. Dell also initiated a pilot program for procurement of XDX (a disguised name for one of the major components of personal computers (PCs)) in the United States to institutionalize the model and promote partnership with suppliers. Based on the model predictions, Dell launched e-commerce and manufacturing initiatives with its suppliers to lower supply-chain-inventory costs by reducing revolver inventory by 40 percent. This reduction would raise the corresponding inventory turns by 67 percent. Net Present Value (NPV) calculations for XDX alone suggest $43 million in potential savings. To ensure project longevity, Dell formed the supply-chain-optimization team and charged it with incorporating the model into a strategic redesign of Dell's business practices and supervising improvement projects the model identified.","Industries: computer, electronic; Inventory, production: applications",{"$nulls":7},"Bass F.M., A new product growth for model consumer durables, Management Sci., 15, 5, pp. 215-227, (1969); Dell M., Magretta J., The power of virtual integration: An interview with Dell Computer's Michael Dell, Harvard Bus. Rev., 76, 2, pp. 72-84, (1998); Kurawarwala A.A., Matsuo H., Forecasting and inventory management of short life-cycle products, Oper. Res., 44, 1, pp. 131-150, (1996); Nahmias S., Production and Operations Analysis, 3rd Ed., (1997)","R. Kapuscinski; University of Michigan, Business School, Ann Arbor, MI 48109, United States; email: roman.kapuscinski@umich.edu",null,"INFORMS Inst.for Operations Res.and the Management Sciences",{"$nulls":5},922102.0,null,null,null,"English","Interfaces","Article","Final",null,"Scopus","2-s2.0-3042853813"]
["Smith A.D.","Smith, Alan D. (7406757527)",7.406757527E9,"Potential for growth and security in internet file-sharing: The VPN concept of gnutella",2004.0,"Journal of Internet Commerce",3.0,2.0,null,1.0,19.0,18.0,4.0,"10.1300/J179v03n02_01","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85010575506&doi=10.1300%2fJ179v03n02_01&partnerID=40&md5=fd4bb3747d6166436c946ef1767151a3","Robert Morris University, Department of Management and Marketing, Pittsburgh, PA, 15219-3099, United States","Smith A.D., Robert Morris University, Department of Management and Marketing, Pittsburgh, PA, 15219-3099, United States","The integration and use of the Internet and database management systems serve as a foundation for management of data flows for IT strategic purposes, such as using bar codes in distribution warehouses' informational and material flows. Although these trends are fairly common to B2B and C2B transactions, little research has been done on the concepts of Internet file sharing initiated on the consumers' side. Literature and conceptual research for this position paper were conducted to determine the potential for growth and security in Internet file sharing, namely the VPN concept of Gnutella. Internet file sharing is rapidly becoming a high priority issue in developing competitive advantage in customer service within an e-commerce environment. Management is finding the topic to be timely and interesting, especially with the recent press about music downloads and copyright infringement. The Internet coupled with near transparent automatic identification and data capture/collection systems, to ensure accuracy of data input, has been the key enabler of these worldwide product design/delivery technologies. Application of Rogers' (1995) Diffusions of Innovations model, a conceptual model concerning the diffusion of innovation and technological acceptance, may lead to an important step in describing and capturing the essential elements of potential end-users' marketing acceptance. Leveraging the VPN concept of Gnutella through examination of the technology’s strengths and weaknesses (although it is unreasonable to forecast the rate of adoption of peer-to-peer (P2P) Internet sharing characteristics) may generate useful insights to its development. © 2004 by The Haworth Press, Inc. All rights reserved.","Diffusion theory; Gnutella; Internet; Peer-to-peer (p2p) file sharing; Vpn",{"$nulls":7},"Allen S., Go to Jail for Downloading, (2002); Borland J., December), Peer-To-Peer: As the Revolution Recedes, (2001); Carney D., Senate committee holds hearing on Napster and Gnutella, Tech Law Journal, (2002); Gnucleus.Com, (2001); Hamel G., Leading the Revolution, pp. 70-94, (2000); Harris R., Gnu tool for music pirates, Abcnews.Com, (2002); Harrison A., Music City creates links to Gnutella network, Network World Peer-To-Peer Newsletters, (2002); Healey J., Studios spur measures to thwart piracy, Latimes.Com, (2002); Hebrank M., Gnutella News: Gnutella/Napster Comparison, (2001); Hebrank M., Internet security for the home, Symantic.Com, (2002); Kemler A.M., Bar codes: Built for speed, Business Forms, Labels & Systems, 39, 11, pp. 69-70, (2001); Lipschultz D., Peer-to-peer goes corporate, Available, (2001); Markus H., Home PC firewall guide, Home PC Firewall Guide, (2002); Marr M., Warner B., Execs Hope Eminem.Net Can Revive Music Industry, (2002); Pace J., Dewyer B., Proactively managing content management, To-Day-The Journal of Work Process Improvement, 3 June, pp. 18-20, (2002); Reed P., Decentralized Digital Music Finder Tests Limits of Copyright Enforcement, (2000); Rogers E., Diffusions of Innovations, (1995); Smith S., 50 Napster replacements, Computer Power User, 2, 2, pp. 54-58, (2002); Smith S., 50 Napster replacements, Gibson Research Corporation, Spinrite5, (2002); Stiennon R., Personal firewalls: Panacea or Pandora’s Box?, Techrepublic, (2001); Sweet M., Privacy issues vs. Security, Guide to PC Privacy, 8, 4, pp. 14-15, (2000); Van Winkle W., Music after Napster, Computer Power User, 2, 2, pp. 50-53, (2002); Van Winkle W., The next great thing?, Computer Power User, 2, 2, pp. 60-61, (2002); Gunden V., Tom T., E-business puts ERP under the microscope, Integrated Solutions, 6, 3 April, pp. 56-59, (2002)","A.D. Smith; Robert Morris University, Department of Management and Marketing, Pittsburgh, PA, 15219-3099, United States; email: smitha@rmu.edu",{"$nulls":7},1.5332861E7,null,null,null,"English","J. Internet Commer.","Article","Final",null,"Scopus","2-s2.0-85010575506"]
["Li S.-T.; Shue L.-Y.","Li, Sheng-Tun (8524895300); Shue, Li-Yen (7004463437)","8524895300; 7004463437","A study of logistics infomediary in air cargo tracking",2003.0,"Industrial Management and Data Systems",103.0,"2024-02-01",null,5.0,13.0,8.0,6.0,"10.1108/02635570310456841","https://www.scopus.com/inward/record.uri?eid=2-s2.0-0038267894&doi=10.1108%2f02635570310456841&partnerID=40&md5=96c2460be17b843e73ab01532e212f9a","Information Management Department, National Kaohsiung First University of Science and Technology, Taiwan","Li S.-T., Information Management Department, National Kaohsiung First University of Science and Technology, Taiwan; Shue L.-Y., Information Management Department, National Kaohsiung First University of Science and Technology, Taiwan","In e-commerce, the infomediary is rapidly becoming an important business model on the Web. A low cost Web-based infomediary for the air cargo Industry can help Integrate Air Cargo service providers and their customers, and thus Improve the productivity of the logistics chain. Customers can access flight Information of cargo carriers through the infomediary in a much more simplified way, thus management can better plan the subsequent operations. Proposes a three-tier paradigm for developing an air cargo logistics infomediary. This paradigm Integrates emerging technologies of the next-generation Web-based systems to address the three Issues for the development. A prototype system was developed to demonstrate Its capability In accepting requests from general browsers, retrieving data from different platforms, and presenting data in a consistent and personalized format. © MCB UP Limited.","Cargo; Electronic commerce; Logistics; Tracking","Electronic commerce; Internet; Java programming language; Tracking (position); Web browsers; XML; Supplier agents; Cargo aircraft",{"$nulls":6},"Ashok S., Bansal V.K., Java: Network-centric enterprise computing, Computer Communications, 20, pp. 1467-1480, (1998); Bailey J.P., Bakos Y., An exploratory study of the emerging role of electronic intermediaries, International Journal of Electronic Commerce, 1, pp. 7-20, (1997); Bakos Y., The emerging role of electronic marketplaces on the Internet, Communication of the ACM, 41, pp. 35-42, (1998); Daniel E., Klimis G., The impact of electronic commerce on market structure: An evaluation of electronic market hypothesis, European Journal, 17, pp. 318-325, (1999); Survey: Business and the Internet: The rise of the infomediary, The Economist, 351, pp. B21-B24, (1999); Grover V., Teng J.T.C., E-commerce and the information market, Communication of the ACM, 44, 3, pp. 79-86, (2001); Glushko R.J., Tenenbaum J.M., Meltzer B., An XML framework for agent-based e-commerce, Communications of the ACM, 42, 3, pp. 106-114, (1999); Hagel J., Singer M., Net Worth, (1999); Leung L.C., Cheung W., Hui Y.V., A framework for a logistics e-commerce community network: The Hong Kong air cargo industry, IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans, 30, 4, pp. 446-455, (2000); Li S.-T., Java Practical Programming (in Chinese), (1999); McGinity M., Flying wireless, with a net, Communications of the ACM, 42, 12, pp. 19-21, (1999); Malone T., Yates J., Electronic markets and electronic hierarchies, Communication of the ACM, 30, pp. 484-497, (1987); Meltzer B., Glushko R., XML and electronic commerce: Enabling the network economy, ACM SIGMOD, 27, 4, (1998); Rao B., The Internet and the revolution in distribution: A cross-industry examination, Technology in Society, 21, pp. 287-306, (1999); Sarkar M.B., Butler B., Steinfeld C., Intermediaries and cybermediaries: A continuing role for mediating players in the electronic marketplace, Journal of Computer-Mediated Communication, 1, (1996); (2000); Tornqvist A., Nelson C., Johnson M., XML and objects-the future of the e-forms on the Web, Proceedings of IEEE 8th International Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprises, pp. 303-308, (1999); Vielmetti E., The (r)evolution of useful Web services, IEEE Communications Magazine, pp. 92-94, (1999); Extensible Markup Language (XML), (2000); Yen B.P.-C., Ng K.Y.M., Web-based virtual reality catalog in electronic commerce, Proceedings of the 33rd Hawaii International Conference on System Sciences (CD-ROM), (2000)",{"$nulls":8},2635577.0,null,null,null,"English","Ind Manage Data Sys","Article","Final",null,"Scopus","2-s2.0-0038267894"]
["Chiang W.-Y.K.; Monahan G.E.","Chiang, Wei-Yu Kevin (7102015428); Monahan, George E. (7004174773)","7102015428; 7004174773","Managing inventories in a two-echelon dual-channel supply chain",2005.0,"European Journal of Operational Research",162.0,2.0,null,325.0,341.0,16.0,247.0,"10.1016/j.ejor.2003.08.062","https://www.scopus.com/inward/record.uri?eid=2-s2.0-9644279796&doi=10.1016%2fj.ejor.2003.08.062&partnerID=40&md5=8772a4d98b6cc3b1753dab182e15e993","Department of Information Systems, Univ. of Maryland, Baltimore County, Baltimore, MD 21250, 1000 Hilltop Circle, United States; Dept. of Business Administration, Univ. Illinois at Urbana-Champaign, 91 Wohlers Hall, Champaign, IL 61820, 1206 S. Sixth Street, United States","Chiang W.-Y.K., Department of Information Systems, Univ. of Maryland, Baltimore County, Baltimore, MD 21250, 1000 Hilltop Circle, United States; Monahan G.E., Dept. of Business Administration, Univ. Illinois at Urbana-Champaign, 91 Wohlers Hall, Champaign, IL 61820, 1206 S. Sixth Street, United States","We present a two-echelon dual-channel inventory model in which stocks are kept in both a manufacturer warehouse (upper echelon) and a retail store (lower echelon), and the product is available in two supply channels: a traditional retail store and an Internet-enabled direct channel. The system receives stochastic demand from two customer segments: those who prefer the traditional retail store and those who prefer the Internet-based direct channel. The demand of retail customers is met with the on-hand inventory from the bottom echelon while the demand in the Internet-enabled channel is fulfilled through direct delivery with the on-hand inventory from the upper echelon. When a stockout occurs in either channel, customers will search and shift to the other channel with a known probability. A one-for-one inventory control policy is applied. In order to develop operational measures of supply chain flexibility, we define a cost structure which captures two different operational cost factors: inventory holding costs and lost sales costs. We discuss several insights that are evident from the parametric analysis of the model. We also examine the performance of two other possible channel distribution strategies: retail-only and direct-only strategies. Computational outcomes indicate that the dual-channel strategy outperforms the other two channel strategies in most cases, and the cost reductions realized by the flexibility of the dual-channel system may be significant under some circumstances. © 2003 Elsevier B.V. All rights reserved.","Channels of distribution; Direct marketing; E-commerce; Inventory; Supply chain management","Costs; Customer satisfaction; Electronic commerce; Marketing; Mathematical models; Probability; Warehouses; Channels of distribution; Direct management; Dual-channel strategy; Supply chain management; Inventory control",{"$nulls":6},"Aggarwal P.K., Moinzadeh K., Order expedition in multi-echelon production/distribution systems, IIE Transactions, 26, pp. 86-96, (1994); Alfredsson P., Verrijdt J., Modeling emergency supply flexibility in a two-echelon inventory system, Management Science, 45, pp. 1416-1431, (1999); Anderson E., Day G.S., Rangan V.K., Strategic channel design, Sloan Management Review, 38, 4, pp. 59-69, (1997); Axsater S., Simple solution procedures for a class of two-echelon inventory problems, Operations Research, 38, pp. 64-69, (1990); Axsater S., Exact and approximate evaluation of batch ordering policies for two-level inventory systems, Operations Research, 41, pp. 777-785, (1993); Chiang W.K., Chhajed D., Hess J., Direct marketing, indirect revenues: A strategic analysis of dual-channel supply chain design, Management Science, 49, 1, pp. 1-20, (2003); Clark A., Scarf H., Optimal policies for a multi-echelon inventory problem, Management Science, 6, pp. 474-490, (1960); Clark T.D., Trempe R.E., Trichlin H.E., Complex multi-echelon inventory system management using a dynamic simulation model, Decision Sciences, 14, 3, pp. 389-407, (1983); Dada M., A two-echelon inventory system with priority shipments, Management Science, 38, pp. 1140-1153, (1992); Deuermeyer B.L., Schwarz L.B., A model for the analysis of system service level in warehouse retailer distribution systems: The identical retailer case, Multi-level Production/Inventory Control Systems: Theory and Practice Studies in Management Science, 16, pp. 163-193, (1981); Grahovac J., Chakravarty A., Sharing and lateral transshipment of inventory in a supply chain with expensive low-demand items, Management Science, 47, 4, pp. 580-595, (2001); Hadley G., Whitin T.M., Analysis of Inventory Systems, (1963); Kacen J., Hess J., Chiang W.K., Shoppers' attitudes toward online and traditional grocery stores, Working Paper, (2002); Keskinocak P., Tayur S., Quantitative analysis for Internet-enabled supply chains, Interfaces, 30, 2, pp. 70-89, (2001); Moinzadeh K., Lee H.L., Batch size and stocking levels in multi-echel on repairable systems, Management Science, 32, pp. 1567-1591, (1986); Moriarty R.T., Moran U., Managing hybrid marketing systems, Harvard Business Review, 68, 6, pp. 146-155, (1990); Nahmias S., Smith S.A., Optimizing inventory levels in a two-echelon retailer system with partial lost sales, Management Science, 40, pp. 582-596, (1994); Narus J.A., Anderson J.C., Rethinking distribution: Adaptive channels, Harvard Business Review, 74, 4, pp. 112-120, (1996); Preston L.E., Schramm A.E., Dual distribution and its impact on marketing organization, California Management Review, 8, 2, pp. 59-69, (1965); Pyke D.F., Priority repair and dispatch policies for repairable-item logistics systems, Naval Research Logistics, 37, pp. 1-30, (1990); Rangan V.K., Menezes M.A.J., Maier E.P., Channel selection for new industrial products: A framework, method, and application, Journal of Marketing, 56, 3, pp. 69-82, (1992); Rhee B., Park S., Online store as a new direct channel and emerging hybrid channel system, Working Paper, (1999); Sherbrooke C.C., METRIC: A multi-echelon technique for recoverable item control, Operations Research, 16, pp. 122-141, (1968); Svoronos A., Zipkin P., Estimating the performance of multi-level inventory systems, Operations Research, 36, pp. 57-72, (1988); Svoronos A., Zipkin P., Evaluation of one-for-one replenishment policies for multiechelon inventory systems, Management Science, 17, 1, pp. 68-83, (1991); Tedeschi B., Compressed data; big companies go slowly in devising net strategy, New York Times, (2000); Tsay A., Agrawal N., Channel conflict and coordination in the ebusiness era, Production & Operations Management, (2003)","W.-Y.K. Chiang; Department of Information Systems, Univ. of Maryland, Baltimore County, Baltimore, MD 21250, 1000 Hilltop Circle, United States; email: kevin@wchiang.net",{"$nulls":7},3772217.0,null,"EJORD",null,"English","Eur J Oper Res","Article","Final",null,"Scopus","2-s2.0-9644279796"]
["Wolf J.L.; Squillante M.S.; Turek J.J.; Yu P.S.; Sethuraman J.","Wolf, Joel L. (7403565732); Squillante, Mark S. (7006147882); Turek, John J. (57213800922); Yu, Philip S. (7402366049); Sethuraman, Jay (6701742793)","7403565732; 7006147882; 57213800922; 7402366049; 6701742793","Scheduling algorithms for the broadcast delivery of digital products",2001.0,"IEEE Transactions on Knowledge and Data Engineering",13.0,5.0,null,721.0,741.0,20.0,9.0,"10.1109/69.956097","https://www.scopus.com/inward/record.uri?eid=2-s2.0-0035438912&doi=10.1109%2f69.956097&partnerID=40&md5=f285bcb7455120a30f71a0add53e17fe","IEEE, United States; IBM T.J. Watson Research Center, Hawthorne, NY 10532, 30 Saw Mill Rivier Rd., United States; Columbia University, Mail Code 4704, New York, NY 10027, 331 Mudd, United States","Wolf J.L., IEEE, United States, IBM T.J. Watson Research Center, Hawthorne, NY 10532, 30 Saw Mill Rivier Rd., United States; Squillante M.S., IEEE, United States, IBM T.J. Watson Research Center, Hawthorne, NY 10532, 30 Saw Mill Rivier Rd., United States; Turek J.J., IEEE, United States, IBM T.J. Watson Research Center, Hawthorne, NY 10532, 30 Saw Mill Rivier Rd., United States; Yu P.S., IEEE, United States, IBM T.J. Watson Research Center, Hawthorne, NY 10532, 30 Saw Mill Rivier Rd., United States; Sethuraman J., Columbia University, Mail Code 4704, New York, NY 10027, 331 Mudd, United States","We provide scheduling algorithms that attempt to maximize the profits of a broadcast-based electronic delivery service for digital products purchased, for example, at e-commerce sites on the World Wide Web. Examples of such products include multimedia objects such as CDs and DVDs. Other examples include software and, with increasing popularity, electronic books as well. We consider two separate alternatives, depending in part on the sophistication of the set-top box receiving the product at the customer end. The first, more restrictive option, assumes that the atomic unit of transmission of the product is the entire object, which must be transmitted in order from start to finish. We provide a solution based in part on a transportation problem formulation for this so-called noncyclic scheduling problem. The second alternative, which is less restrictive, assumes that the product may be transmitted cyclically in smaller segments, starting from an arbitrary point in the object. Three heuristics are provided for this difficult cyclic scheduling problem. Both scenarios assume that the broadcasts of the same digital product to multiple customers can be \"batched.\" We examine the effectiveness of these algorithms via simulation experiments under varying parametric assumptions. Each of the three cyclic scheduling algorithms perform better than the noncyclic algorithm. Moreover, one of the cyclic scheduling algorithms emerges as the clear winner.","E-commerce; Electronic delivery service; Scheduling algorithms; Television broadcasting","Algorithms; Computer simulation; Digital devices; Heuristic methods; Multimedia systems; Resource allocation; Television broadcasting; World Wide Web; Cyclic scheduling problem; Digital products; Electronic delivery service; Scheduling algorithms; Electronic commerce",{"$nulls":6},"Acharya S., Muthukrishnan S., Scheduling on-demand broadcasts: New metrics and algorithms, Proc. Fourth Ann. ACM/IEEE Int'l Conf. Mobile Computing and Networking (Mobicom '98), 1998; Aggarwal C., Wolf J., Yu P., The maximum factor queue length batching scheme for video-on-demand storage systems, IEEE Trans. Computers, 50, 2, pp. 97-110, (2001); Ahuja R., Magnanti T., Orlin J., Network Flows, (1993); Aksoy D., Franklin M., RxW: A scheduling approach for large-scale on-demand data broadcast, ACM/IEEE Trans. Networking, (1999); Ammar M.H., Wong J.W., The design of teletext broadcast cycles, Performance Evaluation, 5, 4, pp. 235-242, (1985); Ammar M.H., Wong J.W., On the optimality of cyclic transmission on teletext systems, IEEE Trans. Comm., 35, 1, pp. 68-73, (1987); Anderson D., Metascheduling for continuous media, ACM Trans. Computer Systems, 11, 3, pp. 226-252, (1993); Anily S., Glass C.A., Hassin R., The scheduling of maintenance service, Discrete Applied Mathematics, pp. 27-42, (1998); Bar-Noy A., Bhatia R., Naor J., Schieber B., Minimizing service and operation costs of periodic-scheduling, Proc. Ninth ACM-SIAM Symp. Discrete Algorithms (SODA '98), pp. 11-20, (1998); Blazewicz J., Ecker K., Schmidt G., Weglarz J., Scheduling in Computer and Manufacturing Systems, (1993); Dan A., Sitaram D., Shahabuddin P., Scheduling policies for an on-demand video server with batching, Second ACM Multimedia Conf., 1994; Dykeman H.D., Ammar M.H., Wong J.W., Scheduling algorithms for videotex system under broadcast delivery, Proc. ICC '86, pp. 1847-1851, (1986); Garey M., Johnson D., Computers and Intractability, (1979); Gecsei J., The Architecture of Videotex Systems, (1983); Gelman A., Halfin S., Analysis of resource sharing in information providing services, IEEE Global Telecommunications Conf. and Exhibition, 1, (1990); Hall L., Shmoys D., Wein J., Scheduling to minimize average completion time: Off-line and on-line algorithms, Sixth ACM-SIAM Symp. Discrete Algorithms, 1996; Hochbaum D., Approximation Algorithms for NP-Hard Problems, (1997); Ibarra O., Kim C., Approximation algorithms for certain scheduling problems, Math. of Operations Research, 3, 3, pp. 197-204, (1978); Iyengar A., Squillante M., Zhang L., Analysis and characterization of large-scale web server access patterns and performance, World Wide Web, 2, pp. 85-100, (1999); Kenyon C., Schabanel N., The data broadcast problem with nonuniform transmission times, Proc. 10th ACM-SIAM Symp. Discrete Algorithms (SODA '99), pp. 547-556, (1999); Kenyon C., Schabanel N., Young N., A polynomial-time approximation scheme for data broadcast, Proc. 32nd ACM Symp. Theory of Computing (STOC 2000), pp. 659-666, (2000); Pinedo M., Scheduling: Theory, Algorithms and Systems, (1995); Press W., Flannery B., Teukolsky S., Vetterling W., Numerical Recipes, (1986); Ramamritham K., Vinay V., Scheduling algorithms for the broadcast delivery of multimedia products, Second Int'l Workshop Advanced Issues of E-Commerce and Web-Based Information Systems, 2000; Schachnai H., Yu P., Exploring wait tolerance in effective batching for video-on-demand scheduling, ACM Multimedia Systems, 6, 6, pp. 382-394, (1998); (1999); Squillante M., Yao D., Zhang L., Web traffic modeling and web server performance analysis, IEEE Conf. Decision and Control, 1999; (2000); Su C.-J., Tassiulas L., Tsotras V.J., Broadcast scheduling for information distribution, ACM/Baltzer J. Wireless Networks, 5, 2, pp. 137-147, (1999); Trivedi K., Probability and Statistics with Reliability, Queueing, and Computer Science Applications, (1982); Vaidya N., Hameed S., Efficient algorithms for scheduling single and multiple channel broadcast, (1997); Vaidya N., Hameed S., Log time algorithms for scheduling single and multiple channel data broadcast, Proc. Fourth Ann. ACM/IEEE Int'l Conf. Mobile Computing and Networking (Mobicom '97), 1997; (2001); Wolf J., Yu P., Shachnai H., Disk load balancing for video-on-demand systems, ACM Multimedia Systems, 5, 6, pp. 358-370, (1997); Wong J.W., Broadcast delivery, Proc. IEEE, 76, 12, pp. 1566-1577, (1988); Zipf G., Human Behavior and the Principle of Least Effort, (1949)","J.L. Wolf; IBM T.J. Watson Research Center, Hawthorne, NY 10532, 30 Saw Mill Rivier Rd., United States; email: jlwolf@us.ibm.com",{"$nulls":7},1.0414347E7,null,"ITKEE",null,"English","IEEE Trans Knowl Data Eng","Article","Final",null,"Scopus","2-s2.0-0035438912"]
["Subramanian G.H.; Iyigungor A.C.","Subramanian, Girish H. (7103332187); Iyigungor, Abdullah C. (12784784300)","7103332187; 12784784300","Information systems in supply chain management: A comparative case study of three organisations",2006.0,"International Journal of Business Information Systems",1.0,4.0,null,370.0,386.0,16.0,17.0,"10.1504/IJBIS.2006.008955","https://www.scopus.com/inward/record.uri?eid=2-s2.0-33645014610&doi=10.1504%2fIJBIS.2006.008955&partnerID=40&md5=9e81378feb0ad680ae1e144fa4e73510","School of Business, Penn State Harrisburg, Middletown, PA 17057, 777 W. Harrisburg Pike, United States","Subramanian G.H., School of Business, Penn State Harrisburg, Middletown, PA 17057, 777 W. Harrisburg Pike, United States; Iyigungor A.C., School of Business, Penn State Harrisburg, Middletown, PA 17057, 777 W. Harrisburg Pike, United States","Supply Chain Management (SCM) is recognised as a core competitive strategy for businesses in almost every industry. A strong supply chain provides products and services to consumers faster, cheaper, and better. The paper discusses SCM and information systems in the supply chain. Case studies of Wal-Mart, Amazon.Com and United Parcel Services (UPS) and their use of information systems in the supply chain are presented. Wal-Mart and Amazon have established critical and timely strategies in their supply chains through huge investments in Information Technology (IT). While Wal-Mart and Amazon are offering their products to consumers, UPS offers logistics solutions to clients. These companies use a variety of information technologies which include satellite systems, barcodes, web-based Electronic Data Interchange (EDI), Radio Frequency Identification (RFID), data warehousing, and e-commerce in their supply chain. The supply chain and use of these technologies in SCM are reviewed and compared for these three organisations. Copyright © 2006 Inderscience Enterprises Ltd.","E-commerce; Information systems applications; Information technology; Supply Chain Management (SCM); Web-based electronic data interchange",{"$nulls":7},"Amazon.com (Annual Report), (2004); Angulo A., Nachtmann H., Waller M.A., Supply chain information sharing in a vendor managed inventory partnership, Journal of Business Logistics, 25, 1, pp. 102-121, (2004); Continue making investments in supply chain technology (logistics management), (2004); Logistics today's: 10 best supply chains of 2004, Logistic Today, 45, 12, pp. 17-23, (2004); Bacheldor B., From scratch: Amazon keeps supply chain close to home, Information Week, 23, 979, pp. 40-41, (2004); Bagchi P.K., Larsen T.S., Integration of information technology and organizations in a supply chain, International Journal of Logistics Management, 14, 1, pp. 89-98, (2003); Bednarz A., Internet EDI: Blending old and new, Network World, 21, 8, pp. 29-30, (2004); Bednarz A., RFID joins wireless lineup at UPS, Network World, 21, 38, (2004); Croson R., Donohue K., Impact of POS data sharing on supply chain management: An experimental study, Production and Operations Management, 12, 1, pp. 1-12, (2003); Delfmann W., Albers S., Gehring M., The impact of electronic commerce on logistics service providers, International Journal of Physical and Logistics Management, 32, 3-4, pp. 203-223, (2002); Elbert B., Making your idea happen - Creating a viable satellite application, Application Technology Strategy, (2005); Ellram L.M., Tate W.L., Billington C., Understanding and managing the services supply chain, Journal of Supply Chain Management, 40, 4, pp. 17-33, (2004); Eskew M., The art (and science) of delivery, Chief Executive, 3, 201, (2004); Fishman C., The Wal-Mart you don't know, Fast Company, 77, 1, pp. 68-78, (2003); Foote P.S., Krishnamurthi M., Forecasting using data warehousing model: Wal-Mart's experience, The Journal of Business Forecasting Methods and Systems, 20, 3, pp. 13-18, (2001); Giannakis M., Croom S.R., Toward the development of a supply chain management paradigm: A conceptual framework, Journal of Supply Chain Management, 40, 2, pp. 27-37, (2004); Gibson P.R., Edwards J., The strategic importance of e-commerce in modern supply chains, Journal of Electronic Commerce in Organizations, 2, 3, pp. 59-76, (2004); Gilligan E., Ready for battle?, Journal of Commerce, 15, (2004); Grean M., Shaw M.J., Supply-Chain Integration Through Information Sharing: Channel Partnership Between Wal-Mart and Procter and Gamble, (2005); Greenfield D., Amazon: Website to web services, Network Magazine, 19, 10, (2004); Hadley S., Making the supply chain management business case, Strategic Finance, 85, 10, pp. 28-34, (2004); Handfield R.B., Nichols E.L., Introduction to Supply Chain Management, (1999); Hugos M., Essentials of Supply Chain Management, (2003); Janoff B., High-tech knowledge, Progressive Grocer, 79, 12, pp. 45-48, (2000); Kandampully J., B2B relationships and networks in the internet age, Management Decision, 41, 5-6, pp. 443-452, (2003); Kinsella B., The Wal-Mart factor, Industrial Engineer, 35, 11, pp. 32-36, (2003); Lambert D.M., Stock J.R., Ellram L.M., Fundamentals of Logistics Management, (1998); McLaughlin J., Motwani J., Madan M.S., Gunasekaran A., Using information technology to improve downstream supply chain operations: A case study, Business Process Management Journal, 9, 1, pp. 69-83, (2003); Maloney D., E-conveyors, Modern Materials Handling, 55, 1, pp. 49-53, (2000); Nah F., Supply chain and enterprise systems management and solutions, Information Resources Management Journal, 17, 3, pp. 1-3, (2004); Post G.V., Anderson D.L., Management Information Systems: Solving Business Problems With Information Technology, (2003); Russell R., Taylor III B., Operations Management, (2003); Sullivan L., E-commerce: Promise fulfilled, Information Week, 10, 13, pp. 70-73, (2004); Swaminathan J.M., Tayur S.R., Models for supply chains in e-business, Management Science, 49, 10, (2003); Taylor D.A., A Manager's Guide - Chapter 1, (2005); Tracey M., Fite R.W., Sutton M.J., An explanatory model and measurement instrument: A guide to supply chain management research and applications, Mid-American Journal of Business, 19, 2, pp. 53-82, (2004); Wheatley B., Amazon.com sees supply chain as crucial to its future, Global Logistics and Supply Chain Strategies, (2000); Woollacott E., Will RFID make the grade?, Computer Trade Shopper, (2004); Yu Z., Yan H., Cheng T.C.E., Benefits of information sharing with supply chain partnership, Industrial Management and Data, 102, 3-4, pp. 114-120, (2001)","G.H. Subramanian; School of Business, Penn State Harrisburg, Middletown, PA 17057, 777 W. Harrisburg Pike, United States; email: ghs2@psu.edu",null,"Inderscience Publishers",{"$nulls":5},1.7460972E7,null,null,null,"English","Int. J. Bus. Inf. Syst.","Article","Final",null,"Scopus","2-s2.0-33645014610"]
["Paris M.","Paris, Maeve (56208313300)",5.62083133E10,"Local e-government and devolution: Electronic service delivery in Northern Ireland",2005.0,"Local Government Studies",31.0,3.0,null,307.0,319.0,12.0,12.0,"10.1080/03003930500095137","https://www.scopus.com/inward/record.uri?eid=2-s2.0-20444460208&doi=10.1080%2f03003930500095137&partnerID=40&md5=0076dce761a2ba4ee87a4b19254ea9b4","School of Computing and Intelligent Systems, University of Ulster at Magee, Londonderry BT48 7JL, United Kingdom","Paris M., School of Computing and Intelligent Systems, University of Ulster at Magee, Londonderry BT48 7JL, United Kingdom","There are billions of annual transactions between citizens and government; most of these are between citizens and local government. Both central and local government share the same target for electronic service delivery: 100% of key services online by 2005. In Northern Ireland, however, district councils are being left behind on the e-government agenda. The Northern Ireland Assembly, currently suspended, has no provisions or recommendations for local e-government, although many transactional services of interest to ordinary citizens are provided by local councils. The absence of a strategy for local e-government means that district councils are left to their own devices, and this contrasts with the rest of the UK. A snapshot of local councils is used to assess the extent of provision of electronic service delivery, highlighting examples of innovation, and indicating significant challenges for Northern Ireland local e-government during a period of suspended devolution. © 2005 Taylor & Francis Group Ltd.",null,"Eastern Hemisphere; Eurasia; Europe; United Kingdom; Western Europe; World; devolution; e-commerce; local economy; local government",{"$nulls":6},"Councils and E-government, Research So Far, (2002); Councils are less powerful than in Wales, Belfast Telegraph, (2003); E.Gov: Electronic Government Services for the 21st Century, (2000); Electronic Government: The View from the Queue, (1998); Corporate Strategic Framework for Delivering Government Services Electronically in Northern Ireland, (2001); Guidelines for the Initiation of E-Government Pilot Projects, (2003); (2003); Spoke in the wheel, Guardian, (2003); Local E-Government Now, 2004 - Building on Success, (2004); Leapfrog to the Information Age, (2000); E-Government: Electronic Access to Public Services, (2002); (2003); Implementing Electronic Government (IEG) Statement Guidance, (2001); OnlineNI - A Vision for 21st Century Government for Northern Ireland, (2003); Programme for Government, (2001); Programme for Government, (2003); E-Government Priorities Identified to Help Get Councils On-line for Success, (2004); Electronic Service Delivery: Spring 1999, (1999); Electronic Delivery of Government Services, (1999); E-Government: A Strategic Framework for Public Services in the Information Age, (2000); UK Online Annual Report 2002, (2002); (2003); Bridging the Digital Divide in Northern Ireland: A Consultation Document, (2002); (1999); Information Age Government in Scotland - A Common Framework, (2002); Fifth Electronic Service Delivery Progress Report, (2004); Local E-Government Now, (2001); Better Connected 2003, (2003); Better Connected 2004, (2004); Thornton J., EChampions Conference to Announce Key Survey Findings, (2003)","M. Paris; School of Computing and Intelligent Systems, University of Ulster at Magee, Londonderry BT48 7JL, United Kingdom; email: m.paris@ulster.ac.uk",{"$nulls":7},3003930.0,null,null,null,"English","Local Gov. Stud.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-20444460208"]
["Bergendahl G.","Bergendahl, Goran (6602625463)",6.602625463E9,"Models for investment in electronic commerce - Financial perspectives with empirical evidence",2005.0,"Omega",33.0,4.0,null,363.0,376.0,13.0,25.0,"10.1016/j.omega.2004.07.021","https://www.scopus.com/inward/record.uri?eid=2-s2.0-12344307369&doi=10.1016%2fj.omega.2004.07.021&partnerID=40&md5=7d5b5fea88797c96d54ddd27ac91d6ac","Dept. of Business Administration, School of Econ./Commercial Law, Göteborg University, 405-30 Goteberg, Box 610, Sweden","Bergendahl G., Dept. of Business Administration, School of Econ./Commercial Law, Göteborg University, 405-30 Goteberg, Box 610, Sweden","Electronic Commerce (\"eCommerce\") is a concept for trade based upon products and services that are being marketed, contracted, and paid for over the Internet. Consequently, electronic commerce demands for the investment in computer systems, marketing, logistics and payments. This paper will develop conditions for profitable investments in eCommerce with a special focus on outlays for information technology systems and sales management. If the services are made more standardized, if they do not change that often, or if they are well known to the customers so that there is little need for supplementary information, then the less costly will the information technology system become. The investment in marketing depends on how well known the brand name is to the customer. eCommerce firms \"Born on the Net\" have to spend substantially more resources on marketing than firms that \"Move to the Net\". These investments may be seen as parts of a process, which aims to generate larger revenues to the firm, better services to the customers, a more efficient logistic system, and lower payment costs. A financial perspective is taken, where investment outlays for web services and marketing are balanced to cost savings when serving existing customers and net revenues from the generation of new customers. This financial approach is applied to five case studies from the sectors of capital goods, financial services, food, ornamental horticulture, and books and stationeries, where the given background from practice and conditions for success are developed in terms of a customer-base, margins, and sales growth. It is demonstrated that an existing customer base offline reduces the need for a marketing that is costly. It is also shown that a combination of services online and offline improves customer services and increases the extension of repeat purchases. © 2004 Elsevier Ltd. All rights reserved.","Cross-selling; Customer retention; E-commerce cases; Marketing investments","Electronic commerce; Information management; Logistics; Sales; Web services; Condition; Cross-selling; Customer retention; Customerbase; E-commerce case; Information technology systems; Marketing investment; Offline; Product and services; Systems management; Investments",{"$nulls":6},"Kalakota R., Whinston A.B., Electronic commerce. A manager's guide, (1999); OECD: The economic and social impact of electronic commerce, (1999); Varianini V., Vaturi D., Marketing lessons from e-failures, The McKinsey Quarterly, (2000); Wigand R.T., Electronic commerce: Definition, theory, and context, The Information Society, 13, pp. 1-16, (1997); Osterle H., Fleisch E., Alt R., Business networking. Shaping enterprise relationships on the internet, (2000); Farbey B., Land F., Targett D., Evaluating investments in IT, Journal of Information Technology, 7, pp. 109-122, (1992); Giaglis G.M., Paul R.J., Doukidis G.I., Dynamic modelling to access the business value of electronic commerce, International Journal of Electronic Commerce, 3, pp. 35-51, (1999); Sarker R.A., Syed M.R., Economics of EDI investments, Electronic Commerce: Opportunity and Challenges, (2000); Elliot S., Briers M., E-business challenges for Australia's wholesale financial markets SIRCA; (1999); Hanson W., Principles of Internet Marketing, (2000); Calkins J.D., Farello M.J., Smith Shi C., From retailing to e-tailing, McKinsey Quarterly, (2000); Cunningham M.J., B2B. How to build a profitable e-commerce strategy, (2000); (2000); (1999); Whinston A.B., Stahl D.O., Choi S.-Y., The economics of electronic commerce, (1997); Korper S., Ellis J., The E-commerce Book. Building The E-empire, (2000); Meeker M., (1997); Carpenter P., eBrands, (2000); Dayal S., Landesberg H., Zeisser M., Building digital brands, The McKinsey Quarterly, (2000); Levy D., Bergen M., Dutta S., Venable R., The magnitude of menu costs: Direct evidence from large U.S. supermarket chains, Quarterly Journal of Economics, 112, 3, pp. 791-825, (1997); (2000); Clemons E.K., Hitt L.M., The internet and the future of financial services: Transparency, differential pricing and disintermediation, (2000); Schutzer D., Foundations for electronic commerce, Banking and Finance on the Internet, (1997); Ouren J., Singer M., Stephenson J., Weinberg A.L., Electronic bill payment and presentment, The McKinsey Quarterly, (1998); Skibo J.E., Gordon D., Building e-commerce from the ground up: A study of the retail industry, Electronic Commerce: Opportunity and Challenges, pp. 1-2, (2000); Booth A.Q., Making the internet work for your business, (1999); Konkurrensverket, E-handel i Sverige - En explorativ studie, (2001); (2000); Webvan: The new and improved milkman, (2001); Deutsch J., Bunker D., Electronic grocery shopping (EGS) - Ordinary success and spectacular failure. A Tale of Two Models, SISTM, (2001); Kinsey J., Electronic systems in the food industry, entropy, speed and sales, A Paper from the Conference E-Business Transformation: Sector Developments and Policy Implications\", (2000); (2001); (2000); Quaddus M.A., Diffusion of electronic commerce in Australia: A preliminary investigation, Electronic Commerce: Opportunity and Challenges, (2000); Rao V.R., Resources for research and pedagogy on new product development processes, Journal of Marketing Research, 34, pp. 185-192, (1997); Rogers E.M., Diffusion of Innovations, (1995); Bergendahl G., The profitability of bancassurance for European banks, International Journal of Bank Marketing, 13, 1, (1995); Dixit A.K., Pindyke R.S., Investment under uncertainty, (1994); Dixit A.K., Pindyke R.S., The options approach to capital investment, Harvard Business Review, (1995)","G. Bergendahl; Dept. of Business Administration, School of Econ./Commercial Law, Göteborg University, 405-30 Goteberg, Box 610, Sweden; email: goran.bergendahl@handels.gu.se",null,"Elsevier BV",{"$nulls":5},3050483.0,null,"OMEGA",null,"English","Omega","Article","Final",null,"Scopus","2-s2.0-12344307369"]
["Garcés S.A.; Gorgemans S.; Martínez Sánchez A.; Pérez Pérez M.","Garcés, Silvia Abella (56549046900); Gorgemans, Sophie (6504225844); Martínez Sánchez, Angel (55461631900); Pérez Pérez, Manuela (57205467233)","56549046900; 6504225844; 55461631900; 57205467233","Implications of the Internet - An analysis of the Aragonese hospitality industry, 2002",2004.0,"Tourism Management",25.0,5.0,null,603.0,613.0,10.0,50.0,"10.1016/j.tourman.2003.06.003","https://www.scopus.com/inward/record.uri?eid=2-s2.0-3042544488&doi=10.1016%2fj.tourman.2003.06.003&partnerID=40&md5=7a95cb6ba496727a234c8b2d847f78b7","Depto de Econ/Direccion de Empresas, Escuela Univ Estudios Empresariales, Huesca 22071, Ronda Misericordia, 1, Spain; Depto de Econ/Direccion de Empresas, Centro Politécnico Superior, Zaragoza 50018, María de Luna 3, Spain","Garcés S.A., Depto de Econ/Direccion de Empresas, Escuela Univ Estudios Empresariales, Huesca 22071, Ronda Misericordia, 1, Spain; Gorgemans S., Depto de Econ/Direccion de Empresas, Escuela Univ Estudios Empresariales, Huesca 22071, Ronda Misericordia, 1, Spain; Martínez Sánchez A., Depto de Econ/Direccion de Empresas, Centro Politécnico Superior, Zaragoza 50018, María de Luna 3, Spain; Pérez Pérez M., Depto de Econ/Direccion de Empresas, Centro Politécnico Superior, Zaragoza 50018, María de Luna 3, Spain","This paper studies the impact of electronic commerce (e-commerce) on the management of Spanish tourism. The paper contributes to the literature that emphasizes the importance of e-commerce and information technologies for tourism companies. The survey analyzes companies' reasons to use e-commerce, its difficulties, consequences, and other important topics like electronic payment or the logistics of e-commerce. The paper also analyzes the relationship between the use of e-commerce, and a company's strategy, organizational structure, management information systems and human resources management. © 2003 Elsevier Ltd. All rights reserved.","E-commerce; Information technologies; Strategic management","Aragon; Eurasia; Europe; Southern Europe; Spain; e-commerce; information technology; Internet; tourism management",{"$nulls":4},"Institución Fernando el Católico","The authors wish to thank the financial support from the Institución Fernando el Católico (Grant, 2002).   ","Buhalis D., Strategic use of information technologies in the tourism industry, Tourism Management, 19, 5, pp. 409-421, (1998); Buhalis D., Licata M., The future of eTourism intermediaries, Tourism Management, 23, pp. 207-220, (2002); Cho V., World wide web resources, Annals of Tourism Research, 25, 2, pp. 518-521, (1998); Connell J., Reynolds P., The implications of technological developments on Tourist Information Centres, Tourism Management, 20, pp. 501-509, (1999); Davenport T., Saving IT's soul: Human-centered information management, Harvard Business Review, 72, 2, pp. 119-131, (1994); E-Commerce in Europe. Results of the pilot surveys carried out in 2001, Eurostat, (2002); Fahy J., Hooley G., Sustainable competitive advantage in electronic business: Towards a contingency perspective on the resource-based view, Journal of Strategic Marketing, 10, 4, pp. 241-253, (2002); Grande I., Fundamentos Y Técnicas de Investigación Comercial, (1996); Gunasekaran A., Marri H., McGraughey R., Nebhwani M., E-commerce and its impact on operations management, International Journal of Production Economics, 75, pp. 185-197, (2002); Huber G., A theory of the effects of advanced information technology on organizational design, intelligence, and decision making, Academy of Management Review, 15, 1, pp. 47-71, (1990); Kalakota R., Whinston A., Electronic Commerce: A Manager's Guide, (1997); Kasavana L., Knuston B., Polonowski S., Netlurking: The future of hospitality internet marketing, Journal of Hospitality - Leisure Marketing, 5, 1, pp. 31-44, (1997); The KPMG Transport, Leisure and Tourism Industries Bulletin, (2000); Lukas H., Baroudi J., The role of information technology in organizational design, Journal of Management Information Systems, 10, 4, pp. 9-23, (1994); Ngai E., Wat F., A literature review and classification of electronic commerce research, Information - Management, 39, pp. 415-429, (2002); Peacock M., Some questions on the hospitality industry and advanced technological change, International Journal of Hospitality Management, 13, 1, pp. 19-24, (1994); Pfeffer J., Producing sustainable competitive advantage through the effective management of people, Academy of Management Executive, 9, 1, pp. 55-69, (1995); Porter M., Technology and competitive advantage, The Journal of Business Strategy, 5, 3, pp. 46-64, (1985); Porter M., Strategy and the Internet, Harvard Business Review, 79, 3, pp. 63-78, (2001); Powell T., Dent-Micallef A., Information technology as competitive advantage: The role of human, business, and technology resources, Strategic Management Journal, 18, 5, pp. 375-405, (1997); Prajogo D., Sohal A., TQM and innovation: A literature review and research framework, Technovation, 21, 9, pp. 539-558, (2001); Reinders J., Baker M., The future for direct retailing of travel and tourism products: The influence of information technology, Progress in Tourism and Hospitality Research, 4, 1, pp. 1-15, (1998); Scanlin J., The Internet as an enabler of the Bell Atlantic project office, Project Management Journal, 29, 6, pp. 6-7, (1998); Spanos Y., Prastacos G., Polymenakou A., The relationship between information and communication technologies adoption and management, Information - Management, 39, pp. 659-675, (2002); Stipanuk D., Tourism and technology-interactions and implications, Tourism Management, 14, 4, pp. 267-278, (1993); Swarbrooke J., Technological developments and the future of the UK tourism industry, Insights, 7, 5, (1996); Tallon P., Kraemer K., Gurbaxani V., Executives perceptions of the business value of information technology: A process-oriented approach, Journal of Management Information Systems, 16, 4, pp. 145-173, (2000); Walle H., Tourism and the Internet: Opportunities for direct marketing, Journal of Travel Research, 35, 1, pp. 72-77, (1996); Zuboff S., In the Age of the Smart Machine, (1988)","A. Martínez Sánchez; Depto de Econ/Direccion de Empresas, Centro Politécnico Superior, Zaragoza 50018, María de Luna 3, Spain; email: anmarzan@unizar.es",null,"Elsevier Ltd",{"$nulls":5},2615177.0,null,null,null,"English","Tour. Manage.","Article","Final",null,"Scopus","2-s2.0-3042544488"]
["Zwass V.","Zwass, Vladimir (8232569300)",8.2325693E9,"Electronic commerce and organizational innovation: Aspects and opportunities",2003.0,"International Journal of Electronic Commerce",7.0,3.0,null,7.0,37.0,30.0,183.0,"10.1080/10864415.2003.11044273","https://www.scopus.com/inward/record.uri?eid=2-s2.0-2442601797&doi=10.1080%2f10864415.2003.11044273&partnerID=40&md5=f37651f587ae748099352742b566bbd5","Department of Computer Science, Management Information Systemsor, Fairleigh Dickinson University, United States","Zwass V., Department of Computer Science, Management Information Systemsor, Fairleigh Dickinson University, United States","Over the past decade, electronic commerce on the technological foundation of the Web-Internet compound has entered extensive areas of organizational and social activity. This broad-based organizational and technological development requires categorization in order to be understood in its entirety and exploited fully. The principal aspects of e-commerce are identified in five domains: commerce, collaboration, communication, connection, and computation. These aspects lead to specific innovational opportunities that can be exploited to organize and address marketplaces, offer innovative products, collaborate with business partners, transform business processes, and organize the delivery of information-system services. The result is a comprehensive framework of e-commerce as a technologically based means to business transformation and a metadisciplinary research field. Copyright © 2003 M.E. Sharpe, Inc. All rights reserved.","Conceptual Frameworks; Electronic Commerce; Innovation; Internet; World Wide WEB",{"$nulls":7},"Anderson, Clicks B., mortar, One channel is not enough, Knowledge Management, (2001); Andrews D., Preece J., Turoff M., A conceptual framework for demographic groups resistant to on-line community interaction, International Journal of Electronic Commerce, 6, 3, pp. 9-24, (2002); Applegate L., Building information age businesses for the 21st century, The E-Business Handbook, pp. 1-32, (2002); Astor A., A natural progression: Web services reaching vibrant new stage, Web Services Journal, pp. 20-22, (2002); Bailey J.P., Bakos Y., An exploratory study of the emerging role of electronic intermediaries, International Journal of Electronic Commerce, 1, 3, pp. 7-20, (1997); Bakos Y., The emerging role of electronic marketplaces on the Internet, Communications of the ACM, 41, 8, pp. 35-42, (1998); Bakos Y., Brynjolfsson E., Bundling information goods: Pricing, profits, and efficiency, Management Science, 45, 12, pp. 1613-1630, (1999); Bell G., Gemell J., A call for Home Media Network, Communications of the ACM, 45, 7, pp. 71-75, (2002); Berners-Lee T., Hendler J., Lassila O., The semantic Web, Scientific American, pp. 28-37, (2001); Bhargava H., Choudhary V., Information goods and vertical differentiation, Journal of Management Information Systems, 18, 2, pp. 89-106, (2001); Bialik C., Sell first, advertise later, Wall Street Journal, (2002); Bichler M., Et al., Application of flexible pricing in business-to-business electronic commerce, IBM Systems Journal, 41, 2, pp. 287-302, (2002); Billsus D., Et al., Adaptive interfaces for ubiquitous Web access, Communications of the ACM, 45, 5, pp. 34-40, (2002); Brynjolfsson E., Smith M., Frictionless commerce? A comparison of the Internet and conventional retailers, Management Science, 46, 4, pp. 563-585, (2000); Burt J., Gateway gears up grid computing push, eWeek, (2002); Cheng H.K., Sims R.R., Teegen H., To purchase or to pirate software: An empirical study, Journal of Management Information Systems, 13, 4, pp. 49-60, (1997); Chircu A., Kauffman R.J., Reintermediation strategies in business-to-business electronic commerce, International Journal of Electronic Commerce, 4, 4, pp. 7-42, (2000); Choi S.-Y., Stahl D.O., Whinston A.B., The Economics of Electronic Commerce, (1997); Clemons E.K., Gu B., Lang K.R., Newly vulnerable markets in an age of pure information products: An analysis of online music and online news, Journal of Management Information Systems, 19, 3, pp. 17-41, (2002); Clemons E.K., Reddi S.P., Row M.C., Information technology and the organization of economic activity: The \"move to the middle\" hypothesis, Journal of Management Information Systems, 10, 2, pp. 9-36, (1993); Cranor C.D., Et al., Enhanced streaming services in a content distribution network, IEEE Internet Computing, 5, 4, pp. 66-75, (2001); 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Manovich L., The Language of New Media, (2001); Markus L., Manville B., Agres C., What makes a virtual organization work?, Sloan Management Review, 41, 1, pp. 13-26, (2000); Marwick A.D., Knowledge management technology, IBM Systems Journal, 40, 4, pp. 814-830, (2001); Mearian L., MasterCard nears finish of payment system rollout, Computerworld, (2002); Moore C., Media projecting further, InfoWorld, pp. 27-28, (2002); Mount I., If they have to pay, will they come?, Business 2.0, (2003); Nishida T., Social intelligence design for the Web, Computer, 35, 11, pp. 37-41, (2002); Ostrom A.L., Bitner M.J., Meuter M.L., Self-service technologies, e-Service, pp. 45-64, (2002); Oxford English Dictionary, (1992); Poropudas T., Big three launch WLAN-Cometa; Raskin A., A faster ride to market, Business 2.0, pp. 49-54, (2002); Rheingold H., The Virtual Community: Homesteading on the Electronic Frontier, (1993); Ricadela A., Soat J., Play it again, Information Week, pp. 20-21, (2002); Sadeh N., M-Commerce, (2002); 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Customers as innovators: A new way to create value, Harvard Business Review, 80, 4, pp. 74-81, (2002); Thompson J.B., Ideology and Modern Culture: Critical Theory in the Era of Mass Communication, (1990); Totty M., The Dell myth: The middleman isn't dead after all, Wall Street Journal, (2002); Wenger E., Communities of Practice: Learning, Meaning, and Identity, (1998); Williamson O., Markets and Hierarchies: Analysis and Antitrust Implications, (1975); Wurman P.R., Dynamic pricing in virtual marketplaces, IEEE Internet Computing, pp. 36-42, (2001); Zhu H., Madnick S.E., Siegel M.D., Global comparison aggregation services, Proceedings of the First Workshop on e-Business WEB2002, pp. 73-84, (2002); Zuboff S., Maxmin J., The Support Economy: Why Corporations Are Failing Individuals and the Next Episode of Capitalism, (2002); Zwass V., Electronic commerce: Structures and issues, International Journal of Electronic Commerce, 1, 1, pp. 3-23, (1996); Zwass V., The embedding stage of electronic commerce, The E-Business Handbook, pp. 33-43, (2002)","V. Zwass; Department of Computer Science, Management Information Systemsor, Fairleigh Dickinson University, United States; email: zwass@fdu.edu",null,"M.E. Sharpe Inc.",{"$nulls":5},1.0864415E7,null,null,null,"English","Int. J. Elect. Commer.","Article","Final",null,"Scopus","2-s2.0-2442601797"]
["Yuan S.-T.; Cheng C.","Yuan, Soe-Tsyr (14049457500); Cheng, Chiahsin (56309773300)","14049457500; 56309773300","Ontology-based personalized couple clustering for heterogeneous product recommendation in mobile marketing",2004.0,"Expert Systems with Applications",26.0,4.0,null,461.0,476.0,15.0,35.0,"10.1016/j.eswa.2003.10.006","https://www.scopus.com/inward/record.uri?eid=2-s2.0-1442359660&doi=10.1016%2fj.eswa.2003.10.006&partnerID=40&md5=d1695421bf98411d363bbf5b76a8c104","MIS Department, National Chengchi Unisersity, Taipei, Taiwan","Yuan S.-T., MIS Department, National Chengchi Unisersity, Taipei, Taiwan; Cheng C., MIS Department, National Chengchi Unisersity, Taipei, Taiwan","Plethora of cellular phones has been increasingly driving the spread of e-commerce mechanisms running on mobile devices. For instance, mobile marketing fulfills the wireless delivery (to the devices of mobile users) of the recommended product information and even one-to-one recommendations. One-to-one recommendation not only reduces the time that customers have to expend to for attaining appropriate products, but also is a method to engender customer values and develop the long-term customer relationships. This paper presents a one-to-one recommendation mechanism that iteratively takes as inputs the audio customer messages (together with product information) and produces personalized product analogy structures (that subsequently drive the generation of personalized heterogeneous product recommendations) based on the coupled clustering algorithm. The personalized product analogy structures also evolve as the messages (of the correspondent customer) grow. We have implemented the mechanism with J2EE Web Service that has produced fairly promising evaluation results. © 2003 Elsevier Ltd. All rights reserved.","Analogy; Coupled clustering; Heterogeneous product recommendation; Mobile marketing; Ontology","Algorithms; Cellular telephone systems; Consumer products; Electronic commerce; Java programming language; Marketing; Speech recognition; Wireless telecommunication systems; World Wide Web; Analogy; Coupled clustering; Heterogeneous product recommendation; Mobile marketing; Ontology; Mobile telecommunication systems",{"$nulls":6},"Balabanovic M., Shoham Y., Fab: Content-based, vollaborative recommendation, Communications of the ACM, 40, 3, pp. 66-72, (1997); Deroo O., A short introduction to speech recognition, Tech Report; Falkenhainer B., Forbus K., Gentner D., The structure mapping engine: Algorithm and example, Artificial Intelligence, 41, 1, pp. 1-63, (1989); Gentner D., Structure-mapping: A theoretical framework for analogy, Cognitive Science, 7, 2, pp. 155-170, (1983); Gruber T.R., A translation approach to portable ontologies, Knowledge Acquisition, 5, 2, pp. 199-220, (1993); Hofstadter D., Mitchell M., The copycat project: A model of mental fluidity and analogy-making, Fluid Concepts and Creative Analogies, pp. 205-267, (1995); Jasper R., Uschold M., A framework for understanding and classifying ontology applications, Proceedings of the 12th Workshop on Knowledge Acquisition, Modeling and Management, (1999); Lawrence R.D., Almasi G.S., Kotlyar V., Viveros M.S., Duri S.S., Personalization of supermarket product recommendations, Data Mining and Knowledge Discovery, 5, 1, pp. 11-32, (2001); Lin D., An information-theoretic definition of similarity, Proceedings of the 15th International Conference on Machine Learning, pp. 296-304, (1998); Marx Z., Dagan I., Buhmann J., Coupled clustering: A method for detecting structural correspondence, Proceedings of the 18th International Conference on Machine Learning, pp. 353-360, (2001); Sarwar B., Karypis G., Konstan J., Riedl J., Analysis of recommendation algorithms for e-Commerce, Proceedings of the Second ACM Conference on Electronic Commerce, pp. 158-167, (2000); Schafer J.B., Konstan J., Riedl J., Recommender systems in e-commerce, Proceedings of the First ACM Conference on Electronic Commerce, pp. 158-166, (1999); Thomas A., Java™ 2 platform, enterprise edition: Ensuring consistency, portability, and interoperability, White Paper, (1999); Web services architecture, W3C Working Draft, (2003); Wu Y.H., Chen Y.C., Chen A., Enabling personalized recommendation on the web based on user interests and behaviors, Proceedings of the 11th International Workshop on Research Issues in Data Engineering, pp. 17-24, (2001); Wu Z., Palmer M., Verb semantics and lexical selection, Proceedings of the 32nd Annual Meeting of the Association for Computational Linguistics, pp. 133-138, (1994); Zuniga G.L., Ontology: Its transformation from philosophy to information systems, Proceedings of the International Conference on Formal Ontology in Information Systems, pp. 187-197, (2001)","S.-T. Yuan; MIS Department, National Chengchi Unisersity, Taipei, Taiwan; email: yuans@tpts1.seed.net.tw",{"$nulls":7},9574174.0,null,"ESAPE",null,"English","Expert Sys Appl","Article","Final",null,"Scopus","2-s2.0-1442359660"]
["Borins S.","Borins, Sandford (6603478843)",6.603478843E9,"On the frontiers of electronic governance: A report on the United States and Canada",2002.0,"International Review of Administrative Sciences",68.0,2.0,null,199.0,211.0,12.0,44.0,"10.1177/0020852302682003","https://www.scopus.com/inward/record.uri?eid=2-s2.0-0036079160&doi=10.1177%2f0020852302682003&partnerID=40&md5=7caf146ad5a6c334d4624e00fe3be3f8","University of Toronto, Toronto, ON M1C 1A4, 1265 Military Trail, Canada","Borins S., University of Toronto, Toronto, ON M1C 1A4, 1265 Military Trail, Canada","A great deal of activity that goes under the rubric of electronic governance is occurring in the United States and Canada at both the service delivery and political levels. This article will attempt to make sense of this activity by outlining the major directions in the evolution of electronic governance, in terms of both service delivery and the political process. It will speculate on implications for the work of public servants and politicians, and the relationship of both groups with one another and with the public. Electronic governance depends on the use of information technology (IT) by the general population. Here, the US and Canada are in the forefront. In both countries, approximately 70 percent of households now have a personal computer and the rate of internet access is over 60 percent (Brethour, 2001; Governing, 2001). Both economics and public policy are driving these percentages higher. The steady decrease in the price and increase in the capacity of personal computers is making them more accessible to people of lower incomes, thus narrowing the digital divide. The governments of both countries are encouraging universal internet access. The Canadian Government is providing internet access in all schools, libraries and small towns. The United States, which is more inclined to use earmarked taxes than Canada, has instituted the e-rate, a small surcharge on the telephone bills, and designated the funds it raises to pay for internet service at schools, libraries and health centres in poor and rural areas. By the end of this decade, computer use and internet access will likely exceed 90 percent of the adult population in both countries. In less than 20 years, personal computers and internet access will have become almost as ubiquitous as telephones and television. In addition, the internet is now becoming accessible by devices other than PCS such as pagers, TVS and wireless telephones (Caldow, 2001). These developments create the conditions for extensive growth of electronic governance.",null,"Canada; United States; e-commerce; governance approach; information technology; political process; service provision",{"$nulls":6},"Annual Report, (2000); Borins S., Wolf D., Realizing the potential of public sector information technology: An organizational challenge, Change, Governance, and Public Management, pp. 159-276, (2000); Bratton W., Andrews W., Leading for inovation and results in police departments, Leading for Innovation and Organizing for Results, pp. 251-262, (2001); Brethour P., Canadian love affair with net has PC ownership booming, The Globe and Mail, (2001); Caldow J., The Virtual Ballot Box: A Survey of Digital Democracy in Europe, (1999); Caldow J., Seven E-Government Leadership Milestones, (2001); Clift S., The E-democracy E-book: Democracy is Online 2.0, (2000); Conte C., Laptop legislatures, Governing, 13, 2, pp. 36-44, (1999); Fountain J., Osorio-Urzua C., Public sector: Early stage of a deep transformation, The Economic Payoff from the Internet Revolution, pp. 235-268, (2001); State and Local Source Book, (2001); Kernaghan K., Marson B., Borins S., The New Public Organization, (2000); Kippen G., The Use of New Information Technologies by a Political Party, (2000); Leblanc D., Web site offers help at the barricades, The Globe and Mail, (2001); MacKinnon M., Police-building petition comes to life on internet, The Globe and Mail, (2001); Norris P., Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide, (2001); O'Connell P., Using Performance Data for Accountability: The New York City Police Department's Compstat Model of Police Management, (2001); The hidden threat to e-government, PUMA Policy Brief No. 8, (2001); Porter M., Strategy and the internet, Harvard Business Review, 79, 3, pp. 62-78, (2001); Reschenthaler G., Thompson F., The information revolution and the new public management, Journal of Public Administration Research and Theory, 6, 1, pp. 125-143, (1996); Tuck S., Canada No. 1 in Federal E-service, The Globe and Mail, (2001)","S. Borins; University of Toronto, Toronto, ON M1C 1A4, 1265 Military Trail, Canada; email: borins@utsc.utoronto.ca",{"$nulls":7},208523.0,null,null,null,"English","Int. Rev. Adm. Sci.","Article","Final",null,"Scopus","2-s2.0-0036079160"]
["Williams E.; Tagami T.","Williams, Eric (7403996458); Tagami, Takashi (7006012719)","7403996458; 7006012719","Energy use in sales and distribution via e-commerce and conventional retail: A case study of the Japanese book sector",2002.0,"Journal of Industrial Ecology",6.0,2.0,null,99.0,114.0,15.0,78.0,"10.1162/108819802763471816","https://www.scopus.com/inward/record.uri?eid=2-s2.0-0036525134&doi=10.1162%2f108819802763471816&partnerID=40&md5=3b0ae5fc05a84b6edeb071c19643ee24","United Nations University, Tokyo 150, 53-70 Jingumae 5-chome Shibuya-ku, Japan; United Nations University, Tokyo, Japan; Institute of Behavioural Science, Tokyo, Japan","Williams E., United Nations University, Tokyo 150, 53-70 Jingumae 5-chome Shibuya-ku, Japan, United Nations University, Tokyo, Japan; Tagami T., Institute of Behavioural Science, Tokyo, Japan","Energy use associated with sales and distribution via business-to-consumer (B2C) e-commerce versus conventional retail is analyzed for the Japanese book sector. Results indicate that e-commerce uses considerably more energy per book than conventional retail in dense urban areas, because of additional packaging. In suburban and rural areas, the energy consumption of the two systems is nearly equal because the relative efficiency of courier services compared to personal automobile transport balances out the impact of additional packaging. The main reason e-commerce does not save energy, even in rural areas, is because of the multipurpose use of automobiles; e-commerce does consume less energy in the case of single-purpose shopping trips by automobile. Overall consumption at the national level is nearly the same: 5.6 megajoules (MJ) per book for e-commerce and 5.2 MJ per book for traditional retail. Although this difference is smaller than the uncertainty in the result, the structure of energy use for the two systems is quite distinct, which suggests reprioritization of energy-efficiency strategies. Important factors influencing the energy efficiency of B2C e-commerce include packaging, loading factors of courier trucks, number of trips per delivery, and residential energy consumption.","Business-to-consumer (B2C); Courier services; Information and communications technology (ICT); Life-cycle assessment (LCA); Loading factors; Product delivery","Automotive industry; Energy efficiency; Energy utilization; Sales; Courier services; Electronic commerce",{"$nulls":6},"Economic Inventory of Packaging Database (also Known as BUWAL 250), (1996); 2000 E-commerce Multi-sector Report, (2002); Enerugii Keizai Toukei Youran. [EDMC Handbook of Energy and Economic Statistics (in Japanese).], (2001); Funazaki A., Taneda L., Life cycle assessment of an end-of-life passenger car in 2002, Proceedings of the Fourth International Conference on Ecobalance, (2000); Economic Input-output Life Cycle Assessment, (2002); Hayakawa T., Shuppan Shihyou Nenpou. [Publishing Indicators Annual (in Japanese).], (2001); Matthews H.S., Hendrickson C., Soh D.L., Environmental and economic effects of e-commerce: A case study of book publishing and retail logistics, Transportation Research Record, 1763, pp. 6-12, (2001); Matthews H.S., Williams E., Tagami T., Hendrickson C., Energy implications of online book retailing in the United States and Japan, Environmental Impact Assessment Review, 22, pp. 493-507, (2002); Environmental Consciousness: A Strategic Competitiveness Issue for the Electronics and Computer Industry, (1993); Unyu Kankei Enerugii Youran. [The Survey on Transport Energy (in Japanese).], (2000); Miyamoto S., Tekawa M., Inaba A., Life cycle assessment of personal computers for the purpose of design for environment, Energy and Resources, 19, 1, pp. 75-80, (1998); Jidousha Unsou Toukei Nenpou, 2000. [Truck Shipping Statistics Annual, 2000 (in Japanese).], (2001); Nagasu H., Life cycle inventory analysis for a truck, Proceedings of the Fourth International Conference on Ecobalanee, (2000); 1995 NPTS Databook, (1995); 1995 NPTS Analysis, (2002); Peereboom E., Kleijn R., Lemkowitz S., Lundie S., Influence of inventory data sets on life-cycle assessment results: A case study on PVC, Journal of Industrial Ecology, 2, 3, pp. 109-130, (1999); Reichling M., Otto T., The environmental impact of the new economy: Deutsche Telekom, telecommunications services and the sustainable future, Ecology of the New Economy, (2002); Reijnders L., Hoogeveen M.J., Energy effects associated with e-commerce: A case study concerning online sales of personal computers in the Netherlands, Journal of Environmental Management, 62, 3, pp. 271-282, (2001); Romm J., Rosenfeld A., Herrman S., The Internet Economy and Global Warming, (1999); Sebun Irebun no Yokogao. [Profile of Seven-Eleven (in Japanese).], (2000); Sougou Enerugii Toukei. [Integrated Energy Statistics (in Japanese).], (2001); Smulders C., Watching Rome Burn: PC Empires Threatened by Extending Life Cycles, (2001); 1998 National Survey of Family Income and Expenditure, (1998); Yoku Wakaru Shuppan-ryuutsuu no Shikumi. [Introduction to the Distribution System for Books (in Japanese).], (2001); Household Vehicles Energy Consumption 1994, (1994); Williams E., Tagami T., Energy analysis of e-commerce and conventional retail distribution of books in Japan, Sustainability in the Information Society, (2001)","E. Williams; United Nations University, Tokyo 150, 53-70 Jingumae 5-chome Shibuya-ku, Japan; email: williams@hq.unu.edu",{"$nulls":7},1.088198E7,null,"JINEF",null,"English","J. Ind. Ecol.","Article","Final","All Open Access; Bronze Open Access","Scopus","2-s2.0-0036525134"]
["Van Dolen W.M.; De Ruyter K.","Van Dolen, Willemijn M. (6507929574); De Ruyter, Ko (7004664517)","6507929574; 7004664517","Moderated group chat: An empirical assessment of a new e-service encounter",2002.0,"International Journal of Service Industry Management",13.0,5.0,null,496.0,511.0,15.0,27.0,"10.1108/09564230210447959","https://www.scopus.com/inward/record.uri?eid=2-s2.0-0036447507&doi=10.1108%2f09564230210447959&partnerID=40&md5=0c5d5e771c44bf2966e1c2879d52c0f0","Dept. of Mktg. and Mktg. Research, Fac. of Econ. and Business Admin., Maastricht University, Maastricht, Netherlands","Van Dolen W.M., Dept. of Mktg. and Mktg. Research, Fac. of Econ. and Business Admin., Maastricht University, Maastricht, Netherlands; De Ruyter K., Dept. of Mktg. and Mktg. Research, Fac. of Econ. and Business Admin., Maastricht University, Maastricht, Netherlands","In this paper, the focus is on a new type of electronic service encounter called Moderated Group Chat (MGC). MGC is defined as on-line, real-time interactions between groups of customers with an active coordinating role for a company representative and a commercial objective. Based on the technology acceptance model, we develop a conceptual framework and examine empirically which factors drive customer satisfaction with MGC sessions. Particularly, we look at the impact of perceived usefulness, perceived ease of use and perceived enjoyment on customer satisfaction. As MGC involves multiple participants and interactions take place within an electronic group environment, predictor-criterion relationships may vary between individual-and group-level or shared perceptions. Therefore, the relationships between aforementioned determinants and chat session satisfaction are tested using a multi-level model. In addition, group size was included as a control variable. Finally, since chat is an innovative service delivery channel, we also took a number of customer characteristics (i.e. innovativeness, experience with investing and experience with chat) into account. Whereas we find support for a positive impact of the majority of predictor variables on chat session satisfaction, the precise nature of the relationship varies across levels. Moreover, while group size is positively related to satisfaction, experience with investing exhibits a weakly negative relationship.","Communication; Customer satisfaction; E-commerce; Internet; Modelling; Service delivery system",{"$nulls":7},"Albrecht K., Zemke R., Service America in the New Economy, (2001); Bergeron B., The EternaI E-Customer, (2001); Bitner M.J., Booms B.H., Tetreault M.S., The service encounter: Diagnosing favorable and unfavorable incidents, Journal of Marketing, 54, 1, pp. 71-84, (1990); Childers T.L., Christopher C.L., Peck J., Carson S., Hedonic and utilitarian motivations for online retail shopping behavior, Journal of Retailing, 77, pp. 511-535, (2001); Campion M.A., Medsker G.J., Higgs C.A., Relations between work group characteristics and effectiveness: Implications for designing effective work teams, Personnel Psychology, 46, pp. 823-850, (1993); Dabholkar P.A., Incorporating choice into an attitudinal framework: Analyzing models of mental comparison processes, Journal of Consumer Research, 21, 1, pp. 110-118, (1994); Dabholkar P.A., Consumer evaluations of new technology-based self-service options: An investigation of alternative models of service quality, International Journal of Research in Marketing, 13, pp. 29-51, (1996); Davis F.D., Perceived usefulness, perceived ease of use, and user acceptance of information technology, MIS Quarterly, 13, 3, pp. 319-340, (1989); Davis F.D., Bagozzi R.P., Warshaw P.R., Extrinsic and intrinsic motivation to use computers in the workplace, Journal of Applied Social Psychology, 22, 14, pp. 1109-1130, (1992); Deighton J., Romer D., McQueen J., Using drama to persuade, Journal of Consumer Research, 16, pp. 335-343, (1989); DiMartino D., Zoe L.R., End-user full-text searching: Access or excess?, Library & Information Science Research, 18, pp. 133-149, (1996); Evans K.R., Kleine R.E., Landry T.D., Crosby L.A., How first impressions of a customer impact effectiveness in an initial sales encounter, Journal of the Academy of Marketing Science, 28, 4, pp. 512-526, (2000); Fazio R.H., Attitude accessibility and motivation as determinants of biased processing: A test of the MODE model, Personality and Social Psycholgy, 21, 7, pp. 704-710, (1995); Fazio R.H., Zanna M.P., Attitudinal qualities relating to the strength of the attitude-behavior relationship, Journal of Experimental Social Psychology Bulletin, 21, 7, pp. 704-710, (1978); Fishbein M., Ajzen I., Belief, Attitude, Intention, and Behavior, (1975); Gronroos C., Relationship approach to marketing in services contexts: The marketing and organizational behavior interface, Journal of Business Research, 20, pp. 3-11, (1990); Grove S.J., Fisk R.P., The impact of other customers on service experiences: A critical incident examination of 'Getting along, Journal of Retailing, 73, 1, pp. 63-85, (1997); Hoffman D.L., Novak T.P., Marketing in hypermedia computer-mediated environments: Conceptual foundations, Journal of Marketing, 60, pp. 50-68, (1996); Hui M., Bateson J.E.G., Perceived control and the effects of crowding and consumer choice on the service experience, Journal of Consumer Research, 18, pp. 174-184, (1991); James L.R., Aggregation bias in estimates of perceptual agreement, Journal of Applied Psychology, 67, pp. 219-229, (1982); Johnson M.D., Fornell C., A framework for comparing customer satisfaction across individuals and product categories, Journal of Economic Psychology, 12, 2, pp. 267-286, (1991); Kirsner S., Close encounters: The most effective Web sites offer users a conversation, not a monologue, CIO Web Business Magazine, (1997); Klein K.J., Conn A.B., Smith D.B., Sorra J.S., Is everyone in agreement? An exploration of within-group agreement in employee perceptions of the work environment, Journal of Applied Psychology, 86, 1, pp. 3-16, (2001); Lind M., Zmud R., Improving interorganizational effectiveness through voice mail facilitation of peer-to-peer relationships, Organization Science, 6, 4, pp. 445-462, (1995); Mehrabian A., Russell J.A., A verbal measure of information rate for studies in environmental psychology, Environment and Behavior, 6, pp. 233-252, (1974); Meuter M., Ostrom L., Roundtree A.L., Robert I., Bintner M., Self-service technologies: Understanding customer satisfaction with technology-based service encounters, Journal of Marketing, 64, 3, pp. 50-64, (2000); Midgely D.F., Dowling G.R., Innovativeness: The concept and its measurement, Journal of Consumer Research, 4, pp. 227-242, (1978); Nash S., Wilson M., Value-added bibliographic instruction: Teaching students to find the right citations, References Services Review, 19, pp. 87-92, (1991); O'Crockett R., Chat me up . . . please, Business Week Ebiz, (2001); Oliver R.L., Satisfaction: A Behavioral Perspective on the Consumer, (1997); Ostroff C., Comparing correlations based on individual-level and aggregated data, Journal of Applied Psychology, 78, 4, pp. 569-582, (1993); Prabhaker P., Sheehan M., Coppett J.I., The power of technology in business selling: Call centers, The Journal of Business and Industrial Marketing, (1997); Price L., Arnould E., Deibler S., Consumer'S emotional responses to service encounters. The influence of the services provider, International Journal of Service Industry Management, 6, 3, pp. 34-63, (1995); Rogers E.M., Shoemaker F.F., Communication of Innovation, (1971); Rasbash J., Browne W., Goldstein H., Yang M., Et al., A user'S guide to MLwiN, 2nd ed., (2000); De Ruyter J.C., Wetzels M.G.M., Kleijnen M., Customer adoption of e-service: An experimental study, International Journal of Service Industry Management, 12, 2, pp. 184-206, (2001); Snijders T., Bosker R., Multilevel Analysis: An Introduction to Basic and Advanced Multilevel Modeling, (1999); Szymanski D.M., Hise R.T., E-satisfaction: An initial examination, Journal of Retailing, 76, 3, pp. 309-322, (2000); Van Yperen N., Snijders T., A multilevel analysis of the demands-control model: Is stress at work determined by factors at the group level or the individual level?, Journal of Occupational Health Psychology, 5, pp. 182-190, (2000); Venkatraman M.P., Price L.L., Differentiating between cognitive and sensory innovativeness: Concepts, measurement and implications, Journal of Business Research, 20, pp. 293-315, (1990); Wolfinbarger M., Gilly M., Shopping online for freedom, control, and fun, California Management Review, 43, 2, pp. 34-56, (2001)",{"$nulls":8},9564233.0,null,null,null,"English","Int. J. Serv. Ind. Manage.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-0036447507"]
["Blumberg M.R.; Snyder R.L.","Blumberg, M.R. (7005412878); Snyder, R.L. (7402214422)","7005412878; 7402214422","The strategic impact of information technology convergence on healthcare delivery and support organizations",2001.0,"Biomedical Instrumentation and Technology",35.0,3.0,null,177.0,187.0,10.0,2.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-0034985475&partnerID=40&md5=0325f80ea37e0966aae213533275abe3",null,null,"Information technology convergence and medical/IT convergence represent some of the most important facets of the changing healthcare landscape today. The healthcare community has traditionally been slow to adopt new IT systems because of its substantial investment in legacy systems. Now that healthcare providers are beginning to see the potential benefits of seamless IT and medical systems integration within and between facilities and providers, there is a strong emphasis on IT convergence across the industry. This trend has been magnified by the emergence of common standards in hardware, operating systems, and other areas, which makes the integration of diverse network systems less difficult and more cost effective. This emerging focus has generated a professional services market of over $4.3 billion in the United States in 2000 and it is expected to grow rapidly to nearly $12.4 billion by 2005. Information technology convergence projects in the healthcare sector are enabling core functionalities, such as the linking of financial, operational, and patient data, along with more diverse and technologically sophisticated systems and processes, such as PACS and telemedicine. As convergence progresses, a seamless medical provider system will gradually emerge, which will enable patients to move freely through regions and providers along with their records and other critical data. More immediately, healthcare providers are realizing the demands of their customer base and are beginning to implement E-commerce tools, patient call centers built on technical \"help desk\" principles, and other joint means of service marketing and delivery. There is currently a diverse group of service providers involved in healthcare IT convergence, including high-end medical equipment and system OEMs, medical information systems providers, IT vendors and consultants, and others. At present, more traditional OEMs and in-house service organizations are in favor in this marketplace because they enjoy a more comfortable position with healthcare organizations. Space is opening for newer service organizations as they prove their capabilities in meeting provider expectations of increased quality of patient care, increased operational efficiency, and other factors. Most importantly, the strategic service provider in the field of healthcare IT convergence must be able to show a value proposition that meets healthcare provider demands: technical expertise and capabilities for supporting the total cycle service requirements of large, complex IT convergence technologies on a real-time, rapid, economical basis.",null,"Cost-Benefit Analysis; Delivery of Health Care; Information Science; Information Services; Biomedical equipment; Economic and social effects; Information technology; Strategic planning; article; consultation; cost benefit analysis; device; financial management; government; health care; health care delivery; health care organization; health service; home care; hospital equipment; information processing; interpersonal communication; long term care; marketing; medical technology; support group; Health care delivery; Health care",{"$nulls":15},8998205.0,null,"BITYE",1.1395977E7,"English","Biomed. Instrum. Technol.","Article","Final",null,"Scopus","2-s2.0-0034985475"]
["Chen J.C.H.; Lin B.; Li L.; Chen P.S.","Chen, Jason C. H. (10243764200); Lin, Binshan (7403508463); Li, Lingli (56094184200); Chen, Patty S. (7408354080)","10243764200; 7403508463; 56094184200; 7408354080","Logistics management in China: A case study of Haier",2004.0,"Human Systems Management",23.0,1.0,null,15.0,27.0,12.0,20.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-7244233282&partnerID=40&md5=4563f28407d22066bfdf093613492bd7","School of Business Administration, Gonzaga University, Spokane, WA 99258, United States; College of Business Administration, Louisiana State Univ. in Shreveport, Shreveport, LA 71115, United States; School of Business Administration, Washington University in St. Louis, St. Louis, MO 63105, United States","Chen J.C.H., School of Business Administration, Gonzaga University, Spokane, WA 99258, United States; Lin B., College of Business Administration, Louisiana State Univ. in Shreveport, Shreveport, LA 71115, United States; Li L., School of Business Administration, Gonzaga University, Spokane, WA 99258, United States; Chen P.S., School of Business Administration, Washington University in St. Louis, St. Louis, MO 63105, United States","Chinese businesses began with a weak foundation in the intense world trade environment, similar to the many other companies that grew from developing countries. How were these Chinese businesses able to compete with foreign competitors armed with strong capital structures and efficient communication networks? Haier is an excellent example of how Chinese companies have successfully adapted to and prospered in the global economy, using information technology as a strategic weapon to improve its competitive advantage and further to create collaborative advantage. Haier's growth is miraculous: in less than two decades, it grew from a state-owned refrigerator factory into an innovative international giant. The company has become China's first global brand and the fifth largest appliance seller in the world. What are the secrets of Haier's success? Many researchers have conducted extensive studies on Haier's management and found the key is Management Information Systems such as e-Commerce and logistics systems that improve business operations between its suppliers, customers, and business partners. This article recounts the journey of Haier's achievements to excellence through its MIS, and provides analyses of the company's business model, the market chain management model.","Business-to-business; Customer relation management; E-Commerce; Information technology; Logistics; Management information systems; Supply chain management","Competition; Customer satisfaction; Electronic commerce; Information technology; Logistics; Management information systems; Refrigerators; Business-to-business procurement; Customer relation management; Relationship management; Supply chain management; Enterprise resource planning",{"$nulls":6},"Applegate L.M., McFarlan F.W., Mckenney J.L., Corporation Information Systems Management, 5th Edn, (1999); Haier's Future-one Net and Three Flows, (2001); Haier Entering Information Age, (2002); Bumaham B., Durham's beat: B2B, investor's promised land or giant quagmire?, ZDII Interactive Investor, (2000); Chandra C., Kumar S., Supply chain management in theory and practice: A passing fad or a fundamental change?, Industrial Management & Data Systems, 100, 3, pp. 100-113, (2000); The Eight Principal of Application MIS, (2003); Haier Cooperation with SAP in E-business, (2002); Choy K.L., Lee W.B., A generic tool for the selection and management of supplier relationships in an outsourced manufacturing environment: The application of case based reasoning, Logistics Information Management, 15, 4, pp. 235-253, (2002); Closs D.J., Goldsby T.J., Clinton S.R., Information technology influences on world class logistics capability, International Journal of Physical Distribution &. Logistics Management, 27, 1, pp. 4-17, (1997); Closs D.J., Xu K., Logistics information technology practice in manufacturing merchandising firms: An international benchmarking study versus world class logistics firms, International Journal of Physical Distribution & Logistics Management, 30, 10, pp. 869-886, (2000); Copal C., Cahill G., Logistics in Manufacturing, the Business One, (1992); Cox III J.F., Blackstone Jr. J.H., Spencer M.S., APICS Dictionary, 9th Edn, (1998); Hao Z., Haier's Innovation Model - One Flow and Three Net, (2002); Ho C., Chen J.C.H., The prospect of B2B E-commerce in China's internet industry, Business Forum, 24, 3-4, pp. 62-69, (2001); Hu Y., Competitive Strategy and Core Competency-haier, (2002); Lummus R.R., Krumwiede D.W., Vokurka R.J., The relationship of logistics to supply chain management: Developing a common industry definition, Industrial Management & Data Systems, 101, 8, pp. 426-431, (2001); Porter M.E., Millar V.E., How information gives you competitive advantage, Harvard Business Review, pp. 149-160, (1985); Sum C.C., Teo C.B., Ng K.K., Strategic logistics management in Singapore, International Journal of Operations & Production Management, 21, 9, pp. 1239-1260, (2001); Turban E., Lee J., King D., Chung M.H., Electronic Commerce: A Managerial Perspective, (2000); Xu L., Haier's Information Road, (2002); Haier's Logistics, (2002)","B. Lin; College of Business Administration, Louisiana State Univ. in Shreveport, Shreveport, LA 71115, United States; email: blin@pilot.lsus.edu",{"$nulls":7},1672533.0,null,"HSMAD",null,"English","Hum Syst Manage","Article","Final",null,"Scopus","2-s2.0-7244233282"]
["Li W.-S.; Candan K.S.; Huang W.-K.","Li, Wen-Syan (36064148600); Candan, K. Selcuk (7003683729); Huang, Wei-Kuang (56124933400)","36064148600; 7003683729; 56124933400","Acceleration and monitoring of data-center-hosted distributed database-driven web applications",2004.0,"Concurrent Engineering Research and Applications",12.0,3.0,null,205.0,220.0,15.0,0.0,"10.1177/1063293X04046190","https://www.scopus.com/inward/record.uri?eid=2-s2.0-4444244718&doi=10.1177%2f1063293X04046190&partnerID=40&md5=5b6751ffab6c6a4608ecb79b3e294b94","NEC Laboratories America, Inc., Cupertino, CA 95014, 10080 North Wolfe Road, United States","Li W.-S., NEC Laboratories America, Inc., Cupertino, CA 95014, 10080 North Wolfe Road, United States; Candan K.S., NEC Laboratories America, Inc., Cupertino, CA 95014, 10080 North Wolfe Road, United States; Huang W.-K., NEC Laboratories America, Inc., Cupertino, CA 95014, 10080 North Wolfe Road, United States","For many e-commerce applications, web pages are created dynamically based on the current state of a business, such as product prices and inventory, stored in database systems. This characteristic requires e-commerce websites to deploy and integrate web servers, application servers, and database systems at the backend. Response time is essential to many e-commerce applications. With increasing availability and advancement of content delivery networks (CDN), many database-driven web applications rely on data centers that host applications and database contents. Such IT infrastructure enables the generation of requested pages at locations much closer to the end-users, thus reducing network latency. However, it incurs additional complexity associated with database-data center synchronization and data freshness. In this paper, the deployment of NEC's CachePortal dynamic content caching technology on a database-driven website in a data center-based distribution infrastructure is described. The new system architecture has been experimentally evaluated and the results show that the deployment of NEC's CachePortal accelerates the dynamic content delivery up to seven times while attaining a high level of content freshness. The way how the performance and behavior of web applications are monitored and analyzed are also dealt with. © 2004 Sage Publications.","Application server; CDN; Data center; Distributed databases; Dynamic content; Edge cache; Edge computing; Web acceleration; Web hosting","Cache memory; Client server computer systems; Distributed database systems; Electronic commerce; Query languages; Response time (computer systems); Websites; Application server; Content delivery networks; Data center; Dynamic content; Edge cache; Edge computing; Web acceleration; Web hosting; World Wide Web",{"$nulls":6},"Bhatti N., Bouch A., Kuchinsky A., Integrating user-perceived quality into web server design, Proceedings of the 9th World-Wide Web Conference, pp. 1-16, (2000); Smith B., Acharya A., Yang T., Zhu H., Exploiting result equivalence in caching dynamic web content, Proceedings of USENIX Symposium on Internet Technologies and Systems, (1999); Deolasee P., Katkar A., Panchbudhe A., Ramamritham K., Shenoy P., Adaptive push-pull: Dissemination of dynamic web data, Proceedings of the 10th WWW Conference, (2001); Mohan C., Caching technologies for web applications, Proceedings of the 2001 VLDB Conference, (2001); Ninan A., Kulkarni P., Shenoy P., Ramamritham K., Tewari R., Cooperative leases: Scalable consistency maintenance in content distribution networks, Proceedings of the 2002 World-Wide Web Conference, (2002); Datta A., Dutta K., Thomas H.M., VanderMeer D., Suresha E., Ramamritham K., Proxy-based acceleration of dynamically generated content on the world wide web: An approach and implementation, Proceedings of 2002 ACM SIGMOD Conference, (2002); Luo Q., Krishnamurthy S., Mohan C., Pirahesh H., Woo H., Lindsay B.G., Naughton J.F., Middle-tier database caching for e-business, Proceedings of 2002 ACM SIGMOD Conference, (2002); Selcuk C.K., Agrawal D., Li W.-S., Po O., Hsiung W.-S., View invalidation for dynamic content caching in multitiered architectures, Proceedings of the 28th Very Large Data Bases Conference, (2002); Liu L., Pu C., Tang W., WebCQ: Detecting and delivering information changes on the web, Proceedings of International Conference on Information and Knowledge Management, (2000); Yagoub K., Florescu D., Issarny V., Valduriez P., Caching strategies for data-intensive web sites, Proceedings of the 26th VLDB Conference, (2000); Labrindis A., Roussopoulos N., Self-maintaining web pages - An overview, Proceedings of the 12th Australasian Database Conference (ADC), (2001); Levy E., Iyengar A., Song J., Dias D., Design and performance of a web server accelerator, Proceedings of the IEEE INFOCOM'99, (1999); Heddaya A., Mirdad S., WebWave: Globally load balanced fully distributed caching of hot published documents, Proceedings of the 1997 IEEE International Conference on Distributed Computing and Sytems, (1997); Korupolu M.R., Dahlin M., Coordinated placement and replacement for large-scale distributed caches, Proceedings of the 1999 IEEE Workshop on Internet Applications, (1999); Tewari R., Dahlin M., Vin H.M., Kay J.S., Design considerations for distributed caching on the internet, Proceedings of the 19th International Conference on Distributed Computing Systems; Carter R.L., Crovella M.E., On the network impact of dynamic server selection, Computer Networks, 31, 23-24, pp. 2529-2558, (1999); Rodriguez P., Sibal S., Spread: Scaleable platform for reliable and efficient automated distribution, Proceedings of the 9th World-Wide Web Conference, pp. 33-49, (2000); Cao P., Liu C., Maintaining strong cache consistency in the world wide web, IEEE Transactions on Computers, 47, 4, (1998); Yu H., Breslau L., Shenker S., A scalable web cache consistency architecture, Proceedings of the ACM SIGCOMM'99 Conference, (1999); Li D., Cao P., Dahlin M., WCIP: Web Cache Invalidation Protocol, (2000)","Li Wen-Syan; IBM Almaden Research Center, New York, United States; email: wen@almaden.ibm.com",{"$nulls":7},"1063293X",null,"CRAPE",null,"English","Concurrent Eng Res Appl","Article","Final",null,"Scopus","2-s2.0-4444244718"]
["Soriano M.; Ponce D.","Soriano, Miguel (7005888433); Ponce, Diego (24078842300)","7005888433; 24078842300","A security and usability proposal for mobile electronic commerce",2002.0,"IEEE Communications Magazine",40.0,8.0,null,62.0,67.0,5.0,24.0,"10.1109/MCOM.2002.1024416","https://www.scopus.com/inward/record.uri?eid=2-s2.0-0036687237&doi=10.1109%2fMCOM.2002.1024416&partnerID=40&md5=80b983e87f8a068db86d1104be68fd23","Technical University of Catalonia, Catalonia, Spain","Soriano M., Technical University of Catalonia, Catalonia, Spain; Ponce D., Technical University of Catalonia, Catalonia, Spain","The possibility of making the Internet accessible via mobile telephones has generated an important opportunity for electronic commerce. WAP was intended to become a general standard for business. Nevertheless, some deficiencies hinder its mass acceptance in e-commerce applications. End-to-end security and speed of information delivery are absolutely necessary conditions. In this article, the authors present a solution, or at least a partial solution, for this situation. Wireless is typically a more constrained environment than the Internet. The theory of constraints and mobile agent technology can contribute to a strategic improvement of the overall performance of the system.",null,"Cellular telephone systems; Computer simulation; Constraint theory; Internet telephony; Mathematical models; Mobile computing; Network protocols; Security of data; Wireless telecommunication systems; Mobile agent technology; Mobile electronic commerce; Wireless access protocol; Electronic commerce",{"$nulls":6},"Mobinet 2: A rude awakening for WAP dreamers, (2001); WAP usability report: Field study fall 2000, (2000); Goldratt E., Theory of Constraints, (1992); Khare R., W effect considered harmful [Internet WAP], IEEE Internet Comp., 3, 4, pp. 89-92, (1999); Ponce D., Soriano M., Mur P., A proposal for B2C electronic commerce scheme based on WAP, World Multiconf. Sys., (2000); Sau Loon T., Bharghavan V., Alleviating the latency and bandwidth problems in WWW browsing, USENIX Symp. Internet Tech. and Sys., (1997); Ponce D., Soriano M., Secure intelligent broker for m-commerce, Int'l. Conf. Adv. in Infrastructure for Elect. Business, Sci. and Educ. on the Internet, (2001); Saltzer J.H., Reed D.P., Clark D.D., End-to-end arguments in system design, ACM Trans. Comp. Sys., pp. 277-288, (1984); Dierks T., Allen C., The TLS protocol version 1.0, Jan. 1999, Internet Standard RFC 2246; Blake S., Nystrom M., Wireless extensions to TLS; Hardee M., Why wireless needs Java™ technology, 2000 JavaOne SM Dev. Conf., July 2000",{"$nulls":8},1636804.0,null,"ICOMD",null,"English","IEEE Commun Mag","Article","Final",null,"Scopus","2-s2.0-0036687237"]
["Bhatnagar S.C.","Bhatnagar, Subhash C. (55429687500)",5.54296875E10,"E-government: Lessons from implementation in developing countries",2002.0,"Regional Development Dialogue",23.0,2.0,null,164.0,173.0,9.0,44.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-0142135853&partnerID=40&md5=7a428c4fbd1140a88d998715c46bd002","IIMA, Gujarat, Ahmedabad 380 015, India","Bhatnagar S.C., IIMA, Gujarat, Ahmedabad 380 015, India","E-government is about a process of reform in the way governments work, share information, and deliver services to external and internal clients. Specifically, e-government harnesses information technologies (such as wide area networks, the Internet, and mobile computing) to transform relations among citizens, businesses, and other arms of government. In e-government applications, these technologies are deployed to serve a variety of objectives: better delivery of government services to citizens, improved interactions with business and industry, citizen empowerment through access to information, or more efficient government management. The resulting benefits can be less corruption, increased transparency, greater convenience, revenue growth, and cost reduction. Specifically, e-government can improve the performance of the government in the following areas: Delivery of services to citizens: services can be made convenient, and easy to access. Delays can be reduced. The rules governing services can be made transparent, and consistent across different branches of the same department - many departments have been able to reduce corruption through e-government.",null,"corruption; developing world; e-commerce; implementation process; political system; service provision",{"$nulls":6},"(2002); (2002); (2002); (2002); (2002); (2002); (2002); From Vision to Implementation: Lessons from the Experience of Canada, (2002); (2002); (2002); (2002); (2002); (2002)",{"$nulls":8},2506505.0,null,null,null,"English","Reg. Dev. Dialogue","Article","Final",null,"Scopus","2-s2.0-0142135853"]
["Zhang Q.; Cao M.","Zhang, Qingyu (35932752700); Cao, Mei (8581933100)","35932752700; 8581933100","Human-machine web interface design for electronic commerce: A review of design perspectives, objectives, dimensions, and techniques",2003.0,"International Journal of Services, Technology and Management",4.0,"2024-06-04",null,442.0,463.0,21.0,0.0,"10.1504/ijstm.2003.003625","https://www.scopus.com/inward/record.uri?eid=2-s2.0-0344926269&doi=10.1504%2fijstm.2003.003625&partnerID=40&md5=393551e30c6dd6ad4ff2ab8fddff7db4","Dept. of Economics and Decision Sci., College of Business, Arkansas State University, Arkansas, AR 72467, United States; Dept. Info. Syst. Mktg. E-comm Sales, Coll. of Business Administration, University of Toledo, Toledo, OH 43606, United States","Zhang Q., Dept. of Economics and Decision Sci., College of Business, Arkansas State University, Arkansas, AR 72467, United States; Cao M., Dept. Info. Syst. Mktg. E-comm Sales, Coll. of Business Administration, University of Toledo, Toledo, OH 43606, United States","Web technology is revolutionising the information transfer and delivery modes of physical products. In the field of consumer-oriented business, most online merchant-consumer interactions require direct manipulation of interface. Thus the design of human-machine web interface is a critical factor to determining whether e-commerce can succeed in supporting and facilitating the electronic transaction in an electronic market and hierarchy. This paper reviews and pools together research on e-commerce website design in terms of design perspectives, objectives, dimensions, and techniques to help manage web technologies to enhance service in this burgeoning high-tech industry. The paper situates and integrates different design perspectives within the broader context of user acceptance, indicating some of the relative strengths and limitations of each theory. The review and comparisons of the design perspectives, objectives, dimensions, and techniques offer a basis for user interface design guidelines and future research directions.","Electronic business; Electronic commerce; Human-computer interface; Internet technology; Usability; User acceptance; Websites","Electronics industry; Interfaces (computer); Man machine systems; Technological forecasting; World Wide Web; Electronic business; Internet technology; User acceptance; Electronic commerce",{"$nulls":6},"Bakos J.Y., Reducing buyer search costs: Implications for electronic marketplaces, Management Science, 43, pp. 1676-1692, (1997); Bakos Y., The emerging role of electronic marketplaces on the internet, Communications of the ACM, 41, 8, pp. 35-42, (1998); Benjamin R., Wigand R., Electronic markets and virtual value chains on the information superhighway, Sloan Management Review, pp. 62-72, (1995); Brynjolfsson E., Seidmann A., A call for exploration: Introduction to special issue on frontier research on information systems and economics, Management Science, 43, pp. 1-3, (1997); Clemons E.K., Reddi S.P., Row M.C., The impact of information technology on the organization of economic activity: The 'move to the middle' hypothesis, Journal of Management Information Systems, pp. 1-23, (1993); De R., Mathews B., Issues in the management of web technologies: A conceptual framework, International Journal of Information Management, 19, pp. 427-447, (1999); Straub D.W., Watson R.T., Research commentary: Transformational issues in researching IS and Net-enabled organization, Information Systems Research, 12, 4, pp. 337-345; Miles G.E., Howes A., A framework for understanding human factors in web-based electronic commerce, International Journal of Human-Computer Studies, 52, pp. 131-163, (2000); Wang H., Toward a general model for web-based information systems, International Journal of Information Management, 21, pp. 385-396, (2001); D'Angelo J., Little S., Successful web pages: What are they and do they exist?, Information Technology and Libraries, 17, 2, pp. 71-81, (1998); 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Holsapple C.W., Whinston A.B., Decision Support Systems: A Knowledge-Based Approach, (1996); Kim J., Metaphoric navigation aids for cyber shopping malls: An empirical study toward the construction of customer interfaces, International Journal of Management Science, 3, pp. 1-27, (1997); Spool J.M., Et al., Web Site Usability: A Designer's Guide, (1999); Turban E., Lee J., King D., Chung H.M., Electronic Commerce: A Managerial Perspective, (2000); Ciancarini P., Rizzi A., Vitali F., An extensible rendering engine for XML and HTML, Computer Networks and ISDN Systems, 30, pp. 225-237, (1998); Kristensen A., Template resolution in XML/HTML, Computer Networks and ISDN Systems, 30, pp. 239-249, (1998); Erdmann M., Studer R., How to structure and access XML documents with ontologies, Data and Knowledge Engineering, 36, pp. 317-335, (2001); Lang K., Burnett M., XML, metadata and efficient knowledge discovery, Knowledge-Based Systems, 13, pp. 321-331, (2000); Hartson H.R., Human-computer interaction: Interdisciplinary roots and trends, The Journal of Systems and Software, 43, 2, pp. 103-118, (1998); Kim H., An XML-based modelling language for the open interchange of decision models, Decision Support Systems, 31, pp. 429-441, (2001); Montazemi A.R., Mantei M., Guest editorial: Special issue of INFOR on human-computer interaction, INFOR, 31, 2, pp. 63-64, (1993)","Q. Zhang; Dept. of Economics and Decision Sci., College of Business, Arkansas State University, Arkansas, AR 72467, United States; email: qzhang@astate.edu",null,"Inderscience Publishers",{"$nulls":5},1.460672E7,null,null,null,"English","Int. J. Serv. Technol. Manage.","Article","Final","All Open Access; Green Open Access","Scopus","2-s2.0-0344926269"]
["Di. Gregorio D.; Kassicieh S.K.; De Gouvea Neto R.","Di. Gregorio, Dante (7004136058); Kassicieh, Suleiman K. (6701376108); De Gouvea Neto, Raul (6507134591)","7004136058; 6701376108; 6507134591","Drivers of e-business activity in developed and emerging markets",2005.0,"IEEE Transactions on Engineering Management",52.0,2.0,null,155.0,166.0,11.0,63.0,"10.1109/TEM.2005.844464","https://www.scopus.com/inward/record.uri?eid=2-s2.0-18544377999&doi=10.1109%2fTEM.2005.844464&partnerID=40&md5=3456e160eafaa7786ecc47b1ad82ff1a","Anderson School of Management, University of New Mexico, Albuquerque, NM 87131, United States","Di. Gregorio D., Anderson School of Management, University of New Mexico, Albuquerque, NM 87131, United States; Kassicieh S.K., Anderson School of Management, University of New Mexico, Albuquerque, NM 87131, United States; De Gouvea Neto R., Anderson School of Management, University of New Mexico, Albuquerque, NM 87131, United States","This paper presents the results of an empirical analysis of the determinants of e-business activity across a sample of 26 developed countries and 52 emerging markets. Several \"e-readiness\" indicators predict actual e-business activity, including Internet infrastructure, computer infrastructure, affordable telephone service, literacy rates, English language capabilities, and logistics infrastructure. No support was found for a linkage between e-business and institutional factors (i.e., country risk, economic freedom, and transparency) or payment infrastructure. Moreover, evidence of path dependence suggests that sustainable first-mover advantages are conveyed upon early adopters of Internet technologies. Important regional differences also exist, with Asia leading other emerging markets and Eastern Europe lagging. Finally, analysis of a subsample of countries suggests that entrepreneurship rates drive e-business activity. The results document the persistence of the global digital divide and support a broad view of e-readiness, whereby a country's e-business activity depends not only upon information and communication technology (ICT) infrastructure but also upon human capital and logistics infrastructure. The absence of a link between institutional factors and e-business suggests that e-business arises not only when supporting economic institutions exist but also as a means of overcoming inadequate institutional conditions. © 2005 IEEE.","Determinants of e-business activity; Digital divide; E-business policy for countries; E-commerce issues; Emerging markets; Entrepreneurship and e-business; Models of e-commerce usage; Statistical analysis of e-commerce parameters","Correlation methods; Developing countries; Economics; Geographical regions; Information technology; Internet; Marketing; Regression analysis; Societies and institutions; Statistical methods; Determinants of e-business activity; Digital divide; Emerging markets; Electronic commerce",{"$nulls":6},"Afuah A., Tucci C.L., Internet Business Models and Strategies: Text and Cases, (2001); Afuah A., Tucci C.L., A model of the Internet as creative destroyer, IEEE Trans. Eng. Manage., 50, 4, pp. 395-402, (2003); Amit R., Zott C., Value creation in e-business, Strategic Manage. J., 22, 6-7, pp. 493-520, (2001); Arthur B., Self-reinforcing mechanisms in economics, The Economy As an Evolving Complex System, (1988); Bartlett C.A., Ghoshal S., Transnational Management, (2000); Becker G., Human Capital, (1993); Betz F., Managing Technological Innovation: Competitive Advantage From Change, (1998); Chen S., The real value of 'e-business models', Bus. Horiz., 46, 6, pp. 27-33, (2003); Chong A., Micco A., The Internet and the ability to innovate in Latin America, Emerging Markets Rev., 4, 1, pp. 53-72, (2003); David P., Clio and the economics of QWERTY, Amer. Econ. Rev., 75, 2, pp. 332-337, (1985); Davis T., E-commerce measurements and analysis, Joint UNECE/UNCTAD/UIS/ITU/OECD/EUROSTAT Statistical Workshop, Monitoring the Information Society: Data, Measurement and Methods, (2003); De Gouvea R., Kassicieh S., Brazil.com, Thunderbird Int. Bus. Rev., 44, 1, pp. 105-117, (2002); Di Gregorio D., Rethinking country risk: Insights from entrepreneur-ship theory, Int. Bus. Rev.; (2002); Global Card Directory, (2000); Fingar P., Kumar H., Sharma T., Enterprise E-Commerce, (2000); Hayek F.A., The use of knowledge in society, Amer. Econ. Rev., 35, 4, pp. 519-530, (1945); Holsapple C.W., Singh M., Toward a unified view of electronic commerce, electronic business, and collaborative commerce: A knowledge management approach, Knowl. Process. Manage., 7, 3, pp. 151-164, (2000); Hoskisson R., Eden L., Lau C., Wright M., Strategy in emerging economies, Acad. Manage. J., 43, 3, pp. 249-267, (2000); Hout T., Porter M.E., Rudden E., How global companies win out, Harvard Bus. Rev., pp. 98-107, (1982); Kalakota R., Robinson M., E-Business 2.0: Roadmap for Success, (2001); Kirzner I.M., Competition and Entrepreneurship, (1973); Kotha S., Rindova V., Rothaermel F., Assets and actions: Firm-specific factors in the internationalization of U.S. Internet firms, J. Int. Bus. Studies, 32, 4, pp. 769-791, (2001); Krovi R., Surveying the e-landscape: New roles of survival, Inf. Syst. Manage., 18, 4, pp. 22-30, (2001); Lam L.W., Harrison-Walker L.J., Toward an objective-based typology of e-business models, Bus. Horiz., pp. 17-26, (2003); La Porta R., Lopez de Silanes F., Schleifer A., Vishny R., Legal determinants of external finance, J. Finance, 52, 3, pp. 1131-1150, (1997); Laudon K.C., Traver C.G., E-Commerce: Business, Technology, Society, (2003); Leamer E., Storper M., The economic geography of the Internet age, J. Int. Bus. 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Develop., 1, 1, pp. 89-103, (1989); Teece D., Profiting from technological innovation: Implications for integration, collaboration, licensing, and public policy, Res. Pol., 15, pp. 295-305, (1986); Scupola A., The impact of electronic commerce on industry structure - The case of scientific, technical, and medical publishing, J. Inf. Sci., 28, 4, pp. 275-284, (2002); Sen A., Development As Freedom, (1999); Singh N., Kundu S., Explaining the growth of e-commerce corporations (ECCs): An extension and application of the eclectic paradigm, J. Int. Bus. Studies, 33, 4, pp. 679-697, (2002); Shane S., A General Theory of Entrepreneurship: The Individual-Opportunity Nexus, (2003); Smith K.G., Di Gregorio D., Bisociation discovery, and the role of entrepreneurial action, Strategic Entrepreneurship: Creating a New Mindset, pp. 129-150, (2002); Stata User's Manual, (1999); E-Commerce and Develop. Rep. 2001, (2002); Westland J., Clark T., Global Electronic Commerce, (1999); Williamson O.E., Opportunism and its critics, Managerial and Decision Economics, 14, 2, pp. 97-107, (1993); World Development Indicators (Electronic Database), (2002); Global Information Technology Report, (2002); Yergin D., Stanislaw J., The Commanding Heights, (1998); Yoffie D., Cusumano M., Judo strategy: The competitive dynamics of Internet time, Harvard Bus. Rev., 77, 1, pp. 71-81, (1999)","D. Di. Gregorio; Anderson School of Management, University of New Mexico, Albuquerque, NM 87131, United States; email: digregorio@mgt.unm.edu",{"$nulls":7},189391.0,null,"IEEMA",null,"English","IEEE Trans Eng Manage","Article","Final",null,"Scopus","2-s2.0-18544377999"]
["Ratnasingam P.","Ratnasingam, Pauline (6602971105)",6.602971105E9,"The importance of technology trust in Web services security",2002.0,"Information Management and Computer Security",10.0,5.0,null,255.0,260.0,5.0,40.0,"10.1108/09685220210447514","https://www.scopus.com/inward/record.uri?eid=2-s2.0-0036432811&doi=10.1108%2f09685220210447514&partnerID=40&md5=6b51fe3c5ad45064a3c6babbc0addcc1","University of Vermont, Burlington, VT, United States","Ratnasingam P., University of Vermont, Burlington, VT, United States","The Internet is changing the way businesses operate today. Firms are using the Web for procurement, to find trading partners, and to link existing applications to other applications. Web services are rapidly becoming the enabling technology of today's e-business, and e-commerce systems. We are having a massive impact on the way businesses think about designing, developing, and deploying Web-based applications. Web services may be an evolutionary step in designing distributed applications, however, they are not without problems. There are issues relating to security, transactions and scalability that need to be addressed. This paper addresses security concerns in Web services and the role of technology trust.","Information services; Internet; Risk; Security; Technology","Computer hardware description languages; Computer supported cooperative work; Distributed computer systems; Electronic commerce; Electronic data interchange; Electronic mail; HTTP; Information services; Information technology; World Wide Web; XML; E-business; Simple object access protocol; Universal description delivery integration; Web service description language; Web services; Security of data",{"$nulls":6},"Dumbill E., Welcome to web services activity, (2002); Web Services - A Business and Technical Guide, (2001); Fieldman S., The changing role of e-commerce: Extending the boundaries of the possible, IEEE Internet Computing, (2002); Fonseca B., RSA: Securing Web Services, (2002); Glass G., The web services ® evolution - Part 1: Applying web services, (2000); Goodwin C., Speak up for services on the web, (2002); Gottschalk K., Web services architecture overview - the next stage of evolution for e-business, (2000); Hagel J. III, Brown J.S., Your next IT strategy, Harvard Business Review, 79, 9, pp. 105-115, (2001); Webservices: The Explosion of Applications - White Paper, (2001); Ratnasingam P., Pavlou P., Technology trust: The next value creator in B2B electronic commerce, International Resources Management Association Conference - Washington, Seattle, (2002); Samtani G., Sadhwani D., Web services architect: B2Bi and web aervices: An intimidating task, (2002); Sullivan T., Lamonica M., Web services standards take center stage, Infoworld, (2001); Udell J., Web services - It's a brave new world for application integration, Infoweek, (2002); Yager T., The windows way to web services, microsoft's web services approach may be the easiest but at what cost?, (2002); Cassell J., Bickmore T., External manifestations of trustworthiness of the interface, Communications of the ACM, 43, 2, pp. 50-59, (2000); Orchard D., Web services pitfalls, (2002)",{"$nulls":8},9685227.0,null,"IMCSE",null,"English","Inf Manage Comput Secur","Article","Final",null,"Scopus","2-s2.0-0036432811"]
["Hatcher M.","Hatcher, Myron (56208323900)",5.62083239E10,"Tutorial on Technology Transfer and Survey Design and Data Collection for Measuring Internet and Intranet Existence, Usage, and Impact (Survey-2000) in Acute Care Hospitals in the United States",2001.0,"Journal of Medical Systems",25.0,1.0,null,27.0,45.0,18.0,4.0,"10.1023/A:1005684215664","https://www.scopus.com/inward/record.uri?eid=2-s2.0-0035260082&doi=10.1023%2fA%3a1005684215664&partnerID=40&md5=ce6a0f9bd1452acb0a6b0c74d426e942","Info. Systems and Decision Sciences, Craig School of Business, California State University, Fresno, CA 93740, United States","Hatcher M., Info. Systems and Decision Sciences, Craig School of Business, California State University, Fresno, CA 93740, United States","This paper provides a tutorial of technology transfer for management information systems in health care. Additionally it describes the process for a national survey of acute care hospitals using a random sample of 813 hospitals. The purpose of the survey was to measure the levels of Internet and Intranet existence and usage in acute care hospitals. The depth of the survey includes e-commerce for both business to business and with customers. The relationships with systems approaches, user involvement, user satisfaction and decision-making will be studied. Changes with results of a prior survey conducted in 1997 can be studied and enabling and inhabiting factors identified. This information will provide benchmarks for hospitals to plan their network technology position and to set goals.","Information systems; Internet; Intranet; Networks; Survey, acute care hospitals; Technology transfer","Computer Communication Networks; Data Collection; Decision Making; Delivery of Health Care; Hospital Administration; Hospital Information Systems; Hospitals; Information Management; Internet; Questionnaires; Technology Transfer; United States; article; computer network; decision making; health care delivery; hospital; hospital information system; hospital management; information processing; information system; Internet; questionnaire; technology; United States",{"$nulls":6},"Hatcher M.E., Survey of acute care hospitals in the United States relative to technology usage and technology transfer, J. Med. Sys., 21, 5, (1997); Hatcher M.E., Information systems' approaches and designs and facility information: Survey of acute care hospitals in the United States, Journal of Medical Systems, 22, 6, pp. 389-396, (1998); Hatcher M.E., Impact of information systems on acute care hospitals: Results from a survey in the United States, J. Med. Syst., 22, 6, pp. 379-388, (1998); Hatcher M.E., Decision-making with and without information technology in acute care hospitals: Survey in the United States, J. Med. Syst., 22, 6, pp. 397-408, (1998); Hatcher M.E., Internet usage and potential impact for acute care hospitals: Survey in the United States, J. Med. Syst., 22, 6, pp. 371-378, (1998); Hatcher M.E., The relationship between business process re-engineering and internet usage: Survey of acute care hospitals in the United States, J. Med. Syst., 23, 6, pp. 497-507, (1999); Bhargave H., The World Wide Web: Opportunities for operations research and management science, J. 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Health Systems, 5, 1, (1995); Auton G., The role of total quality management in patient-centered restructuring, J. Soc. Health Systems, 5, 1, (1995); Eardley A., Avison D., Powell P., Developing information systems to support flexible strategy, Journal of Organizational Computing and Electronic Commerce, 7, 1, (1997); Vassilacopoulos G., Paraskevopoulou E., A process model basis for evolving hospital information systems, J. Med. Sys., 21, 3, (1997); Massey J.K., Grams R.R., Jin M., A PC-based free text retrieval system for health care providers, J. Med. Sys., 11, 1, (1987); Martens C., Woo C.C., OASIS: An integrative toolkit for developing autonomous applications in decentralized environments, Journal of Organizational Computing and Electronic Commerce, 7, 2-3, (1997); Zviran M., Armoni A., Glezer C., HIS/BUI: A conceptual model for bottom-up integration of hospital information systems, J. Med. Sys., 22, 3, (1998); Matokovic B., Prerequisite matrix in decision-making process through the business systems planning (BSP) study of the public health institute of split, J. Med. Sys., 18, 1, (1994); Armstrong C., Sambamurthy V., Information technology assimilation in firms: The influence of senior leadership and IT infrastructures, Information Systems Res., 10, 4, (1999); Lawrence M., Low G., Exploring individual user satisfaction within user-led development, MIS Quart., 17, 2, (1993); Vassilacopoulos G., Chrissikopoulos V., Alexandris N., Tsouroplis A., Participative HIS Development: An Approach and a Case Study, 20, 3, (1996); Thong J.Y.L., Yap C., Raman K.S., Environments for information systems implementation in small businesses, Journal of Organizational Computing and Electronic Commerce, 7, 4, (1997); Menon N.M., Lee B., Eldenburg L., Productivity of information systems in the healthcare industry, Information Systems Res., 11, 1, (2000); Lee H.G., Clark T., Tam K.Y., Research report. 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Health Syst., 5, 1, (1995); Todd P., Benbasat I., Evaluating the impact of DSS, cognitive effort, and incentives on strategy selection, Inf. Syst. Res., 10, 4, (1999); DeSanctis G., Gallupe R.B., A foundation for the study of group decision support systems, Manag. Sci., 33, 5, (1987); King W.R., Planning for strategic decision support systems, Long Range Planning, 16, (1983); Nunamaker J.F., Applegate L.M., Konsynski B.R., Computer-aided deliberation: Model management and group decision support, Operations Res., 36, 6, (1988); Hatcher M.E., Group decision support systems: Decision process, time and space, Decision Support Systems, 8, pp. 83-84, (1992); Zaki A.S., Developing a DSS for a distribution facility: An application in the healthcare industry, J. Med. Syst., 13, 6, (1989); Hatcher M.E., Uniqueness of group decision support systems (GDSS) in medical and health applications, J. Med. Syst., 14, 6, (1990); Hatcher M.E., Connelly C.C., A case mix simulation decision support system model for negotiating hospital rates, J. Med. Syst., 12, 6, (1988); Martin J., Harrison T., Design and implementation of an expert system for controlling health care costs, Operations Res., 41, 5, (1993); Jeang A., Flexible nursing staff planning when patient demands are uncertain, J. Med. Sys., 18, 3, (1994); Hatcher M.E., Green L., Levine D., Flagle C., Validation of a decision model for triaging hypertensive patients to alternative health education interventions, Social Sci. Med., 22, 8, (1986); Shao S., Grams R.R., A proposed computer diagnostic system for malignant melanoma (CDSMM), J. Med. Sys., 18, 2, (1994); Grams R.R., Zhang D., Yue B., MDX - A medical diagnostic decision support system, J. Med. Sys., 20, 3, (1996); Sear A.M., An expert system for determining medicaid eligibility, J. Med. Syst., 12, 5, (1988); Martin J., Harrison T., Design and implementation of an expert system for controlling health care costs, Operations Res., 41, 5, (1993); Stevens I., Rasmussen W.T., Remote medical diagnosis system (RMDS) concept, J. Med. Sys., 6, 5, (1982); Aleynikov S., Micheli-Tzanakou E., Classification of retinal damage by a neural network based system, J. Med. Sys., 22, 3, (1998); Papaconstantinou C., Theocharous G., Mahadevan S., An expert system for assigning patients into clinical trials based on Bayesian networks, J. Med. Sys., 22, 3, (1998); Zelic I., Kononenko I., Lavrac N., Vuga V., Induction of decision trees and Bayesian classification applied to diagnosis of sport injuries, J. Med. Sys., 21, 6, (1997); Solin L.J., MacPherson S., Schultz D.J., Hanchak N.A., Evaluation of an algorithm to identify women with carcinoma of the breast, J. Med. Sys., 21, 3, (1997); Kaspaari N., Michaelis B., Gademann G., Using an artificial neural network to define the planning target volume in radiotherapy, J. Med. Sys., 21, 6, (1997); Austin T., Iliffe S., Leaning M., Modell M., A prototype computer decision support system for the management of asthma, J. Med. Sys., 20, 1, (1996); Modai I., Israel A., Mendel S., Hines E., Weizman R., Neural network based on adaptive resonance theory as compared to experts in suggesting treatment for schizophrenic and unipolar depressed in-patients, J. Med. Sys., 20, 6, (1996); Hatcher M.E., Voting and priorities in health care decision making, portrayed through a group decision support system, using analytic hierarchy process, J. Med. Syst., 18, 5, (1994); Kwak N.K., Lee C., A linear goal programming model for human resource allocation in a health-care organization, J. Med. Sys., 21, 3, (1997); Kwak N.K., McCarthy K.J., Parker G.E., A human resource planning model for hospital/medical technologists: An analytic hierarchy process approach, J. Med. Sys., 21, 3, (1997); Vitiello J.R., Levary R.R., Determining the optimal physician mix in health maintenance organizations, J. Med. Sys., 21, 4, (1997); Applegate L.M., Konsynski B.R., Nunamaker J.F., Model management systems: Design for decision support, Decision Support Syst., 2, (1986); Hatcher M., Uncertainty considerations in-group decision staffing and rate setting in a health promotion center, J. Soci. Health Systems, 5, 3, (1997); Butler T.W., Reeves G.R., Karwan K.R., Sweigart J.R., Assessing the impact of patient care policies using simulation analysis, J. Soci. for Health Syst., 3, 3, (1992); Shuman L.J., Wolfe H., Gunter M., Ruralsim: The design and implementation of a rural EMS simulator, J. Soci. for Health Syst., 3, 3, (1992); Lilienthal M., Defense simulation internet: Next generation information highway, J. Med. Syst., 19, 3, (1995); Kraut R., Mukhopadhyay T., Szczypula J., Kiesler S., Scherlis B., Information and communication: Alternative uses of the internet in households, Inf. Syst. Res., 10, 4, (1999); Sussman S., Sproull L., Straight talk: Delivering bad news through electronic communication, Inf. Syst. Res., 10, 2, (1999); Zollo S.A., Kienzle M.G., Henshaw Z., Crist L.G., Wakefield D.S., Tele-education in a telemedicine environment: Implications for rural health care and academic medical centers, J. Med. Syst., 23, 2, (1999); Keeney R., The value of internet commerce to the customer, Manag. Sci., 45, 4, (1999); Brynjolfsson E., Smith M., Frictionless commerce? A comparison of internet and conventional retailers, Manag. Sci., 46, 4, (2000); Dewan R., Freimer M., Seidmann A., Organizing distribution channels for information goods on the internet, Manag. Sci., 46, 4, (2000); Meter R.K., Synapse health resources online, J. Med. Sys., 16, 2-3, (1992); Yasnoff W.A., US HealthLink: A national information resource for health care professionals, J. Med. Sys., 16, 2-3, (1992); Singarella T., Baxter J., Sandefur R., Emery C., The effects of electronic mail on communication in two health sciences institutions, J. Med. Syst., 17, 2, (1993); Flaherty R., HEALTHCON-An innovative educational resource for Montana health professionals, J. Med. Sys., 16, 2-3, (1002); Antoku Y., Hanada E., Akazawa K., Kenjo Y., Nose Y., Remote connection to the Kyusku University Medical Center LAN using digital and analog telephone lines, J. Med. Sys., 21, 4, (1997); Brick J.E., Schreiber D., West Virginia's Mountaineer Doctor Television, J. Med. Sys., 17, 6, (1993); Screnci D., Hirsch E., Levy K., Skawinski E., DerBoghosian M., Medical outreach to Armenia by telemedicine linkage, J. Med. Sys., 20, 2, (1996); Merrell R.C., Telemedicine in the 90's: Beyond the future, J. Med. Sys., 19, 1, (1995); Grigsby J., Current status of domestic telemedicine, J. Med. Sys., 19, 1, (1995); Ferguson E.W., Doarn C.R., Scott J.C., Survey of global telemedicine, J. Med. Sys., 19, 1, (1995); Friedman R.H., Automated telephone conversations to assess health behavior and deliver behavioral interventions, J. Med. Sys., 22, 2, (1998); Patel U.H., Babbs C.F., A computer-based, automated, telephonic system to monitor patient progress in the home setting, J. Med. Sys., 16, 2-3, (1992); Padeken D., Sotiriou D., Boddy K., Gerzer R., Health care in remote areas, J. Med. Sys., 19, 1, (1995); Clemmer T.P., The role of medical informatics in telemedicine, J. Med. Sys., 19, 1, (1995); Grams R., Morgan G., Yu F.S., Zhang D., Zhang G., Iddings E., Fiorentino R., Broughton H., Medical knowledge systems: Applications to telemedicine, J. Med., Sys., 19, 1, (1995); Kleeberg P., Medical uses of the internet, J. Med. Syst., 17, 6, (1993); Wagner G., The Iowa medical information network: A concept, J. Med. Sys., 16, 2-3, (1992); Pomiecko E.C., CompreLink-A physician to physician communication network, J. Med. Sys., 16, 2-3, (1992); Puskin D.S., Opportunities and challenges to telemedicine in rural america, J. Med. Sys., 19, 1, (1995); Puskin D.S., Sanders J.H., Telemedicine infrastructure development, J. Med. Sys., 19, 1, (1995); Allely E.B., Synchronous and asynchronous telemedicine, J. Med. Sys., 19, 3, (1995); Blau A., Bringing the promise home: Policy options and strategies to promote medical information networking, J. Med. Syst., 17, 6, (1993); Bashshur R., Grigsby J., Position paper: Telemedicine effects: Cost, quality and access, J. Med. Sys., 19, 1, (1995); Dugas M., Scheichenzuber J., Hornung H., An intranet-based system for quality assurance in surgery, J. Med. Syst., 23, 1, (1999); American Hospital Association Guide to the Health Care Field 1995-96, (1995)","M. Hatcher; Info. Systems and Decision Sciences, Craig School of Business, California State University, Fresno, CA 93740, United States; email: myronh@csufresno.edu",{"$nulls":7},1485598.0,null,"JMSYD",1.128848E7,"English","J. Med. Syst.","Article","Final",null,"Scopus","2-s2.0-0035260082"]
["Mukundan S.","Mukundan, Sasikumar (57191766468)",5.7191766468E10,"Spinning the Semantic Web",2004.0,"On the Horizon",12.0,2.0,null,74.0,78.0,4.0,0.0,"10.1108/10748120410544153","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84993035709&doi=10.1108%2f10748120410544153&partnerID=40&md5=d2f720a76aaef237e111bf8a42b25548","Centre for Development of Advanced Computing (formerly NCST), Mumbai, India","Mukundan S., Centre for Development of Advanced Computing (formerly NCST), Mumbai, India","From the quiet new born days of early 1990s, the World Wide Web has had an exponential growth in the last decade or so. From the original goal of sharing research resources, Web today portrays a virtual world spanning from research to entertainment and e-commerce. This growth has necessitated substantial changes in the Web model. From the purely syntactic and relatively static framework of HTML, we have moved through DHTML and XML incorporating dynamicity and extensibility, and are now en route semantic frameworks starting with RDF. These allow Web documents to be comprehensible to machines (and not just to humans) allowing software agents to access and process such information on the Web. This leads us to semantic Web, and thus to a generation of Web applications based on Web services, adaptive content delivery, etc. Spinning the Semantic Web is based on papers presented in a seminar in Germany in 2000, and sketches the vario elements of semantic Web, the issues in realising it as well as some visions of the future. The stimulating forward to the book by Tim Berners-Lee, recently Knighted and widely regarded as the father of the Web, portrays his vision of semantic Web. The chapters explore specific issues such as ontologies, schema languages, annotations, applications, etc. The chapters are largely unorganised and presented without any cross-linking and most chapters use a fair amount of domain jargon. The book will be of value to those seriously interested in the field. © 2004, Emerald Group Publishing Limited","Communications; Technology led strategy; Worldwide web",{"$nulls":16},1.0748121E7,null,null,null,"English","Horizon","Article","Final",null,"Scopus","2-s2.0-84993035709"]
["Rutner S.M.; Gibson B.J.; Williams S.R.","Rutner, Stephen M. (6602744417); Gibson, Brian J. (7202976303); Williams, Susan R. (7404836088)","6602744417; 7202976303; 7404836088","The impacts of the integrated logistics systems on electronic commerce and enterprise resource planning systems",2003.0,"Transportation Research Part E: Logistics and Transportation Review",39.0,2.0,null,83.0,93.0,10.0,64.0,"10.1016/S1366-5545(02)00042-X","https://www.scopus.com/inward/record.uri?eid=2-s2.0-0037354959&doi=10.1016%2fS1366-5545%2802%2900042-X&partnerID=40&md5=d564c6f4dc12d19fb61cbfe7d1625ca5","Dept. of Marketing/Logistics, Univ. of Arkansas, Fayetteville, AR 72701, United States; Dept./Aviation Mgmt./Logistics, Auburn Univ., Auburn, AL 36849, United States; Dept. of Info. Syst./Logistics, Georgia Southern Univ., Statesboro, GA 30460, United States","Rutner S.M., Dept. of Marketing/Logistics, Univ. of Arkansas, Fayetteville, AR 72701, United States; Gibson B.J., Dept./Aviation Mgmt./Logistics, Auburn Univ., Auburn, AL 36849, United States; Williams S.R., Dept. of Info. Syst./Logistics, Georgia Southern Univ., Statesboro, GA 30460, United States","The growth of the supply chain concept has required logistics organizations to improve the flow of information both internally and externally. The increased information requirements have facilitated an integration of logistics information systems (LIS) and supply chain information systems in many companies. The increasing use of electronic commerce and enterprise resource planning and other LIS tools and techniques will shape the business process for the foreseeable future. Companies should understand their options and their impacts when making decisions to support their supply chain systems. © 2003 Elsevier Science Ltd. All rights reserved.","ERP; Information systems; LIS; Logistics; SCIS; Supply chain management","e-commerce; information management; information system; planning system",{"$nulls":6},"CAPS logistics debuts software suites, Fleet Owner, 93, 6, (1998); Bradley P., Thomas J., Gooley T., Cooke J.A., Study finds growing interest in ERP and operations software, Logistics Management and Distribution Report, 37, 10, (1998); Bradley P., Thomas J., Gooley T., Cooke J.A., Study: Warehouses need WMS, not ERP systems, Logistics Management and Distribution Report, 38, 4, (1999); Bradley P., Gooley T., Cooke J.A., Logistics execess focusing on supply chain, E-commerce, Logistics Management and Distribution Report, 38, 10, pp. 29-30, (1999); Brooksher K.D., E-commerce and logistics, Traffic World, 260, 7, (1999); DeCovny S., The electronic commerce comes of age, The Journal of Business Strategy, 19, 6, pp. 38-44, (1998); Dillman D.A., Mail and Telephone Surveys: The Total Design Method, (1978); Forger G., The brave new world of supply chain software, Modern Materials Handling, 54, 12, pp. 62-67, (1999); Gustin C.M., Trends in computer application in transportation and distribution management, International Journal of Physical Distribution and Logistics Management, 14, 1, pp. 52-60, (1984); Gustin C.M., Examination of 10-year trends in logistics information systems, Industrial Engineering, 25, 12, pp. 34-39, (1993); Gustin C.M., Trends in computer application in transportation and distribution management, International Journal of Physical Distribution and Logistics Management, 25, 4, pp. 73-79, (1995); Gustin C.M., Daugherty P.J., Stank T.P., The effects of information availability on logistics integration, Journal of Business Logistics, 16, 1, pp. 1-21, (1995); Harrington L.H., New tools to automate your supply chain, Transportation and Distribution, 38, 12, pp. 39-42, (1997); House R.G., Jackson G.C., Trends in computer applications in transportation and distribution management, International Journal of Physical Distribution and Materials Management, 7, 3, pp. 176-178, (1976); Kling J.A., Grimm C.M., Microcomputer use in transportation and logistics: A literature review, Journal of Business Logistics, 9, 2, pp. 1-19, (1988); Lambert D.M., Roberson J.F., Stock J., An appraisal of the integrated physical distribution management concept, International Journal of Physical Distribution and Materials Management, 9, 1, pp. 75-87, (1978); Langley C.J.Jr., Carlisle D.P., Probst S.B., Biggs D.F., Cail R.E., Microcomputers as a logistics information strategy, International Journal of Physical Distribution and Logistics Management, 18, 6, pp. 11-18, (1988); Maclead M., What's new in supply chain software? Purchasing and supply chain management, Logistics Supplement, pp. 22-23, (1994); Piturro M., How midsize companies are buying ERP, Journal of Accountancy, 188, 3, pp. 41-48, (1999); Rodgers E.M., Diffusion of Innovations, (1995); Rutner S.M., Gibson B.J., Vitasek K.L., Gustin C.M., Is technology filling the information gap?, Supply Chain Management Review, 5, 2, pp. 58-65, (2001); Rutner S.M., Langley C.J. Jr., Logistics value: Definition, process and measurement, Journal of International Logistics Management, 11, 2, pp. 73-82, (2001); Shaw R., ABC and ERP: Partners at last?, Strategic Finance, 80, 5, pp. 56-58, (1998); Smith C.D., Langley C.J., Mundy R.A., Removing the barriers between education and practice: Tools and techniques for logistics management, Journal of Business Logistics, 19, 2, pp. 173-195, (1998); Waller A.G., Computer systems for distribution planning, International Journal of Physical Distribution and Logistics Management, 13, 7, pp. 48-60, (1993); Whipple J.S., Frankel R., Anselmi K., The effect of governance structure on performance: A case study of efficient consumer response, Journal of Business Logistics, 20, 2, pp. 43-62, (1999); Williams L.R., Magee G.D., Suzuki Y., A multidimensional view of EDI: Testing the value of EDI participation to firms, Journal of Business Logistics, 19, 2, pp. 73-87, (1998); Witt C.W., Thinking inside the E-Box, Material Handling Management, 54, 12, (1999)","S.M. Rutner; Dept. of Marketing/Logistics, Univ. of Arkansas, Fayetteville, AR 72701, United States; email: srutner@uark.edu",null,"Elsevier Ltd",{"$nulls":5},1.3665545E7,null,null,null,"English","Transp. Res. Part E Logist. Transp. Rev.","Article","Final",null,"Scopus","2-s2.0-0037354959"]
["Wen H.J.; Tarn J.M.","Wen, H. Joseph (57220567649); Tarn, J. Michael (7006709448)","57220567649; 7006709448","Privacy and security in E-healthcare information management",2001.0,"Information Systems Security",10.0,4.0,null,1.0,16.0,15.0,8.0,"10.1201/1086/43317.10.4.20010901/31772.4","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84887445516&doi=10.1201%2f1086%2f43317.10.4.20010901%2f31772.4&partnerID=40&md5=7a7f37beec537607a40358229c60a5e3","Management Information Systems, New Jersey Institute of Technology, United States; Computer Information Systems, Western Michigan University, Kalamazoo, United States","Wen H.J., Management Information Systems, New Jersey Institute of Technology, United States; Tarn J.M., Computer Information Systems, Western Michigan University, Kalamazoo, United States","The E-healthcare operating environment is defined as a cybernetic medical setting where healthcare or medical information is processed, manipulated, transmitted, or distributed in electronic forms via computer-based systems, networks, or the Internet. E-technology has changed healthcare in the management of how care is delivered and in the transformation of the infrastructure that supports the healthcare delivery system.1 The traditional paradigm of the healthcare industry is challenged by the new paradigm of E-commerce and E-healthcare in the 21st century. The healthcare industry is undergoing a fundamental shift that will change consumer, patient, and healthcare professional behavior and interaction.2,3 During the E-revolution in the healthcare industry, technical barriers in telecommunication security and privacy must first be overcome.24 Healthcare organizations and their computer systems are required to ensure that the privacy and security of individually identifiable healthcare information are maintained. © 2001 Taylor & Francis.",{"$nulls":17},"1065898X",null,null,null,"English","Inf. Syst. Secur.","Article","Final",null,"Scopus","2-s2.0-84887445516"]
["Weber M.M.; Kantamneni S.P.","Weber, Mary Margaret (55468037900); Kantamneni, S. Prasad (57731488000)","55468037900; 57731488000","POS and EDI in retailing: An examination of underlying benefits and barriers",2002.0,"Supply Chain Management",7.0,5.0,null,311.0,317.0,6.0,53.0,"10.1108/13598540210447755","https://www.scopus.com/inward/record.uri?eid=2-s2.0-3242666834&doi=10.1108%2f13598540210447755&partnerID=40&md5=00b4de79891647eee44e3861d1d7ffd2","Department of Marketing, University of New Mexico, Albuquerque, NM, United States; Department of Marketing, Emporia State University, Emporia, KS, United States","Weber M.M., Department of Marketing, University of New Mexico, Albuquerque, NM, United States; Kantamneni S.P., Department of Marketing, Emporia State University, Emporia, KS, United States","During the past 20 years, US retailing has gone through a period of unprecedented change as consumer demands and competition have intensified. This change is being further stimulated by the development of e-commerce. Study of successful retailers indicates that a retailer's ability to successfully carve out and defend a competitive position in the marketplace depends, to a great extent, on its ability to make investments in and utilize information. The study described in this paper examined the use of technology in retailing. The purpose of this paper is to examine the underlying factors explaining why retailers adopt POS and EDI. The results indicate that retailers are adopting these technologies to achieve direct, indirect, and strategic benefits. These benefits take the form of improved inventory management, reductions in costs, and increased flexibility of response to customer demands.","Electronic data interchange; Logistics; Point of sale; Retailing","Costs; Customer satisfaction; Electronic commerce; Electronic data interchange; Information dissemination; Information technology; Investments; Inventory management; Point-of-sale (POS); Product lifecycles; Retailing; Industrial management",{"$nulls":6},"Aaker D., Kumar V., Day G.S., Marketing Research, (1995); Armstrong J.S., Overton T.S., Estimating non-response bias in mail surveys, Journal of Marketing Research, 14, AUGUST, pp. 396-402, (1977); Blischok T., Retailing 2000, Chain Store Age Executive, APRIL, (1994); Carter C.F., Williams B.R., The characteristics of technically progressive firms, Journal of Industrial Economics, 7, 2, pp. 87-104, (1959); Cash J.I., Konsynski B.R., IS redraws competitive boundaries, Harvard Business Review, MARCH-APRIL, pp. 134-142, (1985); Cassidy P., The point of most return, CIO, 1, APRIL, pp. 46-56, (1994); Chatfield A.T., Yetton P., Strategic payoff from EDI as a function of EDI embeddedness, Journal of Management Information Systems, 16, 4, pp. 195-224, (2000); Comrey A.L., A First Course in Factor Analysis, (1973); Czinkota M., Kotabe M., America's new world trade order, Marketing Management, 3, 1, pp. 46-54, (1992); Dearing B., The strategic benefits of EDI, The Journal of Business Strategy, JANUARY-FEBRUARY, pp. 4-6, (1990); Dupuy C.A., Vlosky R.P., Status of electronic data interchange in the forest products industry, Forest Products Journal, JUNE, pp. 32-38, (2000); Lambert D., Lewis C., Stock J.R., Customer-focused strategies for motor carriers, Transportation Journal, 32, SUMMER, pp. 21-28, (1993); Lohr S., The Web hasn't replaced the storefront quite yet, New York Times on the Web, OCTOBER 3, (1999); O'Callaghan R., Kaufmann P.J., Kosynski B.R., Adoption correlates and share effects of electronic data interchange systems in marketing channels, Journal of Marketing, 56, APRIL, pp. 45-56, (1992); Peters L.-R.R., Is EDI dead? the future of the Internet in supply chain management, Hospital Material Management Quarterly, AUGUST, pp. 42-47, (2000); Pisharodi R.M., Langley C.J., A perceptual process model of customer service based on cybernetic/control theory, Journal of Business Logistics, 11, 1, pp. 26-48, (1990); Rogers E.M., Diffusion of Innovations, 3rd Ed., (1983); Rogers E.M., Shoemaker F.F., Communication of Innovations: A Cross-cultural Approach, (1971); Sheth J., Emerging trends for the retailing industry, Journal of Retailing, 59, 3, pp. 6-18, (1983); Trombly M., Value-chain management, Computerworld, MAY, pp. 64-68, (2000); Wang E., Seidmann A., Electronic data interchange: Competitive externalities and strategic implementation policies, Management Science, 41, 3, pp. 401-408, (1995)",{"$nulls":8},1.3598546E7,null,null,null,"English","Supply Chain Manage.","Article","Final",null,"Scopus","2-s2.0-3242666834"]
["Bin Q.; Chen S.-J.; Sun S.Q.","Bin, Qiu (57197689350); Chen, Shu-Jen (55585645000); Sun, Shao Qin (7404509794)","57197689350; 55585645000; 7404509794","Cultural differences in e-commerce: A comparison between the U.S. and China",2003.0,"Journal of Global Information Management",11.0,2.0,null,48.0,55.0,7.0,62.0,"10.4018/jgim.2003040103","https://www.scopus.com/inward/record.uri?eid=2-s2.0-0041473605&doi=10.4018%2fjgim.2003040103&partnerID=40&md5=02b12fbb4ca9d09d57b8a5d94b9b8690","Department of Economics and Trade, School of Economics and Management, Southeast University, Nanjing, China; California State University, Fullerton, CA, United States","Bin Q., Department of Economics and Trade, School of Economics and Management, Southeast University, Nanjing, China; Chen S.-J., California State University, Fullerton, CA, United States; Sun S.Q., Department of Economics and Trade, School of Economics and Management, Southeast University, Nanjing, China","This paper discusses the importance of identifying cultural problems of the online globalization and points out that payment and logistic systems and language are the primary factors that every firm should take into account in the process of their online globalization. Next, the paper identifies the characteristics and trends of the Internet and e-commerce in China. In the third part, the paper differentiates e-commerce in the U.S. with China through analyzing Internet users' behaviors especially their attitudes toward different payment systems in these two countries. Finally, it discusses how to remove language barriers to enhance net growth. In conclusion, this paper will suggest some recommendations on how to expand business via the Internet by reducing the gap between the two cultures.","E-commerce and cultural differences; Online globalization","Fees and charges; Human engineering; Industry; Information technology; Internet; Modernization; Social aspects; China; Cultural differences; Online globalization; United States; Electronic commerce",{"$nulls":6},"(2002); (2001); (2000); (2001); (2001); America.com: What makes America click, (2000); Shao Hua M., Credit cards in China-Enough cards, rare usage, Economic Daily, (2001)",null,null,"IGI Publishing",{"$nulls":5},1.0627375E7,null,null,null,"English","J. Global Inf. Manage.","Article","Final",null,"Scopus","2-s2.0-0041473605"]
["Loughlin P.","Loughlin, Peter (57191769708)",5.7191769708E10,"Viewpoint: E-commerce strengthens suppliers’ position",1999.0,"International Journal of Retail & Distribution Management",27.0,2.0,null,69.0,72.0,3.0,15.0,"10.1108/09590559910258553","https://www.scopus.com/inward/record.uri?eid=2-s2.0-84993012761&doi=10.1108%2f09590559910258553&partnerID=40&md5=0c440df220431cd60e57619ed634a2b4","KPMG Management Consulting, United Kingdom","Loughlin P., KPMG Management Consulting, United Kingdom","Discusses the relationship between supermarkets and their suppliers and whether electronic commerce will alter this relationship. The use of the Internet allows supermarkets to communicate electronically with suppliers regarding matters of stock availability, ordering and delivery without the associated costs of Electronic Data Interchange. The advantages for the supermarket are that it can deal with a larger network of suppliers, including smaller ones, and handing stock control over to the suppliers. The suppliers will be able to use online stock control and will be more involved with the management of their supply chain and price files. Concludes that, if approached correctly, new technology can assist the collaboration between supplier and supermarket. © 1999, MCB UP Limited","Internet; New technology Supermarkets; Supplier relations; Suppliers; Supply-chain management",{"$nulls":16},9590552.0,null,null,null,"English","Int. J. Retail Disrtib. Manage.","Article","Final",null,"Scopus","2-s2.0-84993012761"]
["Kinsey J.","Kinsey, Jean (7101820598)",7.101820598E9,"A faster, leaner, supply chain: New uses of information technology",2000.0,"American Journal of Agricultural Economics",82.0,5.0,null,1123.0,1129.0,6.0,21.0,"10.1111/0002-9092.00109","https://www.scopus.com/inward/record.uri?eid=2-s2.0-0034471738&doi=10.1111%2f0002-9092.00109&partnerID=40&md5=a42d10c6e925bff87cf396976290c680","Department of Applied Economics, University of Minnesota, United States; Retail Food Industry, United States","Kinsey J., Department of Applied Economics, University of Minnesota, United States, Retail Food Industry, United States","Links between economic agents known as food manufacturers, wholesalers, and retailers are complex, ill understood, changing rapidly, and decreasing in number. This paper focuses on the economics and the reality of a market for a business-to-business, e-commerce system; a system that will capture economies of scale and lower costs of food distribution toward the retail end of the food supply chain. Business-to-business e-commerce is a new way of doing business. It tends to follow a \"reverse product cycle\" where process efficiency gains come first, followed by quality improvements to existing products and services, and finally the creation of new services and products appear (OECD). The e-commerce marketplace is one where strategy, expectations about others actions, and trust determine demand. For purposes of this paper, the buyers-users in this e-commerce market are retailers, wholesalers, and manufacturers who buy and sell products to and from each other. The seller is a service provider who can produce a reliable electronic logistics network that will improve communications and will speed up product flow. Using information technology in this way tends to build vertical alliances. It differs from a market discovery e-commerce (shopping sites) in that it involves an intimate relationship among market agents that lasts for more than one transaction and frequently covers several products, over multiple time periods.",null,"food industry; information technology; market conditions; trade flow",{"$nulls":4},"Alfred P. Sloan Foundation","Jean Kinsey is professor in the Department of Applied Economics, University of Minnesota, and director of The Retail Food Industry, which is funded by the Alfred P. Sloan Foundation.","Belleflamme P., Adoption of network technologies in oligopolies, Int. J. Ind. Org., 16, pp. 415-444, (1998); Benchener P., E-commerce: UCCNet, The American Consumer and the Changing Structure of the Food System, (2000); Besen M.B., Farrell J., Choosing how to compete: Strategies and tactics in standardization, J. Econ. Perspectives, 8, pp. 117-132, (1994); Blair A., Supermarket technology, the big picture, Supermarket News, 23, (1999); Coleman C.Y., Big retailers in U.S., Europe form exchange, Wall Street Journal, 3, (2000); Senauer B., Kinsey J., The efficient consumer response initiative: Implications for vertical relationships throughout the U.S. food system, Vertical Relationships and Coordination in the Food System, pp. 443-452, (1999); (1999); Thakor A.V., Information technology and financial services consolidation, J. Banking and Finance, 23, pp. 679-700, (1999); Urbanski A., America's 50 largest supermarket chains, Supermarket Business, 55, (2000); Walsh J.P., Supermarkets Transformed: Understanding Organizational and Technological Innovations, (1993); Weinstein S., SBT for the common man, Progressive Grocer, (1999)",null,null,"Oxford University Press",{"$nulls":5},29092.0,null,null,null,"English","Am. J. Agric. Econ.","Article","Final",null,"Scopus","2-s2.0-0034471738"]
["Bouchoris Paschalis","Bouchoris, Paschalis (6506295591)",6.506295591E9,"E-commerce challenge: strategic implications for enterprises",1999.0,"British Telecommunications Engineering",18.0,"pt 2",null,199.0,202.0,3.0,1.0,null,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-0033170189&partnerID=40&md5=85577f13459eaea8f6f690f2819206d9","European Dynamics S.A., Athens, Greece","Bouchoris Paschalis, European Dynamics S.A., Athens, Greece","Electronic commerce is a serious strategic challenge to businesses. As the e-commerce paradigm prevails, enterprises, key among them European telecommunications operators, have to understand how they can enhanced value and gain competitive advantages through e-commerce. This paper puts the current state of e-commerce development into some context and sizes up its short-term future potential. It discusses the recent phenomenon of very high market capitalisations of e-commerce ventures and analyses the prime competitive strategy implications arising from the introduction of e-commerce. In brief, it identifies three ways in which enterprises can benefit from e-commerce: cost reduction, differentiation and new market development. It analyses the impact of e-commerce throughout a company's value chain: inbound logistics, production, sales, marketing, outbound logistics, distribution, post-sales support, staffing etc. Finally, the paper focuses on the development of e-commerce in Europe and the reasons it is lagging behind development in the United States marketplace.",null,"Bandwidth; Cost effectiveness; Industry; Internet; Marketing; Telecommunication services; Competitive strategy; Market capitalisations; Product distribution; Telecommunication operators; Electronic commerce",{"$nulls":9},"British Telecommun Eng",null,"Proceedings of the FITCE '99 - 38th European Telecommunications Cogress 'Networking the Future'","24 August 1999 through 28 August 1999","Utrecht, Neth",56082.0,"0262401X",null,"BTEND",null,"English","Br Telecommun Eng","Article","Final",null,"Scopus","2-s2.0-0033170189"]
["Sulaiman A.","Sulaiman, Ainin (25926787400)",2.59267874E10,"The status of e–commerce applications in Malaysia",2000.0,"Information Technology for Development",9.0,"2024-04-03",null,153.0,161.0,8.0,18.0,"10.1080/02681102.2000.9525329","https://www.scopus.com/inward/record.uri?eid=2-s2.0-39749158190&doi=10.1080%2f02681102.2000.9525329&partnerID=40&md5=21a611f1b37146ec29e752eb482fbf85","Faculty of Business & Accountancy, University of Malaya, 56300, Malaysia","Sulaiman A., Faculty of Business & Accountancy, University of Malaya, 56300, Malaysia","The main focus of this study is the status of e–commerce usage in Malaysia, specifically five main business processes and activities, namely, marketing, advertising, customer support and service, order and delivery and payment. A total of twenty applications categorized under the five processes and activities were identified and analysed. From the twenty applications studied, communications via e–mail was found to be the most widely used (70%). On the other hand, applications categorized under the payment category such as the smart card and prepaid card was used by only seven percent of the organisations. This demonstrated that Malaysian organisations were using e–commerce applications. However the usage was limited. The results of the survey indicated that security issues seemed to be the main barrier to the implementation of e–commerce. Organizations were reluctant to use e–commerce as they felt that the transactions conducted electronically were open to hackers and viruses, which are beyond their control. They were also skeptical about the security measures that were implemented to safeguard on–line payment transactions. © 2000 Taylor & Francis Group, LLC.",{"$nulls":8},"Bloch M., Pigneur Y., Segev A., The road of electronic commerce – a business value framework, (1996); Clarke R., The Strategic Intent of On–Line Trading Systems: A Case Study in National Livestock Marketing, (1993); Clarke R., EDI Is But One Element of Electronic Commerce, (1993); Cook D., Sellers D., Launching a Business on the Web, (1995); Anonymous, Barriers to e–commerce, Computimes, (2000); Fletcher, Marketing Management and Information Technology, (1990); Foo F., Becoming a role model for e–commerce, The Star: In–Tech, pp. 33-34, (1998); Gummesson E., Relationship Marketing (RM) and the Imaginary Organization Proceedings of the European Marketing Academy Conference, (1997); Miers D., Hutton G., The Strategic Challenges of Electronic Commerce, (1988); Haynes P., Becherer R., Helms M., Small and mid–sized businesses and Internet use: Unrealised potential?, Internet Research: Electronic Networking Application and Policy, 8, 3, pp. 229-235, (1998); Hoffman D., Novak T., Chatterje P., Commercial scenarios for the Web: Opportunities and challenges, Project 2000: Research program on marketing in computer–mediated environments, Own Graduate School of management, (1996); Kalakota R., Whinston A., Electronic Commerce: A Manager's Guide, (1997); Kosiur D., Understanding Electronic Commerce, (1997); Kiani R.G., Marketing opportunities in the digital world, Internet Research: Electronic Networking Applications and Policy, 8, 2, pp. 185-194, (1998); Lawrence E., Corbitt B., Tidwell A., Fisher J., Lawrence J., Internet Commerce: Digital Models For Business, (1998); Soh C., Quee G., Chew D., Reid E., The use of the Internet for business: The experience of early adopters in Singapore, Internet Research: Electronic Network Application and Policy, 7, 3, pp. 217-228, (1997); Tull D., Hawkins D., Markerting Research, (1987); Turban E., Lee J., King D., Chung H.M., Electronic Commerce: A Managerial Perspective, (2000); Zwass V., Structure and macro–level impacts of electronic commerce: From technological infrastructure to electronic market places, Emerging Information Technologies, (1998)","A. Sulaiman; Faculty of Business & Accountancy, University of Malaya, 56300, Malaysia; email: g5ainin@umcsd.um.edu.my",{"$nulls":7},2681102.0,null,null,null,"English","Inf. Technol. Dev.","Article","Final",null,"Scopus","2-s2.0-39749158190"]
["Dècina M.; Trecordi V.","Dècina, Maurizio (7003287757); Trecordi, Vittorio (6603916474)","7003287757; 6603916474","Voice over Internet Protocol and human-assisted E-commerce",1999.0,"IEEE Communications Magazine",37.0,9.0,null,64.0,67.0,3.0,15.0,"10.1109/35.790865","https://www.scopus.com/inward/record.uri?eid=2-s2.0-3042669814&doi=10.1109%2f35.790865&partnerID=40&md5=4f7cca316cc80ee5ff6c187c64ca2c33",null,null,"By fostering the finalization of open standards and the convergence of voice, video, and data, the Internet Protocol provides an ideal driver for the definition of the infrastructure for new multimedia and advanced communications applications. Voice over IP represents not only the chance to achieve cost-effective real-time voice communication over IP-based networks, but also the opportunity to build an integrated and open communications service delivery infrastructure. Developments of Web-based information systems and IP telephony in order to enable future e-commerce applications are here briefly summarized.",null,"Cost effectiveness; Multimedia systems; Network protocols; Real time systems; Standards; Telecommunication services; Voice/data communication systems; World Wide Web; Human-assisted electronic commerce; Internet protocols; Electronic commerce",{"$nulls":6},"Packet Based Multimedia Communications Systems, 2, (1998); Handley M., Et al., SIP: Session Initiation Protocol, (1999); Schulzrinne H., Et al., RTP: a Transport Protocol for Real-time Applications, (1996); Bell Labs Tech. J., 3, 4, (1998); IEEE Network, (1999)",null,null,"IEEE",{"$nulls":5},1636804.0,null,"ICOMD",null,"English","IEEE Commun Mag","Article","Final",null,"Scopus","2-s2.0-3042669814"]
["Rao B.","Rao, Bharat (7403489168)",7.403489168E9,"The Internet and the revolution in distribution: A cross-industry examination",1999.0,"Technology in Society",21.0,3.0,null,287.0,306.0,19.0,38.0,"10.1016/S0160-791X(99)00018-4","https://www.scopus.com/inward/record.uri?eid=2-s2.0-0032743925&doi=10.1016%2fS0160-791X%2899%2900018-4&partnerID=40&md5=30b6a4834141c360c2a24fefcf9ee777","Inst. for Technology and Enterprise, Polytechnic University, New York, NY 10004, United States","Rao B., Inst. for Technology and Enterprise, Polytechnic University, New York, NY 10004, United States","Distributors and channels of distribution have existed since time immemorial. Channels of distribution have existed to get products to consumers cheaper, faster, and more effectively. Distribution encompasses various types of activities, depending on the type of and point in the supply chain where value is added. A supply chain constitutes a set of activities ranging from production and manufacturing, to logistics, warehousing, transportation, and final delivery of goods to the customer (Handfield RB, Nichols EL. Introduction to supply chain management. Upper Saddle River, NJ: Prentice-Hall, 1999). Through their interactions with suppliers, manufacturers, and end customers, distributors thus perform an important intermediary role in matching supply with demand. In this paper, the impact of the Internet on the value chain is discussed. In order to explore issues pertaining to this transformation in greater detail, three industries that have been either radically altered by the Internet, or that are facing tremendous challenges as they head into the future, are considered. They are (a) the retailing industry, (b) banking, brokerage and financial services, and (c) the music industry. The objective is to elicit the underlying managerial implications and imperatives through this cross-industry examination.","E-commerce; Electronic retailing; Internet; Managerial transformation; Supply chain; Value chain","Internet; service sector; trade flow",{"$nulls":6},"1998 Holiday Sales Data, (1999); Rayport J., Sviolka J., Exploiting the virtual value chain, Harvard Business Review, NOV-DEC, (1995); Hoffman D.L., Novak T.P., Chatterjee P., Commercial scenarios for the Web: Opportunities and challenges, Journal of Computer-Mediated Communication, 1, (1995); Ghosh S., Making business sense of the Internet, Harvard Business Review, (1998); Ballou R.H., Business Logistics Management, (1992); Rao B.P., Parikh M., Navoth Z., Re-inventing music distribution, Proceedings of the Fifth Americas Conference on Information Systems, Association of Information Systems, Milwaukee, WI, 13-16 August, (1999); Myerson A.R., CompUSA: revising computer retailing, The New York Times, (1998); 1998 Online Shopping Report: projection profiles, competitive analysis, Research Study - Digital Commerce Strategies; Guttman R.H., Moukas A.G., Maes P., Agents as mediators in electronic commerce, Electronic Markets, 8, 2, pp. 22-27, (1998); Dignan L., E-tailing: Amazon.com's push to profits, ZD Net Interactive Investor, (1998); Meeker M., The Internet retailing report, US Equity Investment Research, (1997); Green H., Degeorge G., Barrett A., The virtual mall gets real, BusinessWeek, (1998); Alba J., Lynch J., Weitz B., Janiszewski C., Lutz R., Sawyer A., Wood S., Interactive home shopping: Consumer, retailer, and manufacturer incentives to participate in electronic marketplaces, Journal of Marketing, 61, 3, (1997); Rao B., Horwitch M., Navoth Z., Developing a world class distribution, logistics and electronic commerce infrastructure, EM - Electronic Commerce in the Americas, 10, NO. 2, (1999); Fisher M., Hammond J.H., Obermeyer W.R., Raman A., Making supply meet demand in an uncertain world, Harvard Business Review, MAY-JUNE, (1994); Rao B., Blasberg J., Salmon W., Raman A., Norwalk Furniture (A), (1997); Kaplan R., Tempest N., Wells Fargo Online Financial Services (A), (1998); Money Changes Everything, (1999); Rao B., Developing an effective e-tailing strategy, Electronic Commerce in the Americas, 9, 2, (1998); No MTV for widespread panic, just loads of worshipful fans, Wall Street Journal, (1999); Consumers are ready for broadband technologies, Consumers and Technographics Data Insights, 1, 15, (1998); Iansiti M., McCormack A., Living on Internet time: product development at Netscape, Yahoo!, NetDynamics, and Microsoft, (1997)","B. Rao; Inst. for Technology and Enterprise, Polytechnic University, New York, NY 10004, United States; email: brao@poly.edu",{"$nulls":7},"0160791X",null,null,null,"English","Technol. Soc.","Article","Final","All Open Access; Hybrid Gold Open Access","Scopus","2-s2.0-0032743925"]